From 70edaa5d524c08a6b1fa2680053f2880a95bb348 Mon Sep 17 00:00:00 2001
From: jpan <jpan@253336fb-580f-4252-a368-f3cef5a2a82b>
Date: Sat, 10 Sep 2011 05:52:53 +0000
Subject: [PATCH] add PQP and svm_light wrapper
git-svn-id: https://kforge.ros.org/fcl/fcl_ros@27 253336fb-580f-4252-a368-f3cef5a2a82b
---
trunk/PQP/Makefile | 36 +
trunk/PQP/PQP/include/BV.h | 94 +
trunk/PQP/PQP/include/PQP.h | 338 +
trunk/PQP/PQP/include/PQP_Compile.h | 101 +
trunk/PQP/PQP/include/PQP_Internal.h | 203 +
trunk/PQP/PQP/include/Tri.h | 54 +
trunk/PQP/build/pqp-1.3.tar.gz | Bin 0 -> 326131 bytes
trunk/PQP/build/pqp-tar/PQP_v1.3/Makefile | 33 +
trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.DSP | 154 +
trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.PLG | 43 +
trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.dsw | 29 +
trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.ncb | Bin 0 -> 287744 bytes
trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.opt | Bin 0 -> 48640 bytes
trunk/PQP/build/pqp-tar/PQP_v1.3/README.txt | 206 +
.../PQP/build/pqp-tar/PQP_v1.3/demos/Makefile | 16 +
.../build/pqp-tar/PQP_v1.3/demos/demos.dsp | 83 +
.../build/pqp-tar/PQP_v1.3/demos/demos.dsw | 53 +
.../build/pqp-tar/PQP_v1.3/demos/demos.ncb | Bin 0 -> 377856 bytes
.../build/pqp-tar/PQP_v1.3/demos/demos.opt | Bin 0 -> 58880 bytes
.../pqp-tar/PQP_v1.3/demos/falling/Makefile | 33 +
.../pqp-tar/PQP_v1.3/demos/falling/MatVec.h | 881 ++
.../PQP_v1.3/demos/falling/falling.dsp | 95 +
.../PQP_v1.3/demos/falling/falling.plg | 21 +
.../pqp-tar/PQP_v1.3/demos/falling/main.cpp | 537 +
.../pqp-tar/PQP_v1.3/demos/falling/model.cpp | 144 +
.../pqp-tar/PQP_v1.3/demos/falling/model.h | 63 +
.../PQP_v1.3/demos/falling/torus1.path | 11991 ++++++++++++++
.../PQP_v1.3/demos/falling/torus1.tris | 5329 +++++++
.../PQP_v1.3/demos/falling/torus2.path | 11991 ++++++++++++++
.../PQP_v1.3/demos/falling/torus2.tris | 12961 ++++++++++++++++
.../pqp-tar/PQP_v1.3/demos/sample/Makefile | 28 +
.../pqp-tar/PQP_v1.3/demos/sample/main.cpp | 301 +
.../pqp-tar/PQP_v1.3/demos/sample/sample.dsp | 91 +
.../pqp-tar/PQP_v1.3/demos/sample/sample.plg | 20 +
.../pqp-tar/PQP_v1.3/demos/spinning/Makefile | 36 +
.../pqp-tar/PQP_v1.3/demos/spinning/MatVec.h | 881 ++
.../PQP_v1.3/demos/spinning/bunny.tris | 8817 +++++++++++
.../pqp-tar/PQP_v1.3/demos/spinning/main.cpp | 372 +
.../pqp-tar/PQP_v1.3/demos/spinning/model.cpp | 144 +
.../pqp-tar/PQP_v1.3/demos/spinning/model.h | 63 +
.../PQP_v1.3/demos/spinning/spinning.dsp | 98 +
.../PQP_v1.3/demos/spinning/spinning.plg | 27 +
.../PQP_v1.3/demos/spinning/torus.tris | 5329 +++++++
trunk/PQP/build/pqp-tar/PQP_v1.3/include/BV.h | 94 +
.../PQP/build/pqp-tar/PQP_v1.3/include/PQP.h | 338 +
.../pqp-tar/PQP_v1.3/include/PQP_Compile.h | 101 +
.../pqp-tar/PQP_v1.3/include/PQP_Internal.h | 203 +
.../PQP/build/pqp-tar/PQP_v1.3/include/Tri.h | 54 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.cpp | 323 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.h | 94 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/BVTQ.h | 214 +
.../PQP/build/pqp-tar/PQP_v1.3/src/Build.cpp | 551 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.h | 49 +
.../PQP/build/pqp-tar/PQP_v1.3/src/GetTime.h | 71 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/MatVec.h | 877 ++
.../build/pqp-tar/PQP_v1.3/src/OBB_Disjoint.h | 216 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.cpp | 1376 ++
trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.h | 338 +
.../build/pqp-tar/PQP_v1.3/src/PQP_Compile.h | 101 +
.../build/pqp-tar/PQP_v1.3/src/PQP_Internal.h | 203 +
.../PQP/build/pqp-tar/PQP_v1.3/src/RectDist.h | 753 +
trunk/PQP/build/pqp-tar/PQP_v1.3/src/Tri.h | 54 +
.../build/pqp-tar/PQP_v1.3/src/TriDist.cpp | 407 +
.../PQP/build/pqp-tar/PQP_v1.3/src/TriDist.h | 63 +
trunk/PQP/build/pqp-tar/unpacked | 0
trunk/PQP/installed | 0
trunk/PQP/mainpage.dox | 26 +
trunk/PQP/manifest.xml | 15 +
trunk/PQP/pqp.diff | 10 +
trunk/PQP/wiped | 0
trunk/fcl/include/fcl/broad_phase_collision.h | 135 +-
trunk/fcl/include/fcl/collision_object.h | 10 +
trunk/fcl/include/fcl/transform.h | 7 +
trunk/svm_light/Makefile | 37 +
.../svm_light/build/svm_light-tar/LICENSE.txt | 59 +
trunk/svm_light/build/svm_light-tar/Makefile | 105 +
trunk/svm_light/build/svm_light-tar/kernel.h | 40 +
.../build/svm_light-tar/svm_classify.c | 197 +
.../build/svm_light-tar/svm_common.c | 985 ++
.../build/svm_light-tar/svm_common.h | 301 +
.../svm_light/build/svm_light-tar/svm_hideo.c | 1062 ++
.../svm_light/build/svm_light-tar/svm_learn.c | 4650 ++++++
.../svm_light/build/svm_light-tar/svm_learn.h | 173 +
.../build/svm_light-tar/svm_learn_main.c | 397 +
.../svm_light/build/svm_light-tar/svm_loqo.c | 211 +
trunk/svm_light/build/svm_light-tar/unpacked | 0
trunk/svm_light/build/svm_light.tar.gz | Bin 0 -> 51026 bytes
trunk/svm_light/installed | 0
trunk/svm_light/mainpage.dox | 26 +
trunk/svm_light/manifest.xml | 15 +
trunk/svm_light/svm_light.diff | 543 +
.../svm_light/include/svm_light/kernel.h | 40 +
.../svm_light/include/svm_light/svm_common.h | 301 +
.../svm_light/include/svm_light/svm_learn.h | 173 +
trunk/svm_light/wiped | 0
95 files changed, 77677 insertions(+), 17 deletions(-)
create mode 100644 trunk/PQP/Makefile
create mode 100644 trunk/PQP/PQP/include/BV.h
create mode 100644 trunk/PQP/PQP/include/PQP.h
create mode 100644 trunk/PQP/PQP/include/PQP_Compile.h
create mode 100644 trunk/PQP/PQP/include/PQP_Internal.h
create mode 100644 trunk/PQP/PQP/include/Tri.h
create mode 100644 trunk/PQP/build/pqp-1.3.tar.gz
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/Makefile
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.DSP
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.PLG
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.dsw
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.ncb
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.opt
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/README.txt
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/Makefile
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsw
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.ncb
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.opt
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/Makefile
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/MatVec.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.dsp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.plg
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/main.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.path
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.tris
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.path
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.tris
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/Makefile
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/main.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.dsp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.plg
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/Makefile
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/MatVec.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/bunny.tris
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/main.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.dsp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.plg
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/torus.tris
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/include/BV.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Compile.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Internal.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/include/Tri.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/BVTQ.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/GetTime.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/MatVec.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/OBB_Disjoint.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Compile.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Internal.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/RectDist.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/Tri.h
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.cpp
create mode 100644 trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.h
create mode 100644 trunk/PQP/build/pqp-tar/unpacked
create mode 100644 trunk/PQP/installed
create mode 100644 trunk/PQP/mainpage.dox
create mode 100644 trunk/PQP/manifest.xml
create mode 100644 trunk/PQP/pqp.diff
create mode 100644 trunk/PQP/wiped
create mode 100644 trunk/svm_light/Makefile
create mode 100755 trunk/svm_light/build/svm_light-tar/LICENSE.txt
create mode 100755 trunk/svm_light/build/svm_light-tar/Makefile
create mode 100755 trunk/svm_light/build/svm_light-tar/kernel.h
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_classify.c
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_common.c
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_common.h
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_hideo.c
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_learn.c
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_learn.h
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_learn_main.c
create mode 100755 trunk/svm_light/build/svm_light-tar/svm_loqo.c
create mode 100644 trunk/svm_light/build/svm_light-tar/unpacked
create mode 100644 trunk/svm_light/build/svm_light.tar.gz
create mode 100644 trunk/svm_light/installed
create mode 100644 trunk/svm_light/mainpage.dox
create mode 100644 trunk/svm_light/manifest.xml
create mode 100644 trunk/svm_light/svm_light.diff
create mode 100755 trunk/svm_light/svm_light/include/svm_light/kernel.h
create mode 100755 trunk/svm_light/svm_light/include/svm_light/svm_common.h
create mode 100755 trunk/svm_light/svm_light/include/svm_light/svm_learn.h
create mode 100644 trunk/svm_light/wiped
diff --git a/trunk/PQP/Makefile b/trunk/PQP/Makefile
new file mode 100644
index 00000000..2790aafa
--- /dev/null
+++ b/trunk/PQP/Makefile
@@ -0,0 +1,36 @@
+all: installed
+
+#
+# Download, extract and compile from a released tarball:
+#
+TARBALL = build/pqp-1.3.tar.gz
+TARBALL_URL = http://gamma.cs.unc.edu/software/downloads/SSV/pqp-1.3.tar.gz
+TARBALL_PATCH = pqp.diff
+INITIAL_DIR = build/pqp-1.3
+SOURCE_DIR = build/pqp-tar
+include $(shell rospack find mk)/download_unpack_build.mk
+
+INSTALL_DIR = PQP
+CMAKE = cmake
+CMAKE_ARGS = -D CMAKE_BUILD_TYPE="Release" -D CMAKE_INSTALL_PREFIX=`rospack find PQP`/$(INSTALL_DIR)
+MAKE = make
+
+installed: wiped $(SOURCE_DIR)/unpacked
+ cd $(SOURCE_DIR)/PQP_v1.3 && make $(ROS_PARALLEL_JOBS)
+ mkdir -p $(INSTALL_DIR)/lib
+ mkdir -p $(INSTALL_DIR)/include
+ mkdir -p $(INSTALL_DIR)/include/PQP
+ cp -r $(SOURCE_DIR)/PQP_v1.3/include/*.h $(INSTALL_DIR)/include
+ cp -r $(SOURCE_DIR)/PQP_v1.3/lib/*.a $(INSTALL_DIR)/lib
+ touch installed
+
+clean:
+ rm -rf build
+ rm -rf $(INSTALL_DIR) installed
+
+wiped: Makefile
+ make wipe
+ touch wiped
+
+wipe: clean
+ rm -rf build patched
diff --git a/trunk/PQP/PQP/include/BV.h b/trunk/PQP/PQP/include/BV.h
new file mode 100644
index 00000000..cfe42c73
--- /dev/null
+++ b/trunk/PQP/PQP/include/BV.h
@@ -0,0 +1,94 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_BV_H
+#define PQP_BV_H
+
+#include <math.h>
+#include "Tri.h"
+#include "PQP_Compile.h"
+
+struct BV
+{
+ PQP_REAL R[3][3]; // orientation of RSS & OBB
+
+#if PQP_BV_TYPE & RSS_TYPE
+ PQP_REAL Tr[3]; // position of rectangle
+ PQP_REAL l[2]; // side lengths of rectangle
+ PQP_REAL r; // radius of sphere summed with rectangle to form RSS
+#endif
+
+#if PQP_BV_TYPE & OBB_TYPE
+ PQP_REAL To[3]; // position of obb
+ PQP_REAL d[3]; // (half) dimensions of obb
+#endif
+
+ int first_child; // positive value is index of first_child bv
+ // negative value is -(index + 1) of triangle
+
+ BV();
+ ~BV();
+ int Leaf() { return first_child < 0; }
+ PQP_REAL GetSize();
+ void FitToTris(PQP_REAL O[3][3], Tri *tris, int num_tris);
+};
+
+inline
+PQP_REAL
+BV::GetSize()
+{
+#if PQP_BV_TYPE & RSS_TYPE
+ return (sqrt(l[0]*l[0] + l[1]*l[1]) + 2*r);
+#else
+ return (d[0]*d[0] + d[1]*d[1] + d[2]*d[2]);
+#endif
+}
+
+int
+BV_Overlap(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2);
+
+#if PQP_BV_TYPE & RSS_TYPE
+PQP_REAL
+BV_Distance(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2);
+#endif
+
+#endif
+
+
diff --git a/trunk/PQP/PQP/include/PQP.h b/trunk/PQP/PQP/include/PQP.h
new file mode 100644
index 00000000..f6f3e539
--- /dev/null
+++ b/trunk/PQP/PQP/include/PQP.h
@@ -0,0 +1,338 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_H
+#define PQP_H
+
+#include "PQP_Compile.h"
+#include "PQP_Internal.h"
+
+//----------------------------------------------------------------------------
+//
+// PQP API Return Values
+//
+//----------------------------------------------------------------------------
+
+const int PQP_OK = 0;
+ // Used by all API routines upon successful completion except
+ // constructors and destructors
+
+const int PQP_ERR_MODEL_OUT_OF_MEMORY = -1;
+ // Returned when an API function cannot obtain enough memory to
+ // store or process a PQP_Model object.
+
+const int PQP_ERR_OUT_OF_MEMORY = -2;
+ // Returned when a PQP query cannot allocate enough storage to
+ // compute or hold query information. In this case, the returned
+ // data should not be trusted.
+
+const int PQP_ERR_UNPROCESSED_MODEL = -3;
+ // Returned when an unprocessed model is passed to a function which
+ // expects only processed models, such as PQP_Collide() or
+ // PQP_Distance().
+
+const int PQP_ERR_BUILD_OUT_OF_SEQUENCE = -4;
+ // Returned when:
+ // 1. AddTri() is called before BeginModel().
+ // 2. BeginModel() is called immediately after AddTri().
+ // This error code is something like a warning: the invoked
+ // operation takes place anyway, and PQP does what makes "most
+ // sense", but the returned error code may tip off the client that
+ // something out of the ordinary is happenning.
+
+const int PQP_ERR_BUILD_EMPTY_MODEL = -5;
+ // Returned when EndModel() is called on a model to which no
+ // triangles have been added. This is similar in spirit to the
+ // OUT_OF_SEQUENCE return code, except that the requested operation
+ // has FAILED -- the model remains "unprocessed", and the client may
+ // NOT use it in queries.
+
+//----------------------------------------------------------------------------
+//
+// PQP_REAL
+//
+// The floating point type used throughout the package. The type is defined
+// in PQP_Compile.h, and by default is "double"
+//
+//----------------------------------------------------------------------------
+
+//----------------------------------------------------------------------------
+//
+// PQP_Model
+//
+// A PQP_Model stores geometry to be used in a proximity query.
+// The geometry is loaded with a call to BeginModel(), at least one call to
+// AddTri(), and then a call to EndModel().
+//
+// // create a two triangle model, m
+//
+// PQP_Model m;
+//
+// PQP_REAL p1[3],p2[3],p3[3]; // 3 points will make triangle p
+// PQP_REAL q1[3],q2[3],q3[3]; // another 3 points for triangle q
+//
+// // some initialization of these vertices not shown
+//
+// m.BeginModel(); // begin the model
+// m.AddTri(p1,p2,p3,0); // add triangle p
+// m.AddTri(q1,q2,q3,1); // add triangle q
+// m.EndModel(); // end (build) the model
+//
+// The last parameter of AddTri() is the number to be associated with the
+// triangle. These numbers are used to identify the triangles that overlap.
+//
+// AddTri() copies into the PQP_Model the data pointed to by the three vertex
+// pointers, so that it is safe to delete vertex data after you have
+// passed it to AddTri().
+//
+//----------------------------------------------------------------------------
+//
+// class PQP_Model - declaration contained in PQP_Internal.h
+// {
+//
+// public:
+// PQP_Model();
+// ~PQP_Model();
+//
+// int BeginModel(int num_tris = 8); // preallocate for num_tris triangles;
+// // the parameter is optional, since
+// // arrays are reallocated as needed
+//
+// int AddTri(const PQP_REAL *p1, const PQP_REAL *p2, const PQP_REAL *p3,
+// int id);
+//
+// int EndModel();
+// int MemUsage(int msg); // returns model mem usage in bytes
+// // prints message to stderr if msg == TRUE
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_CollideResult
+//
+// This saves and reports results from a collision query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_CollideResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // free the list of contact pairs; ordinarily this list is reused
+// // for each query, and only deleted in the destructor.
+//
+// void FreePairsList();
+//
+// // query results
+//
+// int Colliding();
+// int NumPairs();
+// int Id1(int k);
+// int Id2(int k);
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Collide() - detects collision between two PQP_Models
+//
+//
+// Declare a PQP_CollideResult struct and pass its pointer to collect
+// collision data.
+//
+// [R1, T1] is the placement of model 1 in the world &
+// [R2, T2] is the placement of model 2 in the world.
+// The columns of each 3x3 matrix are the basis vectors for the model
+// in world coordinates, and the matrices are in row-major order:
+// R(row r, col c) = R[r][c].
+//
+// If PQP_ALL_CONTACTS is the flag value, after calling PQP_Collide(),
+// the PQP_CollideResult object will contain an array with all
+// colliding triangle pairs. Suppose CR is a pointer to the
+// PQP_CollideResult object. The number of pairs is gotten from
+// CR->NumPairs(), and the ids of the 15'th pair of colliding
+// triangles is gotten from CR->Id1(14) and CR->Id2(14).
+//
+// If PQP_FIRST_CONTACT is the flag value, the PQP_CollideResult array
+// will only get the first colliding triangle pair found. Thus
+// CR->NumPairs() will be at most 1, and if 1, CR->Id1(0) and
+// CR->Id2(0) give the ids of the colliding triangle pair.
+//
+//----------------------------------------------------------------------------
+
+const int PQP_ALL_CONTACTS = 1; // find all pairwise intersecting triangles
+const int PQP_FIRST_CONTACT = 2; // report first intersecting tri pair found
+
+int
+PQP_Collide(PQP_CollideResult *result,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ int flag = PQP_ALL_CONTACTS);
+
+
+#if PQP_BV_TYPE & RSS_TYPE // this is true by default,
+ // and explained in PQP_Compile.h
+
+//----------------------------------------------------------------------------
+//
+// PQP_DistanceResult
+//
+// This saves and reports results from a distance query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_DistanceResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // The following distance and points established the minimum distance
+// // for the models, within the relative and absolute error bounds
+// // specified.
+//
+// PQP_REAL Distance();
+// const PQP_REAL *P1(); // pointers to three PQP_REALs
+// const PQP_REAL *P2();
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Distance() - computes the distance between two PQP_Models
+//
+//
+// Declare a PQP_DistanceResult struct and pass its pointer to collect
+// distance information.
+//
+// "rel_err" is the relative error margin from actual distance.
+// "abs_err" is the absolute error margin from actual distance. The
+// smaller of the two will be satisfied, so set one large to nullify
+// its effect.
+//
+// "qsize" is an optional parameter controlling the size of a priority
+// queue used to direct the search for closest points. A larger queue
+// can help the algorithm discover the minimum with fewer steps, but
+// will increase the cost of each step. It is not beneficial to increase
+// qsize if the application has frame-to-frame coherence, i.e., the
+// pair of models take small steps between each call, since another
+// speedup trick already accelerates this situation with no overhead.
+//
+// However, a queue size of 100 to 200 has been seen to save time in a
+// planning application with "non-coherent" placements of models.
+//
+//----------------------------------------------------------------------------
+
+int
+PQP_Distance(PQP_DistanceResult *result,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL rel_err, PQP_REAL abs_err,
+ int qsize = 2);
+
+//----------------------------------------------------------------------------
+//
+// PQP_ToleranceResult
+//
+// This saves and reports results from a tolerance query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_ToleranceResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // If the models are closer than ( <= ) tolerance, these points
+// // and distance were what established this. Otherwise,
+// // distance and point values are not meaningful.
+//
+// PQP_REAL Distance();
+// const PQP_REAL *P1();
+// const PQP_REAL *P2();
+//
+// // boolean says whether models are closer than tolerance distance
+//
+// int CloserThanTolerance();
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Tolerance() - checks if distance between PQP_Models is <= tolerance
+//
+//
+// Declare a PQP_ToleranceResult and pass its pointer to collect
+// tolerance information.
+//
+// The algorithm returns whether the true distance is <= or >
+// "tolerance". This routine does not simply compute true distance
+// and compare to the tolerance - models can often be shown closer or
+// farther than the tolerance more trivially. In most cases this
+// query should run faster than a distance query would on the same
+// models and configurations.
+//
+// "qsize" again controls the size of a priority queue used for
+// searching. Not setting qsize is the current recommendation, since
+// increasing it has only slowed down our applications.
+//
+//----------------------------------------------------------------------------
+
+int
+PQP_Tolerance(PQP_ToleranceResult *res,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL tolerance,
+ int qsize = 2);
+
+#endif
+#endif
+
+
+
+
+
+
diff --git a/trunk/PQP/PQP/include/PQP_Compile.h b/trunk/PQP/PQP/include/PQP_Compile.h
new file mode 100644
index 00000000..f76c9813
--- /dev/null
+++ b/trunk/PQP/PQP/include/PQP_Compile.h
@@ -0,0 +1,101 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_COMPILE_H
+#define PQP_COMPILE_H
+
+// prevents compiler warnings when PQP_REAL is float
+
+#include <math.h>
+inline float sqrt(float x) { return (float)sqrt((double)x); }
+inline float cos(float x) { return (float)cos((double)x); }
+inline float sin(float x) { return (float)sin((double)x); }
+inline float fabs(float x) { return (float)fabs((double)x); }
+
+//-------------------------------------------------------------------------
+//
+// PQP_REAL
+//
+// This is the floating point type used throughout PQP. doubles are
+// recommended, both for their precision and because the software has
+// mainly been tested using them. However, floats appear to be faster
+// (by 60% on some machines).
+//
+//-------------------------------------------------------------------------
+
+typedef double PQP_REAL;
+
+//-------------------------------------------------------------------------
+//
+// PQP_BV_TYPE
+//
+// PQP introduces a bounding volume (BV) type known as the "rectangle
+// swept sphere" (RSS) - the volume created by sweeping a sphere so
+// that its center visits every point on a rectangle; it looks
+// something like a rounded box.
+//
+// In our experiments, the RSS type is comparable to the oriented
+// bounding box (OBB) in terms of the number of BV-pair and triangle-pair
+// tests incurred. However, with our present implementations, overlap
+// tests are cheaper for OBBs, while distance tests are cheaper for the
+// RSS type (we used a public gjk implementation for the OBB distance test).
+//
+// Consequently, PQP is configured to use the RSS type in distance and
+// tolerance queries (which use BV distance tests) and to use OBBs for
+// collision queries (which use BV overlap tests). Using both requires six
+// more PQP_REALs per BV node than using just one type.
+//
+// To save space, you can configure PQP to use only one type, however,
+// with RSS alone, collision queries will typically be slower. With OBB's
+// alone, distance and tolerance queries are currently not supported, since
+// we have not developed our own OBB distance test. The three options are:
+//
+// #define PQP_BV_TYPE RSS_TYPE
+// #define PQP_BV_TYPE OBB_TYPE
+// #define PQP_BV_TYPE RSS_TYPE | OBB_TYPE
+//
+//-------------------------------------------------------------------------
+
+#define RSS_TYPE 1
+#define OBB_TYPE 2
+
+#define PQP_BV_TYPE RSS_TYPE | OBB_TYPE
+
+#endif
diff --git a/trunk/PQP/PQP/include/PQP_Internal.h b/trunk/PQP/PQP/include/PQP_Internal.h
new file mode 100644
index 00000000..90cedcfa
--- /dev/null
+++ b/trunk/PQP/PQP/include/PQP_Internal.h
@@ -0,0 +1,203 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include "Tri.h"
+#include "BV.h"
+
+class PQP_Model
+{
+
+public:
+
+ int build_state;
+
+ Tri *tris;
+ int num_tris;
+ int num_tris_alloced;
+
+ BV *b;
+ int num_bvs;
+ int num_bvs_alloced;
+
+ Tri *last_tri; // closest tri on this model in last distance test
+
+ BV *child(int n) { return &b[n]; }
+
+ PQP_Model();
+ ~PQP_Model();
+
+ int BeginModel(int num_tris = 8); // preallocate for num_tris triangles;
+ // the parameter is optional, since
+ // arrays are reallocated as needed
+ int AddTri(const PQP_REAL *p1, const PQP_REAL *p2, const PQP_REAL *p3,
+ int id);
+ int EndModel();
+ int MemUsage(int msg); // returns model mem usage.
+ // prints message to stderr if msg == TRUE
+};
+
+struct CollisionPair
+{
+ int id1;
+ int id2;
+};
+
+struct PQP_CollideResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ int num_pairs_alloced;
+ int num_pairs;
+ CollisionPair *pairs;
+
+ void SizeTo(int n);
+ void Add(int i1, int i2);
+
+ PQP_CollideResult();
+ ~PQP_CollideResult();
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // free the list of contact pairs; ordinarily this list is reused
+ // for each query, and only deleted in the destructor.
+
+ void FreePairsList();
+
+ // query results
+
+ int Colliding() { return (num_pairs > 0); }
+ int NumPairs() { return num_pairs; }
+ int Id1(int k) { return pairs[k].id1; }
+ int Id2(int k) { return pairs[k].id2; }
+};
+
+#if PQP_BV_TYPE & RSS_TYPE // distance/tolerance are only available with RSS
+
+struct PQP_DistanceResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ PQP_REAL rel_err;
+ PQP_REAL abs_err;
+
+ PQP_REAL distance;
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ int qsize;
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // The following distance and points established the minimum distance
+ // for the models, within the relative and absolute error bounds
+ // specified.
+ // Points are defined: PQP_REAL p1[3], p2[3];
+
+ PQP_REAL Distance() { return distance; }
+ const PQP_REAL *P1() { return p1; }
+ const PQP_REAL *P2() { return p2; }
+};
+
+struct PQP_ToleranceResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ int closer_than_tolerance;
+ PQP_REAL tolerance;
+
+ PQP_REAL distance;
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ int qsize;
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // If the models are closer than ( <= ) tolerance, these points
+ // and distance were what established this. Otherwise,
+ // distance and point values are not meaningful.
+
+ PQP_REAL Distance() { return distance; }
+ const PQP_REAL *P1() { return p1; }
+ const PQP_REAL *P2() { return p2; }
+
+ // boolean says whether models are closer than tolerance distance
+
+ int CloserThanTolerance() { return closer_than_tolerance; }
+};
+
+#endif
diff --git a/trunk/PQP/PQP/include/Tri.h b/trunk/PQP/PQP/include/Tri.h
new file mode 100644
index 00000000..496cddd9
--- /dev/null
+++ b/trunk/PQP/PQP/include/Tri.h
@@ -0,0 +1,54 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_TRI_H
+#define PQP_TRI_H
+
+#include "PQP_Compile.h"
+
+struct Tri
+{
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ PQP_REAL p3[3];
+ int id;
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-1.3.tar.gz b/trunk/PQP/build/pqp-1.3.tar.gz
new file mode 100644
index 0000000000000000000000000000000000000000..5d6a386167dbc1fdc61ae05638d30ae37f8b2e69
GIT binary patch
literal 326131
zcmb2|=3vmf_tT4k`Hjur;@f7M{(k)u{@~Kiu%ZmtCHv16PO6-=_Q<Y{x{*t+F5BtT
zHc6pd({+_f>hZTv|GwS6o5Asev)%U6;{3Ryo;pGY^u%^||7CE{tB=Z?eRgho{NKiK
z?sd(3ZGUWyS}Xe}cP4wab%@^j^*)!aZrs0Vow2oSf7Z-rajzd}Z~N{pG&OFuMWOPs
zeO=7uC*Nn9bBdp?cvQ<dY2TBrQ$ESZ@Y&t@<Jjf!$$m%tzqQSGnX}K|x^M6BGn(D{
zxAf2Y&ebaaEoRwl<Fg6)_j~Q$X69n?cW39?7MCmk*Dnk`wcj}Focu<9kq`g=y|eoH
z{_Pt%kDrI%nCnjXzwT<&&-+y_QrF_@i+<YQu3GbY{#L2v;}1XSeOmXN)0m&1f2Q&C
zH(DR^DnzPJ%5tZ_QR<mwX<fGX!gr?WJ2|cAF+Z*?d-bzU*kDWTd|pB4Gi^4{F7nPd
z6a3uZ&aL0K*C4_3M3|xZ4Hhfo8%lGkHd{Yq3pV@uNafS9)h(M--W}E9OFy|*x^UH(
zNfH-)4xh|A*nGrS;IdAS#Qb$?U!MG8>t5h(KI;sp5=ZmfRFQLgT6DuN8ue7>Y>3vM
z*}j@3;H<@khPNq##W!=GsB-epsFp44yKAr@>726NzU1o@rB!OO3>+#S`~DQkXnCk!
z%(vrCVa4H0ho)-B85P2g<|YhQwf1|yHf2{ZoymFWcA<6moa1L=^%|3&IWFJFKZBwD
zcydzY`=;10k>ywR7R;!<WoMmyE^~Tp>=(DY3-1=++w?Cx!=S|PW?}UW``58sB5x-i
zU;ftdd(Yf&3u>2hXPm2gdoFUiW$m?n6{p$WDmv_Y$A8l^|AuWD&kMD^o7wL^j{D8i
z-B+!CLHFMG_7&oPxp!ArvbqMG_q+A{t$FP1TXSRQe$l(PVe`JX8xC&xzw5a}W%Z5C
z8@JRyRhZ~t_F%`R-H#Tg8}I&q>*qS#H%y-DJPtQJ|NnR;Q(aQ^m%EwmY}I;hW;T_l
ziu1R*$4Y2y$)Dd-RrcNG+X=SX+wV%N(kBIfyZTX6VZs*S=Ksppor>$Lk01EG{eb@O
zA8YPfyPGi?Ot8;kwlAtNh+uE4xme!t`nfH8N8vBFua~Xm=X`x&$=v*p;cR6&hfs5)
zx7S3)14p{o<xZY*OJ(D|k5?nBPq2kMON4IM^zfhAu{ryOeB%+n8=2)d_U^KH$tPK`
zliy}%g8wZu8=J(r+wMBwbYNfF$lN6qoqJ_p-Saiy+gg$qvz@HFQMtSPVTt}N@#C=p
zvsWKvXyBdl@xhX}3hukamq&CeZ4GR{QTe~c!gB@7_r#<f+B2#G&xpN~m43|9G}E>*
z@>rhD_sZTWZF6_e`#<NUxWR)ny-9LcBEFU$N^Da#X*`%F+x(J!wvb`<qmK!Pt~=he
z__<i(%_+?@uFbOLH?CVhczJEBe#Eh5M%}L&OoB5vbSJ0DzLAy73l`TnTq*J4IqQU9
z3oCC}+}XbEZ1Y{`oU6K<n>S|5>HSL=G7mqvg!9{mu+@J*U;K0E+UBUY+4*8VKYJ3V
zT$HS}SX;~MA9r9gQ-+YwpQ}?gi*uXLG=IK+(<F7jC#KK+w=l6dudJ{;-X%5T?^Tt=
zxq)xRQ&_I>?M_H<dtY|%@P1{f$D7l2dTdgEH9mHpp>)5Yt*qm~6tU-T7jPd9@Z4@?
zryg{JLw*N~zN^?r&qr+6?XENaDW8_r&tQ0?_SxqLR*a|j@@ZIIQek$OX#F+picQ=i
z{lt%18y_5cn<8;RyU99Q;o;Wxl?;9xvmy*`ecEv7>tU|r$$MXhWOw?$F1|kB^uWhM
zF^>0TmK$iY^4J6)N{bUwmscx3KVMFC7vuKw$G^1u=3Qb|{n;Y1<y%h8<~%EfNe%J4
zD^+fnHa^odmhRwIVmg@Qa9Q%IwEKtO`(N@3xnGwoPyfnx?=O>$Z&=_2<wva9vK!A^
zso(o><XhddhBn8KzAt<^&u8lwI$gNFV_np@R<S0@ew%HqPaH%V|FW$<%3j0dWG8<$
zD~=&}{&kUvwZ>KdV!kqU)voXJn)Ujle_+t}`&;kjKa@{s`hV_7_2*h<xixD!s(#P<
zZFoIl*^L^lS^gU>|1GTMe!uoRi}R;HJtb-mx7zJy=-rRK);;;`g)d!l*2>#V&7Q7j
zUGYxZgR9$ij)Tebrk#IzV>SLx-@o;L*^IyS-&URZ?+`fg=h>4*KP77K%>N%*z4ou|
z#Q$%%>zqFHb-wM6+fVA_AKiLVKl@Mq<o~&!_WS-@9zXlf`@+xr)6Z{{f6J62kowys
zNH^f%BeTrI#n*cGcxokT*ggEH@@ZPe<N1$`GdtOLcAZ_%u6Sg#q07G)Tnegl7fqb|
zBjfeKSHY^xjk^+x_HrC`akN@i^hfHevYNE+%O9c{m)5A%#oWuV{Iqj+&kvU;XN`UK
z+1Fg(ePiPmm+EKjc}_F8ojGR9(Zuwvu`cAzpBtMl&*VEFVY0+UMb9Yb%;f04dnO(`
zecxm&dE{^Wa`Nz@nE9>`nWT6AGfnw%vgY72m5+v3DjVM<KXI1Y%kb<!vzmPiL*1Xp
za~nl#IhbQ!lsIjU(dF|={kCw0!$Iwp+)_+G+AX&;NVz<0ac*InWdAsYljp-@-!#Xx
zO(p9q&wTr~?fb)nHh+H0%}DrmV$pG#Ez=6apL#5QXPD}_b$`ao*WZ8IywbIOC4O%5
z91D}hEW#XJq8}O>xLb3zM1)&s?)XylmX&Sy!^tW=*B<X$bLeX0A-As6T8~cY{_JSk
z@HbIPP5#yc-<QiKPg^0azP6~Z=)!Z0Y06tBFFv~Boy7EG4c9nToW4!!eUKKCFP*D3
z{YPl!@fR6yt)r^<-nn>6mbZWL!-JosIu#cd<R5fgyl1{+x6+4F=EY}S-mY5o?b3@4
zv+UL#iCB80WtMY;&oZv&({pBA^ja#blIW}FAb3jVm?nS1rM*6qo2MEjS<C*K_Gf9G
za7N_x<m<Ce1upk>Ji@eo(baNs@1B$4bxa3s78ghfH|(6%>7lXK=xoH^c@M07oBzI!
zKQ!s;WVhyBd9sEvpBA`rR=09HN8~K~yWk+3o04;pkAvN^JB>@6uOy!7E6|n+o^)wm
zFPr<ti^uqWEWAHe#a2~1K-!_jTh{*&2ir~_!(053Ym+`n>a;kzZ<l*&dt{nun)XT)
z#{P4gS~TaaxzRn{a@m>&&HYz0*!t8K|B7yo<q8!}@-qDrsTCDD-RMVZ=i&V)ZuZ>R
z$3EMM%a_%l^}r7Y_Q;p%zgBxcR_$_r7{MiD;IDnLCf;pvW8J3Uga^57_ML|;+HThH
znfmc<UZePifmzq&&yRS)T|q6^f~@WfxysJ1{2C%XZ&^)_jh6C#J3i(6|J>Xrd0y$P
zV0o6t)9R<{&ATn@4_}_B$E%RZS2QPmk>2t0$&^p!<$n`G{VHcYbYIo_dV$piYok_8
zHwM<85ZC%`zN|kZC!c(Nod5f#3lVHdMzgz4?{mNL?Y04T-_c)QDu<m}9C(&q;L#Ej
znHX53sZ`YV+KywPVz*+<fzs(Gs@-Mx)h{>GyJxOixi?a->w`nTydZ;$(+&Nbrtd66
zdK0E8Go7_^(Y$bDfA*%!AEr4UOJA_%)7+LMQ`^J+9vhx-l&%&&q4r*(ykh~^oV;01
zC*(AL>GGIx2&);%a(vsX>3UAGeWC6h=bEl5of+F1-aEPZz7FVM`IPmK)4fr<uwQyp
z+HBdCvqYLs)x@lrvQt3**2{ek3-1U%<>lB~FZeD{Yd(*x<BmFy?yNa)FF%W!!(H@7
zdTXij`=X1BIM#%2;aD5}p7;0M&ibhLnN25)v^Kdcjmzs?7IO2%AwQ=l3R4y<7v;H3
zRMq-g<ZZIlOVncDv8%r2M(H(GXFYRyq*h7T7->83PT<kd*yNxX$}D)qC#Ca%iP-OV
zGp-tb_)`0B^V0W0m4}|)ncEfWef={lmz+SF;1<T1#ht}(#H^0&$&<Ucsx;t5?l#{o
zhjKiQ_$@fnxY*<CWTlm%PSq<X*&Xpt=GJNpGMse9Oyt-cw<B3<CagK%*#x>RyO|j|
zGPs#rI_E6$_Ah>?pRO&>yhEN@YKl|*<lA#M^@kcveSNIB&oTC($el}K`X5vS($tqv
zS-eQ<Uw}?TMdJ+Hg5sI?e3rkgQ-Anx!lPv$B&-*hO=&n_BNJH~{UW&AjPI<nRP))V
zaeCXniLGYszAHJy%#1y|(PKh$>5*5R8*Ve3Z(+9gpKrDxtU~$fv&9*o1GoItxMlEk
zbH-fu8zJ8WojT-xx7D^>xfSnueZhexP1i5mG8Tz_^w$>ny=7rF?}TMn1Ucs{J^w<D
zeZv2n?`>wxH~(?H^1I-_I|t&Q+I&6XrP^JQ+IcBNwNyEIN}H+6GmfBbH|O41bwWMy
z&=K|n5id2bXc%Q!%FW?jV0MBjJfmJq>XL~@<ibsEXSXExh%{()tnhfm8@a}nOCVq&
zSLWit*6GKVhRs;T^D69`P{l{)4Qt=oZk4KMetY?%#<m?@+V&C$vi7PsmEXH+@Ac!f
z){jEYxUCB(T%4--*!=#6UlNOVina6<9iIK|MB)>vo<qB@EIFzruv=+e(a|jzvloc3
zk({3W%KHRg><rh(Z5hF{8lPQ^*IHzlXs&nYOx^L9w^Zkc-B_>YeRgSk+0&gB2D2A<
zo(d9Eo7{daCL&t-Zmv*5LEtG((@B2m52To9oe*e9d)MOqIm1-jNlo&i&cVGW(yV=B
zmMq@*KyhNjbDdp9Y7KL17|Z_U>ilBtU$|n{4g-cXp{-)2trz`-*8Yg%pK#QpovZiU
zWy|@0B$ihfI4IBfeB`fSxSV(Pq)V<ECa&QdZyzbv-Dv*peUH{*yQkM}9!#8lV8M-Y
z&7G<xndK%n@7xkN)pnRRMAtsqb$Q1*1-CS%*(Vb@)K!}-N<w??2gE;oRkhC2Dd*U7
z$^6!`(3fFS!4tl!_X+9;NS!(3?#uX7#`?qM$xd5!iZ?PlAM-R9IrPFYvcY@h5{9y}
ztae2uQ%ymejFj|_pnyc4%-VT=;Sc9JgnO&AvdFqHzuWKkaf^hMU(dga1|P#qqQY<9
zi5mahw)46|M4}|)Vd)Qb41WUK&fc=rQ-AKZ=|{2W@uewk-gZi#R~>S5n0&4J?6U_i
zv~JCgs{YLQR(I{*(7SOPj_|ecb`%~zy)>cVm1|Oq+pWH9$6I6<IH!MPTAsD0*g5TW
z<|0PhyxH!NZ2E0KwYHu}68W`QRqnGOLlf5t@uUa5t+uh3qP4hZwQp4EIq})ZVztrz
z@V!r7R8L&~{;2Jjy}x+B?A<keU;C+!)YmFZ>_4rhE#7?Senw(P^Q0@ufsO8LtF~t>
zUNYz4>xM=S?u*k3gkQFp&Un9YBeU(qHkGd;tr;gLCZC_Ax@vM6lM+X!=BjBHJ@PH;
zy2tfguRQx5BQV*0-s+hCxc3VdaeE&RdbcE?Hs1VaUrRxX{exAHBC2XlZV3cdoZP-b
z^ydk|+#*5tLl#~R?lY^;)>O~v<a#?Z_Vh!6*MZEr7aA9qe3z6sbBDuqL&eG{ajmZk
zI%iE4F62F#Rl82~Jy&C3T5{|5Lan{M!V*R^r`=<FC3ALe!rmhFL%|pRtSMuh*{*%N
z)P2cEuh_RuvE^K4w>+<NZTj|%`BrpP_3B-Jqoi}5=Wdw0{oprSvm4W{UHm6%c5a&4
z<+=^L+diA!ICneYx198xzBkt|e}5JC>)pmRFI9FQ-?EG^@|@)ITW6MP{gOU2r>&}Y
zrtpdS_L-M=MPxs7QQv>~%)*@#E7o;wYsopk)QvMDG_`upq_>qapPLq{x^A1nUo$(w
z&0$jBstBXgE3Zrv*yiE8rR&$#OB);ZJe?47WHqb!#Ls+gpLgGSC#T!f`l*G@bR&=C
zfmNxSE^R6_Hjb^VJtG#&(r>tSdXIpaRB%<~0%N~5JTh0e)JjG2u6+CaZ04)~_Tf)|
z=GS;Waanaic@JmJ|DXBA>EV0-&)xTbcmBH>vp?UDe{^fk|9dd>FL>_%ZL{C_&QST7
z^6r=YvqkQ2Z_Q!+|M(u`GKR(J{}=N|O{f;P2;cb3;PbBO4IdZ8PI%yNA-7s!$2@D-
zsIT7=wy968mw9}#QMpp*h-1Ce>Vhr57JU=QcQ)g*Uzpq=KO-k&<HvQ(#cSN3#kc%E
zbnE()tTQS+i#0hU!`Hok)S|y);rrOf$M_b_cyRJr$F<umkCt8dKG)y6Bl%&|{ANFi
zd3qnyc06#KTPOYeUg5NSj?01~UuH20&-E89DA{ymg38a;trhj#7k@kc@r&mgKJP1c
z{cj5Ii}qgb{3Kzbm80pR1wk7R@tqT8pZda`UxrbE@AHfGeB2gq<oIu}_~<F_5|leG
zb2{&f;-iD^cVfQZ<@A59#d}#`!;Y;{DccqvbC1@r_|D?|@&a$c|8%+5Ng>MREyouG
zuPClN&U9}1mX9qn7m6JEvM+G!=fy(GMYCV+jSso&ekI!KgV4w9jt&Q<TaF20@-Izy
zWC%X><1b0O894n=<*W|<WSgfm#7unl?X3^-E|0J>UNL9q;~n=79uXGUdapZl!_m1K
zVyrtJEYq65Pi2cc*8v@-8Bz_Aj0vKQI=lz8m}a<6^66FC+@!MEW75irDPa>*#5|2m
zC!OJ%v_{Eun%ksM$4Q|oCog$y((>5Ur4lLS88&Z8R8`7N-gjNvGFy&|eaN+`Hom$o
zdiuh8^XHdOoSi$(+4gdO<aS@S&j$`UA6q-i!a$odC_9<u6R+HwV}Gk_k{7<~62E->
z$L6Ikd8f>X?9}vHvxeoEdfdnP8-K+sZ~d8{^{eYk$%J`)mzr1gw&awCi0|02?W*V1
zriV&5riq*ntYg_2Q73xDc*(pDd2Wa8E_+sYn1_0L?GdOK{aBP5wCS=_*|rID(<aVM
zYn<!zeEH1h%Of9w(9UV|t-W^XsvLJITBBt7a^V)Pq%}5%VVx4IU3#`on{ju_48Bjx
zn)ke%p?YyvB^dFGt&J3dA>Uu~lw^P2aI`C1BlI$CUWvB<uCED~)(X80>nvIA@=I#n
z`{yAJv%Q%@v~HMP^ksdm7SMX=T5PN!m#}M=UXNxv_nJw%5r;oFpAqA@be8MVS*4f!
zK@)85rgi2SFWs%tBy%_W%z^u#dA4h<*wz(dA7Wlq60N#R*U|iRaNe{xAEi$57w=O@
zFEc)?aO!D56#w?Ec_%w|RK{tY>h`ib=e_J!{+3TmW{WPF?RrT*%e!dFY}HF=jV^0@
z#vd**e&1M}rW)MO^z!>_Z_}q?ou9Z$4ZU9#@jsom=+3Fv-78nJ2j07sb9VibJ32p~
zWR-68vWd?>cXqDL(=^tnX%j!iuh&aE`8;H`x9ZE+Gxp6^zq?A|uGXY~1)qbiJdk-Q
z`YUPbm#1=<TE#=FLmw@8V-xc;_*i|^PP^=f)_SitJIv;14t@9kNmy82z5M@&zt^*~
zKWqH;&p(^}d;K>)KC}Dvf0eGM{ZHTgfAh`%H{bmKQ~ABV=j`)_f3u?<kN^Gb_<l|F
z54D^yuhqW=_wAi<<jY4c4lgCPFk6OViSEZIvl^w==+<6Y_NsVO(%jf9-NAm3z6C4)
zezII6D<HR4YTYrr{F<x>)9s5dOg4z)@0t4jz_GXj|KkCb{5q`HvKv>L@&BE%{`IL|
zgRiaU{_K;e)Kp=fJH<k8<{e#2tE`el!F@@Mc0vbczi6H45#{fu@<o<=M%<PaHhhW>
z6V~6X5Ij})=xEVu_Gdqi#4gpJyzE}>yJJbgXAYY`JGMpN{ry&l_n+QgV=Y;AZ=agg
z)aOTP4gKabFzt1+DJ{76d+q*<*R2k*vhSH}x$pa}3F|xT<=nGRD9zz$lJDB?UO(l*
z6Y=oPLU;Zzyq@@C>percpYDBkAEYUye?7NC@kqz|Etg&gocN)BGrikz@2;n(UFv52
z;9Sk0yPI*RV(vFioyi@S#S}J(-YTk5=7~?6aNme8`{hM9e)SzU9QQDG9v1F;t@m4{
z`*;4ge|v4al)VMozsJ80eo|3>M`+z4$%*BczwL8)ocE30jP0OL|8ahQPpt*FCV8z;
zX}<IL=bQIC-O|EB=Xn^EmHT@e=Pv0vabm|Di|^jE-~JGDyC<hV-TuPK$A*bJ4xWBe
z@$s<C?}tv$QaX7H|1LlI>C+sgo9D%+9PWHOZwAY(X*&|WFwMEjm>#^3W0{*or|;ZN
zwi)Md|9y6DuI(m6rsQ3hKJ2=DdNT92hI^G}OEvtG9v(@YJpV$|$vI3GuRi^m^QMi_
z;$&L4v8{8Qh^5Eb5?3Fsw5G)6=g(PGaPq~UZIqgG`E27##pS=a0#c<dckNyMEQI6s
zhTm>_Z+T|iYkqt*@zW=L`!&8wdpPA^)jPcB5IA{R)Z@+vwkTiDOBxj)k3M>;`ZPg7
zuI??1-|d41w=){O9ln2IVY7C3{;s!%TcV`q_qokmpT7NA_W8yRZi`^QmV%ly5h=e7
zb}hF#b@s{2uJbeBJYTObULe-6^Q1$~CY${HS6T;qTNwSOyBG5vOr7&te1f*+F~P91
z;Nti<`jfA|ao-|wp3kvjM^s$Up2QpCw=`zjwf=v_G5N_<CXPO5ho;|cKe;`GqT=sK
zCvbi6^^|K2%bK9@?72i~hyLMbfAWq-s#SE{JD2~?>L4$Zww#9KzVPYk=?Z5QPqm54
z8%gYS%=x3-o+5X!rhj_+iz5sVdVVA`#~fL3-s$Wlqc0bi+fDx)<t^-gbCL6=7kr0}
zZiHW++y7Gf*x&VL-oM)2e*AiPPb#M3&g^yfBmF1a+xUlO?%n*yKHz`)|J(c#j2e&r
zzpmLB_+MTBQug2T`5%kd{@;1+f6VLpbzklOhy0qK-FiN1{rzqK&i~skE!yxR&^>eW
zE{iCgYS)Gj7e78)5HFE&mvzV2r9NeHcaEOYos#jQ$EZPdZEC^w`xc9t47X33J72g~
z|Dm}2*$JnYiu0St-LYkPc<pWNv#(bJsxsoMw#}@!QZ3!Kbd5J(ol95C{ezEG+4o)k
z|G-^PHT=U)X7?`LGl@(`_!t_h%H@B&D|f!CTxe!DU%t3=&gZ3*Y-@zwT(7#nzgnyN
ze)GRqtODz=e*CsQvwh_=zjVeqDSoGZwk%<ql8_)aY2}0oy{gsQnEs^CpE&*PpN^?D
z`V6m3!*6O&@SpVfXE%3<Rs%!ndtILoA09n?G{x(sjNJJ!ZJSB?Pkl7rUVXH@GQCNC
z^LE)x*>AI5>|b*8etE7t^O&3clI;pou}XRe7Vj_o@Ypr|!%V9mW$`oBv=g|(R%IzA
zek@=9*?fPpSxVUtFZRP1&*hbFpS165Wq!=ffLlj@8ZMV>`Ce8Qk@J5J`|oKFD!yKh
zlRnlbJ+X%IeBRgZv!xPQGMXbFp1z+L&c=~zlO3Jkl9qMF_VOQh3CmyiO_)PMnWmg;
z)cyVLcT3r-@6RQthaKv?XKlHA$E~-o%x)(d{@V5S=kcFMuTNK>u{-JN+xzokmMc#W
z$g(!n_;SjU@x_CPyKxqq-(PyaJYKFa-e#8Ag&pR4Q?l&u+F319zwvT%ovV7*{eyFV
z{P`TWo%`FRW$$0?x#;~}xZ;wXLVugI^jy8X+&xx*C#_eMo0!LJy+bf0_Kg2I6ZSg~
zqvUrTzBKczTgS_POMMr%%HKMASo}@Jj_vK%&4wSZly%g<ef#y((>3?boSS6am(KA(
z>ts=)Ugw^wZ-3V^#C~uWa(iQAw?y?Zlbx4SmdLS%MY}6%g8ni1U0A<qw%q~kWl!wq
zoWB0ld+uMW*R`uJ7ic{E(|+q^dd#A{yUXV*iE^m(-qv}(hfjT0{UoCaN%u_nloRiM
zo@0H!zwF711%EBK)+@5lue-nOz1?oFKErt1dm$Ht&V9VLA?T%8xwGZ7Mg8Th*XK1X
zC_K`k#JTwMJa&&+o0Nr2*V*nrX)WxRnVa^*byn>A&BcCFI~FG|d-(O9xV5zP+@h*p
z-UGIe_waEY%PV@J-hOBLgR<*}JliDR3dCl%N?JS?QTQORcOU=V<?p5~`I``~^y2q#
zgZ8f>{8tX<mmScXwXfIMc9Cn-)b<ctK0O}KTJ_W2mHN){_FH9`=P%CwTFvO{f4ytL
z`wN~{+`kUrzxAu^`%~jO^Dn=$f4~05eZrpk`i9Fl;*On@>50BtU3&WNqxr^Fm(G2B
z{w+M}+qY7gIp@>ubE>ufIO)$;cbygXNNvZB_%9LnQqzT#v+quO=KP(z?E2Sj*K^;k
zcmDG;u{`2mru%{2+c$4Jy8Lv3=%H1+m@g~XtIIyOJ=(avim$ppyY%M&9rNG*y6<hV
zihnsn-;e*PGw)ycA9l0!@BaHwo=5$!Ui*LVwf}Li>;JF(vj6(O`g-?Q50-zI|C1Oi
zuXFy_thkFG;@-$8RDYUdGGC<Y--MC{=6)--eW|{6@PA}I+nfLLtG*cjb$RnY^ws9l
zf9p?d%KrC$`;VQ^{;&JFKl|VNS^s}8fAoKy<i7iJ9vZLtq3E>u>9+>PmrH-$n)dJY
z$3GvMy6nHt`xZQ%>2SsKo6qOpuT&G0Fmkp@*L^QO=kzqIKij|jkbL{ofrqcz-64A6
zn}=`Sn(KeNuXFo|&*r>KOKsN~9y3kacVxfoM9bY*wM_Y6bcd`ExBq?hQBwWR`h71%
zUjJ1Kk+F_fF>jc)RxN8{U0?m$$VpZ!H+(3Nm$SQ5Yx7ergkkcYzjGgzSg;9QI6ikv
zM2hI;evj+=lisw|ZJsWd_5Ijl+ZhXHG=BY9{&w{&>s7PcZLYF&|7qoR*vh)-Q27eK
zkZh-#9sj@Ge5ZW&_n(TU+I`VA^`CvZ#e+^SpWijBdc*Ge?eA_@eg8V;vwHXC?ZPDr
z72Z>~u6yxa``2IfU$XzIPfUI2aOtJx`?^cJ-UR(rxpMijLq<eyaqNQycM6vB`bpP4
zYMZ~Mk@@}MX}ik2e_CAY%2%whYf3FzRXXS3ymQWS_p`44yn8PGlFj#9H_NQr>-^aE
z-nwjh;&E=XmE@PK^|6`Di(foXy)ge<$=^>Ew->~*{moo|cj*PmwLjW(YIBNbEH&?z
z-o0g&f2F;~M@jV?x89T<-Mend^!xW-tH1jy{I!asVB3Bc4(lh?l_oaLnbysVA4>Y%
zmXzT=pRmeUV4{WRHiyN(Cb3Je6KSv8YVqe`$-YM#LJ95t8}@zS4E=9CUshLdsnK))
zjv%K1zH5edbCV0-zst4!lgYGxP2BwdN(_Exia!n?I$D_{J-KB%<KJ`n7n1nuyJYL?
z!_#N{%rD$HL$-XC$kyG*w`$zqwl(%i>8gFs<s#eXJV;^N#M`kpcSEeh!;C1m-|`O?
z%T7JY4PU*$E^N&oIcfhDk1v*6X{0`WQI}MxeY1$E#rc8m&wYEYo=aP(E~vmRR`^BO
z(Q<zHZ$~ftq92#nigkWl&aCcWIHxh~^hMvq71HkZzCq{Y7Cmm$EIl4-bA7JCuL9TO
zPlKx~_tiL0zAd?+BH3)_M`P2BlP!z+-n5;3<j=0%AG5FS{aY*5iqmWFW^wG1xiR^B
zd|%Ln^7wNzV&Chf_lA9)wwQDOy_Z38ym6<r_f83Cp8n}@obC3yuXlc3l~&pk>rl3F
zcDd=JYq4v$?&2?bz3y7n-QRb1t^Uq(nUC3+&&N9FwDrARt4qUPX8pMKx9O=y_t$r)
zE4N3NZ#{P=Hg|vN3B?V2{2H4?5_OH(H%mob{3wuY<Tz>mC%ufVds{=AZ05={)f-vw
zk4iT0n~=p|TxXdmelqT8Am5w!L2vddHa@Zac=N%v^6q;wUnffQUH<h+=IeQe_6%wL
zg>PTH<<(KEDk)9AX0~9;R_on`oyR|yy?6Vq{e@@l2lwc8xBLu_`v0!woA_SvM?>9S
z``?py%CJrD*6a9iE~aSj$`5bW&pmI%&8J*8T~#9SZ{hx|^I|pEcOQAb_p8B?X=~^2
z`+m*ey4wD4`;D3-KEcJGudk|@x#x6sET6=)SiR$-^Do@)6`obrm+_0g!ghjbw0+mY
z*N*@HCX^qsY3#K&lHI4G-2dSHk69&riZAWui~T#+bTc`Xhnn#2>R%L;(B(6$`Eyut
zfzJAEtD2%0ez^XzJj%wuO0c_9XYux|=IDj{x&O}n5^jEaiSYc7FT|{O#3yhZ{+w^&
zf9PG+hKp`RzpT$sl9ssY^1tdz)T~toz29D>9;mmuIbUYS%jxcunf>{;%P=urW(jzA
z@ek|IQ>)!9_Eh-j%eDJVyz>4#L&uGZK1<bwKWo;{m)@gWqIUb^XEW2dfH^HS78ky;
zcYdmx|F-h@(}4Lej|EwAPq_L`MC9eY|8M`#t?^TSC>j6z#y{hKJWv1snZT#8?0>s=
z@&1?pqo-Zn`u}+T$KtpD3t{M^|5Fg>cli^(O*5ZAlo7b=Hm`l(Z1(gOuWTRASUThS
z3Hj&Zzq=<_{(t!Ir<1K`*|X)-)j6#d>=|>4*89G?Q2FD}y~FOm>*rlatNk|f*nOrz
z#;y$(mNVsbA6!pX@X{CXThS$!))_G`U-H$tz4ms0t$2>+-<i2TX3nJO&+qQFu&YIx
zS}*$3ypZ9`w1*Gc?zZmc58o;KjwzGv=#r#YoF()3IRu$AN6yRCY+cPB{_4Cv|Nd<g
zPcJ{+`(=X3o2zpkS4CE99lUs+zb?j>eL=k3x&9E5smK4MO9)S!B(r#d(&GvBUe9}T
z>%Y6ZX_jx>bzs_u2HPW*_xIhXt5CUCHto;-*V)T%`13UW|Mjw&J!a3I$y*&<y=L8a
zQ2#bJ@#W6nE6=^0blvwxa_6l$wr-L24Eru;?JiB5EBf#B0U_(E*IQ@ipWEd7XhHP7
zdDo}a%3CCFjh-`C`PdxqGNIO(q@6d|Jr9J76?ZvR?wUU5kj2*np7ZZzEo8Rse{im@
z{MTN&!}}-XhwQ#5p5EZ17x#v#Zsz>?{v6FJ-_M<&{`^0a%>mViA1D7j`RPwraU|0l
zkEGtqPad!R@$K=uxjqJ~AMOA1{N?e#w_a9oeV4PZ<J<D;Ui0$<du;wcTm78>z3rc8
zALswfV%g32EM#V;SaJ*_pT|t0%&a+9!XBr0&-r%YQT6GCy+6$Vz1z>wx^VrsX>Ofi
zw>NMl1tl*18+b3k=RIrkzS(nFXYfl$^Yu5XPW75LV|V4oJu$gF3j+iklBe!D*t6ld
z_kkmCuiXltIpO&=;|Fm?Y-g(P?G;Zbd9q@z;r^fhx5cKOd0x2hM(paz6_3yOPSOq7
za`9~c>uI@f-Tsxh%cfk74Hog(mA>xV{RK*WJfazA6wc(b8sF4m+9-D58l&^W<VuHi
z-7NJSA)AwzMNCoqm1Zrmg_n0@Mdhw1Uv}{u%D%oRq_CU)bwd_sSl|gMsT6BIXAzMP
zHx!f%8Ul`|w>VVzt*ps^)1WMBT)(q(!tLaQ^?@g+3l<5o)a?9rkN5t^t-r<JoKf)!
zy|<sCyUr)HX4mf<^KM9elIgcAz5if#dwTe8i-(?v>^9A~l>ReG+-`&TpRn(39<d54
zZ~b^L?D&`W^5n;voD+}bcuo1WvpDP2$rf4n<)LAxFYn*JZJTvwIrH1NTei==BHurF
z%3Sw=InM3@yB&!6f_Y|*g7gmuHTe^4b`wsrZ))V%DY!1~K8vI6;NM_f1*xM)zx(x@
z{n#GQ+P_u)m%@xS#&_&B^n%}ses)wZKEl7^d(yi);l_!g$L|z48qVzv{PrSbXV1~2
ztKWK0Io}t>GttG({BG--xPw#bJObXk3#ZN5wy&>2bKe__=ifgVyva^jcHN*r{C(DT
z)8wDk%J<*?(Qdl%^4GLF4xKfZ|EJD~aPLfd{LZm3wJ|PikM;R5MQhu}F0SQsw!E{J
zf7Vhd6aDjHf{2Tr`L@63jI*!*j{fKOscFJ2U&qz^n;1|2IvaEPo*-AwcII`*XV2DU
zKjV01h0gMsH**RdroVPFpMP3H=5ImWrxMd@OZ9`_Q@#cTnEo?7?rLM7c6&L)#kuJ`
z&Kq_`&#n8gcWa+*#_px(E{LD*zWK4Zg4y@M+>iEe`#-Jh6H+_%tc-<c&f^6UKR?>l
zH9TlA{~mw8Zr&g5uw6S8?iec?A6YWDUFQEU1BNYM=E)fCG5DP*$F}Io1d}NKBPsD}
zbN5O~$SL>S%m33WE$h<yZNuS5FZM8go3#7BO+|y(J@w!I`+vP+UVdTzrc2NC#B3~P
z+0R?A*RLNDf3;f0hT+=n7c2X}IR2>JJ?&Mc{^X@^T)sa%AHDqJedo^^g7URndYNt;
zod|#a`KR)muL*)i?0vI-9doaG{d}{d?axOdAJxQ8RPdyCY>oe5r82!jpFO=*)8zZ~
z*xIYHYb_fmhb~N3*C@GF*%x%WX5O9SHI2&)=C(9SgdF*!XSVnL){e5r&0KdjX#Vdy
z+NP&pHT(B^_Yy%r^|>$01IyU|SZ@l=*LKmqIyo?7!MPdcPrSayiM)UDFgPSLRhnha
zwpU!jyBs(c$IdE@c<6Xqd;9GVPsJ2or+?#lq$TG3u)xZ)u~$6*hyUxndKcN4TGTE$
zpE<*M=EKuhMQ$#$?)}o+)BlJeEpN`<Tld;HW%#RhH!iH=dHTEm{r!Kx`uX3f-nZHP
z{l~$#?kE54RsYT9Gi!~p#k)CY?(rQdDXX)O`FwHbg_Rp;{W$$3sec~p(GQ8g-)vay
zwQI-Klj67h5(|HIFaPjcH~7b1)7EZTPJZ3n`S)k+eLJafpWEv7JESi8Z#^IX{a)qW
z>gT1~w#{;{xN*L3n)vy$LO!9#H_d+6ZH~`A_v>ur{-3x1Jy?I8?f*9WAFsC_-2ayU
zpVj4{uemNSqL0Uw?d~r)yW`SU$vJbZzI~E@_wm|kiTh6d`3sM4mrkybTzuWxQuN26
z=@zHrj<@>GwlUpV7ySC`vFmNCa_8#v2khgy6?yK~>5ckRwun{7t$U_&UsktH<%?_R
zj(a-i>kp*NdeKy1V?B3n`ILw!_8dG%V$Cj;F}w@p_mKPA@FehBaNKs@``_YzZTl|t
zhO;fnc+*d|*XpfH*G!6SNM?v@;1^i3pK;v`m8-E0Aq@T&H)j92wRiFKpwAiQ@6?Lz
zXQszQWqog*z30PZ@rBQ?pZ+}grs4Ni<^>4~>i74#JfEyA`F!c@JzpkIw>qb7Uinmg
z{UM7*!N1HWq=ji4t?MlIu&%X`E8%+hQEZM=o#|nwY{f~|k+EwVygtmZc@!@3X<k98
z$po&xX*&`uj@@Jom=}JshvUY>vscfiY@PDt&6GU3x|_c0AL^^ks}G(}?~{=@Z}We$
z=a%w}`m=A>@BI7K?f0D9&+pjX&!|86R)5Feqi(;w^XgB&)i=KtU-(-)uYT*rx>Ik}
z`<S=vHm-h{lBYlCdc4{5|A(^m*YEu^EpFzwQ(MB9?VYfo)9k~<Wclo0-@_)Y5c@DO
z`Fqx{>GP{A-#xW_ofrE0`-%0uD!2Bz*X1f){ABy-HFIa#`@n5x6EeQarDijCnt?b1
zfBt7j-rb(Px>|Sj@3P#|^{J)z*R6lIb<MlmTd(e&cC~i*wq4gZ?aIF%{yi$}``cTu
z;!eNX7aM&Sq$xVgyj<2*d&}ID5yjU7H+(8qKOcQm%l`SsXZsch9A(pI{@JHAb-s1w
zJ*|MBJ9(y*mYlvZ;iN;P`|>mA=i20#p8OMIvPnNBcYP`dp)*Qz(M3{WB6y@We|s`d
zcAkFt>h#^q9qgX{uvh!?>j#V6-UI(Dm#zBsXK9Ij>E3q@=Mr1a9+zCSwfFe?ln;})
z9+%s{{ilWV9rb?e^MdXlQ{ukFJIqn#t=p?Oxh-eyLF>2!#{%NQwi!-2za+7C#hH(b
z%-c@wF<HYu^`zNejyqFMu(7YWlJ@A>Qud3<4Ozt;=AZQ&bB`9g922=2nBp|?p^KR?
z$4@okEBnffzHRL_ul#-g@#Gqt_urGg&C~z&eeSCI`zwEapPTh<U+~#`<*RP)Seduy
z=cm7Ezdrqa_Vd$UvoBYF`+frB7i-^e%Dgt(VDYfGdw!zz_RH}#_fIZO4g39mUz>gN
zX3?o8Rg7<}XZqQ2S$RKOzH$PasC66L^~Zt_J1=V<d>`kfYuHt{&HJq8ww*7hr+0Bb
z-Ff->zW;Y#fA+b2bWULR@`-ZJi;o{nSo`|zy36mjZ~5(4z3lBb|7x!yx!viLug{P^
z`LMp=SwYE~Sgu)14|@v;l$%fSJ=y#DXV#{FM_*h_`l@|@rOj3!zB}6-RbIco<m<$#
zyL$HYyif1DAKyI9z@;B0nc3tzOW?r$GxhC1w_4oe%?>kWSida3EcD1E-!45DbsIjj
z+WJX44+Au>-+0$}yV<_>$L05}s~3t%|5E8Hn=9!tQDW*M$B^pkh1+_Quc&|7XYlva
z!J2PPdn;G4XK`1_=T@JXlQ_ZOuCY({ZCpgsg^J5khD_&H{#svL8rS-wR^b+VRrd>~
zL|ZL)*KPhwH*H(N_4L!BH+BbECx{;?$<@5;lbf~TvbpWvmxpKnRn4n6R-6B=G<HSK
zQt3SxpKLvuZ<2az%2v_MKa7;zmejtDN&6L@zog`I_T4|<@@__L&si%yFUS45QOE3+
zpW~liS`haAMaSc`2OQ^La%HdNladQPzGL4}!TRz-mHWRfT~hKE+`HZ-TmL)weV(g=
z&Zhi5vBC-p4ps~Y3o~AxEqU*p*Lm#Hw_JAXtogQ0k7q8p^faT6!@{`ob5`fk+AUsO
zH3FsC;twyi&yD@N<>{+-t@Q1`Vz)nN@VlOO|9E@Tgzx+>_h;mCOn3g+>i_Tceuk@t
z_ih}WS<@-cSRy9CaXt0coW$oXd0S<7@(Eu{%DMc>_D*e$Mdp3GBirTu<&vMQ7j@=Q
z`TFFh-r4F+`~Us>w@KI{=ey1OXFii{8h=Ntxx7DJx&ES)O3engs_dc{Y7Vsx9|X?6
zWO$}$7qEZH`gitqoBscKXCD9l{=VJkU9U4~iEZ|o^ljy_YiB?0FWCI&#o14f%}(#X
zo%ZuzTB%I%c841Zd<Kd=-`{*(Qajh*WM6tu!}slb_UxbY=DXS17gc((hu1|)7dc#D
zHu$3LaDH0vhy5wae}43Sc)wfF_QZuVEVB2CMdWWO*=|4Cy6Z#v=_I~AZ_V$2lg?ky
zsb2f;b4F!l0Z)%y)8->;Z`*Rh)L$&yxXb2!1oMgWExrsQ#~06$iQC~Z#o_ha86_)%
z3Y@BbmA<&J>&V3m|H36^iA%_cX<ka*I`wGS_cq^SA<-2&3zqNS?Xa`4Mml5t3E%GC
zKe>)azIn;$>0jJ&^>^0!<QDdS&)RQZRe91~?W`^+@!&nf)>{4J%*$K9<>*bQ-m!>l
zXS=q(nB2Rctbbms{eJiRe(m=g{@?c6{JfjO_5bGoeg6giF>w67`)=R-cf0q#FSlZw
zYZjcoe4W0VCfDJ+x;MJ}HLVSTxF0qo2=!k-Gbgs|{-T<Oj34r0UVddP`?<ff1kYB{
zjk_OtTEXi58=<!z-oinj!g4n<eu%a8b5V0L*X-#0eacJd)}oy!qjoVHehWHf@v?66
zG~LTvKh9pT=3zd=q}K&^WPf@5e_OxB-RH6L{QZYd$Ua(~zIp$~6x)S!7bGs#X?@~!
z+Eq(`TKdV4f7~6yUf9kokom8sr1r|*Q;>VPuF$&&2KSFA7OjqpKX-opy!Zo$pRfL@
z_;X{$nLUr6yxn&`A!&K^%WIeZy-BLHv0uLGR>;A^Z;x{dZ4S@8aOr`l_wB~8H^Bm{
z!e7{NrQe_SLT#b+X7-qQb7l3Pxog~Xb9>aJnd0*QaIHgU{QbXI_uTjRy6BTn`1eb8
z(qa2*B;KBG_;vJ+*cJWkJbC$m89z<GC|S!cSKp=W5L-8Ay+Omg5M$ZjHg4DFolCEn
zAGeV6-lb(<`X0S^4&uA)n7_$TX>&~c$u(2{%)7p7dxr1s3)#*5GOd@EtYBLj78Lwu
ztLe#=Wh>ge4v4DAvu^(=re*vqf3Kh4h32OVoEshpMVm*&soWK<J*Lj^f67Uz`hwTH
z@166zx?;!XyKL(Z{cpJ9zeGCB(q4Vljl&jCESo<pkz(jsmEzPF$@t7EUT~X%t!_;9
zj`_zA-Hp*OkdxC7|6KfOdh*(5EuY(C=1pGD-S4=zp?muBIZ>^D81JUIC9#ExJ^M2&
z|JI{h`)B{{yAxJd{$uytwRbifoYi&KsVO)eyr-FsF?OQI*Nb=g!qh*VJ9lh_c-j+1
z4R@hHj~XrasvEV-l@oXKh0cw9)iFV=r=eu^9h=u0k~y5!*8*eKc;1LsyRz`JRjz$l
zw^7oq_QlI<Eo|QE3TH{4@O7-05U61n;EQ>FAX%&N@H^@DZ_@L>nXs)>KX9&%_36Dd
zuEX1(K2`X;j`P&*U3$BlimX-b!^-ZPE!EZM_sxvHo*G~FzjF7RZ!g6=->;TDxpMn#
z?fxYk*SAhP^Xr<>jV3!~hkg6^D%x~w+CF&2SNP(4)T6o<(>wh!`_<U&@4mgfQgeMq
z*@h}R`{Oo^4ZE0R8_o0HEQ;&=#c<rE*6c;X3Z?lhb0(?0{v-V<%X4=Zr`R_C3F%Fp
z_h0S#S?vC|_{qJ>L+_aVE#}-|dCBfuvFvDA-My;C{|(dr@w1CA;(mRS?S9-j{l!d&
z7@|dlh1>2+DT?KMiJi=Au$}+f=K8b0|4AjQ{`ltPy<D$GsBVAdg`}_FBE3&<)CsCM
zXEGu3#D{|U8zgONnSUhhdwoM;70<h65f^_J`R}`-l~}TD%QZ`esPh81>wfNi$`|};
zLrVXOFBju~mKmyOb$lsLaZviHYIJf!h*EDouY;w|j6Lf!K4o*LFRMu6&}dfjI^p%_
zqI>q%s1J|svaI~|`m`|1)~k9q-M(s`zE$CMTj8teqB&0r+PZE`Uy)b4c?pN&G$l2i
z?H=Dv=UhJ=)-luS`_^LbwY^MpE;IUt1eYFMv(!u1H){4iiKKYl`wQ+p&e&%)C;8ve
z)CAk#!SYuUzpVH0ci#AIUaR`Aw5UIlN$X3TI^-TMxWn@AvH8Ah!bd--EA`bbDOb%r
zD9k9Y{LCP+;nbR<7pE_a%BZ?YCNz|=bC$=e9gUej@qN;VfA8{4Rrr<WNB`Y!mQ(ks
z*5~HJpxj5d)b5z7DYehteb`_1ncMZtW|MndYvuC0Om%-8lPvm^>AI3{%k4|oUtGWD
zVmR}+@x0$|-}kLGdvo}r)OlU*>4rWm*Cy_+od4bGQcKRKd-Do|_LT?4`JK8SRV`(!
zdEZ|1|LQqY>i19nG;#8$*>|_kn{vM_XrBM6{g*v|o}K)uDCo}a@W_PbP5Z3Z6(kq7
z%Dagcial;#*mds6_J=)sYLz#Vy7*$HpVn_+tk;=*datw`Z^}=x3uX%n-zc2^>R7em
z=l4#DwsWoqF5>w%IUf&w^OaZ`^fGs){GA~Ce=$nUF6W<`yE0op+`K+NX`22FG1>d~
z*7mc_+IHgBm8Wvggzwya{rjOT!{Wb(t^Qwoy>RwKj^$PFbqlVyi}Q;w|8j7z-1*Ck
z+LWhWcAa+o#CKC|wgT6;VPE6+PRu#=vwF62&dT+dBK_A}aVTt=Z~v-d%a=P3A3xh0
z|Ln>q?!8gB_H7cMyFIo1dfb83O*#HS|NXMv<K~>XekbwD?g#aIoX`CJHLK#AY2p8n
zeQLQPo1dNDYhyioe(}7d8!{;d0pH%P@Y-?YPM_HEYc_w1S1qh4x_Rr#FT?X3f7hq(
zdM(wQxYs3IXMPFm#|5ijWJ#R6Hm~B<=FRi6CTw1OK`6Rj^Jskhi&$>qskdj;Ed0Ld
z@v6^^bJzcKyi@l^>csxO>T?mt=a-jj3eB=V_5S&Xt3r2ApPxQmJmPv?S%rrsbKIj&
zgYdo;73vjL!fD60oRO99$o=(lUigK1Y<6En{&z8kPVYXr^T&FDr;fZAZe6gx>(gA~
zc)^o>YyRpZs@ts+w(m&DIq@d3Vf|^oeLLr<I67ay`AzKUoYEviy-IQGCz)H83xAz!
z<hlFky3pB{mkg493sS3!3V%L2+Fm9-Yf`4dP0sl*Z?RhO`yM{9Tbh;a(3XGfKUlx!
zT#;q9onsox78fwB_}dl-M=|ADrL)VQO#0LRo$u9ecFts(ZHf9f7d7#o^vih8G*#8!
zHlb$MZVmm53*LPDBvWmZzn5vhM-#&i*R$t&>%YHqzdg5eU2GWy{Y#7~JJhqzwydu6
zxZnMLmic)?Q+dUXe_6!Q%sYAFUcPrz`FEH9_^@I5$+Gt|_)UIPuX%MiC;fGYP~6=Q
zE;mmV@&%muUhG<_9zW%Kf!j~t+Q71Za<PH;dN2P~|K=X~-9z$Gv$@XO_vg6#pSJPV
z{g6NLdTI9owpADV%hGPLeEt3*^=99Pd*^4SPBHi9Ir%s#R{rw;^Cb;0&%Fx&)O4}R
zY?cVqfrX~ItA%on-mqWZdo$%$T>1p-+1Ktp&z7H2ZzexO?94UYyYj6wOKcLV_|5xX
zF8-(aSLy%s{$p>y&H8<M_nxbki_0GU-*8U<eY5Hv>jcjIyxuXp_e0R1+&l3{9_ro+
z+xLb0W7X?V(o7c7E{(c+CV#*G+3{WJpXrfz7n&a^G0U94wcxf>MY~J)me4KIdzO9a
ztbYCCw(Rs7bLTxu*dp~%-0J9`p!GBSo_WlDQ`K*3KO<3n#@zoe^$cG56qK(vKA8XN
z@21b*wh?7K|3&AiPOl1Ea9|RbO4i)D@$=59{{8so&xfgUY1Oyu{Aa$Jbnol#n^l=5
z^V{#+uepBQ@46<dael!`CLInP#uu}Hbz1zo@zed2%1`xDWyPuY*DUUd+Q-Qk9@P55
zz2u11{N%g``y><ZvTT^9Z2I=)|I4<eU!;O&zb*0cTQcL|FXaQd=PxeJwz~FEb;9w!
z!`}0wcry;9ew(b4`nB9jB=L&s{Oo`F+4466q;JOmWdGiF^BuSHgCG0X)z{6QzxjH4
zaJlhsp8f~!e^N{9I_mG#e0{iY;vxUYXCK!4UtV)ye{5*V7nymXp<MgJD`$$OPPP8O
zKWKV-<k$U^z8v;V{PA39bE4|W|50<#oqOhHzr=g>;iLJ6OYeVrzFAuS)pL8x{2Mo~
z{(SUwb@vfd-)702Nz0dW`y_1MvEbL5c>VMGajNC%&rd%-`jTfg&)r&9>H0Z;G7D>Z
z{@i~1`0*3Nz71XtYv<4ZZ}D8kwEx+2_3o=(s{(W<Mmy=Ax_Oml=l!GI+Mh}tH<j$O
zNchHRT%jAEz`4xQRIlNt<Cap6HK$fu7%HDU#MSZT`kNUOWC~-y9DDhxq^fM+5vv2~
z)1Rk1_%Wz14r9yU;`y4ySA3xE6UU23vp*j_%Gy!4dHVCumUV0sKdt`x^UnjVN=}KN
zOx^iqfBI%Nwr@;hKP~@!i^4tIgr#EbHu<OSZ?<9c^1kv~w5KQT+K0}YH?<%9I)84$
zLgq94Yb1JDl69VG-`ey$UOm2k@}26k_pkpxIXOSio?+Qn|L>EQ$KS6nd;f9r@89))
z`+jm++1&ddT=f0h<9xY0|9_PgRon0Uz5I6nJ6n%`CGx-SJLWw*`1f|X+#T<4`#tmO
z|2}_m@$K;s&%*E9`28#R|8ehbhk5Vn*Y3BiEP4O#?`{4M7w`VAZ#e(x{e2s^9Y3CB
z>q+kAe|u6s&wkI}<JJBv?l&*5-|_#e{ABj~HaGnplzzPWXJ@nj?~i}NHNVbYuAQUe
zBYmvm*Auz_h5tQ2J(<1!+yA%U9#<PIwO9Gz^{GAoon385{GI*(&t4afDk=KEdMoQ;
zh1uT!F27Cxp0M!3|8Mg1?y?uU?3-cp>)FZ4zsuj*PncWv>C3zM2@Er>a|=qWGoAPC
zsu%zE@B9qOckh~Sf0ut`cIdRh-{ad8?W=wpc)mL@Y5%`8`Le$c|JKep^UqxP*SWv#
z{c?BO_usz$pxR@}d)qeQ=GN0bh0Y1W``J!*`Morod*knJfB8Fgb8M=9NraWYSM!fG
z7tFu@IDg*3&cBL3FYi76eO}$)_UeA&8&C5S{P+3U?fc8}?}x?C;@>B0ZKQu3ICdzp
zqc^v<>B9H3bJ@TD_h|pbqUf=2vdx~_|F8d6$0skcVVJ$VU+&;(4GH_&FYFU!A8LQ!
z_fOdD(L_5(2`>k?C3BZ7toZ&g>5SgPS98~|Sof0ARV?XL@s8*Nt#$jH9VXk%(e1N;
z-+9MBPpv*CE@lm1{Mo+xhWxuea%UQz2YtSF?7aLliE9quB?D%3EPsA-^5LT~YwtwY
z%~Q~`h-aMjQ#j_VXVG`RPy3A(YMlRG7kGNMLA5>ZMZ!7HPhamI33t8h^HR8C$@*!_
zKcBxIcQZF;^YtlpuU73j828<*T-`J7+;sK-`ww3|d;0R>*$r~#Wo7?9H&5)8o*!6u
z{PJQ;?tuDRKkt9g-t^*+xXC;@xp=v=D=pp>-+6QN<DX~RYwqm2woEj6XW@_ZfScbF
zYu7A)v(?w8tmyZ}+6D1P?%K_kjXxJIe`jg+uFcJ9E!;s0hU~tRww$==A2^>Oh25cF
zO}XiU)=nGdj+j_ExpU#G#it)vDUd(kDRb_=+`035A$;u{&+GH+f2a~HoZG(t`hJ^$
z!!pZ^ORePZ@yxg^%_BK$?xiJh3@sO@^QSLgVH+VAbEaX^S^w$N_2V;Ve(heW;iDID
zin+`8YO-Nry8G8{HV%!SpKY6&d#2Om!R+8g#mXyPmkXb|bE>6)ZS(Zc2Fh1M56p?v
z?eBl`^r+^k*dsv<i}u!^+H>L|Pox;v!b#^pNw{zBo_Q_nc>bh*7K5cnzUAnpIp?-<
zpW3GX!epn-)V)pVF$-nVip-)r*JWOlV_<drsPTDw`i806eyetUvkPP1@A55UYRRXZ
z_wNpheK@^$$I-oOy%SUy&fzL%Er0*e=u__LA2AQw>+hUp*?Q+W_YalaS04?Ve*R%?
zIwreD#_hp|?x(i9-~XJw_u9GL-IFK(yvW2S`87gcVC`%6Lju1m>SW4GIo=27-FSL(
zPIi`@e%%b^=jPV-t@ifIh2!S@+wsSdzoL@ul5M!Z>ei<>4MWAP_Et47tgF~8@UCx~
z$Xqs_hn!!3{YcrlE5P;P%dCGJRjS?`@GtlB_^&6H?qCt;A$Ni`Nc)LF>I8$tCn3}C
zbf0chI>9u(tLKU4x`P&5s`=&L{@>ZUJL&h+edSeKcAod%lgQJ|P$|=1uJwII@A+y|
zX0sm&eHW@(bc~F&cKqD&xO?(ZL*remHy^dkHl0y<Y{yB{456b;@6Nhhh+3_0KmV}n
zQR!>*c>6zb9r(5S_IG&(d6T)@R+UyfWVs+D<MrIG)`s)W&K$EjjQq`SZmU))#CCjr
zKF9J?eDAFdZtn65@n0TQSSo)u5`FHex9;4tMTvE#eJgS_H<XxJ|6w$cdMfoaZo^fd
z{(d2;+`?I3UKr?0b8vr|weTuy+>aSk9p(Q^nY_Dx+oUP5wqUojcgKY_9o)0x1sI*y
z_}p$!5_@!HJ45e*<${OyOP1O0VXS6iZ!nUR{Fq+CSujUWXx4%+-8Wx7w3~O%S$tmK
zg9QvJ%jY`Y`du2ly#L6Hn!Y7jZhq_s%O@~Mv^?o;Raf6`rqGf7yC^e$-5YP^^r%NK
zc?)LcG-TBZ|5h$2Rn=SfWtVIs+Z5i<=i4T_gr7;?^KK2(#}Mgvrz$3Iyt*owQIb>j
z!Wr}Bzn+~u`|jMmSDPze?2zj6ns;L5W9v<)qlBZFC7#L_J$SL+c+Vo%#p-!Kre6Q#
zRUMQ4IVr3A>VlI~wq2hc&!E+n;MOSbz`aetY_T`v(nSXuZ^dx<H15#npEyr;E1!zV
zv~%6>etF$b+PqL|e#5l+aSP0r&QItwSU$x`Iph7o6)R+J1PjOKB=Y=MVr%c4yT4Fj
z@nj`t|B`>xjz6}0zS?tz%iaezZ#Ih;e{*LsGu`8K*y!NCs5qmC4-#kWO=J?x__@Ae
z){`E-hYewKP1S?HEM^Hhdca#rb7AnoC2OxZt^Xf-+>%*jm&Ko&_R47na#>e?UaVhl
zJNbCWed`1L^<5|VO5d3>$R6Ewp4qs&T>lG4`<nR9{{>>N_&g37oHo9?V6B*j(Eh^_
zn?HZPDcYQ9eNy>}!Odxx<5$XP7;7-Tz2gx7v^Tx(^yZvNIevWX%Pz(4^)G#w`~2nM
zpC>PiPVl+)V)E6~d!v(D9NUsrd6+%)3YG_i99UHmF0S&=_1nWYa||AH7KrO4Gss#U
zy72cX_aDArpWfNmRrRy|`gv`=r^N58#ZfUX<$|&QC#uaoe}39?gZss=RF_pO2>hX!
znK{!;?d1CM&k=HWjh>e8Z!BWV5OUwY=WwXJ$i96xJ3sr_oXGz=pV?%cDNDw0v2upB
zN&e5;SKpiK>aDfNevkWx*dr6V-*xTz8@_#tdAv;g#y=i+#dh59SY!Qo0arEK8I!l>
zpSe|b8tz)+DlEnK==a$&IT6u+qGz56)_pnHv?qVkJ)6j7Q-j~V=gPM#m?=Hm>G0S2
z_w0*GQtKkBUse0p3m;IM|6lor%#@<&2HP3&dmK+P|6JaXm3q?Th&;!NXN$^TG|xGp
z^v+I5VT+lDqw;6%lD6}P?=tN>U36rQm&=^{x_45kkVxpu6BS2aX6}oeCoiu$|3tM&
zZ|dIX)$h0RXrFoV>B$tY9ATc+eB%f28`Sow*7W4doCz~{*IyjQB6$DW<3$Mx^Uge+
z<oJzgt%{b^#e@?Z9~NBrTJtll%IG(D57XS|&wbv?y+8E$iOj~Yg+)8qLtcL@e}2Ed
z{73DLS-;n4@A><n@tQ^TqSZ^aGVB+1<tn{l*mP3k*B8H<LpBo%)c<ZyzAIR~y-6pa
z(y7H$;>Y91-=5s)ULZYZ^RAgTJ8hhq1B<>J`sG}+triK|zBnu}>SH8_IJ^5n(-jFb
zrh9KvQ_NZ__|9%#-OYRJ%BG9EYm2^&{b)Ty-<3zuZ{p8y76-m=%#7JHU+?~6!=L&6
z_3Pyw*I&4^&G^Q?qg$q%@VzxsTroXp!s}KQ$y>X&G89f<zJ`5AOzuq<IsTt<3yyhz
z34NA(uxRV#4I8Fh6OB8*_2A;^ArF`BuV=pe!}P~-Q(bTV9flFB9~UrtABo%(xge}@
zMoPo%cPio8&0qUDn^R_ZI?mFS-e>2RzS}+gYIFVne_XFs<8$7q?^+WPx^%|!R99hz
zPnGWb6L)h>&Z%zEy8KwKTkwkNel^S2%Ui0=?Q|;&{w~Y86(zKr|L}6vQy1$4{B(P~
zxE`$Iw9AndtiG1s5|ZNl@<`R6sMlMpISn^2nLcGzw8e)v39LtcE}H*gwej++H~$oT
zOfs~8wV^oCb}d`n^j&%!wne*@cCNT_b_v(cptoD4s;*z&y`S;$wROz4zi!+*q@pf!
z$hs&uTfm|(cX8n%@!j8K|DHHLDfVr$YUe|ppFjN4p08+lbh^Bv(9)Xkv7!05jVgKE
z%xmWEH)Z(9Uvt$j;AY*rBRt<-UOwi^=Q+f^GW^0%iK%@XjCHc-#WCg8A5@VtPyF|Y
z_2%W0+9w-5CNrP&So*h*k3s+a&q<Q{MS5=T?lai3yv0v{KFZ2}cHZ<=c~((#lpkNU
zvcCLQK|S$G<;APJI(J3RdbX1#NI;owbA_qB-Q%@Zb)E4QuGilRd=1%a?IClg+tO;)
zI=yG<+MAYa*>mENi0Semqb~&~4@ndrzVSP)X#NpBv$J#0#q020+%H<1`blnm_qE**
za_1-Bb@-;KH2Dzsoh2`i7J2PIV17ZlW6nNt^XKO3jgBGfeE<B^KXF;!f68-Nhq-Fy
z9(Jrtas$6=H6OTHQ&&>iCi3?~yTCeIYnwTXr)$Q`8!czx+4z)y`|}ddUwgwZSkC!5
ze_H;t4?I6s_8rzacYdj6UPF6*L1oIi$g?}sEQREXKB$CR>c6gVD_eSR--U2{H-7D#
zeck=h2UD-UJGA~#Men%{U0>?Y);<ttoAT#S#iR@0=Wbr3B)sGMYNgj(3+9wRcE6R;
zaDR$oB){UXt(KFvwtY|ce78S>|L;q;xHpTGtJPgnl-NWbhTTfMl0B(R&S1%tId3-`
zbGsb6uh8bmm~yGIcCu)a;e_-Si_a-`hj;&f^yx=hIqUmVD<kHdxOGlOC-LeAcI_)#
z`zuY=4_`iDw>98;@|9gydaw5K&%J$Pb9{98)&3IYYtOI#`Oq$UX*%z|<xeXo`25``
z{Q2@Hhgz`=*=Ozs_HXTS6YIWJt3-%C-1RxfbJv@K92;MSFY%9V%eQZ|56j+vEN6m0
z%gkS5>gmVBb29?UcgQv-<*3XRy}jU;r2p3s6VoI1IV@%0<eXs}5)mQvvc}MQy5xDk
z>&G4(k(aq$RC6@Wc1f<odbwpQtR2I(&e=Sleqi0%FmbC#yUtAAvoJ5{YccB_M!tm&
zUfNc*8!IYL?#K{*lXt4?Y}}%GUO(1dWw?Abbw}I>qnVeT?E6)IN|~3}IchN^CRQvt
ze7bna$r(>mDw$M%cBoz4_>SXyv%a2Q2d~21b6m_#3`-w8)6+k{TjhVa^3!Bx=j(qN
z{x>=~Ppv2}@e$H;ymVgw)BpQY|36BsvsHS=FT#>^y#7h$(@$G}^ecUTXZ7##_8&X@
z{_lXHAIrP`@8J6p@%n2tTaCi1hSeMPi~YP<d8e)NkDN+xxOsf-P0l|R7P~9V?2k<7
zKj<-0cG`n?a{A}KP47=%uJ0=1<bHRvsMiX|s#zP&wLeWfZXtXw=2m5~c|qp<KOHPd
zzD$2pw*7q3AY7RcU|IL-`^lXCeLr1|oY}umm?JR1cBV|m<Hl=D6-M=y;<+zh<u<Av
z2)+N5>z|LEr{2TM2bQfrH*LAp&2>@t_wh~L)-1Cj^r%O7?AiED+tw<d*q9p-wd>r0
z%@^KY)cI+$v-WY)q$Mi(kLuIbh#vUA*RhJ--AFmtP-|vmWa{096-!gUa3+Xd(@>v2
z<7!7OPX^Dcdyzub{jV&Nemn~gZ{M8kmBF}0L_=GkxNMtJ{LOI3r-El#HaS{}&3fnA
zerq;2-+{}Gp68nU;?(}_4lS~=ujQO@^X3jw4=;n&=gz$>lRZ#&cW0sI?b6QwmJ`fG
zl-KWa653$A`SR)o``PEY-+gc;-^k<E7LO;nE=RR589q;Zz?;2u+Et^S=bh}dn<`R1
znyK+QGdqegoH3BA<_}1@5R>bxbbRZt!noJIV&32F`PR94+jezN&6_KecOmM-(dv>7
zv7H+tR$gY_W@|l9R@aZA;J^HX+z0pi!tG-w+8;O9Nj!b2dGm+1z9sB$%~K!0-#)A7
ziD30t<s-H;;x`Dtdig2sks<4=H>w>!Tn%*}@?XEg8gSl4u<goKj&QRD-Tsrh!(>`k
z-<oXqTjKHL6z0yFNis9^@6_>C|M_#S!|r$5eCs>x0%AvZZP{t{Z24*75+{#kC)d^F
zym$Mt*7wZWzxzB46uX}lP7G0<^Mh&rsp{VbGipAx^?i}-Jz%N3E8=_7B)>F8Z?ixD
zRiE`=xPGhAME;^`+R>L!*!SlY2R-D;+rD@0dzLFTCp&hU-*L3QlRD$X^2cpyN9z86
zx%sK4a#svTOn&gxxlG3L0_Kl$woKS4f9lT*)!i2PM>T|xPW>yc#&#@j&8}<D!#6(`
zFSu-I!Fk{Dzr}<de$i(R2Tz)P+AQLa*uD9;mlsU^qIG}XokSjA|C{^w9DQH&|J&mV
z$9xIN>_gYqR{v9Clw&DaaCGvKtYwmJ?}N7AuS;=|)VY;<|J9|P)0pn7hwG=YufBV(
z<~zfqyERdnRq-cJU(uSX)=^ToXY1na>9-<XK1E)V>{_&A*Me%!1=Sne`^(!D>;CF8
zR#d(|-pH+ecE^fyA`kX0&3^f}z9qdt(Ee#?Tk5WdSAN<bnsz|?@<Q`NZmQPy%xvx!
zA->Za-i0?_z4a<yVBIyYBU&w&tyAW@ZEG}2klna$PP3rclbEWyu3t}sIk!jeiDBq;
zpO?|vIW7Ho_w?mLD;n4Dn_IGDZm(Qt#rH=Cb`&2l{WhzfOY6~lx$}H#zc)9(KY28F
zsXTuc|24hKR~qaiH16gY9+#EP{5JQ$-HxV9Ju^Nlsy+CoV!7eg`xfgp0XrA}zPstF
z!ByY4nzpa+p15{~GyYA<QO-3}`*zJW@>x3hgLc5X+v{qz_80Ljx*+@4@8RK>-#`4{
zZpFJU_d(02M2*aXhrHM84}X-td-AN+=Gmpo%wM0$zcw@B`PJrgtJ&v<^INT#+p=D*
z<a7Gnr)Lx9nICG7zMHoF-kTjaOYfImcvF?X``zuiX;r@${C?Zqn=fC&{ygn^_B)@q
z4Q&3^&AY!oySH)Mff9qsA>nf#zDY2f_<G~@_di+^_&zR6v*tDtxXAtKsY{b*o6zMA
z5#Cjo!tw*YIJIQg{yrG|>$&FtuOk0m&3!BTuB?6c-G_PQX1i<~Oy!)p|5bDTx0||u
z{;B)??>v6XW=`Kf|I&S)cRy5B*mvkNZTk`WWYUV4m(Q&Xetnredu`_W(EGK!F0RU$
z7x%}u{9%$<$;L`Ut50h`yfNxIetuqCorSQj;fxcDUhe!7x@p5#Y5(mtj}K1Ew~_sE
zjQKCypXYr!kL(t*YOyO-SGbqGT)@7jJcZvpDmd?I`TV@hsj+*McUPp>ioZW`=6y-o
z$G$Va{L;mp_iv5msqKx;+5fTRw7Fc)&tsPx^GnJF^CaHrJEreG7kl%QKBsB`<FnYx
z|K5iJ=B`S<QXhWKFaF2+|F16fPAhbgF?3Wh&HR|kZteH7^hf*qqbbi9_fOh7zae4Q
zis*X<_w%)9a@b$4RbsKI`?2oI_G9z??QZ_m__J}hwzY<~Yz%j8zu1*ajBQ8dejISG
z)V-~CZJk@%kId<lKFlg;_|Up{Z-Cn3zY`ZmGyX^_vV7@t{?CbHd$!e<uHAE3IA+N`
z8wtG$Z>0aSI|%5d{yn+&!@A4mbIVF!zu)!Yo$K#;*T3&6`~3QSW!?Ju9F~!L?e^cO
zW%I7w_B-X1%VxL#I^0d!7k082EG^r${lO1i@2wTAaxUu+EdBCt{r|3p|6A%$W#;eS
zF5@L1v8{QZL#6x%>w>=tvg_`PuDQ=T$@f96d&6C;FpraV3_Y?px*P6!cu4a{$lm$o
zP`LWgmFBlILJ#D~E|c41A2pY4hm}NO#${6lDW|E?6H~dr8v0ni-EihILn!-W#(D|g
zZ3n(~Us%W^*1T@*ig)k%kFIro)NJYzb38BBz{l$A38p)<p64vser_FqKt|hsUzu&Z
z-Fw9kaPB#prlg@B*}kfrc@=~Ek4qdrU$;92+Dg9cN?oEoZQ{BJw_RL9r>A=9=y~Xb
zA37Lcsw%cz$a}x(+pVv5`)}Wp=Mf#QlpEW*MfLxq`~2^gDCI7NAg$b$e~MK<oxi&4
zkMOgb6MYZ8vD$QU>IsGLY!Iar-u7p+S=@7J{%tjnUmh@*dtrW!Rp`mf=tl=<Z_?{u
zlKrP%Y4%pV#Y@_BHktjotb5r0h7p*m*cHm-S^Y+Q&2R5ZIvOi|u3K(c(!MN(|LfdD
zpQ-Bv&%E^!4fGdZI4@Q==oXj$ZI6|kJu`pt6}jIs%6O^rvM|H;qPf*~U#%BvC&iYP
zh-mrj);Y0l;`T1-*YQ#ZZ<l^hp8R-YliUAT@q4n3(bn$`BkRhwbd22OPxP<f6;i=`
z=z40;Y6(%l>nk_R&YAqmN`0%So6Z6=&M(!?AFWSFW=_9Qr{Hnd>Kcb%!IC+KLKlu5
z2sKj4SW@elEL<JcbgXPoX7brgk-)Nmvsc`DuhcqJh@M$L;r`#whU;6J)wZ9IxtP6y
zxBH`&9go|TjrX{p|BZdTi~aSEcL&8{(hoeYR<xR^tdzd0VTW((q&3Q$Cth-szjAFU
zukemKMVqY(UncT8D?2=6R$9sE`IygJsyyP-j>D6V%~i;}Bk0+zzAWpn_CuZZRpsti
ze?><(NB#HOarW!AeKQo3j^qj|KY73WlR4+{@T4m{g%<bysjl3bnHKr@c>eO}H99Y6
zg(^>6zb-m1=<p$w$oT%FP*iW-kz0jVMfF^Kc3u{o`L3g*Xt}acYn{J*$^63oxsNXW
z`ryBv=YPU!FttE7E|}wRkojAgmtoe&MK|i_Ni$E|*X*?J{Ni$+otIO3%Jc$O^!1ke
z-rc>-zFWfd&?cUkX?YnYlN{EhOTXH5;>h+J&Q)tNynpAOnclZ?%Zz0`AC^XQ34WPd
zZk!TxWa9HM-ubJ1eq4<YJn61*&pdI-Y&9O?UG7>xuSu-tdoGiptkjgpoYk0lyX9kD
zz#ZmCybe+e&dKuysozdCJoUMkarei7Z}Vn7F1g#bQ8b$?d;7^#d(BVH`F8eTY^>hl
z(`C=rrPuU2Oj+=oqj@@8X;HW6_DHWJgZ;eOy}>5^ha2`EsrtC@$J=nX9Iw6dYZh-~
zj}Dm4*z~^j`aQu9+YUxe=diDcPY{lfW{=x1u;>`mMQerS@#k|K9ST%yeoy`I_EWwA
z|B3x)wtHLu-J2=ru&=N;|NaKPCE2$s64#jPu&qp#jFA5Ka@s@r97!-`b2mw3htT2!
zS7!w#H0S$Ymq@#KEC0i%%sKh~<~RP9{a}x7tKXIS<6ctKJlnU1CbxT-%#PdLQo6AF
z&Fu)0+e!&Wzi(gl7dt&~AM@tTzUQ}`+_;;sRMvChov?R#B4sz1-PxKee0$%L6^dPb
z+itPAJy^b0YC_?iE9{1xOJ1urmRwdz`26OvNowYKxqYpQy^P1r7Tk0D@?=ldl=p`Z
z6ur4u>T!de>BidRUK6gK2g{Fjx4%ETV|ned+HT(mt6qQIcy3pD;q#0uJJZBo%$cw%
zPM7bMtUwC)FTsXaJC@{_+Lt`HkTUMOe7o;(t7GTs=09yW-kEP=Tk`r^gRjZ;_9LYM
ze^@j0+HNjmGmB1s`1tb;u9DX}dpJ|~3v4)cYsx)F-@j5nUY2+sl!@ZaKXlW~KP`W<
z=(D;B7Aqe=eR=u`Ynw~afl&Kx%vFc3w*F6YbY#?>d1tz3m2vJ#)o(n;`$ZkJbr{Zz
z{3_n>uPUXsC2!AzZF?RZ;_kU%J|ku3;gSlW__AYj`eq(E#(i6Dp>(ms#uSb{cQq?Z
z-$cz9YUp^cclohVx|M3y+x-u=?N<mc`gLeq?LkkT^AAs-n{e5%_(nxyF<*89%l-RH
zWB*LL_iO*2rSmV#v+QBIeuJ}pIp2l8I|t6s5__{(s4@5K|F6e?vZl@Z6JYw_?VtF}
zcR}0d{XhNti`D<@`5%kt{(o)t|9a`a^{@ZL{}1`Of8Fc-|Nkyw{{49G-@m{4->*$&
z&Yqu?{^oc7_x<N=&h7B!D|56tHGOaT>eW}%fBb2XR{78HsCG?2_n8$2=DTIhrhIO+
zU;e$L=t2IOo3{0h``_0s^8X%nzvAi1EicuU?)`7VQ}CIEFRid}(wze>A~TmXF{bhE
zJim5w-FM5!(KGDU*uR`U<I?w(eKmz9yR(+tc?K1Kv$u;s%fI_`yZZDW9na#oeSUst
z^ZtgHd;b00{qyFj|Ji+e`M>mf{JVc?`Bkg`{QKiR|KES~yy^e?v;X5i|G)m{zrFtd
z`m<j?pU*$}#eUD;|8MTyHJxW~v*pwOe|4pWTOz&%Gp$ek&l_L$<IlyvbGP29`oXhx
z?XLv=-7ky6P4?+*TD0?O(RQ8EJvMva)VxstaZx|v_3F)=BO{uYyr|wi{m*m1O~1nv
z@6ETLzH7z#`RC7VG*K<t(Q3=^e7#?p{jqX2clP5a_wVxjwEpGs`RelZA0ItV3BPx{
zdH+xUifaG+Q{4W%e!jQYa=y;Fu>A#LA5NWBp26pH^6w_iz-jwZ(offvl^@l9_h0Su
z_LI*~-rgIw?L}Jn-Aa$C7vtBZ*VUZJd~ESky0miR?~nWU`Mmi5|8vRhe0l#eyQc3a
zewjRspY!k0{^xGXd;O$iZ@<`jF?;cGw`+&KtN(3Uw&nNLT7|jhaXBfS@6P^f^^xE8
z*Ef8_&e!$dXWyIqY4h8LPiJO)I4+!V?Be{37tU|%m$p2eKCxNm`^2@s|8_tBCtz{*
zGPi>M?%U@B_}Bs(a_s)PN%QRAIa}nUO8c_8H7{KBm(BIFEAetx7q?ogUs;^@J2B~Z
zl9||MgZ@3aQ`+14t+TDKr%V!i;IzK%>YVq1^1D7<*vem9apIeG#j9Prm%ZQpPH*S8
zh3|9b?s>o4ddd6W?-+M{Tljv?sb{~w+uvc^@$T?BmP==OUpThxWZcJZ{q}cVGIP}d
z(=z6HvUb_m|G%lZ{pfb~mp607Klkka`DV`ZZ$10Jy_sYGHRrXPyk7s~`Bf`^_g8lF
z|CV1WYqLc50{`V@E$(lv_}TaM|G!yw>&w>9ftw$mwYQ0%EttRGu59k{eYG|Qo450y
zpV!;yXny4ZyVSSsjc@dN4)4Ez!2IWR|8kXhd2_4GlG{>yO@7rq-uKI)G>@t7bmaY_
zYuo31)D_?N)cXFXYuopH)y=Ot-Jbt)>)kuf>2DvVB|neOtKh%;&9>y4Tu`#nmd?Bi
z;k(~_ORlNqneo-F-riaFTdgWv*j(EB{-?vUUu@4`wB4+5bK!^Ry|!O&f4>l2z2m0E
zkF{%cPTdatqTOa)mum9ywNhKWxagl<)BlI>d$<1`>;KaAU)EQ5*5A$E?YpA(cftSs
zy3p-TtKYBtIX&j;+6%i%zkJ`hD!Q@s^$X_kQtf$CrJ;9koy*z1D*EG<9jjkm+m?1a
z^lsM*x7g6_+e~k-TeW@LG4~A-UsmPyy<2nf{znkK_Tu*VtNQ|eY*$*PX0cYk^0x2W
z_^;)PtNz;F_6zyFBWZ@#e=e7;`;BM2&ni1#ecRV`;)2@X>jyJ$`@YRTYv2HuG@ad|
z*?afOziWHA1K++s^KJGnzl5H-lCB}YO-$DXN$gsB{!Uxm;@wxz$8aB>Yg_f~#h*#%
ziuKQ@{#-TZ#iIjT58gSDkas&lS|dN#z}{d+ymZcF`O30y+~xV7SN?xcz3Tk@N>^$5
ztY&NF-Tb?6&z-nE?{C)cd)pm(--TOrOl^LdYunquZQfCL=?lKKFJ*Qe7dUp;qPu_F
zyd&<?4d?n_O6*!Lz;@4~tACr^5qD_^dA572e*QgM;GUj*Em7_5oeL?v+pOJ<*tS_q
zZ(^-1@hi$TuxF}NdA)o4tzEV6`47BaP?elv-7DLhmu3Ct*gmOf>Dzb9uJrPneXDq5
z_FuQWQoHV+*SBqNKAD}7x%)JcNn>%|;Ztl$a`&F@6MUkQ$0FICR+)A=h1vhpk!2^@
z<|R)u^xgJ&rJ&0%+2`M0Ubtf?JL~rH!^PFVpNOAX$9?*k&%+mC&70qv<ei%#eR$1M
zr>}>v@_#lzZ<e!5y7*7wl7;3s3POc`f3)6sh4p9Jt?DN`Cr?(_O7gw!ern#~#arG!
z{jvAUZ{KN;Za(~3wDs451&{XaKRDassqfy4t$gC&ezDEJIOY7CHV3cw4ndXEtt~5;
za{Dbj_Rv_b@kXTkj3|AZna4yV77DVeWH?2qwx-Lp?)j0qFZaW?s{Hc@Pu}&JeEwLy
zk>cfyqQ~7&I{p{jwcqn^WA0s%{J-m#FD>Lq?5`}_b=>dYry`wd=J|1J^ydBi{%=Q3
z-6<KXPdR({vx>gIv}W0v9Pj1d-utQh^Vhx*`FF2qiSma2-n4Cr({nvig{O09RqomI
zqd#}oqHR;&w28ea*m-MjMEJcmV$0tiZZO?)c$S?rdvtkwMyOENB&&5yYtP&_`xX<r
zP3P@>cRgSAYtggLE#1DQ;l`H3w|q)Al)878DZYIZn}7G^v0cI0ne}ozP3A`AXIf3a
zcZo^rI$yT&#e>(%7Hytz?_kNbw`SMgvQ7W?Ch6x{dHFY8>mPl3`tfA>x;uNs`xo0W
zf6?kTv$=6Exp9|EbnO1CU!!aHU;Q4v`P{4*j{81pUVj;vQ`42$B6Ye~zf@}VSN^Ng
z@}F|wr#-fw>oz^FX2tDS*Y-cDir%1aK5h1<y5RIfdhg9k?E`b>?KUticp-keU6$>^
zN49|X<$N`~c0W$Yvq$7=E@(KYn^ksu_FR+SZ_my<{lkuL!JcdLwlB`l*1L6ayXo|~
z7ynNCwoA4)y7+S6zO^@(+Wh(Vt@ZQGH~DjCoL*A+dWYp_`-sm~-wyvVsVv-Q;~5u!
zPOnd#eX;;|alurZIGKI3=E|$qFEW^RbE-w^V*g9q|MxMJum1hyJcs;V_5Y0iHSbUE
zKREeK7=OM>i}3#3h0ing?W(ZYZ4tlcF2mxhKOb&4@VD4zdaW}v?f3KBS5<a4{r|h=
z(G*LSiF+%#SMP56|JNi?khkj4;q4zj<bHoBYO~`PXWaizZ?5|bZk(1r8GicnlTRgu
z3x#K@)bDIry7t)z`xxyzeJr~k+|U2mc<%e{di9+Xj(P0zS3mjZ(Fe8dHEr{wzMeZR
z%)jGy<wLjn6CbY6x7Mw{*59e9X!6H>`Q`dAasRjbo!;*$w4hg1LA+`9<?4UWKm1vK
z@AH3-IcH{Xzx(`u+xh#CxbxSU&5OVIdA`}a|1QjXYj+zeO1*e{^;oggi?{yL=PMVi
zUfnBtfjitj*XBRx{QqArA3If`AhD8p^#{gZC#?AGeaqHw=sDnTFSs?X{_*)A$D-eS
zc(y$E?SIF&_6H5}*O}S<O#iFGV{q5#!2GYw(!o`~%YIM!w`P9J-UiLRcYi#oZ}AUm
zU;UNwpR;|XYjNG~wSVo~mY0;a?kU@JEOJlWoTM#h@1)G}+qKO9h*|f^_>5or)1L3{
z)_;(tS2zD)z1`m_#wiaU?|%SBFCOoIXTY~W(BSi>caMU%e_wxd?YrXh=l|aNyg%Uo
z{+uuWyPrS5`)@<j(eL;Fwr+d$WcPlC-iU@5Ec+QPBPP7i_OGpYWpefQ`KJBy=fw3z
z8|!N;jqKxP&h<?`{`v6Hn>DQ)Tgx?fsd(OY=qonvbGEYmmsVeH*7$e!9|OyK-f?w?
zk9XeliaWU8zUKd3!#`T*_f=TN-n~)#_2p@4@y(}gYkc0u@A)Mnw|~yQN5?A`h*zz!
zdHc<vJ|-?MN9MVp{TrK^xiSU(FXQK&4_~h)zW$l`X3m=8BE!hJK4Fu?Cr_VzIQrAE
zmp?x(`hMwPxsTT2=K0s;|D1?_YiqrT{lk;v2e$o@sOXUYy{WgPXyIi3xx40k@3(#H
zv--@-!UrGzv)?fZZu^n(_Wk^-#d05B8$XO%SpNV0{Hnw9A6U{3#X7zJci+DBh{B7$
z*(YNd{MQzr@7hv)(Wx@DxAnvS%3p=EGxAD5vG#HNulvQy_`K(PcK+Xq@zqzVreCnF
zW^DPS^79e*xkq2GvoP}rY*Mp7l>H*7Pr%f&$=;=Q!w%K0c23V+WRe-TE8R}cXzKha
zy?XNbvdz+xd)yrZZ%w%OYX9%+bNdaHPA|Ps^0+2f@#HyolW)@{pXojcv)Q@VKfdmx
z>+|z@t6y&qk_%UOVWe^Xf$}UNzPtY)O*ip=^*=l<JMQ3}f(b7LH(rr{S@d&n_y^59
zR)4v#{dbjkvpM|Ie4~UKk!imL@0!l=D13Z1{cY05hujQ*&!^<P+WK8HbJK&5%fEc*
zt@GMjDD`D|TBGxdS#ftR`Tsq$U*^&Rn={MB&GiH%_U+hFSiybc#%cYq`4=CwS9dJd
z%R7;i!m~@{vi_uSrjPS4t#^NWdGUuS@h|d?>=LKU@cVPb*QSQ$|3ATh$Nm>T%x|wR
z{rBw;Th_l!kv&H9>%5$`Ui{r7%&5@xv7BB0e*V|k4<E&T{7C%p@jZ{-zqtpF|Br3#
zzt3e?r~TuH?}v}K4;;^Bl;6*0SI1jZ!&0O3qmb=Sj?#?4507<z6c+v{T>S9(Ug1AG
z_G|wrwEa;S{qQ*N;eP3s`CHiS^LXp-Nd4I%_~G#Wf?3z~Ic_jV7j9@>{@|RSRr!vt
zW?dcD@^6=R9uASoDG-s(@|t{U!I`T^FaG&cGpWWW=JE5BM~i08Ipeo}($S-Hg!c)p
z{{26#{d6<ygy%P3a#>8Aobo-s|65+rj;BpCdmX-&-zxF5o%j9QzrFnDzD;8I-1zfe
z@U=x9IfjvY=INYMt4~gw;kT|g>hHuKMvpkocc|L@{;T;<yyDOj^)%U<?H0*u!vBu`
z*Hn<<HT|Q)%b1}OoqM{k@3C9!`ziYmg=8+X39S0|i~GmnyHR_N9bf;ku$^`3%Dr+)
zPUUt=Z^R`ovXryRv80(;K4RyY`Qf#cz15Lv+cs@BTCv>R@34xGS?TYICE>F!1PMp2
zUh^O|K2Du$^G0U*lP)t)XnYg-#CW%3PRYMJ*It+Izn-mV<tbz*Qjnxzn=SnE!aRrC
zDgPXPf9XhkxwtI5T4jZQW61@F<|$kc_Z?tXbG-XlAnD3Yu{YOVZt~uu={M`i)x=j{
zE}pkqdRV{e)D*dim+X92f6-Tr+<SdOMeAE7DYb46|DVr%qpe)~<Gy=LkGu2o*5a>m
zv)NZ&=(L)-|4&_E8F#3W!g1Ckf5csiJKize{Ws@JyyA)0?Q!{gT;KET{W|NO)!lzW
z53cUdsnopt=~zGW<ktc*Nh)=6$IObZO2`Xs4Y3IIsSud=C13&1FU5>!XBB2>yE%O;
z(k)haHP__n>HAi^x9s1ZzxJoTTu=PCyE*^)b9QIU-~6eUv^it`sb2hQ>A(H=A3eAF
zf4}tK{?~u%umAl2uk!Q%*ysQMNiSiNIrpr+zfYX~_4x+b+MN@>@)v*H%5ReW@p#Im
zJ^!0B874JadYoWCaarYg!*cQEpG6<!EHHL(Wk{);Ggm*YppU^NBg*eXuFD?v&yoQh
ztRGf2l=Dyjz`3d4Zr|S*|Kx@0H!uEpQ2n3f9V?>=O-ruY-Ml%`=dQYU%lv)YPri*-
z@%yfG-gfE<ud6Ed_qmwQ@-;TC?KiHQvd;F;2MLek#Zm>+|IMy3N`8Cc%`%H~5B2@(
zU%tALW*&YpO>_V5bMIfr#x7s|x}<b=Z0+*Z?@PYEj?GuUZQOJ*Xx`_x_EO&`ER+2C
zs=SXp^89m~_s7$3x|xLwkFMSN<H93r-Mz94zlFYjaO<7_?MJ(G_uYQ9|9$?fEj!+2
zth1i=y6@Sp#XH|+?6aQrzVF%Y#XrH!A6%#IT|RtUdUpTzXO?jywheJTPSsrMxe-h<
zk5Br3y-<CEy{;&@_LJPFmGkeU=<hjr-cVwF?OOh;{LwSo;_VKnme^??zgPLjx<SAH
zy50Sx{<V{Ltd6?*&!#E(<nCWn7|!vZldG`#^Lxs(9Y6lD{rf!qz5Q*wK&7ZEjVdmF
z>sJpq@7wmH^#A$KXDyn&Uwu^m`@Ofyh~d+ee8J~jcfRwSl>ArMX#Mq*1gBb?cC6o|
z>j!v?&oKV^tGwa<!~9OxN@GvG$h(}+6~*@*u+Zq-Sg~3Bl}7Mq@u>2(p*)9MzD*Q(
zaeZ?5=Fm@<|I~OE?><>`B#Up&;lNEc_Ds9_KC|Dd^kQn}`IuJ8`Gh&5=jX>qEEz_h
zBu;$4d`K^R`sQSt&67_jJD99~+M>dpljR<f*l2m9^Yc^26LTDz8#vB(vYeez&K}0-
z#>&@l>|y5GjQ`h;S+;b}UA$lUlE%F6CAIfnTmRb~%Cv^HOGHO<4X>)doYtlLwvRP>
zuKzi2IkUw++qQ3tnuGoEzcSy8rT^~v^7+pBVtf6+R=YRXDkd(OcH_d6ypptv#l~l)
zO|D1(y&m)3^m^sl(zs&j^*`Tb@B2LK{hnvP*YA99ZC$*0v#q&R^_HKe*Xz!f?t5kx
zUmU&f+5Y!$-uIqUyZ_?NmOaPvzs9Hi|D!keg^$M7V-9Pq^2?-K)gJU`{r*tCcFT_<
zKc_tL8$J%nKMWJsyfxy8V~U;oo<HVeij`~T?EIUvExqoac;9$n-HYty{Phj#d2h_j
zD|kPhU(Tpz&nxgVle>SuWqtN?{=V6ZcNlbWgNWC?kIdW)=LW_|9BmD}^Gri=U0Sl9
z-I=59JAW96@3))&H83V!MBJ?~QDnPi*L|6z<!&DnMdaN+M!Vl^dFfao*N{57Xx)^O
zdkmL$*6;JkW9W-5tUDY0!0O}rdC7{*54(^4e8sfj-H(bsoj)H99jEi0j9T*a;L)7I
zU5+L{|6b+XV;sLQ>4nLKbq)9OzrFIj$M);Wrjr)DRn9uIOadic<Vq_9Vx1CPXLPMA
z<mYd^IYT8S?2x5`e9`AKzSrb_^y=Nbx7IH)RwlJMZS#C)|8rZ@ZU$^N{*rn9fmNQu
zp0dKblY1Y$FR8KL760G%>#Y~7@BfY5$^9p6x4iVTiJE^loK4RDy#MSuf5z2+yeHW-
z%JMwl#uUfGQD<?X-mooW{|051Vn>Feb2d!3Qp^~c9bP{*vYa9NPvH*J!b3-QKH7RN
zV1?Y9O+2rQXD7T~$)`BKlC^u+B}ct!2Y${;xP0)@qnfh1sR3R;W?Nr-Xz`J8>%t9>
zefKh2bpG>nK6R0E?eCqB7hXJdeDikQcDvUbcCgRA&%b+~NOp~WlwbOG76ZOX`jff0
zEt7k(`S7=!3+=44<_GGmwU`(qurKrZHjBRtihuu|w)1b@={t4yHs(%E4leVx8ILb^
z%qzNj?#qOfhKVmeOfY<>xcJrKefk>&a{h=-$UM-fzWHjFNFUeaosOk_(R)g=_ued@
z{nxGdT5g!y*MOAg#+|S1Cp$dd{Kk51Z;gi2mzhVt&G-CbR8qLG`?_A-u8NmUaXy|5
zx8F^i_ic_^nXy3qp=;Zuf87-4WVAoK=<ngz@_Q%eEWLJiGtWwvV>0RKv;6Puy7#g(
z{HU-^?V}$z=3Cf(S6{dMY~>^7=C4QCi~b&|-~R00za#8ouR8f_E(rg>JFES-u>6hL
z>UJMA{Qs2O>R!5Uc;I8*O@ZUpnawiqKP#L$dECj&=E*YI?89FU-*x)@saVZYx5V%E
zu9Qov*{Yigl0HeQ&o4YYzwpz{gL*SdPDahtnzO0q*y;2?AJX^Kq;2q4i`^8)#=T(2
zw#;K$mwsej(p~Mjd$s3dFxtN6SgHNvNAn9mp5O5={hr{)gLiFW_dWbA8E}m&TCQv(
z>wl}K+QrTK=hAx^<jVqC{#!lGE^gNMfARc!;E^fo&++baSQyX#d&%31m&YpdWPg|J
z+if;4|M=&<A8YDuPTsq8N`LK_ORsuw>u4{$=d?USJ;~bP$MTapmT_xN%(?ndH2vhO
zHx-4BOdsC7bz+$;nPca1cF7m7Y0E|4cTdZH*Enq>tK{Y1ca#M>Qj0#O&D>)XA2)Ap
z0JB%~9u_;n_6p}U+Qo}cMXs47t|4_Y!lG_db!FElt3P(uZl{07JJdDxzrB0JP)>OM
zrbYJ{EZKVw2-XQrToUoF%GA2fu`&51pY8;QobrZ!Yc0=|{aj~y$=y_Rj#r?qZPt6n
zqk507>pfFX&s9;}J7a<UGls@SQ91qT=^td<{&t_AeA+l=b2-1>Nmqr$+u}K|<o;Bd
z)OTNQoO*ehdY+I)@sm5r>-BD#@7=TFy*fw0-v2+({lE9=f8M=4o&Vd)&FT{J9;RRX
z%d~6bJYOr8kN}})y-m;Ws@dO}^0g#J;?Zf&%mwFt?p1Z~30Ssn&557;eCz(R&eQ&<
z+oT#Nc+dWyH2+%F3rcRM;(z_Q@KuWM<-d=ao6qlees23GcejD`zL$ZrrCW{&JKbER
z-@ZtW;h?!kME7Iun4_Oc^wu91*IyTsa@Y07A0}nv|F8E8{ZxK%-L@^}?{DM#UvunB
zq;CAb`Y37Y9H0F*HCrw0ZrL(8O6Hr!n^$ctetdCaSKx8h`_^wZIKTS-^Cio2k+`P+
z^_)y9MKKLteub>EKAVC<E+tKr4H8_v>PbyqMddyw8@AW#yWe#g@cMp|agg1)<J=s}
zv?*40&%-Slemwk?Q8(v~#lzqA1*iVEt;|oZesANQC$qqGmGPflH<PE$(LcJsL-&;J
zB5@z5?_Z`*c$#!{nUX_wj^^z1eyVp_6V63TPkZW;o7r*1#kASos$QA*{>wX@vTI*&
zyft0zr26g+3QTu5{CfXgO*ZQco1anA!TQV{``+#-z3l$RqUF}4(#tw`<9|xOo7^%{
z{(PeJ{@?p9ALG7}mc85h;rjpiJA<7+oxOWfeRlSok{`UP6FXg;-`{H%o~crP_~$&?
z^A}WKznybN`@2BwCL_szOgUU1_Bg#z|Ho3!m{MtR<mg2fQ$DS%#nTLb8bwZA`DFc#
zL)EIc1o~7|Rj<ZBl{5>|&wLWd@bRCVTce)MIi|^V3;#La`!sjrA?Y8n603i+o$+b=
zo_*ggYyQ@$?Q;H?PVVL0b3kn8x#ITo;_hGe_@)%`R|@=j(p!CEx&wPk!4J(pdj1RN
z#uq=_TC$gU@3eLN$JYP6mwo48>Aq`x&%R_^FPfH`du?v|j|U0AR3GgA`_!(8z5iiY
z4&w|{KGE%F38n|uuXEqa7=0i)Ve7Na;y;duOyFL~SLT>_>vq<g2)X8&CDnBkeaa8Z
zG+Zw`<Wqjm+~?8hvz7`wr+Z2mKd`;=Dfb4e%-;vcMJI3g_TGR0hqYFpK3py0ocywQ
z!kRLkevZi>rGtFCXLvNM+MD}B*Yn!h-#@<JYMrjVf8m@(>mI+enV2yrDnV+-_M?hc
zT;Wq(Gj#vBtYqfzwNcx1@1ef$hnYDOr*Hf7!6qYbZfDK~d$SFkKPM-@nP|PBFm}>a
z>qnl`pL`WRk{NhE)u83v$!SYV4{rb8TjtMTwY~P=^J#{TTEEWz7vIFUF!F!KzNXFg
zN%J0FO{(jAw>x}_a+l9NhSL0L&yTxb{`}MM_Vt&cy&(~b&dhVz8~krC&b>SFij(?g
z`Df>M-Y$N-ZEpLGx;5FFrz%tw|FC?&QS$ue=fC#$yQbGnvZ?#jQg_$xM#}4q-_K3N
zoWDGqaR1KE&+nY|tex|!bA5mQ`SHd;ga76A2Ic=t`3?9P#NWRA`a$Gf!Rdo*=W;ZE
zx#ny!Q=-AP=J+pt+q&n*3w&SmZ>s;dZ}<M(4NJGa-}7_(z3gzi(*Hca7cmJpUd`g$
zF>|}d%O;UfPsRmvPt?ZzzLuO=B=>He?fe7Q9=2=tI`*sWV3Dpiym<Rmb28tjM!kOZ
z-+yKb&NlzBb!lC$<&UjTzpdXW8nbkn@R1_hn&am4mu_;o!RWFy@6yHH2HB140*v?F
zI(e{v$9rA&gU_PnJZ(y%Z@Jmrw0i3K@_%Z}yj33rR8CGmahfrD-vxnwQR}zsCN}ua
zxj*@0h|+CwUq9)-GYS{Q*4=%+p8w9ll23Bt8Jqs!yS}ux^g~+C;-&SkC6>INzyI#}
zYd`G&JpQLysUmm3=4<!<#N+=h=cm=_{###?S|$7cd-R`}<Nsq(QS1EsI{)53{`=Y0
zzT^ElW3C6*HuKhoc?wuK+_+)6+r}bJrf%J>QZb%}iuf~@ySGLa-weBGdiPG$@86a(
z$3GR+xxAm~y8O2DmpOCotN*^VHn0v#>pVJfNq_PZe(@D2Qkl&X>V#$sm?qaR@)Jp~
zVEkK_G3`g8*s&MIE2fLT`!l)uz2E-*SFL<5n7x_w<>URm`%_nyKhqaq{%6DPkO}Kw
z?Tt>^Ycc<_(S?rwl>EyL<=GtPs_b+8)VNBFjz=>%>ztobw@&O>YlM7yS)JYPsENO`
ztamO>+2-Z<yjWqvrY*PK-8Z~^z122vPVTh6U5$3frO$6Ft!1CN;zm&8{(IK8uiog{
zRa)3r?wYlC&gHOqYvLCD?Y^?^P2PdyRYvxVW-L{A?>zf`DOP>wr$gDFMa$IfBR{=z
zJuA`ESJwRZxc~doW}Ej+2jdksf6mxuk-wL(@6Or}tKYk}KB{`Tbg|_I-|5H24K$}-
zc-Y6XSfu$&G0VZP)feriocXn0|M~Oq^ZH`ypP#S(`Oxd>o9$CXdyiz@<81eS6#v)E
za@TX7jq+ETK0P&#NPOP4*7T0jvQ3*M3l{v5k@7JAo$~Q=O}(aghu)HH3=cL~Uh-AB
zZKO3N)oAb8S21gPpTAW*^fy+fZSJ36pProCTzhBJ-E({2zSY0|dWU|)him8F9t+OD
z`76Kh_4mZ*^A8*=kB_vUyx>JuV~yfHpRcb4qh@?4Q+;#LS&zA8_6q4g)pqQ0zdVjP
zlvS|Z(XVwqB;@yy*X*R+%5dIi58YNo&%4ia{DWwX{Q2~+3~cwN_O=;jYCKt;XnpwJ
zM>S^q+p)LuEWSKBt#bGETe;pn`${(%y)FBH;$q?d3oqSb_x*nOdv-;smF?cElh@3%
z?{>`E{f;es*^fV)yPtmiGsnPsk<qOUH~SsJ(kmv3sBo<Rn)gcnN$Ad1_0P?>_A<_u
zw`bo|x>|gTopr>?!|#Ic&e@kPvXkTcJ-g4JB4h5o7QOQ{+DGcY;JZ6@{wCaCWY?d)
zIjO*|hGjv*#wycv$9E}(yDWCvaMs?gKK{|6z(^_iR4BKW_opM)5xV_>yITLYh4W3D
zp7CSSS*zLddT}}dQOowre`FC*vh+Q8@p(48;l;D>=e0YfmH&OHlezuc%h$@+-&Q|k
ztNIzYzTl|U^rZOp7wwO&J)p17`MLJ_`HQ_TD;-$2PpV65k7M4p_kXD8ukxqzPnO-O
zzsOj?<aN)y?EfuS{XKijrk`lrFzdDIBgK$|&f#x(t@`&l{`LIdrW<ykx3)PkFkfti
z(xY(me6@D9k3JV{nRNdaw8zKD-TyN?mVMsqgF<DD-%?uFe4HI#9CP}@zO60l4}?`W
zT*;QVYK^}7_W{ENuB*wyhweuiSN{DR{U_(@|H&c$9_~wg{r|F#|J_;t?9cDrf9?N&
zG5hPk{%8OFzxCh$sQ>@Zul~P3?APb>>(_s&FXWn}(OuR5-u{2^iTT&<UM~M$-8Xxm
z#k|R`4lJ$-zQ63+)1?!SJ1)IochbtM?dZj|*=FW{cs|x^{HW28GdT4BY2?mx|3&wm
zSpO3=elzR;ZrB;%^Sl1<F8lH0_NTf6;cw<Y?JKiBG-MPdUP~$G|92y^InVNsd#!;>
ze$SFeXE#lM(9qO=dkLd;?9&ei|2#Td<CivF*h}BR@pw<Ov)s9J39GxGS|)w`e6;+_
z!T0;EqZm#obpHCc%;$ZbJ^%6>$zrSbKj3!Y%J_19%H+h?TybC27_YqK`7FPn_|MrV
z{-@208|HVaFukr}$vFA*<C`_I^Mj%ePv=k5Uh}4#?G($2ix)q&yqWhy_NUTJ*K1;3
zTt)Y?EhLL--@h~X61!mihc08|HOu9W#<u_V4B=%zD6%TQP}Jo*bN9Z*?Agl~^O`67
zF5Gu%$KtKegT!**&$=)F<K~0^{m;}-Urm?)B7NdXc&Oo#|Bw4W{11KlN#yJPOtwGu
zA05*TKYaE-_n&{x|5rJMU2GfqnK<6p{d471dieF{e>VG#pX)7tGj@F0xYhXL{Ek2G
z=S27aUtts;a~iZ7<G-KWA-;^L^H*&uD}8JZpH3FYIH^2Yc$1E*&HHjL$^Ex)?yNTd
zsZ{y%<#KE5`kD_iE;HP>J2L!GntAX4o1)TxGYbmmCq8ceUB2Zbqp6%epWWsA|L^WR
zu4+4Ro&SdWALZq3mi|9f|F8DnH>UrVJCFR=`(S_WV13~vYislQHh*8O{{6r1{mJK?
z*K}T=dHpV&KkxrX&!)qBeU{y?m~qSZ&;7IKAN-$s`j7qYw{O0e$^B`(e{kl#BmV>A
zXT+pD<NxO%ynN>2*rxyUKAiYbp?~w{&u8cUH>Y{++-R{^^PigebnD;S<^O-YXP3(N
zptqIvpjMuq{r#UW{=d1mclY!^^Y?$Us`Fdce)9j%zvs^Vzxj0fH@kNK2Ro`4zSb+h
zd$}!Tmyc8V58r9W_g}hFR(4L`-#*{^VZbkKQI5uAbNkQvPkPz?<XC-s;cdtAC(rYF
zPhPiw|5^C(f1YLg*N7yr{GXm0w(jwNrPAv^{%`-W6MQ)S`mg)1|GJ<3_x;v?-`}rz
zaR20+N1^-g+?SWHX?s&=A2ng8a0qX?c3Fav$j6YnvU?Y~UKwwHI+OqD+Ie$}{qCms
zZRWE7JSqS8P0Qz3YoA%XeQ&H^SuuZZ@voifeV@PEeZKvwBg1nwzmf6xzr4S=>UuYc
zl&e2Jl#+Mh$<AP{^=r;rOfBCzd2+Z}di^dN`<b%(b+g)8TPjaBE9*U<P%|yy?vHd6
zljrR9Zp_8EUZ<PrpXKnC&GWd+`0C=nhhO<;aJ#;!{b$MkN_HPpm;1qa=L5|TZvOGg
zPGF_9zCrlw?x#2Zl$dYvx3hb`NoqzXmvzm=n!jHTGJDw{m3q20OIp5o+U(sGd@|3!
zSpF%jtSR|r?Z9DB_G$g<|2BUsE}e7uwB+o4J-xE!exIi)PTpWOXYRg+^?r8$t}pIa
zpFhXzl+-B^?VDCFvwuJDe($Fmxx8vs#<~Yfrt4HxFMII$=Nk{v_aSexRZ~r^ge~eO
zy8QcIs9%3mJ>&L)JG(UJTw3yb`Ro5L_uv0F@AdxYzuxaW_`T-8?fv@m#vfjs+N#3o
ztYI%UVF}AQ_D6pXM@~wc{Nd+^=v~*h$+s-8+Z?-YgN^;%GivO&uH56#<@J>MC~$HE
z^Kt<uuK08Q&!0>5aQnQzX*fZj=fq*NpT8|xU(`<AWApFvACcr&VY}yi`}p+Z_0Q%a
zDc9dx{(Rj0ynKJ<4-UP?FN-=7t~k80-&g<pwY}Yr?=Hn#+zxWuIj%n0SNCQ;+w6Ia
zIcM*e%{ufgC%f2fHox_kPe1OxytvLsrtYf5p(Vv%|3^2KNIoqoKC<no?vmH?=hE|+
zJU;z+w?nu2w(R`Z))Hwx;{2b(UjAnOy<?+7je5?pfYrv)wY!;jSMT>tTQ=iQeL-ba
zRjF{|lfU~DPyJu&&mF$@^#9Olv7qvx|9j>>W8eH~>k3^b?o!!1^Lc3K;xF^=mFTVB
zvGc@ho&2n<Z<&YB+MRw8{wDB=FC%lso4~3U&dHV2uRZ1K4G@)!xM0+H|MH!1(QVU8
zpRU|kxb9@4PtKXF=@(a*PCoe{G%DPbukWqF#W{9-`wxU?d|8uoX_-fc+_|ZL3a9T}
zwCLKd+Pw|!7JELsI(svBtj>6P<3;h0sbUku)~(3Q$vIn*ni=@qa&L^d>ef_Wt<`>?
z=iIuqY~7EoYYO%(&Wx*g^XSvAH5KNkHcd19yyoMs=zY(=9@~D~YQ5|aRo~BB4ygA&
zpX*n<v3Yja_g?#H(`H_NZ|2*U|1{Js|KLW`EuKqPOWl3E=j17!<?o+VPP^Rp)b~||
z_-dxIDQ>50=1u&T?zQ`c5fguSWu>Jy*B^zg)zhb1&QExzt*;O;bwkgT{v(zZ{Z>1=
zzBF;>SBIMVy2@TUW`1X($5(~bm&8TiFqVEOeO3@0H2tY6qvx~NQP<)^d|i!QWTpmb
z`z@IeW+DA%$KilzgPxyiU;E1UtjG#)m0k7f(!+lTUotot9eC<GmvNr5g+7-><h@p-
z^&ERLt$c&0*K}U^DjI!x4NrB5Y3bVe8ndm+H~H=>W1U;Y+P=CVkTHUDMfy6wuPuo$
zP46$+bZz!CMwcbB*C#v{FzH@%;_HIgc~`e|tvQi!JhO+%&t>7|<@=^pK4U#KqlvdB
z((KaFO1sH2tf7D1rasL)Db7$fW7`D1*wBw!iSsI*Cvac)e_(&M(dL7a>>FkC<)M-d
zXP0VlDsz4G^}N9UprKsooo}d8!)~^9Mhn|^t&tRaxahz`o>)n%YrEDxy^^q8nsv`2
zmI+UTPs_}e^08XYl9!mydFpY2qw^Hr2DW(l9fd_&mJWFq5&XY3#pU?=^n@I27W?-X
zxbB`Cy6;%=qF(kD7ytGh=4B{7$KA{wbG1l;qvOuJU2b~f3l_!%>fFh4JG3Lw^;z*j
z=hR;J*^JYi?`%69a3-Bee3?*7*lxAQY2nPL9xH2qo+LK?x$4<EiP;AaKJTp&>~NKJ
zTdTC9Z=G?%^ErNN1(uxOap>YSCY6I_$=PfX{N__U{2ykRCj>u`&0&2L%VsnAY0a!m
z-YtFNldo^__C2P-a<1*+dFG#srXDybkadc?jyX>B3e*0uZ=cvNZnac66vy{kn`8gf
zO0Db5GdA@YD6U&6qBE7rknin0!9>0ZPn@g|u)g;T+-)Qt!Jrd-;R-|EtC$TDuFpHG
zXN#6xyI`BZ&(F|ye45gCh2D<2Mp-%!6D0BvFkaf-(VUsTSu1%C<BR2!yaU8t^%!`>
zCo#%sn8gMyQRcZ7I*W6k_tdhV%T^Sqf0oi?-pZ(?S+Q0wPr8rKV^>+vlLuZNvkjDg
zWL;i9vrCJy{!rrSu!E)HUVPyvPv(g?Y&(=0Qj=%nHBWORyV98-ta{mM-<ivG&R1qU
zP}5reLn!X{LDMTOcYnT1-#RJGVKVEazn2(WgcFM|1n1l32nRot={usiYkfiT%Pi&#
znx7o9W}f~NbM`u`e*L*<{uhR;S$1AMa?oH|)9J%IIP)3}oE!XKlyvV=5fQO&63P?|
zX1e}hoAK2)-Tc7SU#%3_7M3uCspcElh&ZuJ?3{4X_QM2=gNHtbXWZ_5EHLMVaZT^G
zy({;0&-Y5X&K`JFz^voWj~9xEmS)Z=%2>DN#VQk@giS(x-Z!ppc{ID}g;Ig)M&X<X
z?+Q03f8leVApY#5!Bf|DQ4{i6O}e&mKjC?187w)iVy0H;C2p5#>n`$b4x71Y>V`ah
zX}*ZqC6lBq1g#PmteQ6=gX_*0jfol$qy;PsIBRx!IB*2-R0{Cn*GYBz<9q7K(j#j%
zS#~noe5myieb?|zL!G;)EY`4`S!IqJ+q4~uA#BmkCPA|zCw=Y>p22n{IK}9#h(kfU
zV8f$HJgy=$&6uPG3nh-fE@U~$yuu+;xU)T0?al0_JIXo^F9q|Ne>`tuE?`;sLE+wY
zosSH+SUDcwZPAWi&cvti)3BKLxl4w;#CIotp&zqi!rsi?BBtXMrm;_ufw6<*8{3Ap
zPhDS}pCR1fv~AUiLt&vcEe=@{5f53kT=(qQRHg0|mus0-F#E^6r#c#!_pS_#SUR`i
z?!v?E%7wiLYzjg;3}#-;RTZ>|Z_s=7peR)=_ATqD2Hx}C3SO3b#E+y;Uw1BrC1HAz
z9HW_axJ09_moxhTUM(L+-!m!GcFLsBaqlRQ*znZkt<d?f9r_vTFE<3g+9Yy`^G}*@
zh~zho2hT30`vsb>nKPZ?_oLEY<sFX}eXG>&7wz33-7uZoRbiWlS?`IGmglRtOqt74
z;}pVD!Jkx?ByvPSP%trV!d$bRX_nH*^p>9X`0{A7CfD8Y9eI8#f)>ro!sadWTzz0e
z#D#+%tFk1-#aGM;Y-4GdRACu^tyE2bCns3Y!1{rNRjtBt$?i{<pQfJLYaOo{xBcjY
zO&XGw!ft1>Zz-`)2^96)(71JrvY>A$^JNjomR9dD?o&>QQ`5NvCOu1BoFK&0z;LoP
zhta#?<6O5nTuWlNGfsO}x$E3j)A=enP1+^XRx)@6D=cfP<+AR0w?%b5i^hVY7afJ1
z-%U%ey<j{L7*Z(2yvh1i7RR%qCyQAPM3sMUnpm1%(cP-g_Qx*his_C`9Xt#wK_bi>
z9<HpBTz}c><UIkwMIN@r2X=Ebu8#EjP~f1~_TKm9p*xzz@&e3E>qSMTD<~TJ^M9|~
zD`=3jBT1oO`2~Zr(y29vwpQr2&V3TeygTZ37UNCB%7ino7cR`QG<&G<AZwS~OW_Bi
zO4sEgeRo<-jrl8*Dl=(rqodMAf$$^O<=&Z?ikcQwpV2lxV(Fm1)quf6sbcL1{e=-J
zI#d3#Y-^~TP~cq@u}@Dm`GDiITSsSz1&bX$e|S>Gwhw{(nm6oR<9&wFI6!!j*Ugxa
z(oa{NXL%gH78z>V)mjthrkWmY;TEN~r=&CLL&M~Nw@Vg9HAaQ_N55q9X35|-4Y%vN
zUQxO7!cq~@l_s5AbhKxxyzxG_HudNn-8W9L9Z8FvKBVRFFIrS^eC5imW}0&y&vJZa
z+^_nZ|9ID_1B+Nz3g+vsS{E^&dqw<;>_F>9X4WbXLqZcCME+`4+j-S4R95o@_c}of
zv3)`XttN*SPS@FYV5e8|!Ur?V)+ObMRXWLSFDS4(qiw=!Y`Z2mIc~eo6z$>$tKwsG
z8a0`|OiF7N3O3u6;_GIk=DlWL&?<%+$6Fk1Ex!W_idP*H(wX<YWdd8yBfgC(l}q0$
zxU+1U$n~D#cjPmz+^MC0pV=jsq{^OJB(jOeDMD)svxd*H&*k@6JI@)f)A2Ao+qGei
z$d4r*pO;+EjcDpTz_Gye{m*;W*PIx5m(K3sSvjLO==qG}uBi(qJ8t&5!DBJa%^<eX
z{!`Ie8xDqseKAub&)&Ll=6Y4g2S@#mMI8*{_r9N--SI7C<-t==4V&HF9MUE~QOasR
zd(iE`=~LwqI@y8Ze#hDL79>U;U&T4W)M)GGowHstPCmJ8g7TRU>rP(Phz(@n(8>}r
zNPJ|O%;3I6wruK!B%eKN93q-Eg##G&hYQ_Z6(pLTuqZUaN`jZc`RFq3?o5TOXN@cK
z7si!pH=J#DcqV<|n$m=cC61Hav@Y?TP+aN|cu*+yU67yyPlJ4Md{<f4f!kqPtUo7}
zc^FLfk38|!cjYR3iG?9?<x?!#cPN_LG4yiBGAwzL(7j17<ONIERo36KG72vhCcYQu
z+p4ssKkR|ds(C7}<}2BsUolNboMB(-vaWZz<<%G1OxV0#`C4_(92A*k>i1>lfgRl|
zt@Cu)4{2m|noM_YP2EwTBA9G-sC9<Y>je=l%+7b>`kjt&Xy<UPZTaiGLZ|s8s{zmI
z63)E`RYc6i_V8EKGUkM|Xs1qO-J{0-`1UuY^wr|;W7YnwULEL=zLR$X|3ZTU+14p$
zAGdzsaB#@X^$pczX6*2aYjzcy>?*_1Y|VA$k6zC9^nXmZO429#h}_|^iBg-R62zDq
zCtGvi<t`)DMumc~uN=lZmad$CZ0g@Li%eVV7C0>4az?OaUD&2IQmy<93|r$4Rz<{j
z$Hbj_D|uq$8vB;slP{KC%VJ~y#&vS<iNZ6f0+T+iYG7LP#`P<6w2K#KM&_5Y15ZMJ
zHQ&{fv~bthP_)O_hBYDgwVTL~I13ev@TWxr1x1n!YO`5?e_X&5!PwEcPU=?EO2Le&
z{eoRTKK5Biofb^e=})<rJ6U5x+eV&O$wAYCwc~#Wg*<5RH2P+@^0P&@n-jMdOXgOE
z2~$q#E}qo=Q^ireGKyPUHigUOD_4<&hmGTYjZlv349c#LjE&}72K!CdT0H6LsY%N+
z)~VU3ewW=CzHS=pj<=a^4CjNqb5f2RKNQGt|L9r=^T4^Oix-@5yCqYTGh0?Dq)u8d
z(M@CWm2T7IGg{N#rf&`uykXBg{aE4ODW*AA>i(xBX9^2`SL2)FlGp8Z)Jh@q%B#;Y
zy!)CpZr{t?qZk**TBDm|B>klGyl!wF%e`e{rGAVJtp@CKs!u*=aM`hBE(_D_&c%MB
zEV4HOL!B9%67rUx^v-QPA6nJEcSo7xWC^PVg>`9nMLw{;|Jk9dD&7C6am~joaXYt2
zwz4NVNC=CxH%@s{u%l$p%LB%pOv_iWdQS?8W#L=Fc!7J9@yAzu1uFdW4l)@#v93$0
z+!L^jp<uy_LtKXztDM??n5lTJlH~`d-t>q@X}t=y8KNE~+O;JGk3;Jw|16Jae$OZ*
zyyV={wYHkIACC3yx{{pdUvfD4N2!G6@eivT9fB_}Z7-c&X)v*hEp}f)=>;{$wpH32
zH!jtB_cYYc=dH%gCbQ5h7aP8F9jV^8Zu5alyk6|V)A}NH84e5159oe<l*711n@KyO
z>r7Dh_66=%>t~6yEc>voz)?eaf=V~5pX;S_T&5E&685sZY@Bg2Yu}a!ySt;x{%MIh
zrCy!d;kq%Kf6D%VdrWL)s_(0pwWS{Ew3%sg*29YFW1ua|glxfHF`cHRj^S*}4u@{d
zTI-dj88C_8e8D-F&odTnX5dV6J*TvvGpRt!G<sFd%uV%vaUC6v9<c|wS14weGPM3W
zpt*eM>ZgaSOCwKTwDk*}Ss>cHZ?#{hJjdBzT9<V-V+uNS9_D?zn-*(RzobQ5)hl$z
zq*d#6jW$g-F72`4IQI8{QE9`m$(qs^Z!a}mmixhmQ}sl&LVS4AAC@1d_e_fA7Iy!T
zcx_kq^o*@b_@}!jyl3Q?+r{A!;Zni!?C@$Qwwe5`S0=eI2rjY~d$8r4i)h^91Ikuq
zCQnZ(WU6+oEqOHY1jnt*qOI{+j&ZD~lyC91=*jn9^Yy!<@^DY!f%zYvy6dyftUu=P
z_;QSet-#-#Q+Mj!{3QG}N3h9lH}i}BTxY$G0<(N;AO3(}&8=GblNX;}Hb*vL&8#V=
zdcjh27b`P&MsCoUD7!lB;2g#GOEx9ntnys^S)q9256!Fd4t&#GcX0Q+qm~QZ=37qU
z)86#lB*$r0iwx7Jk`(rZy=SlPh+NpHbUj*Pi};GeE^Mr7VJxo;b&FXx_JmA$@iOG(
zZp$jMj_1q`JG&)XKX9jN<?*iz*(d0?*i6?g`Nly*nWf<sXD2LFNYIV#K9LmT^~8#&
zV`@_ex7tBF?HdmlX}tP2ZH1)q*;QS=b2ENSNo3sL8Q7OPOXvJixoj(u*?N4<ZA~-E
zPKswprlriD>?Eimo!OXlNF&fHVtUkU29X=eOIOrZ*t!@j5q<r?!E92Mbc*mlodrx{
zzZ*2U{*@-bi157av0Y31$X>1W7agZ(F7$nI=H^p7@434kGH#hrF+Fta8?yqw(xn$I
zS!c#GDlFR7A+f`C;%e3sF-OxCYIkPqh<9!}GxbBLE5ojiC&`~aPPDdC)owqr=7d;h
zv{=CHMTzr*dES4iHi%?e%iHAQQqC^pD8YDPuAjWwk#HaBoVRkj)zT7M622YcUZ=wF
z*U9t-m)P-%T&aqG=B=%rvOAjNag1j}$jVdy+-6E8%-6nWyJJsbtuNc`rRKsb7$c`Y
zoUON`^N_*T0`CI}FSZ@fU3hI-Xxrmita?U8OqcbSym)+h`^<x{F77|-y<0qtp+ebe
z`=Y}$_#a<;(QS6z-e5x}lS+f;l?grDWVZHAW>f82m!uWZzffq+W!5!QJ4+X@w3yPu
z=5XG|^rUIl75xsD&+GxsE)nv1;<X%CZEdQiR(?G#DsB2xeZzjk4Qv`O1rE<XwEofF
zpw8ci_-y?|1DPfU7D_SfSrPI&<8ftj`J-3mpV^d*PQ6yBP})6b!XnH3yO)&qO+CVS
z<gZK4eG}$xH^*z!Teg2Z+H<$2s7Ov|ZCFce$3`jV8F!PW`|fXYED_l%#;_{L-E+c?
znt(b6?%>yE?n>5cX7Wba6?)7x{QY6#`RO@(3$7KsztS;parKll$IVjQQ=gtV_+0Uj
zklwNYy;e{EHw?ycp;}=%$L1+-NMQNNS8vI7((sFwjqW72IV=+!Cj_lp!SF}&<r||f
z^$Xlg6uZSG3ap;6vITLRWtm_u_4eo4L+Mj@@vc~&)W_$x%Gg=;OvVZ6rkKknuP54H
znp-B*Ik(%%bk!O8p3^c+PZO8R?YbDYqUq({{9oBoA6b(39Q+(Lg-^753sc$Lgs&2-
z4Ne%}wkbSvFSR|LZ;^YntjKp}gPIj?33E8^r)4v^Z@A)jr)$}gClA-^#dO4UZMtJ-
zyZNJ(Y|>2Q2fMFqj4#rf#~|ovnj~RbVpAx0va4&=gQlyOp4~`hon5QC&uT~9v5pn|
zA(mHmM^#!+?(j)&(y2|_Z7+J)#dN~66RQKc-6S7v5Y%5+XjF35f^|CA;wvn3vaSn0
zY|7)BX%rO`$GV?Y`p#mmw;HU+-i9}v4J@6p%DXc2=OW*qUzW1^=4Yw7RmO;xPZMQp
zS+*!h|MjdJK}!^0{g|}0bRM^Iut0pjRa@Y<xevpY?<jrVsL{PbS3J4qi2my06_N=T
z1oWPI7rHw>HGCg2l`BBx#o0p+jF)9N-v`dizB2RH{10olitC29Xa!9RejMD9e6r(`
z(xRC?o9dKzY_|~Fc5zMTB3(5-t~uMbBt0l+I@ck4v^%!**51k9GZzLcZgqd7b7lD|
zZ{CG#4P@r(H|W2*<Xye&-yTt`=bOy#PTwag-mUc`nK9{1?28~4?*g6V<KJHV)^u0Q
zP!c%H<M{l^(aUyyQ`!yn<~CSOSa4~<mDlrsCiwSe-Sd4R&pJnQX}3d!P_`T2442K#
zJ7OAz8|GWeOprE;oSWS`dD+RzPrmP3*v;PXY92iiCgXRxfM+9ngVOcV9Z!yQB<r{=
zw8_%?xNvd6DFa!_Wd)0W7|yPV{3G=`o&B-xr2|KItr9t!=XuK6TBzmczcnAF81(t3
z?wnpDenZZ8X7ba+orO0xYP38QXgd*jl+W^%P|t(;yc7RVkDvSSbmHX}i<2AL-Q+nE
z*SjV=%+UVf7kyDO&1aHmvB*?u<&GQ`SyO%y(WP-EvzI=*%}^pGv!<6>T2Y60(&?28
z??^YA%c#W!Z{GU+MPAyXRSBhh*I9muO{y&FGsr*YxQlZ|8<SRV<szwX6FT0jB+XE;
z=~lDil~dT}9&<#zU$2q*S)+t<gjV!_hBqFZ^QX;tWT@D_(&y3^(W3RQCS9J=;BnF}
zbi@0n7H;C)&78AXwz-{QGDzTd5OeEZyhYIB;yfpo32sh{f)fs!1U(ei%m4e3%Qe<v
zQ)Fy#fk^qBg&i>g%<p+$zD)Wd&{A|pC)j93YAg3W2}{1N$|SFotwGxsD$Ph=`tX@R
z7k|R5BdfZO9?I%;JNr6j0o%4|*I6EaIP%G-Y!%Z=lk{5>CNES!O#Y*$Gx6%24Wib{
zU*<H=yP@_;{^%o~*9L7&Cl|S07dp#vaJlN)BeFW5nZ65dpD$adt5Pt<g|nt|p?<N)
zR<<7IO74lK=e+ODtcYQ`Gu7>K>5^QlX<TM$XV?>NPHkDr+{P_=_tLIBw@q8h1mZ*5
z`jpgv$GK0Od{j>1#*3xjKQSG&s#>%B<Ah6@Qs-Y79a<-0Ds}8;yTt#*;7sYSitBY&
z@K0M?7JH{w_O8ITWtlb$kI#5eb^FVy%`39RCf2C#VB8yN(xA)aG9%vc&?N3YhVvK8
zb7h2ulNT%Pmbbpkktq|ieU7j9=d7}$IbXXc+Gekcda~PXtHzE*#kH&c?)v*QF-k`M
z=Ca4n%KB2&7V(_t$U7W$NMJ{zuz~2MD@$hC^QO&a-MV0H;I<aV=7%$uO`O2+da;_a
zF!$k()F~Y;2P4<D3)ZQeDwW_2$vE=%=hbDII#*vxaP%137_Krul)cuAxxd5j&8w+w
zSAvWz7ie!6D1Ty<(xQ|fdqk=H;xWd<Dd|(%&P&`{7FpO=yW9ALfVTYJ@@<!n?6GYS
zwKyuj^p4n}=UQK`sW(oHRh@9w`)E8PbMfpQyC$&&JP$c}yTe(M<HD2MzSkG$U0Ez6
zEZ?bKFZJjY*WMc$->3A{Y&coE!(RE&j7OPbiwga=y>~pawIQwZWRIxJstNm9nS~$s
z6}MfMHT%6w>t-R}x2C`BbKF{vgv)=9D9rGiaCfDO(=we{+fz*<f%|S$IefmXyezNc
z(v9uLRl75ft>jQ`FwnRlJJESzVYA_VZtt}+oXfV{dA+vAXWHx9GntByYWCl?uT}4z
zYHDz~CA#vYvigBJZ7bF!Fh?@Bdl_VIIm+2H<?`iB6J@QmZ#+DOT}>k1OP0#T>uvNg
zVOl2ifUki+<Y)g*Yo@{jLfUs0E9tdQRW4n4ZSxEB3x-}>Pc_uZ7RyboSaj2PM$|3I
zMM6@|&t`Z%6{+&v&XwV(@KT}j)XJp?)@@qN(iXbvt+8(CJ+>F6k0hToi|fbn`36N~
zMDnvd3Mr@y?C=#XQ%h%6TXyYX*!?TFqNeCxH8U@}^V0Ra{reqUtFK$ycwe=>a;obH
z+qSl^n?ui?oHA?8q}3)fS~SZNb&e#&FS}veJB35S=YU4ohQ^qfmKQ0~#Sf3pY`LU1
zQ&6^o<G|JoBl9QfmilJu{Y#!@Y?42HGwaAIOGYL+C2!q=vzzYR>C^0t^Q$=Jb70li
zNq!eCd!#S-ye|&i&38%iK*lN6Zqt2dOrP31?aD~MaNx|^$fXmD<vKQ=;9Aw)dTo|y
zjzQ}xnWKki+DI93#7*=(>@jUxZ%HOg&kVCL<_5RcBMe1aPW@Z1{BoJ;eOx15GV<!A
zZ5&6XPqMSxz7Fhim%eDg9~^#)Iq{H#q;mG(TZ=STzuB_xv7OPfD-5foD|mVyO*!52
zm{m<mCA3e4U27@VHXT)S*^}$0R$dh`KO~kYF5#!#-R)E~X<|YMyMMgEip@Ljw`#7N
zv5C)kb4b0%CHcY>_TGT9OA(26;X8G7l0JT65dSD}F8hbyQZ><66N=)_cxbBlT#tM)
zFQrQI)s__Vu7fecF7NlM{AWnq$0b;jy5Zr?)F~Z2k*za0I946l$oxSh$5rPB55o`B
zaG_vMBc?y9naA5d6&XE}_WR?yW9>8-K30bX&#DU!#xL-ZE;Tu0Y16?P<B&M<gIDxN
z;mdC%xTK=2uC;n-%*|OgHA-fh+Gb~gMI2LgjBnjbyMJ<~MdY-tO2Rp;$Il#Gl={@w
zS<Ig?`H61F=f#J0)E#R#{9p2R`bB5E6AK!2B04WENxE`Qn)Al@oh!Z;>q~B)xlqXb
z{TXhngIjn$tqQS|UUqfm)UcCkPXz6Sjn7`0u=t8bXp9ci)h))yDondQZf`QUzr@4K
z`S;_CA9LN#d8HYhc(!q$)CtcMD;pBlrq5#kZ>%kEH<3?!zTIvvBcaC6=f0GhT(;V2
zwslIeMr^ynQ<*)+57IQe)@S4eh8MKWyTfUb&>nNj?5NE1HC-xcVILx1<r~kxnIN%A
zusS?+-J}DZTl6^9txRkRqTjl1ZD+NOuv-xvnh-i;?cC7(hQ&Lks5nH-?zeVY?|QVQ
zF3xLx<I6LLa?M}v^z8NZQ%d_Fame^fs7~$yg(%Z1;clDP1%hm|1&_~}Asao#%Fk$P
z@g94|F9mHEIc^%SIK4nlrKstMn8?<5hRajDBIes%I>TnZL@U%bYTGOhF+Q%djjRgC
zSD(G@QuxiWCvg5P#Z8B&+pn{cofgurpCskmV^Y#~?WFtq$S;$cbTs_zw?4>MS{iAm
zW;<u*?920J)OsdgzwKjfen?~bZzGrQ3!T;mE?lGe$ZWTX*rg1iJ2O^kajCIMb$nQ%
zuqY);k|+4$BvG~-$|v2^(iS-=y8K+f?9vD8{*vAj!LYWv-LKqLvM>3m7z<6EbtpCU
zjM7uCqkPL=R(y$Km0Tb{Wuov5o%!!)q@8-$BY(K@r}H)6W0HsGF>VV!=-_Hse4)gE
zzf$U~Y4YpUK3h{`DvU4hpV^@|OG&+NO-@Zp$X>6tHlGfMaw~1Rr0`>=$uSnk(|l=y
z%RNqMC;J#TNN?MJQKU(9;SZ6!KAv)`ZwUo24G~aS$DrbxbACfdw}RjUCzsTq{zcx-
zoe7sa)X(}IDU#H_o%s0O+#QSk&Rjfxq9A+u-s7+1PtFr%J>mQ*Gofipmg|x$hFvom
zpL+Wo&&zIEW|(?uLp6Ksl3j&Tr)Mm5n>u^xC*id3!5&_&+k>v1S>X0GUMVM3<7R_}
z=8QE)j~XBSJ3p<f&OL3_<@EuLI%~XMUf@uA=%(wnZo;9B7Y)2`-+8z3RFBfEf=4%)
zI9%7wT-vy9lSJV2Sz5d)Vax8BJ{OkMdtt_=!>yxv;Ja?<ef|XxwS;dbc<+e`&eYwd
zl>1s?Q9<w7d#0fQ+^IRglxHgEs%W!ssD1RK&rI!H#iXmH8U{kz(E=x}(_Sup@zrDE
zlL*sz@t}$A8;)HGPSyKVCR!RDx+7?^+o94^CntsPelYd)P2Z)m%GWpUoy3&(rA{ns
z+p?8m4yxJ`*Pr_=y|JY@tFeE|N;MtJkY@AV6z`r2RX*))<q~@<PX;l+%`rT9sQF;%
zEkDbiu;enQ%sng<x0y02n{xEds^QQ#(K~a6HQx2Bi_-lSURPJez5S>2=#uLu<K>b+
z-$-6JT_oea*y8_ftNV<rL^Uri4)t0uP~*#+p|QmK)y7E|`M!%y<gqR~bjRv>(kZzO
zjK4W&Eq!;Us%+wtjxw(L%_nAkj(T=vq1pVhS&~6{dcl4?fg9VFpZJuJwy8mzjcMYh
z2Wcm>gtr8|SI^bEvF`yJYyU!t4>ONVp3y3EIO)h^R<<uf4}wzW*1Vg@+pi#19RFsa
z@{R+)Hr;UM{r>FXu1R5`SxG7v-}&i#JuQf6y2G(LZY%q*1$xcB`BP*VOjo<VEtWGA
z+Ht<e_h{~}kBK|vIa4YpdrO9d+@5mkR7mKC!|n$Rrm0v>VwIYHA#E<hokuOAtcHuu
zKI~bc`GUKsOk|SC#1kK;ZWRmAPlza0U1eK2ZEET14~(lW%A9X#xhXaK@zpC&HnUpC
zGS7c`WbU482BKGPYQ8<;{LkRVX}8m6yLVkNaoDhDg3Bha+gD^aY?dl%(oqtvbBo)X
z5Uu-;OLU30r6qGh==#tv4i5rq^~J6PKiy_qJ7t11lQ#>)vE*}~uQ*FbDP)GPdT>md
z*+x2t*Gy?!s<PSM$y_`?6mJ<l=!rRK#q22WvNelK_s|hruDok~JpI<M%z6{nE1fvK
zPC!Q5*2sC%L+>f)W|p3fUYc|^D(1@;LDBrPikmEVN%!qu>b!HlV0?<>1LuVF`Nf{8
zqJ^wx{jBC&`1Xm#d52C3@fPr|-M+J9$C>H*PB(34FYfuc_^_$on;UI=rd)IgIw!#v
zeC_P*c@7&nd5aDhF6h3$jiae&$qCW)**-!|fxH%iH?%ra-GUdjX)!pRSR$F)&hg(b
zKe@K7SMAxYN*zPSHJk0*l6!N)I=4$T&U`#W&GUkHRaDdQmWbr_n!9FqH7zs>5BTF9
zWujBVeErnU^t~2MOdGCFI&yDKM_;7CkpLzihUBu6quj^Nxb^CUPD^e2q3W<eaGLyD
zHy^(SyO5%-$}?}S?fD$Wmn<V`!Myd}f~shl-$uHtWIZ|a8~Eq<Pu*SnVv*o>!wJ{#
z=JfDHEwENNt9F{Bm9c4JiR&|2X-Ani(H*ziqxMeSB=GQLUGEa}6?<6b2ESC`%RL!<
zHEJf?mO!JD#H)V{Ro_^Ma~|rLtb6`al<a)tDLGfodai0Obw9S#<-%RRQ=4Z@m1r~!
zI<{A=UHehMj;yUbaob&uxW8Uv$z0yOq(MKR{mZfok17fj?^=A4x~mqEyYyM<m%8w?
z4o|-dTyPM%^l8b=&zE*`oO~Ipb#7i}Z0IU8?xPEm!>+8+5n&H-(wdbR*?IQ>+d;vO
z18Secaye|+mJ0Ohtw{+#dni=#F3X$Jf&;EgnTuDsnROU4J^iMgKj~-Tha^QFhCKDm
zBQeL)97DFZbSNYwuWmaj#u~A@a#~uC((W}9y~bWw0)9NcTT;2yi@UUzkx6am;tQ7-
z2;_U{@ALCxFyP%TaFqF>;pIgaywYPPNvqtA30Wjm7MhS78K$vB;@#<UzAJ>)TUUMO
zDp$C);9SI(d6wCC)<%6<BB~pFb?V{N&r%XG;h6_Fh$j2DM@Abi-R;GABs6B)nse?8
zj+%(DcysGD_&s}Cen7L3(dN(<_k>KZLuT5X4h*N~?h?G>YQ|^TKj)dizj?<>ISe`F
zG|FFd#$=q7-ttc*YtzP*Kbcbf>$}+3AB}B#?IZkynOivI^9#)bJ7g0)%{7+x<ji>3
zeJkMW$r`l{NxzhS<$nCw=V2;yy2sOUerb;gcmGL=kow5Y%-2eP%Uac&{W|zI`RUD$
zf|iUuj7|%*&TgKv^Gu6wuIc@+Rw1I!pC|ckNfR<F>E$eAWldz{=lyr|L66{@;FfQ`
zkAu2ozZmtNG7Q_a+~XFD^2BAj)7>q~yYCp^)0A31Me-f{Kkhkg^2(oiH&std;(9K!
zWUq*XWgq9Mt9cT03;T|_pNwf)Cb0IwjU`i~!VHS}rDGd4R^4Rb+gISIrfGcfg_vvP
z%34u>jh3YggePdpZ`igY$wXabS5dB-vASLv=gU$q*6CcImAU+icQ^z}AJQ>lov0{1
z(<!tk%hh@PhvJ>j9G<!u%<Ea#)cY!`Is3xgR^inptK@njY)^O<{8VXT4PA0jSO4)L
zN0IV#Du*||x@{fk-zRFZNagIZdxbMEJdsV}QILAcda02oXj}1}<cm=Ye)g;P7*9Cs
z=%4mEuJ5+w=hN3Nd~Eq|Xe8=+QO1<j<qx0tl^T!D&zqCX993&3-!y(dyLPFMPiBFi
z;WeG!YaLzcXF7LY;|ulgzx0adCEsM#FHyc8FTVKpJnbvkd`wZ0wWCt%cq?bHk6hw)
zbED6aYX4U}RZ8R8<l}kdAm8pB-(chSmp3#9r?_p_Xx6PhvS9(E`m^%2g~7WY&7Em~
z(dN&O6J?)VKi>|#zS`v7F44x?-`kGc$w}KBo6a+(-gH63QN7K#I@Zt0YLB^k<&@J#
zqqTV)Pi&W)DoRChruLt_Qut5loNYw;xjkzp`s6U^udzNg^RBzPo0#L8B>}-<hc`Y>
z(6pMO8ELl3Do*VZN0!;+X&d9!4C1dHT&nB6ldZUAUn19(2X38)eXlYjw`ErI?C83p
zY^HtnNSvIWYWlRQt|tz1eRDf@TOF~nSB^ZC`{vMewG>so)q5^25IDcCOp@*4i$Esz
z^>-vEFl*lIkdnL>`&`Rt=dIm_I}QgtjNB6`WnS-=-N1KqfxCt^o5d22Y*Bly%a%H;
zp7$@=B4H9Dd{1g!Hs9=7+|S!&_9vNI>=f8z<7OwXSQj00*uY3)-`gYMT@x2PI$)t-
zT^b^vxZ_3-qt4>0oGk14Za20$mYZF!ZTz}qVoF3B*SCsgI>zP}Tlt^=HuyYgGn<}V
z)4W814KLp9h-3TgRC?mJ%-MT0qWFHWG&RdHUE}Slde8Iw(2R_ZZG9U0`BidiF<j9C
zwjw^Wj_nbO+uX&ks=LWh@8HHCvlsrDrFpV`rAX+}loFHFPNjo7Y<H$?Y&dG=H(_rl
z1Ha^^4QmS{1LB^xz6fhz&r;dRz3k88#b-^57?LfHTULt&Ig6!kH8Ws(etaHhXsnU*
zi&+aSkKfrG^<{m--Q~9<m+BY^ymIE!p1}UenZu6bW7S-f{==TSZZ6Wir`evRFJ@Gp
z<{x)tzu~hwOWCC#q=Z<OwHfJnrTP}T^st0Sd^6?$(fPSyM_0|g3v5%o1bG{71sq@d
zMB%<*m)_$?Jh8lL6P%Adl;Airp<!ZZuYkg>xigNg-}_<h3p?pkOP=Um=ktAe<l2P7
zw3t^6>FUoi6W*`{PTh6$o8_!^pPpIXPP(`uR_&R9WO(9H5yov@*;1bu^{dR1YS42^
za40K&%AjR<Ir*ED=kd12BS8xV{EQyoW%;8v(~i;iM?#EGaH9U6<n#LkjkoXlv;447
zWsJ4?n>??Fi+nfSXH3XgQK!n7zKzSQcjwoHdB%=v1s^T!{pNcAIu{|NYu$5Xk`YgK
z&XmwjBb74M`4+-f5wF^3W$Sny`aR)Pub<&VM)N%W)hZfNJ;zg=lAp}(u2?Bmx1vN>
zB~6-nmuE-DjB9T<Z1&%9Yx#?GWheVD5)W+zRW}+cf8_XopTk>p=j0Q5t815t#A~?x
zd=b7;_@j-HZTBS)N6p(pyvJX@YPcD>{(%NBi)_Tw*?bXQ1tK4$m7S-!UnsYjA0zTN
zBqfM<#gr4yhCc)rTWS35eUOlQGu1+S-coT7XOA_f_lTtzo+&<3t0tQuvorgH!Si*j
z?aIeKZ#?GIc~Mq<$DSp*8_Yd)XC)jt@<(t{BI~A<1L_@YR;@2L2{rF34lOrc+B?xk
z$>`~f36h*Iq*9x^cfam6RCCF2IkHfDU3Z80ZL_skgZF)DT^7H>Q^{R*IZH(7)E%F8
zO*w5~Qt9z6{(+U~=Y)F<R!vstuX0(v_+!WRYO!K*85_%)c-6}2xhYMvCVkq?VR`e?
zmcU@gC^k!R->;LVa6gGTxvTB+H9iC9wfAR-X;i4T%xGT4w$$j{eo@aL3z@?*>X~Ua
zM>x8~FLNFHvt)5zxZwNQo4)Qld9$PCUGpQ!q>5)Q5?6oRRc|ePVD@Q_@ok38HB65>
zMbvwqpYKaOA(!}cL)Y9}GVdkQRD+9?)0q>SZ(cwABz4)#8F!R69#ITd<A{2^OwU#2
z=pL<ACptSHx3M?J%3CMxkWk(wB{xqn@~B^{u;v@#?R7_)N^)M`kf^Oc5|wgeX42L8
zoEhf&XDpiJ{Mlsq6-<>E3VLcDsahz}u~++$PuU^;@ZV887CLq18Eo(L41cjNz?A6`
z%ZH$8ceu`&aJNV<-_5>ePIy+=^EWy?pPIw=%=mfU<l&K};?{@beRgbAV)FI=zag~C
zMa}wUv5Kj`ih9YMLK()+jlZ@Titt~O4ZJGz`8o&N`7W!rf5$xzu~p7kmez8x?`3S-
z%XjQ|zg+UL{PfVKc;(bd6A!GN_9S`fbfpVB_8iLIrBI<%n0KH`IZ#LP<xc^P*If5k
z+}c`_^^mdQjB{Go!wUt<3+|M$cf>}0E?W}#+_3q>u{nIc`!@>qM7zA|PRwu8-aSvZ
zbmE<dja<HxsvG)vbgP?|)e5s|tUA<wX?<HiN9@^Snx7i~9@xQrY44Iri)ZbM$P9Mv
z;rwOdP_1RFu-w(A<lMT*J8!mplY5kM?ti=|7yBINyHY;`R1y!W@!c--?3Z})SU#Dn
z{l;OJXNFGZP43gLSFr{Po?K()pFSt=(zbNB%Rk(G`<1T=c$=lKElh9uo8eGB-z{m{
zjd^p-W_{Wxklx<qe2OcjBO>rQ19RqL^|s|#6m*Xi72LbRvHO(CwNtCJo+WR+^z5xm
zk6+>J&?{+KMmB-RtsG=mUTbk*=@_v4@}e)6GCPENxqREJK0ZvFlKg?GBSw*FJ<qkJ
zm--jnJ)D;$$aiT$qhL#Zn!n*(1s?5_3!cq1-@zB=zhjHuhRq#LHz%%N7n0k2N{`i`
zL`Qu2d#levPT^Hw=X-c-tvBnfbm6tOd${`Wza3i?)4pa+P{=rY;m9VdH!}@N4(~gy
z{KL_B$(2W<%LS!pynT}NVS{yH@-u^d-M>B^^9e0`kl?dAt@y9txw~6tyM)$lTXnyT
zea5jlb9MAJ5BJ+-mB~%KVlU<)d{H#A(S4&u+lojN|JMhWR`xtzY^38L{)q8urp?<e
zQ#agQ_2B@Ef`C*)<_?dFS-U4NFUi~~cV*(UQ{9`b^^#9rIw^a2jlP!_>%9)!45?O&
z=Q}FW8&4%|^SQC|e$Sn}j&%`}o1Rr%-F;Y4@SXfQjod}?zg~2#x>WY^S;zb58mzG{
z-!|`+T6AX3K}Hwv$&c>xwYg2$VeIrxv)lE+*Q>orz6;_^mCf9qr`}CbEX)sOS;yJ2
zU1C!5xlm2H89S1n_}wwQ;I#TGw}I)Nh!>h7vo76QdggKG_4gaX^-o@A%A1niEf8@`
z(sPmCe&t0wS1<GB4as~cx#WV>TuEQq7S+llYlZinaX9#pf6GA&-JsS7Mv@DHJoUOI
zXZ)~zac<?yZkr9?SG>H=F?r5jj!kRA*1K-*5-Cz!wBsbVp77M`kIcFQH<^al9j{tw
z`8G#)K~U<v><|a;g*FVyx;gw0Za=AM53(`LVO!>_W_?9MwlqWbN{57M_`8-5Q=C`M
z+UB3Tz~yAae8rv+bE#jg3-4H7Kh?C@<6|uUg*Y}v$;0K6dWG&C*{35Nq$WR>eYf_A
zk@$+N1OdinE=O87$ujPBlG<tRdoAfDm-mX!Jxz}~1TNgE_ACgSUS+I(!?3qUE7W>=
z_||D_-Tn(R)hs)E?{`qEpGddreLe=`t!aMxYqFy(c?II^^r{=D&Pq7-EY()xJX=KH
zesAlOZX0wqc@%FgZj@YK@iyX;w#QYAI_r~@EU&EMGTr--X*H|l4fTZ*VQma)c88@l
zCM6#YUy?ZC3ty?lo=je0-5W-&p4``y*4o*I9GDPS`fY29cK18pg(~Y8Fo#T;I>BYK
z&C>7enK~()&aovL4qdM{%Pz`X$6?iL^hQ=7`{c6R(20wm{$7@LIoIopY)Z;O?H6By
zI|Lrj+4Y|xN=;jYBV+5XB+*%lOY?Rv>IyO}sy?R2zcTw+5a;3D91`(<X?ju_H}xjo
zJu~I$lC$9(g?k%yRV<4_x2%?A$Q5#DQ?XZ+<MO`7&6p+9&a9_(HJnj(x4;(@2|GuR
zLmhh)LgrVWOm1AH^K=VaPF$a5`ezgE{>t_U>&}1E4jo<8#<}nUkIR-2UF$yvL0Wrt
zPDgo}HRU{No%-p-4#N(qsaG;@zY1EP*!s20Wh=*$StqRw9y{J<uJC=pds9HZ@2ItS
z+lPH2>B)f$Z~0_PX-=^`p>E8yE->DIj{O0fT-|G*AFnMAU8-F!wT{7H-JZDMRvVX?
zm!cC^2_MPZe>?M77Vn`2NmU1r$w}Sbw7~sn2dAu*0mn|0s)nS}+YED*X5AA}Da+FH
z;9KggVptKXxl65q^P5GAn|83ONAJ%!%L=<2VpVf3_|BcUlI^Xfp!;l<M#c<_gu>9U
zQ+&t5FaOb8)ufx56zT1~QRY~d-{IcLQHAqdk4{@+yxKTIWLjXh+^Y+r9(7-KnJipo
zUBK0-6>2GKQ0l0xcU~dx!Z8j#Mu*Ilj~g!8v@FZ6syi}$k=E(e6aGqR?0HtaZtI#N
zwk5VX4epimrtxaH9CbdqyW5cQ(Btr}k0N@GJPX!b62qvlwr|ryB{tDW#kPH`w5D8R
z(wRI@<O193=chula*cQd>sBoZ=vKX|;2F48ercq**;27@Dq3G9D!X~7Cbsdh8L68z
zo(w&dmFbfiFn@Vib5q4fnb>vBB@I$6V%ky%R9Y^qKJb>$OV;N|!-=*hJ9J(w&x!5#
z(n)>hwXl8$*VGNd9z}uIABkkkbWN^{_13!@RD5Ci495QGM&9!+*M-?6*R79HpJ4Dx
zM`PCK5TAy9euqOHL^-#LO>I!(`14SSb!v<nk8@9&ds(IRYqwWcCna0e?`}|Dw!t%M
zfkD`gl`C4EPj5ETNW5UABbuFHy;>nmKzUMU=Jn*17PGBqY7|{pCU$3Qx;+c{t#0gm
zyYC45v#j68itaNOC%w~7ddP71#hz}RkbYK~xG8~R{a@Da6O;-%k=kNf{gr)ft>m8`
z@6ec?UEQsdyrh@vdgcTuURH=LSZB>vdsysi8S|QDS;w|KxFasHM`+Ev8FK<xq)qGm
zd0s{RM5Kpm=9<^5*)(6gyy7cvm@C~Ml@S+q=CIhMs4&+Rb9;ZqE&FAv-eOYepK$7l
z7qigv??I*R9dnl-3|^jAt82y3pDFfIz*uPF%%CZn?zg7Qd~u7j+BnWln`d&ujv6oa
zi{F=qygXCBN@j8XlviP^67Fef$tiq46~3$?e6Nh>Q68~Z%2%^zuil&V!O75#uajw~
zrl`=ALq<)>&dX+|?A2fKL|b5sfLC;4K<ACwwa5IPudxZ-9<)YowUh7ShY6B7MI6<Q
zKTq1Oyc*K?h9&#ZhrB}NowF5ZE3W&nDAZwYX3U<A4wo-!^*+$d4t=snTwFO(e`S5!
z<T*Wt-;WDTob_-?SyJOdh1plu=uHed(KLyTVc7%jCX3##9EF|_bFw(MEZD5H<M1!8
z+%wC*^Gum}<$%k!`1j0{dc1mkG+)IYud&LVE7GW#-87GV#^0XuC3>0etAZBopV7BD
z`SO&A7qco98#*=#b-6Bl+GgAIe&;e(r-%CCf})ldS!+Kf*ss6oDU^IlvUh=@TV`(W
z&8?v)gR_tR)|lh6ezD*;$+Za<Jx-6MdKHiOJy86}d?ZG=on!a;6{P`_r7ybh7@K}M
zxaiB77h!!DYg7YMBi4nru?T2{PG7z%{7F@%k(_JfqHChj`!_!7d&Sq_7oL>cR-4Fl
zdBLCKJW*<Ok}Kl%9*JBG+J55|ld)J@#PkVnML&-m%IMHnpUC4kV}1KF;VsHLlXuS3
zkO}|D6kwd1+i-#F-u9fZg8n`C^xN<4(Rsw-5%Fz};hB^cKKFI(58{q%+`8K6!Mx4e
zb$NcsCIf9*7uNlmF$G(^RgZjZJ3GTwm1k$=#Vpyv*|A5|#Gk(KZJRqsziGCoYhh6E
zw&qWIu9k+~X|9&0-IX)lax;qzSKQp_x5dwSPo2ww?(UAjM-!O%RcCoW554=W=IE?m
zM^UA~ohIUYW+@lztPe|_eM;3We0d>XU6v<<;A8i=hl!K5=d3<CuR~`_*FBF`?zpP9
zRdtT<c~>2YjPLt3xl8i+gEd`&S}Gi2mdA8G5~L?2J=H#aZ04;pvGr@0{BHRWdt(O|
zLsx8H;6bIy+l&8CE{R`uaH@fRtKzIp7jt@=id<g4v&oIkeE3h3BjMAD2@mdiiAsK#
zKdh~>FF;RsYFL=xskG=dDO2K)G*9{b{eamPO}U0Ht`xJR&jm|Y^lzBrl4&ezSd}j9
zb$LQ0Lr93s$);@qj$1<Ku?u?$&q?F5FbP!**r&EL-!dq;w5FLiY00s!k1KQ!yRfsV
zNwNkM&M?{f=*>~tJki~^I}2_JJWdVhyt3wVuD5UDrxb4A5-o+<tQ)(x?wZu16#ky$
z!K2O7n3Gdk($prF%qml04Qw*=ka3vwcV?qNicBkOh`;ZXombW$i&5WUQ{#KRPnqk*
zv{$7WmsfNY+C;_9+je}rYNWSLjzWiu`0+V=vYK-lE-u+RV^eT0`=+;F8j5PpT)QpA
zx$&9esw_jzg$vF#1YdjOz_@&Jr?a`00887xME{~4@`v__tYEw%nh;iDwE4MT$mJK0
zS4^C6!uR6o759bnb*4Y<VZL}i#>m{#H}b)ai!=O>b$(8q6Y!+>^p(tIe1XaZLT4?k
zlF|hv&owvqIy`OJsyBy!Pv)^wzenG)CjXnoBIdeCjlt(sVz+N(%Zf#Ub~DA!7;<)0
z^v%dqmvC8`!|x%tXkq3n!5hooRh$Y6S^YrE#ir0FZF0zE`7LWyH;5I~>X|R#dKY=|
z%Ez#O<(D_lTQ?!&;e$y(g09vx#OWwB{0Urb?A3acyJMn8q_cc^SZ8(bk(de}o#RFU
zHo<w4Lh{pHV>4eE<v4w4+T^-c_LIDp*Hb-%@0@{*-_n&`gJxy=GU>Q1sFRQ^=GbxR
zpowQo-=eDls?6L{ZzGoWy9v(x8?Z6NZR5okW?LR~JZ|7$)Z_kJfj95?ier|$B&;oD
znoWCGi5r$Vvq-2}%@NVjHN9lCs!`>FyI=5}e<uYxgI|UzNF~WF7rX5_t;sF6jho3)
zQ2DbLYrz%1Q-4=~GWl?;a?0DJ8|H^SjxU+n_hf?K;*|kwc)UJ}cz&!F-dS;2Gq}^#
z_|i1VondG5-H!F1z3#$XW;1i<+VdVK&7JmVYPt8yII%bj9xvQ6eJe+J=xP_A$p4v3
zeC92?$YVcI#n_p%VMez^V5Lr*xYE><ZYg(qFMd0CNk&;@OW>`n32DD}JXJP+6Um%2
zKds`7<st65a&DpDI)g7he0{E6p|WsKN0fumo=uE=r>A)s@vjeW_<GMr!?@FpiSaON
zBC~Tuuy1%qI(K(lK!3;QzAImiYJAVmivM`?I9Hcs=aje4PMisN-0pfI<YmxF*{~@V
zYT>myPcm-^9sJXOWKELlo&}599whfW?w*yoBq>uR?`na`=6CWJCwkQgT-x<1XB$hA
z_w)=6R)NA`yBAugbUf~8hWX!<EcV=EWO72-P&;zD)){yG0GoyBEFQTAEIv<EuE{I=
zc^Vwqee_q=$Jj$_97Ucy@XpUk$x&~g%<N)j+2{V~<o!n{Egnbbs+#wlnaEjwXa4;)
zVe;E!kNPk&@Om9I+~XPaAhGN7Avf)h8^Wz!opiLyc;?KWnV;OLo?NQG_Rv%|cSemf
zFTXNXF5>cgGWGOShMSz_!ODsMCA<VI3m&_ibz(HDG<xZ;BXh5#Tz!r~j8VaqFUd=r
zq|bdd%X$$p_2@yVuE5osGWk2awysz!oa!DrWz*sfc3cY>POVzSr>_|v%;)gnEt^HU
z(3KXUkFKG+&9v=eN=nra?Q?uS$IDM~cB_u|$>i?N)=>YJEcL4|Z!vkkxpm9akoyvo
z=RUVSEj10l$cs%aVY&gS0nZk$^xV36g?(^@o|f;c)@2hCmTp?SLMQvrhV9#=TAi81
z7U<+$@~e%0ek1JHtb1$rnDuNuJUeXa(xOh+yT8sc?_GKHxcI)?A-$^(7~lIlV_HCO
z&7q!YFMh61ZU{K<vi20W?Baz!+b_i}%Qcy5dVb@pQ-)7>pM8JiWcnPj8!s$=?V5hT
zY}bp@rKhYLl<k`?^(b#H`#R$Vdy-6>@4B|8oo;XTPF|6^V|vuY+Y1BhkDQZ=_gnli
z-7@B$f!XmUW&7)IT+&T{sI4^ndF_H{v0hl!)y+#U%ULj~DVHf5G0BAQR`nCks#M^e
z^s$U($&pq5w_CN>9Lc<FC}rkgw&*CU(dy~4yrqmkd9@!-Sn+F7!u5n7Q&u$|ViWK@
zwt?df!~CG;#m-q<gp0*H=dWj!nRr;)Z?EaCr+qSeUgSLBdRAy>UG}Z;MdSN!cEb%d
znd@T0CZB%T_p50q^Nf{_7jwdlejgL?d&qT>cT>E4pwI1?hclEr?yi3!p2N`fAc&dU
z-9bN>_p0Q%z<u4U+mocdovhgAo_c*?zSkj%{*&{rY)PCQc1GsY<trNbImexOS)cVa
zeB&^<$?oanv*g342a|%{H|s6Dq9md@C&aR7bFRkUr2%<zVNz$G%gnET!u;$@M`M|<
z#tY6nvlN`#wRo!^^JYjk+8mqX&5~x5GrhxgM!I+6x|D@wJu#_Q&HHyc^nS=V$@OJY
z0^1&6g_)M?0&*m!l2fIFR~wz15;CpkqU^5tOO?eBmx_FAoVz&j%N$F=t_2MLG@i@!
z@T!J<Ub^elQ4v{&S{chwW+qpS3msn$+B{IYzLHmO@sGSs5~8b=j->4GUG=W9{&BCi
z3U~8N>E<PV45{k-SR>Nn&d<0#NBFj4PSMg6rmPRA^p-m_9x~iBf4g3*B-;<I>-@)s
zF3)x`_}6h;XlG&I<|ihP>`m2DCq_o7E@L!IP(81)X&&=|t~0AU`WIFoIV`4_q_p09
zn!%=1$3v7KFA4MxG7)XzyBqXlRjR7I+iTG`7h5~t?k+voHCgTYrQKC`4VLdppAxpk
z^86Z;q%u2`1J$dRo#YZzH~4w;9LIy+km(X_Zw(95tupwTR3GkqcxA4e;kCpyrd^_j
z7JQ2yg-A86X**bNa&(U&&uI=Ht&a<vmL<(Oy}Ebl6-A}IYCYk$Eyc{P9{(0NTb(z!
z+Qpt>dQ~PYb=|}0(xqzQ3nqANH#)v;pXTJf4=&xyu#;M_E%)b1CR4UOtufoDyx7h^
zGwczU@8?_o!OD*})MhJ}8*5E)XWoA1*R?(0Y`$w<p1$=4ug&lO&$hC}J>*MB3i-3c
z#rxAXh51ti_G((kT`iT}!2N6khoRN1lsn=}pVV%4p0MJ00gphucR1(#gY()-%2(ZS
z-JmqbPE+bae?ZZtg9rPcGAn;8Y4%Ool~yh7+MAblQh4>eRWqBbZrC2Y=l#WL9m^40
z*HZ^xnr)2TX0ho;tL(vzjN4}#CUe>NpL@}9C){AI#rc(bSBjeJBHy&ed^C0YHpiDI
zs+}cW)bpO9@8Yk|l%GCvm#JeZd9|oe>O$AW?@!cJ8xnW@T710f*gw@xPhA$9cpczi
zQLqusNS+pY<ZaR$mdOiv9<L5M`L*S_Gl$%?gDa;q$OU!!Y3y{ecvvMUR`XQk#zU2?
zrJrkj+ilOeKe#5+7r$Uy($9s#&v;HqvVGy0D(Co!y*Ra3a7FKz^srw$4VSGt)G5_=
z_nqY>=40oWB6}K*6O{B>jlH}aI3>FI?fO#L4f>eo%&a~0jn(w~?I~71Y6i}a4deZ|
z)YLf&75Q!}9Suy9T6}EJs}*(k)V{ZUsyoB==*<a^%gZOeZRJ}&QD<9(zJGFWW8Q{L
z(Z!-yw_kYPnz29V!L!$bcMch>;d5TJbD`li`$M;nn{ZDHI+PsBnAd!?<Cx^SirHbB
zLb0-ce;6dYTi*@YdS%)n=P9$BrtY*zj*eoVCcVIJdh)S7&z{MutP%5cmi2Ur3A_|@
zQh{N`)Ni`kR#m+ZYqZ14a*SDbeD3>OEb~E|#Zke?LQud<O{-w{&Hem(4pTg34_Zn~
zMpsIoDY$=v)3wGWNlxKOpx~tFK#_=(S0=_R{qVtbUhAn{8$LuV^0rwi`|yBK?)53m
zAI>i7bU*P_LcOI|lB-)OP;ph~Yza<Ish5qJ@jX5AF0#s+?i%-%es_vFyh&x6x~tT}
z=d%9F-LIlP?0&L;i;&K(IcLk#P9#ms)C&`oi~ev|Pyg~&`LZ9|nIn4(7#^HlJwaVp
z*Jc034llm!YemzxoT}V*Ygt*Tw9ye|_cO*TVzjuwIL^+iEjZwQ<B3;$>zaqXa)rIh
zt1fixy8NN}-0M|2CG}Ys4^9>NnVlP3lFrV5`bMENBfoc-%mj~+`Nj@E7Hr)Va->;o
zU58NShoduC1SGHT>1_LuXJ{M9e_+MEyq122SMRuaHFI5(&KCP|YHeC7sVcXcQ;;$7
zcNc%mqZd!*dCnLMHivrD9Wm|C|JKlX{)ngAvy-397KsI)F1VtnRC6(OhNb-HO}Q>R
zf_?|P9~BN};0bTs9KvkKckqd>f!#C}l?BaOcM~*oj!iqfP?61pr?vM;O26T`D8t4}
z9tJ#{vX)iqzB;3+TlVH)_EPyi0rrRntr{b<IZ7$JB<?CiCT!RdmGx9;5%bM?n<tf3
zw%j^@rP=3X-28MN3D#BhHyk1|;})EFy3IuB+R^8;^KXYYY%G-e8us$_i+KyI{&A??
z_f$UmMQQ4fqBV+I?XSAK_Rlkq`Xk9Avi^nS)z@e4q=hWJ*>y;YZ`&q;I>C_4%(o}!
zGMe?v{9sd@W;jzeM%poC+ij0O4LPi@H+V^;2WM?7Ti_q^L0|o^=~Rc+ds9xa`M6(_
z+@t5|CUr8C`Hx_s+X0KMR|P+chpDDZSST*I+~yf|>rsbQMT@0D-s#Of+}0^>C!FoP
zkN;|n`6M^v_M?KxO|$i$%fuDjvvw1{dqpQjO50LZ{MdWXovG_f7&CP>#bPfW`{35J
zTWMZKrF0CNiQ`{M<M~^^_8EFDUAtdh(%fd+tEJagO$kkO^_XUEXe_!lQ8uR3u<_|<
zroh8zo?5O9V$NmXtQ6_GQp#BGR69qXt9L)6^p$|?ruzez>Bv1hl-=`TN$0M9*BTw&
zGYJA~9G3`wztHJ_lWTR-Uw@U=4lcfCb55RXi(<ake(@}yqL#1TI~4;N*I!X5PcR&D
zS#mOQN2k!bwUg3PPAGmXN%&>>%I?K66VqJ5<e&RzR5zZKk4iV%!Y#<BmloddveW&{
zyJ@-?CvYs=rjfII{*f1FuNbu4KA~C^t7I*kuARh`9&>OuqqRC~ti)c1=2@qoGHud&
zni%xOeAzKK?Xcwq3*x@cc=CreV^N0NhgodKmK6(^D+jsHlss`(=doO|U#9Gwn3^)~
z1jo{~tXbMKEvDUxSSTfZG@#d^)jV@w>yrM?XFL*TZYHF#8fCmU*lLy#Fva^#2*Z>0
z52_=to)YEPmQj*A+YuZjvihc7Acxr9U9t|5TmLaJMCn}Ca9R;_Q#0DkB;0+LSDM2P
zvzoOJqJ9M}*fV9<W4|3dAyYCW%sG6g$aB8*JN!KOX-*SYXKHfWFE5j?p|es~U1IQ4
z4wh8OJE<>N)+*nS9e3giOXDoh2g^lPKU2NSK8<C<Tany`gN~9l*B`jKwQb=`NND%`
zJGm=&2j{Uflir22dGY@giwSsixS_T0VTO!|aD=$mV=uFuDKlNPXU;kOZS|=`X;;=C
zTF@-Eu=#gz%WWYpfgfs5Gv=@HJ=B+YS@C%CRBy=z6-|3QCYpt7%*$Qnv@Rw1sPIR3
zj+ft@-Sd{5aV>4C*;w$RfqBP@OB+@s1wC^tNSxEbsWKz^yiIiKkr$p4yC?iAQ{bN>
zq`=f<Zq8&j{aDXLd4W|?71_<xcqS{zn0ybCIo@ornDvVGm86$Fj`t?@oM+IAnz}P7
zU3q5s;VE*fPjq!~y*_`1snPEGrG+0vZ!f+abaToj&y!Q{Wa`w->;9H8tM3$Zwj}2a
zuf(hFS?f;Jd9oh;EM<Cij+bn0sLIcbhc13<w{^EZI{N6^8Vwaw%{}wHr*&>QXL2#{
zDo1%kpXw>kL^&z_Cezz9Kipn;t@;a#*BVCsU!D*Cc?bFxiHY5~HHmwsLh%AU%M}+=
z4o`Y=;=t1szml67u6!&un@lx>Bt36MX0a_iG=1hfJDH_R^w|zx-)?Z5MLh9{h05cA
zcLx&mr)M>9G@9xxs^>l@`pXUPYsUkpPh!pR*`lXX9<kJ$<$6z#Od#936$0{_dLm`(
zCR9b5>B$^fbV!c(%Dp+0x*{ZBoasI~|Mt#lvtO1UpT2MkN7NR{lex!Rj?YpTy(_)M
z`RGNrD~u;68`S&t*14X%sUsw`HtTDmu1TJVnWG{f_q~js8vz}6rg%7ub<McGP)Rz?
z>AK017apQlwEDF9KE35uw264)_(4@hTw3VCJ#PiGwx6t5InvtFoSkFYgH7c2&hhW;
z^8U%R;GSDK=Mjy)GcL4#K6`1F)zLTY#hZ-$#06Jn9J$!H!zEQO=#55Q$;!*s-4?F5
zjMXi#ecE;Li>E?-`mA}kOQa1>opU>N%B{x6Yn9u=0$=l0V)K70-cL*WnY(=MoUZ7C
zY>#-(aJB0}+h%>^_wbx}GF5si*QG1-7hQ_UTEcXD`3=eDrBUSt+NRGY9Oq_SGF5Mb
zin)i{)qN?m4^L@qJKB2e^~baofjqybZai#sf%jX;39Z1x0+TMpw5&KP<P|J@`|xG)
zy`N@8%j{n65-uIjx%$bHTQxJ=U9PEJm3>zE;%-oPL`BInp}wUme{XZl%9&hpZT9v&
zPKQLNDBB&cS}(~>V83F$PER$5TU&-@fA5{lW9bgkNpk0n^sKd3Txu<mca`J%Tp<$j
zb54%%Z<DR3%}y!uq%!-hz18_LVQ2pAsi|#FK~t7LGLBeazF?OY&!_W`{kEN4;>Yr;
z@XD`{O`Op)_IjO`GS5msz^7|1{I~7wd)`k!?#$v|-;<Mn)*|x9{~P7X!RCc_vF{J&
zWL{a7<S?@;wD@W1GiLkb`g!Met$G?3n)R@_%OmmX)@8}u*94wKMlb)k=xW=>v+Jfz
zQ<^bf+yCT|Pd&kpj8wHluX8Y*6YP`to26}#?2x6fT(CM*ZMyLShjnX01YG)5U0zj8
zd%j`A4Ds2GA0BLKiaB*H{nUL$X2;x$;PRGK0n4>~8qy6@eXTRq;#Tj}nIgr#cHK;|
zs*OeBGG&fsCye&ao*}v;Ak^Qtg83iMvlWZ@CWbP+JhCcXMo!^RLGa2z`3_rS>(tkO
z(+`D(IBjh_-^LQ0w*8<=+rf+9ow;W(Ue~A0xM%XJopB8;X{&m+xr_GR^LXHyde>vN
zWo1(2@<W=}Tj!)}eVH6k@^+>H!|P=&jM-71WyRss8&CGOFFW>H=-4W@8xr+AcH1wm
z-Fq<V(iDc{PiNiOo99*fn=#T|W>ay`TX(LxzrHan5~(^P-j?RE_JAI%ui1vwnXA%2
zZQ-iEb1iPIftHuo>M3)66}UfJcSnM4;%e`9{Z(f7`#v8OWxQNz9DD97+rdVbHohkh
zy)5L8h#ur=%jr=|)4B0gI&X)8ltrR%2)Ds1$+Mrky48xNcdR>6rY>8mV7Sk;C}D9$
zesHnDnm2(DZ*|CSc*Oi6aYOcwGukW57I_;AuQ*b)J|Sd{hwwhJM3G{xZ7VVYVrJed
z@>9v!xkjt6we5E7=JkBf|2?dny7X11HeU_1lE{I5M|wW&d=fn2(rnGELEHyFUo@F}
zF=k<Cz=4C$gG84)ELk6YsN>uG0_WLI-O7wl+GY4Qe##7;yYePK_dl<RMgrN*@+EDb
zCQVx@(86`WA*^~2`>iKh>Qff!Xl1Q=J)va}Q$eCvfT&`1M2h@M_oydQC&I43d3MBh
zrR2K)mPre}yEpYYOmST-s>$ar-LT3pj_H2wJEj{xm&Dv;jvjw#;1C`3kYn!_4o)xE
zkcqQ`&u(d)=Njd^S<Ek4=Dqk-TVKnDcRqW9gd4I?a85GaI_=9rg=GTwlS7IZX~(XV
z4u~tzl0I<i(Ig8eX9G88fv2|@ZR^}|Wzy7FZ`s3F2!2!It`?Y>ne(r?I%j*G&+!*Q
zzM+~8(|37Uthwm<;_Sv(8g0MWE~>?cKM7L(@2APS_u~((Z7jzg%-Ob^r$x+_xk_HQ
zXV-hR=dJ(5gjjf{bUoId;TfC%^p@<Gb(3ENZstih@ti%evA3dW&Bs}D9lLlK540IY
zu<o+R@K`pTyCE(3sC=cEP4dKp)4W@qk_ui+Kbw5);R?eDjqgu156@{3um54>lF*)X
z?tp}8Zqnyd>|aZ7y_~$+UnzLXrku<E*B>3|@Y(aCNoJuC=M<6UueKyTly<$Nl#`;m
z&L+~0?V8eBW6j{`ZFjT|I10{aVk;1i&y){&{AzN;zsW6I9_V@Ot9)Q_^&@lM&a`N$
z!1?7ZW&4lt@b;`T5S|_Mw@X*=k?4%6TVH(N<Wv}b_N1~~@sXLAb)pM6?1E3t+-`a8
z(G|%V6BGQHE*-2hUsq;$s`ssEQrg#o6`STrnyz1WW2)bT5~&zT$rEv+#~m*QZ}Xe<
zp;WDsrGdT3@oV4K#L7n*KEf=Xr^I$$Y|LNn5j}B&;KWd`1C1>|ijyz;#NMuoIxv07
zq{j!6E5on0DxT!_a|u;znmsu?FS~u_v1~Ec9qXS+_ekBd5$KahmAo=tz@_2Cf;TD4
zo@NG3*tO(bl5Cf1bwcvZ!)(oWT=#s;sW=q9VgY~oCCjZhXN8{a4p_N;O2*HqETaWy
zmUH#r+4@rZR7h^v#*9Nd7$iTcoG@;Rbh<g|FtcH;<Tp_>-5t{yUs&5ol!z`kwud8B
z?P8+)(>H6T%5fi2c3h;-?H9lN3iHQ399%C1)Cwm43X;vZ_2>S9857Jyd-tWD;ht%A
zQe(Yn`qCzTu3t?nSE&l;H^1b#yrF#6uj97ib6&)*WfXLFYn`FHNaT0`&%JOzvEsxP
zyyu>|ZuC~K)|$3i$xbg-W64bO#B!P9N1WO1n*<AGl(QZlnN;te{L8_r%%?>6^cT^E
zraBqAmCJ)JPX2gpQ<9^11b<pi?~>DoMI~+q3OZ-KZ7**+u~mxiS;WGy2NIha5;qF@
zpIUe}>UzcxtqZnaO4s!%9z1`x(_7?M+15YFVb6M>ojY@7kNou&y$kLJri$*F!mTE1
z#%8;(xgt#@;P92zS$}e}RO=$HdK;*2N|T!Xh+F&}_pdVJ*I}Uxou^(uwL<BIVg0jP
zMW-4Ri*;otUGr1g$#r1<qk~LMfh!Z$X1!c-*NI_e7q4K(b-{znIQ`BP^h_0yD16rU
zc&6k2c`qgEm(JL>D8;G!Y{Y8k4u(4gs_zVI+Y+C2bI;kf@=#bn&jdLJrrWDF_ZECJ
zY4r(t<|k~jFlB|g+``tV)m)1e_i)6|GSm2aXsfIK^h85RvscSEcDQaSU8St|s8GzC
z`<eEeMVHe8U+&Pov4zidD!YZLcux{*qY}@&)p5G(Z(8xUwD~GGESR~|&6IEJf@1F4
z%iLK#Ev<>QOT8AKDmdn~I!3K>uJX;P4qwh2?UgS*$*mW>wf^|yOt%%2eGQbpgj8RB
zyqK>i!9-lP;jEhLRQZj6JEt&<DVXokYO9o)GGPW^_0Gqw500!*(|I>7J?W~2Z|}!t
zhfStGlMn4amVax*S(#eR=1KjEn-cUU&g9g6^U&qeDei=2R;z+OKKrn=>%3)wN@#bC
zQQ5)P*za#<JTOk()gZ7Ul69-mq6DANJB@c&hiv4JKB~yHRikG{d)H6rZHFXoMVOos
z`FpXIeX~fE;ocu6Pql;(ZewWHERU&l{TcXLag#=4t=riJ8+=~Wn{;KkHyS%9iO75`
z@|_d<w9$Ec?Z;(pJLg<<3R@Y*S0Ti-fv5JLr0?W?U91o1Y~8bO&FVr9Vcxg1xO?~b
zYqf1S!_IK_>7izqh^|Tw<!4jY9shHdr^}$XGVVr}RE2K%Wx=l1ljh6(z4GK%|AySF
zsR_#i|Eq1~N{BKlzWqzWySY8m{Bzspppcr%O+lN!&Aha2^{IqtcBcULo@w3xHnnD^
zd@>1F^-@dPmi5W(jE?JFbK&SdA=y^b<og|A3r$}67!}=?dtl#oX=eDLwyMkGx{o?V
zzMC-Z+ZpgQEV6iF<DNB-jY7M2mbLz#W_0*K`j)=C$rmDgEIMCUEE8OQCR56L!7Rm_
z>HloPzj57A{3s!*xcA1N+Z^w79_`Gw_KD2f8<>?nDR@`@RF<A4lWsRZSs3<d^Msln
z!=9OYl8RDO?!Rr8Zq~RM8|QZ}P+do3VaC2?yQT*{UYxe!-42uHh8b*)_SzQLPfR)D
z^GvAW@rmX~n>puo@_q3BkgAnsSeddyW!bYe(>@%QxNjpn@xq}K?T+{57fzL2d|NWH
zWMcy3Ljl{CEwVp~7IkLKlsPT-Y|6VXPvO+?rx(7NJXk34^-zn=!m1+AGmM-E4p?h^
z?Ftjy_%*}ull!8+sU2t6sLnjL+SScDMd{rI!&>vg)SkOC>QfXO^ombfMHViV^m%bO
zU~cA@p2G|JTSDJ5ojKI+e)F&3JW=JED@xlK4s+T*T9&Kcy3Kf@#LlaW_e9)tTORJ}
z@xJ-Ah@{)pumdh3RbiT5Ta?&-`fNR0xz@6_u{9<Arp)9+Y=Y_{e5Z~qXP7bJz>=vd
zle&^NXC2wTZd#0k%hnUY%vUW<lh+Ecomi>Tn0U_R;)_>q_mk||b`-RpQZ|(5J=~qp
z)6I}GMcY-I&0|7`XXxgaVu{B#zqCtc-JgB*W#VN`;fk$3RS88b4qeAKFIC;jG;_J(
z^A&+ITTgy;-|?1d#;pVYO{Wz0e7$9`?8ED}dnd2-8vTy+(weyHM3cYig8wmZ=C4}r
z&?0LPH+QO*pT&<QM-B&78XlZ^Alfq`;!dIZB8Ov-mU&H=5-TzEjb0g~wq}*st|y<O
z)-r8qb~VXWQFb%^Wl<78DLW!$YK8O?rS4^}7YbPUj(svUNSMU8wshW^taH;DWLMtX
zv^uKbW2A;=gP)sqi%~JJgP4-bE{lz&x999y>v{gwwTK=)9;f*Yi9yU!A~JhktxIJ$
z5$8I#JuLYFt9Ba)Yilj1Yx1l+p8MWi<6zltl5aY5tN7E&QlE=uJTK}km{uesr0u1b
z@5FuD^Dl$X2Kk3Ud6L{`)^r$pH@z&#k*Hf%xPRh|*;@}T@^|M<Gt|FncuUG#+M?~N
zY;$u`#4)>;9o9uh?A#Zg&-$#{5%auaFLUGO*!H@cn*6U;FPp~VzQg<#Z}!ebvmAel
z>2)P-T5<OLr=Oj>8lTST>5%-&=bL#dNXWYCqS!&bRkG5CcBwIk4jG>E6Q3j9o4GFd
zI`<cz(0lr;ZM)YpB(D2fFMnmtt%9r@-ySh>eBzB<*Y?J#Yv0o;a%aS9+_=ii?w;(h
zRG;+AdXjm~4i*7({%0H+6ZR&2%@6hdX1QMV_nJS9$u)5s1vaUDVR1a?nSTA(^%-g%
z8r2f%dK*m|3fxOID|n|S2yqE3+6gWZI~*nWD7oHd*&e0)`R6nkjn=OZ4Y;*XHg8YW
z^0uIcf=8*c-VaTBZ<-}3u5{-6X3dhYRL<;Kpz1^cy-?ksrW^FuY8b^%p57DUa@mI`
zYuUu(roWF>#IKZ3R!Ph7y0*}1lg9LjxtbGiuF5Yx<6b#smEy9tZ94s1Y9%aAy^D8U
zwewv;Vb=9SFSLB0-dPYkE$vc>V*1?aLHk&;?RXe13{n(yyfkb43{J>!*IMgGheoKB
z%k4V)N+5IL_jL`bPnB;}NMFCXBj-$@`MODqSqv>h<{XiTv@c`a7~(eZPUC@1mVHIq
zwQ*TaM^_ydJ${-0Sbyf3@Fs7`4T6f@>IEW^uOCj?9dapgqWWAOrHjH0mm)71rcO24
z)^}d{&i};$wvUuA3d@@IpGbeRR)RU~qW+A8)cNYQ*#-h-EC;(LT2Bt$Cd#?2jQc~0
zrs>66PoLOz+bwrJ^4Mf%{6+j9uW6G(p67kG9ElT>8{}8Txtb?Et6I5l){hqw7rh_%
z<*;m%W!r6-(~-K^Y2~&jI(svwDqp-B8ueW2^s<wWP8&^0I#UzI`uvaJ4`sH`FM8iZ
z*fjsNHhUI&Fml-;9<Mdm{fzr;R_~3|n6S?<GDP!iictQRkZc{3o)3Ehqw-F1)%e~E
z+ikVwa9z4G;}tJciJj{U%Nu8GN<Z<#iqFKiB>j#}T-3RxEe=ZOr$nC$+H~A3dEsdl
z9_5GUj|oiNE&5%wJH@^uwYlp|-jPp9KQ)qzT69})c-YG+7z!{8-rl8=C(D{>_Tz!?
z=d4dx*IeFFZMl5+Vm`l3RtwTBE?){&P}>}OeuLhG^S$1Yu5pVNm3qDE*`tt{nmyAd
z=yh?Rs!qVkzJD{1sU`37{rD-@z?iGH%e9c_7nf*v4aXCu^D_<0d;P5*9mxrwpli6#
zVejM`zcTab*L$Ds$Z?TmTT{E@L+4Ks=V=BN(Yi|>opg|@kgPkw*lCyhlWUr&oNS<l
zk9~YmbceR-bW^@lTAj&<_LeIOT6q1rd1G(C>SBqfpVKuK9j{T=w<^3-`kFDY^6Y8B
zPtqYXmKZ-doN+lU!9w-)gA;c+BUh>NDDz5ru6ZtU=UEn?y;En@Mn(bWRelE)VzSrn
zb-Obo;q%Ua6>VOTtn)1zBn6&G1YfwT_FQb?Cr#;_yzkAqbB>?oPVlNxn_!su;n1Qx
zinj5OEBrTBZTz$%GHg=#^K&y+GoRV+bMW`7VAZ*=cSQc{N&cqxh_Caj>yaNZy9?eh
zcqqON&G|KvU*huOGVK+o`PjRAbUb9%cc154KJCCEcJ@r|`|K0@Z>?0`sb#Ni@pFUW
z;jataWL{s0l_^{{v38?gP?SZf*_T;o8YF|W%#8Q{ny^JuHgQj$__3p`b@?ud2Nyj_
zIpkurm+RNPt*sFTqFd6Jc{}x0K7S>!!A#5EPp2_}MKL^LmV<_HwB@d?3)oeqv%IBs
zSN3(52^ZZvp&S*zM(6l%ri7DC9$sk%lizM=D3PiAy!DE#`^xnqf36)%aeH_}V@BFS
zy&%b50+*t8IMuAav};;a?W^#{%EOk1S}_xYy7(;C)E{_jCvwy|+c|-^=4p{`R@2g(
zM`Ib**+2Kz_<SJtT4{#caqX{a4UArI1)09rdK`Nv{Z(eAQD5wW*{tE)yY~8JtP|Md
zCGNWU$YC3kYE8MIrT=6#U+<adCq8APw0@}5tCDZ$4(&XmweCXs#EBgL93=0R>}yo`
zKP~y2?j~))Eg1*98M79P$_eJ>cX%J4%X}hGTej+}!Aj>Nj!O-L<R>*9e8Q61DkZV4
zH04R?k(T^JSt&6RCaafdI6j%?wm2ZyI_5}Buepw}{W~LV*M7z)3L!NP{h`a}-E(z*
zA+UJ1ge;%-gku}#nN5{DQ!6Zf>P^psWfzVeS@%Fod*^f>HWq20#lAc1rNU(|NNk9l
z#3bhO&uPy8OKXIpt8dS-UY;7(Se~R6vdc-i!O&NYU0_N~3-3+qYr2gO^lAd*++Nu}
zzOnTAu|1}{7CdiAn6^hSecPsqRh}h5p`sBSSKe+FyT9NX)0~rks&t|QYZ`vY`1~<{
zr)>7<yhrc4O*6RPZCsJ}z^cgk*o76MTLZ*+0(_LO#O*vbqlM#zY081ei&}z?+lDWY
zQFiH*IyUD-!LCh(v*i_6AG_Ie(9BIsS9_wr$nA((uQFXO%euN7=9svh6ioh-#I@jI
zuBwv2#-<~hJ}q5GW*E-CeJJ%ISMzb(Yjdv_y)Io=mlLWr&7k4ZqQI8u!avP{rW5s@
zJe_>mzVt|)^6C+3j?7vf*qPhnBj(K@;VeB(#+AD}bk>*L#QD3{+D$$r*}3r08S}(x
zK}^T?YgkI>_KIoyUF~vGZf*(8&<ry_|6uQ8oiZK8qA8XVdrq&pal%OLp5K*EEH7Tk
zSxk99&zkr7ss7+~FH|22)^vz6d;0fFGuvO?uJR}<bJxRzJ1u&@GR94PYSv<NzbfzO
zi5n4GY1KSNw~UlGHeOzLbX(Ukp+cjtFHRpeU%rmz<<p3Bb02J2W$L@ywWIB>yRwN^
zlfO<#%CiWiFr)J($>Ig=F*hd()g+uq=y-T4AXM*?r?Vn^=(RRw0W+bW%GK>(f-m}1
zC>NQz=-w@;eR3<gRnzLF*~~*56l+u(r8j-O+#}dnxTtYYz{_*uOK;>a`fhe?<E<_F
zYSQApmnD)DZ**@d3FCTaaop(GXU%h0j<oJk(!KfksQAJ)bGnruW^i>IicUPGvtozA
ztcK$rv9mSqUR`?4l=tPS;`J|W4VFtZFJ?Cj=yTgQFR|=YOWwW&jvW$8_fn!bny1Wg
znO>~+?LeMb?$Y=POO8yKy6IQmnO#4$mUxJ9E<AYXhW!SvV+(G$b`?~m?P)0OY|DL`
zvNLbh1I`JpC7N>YgS;B6D$Rc^e-fkORAubn_x;>U)kPX*x%v|>Z!9UB_U?L`8AtNw
z_hJ`X1Wb7T%s=mOL1#&cAMcVG*O>1p%-oT^a%;HP+{|SxQ(Kn(o>XbIZ-e4g#RE%!
zs7f|IzcTOeUBNV7v)MBDCcYOx&$#+Z^4$!+)P|!*Yr-EFzTLDV_}i(#VAWL<D#L^2
z4;8L5lQTNql+1i8zN>5Fk?m5a8GB5Yv#eTeTD6U1YTTz?DY=oy#BwXnw@<hq^f@-+
z&bnK_c3y~yd!oa(qi7AQ#kp%oRw?;hu5diF@K(c?cL!HBO-!3*e{A-KsY?ag1%J#o
zPQR6EQ5gPtf!G0+*$;~n?`3A?XPb(fTGxKQE_=1KKjxg^mHU?pnk2%C8{A%5u57p#
z()%-&A#l}|uoh9(m$R;4<(SXgT;j^TX~q)Wc?qY}4lXwoJ<oA}bH}D5mp*-tj9Pdn
zY*DuIrQZJ4Yn<&o!<vjfd0f6Gtj>K$i-R|=g-N1Sd&P_&nNyajAG<tbx%BfX?kXPA
z2Yrqo+2f(ro2Y0Yx40*BKePE8!>;g0T><lycgibwnkLDm*zKFMZi>>2ZA*{q@lQT>
z`mIrYT6OM?JV}$yjQcrL)IT%{&2J3SKEK%{x2^e9pX?<Q?-a?JJK8p>8*)pvEWOyL
zT-s(fJ8a_a30ID0&NEjJobs`0p_@~xTXWd0Z$iuU`AQ1{xe`}9eOef@G|%Uu_Lfzr
zA};BEcIbY!#&_Rbt7&Dck9F>kzS!}a^X2cN6k*0Y&6^`Q7pypBu)(yX%JSW^02T|w
zwwU>WQSTRB`|xGUI-AoMKJ1h&daO6~A7l0j@1t2Ol*^PR{jodk^v77Nex1vO)mJB4
z_;QN|u9|RT@>4J6^@g!;ZRW&tT@tzP%wWUGZkkms$Q(0OrkSh8X7Z<1D%zs6f>L-x
z7pgroOJqA2yC=qL%9X-cQTCPzz1mYRwI8UeFf~sT4WE2BQ9|&lN7$8xY+}>;&pGWV
zi(%Zc_tu9in{F${eX(25l&I@<wQ^ZROtYYRK;+cqSrZ~<1LV`04|cqq@IgMGYwuiU
zS*0Uf;d&3&#nd!RFkG{!@StYsaqgKvO|Ejv&YJ$D`P)?Hlj;ejTO2k#_kCs3Wcy@y
zVW?o9FV~$fek?Oye0^ABl6Fnfn@L`1)63~o=6=7ZA7muA@ulbuO+UeY&V<T6t4^7S
z^V}&HdS-B|p`WdG#f|(9=XK791lZH<HvOBo@X3aX&cZWoy6a|^Ze@3@%{mr$WZIb{
zhfn%3-6(n^bj)YD^S-+#6>(Q5Ez}fVCcU7oy*qX8mOD{x+RNM(d3?3E==yEhHA8io
z?$LSA{J!KhaL(XAsZyEzXWyYpuG+J&wwO+xE?FJ_c)ee3)#+<BPKjr`ycaIySQFML
z_x07nxTTL+SSJN+urn=s%Gj7zxL4I%D0Q7v;lo>Nk~6hDxz_e*yKG$3qg(hYefi&X
zq3Js}oOZqDw_&1%S#yKi{pHs`3#{yKZ7@y~3+c=Xidevqc_Nqpkosj${iPGzE9Ycp
zrMzTfJk@=l^NnL9m-ES!kEO4;8A`WnDaCd2YqsXLi*;*7g}F?Vd|bCw%}aCBs(_8F
zbDFFqmwpP+HIx%fWx4Eo+{I^RiJspxopoEYmM*%pH15px4Z(dP8Z)eYZ2uTO?fr4s
zibeI)rn9EgblDAEi*gP;I=yX9iiz5-zEkIn)z?pVTz1^6QnAxrhu`<e@dG?=J<k>~
zG_LlYdaO~_M_Gz<YoE$$1O9bhuBv_>`x6g^m@K;N)_y4Db?1h6O4&_KnqQ^nMVt4D
zdiu?|utrJXaL@0KmwbMiSs$Xzq7228HfFFbJ9Xjdq^0X+>Lh|!ie*>}b^8`^?2puz
zX#L$5x$yh5g-UWwGk!<<aA(X@JM_q_@w&{_b6yq`FHYqY@7wuIBhgG%@Ku9NZ&t^p
zpvS_EnuU}2&z(_CKbx<TX!`P#L9~I>_5{A%4#$n%30}9$e)+tvy7@JsZNdqO4SkmX
zd8%C{e@uy5dr7AG-Z|yIyp9$>-?Fal7n$A9nHYWEdF{5hVNWVc$c&nKy@l+&tc4|a
zLKd3w1}HeSPt{nZ?9TmJugSkj>@%a?(d;1k+p4zi7wu;3UNvC?^W2`9vEJ5^X%FMH
zz1w+a%75?VXxq3|Gf+iLR?)0AFoVlDeKiYfhSlX>Juk}|;k-rHIHc8dJNmliuf=w0
z{9p8MQQO@6Wm_d#EiNXTHkQle%nCi4lpws<_M)o9q@OEx3!i*y<*_^UgV(}!A0FN4
zTyOoAvByCE+lRuX2RDeBl)ZH4NE8&zn{d5<<C?=UFBQ6u+n();N-}Hu%I5tbY?(O6
zz7DzVoG)(~eLeI&!XWI6_lma@r!=o9U;J!J@#@=#e9M~TLPL60mU>*gI{%`3V1-xj
z^?-kqm(25bl@IHFd||@PZoVl+NsoeRq@1oZwzr;{@?uuN$92lbCvA;&TBT^rD0}~e
zpy!)Mty`2UHyq;=jx{{fY0bbN(Xvylb(y-${izH3S)Tc<a-PZ>J^PfvuFe&{H38gK
z?Tc1LF=x$e4QLYidUzAV`pkD;JnUCp%`!VKZG3M2%w~~XRR@pC+!DvIq*L8I3|GUh
zUb%I=A^AinL-5zDN0#4~do(TG@_^^EU-v>*H807ycDu8piC3Dv&1j~}yC|=B`{w-c
zuJm3b6zif_p7XJp+sE?tjG|R9+!SO=JQp82*^$b3Ia~8h@>2Fs@oLOFGxjw0Y};tR
z!SJd@t?4rJP}PW=B?WOe+cq6xPI)V_S$5XkCx6zTSfg80J#X@RS%K*aQDJ)CSHn*V
zHY)aK8`eC^YxUX^^Ub>GXAiGg?~#e-?6Q^Zd+Q%tsPO9@ePOL~u1Qt$WUe~5(I)YA
zYx&=1ugsa8bV~QOq-^l<Y$aKRZL`ixOUyRvc5O`%boE^qRegN%vyfGn_FQvS=JO2}
zvb=5F%I$kEbH)OV2+185{OfOAmyEx<Xic}-^>re*7G3_pBWiiaJ~gUq4Nu?1h<nrS
z<yYARUZ`iT2u}LH>+qK=4ZkEjjEthD^*+`KvDmM*qa~3m^48luy~|FhtXIgD-{m57
zSXimY$Y-(Yy(N)>Sw8bx7Bjv48gp$|;UnfvS9{#ApAG%P_hGZr&nh?NWumw592Zm<
zOq{!1q;c__jq77IxSuYqS|a<vqlI&Gv~ZZ-<|wY0S3>h1zh*4&xS`wgpxe<$`04)-
z8hdBx6_=T<QoX$F;3LDA>#scFsfm0R`fN&+)5b3Auu$0pN2Crl9X%cuzbt@{+cjSE
zG}jyljv~#SSAO#;`)Kp9Rfq(NB`uinpmxnSLDs!Yr~5U|WqYapyKqcU;+f-2cN>|O
ziEfjvk{|L^vZh94v6ie_`=Kf7=tcGTSA`~fgqtI;ykWWSe9|xHO}2%v<cyge?NiDR
zd@Qu>*~OsHC3qq2VAd4TZH-4;+Bl-k-$<J_I8>;wimBMO=h3dIOWq4FJI=Li&Lr)<
zEm8{>C%5ktTz6oJ=+qiRf6G@a-Fc>kkCKA>CA70XnmG4xE8kJPE*I~$DJFb{A9uux
zOG`X=yqa-)?_2BqUB~?w2eOA9aN>J%d$oD#T<g&A6hCb>>G!vG+>*I9t&B}r^(a%4
zPJnS@=V8lek110o9;tqEge|mHOyQ8of;k2|RsIAw?g(Z5Y>{O8u))BopXXRmpLDO;
zqvc#44v$(5w<rWl%gsLBS+ML8Pi&>WWk<38$*&0=MOR)PEjpO&YkTvY*3nPydpOQ;
z=w@#I>?0zis+F{LFWX7?1I&}lRGwVE@T;A%b4tp)4pYvOSqs8FFK$R!ucO7y|MZ<n
zQR>lcH*cJ@Sk<1HJxfYQL+w^rgcnD3x2SdZlx0O4cZ#gpl$K7Kx#kJ?yP9SBzr$|w
z7>nh9bh^YII>Xy_RaxSm(;SgnLVK+>vJ5w0;W;jRe5PUd)kUe15C5lasqR^{F(RmQ
z+Rjtlyn_0lrimVz;#agNGSI^&Y~uAw(O`LB-HT}_1TQY|>&lkrnmQlYw`ItU>nX
zV8#&BRd-Da0;c?M;qZA9x5zU%&Rt!mcJG4-m!4+{hawB-hR&OnEwRm8eU?N|!Znk^
z16!Y&*~zOY@l222TfKbQ3p14kzLzt)v|or%5@j$dUNymqF|>4Qn3T@!&E0R;7g{At
zNUwIgn6PGHF58CG(}~gtIo3?>>nLwLJfUf#@9I6wKfce}p)cetAgg4>xy-#ad?TAg
z<i{k2ie<j#rJCXA4j$v`3G-W%?$G7Z=ae?LQSk2_Hx2Womop#f?G;>}W>f$0RQ6hp
zr!!b4-<I1h8mh~8qapRU<Px6P?`21=geNAxf0JmEpmWjb!{K1VfbNLiQw<G{DG6pF
zK7R__{Q9I#lfA?l7@V`hx2S1%$8&SdnDn_=?!nnxe^&aw<ZOGYb-MNIiCTdsvq|+c
zdW=7<j@UR={gzr6YffyaS9sP@y#~f3cehVqI(axnx$R1lyTy#KI*xNnzq%8*vOjxq
z{raX^tC$~HifpVl^XXe7Epheq@`(}(Dh39{h7UH_v;ChJHg$$yPiG`!;<G(314Gug
zznj3cy{L6l(^>uGii;UfuXz|wIJGsg(T~eP-G$Y1^`UbGG0SJJJ{3?jW6|A`DX!L0
z9obV3>dxD2I7zHXq&*~I6Xz?&xuNUdC-!cwQ#A{pQf4E1E>)C~XWbc{cOquNYI7N+
zR~iKu?2SDWV037e=*1~BeO8|oitt){(8jnXd(EGm7e>c8oogp{y9InQSyau*SloK@
z)77o~=jP{#8HVo6d}wI0d<VZJm*SpzR^qE3)at!FZLqFq3wtGp_V-B-@-rqMb6UW9
z^fCu`d}1YIS;gs#+rwFAu5zuPrmfDkU`BgmL6C2#Sxjr;N2z11@2$!XKb>`{!PV$w
z>a7edwyrNiy%Lu+>I7Xi^TeJ_;qY5Ji`Dw$^$mYSJvq~uHXq%b>go_7@mJ05xsv?h
zVE#>KTeL5)3S@eh-McPbu_R!+<$^Vvd{vbDjvoG{UAy-~(j&IEBP*Fz!!#A|iE3no
z8TCzkB6)3Q-;Xc)5;t~KAKq?OmG@$k+8M(QovFIw;h#8XJ$7>uovkeQtm>___|2tn
zk2XA(xaT8oR+7BPPsWh>`i9BuuMdP|a?M`2Mda~^CT=k?u1S0`86wH=oP~N!c=ODJ
z3f)=)OTx??Zr-+GIkxiU4T~w9$x>IXdv1B3etE9wt)?U2^fw>p-MyWmZjfI-XL09_
z(?=r2UVr6qPu85C+}&mQGo@8ydO*0yq`j7UD|`a(hh&)?Z&6j;9Oca8!4{z=&i=${
zlVTIYwP{jjU-g?!PAoCfxwOk>iuRh|r$!eNmp{I_lJ)6=ZthY)>Gge+w|!Q<yn5|P
zHYKs$Z(pYB_%kf1m)X>o*=G@}(9rPeV~$Y9v9r<>KVGyoyUE_oZcx#E&{m<S`CZhO
z#jKU~j60PSr0>aQ`?r7Lznr*~HTjle@sSPX*AATVozKl3I+N|UMYUZ*?fhGFc2_Pj
zbSPTsb$x48h=A=%_1^)9RE;@1roK9SMBD6pmT`cV@kFlWA#3y6rZqn(h`lZ}bHep~
zE0|cly91u^Jq~f6?se30LbK)f&e~6H*FP*M%h~e6)QvY$Q<7(wy!yK>XBfY(SU6K{
zh4dD6Nw4fH-!J(dU}&1~M!c`>c*|SWGmHYK^X4&J>g%dsvcaIPKS(O%(4}1r7Yf1@
zOIQydtq{-JCy;4U9%W-5b?3Utp@11u(=x5p3b-yTnep<n*$aUi0n^kR@~*AX5?yMy
z^zvDmj|Iz8wUXvbT;t<c?~}d2A@!rxl=tvG-)S=pI^5hXgxnO47n#T`F5mX`)MJJ7
zr}m{-Y4I+4E%<Xv;bdn$XP>ace~jnlT!;y)Tvr`Ebw*S>^D6J_yHwl{|9vxIyN5wS
zSLPebLiR@$iCq@k7g@}Rm?yzz_h_^6XA##!Rzb#EDJ;i2PS^*wBt^~ixxTg|^{(6F
ziMsOFPWLSkSQb>?QD-ny`dg1gNtWc695;!j9Ghg9^{3s;&pCfOYGUZb%~$8$(u~&S
zW{SL5rWs+%DBd)=b9cguCh7Rqj>?O9`j>1Kcr!ooq<^li@w!)YkKJJxc+@Vt{_+lH
zXC3Wy8wM_qrD@NOyx}ql_M3e6M9Pi^h34t8n~lQw&#hU!{ctV2@g4EdRizCE<%Y(q
z{Z_4IK30%<U`s^Dtiva=<tN2XJJg}XnR0C56fet&#~~qZz6*VIDnvOJUb<2w6Uxyp
zm$>k}YLNKr&8>V4k0;sgKEraB;oW)>)<t{~i%WHrE6<$kdoX8pyhh^^6_cqomJY4O
z6XgPQrfxOQxz?eoD0L$sO6<ca#jlLZ;)9I$ettBUKc+DxUeD{xoKJ_&JQ3nHnj_t}
z@7;vQ(_e>f>0I)#DP*IHfyvKf+|uDcl%8asYuKM)wtA)WyB%FS<kj99gck<n6s`R~
z;aSr^M$YtE>6TtU)^5;MscD$#G^O^X%6UU}MJ9Fe9}#Cxi{6pn>|?ZBNqI$!;J2RF
zEJ~}=9v4jW+G()EaHn{if^h#{wIxeFWJq$dEYk^o_(Epc;)zGMGcwDa{*#og+m{&3
z)yaQucEe!}zAabY9B0_!E0?t8lb_}0j@@q-IP1tRoEG5L<bUfvPkz)Bt=kp{))lv!
z=3Px%?3JQ$xO9ojHIqq6$EW>SzO6j&$c}W;KO5&(>Fl2?apTs`>5l_)A8ASNzwKc&
zZMo_!PoauWUeD(#@8h_kcbTO+utxN3SZ2yrCE1PqPAm+)*WS13svbLdFE(p^h!?Zf
z#H>w{BJ<pjt~kWT?#rhWe_CLvMoGf%$R~;Fa!<0FrU^1yw}~Cxd*<-R#y3(5!ilPG
zYup~(c4Yo+vg*RRD`(=SmfUTLJ>!+SbIk>om_@=<Mfs*=-VOg^F3~Kcdxnk2FR<m9
zmWuj0w|6@$Qx~-#GFJ-9S9=yJzuH~+vij4xI^ioSuJSdUJU!zOC;xVx)?(&u%O=e-
z)R^ma)i3_~!qCN&9&Cx&ovV65zEC##`b{oP{S7QU=XFF=l{2+vSa&nO=~y2YyXb&k
z=E{l)Veg|Ai#WKt`S?uqQ~H}z+1!nKEY;eruYAh5w}eaEZ^g?yrjNNU9(cBlu`|6j
ze808AETN58Sz1|jj)oqpw$xoPHF46Z2R5p9t_PlRus2r*W{K)MFVw!0^Mb+cSXR@l
zgG}$IO)8Mu+%=1htNZ%0#ao1AZ(EBs&X5S)l7Diykm~c=0=Hu!kIXK1%`r=qx6o1j
z@xesKe1VW{p6~-VekO^ttfo@xQj6>wRJNR3Goy5q7Z*peUEIkFBF&kzE!-6DsX3~B
z-L&)DjnH1>96`ZL4*yI_wVfZCq`m1-x+U>%d*RcPmi9uOA0pRuBz?W@5-a!nn7&YM
z>(8x`eyX|r@UL^3A%U}|&T(ApG`}Yx$T;}9`t5Bpns04-Bjzt(Iaev$>ePPe8PePS
zP7jszn%f|7G3>~p(@_~ymhua<Et+6;Nc4op1qIFNGrfL1F8c2y{>dcl%}I@CDNWlu
za@^j|(g{&u<<Kzwyh>-K<e6&EWsh{8NAtcZ)9nl{KKZ;ea>0@hp^C*$VXL0(*x)3T
zz<74Sqm%}dEX@GPjRn0NdkxO$B>SW&t0m4#dbFS+X=0O8a0M&t88)>N1*w9BQ=ZRe
z^6mET*|E0y+`Nyo*T_u2q9T-EcH_!|KfPh{8?}2XCL9etA93ALo?qNsR#Uh4@0Dxc
zKcBl9sqp5*<qpv^>mD5Z5ZMxPp<{YePk5haiBz@izrSwXMWPCi*x&K$ZFq5i(acMW
zv+}(AWz`!4t@4sj@_gRS_TrT3rd6l5zGLc`(OXa!8P-+5!D0i$`sY`!v>nxV3G|lS
zJ6Gy)o6zwK&u(R=znS!H<=oVBdgZCh7j)l${Zb-OyIJ$a&BLXF*%Hgz`B}`4MJ%=#
z6c*W$;hSKX7=LW#T%})}0zEFKAxTA<$7bxbn!~y$Wa0J3hNbeN+8OWbw#=BJ*!D^8
z`YEaO6<@=z?K;!E{Efn$V@FrLnA>sK_Q0Yg@~lz*ZfsAc?#!4}Y$u}3_$+vhxaF<2
zU(fB_G+}!q$12&&ySJUW%dy5@>EhDUSNfvbCs;Pf6b3jPTBoNkGK0%Wj`hP^fx7TO
zZV&aP`!zTw7ERsj<MXf2_lG6t?kAU6MCKh|vvNmwfk5iYcM54<n*!_X8gzE@1q5$r
zYl+edV?6mi#%?RimlHDt@&p*CPG&N%yvOFb{Dh=Om685MpGe6G7Dk+3{jMyuc{IUK
zA+_qmk>WUa?Zn=R>`E^?mlrlBwBI;ywBbM_?-3P=Q>Xh@9FtqS%}zwO+o`y~srBu{
zWwW>%C)-~S$UD?=>5|Ty&e;zyEy(c|3@vsHetx24V&c2c2}aKE+!?m3$Z{MkTayso
za&);Wqq^Up?UPSEXIV69vfRPmhr2ypEvFl^Kicf`xnFc<#kRu?KRx))>M^BHS<*Av
zJbqgUo5Cgz*;6+1$L9rpnwpTcE`*cuN+^d$!I#Y23&W-~WlZ1dFY#IWghJJf6)WPs
z-yMtCa<b#__6?^w)U9UU=<}?aHC1-8UBbUGj+J|s$@afcTAasd^4yAho<^vL{-YYz
zR<Z1l_ZgFfvXYDQQlbJs$Z8$kyftsfzepcJk>ES-6Rt_P9~C^_vt*4>hPY>!!-g}a
zJI_eC1bUR7(Tu(k6{5&>^+)*&--u;l{hvNLhD>7(+*9D=7Au=$uMlJq9`!`&O2CFG
z;SFaE>V1AVZFv#pb1*YJb@AO#Oacv3Dsz^6j1y3s6D%-?v9mke$ic<*)q%Ad8v<R<
z{P=f{BfrWgbE(zGWz#qr4$PL^U4BA5AgAp>Y@1iDoSlwbQ^XP#g`AS3oU`Q4xV2k|
zx{9Rn*{}t3B+uZ~HQs*JPOv&_V*c?yl}-1R^QPI>yt#LD=aGosr-3h5CaV~_1?le0
z=;_moV!w3C(=x4z&2zq+%DoqoX(!H~Uh7&UJ4Z3gbA^!oW5Xvlr-WRTe7N5)Wm=Zc
zB+(dfX<k!g_7pb_69JR+7g}R?9e8#%QSn>s+2#|0f#*!m8eE=W9M%@ecZ9WHCAm{w
zN^o+{()ZifEH#vuzs-HEL@!xRBk0|Yb9H9Dg|n3n8e*B0=f!Jk#rGR9yD;hH@W?LK
zWk~S5nVXZ7EoQp2joH=rRas62OH-22qX0kE$x8hpxe-r&8E#y0Yf$BBUD#Bcy_$V?
ztIS%i35QE(CreHLv8qSsW3cy&BQJvW*M(O~bv1Z)Z9DVR=f?R%KMUGszFL-4DaSt9
zbV>3i{bOA=H&)g?GF3P>#iMIx`QmN2J%YBFh;=GCa|BGwRCDEsd~Mtm*?sXA2XD`k
zRXsObdz4d-R@`}gH0-lq@~!H3iOb@9XSlO{HQG_9-j<eNs%7TM6?i+*vWcIsp`%o<
z!BtZ@=}XF@^~dekvNQ8U&3-L)I{p~DyyD$s%k#VUKX%DTo;FR+P-(}_iCY#gG5>vO
zrqKk`*AkH?o$)2t1miA0Qgzh3VB=75Xx5s`-C{NBy={|c=$u@k+kaN!7w7K_i+m>5
zK6mR&xOe)8cmq#&O7v5`C+!Z)la}oeoFjOYtMF@-i@n^`({H#FQtLLIetPuaVZMwm
z2Lt2wvX?g2YNp4cmzBNrH5M|T)We{Cu<JeNu_*0UZR2M?fyY9AZ$3Ub?K-Q#iyIXT
zCgvv=s5bHz?w^^j(s09D=-(!VX;G`zT~E0$RjI$I++1p*oU-}E$H{BEo~}uAGv%$a
zbv=LeOt5iGeyNYmYT1oezK=auE}pdPWb2X2mJCy`-<MpTq}T-+r|3xCYqIbO$a`$$
zd9));%w9{qUD8#KTWEV}fuZra33J;V4zDP6nIS!Wu9uNR;og>R1<`i4)fX?MPEU|`
z+M=*<r6zywG!y;#r(IpwsCev9+`Cnh)wFHD<dcL&UlL_zbuF?wBc~U9X1381&s9fc
z8f^{IruD0;dj=}Z@=7Qcs#SMv?pS#>k!5iQ*ThwCjV#_IT-4a+qpHd_CplV;J?-#z
zv0PW5r5oaQaLiFY^nbBpY^Agz_ok@~0)LK`7iokk>}yUw$6yxR<7HsnHqmL3_~O~t
zU5AY-HFjLxRBbs;jbAz8?(V`VT1M>>QJq=cNxQ^ds&WeorzS2dZ|O35dSgSPI=9{J
z1#^8>9VOpIX-bB;x46xWOJDX>CCW<qU4Q7yXQ2m<vsF21Zk4RQ8Td9;%**9xOtH-m
z8>!E7q1En_vs`Nm+*d~BwA<XipLgVJ&&#E2XG>qry!~mpWyzFMlclQ!ubZBF<`US{
z8xnCc+Cq0}Yq{yuITuBX*N4ey$r?Fib2JIbO6mIAK0dQ%j@uNTiSzm<#$GZ%_%&ng
z%C^h$&Z~`9O6Kt2ogI^PU-H-M!flIoJPtfEL!{B#n!TNMs`8DA8f$wdSkH=A2@VQb
z(aRZn@m5mUlcvy5B~p`5o>_7D;gqM!-~atTe{X-o$<o;8jW6u3US+wU@MFS)<*A=J
z7HKfN$(!SD>)3Q?vWiXvL!+8X&=q#`U8@_EcJH1Qd$+=KlW63`M;rh4%D8t<vhd5%
z-q&f{Ip@eci^4aZ!u8iD``Da3Tajn8({s*A4axiO{np(0bR=w!OZnQp-z(o*rLQgC
zwdx}8r#Eg3U)fxXd%p4i-hW%=vx|M2@^cbz3tOli++*{PGw@$tS%BiLhfk+mDsDKj
z%gIaFuyB+5hG&UoHpc5&?<{C@e$y--mfg0evp)Ha>j$eHH<E4sD=XMO{ovewa-;j3
z32QXd1Q>*QynmHBq)xfsoN|Vj|9a6?3zzlFM3!B%N>QIA%ve2R=@z3$zbv0v1sze!
z*wl6D_5K|a2~n3fF4KN~CpmWcGEOsD)7JBc!&qW38M4gca_ijqZ)<F3WtEnty~2zc
z>yG$I2QHqx!qVEf@(xGUzYd*aUvAi&&C|Nx&7!Y5N3Q9pw#1Xb&&<-3QvYS%TX2Ul
z>zdWJE;inMb;fg+Gvs+`AD?heQvLWI?J6tP&sEFPO71wcY+N-VYm=#i|LbFxFW>I!
zQ-AhQ)8d#)OdESq&I?5e4n59m)5KXK%fFnmJE8r=qVVRuTU=}b%nL7UmA})oI(*7e
zX>M`RkGFagw9-~zyznk}^U^a7MnN|xvwk#?HR_kvJs((Vb<gK4@2ME)eHQVuXXSOK
zbG$im<l@t_)7N<2-qp)LU6S)`xN!A5(btI{ysK6CS3bR~Ij!TuMWYiLfo~S%IGDQ?
zhBH5XeKG0sym_up{I{m{&z#fh#4deomiKyhhU2q$#jSd&didr>kC@4}&h|f|Cg=T6
zkz$CPuDRRqnN(bHfXBT58|9+;Iu?qron2lldP@F8&vfS6Re~KH;WPFbP1@t6G~pqS
zv0P->k`f7FI}Jwhdu`qEQ{GyixXziPw8r9Uh|Sdt3-aXS#QXw3ZL#cQkY-6_b$RU-
zy>0r+<&P_~*i0{bIDF~aP%zPq@l>RQil}<;meTY6-S4)|D!ZBEwpQY6TbFV3)fv&;
zZ`2G<hb`ck9y>j4<Fgf>tAkyZDta%GnW%sKXUk=^!mb^suY{gbs^qoLxG~9eM~>#F
z#hMR{s!N@eH&i}gymB~lhvesm&~ORS=sD45wztD4Y%TQu9)56k;OAYnJ$u%?i(IE`
ztbANfOWe)QK!46XpVoqF8rMsC^@=WDvB+Z;W>^u}{8NibO)lbaW~-v$0i9P7KX$xg
zY&J`MFk^+^mOQgt5{5@wUT-=p)3iwIfQ<2%8=bFRG;|}=uY~HTXw*7x7PV>JCceeV
z<ZfHkRblC_FIyY7UwI<C{fyAe<zJiMmn~Txp|pTMo^dmu;_>S{Jp9hoNZ7fsT(>^7
zFMQE2m6x-es-Gn>&v_Q}bMwS-W9Rc5&-dwVy?MTMw|=O*VBp-79!FeWt9Og8d-XkP
z7q_5gg7Zf6aI-BdyW1`;R~J0d7=7!-l`m2;DF&}3EjNngdv`HUSX6p-ZklbmY}@3R
zLtCfV$WC1Q@M`3e!mT{9oo6<*8MeQjwNTO^(d_dL-!#tRsvY*H*RQmA<kIgNclyZH
zi8)JTu4${C@=d$E*CgwSPKV6edvn51_N_{kb-wpIIln1y`h#w>^)33%pCVrra#*a@
z&Zuv_E_HTqVe0nfdm_c7H!$_Htc#XgcAZ~x;x4DyHS5o3n}ysq(Gx#>(4TRIs9Dc}
z%O9uoFIpt=Lg*cPqrs~i=frk6F>KqgUFuay?Z>kRCLW#GlQq|O+sDRl$Di1yxHFwk
zkKtfGw2lAC$|JXOWuq@%_FY+^oEV|PzSlXl>VSRe;@7L$uf&yiJicA}dR5};d*5DY
z<+Qz7KXuEU^``^dd!t(FHG(!B?|646!z?>Xba~a@K<+!wcZv51obBm9cZa8R@1}WK
zW``HCJ++m&e&JegK_s(D=+l{d{cJaH;}5k;<9Ix0eP-uLo5Sx`X|>9PuE>i&?!a=Q
zit*@|+L+Z7&d*=E;?FCAkRK^|j%sy|>PBG^=YB6|&kO2re{AZL%@q8;DKL+{S@wXA
zDbwv|*P^WUsL5;d?T+|zXVSJff1b4|`&xH59}Qi)u8nIlJBzDc+o3fR&aHoOuyw|=
z$9csYpK+e=ytam8I^TPn=EeVPMAxx<w=TbXX`Ar3n+-QtdTwW2Wg}Z<p>}80?|pII
zt0mVRZJnaqFi}0arm=GeukYs94;)yhv%lN=Caam7>!#1zUgq1S@2eNDJv!HI-8bzj
zj$$$Q3CH&&EaP|kdHLLu#Z}8<m%n2ZT_t|RGidYe$j54b4b?TC`4)tJ<?xR;Tlp%|
z?S#md!u+d;(n2zyr+)9e&#}fynElX;?^i>#d!Gk4Exz`uQ7D|hs(Epq@p;!18$EgT
zUoo_q-=Fq(!-?+YDSIEd?roWM<bn1S=9i57&X%pwymRree%89Ys^ZxPHLknei0M8Y
zk)5?A=0-<PF4L;t+ZV1_C*}0&*TdG<M}FR|512k?n9Ngue*84k>cwl6j$YsSdsE!e
z-)`lR>;Jz>OfQ*HefRQY#|4}6Rvr-Oty(R)?a}VK4F<c`xU6VAd*W)=uHfw#k2FYZ
z@?IlqdT?^@^G%C#wl|00TJgH@sOg*c+#ZHyE7@yVwD>x5Sid*lOb+mia{Me+_V!fY
z{i@(LyCYlYN<Z8<YgeY|9w)x2kJ-Go8LZ*u-<qQjUp=RK?xux$f^bPTr_jp-C5@iP
zw7jp1n(lx5vURnr?NXL=xh&@<M{_sayi&0x)jHq1oICyK+i9kq@@vjBePs`GD$uR7
zt@-w3^6BqyZu{C>EEHssX79OjII%3ik)^wOw`u$}%Yx9lgqfdh6!d$3M|@W5iavZY
z!g00Px>Bh-8bWra4ot6dZ$5d;GWpLdqk@($r-xglgr;l_+tAV*oV_|wP@+HBcMan$
z0h0>{FCTALId1b{Mqx|qn>*aEnN19ZE}t#CpxPbCvgqC73u_N8IDS@!%cJmQ>75L-
zrZv-2ALgxQn6>KMm&1v_<6_-w+H3YCJThS`<DI~(zi8=ewjB8r!OKs1ZN2*K(DT)=
zT~-J-eT(jqkv5r^Ab9QYxvZ><()?>z*OhK9b7r5MyJd00rkFJgBuyXbM7+Az&*XPN
z^H#GGvzV`C%!2x5kMfUZIovc`<F1>aV1M<{TlQjQgRrS>oDN?6^Kx2`2A4myEGkXt
zX_K>wxOr5~`b8G+)oWh9u8O{b#oN35%n!xgY`D8(Uv%p)H|-hg7KY6~YBtl&z-NJ&
zh`4(d<EHZ$1D#E;)I6z}nOEu9AXHJ$dzJTTYpK^|-dnR5WKD3K@?wYo8rJ7ig7vGs
z%4&W#Zv7P1_pb2k)vV$#(uaR(yx4VE)%<nihQ}<jigGzDuMacr-99yvU&+qE;hE2l
z%O%anxkQtl_XQp2UDoH=d!38#T5W0Ork`HhMGnNW>TeCa>@D<o$;DlHHOf1ABd)kr
z7)107^452&+HLx^&U_K4gGIXA#(mpLvTj?hNankDT*!Ui{Wj*`1!=8Pa%_3C_i@Tt
zJ!jz;Xt%ubg!RX!{7Kcn^tSD0JwAJvwEXhrZMK)b*a&{O{%2QLQAoJ%o`^-Yd-plr
z{>seED=xQ&g}Z(4f~{`nW3#T!D)LYiP|7I^e#29dC@^KmyH}haN=rVa-h1++S+mx8
zYgB=&>ECyu<pOSXd2D`@)cX^Qr$tqWylpm%wpbA<c{bsu^^$o9Z|AUvN#3izd)D1@
zrlI_&Lko}byM5CB`rv;%@5B#cQ~#^?S5-|(TI_l6)0CWh8Lmgy#9d|%I#A4$B{8W}
zI7IsOi?%$agN19WzAS4#{8ojxqwUKhgSiQ27Hpq_t|kSnzpCKb6%syuPP2o7PHVbn
z#=54N7we+4S3Il^5v}uhZ?I`SlbVD6m!BF{lOD%9&6V4upYvr(Ua0q18`Iem&2GY{
z+EniA^&Jo0%=#+t%QC6nge|K|Zbk^74LmJVD&{OV^ZB8fQRf1RPph16kKqrWvCjN&
z!I8q~b7>3KDrUY-TcUlH<9bv{Xni~Tc?bWsSuMtVQ-l@!cUko%o#sAl^PBf<?~>}d
z>kpXBvXJrJsnGZQgyXFVz89|FI5JNsHtm4mq)_27A*=MFn(aJV3!k4m)f1RIqwv{_
z{A0h8W!f)TXc|BIp=&Nae{o*N{`oo?Pj}qh756gGFJ;Qr#wh>BY9Sq+%h^`@D%+O|
z++=A?&p#9TywHWyJ-BE^n8~(#tJ%3Z7JS#!zPW4ha$A$w{TD-Y&bl97eN+8#|BW`j
z(m6f1Y?Yn2{Mcm8J)=>cr|z??XTm2Dw@ogo;-Oaq{C!xanM&JQF1)&qb;;qCtU9Y>
zzssI=*qLTxw1Z)ath&L*-f2A>^>YJd4^R7W$zh6g>C??-1sxmrmCOk{mv-*9f7c_y
zP*s10^f@xl2@6};!j`;a&%Vl#`*r!J0`_~~AFR>1TCmzWnkn3BLqo!@6qQJE@#mM=
zvmfTz_P8GrFO|uT4)2Yu*erDFtQkAAUi7go2Mx_7o^=Rkq~2RMZ<5dT8zv?fo3Bh~
z`6cyARI6ORYu+)@zR0OfiA#@Piwaq~JbSA`5yLg!SI0Ik*^t}kvsvlnnF{>_$M<cX
zFzewP<+~=YuV>v-e!ko3MVR%q)MG)i0ydGptF$v(7?V9Notxy}cjr?c`^%6IseMiX
zVU<UU&YxR!xFYu#OGTUG&dds4)}IRk7{jklV88d8{o<b;eR7*tD)|2^DRu3dd{y%6
zof*e{!?pc_b!R@!=#D%rVYKUYL%@xUD_OfjBl{jteyZPb?!ffCb*dLin-eP~IChAg
zurA%o!|*(B@;=3fy_X%2EtxDl#c#Xp(UQsDH$2|!e7bTsgGJ^;OWXNx%s~q$?s(vS
zrTbLX?-T6NYtwG<zkj$xGt%9(`9$gg`KAl{7Tf&yvi3}Vkzui=!K&>t>+HT&e-{eP
zn8X{OxT1TR@IK}JE1lk)IR5bU&e%_tjpj0Eq;j|Xtr0bizxjEc$^UCJKNMbxerntO
z=KH+kx3hi;^4Ww(2O1d7a~Ch!Rk}dT*5H1r$<18zSqFW5HtEjY9J}V>>fdz}b}w%8
zdXSxGe$^=N$*Sj9r1DGF^Ii|MaV}#&e?rUd&6}xnBP!09Zok?!Q?96k>H56GrZ-I-
z@`Kyg7i6uv%~?Hb3U7nE?2q*y0+#-Nv%9MDAltf0aolWnKlk<Rd)~sxW4Zc7Y5j)U
zD3!o7&zefgMT;%kH!i!wzAA2MJnPRbmXm#M##V;v%I-M)-8M5gy6;)`jsq>L@A^3K
zrSbgSp53^%ye9lR<LMKg8n@Y^o#O-7^{l*oa$nrC{FaEOsc+31&7W(m_1(Hhvu*mC
z_O}|n33v3Suvqd6n@v5e#sAvEq~dHqR*osV<*e0i`fH!P`q=j4+|#owJ{~*q=ab1J
z10IR~G#2I~m!9oz+|KW69&=P=ow@(SWwF=K2+cpu5u`Td_1%PH%L8Orw@g22bFxf(
z#c9R<goNeX8#13%UGU}Q+`iC=&H5pWubzm2=8BJddvl5fjKzG!uAC8#pYg)|=EBKE
zH?CDl$Xw>OK2UI>HeuGoUNa`<ChpZIxYu8Ax*2HsN3iG#<I6Q0N`LwEF|OZ{;HuCc
z7`%ir_v#^WZ-JUgM~uas<-TvMww5rx|Di;A?)5S$!Cikh?3RdVUhFA(&2E*oq(|HV
z=Y#LezZ8m}txdRk<7I2Zylt~S_svaol;6`;G(q-;dHBl%^Q2;Ty!!fp<%7a(%Twog
zE>Ckb{T|p?&RnrlCiv+C7n^9l{O`>#T_n>CkKayV_L`tLOJJo-hkERk*9U*aRN2^F
zJIHIAG*_F`IIGIz0!#4WWuF&FE?LRG?RsIHuff{wtSUV6(w|~->+UAB2!<ScTVUWD
z8@iWw!%@bIM>F?)O4uwWB06cw=GMk_i5L5}M!!wil(Jax81L7oyIe1wc^UYCH{N~i
z^s`HS?=CoHdBk$|m6;PC#oSi3R+w0NYNcZLPa}u=80ml>j&)ggcA2^KF#W8^ez+u5
zCG*t$jBCw5Z>GGcTeF=x@k7n5TcSsPc4_q~S}IK5{Y8e^Z0GCj?X~7dB5dbyzj(k@
z#CY<|yoyPiFAV6c*6Np5+yereXWS>kQ4v$jMPWy$z0=Dc2Zz|d(|_@2n?55o`c
z4-=kd@MFf5oYi@JD-sUx{4T*@#c@rhhk3H&i7yTpXGJMa`f#Jj<lM!_hBu};mhEA)
zc5R%Qa$t+?^F&3N;013)pMLkaYiggc?7<t4__J3N&wFGazwM+Gs^zovRrs;1nHt)f
zH&+OkDPJk5wLKGbv?!s<G<}C(;5yf)ypV)j+Bf3VR|$6H&PdjFTlMI)^XCma9@a#?
zJ>fWY`Cp|KQcKj2>s;<@waWOC-*WKvp$B#;hK|}&Yu>zEG0&?d@xhhF<*T~8<}3>;
zkFs*I3oqK-9bY!H?1ka$E#^x32g?r$zuKjD;9I=x65+$^*)QiE*m#Lon{VC3r92ML
zZW-<9kD1k0KW*mb_b;CN{IdANt+HDy%_6SrY!}zZ4_iWf0zT}By>(&b^fltbA^I9K
z>bpLQm3&;WbJrJ>l&PAzd9jj735!f+)t0?`>3MNpkJFlqhe|?z3SM{B)Q=Ed<hOn1
zvro*Mn2(<=h-+G>z35uWijolNDQ!w(CmvkdaBa$0WjmX1r;5Jb6D;<;u~ITd_V^_I
zq?>BfOjCcU=`5Xf(opkS{)?S|{Z=cADl0D)JbiuD%Zjug4t-`}lYCOHDp^_uW-xme
zuaQZe&U@TrdhWLLwSuh`&hLG#8xG9Lj??>n&NhN4P<)&Gs_mE7uo|;!dY|xq{Of2{
z&7$th?{h0nwM+`jnwQsToDI8R^LT40@BM<OT8G}GsCW52t(<+cR6;Vs`1lmbGzSgy
z2a~0<5A?{X&zHV_M!Awvl1+xWoW*_NwTmCa9yl$#AvVvZbi;D-_=zb?7b@kN-}ak5
zd%OGh|3b|cPkkM?if{N8rQM<Yh@tG&PC1Fc9ukv1q>@)%I(c->jBDwaY&Ph3Kbdu8
z^^r%jY=w*5cJgjzVCY@2kbiDRLM-pH=$T({X7ULBIBjg!Ci(wR>1uEPDRJ>rV;rVx
zZu(Slw|KGR+oHW`xdFEhiZE;BZC#;MIOoE%7on@3Xr5j0nyq1dU@O1Aj8J!Oz`@dM
zcQpdmKYqc;Vd}1zx+-n<kF^Cmm+tzOz9Cj!CG~BT@~4PBWwl!Id|QrBab~V`lM~%@
z`>88$_ok;|(yhzdWhLZJ>le;lydYPiqG7p}R+N=Z^1M4UkCh$@buxbU@<rT-N7;E7
zuD^FVE&R)>&RQX6(=MqG^9t4)+Y20<F}p%wMy@go(*yM-rM&A!4Yp5v{VXD$!E34X
z)w4JDtUZ<C-M)C`Nw-Z5?zcJ*^Od%4+7>f$*V2Bgx*M}@h3t*rajzyLLS-tqmHq9n
zGUtSzuh_Zq<`iC@gUio|&3LYGM&RX}<PUtYwb%D<_<n~~Z0_Qwv`^2xY?jXcTAB9g
zi}j_mH!gKK?3D<3<;Fa-=hdb_XV)0>C;hxRHdozPX8&m3=A?AYe8S@m$r0=4yf`7)
z`S8y@DRIUY?mEAVb7d}1JK-5_ys6td>I36PF_Cv^o9{l@=vcUHPN`qnQq`^Odvoi8
z*XOpRn`S*!@z}IJOU=Ds{_>S)=Fa_V7wSb7vg}~0Y<w}R^_O(u)qwC)_MN}d*4=8Y
zWZV(awr|fa={3{BvRTh5#Lj)bf#XAtQ_I0({<h?*SGhhLWwkfSosr``JaLPRv-uAt
zhdqh+gijmtwsFKBn69voLBLffo-Hy}#r;_&gHMu)zvQH4?(RL#Mm^k;tgE;D%z7Yf
zmm|7nx8%{~69avi7j?~>nAaW}_~EOSJg>S$-Z{gvf41r8re3<%H_J%&%daHu?NY)I
zS`D9Vj#|Dlxn|kT907i|wNHD)ZnV8h-mZIV&Km~~KHDRSUS&c*9hWM*pMHIGj?|`!
zR_;fPt+FKU+nqVXdonNhdcR4`Gp(*@4lO3DfPO=^H5W_2>DgRZ@P6*HY?;hMOLs>x
zW`4T6D=K~UI$Nv0K*wW=hxym}D6F>f?=MMu>nOKiQ%3sKl-NW$jv_zv*FlTLFLGp`
zp7ok_Z_nFhaWkeb{q0gaPoMcdx2$8ynZv2vG5%8*%J8|WWiQX>se3cE`(j4vA1{B)
zq)oY=!bPjtn`=H>N)_*Hkc|0m@c+Tha{qlZYu@)=Js9j{#@!aULFz`7p8ID0NI|dT
zE5klB-+H+9sRrjBPIj5vr<aoL=k04taI@cLw<`SUuZw4vRqbBa9<U=(wWaoOR?5`4
z>oTpj?rX~ej!)>@6gAcP%~Qj@Ee2&~D^wjHC}xISmFkr-=F4!O6vf%~s(P8#+RQCh
zmCw#^mG$*q$T#Kko(VkLih2&74!?17l3Kj-&Qm{mj?d~)ci$d8;cN=aVx{N{FQ)l@
zog}q&gX31+!`Zht>3gi*e%N%!rp0@TdW06MS@@syKHm7X>Q<TeIj$o&dwENHI(AQ$
zT%FmLyvS}!TiJ(o4;WuZT#8$LmqYw&tGU>QMNw;)9Sby%y}4*{_T+7^+0Rz5U66JB
z>Dw<I>)eiLN*DQxo37cgtaG*1%<d`Y=1d9?yv(~hGy1E7+G_D@#+6c6e@e~DE<N58
z?U>knOEbYa&X`Am<*8{_3{&FWKTk~!^!D!)SmklLh;hp4;HQWBt(HG9+}eCX<Uo;V
zf3~UU<nPkEJQ6K_Rb9vx_PN`dewTyYcEVNWvrQJOda@t2MC7jwtyt>++`MV_bY(Fn
zR*q!`hdQIB!w(*foRKK|+U&|E`4`vO_9oo;y7;MTOh{q&&x<V^Vp1pV<XLv2=+TE2
z&5ToX)gx^9Ue8NtWDje6f8|h^OpLMXMpn!C%C@(hhZO}T`ger(?_*kVq=Yv#|0q+O
z$?aXb(mE@|kLW(h&gUyqxWjS#lkFb=&?OsE&Gl7oznvu<=dyU+U-viPuFTzgAXmoL
zdBf9fha_7hsy%1gO$aEpkc#;_L%QmWU-0^*$0t(Nn^*j|Saan0;&21uLSyw?n(L>%
zTg4*bx_Flq?{di_0a>fv)a2LtSHzU&dT(+5JN3N&+2+*c3z^sc;=SsiQ#nV5vG;7p
z+Nc-RRu2~>#((`Ms91k<URDT4+IBg|h_(85%D$V|UsviaRXiBG)v3pHQGzdv$0yB)
ziDzQn?Czb2<0w`?6T!P|Tf%aSiFZr$ERM-#Y+JurYs;4>OWrs-e|lK>aL0+lmv@SG
z@2p_vb`i@soAFce$p*g*9wGU=5@p@On{#B3U+_Hj<lF|8d22OhyxH01qIq#~)78~k
zY!_E$uX=RiuguKnE??JpSX`Z>z~gQ^W5T6xvuf6#<~ePhRumwvAE6p-+v;{9=;7AF
z(zP-c%cKu|x>8|bs3NuedI<Brtb<KCJ!cm#SailxNI$opQCsMo#Z_&or(R~QMtf&p
ziV<*>EZ{1O<v*5ns*B_H+ve8AvyA#0O%C;~PBY&9wP1#}`KFHQ4>jJBm;X$@dtmbO
zlb0_&@s`)kHeb?Ux;~8i(AyU~58UhuJ$q{f`{vaTwwk|^`oMcq{`SvTYE28zJSooH
zajW;^RaL=7*Ls&<pYwd#$+H{Qx%E|P^1GjOER~q9-Y=HtqiOr0<1O0(#-6I&%q4#}
zZ7?z2x5?YfPuk7B?ev=1CkNLAOtsWvTb6d{TxV5E$*Wh5*KFRp6@6)YGjI08m5LuG
z6yz!Fvod|X>~6tq%T?^Vd}pWTi5Sm5`E=g14~?3q3=f;KTjpf=X@y9MpUiE`S3RL8
z<8$(nw4lk8!?T;0-{bLP_<Z}Bp8ol#j~9K|l`B4R+3wl{55E_S{I!u&s_&ljcxv;F
zBG(ShR!d&V(C>v?XFL0f&QEmLxoCXy^FFTi58D>EWhwqYb~E?S>{G%0j}9C>(!#RG
z(f#-Jn{)Fw<#+J%Nt-yGEPr$2%tpg7-ET+MuR7{7<AL+XiwD1@6$NM(-BG-~>NL~I
zR+&ReSNMLm-Vd5;8as8xckz8nIz5b~4LNsXN(D<9D?g>bQd+l6*?WHT+#?qq&1djE
zw#r>sa<0H^#=CI8A8P`{O0G6cZuq3ba<bR|q~TKK@T(IZZa2Q_Ht+hW2!(wSzdq*G
zD|oKDv~sna?1_Dn(wX-!Ddrux8-6-2xOCd8op%$Q0-Q@1A3ocn=((cskI<HRw|hjj
z^<SL*RC@4a;+_{`7D}s*Oxb4o@G>*^Gxj|@pB?%2HEDCxtT=}=(M5$Up@s*~Pe^*W
zspeqA)mcTpMN@**yjXT#5tB`7<y_&}e&$H)FQ-KDj`e3Gb9%cjUFEy>)^*Wq*5+n|
z71P$4%z03-TUPH7Z{D`~i;pGdsD|c*K6@J$vgOW#x7P|wk6W&tb9%09_<_LsZBL9(
zd@MK=^584W#vgmP#q+CQH~5_YNkHnB!l#<!tmhARdim>0u)f)`k86#Wxc<67PZ;z2
z)S{Plojkp;(!Y21l_$r4@V31wZ=Q9mwE10|&Gs{Q{rP5}2nj36y~35P>|dI8TPQC}
zXkpKc$E<scBqEhF_=1X;{5+<1>dL0Iuji<$X$EYT{T1mbU@mh==1S>J7EOO+mWwSX
zCu*<KdYC;a=3H#wq?w0(j9SgjZ!Wqm{PLM!TF9!yZ8obcSHw$KFUad!>v%AG)8a2b
zQ~hRaJv{T%*&{oicG-vAshd!Jx}147`}+v{Qu{ZWxveImXFTVwfBo^<#+%A7+FH+)
z8k>IGcp~s$Z$jZrw^%me(8ip(ZO;AOQ!e)!U4Jm)eQ#W?%H)3*AubxF>5-GCs03!V
zD9UCZ{K3eu{5ZR1`Z8~W#FiDmCc26@&y`8-dC0R^)UnUMpr?^j`!tW*IX-2r`P^H%
z`VRLAJ!PL$@Zrm>#Oo{G{0VS9mAPtSxk$~`&81QkMK8KCCq6MR+RCut)B-~pt!)W4
z=Ib1^)dgHl<^9aFG!F${p3*R9-w|K`q(>JotWFkQH@WI%Z^QG&mb}M27@a=b3O}0p
z%<yjItp7LdSjxQ0j8};?RIz`RY1_-+WdD>y`NZ1SZX$KNCOwnp4_)fs;<#KpyK)9k
z+POA~XVT_|T|rljC5~yAN12)iP1MWCaZI|F)RKHqMJLjn)mh-n1fET;xoYx%AKR*|
z(rjxpkPYkPoAcxehl88WH9x(Ni(dUb6WFrpiACbyCVf}`qgU^CyBN%s;cf0&xs+$C
z$oV*JM!BF1m)~t;Hn9x&cumrJ%5sgO(lj#xiFl3nyiE(bf9tN@x6$hHxnJ&j`zk)Z
z^8K^%M&vvGKAx~@ZSB2NU%OxXoh{vb^Xt}o37@SB=CEEU`{8yw<alll%jDl1b@}4j
z3YNHYi%xmXX~D(nbK~5PJY(xzo@>vq=S1^_Jqx!!Qpx@I>D7Zy@8e=F?ez&*{6NJg
zM`weqsrPP0@x`n!4!^#1QKB~7?PgAbXrH>$l~=s+RfiHdN~4{nD|a3Vl3pxlddXEo
zcBar0zJ?0#IQw<-H$u(^JAAyeiz}MBzNl4b#Y7qN*oG?;R2?%`Y`wbk>#jHD&c^MJ
z|1I6g>bz*#nk~1gF8(@lGUS-1`ee!9>)Ovp-jb5}qG8Nny}aG5dPmCol)}EKHPsOf
zK@(IRG(H>*dsuPui0Dt=70e-`JX5nb`*H_x8L@b<uKT#GLHl~PR>zF?hslrmO)8D1
z7T!APax9M7SxD0L2J@r1U_WaMXJ7NU18uAttddMim|`>vI9@vxzuI?5dro+^TEPq@
zr<W(DD3qRvzHnClK+Mxj2St&oyjohdVl%@ZnP{zlAeH_?y|I0x<(9iA1QuOM>AsNF
zG~LR1n)J(<3JW*A*tW3An$D{xF0F54nWnP-MyFAY)!gb^KTF;@E;VqzW<6;u)8exN
zic?d%0=y2rGA@jD{wl5Pq;*ng;nXc>r<<p+KI*@2G53tk*AlJI7rv;S`Z1x`M`WLf
zWRUkXj>W18S|?{Ec6h2N%vN*JJ|(tDbZgVBNlQu;-zytE{<NY|UPn6l*1qR2C-CU%
z^RLb_sqxj2GV;H^`ls%^52>0@W+rWO>MFS^n{#vX)YJFE?4wH8ANzEMr*uxtHmg~^
zrZ!hKE`P8U<+_}k=)yKjH7)D$jnr*sT??)r5WS+v_TZz(sgUA1V!G4U_6ncA<~DhI
zRPZ`eM$wj84<<YJTsSuILQbyA^6ct)Rf&D;o4&QIZ%ElFdCQ`2*4kdR%B{<!KJr=_
z<V5YUn9O71EwAqWa`8`vV+s>W-8Ww>3t8v**J1M|pQ&q9mQGsI%~!x1`l7byr0n`q
zPpjE0CkQVQG5S&%v0SF0Bhe+IYxc@%;!CeyVkv$x^;B5!`l~#L{sfE64miU-xhs<`
z%gJrqgI|5GmZ?b^EuA`5b?c-nS5|bXd_UB9U8YbiWYZD5XjSLv-cz>ARTfTM`f!Td
zq_a}jj6S+$Xw6?aX{t&{(U)rp3Y|j!#UFCk+SICVH7cp-xOp^7tZjPw>ZhrmTT@nR
z9lWTSHGl1dlUEomO;?@IHVrY)ySuhJw@vJD?Y5NGmx<yHXLeu9IAzfwQhEN0+v&ht
z8ew-D%2k*<9RDh%+f?zH-7~mi>n*7~ZEeq!BWIUI_1?|btb1~G19Q)_w~?zPw#{GL
z_2{q#gWpE06^Ct?iaw7v(sODvYI~ioz4*q4=i6dsqhd>6Yz}JCiqeV}J=r|FPw#f=
z^{J~XThGrc;@dREP-lLCn{dM0sXOB~tA?xddK;X)y7|gR8T)8i&$@#V9;FcnO&^ys
zz7<c&c>HA3*1#U|<(Eyrd`VhAcTKow+q{K+g34D7b*^7|QBk*7)&0|jBR0|M=U;Np
zH92S+uPn!UDf+T;x<|Z%x2C?Qma67DPCgqhjjwl2Ua0SoSU5#=>69Ry>uU;9*4<bd
zu$<F!;e<jtjaHT8rmNr2nY6^qZ&HY-V9aGHwKxvf6P#1$e0Ny6WanB>eW9asQy#Yj
zg-r?Zx^z47kXWd?im-agrbScyR^6Qa==Mz$+i2Oz>1+EIZ^-?!b)kcHJL_}5>ynG2
zSD!2_DOyz;oA&Nnp&{$6p7iYGCmgvV*N+O;6j=%LMTM*u__5W>b0TMIkHo?rh23?h
zLv8Mq&(bv&l;;ZTefT(XSH{MiSe2V!UzeWLULcl#S~Shp^5=|&k0p0WXgZ0zmKFY4
zRwHfq<3OCAp_Am{$D5~K47uK_qgqw?bH|Ot%YRf%)9X8y{%TRiy2sm}em-Ep-5a%s
zW%3pKSaD_77pIo(_+TVuRAAlb@J;9|!_mXWArpgIv?kry<$FCe=U9HF-zKM}5f#hq
z!t|o$k7l%gO=MVH_G@!bPWUz}zrFx><H*Nf9|oRSyG%@A*^KgSe$zHjw(>N}KIAw_
zVg>hYotx*co$L~_%CyS9rf+oHtnJm46Xo0d!X{nu6pGq>?3}ij)>9YHr6!9_dlUW~
zoxn2Z!pW{6D^I8FO<gW4)qj?6^Yfc@&2!_e#93ljHAH@^nG{WGaohBCmeNfX%kv>8
zQeHXtsvV5{{Cd^RMQi1G4(2kl^l7I*O2`R#YHn2^c6PsUh@n%9R?{sdjVIPC8P8^}
zI+m^BCU<t9@l?a4o2NALUjOus-z&<~q{QDCAHDo$`82Jlt^ikqXr4l?bn%5dlBQTR
z&r`lH35kG>YZEoY)3+~4KHHu8I%x?<EX&5yEM0f6#2r(^{#+EkV(l%e>$*azL)UM2
z2=CRmZkq-5_o#e6cfqwg^|g{`?%ma|H7w?FJ(3Jz6#05C;HZb-Dh?}d$(5^a9(}qf
zYGc+Em7kKQEDW6_9h2L)JbYrYe&Rm~<>IMJ!R6TH@W*>kHZPc|ysyPAY{Dgv!f;`h
zPYH`JuDiHq`lS;)S(ms?+A*uN%jVXl*4ZkzK#4TS%Q$@Tq;uMyuToq!=ZX}X_QpNh
z8(?A`t*q>kwWM?PNkt*nc_}wRN<+LhUQY}X3sn_44+`NaZmVLgX8Q#5*aS;YUHtxv
zjA`h;-q$A{32w-HyI{5Y<YQG9!f|ev8CRu>9Garb4YtX8Zr!}~V$l?{rjt$0i;LH6
z|KgP(Vb`c~pvB0oC%~;Ba_765HO3NaU3qO+?mnyLyB!+*M%=0Au1Z#&Qp_-U^;OJw
z`{s~~K`mNMXLcn_eVP%+bM->r6Cvd(7n7zKHJ#hV>)&hfO{#8pq_@rQoMUrW_6VL1
za}$i(9~s=r*|Q-?OeC?XFn#5sr5vFwbB|s#x+;Hj#r8*6860<PHn|vda~6lvYqs_%
z-}v4(e(m6<-1HTTS~Wshnq`C7wz^+Vo>8{V$W1R=@@ULib2au&W(SH2bgaGQ)!kk$
zj$9r2<D<rd$&*z|L0Ns$mRVCfWv<-GG2gqT%jjU#=F&}*miTpTn{~C=&of9>*>lyB
z$kmzeALX~I+-&g+n{vtXQrKjBl`fl;8=*?~@)>X1ptR7!Y~h5-Dk5py>?Vg;b=Rk7
zB^e#rQB?GzR(6kdW|VA&ey+Xk`4fv00@NcnUn!Jpvtf%{sHA^W#X4GAefrwogbni^
zUwNJN(&%ba<3=%QljG+?j&`K3Qu?ua^{>M0uThH?Ia%FI@(ll2#R}?9S=+H--HF5y
z2CL(Rp*2rt#WZ&<xh}a%Vqs3GNTKWF>yvneOwX_Vz4HhMxCmObP9oVM?aHAE<saMq
zC%)DJ3ocmy;?M7_);F`>@9g~KE%-(!cZ<YI-Pwn&be~+wx>V%5)v<l5gW2hGVQ$@l
zr!>S~JBU79X_vhG*{_paQ<ZMtl!|opN;aG98~DQFEF0SoHBIw{{S%eHPP8d|q5J4z
z6f;-!?8kSfM1@TY^Dc}OmY&pWT5yQr@E*;%JsN8#t87lIWp<Bczp>`HVZM{Pw%3a#
zC)Y$aKcBKBWYeT6UR|fu-X=bp8nDGWT3+4bg>q%iqzDx+tCKs7MT?rII5nN+6W$VG
z>Ll>ar?f|6X<ttJvK6MjCyh;wb~Y`zJuR^QA@7zef9iTf-x=)@JC}L-_WJA6Mk+hF
zx5umBG+5d*@pRZU&)nD^!IvlByjnH;$XfF#&7~TCszzTf7|pEORH@6iXL4-C*0gB%
zq+IjT&zWNH&xN>f33hS#z1}kM%85hI5;w$Vaz&e7<?s}E4-U27gspy?Z)TkQ{Z+c*
zOij@gE4RKN_YYCa1HZ?*pR(MsDDshN%I5bur9CnW`<84AIKVjHXnob;$$QNc1DA1B
zY;*FP5adx9z5H6%kF1Ek_KW3@O_^K|Zx$_TTH@4o$Ev8**tCh`aFM!J#H9B0*H2VE
z=c??Ky`=Sa{bTdLR^BH#_gbcS?ln0qTeW^us_6BnK3|^;?P&}Gw@emUvq(S5&RaY2
zmAblzB)Dl36jQ#!?$F{o=j+KVhUy_jla_dOz2m$3@u!OC)Hy0ECnfAzcGYLk#GEX@
z7mHanYegQLa(XOUBYegtT3*@xm9pe|$0tIioF~t5&fTN2baKX#WttX_ca24jW<Js?
zS+}OMaH*wdgA9AmreOb*W{IVHq^{_G`pDq%<O65S{xxBrJtq0Re9WR*d$Z=o$0sbz
zKkv*ked_a|#Vx4s%5hGiUmQVi9$c!r6mYFTQuONGxX-C;qMLT5uYUYw)76P<ZWKlb
zl&|(vS>X|~IcaZXw!s_QXhn4o%_SX%A*YMZD%;#xmAUUER}fdEqm$yvp2COo+oYs#
z=2hiAN)3>)3s%(j&`_DV@pTf5gw2hD=uKi=-sUGC8jEgfYH^w*);w>UoXm4;UeRqv
zYYaWa=C7P2oDwo=%8kt5b(aGdPrhYUk{Tj>*=F8_+0N6hc?UmIJX@5)aNyYUPMf8c
z{U%FiE<5U+A2DhBGWGOh268M5r;Dq7oph&y!=XY%oOf-Z&%A(B-9cWSRW>1}4==i{
z)_lBlatc&zl1<3V=OU_8KP_qrnxxGidHKieg%P$3Crwrfos?49vE;~U+mmlOm+sM6
zIYr@&^Bw)TtpRuD1)TH>(ptH#sO{k8JNDk{lh@ar+i_uoKL7RFy&AK_%WtoGI5FXT
zki;rC&)KhcOk3J@gL7)_+=;1Qo(ZUZO*6{8>D;z@)k*c2ze_n48p>j?w#=Ng#V>5i
zm6@K)mo8}!OnQ2;t!a1nYkhN1&mdKO&lP9Vu53E<km>8DYabVsg&&l&5l~h2oVrG3
zrP1V&)n=X3zW6-cHv5w7c}0(`6jjaMnQNq2|8BcKg;&e&O4r)5PrWIgK~j;9LCI>X
zr%l>-{n}=iTW`ax1FsmXdQRP=vT#z;l}*PEdZc7MaMzA7H(KMtkr<TE7wM+&xMHcv
zl_&eM%JL7|FFv>INao$0OC;~!Tw~?CJ?m(W*_|)jMLmsIefF5VinD0$w{@zug}1h-
zES@U9Y)jhY*Cr+pA5MF{C8+j?$F!hX&XYoBon05aYL#S;8{4x-mltgbi<@?3mhXnk
zZyfw0gS7R%vQ#a~W=-|oGcPAHN>|@|^;xxBnL2804LP1snS7B>nP!*$7I&P~Qj4B(
z>6CX-)Mn{dpFh;!syq>PHdXI*X*A=)xb>OSZ>@A*dU;K8OElNx2y>gL)jPA6NpP4y
zD3VN!DwInMDm44(7Foe}Y1_5Cv-E!|+MHY#?5)qVP-E@X=}Wh!P0EjC`5WcUwEyBN
zZ}Gc~i!Wp?TdV_48A~qZF!e2xbDMIsdEN8tQ>ELuCtsel#4m2jrJ0@wL+4(emU8WQ
zS$|E@6uYnq7pD8}PfrQVGJDFT7PmXF_^kOPP45>etd?_UK8a@9adFLR55F4$@1#}j
zf~SR@K7A>R^PaBY#Wkz9zO?0k?YlYd<g{g`&jp^D2ycn*Y7SPGpYi&~*M(7YCZv@-
z7g}B_{KVSVa$5NI$ovgg=7!Dno)t3p<iX4LOyzQ#JhLY++7c8tC2-c+gO?3jzg#Sh
zmYi3w;-h^|(MS8-vxkR8#pPO_U;dEk8KtT1t)=Qw(G_|^+dK2DqF0t`L`Bz0-+gm(
zB7<`IBBOG}c>Ncec=DupPST3>3{rL8?|W{>nq-c|phCICD8q}N><?G7_IOWRI`e##
z-=EBr(RtgZthwC8we0R0#{(N@M_jsL)%W=7#ye5E@pp~i8Vht4b6oE76nmE#ziiHo
z%S_dwleaL)YbkqWKTY*qtHRH|yLIQa1?Q$8Tw-{^Y4x<OjV!Te!cKMzX=y6G+m@ZR
zsqy}**8!am_FSJm=lF!B{gaiy3aZF>O^-=t&8=6SFR`?D^66{G4Dzq%UzgT$iCg^C
zWO9B}nb@W&&nBo$y|hGH;q8gmRkr(|t>9}|G2`+&r){@nHZ6&2%X_>gR@CWq=8j$Y
z)~kFZ+!dpX<r3YDeYf4tUA`>M?XdTnt39h`e-q+3YZ=4iXMA!;aLDd}qwH@wO9VNN
z?lD<AW7(Z&+0(W<9xlCfy0mFS%IdR<-m8{cZtqmLdF32B>)l89O-pXcY?=}^sYE?n
zCo_L`uiM;W!A+u@Cbc+C%9d_Z0QE-2mzYd)vCfQ|oZno;Wn{W((iFEz3A0;N18;dQ
zSMXNV_gJM;S;{5dvr71q<cY9T-Iu&hiq-YKnw;mfEY2=nepSxX8D>)Z^3F1y*wvfH
z7xeb`+F5ICA1-=TmBt(5RoXY<a#b<M<SNg!x4Ykl`HH&x*I5@as<us@Y*iWPrS7=y
z;KI<iM!73oQxE4I{wQ@;BtSJHVHvpo+>~7rX?o`Lded2(ww}w}**hyQSA9-{PwN_m
zr4trho5%fo)-5x$BCeoc7M4Nso-1QDawkoy+Pdxe?EK~;rcF~fE!q+^$*29Y<H2R8
zr%P!+Ucx+K?PT$#C6{ER$||$ETvy)<*rT$_G2_|%m8R_)OQ$|QzmETX;5Uzhv$MDL
z&YHFG@6B1ooWZj)x#ljC$k}&0$<ltINxRO%DND{DI~{uE<Z~6xse4qGPFi-Jtt7?w
z>9x66+L}D3TsrAJ$%>OLH_Us->X)oF(-eNs<dSrZQgmI=`^s*<!pezLRZN1u+}yCB
zbGoC!U!T%BGE4iOoMlt@6e*hYEPYjqs^?UdWWR+~iC-Oy{`i0`$m>a$usQp0^OaAM
z*A1S`pA-Ck$3dx*+zra7N*CWOI$Ii*`!_6lU6j||{GVITqzguRI_2_32I;!auHEp^
zD1ODWSko9rIgz#<OI0%G&e2#o`N=tliL*A%y#4)lmSk>$*lg2TC6lEhJ-w8V&O7+>
zdiU4F6~;G<?zD)<_^%cd{$d%dtnHDda&q(a43=Pn=7O)4E}l!*Xsn!)cK*i8HSFiE
zzv`P^qpNcBeAub(NnW0x?qsdDY|>L$8t5-p(e);Mb;@0qAXU#<8#PxfY}>qbcHQX}
zz8UPw!P@$#GM0K4@4XuIakZ_#yKT>^oVKUwug@y_yk0uv^M<JHjm|qGXMx8?LMI)$
zS+Vw$h7C*q(w{TIg@NZ>-wP)eTdbJ1{O3%s$iN`Yv-8htdCKMP@}2i4UHhr4=Tebg
zv+O@L;I4m|r(ovc8EW^r9Di*#-88AiZIat;8P&i?n&;-PoG7Yd8pLDO`o}et)Ai@(
z(4t9OymnojyYNeo^@OF<&r7D~pO9jnR~x+k$h~i~)`nTLH?K3jyNkz>`T7-}HA`Pt
zR%+NUv}iY2Ib+$Stx|nKhZpy~J~>U1y?uQp5BKt|pEfNC>+-)|V8MQ9PvqxR8QbL#
z51(G%X|ZzR)Fmd9Qf{p`4|NF**L8TmC2Q-ltTe@y^~>DCCSCCOoN@o)*E1hhH0Ri_
z*H}17TqSgpjg*hSx8CNLPI*P03vXB}M%Hfw4_kcB;IE#PTA;OIs@9s=kUO4_=C7S1
zt~%97Me5vS#*7Cg>t9Nna-IFN`RlU}QW<+qCg&aWTPc2BbA@E7x$mFNS3hmq5;e=8
z|8=X?)$=u{48P4^J9WD1)=53LYPRp-X1J1e!eZqVQPrtNJ+~V8->upz<!j&0K4B@y
zhDmd7t(o^E@c7E>pDGw6A(60p^3-}i#~@XGuN6xwwkC!M>$jFL8ht4&T4FaTWOj&Z
z;5|=qg<y4k&zC6@Uk&&{B?>3BM449E_hd33s6=_b>-wtQn{<Az-KKSoug@~O%JM~t
zY}`z#Ebe>#v)GxhhnN3hd(Q|h&!b|q53ek`Bs0at^5M0WjP)z8M#?u_ICbh$lxAM+
z;e<1*wD0GxJP@V3{HfN3pgM<bUSX4hJPWh;zuo#YQ2fkfoek@n12ZMe6{6*zZw&b5
z5%%^s@9{uJ|GU$^uzdCi(yH`yQuSTAS1e>^(J9+L%MA7V>@S&8UOllD3sU!7&UkU{
zEUpW;a!&93zHyUZ6~j%h%0Ms8!%GX7HE^B3wa)qPJ%d-mw-`@^&2gR<=p&qU{$ldJ
zTYk(1$ye@f;djV9r|6rlmRUM0?ZI{4`>B5!oOJcQSEbI_`mt-N-twCsrJ2Gytrt$6
zo)ndtmHWWs8Qb&+AJ;i73yPZ(bZSEO;#rec9r*dF^1pJh=6lx(UYc#WGa6!=mVkQ_
zpRzA+QoG0bk~d}56P3)VCcDifycZq0d=IQU#4G5vh?7L9<`(k_E2oGqoqEal8_(_K
zwyi#UYtFs6xb@YldBvp*><=U_jy->Hwcw#m=T`o#+PA#h(Jkhlpu&}B0%}(-UD@^S
zVDXf#yJ7@lKdo}R{XOV@P1Ev}SKyAxezx~lLpRnuusre5G~oMgy~Afb=kB@h^g>0l
zjMr$w>aDwX%;?MU{lajP_nh>JkP}=%T$*KXo7Ya6%9pU>?X|r%lcu;`%U@_>bY<7w
zu*v=l|Lj~>welgiVr*m1(mmpiTB@0*AD+AIUFIdTE^La<`z_3qR!$XPy47gPt-}xB
z3aOS>Fs*XeUlk+~-ViX?eO8$7<t+XeB^TbaxScT0%D*M9VDelb&BXZ0t&rY!$0O&T
z@~32j;vr3A+s8#83l@iEKl{MB>FTo&>K<EFPRlt>so6Mz^YDett$TD<PE)?^wpLX>
z{_w}(=q#nks9e7FO(EXJd53kLh%DXu=^pFSsfl;nPWtYVyXAc%1Y8<k%e^#{g-JqR
z(OXm7ODk2Qe3FjZD~U^<C$63B4zhYFR(p(n!QXbBt(Hc4W>*)z=KE2tyLZ;a+Zon=
zw|G_82JgLCawX?!)amRK7PtI(kC$IenR^kGwmmP!et(_Y`9+G)HaIXfTK9PFCOf8u
zQ>QQ8GU?3jYgv_Aar$mP>sEFwT3fdIm?h^;t;p$ZA)bZrrLIiQDiCgC3Nb8@?u%<`
z{3N_76x7?ERrQ;<f<sHhXo~L5i}T#4gq-?qIwfdU<!?Xl-i$(n86LZ*R_HHTJpod*
z%-Q{L7ni!6%GKM#qSd#;Ph6XQ`22#eMlH9?Wh6HpFT5S$sj4l0%pa8OXM~;k^mg0w
zWsi4D*d8#?Dm)i>;@aHPXBU(fuep6eS2ud~wGWr$!w)S9TJ_mNYD-pI_3Zp;A;txX
zGKJ|T&nGN1HU4wkMU2bbcCQ@s<5elz=N=YJ=(6O?3rn1&a_vsfEi0jAqR$1?M2%hU
zY!S9h&D^@@y5s7lJ9lJu3hQ^4$!)s&3Dn5ym-bO-WV@Aq^4h80a!bNy^+~%JMZTUO
z=dvs)Y*OH<5*7nHrnd<Kt3Ic!<2&ziocFGYZg_jT(DBFLeRm19ypp-plQn6<>cz$%
z4{v<rYGv3G6*nX3^oEks6175$RhAmdm7=xZ_g{$eT(qwLoC=@&SCyA%Qov*OCgIoJ
z(}miLPh85X%<l;EE-I}B=`s2}rQUG`Xi#4!IJ`am(eY%K?l1ZrM=j?FM;SU_zWQ+H
zk&hB{m&*3!oV9F`JS*cJems4V@FYH#$MFKEig&tgDe7CvpE=*N+GM63+d|uZi{*0_
z-#F{ns;#wH)>(Y2xWo9A<t@9G%`-**EcYzlRcxW%lQ(M*e|WaB=G5F-CX21wP1ep@
z{J~jGWj%;<{m_bKGyiPZ>9<G!*h|Hb=M$EN8u#2&ar11MV8^j^MtOq7QJJOkj~1NF
z>iq1+@pk7NNjK~3-w#yC%rSP!IREs5M|zgpmt}KA(zT}T{`h1mzr|x0S#@W-gjG6g
zE&5HC&Uo_u*4cTSf8QjUTl<2VM?qGWMeC)E(&nuAoU%eu*>_sV?8DO)uU>i*XD)u$
zB2fHPKylzKot0+oI!mW1e_s{qr)2-a?WC&DtFsT!T&R*PS})}gTDs(SP@9y)<(AB&
zmVYFJ43EDJO*WR}+a25{H5)A0l6h2SeR%Hg3Y$0nl3BO?r!EV9K5<!S@tnBQ<sO+=
z=TBPk$g*7}x?C^5>)P3%Uy5%(#cUSWwq<s!*Q@licYo6!zvowGiQKaE1F;V4cxG@v
z;P_|oD8)9t<i@hD;#;3j7~hhdWFK?V^KjCazU5uUr#@SRZ7G`ee0G@Xc9X@{{q@eT
z(^mYO!0W%q_?+dbu(|HDLe2`+PS#glc&I|N<(-Wk-{RRzf3jKnUJG8+@04*~)jvDk
z+RQ_~r7&Sr=<^fNyv4IQkMFcReE80yHIrN7drwbZRFp8!*hEj?b<(wyU6ZUbx2<=x
zU6f%Eo0@SYxl3c^l=57Sr94-|7kdSo%vf(^vdYAD3b+W$oVDKV?W2ncmrh++aaSZT
zNb~)b058k7^=xj7a|}vVr$YmJ@%OABJ8R0Tex17T;j;;-2Ugz}a@w%k@<jYhCey~$
zj0yFiIO#WbUinmG?;LN%`}1e{2(C}HFxT+Tm$PrXa@w%cT|ZRNC)V@IlQsNPR$BF&
zteutmLGx7mbFQVQFW)NeG`?lYWdG&Z#~&9&)|OPd)#_Ec**ZULH)u=eJKNzcnm*;Z
z;PR=(GIcAwCeM_f%pbf|@@}P#dXV|yhwW$F;}W9^`4XcH&)#o8Q}QYI;ym_+mhHz~
zvY+kvEg<jZ)KX}p@wD=Y<WrtX`DOE*jSmI4N}jch5sNauT<%ycy2X9c+8O7g+<9hj
zI<r}53Nk;6Jl->hugE~y&9b1aS!PMcrKrkCFYUumLPa`f8uYXn%eX4R0#HrAx#Yn?
zg(KGkCiIDT2C3_Ny?7F_$4ad2rxaKHBqfi`GY{9NWUJiV-KV8Izk%=bRQD+XC%J>P
zEFbA5e>;)B;BXD^(Knugs#BkR2+~+;k{NC|F{E_qp&H(!E?$D5F`p$tv(~=e5d6vU
z#E#%|1vgfjL<WHdAC`LV>U*b}np&~mWv}mV@tak}CoWY<=FMAFX)!HomC0Ig2tR)M
zEc@7F=Y_9>j%MDiv=MSMKYY5~p!InBB9>*KWZ7}~lw_V=NbSipXA62VFZH~VIVZ4q
zR@(EnsV8(#Yn)T`)qK{mGqYpz`>v0gn@pb<wq~5=(U(uM_G~cVV_j(7Z?bmw!)KaX
ziY(mnW*IEDY&Tgu^Ibv09JX5zPlTOGU%Oc2^metw8rGVDQyxbi_uR$xM@Lab+1~na
z<NRQk%(a#&nrl^juTR|iF?_?dlL0AjK?zXXOIvm3uC6G(?69r3IwiN-xK6lo!b?cX
zbKW|pgO4vJY!p@&sOeGw_pvXE#Jb*?U$|(i-=~gAUX}SRL8k&rwl*>T<GN-g8Ff$r
z8b_W@>%u!G?Eey_?yT*yq+=4eHR^lrE0@d<Z{34}>-{|Hm7+EEy|k7_?u>fk@^8ZG
zIVxH?w`QIQo9#R;#QX9`k-dkrPcGq{TvdExQkA8W-IuzLKQ3&tUHNFsJDW>Ad2OBi
zj-37cYbQ+6I;U~|@&5~_EUoN9avy$Ncy&e4QAu#hQ&E*S5~ysIJi6z<vv%5#9hohY
z*LRnxXq>fNl6jU#R(_GCXOBT03n)w%&tCZCa86Oh)B`4oZpQj&GnQEkO2jvQG&U0b
z9QnFb<>QJdk4v7B?nd)U&#ZbmRsW;S)-Owqw|q+NQdv7?y6TimZ(`PKbxo?O{Jt>M
zH5l3rReF)NG3+bLl~3=SySMUj2XR?C1}UCAcU5Y~r?s!1-fh2jz<1)3kWZ6ZyxL~1
ze%hM4t*Y?5&7vuOag(li8Wr!YGM3}LRwf^{*Af(_U6Z^d)AYoTPrLc*>fLs+<9-uW
zN<S@{;x}vR>eAz>+ln53j0knwEf}d)>FK5Fd;IFGcR##!U(H*wB2!$+JCn~dNb~IB
z;44;k8>Y$pV_s<9Z?JT_;)7?aj~<@)c+0DoOY7AR`ff6PE~sW&{G^)0p<>TN2iXhH
zj%41gTq1dw=fB*lRUax&yNWBd-*?bFuXs-5xyO!7(NEsSyFPbZ-jykoCw2dc_Ts(l
zPKBT%!TF$X-DDQd$5sNXiajo`k`$Wfq`26s^P3FEUdxuuy(!_0&!r~hxq`+j=6qTn
zwq^Zp->rX^UM~7mw)^CyLXDa8X1xh5k6N|;z}lT}&!h|9iUZ9?yjt>OM>w;Xa<`&I
zMO-wmVCD|Sm*>i4A<d;p6RPJe{+x5I_9pLR^F3m(ty8p9R5@Ek#E+kRUK$zxOSi(t
z=zQAZgVubK;Gv0=hZ>J*M8B#oi1KsvQr4fjc4Fd#4^>iCGdH+-uPqeY$9F67M8HYz
zNm`z4@3zV8eIs_oa%<Y636tMBE%OSS6yo_Qe?@B3jdi@?Y0{zcOLk9KIce&W&`DRM
zUzIOk=E3Q4<q4Dg##=KBC5%KrZ(5Tysfu5_EXLq_@0#zzlAd1r?{hCyWnQ!W()7_{
zg7)#pOEST&3ZAEOO@eay*Rt0}S-0<Y&^)i~r~TYwdtmHIrV9s7@LSGd^(vJs3^F~t
z(|7WO=oweQW8T7fhaXAlcYP7&*t^GI<@ANOoom!Md2e}wntIa$eT3eL9Fkbw?xEgz
z=`{D{s+V~T$M_f2cH|tbxt6#1ZqU)?aqY7wxgTuIZRb76^7Gg-&96INncmR$opXE5
zYH77tR;O&fNH1;AgN>qBLRYTYZ5r>EbogKK(_<6gIc*Dyn-bzBP&ntzl3Ci>y<vAh
zi*P1O*nrn)Omew%v_YRsVjX+K#GAk33=EWSXPyW<=`{&7c4u-sYe7r=_g8CUik8^<
zO}OMfsbKkAli8)_28-5xbn=)FYMGzZQ0?4tImhI+7TaWY*9)J8Q|Eq>=GeMNXYDkV
zM|>TxI`=m8EaR#Y3{zk7-2u{Y<1bH`FXzY;^~!DO*$V!aS235SWVLnjuRb<c;eN)B
zIW}vp`wf=Qe)#C{dg=0Ow|$pCdtRWD@wd|G!58D68i~YLxy+kA@|!zO7Qgy@qWG0(
zTHdwvO-^lEJ6*ersv<L^^nK5?>$t^%$H0U1&z^37Q}{`B;yspy)2F9?F*;Jy@kwRj
z!5_j?KG{6#DVjBp-_Uz;)S|mwUgdn5e&%<B5B%Wkx$n5*nelP15cj>!>JLtvddsfo
zliV6q>_2OVTHk@me=RMn{9Pa9na<+fe#}Z@$|IRWTaqU2u<o7qe&?nSS8FwDKNXzK
z+-%3T6f~4R>4|Jk%k%8@Tdx*ONjY6=GI2>wug_9T70;zA?d7kwrUmo%udO_r=6rVl
z$EJy5Q}%;ex0zc-CYC?oe6dY_#cx%`Q;MFiL6g=z-R@1-*1UeW;q0ua%i1;8Tb@r`
zYu>K2cKWlAef>uqd`((@xpQW-T$snc(5&BJ;k1Px<US<$%ja!<YH>Eg^zaY4$g1Lw
zqAJf{?-CA(*)F`CTe)hg_Nq&g^V>nay}+}9-xI%n@-$np;@OGDolSEj4Z;sx{QmI!
zx`fd3tjaz7LG|l+B>u|u%Ckv_rP$37y2qPv<@sdwtCwr)R^%N%T>9X&?lty>Up^h$
z5;yBS|LqBTE^T=xbEqe+?Hs@K>nE!h#R_^=$`!g<9)8|FGmuHON83sBysDq}bB(_S
zg1*-R=U6+vJg<8Gm3p;m#Qf&62#&ik?|!VlcEL`AFE;;Gb@sy?$$3w_E4Qyx`hQh=
zZ5xm7(}ro&&T|&;Dn1#!%Xp`qmy_-SAJ4n_t7Z!7X%&MeUbH<|pLzCEqdPDuWb4(e
z>#wt1Lr*L@c4AUi@rg-UoU7g^BsZ*o-6&-<uTARU{Y%-+0-KgZ#Z3#F?fW%Qq$^_g
z+P-aBr((}4dTD{i#8}R|N6Ig`Dv`MS?w31HUZ0$%diB|arB~B7)=VjhUB4`<NIK8^
z+{AuI1@B2A;OtY>9~vla(Z|K`ve7U&QDQMy+XOYp#K4j`uitgXGqNw_tu(Od^qPC3
z;o3a!Sy%l6e}(+LBxb?)BPxgOjp&opjXRmTt}fqOv*mGub<`S@<u>g$%jYP3%Z!*T
zvSeBK-vvuDuU0O}yvnlGfAysg1*`9^F_nO}^ju$G&T-Gnj4GAOj50m?^75LJPpN{J
zw!D(LG$*U+>~h0JDmENYS<k1JPb?4A4E(g^Tg;<5Ws8^(pM0EQQ0KL+%&dBk|M^ha
zoCjOCh6*<@cVt@YIltbhxan@$7UpXKcmK}=&7bOeYNw`pF1@)#PW7P8ikQ7s-nx5k
zueln#-LX5!s?swk-E84;n;P52o3G_q_eGsqb}eK1VcjW^wF6COy>+&4S$W{x?PXE6
z8y=dx-lDN|^5m3~wBX7b1z(NGRWtdfyPW{_{arJc-i(oZ?Z3iUw7B{C!z(@JlQq4x
zQbEEtau1`vADX!_Vau(PP4jiVvr=6%*NW60=i*o;<;rR^A<R3~HI!S?NBdc;<x!Q)
z={jfDuY4uKwdAtF>jEq0sCv6fKYQ2Pm%l9j%bLFG+~zvBYQ4%JYu7uM?^(;SIc&9c
zn-O+~+qjGK-n=#gn>%@Fp)L~**3J-56A@lxyH;uP`aPkm%_S0}4E4`wsA*Ks+Id17
zWL4%-k$C@&Cp*8poVZjKndqi}@N#g5Ka*gK&dO=imtMW}=8np=&Q<M`RKGqGRQnpV
zm)|l5)GQ1+o5uUKZ@HA@tGd%yH;PN=ZhyNxb&f%j+><p<bFS~5wt8`_#aXr;!Mw*-
zF4(eZQBPRcis~DamnA7|xq3#uN9JBmaUAQ)DWYmqf^1|rEQnHlwbjje`%SY4I}Pky
zmsz>>1-O4M-rjik^QQ&OTlbZy&k_6Jes1oGD<`;uq&)N9Ii)Uk(*HGM?fl?LL7@3j
z&$xGPlj|B+U+F1#vJ|>$73mqI?tHRQ_?H!5{n_t#QX-ejayse1Z@Ew<sdewr_a)X6
zS@YyN<U%!i)E!qmYmL0h!<%2(cRlEM;`aQIdvo|5v(77@&se^)VpiGp_FCP0jSEbk
zPf#;8j;VQ3`#90y$XmAejsjhkpq|Rn_5(}j^(>CE&SY=8aGL9KRi>I<Nb5=Mj4M;B
zeRlD;M8!=D@&5clQF>zdw2;%MgR(NE@**Dmc&&Js%}G_;YlX_o?FX|T9i9J0+z7l5
zps8T_#G@PP7Vc^BX`Lgpa>6_Dgdg^gty5m57Psv>l(|~y?zd>iHy_Q;#hpI5J+;F2
zZYujxKiTiIeAl0?=9rQeH|v^DK>mkvSy7$kVfmI?dCRXiczbGQ75;M4NMX@z75U2c
z`f}LUnzOl8rYE-+_$X<*ze;A&tQC3t?a3RR(23@@{(QWd2Vcf@e-zwgTGX_}t*gX&
z<M&Yg<?nyxZmo&o122_Xt@6{%DZI0acmLXq>>pkl{EZhti^U{o_4+GHBs|{jl^t;<
z^SweeXtMR`jji3q79z*9&8M*Pz7{-Zs9^GZqMGUDD^m9s^c8enRQdXF!>zQKrktae
zDUwH3w)zF~@cFJj*Lf+cGSN%-?CSP=8>)12uljoYV!9bs8R(^bc2#?Uis_ZRX_G%Q
zbAab4mRxZboqA?T;QHm)j!)D84`ol9Q+0ypiHPddqD5PRn!@=dZyf19`Hg|2wMSv;
zghyAM*Qmxl;pA@!IKeTAE7NVR6YF8F))FR=acigK9DnX%_f$ck>gJrkVj(KKgx9ZQ
z=G$hdW#Yd4Z<=z2pWL2M(?xt`O@&W))GzZ3n{dr@Q`Y{t@1YTgq&iGgElZ?JucvZY
zt_3X*4Z3sd`=4d<4|Xq|Rd{jpnyZrb4FM-TCuw;W@s_ygzEJ%<LHXG%UH9L2rl>o-
zc;cct*JLMK^}T@gK5gq(J{MhD0$!pN<^1+?P-)-uYF|k)-74KF+72t8sCZ6QSz7k6
z)GXBYUY?0`CzJm!#uh)nDOWrVGq=B68JBh9;ALTs!@pXT{@;|cbPQ7VU3fRDVuzsK
z_XXP7v%Uy}JHoCDf~P38u1dGLeIY1K`w5F?t4XO@-1DB2ppwNJC%+hjM-3;L^E0y6
zKm63P@~fkY*UKj=nR8Wg<yN&`Ssyi5P<862MN@)iS<Mcu@$(E)*Y<j;^78Y9zdidU
zX1z*(1y)-xr=<Qd$^TQW6KHUB>B(ZQ@7%9NCcPK-iVXD9ysYN`q4JpEi7>Bp?xjp!
z+o}v37-D11XO~7+Nq&l1UAasD<oe_ii&BY%C!cEO2c6-*+~vs^%gi5o)qLOmoYOa)
z`)=o4m(qE>e9NXyOTs3(HJ^X+vnoVKCiKdxr&{y7l>UMO<&x*74Egy@ecGH~{61Yu
z+uhgw{=yvlXk~SeEEUf!*R!_VTD9!^L*L3uSI?z$G}ca8a#8M^M;2Q^_O(g*tso=9
zrd;s+l)?Xe>8e#51G7!CI)(fT|K;?~QCK-q?c&)o=d%V!QlHo?c2dl=UpV!vM8;Z`
z$$7ih$!&SNy=h(lhI?v}_6tGtE0c1pTvtcu|BgIwzUUuhjoHSR3(K|oe{Hood)RYo
zkIKqP&n`JPOmwe}wc>o`{{qyOGMQ@jTB&l&yAz%fCZEq=Iq5aYN>j@=<l^(mDxpS`
zmUzwb;Fr93BU-W2e&J-%r6rS0sygN$>9+Cwy}7h#(iXo-uFEg(-(aN(b%K!ZN1l!9
zHcdIbIonE?3$Eer+8h`1yM8s_)RM4shNqePS1iqP=l^uMTcEOT@6~USr~Eb3S|yLF
zbgwhLReE>k{SRM~Chud`x+U`x6yj6DCV3{G;IdtFDSzwiq6O}k9d{quQ0Jto?zu{(
z)5L*!Pb{nW@#z<vAF5pc8uWUN#YD9!MT?dM&GP&$C!*OpBW<^;c+N>xQ2pq+RAgq`
z?ED{Ab)B!bz3Mb~7OZzteZFjhmZ#R+hfx!|9#)>6_Fj$4_T*pArE4^nPFZ+q-s5Xm
z11k)69aUQsmhsMi#naTxttNBxs{2;i7RJ@wUU4AvpZ|-ewd`*CM^^=Z*|pUz_^bRx
zJ%)u-CNG_0wB=UK)(R2v;A9EQrIV+slup`mtL0pe2t(3QOU9d8mYzYXo~zqmsiv+w
zFm02c!?qy5DIuo>vNvBl53bBTmx^qbGg|f0-1!&dO)W{!Al0+0+a<jBT$o(P0FLNO
zSFBnE+Df@zvI~F*Dek(R-%xugSmDbi%j?;_)21D0XkL}i;2iLL!PS5@Omnv1;=Stg
zz#?M)Dk0ZhOf5-q(*k`iWfyF{+m`o?NqK!zRHd$i-E*D^S&@lBx+ga@+FIV4{8jMI
zk9V~dVZ7%Q6-tUgo%Z<abKIP-dg+OT?ljr?`dXIh{9<-!Pd4uN)@5oz3CY=YpsuO9
zXGY43(%YXyti|mbmd&qFU7|f<<)p8Q9#d7;e#`O=-`=`KVSAZ%;JwW6%F)`|UfHUi
zTc4Xr?@G&k^hW6VicpX6hM+U2jJhPV-ddiW^+=u1>~?m(!iqzg=?!6LyC<*8?3%kw
z^0CfVsWt8s)=m*#I@L($cFkd-`)hX{Hz<kHeIGC(D|1;cljpU0YnRP(aJN>z85J4n
zrR}`6x63Py+rMd|O6ev))}@n|+;TQkSPp7wsgxRp+%{PM@w!tr+fA#;KreOAE$u73
z_uRPL=eP{K(s=S4kt~TYoh9)O8mX?DOMSHMPX3mht{AO5+wjinS$iKQ{BiPKSbKlE
z<5SDJ*nEpz+m0P~8?xM`B2Vm8dw#;ek8!CLXuSN%%~E-vNmYEgKQ3ptB>Z?G_FOz5
zD>5=j*K=F8?)tS-X$}jXu1bAj%P*(+STexM(!K49=f$_P!pmRH63__N^3T4W=^3P|
z?zwWwi*5X^KGI<^^S0bPr|O}VvPZ&8@$8ny(Cc3l4(@usJ=EsugWd`27{STKNJsiW
z)a8e2S@XVS92WBb&DIikZ~cO=MKZTP&q~z!yzTL-8Cw$X9@?ea^2z4WmZG-o-M!Q1
zsXR2ltDuk@FxU7V<H8x@%S4N7ZeP)Py*g_3%`-I*CQf$9IQKB|!Ys*awqKT|-er+2
zJk$ej9ZY_&n4l^BdRuVqUyo^Fr>&%xM9pg8zZz$hy!_r0*UY7JG*(Vo{9sw(2~F?S
zPw(;u>3SY+*UA6$_QE_ba6a(*{2?((*q!06g+P{Nq?@kqk@g+Qi#9Es%kHGFefov!
z?Z1-jjbC&%_SRfG;Fhb-{xomP-6+}ftY`D~K3smk=#X_l<mcy0(|nCz?Yf_{HRYd0
z`No$Od-fZyX`SwQ@z8|l+pKoS<)0K4_b9WUWBZza#?8rJc0AiHVeH^#GCQt$qQU0$
z^L{7ir5&)d`08=F*lWqkgxXFMQI+FImwowRtUB{Y!M8On6K#)2OW#PGq*G*a-cRd6
zX5}oVw#mP41f(!bQM}+BRWUI{m*?%5lD9_%9zR@DInyA!&xvj3`3wE(iM%E6Ed6}W
z&rR$&czM2}cVN?*WiKAKUiwmya^dRp^vAk>{y`xhbjm$g&wg_XI6vWQP!q3u=!fUa
zS3a<a4fy$Vs%Pk7;cFqLCY6)hl>W6yCRwj(nr;}n;f{~=<%-B9l}i>XvA_2TK6r6`
zL%9mWnMqd^eJxuqnHs*`ulRp)W|G&v;6*-<y;kS1Ik#i;zlq)YaeJzS>vhVe{ccun
zzIyMJSN_wgAIW8f8+Jv?@-1;&%yxesv#a#>*bTNt_Dh!C{?c-JO=JA!jB7DJ-dfJP
zF0jq`ob*{Q>E^FLO>c`ePyKn7ukfBzeP!u}3%kXqm*`(+fAe{7>(+k@?#FKTFV8ER
z_G|TA)8C(d9ZOoDA0P92|Fy`7?epL2mcEhv-TL$CxsA+@ofZt$dgt`_*wyb%j^DBM
zQl#~_lD9K!gHzhhmp<6@^Xs`qwMC1!Z_zNGw{8C0^}6TR-wwCRZjP%zy6(Ic-?QQ$
z8)|<w{XNub`TNYv&BYsb=5v*wpS$DBoja$+&);CTyA}P>_V<IgVUH)&uG(+(;&AA^
zh}hUyx@XoqyRqjy-}czbu4``9x1GrcTMw6NpS(ObTl)HU-@X6;%sf5a-=_T7yxkY2
zZ+ysKx<BvyZS&{TtGd5^`ty3OUd+=qw%50>KiM63{BqdW#Wy7q`t;}6f1GH1dE**0
zHd%}H$@6#ay%it5{ru~g91YjgpS8Qq>aLlEB?)buZ)E=4<2v8`uR1Zu8gG8t9RDu=
z2KQ&}ZwXsBUwD15Q9J&{`jYDF=GUGCZ^*y<V$FheQ$IK*AG-eTMt4E#CyBWCpKSJ6
zOV69eJ86gVjt5KcaoI3e1eZPk_UF^9pywG2vyba6UNpIenf+4nt{d_^Ro6evy!+z2
zm=*JG?o*Suo9&-gDtUO7Ug<Qe&&}r;e?Kt&5!Ld$y7azCd>h}ynX6v+Z_=4IU+cWO
z_4R6P#w!KKk9v#i-I^{gw(gPLkvX*w9FqR;{CDWjrK3N;N`E@AvRl0W?mJzbtLfI;
zt$#1mi?u7w$#wk87MnhQ>s#i2`Ih7LFB)p!NPJAVa@9js-9N@IdB4ev7~B7EG;d4Z
z)6M_=YUjPJTYqkq+avjS3b*v@)zYuS{l8y(!yNeTqw%?QYs#-pv+lNC!M)=1vuD@W
zm6!NkT=-CXvA$NF?Pm8yHAOK;Z@$+4yY*ZsYw{VJX>Ttaooi7W6>GLf==TY)`jz#2
z^W}f8$d|8tm;7xa_q^ICCL$9y>;JgN`15n?<#fM&U*`O({d%QUTrb|D+%12uedQ~o
zKQ)q1=Go@TM{;aBf99voom+2Ke^|eL(}pb@Z&(_zrGAQAU~|)b+5)Y$mbt%AB+Upc
z2>SMM@^t^7_cmrXv#xOtZR~lf-Ou)2NY3+}P5HOheh0Db)d9cv#L1s>lHC^ne$CpF
zX*Ky}oN@did$NB$|9W)ZztYv)jUwKDpZ<jHN=CQ$^{*3u9-aMp^})<$>A6c4<PYS2
z$*xPbJyExK`-*RRanT%p4fDBIS1H$6Huq*XTQ`3__vs>QEU!%CsjqAyi`~!vTI*Jz
z{7Y_~eyi4jxOFl7ddcp0r3+lY$%TurmyLb7UZR{^bxC=yXx5s=yQUmkwx-}-{j)ny
zjca5@Z*=-z56COy75yZ+uIrRV;S{S=cU@#fZMqGw2b^A|SGkn^>&Zotl`*p6zFTK3
zUUsWx)0bJVw1R_Ub+cFTi0CIt8Y}W#h}*yUmZjB;HS6~OT)qB^`-I5uy#-QQ8!hGs
zUkI)iX;<zDf2JvTEp*-V-_qIKvM<dNuT9tAQ}Xi4%;e4M_0E3}OA`+Z|9Hmuz%}9L
z8xQ?GdhSxkC3B;c!tf6oSHe6>w%`7&E3CHeuewI$;ui~U*V`<A_-obQ<&5ukJ?6A{
zWtyG(`}|%HcfNk@y;i2F&8K%)rLQgjdu-R+ZMSo)-?<&H%UoJ699?$p{f)ot{xWTt
zBK>XU&#iV5rz)%K?%I_y%l(=3w<bR`Q>@5h<Cc{8Lo#duj!j2*+>D%abdEj~?<?LE
z=8IMGxhG9#bYHc;Y!>3M=_d25X-DrR)UGYhP2Rg$DszM2t80Iv+~wY^<yV+}^xvUl
zMd_)rrV0s@oze@Pe?I%{efgWziaGJoI}}w92%K57?(6QorPZa$xm)dD@GLu+u=f6o
z{58&DcllzN=PfV4`T5)0t@nOar5~NQf8Vv23#4-Vc3q5o9kV+*K7Ka4-gb*#Uw8BB
zZrL1<rrYuRFE;LZw*G5=*%RKC%eP;Of3LgZ^|7!SdG(nq>%C1cIh_0U>W|cl8S#4!
zH#`pyf7q3~V&U`Y(-hQCFwa<8lae04A$~`~{GCP5S}lKn`mBC#?&jz7*sJ~=x~ZM6
z7i(wzeN*kjNQ;M;?tK2XQh2&vgQk7r{2815ZR;OBnpynqbNa(SlhYMu7pMErv0=CQ
z-c<Xjb^6<Gb-l(Xo5l5RE<Yb<Rh*S4b%kZWUc625t2dp+J6>P8d3k|Yef*A=r%V}l
zW{Sr*#TMMLt9|sR^ZB`$Y0u|Yzx;AjeBS2su{&(qmwdgsxp>3>BTF|=FMQuR{n-bl
zhnp1pr%%}N_}I<U-=1=xKUe$Z$Wr41&*ixS8~x)gzFw-lVp0C>5clOz%ieB2FJ;a%
zljr`Y&+6+Kj$1Q7pKnq7^vzS_<y+l;KWaTa{ro(eYCrpxr}gJn$r)X^t|xEs+u|v6
z<+nGQ72os^f8JH|>Q3k8=N}E53}XH*75-o&bUyKx9q0C*+<DK>&9k>=7dI|XjCy5R
z{qNDv%^PGp8|_X!`!mz~!?6d)zD|9_+}Qr((9F}*pGI3L-oJ4(Sbwf{;mLhJE~)NV
zZM^x_rRMgI7rROxa_!l8`P=7oy}6Z~F+aS`Y@Tv|@QK^NKW7JzH2Z{;^NyA?bG7Bk
zY?7#2GkxQiSc}ScZ;C%HjX5T?<m-*+{&Q**-<{!BkFzLc>pJT#uHW>*WZ&cN<^E?L
z3R`|Y^tnPH{$;9;^S7Ve%b!l361j3Y{{e<y<%{>5ZJ7T2{f+Aa4h?TubK>{ioNaHV
z%H3OAw{LsNl|J<fhUd?&v(25VX>B|A9mAn(stpUzS+R!NU(w9|_OvxFJ$2z^)l$iW
z`^_4vo>m@sw59gdlD~}dI<eP&x}CL<4(pC&+PJFdR^7uXZ%tpn{niuG`2GW%!1cv#
zCk}4AZFeQF!Z>g9wPTyl@!0d--gob%zI?pInY=YRXPjy+OijPOy7A`FL*?LL`3w8z
z{r!?qyYc$`y&rvw#06eH*_WDd^Q7(hxz<f_Zb{D>6LdG5^BpP6Fq67pT37eiE1mJX
zui{C|{`4Ey&BDSCl&$%G-HgrOcV%t+({rm||6Sdk{dxPcw}(GvZ1{WSN(g@!vsOh`
z*2evfx|gp{ki0)H?0)&7y9sS?lDEA+W0fHP?%T9P=YMSb>VyCG`Gr0|b-4Ruv3Rgw
z-0Stb4;KD-d$jKN!Ic%gpS5i(>SXV*hSzSsA3euv_oe9lmtNm_wWcw7<Bk2LA1+)`
zUua-czHavwcIA?!pHfraeC@AiO0naVti1d3$p3e1E^oE}J0<scir@ELu?B}1`gqTi
z{X1W+xN_^}4I54NAJg`lY*kzx%6(0?G)U*@Is3((PAiU1{ptQcTbHB#wReD>RrcPW
zOW&PsK0kN&uQyA%^&3>1<JHg2x2a~Uf8AdELi1C}in;SxxlLtl#GjRH;fYZ7Z!bU2
zX;c5Lb#ugO|Ks!7l}n!eiQJHQN#Rv`k;d0`{_`xpPW)poJ8$mmd51R_-zzGq`)AFU
zx+(vMh{fOR#*iOV)-{<*?~)g|shoOl%^Bu*AD#q@pNrj5^3~?XGH-{3ka>=U(N4$8
zL|-K4+iI2QF&Y2j-_Xg*XKdTPeD!Iz%Rm0iQ4Vd6v|GKx+sL|h_r<9iGr!z*P~bZ{
z<wVw6ak;%*YG2OmTwN@`x8SSMjf9nD?=E?#H>tC@<^MglIe}>j%LdcR#h#|i&&SNE
z{-+i3VyDBaPrW~n_FYktf3;J%IO@d}p$|bnukc&_5_I{`dTFEjpG%ek_Jyx}6!vZ0
z^5xARC-sWG&eNG{9{=eqPLH<~*1nXz_jZM5g~W_w<xHBb?ou|B{{4A$(^cbgLO%bi
z+Vf7V`}b|E5n!Kgu{HB+eNytZ!sQ1wd)Ha4bhW#roqoPXgs(p8>eg>p+^x#jeSLmi
z%zv)Uj*UhyV&fU@HWe^?{CX|B!7{@6epq}t-_1=@at-Vo3mz-T*tL9>co#K8zT^%6
z-j53xUlMXiooC?Z&ssfM?bN$F@7Bt<cpr@sv%dSYcj?!~hQ$wV86On8_ka0S+1xep
zZ}_k2mmUyVt9SNv`r>?69_0m6dCdCXUYV9&3}^opegDW+>r>Od?D}?aHFM7X`geD{
zi^Jo0Re0R*(&c?L`S_BJ)n4x=Oym3hfPbs^E$ch2_E*-Ouz2<Mgu^S@Lgh~DYgVtN
zv$Y@YJ?XtmEbfwOCzHaB;sA|9-Ok<Xd{px^gZXZUzvoHs47YqSV^W^aCo`{merI1@
z-nhK$1fN{?spJsJ!=^{&7FLP<_@B6ArS%83(0}cH6@B~uFXZNtyK!*!_U6y|@>W6S
z^6^I2HZrq9&P>u!*()j|o^U#;zV@Y8dhXuh+xsg6u6Bppy{msD5YqaPamAN)4mbal
zOq;RH(z&R+aZXjuCfiRYQ_6jlN<xK0FRRB_eY<J=p|tGWzbUd|Q5WwqoO0`3@V<oa
z&zFNj4ojq0Z%^Yp)N9|V|8T-OE4{DR3l&Z~*0lMbQkM+<>L@C1&mVtu@~74p!FOKl
zd2sIB8XdKFuWv5xJ=nWo-K~iIHQ9AvpSW%3wsV$Qk}f`7VDT<J#g8>nZx3yLdUB(?
z=KPZrmA@_6oR`1m)TX^D>mP4^aq6LEKoUFSvJzRLu&`~5mNndq<Yn{pFTBmYy>{o@
z_6IITbuZ6!7JpL}kF)qQd*73n^2O`^$eYjanqO&W@wukpS!Mj+3E})nd{Or$D+M<^
zeH0d8ePEk-?qfdxx$78sqEBA7ef;I~2Q~Y$4|}Y8ziZv+d{_DNK_&n9imdZ*KeM0z
zeYxOLrM}HmQQar)%VU}zS6o}Tu;=f>o>;rb9^X~<=Naxfd-a^uKD(PnX8h|`|2^iG
z{?_l&$MvPt)|FkmwkXTQ#;88mpytVzb1#F^8LqKPpE;w<KEGk^<%0g=cVC20U2J+i
z>+`bt6Ru@NY0tTKv;BIPnh&qjp-tu;7tQJeodoUIu}xd2{p<SlY4-2TQVcEYQ}@<C
z+*!<CI6r9p#A3mKC1=VSmVPdHnRR}VP3$|rh#NE0nIcZe{8}Bz=6wC>s%&eM8o`R&
zNA;8vFTCvTu;0|Gnlm?Md-(4JZ?<oL4#?@8*Vnz-9GX*WGH>a=doL$kZOQ+$h~=KE
z%k?j!KYx2M9Ma|v=ZkB3bWQS1TnYcGsDO8$uh{v&3!Z*;X8ewYdaSqYtFu&YCWzjU
zF)R7<fa$4ro!4C1FrynAs#ovdwq?b+sW*1irhYwjP+M=``R-p+(`?RdxEI&*nek=?
z^SVFxf4hXVew$v^J^iV(rN!$j%VYmc|5&p%k3asg>tD6v7vGlT`M>&Rw%Yn%-qN*u
zu0`&@`f|;ZJvqMjs+)Pj9j<-MvbPAXO3x@>zr(q@Nr?N}i-aG>s>K#UQfoT?Cbdsg
zG5ef-U3{77d)pcbvphMjx5C@pWNMt|D)ifkS}({IG0OS9;7RUs{XH$b7v^8mdAD=&
zLI2Df&Ap%X=gzjS{(0nQ_w#ct=L-_o8t-4{mUM5@TRFzZwyOLuwh838ZSpUl_WMAS
z9(%Km5ZlK?S?N!A7H`Wbdaui{<HEAr#>U?^m1%4YtQYMtyt3VbuXu0yX5-xQYvLi+
ze*zwR+vNXrV_bdxnRuK$%k|~*O<#^VEta)a+wkMl1f#zX>pZVNW%Rw1?0%u)wR2Z(
zTT6PfZ9&A7k0+`*^*6JdGnn7py;^SR8jX(^Hm5(_D)VmLA~DWynboXZA01Aqt_t3u
zs697&+b3cE6V96}merlP8)~tz+nHU6eL4Rc*$LYlmN1{UOxw?pr!?vCyH`>fZ{%dw
z=r7W>ELgRF<CYzt7M5E6JJ9#3qLj5LpzdOiwx>#lw9c9JC5ne%GRw!<82oM7^UV38
z>v^veE3&7)+Bo|~g1;4K+4;Jt`%CUte>y4Q7|xb?b+7H-SN9sv-+dX%UswI%cJqC^
zKi?j1uMam|^utxBH1}C?!mW8-re(H`S@Rrh{TD1!54bG6;uYtWuPj>COj{4um-B1Z
zCd%&Ddi^yt^7#5+yUMl~ZclM$Zx-fn>|0*2J^S50<?`xhd9}%_?*+KYr9I(IeR6l=
z?z2666qM^Vl;w>-wHtkUf8uVM+rh<Q`d^PcdUPl1{exB9-}%h#?plld@Ofo%CG}&t
zo_1t~ZKT44wyINGZk#OA<4>LX`Nl!t>7O<Fo1VsSPJ8;tH}u?9@3VT(Us;5oOKohv
zWET;CJA&h`T`bRKpQnKu)fc_33j|+0V3@sb!nwU0FGkPzwYJ+|bo?E2U&>;Mc{}gz
zud7|Tc=mFK)rzI-F2~MiY>C}I{lWCVEo*<BbQF*{cB)jwrEtM?^MjYtxSG>{vxq#5
z);9F~a`$RMLrJEklw!0^$=ak#4-eZkA2$DbhU>vW@4x?E<s>{le|TQ;2ItMo-%1J`
z?fuVLb>8iwWB>ny97=UX|EAymawpC5-}AU7MSuJ)|1FpKAKdr9(!2NnPMd7|>+$jO
z4Xp81wWs|2pGqt!>}PznPN!_wqy_Ws4a=XNS-JYWf33qgySFOklO8v;u?r}w@9lce
zzWn7QgZU1Zf36lk@AvS+zpn?f58B>X_Wt}X)9v@ZNtN!uSC{pQd9LUN#UO#F>(=KS
zDcaAic|xrJUPSC%{`J*A{mTE{dhp<_^S9N(-wyg`nTD^wHz)oU!|Q^tum0RBRe8Pr
zplY>f{L4QHKOZnonHjfdTT1<fx!det$XH~_TU@hEkiSyYo)Dee^ktz#ko=Lg{_;}0
zo;|(yD&fd#rinLQcgXBeDc|CK$j{^UJg=Sen%VQ4<6p{bvd=kxXIuZR?fky2NxPy0
zzEAXOfBehw>#s#}3Rmwgo+ZRQ|4H-p+@J5SPTdmEzHIrohB==(bEb#d-+9pfowM`;
zFW;_%j^<V`SlRbJSn!?m>bl>VpBGKtUKg;vThaOCzF!A6w_o1&m9K67ufF;hAHDZY
ziVIjLAYPLo#h3gpJmp&WrO&DNo{BzmeHJ|F*B<wM-#+hM5N`cf_LVquXhYqPPt$7-
zSj=-Q{q}OY*qkS=>Yk43Ws}6`J!w(j`Ox#3E`R*(n2N+=t#(UQyX8fGr=R{g^z+8v
zwJ+}_2;~=qm0bUHJ@}xX`JI<;)_V(<FW)78J*oVK+o!xgnmaH0>3@5%Wsi8hQ{x`-
zdd9phm%H~)efWF6^nK=n$JWW>4|wbwTsjrx8>Z`6Puyevg+ZuQ`#tl7*nY)?YnSru
znl4T?Ej13Ga!xz@)va|Jx#8EQtkPb|U$t=mk=0i6HuX7H(H>e;{R<qwE?jq1&TEJE
zuJf%te}BZ^x;^dIwW8SGsvq3h$3#~imw!{1ynAm(`LU^Y?e<rx`b(B<=Btooe|D+s
z&B4#>{?$sTUOlgVFzmz<zFof-%r3idnSJjQ$2CQKl0V#H^_HGqTC%f6&-}{Mqa~G7
z^!hJ772LHaAe`a$!}J$H=L>!$_)MSum*?&m5HCP(%VxPnv;PX*{nGv-h`;bh!m@Qo
zoWER>U*v9k<YBX6Y}_{lZ{{wc^B279+vL9TwDYIE@>;5~z4)g7x_37oWhG^6x2;{v
zwN30#G|%_7tUs<fRb@Nw*}B2EI4ght{M%(KmQ4%OuRFik!F21EWzY6Wu2?2^?aCeF
z1+$|3pEj+^wwY<NV%fFep9@||^{er&S}7W;w_?|^#h%Tp+-;@$S00U6!T0=K&`$A|
zR|W6nrdC^pO!j+NCK<ZPV&?WaZC6yTbW2=)V(e|c>f|n^+gkaJfxdP#ABMj=a=%<E
z=%m*Kw^fmIE=`zKV{((Vin}N4(?uR>wRY#MPZvcDSDjR!+!u2BfPlZ+^g!QRA^SWP
zxtA8jlx^x%{I}xijr3Z}jp-`v&bR$<ZTvg$-uis|j5!_G8{N|K+|u%*(wsx*O`JJ>
z;>`3Evor4N*7W`O()PV7xqjKfI!n2lHT)LSHe26YE_>SY>qY)c^J{n57Hogu$`do^
z<Fs#P-<Is_wsl?_Jx}|-^B>cepL~0}ZCB<eoeyvf-~BYZV}Gl`<AvcH)xWyFk<|K<
zcx<Ka{_ktvb=XR5K4W3na?9;z-`+_!sn*{dg0%W?%r-IlTofX=?dKP^mHqjjS#Rj9
zYTqoU{?X-TyHu+6mzYlX)3$dtt}kTwv3b0wztVbsQP$r%S>J-@6-AvrWA`+Nc}21B
z>ZzSwmcKRCtsSTR^qa8f>Y81fB&%1<3lTR<=D%8eD&@?LmtRBplw&{Kns;W`HucTx
z-kyAuy}P!uWp(%T)JI+quksqLH!Can(RKA;M$^`Hzu4E8=fz6Cx-7fv*lbJds>617
z4hZl5S$H>C{Fk|LXY4$ylUJ*m#Ix0IiC!qa@zf=Kr`NfkM+}zkXv${gITjUi$6qFl
zztGM0%HfZf9=4tTwV}%0_|;t5YpSXron&-Z`xR~Vc%;^pJ#*KlE0H_*)hU-LKis-f
zfa%+V-mPDo!&8>+ns7p=bmoNcDX(;5A`f!ju=uE=`?=tHQc_TZ_3In%pH^>4y}zRN
z$Bexz%<lYX6VF+4??+Po-%}R^*xuE?OfNF1IrZvO)ABd3bp7|waE{zn-TYPi-m<OP
ze~r7ADCc_TyuS5g!JajeN4J0Vyjb=|#sA%xLz54^oicsaVx~pev$k-lt&Njh=U0-e
zls;j(iFoVoYwc1^V!xW3U#I;(yI{M}TORGc2P}&{l~0_J5ft3&#j-UhXN$v=Z|>~E
zi$mLLTr8K`-QUX^K5fVL2T4NT#lrFqavodCGIM6L>LTk-z5Bj*b{LmD_WN`1Omwy7
z^R=wv({^lq5GAx-EbQq)&SO(qW=i@il___c3-8V^f3ffGndr;K&wF?Nbw04;NT2kC
zMW^-#&XnD?q<gNcOzC9zyH5i3E3bIVeNFzZQhuc^Waq}qubo$gNKRyzcAk~QK6}}s
zYZH|8t#;ckQ7^kt+9q<ef7dcK^N$?QOj52Y+E;3n9n90M)L6I3?$15bjg8ay-Lsch
zW}M!}^)=>AtMpUny`Q`jBYS%m=&|{qJe>C{F<k!JCH`uyEhm<4(2zc!9r!M@{WXY?
z-gsy4l*el|zHd4F7DTLD{CLrl`#Y-4i&u(2`}Hd!YoF=SMuW1$e_qcO-M#x-{I>fy
zX2i$8ik;1;eh@VF`0C-G|E|9)E$dVN^~v@2KAsf!XNGRG-qCM+a!x0BZM0o~Ku&+-
z^TivE*J}ml-`M0=W2j}@J-3l>jbTU+TQ;};q0&Ry#y2L*wiyP_-p+pco9vG}vJbYf
zL~mVne;03gIlEo?a%OYhb1ieXCq94s<DB(|$LC@N_ODK3lACrpivKk06tl3Z*9TjD
zZm-Whur^VKf#>~`#5bxItlRS+_dTeJ|1;wYZ>n5b&H65*1${D(q0L8re^TMKkr1|+
zbH?aSm1WtJrw%jU`Ec;>5wd<cwdIF<vb)_cPSgK|FZd?3Jvi+7rrz>Sz4^xfQzx9d
zvrG2=|G+!-(yV!RC2!TczuRxU<^Q@fFTTB9$URB&?mpu!@o6Q$-(9GidU39`bGZWR
zyF0SC>czj`-)mixULHE7B_fiQHK^0`ar&F)1@ApixVY{!REcxzyj^i<?e5Iu@e_}~
zcQV`lj%Q_!Wk990a|3VshoS`uFD5;RTo!lfbfZ^=Sb^vE_K<x-tEQ;mF*L4F4XAXF
z`}}sx<Mk==m*!e~Y|Cwq+;cJdV5XVuBn#c+yX`}5y02f^^7r4ZgZB*Qi2UCo@7Er_
zJO1$9^$*`&Z@N2wPEcvX8Aj%9a&K&3%Kci<QzQEB`<1%$H~!DE`M-7H=lIW8{{8q_
zz`obN=8x%5jcNA(q;7P`S@?h8KI7=WYk$>x@po7MvRX;VUb+9=dhcsTR`B@t+U*AW
zQ{rFgd<nBQDmt%ed6*@fhfl3|&BS8MFP_u&&dAQ0-}c=6@2@YH6o3EPSXsK(|EBqa
z=db7g_#yP?%J06|`I0hr6^~E8ZomHAobO>?<)0h9>WSaK&XmsD&a+>7Pe|#_i>LS8
zydNQ7HMct}J?H$N3*3Gozg}n0J=pv5tMuHjKQk{_?zOXxm?!6Rf5tw$y&tAbi->%^
zUcF^q?H!Jwvg>yWKR>o|iM$i}e@9<rneh@`b7#In<Ck|{Ouq9$Mc+pA+@5^3sEkEy
zb6J?%>#tu~__IMkU+Q+b@Xom4N1tbHJ#_Qr+ufaS*01EAas7?ZIlsL7y*nKXtn7S_
zGF@4Ev>>cJ$>H~tDSDp{)^O<0N!CAm`IF%p!F}^>)VQDTsfueq6FYCCwp5~0;Wbw0
zojQ;8&RI!RGpkD`oSe0fGs)tCjQ5o<N;xmSHP7qX+^9K?-R;~5{*{+l#GlE^>Bw8Y
zkpE_A$L`m|#b@EKnrd&kl|4Q6WX9t5>pjvNmw!94Xa2{x>hms095F9{aq{)?zN2Q3
zL1oMhn-(6|^i}H;`uC`uv0C|2vU2LDKmJ-##mwt?jb}zqnNsCnu-oe$+loW(;yDNZ
z%5xiA7dg+@UmX07Grzq5h*XTn-w(aY7tcOwOb+<c|6<S6$o6?tdLuXd_S{(;@pfwZ
z<J1$rYx+OjO<XxEvR*6TYv$Kv$Fx<ODvSPpuo7!ae%&rUk4b8GVNQWd+P(sg*DJmr
z{*_fCCnREg{EhUkBlep0dT!O?hxd9Z{G3qOze;FsX8x_Y-yAse?ziOrDL$MlzCG#o
zyh#VH)z9R1dUjGhb(-VF-(N(68&V|o<7)Oi3Dl3Pv03$_;^xug+A%eIoQ@v99eDJ(
zx2|1W*2j-+-Tl+UYVJ&V^jPxfapSK3<0A5_{_Jr1DY-78XsY~lEqlHAx;uBC9@h=2
zyCWM~cgN*tVeskx*|BwZ&U|{Ta;iUjiu`pA`@FtSi|ag+7_S$Y`)RLRTEJDhX|;df
z#;$D5DNb|Wyqui8<k2mG#T}8C{a0s1cixEn#&}Yy|JLij`}X!Qc2vEV-8yN*l3n*L
z_g~n5t-E!x&5wgeoi`VqO7)-Ed*O|8^|Z}%7_AG>RVTeWb0c$oNy4!+)!`x9UEg$<
zRp<MB4_m%{CeLYe@v|{|C0$gkZ$wX>Qt<Vq=pT8Dg>wrwudCg&eU*n=&0}>9j_yeI
zcdwWe7hVipr))K=zc=gN%I$}|r-rZ63wc-lSR!YK|JQp5?&d#uC&4;(`ZqT*&bhag
zv-eNvxb-9C+YLd<t>Rbv6uf@QHTS1oymX?RkK@&;hf_Z&dCZ#i&+Acn*6HZ2PxrpE
z-ZAgX^`)(nRZP`iTD6pgugtqub0G85oFitJ&s8Z`UX#A{;zrpDjWxo~my=^W&U|aR
zroO?xpe8MF>QdW_i+yJ-Si;I>#G4zC(E4HL0lw6xN9&!X7vD%ecsXgg%#>}N=DtxT
zx2@j(EGh8hJ}%U&$*C+lXK_yGhNZq?PCUKgKXxqPy=*S{F7(9g&Nox;e04ii!g^q?
zVcE=d-u)LAlqAhQlkNXKZ2loN$q$bYb^SD5^K8Se!wj8eK`zr`CR8PRc%4e|+^e`W
z>{9E3xLRG;6P^=y%q%Q4Y}W2PvV3#4G_Pr>yjQm5l*<d$_K3an3~98wTzKP*#*f$l
zWyQTcOwA|WE4RN@xW;W3m0!-WWqV1|_5UH<S-ne|`~I_6zv4CiH$PhY`u{!ZD|`Nj
zAN#NU`2W<8|L+BT{D11JeedRXp>OQBGR2B~)4wq<=-{%@J70EgotLwML#fw#lc96#
z=WXH5Up>BD6y4dGZK<bomY+?leZ^eowQdRRlDFFv{V&uk6!+M*izSWOD5908n%lj3
zGykfk+6L{b@7|jfb?3wG<b|7`-k6-xIITc<asFz7TitVSw_iD$`E2*yYjqZdfAoJC
z?%q{WyV)w@-}BuEf4!HRqw%2re5u#Ja{Ws_URGD*Uw&JcuVMavg{%l;^|5~$`A5Gu
zOxG=a#y;2NVr^Ebna%H8Zuy>t$|*MMOBwF5`^naRU7Q}DaXsF)_Sq-*XL>O;q2kv0
z*J?w>_JlL1KJ34F^x&(;OqH(ezyE%{*|$=-s8n>#tHs?evzD%V``~TZV}UC-w43d&
z@TrG|GhTW%rTO}US>m}rj?SsfxPN8e%I;T_>`ffbmvd%Zi+cWI-%8u+Z!#bD&dff*
z;V*0X^~vOIeAc_vW~Q8O)Zt$d{Z8*}y!;LJzBON_|GNJB+r-b$-zdv}eXD%F_KaQ8
z!Oi`1w(_4jw~y<8$()PK-zHxE##mvoZ+Tr4uiei}#jn1HF7X#XH}_)nbN_iv#WhcE
zUS<B}dn9020dwCT9<O<C+uc9jIeO$;=I;|twGMavKlri#?KNF6=b)_Q_l+sm+q3;{
z+ijAFoptWPlc@h<0;Rvd{P|^Lmu#?OJ^xAe^9$<}%y!+%Zf-T09xOhu_L|-G=t|q)
ziAfh~?$3^W6+3x#d`$c$X@yOfIL!_iM_jgFumA0f{(^JOp%wi_%oFzPD2bJy8NbJJ
zztkMF9Ty|HJ~cWC{+-1ynxFGU?CQOv+1v*?KNKg1<~y`%?LTZSmlGp>M{-U1w0^x8
zo61s3Ki&!~(0g$G)1O1U1}&gf0BkmMdcQ9I`26zD-lt4O(R1VX7lw#S+~|>$x)S#{
z^|y+X?$0$}IQ<{LX7Nqvn{)f~d7inO^S#!!sMvO&`?RXJO^@yJPUGkL`>I}kI=bzC
zQQGr!@mD^1Y_{5Q?#5;7oi*=gYX#kZ@QY_N_v+Oj0_JtvifZVbe$jgJ;wg5qX&>g^
zINr%V<$vd{mHu0Fo+K*XH#hygs&4hGuV2>hopwY0_OgWZZ`{rQ<ImTn=KVO8va~(i
zm|ILugX{OQ4R&1LR_*_h+U!{J=G?8Q`nL}rTrl~w&vbv=@r3OAd`qfUYIgrWtG`~a
zw6DjVebSz^&GU}_H+cDNf7<1>2lK@x5@T<C{kUTJ<>)#8FTR)8wG2yG{4(K({hqSo
zzti0|Kb-#Of83Jb<!_R|eN~@7XO`91H#>#T$8OtLEWq>Q%+1I@XXF~|Z?*W(wbu2&
z$(%lC_R)SDu254M%kpnaCdD>QV)?JXx~+BP%A2S4ZGXSH**|w@&6Q(TrCF~&Ee)Rj
z@q(fCiuC2n^yVDdddo09^t`|C*||Hu+?i=<<1OmCV_$K)-yVgha`r3E+q2kT?QC}t
zd}4Cj-fHXfkIl>d4o>u6CH-rQ?dAmge_yVIRJ^(v!S?Vb`_-H6Z)Vm_$&3-c_vtbF
zS7i&8`bW0SkGA$sUA&R|rtt1%tOg<41)lEfzJ~R!(Y<XPd!@y^C}Z}uY9ry^{||V3
zmo*>T|J+=<_rU*h>8)*t_J=?EAGc)F|K)G~YyPf3^>6<6kpKQkf0w`9Wc}h^IeY5*
zXC`}|2(Np;L@a?ztlMgK%mGcCf_HCHS8&bIe0fkl<Z$d{?e9vKQ_r$xeJrWC6I`XT
z>dlRf{PBl5D|WQx?|85Im_`3B%hDG|ltQj&+s25A-0scYyW($@erd|pp!&MNu$S4k
zGTyAu-LrmO-|)54z}mX|^sifY-(5QPpiRtniKyG*>a!;&_@7)IIj^4g%xx)+n-U3~
zmsX2?7h*0GUUY8Fa@T6@mx~<tOWCQ)h;(x<Z#-;h(44R<|4g%NbRqxxigw$-I@2B`
zmOK;BW7#xs67Q#55i_>sw>fu-|B}}J=(ywhotf!pQoGhy9{ycmbLSXSpV!@pimIbW
z*Z){`wBpAyn;K!h>L00o*LmijY@1!7!M->0`G=#M+s(!JZo223sq#4BE!yz9@{;Wo
z)e_^_)4ofOdJCSoP-J|i$!S^0p4%n2roC1;9IiW~u0u0Mu=3u#MyA4uHtwCBm8<4U
z=UEt7#C*1R9ine_)!+K6_t~w-=1843jaX*+l*wR$=clNb!NS*P6|I^+E4$ayv~X?K
zq9(f%<HFpT?KO`lh+ns@(U4%}x9AM3V`KfXX}Rc}Lp+bvul7uy*Q3Yy@#yoXhLtZr
zi!7KwrBJ3o`uMD6{U)(2)k~)t`mcQ7c5dEbE%$3?@-Ze_Ql{z3yY47P-ZbqDecv0G
z&im5N=-HW7V)LVlF6QhhPnLYUWp-e5Vsq4+n)IJb5B~Xj&e8nL;Tx$dwmI+KbZLL;
z{Z|R{OYXY<>hJbvUOM5bQHAjK>eC)l*AB2VYFo?*b$Y;d^X|P{39;?I6Pa~VT;+JK
zT|Hc}RC<x_iZg|ob&gj0TJkIY{g%%D_G@k3pTdQQ3s>*owk3l<?BSQiReQ5vmbFSA
z2yI&2CS{eup8KKj+O%ik2NQJ9u75b|?&%+WY0ScFoc6a&RM2mI&3tyHSI)U^wXPU0
zCI`90^ADbR>Fs#oNWrTwOBG~N3g!vV6`w!3M6-iea?W$t=Q}@Io}RwPW23m{w>FXL
ziAnlFZ+JDoDIJYla^v@p4`<$5nsafhZa?&Rhv0m6)90>MPr}~#=v%T&hu6Gc<GIX;
zpEWgerF!ifb2F>#@+R?Ou5$gd1M>GH4v8+eO57k)`{aS}4&k_&-TK*5r>ytc)g*to
z9c(=D0Q;f3eLID3%n@4=_v-t`=A&VK20QMr{%fkSA>fAiv+y^JQ@%#Ou)FP;d7Y)6
zA$^VJ`{<{}`%M}iaT-iazH;4~xt7adYwNiLgZ*XCGipSChlg*N>6o5&&(uQb^>(WV
zM_)hMrR6CVV(xzR!8eWB;%3v{P7a^4YjFVo$}0AGM|5N?D^vNt%iEZ!G(DbhDfNNJ
zw19$*t3NlqR6N+dBit)-3){)&<w=TsNx?IDIt$_^FLHdy9K|nMw_#g_h<3!Eg;FY4
z@^_v{K9l)Eb=#6zo4el~yti=6U%5BaxBqxqP}ES<ufL*<zvgP%%!zxiMHrbCNU(?4
zZ?ZYjbg_TBYwTao_XV61|4!|Z(Z3}9qHM9j=k)V&yKKZ$^ox&+US@ke_vg_Fx$IRJ
zzOyA3_iE`snDK(^dYG?U!1=^tp=tJiUo2bPRk3ux-sugGE}eeRFh6#>s|>ToN+<3A
zugex(dG(2V`tB?7GveESI~4Oj^L@I!c>Y|izJo_}wFTTJREYH+oh>gC-O6gs$!5*X
zo5|kxP+-Qt?!>!2y|X`SGw}ViThO=XV)Twg{=6^d2RL5OT)A=cf+dck@>3>WuG+rt
zka%)vMZt>)!rdu98}B@+PuplYcgMOjMUz&~(8*ggL+8>_l^r$~^(&=0Tgq!SwzyuO
z;IwviAd5wwW3p(5_y&=yeAU%y|IDti<g)(|GW&Swans%MFT0)U+CqHIbQntFk6*jT
z@Hao_%ZA8Z`x}!L*Li<9X3=Bx(s0wGBV`qy^Mv|$WE{WgU&DUtjEl?(<J3J7GH%xA
zW-IM7Jh$s<h+D2ub;vKzwJiNB*2HdGSGMrA*oT~r8``aRZ~F6k*0ZSN`}&e|FZkSL
zU@qIf`I>q5Ov7;17{!}EL%lyNx!4)?UcXUX^p0xPyl<>u_8hv~d~Vm8<^_v9Z8B@r
zwRV3v%i_<$e=_ZC<Ex3U)Qwtt4w%Zh>}2_**gAvz+|_T1wrTPqCJhFgE2OXF9IiZd
z=HUb3*H3oy7aPU@i+QwDr0RFzOnU|Q%dX+lduHqiTee_L{-OnIF0($p5>zj+@8|<B
zyBzr$esR<0tn9U1`T6;SFE2LAS&5{Tv-<`5au;z`Z>U}>e|F#5iukRcYTusuzVyZM
zqW@`=YF4y;Wv#WW-MO0o|60v^f<N}1u2p#VNiq4noY_H-a@M=bFW*0S@RLtKU`JR^
z^-FhM>+Qd?*Wcb=Wq$4L({sOi|2=ZJ?Db{xy2P#e?w`Krm#3H?5Hd3<Wtv{Sp)2{<
zQ-+#=YQ|MYZ|<8Nogkw7{o#JU?Y9r}8Ly4mX1O+b`Mx>23`<oEnm=vi54-rjz366q
zgFDYUyIo-i_NG0XUUfaZDchiA;eXSJ7i-R}|N1N7`PaDc#|#&4M+N!@|8RJ+xm*15
z$`$;~>&qJU)_(pJ_HMz{BAM{*{$H+L+1;>QcXxkU>Wd`{BGvA(2Ip_T{k_5M>*RvN
ztL)>Xyu`L%)p;eiao!s7-G^uT?-C7~u<Cxaw~NieOHxmh`9JNod|G{b=X+im27{F!
znC5lmR(!mW`r?g$t(DoADRTc;?knKBr;*Gv^W**Aw7qG^{(sn8^yj;+r~HQV-wQaG
z)s^41ySwvd<g4|MPAvP{do=F;waE%^(+l}7_xwHdr|9_&#!xlB1K*DRY`y+`efb;i
z?O|5g$LFoH-JIWb=H1S7Uhab0mWjS;*1d`!r#HsM9$e^uApKRq=>)rW{@cs-PfRRG
z_nSYr*>_IuXGZDvu=9IsKK9f$%sg6ope)aN-Q&}idFSoQePYWj+P{`Ozjf?uZSZ^h
z`e&b>3ZI|L8M!%U#rAxr(=l77e|^&)S-o!k^3ALM`TmVC+YoxM?%|)#{y8)IQboTQ
z&e_>JH?qv2U1`qDmib$Ir_OMBv;53iyGvWY7SC(#wlJ7o_wMvx-mAWBE-`$KrfNs;
z?P8p&nGwaQZ>+|1C+yqLRgOz<urt0t+os;SB<O3Ai}1>{r-xYQ-u^VHPi#lg83PTY
zlj-#ew$r=+9$e5a{98QlOEveb%j)^wzDIq9%|u^zCb1_K*WXMk?l|Ee`y;J5m^Feg
zhHFBrwO-t=f{Xk1Y$y=@u6X3hkux{`75{DhxwQLp!ov^XrP3=iJCGJhyQa@)4el_O
zoM&CapnNgamakON=>KGOz4;sCrApS#tN%9TEzkRD<uzYp-ru@qV-`AddCZN7_`4D8
zY<tq=JBs?}7mDTnEK1+VzGL~h*@qb!t(L#I@L}pjanb$rZYl@bS+0BZ=Bwz3p!Hf8
zlAdkMY1eyq<mKg8n;z!6OjdaOIlkMkY-(^+;jOF*wQ1*)XGB^r@wvx6Ma?>QUODQj
zX2Z}zj8)ACOU}0JvD&s-?Ld%l{Nu~9&C(aY3!IsKH}HGY;q2}^!LL$c_gp-!KX=aV
zmfDxU@)Vs73_nYI@6emDX5qOxyKCB3FJ*eY;ic87v+EW&?RhDs^>$6*EA?{WuagUT
zAFrA_E!6gt7yqkCuA3k2uv!<DW$3QEl{59_)+?dQrtONl7L?f$cZ4a8sk-#ztzUDm
zp1bInUV3-MuBNC*XN#K`UrE-V)0U;<_d<l@s+{X1qm$vsI0YYt_Dv795i6NwaQn1)
z+^&*WXExppU;Khae#3bNd;dAh%UH!1Z*y8V^V$EWpZ>dd{B7y{_<!#*`LqAmm{0xx
z-o*R=|F|VKALj>ge^Og)|251&$~*nTuc~@eRjKZfuUS{#gt*l`QhJ=xa!<T){*|p_
zJ-<rs7o}C~&n}Yq^XJmVsr$G(gl$=GSWOU>a-X{~d6B(o&Gu<ht5?*R?o1NP)v^iv
zav}JzK<jnGB!NXdzxDsmkB!`6#wYE3v;O+}%EUkO+k(H>O8#H|aOy|-_nuv|UQdl=
zPOh!Zt-Be=qgCp^?fCxh*7KVuuXc)f#G8Fr=+VLdA6Q=>DT}X}c`9U?;ALT_KL?L2
z|M&U-$F)6Q;y>*F|1kRguV?1_)n89Bn!3^_RVx^zjsSDZT2GF|yF#z${|&qOKYkej
z)ge#?muqM5`{>+v_0K!U;`IWLxF<WwM9z$V$MYcj;jM|Kl5Xp^UwXUx?bCmcjs+dR
zWB2LJ#qjmzzfN1t3OAY*F0e+g{XmvK+p2p#Cw~6?sy(;$rnKvp2U(G>>wQk$>9C)p
z{PN(%6~QTU_CMi_a-0|})RnjD#!Kh?XFC_=tHn0d7;o`-H9K+3l6^C6j4Zd5JfA+z
zOm)J4w@F$>cilB6RUG(r^>uTKpz--mQH8bUJ^H1;&OGfu6T8Dgrdt26Qdjr#du4$?
zrCFD*beiitOXs2M6Z6W?&a6KTSM+6nSb5<2#s4-x{OcdTY){!R?YQ9=p_=+Sr;hK3
zzRT3?XWv&ZZWqz|pMhhKGke*}L(kdf^iMi}@VniQf2tP${C@nis@c!Iub%CjJ=6XD
zT<W(!{I!|U!2IEFzry|R2fzP*`1|gMzkdtv9scmQwm>fK_Hl<g`)BO(Jx1S77yJqQ
z@lT+p>?MDSsvXnwdiI+CB2PZ&YOv40Td}v`-|Y{x9{$+QU8>8!K!#(l{MUo&{55tQ
zRrl=Pb(p7iU7FrfBls<`Fe2}N!#z6{zLRgyKl&zp$WDXr)LVOX1GX6(`a3eY>;GEh
z{I}Y(r2p@y^^x%{)61Fn{nx)yF1_#L5qq}#Ka%#Z+5catCYkYH<=?;dhs?#U+;7O|
zH#y%CS?FR>VCwJG_)9_LS-I20itQClUDq6UEPGk~yW&*HGV{_?t@Viy_Rl|3A9K&<
z|Mi|f_aXzo9{2Cs-(}gUT=jeUk=;5b<=gK4%YO9y!H<?7x!$?|TYhjhs;S=iSGclr
zy2Xm~|0_RoGx?rQ|N3$H5#C0%C#S1^mu}R%!16D8@883Z^f^pw_pjNW->J`KGPhhe
z)8g$ki>`2Oy;pB{t>88Z_T3vh`Pt9Ak9>CY9>1@=kMn={{9`w!O6>i#_fcZ)9np0T
z!WE(U<}S_)I%`!o{(ZYhIM1AQ*12NNzx|!l59Qk2=X?G5d&K&~*V$XrHUIA0v+wxP
z*T4QOJM+Fd$#mo2mKz+~qnXZrm%FpC@p}LD>Hs0W(!X{&@<R4Jw?Cd=*Y)e)vW@@M
zAABzU@RN1#-}4VXumAGCo?(8y(Czm8Pm<cd9xV8hzkSm0CjL{~9iN}{+7>hO({la;
z>K)I2UQSrB{Gs&s|8L%}cpu;RKA&Op@6sP`N<U10{1cIQcfa}l<qffa@9IZn{QrK~
z{MP^D52fGM^X}W2Ft06t%kSb})q?vb8mxQ${`^7nTmS7p?$+AB{>7iVu;<^kt>(wK
z=d<tIzifZKzx?_-XW9Gw_vM)<{rq7bvd{EyZPfeum!Ip_IiFl#@BH%j9rG#s>=*Xe
zyUPE+nV(Q|*?r-=Uw(ymKOJ>HV(D-s@Z*$<C>iEgzvT{m+s;_GU$)}ZmK5Fd41u-B
zoVI;hRC==NsMEerE52@8dgDwvLm5A(%T4yAA9d>wZ5Ms;`!-L_e*c>5>ni?!mwmWx
z)qj(Jw#@&NT>fw~{|__!_n!6MS*y0g_IC6AJKqat^wtT#WsdpZRl$6J+Yj;3(wa?1
ztnUA2{8(}C-=eSS4_~t%RsZsB{`NYqegAg+*l_P%^!&E<`rd!<vp;>O@4qVBl0WtJ
z{m`HH?L#~3>RIjT^PO_nzj$l=>yGD%?{`1^yuRVR_tcV~_Di?#7dWlF?{Bn1JmZGF
zpBcaQJi1-+M?QSfpS;j1weuQ{dR}r@Mc>@s!EeL)G^XRkKL2dBe|smt`Wdr+!IPFB
zvVZs73wON!mht27s^0-eS1+*rcfIQO!c)7oUYsgZyYj8SLtgmO(JRO2Z<)9K!q?qP
zw*T+=$}D#4{{KbWrKdjE?wGEB=>Ju&Y1cms>8GnR{r;EQ`0W$>*Kg-L_v?QAAi4MN
z{m%Vrr@#MSxBkDa@cM%jUl#n<p4y&xTX6rXpGUPH?S4=b|K{?i``oGS3~BYw^6?_;
z50(Z0vB(Q=t##bPay$29d1>AK_@72Hl~FZ8@&E0&{1gB2Yr~J)x%cxsJ%3oK{tL+W
zkCbm(|NKb5AIqN?*%R(t8m@eLK2pAQefOikRlh@DoBpWsys~v)@l^kYebbMotBKAN
z*OI+a=c@Di?fX?{4u3m-G<L6T{7$yp>%074zs;V?dgEV9h41VC-H-Ge|GgKgk9z%^
z_jP<yu2x-a{{QsTO`q3y|BuZ7Kkw`B4_{~fSpVy1PRDJ9{W@u-b@mGXqHnzGmcRV`
zzclyEo6?VF-TSxd>*fzz760wK_wRpH{P9a#yQ+RaUmM@D-oNYmmv8#f|NVdb>ZwRj
zV*S79NWIv<`%6=s-tL%JZy`DN^UbVZUxRP|w|Xr1__q9|-+hhi#BOE&h%>coJo7)Y
zvyOdJ{mxnctaqGuVEcURas6JaIqZ4qZ~ODtzp8bd_wn_?`>PFSrmsHy{mffu*;K8|
zdwl|UHa;|a`G0@bkN>+b-TEJ+{pCNu@xT8~5C5;{_#J-KexfDozkmOg{>^mw|9@{a
zbM=2w?w^O}GYiGv)qazHAZ*e8|NYCS)LQBJaeVpyf7-o&8!YrD#QzE2Tg#NAY33_G
zo9oZdZ3onfUY?id`thx~&3^y+56|U=_+P*NIsH+!&J*?BU%u&g#S7l3`_LYo_1iu5
z_u;ya)>Xgvi`pwqSpP>XuX&&8&y@Si|NM8JxPSha|NEVP{$E}w{qsk1+y8v&e+Pe0
zwP!g0d46}j-h}_`{|^3F`)A%*^S}P;^<t?U-A}bY|2_CKf6E778KXa~hab(Ui+k~s
z<3Y{(_o266d{?lq@{`X${cWP;M@^f3(Kq~?|0^Hh{&jC<MfGvPkFP==_$O3%DDRVy
zbFV)nDji%{f7ttnh<w8y|3l9ofB4BA{OWW0m*Y?V&Hn28>6gs1`-1-$@cfcp@9TR1
zyZ5i$g&(ZA-}41ukdyfEdwu7U`VZ1dFZo&iF?Rmfy8N$PdG}xaoBP5|Z+%zm{kGTE
z?f1QAx8L^`yZyd*yXV{9?b2Tl)-ATHXwSOOefqO?=<j=%9V_dnU)=XSkNN(4!&~3)
zWk0B%{O|we=r{knf1m!ZAN+61>Hqed5C5&tF8Lq-^Y>-9>V|LswR`^OOa9v*`s=^-
zssHudTmLWp`FrXA_+S51wSuF#e$*zMH$VE`^~n4BkBpWJ&cwCtlKlCH|K;2FB0F{@
zh1P`T$4~!OWVA&+_oe+i&e!$spB~mG{;dzP(VrmCQmS&T*nZV*^TPYyA9gd(_qUs{
zuUBT1PpVe1(bfa=YkmlKY~Loc;pbO&6>j!F=T9-t5IWC&{GfHt!Lo+ukD317v~75v
zUUu@^;p4Usj#VqP_dnRCFZZ2se|5uu?>+f4;xF>w3GP0!#peGGTjkI9b^kH+*}syT
z{_nWlkLu_OneEGuBzL~uyC`UFSC=VgxDn%g_6N-M*YbYIug~)e`L#Rfb%*xuE8m~2
zd$QaowMu(={bu#d_r7);B7gsn{OI1g<<5lv%H4<lC11KfJK$@3Yt4go4!`9;Fg{&x
zyWod|>I3HBF8(#FH4hYzvTHHQSE%IFS5=(9R@}7y?}aGg{Fh2660IBczt>sX)J+n*
zzgJqX=DYaO^m**|Uj;wzu=pss^Z$b-8|;+#ecsT^|7`Q}wVR!GJvhEU+sV#xpX2Ml
z^MkLOer~AxSN-%}yYThWKNHVdiHrVhI^mvL`>f*DyWn5D{xQY~-)h~vY1+NrCtu%i
znRNZ@O!p({{q-07-p;#tJyb3Ce{RnG+9<zU9dG^%{#>RqFTB5d@rUi^2aIq0U;ZFJ
zzv213N9@&%=k2#ee{8h6@q2H>^9K2Z>MwB@J_zpZefzTd;6Lv_w~sg0Zb_`}f5iT+
zusZD3{GdMv!oJn(|2g{eVBE)q9{DqezS$k+?0eUg|Aga!=#jjmf-3P0bqz}k-Z}=Z
zd~<S*wb#CYW!t?DWfiRWA8+vZziZK-`kHfz&s?s?Y;Kt^w?_Zlug&K31pW2TufKml
zp4}ng+cCz*=N<P>Rk^u28~-p^z4V^x%<IL^`(om6MNGf>QnHNwNMnN6bH>8l<kY8q
z2YAju4%~Pz{<g%5z2Vn?hl^i-md{!FWP_E+yCY|gY(4k&-l^P;H}3D)wq*Oej-&S+
z&fI^i%e~|8>?A>R@u%Mw-Pw38zWk#-|NqZN|9J7g+pc_W-Ir_YzgTUz%Kq>{?DzH~
zXY29<YnBv0kE*ZB{dmQ5BY3;ZOPyQX=FhIbxo%zlVd9PLPyd%ckTPeJwcy^qE-pBp
z`Rh`@on6n@eE+3gaH;tDx{_<xthfK2y=eE9`SIJ=-;m#4`&;;z+o7|QE1Z{q%sanE
z=hXYn-QFvnmgH~PWm50{dUpKoeF{%PW!vm;>^iw;Wr3USzK5%q|2n;T@6x^+!*a!k
z{h!12=ZSLvoqBNBTKRWBubN&cjeYO3(>vX7&gS#0y|0Sb?9)Ckbbg*~Ih)?n)k}{|
zEqVCBZhgt)<(;4R9zA!eDnE8=w}@$YoBs^%bqNn^e6n;aON$FWoH{i1MT>U!!iaiK
zz6Y0M0;GS;zZEC^Jb!-tUZaxdc}m5fSGdbg4YyYO__u6h{Nw-k?Ky5Q7rgJj=+^_Y
zc=?J&V%ON;{F(2Z`MG|>^Rn5${_{)z{Xe(q@Bc$D{@a)I|NbA|@^{A9HqmeY<tw_s
z|9{T?SRwn%&aH7j9>2I4s=nf{iPB=_yqd$^xocM3e^q}YCcb%BT>hHlMfN)X;w$!k
z_{W!(&h?)4_w?pE`8SQn>lEG?AKhpCM*APjo5STD??s>Aw^?(0+Xj1n;cw2zgukty
z_3|~p%l?i00>7_(fB8A+qrJh0{62P*kNf+6*h@XCKk;9@?Z3Xn|NBON>TiGezxLzL
z{}pusdFx+o`t_YNT=I9s?O%Tr@8A8M{QOY_0}J=7<8`%ftdH4w<ODm`C~VvKU+(wc
z4fADg3kuZV$nW?n_HAkMf0HDZ<DL&9xZd<1GwOY;@#O})<uj(=3pVmH)z<CdUt``}
zcm4jg+R5{;{+%1){%=XZ_g=d*$+!9sZWOfm$MpL|p$zM_&>Q>v{+@e(t#<v7e;fUO
zcyCN^NY>fl|HJgId(X@FukvNqH&`4kRE^l4RNGm~*VlcZy!-wC)w^sS?LP3SC0RsZ
z_x`1y4;XTFJl}rwkM0&_-?y9pdwhGX8GKOXZ++sA|9f-4{cnBvzq{$*{tN%=<^TNe
z`u6{Q#{d61+ngHz+wb@Mzdz@{v|sA)`?a$-^w_ebKApJZuXx+v{TVm@_a*+f_WW)C
z>CgY=?>B$kul8U3`;7nHhW-CdpZ~Y7o&WK_(Nn*jAO4Fn|1ZD%=Re2)Q}>Sl`d{Dr
z^8a?OFaJ-Q)!zO8Ut9C<|3wl1>n;EN_kHnyx@P&I<E?MGZhR|{vb%iXzW@7U=Dt6E
zmrs8C{{jDv_l=wO${W1U`hTF#{K+o)4?nVZU;SpyVEvnM|L0rv75abPvj3LpQLoya
z(_G>4XPMpqxeaUoe$f7)zM<_F|Neg}dHS8lH=eu2AO7v{uOH3|yXBP&GX6hu{J{F{
zaQuV(H<ORwSFGbZKVP8Vo@vu>$K&B!|NZ^+KK4;{+3H_uLa)~SE#P;o-OBw+tLK;C
z4`u!nkKc!W4K=^<Z`+1_RSd5d{%yG5^~F<8XzIP@RqsDqT?zE&e_eOdean8P((6K3
z(l<NKSN);?Ks%(*j%)vYzWIMYRI=CHQ#<`%`U8*se)UhW_n7B@Km1&v#_yGXL+=8<
zBgOv{$~W=#T<^{-O}=^m=QDq6rGLlY2|oYNk^Jv`9u&XR?fb9Db?$#<%gq0qt7kv|
z|7PF$=l?slpZg<UypR9d>!*L_7ya{}d1}hEpvU!ciNAh_wLh+B`+4%)zSKnax7Q9<
zJP^H^Z7leW{a@wB{{j;GoqsW3Z@nwHp4&#^3;(-Gw)3kG|2w$)(JY632R`1nc>ece
z^@l&FLYDouJo!WZ^x=>8O!W`4m5%>$F#dO*$^Kt^&;QNWJN_%bEBrHGRQcceF2VoL
z0}lSMKh*JGdBzX>MG1f84<7k{Gxx}ULFHrrBMl$@?`Zm1@3;Tw<Nqx8S0DQ^XYRBM
zUiMnI|6g6u!|;EyQ|yi-_BWod3V0IoXutLw&V_6Oo`3dt7=+m#5&D0cP5y;Tjl-jQ
zra##q?{^CP-|#o|qq$2*{f*iaR^ku$tH1evGF3_GPknn#o6@2G+fS#enf!bBOK$RM
z50@YHyJOZR<=?pXza!?G(xLx{H|@9S`u}x<&AN~LKmUGz<Sh8_;je!^IqNU{SkLi$
z@}|9xkN0c6Q7v?D`7!;YLzPnBfA^<Fl7j!PmbLtMf4WJ$zx89|)vsB9{2!Uk`(J0c
z`hEWT7_lb}886?mKiwoRFYx~Q?dm5+vi+-nF|2#vV4=RDj^kCc_?q~w8*Eip@XJj)
z|9HZWhH3LB{rwjB_XFR~o{n|$3j51XsoE?%>KiM+$6L?aNcb4{ZT;!0ov+%zpL*)O
z=+{HrPk%J*Zd5=0q#XG7gIwi4b-By8cRzg-Qty66{KfLe>K{VS?t0`sH6^z3zV*_1
z0YBvP{`)`p@5=W7I`5y^{~8QF=<|TOmxm7QPxugT3gU%J{wbG)i|O<HiDvt^o9&-A
z+rQRE(4fWf2la;z?APe1?>@Lc;X}URkL?nF{H1=(*Z63^PNet0sMN!27c8&3=lqU~
zyL``n-LdqCGeVzimY-0~-+J7C-m#B4^Q)h9FS08ArEmA|;3?&bs|8<o*Jp6AQ>&8u
z|6sr5l+X2-FV$N8d;c|dm2LL&slWB#?J9q2*Y`iAYu@qWR`yEkU+2HOHS_7e__slY
zJaSX2<pbI0x5xKyh;*>xJJq-R&33!#s)BJh-+g(!zU=DfDu({|f<-I`;&%SIXCV}G
zJ$+UEn~BDUuOG49xcb+wxSNUBzrJ6;`t`3%^X7)`t9!#*8oPf(divD$hr3_x+Q)gl
z<*ojzwhv!Q_xjo}T|Ibz?~lvB-W)%<y8GDwnJ3kr9@*+HXBlww@4n;pHRfSnMc4l?
zy#M(5_rAK=n=5~m`qut^Z`*tQ>-KN&)_j+UxxU|h@{Z;Y5;514`QPdMmWa9D&Hqj(
zP9o;Id~HGcwDtRY#is=B+w}4L(u=3VL4%NQeK`(q`M6(s>;LkeZ~If1{XK7V>%Us>
zxBZ<>Z~w>qj-Q_Sf4$M$`n2EsZ~jxC@ooPiu;|5a^`|rb&o;RAf0fVg{i$32m-c?!
z&vp6VeeK)-%e{Wf?-P~D+&sA=?&iPnZU1{!r@pPv@nUm5cp&opQ?7ZJ=Eg^Paeq#I
z7an*p=<}83d`FWlt4b6*=5M+a%~^l$K3|>Qssq8{)2o`lCfq-^px89`fAQR};%3vH
zCmBZSm0ydODk=G}s<=XnErRLi1D2k`*2Khu^8D0|#nH!)M_s;u{p<IwGx{d~z5V=Q
z)Z>Gz_@vtxziyYEF8*w~mE)S3-klo0Rp|oWT{R_%JZok6CGNj%G!VMQSeQ^*_jg%W
zy_+|?;MKfN>7=E``^!Y-?r`mU`62xOGg;X~JS;~N_HNb+Gn=-)^xC>_yTc2M7d%?F
zGyJ;shMf|vQI{F7?s?E)$J@MmElc~AW2)voGfF>fsMYv*;@PFXPVad$K0na?c5VH=
zDTY_q-3xNODz+{*_LxWJEA}?$!}051Yh?e}y?uvD|0^NYb6=l}>z`YHzoV&4b_@S)
z{{yqV<2ni}^!A9!O02yd{c6n_{qiHy(sQ?3hhKlcrtFA=SnJn+LFu`5sSA}c*N$Du
zPrWw#Y>hFi%b`UJQa5F{ZTf5Py(s6u{QJ_WZ~q^g_~G28{{GE>?X7QqdH8$9-~ajk
zfBtUzYhUL3J^S~6|5x94T)y>Rd+PrB``iBK+x0H~YybS${^i_#|Ko2y`&u8qt@6+R
zytKdZ2Yde8r}X@{KeFb(_Kc7JwU7Pyzc>Hi$Nz<^YEx1l-V(fVC*qaN$>&*~onL=$
zeLeT9a^yU-(!Ni-9#?ISY4KhA-#Y)y|BW-hI<i$hs?SaS6CY^s@BG51kNd4yAODvz
zdh}n$;L-mzJjefg9r-Wn^Jl(u{<|Ocw`1#bmf0(;<=ZJ<%e3>_|CuHqY&CZL>%Xz{
zV}1SK+3_3dWcTf7yI-+$Kl^>YX+QseVSO#j6!@z1wb-JSeEuwpr^zxtNmg0#ohfQ#
z_@_dLtHK4}_1xq)ZIFNC`g+pWuCIy}PW@5((d`dU?u$;SU&{OK7ej)`@9RQ;>#sKb
ztruPPe|`Fw|E2B6|JOSl^X@$MKYr6c_3X=^>s@aBsK2^8r|&=ik3+jl|HmH?-^V*o
z?Njpt`+%?fyAtakY(M!gUjGUA`>D@=ud=_u^@};%y2<{I{}1-iqQCv@$1MNryZ`?m
zFH-M%<mdnM9rHyC|Jf%mOznI2f5pGQ9sljsLS6pE_p*2V`k#B?(6Z<MBM<-mUmt9f
zdGzQ1`Bx{N{}=FmdA--4Ou_g6<EMR%KJs7x)DMSQ|NX^|{AaoR|Gw^x|M`#Z8-1`p
zc;^4gXEXncAKstv;lA;Qc*76(Q$Of?{mD0*`uBfK*F5)||L0FU_3!`2C2wE+Kks+(
zv&QfLJ<1Q~E|u5+{l6<V{O1338P4}Qe=BbO4}Y`k)W7{tObb=_zxjW9@}lQ~-~Owv
z*UbOfb^QOauPu*0?w>Ds-sR)|=|>*lu#-LZzwH!r^s`4F_iwDVmHRJ!`}L!b`(J<B
z(f6PC_Kkn?{r~@({AvBTKR)EO@R7&$>}%^B|GbZ^{ImCA6>FAt*Z<zPEuBB^?|62>
z$l$?K&A^v-Yp&~b9Q{A-weayr^{4k6{VSij%}g=u>Yx3WFD3U}`(KvQeN#WHW=_-o
zzm9*-iT8K&AHH9=qC)Rg#eel9oi2a=KYmo9^zXl6p^o7H|0;i;9@}s5VgHc_`>mD!
z9i8#<|Kx`M;-!D;ce;6Y{x^Et^QBk5Xw9>7{#hQ5`x*9K7nGT2)4{LzVr|Lqj|*9z
zeVZ7gUHzHKS-ax7IA{Ao@e7lztd#E`+W2vz_$#}U2PKbbZrmt&kn`EBmzI8>8oO>r
zN`LvK?VPVxtHu5?ZN^Udqpm^sedbB3v98zomsZrfMN@0Sf48>wTkoHIv_G<@$+rvp
zB#ET8aUlc0*>3w^^V$Eu%(wYFVa>Wi3%;u2`SS%fHRt3xo#@=WUpr*;fBuk=>3nJ>
zxAP;M%2@2uIbZ(x8{~STZ}<A}mNy%IOL|+b+8-6lt9{;|>t^Avezlf44Zr_!n%e&P
zt$TIhhuToZ^>33!6<<Eo=Tx*7E1V%(=27Rtv9m{~Zo~Ii%AtzZdG%RNC-`>vb3R@B
zZ=LGynMd!fnjl+Up?iaIZ+6g$&fE9(RW6I{=s0uRJonD2Z}nyi`$}~}{y*ft=6_gv
zMqB=!|C{$O-dE4MZ$D%Hx9bn3xer}`@H;qwsh)q|!y=cj<yU{q{QKdrYei-M;qU)h
ze`oJseeCj_w)~on;Bohj2iAbc-R&^O-T%j$>OIf?_51smkFU(HeEj?2uc1atf4%e5
z=*#z)fBk1!d+(9?ls~`Br|dgl>-_S!@UI`?Up~(N%hvb*VBpdFn#cdwxXcmu=kV`i
z&Qdw{e^2y^Lff}JAMGvdUTl#0U+l3!{Bxu4e(kBJzSS#Fefz)Y{kQF#-(UImzdm*9
z+y5W4cg5fSU!L`6{ieV6mA>Ei{M~<g%m4j5df(PhPkvn=_N}Wcbld-_na@>@Xl?sm
z?elwo)_VSH@40?4FZx!0^`89J|EvEszWG*vHGYHZ+yBBozw56b_}?9U=U@KIfA%^5
z@2~wRAOC;*F7-qEL=)s+HG4Pw2O+8de}(?1O66-E|6jCH=6`hG|GnlA`f2dZf9Xp$
z{q=u$_g~qzxwrm>_x<;cyZjf-IJ=|i_m;o<`~H3B?~)h$_;r8(i64v?f8CE4_}{B>
z{l8xD%ww|!+CKh}ceGis=7+ugg6$_O?2|0yPRyV3ag*Ai3Wfbz|2A@b)c5)`eWlOs
ziT_?-|Nr{>M!p}lPdFr-BZJvDr13<Zm02+>d&-B)&0mkk)qgu?{OIM=pI@baJZ9iX
z=*hBScP>g#F)?Z4-yHQSc5-EF;Ce-C+e7afEChI7+9<5cU9;v+XH(GX1DCVjU;Vm|
z$3gee!&Qgp&X~F5+Rl5?JJ&ugTfNpgX`{Ko=kn^)OnLv8MI1Tnx^u5a`I@iSWB;5#
z{J%!lW;bMv<wV3)`Ot-{^1oGgKT@_b`nqy*QgZ5r-TN*@Zb@}`dEL4^Wy+`9pZ;4H
z^h!7L&1sDeU%zsF<FBCQF-MCH9+=Mga%ZRZ+^t{F<^EsRmtLnT*<f?SrqjH|@Z!;#
zQ(b@7mKAbteIf8F>i(ZwUt1N<d`-Lq9!hb+I+Wtu5+eRQ{JO*S(!It#+iL9uTYlGs
z&r_XeTm6pb*qv)ZkGysj6wD9b_3`qNpZAi|Q}=GKb5B{Z)2PNtVDsNUhknku67}iT
zvj-2RwrXGG48P{I@t=^)f#o|Fn0>I{x>xPoeY^ctsV~mmb$RwIu-{5+{k8)gcOES+
zFgN~G7Q8su-0;x1%*YoTy)2|Yhwr)Z{^}~OgH4G~CnPD99$dD-dxQL8p`*fm^+!J>
z{r9=dpA&T~Z|eOcAGd9g&*Uv@t=q9`1s9*KOIEAz<NNDob4}cr@LjX*#z8gToOA9~
z&5G#;X9Brz2$yY7vY1^T6L^+Q;@<QBE%)cQ*8ETZkx;Q%e!YfNOYF+KtFpolZ*Z7A
zdDTn)*=ZXzS)8A5DO)+gM<R{a*;;Y0v$)vqP{S{LZSghcClVu+OY-;6Omg~n<;VxS
zH)5_??IFCvZKj8ovGCM?X}q!dcR*-w<}rhS>Idd+@_$Z$=uMP*?x5e6{43Xc=WqGe
zzY_O8-alMwv;6aqwLJosH+**sR!@KaP^$jwi^D$xZ+wr}?pl;2q0aNW`O8=B4gcRC
zT+S^2=G@T<B{!CA_5L1nX4xJ6wn@LsLq+pAoI~Et4!9d0f5gCHm*@Zd)n$wyU++?X
zR{eFWdGht2>%VTi-}wH1JAYgKuUE{6e?5xbd|WN`J6D_dAp__CtWVB0{k#5wdA~jH
z@r}~bht-ujkE`y>3%z0#e`D@H)*rohAI+Z`;@jo;YhJ`=rnb^waf{D*->tg;Jh@1s
zsL0iRarx`o^~X~Fe@YRFdud#7Z-3kQ_lKYJKQ!jN{#*aSXU-pgLR?$3Rvq|TpXkKv
zdtjaUo3;ZRV)|b`|9O4mo)_tz5C5(^GVg5vv3as>r+#g!yLO``q<`vMdxKd47kCc^
z*9(04XLjdy{>#_LKQv1;z4`m$ub#y>e#L%vwGfRJ`?>cU+K9G&ITR2q(ZzFk=1GH)
zYL~1k-{;-yc=$>WTnL!&qVsA~*V%{n+2wg|w<dB=e`wBEcpyxdXYQ|@(AFGh^Eaij
zc7`@ry?@!&`%GWn{`K2_-~ByCdqaZ_{___Go%^r-{QuO?|4;p_fBI*C(ZBn%lm5le
zyb*Hl|Kex==ZfnedG>$jqn?T|8})hqXZ}|Q9cQ(lZTO$xolpJw|HPWR8`u4hmNopB
z?|(yFHz(~x$N#&jkLqW?{?DcSFMn$1f9r!s{;!+zv3|Q2>)+b%CjY*($p8QC`I=R`
z{LlM&g8z4CANjwH>)3xWw?FT>j{UbwNj>&|ozchryWRfeAAGPs>%sk`5B8Z4?i+o`
z|M>C0e$@YDvwy9P|2vyL{y#e7@&9n|KmFRCfApn)yqEY<Kk?xIQs(~~9jgvjG&p_y
zznb-<zFW`#`)7s!&p)tVL*oDaBlWEZ?bH9eI{vml_+Y>JqhIo&%>QGV|4(ZKb$wGG
z)L%OA-=*{a*=4#L|DR_2XU+Ccm+k*#wtwn8f4;jNso%cf?{-+{c{S_D_$mLRl^@;T
z@?W^;?|P#j>kWR$Z~v?R^Z$)WN9vCs`2Wf5_WwnH>JJ^Lzj~m))a76Nm4CB;te5x!
zH)40s-}wpG{y+L~{^S3Xg4h3Rb=9wq`Tu&~w*Riz|8H_TvOn{`I`^afSr7JC_5Z97
z{B5uG-~3~~<PY=f|BZg`PXz_aeN#wF^4kALZ~nVv{y#o-+tL5;4Zqbl9sJ+YSif4~
z|9Yt(^L0A@uWS6@)%bs1V}16SAM3@A?7#Uhz4yky?N`6;fAatP_P@{n{9p9vzSPFQ
z>$4x!7j^%%PyfH02Q)yin)Rc-q0;~DJb(P}JpNk0+UNKD&i`?sAd-FfKb-qhefPot
zM><~rFPr(zUKr$V-K_uWlK=917ysYi@b^6^RKD#$_2vKUANp_qPg^Q`@qfI?|7Cy8
zfB(1qm;b1K(SpD0jlS&<68N9?d;ZZ6|MimppZ)iLRpbA6W}p9`6#ThA^ih3Gru(=5
zpb-n@Par>Z3jX~6q~p*2s{Y&mef|{x*`M(r<Qvg1Af4+P|7#`xKmG5&?{e9T|L^N&
z{C9u*|M`#lqX+7@F8H5s__lsB>qk)B?>_qX|Fp*cuWa-FKmHJZ3#9(x|JmR6Yy3C=
z{eP`t|9{=C`g8wg|JfgP;a|AK@BDB7%X$BVyFd9qS$W%k-<}iycc=dUzvEKhi~r^y
zL6LCx(Z~H^2S4r?PR{$U-31EFE&nHH{{6o{>*>4y=0EF8T|j1p^ZY6I{=Gjm)BVf;
zaEagcme2mxuU_!?eP71^)olNE{;ZGrJ>T+Q`IVob@tDm2JAc+MezbqZU;U5v+gcbG
zY^(V@Uz~g0e`CW(zwDp=ihuUY{?4!XyN2ujZ(el$|Dmt-VTG(cQ@+;!s&;vL)HASf
z^`cEO(f`w3*Z=>z_OC+py8ofeKB{;A7eC(f|J{u1{~ulZKU>21-|@Zw#2?j*efTfh
z`=9GU{mF>`>yy^}{r;crk38!iedd4ZjQ{U5{i$Dlq<-eH*+FmrcYpu+t6t`xI@hE9
z)@*;+U;po%^3`7d_1FLVMB{%8UuQPG_TMJz(SD!DzR3^&$Fltwj?Vdi{OteuJ50az
zzx>+I_)pvL&wtI{|FI4K?YV!vXZ{y&@*$q_Pqga4(<b*+KH3|m{rmrjZ~On~v;TKX
z{#eiaZ~xRs|D%un+Aq%Vznt;^S&4u8%>U|Ff}K<L>d$=1*Ne8k{JB5vkN&#<{n`Jg
z|E>4$TmSd|oBywk{?@xbuAlk2UaRK!|D_dw?2G^P-~504=zpW*{|i6<Kl80V@85pO
z|EuTx-~4im^0EIjKL20M^Ka)*d)MFp&;E#a{g{93zwz<^g@6C2{l6df{r~Kb`>WXg
zo&9IO?*IObKmNx5!Y}@qpY~_{rvLeuGu_YpH+*Zq=YHgCS8d~e(?OAE|Ln*9MIZO4
z{5hYgZT#<g*zx~5UG>HP`Yr$4AN?1<?O&qVznwqgm;KfM{r|oGpZ8mS+8;VlANVi-
z*nh24|AUYJKl&kl%KzEl?)UsZdi1}J)c@|y|7HH2{b}#|xW4eCz3-pdpX+`86o3AI
z`ltPDKkKA_{(*mrKi8l65ij%aEXdsL5`Xq{KB}Me?f#ShX@Ax)`e+aG)!TZ>|Jga5
z;?*)y|9=-I|9#JI^tyijgX{nQO*&S+;otZ39rMLI@^8vBd_B(JVXr4}|KhLv^Mxxm
z<;-W_Qy*6|-@%6c{N|YNyM0onY~OZ#v%mb$`ET8kT~p@&pZ)p2&;R>9|4$zMZ~S)u
zlmEtHX@Be||1bVn@B2Id*nfk^|HZ!k-}z&|=Ewif*8JDp|Mz~@|M}UV++hg~LF3#1
zAMQww-F8gu|M?^K;{Wwc|2@w!`>+4%fAPovKA@0!3<{IOpKDM4au0j<$6oK>e98aK
z-T$*6?a%lVFZ^Hi|NW9%f}j5f{rS)G&-eHFv;U<{|HTLX$uIpAZwyj9x%>b0#eeM^
z>(Biw{`lVl<Sy-3|EK?ukG{3?aeYj-p7ej$xBDgkUq4d6?nk}*nmZsx=O5nh`Jesi
zf8gW)%Z~ito%DCs)apO};Fx;w=zrnI`m;akpZ=KdyIl6+|Jfhy6Uz@*-8|Lv-~81N
zdA)z}S%2=&nkxB!ea4^uYT5t&kN-E!?~nd(vj6Y%59g2mH~m>J`TzUb)c?l?{+olG
z)h`9IeAVCnhxecSU-tL;qyMu&Y1Q8NU%TZ0^F9Bw!HM!o$A8a9^}8ScpZeqerY*t8
z|BD>jpZWjnkNUJf_tzf#zv55*op1M#)O-Ee&+>2QkNs(X>^J{CF9RBj==q=C_x~Z-
z)Kee93FlA0<p1s25AOH;H-86Gy8p_L{f2*LfBf(BXZGX&?z#V^&HtM}{_oo}^MC*C
zf73tKZ`XOt@qhm2|7m~hFaIn4`~TUG|BFDX`?EkUSbXfi>0?l+bbqSX`zPOCzxi+e
zoj?2EfTQN`f6X8D$7XHcmisUN)sO$nH-C)Z^7s6f|1$r&&;5V;W`Ae>iTZ=To`=2r
zvH#hh`_;1luh01(4KAK9{?9-5zxDg?#Me<~|J-~3XFr-h8?-Z3?)IL)&!7FD{pWtp
zf8)3RS3LfI_UHbBnv1{wr`)dZ`!9ZUzvch!EB@*~|KF$k_Qb#Xiv7pevTA?-6My+%
z@eh5g|KYd(r>{BlbN}K;^Sl2if~s@1f98V!7bpMa*53So|BFBIAoqW?_xTt9?SH=2
zTaN$ssej&kuAZFxf9JpdfzSUhd-T6z+h2XD|A*)N&%RYJ{6E_EzxapZyT8J3ew#o0
zf3(TJ_Rjx{KHB^Inf|T*GN|aE{Y`$``3Un(AM<b3Z~lLO&j0Lf|7ZSq{_Ov$AM(pT
zJ-)x?|98hf{nyw0x0U{{_TT*Z|5@MWKmPyp&;7Zr|L0!&&;R~=<?FA1e(0Y9)etM+
z)}N2s`TYOPALeiOch>9ua}WGe{LMb~-~CNrO|vh*{y*!7{^R;P@u0?uyz`&_;IQkb
z=KMF$`fqRk|NNH!MStFR=KPK~`FDK9=l^cG|Bc_;KX~5ubvD@T;Sjfj8VSkX)`$N4
zAN<dmZMYv)eV_eV|Ljlv<p0G#rhof?_~sAuxBquM2Nwaq^UwW%{Oteo5C7MF)!+Ov
z|JMJt^Zti#`MVyT0^ZiQemH-#p6~y&Kl`uz+;8|N|0^gZ_0I<B*I@=VBTSF~FZ%rd
z?9X~vu%TYR_rKht{OiB(Z&3T^`TyQq|IeTO|M)}xx&PW$|Ld>(tiJ=w{+74?bKR^L
z{_py>{^b91v46*N{~tH_|KED;(~mdn^ZwQA{rkViblb=M&;Hm8|9|$UzWCq#&idki
z^5*~TS^w9*z8^XB@BhUhBmYgG{XhQ^G|m32KlLYG=zq-r{g$8*lld3?{J-!I`O-h{
z_dWx8VIC;kf(k!SVT|eIKjplCK(fE>Ux93tPY1=?oj>)$|I>cUoBz8$2b3${fTQ{I
zf1ls+pZ;$b`&S<Ie?O=Wsh0ssh|m3Rp7$^R+<)n-|G-AgSN`YD^gj(8hdH21s_2LL
z@Bcf0{#W}4Yy9M&`~Uoh{q_I$uRwwPpY=n2-+$BF|GPecqQgA!!oT9z^?kSh&HkbP
z{C}_RTaN$txBS1_^cEc8ptLA@)IR;c@1K6F|M#E#zw_t+l%Ms{r~aS)w!iTFf9>D@
z&F2PP|8JSN=D%{!*Lu4Q2rcIy{r|Z>XXK@CE56p$Mg8HOSp8Q%aNYmlWk$KKw*(*8
z`~0@gyz#%<_P=@QpZYWZW`C}C&;75T_22hj{w+|W$>_~~%YW^&|5vYnTtDMq{mK94
zbIXqWkT?Fv{``OO<N9N^|F>H!fkLGCbN$(G^~L|zTmGx(dHsLVpZT-@TWkI6{`6ny
zf3kP}sgL%L<NjaY@_#WXLt88SW4HWw{LBBHKli8o-f#JT{_Ov!dqKubdt7fex6B39
z>Z(sV^3h)A|MO@6i+-3t|1Z`HDGZ{|g31%u<Ns%T+u!rQu>NuVop1F#AMJ%eie`PA
zFa1Ax+kf%7|DzM%)L;A|f9Fqp@xT3+|EC|`Z~0IC_>X#_|93z|&GbM2{~h|zC-cAf
z=B}B!|1JO7zxp+Q<=cAww8!%w|DW^s`J;M~x&Ke!{4et7{<eL2Py7BKJp2FYqxu=2
z>(73)SNpf~<9|pEWB6~m2B^)(zWv|w)Cc$HfXbKSD?o*x_9>7{h1o!Xu;`=xj<5EX
zzvIvSmyOPPdniaZ$A8YW{6DV)cx`MNA2Z5yN?fh4kD1f5|8K;kjr;di$AAWG8_suE
zKPmieF=w;<hnKJ3@^|we{+9O<G#77J$g}PHihp$$-&y{=Z8!SqYz10UWIyHM{VUJy
zmFG3SZ9md~@Y`bVM<17E9Q=0pk^dtzktb~#hrTI4`hEB<TaLZfyqin6WiR5poi8kZ
z@pftDpSO>mfBC6fD6;MQ>yNC*k6!-Jp8BQw$;Zdvc&1$a8*prS;J>4fzX|@dxu^Q?
z0b^-Rm|Xq#iredce5*c^{P3ILjk@(Kblx{dy;b~S!!dvFhnY?14}ZAHJKz1mXNH<@
z2hxK=c7^`9r>gZSpUJNO(DSz+Zt~ABKkz(v=3{xkSN?l^9!7B3eCID){q|(+tLFXd
z-*lZy*kJ!p^K!H@q)8Lq_SgLR|Ji@$OaD(l_W!{%P&4casKfv_XU_cm|Ll*v@xT7e
z|Cayjg+JE2ZTkQC+y9;4>L>r7{`kKcIL&VUTOaa&{$cy)|Cb;8FR>U@UYY;gZ~6cJ
zk^Pqc_pkU5D#(uiF8~#C_A!6th5x%g{y*b~{?Gr*F84|NpZw_m`N-{?KA!LWFIoDp
zUhAKJ>f`+xf941N1+_wEeE$FNkM*_s6ZxP#KL_Mi@vr|+|NNiqZC&(-|H=PJrMFMn
zf~x44Kl5Wg|JRS+`TT$JxA}+nOa5Q3@o(o3d(F@P-$(6Fek%7rc*_6TpX)9D#UJ}$
znce%}v-AJwz}M@hTK=!U^3ndzpZ`~W*z2d>{=ew)|My@2)c5^ouCq(6RlfaCJof+e
z?*GZ4hS&T_|NC{{c6_v#`3K6#^~HbAulW2w_^o|o{pElC)}R*e{ht5H=l+`?|No@p
zzauD5ey{qszw>|5zyCKb^~wAX*6jdww?0A|wB3*DL%`kTKliu%SNj+I?7#Yl_>#Z!
zuqMo$|M}o1%#6?fPa~Qz?DyUuU;BQW(ewX(R-iIuw$%UUsoLLv?SJ;;f8qB3qDSqI
z|9|+i?%1!tIiQB&-K^i|kN($s3kvTK|9yY+-wt1U{@M2bX`o{My3GIhDgV9y)F;(^
zyFcgu>9e51V%Ep{Ge7so{FyKE@4w}1{>>lHpZ)*zL;RM%{g08#U3;y6zM!K1{*{ma
zS^nK;0TmU`ul+ZC{$FhF|NL|Rb*26<j`?4n18xX>v{#e()4%JV|HYsCW5E^QQ&>~x
zqy4KN^~L}6L51*a)UxN<+Vhb+!L5SB^%sBczw|Hu?6&`|AM?+FN(_;?|95x(ke|Q(
zU-#6T|Km&kt-ty2_}TyFALC2@<lp=csz?9)pYm}(=bzc%=D+?gU-~Z}+&=DKJMaH(
zV^F<Z{4f9F5BX<*?i>9(KKt~)e#L*sPhVROYOO$;F~y(jQ~&h$N6q|P-+k==15hPw
z4jM7o3DOil;eX!i|L6Ka4eUSr=ltKj`NRIpzy9ko|G)ER{~}N^J^j`{@x!3T2WWuf
z?9cj`KmCh-fa-uh;&1<(e>{KmzroM_H~;59nlJr78r<aS`1gO&xB5FD?JfR+a?MXr
zLA&_ef8*Q#-RAx`KX{`)?_d1IAM$Gdx^MjlCq<6`^&$WAzk!+)UFZIrg4$WaptdwP
zY-RrMzWVup@U#D-k3dbe{_Ow8&;L*T`+v5d^`igxbN;`U`XOHmYPS~ui+}a!zQn)n
zRsZH^g8Hy$f7VZHtX~JJ5TE_HU-a+)-`4+c-~E67X20eC{44+J^FX>T{}Z1Js&ws(
z|LL3mKcDm87!)?$=l(x_gJ_go_#fW^DpTfwjFmV4FAuKQ&;G1e`*#-9mZ|3hrNhks
z-SEc9IY^~j)&fdHYmI(9|MlPUcmAXMbN)}a`al1`{}qqx-<yI`>DOa-K!%z>|1Szo
zZ`$A#4jQMh&wMaH`v2tDpg=zR|M44p^Z)sGKK}=GBtgXA|CZ1GPyTWL-OqZ}|Mxd-
zQU3kk{ptT_f9&)A{RcO6?9V|OALrNpj}#%?`1o-C>;HbM|N5o>>KXssZ~y$C`(u6a
zzxcr4=hyzv1htc&{@K5ADX7cztv>0<zxv7lXFsm*KKI}FV|>X!`QsqJn?C<P8`KtA
ze&+w}OCR^Uf}1a!{zF>P#ee?Co&W#%*#BAI_GkQ_Z~4C;lpE?@-`ZaX6}Hl)|MD+_
z8bsdEw&U5K|7HF^|Mma4?f>=Gi$GBXYX3ooTU_7nxBS0e0~Gj+Z~YhgKijYI@A0p%
z4OqX`OWjjlw*KW?$%^SS>YVfKIp51&=6~__aDbTs>koU5RL<ar|IPu^3|PPYS3epr
z`r~!Sy??5e*QZY4|6}^GxS+;K=E`k*{W`}7vyZJ%$XGv5$ULDssODzS@p$pqOdtQ}
zfBnYay<b7#K6GzS%*^-e^zQHYCm$CXAb-VGcH4cqYwV^P-W|`4ADYS4xBplc@a<IN
zCa!X2xnqw5>URZ%3BG6CS7__RC{dxh@$b9~`yT&lWjgg^XUo5Q?zh#k^Zwg?jNN_Z
zD|oZf*XBFlTK+!XbmhjvzjbG-n7wN{;^X7~KYmo|ee?3NE8iVAuIgX?R{e<Ej=N27
z`8#c^ZcqGP9AL9<d+Y(JYwU${a>R_)zU@;DndyI6=+ygFE8gcXOVHGvZ}imvcGLe;
z9Y4f*{_WKTP3Y=#J=$-s^iP-h|Dgl>Qy<jtJW@aN(&cRr>MOfH<{SQaFM4Eu`h)#O
zO8>fV)t?5fQ_8<pANXj$&&!wh8*YEu=GgLlf!&Ei`;YwI&a-EK#)H4Pg7>cedU)vH
zq#xc+)2`TN{a$|bzQBw7=U=~-7pRX}Q2*cg*B|9a#Z3PHR^9uz=Z9V6znXx1XTGjy
zw&%LO=ikTbPftKg+w8X<m}kTD?Sk;~)b8`w<qw4Et>KrsnY8RfHMk+9Sl8bj{9(KN
zhw8xG+s6~{*Bw~Ddb_=j9nbCEN7uh?d)xW=8@L&iu}5B9{XxF{gUCmBt@P$K?f;vw
zzP@<-q<S|S=G*+8^38AES3fG;;{W^MDagvii*@hXjrYrMXU#KD_#OE1jNaDXZ&mhJ
zV&o6L6+ikI(iZyghx4Pwt^a>Nd=FjwKl8_7vsLdW{*-P1l_$3CzUH#>m2Z_lRqpZr
z!#L;vi;0gX>Az+F{m;zi9`CmM%5sx`75wJN*)J|}*6xQ5%Y62So5k&d7bV&9+~581
zGe?b_z|>Q6KjyXgi}t-068&k;IN$x@=dvGf+Rs}*_`L1RulGy-9l1SagC1yE;`Uqf
z?ku(Y@%z-e6}(zE<o{23xpv~a)8Fj-{&P3~kM8+@Kl#W0)DQnt+x}Pc{9oVm;{WtN
z`=9(z_PX8ve|?w5zyItXWjX)+Fa3DG+v4B<X+Nx!F8?t9`~Q^K_WzMQ|EBYT)}2)!
z{g@w}{qy7dsXz25dsz$pmus%y{C|D80BFEn`}>Z+@jdtdi67b@`e?t8)?1H1(a|~o
zegEyxd9XiR;QzfDALAtj|EK+rKl%Ukl!;|3ptkNQTe<(qkM1XZxUb#u|LLQ@^-KPK
z_xdwk(>9m;-(JJV^_53JL(@~uCI4@i`19TC&;HQM+aBE4>iB<8>~p>F|I<AG_BMeA
z@6B)jKi2zy(*Nn2%6F&#so#D4e>CgI{W%Zr-+l%%K$PwOUZMZ_*Gl3a>^DmL{XX~e
z571!xd(bd?%&q_1vv%o!*l&{t^5b6Fd;in7{r~#T@c;TLKk7Fx`_1%U?f>%+_qA{Q
zOMh$dr<(O`eQNi|{V|XJpPhA2<Z=C8-EaS^qkHN%|2>}s8qnV#)AwKZ<NlpnYG2oD
z{89fXcl3Yd(O+A(zWlKtwA3>1Z+_(enlq<j{zvyn{9kVU?8p3PzvM;h{=R>|@!#U9
z)qnX99{F$l_<tDpy8pSNG5>eR{7=4|`TJ4*u@Cu@p!tW{uj`|u_xv+&uP^@lUQ76Y
zxWViC?%Y05{SV5zr;q$M`lvtSt9?u3e=o`Z*{d&oTl?S84ODO^9{X?l*1r9JS7ZIb
z2lu!9zuWY>K78ia{l0%dW*)u%U-@Ic;p_U@-|ipTuW|kVjf+3-Py1@WZNmR(<zxSS
zI{$k=n*SIy{{OSS_2B;<Z|hI}y3YyHI^)~?=>NO39_&B8=6|l?kL@$Q?mzw2-fZr+
z{J;E6pedSXzwY1pB`*V-0Wtgrnhsj`|E}qW_`8q3{y+0$zw5{Rb^mP*mHw|c08KRX
z9sgf@^<RG9|IIz${-5f2`~P0Y-}=3}a{u?o9Q&_v`~UIDWiG$vkN;P9kNLkm>qdR{
z5l|YR{cV5JjsKi!f6wPR{)<n&_TTXBevKFZ%in+eH9zL}{>=YtFa66m%f0{0-sSiH
z&icR$|KA(^F#ox~^ZzT`Z=m@M!yofyYX8n>`FHkfz0W`UgKPfZH2n~-x#J)I@&Bt;
z|I3Hp+V{1d<9B@Ohx2RyC*P_+2wwK0&Gv71^qzm|pb3g?|NTWkO<wn{|F3oY`=8SJ
zzi_Fn<-hbx2mT-FcwE1W?cZ+YPxaZ|Z|hTC{>*+{-}R}!_>ccrx%K}eQ*ZtE{TJW&
z|7OW8!GHBz75+az_CLfOGz|Xs|FXZ^xgOou%J{#V=l}d0k3QN@X8jni`2tko`uqXK
zRedI;r#*iWXcWovU-~A6f2))8{;w9<0-l+<@gFoZ^U?mQ;BC-2Z10KxyOlrv?-cs~
z*vq=;&-o)Wj{gtm`4i6j$6xG7{dc+T|DmH%m;cTFvE5Au<XLdz{rpXkd#@j;pSlsz
zpFMq}KKsn$dNs*^@rEDbbu<2-{rEracl>sc6XgD<->T31bN-0!JJ8Tn`~OS-z+-Ut
zxBPbnwG!<OpMCuA`Z4~>zi`Pv{!-xiwHg2Zznk&1zWm6y{jX*mhcxYOKl*?8_y4XR
z+Dd)@=L_0vKl)LB^Vby7`TxJ${rso=M|+R^xA?346aUupY}okn=YGw{|Nk%hu|hQe
z|9|60$6aLp&liaoEBvG1X{}`U|9R7kPT$A%A^+wl{par}R_goze%rr%?Q+nF&1%7a
zlfTueZTbFQ=)GXa|AzPb!yo?-y&LyguJTS`#ruaJzjGe>-}dePJ>~P?d8*&vFR!@o
zw`Td$+>f9Z@?`LuTvx|G{sy3t$?fS6;thVRm-->j_OE-}|JgsxkN=<j`M+7~|NH0i
z|63x~^n#cCf~P`r!~fSS{svF6JwNvUDX6ctKU(1bvcK;QLG7rbZ}pQ7)=xcHuUh}R
zUhnsP-H!Ux2Ox87(SQEyHP@d$@PA3;|5qJ9p1-L-^<%#iXzD<$x&HD$aamA@D4gd{
zwDPV0agKjxe*?|kfhIdImG%Dje*ofb=lK)v_T~Ta-v4oqzt4ZHzx;3Z<Ns$q{=a(m
z!~gpEz4gZb+B@qn{{v0sB|rOr7nFEzU;SV2|Fb^-$hUf7P%als{_lPiH1PFt|Fa+S
zJ0Jf0&jMblJX`+%{L}yZjlO|qL!)l}U+Z=I(SHaRG{Jfu)XLazwCL}9-tYf=kNo%j
zQ~dY;oge!H!PBOBe~Q1|*ZNq${!-c3|C7JnKk|RYxA}+bTl@bThy9uTZGXo9_<qU%
z_fy~4x7X+W<G=WSeph|=nLqWLj(}$PK7exet$M!yV$J_gb^NKn0~+tH=lj3-7HFQ*
z^Vq-Q&!CMJ{suqZOZ|91^;`YwOWS_@7v}j_-Sc<8$%lB^i~pi|{_Vbf=YM?Shxn3z
z^E>|s{@h>M|NFo9pMKrFn!o;A{^?iz7ryWxXu4MZ`!D&)%D?`HGXLLe_#HGO86@yu
zSoI%xV%Pj_ed?LFAUW6L|KD%<2Xf{9^au4#ph@lB$$9^0>%9HH*Xuu<+~eDJ5=TGt
z{%}zG_x^F<pZhT%>-=3l*3}EHn(Dsb-w(!*&s$xN$+_?zTmM(H@yEY~>{q@Ceza_?
z_@|ZU{PPc}1*Oh@{&V7lYW|vg{PUfwuN42e$bO|9w1)ZY(rbEKvLx>RREe-x-1o2H
zR-MqRv@Hfg`ycK2Q*CnKefROBoIk2XK2!%j`nlt8PX*hya?bF4dEw&;)!Tn;y_@x0
z^P@=4d%@4IcKk5-W6Ndc`KbQoj*P?i7bhI93!eXfONG=nc_I64(u>Qwj~mK;TU?NO
z{!P$riTl3-Ej}w(Nk1-L%=_1}w$6FWgWtKU>=<j^AM)qE0`CaaexJYp2eZY$7e@*s
z_uF!rz0Uo$<5u1B3ZCt|ci3{@e$UjlDLh1rzsoD1tL}aC`8;rI>A_}pyUB|_RfyW{
zc5(gZd*Hd?4;!xe+Ydf}c*g4Ol7B2_N-G|JxMP1q_GZ8K?nU<}@18W@XzEIjTO$8<
zD?b8F(<Xe_zvU>X=^JnI;XcbBZl?d&8UM>3s2BfmpZSkD<A2}Y|DRR=o!(L$)bgL-
zo8Pdn{)+<hALV)STt9yoHdfSgoT`zz&(HYp@wY#U7M6X_+Zn72tN#f+umv&wh0Y6e
zo##IoFLVCI<YOQI2>j`K{8RCV=<(0a4cjf|$us>q{`RMHLw#%ffw$5P*H2A3w4POh
zU4QeZv+PM`G8^vId)#`@6=VK%`jj2Im;X*u`8QqQ|M?SQQ!V~Y<Y)Qe{^woyL;2Uu
zwQT>sv;MgLtww&1%<<oLD-s`7+-Lvlc&F|?bByO6e~mrwoA+DX`_7p3xZ*y0xYY6A
zb{58c-)ld--dIpAwryhl`=A-~dv9iEo?dOZ#(qVv^@G~9e7!Z(CG;=<ouTymKhFZE
z$Mv2M<)f!O{!xG7!2jmN-*XTBZl2&Q^Pd0E$-+JM92VV=|2iJ12l3-&-t#lDJ+3%z
z_SWK_e2aGf<G+p*dLI9Ed|7P2z#yOT+<w*_@$7Tr?+G9N71vsxJ%0`Rr!D5wEc7qW
zRz3Q&zN6l-r@r;O%K!ey@ee~E$3NP6^1*(=hw|HIZ~E8qp}$5+_`mn;1NOImzRSyf
zZu&1j`%gJjb^N3KKKW}^KH4YV_%HG&e<f%aRJ_#UzuS|3tY`RFuif^4$6x)A@yoU+
zO#1u3cJcrH$zT5KOaJ{p_s{FU{}#Qw|9?+UzvS2d|2uwkas2)t`{w`uJi%}O4}U!0
z@m@6bfBno;Tef;WiZ^&%-_rR1F5AEViyQxUv;A9rC{DoKwWI!lbomi^K}As1$cq>L
zsduWGuJJK`nNe=;q#yTlAN;qM`msNv;LrTb|I@)6J3^U31;Xi&Wz`c^{w)VLs@DpB
z)R*`Zz4Whs@XT$>xm}>;5)c_(Hqb`#nWwhMdOq5p4c;c=&Gs)o<qgOM|0g&8S7!US
zTlF8<G_zFDIQ*mkF^>P@Z~Zr#ni(Ag8q2EBllfO4e&pkQ;rtGv|EXG+zb%XT25K9F
zsw`W!|JBg-hi0w+^F_D(uLd`=!7CDvJ^C;H^#5tq|N6l*%baeB{qg?2pX;_T+dp;D
zf76-&*iSf6-}%#MYUUo$Z2qY)*L;%?*3Un<|K`8vMnA-%jshE=e|JjP|9`g6{@XJD
z&+GheH1%cN62(97C7b`>*MD0-^HhnwitvBNd(40GPu*kQx4yHl<MwaqMfy&Aoc|hV
z#|bLlTUb{S8Y8ND59H6;D*vWS{sC2GZ2z>Cw|$@fZJ$r-t!XMB^CdyufOxs$`go8X
znbAR+|4)Z3+n%Qdvg6A&-{{o;@#3Hsg!z$N!Q=J8Ivp1OtRJ;G{E1(^>g#6NK=DHz
z$7R>^7r^#D7p$KbHuKb%XI?8`|Mz*)``<qC$p85!kN(>y9Ql7g^~nGGYajjBXZ`s9
zyTt4NK9V2*f0z3BU*6==|M$j^{@aVJ{eSWD$N&4M*#E1S{Jh^M|J#(VdPAju)43kS
ziyZmy!uaR$FZs{||6h9Uy_U}Nf49lM)l#5JHMJ^R)%ah$*8lpJm;e9!g9HEF@hz&4
z>l3OYw|#g0A>XlEsqg<b8F`V1|94gRPWho9Jo8=dEv-NK9@X*>|4$AwI`p4&qt2rr
z@4HPKfBe5J^*{H6yTJdGzaA{S^VKoZe#%Opnp;|b)^|rM_5I&%bT7Z<|KlXjBOmuK
zddxT#Y*_51AMr^a{?{>ssw%za|4+fm#?MCx%2&PjufE^Lc+>y-kY^$f|0{2*>-bRb
zUgOpBBmUg6|M#!oRzLcgN!2`B{=v6(r}kDJOVzsU2MYZC(YJnc{GTs;U;ojM|9(5=
zJVf5V-u7e3iRAy@pe3-6y?6fkU&;KRnfd=*!H@rwz>#P@>B#>B2kP4o*7tq07y7R+
z1x;CRJ&OL^7wY?OtyUlrUGwLD+`^AGg)ug)_0`Fb{}<RixOd~nez8AqeS7}r9x5yP
zb3ZQm&;5G__x4NK?+`cY@Be<A`$vEO_q*KnA3xSrA8qdZSXcd2BF^?+_=Af3t5&Re
zD>l{7;95CX-TT(_&5JJGog7(y<oK_tkN=$dlIC~u$NlBXfAl4PTz_2n_(%BHgJuuw
zn-1(>`Z3@4)y93huSVRTcg();`&PLr$qn9rroUV}uc=}`KgU(iZ>oE3IU|m#{B3-F
zXdTlugTHM7k6YCle$QA^&rl<0*yj0*{eeBpPw)Q;kvGJy$xgTz8TjX~_M`P2e^Ot+
zoiAw5eOvV7y}en#MPFYQ`^8+J=d~d1ckQFw4}a)=>@Tc#x^Z7oPIyP$h5Luz&fBm*
zwx<2Ssh9H~m4)8u@BGgFMZPcd=l1Tu8}^3BY`OAH`9-P2--}zW{Nzv8<@kDB^3Jvb
z>3(|^xnr+qihR2-B7b<6)0<1zzo#GR=UlV%Ux8O{eNc_$w(s5d59U_bc|YRI+3)>l
znq8gamxSN7k5*m#uW_xZz<<5Uw*Af}hu&^K{4M!W%%iH@kCXP@bAR&lz4+!||Gu5N
zDaG#Mo&Wd_yP}=Kz5d&xiSHZJ8LzJU5&!k8jKK4R-_4KCb8h`>doBO)b;pO9wfrZa
z7kbn<JU3TedoZ!kFMq%D9^q~CMb^I$z5TwWTJ(Xjo%zyv_v=3L-Iymh|Ip(PHuqHT
zG2h<&sCw(4>Z8?(zdI^I=l_?hydxOT)4!j8TkOV#+wUu%|9&L-*WdSU&MJR4@Et$T
z?r`1nM~#eKeWF+GzrKG7vHyBRYabQaGtQsid|v;>+j_S7^-JsjGynKA`NqEVAiMZg
zE6%@4nUXHO%|C3)J^fIn-9j<Pw;z7Kb>)ld(xT52a;l!Fs~N%D`0@=w9UF1je!c7m
z`%gWHmjLw(cC&#-*%m4MQ|AT^f!HU4x(xFTKHQfU1dY8Ve9)Hwb<4UzjqT{9|I>N@
zlylwspXK;F|Iz;AH|mA|A39J!9n^dTbtgcR>yYk-cF*7K+iv{x@00v5%=T}s(EsSE
zDxl?%)8B9WYyOdcw|!o1c}sn^%kT3a|H~!+R~PuN|NQv>Co@2u;de9M+UL|C`&DK3
zZ#CP$-K=l-r#{%9^k9F~1jsrYvHu{R)tUdoKg{3O2ZDNS?+w4%PyK)V1E~IpW&1D8
z`g4Egf8ArC^^#&o_HRA<=RRnzV7KbO?OLFT>Lc~r75=SO28|(4R=!o=_dlBTZGHd2
z{h9xLL7t6f{doT4e@<r5>a#FM(7g6kkoRvt`X62MyPoNPDBJ&QGd`XNEfk1l23b}g
z_}ku6>7OsS|7rT+zUhbj-kblvd;R-A?c4uq){pUtKlb1JZ@%&9kLPdphhF&qUhK*L
zt4)9QgF3D*px)LTP)k35>JRzwTND5OpUnER{`!Iarb++*AL#(iY*_w_7Xj^+wmtSQ
zTKQ8wc+JdJ!JqY+|Bp{I6aD}AsNwnl!cTvIs$A=!S3mBHm*4ntf4-i@zyF)${@?HI
z{V%%l<Nif5|D%@~C3+p*zvK9i|Cwz6^~H|tXZ;axdh9>@kL{;Ef)4MPpz^=|#Do9*
zl7H&ujsKS)dhq|j|9ZEY^&CI{ui0R)Ul-8w=fC2U{}S>cpZ^z2$iKO)^yL3%w*T*^
z{Mql5daG;7tN;E6Kk82$`0vaET4h_z_U}3GpYujP>Q@}8pLxopuf+e&e`koG)DLse
z`pfy+pr%T%a_*|X|KET3Snu&0wEL9pf9h{gvq#nQ(f{{7_W$a^Me+0Hm;Oy(>63p~
z<)i({2lbOA{~MotP#+GKQ&;PREWrg0?MVK(9}8-LysY!MZS;S8RKdUa^Ai8_MdyI#
zJ`5lKk6?ZNzsLIDbPbDt^@|?-u@5x(=YCz{zrE$Npa1Xt`0r);?|<CV+?oHQMgA{J
z_|vav{Qr2;v;UxlfXVaz+rRq}Z_5no&7Cwn|6jkWKCs~5`Ig52S)j2NhX0#C<QcI3
z;Qvwofd4^7w9kIUNpD+Sf3r9Jthd+vx9UK=`<HL}C)EQvUpMbptMgm1zaSw0|DGSL
zjjE3~PrFs;bw}WZeNANke!Xj~kN)3(WOl{gUguwvL(Tt9c6Hu0fe$<$?%q|i{YYSC
z>cN@=yT0h(ll#;-YX#?#&1?9zKu32e?$f;TlW$7s4(X2@rj;*TqjZn?_dNmL8+F?c
zZ5PkkufF9y@5Pq4-`l>$zWl#U;C^Z4zu!m7-v(X(FZ@WI<r@FNZ~dnyrL_O3JyXRj
zC~)rn*Qa0Y_2RDoG+nxnzbn-Hs(99K&W(a{`3JwXACc4EVZUd7^P`U+{?#;ob(Arm
zeRM+S(R|L<W|JJ&I;pyPW7g=*pHnpJZ%zF1zPAI^_GoSV|Fj8I6m54qvOiSdf78MJ
z1|Qx}{ZYSqnQUkM<$u-6kM2te{%<;1fBwM#O^x-1{m`+()kpqEo4)P%VSnhue|4^3
z|0gRS`~NDh@Q?h#E&oGje6!E)zWsmIi~s-GwYUGb&-!y;PWb=jq+9>J{@3SZMnC%h
z#jOXt$h>@e!XN$Y?#KVT1RwwJkp?f#p7Cw}sgAexcYfKY{hqJ!(SF?)<wyT#z5ZYD
zZT{i^Pi*`CXFl2=WbkkO(FdTBkWjUM&t0N^*E53V&bIuI0j(NZl<;SL94Pi>cY>z$
zcmCK9TF`CqW4=uBpZkj-E9vaF|MLfzFlT@4zt-_>fA)j@QQ!XGU%f>cJZ@6_cmBPO
zKlPI~g0lJ5rf>IeJ^Wa2`P+Wu*}wl)|GkgAHSuG;@1NO!=5Gd<r-DE01OJF`{U3Vl
zA85?V;PwA6Jb%hR_xzVu{;&V||GoGh_g_A)2aO8eXW9I3`^o>uZU0R_Tp#!kylTqz
zZT;2-f6cFhwqV{j{t&PE5wxOs&41&}2m6g4{fGw*y3N<f_zxOpE<N+O-WN0`y*v3>
zeITf;lKKDqP5sUP=G#C{4+PCku4V--9J~ClzpMW8zwZ*i?F|?GoiDTT|9+!q|NiGW
z{)vA2%RYK)*^?jpyA1!GzxC|n{-h%x|2IkgPtX1MWB)wEfB8Ef{HR|q^Z$FA@9j(f
z*gw?=KDM{K7k<0`#@|(6Z72SnFH`sjv{vF@yzI9B_WBcLdjJ32yy=VUxBtP9{JVGj
z->>to>&K7z-H%K+CLjABa^c^6@sD5k|Lgc_eG|0sZLi?Z|1LNGeV?}JzwNPq`o^E@
z*T|;**H*q&Z@B31cegqJ58td`z2$%YwJoua{|kMqKeXZhp$-3=I{ybse*SfT&R_AK
zzwaf##Y=p<FZ2KS&HBs#*Gqi^l|IS0>Jx9&AG}eY-QN5E^|WvGF`2uM{h#<}{^9)^
zC;nG2?*Fg)@qX%${onzcPSE`1M|(Bc`hRU6&}xR6Kc4^iuX6bR*^l;DC;iV4y*2II
zf6rt8Km(x?pz$E^kl2?0dmnzZZv`!GT&?i0yYIj8NBv_tph2o{^AFpngI2kz{@bpT
zd;N#~rGK-3$Y1?e{A2xx&;Q*H*{A>S?)(2z@&~9!2aivkK2TqJ=J9{Gr~fB|28GI6
z{(}eFia}fU!`+^M#?Y>HfQI^dZ-ZT71RCkO_|aaN2Q-dWz4Y(>RiKI8qkP@}ReQeu
zpLg-!{+j;V|7{oly`S{xf2do|fAQ4c|7V-#a{tqg?y1jj@Bja@SK|M9EsKBYsIzz<
z|5veod@uQ9eNW||_`u)#$7KF*KJq`>EZ6)0eU``nzt8x#-}CVQ^?f(~r5paM-=6S0
ze(FciobF14f1us%T)+M&9r^Y@@Ns=d(VzR#tN#1<?EF6;v})?QRPq1)o%O2|e#e)e
zd0RhO`P=_c-ap@u+5A7A^M5s{>jTQGZ@d2ge10@uNb#TI{`q3@qJ@9rH@;K(u>Mqd
z%m4DzpM<vl-_O0HOy>W4Mm^c>|9`8<DgCxr{V4FTzF)^*@SkX$(x3mOhT;$9KYUdE
zsI1iYfA*tx*FAs#@A~4d^rwD#goxt5)ID-Xf>ZuqElc_T{m|AUAJ?xlm-@f>!;gOj
zw)4MtK4*DkpTYlU$=Cmz1@1T6hF4T7ZMnay?sq^(eCT``o{!QG>^IzBWoIRG>;2zN
zcC|)5_kWgE)>!52zpwwgeWt+vRsZJR6|C?*tkHhnJX`Db|Eaagf9p?w_&;6p|NZ1Y
z|4-S@`>*cxf4|Sm%-z5K3xiVc{_Gp|r#FDh48Gg-srQwB@AtoT{lq_eji1FS|K+C~
zU;NRY^S8d+mj9RbDam)f*?;TWxA;%_Th34X8-88-WBt+ed-8qHeQ(qo=KP;pFL3k!
zcF*d+3pf0ayZQXYKl`qH-L(HxZTsKsf8>4Z-|31yyInK>KP`Nse(PWR<FDSo_g@AL
z^s0Z%|MWl0@n3##$A3@e|F&%ZuQq{_UUw6;F}j-PpQ|Hi#UnR(S54rf`sK^sX8l+G
zTc3RfG%EpWttPqrjyDBuf(A9Zb}QckwIlN%?T>o&zs~cv>A(3~{$CaRcwg4||ML&|
zy(j+bf-C_g<Esbi`w#wK0@|xnfAatP*;{n~fq2<RzJWG<tZn-7UhGKydC*>)|Mho3
zMXd~I-%2?5qy1a{Tbt#E|GCfdZ*}yY|JRejqq4<+<{z$~eh|{U1WlOCPx+8P^~e2{
zneIRStASbu+1)??Kbi6SfA_8b^S~QRf`9#Y-vnw_iZz4U3v*{})Bg9|1GMzA>dy~(
zq5oos{~y2m-+brMzx7uQAJ5<XU-kd~{L6iB{+oZ?fAw$u-s&^|&;GOT`#<{!s9=!%
zcmC^t-@Xpekj8J*yW)RA^E49RT_$P&<EJ0|pK|cu{zZT8AAydK$NZN+{@?d^{I~yi
z%`>AxYq5&|*6(cs?`es@`{>{Pyn`Uai+^mN@o)d6|NFOow9or(pY`899W;dfXn)54
z`z!w3fAfE{1ZWBh6!_IWf8Y1r_#gi1|8KM0?*I1h{_Q_0c>BKvXj{$c8~^Wh{F(py
zzxJvBYn%SoU%m8if8^zDKmK3UefQt^<NeeR_K_F<75}XdbNqMyA!xnLqy6S-phePm
zx4+ys=YMvu#sBS_j(+^FllJeuk?{Z3+mC*(-&^!Ae`d(7i9fz`o%{b@^vM5BjsH)X
zt^c3>D88qo-uU18PVh#PkgDLG|H8>~|C2xcU-Y=XDtX@j`=;Q6w!81Y;qCuxn*QvM
z`t|>N_AdQfpt5%|XbSDlzi`tJ`Jy@hjX&DI`UBEu@rRrF|K3gi-|M#ipKJH;{FeW&
z$Nv|+t-ss!wtnx$$Nwk(*naHJKl8|Q|Mfr4pI7$ehkY?<EqwMJ(7Ln7a{rAZC;a~|
z@$bHD;h+9aP*FAY+y8yO-&_CRH~w&6_r(A0Re$)!|7TzMXutSY{pA1teK$ZWZ}cD6
z-!%uNp=UqlSIhoitpS>|{PZ8x+LSH*<G=mE571)2<Nv>S{kg9XipRV^{`qG>b9w&*
zKj!!Sf7u5LiSWRG`5;4Q|CpZwT3H(Z^v8VJ*<~&N<4yieKly(rXqU&%fA+%vCx5s2
z=N<@3N~My2KnY^g|MzDnm9_l8fBP9|#k2VJ|LKoF+w0Yj-}#^Z3AD`a&;29z$N&5O
znf`HqS<WrNfBR4V_x<C4@A1$7i$T4U*?;P<{M)~_@BdX<<A2qv|H`v=>Hh*H+`PZ@
z7k#^b#QysK>vt3X-0%5+HTl<npMT(FGwJ_*eUPWs{;9h^`S1F;zBdb`W%7UVxBp*@
zfs*i#_{Y!wr~bcRI~lZy>Cyc+5b^f)|Bds0=YOgf2F;O!%*+4w-*?*M`g=N{z}fsi
zzi2k7r}5nlv<$gk_<ziw^=sq)FJJNZ`LF-GRR6u7zD4;@{pSDYWByM+{C~yY`o$ol
zT(AFs*?Z!D_oMlb|EK+*FZuuUlm9XQ@27PBpF6AU$S-@f|De7ns9*N@9cYDC`~Skv
z|4$mO|9@F~$G`QR|2O^5KfWyY<NxY2zxLlg``_}n{i|R0kKg^DediHqZa4o{z45<r
za3Q4p8#M2_<$r$BnIHO6|C2+&N?m_~oU*s*@BQDVe`nh&37+?U6zlSFf6(LVzhB?{
zh}+L`^@Q?$p>OF&zH>zieOK^m`CIw1ndx!mUje!Kt~PhXB=)~vz2ooy^!J&`(w6IH
zKlNNLeE!_YchhHEotWddZRuv0&R;es%hLlzR1MW!Wj#N>%h`EmQp}{+(eEzp_OAU=
zbndF5%=WyC-i=%MF6=6p!1nXUMHPn&46eN2nLUEH`!=#=2$}SDFIro_rSS4UkEU&Y
z_h&~=I<2beWjlAx>9>=oZT|fA+1c5Z`TNrA8!x1vFm3wuuahsXe)-ADrcbk9KKPZ;
za<~7h+^6Lk^>Z&+ZgLSQ-m2qY@_AGBQw{TrxuW+}E7r;7=Dz<V!_yyI@NmPSnR+=_
zKh$mCd|{W+C$kgBI3>RxG`Rf0XWrCEBj)<!*`I8@<r?=t4y|PSE&0Qm@6#VG6Xx$6
zOY)n18vklo@_W3ubo%wdZr9@phmteYm+-&8Y|WR;Hu-;Fq!DlZamJqtpXV>No3?NI
zpAQ<_AOCGW{_y=hz1@HHKK+|@m;KxBh3th>Dn7*?dHhmk-gT=3bv+d~?h8JuJm_t6
z;X!3xjrhl!z17io8~s;x&z>9G+t01{N9Ewc8UORm|Cg`c|Nr@$|K(P{{(thF_rLtx
z|NL+N)|Y**{~5jK|MI(k=I{Rhd|RXQ#{cIn|Ce8Q{(tVL`qkh6pWyrXevjwR^Y<UU
z|G!oGzxC7md;h=Q*66(RKmV)qsSln1*Z(~K{{Nr<(@!3K`*i=^zwvLM{m)DK&%c|0
z&RYMv&If<*U;TY>zsEk0fPd1z+4--1IlTGMca|yd-ToHb+GzhGah?2=Rdo_2FWME?
z$y=@db@2HOd6PF6_?7#9I_^)dEBJEZ1^e^4kL_3fdK5eJfBCxqTVMQt@A+@;@A^5<
z|9`9cAHJ{m&;2*Q<_G`FU-bX{lh}e2_36?-&u^bt|7b$}CAWX9?SIPO1pe#P{{LPq
z<oJKy`~N4ry8nB{w*ObZHmv$%Uh{wPhVSp|Yo`9;-FW){{Ym?k%YOb>eHhI9seYb~
z*PBoF-b_dC{j>K<>#Y4Fui%)J|Ns1i%%th{|MvF&`X~QyZ~w2K`wO%8F4X#eUr|0U
z<NyDTKav|y|JQ!=TjlF#`~By>ILH1gJ+|_<?0xo)PweBjUcdfd?dErjSKsRkt5!b#
zt?>2R|JzS)FH!q1@GtsF^b)oI3;3UPy1jY(e>tm8C*$$&O|L%LJIg7S{j6`9qgwWJ
ze%gJ1$yL4l=Qe$niqEY%u)p0XCR+Z<eead0?f=j7i2e8TyIagp`-~g!e%teYiqBB~
zFD~;bzUajMlF6U$Uqpn4Gbmh6S5K*bG~xd_vrqRQP5=ehqY3}{+W!cH5%+JM|CQ~3
zp5H!UU-<O@2B*?L_Z9vxWzPHmxjN^+^{p-cQ~E#YzbXFxeoFm8#s8a}|Fznl+Q0d4
z`KkJQiXgfBJCA?cpWOfH{=-xM6C0<!{(ofSKmTt#{{62!{>wgd^S}DU`Pcv3#wL^<
zN{;^j-im2|Tt(mEV)2h9yI%j-+re=4{;Ze92U*46nG`&|&no^d=0ND4#Vzai?Re0{
zT`soc)B7gwa=itAsyXk!ebmIQcPH|}sr}q~cXl>>uHR8C7XJJBLrEL9XB*3>tBJ=H
zJWOCHpJ>m?|Bm~i^`F*d2C}wO<Wzi**E`R5GP2`+zhnMWkz&~uKhHNVn)SAF-*dK?
zAI|-cyU#pNZi&<i`)?bg9en4?$Nv^>zPR;~;uCpm&f5o_PMj{?RpwUmX2t`><9QQa
zdq1&ysaUI0Fn8zoa-oM-KM!PjRk3`!vqwN}jYgV%Ma$BAF>-zuKW(00zYw@D{;@@|
z?L~*{IsV7j72W2MD{DO67rvC^dU~`ayY8-iY$gx)@!zSum>XEGaNxzRd(QJ_?{&;Q
z=PVW*zKbt?@BWLWJ6`=&eYssSw*Eq?#p}QJB_FGM-X*QGy;ID2uc~bF`ACnPZLPaM
z{3$ccnv#3jKk9UGoviEsyhCNGviG+Oid`t(`}pX*0At^`7Sp!9sQNSE;@9`Ae%Fuh
z<`4f{RXX$X*Y>;ZtLx^TE8JDbV)F2x_c}#4-CgfgZ5Qyx#sAzRx+~w@WgEk;&E?CM
zFTY;==HEVlIp?KE=KMRU<qit!Zw%ovu>}v$wU*zjd!BoRQUAe)GXmbJu8W+%ELzjo
zduhiKk41`>bDuBuS?bWUY0aulQ5nx;TsIkP4x6y$(yddiQ@`x0*HxctlH8jdr`@^f
z)#+)cpR7rImU1@S#{b+jm(3medj$@LzfqNFJF#jfuafpnw~($mi95uU53?>!GAdEk
zRoCp;V6HVwQ?q;h%&t{=f-VxS@kv=#M<1-q4EBCrQrK)T|MH#H&pJ+cxM`hurFJrN
zYERP5Z61DR9Y1<vlqUQwo#dR|ceD76<8>eVe?5=RO9+Nae$t+}L2I^V<gE!M32}b6
z6<*JpqulQqE$Mru_@HG_An(ovUY4_TyR7yq<tlo=Q2TwCNlLqoW#NTs=L!x#VB?>3
z%wXA?l>!-tlO~k}-;#+|uXGjmowdmSg5j?vQzy<U<uf+v-^shuGOewcYnhS0bgJu}
zO_zkfI!!ZJ<#$;A#<km1LZ<#*({kByZOAmyPSG>Q3_pZ?*SC0v1@lghI@3F?)MIsm
zWzwDs4S|J$eydyyOwKz^Y%Ne>S@L9UgvwQ`BGdUR_t;8wp0e~bO`UwbTkPbLS<EV{
zMN$@Ti>OjA_59$I8vK<(bFY|h@B!wXGoOn6c~~~r#eDJ8kl=HFc~8vUx7hmUwH0@J
z9!+MsbR#-gNwZ!zW!21<DN{KNca)z!{6YDc$d1qPKRl;C(A=DEoXG9D=$L5cV$QEs
zQ?EwG8uN54^T;}=b4_W|Gp7*Ky((ItjD<X(ng}mycrtTkVAD(2$FqJ`*!G>2(c5_c
zw8|`_tv8aEME%~{6vQ;=-^sLnN2O<Q75eCAoi5wMdOliVZ^6k=hfkF~G}`&WVrRj`
zi$x3jwACfmPIT(!n<=a{_B$W9qTz*|<ME9Z^QK)b^<+<t<_^eOQ#~nW!j)a`cZC^7
zE1$bs^C~aN`GQ&2jLgU@heLB0ZBO!8n`XKzEL-IAPGjR3&FEdMGZL44Hqv5#_gm-t
zwj3YFw{6>$`X^p_dh7HVpUNd(>w6jAJ>DMemMb>ZL|}nZV`z8g;ksEOQ)V5Dz2lpG
z!zv)ydwcPQS+jDR*M=qR<_uS<3=E7i{p?qMPdlUYGS{sTIb-9STK~N^MOBNMuU>C?
z@52&Nfw!xqO=@0-z3ZN|Ge%Q2H+9m4Goj9#q}Fq=xw3M9d>hKKn$^l#TPHW_?c%(d
ztf$Z1xHRLk*<y#)d!^==Ra}3`-tH3CB9(J>t6OiPW!ToweQR#-ERdG$NxdEYn$yvk
z+qSRt-v67HWn1UvPEZO|4fJPz9HR5`*6eNjQcDvRm<)YZ`dsnSRDPMMJKt^f!Qa0B
zws3O!p1Qg_Dy%(g%d14z!{??(eSI`-$NpuVzx*#ZvQ1Ns{yFi7hG(CX=Bc!*xnEaa
zlHL<M_3RSw8^MqCZ^$0nt{tY&eLwZZ!v&dFHH0o6xzm-AU72COViEhoCu~u#{ol=9
zb1_L%|4Q_#h)E|di+Z;2dm1KLb$yN2j9E%A7tNY_q9@nGE~{F<{J>?;6a5eWJ}=yz
zXFh*sPxJ5h7Jf4SHy+5}eLVPFMVDx}Rl(HvyXBnf#O{2&@-ALh`AJ|$^`_bD|2+1r
zk6Bqc-?Z44;ay$D2N#QT8y>$Bnm6UB@Rf>J|IP?Hh3)$J^3D3_)6VJ#|HeQ3YkA=J
z^$!m+fBRSc;C%U>>0Ax_{HM0e53Q_!`h00$!@BT$_0P-{o9TVq|2_6)u1J$hkBe_A
zs3_Va|L0wE#r^G{elHeNo^{{q(wnyBZLSACZ`pcQ(*Ne;Q~dLe*{43f>pUS(Uar5r
zWY@#J()aASpBX2pDaP)RWq5z~(AAmU5B{AG`>7LUaqreM4bgc?>u#Jf;xehbx^c-j
zt{r<HKh&<MSj{jm>G*A7JJxsgO#LkU^UD6UY@KjD_2b#=O8YCS{>EGVc=_`=!}+`J
zKeAr&7U)N7`-J{zYkjXQ_BPne>i(8L`}m*nKR9@sqwar3an-lU7oS`G%#xos<+w0t
zC&Qr$|AK!U_-*>(c<{Z7O>*UPAM{P;<-cG0Y4(R2k$d}jo_+PRI~?1}e>?5)b;Wr3
z%)(Ru<~;q@q<c@)!+mQ-$^56=(z<`&JohV?@w(!j*&qHe%=_QAT=>P`>WX<S&x_^i
zJ~yy``hQXR&k~z;ERR>+;Jm%)+4K$jBK90v@4F;tPvy~L*76UkZXSEh8GZNX!sKW2
z`7aMF*w6N|j{noQX|DElyv+GWEI6N?Z@eGR(6`wA$62=Zhpq3eYcThDaF(;enC;%W
zgL$Dh(stK>ea2)X+OPi8p6}=Gu1y(NLu2OtOs)73#`&kqjq~2e7W;Lpd7Njo^3^qS
z++!*_`iS%1whdWNKZmZio4eu7{Y>9BZoM4^3LoO-r3IJGGhG(o_)ql@PxAL849c@5
z&0O~?I8N7FUugYBS-b1W7XJ5HY3plSmKC0TxA@AggVi2Ouc_b5p0jAK<>A{tGv5ic
z^mj-xZJFnF*U-b+$>K$OTu$)GH(66|+8yds-F*7ubGe|*NTc1-Q@8a#lqr5^b?BY(
zC7V~bYNxQVMZ505>ruVjU=LGb{&UAe-}8EFAJ*4>-=q3jz5m0!3(pT6i7wi&@FA90
zpR?xrjcf}q24l{D6{q#??dg`CKAl6lWCHsE`TX|1F0Z0RHYEP{Z@l}}HLjuJy{q-Z
z>Wg)vhyL@leHSR}ev{2|UPhqozCc-(*v59Qw7>_y1vj$yRqGarG;jZAm(p5$`*3FA
zL00i^?C;vy^ZV*He&&6st#CwNzP9=6S##abt_Jg&pMJPjeNP}Dy@u_Lr@*iE4V|0W
z>iM3TJLv7_e8wyAZ2N&f=1t1?%x{RTPL9pzSYiEc^O-t>z;EXxo(auZVXaqMSo8nl
z$&Z5E_tUK`=hb=Cvz#%W_OnR+d;MpY@9GJ0OnWaEH$7fD?WZqCxqc6$sG`0|%OVAC
zf6he{1UEVP{m8tK_nwuv!oE_z(kViCo=9EbgqHbA&sq26{%H~rmlKy$`ujxg;id^<
zb}#a#793<1k3k|HZfpH?`KjXm{G1u*-4Aiko+#7T6|S=FWR`sbOF~hR%$bW5CvN22
z@_V`3u^HBfUi{#YoGCS5X6B4JQs4V03I0FwV~YIy7JG&j63bQud+~(oyq|J+O_-K+
z<WB_;D-QwD)V8YKn=MaWXO&x+eea#n6ua`xYB!`~*WP@#Yq9xik43kn_*3iFZoK(t
zj)m^}+b`7q-WJ|AvHsiZ(~{D^C%Q@h{O<p#dhs8Bzuq06>IDR*7UplAX8v-|7Cp_V
z$V-`r);vk+jl1$i+b!~pR|#WOljE+2=+(Zn9(DJY95Od5+WuW+uSAD_`*iX27d1V4
z$0wPX$opN2m~*aOX<<r-+Vn%5Rfb~qIva&J+BEV`*;j5CS9+(fa7r|`+UwLT<1N=O
zsqKAUvvsTK=@zTlWzHq8XW|68g?e*WOsaeL=0~O2eCv7E){NIyhp)f)c5m6+sOIB4
z4nLlj)}$SDrg>}1>E7F#?9&dVSFTuhH7uU5)=o@RS6Rz=_u}+7*De=(KdG1go9}u0
z!@ebrUUgYnNw@#WH!S_XeA%DJd;XgncHOtIV%Tx`YyIp`_oo*+?EZG&{%Owt<$wMe
zZvSh~Vd1*?0ArSinrZhW#fwc&uBPrEr!a(WS<`X*F>h9uN$|v}GPNgGN%B|j?Veat
zVYx%dL+@g7iH1##;g`gog*>OT!d5<6lE@>(c|Nq+CC5?3(m1Ac=acWp)n|5#Dmp4!
z$OcIWI-g2Pnfmw8dDTqeSiPxQKeQkB-+%x0m(Xf%?uXtBkMJD*YaEwvz#+lKZ~ul@
z&xNU*=YBwr$ciryA4|8@cYEBr9)JEsgSpXpr4r?xb~O<Z3wql(7d1azRl=vKVErL_
zk<6-xLd;iQ`yOfLEU|H4U0t1#8!u3C{F$8qmztsJv$c`)W?i4nb41+Pvm^bZ^d=Eb
z)@hQf_SI?MW7zYlf%yQl!^_KQd+yf$J*e;_=4s@9xAsk2-mkeH&25$J9Ke0|yfgm=
z#kGA`<_T?Dy#9XDd4}rLnO~~Dc3CAWFS+d|EH7TQyWMz`)tc!q0_1`Z_3-R)-tEko
z`*r`;w{O!D(*N4qSz29M@?WuO^?!b*HvjkHYby6nVcYs?nx1%<+E;&n|H~<Xi&n2X
z^KJR8=#bNwQ+>_5O*CFfUD2O-sKO|M<(PJfXPAh50*3}yuQFTnv4ysmt}mU#Z@Av0
z%G2z|31O+lU5w0^bX3ebw1Us&Z*=26|LaxJvLvqyGfuJ{EqvRy!uw3H8Lz|S%bTW7
zS~6=*?BYt_<w5HXMOy|+F0oS4e05W)dtuhAfXM5gHhG>F-MdC|lA(ur%H|cJJ`Pi-
zH?Z-fTLw<dd$B3gOG}h{mrA0M$O;XwT~lr@VvP;))in2De7bAS<RXW~C!%5xsHSZx
z?M&?`_P^?5dHQ7=gTwMg8PYorU)EttixMmKaMBUy)tYwN!EmZ#pev(KgYz_=W1Bu0
z@tnxi5RLM?bR<YYsPSM$$2z_C;Dr@RbN2Woa|<Z&^%ffl^t&E9%_!w@=|NC}s>nj`
zL=Jm#CX<N;33^P-KP7l|;+JVRS{#Wvz*uL&=X+Q|CAijmO-s{52bQ@_4=X*y?k5+n
z5#RXK<;5W_i$?po{4UJh3t70uBj@t#>tFKFnYcvz;|(VZ&UcL!7LDsRUR4p|OkwW3
z>e3N?h;vqlu8Ka}BSnSGc}^l$^4#m(43DN*Y_mCG<a?OAkB52EGaY@_AjK0JE&OMe
zAL_iYXR1<cr>fAyodri8g(R8oVByfYCE0v?(`3UGMH!ZR@oaUfO%oj~x^h}hIMmrN
z{K<H5SYd9n&SMiV6&YUj#u+I&6P611t#dh)u-?7-3xltTNV`yTPxKTe=Z4PH3tgI~
z1~p8Lu-GBRdF17(ESVzFPlcCO`?$R9Ivx~|^tnV+gnzBx`SwR5J7k#W>0G|&z@)Rc
zL~jB|@=XUOUrBZm-yGkBx7}x54|T5z5Q=DCQ<7mK5a-u6jrsIJfsol(r;2vibfoSv
zlJ`(@cRKC;qSJNO0V|iq8!L}_wsjTDvpBD5c=3|0Wd61cHdYQ5YwjSo>#2puPHXY@
zc5O0pemmjAMc1<?y*Ys)>nbv{XH0iE<)e0F!S)YzTo<&hd{a_A&wAZH>a~FB0`CP~
zZ-xG56AO3$UdQb1u@&uQU#^BcE)&doRWw15{pE`*N4|U!@Mb!_amC6@J<4AHx71f9
zR27w+us5~qUFdXHXQ9aUrRURl<6Y1Ga!{|@dv9xPwzMCA_1@)A_RO06>5W`#hQdrP
z*2~`af*&ZY4qB|tvh~-qtI-KLdRL{BUitO?c7CP#@UP;%w%M!~Slh*t?f&nmPpT>@
zO3F$4CHP*`v(>D{^+*Nl)}+IEcin<M>rOkJ)cfvISlk(jzq6T3&U*h|A9Zrc<=2aX
z8m}qN75mDh!ogUO%Dh8IYU#hY9^)COHNG(ZSEx-`Qr`A$-s$g`K*h|t1S9Puax0E)
zvAI~5yP)&gq!_cjNm?C`PBU6MT>8K9`xpP*Cnx^(tbSL2;bYeKoaAJ0ott+z><e$1
zq4VD3P~+p6NxnP(7(P%uW@enc;pFN6|Dx9RPjr*I?fGESS3SPQneW0@@4ou#o#c6s
zFRxv=+zJ#qr<<>{Ir?bMAGcSkpYAWQQtv;xC*;Ceu7?sb_8K2d^SO$aPERUxom_7H
z{^9bF9~^&`PgWLwZs%^YukWdKpFQ;u+m_Y)+vj&#EO^zhSKMROgb>Bdt`x45B9jVL
zH2!F6Z;5bPrV%#J^0}zjzAw*%Y7~AiliCsX|FZO5k)3bLr+gD?G}mr;cIWnqU2mW7
zPSUxp%~rJ6Z_l@XSvSAla&`SLajLOVK%uwaJtM(l(e1Cct}dp6mtAgb$P+O14Y}?T
zBAgmpmYSV;FsjMf+a#a!oSokJ-{*PnDlNS8=_gyr%4-!{mN$ejXL6-Tow)bD^V^jz
zv$FhswJ(aC;JJMA+nFsBvd*7jT%b8Ya`B^A_jlPd2MA|y1eEh8R2~UpHn?4W>Dw8@
zhNm&Fr54=HU;b;m^88OPO|smbW^Q}2S(fwWtwr0*RCZ-m^Y&&Jt$p=s=O+7gS5wQo
z#NI4s4LP16!t3?*&GRqk>wmgMui@D?&E(LJzZ%LD4fZnyGoJ}6=u4@w-BemL;hACt
z-=e3*H<dmJ9#6d&B$Ma3?m)joQ0EdmmB}7y%9STHQ=gf?@78+_MlZWx?VE8?Jo*|K
zT@t@syE60jtqFRY7j~QcTJ+OwNuBhiR5KTqlg3JC&6U1NPt-GB)P3gdX(Of2(i3%!
z7j>KbO8V)RQm4Er)vaXW&e}+`lsf56sb(N{rT3JdQ9rXo-&8y>__(3*VWRWF!+!tR
z=e^^%J}6)2W&cK{?ndV8-7DtW=huE-`RZ#}+N(dN!B=0eje8ew6uS4^tEcmfL-!VD
ztzGG5Jnf@zX#Sk2{8g8FGHZgbO0T#!Yn4f|)cugu(>{m8TsBS(zWUT}dg1>wD_<3*
zpWg9%`KsE$A8RMQ3MxOf>dowx-$MS+S(0`8%>0nI5fkT6l~-7KYg%FZmb||0`OEZp
zn@*=^U7K5DeAUc%pR>I~&{p5aYRi7Dnwd5GS@EP*xsv~V&Z^B&offIR@|I=kSKZb<
zk++tetL43XC3n`Z4T+1*j(${To8!47B>wIkgXDxZ$+L-WwP)r`n4Wm7XvRh!<Lz>p
z{`)Ug=}o!2+gEhY*^nDM^qHmSy!;z=`@tL2+Be(xZhZ8cna9P)(dK<dPQ~%0!yogO
z94$0xcl=y>Ea|YdkaXW-ZUeq%ORiZPjYXvIHQp$g6KDMG-p{|=kMbQhh@8Jt+IUJz
z&25QEr8Tz=I@Bv9lxHR$yT&1>lD+pv_CEdc2WwVO`+R2Skwx0Qvo@8!*>z;g>NT^A
zN_qAiIre(i&*-R|()0Ibo=;AVPl?NX`iDhh=dVSdCLNfQpZeQ-!s@H>O>3mnT2n$F
z9r09*m}*hzx1>kw<MEZIlfI;%+BQ}FcG$d}=%1U;p5NzWb$R-94=!i%=U&+gv7M|z
z-o7a>j{649d0!$cnSbriqVW3m)$5Mr-8-58>dRN(t4xNDE~+lENuj|Lw9Yez_^(`%
z5nlg(nn+Rh^xq|-zxL_$M2NcS&c5fkb?xb-o>fU_PF)IK!?^PFwx*6#YSV<grZwG}
zeJsG`v>5A29jVDbth~B%Q?%x?M0(A4=-eaD{c@g}-Lsd|bZwGXZ5Fz_Zt|^Pu|j|H
zrc9AeQSe()dFV=Kc;UYDeV;iFulhL2OfyTH`{R_UD{YdC61*yFAHTDUzq9+zeyy&O
zxNVWojikf_*Q{ExT{W;OPr#7H$al$k+vZ(v3{i5KHH^o^!|xO*E#|z>d$N4DN3+m#
zw}5&f@yT!g&bE+Q?jUO+;`nS@Thg>zC8fRE3l~lLxW%FB=6t2K%R}d6yX@O|dDbq?
zlR9^&7);Bv+M(IhqtO-lEwM9Xa!5^<W?Z?*`q{fuL#sD0%knbtHdXCjI*adVmx6L<
z(zJ~&3p-4W+U{MsIQ!WuwQUcyq;{w7UEF`CvvAj^os2nJdigAyFRd)GUbNxLu^{Qw
zIXas+TDSRe{5bitOX|sPzwkru0zXf@Jn8Un&f6E_%ax}E{eSf(St0Z8%M(W~<@jGQ
za`g6#Y`nEGu<gJXb?MZyjj#K5>*PF<%W^GmS-UZmdEQ5U!zascg<n?DxSPO#@k;+P
zp|gK7)-^oxv;8qY=$+k{yi<4E>rx8R<^JevmdpRTK4mw*@9U=8)9ZIg%$^o*Ad%Gg
z<<no!D-K(wJa@@A8Cv$Mg+Hmf=IfTYeo=hWOWhNhC(P}nCfxt{cj~)E3%2i3{{Kh3
ze21;@r?%hitd-mXX^wHsDe33Cq*;<5*$2P(EI(U($0KhB`{8LT=eb<+@qb>}s`KD~
z?3s9Pg-7dty_MM#ec=D@u3bLNUJU0LEzBFa8Fbz)_$k}xu=Y$d<C2GmJzdfs8w56m
zoLE}**X-G@LvIuu4xN84v*5|!=leh05~vgqj#6~IbYE<S)O)RM$GQ_GBTS^G<WBqb
zrnj+jvDM^wwTvUt%`eto{j;^P^6crYOogToQaQ}~SnC%*EEoH;RxdU0x!NDo_Vbm^
zw_BOx75<!Sysx<U=N&-~$+O~oGLmQC%j`(l5@8{g(0p_*^Zv&lc3Zm}pX0EQ+{Y!G
zpnlV6pI6s~`(g$MbLQrLY}-DgxaqdF{6F1C?;Fm(J@oQZ?<*mR5L=#mEBIt49+(z4
z@!kr(gJKGo?!5f8_MH%?SR`A1=ydKWmG2JkKP#TO@xf8ElObYR>1UR<UY`2%tNOct
z;X7SEo>vbv%sFs{r~Y<hd~~$x92uFKlLx2E)T}%p&#lC!z<!FAcYDUm_PMsg=UC>X
zKA7%N|MEh-5u^D_$L0@zcYB*0y}H}`grH)K%|XE>%>w%Ms#7vo{Mpwq!QZH^Th`H)
zq26#e*P;#gWhY)<An(^aV}D3RL;j2jRlkhfw|t4^^DOzbDfCU)fx4;uQv*9=Om;b4
zvo&ft%>Vv=?}LCtQsP&4#K`2uPMQ2}&5?s0`8?YhY64}s4CF7k@U9ZDmi5^;ai#Gb
zW=0c**z|_A3+B5x+N@DItne~y!FjKs&h=V_sS!I@eEFWzU1;LD#%*u8QfStJSg``-
zs;vpkEDTTFrt6yTYTL0<KTk#Qs*8{C%&FgdOWW1<E=&%6@ZqxXigj8Y>@z=GcW3*X
zyg#){bj91x*4?%K92cfuRSmfPy!=?Iz=Y!DE-i<Sv@@IU?lQb+C${AD>hFp-<RAM^
zOg6BMHMMa6vHPmS^EX`8Q#UD0V_fP#<AIHJyGy03ltz4KjmjTY=68`(r8ADnTRfKw
zl|0b7r(WRQK^LK3UOB}xU2`XWP!s5x`gnCz;qpDqZ$BK>XkGFCX0E-M*^lVREqp7A
zrUbT#m`(V8zx+hM{VB^6?(4RcUd)hKt~TvfgoW-$E>|N_p_~OCbGF`nd_T}@$$yPg
zvlLGpn;F6$5tOe{>bhI8<f!lRa}NL8(!!*@s_xCyn$+-??VPDV%66MIOHUQKFvsjy
zt5gon<jzlHtl&O>nyKqb43Evzj~)H8-&bXATE6R-3g532AscRbo#HHSa|?R+-ciyz
z`-o}EJ^haoQ>QF7nZ)kbmDS9%^mzWmhYGEHCLtypde0~-sa(@u<D|`F_3*iQ!MXo|
zwSGTm7M^qAuKO;(^MmH*t*ts!U)O4_DNy+G@qD>_TJp@7b~!VDZ>ag6IRCBPo6UFH
z|E|2#UU?UUcD_4Y^Um4!-C-jz3fpns=>J0RKgW3uvVZc&KC>^``v1b#zwLF?{$H@4
z`aj@w{fg`L8T<ZUi21)V`k%8g7+wD$U)a#fdZHkGny9V6uVTka6|+@c^Oi3WIN~ED
z?dp1drAALqm(xmd<HsoiE`hB%NmqZ&P?^lR^Hra?icgb=UIFXUcmGR%PmbewxzoCD
zq0mmHqw;J^b8DU&i5zY7`@N^?*!DSz?`D|3uUlRDK2<;Nz@6f|)?(#>Pqw<M?pfDz
z`INa{Tj7&S=HdAp^bU6wbg4f4vfc1Muc_ijz0Fnc53STNdZ_<@y-ebS_8pTs-kQvJ
zd7f#xE6!BwwO{2jS69#01suEc4shP(UT^thR&%eAi0kfi+D_ck5`Rk+y>^5$Ea(n2
z5@2{ZvtY(b_s^#;eYq7Wy5jMt2=0wre7^E`uGDl4<$R@Ox?{uo>xPFd#BNMz>QY&}
zXt|HPL)*(E7GDEnZ--nrdMU8T`jTPb@_9W9ZtpJMbbl&;Ae{ZsbhDt#QJN>tIdrW&
z=cvV9xSPRYi9)eOijmQoLnnDADLq?ub)~1-+4FwV^QU<HZ7VfC>J`-G_C%{xEqL11
z9(Da(y)%hHoV=pO>t{XFWQmPl>Fs+bi*3r%BKD9<_5JF_Kcg+~KHi@4z{-#PnYY}t
ziXF`bzdLXEUMOC8b?arW+fTOcIu@2(uiUYE`aHK%|L)l`4|`g=TaPUNlcBtPR!92`
z-Kq0edEB@xpv~g7?E6IH?O$7Wc6sdC<0H;?aQ{}L!0f#rW?#Es#kuAGi}PJy|M!G$
z-oK|`^!5IKG4)gK{(tz~{p<VJ`~OGV{db+VhCx64)3LAjJ*Vz@5y#5AciXP|x9^tz
zna7$eXVb)3+0=bfFE)H%%(k#8`qK*|a}Qk?%iU|4Imvh9)xyGmrxy!ZHdL4}Dt=#n
zIZ$KT=i4e@E9YJ-uh`stIGy*s+{t>)KVK_9zsdO@IeE*EuEr0>^FB=dlecSefy25d
zpN`*NvQ+HA(N@;wmkc(~D6aWf^I!gK*TJk~r<W%>%=-LN#j7LAWo83^>_^qVKmKQ!
znMFyopXj}E?yJ_f+X_dYZJYn&Y>L~jyM~?19p%FvpTtj`-!5(}xcKB-1BuV;jz#$`
zF3flQaLILzwnW1=gCdq3*B?sVheP7(-frx@AInx8)BNw_^Nw?tS=%?B-T(4=u~Fya
z3H3+s%ljRw6L@UZyDjOihCj!0^__{|)HJ_6INzYX{ZhHtX$h{2`=`t;c&vVqb&0>_
zL5l}ZzC7i$eEr>8=2*Ja%{yBj9Iv_iWOAO7%aMa8J(K0Wx$nMx(B_Bt!!K_Z2!1_k
z_@%VO<AhrL<?oT1ldmt?X(o6mLEit{`B_gwWlHAB%T3tD?Y7qXc%uF*H^m;$wkJ<@
zW}cgL?y`Z>Y|Zk?k1}|c9u76&P-N0soc(a#vnD0ios)FMPfbbRJ?&GZGnaeA-{t<T
z840C9(*ACfyE#|xy{EV}{lC)I={;BGHSx>ry^%P(;>V-R&nH)>KiYA4`o5aVJ5$on
z&zG5V@S$`@`Hv}Aes$IAJy#Z}|IPnnBKM`-d(P=AxOecZ>{ami7xI7V6}DLul};VE
zx3s>I*c*4}`NO~;a}J7c^b+sg*m&Gs{~x2yGewK1?Xm5x4wLyEP59ibb7t%B=QT8)
z)Gpo}Aa}RzafQ{)o)0XGt|pWy8s0tVTfXYVqeO$CnuM%n?sp>>-8g@!v4O9u)|H|C
z?@F7C&BEuaJ}UV&tv+6Bc{y9aqFq2qUjFT$Pac{|r4PJkXqR11s9AXANAOEF*9Yk@
zJ$^L32<C9@Uz&eNvu)CTv;On5w43|6{>IBxWz@Y0+%uhBPX6lk7TI5{iR#LSpR>%>
z7L>c!CZNQ2v*N<e{s)s^CZ-DfYV!N*xMH&sN9jKHg>yKq9{ig!cll*U{YanY<Anyk
z|Mt5ro7$z%8LmIiX^WAzks&XuOGx6+rNMHpR-0MRZ$7CrX?I59v2^|TxpF4bx9eBv
zDq5rppUUaZOHJO|dn9~|+_NoD6;e40mvLXsuig9WZ}I;5qTlPMbk~K-pML*;!~F8s
z_T9hj`(J&zc)sZW{P(}>|3%x~|6c!N-~Yqk|H|)s|Nn#h*8j{B4|Yf&J-EZ+&;0k*
z_IJMD<NtZvyg)$YiP@RE-yhyA?2X@e!`l9YQQ75tJcrm;=&mv2{&DX^@x7KQlRZtk
zGu1hh<R%~0oV>i6)$xdZSAjrj{&CSo93Mk$Cihiudn@|HJJU9<?7a4)_fE}<#t$c#
z-Y)f!EPpul$E&SQ527Bq)$*?PVAWm3uJ-nT%CUL79}Dmtz09=F;;5s-{}7wQP5dv;
ztgCXoGILJ3g^k#O*O3CcR)1c32%M@D-Z7&|<m&SaZ-2dubKIZi+x0X!Dv1A`#04=Y
z-3ywZg^V0m$fa>jKIbcOrzvB?6}HK@7gd<Ny!r8G29sss|5fb5x|PTGFZ{>xYt!eh
zue0;6pFg?WwnoKuYo*k@`OcvWZvSbz@-jbu_U6nB^Luwq%yXG&^LMTE&nVO9!8Z%G
z>vi<>JKmpCdfIBQ!{%<miX4H~yBB}*-uL?O;mcF*6Ke~${Qq+@aI(Dj?+2f)em)V<
z=T}S*o01te;d9K<$u6$iJ60Wh@2=lhF>mDzwaAMre*WRuq_r#~Q|#johiykE|81^c
zvwq96IPY}dy~|E%{{1EO+UzHnypP*tkFA%&UOCj2ehKuQ^;pj*)UW!(ryox>?;9<z
z<Px2FK)YS~qtGViuURve<hfUJc-A`#Fiv+~c6?5Z2k*{b-@|09+pHdXTnRF>UYV=a
znemw2*)`b6>fi>ctQ_{Ds?R$vSN+{o%;w5icH63U>DE@AIXwJ|>WSPM@_~W7XD>fH
z`PzF~4aq1zt~RlpUG*2H%xJ!uQF7xgdsan=dHUgZ3Jw<w1p2;<u5K0#xn|*Ybk~;1
zU#AOhYs~rlY>(*`^P2rW8)jdsz9cKNGF?jbjX;ox(Qd7<M&G~7yME-(&AFb*DnIG-
z_olLJdDHmrQdNT$->T=X=B%ih*#5)MU+3Tb&ZqZx{@Fd@e8arSN$StcpU;=wpH&(+
z_k+6hQRb;OzjI6txI5YZTj;X?bK92bskSLst6;`F3sZXm1)m_9Bm68HXEQ$8oXrwS
zNHgOL;O9TtJ}KbNJhAU0bJ@9`ip_}RK6iOTRn_DZf4HB|Z9N@i*E~Jbvv=Ab*Nf-w
zoPISqx5!SttI|wtj-$rmeTO9elt=E@h=23py1uLXQmNJ6&K8rjPK#O>yV~ntEz8xu
zb*AiliPNP1ou7<er3k4nXXG%HExo9})Q_d)mw-;y<UA9NbH@rR4BL`s?LXqnpd&J+
zO3#bsYtO?^+wFCjq~y;$T~KGvcjErK|KDb09Q>iWGtl$xPKjyV3wP-i->xta_~4f*
zcBx2V`I&_iCnU(Jxe8uvQ7gTm5^Op#PNc+siHeE0ldRA*)kMCNe$!HpE3VX9z3gk$
zRPme;DL(n{S2Vt!SRQ!$;p(D88*|U`PX9dZK~6A#)8}_NQ*5@K_AjukU8nv|E1a8M
zVAbW9izJs^cD=UQ_0Mis1*X3b!nRg$K7M^_&e{s+Kbkvcya_n=-DIX+WogBY7JGNy
zPy1b#PZL>{RH(M3Tl4B8e}_JWne(N0E;_~hTx|YFRmore>YVleR-Rb?O3d$uiTvs<
zNtZtU+}FA}Zc>2#-Ssk&PfzUnk)P7`tRi7$t;MXP&QrV7PTtHd|CLf!#}~fHwRo;l
zQ*()77JH!3nex1@MLP~mUA|!61&$RmxBg7Lx+m?^r$d?M0dGqTt}?ebNj+|D+kWqQ
z>lzy__Jf%M&FYitL|#0Vp4V1*s5X2N8{4X-f1(}<b)H_M-n94RifMjsPbXP~zv@3~
z&9GJKp`&-sZQl&XDy3^Y*3VtF;-8+bTM)_fGQ;cFoPaw|gZ(ckac>pk6JJ^6b-&QQ
zK0fng^Q2Edge5!zB}Gi%SZ1gtFz4tArhQoZFLsux_LYP~+w1$AJ~Cuo`q=s^)#&P6
zi&Y(M2_7#L47Plj(JpGU%W$dmZ?C%%Zsz?TSdIHuE?n|5z^|F({_mH?&ktFjwfMt2
z(@yui_P-Nz&&kg2s!d+_z*s`D@0O_c+|UmP|GsJezOVkw;;Y@)?CwvlJ^#ApRhs$C
zJ1iGhSkHZw`&gr=_St^^>qUQT??05O>IfC;;@{GJ<<$L<hu7}b8Sb`v*(Ndl%=P>h
z%R78gfe}Z_+?k_zysK6=+xVZ@@jPAfo!y_Z&WA;Ne*WV*Uc_@eOv3Mc>lu@zcP3IN
zJl@Q9)$$Urm#H~w5@p+8bZe>SrP3A)^)CA>Un0!{W9I+8b}@J+mps4R$Mr{qjOIGz
z^?91BeGDx(QTjNg{;BA4<$1S+?wgz5^|-HMbI?@Uzo0U7W1aH4>lz+~+wG$s?%P!B
z)P2fX@Qlg~#RyKxlHbmX692jMM9v!@58m<T`S)8tb&emr7yRXA^!$@8cl;JzbO=~J
zscY-`+a|K56EuuJc&}N{eWWoWc~eujN7yCN=2TO&#y3T6Y&wr(8)AQa>~rtSUjMsL
zBzdKEqpz{t)@4aNqRA^Heg_@B#OIrS_|_(ImF<oO-zw&7s<Mc`kJacqyecRm&g8sF
zMEL65SB-|e%~88D<~%8x+}UfLm*b<q(dJ;_^_55EC$I19i<glL{&?o%0c~%)t9(12
zF21(G+D}#YuY7g=@8YwQ=6+B7T=}nyo#jl&u`7vt!?*UZ6evXtI^Epjq$tnhD8bi$
zMd9$w$Cl1F9fbbBja(h}_1@oY>q5Uf&)oR9Hplb)oxSV-y}cW|HEZqa)vNyJ%zJa=
z`rqsT>1^Hn`4+C%mMi?(|2^Y(p2y-jb)iM?m1cDZ#)*75&*vY#@9)d~KR4fARq*d~
z{NI^x7M&<NSAR}BsP6me{r|siDSTGlSN}x+aQUy>_P?X`_WYmrobBJ{znk~}_@-X}
zW3v5k<8531&946~UjOm!(;qfEGJn?p`@p^`H{x97m5BeJ=KnPbyS)Dd`)<`gH}fj~
zzV+Y#>*@P{(_Z|sdb)pM|Noau?@jOiod4qV-*?ylKYq>r@B4KBzq`LXecm7S<Hf%7
z*S9}>D*I{W>YE0iR(?M}Z|h_I`j2ndzdUrV=gn8{e^2axzr9~K`~P$Qx{u5E|2aDU
z-&g&AU&23^|CheU{$O9`Q~mSq`n!$)ef{|&wfflmA57nK4eKlIxb_{WjXnk9_L@Vv
zk58|!ZQMWU^beQ++CLlpU+fq9GFMwW<M;uW7tZ=mGfNgH{{6&X|9$md=6}z>*#BEx
zAuICx$HEs98s+!j#9x&EcXNJMLd~cB7BWA?lct_wXZrtb{lCBaf8_ty^}qD9-oO1%
z{J;6%>-og9|I7dXb^qVd_`j?F|E~YJ{{JWaXU<|w!H@o*wm(&6S}C!+zVZKQix2-N
zuy6Sj^Y`}tA7AhP|2O;hxA^m-4eNtHluiAwTl%H`r}+J2YnI&q(-q`swrroJ`~KK@
z1t0e;m#_cD%HOyr>TUo2pZ)u%oz*^iXQ#c8-Mm_!A1!}h$Nziv|L5g@tj}E~{5$S_
zyZGAbZ+4x`CV83jZhY-Gw$;l|W{=h{|MTBW_QPN1-OB&=vDSaSeSPN5!+YY+e3vNW
zTK&gm9`~vEj)`BpWb1XKv-Tu??N|Q)xA4g!`(?IP7hm$*T`p9Z{n2+`;@?i0pN)>6
z#pYgWbv6)bta&Ez)<69RtNWk-kDfo*b4~o|e_X%PV*hXZUYXaW?`+q|IcaIfx4!)U
zT3hzp@dYK<<(n@>*7N+|A@DKzN=Kmbv3eE5%p*$#Cp+!AGvoiK{C{oUf909C>Sjgk
z|8X|^!rqz*LcM?gom|qA9AIsB^vABhfw^5DuZcVspPlq4DY$3;vLE};Et3eJo%F{m
z_>b<>1NSRxk9X`?-}B>sLFK=0+Zi7VGi~4V7tH+Ky|?qN{Dk7ZoM}qm{OkW5w*Qlr
zQ+|;B+h6tf%@6IDpZON+_xEIc(A+PVpXTpzfBU}f{NV@xzs%nM+_Qf1m)X`1=iTG?
z|Gyh~xc{nN*_WTpf9hlZoQnVV?tR_wY^jF-hu^QX{`ai>{=W~e_y2sT(^Yb9vvs-s
z%cFOGUVUHxeRq8S%&GNfSD!iF^<lHdMNj?Iw}02vKe%~q|G&@o|Man+n%_71T!qkA
z^Y739yVsrjbD6(<DbLFL$Jk=(|K6_uu~jEm{{AO^o5@i=jn{wbr9YVKUFR<^(ZBKL
zqo0r8|9|(s;>}(C-`ns1e|NtA|MvRdxAwKnI#7Sq``fca6}x)&|NZ;E{!gO6?LX7M
zPxW8$Zx;D||J^2u?7zqNoq8dE*x=j$6{c5T|C8TX`|bY^^`GxI|9gy#e%w$0d;I^c
zYxRFlX8%1t-)8Oq9ec%!=a-h$Y`*nx`-czP>zl-r&Y8>pQ~#OvU*)|;NSsr}oC~J=
zuJ0>wjf?oO|4cT!JMWM4|94JldNjZ2<-hkoBM;4=E0?fmPxJMU)AJ3!z4}vFUuCFO
zSE*52S@BVQ)4%reBB`hM-~az`{$>52!}<T8mH%(I?^Boh?0M|B^cl&ij|1DdKiMDU
z4O`QdAG1>Stk9~q|Gx`A+?P$?ts5nl%yms)HT=QnpopK3Yg)d=yv+Xp+~4m!%l|3o
zzTW@;?Ec>mi=RK=b^O2Nx&OxhcBjW$ygn2u9ujNw`cb6$e4Y3EYreNHZ9O%=JbUWz
z%kle{3kD?oc&Z=w<NE$@lAJYv*2mZPet*1~`~3d@@5J~2IU4`I{odbX`(H&Sa=zXB
zXIDS0oxRO;>J@w5_x1nY*Ps7C``xemf4{~5`&C}=`2Sy~o$~M9_y3vi|0n;G|NomG
zC*ylE*Zlvb|Nm<Io71v!{=5Fay8mbO|4;jWPOmqdU$)*v-Ki)3aIuO1{%0Q|{?xuG
zt(@0)S8lm{-_h%$RyGmx|7Gm+CG6g>`)}_r?csDT`;yt*H?~(x>%Q2Wo__4n?Weys
zyYpHHCH?+$cK!e5vFl@w-{wy``#LGZo!Lg}ez-$V>;I>(_b>hR-~P{I3AexVy>?#v
zzjf)CmH+>1{`-C9|NLM7ga6mR`tSd@{?Gg1|Nob-`~QDh(475$)wt{auU{X&?9Kn*
z&x6wUYAsBT^nA)He$+_)(e3`<OCD5yDSur5uU=#IzpMH6KQH?iwSBMlb1OQ%H)UQ$
zNbm2Mo@6Hv^&b=ce$0;l`}yzX?OKyl|9^fM`Dw<@&+`s`|26-)PSCzPcYgl+e|_=a
zzxK-it<SLhtYbU#Kj_@fski^V*R1=rzrO3glh?=R|Jq~r|IDBFKQQQ3r?|(KYn#sh
zSwAJ{L{ZLa>G}!(rY-Kbe{TP5+GR7Atw#lZ#&4Y(AkWINfKx!>>Z#=t^`|#}wL3Sd
zrt9$$-K}xl|FahdNZ#JeVi>}j!t%33JyGYej2*juUFqFNX8%MrocZ|Yw>_`>V_{LA
zrTdZdm}b?xx|ju54o$liaDn~DpGLNcYi+m%9D@~{`b_Wc7pgtO@0cmg%H+(*v5G-3
z&s^tc&=0T6%aeD-U3o2g!T;}%%z{@pgugaqH}~awCz_nU^Goekcyjdwg|=k}cz(V6
z{l4PspNQls|7L#<+g9^tMmeKO2A79~VE6w}t^fSL0&Z>UKi(nweZ#W(FTZG(Ec^LY
zW)DlUIRE|X<%RDeSv6K2SoG%m<%eO$=U#4~wOeUZz%HIearPV~`gSovZ}!@87(56}
zVED%Hus}e{eo~a@+b)jg5<#}Nf?q$q)e}5_C81BxX->`l>Dw<pELpjpsp8-9^U}}n
zyFV{}yuWwha<QK(hZJI49IKs*xumz3JifG0K15<kmd*w3jzfFiPn9`zIWm3WF^hfm
z3%qBkG98yI>^jb_Ja;c|Y)7V=vt638X-L5|z6U*fdS-oKcs9x1PAK}r!84+!^X8_k
zvYD~&V&yN7fEWK|@9ar6?!S@{_G{&#gkND^-)}ce5j(a~>P3)5<<dh&Aq}jXcg=W_
z@_75R3F4&;=`R`hmQ_VB`9J@^i|)#$mt`F!*R^fF6fT>dTCaO5|Nf^OzxB_0jDveK
zmTzg`*nIR+wN(A0Ld9t{JpvYqR~x1YFb3+)^gi)-HqX+9%aV_{&Ro}JT*8sQY%2c+
zkN;68>q6gkNfZ>Gs@y&I@tG@;S*y!Ftxe2TJtlSY#n$Z~E_yh3Zx2r6*mhMQCuQaI
z1e0~{3l;LyFEM1NKNR3DzL7m8eyY<7P1gYBt$TasF5lgJIp1OH){d-{-Op>D+~F+n
zS{M8_M=t2>lOOY5o()J|_R^}{b#3uNaqds0Q=Vy?JnpfZa*o-%r;_cMkk_3amYH7j
zL>^CQ-I6=0D`2w8rwZP-RE}lKkFUJEaUoaX?a#s=?_6bxQ%#)e<+ReUb)QMl+1%Tw
zEaJJ>E@+8TPZU&GxW?jAh4H^Do8`~id<h9QD=OzrJHf!S<jBNJ_ciJtRc};bHqc=<
zn8S0KbLr>S3;xsPQ{PIR@%mOO;nS=+r83jbwyhxN@D8T{P$VXZ`Rq0J=Droxcie+v
zaw#t;9@O@4%&U!=7V&#W<@*&}n@fAsUkdQ2?lGUIU$^-GeUA&Fa~3*VD4*VY-$}l9
z`DUFE7OgVJ?hOXV_m=fm-t$rJnL6!tKrrV*i{pFUWb97yue_c1^hrlnmZIph9oG%^
zX|)Dy?q~>@@-WW**y+8DnwAMsUMG&+e5-rCVtdVuKILUAS$%Bx?oH2qzhlw!2U^^#
z1-LEmE1bW!xp;1yzvuS_`HutMN6-H!-Fy1zi9+Gp=D<)FtEnn8G;@|dR*6|2X*HKk
zD7Nm7QAo+=6p2+Az0WOIe<a1Vnt|)-&V`rnM}$RXUdo^RM`uD;wvO|%%?{JN_iyg&
z=}~H3uUwU5x-2W@5f}Gr25z;TQxDC&GgWE6VQ53@i4rld0?jG8k8PxRZ~U!zn<(|~
zj8RBK>!j$cFOzgkzNz%_N-TXKb!GyigjY`O)CC8>t6obMarn8N%{YaDZF7`-vi$Nj
znw`QwxK<eazE-h}??ZxJHFMBxE!9Ltrddu5EuC-P^8K1pwEBGRuL)(V9lSdlEL!(|
z=a6UOy<RqNy-}`a!l6H3g%XcU$(i_1c1=rk>MW-dM>yY@W~}cvynaP0X3p_@Y=^Jk
zJ?Lq^<W_2vAM49Ew%aSV*GwqNHgIlD(3rpXdB%H>rb~IU8Jvs)kykZ#w|VYt+iX;p
zwd>FHDc(}8E0?ePQFH9@3#YT`F2|?TO2@WH)!j-kTC->a$3llN@BJqH^&P*GPx~I5
z7c)QqrS;Sc32i(FzHFJMRFeN^`4RpYxAkxC*e5<(yJ&-#`@uD4`I!+fHyY>3WQ#25
zJrdn4X~e*snY%`L;ez=(VY4-vRMuSb)L8m8@{gQX@hlbo_1gTG@>)|@FmR`AS!gcg
zu_O28m8!sNYY%SVIp|>JJ=JUW<FL=m6&NPvO-(()!2M)njNeI}Eo)oC_$G=xy)AWS
z%1eU@2k&L<d*&PCJs~sOAb8oKfJasPv#%6w6DT;g`mv7Wp@ltPul=)4-LThI{K|SC
zuj7)DmWLkNd=>Ngv0{1Qy4yeZcx_!eA?wM??;LyAv^`-pRB2xF)$Y~a{0Z|Slx4(}
zWKKoC=RC4|@8UO6>`_iEE|IToC97Elro_Cq@$RTN(Q?f=!}e`h;)@m;`D2wYDke)t
z)OMH1DVO%H{B8Jig8XxjYoae_+0^%c&sctmM|MHuo2l%(FNzBBnj0;<P&<*u`~3RQ
z8H&sXQ}(fGO??`kFS7r5N6@dZ9uY{;N$UJv%`a^q7^oG=FL<kXOXc$oQaq;xe9k92
z-_DYgZH}5|vwm|3Lu)7lt5L+M@Y5b5FOEc?UY@-^{ifEL2`>$%9BR9>TzbOcA7@r`
zHmgLZN*c{ws=h%nH&Uo2!rSY(!-D5Gq&T|;JbmMwSG|0C?@O@B)z8_YsVf+~&PKo2
ziSN2^Gl_B9LMELlTkhq}=s((?^7NY3d7)P}GuGXU-uHcD-aY&BSLIeqnRI1Y4yk;V
z@^G89tM#5Lufs~y1+#*Dj;?%VYO}uE@P=5jfmihV=6fIc8hNA*c{S4(-T6AtO(x3D
zV-w@WASES_g!i5|t*15UL?4&5YPf8hKE>y?<c=<*a~{sloHa9zx8Abwi+nld<f%kw
z)mllbUymj7Y{H{0&R@%H<GbJ><ZZaT_x03T&f<h~yvz1Aq@D~B^GI~=+}j&{xmL`5
zQ^2>-!dYuK@=QJFWSO&|%vQ>Gky-q)uPde;v1^^}EVTL%k7Prm%Cx%7$qA10C&lNU
zVgTjlQ%NtGP88goJ?B^LPsc@T4}uiAT$^qs<-ewI^>H(vPdU9Up;nwvHY(q0O`P=f
z*3zPTj~TqSib{kf&X{+qYTKM+a~H+SdRw%HOvrz2<IP^FFuPXalf>$)!tW1qEBLB9
zHMM*z<KMfSA$-jl=?^_Zj2{!Us^1DE|6=vOkQw%Ft+B6a$|Id`Qi;c6Ug?&tT%Y)g
zcf&TZq(ZrB-aDtGI<{`*=-zzubwR~0M}x0y0l{1gHCFCbm1w`#KPlf~%ao3eNw=$a
zedE*6V7%VAOn_mcDQ|G@ltrr@9xstumikTV{1T!2?em{hYM=cYy|VJpzd6Cu_WP%9
zab3|2O4eEHylsnLuRJ6F-hI-`)2IDIE)~jxsu`8t`@$FT%>AA_dDAlA=FsyeN<p>3
zg!h-yyXD`iU%hvHv#r$e<>719pIV)}peW-}S=+tv`p3&F`Jb4|9*VSTVD4PM{D}Gw
z!RfW1jHG{;ihsEhb6nD@<?`hC_-$&||1Y#ZubB}(IZU`jwk?%`EjV82=N&h@$iENv
zH8Y>OSh_&d#bL_NOE04*&yO#X2z_k*;E+vh`Yo>$E-&9RPg#EUOM-{um1#^GXBzU&
zL&E-6-n_@G`lcaMOHugQ{_TB-+Kpq^Z#*Nl><veDmZ8|Q{o5H#$^tSAKcDrwDR}Kl
zlFpfi{Drll-5a-wB_+z$NSmB5=SY1ER{Qku_M9hocpcvLEtqztp=r$z#pBj2k`oRn
zFVl4ONvU~kBdhj9>ynl3RCCo&{3lW;M?A94KN&UUvz*&vhwBS?Q>7G7_2;KO{m77^
zU8-<mQtb=nmuFU<3k~dzPn_7B5_fc_m2CT_Cl?)$AD-h=u5+?P=bpck#LGQgCZ!x5
zMyc{z>%Tl`Hqkk0Qj%35%B^@YL`mtyw93j_KIa+9lRB?#6JYdJWLPxiX1mCdWRE)K
z13$|e&cvzDa&l?OEbg!~J85&N!>iq`PpD>YhL)h9>RH7PD=hfLB$N3HnV0_1x+vnL
zbY=!~sC=ZFL(Zp-$rf#z`}|@jIB9v!%D-V45TqtF#kzQf4nvtE_eO)<efMrow7wWw
zWnx@=BvwFK@7(Ns+jjo#a!DH|<(-JV;G}nMPX5GB{`^1x=4Pb*=GdcfEMbPteW(AM
zB$~yK2=o}gxP7B)U!cKr_Xn(oERS7&P1-%Dn&r%I!7|654F)sq(p#TzXf~>s&D0hY
zihS!<)PI_(wbS3aF6?}v&G)mdt9IEO{o}!#cJ-2IR<F|6O&6y>FPl;LFW<pevn}i7
z);o@edc9{%(h>if`B|2WcZsH}hwWauOD}HUFf{xfHG9eg#mfraTPN&NXbmwvEoa#F
z>B>ZvWz!~~iOcOgX0YOjPcYZatVOm{IyXGdxV0qwhLgvZsSPXCZ{^+DbL9!+_WYgk
z`CY4A1EM<@W^J=wl6w1?S=C1G{)+9DzU`gcLeyV%eiK->t#aeU;OQr~9xqtb#aQB)
z;qcWZ`ik8t9^N>?vhEwZZaL_$G>kgGZT^kL@AETn>uha|3v%8vukikR<NvMu7-D60
zOgC^RwXnYY793vm=Z9j6GuKM(C<oS=-<;<prTT2mZ4(O=UowGf)0^du386eYwWCh3
zW`4UIP`$@_mq@bs5suYrxBO?GSt_0pb!1EHjFro7`LBGWdM+c1IXjzo&8vs&Ll`zx
zT{w7c=g+ziRR`?qjHcG--s{NCK6++%yH%cNUh=okH&ym?ofJv_G)ZdG)i>2&W?nlU
z$1`)6&(xLmbDeVEL~yU%c4fgU&L0BR_S?8Uq<h1QlHzMOPAWeWE2z9~UVDGvyVEz8
z8H7IStd}bG=k!**GA(Jvw2sY}f|nUgnZnnyYekDkFy}-C;prDwY&Be{nrC{N`N842
z7mrTJ&emNwsjuHb%6#S}A?Z}Tm$w*2G}EHIx;c$L8rB5OvMy`vR$U%FfibIjuhRA#
zRa$meOqXojsCW0quKgFD%U)}g**yJ<ShW8M(I0Nk57Jigew!q-`RblOFYCNj7VEWb
zl>mjnv>Enawe4moizR^*hjKkf)Su;(KIasz5;62$dhp8TkL`(xq1+p}qdG!Ae{2u@
zUXgAh%QDN0g{AX{vtM!EX9u1Q-a#ElD}Ok@s^HLd;5n$B#KYFlI44$4Vr#40Hh<Yl
z`v${m?EsO94tF)T<eWWsSo!NKwW$T3p-O4%zO3cZJ*JnTDE9ne;%e7<=f15y-&^C%
zTez@{AtpMfAW%)NN-sHkL&$N-J?sByDz~@$M0d?F5az#fBZa#mWV_L&TNiBY4O)VZ
zY?(TN^Kt>#qKzkHnm3)D%PhV`Aj@0uipOE+TU{!eYrpLjKKc9JgI$i#^)d{vpE$I#
z_zdU6)*BD+{OSF~I3fJXgdXD$2X-fZOzoPIc~;|VpUIAr3p=@^n!6{z7nr5LDKMGG
z*l(}%u0S(}FO#GeC;t1}z^8cqCF|iyj0NFGI=Ux+Xx}Yk<XW%Y*nWdm_sAlbKeuMO
zDP-?{$ajiOHd9MbNd4jUhNJaad&@UxU6{E|#4u5;PFC>R6b?|XPI>Tr<F^|3FIA39
zBduJVHNQKvea?Hn!RNw+Z30S(%l=MK*vHJN!(XyO({#aw-`gkE$5>><{64dBsnXwm
zhR>`DSK?oa={~u+G0$kT?bSV<+dgUY=;}Vx>kt%Qersb+XxQuN2R7^c%y{%y+HAAQ
zg_YYxf&;h77E8tPvVN|dx#Q^5hR-EuOqNdIoSa*?`glg}$>lpgdMpn-p~G9UM3>cL
zMymV#C#k+B^PX8QE^_1oxv8-1?0XLh{e7L4-TdEK!&t3uT#HJW5!Zg}w8k!__FvJL
z-BlSM-AX!hbZ4nXtl7qX#fuB7dJQ(HF+5=1$k?{ibn70gYcpMUd2NsA<7Q%r6HGQZ
zwNCy(<EOU^?k+pru_{=6O9$8I*X_ThPhB%#d&Opnj@FfFP8#Pnyx*(w#p3yi2TcyG
zw}LoaEx(xt^e#009qxRYn@KcN(@;qD*7L#yU-rgjLJW?xYNccO&7Ji*OlGJu8_bBY
zPtj?2>+53V&EyumbYgY>%Lmp?2fQ58Zv~xbvD-KG#bG7K!?)D^J|C35JK^VywA*IC
z?8}^NzkQOmHTy70*fM5Tew&zMu4>z(DORmQ$4ibpN&fIDLnE+<huf5aLBGRLV%fDX
z;r3;L%Tv~$yP8&#l*O8+%CKSCwF6CmthUYgEa95X;h5uZm3!xq^98G?*Bdf5dDVQ@
zCFf=OyVU$|y1{TeiD%oT*C(uR_dZsf{{6Slb6uk@rXz6^lg<1#YPN_~PPDrFL6YI#
zT}E*>22dTMeDvNT`JW>DyS8riesQpskwHI1luaW2=H9J>%ub61X6p;y)8Hxj&~$_0
zaL8{yzRpAMoH7>#=jtvw6!ZJxKeks-YBy&yi)MKlilp7<->dN@>dKDK=LAYu=(+~X
zDYAFbj+5GBTV<B7*>Wq0gLUWk!wV9)6)y-mDV*3V?{?>~?#0(EvKgF;0&4g8Z=Tt`
z^Rbm<>#QIi*UazEhko>_t?;`rahZ_P#)bT^8Dbn)guLGKhwt6Sw8{5vEZX<>GR4N9
z+!4HZnYoqs$@NdI_OR|yJ@$arknQoD*;>cU^i;pjzw<nWt?Q%RjZ!8C{SL(&C-zht
zpEZ1IcPz7_;*@`t?^Qifh6=}?gKnSZHsyS96ZgLN_Hpe>>7^Xps>}-OS18`}*!$A!
z%TG2NrfvEw6f2irIhZo1>Uhxaj^8EwPrrG6d^W2#n?sy{bjqBX<5Onm<e!e!jIU<X
zkrb$O<UQ&3?d*H$X+GxP*Tx<eSSJa#$bzvy#H8nL%1gUxy0K1nP*DT!dIom6_N})|
zBuYwGt#u8V(`J9?e!vgkBWX7mIOl4%JTm!nulI%8KB2S_vlRi+TnjBk_q(hvG&$0`
z$}#m;(2<sxKT<s+gq0Spba9!{ec%1=VO__i&2C#-8#;_XwjX(R_g>=N1xC55DUV$K
z%(LBhm~)Lx$qL=pfG;8kR`3RdE;M@kIW5a{u`Fv`lJd<A?R{o%ugkD2bbSepYdE&0
z(4;ymW13hosC>Hoe#=(9_wpIi?rL^2HnDw4;=ESn3ojjvnNy?AHTf~?>xG*-j|bIB
zMsCt(Ylsz4*74aL?6>!nhN)WU=cNnmCUr$>ukeZPoZ+_1SG~`1Q^SV+KH09|I$>+j
zTe;19j!t}To%8&5atMc2#nL?u33D=!Us^oJ>WZ1UM`bzlVxz#F+)-zac9xwnWWQOM
ztGza!iBFFo60+C(I=4s3Kl-TgSLRk>CBp&kB%WiO-(_Wf%st|^u5aZwv7o|Zwfpxg
z=4yuTb_!UyO~k42RP9TbnlGl$nZ!7>E>BZZJGFCt;;EBAi_Kp%_hxV^3O>DaJu$(P
zqj8!5Q{tgoxupJbW-)fH3n5Gjep}z)JiUAF<4X>Xx12g!W`47^tzj385nlmn=-l{X
z9#p?LCt$<3&SJep9o9t~tNj;Mum1FfGyR6;*;w%xv(GL!GGVxy25M6)t(X}1T*6ym
z&G$(g*y==+H)%7;?q1LuF(V;=Yj60655JE*bF<6U^KrY{;Airh!=+_q=_=I|H!HSZ
z6TDEnY@w}06wB7B5?q(FoJ4Ql={9;9a(b0ma<1+XDbKHN|9PWc|DGAYo&6ePL)LYH
z30W#vbk9#ev(<s~{?d=qsST%MFC?v-=s$hhQ{UpPAG`nP1s>C2F8S1SLqXcJbYWoW
zf^1EZ<$4$IXs|F;x%OVP*jeZF-Q(<K0cmh1llfh>_-BEK-TEsmR@cRn^?bIjx6PWf
zV@V}{VC({CU(FUN&hMr<A0OUHIvC`$m7Ck+Xyy0Pl!(brpp-YIDxU4$=edrlO>A3Q
z1UNpw%l0eI`ntm>VBs<mr^0Ks{u1{aS*LPZT?$E3Df!WB#1JN+b<M8u<&_P`ckKK4
zKsT9hf05k{&vHG(lQw^@eBRc3Ibi+=$K4X`k5~%Ck4)eWem|${zObZxs`~Fc8Y?r?
z7BYZ(c!|G!cXqzna>n|@_KRz4?^duEtd3y_2<}?w_U-N}`OAko-#yQZw4L&9zVmg>
zziba$i<p}W+5Emb%0;*T*zr>-|5Bt-@`omgrb51R>z!UbE;=gp`$of~g82z|LB=Qd
zvh4X>bzkvZoLaa1FQ#?U3>6Ds97xdqyY8sDrs`sya2poc)j1bVYG?VFU3$OiB#-j>
zzW;XnKZ!nEyUEdYeTVLriOumhYIXz^^e(%Vu>OSM?K4NumsiiR{vh<Q^^>Ez{#CgN
zIZK{gKW92gTFzyfm-y5@0nHAZrp}0ebYq8->eqyDA*-^5T#XUR_WOCnyQ6wyHCz<L
z)Lw2c{8`gpAh|fnSNE9I%wMK|Ez8+rB45NrXBQN1tMfHFKao9Lf+44y*Pt#TVT#}m
zmWv0qpHDmduJ%ung!<c}8*}^Q>rB^~Fo4rQ<^1-$FMn*Dc+iM_f%p|Rsq_z@H(1Nr
zf60g_SNPN<HEFF#9N+H8AD!Q{w6Zhkhv-W5O#V@ML$+VP(-2hBT6E8Ezx(mWL$`ys
zm>a~82;``K1Y1y~A5p{b$?0j*ghD=j_q!iIC|+(|%KqS1(izjs-wW^TwSRDaDeF3$
zl5atGn{K)>)u--We)`iAvkTl=%(+WHY`^_>-mHg<?=4t=f_K-{)Ay}rRKNP=U&OsH
z;6Oxy^2+^3O}>ld%zq+Q<Cu4__su`EE}hf5Kbr0|L`VM1y<>OZY_Xctht^xinr5H;
zXBuwxU3|5d<Bz3U#}CYo{BP=N%dWlIkLic#-cIv*@e!e&ftMM6oqD<SUQzYIr}D4X
z9zLlb9=FP6`}EF#3%zPYoIeB|Z9Wk8N?&xRwN2g5&?o	C3oq8z%nj{`!!wKOyhh
z@yTLI;$E^XTQAia&iL`+HRqYD300Sz-ZY6N_0EaU*&{gr+i`vEsE*hRPHQH<?~Xpz
z9`7HYm-lkAM3K0c%n8%awI7$YSJnS1`n*j3s>I$!$1=3<%b#aD#-Ps6?6>gvija~|
zUNf6dhV9ZnAKw-uci>0+bN&7z=6x#13$*XnFS<Xk()JYZk4Z9z*OvURyL|lTdVi_;
z{s|wZe_^|S=I8spzQ?wI{(Lum@6mXx#)Iac|3y!b7Ju=}=kHGzw)&N?HvS0vR4*U7
zuYl<_x6a%HKbX=O3#8BamtW9|SEzf*B9Z^>|MfpF?=-IY#Cl=+D*5KTXaB$Vd^NLu
z6`6Zr`WJ~j8{vaXIrXwbHq@rgbU4nQ$~L!thC{i{$BhgU#{b$%e13lZE?Lj-#S?ph
zN#o4l=OtctTAwxl)>=Jn7BTcyO^K@fKV$VN_vcA7UdLQzS9H;vVqta3<HvEC1hIGC
ziFw5h@=F+Y2HaLq@%x(EX6pSt)Id9kW9w3mtmi*$+UIWltu*7c%r|w-C3>NzR#!dV
zrA|HYLO66<z`Za|n@qt{N3NA&LHer=-HuC~HtcIWs^f0*p-ZB<w<K=bKAw+v*#7VP
z@-&e5q;^ts&XbSjUuxH0Tr9OX{E9@b>IeSszxM5T9ohHLyNJiU=zH{aDfRt&%c`d&
zf9sOk{C3S>sS`hb<i32g`Q8Ejsk&_Uyl&+)9~b|^R_B@jpzu<i>|*`xeAlEq_AF>i
z(T=Y_(ef^PJ~VFUtiQkM>~E#d?3&ANedS#8=(zZfwgXSw-M0GMn9E5l%zR_>;Jq}z
z%=sFL+t2(sovpTceb_!%NN&oEOfSL99=B5Exu%_R6ZyA~|7f#_Q?6#qqAjszKN1qB
zn9JQW`?2Gt!g(PjIlmjnmuc$U+0MB;Z`LOT7nf+x4vWy~YcuB5zvth!fW>9E8l%gc
zC8zo9&%KZSBa_deqh+#4v&Ci3oYU_-ALsSHo&2Zv`x16=3-4&;&NqIhc{gv&J9WQ&
zdDR4PVXrJbUG_j*Sq|ef`7(xTA?J5ZV#U2SfB5$0Z~LYKZm~&g{`kvx-+Ws&xO{Ey
zz4LpavTcsi4~^q*L`~D8E5GX|ef;=)TW^0=^FF2RFT&o{N=ofh*#1J>wcYXf&+oMy
zbvOFIc;-wHzcQmI_(QwO^L<}mPlk+(T>j9m@@d=gcaz1EbJsSuo)=j2h(S!u>V{qE
zEY)jw8gAOZ*<WMx(NKE&+ePhVZ^YlezwK)8A$U2=N$uQ;RP(%l({ql$eZRZV9#mO7
zX?UG}9`;;l$102C*VmqV@71woiUjAUPdl4!{(Enm@O``NllM*>TUt0eE*IULG5^1+
z^=Exe#Y-VhD(6l;UCaJhs^_|#%zKV?N+F;+aL&}z(W=K%CDu>1Fe{I71vl&rROjcv
zl_)ITv+c2jUxDaCCtuCBM>#e7Bwg9g`idR9d#~q{O4}V)-Di(d{xH_mbDjnJQX(hi
z(Rb^b`iJL1+*kZOW<?*``%3EfUxFskr}z04Uq9>(J747!KPh?F)Mk4g{?$dy`;^Qd
zSP0fjw7!3zTP-C0gw<5-am*jZ^E>yey!Y%m$Q{bhCVldU?esnSCwu_$lX#Au=S-N`
zaGF~-dv3+P)kSyuKW_5+|6$#!$DRF)XYPqE&e*)?`Kw=fXW3QTZbh-QM*gfR)RdoU
zKK<A4Zg2S|9husK!s*W*uifxCtLOTmU%#Uh<y!<Yy%~klpM6?)w~+Uk)yCVq%j8=a
zGPoH9)SrH0dtCVMXWLIvO$SgjOY>)q{TGEEahLgdoH~jjD>RP=%$Rikdp`f63dZj%
zcP<ukYQGi4a`fkqn*Bd_@MYRL?%8+$k0Tejt*2#oU(sIgWJTv6&6vkbPS4k6D2k^)
z;!il`Uvy%cM05BNj+`eC`O9yppNgM#ji2u)C%7+`{(%4QiOa3ZWt&#BgB$wFzxT1~
z9GCByyX&XZ(}oAysr`)RLLW|F*q~>2LA$8qnB<S#FSd8}Bg|ghVAVY&_42!OQSl4u
z9T}iOfHOybez&c)aZ!vhVtCgiQFQS!<6<p`uPvvxoR^Nb{`&mEQ`MRKg3rvKDdcrX
zbCKH2RWoZnOY?4r?Ts{ISf=ahGov;5#{APd!S|~snlkR(mUo>;>&lcQjT1*ScTCfp
zyO(RD+55F!j>jXN8kj9B7Ko`P=RKOC>>v9p=EIul+)`&JDN3E$tGT$-_17Bx=y%y(
zEnB8CbPB(pu%cScGWTtA=gr@F2b>&JZ+V?KQfdD8hn_ok;^CE@pbpusAdaJ+<u`6=
z>uPRV`(L}|ft6$HtstJGKg%*i%3P$IbuQGmXDs##*r^?LruF4F<{Rl<lg|nzf9R5E
zD%|$Bpxw5%aYukM*w4K-zpwS)F<7ju+Mc=4<HAktq~_ezTiZL19(R6TYb=(<;t_vQ
zx@1Pd{kFEyjf~rlvPmqvGkxLrs@(xI8+L4yC@wtpcfz$jyV>=G8Oj}bc3QmN_q?aw
zfMqqy+$=9%tvZ&3DNJsX3!B~sw@+F9X20XweW!o__FCA?eY1SQwP}+wHtQT;?zTO$
z(|Va+2BWC@!^Xq=6PRN=Cw>X2&bg{14(=39=)Jsr&l*Xu=sD4GPdQQr(z!}yP91Un
zaP<7Km(^1;O)TGAu81?sa0q5^G~oTdXOG{bl*R8hF9Q$08E`HayEaRwW$B7}&NlZ1
zBaFcv0t43PNAJXj$+&Y_=+3=uxk@r*#o8kQGa7_9=Rfi~{`c(Cc88`ewuY@+*~FIJ
zpO^Q%M%MGp-d`nr*LP$wJQ3aK*e3Zy*s5)tsCN!%go)?#``@|G>@USvcgUVLym@U_
ziuUh)-!=awe+ntS^>X)5-f8C&YMGV!_q!U}&0EQNVpYcCx`r>TdtJ>xeZ1YUQP2E=
zb`f*m<xjUa)a=aNFvH;m>(<7$lRtGo?ktlG2~hadBr&;{<*(xQ8h4GDP=`-VGLs)p
zW?Efvz_tC@*7I*x{yk#1t60y}Z07T*7wWnyuS)u}dxPIRKRjpC#qUN(*g%augUsde
z{zsISFLTp;&v4Ud?j;=qfeOc*hOaF5#Iu-;vQpw-R|JM}Fsl7yyEuhO>CFAwyx;Q#
zRz7`l)XuNeT-<TzLZ@8SwnHNGtV|1!epsj%B))XUt_7?iGY$tIUw*}>N4SgaZ$);%
z(S^dks!EUE+*R)~HQxBr=;7D9PYMq%3<_V;(PdnIe%{SFD}sXazskfE99`HPzJ*O9
z{hi8p!}BsTET#wKO_AZ)r*^zx#@_o6|G4imnery$=6=TbAn5|*%Ki6BGxzLUA1eQY
zTW20qEu(hj{&JIl$-Fna#j~%<S=IXXz6|?S$DRGSZ@De!v8n7W>t7h&IdT8}<Kvq^
z1En)^mwfoX@K@3Gf{%?aw2LO^rF{B+=EarNHBu~}uKP9oG+4Snec|*DR&BwSIDy$2
zKXeYQF)!HI^x)ddm+^_SZ^t~}<h#2g&+DDZg_$@1PH^8jdFPU#r&n~_ax!^8O_G`D
zIO+VYxMz3Q{O($OX`7s`?xA%VieaZeN8Z@<ee;QBfvFzSUuSP{)O4EV)WZ^K*S(tG
zby2}%-pi^hKmS%{i0wJZoy5E*?RQ<yrRk}PQKt-#?pk#;BD#BH)}iy4M7oZwa*+(!
zb5Gf~YvHmh4XaMtWxJayu?L@+F1NtT@anZBEssx;GLO`*6|Yg@n(n}SWx^h%Z6~Ul
z?63T}$7H!@YZd<+hyI7&S;Bpneyjg`;kNPH-d}F&8}=Q1B-xX{K<x*=`MmyZH%?94
zc<sThq~>m;-^=5U9j{z{J7v1+jD0HRFBG=db7l5vPu&&j4XVr8B$s^kPd>g0+{oe;
z{<VDKucG}E<StKtA||`!%fD$7u~u9H(l10U-43_hyKi*CJEEzGBYtwSMMc9y@hslO
zK^HGv+xhd|6<rVE)0L|~*Lv+aaNPdyn!^d^?{dx>^%^|i;%~fkR*!s}(%MGTt!!au
z-$b77UfSwC-Q!+>^v|UcJNOJ&EE5ZMOnQI3?Zevc8^6`oyFGs)wpsC5LUc}pW7hfQ
zH+RhLIlQ$za)x{P1h)d`o`c(NFf{+E`|{($^TW@kR33V{3e*UZ;F(m@_g9tGUOhzR
z)$i%jOF{Ft(h0UFpV#M|_1@A|B7S+R|B9#{)2(b`Dc^P0nH)QH<kzd(y{>Yxy(hVo
zx_dTNU3+f!U*@IL)f(Q<9{CTZe-V>g@{McX)GaqzI}d`!_D;N+|8D2wkabUXNha~c
z2_zeMy`FD1Lt4-D>6vL#i$NW=C13pyp6NYVw3QX=%$9$d4<bZC{n_R~qyHve^WTdE
zB!6kT<?wpuo_deYbGFV`lh&*>-C)pK?`6xc=y5e^&05n94>VijHFOFh7j1q!xm~Qw
z<;ch6v__xlN-Lk+@uV%xD=xRwdYg1BzI0da!4R-%hjZ)#QZ*Kbe@nHq{9d{E{p2%J
zERCQEtIa<HlJbkI)OUN{PkaCVtd66=bunkXb5EVWnQZ7?-1_MCjC(@cZ!Fb6%*2wA
zt9$H_%e=!O6L0Qcn7dIoTk+a8C!KSToi%=&{JpozC#CkjVnh|gnzgMFbB+Y3tTn#6
zrf~K3c?{Y72exiyyME%{&e^Bq4jNv!EPo+TR`9m*2KUtNqh^!Jr8tVFJem9Meogs9
z>nqZw>`m)W@LKpinE&99(5~EtZyZ1kqQigwJ}hH@_2cc%#`%+E8cdH0bO(QrKK^KN
z4oAr5d!S+Ppu$^q-0?MA%<6*Wt~sq)do*Ik#`|oYp}I$IMRgqg`72k$?yh1)62y7y
z?Ne;t$1!O0IBeZIflK)7@;#qqGZPvY28%D5&?Rphag=$TP06Optga`HaiUYV8O)yk
zUizsnx1`nk=@#WBFG_!D&x>b&rEAD`JBgVm_>07EwcGQTi_NNGmtX0<H1C=yM^3k)
zgxX8P3%%1f%>Ox8q3BhF`TOqB2!(YkO?MdhK2L8gZgYInYxhIr>#uvqeOsooK8Z?d
z=Kfsr>$1#2rLCuDP2Va3n#5i9^2)2OBNrnsU;Fe`Zs9GaLf^Fqk6KopsI@Px+xzV8
zRmp^0#)I3W8rQy=GpRv`|ETiO<&x9mCLY(&VW@P>nNV0H7vvl4qyFl-LH-qyjy;Ro
zQfADvpO|TKBHB=!t0DFRla9}M`F95Uo!4uczSdsM=;GbkVW40C%5~w?eYR}9+rizv
zLv#L!t^ARZ@4Jp^l@i01DNY(bC-N5`TqNS;tJ!j><WJ_2+WS%=_6#djj|NQXu~#*H
z-^Sm?-mqngMCYUr%lCYg4Geh7uwa>p(??_G#d-%!ThE!EpHnl-I`+w=Cy8_7J%0WC
zur0UnUif{L8NX(2zjwCDv2~Ug&(X^AH@4>w9KId1zwP&i03C*PYmde#f9yMZK0HCy
zKQ?BPw$#_(9rkWJ8!m8Xb(n2>KV$pPORH~4>OFs!tG$ACwkfmI?IiBr;(}8gm*zaZ
zwCMk&TS>QznsZeiU3{+hS5s|Y%XI6u*X$?aCM28r9L@aFWn8@^ZH8Vfi<kgMc9^Y1
z_vHeq!%Je@a<l)*bQZjA*sx6^DUi>v*+W=cJ4e+g_;u);hDDC<x4c?fG=I$Xl(o&h
zs3RV-WG#!wj7IxA=L0T(2@Tx4KuA|n<<OVkEBCj=Ez9LS%_^JaX(+PnK7U}R`I6b!
z`9ruHGQ9+a)$aR0tat62u}sLY@Y`RLGyC3guMvfW^#1vuW`^%>f6CM_D~RLh&hO5*
zespPW0F9S%E&O4~pv9gb%edgjmQL{izu$}Ujmz(8w1~gmzUTP75TUO{7sa&No@8j1
zJYN&Vn3$`3<k6hj*{(Nt>TZ)sU2k_@G=FP0E6cW{5<SB2M1HCHr~a&6SoBO_MfZ$U
zrbD-qTDBU!-Ldr5^S0Hw@7x@YCwHpqgm79_JLYWc4Y9r!l{QbPYfWursPr3F%e2QO
zvzuGKeA)1H+xuTT?;A!aDy-9Wi&4J+?E1vhLH1mKi@i?mPJST8SdgpxY|#?yPj|Eq
zUh2?pd?ni$(AfZ9bFjy{N-puagxTlm<rCaPnVMz=@v!dvE^Mmeq*4CNb`KM1CBlqq
z`@12hj;~x9xfK)~EJsg%4_^Op`bLqp3+$J)Yk^YcseS7wX3DHF3|$<;07}djpZBr-
zchyXq<#nQ^^ZQ|i-}}@z_+6MeO~fei*54_o_sq7@5-wS`vc+dksr{1f^&L#BSr|;0
za&-07$8a3ra#EeO{Oq10ufAh8_uX97H3O|bCcasiJ>}8uUz6U4R4`6fZHo!cE-2hL
zw`zg3rSmVF;w9%MZN2^PoCmlR_1Y?2e!KR<os{eX`HHxCmuALS$|pp5o!BDuMr6B9
z`rU6f@wV=NmHTAZ_ncywD1K!^j>?VOcF!jUH(tLzBUksxEmqbehrY~OR5Nv-u-AeQ
zbvwN`h+JH`OeDClPS)7}*(8pu-@i7muWQg|0>|R!oKwp*7$w>to5fpw@3YvU=K!i8
z6F2#CUNdXgoA*xU+(FrJb`H=Gqu0*)2d+p=o+B}p1H5+e`5pf6=1+9h*E;T>EH0bn
zr6{ue?)A7QOS*Js^?o?VTe?ECHDE?XJo8nH+*L)A0W%jU>#DjO+Vk5?K*vk*$|NTZ
zpFR1_Z$EBZV8o~ZlG*ZGac<?-$_Q14Wty%&bIR>gy4O!=>Smdmsbwf^_0LU}AzN5B
zd#=Uh2ZHJPzJ{kSN>%ri9r86l?eD*=#e)6Mjn%5HA<^9{3?43Hh<x50rd9s^%hD@h
zYkxVU&+<BPWT%;Z)a-}z{wbbj7wUCAsw2Q~RWCz8^x4fT_m=&3ow%j7@LtFZm43n3
zGtyrB1b5D`IO%6tdGmzv2kW@$O9isL6t8$}*lw|%g=e1MbieIv;j9eV;UWUrDc8S#
zZE4R-nowS{$GRa<<V8Ysc0=!%S>GFGPMlP=vm&{Af?*aD3uqy&%8i{Zky_uPoPC!^
z<bj6XuO;dEZIa*lC*zRE1w+tkn{%7<%_|IcET7%Vcwkmk&(V|Lwkn?$K7Rbb$7xBc
zR<?%B$h&{&>W>(Ye;2JPy+L8PVq!r&dyA`P3n-&&eox(FdrvY(;e}6d*9?uv`_zn&
zm+_xw7R}&L6j*-Czw(h>SVG|fV_(&zq}lRn|99kESoo~c+bg!IG+X3D*?hZRU5&(L
zb2S~j)IanxU9M1^^IgRI=6pjh=9aBX#Kh8W&$K#Tb2V`Blciqoo^GGDJ5)Yl!^*aV
z8AX?$&fIwKx^CX*t67?->>O4&IRtojEi`!U*So8^C)o633(r6Ih259eN-+kWoy8WE
zcxrCNa+irg7rt!z`K3!N$X9d8qZ;dv+g?rjHFd_i?d)Qlpan+PPHoF{m{hsS?sK)#
zp_Tj+u1rq)QzRsMh2KdnKlx-Om-eT+e&-_xQ<)fMM{(z<++BK3T|;F1r#bt!wwEpT
zYe<RaJLz_>*16x<JZnMO+6BeAy3e9ke*da>dgW=c*|B;IpPbe<o-|<I|6TKB>b8Uo
z-gT<SVwAb}x2`vA_$dA2%qGSJU)^JmeEwLu>3A7lz2c<hb^QI}4==whxa62F<#nco
z^QY};%TmS=2ZdFtrYkJe_dlI<JfXRp<A~|e8Qk(L5=)uZ7%^P4Ggj5O|0jqk?#DyX
z`dQCI-S>y+owylp_p_vIPQvpL?Z2}WS6Z5#EG*<KT6|-YJJ-1-mi#}}nzx7lx^K9-
z+Tq45?L!_@qrLwe{;^&<pDXv-7x9KjCL5*#BcJjG%hqSe8E$(f*eranWcMBe^Lnsy
zuQY3W+kGZ3b1IkLwly*O>fSPQ?WLRLm+qCGee%mMD$sUfLD;T#^EoE>&t+?W`yBQ1
zsm<nQ@#hwPN5ao+vHM<<rCoSu{qDnSU(9)S&y#zR`=qHV??f)V@0)pA_{h12_X5g-
zcdEA^ZhSR`DNbSA1Ieb~eYR5TvgR2sdnTBiR(^eTj><m%39V<ovTYRFQM<<0)Z6&v
z-n%~DAA1aqO;7su+1~QfdM^|G<%FTn<M4SMmrwp)S^sbI|F{3YKmPw=F}M8^`~Ro^
zztjK!xBf{zXp6_c@AiLx-v9S$`~JUY-~W4e{{N5P_J0ohe{8q^_t4zF*1q|EjN4a%
zzxyv<E;#<*dds9^_bYF&e)IQy&FQI3?xz+1_4EZ9{@R@X&;IWDEB}AD&;R%1w0+I*
zZ=2`WeLpQ<&ujO6_5J^U`|ba}GXF0U|8o8(`&Y02Jy&-8QTf0yb&rn@%Xw?@qUATX
zNvsI=unMkztYXwtzH`%id5!(Alz+Y!IqRlUAz(8n;;({5;oW0>8*5B{20Z$q)OhIH
zkDA<1ZEu54zxevSzj<@^{OjlEJ$ik4Z(8RIX?^9XpN~(d2zBkTeDe0==U+GF?fK5%
zv*yj1RQ&1pGL>g}iW~nQ-?%%+)}TRXwprZL0`Z2=+4J3>_wNk<`EN?n+3jDx&H3TV
zTz6x|rk3V&0>`ZT-!ZWSuy9<^xTqa#cmH(F!Qj=Vs)9cz8UKIg@|@#oU;{%J1EZGe
z%*_9P?9x}33H2$hcl~u!>4oAlcSa@+CXNTOjI(R@ZPmN!_w<5pYWkuLXZFreE<4-L
z#Bza!At23F#+&2Qp(lsDi;ll>+;!y7|DgE0ZhGZEb*w&KUVgAsGp1v+(98HuS0mQN
z_RQN8$b90l%gSfR`(Hn=`)6WNzAkr821|GDIs5Yqmsy><duIRS$5A(&WN+WT&-&oc
zt>+hiUanx@d4oCnMe((=?}mIXQtKn-D|6SpjcnkU#Uz+?<5k?JAR$ZfyFnKw{XJHB
zdG^oWwbP~_vGrhZ64g<Z`4@Fg$no5+XJ>BeZ*1Ov(e|!;`7T|C#oYpF`Tcy`D!yNN
za(5x`YaU-l$?El`8frV*7d+_u8>61V<#NN@$24qL^oEl5AIs<e{`mO8o%IUuA6Pt^
z$0k%RAraD|cA%ryprl|=sXy~NYrX|mE>jgwXy+Cf7#I4l?6h7Y#jwaz;mOnl%Nd7v
zE?0S{+bH1Mq*$%>Dq+*>d7JKTXK^y&Y}pf3*6zjhJw$j%^0f8FA)HBXLVKA*Cs%9D
zzQ^QJ5teW$?z?43(5~aNJ}EHr#4a>i!c?~^B!270Rka}(FPeqzJR-sry==oDo;PWp
zC$IjF=<`n&=Dp|frNO{%ozfPkDgN#olR93sZPvQra7##FrOcW@iyb;k4=VJx&ocb5
z!`A4gUZT^~mpV%h>4dDvyJB=qL(I&p&dpN9(zV&DVRMNUU)cJ+KMd|&^%7s)H@)+d
z_LZb|s|Mo|26pdTVad`{WtMwBp1yqTlxqw49`MK>cxbh~b)$OuiH*G?`u#iQSNsSI
zZ1ZzI_-Oj4rGf32G+$+;cFKFFtOyQhV_V=5I%oU4%MO+E_MNkzu4Ey^C=~KiB|<Iu
zfrR0ae7it{-)3s-TE!;#wM%NTI8QZ>Wm{RP;dpNGf7dSQjZU(UB%Ka8A1&!p-DVgR
zpk}zvFKeay5+)tzWt$U1&%S>nbN<cBg~3k^`GW4uu$R8_SL(u*TGkg2%1c*Ax%}Pq
z#mDvO_oqUZ7a01kF)&1V$#!Ia%3fT&!d><+)6@(uLBY^B+x^}+bXfi3u(~MVq_pa(
ze&EHI7yrF5Vwj_NrEtf#{d@*|ytCb3JE}%Gd9-}}m%5@Xi>+vjQpud9R|<Cg*uTt%
zFSXb`|B+<+N`Z3)%z7^uJKy|xam|H^(}Wax`yWi2WF1mCCr3y$Q&Ul>iha7)@kXw9
zDcLI=yjL(yoL{h7a&8>Q{Iz_&Z6!0<ayycrzHR6(D6uP<we)i4_Tzug*PUq2UNk4z
z^5C^4YnE_}-}=iUzIRQikLovxC6yO67<(ta{`s)|>*wsY!#h|!xf(b09yt1W|E0sR
zmS&8sEv{TA3Z%BhHHCb&?3TaeE%Uo?wb9(xkQuBoZMtUnl#+NpZ0x@^c^%_4#u<v2
z6Hg>9aM9}3+`s2<>4Z}|PyP~3Xjx&P!))-x@Phx+cPBQ@NfC7Rn|jNB5~IX4#u-^g
zBKO^PdOkn(=l?UA)NJXajDeE7T+$ti7e1M2czNxI<U0%Rzn2bqsj=o#;Dx9K{=A_d
zZO?x`dwlh-^NS`d;FvgJ<pe9%h@VGQf8KmNE4MDg!kN9`LRd#ho+MB4`N*iS>9L9v
zJ}*4LBiZnB8q?psCzE=5x#nwKSKG3QQ8K|%G(}NfahjCM)Hh$I>twrET$B`1TA=!e
z>B7VHudXfW_?h~&le4Gg_SeE+ckQd>7(fl4pB&f4o;$=_MaeZ}Xb1{Mb6)3r6HsDR
zC1-UhL`lU!cpc-#mka-8RKKuT<81LlHHJ-`z3t56rwc#xC_Y#jb||%>tm@FmBI^*I
z3k*Ca{OfM^GXK1F@kKyo8{fwTg#~8?WIgKo)!O+?S~xmto4xnFb<iv<u_#%f*y3>4
zYDc&}-<4E#Z&%hRC((=>?9aU}y!`q$x-Fy4oGIf(xW&}Ve#UI;_>LQMt!8+Ysdv12
z@5h9u4E3u#lk9@jxq2r)-j%2kBAH*jc!%O*2YpqEvQw=M_G^Vrq#OB`T0HB2vZ?oS
z(B!4>*xrh;HoNvq9JbB)vf15prk7l0{HHmIiZk7uq<omJF{b)u@=Up@UKw^j%J2-Y
zXzB?Qkxjf+FK&BS2&EoRUa^Q#p)Yqy!`6ihHgGJMP<>#%@#Jeh@_jY_MN@PCG^}5^
zX@gHXBYWfaE%LkP9KE*UG5^JFj`tna9R(E_*%u!9SseUovGKD<PgytYI=FDs0xxyP
z&kcvRitLX5bol==wcyKbDORA3Ls9IioVrt{9shQv^VZHi??iTJf;MaLRIrO&n)K(@
ziJdpMPYk#+X(G>o4Lk=H6gnhs?J@IZc9L(+TT%B~`U>NmrOXy7k^$#59y8SLIHtwE
z*{0I{U)!n8CGig}fB4>=C1SXLjg8^L%!0iRe5MVH4>HbJCStHKyCAoeuVm%o!wZ>p
z6`7Q7Ke*K`%MsvS?aVIa#L{x?psAXbz}tR4Nc8Enoc{6XOXBB@f)^%hm`$E2#<XWH
ze=g^~-g#-F<RVArhqK;T*tT0+$y%KkV3OOyzb<ky^UV*?w6LMN;N1SXabYsCe6r~r
zjDF_)?@D`^uiiWv5?C<J=cpv#p_Ni4S+&2#6sJAxS)ubpd(P_2<-eKK`yWfDb}+mu
ztU7l0UWI|<mdRS_GfoygRDatx)1XW`$$HoHE&h2owal#imLHeD>c8HKW3H9m{3Ta>
zpUn<@G%4B5tjo!9T8EqA8RmO&=?jE5x^42e|GLppe)lTS9;;=y*-cO0d9&xMitOCG
z&wa%i1%wy{zVO{r%g)X?@I~43l+0OUaK4t<#IGSL7ps-K_0uY^tQ&vwau+aZtYFf}
zP{`Tmd2+TUr`(loCvQ1FS(*VV8d4N<ME1=PtmaL&V=h0qu~K0}u!%?rqll5fi}<=9
z%lB04{5|im*I0>HLDHzTWo>hA{5q$PWp}pvI6r7hk>bo|;M~Qwb*h@G^SR`gX-_mC
zwryW{Xamo|3CRMQzB1?UD(#<FB6E6Eyy6E_lWB^VBQK~wsQkBh7VlK6hZb%>VipD*
zkKDBWfy}Q(d4XLs;zQ@nJfX59PHy@AUz3{`G3%-_DD^+MbxY=jySusb(@3iW&0+_)
zKDQE>*q7D@%BCE#O~C>s3Y+BT^2|-+2$lN8v5vX(a{KYclNWB_5lnDweqbeKJt0kI
zE{|*mhoFEZ%k?A28hhS8NP(0P0x`ud?33;<p1hEmSCNUS|G}(W>%AQo7Lryxrxbk5
zIp2kLGatQi(c)rbTLAm3xPyCt6lXd94pI~eQ54xEaPI5o%drjHc`ouuvs{?BEGgz}
z5Bq*+>&L!+_jidzN`#qbP5A5if7<2a#`||R+n;;9{0xiXo?dmfe>;vD%xRu*`@{lm
zRqxgJ+S-g#w74wT{~TI!;IKn)w9Lekqc<wl5-0jK?Q7((-E#3#vLt_c_!?f;)D<Bj
z+jzZXbeA64b<$@7YqE24qG*ESZH3=PyuFiV-C$d`8Jxi#Z!b7v;rH12%<6q@ZHKgE
zS!<b3HKjy)Wz9ar7HME+A{M4N?UhVP<+n@Qb4~J2UkQ+OSZp{UdV<p@Up2jLHqW%y
zTS%Q(ab7%mL3lux%-?=J_X!od64F-~=r|iZ5MjyEeC$4b+OZuQlF~CY)-Y*2;s5Y%
z!Kc|jIls;b*!Uzh!@~JH>zwBM#W#-ybjFKXJ>at}xGWyaBimjo(7vZJ+d8_`uw;QM
zi$ex~%<ng=y1`-pO75WMH{D1HEA~|(d`4{R9v@rPy6^&z=px7X2Sy*(-4ci7Q`U8w
zXBO2je8eMrz%l;8Ebeu?#I?>}P?R%aTbKEDQ8T!pXDogYwqVUqanNpCzwhjMrS~Rv
zGG?^-EmnN}AWlbrri9g*0L2@Xhgy@8VtV<$w)Cq%aLv-~?OMHc!`J7NWzJtLp8i(N
z;$ENXnPMTH5|ei#k3Tmos$#WuJNfYER*$%z-?jH9rlqb>(75DyKr^AgkcHJMQ<C#V
zHka52BNI@{FyKnkE3)@6W?Och$KvkE3my?mCoS-Hcs{YuMfrsU>pfx4((^8kiBtQW
z)EG^d2F73d`6`0p`@Bgjt<|_VyBIhlSZq#~%V_z2dtB?EbM>uIZ%e2a=Pwq`pBvA6
zE?Sd!<HY)x2X{3uT)4r@{biWr+}#^g_6aE~R{3tac1Ea`Nu`6yrs;{Z)aHO>Zcnwq
zeaq%BA9rb%G?HbDW$NP&J@+D2e&ThOy1T~%5+m9YPN+Qaz4@wR)7AcMpX2x#*YNPB
zohXsm#=a*fM8x7ipQp%gF5xH183xYV_=;b6?^0EKP#akOBr*FzQLN04r|QDatf0Mu
z*A8r*YI&j2Z(S$XmKFvM+otUKr3x~#zMx#E7*NW!?&0}N#lJ7oUVw`sp_n!ScDAF7
zXM&?kaq<HrE^FKE7EzK~Jf|6WBw4P99BcgZCLv{oi8EWq1-Tt6EqqIMx=TAh2el!;
z9Z+3gwjj!4hJ+T+X#t)Y%-0_sd8vB+;-P@dHl7P1<qzT>TJFuU{h<oV!aR}e*R5_g
z?)tCm0@`o-eWqB~#E&TzE7ZgME@f~?^`EU?)9AgR9Te$7Q!|_A-unDv((ij(7q0I}
z?m4f_Q@|TFL1cX{OU|SNC;H3|T)U9i=GUtDc!5yzmFz3OpPpH7Ti398;l>SI8%tg{
zG~1Z-TP41HemA@{-`O>BY9G@*#<@FsismXgtY5x1ym9-&g$uYAEU0#<d|6Qu@uIEQ
zc;B{<PT$%<MLQc$%cj)8!1dY2(u_g}8nt?x|1_^XY5eGnex<zp&F}Ls$4+tQnesy7
zh3u2s-S@98HQaCZk@;I&lTnBjmn8e_^_ll=QkEQgAIsY~dC`UqTpJeT2WV`abG7Bn
z?8^80oO^h|Tc>}p86Gp5v~WiB1kS(fW6c{UE&^@!W4x^JORi;_lZ5ehzS%QgJ!|ta
zPKjS&`Nj0^EFr=D8aBcU(+hT*@!k18dG|tLT~#He%MWf{lX>B$ZVze*F|=F*m&cR)
zzP0gzR@%I2_LeA7*dw3IH#ePwkzbNy`o|+Lou6EM5|G&D)2{gcft8ZA>S2p087;2U
zB_c+A>wfkyN8Y;lFd(Ci>*9ps0$;AV^WMt6<&{l;!N6C^e*Md>m!XF*KD<yE!CrX6
zZpSrEzAN$WlbzY4oETcz4lR9BykLecxDr>A+a$W~>1OA72QI!0Xq?8!G+!;*W|xeA
zUPoQpQ=O@7mwV4&`o7ke$G&m-+uq}MWwef^ocQiNZQ|=f_DCj{OLtpd)yhQ+U+mY}
zl>6zQp6cEA7a}8;ZJsbU;DuX{>FM0ZE%{HhK0ggQ@By4{4g@Y(aINjAf8y5glR?i`
z?`n9y@DR^TKIdsp&uS<CSa;QLZAQqv-@DIGc)Jj^!?$7m1aFzQyN*pUyZJbApEutQ
zIjz$ZR_ff1`CzoY``m_;(YfEhe_Xk(oyk#1v?+%*OD9q->61*h-M0Og1#W0_adruC
z&fscP+VdvISzdnr&3Jy!9Dd%`P%Ew|uC;wj-BwmtmVB-{uT~UcA~uat%t)l@Ywn$8
zF1Cd^cQ@|eDl$`!>vRC4*e2mcYj*q8dB;ubI2V3E>9ljQq|sc~S{AE=Kcepx-FWig
zpI2-~rG|y~H`Y5>T`aWkE)p@^zskmV;lzS{Hhgz}Z9cw;2~;7=KLl0CZtC5xk0Y&)
zINKds`WRFp*R`M9++xLV$$4Gi#g_|pTdYH*ra4L#2(NSQyv%-L@xz6Wd1Mc~tUHuy
zQ>L)LB2vzZb0q_(73cJlV~s3tGb&bCc(WIr@Z6Es!uMpC`*BER?{~;_ciDmhiz+#*
z3j$6Gn}pVF?P5;7aq;to#%Tf!6Q>sF{+SbZNzRrZRJXAIZOs;aJHfob$QCq`e`a~4
zbbsIR$;ON3M_O`kzYzDjqUL)+(`38+P#*qA$2KZmx_&Fur{NIy;U79F4Cak)9Y#`x
z{?St151D!eRh1+cNm|Wqd&6?-!=Dv~*2`6uk1t~k74vyDt)0s_g@Nr&i_gTeSq(d<
z2d+}dN@#luiT*k#zCG71PCHGLeU-F!qq+*SfiqjeuJsO*p%R=4vgg(J@fPno!C89R
z+1XLli7{XCx=|jR>E|16r(a5&7B64|_p@R+zAzv6^2suPy!GD3t#VS67(v^nQ}jzB
z74NK+kzC5YbrFv%Lu;xQR~5Hvzs$Tz$(bJ;xt8;}Xt8IP@NE)(k)OO$*Hm_XyLYVF
zE_aV*n|VYN82uGXG<#OEy;5fToy#qIiUD-qKo#eg-|nW7D;+<s|2`${$}UIQM>7wl
z&U22xqN~ODvHOs*U?k`C?8gUs?JMQ9&R<fL`y!;5d$!T9#K^W}(NY(e2kJ4u)?RMD
zcrqn0v(0b0qxD0XzcL*!+%G#XjkKEECe!+w<I#Z&6(+VOa}=E|QnX^)la@c1aDVR%
z+6l`%?~v)r!m4#;U+hXiTWg<a#B6qEzjSZ$cW`sS$^GH1OzQv_nZ5k78JvOwm0Z_%
z9c`TS=0)ub2XBss3xPYr8u>zYxc>%~1S~CfhqtaOJE37QQ{L)wh|{ynHhrr<e@y6W
zn0(KFg4I_o%Y)l~{;O!3JnvWPq-4u3?x2j87m}~$SuAsS&XBFR)#A_Tc{?mWE1sXo
zvXbHSgqJ!AI!j*t_E=xN;7Y=oFK0`fttP$Hab}G;5biPa6I0*bwI9P`9`~gFNlB<(
zq2s)4bHjRvEd7I8M@{1N<TEXD{U81i_-8t8;ibqEkqi1yE%|)wxptJYDhsca5Cdp$
zaRm1l=F1r$Os|@3-~73@+DoMGTRYofBNpaoOj{?{+UlIYC%+{?Du{8KVsPYv_!A3z
z%g!I2{AS<7+DocdtXUyk24YFmjy^uRTuZ-b{ah=#fRzes7!{sqvFLMuSb1p9>X@X@
zi*1u1Kb8d9RmJt?_3^yTd*<KExEYdM)Y9y9U~|cY<<?w@+Ma5Am+SGn+VZj;Ennhn
zvF10^xr6UtUYpYK!}Vb+hivQVtA#J#&40tsuyu(9*W6a`*~JUo=kf^5&CnDSyup3l
z@6DGRC7WVGK#_MhZpSgF<ww3PW?i&+gO96Y@<XdB7PTcdzvQLPPGXe$B)V?#M&`<6
z7yk!TPUHJHVST~b92t*WeS96@CVXvc_PiGkY&9hgB@0wt9G+;$OwL;#F6_?i@;uV%
zfb+UTTk8rJ7+C+32PeWJ5xu1gm`&eZ{ClBtn!twzR|_;(%YNeWJJ;@I(%Mil_x#5v
zHFwSkzAfpRcYVsQkK1*={rs!4y!gnpC#~ML!2;5&i;5P6<w+=%_k68vxY)~@wXrls
zbM8OWQ-b$x^N;hTaI~dzu&rTz_thx9Qz=^ZxYIhpQvzo%y)?NS^I&S-V!vnG_w}CK
zClbFm=fS#L@>-xXHzK&F2prki9DaJr{vO@mSy?L;B^yA;L0n_X+@|KOzI03W(mvHc
z2mS;Ew)r?K#w%X>E9L63R+YC}ZHwOTnar=99VL|-n4U4+l?uGL!cNNfv#pY#LgG}v
zptr3DzVgf8sF8chwttDzOQE?<CRVIBxE8WkKCN9Cuf?Z5_iDIGa9|t9f`-KcQd4(7
z4qFn^Wx<vEx_G(o)t{gS(ZvZ11+pgJkG80nHvMyh-^5Xo2~=~oIjz{)m*>g+Rz_h_
zeu?V>0Y=}4Ru>Mge<ilG<7ep8&d#?juSJVi2=4fNHe}&85yy$E3v#RYO4ly_%Q#`0
zkkZ8c1#i#uxvW~u&eSnYNU(JJLm}z8a&Paub@UxFl4X6<diutr0|}J{j-Z}~n334J
z<ju^I$1gGkR!-yluwZ?`xk4F_yM6!K`!=^&@y+DA9&@o#<;RP<3=8kJf&;-j)b8?y
z2(v@V3Fm3x=r^*ilDE1bq@++FvTo}F=F)c;|6Bm4rKbhDYh^!h``u%Ai1O;GnQ`Ug
zn?{>T)mJm8ZvLQ`@%Ui!@_GA~9^X92&#CD`>c)#RR9^%yxR}_yNxet+g29P24&A)u
z&;))@sY%a$r=GsdYi%aTn|?~b@4J-K-AgOp-VS@M@uW8Ys`?6N3+MKN1NjS{Y*4YB
zwl_kl&O6cB$Ypbh6>kLJ98Nx|)Y{EUv=pW1b(}IvvGU$3<J2iE8YNn<7wEHMm&fyj
z-gAs?&L>iJW-SZ5x2!8qDufZ#7vA+&;F6klN!H53J<F^wY=~zLc&Vau$#d6x0U`b`
zk4x5`zrLYdezzWzg3cw!14SGgPtW#U!TxKa&gbAlu6z&nj5eN&6COGw)}NkqYPrF;
z(C@n6eYuhodS5sMb2MBi=<s>aT-u#%&U0_QvWt$3LvTmKiCm88yyl3-d+r~(d~<P$
zYfA452k#%O3!3Av>Us%&UVVyN*pm0U_LBf*i=Rpipy}UTyw|rq5BOg6Ja3Uxu4a?c
z<A=9a%5p`ym$NANsye+AJ7Vf*W&2M)M#$l?m4h?ik<tT&zZ9xUyh=c0JWm{A+H%=9
zO<Wwf=(CREgO_|qOn(<<d6j?h3=s=c6x$@Pr}-q~wO3qCiD$_?%`25BYImePTD&T}
zt7ozQqE9-qj}*T@jJjqKvPHI5Xl@3VqTo&b>s}WZI{iqQ#sHd$&hVY{I=?-qb#gS*
zgl!@U^3R%VtX2E_PJOPNTKpp}OOE?M^@+LR5AOOES+Vceus*qdQNo?WCk}Xh30l5l
z+ezkQzibXMC?C3fv?KXO0)Nh*!_Uu7pR!O$$ye1$$-c>bjaAztx5#TA@|EH*vu>(2
zWM~NnZda}0w>$aHNB4)sbI)jlJ;HO-Ukdn}YiO*_{j_SCTl1$IZDs*2D;!u8Bia*o
zxj&5NopjA?S9#H?zqMTl+ygVG@mwfbe8~LN%Hw&?rMHizgzqwU6bicPaWS&ZC!KL~
zQ<RXY=03iu>pUiLPnw<bW7q6Omvkf-y{v0}uKq?j|KZm;i|5@f(tWCV)K=w+73k!N
zP1-d}Q?fn;O{g`iz1=l^H$#u8YzCL0zzxxPuU=Vg`?m7RyW`b!SNJ^*64esCDB`4K
zpkwp(nBlcgqBq=@e@(u8iD{|;XeYCz*uJ0!>FpD;R_`p&T@d2Um6fobVadurOqU+!
zzZTm%;aBR*nOwZxw^NH&nC|%Odv)VBvE+%_h1qR<rQ0T-Y}x?gHWt2p%ICUi^5v!#
z+r$DVPA%kJz}GAAPUKbSl9eqU57O_nsj{=(UHq8|RE9LJFO+>Tciv%{z2XNpw=}fR
z>5abi#KEoNOF{`~H^bdKJ5(3?`EKY}<9Pt81+E>_U0%K-$?}(h)g>V*kCfb)*DB?D
zXBtGCL3S<NU8wDNe8OVUTk6Ja0lAvXUOhX$cF*&}UB!i)k_9dWNuBt;MC5E=<)_>$
z#rE^n1GpFL|97jmWMljD%QEK<HAVc=TM%I^zvJWSM_OX`2XY!2FYERn*jsoy_|7(8
zIqsixs;l?4=Wk>*J1Q2j)!yT@<gIm2U9*z3Q>E5hUy+LN&Q2^fZaHGJ=gp&CrYmhV
z)=t=azTpPL>?Gzjvy>a-#pZuscB5kJ!yR(bFWS~8Ic&VrvdYi%!JEt5W2K`fHDx{i
z&RMd;bi=f3hqCs0F4&~JH(&RCtE%0BYr@l{0(49lu4;CQ@_KgpN|;opTk`EwZ?>+w
z)DRWLakX~J2j;)Z`MZOp9!6Z@Diz4kPz)#y^f)ek=It(-C%V=1@^cQ)<9CR%;$A7O
z`LKP<Tl39sUT=?0I5OMs2d_8p8db9myJkCG^4eG|&i?C&fO_3)j%!Y<G)-6RnlE&$
z+xoWm>!;20f~@S*rZE^kn{`XSXztgwcURp>sPF%Ei0#^`$F9XIdUsr&+m;iZx3Tf)
zrwdN9Z~ECcI&Qnl7P&o2&biS!@cn{g3EtVwrI(+I70613@_BJ*uM!li(Dy$)(|PeW
zYo5JUSAwDft~OSl5tZ@kzGJwPF~U15snqzHp<=PY?~-;Ap~bped&B0=JbvbS<&<Z;
zoj36voOXjrx%t_~V-oTK-m9ALG|euOUKefJ&w96GWfW_5Ky*fM?xM!*&k^?h{43fH
zI_4eB-O0&*@7&^eL%RjHjM#UwZhva_$Lyke@w|C5S|#6>3-A1DEbI3~u5Q^!?fb9N
zpUmP?Sh)DH+^s1Wm)y(hi3?ITDJi|PS6=$=58Y!=R819}vya=d_$lY@yE<Wy3R_Cf
zhaK$;vo20P^gz^<!Flp=+a;{4w~0K`%PiF^tGZ*$9=&y$Lb>Of;>L%M<%I5<7IPVj
zPq7N#UUO$}2ZQO6XwYs}#)Y?ykKBJ5;P_!u1iSKKccW?VH?2@8b?jPk;=Saf_a-Y1
zDqMRGTzD(_>iyT1234MaO}7~D`zhX|<?~<f=S)7?`OCGp=Y>jsP_=APzWsdVM!nsk
zY*ntk7utS)7LeYT5Gnb^)OOKpvkT5Laa-0JT$#qCQPMc?nAP?dF^M0VB$_sIf0^L7
zBlS1e=Ic+aZW}bsGcw<vli>Jmmej_L!e6Fn><$&?21^w*&EuN<al5H7_o3-mB>MI)
zXpahr`Y@?K^}_Wp9ermPDE_Zg=e~UX$%MYUix&Q`(?5M+{Y%4tR?c23+``*?inY~?
z{DV)<^DDKRyv>VWTRzcSN_JVb<2$?j3;UPxCh0b;(@+dCZM;*Pw5<N@=@!sNF^N^T
z?cdpb{c8GI)LXICm3zgi&yVvacf}WXP2~INqxfiLUjOd%m+O2lw|P0l2q-N|`?BNq
zlkeB>lrM3%3GS#^b^5SVuB?0r(;{6Lm%H~Ry;2S3LzJF02`PrAw@-c5WT)Zk6Wuv;
z*Gl6pw^rG$X}uw;d*oH!xeHm@zc+{_g>Mm9ecNJ9X!wsr-6MJ#`&&wXSnp0XRjF_P
z;l+0E>|xg89kn|?`?6_kf!6a%nDh5uez>n9AQ^O$MCs>eihLFlpZSt_;sld7<lVPv
ziEeM3+ALNK+6_Brc01$QgNeV_f^A&Ych)wxKts7oTk-NVr)BRh*{CG(J)4!UyGYN&
zF!XEM9o?g)2Ho|Vip7pxGfwmtet&iFpwdePw>zS`&t9qZ><&*qx7h28LK}$B^#17G
z?gxT1zEu5RaO{QX*2ZJUdUhpTxRCT=l2lW^@GO^48RE9q-luMPzqR@Pc6Huz%lWSN
zH%fEJJ1%2rn(%wk`|G?*1+u&qMP}*0+IKgAb0&At5teV=yK2palon{ZI6T<5Vs-^H
z=!ByV=6l_n=9*7ZoTGWA@IYDM_AhK!vS}*?cz){MI(E;ay<(Zb$A-&`-hAjyX-Ip?
zz`INPmD>G)mCU)aEK1?7_n%3730@9MQY#AivUlG?@K!h{eb@URrM(nO9DlK{I2?at
zZI|Nr*SEOEf2$|F&eu8iK-7@U`8P`rL*G$}Jql(AF4$i*XF48rCRV^%?~DHy+k*=Q
zlyWtll-|4Cm6Xw91XXpLe7~GMI8jK@S5d|3yvuD>87{?3)09*UyuZvnG*O7bSC+-8
z-{ropj2Gza77Y{kFSds_iY19}5$Ns}+>mb}=KQWpthh0m$&BAUh{trP*q21B{%4PD
ze%k($dvmMv-TIl;78ifoOfSFx^ZM%d3qDQUs=%m|F(Kxj+KcbgIh_=hZh5(|{5$cL
zwYRR`URj7~-b!bilnF8Ml`o%5>w^>U1I6|yzqkVT?{^g8WITUGabDh}nES_HeZRi(
zl@W_^3P+pHq}R7||NbkAR&jCg=4d>ix^tiIjq}r4nI#v2jsTRI^jdrR-aUnp;*66P
zUh+I4vUA_|TkqGeb#szUKPAAoOY!>j#@~Nq9|Uwx*e0a7P_(G_yw&twpJtUp68;6Y
zoqLYm+kY>KAG8*3KTGKk?%kn=PwHZ;pE@x=sah+OBl@nSnDK^~bi$j480jU>vghai
z?mq_#@e;>%w)Yk;_%;o^qcEW*MtNoM@s8;{k8~FHHOrkS4JrCn@LLS*<&1_H_lkC-
z8QVn+b5&EA_@B%&wY1f&;a0pLkfdPZux{oG=gM!<;B8?G{}%ebmt7Hm&+EjNr5&8T
z{n=Na1VsLrrnGGB5uc3em{o!8TzTc|W{19N5)0fYTcr6#_KP83luPV{q*s@1q>e7C
zG%4OPdG&Ki`(&M|bv8$T^6Yt6GI?>d%<@kqv!l${&JsTQ%U~J9<z_t>N#h??w}KuR
zw>)v)ct&z=I;SB2Ou3nQuCu$P7Ef`xazZuR<y{Y#Nh=3OO#d9q#wW?9-yfO>c^O`h
zV=8w$8fn$yypO$CqH@b}w}sn#K5Y(@5?%;8or+26dGqaa5zV3A=MVo}@GMlN*Hx~U
zYfB3U$60<YgHsw0S1q?NtE;<jzQIAR7i_$bfK{TLv(!-`rB55LRb_az7fj=OSR$=b
z##eWx)%@l*y-T{MJz4@H*aA-c>1Zw2NKEXzB>tl^tlesE+9?L!nQ{}`IulD%<CmR`
z+!nGy;De9sBgfs!ZTH-sO^SN&dqzd?2#;pcEw3X-!r0^a^O9B;H9u+&>A$`!Q8h)+
z<N8d#y4dZjT(9VRpAR|wU`L!fyL8L$JK?>%7q!N`D2$0-<b3z+++V$Zpw;nf`@GG|
zHM({N+XT(rCSo}8eqq-fzFyAVJQsCj7bq@%Y{g+|vTxrMhK!d60#dTq4eu^o@>I7q
zAi8V8jaNIKdGRf6h8#Q68h6~3yHw+1owp)r!<>=zx|e@<<VO8{)Ysb4WinNOb8a6r
z-oc6MNpVbfAp5De+d&O;7pKpUqn=nliQTbTeqm7VO2^t+{Ke%dayilkkCqo-k$9~3
z{DJDx^Up2jH%0kpCnbON)tPl}_TEyR+LoI_9M0?5TleqbwKoonydd47^-SSYdI{)|
zj+7daybH=Faz*C3A3PbYn-|d0Fin7I;^#o2r+k|($Gl0N(wUph7_G*U!6hhQDPQ?o
zwI}oN-nNaW3|!??G@PL^JhwmQQO3WiLT4XVU7UJ~(ORt|or{s*Qhv(6XCGh8Fkf`1
zZQc3WUlSY`KlG73p!mI6=(CZY`@Km%GX9#sXDt-?pd<T;kzIwg@cGJFOV0Nfb-cS*
z!?)s=iPo73iV~abqt?p2Sz+lJ<TrnX<SBu(7Zjzw*c!R+Dm*Uq^@iZfZ4O%{L?GF%
zGT?%AUCg5SZ&G*O6I=cE{0f)o&W;0b7WBCKNo|)o_V?4x=ku6Cm=>)3&2-`6`&W>*
z{nReszR#gWD^z!MYcEa`Kf=+S+vm+)vSPAjeOc<fncIYn7Tzp;cax80-F5*XUsWZh
z-H)ZT=i2e@Y3)dVp}-$4dwt{ag%iJmqMK{sg;zUxUht{v<g2F43Odo^c3joBNQ1XV
zTkujClgc;Cbvu_k-~1ZgH3MYo`NFd=WwoO31#y@zmEfA&m%a5#fa43l*123;mkNOR
zvabTxzU@=p%xAh(qAPYncJKQI?GMlOwVaB*;Pft6@62M$;^KlY#jBn#SbeX1jmzpr
z@r$-|U)0QV>+JX8=Z>vY{CnS2_4d-8hjTbv6t6E1d@T`On)_!;Uw>)WCC*n07eZb+
zWK@MbI<YKisha(omP_d-&fj{DZ7!M6Zqq-@OLAZKXOTB<Rx-&qe9GNeLC2UbW1qXP
zM|9y7_OBa{XRX?MoUfGwbYjj8IaRjG2fof_a@S&RW&Fs4WaNg|6E*z>Vi%~H$({7u
z9=km)WZJ^u$O|7Agl*|%{XX;lpToz0w8~1p3YoFg$>2%F2hMGglX_DhYF;jAC}l{0
zRU%_zV-|lo=Xb76{qk=j&)#I-opCXvjpx#Wn}K_D*i<8ZgdSPUY;<BVY31nH(<hN?
zp8Ly3BF$Z5_fI8IE!}cht$n$jMTh2@+<BV*KD+0(#z^*NYVSW(^5gd|NKyaLY5L=$
zg)$jD?@Gc;mua^89DZ)G-Lc(jrgf>9D5xp0OLqFYw+=6=v=uLfC@pzdHivnc^WlTh
zoHLh+7;U^+DAyt*m3SY#eU)=>-|H3cw$wb;b++*4C^+$WhnfeUN`3y)bDL9Uu)poi
z-uE)V=`X0ta1F@GkNI5D?lpBgX!A&$Q}yF0MavN8eW2Edph&g!^h=i)KDs5FoiaDm
zOHtTb{`#zYj;9aJ<>lbrt#I_laZQ8sb!QeAFP<N38>sIa7wdDs>h;r~F3&$-&_8|o
zrcbo|<(L|ujfqc{Pft@2E3mHWd8GZJ?$hH&^Zb_i^WNRxcojU`aN%`ENta4?PNnOM
z?TH72*KtB(vQkzzO>(;S$zvOX%$(aRmIXX_T)$ZC)b(RA&wSI&QvDZ7R;w_izZBrR
zDf@UL_h+vqb84keMlM~*!o_(0lH$C)N|F1iq0X7LXLy#mWURh1CD1cs>EsDF9VOSw
zSHD@ZuUGuZg{>cWL1%9&N^GzSS{iSaQsekcGhLO9N3u8VgaEIUY>3bjoxJP?FRblT
zqm8sKh$ty+v9f6BDL!f@R~qouqco+>iDgTRKu2%iwUj{J{nh1v7JpEy3Fv58CcwDy
z;KRK>|M>T8Y08&;-d;SPBj==sNAyqDC5P`{)6Ek6`udWw=x^!itDgh}7c7rn1v-Tw
zsr~UKCfQdhkn;Jc-0`LP)*}1Bc~YP&w$J-QNkTxu@(=5jd{teXmOr);vNSlguXO@w
zB)CF$dg0xLHAnaAO7ga)a<tj@Ww$*E`1F06(z3NJJ{g5EL4NH)ueJ*r`D!L5H9wwo
z!a8Kdo~ay}T8cuqq_4j^vGCV>T~I50#)aEE#OCsaTzwZI_u9j|bK;HnJH$ToNs7M9
zv0ec>e9i7$d8JvR+*_%yPhM4OupIfgXwt5wxv$SZx15`Hx^nV1*S|#-cMg6JViK{N
z<io0@*qzM1v$uKbB6j6u4k6hIqKhB-EbMCj=eB;&ON-MQ=@RF=f9O^-zABle>TL2L
zuOQ4)JoNaa&mMA78*L<b(@vI16q!l=zoDRf(oBv&g=_yl1=$6XMlQ|o+|Ew9(^q_T
zQXBW2$_EWrM>e-~u<P)>T2>gPZ`hr6dxJ3(=-A*1haClOzEoVQmK>=klQNO-0*~Y(
z$9m<jk*9MW%RRk*I&>oM;!8RU{hZIaae3Zba-@FMV)2x$U#wiAvsN;h<YZ5ga+hD4
zt-Stp=N$1g4RGV{!WE9KJ+|r0z1x*9v~Kj*69Ko#Q_?T&WD!}hw%_2b_r2$u3g2Cs
zqYkZSko~hN&$nwveAv91H;(U!QEZoLw7%yf3py9<x5RYth~Dx%@Q9w2-?63P)*@Ty
z*he0h0@cT5#(f7bEu45@uF@{AElaforKP4HJl;6*s_b!(*7TDK{J$liZ@klJ^HjIR
z#hbJ9!kHav?tDw?@>QK?d9}2}9W%XKqA<HoTkxWglTwM%I>|kkS5Mw9Af&6R;w1k#
zNXRne-QKAjnc9p()e_UCE;n-h(sgkO?(Dd5bw}7+zMq2m;Ijp4<{bN!v)M+<=+()o
zpIhW>KDqvyR@8S`^Tp-F$@6Yh&(#0-HFS;F-GZG?XZ)Ev-o@w4WjYpdKH7Zdd>Q7_
zqdX}Mtsyg7-*oFP6=Bm8%;(AevRZ!j|Bd@sT6nh?95|p5!(kM-ZTZHVIj>Upc{1G4
z(E^R6nHWUf?$WW;zb9_Uo{@3_+y-Er*cn*;xm4s%^jahHrGY`WC-Obykv*g+y*OuI
z<;>55e=3%oyM3}0GCF+W#EIyY$;a2-s0?~y;ZeTH0W{Xma%C^iujTWjz4*f(d{=xe
zbmXAc)aF0kE-PO~Fi4x}J8S!Q&2MEbh?<u<jqBou%E0J}v!*RNb|cs<OzMZvY|s=t
zN6RzUC3B|edv=H{J$^HrkN1_pd68E(hqrTlDw)&PEA=#%{R?kVs~3YwX*{FVkJ!75
z#Dezg*aq`ne^fM4CWGx=iFN6UwXOjfQ8Cf;o&TPm`>XTVmZ=??H^ipLy$!fhbev&{
zv#(|w)B8sfnscofb|mXukBnHpc|&@kY@v*l_uWjN8ns(iE=T4aP5n`(U|*@Ncqzz9
z#Y|VvbE325eQ(Z*(}a|GZ$FxpX*I=bKd2+2C}Jgko#oy_uBS^|Ksouut{u}{`9f;*
zRb8UII$W+D-Fm5HL026o_}sY-#(7J3JEt9q=A7AfCBg1YVCAQ9xmby}d-#_xu-{_0
zD<+Lu-+tc1nx<QBo6oJSIC(o~{nN&z+PK9I%+2+2GSNqiJmN|sOJ=MLPCT*a#tkh|
z?S}ioKXcEfT+E1Q&AhPdMvZ53^W-;|3-qSxh>50ih02)dRlT@fQ5d-@vS_Ypv+Kb~
zqn74#uH7Zy+ZMXX&rg2Wba2rp9mNNZkDIz$wRY=$<d(m#E7l7-99~MIr2E(`p?kH(
zUv8Q<yFQI{Iuh*LGiTD714|s#6Uz@~T=WQN@wl+pLzT17>)@Nz%S%P)gJO{7$T!x~
z){XI%9X5Y|-ClKm5tFVW3)AnWuB%2)^1RBmB2C_Q-CdhYIM{2s>om`D9RBiAYPC$9
zQB=sXwSTxSOWwa;doUw#=lzAHCr%cv(A|-`+%+B4u)211EAOt<)voQgf>=y#dc5zK
zoet~fGhHgsHK)h>L`n9%?!LoTJ%{y<RdN)ap4NTNWNAm{4T<T7cXem$X<ZI+T9%qT
zCs=j+t6ku|MQy!>Cmrr?db!BRS2ZO``SGOdyHhW_y3Pt}FqzZiz4pnqSaH@&ZbhL8
z$?Kmk>)zJWx;WvL%jt&};h*!)76leA<9VnT94fN?Y1+w*<ss)cY`r-1QucJ&l&lLI
z<CdgPyYckw)?zQgZRP7kUVm;_R3TZi#AW8n`7dYnf2=%rCg`o0Y>TVZ2?Im3dq2Iy
zqAqWoxNLv8%gVIwbBC>(m+zK{Uh<|iC*+0ZVaelh#q6c)U0WrM7@Ec0mb;`)J|3|0
z<ewSeS7|)hx&pMy=fvTRo##Uu{eOpKlKYU>IM=k|gNhgMwSZr(FV<3wE7`_{k%
zS%H<)1U^jY57ao;Z+Btu^p}S3mj>>-2woE7DBj$)RzsD^|Crpw_j}E_e&|YproT-L
zh2F0-<2&}zDWpC|o8gU^Xa=XCz%7X{8?E#>Q?Jz8T()0xh@q?-+^zHNxt5ynS>&77
z)YV_29x&;MPtD*o6ud2N64rCvVPEj~vqfL_KIATn30a~0SLn(^{WoGqC;XPZWh`DT
zaoziAz~qAE(W{elb&pAz9owmEb>;q@jrSQqyT#t5#r)psyztCir%7B}mvUrTNKNN>
zbwT1`-@&+c(0;LL$0}2b67G~97YtF4@^Ufx)AKpueSp^IFr_6cT|C~T#avQvzjS!I
zkf5%jid5P$RrOMhm*9?=lg1Wfy_x%%ThDlNG`0yaZ=7AYa-Pg8-us||I4hBAspnN!
zUQYey&6e4g+?;XYoyGNUd=;Ykprid+YUUjMl(Nrerpc|&tCPP>Q(4z`;BvCh>cycm
zOSP)6?ECiXpx+tMq}sUl6>RLXr&D>#CjOItFL!Ud-=Vhi#;1cabxz;Aq2a3|)O}j*
zebr6##g}{~=C+rz@&A;LzSFelV0QM;O|phtYE2esvN*gb*x>%IJ7&_(hxfBzn>;xJ
zj`9nSGfYqI{1Gdctlai}Udf4`z{Y6;j1$iXMoX+tbefm_?zvh0fsR1X<_5+3W~q?d
zDr<eW`gt$3S4&$S@_{ooLx9Uly7IMMXJ~9n+Rtj^<b;DOY`i%tE?hq$;&;sPJpaPu
zHA@c9n|Gk;V#6{%ritqv#Z&I6?Q;LJS^u^qGq)QksE;gjdt_>rY_oFqm5BGf853C-
z3+1XRI2kMdv@u)wbxPp%jp}y`r^i3ppWzYxLv=}W{B_s}SG44G?WYOV1<P-*N)|uD
zkX<1;z3fFmdhv3*#h@XRB<;tyj>>W+zmw=MS*3Y2<V||aq2<oZN1{6yZWD7@xVTVu
znv6uz-NHX1oznz_7A`K7d^UI5-W|zOiyrGN?K<ps%rw48L$by@bb)5GLrzM}XaDw~
zH{f=6i&WS#)y?HADnJ_#rzB|<n7lKc>>T<KG#V4q9(C;4PO;Jj7wWhbFPh{F2wKS<
ze{@fA_oKDWHn(?Qtn3$#o_A-u`|9UE_q?*y;CqujH>=j-_)`%}QOT*>t)4C4A9p#m
z!Z5w#V<Ai6Ti$u%p~v6UE!v{jAO2)%`i+klGp6}1j=bjf_$*iZ1gjY_O@Bj+c5yEL
zyy4sf#q{Q1Q`S8D9DOsT`PO&uUkhF@7W7qAa>`%)T;=q`n)jj0iuT1fbmU0Lg0^GK
zlIh*_NyY2D@CA3B+xPW4=YWNSwpwdF?N7dKf2!!^ua2zx=;hCjztC9Hr17FOq)T(r
z6U{$H!f(F53Vw3xg-3AbgcI*HME<%zUM`d~`{%)$#X1{OOXeuLSY(twxz#MPS9<IE
zi4}YAUE$7^>;>&MiITOvVj?AU^y9YmlWxQ}_T)%T&EQfLw2<vQ#%Gy*%k1WdCtr&)
z6HdLbaptJJ@IWC>H(6&%aZBaQxc6_{mi2ILof_X{^;mj$sHs|g`wyo!z2i@lEH9|s
zd3lX##md%zjG{ZU7CG-d`*X7H;y_=`WwXqV@0@Kdar%y?+RHnvhEJR}KbCQpl~BFs
z<gsN+N5&7?>kCgVy!d^sYd~=4!d<Tmr9a4?NWWukdJ(i{?#725s)2k@JMwjpfi|Dc
zJFaV4s=;2L4ceNzCb2qZa(%nkob6)CzH1v<pB>-3t!PC}$#ScJ<+q~dW>qRYUv;%{
z(I4Fwm&?x_U7qyKsbyGREzPd@DAMXg^&IxkPp;ZjT7jn8YfkUEvoU{v*+RQ{k1E*m
zv<xrEdp^m2p|t2hgmtfaTYa(OLx24V6V#n%`X}Zt>QVN|U0}G(<?=qp5by34(@dQt
zpI%_=I&pj5Qo~#2D@;Mh>n63g7@Z5-ui8~%a?7XCXX2+|9kT<=ZZIUTUJ`s|fsDyt
z2WEed-7|_V%-e7Sbja?pd!DQ9E>_H|TVS$eTkIW8ku<1!<)wL@(J_xAI~MLa68%wH
zOgbSrr*YxxAmz}ix6ywVe*K~rT&grX%7LAuG1rhyxw*AT;AO`q_J#<j69H)qyqXM7
z<x2zB-1m@tEf#;h{ogdJDNKu29(H-L;mNHZOfGtUwf7E-JoPv#kPJG};X=m3%c)W`
z5AjF$)n308&UsfrIwm-~aO34kmacp%%hxR1?-u7ZBkL~DPS*Gd^`h_2=)a%lpYU<N
zfBi#e?q?5QS>8yy^YWPU4&Ch!rimBlZ{{ltDu0zZVc&x7FD}g7d7PvD&_e5DrXFTj
z*(9w^o_oAGknz|rnJr;f)PXHAvwmwlf6(x*uXz*Kwxwzkw@vwXwlu$-Y`xThW1oWg
zgSPz76ZTrp*sv@466eEhcbcTx&N=UUlhFBLT695l-a%gN=L?+*H)vF!1|7xN#GL$m
zqe{sNwz}22TUH*+c=6fh+I_wqy!jhh&5nvmR5<qgwL6EMbIjYAyY*z<4AU<ULhioN
zd3}X{`NP=;?xp)ne;In(Ui@ft`1##sYqoCbJ*>L)%4W^_HocPuS2i_O1fSF?GOKvX
zR_K<w(hzixWt;4kYM<&fv1qC2{VZLfTcfjj;sTPtbSa0JXa19U+dk`9Q%0v@r7Q2r
zX{uYcN<8^$XuCC6C3T`v^D<uH>mNVP+@o+T<+MoF&Y;;cudWq)BwNWmwK=<Gib0ht
z@5N>MN6I7Km3H6l|CweOIOEc%g~58uK!>p0+R(9LwnwHTbI6;dy#e)E)5My?uQ2qi
zS>*K4;oIF0A%|RVdfflrQo@n`LV?fPMfJOe|J2${)4mwn3#OhI1(e@3i6rT^uLuyC
zI`ig~8NYv4%sIU)2jZb=&MxlTYp2Vd;#PIdkN!}3@*dL{(Vec_c^2J~3SZ>>ezE-e
ze+&Qb7MDD#)6D&F`j_}))~|o>)}M3m2iyJ1rqkvd<}SMJS`sE)^xUms-=SNQYt|>s
zbo-w6ribrMU#-BWaKD5PzT7Xx9A)@sy%YJxP~)0+VB+Kw{u_R>)9++9Fa`v7FWA;t
zA}b^-_xo<)k82mTvwF7OSzP_-VNcHMwe25NP1|OFyJ&l}*sbsPHR&IsdmGJVmsC%B
z+jHsBTJsOyRm}M}J-**M_OR)luK5e?Dj)MROO`iXl1$xV9eT*B)-&(I#>HPkj#(ex
zTk)FrPuIOe()%tq*FVxZ{Gx#AG54Ce47H8FzpP15esj{E`T149!`3&y-(+-Jo+diA
zc&@)|Z|C3Vie9B_%063ua7lFj!xJOus8BXdBiB3i8`J$`ixTeJ?mu=|0CW^ilWu(H
zF%!v|nqogUn#}mrDg{0PT~WNsD|hi}(|Fs>rXS}Te|_8p?si=HGAU@{^*L=)Pxpo_
zTsCdi!dB3@L6Z1N*HwN`9-2Qr_UYLCuvKrWlYZt&fv$3z)_ml<|CXI8H@TL7{ke%J
zr}||?boa&+?u(>nKNVGJ{Pm|oyC`Fy`<fO|4ROJB)tB4PRl9EA*xwnya>@ceCSO&C
zq{l0^+({8CTOfb$+3i)c*0+f{<f^tMZSOdDCr#n0h5elwy;b{ij`Z~E&E37AHRiO6
z*2&W*Oj65l#WWq8?XK?Kb5c9Y!)%UX*Xuy0tOdb+6Q{MsN%80yvaIje&sO#$dv~d2
z3TU={o6myRp~Y_Ah0kZNJv{x1Kwgx?^|Dtz>t6c(^-f>Ef_K|fmRRQI!-*H>E|LVD
zR4YB(ak{{p2Of{_F|#$yiefS4S@4?S`2&r2ea#!$woaAEnqjy7%fW{}C+A+0mEF6j
zE#vgNol7(M(wDxQ5yb>Lb4c3nysm254yJ<TCUNfTS18^xsLZ?Cet79MZ_tTVJZ5L+
zM$dd+5coSR`Ad`3V%^~9VS(0%ohwcoR=ehI;Jy9)S%O8*HJK-DpmaGuJzjI(lt=L|
zS^mb{4L&^KEmPJE>++dt{CE4WJX@Xh^4$rSUlU$(Njyq_(8a;D@$})D*J}8^KR-@w
z-52DneSZ7bH$E?8qI-5;c%IqI#vu9c^b4Vyq&lIb48^O{oK`*jJjFw?C?oTWsQTIb
z%)VI{W?ljvF1_)zv)9Z6Ub$!bkM3*S=MeW{X$a_y$HR{@*Ph8dw6#}!Ys-|!HGRx`
z4MahwKzyjk$~IPCB5gj6E70m$w_+>kRPPHfR+^kTvAa=|Z>dI*{e6|DS_ANasD<s+
zuH!b}XTQmOvr4Ywc4J?QKnADag@THzyOUS<uKK>QsMGu;Pn$K%%4Js;B$Y1@*)_4)
z<k2+qGqS55*P0)Z03Gw5@otJ!c*e1Bz3JLNHkyWXw1G~EKIRnNzWwKnAg;HMqgpO4
zE=hag#<*(jU#_bU^WTIWo$$N#ZEN-oi|gG_6D}7#|Gj#$_z||7MuqF%UV7N~;@n)$
z1L05D?iduWOFZy!!}l=h7p$gk$-&R13T34t<AR#AGI>`ezKA()!ruOFJNOu^p1X6R
zuRTa;`XUC-YP{Odr_HvU(Y6mXzj`d;&67Ju4=!?CP5G~TEFn6lVPk*sYU3Xp;)3^r
z<l7PsAKp2&nD6?!d{Z_34&F_P4`R5}+iRPeAx9+_m95ijJzRIjvF|2#*5tny$32VZ
z&Xd)eyI_7d+i9J8-%h0`%jUeU(c0DN`$#MEg?rzYjV}6(va<vD4~PmfC26-i`AlCP
zrTI<ix8sM?*2dG4R;_IfIecp2ey?CJ!*3fui$C4I@rvko&!>7BhT^v^O>Uh3-qkkg
zl1(8u_qWO5*{Z*DZdu1RDt<LRS(MUcEUK+|d5Y4qhtIBT@{H+;){VROW$*s8Hw)&A
zfQBg#pXrSKwySe*&@l~j-7|ZnX8D7!CNL{GwC!Z-gL4WO?kuS@<k9cV^cEEUZ8>FX
z4%5=prfWR*2Y!v57yLE2bAh9;YFktqAMeB4F^8R4p9yU5wVTds$fn<6cw<BHiUs#S
z$?2;83qK#aTM=@;>NLNT#m70dME(@0|GnY9M*?z4m|5v3vv_acz<tLS@^0Lxc0xhf
z>-eo(`iXNt&b_-zYVv;P8pY_kb6>kG@3`FgX~z7c>rO*--?^==R(CY-?o4I`@ukn5
z(^a#OVdF1i-lufD;P8W;tcmT%Wy+<j7^)m|7x4B!H+o=cv1R{Owi{u|2HPs~B3qk(
zUXJDgALPz=Ubnc|z`eHHu)>k&VB6th?|#`;%=aL3?AyxMiFO=5dM%n~=eBDPq^_M?
zd#-rL8ru`#EWdGU@!FNLTLk!$n)fVdOF8{<=TC9I-zMyqY3o<$etY~z?QCyV*}9UZ
zx^-^Ne)IGHXq@Ui_k5*E+o{qMSA37%F0Wm3&RDkejZbXGwnGaX%iG;nM?Amnxb1JK
z@6PSde^+LCG3;K@8j<t<L)h})(!P^?m_M0FncU3hvkn4Znvn4+gzs<Bmgjcc48BiU
z_eOewaxhmyuI`bf#p?N=BpSXeemwkrv3-P?VA`yp6G!a$T?J3>3-<kdF7J=t!oIB&
zvb+sNqiz3q?)1AdJynfWHR<G~B+$8GPrgk#``gg()3)uKRtC<j6^jbCx;TkxQR=4v
z{tV-3{bCWT=YLh&wp8R%Q;@pUIls!c+1`e+ag$H;f4SWy|CJ|JAZf+JS0AjOrk`2p
zp~?O7^S-y8PhD4nPHUIm=jRm}C1q-Bzb4!3+aeqFEo(HU?pA1vIefKq@9C)3M}qG?
zEm*L6B9Gw{y^Q_GN{?+XJ6&|<pWN5h+@F@$yPqX!7e2S<y`f!nX4{=P+0vyu!gm#)
zzjRYOt2y_E<@Om53OH;|@PgCBymOjN);5=9matX0u4~@7xLER$jMVYFnI>T!+XMu8
zm7mYDv6!Q_GkM+OqTH27kNTa{bu6}!EnU7uXaQ(h%P!07AvYebxi4E>eqig-3E38w
z+nWv_eDrF;u_vq>9nI#<iB5f9pjkaZ`h)0B#^Z74)=nt9U}>>}7hH*`oj<$1;Kp3b
z6TCkr-D$8tS5j57VBQ+7lB%aJdt&F=6fRbNoca85=eg$#H_T6+l$^KeL)y*$st0R3
z6!@#Gwr+T<e@iF-Voceh63_|78&^92pOUUO(`x6Ml*q3O!RL*(Z4{P{ou#OkddBci
zlkn0a@hvmD&&r-!{$#7p%yo|5uhXXRZQaVzHFxf%@0LgRXcqjRB)K#&S94iXdAt6(
zn)ou0)b98Xi%Q-!i6t&P?p*6C$GvoI{^wR5?XoFcpmXrw$kruJ`@;F_@9VfJUB)E>
z=@nLrrktK3uaEsvRrWfnm!WvApk$B!rnDaGmLB)hW>Y{%`0JIF7@fZ}fzR;Sl7#$+
zDY`F0g1cAVICXNb*vjL<o{tUh?qXkBEWRcFvDM?~-KmyopbGw&-np-{K-v1G9rLFq
zsmZ$R&u`huzUzB;WjRB&W9~*>;paj;GJJLHTMx!fOg1YhUYB_N<>J$hofD@CDNmeS
zEPeUTs-G;Nqt$fzpHI`<p+Cc)0dy4k;bS{hQ{Qnv6Lwg?!ca=ua{HI-y0`rsvbznh
zZz#wMZ98mw)sgR_b`o=LgvIrya}T+`EieP6Dl?fm(SP4;NGzC;{H^O&QgZe4tZ<7r
zr)93NRlD-t^xr&d-rVKx-Cnj^>*RhtRx4k0fjz3$?&?z?kvYGvERlO+_%6Fn%534g
z9jv@ZB<=iOIKFXxrL^?qZsqvR47{H`*+KWJNLx-h=dotVp47?hzu#+4zfp4uw4`+7
z)Zi-q&*zS<eUiU?<;ELTmo{#bNSZh`I4gUS@HBx%`*qY=u1)qbY3=CnoioW>W@5{&
z>uS}@_Nrw%U-wME6?Ei?o*z%{w`aRd1K$Zh-1u;bVy>!_lXiR8#!Js-Uq_3)%wEW3
zGS_6;$|F7*PoKCk_rxsT5xDl}+bs*2XZl-RndYRirLgGbrr?xiW$I?X5})!E%>y4o
zoAc<&oM+1pb#8w+QQ&9Xa+X?kaD(p6qbDZi)BS1}|F7q9S)ZDCp@JzSntSDqeG4C0
zJbw}#7W+qH*}c^tHoRYg5#i6yew}4`!{yFTaD-3Neg5nkIKuBNFZtGWD<PTtxfHid
zPYwG<$GCuGqiscbf!7x@K2rc!AIaL!&9+%ubnU*Ju%=o3h(u5AoNT6t35%Ze{p16k
z(SKC$oT+QEfoN^EBB-5v<G{|P2l&!{>FX}J735<&XLfe)!vxb(f#gqJQj>VEKZ`nH
z8L?gNia<`b?uOKxG1+PDzD><{8rGlS-I4ezMwg3y?~LYK4*Dx}zkFs<JDOkhZ5gN_
z-}F>x?Yw>U4^&J0pIgoEimy>xxc}4A2}?e0Jt|SQK(0YsiQ|YKU+-q!p2Jh`pD<jt
z^?O*}jY=j^>6fhBo)`4)vD$Ty?{D{fw*EGcq1>@&$Az<+JJl)!y}wR%QjxEH8`v>N
zT^2M=xZBe3oUgg}@<WMhBx>F=cb-)Tx59o}Rw}zrnf9zw-=qFUj_@phtxG{kDw~Rn
zmgWUMk;=JjQ~5T%>kP;UL7~}}f6Q*p{P%Tj-%jKAw#f^BE&*NR;$*DOE_Hcn(Tb2;
zJ>6UK&v5Tmp9`wte_8zIK3TNt)2s>K_Z`1b5!AU%NN{80<S5V2LM^*a=0&t`7k4`E
zxmZubQ1q91r_!>V3ZLdIf$2{^DA_!*WCT?lId@g$w4NpfuqpiJ+Y|qnU03};tU!I|
z>kre*PG@=i<NMg!<2(B{Yw?E09iL;bo#akx&Y5Ah{o2cd_>$*(tl$HI=g#(4DbRQ#
zyM(RWv3JLfZ97?`+mDHq%SeW-(mfjT=H{JaM(pmn<x<t5@0!GlHf9!ki_4tqz8BTA
zb*lt-?CfZ#X94$qUISNSZ*JZ(ienG{y<MU?cOzrlw6kkh6s)MK$~L@q&1p^QwL4tq
z?A=$I!Kb?BR+w(*x|!(zK;ifs(X9u~a^}odez@Uh5x9J3t)H`gNu|&Ex+#7a&WCz+
z2_3(kn67ttk7niM30{A#`%kL3f45IM{<3kqLX*v#n^Uelm#&sx%H|j|;jiuN8|jxo
zca0t0=F9Urca5%z=KZ+!CP(Eap8_rPij|i8@-&of>am-K)^EQ)i^ws`1l^r>Vav&q
z<4+j5V!MsP&h5E>j$2o4YNocJ@NKgziQA_<4}BpmU%Q`Ga+VJ`=YGrm;Tby1aKdDf
z`ii?I-)4dv{26zaTzfug-XZA&+Z^Yv|9Z@9@+p(06FTS2p0ZuVlf(ajeD&`4`9AJ)
zlTR79TJc+&h1?1<mvt|`x$WcQ`1gz0*(SGbP7!GDmFiN@^;`I?{A$l<vt66pM1sV(
zbacf^Nqv8Q!0+hyJ6v<O%bz_fpu9%cbi;*3owe(pzLL>Be$Z>;my4>FH;ox~Er@Nm
z`cZp#l~~|@oxK6P-p|UG%H)Z?D=IeqGD%`FZ}_uYYO-${-(BeysB-MPcw*+xueIz-
zbF7bQP0iF&6y9yL{lKdO2Ojn@H-PIi*_pQ+o?ck-#xHrbTkHfUEwhxon+?sC{nlyv
zR@bjd#pIm0W2DDE`82qhFOU;qw0+ODgFOFqA%%zgvoITr5S6`KXMh?UZ;r;CHfBG4
zVY^roXtqJ_%vy%B4L8c4cg3o%?=ZZ%DNWC<`Ec7Q$KH$DS<HVeo_ZMf%JHhnGWZ>>
zpRo1C`E<+qEqqmyud8n+P5iR;+coh!i-k}A+2Pp4=JT#nZ`*s5Ywa4FrJOeYRRSHb
z+GR7tC*0L0!YfQeU1pm5+4ZiTs}h$e`>HxQajOMeDM{;@@J-1Kd9v{xziY{15BFJK
z9Y@%FIwCjib-P$4!aec1nwk!zYu51an99P%)8-wY)8;Wf@pJ^&!et`P3z;Vyv06{8
z(yz`f-uoc;um@;jtkukiOVi)E-pA{C^V*9Y%u@wGg-V5Ch`yJvgX)7Dp1NXEdl&LN
z;!!;0D6A%S&)BWc?WOvk59^Xu6>d4XxV-aTvfHG7pMJ=GKJmVF9AQd}G+kT{S9UHm
zU+KA`_N$rLzFcWnS8q@Yx|#co_&%*osvQ2W<oTy-WG^$4)-t?2ZJn{~zg>BO+$-a!
z#jU)Nw=-6=eRk{aJJD13E@{ij*?ni$66d|==T-@Vi|%`;w?4L(xO+#_3q01V^!=$&
zsH}{6nWD-pFPD~er*k(H71-2e3SJ3GTJdnlolgwx!t=oKEYTx7J$l{Kgs7k3?p*W6
zr$whTWPR@4PvQZc+dfNg`=)~jf1Qv$EhC$qtte)#xBbwWg}*M(J>?;rooy&KTX*}Z
z>j$O&LlX)Avow8+7xQ;)R$c_^W=77`F=25pe{s>pNxk02_u1Xe$NX<*aqsax`#AGl
z`pJ!Eo%+!W`FjrEz1(o0_oH!vV@u<O>V<WIDg3RvOEvP9w70&o?qXWb5s<69#Oc3k
zuCBM$rR@<*k93;E<U-?)adOnG+e=IRHXUA3Y|iyM0<s{Kaq_3t_1o^4t=kj)C6TY?
zgu$hS+e92UG8#`3wOqfv?bum^)L)Yy-gN+V?lTS^@w@1E=lhet20MOiI{IAZS&GEU
zfZ(o$7dkt?Se}gLz8d*>pX$9F(`3-y7%Z-3K0G4Auj@>DtG%{|1O-2kc?nu$d!m=~
zcFhED!~5qqFPpUyx^O|wL_Ssj%$3T8mn_1289@u#lvK<THO`$EwGH7tW+kV=^6Pk0
z=8_=sB{RBWB(l6`@5%0CTc$C2?WXg#tZQ0BqJOEbGTyf-IyCuHdB^&coP&4tW;Cxo
zJomjJc(~@b!S!V?6VywV?^^<1Abxg6_WN>;V>^Ra1c7c#m?&M`y@szxE?+Yx%Il2D
zoEf)QJbm!s4>X>Ii%)aQ_%z;w^dZZV@@`IV?tB*Ab8wqPGq3)$X^*XDoZAoTvmZ;y
zIetfrlf8QxG{O9x5xw_WLgp{1L9)fGyJSlk?tv4`jSX3O@0t(mbz57jSyj9C-u%w#
za^CFH-CU;USN$jN_<T{H!@h#6)7SFqPahFOX8!e!<&rm4CidFoU$|iRD9nU|J$L4m
znnxEWFInhSbz5_j`kEG>Xs#JIrg$o*cj}e2KYKIvQn@_yOb@NgVNPmaQk0%nOq!K5
zC81w;yT)4H*>4qJf@5y-L-)&*Hka(;agMB>U#+gd4Q}PN^!c2r+sC@&<ATG!2DwwV
zndpF*5Z##2*|=)DQY43|+dH91IaP=69_qJ(=5oB1;Hv$dQ?$z}xm>l*x$AtyDq&w)
zH794aDbt=vO7OM^>M_*b3vgPd%j)yu#D{f)#p;|=D~><&DpU?>@NzL}ozQV-h67{u
zWY&<@P0BM*AG;|S;sn~!^x_B$*R#;ROE+K5FtggW>KJIIRG`aO!e7zw1k+ZJ<X<zK
z&qNC?t<+plxuiMwZTP`+zwYHl=3m(FUAHh<{aM*vnH;ru6`K`rO_R=eas1A#70$IE
z*Mg6Kzc6_xD`UIUT<caHP;R~UA!VK8wSya<tUU^v07`OyX4YkC5wZX1gxw2{f{Ob~
zEX$ue<*P2cmE>T$W=1sMvxHSY#h70;2?cNDFZL~zJ@fQFq!(Y7m>1g8{PhyF$FFu~
zZBX$BwOY^#=*b%%9*8-e$o~4@cJMZZ>>tMArw=AZADwF}G<A>Cu_w<xUC$qz_{ebO
z^YHT`mygvN{}D*iKfl~^zUrq9^V^k9{E?Oq&WZTJ5GC+JA?2_O*Dcq&wEj$)C$h@&
z`S&;8&9I4Puei{#aDv>^Srw;NS{z*FE$n;<yl}Ad?R1a*;m;1`n^;{7ten0nG6;0>
zXXl&g7e1faq?s&r`v0bU%cT2k;8jH5Rj-7k234+}{iDD#u)HGzypFW=ziL2J)U&9E
zy3ZQV6s~RyUh<en_E6&M)^n06>{Bjj9DY9EKm3@vGo)1c{V3C6UOwZ(mW+92>wirM
zUIJd&_WNkLRO7Sg{_R@U69c#BYUfS#GF{3hYGttR=cLqq)m{tvH!G*<g>Qrm)iJky
zf8DvcVCg^Gd&f>~Uh=dy;({qtL^SutX`dfyMwM0i_$gOToBN9U<>IBsUWk4bzj*G~
zv%JXum-p4}FY+=!t9vMuqy4VrFe7MKW+QKL{tCWt-sP`i81^nOyKtj>Cp#;<^8#yD
zqlUNuaN;<$-kJGqbasL7#)C)u&gAwK7Z}t-#%WGW*{LeXm*(|u?xz=^<u*6^ccy0W
zr7g?{k3UIB8D0N#eWA&J-J{^HNzcx!;(XHr^9`TeiaKL@W=1yS^Mr-Jt|ftPKv^hU
zymo?Y5#v2bLOwgQ`}czh>x(8hz3LJRoWD%K_Lpn_zDY%CPgNTCRZZA$8n^vV$)wAc
zOubKJuD^^}`afUh%~F;n)lX(H9bvTd;g~yj=SS_&8d4gY&MPqLC{G2ihBi=a>775}
z(!p8L62T&mYQD2?>Nc6Tmf0p_Kg;}OE4>tV_lZAVdaWy0bfrf$=Y$Kj3td*8T$WYK
zof>j)ro5~83Ktjej?N1W3y)n<d7iO%Y3`iums}4(whPEg+;`HNRC{TGqQ3az8`~n^
z@iyJ^;%QamxvKfw_=4NX+Y`k44n=f<hKCn&KmK|1&cC$lFFxmFe2zVR!Ti$7Z6ZOu
z;%({W9#Y3|R!{v|CUUKN;n6#yhL4h@+dgf1@cf^}rsvTwKTp-XVSZ^LcNBx^o9Q>U
z>21!cU_EGIwQY*o7KU95S^^FiFMQ{7w_4`hmEgAckWX`-B;Ih<DtG;Dy3Tmt*669p
z-^y2>&pBMMGuEVic8B%-%(;72+H(#U?lcK#|Gmh%R6};pBDaLY1v^_A+neWEv+D8g
zS=5?vxNv8CG`sus?NXD&kId+qJN@>FXAcbC`6U}F=&vx8+^zpz<j}#Amuta;GRMTu
z=!O<+Xx3))erS?vTF74P-7b6T*ZnAutxG3lSr}|DI=pbvtF=eLW9rR2!;1Mr*FYA2
zwu+tE8c=qCvqD?3*s*KIfmu6m@$>!A%2!pI<>a&Hyj0MdMeN?5)*nAd{`nz)d-IRA
zQ~S3*ds_Q&pI>>H@E-r&A2$BZG@b5hH~$%neBE+)xB2x}d;k7yzntxNO5lgtyn6Lt
zp67jkeEqrn^X;bJKSQ@4>9-I1q?EnBYNr1E08xI1*Pr_t9&~mbsowSCaLfXMc^jVy
zZc?gjSaI)ofXTc-JDpi>g}a@PDjy27QEWJ9XtFi9UUE|IxkW6K+)s5qYh3hOBJQ8m
zWrGA`(U6r1Cxw$8KOSL-Yn{ITQ~ZyE<tBFjJ0dRL5m+Vp@ag(5#;MN)d;O%R-C^LC
zuV>1rYv!oAe=KqZOP=U1rGAF!4-6OnwkRt8RD1tzO=Q{o3!?o!tS5z?%eh@9P10Ha
zc~6aUxbv5m$VobhcRo)qKD{aZT6jqKw76gL`mN5}ug2zG;@z^OieV+|zm0z_E^y!3
z85%FS?a@R=tslwx#RdsGyg7C>O>^m22w3s{;K_#^ug^XF)D{_Z*I<E=y;~8xyGprS
zg5LzugUT$Sx7#P4f9Uu}w@OWS<vfq7#9AM58K0WCS?;Hro=jwV^*p)lX~L=>Vz$j;
zF8&Gu+VYcw*o$9Je<rzkQRSf*r5~+3%UAGJYR^+#_Dph7=z;d6;|r7CF0D|y(WKrK
z$1Jbq)XsHtJ2;S=?kr1;IraYet3O4{nonGiQHfuD@L>7gdVzW0gWlAw{kBcE^Y-(L
zH}y;3U4NB#dg_k)DEsfurN6Jvx?P|u$0|{<HfMiK-tA*Yd=munLf?jW=iZ)C5#VrW
z>w>>UGjpqizMq$Fh_?LwRI2*mq>2d%$5zh!8&#VtEjZm@`uV=8o8s546SwJ5=S+*q
zzNvrhI=9-9*hYryLf=*|-TKtwj(y&oe_@;J+<o^ZIN5kk(>V7d>s-*<YQeS_Uc1EB
z#;;#GeN6{D@3K4I*Yv|LbF&?p%;ubT^;NmZrENbyEHF@b9`$v#=$EGV1;6(c{;O{N
zCHwVr*W(W=Mi$$-zFKEJXFdPWF)8rf*O%9`pNpP<=-FcU{nZz1uJqga6_X;SL|6X$
zx~cML-i~aAr*RAGwq|ULX;WupyR+)@`fF#l?f$T&p(Xn4ud7uzw~4)DYBrE_f874y
zhE2t!dvb>kFA9w<Y2<qOyM^KLWi6+*313~s7A(6qeN}>>!b;V(`*tx+y_K+$YZ~K>
zxW`SQqAPx}X@_p$xe#!3wf>3*R?Dd6O|2cvuOCWKW!1WLkV{m@*(5}^Syg05nfvQt
z9aX2MTar5S8dz<k<|J_l3S7OCaFb=-kBhrRyg4UUZS0-q?I6#f>v_=0C**a(7C)vN
z%ms>ER~%(loVm!w`9kKvSM@d_Wyhs`*W41U8Q0lwToT`G^{4gjB8j5?&ehMFF3IV&
z9k|CFSD%z=7^eU0p%KRu&j+UJ5uFoH@HcQPYzS|hJ}V-MxqA)MmLCT<7=Q2*_U_qv
z!r9@q+=i2k;xi+HI9ks!MSV<|Azx70xw19lfyIKYd=~^8PkZsGx+sY=ttmdB#~I_3
z<jE*}Q#hlMxy0{+l90|3mj}@eTX`=8HLiB&QB_%0#ujm{p+{^>3d?H&zMt~1Cb4Dg
zTd-7Vn!ty5!Xk2eXQ&@{i{}1R()Qa={=$z7+sj?gojJTu`Nw09MbUDvrmed$jj{T1
zlI#M;)6Vx#i%J>)`nMyZE#t(;3+9DKukqZF6XzBbm?`&)ZQX^LjM5;5iu;}K?-Z>z
z{?)gmjql@x+Y58<bookdkX)x2l6m6kh40x%`+Bx<>V-K<8ChKEjoK*6{Oy2gixt1L
z%rCyRZNiK5>$5op1+8R$U0c&8%Urg9>l6;ozr3}<VTbz|rSC_1wH!IecBAWRLGpoR
z+o$z^c3pA!{*AS(41Zc5NjEaHIPh-uGI{3hd$wMY=<(&-@OjnK(+lS2`RX1?>Sunl
zGwY{OMt^j0_l6r!E_{zRwUOMib*-waPewsQZy2vPTTVu{rlPQv%q_dsZQ{*ln@pE9
zaGd4cuy@tNqbq)2kFxS`dDgaXz1FwH3(vN;2?=c6$!Hd0I!9td=Gvt#J}HF_b3-<Y
zH=C_F>eb_7*S@b?%Pi%B-PSfCp;CU9ocUb3k{hgbuO;5geRq1Za`E@vFMHGHpa1xw
zN%8O>hWFEsshz!C-Ot17!uZ~~e!fXb#)a%%8wEa2_`Yzzm(*^P2fBA7IvOtgyAZF`
z8!PppEzh~5;Q+(MczNDlsSjCsYn&~fG`!I7JLbk)p}t+w#o;Q;#dt~H9;pv%c?+C0
zUev$P?*_>+gX9wGU##zJbK|Y}Z+1;lrpWF}xJ&Y6wmntS+@S4yuWm2gXuo)W$?Xe_
zGDg;4wmT(fyVXD3wvgH8@Iwau=4~~SACBb)|1w>5IR2*YYQ>+{N7O;#{(3&IH`~6V
z+n1cQwwQk@x0kNtsXDn$)zv2_Z^ioBZEGa{UcEI<NO9s;#<=e}5{AF5w{8>=UbvO<
z-shYj1}{o)O%ri!+|79JLr;yw7opr0%@!HC4dvF-c05&;+Z2xmq~tYhw@TJ#+iP_@
zz)8i#{J`%yyxMGg&2CRp(lE0)Fni8I5zzf9O0${w9G28nycCe6QsQ`F_w0pYLB1;;
zYiDpRjxgqz<Es+fRwTFc)z)7T^UfFA9SwV);ePy)Mnmn|xsNQT#aUikZpdCKXL3x`
zQ_iY&s=>UvOAmsSM4T2aWpT-<3i$OxHLS$1_?TyAgq(NyMBBxX6I7KyPcV$CT)p$O
zXYiVXo6<|b$L~~Mm@#QGk9K1<2X}U_ts{65yURQFR7=Ns3fG-po}CeV!F!?rkBk)f
zL`^9L&C3EhPX3AIYYJaRf0Pzc0vVFh*fU?Bz4%S?{@xo=^0$o@R=crBIkC8?aZD9U
zwKwT)clatZMG<s1^9iQTr751JMSYjlo9?G9Ta$Ms1ANrd-ww^vnMQMKKPG3-3DA&k
zwsJ5|>1d1L*Akia=hKy{{7)sxi(fH9wi%dM{|Gv9(Cci^Ze7)_Td(ngHd5C$zI<>U
zc6xNH-|@FbmN%sCyj-^`B${jGiMKmUo!F~pT7MHiuw}`F&Od$G_sbM=b|$l2>YOGd
zu<>SL=TyF4=64e3Ll>=Nad}a8=a^hO+x6`t3c8AJPP-qQEwY}nWe;f4iJ*wI-1eB0
z3rjxewgv=qExhn?N9sa8)m!<REm1){t$oLJ_m{6|0WYs~()ePNH+8b}QPA?rWg?Cn
zpBJw7lwGy^K4|NkK-LV!>s9w1wGYp|!#OuQ+wgl~)|s=5D~*aSbjqJ|oNl^J=WI(l
zgZ=!+HC^G?bxh6uW@(CDS}=3tr-`Xv0^C34TX!vNc|XlrwqLyY`3z>zMkYalpYp10
zI*q$oxyovKrni@`a0V@DJ@NNMw7wDJ?r&1Zn$*1>Ea_*Q?RHess>S)5`?49gQ&#ED
z4Jv!IAaSSdu@8rLEc~P+`@r$Ja=O=*l)Ky47l(<dO7MdAL2?QTSjsPXoVs`pSLm;=
zkDq`3H>p4KxZ>4|;B~j(9iO^RVlPnrH7#Y6n+9mZf&i1;2KyCS-kT4-nCHYL|HY0`
z5Ol&3(>eF9o69TL<Q$&Fzcu*0i<NBJ3IU#-awnIo9aZ98nQR!>arV6BiCy-KLFdOf
z9&Vof_0EcxBp+$**|*%D_Psp6!oxd5q4Bn3u4mYq627{cp7{rV@s$c>XiabAs}0`1
zg5`)lm%d9z;hlB;&AkWa<}YiDo#3QXVzsXK{6fBGe6p;Ly1Fe&n;&0WE6Wj;uc{Q~
z<iQemT-VP^_uu|hfpm^inQs<(&V9^_Uq*9wEE5o1xW7>PpzNu@dqGFGOqs#?wl_Kr
zyxYlXg(hfE+npl6_D!!KYipgVA5S}D9k6E4)Cr)geP&5t7dp96=z^@5C3xNHEvfCh
zE-yUwOV`yWm~&>^!$Qp$vRkz8oUFO9ahq6T{^SI?*cr1!7tar}J?i#1f1UNxY)QHE
z#dc@KntZk`IdS~3h5Z|@E6h6P&lpp+1h{TWx3+Z)ESVk_zvI$}xoi^ol7<YKnu<ad
zGE0M2Nbv4Hrh8(y{fo<juM|MX9e=X$dNwoDIAFU~SFg{>Ku4<<;}VW`89u4cLDLu~
zyz`OSU3cAu*&LFWpA-Z<+i^ZYFK(L|=M`S37AF>y7J&|(zL?)Nt0E6=J6b3lJ>8s9
zK_8UE8C?9>|NheZ*fMFhl>5hfHT?nY1#Nr}OSUV2{>^wy|NNC#ORJ~N5e`rU9aC6j
zl`&yzDR;=7yi5!3=+C037|vc`l-ghsq@DS$UGkOKvB`~Vb8FvtaKDl0O<N(r`&+s*
zDSqZ{{v`^*QOC~h<OFXYUh%F_Mef&=B_=`bg%`}_<@U5KKFnCrRxtPZ1M$*qFPA@y
zJ~*}PJNEXM#SN}IFXLXtM04-FaBs&}yY{LX)@5Q0TbD?1<@R}>FVo1`nf!;*CzyN2
zffqYkz1ZCtzjr;?;ytavYbmom@%Tc;tFp)3re<&o3f`99UU+Ar%TZZjK3UKaNw=l1
z|2eTx<brIlC7Az9di$Bn3!nVbZ3W$!a^m5RrC<22>gcPwM0vHeupM6;P_#gx2C|FB
z#60im@@Ca<(cGZhd^Y|s)O{;kq{j!kdrsoF#p9<pr&fN;|FSt-ebp2_pZ2}iPE@b3
znfszdj;mv#zvrvRUyqoqdcGq!;upteRSvdXexWuQl~WfgRato*@BLzsm0|$x1$o17
z6*|TI-^Cp}o=$B47FK)6t7FR)fli$XPJfH;d3wD)^83~$i6;}nnH$=K7$-6ZX&tpx
z44V8Y=)UN#xB!j{(1~4)L7#k7KRw%i@kzz*hM#L3%Ck!5sj}FlG+f}#`7A46n!RZ8
z?XFUW^p^~Ll?paG-)AoQUU}}x)49wiRs>eI@qKFGpA>yJZLQ#Tn{S+4d;E4P%N~-n
zYG8KrST;jleaSJ^-ETilt7QDC4nBKLR^V4}oK^0vXWS2LzV_v=3uW!=J!dj?0%z=m
zJ^NQ!U6kL|Q$4k6`N9^^g*YcTPKHeM&U9PpGjVg<rNuio9N2QPbJ_=Om-hW@qOUl;
zn!Yq$%gk}z^pgj#J@ET3Qjlx-BuV|rH9pxl1@Erpmw>JkOX!OEy_0$38QEkZ1t~9=
zmTf0=YphJnb~sPC4%*tZQM*WXqKs7G-NF}F7A_NUTBuzl`$E<$1$0Kik_nu)6SIFk
z38?x3+F!xqk<)pnD5!nXJIH-$Nx@Ghy|NBD11$lfl(q|<I%xHAt!sdHro%?%qSgMg
zI!E|H!>tlMcPGtef3V<ep+NEmU9$uJ!s#O7&o92ecz)g7j^#I8ZyN1y|CsRcrOWfr
zA@jeRJLc8qT$k|vqO9la{k$>Nn}NGZd22y|U}~Oc(dDz#FRofRd9kstYKl|+l1T+^
zMf39QHr3Vj&&zzuuuPNH=gGu?$1``!r|jYgT6DoP+Te`LT+klwnJQD|pTF6>?e>gP
zF^#5>70nLboDBz5HEXj|_w88pTyN9QywHSaD@=5nO&(1Auyn@DD38<_v0d(oDZ3Ax
zzF64C_h5m0&<pj`vvV{S-rvJfT<tsM>K+;J>5Y=At>uXlyZi*xcASk~x723Yx%QG+
zaD%|kb77IwAs*G#Wc|$h+a5hlV+eK!Nwmm$eyrQ~!1QWJDwo&S7|~?#&0Q{fp3mfM
z_<}xbCx5(lW72j9MHMM8j}|^o(`8ED@<E=DPm0L)mWsVQap~gBWuLr#+V`)I7Il7i
zeQUa2iTk?nQw!N1`h6D-@YP+C)coX{5GWDc$Y;2IMJgs^N=)@G=Z|j`j)nwtue_kO
z^H?BzJ6Ac+Ppd0aoHV|8<ta~bZr)(cx6JCw6eW!k?>y)I%sYFn)ikX@o8e5n*Ktl|
ze)%XGycup`c#(IItjD4IUME0}i#d~`pS=&r{X9)+iE4|-VU?ZJLin!rvg<y(m2~2$
z*vYj?r5jA_I~1>9OInvWFUE(FJ+{ADtT@;3ncdl)fjV>DKfBxRESu-{xGg7tYHg*>
z$)7SN-_E|=Uw1x8IX^69;iq$kc72vNlx{w%5qG<_?N<AgW7EFXy!Z2U1I>Q9+IhZJ
zJomBC+p|keXv@awA|(?`mMm@Ycri7^>UPaX&DIY_XKcOnQp#;!yapes_F(1}o8x=0
z{P-%gSdRDZhbVA;QR1t`%3fJ;%5%k?)4lPX7Z-xJ4=FuvneTRb@m!a^r9SKndv>Th
zgS|hoJZRg_sp{`7G$%WDm3Te*$S`jqi%rTLk*pV++^l$Ktl@3bnwxquM6Af$YvC5h
zD5=sbcE4P@duPdptg`TCExe$$FeCh#)q)9+X8e3wxxPQp)hV9c!B?}%Y4egLQ=T6)
z5lK156zX;IQB7*&yEhD=lSp4onsVd$=f6ijFFDS-DCf-SCn70tUibw6R9$xXK6ICj
zv3QlrcI~GQ%>~PUbFEk=7RcKTP636mVjyGkon4?5u;6G!aQDUwnwG3V?QEURe9FFS
z`;M5MtV}7&xKVoiV(`P6phM_S<}N5Vm|569$0aq&shQJvQZ(1oghem<IOPw_it1?f
zJ89}zYQSFJ9wTL-tC=EYcGC2F`G!N5;Aqy{=DBX^RA<vCj@=uVi6!$+e-gFVDq@-Z
z5ed*`k=7dF%?A{JKVATy2=L!rFt28=x-{pUUmta@Y$~3sXysbwIPYAM9q0T1Dz-D*
z6lQMTl=j8uKn`b%;^~&QBX;vwxK>7AU9_Kh#xfDZg~^waI5+*9H)(?2&zG|fLkflK
zE$NKsAF5A@<kb6V4Ze0zQhkaVtK{XCkxO-TqHL_r3n<B%`2M(l`d>=n>Z9weZL}_m
zC@F36T_IX}^RI5uOr`uA(MA;|OIEUYJeYUEef!SZ)UTRre_C5{pJwnb_uFPC+~Fa<
zT<4dy7FVYMm$cg5>YIhi)AW8fte3KZ<R>35-NgFftQA7XuJg!&YpEFFU0k{En7zs`
zeoyUZ2i+a#bhxFiU|OA2@w$!ct8EyvypRv5d6u;QN!3c39N~8r*^Jk&B&~TkJtlf_
z^WAfEt@uIPLCkU{XZM#I?2v^7s)WY%8LzH5K2|v5pmW3_VSWs|*7l6A3<_aN3m(qC
z(^k7Z=j#hl$Dpma$andjU6&UpgH{hde==*$uF&=F>9c~499ed9D^J0OYnB;;SEnRt
zmHFhEPHR5;#F1y`HnHN3sYSZUvTLsMN1fSvbVm2zDXW7YED$dea9+2z^-lXv%YL)-
zlckr;54Ywn-KtmL^ZxCG4XsX+?n2$>K})7|eKB3kWo5^25Z#n;!unyawCaNChO_U;
ztF2aC%r3yIs^au`$wgBE=joFtd`x@zJ;&k2=NF(R;|ZHg)pKUPH#0Sp!q5DicH$|c
zi#KP-37brn*_xTF_RSZc{L-wy<3;bn;qLNhghKTLYi%oxYH<-<@5`iNocd=i0R=
zojHDeFpD$%I;)u1Ru#OTu|mW2>(3~*dy>XodFN8t!A3B&^G@-4J|WI=zfG_0^84N_
z6Yeio_EmLC`o84)Ommj5D!Yz@+w~7P<n^E1GG#{R+sV89*Ky31zHRY7yOrCdx&(Aq
z<D2;x9F$JFWJue~e>!fOdExy<P;I)g(n&W<>-HV<-&=jSZ`)d3o>JF})NwQQnf$u6
zXoKsH%e7ZQ0nK~<$t^M2H)ZdxR5IKUOWyEsZcO!_=8bO^jwM9*9K7Mavo*B64OD#k
z8a_$Ve`=LuX<)Q}ssN}Zd|Tss&4Gn2&vn85v>R?apGER5os_THGAoF~RqvE;W2uI7
zJ*fNbr1H%_ue6bQ>Ul@dssg8t<wdJ^$mr<sC!N^3bq4p|$=R;210L2*0AJphv*wNr
zGrR1>W{D!-wMT1bty}!Vw*TCOy0W(}doN8eH!nJ${P4nM&=N-vi~BJbC%;Mmb?+kQ
zE_;51Xr_b<UN1#HtNi=eZT2Z5|JyA+Zb^G^qrFOVE}OXh<`u6FXTHvQ@tXm3bz;hj
zfO*^BF9<)rCH()rx4e?}-~+LXLNaz}`*xU~Dp_;gtm?#XQ1^>r;o?ggE9YM>@SZmJ
zTKsKcrT35;b)MJx;`~Dny{q{i?R%~KsjdWctxd|x3%X}EN$bq@o_1p2w#zMflR<|S
zb-bBkH7~%sZ)0y({rzPkmiAWXgjQJ`cFhcF@_HtnEV1r<_UG`7Ul|VG?2R`ZPVPOs
z<3yu>+QYZAUnL!OPX%4f$i`)=n8;T5a`TPg;@e4w-v!PDl}6P<&1=qZP6<54@bi|0
z)GS-A3qo~_FCK)Kb_X5#v+C0slQ)x2s}^lg+;REsm5tlPl6coYxy2;=ChOgmWN=gM
zu=dWfqIRd7j@>)ANfh$#e<I{8E1`1Fsbk9$j?5XV(<h!>xbV9!t4A=$#2Z>W`@Zun
zHGxEMYuZWO$weBGHINGyA5M!YzVcCDm$x3&hj7x^=C$tT{~d8rji0AEfzoQulsjCj
zFLrMI^l?EexHeGVIdv`H)aUHFOJ)UmZ2dENwf=(zA7O2^;1ZGe=NB0-onJRM!`t+X
z=2Y8@7rxajx?E}YOE=ibwrX<ZpWnM5Ejay|!B|y*O?I;Go?Ab|s&2Tw+`qq#UkX&R
zDT?e=+k1S=exsISz8ihNU6)a6W>?@<b#Z#!!am>XcHMFhiz%P~PCW4ld@t__%gpHR
z;^?k<Qr{W=*BPoCRhBGLJmT_Xu1TGI!<IeQiX|?`#Od3*n(;e;#vH$K-ak0=<Z-{;
z{;9vEQzu?#p3o+wys&-J^SaghCK)|xoHG5Z(`tA2C@%&UF|N{Qkr^So>K9kcTW`;H
zY*Jg3R>Prvp6`mi+2f<0&Mp7@+x60grxzQh@iA@86#7;!Q<?Q6amTau(@T>3-9h`0
zU5{~IJsdr?&vE5@wQDC|tG>AK<l@Y>O9@J^TbjJi7V8TBjlA}G?>*!GIdUvpmw>iG
za_@FEd{!4*{mkk0le)DsS)e1w1aF8)Cmgofxz(fn*FDFa3BFq$+vHB|y=^UW_l}_t
z<C>MN5h+XVG_MMF@0rfW%&W?j#Q)UF$I^gp|5T1lO~p$F0qdCeJKsDT-MwI$kP|Qa
z(`g}=Q>^!GmB`NI)iDdq^IYw`@@F)-_FdRrw4PH&qvl?a&(<vyx_qZpAAD+~p?yEf
z!*uD4F5M~Bwx{QZaDQ)>X!hO6c<kM&v&ID%#4I}uZ-_}hSl(&X_4@M@{>IJr^E>n^
zm;ZKfe0yE*%Ja!{&Tl+=pih705B1Kjru4UKrNu7vw%YGI&=hwnY<oc4EVdJJ%dAx7
zyI%fH*tGIkO3vzlD5Ikji&pIGUK!c@MR=EkKu#C0fl)-2f8%@s(_ayFnVR+!OXr;6
zYl?8rPS|+<lJehAN0NTk+<9O4<nJ*d@Setog%1y%XV}5D!rtWGoh0$gtT&Csq!YYz
z8hGEQdMol4YMAcbQtZv0A>z1B)ojO!u7$h0=U)@AJA7Q)yEHt*qibfHknuv*VD8s8
z@0mBe=IZ?rkS?%ML};VD@E<o>t6<05r}dsbFO>Bbyd2`B_9eL}_bk6|`jy*q3r@M6
z73x;JHc2Yt@RXB#ELm0xx2_8M&T#az;x0||8{2LrB^Rq5-|(^4N2Fil+nY~QvewR4
z-2PzOpVI~Db(Py|n7aSh{xZH_kUekR{KLA(=jPe{W8zldu&*KUuFck1_TQ_mzghWg
z|0*UMZTY?8VM0zxyFmNJWp^Bu!=H;yla;BxQ_aKZ<J~pm#+6Em&oWZC?pC+3g*ayh
zZCv|#LWso-$Gum@Zcj_z_VV4G&*tpL*S6nDn4LAbH+SChnwtlO9_ns?u<TBgblZ97
z#zzUR&-hYBU1n!-_r}g&UUlIh(+%0K2p;pNVs}2&&3l#4Zri^7PSfoo?z|b!{L|W-
z&z*D3znHtzvwlYJmy|f$%G6^g>;G;3KleYWw_eKE|2+Qx!(Sf%|ACK}{-4hN;n08U
zfEbzj<vOc=c>R~VxM!Qpqw_Y>SO2Bo|5Lwf{>uN~`R)IHoL>Lq+uL;ezwf5o|C6eD
z7ry`hZ~6LPSM&dA?z?3FwB9gxuGQq{=RWE7{Ga{r{>S?MxNnvpM&WP@f%y*(oVWY`
z_y75N`+xlQyFNJo`n><o`+uMA|9Ag){QjR`@9Y0xp8x-?e*N#;_y4?m|L;%#{{M&V
z|A^H6_&B}(5C8r1AHKw|o%!$ni(0Ke`<=Bj|JeSRVf26Z(^uZPmPh7)yg04?+u8ri
zf6x3?|Np~f`TC#j`S<I-U4CEp^YQwF&+ESa-v9sO^7y~c=0DQ@8~jiF^0oSR^*7Aq
zv;RM<=g8#N4Ky!*U%$Uk?(qTsr8&{7?f=&m=G@nRx3p&ej;a6tKAQDUFy1=<<L{%I
z%ifE(@2K6rWAd-xN5B4FAAa7he!oS_d-3htYX5&-6d<-Q{>}FH`E$3nzE{8gK0mHx
z`u_h>)8FjhZyenJ>tFnw;vfI+&#C%fSLF5acYSfr&)@6I{<weX3iu~@_Vo99mm6On
z{?;$MSM>YcxjEI^_iGOpeZMb%py>C%iuu`o_hmN~|NQr1YVq%X29tvS|NCfo{Oxb%
z^uB-c7hRk@?%$ocng8qV{buri-|^^t{qXme*gpF=YJOk#N6*<_f8?vz|BgL|N5%H-
z?p+eF&;FO{{9EPat9G=$e?M_!?xMH1r)gyy_cFHrb6hH&x@0cj?!)oVpU;uuFIl~9
z{^|cKOrL1&np49!Q{ip9?ve}jZ)<)&JH`Jc{QUpLd_}d3oh9R~ug`mI!8&)wzF8Bp
z{cmsoxzYDTqtFJkgA={Z-Eo<ES?u?ZwO`_Y|NLRJ@t9ZqUDtnthJEi3{kUY7skt}T
z)_C5dMdu&8lt@X1u+3w-C${fwf9b(s;kz~BHmMS|!ZmMN^==;du2sSG^v1rOf1FpD
zT-ozs=llKhyppc9OEt&rzf_&|>G8|_$M-I_dkI?1oe;J2K=x7_Gv2_y!q<g|UaNh$
zW<9n3e$3y-bCHL*=WUz0x%^k<<8{~9{?47VBGB*M)9u%LSAN<k#d7~ef^O4t>!9KZ
z?_;F?_H~|5eZXugu<zsFcE5v5_Pwk-rm9prt=;Ws--YelQcu<1`H{S;^uo%UXVk9W
zuDkEdaXTmf3R`oG+OPge^AGwde%(8_?ZM@Y#8xTqX^bn5M@0y~Sl0X6ZT_M#Q@xxQ
zBF#^B1y7%7=DuGgsLkk~=lA$onf$ujv{HU$IW5x;yzRG4r(klt?22d(%NDCT)2qi9
zYhPIY!mGcSJ+I=i(I?f(-hRDhpFK}3J+J?IyHDl4KNoFT9fSQ(-tJrWM5VQH*)q!$
zxvQB^sP+DN5>zZ{Zv5%3RPJ;;7vHQ48oB3%?>NiZcH4!%yv;Q|YsJCdHy_{JaI^2a
zUHq_4asLdv>$e|l)9sTJlM-Fydthx}_2#Yb$_ri={!7{we><bOq`K<H&cF>Tr&ab^
zB;{m&xhHgM+y8r7^<5&fn`?gevMq01TA}uLS7=|T-#(GA;s=lE-S1jw7u&CNCu&Jy
zpvOXaqk|LuRPT7%JM1V4{JHwrj3)WN&F?}dUlV@3=k=GByL>;moekb`XZKUC!22DW
z?JqwS$h-f|+vUG<@PrB6v03vUSnSjKx<M;ZQH{(0vHHdPFJ|%S@k$g4WhEA7GcDVF
z!7NjF;kmNVJq4LL-qk-A%E$kGk*oT|Xm-isKFhp<MHR+TVt;#r)OUn(`slv7U$-S=
z=cP`ku7d0@xA$DI^oU=SA0NNicgbwyT|pizr=I+p9MWZC)9ct&$8O$z@a!FTw(0wN
zV_wYAn11>Y?`)QArsXrzUp)G4aG-?y{@fjx_$3}HU)cFs<?;rl{T1HIe}YSHJmY`&
z<u>b{R=fHFy=c*boGD9AO#OEExU9{Nnbm7uLS7Zu9@&5BW75AksjZ9dB)kf8y1VCy
z_r8O->zW_)$X?m?xNoVv;(qg>_4BXjHLHXQFFki~_M&z2j&pa2n74W-&nQumn(6jg
zCFGQl<sljSo2A`_WeHO4>eG_fyXbH!Chk9Yr69%Nv6?-5{;sCN0^8n>LrWuWx<Al}
zp1`(uW3f)-;wyzuUk0b%yYJwe!QTGLTvCeL^n7kx-<_r0;#>}ye7Bd(y0eA9dtYC^
ztE{p2g9V1GJ-e6gKWeFUiS<-*%p&Q>-`kFIcFvjk%WKAAX7Ovu8y4w{Jw79@v8BK4
zsphsbiJk8rooLm#kk6!dWkX8Hr=qzlD}PF|8eKO{EK_;cJW1{%!?xo(QlDCGOPfla
z%+ok4xl^uC^VXS#J6b2Q1m3fka$0n;K-);5{Yko%gL$>mi(|)bHm{VuE-72&k$c`L
z!p?|I&*h2u<)dFJCp~5fo-yIeauG>h&E1)oGG68vORT#hxuo(^{~F`}9!5L7)TT%p
z9}HaNF8|Q^z}!Wtf*-b6Rli*P|FV0LWNhEDty+&|-DNvvO?X=N&b;uja%DD$aZ3=_
zh3NSojm|!4zLoIhQ>|t%kMjA1g4^{)Qa_ph?$I!xDJ0W%^t1YOlaqnR_+BY)J!>*M
zX!DlmPFMJT?&3G%EwGnwE?(3VIBAhXyb|{euM3rvgC(!;3KW*SZZ&=0sy|QMBG)g8
z4*9e6W}Wctd}g1=;rEOcU#&j$c1ja(Ucz~=9cw+z{O_3Mw#`%Vex#;)upzo<y8Imr
zXSq8u&&royxU=YsT9!-6boK3`nNfRLf9~9vDw(H|W$Jlqg}89VvWmo%sUiz*aeSDv
z^qJJ@H$I6a?7xaipG};yvsH45WqSYT=a>FUSBexqU+*jO=gBv-U&&J(XS_RW)_mM7
zNu~6V(Ynd&O>~y-NuT!l`la&uH)aG)x*ctH?q9mb;_9m`r?1WEIb(Qw?#mb*j|tyO
z|Hb^8YP@*qdi5B;+~?<?9*Jra<Gr|9J2&PNkAZ7YAK#?A$22%4S;IU(tgvpewO_t4
zNGQrn{Q29Z(=Hx=yR<NRmT0JO?c|VIQ65u1<v!zx5x!WVys?>U-<@YO4sLXQrynX?
zR4*+WBILEwy2R5e?R&1S3FpPVrwdN~44J7o%S%8~YDK{8fL{xyPnsmf{r5v<xup>2
zl&Z@O-*$P1`St3bVYGP9Tre@fZDq(*HP`7=v-cV*1TLN^vg^I1n7P)gNy6UDp|hAn
zr>4w)l`i@7XZn?y&)Wi?ZFv9sjQZy@w|BenNpZAEnyr{U-P(Kk{lyE@_03MMeH+to
zZqF>G$_dMS?$6t3Vs*JyL}#h$XRhtG`Te&u0z+EZUf!FM8}NQ|qJ8e9JponUz4$bf
zZ^|-qJu-3Om|peh&8{n=$0}Sh3#L9hU>Q0=&qea*pMxR^ZgJwX?nIj@c?sp^*DaII
z-OijLG54#5YD`Su`88JOd1lQQ<<)Ba75OG`t4{dLyrnHqy%MMBv(|1k`gJX%WVVX*
zk~>ShPUgzjSe~9}eR}G_dAEWtN<WqQJXIzn>zz?e;6n9ei+Z)LSQlLdu5F(C7c0#B
z9@Y5C@1#obO>RD}z_={4Rl0}PD7<hwsx#N@`oyS<J10G{pAxaOvN3rE|K1;Fo=XK(
zJo&EpJ=v!wmC)j8`P#(hMZe=QJFR9*@p+y#-#>Y;yx;F|@aA_l&$M@`arZ6erv{iz
z%IZ1w>tZL<bJ5ak9G9Owj7gqWQew2~INOw6NfY<Gy-N12(|G!7@#_n&U6Tp|*XR9y
zy7Y?o3X^X=B1Y|*eXMDotpcxeyy~`voLh8>=jxnmJ{nuwPpaHX_~b8l!mE7Y+Y>*X
zn^TPDeD2RX*WUCcEK99)i>I0HtvvOso=dV-d}r0|o<66W`JKb1+=)r;Gp+<3N;%hl
zwblQGPuGma4NLfDtJE)Mv1Uo!W>xL;s%9zMlyy$?e5Wt+nkaoL`TBWP?mH;~%RWqq
z_uYPatFAAb{i*iD9c^<&!**^9nS9D2T=U8qYcF0y?=?$~-A{ifbMwaJ)u+?tLbh#E
zVY|FQEbXP}v&Ace+<2DUS+81X{n{*FBlc&Z=nJbLQ@e#GkG!+|N|Psf`yHOS#Z^kK
zYewo6?QNM|0dYIx<Lup~Pu*yH>A2mZHFI*%XAzCwzQ<vqUNPwz4~|DBUAnkn+u38T
z_N#lgOsFfoe=K2gM#%)DmagLl>-F0W76$z_dzAmysEjR3GbzwjYuRNF>zB{>u5r}L
zd;axo%q2bzRmDQ5m(O`Lp3a!$&hqWrFP>kKdil%3?AGbu{czEH=Ty&(2ba91gzol6
z{tQStds$2N@%!yF6}HdZ8JuUpRF~B6?-jO7_46;beLt8_SsrOHEBwmj&p5HcU$t2x
z)<!dB+mcg^{!I$zwmYwixOAD6?21aRc>E|vh(qedFP<NX-)|W|ujX0mQd!f*c4y{t
zSF6h>7H)I$y#HtA)?+H~80&XSvaX!mdEKe`sG69<(%YA+UV69v{S+jp5b(=M+2X?S
zrRT3~YOl@`ODYUBjC}QOd(iw@uAR?2>^3F6%9zyDf9l2aPs<fJS&p`Zq-pIrJ7)^(
z<K=mCPSr@iteYY-+bMDy%c1~HvwE$&t99C)pXS*wn8I=-l6{l?+4@E6R9`alvZcnw
z+aFeV%6=*Rg~#2?^_pfG6DI7M5tVbhH}zH7<)3S#r__1fU(>eNVnUDV=5Vd>>1+*^
zrIklS)LJd<X4o8`dhpJwh?vf(!yQ+yc)Xsc5%}j(O8OPWPUAC<Yjb?+C*N|A5z0!6
z6=LU_Ublajh<l5dV4n09n{{lZPh`|fOy*yluDQ!!BUS2hV*2^we^>4unX~l5@snqM
z$dv>hiC*M)CH<#WHIHb0;EZUA%7_OgbxZbl&T5LNo$35<jo8iw6XLbb)?SegNk6OA
z@pc2_(p%A=*iK2G{t?;g?R&Cbncw6-o6`9&vzzAyy!7h3*gUIvR^fzOAs;43{Wi&7
z8PZdCjb-+qpj~?}pI^24)MAgFXWQ3_ynd8mR_MZf{hcyb(8@_EM;1-k#9pH}qszwb
zrp450RqH}4yAEIb?oec>v~Xe2PNiio>DyBjUf$wQ6FIF_^x+<h=2OP+v+QEcw!KYz
z=r}jJ?Z&4pm)>6oJ9d}+d$Zizb8eKL?rf{3C%+OEZuUr@G2GcO)8qh$@zT9fi{4A6
zwH}q+VemUF-S6JYEmCJ*q?RbDvDy?WMa{LJJZb;LvcPlKkKFGr4)I=jYQeP1gc+>{
z?){N3KPYbxJP?>NS#kTspgOf!lb2d^^_pTLyk4uMF1VA*BFz<8r_yiOF?af==>}fP
zpKHz?Q}vv7!XxtL7F(_5i;7~k`_Dao_RRLdCH+~~w_dxM!fan6b3|9I@afBvBK_it
zB~zt7zE))TJ#+J+&eSwFlZ0t6P5r{Vla~4m{oJwhWa-jHeoRcghRic3$9xKW<DtJW
zO!+*AX2@BV3HxfMr1WfBeluQs>(|I@s$KJ#PxAY?TP(1c{H!%~dxnDMs-B)Hzm|q9
zvk5y};UMlYOUZu6oYMSBO`4lt>h0h2@pJIci5oll<8IuNJ=mb+H8sz(xz$A>EAKI1
z5Wmbc)9ZysX#olMjv1fT4a}Zr<K?Y-eYs3=Tlp%3XT{sZvSczP?8PRTH0FQav#vz)
zd4JF0Y7dh?eF}mrFXk+64UjU`_1~uT?Y_s&%@Lm_Hl0WbQpx|k(P7%hT}5stPL5q~
z7V)LsQor>x@uWec?-fSf->plnmEJkti8D98e9%sN<r~#M1t~JJGn`gGNw~86iKHO=
zG?j3(%9*<zSl4WM9`bp@MGf!i^#VU9^*(dHYx$=C<%;mP{ZSfW+!LJ~L{gq}obf1|
z<EF9TT==u4PnR1XI&-Nj^GNrnl;)&mS7v^h=zB}a_4(fXX;&WCoZDnS?fsuCId{rd
z>FqYSd@n__?~L~8r`-xS!+)C9g~-JB1pP8$&pxGf)cfJ5l=>AHo^HC#yTbTSL7AnL
zyle5U2<DS#y?dVM^oMiV>&iM#V=J`RD*WZSS!c~my>^B4#kY2>xRon)YO`ALY{zZe
z-#lM`Ceut|6~mL2yrrgv#+JK04HocJNDH$F)k^=IDI)r`EwF2f>i&fjtmMOsTjnfd
z7G?ijl>gZBaYGQdZ0+Vtd#Al=kiXGWpSteIQqI6H61Ls%g5<yVv0c<sHoPlj?{y^C
z=H3iG-q|NN7i1UDStfTctyA#m(nb1u*U$G$+3~8yUg?~ozDmUV@frn<E9dTOPBRj%
zimtb<))BgWx})UrrB6S!d&_J#rzxq*e5x_{xaX#C$JX=S*2SW3UGon%PxvyW_tBYu
z+S^}7Y`AZC`m&v~_0-HHPC;YO#j=fxT$_Jfd$yh@_nzO!lq0&`HCt6)eAPXl;IMez
z9dAF5#VLDQt%BzsJdj@~){`j2EI#di8n1Db;$3g4xvddLoqYc^#H<R)lBzYkHS<8=
z=NTUxv`<MkR`~7wa`x2E)pyRE;rC!K5nen?`0>OgMb5sP=jVj(Qj1+Kc&Bn#k4u!-
ztwjo*D&l6rtrovMCFKq|2!+`6L}`fesi@k;IR%{8J>}thGk3;Ehd;ruLW{0eF6(}>
zrc?fxhr4E?l*^Q~Z8uYr=W*JeUp;Y$<J;gYhf|7KlPWIU){$6oYr@S>bCUa3&AyeM
zn{?}oS}I5E(JN2eKOOFx>Hh1lrQLFg+iQYu9G42ns!NtwJSTJYr9h3V(>eX$TswOp
z{8z$9mE9W7UiaGlvTg;f3$B?JK7D%PnY7tEH{JDqqmpX4lq+b-2VsH2`z!Y6KDxyJ
zK5oHZ(FeB+_>}y`W?oSF$Mo{M`>d%!IV-I-#piYAJz>`@Doyvh<TX`2r}H_(8O2sE
zaY@T&9`>Au?rgv9i_TA3axT5g#NeD@x73q0d_SAs@o%WU=YCGdc$dcBiBFm)1(Ypn
z*_pn@q^0k)dxMpg<nAe@X){bdoHx-pv-*U;)Fqw|3(tu(?ww#G|G<6baaZOYNAj93
zc`gwQbW}36U0SQW;8Sy`Va|=BN%tnbY~tGTN%@;#(Tl8;%CYloH_T4%yezwrtuEl;
z6}e@xzGsztADrquSu^W+-Ln&ID{f3_Qv9?z=j6TMiH2Ieo-EB?a|7g_1@8Y^%oObR
z`JwuAeM63t+2>Ve|6uwO{AkV-nH9mFdk^r>-q)LHvhwV%6=yOTX3oF=esS33<pMbh
z-H$~k$7p*QO`f9BD}UuA@6y-XPVzpLs+p$oiDT~Nx=xqIs)ZtRLi~CgycM%{J(hm%
z^x6HBbDf=b?9{uvmpc~T@vGaXe>rD`-}>1{7CQZWwC0G)-G%c-+|N8&$!4t2`Fo8_
zU4-TFv|S><gPGn%H=q2xROR%OFBJwig{IG*xhUn_oPFnu?80_Bd|CWNQ;xS`uh0D?
zKmU`u9;@VTNO^qTd1TJE$z1$Lnos;q5_tR~rrE=F#hufe^j|ItshT1B=GB=^vzU5K
zyuWQ(vgTgP_KlpnPn|MS=WRM&oc~Ja5!+XhCyoy~I*eajHCcZ2lko#V-WN%IC(d83
zoF^79&Y!GZcdmGebD`gI&aI~&&p0%>X354Np?DTg(Y<#(r1<{m{GG*fRphq$N<+=U
z3G5f<YOOVjb(Qo#<)i=e;bl8hpS0eKOBea6vkKOFN%_6|RB}8xQM~!ik-#5(a*1wp
z7ORCk4b(Ab{^<9dS$*52qa0kxsrOdonOEvOx6GgBUzi}J%z5=fq@3C3&A$}PC$g>1
zyw>J>=|-H&&jpGbJAOKT^y>P(R^-&ARu9huc9m|YRLg$d+gyIE;bx^?>z!k>RDNwr
zHE6c-Zx>xY?eZkYB~H1^q;u_rbd2+PJ3k%ySujO@alQ1~OXuA~d)1|QmF#Q$oZjqy
zex;&oZN=eSl}eKilgbT#(=+|#o)l=zi{m#6oUHZ!(Q-qlvnhYvqzb;LFEKr3BO`Zb
zN%j`Y)I|mSqNfw=_N|Oe^9gjBc`oJ2o&2hck(-_zP%QbR@usisaBAG#^KO$<?EZuV
zEo(_x)%@&8&%W=xyG$O-xz{Z+ny~a|=9hkVmSmQc#m*CKUb^^fJ!@W>Hsf;56j#>X
zFK%`BbYr)wuVlUXV3zS}uF%a+UyPb9MEveA?cY9=_e$i=i)%j@&fl*vukwLs=I=kA
zKRc&9J0Z->^etDdeD7QTfE6VYma%@D?_QY7FZ|-^&u<me6dlT%Sv~BX8m<_>V(EIn
zxm9QKwTwAJ#>)ygCq8rDF(IWXZt9Ek{VqW>j-6Zc<p+2Fl9^mDcD?-^`0B+MlRdvo
zZf8z<nPp>i!a4igxyySxcPo2O^t+{5T0ire&(mfbsfF*%mY)y)rhB&SlzAu5!n2Y^
zjk){wPCX@}*2VpZsZy@xyJd7;*}teKw>K<Q<qy&HocK=cn2rcz-sXj7b#1!;tfCno
zPx|oq)lJc(i<cY;lsi{dR(p9%{r9a)ZTO1>eny`E(fP-uENZ^Z>tq3UF0+o@S=Cp<
zo+Yzq*%eP&w5OWIB5t>;u<%dMzB4vYb_V@EbIGVZq0;I&=V!Cqb(1=Swsx7G_}rZO
z>)ecMHt#A=8Zl0PoGC72|71ne?UZ$<kGItxbDp}D!Df4=nYF$A{tFuM&xL*KdY&&^
zKKJ|bfI2&;Tc3I!1ggpAym@}g_sL9#&uVNdXI0uY+DyBblIQ<mr<jnx#z`^fxsT@F
z*k|LIB=_X_ETiK2>pso#-*YzXu;i+q8HH+Zcyw;h5xM&;V#f9j_P_4S@A>d#zGKZ&
zsW(Muj#npcGm<h|VrcHwv?RGi%I>LLkb%x`+dIphzdw6AQ`p{F?#Ps9y{9(!hn|}3
z=Ko}wj$7gbnXrADoJW$My@_rJ={*(u#4G)ttNeG#2-jyjum0?~@%hiOpA&2^zn?C(
zEVc5Rh^@3n(-I5wDRZAU)ldH8`^sY;pQ^INdSOlDd3nWR?B}beZB#lZ`D;$?8SUvW
zq|e1irc4vH@0+uKQiBoWq^21bhjY&vaoBYGFFP$dFUN@a&Ya2ClkXqsewC8&G{Snl
zOzBsf`sAsny=s%{q|fb6G216zJ}bS7r(S(S^-Y$Dq`87y&vke`EH`oQ+qKy8@`g#z
zl;&z|R{3ex_0V8m+L@Em#eBN4X(t(WUc2$>f$Pd2w!2@J9=lwtn?AkFmwDG2l?SJm
zoN1GKcH<bYsVL(#i}V#+_6E$jRwN<3dj+rOq)-jRRiD2d-T7k6`HP+N=bW@+&&&G#
zM0lq7k-G)k0_WAJvLE*oW8QXF)2}y3=-|mSQucDs-tkwbsV{k;<j-a4I{ixiW6RW{
zb1I$;{&OenQroop|L4FQk(ocv+J{$Z&E{;Lu4?^g<=IJl#q|`PpW2{cY|T{b8R>U$
zaoLRLPvi_6<969DU6$%6^WNrn^q(e$&p8<q3P%zy)lOzRb>1*NFKSujdE@Y7yk9=W
zOsK0~SA5Rk`Qy#4=XT!y@^I#?;N7zx2m9n+V=eV_ebRn9Nn^U5uSi{+<z%T>MU!@X
z5^0lUEWUZ_kK&sZXB;cU%t9o7S$>_guTFs5@N=@>PAQw`Ie!{7N=42;&)j_CM)f~6
zXWnXtxOs`sa{WY?XCGX7UFQ4IA3Y%kr)7Bkb%WQioNCXW^*L;tVMaj33~l#}3lm*~
zY*M$K-`bn%=e6u#_>q-MboP1rojJYmnN!25vMmn3>#Qwz-ais^x@hXpqAMB!l_Cd?
zd!MC<%*!;aPxpP4VLC5b`KHzR#>tz5<P3|C-FWhnFVtb<nas6wyU!fFlWq|*?}GV^
zJ3=jykN*X9%j@!_3145ZEptu4GL!kG8!j5Zest>fJeHH^S3l9P&l70g|Hj_fZ0ELv
z-KP)m>j%$2T7OS`-}cCWpg;Fh3Z+9IOk(QEd@{-Zg73te?SG1&M=kZ4x=$tLZ1>X>
z_gqDu?W^nhH);9g$(0wcCzSn^`eSqNw1roBdQ|GXUd@?jPw{z+W}N=4tvYX|Ql9lz
zzs!3!k|_?0pPZ`^KK<_L6icnmu?D&m_Pq7u)X$l8xoEb;{wcd=Mm*gZ{MJN#a=}c^
z%@I!?YSnHvcojPD@^(*$$Io9~KJ)SSu3Nh2j<Z{y<9s~jRes^Rud@=@e>g9Dz$*OC
zMe{R@=U$$lqVQyA`clq<$((1Ws;@qI*C+MdoV(AM3+<!s#T+<R?&{|~bA!v4Lzh|D
zC;$34huJULXX10y!z(8A2Tn6wu=A|JtXF1x=U6;X{5+*#=5qI$cjv74?F{ApEoE1E
zZC|fr?2OW9C-(#uKKt_LX!=*VW1E=fCF{TAIx1v;cg_xftLIbYif8h!_nUC?mW}F(
z_t~c2vtIAoF;8Z#M&&$ropxjUW`XKsr&}MLH_db_)oWUKL$FML_xZ2Vf9C%=W^m2W
z&v<gyx-I$_=K9aRVQ{-8I!^m^Md}>`!=L%N|8I2g*c{FdsJy!D&UJz3Hg7hTWuBAv
zN}ca?WHL)i+}((2*3rx6@6%g<RGazq;%zpo9vx*Wty|^c{#GdOW&L&&Ub%Ts%r@rE
zH@o+2QOl8MGv;hL{f9{^dXG(`-yeZul@lfPsk@l%r--+=+o`_YetxNM$kdaE9qK&(
z@7k5>mzP{$6~F9+-u5}BXWIA7yuO;V=ycNK4Y~7E?w#4P^ha>yJB{V<4&_X8Pj@@E
zck(&*2AKoP)#WPBU9r%;8`YUx8Q1L6TX0USH||z|&&D_NB`<3qwzIo%cEOP%yJOnL
zK^*6=&+ZS>F#ByGZx-NWtbW@}@@d7kE}JfoJ$Auq0hiv(9?pAoRADjeQ=4T*A7xxO
z#;jo6B6#N03<=|zg??d6UWotw*IfDYsYUL?Gg)(Vz4U$e-0^t!{i<G`miU`VT2Ca7
zA2RwDlxp(2_@}R&>KmCT74hdeC(qX}d-i-u_@gtWYBSaIxi_6vRkvwQ=4t3``*O3c
z!b9f7li5ADOjKNV&J;PG{wO^C=lSfTf9J#;I{)Y?r}Hv>P2t6t><+7aWG=6~b^6((
zIabQXTrY!5b<U=|4{GzAcTwPJ-LyUZ=~vG`FARBqWM`jRu&m-VwWX6cJ)0bBRQY9g
z(cLA>1K7VkHe2R%*MDDB?%@v)gEIAU7N$*j()Mgu{#571@Bevhe{)&EYldruZ1BwE
zH;bl3_D%8fFkf`+;_({GUt*Jbax&i(8F5KhPB40wsJ3%q=KUQB)wb@pDkP8133fj@
z*=E7=*$UjOE8{z!dW)`|o_FQA@rnG$GXrN$E`D?`Tto6si>K)FI~R7e+8+P9$zba0
z!#`K_P2YDSd6mY(+0VoKj?J}LEp)$m)BK+)Iw!MM==LsOaQH~)q=n{n%QVc5f7!lI
zzFcF+%2AwlcEy4xw=PcoT<qkPJNe{oj<df?dBjB)rq0sf{lDo$OJ4UG^+o%GOVzg*
zxm;@ek}B2T82<b0@#Zh@U;ZqQe72`ICThZ;J>fw&Y}~?sJ)D&F;c)cHwxsDZ1?J7S
zN!>X$<iokGNmKTpNL{+xe*R4Jx@kJ^bbJ3y3hEEt#_TD1V}^?B;l(y;emYaquh{tK
zE8GkaN}2vNZszj8?|=JU>GY|LSHJUP;h8Th7tN56PEY-$y|Q4!582HYYgdMylsW$R
z|3$+}g{daCOYQc|KNBpTb~Ey?OVC04WI6v|=P&2I*mO(fi-EJX>bvBXvesNiOM9O`
zI~CIB+xF6=ID@Hdruq4$Crq|g9$grbDw6zr&SqmD;gwHW%wJt?%ud=C@L*c$v6X=*
zH8)#CdCsm8p2>OGU+;;e-?NqZ#hIy75+_XedmB4>k>3o<9Z$mcsCS;Z=5^=H@yKHF
z=gKF4&HK2vspX5ybQ8{k$(1ui8voXWT-Z6Adt%hB8V<`pTP{{T?>J(esKR*7rbxhQ
z;+=a}zD>2h!dw2}%$c22^oqE5%FR!UnwsZ-cj5c~=PNS3L;8v(dB1x9G_sk!sW;yL
z<m?oMJqHh~-PbznJ?m)J$2}UmPU-g4p4<1-XTR@u<K;j9Y&_}g+qW+0{;!SM2N;5q
z?Dz3(ubjC}D1}L+UOUss^^ZZ_DwWHNi<iGP55M+Y#dz(ZZR#gNPPF{=wRGtZcAZyb
zTXE&9d-~%bmuHbre@?v=Q7?MTWUAxsl&RJ4_RKtPQnOs~`FGK<EB&*+uuHu;X1w*>
z>dmaj^xp4qkI_7>vp{Rwk7JXoo?4q#8l0HsB)g9>z47zSqPuC){d-iqY^pnInBA10
z?DSyvC||*`A-!<@55>(srLQijZQFP*df)QtM$MZvBF`S5?R)0s`acFHKJIy8&l;cK
zRL%Tq<lR$uw#UI{a{8Mh!JQ0p(~D<!xBmW6&3fbc;lt-Pr?O3$zJkMGy6lP93set$
zyz_j1_x;yT#eZ1}n+9*Rk<w4i4s_%GrRCZna{Bo9CpT4%xHcD><tZ+2`7F-Hsk5ge
z=ih-N#(nJTPqX;W`=QS2{A{cJWA<YjYbQ*at#iLK{CMw!;I!t4&o34+8^7QA`E%fl
zs?2#4my4d9Jax-it@&*4Ci0hY30U_X-#5SiCr8ru<r@=9YBJ7zkUF=kB5JOA?S$Xv
zIu8ymZt>2l`?YP-1D0?1kDITJ-Sg*MY|f_&#y<~oi#O@yXK2YM*=KxM^rqs0yZwaU
z?tk^qrcZQqIxfNSxaL8`(&t4RkE*{dQC8XaM8;jsVdqSn|DHK7a+;49y58D4r6DKl
z<dIaqO~p4;KNkCR{mIC%`?uIA?Muh8a~B^>)ho_4KELR}=1+_EDDZCa{&nr=%(|Jf
zo@uX3?)fL*Ie4mhvW@?`Sfl!LztY5?7^RkMmV16S^Ut3ehIE_9nLm>&yl4BAEX<Bq
zxfCccS$Ba|eu!b(`@mS!&q0wNj0<Yt^&ebzAwu+MzvMC3$44E6QdjofKDNYRo}s~|
z181T&dbm%y&ik`3=*dLM{&MB#3p_Tj?>T4lF|wvr?D_lEQ`Yf56-%A2S6885oKZaW
z=xm!*S2k(=#WMYmihe))v-4c$?-{(F%;htKb)qIbb*$-5f4}&Lxte9Mrq#NL=aQY5
zZda<^&CrwaJ+`xE%EEcGBE%Len|ofZWM=PVnfZ1m=b6n+PlUXqydPICZl0dzz5Z~h
zgw4N8_VU-A(!xGWekAB&E!|vXdi-2mv%BZ97xgy(OZ=i2&eO<zdt%db2aD|TxG6gK
zZO@c+$xga>vf@79NxvJ>H=jiR<a|>c>;GKW?fCXbr3Z@>{by{Pf0=Klm!#Rf!#=Z?
zpP8kSFj=J6$<;?DI@qIVzLEVd+1^!Oe$Hv--DlLescP2s+Z^Z4i)ts&yC}n5S@-uv
zoyglue_j=dR?O}VT>4>^NoVMv30Yq*9_stlu`6zweb33QkCUDoef#p`=L+9FKRP?N
zhY7s5-;ip=bW6?u8iz&r(q|jZZ!qL-QsuH|mWkx^7tNgHb8=GUv!@gLH@r7s&Ug~z
zy6f=1>YyjCG0rDs1AocqFIU;)JB>Bq>D6NybAC3m)VJM@mkh1AdijZ}WWi0zIs5y?
z?a#b>{<mh<q_nkqm)~`UJ@t6zcl^1}%%o`-%w}piaAu0jH(&RDYw!Q+_a<xg!gzb}
zO1<YY(-)n2!d>}J?848&E)%g;>h4W*Pn~J4+;mTZyJGTIU%fP~B#+X0t@itbLo<F~
z+3|BrZ~o#x-RDf2-_7YWd=}xEzr1cH>+#QP*z`K0Z(AyzSU-E3)#D|f<X0CxyQII3
zm*vH8nW;PYrmorA6L+OjYvmp5KE=oP0`IA|o!@tE|L0llI@=xQxqi5_(SWD;+uP^s
zCVuI!wAG9{6X=;Fc~t)7S*`n83w!gfKU2<;JJP+N;x_xqkAMGUTAq4y<ILo`Z><5B
zL)UL!)RTO><KU<0>1Btk#r(n~x5=GnoW4Wy*_F0)+1+WL8$Dkh=ij~bcIvmC&x}^=
zt-Ube*7N-qcY2*#*$Q`-+PqF?`pjZB)BWVm_XYx1{@v5OZ>B6-@_vupHV%Wci5hzh
z>)tmQulX@^Yrxl8>CTy<R<i4TJ&H_IcNU~a`_$btTYm5BEtTLikE73thF98M%FcaM
zA$)3^{k3;Sd|UOzB<u@5Grb8C`^XdRnVX{YV1?pknbgXxg)#oWmKH|}ykDqrz(k()
zqw~6nCq8d-pE<|&n~>xlo!vrD4QGZ~-Q&@=iSzm<aYXOo^2LQ$3~bEv?bbcKrFn+U
z(pY#~bn3BtX7iITOqlzZ<&*QP`QA1+Qyx6#-NClOL*RjF_@^Za($PCP3*!BcNk8;%
zf1K`nXz?F6HPs+N%iu{S$N!)CobqGM6~Aqk23sm`I!|iqnl5+ZnADn6hq^y=9=mbd
zqruY0c(%BrUw7VQOZB<i1!gG+PS#TU++55kHZ$?|@vLlnv*1awQ5A6o)7VbQX88Hv
zPm6!<s(ZO@iN5Vz6aDP>*6VF%I9Chu&)GD~%>9<-=Uu;do)`1?osyoJe4jaUN$%|K
zqKfbfGf(&LIe*qcM>{qnK%%kb`{YxTPjKINJFCQ9wUYhZq$zbr;+W1@?vu_xdyVDB
zH_QLIdGROttIHo;+syEH&T;3;&EG%I`oz4#am{9f``z~TWwNr)TX;4m=6ulHqtvf`
z><`buk3F*+7uV^o7S`aN#(QFgdFV$$4eRX3Cynjb&fNJ&ZE~&k`v215TPh<Br79*~
zdUCW@(N$>n<Zgb>>oU!Ibwrl`Qa)p)a*A1BYW}4eZWDIin;0{1*Y6!{d$wNOv0%>L
zzLg4gCm-)WbM#b<%J%6O_P8Xv&77B_AZ={W9a3-XzBGPM@9rs;tzB2Pg-#PQjhia4
zWXUY)4I(SA8(rrsU3X~av>+M1b_tI!2McX88APwAT`4ubz4S`<mJ3GHz0~Wv)NNk9
zNjm++a&jO0Kh85rdLL(~YfrC;Trj^cG=FxEv|!hn4eyj|Ww&xkudtW5FIiXdv{k+G
zL(qJitn}n>)88A}3F#l%c}Anv(qx0S{ogrO;#C3a6ZaZgt-rK#v&E#q>C@SJ8eApM
zN$h-K{jAb<_M5M#W*_r7<{!TJ?AN3{1z{B?9)9huZk#tKb;!H-{dV8k=CbFE_12Hm
z7iM33vXX_DPx+JSzp!TY?wB8myKOv^CziBdduEdnCuiEsp*rVNg+jr4Ip6&5V!kT9
z;x&sWJWO?OJbU_a$s(1Ne=AOJv<xhm&Dgg6jX=UZW}iFZ8NvJKe=fE?U&!^S<in{;
zk-pw_lPe=<?<kE`ig;Y16es?^(W;}^Nlvi)%@hyjbK9O@se6BQkCW@SsZW-R1$E_A
z*B;RpKjv`aVA2oa+H<NIbH5u+)>{5+XQ=-?=32f_7ERvzmD>(mH=NmhBtE_VhEJ|f
zTj9LFMiVtTCvBIUc;CW2CCg^1{{&AVw@5aF37K}0uWZhjUDMp-f6;{X&%V#5spm3x
zWvulRHu*d+-(LQFUuyM&BfkrK`wklaKHmF;)$*~MoBr?Q0-uS;1?M<j|Eaxl-978*
ziLnchAKMe;(Iflgnd|%HAG$V)WhJ#{-!3Z@Es!{(Ro&lGJC|2o_0gizx_g@Tlk%EM
zYPnqO&g%AW*OEKEtzYENovc4j^Q!bt+f80`EJ<F&>u_dqx2x8=M^8Sk*>!Mr@olkr
zasg>8rx(u@w)2{^+PmVn*2@)pQk{P9d{b^6vu#Vh_O*(pHxhGxyzDx&dUcS;CxPec
zhOH*)7xQ*UU#oNuo_XofZWF$HYPRS0ow|IY&aNy#uDDZ3U5v@6*zVS|)SpLYaOf_6
z|9|@G?;e{}JSXKoFBjd{s1U^SZU4q=%4d=yuhf6Aj(2V8o;{O^k>|uRr3W2i?XSMS
zl;&8g%pT*s=!p2G<+Im&M?T8A`9_y%>0aj$;oGPBglztDv3z4P3-xASX=~22=9##b
zxSRUk&%Q+ySr=@0^i^YR`ljFa-@Y(4-rjxUcIgXd@35+i4~w<p0;(1%FESCga$7X5
z?8Q9cKH2pJu925`Y8P~r?|R(3^7TJH!Q}#L0$YFS2|c{mx8%*$#+6kq;XlPW8TYcd
zsxTFlc7<<$y!T05%<{c^KTiC9@$=poze}Ocw$B)U1<7yl{~pg5BhcC$k{U3ZEjLE&
z6$k&6jz_glb1oL7|ICqg-||*!6SLrX54RT2z3LMJ42%B#N?*jT8x+>Ka@|Xl=7_gW
zTH9}YeQ-Yc=$n<2P8&9TaSKhqur89TV^JMT%Y~N>FG^hx+;iEfYoOPDJUnmXWv<Rt
zi^)?(x|lz*uH?U(w8#6B!Cx=Q|ExN*D)$vHeD$TSy*zlw>=_qMyb<mH6Z<i)O2+!b
z+lr0hlKe---b73N<}LIn<X*KT<^IhpCOsAxuHGqHYSz`E&uwz+RYygk=8mn88MQU%
zZ7#1kxG~$z<>ZT)whysKUY{~KrY#*3ER$uiHz2_KSJS~q;d>1Fx;kb?uZ%Y|kL)-!
zb<uI{caL}PSh<Byq_=X~BGq*aam(cL9v)T*$zLn9aPOJyE5@yVE-2rdw9QWD`Hu)`
zrt&RUEoC1?HGNy%(4pdbV1~c@fyy;2{|Yr~_H%Ubt?JghBe(Sb_M<8?H+>Y>DHI;<
z%cwcPv18T`ef`+r-JC}z2}w!(=rXUl;=_@xS+B9;+0<!nDv!etFZs#Wv08X77yCX%
zu@}E{TPwwzO%&J;-2GAa#dw?ihN=qFK;xnVxr%#dNq*mbt^AC|v(T#-9_Ajk{lDt&
zBJp2BUw$-ke6*e?*<A2y>V#{85^p-#GXqW(OEd|-w{5-mJoDAYeJKyL4llneC~cRL
zQa8~kBzV`Z7yR#)w5t~WX6sjDN@H!#oGV!z`YLkzlCbma*Ls3e7IKR1ylk{A(b=^_
zJj(a?niH?J?tL_9GThRhGDr4f!|EB&Wn<)Q<=0<)db=x*QEGbd!zdZ0_c!)TELad&
za(3eC@P`emS~6BM1p9ieMc$RH&ON$b^kY$2{}+!puR=5H-47@`JZDprkpJ-Z>?;0>
z6#b^WB@tWllS71eRekr!xtR5vg}s|OE;%_)P~^R^#0mu&_e)>9XFGmev(3-iLwF`z
zkJrbb-Q1H_$%z)MSJjR`r=F|wW9}`%?5q-o8Q#_fb5E2o?^r6nYfG*+mqgcf-5E@g
zCycdA)~|Y0$k*Y0dFqO0i8*x#1caXCU-a&(h<3hM&UJ64=lk2+l}__GhBDhNXRp!p
z@vd5vdQR}gxrS$cahvL$S2>l>ZwOzk8^vc>7FF`*tJ~S*HOn^{8hU&_I`v4x#pJoi
zw)HeDjuK&;DSgr7L#{zi4hQr0hUc2|f~HMZT7QCTW$T%cyNl8%|MC#)pSJqfanUay
zLu@ocyUK$)8TaaycWmLizw-Xl(2wt~uejs5`e?yx+XsdZJu}uEY*BhwQB`p4h=<~Y
z3SnI-!+kaz>z<bc3!Pe_H1E;VMb}Tc?>@rmc4yViom$g#lf>RiyTAUH#du=PWVZbr
z7g@BfuqbX{;HDMTufrPE^gz>l?dzkPI{Vq30{0j*6ba_u+~0Qpi`1k|b3W-A1THJu
z_bKx9<nId$mb#ekIZ%^Tsdsb9o_e$COuJ_CUi1~dVUZ;wFq@q<Cu^<Zv8v#+?{%0D
zobi0JuJ3qt{C}%C=WcA@oZay4!r!TVFQb2F)$VT!>u=|qZqREU@>S%$=$UORU*2A^
zW#V)1_Ljfh)AhbFF)o&KSrj3jFxlk&?v7BFFe~e>_NK{?4qA2oPZ6K_rsSN_f!wnE
z?_yetM`j!C?Wp)@Cpi65-VP<-cCloZHSWBp{?5PhxV2&R*P_hG*@3zT&gIUWSJrpv
z25-UdvV9jL3?DZ~g>;Ir{Iz3Jny{qd>K)%5dRMjCIz8BJoGp%4?oB9Y?_j_4o@sWR
zK_O#N#nB&6a%DqBZNj$Q+8g(R+2Y>r^sO3YB02w+wr^gP7G1fEVPgk>hu6oCZ5KXX
zVhv>P4A(J!Iq~7Qf~k#<Jq_1Q(E7i;`_`g8`j17Ih=ui}i)k@dE_-`9xZU`Xi{TCD
zq>Wx@6Ly~8w`<n7FHOPuYf5v!`+l0vRHgQ3tHe^FK7Z-<=f9_3d6+cgaIk{V<*z?i
zG%4SEId6e{<e|d4h^QjvG70-)<MrEW=BawWE00`gCb*Wd;DT7_?WXICvP!=+MDOwv
zJvfQu$GOgR4FY{48&Zo!LRz2BnVljtamAZ?i#{_d-wV0k^V;Kne_>S%v#$8VRdy<W
zBm}=YtcrfeW0Poe==MI%ZyS9Y*;yAH`>^!5#KU(Va<!xGSQ}5x+@d3W)7Q!T#^$28
zRlU6P6?jB)s@E=9tZunFcSY=O3%;X9uP?v<w4z_mYiU=Q@2$OQ6M~+cxbtN0nPcD9
zi>W-RFHGE$&HEu$k8S^s_6^|%Z_Yk1D>Hjk7vmaRexu6$KHuMO9qKQBcTF)pboAV9
zF8AWNAU@XzHitAn=Ux1FO><$T)YREF?RsKi_NM>3T|JI!zHlh}Y8TkP$?pm~N25*V
zLuZxbEx)(9d%ZUj?5lEqce2Ku>t{K8Cs)U<*qDn4uZOzuZRwB*Hg`>NvJ?GyOYcc6
z_wD%ws?oWpeX>5+mekDpz#p;X^;A918b$RIkqQ5O8DAT+$vE27s?AG_W=zpgRbTY{
z>w2LpixwW&uUx<AYyYGg8M_m=UvchUvF*<7LdP|7vxEfm8J7mxtT`_7e#U{T+xWv(
zUTjUXxNv2WKyUhdAqAHcDM}oRT^5U(C}baHwpmzF9A*1$E?-!2SMPh_wL5ubt@R%@
z&g`wo+p{kyG(zE>&QHk$p`ovf<aeIa%bRgUu=?rg!Xue?r<8^=$1M5Pe}9Eq#q6?$
zvrdODNDW)Gjn(Lb;|1+Dj&GZFu6)0@;`2GC0$=tYZ6DSLvt8BP>e?s$=828_`3Tc9
zjRHc!P32GBY)>hB+4BZ%k9$?_y}?ySq+Ppb9j9K1=i@oLMkZN%?`DX3#BTIq{VLDX
z|3%bWGs?I;s+;M*G3%7GU!)!$UQu!P&OCvdD@v}uzH{TaLhlP%e=<?4wNk#hcH`&6
zl7ZbJt-|-cA00@a#k$>Yb%SAY)(`*Iqgyz(*i3BrI&aU@t3M*mpT%7~I#uCp&$ii*
zL}w@Pn0kCL3zdJnbn;oDW*?<1ad&N2Z`pCrR%6Anp9jJmIXk6ueWp6hsLFSB*<`(J
z#Vp2$)3=*w%#6)Se*bL0-JX~GD=u!x|Jrf(tkMFZJlP&C+peQ4tc0Q`?Az#bU9j$t
ztoEXf$<hn{sUDG-fB!bK>XRjVzOB?RvHxl(+}3$+gO+Mr_(y+t^EEYI$0w*HXg!*;
zLy+T4-i{qlRm6)9-;=1_746uW*t*$}XStME;Y)2Fm(YNdUkr4#L^u5S5ypEl>s7Ao
zueL7t#6=al5eIj@jo<X;^5c%C>O(QXZ@a=jx;nhlIl1<*c~^tCf#0v^lNM?|V&1>$
z<En2@woYHtaCX(+Z(TfrhpjJ(3i5AQ(|-GXPVn07NbYORPqL=}6f6i_mYUIWn)|=?
z^Y*I(78VE2<=j);q`T8gO-4EA7~8uaVN+eTCxtTY&GNW(xcf+O`MxXZPJew?t9eTl
z{me7E&-wefhiCZ4y4j(H6NA4$ShH=hP_K|m%ik9ZUQ3(t#%jpxs#!cyXJPd`Fef&~
zT=_wHS8#&Rk`D3Wt@|BBMVZY!6&Iz?{}p2FTD$YbcIHzquit)JX7tWP)>KD3TIrGW
zqqXM~j&52WbkxyqL8Xi})7#JUJR5u+j4tU#Ev?a9^oDU(wB-AIIo`^9PjBw!wf6b`
zj%!&=_er^*E0nS_)=1sZE!}$ZkJ9v)O?f`EW}j=Ez2s8D)aq@|^o(V<PWrXd<Bf*W
z@(2219^t<ltacT)DMvjjd>myg^?S>Yw)fKuM3dL1Mfo0IzlCS|!lP%zdcyno&83?9
zcGxgG7?{ov+_Q`Gs5;Z#)mGI-oawT~`_jK0xMch^T%7N+|4O;5f9|A4`+O9g5FNcS
z<hK7FVb3~q;pWiiOD?s{R63v_WVCGmA}RBnBkvAfU^Ut1u_~i%tDMT$9c(vdE&O{~
zC8&GZ$-vfWCoZVRM1GN5FZrw3>c$<_g*sa@T~g;g@$GoG@=>WH58po#sXZ6Ahd#b{
zDD(uMM^jRpcD7)%(xoHcdUq@j*Yv%eX_>Ri@9u&3?p0?QKJ=eflJK_5aEi4TTfU@j
z$C++EhQ8ubuXR_$?yP7L+7cs?_OT^zWv~B&T#rrjZ!R{NBaty9=NN~UQry?e2Km!&
z$#T`ko?Y<BG@11%U&hg=xBl&!cu$_sR3jlp<H1y`2Z;*XYO8inc7M2`<PygcBhM?3
zmu_3RGNF0y`psXit+#t)rrf$_O1T|ds-WP@3T7u;xzzsHt?$>XTnp-Ai!LwcJIa}1
z8NC1KuGt!YZfTVy{aS4<l|JW?>BC9<N4Fgo{m3e=mu=^`p4n_-wDga_rGWxRm6Fb$
zPKpX^5={Ee)FiO}=YtPFTJ58r&5ZKl(AaO%vg~%d1y6kG_NBj@dmI()9HwO?w7*#K
zq-f!T9Xn>6ma7fn-Nmz8_gbO``;$gRuPNUr$NOosoxi}beYtPn_A8gIdUb8@Z+Ndb
zS6X)QjiVWRw=C7O^vFq7l+DO$S^TYkZbNW?S*@m=p6^?+8`+P954)7-YW&OQyc;+@
z>$S)Fr=ePpoMmoVp7J!@Xu0Z>N~pn3t1t4$AD_RKx}N!pbGyc|MW^OhRX878x!3m(
z&q+)B2OqC$A3b;?X!e>-;j_}4T_!}UURZFW@oR92(Sco$8J9G?ef6w```&Wy<xdZB
zdfTNMd-OyWEwY|1S+=T%{ms>vw$pBJJnHNIitFNA#kVh+7wuHJJG<0(M)R%ZVr<2y
z^;S9jNOfKLF>Hp>B{jcGJQA@ibF{W~hcexp+;!}F;PK#dfA`(q`d|Yu?}^!_>!k1I
z)uivrS){lm?U$Hhk{R>l4Nok(w&i>dWT|=cAmnSogsq}Ey?dVNXU<-f=<s3ro9hd_
zg>G7CRBhdPXUZcrvG7@`4-c&jJ0!}zHraH^`tY_ndlVnf>e-XI`giKBZ7tTRyDyj>
zoh|72N3SPI#r2Tvvgg@K+FO%;KGQRQZt=W-NnHlJY-+Of`fG0+f;21@`4-19`LFeI
zNx!?KP<CSGV$Fn!+ur={bN<ZquIy;`*<044XSM2{1ZoFYE?_WXZ@sWYgpZef=J%-5
zIE5#i>r5SDuAk@IcmAx`?~`pymb=(CsOuheetz#`nW%koW!nvgSF(5KS=nVC^_ZdY
z%uX;rb9us&in9XRO4_Zmoik>NwyxpOD9=gtXv$wV!STPi<V3a<#nswzn+qS@abF}6
zcfVIhwouX1?@L2PVt0Ahu_=#z(+z9QiWOgLcJ7K{+;x0{-@_fg$}!Vhoxa|4zT%R9
z`JUR24&TWtyKi@>uQ2Uen*Vo_(&t45Q^G526W@PYe4yi1K=KW_gI&3DjT2wS@}&zK
zSC|OC->W?LT8G3o{Rf^ustx`6zco~;ERxx$<yW5TaIx;<hU+csTAOD)(w#eZiG`5v
zZW$x@k1Ku|&+}|Itotu6pLRU9ySiL-<tL7mgWcu}0?WB(DC?gK=XiO$*Vx`Pt~mFe
ztKFxPnY%LhCNS{s;Q#Pp1>3Hf)!t7crbx7;%UC^|U?*V07Ajr4FVWQKR{X1)qW<^K
zGM2?L%-<ySdd9|(dyj55%~Y;ldj038OhuRGYKa9K6<5>-TJ=xr3P=ffA*<`MaO=mK
z%b(a-=0~#Ww|;3|WcqcZdeQY~=cRw}h3wJ1b@A#s4QGG$HxBpn7A$;Mk@QMtjhK?m
z@%`0{9@k0ys@PGrbUMosU!hGp^PYU|lwmap>tKo7c{ni6Vh%^P`V@_StW%aAz4=jW
z$%{k!d%BEX2s(Yu&kYMPEB&;fdQC8^z71pH?&Wprv(DNrRn=&U_I2{sP*<9hExOCM
zP&=fubW!L+$qwEU_QO|JC%9T&cwla7a9BR=$EnM$60c6WWX*Z&B6W5LtA$%tf8&x~
z#qSrE@4R~a`b?(f33HZ&ui?CBAA9%GQzpOLEK}s>)h}ohuju5x>gq7P^77uA&N;hR
z^N6k5At3nP>*}Xktxl29BVF4boxNHc6BYffWv<VW!>(=eTt30?S0;uCeY_Xl6?(G5
z>9Bh=Bi{|@=#Q%;Sg)KodcM5snD#0)zn&9|a-6QI+X?u{31%I*bwZ=rE|%rawfeRr
z>y25hFLG2Y3+R8cDC_@z?GI(oXO~N`@$FG$+H^Ph+4i#&RhP!BTwo@Wzv@c;^M;ZX
zwwZe$CCX||y#7{B{mbE=@-?%1WtW{@yDR7Zy@j!VcWX0q?#<eJKF|1A@<iV~&sohM
z)b!s^`Dzm)_V0t=eb+4wGbYS4dh79jdf$<PcgaVDvL-&7(HZ~woxCrX^F!~`t(nUT
z+>e*Ed=|R@IOW#eZ_!z+(q=Ml6yAKpF!25<r7{)w^)ZtY+qN@B9tvEuR7*ghQ{Otn
zZ04_-BK_Pu?y2m({-PmArnB@~G&fUA(GjDm>_OYkosQ}aNwYn*K~yQN++y*ed*7v}
z{k(DeoJ)fBU$xmQQ}<@K2E}<=A8y(t8a}}yB-{FO|8iv!-YGHa$K#gHX??XV;P{T#
z`d1oJ(={`N-PQ^6+XNq3{V4ic^2Az+by-z>>*i0LfAxI%o$YOp4A*EC6?t4VJ#!~v
z$)u3nwMGs1_8%zg<dAug{?MiE?%N3>FYQ?G_%(4{Dw*UPEz`7i{!PF67yWJ>aM|<m
zTzyc~N4w)8@&*M4zpR&JcA1BmC~98Vb1{E9oBp@_T|ytO6lQ-pbh@h{cyfbalqr|R
z)~^~nMFmPbepp{|;JU$bqSbHlB^K*Q^=-lT7CRiilu%xr=VGHB7_{nzy&i+pqf+r{
zb0$6G(YG}3FW~y!eWc*W&jWogeukMvoR85AW-nG2%kW8goG!aD&Z2dCNyZTs_pc{b
z7`SW^J-?&6pwsD`oLla%y3?O_<#R8&mAIT;_%{FdXDe49luHk_ak>1g?7B^o!rg`a
z=EqJZuKs>++BdZ|hUbq8%nSMb_0zmBDX|TI*h=5%cePHI3iqC4q~ayQ%c|tMdRwpl
z<y>ixjjk(i%$il%{CV3CIm`9-vNKBlzq&Rx>UWgInT|zQ`i{MDe*3YUIoJR6>mYsM
zn>v#J6Y|&36trOXHuu~9b8-EOQiZ993J;x{T@l^t#5#5JmtD*C6*X3Q8MHl@X0MvH
z?U&p&HYv^9H&|CK^eq(jQ9dc2c)n57n{S?8XWrjipKq>e3x73NkW1NG{i1KSnC+rB
zb0@PL-BfdY#?>yJx0X!V5+9dIisu_1XOi_<C9?izve1JG0;W5h&9<)$H%??*tIDeL
z%uM!5)_;=#p^lo13_mn8gI94{IeTvx*Y{;`j;-G|NAcjPX`xdTZN6yd<VP5CJ-cJm
z!Od~be95K;o!%AMXY=;IS1|jrSus=O<GpVI+br8{6Zr0woHd@Pxp~E0&bbaJ)7Nw~
z%eif74nD&?EjBCWmt+E)n~lVQuIo80{M<p+?~7Ek_gMtLoG@+YqrK<Fm%ehm;T<(O
zcwLF%<%uU|v?mIDa^1K@;j*iA)uQ@BnIC$!opW=w@4ueze586(9=~TnUQ2a;pz@??
z*MFa`J;JdlLTt`onZ=VcJGAC>25oIE2x{RD41M%<lGf7G$|t@nAMvtXSn0VZ{9xuq
zW`(Z3?P~oGetGP4*^@i>N1s^7j0u<5IWi_+p0Iy)bKmLBrgpC_qFOe%UcKt@CjOJi
zRUYlAz^2XT7xT!yi)yi6HrMG$h}*Ysp%>%wXOtfQ{E#<6JYd$wk9Osk_k5b`a>#hf
zJ)Nm<F3Z+*&g0{le#rFqy11%Y;UE31*m6~3I?{D?=WVqOP!xG9#h_nvIqCN4w0%a?
zE+5Zk<8ND3+;aGdOBLVs<)?WC4HP?V_8s=vQWJJyV&y_<P4BygXFfTszq{znB3=W(
z?{67HbROxRw}}6Eeb-~(+W`u9l&YH)7XG>Xz{~f{bn&bXZnm0P+tZGkwMe_Ne|qXS
zS2@ptT{ubg*a2qO1JQ5O?(E9ht|z17zQo~)GHZ9B2CG-EMf$rJ*RH=ir5j(j>>8sS
zXP3qDH36BdH*95B7u?<=cE0$6j!$ysluJpm4HHZY@=vT5_%naYyGI<o6JDz*XL!X*
zCx-3ZeXe%TYRLyTlWR^t{xI)ak(GE=rKyq}r^<plZB4T%-Kw>v9jq41rsQe%@6EaK
z<<+C8G`95L=NGwd=Y1w|_15(j6I{ER!c(uF4esqx_<mh^TB7)pcUySxxT~aJ)C!58
z!`_|4DVh{LWkH@?zUX<b+c$#0yUvx&@s&T&rXBp-JMVK>3F9n}y)AjM0X)xgCUQ;;
z(-$pU_11gUtmO(FbLKyE6<~kKyQh3k$1(oJlb2PvvxLr?xXba^Zl*1!Sy4sPCLHdo
zIIhw-{XA!Kc_x>ZjAX%{9of^_j&v;%;F|AqO(0tM)u|sk>p0JdFJ5>hb5)j!>tt7U
z&2wLp<nAqCaXT^7Z;{1v?Zk)vsy4!V*8k{R@%L806UUTWzW-~hU3jmx1tr?3Ox;)2
zGkx2x6GiV0w30&hD?5CS`oI%>Qll+ZYVW?H10T$m?Yp#N>PP?cvzPFHte2iPVb=GH
zF_+3*(y#o9a5(&{FD{hzOq<D@iUQB8er=1U?VW#WLBwkJ>2D0x&9#@7r~C{SQ)rnb
z`H(F^ur_LCQ_B6>$2P3rk}LGR<7AZ1S3frKWL}kXPuwm}mk+tLSvk;^LE&vYXGEZ?
zgw!vyUkahu*46mW5-x7DG<<#Fs*jNFAKONi$Lwxr)Uvw;^oztExyTDg$R{y8F3q^@
zYyR*0_oLgy^_)KPNnhDE|9@HwtMEdeX8Fv`GqfgXh0lqccbchly@|)=+%w9v9xs~v
zC73OAZ<+4SPfUBVO*OnaE=Vkp-*)L^(?K=u6>nRdB_qo{8&1?Qvg#b(uJ`}S`iOb5
zTi$LddU)JAg?E3~4{zJ2kJE+CB@!M^37n!LwCK@`S3JzKyPTL?{EXWcFXt2gX1l4%
z<&?X)gr0=gb1zQU>4JstukW-h>$jY>>|<hy22<L_+jp-`&T#0dxhwDg^CRcf|5-D#
zGy2m`1v_2Uj(ew<IiL59nVm-GK9L0%>P7tPc|M<F{_v~YaAId#ex`5rn?{|ept@sQ
zb6%R<dgcE3d;rUT#l#J#4_OPV-thT;<^6P%V?zAbn%Y0F+u#!tbMAUb_5KgrOD7pd
zcdb}lbC2sreCgi1=c_`T1shbhNju*Uc)dc)Uy9>+=0~MxFJ?^8{^R?T$G)E5HZ#jG
zagq-2>~5dsw;#A(vgnCYPFlSyut4_nRiRZ2_DlS!`qAgPYU=8U(y((mPG1rfo=x5t
zv^{%!4mWGzwo{wA;>u2Jy^t%Uy(Z1Cs4wDv$Cb#XHA+3p7uQ86zpmX~vDRcwURY_6
z+P+NAnB-@|AMeR3{C0a`@AY?jsYBrEKK+yY7M{5geY{C)JSL`P=d`f4zt+(@v~t2-
zn`EDwmNgn#KOTMwy`*~TmeAi@dTq<rC$?*}@49kGqv+Xut&dgdQ*QH}xwf@z73=AH
zvnMaiI{d>q>D`I`tW73Ijy+%Bv4-{k@k-@{I<-Mo!5flbk&o`=0LFcd3xKY|B%h
z29`fBmxiv~**-brNKTVBkA`8a;p6(Q8DI3bCiokMie-7pY_mR@{KD<@E`>XZCR(k(
z*9J-*bvdH5$ReaICsc9vfjbk{MOT@Kzh3${QN7BBS4~vS?&Ly)Jk}%6)tDABuBuDD
zdadhz+}j;WE4K;mkY?4nnc#5DZ&GZ;57&6>9cMqrg`at*tn&8O$~{X$wG;OGxUH2^
z*`lPPYwK-$Qj9}Z#?Vwdxb|(qwwbFZA3oI~ZR>iW`TDvU>bsmy?RV2UeDm0wsaLPF
zJuwSgrMO_(jBWi+^8+5Aza+EXbMd-^?0xTl_`N)DwU0}%piyh)yx>i5c_bpkoi4j9
zZHry{s4}KmvO|wWgs*!#pUoZ*$Mt%VOJ2lWIF}kOD)sd4qJ@{w73j~MbmJc1-Y@p4
zE_p{8-gitWIktA<JogvelIJfLKIpnUbz)}J$?4MkO$s|TD`&hq!gg@6+d0wem(qLM
zR+)L23NnOT@$F8#9k{o78T(F#j!ur={8qK?JhpRhOxFLn?TXG6{_nxLkA>XVJB8(+
z%n}e;t1mzK%tqrylZtDirt~aW_Ei7px(&;ibo4xw7R|_M+w$%BqV<C2sUHQzUw&TP
zVEn$Z++)?TM>@T8?|ct(emd#u4{N34%Y}?%p8x;rZ^)MybUS%t&DIdZ^Z*Z;?aC=x
z42kL&_bBUr?mafMqTbXhN-$`d*ohV5+LCu3CC>VK`ChmF$}8J-)o<#)_vlSk<^N?A
zXTI3m@Y9?pk5x=FtL`{Fe4XDht%Eu0tB}R(B8Q&~oKw#AN7zQMzjDLwvBjVIiw+{b
z%;t9KQ>LXA9S(YBymjaAZEOBEao*WfbB{Y~tNDsxu1MpQc&iTw_*rXb#J<k_^5SH6
zVX@}DC;MN7EX`rq>U$*l%JR4Is<-R}eirXJvY4Ia=KCupsVtXGM4FY?akHJgsL{+f
zEAN_Cv&xDINt_}j+q#^yJQW)>`h0jJv-AHyKJ?e8^d6hiqLtnMZu0Kr?vGxu^^};^
zWv-Rd4Bc7%$GXy*zJx7j4$J;^eU|#2kojWUMUpE#Ohxsd?bx5;A+_*iim&djt$kCZ
z)Msmb-&g9t{e7}bvdH_tde<43F8Fq@CqYRu=lv{Z@%-|bSXBdo%f3H~4y3JLx_zc>
zVA`_emN%P~!n~(NaDSht$-L+S=d?}V+!r?Amr#F|7<v3Y|Mrr-fo`&b8+f|)+IE@0
zZq(cSXko$HisM<w#RZZCq;~z@@#o9y5Wcr%Om3M{jL|)ty<S9noY~NQ`~RcP)0T(2
zZhzdh_R`mCt$7c&Em+p&(vvP^8(qR#$9VmdL%EatMd3v*@{G&X!y>%8<HKzC)(QqM
z=O~ns&zm;)c%{BsQuI|Bp0)tPbL`gnvC0$ng?*T?LjQB&{QJIV6UzFeSn}t~aNmFI
z@Few@Se?xyZT>AjiL92&@0~Nv*SQ2etYqIG{>d$nv$zpH*C5e}?1P56;@nq0J`(
zZ6<uUxOI+3iUa@el}*ue;`4Q7=C*EmRC;o~;;B%_w4--_s3iubY5f$OE?TT15q7L6
zO>LTgq2HeQ^KyRfc;_Nzd%0oz^bC%eO&adXkLGBZUI>}&fA|gCW}%B-<|d^w0ow&$
zeTbbkan9<lj^@_14<5~)E8C_xPEY#2m;XSe^^ymRzMTJ7uPCe;vcEk<cF%-Q96@|%
zKQXjE`t|*j`q{9B&hBTv2bi5IGk*}PRBW{*FjTn4r_HAB)Uzj27w;tsY@cEnE_z}1
zzsR>2?UngMnP;4A*uC%V4)?>c&(0?1raYMNH`?l4kf6_*4mT@t(YXnKR15usmDatS
zp0HB&V1%#Oqt%?>J8cu!a@|m^G@0;a{rzVjDkn>Y>pyt+EbCSJ#a|tfOu2XTbnb6+
zQrWuY?75Sc$_eJ-N-0yegiTKk$hO#{k+3F%UBvINL}B0kwl$x#G;IGhiR2$=J@)7p
z*Mk)~+jp26xU6ztwIu)iwR!F_au1K1$SS#6?)q?q+tt8B;-Z^N+54y)3WpXxU-0>h
ztimKC+p}_91;0b?oXLIrN@9MrIqSv$F)M}6-F2Mzlbdh$g<RGbbLHl5YkHZsUhVS4
zs1}~3k1vNTn*5VHh|%MU;bBK#L&*bm{E`W5r`$3XB8%83gl7jC-Td~FWyhN(6BDod
z?~N>fds1{u$U|<6lq9ZqmbEpCi)$P1g{|2s(9*q?`FfW3n$#Iy`&zSBt?2fiDyDq*
zY0hHlsqCWK^FRGMI&b3M^UnGY#J?o-G8f!3)?ch=$@{VXOmE7)hcmX`=KcD2`wW@)
zKc<-T7IPeYzz~0<PiXeRf4Voc)+qh0YEmkd&o{d;^<&!aZIj+FYgK<D=i<WZdMo0r
zrA_VD6vv&Gl{$ypQh)d4pVfQ#vrO=&WbdNI3l!BP+VlOzUd*z)sP6D`K7XCQtW|kd
zou7)4Y>A|2;rCykc5Ypj*QI7D;$x)rjAQM!9Z3(?y8F!X4NIOa)TnVlwZ}%wNrLB!
z&bG;);*6fG`02R(fSq`4m;K4k7k7(H$~oVhO*4DH(e*WVB+IuYe|2;Z?BLs)GgG^6
zsr$ZL+xGu)p4S-?a$MzVrgO@bE@!omcMlxjBT}F!Xe_c~s!5C|i-G*c(<i_3tpE1m
zO~9F7S0{MO_Byv}er?JA{r%>X&#b-C-R~<Vv~O)<)(hbj3D~5vW5*U9h2!5RY^^`;
z*!}Kl<})`RpPr_GmYD@l)*7pF_;3AYrKfsX@&3n$n`$(6vg_Eys_pKpWITRKKl1UO
z6cg>My%Yc46W;jEqcdW{vH$Uf7bcW%*=E?H@Bbs{!=$?E^2E6P{4b{n`5#vFaF6zU
z+u{7p_IKB^tEZ!5&dbl5aqMu&?hX5Eq8?O<+;BD4co(-n{wQCGV%j$2(7q@EE(gOU
zv0oCb0z!Z7HHm7;kQInhPMZI1JG<YaOFN%znHhCA+GviqNKsVIOs168U0lY=j=OVb
z^F1;<W!sf*`*h2NYrD1AFZH|aSm<PU^o>H=_w2iQY!|HG$NO+{IV=yn**VK)jqI%X
zhGG>re_mV2bFe_7BJtgC>z>(+`xdr8o^kkmrJvn%&g;fUMLs)Ti~7@i_pJoqS-;e0
zK5Zv%%F9UW794#Ot@r7~6YeiN1XKdgWb>N7m>0kFYRktNFGIF0*C;QDd@P}`+QiH!
zER^Hna{phS6n{RN%hD7oe!4{Iv(im#{@t3~H;QNO|L?jydui>(fY*5sQu23%-My#8
z`t*E9Cu3JqSB$&IcIMT$ja69R-MjSpLcmPB35kDaX-;=|>sH@%b$vs5#>WlCTN5Tq
zn%zx_4CH;#>%2`QCSgbUzH@yB;;GA5Pkc7(ecpyQDw&&DP9<o{wzFu6E3T}Ty=3wA
z<P;CZ_@lYrw=QkoBR$E|q57K5#XR-=Srd&SZ&@GjD!8HaXyPXR!%9D8lf1K{7tDTo
zcXjIO&z@Fnd^aBH)!e>1%dW%r_^F+p=XgE3C)yh^I6YYS%J@-k*qvST%<Q<74|eRB
zb@z&Z$mtF_o1|V{g9R@;zU*66_kKxj)Qw#3^2m>WuP6$1wC7CA_V;(0DpGhmrSa5p
zcL(wFuhxbLdRl#8i)UY$FJI)z_Ao+_WA~1v&YV2i<HgS|&hhF~`R4NLUB=<FAGCR&
z_+_R{o7{8y;MJ-xSJvNo_2E$Qy^m!ZMCLcFU)eA6ub-=8?M_kQGdW7zHPrML#W9wZ
z%wo+?s0>J$_s})OqhoGio1kb#$;-co8v+ij-DqpoywhX3`nH&Bfi3q7T{j+53VzIT
zOv144=H;h1d;d*S3iDK*D(ZK+D`P>PgN9AriSS)j(;{D-`jZq=GJOGGTj%1h)l2WV
z*!war7yPkdo{m)?`x54|@=51@AK`kTGGVh>G}GB)w<TAS{Qih-3i@}gByju0$CnOt
zW}Ln9*0lNd8hx$xMH|GFYS`yo;%&TUv@$D5f6-K>)cKaPbJ_dWX<l)=d&=4UPS%UN
zo338bj=NHwnwq{KsCCo&!@5`GL^rOAsN<Zd_1A5o+KrAUcAn2dGz9}{H_CMx3Vyg7
zZ*}>!8Sl4Pt9h00^5R<zHfP7J5PAEnXO<fC9Fq&*ma@%nn`QUQyJOo!zVHckcQzkw
ze(>m1WV6G5w|Oa>1dW=i&BY2gC*1DVVrX;Tp4)NuNVlCfqrH=T)9EW|Dx7<}GOnqu
z>3pmBdg}$rw`P;s0-t`$t2wO{r~ShH`;nCQcNhG5t$6aR?P1xVy-o`+dTms7ym?t>
zf7jwXuBWA|Z|v!CDr{UgS&DbZ%{i@=)@;kPl-5n1ykB*1YD6B>)=RrewK+>Y7BkH%
z6k%Smb|L?ZCr1>^S*|_%7E&&?{q&6q6CV7X5WHFKRqo`e6CR31_8G6TO3Q7lIB=_T
zhHcGXr6-d%9jw0iaW|8X@W)M@jd%REdC%0~KKr$A=39~WQx{@6B&{BAQ)*W#kZ8+2
z5Ph+&ro1gJc(2EeZ=o}#5|!u5cSLEuIkNm}?&@pP*W9vBTI{?m>s?HE@rh?#HpXXX
zAGx4r?R{mE)V*!05{xIGZ#d&9v3Kv5+r|qLZEtM|*(`nB&QChQwY+_c7Sr2%Hv-;A
zNnQ6^rqI-;v~R2Mba&fVGZyR-J<bqyB9E<Cck7%cyH@_swbx684{ffRmF6^Szq$Ip
zpoIrBz8K_w*<si4m7VYBUcb4U-rwhM{lYC7d{m~)Ygq!5(+j(o_w=7MxNdh}5qvB<
zQ`oD~Pbg-pQiAZ7wdIc`q|OD|-@W+n?Ik`&wV9cBRe2<23U`VceD;16xiF4R!Atkr
z1(n_-A6H~vd)RTzEpeZS;%|?V&FvLEkD@;s2fejkB$;cxs;gs1D{JDeh`qLAd}e|h
zqvJlmz5Qawp5(nHGm9^Ehu`{GwsICrvSc2I>CMR;*38PXE2p0-IDGZ}@045euR~27
z6?gtBll`>l!kgRjh0|K@D?bofuVFPskk4!FiHojA5(mSCf4o$^<lMwMLr;2Z_>)f^
zQWHepr%k^Ydi&e#mp8;;<R^a<h~MabY5fF`AC^lZtA!6MHX62j%n<nHC8z9e_L99L
z<c*t)X_C2-WA~W~^Xckm4DK%6qU-*pQ6%q<jPr_A(ekEEzoz%^oZkE~XA6Vh_9N$C
z85KWV&?%)?^KeUH@Q-B-drr<RTphsh;&;dX<AEAFDOzfi!gkfnP`o5w#JV|xvz+tj
zxfi|muO7}{+7WwgQp#(d0;TyJ#X8St9op{Hf3dMRM)zug#J7c8*QXtgU8B+^)p%-Q
zquZzcvkj3V;diCl?B+b-^6XnLAN|(F&{D5ecH8dsqZLOw-fX>U+q6rHztd}eq_I(q
z6hrpb{t1)5Z&>+IZJCJVizZ2(t0wiwE>~^*&XIX0>g<fz+J~EY&N^kj|Meu2tMbja
z!sICnCx~B}J&nJ*#CnN9>g39ff(NT+$Fof?cMRP3Yg+n7^BZExJDv6WPF2Xt|7`fg
z6HxoQ^5<GVhFY%WX?$9SO*_T27qZU|-2eHs{<3G6+Z2@#$p7zqz5jOnCad*Ko1R*J
z);^Up<+Go_<&pzzuhu1fQBA4+xFcI#>D$sYXIX8XBTG6L@Bb`kdr9k3?Pl`}lRn<~
zzBkBRF8|CNkqZI;7R=Xp@PYHc*xdK?wl5a-cfA_zf7R=mvRB%X#*#Y^E|m$px0m%i
zQZ<x$TiTu-`h>$`X;L}gY<s0^>+(C4H@JqX@LYZQ^hCqPE7NLrTc7pHQ{LMr@a^)X
z!mUj0At$!-9S>*<;JB&r=(qQ*j`_;XyUI->3g64IZrQJ}O5$|ImF>@unlTk$5j`hS
zchcY0;)LBq*BJhaLoWVHY|fq9ujE+0_x3VRMIJWMnTb-FSNO^t9u-VkW~ng2{qVJj
z=UqFl809bS%bgTC{l(jZj~rz}XK;U95^BwMxGlNrZT+IBJ-dzsI|c=9ExDcbPw|+s
z$VE%BXJI#)cNx!;ZZCFH3H5GU&@NEnF3^5FB~_!St0Lfb$dSY#tA?`V#%(bN5`TE#
zDr@~5=rYIkZp8{YvzHpvTrM<P6+AS$Z4-Nh+k4dyZNJM++5X#iK73|zV#+#eF_G2Z
zr#%(YbGXNG<J~X$WAcK50RcyzHB{W1aX%$rQNw7}(U-DWH}@RTi<CAy#IbMxF|EB`
zf1itbi0RDCs@~`SBBozA{mIj4$DeNftQiu`nhEcd;@lQ*{e8%K=hi0)pa0!oq;~1@
zjeq4uobw&5ba<V#Z*4W@HE`Xt$^F@ju=5&c@<lHG;hK|ZntveDGuZNilvAqsZ%h9i
zg$|DC2c5Jx*G_)FWdq~c1+JHmwsnMCo&BTr%w+CbCDSLps@#T4ezWUV?&i!c)}8Ze
zt$9f`lSJIx*A3HFAKSlKV#aRM{1?uB3uNWiMt%xDD$Sf$`eugR>gjcU3c+d_0egd1
zBxe;JTyVjBOOx4;ti20lBo)7l?`JTb&pK(%jxDof=5F{Da&6!CSBV);uWl>fOL-%C
zeIoCYT~hg5HmmGtRVi*0zAZedbAF!dU(qU^vyA=6I3kYU&g2V~XVrQ4sNvEIZ^q~B
z^72JB{QS<WZ;m#-Nna+zs~XO-<uWsq=Cr*p3O&!IYDfx6zB<A%?MvH_7fYwcrL{zd
z>$b^hE1pYfNfXIC!CALBE+u63oGP^$%8?sOm$P*|U-9wOsR`4B`BpR?577?V^ZtEd
z4a*<-wG$#9P7*wN^dLjd{gxeHGOZoXUU*jdeB$0JwzAn>>HYoU{vCB!mV9E~wXn~2
zyOan!`^g!i-*4@WZNDIBIBDWnX)d)txqn#S{4-CSto7jP?1$c7r3=6R7h4hfGU^5Q
zF|PPeMR!A1c7A^&W~CD-8=NJX<6!NcU(!}kwq|bBna4BabiRChYyX~ujc4A{#x;|j
z4;w1y=p-&mKVkZJMwtKY_qhuempwTg;=*|HfM|hAW7*fQxfP*D&mLI$o$<ZcFI6A)
z(qL~}$=lZ_On24{^53yqzMwH6V2_@-KA+UZr`8IWY%YEgnDO*Qz>zYIM|+#sO2zFm
z)iDbb+ju$e=Y>F%YsXG6`Ps_%avE!C#Fv_?D!Wao($)gIJ@)R?lAIsZl6~}>!>q9U
z^~Xh+?{2-ah22GzQSk6(siU@cy`TMxW7d2Ty)s<$z3g@oK9S(aC0|~9zbWCa`JR`(
zHg&x~-`8y09S>q&@0fT_EvPw@A^q&?^7mQG3l~TTEqu>D`C7mF#C#i{I>ozrm5&17
zD0M_m*Im6~#pR?(x9kM#V&kPdf=siI<t9xGUGggaZk*)0l>t+^SRPqxt^Iz-&^CC_
z7was=sS*!OzB<pX`Q5Z$>!!NUw_ktspI>M9Qh$GW$s8YZt0Y<TJs-AQvh14B@pjII
zzRO;QFU0)0)o+Hg2$W1;({^@&kHQY^B5s3}ze`t_{Wvr;QlE)2;bRa}a>l()JKI8k
zDDBz4e@gh>eLw3`+BSQg`fY9(7Qao)vEr7MlV7R#xwn&QRCd*`TEA1RZF*;5oz3sU
zu=?#SC6mkBb~Ua!xb2IC+lkA6SQ~=>IzRbd!n5|n{LYFkzqaTI9=aTLbEO`evERp4
zTIvlAW#2d_X6kZuu2Hxm@?&0s(Dg}Q5BAO5W_16W$2QUPm7luP8Fb9V?xxOMww$A_
zKFs=JxburU-o>lpTes{tm{XGeWJh^d^}Pi%`yT6_zP|9B(%Bx<nxMt^Qm*u!4JnU#
zx^d?EThYu0SqhgLBD{BPy2a6cZsR6@lW#S<A0JuGnmkSG*~PP|c^4lZOq_q)^VBDS
z($Z%NmNFMM$Q=q*jJ3@5N_W5Q_TTudRJq?HolwWr)P29EC7!W9aM!Hne{%sd_ebxy
zcAn+B6)eZR%W@0uyq%(`?6@G~dzDkM&y<eY0T*}O=wn>GIpTL-)TgsoCCuIXGct}I
z<Go`e#X2oz`=^~YJ-p|Abf+!;cYs4@+b_HDKhIr@kISWo3-!HkyxK1HGWFyV?}{yD
zJyVV@b<Y*t((<LI<4wj!nb*8iKQ#4LJiej$ZrMBicN|^eyTa1rn`SI3*E+n&jyEdi
z#-q&diE_)18tw8b_;K=3;gmTmCjLKuo!K$LB~w4>lU~@--g><ci+q>2DW1DycskDQ
ztnQ3cXRf@toI2H^r09z7950a#+2PB%ZuVrZtW=jU(wnkn!=Z)l;`NpmJYDP$eLpUf
zI%z7>s3e!0cT{^(woXK0)V)MT(T}?({Sn-|-rlkNtCf0E_n)_tS5|Ux9K6gw!@_CG
z)+Gwfefz8S1?R5&Q1H2~YNK*&{n1tD7Nzaq^L5f6CCBwir%qZ=@iO{#ukk5saZ5mQ
zie{ZImrm8<5ZlHD`W4Dq?k9JPoY(SQa!Z6m=I9#Dm77v4c`PbVm+UJ@=%^@25%rJ#
zae6^;?C+IZgxB*j&zs3GW37Siq^qUQ#iA>ou~sSirz9|jJ>e5_NZE6=;^`~KJbzZh
zV~31pK4Z_xf0)M3`<nmLu`gV4KUE~^do=&GO6*x#ChN9HFFHd~EBpPn_UqPKwl6kL
z<lV9Hq3oU37c(-P-5sKuoIK;J?H}^4|L!^4yXn;fqbD&|oA;Kep1fB0)$1eE)l=4U
zthY3`2R+|u^Xe#ryW7k6>a0Q{Pame*@y;?7>^EyU#Oq!7Na*#o+t#N<*Jn;>J#p9M
za^gwxVx!aB#GZb0-zW67zI2uBvemDTe%Sl%^&Bxz=l9V{Z;z^Vym#(A*M6j7oAqnA
zgJ-_F-b{SW-F?MfZ+C9u`4{$ww%%N`^N_@a&(%*SR=B5F+}3$-5O}Gx@Tl+89oyM<
z{_d7OX|(^W?iw~5h0@#BMJxKY&+(F(Sm@DUdzfv_!sFHZuN2x`UU;A|<Fiks;peX|
zVitjEN3XA5q*2bIy*DE0`Pz4Zo6p|2z00~#`r|G^xo(!-E6d)N<#ir0%loqKdH0E^
zxkqK~Ufj6PthSE*McN;hin&pGJ8X{?c~%Pfa6IC1eCTtoi~aO<j*fthea71>)q0XG
zH6A?JY`oxigmY2(3$B-p?Vpd>Uiw;mP{@8)p6!C$VG|GAdD^n9TJr4gyt)AG=i!3q
zd7tK;Ua-;jYfo4N%bUs?rhlDJHb*mvpL~*G@F7)ad5)G<Y<4Y2pPYGB+@3j{ep@3o
z9__h*cUjHvz02IcS})$VN>`M>R!?yILhT$?17+Jc_bv0SA0=OLK4LuW$&Kx+Z_nh}
zzD#M-nQwouZ@YVSg7vgZm&2s%6WfGOM%td;?##jZzgzj!o%}|rUEAI!o&9>nMt%AN
zWuL=|?m0)Mhf0T@ekRNKAbwe<duk8=8Qp4c$1j(@zx&s%?sGik{+h)rpS@nlEpuQ}
zLEH7++$~zM-|xLi+jehR;7yT;;@I~B`;=tr?*6^qFl*tij-!oHYd@9uXidC(P(0A4
z&m@%Nk-_(8=Z;FfD>RJye7vr6X&9f7_5FXw>G#?Uwy@@Ny~;SU_i<8?&6lF9EP~e?
z?<Pp!QFT1cdhK4jwacrHcF&{R<65jV&Pu=f^5}bIRm_1qC0RQXWpnDCqZe-8_Gsy6
zvE6UBuYL9BTi@Sr9xd0!^$ty0@Y}1i$o#c~?`@R=iPh>Kw;kNV{XBN#1u2CsC#E;#
zocyY~By8)RV_VOQdjIWSaqzcL>(<3*U$HFXvfuf7+mG{HFP2`qb*cB+t-?3DDbF9h
zv1GfR=#v(|c6ynYLVrb@(pi~xZ_9(N5+-+9g+*uGak%{E(zm>eF7D}9pKkfm7ob|!
z=6gOME$3p)k4LOCS}Io_zq{qRNWRC5Jm%iQ&QKkz{kvNB2vkjYE~v0%@$18@dT(sJ
zah!YhvG*R?FFO=Eua<L(>r3gd&c3wp_ME0|?`|?z^zK)hx=di6yJh&Z1jnG#L#yh|
z6E@bL*U0&8eLk1J?|;MBwbPbG&i-;wu)X23&dG}Vi95svGc%8i?tJvx#c$u5qoxxU
z{r^@gdg)I~vxwk92hB%epX(00U7SAi^ixhIQNfLs8%&*(Cv+rNx@~(QkePnR`gy&$
zD@#oA?Ik~Utyz{Urn~n0t+rt9j%$W5U0h=sz2|JZagL?vjp)^2@rPV4ul7GEe-mRC
zowfdgO1YEc2F45L#2@B&SBvU%@^~CEzTZDPP)>1%`!V+=GW#V1RNpVje#?HxY+_Zk
zD-Y8#b2iySv6nW@42_oP={}*XUu$t_x$eU$YBL?56gn`w?+bdW^22%8e@;Fxc|k`7
zR~OyLmzPC^pW6O8n|A!t2L8yNye&7vPX7@L{9d@@vU$qF^rTz1ZnO5Csc@O;k*r_O
zYnc<NZgM<1U`@rN>y5{I&2Kd(xg`CWyXRs<@eZq+D>14IYn-<xdALql8~UPR<LAsN
z+A@c3ZFK8Tu$pqsQb;2@_3TDHZqAOZ37u7oQk5MiRZQek__j~}@Wc3$Ypok^nP&3c
z34bN{WZ~Uz-s(fut}9<{d!l-`_<F19nntCh%RGz)SGNTJh-TxI3Ex~WdCjZsb{@S)
zB8#7keLBygRMK8LXIc95MN8K=C@h)MulGBx;X#PmjgNBP=RTXUmP;<#bfDdJdb|B4
zvnZ#ey~%6Rp1<}9zP>w?U3jm}+wL8VC3DOkI>fnHGA(|+T>Ho0MfXm#t8U$)zf3G7
zBi42QcGHKtVskjI8d!HPlU$X-l@ZKd6~2ut`h~8*$G<A#JS)WVzc)-Xer=_@=eDY|
zp<!{Cb)eMMi6#EuXR$Md|LeNl7IeURX@XR;Ez`coOH|h1EZOrtZ}~M|{W}f|HIF;K
z$xG>FIpba0)3}v6+$Qzs>DMB0T?f*Hx5cou=q%J;wQY->{!49#S#q)aPi#|Okjie(
zIf?u5L$iAeyq6y770Y!n3GBTZHUG9U=L5;?-8xojY>#Vq&DG}GesWgFR`$(-YbS+Y
z6N?vVEa=Prm>N)ZD%Nx}%g<$H>c8Ag>i$m^2)(x9$J|G|XRN6;{a&-)?|1p7U!u|i
zA=y)mFSk7XaP>oIk6A~O*~(gF73KA*A->z3zDWjkOgy5WyQ$YR;@QG)1xM<Y=Y2nM
zDWO>ZC0pJ7*vbPOwo^JRd<@#BuWe`1|7u+RY%l-U8@ueecCHi(<gS|>^WvU{(EK}z
z+Dlw4Y*+typwu7M@c7vit@)35-rFlbZ*O^Z-!alAHtS|U{^6b&Bd*#DstKH5j=a9)
z<bF=!@s+xo<x4);ua^s0b#SA7y<0_D;JyrxWr824MT;wa`sn_C#*}8U*?)GZr#LR(
z&b^$qxNl;`gH31F-n+eiiu^}ohE>OZ9-aD1ue{@9QADvz=XqNnE7#2?(|BL4S;gmX
zoIBO)!0}frgFdd=$n^h8@df2e2|?`>Heb*AU7Rary=wQ%wYSxhI*vAFC1i!^YTr08
zyWnmuL+fAHyS1%rTRpGVSzdVk?&9tFY5e7{Pu>dIp!+@CA=vZ&uT+~|pYH4DSC?IB
zyZh_Vw#c=U)x6S{*Zx1f?DwTJ$+yB&)eXv&u1WHKJuLR~GvD+eKSL#jv=z6e=vNlK
zp1J?owa&dA_uVSZ_gwZoxo54M^5Ocz#4Bn#m#2pO{g+}Zw6#dUu!Q~M9FLNhcXn<0
ztG(<}b_ul|PPr6+X1)vhcb^&QtX^UJ9S}>0(*3hTO+v8#6@T^u4tGd9Ii}M=A00
zKcQ814h>;Pm<5c&{{OCsTCUIAUnTGR%tQLdI=LtEE13)8s~gyUdWyTB2-H+EJuv^)
z&wm|<{VSqZt~$M9y^>t)R)-&Jvz9+iRIQrBsuHm^=<SQxr(y=|2VNe2n^zn%%eB~Q
z)<Y{l#)-!=ySB_bZ<ZpnggGpk^?m9h!^bmc+?Rjy!A3FW^tEd~@iHH{nvUy)>IyEf
z4QJfR^oYfJC40NYa)G+F9L?=HTc^FW_U}u5o6c9+FWleQHB;_T+8&<YC5b&2OCIq{
zUi{r*cU_CqTX^}rdlf4E$LfyMa$3Yo=I)4EVK2hjd~asxK>^mT=dTl=2-HiQZZF7|
z@cDg-TU1})SH$q+gQdEQDzDZ#o;)k$w0%}H>xE_74?=1qX1nOTxLtX&g>9MFl6P~8
z@25(A3`t|x3@mngrJQ+H@%q>0r?2_^`u^(0Avc>NT}t-?wU-9Z{KXt3;Ht&=%iv;=
zly>P2g@-Rc>4_KbOAvQC@^-I#Q#$|s@Ah5a+28z?N?OmSdwtKl_=rhH>F=+K^ECx7
z`?5my>!}LiD2L82_A9k+A$v+h-}|U`^YSE?7!)R5U}iE7v*{{W>T&(4ICn_fmIoHj
zPkWrAKfG4GsC(po6cf+ceGc`Jr6QZ#l8(MxyG&_E^!k~+yKLWGdmGbJ=DBCP*uRDK
zj83v_kz4cD8K=$p^R~Q4CtCSn^3FOB$^OtkGRnspIv<pGElZnoYJH0#)0Er6EN8cU
z6?B}J<xrLKi+9@*hC&(3s|Nky>r1(w`Wk&cJ@;sw6XS>Z$7-#n?`B+eX6_rVyD912
zZi^-~J3DP#AgZHhdzi(6(N-dLm7<qYmyg@xdy6Og&iY`r^_h<^@5vm4Z?`w~dhMP+
z?~e1UDI6W&I@668RxIoAJ^9@Fs7Z8cj&ZxP)bs5V%K92gw4WTiIqfUkT7FixE8AE$
zM>S5FbUg3O41II?_~Sm$Uw!-3b#69O)`j+U-Fgp%U79*>yxq~0)SWY_FXWzHX4i$I
zE6%@^|CVu4BT4HEpKs$$ySuO1*4u3E`&M*BM3!yG`t&`QLJ#FvbiSJrS@*C`t8VoL
zB~ihL0q$4ITz;RK{kZB?SI&fcT6J-bm98gz&hNOov-jY}DeM{3vX-t3DtUL=Bcg7#
zyItxErx{x}{|P(1^So0^=Og(^ztmn%l8*D3_wT4qK+)A5m!<9Zu9dqP9J9dF)boCT
zZpni$+UE6}-y}**|2KI-VnD}&s$&oP-ldtJ^~l;i!%Fh}oqWHR8Jk`UX<f6C6LRF3
z-DQ&#u;JRGn{8&sbGfF4eATZiINMRb!>`}wBb#!Fxm#qGfx$OHwWjl>IT;&ERQH`)
z%Parjan;OY2keyg>5G|vn82p2>9c0*PSZmcirkB&EvEjJ+#_b6Ae=j`w&H8c=I6qG
z!i5=sUzyBxbz8T`uCk%=c*v=DVb3<o=v7^uH!<nYf@Zew8grLkzc2f~bp7;9-M}3;
z)wVHI@lJEG^!mt`5>mKTVVfJ@S9!nV(<Ui@xi;5TV^-IDzMeZ5kG;|iO;vhwy8LOm
z)P$1Qc6axStK(V>9^MF4>I&I?)z{nLwWweJSEXxOhw@&|Ob{u&?RX^8IsL>8u35`n
z+&t4=>?NdLKCE4Fcvs{suHRKp+j*@f_vcQv-}2^8P)0)i65rsxXFga5bNzXjTzO^U
zg(F3pWeqkbx?fr?N?v|x!kxI=bD3O~SdI%vmV_EP?qR#JUVot@x0ZsMzW;@{-Es+A
zvI}2y$?OQ7pE*Hl_2fT=t<Q68`%T)ii?%Pyo};<)?oto)aJMPb#Ep6bEe-~Ds{L?O
z)QQ@0{m`ok`bKB>+c_8dgtKkU{obY=!nQ^%H2S7g(i_cy{l%wy6<RV@ygw!ObNP+G
zWi0b9o$ayxE1DRmnGh`5Jh6j+>v_h)_KlG&N6IyR?VrYZU*fdu<-ZaeU4AD<oS)(B
zEa-U7DoJ=@<7%(?jiv7^XRRtcHYZVZ7IVIi-J?x&OoJVIvnH4aIwwAl(tLKuX!p&X
zeyWa)b^k5oUftxfV7+qq^A(pB<<*%f3^IoM6s?RykGt|b;JaM?-DlcUsY5yk`EP7z
z`zfRMt1U)Wa>EU|@>^S`pPVM<dw<?f!^c6b0inzjJgmfPLys37xVtAKz$nOpU-(4g
zrl8qI(+{%TvfilpRN!~gi}Ne4lqmEa2x0N~-(2G$Q+VWEe#iN~X)lE)Zd|-ze*X>=
zJ(iRd+0|iF9Ve>1l-`#TIW6My=`XR%ela94Ok;l6vt4C}#?0*8!;fMEO{X{=-)hPJ
z?$o?vQ$ugF)oHP~=LfT&-5O!87comUVWyEx-jgoDwL2I8nftI$Xrt!s1NDK&Gb$W|
zbnXZ(E?n4lYQixIwPjWFpJrE`Yz*hj{QlZRTw+y|xnk=ouZvmU!VK+?F0RuyyX1HB
z{=uoD;+J`Jub*g%V|t{{GXIVIsyaK{>lT8EQ@`4H&6bKj!+uwvGwZLv<ti(a_s_zU
z_`KEE#Z6dSX82-SS86S1-lY#J!5g=g9NF99=-k~A%p-K5U2nVp$EV#l7xT^fxpA)R
z5}uAFzr^nbxx6ozeD!*7>w3e0qx+qH%S~CrET@|gbTBWiJEy{J&Xrr=lJ>3JTXOYv
zY(idf%?X8zs}d>%HEsx2EPoLB>hy(A>D+4btmD49F8IEp%zp3pr;GDf*$S7<oM_E^
zeV@p)yP;89mWBM;m+wz&RXkF;aP?dM!zX-G-Y1>>{C#%zKRfS<+ZlDuxvl123|6d*
zRd0Xa$a15aebuo8uAdSGKb$)FaBar*^VK`%p0`xp@Te(H-u>d~x+lyLHat#010SpJ
zF^jz~eneX2;`8+arXP>CTRqU(I&E*dVQc1l_oKTlqg7^je3E0-wTW_`?Dz3OhQ_@W
zk=fqU*ttdaUo7nDd!BZY*=(w?&iaJ~mD~7*dO6B<fBO1or`v6g{h>5rU2(P4X7+{m
z`7PS_h>Ayv$%U6_c9m~(Hy2#m#IV9aNd7DnUqaBV^?zHx{M?`M(l=dvbM(cf=W^oD
zXm3;F-TP8eV8izp9DA=XZ*X3)kW<=8^ysI!={x4{?%3F-{N&v^q4;MDbR_uNy}Oj1
zQ)`;`3ogp}aL;_^<q76nHwu(a6%;Fy4bn_VST)^vf=1rWnWa)TLED#o{nHmcNu`nL
zLyTDH{rEXMy{(y_POtEYTJVZ%YF56&y!*upF|#-QeDipB{PVksTni3eSAWYjU*9$7
zl0Yrz^mX?W%{kx9d1Bb+(I4A(Y~#<D2WFgnTUu=rFwxq0=01I^XsutbPlvtdE@&>D
zp7%BV${G29H$^tP7q*5hJik5MziQV%vp%i2ajDa8I@h@hE-Y|6QkibIs7T|_fz~rm
zp6#?^4*#eew)@J?Ws)*spQR&KgmyVcw9Gy$yReMah1qdk|EE>Ag@sSD72D=5e|ebe
z$BIApGe!Ql{^);sQ-99iorXUIx2=8qSX5YJZb!T8+9wlU8$5a_dv?{Em#$t0wV9>u
z(NnFKhHq*5{!a3r732D2&n`O#71!P@5almsm5F{fclGuEY_C71X9Ngdjh^0oOFNA9
zaNEqfrGJW@r2}4m2zk$BvgVgR@2<)t&aa#q?{gNL%I_4jW}PgpFR~?mPVRC~lP{?s
z`@*l9F5eY#>MG;n)1n)drY*WxJel>I_xoAT4P^sO&%5Vr-*EVqZdKLd=v((Yc7Oj{
z9`g4Oe^|QiRlind*Gk=)CNB>8M5eNO@x~di=Dy1|)64xz+j-Hxjt~4lLivAPQ4(va
z@9jvIJ($+D@oB<8-~P(@TQ2{!#j>`@$mEMpK6*+=?r4*RqTH+JQt~rYOcqXS`4Jm?
z%8P5>>0{61Wu%K07TZSj-?rjCTHspqUZd!)faQf!MnmN{mokpH{fu7w$LhY)q?;N#
z;hX_s*-2$Gd_@Yyliw|`zs@LW%KpY&UCdKbX7TL_f8PG8Sen1tS9yQb#Z8veCOQ2)
z&TDqZxt3A?zvAUb93B7GF>`%$OIs{>gl&>Q?4=`IvV81!4?MgmZRO}@xnIiZ>$TnD
z&rfi6{*Dc}dR3*?bHaW_jkytgxw9T`37`6$RkbF3v-HuRsq)UjQ6*28<uiXj85f!M
zMow7hvOv!Mn+xOb_v~QV;4#OdjwM(ul4IHtZCP(4pUt|K3EOrBfB2~3?7FGk(%VFM
zk4W>1%ng>e)@jXoVN~VyGl-{k_O%t)M8tf%cT{eyFIkx6n*3(v5$ogo%O$lHT+hn!
zCc9^cdF(yiYdK@;Y5ww7fyNt4LSvrD3GDj6i{sgh$bPexFH)bfABqm}XKT|fU+_oq
znB}!CjUg(J4<`B@KWJ^Tkm*+A*)-i1f*Q<q%dblMeOj*@Rgm5D_d}oGVf`7E9Wy_5
z2~Cau?KPJrrR|cgp6b_tM7bBe?{Wk0y~~mJP6=-<m2eDpsa*Cp;`0SJwTbdyzx_R1
z8MV1qMJMfS(ll3=h9;Nel9z8=Y+rxl@UKW~>sMl>mDiUpP5U@+M`eNe*I4#R)$<BM
zr9&r1xts{rT`MS}*k7OG+<3d$Jn=$V>~GIkbMv|-<Q)Faeg3`BB=pelLs$O_UgVs4
zdsT-v`(oE+l_w5*nCG|aH7Tuo_wxMdbFE(QELOQ3@a|gEQ2YLh`=$hw>y5n2s!epx
zn_dw=e#$~n&!|yw;=ffZV}$p{m4BN3F+8;^m38s98p&fD{2U7RfBllB{X{B&!KrD(
zGyR40GS5CzwK4Cl)NKrB&AHw#ut{0oVtGg1-I=F<X#QR!wtt1TbKXzZ1WT>|Z-cH%
zOH}x2JgGh!^xApW8O8m9sq#*_i{sOzUtZjtwD_l9T-57nM=ez@7dC8Px#rVeIcWx^
z7X>B}n@yfZSDVi_68mhwwWWWWm~whAlT%X6N~J4D?Uz<fi&*$uX8I%T3yZ}LCHQIB
z9I-ZuoW1KiSLa%$Yi|_;?3sQgHNDGx`Xfzj%FNq$LXCM}TzDn6tW=aSdDkI(7uQQ-
zk1yXd*A~~-cWPDNp0D%tai`hS_>Y<a>koLFDA`Vl-1aJ&N4&mm*R-hJffqC%q%S@5
z;*9vmYID1n0lRvRq&G)juev+4;rbgtCI9vR<jfKbC-F{QZ-3WINp)_f^jDWzllJVa
zw#t~R`C!hp(l>HX567KtUvo?+Ut5pCwy&H^c8}|hn}5De@A$A?`j_MB163jptJj@t
z*dF%e!KQ~f*(>k8dE;EZdBXXv<wnixDptOqeLODp)`e2`p4Xb+xA}<7xj2(&@6A76
zUwQB8a;O@_@g8w!mzngXM*IAk7tDg1lQiF)O}?9u_TFZ*iLBL&e=BrYC$DIk$h@X<
ziRw*3mF3kJ&+97+2pX>5eR=Z?tpkoywXPo)aak^jy?wFZ%!IJFT#78QCp`?x%5|%*
z8gl3<-BS$SGRIoJSpVVoNV)#1pv;O}F?qhLr2cXo|8g__NJZy_`)o7k9sR7hT(Ftv
zxQx)m=u|sf*FDRw{LY%vTfcDPipogqFwNZ>(NTs{6GL_9vm_bM>N(#k@W$xF=Jhov
zmi5Ucsk}N6<D!+k_ue9*XGY0N3J>h^`?uWQd-Ra$fl?c>MX6H13)QxEPYaa4ne;(n
z=`#K^)xNg{r*D~}|L0eNX5+l;e3A2)NB_Oh+~X*^Njudg`l_z)yY&6nlsP}keS6>4
zA;+tlym8&q*xbt4^*=5}$FhA^sD4q-)#S#w{8r0~YoaS#6yHBDyAfE*-FHB1^O;qx
z5f(yAcSOh@dBeSI8Q-VG`nS*i37t;(#rTy&l}}1oqx$2OCnlD%41YJ9rNve)ZRqQJ
zbT_;FlPZV&Z`T(ZBE}*U0vFpq3Z2@-xJ~G!xM7aEa#G;RD`nn~HGl1M@(A&b(3kyi
zVW!&!mDs$^3o{$%hZ~39@7v8)*J-}Eweb5Xw#R1ktS3Z@^_eCxioe)lnKoTWWSfWG
zvA6%N?QR&zvi?1gXD9vn6TkQT&tGe=G(HHK<iu&UweYy}rR#=$>l{)JPd^>xopvKC
z*W`S8m3DB6z6`6Y!Qw1ayP4nGo#PT!q*h!Pd8czQXQjurPp6xHZ{M{%>WKL+i6~RC
z?i%xZUu=&migtg|O?^3s@#D?BFY*sf4wyz<w_A`~*tK11?ylY2R&@Vi^S$-PZl~an
z-Luq~LJB5szP$FSY~@{<p194sE1sPBxNpYOa1GNEQDeDY*Ux%+p;s${T{?fw{qa7~
zcH#?%Pk(#dn-p8+ChmAWMOJd-?52?DSNi2VO^euWR7km>Nu9h^JLcHwx8CP>U$nA#
zpTGOn0TnH!Py1gAme0I@?)sSt%}2R5=TB{!F6|fkX<ohP@(q0){>P5Z&{j-nZQE8=
zm*KwZ=nbYeIYUX|46#a~r)@^wA#pR3EM7!zJL$4WecCzAEYCmRC+O91_n5C%KPV-4
z@1Zx((sHHjs6&kNCueNXi4xb~)p#<MmvM@8VDSCekhc9xf7dNA*rT*QFkz3;bt^5m
zPEG}fH%Hv`UI*LMO*_akJ#y|N#@aVkM_zBeoPR6sg_CYiht9#`J8EtgslQnxIJ;LZ
zy1Qq2&XkEs;wr6Kj4kUXEAwrY(0j)HYm$%z$0hH5S1;SFW^I+eZa*tz)ia0k=U?yd
z<q7`YY3;b~alUcy4AuoUs;_@d7w2F-RX0Cw!rJPW46bL3RnJ)li7Qqo^gaD5KZ|c;
zOm9g`p7!;JQ7RoR`ps(5Q=+2QIe(bSwBK*<F)=%t%8Fe|2L(J&n!B~l43mwV-|>G%
zvHP`CHSD=3lvi;HsOZm8+uPV=Guiiux5W(2MJzeq2{*Pz&74_xa`6oA1l2c7nN31=
z8(lCJEP1}0!SUl~R<TIdx>z-{?~`_&SP`+(WO;Hx=oSXnlRA;xC1%Xsvr#~xOD@Ph
z$n(fPhdD=^RDEPNT<?r<NZe)2ua)B-E9E>@!ga^C%9V4wtu~2&O#6LeL&=dV-bVV*
zE^WBVeJ?iQ(8jyjZ3$O<mQ|F`|M5k}`gqyS_aDN(Z)=xXb$Hj^({FXo$nEUsYndIB
zH$}m9ldk3Js{E>o5*FJF;c3=CyC#>mpE^C^jlcw(e#UB3N5;FS=T>$c@!U{oRdr+4
zHRkD2C0q3w%2dzn-Fd+|Bfk0gcLh03Cx&-k&A<LGTm3$o<Kur{&-@c5Zstj^6?PgN
zZJR#l&b|$IwtOf#YiG@+b8h>+Nd<iW>pU*ASpE^0z3jv>;p>}i4M!G8-C(nOcw6)S
z6e*Fp7E{*Wzkh(!)c9*^Mxj>mqo=XD^>%K3W%ne-cZ;vw+_Um!^4o8(_ZZgqPVk=h
zMr7Kxrg;gbu@Q?>7ff)F6Zzcos9+28tLu{|gou|;iqGv}2|DdH<>jN;Rp!-qOqb7l
zIa6VV3Fp&OJKWlq>#bXzuztevV<*%)Qj$D%-l_#OMG7A7zx~y8_K^uIWMUZ^_XM0|
z4ZK_{U{roo=NkJFS4Wpvk^9TS1Ee1@nJk;T&SP81<2bKJ$<q(zTgO_tEsL%d?rsX&
zcW((h%kC#>4<}48lwruMKWAp@pStp=NR7Yf=DS{{Yo>(V4Dr4hyu$0>oat?IZoPQ8
z>A8{OcdiDnMzf8nCuc-In4@<5LC4J_>?`k>R0Yg#HJjohS`smbRo%2cV3PgyxZ~@d
zrp(-wBl+Xlvm;yG%=vTt_C;T@S@c6{QP7^~1*cp)g^z73H0M3pm&<9boo>0roNI=E
z;?lUFkj>#c?l7-l)1N23@4&6jjYWDs;kGL4Lk_EE#~u<fv1S#z9{!<neoN$Dl`r?i
z&;3i8eDqKB9?$y>#qz51LcAL-j|U}PG03{?kUeX9SYn}eHGAW-#|gUKybgD^_ubxY
zQgh^c-t^fgx<n^s3M>8&-|;;$wM*^Fb>8Oc=`)X=-}B~5*?iu-1^%v8zCovVZBIR;
zczmK<-;S=Ic4;A(V%YOKOztx}m*w4fxnh&-%dRf2E&boW-qn2X5%|_FY1y>1X_ad)
zPc>Kg;PUSL$}LxaELMG~oe(N0b81!81C7%&@0e`wR}k@=6!hs->`JrkbCq*>%CBg9
zC+=acuy#6B(plWEw)}|nx0O{s>dWpN_q@O8<l{b%JRy?_OV;s9+r+;S%i8eU#c{j7
z)qa8IkbTAn!kQm>E$kGES?PJhN;`qWQ6s^3J~M~iwbwHD)jkRyUUvOrozv-t32PQd
zZ1{6cP)Og)@l)ZN-U+wO8k=9P=bxX}!+c?u=G6mT^)YRGmN8BGsga^#Gj&O-&?ZiI
zW>(D=jvKT~)+USW5q?v+Y3I}?8U4K-j&2)bx-@sp4e{Z<HTlR!-s2yZ8%54c<L%zR
z<IHy>!2>5^p2Q3F_54|#TooB`D6_|fX|nFSJX^UhOHG-%R)3qn?!!Z~eZNBQ94;!c
z)O`MpFX`^Pi%s9<G=t~P+Vt4$Pq+P9HiIaGV~48(HacxtnrtBb-DBsY;;lOZlw_LO
zTW>G5lxv#Ycm0!9?uv!3d+rs<b?Y~;&@im}xm>Nz<ch_Vb#BVRj|x0~b144U#ApA|
zkbnNh=Y>aJDc3GvD*7u~_wxijZ4QG8*R0}sij|cV&Ua)y;>^5dqH*!~Yum7Hg{x~N
zFUnn!ela0LW#L0rz064O{M!akY89uReb2r6hw~n1UuQP!C`)bEJ3BciiQRsG>ie&w
zZ;lH6R4tZgF)N+9@UW!f{YpKaxrIyf&1cB5R=CC&#dohtzLt9Bp3k;hT;5u)f8_ny
zwkOT3md#d<ulFpOz+7e7wW8wv%%1F5MiJKe%D*4%ynM~#z+@wN4K~-s?uM7ADduSX
zb3M3na(Y96*Sa&S7BTJo`+HqY@4Q~Vx~ZQ^4=nif>W<{*=kGGg<SY00*2={FowDX|
z)_JX$*Z*^C^{H%H7%R_veL0Jq6|?8ub!)Sy?&HloRZ;mo^xKv2wwmqNJT|vX-Mi;y
zw@!<`$R!QNuE>u&@2q|ipzvkN-Cr|IYZi(W&6#Pf!hMnViM!ODFH1JLW=*y^v)4v3
zl|e=^QSlFJ+CwhE_TF7F=a=!OU9{X>;nH#F>5B#Rk)={xHEWx5Ki-jjCiFjv=g#(P
zed{MQi}i|%gl`e!KkI3qYPyoaEA+JNq`H%D5??O({QCQoiMn^S({I&1QrIW1eqQIa
z!-RE;0-<}w-q@~NlQE&vORH<k`Oo^#uJy3GFIl3}5@z%N_FOlOq>yOQ&0fV1Vl!qf
z+H?8J^=r0AFZ~g@!}XKTZ-0bOmdvH9r5ugYW*nTE-nW#$%u`;H>w154XuHbA3xyl|
z5}L2_h#lMXu6%y>M#F;8b*C@*Oi(&3BhMx6*YV}EVS2!s@Qk*@@_a>t!Z|xw3!aAl
zy!YHra`SAyKY7gGzcARUvR{_e2}}AnE4DZ2%Kef%fzHP()wwrSTy|YBJ<m?o+2;M}
z$;Ou-97;d%k@d~2v&wA~OFDKhO*r%-em2XDrg?=|wbY`c&0ZJiv(3q#CAa0wrOZ~#
zMOQx=ByMjE5V-#Du`|n#$?G=k{M7SWB<RB3?|05^Wz>49xjpcAhE~PVcT-QQ@JaIR
zyc#I4GUKGtNB5+A%eOGH2JFAF_TDc?M@y%5m2W;&@H|+PFndeYy`70~4p|%C(Z9JO
z>r`_3)RgL}i&yGPwy(P6``y@YPv+aC8}32v$NU@=PA26gd^mRY?Xf2(4gHUac<=Ox
zQ%e>zRZP}PE#f})uS-+XVp5dmE*WdPm?t~_WHqL1K08%-Xq8#;!SvFf4cd2itGsJs
zm@+>!Xg8Cl+tDkE40~czCTD;2xWG8C_MuAZ)(D+5b1b6o{XfbgDq?8J5bD#D^Vnp;
z)|@8qv%N(;>*}*ta4>ZIDLEpeSAQ~pazXFn*5t7F!V@}wX(?;YcwZNIsH4r<%HhoF
z+M@22)lHRqZpH2kdoQM~%zW!gn`X}W23=;Zt!5c>qvjl!)8n3>-`HV3na}>Ah|jHb
zW8<d_KULO${N=NO_vorem3K}=I98ov=2Y2#<>}+T{b^T!htKPtXwz?FzH#5Qex}Zo
zh0_nLyQgkzs<1Wf=)E<9!8?qf_!l>5Xg%9fZxppCE3fr_g<izV$xo*mEuYGqr@d}g
z<@!8_{f9L_GZhH;-86kGrGC;z#7iiD(U0O2%hc?C8|5)>*q#)i`%5!x|C^cpmZ2}5
z*Z#hC?w1oE<A-AhwT~EPM<>m1@a~y$f-`r%{U!A!5f`7yhNetdpk%d-_o&8E+rDM{
zKK!!uUTS{VNS0Mp)NwOM%(q4U#?$>H3pW|?O;9{-u&(1<?!KGZ96Tv&?o7MMoc3?c
zo(HOj*-XNO?kdDBn7QWo5~GaDnMb&?T(_DZsf)d|{>jNB2{S)kV&;D`<K)sCjek0V
zmpsW0T0BKTO)W+6Q);4P{DV^>%uCH2)x*vRUNzYwrqWyJZE1ca<*uei{E4jadAE(?
z*NYlHwfB5DlmFTWp^&%)(Lae_Gaf`nIUIM>6WwmTSh8zxdWK)cnTFR><%(Js{o3!a
zdDZ2O2Rv^UC{OvK{Ci{0+t^F0EnYfb-kQE<4XJ;1d4KA3!MAoFl>C}=^X1CdFMIc?
z@o}6{ZRXpxpVxUMvOH?5akzI(?$z4sHr#&aytHO%_uXjc|2jL$ZF=Kkr+t@?PkAB~
z(N(XQuD*26^ixsqDjv_5x?QeOyKg?vNA6h~$@dmb&$+cUu=VtLi3Oc@s{d~b9bKx#
zyljT=rtY5QDlh+tO-Y*cb>+pkEdp2eo?Dw?^{jYRh-QJpkr~cypRH033mKFhGMG7k
zVM7&bP=ezor~l&1GkgVjJ~4kTv31-#Z?8TBE8mSRPwu~db<B8gLag4k9Ume#$UWw>
z4E3MLWLdqXch^MC(|KP+btawFJaE-=iT~jP%Q&varF~3b+fgZFw}b1-m-7>k9JbyO
zYQ8o+(B<E51Al|8(@94}j~7iejbAsDcj6o_2C>-i6z>`{(a(1yg*<O4f4~0dO~BVw
zKl6WiSFb4;X)|{QgkPI+Sor_fsqgN#ol-rL8QL@_QIx;s+LWNfhWgV~mgRJc9lg4S
zX|~M8ZBD#y$@<)a;Q=vfV%OJClY3cG+2u1oFwIm<etp#2ic2D^7xt|UlvXgWTsuMI
z*xSf;$$c)Du75b+GovS3cGI&(YhBN{)*QHF*zinreXeqC(#fyd+~TXwuDpCzUA(Ax
z-pyqPOZHB4&fRj}DCM`)tzCREK5Z_1Mcw&**XAc(d&n0)`Rz?D*LT-uJNB_{+nX{y
z>7__w$5h^%9v4L>f6`0ZH}$b;%et8xf*%-dKU?!eL1Kw-Y)ojW;3*#|#RZ8k?mb-j
zH#yh($pz`d3**vwdv>q=)v@yKhvzmc5C7KV)m*^X952+yd}qxW7ulQNPhYvC^WOIM
zo=)L+|4qN}uNBl>^)5Ryq~@)%ih_M~iO$V!47t+FR%d6moIiT)d5qZv&ZTmHum3q<
z*nQ}v;`$>w>K*eZd|+i!*0=GKyULlLT>f@S+R<+YH)coOa-Jgk;&hZH>!s>H*BJyK
z&bXZ$nb3a9C%*UI(v{poes_&`Z4+8+8}4+J=hxGc&MS>7e-$pf_|&-{J+t`h(v9~Y
zoEEV9A?_tUQD#bM2;)@Y@|TT=^&Y+m57cj!5v!MFQh%2#^ToCAqQ52Yv4jJbMVxng
zGL~Kz_n-CRy?D!CImY$V@9`|};)rM|oOfrwP=Kd|fJdZzOrDfU;(FyrI;X?AdbeBf
zMQLaY74y8#|M>fcQRlPbI~qs7m1JyvdFH`35jQq#&ZA#8Rp)O=IbT#|!O-Cy*S5t`
zN6yCCy?4ST0o5li>4r{a|GTb+Gz(vtJYT@b%KF~g=vo#=^Pl`Gvp>HI%HjSMH&agd
z%Z@3_R@8sdbq~p(cm4&N&})g0EQc9|-7h{c(y}<K=>8`Dh{R)ok7kyc1+z6*FAL5r
z=lLM(D7W`=QC<1VZ`N18s~y@`wMD?-TK(B+rH6d3u4fK(<*Dm1y)<`T;2(C;a}jdK
z`e!*_&8@WR3})CJSY{9`YPrFzF3KfXwoq^Wo0xAKpETNLhbMhpbH6?+_OouKVqwEo
zkIC$jvlgDe+gq`QO?Kb^?8Kh!C7V{-pWR(4IQ@%e+J?_cN>+&<!|sc3V&~r%Af*3B
zif1vKrlj!-QFq1f+tQO6G)q62KDG+yc&PEjx=i($2fvb1ki`-0>g|s_PBVTCYMj4Q
zTrYLDaYMSR3$rOxz{Q%vZ8@j>W}n)7b}`%UBR(NqFJ1NCzF$)Q_nY68t1iLvP43C<
zlDYLN;Vm!vJd2JjHY?ed{x@Ci{xnG&1EHkmy_b(keTZm0wky8#0po(DKmYA2lX(-h
zk)1iLncsFz)>*5o90yWX$=wlTeN*<%#XZZDd7sDmDbF_e%9Pdc#4`&{nC!fM@BRO+
z)^10V)!jI3cIJisbvoBC7`@JU-+TRg_Y3XoFQ{*OHTPt7&B_XoklNnpt;X@(zYSZT
zEGjxNExu6u`@9{AFV_Y|XWnUE5#;hjrLRG)zej1gl$7}{rTe#aza4sWlQS+O*kYcx
zNQ01)y<?e1kv7Bklxy?9>N4cGJFIzW`rdk)PwTGb%6ap9Ixg*1+L!;#yYl9`^&2kb
z@b&~uRf_9%KIj>-le@-C=c=K~s_tLG;U|)9F0;H}J>j@oiRi96y}3VIOE&%&`lM(s
zW@Em^T90d$;HSB=jTakQg!oS`yJ92QHAAUt?!th_Ikjwg;ex@Y&0<q7H8}EXDJ2!I
zod2!pp9|}k9k1`Z2bnfBOq(KgpHC<uDUI#Mib*951wZOuOn=*4vu>5%9T~I66|W}6
zEm+`YH)U1wo}~gRz0SV-cV>$kod4)}+n+K1=o_n)xo?aA)E35We6Ob&su(JJU%~jp
z_8DtltU6>7E^|`5SmcYyo(SiuA(3<T+fNVsw*C5FrMQ(vhYwD%<(g~W_$$EE@b@3D
zO}iU&gp6Ni_0(wJtL4gUiQv9i(0W8BL~*<7pHrMpRV_BTr_V4e9`2}^ykO_L1zr=*
zKNUG<6Z&F;Qg)8qC9jj0PrXW6RLPKYKjp#2t{{f8XQ4-|UBnbC4I18^*wic>ARu}q
z(RFsS%af^-Id@tf{Lzu#oNzm<`>{tk|1-lVs|mMRm5yAy`}g)*JIUT~&kYlTk6(Iu
z#!2+zt<KdE8)fc4dDE`;YS)GMU^a$GKf#xO*|$Bl-NIOXx3<0OQY{0=z3z^04jUTw
zl&pF!bBjM}jp#$acA4AmKdprB&ld1~%T(;2a!5R5k5iGKXM5R-zxVpABqLbX+dTgx
zdy|Xp&)O<s#_3=AYJc45S2-!ze>*DV)T_dx16x@Z*nG-Txh%4#WAUjH2J7{vZ<hM1
zS4#%7ZPBzkd|_{}{-ayv8@u@ng5zW(xBu8EAmD0qh$m#i7Tdoq>(-w98IyX);)G0L
zy<oN0)?TA*D@CcrPiB98n)B&eg|ySUc`p=Z{s~!HccgcX`r-9gLu9>z;=?&QEf)2L
zDQuRLX7#$MYcl<=>C2?ZL^b)3OOBT&hpj8vr}tpRmpyN;o3|XCeDLEm3lHI9ZtKN6
z4F!7y*Rp(=nsi$1wlZ(@{=KYKrWSK9FLtckE5pMe_qonynoYG~zt8d+nmW7Z%YA&1
z$Kbr>m%xp#)0@3tu-%H|N!jq*qH66FtFE0k8T=Ce&&@DRmU}I~peU37?9-Q@j&8s8
zoTIk$gy*z~MBSKZ4$JaTkKdh-;&XH~;=(Lny49W&bpBv6C5UOy+3YooY?X~~Y<lok
z@qEN=TZRLNUtf1}^?bcmI_>5KMe`L>XVc$LxV+iIKGrJ9*ogh8iMUwU^jniwtnltx
z5W4?nkgv}DP^NeK%=^oj>t64b*eoH-b^OZ?p6Q>K{`wPZ={zs>_zI6VE}QB!n~pxN
zl+BX4u;_93;y)#u+DuB<KFe(^%>4H5{2!;hpN9KxFTKgdx8Uu!la-r-ChbsPn|`xk
zpZ}u6d~c;{&)%}}(vG?P@$tuBg%7K0P95goI-lp5h7pVYWr2Y6CHL>%JzBWp)Qh+%
z?FWCBe%DWXV7N@elCeG8_-Ie&@#?*cCND^o*&M!ewZ3NFMt84s7QZIVI-}jcM9!n#
zFpfnav~<I+hm``JcOM=&Q&$&X^sMp9+lYYnZ>bL!l!$$?6|UF3!}K6NbN+(Us&2n0
z-o4KqT%=VMJ7>DwIg6e8bL$#B?+D3ed0*#P{B-5+%HQi5jeGqgFC4qHT_)P(l(bXx
zev5T)<gXvz8RHn}_KPp_`np2-U0>Ozy%)Ef8q=76mZevF&wmrKP0QxHZq%RI_bmEo
zrHGVwl%|iTUDbyY@hO7S?4JkN3tf~~Rw<6^IaFZKl-GYwR&e#L_tRTf6xPXVE{=)$
zE^^^?<c}QhtNZ1PR6=>X3y;p`-LN8yiA7Ija}4|1l6KBpyKa0CH;r?QpT&6cedzS;
zGq&L+(^xsDJ?NU+c#x|})iKbsXMw|i-ed2w9zCcIQ~e|=*C_af>(ifq`Cih_`;77*
zPw-6BePmvD@b(eUZk>7e^n?~)W=;OIa(a)*31yXsG2JJBhxcxFR=)Gi^}5t&hNERk
zuHoxFH^(NK8c)9XQ0{U4R^=V9ru07Q`4XJFKd9Y(ox%w#wgUo(gJ%ag1_z%Jw-0Vk
z-J<lW*xf5)3&W$ket-NH&8m{WshatqPAQG6t7)nAuA>S(><{`iyM8T8-F-%%BPNY&
z%Ij}FotlPzeZ5A}f+0md!Iv#A9Zg9-Q1-O3<5JO@cehRTEF{cV?ffqPf~BzY&fK;r
zXO0a#H`9v54HvIb&NzQ9dugMzA^X{;{T+3o4SVMYuw=hEe&#o4)diPb-l7wD?<bde
z3T6s;t6SFYyY0i&`Q`tdvoQ;1Zp@oFS8R6C_ADpqzd21!j{`51yIcQFSP-{q^1k3W
zVa_!iUG`2ayf>fiKd?A8S>oqLiL+vD-!27LxCeh_pL;Qte{WLl`DA8}n0fBs)Y{*w
zWMu|@bolksWopBNMbD;vzhR{DWUUfE)9=}nxVC$+Sg$F1GIgd&d4TXSzpx2ApG&W|
z%qkB$E!4MyTa$NXZ}3K~!ox{^bAr3dHJP1Uu1!wj{qb17My}7JD|7C?x!cP6e)P^_
z>tC`=W5&WA=PultX7b?NPA)g+O^cPL$%r?9T~yQY#9gevHthF@OZ*{Me#v_*QEy=>
z{ccgVlkLlz$0yjByRW=nu|YF=c9NLrT&|3OMZX!PdOc13-pPet6x_V)8SmfeM~o$0
zyXQu`)QYDr;m+TBLV429O_~Z5?j`-@>)*+x^Y%uR{<0S)Jhx5u)|Gb(F{e#cZ7e*?
z^O5Vlr}5_KtFoO7%>-|s6+Fz*yFWhWzb{|ohGngl6^2h=>=Rsn{dVe=S#y4W-({CE
zXSbx`or}%;>KCo}E@NHCo2@4D#{QAx&j)9FDqk;aI5zq3qZv+n)?^1?E4NTCne2b7
zC-$IK0JEpdp88+g549=oOMJ<CZO1v4AEH9ZO<H$FLh|kEA{jT_oB!j4wxhUD!1JvU
ztnK+aOPZHuxVX*;eV5xg_36e%e?>BKyBGRtD<-bdiGCM8b%j~A{UL*twhixh3cs6?
z;1T#yV(%)}z3pEO3+{fAkknh!!gE1rV#4v;+}CnDriyT12p4+V|4^gmN|4=`%?pb~
z+ty8SbgXl~v2@Zj%>~^br5yYhiB+AontEaLsr1m_Yz4b{Z*~1TwIwEg)vKvr%vLm;
zecyM#?`73~hX+gomn@h4oo3<on0J4C%@Ui)g-3Mj?n&>o{qONS_K%EfTl&1mt`(eJ
zcT&y1Dan6b%oM5i_ljnZ=_B@zm059pYj2+m|8Z)@<n_PU)Th-?op9mu>U%t5<~QG+
z{`l~B>@v3s^}W@Bn}V4?%q<PPwEwcm^!EAu*WOKPnf6@sbm7zZAOAY9eR#Ni(!U!O
z-_z_0jV@<IoNTUMQTVy&>{`z++qQD9Y)-zH`~N0Wd+_59@gny7X8#&nncM&Dbe@;|
z+vCX3%Z}3z>~GLE&9XSF@{Zw|rx2g{N98@ocNfn&zG#6;dY^Z!fFJwnT~d}`rn!Er
zHw_e$NH+?-AGJ-uR_o}*ww8p34~q*K`aW#ybY}joaX<0up&LF^l+HeQufDhOc>jcU
zwU1>U>Iug`{d=hS^>^j1rwe~xS!p1ZzK_Ai^yz1&g%4^>VwW$y|3lwxYT34>i+pdc
zO5Ug-ur12-wH~YML0=Bl*=K@w@lAcN^ZfFhCd0p1m;U?rvCpM!2L}_AWVf{1jZY@x
z{|jAnUC(aFbpFQtDKKP0;g<zZdb9e)xFRRZT0EGhAAb7AW-(WbAK$c>omjWz$G@|Z
zrJ>D_W#4}ibjz$b&6V!8?3*m_?HLoAxR<?e`6bk~(8kGbqq5ICWsNl^EBh84e8ztF
zdS_I2+u1o8*H$RZQaa?b{_gZ6GVAZg-WC^bSv0T2`^@LR-P1%~+^q3T`0-5ruA7_U
z@x@b5uX!pyHGZqBv+&dDugkgiI2@WQQlIhocIK_FWunI0M1&rn_#f<+wK~^OK(zS9
zlJrzpj~@wX{i{3WSZDJc`W(-BjI~rY=$gI3dL4g*690Yo?YQJzbyhC6XNm9Tsn>cY
znE6GN$9$X6vy1y=xMy4mY1|>Cw)YDQ6GvNBzE=Fzh0SjsELgSR%44oBy|qn#2d(pr
z?>66d*gN}C&2qQYCmkM%tM<)EVr=5@&RnrF_4J=}O|_@rM6WZioOn3n`t>)lb%z#i
zQ@<N+uX3|(=TeJr89%?|HmDur<*Ha3&C-y4vnioysn()s%jreFjQOv47rFfxZ~wIQ
z);DY4@G$q-8{!(z0u3HNN!mD9apslpZU#33UAA>{=NMPsvkzW-BD!lbe=Gm%_T!<;
z`xA~S-7@|){k_`mOAX9{YN<>yMUTDBPHxjm>+0CL`-pjC^Adf|WzL6tjhCEZ&4{0L
zdxq|>hUG6G)gA8j?<`thl(QjOOG8oV#@Q0T|G_cQS3a;vT8R{wzFfX1_rZ+q)jw-i
zxUVbv_#xgwvS{!Ac%6A-awi0ZnU*B;G3#lq{2bylcdNkCtL^iDmCwlMtZJVf`%FFM
zYxG)~uWJ$#UgR8l5^<V+vSWM_=dINVv-Z~Y_0KPFcHeg2q3-yvgMa*geJ`$D5&B_)
ziS4|~wlylVOAB5Gy-H5%c|5_b(b?O0kD$|5CppEE*K2QWe0Xx*_paX_S@ZZJFEj{G
z*sL6!;W>5Ai;J#Bfzzu~7~a{mvKk8*t}f6K*NSnu<$8uUt?OInjjc<M@SmJrof2%^
zyp{L(!kSGvH$3f>*SNdSdG}gr`eJ9X-jLcu$=z``f`gX2XFFtuO2^J)d2zs1%;juK
z=ElX(^cR2kcfV|#Tb1jcy}XX!a?LG16+1Ns^-#C_iv+?NYu1O>dxre0D-@2>n6-A-
zmbgsj^b<*+56}I^slVjfYd$mg5+=9lZP&ej=j^yRd+F*^Q@lhDWw`(SeIc-?!+D#?
z`gc+{-RI?|duadu5Vy7B-t&Nm<psy5Dn!)i{CjwM!ByGS>(heYS6T0LDfLd3<Z_LU
zOmdY!uNb^YFnZtA?&WDdv1eaD6~6RbCxy3br|!d;{8hHHPb=U5|NqYI_?=H1bU)RW
zoGIctcHygR^^w)-o{zXJO}7>n=o>xOa^)46bJ4D%zJ5jiwLr&<p-!hg)=%5G(cE*^
zf#mQ=w|T5_4#5sVA-BpVXPsXDK<WTXt;U1D^-%>``+_{AU-)LN4do71SU=e+#3$V3
zyuV!KS?N^CIgZQS9QL}cTe=}SPRe3ZPsrs>yP3CMF3V$(iRG$JIJd`s^;faP-75o+
zzT79eO=_vw-{)GPlQXx^XuGk4<x5ncSYPJ$d-V^Tre2ThbKd*7Jo<NyewYFy*S+w2
z$(7$?`IkRjebkU+)wMW24~~_#Z9Qc<m!>y{F28kU?%CCum8^#iKbz?qPc(a#c&vBr
z?c$541H<3=)!z)a*pYC&$jnc9S9sO6t(zw;T>Z-Xx86=>kt6TR?bfu4Wxe|9p0_A`
z&x0i{H!S`rzqzwg?d$_Xv#ZuAQ#A}2!&ZHHCA2@jKe{n0?mW-&t)bk;CYEgz8Y}}n
zX72H7lF#Pcef%X)XsT_MlJ{Ya85N(VPh8#L=NS0s@%0SJlE_Do=7w*zI)CM714Fxi
z>c9OS!S~8Oyf{|m&pNf<^r-_oU;Hc0*BwgrZ)^)b*_}IPTGn*BewD}`skMiTjEh>T
zJq;N}o=pkn`mn(7>K;d->R<al*Kj{)&ee5biQ_)L%jHQ^I4`Tildep&LusAD9}~2N
z|G&#knrrHzyE587*ivNC`c)Dck*mrJHNS8x$)57OSupvPEOV4o?JZ-yu89?AZreYN
zIn$)9@y>W-%YpP8k$ItWOU$2K6#WwNUC1swM?ohqXzsIUUTY2IlJKqFQJxz$%9j06
z?Mu0%C%(j2b)sXakML<P{?`S^eV)!N*WY2ws_0_)+HcRHNs{62JWh&_Z(jIwc}3B*
zzhCQhG<Khvc93~bR8iiWC2!SU_sxpC{O9zFt1q^y7HFIHm)|g5KCL7!{hftpvubvM
zP<_z#?~^uIFFU`_(uQH#{|8>>yI8xn%`%A(ki3?ydU$&DHHk33*-5ReM)CfZt1JGi
zuIc!!xz@rk-E?JYs`0D2^VsZ~8n?Z>TpBg!NALxG>yJUZN;h06%r#je{#7aI@YBzi
zo)wi=Rk|p@T9v;sH<Imh(7q`Z=YM*xIvegV!+Y*5$@)K%m&>lt@%BsgFp>9GyvSDQ
zQ<-+LC_8KF1GB8e4|<*4R?Cxk%ihi8*g4D8;G%xVU*=~Q`Z+ryugCs%i^~6g>sx-_
zOfUER!2X{PS2}ga2z~l8S)^FoaYe!F)}EPSGvDOsE>)j;*}>4>zJ%+;oGbC$7ru~L
z`FPvpW54zOW^reif32=q=yJ|GNW`#u>ep8s(#l7doL@cTeZ{BZV;=<!-xo@AxlZo*
z8P~LQdi+Y&R_#;&IXuG+rWWlE>~U^BU;bEP-#P6v7n4P@7rk;y9a{pAsF}RtWYzsA
zaAZr(8uMPO);E{lDryS8d-_&2({r!9)$XmIS^uY4h4-jQy>vdmaYxCz?N6uW?w)2`
z#o3XPy)RMgiiPWuu<#3q6VEPgG@KmO_3-AKl9ju+)mb0UICV9J^XwVt=f8e`d=|=I
za8Ycc=3#xaBN1LJ3|9p<oyoEBi0ORwZf&$tns2ek9R6Nu^Ch`$C-3T~7_IZIyq`4X
zBGc2p_%}iyK89ZM_F5Jo_Q+9TMy5A=Y+U{})A>s4z20_)Y&T#zzQ;+f?<~j9Z%b49
zCoo>~TfunaD$|t)f$VEPN)76^FrAyRZ^^|Erw%iG=}J16X};yPid?ydt?GLB6aRKz
zHLq1{mCsMyC97C%_mpS5jMF}o^4~|dmGm-ty_&!iEjnqZ_nCn0>f4ReZX8)6{ak$Y
zA$Engrq6EjB!AE_Ta$NmZj_T$R7c*_LZ|4n$!_brEOxE+zb_fFbf0H?p7oNv@En!a
zuexF-jz<>X=BwzO=y_yfIA_t^E{~^w(swvqPAQ1GQflVVP`@#@MzgHJ^^$tDR6%^u
z%pcQMx6D1VU*doM?*Dt|&%6KWt>yj*@4x4J6E`GDMH<h(ZPnZv<+dm5kf^88qf4vG
zjNe?%o;gjKkI_#!Ps=>*o0s#2=^NLb-Z#%R>S#`q<FaigKK%Q`V^t?Cm)#U8HzEF*
zGOyXTRh$;<?@crPenPOPH{C{8yk98t&z<S<uRlI44&e`cmZ=w(!*ejiqs!W3vFkJD
zP4^%1y`L(_Z8mA$OXpwKPMHEP+oYnu%uD0$Klf84e`;mFoZzWBW*!zMnawvU*jH@#
z<ZYh*?&>O))FcDjTD}>^J;s}t2w%J!zAA7kS3-rV4BH2fy;uLW%Dl4Pqw~F1VYk*@
zpTz6a$}S(-Tls5)^smDQWi?wpSpJJ_;w)~7Stl~(<pm8Dr6so%-}hWFJ@n_&%UFBs
z?@y%K>SQEl89v+7`Sz4|^ZySs&jrd^r+iQJ;(VDf=jC%LZFf}#dDRt-?-;%WyFFs9
z{nWC*C??ia)<)sZYeU7&T2Hp<AJaRl7j$|<--V7%-WO-?a?7h|&`ODld$h8Gr!8aE
zw}fvuf2DF4Ge_5_-_tn$MeKo1>zB3v`#xsn&n{k45Yzbm#?<Uu_g@oM$_L*toZ3<l
zu5okHi#X1>Iu@IE-Rl=#GfbcREPFwSZg};RnLp26et1~)M@C$9)9kY!E(9)Wtvo)z
zZck3Fvz$NU+Zm^3)MxHwy3p0I<f)uT?$j93`(>;?OO=*5^}Ro7G}pIoTfb^W&Yv~c
zLMq$U1J=kigjX$Rl<ZovCeq^l-MLB&_expcw*RZ`78cB(8&q$Vx$bfj>yL{plB_f9
zYu!A4z6y(Y{j}BOiAl{V(NAyB{^!XwUQ$25Yt1$zYn}5VpKft*9cX^D#-aa(XU1gh
zl-G7K&4x1d+wLCNpIG@@JoM5T-IFU$&Yb&7V#3SIM^F5@k^9K#vB%;wtoln-7abH$
zddQUV#nPfSz43VP#4k@H_Ad33Ubn;TZOfOS198)De#v;Cm1No@=hd3$simPCc4677
zV^Lf;_kZ%AZ2V;7-<}I=<{ES_`o$-`@z}{rF-8X2S2{lOY*pRBdM(=3%TfN*7nb7;
zU&A9g3*YK@U0V`dwn8vcWXExqE&htU`Z4Z3nFifnhdx@0zhs|Yq<d|0-1p?A-hxT7
zvz#uN1s|C7c8>N-&PTE5vuA%yHJsORXy(P8LH!p^)f$U${FQX~UwmTOcd=h9rMAw=
z>f)L?|2A{F<gq|r&AQIU#;H^HZRW9l_f3+4;iA@sQ|g?NIjVlj*K|2W=aqEkPOW@9
zy*p=BfD*gYE@_3lYe@l%vqTi_^1p2CQ{Brfy@G$`RYty>T;Dp{-S0D*8!TmdQ?ozf
z&UKmKoyTt<oYtqiBuZ=U!Wov&ERPyJax0i(VxnlhDfdR&D+xpYLTAzI;^kYewHvIK
z+u=ATOn=(5y%j5eFumR|TeWLVoATLD^S+$e_)uusgtPlpl6M#OFz36O7~3(d%S*5I
zF#FE1<lTY>UmmkB3!>*)pEdrJ`sVNI)a{WvXIU9}nxF3LUZWJT;c%?=g&sj6wdR)n
zg-<Si?Q&aNmfF2>e_!}v9ly<5tdc!RN@~w%Ow+3|JpG~ZU!LdDFYnTQbjwtwp6YSF
z@I7wYd7%6Kgoy&vrcbUqndfM5=u+tIPkViwMH1KleBsy@pg31?@7BeqCzPdr?B4sS
z-Qtq!;|nuB_Hv(EB)50*busIeQ(G2ao>juV_OyT7*`odJSDvIl=8)oDJM+-i9e;1V
zPv$g|DD8I>OIYT1K0nfB&#jfl-~Cq4HJly2A@Tmx{><$+Gubts$eDz<99bH*`rF$Q
zhUZJ;HzxP)UbuEytmjG5?wu>0ylTrHO)V}uc+9<O^@_69UFMB*4)OVaGqTH!KX8CQ
zSaQvsNt^CxDrbBZTo?KDWvh0cj$`6U-OOXB1-87OTad@1w?k+nm#}L1vMaZ_cX8&W
z>P8<us3jq3uzqP|`@>UL{#CwnIls7Qm8Qa{pMr(qq0<lkx*9b1X-8ON-~|5bbvFJl
zZRIyEyYxfnP%6u{mA^}_man=VrT>0@<-%u~(sJ_aV$*pHPA<7(pW2b-KjqH<qZ+p*
zwys)s_|3KL?oyi;2z^`r<=AZbt>>R@cIm&a%EBvfDfgb{N8u8YJU{v9s9U<l;(3N<
zOQbB1{_xqJyxy*BBlk_E!?o;L;$P(rm(2cNUz&R<ZI;J!O~qW1&|>$HtWU8YbEc=a
zm|TxNGj~~=sFy2~(3Bl39!r_zGH`XQ>H22)bh}%=;i0*S7oNSGc|Sv<wWIS+l;+Yc
zR)X67B_GO|r5kyV`q;ZwoO{sKZmO%hsek9hgf+8Q?Wip+lRtJjNKyZ~*i6;iG7Lf{
zMd<?nmfzP~uzSt7X_l+bByMCie8KnmGtZ2VY3JK^%C1?P>!5w^@5}D?gqXGOeKo5u
zr|fl2T&W^+^JK@f?AgMXOkdqjo#psOfGLbGZ~B?F+q(`<`6m0s<0+rPssBsn3vigM
zV82)PgF8dc<kHvAvfIQ2<iw;}q765ny3k;h(qnps^ZI&@ik6;-*+;@#VuP2+F>i8d
zz4B|H8=qnJsnsk&E=zB(nzivk^7dS}<QR#(C9gc2wZfzSnPsOMSpIOmS$cP0Vw9R;
z!&4)!LX-aJ_FM0SE$2QBx@h&`+o>g?3!WLs-4e{<EdN_q#QV-O|9FXfn`+SKHm1+=
z+Z2!A2y4ID^CE_$-s@@ERL1Z?(f1tDyjOfLc}{<0b)mH6WayiG&dhHcUI#feuyWma
z8Z6lPsAO$^>Z5XgjsHvPE-_zIyKZLS8h)Su;`aC_#Y=a2?p?O#)UOlVa&HS33++;r
z$XGEiCqpKCqMUtVp<>UJd!me`vet9hH4K+&O<T;;q5InMl}-NlCt^w8v^$<0D^Zwj
zCbl!nZu7+cfOxj~Zmcfprc7m$b;(at<E74=d@LffdzL%TW-UjxTlE%KQ{!Jv4h&k>
zUA}r=|B~?SNh|r<gO2HYOx$~$VebjHK9y5?#_yYT;`u_~>=56;wcGi%ukYfOhWfw$
zI!X4VE#6|qtDI0E<l*{b!Zwl0*E_SXe2Ht5U$3H+C6Zd%v+&u^^?&8&heXVBTYbz}
zF+!t$*1z13rt7b;-hZF5_8)Vh$IDM=cI)TPh}To8&XRhbb$wBpwt)X+L8gCO?+Fy@
z{(ae0wnMo?GQjEMg#(7mUssebSNrj-Pn}P=<ixu?-ABjkzsy*^H|7Dq#k_~<7lfzD
ztv|wO#Uv&9(eLW>ib!{-^#Y-HCH+foeV_5}v%li{g45kG5<1W3)XhCS|GbXKl6t4)
z_L`GNX4s|_UsDvZxMyW|t}B7ZSi`x?oMpPg`-0*pJ677LG%mX3Z*oPO@$mN7rOX$8
z++8(Q(pDoXC#rR~+5|_#6UV#H?qZPgS!xiP@hVWan$x7HYP<U)>-~GG^iR*c7~#or
zX9efhtVzCU2|5C1whxtb<5w@;cV_Ken{(?{o%(+IMee@;3G0=m6!x5rd%R@oGCQZ{
zyA#`Ia?}d5R@&baW8j^v6KZ+(8{_*gl9kguo!`!r)9O^wJp5*nTJmhUW3#xzb=##@
z?&{lgtEjB7WaobC4Lj9lo_^S6+!?!BUpsrt$wgBI47Z4tGBD-*(4Qq4_IizFn{$hI
zx%JV>OK#tnp5mUkL8^57@uf~Si^C2iv3i#)-B`5Of$z~dulMif&6!x<JT>mcz29%<
zygz#E-s>xq{*?4A33(v*Uw?;wWrxCYPZO!t@&!5XZNKP=<co(V7NnIHTr>*YBa-sY
zSHNB1`sI&Z4Lm*;o4LA=OkQ;LKEE>WTCoQPUEj~%I_|lu^s(~aCDZMW@=7<gPw+Mg
z=XJIWN^N>>c9d_@$<vK*`g(kK-+zAbP4CPEC5Bw)e~;!qJA8SCM4tKDqsjKu_H9$i
z&~m#h$SdC7@hz-JE`JA~!wrRa^?eWYe(kZ^U47@t?ny51qW39HJ^7&Q>AII2?yhQG
zuPR|w!DW{6!_zTYMx5zQq~q(w{#W|`=(SI{Ct-HNvijPh%$WZ*?1syyDlzBJYv>8q
zRmq=Xz{t9B1;+`C1skR<5j^DiW=5Z2z67Vh@&4NxSqf$@b5*BZdCGfAbkWM=@4^q9
z=TOg)x#z=YzN~V?d*8|@f5eJUz2$DXsBGHVaP<$%nrBLKuVx7HuQWUQSfI@2=~dGw
z)AsdEo1b63`F!TZcP^6-trFbxWUtH3r)E_;mpGK)DnEGMyP?taX;xsi&|Sm%dOzBK
zFc$ZmUl739K6%57lkNxFY`V_{Kh5!QXghTJ_tEWq6Q*zN*eq@5Z54ZNg<Y&f`pXUP
z%;y(qnzKkQkP=(5W*f897OMl(JN*+rKK>JP{l@X$g&WSFzuRk-FK_YM%ceEt`t*xi
ze#aXKB#H3HobIju*BJA^g^yEq!u&q&)FzIK6MEdQ1@~W^HS-<UjERrV_AECzeIzMl
zQlI&Poi!KxLv}<ttrbr9+v;#({@Ke>%WM9!S&4RTe^y|9f4R%`z%wDI-)%npZb7+?
zYR0ZUsZE#cO#_4e{9k)`PyaIOyZMRFD?H^p8&*I4d{R1L)vAW_{XS=R9XPDKpyZ|I
zwbCOC+%jJNSFW9w_o9?nrfE^BbM!Zjoi?G}drk+)i{;du5|RnlY;=nDXWzMqW4qU+
z&4Rw+J3{~3Ek7RmqQ<iKU3vNuLGQAQ2fEj3SJ*qt@_QW-EL?T4fHCYy(?Om<?k#O6
zCT~);f4E_r;o?-z`Fmw6KG%jlohNL*a(_eDndzl24o8w$vmL)iF&^Dg|N7`76=_M!
z+=E|uD{f!a+RXEIt?<XX`E%QQl*{g}Dp)XG*!s`9DFy!b8+gS+U1CDtin^?AUw6k=
z`0ek+vrA^3QnWI@_eERw)S-s?>RL65x<ADmcRSR)y?b|~o8s2jQ^m9uN?ys;9w`l$
zW%{sm{)Hux>p1nL?OhB)eGfW#s4@A8{<BbPxgb+u@b=)MTsO1#wmZ&!5ZrvaU_V2T
z%e|(1LaS$e-uq&;nzmy)%L#7A4FTPJZPqCU_KAYFleaFu_WZY}+kfST^uW*W;y&?R
z4Q>5W&GGU~k+7cH+vGW~XUPZEMR$9)mE6ityLsZRhRS>|#o5o|pBP>*w_VpNSj4Yw
zz2MUhVY`c~Q#o`m|14^`FhS|{4YTD9%F8CmG49u$u}pfm{Pvl%o*us^{wY%H^ve2!
zaysX<q?0U|xOfd`=%r?!P`Pp=<o^@POJAl)EY?biemApOv{><e@&EAB1@R|luJRG6
z-f!7kV|UR_LUNPaiImOC8#UDr-1RNtd0EpQ)7hMn_IU3Erl571lBE~!XkLy`-0)vi
zF=ua;UxwKNn?+5TOFw++zR~SjdYx-}>FvuUNwsq|_jyIygsr{LDthGIt*xAwIc}6%
zFR5t>lenvy^5cV$&~c?!o5LP)0-o!%+O|I_n9S~;^t-k|<*Lp!)oBc~BCVuP9DA*~
z(p^-DDYC^y&0BH0snRR6h2L9svNGBIb<fS6`sk&?%C_foHc0EbznWYcx;K1N^xklb
zOPsw|t@u6pW*<?RTHMaCLF=N@ZKaF?vm=RZGybqtZZ$j~Y|89wb4@#W&*BNYSCpQx
zeB8d|@3ILZRa`eW{g|uXrMBhZKX;yA-e#*Gya-QD=ld-1G)jQ&OO*MuS@ni3Uhmqz
z%?;Atx^>ah2ltMiN;hd0(zUARmsz2dAg{U3@=r(1lscE!Az!xVojr2U@DO9Jxvyii
zkj{<I*7rh0pH_XkYt`pwA8zsEz-gBQnWw&0>ocu0y!>6buiEauzUY!STI**oJCmmS
z=tw-1&70t#AzN=97g#6b@@QgQr>EH^@6LjCd*UQ-)jnAeGFK@5`s!sC&b1%+Y?HEL
zu(RxITbLnZvHX^!RIHEC8<EScsW0D)uKdgW>AA6`$YK%QLhplLR{yjYyu3lCw=w3S
zlE@zGI_;#Xa(ve_KWeXKs=8qRWxM?4xK9~VGOzuz+qzjsro3%`qG{@Pi@C=H4)68X
zEWOCYyS&Qf@lp2&7G}#5A`UUV=s7Q4biYKq<k^gUWqT&hbzZnuWqF(D`nnsXsm!sT
z#re}jzE$7Y{Iz4R*yj}%9FNl*xhLk_5vh6>8h5B5@z;ZcC#&lY-p-D<+Ov}V=;5dD
zx_W=qvFh?h{g`$wZ>Lwbx8mQdtxH;qS2LNdT=e0@Os<J@v=e5w-SEFWTRUi`;D-po
z_o*MU{_WXvTda3|%D;|)y{kI=-B+*Uy&-q6W1GZkYhm|2eWvC%np2NtsNZ|pW-Tw6
zdDZjG?|BdJe<_)7Dn7H+RcBFC<Dc;SjAP<``FCr3_g@Y$yLnt>fArgxyADZ5GA_@U
zT9Ht5|IxW8Rh_o1YhGC`P)yENi!gD!8MWf--Fy=zQ3DQ{!mQcp8{C9_SkrCpcSr2B
zd@$*V><h_<B?rpPo=f{ZVd@q5KcRI=MX;E_nFWjIRh`cCw^ywB#L@Aqg{f~+#MZq*
z9A7Gu85)A6%B!quMH=@o%vfb;>&3w<7#Nb(u%^uK)5Bi&rLBSmtN}Zcg9ZHjT)COt
zRC@p43=DbQmvCA1b8Of1RdtVYceVIutyIpvVB2M=yrfCA(53mN_$DDiL1WL<W4E7j
zxn^v9!?9|b;jP7Q6HY9hb0b0X<@^0t1NLMH7+rX^Z`tWR>w{UQJF0}O7unP;#w*tO
zar>`LzWQOln=~Znu(vtRU-9cY@6w6&r;4Uzp3%ST@ba|c>^)09Xp2RqNw4|Ew{pw=
z%IW{MwD?SVbkB8}(SvD<SL5_ppZBc!^0a%Yn(0?Q_cyOP{a2~Z&A+OASo{)CYn$+d
z4Q}r}^I{HH94aqg^z?k!!cHM!f!|f@5Ae$fxvICyFclrr7FVcD-oIeN1-(c4j`OYt
zE7>U&AD+HEY&W~d{-Wt6UD;PVKXSB3%?)05*w{EwtB+$=Tz2GT!QD?Y15|??(sGUZ
zo-O*-o#@mX!d!0g(s!*Ei{t;U-f2-u7NVitP4c~41*NQ_R)<Y!W=h#{Bid|JsH{hd
z+Ya%v<M!QOtPbgh#@426Iw5iG<F|<_$KE{SR1{izd5Y%5N3n<9oENL}Eua1%^tOG;
zPG3i!(+#mZG}hc*`!gWXM)Q#;=ci>I+ySe-{wIAeHJcQ#QEdN~XW1dC+~j>Sg2%tR
zsiquXu=BTsU7Ie$b<uOlVf!z!S}T8hq;2s=t=DkkJVBqnn5)Z6bpsCWs&f1BPtcI%
z+SH)Fr@PtOwmF5p)Jx=0_-DC0;`8#tHP4&p^dFo0Kv`u*^X;@dJQZawR$uwty*(xx
zt!TZxeXeXk)aTA%XOkwozhBQaOrGZJ8=q!qbFq^-!|V7fE?z~az71s#E}HV6mhu-q
zC}8`&m(Tp{jEtMNSp%nZbTrk~oD@70p!6+<Np-^ek8u}+uL$hOYmaeTsdpm$kT37;
z-3oWpvllsBbU9I;|7x#XtRutUoE}fb6wfvz(|ZTP)$|^3KKxV7>c}_UI?uK_s~m4x
zFLk<iL2&sU7PYwBzJjYgzHr~v+#ANx8)d`rCbhhF)uh#%Q<rab&UF@CE|LHKhd~~L
zXBGE`aNd_Qj5{p%1n>s^7ISiAIimjB-D2JG)c^6zP6<ws?Avtq@}Hiwo=)7x6FVe~
ziUdE3R6pxc(&yAszuTa%C(mH*wN5muB}iJwmZgt@Wx<5%SnK<m?W_ympLr3>u=d$o
zJv9-j=1E`goc+8vS5sqB(8`AJkdu#A9a`<&=M!!AcD+X-JM*ty6Sn0>|6I=0zr`?U
zWAM-DS5d2WbGdvrVwbm)IMpsy$9Pl!p0{L>to6gw5~UGaJ^g1`%sytj{{G7i$Gm2F
z_7)uJtZ+TGjk{b>Fe7hjocgNxML}n#Pdcsty7qyDWAc<W=UbfSu39OVHCM3zf5@J!
zNeRa<o)NsdAjU-eXvWU(9=vJ-lQ*7WS|=;$_`-To(42;xthsF;YFt=0Jnxw0ZRjFZ
zx74+GLxtSGOB|2ya@?@ta5m967bhi9{Y?9+a^5S=yCG?91r@j17SGK8bnjQ@Pr<hl
zee;_%(!Ol@($O*Xn6~2u-E$##s<(B$%+pLh;J(WAN2ut=i0d64UMoFjZ=b$0?3h;O
zsz0wL*0_n7lwAIjt-gQS=__}Sl<S4@wn_Gds$V&L<J*jdu3lH2E0mSWbnliMNxk~~
zZ>|=X%eoMwMa=4lEp>R7pDurDer8rl{)X98yY5bQXI4CVkd5`K?5BuXt9SF7@7kKW
zGw7XBfY0mKOI=Ot=H9(L>(O4lpOSlm%B+s^zU;19pZBON{NI(NUt#IeA%+S*p7Gzq
z!V~6v?dss#(<d!`#pjY-`Tw;IjXBl-&*%94mY3JFe<G5?=dyd{jgI7hi>9w;Nw_!h
zTzhS)?W1pRc_#(#b9{f}Mct9_rT%(h+ze&~pZI31J&<?pns#?-j#ysI*2y_js;1XG
zkeu+sX6`ZJ`O`fu?`*J>yx79gsJvDrefOOOdnd?TUU1mG&3Uu&x3j<3Ee!qpiFf^#
zmuWA(RciF(c>cw7%PMzptla7sJ6&=6G~OAOH|OoG@;lAevX?<Lqw5RD&r=rdTR!@n
zxpsEP=4Fq5TW{yj=i|R!pdb}zzWe6ulN%N^_GHEc&uCwLy(v3j&z0>{Uwu0I;;;Rx
zTWt<zt6$%qR`<YV%kND4ojH>Nt*3o_|8TaP_Sdz3A5}F!{PbS1wB*qj5#||<X1}@Z
zR`FJGeck-|zdwh_ey8=bmG2(sJQKHGbYam)o_B&`k7v8Q<6LRsRCa$!N%3}%M>_&E
zRHolKGa<_QftSohQ~pH_W|N=1``6lc*rI9aTCFE~5$du}^!wzPk6xeKle=Cv;^yV)
z$)CdyFT1(^YM;a8V{6Jv5*{h3Ond!t!tM-{BMTxkWqvTn9zScVQ?T>Z%7h8QbB}LL
zi+)sV%vdoqcusQuTC-?Tg_ClE8;^##a8%X{u2_Ahaf(tS<Bxf(bk7GcHMCB7E3i>b
z``^#Qr#}47i=KXe*8Z=2rkP(%Sta9+dwKZG4mtTX!}PdzWKo;D-SzeZ+|%FPTFY4>
zUv~c1q~$XbntXQDxmi4OIWhU@ue%dhISSjI3gP9hRt=xn`B&%WKgG8{AFcF`y}Y2C
zEv-PuO=EXOyYJjp%-iygXs%#-Vc(X|$8aVpBifRE>&LI@N2XYAZ@=`{;9VKxgTqw{
z+A9`UwitR`Ic^*#+Ftf`@iWVCo%WBLd=?&yJYTomHkL6uV1ZJC;S8lYYZo1=mk$1E
zqp+-Esfzi;z5Dx@ca;R5cq!ODxBOV?ONj_!_a{mx&MtJUsMuhw#PPgi#;^4J=(6@N
zo9>r%uA8>zO;(&s@RfVl1%kwmHK%UBzc%-prJ(MUJum)gEwW?U;H@s0@JZ<bm-){V
z26t5MG+kTtI$t>=BS-7&x1wO)0}1bXmI^OFGpRLsYQX&kdmo(1xgq;##$EoF%@qn4
z56%C;x`k75uTrPvgPjXzC%2nqx=oQ0UU|3Vh-7S|<II;V(m9{>A1FJ|vyhP5<sV`H
zp6PYug{9ZN+5Z$Z4-sL%^XlQFj}!VO_8)q2d!MvT#2VK(iY7cxFa1uKPV$<*(kdw4
z>Pqji_s)-_&)lqvJD$s4!Jd(LQ}V-$EBo6x{Z7OcE?LLI@Hw<~cf-E*>t6_eooY96
z^2WHeKIcn+#~yoB!gEJ^lfgAhA*MroKlXXAnI)>4!LsL;l0p`<$<Ev9XHI#pWZv{V
z_sqT@dC8^x@p&q~LP}-cdn!uY{;9BcZBJlrVCxfWWq#(Ywdx*!QJnSq1j9FGfx$1@
z*1b2IHu;=G-|Ms!t3*`&cS!VWK8ejbxZnA%s&$EK?TO_2PC>TSR%W|}kNbXC;-6Dt
z-Q4K(uI_W$A@xW>#&ds~sxm)meipeJ9+UmAFLe5Mh1-EH-?l2T<r^vI?Y(}5E2%i+
zP3;U7*AoR>{&;?UyyAR=K^yDhniWh>HXU6T+{bzUaQvpTubG#NuikO|;fjt+j&H5+
zGKf8xWO0=Fp`$~_WlzbSS$&aGRSk1PtbX-z?hkpmQ#K$*_ED<C-H`Vy%$G76M(yUg
zxMsTagtLOlKNdH*hd=f<UiNxfnnCu>_s+Lejn3CkS~``zL2~u#9XtPYof1sAU|}iq
z(d$r-(xZJcm%6{oYOQm3{`o&%XXlX~;Y(r9G>U((5)w-alUAQJ<JhYQHrEzB{G$5j
zOUv7hvKy_FrluWqNxoI}U1X=OvX*s)`?*uME6lgo@unYU)GUkTl>8g9hKJ#aTAzt?
zn@r?^+jfdl34%i5`T6~NX>yY$|C`_{e6EjY@~vqBr<2#p6|jC<FElIHDX(D97oBNb
zPh>LNLwB72Wb{ty+rIuCpNz$_TPFTpVaRO|yd+{tSklUU=byh>A0yAOMeeGI<mJh;
z@|3jdu9)UOzE@kiZ}!QPA8nT@^JzO=e$~B2Ddgvq2fT-4+S4=bBJSIVGz%G8UiDnB
za`7w29v%HB@5HRjiX<;}bS7m^n!4R4O>&nne`oO?*^qa&Q=)TaN<TeYxX5(&DXya$
z?o*a3n`WMW645Q1$tb@j=kSdQ;<9@yJd9lH>mzR$oq1W;P(I=D`<KmA*&OVW)ndPB
z#}sEgW4roVs+8%2meL|6`MLXbW$kj5K2P|p^7pB~*5`(WJn!9)g;&0K;g<HJe)B}_
zWvBfn`-ZL0Wmhaa_RON~)&=?1buO|Dwddz~{Cj#=VwIbuKi^00hz;GLvNLXM%(}ba
zpNKj8K8Z!2WOh&8?~}oMKlIujzO#{u_os>8nK<vul)ard?E{>CoGR>mYPj-(w5`o~
z{aaa0b}gmpYi5NDiXY!?WoCVR&1@sFTy5b!1$n)ytP9FrEKV}kNJ<==IIXAQXJ3y)
z^j4(~=lyF|#mYXuE_88);f=Q|^OqMoSb43JdLGcQGS4jR(Y55?*#f%^bT1k6trVKP
zMO52i>ay9dmd!VJcVfA7)LpCR`JNuZlc7p`=B|8nS()`vORR#!HQ%o3CFx5PCQda-
z4c#;6Ku==L-_s}ON}W$VWb^UJ#nc@y4pl^idUml3=AZb_#K?Ov@!(09CI%*_qi!qb
z{gA2td*?*0(!D*8cXv&-4G83`KOE@V&T>=5%jM$L^A9tNzrKE5bz0mbZnfY!*_)O7
z!<d~nzLyj07f${D=E(QNt|_tJGo$(=47W!8-C6ok^mmle+k3WO88h`eW@-EX=CC;R
zH!tz*%)-Qz4d>1tWX^S$Df-D>tZ{I8-*eS7+e9|L+V^16UN5!TrF-KSMt(2n)Sg?@
zU+}3l%rsa_OG8QHO7J=+zrql^UZJ9-)T2EXI^wsNCV&6->xNv;elLsn4;IF7?>uR9
z)9I>7zzMbDBs-~(-!i(kn=r7NOmN-*lINge_bpNRg8IX^E}KYNc*~e9<ej^j*PG+&
zGH!NL&$TnRhb)P07b)=3e|`5|r}_0g`CCslzsY?z*?)!OZsjbQ)72dfueq-DyKIin
z+&o!fv(ruXzKm<fKHqtG?QG$BZvL>1?w?mZ@Ophu#QA-iLDLoKrKk9=-COZ*?#-m4
z;^mt~*rlUB`j)5V&e}h7_8q6QmXA{V7}X!F=~*6jv${9yr=p0)t02?1^ur$A8RzD{
zXgRvm;n%YScU@kWwpDKS@1qPu7|t#E-ojbje5B;p#}uxA+vf2qntx%kY<Qf!sA1CU
zOo8}W(NgO3{kvEd9$tRIbuLCP(A*#+x8h_7=kXBj%1dS2CjJ(bR+M?Xc81*?$BhTJ
zBuo=@UdZ^QVsQ%dzSBJ=EsK`=Z`FOqy?TB65eX%us_9kVq8DA-ulUp?=djKRJ_{d~
zo7<25_4|3Ia)WPt=2h)yvHLE{xa>N{`&EFex8wbfsW~C~pZ@1`#IZSjc{b}MPyA7(
z+%W6vm0FLVocT6&^VYOk{BP}kdtbfK@NpBT_X@Yq(d{eUS>JE<GD?2iAfugrStPAh
zFTHJzvUf1AuloUMk)m12feV^$6wFZxC^NtA*EHR1Yl&*R;p{obPwl_Udsy*U?QO=r
zI_?F&r{<?tKV$!XxGf-MwfXt&FE%|~tG05p)^Sh1PYaUvU%JUw%q+6XT`>9SqnCLc
zTPCFUbzF90Oze8z@y_UtMViP5DaCDbB_t}m=f~)_b-h;o=umPuzgWco{`O~$EGDkT
ze`G`_Y;57QG1E<bd-~4?3*P$uJLd~Z?Ahg7@X$r*&!62IiI)WH;+9_AF;(Kra}%kG
zzUT9~zf^~M6fgIhob^Uqy)31h`>u{{+IIK1)t9S(@(9$cIq^+@V6$w4FGuL?DN6S?
z1w9J-syhA6?Y=j9R$@~gEei?0dyg@`yG>qIdL@U13XA)rkdKPI2HU1MInFzHZ=J=K
zwg5NATcRH)?d9g|X^3#hx@4?k)p{VzPEo2YYE`JR{EfA{Rkt5_Gog#KODKu+u+;*G
zB<BOHQ{L1qS)^Db`f-}{QxmJt^L`chKGi5~V#~V8@N7Y!hqd$8M@!zn4!^ae{*d9?
z+wr@MG9-Q)KVlY6Kake=Q?D&x*^KPSKjJe&j<9S{S#<vQ^fs+TlSdPr%oyg1MQw_|
z?7Ut0n<Kxq-DA&tth>UlwuTsfe&o95nZ(;^d|m4cEZ7=?gtU_Ocit@eoV;?f$-{^p
zGo#KfuNL2P*X;hsj2w2?Lz6t#W*@D6km2T$BQ|?>LCRD+=4mOqM~q(^EA*?bS%23c
z?TtKt<ww7Amn-i@H+mQ*DAc~6@MF5RiiM%MdElD=_lxz;IJ&S_MwS(PXee2+bz@+}
zpYF|zulmTeoBp?$8dPW@_@mrX)h+f$Z1R-j%kSm<+3?`lENw**zb%C}iE+V;!=eJ}
z*4z5V7xJy*y75-wr`@{RBezbQnaVGmv*(gr(?KakU5{H2IZki>6!kJ`!W)<A(-~LD
zPvTo~;N5`@S10c)t7GuZy6BvCPby!=sFfpgy4{B2tG|49&CFaYom{kR+xgRvUl;M3
zzw+~`ncl#<`0~RU-)E^F`}NUf={kWkFK0}6byUog<-0)oU)Sa<oHlnK{Mg*UysM{L
z+WGy0MTM)M7B8u+aPo;%oL&3<!@SQ`Tl3`CEpTdM@B1&Ft9N@-fA&W0yw8t<=IE^u
z3F3RUs4GL{yW<JpY8JJL4{I8Ze9`URy7?ZLrVwA-*Du{?Uo1N*P#ZFH*M03h37)SK
z%0&e;&0LQJo(*8TUTPEYwWa^)f@v4C!e#rWJ9z}BA9?aU-pB08f=_)CujR#W90}v(
z7M5<6DcfE#f64N*U(JN(=zX8q`|z5J#N@dv`7gD8Y|2zrH1FHC!&P8TQJg#f@tCW|
zcY;<&vmb2SyR7*^?UIFiO|lF8rY0S|XzaT5QB0ql-m-;@zMs=NY)~Qpv*&m65mW8Z
z%k!oS+&aC|_l`=u!JXcpTORS&Dm_`Utf)iPIcrjl^VJ0%SxN5yUYMObe#VMXr*DQ+
zsG{5={-7CJuk6`v+b-BFZcPc8<0oEFYgqX5;ijee0U@rro2u5!9?713cg5tqJl?)O
znU6JBcWjZBIPbpc%t?)qJ5wjzKQLEC>6y-2-k+9=>2JAOHk}ANpTRZL;ldm7Cb^a8
z<~}I6{b!-e>QyJtPHl*O^IVYOb-YZaSe@epw+ilK_I5FbY1jJhEKA&HzJKY&5&^}s
z6QYka3U4QM{s}&-W~dgc!0d0rv~Tk@KCTU=q6P0-J|urkTfbaw^~uK4=p)?IwmdTI
zyXGxxU7#%RvDajZ3TJNl%^l~GgkCL4k5YbMSUdfScR6=WY5B)pH+>iUJS)VS`oLt$
zECa21x&?oBPwD*_S$yn(Xu_`WtOItPJGyP%;*JytGyYwrZ<tYkW7UZhiVKcz<E^n?
zaAbQ>viXAEOLJLF#pP!#om0?JX7gJ2?oZKW3r-#p-^;!6#jA#ekLA?QWqtdTy4_5&
ztI4)wf_Fim;64SxOFLFB_;5TZ_Su6^qPDwMtV|bv^<(9%m(y=01+3BHEu5qg+sz>O
ze#i6*&9;3PIbO!({p!0BaMXC+9y#ZRn~YZr*PN}np)mJmk&K|f@|=(1{nKyl`ZJ$T
zH0?`P<Hy%)!~D6^^LplTKDnuz`uTqNnRn}R_ZYNIImS>{+4sHg_l-Xr+>#asojl61
z+*5FsvedjEZWD9N3nyi7ntR$naau_2k2h{ECik!MRe0_z($Qf^&VKM^?QTJhx$1?=
zQKvjMN;ho%b;s^O+Psw=KkDvjr|Dds8JGHg?J;LRw>eqo-&yn}8FR|k7-V1FQ<%Uc
zD4U#|neK4Dq-X!^=ezs;?Ut6jahtN5Yv<B{b6XP+Hhy>BKF9W9)6v$LrS(EDe_Snl
z<M+2LIQ;R{Rn@;jcw=@e?YiccvGK>=S6L2AU6*IipE!Xf^FnyChRpw$m0P5b8|0+C
zQ|)7sTJuxUG4Yq+@-K%L%v;)9EI56Q(*%>F54#wH3peykZFX4i=Da>E_(+C>>#E3S
zL4BKx{-2+qUEt!VcewQy<5Gq%eGAro+S;#l;Nfp?XHFxvl6hKdDsJ0u+TLNl<za?K
zb^ZmzO@8~A`m(RB?YzNsY4QwNy=#L0ZKqT(q#2dn-r>EPn{ST|6QB3OM~~!QK8@zF
zb-wm1@*5B5L%w}8<paO4b+F!zt$m|fXLx^Gk&v%e;*O^8GJ^g||0CEK(=)fGEo@%1
zO1{X0$v3!oZ}9j2{Vy$h!<=`VxRA{IPTT)&Ys0>E$I@CZ?@6l4HR^i9vSrg}!FC3|
z_pM(|_~uO0iO;KiEbq3beAoIN*S~E$A-*-o=Ox40UDtG6Cok;1>QKH~xnA0!ch|#1
zl^3KBUp~97h~<<~?}QcQX3BH6RR*Y-Ow3DgTrnY8Qv5_(3HQqSK5e$Eo5d~%#U6^*
zy(K32(dVud<Fx79EFN*O6}Gl<Do)S0IJUPicx}Scv~)eoSMR5XGBsRSuKIcH*Y9Do
zRCi^R{8C!3&?DS+bMMPv9cC_4)4v(~IM6-0mbqx@p7I&`ovJ6Vur+R9I>WRzYSqlh
zT-DHtYI74-yx%+P{Z_{kmorn}PPA%GUh?tbW*NZ^lg?{4|6pYDuwD|CEYt3Jp6jCW
zsrp+-gB`9r-_Yt>_G8X=%bic<1f^!FK1!23AZxE~*U@!zU9a4;8AbIiHv|nG&p&D1
z*BX?-e#Gg3eVDEMpKm-;Sxq+!e?Gsn*wDMwhx37Pz$epAw*98_C(pg|(phqPDNE^%
zi_g0MGqnBf*4wnyDR9abkt6rkO>x|KBfdCs<MJ6t)i^eE`pU|2c3MrFb@+7ckB=9o
z{=K}#K<H_p^KzS{d3sByNF->gWqqIj(A%YkKlR}|J>{3@tjrJJ+V^?FG!{ksw97d*
ztHX{w-qKgGchxti4=1zDEOhIRmGfuLXGkeoq~j$1Ih?=K;F(9!vng*5P2J9Wwfu{V
zWV(t}ccF`n$n66*X*!v$A^yb&lr}CtY`W;{mCH9DH)(e?@K~3!%z5-$uCBsm&#}6a
zg+&);X{9wOJq<Nput`?vn7>X;hu^l(>V}3orwpztAL>~Dde?p}J$50jlau0iB?vsZ
z%;u<=|NPKI+dl`kACj~3y=2(Tb?j=j;jb@mxmG%_o$=z>!FJ1xE%LuiTlbvKEtvSG
zUeNaDx*Mf0)*fmLxN3Fu!(xjq=R!P$j@FB6`spgPc<s9w{`2U4yEyY{Z&^L|?B9MX
z>z00InuEjXtl)l*qnqrR_vB44N|9aFwnE^|V>azqCZA{V7QSrLYn=2&*NNRi_F~(l
zg@TJkTen;`-O+B+b9b3wa35>I8@K)K9r_RZ-|zUz*;O%R`l1PmaxZ>=e0Ct@h--=Y
z?F-Kiv<e>CEq^;`(e*sfJT-%QMi0S%Wse!ORz7JlP0(2RRMbz{uBhtl>B`q7Y2`Z%
zmLFEBQL&r<al1fjR|iL9=f&1_)lZ_bY!5KJTDjifuawZ{U-z7>7BGlhyOw><Zo^XH
z-mUki%w#CZmfWCw=`K%1DvQaPq-jY`;!f+8B$B4Qk_`KPrY*_oF5kM!t@5+$t{icS
z(Es=Lbk@?%+LISZPTuGdf8T$4+@{}i-^a(!zNz%$UG}@M-DQfU&l(PgExmdwNn`G=
zso%`9wkOFRV*I#oyV~P7mo)<)W;qwG@wmKw-R`|cVNRyn|JplEu5})661IAEYu=-`
z&B2$yM!Bj;Z|zVuKOwkiTlUJe36FTi`ew#2ee+=6^`gHEHkb<T2>Z#JzKl=S;9Zh-
zMz^(*g3$cmdkg&)XGu$~z9}T+JL?;xU{-N^DtGO<)|_0^AN%b>jnuX{?S2?r6aD{6
zOaFxTOT~JleocS<Mx@iB^Tx_g>oO(kW_K00`OHdO>tK1ju_okD@n`<oVvB!>vR?`b
ze!hTP<b7#tv}enkZ?cQDU-YH#oEOaY%}ubH>qFnV#li~xp~pSaF5L;bFZpEJAFc^&
zrl_bd_DfxNeGTtAsqo0F6Bd?RTebTXvlxVVH666y#ot-6VD6Wk-&Rewf5mmztX+9C
z(s%izE+f5fCh9X@d!+P>TzY5y;zGa7cCRp@ee0|zCi}nM+;Ha0f|ONHIhA*KZYxT6
zeGuESZvSn@4$kN&=~A;I7cqYCz7inoRI_ioJF~j$d+Q}DPc-SdvAOV^Iq!d9@uVj;
ziLVwY)#-N3ZNFj2VmwKg|Ml#1ZYpNI!VdfPEbqK#>Kh`*obIQ{ByJiQ^psUJRlurP
zt)RPju5ijmj?A6!TW8L@^!{O7D&yHS<M_P3lAS^SAKQjZZHf6f=l|TIG``EzZpI(J
zb6IxwH->bdN5&<~J+7`eqO2mGamzNcx?|>wc0GxUf0gELlGYBJsdTmcwBytRg<1Uv
z$_q}koNlrcUb=C{i>@;7mu1|yO*#L+x0s^E;1>AjG{fqhdpEC-Fuu~onP3_q<C(W}
zo!A;7C5=T}vN*~M1Ml~?$Sl0}X7^v#f9pcE{L__tME2*NpYdn;4v#I%MK`~j<Q(vA
zXOh%|lbmb*>BOC`H}u+nIO*{h1y!|7y;I(cyBY*GmHrSv>u6qBkXqz2!`YIx^uEZu
zwm99%2P(F5_#O{7(_?qF*`&l^x!CXhzKO|(#(|nY`gSI|N#&_<d7Sogf5ZA>MMGFw
z%+jt@E+yN(@?8RPHrqQtdK4e@Qt9~lH>o67+iBb0hgU?nyFBiys<>!wTB*K>OW?}n
zBfr{nG*8}XyuH#%?`8l){Z-Ctr;vuXbG{kBUlQtNXfVfUPqpNZy9bu0xU4K;6ck&`
zbhzzDpYV~5emAP8mOJtE``H%A2$pXA`Xgg=)5MQ;d!rU-ub<#tF;Q^dH^HJ?i{I}J
zF)iV~<$hPs<l2<{hG$Q1HRx8)Im0O1HDSYs$Lkhe3qJ9ER@eR2YuVfkqLrQ$tS!Ir
zW73Qg)5zJLd1X6Y4AM_+Vc9Dac9i+X%7(jcQ&qpb`_ps!LHUL7s$=0VUOD$Il$6{i
ze>aWm>bF``pT%E#O8Po0a@)Ryoij@)wRo=kU-p`Z-qcyQofUgeSan2v<Y!Ebl|Frm
zp)2oco8LF}(gm4{+^cs#TE95)>u>$d5idp7)tq=3R65&Y_N#S?Gld@=NSvUwxxf79
zX&Y7EB{M(qvwqPv&+Dtd*j9cZE-kPBrJ>rJIVa*6Z&Vz~j1IciD61EEdP<|NR`kc}
zz#h&m)xIm`6l@>2J5?J$eYG@ir@hWx2ak)VCSDZHV4W6Y@;1I{UZ3ubzMNK(Tavz#
zd&5$GnzY;!`|ZwmzMbLwC8H%r=h@DAR(QtI=X*&_=Ss$o<jylEE~=i6N%3A?udgk1
zC2!f^UB~yFx;R<xghx2z>pPXT8B=&amU1y~XsKQ{Q=#%jVUB7zGo#phyIF<1jxT4<
z+p8j$Tj$Z0-n>v^$<wD7zlPm5{qOE7Dn2<kWZg@S_kWBx^|I=|T;q`ZnzJ<etVW2e
zfuQ?=iFcMdUk=r7FIyPqx6@kr)MdHWR~1<y*`{1avy{$-a>V}XT0C<#`*ue`^Uuca
zCDBWBCZ9?u^xn()?8FuCxxZoqUtE;j{-yg+R+vx$^HU-Hdtdf<wmm(b^42te_1jB*
zN<r@DrbxXyczj#--9528L<+rr?g*?pGP_<pDCIeK@T?=7I=1{g=RaLfaMSZr)q|ck
z;obh9R%iX+;-D`$>En-p6YrM$Y<|=nweYCF_vf8an^`s%gn1UkaF@sOIvlB;Wm5L2
z)R5C&kWZ{-+yAL*F}Hv1dmk=!jrrI%+x%6TYx{L7%$_WoJbm$3Vcn$Q_9JoTx(;(!
zNdIJM&7O66fBB-OPZzXroeGYL@-Gscxci&?71t|QqT^4o_q<Fg&OaQ_bN`Xs()00`
z9@Tbf^51yy;?S~K;a2wYy^}0@!aKi*Hoc$!{mK~)x$O!C*$&oDKkEzCytA4VXR-1m
zI=CIU`0Ugi6{|H5Et20Zo*Q?%<En*1i^%*3mVtT4reB`bk>+drN?bgK>C5U(K1&v{
z{q*57bN=MVVI1}2L6jjwbW@K-|MF)!8n#K^%sLE9FP`3gsW;)tJ(jPsm(^^(WT?hB
z`mFyYdwZAsiY(FK(z1P*cUI|Lnw-!*^U+rKkboC*Qaa4#0`I=P)%KkAaPzXQt+H`8
zO8Zjf9CHdw#qMV1JBNJVla+V5G)OQxP<z3vL)A<7HavOoZ+X<xX3d!u!p;u;4L*8X
zpY^PZi*dSiZDnUhx>;^crtaMhr#DUwFx=aDuFCd$oMglNx1U2@MG}5{m@HrI;<o))
z+WuhWnyN>7=J!}bg;-;k&;Ka9J!|Sm?T!Oi_IzLbIlWw~S@qkr$7&^SUQF4moFJ2&
zdp<Jj;+Yz!NEg=wX{TgPvA>$KHSgf{g?pAa^ytrDzih(#@2~FMp5XC#ZV}V03%gmj
zFVL(wv$b!&DC6&s!g|atg0d45LuG!{Uu19!2sFL3XPW2EU5j_TW6CWQ`hF~J+uo~h
zk5w-24$D=y7qZ^{&1Bx1j^nI+uB@Ux+`m~Kzsf1x78x4Twm8*c{w(V?H(0nf?|)P0
zZgthC{NcVZj|jP}vyX+A`I{~(WY4~-rrq(|>tm9fzshopQzdt<%EvCL&U4!8FP5-V
zxmRc=*PLCtACBaOES6ccp=*cr8=f1^O?rH1bhYeH9I-fh|JS|4CD-5e2|P~Se|>^g
zut&Eg-<rcVTEa_&o;tIhv8!DER*8Y>$XAQXc9XzE{=u_9=4dW&n0LNBYnQ>kU3Csm
zp7hS#Sb1RMKgF|b{fiz-X1BG-E&U*}+&%f<-~F|l+t)hl%(;8FM(z0g%PuQ)f?q1%
zbgkwpJafi!lIfp{U4LVyA2rZ?=6_0{bnzk{&*QuyX>sq1tCoGfw%K}(?w=ZEm7;fo
zle~1!W%cZPymnj0hgIhFQ!X>D5btUh%-<8{w#{t)25V!cGsdT9Zw%_*Aa4Kkt=Y_Z
zL2QjPrOTC#Otf`Vt_CFr=xONL_AE$l+c1rZZ!7<d&Sz&ESDkjBZyfObX<rjt!dYE4
zqYD@IHz=r>u~a80J}&<*dh4utt$TRx&yK+C+=L@~lIv3irPw(6UKCo^<=4A1)qQNy
z&+3}KUioI*_iZdQZ@rQ{GUI}()CTUimnX5*9!U%SnZo&uS=mwdK=rIme>WffTJzlY
zUW=4nm1f``m(<P9TvHo(s{b?`EtgopT7THeW)_RhG?@;)L+6$*<L`U^M)H&Hj;EdP
z#2Oo?1e(8-ZL*tox?p*wHJ9y{hl)RpucdVg?)mpgb9vS31pX->l!N39Z~9d)&6^b~
zR(|NU*#0N_LHAplFCOeE|6sIskDRGp&kVoa?bav$Y}y#J!B*@7ci{PV)p{<=zFroX
z)YqXiFTSKR_*>rFBNg9F6g3~IyZ9_|l=&>NrdW3=lUc-(eNN>oq$ghMk1l+{-<7db
zkVieIetT<z%nP$uTyO7}lpo$7aAnEsdaL{gvZYT9viId}IHYehi`6%C{u-@w;v%xy
zo9>-?WwN4oe`;|41*30sne11Usju{R6aBU+ZSMhXKB?qCTG6*Q#K@Zoas1!>qxwYj
z?HL`C1()x?e*0Rv(uyf(Z+b-j#qBQBHXho0>-GAKzpd+zGCWfJ@bC)bvFqP5h5wqa
zt}WT<;u)(O#BuMkmGF%ks{+$~Z}pTPFOZu4%Kg|m<9QO+a*2y=&MyewYs0taq>ziI
zuHy2uUuE0Zw_d!TboTk$V>Nfud=)D)Z?CtRv$l@$iT1h)_uK^EEqt=b@$Z=*8dkrZ
zJ~i<bUdcPg<}veqV(O{i^G^9bV35~%Q5}DgdBugCFPC?nm~^JTcW%AveUG`nV{NkK
z<E^DLb!FTBUi)vi)=Zam&TjVni?jOL9AjgYSDf|i-6-ANuq#g{dO_DT?bb!{x%J1n
z-A+uqw%B9d&aQs{KUsgmXJ0#V^us<E^#`&(S_e+d?YdlTE}#{E_}8t-W&4(#{$l45
zeeCpu2^noiO&{@UbvOC>@QZFS^yuRL#W8{LpSOV0tT}8;L=G41NIS~*F!m|?af=|w
z+df_MpR$~Y`y-V%<GEWvLO>(Cd#C&Fg7cX^hc+roRrzvpEr~f5ahfIKNGH#Zrd5w-
zM7Q-!FWawrI<Pv(N5#4M>nFeRrOr2&xlR4&<)EDJ)EXpOy0t=k`li`0kDK}=OFWqI
zY4^??=T?_nk@6z@DutUnW%T`a>gxAxk9@yj;YCCK&d$xdw5+Q$8$SB%WL`Y!ji;#A
z!LBVP#h!=4X1l%L8@{bKbW@C(jojITfjwLIJqlS^=diMBGXv`tON&3tPROt*?b>wl
zNBE&9cNRYoXcb|&!Zlm=%=`ES(mjhZOZJFPt~z*We{QwWrtDk#J;{P6zDH+sK5X0T
z!&bR{Wnb$)Z>wY9--Q^zm3>qaZg*;TQ2lF-^GBE1`nQ$`MLw;U`0C83@ui8g^#7vA
zkIgP=N5sj=_-tQcrc`dQo^3JvVONiX%4%!=L^!YCWVA7Xb-UuWgvg(BoD04jX8MqC
z-J8WaWAWe4C!H5tV)J;7&y*^uIZ6LZeQ$Vwp?Zk$d$sI$4|cp=5X#H)Nm_aD@$YjM
z^JmTsIwAcqD#+&k{WT9~&+IL249V#I@gch7t#-=px^v$PR@nxA{SZ)oqn3jwJG{H|
zi?8RYX^iiWoN-<tI4dL1M%?rL!txYG(=%^v-ppG3!}4Q6pBv}Ny_}13-#t0P)9LS=
z5Rj@_B{{2bQZwU*MW1J0UD~IXw9wL}<@DMK#<!=H%w%zsoM!5<&DMF}cE$Cj=MtL#
zZ2Nk<vD`f%r0>ktoms5SXU-WaJ@IYMy1!iX@PWJUY-c;VXV>NAHC8Puv@V?)*v)Co
z(DOE4z;pM_MHd#E_;N+ExGtF$aAd9a+^|Ci;{SJWS%%$jQ&<qmQI^~kqL8XmYq-Hp
zP$;bB>ApS_TgPsR89l3a-TWV5A@XVNuU|8c20eVgD&MbDZSJ*<to^4oSWnp2%sd{q
zM<T@a$mNzrZMBub32!dv&i(#Fabmq#lcHt8`i^<~f)0HTPvXtXIv242X*^S6LH6S6
zBUd(Rb{sBK-zD*wGumiv(cdYTGmZtMhMk$&scjv1%ud58>XrYdNC%xSx)=S!j$}TM
z%~6@O=V;=(tDBut^_|M1&G+Q5nrG<cd9FzPPO5+6Gzqu6?-+b`Y;mjd|2z8}uY|jR
zpYh5iWy>cXRuuiUTy9xOo8i4pU8lX@*UA+%$aMei<YU`u?3CoWZo=(?0vD0ibxfhp
zZtqgRzqK*P?COTjB~mX_ZJsZbUjIBLIA^AWOsU3(mh1Ir^1>rd*hf9JO_{FzBG;{p
z(QK>GiCLb#&B99$Uf7uT;N|rR#bF1gnIGA;??IsG-|o+8;=dcd&wgghm~<_p=2`Q$
zIrZze{#~$F#6Qb<*}M3h=NDy#AMcWQviGy+#*8<d(mg&6O>Kpxb9TkbMjv=O^GWcx
z*AJps7KRI^|NnWd!@m0W%O7%!y``#KFB`J2ow?BHVZfQU=MUBF^x)wwj6Z(oTVIr>
zK+lBDZCf3u^~~5F`F^H@>a2syIS*fwjEK}+7-#?NT$^2(+`^+mEb8qt*AEBBxX5ho
zc;#_B-oIROdUie2ME;HEjad$`C9UpaUflI;hWXT^>#uAm_;50Njj27?yvKFtE`6Ev
z{=p`_*GHX>vn}9R_sCLHE4k>ho9~Scp;;d+UT3x__wR^yUhL}VUApr8PCb{ybAQcq
z%<BlRs{VBC#e$bT{J*Eo__6S#N=r<6ZuhiS>q84noY>g76ZYTT#haG9;k3w?A3eu+
zIL%Z`HkFlAl>g1m(JUp|`>y!F4uJ<>*^lNao!WUg^n-X>zv)%W<OvHW99!b(6vTAR
z&v@o<+n-<dGR?P?c%|+l_J5Jr^u;`f8(y{kp188?_O`dYvRtgWFQ;$(9HixAp!~vz
zH>^QG?X{Aj#M%|xSxswGr(JG2U46A{e}-J_m+#3>4{3X49?v_>Z(}Y}6nXRO)33fa
zzfBj}ySItW%Vo<<zsJ8lER;39mb9K`t@@l+shPJ<ao*kjop+Bfu*j)8bD_F_#^unu
z#$NGkj+4$0XaAa%z<*BFF5fqLnX0<I?Uz|aH!tlEJh7OQiABHkF+*(j>J3Zh+>G00
z^wHGu_VMd$LU(C%h*q&yo(OFBEs^~Fb3<?BET+DRYb?L^-VZlhAk<e_>ROiJlf|I)
zNh;##;*Puf`X6pxBF_EZ&9PAV+?gdS7aux(?Zy9NS35&m4uqXCY+LH-cS42rWXcig
zZo?LqNz<cQL(J12eUH7o)MoOn$4_dj*NCN0FI&o6s#nAtmT>Fg3PJIGcS0lI1x{xC
zULw^Jw>Iuov}@V6dihhgjRY3)-PBF{Y_ziCMEKHb&HI98cm8mTUE^8zigV&ri~1Lr
zjwUu7n7QblOI~!)&$hiw^Oih5CuMa(jA?#W_~uvZ{P%pHW2n%cr`U9=QCa7tYPVhK
z2E(o$ySfF;_SOViKHVHT>CuW6?K2s970sK@mCSiKqxWv;i;wQtnWk&#UVb;HCChv9
zzJEKn>|u|%HFZM&-QT<J=I#sLcO_eczbZRU^uz67<!1-hTVzQIF<+k6ntLe4fHkUZ
z)3r3+>1_A?+TWNvXkB;W(|>ZNa^1l!*|QwSbKKUHrTyC2q#*Apmyx~ahW@SPT{FL2
z3{!DzJG^$eY)4w8&jy+91r5Qy9qadexX8Ri)9Pt*Wlr^uMPE2~FI{jy>{Dn_f|%=x
zDw7#IDt<iOvU%AY+cT#`90ir0+ZPJvm7SfiNKz<&TjTYPfN4t|Yn^@w=^2TZ2Q)nT
zwo1m5t8@PK!V{SX4%;bBS9-l*k7AEuGK1vd#V6c8L~UNyp^`G;VTt0glPVs?tODQE
zZ%595wL&UtuF0NRkJ1&yWexAoTsL`YS(xDTe``+{tXBKG{fnBBp`dVeS4U-gXp!Qw
zbhDr$#))yWCfyE-e|F0$|IC!P6|+|!<Ex$@lhyNp$NuQG#7)oS+TO-#UpjOvlIy2k
z_@mXkeqPsq;-TKO%JEb5KfAB@qbCYGviiy$TCSmW;@zU#+n(($Te?Q0^2u!7SqJyL
z{<^E(v-N3R&I|d!JM&jf__NYEER*f}gwNf_4hgX-?_O?j^y-qD-?wrOP2cNk-Xm;d
zn8L7QkN2)A!VABwa5U1}7bjS7GeP3CPh{$vt164X&D?OwR$M{r*aWUj?Q;n#H#C;`
zOrO}hZysAX&+pJVCEGurdvmJ$LDVt1n^(3j+9@f*In5(CFyy#Tv5vd%l<tE0^FCcs
z@YQ;<>D<%b8CNq7EWBxUx9P>#J&Qg_2;7bhddxo2Lb_JR#ry1v1b2_AeEEW{Ioi*;
zm%sjUa8vA!J<}p)mnU`#^y%#T+wP+C`gj6QQS#w3Nhhng*{k-2edG|@nz=uu+LhNP
zo!8!{x8ZxV>B&2Mo`OYQr<fQg8p}?4um6(qVDRs`yIy<uR{rtZdP$@(szB&U--Y(0
zi~k<J6Xmr}dDn%Wq*YsWTI`mseZAg-NoZk5Y|pIjPhCof3_m`TIHa&;=GEQqh0BB5
z|FLe}eEQu2k=Qva=6k)8Z}d5M%jrnu#|a)kx|yFm(RPhcdwiFtLO4D$H@it@cGy|Y
zDV{AQvxSb#)Cs;9s9|%3XYE~%lW(OJ(=Xk;=;r&d@xs(@<3DER+(DCj_^y|o*ctTf
z>M@}grAPOBhc2I>*~RmcNyAhzY4<$Wndg*#o#1)7{pd%>>f{$2tQOw+r#@+l;{VK@
zp4V;rzC4@gdF=q}Yt6<C|1Hw8>t`?K>j~TcYU&SVD^06jrOOwD%PJf5t131IX;&!-
z7FdSMUD45-{J@pNHQwi(!jnDsWXuwzJKVI@CjI<1fjhdpBl1nm&b8NyreEQEVDIXn
zvpj}}sXT!DeQZtqfjyIQ%Uz!?H7;G^YxQr@#3k1rygb5K-a2tH=iWOXB;|M2tm^h=
zcUm!j#=mFLXRqn8tq@x7zQNOQ_0%<eZSyutZlCsQ-QB3L&^fLfet8{~d}y*=!g807
z*sRaoH;wX5ujk*a<BW(ZUe)|5*@dU{Q0=U1niq^x`9ipENvY3J_>=P{Zq_5li{~m9
z_vyST$zQ-WC35v{t{qOU>p!YKay|6ifoUy|;TqBXzr1+%=GNV34P7!zYT4oVGgJHS
zMCWNcFPk4I$aCLP+&A)Qj8U0e$xp8RQETsR={l~W9C9{fdZez-fz$W1ZEu!E7A43V
zWQ1nLO1CW55m&W*`$D2hR%p6M*z<`sM-JQ%KmGOTit94FD|73dUtdd0{C(p!Lt<rY
zSPb(k9tF0Szs|indE=(lvuhU^-Yt#kaXJ)f*zP$!g41Ve6g&UR*^aZH$60TUf052}
z{iSn#MS7&z=Y>U~t8z{rUscsGF-2+r_8g~!xjByS&v{i!Z`m-1_02oBpVsq_a8*s+
z<hm&T#UIxr6IMR@u-dxUw(Cay?CNO6^&(<||0K<X)Ar3(oGv|O_e&`$lVatM8I}T%
zOC~P(zvh$6vXe6FckS(RJ@N1Fw<!mI`+h!p=y|~rmB|XZS!-XH8+c|iPTqEcSz`On
zmfG*GJgQp3oKqtw9RJVM9JqAhhqC{s&WS7doDy%=lv}O;8Fe{`=gx#LUn=HRxYhK#
z1Rc`w-^qR>x%E!a4ToFte=kH#;oAAjebeo2KI=-K%q^Y$d*SP@f5$CXR(`qtKXmii
zYMw>4Kj-|>Rj4`g{`}v_rGMS{)=UW6s(s^qZOF23t}^>(O!t*apJDxPitJAJingM?
zQZGJuBwZC=?fps1XWp5doxwYFTu%7N-HY5Kmo~ZXKyKCTFX2zRUN6$TlTqTbXQ|DD
zr9!V1_gvNZ`i*guep&l>1s%SZI{WS{{Q6$miZjAnXUp^zH}p0fSpAWE@1g#EOuk}E
z*{z&wLf@>PGUxhc+4D9hi%X35ZZ=DuaqoZ1BE7#+#%B*L_$z)qDc);s;E%VT1T{WI
zImZPY{T%%=YpYL6?ANf>y$eq5)jM!L=cP&MzT`Y!X%XLJ#ruB*n_Q}Wrm#f3|K_IM
zHvPYa7-lS)`Jt;Kv)D(<bKS8uQyR`cJvl?!-7r>1x1cB3(C~BV_NQ6X0zR5um~P^*
z@$rczN0#r*JNi<$j`Nh^M^nMwvXX^6JGai#h?&S}rNUD8H8aj5^LmJ&b_8Fv`^-5V
z>9Nn;Cihk@j7;U^Jg`UQ<@$=GNcYbNw9MT96t2*${Miv1ROoxvna`P*VM-M5gST;;
z_Xj9+?ziXpQa`m|=FX;7mA~K4ow+I|T;lo1;~Nb3+Xl5a@%^0N7IW&Hb$o}5+SjYA
zw{`Y~GVX|u-Ew`F<L~zAmqLvNd|q+gD(wB@s37LldSUVAbASH@7<ZIgMprzjS}tQ~
zwB1F*DQQdknV-FTRo56z`1G-PU8c`x*XAesTn_}#B$sgAk$P%3afh=;(DTd-Q|pc;
zN<Cg#yYKm(cLHpdhEbAxesXY%_(q<X*L3moN2UGFk;!RiS4go=dUUJundZS|r;}<<
zuwSq4oD`T?oGH;N&vsSpfAraDPg&mxg^L%jvADt*wNl{yRV5bN>LQsR8`*D#=apXA
z+jsL0x0+yZR)^(_P@gLcJ~!p1z1=IMb4{Qr^A+<a{iU-Vr@lGueOV!|qL3r~znQo9
z*4h@cFIo3rE?O@+*-TY2dT)4?*{f@JpGsci)AI{p%$_7x=%t=uoXztmHmzJg@za$2
zy1uxF`$PpVuDraG-Phm6@r*?>>(x1Rd$+5zPVjucMpNV0l!=CO6wlt6mGi>+`>6w*
zvk&t9Ii;+^=KX3?oP}+gdi=>Vk9y{5{LyUq$g?+7HQGH&iuYjb!xed_9Ogde6ti+#
zb?rLm(%JPFH^j|4cF@n1y;^VfqI(nB<|g01&6O*rUSVd@v`ryY%4>~Hc6HaE&lk6v
z=kMtJ*L|@|Rpy?w?Z;<=*C%cG=Qi`^SK$rcId-kRbf6^k{j|m%A%2=~j8{y(7<g#<
zE_E3hR@P;z?@sJye0)n+ara`qhbLA)G}|oioclRGM0FmIY@_yz%DQdW-#s_I<hoT-
z(nCvOt>aSr9SIsoAH;Or%D%YxIluKcNuv*oH!h#Buw1x1K=riwQpIOxCs{q~0#Cg9
z@UidG=hDO9*G8MpEM)6F|MS~ofe3~fEP<0R)F09D`WyI0q=hl7GVfeocB5I#MyA>g
zf96zIF~}U<wy7~Z@c40=vMXs~8QvF@$~eA72TtGmtcPW*m3TGBf#?|qh4*%R-a0?K
zd*K?M7Zc7gt35s5H`yyKV9trW$wl6Fep7>63yPPo`!BRU@r{|1q*UM=1J6#|ySoC@
z7NkAm(f(4oR{P@m-r9ABUyYaaU1^#bWq0X<`m-PB&Hlztm0#d==Amxell=*g%$_oA
zJoAWU)`x~A^8&wUs!s7gvit7UU7H@cgxq*P^@*wSt<w*5lad<~C%!!6%<azUP*bhR
z(|nTSf!N(0{_W8Q$`@w+nkKP1lc8>DgTvvEDOHv=@eEr9PS^Y2*{Sq`)kxOyv`3Mf
z?WeC17qoKXjLzz&?<v2#v}cdu8%0)!V^2>QE;m2q{q;z7m7#OgkN6WFGpGF1>RzXL
zeWCpaZoNakoZr{I;bPfjlDk3tQikBv7Z!H{x1MM&lk&SL5wwzpe@Dp?7mbKIdzH9}
zE7{GgEWXU;6?VM%qOX@J?dIQSipn1XP27%metmYXWN-S!DSz+n-}cnW$I~y+;l$&V
z<4@F{`EtMIJN;k&qxj6A-Sz!a>h?W?33Dn~YaEVQzgzxwL#n=Gw@ja=d4K)IsZ&<z
z$_1E5*`J7t{O~LGW0tM+^9$X%M`O&^RXOfH?X~orNf*aA*G*}wubtoh_pHl}8IM+)
zNKB0S`1FEV$Bg`!r6;At<=?D-Q?~z#Li60dXY5t!mwcA^_+38#-Q-Ws=hXMp3Z<@n
z(~h#A{Qqpw%jmTlCq7?SUamM%v4^LN_2;vCf6F_;uf;xa9GJRp{oS>n`Y&z0w`P~=
ztDWW2{rSOaifS2Jnih#7jJrA#FQmK{*vn_X{5nU)>ZOk#+!dd9V0~teaq)#*{aI;;
zqe?D4o!i3Ol*D%7<?dNZ8NcU!+Hr%&R<m`^-SuVeCxvdOb~Chn$l&ZvTeW+N_UfeC
z1Fu2@|4y4Z`%6i`=%yz#Ub8$`NeWYDE8lYMF-ya88T+k%g)?4rr5ViL_`c+M;78}<
zep?;*v(I~Y>Rj}`Hs|9Tv5N|ij@+-RUhzV&a)0`+?mLR{@t>Ln_hnfqm43dh%jvv1
z_;~qqhVHXnXVzrAT3zE>vrF&b*3Dj`RW)2vIx1@gx_=+=6YlGrc5L}e%@wvz`Op6E
z6ZT|bjoV*p^nQE8H!tp;#kqfdlYcGGKCS-SI%w+rX-<a~`V>Sy_^erahP$HNd6iz%
zw~XsYkKR`O^=(u0#OrBNrQ6fo?>5^lZrb-dlKuaaYr-;17di;!)M@41)-m6zBYt$}
zJQ0zulJC1t94(kqB-3I#srU7?y~#5QG?f!yXQ?op@XBWEy03lk@XN<y+AEYT6l&u&
zcKuqF@JBWA(ve$ttygKb`wGa}dwblL>Z<VC5yNy`F6eDvlK12utJu`m)?i)6Pp^zr
z3!X1Z-eR^S$Zm3T|I80Yky9ovJ>;~dZ^Ht$Ge$F?O%hEjQGIsNA$YP;?3SbAHkBWR
z8tS{Nf{t?5EsyvqXBN59Iq1)iZ926PQ&^UN?tgXs(AyVok~dZ^KeD9Sa&O<=eRB>O
z2TT@Ve%J5Fb93R0M+=^Rwz>Z8kihd-*V>qtuWkI1_(?Nd@b}i~dCqfv_p6wlJI!;Y
z^I&UW-*f4MZ}&g=Hg{To)mt&wZ@c$)y#KoSkjeiw>)ovu9sKm;sLJUTd`G@4ap9|Q
z`m{tKc}eUk2g60{zRLQTe>`9CYfEhOyYK}ezt-5s7${}EZtC7MKYOlAP>f;GMaBsi
z-gt-3PRU-rW!1M+6BDLvP|y5%Xi<?{`CFMM^QQ5(dEZ*NMK&+I@Ne1E13H>>eby(4
zrL>g&_f?v6qwoET^OrxU#feoLWPiI@+_gaX>tYVB*=oFdns)r(diU|At(RoZ@_$^h
zGIYz5?77=ionovPtJS`^D|F4OF7R*YbKjljd<NyWX1K9d3!Pef)}@^#;C^_Vn1+Lj
z+jPd3;~l?(Y_IR#uHw8YPql0L&eIh)nU^izQ+@D`PE1bIoL{S^q@KQ#yRzV1&c&Dc
z+sm@NGjq$T&(An%x$@zOWebk_?|Pf=SbW6zTVsyvgy4@mu6>eqy_J#BcIM`t@*hVs
zgxqgwY_H>=Wpd~HyQ{{_f<C(6WnlaF$bA3ZFP>8CT;ulL*s7H^d8yPkt5@My6cn<*
zmuV+1GqIJv`gi*Smx|?na}S7@?(2|T<s|rN-Q85v{=EL=vU>ZJ_ODBlnjD#XxEq)3
zPCcTMljQfL*x-w!@*_L8?+YE%-Ta>)KO&H_<cK^|Z;-k}zvKKVg&q5ht}N~N)wy8K
z^i#|3r*57rUy)rOv`Z~3VN;NA99QfWiPi%W^Z8bPYTUZCH!6B+b<iLE!WaA>awWep
z-wt2>QZDTsAGd}@ldEmYFHhZxx~##azcP2PD*F_d-PL?$T3P+-y5pvqW*MB{rf>;u
zH(k>Acar`*`>xg{h5w$<oTQ);*r21Y?w$6A->QD~)yS9XVlO%G)a^fUd+*`d=GmqH
zx+iWs_~qfjx5ry&EYfY@Dm{HxS;<t>)mv7(T1M~Yq8x|SJA1N?p5I>^GDj}X{qD6k
zr>rvT{u?I3YhV4DbY@9OuH{rkov8_Bw;p#{nTFq)$Yi0XW!JUaRJ*G1`VTpCKUsz*
zwjUn^lr8t(o$yxHXC+5t)Y>{tDW;8?_h$wMZFy>~73FVs)Jym9B+)ypC30ss3W`Yx
ziXUy5v#_Nr@s3q^Q-p=)ZLN)WwHVi`{?aIWsB53QSv;p9r&MbiLw$zs>G?a~Oxh!z
zax0|dT9V4o+rg7W*(PS$nYzuGcyP@EsehfXP4}nYeRpnZMv|+Q#H#RHJ7(=	#Nf
zuQy_;?n=!s)+@K&XlFm=u;ydmjNm;9AH0HkDpmh{kInD8@HNNo&bw#KQff@I0}RUE
z$7|?V{o2qUctg$o?Dk;)DKRI0<*YQm6LOS6WZvo-ak~~ROZ|E~(|U24AhY2qqsG@o
zTW4&r%hBI^dddUCFROOcT#UQ;-AUeU>DAvYrt`Oc4>4Np-21eaNkQ=YInl<B=bsOH
zaQpq2$o(VIlz3ys^_@#^G^s~yX6<~(UgIvT-1wn={#Ksy=^xLX)efufy`KNG*lM*`
z(1Qh0Q=YEdayYi}xAVh?UX?HSx_6zKTWk}z?``OP{ncXE`26>IsBN?Q`@UJ?w@}3q
z5tCPGyz<Iy71ND4ogDXQJ)5E_&V2d3<=qeU?0*W}SMJ>1T%T(qCjEjr*8b|Q-HK-y
zY!clt^BNDIYol#O(7R*1-QF_vnQbq3^6?hje4X`y;biC8*Be5&|2)2XP5agV>pR)+
zJc%<rsG_xSuJWu+iaZWh$HjvV+~57g-?Txzs(q5X`|G)^^QUpSZgwmw&Y5G-ee>S;
zzey8~9$lX8)F{MT-@Y-@_skSs@1n)=Py2Q!@5>jJe{%K9GS-C^D}GC<=9tg^r5k3k
z%c#6=`?B?B6F#WjJpX>uMjiES>)+{}pX6ySxkvi4Yw5Am<|RsB4s`zQUe~T0vY6ZX
zK&;C3_H!$a)U8k|+Uv*vXu`>ffBAo{jI((^{i@I7wa4@FxQ}sVEz{ZkJm~-QSL&Ub
z&#Za2K6K)Bo&Tlhv+a_ZtfI*}ZztAm^4hxS<$>2O?@bjH|2G{Dx#O?BHoE22TqQ-#
zARd)^>22ET`{MZ@)V;H~9ws3m^1IY9FMY*?%)kRImrLdyw#$->-eW5H$Ni0G7k~L~
zcf<Low|>64<IWMsMM2NSxNSL^eP5So%?fqiulcf}roC^vR!gyoU&)Q=2fRM_uZQpZ
z9Xu^?;*My!jg0yNY1%y(m6eW))pO)sx!0Rr8zj8x0&ldr?QCA5s<WHEY+k%}`!ApV
zoUq=hJNpEcyg3|w`0n=Cdk1wIy?C`YeTku5!A?D<uhBPxif(yoI`Hp&s_Z2wxgqmx
z$GSyf_e@1?=3LdBJ@xm!tye__HovG?dAN@K{c`=g53F;S^cM(5t$e)y{EKN<x32yh
zl~=gnZ~6fR)k(i1y)?{JvqPR-{$P2pk?WJ`{v}lpHavQ3QIx&qWrN5}!Gh%<U+=Pf
z%;9>J<3?ZaF~!YC@6FIPJ%8@RskdrR)`kn4u5vWdPcoRR{A7#0!Y|cdJzK7A$*cNW
z#uB-BJJ%$eIi83AI%#|UQE<8adFvvcN6ZOPmn61*KM}S-`r_$H?n}D8bOaq<PSbVV
z`pW;QbH%N56^}2*-F#=s@F(!dr<;w7FD!5PT)qBm&^wP;w{4SoPxmmDU%2$}OyJwr
z@`9Ex0rH*MnzPGZ+}Bc_(R=&r9}Wff-}_SbZ_Ws5|NrPzY)Q!BemRrx^%w2sy}y=-
z#w=cW^q=3MWc3-d{(U`>)3@e+?8L;ZSIb>C9@)KRIkSyRXGh2SsjjhYr!!mTCA(kR
z)W3P!VTZpx6V*;Hm|?tGJ8u1n%N9@G`88IVYR<ei#ZGm0P_N^^R+htEYo0l7(ajd|
zH}BrzATp^-;p(F4@sFNl1o|vFRl9VC#1FBUV=^mM`(}By)Kt2BS##~mOrA-K|2Q14
z%?+A!_zqWHy*P*VaT_09d+%gz4aY54epQyQ)ZM~p^U`qr3mINk%azWitLvww?X$Wy
zDe|e(+f@@5Kb@WHR5n4b!id@Nqwvx2qbD-AEcL&}dbHZSgZ2Nii#sgVJ(;~!e}dJY
zO}f%&9u_l7ez6KF?hOvDJTl`byN=c?tsC)YK0K?EkI5+h^1x*aM_nUV$P(5+hSPWT
zT-dqSGvUFn`qTdRid@VbuD#SWJa(CZvm>wN%|5G@j~5s6{&5$S{2ysy<*GPi)=$Ob
z)B1$;ch?*~lGw$Y-s|M%-#uZ@TER<Bd-5wY<}Xxv)g~hJTlM;*ORi_`e{M8?W)zn+
zbL~Gb<L06t#@z4rn>c)SkJ7L5v1d@R)x7t>WD=L_(xn~N=ChOPJo)dR{6D)jUP^-H
z_#Ls|ho<{Fw@E*`HF3XxZ&_cZtnr&ack&{xZC0Cl%JK8}tmxBCCvJpn@NG)%ue_Z7
zYiY|YyLC%lx?ej9uTd>~J!k#4e=ItCenkr^b}61II*`<AaW8n$$8#G$RODXEtu|j!
za`M#e+Aa%~m4A(7HoiC{cl1l4<i@PY-W+phR3<8E&)e_5>TSsKvgVmnFW8t⋙EU
zP0p})B5R-g*J;s{j?_G_`fkGcvU>getHnM$W^X^aO`|4y^~@!labAxbQ|I;tJNd0_
z`LjWNZ}~E@(5O=zlh^TYw)ADZdpb8-!1Vs_eJ8mkY!$67WoMY3;{6pf!LF+#`_74v
zy8Dy488+U(VI4VL{QN1;*z!hs`5R{>Z!P4K@H+Q@&2ohlA*a$sGfyxyEQ+dY^~uY5
zZE{%EDk;xg*nCk-U*_%;8-wLO=pLJT#USd3;Aa2d`x@qV_zKOE`?%la<JuXFw|1{$
zm(g>&S5*9W$5GKUruJ#C3>?ILeoS@Mw+grxVQ(REWY*sIn@=ev%*-sl9M9T6Pb5<B
zSzg19&-+{q5B!h*sM|Yn`p=B3R(&15Cw&)B3_tckZ-eVc?+%H!=B!y!)BU|}b;$e8
zf4My8cE{JfJueqZPJ6SVtmN~<jOFP~u~xSFI%QQStiR7NJAEf%nP={0#iP+VmIvnF
zE<d?KEY!>I|Lz@U=Q^)?%^_BK`fBhw&4UJ0+-6;Nc|NuI{+Z@k4Wh4f(*(bKQmH>P
zwX4@-np)NQPh#(x{jHl?zG~FJ){tjlUA4RZ<AJWuxee?ueXiD|$K9W4_~fc;Zlc}+
z#yI=czbo#A&9#&5$~8F9B{1LO<f+M%C!S0Hm6KubT%x(>jRc?eljvh=`jSts-#l1%
zX6}+VTd#a$RhKP_-rFXhI%ihihMvkZOfn~~sdy-!-=3NwZ)Rwx*v499eITs<?Bioc
zZmWK(U=IH=`JDfpc~cx0{raB!O*o9_<f+`_CHwZyQZLHSS65ma|GIYFOb4G`b-SG7
zD+T>q6rIjoUA^#Ydy8vI8k-qc<m}z8PfYWCHk_3)atP64%<b(H-yOKsFtYbgO6<b#
zht#aoer~<h@#@B<nKiEECG9K|Z_JvTohqr$x5Mc5otG;=6<MB{arE-x>29YKICIkv
zvhQk0eeYZ~-;nuo*V~)L47OK<_GQfZ(fDN1`slw#2dpICvrbT0zNE-aRkP=|_PzZ#
zLXvO(`IEYP+q=6*bzXhHq?_dXYp(p~x8C73zdqV-DsIiu^pq0Ps#+#gshU;(DRE{r
z?}xhmQlCY;u6MBqt-JKfMEQAgV4L*%bMvR0EWhY&zWT51UH4Z-iIU%g>kB(1)7|^{
zUYseqEwSL$-!GPS3^{pc7I7M!D10tEC$%pl=!mve=%fADD;6hm+}EmO{qygUqUZI!
zRZ-`jFVx<7?$+tun<NZ+R(Hp_y5GC-<Vs?ZyJ+^Vmeo_v-PjjyBvZbnH=(uK>a$s{
z=i3)^UxXi#kqKV=XknCBWnXRig{|BDKY8me5&lv4@<nIB#nO%c`zkUYgyihG5g2Q}
zrayD>x5FpzEZ_3xtk~vL)_2tFPbIcVMh1Uwk2d_u^LP8g8HWWP-;43QEL)-^_p0q)
zQ`^_Ox!lGxYR)R=W;AxKy*)d5l`88cyNZDK3wJ%$Th24{0AIw#eXOAezP8<sD{wD3
zF@4*y<3|*|BafddGZyyvp0-=_@q6AEJ*;<^g|AIhoqh0S7{~3O3v^DOp1S&$gOmTv
zL;>G?!J4}@<&qVD&x!s`DzJLI$63Q+M_h+PqbR$<GTkPnxK-xjyB93%jPISkWtWA~
zqPy+~eLY3l(z_zN14I*8TK8pNUeX(QB<y9!u8hAX6U9Z1pU2+qJQ4lsk;;P9h4*<T
zOG*pxdmhTieDTAK0Nxq%XBc$&_yxLiIxOVe<#TtAU2@*~qfYfV1Fi(Q$TR%kSF_>z
z)M;gI)iNQbYgS)iI(v4P`I~ze>fOR`&0I2dTJ96!lKXvbau@0aYZ>0kWT&frsxjj4
zoNy(L$&>jg&zTpS?&L{&c`h*e^(XU8@E+s+%e+6g?wpt(Dy`Z*>0VHCHp70O+7n6{
zI<g;5%!~gPXi~UqnMM<j*=EN5@4mhDF`x6ILgLJwl!VPuRl+47&bIAdoFwSDQ+Cx-
zzqA>5&nJf4J?IMB@4Vc>F!7k0NZr$zwAuSV#?4!i*zj2QG;dv$;qR?Kf9;N2CGqya
z`(z&@N0t*emV3Y9=THA#u_a8X=T@)Mqf2*={gG$R6*FdR-oNT6Q$wJx?SWDOPL*Bn
z%hKjOV!W_xa+dO?JU8ZojMNMBbdSt(G(Yvd-cWd}r=0n`&CT1gR_&3mbiOC_PonYu
zx8^c#R|fy$^U^Hs!Vl*?wMyeW_E%qW$ECV+Jhjz^6U>)6Ggd`Si;OA^)puJ~#4C7T
zp+?s@W%KsR*OulSzuAuR9Dn;`y8OhhW!vxRs?U2kE2F99O(5?d)&E7_|N1Tl{JAy7
z)K2(S`U{4=2S0ofxb;Uo_Rh^OZIia$V)`Ruc)v3Jh6>ZWL)+uH{!|2<dz5i{-m3fT
zyt>^75=$T5E!uXqNxfkm2bY(NpX@@3&;GFi|6V+O(X?sG4U><i6BQ;ed_S%4H&^XK
z4iEk7jD>=QM{FKG|7h}SYKu_8U2R5P?%R(zJp1G3S%*%&!g@xM$#<cyV6=}>Id5oD
ztY(MV66aGVAIsiZ#^iKYfa~Y9l$3926N4`FFg{s#-0FkCvvqq-@5aSv@g-h(R`$WV
zCjI<`%3b@r4k|9+eY5<@_qMQX&E1Nb4zr@O1n-EcOrJ5ALuSLNu<z2QuABQ_Icc0$
z{9H2K>!N+{)+O@-9ymV#7s~qWUw@2-LH6gSR5Q6Fd&`Yp|Em7F?~aJ#C9NlW*zAla
z7Fyc&AOG`ZWob?_`vYa>$+tOv+WnX|g(b*fV@&)esdCfUB_7*9OzeNnYbj*xb#d{z
zEw%F}tv>!_)pYrliA{U1`+7XvF!{#s;F(+Z)h<+#Ql8_nhhaYFGTwe`19|C>{zp@`
zOf?J_+O;k5NWOdYBAL$CoOkC_6~n&1KiyGd>y#ue%yV6NZ~M)*ZR*@7c_l59^4QCx
z9STJ%vKD>I?m4t6H#m33kt4otfx_34Pv|fDDI<9QcmHEyJJ;!JI4ZbZT|AD(XGZ^O
zT-Ku5F=MfZ2>Y>~SGwKLw=SHs+o7>*-xKXs@5NNB*SAbqHSdtKiND;A4U&far7S)r
zU2=|W_ljn9zE1EERE)p1ICtj+{+{bx)lrw^t{(dS{=e+|eHZyYX7hUMxBuz;`ixB=
zm;EbazMua__ilTwZMrQLD;KA?=oIrfERULKd-p`Z(U3hG_(~YR&3&;__`+F^y-y`l
zKFi&j6Y*{SpMPRg_6oSVimJW1!Na&@#<ee<_kRYyPhU6XclFasyFPp651(>teY)?4
z9%DT8E2jE#qKw|!3+0>K-!-R~OcZ%Gb-BR%iy_~(>~XqsV^t{U?w3ontxUhqUA9(y
z^VRzgQ)j8K;62IAbYtR`4Ods+;}<<TrETuZovoj=)=!xF`Qf|2H=OmY%Wj>T_->Kb
z|Cgske(z{$2>p{~eB_tYr@(Ko@-KVIuGxG4en9zy8r_#!t7ong)8V&09TfSIPv`MO
zZN4Q{0aEujs%vh0RQ7lo|9%ynvXJxp7MW*R8AbB9a_y7fH~H75Jy8zVMN3LM8}8qn
zn|6IVd&WMQZ)Qp^k2yqN_joUJzc8K0Q+#_S&zYPHvFkoe_x&Zo!p<stZu_l*%ujL$
zHy!GzeX*~`y-{K<d-=8qr*5V9;?L(DT|8ZM%Y^&Jj|}##dc%J^UGBB*lAgyU(M+05
z@5PU<N}7G=FSqLQeV3m0>~EWWQ{RtO^7#Jala0ANs;1BS!awcy&Dv)><(S{czxlh2
z&B#D(eXPsHuVo+EC#~R}eCI-a?53Q(FZzyKuk}_dR?xhZ@#e3crN#?m{%_ZUk33$H
zP|0oMdN|tj_9Dga*F-l({{N~w<weQf)8WgC9!#IoGetx}|3~}|ZpQsb+^cO@$}qJU
z%=^6MZD>o=o3FF&f6j5uYp#;r|6|Lcx=@$)CERho)ivMm{<DgG){ytaL{upL>5l-0
zAl*GbB+d67v5%VczB*~Il;YyLZuV`BHWH^U+*)`itM6yf(YcP^-)bi93fS<pXWP|Y
zPA`_V&U^dBicUrCbYoNwDHSPsWAS_D3%8q1PMwMk?}ZNb9;!X^*e}4d&7gxj(j)##
zXwRGDU+&JCESY)PTH+4ZE<^q96}S8PpCkpnUVJb73fpPZ=XZmHxgVUnrT;^ma}CS<
z18bS2mUeOGgdKkuu&rbz|DzkN@_K<w&DOJ;l$*8PkKXK}^d-_U{QB|Kqx*A@-KyT7
zxAt9t!pvvtTMI5_8a3?lS-ZN)OOLZ;$1ZUOBjXI+)lYbnMPseDuheRp-8TQqC*gcv
zg$L`-YfW{mYk7Zb`eK&iCq_CQ`gPYY^sm^_$QH13fl`KNK*$5rzftO<l3aJxQYXYW
zp4=vI=Fi`lwM#qy{S3Jx_Ul1;w7po#yDLm}*XtRkUJU&B{E*%?E_?kY_w<#k{%+X*
zOUG*Gi3?NoKV%+x^E}8R>Oi(e##DQa;PShM3wm0s+<i_I&wl(-d|HhibK`=tTuFXb
z0gqVD-SdR5rJJwT|9)xT>gwE?7rAb$_FWS*vUa+4*v)U+^G`=|e&@Vc_dNf?{3|^N
zJG_2R`KveU%c@DocE6}O@+j8(MZ47-7x8(Fjhplz`n}6Mu|{l>q-y_x)eF-(RxULb
znjglVFW&HHYUz)MFC3(9Exq$mh_glK!}2@zuM7=CN*q7jn`xlDe#uGpqZc*g9<<y!
zYR}8Px_0*k9?|@t3xXF;_pXmSzIQ@S>CG>yUwE0S<aS$m&re&w`or9?5WlSzE!!{p
z>O0A8x+SX1ptAA(jB_hKpX`)(OBVmXCBozV^w)l2v)(vyA7;qD%GhsoWz!5r#?Gu)
zqRUgb-Jh>rX6E<({DREzyEi{fSoE$nMxgu2TW7_$o@aI)N?LWvws_Yyk)t1uRz_~T
z%b=NjiShoVFK@5qONq)b+ZWD^^^#r3WoEQwbxwiz%|@BuKMGddHkQ_qn7M{ya>@3)
zzav(Me|PQPxb&a9&w+J9?Qe5Z*R3|)l5)C7<&}W%lCP8W9<HunY@QczrabONR<-A3
zOG(|5qoPx?Zr`;t-|^l`OKro9?ydLl{S>uiak37dxAOhFfBYwkbW`hsmvC8I+c)@T
zXK-?KHbh@J<7%tYd}gNDysR5Gt55LV)&Ixb%VV3dfM0a;U4G>|TQjACT2F18_Eq9R
z!A!%O4Y9vY%n;hRtHfM6`e8)RjLU}-Q%;00+pJ)?x$oK&PQzKxdcNN+yj4H{Tg}0n
z|9)**{&(r^cW;fV8TU+;Wk0`kxuW%~Rool?%2(GjrQNKY*WS2Xio21?p-F*rf{13E
zlgM|rbN~N8|MT4bLEF-e6K`-hG<Y~RN!?{#aOB;puuxOZQ{D=leJ0oRqP@~`+{@(r
z*A!0KnCjj6*5;!}n9T2qb2r+4>oJ!5z0qc)y!*)`ldikmGr9kJ@B8xAyDs$R6^I_K
zKGFRu`unxN?<}9k?|b_9-u0ax*Ji4$YP>Ie|GnLO>1U$T9e)%)@_#$`SJ9=`30H22
zFkij4=#;M-|C6)ZgB5&*jkt4ST;fwrx=hX5ou4|K4Sp78&@Zej;?U{G<-Q>}!*N^v
zgfzK?n&TJF9AFE6z+7@BPbRWzyJa)m1hdyVWjaeXO#3+Ne8BD#Do>bdA~qRi9G&Vr
z!TrQ;c8!y{d|Wf1HCpSnEV<D=%d_R|-3YIPqR~3JX%}ZG<~lr*56_uYllX$)K`85y
zt;C<?T-jyodm_zNWwt%p;BkEQl9?ADyP4R2NfhDaE^YbI<07viw^@QWEa)18&?Ir5
zy%$~Is|C788GJr3!nI?2%{qps+gNsaDf0Z}k7Aj1Wq)np-0khV_@%XrS@V^ddxEBK
z+%7IVAvIU)$pkgK^AVfxD(#A8WiWl-XEIIC?2t>6QoH(#&RTPpzExTZuAY;xi^_=0
z+}23gb<%0uEG88O<;xR&*iSTH6S9qJ<=_rUPZ9bVlqR8-su5c}WrfHeuZg!8G%$bp
zCbA?mq*1TAD!yy3fa!|2Qo4zMKd5FF&fMzAbk+ZoSog#^_Qe|JPo!-5xwafAIbjlb
zdQqy{E@6kIGntP!rAA&pXK3NxS`@VTd9LG1g9%qSINj&o3%P0^x^xwnfTZe5wU3jN
zd_Qor%zEP1T)d%r=5g(RmltyEG+$EivuUZ|60P2oj8k^9EiL4l`8};++l;9~5Bqwp
zzJ(q7IQvE(hoHLZM=oz>g~Y&@f-jl5k{us(G--Hj*k+)~oAx<kQ<2WuSe+&JY-R@^
zIPGL+e#9&9(!Pf(4)wEGCY}mBDB18hreazD2TcyM<(7U%RqxX_%+Q^2VaXzaQ=j5~
zH><x-?^ctFI<vWAQqDu=cFl^nETS$fr<4Bo$O@`CG8r7*5Eyv&<?)?9XPQ6F{PLA;
z%f(%p1zkUKT*@Mi;vYypy5RV7l32FdPGg~tC&yNM+{#E?d+`6VKJ|R>l9d(@j^A17
zIaNA-Be#D!H_Nn^$4lKjwyyPCyr9#0LmTts<8PTO^q00R5E0v>%(9rN&9!h>>P~I%
zrezCG99k$m=kJM?n>Se<h+OO{@`Ll%jL3=3-&TFucudq#a>^kq%TIr&{MDZM%V0t1
z8_q2oULRa-we$5`HN}HZ)Xs)WFFxY1VNr3K;Z4&iPd$_FCb=%pkaFyu=+(SfM3U{J
zmc>jv-*Xd1n_jU+vmU6jT0Lo!h6mfDClfUlIIb6lv&pAisPbF2WWfpE$qt)4kIY=~
zuc`hATW8zexVy#+{TKqd`mPCn@6a#}xTsh2|LxI_?Rw!0w>m^Gtr9F%mX=xJxzC3y
z&W>%zg=WbX&7e5JKc4~@N*(<cwt)Ag*ukj^`RP(mJF5EkU#nL8BlywClT(l_{*%Mu
zhhlGi4^F$~QpWs&E&pkUj>O7@>Su{UO>&Vks#Of_%Zm1Hw^#Llu_WY;&n}VkTRyL9
zI^oG8Id#!X3)fN)hI8-Y_dV5dOLi&$Vs%W$@aUR^!nQr^M=jEyx?H^Wbn(?^(~b8v
ziY4^<t+y+F@+H(*=*{GP$!6!L>)kmRaP|DPLn2EIT2HSicd5F{-w?ZKlKZ0B48jH5
z%A)spX=%wWxO!P#aL3k+jjEr58tz^Q_u5duS*MF-8HeRZ-3&q7mvLXDJq$Y5#rqd0
zEPQF1w=C5!wq`Q(6A_c3i!=PqtcCV3TtEG`a!N|eU!5ltjQb6P151;*Kh4;r^3UPZ
zIm2ePOKXCT1|_D1y%MtZ&w6c8-t2Q%L*HF(7Uz{m*;}MTqV+#1sZ3;fJuyFY^V{ir
z78QFuP}|ZKw1xSegl?1NQSSejUBnOBaBZzy5F$QfiO;g2<qJMddd5*<q!YE|X7PC`
z(W)EjUTPYSi3i_r(QW8rTD4k6|Bunc9ucPoodZ_(GY`bgj1g4Gd~A8^#N@1t9`4H=
z%FZV@2!3Gl<2kU;GAp2Mfon<GZ(kN?%d3n*-Cw$=U19R=bun+;wPR_~3Wpsl`H!7A
zWvml)-!CgtFV3boxx?UZ(<1&``Y!@ZodnMaDsg16pFfv2IoddUzRi*5cMH~@uT_=h
znUVaYGc`BW?8?){*9w(x+_|<ca*~jy;6kP(tvoZ<yagBRL()DkGy3}GgUdpRGX|Aw
z>^9$3s(U$Goi!+NW6@m3?6#7nZk}$p4h5%WW_z#NS!w-u*LJ<l*@v&GbRJ*wY=`Lb
zeVn!DXWE=^_TJ3(-FU*oBB%Hn^A)YsEZqW^Jn5LZJo0PkgmYFo%-P$d=N!?0_f|Vk
zkfZKhr}AHk6?&{6msM?8c15Ep@v_f?@Fx~GZ(r-a#`pGaYm*O8DT7YJPWF?rLBS0T
z4yC&_OE$j}x_YE<*`3X5-6vx2trSnr(A_0}>&!0>35gRa@u8{GHJL@(p(g2>b6PHJ
zpSkqR0`FB97hGC(@>$)D$r9_|A9Ff-)uq~4aE+L4$6>x18GPc>8=H29Ij+cglKFZq
z*W%?$ypx}tjo&pR>wMcHosYMR^`9jkkUS}G;rU)UG;+4{%S(R!rW1SihMwl$u-xvZ
z`>Ul3H@k8Eo^s@%Wrf?tw<~=Mn!ahxl$7RtrtsDJ)T1SR5e;7?5)?!(l)NyFVsKpQ
z7{GopVdhQW_bJDo_np)F81tdm*z{ii;xwC-2osBHPIu<kmA(ZJelR6X7u>Q_$+z>@
ztd?nWxhIy#y-^Uan8o6iapvWNz6tZ#ULD{PK7NcL$w1yY#NdYR9{-YQpIP#ZE*@K|
z;If_5->h&$@fi`<HBxULyR4I2q2G3JNniYjM_E5tdbedvdG;bQMM&FWuK!jJ|AqqJ
z)jB&9qd%`b{>S-}d*l99MrGL>)6Ch=6!mHzJo)<9=Xb2<owS}ez6xdNK9w+S5&tIj
zcdQPRW_qzqnDq3j)XUY21m6A@y>Vko>?hY==NsS3k9HJKEst3JfT1==xH(DkL|gF$
zzmod5+$r}g3O~<yd}Y#_-ew{1t;>Hm9$8W2>`?epn(xhS$Hg8o=dF0MT;|;H=ipnQ
zqbmI<@?l4?r3g1yxMaTgq=TKZA`{NVvMtHk%NEJ&`Ha2f?aE&U2Ate?r4Bt>nE9go
zLXwP>RGQZ^<$if_lb2OZE3ds(ytzuFUdc5<nTO%e=_1Xlt=_jR1HLBB^E7;1BUfj+
z`SDH}3$ySl5r-)m-Tn)c-x>+Mj`{O)E<@kh-RZ{RJA;2Tf0?ys`)sl2E{RVjR_7J2
za@sy4o$ZH$y})-TgEfsg(V~184i}VX3%{P3VHW)Ebl}%55ldxwgG~LC&M58ASF+G<
z&<>SiIoi&1={Ae*@;rqP%$926m*=0G<JKIia3x4JHj^#AJmpzkg06_=lOs38=VWh*
zxN?kjsnW`WOfQ$Hq{XW|p82w?(K<SEaub`z&&(^0EDt;ST}lFe9_!SO?`V-P5zfuN
zJV)aQ3x9{(lq_TO_N!b=+BCf;G-+_yUQc@OvfcRY#X_g)yXu*r3nffjmRcBab!Y4A
z=o!(@x3?6jJ&+Q0@Zy!|IMwn~;?t!^E(U$4U#dO(DXFHuMr_NB8T(}pE;Vb{UX{Cq
zUrvOhFNC%F=6QM94Y?f*%h((>kH73$akuzS+4q%4tR~IfqS7NOCFA^ZE7z>{D}F0x
zPMKFUTVb_Q#hJ9(F}dd(FDE=qIPzx!pY@`0^9Z)2q=R4Y6dP~R)|@3Z#o@)zW_t(I
z9TOMwhkcK8$WG)^*y4Cxa@Pi#Wen}R4@Ujnrk2q8XA)De-h1=&Nsm@qacksiw$5Bo
z^zQnVbt#XIGJfaeJ@-hxd5-MsmkHCq1<NcIWql_V8t`n@A<nXhOqRvv%L>->T-(_)
zg~PWmCtB}9)CJ3PT0LU<g^N6c($6gT`CUaQC|4(~LEj;L<*p5<8F}x7cK!N1@$14X
zTX`+YrvK<z?07VaRlx6_+kxkI5|S4R-}xmItjD!}rQq-2)vu;AH?zH6>iJCVo9Ke+
zu6`?n8!p8yJ@v5Xj}Z40fz@#pFB6`WP3(04a+BYUD{79Xe%|Z{OX_yq3k>KqOP|VK
z#K73LV5&}YLRf~{htQ*D%8BaLCvKi|ntRnItACP9+AO8Z4Mx*GSWRJf$eOfMC0%9N
zQMFewbCxb?ohVt*{aE2c=h@9pSElEF3jJM>Ju#5s{`5I=x{nudpYT~az0=}NQ>^~+
zKQl_zCl@_Ayg)npXjGfWh62kng#}7I0trmq8o@HboDo6=b9H7<S!Kr}k`uaXu8Vav
zTj7EofpJkM6%{faHNxDyH{EXeH*Fdt$NmdDS2wCUI$9Y=W^8X)E^E26BWKwXOQW;N
zF){Pm8@BZx+HJxf{WCAvLjPd~$5YN}*-ats43Q3Jb$eHN@~XW2E>pmB$L^@E>N4T<
zTPz8ZA^X~=S$t<oSp9ce(tq(Vy)T?|QfD|-)}6HMnRD-6Zr>-_<3>lX`cD4l$-%qJ
zw}j#6@<m&ZtEYdwz@gUNT$>rhDwbaqpPnSgQfuQ|CcL;Z<V6?Pqq1j9*_>7=%<;_$
zD4keclQr!TN5G?fa<?uAt~~0t>|0ZDt`M_J+m!O+DdLPA)1>Dxd=Gfm>wED9^JNYu
z^VRjQ6hyO9HgYHxPWyG@dRni-g~A`*j&6y`(;6zRr89puo~pZPKfja1y>+Iy+^L37
zpPruNZ&>xSy~!^)JoMGwhROi{eff`F7P-0{^w~4*!i_T-4-);V#JW$sS+Xk6Xm$3D
z-RXZ-9x4|fY3dDCk6dZjxo3ijigC7nvEX;{s9w&9t+G462Hjfcy1V%CFJqsqv|_RB
zMbZXO67ri4b)|JY*pM-I#!A*%X;=NZ{}xS|lBw7EO47F5OPA@GZ@j|;X9n>dH#9?e
zm26EvFYR1f>X8v})pqKvX~!Z;Jq4eLyuY0sxKLkp&px*|ZlbP1ZbuspxIE77a(tp%
zvX(vQ&_es2-xIq&1YTWx?8bJLlnpP>c0H6dVQ}%j_4NCW!)5;;ER)!?e~)_6o#r_!
zcO6+Ot>a=T-tg<LTvS@<ZLQG4mLh4^i}M~FYdyui;HC1nJ2keBM;BB+5v;j9{pG^!
zC8>;Wig-S;-Jh|SZ+hsn^-ibGUp{b4AVy}Rl48ZYjExr?OI{V;yPufDsPjPe=={uQ
z&v$fYsFd!ETB&1oUDEsO0^<}HqfTE*z8QZqinH%H`+ZQbh;?zu{a#%Vp<i<MnWoX7
zsH_8453idz-<c$4{97pJh*!wzbsLl1pG@djU>bk^F83FHt*u$}+IAh9FrlzptifGZ
zYhx_e4Oy?%O5taFSE+wHwC;n-Gry9xZt*s+D-B*Od@NHFz}k^-_Pulc;{0<0hxfl;
zxv+E58<*-YYc4!kdrkS}MzJj&t`4!@5sS?XIL^2lFSN0UaNH5O<G<VfRjZu$Gk)3j
z?()oz9X|IOcv=}tclQRp@aYS_Qt;6~r{Qg<$_e2$cIBPX&hnc!v}hz4)UfF)KkW^C
zAJ*cWn3A!1Rl9-js*BTi9B=qtm6RMbeNXX@-)qjT*s^2qPS<<Ox@HTfKI#;DaAAMa
z+f<=c1Cz6rwg<1Q7yEeXS<act{namILcH21Fnn2TSe&fq5;x7;ZJwOfk-KwZ-C|cc
zy_#UdBecP>H#FL8)6AGlw_Fq$R|L<PT0A%D{+zuFIOpVdJ#t-YvAi<#1IP8+^RFc{
zzl5wl^{(Q=9P2IbHZ5RqKF`}L{yOf&RFi`ZFWt;Ht2g@cALaTgy<pYRW3%7%RQ9aj
zdHH+6^*btGOz$r7m3=sWVaqbM+t+67)m#u%HhJcP;3Z}|vd(8*@2V20tn031yVN`X
zNMhd-;fKXHTV3xe?drX|$lSDOF~jbe>c3|_xg5}#bkN$o$Y}9iMeUhJ1)Z+d-u3}2
z<8DcLI0{XivEk&Uq{(({SB`it$vby+!i@7RF`H+b><|2xy4d=<@?1T02Ek2nF22=s
zS8hD^?C+^KwhfC4S3B^9O-NW0Dk^b!a>Vyz2Ul^qU+rOf;%9T=;-#i}>TW9)QVY}t
zS*4drOx&6hb<0UAF6@h?_swHVvnr-7X#Hwq=x`#>NNNScm7=2s*1bVW+Q-TYHBxsu
zzBs-ydxL;<%fDnnt)~;yd5^}Y>7{c#s$3?Ypn30j*vz_?g0;V&a_R`}TGnY9-4Ims
zivNS|Ng*Y3#hs6qUFv6!HY{HHh5gqq?xzNdpPoK@qgMFyP(q>Av$$M_00aF~?0hq?
z3%ewoTCnLr`$30fjo11z0t#=~jLhpavqf*u^4M-8@njP(qpa$I)l;fB+{)UsAbN(z
zgn7N5oLM=W%(aUfcd>*=e|fZ_`TD^l1{zP>jJ$1?3nLe$+i*@cI_w|+{QBZ;uO?Uq
z+?BlWL*;mC|FX1it>=!oIZOAaa($UEwB><9kok0%zWy$z*U||dA1&=~<-R<r7n-$2
z^lZ*-sRQp^JvfXmZ@GSKk=7Kin*ukLqotBm<+U@iLhJTFjcDYORX5QW>^3ww@paMR
z1-IROL|nMkuBLQK&nY@_sz>7Kn!pq@F3a3quf&BfZeTs37{A?JF->~MtV})cK32n-
z{T?j|E;(mQxYaEUl4W0t-Yij<%w*aa8}jAWi42YnT-#aggp1hw-n?Yl724t{=DH~~
z=fWdKw!HoJrF?<H#nX@2bw|&?Bj@3h+CTZ0HQ%+l*|TLug`=MA-IJDA*qz#XCVs(8
zrIVsUbNyNw4k+ZuNOw*<Ap3EGe5HkIn~q=TtK&81`zLYmpSUf+Gx_A#%SjKvMDp1O
zrLzkjDotPZ?&r+1`PmC}s><(9`pkLh-U17b8V$R%xsSU0Z?di6FWc~b`h`Lj(>SI*
zlmDLjBxP{k^y1vygKy8K+;u#s^lsjQ(`9p)UCPjJza_gTV|%#jT-yaTC#EhF`p7A}
zXPyp!ZsvNSYPL@&kG+<ZDBWycD5;&n{p9NvE#6Cu8lN@Eoh<yBw{F55uDLDm>aHn-
zIbU7Z#e2>sDN1^gg!UWLB~#t@&(aH&T<Rq+*-%=%Shq7}%L)}Cmz3u7?_;HpD0Oza
z=9otPPK%l>65}Mi{Ja&9)jF*OuM%b!r8rrOo=CVH6Wk=}6uM{H45!yAIf)U5xAwW`
zDx|+%Y|D9d!58VwlQYkmh6K3qMF=ft;`n+;#_EdcM~}+>IO}V*ch5gw)G1<fR<QD6
zSHI%~y=}Tb=EQ^?2=zX<d0tX0=LEJmUjw<qFHf|VFl0>Lnbww(;C1@+$zy9<<P_dI
zc5;}VU@m&KP`sgNd#DUA=Zo;b>65fn6vdw!^Q+YG#c#gopkCOp$tZBK7*oJ<E{1qZ
z9hW+__fNiYA3Ga!^&iVSvwM~avpbtvj_RLZyPTb6UZ~&ag>4$lTf!_1oaeBgxHj?U
zoH)s~ikd5%Tqk66+$waDyusciw)bsGW?EPR<5_{);`4n@6-~<FQ+Jg-mP~4DIxg-z
z+b_~CEIE?(%CDp=E?igUvTwM3F(P^Yy%sAz+r>xr6|V3XU8lLQJ>d3=kaIRgQVZVC
zxAR}NMKVi5=_cE)tA7o6w5G+YKPb6#S?ARPc8966?_NlXIpiPWaQc`Fi;s`{v^A>5
zdY@(qUAperdLmA>n0r<E3+sf4r{P~N8m4X6KI_Y<^Jdcx{mU=*T8Ts@1$2wpJ$y0A
zep}((qjRTwKY4ci)Fn}&Q(O{RC(^}Rr82fJNS^&HF!4r+NZZ1)gDc8H79Zkq47tC@
zQCeT>h|;nRavskUlxFYoUs8E?=FC$uhaMSRTJ)2{>r0P|<aC}*G0Pm;+DuNQ7ingD
zS3OZ(9>f2z@Q_%;xu7TFpVs82tV}7$Vb<kq3}0$z_M+TUae?r`gyVW|9p3L<@7OqF
z>VLKk4Z6=WM7|YlTDUej$Y^zDK7-jw-lomnZ0US9OSb$vl@qJH`^cNj$n6$<i{`l9
zYzvh56uo9k^q$)%4l>?iSawaQbIAoshvmguT3#lZ_RXzrr%hv0N*$C}?sITqG1B+t
zG4xj3o5si8-6)~?Xrifkt=PMHsgf3H><jMboJn+zNmp~^u+Gn1?)anG#G<QO^wY7>
zGtIrV?3ZsWKOwpKs{D`MnduST|M(WY^NC$>?ugCa*NMB1o>Jv!dF*;RYLbASLfNK{
z8OMa}_P%J1t#T3be9d&_s!Yk0NAbmCt4rhEY%V@$(`;x?n8qru{;7Xb(+*MXXzm=9
z<q44uT~lv+pLsCbmUGHX>&q_!7-lXzR_Abe=A>E96M3~}oX*YcTgQ{Q_)Mu%tMCM=
zMUKt;EIlV5Gr4rIO@%S{oKMb-vvDU_4(xn!-f2dciE+n*qp{{XnX3$4@2VuIymnz<
zRd_zwL&m!E)7{Rl?tih9GcH_kncnQJu)00x)y<l;b(4J-F$jpv@L^tTzfd5dX-D_z
ziMiET!jZ>xmih%+CajV<IXClWv7Ny29zTQ9dt7n6UJ9ili!UA6{6_u!MDuj-M6-pd
zx#=1E9|{Fb<5Jsv>htAGk0#7?b$mGY<x`=vp$_j>KT2wzmH6Bu-E=J{>+NK=$qU6+
z6yEa^ys><zQR-Wrs*3`)n--_Dy_Wr49{F;2&*j4E35FlKyI7~3ycc&{?OR4!B=f3c
z!e{>OI~1<A`?Q2J`={-1e#>dui{w^Lo)o=z7hjk6oWlwZE;6e(-zd^@b$f94#h*zN
z0wPzrPdKmby=$6G>F*;_g+bR%0~A;3O?NpIG~x5PIseRF*UG<TH#~kz)x&1*l3EE{
z4Of;%-zkN0zmvUB90^mKFkip)l50r_!vvASyd?X$^HMy2ih0FT0%t6haPC_e^3`eC
z1bt>d*O|#rA1^diX?@LkrvHnY)=d+K3ZEtSLT36ou4=8GGIzIf27?8sVSiyjykvn5
zlOykvMXm`ez4o)-VLmPB`RfAf+pj7P^Q4701jkP^k-PZJeOB%KG@}=vca#_SKG>7B
zFs!xx9E)*-eW2((#{lo>JZVWk#kbFQhbVG(tldB5vNY#Y#^5zxh6S@apJpnGahk9s
zK3wqN`A^2kqs8;xInOU(J$c{sz~9fY`zLKb8n$57x<hW$SS;K&9q-H2NMG$_uP|eo
z|Fz<57OUcr#&v}|7%IHpRhfMBdv`^n=gijW_rqL|&#O9dv*@SjqIK(iHEh3dWtOJQ
zyz*`z%e&8WB(5tSURT||Os4!+RA{FTYd^DcaDm&^4OdfgrYJS~N`7OU<vzjmdz;d=
zEz8!XPxz73eE*rU@C0KsNqyA@qrIjIY13pMFFCh0cL_gBX3#Zut%EITUrrqsNxP7-
z?$whvN8RX*j7M>kos)~^WC&<2GFmaM@7~sFcNAob>!!S3p6EPFy1bp~nfE>G23^Y_
zuF3xo-01usULfs1_je5clMg|aN8buEy!m7BV}X<V4NiFzJ;!Rr>_^At9)wq&Q0bV;
zTfp^-Hz~&Rf?4R!BBet&Gg}w4<|%|NPj!pxuzZo%{G>W4(fRJX1;L+xNUkw^)1-UJ
za(?51l48$!9o~muC3W$L>l$bAdY8OQUvE%wFf+5G(bGV0$_dGuzMjH~%RWb1H!W+Q
zyl#HdHQz$b%>fM=u1~g}X-QA~yZnB%myTQ7{tolHf*1NMHzQ@ZX6_MG)aSM;4s&FG
zHe)*bDZ@9SooY`ylX*T$KEE4qG?+i@S>WcHvgfjgGFfyMtZ;edl)v|b27`mUWXe<C
z(BCVM+?7^UTQEoKL&fAJ0;d<4ZdPYvKXR+{&Sd7Rn;qJsN^M^Xd{eOCc*ermTV;5K
z{kg)Q{C-yV69)@EPSa+Pu}H3bzOF1<BYfvtpYr?Lx?C1Mm%Qs>wewoj+^{3FYSY96
zrKf5fS>`;qkx4K%&mloB=Ziv4;@62YXL4&VxacP{%hok0eaFm2-ZNO69cy)~;)DyQ
zn5l36vAs<(M9%QQ&gJGtE1h=tq|Q+=oWE(qk!LG~jjWoJJ-6uE-mGd^H~rXbVSZul
zdmdub=XlNf9W3-RRg>vlq`)O1-E(igH29yJCL-`;1JnH~&MS(6LQj7tlpN|vW-w9Y
zh}|)JRT0Al1}j&NOPVbbX+rH{n{*oH&1Q57&f)EPZfUZ8@(R}K0^iKy88c4hu6w!t
z!`Brj`)4eUKBvdEagCXMb(t5Nx9T<H_yj2inb&99wpy}G>q>az_vW}nVo#K>zfpw#
za*miMQWw9JR<HZ=Vx^k3^Zm^mIo{4YBVQ4|Yqm?H!mkrE1sVM`JG{7?9L+U9)azfB
zo&WBDz@@qJC%x=nrZsxcS?O0X*T(aN{7%=L8;auR75mu2zTVntwR2T<u-M$CYoj9H
znf@2J;N$j1qj9&Rcw+F(gY15<HEkL4%r>4{>UemWO5*H~oqHEJE8TQRQFQuc((<Rt
zQs_<X0o(Mu7RJ|m9c6@0tNeX;@Rh=+Oa}fJTu)Z=yKw}1oL|sic&wZ8ON?VhY*Y63
zbh~S8`p&i@iWPl3TN%!{G%&xI%j)YS>XVRNyyU51-xrRH6VA-ieR9I-<R%T_mP_3$
z9v<v}ESCOj$q9FZZoZ!>Nj*ggA)8Ly?(j^Qbj63UQ^?#>@Xr0me^p<lPSjv@7k?g*
zboJ;l<+&|PMy{78ep6Y|U@=3bNm1hLm;C(2VQ1O4rgJ}fGoi2bvBmSquI_F3SMl9h
za=rJB?MfF1(KQN*V%qbJR|sz2vB&D!w}P3`N^>@D>|WS<AwwYX(Bl4`!bcx0E9E;7
zwtwo<aHpNi=UHg1ztPB7IYE{C;}IQA2HoNd7kZSqIAv2x<~l^qGh2Q@w=a@&;WIhG
zoURVGd9r_l7JT5$Ea6L*n)|btVX;6eQ=>Jv+n%KTPMsUPR7&_b`EKuZySgRoX{Fi3
z<7Y4BZGJlUjyS_Z*238HGfw(^`#gzdn#f6piU1$J6Q|a6au)G6#s#lea?U<AP04Vl
zf|Ot5dzbtj?j`EoPB{*0ktu6lIH)}KUZ7n4q(-IQqG8by-CITXuBfj%aAE47J4yQ2
zP6>X!T{`Wv^2W}jrv2G&#S3<YvTaj5ySV$|A+;R~L-%~{{}{h*rq5hn56Ssz&zOxZ
z!Vf>}a9Z}M_28_DixpWFYgxX_Y`8kxxW8)O&a6V#;1(C970Oxn?3n$oST+5gs<KGJ
zt5eq9<43pIx-YwKnm&<Y5LJG&m+8vMJu@fk?r@#5_=oO=+(X7^RJCQ6zF<?bx#V{1
zMQ}3f7Psc^mRqHMD>Q}HB&L)eROPLlCfrbAbvDdm|AE==4Cm)~dZhO8FU(@7)V>(U
zal-kMYQ)dB#!O}wHLqDBD(ZKa96wige!^|8$y=uvFs=9*={7yZr&-GSa#(4YC1Yx`
zIoJJAmX-wOg2fNmgahYJ`fR*9+WqBG@t{i#r`Ge>PYLy`yMJJ%&+3dXg{y13>ih%~
zcYc_X_Us0WCu^44uEvOldFqXq8U?1tFtaSVv4e5ip|}?;yPkcEO+Tc3P~+sMzYd#}
z8F-G)pFH#Yd5u#Yl>$XKRb+G-EuEFipZKy*I{R$SqCe&v?zN;$WnUMmRP(@ik)_FZ
z?*2CohwhpFF!9{bx$!8!>}ke)pVN_t-UuGJ^QACh!V(kV=;NCvs~%ePyLn!28=nO4
zwz$nkto@yD=SM!7?W^nc!hXVnw;Jk<eN(I~xqs(J94cuJ>Sh!cRy?pyW1;sgwP&dp
zbQY#599R_^qH%F5&x-xmtj^U-hxX>>7Z-f8s=ccf=9<a1i2v?!UJZ+16T+1{ecT>z
z^ecK%Jy&(b{~h{X^U^%tB(ucXXU-AIZN1xlQ9eTKs@OesL+()Bqz7S7ezo{Ilp9{2
z*|;;oOW&zad7|Tj?pVQvK1MsWas>=ta~|YqvfH!jDO=!W@%lXfRSCPdP0VNb8huqY
zlyTop%hP{X%w*f!+`%Tim;e3a;^vhrwdd_x5%7N!M{t>?M_yL*w6KKzE`F=k9##q*
z{uQ7i!tl<>>eP!_pAETYS@4Giv?%Y%PMaq-cVF;?iu8*Ci=SJrsM5Z)*ks1^pD}Oy
zcXmdK?BvsXQYLj~i*c5xY09l%fxOw0*CWaeCbvp|Fep7SbAS7*)oMu-(wD`(n!_P7
z<A3Pwb$eTFHeEOpDUg3a@o~zRybXTdC+9k)&E-ky;ps~i;eNhAiT}surE4@UxX<#a
zOLaC0J#<A-<j2vl&2m-8J0s6JeCT+#vnQpB^<nFqg>#!2A_CU8%)W4pWBraTjq_uK
z>jhrgToQe<?&KuVP1_BG8S=fDVmfjveHB~0CmWpj@-L+6q4ZaN)`_=n{#p_lc+xmw
zdRX%oey@$!innj*oVkfDbD>cZo9h>uztO=-Qs*j<C!3giF^i^jMZDK8d2w*ckz>nZ
zP6YE?eN;M;#c6hxQ_1p=&MS8Yj|I=x3O3l8&sf6B_mS=C?Ss4`4JmFV0_BSic1~RW
ze4FIAkPR)r+W9UAP030)Ec+tm){$qr1*<PSb_ljnKK5Y0=4lhVeXI-T24u&5|Hty|
za<xgXfdYe7-;!k$=3R`C_2^{$cIQx<)&ZNFDZ$gDX86V`Cofy!BzMKO*Ct=J^S{Fb
zgD740OXfEgsDJ!mbJ%dQ<GYV95(A$~S5K*N=XR`k>-glLg+}4=4NHCeOlr~tj}|@o
z;_>BsQ^BU`qHior+Yc-}5^B7v_0>JCU)&55w}O&FUS{^bwQ}c|oB8lSro$RdmbsG{
z0{m1T-N?wPm9kWhj8f<@zNDnbc>T(R5VPx!jYWkWihKVwz71L6T`<}2%JajuPC^}(
zjHRmIUrf_fbTeHwvCc_v4sXoV6|&JYTwkz<IjTK$oa9ihVdlRjU{fpi+w)&EbMGha
z6I*-lk-a|0`e{K^OCBlgce>$n(&zL!KlS4xeqG-J9bUfta&}U(!_mnxhcB#N_MXQ}
zPE?ld<(mb0(piOF;tF5SnW?kru>3glY5&|eQ`c6kRp%{c{5M;z@on*B-@o@3<SSg|
zdvZo4iMJ!vgNb>&zhASL#M;S{+IgYz%Y38Mq8isH)b8ucyxDiqt#VCSPe@dO$AUHD
ztAy9;gie0+?Z(pN;;DDfta<c7A#O#_(#Vkd3%9>WPu;BWrq_k*SqX;^x0|Z&#uJx3
zq!=3u<%7gkrEa}axp8*Mx!!}<efD=|Y?vOXdOf$qK!@qF{ZzfGr>@n}&n0gt2C8<R
zX<1aTrt*l4b+vr^TFZ)=F4I*v6}{lqIBhUl{nirs#jdhnjgQXFxSAHXXGP#*_KoE)
z4z2jjC~{)g7J<`3Gt*U*l{Tp-O=g(M@%+FUQ9d2_n3TOqXDar|zqp*3I8*hj>7t%x
zxtX8x-xlO;D^^qGO54$MDawtlVevLWpGXH=?Y^luAODl|?iNzr`%CxCPG7|gGZ)2^
zdgilt<k<Dy@i9nCkBtnp6%RRW*^*YM@0h=oGs|yl>h9TVV!nEuF#kIFY)}!4fcB0z
zvlj$uT>6p8G}Gv}!py+ZVE&ki4_1l`aZDDi5cy@icp2Ar9})A2<A-i3{S183ee!U?
zVt%jbxBT7KXwA{&Tl{#@yq#>K22rms3HjfC;8s+%>a6%(-l*@FB7O_3S>q+1dSb;Y
z8Qp}k{x@3J_bMuw9-V2lW2wm0y$-U<Yf2Uean%H!f4@+8n(D-sDAwFQ(^D)ZnhsNM
zbsY%Fn!;+hxZ_{Y7dx@eg^RAuV%1RlYkJA{oojRS?6Y&fJ)7|7wBDnYBK}i;w4d?Q
zNKxN-ZueQwO2#+OCzoXj$t_%9!>MWzw23os)9(t+jmCGTX`YO4W~-W3!tsjb46ANx
z>_$7)N%@V}Q#>6P?Ps%2RatlQP=CJ1w0}V>*(Y`_3E<|czmnEC+oHw9Ve$5NcT65B
zZ}2|l!*c7FrKS6Im5=qlzUqP}1XWIE24CR&9rR{b<Gu1{LLqOoG!ofg?NMmr;0SNz
z;K^lDdTkbHu;A>fYhQ(0PHdAi+a$;k<+5hi1dhDo5D5bvRRJx*qz=x|^jCYmj>)}P
zb1>JiFr<1lm&Ah9WhHW5E8pxo7dcnUc=n}-%l(8nkJpK3)|Z(xywUttm994JPON94
z{qmjt+1?8x&pp|@ok8RH(o}s$hBm3&AAbKaKC3+M%KyBFtPdpw^lzHaWS@CuUoeB`
z!<a_?!``!*9-m1I3P1cXGVChLg*|6Bv!umKb7isT#LaE0mNBnRTE<?gHCJ_-^3IDT
za<*3=sy#pRfxByy%NBm$qg`qxCHz*OYNs%KoGhR<W4hW(jShZJIls(ji)J?@Gjr&l
zJ9~06i^qPAWxA1h;zhH2qN<-ely*BEJ?ty@Smm@$mZgKThHumCv{>%usDAY{c?N#{
zEtZ)_)Rc^J0?(b%ee~<xBy*RIff^fSo@X@Ado0RQ6I0Kix9ngd7sq{#U2B~#C}ut5
zsbKv3wDf?=V%IP7E35L;Pi}kgH#p}`%JWT6HfBzadQmJEd{D#okYT7_|IYp?tf!N=
z#eQ?y-|#wD#8J>ivGcFwZ?VSez)<cpX1?A!A(A`Solm;&nR@M6=uA83q=rg`lKmGR
z&rQ?(A3EvPuCo(4kMQ_Cl`>l`<+;#9|Lq&6I-})xpWB{NzJ2Av9G;kKSC==tsa`vC
z%x#v1LvfIXs#vG)A{#NW>9eL6E9kL3_?=O-K*K0#F^k)c<>wYnzwpcIi;KULVF%mm
zO@Wnu%-h#p+-R`L!liO`_;ig2I$b{%yc8a39qZ!l5xcWsaiv=n_l%T1lSLUfeYhhe
zc1B^dZepRQ;Qj8bT@H6u7WrJ#I9xe<in<Q7es*F`R=OjT{qvs-#F;X0Mm9~@s%hkx
zP&f7L84;!_w%I!r868<_?PZT?vhQ88V}6donOEnPU+V8MTlvuUv7P*n1NyTW#o})H
zT;g?l7@%^T!R^Ac2~WHGSxPKd%AOCFO;~YNxZa9;_lrGZt5&A{3VpDIuVt(7{0rsV
zY#kf;SNL5}vW~1id8t8ULZd)O&7ZhMtUg=WxAuK!FyZ3nE3tkp-cfQWDfocZ5g(`M
z)+G%a8M6)C%DDgBFVWmNNBk?FlKFbiOzXgCu3W#xm$aN?e=!Sx_U!n6B(!%MW7L|(
z>#~xpj#dh;6loFKJ)33kpF_=^GY{YSyhb%+#tbHwWxL|%J@pWMDk*B+cO%Ao@}{hr
zs{8M@t2J-#+<kUgo_7iJE??=aO_}nNwJNO-lzwnkW)@4#_{^X(>AO&>+1zxcm8u7t
zPxYj{>buo+U@vp%FP&HX8G*8;*UQc&3zVMk$y`{n<&JBc&Qa0t<}Vg4e{d;ta@MiS
zOL`h(J&!uRx$7G#;VrP_B>T*E)wLzvyDhhDurOQd+Vos*7sI0M2R%|3ZZs@rh~f#{
z<oIo>__pbJ{Z0xR+MV}UrW|GI7Ee@hc;uQcBfR^_+%r0VX3X_e*gDTV<(;!{_fMGz
zvpY7-SNP`I>@jD>{aTsX4?Yy<Oi6g@)x_W8>abWfQhForD)&A8!SW{MUlfEj?4O8u
z7l@R0B%VBdV5z{7w^p8?r@uavo870$<foxpw`oG#qbygkrYe`R^Ea>BzHsATD95Au
z?Zr!ZiP9Zy8gCmP^wh|yN@#WQD=g#evPqP7*U{Q#Gh2ENyXL{0DM_najJNJQYQ!d(
zt$5_1>C=)f;RW}c<}LZK!AoP^g0B4q?h#xQIi{TmP`k^vMtDlhDLv!*DF^N*o?JcC
zb*9*qPad7-fkxY8LRReM=z6<a%=9|%o0YHA%kmnw&dO7{^<c)!?b^Ya7ytAp@cF82
zn46UKAUkjt(_KfWC)LOPuDCDBIeUS2!nA{(lj@d!OIb3_f5wFQvOi`{-ZF===Ys3n
z6^_4F-;nH_H0!EHe@;ioFK=lJ^8-mT;-$-0th{pXK=;yX&*Nky18QGS_Yn{I%#@qj
zF{{sMo@&XxU9M(#4k>NWR5_a~wDBW<ad+~gPtUs&>g*TaY4BqSosfOa^{XCF{X~gv
zk|pl1EN6s%Wla@IT+_gwJx9%JMcBkVXTzY}b#a}ax~CNdOm)gT`Zo2et;&JRN4YND
z_#3KJ&F0D!CjaK2(Of<`gIUTROtO);Ha%;6x~Row&ARjzi>Hcwbt*~ie!_EVVukdI
z#HG^`?QDKFtbP))z{%n3W~)n^nO<phhb=s3b<jb(>0I->#<wdL{*Y!l`mB7zgol4E
z>^vqnt0V~IJ}|L3_BVM3Pw#P$hJrl~^1;(LUw?Y%`3v>~j?bzjSMQql!9?=F7DW+$
zEpOIPr2`MRXU}-}@rn7{s|Su=op;W(pgi>Jy~vtafoD2dwhgxgbPw^j9*vwmQP;>g
zb4ym@nZ~Z^)dlxTeVZ?<m@d$|XPlt=>p|^WpB;;;Blog@K4ZZ5$Y)9C+?NX-K3He>
zDl!P}kS&Yw?U-KT>Y8K_{7G`w3B}lSL+8MAE>hE0%rah5)WWjTahXiXHJ8L@oB5?P
zy}EcAzIB~De`kV%(TvAU(-tvuC31Z|bp8@U!|{XrT{@mz{b=HLsaV9a(AD(p_Sig=
zzY}CRp0Lfen#uOK$tlzGfXYW@lW38pObl)}CyHHGnaCJs-6)_GsPWD4SN4@P%!k)S
z<p@P_WUfD|+RD&<AUv}2XyFA1w`}GA1p+sOU;e(p%2B^8>}PS%mWCbkgbYvmIW5_y
zaNv{otO){qJH#EY<hq2b>oQF|`_-?@h<TRmiR2}Jw5-m&h*4cu9k_A*V!uL>w{qWd
z%>Fv;v-~lgeUaVSMJukcJ$Y?%OYPKIi;^701f|!y#?f-c-jTB=aQc?t;eOc4s><qk
z@8;9H%<*Dt^JBKR3q19z6_VZWYU&j4=ls|}cG41=b|cR)5gTz|wsgaoz7S=HPcbiQ
zkAx|8X3X4qk}**#)~DpZ`|c%+df3>)wp;oat)3hu|G_ipvu8w<iEOul=Q+JaFK3*v
z;9v4*!A9m~(M#RA%By;opD-7ww{*S~5t|*g+HukHJ<8wI&+?lVr~7PBz0}=u?}Ts`
zXM@D<IiIC?_bE?wZ+NwVCsA+yd!GY8-NkE#PYAfKd7#Z}v}sFBaO3TzuIhVAyPxqH
zM>N!FZcRAzm)B_4k=vPy3VXXJ=#;Bnay-2Js9x(I<#zrjs$2BC3iu>v={(~!h}g){
zFD4szqcF<Pd*0I{Zyp%=URlgym=$&I;38`eEx{MRmM%A3)q8Va`1;o4Y*K;t7i`7b
zraaWYq_yuugUO-fLY1y7>35l*t4==1X3EjUY_D`@`>JD%AG}|x6pQiOPffbOuACE;
zwPpGWrItKB&8fGics+66C=m4IS;Hj5QkEpyw|{pSG8KDy9@*@#@}R^?X8!cG;!o=q
zec{jGt+~nCDY;xhOC?flb()7mwZliTH`lfuI_@OP8<5IZ<#puHqejn3j*ToF=Zlu5
zEbL`I8RuZyDyWs@aZro<k@xn@comudkq$K?Qcufxq$X<^c=g=AHpk=S#8O@@m3Q(B
zvX=ei5lOw&S@qfUzo^lT+Q4@lZ<ob<XqYSz9=GVja$Wn)Q#5UEE}7bp(HI%?Cu8M=
zABMZsW>oscRX%^OBlO*qiS2@f{iTNo#1=k1URLUE(OBu=`$4s%Ld|jitX=j3JNQa9
zCrG7h9?EsdmRRBZAnxA(D^rTu=d1BDeR(W)TrtJvxY&xS;<tAe{mO9MWtF+mQDx!o
znavfKzJ}d>!g7dZpVi7>_C_i93ko-dtHW2lTAb$^%*mw^!}%wSDM~w_ip{`T%=v~|
zrx#;mYzsr^53d5A4A~h{3k^kWCF&++EP1e0!sGsJt?Q0U#H%cORvc?Ts@8W|r0D35
z`%#I<y-cRnK9^#i_MusB$!nGuH$69V3-|8Yvqo7^Mc{^T{AyoKwfY5a3-4DxI;E>5
zu4J<IgC6gmqZ^k^-nyCns9s<{$6|{EoBV`&+PLMbJT*l^Y$oYUQ~eXK*?#Za8>!tK
z?y^!lJNCBcsQs3Cpt@0$!AfXPzvjE-W#`kH{eK%X%+~eWl;!vBk&82H#KPk)Rb`)b
zvUAQYDSPK$;;?ada@zi?;<C7RlXZ4FUvm}+Ey?Hmbk3<#W^0_<xfqwYg9i@0d-v?l
z-8{pIHCK*v^9sFbY;(^qW|ZhtVR^9RqA9CTneDah6WYYyaB&?}-Sc^+_~DLAEDA!4
zEKEd%Z<N1DkhypCq^9Gul^5Q#{RnF*7ppn(+o9Co;pY;$fB>5o?MN3fi*vt%E&4)M
zHwv%1x4^LDQJbfr|J<cFmz<Jcx1Hx&kc$(4_q=$fGu1c$FO<^{$j;!-WSKhid*IAR
zY|LEm%~%*_Jj$7T;dkkT{2sCD*z2C%mM8c*|GUah-xS&q=99&h=X08Q?y+ThBC$gG
zYPa+=MCKkm^Ry`Vq{6&wZai1ydfTSAzHK$OTWB3B>+;R|n-`P&xqzae)6yH3X-X76
z%V1jQ^e#p!`fdQHNb?y6Tlrfq3p>pM+nz8;b<dGo;3}DWbCt;2Umg>71RhwiV+p@d
z8rz52Cx6<s?t5*}a&cw22~)(nj>%`1t6zL-<FcRI<n@cpnd<AUxjHOmy<&8a#cY;Z
znx2!oA=B@K#=I*^C4U%1vv09@OXoK2oAvhT(Zor6YG=;nuN7P>ZgBV0Z1yi(E@Vhv
zWihJeUcC0{mxmW+h5ddW;94JksUr8_KR5jg#~PcyHm+)6@XPx7a<Be}6}#`1COod0
zS2TsW>%dp#i7Q_$oAgWSNq6SO&vV=(?Xpijd}wkt&_>wV$Wb%uSNr6QZ4Z}CRFLVa
z)M8&Cu>W1I`qW41=PtcA^LAOH$jnyWxJmy+k*jyTQ0aq^i*MZ~YpRRxf2A{X*QF`f
z=iXTU_Dq4@mS+=|-*~U?E?OpOU~u0?KRZpLvu>s0t)-hj37KBY+H&buywTyi#kaO8
z#VQ^7ZTcuoI{Mb<t?!lg=zDdZ^Za6|Gu1&lcxv&6s+H3iE|or;k`~stu+57r`NU%D
zdIpX**FBsYQ={fEg?5N(#{YMmsni&G{bihmdDi(9)fHl!CS7RWaY&Kz=)OCLo|S(w
z`fa&QG3CYa$XlTuZ%){<hEF!-xW0YbuBC5P-x-EZX!U-)>Ri`N#`Gld{|>v3+!XzH
zZLUv4?_JS#n?C*DrvG}^IWHq7wlmwJHe~X8PYimbtSxYG5?}GFy7E+^a2pk6PI1<V
zi`Ea^j|OR&uv}MEDzysU`-P#QUE!b<%aar#r|=!OL_;GUE^L#koV|?2?9%)kwl)KO
zAEvVQ^G!}0W*9Q^WK5i<<#=5;HU56o&JE!qZGTK2@^ejTcvkebF7nOuzdj9GR;T`4
zYT9v2UpHv!Ce8`6xk{hCXP15KP|e8TES^1C$@b2x3v(E2Vpe-Rx+^pF-}bdFbGDpY
z6HxnLs!aGcw^yPY*yAF<M0Cv4H(km#Q7yyn$AQI<)DDUpWGGBHxvW98SEYBViq8kb
zTE)YCHf<)s^Ru2Xws^~~in?<lS!a=Sbcx4;rms$=ItrVn&XY-hsJ!}$jKJ>X-nB1M
zznG@v1YZbu`W01wy=B=q)fv4GpBG#?!V;P`=husXqFXwKKUOh(P{>u;bNpKD{!O(>
z-RD!Do9Va;g~)9YUG(bIqWSagC{EZ?GWkdMOdl1~9rG@koKoL<(3@x4;(|NNjyF7R
zNxi;(Puyuu2QOdovPo6EFZ8R6%zPU{FDvbe-q7P@Q=w_O*yfIkZ_1S|p2=<NGT&Ty
zV5q{QW4)IDzU^1lOGjfOs>J<1JZ#Rhd#AFtLto2XbG1Bci^syZJbp~mJXgEB_lbXu
zy(_jX;Jn^L!Ja<lMgEPoci-|ZPC2Ytax~<VfJ>ml>!(%MAN)PsJG<R;QaZ<<YlW^_
z2Ybb)o>_R3rOM<Ux52gxDMCNRH!wwAJ6IC&!goRA6f@!7_b+fBer76odI8&u?}Y(J
zmpYcIekt1&CdVOB&{%rca^r+^O&Vr>Tj#yeW_%~lv3JA7sHykfF7<BYGv&F)csG*i
zy6e`X>zJh@0(0i3ZuWf3b*Jppy9u`xqVirnO^z10F-6xYW_=#R*M2^U<*)1H-HN7e
z=kOH1;gfcBb>*b9Tzc<X&quu6*la${%IoUR%LzqmoIWRc356IK*3B#2zj5E8WR?5I
zA`VPqQ?h-uw~BsW;Pxn^^}=hF$s7!KQ-Z>)-296!WtscwY(JB-@p!}mK3+ceRGrNW
zo@E4F(+apP68pzV$f2f%O?Qp(`Rf+$vvrRADysOI(*4M^{b0=9z;fNQ3`<TcEy&ts
zR$Q^+h76l%nzB_xnz-lEw67h_i?!Vsd7QEcR_x`~D82K*AznYNS}iho#^SAe_H_D1
zxMV9#TeeeirF+@V#v5e^_dWFdnU=xeV{>@o+mko;v^z}o`*d;fUs2|%Qcf#oUU|y-
zisxYea^pEqgcn)&o{&)S6ytf9vEgfzXV_YUo2w^DncHqYo=~nHF1dlb=wkY+r4^!)
zzDFZ`AFG6(*B47!b@jlt*B6gxJ=@2*E~K=%@krRz{R_MDjlVy#Z`{z}#m0MR#+sOZ
z)hi3m%ng&Po3U8aQL5;L$+v^E(&A)Og4DLo33*xOwAy{O_BXD%>9V4K7QAr~v$@c6
z;mIDI{!CZrc2U8V4|aVsU9d^4-H$&`=1F<-?-fNAmvmyKW8Mg<-<*8<@SUSNljaNl
z2#JkQI>Du;@cqP*9Sp5%dh1QU)SkI`I(dhHZtK~`EqmAXEuPvZAe2(G^UO`R)7_7E
z&S_o1`HsCo<I?o7&t^w8Emqe(j*{JMvnKA}rugcjH0Ifk%?Z;|4sI3Sy03h*FBf;!
zs_l+xleQQgz0K`->WoTwp)bRI)?Wn|kH?89+itR%rFc++^;Yhuf@d$LtlzavfJbSL
zSjlrc<=n!Oce@WZb{TNQCH=d}V`lGaH>sM1p)avjTPyRll<{@H0%MM8akJmGTP}A#
zG0E@MW<O?5&&G&n8LZE@RV?*-y;Z4S>E2PEnH<|!dVli_=+QW7#hI7xT+COZ)6n{+
z=)HPr`@+TCZi~}p&&^sg=Yr1Esqz7{B%gb7sF*lBefOm&(ZTVe%a2z_S1gWekcbLg
zSREjK$H3~Z__30tBeos&VxKj>HHz`}uP75dmeQ6Yyn($u_Iv2J3!=vZwz)J`YA{W|
zamcV@Z_yUhd(Y3aoY9jF_~3Kmh03}Kb7pMxT=4EHgH!gT;4=#&w3XIGZgp1RKQhIB
zqvjGv^;5RHBTc7q{@yE)we7jqTk9U*?0#LlP&4P$noW1l9^N4sTs-CaVl~;GZ#vJO
zif#GT`-D|gRr3Z5OEgRI%AV7QPAm|d@^V$vlhtkk7cSpFeod)-!NK_-RZ?fI6y-he
zcY&PRC$nohOcf;;v>Ogex_{iDq0PwE7kO^3STkqU&U0cMB9qd-hU{6z;=;Z&%;m$|
z&N`u&VV||D-8L;gwNT)C*6-VEY6RSWU0zaIzJ*ga*xvU;c0pWoovUOXo1VwXjo)kz
zE)MK?eo#YbyO(#bQ}VmjWd~RlH!#Y*5inHU>7nhBm8?2*(h;YX8I4cdo<}_Vx^}k?
zr}XxVnYXlmvaz|Tik%Yi^H*jTpE2jCdCL<;VJS<`7qZu<mq_Ub_SPK9QE6koDcwKE
z`17=kE-|4K=bTwjUs<GXvHOykub89gMT6(fdz&(hlO{g-C*AU)CZNxA!BR1iGXlz=
zYs=>>`2JQcFiogyg%($NU{cx+-Jm(j>K7vz*|{fLT}>CcooJ-lYoS!3{9V&YW|_(h
zZpRC|IT~1m>QXzeoVv7l$MKlYET)XJST;{j&pq%$;nYhlr=Lce;nNy3%O)#rn>T@D
z)ts}*-H#%K6ofD3NZFcB_BsAd=I0rQ_-_;AXC>{K<S!TN88zKSHLm5j%M62$yM4H3
zv8`BNtjw6YQSY^hXD;ihb<LN&dwIk}le#V`A28c;?>+MlM*V;*Twm2^EqR??*H9u8
zQy1BBW~JKNvKJN$JeQ~OOy1WKrq%SDOZ&O}k7E<dH+5Pq;>qDWeBp|>^2I>rh*;K(
zg_msai!^9GHZz*$A-e5|QpQo=tfJZ#H%!j+y!mJwc}b_0rCYe>?Xl@;2R#B-b84(-
zGB>H8xK8p^+pE_reKRXF%FY+5YtHW4rpMPm#d5mzme`oR>0xJ6SQuKLTQob&6!VTu
zQ*QHI_)A1nd`nxU*_N#j`Whw}+le`Lu0NW5K8-&?W~uJfWr1v)my}kOoVuJaY0mCo
z_r8gb1*hB(JN0a<nFd4mL}l-5=Vx2Y{4crEv#n~4{_YP~W-xkRJetmZd56o~>|+e?
z+@w6O2Xjw0zRth<%V`TXS*F)<&y|I$w-la}&P;z2F2k&MddZ&0f;)1pT2FYoe>!ul
zeNy`8qMH}D#cgElxL2T5s;IG%lfCiPwtR&H_kWvlUK8w-eWRHt#8C6}!C7sdW30DZ
zW-*-gUF*W2SG1!^&S9?Mv!2I&iZ@<o3SU{4cR5e*yFlQtevhD!CKp58*v}fSn#kR1
z)ph&JB)wd*viQbzKA|ZhNi~0NTwS+?(@Cs+vS(>i#Es%0<w>hdI@3a8Zy5&YA6Txj
zac*;x%+pZ$H^KMyQ@5w-EnL9x;G9kOboM<Hx7<+IW7_Pn&LdRa^2gDoB6k(8SXIUb
zdOTjo`fciw*HS$(y)o}uO$DCuU+ucz!1wLS>aID-WgjL-vv4ZvK3lZT_Vewkv^U>Y
zw$})L@8;rTbYxuihMPZRYmE;7!TEC+s4+D!RoCNfshG5T*3~&rTb6AKXMNwcuj7ID
zij6;mTE6j2ov?8(Z=LUP!;gz@>Bw0Wb+uPKW8C!1wl6SbYyHZdY)3v%+`isevT%>2
zuej*b@ck<$e0&z_t03{YF?hy?&5fRg!4@0(E->u~TF0O@UB<Gw@1KsyztUO4FB&p8
zYfWcW%)B4^A@}M}=Cf(@<%KdgN(8y=%kVqe+p<8m+raGd&h&-f#P$YhaGTA2=3=Hg
z<I1wuvllm8><D|bdb8}2-E6ta>Nn*qN`zw>Sy=_TN+-WCc~DU5Bk$X1%DQ2qN|eEh
zJ>55x^)>%&RpL0#uyJ>(nk2`$6<%)|%#ZnB`uA}2DxteiPG<|R=PKJDx4lT@q;=lX
zRc&VrH`e)Ivf+9V;Hft2<Z9Lcotr7{1#VRin!H*Hs!L^F9O>CIV{XM1F>fJNDT{Z?
z%TnG7IR{TX++uukU!dO^*Q%RSX1r_6oG$o@MfrMPVMN}P$n8do{Z5OSPbY2AoWVQG
zXU9pWWYrahbLSjS4DCr$H1o`QV6)4(<<)F`jR^)RUyK-ZL~VNxP5bg9jdSv1o08qD
zbK)82xOW$nYRZ3i(E2Jl_nGSx-p%`4SeEn4Z&6-lxnNtuqZtnrU*<KX23<F6(4Vm5
z!%PFFD!CSe7j~ugt2c_W{>n;`VU%9E+<B*BQkr|7l+DSh>Rk71Q@Lv!3QZZb_fJxE
zy=eR`K=aj?2{%g@PdY4Zb9qO>5|^);)(zbkULTh@P?D(Ft-Ls3#pNOc6E>3%BCY=A
z^CwEr-(ziZsQ*)<WAqM(6BZLs^9g=ia){$;hWdFMBPm1iX{YD?e8LozEU@xWs<y|H
z%enENOxRQ6r@lBITJ&p62&dh~t@EPqywPyo9_i6&<Qq5D^3}`dOIq40uWGU!X7cPk
zsr^IupQ-VT=6OxuJ~>S&JhaO7mHxAz>6bp<^i`U2Z(8fVm5f<I3{PsWcpbSVl48`j
z+MGAcm%ZWK(+v%0?;L;Y@XVmNV`}m#g}LREgI3S$;A%L@>B#Ntmmo0Vqz_A4(Z<x9
zb2@i#>JQI&sXO&(yY7^*la+=O70;O+d-7Vq&CK&bbxo7B>&uzi@*n;ccb9fN+0>^x
zL&;xLu*+=Q0?x9d{`_Cr`eaHZ`roL$ojL2n%@cbPd5=zKYG}Mv(BN=NgL%c382ctO
z?b8AsucrhQgmGmlJ(AM1dGO|Ff6C%3%e`c)EbEd(t5-6|-F;%jWHLE<>iMUOs<&90
z8`kkNRvhx1ow-?jJ73q$I``uqC!F?7nb^Esuum&gbB>?Ad*-#AO|Ks6Tz{T2m)%9f
zOLNLhC&?T7kuEHZ%kG~qeB{O^Dd$yjKsG5RO56Ij?urwKbbhC(eO2}IV^a<3TlYD2
zS%u6>8C%1}t>=Qnb~!9~>iHn>?wM^SZ6@+sWs6qLI3}`K>~uqP&a0D-mk)VtnEg3^
z$4SE@CcjnY&TNvJGJB5OG+jrdx7Vj`_`LYuJ>>~)o0HFMjNScZ<!zn?8#m9^`?1$_
z+r?k5S%)k4KTS#4(Yf=)OHK=EZjP;bFZtCAbrsXjI4a%kzjf+NXI`M%%*ng*TZ%Vm
zN8LQi5kGNe&6gKH4w-wNW?HmQXG#U%n-%%*v#c4lGk<LHjJ>eJ`grEKd4JvRDsQ=P
z+U3-XZA%U|oKZeswCs^aNO$Bnx2ch-M<QRTWe82#%yqx}RP4%~210T3V;|h@ReLAM
z68O#c7PGLXfzXq>+GP%}3KIfnw6JJ!d9UQpsG4=uZrb7LdW;^Khj-{`2yJc_+Mhms
zg7<4p5r%(xiA*vqZ^E=SEH`#<cWiwqv?@y>O*Eq5)zth_*;96{R~^G#U-1-qf6Zj%
zGUIlzGs;XzU!3>OEi@qH$Ca%OXZRm$E?~(l(eb*RV64W=*~67&(p=O%b)ier9=R7!
zJthZzvr!f2{OZ>JYD>4n$*(z@@@$RU56sh^z4VyZtE@S*3|yy5-3};Ov_qwCQA13~
zrlRv_CVtmQF1*YZ&e!`b>5;RCwnUx&r8x&<S9VBuMYK)#knngHc<<<+A~Qdx^Qyl-
z8dkcn?Uml;`@rnOo~7F#Z_2McvG>B+XKdNiZu!bEEpOxVJS%yken+T?<Q-<m_KowW
zeXs5Qvgf(lg~M+@hO$Z~$a@^MKYVu8S-Er57j0sSTE1hc@!o$eFPC~1>MhyaqN9D%
zu`%pZV9M^|<m((6KThWNneBUKCY&nVkQd7*`9<}zmdsMIjSB)Sa=GdmZ5};YyXo&0
z@1(t#Qzz(4@0F-)WsFm}zU=a>>id?@1J><LkqGPyPt6S2%CJP(bM^}FWAdsRr;DSW
z$%)^yH{j8i+;wx?wd!)w?Rh-$Id)6k<`##gd-QKp>s9%%;)MTp;l%ibGi6&PXEKJ)
z&z$CCW8h{Kq;a`rmY&9Tw#d@+0&zBxcLL^3{P(ya##3O^Rh4|9O-pv|tL%DhZE%-I
zW3IleZOe%pscbfhFDw`Y!zvqRE5BGMaPm^ASgHLr(G58lbNKi9%wpx=IOpyIlX(+A
zJUfyZse9mqzGs@fm1|4A&xyQQu~kiFpVe<2m3q-Ezi9oUROi3$9<lM4Gfh`Kh-p?Y
zWK}yQ$o;_OD!YJ5#{8x*ZuN5_uj^6|oflhnuY8wWNI~e5&dW0YxDMEM#V_l)GUx5Z
z?^kBpS`{35b>bYqkE!7FYlqTm-z3kgY^aaEa_B@|ra<$`+mb5#H$R&^H-Tq`;n%=9
z^6Xuq{>;Y9>YDbd=q(G}$A0Sao_PsPSv{Ip1bl96>u2fKJECRLR%IySq4MnBv?<}d
zXR73`oi~11_u|vzW3N_m`tIc8NzpsJ#7O3M0q1IuWpngrvUuBm@%cSrk-!JWlj4>c
zdbjp|IHEuI5lfZ-cFSLDjx6H4tHSs2NL=)U2*bOE95-+6KD4E6lJ7#pML#>2+J0cq
zh|d*Z`Y3Sm5&I&xP3=|xM2|lxIT2z~9Ac?wYm|R#>ef|?9cnV63yKc}J1mJaiH?nJ
z)|_)>XWwL{BilU67FE^nDw;4Q%i(vQzTjfrM>(H7Z8e=QPF%maWQmdPt)q`kd>Or5
zs`vlTD_LT*S9qH2f+7tUsadL3l{z^AtTiX6bAK-AJn8bt-RB=)Wk68fp)_5Qw@bEN
z$dvlsD3CX?eQ9CR9)7i_j=a??#KW!9nYfi}-wOU`StTLSx<hnz*ov|fl?^v$aHVce
z;?k)99hPah<HGx?7Y@(65MWhxhd=EO+j^UX=JY7%1Pkfw&z^KiZ0BwCXi8G>_VDJ}
z-}>TA%ncQ-RX@*NUL&_#L^9{Y*$bERnwu9~FrJ~5IVGvi*L%_}mHb2RVx%HcT;o>@
zU7NZ)T=le-oqWvBJYgRxrK&fboG#%NVTsc@&uD)Aly$JsYx32HW&0*AsT1lF%S={%
zD(mv%r}H#@p&w-{)uz~L*}VG0zQ}T0?CE?Hsot7;2d;p7Nt&;0nH;Bni8|2bF*&1h
z`pKCsOU<~2BmEmyFHW7yHc>Zy;lzs*9&Hx8*Y18WSpL#$&Z$|qSmw|CHBD=WmY9xX
zR~diul5|~3=~cH&!q&|5U3l;jcaDATx6aV2tup?ejIuJ%Ri_q*>hUF<Ua?ti>bjgB
zaj_R{g|2B^v;v}d7B&1%*}QL;e-`sfGl`paK|96ON{YC9nE0K3t4DlUlw!9%)wJP=
z6a!m_0RvAS&$YBbuZ5{|wmb}86z8}0l$!5_lG5WwUl->rviEz!<*?i+*<`84<=a74
z=Z@HmoZ?OG2>Bt@BCD1)*{}Pp*~u#*?pI$f?6{MC;hC0G!5z!5!VN|Z+c(E2y~@>`
zd1IZyWF3(s968&a>z91Esh9iKtlBF*^aD#}QK{t1TP{7quE(2?l($8?uoR2=NLEff
z($wH;nKLE*89%2><~GwwHVfTOq+Z+kyY^^u3TJ9eQ|STjm}ZxS{0sTdKjK!LqVAaf
z$)HQ8LpJ_o=bDU*i}=$5pWVFu>0rHg_gaBTeNnwfI0~Ycx<(t`Ub4|g`@V%D(~3KL
zU1TR|9%sB0w1T~#=WO}{&kq|jBp%%;>{ZxqF@b#nzecC@lpC(CO&(h`1D2PvG;+Na
zJypLjNP^9K;<uk?rv2G?a%R?p313fNoBZ^|!KhbS-kz(bpV*N8(@tQ`H=cF-G`&8b
zo51nnib#^ik@E`EA9*JCJMOS{K08PImqS12sU5BV6q{0?-OK6hoKiT;Q^I1AYkN*g
zuVr(~wnG={)t2i1DLsF>SNX}}yX=x4{$0D2%S)q!nziIv)OA#pJvI4NnD1>Y_|e}o
z%fUeIX7s@&zdO6WZ)-Z!Te^CU+P6hhxF&VQSi}fM^q#f-ntbq&u*I#Q$c8Ns8qPfI
z_>z$?q?`F}sYjFO>BIIWS3P&nGSP{MvY3~%D_v38;ni7H0lA<np)Ap@I%1ZVUHuw+
zxVJ1cnej5=jKkC2(bHSf9c5>-1y)Yv>l9!8au)02ExwmE@>RHmW*s-tx4iR5=Yo%j
z&w8a@%v1Mphw*RTA;7pNp^bGxU0-m+!gSMvhsuk(ll3daP0pRDF!pMcJ5s@C<gwMu
zkT?6bLid%&-=bPBT(~6Kx<a&__t%oC%2G$|nR3d%%v1>9_hFI$)I6!CM6rTJ?iG40
z9~N^T*?)$iq}QEg@{aZm4eF~>8)iA)Rd-(eV5Y9@W|f=<pRfh#2U&y<t@yd~=rSkI
zSx2*s7JCPO6ni*f>W=&zgE~jY3rqUUPrRB~w4r|=OGeek+WUXrsL1)PT5|AjNY$o=
zF;A`qaDHF%(q+<mv6~7TcrML7f5NNt#qvo(V!V^zI&jUoxcSQOH&Oy0t~l|Xy7}8e
zbAi-j#~i&!{%792e935<YtkXrFv}_Z-@?rn%RJn?A6{-M`4#eEZOy`&2cNlgJH~f)
zDcttfDil{(n$*y`i=#Eg=t||ZlFp<EIqxr<O)l=~-@MKFj*M90<V_{Psdmg6OG?uY
z&v<`mmQQv@^Mjv?y35M~+71ic3agg9viwAwMSv^A*#q;AH18MQv+fhuS*c|28183D
z6MlXF$oWP1CSOp1qtb#eADPbkdQQL6?YFOI*Nm%s<F2;^mngro-Xdl(gInfr%e%$K
zO)*LtX$xLOWIFOOY88KSRR~tAE>^pKe$DNMFqZSnEV!&LSO)G}FhlSP+pLIb>icay
z%)F+oo>8tH!fz!j+2yoZZ&IYni<4r(Md~d-Ed2#t>P>D0uRnA0oz2$E-*uWD9Hy+y
zihkt1@aRg<dCa`idz>1!Ep+T&=E2wO)9_=F@I&dFv%PkTrOkcl@GpSl#R?I#^m7$k
zRvCvesJaU{DPP?2VA-l~>en4(E_lzjv<toCyn9W6w(55+r`~t(o;&)9f9Kt9-Z!QA
z>z6&V_G!5?JHA)UujiXp=@43(*%-FO)}&DTro*#V$yuf>ks@&?ZZfl*cTBrJ^W|l=
zyAxWb$q2bUcjQx=)xsIOxgqSyp>1+MmS}Vwe#t6ow#RAP<Z3Z7n`?r<7UfLe8S!N<
zV_|;Oo5<x1>Klxj`XoQypBl%qQJGc!!OsphhC`cTTo?@=FPmfOb&=ua<wJYK)-Gz8
zkQJpc;oD}z^!RsDFYZ?OHr9V#d(W^bukb|Ht!*1mOcS;cZ#}p8h1YYpSH?@0oJdWP
zE6{fRJ=5j3!&H?c5+R#Z!r6|!u`F|%<)Y4~d?v7Kt?`{Cu|I5#a~-!CY3G{oUs>l?
zwW}?8Q3BhVx=ohCQhhGmi#;|3aDEGJzMjX#H-Gs}56uj=W1gJGoii3Q*cShny_lw)
z_dh}UeBd9qOWTYL`xWNTS*Edi_gT*e;VDzP4smmQ{`K|p?erskPZlyw*kurIwX)NE
zansXmzAr`IH$<kZoM7C1XI5jjL*c7;i|s7Zw6-1kpXR68{iE2eE$hnCw<}fOY6*0;
zR;?{=`0#$d`e!@as2+*d=2^}fkuRB@9?z20y>r1QZ<gm>CX3)nGky0ub0=PXxg*0=
zcyku_)TV+4(?2{0db79v52~5X9GM}ul>5X-6H|45&Z-wDioP+FtyvSZUX1t4fz~-C
z4<o!el9EL_&kN1&s(7O)ZeJAI{nVi-@r6{vyh<OhH)ohVvmD*rCj{|JbovSHk<T;u
z9(dOIF}rHB&V;9LO{O1KoKm*yv5wB8Ia}lo*nhag-tnZ;T6nXr!>5f466Z}RIX-F9
z<CERDPM@4PrJPN2@q8sMw!DkRN8Ke)p8R^;>g`PaVviZgGhKgm+|a0U^13gww|`2n
zS1s?)KzaK$_fwzAU-Wsong8#4p%?EW<F@7+rTekmewUuQ$?|66gy6D(IQb{7J|Dk&
ze=2&jw5f)<$?eDP$Y;Npmt9&DJg20KA@64ft9+Z+R%Pkbi(==eM1|fK4~w0vSQbB%
z#j$_(mWv)H%AX{rs!cwU9$1^kyDjO8)_>C#yXAJKdujBDXnd*D*m|w$#JrXL``o@(
zN-;;XEKT@$#rF;Sw%-btfmb+|^hvzkxi{GIr}#mUCAa6U_Im12maUmEKjD4N`%fIp
z6t~rG$eW;gtju-Sn&N;P$rc$i=Q0<EFA-$g%eCuZhv1!MKT{3`e|dFvQ-9a3yPGba
zQqx)8)NuBvr_&zg6DKuZn<-D;^)B8&<Nr?A`a2QY;*BfiotH?jtemI(V6Ww|?D%G(
z=B$GkTu-xDnRR+F2D<9AdvCIO^2|~|d5Sjcwx)&3w{}iilG(Y3QMhu+qd!7i_YZct
z%g&G~{3?9(qwm!(nyi^_b7!t}Tj%rAHu`$Sqy@H_UNQw2x4jGqwpgFRp5#|}Wry@q
z4Zhxt)<)-<O2=nj{bHxwc%sv4mDF?%C!48}m6Zi?f*lOE_HfweY`${IIw;eIv2Jmn
zq+y}T$AGgQ;*~*G&jsQnk1sp4bEo`~4HZ9o#Z=`RR1yMAonH49mk9~+`br6I>^jDA
zT7B;Br?qDsE_7~D=;Y)~oHJYH*^G7kypQ(1Fmq~(&W(N6c`^3GtqOmZUMD8@nY)kL
zwER;#x&5H@u@>PYlQRTlgG_F$Vwz%jjbVdv*Y?GMam=@SC#;H;Oy?GPdFbo{rU`sX
z%y(waePnk#-F-sir)a?wZ<wa<yRBfU*1h-BA5~4>2}Kj9zmn<XdUNX1`B$nd42o_y
zbc6}-e|N${=$*S};^gGgCWWHj%{orbYN5L~ALC`|H3?o?7PPnJNU)BOi|}@FG1qJJ
zE>vigW%a09abAeJ$kpJqdX_-7;dACQCniolqV%ZudrahWmo*h-M@{$lpSb#YSJ<+`
zhm)UfIC)O#1p9S|c|D46dW;laz7e)&UT*b`>y>fmMT0Qc3H{501s!|#tl3so_=16d
zUeXJbolXM1bCWI#I{Wfn5UHxUd(>;P#0D9^^QOE4k$Q}p-#3PH&l5TKC8BBDTwRNO
zx2}m)aD<$Z@Y`<Tz9OX3FK>znzfkQO^M*S&cz5+M>~~JvqP8hV<hHVEg0qIU5!06*
zHtAn&TdOW{dOB{I@L;CqcC$;}4%NG7R0(Zdrx7L;5x#ii4kdxEVig}Y--d@5w_Yf8
zRR4YE)d2$ye>1;L5zj1?dy3ypIFM@mK#JSE@!~Z0su?Rfk7QoTb-lE*FR?_cQFs0<
ziTwf`qDT7zjrE0;XFre-JZN-swyUs(uv=~50oIJrIWK&|54@k0v+afH#sf`juO%?9
zW+}SeH&c1<xve7G4{iS~r)ynuL3s1-g84J$9dvZwG1cF1dKagE#L7a9<M*i(Rv(l^
z9qTV@3w$}KHCZu!^&aPiX03DCcfJbn@;o%D@wI~)duszjVTNHw)|qy9>nBUK9sg7a
zTW;TM^wTC&KxN@^n^UJ}2~TEO@c+Ya&T|J&ym~zA*K&1nn}sJ`G9{-Rl`8&T{Ln^n
zkteSl-{G~-mU{OKt2rupylOs^7bdkt&vj09=sv|n*)yqrZx(Dkr6qJtD%9qI(50lj
zPY*8?zxlp%<2f!5v*(9clG5WoD{i{C%{thh?bfQl5^AbvI_DYwVm?r?@`YlWl}N_Y
zFKNQv$*X;t>Npm&T+N@SEY%-9M|taBcY)rP$*gA<y?=Iz#gpOj#RXPTG8OOT<5ouT
zr$svodsH%X+Uw}gu--i7hf&1-zq=VGN=Izh%9<bPyYr;9`n8uQIcJ3*-0W|@b!uZ=
zN!o=pvD$`a_w2qm31Ye`+XUnvHT-+Fi|0z@n$0J5Y}ZC|^S3mJF6jBZriR@huw*fN
z=y_@HM2(W3ckivb0*=n?6!2~Mbb7+Hg|d}@0+%dlUm7@h`VH;dKSSrT=XM;w#IWy@
zg7$@PPoKpl7<#m=l(6Wpl58p2nC<u@?gq2d6NRG|f`9TiPU}b(`cr)FyW{oHRl&yJ
z<R0>{mssrxoU!z5VnSH0OP8{rv0%jPgWC?As!MaX7BD%}dt>b!u8Fy-h8)f&u9F`q
zmriczwB~euzl72G38!>>|Jn<dMz#uk1^i4Gvh~=m=r!}`EmjH8+z^=77Wd3*vRl#3
z*D`C>Lvy3VHtI3nEmm5^Tk!Vp8zBMdyx;(16}Ilj#=-HL%R07h;aD5d)~RmA&sB3w
z)567De~z15apjdo9cphc2HiP+^z4%D=Wg)UOlLf>YSr6@hc`PsEM7nQRJSZn;!dW3
z&c!=dB7J1^@{cUZSAH&ft9-ePWT($X3xUv{FF_7kPjBDr37wr;$=;A55c+lR=EuVG
z7tC{5F|Y75)1vJzl09__H@*Z##l^my=h!>*_RA|%w#;Ol@L81mshd^hf_teyoobze
z<#&Z}{^HFOwzc-<EOm0c@MoT~_-iKSyy694)UU9xmC7;vJkk>)WRp-fH?VvvYyT?W
z9K9JAnNKfxlTb99d8bRRYGb*q*-3+`2hA)$O7HaQ*5ANvygQ?Kb<~d=`TVUy)8@Hx
zax^Sx?2LH+=|bi-CkLGmH!}a5oJ^eW%E}mH82IABiRB#}8<fr*IrRV8)TQj~I;)!G
zOjde)V6tA8W!QO^>w$%pL8M0;i>OGI7V8!cFGG#cK<_tUt$lhdTXtylY`&2+@kF6N
zOOe3eC7(RbU*ddH|NC#^=|e@Hw+;!WPEcXpyUCGn))w{K*FTyvPPw$kqH&ws<@t(R
znoC?(WIXPjp4V_FamExYrIh!b&TdB>pYP^B_S}rEPCtF#5+}U_g564AG&d$Q=pLVZ
zEJq`psqp&y=Q~#JG!tlJ72SX6+BG?stwJrHd(Ct|2iKl(3cT!o#lZEFonu{TtxJJ9
zpS1h$3+t9_GXE9yE7dMVDK=V;{h-#~E^iJomw8KGU({0M+IG$Ob>Fq*S*0tKk~b}i
zGpq1vxn7lOnw>K3MInRwDhuwXDN3{CO!BJ3J}FeM$xswrKl7rEn$UL7>)U%A*)KL%
z`s6HMaB!(OqtC2k7jK-%Zi(xO^Za%%**C>lLv5zI;@OZj=YRZDD)c^+zG&6rX;B(E
z8lTp$Ii$odUlnUCv0J8|zh;J%$C*X%zZYLP)bt?sLx0#E-P3DVy=hGizf$rcaEeuL
z+S`_ECFc$pz7-d~`Y3F{>=SW(8J@+)lb<BA>CNus`jUEBEz104p;@<)*sj(_+g5|>
zOHKzZcurpwP~+CFJJJ4mlk>l%Ys=2w^D_|8y2^X#N9ppw2U=Fj0zwa?54>}1if*!u
zUdzDBy|~71OV%N!O%ZlE+yTq_A{`>*ubOXqTlx3E={Fv~1UChIo}^b2uwGPXXH=`s
zr?g7r=5HR-Wg5qrw_M@gkl(j?cY;Dh^22RLq0CQN`~42Yy2%O~9QmYk@rvew+D3;J
zK@D%D-o1UA%EfV#ce^F0X6m^D#XQzoY?l`0@&p?msNKKqp+eI{%Wv5R%qutA3qN{n
zrad$Lfg*3#Nw=W(p8I0k3#FOaQxn%%dZ@*n>bhZClhMc<s>O3~%Dl$<sXJ_c{hRVq
z$EA^}NxzBhPJLEG!t`rVJsTe`6ss!R;$S%2+^M1J?(GJS5A&BT<I>bR&h>$N(!MP>
zCNoZ2Gw0%3_k5{fOLs=o&4H2;j*m1}O;L6H`}(_3Dzng>h1#8*Cxmi~7YILp)qJ({
zb@$u)i~GB``IW_|O^e<$?+v%^ly5H@7UfUgz@s8{t<Y0#AIqopQkLhXc*7WYR@@8p
z*wH^z`0tIi%kLR#w0Hg4lo+sXx4?}BcV(trt~<y$Y33F4gI~{y*<Jj6``x?CXWu%W
zYs=2qu_a?o{t~`fY1h6791C-*Pjk|3-Zs-R{&S>Eb=XnfJ3DH3om^Aa#5loeX^52O
zw(1iz+C9IVvGBO07ZKJStY*mgLryyU#>QT+9O2z2YIna~tG?WN&M4<vMxa;Z>`m9_
zF7;_)X;+SYK5xS6I*F;S=Nd#WvCB+1S@-0Y!-n@W${D(6ZQA9l^@cg+!;~YEoNw7(
z_J~&siA=3NwB&hUs?Uau9r=9syVo_|iDFTe>*@0du&QS`!JDz!y?yF!m#GOHj%ubp
z2Y+^NO_$;--=|f^RG<+0Qzm(#@0*uLZa6%sy&HHs=iKZE%voIv7@TJ(+zk#4xOMD;
z%!}!74B}oKj{kmUYU2N89y4=WPSq^*pLTiE^7CCx;?eQ}OQlTQn}S%jtoqb2>GkA_
zD_Q4SgMKGiE??y`^G11BNvL*-#V?(t)+<bVO(y#ap1Pe^^5&{;w9Q$c#k`-mO{{uz
z<XC&}uUNowA>MvACu{w?hd1v0@nKvjb~eSYNWEL%!EDRTEuj~u9WKm%zNoDCm8X=H
z>{PDTpX<6$NO1mWdpg7Ip~`QACNGVJb3Z)FDEYMNcS~DLdMsme#D%5lH(40GR~~Sh
zzsUVd)YX)hH_cIt(kx@Qg{So&Y0xQ{+}z>&_EgYjkxi52bbDUxo$9IZCbKxkh`llW
z*x`$EtaAe9NbNm%T>R|DRg3v=@O;16I8o`Iw#%a9XMCih>V<x4=O|vb&`Pp*zkhu}
zN{M~;;g=s5`p(>&7<7PD?TgQM#v4-RR-Uh9ZzRpl`s@>}z4%3p+lzM>GsFt#^!`wj
z*<vnz;>CvkW1AxnZs0OCz18B^dfeXkRqeOh>Q>bWToL753X@u9-9J^jyux#yWaSmP
z))T9O>fY{Ms4mj|=G}#d4lAN}Z1vOe+m(N|VISYE(`R_gwzEi=D(&<V)So)p|MRb=
zccG?f=c6yLxhothIdN^WpODR5=I!Cp8*A?7E-GOWjGj2VVQ%tW^Lt9BZ|o+$*|AE?
z{)(sXk&}f|J`)<R`K$_;;M`TF((=-=A+DlvW!kOk-$v6_L?=1iI=$(Nj8bRiyekWm
z7FTo0t-5iyDt?a2SI+&-eoqe6F{PZY&RXywMANE!nw{=G<;&vFmUwTMIoiMC#Ipq}
z9Cya<wMbB&cGrkqK%!(}&YF31(wdlU60$Pv7Bs)AjgdK`9L*50T2*MbMe_=2wh2dh
zqu*F{O2}@N3-wp1IoO%3JdHQ(L~l3CxyI6&!R-zDVqzI(QZ}vDzm4`M%yNHWc)_H@
z=(MOqs+iHtRkyC(n)WN{RM3?LF|YSBI`T9&eLh>6w#H=9#;fPc^0@9UQ)tZh4r_dt
zy-4q~jZWqfZ;SZ}N0LOPS~Rm-#Y6?l>aRt`%s;a~T4^=cEZw_5kC+E@pKnRXt?X?z
zcsqHMY)6Iy|J%*%;y0fkHRw_in8UrdI>EtZ6VD{h2Mkr0L|5)Poc_=|X#ERuh1!Xw
zHy?1`+%Ht3exi|MM|W1|skeV+N-|Ruu1Vc>JYsaXIoOzK_E!eZPcDg?mxZhav$D*3
z4({_?oy@)Ht)i=XP@@^^#7D_5LPIiM3SO`iEnS#$P1EMpHLHs%9`mODIllav)MWQF
zmrn|>+mdA-VE7@xX@^*-+t)j{w2nU$ivF=<=dEk13)n9+DBM^Wm45%q9lkv~BP0Zw
zkF(B8pXg>$D-<iPkrBA<%)UudwbGWRxwBWcboeSAb(_54xG!&$vs~WB!sjc}pDTT6
zyR=#_|5WXUfaVMr=_>yYW|N;mCBjUJ?-et1y^d{6<knD=PkbP#rp^87^Pw{blP@$`
z96##Y%;v>-yFX-yL##KK@<mUT_uHeFFFwrH6?vheVc}j6cB$(#Syt|y7A^85XwAXk
zn5ZlFD>A*yeCFJCVHZEC!Y;_$Y%%jIONzV`Ly*IgiK3=CJD1F1G3c+m*fTFwQg-_F
zZK+e&z4a;L)?7DJ=8%Nb@1&JJfxem{nht+eSI?7UiDX`xpdMaj{i^cHf(j?&1$ygd
z&8=3@nY_X#w&R#=;EOO<4bL4*ceoWUFR{-4rrlr`d|z|UQJX5oWioHdYGb0M-%he~
zsh_w`cSmgP-L26ErxHtZ=3O_?n#lg*?ZZcm4n5m>n=P&|PkQvw=---erZ;{q7rTD#
zc4LOf6!$GRvlej)3)p+<@UCI`rtnas>C}{lO}%nu4MDep7o5;xnZQ{Q1@^+Ka#_s}
zYdE`h+*Y>>VP*MQ;%9MRXjV$BV!f;b&$44`DQYLD-CndfX~F|V6?S#i$D7V_i0<a{
zaLT;$da2yZDVcm<mn-dZUa~l1H;W)&yCBn^Qa7i%!-2M%jEkq_h}bMW;E;6Y#G4uX
zU#=SUHSLP-ol>ll?mmH0V7aoF8H1J0*9<?t>rXgs%A{6QaxtWSS)HUWn0S(*%|149
z`kHuy8@<b>s@{~Sada|qU~^mjK_gMr>6+d3fJFZ7c0VMKi~Kqf(ObICxTNvQY)hd$
zCaDDy|DP@Vc<k0G!z&7GVUo3J!KW-dPcZ#mp!GF*_v~r$<s3_ItIFyvIN|kzM`en1
z@QTSwE|Xh$Ua=kt2n)--c-Lnu*ODgB6Ko9D+c~4_-6GGfy)QnSZ<<1f<BEg*q1I1A
zTlz~5ZZFLf^pRJ6xc|b+CvR(S$lN%{Q5c)oF5LCcr1NggO!rfcGEdfN8HX#|ZeD1y
zeRtai7N*?xl-GJzYdE4EvMTOwl|2$_ws>Mkbv<jR*x7HVpIx}p-XZtv@S@<HGb;68
z&Zwqqw=BJz<rshU(Db}(e{>BJO8L)<CdFy(<o8O<;LvDmev!kI_;!UrLub-bZoLC*
zoIhq<i?Qvz`Bg;LUE5ka>jCFCmHgoIQdz}|4$2+7uzN+^%qdq3CT}QWTfh*TI`27e
z-kYe)LHb1rl{-W;H(IgJ4;HjOar3W7V!%Uw4<iwQjjL?(8SiJ@X|T~*xH3i2EkP&e
z{spHx{qsE!bBYtng*4pv-0LoBs&V0-?%cb0nG9#6>hyw_rXG%oK}`E{cgyU~4`%Sx
z;)uvBOLCti+<ozP>!XUqxl?jlR%~PSonI+hvNJX?i1WS&W98QT&J*V~kHm+3TH~O1
z;g!$Bc01>bZegu2n5MF4AGt6yQG)GMSnne*S&6mhxFQ)}#2w;I4|5W})fX~v(?Q`y
zjVe~o;oeEj+zi`XHa!z+tq)@T9&r7f5%;a5J5DsKU2kzTW@FhP-c~BL+Dya5vb`mE
zqMZ1W0%32*wX3GHSQ;HHUggG^^>HF=BUgFM%SEE6WUh)>d<wgH<-wmsrgt}dG!&;?
z*FNJUw&GQkFzfV%N}@jTI>J+Uu2rU9nebzBBIohNfkjj7bZXQYdoEnn4`--uPFb?-
z0Z+>XYj6LxUYpoMbH2WDa+vq?(<76M8x4-83Fy4utNwKQ51Wa1n%vy>);(4UQuR=B
z`Oqxu@?xExS@DvSoM|ifZcx)O?7DWb?CK4{Umc7BJK1k4ZeF<WwU3g5^B>dJ7eT_B
zD!-mqt(AA49M&<%{!O)v{??@2#ZRS_{1g%{uS#8A$o)grM(^snwgz@<Yt!p5cCsGk
zOldRibh<C2k}@ZgdFz{tE4M#+-QyNy@X(X>?zN{<9^FzOK5XpUWwv7XN4x1kPlCS*
zY*~C$DRu73>-ioDEd7=$%Z?oscE2@omJHK{!|cmgI!kxfKRnHQ;_#Z+LN7xNn1$Lb
z&lUbp-z9hUWm4^%1@ruOFXb<>{WP2Lj%#t~nWur5IlRt9T{O(h*uL^|#=6CGET8{-
z`gbnpvRTa$qGt*{FFktv?~jh^r#y%4>^sWB?wy>-?)b#u+rq#r+Ck0>gTrRU6uw{n
zwQ%V<&S>F<(S=jiMf;pv)R({D{}#>4zk!n@7AlmzT6yBd75(xlB6}BVb{$*#JkIhw
z<Ks<#*Rft#p0aBCSIedR0nKqzX|4Mf2x!Okc^=v+`9k|=(uYHqsTyxP_?+KmEJ#XW
zEY7)6lv&2&IrEIx8wXzVus*Y+-{d~XtCU-ME-+bqKqNmzJ?gw%r>9DD+4`I785dl?
z6JqA<>)c#<VTR}LbD_b?D|vUw#MMnbl`hvjQ=^}QD|5@lH!9sC(z35(RDw@5HtyDI
z3M;f<x<!PssI5rp>u<wuPqvr!w|uxZPOK7DPFPmM^TD!c;c182tP%O0$9}6!4ve+G
zUBJu}_+2ql>g9)rDp$i@Uv|E2dbQQzo8iUI6rRT$jktC&Ci=$3Jh}eMBKV{;!$sj(
z5husgBi@e1yGkypE^I!O893kY>x9NI)j2ENHp)NE|M)5L#EmJzIu9+<f4{n@s}!ei
zVE*(5?<)=2g^FDITY067v#O2Cr&h9lZmrhywcYT)a2W$vrUd84SqJo_c;+Q3Z!>;z
zwe)ez)_>bQ6wJ?Q=!8w4##|Wni>tdoBTMc5Tsg07!w~l;$vuw#+^U(aY}+~}Wt3|;
zKZ$Jq%=fuPp=l?t)Eb60>v!vgFY`ZoZqMSnZA+(5Q0huF-4><)>6nxN)Am+|(u`uh
ziD%@PHZlFv{F?N|al7@Vez8;ildi5!=J~?4Eoxn~u6}ug)TfgTnO8KP8h^B2l(y)t
zKtW33)bmqgq-<F{u1@T3`n2n{+vHb5Q=`AOBq(U#I&-A%;)Ywj4A-Z-v+^xm!xD92
zr!#M?;3muaQ`}w71xz&wai5#b`KrxFxbHMeKw}&~Z}ah}$67_E64$-&zCP9T<p!H)
zuJaEy&5pxf=cY2;=ogtj>&>(qFYg!#6o2|&6q!`>X~Di+2Ioid39AAN_lKR2aat1k
zTg&3>)0K^P*LBtfFsMwZ44S}c>T><kjAI?!6s|j`Ca5=QHhRoF{y~||)pf#GC4Hq7
zmaXggJY84m7@k|ICX*$3?|0nA;&-f{mj<Y}B;1zBTpKvg?u6D=<Fwa(KS~s~I5Ezs
z)HJ?$!S#^+J7H_>1KUiq|824_eiivmU6kSbW4j%uv5jHY-<ODNy2%;!)5^1uvn4uf
zqk(++i<5s+gWF|U{^~3jTy^xd-;)!^VhoO)x;S588Ea(XmPw2rI_Y=yTcmX#$<6r2
zy3~=^agu0$kLdS>zfS4ImCl>La+N(pu25m}gwvOIR^3#03#_;=_h4sa;%>(;TIMn*
z*p#d;7M?N7v*>umlcn?d{2OceK<O#!Ru<WE`8=Oie_{?!V027bQnGV}U38y`k=E>_
z32Zkt{Y|6T5B_ex9(7^D%=&9BcUy{;XIYy>A6;ptYPn#V;p#K@S0r6x5@5)jHtXiS
z7Ppydi&=V`0xxJYmsxk{9ayIR!HFyLl3Y@S(boC%<(>y7pRBbKi(Qq(Ch)n_O`gYA
zI9m0X<3ZUf-aUU}Pqy*=y7HkR;7aN0=G8SPS9N73Gz-7TIPmRB$I_b%qw`7`W+mJ;
zU*M)CA&}YiVy-|@fZNYwdGDuQVpe!jbhBX=&y1Lv)w$oyVnicu>#cgy^8J^_tvSrT
zQ7WN*rcUQ97P4o2&QAK~_wc>{!N+&1r&mQxWz&mUylc%DVXl{!S`!bkKeb4R65%Y_
zsJ`9GvZz9DX6TPiIdix3Mm?#sJuz81+o+p|`L0CL3Pz1qM#GL{-&{p*9GR0|_E9;~
zTB|rPa;oeNLr#<T3o@n%^=Qo9y@xCOZbGN=@z}Q#dN<Yy<>yEzub-34<@I}C_;t^Q
z?{B{epXYexQ~G(5#DaEf8`eUp4@Fxdn01)K_&+MP2~7ISDe*W#&@|zgZ?4cJ9wXtC
zxn9K@izn&N7ETZ5&wIWp=J`_1xdJ=gD(yG7^Kfnyh;y0cr<;)#d06LZSO4#q=37>6
z=6^RoW{RPj)F!r~6%)L|r?Adawdzt}da}S}uZfizdsl(#bB^>sOnKtHvHj);-X1?T
zho^*XEfeG0u(QV5joP_h7n#4PYl#|M<8az|<xTT*!=6_S$=o&XS<BhZee=`b8hz!&
zG-d;xS9@|Y#R`>G%%{Bd2t61&yJ;iWUC}wqFKbL_OMkYs@o=l`r8B9QCWWNWd%eOb
zt?x`dQ|#=Xb6WRQGYVY|jk~AcewUj3n5(O?<;$U|iH~LH6tP-08nE8K_rgteUa!dl
ztGG=f8FRDKd7fnkL|oER$x7YoYI!@%$4o5cK&XVK8e>euvOcwtZvhPtJ=3LjYMZRu
zIC}-VwsN?lbmFTHXFXrD?B0bYUUdg$mNi~nx%T_3Lg(=9Rx_j$4HLF3yQuSrv#k14
zs_Kc|tGagPq&fW&m>yngr68upSm#pQ#21wNcEX{+9X3Br<|#@lO!k!4;%Lq+I{Bo-
zA*94xQ|P$a%WR)3k&;X%t5#gN$F67_b+UBcl317RF6TREHJz+&i(8QYU+nJmh&<-r
zeJwJL&aoHdPn}EneLiW`+-Bp|@@lG)EI&(1&#p0CQr>v2lTS9wG*DhTYC^F~oLp>?
z>lJaA^;V3N-)AIjde$Cla4Spw=`QO+(ZeA#n-^LMSFncb?Rp%T5MsV=r-IQ<?-tG@
zAx~;Ht@r3UYS-TX&{SB@wQ|u(ok!RAwH~>b(d>F=v1yCu><@n&3RfKCi@X&mE9a|w
zE@<+RwVYLFZM1V-cKA$YxtDf*9jAHp$s&sy-D!I?b9UWP$@O!5Af~kaz`PB2mo}6;
zuKs$W;n2SD$7fUS9=#gi{2+0Lhg938)|xkBwv}eB?xk6&>%DiJJu~(Cv)zyF1=!Cz
zMox6Gy|lq)r{~o<9|ITeVvWlv72nnnzo5e*qR)K8$!8jemK2Kl9+NTRNT>-t%i6&H
zF5Thwr4><i6Ltp9=@8*pfBxjx$-Izj7d0-V-ISRU!Dcn1_rTO2l?KhvALs>s%9$j=
z!WAw&k+*b$h^onzSytwoSqct(QOeU)k$<wF;nU;>>lSmV-${>FEpX~dv^z3w`OKh5
zufjvmSMkcTJjoN`z41!Ed|Gk2phCFl=3u8>uL-GB#5)@p`#bf{++a^C@YuDj^hwhM
zZ|;B_0b33zi*bc5SaW{ELm};^UuSd*Ql3jri~Dr1;kA=hba4=8(V|O#cs2=Gx%x8m
zKI%~3ud|}E%Wtz;=A_E$Jsa8^7<TsGuD&U^L;TZ4vy7I4Grf!_OzyA0X#UWLQLtG@
zX;0GhVtbv;##z(+{$FFXmhq@z3zL52cP3iu#mVj>-XLw2bL`)D#9t2-h*wznw7a=<
za)j(1p~jt6NB1*K%*va##8+b9#_Kf)cpmNcEGsx4*lu97+FJRvuX)|KmPtE37QUOq
zZmQBWXEjUtyjO*iCdymHEBrckSH4@lz(~2>f04%vd-0x%XTI|e^1OV{*5r|y;oyF>
zPfgC(z~?28qmgU(<paW-|IS_-{6xHJ;=Czp-BUe;9rP;$=W16y<n`Co(^|J>*N)Zu
zw6uJJra7;l>Eo5p)V1o3yY{`EO7==o>$iM!czAJrmeAWH47z2O4_%|g^`0+|WMpHx
zC;8xIY2xaT=M4uF7SE4e;4@jvFrA~VgL#F3+H8(u-Oa~;#8f$?y%uA%4%q%`!Ly$>
zS{w8kL?*4-84$iT#bWWEHH&YZW~fYAFR~|d|HRE5JrfsQ`o+~692X{C^mr2U#{Q3T
ze<Lfy=CfsNTOrxG*SkdhuSUS;FpfK3R!SY;#Z|8GPCs)^x9r&M+{rH_R>-LeMPzU2
zPjO%Wvqwam@!gUZ?b#tyj3=1n#071Xc_Q{@+p`5H%NmtGYKL4{cv($G)^}53&jydE
zwBmC<q70v%!=_IXy)~nHLDJU?C%TfYtqeIcM0jRy3%l!W*v@P6{uZ~}MLVU(%VJfE
z`_441-Yi=dWUrXzD7E3R3Y%ua@*TT^td0t=T*NDRan=JhX&1Z9qM#2s`?=35L^s_y
zYs9Q{<mu_wG8@sT@8M0Fv!<)v(uq9P&2Z-ALnd|gT&uikd<_8{5ur!E_SKaIZDTmM
z?rPpM9m%Ymk_dy8;ukMFJLIK*&K0YC{`3gT8;cw9(*?>s&R$e&N;vmfMJw!gms0Gi
zNz&&Rd^)p9b8^Z%H}irGuNDZNFmA~R=9(0}HJEvZ@{{PUk}o`Ew)c0$95{8oi6NW$
z_}VnhMH8QU&b<)eqZeqz{pop2oKB^pRip}sWzD4Kzjq!SnIk0B+UYPeFhe;#HSHVQ
z&6p^j)}@vU++HLoH2azuKi;$Gy!w^X8_bN?$zJW5#%L*?7$56Z8&pv0mO0Z;r+VAM
zBhkvN#uMaulp`{I_<1u0CAODdz1;bxv_bK7#o`L_<2#ly_<i;>PwQ|{P?B31x$w7z
zfM)mVxTg=JXI$ytu`Z=C@$x1A7VUS3*%}0juADGtom(1qImQ0cQ7_j^Gj&(3Yv|eK
z=wYZKu`>CK`L=y6j?30u_~@X&Hc4jf@4CY>-g?2p%0I7&^Ie|zGib;A%#%+3R+}E_
zN!6!+?mg=wnUrgCqxjbOt?9Q!c!cHh59UsF4xi*^6cs43uDFp&eTml1%|{#qd9E_O
zw|Obddn@foC1b!xjZINiOfPtp1uIuZ`E1(FG{>g-d$q%hDVA3fFCBMYaU#CCW>HAF
zki)7syv|>zJnyjT`1Q<T_Q|U^qrD2huX<p=!cOp6_q4!UGOGWY=SJ@1y(Y4qQ&ImZ
zue<5>#@X@rc52Vu6cP6{pI`Z_@aG*R(JY$n_O|^+(MPM>wanMoB~8xa-zcX#U2QG1
z--WfWyMiBElvEmQzv2JHbH%;90u#51zx(cNx_e*U`_h6#ynkHodZp}|D%bE#+4ovx
zZ`!&aHl3AiQd72>8NF}FQ#smvuJMW4MBT5omFHya{HhfD-MBV5s4Z3KoHOG<^Oq%3
z@s1(WmNd<75?`dg+3L`x2SS32r?~3P`|-UjcG~Gh%}hs%J*%cAPs!2x;+V1NRH>`P
zijrpCb2(?XJ#?PO>%ie$+qx^#SSEV@RE6KmPp;Xttn#oI>*9R<gm-4VJ9rlCTA@Ar
z;`S47?w(NMnzEhiD`QmWTt0z9OP)I8<MVjZ{+>B_K-ZH?heMb}viS__b*s<+x9EOP
z@R)Mes^~<M`yp4kAnrLlQbjM8+|W9HWS>+<mBWnR86R|&zMR*4a*{VtcGic;rv{6g
z1AfSS&Q*P2+CQcJtggQ2c9+!lXKDNAbEqFtXRr0sU2N<)Y2C!#`!9XgZnU~17P-XF
zkwLfZ>aozH*Mxp$Y`f~W(9HOhw1d}8{q;L<cpY@+?l{eJ!lY)QEL+LzOByGp{JA<!
zmi3Wh!qgzGoJ%V|7(P2A{!rBGBjXjJJ36__YMH_pm}2%Y8Y=qQ*l;JlHCU5b$Ydz1
zzc=Lhg{SwXaITC?H12k;X!Sj_NucQQQr26^59Q8<Bqz>3>eVJ;bgJ7=yfHjiXMy{k
za*p!J3+8y#6k6LZe}6xE=Hv@fY@S@dg{Lk$mMd^r@K99ROoi2&S3VhV^Yw4@Ir4h1
zIsd8c#X_llx9@F_-feBgeBu6ut48vhPc7Tj*fFi!s;m7@(_91Bpqv@3OJyGX*%7$l
z@sdQvhW4}PZ!T_T($o0*i1YP1zL}Cr2ZHXfs;13JO*3P5vIy)yE_v}mOzn?`C-WXC
z#27AHE12-3${_uz*aM?ayQ;Qa+pW~WmBxE}wvU=%EWZSM;Et1jt}`6+nfJKomEGR8
zaf^a8PJJjnztL;o65chr=QtMGm~HqicS5WE@lMa(-p$vVGb6R7A_W)>g%~!=9n$!p
zVI9jSsj=>D=&F?&Cg&zy&a@LuTVC;Cs`i<<g(nSo`Yy7x+{j;c(5hMZ;@#D8OAepX
z<83|ir&8*O23vw)JKxfa=>dPUrN!j!te%v5=05D?iurK-mb;(vSxZ;x>mp^g{OgYQ
z=uc`9b&c0uE@1F!AIB0g?tLk*&&Ksg{rHyXFTwr0ctvaRA7gf-?>UdooSX8Z&cCDS
zfbvo+M}NVDBOzUn-kN@t5V`n=-(h*XZEtu$Q(Am+PO!4&q~%j)HoSIMdT~m@B3W{A
z*t^AyV!sb0IOoQeUr6IVeVBPgSgKIs+Sx5;eExz_$4{kBWaF>2_@z+bwbQ9l&f)I=
zUf+I?A1?p5?#MXEBh2T>Ime<%cT2?FU`}I~ob9{|#E#j{>~fG?oOkKe`b!3<-1rPK
z?p3@jw}|p=_%-cGyYTW8OEyh@#^~^{;I8Xr$-0JjjY@8puN(=H<IH4es}|JoeRGBN
z?RuLPYu4Qia=O7DKa0)#+4OA-I>fKuu{xDxc0%W;rdbtJ+$^abX1p@NCtm)#>AX22
z+OTSOsqbnRg$vyh-MlT6{}`*?VU5^ww1KIemv@_r{N(N~+nDbMelEMS<V)v;$H7}d
z%#Jd2ymUEm>se~zt+498Icz%ZvvqvpeTz-@I{cpLxzsBA=y~SqTe*8CEZ;lTQMfch
z&4cS=VV>a>IfvC}SOoSxIxtyAut6tg<)oCEOW${jGE2>|dl9flQB2MIePp_YU`(K*
zwaoU5hXUfRi@mK&D|+%(K5doqu0G|RQ4_W#`>hlUlD6cxc&;Diac9w%&$FgS|L{D=
z=F>gpNR#uOq_dJw{`0*!_%V0!q|e!>CYfxXTRP9PVoprp5nZND4<?s|o!8po@JHrt
za?!=qqekxCm0h9fA+sbcXE}9qH1CnU+?FE$($Q1(`GKnmOvd>)b7t+n_O@l#jC!$#
z$5D~o*4_)vg(Qv?hG_77DgFF9>Uifv*{-^ITebBr9Le1peo*j6(07ju%b<S#_l6
z|HD6~XD3dQ2o7^GH`4s1TynSIO9;oB$1GYis;0b2ebO`MZp4-hpOE8uYd08KG&Y`#
zmo~h#^~00SIg?m*dN0mU>X=yT{>J9Dp3NJ}tFN}GbIY?f|Ip_yNw1t0ELE8*EV@9U
z>}Y5BTvZ=6_IHu2f4UNb{w64YD%|(2!g$8^<BOsv+$rVTZu@HM{xxfUH%KXJ9((3C
zZ(+>N(i<u#3#WN{m1wxMdFoBiu%7w%kd<uj;X7)V92~Fah!xIQ+u}2yM`8M+gPk6n
zCCr~q6XtB$*6b88bDr1?%iZ4>ADek}-M-ETn>p4>OWCIFIIenN_u{I`+=t1Ei~?f(
z6IK^D@4jfZB6i~e*F?1=PE8T@YJri7r{%k)=eqDb;+s4F<%<JL7snlxz9QM+!eG9G
z)3@dIlpCpOX-t)qt}&+^&k#|Fkes{o-Qv}of4yPhWN9@!c<_O%pi8>%&E<+>C+DS3
zH&b=;%9fvPdt#2oe1)!Ksw)_{+$Q^;yU+2-fBz2N%3}5I6*KqhE%iGT+8ojGGA`!!
zk=h!+H<o-;G^COasXLr;nS8+Dgvwv#2d`FH+cn&`RO9(@IPi+C(lw?H?tKqj&dzL;
zt7La!KI7S4+VNsX!-_k)i@5c5Rv8x^(f#;#wPKEnWP;MFeK$@_W^rciFj(e!esahi
z<21w5K3C)yoLusHS4$Z4+hZ?NzJ~;QFe@Fr{-yKN2G)gdRya8&i=SgSYcyZ|M9z=W
zx6Pgl6u0o`Pw(T;nx89gb?RVqm)UyljFmNI4jmKJ(jQ$Z-ZII_XqvQIhT@*xl}<O_
zuqifKo>uT)W!p4EL`-!j<EJARV|7jLT3%XRah?AkqsWsLpSE{oUYs@mq?v`_JR^^$
zos7>!#I!d?EjZI%_tcK(T-=H;o?$B;O+&TL@?20ncSO-|<C=b#`=%RCT1h4pWvWGN
z37q%MnO#(U*@71>%<tYGcC!B<!`Py5d_l<312YfoQ{z4`X%Ew<2M%Yh=ZpU6m#DkZ
zDz;jOt3K-8hRH2QXU?nhZE(D_h{GiC{^Kl$M{;qY1?AckUU=GM$BD2n@%=neaa!)N
zrTv>lP6*8H_j0?UBFOzh%<w#OzS|QfmlymAmpoZEnxzJ}{hju|Gfr9P_?*cJ^TO=3
zy_tBgrW=YfG9DL^Tk$8QaKR>3t*!r7epqv3BBNM@ufUeazba&}hzEu=WMv$D*wga;
zG}Aqv7wdUG1vN-07cO)@sT=UB(`IgI((^5r9me5VANE)%F>hg;VlzkPM(vek1H~r~
zd^jdvTqJG2vw|Vls^Uhj*|7}))hbh8He@BFGS*C5CbVUp&GP1LZzFfjKV`pbw&Zim
z(2IAcs~)iI-)#12;~A^KFIoCkLdCl_C!TXr+il<ys(w^<as%(ZBTozygtkaLmHioQ
z$uj$4=r#kZVhvBLyZY}umRX1xRS7a~bQP14<(fZHJz<5(hLrv?n>f4Zm}gIqUNxJv
z+@rbiK})CfgUKmEiDwSk%4!r?f4#$S%G;c)Li+rIZ&%WtSm(7~jtts;V5KJy=XQ6a
z?v?#t+Z)w0n9|m<J~Lch%kjsy&;O{#5^bg;xzw)6Sx3XvnXa^$J$IU2ns@s1lGE?*
zyh{wODHZLh+%tcHXTbTRCdHYb^+e{+E4X^t|84q4r7lO_w^yBhEP9<}8M{hl@kM^^
z&5Q{~$9JaZFr^j6)^N0LKF%Nz^G*AS$40fHOQyxyf0j9N%ybs&irRSN)-<iFFRmp?
zcKN7wFqyaup5wT1eR7Xvq1o&o5B{udXo!6Dm}A$gIqh0IcVs>JG>uElh%b1Jb90Sx
z#R1pZH!iSGnlihaH^}g4&%Fz;)#m2hPkyJ_J%u;5=4*KM!(B&O1WULApKSWs*!ihT
z&Td^jhr`scb8r4O{m`*~>6UKyMLah&a83Uc#lJb-Uo0dyv~IPCo~BfNLR+U=kEPYj
zKSbS{N9$I@ysPFH*lxL)cb$zBNp-Pp+8wm-FN=WE^)|<|KO<OJn@%R{xH}$f+_bJO
zzi_I8{dAX|B6mE?S`L2hHA+)F8@{>n^gGWj1=%W7Io2>bEeia+Jjrs^s{f8f&iBH(
z_Acd7v|T>Sv8lVfbj>Ln$FBiX_LiM|IY;;No`hd3l5;Yz*ll{7*CD#{TAZHwG@f6V
z9?Mh)7z#J{?OgvRjp^{x|C!822i88zc(hf+KRamN@(*H@9$mHD<(xY=p`q{C7fsES
z4&O|Ha?^;$ZvDL+h9MW$b*6N^IN_DEeD3323;&ybllX9IN2tjxmi!*8vuY3aOj@Me
z`s{*<e1_<nv^>!{{1+EpGR|!&S$Y4d=UY|dFEWP{CwQp;(n)gUV)IQ{`%+wy$H!~A
zs*=5%dRW2i7pwU4Vy=}b8lPC9)ZEdydVTFl4Y#wQ!pF9)iI}AJado4qRxekD>t1t<
zKN$yadS-6sa@?g5;gOTs@`2xa;f5dLmfBuLQ`StCOr0JvIVvshzL@57)uR(m?fP*e
zPU~>M^}`JpO<b-gi0$NA;=jXyx$eSg<!q*n&Koks>PqG%duC1Lth=CZY~Y+|^+@Pr
z<01hUG2RnTJ3~dH_V$&{ndN-A_D$owYiDoGcgqPgY4}~(C(0?<89jHEm%8YZKpw&B
zuigD8ex1^)I&oL)$PwE;>`$fDH`O*xy2iVeQ}xh+-Hw|B)fmG0uJh}xKKZ!1;0({i
zgNhz3Zy%Msd2M%5z@y0MWKGV6?)?W_r7L$y@NE3c#gKb2bB#~&(?y(CuR6<4ueoDq
z*3cPy(({gihxxVu<yo@X3|0#31T!L^&S7?(-J*Q4+H=Wv-8~zPSdVaBy1iJaH#D+J
zU{A%AjD0^B1m<)vaIu-SgfS;T#b_SW=Ys}3xdAZ;&a66e{eq6<B=x;rEN6euw^^8F
z+{k?D+>~FpXM`JBP5vgQA{~<MBrfs0mR+Tya@F1rp@|KAv-#|o`|i!EYZDIoZM51(
zxMQWqax=4IqTjerDmHi?4V*ip_{}l7U<EJrAC(gq1|4>AzUptbwQ|dou7uY)+U1jP
zRM*}L37L{QDb%W^ytAdGWBHDsqO6N2zg1|Gp88=iLu%x<9V_l#+>`TCZQ)&K_d<pb
zr+OEypXZhvu`6)H$sd`0$^P4>2-Y4rli3sL%BGO-{*{}h(`b+4vX?oDOUv2r-ixfO
zPky}X?Gj~Yjp<nh38MSV{7pL7^6XYRy#J(Ta^~iMM(!s9zalnU8XskSc<~jddx`UB
zrJF2Dy>C0xa^_|v{^yy(pth~wzxQ^uYw&f4coo-oZ4VsMeWo5=Q=|XOZPWRHDJ)Na
zI@_M|FaE^$VDX#2^!&6CYqifDKQ0OQCS-i;%~4L7nrXb$Fehwjg<F+&hTsJKi{Eul
zGyivKlKOCc<J`PAH<z+qbDs39q0P_G%UkQd;=%LtI64H|T}xj*J`-_KlcRly+0ILo
zZf{9+ntj2)q~w50V$zp2mo=L|@s<ZT96g+(DkD|9%A3#e<9!o`%E&qy<@crwGY{rJ
z?YTNhjhU_QS%|#-jqP{T&N(xt`>9@AurZwZRs+-0o>jeqx28=#wJS8j^^K@p&*Ihd
z1Cv@GX>toGUsvB9G?V*2OUIP^YS-WKEY8{OHgV-qC6P=A4_Bl6GZx-HYAkDHtSu^(
z*Sgv9mHoDE-#MCkQ=YiJ<tp^+TkyAE>h77h);lw}diiGF=HqxdBhb;TtI%wh#Ld_J
zOC#(e)A;ssNOQcbimOc7Zy}W9K1*G<CbTwoowbnJPLl?O+N55&nSAFAQ>N_w#i$hh
zYhGvX!WG|tZ*Uc!%72^l^klAx&ofFh4?gtn-g!*QWW`IV0;aggC)_){7AN1!6xkrj
zTk<AdP=0aa`RUAG!hcM4t(vhjM&wUPqI%=^16M`71%6$5y5P`D_YZbw1>GGbdxAJ0
zaKv6W{mgX0z(JeO>>$s(=QndEhP~pcUVH7<vaok7GmjfYDRT#{3NT)=zKFxovi70K
zicXOLv6ZIB9t$f@5N6_+zj#A*%E?XA%T*F4YIyN~dK%H<X1MU|Ij&b~n}5}-y?J`m
zw@EZ+_v0rDtT|`x(yANw-Fd>`SY_VXcZk8!vsJ81ZzEUey{tEE$`3unW))ib-w5;c
zXS^H1c3)v@dA+q@409R(J)Z!U;ss0(R`1T_-t6;CXmvp7)uOgXnab~0u`k`*!)N0k
zvQcX?Pb<T;i5FxfbRRjF$Jwo`XckI1a84j(euEU(V&m0}9@hli!h;H)H@6=SpT+fr
zGdHYJ?YQ7QrnqclStoI}W!Ah6ZI5i`C*>Izc)f6c#xU>TGM@nHJAbE`M5=rZxp>2;
zTxe#!kPW{}Yl#1a-I1R!v34GLdezcey2@X*IigL?vfX1{mpNBdK$5qkIP3d63}2Ph
zp2=)`=f~LDc<`dbRE`P4Tzie35?a!9)t2m$OH0g%^Z%mma97>J!erXiRK~_lAt7pc
zx1G;t3Ei;0Th*G<w>~%_<H`I+qtJ6|Vc}c*lzpaMT(Gq5yN0N2$&pno{V7YGnfGWd
z%F&*<MYO5roPRS@@zR?o3Z3_@eRVGCitDfDHUpzGVfVN<RB;;dI&E6EH7;cS3ckyq
z4;H;pRj***w>f;rXS>KoF42j7s|zmctQ0(;c=gkzRpq}`T^uG|aXO)OePhp?rA%&<
z)<ra)Yrdalo$8-{(>`sNfyUDAi)!Z$JJ=tJ>eMx=doAX>Te#R)qQYdVahZGO<R;e%
zb2PfjPBN!8TF<_(b!&b_<7uPaouZCm$4|Lcnn<$o-+Z!H^yJDlC6x<<ozKhE_HKEw
z^4Ma&+Kb;exVDBTet8ydZq=0|xpRM=z$clk>sz`Wc}KKvFgW9st|TG;O2@uHA=z@l
zAER!&(EB^9-|MA)n`^$cWqEtev@6dX|E#{vHB~ZlYp%d&t%Ws~Y>mg4?Bn}=>d3FK
zfUAb>hCFM&`#%UhArm6J_eiB=+qb?;Axu|f^r!7?m^X7;S@y#Msb4Ron2qLNt^DE|
zrpLPYoS7r*?6?O{ESGSZvfSid_@L*?#&cpy=ki3mq`X(J%bH=cskhH&BB#UTQ^pIv
zN$%R5>6atiDstjPr?v4*D`#HAC&kJ?+Kg0YCb;E@Z<=W_<5<8H{fGl0i)ZdUck3XJ
z`lpMoA0@A+^N8^-^?8(0AP}<lVDfsor0}Tts4sub7p_;lQo>*x#@NG?BC0iA$z-m_
zG}barJ{66^0>d-Ce*-wr&b}CM!QAj*M9sD>FJmurdTKO2db_UUi3sccPGgqXRcD@_
zd-H^4&go#8ZABC2XS-?LQa)bDp{eniJ94o@d)1Mw-q5oyqGGp}aD58&XPDH!K}ke~
zY1vG7W3A*P!mPee&ODuNb>ZyKx;rWJnzrwkpDt!A<a6$rx}#c4;h9W@y@xm>H*NXM
zutO<OY{%9=uPcHk?v{S?T_8k}SFJ)l;&Fy(RPn2IpF|3n;#*WK54fI=5#3ey=kssX
zrBbQ|>M@;;(R1{2=0{99?fof+`{0!ucb)B2d90pKirg|`^YkwqDMu@2HD6GBAhqnp
zn-`Ko=3O3l_WtwqnRepuucnC)pBB&SQ7I_8J3le=^1+UiC%wBoHdMW}3)rQ4Pk^Ou
z%}no~vb#j&Od1m=<lJrunwTWZ^F?aQ)|Rt2zTUGhNVfWxWM4?jR?=cw*77QI8%Oa@
zv;U1=Hz)JzxvyYad3uTDt!aDR5AJ#GdE2}o`%bJ7$6u#wI~BIIU$p#k`cLxTp5q$>
zWft=LbtgWXnycG!+2dz=`2^qP7WG#1pQ%iodMHwP`nNsTwJOgmp1o<N7&DF4+^5>n
zsaYrFwDFTD1EmF1;{8)Ae_RbcT<SMx>VuO}w~GIyJ2_`f3W<_D8t!Ohe}A`ZE|b8M
zBM+lEHJFT*WDTu#LkktN4|+ycYfYIg9Q4p2BdX8u^K6dtrJf>D6@3ZC3k5i4&Dndx
zMrbm>=f`>KH^29MQk>~fxy?{3+2NtlT*hfj=Qy|3lo&O&d@7HLC_ZD6!2M<6)GZpl
zMK_cmh7^?7_L@K6wIQOh`|WJb3u#^=iJ6oB>AyHTwXW^i*&`Q?E&C2$pPShA)?q?T
zfLFMt#&=;>jZ;gmh^8<~lzL0C%=Oo5x}w@?lvX+`YfE(1<(Q&lx>8H`T?tgHudKXy
za@)HX^|?tLPBtgIm1>jo6onO8I@KB(UM&ckT|Mnwk=N|LKVE&8mid~j`c(ZbIr$lP
zX+%nCjP0H81_9YSeL3D5wm03n>GY?uN9b&**REX;?oWQ=k~}@MiCgcu)V;Xi%|CrK
z?O%w6e6?0hJzmYU#!biA=T1t1!Osg)>~}9NRnUJDTzq5Bo?5kqj*d1Pwk55;nXaRv
zFzZ79>x}7MQx3LNKYMP{#5BQk<C(a!FVDCWL-tNR<Gbj1TIMD`yS4+h3ojqhKU!rJ
zcs51K)gW}jv)o;W^Mnu1o>Xr;Gidelp3KY3cIoNvV4r5Tu$6nZWbbmH6u#Dj7Ali>
za49Ii(Ac8$YN=*$KhF#Qpx|2(uOvfV-&<C=dxml^yDcOZz3@4!zT+&1otev2KEGIT
zyz}4XQuomB#^o~_joGfsw=FD)?tEf;+)+5SYXg(D=?lh`&3wYSZS@QXCR(VsdrH>p
zyB^Ru@L;MP*U3j4SB8du{iXRwJa=|5ms9+L!evW+-*5H0an+lne$kru>zNL}d>+Z2
zxGq_rx9s!B^n4Ea#tbRbl{51l?!~@cd_nWFKvR^r#N55|$_p7IW0J1k4!`?*yM10?
zsmrdT+g}Sl2xe>Cu{h7P`TIP(9`Ps3nbi2CWUEg8+Ud9MNMu0tBMGJ*nmu8ee?#X_
zk724hZ`!*;q(Z}nV}sEmiGzRCi}nk%H!vl*=wDK24qBzVc9%w!Q;pIt2A`spx4-tj
zd3E^-?}~X5p&C3(!{Qk)$m#s(u;IFP;;vd$f9mC$lACj?-M6WD{M))?PvlA~j_ly8
z=j_^L8BT~>Zdl#)_0n{E?hMX7E|=T3MU?-)v+D8J4AB?!H@xEb#d5AcP`Is}xARck
zyI)86yl!j0_}sf7>eFYI4Q(rz7zQ(%MNOGFwc9(oc<ywzi!YwAJ>L@}@+|Pltp&dq
zZa?P|=c@BoTFj|bO+NSNgUDN1-mijmO71jOXU<$;xT(!^`BdY{OXs_s37J@+xW6><
zTw&Hs-k)L}%O-k!4m@GWJ$pu0L*JTavpwqGv-f?lT5+o-Yud~&VdBO!MV2~bwG{1j
zu>Cb7*I8TSsT0$Y=j<6#chn2k>AZ{55imdRbty$I*_R=zGV_vQDrYIr$1B!nHI!tY
z3ztn6t~9=I+C_HBOy%;7nc|`zg@+Ou)C0oxUSy>TY}#lvL-Oq6TOzZ!YM91UO?=)l
zr^i{NWu?r5*N#hsf3RQQxp{RahqjKp_9M2to)hNj_&PmeHgk+pTb{DWPrT?%O8>UK
zr)Qqu@a&hW`)6a$BF3({Gb$vGo?>R`TbC_6?azS~;_rf8s-|=|g!C=*b@KAr=J`{i
zz}DjErrlNC$EAZGvGb~VzIc)tB<{a@)oYV8>9^+OPHOc{6B3$pf5Hdm8#B-DVlwt!
zU@s-}FL?9f*Z@EA9(zs!-W<!Bo8C+|aevk!z0kr|&)4d|me09h51nQWCbf&_UUc7h
zGu3eY*8VkDLN!`<y^je!TFmNXbosf)m7C(i1-wEVD>I9q?U^%;=`{0o(HB=Ir|b(~
z&1P<Yb>&^TAC`CSd05&<^S7FOxtFt@P3vLg65}s6LhE+ksM+wXyMy&-mHG3?()9Le
zHZPy>iQRfMdyCjJpR(8sh8(-2TQUlkFKcsrzuxn~N~z`utBofmPpx;_)jLHuSK+6k
ztM{~sF9Mwg8>G7Dn7Eqp8s~@^T3tAkczL7kNyb-RG7cMVxU+jGwyb+?+h**(WTT?+
zg!K4|2RT~3hO0DF${6);$uw`Z?p>J2<FS)pX3FcMn!Nq<O5#qa9aj0Y{@&+~EXLhG
z(@)JxP-}nUseDcL%d?By-c89cvAnM7W3<?uf!VV=^fdRROEV>WF9@uu{w<}Q%D1fJ
zMiA$OYu~5jFf5;;)ihzw!#@mh$sCjY4$s+R8JXGaXrr&8Xy#d^_H7-L=p(bj$$t(#
zn-|rg@FroV<XhX#he8Wxo_cbnNp)q_U)4kf4MDqxi!E2uE!AhO>D&_Lu}0w5yp`>F
zhtm~2zfN&0Dm_18XVSHW><@)}e;t@`@>I+I)(N*X8;uh#u4lJ7<hyO2%KmdEExKpl
znM(?@Juuy?x@CG+mi=Zaiv#}iQwv1SNOSnA{ci7?d%L`OS&!9&_eLx1L{B^rT+H&*
z{ad2KXNGFl(rj}Jm-*iPJbJo|TwTO${hAI&ZZc&JkdzmfSlg1L-28}5n^{@huzdOX
zX*x|04|<ty*tyNuQ;bo2!qJ8Ot?8?LJ}IY&zrXw7%GP~dXBRKHJoSt=!-NaZnNu6j
zdx;x;+uWj{J^iyv0@JIq<T<I{8^0+Ol+M=mDk`w|xRO5ai_4QQ78AZPbSG!1`aM~u
zb>sM+?~3m7^0QbXY~8iH#F&13+2pBIyIIoGJNhZtW=jpGODa+Fm9w;RnP<kYVC_A6
zXtuzF*^0vd7A!r^cFp0323wwnjb*=uPt#lHJLQ*8REe+XZ}rO0<+yj?0)w<=?FFV|
zekJce7H(%3@iO6LpP{BLC7pSxT*u{smRirLJcrMRj;s6;jc2{kxyV4kNNkI{jmlN^
zjjxy`eX}oInY{G}*Mb>|QS~hz^SE4kql6wXJgMc`mLT5FU$s)Ix905esjY=qk~i;N
z8!m5Lc5cGXjNeakrbhnV$TEGC<fl_FU-azcGgy(r!!wgP{eSTKM=ySQM2pN^edO3$
zwhvo!=51LTc|_&G|8%$d5?j710Z+cdStohePCRpwYg+YypJCO)%#+^>_Q|hMxEaK;
ziRWGSiKMj$o1c1J-e8e7wPnHI3mj!zrH}eed=)A-CDY}kd4EX%k@Amcc+417MHib(
z>SzRg^Lrz;_~@&3mI`uKu8!~B3kpA|nO#afF#qjzhw}2<Z+G$78RqmZt~b$qZt<i=
z)2G<kz<QC@`9R~=Mdl$-?%qF|H}^`q$%W4=CU1E#p&{k6!m`=v+5u@P4YnQkjz(H+
zop5*}?_>{`gDKp1-7Mb8Eb#bqHb?5U<>A?}Rf_x5-%ePd_@T<$>qSV29MfWZixrd1
zo@>Z6zc?TAkK?EsBSTb}LC!o)*_sa)6MrkPx~X;t^Z#&u?z*Ae{Mnt0&Z|DNFiy<z
zTey&KXBB_Ew$MAJJxq;Em)%V_|4u6qv}iK@dssom%Xjs{pLM+~Td!vYY)j3Rzr*L!
z{AHdjcX#W~KV0uVlpa;T!B8<v**nug=!EHeSLU`$zkR$IFFdJQ#H7AUV3pyf&!Mf_
zXFk8^JTaB?Z&%iQWzP%WkLzUbc(84D;8%u(9JMw^^{;Olk2aPp6+E!v8vBerKVm0M
z@^@JNM1e)yR`}OdS0|f`hc0qBC~A7MF%;UIl9D*HVE5(=f%#Xj%ifmuC{I3kM}|kR
zl5e6$!Nj(`hhpklTY9Hg9cX@9tP+0cjI@wuU0c8ewJ6>{kxLe7EJ@h>b{EH-)N0B1
zDrs+Yx*5DqB&Evj-xbB;ljOftCd}=1%WM(HPa#eJmn0obyV4;1UB)#ri_PZYtZ5Fx
zUK37<v(8eHE!uVTtAxyhsYO9ur<}~*Iock6sv4W7yC`$((Ulf6Grrcv{}KJv78C6l
zCFB&M@$y7MBHR8j5$3zb!NMl1gkt8qcPIQkwUD=UhTogH=Po~*b!G44QcgiBwZip`
zPmGRBo=euTaZderuWrI0*0;}uja_|@7<b%RX^{GH;)9)?Q_2@C`+Dv;XOO_DLn|D4
z1ZVI}3rfEFQOlNRn^%SA5&j#}?f-(xES*nYa$o!@Zt~();_v29I3m7UTKRcpi1@{Z
z2TESM6sL3eMJ#)#ZNtN)z?~Sq?NRZrpL@O;$E^C{>zt&mupq*xT_o#_!y4C`$Y;;B
z?=asDU1O1A?|aYa**As77N7KmV~a%Y+MK+->WYeE)AQY;7K>yQy2Uu$raA|m=)aS?
zK7;?w3`d`v#<~1UdX@J%8o!J_&X5#x&-uYt+r!$7?^dpindu(5%y;wL*7!>yS2$Y)
z7PR`^-lHP#Qgxr#>2=$I$cLV7irHs+&a7+r<+t|L1jZ!?8;iGCJ~$H_ZaVQ%liwzG
z#WfqkXRbdU^<Xp8<2#Gn6}i7(3NT!J<fjhb=cjC4zK7W}odsT7Z+R=fDzZP)w7?`x
zZ>Qbzc_)8yo?Xb-)Yg5boB97;UB8@Mhx(<ztl6%&e*I?u$*$4p=w2O;td+8yDMcn7
zU8xc}K3ACS{YorjG?y)vs$43~rT;Fh!6Q1Mq~!G>g-eer)_QJNx8APL+qW<_XS?Q6
zFXtmcMGouqABcti<ea8vYhAMGOcC$Z_>_eVJHN!(bmSd0>9#79s@Sh%w<_r5>45gh
zjw!x(9+-$V-b^?0XzVza&+V}7U5Mx=E1A+ICPy6<JPw6i<4ClhxB0`IXYxFTITMz0
zbhn<YRPe0mdeG-n!nrbu;ld{M;y3+ji7dJTIYFTc=O;b?eKcc5VU%o<WAla8lMkMH
zV$;!Xk(D#|ODN0R4Ksz4*WH`jG|eSZu{c?gx8l>hnM;o)Xy|_JZOrVN$)V>IIj8#B
zvxBTY@7Bc?igfhMRF<9_aQNa|;nztDu_C33=fynVAN+o2GjBy@!8U>3g<hOjw&{p1
zd)BC#QtcVG-LY(?8b4EY(KF}MjT1lm{Ib1YDADONHDt2F+fbdpdp@2j=W2V8vfa|j
zGw6RZnZZy*+T)c=N4unq<O6@<hes9kzU)21WW@E`<n~{Uz?%W37hH3*N*O;b&)VsE
zMb)2U_KxI+!agU?ZLwZ1o9B1@Tj6=<@&O-SmCJfd*1H7U37*cez~Gme@RFUWMz@p?
zNSpjR(P+hE-TKDN=it9ryG3{L?iG~NFj;iq;?c*RtJ!9V>YfYP?8fI-_mQQ`c-Jin
z>%@&l`u$-Bn>Jk4;_{uKyu-28aNYOgjt_aZwA7|fYdp9_weCw@+qBuY<ej;<I?RtW
z3qHSR53jnAZbQM6E>q=n$)!0OdouHSJNRlHnOt@kZZVsBvOz)Uv#o^bs*EWM0!7TY
zg+HHIxha$*#LUj*Smu2-Rl$pjdb5+~TQUoO6!K8Ioc->gq*PCl82h<RoqN5_wAEEN
zUCH_V>g9aZcB_*q2hLxJG&!B2ypTPQl|6UTF889ZD%)=c*iSzj$#hn7F1y^8Cig{`
zRy<Msv&r9R)kb!OhHFe$y8aYZY&>%LRxL-X+S*QMW^vtIE7vVKV#{9SZZn&7$MJO6
zqem9ak&8XNpYlBSb<5TGHFJ^Iqhi)Y4odp|QU=Yu4<%eHg|ZiPYyQ-jCH#B4`}Oaw
zfgk3Fo}Id^iaBBJ<TgFezJqZO<2G5&TxidGD<Ssos&}d{3Rt3<W-X}|IXg4gI&S(m
z;Z~+EOG5iu=WrT(e4c#e2ImFN{o6d;jAfasQmmdiZBi1@+sLAM)M&B&^lxcd7K(qP
zH;L_SoX5S5(dnc@|5LVytQA%%oKj5Fo7e=VJXkujS0sAI8lQ{J5&KRq`}O0u$g{H<
zj~dP^TnO0ja{id=j^1}^PZM7-Gm2bEx{+=g+-7u4%jApCrREcxPp!CRljA9~;%4VY
z$AXH!g!*q;wmC|VAFPwT$hi0Qy4{YuuXwUuEYoRj)%+znY00k1i?0b8A7+tF;`zpy
zAR2o7>=|wD5dFE=<GAg2ofZ*jNDna6-O{Ie!b$Yr+01jhHZ|Xv(%_lodc240Mfc~t
zSE){>cb9*dawofiZHb46l63NEWy3c&oR>v3xg82zn7o4VivHCDvk$O|)lP6*-umg;
znm^1>LbN=&7qc=Lyj!JKJi+3`qdQ5ApQirFC_5v6eZJv|y<Ta)OggGQE{-oIE|hIL
z<Myb?|Gnit6^S#GcB#5e(9Ae-En!o`5y?wmZoY1dx%J%4d&veqE|&>5<&%{idcGtr
zT|B)(=ELc%%f&*PQx=^3yCBN^6Q5&Qqfc2`w}926lQKoq*Q%=sTG%_K8N3KCxxP7@
zP2t_EhBKTpji0utJ(Y9c(8D5{@Gkl5%6B~JIzQh0IQ~uRqRg4ZV^cyO{1g0Tmb08k
zOtvGuQs{otrG=TI0r~m`g;JXxp0=Jm$;)(LiCj|YyC*shvNG&t$$blpuPJ?gY-_tO
zbat?*?n>2G<HoQRN$Z?$s+(I{R+$`*p0zW#@379j$qP5O<hiv5N=6G`E^00@>zS25
zsrL4lxHu_R$q6S+E-Gm)cJ5>CIB=(iTYt~*s-{;>sdILw7ObA+eK5wlFv~&odT!Id
zBe_i*L;o;%>YePEweDG3w&k@2CwFrhhjd!DIj}v@XVf~}8N{;8fqlXb0r&Tb2h7@o
zCf?rSX{fQD?UHEhvz6B?7l{X%-3*&in7-rPO)23kT@D?_K_`;Ftj>r_+&uUD*P`ON
z?K3S;I?fG#aq;}FUAkf4ck*rI*m@|CWuqCJx@&Cuw%`f75A5l`b!Cx^Q}v34m1kuQ
zo2_Sxb?V)o&YtQs;j{1rcA=n+Jf_Q~PVbxJlXE$5V?clFL|HEu7yBD8SE`C{bn$;1
z$x=6OE@MFVThj}hlvZZ;Z87t>pR715_McAj+;_stXLY#Lxr2TOuJl}%>)3s=li@G>
z{`<BrOSBT}9g~@VmY)siC~psZq<S}FW{t$cHAjqP8*`r~&Fwhp_HBl;fSxhCt)3oZ
za)ZZ?cq6Bz;9i%7iChyFFJSd>I2vWLn=5Y_$9F5`^sm=={+=-tN#CCQKQG=}-|WV|
z3HNzU3D>QQlY8jk<P;R5R4n*=)%t&1x)xo26Q-!}G%WZ`x1yQ&hMSwd8@c;Wez%}q
zvG<m(#?)}rWvXkxvOcK4b!02&>=pYCsfn3>TjDNmeCw~pq_&M0Tyq1st{+(QM$=4O
zT)9v2^%+?)P2*UBAG}t<TLfA{{q@qi5_VtJ<T#nTr*oR%JC(K9E<BS-%d~7fyRqU&
z@1wFak0Sm0YVS@cbbsgL9pomzCYn{XJ-St<_0jPY?2c<2#3j65EV7)}`Jr*k`v-l2
zjB_`K>1=%7=U{wEO~UW+vcrFk43c6dy~!>vm6$Lgl~r-$+_G()_l_*%e|D?2eRjab
zf{pAY#vNVh0vo?txcsbiFw@MjVzIZ*6%Af`(lqBUlV6T@9`lT%J6h8u)`dS%{POwD
z#a$M`?-F$!j~ZvxE%@)Xf^$jkR*k1`PO;3qX7jRlSp*;R7Ny@yG#9xzh39WsUa_OY
zzj$fMB7Vo-3sVlW7PGyr`Z>MKJ@BhTaq*{vPa-(BbL-{)W1SIjmzPD+R{zt6Cmnvl
z6NBU*ygIpAyK;UN$4U{uaGzZ|yNe|c=@snRkp27ofw(^k6ArV82S3&ju)6Wv`PW(l
zhZZk&SIN%}4h_Heti5G*dzmk@*6ikK%Y4G#@<ePmQ8l_^W5N`<knOnWar*<tzfLP2
zPi6aXMK(8wF|ka@dHGK{-vhiHQ;yzpx%Rt9^RUK^Z@XWp$+Cz1y}Rz_hxI*)YK?N7
zx6;L)3r|>SGP6iWXv*61$rldrO_tk}Ua}>Klhx(quJvX<9l@K07oN9iR(1VkAL{f)
z?EJYL9<RmPMmuhLUKjGra6MSo?EKAy`RtQ4&jZgVl`IN$m*<@+{M_q?Y|0AJi^{)`
zzK)(Swe+AzOv$BV36oy_npJx@ESfWo^;9!=O<IM!%Dh*Tiv=%Sf5qzZl|}n)-$a?L
z7lISGezfd7F#9t5dafxdr86%&`kglWlpQf|62HcQeJWG0D4$#s7_l_<y2A2<6K$#w
zw3#<Wx6V_alX0={nxROWuAA6gdj@l@R|_(o<|WA4a!wB95({JddrV2_;MH|UqHY$c
zT-H6ZV&d6Hf7xE8r@hW})Sjm?p>1cEh}@eZle?2{q#IXd)RZjTU&)iu@MzD*z9qbD
z^Y)x9kegA=^P#F==)(%VkCT2S?C08Ey~gx-uUmE4jjygI%r3IOq8IpF*_AlYpmSa$
z>y^3d-f%N#maTC0cd&JN8{x86;L23@zHgpY#}_=5NRhmMP4{*xM-{`@1r0J&{z+?0
zNEPo@mb33mQfb;8DSBC9@q(Ww+8*+r@}8TWy%NQW>J47sQT7S<y*w#?&R0tpsT|uG
zxvU?*gh|QVeqN?NXHNYl<Jm<C>L)vTE~NEb&OLo4xU|Fh+dP?@tQ)5<J7jUbDcS7V
z|MUWDFPB1&dp0VmfAlXZ-^tj@Uze@1@A%OZN<Q1G`8hLZv>s`RV5-W!lg#tt$t2Bv
ze$SSksd^f8r`f1B&D^BRZIyQ4-j16S)(ZR)JNqf|+U6`ti^ob=Bv<U{{^qN7+$>-2
z(LRQzcGg%0HkF3ETjFA#-&<8UMYkh(i(!A{^4S6mC)Yimy*b(8>U#d^VZQ^HHm$1^
zJtZBrVWtXC(9?yBjF%SeVDdQhdG52g6KvheE}BPEcD@PfvsJEEno`fEGx4Lr2ljVQ
zz9ju=Y!PF0QLSLQc<5YU^1C|Or&%gbJ9NV4?7TJes@bust8;$ZFt;uCQ(kjjivJ|*
zO52e0yG}{QT{{$g@k;Cc#kDie1(&^RTYOJt$&%pJg`I}6hgW=8O<$mSC8nWoVya$i
zF8709&;J~({i0QBpQU~D))B_3f?Ste*(>JBUu3v6@v79VxEEhPMo4XPaP0_*wLX*A
z-r6v`>0)N_TCE6HwuqB|JiGWS=RM6>$T}ra>qErmHPh<4OtaEhOc;Vyp1fVqx6M)a
zq`=x#`|ndu@+7}omLjHeL-K}C=IN^Qj4XaeeC`=0>N8pR!qg6Gam*HWiJ74_C+%s!
z*3aY1EFVQJ;b&PJ^DRrMCDku@kNt~JPp0*#tiE)iW6~D0srP2e8BO|M{DJjL=turJ
z?AvF$J574<M1YZHtIfjT%|Ak>#qF$2-rQoJcBMVD<iw-=B9D3PmmC&y?T9UUadnE~
zYVV_!F?~gsCfSNg*8Q|7P3wu9){r)R`Q)3HGS>uce<fZkE!`}<KW!qL2xIle5S3C{
zO+OZ8>4T96W_(~0FIaD|c$R8=#}nS^Tq>`x#+f=@j7j@jD=FxZ@Nsz}kB#DrmOHO*
zT(&NsrM+rXPuDM@3)h|~NrilHp6slD?S!I}!V~2z3D)a&Ys6mkttnpDp~NYxqbxm7
zq|$d?{l<cf;GnwFj#<`RNAHwfEHd%TTi_<F>!7N-rixMfzLRM6d1<HWxV=A4XzA{W
zU1wO~#Mf0|{bgsd1#f6-L4jVe{HkY4ofW&?S^PF{T~RTEQSAFimXkrIQBy@+Ub@Qm
z1`EAc_SjORr8rZXt6P}eBIL=A=ZjdU6|b<GyQ9ZXRfT=?dz+tP;_{*P0o<h>OBOb_
zX<lS)T5@}Oui}b-f}cJpDOKN2dN}pdn(q%XV`nY0n7vnwe|2#8yI)q{6i?f2Tq*iP
zS4~Xz`}_T`X0zmG`)G%EPyQ^dP|97!ChFyWfFpIw7ag;n+_3xr?zn9+tsXN4)_3j7
zSIB<(WYMfGRxh+?t~I=oGF7|HWL3h68@H1)Kl$vIY)!v*Wz%+@^{glT*Jdqp=a~BB
zz{+gtqEEZ_<xU9D6q#kxI%(%6#goBVYkX6aP9EHtndOt?nft&YWAprbVWnyRgOy{m
zn3oEQcb=TO_K$w`MaDjk(#q)KYfGGsLp5rrFHAqnm~1QM`};-c2_;{)>0H+t6Utf-
z3t6x}IwAESp*37jGssWWhI`g}jeTvQ`&V!EIlb?pNt@k!jUtEi=*N$YCrk5+bRGQ0
z&}8}d=^p-ut|x_}4g#kdHyZH@zvlDUx_W=9N6{ytGPR(MPQ8t{CwheBCcmHj;>5xI
zNB8qARVa};zS5~MAnm#3v}GI9pEAB$XJq}&^-)BNuEo*=2No=DSl+m(X~zFu{I+|8
z9%vpZ>)m+Jk;m6NuXJm<Sm7+$h?*6X)9?08l56nJ>A%KOB+U0<P3i7bwF^QvixanV
z-A#-R5e^R%4&an6&`NYv%v{-Sweep=gxlejZLgy3cSY@<Eo;1yS9OPE+M9w)k?%s;
z+!#~1n8Z6Z!&m$%JeS0F>{ZB2->uo|8<QuP`%h$2+<9Qa(vuUkRg}cn?G{+IYOlnF
z#<_f4mlu_ARi&9OD7c+mxQf|Z;KlTb7gtW;U-;fJ^WEt~EX%kityaFYfUjCe)iA+-
zPGoTWk*hpqZxmIIcS#u^2$gspJU60s#s;6uIjJkRvo~LJapQ{Ky>y|;*DK8B*P`^)
zQ=jFrJu>Dzx83H;BF}RZH@J0(ycQNM`K;>~uD!YUgHgkdEyov}b8=v-IJdM<E{Su-
z)+MEm_T2f~)+*21!mu#Q;i=f0HU*mxjHZdA9Gf$j$(gG0mS3@S;k>~5YSXP3*^}yL
zKW$ZBb1j_lLi6L3W$%`}WS%(L!2090zR6AzZ|*s<Epa&(vgG5AEuj<U1&Ua*USR6U
z)~T4fhh?W|r<!8-di$e%3X9i1m*e&;+-NZ)|Mk?^=O+|*$H?8X+puQ&mNK~{re$%g
z>pfS^JaC9j+|;EYqx40#PQVe<w3fQa*dM`4r7O*!|4{G?$cafev->XeW!i@gs}(-)
z<NKZTVDFxHT~D^1yIM0TV*afoUM#zmw&-}RIMpp;^6E^%nTI`bzg@Qlh)l`&zL?*#
zrJgf0rgO8!hj6#sBI4~P43axpwjR3CW%bqN+PQ-t9&${(cbiXZYX8GCA-VsPh5r{!
zy|VWB=1X3Z7w5QdPBz%}c=jf#iyOjE=~%yZ_~w$7eEaZRL2iixt&4{bK2u`+SYV`k
zc)GBK?!n51-uJFsgmeE&E_Gsg;--7$l2PN{Qybfgg^zQe_{fo;GKJk?b<vk(p_d;G
zJo)!*zgwP=y1*)tC-;`$qN$uli|nRIePp?#=CO<?LHy;7In&rDCn`+jeYd!z>R^&c
zxVec)z^X}3qIJtxcA1n&$VRj<%njIZbIHbyFVB`rRzE+iyQEf2$Aej4f#HCK`9@#H
ziubQI%EDXu?=4#RRN%>i#L^_eL!sZVUEh7b@A%C3HqFQWM9csDq3mBT_1|J=VO90_
zYw7*-t+wv`8uMq*(=#id+to{F<d}#rWM*HV+gQOD$MoOUjPw6oUUm(aTc<8Oyju85
z?63HH6aAVwckf#7+Z<7{JNo$foIPiL`{m5H+gzRW`Si!B`{o?K_*terH{W*m&pS8g
zKCYg9J9@jW37eR^xPM;WO}Bq9j;-u{yj%MD@6)fZy}whDSIqss?%A7XD<^lK&v|FN
z-(vITzp~Qm-^9%Cm);KczxV%wja})RcgO9%{W#ojvovsezNi1s9o1gj9zEApFF$|h
z&%dJ|_Z~g>?b|)w>uc{9Cgp#=EZr^4zW-rTarpf=clEdYn%7$U_wL(Z>2B+Db1b)3
zHsx1-H~!Y^ulFWiyz+VVy6F9Re+BCvmcP~ewr#urTfM&bId{tL{<<0-Ut4_Aeg4fm
z(RWH;$G)$g|M%xh<Jrs2%EZp+z1NA#m#;MT|8X<;`25?kcWPc=`?m7!^KIhW?S341
zbWQ#AqifasD+^yAt}J~0w|jQ}&ZnBc|3ACd8JzB)cW2LzuQwj0?KV;UJfB~7_wRH0
zyQcrI`?aoJzUs|G_IKAdv%lZ-+VJ;t+w{C^wKwK3R-d<B+%D1V-Oadt9oy&GJioc|
z=vs9#^Uo!Z+TP{OziYX1qs>C+<%L-n_cy$Kdu{UX`#$mo&(D2JFMG=+W4*6jW_rcP
z2Os_SK6(GxDCd67=})IYG4)fi+_vVtZ8y8wcDvGt-aqfG++3}CzbNbT%%k6C_O5;I
z_p<Zv$!l&lmf81R{@1*Fvh3g2nP=DDH7*nX+v)pg^746?wU7JP{rWMp;`Y1G(#sze
z=XkvN|N6(J4>vc@R{wc>^7%O(<~Qv9=Ufzy_Wt|)Q%m`IyUo9E-rd`KdHdW89=or;
z`*H5r%igtnA1}|ly=nU#%b#a*+4Z_@w^o<@`qBB^e7jlR?)^8`Rlojrb8mD0%?ifH
zN8ik`-1q%Yu9U~OlK(}wCT**&DpXf{uroX`|A)f6&)=ria_-)E-2Ts`?=jo!uAgf=
z%QpMyx4Y+c=4~}BO!#D1_r1B_=Ie{({u#>G?tl8x-2dYJTaoW?l*`5CWA3i;-Vu3y
z?fp+vmOTw#-k+a$chlc9<#Rsoemhxu`G?c|@;hY9JpJVFTkYI%ew%gD|Gy$SI(hXo
ztBdbirHSo3t-JlfwMX^r`{u5F^*1RwJ-zz*-QDji_y7HEe7t-^-R;e<>#D14RzH4F
z$oT*K|LW7<X71H*>z)4f|D>Z4wfn#P_c}S(_|ucA|Gz)A`1dQm`tABZ6X(}{wzv56
zo4<T|>HmM`>))-j`LNs6_Ro%eo3Gb@Hvf43N9SYn@Z;fEKfZsnal`MjnYMb{kBfdg
zU|T=ccHO4qSHB&wE9iaqx%AuTtKTYk+a10~Ro_YIzkc)a*KZZg_sS>#tyye)FQwo7
z_T$%YK8jWExhfZ*-@pB3?f2W~XTSZ(`>mqgcHc$0_gjwde)BP}de3pW_gAa$=iB$+
zdMs9bCyRd#|4F%<a!2Kw?}fj8p3<Mze^YMz&Bx5&ek`!Hdy+i+{qDPU_Y(W9-xf}{
z?YsFnuli1MfA!nK`S;q7AAfV7|Hfm-YMYe)_O~B9Z0+*;-QRwkaqqY9x6ho_HktkT
z+m5Th`RG|)(``F%)A8-EYW;7Y&)<H$u-YcMU-+9vCclp3`CE@I_wsX}E5GqL_?ty)
z|K)EtHXYw)d+x?#>#zIHf3LV=m%01)Yq7Ft(cg-f|IYdD)hC^M<VbpK;l%I%4wdTv
zyLD{+zel$YetqP*d0%q+_U!cHJL?X$)lNSCrdnqE@zc7;3w3rWXG^S>*uB5<L2>*$
zi>Cj3=KbGyc};%#e8b<;-`0oM#pHi8EMHg2`fa^!!vDP8uV<I7yFGt;>6xR-+2N(X
zU%y-W=WH+goAo#U9{yfGwdT;r&s`TcYR7D?PAleK_qgO^f5&#c|AO*GPv3pKoPK8U
z{+9j^=C9oU?CjlWZntG`Yd}iz>o*_M&vfqp-6|}dE^zbsyVTXE_4mB{x7J_Yersh>
zVb0}8y?4(xum8Vb@4q(dva-JVvcl)zZmylY`=6k+y1Cym>$(&73Lo1p-`4+Lw=Xv*
z_x&8Zx~z{MX7<W{KJ!@DJ}19&@4ZbwU!I*T-JNc?`^S@G=gRgxbpLk0;QzH_+{gXj
zDDv1>XX)Sju=rcs>_@zRHsw8j5dPP&`uysj^V;qAZv6aa<=gW|yzTS!_fFHd-B$kR
z$a1lA+x>-)f<L}`zd1bqaQObr*H3oV|NLE8_B~qXyUe3spX+|k->^MKKHoCur~1e5
z{cmo_&)am}|JL^VcW+x(KYH-}U-^%Ff1=v|SH)~jeRPAFUq|lNz34m5ujSX@$y~pO
zbN!wDsoziQohUclT716HcuURo&bycQ7hP_itzNdReEa;n(F(qwCkZw%zdkzEU+%v3
z$C|GCCqLXf>u<DuTK#Qb{p0$r8;jG@FB{85AAh?izI=J@-_7Y_9LMGET5QaH{_&=^
zUB&mq{dGUCo>zKR`~T6)^FQqM?*BbE*LGjggZbgMdv|Yam+1HZdb;{e$h;eOe(=nX
zE4ov^al?P1MgP8rp83DD|L1w(PxH+m{cmFW$Ncf%F4^f~uh*}CcR;*`Jt)4EeTMs0
z+X8F#b8{k}FMk}*{_X<vcl$3JS&QD3ZQEns%`W#V!b|t=HjBcV?9*Y6XO<s*c5UY7
z>RD5Fb(pWe|Mva%^~I0Y)L;Km_I&5ZmrmyYF2(j<-Dnkd{8fbP>g3WtW|no|*w_C$
ze7)>^dG+?3`lb6%fn*+^u8G+efAOGw*w6i;|MI8)kAC_;?C1XV+umH(`u~0EKIYYb
z?t|1Nm#*o%y3uN%R$u79{L(dj>+e2Z^={L<gY0%(8LzeeZ$I_FboHP6U`DNI+I)}^
zUt}Ym{)gGWrtj*<(84vJ>Q^V1*1VN_{(67irrU3}?V5Z~ymsT`XYWo(Sun+U{{MLU
zqx@I-`}b{=`j_ucKl@Abx4h1Np;bH0XVrcwUSB%>Uj5&FpKshZ{k{CH)SO*Q)_wl_
z_}IG>mUG0Xe=>hu`F8%t;`>#t;SbK1{ab(KpF7`;{cCn7-TYnqHFkO5`*-i2&tKR7
z=FKCPxEnWYXRO|Jpj-UM*M(=U-JW;n-p?!VW<FLo6MO%u<lXMP=qV36H?NrTewW^i
z=K|l}#r-Is{w*{7?*6ZDzWoc|@$km6<>r2oIeRx(q@@3Ta#Of^_iO*0ck{Ly{8{&X
z@B6jC{~tMh{;iCCZB_E~*xlXL=kw;>*>N%Q-5(wMjkRU!_dYI5z4X9h(z@!|>SFvk
zcAJZ9o^M`nwQXa0&F3rc+HI`2SL7t~=Wq7EeZ$GC{PB}VC!gz{*v=pQBR%Ja`kpV+
zdwyQr9PKWD-)66%{O*d9$2WWD_O2C{&foj^%FO5e_L~`Jf1h*rQ_kyutFPbLd!xE8
z{r8*V^ZM^1t9{;-^2^+>diUnzb2FRfm-|2P-@S9Ac5m&^wUdvR^Zom^IlNwg$6~oz
z+>Z~u?E7ve&#Sw?_u0l|`R@AtZ2#+iH12-<(^}55wC4TIw{tJQkH4Y)zP$MO8{OmE
z{O5et;otXq>qoUc&vU)aEcbjr*n9Wx<MR(!*=^hS`Q=$*>D}*do_}xm?IZi2>(bWG
z?=3sNeY<~cR`GjXf4h1alREy~nzW5OOF!KGI_=}!ewq6>H#csIkf{*=@%)`dWmR!@
zaryaoXTF_#*ZX7j?(N^ge%=rL_kDZ8x5BCa|9ahT4E<LQNuA)t7B6~S>;G=6u;bU?
zee8@+diP}+_X?YsV!l(KSH08ARE~M^SNzxB=Na)Wu76(F?@RLi|I0j_Md>|n`~Ocj
zjv1%V-~Ho$Y~|J0^3`w7xxdv}_wrrUpC9LnrK`V3+f**pFG>t%w|lc`vUJ(D_3z(V
zZA(0O{bcW2;rV;BZ!-mTGnRjuroFD}@5X++%9HsvKkg%CsnCD#w_nARB_{sgJ+b#n
z`{vZw?7vrk-&`+V@tw7<cHx=3ule`Z&ir8g<Jpfz;vS!44?Jny|6@;32`sy<{Zt=s
zdvkf{zxUd;>|sCmBW3!UP#H+}jo<D5<o~@LZ*JR8@!b6_rt8>WnFp-@A2sR6Xz*7&
z_Wt)^&&&he4FB{pzNPxe{Mezd`vhJRfPL`$Z8aXFKk(P>JO1nW!TKM8f875xmzOTz
z_4w|(zwbNqHs5|>_xaRM_4ti{kMrNKPcxhU@?6>ZoBz#r&Gr8Ixwuc-j{o=lvcA7>
z-?iMd&%L&Nm+fx8^=~R_%Tss_?@YbB^mDvj{eikC_4?799BxfEJ^A4QuXp79!}FP<
zSO0mh^?&!N|LZ>OU;XEOxXte!r~cP1eSZKF^{^6aeOL0-|FN>GA7_7$c)jk0-s=fx
zKbPE!U0(Lyvh>r&;M?bAJlM;!_2oP`*6pqE^D2N9e_&5XKmEUN8_2}%@KSV5AK1ib
zh>73d$oHAwdfb)w_S@=-XK&rKEB&JPN6d5k>Nnf3AI*Qi<-m*JkEbTCtNzG);@X?q
zZ)c7@I(YW(<K<@aZ#%u&wyZqnV(I>Zzq0CnId9(S&AV~O?&-~W6(7B-KkoXyU94Y$
z_vt~OJw=oE7JYTT-OX<9m;b)TtnPQ%@3*ht*_UQLw&b4n?*1)Ez4*L#@!o&O+P7_=
zFzv=2tLi_J-P7LHJv?%3W^;bk^7<3kmcLy+FGl9}9ox-&cUOM+D!=9W{et7?&V4+u
z_wJ6}?$V;`_DPSQ96MQYod2eE-k#@IzJ1(#bYt(@w{tIl%aya+yfHa3Y0uO4x4P@E
zN1NI2tt?9ZcqUzZ{+$~)`^^8G_$U4D{;i6KKRWjwT`avj-CtM#PX8_Gye{((r+4)>
z$A3Nk#&-R)YPo-3j-A`Qe4D+n{@)#YzeMf(a^v1d;rUT_zWzDZ>3?+f{_}CQyzzgR
zt)2Y*-_!TUZ{FR%b^FIV$Ih|t`{Vy$*|BK8=zpGn{wiC4YcHE`<~Q%X-CygP{JOP=
z>uuNFoM7?o0CRV{&ZoWX*X`qWUXH62j@wy(`rY){3GY8;Z`|>Ghh)^g*GJyHjNh4Q
zZ{H#F)Z2}r@3i5cc{cmXAN>^hf8t}m(0_?t@50~K{y+9V3!Dh*xYG$%V&PSJ%*FL!
z<*?fG_o_2?pbYuadc&#zYe6+8xJ+98c=aPlW%%Qkt<E%yS$Ue<?LK{UpZCw?Ut!VX
zFW>b3b03|q-`0DtFN*#5%-{QZD&{TQ_~ZS@pp!daFJJgAd2U<Ef4^ke<#`wD4SV9>
zSnS?iUX#A@McMYg`8O+OeqZ>z^!t%#(;sWsTK4Bhyiq^hms?Zyc#7+6>+a*<&ds}X
zC(h$#dgGQUM<?*h+VB0iaCU9Rog9C8%eqIw9(U~i%v{?$m%p~)$A{9_`oA-OpFKBk
z@hAV<|BvLJ_<tAk&w2AkX}0;jOW%LY`M$5b@Xf=c&iwZKcKp8axBvF#*VjJ2KK{Pq
z%e~|FA5Yxvo_+J^-*@6swdWt{E#-S>QT*)6Gfsc*dwX8QzX*>1kY0Yb_<j4I==rz*
z)ZYDdTYk^)jmO{Z`2Ozb<Ma9N^xpjE*xs){BiFX}Pq1{y_WVejeS0g8?f)ouugp#S
z=^H(#ckOa}9w(RY|9`-J?%lf^zAL`3NvlrJ|G2;|b*B4)<mYd$HSV|g;QxQi(Y5FG
zDyHUdd|&Wc_j$c`)lq+$`%!P^-L%;F^G*8O?D;qDRh50-x!Ffh->$i>$au@vKhxO%
z{g`=P&+pdtPuD-B`pa+My=}wmEgSY9(dSFE%{yotm9yu;+dJE1e~BM|p1EUA^}~F-
z|LHcH_U_)@IpuHX^X(U(z1@4``MfJ1=W^FJI+snkxU=$O-j|8<k7UM{9NF{yko@uW
ze}C3Vw7;7xeLgqu=#)eHa+O~mx{LMCwfJaK*S>S>j-Stp>;513*7<n3oaMgnd-fMx
zSMINQaYS=T@w({xFB^B;Z7FX0Z|3~{{^p1~fBMRAf2})zwwu59g_C&m{loVE&RNUt
zuKwt|TiV~g;(ToPzoq-X3D;Gf<S6)|%Rm3Fb#dAIm&voOyJvs5|NFo?K=y{^-om2G
zYJX1e?f=7DbNrvT{@*nH|4ZY({f;>lUU_o+j>k6)>+E;G`hD^g$|!}QH1l`+kWXj-
zop0~ETl?Jn?&*5_+Utk;ZNGhBE`NQqx%}SO8Gk<ue=Gkk6Md&j$?l)`_mlsQ=62}h
z*`}_3aN&G+w7;Ic#=Vk<*WcH?SvSf4%b9naYZ_#d+3l{!_v-Jfd3q;aX=SFo;L8)m
z|K_d#du<i>o*1)V35zWKo~-^YlXGy#@5bZr_MKQHsQvZ%-jpTW`jQ`S>hDjO^FB8I
zMA5`^yJKWF6<u8a(Q8`Q<vCa8-`Ubx`{~1xx?kNJQ))Kq&Z&P{@k`13_~q40AJ<%d
zr{Z?*VbIl?lg~5g6yAP!Z06qe*S<ax^5f|~<9s})*Yd@mf_ERxODgo9teErv>)(|X
z+kY<mm|3%}WX--yf>*<@f1LEAzWDW#m7CSg^ZqK`a+qN6`?&Q{y-e5t<(j-5|J#k8
z<r&rq?mx`hzy9No|Ek~b|0_IwtuuY!46``B|C4{sn*RO1n}et5_x<w6LjOHKT`1Gw
zWvP8fa?=W3KQ`9rZ!KqL+gIg3U$AoPJKt=5xtF`L>;L|~=2yRT{~u88_L$oyuJ`|)
zdw+ke-@o;D>-9gs@5g}J`QTPMq|AXf+3|70?`~{ijJc;<_t`xB>wlz{15w62Uj6aM
zbNg%S|L(QlVBE<1VAty1@2;(VyxhF(?eWg^yt~CsOV6%N-~RK@mv1LGFE`_}-~V;q
z?Riys$-ln@FPTu8RsQ@)aR2)px!ZT{?tc2Sd+)`W3HlFn{T<Ao3f(K^od4y=as7Ym
zs?ER2-M86W_|e?1qUL>PudsOi{ln$=er}1K`2NPdJG)v|Gx5#ywus;JHpuRE=BtY_
zhh9FIf39JB>7Oe{@Be*qtkZV?+36o*r@!C(V)?BbJC~Tpu1e+G_*B|*g=2Av-r5_i
z@uHfN@&8RSyW)-5-|by-w|no$pWXZ3E-ilW=l!l0|EiNR7Uy@Lvu8i|`Pk=kji2|t
zPknZv@?Pye%Yw%3v8U2w6Zm2toE4wJ{Jioz>#?tu_kLa~to>&`w>)P5ndtL>eNF`B
z=AC^UeB7+ee(UyHxB5cweNUgdJze_us`i#Imp)c;)_?NK-IJmc|Hl8E{Tlsm;m>6s
zi~n9cUGjtY@5`Ti|9StM9iH=)>GPwYf1j8pKS`>uYLqPAXkY#E%g&bl7Vl$rUD;o~
zZ}u6@UuM-YY5n{6f6M=WD1YDE>;GTwkN7=To+<8Ay!^{u<~Ps3-+5_{+V7vYw0FIW
z{Z_o~{{DM)|7M4m#%`S-pTAyy>wNh=dtT>lo1fb|#ryvax$Czc*Kg#Hzj0oE)BX5-
z`}#BYzVrS5`Sx4o`;GJO=g%)se%`g>g7@2h9ee-3e*0X06Z;N5`R&j1H_q=b5y*PG
z>;KJv@BV)KoPT@r?KjWo+a22fxAJ$gz^jMWx58i79k};B?)OjGwD;0)o^MY3Z~E<X
z?YGMKbo=^?_gI*Y&EIr>=G*kG^LNO}Z$H2DXx+RG=WCn){%NQ^xBKn$?KggR|NSGc
zU)~v-=v8=k*E_a3%m2o1nxDVze7*4;-`~Hl-#jnBaliDN=U>0=d;RA5>$m;)^6cx+
z*?q75_SygD`}l18|EEvK-oLtk_ueai?<!AO6MI8{(_fq1`|BT8-+nAr{l|6lXS3fw
zC97w|-~QWoI>x@NbWZi2r@eKz#pU0;`;ho=|J@_c7xT*TZ13Ej|FKRwq~c$>wO#%E
zyD~Qat=)h8xogJp;g4?B|LU9%kAAAJfAsnLt%Sp$XW#F*UHSXb;k)iJ)jw*h{!M&W
zR$aG5`pciP-*(}*%&Xq?uDiLbVu^L$`Sox9B_4l%U9R%^MD5%I^DBkt|8LL!-@jEm
zm!X#9{r`J;h2`HH_Wm}#`#-q;|J}RiZ+^c1d(P3%_Lu)ESN}WqZu!Sw&vzY7-*rFr
z{Qh;-%j5oUzx(>l=X=*|S3EagXPa?;|H9w3RsZbQ#O8jxe|c}&-1GHYf0zFL9lh(n
z#Qg8|FT|qnuCw*OyZpnS>${G+eV6@K^FplZzy0gF!}HGH-M_!{x%JHldoQi~8EW-E
zZGG&`+6B8E&!_K~mw#iH^8e)4{|EM+mn}OQm)gJjP2pDCdl~)aHy@w98(cQm@7CU(
z=jG}z{CiOMdrtoL<Lhs~|L?l}|L5}C&;QC*|G9MQ-|r8f<!||4NUXahw}09F*!=gu
zjkABh|NA-rPW^v&{=MJ!$Jf34yy5HRZ$GrZ{RpjoV7)J4eeHVNdkNQ{zP@+l`@eI{
z^SkT+Uywfk|6cR+j?bLc`Fp$GN6L!Z^PNkVnH6s~Y2yj`$iB&o_jTSBW8%ATd)LwS
zUDki+{=4(f?q^#0lI(9X{pG)xB_#7bPP?d^_tmv(?eE0A;%@8R-`6E7*881j|NmQi
z_jTEa&+l&gHqlh)Nquea`TljG_39=ouJ8MJ;t}(<x&-Ef-w#{-RL=hWU4H-J8$bTv
z*#Cc~t={JId)$(re0a~-w;D8na;>i}x4!<E;P2Ws?EJ4Q&-}OM|G{i=uQXx*alzmJ
zEkFP7ZGZNEbNjRZ&*L8ciT{1+%>V4SpHuh$PWyd->$3-^>b~#z`#$P+cz+Gc?>DC3
zDoV>!-kN?ZzAJaV%>7d7x6eh@G3)={*faC?I*a$;tG({?uTOk$Rr#Rte(kpt|6Wh8
zk^_yu*d2H8yKsO1*4@VsUrfIHujcsYmnT5vjQ0`pAMQLaXV3r3SH14%-|X$><+uN@
z+xqiwvHOo-hQIG`HB<ky^XGB-w|05w<FEdGUh!}5cKvs+-femwURo}<aR2Nx;rp)D
z+>$@`dFyTQ?KAaj)}Gy(fAw`U>+<WjZ2oZC{&)DESY4O<oxRVcrty7o?Dp>G`Frj@
znwfPz{_Vpr+4kkX7tOM-T|4(@@vnd7xBlx{{I@Sp_;>jHKhLxO{XW;9eO6yS@8|tm
z$>;n3{?7gO`MJ%SxX<sUj(^oJ{vUtk{QG0|dHwg>j9Xd`b?e8yljQpSUABAmuGMkx
zE}yfVcl++l4}tp=?!P=~uDrJ3$gy+R5BlCQ|G2vT(c=4GdZ+)H7=NK~YTdte^Y4Cr
z|21Ft!QT^4ebhgA*ESyi>b~zc_s`Gq|E8z^skTkH|B`)*-^*S9Z~U+RY59K7E7khl
zHe%v`in7hj*2h<W{JmRz{rh_tW6%EnF?-g3`At8&e$?#fIsg9czN?qb*sn9&^jFA#
zmOr1o|M;(l=N|79{@qRd{F2Rj=JwY==bG)$KajIi=h5%mZ-1uV<(>Za_;2$Yk#S`=
z>+Bw|?KXaY?ep$8zwaj8{}8TsICbCMXGep-{n4`9zb9Jeecf`~`1fV{pMUPD*zsEp
z6v)X{|5Cm$vE9G!w|2$8vg+@;-}X!A@O`e_Ua|4F^tV5zcjX^F*Ejf|zhVC$;hO)C
zgzu`q`I)`@zuS5Ho3)qb-M?V_?Ed=d<HvWgzq$E(SNfMfjqenz|NVM5V_yB1-!p9M
zoy}kW{Cn5^?a$u3?=OC@UQ~T(-u)+^TRvV%IDh}jU*n(7ygM1@JBG`5{9J#*idp`N
zTJ@cb{_D3N^G5aGTT%LItKH|m8{Z$#Dm`0t_h6LJYo9ft|DPBgeKY-I`Tl5o!?3!~
z7w*@r-dpx-)8G3?AOBze{qM2LWmn7Ps{XAvl^0*X?c+DL&z5iZyxaVB+im%u+v6(^
zysr3oBlIrs{mnoAaqs!lYyRiQ_x~@f@6}!9EsrVvJ2!mq-y3tU%kTdDd;kAc*6aVj
z`@L@epW|_R{ym$$e%IsQ{JyLA|4FxheE;<q=@;MkT@v{CseAv^&sKInWB0_Jzjve5
zzEnAQ(Yza<-v2)(Bp>nLpg#X|O5ydpYo7P~e;cfCfBk=d#s8#_|9|Jbve{p5x$e+u
zo$&Zuk6lwX?ar@$Tz>28uG+vi*0xo`mw(Qy*)MCq-zc6h?Eh!`;~&44zp++a|3hs4
z+43La@zrbZRUC8_7k=HP|E7D+&3!-bUa!ylSk3q6)!zNhzqg%zcg{&-|Nj5a-z|Up
zb9=e^x}HDJ?{Ah@-#!1r=lX2NnQwpG?SJuef5h+mZ;qFj)W<)5ob$cu@86g2On>c>
ze^Ym4UVi!fOTYi`&;Fmmt9|(Q*FXMi{?7Spal6*<e0}NL>(?fndH?m#`89vdzdbH5
zX`c80(XIOJZ28aRPv3k0<{$I#Kkr}GIiBBMbM<G;_x3OUwENcF{{HvhySG*U7H8KV
zsQVM}UC;La%B}W!_H}!9N1fk(z3#fyx1=@QN7e2muYV-<Gt7Fvec98a|Nk;ifB(Pw
zw48kf>-_qN^Z%F4`(OUe{C|G+pTg>YFHfKU|NZ#aKjwXJ>W>|KZl8DmZTg#!-0L4n
z)qJpw`#*X5`}%ta|H>Z!JnMb4c<Q;Y-wTiYlmGbtV)(~jb1XjXbvM}jZ_2vs(*1k>
za)dS5FMfW%;>k2+jU#^qZT9brjwycfH9+u{TW`DljlUE5<{j66{qy&=chSx2zs3Ik
zEnollffQF{ecbua6O-K^1lB!&y6>FcuXhLej9>Wv`hEX--R0Z6)W80DzT5u#!VTX#
z=Kc5izFBtD6#E75|F@l<x0k1NbH%^*{+MD(t~C3#A3u9a|Nd~|U+28~{PwwNZ~m>B
zH-F2<KBk-BUs?X)7df}jdH(lW_qzSH_xa1pAODWOsase1HviUo`%8Zp?K}VfN^GM2
zyI21f&0D|z;i>z#ZP!1qzh}Iezog#xynIA;5wGk1|E}lfNB!pe{n7XC{!3qXzCWRU
z=AQbl@B6y0KYyuw{OwQm-Lt>^S*hHyWZ%;2_IdTMC+2@%@i?~XU#|N+yH8%v{^zgx
z`+IBi=l}E9{yiOT^8f$ATlRZC{HdQCJAZ3^(ZiqrcZJ*i@0Y2(n*Z}>{r%bdzkL2*
zfBn3?#TVhSZ*g1y&tqR_^Z$GO&gb=in4VXB_-TLjz0$nD-_xF-U2pYWu>SLO{rmsR
z|LE3S`25%Uobf-l`MuZ6*VnvEfAF)luKvT%+$#T?X9wRm*WWLDV7zYsr=`zpHs1ef
zx#mNCyzUSC1zPts-F5!nHva$4Y^Q(Y2971p3JOdg1w7gv%vdHV38*%H;c(&LYY}Sv
z@#AP82S`*1Bx=C9#6`h@$y3OK-+h(Lx$o`v0>6Lf@6r16cmG5A_ODM)t+tpSkiM7o
z>)-G1uJhY1ulm3C?%L-+xC8k)Y#gp|*L~5l=RC?E`~Cd-g?m@){a$(cf$INHrW@<y
z9!~tkTy;<W=9kl7{nw@a-LOtJ`tZO1%fJ5V&CWk+{$}3w&tFYrzO8@%Z`!>5wQC<F
z?~=dtS^C<&4QvlihF<^l`Tyn9|5|@D|9>1>^S8XzzWw%{zpA$Ndw%PEXP@=&-~Lb9
z#wGkOe%im+i)Utd!T;*-+THj6HqXEMxxZBY_}W)>{cry6J}tkgx-|W}vDN;~?sn<V
z%j>^qAL9P=J=^{5&&A$*4!U2L+bHj^^O2>0eQgo%@88y6{zP9tccVXj*X3V-dQboV
z`t(Ns`wO4zYi}BVt6BbAaPR-i+52<s?OwmWbbn`Bz3sk}|Ni<_%WOT)zW$}&uU*eM
z-x%+|`LFhw)V_bV-+tJ?v@L&Wyl%tyn9b+v-S0hoAG>wFeM2vI?J?;$GWRn3Uq<cw
z9-qW>v$TG-?WL=K?jAh<>)Yz{XMJtT-nQER{{FI<|5@z+p1=RZ*WWzu{9yMZ8T}I8
zg1+{TT<!B8SIcajFTdgV-)|L{<fOmd*m}JD^{xli`|i|M?7aT*XZ-=Y=l_%X|DTep
zzbIFKS?>RXfU1PYtBRlhzZUxZ+<)<PR_5{ouU(IDH_HD=I{QC-@6QJn`+r@i`f$tn
z^}*RY<Z_Nx6?|U!^?@}1TK4xgTjch<zEJgHp7ZO2)%<JOA20m+V4L&ngY5ik+2yUa
z$kjZ#P*w1I;nxR!&aV$1-&MZ%=Yv1BYj%G;%l`cR_7eH3&j)}0KC|#^^5+Xxg}*LT
zeViMkzpm%&qs`MzwuNW2*nju7bdS&b`_t+Av}X4=-wpr&&%Zv;`v3l?R>zw6-}yV0
zPucx<{`dOw`UKl&?&W81Whd<2?fkxe$M2_n?~a+j_-T9hu<V@)`)hUQo6puRi2k>8
zUj2p7arv*-UHkq1#k-de?B-tjy#LbQ@3N2n?qBzvpYL0Z_nGPMW<2M<_wr-Y^EK;t
zfB5^`KJNJUKYvc|Q9pM6{*HG`Kb|;vd})tp&9Uyg<>k}&XI%e(^c_>_w)6jgq+Puk
z_I3Ysdk}H$zs&#L#T@^C8@GShZ~u?$<NogM2leIpP5=MK^FOS=9;f)P{H^Gt`utx?
zkL$1VJ*;29gX7=#P0l~=Zw+twf445Q{7K7){nPhuv@Uwe^}pKg&-+#X%KtrHyFPL6
z|Kx4<$*g~N%&Wgs<EX;jcKy@O_pknKP&a#5V>*BT`9I+mZ=ROc{F`4^zjOEc+sB2I
z{yqL#l2Ci#^Y^`NkAEI~r&zu3T5ZI6d86OoZ<;UoUsqjz=wJE#wP)&IR$V)OzAXLi
z	lD=bNAZYW?=-YMbV!>-LvxkIjp}yI1sl{GQs6PT!ks_b<DB<$itp+5NwB!vC~a
z{mYcT`Tb_q$J(lYE8hiw`*XF6KX3cS{fXz}FaJ%i`WsSyYF_;Pzp6F&we#X@x_kHi
zKJ(-LrQh>6{=b`U{r>*Z*VFIst625h4AdH8nHOLA`_XKju>I%%ES6sX{HNXB+TFJM
zH~wB;@%O~r?)=yDwmmm5z5iS4+<*05>TiEa?_Tu1es}%9*}LplU7v4q|G(Yr=k_YU
z&)@q0Zu8gI^*b7$|8L)ApK|{GrP^m~b^q_*|65o6@7g={uYc5c&EN1m{{CNYoBgl8
z9j(9gSN+?c+`G|n$FJ9~`mI^L@5Mjwz5msB&)@Pq|NX!9Wwr6YOSkLqTmQSRx~};9
z{e9E!zyH1aem1BF7+&>{`7Zy>&*dfNH}3EMmYyH~C*b?xZ-1nBSAYFgUVcCMysq5k
z&+lLEyFPFK>fK-2?EXJ|=l<sB?%ma2{<!aw-}?Oh%YC8e>#v-DzW46?tM}{kzt?{I
zQ+xOR#n1O||821C|HJzsz5Mp)6ZZwym)$q2FWy}_`}>X0C+^?5cQ^b0Zv9W@+wa}0
zz45O+-n`WQZ`Qs0S^xK)zxIYb&bPXD`rDs({>~2nTvdDF+N<9=fBzk?`fFDI@8G-h
z`(}NYe*L#rO#a{1aQFSkbHDvLe3!c_?#=Ey>D5p8U;RCB{9b$I!t0xBzyE$CV^bHi
z|L(n?g4K1)AFC()*DtL<Iq&|}zpJl*{;6NKKjVCVsr|a=_1k`L{`TkHJO7tI=fD0p
z$9Dhn>b?K|>6g?WoOl2B-uUzND}Sq2*TsJ~|N8I$uHWn5-u!#_{Jy^X&(nAPKLlz6
zpRW2BUs8W)Uj3TizpMVK@3PN4FaP4+=PJAZ!FT6xd(L0>{ngk1Ykntx`?D}F`27Ef
z@0Y**dH61F?|=W>|7zpEdwkzA?|;nq&)@z$zMKB#&-1@Ea&PMb>i=K9d;Z4f<GV`t
z{!`y=|8&MA<?KV}*4$kYH*>wP-ZS1Kr(^0Szn_2PVvO&bGhf6WW~@{1dsZHES++83
zul1+zan5hnC+FTv?JvLm`0w3`%J&oO?<e*zPJ1r>_PO=jk8;&}uE$l+|NEz^de2!o
z^K$pP$7}CSG}nJ~KfnF^W!azc_6hds)%SD1ZN8DrwCa%DRk_8sn{4ee`lH_#cH34}
zt5hd^-E&`#|JHrE&GXA|Kb8Y6(y4y?F|fMkj2!=s$I9P!+?6Z8`S|cR2l<P0zx}vi
z^zZ1s-@4nr*%bf%SNvzs%dOA<+5BL5r~HTa$Tjwlt{*ENRPB4O@QkBBJN~$P&9Rfp
z&mXCLwCI?4<oBbkpO1dKzVF%6jepPYulldP@BX{h@xT7^{d<>m|NV#RbKn2&6FDwk
z{NMh@{r1NOat{jr{x3Ga^j~JL=9f?J(ro|Fx&D6r*Z0YdZD+UFKk~REU*&w|y#3qz
zg2|8F-`d(|@Bg2F|3J3r|GNEu|J7Ch$^COrF8uz9>>roEeHMTFar>K({drG*{OW)6
z)&5u8-~F~f%(egZhyKkE{l9z5ulw0o-dA7wHtY26;?Ip0|Mt!P_P6(RuG)UT^Z8qA
z*)zVc->vy)KFgQ9@4V)$b@tZZ-go@%+fk7a+COKr-@HFcOJcx7vh)87{;q%jMBvEr
zr2YR2zFS-CC^{rQ{>fi1ogERk;k#Yxd&}JZ`?>w|Hyl5I<MH&oM{$4q*1z6$QSSSV
z$1S#Tf9n5U-I~Ac{{Iz!{{%+&{@d{Ph}38Gx9VD1`xETvZ$JO%^|#NizyGekaX#NY
z?rz<$N8h*qe|78rCi(0CbNB7rF#mp@ef96o*7s$<J6(UQGOj;czwcsQ(%q`<e{1Ic
zyna8y@UX6InD!bE`RyDJ4Xu}NpT+*qtUHhWbB&;N?TI}P_$yk<*8e=Sedc=G+5c<K
z{CRxw&!hF5Eq=X?zju3+RoL<APc35pU#|Inli@pKvDK#o_tX3ByRPs5De&+A$?1>&
z?_cys{;u|!|K;&d{?wOi{J&q@`O{u5{$qWN&j0;Z=jvm${<D9ydG>z)tjGG6GcP~A
z>s#gb|DjjE&4)Sl^`Yghw)>CCiT~R9=zq-7|Eque*B1X@{r~<q?Kl5_|5*6<|F+NX
z|BJ8rzgBkD|JZ-7>;9L<Kl&A4KJiz4`HFwnL4uVl{$1aD2rjnWBIJMduYkYncYFNJ
z{~YjleRb>C{qIDt{eSmQ>H7b;(iQ*8e=huW{}vRBw!f;syYScjYW}NmNs#gPOIG~5
z9=qgU`O)X`|9@}#@V_KJ<=^^u-iQA`{`dJ-<*WMH`7ir&<X8N+t?#XRcRu+4?dtmS
zCy(!6klp!P_U=Sw_qXK`ljom3sk~iw#sAV(|4Z3l)$d+wUG&P~@B0&{ul$#*y-+8&
z>i^tb+pRZkUiJTP*~<U5hW*};{?Ck4{O@1h@&9?7^B?=WivQ-nQ~G0n*Y!vJHN8Xs
zFUvmq|5ESJ|Kh`^Kh&49|JZNvf4=Dd>$kf8KmSlD@c*~=blC&{<Nj2~?wVNKe|r6U
zz50)<PV4XgbK=%l_jTLf*X*>-DUH3+saL>dvDsd8&Reekzg-{wxBQs;?Eg!?kN->7
zPx!yw`Uu1t5WoFL{jTs6|BDa1{;1EZVEtoXJ^jG{&qoyh%~x*!QLp!Z?a}|APe-ZO
zt^WA`&!zeun~(fwdhT>@M#L;J@xNa2dmbNsr||2?`xjNUH-FT>(tiH`r&FK3Zk&vY
z)xSh>?a!yzoxfhcPx_d)<-f)MJ70emtUlns<68aiUEV)0zYhOvzxv<&ZrT4ipWXMp
z`Tbw@<Nqtpf9%!wIsBXdPT>D}_I)S**vnfS`Tx1m`H#JPMe85?`$Zl9pHI_=_+fLM
z;J^9&HLXAE?LM%6`d{-{@!$ODIK}_x%VS&qFOUBCf6b5jy6O-A|AamIU#(VNZr8Z!
z>AjC@g{AMdYOOP`KKd@Ldi~%3+iuIf{m|zAe&6H9quX^(J&OJrU;pysT<7&a^ZjN2
zq+Zi6|G|Fy-{U3!zu!DN_wL^1{x<t7yUxqsu=uy;|KoeTdykv#f6Wws;q+elJ9n*j
z?yNoiS^k||#V@`84QJQxJv#H<#K+ds(bfN+wA5aCTybH}-wL&t>Ceu)|8&l`+Pt&0
z=rQY`-;e*zznypcX!!&C?dRs*yM5#C?W>p5?e@0U?=AoTQnFrd{|Ekq({KFM`}?e1
z{>Po&{_}7CUh^+^`L7E%FZav;cw<p%S6xudt$!?j--hkQe~#SSxqr{&CnqbmRjB{p
zeZ%_x*4z3`^#$ka>u#)joL-)PbaMI!pZphodGl+ZT{-rzyW;KBtf%Jn(`6+L`R)Fm
z_<OhW?b^G0TkRenG`232op)J(`r}6ji`y<WpZ~RcSM|I42k(wni=ThBewX^W|Hu7b
zoS#?m?ZNF`?B@Qr_TJy(UCn6huXF#ygHCq-J(<t%=zrd^_s5Y=^>6n-9P!&zlJtAZ
z-Us#{<oh<yeRoh?&gSzGZ$HDipEtJ0pVj~V>T%+SR`!n-clJ&B|60{;p2z8OyN{RF
ze`x6`*<Dll^HAO)b-Tp<&+FgX`_I{ST(W-8hZ~LMW&H2zvK|}j|9s(p+|+jC=DoYK
z>&vo|U+>)eeE0NwOF%0lj{7IN*cTR6pTAdm>DqktB6eebyIp&~pZvT3=I8jD&Huj(
z-);7PlWSk|o>{85`|WeTx!cbBd|f*I^~K_KOaGp|_pRA~jxpc)pRfDtH^&`b@$-lJ
zuKxN>zkf{5`||kr{ijQOHKiX|&(@#w`QdNzwC6{TpO?G8Ii7#VpZhy^vT7VW_D|Yx
zzV#|Iv-!7g+^YY2`F8sEbN>&jPhbD$|GOWS`G5a!{;qqWP$c};_Go4Ay3<B=w=35C
zX#F##wNZoZ_9hmy6A_bArF+g+m`I&YHj%1KOF5(bM#AMy?1SSDa_5BjHYj#Ze#+u;
zV%=ohhYXQId_TYUe{TO%81adjyV}FdlI_nawGWT~-&>XC>+gHsd74gt`n%<qSM9ud
z_3qWHrLV6&z85|7YM|5Fwe!qekG&6i{l{Uw+{IbHET<`PZ`*&O`0W*gkP~V<nd&|6
z%Ky1~`%(x;qS9BFfCV`bmjj+h-ruxoX`D@N?uxVb1A{OBzARTcJvnFXe%lM0$(`S=
z-acO;%ftR<SK!NctBN|J9|?r(zLU(@e1FTn&AOVx*?$l63g+*QSK)WN<+$oeNlC)*
zOK<v1%3YpXtGZaK?$TZz65jszpPT-vQ*1hJ%UM+P0ybF9IjAH!^GnzNwE|z>b=IfJ
zvoO!SAj<dl%kM?g8`rA5S?Tgqby`f)%$qA>IW@~wm)r^EjYzeLcojG$;hS+UXSk_a
z%+(nM|ChB)@#WN<z3O9k*Yxi#fA{5eiwbkGOm6)<@yBu(s}R-hWm<-1ojp?ze&fqO
zWZq}LZRe?(OQTkOnej|jGbqY;OOo(K!^8JybY@Kbn#>uod{*vyvHs0_XN%sv^7eh1
zk8FL(jr$Kjw&&Vf<Y&9MT(EvGG<SZ+io^2DRtufla<t30qR8g0Ue&hGqT9CZGuK+G
z6yv(+TU6_gio2ysEAsQct%(f}zyBa|`@*A}-({V@^=s?vS@~~lpUdoi`0LoS($%l7
zuV24@a`^Xo6MZM|%Bros-1h5r_|@$6*VoOq-O1RUm&#mbcRlw0rlQd9DKo;?XU5%6
za$UNr?#R=ywMFqS%l1sXynO3A;dnOvm`RHs<eX}p82eBo=RHT|)%x#pPbPA>OnAHf
z@o~RW=Gli9BrD(Xdb@|cSmNvL#S`}`ha_viop_`0TZb@Tp<KSZ`-$iN8Trv0nP-<Y
zU%TshJ$cIIr?PP}fe-e+E!=nSW8>EZoxR!)HBy)UF5YH3an(xBEupIJx}N`*`1P(k
zGta$GJZR4HWd^BCPv(Efm3viDtyDKZc~aVPk9IBf`PW=8DKFd+q*`R9>8~=yZRwOL
zo8IzRO!4;R?aSJbJmHmS<{4qWB{p|mR2^(PzG~i!pLB!Sv+(n=5dF=|eA9l3J)i6?
zbK|_?sfWtesvdt%RdFppzh-%6Sx;_Z&(`hFe_5{1EVsIzHl62}r|O@{i{^51#d~`2
zE;o)UEwGpyAphm_Nl_>N!0GRFrM~JVEG^!o>i6la=DCGT7Rx-=FnW5<S>+J4DDC+R
zvF91_?i!Eys~1`CnL96|>4vY@tcN8|dp)dHYq=HeNtV2|+U=6&+B}Q7{wriWIVWYi
z2Tj_wMgQ`QN2znPS<LJgO^Dvm6Md;PS?J5l>%VV@w>mxC=COz0<+F*|qG<WaXO8t%
z2Zdx8UGd`YTVuO*rQa5n`71)zua)HSv^vjSxFk_H&YSuB6!UksHz$2NT7F<vpF_C!
zikr7@zT3Y4bzVMu#LAq#Df!u5d7DZPU5gH#+`U(Dt(MYKPNrVIj{>FPZQdafy3R7c
zQVo0$^xyDk&bsZs$MO7)-gCuPz2`1!&s{uw&f@G~{<BjfTNeM%FTek%o;^ED>A~v{
z)raNQpT924@-aTd{o`q29@flRp=^u%*#6$Qm&4y)b^dEw<k^Eqh1qjEpT4bKc=uj`
zLyv6E#=YecOMR!Z?%uWd-x8Y}X<rWYc`Aq9@~XaNmhs)))~<)YohkQ9!uxOSZ|`4U
zo~JhHsPV1Y2A8f1cAT<X_eLU`S>CYe&6L_&!^^&ZFD>{kW?!~7W15t38R(j`zsjdC
zpS=}rt&+*P+*Ud$J>Jl9N1)Q>qu$4lOlLi@wTm?>ZRt|SAa<+Xk6U=WmhnDWH^=8&
zP~$Z1_ziQ_OUs&`ay6aN=14JfSjMwdS!libX8WSeURs{LSx*-`J?(yz=dpEq%$Z41
z_A8H1s8ZK0oHR>&=MmLXQzOfTsg6P33Sae&68(2O8EO8l<WAvoIDPeqQpz)jbwwVv
zZPQv#o@t&Yl=*XVM9-BeoKLu(&uHGov-9HC56+=(OHOTzh~}#b-rYCN`Q(wdX`!4c
zyF9x>o~X57@oGLLYq;~TN^t$j_xG>9sh{tc|9|x~1<ob++|)#cL*%Bf`tjZ8rJMu%
z%)b-6?!A62{CKtZqy4^L`<{e-|GjEX)s^2qdR}|_VwfjZ-)&yymm93O^2=ncoBknk
z>q=Hke(a`loL7FT%yiBtry`G=?9|b}ayLFGulqzv`<0g`L%z+s_;E{0(B~x2Pqr<Y
zy_cRTZO%06RVsBa+ApvnQ}$)_^!lq|<rz1phcK1hcy;4{!G#h<^PKwp>i(aPA7`CT
zX>!(Ev3ym!oVM4#c@Ck;Ys&J2%HxuMUwb0gcZ7YWXYS^wv#+=)Z`-tf!_)GO$K=(w
zKCiP<`8WHH?*E%%?>*)|G=2L!pmg7DF?Y2f^{dtstJG&UTny6Lxob&kq|rmgt!zfh
z3c?IQD;2g|rmXUN^=`lB#AO##Hu>ny|GR3h#Ikpudfz<OwuZzWzjg29Y`(AWjbGi~
z8ERFOy;OP0sot2<$-m53rtpNXir-S>A8j)s>$29@zW-Twlc$)xf2k||r}kOQ@BbQ8
zqd9IkYHfOAHf0z85<YLO4NI0eFAKPGS0eE-Z;;{*L$*l{S;kNH%|7!{KKTCpkYo+*
zCrJ~|%sY|uXYIsGQ}%wJ+wL))Wl37ibgkD_rM4?Kt_yy;+54)cQMkJ3^{D8b6RlWQ
zx=qj$+9{(v{r3~KyYn5p^S7^+i(Ys0q)h)6)str?+}U#b?!n0`O=reW@D95b))><0
zd3Q$4`N`2+v%X4}Oz`4f$@|wQ^ObDi*B(3mmFFjPO3j=)QA=QE^F(fzpn8St@3#DP
zp4mJ9giOB=%l**zZns${RB_D=oOHT4=(?hLPRca*bqi0(itKDywefEAnSa-B-!eD)
zcw_xm;U#LWtDY}0+Y|PYf2GEI&&zU?U&*b^uJ_zMeQPem%EJ?Wam;L(u+zW&*FBX}
z9%r+g*2c}<_E&APZ;`d<I<=FsYC8|)NJ!b|o9=xQHR*%y?cI}pmj`^Wy0ENMddtU;
zHojuA0jb{0ripo6nbd6^B&aAXdFh>P((2~?8~c7Q=6kzyX_ND+mL(Qu=B~4K|Na-_
z-|#;^obCVqod2i4?a%o?Tlm|4=1u?mchCR*U&rU(|L3yFb2IP%Pj|XlF8uBP&rOwq
zHUH(8%s%`3O!3bD=Zjrk*B!j`Ki%cywU)p2i`FeX`t5Ih+pZPeldAsD|F8O`c=MhA
z>=pm#JKg$!e8bQG7yi~;zWcv9?Dqfk-fjQ;qi_E|zV_|^$LBUc*z*(r&u6{$&;H?^
z`~TYyo^a*q_+LN$+5h`XfBu)h<o^Hv(Z65*$FKSMUw_-r|KFpxZPxtrfAfF-Z~qxv
zAOCm0@xArY-^x?QXRltUXg3J^`Pn-B-+wi^ssHMq%T4`PyWT?U@BekjHgLa`?(_P;
z-}=f=Tlb~^@Bal6%^<>A%ce*1?B=~)57S#+|1r(}A1@U;QGLSB6TMSUbS6(YUFg&I
zcT(pKF(0vcb-MQt7`J?XF!RLz%@emj=YM3LXu!t3=zsj&ga5=$e#c8BK=6e(^^TkW
zx2F7#&wOtkznMMk+x`VN{~uzw{ojf0cf7^<Z~HI!|Bk=#rhZ}nxBUmc?Z0{Jztzp(
zoBqCUP5!_7{r|Z;=9h0ao4-A9_W9du&OYDD)ylu<>A#28M;{qnEc*XpL&OrLsB`k4
z{=~;W`+x4K%-x-HqPHk(|Bs(4`KMlz`OW{+XP*2&{ptJCKlP%~{|;>W^8e}PKefG=
z{xr^A`hWdX$v^duZ2#jY9Q;2$@$-LHv;XmFQvc(1l@FRs`M-XaVM5!6FTESH_>x_s
z{>Q6#KdL*xcIdzO=lXY_{y+cF5$ONtaP2Woo9#T#UG*P#@bo7{w8sA5Zm440>TfW|
ziudyT8|fD~4)!XpeWQD<fF*7t)8TN#oFfxnT{q*&{6Ak0L`bw<StfH}!mFFY5|@7b
zkK{@I62p`Er=G?6QhcSfv(*3k73U70tWEk8-=^66|E|QjCC^tEu(p}}%MW?JeeRT>
zudOsci(6}cE`PA(%za_?)PM7AH9voU<T-P{vU=*jdv=<izd!W+`X|_^K6QD@zB|iP
z{yYjcir4l#S(ItBbY8ue?f)rN|1`h;34Zl+`IXQ9E1%B~I&Tk_h__|;Tm5`~*m?W4
z^ZFB~%&U*Gl|QVo&E$%jYp$_^dD8qU^KXm4Gi1hWVR)&Ub7)(h@wWPpcPBhsa+7x@
zqkB|z(3#n57=Q0MSu*3U^<^XZjCRYYuiqZ5aD8{UME1^^KlSr|+H3#czu@P8Q<MMu
zr>A`Q&pmB_{OSMepYm5U{Q2+1_J6<btpE3y@%*b-?EQcLsoDSi$1+r_-5Vm8{{HVO
z8EaheuYTwM^MC5i{^)=Cy36$c|EaV7|M!sp``_K<|NnQ4-~QXbzVqY1|MLHz`CV0d
z+5P{wAOC;mfAhireZT7~Cw>3#wfaB%tbg$im;bN6^5wtY<uCsgBLBa?-^0rJtA43#
zzxs>+Z;iW!zx)@Q-B`Tp|M5TP|IF|I<KNbB<-hu0>rH|Rk5^vQSU<h%uiE23exK?(
zuEp_e{Bc|NXEn!>@BbhEwXght{`21d>YwY={;4}3yXZ78oLl~JS#83i=e`}crFU$2
z)*EVaR{df|dDo)MvXiZUe$C{(_M?{b(u_s>Jo>s9n}p}8z3{v^aqS;{{a@SE{=4(9
z`cuE_#bw8-|5cBg^Q`#8zcc1&+0XYyr5paF|MQ>lp5f$g#uvZrpIm8pbvkH@{}Roh
zg)ih5?l*RN<L>ljbAiv9BNG>{dZ_$YQfsQG()}l28f1hfBpN-v{L9zvd5Vso+xe6T
zZ$9-EcTSv`-}53qyzNT~zfqsc;o#R%zfI5l2f>>k_nXd7?>#U3_CJ&4oBs~d|MjmP
z`#(MN@&8l%`u|7%GyZS<pWo)c^{xM`Cco`3y!r32`9Jg7f9J2f`Ts0^!~f42-|Brq
z`ZoV>zO((mb@adOZ)#Qdue*M$`D|2m!RBjnTe99B^jmA2@b5kU|MW)(Ki{-VIsO0N
zr6Yg$T1~BaH~H^=z5kAr|1<jj(|`K&f6nv&y1(l!>*crqpZ@v#%D4Yhe;@evKj;7a
zJ7qT>zW874d;d>;+LQlFrT(+;_&<N`pY1>5Prd#cRsTS(_kOf#-TieRfBW^`kNh{^
z|DXMIn|W*hY=8Eh?aIIJtC^Gkch^ju`d9zuU%8-#cmI{IxnQ2VC3C;m-pkYCdat}O
ziSumVDmCN(%>SSJ|92i2(!Kju>h`4K9)p*!YokAG{=j~V?OlDNezKoiS9wik)%}{L
zP5=Hsc=12qd-ebQW+#~xc3+#IGdJ&5`@jF8dw>0ZE574jz1@fX@BV)`_*7*1>ATRv
z^{f9d9yj@y|6cyT`p^H5|Jk3efA)XQ)c?)B@BhCD+xY*Bx5C$nzJl4yb}w0zBk<|#
z)cfU~H5b`flUu(F9lF62&N=01g8q)AAGseKwuKvnMBG|mb5~&E?^1vBrNTcpdQ4aw
z^#1VW80p}LaUN6GNAz5aKJtF*yC99T`<C1e-IuYLcT@H}r9I1iC(gfAbwqyN&a%U6
z*5u#Rk68NW=W`{c_$Mm!=X8j7-`Mh1+j`2(>fgmbvzMp*Ra$=cN&B*>BXT1Dg}*y^
z1jpaeG)|v!Ld`A5{>Z5bH``CWKk;Y2EhyA3FPi_S-sZ!D1)uF}*;XCAvVOX1fXsfS
z+_RSD3IE<p&-lNY`E$L||I0ddZ(kq$GhY&v^fC(>Km9k^df)%hKl}Y>H~jCnKK##q
z!Q20juYLP(x$5oz&%3#E{?9Kre)GTB=l1{S_qYD7cewrkd2H_g`SEEt{y(2<_wGOQ
zt$+3xj{mJsnDG67BjdgQ>|4N!V3g4tu!^>A|NCbq{+FM=?LU9U@BbpHH~zDqtNTBn
z@#BB~S^w)V{Q2)J|M$PM{onu1&;HBj{QJ-Q)cX9|pa1*&4)5r^)F1aX#lYF@|Nj&2
zhwk%h{Qp1U*nj(Lmcl;|9NCrM^z8rs%|br^ZEB`Lv}Viv`JWtX==k%$`Lu)=5B~3u
z`}v>!>Hm6v+Zm2e|I6=R+<E`lmpJycV&)mLrw#ev{I56o^MCjC<+rErRDHPQ^0Cv-
z%fIA4eyaR2Z@xpo#g%4pcIw~i^UnU`XS@C{e}j44zRFLLIeXSPysq7H%(IR?F0^i1
z=GneC3h%C(&8u5F!#r-=;tS?+^A=b9)|~J-Fe-Zcgtx~|N8bED`|pPT?5Y3x&wcyP
zy!WHgOa2M{iJ#`qyDY7r{d&Wb=ZE*zWyh~qov-kO{ph4ZmPwUga!=HC{YrT9yXjZd
ze64+p>sHr3ewy!h?tSlcPyI(T)PC!HICfgdPg=j8`S-k3?Q0^7RodrSJx*M3vh@<*
zf=-t0Ud0h-rwi;4w4JD<&Dy8t^xJ&mRr4u(7hm(9{y6v~Us_wozTSUFtJL@QgiQaR
zQN}vu{0mLd_Yd3TwqM+@x!{KQ+IV%o6Q359wY?EfEnR-MlP#g|q~N9-FQaE{JesPP
zy!3JTkE3>$^6q;)OKUvdZ#A6xASTuSuwL)K)vMyKd<(jtD0^+~)kWW31Wa>WkIg>z
z%4^}Dyzl=+mZwj(-}C>#8OfzjwY^Vgd8c2wI_>J!clYC?qPLZo&V0QvBGT3M<*C0>
zEBF3#w&eGnT^?*bWs}y@2IucZ4jX=!MaJC@+!tIQz3GQaC~w=+y=4i4%vw_=yJju@
z<oZ}>lJArI-M<)`Z)vGK^Z(M3H*W{`=dFi)-<o~hoBG?->FTP_lP#-W*{>?)yLD#n
z6V0<mJc4Bx1dMfV&fat>@=VkmEyuDKT%l)lUl-ob?q0RWd7E%Z)z0bbZ<gDbsfu53
z{dVx7=FXjZU-mD5@@UtEnT!9Mf<*b6va|Bmai5)GRq@)X_Jw#{?b9nUZ^ZQ?-prge
z`|qLK%b%s~|1fdo&a3)=vL0kB#h>>-d$#W3e~{$*$-%`N|F?dvjmrDB|C#@3-@nsM
zFBh%;Z~CTr`t*y%${=>?)7KX>cV7L!>C@LwTkgE7kNjCxAC>oY|C*ZKT^8Ga#fR-%
zw*x}&5uacCfAwnariBak8?S1bHEZhL{Y`uKD?Rx7b64{xd(}Yus$}R8K(x{KobBQN
zKB?F+K8{v=@x82STf6h#=T*~PuCF?J;ocF)=%mW(_>Ar5G9Su*{rPs|p7okbVKL3I
zcLVE#<gOjl=df1mjmXq~n|XV|UHPv+4D4jMwp1>9cp$G{;_^4O4=ZPPrhM%Arq)wZ
z%CgACZNXOS3m2bp{;s|IutT2d$BJuyf;s#x%1XQ}d$<3vjlE}J#}63`s1=Nym*=<r
zoX+GeEtlu<uH3xZNmjPetbX&UaBt8UT)9VA#;b4T$CD2?hAup};=1_NJbvEQWe=*I
zqF3zRdiec5M_bp4=4vUPu4Y!Q>q@$Ein`YL*0>}qy{zcGthLu_>JGR2(HXr}E|ZHN
zeoOrOf7UGBxBmhPxaZ!B-Kr||EqCQotxXr&V`hDN!goAaIyi2N;lr*gyw@TZpUIle
z7c(dNvA%YEyZ*VgAE!@U|G&C0uXn%N?mDGUrb$(Kz5CaE`gP~a9jW@rpSSF6w;ziS
z+xKq1-rL`)_Z_UR#T2fSn_Ku%nJqr#>+9>6i?jcvPMv<Bb<qh&X<hdmFFw(2fAp@|
z9rM(EKmV3k@5vp1&u=^W*7C={^_g8}DNFp=J{pJGd7i8=5Vg!WG|_>3&31p^Gt!zx
z7g{blXck>aDUj1Hx^P?N=l_gLf9gxJ{@E|6|7S0=%b?q;c5Qdl!fo&P{x4b`T$XOM
z{L~{qUEi6(v5)(=u{8ZV!+E`GvGm`4XI@^rdadde)5N)oZ|<f0_1bT)jQ5&$cCXFq
zf&}3gCmxl)cs}dg3i~@R-=3HwwfkRS&B_e3%D29=Kd!Twa6&6^n}1*VLf1np%zK<S
zyUsYU_rPAw3z2(|#6Hh|o9AD-?PkAnw9JE!&lYXnEKYM9&%IsP@_gCbUFlN`+>fQ4
zw3)D~dcL9W9QI8c|Et&eKlmU0`}qHpHV-Cvs>^vy)R|qq^g*LYXYhvx=T{<MZz-l0
z?Je_r60!cWitnE1t7hp&<l65p@t$j6<ZW_g>AHv=DT%wHX5J00tqCfsJ^N_VK0D==
zrsqpKi!aZ6sdc=}?y_s9)L)<JR#*S!tb6%6xMkn_Q#<PRKX~t|@MnKu{G1=xKY4E9
zPZ1Bz{(Z^h{LG_<r|YNv*ZF^b{vUhwfAxyh|My334?THRsasp-wa2#WZyQcGZo4vp
zTRUHJ{+^n&U+wa9P2TO9#Pw|bvKd89yFbodnQ=_S+nsCv(F&P$hmJ>dr6|-I&Rf1H
z_L<W67KU(%MLiE{CvZ=#*O`><%r8;o_(9Rfz0YU6Xmi0t53buLf95N6i_bgqMLhY3
z#EF&brYS`!9CH*sQMv5@q1Pv-yf$C@WS+o--^=!VW3Mo*U1a%+`F=Rhq14}gHTTk2
z1e&)fa-7j##Of#`KW)Np=Z52%J)I9zC4wqVco{!t)~e-xZ)#$C@66|yAH<#fe%F&J
zS`BlUtGvSuemoX<nbXA6nXxN*iRSbS`6I7SBxcT3R8P?_I?4I?`Nw@KllG-^Naz1h
z7vEVtrE<BZQqelEZ>)Je3l?Sxe0GmMw1;I&u1(+WkCr#|TcaH<X0%vOm?tLxFY0L0
z-gTj8!Zr$X9sDof`~Ri!lGp#kAC_1A{$ba=>bkmw-_atOLZ@FdOXpAcmn#k;!skr*
zmn-e>@qgQGKac<0V%3+_-@d{5^8U2H|L0Zz-+w)6?M*JZZ~wX9{5KZ;zxn_CHwXXK
z-}vtz71Qvq{>H!lxBt&=pT~In|5x6e|I<tV-T0?3eB<Bx`w748xBd6#-u6HFw|&Cz
z{XPl5_wQ3;%lThkmhgK&PXbsF)H>Vn_x{h#|E<{*e$S8F@R$Gg|2hBviQoSJg*U9S
z@c;h%KOg`5ADLkA`@d%X;lK3{{?%XG{ziPq|N4Kw{;SJH<@|Yf@x#+4ldOs~4lMG^
zzaYO++xhjbbDq1-ulaxe*Z(#D>l<JFU+(wx3^O06Y~=yPSSdNMyOMwJ|D5=LdXxU9
zokpyaQ+AoK9tYdaGwm<`>;GRL6;~X|IP>SB-D8osUGOgQiEsAe%l@7Z-5{LT*eCMM
z{`LXxwGW!jJ{&H~XqSz=^*@F?TJZw^Z+ZXqf6tfR*s<wP`p@&9<Rkv^FZ+}J@BQAU
zr}cKH|Cez%rE~pUAN~K{l%;?28@6spJ@DlJ&rScIf3@d)_W#e*|JkhH+k-yT?|HwU
z`S)j&pc8%nGw)n5RQR($v}9ey-~O-v-z5CqA9L~l=1)g|)vpv_zV_d{QRmBlv-y>l
z%fJ3VQGYu0=%rTEotu~KovQgRG(5>8^Tqbkc^S7(?+lKeoqNaqugT2>gI`=ihs*xg
zKY2Fqh4;|~KD#XR*Z2KquRT2F`SWg1wFXwzOZVe<?>xUm?!@;tkE&Icr<aI**sw_7
zaQX}rf$E@(i_dU61?OjOT(Y0dpUKx@@3I$_$FiE$I+m^aQr-KTch-q2$BWZvuJ)a^
zV$t76p8R=+eO{SMOgv-%cf6SIE1q|;^B?0Mj*O(WffxM`7dr@te_#2>U+Y$+i*UNw
z-zk>6I@Hea?Nr$-`Frn`&(_OcR5z&H3i`2d(d`ZFzQQTrHL7I$)?_})S-$Ij?K8(S
z?~OJ-x4pPta{r-(odt*ezPw*3(H#1rYf-yo$fxTaf1h;LIcCI|9ncrKn~<|8Q0!0O
z#ps^75;+3Vq8*=~h1J~aJ#^J>YXA8!%6lW<*!q7lyWIW7*C6;}+~%t)`oYB_ce5_B
z+z(q3`29bd%%SJ`!s|YD+GYLWYc~5aX_39*25IiMhtAqxRPVJ<-XMH0=;_5?Wj>iD
zhcim||9<GW#JQl`>%aW5dZ{bSGuOXJ?|E+cqD{{A|G^&z799MO<SK7g*K<&|VCABC
zqdKp}+7<D(@BMyA@A-fC!=gpjuJ4zz%LTveKASk>{$B&<i|jq_h7}CYG=3F6wwAEr
zaTb*|vda&cKmXR-ES<$)RX6d@Z+riFt>Vo3`_H@nFZ=edZZ^+`(=GEKneLZWy8G>Y
znPvR@&@b_4e%QYGa#*$Kc9*#K5_tn_-{<p7kG}u@l6`*A!9xM&9LN963Ys!mDI}_P
ze^-lXD_1~z)ppOW_tUQ|&0nzPbY=e%k6pY|7ICUy){qG6xOtIl>+>*!E6?65*gtvn
zGP|=Vd{=Xy`GhQ;(@Gb&^*OvgBpZHk(*pBd&2=FcszO;qA|@aHVZ3igqsyZ|`K(v+
z)~sB4SEFgSLCovBoAatquU%NdS@GCD+I7=v=8Mw;xZjFyvlhwdo*z5?!>t(%#roSs
z7T-N=wY#~fe&em)d8NDmKIF>}|8pws`Q0^F+(Ifi@2%YG)$091?2FZw+u>b@4lWY)
zHvUqjbpGte-M8djmq#7CWhr<&u|H;!(&0}{6F6=iso$wR%RfiWt)%(>?$|#&j>*T$
z@33`cJIbV3yVs#(Uu3iUJ2yAh)}u;gcET<E`B$CVYh>6KNod3<9Zr*6;S$?;&g{S3
zue&P$u3mA`;Qypv*R;Z3s8?fCY5A18&|@d{9HRvvsZHrT@mA}Z-tF4g&9N76U&*hz
z`g(V>?zZY^ef^bN8~v;@V|S`cefzbjbE5X`TRNv~rN2z_TFo)T@2CFeL-A6o`=@l(
zN>2T0r2S!O_$}|1E2cYI>aTT*`{q?~Q|n&p%ADy_n_{PRzq+ZvBz<qiwd1UtbHq<>
zik5hNJE=lm{J`%GFXrBLDvuZ2K0Wt6N9E!xyS|z&k$xQ>x!W>r@2$7JTXM^}EkARW
zsl1ctE;#Md;C<YK-O2f-gnn;5$CZoA&OMY2w)(TE??Z*m`g#MN2Y!3rok+>-aO;*x
z$q<^O!&|cA@UKHImMdL8tgM}N>x#<t^H=V<KD9Vy(dGWK;|SyFDV~=!U&r3C%@1LI
z#<kU6Y;Ep;hWFp4_dM%b805H0w%Yv4$=E!v_Lada54W6O(5Gm*>`&#yI~!W&2u^go
z|0i=o%R0}Syvw9M+%!p8=y%;TBG2~6AI~2$QX(}i=a-yQDQ(DXnm^~lrIs^{KE-De
zH>Es1@#DSxDx<27HkDgPUd~o9Pf)zmlj<Y;sPe~}=qvN$<b9@0);{0Myo2|?`3jj!
zeseW?KkD4+{-}P!@vVyG%!>vsZi+L~&m7-7`AN#`*6<MZDFN-3zalj`+&{D|)%s@}
zoX57fS!TcchgsK;s~-!Wex!bKb7;{r*K@`D*MB?tD)7B=<ZbJ>0{5OzpK-idSaq*&
z>l2;nYP$7{J{3GY@?=ks^h6o+nvkM7vL>FZlW%@_vLmx-0W<FjVf{q8|HA#tKkVM3
zw3p}fXSv&QvG-+_t)I6TZ!7v2-Xp*GnX$IP|Kl5U?&(dM{gx%?TkiLa(nqVe?V9}h
z_w~JNe!Pu&AOC!7t+{>7kKflXy5z-wTff-zn$4a4emWEEm+iCn?YnR+czQzR{9}(B
zJ1^aQSuMP@So`C-8D++H+d1Y}PJcAHs<c+%@wJtoZZ3UwM{&>pYf38_avtvg7$fr8
zb8?`3(oMVGr!~U&PWOM8?SEgcllORL!`*FFIhODK8C~0}ZSZe)>ZQ)@cQeg(*<$<d
zZ{a+>nEidNO#OQON#~BsA9x<N+IPEKmQlBwX~v@$=~@5&bYwk0(P`nkpr+^hUU~jm
zJXI2>UkXg~XL&6B!Pd(A>5?yrNA<f6>X(102(LXn^Y9avqt&UG9IbqB*tAyO?8-cr
z6u0cb$C;c(Mm4*$PQRO_qVB`DqWapbp!H|@W@+pex&PK*Vt?4l=vj|$PhMub%=OW6
zkGk2HCR}ZLYB5jEMeT8|^0Ja|e%*EazSH=wWiHA;B(c*_^5K@XeLpwsS%0wT<AXxM
zeYb0Dq}q<1kM@1Pp*!V=ZuD<wzk7~%Upq?Yv*y;=_)m6a54rg-xYDN2Ec(|e3(K9K
z`$NJa)ZBS?c1ktQX*+i1y?bcnzwWg>YdqD8)O>^6i@TRFJ96h+Ub*PJc**4&CSR$y
zhx7li?K^Fv)9)~|WXqet?>{V`rO#S>X5Qgq{uM@5&X&9UcWhtvdy9fk@MLa7TVK9Q
zO!s_Kiypl`ce1Ey=7(Pa1uUBE7nT_N+DuZuFg?V^SLgB(F<*zvON=c~u0QtsU)7?R
z9scd{56f%VPCu`mdffiO?!U78Zm$*heE#RjjQMj`|34(K%a!@*fBU)p|B82-H^@%=
ztAEvD+yB(x@yLWO&)@oO{}X@DZ`%C-<ix-Gix&R(|Mh>pbm8CsKfV6{S6cetKKSMT
z{XaKe`JW&1>;L*Xov&wh_j&*QcB63R{kjJ`uH@H00ukSKT*+6jX1W9-X8lvEW|~#>
z`@@ba`Rq&Y$1nTx|E|~n`i+<V$1glLIrgC0gfi9;))VU*Zm2GE+N8Z8>wAmU|23QZ
zD*|t-%LIPo%-8<i!auc^N#pN-qox1fhyD8BJ@wyzuBHF|%UGw_Z_-{+Q@ZlUj7{DO
zyP346t55lRaJKx(=l@?S|NP@`H|hNQpDuR)yXT*HZvVBj#_nePh0p(=OaA<0e*VPs
z|1W!L&h_;_{rtT~Xa4^G$&&RSl2`t(_o$tISfa1>_Jgt=%B}zQZ{eLL#uU4O`%vVo
z|C6^mq#XG6KY31kjNa_@?=crUPOB<jDqkh`D@e7-zF<kdsPJNCm)YA~eXTEj;?tdb
zaf-I?W{bC?=MoHx#GC%}_WtKp|CgWiFWul1Pvpt}#%KQXxY;TF{%8N$zIkGP!oPF_
zF7cb+|IeQJU$V!hS^0ndr62p7p8uEZscCuqXaCBN`w#v(pYTMv;_v)}8Zid{jU`&S
z5B~R+`hOkFW^n&`f8odahM)5fo^UVt4^qSN@BO78_m_XH?*I#em2n^c_dn?!NHc@`
z-}#18|7U}p(ex9f0jlET{`TYldE68aO#Ht);(z-=4HmFO_nI&NzkygkIo$v8XZ*SE
z`lsF&<o0xdKku*p*dP7)|4($oy5Ib*2Ww$F{&WBSt3T>>KpOf_Wc@vV7VMi%-~S&5
zF{Eewm+U#j`q{oYa0etPKt?@;xQpXoebD3o>Y#veYFPZ|`q%%*z=m>wJ;HtPzc5I*
zlS|m&{{mq16MoyXEiQPd@&7eg55xKYh7zsZ&+6G07aV+yM82-)aeL_Wp?><Y|8^i*
zfdijGA`n|aR<w4%`B|?EGBds4Nqz0Vd}a{4|3uy2`Jga0xA;^q4stWchv`cH<JsO-
z8u(wB>k{5nZFffe%e<hQb~-JsP1|mDvu<#>kl(aKdtuN8TdluJ5h^dteU>nP{FZ7w
zH=gUA_X8nEd50>EW$T+xv&0%jZZrR%repB(Oy|Q%db(A6I1+gFEPGL#W_W4x0>_Kp
zXBn2QZ%D4#Y_vq*_?1DGSWWyz;oeM-^KG(Sa%oc(ZQ0|(zwj)Udg=Xu(RI4?;|c3p
zE(w16_dlRSX#RGQd%9Df+w-4K&dYv~-j&yQdtw}0_=?y6CGA{(d1VBA;VgKVJMHlG
zkYCyfyz}B2&ujj&%5bVuy|a4W_x~~1#hGK+i$f}Z#MYNGu4(_+^)EY6`;z&=sa^MS
z_p~``+pImc`1YHFpEwT8NSw6qTE-ED4t>3sV#&sAyAzfz+Ab9<aYyaecVmg~?<M4p
zCo|p4H<RQ35YcvA%SPj@^x@#;CrjpewaqJJ{`XEw@BIDV<M&saTr=)6Jo_Q>lX<N3
z!}nfK^Q~S;u6$?6ce>C_ZhHTOO#eXJ!}*51{i_xlovT})>->2C%Lsd=uY2VKzc2k0
zu&d<hgm*T!&jV}r=Rf{<zG6?)@%0}n(q~LrdabnG@U8dZ$D5{}dwcLl^#=)aotevi
z>mB$|T(Rb0vanp8jZ(!M*=Z;K7n{^AtDgFxQ1qYRvA#)Poj+~n4DMK`RJYdY7OQZ_
zv2RI+I&M`Q3>SUFssp)>dhj1t4n2`za8ADBZ~sA!m=C|?n*(>8==z^7{NEguoGRJe
z|II)9X+A7Val8M^zx2cY6etHMZ~FA#uo;x9+&Mtm>pyGn|NRFbGT;B71TmzM@_zT5
z@BdRlWeIQJr}+8*KO6rymH=hU|67m!-=7AO5WM;Oe>#Z43(iW1HvW%4`saLt2ouZy
z_KJV=4{EqreEWYFB&VqG`)@rcr_?xy{i-(w3E3%W|Fxg?pT{lE>BIhoAOBxB{rBGr
zoc0U8{J%ft;Q#ui&;IZC`uv~&&HwoacL+?l`cK|g>VNaG|KGFz+y`ap7><G`|6Qg2
zvm3qnzq#+JeRHAWqcz|Due$z2-sB%YC^W>GUVYG5-}m`H-}D@Qy;g75+^ziA{w+wd
z_wRVmziWZZr~2JH`Ok|Sg!N3nJplJiJO0|t5BZ`|+~oPW)4N;suW5zQdo!uH;4e1G
zrfkWHtGxDK-!Z=|phaAycIHm0_4Ao_$6VnG{JmLh{d}&;SHAWia9pzdu$t?ChPsw7
zJ{cijE`N}@RQ%9x>VHpH>u!eoCl}2(a#!9f0q&S?OZ=5(vFt^4g8hZM1@<8&(r;XT
z742}p_&S04()`xBuj;<fWcR%#za{SJf78d|Y;W0rO*(ZRrDJ-4&vie;`-gv}9*B44
z8JHzr;HVGzB9^SqCjDT`uKMPkqVvm@L#Cbh^l@h067$0>uKC7$)!xcmf%~OPuGRM~
ziuRSi6ur>x?tke5j`{m}YhL|x@4cURfh|7hi+Wq*%i9kfUFVzp>pAFG;XT#e{0-x+
z`jRcX?*ILua7l58>(c-HkL`JH^_T2hG~aOE@deUVB7fN*GxOxN9__Nr`6JP6{UFG7
zf65<`W{ExP=asAf;l1}iuOjf`+$6i*1Useu2OSOn$M&Xf+2``^y(RDc=h4na|M#62
z{eQRf_}`<G_IX|0AN0ll<E;CSKFTf$_b=ObZ}p4)Gd@<|c-d~4@BjE?Qs*7+D}I-M
zrpJE#{dYUp`^!#Mep^)LElcbu{&)G}eb0}5Wxtd~)8Cf<(zHu2@_dvS`+1f2zuUW}
z{nGZ^zxMl<bqlL6|2#3_NwvUSt$TjgSD0M0efx9aeba5#Q+Pe=p8FJj;bBWQP<&#a
zGU5MKo&S;lHiHLh=0CMpo`2vmcq9@kreX8p$NZ=Er~luX@_%>ix$9ts2|O$nf6jjb
ziG$TjwzA9p2g^Xj+#WU_|BqyBV8w%v_K*Qiu(2X?5bgDOr|Pf$Pycy7VU9P%8nAJZ
z|BSi#ZT^9Vj-Xcb9AXAdQp2rS`~lsSJXe0y@BZ1!^3(q4oS6#$pU(>A{8Ycha$o$X
z`jwSu8&3W2bZun$`M<RIO2euD`;GS-t@!lcs@S{fPrm7Gp(p!~-<hWHKeb*#4@6Y|
z{J)Wr^V9#9!d?EK{>whzyXDjW@5eSWPW`V}tO4<cBx`S@6tb76{qNysXEyzpZ(J?(
z<iE;hCC7i~&BRqt{D1h&_3xzrSJVDBocjOK^)2V8|DMH18czNH`)oQ}=)d)b=IST@
z=Q_<h{`7y?=VvTG>o>pjobZ2B{e-=L{&#;|nK=Fb@!nud-T%IuTb_c0u&3#mL+}6E
zXSST5>K9omJN`RwB+j?uPkhof-W7l3!?)Nv{<BZylMnd0|NNgv3r_vN`mC4p(|zS*
z-wS{4cYVQr<mvu5{9s}OJj&w@15o1p)BM7R4MasC*hM=3C0pB#)jVSh;yJ%+tYy@5
zU1@%c;k)ULZ;R(l|J&?!(_Z1$r2kjs6{@tp^7Gu3SEw?Ivu6w25$>dWiS3NSt(b@F
zTyKW)sqq9q4?n=Qq<g`h>2aM~xVuF5#>~-g+u0S@`cwP3%)Z_d$$7V%>YoOz$|$IQ
z=(nWZ(Pf_ar|mMo#rZX>gmav#RQ}9)@l-qD)7_RY8lI288vandwD_Un)PHO{7+)Gy
zxLq_~q@#O$&Yy^jvjeA1dwjoYqWz3Y*;CJo-mKrEwTp3``!A&x!C$r($X<H<U~^X-
z^K~U#xpzx{i>@!oZ|U{$Z}6SGbkE8||H3VOnjS~oYvaEYe&G3pc}=PoBK<-(ULQ5s
zE=xEq<yuzF)b{w}4i2AUnHd)+R`|G7iOi5b-Vo`$)L!g-@38`l3Ex#Vaj5)sI4&j{
zw7X=DN1J+g%AHuPCA*5;cBg62;}$#mc+F#fE!mSQZto6F{GZtHQ~uY9|7mRh^xvt2
zDv^D4pZ<TU`(&T;pkA5v|Lhb07yOXV`Lkc}=YH0o_XGaKH~*18bjf_e|Hhy51=~&c
zZ9n$^i?8>+<NGur^>m@2j?<|Y&BbeeMY5U%%~|l`s72Vak9Goo?RJPCa$4fOP~zpo
ziX~i<JjZ@AumAt?kNkN!vG~J**Yzm5dPmI3?>jZPInN4j*t?psd~1fj_X5`c(sc#*
zxw3gDT@T6Mo-j*6uKeLgRhxOo9;*wh)c^c=qxZO-%{;68{G$m5n;Ku-Z{PB>{>Ae@
z_8<O$>cNDbAO7cNcTbqzJ+aw)LU#Kh1Bt#%bt;=aXGF!P8%R`gfZC!3jkTo`)%%PO
zCK#OK_V{=HVDqz|OID@T2<>`f<N0ru`=RN<hrbB@t6Og#pDF5jnoW6m{Lk9yC#HL9
zPfq$eX+r4hNU`R<54srN9AyrRxY)+!{d?+qX{AkjmL<=dXRhha_AIyP&%?}hy(<g!
zmz)aMaeLkP=(|_B=9IMfOK-K}^^@j#te?4Mx@UW2jn`|z`if__csFm_m%2Y;>Zj-P
zyE|%XgIG4)Nxk}mF(5?G`1`l#pRW6z{B_mgb+PJ}TRs*V|8@%nEnBJoZput!pA=!`
zZSqN}2EuKp-v8j;vmoc_tR(Re2miSrH|(g)Y~L}lboJp?d+M4ie|dAR{UqEa`|0ZW
zt~=&a_AWk^ZE5$_YfZed%a`0Q`q!dg_J&~0u4@VWUi9_#5yr^4`$yOoC96Ep=rWLI
zTheFgBxYU9ZM<#Anbb8UfB5#_Q2+T+_l&^V$9ymMnyCr%Oj`F3GQFO6Cit#JLuthJ
zFz!wlvgg<TKH=W9r)kFWC}rPJFUIg^D(S6fx1auW%TDgW$B#w(<Ps*WVmo~9V(?r6
z*aUm2)Mt}?rmOnQrw^F!SnHJZZ`p<av(?`ns##kQ?myx6>`i~A7G_=jc~Zvq>-JUm
z_BU2mr3hu}Pc%L6HL)<c$7=>?j{TPZ(#CZGNAGNs`@VPEic{7pd()rT|1dU|Xzlj5
z|M7)6i#c!E!=&Wk#np|~!3#E5b?!cQ|JL1k0+-*s|4^-5w_{hD_ilTUJ5A4RcCX&%
za%i8f?n8%I1);zH-^AAD$Q&=7udLg-eacte$W3e0sy68c3iZ3o*^9V^`N(<BG}8>S
znKdPw{mZ?3cka%r-o5;;ZJk8xL^D5Wk-}HYJYHY(y~yCWYLP3Wdco^|mk({=m0sJp
zsv}t1tx0VK_w~Pr3m>Yn-n#Xw+IVyM>Bk>ERyM`V{;WLB*!pwYv$L~r-kiDp^Rq{+
zLWeI*3D%h@)-9goaxB5EIQTGgvM9gq#rBLzbql2m0@)<`-u~Po^rrK{uZjP<PFT(1
zo#v~p{nM$=sKP$HWYZa?Wx7A4j$2pF5qq6xAZ+fXT6F94=4mrK#m`N+?0Q#!fjV2^
zgw&jv@98rR?hQWkp;hHUT2es)U!Gj)0tFt4IWOPK&v|(6@q@nC-oiUyx-QpZ-23Wm
z!6w1W^UEAs<RS~s<d~Kvxo&M_*ztWLkJqBIofgOQ+0vh>iOtA<xist4N>NSigO`mG
z3fPKHm3VFE-hANIi*141?*=lcus!X5RXA_?s-11!hgM{6SL<t!dU!xj@<kU5U-_m#
z_2)`#>(6O8Fn{`Oxa|3k=Q^J+KTFOwu&9-bIC9NcHfQt3og(KMSXq-U#<I<2$mcnc
zC8ZxIV-dsiqKvcL%VN@slv|P8TK;|h6JNi--G)Qor18AX{mI*BvdY&UU%g$mPM+n1
z&jil*hLWEuH10o4IvGE$ZpEveMTJ&V$^$A3>+aNG^%_6npnWI2&Ke=7X|(yB)6U
zS-FZd6)5a`q#afxcae8-jL83qE>&8Ja)t>71<##QzUaL;f5&|LA{LJG6O=B$-8tuV
z$Rn-TgqUwVT!n@%I-AVru--M@=-=k7ZMh_ittV;ao6Vs%J>kMTN<H^Be5;sY=KYDs
zO0i}42bV|1Z2l4#!Z>(lN~*6mic<XIHSJ~h^WYv=J>ye)JgaZ~lbmh6XgM>l=Bv*+
z>yA`w3PkPV-+864QK@RxMFUNbWp~>)_VxH$PD@R@Ips<At&KCfOCv-J_MJI(HQ>6B
z<u?AiYt^ca)aLD&o_O%n)x9le<W-hbmw)9Iu?_gT_$ynK%mYp49bGQ3yO?)#{M6LR
zs{i@mR=(kurXQ~Z_9&K5OMR;Ja_ZbecQ?0BFn^eJbDz=Q+zr39wsuYCQ+wK^rS{Y5
z?T_LK_oXL13kg}X>+^?GE~h)sJO6t-%YyYW&y>b%Y%AU#305sg&rzPjXWGYaz?QmL
zl;_<Od+wrYrc?GTPZumbx!-wa#=?d$(TtOqB}FsmG0pn^YK1&o-nw7^y-soXpYXV%
z!(10JnQyI*pF`wlr&O1^s(>29iZXk}(*gG%m2GVP|E)QxRrbMYfq#rAzOHjlYPX3J
z444ou^5aL5@89@o(|9>-OdpFzDBV}8d^7Q3zIkWt@vR5$wp4sN{+d0kO?`XlU*AoA
znGar82l@G*_;u&j9;3UeC!WhU9ABO~zshBox8TBsRe_%h%IDhctpELLL-x&=6}w7H
zZzLw#Iv;y5vx2eWkNA##yl*Ep{=TemUjOZyOaFf6C4LO-o~}@{Jw)he!~gFNVijFn
z?_QZX%Ny?txvXBNf2I7wEEe5fu7!5rwp!gfym`X?_wBC=KQ(Nq`5_jg{6WT!zi|6$
zqx-8fn-_m#W_zb}KYH@_?g@1!SFWvhl8aur|Bt|{{~jIrHnqpNPuht+G7tP*^T(a{
zy?pN4U-i<rzSuke<y*Vt-?nA71<!x4Z#yLRy+b%epd!mhQA@{$t(+sfzx;q}_DXk!
z8tV`J)1s^w_T*(uUhkRvTQB2s;Ew$E8p$8q8+|^o$Zp~J_0I0l+NU2_=I&i+Rkz&l
zzqQisKCfNo-_|cHTyp0h+a>enJr^&n4y_AxTD_q0?W1l_uWKKdD)h@9>RO;A{ULs3
zpwqiXD+7+t4}OX6h--WOyWlU&I<XG#!=kK~GSkjKJs;J=_K{iRbL51xpI2;U`>uSG
zt)Ahdw`rHPO{F@gNxPzq|ILGwOE3I-zg70p>Z9K-Y;K(9*?Koc^n%p;owHlb-p$_h
z_u?ZyU71@B_w3tWpKNw&{#W+mru*uR@l8b^zbrbwbWM9|m5pq=)2Zi+-V{&g>zrK7
z=3L~gt-WQ36Zi4&j@#<lit0E%B~5tW`0Dtc&<KvNkIy&SxIg?Q`=WZe!XIk`y)%dY
z8W;TKjHzGAdA44D%gf3M$Au@D&ogLQF7dT-&HR?4$(MF57R%6Vzt*w-gueFlRQtoS
zk29uzzdzx9_(Lb|!|R*p=*fzNg(e5^?{<x_Vtv8zua51y{b{p3&cb2&`Of#m8|2n9
z?C0H6!<g}nNq_sn(kEhxiJ}iaIv?WFKcH~y^VJ^VjM`51sE3&@k3ZEmtIO+}O7ws1
zR+z{1mG|dWqXS|OHiim^m1RtQ*7$p|*vHoP?aYGlZ}T|6uAblihwa2~ofD~i>uLkG
zPcG<nUH$Rkh1G9`-^sVXs^YdQHd=q5$2R)th2ok;&tkt!nesON&C0fgq37Pe6Q7n|
z-?fQpW(?oggWH|n{_~mp(PqP&!}?Qxr2dQeoHZ*dhAHyC>Tj+nrGHjiK1K&jKdiuC
zJpD(N_=EQi^A9V|wB;`J_mbS(`nhA4;rB^ze*gH&|2FcmL%-PaAE8ec#vYnAY5COB
zN?WgMEKx@F&X@Kp9KH}Gxt8PNDoNd$-<#h|p75Su>WnLMjr=V^fBtIsPe1goyft5t
z*ZsT2^bz;kN8NwrwM5q(I^M=#r!DyNqOo3m<NStuw-R5wK5I-)v8uV-8oDO)xlCbv
z$)?oqtM|%HuCT9jmRRxpnzFFhj;|}tCJ2XftaUD(_VaSu#I^nsEB;+u9KDh&reCUb
zs`Lu|@XWl16|4I1a(rCz*7*9hwO?0ipE}3;Au6;dZ^8SVj*P{s-Fjh)B6D{oZ(UWr
z_J+gTvya7Ryq?*2c0OZGINNM1tN+WtB<`<S5|G&NStust(VvI&TRL@j?)2RAq}=t$
zv<dIsj#%GqD5&ZGA1+)k|GDO)?U$4#yGpt5E8bUm^w@6SoDa4;JU%$^MtpIws*&I8
zd}P{|U_m?e=Qa;^{jBy?@}DE~aF(X{L-(3V=MUMQGgUiz{6}k?qvONJ%y|<m`Irwq
zmER+FlXLNz-w%?0tTb<_*59$eOnuF%14kW`IPcs}6#2!qqr&OJ<p+;WGEP5mmrrvZ
z`}a^AY37(K`}T3ZW9|4KUNHaA#TWAN-3yj&dV2P{(h6Bijy%Q}{f)m}b;R$uCp_6D
z9wYNdui>}V4pzziEgv7$vBt>!n8zm0{?PkUtz3+ZPCV=O`EUB(Fs^&Fq*=v7{iTw*
zdznj_Tbb)N*C?fn9bz|mnIF_ih}gF<nh0ff-Eo_z+<ww`;&}nDUnew+T1?#EsYEM9
zE3eI(wr&9y@PX6mWzx#M#`E3?$om{jo;kDcb&MO+h3nUu^TL%Tx|m<Qd42Mehe9eB
zuiu^h;^phtZ{8_&o=Y*GaCzSAGw!idY~#x{Rp+gp9>Hv7!uNsav)hIe<&CTU9{*Z7
z&3LWbq8(8Q%-_G2t-tzjZfxz{O@FI@@3P+bclYGl*otLucn_%M{}1W9=lfaRFC!`|
zCFenomDJwZ+x$x|e!IA1+0o1VJv}{f5`Nz=S9Cp+<MN#?u_xcc^z6%m6$flJ_-Z4%
z-8A>h&xx!&Z64p^+%#93Z;FMPO#z?ruE#UZZ0((Vp!MdfD_eM1&q<X%{+QLbIUu}z
z`fukeQCpOgZ^`CO-1a<d$(2PHmgQ9@rj|WyaqFyFckrfu$SF?taPzZQ`q$-6j+E_}
zo*35tsaN-Eg04V#{RFnB(t96AXkBGn)AcN4@mn{IS=+2dHM2!Oeh*)DNrPQdKILF=
z)<UyMIV`(VuRT*)u);w3Qnq%~cKa1Y8+_Bx{&6yK>|1Epl$KidzpJfHX2atxcTY6y
z*=>z5{r9;p@YDKqN#5iC&!xma{mY-<kP^;x{QtQYssH&LdjJ2vldpe$GrB%Vx~|P+
za{oFP&kSL!?KZ1&ns2x&{5vK3g-!2K*CBN-`9rRq7Q*b`&pr^7%_+WP)A75upjnY`
z%i2wI3m+@x>D|%X#c=;X$871sWaT`yJNhpR4lCw)9pUZW!721z@-E-?#2s~w5A=&U
zcLf$C7sx99cpcO7Ah2LZKf8J0qkW6acJz5i{W)s*XDZX5RK}Ra4}LW4ce>zuBr@~v
zq;=CD=obnWbv@885Nwh*ws-$<eLKg_+23;=%lUUy+&ZUlF#ev9*p$Nsy#jxp>N>rf
zT2gV>AEf60)Q!a~=T`_xtDiq?${HSZ>CyVSvj<GM#otv|O?a?A@1cI~$@{0LmHdx4
zaFzM-nX`4)?FYLa{n^6%nBmI|h4o+i_<ujzIQ?Gg`+WkO{o<Pgc6mSRboX*mXG=Wb
zDfQ#R!&@h$T0X@)iPwJj(zx&TpvFskwxh;f#qIz*=KEKZ#WTAeY!=?x^=W(iDS5TX
zB&XQ9*;=ymk1jhA79?A4KIxgmia#7%<Uifx5pGmo`L8|Q{e11V=MNV?{POp*@Z=)t
z(mmSuPMXi=U#dRwnmN~9$GD1myFTk59$PkL%e{|kTKlnLbMn)F<vh34o-clJ|IqS>
zFLqZRJu_Q9*7D{tg|)k8&RPCUIQz@iwr7*(EbfwZdi%~+B;?-JZr5jWUtiqZG&7Z*
zE%M%$+{@=Kv(Me+tscv+$+t9S*>8zem$&fSHTQK+J+V#k+3RIb@19jZU~;xbrTNZ`
zvoUwmBdwwn%+lN{<#>u_81CJackxQ6u;ah&epBC;i9}D(ottF&%;<JPJNud-$MXg{
z#Y=Le_r1Jv^~SZtSK=|t=jdOU=rL=VmBD4hyXU5VwGl~8uhdiuo?Q96q0)Nw?uQSa
zzQ~+&Eh6XTnRx=~nX-rXT>En2Z)3gsFZE+>&A+YHbnl+G%=@U)I%D#l9f}H)MLkAx
zvlb|?zs;<)<mZ_Q?_NvZ6<*V8eE#xhjjJZb;y%rlxsR7Uw3;{hbLOu<68vdX-2~2>
zytTNt=jDC7=nJ(wY>$g2nu;!a*ZcjB>B`-9zCm8jAqSXcPl)+S|6<zG^SFxL;Hts5
zRg<!r{2%Y)4J!W5_v%>9&Lfd6e$O11osRb7_xG85b7HaA89UGCVmqI!y<haYdj|7~
zX~!q~7%xt+o;I1ivipR!V_Mb8_s=&;YcS^j@!%|cbf$!Hm#bKdLdMbm(*$4qGFFQg
z+5Yv=y37Ru0RaIV50A%hKXEPg$=`2Q9+qY2&P<QBoACXz6<grfpv*tAU5BmgZ@1~q
zs%xAU^E|L3@$wC}W#WbvQ-543m9byPD^YQa*YwbwfXkC(WTLIE-VXchw(R%^*2zm9
zwwndcUgpcy_u%b=?v1xo|3;Ze^{Vc^WxP!P{?a0;N1v`AU&)dpDlB>`(rVAMWZ9Y(
z<r&9+NW7ild#P`;c*gM-{_thpWjq%pLd<T8KE7A%e7Ko^j_5y24*6L#d=KCC&=h;|
z$jgn9Nv=i5O-8Qc;?1u7jxq_8V>4w+=DPCVShXi0F!lYqgR_G*6&_0(&U9AL`*|%|
zJM-rI<5%|N9^egHern!(5zYBu*Z62X@?ZQwM*4nnr|MrH-OjL?0YBG7Ec&rl@rvoP
z_T%dE^Su1a%1g_SFF&rHn)QOkZr({3|N9jyvw5xGaS0#3!IqJ3=ArTYxby;^vsKBr
zX0ED9%nLt~*_nDvA?a|}W>vTMnF_DAPCE3za^4PE7H8=a0jYY4_e<R@K4%oz3-5Z!
zb?j8E>($wnBB!7C%NPjsAK$u4E9%uTX5R9M)iDnv>f{czNWV!~F7)wW<I7OlH*zzM
zSYA2#bV^<1!(jexlmA?NTAlkT<l?U#k%0jLI}T>7tGnpff9b#G-}zvosp-&i8L$7#
zztkfLuGzv~|CcY=P<hd5*2y0?YIkf6effXNKYuXc=$I(%0A?YG#A2tH|3yU1^k3bK
zKQA=-hRW%;i>^EOn7Dpe)3AD@{Xf?~>TmnqPpZTefB0{+efj>VH%h+R=jPn-m?d0#
zYJXV9^?*A66@NrFI=qwnbGG4%q{p9CPwTHft+xxQGrs9GD=|sbH*(kW&{Cg=|JUyL
zWo%#<kiC{~WniG}ywW?B>z7FP$g$p9{CA6S1iRelTZ?AMJWq|=G2_;SW0fb8+~3X#
z)-5|P5S=hBSZLPaoSPqP*RHx@vnT5JsxSM!{;&SBpNorYHXoRUAiyE8dclUuj}N+&
z_@CdiGX9f0S={^Mn((d(Vv{BnKdUPFdgw!s@4x1=f3}>hzb%w=;EwDv*`%38b-Jh4
z>i)j;@}TB}byJrtD>Xm=C$M7Sb!{D&eM?jCU#Q*uXg@gIFa6il(9l@Z2IKsNM8~0L
zEg+ekIF?`g@79Pb{7}Als(SkD%x>#EhrOYD+AmfM|2wjfXLi`P`>^<0u;9bVMx4g%
z|6lWz>wfz5O?w2jXK$O+6TmLC2ocu{7JOLQgi9}vpqtSWpHCl-cT`_}`F+B&6JiC6
zUFI<EoM`g>;r?33pL~W3{wPh!6P{lY9{F!yw#EMftB`+R4_uvAzxQLkX1wy*g)tZQ
za;{suc~`!O6|;Z%15Y-&ufOeKp}b(h2hP?@|F!<EM-X7|YiZ=f<vf+Lsrfb)n&v=>
zOT>&BmIR>*PsB`p%0GX{#LtULHeR_W>0fq2({)pFRz*Tajm10tpV!y+uq@cVUHZ;C
z7p0rc-{;oaddl(Ld$&)o<2Cd0<*T=E-#pzRpuD{4!jaO)3m6lOR_~r7bpD$68b(>I
zQ#Ob92<qJRxDtIdR@uaNac@KRiB^kNzp(iQH;%f_dRMg~-TSxB^4nk5JpMf|@WR@k
zRi1Jd)0;vwS25_OU##{${V03eCjRclTM`#d+9K#)`Ap=!;hu_{W{-5DuWfm)$(?ZO
zobmej%T|v$HP*;JTeyzhJ9=Y9+s{;k<fRT5H8rOtd|Y+-mSumJuk-evO{!^|#82~R
z)NVep=hdriE2LRx%&-3FrTaB!+VcsiuI+MXUy7Yu+JEV2Q|18?@h6>vX5mdnTpLfc
z#V71=i8tzA#(#z-@}$so?+NysZXAugqAQ>$(%4yZy~XO#6D#h?g|aQYufJ{T=Wff9
zOp-n4K2Q5_Z>o+`^2VgC4Xz=5n{(u{Sz>gort;Wk8Q<MH&5<Ku7Q6OW3xf$ycy63i
z(ry0ZQxW$zIX9x`yu-R3ZuZOPTXSaG%zqhqCir-&k7v0rzsoc6lKFbC=81isqcnMv
zPGh!Rn^N?Z>5s2(WzM*jF{kg=z8{iRmp3lFd|0?3$c)WP=XK#Wb?rm;=Tq%gN`Ky<
zW8b-pZ|^1V377PD@a!_l7g>|A_2!1HJ{&rR;-c@I*qdbM{QMCj8hHOrVWCBg<D|>0
zF1>r+|G2QD_1&X|lT=UFsO>Y`;%&c8Y|GBmw>_V=-756fFML|R_&LwgH#aWap4NOS
zTsrET{lw(MJ}!xcC$pEHmi*IrU3K%LzK=HADw5Cijb3DjUh}`yraV=0xlY}r^dv)T
z{?*PWmxUL^+`IjNag%NL^jik%_g;4WvbnM)>g)o&O<Mbs4+=N+IBl3|%v&3K^0i*b
zouUBFCp&uCV`p8CohZYm^1^T7rIOWW0_HWJ4hZqnkKVUt^P9pCGb&BYrurSvIHq~~
z$HFE(i!jOgGH-fC89#qppQiJB(GLxikNe-sW)|P_`1U#IX#ER=;E#b_JU?z7IUFK*
zK<;|NY{o}d-kqD~t#C7gxnqUmjoGK_@0XWsR}nbEczoqb*ONRKj$eL#{rx-T{QE_(
zP2Sy_HcwqhyUu#S=~eUIwAmT<CQh(q5!iNlKerRdJ$9kO(!lh-Y6TNzF@+f^N+K@b
z_%c-2q=&`lW#|+(>aY485b65$)?u4ShElPzb91c@FnG>%J-JxNDf?CLu|=j#P1TQP
z1)eqBe({!oPoBKb0gf9UTV}71-+xN{A7B2*Glv9t%CEH)mYb9oI=eGx-t^p)8@N%h
zFs^U&<ch;Sd$OAURVbfgV0xy-^1AWImSc(;D>xH+K3^$u+ozpzFjUussV?hK(X~Yr
zWe$3L+iy3i+*y7`4AWf!0h669Q|1~l7(b2p_;I2qvr>6(PUyOrj%oGf;#Q0AU3;yZ
zaH}|AUFmbiH@w##f0~i<_mrQ`w_|HGp4Kg5kE{28<nc7Y%EG(1uQREt>a9HQ?Ww_E
zEf4jH>lXHEK6Kvj^s>Sqg~p>5ioxpJ1s4T9uQ$mkO1W`2`KHScqZus^`Vtt`#D$ek
ztz95-|HX`?=VF=e7UiCHNx$4u?;P<-{>J@i?Z%z<Z@#Io6HiS3F7&Ezb!3@I>V;!U
z_wMdfUOH)e^j5aDvVBiZ?UD3wTCg$Ud+pB3%DT#J+6jjOI{kiS%s+6T+3s_`d|K6y
zte!1v=3iMR7bGg;&!NKav_buFf=<8<oeQ60*(bKSeW;(s$JT5fs(RwASK^aqHwDYR
zyv>XURr^^2L&B!S7$!_8;q6}f!q3z7x@Dbrk@O}vbp~0-+8x}rs&T>oR`VxrdK!1f
z-?B_l+_3ztv5NWhEot(PcgB2~c-eK;%Z}|1Z*+6H9<hIN{~77E`P+=}E1Q@;-1#}d
z_DBMY*cagwB{`>#xs-g$?Qjz3<T`uc%#1yHADDO8CUJA_YL&TlwOVW2mM1wISrxd&
z_6p9}diV2`fQFs}vv*GxFu5%u5m1%fQp#?k&ie1wsuc!d`xHGV>Q?w{v=y>&Zpc5s
zzxiPV({~n$qlqHkXJ$=Wc(s}N^7Ef5Q{AiDUCui;dB{JxuzT-OPL{oFF~1gcE?i==
z*yQYm&lj$`&uW}~`+MM1tHpuwyZK*;yYKy$^n~Hu**Wp&ed4FyIPD`-7=1-Obz6nq
zhTXF!YDTFlTS&&PNlWRjEa;9X@h-kOt+KU0u+5_NqQZaXLgN*UPMJ#=E%w<JGLf%a
z;Nyg@l8{<A@8&sz_GQYF>c4Ke-E|KX=DS+zwxhOPgjrKIYsJYm8LPs~XFokwDY}yJ
zout#DgB!XO|CQ+KPBorqW#(D&`okhdy*eQgP8$iP)v99ls>y3RmVfx><Jhv_V)g#)
z<2Mg7@iOLJ+@Wro9MC=e5!a7zYu2q1$`?_pxhk<#!so#4mlY}+2GiZ_Gwe15a9vSR
zmI#WEV)xvtdg|HSfQKvsj&rSK>^3mBUzz2RE5wl4@q5ZYa}U423#EN@mu)+&9hCRN
zr+s4b{m*|U$R;_IwN#&3Qlwy`S^4@J`}@Y`>xw>HT>m6wMCDeqn5xeFQ&n+B-s|i#
z1CMyNmm%+1gX`kiEnD5hn^Vkk9zNJ5H_NXt*q*1^?|I{GX8o%Q8?MjOKU(8*OND>s
zjX8^c^@;Ppi9I0q#Clsk@6_VfncHO+az8#b(Re~POV?tN1xoL^r5Cd~ilr`Ps^9%Z
ztS6&z>V$-}M<xzm>W#VL{MeXzR7?Jtd~3M$Phidu|CVJM2|a7>@^4d8@K2a7d!0Ks
z^?ltXxh^O1U!u8tm-8J~>iKE-WkCVsT+UnZM<+}C6>Dx%WjiXYac}!U&+oflR39;x
zymH_9(RrqwJQ}N5KDvl#8U_8hXOjKY>MW~v@`Wb5SF`I5Tv0E3QW$WAl|?Bo=<~8C
zTGI;}i`JMd2tCKEHg_Mp;0&*`D?EBP-nz{!P=28{;6an)!DX@%Ex*2<>&#r%qq@v)
z(M7i}3k`d?{@?n)UDeI?-;MTu;is2pn#u1x>z?;{;w_cvmODyM#1yw*$oS!0|HiuZ
z|9+dhI;-APYRtbR_A7WsT;J<s%Q}QDGjgrs>>U<z75s4$Uhrnu1IxUAE(;NvcGXYT
z>c(5;xh*(k8dbT9w<a>OH{6I`)Uj1cm_LnmXUAC{$)6D^`Og-Zl_VP%Oh_>^Da&eB
zncc?lNO6+h(duT2`&&D`0-4*hCz`4pbkUy{(_Z_rbIsx%pY1hQ`w2YS+iB>W{vflL
z*Dg(7M<nCGgvaUXvpi;4M7u<^G#;86+t-?L=Y8{e?#-qBAxynJjsH^&o<zDWPCs#U
zMULmiLKTLjFR3!K4Q4QH_|G!qS%Gb?WZHxt2_2!J3A)>I9zFQy@X%RLOnGs`qwYD@
zry6B$Em~MR{h@Qv_j5P%tcA4aUg>aI+2p$J`WKZB%~Nx2X0E+m*LgH-bHY~cYu*o*
zr(Mhve;943w$W<0kmI^lLaet;7eu-zWc@tG?HnjnY0WRSM0xRi_2PhS@w>PuY!FfK
zcI;40on$l9Lw`%@%tP5W-QiOtwHo*JFHEY++b^Sk=xE8ch%GkB>>+WP_W~ZW$lhFZ
zhjsFSPm)G?mzG$$NnG0%#dl*t+1!28tgqZO+4)3qdWPKFF1;J~Jb5mt9P%>J+@`oO
z%k6+gY`D^=8=}9izOy{s!Pd=Y5q7X!O66Iqfd<Q3_ghJ2DFzMsk^g5#{||ON6THq)
zH~#-=@lQvY*8P`#%HQ9|&*d8P|Fpb({<Z(}9(R`A4L5w#YGEd__T!PS%pdQmDEOVc
zXs`NF==zKU%+?H!QFgO`daihKPC9U}(Dd-!z}54%9}Nu-$^II(TkY2Vx!aHYUj6L-
zTDP4+!pon3z15w=W@Y!bS>fuobLJ{`J14C*pV}2(<?9;b+a4G3>*<5=tn;l)<M|#w
ze|~=c=9&8O`&6{}(zNz5UrPVG;PIFHHhlB{zVAQZpLXKx=QaMT{;|)jJXK!f`d_|z
zTl(MnDd**7o;m)1FaKUX=ga?M8~aXGF$c|%OaB+R=pT&LpP1)+eT8?T>+(lGcH9Y?
zy=nLC4Qji0FL~p#`;JZa|HXmAJCEM}U942kuXmL3+lo2!ran>^Ulo^LH2v(J9V@m*
zJ>4wD{^)~vxS$Nr`P%C$Zxns{FYVZ|Vnv4G!j?-<U4MR`CCa>Xnw-nqdDD*g1V!gB
zIrjh1NrP+3-=;3;+#CJv_XGEHe)%2goQ8!8p*Ani%;}r4%H;Ni2NJLEEG&()o9E~_
zgL$%QgPYdx88^P<1{+=5z5LAc*~b_4Ug&V1q;h`g_k5P1UoRZWs~P1OL;ls&I8+!Z
z?=60$`^v*huZ$r@viprr)8QNI7+QZ$F4B+6+OXi_o~(|r?bXex8g@$4y{BAf=CG1F
zx5Hg@s@vitx4#J9>;4?9SY)5i>|0*6D8x(NX#Y%xeY)GT9?kudr{|}wWFPOdc(<Xt
zQ~K-}-(!nUN-!M>c%t;;qu7=k<{x6@pHxKd-X?snk}D|0wEt$&l1D!tykrVC>~~vK
z_3rJ{tf?QFez`3dKXY^9aXIOQ!AccME{A>Czx%oeCK=q{ruF-1kb7AmvmyVHfaOtt
z&4MTEteL-`m80{p6sJUpJ$LfD2{UIHh55y6X4^cPb#}|Td#2i3FP*>r+<At?lPCd3
zfk%d>yH@hVL>^MrcI>`i|Ee`@>fXQ6o3wTot-1AQ=Ghl%%VKLZEm^0;srs!vG&Q~<
z<5fY4>4p5vWah%vSEIKsRa#zp^AuBfgie9fx1vJt?5%wpMCV1{_*cnu>ESu9<7cgy
zwric}-Sao2a`&319Y=N5jfJOg*y^*rB6I7+42`Bw(>O|u1s5z@I@e}>x<QY5olVQV
zSAW-Eum1Zr>ix0$jk!<XJ)71)Rq@4a$1t`Ddwf$;4PMzijQV@Ms#+yG+p$xnI@RD}
zua<VR!qE+W`L)Z6b0xYr98g-D^kaJA)%p^Ne~0H?`QyL1?%S02KfL~>@2@CX@Y%k-
zHF@fP&74p6=RYo)8yoTVUHhBhxPKG==54n>BE}{3-9F{Nkhnw2_5F-WyYGn#++2T`
zaboQeRe>pUes{+*Py9QrT0!pek6#;gzxoRFXGrbmQkwnKboa4T0q);+*K-AK9w`;L
z>2oIg`n$~^9|*m3J~daMKW+Q^Sgwg@b^3Osy$*8LyPOeuU}}SjaG~m}E6>V;w^kgR
z-Xpp+aK&<mB{!#8XLbMieD#BT?S_X_PjKt=Gz-j%_)z<*B_ry=_5T|;Z>uyr|LmsC
U?DWqz7eCwoxV1u_p+SKG0EWRR9RL6T
literal 0
HcmV?d00001
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/Makefile b/trunk/PQP/build/pqp-tar/PQP_v1.3/Makefile
new file mode 100644
index 00000000..5f1f4397
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/Makefile
@@ -0,0 +1,33 @@
+CC = g++
+
+CFLAGS = -O2 -fPIC -I.
+
+.SUFFIXES: .C .cpp
+
+OBJECTS = lib/PQP.o \
+ lib/BV.o \
+ lib/Build.o \
+ lib/TriDist.o
+
+CLEAN = $(OBJECTS) lib/libPQP.a include/*.h
+
+library: $(OBJECTS)
+ /bin/rm -f lib/libPQP.a
+ ar ruv lib/libPQP.a $(OBJECTS)
+ cp src/PQP.h include/
+ cp src/PQP_Compile.h include/
+ cp src/PQP_Internal.h include/
+ cp src/BV.h include/
+ cp src/Tri.h include/
+
+lib/BV.o: src/BV.cpp
+ $(CC) $(CFLAGS) -c src/BV.cpp -o lib/BV.o
+lib/PQP.o: src/PQP.cpp
+ $(CC) $(CFLAGS) -c src/PQP.cpp -o lib/PQP.o
+lib/Build.o: src/Build.cpp
+ $(CC) $(CFLAGS) -c src/Build.cpp -o lib/Build.o
+lib/TriDist.o: src/TriDist.cpp
+ $(CC) $(CFLAGS) -c src/TriDist.cpp -o lib/TriDist.o
+
+clean:
+ /bin/rm -f $(CLEAN)
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.DSP b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.DSP
new file mode 100644
index 00000000..ddd11ad2
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.DSP
@@ -0,0 +1,154 @@
+# Microsoft Developer Studio Project File - Name="PQP" - Package Owner=<4>
+# Microsoft Developer Studio Generated Build File, Format Version 5.00
+# ** DO NOT EDIT **
+
+# TARGTYPE "Win32 (x86) Static Library" 0x0104
+
+CFG=PQP - Win32 Debug
+!MESSAGE This is not a valid makefile. To build this project using NMAKE,
+!MESSAGE use the Export Makefile command and run
+!MESSAGE
+!MESSAGE NMAKE /f "PQP.MAK".
+!MESSAGE
+!MESSAGE You can specify a configuration when running NMAKE
+!MESSAGE by defining the macro CFG on the command line. For example:
+!MESSAGE
+!MESSAGE NMAKE /f "PQP.MAK" CFG="PQP - Win32 Debug"
+!MESSAGE
+!MESSAGE Possible choices for configuration are:
+!MESSAGE
+!MESSAGE "PQP - Win32 Release" (based on "Win32 (x86) Static Library")
+!MESSAGE "PQP - Win32 Debug" (based on "Win32 (x86) Static Library")
+!MESSAGE
+
+# Begin Project
+# PROP Scc_ProjName ""
+# PROP Scc_LocalPath ""
+CPP=cl.exe
+
+!IF "$(CFG)" == "PQP - Win32 Release"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 0
+# PROP BASE Output_Dir "Release"
+# PROP BASE Intermediate_Dir "Release"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 0
+# PROP Output_Dir "lib"
+# PROP Intermediate_Dir "lib"
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /GX /O2 /D "WIN32" /D "NDEBUG" /D "_WINDOWS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /Ot /Ob2 /D "WIN32" /D "NDEBUG" /D "_WINDOWS" /YX /FD /c
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LIB32=link.exe -lib
+# ADD BASE LIB32 /nologo
+# ADD LIB32 /nologo
+# Begin Special Build Tool
+SOURCE=$(InputPath)
+PostBuild_Cmds=copy src\PQP.h include copy src\PQP_Internal.h include\
+ copy src\PQP_Compile.h include copy src\Tri.h include copy src\BV.h\
+ include
+# End Special Build Tool
+
+!ELSEIF "$(CFG)" == "PQP - Win32 Debug"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 1
+# PROP BASE Output_Dir "Debug"
+# PROP BASE Intermediate_Dir "Debug"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 1
+# PROP Output_Dir "lib"
+# PROP Intermediate_Dir "lib"
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /GX /Z7 /Od /D "WIN32" /D "_DEBUG" /D "_WINDOWS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /Z7 /Od /D "WIN32" /D "_DEBUG" /D "_WINDOWS" /YX /FD /c
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LIB32=link.exe -lib
+# ADD BASE LIB32 /nologo
+# ADD LIB32 /nologo
+# Begin Special Build Tool
+SOURCE=$(InputPath)
+PostBuild_Cmds=copy src\PQP.h include copy src\PQP_Internal.h include\
+ copy src\PQP_Compile.h include copy src\Tri.h include copy src\BV.h\
+ include
+# End Special Build Tool
+
+!ENDIF
+
+# Begin Target
+
+# Name "PQP - Win32 Release"
+# Name "PQP - Win32 Debug"
+# Begin Source File
+
+SOURCE=.\src\Build.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\Build.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\BV.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\BV.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\BVTQ.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\GetTime.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\MatVec.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\OBB_Disjoint.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\PQP.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\PQP.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\PQP_Compile.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\PQP_Internal.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\RectDist.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\Tri.h
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\TriDist.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\src\TriDist.h
+# End Source File
+# End Target
+# End Project
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.PLG b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.PLG
new file mode 100644
index 00000000..f2175cfe
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.PLG
@@ -0,0 +1,43 @@
+--------------------Configuration: PQP - Win32 Release--------------------
+Begining build with project "C:\WIN95\DESKTOP\PQP_v1.2.1\PQP.DSP", at root.
+Active configuration is Win32 (x86) Static Library (based on Win32 (x86) Static Library)
+
+Project's tools are:
+ "32-bit C/C++ Compiler for 80x86" with flags "/nologo /ML /W3 /GX /Ot /Ob2 /D "WIN32" /D "NDEBUG" /D "_WINDOWS" /Fp"lib/PQP.pch" /YX /Fo"lib/" /Fd"lib/" /FD /c "
+ "Browser Database Maker" with flags "/nologo /o"lib/PQP.bsc" "
+ "Library Manager" with flags "/nologo /out:"lib\PQP.lib" "
+ "Custom Build" with flags ""
+ "<Component 0xa>" with flags ""
+
+Creating temp file "C:\WIN95\TEMP\RSP4244.TMP" with contents </nologo /ML /W3 /GX /Ot /Ob2 /D "WIN32" /D "NDEBUG" /D "_WINDOWS" /Fp"lib/PQP.pch" /YX /Fo"lib/" /Fd"lib/" /FD /c
+"C:\WIN95\DESKTOP\PQP_v1.2.1\src\Build.cpp"
+"C:\WIN95\DESKTOP\PQP_v1.2.1\src\BV.cpp"
+"C:\WIN95\DESKTOP\PQP_v1.2.1\src\PQP.cpp"
+"C:\WIN95\DESKTOP\PQP_v1.2.1\src\TriDist.cpp"
+>
+Creating command line "cl.exe @C:\WIN95\TEMP\RSP4244.TMP"
+Creating command line "link.exe -lib /nologo /out:"lib\PQP.lib" .\lib\Build.obj .\lib\BV.obj .\lib\PQP.obj .\lib\TriDist.obj"
+Compiling...
+Build.cpp
+BV.cpp
+PQP.cpp
+TriDist.cpp
+Creating library...
+Creating temp file "C:\WIN95\TEMP\RSP4280.BAT" with contents <@echo off
+copy src\PQP.h include
+copy src\PQP_Internal.h include
+copy src\PQP_Compile.h include
+copy src\Tri.h include
+copy src\BV.h include
+>
+Creating command line "C:\WIN95\TEMP\RSP4280.BAT"
+
+ 1 file(s) copied
+ 1 file(s) copied
+ 1 file(s) copied
+ 1 file(s) copied
+ 1 file(s) copied
+
+
+
+PQP.lib - 0 error(s), 0 warning(s)
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.dsw b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.dsw
new file mode 100644
index 00000000..a1af0d1b
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.dsw
@@ -0,0 +1,29 @@
+Microsoft Developer Studio Workspace File, Format Version 5.00
+# WARNING: DO NOT EDIT OR DELETE THIS WORKSPACE FILE!
+
+###############################################################################
+
+Project: "PQP"=.\PQP.DSP - Package Owner=<4>
+
+Package=<5>
+{{{
+}}}
+
+Package=<4>
+{{{
+}}}
+
+###############################################################################
+
+Global:
+
+Package=<5>
+{{{
+}}}
+
+Package=<3>
+{{{
+}}}
+
+###############################################################################
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.ncb b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.ncb
new file mode 100644
index 0000000000000000000000000000000000000000..f74bfd3b1d5d6f97792d2e80eafd5033771bdd8a
GIT binary patch
literal 287744
zcmeaxOfJeV&QB{*aMpL$)>bGe%1<v!%vDH9EJ;jCEKXH0(lapN<&yGpXJBApVPIfn
zkYsFNVqoC;(9W34FbYOPU^E1Vb_no+obSN!;e#y00sepgN5N<ajE2By2#kinXb6mk
zz-S1JhQMeDjE2By2#kinXb6mkz-S1JhQMeDjE2By2#kinXb6mkz-S1JhQMeDjE2By
z2#kinXb6mkz>o_8(BwZDvoI+9|35naKjb2C)WM@6Fd71*Aut*OqaiRF0;3@?8Umvs
zFd71*Aut*OqaiRF0;3@?8UmvsFd71*Aut*OqaiRF0;3@?8UmvsFd71*Aut*OqapDB
z|NqYu4H)mvE;0w50>I13z@VR(n44P6pr4nVq+gO)l%86WnU|Ii;pgV3l;)(O^Yz`V
zV$xIdb7KMm1LDgJV~UHCV?v5DT{4SH^fHh&VpHf;nwgVAgt9Qb<bnc%hJ_JhQb-_S
zRqm-JA(^?UgcbTGmV~7y6ISQ%<P`6cS)7%hnMXvZ1Ox^U<6n?6f*}lw73ciig3KHu
zyaQ6~nOBlpl$V%8*i%8N$tB=uCL(U&Y6&_xq$rcH)vyFcgw2p723H74)cOH|0SdYb
z;hA~HMhY&eNu}wK#DzsRC^aWFu{aeXUzS=_oSC18kq6u{^8lK?kj$fxQz2@&U{i*f
z2e7Lm!X%75fW;*2c>s$-ta$*7Iy`v*i)v8fhDRFizym2G=wVQ@#-0bTTO5xg4`5M^
zBVA)riJ7jkE5e$i@F+#~y|YzJcxIlZX^cy1adt_50kl-sGtz^U%-B;Uak@yf2{XMC
zv<AHZC#(S@B@@zuJy{ddg*A;6(u60$6VeJw*66997(Jv#5$=3Jgk88Y2_daGattAD
znAwL29a!@cvHCI?%o!LM;ushhm>C!t?lb;5^k4qN$1jXEwx9)*znB;pBpDbOn%Ec^
z^cff!1X&pv)EO8UESVS>L>L$tezP+$m@zOg$gwdn=rS-c*sw4#C^0ZFSTHg$fEruR
z85kIN7#J8{GczzKFfcImGBPj-FfcGoWMN=XVPIfLU}a#?WME+EU}9hpV_;wqXJBAp
zV_;xd$jrbX$H2famw|zSi-Cb5gqeXshJk@0fPsO5gMoqJ6)OXS4g&+jbq)pwD+UIJ
z%}fxzTiF;G3>YA8WM^Pt=w@YL&|+X<$YNn&P-b9YNMmGR;Adc9&}L>}kY-?DILOYx
zV9LP2FrR~g!IFW2!Hk0e93Fve3=Db<3=GLk3=E<S3=Gz+3=A3!3=Gli3=GB$3=EH1
z7#P$*0R%ZOj^REd1A`FApKJ^ah71f0Qp^ktQVa|Xyi5!X!VC-y{p<`3CJYP=0*nj{
zybKHsA}kCHiVO@4TUZ$wv>6x}HZd|V2r@7*Y-3?yP-S3X0J)u&fq~%;69a<;0|SEs
zI|G9e0|P@Y2Lpoz$lVMK4BQM13`dz67~~lk7|IzK7&sXi7^;~W7-XUD8l~VNAR_^e
zb_E*-M{qL#E)L<FGFX9=n>i%<6m%GL!2CN5;OJD)X3z%nZ!tmm8Vnj>z6?~oCW9uJ
zAH@NY*J98D^OYn((dnRI$6(LE#=yv+4dvT2I54m=Ffo`w`3?+@3~UU{48anhGY1(I
z0vHk**cjLto-jc8JWOg#Yz!O>1(Fbc8{;KLHU?e>Tafx@1_f6J9|krCeuk?cJ_Cb7
zBf}O3Hc-Zds^7uzl!1*wf?)+nzJ)=doS~M1jX|104J!YKL70(^L7u@E$`@nwWn^Pe
zW|$1+-(ciqVq?%`5afc`|B~SY0~>=L!wisloeT<j48;s=42BHZApUy>g;a(t1~vv0
z1_h}4PYgd9*cdDs{)t1v!<@l_fsMh6fdlG)3kFLDHU?`3At>Jx93M6esZjgF8S5F@
z7#tax7}yz@7&sW17&sZ27$g{&7$g~(7^E0t7#J8*m>3v5m>3x5FfuTBN-!`aNH8#b
zU|?YQ!hoRbBpDc5B^ekFGa}T1)IX76U`S<PU?^i?V0bS9krR+)VA#QkP`gh8VlGI%
z4Vv5!7F4w$J3)4>kYr#uEy=*}Qj!7e#tKFThGs?v22m~s25Cu%JvB(?g4n$h*wrHY
z5#%qJ+hjQ)=D`#BC<A8*Am?Y0B53|%&;u9pOz`xg3$DZ%7z{vXfLbvq*fKbQb0V0}
zz@T6VuI!i?ELa%87*rmB%u4`OYYGes`rtyEk)aR7XJAlpV$fn_U|?lPhw@Fp`q>zS
znIQSeiqW1CRFGd_gz$A4&A=-2L3~vv1#1R-22ce8ig!@@TgZq=Zy+&H+PKZg!0?HY
zfq|Kcfq|O|lIGFHK<Z#=5aixbJQ@NcDFh6l^);w|2KgIS--GIR5Z@mv56k~fP(G+V
z0FqaS@<H`Ih!3m(QS!e8TK-Q%%l|D53MA!!M%v_m9tHte`NI&w5W&F1Aj$wOe;7g-
zLKt`$q!^g&LG>&*0}}%u0}~@Z0}}%m0}}%e1Ct>y0}}%a0~3P)v_58IV6tKbm!Ih6
z6R6AqVNf{*s-HpiGz^2pDw!bl9f%E5hhAoZ#L>k-VLysTLx9u}uxEm__w^avz}-<7
zX!{<N-$C6|b7=b>l;1&oSbhhU4<J6cerEu+)*Tsm7@+n0dj|$r23H0i23CeGOrUP9
z1A_~L3j+@W8-(A<py0(2$iTzE&afIJ-|V2^%;3zx!@$Ad!~|&%8#0(M@Gx*P^nv({
z4hmKb)(kuhTnw=wK7)gT34<vE4+A&DR4Ct?!H$84frnu>lyAoXat|*<F^DhWpkT^i
z#=yhC2kuS_wm2x5F<3G1Fz`d$9}Wyo3{DI<^M4BiBL9Qh+0&r;p8=Zx8F?6(7_j7j
z20G?{Mg|6XCI)c$3NtW*%PLq}01Yd^*ywZvRG<+=JAeofW&{z?0fmMJ7VroK2Lpqn
z0tW*JKGUGupj3KskvRh+1H%C(28M7c(69m%gAizNfeGAngs6JC-YXQ;uZQqxN`i(*
zKo-<)EC##l4>JRUJqxH63K9i53Pe+Y1(?9WNUjN|z7~Mp<-@|j&<!0<VPKd6HjV{M
z!U&j8V0<JRG?s+KMKA>znHU5F7#lhm8Uz?r7&syE_#c}8Z5dp_{c{s$NO|DS5DOl*
zK`swK!#J@1J}Cc#_^|pOR6c<Cpy3@s1_uR41}6p~21W)&W=MW^VsK^<0@apKz5{~;
zgAfBVgAknW$RNbP!oUpWgT@1d7+4uJpnPWrR|X*lHiiex3=9HH4h%62F$_Ws91uPW
zgF+%h4TBH^7eg^fp20!EpCOb%h=GS;B9tG_5Y8aPz{_wN#AkG1h-Qdp5Mtni@);Bw
z7%nmhG4M0Y1<5lxD1hpJAqD}4^&mc@gF+-jB!duxAj4iLKZ+rWL5M+!AsFmF1{H4x
z9|j=?VTL3q--p4EL5M+w!3E0qV(?}VVi0Apgz`NZycmQS#28vZ<}o-ZgfWCM2r-C*
z^9dukKV`xo#30G=i3!sGu>g$)Fi1oD`LI4eD+3dF)CAN95ocgx5My9s5Mf|q5QUaU
zpz#1c1||kU22jppVi0Cv0+(6b;Bf&^n*-FA0AWx&14M(`D({#f{qQf$kUmo#lm?|0
z5C*9OVUV6!W(I~_s60pvhTlN@TR*X6t3pJg1halY^P>VE1A~hw1A{*UD}x6^2v`n$
z=>!7<ykvq3Vp0t*91KED3LTg-U=dZJNgWeZ6gh+(IRu<I6kVJIT%0;OIGh9;Jp@=L
zHV7ywaX5CMWvdfA%fb0ESCoMP)b53qieLkYAW-ux5gLe85>*8$ztY4Q80L#XhC~@a
zgVA93g9e3(G>8FG{s}QKC|H39iy0V{SRmtdkp4ddgCvv>Y7c-+h4uFd_5ZcSLBrLI
z3@o5aL%{9=>83Ys0F7ib#7PvIGcY<R7>hG71c^h2^TC7f;8Zm*jsw}cdKV;p-4bU2
zk1NW6bF(8TkQx|4W8NSZ&O`^xSfIghkU}zXLB5iPK#M{vl6I|XNWIO#5X)f23Mqe<
zGOPeiN-!j|LHIWq?=mtlq%cf{^8YY0GBGfuGxS6GUl_kLGB9K@+y{*pF)%2UGE{&D
z=^6N;=Jhc2GcYjZGh{>6KVp2!$iPs@pabQvXWYWbz);H20_DGCe9s6P%r}7YcQEc{
zWMHUfFoE(9G9F`OU}#`?4z;g_p&m3j!*Bq~&tm|UIxP%yq3T(gxR@9iIv5n8{0WS+
z85tOQ8PuWt`HZU=85kxpa6<X{jJ1rQx)@YG8nZJn1hYfRNLf|}hUIL8+1)G%HF>NI
z3_Yw6z8xzA1Biba%0I@&z;Kg|fngOZ149{-9%TKAtPBhwKB#O3xd&thGJg^~1H&42
z28ILdkn$Uu4^qDY)V_e4ja<Kjl0XJDzng$3Wf&Nc+xsASSp5&G??HTBc1U_iW@=^v
z<*ZH6@RDFsWCE1{JD_}3COsz5M9e}EUw}b@n@I$8ix7h;G(F5=SjYfsd7OgswHZAa
zLF0QeAoZZ}d&V9{&_vcgDBp<5g$dN6EMx)K5DEqiz6_v=FiEKX$>4UAJVQ8?zm;JZ
z188C`0Lov(u#o{YaRq8;f$CdP<}_x|#2JjgfQg$KG-0*^ntq}f5*R=eT<@U#W(H7A
zW6H1-%1>d)VgOB$HADHJ_6KO<EDIVw?Mzdc7#M6ATtV(<V^BE7c$txb!JgqD)IBd4
zSQ!}@oEeTn`CN>kkauUufb#c&XFhxw&O`Y=jNy!+Nx#=nehgz4BLhPy!#9xm3=9e$
zOp#0s43P|4?2zz@XG&yZV2EN6hw@{XKs~8w1{EkjmMIQA>Yxtg$1%k-k&^#^GX7&k
z&i|hnzmk;yA2L3{o&SXy6kagC!=3+y85Bs(|4dBmgFgRzNI}X7P#FWt-=Mq;VpB8!
zgXU>K=EBT}(I9(Dpk*9LjSo^82P&^%<rhdDE<UIX1DOpfpFnD0WgIg9BedLujc5I1
zV_=YCN5wERPC&~nkbaO^AibbAC^j}o52&1j=>g3HfYcU4{ef%-NG&dLWOY_hy)ZLj
zG)N7I4U-4)1=vu_bz;Q8{sAqY#J2ha%PLEdGSmeh*cHWNU;BhZF^;uQSX9GTa-gqN
z!Kap>gE1F+U@>kmtp5Y8$N;T$05!x6{}lWMt+oJFiJ(;=pj8T>t}tk&18fBZY{dg?
zr2}kb18gM)Y()vkT+m7n*oqL4nV_x&Y{kbx=n4ne$_Cg<2-u1e*a{Pn8$gXi*a{HX
zN)p&g5AaGA^znXJdjM9y|Af|GwhR{;KqDof{v8_!WL^z4&#DKS-`8SL&;l<eVPI$h
z@fkql{h&oL3=FXL0&G42wjKaBUoe3K)GC0@A2Kj}=7zK<IGE=%gBG-$g7Vv$SiwDI
zA1L2|DHFT^=N%_#e33!HjM0S=RR3>=@+BB$89@s^GN61eMo_TJF<gQ26&Z~|)jmTn
zlrO|6$_QF`!odTve-SgN_p8J3m;+*dEyETD&;pj@P<{wQ6}UZM0oA`9JkoE%-~;7<
zW?*3iEdZJWRd2!I32q;3gz~)^0zr#`7+RtB{bliEWnge(SOfK6DN_p*1A`~Sd+2(B
zvy8e-3=BaGu=NIBi~)=c3}Nu~1R;!3jG+2m1*$%lv4D|*A&DUuYJMuqFBVXH+!4zE
z#hk>#z)-}{4^>~rc#4sMp%T1S;1)Ln1FSq2=Vo9~<7Qyc<z`^8;fB;l_~b$9<3ASz
zLj*SiLjgAf14w@pHv_{gs2R>sGg!G87`VA0=7IEp%HX>kkoGEw53&Q78KOK43~D?K
z4CXux;86bxN<*9s46>XI42GN#F=Vq6pkg3%K{%KPxBDhT%>~sJurS!c&A@Pw8?hb&
z<W`U$Ve%k9B8L&kk0AZ9d1cVr26R5i9lBf$4Axu>44zyJ4B=c145?fU48>dw42{rm
z0l5>G9UwR0lLwhUn~Q;AB^Lw3b}j~nqg)IOm$?`i9-<8oq(bv6Xgm*8(Bwh+u>4;E
z<-^7UVC4mDJOH+SfLi&VT?&%_AnBbGtvnE9KrIg>8NlU1CW8W`JWyglEe})~P|E`~
z2GsIE9j!djL@N)p7*NXtQ?&BHiUGAeuwg(g4{XuO1A7M4^1y)swLEY{D-XOG)S=-4
z$-lu2Vo*LL|3)*|Liv#Vn}k+=WTKT9xoG7@Ap^L)U}I2#loycvPbh7J(jF*(;!B(O
z<Uwf@WCyPN4az?tI|h3h0dgb0JV;0$6b`uZD5$)Eg)e&f1CpbpYystS7>3pNu>8ND
z2QvN#%m2~5kpAN-hST6l8*qMOU|={0ZVzz5@&^MqBR^;r7lR{Iy+6Y#2GGJ)Whmc`
z!5_Sc^*Rs4JPQUJ2G9b|&rm*S{UK-!lM|}mk--hLSd<|L%0JC;mI2h?zW`Nl0$%JX
z1IsTAF5vM3HE`bn6s~o=xXbvNypTF#D;_nlI_4rTYF`AsZvwIllm>96Wl((rGNXZ^
zk%6UwfuRvJ;RYUe1jPVsa1S&Z2;!56BZ?v8b))lt_`?qt%A@mti1|P8`rjf3)b+n>
z7!**}|4w2cZT+tTgMuc$^}odg*8jeBPynqcfUo~$Bys&OBZ=#O#i_jhml19KFDrrd
zzswE_DC>V29TbRO|C`Uwz?2MK|H~}Fz{EDX{uk6Q1+}@6OM}t*KjhFrux0r{qwWj}
z-VFW>pn;4)C_j*)61?riL=Ylh%dh~vy~T+S!q;Z-1h3dN7KZQ_F`QuVU|?W?ttSNK
ze-IzGehAe62l2J}A?pEr8T=SL7#JDspnN|De+CZ*CTRQJfgzb8nZbjBmEpJmsQ>Mt
zP|8rs;K9HKZO=O}6fzVtcz`y82twq`8Oj+v7&sYZLHq^>g$jlW1`h^qhD@mbEQTxw
z4+b8FCs2MFLm7hy12026l%LIz&EUbn2kjp?Fr+f1GI%iXGc1G3=P=|jcrXYs90$3V
z)j=VeA%?+&K@i%1a9~JcNMi6{5N5aol4o&Hh+&9h@L&*ONCxrQ927zs!WcXlL>a^c
zApVbMNMP__5M%fVl4o*Ih+~Ln@L&*UXa?~aLF)m+89W#y7>uFn6Ts$6GAx10hciSo
zcrZvo`zsC%X$)x$9t_e9H-s1%1R5L^<}%D>@L-T(C<pNw92BN7Okwa~kY$(#<xgdp
z%HY8u$M6-z=WtM%$1sn<gF&7_Mi>&F^BLwdcrYk1Yy-(NI4DeGn8x72pvbUJkbyx^
z+Cib6p@YGLL5blAh|l1l(818f;K88G@D0lEX6R+`U{GNY5@KKw+~}at%h1Q*!Jx|E
z4wY|YXkzeSP-Dn|@|zf%89W%&8T3Kw85|V)82TAJ7&I8%p!|M@2@D<#nhdc}{sgdp
zv>3Xe`kNWr89W%Y8E!%OT@2j}9t^PY8_@bQR|XFTLuh{uRJ%AbcrX}4`)dviZVYY=
z9t^PY8wUn=26qMz1~W*1P2YjRj=_$>gTb6(1s?;0APZ>ym^p(7g9U>Rh|l1lV8CF+
z;K5+Y@S6`3el`p?3?2;D49}tRR$#sj!%h&N2~ysBFxWDj0r43?<-HYy2ZJ3$1(a{h
zV8Y<RV9(G4;xmEPyO}X~FgP$IgZK;%3PudZ3?2-Qkp3f=1A{$-J%a~>6L|fE0E2_V
zafagz9t_S5-$WqpImmF3!GpntVG@+TlVK-=2ZJlaCMbUw!!8C71~&!~QHc6O42Kvz
z7~C0jp!~xOhZ#H=JQyxR)$eB5&EUb{$*@rvlAhNvtYz?E@M1Ut<*#K}&)~t}&2S&e
zU(c|C!GpnvK~n^xeiOrH1`h^b26w3ZGKS?09t?gAnNa?6h7}AR4E_x6Q1zP`wlH`w
z1Te%y`CAyaGI%fqGL%F4TfzPbV(5YDU%{}3!Gj@~feR|XfngJPO$ietbnOfyXsryW
zt^}>A0j-Mxt(lQvU}6ESqmhEHqXDh;6=YyC2hGfb*3p30_6jjDRdX{i#c(k&-36`x
zgRT8jXJBH`U|?d<VPIlXW?*7aVPIm=Wnf}dWnf}ZV_;&?WME>@Vqjv@W?*8FV_;&C
zXJBGbVqp3y%fKY1z`(?y2-^L`!1UIdfr-JAfr-hAfr-JGfr-JKfr-I_fr-J4fr-JC
zfr-J0fr-I}fr&w%fr&wnfr-I@fr-J8feBoCdNMFE_%bjtxiBy>xH2#?xG^v>_%Sds
zxHB*@crh?Bcr!3D_%JXr*fTIOI503VI5RLY*fB7H_YpZUFfrJI$J0Q48c^RgT7ZEe
zNdVGU0`WoO;(`!9j0TCpFlg@wXgxDXEol4=d3_N~jgJ6ie+Y;V>c@g;5atnPU;ts5
z86dqNc@PH4gD^-8gh6bOI+z@`@jo7Zh&w@QVdH;W`5<B-8sxrWC?BK-hLOc!=7Z!w
zZUbSEy&ylr+<~kHBnHAD^&oX1IYdoMJr*_B|G>ucVEug;r1ifb7lUS@LF<EH;{z>X
zknuTF@TO1}1|=xJ1w4Px1745B$i$$qf#Dr!<t;<6C`5e}cqf@8czk(+7z4vbQ3i%1
zqLBE2v30~47(B%o7_NiFMHv`4#USh8SBNn%928?<xFW{D@Kg*kW;|V#fnkX#!W?8h
zN&3+90<cURIfY^D7{{Ut`zCQL3bF1B$D$6;R&Xq;K@)pK%&CEt5u8rLy~i87#kjV0
zV^KXi{|Dab3~DwH+4(<y=zd>a24m1lJqB3*2jzFrq$6k@A80)<sJ+3$z{nsB-LI<8
zV88&{?II238!#AxR_`(>L-~dbM&Px7ObpD>eKDZ5s*wGJpfVDML1oM+9u0xf5Ez&c
zfYtv7;KLyx>tjI^<8}-+;KLR`tFS@*K893A(3)9L+b%|&fgx9%fuT;EfnlmR1H&3|
z28P4pkh)q$nt{Pont{Phnt>r%nt`F=+8M?O1_p)+*Um6bU}a!faP15usEpZg?F=Jm
zhW)^`GmIIG3=9{ponZtGjX$_{hA{!OZt>a~M(_@W>t`6RfR2Z_4v|;5eufdW63^iJ
z8Ai~;2Z!rt7(t6LI10{#X^DdKjG%H$qu@NFFoP0<GD84^9s{Vf0+mRC3_%RR3?U4%
z3~~(e3<?Y;42}$-zLPD39fLKvhvv@U#$d%@#$d_d%HYD_%wWpk#30Qe13r>sU}9+0
z*3l54T?l~kq7Vav0;s+R*#gb);M@RO?*r<?z|MhaXJBAh0-6PkK->Qx4qLy2*#8e2
z|6^ldV1TXn(W2-19}Fap|1(f|{GS1B{GWlq_&)<=Jc#V`KSH46|D)%BfX^|(HvSJv
z+oKpW1YqlTVEG@{`5*e=L#~(@r1>EIc|-7FPAm-KP(Gynzy?0s3e;YJtQX>7VC7?A
z;O1k%NspfYiKSx=>e!F=|M3mujIRF$ZH59borRx-M%MaY(Eewkd=mHn1)|meR@m!*
z(0m`(`9DSn1(f+e76%2Y&i^scc>a%p!2BNr+Wa2_+Wa4zg96I@9|MW=e+&)^c<28Z
z(B}UX(B}W*9TZUJ{}>3&|7D`h|1pp_|HnY${GTh8=l|Hz=KomG=KmPc=KmPc=Kok7
zQ0M;`(B}WN(B}Wx9TZUJ|5!lhSAgaNq4R&x_8!jpKXV5Kl=(mKc^7!*|5!nNSn}ro
zVDt5$_Bp6^02>d0wFjtj{ttLR0O*iL==mU&p8v%_oAZCb=jSnEng7d_VPMKfn*YlH
zo&N#abB|^IuSAD|DNvb#$yJ4ciAk4%i2-f?j{$A|k3p7!$qH%yj{!RW$AC2dS8Tz+
zl!G+?$AoA8FUXgHi2-f?FUOsMsc3Zm4>a!wnwtaBLwWuWluxOJi8}ws9J2loblwm0
zd?1LA_52?OwDW(2K;<ve`9BP3=l?JeIRA$MRDR+)|A)~*0q^-g3~1;7fXi<@=l=*X
z;6DEgbp8(mDF1`X1AYdkG*CIf!@$Hidj1c3nnXVT2Xt-=Xr%@C{2!=7@c1s2jYi>-
zLQ{##Wf5RtY2aXCVPRqvU=m>9U|?b3U{GLSQebFcPyn5e3|eu$0ea5P==nbk450H|
z_!&U$c?!<|NrsdUbUXit0qy)B1`^NzVL&_ohXL*U9|pAZe;Clt|6y=YAnE)cAqEw^
z=l=+S*8358{!a;LO%iks69Z^Yl?`;N5(5(hsNDiu(<H*c6b4$$1S*f9=l?LFo&Uo!
zxX%AMRSem`FxbxjIot+u7wG&S&^i~;G4P<(agZVh=RsQ#X{wT-nK4kw1u^s%G`#3`
z{*M`h0&Kq@vFHClTuL6f8G0@bXrnV|JQB3Pf&sib8K-#y<W?9sO~fKG{RQNFHYU)?
zB;eCaK#D+z*n?=iSYUMj4`}xm=oB((NL0d-^XU11@PzXzvmbok7(LJbb3t40hxPm)
zGsOHLct1b1z6Uv+tn+^u(9Zv{W>BE&`9IbS3Ml9QSTiV~od09Zpg_|3KhX>dDChs^
zF(^=U{tpA%`9E9?3V6@|v1U*h(DQ$+859Ve|AqJbA62yTzw{Us(9i$Ed;U)qf%AVD
zM$iB0W?^7}od<?|-WO=R1DOw6zXLiK2c#av2A%B#qG5a(4La9n^!y(N2GF@Zu=9mr
z=lg)p`T>O*j0ULzv0?HcKDp=rfbR5QU|<*&=l>-cF*t>Rt}QG{%u7yXz%o(k1iG+G
z34CIY5`$A1gHxE5RS*Mc$#IaYqmM$gg0Vs@gak{46rst1MRSk^jTB<Rf<<65Bp*zr
zfXTGXqT-VH<c!Q52;V0)F%2x?o>~%|S%t%a;N{*n#U&}3`Fa_43_kJBU;{GqN)!qh
z0uqZ-^GX;%oMZ;4un-WovH}?&Vr7+N2;qW*Aq3<xr?3z!E2yG^%)FG;3XqCGFkxj?
z3~~c#eYurYUTJPgYH>+1R3@pc1jNz;5rI}#No6GkAf^^f0Hg`*h~g@cc%YS49asoN
zSXsH|7L-&%#obd&{7Q2}kj#d89-`JaGY=#QRqa|)Qk0lnf-2~kk^)nrpaxQ?pr%lQ
zEpicy;B894mtop5*c4Y5>w`E+ps<80U`WX?P0C3{NP^_BBo_Eud8MkVsw%w<B?jO4
z08fVG{Ji241*jRm1x1;8CFxK>ctY}pBq9jO;F|_k#o*@Y<Eo&gkj4Pf#SjJ-#?TxF
z)fNWT22sY~o0*cDSCUy$iAa8^)`Y<o_$K=zDJp`P2O$}JLy~<N!ji)f3c{cY7<`lS
zbCSa#6o?Iu;^ZO*-wNM?FbppmLJWkE7_vqXaR`Yn8v+&ft?&gI9>U-o0%l=Y5(c$|
z!M7p|(+OcvOBjkF((vFfHUya%#!&1VQUM|>!WhDG!x%tDgcXEU1S9-j%-~y`om!4z
zaT(NwVaY}L#l>L^VL7RJ=_MHmjqpgy%P-1J%mHPku$26gFov*{%;J(TBL<K)zCrmV
zQ3yRH3?P9BFd50<8&;C<@9qOljSBhcIk^ha3WjD1vFO1S1aS<6Wbk+QDarSRxfqfT
zQFI4JKn=*uD`5zXWC)C62n+{X8i;U9N@{V5Z(>PNW(CAp2#Js{E=mq8O)OD}RxnYB
zW$-P`%mZB|nu<^Wax9{>^i9o7Pt8NfmgSd%^dc0%<0b_zgHW9au^mEU%i3t$QSy_L
z;!~iv(;`f9g6M~k2w|w<2!SN13M^S3wvff9xTGjEFCA1cD1izpQ07;HTt%6o#GnK%
zNWh}7l^q#M3{Ih*J}&XWA&w!gVB382Q&MxRtUz7|Gm!=Bu!=gRrf23s)Pl-*NPvR*
zR#u>LuqYE6wIJQ#DoabDzz~a=5f(9HaDL8AL3V~~UJBTFWHH~=+|c60^i;6&+~Rbw
zoO6CoPG(AKP-<~$P6@<MC_>m2f&EBOm0MA2YCvLUQL#^EaS1kKKy_tEJ~kQ0loYTd
z6TxH>LvCUPSQ$8Ek{NO{^B4+>^0QKtOUw}BS_;Ujz~P4+nnuVf3yhI@g@!0R6qSX>
z3?)UG@yYplC5g!pZ-8B)r4WFkD*#1T0E+p6C@KR{R0bL|BtxPgz9==hw5S-86;VQ0
zK}(@1wHWM1aHJ||DdZbMf(BwTT+|363Zc?+5>et9YyjBtLD1qCnqlC<6ap1TQVA`J
zF;qgu8KBt&+%O9%%2d!&C@};Hf*3{&pnEStQb9;wLx_Qr9Mo?x!NAhg(o}4!5l$*f
z&52JfLTbS!CKZDPKsl=r-1sTU&q*x;*^3gUAuv%$Vu#v{P+JJH8@mpK?QrGTiZf6#
zlfj?_3Qxr8l}cdE{@!59H7F?F*Wbm}C*D6aB;MaG-q+RFKPVC|hg~$(FCfU@*)=%W
z)div(t{ze}L3IVY28O!&IYSC5kWCO-SKok;NF;rZK0fiz{(d2j&LNN*)6Fv|I0PmH
zHX2LvE6stlPeG|l!Bzp}M+}2tv4|YNFn!>dQLt4o!Vz#thl3Uu7L_oh<>V(qNreiA
z<osfW;><jTw8W%hTm~S59P9^hra-W)tdc-$JmZT?5=$U?46MM)s-!5h7?fhQkk#gu
z=Ej31K>ma(go(u`=H%ojr=pa%NeoV57zQMjA!S-CP-8qksjL{A_MF7x5|Dk!PJnbU
zK#3Y=v4X9F1p_#0KzDzG%2rgKl~rbnA*K+dyaDTj74%?xP()zPi-+_VK;Fh84=M_A
zDkv;XEvk$MwaVj*Q<EWHM>7M`Cqokq!R49)Q0;*dTxdE$0RvWq%>;-9SO+Y)w7|t<
zCZz1l#1bx6R(_?qPGO*a30C)m`aDIMIHdzYArO+8n;MM6|6tdoWagoi%aGgxwi*<t
zSS|KUfjBxFn@>GcAYMVueqfcTLRcahn*!8WMpuC?n$guj;u&2O64B_Q$mKb@9IR*u
zB}a5QP<tFy#$)wo0i<F?*HeHkpscLGWfN9&(2@hXdFbf@T^=(*psRrKvDzMh-UNgc
zF)%%_gad7Rpw(|+6Vb%5Bmk@`P*VVg5^PBTLlGnmU<gAJ0fumLPJVG}QG7{8VqQF=
zjs?X#hEf93DCq)2Gc;jfibGNchBzW=U`U~*4Q%ou$b|)l0?gEbp#&Dy*dr6#1jW#W
zJwaGmIfDZ^BqK2ot_53Vin5<RI5pilKffpiQY?X+kDzfHP|QF%rRaSUHHAb>p(IQp
z$M}@|l6WUv5+RrpPGB7&44!#m`9=A8`54_MH3dgd#~rK;o566&5WF7GU~taKEC|UD
zO3X`#G!~$KElbQ{fCUdYPQc<piO{|$Ml%^Eflv$Twt@y1;Q<KJ3KGE5Z3Pc#g4!k^
zY-LpdZdqGd6&OMJ#t=F)1)FD}Ept8429Ds=^nm=#yb`2Hj6ip5Bvb%04hDB#0Cr(V
z?81TAg`r(|Y|e!AzLU+N_jkh9`-0~K6(H+*K=XUVod2C`WmU|OoRgYZ6rY%!T$;-O
zCKW)*5zLCu&Cdl5vqC5ZHH9RG+|<Op__U(@T$mi(-_S8Q2Dsu}B*kFk7?ShL5{oiH
zbr8e|h$!3yXGmB;NQUJ6+=9}QRG2+*W06MmVB>YDN{eAm&{9BBo5GNuS`wd}npaYk
zpP2$`JC>yuA;)hr)LyVMghNY;G9e0!3vx2SZO&o_NW&P`{RFi*lk&hVCCEs3Nl_+4
zZen(7d;xfrI=(11C$S{6EEPR_LZnd#wa^k1L`ew3qo5&Icz{7=^Pw(3%ESOZMhSFv
zIq3K|P%;2v&~Ypv8iXZT8NgQqftHVb6Jr2hg919*40K#M=*n)88f+MJT?y#gaF`tE
zI4ckvbQ}bT1|6>kqCv-ofsQf*9ls3X!!YQIaL}>hpexBhSGj=1K}&N$H0a!Y(9&Me
z5woCUm_f^9K-Wuyt~dcLa|Io@4Z5xlbmSc9S|HH1grMu-KwH>B`f*{<74x{{ki|hq
zfq|~80ZqAqjyVGzl>@py3v?w6=$JRqRYIWak3d-rbWAx&FX$*7(3LVEHZlesqYLAM
zjtm2_L08#<mg|GqFbvwh2V;Y1&~-?lBlbYoDuMW*tJ^_adO=6*fUcDV9S09ORv2{b
zXAtP30gz*a)*<HiL5dmIFyP()%gVq2x`G5`KInQo&=J_6ZGa#?=sF(|{e%f}JOGG|
zj6vH0L09yFj`Bek2VJQI<AavhfY_j8bwS5>gV>;Jpg=U}P6ZGR!=R&qK*#IOkbsDQ
zuDA!WK*uA4u95>CO90~ALghhh7zQ2j3uD7*&{jnln^+ojEIztg(DW&2g^P~><me*M
zu|=Sx`#{HO*+?>gkNJb?0UfCax~d7rhtc4p^`OVKD@ibbk46M7qXiwm06HcOrmh)e
z5sbsYzyLbl7{&!%0|mMg2(+vNCI-4v6~>0qpkvrTNA$z^pre>TQ=Fh{)j>z_fsUXC
z9SsPQ2VD;cqR}yEYdGloc4YCxjF2OpU}B)-;Xv0%fR0H7Eggr6gRY4L9lZtPgRY^2
zu|Z4DU~CZm1w<fW(3LSTF6g-B@1S%I6#!jlbc!3wfl{FD?4T<Npj_|~iC-XV`@q*b
zf{us>UBv=A>Jl{d3p&CNbgdca7%|WhV4y3NK*#2oNHBn}v%k*Hz#t&Wz~CtXxh5f1
z5@IqJ)J)J3d!TErKv!J~^Fic5<TB9uc@P5$gO1AvaY0KVK{V)CD-ey0^P%w#I;xwQ
zi2-~i8#naoSJ3o5=!yr>(q_;x>L7ifW41sv10MqesJaKU86a1C{Ratv_Wwin?=pbz
z#{=!(rPlc$91IMgD+FM6f@shcnV@4sLEE%J*I|OLzyw{>1v&~5)Z73a-3C$z!k{aJ
zKu1J^*vJ@kZ5HVG?#Yr2;49rga-gfRKu3{)ju-?Td)O<%z;K_Jf#C^K-UnUp7RA8;
zzGf73L^wzv=t?dS4Z6k>wA~5B23;!#qE|>VFo3SO1YQ3K;)5_~$pmO=1n4TV526g<
zBlkhaq=T+f0LkORpzGXVa<FS3K*w={j*0^vGYYx_0{J+2&{k{E_DRr@te|UEKv#i+
zt{VkidjUFD4RoC$=ol85nJ^l3r5)(nFwoJdATiL9=^z?(lmqDcJkSx9J$ww{tH40V
zL9UQsU;tfz1UlLsbo~Qp=>kYS2!oE}1RW6yx&{Tr2VEBcx}FYnj4J5JbI^5tpkvrT
z$8v&>h5{W21v&x>v=joQ9)#;8A=l-B*dPqL;u&-o4TufHpli}VSI>g34fTcQAJ8#-
zpyM!MYS3xW)>Y7Tt)MHQk>z0527s2sfR1YiT>%Z+?gKhX9;B{}0dl=A=m<j)AA~{2
zmV#&y1|8W7I(8Ct)FkLQOwbXSple+~av%&_@CiCv62u2x{|BN$7<3f~1N7=f(A6p+
zF%SkVAqLSPtc{c&L442^I3OBy)GCMuVbD<<pd;=;OG!XiWP@(^1YJcBk^^DTm60GC
zgh5wcgJ@(7x^4?}MHgr(A!rFL=o(#Qc{m$<{x2()&;MnCoc}$#{}+1x@96$t($4=K
z-TzCs{lB0}3snEZ`v0H`0K|u#2MVgZL43%09*_nEh!5Kj0P27UDNuO-mmci=00suw
z{XY*G{lWKz!tMhTXI=-sIUCfN1GP`4F^MpP?h64`S|EN9Q#TU>1MTkr*~rYy!oWbk
z`+s;?V_6v(5cmI-uyC?6Fd**#;bZ|dQE=b?a}InzFOm2EFpS>+18UrZI_@wG>U@G4
zIH17>P^Av)Fn~HppnK3joeWST4AemasRMPWLHA37)FIykMo1oH7jlCS`Hn77V-035
zsPlz<{}@OP)WHRH{6O~{pz}fIf(AQajZ9F(68Ua1M(~mS4B-3!!2N%u^S?ly3Q+!r
z<$qAamc^Gr0p<Q5Pqh1g6c|wN|50F2K)L@%fk6T9{XYtj`$s_e8GQdwDuV*v`+sy9
z6j1K}DPkD(_y52fT%(N95Ew)u02-VC-4{U7`Tr~q3Ml9Qvp6WAod3_}pg_|3|EvxQ
z6rKOi>Y#vf{y(dO0{r~{RM_5G&|X<A=l_qM{{g-O091F4p8pRypB_}7f(HIT7&KS|
z8khi0Sb)SqbuWkpVUQRIgV-Q-Ah|)5)v-DSe4a->Vt+5l&Fl;e;PZ|^8bAY<p!PMb
z&i|9R0XhFy;|An>UyB=%^M5^VoM9|rU|@*20XhFS11etul4oFG=(qtn|98d>$oao3
zp!AL#XTazGp15&_(UL)kL6|`o>HJ^NsY<2{W(*n(nhaVD+6;mWBA`2Y7{nPQ7$g~_
zz$g8}&IVQlpB}8jpvs`epw6HJ3XD-a8Un*C1i<ZoV?_Q3O%#FJ|0WD3V4s4^2c-T1
zc>ga0VtoKr_Wv?adH*j1+Wub#wEe#fnEQVhFmW?8Fz7IJL+?8mWlm#eU@%}<!2&t&
z6lMP}1C{sxG7#AR%P_$Ee;Fv;|I2{3|CfQp{lB2_VSL93I`R@UfdQ(Ib};T`WMHUf
z08My<_y-w}F)}bTFg%CGR}Diw0|P@718AZjB%jAn$iTqR0-h`a@tK&|nHU&47(kOH
zApQi#*^CSfy$qlUA`pK*<0?i5hDi*dNqZ1KpRtyafnf&t{u<C^buc^R9vaX@FK7Y)
z)Lz2J22ISt)W8PkL442vKZp;SXaw<(u`w`!CRjidUmj8jJCOB*Cf`AP&;$oa56BD{
zAJq0h-|vggAKm|px~~@$hM);B5Df}TP+Wi}fYJG&NiC2VXs<6a4blS=gUN&Vph-03
zcqK**WM?Z6q`djd;s+l8Tf+_Emol|5F)#$7-RB*KcAs|?<UViscwQ0%Xu$_4{X*^!
z&td>g4uklR`@@SEK$BD;KIH!J(fhwa`3HnS<9dX~|3GbJT8+_x(ig}LF!QN7wg|4+
zp#*3F7s2ztv>@#R(D`1l`X4l30OErdR0%Oc+5;dyXn_vsz92^iCk7z~Mh4Kr4iMjo
z!I?n_bW#;~6d!cIuLFY+12Y3?Q3OaHbRw$|=msH>Jd=ZhJp)Ldl>szy36ghaaAgo;
zU}FF+fDwS7_r(F>v%<~;<6;0UE&`2b_%nnu2r=+5fEG=G_~8uU3_=XN44?&H0?DxR
zzW5+~_<3Ob44?^RkopLQ2nHbr0fzO=pc9`6od0FdpyJKo1MY2r7B>hoFsS%2_%R4E
zh%kT_NP+lx&;Mc|aQ+t~gMtNvH3R7EJSOn@gU~SyCOqeVh43;kF+$J(vJzxq$`@i_
zVg%iD2)e_NhXJ_{3rg>xv<#v_=?=6Q21J7v`hdhhi|s%(D6N1nhz-IZJ)p%ApoJ44
zJ~9SP<b(L2Ito4Qg2exG;l7_8v~UGvKWri�KdB(V&TZ5F3PVapN`vw75%+hk*e!
zP7hLx?T$cXv&b3$2l*eCKdC)N5ArKL^1n6cunEvvRv+3Kzj84!*nDUQFE2Xq2|{1^
z)Xr$A&A{;BQ#&K*{`5be+8JeJ85npzw=;rz2nwIu88txn{(f#}<Y8oBaQNKLc!H6E
zA>ea6BWNrn;d49q{-1)+?cn==8a}s!@Bf+bxgC7}&w|hG;QN0zd~OHd|8wATJNW*e
z3!mG;_y0Wj+|CHP|K|f#p5aS7`2HV(FYVy_e-ys7Gpc~>htdvT+QI$*0H}Pz7l```
zzChg9@CD+&311-YTkr+qz71a>?mO@W;=T)CAntqc1>(LBUm)&d_zH2Kz*mU76uv^l
z4M5@y3=9rmA>k7672>{xuTcBHLhb(wwf`&B{;yE`ze4T*3bp?$)c&tf`=RzQe1qEm
z4Ql^4sQusC8B0L+e}mfpt(`HKK@eOfl^~6PL^6~zlrfYuR4{-}Tn}LY-Af$K5Wx_|
z5RG&jk~(<(C+PlH%-fKB7<?IGaEzOHGAJ-0#!ciI)Zim6It-v2=0LZc$1?;lK<;7k
zW{6|JHorES{~_&udgOo5!e~(aug~Dd09ua-9uHuE)b}7hXaO2%JODHw2;zgs0~jIe
zg+YAKB2EEKQ0?u=z{3DL-y7}xU-)^yYz$kN!1XDE3j^ppV0H%3;wDgi>&)QHz{9}7
z09qUds_zXMOc;0=I2k~TRY80!20Z8gG7vcbHw5kc-$2m$?Rd`r1&up0L@@9$h%$f{
zU4aV35QY#29tJ4}CVSBNo6z%r8A0cNL(l&;1f91Dx)Bjnzk=@LVP{~nVug>TgBH^6
zU}ON_PXnqqKp0dn!Rld9SqZ`*G0;M7m^_Gv)iI#Oo}h)EAT{V>A&gOs3=E^~f7l%T
zX#LN?fNO05wCN9~KpP5#N)hXK!0UmvAo&}l0JI=hs2EZnfcT(=u(0v~#0QrL43PDH
zAU?Q1P|Tp9!2oI%Fff422L%QNeFiF?|F24$^ZywbG#Pq1LFE&Jf)Jx9BLjmL184&Z
zsDHeO8PqDK-};}?{yzi5X#1am0anhV_n`>&4?uMUG5H_7eh+DUAGBDQF`j_|vfdAJ
zUoU9G1%!`d{T~CO`~WRf7s>?XcYRQCzyKaE&_a|4pvCt>W{C0vwD_5m0dxJ|Sw>xy
z^?w}9^Fbp646yZo?M$pF>;DXxGHJU0Z#4fiFn~5X!P@4azBj(KiBBGsHb?va3=H_z
z=n=}_gycbCOica<Z3G0h|7{o?89@7$K%1xd6&Msu8LSvU_jiKZ1JL<C5Ffd`0P(^3
zTLF^4L40ui4{Z;C_~85wEgwL9&_*^;d)|)0o`H>lkpZ+B0>lT6_km8b2W_eX@j*Qb
zHU?&fU<t_hcK|~o0~-Sy1Gs!*U{K&;Qe$Fc;9vl4&IHxZZH$)~*%){kKpXu)d{+h^
z1~vwMhO1EhjSO2D*ce1WOAHx6@;exwGO#g7Fn~6{fcWJMwG3<w(hO>n5c~cx2s5%V
z$TNU8qk!ba7=0Pp7?c@68;(Hy8;qPxYz&(4@%Wbv9~jse^cX-J5kc~K48;s=42BG#
zO|&3>Dnk|n8-oday#5ozPX;yyONM{q3=AOuf_lcI_kTkAy`T-mpv`okG!9~eHgbXb
zLC9-fK^uWVVxT?~s1F57@38(AXk!^@UF_)i9|OZmE(V6}Tnr4zYm31ZGn4>rWCZ1Z
z(C7^4-fUR^A2hxX;%h_GrxAlO0}BHq189>MD7}Ji)CTo-K^wk6d;<nU(C9q_X!93{
z54vreg@J{E$(5Ob2}GBG#;PIh2~eEDFtPQ&5c5j3`k$Y!_5T{?f6Vk;|If}ELDl)c
zd=?f~1_s3Z9}7zk3j@RG{2!>?0O653{*PS0gNg)L{)g@Ff%We}<pD?@bf^KSJ~L&o
zWME)mVE`Sz0OGeWEM#C{;9;0A2B|+cFuY>|)oh@Rs*K5?^YcO5E+xV1CqRcDfDR-8
zZA=D*J&X<7bnYp}zyR9x4BA)=I&cD1#)CHb9~5I?038|t+DH$o7eJdMK^sqDdXe>j
z<_FCfT^Jb{R2e`A2!Qw!jIxXj3~CIZ&D|hA7oz|p1A{ul6=;87k<pkDU;lqJ|Btr+
zVPlK1{Xd|z3F`w5)%iczcphxL4(tBEOa=v#`v0bA{eLq^{{U2efcpblr1$?v>wn7D
z|BTlE3=Eu{3=FcI3=E*dcR=;d==?te1FXJ>)$ic_f0>Z=JfQpv-v7sdw*QX-ZT}ww
z+WtQ#wEcfN1or>MqwW6-B(VRF0d4;u!{Fcl_nCo(k%7UUVGajme!+sl6Es`Tuo24l
zW(Z_pU~puBt^b3y|HY&r?I}omJs5o02&laUSq~TmAAj&-3}9qnh=Y$WK;{FJ(AEQH
z!Pf&q%7fANKd2l4VRG94pmr#}Ir@QYAAtNs%=jO8|3A|GUf}v)3z7ec+W!w7-vgBw
z;PHR(ecwpq|Cwm@zbWbU|41GGSBK_*$ogHx{(s2&UEKTsA?3s9{(oAo|09(D3CZKj
zqqHnLK=~AgVf}wt{SR&rcp~yY=s+$|ePhdTk%55$vYrKWfE(z%1JF3D9tQ)15TX2U
zikAN~NzeZywfzsv|B(6`k^dp>foQb$KoVMeAPucOkcHMB7_I+7c@TtYQU4Rl|Fq2G
zAU_dP|HH=jVB>utH&ML*cP4DSfP(>a;3w!%O<c4Dp8da|JAH}S{|j3G3)=q+qLKIi
z3NwIa)dG-Kze3iXhJg3}f>xxOFgP+eFxWHLGT>YB3fe7f%rG$H|D*XIGA9U1&!GH-
z+-C=^F~GG)haT(yK<>fU{wE|4%4@V5KLmvrG5H^q#}F&FK|9?+sU5U89+W@y7(nxU
zj71CzP7Es<7#KJhz~=*}FevP1n8wJ!zzZJFKP1n<06LTwbQoowI0FOdKxNQDoS?&Z
zL4H(`W?(RtW?*oWW?)E`hKxCkuK%a~`u_yH>;HW*b^s7p8iIB@MN_c;-wwY1KYfU=
z|0k5c3CV-<#z5zPSo<G#{_hTX1_q%N1_dMVdR^#wzzt~mKb^At59%*yGH8OkAfxmD
zknuoV<A0;||7iUWTFV3~E0EVef$DdB>jy#d)T;l%8I_L2=3V9HphbEI85qFp{g}XZ
zLr5?alMn#4V=#rOD>D5>0oYxj3kpC7-GlZ&F)+Z6gT`x@Km$V~14{z~Lt_JY*dMAG
zw6h4r1nsN@(d6NX;v%rS<e`Va3o|f+_bS0m!xuIn=YZ5Tf(Qo?0m8`cYG`0#U{C<H
z{TLh-I2btanFi8}!0AwTfiBtzmttU$W?%yEVP*hDCCrMK>%Br%5qfCJf`xMJ#$s@I
zfey(B9U{&OwiM(jFoS$TfC(Io<Qj15D<pk^4($e=Lt_j!Xa<-Bt;GW~zy!=EU=Avw
zfXYSi1Q?kZ1OylxIv5%R7*rTIA@K+z3AO(bX3&Q<n*T`)=h6I6TzJ89&0x*{pECQw
z<q|#fKd2Z6)nK50J){JLl!l-X6<`3B4j>kN@o4@hExbqbKXKtTn*TBDe?!nkKnx7v
zalO&}k3Suaw*N=l|9Ddfh3)@=sQ<zD|1hB4|8tW;A&{YxL5zWc0dxT*Xn#;G!vY4-
z1&g3d(LnnHwHZ7a%orFLKo@y|<QFlVU;y3s13pgxy8jQv2cI7T-5&_zgDxi&yy2h#
z8h!R)U}OMY#wd8#K>>6cjRyl0_>wyT1_y>@hGYg0237{pC03yGK}s1)89W%+pzHY^
z7z!B*89W%+L0b$MK=S1b<qRGSoD8yppz$;Zg$jlW1`h^qhD-qnKZ_xY!GnQ^0d#Q{
zNPQVY8G{D{FGD+2KARz%!GnPhx<9~yA(bJO!GnRH0dz4JNPP}N4uc1S00ZcPO2Nkt
z3egNP3?2-E(ES4r3`q=03?2-^44{kc1m8I*#4yA$crZZk|GDj;06J&K19aA~0LaM>
z3h@jH3?2+(44{i4LFUCV#4~s>h=VT%6ubyJ4=kL)gF%A97^*%2Y`!D|=n_G}hYkwi
z4ABf83{ueZ3LF^H7}6L#7^E3Mmu7<8JC|WDg9n2Q_;NcCe+t7C1`h^V2GE6LApTT_
zsSF+ratxr$y+HhV4D%Q~7~~m1m;8bF^BLwdcrYk1fG(v1@ux9NWAI>5WB^@O2-@G(
z&d|Z&!JxzdzNC=BL7{`8i@}3InE`Z>7D&FEp_jpfL4^Tyktc}X%h1Q*!Jx_jx)>A0
zZ)9j<@Br<{5QKzB6GJnD2ZK5T=)y6Od>=zUg9n2K1L*QW5Wk;c0)q#GCIjfAF%W+O
z*gskfT~Pha4DAda4B8C0p!_a|ZUzqq9R|?FWuWxr!r;o_!C=S$x~vk!cVuv6@L(`z
z09_Oc;=3`pF?cYTFn})l0`c7$+!;I=%%JNv9l+;ddoY+Ytl)#V*NnlO!Gpnq0d(mn
z$UO!OMhqSdmJFcF)dUzF6l@r57(5uP89<i@3Nkq;Sb_OA44}(ALFz#>(;f`A44_Nz
z1X&yuEEud9JQ(a4Ko_2Y<UuD@dob8D^nmPRc2F>3Fk|ol<qHs>!9fAEAJ2oq5xRa9
zG>2`^;KAU;0J`)N6ko>~jx%^LI5U7Q!UORSG8|;^U~pjoUHAs#?_}7?;KAU^K$Y|V
z85~g0|7Sou|DS=x^ZywrJpZ2o?ficRr1Sq7p=akQpq>9;BFey|06H&EoPo($ih(I#
zgaLBao*)AggA4-`10Mqu1L$lY&?$zX^M63+{(#Q^;bCB60G<7#&cMW=!NA0z!@$I#
z%)rE;!ob9!%fQ5-%D}{+#=yj&$-tDS#lV!R&A?P5$H2rO&%nf>#K6QL%fQ5-z`(?y
z$iT#4!oXx@&A`N9$-u;5#lXa1%)rE8&cMWA!N9~|#=yj2%D}{E#K6R0!@$I#&%nf>
z$H2s3z`(>{$iU<ZDm^_Jm>7H+m>66bm?~Tum~!11m>B#Rm>Ap{m>9emm=e7in1Xy5
zm~!kHm`WTNm>8THm>BFBm>3)xm>8TGm>6uq=M{m*jzM!*qv!uKz{3M{_CE-N&h-cF
zHwNur1%(r6TpmP&Fh~r9L2QsZkeos=<W^+}iGFo+2t*h{GGM!SnNym90kjVe*6tv5
z@$v;Jm`Vtp3+3awco{bT2Rh#iq{D>)vYrpN9tgHR2(~_usQrHm3<@aw{}|}I{}1Fw
zdS1L7C&d6hhZ@wjA^PHFP+&7KfY<wj?l=RTI{-RE*oTb)yk-w{4^k`iB21`KhNG;b
z7caxY0z`w(BLUIK7<2|VXiRG)T)YgL8wU9ucJVT3Z4HPI!o*&@Ow|5=CP;gOto{EC
z(Ea}m*!TZ~PSparcP}#oxa|!(0~^%G0G+`NYCDm7@iOTCK+wg@ptI9KZJR-R@iO#c
zZ;;<XSV)3_0r`$L<ntOhBpATwpuqO8fz*S}vjv^a@R^5!VWThu1L*9F`@#(1^F%=M
zpnXQ5y&E7l2rrXjU;v#>4C=3e)@={Bi<d$Bq~1a6I*@;n@#w|Nkk9~~t%-i|@=^u`
z1_1|8Ru%>&h87pbN#I3(961c2DPP!B;tuG1Dd?he(0%~WIYFSk03cIQ=Or0nL#!Yv
zT4RBS(D_n(4h9BWDFy~bu#J@<vH?DI0jdl@A{cm=ni7MMVhaa&zC(ebMS&4KFO8v&
zSb>HqFqNMtK<1Z07rcWmo#q8gs4*~5W&zj~>;xp(L2<#<U?9N4=m-%&Q+&Q1vQ7YW
zDLUwKaW=3#NGWs`0Av6dEJ{lPbQ1@%`M;p)3v}r{sQ>EEz{=nO9+3vA0{MyozA^zM
zf)zKoa4-lpDRf|!WMEJgn$$5tMUg|ukwd_VL(#=az{RPfgTqOn(L;b`VuOH^5{F|4
zC@7HhpV$dmhXT618?;XzXHr7agUkfG99e)$?5HY8`braH0H3!3TCdLlx*;6wezb~(
zN_Jv529$0Xq4|!1K^5w*Z(<A#pt=ckz8B~WAi9<cC=P9q265vg3e6c99TbekA?q0-
z<rfbFBvpX}4Wx{&7-Z{e=sG9RW$vJJ#XzGBYz&SdcQi0UFOdhWg8~U)VpwJcmtUCD
z#EKN;D`^O{D6}G}*Q$n;6QIx=eC|@Ko+~{V*M+q+?2u+)7>w(}E=e<h&)pte>%#uu
zcqPriF!<Jm&0t`WVPF_c>%u-k*M%s`Fo5qTqsO{16554swlWM1gRfnvYY;CpINOC)
zG7JoZv0XS>hJj%)wF_rv&H=B7+9JaMp4S*`?ZRs^gR}khMP@LzzZe*JWd~>bOGkEa
zu7B~AWdNTyJ6PI<T<;IrfZC(QvV*Jr1#{PI*}>KRg1PIE?BHsD!QAy+c5t=7VD93R
z8(i%#n7b_G23PwF=B`9J^4nhp1q`|Qxv6<2P|C{65zfkmvx*rKlaotxAtXo%m}_MP
z7b#{)&Ph!yiU*5BlqskwBtls6C^jglDI_uErY7darxoSr!sG%11LA{R9eoshp_8Ey
zJql_Hxk!p3#wX{OB^G5S<|U^>jDU#3O>l;o03jKY^K%PIOHyI>z>W1~fNLnis<asD
zdj%~8B(*6F>8U00$*FlIMfsU2@g+r>WvN9a#R$Wap@xB#Ash-<SX_{kSpw2m%#c)?
znUfM<l$u;xRGi9?nOCBaln18LGK-4AY8Y}8vs2>>5{pvvO5%%Ba}rB3%Tm!Nks;DS
z5PKmcb|oPQkLDGZD8T&>F(4!#s@FL`Cnqx{H3;giko=s~B2Zvs2n3d<mLilDWjg2Q
zl_VyYpjpn~<D8M1lfsaaUz(JYst^IS1<H+ta+C8xPJ#*sU=wu2CK!lK&<QGtW*U@>
zRSULRdZ>ETIeK`Y!Q2QJKs6UGjLl@YB&yl&Rx#<R`MEJ5=`zEZ;-cgjCr}d6OD-s2
zz$ux5RVoaprZ7EZ9Z17I)M5(2%B2Z%gRB1qbJq^J!PWnQx$B<X;Oc)#u^a}s_ju$7
zSN{tZUe@x1tN#UaSDO6b>VLu9)g#Zq0NURVnU~-N9p4QZ0;g8aM>Ypy39<+pyMbW}
zG<{u_A6)$}Sa^XQyoQ~D;TszRLk5zEK$jANC6NesVFm`!0nsoa&|&7FMRcHx|3Hga
zK?g*G7T1F0K^N<SXc(r(LJrVH%f);!6B!tkklbs4#0IGVUFZa&VfY_pCJ@X89c~S}
z1P06jZ4O~)0AIQU<Adl_1_p*EZUzR>!7d<vxex;bJr{C-1{^{5f+ko&gJ~c(3@h_8
zFn|V(K$D3eG0?&AAQ~CxLuc|phuwlMRZM1MVBm&sp6+I00AG?0+8hkJ><Ba%3_7SD
zte+2Z0T!4I3L8cS2GB)DFg}PLVhcGyApts%1LgdWK(zBe^3cxzV4&>$4~+Ir27`WH
za*}>-eoARhs=gbRW)P$~Ls%6NCWQp*5me=#S`w0(n@U)rZ(>PUYBFJU{!UKuE}6wy
z`I&hogjELw27sGy1pEt9M$jvuz;@2hEy&Cv!aE?vo_QsyMR|!igq<0bnq1<NSzJPl
zTj6R6Iyj^#ld#nxMVZ9fjA%lGgR>;DC_S}AKOitbL02I>Gtbya!6h}RG#!!zvB(Cc
z=A<STr$Xe*Qj3Z+^Yb$E(()k!&@_v)bq;E}gY6}x5H(z|nTMGNu&W}%Bt#wn?eHbE
z{~vVzC(8L><&@=r%sha_BcQ}hMBssx5%e%9S!2%w*e#C7kq5A-#*wbEsKiXy*cD+-
z*Lako`rg?pCOk9G(lo{;wK%&ZzW~~q)HBjU?@%JAO5${pXcK07C1?$(Z%UH8!VoDL
zn!yO!fxT!aqzh{~Pe>D<LZ6UUP_jl({lw@YEs6pH1HkM39TE5ag3bY8)Mo(S{|;K?
z2in5`YVLt<?`daXU;wQ(Ml1WU)Yq`$8Pz#h6haDT!pbny5;nuolMhxk7%2veD(r~_
zi$bjF0*g94Ndb#$Y_X3+8Nr~#UG`x&5m(uVMK!$aLr<yr)Dm<sW;uz)I9LKB!e&Sk
zgDb>R!;j?pAGW^-w%-So-`N=$!22CR-5Fs%$o&)g450J;nZWA<K<xoT2GGd?EDYjM
zc}V|(je!BmhujxL`21gZtDjKmhM6pg(1EosC01VsgE<4}N(~0^#i;ig{~Y=+|KZ~o
z#u{5t!2DtYFS%rBVq*XYjUX%NIxz+YOC|=;HKPo_*%`naq~+Kc7<3sJ7;IP=7?c<o
z7%UjUVZ`tpd|es?!)s>HQfmf=UPjPHWd??cEDQ{wgNzecLD!KnFn|_pgEnG|GcbTJ
zWL?P2z#zxKz%ZAAfdRDCGlZFeL56{WAppE`n}OjKD+7ZL0|Uc#4h9A*1_p-BObiSl
zy<6EB7z{vtRt5&pwrPfLR?zk43=CN;3=GN)3=C<E3=I4X3=G=Lpo6*?7!I<7t~+F4
zn9sogzUs}4g8>{Kfo!15p&1yGnHU&E85kI>SsB1ry+^Y%Fn|^&J!S!2vjz$w@c0tL
zeMazxGKSY|4B#Xq#mv9}TBpy;1UWjbpPhlhgn@wpbR8RLp|l7KWFhw!Rt5%b1_p*r
zjGzs-3=G>?K-alJ+zwjuc!!CBK?1Z)ot*)ERAnv)1A_$v0|V&LIBo_8hNH|34Dt*N
z4CM?A44e!M4AsmG46+bsfk;@ez`P3!W>~O;)ZjW>7&Jrzx>o=+yff6#{{{8`LFfM{
zGpI1AGGIUd*HD{*;lZbNM$nqoKcCteWn>u`cs{o?f}%~~b33C30|SG>=XOROMg|6l
z&+UvS7#SD>K10s8P59i-7{S26Q1H2(aRMs?L&N8GMo^n$^!#5)_$>Ge37-vLA>ni2
zD<pg_d~Ih04XHi&+Rm84$iVR7Yda%owKc=HcE$vD1_ps|?TlAI$^RQf+~8X~V+jKT
zgTpsSyaaq}XY^u-VTfgjXDC5B0X>qTl%b5FoS}jNbOM7vLkI)tWP)&p2!<$z(er;1
z`+Y(AdL-n3P%RER*8|k<hpZ?E6|SJt4^$n2Mh75ldXl5(e~}j2qvwAS7ha(H3#4-N
z{6EC`pCqjFW*FW72TDD-@aX<OTp@!lKDz%8Jw!<3kM92?HoQPP*ccc__y6GuuhIQ~
zcmjtwDag5yqx=7e3oQl)$hq*N`~QdyuhIQ~#D)}D9rRp?(fxnmI~y1v!?47h3o*L?
zkF;|kM)&`L^BW!lx&1Y|{|`?<p-92Tzee}}p#%#~4s5;d=>9*PL4+a!3$M}re<;C%
zlLHH{;kf?~r>Du67~TH^4?D<+GidcazV;U^eU0w_A+G%e3$M}rKk$Txg8^xO!NO~F
z{|}B}LKB9C7ol_EM%({r0f)hbq(8{`>uCEQBY1EK(6jvyTK|L98Cb@JVfkY8{12=l
zh9L+GuhH{AFoFg}0MbfgV1R|!==mQE48+XK!@`S_^FKaMG+?|tyT}~0bCj2pfk8hn
zF*mgsvbPDcR2qG+6FMK;em&UoY=VouA&avKD;r(^k7W@&Xqy1Rpc`HP4?jW!yt4?B
zs7Lqzp(Y$G`^&KJfx)5>>mC>^>hSD=!J-<JxZ#^NpnJP;C?n_<+<5@IiMaN_U{MX<
z14Gaem>U?d7zZmjiSRj0DXPVUHa9>DTy*1!(?z09m}NFWYtT1v5!QgQn~RVZ?8%yt
zF05&skS06{o{&~-sh=1<q(u?#d_ja=xH1VLtvGTFA#Ir1hX@^``+r9F|6tkwGkX3%
zy#Hm*z`)SJ#K6Gwp`Gz77XyRMhj#Fgz=2N?`ogDn#?k#h3=AK>K=#=%e1-16`3l{C
z1KpQn01^l7zxfK?fAh7S5wt}u;VWc+RKZus{-}npko{2;zS4gGj~zo6LpDPWj{QFg
z42cX$49N^B45<uh4CxFRMDG9bVu)qPWDo(}Wy&DVAi*HXAjKffAj2TbAjjazpum7Q
zO+ubQjX{G!lR=9?n?Z*`m%*3;bn9h2LjXe{Ll8qSgEvDQLqL3)A>wd?(fS{HOv7mX
zkA85)X#GFB|5p{dcNw%r4OF<2yZ;ySXeUB#$zj|6AFcnP`)|KM_uqbj?!Wy4-GBQ9
zy8m`a*8k}YxeR$Y>VMFU>&Ux*qlv8leHeThVyIUCGYruFf6$x*?Ea;ZeE$Dv{vW>i
z-wT}k^Ks;VMB6`uArstFAa4IZsNax7mHZ#e5C`sug7PAW0h`Yno&TfX{2wUXsf<V0
z|G@(klCp>D`af8H96kRV9-(Lq(1|RF`!8YPHG2Lxbkh-9XrXc&7^40|?h_iU=YNCF
zcd}z;U;y1k4!W1zij9E*BzA%Yl?JH+iNWMSd;vBFhCHZVkRD>hKz5*p(I{^;1ZW!q
zpuv97`QNbf|3JswgZL)kL)jP@z~=)RBhClC#RNXiO+g2I$Q%QME<5CWz;vc|CeT57
zo7f<H875UG(16trC|{GwhzWEM+d?Rxk4YRf>%d^j3Q<3YVIc$P0J>99zBZ!=Bj|uQ
z8L0Y3#vVq{L3aC~d^08wCeT53g)HFxjS2<~z6_v)@Fb!7Co{}o0384q4&`rU*u?-k
zST6v|U&FAG0d#O(H`M)-%vsE!gY#hgB~1Lxpab((ut3}w#gM=NI^gadl;6w%x@p>!
zVJDQI!jQ!PIv}qZ%J*joWdI$VmjyMyn`s6U1A`5NE7bj`7%ww2FxWF3gu3Si11lo~
zgEPZXD4&ZF6!Pv28BqQ{h9?XR3_c9!p?n|4aL_4h46mX57{)9{28K}ZRRy5)8GV>y
znHU%%8MN3T;gigi%EZ7B#UKvlCom;4F)&0ks6hFNOi4@(3^5GqP<|2<=zzai1}muf
zOBq%$Ffb%AfR4%snSX=vE+Yd&3d2;WfBrBsGBGfuGxS6GUl_kLGB9K@+=qroDMJMV
z14AwYKh(S)hJFSHhJ1!>sQO2YPZ=2)3K?{u{Pm1m7#SE!8CszHmyGWjL5KMnK>0fu
z_cAgtR5O@B`3D(~F)}bTFg%CaSHn;bx}<>N0F<A{06KM~g<&pKJu4Fz69YpBgCdka
zfpIn?14A!^I+Q=3aTOy2!z2byC_kUEmXU#B2Dtn;W@lgsW{1=PvaAdY%c1oGJ~rrD
z0Z=^vQUj_NdRQU)LG=QN52|B8^2gX17;dsLFsx!_U?_vuGax<4`V(0h7(o1=Ob9cO
z`IFcg7(mxn9AJl>XNJrN*|C8Iq94Tm_x>L!U>P_SKxar|9Ey&7Ogii!bSx{;5NlDC
zP}USEF+gSD_hZ2s3I)(xnm`)BH-8mE1t3>J!G((<!VnVeZYhNlh%kg?z~VB<dY23a
zkh}CUl%RKR<>sfP=76r+0z1bS#8c2x$i->^WEqQ1aY;%}W|Cfp9fM77Vo3&wq2v?>
zGExaPIIP5=gjn35#Gr(_{zHkuDa^{sDGW^2IfXI!CRX^Tg_P%m-2e`OL<BPltjsO5
zBqTqiD6^QMEI%^^A?pwEFoXn!v4WOD2}l{}60y9}T*&=mPGRx>WvN9ui3JFqsMmzS
z133h0lv9|3mO_#t1B5nWa0&xmTTlYJ{tHLoWH2a!r)EIj1G_m0VOg|-u|h1|WGkzX
zA~ZR$h8$!;BZXM7U=f%M$p=#@U=ngGS~B=DF;GzYq$Z|;CEQa>f-|d9u{#jFKnN6j
znfahN^NEMtMg|I~0)_za&1#^8ppeYq6cz%)R#qVELaeO7!2qH`!4P6)6$FumDk{j#
zOG&K&2?c@)E30CV8=S&I0<Em_N^?t6i%W{3GD&46AeI)02(+?FDk~`fF|}X<AWdLL
z6jy=71Ffv;z(OFx%E~pjprjHi?w(rWSDG7wWH!w65VgLUc_2xsYS)UAqQvA9R6)m-
z6qphPHSqi^<fbvmQR-OMq#;&JVUdKTeQcMIp{9RqDqz!`SPTY9AzxGmnkWW46qIHW
zhxudIiM%!miwZ<8#pWn*a>gM6Ur>a_RA^DBm%%`2HVINFffnHrr;-R0A*B>S<3JPa
zgcX7F3?XHRWI;$JJdF@ih?ZaoDF-DHVgeDQj&Km7rYj=sMowgelq01$LP{aYj|f%p
zv}lu-lb=`uD&0VS0M{g8uFzXB38qCvs!c3TNmBsVGe?;i7<z;m7_uc87)%5i7%oXO
zFmQsf7y|=n^AD&?0%~Z38i)Ux7#O~ZF@PJwVgd{d@3|NlY9tsKE=VyjfG(m29by35
zXr3#@zyR8y4{EUPlVD%~4Jv`mNe1maU|?WKft)_da2#|9H3I{KkPrjI4Iu^w4jzyy
z1eTU$U?|{bV5nneU;s7dK{8691G1rKTW{rKV7Si1z+l12z>p@!z>v<!0B+>kGchpe
zaxpN-FfuUM@iTxMh6k7!7)~=YFiaI^V0b0XzyR9N2bv55nTd=GB$0Wz**<&>44@9n
z2L=WPcR>b*7BL0}NfrhMP^aJ{KLfZi32Fd?4nQ{KWMBYo$ebX?zyRu0pquIlIt&{s
zxDy&i6G2@PP>&5N4x;WbFfbef9dr#kt6Yi!+#uHGX8<>>LGte<AeXCc6lGwjWMW{*
z<zZmB&B(wYBLTUL8>9w=TX`55K65iLs7W#~fCe*s*cccTxEL5Xc^Md5B^ek%n{7er
zKp50X0X0HFY!_w*hT|Lz;Dg{nd{BoDL_c9-V5kEfJPzU@VOBl{hGJ$0hAYrGgGqrJ
z)i5>_BLl+@X$A(+A-tPGhj%kDfI9*pdC>XcAR2~Oh%qo+<Yi!(0a^?I>Y_mD3P#AK
zg@>VTu!V}l^nqwmw6p~h<A#Pch>Z<{Hff`a+kg%nM-v1!+Cfp}Bf!9LP>g}$sTc#p
z5`G4TBmo8n8%YL+W@tJGX<H}AzyNBjgV_I}aS37{5oBNx1Re6uz`&p+!NBm2lY!v@
zGXq16I0Hi_=+thIA_fMAW{^ctHi(*uly*QJfx&!#9cXhL$j!9AzYerX3S<umgDx}~
z>i5@yE^;L0{yNYgE9i0tbELEa8e$mY_t!B@mSg~T>Ot`e8XQ?8&cL84!ocuNgn^+~
zf`Q>aF9X992?hqx;Z`6upbmZ%2Ll5$GXp~%G@pP5Wk7Pd%nS_v(C`5bEP=#UNHQ?Q
zGBYqZLB&C0KUf$TO4u0~K!Z^qL>U;?a5FGO^D;1`axgH6Nii_I16^<cQiz5@9eS9M
zH5UVeCl>?5G$95C3l;{3WdaNg;am(1v$+@;R&p^gZ0CYp25Zj5z!1pKz|g|M!0?HQ
zfgzZgfdO>+K(8nRgRwXRL#{YvV>QfN5DgmC01X@+ho0Yk0b0(1F82Tpp#0`zVCdmv
z01pOD5@BFiA;G{<%*Mdr!_B~u$HBk=8oUNwk_$3RUx<O>s}KXjW5`?<g9;a9fZ~Y&
z0|V%QbkKm!5>W<*SRn=mVQ~fqX>kSyWpM@u&|o-dA_Qbcog`$y1au)Vi0=d%dV$vW
zAU+6#2FgsB85rI$F);W->s!zeUj?4>*q()fVJ@itW`bN~4>AXYS-BV(xVab@Km#OF
z><kRWObiTnIUtw*PLyI`09|GT8t4-jWMD9r2I*j6_$COUL1Z#N1B1H=14FzB1A~Yt
z1A~qz1A`B=9s<e3ie4@e5Dzi{1Yt2Sh=b|^s9F8cvKu6q3%V==!~or~fmRnyfQIch
zA*ccd1_sb&OVdRe7(fF=t3hEU$-r=dk%7St>fT%83=9oW_H2+m0|Ucuq;v-wR00h$
z`LHm6hYmHE85k5n7llBrxR0b3D#WmYkAXoAnpQxAM(qL&47UUs7-abw7%~MI80<M1
z7~-L3oR(x@kcIjaq<<p^14Az~jBbJ25uk7YNkB1ZAQi;4m11B34NdBCFn|XK=Zi5g
zL<=x5fCj#5q!<`L1I!?GSD<Er*vJ^PH~=*03>tWxD-F5t10)X`SOyJjfd-&KgU+H{
z3=GBs3=CH#7#KhY_kh&k!k0xD7}hg0Fn|URL26z~GB9)rGBA{jFfe>#WMDYR&A=ef
z#K3T#k%57mfq`20e}I~a$l3iU7X!m(E(V5&T%eIyNHYy&J?QFKkP|@F7AWb0vN5Q6
z1FH5x-bCkv%mp=dVMPq6SV`q#U?}EdU}!{2k|3|b_Wy!XAn)k@U+A^#h`ud&&nR^J
zA(r7qc-NMII<%fG0o9-mE2v{jgfi3(UszlS>JlP`O9-2Y+^Z#^8s4cT!mV(%1RV_N
z{}Qko)@vogX2f6%*v!%WzcHYpLbNMZu?%Nn&jVN#V$B0s)ZxhkSX5)n12~kSCMoQS
z;<4ue9EwNp{|p3;w<0#?fcMa&hBKiNDksR0BskMS3s54okZK2bsFD;ruqSImF2kC}
z32DNU;0bBPmimd&Lt60Rt{aH33s*%!NGpz-fRHxKYJmtH@F7xCQV6VW8NL6{lwo+@
z|HsL|0BR$Hx`ZGagcG1*AT|hth8{uPThLH5s7nVLE}F&7z@R(K+W(;S|5q3h`+s$y
z`+r5C`+rrS`+x8JhTQ)b0KNb3#P4?S{eK0YAp2VzK0)@kPWS}b-@4!vWPj_1PmuNX
zp#8+4`~N`ui9y5Pp!)>BFf%ZG_ypNs!|)lhzgFNgWPdH_UO~|41?XNu&^>pcdj&zO
zEkXARf>z>y?iB=W0R!DD2)Zs4bgv+Y2Hh(NT5r4HGi3km2I&2S2cY*8UVz?D_yBr8
z;RopbgbdLAKLTGM`+pRm`+p3e`+ppu`+owyK-`z`1+xFQ04m-95@%pwnD7M>E(^Xu
z?7#C75<YJ}Lc-_IM@aaz{DFkels}O0S@H+6{|L1I8WcWf{zLX3-T4m*pEv&@;gj(j
zVt>VNi2WVEA>uQBL+<}u0gaa(zuOsw87dj77^-os|A*`i2JH{ZXDDDOWGEtX{|{)l
zKrsdD|Lx%Wf72Nt>;FOh&`~@vApjZ<2Cetg0AJz?nGyo6?=l9jmttoC-3tifmxBjJ
zdBE$RK+_MPVMoyP4ruBOG~^1JW&w>uz{V)rp?8H3jITy*9Swoe5FjQ5!1<q%K>;QI
zGcqV(=KnxYD`7PM6BDSTYDPm~h=c$*|1+TFe+IPt|DQpjoMANo50NMxb>?UY5DkdR
z{|uw~pXdM`RX7>~Lns7B^ZyWvtWl?qh5(gAfT;WrZvO|3_W!9I_M^s)hQL6F0M`5;
zj@JKI0=54^3!_KJ{|7q0M(rOB0cwT-IRB%M|1+WGf5y@LPt7nNHET2k21^Kl^FN{S
zfAIL<X#GD};%w9%qai@85E#w>)C$Q_b4Ej8=!F0{{|BPY|68H8|3~Zpp%<~EE*=d5
zB0>P1|Iyq3IcWJmbF}|YL{N?@84ZCU7Xn!GKl=K=(fWVL#p|epM?-*^5CG@@0<`vj
zGFttgKU)726PBZDMnhnzg}`Y3A8Ii+>fX^1pk4@o^FMn3-vF)tA8r3rFTh7l8V!L#
z6awJ<kG}p#5H0^Rjkf;>QIw53Wi$k+76POBpK3ulYS3s147m^(&HqC#%0?YL8Uj=c
z0dW3D@Bhc6wf{%^|5OX_QG-T9U@(OM*8E?9mj6fB{|u%m8+FTQ2v98qM)N<_f^yWL
z(GVDNA%Hdiqp$y~7#;r~auGY~;L#8uA_TDJ|4g*@e*q}}`;DIeLqvFvDj5xdp%en(
z{GW)n{<jn@|LctA|DhD8qi!7y0b)a7H2)JDQlsidLtyxYz-ay-esMbLqtOr`HUz-=
zpQ!UcM*IK7hUuuf(GVCaApp+*=<9zv(fa?wqy7J(5}%{)91Q_dLI7+2N1y*w7|s8r
zgz2c-(GVCaAwX3A2e1DfZT}CII30E8Xb2D+0;Bn#*pM1kHyQ%NF9b&O|L}{`Q6G(l
z0I?x3n*WInsZn*KAu#+xU^M>^zc?NB(P#(|3r6!lu^~08ZZrgjUkHHn|3b9&{|nLP
z|3}CFhhM~x`e-x+7#JA9`5%4#5BmLIf}`{QqlslS1cqY>V9o#N>wiY;|KS+*qkb9<
z0Z9EXj@JGk&Htk*V>ARtL<nH5|Iyq3;QPNu*Z+-(1TpH#5fuX9{6D(?Z$!oUsAoq*
z02Tt^{Et5V=Q=w64-21BdNc%va|mF~|D*l?;T+|oej5z|cnFN<e|S)gGDbsS#DxGj
z|Bv?nM_jy*dU!MhKp_Cm|D*kXP*9BG(GVDMA%HdikIw&%xO6b;;gJ~v;QU{Jw*Ds>
zZTx?9{(od9j!|C^`w#%<fAseM==lGzkM~gzj)njz1V-~eC=^EVXb6nV5E#w>BQxGd
zeLWfipb#KF|ND;K{|O4PQ9K#~!zcu>=703@zfjQr|Iz$EjG}$iE2AL*4gswBAM5)6
z(fkh%uu)<(1cp%vV9oypX!C#I^FK!O|1gU7QLl`K05}9vIT#p(%or538MMLtJP==t
zK|zN>2h6Vk@fjEt^ceKOd{}v*%b*M9-(g^25Mp3Z&|=U6^IM?m^%?ZR{98;63__WR
z^#xHNc~b@jO$JS{`~(gL22KVB1w#fiFrQtDfq{{MLE$W;E)z)RGdG0K!91UtfkBYr
z6qMi2#LCRTAj#kZ<r^?%GBGeHF}&ksU=UznP%vY3VPs%XW!MbmOEAhZGBBtyWI*{`
zi~@`d4C)M5pnOF}V@3uBO@>}5Ux-nZk%2*rfrAHP|03ou%nS^s439Y==GQW8VPIge
zVmJ=vhcHwzFfiCKSU~k}XZXOtz+lVZ1Lc2aU}0onuxFS9Rd2!I$-uziz_1a@_htxW
zU|?`$XocGMm&K2jfx(+W9U2~~EWcP77=jtZp!{FVNh}Nu(G0dwei`E_Mh1o?hBeUe
zC}nD4VqnN*5afcm--|JTk%1wXK>^ASVT@vAU?^lzf%0P+3m6#~DjDW5GBEt-Vqmz<
z$iVQ4k%2*+n}I=%n}I=>n}NZGn}NZZn*prm7B_A+AT#jEgF*&mM+7$mLjgC$jwWsf
zhFMU1V0N%_F)(m*LF@zR0hxQ3g8>|}AU?<rTxN*!Ffgd`Fff?&Fo4y61*J1i1_oJ9
z1_nb;h#0b22~aVRxgZ?O!@z*c?8#7bLGA&m!xdJ9<U#h#=3-!2$;H61or{6tC>I06
zWiAGWhg=K{F${?C-NDVkaFCmUA(erFp^O0{SHZ}@(9FodAPQBB%m<mP%f-N8&Begr
z$;H4B&c(ox%EiD?%*DXa$OX=3a6+9Cl7C_O8DuXz0|SE{gB@6nFdroSK=LyagEWY5
z2+FU93=9k`4B{ZZ7K4HTg8>5r0~-Sah#v?mFE|)j`4||u`5180U`s}c(GVC7fdL5t
zSbeU+paHf&NF0*ijTs6V7#P?YLKq<Ya)#0Kf4~7WN{oiUFbV<U^Z#i7e;7sks8>cq
z02~5D<$pEM{GZS0{69FvMv2i77(O9@HUF!Pj{gsz7#{V>Xb9jAfzkYrJ8VW}Mnhn@
zhXB_6ABa}}mw?*;qy7Kko)$*^H}XONYyP)F%m0d_`G4f4j8Pwtgb)Ddf28#};Q7Bc
zwEW*Tn*T>aS{U`?$O{2*{wM1E&(Ze($V(lgJ|6A>od1bB|7SG+5BIb%>c5c}0;BnV
z<i+`@k4HlQ76Rb>Pt^UtqxC;5%tq<a5Ew2Y0M7sD?SJ&~ztqw3zu^+!qy88T0pt+C
zn*Xn&jsIUA&Hu<@Hp(6if#DJY;QUY2`TwKs|KSqnqy88T0ayr(=6_g7jMAeaF!DkG
zod41L|AuJofAIZ3qxJvDOC6&=9_}Fk&j0y{^SQw5|FGWwGn)U0ds-Ov-^dFAaQ;W{
z|0|%?|D)%Bj=Y31>f;d+0^t0Q-u_45|1;YD9}#I`)RQAG1hD3R^!C5i==|TvOBtg+
z9tj};&i{ng|BcrFBOxh_`f&t?0670MqK*G8M(h7C9<BdJVA2@%@(2h4tmpp+5;*@~
z3+?=WL$ve%;rE4%p8r1rlF+CZhj0jB&Hw24f3z?tpxplfzOM)A{*P9){NFNq|Hlwc
z5~EHZK_P%O|LddG|Cwm{AN~Fxf3*BRTK|ur6g2A9p&SBO^FMn1&w!TyUD4YA3~2d3
zbF}^+%4uTM?IR}yTtN4C8Z#)s?*GeRf!qgZ!e9ap1X%e1yB`#MpC<$2eo$R@$o*jH
zOzlhz49pCh*dTlvCRHZTeSkZld`%`J@O_>Op?p3jaV7=^9tKlZi26AU3mF&~_!&+?
z`Pz&gj0_CI3^Gvljf_2@+b9|KLHTA(9!v}j(hP+xpj!w*<&Q4|1A`2MBvk)oh8YYD
z4Dt-&Q2thiT?`BiDhvTo{u+jj3=9k!4Bb%oOEPCMGcf4D`AeAinHd-i7*?=A+!w`=
zz`(#@%<vA%Z)WIV0Nn?=6Ut9v$YNk%FlT6n^8Fb?85kHW8M2_}cQegk0^JYl3U&V}
z#>?RQKo3IQ^MZkuk%7UP;V6{P#Rv*{cZLioe;>mW1_lNnhVxLq4`VnZ1497AYbZa4
zF^iFbA(Y`8)O;VNSSALBNCqu-Ncbc(r7|%vL@|g%`3X#kOrZNiRiOMtrX(iN&64U+
zeiBnM69YpmgB8^Lr3@<=7#I>5lA-3`V7$x7z>vZ)70Um^$jHRNkj~H#<$q!P&d9)!
z#c&@Q9;FNw450f*`Jv|ZF!VDpFyu32L)AZGd<wpgR0qmm&$xw=fuWS41<HTP_@0r0
zp`5`0%HP4bmyv;?n!yChKgf8Dk%6Is;W^a48islX28Jev15kb*_&&Q9hPhDntV~=?
z3=AC%ictOp#@UPv4808MQ2u<zRg4S_lNdOm{Cvh*Mh1o%;JZ(a*%=su*&+9m%Ca&r
zEN3Ik?q)%#$zx?;=wXHM?N}KYK>W*4{xLQNhMQ~*469ff7(ApPYCv`%>rZ55U;y!d
zGC|})W+3w?u`@8NVP{}Czz(_R6qygYlXL?ML_diA1L`i2eh?o<gX}DU`VpkY2g#2h
z_rlx{QiqEV@&m|Bko!PtV17jAe}wuQc8BUeHU<VMc2o>A;{?>LApIb-Kzc#<m11Lq
z^nm;c(*wH87NoWq>JMZyKx%P`BdfE5>V=sJqd{swY?wTVFTjQxuf&Lf`~xm@M~Tr8
zpi>Bd>wg9U^}jLVe(=%yAJQHet^Y^se^9*vs{cmoe?)r*6ds_u9@IV<t^XMqKy4FH
zIvK71=~SVOT0>F@fb0L!{=dR#|9`aqKidCCj0=G3@zMT20|Thu2G!x9zB#Oa59;fK
z>U0<lQUhYc<U#z={y$08(5T`83ITBaKidBvt^Y^I{|DXpe;IVV8&nq~kIRpa|3muK
zpgI{erVp#1k=da7d35}LfGU+yYlln-fb0L!{{LwGKU)8f*8hy7{eMv39oC)zwIPuC
zu>L)$uMd)g(I7P-HcTGGAMO7SnJREZI}}|1kM{pZ>;KXEf3*G|t^ZNR`$2U)s4j=K
z2VnI(sICXe!Dx^g5E~{B;*Zw<Bf450GM)$5|D*l?(fWV1{vWOXN9+I5`hUpOT%!)9
z1_0Opqy7KU`hT?kAFcmK>;KXEpBk0Qs2M{h1i<zGX#an-{vWOX2VMO?y8j<?4ghGZ
z9W<s68e@mCVPo>hYyObgAa$eb|AtI8H0sa+3ITBaKidBvt^Y^s|Izw?wEsWa{~w@w
zXw=$)2?22ZKidBvt^Y^s|Izw?wEiEh{|BZT8ntzRLI7O<kM{pZ>;KXEf3*G|t^Y^s
z{{gCpMy(x~5CGTzqy7KU`hT?kAFcmK>;KXEe_*PiQCkNn1i<w_75e{aOl>Il|41{b
zpxpnX!DNVX{|_&d7)AI0m@>Ij_5L3T=1i3Pe-<<GQT6_xE~e>pz5mCXDF)^KpCqOf
zl>2|;nG#U$|AE{G6vF_!{|9m(5b^i_{AOf8x&P-g<2RD-|9Qyx1n>PnFBsoZ_5L3g
zCeG3Oe;64UKzI9q*2=-o7lhHEGY3b{{~bO5cYvy;QETZG0^s_e3jP1l`XB%Of1~w3
z{`>z%>wm~yexvvQLDu{u-vJ0}pNy{mr&EP6YR!lW0dW0Kh5mmEQwvJ}Uy?})rT?$S
zq>s}7=VlV2sQ+)w<Vw~4zZi2mO8<W$6AxAU{~b(I>DvGIWQs!R|0jUQ_YwF1#xljB
z^#9|S;!*DZg^Ujn-~a!~_>U3!{@+iGUk7#npNWZmwEsWa|7QT*ApmM$jNbn{qN=@7
z&q6~0T>n#{|DVj%j8gwgFe#$c|Ef%SRIUGwm|Un@|BEuGq168in7FB0|F<(up=<r`
z!4!#7|Hm^WqKyB?FvX(O|B&_oV*DS{9vH3vIoTlhJ?AslGBPmCU;xz>#_S9X!R(O!
zI%u4H^#0$``+q@a6O5k!3$0W}sUZ^r;QF5m{r}PWAOHCOX#GF9#{WnA|B&{}==?t<
z97g;9L#E0abtn}>09^l%_Wu<|`~RT%fYJWHI<&t(pK%o<1H&YS(f&VVji3)3q@Dzg
zcjU2R@9%@gMv&!Ku|o8K=I%jyKxg)W)FAU=<L|c_85lk>GBEsO8=e2BV(~s|)MyCc
z4FPcdKidBvt^dL60Y>Zp(fS`!XM^hT(e?kM>;Lgq9;1>&J_Nw^|7ibzwEiEh|3~-#
zkM92;-Ty!2YqU`hkP-s_nHU)O85k678C)6I7#J8#m>C%O85tDZ8DbfP7#JA9?E@_a
z1ziSRF#i@41Bh18X3z%F3^I%i3_^?y3OWorV7?SH1A`!ggMuT26N3-~BZDG{&*Y%s
z#Nf;z#K6SB1>!R}C^#@UFbFX)GYG-?jtoK!EDX$0zCBo;l|ci_cV=*95Mp3sc)-lS
zAi&_j5W^6|AjH4{<ufQGGSn~#F>o;yL*y0w8A2I^7<d>aLiyng;S53yybPy7e0v9m
zXohG8AqGAOpMgQ4f#D*95CcEMT#!72gF*yD1cMNR0K<AHKawGmL5M++VK0;)#Sq0H
z#2~~F40a!biZ_D~gAju-LlTtl!{Emt#2~`p0_A%#cryqwh%#70`JN133_=WI46PvZ
zSRE9?7{VBY7{nREr6B9g3>i!qgcu|lJ~1&cFeWo7STI;K2r)=AFfnj4Ffp(*Ffnj2
zFfp()Ffp=$LY09@L7ah!L5zWkL4<*cNtA)9gqMM-M1p~dfscVHOpt-e3KaUn3`|V?
z3``8%3?57j44@MMJ}@vafH3Ip6c7y>pMA#+=>vXYhRD@HX;4}LVURiy2I+}qW?;yL
z%7esU_ze?8?@uODQsbyvdWQfgJ~8q?1C{eX1Bv;c$w2{c{%55y|1+TF|6~gDzdeQd
zpMgOBXT*{JnOGT^7@+x|0V)57i83&S@G>wlLi4|sAOlmr5CapVFas0AX#S^n9vjT|
zse|for15`Hna=*4fx(W!4(x1UK1h9}&!Er1z`(>H4doj$7&0(0urP>2`34LI3=E(a
z1c?8fK|zl}kAZ=KgMpQgfq|Qk0VfT%WRw^Ufzc2ckPra3?~(F<1`DKpZ^B>#b`Q9G
zFlGR^_dx=%_CKh-58~^xL&}HI^}nO*e@FNKGBDuU3xs^G7HBO@5014lqvwB&uKxj*
ztD|@{1n3b0;QD`b{%>^tZ*=}|bpCI2{%>^tj~<oIs2zhQ1k9o1e;N!LU^fMcGcYh(
zF(?=_6f!U{urq`(FfcHtGANWY_%bpu@PN-hh!JOC$Q5T`s1s*km@3Y|utuDL;jlOZ
z18D3pm4ShwjDdlnoq>U23E0F@Vl)IsLtwCm0C;>aA2PoWaw8}YvolaQ{?9Nv{tpVv
zQ9K#~gFOTU!43pn-oVVj!obSF#=y?N!NAGD#lX$L!@$eH$H31Z09G?fjE2By2n@Fn
z7|s8~Ek;NEGa3TKhX5l31A{Q}%12d>hQMeD45JVL)&J@Y4B&A-$Wm=qxbFl8sO4`s
zxyYP>k%8eL0|Ubo@Tx<QlOV1Gv9MqPdh}7IzbF8^i;0neK^S~{0mvmpm7W3(42=vd
z4Gav84Gatn4j_FX3@Uv=GzW+v8%GpF!b_fsfnf_1s61z6;9-!0n};uKK+XXvYy=Tl
z-PO>*!oZ*aTFc4csKCL%fzLFMAqbofb=LtV2JpTH(C!7$9tO}&fuQ&Wt9-fMD^wNC
zqB#Kz<=TzK;CTGQ%)nsJ!oUDY@p#i0ac&b}0tX{;iZNB4`U**3J}e9j-Ruku#$Y8g
zz$6Qpgb^^G!1zeC0umdADZt3YARxfl(816kz@Wmw35mz03<?Ya4xX$m3`z_wE{v1F
zi*`A37(h`DGinDkyson|F#Kd^U|<HD3kfw;cQN2`7+4cE34w>u@UrJ%V6c^9U{C~`
zUI`)_;6)cKi-AN@@Gdna1|h{34zNEI7+MrSgCHm>NaHk2fvNvI0g}F!@h~vt@G>y)
zf+f`8B^j7YRRR+1ptxXaFc4s2bc6_?*>S!dQcm3GWdN_^2JQC(=W7ONDL{oRfMz9D
zE@);6S>hKoeJSuUFt~^^F!(dDGI)S%B#<hQuMj0BNCYcxaN%GOYEtOHD#^g0Dm1BM
zf{G%CkRykH6NjRUlYom;M+b+KK%<8M%fto&B_$5W4zy4^+y)7+Tu}xFCr0o(R~)8e
z7Y4f=yA(yDQB{!il_ti(FkcKbO9wJe5)zdRTp$jeFeu$HLh~I1gDTWr-^3Ugw8cTY
z0T>xr7+9e0qLY(QtZ9%2apNQk%^4US6pY0g7(nxzkn)QMS`VW|I!FT@Fv!-M&~$%G
zoPlAoBm;vCcsGwD$o2+CP{Rzw!dZU7GAp?J0;wbq7vw8x2(&1)BI(wuhNOEWp;6{A
z4FR0VYnb|X)LWw=Fd71g5cv20-+NFQ5C`fm1_TBu=qiL~<{29)xTGePrZXUm1f}Mr
zCKjhMxLL)dr{?Fz1Ox`eml?(s7bVAp6lJ<(7MJK{FergUo%3@GGILV(GL#sgG9ZKE
zgIpbb;0%QVg=ht1g;<0@AygnaKd-n%0b~wHgF-Px7(z0jNtQr_AtW}JIhAJSq(I#T
za!(S7AD^3_lA6PinO6d~-511D&{D|7YCxD?azO!uO>s#|PG*u`h8=@VZemFWh@s>Z
z1~O8~H?brvH5tqdN=+_-goF}<lE0Hvyh~<rR(@t)2}sr{%*x6si~&T|IfXI!CRX^T
zg_P%m-2nD#B7&I&R_2yj5|STMlv&JBmY<n|koAXn7(#-=SV2pn1f(o8uS6lQG&dg1
zaSDs~FH0@TNi0C<41(x^kO<)rsDM+Lf|f#(Ap?XqVsHur`Jf~*FBxmRg93m-DWoV9
z;ytjNgAk^IBN%S7l~qU)njBa|4zi$;LM&LY2uz0LgQ*lSnU+~pToRw0k(mSG`=lnO
zfhF8iOM)}2a5yj|P%i@<dzty5IP-~j1{(khr~-z7#G=%^5>P@=NM>*f3jtv(E0FOa
zR#xC(0MVde2(hvXg2+M@6=de6q*j200>OlpRWZm7PGKQ|R#thXxh1K^CB;ygq_Pqa
zOAAB<T3IEPl@x%OS}*~SCa@!lt3cv`R#tUjArN6@<(gYiQVA7zPc88)%?&{^8|Hb4
zTHnk(kR(*KYeh*>VsZ(ppkqo3Oo@UTLqP#UZhkH(5FnJ5l_ONZ$|@JmDrQJbPA<)b
zkRT;sE=UEGQOuB>lbTo*59UIYDX1wVLRj$-qoJlLs3{~d<fbO(#iteJ=fdRR+1(eK
zULblD)D&`&6hn+p&M!+W$^@lJh!GG`xCzb>6Cfl*a(-?>X-O)~9=Nf-h*VdERcSHI
zy;=%LYEu}}Q%mBLQ}arS@-tIF`K&CpsH7NSSTfWwurh>0ONuff3X2PJGD|@EiWwkf
zQBi7gX;E=1IR2CJz!W5<mlS0(<R)gP#utE7X?#&?PGU)BSt@!N2$4q3*l5KhL`ew3
zqbMaTR5l;#a_9V<oXnKeAgH@S@^ey)K!J@R5LlX8icnUR>71Wel9*hA<~{}=NRB(o
z#K6!a%)pQ>!N6bw>)kLgFmQ??Y9mQj1_mou1_scn6rf(@P8J3RF#!gK_goANH4+GQ
z=&aYQ3=I2_<dgXzDnKWkfLO=*K_ml%kPrjI4Iu^w4ju>}MoLREFcfezFn~@v34nH}
zl%VbcjgD{SV_>+>!@yv{$-n^Wb*D2jFsQIIFxWFOFz9kIfKS1(<7Z$vz{0=)8tnv~
zG6Px}3o{=ZT_A}~6jRKHkAXpk4RV@_yC4HYix>lgBntyWGYbR5M}7wI3FZ8(kdt~0
zIU)Kdh%qp{!!rEf2pNh3E7}PSBhU#s2B0PYSQJ9sflzSLgpGkgo1cLp8!}|X@LmEk
zW3W+_fuWL#fgzWNfdO=aw~Pd&hYi!%%EQ3$nVW$@O_G5DbVC;C6mbPE1_n-E28LEN
z{~u*#U`T|9J?PY&;~Wg&(*;0gnL@>%FhN!wgT#<A=#&A_$v;=1aR!qE-P8tSgGTK^
z>|h=ShRx7$YJvI(bZQYu4u)5VF)&=@Wnh>AO;ZU_x`GihLIqmw3{q<g6$i0lSQIU7
zfy6;4Ab@C6unjk+YS5{yps4Z@U|={X#=!7YjDcYZKLbOO00V=KBm+Y;G@XNVt`lTn
zIKU2Kq2eQg3=D$MK_Vpy28MT>4B%6gK&!elktQ>mK^7rtor#oo*03`$d}Cu^0PPls
zDd~d^NWcUb7#Q4z85m|E`9ntxa<b4uMg|5qAqIvW+zbpdP&+}V4k2k}PzSY0p{vM2
zvn|MShZz|dJdxu1gfIgG8wUf!9exIe1SEHZPM<1<rgM;fC8RuIfW!vLeE|_j7<3Xn
zj60c!f#JJ2jK{#B&d$Ja3dvs}8PLl2CM2<PAqIvokfA2<sZkl64B*>lo%k3SKquip
z=VM^#XJcSU;ACLn5oTb}VrO9B7iVBFkzioxV`N|ejkXI&GB9{bFfizHGccq|GBB`9
zF@R6d@{nR+*d)ThaEg@ye1aC}ln#&^Ko~UY45E>-GBoZ$Bdj3t>!KhM73V|4Z9fkK
z12Yo?Loyo!12=R=3AB6Jk%xf+G-Kin_2Utk8GH;3pj`wo(?BbV|3lLkOiW0EfgzQP
zfuWd-fuWI$f#E0@1H)x528M@R3=A9+3=F{%3=Eu{3=Fc+eEF3FGJ^P-hk;?EFayI5
zMh1ra!VC=mpm8vVgMpy}G=v7TfPn#g@|LkM1A{CF1Nf9J(8*fitPBii_#m?uJV<#1
zbTdH)QXK>{<{&Er!&Y9%Xxv<A*>Ii}vco}Bgn{9k2m?c}1Oo$T1pNt8-Upo;9mT=G
z06M*_4jR_3Q2n6OvHYQ7TL?{aD<l~hKqqH`MwMZ9gKlC1ow&RYRMv|!Fs$KbV2I{r
zU`XX)U=V}m1(;f7x(sS2NX(jxfx(lDfnk~u1A_$%1H&=_28M7h28P*O3=Au|7#Oy5
zK}P<~nHU%X`572mI2gbujDb!uGv{Go=oMvP0F9D@c6WfxL&l1r{Lae2a2zsm#Bc#x
z&Vg2p8?Z4j{N`g|=;32v5NBs#m?Xl$utI`?0d%X94>tot9tQ)105m*6X6g$uFnkqa
zV0a9TLlrIthMQ~*3{M0Y7$UeC7<AYe7?y}KFvJQmFbIn?Fi49tFer;NFo14Y1nCFi
zI!VYaoFFy`JAv-=Mk|A|*dZs{fledyh1NHqlg}!U$^?*JWDJ@S1f2p0y00B{8XHWG
zm5YIan~Q+~bfTFQI|D;869dCt4#*4-NDXM$3ux9(94TFWLt-cMGcdS|Ffhc6FffRS
zGBD_fGBEf+(>q8%v>0UI5&`ibCka4U3=HC+JO?$aA1QBvW+q^2w2{&yNNfT$Y`1}q
z@dF7!cjZhMg`8@=8WdKN3=9{bX%nObG!hM>L3lPu9>hSxu#*cwGnAm2dC=*6NYYrD
zEBF`~)Szi)5<3G!y8r{jEkOnbS$+nFOaTT4(Ci&d<7r6-23e>-L1G&@7#Mn?VRQ@B
zjsS%NNCJviK+`^G_78NQtsVyh!+jRWtVpx~0|V$Z1&~tEsU;x#3e+qR8y$mAGMNfZ
zqo9=sAo+!C3=A7s7#KFOF)-|4V_*>FVqh>9U|_h47S<rO==ib-1Nij7=TJAklw@G&
z5@cW~7lGV#a*&&W0W@Pj4=Mc7%^2m6h5&6t;PXTS#=EnNz!kVQGXsNuUSe))F@t_y
za*}>YVo`c(NoHPJK7^l}pHiBWiq6-^J01u&2%-_2LfG&eA!U$3IKrwjkX?$^!Z7fF
z5CN0iQ%gcJb5r#Q8V4KtBV;Y=P#_`I0f7PFK}Q0v1SuovLeQ`Xd_0y2i{m}>N>YpR
z5_1T99zNI!8XzU$R=8S%4hD}V5^^YXSeckmf+R7x6CsIOA9-LKGSm(B02W!;us2w~
zEVZaOGd~ZU2S9C6*rE=@KLvlSpg9#ZU;yfOfjX6-cH4c(7Fz~h@X{;>1_4IMl8{Y|
zprdjb7?PP77(i|5UrY=Ppf(D~Tu?pK%LqE^7Gfx<4w=iq0G`|jRZgIKupBga!oa|A
zhlzm!R3ANO0Bz7^V6b3hU;wpmKyCo_n>RBtFo4YLU}9hZ^_kKb!AJfwSTZp%fZ7@X
z;59!Gdq&C85Eu=C5flQT1u|NU3=9{po?+x?VPN=h^$fT@YH=Mxdt5)m*rv+B5OMts
zBd9}Bas3RV3>O1K$MrLepc4XTTtCAIIyqp)^)rk-j0_AruAgB%!N|aH;`$jz(CF)p
z>t`4v7#J8{TtCA&0aO}YJHrS%bBN={8Aj0Ph{TOEj2Vm!3>r7iFoISSS=>0on841!
z;Bn&&BdDVpapMf*6$S=|45)ksNS=X#q2tCGMo_^w<Hi|AP$9emO7FOFh7nX)p15&_
z(TYKkQHYU;QIA2N!GOV#!H9vEk&ls|QGk)1k%N(wk&97~L4-k+L5$%qg9HO3BNL-E
z!&U}a1{Own1_cIl1`7sd24+T823AHkMs9GZjG%-u>ebN@7!85Z5Eu=C(GVC7fzc2c
n4S~@R7!85Z5Eu=C(GVC7fzc2c4S~@R7!85Z5Eu=CAsqq$3HpI6
literal 0
HcmV?d00001
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.opt b/trunk/PQP/build/pqp-tar/PQP_v1.3/PQP.opt
new file mode 100644
index 0000000000000000000000000000000000000000..3c0d0a739a15af438cfb023f06a35fed161d9c35
GIT binary patch
literal 48640
zcmca`Uhu)fjZzO8(10BSGsD0CoD6J8;*1Oo3?K{^5@2BX_y7NY5F18=*#AetkP3mn
z|NsA2U|?WiW?*1oVPIfjWnciuIXeRb0|x^G11AFm0~Z4W12+RCzIhoK82A_%82A|&
z7z7v?7z7y@7=#!Y7=#%Z7(^Ht7(}7!#2FYEBp4VNBpDbOq!<_&q!}0(WEdD2WEmJ3
z<QNzj<e}<385kIp7#J9o85kH;7#J8-85kJU7#JAT85kHe7#J8d85kI}plWp(7#MUJ
z7#Q>z7#Q>!7#Iu~7#Iv07#NHg7#NHh7#K{T>dY7z7|a<M7%UhV7%UkW7_1l=7_1o>
z7;G3A7;G6B80?_x92giF92poGoER7woEaDxTo@P_Tp1V`+!z=b+!+`cJfP}8>D!xu
zfx(A?fx(x7fx(Y~fx(}Ffgyl_fgzBAfgy;2fgu>GHk5&ZA&h~6A)JAMA%cN{A(DZC
zA&P;4A)0}KA%=m0Ar`7`uq2WohJ1#6h7tw^23LkWh7yJ%hDuO2CK`(|urk2>!bCt<
zgT|4UsV@&Qg2EG~G@K!yp@<=yp_rk7A(0`OA(cUaA()|rA(5ekAr+<w53Rt!1Wu=*
zv<q?v9;I+8uscDC6&&|P4EYS@48;to3`KAi#4`jKm>5BM2UIQ+Yd;Ujc&PoZ3@Hqm
z3?<-D011<d`52fOL1i?^ZV)C$zZggn)P6<=R&bflTu@k`>}(Yi?&)V~8sp*`>>c7C
z5EBp>5MO4fXQXEcV(PgB2Y~!plAHm`Y9Ld<dIR+`K*F5vsU;zqxv3Byhi_s@SZXqa
z!{_hh6z`H*oRy!MR{{}Y4+sp<OD-q?>0|}5!DjG+Y;?}gEy&D)n!^VY@yshpEy_#G
zfoSClN=+_t$t;GN#2QkR36bCqDar(kL(S!c@xf+;-3ui^6<2yuVs36~k$SO$due7$
zs+d!1dS+f;W?s5NWPWLpLO@YINQI<xQEFldNHkF)xFoS8Gg-kWGpQ)CsFK|!wIne!
zr`Xo1G&3hfAvm=Jq^wxMJvA@2D6u3pMIk&RH4kK%0@#dHg+zt0%;M6-90g}>ZJ7B|
zL8W=RpkRX;s}Pi$mRgjWmz*l=m{X9En3M{#)2%cwxg;|`4<XC#s!)<qlwX>jq2R_C
ztl+E<GSnwAFTFG|JyjtwF9mE1#I2dB#UjBaiFqlBMaaUHoHoh%xdl0?6?Q^ME(=Zs
zi4}7PyLc-=+58~3zmF@7uM&`xSdx}sl&hl<?BcBhw$8=HTfrqiximL54-`)Mc|0&h
zAT{zXi6x0iiNz47`KA^ZC#Hi!H8{1XEHgQ^SkpH%xhTIlKdnR|IM7D{B%BJ51V}W6
z<mcyPXO_r>XC#)W7c2OsmMdiDA*(jiGgS*nEGkhjR!~qtQk9lpq~Ms6o0*qcTvC)+
zl3!FT2C~Byl&T7fGK*6cd=v8$(^HFtof4C?OAEl>2}(`QFH0?|WVLbi53=J+%P&aH
z(@}^o2QyfT3yVr1GGZWS6@#^eq$X$N<>%z5XQmcIBvt)=ToVgQtQ0_D=U9+fR00Ye
z1>gLX)EtG7jH1-Ul+3(zh*}8A;g*?`8kU(_4&j0=M-zjl;ZbTd1V%$(Gz7>Ffd`Xv
z7}x|DKImcr&iQ$1ndzlPiJ(fyN+BRHKtWd_JTuSONFgXSCpED+6^kZaE^r+RD%O+0
zbz*sDNrpl}QGQlxa*2Wx5zPxF9fiaag`)iY5<M=*<dV#?RE1<@mndWwLtUX!VPU3;
zRwFBDfGU_2h5S4`iZr>n0w69@FIFhY&(A4VNGwXV;^O4wR5CWwP0B2R)}_#9NRa}l
z`mivlurO0n0DCAcCo#QPK}jE6)aNVc`}!#8hZ`&CyGJPK`<E!_`zIMG=({K=g?suL
z8!3UAelD&~q3#fNe7L8di+^~ql7hZlfl^Lpl0K;UQ;?jYq@W)ep`h=U4;BPTr@&b*
z3i`<kN?=Di73G%~rxq!|D^%aa?9?J0ZiAQwvLLBASqW+aq)|`_tMzbcEiJJE*$-~|
z<zyzobUT+8m*nRvfLlGNS|RSU0R>!sUTR*6f<Z;19l8=OaAOFRMoLn13l!2ab5fC#
zMu@9#Kul0@fQgZbiC&0r091E!eqKpxUP-Zn4gEu%3va?LE=rC82L-4xt3-s_Fd`L#
z;w-tKfCwXDtz58bJ4E;<=jY~v+JQNld8rCY$vJwd6{!ji@LY%))VQ?fWaedqHS6YN
zCMm#UARi-vDCouHWF|qwBR?q%#t+j&a6tY-@L+DwPs&nK-~y$b%$&@;bUi&iE_kSN
zIf28B3#2o-pnwae2gHUarW{D49HbF0hChK>80a}UhF~Nxht%YZe1-h9G|;dI*=6gf
z#?cTM3L%in&#>TvM;^n3+?=7{+)+1<hQMeDP%#9U!6SHJ13@EkqvL;|hH2#J_+L)y
z==k60_#e1j7$rtSU^E1VVF-+l|Ba6Sfo8p+Lm=qGnwY~oknz3I@juXrC~RJQbo?&~
z6dZcs0b<yAA87C&X~@rMbo_4^Rv)8Y8U`USI{r5dB5~9Uqai?M2yiekGx+*=ftI$8
zj{l9W{{ycXgs%A;UH><_{*TO3WmMZ}2#kinU=M-O@xRgWztQnOf~zixSkng{?*cEs
zBfM4+yq1lKRejLaZbYa=S`VkhHM;%}v5IkY{oi1(f=1mpz#%X?{x`r8Flzm12n=8d
zVB3Ek&XCEF$B+Wv7fr}%N(@YlptAx%dyhewkb023B8Y(QKlWq@VDMy!X9!>j1n;K@
zNs)pD7?|Mu&xy5P8)N~R{U9N7Fc%s2n}RHY+V9Me!;r{O%uvh_#*oR7%23Xrz(8X7
zlk9(cB>R~eSQ(fD0s}ama}tY-5&KRdyH6n`H)!`)GDse_trb%QZHuaGcz#iKaY15o
zs)BkzV1T-nf+1`lm`1TCC&)n1#vkY|S%@|0qWH~#=;83pOUp;NTF51}EHx*;0J3v9
zr8K#um<zG7Sr);B?Y@R=EFRteJ-YvUbpJP~R2aphAut*OBP0Yy$A3r1e@DlEN5_BR
zTkR1er>I-UNB4h^kQ!msn<Fg*M#q0gT8xkScQgbLArN^Oa;C2^Xh;t2geUfZ!UDaN
z;sQnn4hCoFnMv5xVG{$LvB}r~vIoR^#R^(n3gQVO+vAd&RGJQw$EK2vLnJuZDTslQ
zft$fOB(W$xwZyX|H5Z#@AcLXGSvf>pyuu;m==h&D^iavs^B+gge*|TcQ9K#~qaiRF
z0+0|G9sg4pJ^wKs_tB9U$NP=$|HeEQeRTi#=>Bg=aXLzlhQN>ufzk25As1z%4jv5w
zs)Yb-{7(?P3Xp+;k&zRA?lNf1jvc}SU!cMUIfoe}%;FTL2NMe!z5iwO{+GNIh0*(8
zM(=;2TDdf8&}ayZh5&6tV08R%bo_60{om;NztQ!78K7IHpcf2{-v2_|T4&Vs!4v|c
z<9~xGHb&ht8UpkU0oeV||Nn#6**WJFyXB+==j11WHU)#6GCKY@djE53@#y`};A@{p
z?|%jr38Q#41V%$(=!d}Q_}}RG-{|<?==k60_}}RG-_WnkMtwj|2#k*ZkrQg8dPYNF
zc!YopLn=cOLn%W#Lpnn$LlMcI5@KLtWMyDr;ACI`pF>ED0bU?Q(DM&n81fmC8A=&)
z8B!VY7)lt5L2@Ku5i-tS3;~%BwI9T!6oby4gkeg}B1b>WZV*kXel7-Ps1}%R76t|e
zw(!J~<P1X?!wAMOhA~W_n!vY*kFNh5UH>_{{xdH{VRZc`tXLSOM?+vV1O|BsjE?_~
zj{lC1|BjCTj*kD1j{gqws%q4EGzx*y@n0GR?5MG$Aut3&fDJr?mxDBVJ39WS5Sd?E
z1iK+d(s^|K=ji%RJHFBNpF^ND8+GDn2#kgRu^})z{x>@QH#+_|I{r60{x>@QM{J!j
Xs&06N!07nj@QTk--;9O;DIov=K6qz4
literal 0
HcmV?d00001
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/README.txt b/trunk/PQP/build/pqp-tar/PQP_v1.3/README.txt
new file mode 100644
index 00000000..aeca6bbf
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/README.txt
@@ -0,0 +1,206 @@
+---------------------------------------------------------------------------
+
+
+ PQP v. 1.3
+
+ Eric Larsen, Stefan Gottschalk
+ UNC - Chapel Hill Computer Science
+ geom@cs.unc.edu
+
+---------------------------------------------------------------------------
+Changes:
+
+1.0 - first release of library
+1.1 - fixed a bug in calculating query times on Win32 machines.
+ added a demo 'falling' which can demonstrate all of the proximity
+ query types.
+1.2 - altered the triangle distance routine due to a degeneracy problem
+ when edges of two triangles nearly intersect.
+1.3 - now use isnan() to test for NaN, instead of a comparison that was
+ sometimes optimized away.
+---------------------------------------------------------------------------
+
+
+I. Introduction
+
+ PQP, which stands for Proximity Query Package, is a library for three
+ types of proximity queries performed on geometric models composed of
+ triangles:
+
+ * collision detection - detect whether two models overlap, and
+ optionally, which triangles of the models
+ overlap.
+
+ * distance computation - compute the distance between two models,
+ i. e., the length of the shortest translation
+ that makes the models overlap
+
+ * tolerance verification - detect whether two models are closer or
+ farther than a tolerance value.
+
+ By default, the library uses "RSS" bounding volumes for distance and
+ tolerance queries, and OBBs for collision detection (see PQP_Compile.h).
+ Descriptions of the bounding volumes and algorithms used in this package
+ are contained in:
+
+ Eric Larsen, Stefan Gottschalk, Ming Lin, Dinesh Manocha,
+ "Fast Proximity Queries with Swept Sphere Volumes",
+ Technical report TR99-018, Department of Computer Science,
+ UNC Chapel Hill
+
+ S. Gottschalk, M. C. Lin and D. Manocha,
+ "OBB-Tree: A Hierarchical Structure for Rapid Interference Detection",
+ Technical report TR96-013, Department of Computer Science, University
+ of N. Carolina, Chapel Hill.
+ Proc. of ACM Siggraph'96.
+
+II. Layout of Files
+
+ PQP_v1.3/
+ Makefile Unix makefile to build PQP library
+ PQP.dsw PQP.dsp MS VC++ 5.0 workspace and project files for PQP
+
+ src/
+ PQP source
+
+ lib/
+ libPQP.a after Unix compilation
+ PQP.lib after Win32 compilation
+
+ include/
+ PQP.h include this file to use PQP classes and functions.
+ PQP_Internal.h
+ PQP_Compile.h *WARNING* you should only modify PQP_Compile.h in
+ Tri.h the src directory, not here, because these files
+ BV.h are copied here from src when you perform a build
+
+ demos/
+ Makefile Unix makefile for both demos
+ demos.dsw MS VC++ 5.0 workspace for demos
+
+ falling/ source and project files
+ sample/ " " " "
+ spinning/ " " " "
+
+III. Building the PQP Library
+
+ In the top level directory, there is a Unix Makefile for building the PQP
+ library. Type 'make' to create a 'libPQP.a' in the lib directory.
+ The compiler is currently set to g++ with -O2 level optimization.
+
+ In Visual C++ 5.0 or higher, open PQP.dsw to build the library.
+
+ Building on either platform has a side effect of copying the include
+ files needed for a client application to the include/ directory.
+
+IV. Building the Demos
+
+ In the demos directory is a Unix Makefile. Typing 'make' will perform a
+ 'make' in the 'sample' and 'spinning' directories. For VC++5.0
+ users, the demos directory contains a demos.dsw file which contains
+ projects for both demos.
+
+ sample
+
+ This demo is adapted from the sample client included with RAPID. Two
+ tori are created, and proximity queries are performed on them at
+ several configurations
+
+ spinning
+
+ The spinning demo is a GLUT application, so paths to the GLUT & OpenGL
+ libraries and includes must be set in spinning/Makefile, or in the
+ VC++ project settings. When run, a bunny and a torus should appear in
+ the GLUT window, with a line drawn between their closest points.
+ Pressing a key alternately starts and stops them spinning.
+
+ falling
+
+ This demo is also a GLUT application, showing a bent torus
+ falling through the center of a knobby torus. Each of the three
+ proximity query types can be demonstrated.
+
+V. Creating a PQP Client Application
+
+ "PQP.h" contains the most complete information on constructing client
+ applications. Here is a summary of the steps involved.
+
+ 1. Include the PQP API header.
+
+ #include "PQP.h"
+
+ 2. Create two instances of PQP_Model.
+
+ PQP_Model m1, m2;
+
+ 3. Specify the triangles of each PQP_Model.
+
+ Note that PQP uses the PQP_REAL type for all its floating point
+ values. This can be set in "PQP_Compile.h", and is "double" by
+ default
+
+ // begin m1
+
+ m1.BeginModel();
+
+ // create some triangles
+
+ PQP_REAL p1[3], p2[3], p3[3];
+ PQP_REAL q1[3], q2[3], q3[3];
+ PQP_REAL r1[3], r2[3], r3[3];
+
+ // initialize the points
+ .
+ .
+ .
+
+ // add triangles that will belong to m1
+
+ m1.AddTri(p1, p2, p3, 0);
+ m1.AddTri(q1, q2, q3, 1);
+ m1.AddTri(r1, r2, r3, 2);
+
+ // end m1, which builds the model
+
+ m1.EndModel();
+
+ 4. Specify the orientation and position of each model.
+
+ The position of a model is specified as a 3 vector giving the
+ position of its frame in the world, stored in a PQP_REAL [3].
+
+ The rotation for a model is specified as a 3x3 matrix, whose columns
+ are the model frame's basis vectors, stored in row major order in
+ a PQP_REAL [3][3];
+
+ Note that an OpenGL 4x4 matrix has column major storage.
+
+ 5. Perform any of the three proximity queries.
+
+ // collision
+
+ PQP_CollideResult cres;
+ PQP_Collide(&cres,R1,T1,&m1,R2,T2,&m2);
+
+ // distance
+
+ PQP_DistanceResult dres;
+ double rel_err = 0.0, abs_err = 0.0;
+ PQP_Distance(&dres,R1,T1,&m1,R2,T2,&m2,rel_err,abs_err);
+
+ // tolerance
+
+ PQP_ToleranceResult tres;
+ double tolerance = 1.0;
+ PQP_Tolerance(&tres,R1,T1,&m1,R2,T2,&m2,tolerance);
+
+ See "PQP.h" for complete information.
+
+ 6. Access the result structure passed in the query call.
+
+ int colliding = cres.Colliding();
+ double distance = dres.Distance();
+ int closer = tres.CloserThanTolerance();
+
+ See "PQP.h" for the complete interface to each result structure.
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/Makefile b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/Makefile
new file mode 100644
index 00000000..15bdeebb
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/Makefile
@@ -0,0 +1,16 @@
+all:
+ cd sample; \
+ make
+ cd spinning; \
+ make
+ cd falling; \
+ make
+
+clean:
+ cd sample; \
+ make clean
+ cd spinning; \
+ make clean
+ cd falling; \
+ make clean
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsp
new file mode 100644
index 00000000..34512688
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsp
@@ -0,0 +1,83 @@
+# Microsoft Developer Studio Project File - Name="demos" - Package Owner=<4>
+# Microsoft Developer Studio Generated Build File, Format Version 5.00
+# ** DO NOT EDIT **
+
+# TARGTYPE "Win32 (x86) Console Application" 0x0103
+
+CFG=demos - Win32 Debug
+!MESSAGE This is not a valid makefile. To build this project using NMAKE,
+!MESSAGE use the Export Makefile command and run
+!MESSAGE
+!MESSAGE NMAKE /f "demos.mak".
+!MESSAGE
+!MESSAGE You can specify a configuration when running NMAKE
+!MESSAGE by defining the macro CFG on the command line. For example:
+!MESSAGE
+!MESSAGE NMAKE /f "demos.mak" CFG="demos - Win32 Debug"
+!MESSAGE
+!MESSAGE Possible choices for configuration are:
+!MESSAGE
+!MESSAGE "demos - Win32 Release" (based on "Win32 (x86) Console Application")
+!MESSAGE "demos - Win32 Debug" (based on "Win32 (x86) Console Application")
+!MESSAGE
+
+# Begin Project
+# PROP Scc_ProjName ""
+# PROP Scc_LocalPath ""
+CPP=cl.exe
+RSC=rc.exe
+
+!IF "$(CFG)" == "demos - Win32 Release"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 0
+# PROP BASE Output_Dir "Release"
+# PROP BASE Intermediate_Dir "Release"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 0
+# PROP Output_Dir "Release"
+# PROP Intermediate_Dir "Release"
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /GX /O2 /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /O2 /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "NDEBUG"
+# ADD RSC /l 0x409 /d "NDEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=link.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /machine:I386
+# ADD LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /machine:I386
+
+!ELSEIF "$(CFG)" == "demos - Win32 Debug"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 1
+# PROP BASE Output_Dir "Debug"
+# PROP BASE Intermediate_Dir "Debug"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 1
+# PROP Output_Dir "Debug"
+# PROP Intermediate_Dir "Debug"
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /Gm /GX /Zi /Od /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /Gm /GX /Zi /Od /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "_DEBUG"
+# ADD RSC /l 0x409 /d "_DEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=link.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept
+# ADD LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept
+
+!ENDIF
+
+# Begin Target
+
+# Name "demos - Win32 Release"
+# Name "demos - Win32 Debug"
+# End Target
+# End Project
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsw b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsw
new file mode 100644
index 00000000..9aad33f8
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.dsw
@@ -0,0 +1,53 @@
+Microsoft Developer Studio Workspace File, Format Version 5.00
+# WARNING: DO NOT EDIT OR DELETE THIS WORKSPACE FILE!
+
+###############################################################################
+
+Project: "falling"=.\falling\falling.dsp - Package Owner=<4>
+
+Package=<5>
+{{{
+}}}
+
+Package=<4>
+{{{
+}}}
+
+###############################################################################
+
+Project: "sample"=.\sample\sample.dsp - Package Owner=<4>
+
+Package=<5>
+{{{
+}}}
+
+Package=<4>
+{{{
+}}}
+
+###############################################################################
+
+Project: "spinning"=.\spinning\spinning.dsp - Package Owner=<4>
+
+Package=<5>
+{{{
+}}}
+
+Package=<4>
+{{{
+}}}
+
+###############################################################################
+
+Global:
+
+Package=<5>
+{{{
+}}}
+
+Package=<3>
+{{{
+}}}
+
+###############################################################################
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.ncb b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.ncb
new file mode 100644
index 0000000000000000000000000000000000000000..40973a4585e91f24a69abe9182fb8287ab8bc0e0
GIT binary patch
literal 377856
zcmeaxOfJeV&QB{*aMpL$)>bGe%1<v!%vDH9EJ;jCEKXH0(lapN<&yGpXJBApVPIfn
zC}b>QWMJU=(9Y<{FbYOPU^E1Vb_l33F#KSy`SbWc4)7NwzW@LKpFitCtWi7~0;3@?
z8UmvsFd71*Aut*OqaiRF0;3@?8UmvsFd71*Aut*OqaiRF0;3@?8UmvsFd71*Aut*O
zqaiRF0;3@?8UmvsFd71*Au#AdfPsO5v7Di#>Hp~b|DcPTQ3s8Nz-S1JhQMeDjE2By
z2#kinXb6mkz-S1JhQMeDjE2By2#kinXb6mkz-S1JhQMeDjE2By2#kinXb6mkz-S1J
zhQMeDjD`TQA@F&k0i$_cu{k#b14BD21A~5EVs2_NgMMCel72~IQF>}gW?ou8grA$A
zQks*B&ewOdib+q+&y5KP42Ul?j7dq&%`c8APRuRHNsY-(%*@kEE+{}Y0EdQx%)GqJ
zymWH3_$HQwr6%iTkYY=IN@@<NE(7a<+5!n2eTY95bQQug^NfuYf>Lu*6N^(J4#BR(
zB{iuu9aRC;>u^(uP=aDnS!z*nW_}(<%(#;pGuSmiorgVU@N2;uGx)XSf<qZS%@Csp
z8Z(e&s*hDiT4GKPIFW%ZAwdK29znH&D1X4UpyU>4@_|ai69-Dn<4}W?fS{q_Y!wsk
z>1Syg<Ki0Z9pWDV&8>PydaxV|wFi4Flb{_OvgqC>RX=LX5Y`RJhUB`v7;g$E!gjcR
zGChxQ0N8*G26+Ys1``Gb1||ju2EjkYzc$<OflrxH0Uf=>z`)SP%)lVUz`zi~%)lVY
zz`*c{fq?;3g!eEpFo=Rxf=_E=$Y5k(0O@pRWMJTBU|`tC#K0iNz`*dHiGe|!fq`KI
zBLjl~0|Ucx76t|d1_lNXRt5$o1_p*R%nS@N3=9m4%nS??3=9n2j0_C?3=9mNEDT_`
zMKCcih=9yvU|`^4U|=}N$iN`Tz`&r+z`(!`#jFer4BjjZ3~~$%46B$K7^E2(7$O)L
z7&t)gWn^Fw0=b!mfkBo5;ubcLK2`<>MUZ_A3=EtM3=FDF3=G0h|BO;J2!W{#;D}Jr
zV$cGc-UH=pGH8PNO(1?DgMtQw2ADq=v|x~dK|!BEhY@rd*dhi7hAT`A3=s#<GEQJ+
zV8}RlmhlY(14G5Zvy2Rk3=ACy&oY7{b_SGQaqui74+8_k4k&%%;8{i%1_p*32hTDZ
zF$gi}GUzerGZ-*vF=#UgGN>|$GKevVGe|I~F{m?WFlaL9fL$?4jE2By2v8#gh|2#A
zX!$=MHUA4SFu=<XaCw2G{w%2cU|>*yl_z3Mpi+ZDVHv|Za7m&M<?mw<X9QJu3Q+z=
zhOG<?49pDgz@-d>!eWNS3=9mcaQ-3&P|3s2paE6CgJCzgYH5P1w`RxyS0OW?{A`92
z22d6F6w05>uz&$n^?@obMg|6ja)t>EpsKTq5nOR9STI;IfU3#>DBqO96kJW2L-{7)
z>RE!p70w6AOEUZf9g}FopkTmYzyPYE`JwWL42BG#Dli_(H)Akk09CP3D12FlR5;(9
z0aSJRK=}~+<rzZZe2{(x23UD4$(YT^z@W@v1d_L5P%s9&PlW*_3aZ=989?T#G8BO1
z85k5Gd^LtrINt(XeRG2N86fwA+^fL=YH)z`8!{L(FfeE`OlD+2!R$;B{!cXV#f%IL
zTNxP`c0<LlGcqvTgR)ODGB8|VWMF`afnw5*k%0k*|1&T!$RhD!;vgDiza<j`gA)@2
zI0b;jU>K&48u?<Rn4!$TzyLeXb2S?SgU*L`Mv&jPe1y<PKDIM{7Gz+!^0A!})DV2~
zv7NDohk@bC$96^+P+I@g&IqdiMLxBI>wlF`?cn;~<WoDi{&)G*4zB-0pmfToc1BQx
zu>?xDd};^R|5H9e%v%CAZwu7CBT#d$d}?PjU}Ru;0;Rt|<yk&M>=F6g&KSYWz@YLO
zV!jEKc7ckAK-HyuhL}_G8Dd|{XNdc!K;@S}<+pqWoo_10AjIIskj`k#;LYH}V8~#_
zV9j8|V9OxFAju%bAk84dAj_c5paX8T*f9t**fD}yD}jtbj8TlB_KF~5BqO9XBgY`m
zpvhp)V8NgaI!0B&44faO7{K|PkwF2HzopUgw+ur9JEXjXlz(z?KBWAE=6@pw1(f{H
zKw<u8K+FG(3<|jNKPW$fFfH>tdKp6~|AWf&8islX28Jev`=I)PkwGDkp^$-rp@rcN
z_zYVH1y&|5CI*HMhHxl<0^@8(28LdSSSWu!<0?i5hDi+eP<}pREh7WN3~<@k$;!a6
zk`+?!`7$#wJYyluUIi^DLF$(<GcX)thUm#-W?%sEIiY5-vNAA8ure?_U}j*Lilhfw
z|8!;s1`xj;$qZ!v3swdOCN>5JF*ZmUiOdJZ)p;g}eh|By3DW-8WzYp>dxmx>A5y<D
zFu?i)+6>xYd073f18s>nvqI8mIul4IGs8z{c*!t<x^8R?-=Ta>CL<<Lm+k?S&&MRr
z#K6GAkjf0vKZju<1GtL`mDgtUU<7sjf}s3H#vVpcH}Nl&Z^q=o1gcLbFflN&FoDvm
zFStJSgqk;*VFm-JtJ(|YZ)MoUz`&rw&;aGHVc5vPz@WkK5bAzO<}79g1|2wm2@^jv
z1A_s>aZvhUU{Hu+NMK-KFlOL|>ThP~U|?V{Ww-&APhrSnU|=w3SOns;FevylgfcKN
zSTY=dn%~VdgNcE`hM^kj{!@&X85tPt8NNf!d%?iU$iU#t@EgkKVpL~jU~p%c2j%Z$
zc*4NI;KRTQ)$hX?&d9(Jz@P}_$1r9wGBAWPm_qIIVTxs9V2EUBV1=}2l9^JO7#N}$
za-sYLrbH$NhG>Q=C_j-YiHU(BhM^Y9Phv`DVql160EG%DKP_cg!N9<fz%UbP-wnpQ
zj0_AZ3|FB1Ka7k_3=HWE=b-#AjNcg<7_u1tfx?4<L7|kPf`Ne{mq8EepB{#O1_p+F
zhJ{e|j~GEMvqFX>D1SZU7Dfh!Qij7&{!7O9j0_Cr3~5mQ4#vHV3=Gu_Sy28##$${O
z3=IryQ1empKf`GLhm{AQJdd3J#i3;gsQduQ!Dvu9bqZR>fz&iX%O{XHsJw!eU-<Z-
zG7MxUdKrhzSBIKw%gVrD!OXxA!pgu<fQDgaJcpKtApM~75~Oz}3j+f-Hb@W1pD;Zj
zvq5S%LG42}1Edz0II_9|s9u<vFdC!=#D>X(_--ty<vKB9Apd|1*->IN1n3k3pvJx+
zQvV%X-^U>O>)`sH9j*Tl9{)20_oP96Hz6$o{r_ZydEowk9)rShh6~{SKdirhnc+Hk
zxLb-F(jI7JT*An}z{W6_i-CcKn?b>j!5%a`%y1sWXJAlpU;y1dz`?K+%C~250QdJV
zLHUjh&fuYGTPWXx!4fpw%mD7sYr@*wJPfG)d0w>sJRbu;)IE0@>cK<c>`?w*h9ltd
zgWp^b_s#>4KZr1Vg!20t=77fwUV!+T3<^cymXr(wxc{%opaALr%QB$$|K%Y4e;1HE
zs6Q?b=^rq_+^c}rKTw492l5ycZZX_q0QLW2{e_zhH$lVa3|B$+GcYK)Fyu2ZFsMPs
z3-TBgmN9~2LK8Ax0PinoG5A2k3)ItLV9;jB=7zK%K>Z$2`^X(CZwVeB(PgLs$#XC$
z*f7{JFfiybG(+Vf;~n}8F;G5aJj8%u0+bKwPZ%<kLiq;Z@ew0%`x;apgRn9;1A`Mc
z14A@71H%F?2;RfRzyQLabO-DAgJ_U?7$&7J0@90)LFS<MIY45_{SJ`*FbvWU8n4LW
zf{a^$XgXzIimiDE9iP)<&;y$V8xMrF??J6j(D)v#e{ch;9@ZZKmlsIo2e`aIAOB-P
z%l`~$<9`_p3b@AqP{;RJ7*NOeSQ${q_c$3qtw>ON6*9iZ1D==y@gd`Tf()qRdqR-%
z0G_{u(aHl6wDLfd0X)73?jM83_rw^$<9jxs{xN90OdOKG89@0LG(IPRmcJz-`5P<`
z8jpka|KawN+5fkpasQtI<Uj1=f1rE;!ldLmP`&}>85o9*+rjwAG{|i9yoj6+k=4S?
z0Vm{9f~XK6s{ilGpa9G7u>1`x9|lGLpONzZKcv5p=>J2;1EBqXCIbC`Mg|3x{y*br
z|9?>R|3}dHAE<0aAMZowgZjm=em<yg4=Q6}d>9St*N^u985ltQcG&m=tbY&c>x04!
zMuXIV*f4nzf3*KkRP{5eXn;ci*1m_;=VZ0-k>>aJvVmsR85D9Es=@vFiBP^5Ln>&t
zkYPQPpAH@`XN8X^TY~$Kobd5q1Mqx1FMRyhiNOOrKLE;ipg9syIX4eFzX1{pWn*AS
zWn*BdW`oSDpz}d($N>)OQR_!TV9<qt1v>)+e=Ml|Y{>vxu=$=1JPW6w&7cQffC<je
z$qoz_3>FNW3``7={OrI08o%OXU}3Oh2QU0oF=8-g;ACKB@CNaX8B~lJOc^*C*dY16
z)PVuC-h`8Zok0gA&)}c{TIa{fz`^i?je$YX5X9GI;AG%r5Q58t_*@L~D12@PCKeV3
zCPr2UCI)5(CI&VJCJ<!gU|<5fj*EdQpB+4ggkDC3u|wuUS=kvFkny04kWmMXh5#Ky
z;1MTe{vX!AM{f@hHNJ<X{%>Mv1&{B83K4-6289mrd@nPk{9t5I@M5R}ujhlc2O#sc
zY>@T<6N3VzJ-`KN4-|pQC(!yjK1h3ji9rF<9uNTMbx{4!&k4!jv}_YRnOI~FTGJfB
z!~k9=02&bktqFlemlKSEo#x<RWMbf$z|i2q(7+(Tpu*tT09L5M%D~vb;H9O&Ai&7b
z<ih9)ZYVK0Brt<R5Hv#rR)>>NY=O8-myLk|R9=HN0)R_#s1A_390WkCtf2xVQB2?l
z9cUv0PHl`04%p<Jq3$}##sIDtxWT0~#C6!zQ(X+~t_A^yCWi^2%?&W~b)oKp@kcTZ
zuKyK4<GVKCjT?yiUmv`o1eBfx3LF@$7_1n$L5ZIelpGuwtQo8sxEY}NITO-8;AUWD
zSjYis512BTGjKDo!P^I*^{Cto?BH}D$iSdt!eGk4&A<U^A1F95STa~La5Hd1+6M{_
z3ZPv8+zech_JIPVeZbAYjnY2gX5c|;ALub~Gw?#%1Xk<}Obnnl0t*8Z1E_5PY9)Z$
z3tS9L4BQM%MLY~lOq@8&4p84>w7oErbH&K<JE(TSnEywr&tc>J`1b!mw!T949Kv?8
zVQg0<YL~E0aY;&MzFvkMgH3K?Nd}0a6c8Aom!ZS}+DXiinODMq-5~f5JlGaWkWo3A
zNgyL^+<o-Zb4p7<Y$eF{(hMaACD@iuC5EKZyu3;V(Eep#(EdAylKi65Vu)ybNq&4v
zQDQj*SVjvX1s4Pv#*mbno|#v{kdj}Tl#>eKRWhVx7BeJPW#%%Z=A@P}q=2|7V15c%
zpeVn@kfA8Q#0W$fGbH9^<|dY;GI-`?mV{-dmZuhlXXd5kmot>*XQnWCr&cEACl;kR
zJ28~z6=$aBrKTt(XCxLWWT#ewf<&PLOja`Z=9d<yIy-@R@ktP>7(zjm#Dmn7Waj5N
zJ2ANXgrydhq*fT0F{I_>CzdFLDMTw6E5t%Q0_Qq`yypT60@u70FzuO=1G2>>v$!B9
zu@Y)uVo`cB1K3qs3R((@Md@V(VhR@g44@c}ch1i($jnIv#k5jYRaF&;;Ts>|$&j3%
zS6re14P4)XqRhOKbf_RG!h&2KeH45lE{Bi|zG+}p3~ru2t_oTTX$%lu3}Ikl49zfa
zhe5SLlri{brljVTWR^hE1r}?<FcpNrT#)PwPE8P9MG#R4$>1B3?8^|A9EMO3235e|
zo1CAM90rcBWC#Z&0^t`i_*VE9gkkvH5MnHZ#E><Dh(kzpS+HwCZA>8sVFnTC{=c_8
z3=Bdpp#44i;6f1G{;xpH-{UF|j2KK1>w(bc|B=cQ(5e$gO|<!c2GIOJXaxlm18hAI
zZ2u2k=KnQe>uaF%|EUZLkoC_*&i{kw$C2j$HR(M6pU0pe&sd1q|D#0Z_5Wc1fqFZb
z`+q=vFAyG7^Zx{@2v8ZXmjNl!Ly9ut3@fVw16b(?DGI@ben?TKl~sWuvN9tiP9B5}
zA+4<PN{TXzVVn{q)3q2bGBAMK!=N+`%3Ppu1FbKIt@{M6zz5AWf!0ie*3N>~ipMfA
zfcJ12F+w(CgVvjX#<oD~c|m4?_91|17zVAchOuEZs7()JgZ2b~*3^U6v4h00=Ko@}
z{ExmK5Gj9y_n(z8C>SwV!SlZW1A_ue|DOS^|Ia|6|Idil|5rfk|1(mr{|_23fbCNQ
zt<3}NO#`ht2Zaqb4BB%6T7LqP1I_V)*58BJAPm|I0NUIG>OX+i^@H|~faY33V=AEh
z0ouC<TE7pP9|WzF2aO|u_TPc#4MFRcKx^qi`%^&s<Uso*Kzk`b`%yq8BWNE5bngQL
zXw3y^4+?1S0;taqn%e-Co3M4+pgohI`AE>3ZP2=A&>E>_43N1I(AXzvOcmr_(B25p
z{tM6^8PGlo&{{;$`g+j56VM(M&^l~T`45^C2CWMN=>cKT9t+UCF=%f9XpR^p2HNKU
zqCxu=Kzji}>q<atEkWz0Kzj~B`yxPl2SDS;pfMkiTF`tAs6GMhQ2?#o0nJl`#6f!$
zK<j!yW5FOk2!r;Kg4Sw+*r1h_AbJ#29s=P0Ke&8H>i=hg*82=#|DOS^{|}xo&}AUH
z|IYyJ|L3zXFfl><|CP}Gzb9xEiid$Ik<9)-XxGi?_#bM*1CO(z3W0c|<A0z~7~B|C
z|MM~MGYBBJ|H13~k=p+OXzl-0wEY07sP#W+y)bON090;+_$2NBw_#AAYx^I*{ubK)
zXP~hC4_@C($MwGqR9^p!zW*P*zIh0>{|9%L8&s|%D*rD*%l}nq`JVwb|AWT&QRe@T
z5SagGgpBVKHUG~58q)`j?K3kl9l<jH&p_JzKd6lgI^P1a|DMeJ56&M*{eODre;X?2
zfAIbWkbelD{{ia5f-tCm1M5eD_^`7*Kx|N-ijwm_K>Zt#IiP+8hz9k)M$iACPB8)+
z{|BAx0UCP%o#&y$!NB0c0Xpdg>HIJB{(co`d;oF&mjHu<f+T|^g9rmBgCS&oP(gx0
zf<c6Vi{UH>c)n0UltGk1gn^qO5hBkZ#URBX!ob4->JJJqI4}r<#~}F_?nBj!F^DmU
zFbKfs6G1H$5e7kqX`uPV90nCon?-~{h@l(AX8`f}7(_rPaDdkfF{tn`@G^)nh`{F?
zc^N?Rq6}L>>X{i-1Q>)EL>R;%^N$P;V6`F);tcg5c?JgsRt7c(5e5m!d?bT|0y_f-
z_|y;ZdL;%21vap}6l6X!4aS#-&quN`urr7-$S^R0=Op<Um@;`FbC2m<3`{xv(0NG#
z$b2Pe?NSai1Ct)8TmzMF><mndObkp`f(%Ry!VF9dA`DCnq6|z7Lf|>eLQV#THcrSo
zN6@+lNlpd^MNS3=O-=>|CnyGuL4f+uAR08r0m?T&I3Q~zKw|(P43dM*bAs3)F?39w
zR5ohLU=0D#IE@ekgM#irp8vtYpg__2AK>~5>HH541_hM!KR6f^P|pA0U{Ijx`5z1<
z?*9>BP{4cs2M1_=1T=~`K<9sOFer?k|1mtz{{fBTg6am)7%wtCy8j1Kzk<f<L31*o
zIU3M7Jt&MoW9!H?NDW8~CJ*9+<_19H@gTh*wZw>l>=>-|#HhQ5X9$4ibwKq$%K5+g
zX#IWk_J09t`yZqq7CL7^=L6(2D1Z<DV}Ptj1<eQMfzQKW1|0zgI&fNHKErbGd7a??
zKstj$DnmB-{0>NefI)$s0W|Z;4Q-z@D8w@)F@Vks1LY-r?O)_JFQ`ombJr+68Umvs
zfEfbd^FMMK6wuHAfb|DJtxiz>#=Acd{rsO~#P}e%JixO42k-em+zbjR=l?L!`TU<e
z(D*-OzXACCpF9Qyl=FWy85Br5|AztX{2%!EAdd5Y!15%V|HDAw{2vaq^M63+uTXOS
zPabG}2Izcb==nbkB%c4{0$Ohlnok(M=l_7#Y=F)I0<EFI%yolD1T_992%i4~ozl<1
z0BaAhf_DQlfKQziN@q}D0WE9+ozoAh-_sZrm>EDb2hj6D13}C7AUi}r>p6sS!FNf3
zJqgbLsfhLfc>NzUgTfMqHQ?PXpmi&Z%nS<a88(CW3xm)9Vq{RzWCWdz3qAiUlR*J=
z(k|#~3E25xp!0M=S4qIm|B?k?Gr`FKKL0C?K|vmTjRY41?EEj#3P;ct8L;tw0Z=Q1
z0df8pKlpkJ#Q9&K@kY?q8Q}b%#-Ol`0dyWGKLhyuFGdE1S>W?Z1sK5Re=#vARD;hO
zg`WS#!l01DP>DGI3w$0(Cir|(&>ADqe1jnPx(r1Ahw!22e=#s92!gM@fS&)w$e;jm
zFZBE`RuCU_-G(BA9`yVy&|V18)g2a4J`ecX4`l{LD4!F2O@|8PJTMjp1tkU_@cCfi
z^;--K3Vw{o8A0cvg4UUV+y@$81&snLL-likcY`3#2Ls*906!m$g+W0Ke4U66LmB8i
zFa`z%aqzVyx(u-M!bHH=k|53p1C9SOFd)tc1C1Yp&Rd0@4<-e^egsiIfX-WHU@&5k
zhq{LYw6ToA7(5;dY7>I+K%Ex`S}z5{pu7%p2M8n2QGnz?ZBY=0wNGK?1B?dg1!ovK
z6OjDR03Q8A9{)$l|A7SZe>z(JhukFt_6a!uGoa;v2DJRofR_J3?FHog&p;smvoI*2
z<bMXV{LjLmfH(iAF(}~8{|spPp8+lZGZ4uC;PF7D{Lcu=-=O>p&HrgIJ~aO`f%u?n
zZ=m^~0hHfC*YrU1KbQ~F56%CX3<`MjKQn^@O8#dcG5<3%DB#Wi3<UB&BZC6o{Ljb$
zo<G8w|5-uupzDsH`Jb6VVKo1Pvlqn#s1}E;{|BG*2(FXS4P_BfK;AxyE=_el_aw-E
zR?wPN(0P`iI|@K`5zHbd7X}6gffj)Y3@ltOOI1{v1VCqSvM?}kOoS<+A`L1bA;z8T
zDjwbc3keETa)_?~%VuW)pN9(B8I6c%nCAv6-A`a=0H5nhk93cm|6%@y(1`GeNSy;t
z_uJVA=f3xQ><kQ`a|}TDih))efZgxGz#sssGQk{tgaZQuBew19j4ily!9xaglN}aC
zF=>$SVgt!@f^HoG?K%cszlTLJ$wG`R3=J$D0<NeUL2d$JR8dr3Jk(uLgUnrT(;?wC
zm2+^VuZ4aPckSjJT<J?I1>&xsoD2-0^Oqqjb&Md9?IFY<Fp+`bK)`AUpFssmW2Zp*
zAJo^w%qj$`{3HPZB_<9Tl|>w&${1|;V`x0KaZ~Otuz^?!(%r@N{*Vpm=z^WxgDW0k
z?s^M45@QgR6EJtl^9-)~5$3Ky9{SafSd$=F5K-E~+||l6IMdfIP{oKNec{gkU{B&9
z$ghWB;f2TWQK``o7!3hBgaD`%!?ykxW&DrS@&8n`@qeWC0O0X|^zlDNwDCVywDEst
z0^@%SB#!^3!N${YjQ_KM#sfhuBE<b4c*p<I$Nw16#{bdB|G?w>pz%BC_#d1P9sdLK
zNf`fQATa*NfHwZeh&KMmj5hwy!k_?Z6N1KEu#W#TGAN*o|EHmi|1l95|IcJl7#;s-
zU;xbz4)pjx=(2dwN*mBT&|n(}86E!vjcbBRX#5qy==py*!UsGqiTnJ&(eXb92Kc#I
z;6qW83kn$Atzyzs^K)ZBrz@2i#-ya?<`>7nj`fNGop_a_m%)&hn3I#4myU7F7rHp)
zR4}Y&LY2aeL>#t~3_Cw1Hxqigij`GvVg*bz1#<9Id`@O@2~4cCI5i%dxO-}eUukX#
z(wQv5sU@MssnEl#d_YEI=9MUv7N^3D0-bRMIu-^boSB!BS^+&Ds|ZS`L+K=#2KUqw
zr~C@v%sl7`OOV5=w9upx?srcu2~JMTNrjy?69hS*2|~gI!KX7R#A1&QSkS@G&>|v$
zL2;`DKM75VK`A$}q%1WVbkG)l-LMnY${8{k@=_Cv;tO&T^HLeo5Ul*NO6U=0nR)39
z#U-f)40)xwNvTEg`DyVWZZYKCG{g9k)Z&uV6!6(s;OK@PsAdF{0H3^O2tIKw52D8i
z$_X+A>jE9ArJ<#u2?;C+$q<4~jv>g1A;gFwGcU6wzAO`TrdoVC<WRNbr1)IWNofpV
z2Ix365Gxyc${L8BnUa$VqM<2@!6!d4B_OdR1MUO`4FxR)HH9EFhk)`7$c0ep5STRV
zV6?Q%oYcI;+*F3b($u2L_>#(kREA=3QYgvKNi9muOHO5Qwu%Y&^s_XLad8dy4)G6w
zW<)(BJy>Rh#XjgrJUvjflAr~i&7pd5l$<E@fTQF8sG$U}kwN3=s8V3w==eW47{CN5
ztUwsd!9k3U|Dy&BJiKtEFKUkequPwjBYm8Gu#W%lVm>@N{tt~>P}%}vC>JXQ8=oC)
z<NwQ`@i^GV|CyK|>1!yC|6@%6L<v%3{GSoDa1b;#r-1kVUl$VB|K~9%4Cwv8c?=3D
z_y5v+{XYkT0^a+739bLvWKcl4|5uYi0q_04gx3G(fzEFP-Iofz|Cf9Cum4Ync56Y+
zbN#&JB>mj{l+v73ed4-WU>zliMd_&}`q0)sMo$}`8c44jtO9B;w7HMbs{rr+VZhw~
z1KaNd+y4XG4+Op+ED>}*pf<Ra0G$shq(I>Q?_$J$LfH8KGKO{FK88LMXp9TAza2CZ
zIzZ?Dl6wA^CM-Qe@Bam#p9nfH2gm)tsj%~aiM;<8d>%3A{4g2tIxt2h28G28iy0Ug
z<RJV!28Bfopw;9G;Pq>u`;Ae~|ApV@tpYwf7POupbpH|qgDL~)EKU|p1_cOTjiHng
zyzW!MoB_1oNS%Qb%7@&?Jv7h%0j<9W;i0r20JJXvlmqBJCjeSE2io6<_x>MNwESI+
zdw(DJzK|hw{_mBa?TlBL7#N=XYzJ>y{_?Y((EyYOezh}-GMF)#GZ-<XGlFg}F=fzU
z0Nq-q&tL#P2}p`TngO&cNrgd`L5)F^!4P!%5F=<GOdw+rV-%x0g9d{jV<e*%gEoT%
z18BdJ0)rxh5`!`W3kzs{KhpdkoKNKZ9}{T)5~Lrx{vUn*FOxw5W&cka+Wa2_gMu;x
z=)4qFc=-{;c$)nEKUmlQLuQr1`+tzu|AW@6fyyHZ2GDwbeTHV}ejaHCX$H{x{}?DA
zGCyd@0NW2F%^=GF+W%7umj|gghU^DogzX0~8M6C<1}gu9`huYQKS1YMfhu&W?EfQT
z{(mXMT5$aj-v7tIps;~q3u6Bt=sY4u&`v$*{y+HqK05<!|DQZ~i2(-#Z2uo9e}N7c
z0Pp`}U{FwCP-0+UAanm8Bj)`7b_Q)m(4AV~{eKJ$3bVoWFLeJOBZEQ>!%PMS2I&4j
z2GISdp!?0l8D4Nf+BX5<`%YyT!2ADLNzDJup!^P6kAP$UPa28y|LFOjkwF0^|1+b_
z|D*5!VL_Y!$GZOyDgQGd_Wxkb|CtO5DEXfWwmtxw|I<M7c=A8PX#NM~U2^c~{6C>k
z1C@{vHKY4~AmM;Pg6G*WL>UJA`QM}S|Cn)x5J9B-(fL0_sDN1TkijuOGdlkV3MB{z
zg%t=xc-YC&`9IWffrl54^ffyFhZ<feJS_W?M(6(!Ap}ZWAdC>fWR1@MVTK8&2qF|m
z=l>9)0}2%oMu=dtVCf6_{BO{G!XgZa^S|vF>=5UF=P;;%#;4)ue={(sfJWw!&;K@K
zFhe>28+5-g^7-GUV0q~I-wX^Y77SJ>=YQKU*f7A){|*G*N1%st{x@vY4|e`H=)5!$
z2I%?U;QNX|>JjIEgYGXzIsco1hk+@Vn}I2pi-9SPpMi-HbT1Lo`QHqn`-zaw|7HN)
zSv-3FH)iS?6`^JbfbuG6uZIAG3-|;q&|QK2450Zv&?q<T{7wf3X9i~m5zv`mp!53!
z9T@Bx>={HDI2Zyzd<F*vM+Qff^Zy+fKxgVB&i}V%uthol--*Eq<@|rV`JVwT|K||M
z|7no>#mUb9;QPiv`5AHkKSlX}86N{vAoToy2GAYkqxqkjX?WBu@<ZVBL<2_ix?*$C
z7W8&j1_pi5^5kL$@X`Uu0)))Gw0sC3vXlUwuaEt<)x_L_oYWZj5@oP~5Cd>%fbT?r
ztv4rL3w#+o@me7J7|>T|VD}2#W#Glr8IZt$1de_&*q?Y8XP_xTTAKkg18M=>6e5%a
zrRJn27N<hoQkGg&oSC185i?j9n?Rg{J!Y_LfI5#HEm&iQfGyxqMvoa{^gv?<n#!>1
zfG(ziF3urA1Mwa~wSp*rz_p+xeQ4@{O2QKdO3dR>gOq@vp@D1t51w5G$eD=*?O3Ca
zRQ;$iLs&PyL`{TlyeXU%{bYI`V|$f60|SEzctVtcLGVxUugx}m;4)r?5p)PT14A1#
z19$>GgqZ<+(B>xw(BY;G3_VN?;Da_nib2~sGZ;aKm@+W9GlGsGVqn<E#K0iNz`*dH
zi2;0I=LSZ|fl0?fbMg!f3?8hYLqr)E&M-5858zZ}hFm+{4W9gDVCZCFU;w!-f(bO)
z$-uA=Jju$yaFCG!e4wd11L%-e2xetqVDM%EEm~q=SjEf$p5TuFANtO~@QIOuK?vk#
z76$OdzBmH|1Ly!+c2)-P!L8lk!{8YhRGApS2cd%eLplb}ON{RS!xwO%Gsa3liRwc;
z<7zer2AvP>pe_N!mX8qn$j5fZ&w>mLS3b5gf@XA|d~9c|;bCC-^0A!}bY3XSC&>C4
zkx%W66IdA-R6eycz5ylPPmuLAE}z;NK@l4QrBgn&GjcI7FqA;)mQU@BpoBW*6U4kF
zQ1iAx%{u}$=gKF@x|}Ca`U_N^<uk+{k<aan5zGt>DxV?dn?Pw7sCWoeUCL*OIVGPV
z_O*P5xPJ;%ehE~5%V*H~AA1G|1~2gXA8!U91~mpF2GF<yXruvj9xY`3j|2l`U5_P>
z^*^BXL0aJTKbj1nQ4COs<BJhOa^$bO9zFjHbcnS>0_e;e@M13lK|K=A|H2&v!)O1`
zJx0j>jM4MIz-y5}`z>%sJE%g3o|iV*_W!`fjYs$YK%x&^QG=K`<_Tfph41_?kaqGg
z`SlRYT~r(YPXmnyf@)=920Q5epP+ggKK>WTphD94KQ+hyf_WL37@+rmGI297F^-P^
zk(b^^b<rXOKxGJMyx)kx_&;R49(I2hY(4-n{tp@NN8JAlnIFJC{tuZiK-~XJ)$xC3
z0^|Q_X!C!84h$&sf7HzXp!<Ir`52f$^M4H73``u*{Lg?i|Hs0~z{CKZ`(tDW&-^ig
z<^zKS8JL2E8JL2g_y6XP-v3LBJTQ{Y99{oQDE2`mBt*^V`d>&mV36Q(HVo0x^}m=w
zf>#7~?*%>2|HthhM7kec|BD(*@Q}gL?;2hIiwG}JSb;D?1d}zo{ueb&;NgWMeT}aF
zMGY?$-st*YXmC(IJ~P<H|3=UMfkrKqB2-Sm#@Pnz_#f#0PT2k5y$qAVQ@*hKzx5ef
zLDR$V`@h>6x<>E+hQ|9SH5vlc3IR|Vf_(l5>^vY`=l_7u`(Z#k4}^j6c_7mmjxaF5
z)(<l<C>&=v4_*oa&i@Py3Zwa-S}{6m&S(e_9|Hg0|9cNA1HOaq2!gDl!&qsECJb3z
z2wSoSSB*m$wp<bW(pvE9S;WFpo8pp`%zV8JI|iHF#F7jULn$CI0CYw*XeBX2W?l&c
zc7rfh@PUlV$xH$nVFN$)+Kxd9vhX)Ui9rdrq*I9@sWdOI5`4BZ_)u!d!P5}Y_>z3^
z0o0JgyrIWc!v#TxF(jp?XXaHv&+UfrDj8BTiy0EDGIJSHb5hF~Qb61kFh2z>P?TR{
z$WWADVgw?Lp@(OuGI-`?mV|-Nst$)7Rb7^!nZn==J(=3siJ>&FI5RyjHANvgBe6&!
zJGBxNBnlN^vXa3UbgH$p6POpD1fhx{6huipNDb(~YiB10cb~A-qLS1K<1*-Z=3&s&
zv?0frE5Nu;An$?BL}zf#O99iKDLJXmP7Kf^)S>nz7NsY{j=9!SNGwV(BM?)t;Aa5E
zaJ+MVZb4>FDk!Fvs;a80Kn&mb08f-7)fs#XiZb&`(xHOz)3$vfE{Bi|zG+}p3~ru2
zt_oTTX;57ZVPIhl%`kt4LA61YG5BVtq~?`mmO#=4_)u?DYr-%Uz|L&<P4)$+CWx*g
zh`S&pgKtQ(FGE;z7(zi9Q~`r;a(+&77&yL?AsmnhgkQwqTj5&}hT(HVh_Mh7L)Hi)
z4k6KH!LG$P5D?3PVDO^W3?dFDhZGcu>`cnaS=iENQuKfw23lcFvZf3Mo3xz##1c^P
zU<E4wpe3de61#wffdO<a`+o)o21!nE?}Pz#6=V<#1H)X<8b+ud5CvNQ8p_7NaGj9>
zd@vB`XbI4@D)&L_ZP^$YK;4?N91INhEDQ{aoD2-0rIVne6;HA;Fo2GI16>uW$;rTA
z$jQLq!^OY=y3$maje¨Y!wRBLn!DBMW8*@OG<cZU%<)ObiU5YXcRz7#N;2F)%c-
zFfg2BVPF6qnzV?CfdO=!)O`*HhBOui2GF&d7F-MrtgH+SpsPPYNAQ4_LdkP6Fj%lN
zFo2F^Ok!bR03GcJYTkj4gzM&D03W@j!NkBI!OFn!k&A%=biD0PkY~~GbkKS_G%+D|
z1_n^mt`HP%3=9mZjF77YLB}6~t`vePS7%{h0Ig{T9RtP5!T>&ga3u=^Llq+fLkKGa
zgDWEg!#hUEb${V33=B^h85rL3Fff3Q6$6>^0<_2ZKKZJMB?4PnB*%nS_2nP5B!
zJ&&1z;U5!Zi`#E528P9q3=C%(7#Nl?GcX)tW?)EVW?+zKXJDAg!oUE!(h_v^6G*2X
z7XPv{F)%!1VPJ6LW?*Ont+i%mU;tfTGl7W#eB>f%NFUq{XJBBs0$T6Nz`)Q9b-OuI
zntK41`^dt;@STN$!H1Cn+yw^Ni;P*>5j<N~1_p0-1_mc41_nze28O>Z3=E#k3=CNy
z%)-D>%gVr@!_L6)laYZzmw|ynhl7EkoQZ+Kg@b`%8V3VII}-!LRt^S+237_J(3PSv
zlk1U&AIrEIz(=*g<Y2TdG#|7<;~6BL&B(xz2Mr_8l3|b-=vX%p4Z<r~85p)QGBE6B
zWMF7uW?*>0%)s!SnStRqGXn!F3j@O)76yh`76yh@ObiTrxEL6i*ccevnHd;BTN4AA
z7#Kj;5c6|0Fo1@qK;~@%r59*erm`_Ggdv5^JkZ)>kRk>K20bnYh8fVX1}z~oh3WxG
z|3LC9h!5%pft2<#Gcdg4WB?!I1rk5Z!T>&kOp%3wL7bU^;S?(a0~<2~!#zd@h6Ah&
z44~ubq8J$%7H}~zfQ}-Q;$~m~A47>0J|J^o7<Akthz&Zfav=u;!&D{)hH6k=gr?Pp
ztPBjDtPBiSxfmF#*%%mdSsB1foInd%K}V;$f$}#4149!714A}w4;KRi!v#hLhER~>
z85kHALempJl>ZcD*(e?j0aysY_WyzM$>{z+0(}c`djq;P3A*zN(&T}6f?&NJ@ZKrx
zN+A6t6a~=E3)~bUl%QBNy8jP3W}rLXM)&`L(-<@~2)B@-`wS7ScQUnuqXN_@r$j$A
zlM(HBNH!$b?Xa;7%Jq}!d4vPN24sNu*p2T0qjdittdbk0afSeBH`?g_KL!Tu`~Q3y
z{E+tl88WysxG}ghc%YpBtqnaF+!M$CKhVh`sQdp|n9<Jv1>g4zI?tQP^S>ED=K+J%
zL(l(aq450QOa_GjM$j;W1_NjS1hf|zbS4b^{@*kP1uh0q??MYaI02H!d;c#3=>A_&
z*H0JRQD<QxaQ-hd=zL$$dEN#LppGKQe3bLQnLzTR=l|lu$?I=Z0wKf0d(&CH-c
z==^VOMn6W-mT=HO8z?=<GRT3qmSa8tJCi{H<^1n7wDZ3i85D#WM8N9_Km%kT^8^?`
z=V{}(|C<5r{BI@(h3yQQ;4Sc=K_Jk58z|?0vk*A{JB>jB<@|4We#deDH~2mPr2D@a
zLHQlzUL5Ctv!dmHMzr()83~{NAHaBm`1Ajn(a!%SbpAh~^S>ED`5RCE2g@Vne-_aB
z;2`zT^Zyw}&;KU32mt5*Tm}V{{GZC8z{&s_9Rm$g3k5PLuz*IK7$AehLTL;N%%Hh^
z1_lPufU!_I=o&A`h!toc3RIrJ+yfd=1@U3~twDp$p!|b3|FbYCkd*%!(DFa2=l`dH
z@;g5R=!gu^fHMo$^Z)VWe+B~ipMgOBXM(i{p!Gj`{s-6hc=A8`{T~cy`JVwT|1)FW
z|ACVKGttifXCP4jqvwAXwE8~{t^Q|ZP(Zo=gONb~2g@Vne^#{o&pev{Vfl?z8l3+b
z(DFY6TK-QbkpBbG@_#P)at^Rl!1+IwK>;QIGZLu(S<&)8GlK$3{h!I8K+*jlX|Vc~
z$oiiVt^Q|3yZ<8%E&sC+xc`Gt{STH$s{hgRKe#=B)cz+m|D)gk!3=8u<Ej5y2;_ez
z1_d$jaY8x_pot<-dtaOZsr^sw`kw(U|Bu%H;Jii-0nY!aX!$=EE&tQI{s)~uN=o~m
z8Lj?jL2LiBP}u%wK+FH=_y3^R|LFOj39bHTgw^-Z_CK5tt^d<N@<{m~US8p7|1+bt
z|IzRNLa+bP^FOG4g0KD0N+AEE*Z=7Ke^T>5BPf4^?gxY3|AXHCN6-JG_kWR-^}%|;
z`JdYLKdJYBF=F2TMN#{omBjqdg4X^A^Fi%xJ_gW215kejZ~q@X{}a0Z3tYd0>ThWN
zhx4KNAIwL}|LFBUm=Dqq9si@W{%1t1|IzRNLT~>wqV@k7(dz#+wDvy}TKhi@t^JRF
z{}(ua<H`Tbpz>j~{}0Z<6cXV4Pw)PJCV}=pGg|u}{r*2@wDvzETK!L`|IdQf{%0jI
z|EHm~|C!L*|7mFLe^CBHzW)!Lzd`wz%=`~_KS)23`5%4!kC8zCpMk>uKc)3Qq5Kb)
zAI<+1W__@BaQ>%u{ZFX>&p;smqqqMV(fa=kX!)Pe_+J`Y`=1pp|AWW-k;ebPd>YpO
z;PyQz|KiC1;PF7D`X8L%LGFRJ|G|8aejNFqnZWoTq4qx`TK;FIu>DW!{lDPxeWdyy
zef$qS|7VVl|A8|z83Z{04|M;Zg~awhBZ2(SjMn~VK+FH&_A@9y;TZn|&j*0yq3wV4
z@jvwbKdJZsl3M@6%PVO92fH6B|1+ZX{|Sx%qvwC{{6C)YKlJv08e01wz5maI*8WHD
z|FfXA|Iz3F(epo{{{QIs9~n6xq6M7)sa^jQ>i?t9|C5^k(d&Qo`F}#~e{lW*<!@;I
zXGUxP6RQ7N(Axj#{eLF3_CIKR4PW~oef$s1N2>qf?uF)m@OU6n{zvcsqtE}dpw0iK
z4RHIP6)pdR^EaqHk7NB0SRQHq4?I2yQa?KX56Q*kli>VM@BTlb_CF(9|38hw_CFI^
z{m)Ec`=6CS{wFm42cF*t<zF1_e{lN%PyPp&2O#}8+W+YFKYIR0um3^i6Y}^!sq_En
z<A00<>VF2b{10y5gYq*p|EGb*_mJBEETHuPNckVV{XaVYPj&$S&i~Y|{|WW~(dYlu
zNNoR8I{y#OKS=dIxV}f~|1*Kw10Z>5`=5ox`9DUq`X7D#j}<h(2g<)h=6`s31+D+V
z?g#0I=KnMb+y8{-{~6Kx|11RB|I{A;Bb5I~+y9j1|AFrRGmx17(cAy%^Z$%!{eMc=
z|B{;j3Dy7L`W=*iq4^))9w2i5j|tR%0qKY4fAsc0`uu+yTKk`c!uCHaiTNLW{Er!}
z{s*`3k?MbN{f<=sgXNLxe{lN%q#oM-AD#cFEdNux{wLJ`C)EB=Lu>!DP}u$_H2w!(
z?~7FbgZW7HKl=I~X0-M{rQ?63=7041A3gu0xBt=C|FELve^C2`@i=1rKcV@52DJRo
zf;Rt8YW<Hs|IdWh{!b&&{vWOXDa-%#?*F6D|1%M&|5?%UKc(~k;Ptbh{0$xdLvR0s
z`5<{{`#+7u_CI?4&w{r8kI?=<LgRm6_aoK+l<xln_y3XdKl=PXq5Xf9=6`Vg4yw<g
z{eMFBKUf~59$Np8=6|yDKj;7`n&1Bu=%8TBV9OxFzzseWN`S$E0q^}k%nk~640a46
z3<3<GLvaKd7*s$vXNoWgf)6Yb%mLl^WzHbNAjAMVs0t)+#(?MkF9s6t|4MUE&}GnL
z5Mhu2ADkq};Gh87#Vf)f$pAW73dGj~%S$nU4!T0{rNIYALHPO%A`CJNOnK1zzd-l@
z6mT;zF<`m>C!dpnDUg+c$&iJCDHrMfpFBYZCI(>!rvD-gOa-D0Obny<|B#)~M>S#%
z0dW2gWKf{${a<Mg3RJ!SD+ewAGoa;vW)Po>`JdYNe}V4*)8k=aS^~}gO#BQ?IY{?^
zF>o?4F+uPDVu0rVYs?HxR)P#nxxx%gdLj%=|3w*?{*UH=tciG3kZb_X{|spPKafE|
zo529QV}36i=z@3$h9PzT9|M8=|CrJ4|6?F<|6dvf^*`wTKT!S$)&HRT|6uh$BU1hk
zhTi}8pM`-5mj6Nb|1m)8e+Cf-CI(RkCacl>Pj*5d)rd6&u;zcz`dd=+f0}~=-upk9
zNo@Z!ptb)A)&Jo302S;1Kq|KXk@G+3{$E)BXF|&V)1mpForQsEHai1TJ`)2|ATt9K
za{gx$Wnf|)&Hq>v@u(o#App+*%xLvLsrjD)E&m5nx&2S?{y(Md|1<{$JqBq1A36V<
zax*af$I}02gyw$+76vBJ{lET93`|wb3{2)o^?$G^1Jl0I{7-g5AJvF81O{aN525)#
z1_lLPM$k!JY~X|TLFaX$od1D7|Bt@^2mSmnLi2y%@qVQFKQJF@{2x63r;YpkFZA`l
zgvS5T=l|jRfpE<KgU9<p?!mGC2mSmn^!-0fX!HMA*8c?|pZ|xx{|9~jKcVx#(AWPF
zI{y!S{2#o&7tj1Zcz*!W`2XnsAFO$s7(sCUAL#Wz===X!2;_f4`+rDX{}0~pLqYyW
zKmQMX{U2z44d42IczJ*$|AXiI@#KF}=l{{q|H@=gK*|5;^MC01AASBmjlldrdj3a0
z{|kNp4|skLDgUFN|A~J7*XaBoF<Bj}8gTxn_xd07{XgjI|5zCm^cVvX=YOJ~|Ak)v
z6WafSzWxuqe+HDFh@AfipZ}?YsQ($!*8iaAfAspF((^w_&Hw28f6({;W2ygx8BZbB
z|Dfl8Lg#;>@Bbrp{SSKmkDmX*@<{9d!174-|7iZlnzxA&1m}Nxum2&U{g0CW(a--t
z&;RJ{fAsUeNNxXPUH^xa|IzpV5^DdW*Z<)4J)reF(DlFI{r(_6wEhRL2SnQc123;|
zwExl1|01;hk5K+c-~U7E`Co+2|0J~k2b{l=>VNS5AUyehbpH=ASskkyaQ>%u{ZH!t
zAN2a40j>T=&;Nw>|Dd1$MJWG+&-=pD{s-^>$CLku!TFzf>won2Kl=G!q@MqYe*PD@
zeh1a(M6UlEJ^u@9UM5EnblIa2c)VX5tQ}k)s4ys?-2bi0pr8xBIuLr^H~RhGj)d?3
zp31P6fq{XMfq@gWo&dDocLxLLe1Fg-kph7X3Ox*yz~}peF3J>OU{KI!XaV22xgNCs
zAd^9%jiHl)fq{zwbWt7%gD%DdUCIf%OcQi*Cg{S;MGOoKpbP&%G}tqv#ApbNh5+6W
z0O$9C9{)qH|Ct#S^cjN?{eSfOAHDsLzW)z>{15&7U-0=^Nd15G^Z&4p|LY?9|LEuc
zp|}4Do&O6T?}N7g;r#(<`yV_XfYkmcwf~R4{||lt50>-)LKsiu?*F6L|LEg?)b9Ti
z8vh6P4?yh&==%TB{eO7#I6g^m{-<{PpVa+-=;Qwk3<?H}!HE1%>G^-?`5%6s7LM^h
zaDM<)K0x>Xfam}85c!|d{y#W>gZlf>{0}b=p!pxnN6P>3@(M@)pVaYx^!`61gF-0d
z8ASd^-~UJG{6F;bKM0-wi{Af7-~R{B-$?y`aQ^^L|9^D+4__9?D+kX1^dA31-~WeR
z|D)%B^!lIB{y$33|06a3)B5~hczFfQ|KRcfRDMAB{}Vd@kBISql>CoA{*PY&6FUEo
z(D*<4`G4U24XV$H?Eizy2atMb{Xd%j@#b-SlHmML?fRe4_#YAD|Aveqi25Hr|D(76
z(Z~PM+yCh2|H9kT(E6XK^Z)b_^*^EW|Ip|E(8vG5^*bp4;;8?@^8rZpKis`I@;`e0
zkG}o~z5Sntw*Q}jK_QIsETaA=wEl<G_CNahAB4{T1F!Evs{hf)|H1tOr2Id+{s&(c
z$14ZU{{!9sM?e3QkwL+XF%psg(a-;*bo~$fJS}Mc2lw}p#{a?Vfsoq&;PHPGME*xV
z|Bux3Kfv>Qc=A8Ee87|c!Q}x+KeYZw&;O*(|79{LL^EDO<bOi-KcW0j==@*w_CNai
zAN2eWZXb-c|M6yIG9|(JpW5|5q5ePm`XBWC&w!Ty3Dy6E*8dQi|3lCJU_Mg*2lxMx
z@;{;eKcVw~(a--wAO8dMk@7#hyn@#M;Pn7V`5*oKKlJrKM4bPLH~$ax`G2GNpUm7%
zSQ|M1)4TsqMEf75{wI|G(cAy%=l`Lf{|l}^LHQd;{ZDEBr?mY~?fM@*|6@7-4<-Mj
zum3^s|D&J(hd%y?zWyKm{D1WG|G@2gP<tNQ{|BG%ht&Q@KmQXf4^j{9|BtT!A)L{1
zr~v1GYS;gS`u~K^|4l=y|IyF?Beebpz5h?B{s*u3Lu&tHJ^vS}{zpIm4}Ja*ef>Y^
ze7(W6{vZAPKV~Yo{|Sx%p|}6R^*bm(L-Rj)d=F3l2g`%hL-YUW_#ckkO;{M5{|CDN
zk7fKHrT#}h{||lqkI?)-`uczPemWxSfAIOgNco>o`=3z#kAD6id^`Zh{2#o%0&V}J
zpZ|+~{vZ1MKl=H<=<|OJ1oA(j^Zy9V|D%upk(&R(<pZAn|LFWb;f#($1vvjxyZ$HC
z|0kmTZ^xL382=-+{ZHxsUvPT>)IUI;|F=Pm|Dor9Qpf+m?R!xF9XkF`DF4IDD`@@)
zmj@vI(D6U?{lBD+|1mNsBs1PZjQ^p}|D(76(f9vSdj2Q+{6C@df5GE}qxC<IEKQOy
zIRDeT|BpWZkAD6y3xk3^V-oKCPiX$1)b>AkydSCkkKX?WpZ{x%JO87%|IzDz^z(nw
z^FN#qt^d)-|G@bjR31U|Ke#+V%KxN}|D*5!WnfT9VZ4pV|D=xplbZk0_y2<HcTj%D
z(f$X^Bh~+-`+rHw<M<SV^FOuge?t9#LiIl@gMtHNG9v#I+W(6_{zoYPgU8Q7`H9H(
zKY08fw8Ma(ft{Oyff0TGFQxe(z8(;o|H0(}()d4m{s;5%<bU+}e<IHRNM*c($p7f`
z|D^8!MIZk|-~Ugj{SThsN9zBh=YRD6|LFWbzATPc4xIl7y8n-5{jU>aDkA@*xBm&v
z|5LjE7rp)m=YI#>^*{RlfAsM`^z}dB`W=*iq3wTgeh2Y!<bQa11+D+l^FO8ge=`{r
z(i!g|@;`e0PiX%yspo&7=YRD1e{lXr%Kzx+e}Lsd?S;|tKfIZn2uX1Mr*{2MsQ-^X
z|Bq$-&y_I)cm78o|3jbuN8kU8KK=*JKS=dIc)c&4_CNUi4`<@@KYIIr2%P_s#rP0+
z{zvcsqwoJEH2#M^|2Mk-mjSd#6@)>pN*FE6$iR@r#lQfg3s{NBz!WM0=YM+l{|UAK
znHdy37_*7b|D?A6!RzOd@<00iKdj?_ZixI(X#XF2{ztF>;q^VV{s*u3MXLY7<AD^k
z{|Sx%VcGwe%lHJ5{|U|i6I%Z_dj1E)R3-)nQ2qt&RR>{9CI$v4CI)c62g!l*JO~ep
z{7>!rpHTlFef}Ry{qM|}hRFZu`~N7N|A+6VA+rAuUjOTe$p7f$|D>M(0q^fa^FO>i
zz|sDPmsimCKc(Y;=<|Qf3<?>H_YwIYz5P#U{~xL6f1tPj!Tozsd!ESgztQ$Tg|$9H
zJGlNI=>9*J{O`z^g2?~q{eSfKKl=PX`u;!k{lDn#e{g>vPx~L-|F_4T|Ix?)sJ;Im
zUS2`-KiK`C_5yVN4}Je1`usoo{vY)G&%mIN#&{QZ{zq^B(|Z3OspEg6^Z$qpO(F}N
z|EXR76YBq?xBsz>|B;mc3AO(T<$v`3f8g-|Q2zjV{vRp-(|Z3OxII9__CNamKSs3t
zPiX!hz5S2A{+H1HfAsx-==1;J`W<Qf58OULn*Rfr51{tK==dLr*&RbUIRDeT|BpWZ
zk6!;XGAN+rfAsx-l+ORd_tW5L{}amp===Xj-Tx2n--GIJBHRDq`W{psLF<2Te*mN(
zTK^N8|0iPqKS}jJdj2PM{BN}V4;}{?vHgGa`X4?2GcYK4G3FBA{wGxb6WaezRQun9
z`1U`c@jvwaf8hEal%JvffADx9QvDAvuW;ml^!<P6^Z!J&|MMB2A=>}w^Z%6Y|08w%
zFL-?)QvDC!AB0r@gWCs4_5bMnKSsSytN^(FAL#x+mi@nY^FN{afAsx-g!ccS=YQ~e
zKu~=PZU2ME|M290O4t9Q=YKFCDgUF_|6o3-ydbjvN6-K0`~NZ-6j1U%`uHDu{~vw-
zAA0>yX#YR@{y+5jfAsv1-u_45|2Mk-huG|np$?q?>D~WFpZ`bC|7mFTKl=VZ^zlFR
z`F}#||G@bNl)s_vfAD-Cq47VY{7-2AAEEvK;QS5BztHwSd_54f{s;5%<bUvbAdr3>
z`Jd4KfAsx-3?%0N(e^*Xbw&mT(26P0{2e+5&F_KmkeUCZcmJQ%_CKNhe}vlq===Y{
z^Jhr;AHDtu^Fi{^`X4<0kCgw>=l{^h{|UAK(f9ws%L8cs2lMgde{lJQl>gE9|Dn(S
zqwoL6GX9TJ|D(_U6WafWKK_Tk{uh1y4|@L}+`b33=b`g|;QAe@{g1x?AHDrQy8oYS
zK$H5P)cOB3(0u?~7#J9s7^Fb!>k0M$3C;ggy8jRB{(lnkKl=J#O85W6%PVOAA3gt5
zy8n-v#QGn7{~vn$pVs^T!TkeJc`-WvPj<$KY6R#1f$smKkN>ftwf{+-|3`2C6I%ZZ
z?(gGi|AY7claT)j)&Jo79aMiq+yC(S03z#u^!@+n<NxUM|LFVwvF!gtss9P}|4D8C
zqmTbld;j0){691|lTKm1|Hl#S{vXhN+{pL;s4^&MF=&A;Yhqwv0No#?!Jq-=p9S$%
z7!))aG{OA6p!<6m7!;;5tU%oVlgXg4nqf2X_x~`A-v0v*%u!-A1gIPW;QF85<9~$u
z|Ey^BKfU+=g2w~#^#9TK|57^sPip;--u_3g|Iz#Z=;QzB{eMQZ_CNaiA42<oN!|aC
z-v38m|3m2f5A^>3==eX`r2;tr(|i06ef<ym`5%P(|Af~6P<#I``1}tF+W+Y1e}KpL
zk=p<8{s6T750*z7{{xTrgUTal{~tUa0MZW~|EF~SFQM^&Li>Ly&Hv!}Jy3rhI{pXF
z-$>(sV0k?A|D*Yzviwi&`k&DFAEEl6Q2s}s|3e@DN8kTTX#O9(-VaazpVIMv^!yLc
z@6i4~d_NF0|AXa`@;|t~N6P<TK2rWium924{}6Hh2TK1Ref<ym{6C@nzv$!t=;wbB
z+W!k)--{>zqu>8Ky8ef<{6Em+f9UJ~nbF$+=;MEc*8iZ7|Dor9@cLO$euB>bqwoJE
zH2;Ub|CiMBKfw7Llz*Z5AI_&z{wLJ_N8kTT>iQq_@xRgYKNyhL0D$KHL3qf_|5LmE
zC$#?uef<ym_&<96kG}sGz5XY({s(>hAHJUsn*YK19Z&raKK}zx`yW03qmTcipZ@``
z?{VaR@OS`H{SPm%pzVJ`^*{RhA0pQOqtyTC<Nt*A|I&K?Z?yeScKuFB<AC)4iD>@^
zGnSFR{vUn+FM9nC&Ob=?KYIShI{p_(z4ia_`W~A9!R!4&?Ez^0kDmYG<rR+nkG}tx
zQ2mcS{>Q+eP{H^fvHl-@{SSKkpV0naLg#;=-~Wle{s+DP50=N%{~uldLnxc$ln3X3
zYS;gS`u{|n|A9CE6I%a6sQr(g|IzpVg3AL?`2b!22VVb=l>gE9|B`zC2YUX8^P%}4
z%txyK;qHazfAsM`^!`7g{Exo>ml-Ypqu2lF`5(RgPwM#}==*=c^*agUf8g-}kowW}
zKR7cskrEc{3=I4X3<^dJE+CrWJsSf9KQn`ZHiH3!2m=EHWd7cP!HL0%L4<*kfq|2O
zK_Jb6!I{CCL4<*gAppc@a8Phya9|K&U}rFd^6eSy8AKR37|wDqFbFU>DA+RCGKes6
zG9*Ie85|iL8AKSk7$$<(2RJZTGgvc-Fz_(khpM+@uwxKm;A2?G!N4Gx!=Pf$V8I~5
zz|SxZ#AjeoF=H@i5MdBt=!Wyn7(^HZ8SK~@7z7y@R7@C58AKR_7`&l;QwET{FvC`;
zdJ6_C1`!4khV@YUZ5V7AL>NRF>cR333c3t>3?d9-3_2kFfes4#;P4P<_`wD;-$6kS
zEHA+z1d?Zf@g*7L;e34t5e6v+rd(bICI&tRCI%h`CI)T>CI&7BCI)^6CI$`$CI$fp
zCI&VJCI(IhCI(gprZg4?CI)r}CNN}XU}6wtU}6wvU}6wqU}6wuU}6wr0G%ZT!u*^J
z43eA-42ql#44Rw_3{Fstyr*;?8v|JV4-Uw=Q>^R^3?K|r6UGh^1F=D3=$OdlGpcNe
zhXA<#AL#Kv^!`61g91wZkG}sOz5kDX{ttTnkAD6Kd_OIb{eSTIKT`dVzW*P6{Xe1e
zf57c~P<tQR{s+(Zf%wq+A3Q#Qr~U`G2SDnf^MB~|Kl=JVLi7LV?SE41e`@#t!Sy?y
z@qcjt0IB{TUH?aRDFn{{)NcP18vjG@|D%upGoa;v^znc6{Et5WM=1Y;^AD(fk0bws
z=L13V(Dpxi{-<>R525}4=<R=ac?E6%gWZpm|IzpV6KemX_x~Bu+W+Y5e+cdWN8kTL
z==>i->wm!cn}qy7I{!~u{vYV|Kj`&81A{^cV>#~eKSJw&DBb^$HU9_U9{(ft{2y@s
z2IXI9{SW6u>whpGPyG*`4*==MQU9aofAsNx^!@(~3<{Nu9}wezgzA4n`~L~;|3TmX
zPip@kygv}B{vXZ%l;wYF*Z+jZ|Iq7y^!%U3pb*Mffyn=a_Wu*A{|TM{10L_kGyey!
z|AP_vpV0n)^!YzR=YNCqJ19Rx^FMe#fP(ywzWxWj{f}k;e--0LME)nV{s(>hk5Ky`
zeg6-7{g0mi!TbA=>VHDx|D)@FD9ir?-Ty~F|AT=+A)K)ak^j;6|5LjD2RwcbYTx5%
z|AY4fg5;s?fAIK!C?fx(xBp39|4;Az|LFN2z5Sobpism38Ik|d>wiM~|Izb5q4R&x
z^FOKQ|A6}kqxC=8nI1{wfb{>-*Z&a8|AhMg=<9zd-T#k1{|B!B@#KH>@jq&x{{t_t
zp#6XFegIH=0owjY-~W%k{)dS3Kk(*%^!Yz}@Bat450K{n!R>?5{Ew84$!3D{KfU|^
zgxdcsX!Sp#{7<O;kAD6Sc>D}hzeDSPaD7jx{ZB&vr?mYK?hoK;|AXC+l>gDk|Iz#Z
z==mSZ{(qGGPiXxQdix)J{11KoKl=GU===Y{?R!vuhVK6X_wSL~|LEucpx^&Hy8ef<
z{7>)xKl=I~^z(mM85E)!>k#dK^!>k-uKxkopGf&1T;C(*f2`;KL?YV%==*=s>wjvW
z{{znNAooJ+e=whf{7<O;&&;6E!1x_^`=8MMU-b4rq47WT_CL6ON6P=;_C22b50(e1
zA6@@LcE*Ql1lRuq-Ty})|6^cKh-Yj<<bOi-Kl=PX3xk3JgAxM+0~doW7Xt$e`ucxx
z{sHADX#J0#|G|8aJhcB0KK~~ck^j;A|LFOjQ2h^|?}v{6!`A~q$N$jle|UKX&Hw1<
z|Df;xMW6piKmP~4|Ifgn(8Bl|cm5}||CdnyCw2S}oWGIsKe&8AYX5`fk@ElO{691|
zlTLy2Keg+BQs@6E&Hw1_e@gfNg69K}@;|u$k0<|=I{pXF-=O-N$ovm4ub}xK%m?X*
z_WudB{|VLqjA;2Eef}T4|Bt@^m(>0L==*<3J^urJ|L^GhAL$t%sso(=>D~V)bp8i3
zf%>1&{6G5oAN2h{;Q4b<{)X27g!cb}&;LNm|LFUF3Dy6E_W#4n18DsZZXe+3|AWT^
zDailm`+o`5|LFN2z5h>Y{wKBlPpJMM&HvEcOgaV5|J1JkDV_gkU{FY8Y(cdD3GM$y
zum1_<fB1enX#NMc_mTSlU_PjPfVTg^^?yA1?SJ(A4_@C3%D>S1AI^v7e{gw#l>g!7
z6_NEn`usl;=YO;@{zbI^(dYk3-T#X|{)c}42ci5=>iXZ&`G3+gK2!%d{||KkAIth*
zl>Cq0|0gv6PwD<&Qu9Ch{(toGKT_BKpyz*hd4(hYQ@Z~*lR*I`|D(_Uqu2lF`+rG2
z{{wyhFZ%pHxPOn-|7T)QkY>Qs{~xXYp}CoK3Y`C`UH=p6|D(_UW9k1#GS(pKfAsv1
zzWyJ5{vW;mCp7*?X#X$x{Eu)%{g1x?7d`)@kN=^c{{hb5NcBIQ53T>f<AF%^Ke)dS
zYLDQ^|LFaH^!b1E^}p!*e;F7Q>KMNw>VHD{AHDrgX#5X-{%>^u@8G)slivM*Li7KO
z3<@aupV0n4QrrLV{WLh*|5(TWkn%sF{eS5BAHDtu=WnF^4_@yJ;!`RAqtE{n8vjGj
z|D?|UqvwA@=YOEL|Iz3F(d&P(Jf8Z0bpD_8iXW<jCiOp|{y+NsKdJRUrSt#r`V>e0
zM{oaw*Z(5rfAsl3QqTXObpIdv_#dVF|CkBX|AhAck$V0Idj1EG?}6s?pzD9o^FLS~
zPyQcm|3h;#=@dBs4|M;Z)clX${zsqxN8kU4zW<-p{0|=g!;}Bf$NvfK|A)8tq2qtx
z@qVQGA3PpNLHi$l{vW;m$Fl#Ar1n3p_x}+Z{{ycN1eF)i^*^KY|D<Pps19)cr+5D!
zz5S0q{+EW<{-<>RAEEpYZto+F|6|?%i<JLqz5fqfK2VVV3AO*x_x~}X)&GR%|Iz#Z
z=<9z+_y02tsq=s7-Tz0Q|0h)cqwoKtbp9XQeg=)F;b{L8%Kzx?e^U4VQ@Z~TJRb;Z
zFF@D-5W4>tef$s0`ait&KdJlwsJ;GowEYjQt*KAZr2Z$=|3|O?3FUu6<NxU6f9U)F
z2<`s|_xF+Ne=r|ZJ|NHkBh~-t`5(RgPiXuPT)%_zFSPv+=R?Q;z~g~P^*_A4f{y>A
z=YRD5f9Ui7=<R<(`5%4$AASCh)ct>?uKxw^??amZLm&SG%Okb_N9X^^E*QZ1f1vyS
z==*<J(Axj#`Jd4IKl=P1`uacg{y+NuKQJFD{}USjqjdc*dj1FVk@7#>z0mv*=7Y))
zX#I~q|3|3(kG}se6RrJE>HHs|{r~9u|Ip|E!TB30|D)Ic===Xh$N$I%;QUYT{y+Ns
zKYIRWMa%!_`~T3#{|L?hqvwD4ei|I@e?s*?q5Xf<-v1BI@1XJsn*YJ>$CLlj=l{|7
z{}QVI(ewX6@Bc&3|KRxnr22m}|5KL#>D~XQb^9NE{~w|K|KR*i$M!#bydOvVAHDtu
z=Xa$14=xXo@<00iKlJ*a)clV=|4(TDANu$o`ubn=^*`wIf8h2#C_h8z|G?w>NcBJZ
z{(toRKRW+US^lSX{ZFX>k3Rp8zW<*At^P-E{}Y=3r*!`x*8Tq^^#9S<|1vTt1TbVV
zFfhn4fOZkEfb%yf{}P%1!TB9e{wKBlk6!;1n*T@d|D*5!Ltp<xX#5X-{~x%1N6P=;
z{Ea97kM92?JHMlA1h@YOy8n+p{>Mxp|D(76(dYls`~T?cf5GEtp!@`F{}bB(2j2gW
zl>bTH|A)T*4?X|G*8@Vw|G@Hi`v2(r|Izb5`usoo{(mg{|L~6gqvwD0`9DJWpVaX`
z^!yJlAMmXI8J+(}&(=iq!TF!s^*^EY|D?A6>An9CydD5lJ`g$nPwMy|czq92{ZA<W
z!^<mZ{~z2Q0O==l{13hUCp7<0X#XFj`+rH@{|_!7K<x$S`k&GMKhgOeT_HIC)4TtV
zKL5|eps;~q3j+fK6N3~t1L&49)b;=9?SDe^|J2_92j2gWRR5DY|A)T+7hJ!C@-L3|
zKX`lqss2ab{|BBA1nGz7e@gfNp|Af(AOAzI|IzpVk(&R}_y2+GcTj$Y_W!~88>#&d
zmd8{7kLG{$Y)v#Doc|dZ!1vjKG)-k-U=U(pP|#t}0dX0gK>4~1x?uhdC|{dF8_e&4
z^0gSW!2BjCUxPsd%s&g|Ycgnp`C?3v{Jo4}9RrA^59RM;kYxnre+4LiBg0k(1_ovZ
z4JdyH!)^u!1{Ma;sbGwZ3<}l^84L^ztPC?4L8dS$WHXd7fG#I|3gu5`Sir!*z{7A5
z$}eY_zyP|r4|J+HsQ(SR{}1HT07j6h3<{<UrVI=W!VKn6z6pZ~0|SEygDad5k{4z8
z335dygMtBr0Rsbr7y~~@K9@nkkin3Ffk7PJzc*trV_;yAV2A?AGcYJX_>v5%aK1SM
z1A`QU50nqFUz!1Q$|%Tvp!*6z;{^%q5dSS^Sj@n{Ajbga8!;#>0`DMGV3-REMbLaG
zV<960gEE5=)I4Lb`&AgSL3}0#1#<?FeX0xvAU*?(uf|Xc=UXr^FsL(dLiq+@|7b9%
zK>3CY#taM$n&A5cLH7@$<Hd{&3|ko)7<My4?i{?%$iQ$9%09`+z;J<)fdM84x^vKu
zk%0k*|1&UvV;{yxra|_wGeOM!2{q4>iGjh1337iSvRarq;Dk0x5ETLglK+_)6e!C7
z3<UDO5rYCv^FISx{%0UD|7U{A15kb>GygN9<$ut42y*^sWKclK|GBXIKAQiD$`m6=
z(SYRtTpH(pMgsXilR<%``rn8_0d$`*0|T`FXQD9wgWCfn<bOs61(f=qfk6IeK+FH|
z`hGP3kD#nglvf{dGB5}ggYNr=wC7>v0j~BxxV`_MK>?+`AIPA9(%u(hP=K}fA@_$f
zC`@Ho0cxp&n&=Dy3=9gZ88$O8Ft9=I17}d^VVK0gz`zc@51c_kpP>cZo`>Ae&7jc6
z&<Q@z7t|gEVf6d2LG3_LyApKgHHaq4^P`GJLtuo5fCW1P1Aiuif)RrY184=zdo~6T
zt)LCQ@1B7Hl7Af-oEV%KL_i~RoD2*C3=Ry=49*N93~USm5Wa!~g9C#I13QBulyA>q
z&mh9U!Ely?fkA-TLBW>6mO+Gp6Pn*07#tZK8AKSkAo-oqfx()=nn8qthv7a*J%fXS
z9fKW%2m>F(LJkH7K^6uTa|R0r5e9ySX&`<MgNhl0IfDp;07Ey3&j8|^F^Dh-GT5<$
zdie}0p!!;bL5RT{#1CXp0rjUv7=#(Ng48oJsDSE!5e5+kaQVXMz+l5*!yv*S%1{rI
zXK+x^Wzb^~VGv``0qJLOP|yd5hd9FzHU<VkeFyM(i3o!PgAhnQ4aS#bkO%PtL417%
z5e6v+CI(&xCI&tRCI%h`CI)T>CI&7BCPsb+CI$`$CI$fpCI&VJCMHe>CI(gpCI%J;
zCPsD!CNN}XU}6wtU}6wvU}6wqU}6wuU}6x0_rKB0KPOHG1`r07eaK}YsI2_K0qHBV
zvNJG%Fi1@pJ46h`28p5L5uPnZjQ3&ny&i)e*v~^^{Etxop8>7?&&Z&Fcl<At!1x~{
zTKhkjK>Oba)W63w{>KE8C!zh%FxvhHm1Cphf8Z=iRbt@s|9WtL05<-=pFs{~{C^X}
zHk9%IoeX<GBkz#$e^T>516uxPBC-F^fR_IWjsG!%@;9FRp9_*l%Kwb8@&`Kp4=#^D
z`eh*F{Y2z{1;!%W<NxUWe<Rp<;OO{2RWs8NG;C1je<KD3y!jt}{x6fn`M+GW{Lci-
ze?-pz5z7DI@jX!frP2H!mhnH5@;~Ef{vU!_l_pLel=+{LK>nw+{%1hT|G8-SKND2n
z<C*_Q&;Ldw&i{eS2c-I+0cJn6{s)&wpz?#v`X7D%554|}^GEA{nq;aWWayyG{|qGN
ze<l*^fAsth&wpgr|BM9kKX|?$l%I)Q{{t?MK<c6SpNRQCy!Ai4y+1ntH-xe#U7R`~
z`QHdM|4+sKe=dRiPiXuPJ^wS2SpSo{{)bTg4|Wey{-?D64{z_|$p4w3{=n$^Ke}YN
zL1xK-<bOsI^M59T0#(QV2-W|&1oFQTf$@KE{s!e=X#XEP-VfsAsQ=N&|EQh+;q84K
z`5!Dln*Rq`)})Jb1|<J8keL4&(DFa}_#Xp-`X7D#pHTh>kN4y0|1*-9|H0$^NckT;
zKZvLQPw)H>-XDM`|7U{wH>2zS>5?JoY{`(w|4eB4pVIL^Bed~9aDD^r?;*4QPip%g
zJU>Xq{GZ97fYSdbb^H&!KLAhu2m5a{|I;~Z(#5(Vk^gh4oc|fo^1l&m{GCquAKX76
zA^)R~|7BvX|3}IH)L#G3G+O`DB{L3yB|{?rqqqMF)&H3!uK$DgzXwVF2bV{n{sMIT
zpV0Up6I%UG?fehk-#l9X4?y;$xs?N#|0&r2kDmXHXx#q?uLl7251{-1(C7cb?PCh|
z|HI24==?vJk0<{#q1FGn3<~nd`+upO|H1wn&Hpsdj00c+EdR4Huz_udt^a3bU<LER
z=YOO#D6lZFfcfC_KhhW!m>HPCeDHq2Kn4ZSo)wS)`1}t-=YN9F|AORy)bl<N=l?`8
z))IgJH~Re_=;!~TpZ^U$KMQoe7xer;Lic|&FevO`h`@dSH=+AK2%Y}}KM#z^^Z&r^
zM>_up{ro@l`#+c%6gU~U7#J8-7_M?LFfd}d|GS>?8{+<NLic|VI{y#-{9hIZ1<>9q
z1_nKb8g2##7DD%b6T1HoEDt&_2zvh4==~p{tVb3G=l=mY{}U<yGcqVZ&ijGpe?|rc
zl>Co=|2OEo8wLdi1_lm>om`Ofd*m48!TW_TLHP;{O5pv%wotw>g9rly12+TsydOgM
ze}m5h2bB+q^Z!utKl=UOEDQ=Y3^T#!1$_kNFZA<&(a-;cpZAC3{4enNU`XeGf%7}a
zJv2K1FOxw5CI1sT{|i0;r!gpqF^DrTFz7Ipf$}%{`M>D-AN~Aq^!q>1&;Md#P>^OA
zJ^zcW3{F53IRDf8{7>-xA4vJ10WJSCpyhw`^Z!8S-5}?GLic~5pZ^QbPtf`woZmsa
zpLyZueer`%DPVx+e<rm0AN~A4^!$&0|5qB?`QL=@{|1*2NckULUg609==Xo4-~U0x
z{eO7#KcV}-37!8-==^{1`F^1KeDwUkEH21dXdt=((gY`vgDH~+=YM*i|4HliKl=UO
zgxde;`5(*qzbN%Tdj2QW{ztF>!Sy?+{SK}F!T0@v_|W!0dj5x(S2*%Ndix*!{txu~
z|FGQujgtS-@BctQ|C7-D-z*FY;tUcD3=Fyq?x6Np8e03GnL$B<0d&5nK0`A|9{v6g
z^!gtxk5vDI?*{>u7tr?q==~pL7Xsk?Pwo1jQ2!r%{|BD>KMk$^N5B7@(ET5z_W!~8
z9Z&twh*tlj-~XM4*8XQ<P{?Jd0-p!^0@NQMl>g!70W|-E`AGFYdj3a0|CiMKkAD9*
zGllJcCbafHdj21+{~3_aECt;S4mx)Qgkfj3fN0POxS)C;M$@hSAL{4-GNO(DGoj7@
zk-Gj5eBK|P^?!uM|Ka<6pzD9Z^ZlUld>re4;p>l}<NshjNIj1Ezg)EOe^7sDbo`%T
z^!#7an*reZf1t<z2=)J285Cq0<iO_xo(HuTLFpa2|4-=t9~K4$l<_}s{RtXRBeMUG
zKK@Ur{f}P%GokhWnHdxW89?oQX!{?0-am*Bt^dLE0eI?vaC-ox9(w*i3xfhT0}lfO
zgA#)UD16ZG|3Pp6qu>9*K%o9lV^H8?;AUW8&|>fbnU6mHNA3PUczhq!KQLsN0JRVA
z_}}RLKcr`Ts19)cr*`|FsQZ7A+W+X||D=xpq0j%NF({yn|D)%BaQ?xQ|5+FmP{#jA
z&Hw1*f0VZW;pG*M{y!^P{wLJ`N6-I^X!)O+L4gl+3M7LjgEBP#q2zyN1_e<DF$M+(
zZH8>nct866pJ{0Qe<rm4Kl=DT`u#uX{eSTIAX5Jyd_Oo+|9|xU4`^;CodV~7dXN8s
z@Bcx{|LFBU3tImlef*!${XeAk|I<ME9jX6MYW`<J>;I>r_5Z1T|0no9Fr@mQQ2!r&
z{GXXYL7Bmqfq_94a(@V+`X7D#kJ9>|5pDbroWDW&naJ^fRt5zr29SE__}^&$CmVqC
zKeg+BLgRmg#{XH-@;@_y_CI?4kDmY2(Axj-`?Sey|1&Zu%m&}TBf#(*I=+W8|4(WC
z51tRe)BY!v|Iyd~klOx7U;o2GVf&xd`#-_;J5u`}ef%HXK0wO<qw9Yt%l`x2|7Rg_
z{-4nL9~QLsKdJM7;PwEhe*m5TM<4%3@Bfo}|0le^5AFYh$NNF`Ikf)|<|E~QczK1R
z{m)Ec`=8MIA663cKNDK}pV0U}`uZRA{10v)AhrL|^Z#i5Pg(w_cKuJN|Bt@@ht&L!
zKK_Tk{)d&s{10yLBenm*>j9ARKdJqHCbafHq5eO-Jb>nZFdr%Z!^bP2`5#;!fXWN#
z_#b-vAAS7~3)=c$^!`7o?SDqJ{y(YXe`yr9|CvYI|72%)G>zc)KfU|^gxdeiXzhRW
z{y%#DC)ECDLTmqn+s~l<4Q>CkqV@j?<^MDqxBt=WfAsth=Hto#=;MFr`Ja(M|DVwM
zAN2k|`uHFE`hP<8Ke&AlYR^Oa|KRmKNbP?X0_%TA*Z-j9YT~)z{7>!rpHTlFef>`w
zf%ZQmTK}KY^*`|Yw4wPQoZpe^e<o0Q04g7#?SB@u^*`wCfAsZ#=<EN{$N#|dd!YPF
zWcwdpUP0@BQu9Bd{y(AhKg=Yy|Iyd~6UzVK_B~Sm2e<D@$p545f8sMdno4l~AL#x+
z`uIPo^MB~`|IBFZe@fT?lbZiY9sdKb_XU*)(Dpxi{SPm%p!uJPK|uh#egNA3XGH7&
zqtE}RQMvt}Mq>LPef*Dw!uCJ7d;paf(DDD#`G2%rO*|Kz|EXR76YBr7FeofxSPQ=Y
z2e$ur1H%>u1_mYuDQ?Jp_mPY>i2c853<@&f{a@@1u=PKX{eFo3e~|S-oD8u2fAS29
zxcC2o>rYVq4z2&u_y2;|1B2wD^*;lH!ghvm#QtAK28CG+3mHH+A;QN0s~Kh>_Wv<3
zDC96yBG&(=F(~*mWHK-?$S}k+LiQ`7tp6dD|KaY1=6^6BR9-;yKYITkz5S1+{#Rn~
zL7D%nWBiKP|4V58AHDt0f>{3xUhfaD?{y*jeZlPkNe0mVU)XwoDd_tD7|{9xRt5!0
z29Ue~WW7%&sDCfRz`$V0PzsV~0?C8g14az;AU?dlH-_Jb2)Z9knVW&ZiJO5Tnwx=P
z0T%@C;bLF_Vc1$*&^lWX2C0YP#f%ILTNxP`b~7@7&AZOXz;F-BKFP?yaDkD50VW30
zi;h9-c|jPoUKeI2uJyh!cfi*8!f23Q;&UzaRD$zAz5D-+X!)O&K>;QIGchQj<bMVd
z^FMff0G|90-%kh4|LE<1Fdr%ZXQJhQ1_Jq?1ug$Gpyhw?_#P<#650L-=Xa2Mp!pxX
z9tfl#n*Y)F|B;pd-y!lpsr!G?^FMsQ503l~uD?O~S)T!%{~18}8!7*T<&p9~SRSMv
zn*UiC6gU_-85kHw^FO5}0XY9tyZ$HC|7SqU{|spPpMk>s4;~*x%KwDc|Do6a==mSL
z{zuRMX$%S|^*^Ef4{qOs@-H<1XTsJ4<7ofG%PVO92bTvR{m}eRsQzcgZ2zOw|11m&
zb&PoOKNAD$`d>Wb|3uaQ@bNt&^FJe~d_c<o@b>;_{-;X*r+5E9jX?fqM9crIX!Sn}
zg91tIfAsth&rdk&fAD-DsJ_L~{%0Ui|D(768PV#0^!yL!L-Rj)d=St4AF25tz5UO`
zpn#J9842WnLhJuBNo@av>vvFohUR}}Q2r*N{vU1sQ=0AJ`e{=C6YBq?*Z<5U*8hxX
z`JV|kKR{;xA6(xfjsH`c|1$}+|Ka%^TK~iO(EJbPBjta1c?GTi!Sew~^*{Rhe-;J>
z9tJ)J1_osYMQDE+<@_%OwEWKi%KvY1xBt=4|3L5mBhCMV>woxoAGG}s-VXrE-+GY!
z{^<E1+`b3NL;L?=c|7g^w9)oIJOfk60Ox;t_y5uJKdsyUnP~I>;QA9(zvHO?!Q}x+
z9!LG3hF1SGqP73g>wonAKRADb@-LD3AMRcp`5(RgkG}qg8Lj=#h?f7;(DFYMf&D*(
z@;{;RKk)i}JoP_#{U1{PX92YjK<c6W|IzxN!d#Eg4$lAd?*Fr*wg1uUe-^a%KQmhU
zKMk$^hp!KS*8fZl3M7sHgY!F5{hx_B|Bo{MPip%gJ^zE-_jvL@czh74{zuRMU_MAc
zk^O)4_CKlhKcV(Ndi_r*|AXsyP=1EC|IzDz@c!S?{Ex_`v}1wuKfU|^gzA6v{7>rm
zKl=C|q4odZ^*%`XA6y<F)&Gnnj{lQd|C2iZmx(t2kG}pt4Xyo;UjGxy|AhAc;F<pi
zxBt=eKX^SLsC`eR_CM=r`=44R0yzIuyZ$G&|4*p>k6!=7*Zbm_{|E06LK^=^&;Q`{
zGobuUX8WJo^Z(%b9#o&>=>LQ3dyspf?SC*Iq@K+Bp9QV`&x+RmN1y*AwEqu%{trF>
zqtE|?*YD%0|H1PENcDf_X#1a9`5oOHaQ>%v|DPGH{g0miGtt`r==DD<TKgY<J|MLH
zPip-SUhjja{!b&Z{wFm52hZ<B_W$AK6^{ImUjGxC|3}aNgvS2}wf~XU|AXs)TF?KF
z_W#kdG1+`@{-<{RPw)AELirzk{tvu<22`JtS^uN=|Iz3F8A%-fhmQwPss3k0YyXql
z|7SrP|I1{c?)*P`{SRK>2kIXXIsOmd?=w38Pj<$KY6RzhdiVd)>whK^=l=+`|5?z+
z|43c`PwD(0djFr&`G0tMg`@sQAO9y*|7W7L|C!O+|LFOjQ2mc|{|C7KC)EBYH2w#k
zA3$pVgU1I!{e{u-e`vO)8uf^ifk8->K|z~A8*C=HJYZl@&|%O4^TGFjsW2$$GU$T&
z;QPK97!<S^w7`7ueP0X=3K|R=VE$PK1_mKV1_ez9O)!5i8v}ztAcH~=!+h|1f6%f`
z0S3_dwW}By7}yvlg5(((6!aNd!1wvA2k|o*6xtX%!T0&V)>HFyGB8MTGB7A|GB9Xz
zGJsFtna2j9!4{1YqaiRF0wjlk1v>-iq(=oq1}6qy1_p-rY!JRSgFbkN894tkIDnxb
z10w@C{{}iRI5Idg2r{rS1aN|O!8j<`G1xH(GO#lkLix4~whV#{91LeUAoA7>)(nCS
zoD7K&c?Nq1dj>%UE=c~*abU1yuw)Qq;9<BARd2&!!yw4O$FPut0pt!9QwB2zK?Z&X
zJ9Y@)n8AcWkU@aK8_G9fFl7Mkso4ruZ^mH3AjlxZ04`4$92l$^tQZ6tgc)?e>KzpH
z!2T0q_`$}&Ajs?hF5d(hL>Yvj@}TlgkU@+=9>h-r$?Gu)GKe!UF>o_5G4U`kWpXhv
zG4L`lF>o+2G4L@kF|aW(F>o?4F|aZ)sjx6GsjxGE?nGo_U}j)q5MW?p5M*Ft5Mp3r
z;0Nz90hMd$WttNw0|N-d_K1LJP#FhO`-1~g)`7&r*b!`2b_NDyOmYGk)i9z%fUNwV
zMq&PEc0kSl3<UCj4g+oTKLaR#>oVZX|A8QRr2KEr!@$IVC;z9jFfgUEGcctwF)(E^
zGccJ8Fff@z^S|$C{vXj9ZjgB%k^k+%H^d^>|DYA5u=*cVpYy@$e+CBzP<_wGz=l%4
z^D(fa)aQH*oGA4<9|Jc^ea^?ggHoUKG4Mj_b7lq=P<_tFz{h}GpM%b%My}8K7z9x2
zb3O(^NPP~?&wLC*DD^oXgD^^c&c`4Et-m=Lm<rh$n3zC$nw5cxk(+^ufrWwTC#X&b
z)#9K!oR@(qA5_otGcYmm;H<+z^)m>M*4u+Dp^rKTYY2eze-49!A%h*LX^+zW2lWSF
z`5)9C=S9l@pz?qhE&ubv@;|gb=VjnT$?v=jTqyaSmw_9S-x(nJotJ?JlHZvbR6y-_
zUIt#2_B$^FA4-1bW#C82@4O5GDEXb2K@gJP!R3J-124G!4QiKjFfi$X@;0=+4z9~t
zklO2@`W@7^=VM^f<t8exgYrBGkG9RRCbLn&K^g+!{LcW%{~WOXe-3CoP#=7w408VG
zLCgO<@bNoH`<;h@10}!nFmR&ecOC{Vl>E-az>SjMc^G(5@;eU$FG_v~?P&q`*TMN&
zmw|_YA0@x@FbJUJcOGz`8<fx48JHMZ8JPZaFff&{Ffav!@;$6x2i5gF3`~rm{LY0p
zuY>AzP#y>2(R@Bg6ZELFND2W&{<mj<=YIyw{12+{k@G*O{g0ggLE~%i{12|b%^C3L
ze=`Pn{%2rNF=w!3K+gZ5@j{&WKL^wwCo%tn#^usLV|Ac<9-99vK<#>N2BuV4eLtH2
zNlHAUiidm%fb%~yTK$hD|AX59$oU^q9>C`BD6Ib(Ankp4{?CDo*W=9pq}2b6(E1;g
z|Cu-#m|h^|fAH8mwEhQ=<&Wn7A)lZ}JwQ?jfam}7LG?Y-{C_Ii{C_Um{C_He`F{qq
z`F{q`eEv+7`Tsc#OAzz_hM@WXI>h`x1A{^XL-XkTKS?n;s(3U6NDl#U{s-6hNckUq
z{SO0L{^vl;|KHHo{{*1re-;LXWQH<C{%2-TsAOnF<o_H{{*Ok<|FH}Sqxqlo=p5BC
z8UiGR06711pw<81(CYsHwERzK{U3V$pM#eF8PM`S3tIkXW>6T-|0G4@sN&HOAS(pG
z`CkVu|1+ZHe?|)PKLdgM&xn@)8AkIzS&=!aX*2{#3;}TdC$;_0h}QnsL2LgrqP71S
z3FLq9`v1}PKZ#K{s(dsAC=LN|{!c@z{{zwLfAs!;4qE;XM9cr^?f*cu{QnEB{jZN!
z|EG=C{}e~;r~#uPKm-8ie^Tpz^!`73{`Wzv{|UAKN9%tgVro>$Xb4b01hD3R^!ne2
z8vXw?#P~l0gF+@lA!7W0H2+gSVn<CJ4FMuT0Bin7pa1($V*dY+R{v*$+W&a+KPOuI
ze{}qhh?pByG8zJuhX7gm|36y)AN~9f^!`65f&8C2n*S+}$x#zVLxA)UAS(Z(kN=_f
z{|V)PaQ`2v{?8q4|C1h5qdG=IfchaYAo(BM|1V%*U|@!v7Xa`7vqJX&<-*4Q*--Z5
zf%e_O_TW)JBt}gf4S|st0;BnV<i+`@k4HlQ76Mes|M>*w|Ix?)3_<OGJoP_({BN}W
zhsDz<JsJYE2!YZ3Pm53;HFGoshDHcr&HwoX*8fpD{)gWGhmZe5`~QZc{r{nndPZG2
z)I$Ix|AX!WK%f67b^Je{!2JJc`+uk>n^E@<lMq19|KR&Rkn%rK_kEzx_Zu=OBr&9-
ztoO@c$VZI#=QAkiF+?#iFhJ}3Oa_G*hIsILK+swDAPhPie{{Tmm?W}MZw%TH0O$W)
z#Qq<w`JV}Gy$>VWcpnp5eUCohkKW!#pYIzT?;Et~W7J{8I|RV_pAjwpGa>r_;QAju
z|L3CRfAso)H2)9pL^JBUVG{!2{6AX%51aTL^~h)lkP-sm{6AX%lM-a3YDYt0*n|K$
z|I?uU&t}L&8UHI}s6dSWF)%2YGbAI%{}>n)QW-M9<9|sk44_*^6bu+l85kH)&*MfO
z4+M=7hO#j*q_QzERI?46=ot0LXb8|X1i<J2qu>9-3>pt0=Kdep`hD2>|Ey^D|FEIm
z|HF=U{|^V`{+}G!`Tv}d_5aZOdO`OEA>Y>vx-SIv{vRH+`+s=R?*9SZ*9SfSKa-V#
z33UGdRN~M7M=ozb?9n@a=$bS~Eu%vSV9o#F^MEMG|Iqt-LH7e8-`CB<fFu9I@Bbh&
z|3mNV2Hh8ed|x-{z7X(z-QfE{^cX<*g)xEd|6pNfU~*xF-t~!;|JkAU|FA&s|4GB$
z-WbjQbV!V&R?s~J!0mse^Z&5U{|TVY|Do^q{e?OIH`@NEdsL2EI2r;ZhX6SLgX??9
z{U2EKKN;(Na~VMUdl(r&mkJ9oFenr=RH5|$Ey3%9pzD7a7!=YOvPS#=B*)&UhS3n9
zECgtk|4YH+eTe*D&CrCB{~Z}}QO5uB8H&L9e<pPN&yv9oJpP9|9>|CDJOK3ZKy*H3
zp){&{Gz5lc2+%73moSv0jQ>}G@B4y{7cwX~Fyx@*|2*h<priSJc&4*aUk%O>0O$W4
z(0D(d_P-)p|DOeI{huLb{~sm)=Q1da=KsMN|D&!N*&zVV|14<v-w<v6FM9sZLCgPG
z*8kRn+xv+2e=7rMB{8D@_Xf8Q5dHs3h8jfsKbJuPSNs1kw142l;K9JaAV7A10MtKV
zXBydYKkEC@5CG?Y8r1)F;PyTu|F<x7qxAp1!1n<|^M5XbLIp!LBL6dt=Ks-@IT`}=
z2mx^ZCp7+_h}QluMyvl*G28zn<^RCZ{7;X#9<^gM1kghOod1i_+W)C&?SJ(Ak3Rp8
zrTvdL{|7QCpw#~iqxl~_UPk$&AwZ810I&bcVNft+uw`IpU|@L9#=yW2ZV%`)a5FG4
z>}6wM5MXv-ux7Ak;0CSC=LGe-9T;pFY#6xV=XX0WSTI;Ha5EsU|21deW<Xv4%Z;}F
zkDGx5zTVf8!IFWSfs+Awy)QQd7X$KoUv36&l=Z&c3_K|7eYqKU8JHNL>wOtO>wQ@m
zn2I<Um{OS-m>587{kRyIQn?wJQh6Ad(l~LB9U!muV`XPxK*scllTkZHLx5f(0M7s5
z_5U`A{0|-vK+6Bn_4vs7A5tE`#`EZ$|Do%DvF3l!dS3>11|~+(dSB35Uk(OP?q|w`
z=6?om1|~+(df(CfPp>pKYR}*efp-iH3_=VH3TzCJO>|SCd{zclu%p520n-^2SQuEq
z{2L(oGzJA`24*lHG^#HY$e;kqV;}+0Dj%U#1_clsgwKN1=Q1cTg4zxY3=CpSko|p2
z7}kQ<2Pi=K8yL1QFfcGNNO42tqZn%$85r0Y=5jHBY*vtAkY!+CU}rcF;xjWS$T7$>
zFfed1>;&;M85Cq0<QPDU4KIQCEDQ?r42t0OL$)A31A~Gvg9rly12;neBg8xb1_1^J
z1|9};5TAuXfgjZBVc=zO1@Rd{e2_dJ13$<;tPBd<86p@#EhBaipMgPP7Q;gD{KIc9
zh<mFUW-u@?h%kHv@zWR-au_NZ7#PGEUV!)v3<~}XnG6gJG7Rw`^BEWv1Q`Sw7#L(3
zqEPs945@IwFaraFJcAFE4{@&oLnw&P!k{1k*00E*2lXGQEM#C%Vz7YnL3<w<7?c?l
zL3}0#1x^Mo1_lNdhO1EbC^7gjFfgbx%mv2+gF-#yJ4OZu4F)5S`3wvSeBkiVWKag_
zXJAm^0=EXW7<{07Q3f#v1_o`0Y;H(+iZO^YFfiyaxP#;w85BeqL>U+ubQx+u@@WhT
z;tY}u3=Db<%^-OO1_dbwDFy}xeTEnipOHa95-e}PFag8|%gZn@Fc>nFLiv(l^+pWx
zAU-pL0taYeDT6V*4F{UfQRZe~aN=fQh~{QsSil9rd$<@FKp51fvtwjnfMJk&7+%cC
zz_68(fnhfz1K7Olj0_C-pzM>33=9_-85m$<F#X8%R3-)n5H4Va=m(i=$;80m#Kgb=
zvKJ%=qG1@MSC)~1A&ZNF0Y-!Lg7OQ!F*yI{qUHZo1_hM-A4nkor=#V62DJRoKp_7!
zGAQ89|4a<1`JVwT|1+TFe+IPtpN5wI!TAT2zj5S$2DJRofR_K$(DFYcg91waXCN{E
zv%<;)BJ)2Zf&9<Rpn#J983^QmX0-gDNn!qHK+FFO1oA%vf&9+`k_VL+(EQIZn*XT<
z!1<rr^?xo}{!b;4{~6HoKMR8bN%cQ^{?A0q|LFBUdj1FJcYX#2SpA<yApbL<<$nee
z^M4vFzvHO?8A0+$^*`Lb(E6VNE&nqyDB!LC842Wn2DJQ7YW>g3pny{UQ=0#oLG1&i
z`XAgr7|s9G%JazPfb)MUTK%6(=lUN#|1&ZuL^IYQ+W(9c*8k}FADn-X>i<koen-mx
z;PL<@4{iT5gX;fC;@khMB-a1%{s4~pA3gu4q2+%DwERzM{m;Ol(7^Z}cl)1(0k!>~
z#-M<={g0mi8PV#0CQ$wc<!5O7A6&nK`Uga||3~Y8<Sa}P8=U{CUH=p6|1&Wtp!EM)
z(CU8%wEWLNVg6@DYyW40@((C~L)-u0{EjF8gWLZ|`Ja)*`ag|8|DPFD--E^jaO8h@
zd4;3?XGF{Y3<TQ$EDQ?h{eQgqpAjwpGmx173AO*x^FMn1pElb5rzn%-(G1T21Ks~e
z&;My8=6@Cf{eMFBKYIRW1+@o2<pY`ZKcW6VxP1@G?>O53;PwDg`yXCj;mH5!^*?(4
zXF+TKGm@D9361|TqqYCj2=xCM(dvIf{eQ4LsJ#H~|1*vD|M6sLlBB@-pW5|5q5eN3
zTK$jS{ztF>SqRksj8xA5;PL<||D)Ic3~2R#8e0FKnZ))#sr5fAsQm&eKZqRvN6-HZ
zX!)NBt^Ln}HvX5!fZG0Nq;mbA398>m+y5kGTq-FB=l_B3|7Q|t|D)%BCIaLC=<|Qf
zXzhP^dz#GlKLc9+Cp7-YNTB@>uJ1wl8QT5_j}Ic%|8V!>sQ+0=Z2zaB<$v`4KO<WH
zC$;`Z@Bb5O|AXsyJo%p$R6Zcp|BR#cKb5jS133RvyZ$HC|7Rdj|Fe?V{!c@z{}~C4
z|HJbWH2<T||1+bt{|VLq==q=2`X4?2gZUKXe<rm4e<oV{AHDu(M63Tv9sg%QYyT6P
z|7W4F{XaVXN3HD70ABwOUhj)%|3CWqUx8@*f3WQT$GiTYVRZdJ)go}zpwSSZAOx_k
z{|yA~2O31{e^)yw=rZUs5WW6Cn4N(MwEjO0Y5gy3{Xb~^FT?2iUkZ}UsMcW=0$B4u
zxII9}{J$D<e*n(?KY=9Xe@1o&rUJC}|FHbeIJ*9S7$x6PuTU5Q;PyWssJ=&P|MQ{k
z|K&y7|Bt@^ml<vUe=37Q14A=pWjScSpdN!l8$&PR{0}}*`yX^45cK>HAJF+=wTSaS
z64B28NM(TD2gJuPdj1cE5k9JYGz5@B0G$89^*vJlXC{#U`Oy0Rd<61816uy~LCgP%
zX!&1{K>p`rP#8V`3n>yunWG^<W(a`uKdtM3KD7Lwh?f8L(DFa}`CsVuzt3p?Co{T7
zwT*@VN(g}SKYIPofL8ybkN@vMtN*c_|AW&0N3Z|E<NrwQe+B~ipJBB9j}mF4oY4@V
zQV4+a{~omdKcW1O-v1xX|5S>NQDa6!fW9FB&i|wJKYasz)V9$O7$hM8&i||g>VH<W
z@qhI7Kdfluf1vfG$m9R)X#M}u_WvM>{ZVI(^bi2&e?|iNpAjwpGotnX8PW1T2ipAK
zX#antC$mxi57H0-um7j_{$CaX>;KXB|7D`>|6?Su{|Ej2FZBIC@bfgF>;J*${gJT$
zpW5etf!F&Z?f(Ju@vQ%6CUO5Cq4U2$?KR}{Khn_l|FANk?*F57|39Ji|KRgMkk0=B
z?+-%S|1-M&pK7HEIR8_7{|}-4zoh1WQqTWLBe4Gme10Bie=juugZKL)<$v`3KTIT^
z|3hg1KX`v1D8J*_{|`PN04e{&%PSoF|1#0`|1qNN|3T0HtOWM|QM&(!+WY^Q(f0qb
zjPC!VRsjIZ|9T91U?XAY|LQR4fcfC_e;F9S>+eAV;PZcx#tXsc|Dw+i;+Y?So&URx
zVI6pVpg#2c-+kbdP?<mniGofFR@lg}6}(<h11i6RVK)Qlq}e7$$a%Zg3>o12gJ(eb
z*$gG%^M9X$__+)UlNlC(&-XnD;xjNPlrv0VU|<krsDhqvYr$XzI++-L9<V8cDFXw8
zFyuU7Mg|2F1{3gkzToqKnLvDyyePv@uq#0Gkp`gCj2ZZ$<{2^=g3tSfo$qVLV8+0}
zAOShw*N8y@!k2`f?`y_j&cMJR1wY>xV!t%xd|w6z1yito8HNOQh<_I|EM{O}kc0CV
zflroIfS=zh&sfL^I`0>JelH_~f-%_rDh%0B_nCw3Q)MUs@iQ3|Abd53QV^d3#J6Bz
zU{Gh^gz^o*{?TAif$|L*j2RdhG{NWNg3h-^$E2L03pxiEbOtUA{|B9fjC3|HOdLdm
z>;c`=2%>*N&*ViuTNk7ThGFJ_(&;EBE(8W;{?BBfEdMi5nEx3-`5h_$=Yseo<bNhu
zeuw6NMi`&W{LjdsKvMo^AdvsT`5jdLK=Z%RX#OWIw+ug3gEId!pyhuf1_hGpfAsv%
zNMikup8vsoJo!Hpbbk_3{htfV@6i0u0OOOH{~4&9|CvDf9V!1ag7~BL|M1J*gnb0g
z{{wyg5Bm9E%nYdK{}Sr|v!b2<fj<66==?wMdEZF=fADw!XnX*A{vWC5e-P^bgU9!f
z`u|J>&i{muS3vv!)E@t10iFNx0r&a8=;!}Xdj4-F+W8;o=YN9F2gEb}H`@OvoUw^i
z0nY!_9{(eB{!b>__&@sjpXlTN==q<8#PNUh{0}}q8<f9sjQ^qMe@3+NKWd-<3oj3#
z=YN6uNaKI-^NOJPAIt}pA4H!2hd%y?e*O=7{%1uS|7RvJ{?CMV{tv0+f8g`|@tpsK
zKK?g4{!e7?Caesc|LHydhkpJS`u#tI>VHD{pOwJ)KREx8kpD@o|CtD!{|O%72jySr
z_&=PFBmcw8D<bnh3)=WU`uU&C*v9`!sQ(Gg{}DR>7ks}LXg&{m{y%tr4^RFF%Y)QI
z&;QLF9sehsvx!py&i~Y|{|U|iq33_}_CI?4kAD6q`u$(b1ls>h1kV2ipZ85c`yc)M
zUsBuu;QAg^9^lCT@bZex{7>lqpG*SnfAsnv{rq1>3hRIH`Tj`xAG|&QPy2tg{wFST
z6QK&6{|CDNpGM&PU-bKbGAV5TgU`>#Q~xueo&U*#*8XQ8aQ-hNTKzxR&i^G;|1+bt
z|Iz#ZgzA4%+yCJDeKh|QkzJ{-1f2h=UH=p6|C3t(qxb&_)&I<B?SDoB^*^}3kEi}8
zHUE=Z|FaMn|AUuT(E6VVZT%nm{Xdy#?f*0a=l_D&|5361KYIQz1M(V$(ffbV?*Alp
z{a+f|`d{??kAD9rspJ3P^?peCAG{tI)IPv5{!i`ozl8EXsqKIC`+o?H|Dor9QtN*f
z65Ida@qJK#9@_s0pYM-U|AXfTklO!DXzTw*+y7K+2hgPcC)EE(zyF67t^LnL;`|?a
z{ztF>(Z~P6^Jk#^P2~80CW-BT7PR(11KRx`q^|!(&;Q{0K+t#rbo@UJZT&B$`JdGF
zzoh1WO2_|3=l`gi{|CDNPiXv)Q2QS}|D)IcECkyB==DFiKL9EpaMb^V`u~LTKYY9o
zI{u$Yp#2Xoub}OJaCv}~{|Vjy$4a36k3Rp0p8uH`Q1|~(I{%-BHvf;_{|A>3NcBH>
zeh}1NfR6u<-v2{20IUB8)%t%XwDo_C6t4dxb^Skhy&uy0Uoaof`acG=^?&g7enhVS
zV+5`D2boW$_5bMWf8p!>q3i#1LF@gH*8hRm1LIl$X9V)!==y)EWx7FR5G?<*F|dJM
z1>66_%D@WdgZKZWGbpeyuz>mC{Xc083d{`5U_N;NPatU94ilK)1lm<YX#6jYL18I$
z|BnK6e-C884-<nFHv<DBBZEQ=V?84S0~^C!E(Qh`R<!;<q4|G8^*_8m#nJu;-v@?T
z|L*|r<l$#vhq`Yzc>j$6!*4Fg{+t?ync)3GAEEqQhAQxWpcf#18iPUrLly%AgA4;~
ze~=&psQ!l5|M2zzmFE8lwf~tw^Z&jK3=FD}{X>il3XO~(iC_PRKK`FcV*ejpzk}*?
zX#XF)z6YuQ50*!&|H178ka}qSKidBX=QU~&u>4Qg`ahFF0q_35T(tV10j>ULWKh7n
z{||lrKdtM3CQ$u|wEmye`X9XCkAnK&h(Q5m{~vn&53b)q^*yxyhx4KPf53b^^*<xX
zf1~w3HS*hFGXtFe2VnglO8w6a%kR+op8>7@NALfmpZ~!`VEqsJ_#e3c465JBtp6Dp
z6!6ynnG6aj^*;kz{SRO7M`ZmEZ?8c6|KRfgK<x+U_#Z3U_#gWEKdj^bNcBGhf%=~j
zt^bc+|D)gkN$d50X`}1^s8x=D^FOuc{|Sx%GZ1M16UzUj&i`c+82<y0_aV*yf%%~F
z0WtoE(*8%!|7i>gc-#Nz`5)fiCo=!T%PSoDAAS4}{rnGRwDCViwDx}*TK;Duu>J>q
z{U3V%C$#>D6>a<vz5S2A{tvuAXte!Ltvrux4mkhQd;FgjE&rp}|14<rKQmhYKMigD
zA0t}*&xE%Aht&E%6Lb9^-u%x%ApbL>)&GR@KX`tS*86`*sQ>A`{tvu90IB~!n*Wir
zELGXy{7>!rpV0Upq52;^|D(76Nv;10<$v&cUp)0cc>W=Zk%0j^{)b-w6UzUD>VHz#
z|74=A|6@jL|EHm?|3k0;!TbO4<bOuA`k#fw_CKNZf8g;wP<;*^{{xTjkud(pI@<oH
zRv`e+{{!9shoAR>qyLXy{}ampj0Ea`@cLO$`yNOCpHTZh4XyvrNTB{Fl>g!50dyMw
zXF+TKv!b>C(dYjO<$qGw|1hJq|Izb5czpm;{hv9y{*PMu9o-yo{%2rNpzHWQ1A*~>
zczM9gK-T$xv>yM@L_7a47c@Rj$MJt71_hM!|3Kv(zVrX!=lzg5{tsT?FgpH^o_B@=
ze?am-6OHq~5tYyXqxSlrOwf5?p!ql=&;LX}|Bn$Z|AW>$Am@Md`9Ju2pV9n39P%tR
z{V*W;KbOY&pAjwpqo4nm$)JGu{9kZ>M_T`9gm(TX6I%Tbt{>@G|1*%7|H1S7pz>xk
z|5G#X3<tAd`Jbxm{|L?hF{6$D!`u7N{(mOg_&@siA1m7UKMUIUKd3%rP-I|W;9{@^
ztsf*b{s-RghiCjR4YdA<gz-NX0`vdi@qN(zJ&yT5@OS{y_&<ES0y_T(o(}}+htB__
zkN*)`|A*fHCp7<0X#Ahj^FPr0|KRaKr2aox9yDG!y8e&aWezz1(|i7p(D*;8^Z$hM
zKl=V3@cuap#{US7|1%QE|LF67@bZ94<A1DZ<Nu_t|6xHJ|Ib7l|EF~S5Bm5Ycz-Vm
z<NwT~<Nwqu2f+EC-t&K%3<~oZR)FvS0I&Z~V^CPlu%3Z|0b2hvFerpERwCB_!`GLv
zGn|Lk=MoH{^uocg6UrB7kO1HRaS6(oWROOw|9Khs7#JA1;rD%TF>rzJ2Qi1<Z^6mH
z$-uzC%K*Ob1D;<H>wh*egdpbsSQr$hGR$FMU_h+@FJqXDvi?6Ed>@H819<&E_`cH=
z#QJ|0(0m;?=++DHt^yYD`W+A-n*YJ)dGInYFv!F22Z6X3TK~hx;}sdMg7z1H_eZ!h
zFfb^=*Yj61zGeii?+4!p0$(q$#^3`DAASZ<`KQj1%?-L$1va0k!Qc*+=VJi1hcp>#
zpz?wYp!SFsLo-xfgh7OXfkB%g2E+%SuL6?SVVD5ogV+CwF)%RbGL(Y&@b;G;%KahA
z+zbp(+zbrS+zbp0xFC2B7Xt$bqu&t%y8i=)Nx5qTb~gwz4KoM%j1G`}Fbq;F%gDfx
z#l--=l?FspE58jkb71*@M34Vx!uH=m@BcyX|AX%X0<F)7-v5(Jp#KlQ?+3^JKk)q^
zp#C^?{EycA|3>@&gDu+)8ux(n{{YPYqtyQlX!U;@TKy02Uqb7D76t{p^*{JL8Pxh;
z0KDH0QUCKYfa+Jo{67x^4@&*d1D1!@|BMU@DD^)Bh4nvpejU^vLG=Im!0i)g{SR(`
zgX(8Q{SR?3wEkycP=K^&p!Glad_<)BpMgOEz5eG0`wvn73xVr%X#EfGA0g_0K?Wi4
zeP6KpUxWcvpCjsjNP7ud|AWut<zQf7fY$%u_7kW*1Fiqz>-9(L|3Q=Sp$-A(e`>e?
z361|Tptb+e^FMm~AHKc>n*SLH<bUva5ftQqaQ_)pK0xz-CV~9V!k|D>`yaf%4p06E
zmk%W5fAIJyQvL^>M~vM52lqEX<r|Lt4{x6nng7A(34;1d(EJbXUm)dw@Oi^X`5!C~
zQa_siq1kTGP~iMO0ONls^*?(5pAoJ8r?meM-!DgG{SV$hgOvXn2;_eT0{NeXLBWdw
zssEn|8ec=o|KR&JKzwNZPip=LpO1)?|4FU?!Tonof1b$v53b)q`58z42j4d^n*Rq)
zCdcCtaQ>%u{ZGXDf0X=>UjMUDnE%1&$x~4OgXhmk$p4H4@<00cA2@%5@;kKs4{s0P
z$p0*$_CClxINJZ{^*^Ef&%&U9(*B3<kHnGxSs4^i+W+AC9Z&uTmk&t!f3*FNCkGC!
z6gdCWyZ_IM*8XQi>;I#-{|VLqEDQ>G$N$0eeW3YrBI|$f{uxkygSP(()&H4j`JaVB
z0q^)fdj5y=apZq+e;?!?BJ)3b`yV{NKtcN-yq^cD{|~O;Nyz`B?f-$z<alfc=YML~
z|AhMgjA;3vg~I&LKp_9a_sikP|KRg7K=}hP|A#XEM=1XjYX1|e|I=Xo0UY_CkwE=V
zY5O0&{}0}eNW%CZct0Le{~x{nho9Fu+W*Is6$eBLoc{;9|Bv4OC$;`(M9crwZvV5Q
z_5UfI|A*K2(Dpx^k0bwQqUC>Ze*n~ffR6v8xBnSQ9REkp|KRmWNckT=pO0hwADqAO
z<bU{i-J|(`Kr%TVOTqb{+Vwx7{(l-;{ZDHCN1y-8M9cr+^`a#7|H0#ZNcBH@`=8qL
zfAH}>9QmKp`9Bsa=YQ~dK1l6<aQ!~o{>PK8hKv+A|I@qwKiKB~!1rY#<$qGg|442B
z!^iue`JYhxAHDw%?hhc<|KR&k@r?fyn*U>kosWiN{Etxn2aoUJssBg&|AV$X0Ox;d
z*Z+k2|D@)B^zlDN0`vdi^P)(o|H1hkDgT4p1EBFX==fh6TKgY;{SPbJ_#Xq>_#gWG
zAH2N}&Hr#dj`lx#{s;F5kn%rz`=8MGKLgtMKcV?QLhXNW{zl6G;PFAE@qe&9sJ$@S
z{vT`w0XYBDyZ=w9{ZDBAFOxw2M{oaw@6RM*{2x3Xh?M^cjsKB4{|B${q4^))9w0LR
zgUbUF@;`V#0jPX~uKz)w|0C4@CshA~^EXod2lo#~^Z#JW>)6}_&i~Y|{|WW~DXsqr
zt^Y&M|D?|Uf!hNl<bU+`Kl=P1Bii~OczqAe|KR>UC_m%K|Ey@^f28LBOwfKKr2LOw
z|ECdX{}Y=38*Tq%%UVN144nVz-T$Zd{2wcY<A31%4$2=m=Klz_|I-Mx|1$~Xe|UL-
zBmaZ@`=IiO$oYRl?SDqJ_CI?4k3Rp$g0}t#T)%_b^ElT3f#pZ*|DjL-fb&1K>wiN1
ze-;YI|IzDz^!Y#Z`acb}zZJ*)KX|=Ap8SvA{wFm5$B5SdN1y*kZ~qg@|KR$biupg2
zK>kOc|0C4?AD#aj3RxYi8)5l>NbUcn^!_g<63_nv?*~TO|I0vN|1Trxd_OY=1_m7a
ze{(_dNc(@$@BaetM+WJaVMt(y+%LG8VKD;(gB+ZXa{ediyd!+)|Do^yH6ro;Pw@F>
zqvwBO%|Jt3a8TxdBiMalM4tbf$)J!8K5v7Q;VB~|zf5LW06yR2Ae3LuFoA)AL6D&e
zblyiUTK;Duu>YUb{7>)u|IqV4BZGo51L*uh6^3k(f6?<l<7oaL;@OsJ&IjjzdXN9p
zd;AZ6ULKD2KX|?mPy3(L^*@;e+W+wOK6LyK&WHB@!Q+8Q`+w8W#{a<MfuQk19P9r`
zUH^kV{s%sP5NZ7%q4qy`ec$N#|4;<r{7>!vKefmI(f9weqRs!M(Rloi1#SMH5$*gB
zLgRnv{eSp;ACCMFE)S6MKYITkJRXRY{|T-CA$9*xCW8V==YNdO{|&{g4|X#+|I>T?
zpVIoD)b&4v#{a<Ueeu-)=;MExX!##~{ttcq4|@Iw*YBYGizEMo%LhF9A6y=Q^y8@i
z(Z~Pc_X9)c|Iz3F2(AAiRR5#r|Izh7;Jh^y2yp(VcKuIi{GU+%M_>Pge*PEw_&=fj
ze}vlq=<|QnUjM^N;`|@@d=RAkkKX<V^GV46=<9#b^FO8Mf1&69(fPljkoCcC1n2+3
z-v7^JP!MAfXJBA}p8u6bV*8)g>wgHH|3&HgA8>t7#rZ#03g`d8^*f&VfAIMrqx1jZ
z3^vFKaQ>%u{ZDHDAASEnz0dz5wf&F2{vW;l&r0F=AA0{E+~21l|EHm?|0A^i2YvpZ
z)b&4^3<{hKqxpZ3XMM2q!1<rv{eMF1e=<ot|BKN2A5z=@;Qjz8zd`r^p!fd?<$v_`
zKWQYk|Izb5c)vf$J<#=kq_+P_9sgq`F#ZRw-|^J{=<R>-`~XP(=>8vYrW-^AIR8_-
z{wKBnPwM$!=<R<(=YJ8(|AglM(DOelh2wwV{0-{A;~4(~%OmywNp1fVn*U29(EcYh
z{|Bz$LHQZF{ui9TN9X?rQMM-9Dd7A+(Ea~R8lV3~DF1`U`|yna6Po`+Z~v!J*!~Bf
z4}vHEgZl%Z@&h{lPiX!Rz5S0q{)fK)AHDrg>i9o;{SRIr3@R^1>wls%CY=<5^FOug
ze^UGZgwFqAMH~Mkb^eb~{s*`B@#KH>`kzqyAASB0z5P$={2#bKfRz8y_y1FR{ulT@
zLK4>h5E}mn-w!gH|LK&aNwNl<|LNWTCp7<ue*Pc&{2%)HU-X{;OB-bEfAsr*GSSZe
zLZAObZ~s$!{*QHZ{EwteIDm@5`JdYLKdJqH^!lHb#PL7${7>oqKj8KNXuOTc@jvwW
zKlJuLsq=r}{egJe|KRZer20RTK|zLrg7d$q-TnuU4~~xi4`8+?+G=qAAL#x+dj3bB
z|4Tz_{}WpOlgXffa{upOyZ;9~z6Z*`G#dXyU;l?b{!eKB554`5KK}=<-$Ctp==dL@
z_CHu2q<*yjPjtqllR|L*r*{2MsQ-^X|HnGO<A31#9;yEiJ`WU6{ZFX<k3Rp0zWx_I
z|AW{2g31Hv{vWVBQvDC^?}OX}o&Q6x|Iz#Zgz`V7=YN6gcTj%Dk^jN>1CG}JbjrdM
zSp&}h1Ks~epZ`O@{}=uIPxShq()mC1{14`X@*9!ufAsNx^z*+6<$v&cU!?p`YWttm
z{7-27AASB0{roTR_&!qpCp7;Dz8?gnezg9lD6`T)GdTZKyZ$HC|3^Rn3%&i1KK@5)
z`yc)MA422*)SmxCAO9zm|H1V=QvL_?k?MbNeGe*+h^+rv(Z>JK+y8{}Kl=G!nP}&K
zf$Mire#TM%gUbh``hRr(j|MrHI!1!?KfU|^nP}&Kq2K?Dp8pBe|LEg?q~?EceUH@s
z2lGMs4M+V?==?82`JdYJf2?TZf0WMukvjhm&fiGuf57DfQvM(9|5GQk(!dmO{-<{R
zPpJP-X#Nkq{ZH!rA1m7UAEEjmoZs=}e^Sr?Ae8^X^*gA($1(l~E+0s!|Iz3F2=)Kb
z>wik;|G@M6NckVV{s*5A3~Dcow*P66g())f5hnwK5CemPHiI_UoF@zrz7B&9nBN2C
zYcXhn`As1HCI$r!1`RO(EQrs*prFa13Fhx*V_*>Y&!Eu2(98fniHnngL4bilp^c%J
zfq{XUVIoLg540Y>f`Ng7m0>-IFU_D(#Zb$@z`({ZlLf3x!IHs_fq{XGAqm7!1D&@A
zI)9Ik;V_7QfI-2D!Gi&0@?=H^1`y`wWMEjtz`!t%4MKy&LfIG?QrQ?7s@WiF(E034
zU?-0fqaiS2L%@Qafq@@<zM~BTI|Bp5do~6J{!CDLpby@`1<ubo4h&WdRt($>j0_Cm
z{OrJB&0x*I4a?6A4h$9y77W}BtPBe|7#IW@8B|Oe%o(^D*cj~C85jha8B{>$(Qz}d
zGkAme3=AqJ45kd+3>=XB&*H#f$zaLA&A`c^1D1DC&|?7E&&BYA4RmUsgMu!DE(13M
zH-ivV9>V8gkcad27`PdD8JHN@7?{%78JL(@8JPC5FfcK2Fff53GXql_7Xwo^Hv`ju
z9tNiKoZxZ;R8F9m9iVa~j2%*ru(C5SAmb66P)0pIEJFa?{vYV^e?sGb=;wc-kN>0h
z|0!Mn13nKNssEpecK#Ro`d{?*KZM%<@cBL*?SF9pfQ0rx`uKku+V~%#`~OH?{{!yd
zgWB^r#{a<cgQNZbp-^Ce^FOuw|AfZ>(fj}C<A3Pue<&UQ8*J-;;PZXZ{14vm0~!y&
zG5=3!{67tC{EyWB|LFN&;JzcM-3P*Uj0_C2j0_A}TnKt7<YjW)2+sfX9{)$r|LFBU
z3xh%=V+|u{JYX&t0|N`G`9F=y<9`ec3R@Y%89_ZIc5cY{#8iek;PHpwTnr41q~8Ar
zuHQlV9h(2)?ExJ5AJ6(9@cjVb{fV0x7#Nh{_XBKX*vP=ZpvrI+<UV-&K#gH8WK>3>
zj`1BM1A``m5%hd;ZU)f!rxt?`D7@k8gR~j4xfvK(GGX_F=`gs1<l*xJx(qcSc~;o`
zpdLdrNFH4OgW3oB3^5=+c>EtUK4`!&0m_G*4`Rqr3gW}Z2aVu;GEl!vnVW&ZiJO5T
znwx=P0T%@C;bLF_VOTx|<y8;{sfXdkj0_B085tOML&t`$GcqvTgR)ODGB8|VWMF`a
zf%KwdkU5~SArSo&st?4rWMW`&VuJJwLH5HiNdHhRFTnYq+Vwx7@qhIBKlJ?1Kw|z!
zU;l%C|1YWMe}T^fLTdk`=YLA)|IqV4oR1^_<Ej6_`5!z#ft3GQLH8%%$^U5#`13z}
zegK;P;r#;~`5(SM2%7)l=YtWM|H0)0sJs}>|K!x+l;{EH|6B$Il>2{D8NlOhAalX<
z0f7t(u=#)+pz;1R(D)!^z5qNwkj|ihGC#n8dwxKS2~vL^XSe{ai4>sx%M8~U7#Nrs
zq@eX{BjXa3`rnSh9&!F31A~GCgChe20|&!SQ2oKcpkUA7zyKPYyaeJiGAKAQID_X8
zY(abm(0w143=9m2^Z!j5K=TPa4CbKvkA*?O1bklx^!`6EA0&^M|G&#nk5d2dWjKPU
z{}~t*<}vJMU|<ko_z0?R(-;)`!R-Tah8G|{1A{^l11O|q7~(<p!S4rw*8gds`+z|A
z{Xp|S3y5#Qz`!8S-~&?62)myIvHr)D0i<3LQs1*MDBNPWg{c1-85C|Z+(gv>tPBb+
z4EYQU42b%F86zkr5cNN3e3pR$TK_XJC|EIAGcYh9^1n5M4FdxMBL7=5STQg#K<j@7
z1_c}Nd<``JgU6E%85kI#`9Bjhe`CPFz<{X#4H-c92|??B@O?@k^`rS8l;`M)!TFy7
zE&ns1<^Oa7`9BaX|L3CR|5U{MASl%_GB7BRl>b>66!7MMMzs9TLSp_0-|qvuF9(|c
z8A0U%QvT0mP#`J)Goa;vRs#7SoZmtD8JhpW<pWawhu;qd&HpT*@&KeBn*SNl@;?Jw
z{%53e{!e32K*|4U1oA&Pe~;#Wdgg0l?E>fjRJ8n`i<bXsUH_*sD3DbDvk<8N8A#0k
z;QWr1|0%8i(epneTK>-j)$gGE3$6d*_XQG}|H0(}NI#DJpN5wI8A#0ktR&X|EF|WC
z76ygU`k&YwN?UbU=l{X$fk5-`3=H7;e+Clg|5u~U|1%Jn{|}_{{67;r0}}%)0}}(%
z{69N00}}%m0}}%`0}}%e0~71${6B3|)~M-2Ap{t~tMG<`OGn)}8UmvsK<yA1&HvO6
z(NXh8LtyBH05f>iJqKu6@6d7ds7psfU^E1%5(1<7pDMvPYRG5^49O4x<$o>)9tO~A
zmm%qaQAdx4z-S1N4My`n*+Dm|aWn*md<cNX|0KXGxfmE+Kr6gB7#LhYOSOl*&qh5k
z8UmvsKqv%2yHH{o7{L2NSip)wB?6cMCs+g&6yO{>Ft{fbnS+iRSjNBrUf-$=wi9x`
z2#D$A!oc7l&>}E_frZOusfsF-0BB7y3j+hkM36L<F(N!pb`^u&6~M&6@Q{@Oyn>a1
zVFuhjCpZf$gM)*SiGgDRLxTrH1A_pA3WH+<Se*td17ib&mzDy903$<_3!^6kc*~PR
z0;p}q2nq<WGTek>3naXB*&ypRKs#?idzD~1K<;u7fW$6LjCh&}bj%6^-lI|&8yv8i
z=L~h%Nj3)XxeuU~7m$5F*i_R%4D7B30fr`r3CIap7wWET_Q9F%C$JB$bRUsA2b}J=
zvk%U6e~+Dk0d$TLXa^fOv4WD42LpouXbU}vjTbvGFfd|EzKkunw82XR9POl-G)Q={
zf#f+Ez^9Uc&L+WS9%<r?Ees7T9RjYXx<GCMVN_96UOd!YQG?7~Z_^>+HI;L4rLTp4
z5O?k799-#3D+S`NpPUTf{g;rM(FhXR9zqNP6B!r|1gwVe8C0M&sT6XFiA8UcfPfMc
zhm6W14p3zbR`3`ak6_LyF&YA+Au#AefKZ(==shs%z|jyG4FR%4;NSay??Gii8>rJ*
zoS0jXld7Pr5T2Q5Y@`sBnv<GXoXUVE?2?*Pn$A#MkeQd4nU@Y%jYAk_h?`YRdTM@d
zOh8~je3@ZPN@{L?aSX)dnB2t7JiX+C0tTDnl9bGRy$m}Bo7}{b3=l&pATU5LLx};T
zh9NVrgaNxjP}iUum6MqSGQ!5)M?XEMv;@Rf%FRzn%>fyx<eOL$mYNJ=CY9#pRWg8F
z<_nT#D9JA>EoK0V#+T&BrxYcYGk|5ZAX0EakYNl-sp*+{6$~l)rAaxd5MCuiN@g)b
zVpV1?LuyWH8AA$)n*!#ifCY;3OAHx`@=J_BgfT;6US@7$Nh*V9US>&HW@>qAQFvxv
zN`5&*S$<{;gLi6WQhs7lin9|#X<l(=dR}UZLUKl8kwSKAB`8P~D!^nVgKvImajLTu
zm=~V}p^70CL`ghIO-W{cp0g8!yH8kZQAuiraT!BePJUvELYP9dg0Vs@)FW`N6Ucim
zpdfI~O99iKDLEipTr!IbauO?{_9YgjCo_OurKO;ykXV#nMj)nO!OsAS;dtl#+=9%U
zR8VXvRaI40ff&B=0iF!W`FX`93edpyEhx&&D@lh6f+8%))zL@67vgdV$>5s?R>k1v
z>Eo)PrI5w|(Zvu37RJyF^L7|i8$=m{Z)QqrUP)#NBwb*!CJa+S2+Re^zTngZ(NzQy
zg^&!sA<4cBVaZ_#1z}JH48F<vImuz*_)3OwKq3%+5rc1qZ$TJ_&kZ5QLP!i*BZxSJ
zM3;rTw!#-=cnE`U2$+RoNf^`;2H%P>OecgvEnz5zNW){L*bro57(=mdNCk+j2xAD#
z4PyWq5mpdZ5sV0dVg}#h?9_4$i_4%64@)k}FD?#a2+K*$OE1ZQYlJi4i8U-QzbH2`
zC$lP*AuJ`oB#a>}C9}9B%!mPGpKnlpNfbg)2?IzV0!&6S_=c6_`@8$VQh$DWPOd_<
zf}xp0EPA*FL0knP8T{RSO7eY?q7zjbIr%Ce8yXk^H5XK-1x7LiMll42gWVE{aAHbo
zafxqYNl|76#5M?tkS{Ju4lGS9QHWMBQHW*mEzHa-OD!r+MJNFI!B`;{s?RqyGd(pA
zAzPMT3et;E0FS#AxC}ydBE%F3Ng#8B3dS68kq*hZ3h+dZ5+LxDg(?b5QQ$Jy$_h-u
z%9fI%%;Na8%$!t6iEL$62ayJoR#xBwia-?sD&zGsAo@d!GT{s>s{#X9{6mUDu%RJE
znO0T>hRDi{kT`h|HiWdY$^$tN#wkHEU5g<-2VUa36H^;vSA<d1;a3JPX7MXSL>MvZ
zG8oblb8?Vte^@n-E)HoGU^Nq}GzMZdB0j9Fl40SOn+XkFE34eZ3YcgLq~eLs$t*5`
ziIo<o#$ywAPc88)%?&BaEQYBJPAv&7PK8!pJ|H79^GXy-i{S|hl!QRZ0wkQ7my%k+
z0I45~pmaKvPJ)@}o?7CRU*VgX2hGutB(H@gjc~tvYDsW%VooY7t)Z3}5Zwx}(iv~i
z;g4L@00y<Ml;ABPB?hJ3#F8>d`v<QbpoSMXCzms1Fyy5s7R49jB<7_uq#;=OWtGq-
zOlDp>LvcxJ0YhGCZc=Jde12Lyh+7P4HyOs4q!yQ?rhv;7aNdG8sEl9|;FgymxW$zR
z(PISV1Q~*LfvQvuEd@<TDFh)ILa@m(1Q{`e7%^n#WtPO3WrEsN@#T<4RdP~%E~ur%
z0A_%iLm*Z*w3P*7XQt$&f@o-pV(`gNObJLts(BPN6too76oSwk0xv%y(jhQuSm6aK
zxAGEmQyB_NQ;RC&ODYRe8H&M4p(H;iwJ0$!IhDZ*)EtMl=Rv2lL75B%EDQ_<tPBkQ
z85kHOIl+hBFn~rTgIE|CK&Rxv)Pd-Oj0_B*)9yj1oPka$1I=`RX8G<jF))a+F))Bm
z;Xlj4z+lh9z@W$pnfV8u^aGly0i9$98oAcwWMDAlWB{KC2O41q%`SmX$_AaF20C@e
zf|-FKfD>{$+j;2pkRlfY!*eDEh9(vUhI1?o3;~P`42zf;7(gea-REFnNMm7O0FClm
za4|5jvNAA$MxsF{$bsA}&&9w1+Kmi4AtZ@~fdO>V5a`St(8zu_2Lt%zI1MHS1_@RM
z@F_bWJwHJN8lDcCHbWBwof@9V$-qzu3O5D@hEzt#%n#@^9%U|sVs#b<1{KipBuoqp
zoGc6soQw<%D_IyAsu&p<LRc9XTp1Y{-Z4UEXTn(+7@k7o3Un$S$dnhXAQBUUPBAZq
zss+jVGBYq7hlUx555n`985sUCL1yqkrwW2ju>;+%u!Na`;Se(eLn<=^__TA-4GAFi
zppytev>q1!f=;h{#sWD#uZfX?ftQ(q0W_OBfr){kfRTX#G{Xea3&K~R6NAlAx0@rm
z^8r-uBMSq=cNPZlX+)qK8$kMyG3bPJ7~hr^GTR3_DGzjF-d`3522W-NhAa?fVPL3b
zWdNV@4mw#+7rNr4oC&h(WEuwpLpu`#!&VLkh6Yv!2G9sM%-nj=tOb-)#?8P0I%yEf
zg;Su@o<N*7Xgq`1*^CSfdC)Kdt#kp2fleg^(IC8%6>(Z%12Y4|17-$>@5~GgznK{r
zSXmet?yxX0#Ii6jtYU(kJjlexz|hVNIVm4B6AYRa;|KMgL549fFl+*)7id_5Zl3_1
zBoCDW-%bHz>v1tK%s>ijQ>Y%0{0}6*g7~0QIzUQ$nHd<~aWa5Ul>&)_Zo@dw#lWD*
z!oVQT%)oGpm4Shc8FJd;0aga^>55T|kdqTZCu4z5*8-oah!j2`b6^;B;wgv?I_+>F
z2Lr=YCI*ITP+o+lRnV+=Co2Q^R7udS8o8_t;1m8qM|A2lF)+A+@;3tm1L&3z(8-Y?
zvp}aUhJqZ=z`(E&nx6Qf{JS6pqj)p~MnhnLLg4d614i?@VslUdd4`#RK_ApSDQ3{m
zOHR@+Ni0fFEy>JF%ZKoD^HWN5QqlSP*n3;xp+v-R9N0jJ0XQ^Z^lOOM0&fNruLaWS
z0JVup)sq1U3`pSULq;&+gP^c(5ZF-cN+3NV6a`SP!%ZPV35rFaPJd>89!AVyZP!Cw
zj6G(sYk)eB94%O5hJY>L?m2qQ5TgegGtg9qRR?O9hy)G9dj!=AqWl5Z0viWMP90E5
zc;Y~bd1w+tR|82vpw^BW_*6{>2ICEX=7Vn30u?ig%nS@5xmC;z4AKk?3>z3Bt7f{v
zCtNZx>;v@@7#J8rm>C!(85kJE!Fz-m7`h>y4hB^w1_ogU28Iam37jAk!3)+HJ~4vt
z4r6FzW?+zFU|{$JK5>(Qp@)fqK@_B(33Ngx1H(S>$(#(}`-VV`9(Pa+m4SgFgOPy&
zv>p-E0tc<-0rg@885kJU!6$z*FuZ4ixCLV4C^;Geqai?P2*`kXEDQ_`9jvDrcd#%p
z%wRhWZkty?=?=Ejj7<Uz3@`XjGlI&D6>O&&LpT^1cCejh1nn0%!FHPQ3KIjv4Yt#a
z6IdA-Ua*~Je8a%N@B^fuk%57O{WK#R0|SEul-6KB%?RpnTR>?K_S1}@PC*1a#Jmrz
z5c3$I=B;2o4PFAP!FQU`fRTa00!q(dh1mCiA0p4df0{9ZnSnuoA7Z`&l)k}wno)=$
zn=ywmjWL}ugE5mai!qTgi7}Zmg;9h-l0k|=nn8v^mLZxkhB1~gjxm){n8A)wj6s|s
zkTHlcicy_GgF%onk};k!0UR!rhWDuc(GVC7fzc2c4S~@R7!85Z5Eu=C(GVC7fzc2c
M4S~@R7>E!60HeDCM*si-
literal 0
HcmV?d00001
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.opt b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/demos.opt
new file mode 100644
index 0000000000000000000000000000000000000000..237033d492a5833edc67a26a5e6693866af97436
GIT binary patch
literal 58880
zcmca`Uhu)fjZzO8(10BSGsD0CoD6J8;*1Oo3?K{^5@2BX_y7NY5F18=*#AetkP3mn
z|NsA2U|?WiW?*1oVPIfjWnciuIXeRb0|x^G11AFm0~Z4W12+RCzIhoK82A_%82A|&
z7z7v?7z7y@7=#!Y7=#%Z7(^Ht7(}7!#2FYEBp4VNBpDbOq!<_&q!}0(WEdD2WEmJ3
z<QNzj<e}<385kIp7#J9o85kH;7#J8-85kJU7#JAT85kHe7#J8d85kI}plWp(7#MUJ
z7#Q>z7#Q>!7#Iu~7#Iv07#NHg7#NHh7#K{T>dY7z7|a<M7%UhV7%UkW7_1l=7_1o>
z7;G3A7;G6B80?_x92giF92poGoER7woEaDxTo@P_Tp1V`+!z=b+!+`cJfP}8>D!xu
zfx(A?fx(x7fx(Y~fx(}Ffgyl_fgzBAfgy;2fgu>GHk5&ZA&h~6A)JAMA%cN{A(DZC
zA&P;4A)0}KA%=m0Ar`7Go`HcOfq{V`k%56BiGhJ3nSp^Jg@J(~m4SgFje&t79jY#q
zfq@~5fq@~Lfq@~1fq@~Hfq@~9fq@~Pfq|ibfq|hAs*c=57sQaykk3%UpuphDkjGHM
zP{dFP%Em-vF$Pu!nBAbXgHPiD-iG(7FAp+;!V{)0oFSi~h#{Myn4y3nks+BOl|g|a
zn4yFrk)Z?}7BF?VXaxo)Mo?M>rCpFaaH&HUX996Ri4`38MGW~2<qX9PsSHIRaT2ir
z0}~@C?|||LvG((T?10+u%8<g4$xs3g1&}bQn2&*p5tL6sc7rf6`o%zsp!PE|u!8eG
zds<>nPG(-Zsk2o~xTl|`X^e|&uy=@mKukbjKzx~@o{^qmOiF5QesK&`C5+ZfDJ}rj
z3LM1+nR$7cdFkeajeseQfiYl)uoWlf7UZNF6JZ2cVGKk)OgjU^0SUkSyyX16lFYo)
z#H5^51=ot?)Pj=C{5+5wL0FA};efDbURh#JW{QGKW^qA&aVD~S4+FyiQOBa9#7YIH
z{L;LXVz3dZDXA$S-5}h{z;Hm!Ehj&*M8PFBFTW@^F-O6_Ahjql53Zz-f#HA%R7qx8
zW=g6;Ql&yvYEeE&KM40D6nN&PRwO2uC<LVzm*$j!Btdur1H%DvhzT&qg6%+d>O=;H
z1AGuQ{$;5}X*v1jAgv%giGksOAVey-Br!Q#!8s!}IU6Jc!jl;o4)8-{L-SHlbxr~K
z&NHthH9fUR!3C@1r!p`c5P&H`w|N>!e?U=YS!PaZdTNS-XI^nhQE4)=yZ?gR4RIE_
zZc|2v1H3LiJ_>&MB?@k!@CUgUgq;`}4oHGzJo7S3G81z$s}ezGD!3(P<{;uGxj6TM
zxNl~1QGRiLT8V<Qwl+BWP*MOW`Gd*}w(!J~<P1Xw1_;9l#xRC4Oc)qmGB7aw2Df@r
ziwcS|i&GVR6Y~<&Q;US15|gt_3ltLbQWSzxlk>|`iz-=dT>XRW_|ozVQuA~a;>*Dd
zmg2&q5{L{ElOw)3wInw`B^4qAAvxSKb5g@HQ_CUT(h@5rJ$-0)(@U*LRZ`H;$xJFp
zEXlA^($kC4(~HT;Oj1%%;^O4wRB|pYF3HbTa4OBrNl{WL&n(GMNXtn~FIG^3$lEyQ
z=N9DWrRJ3=7*r(Mp)28XE=o--$;?YvC`rvNP)N(nNmWpSXTuOz-+-8)-~bb2GXuR4
z-vFp?P)1A5D=Aj6NzW-QF*ef6$xKoJ`93`d%E?YG%1ecDN{dsApyKH%nNU`FW?peY
zetr&EZ*qQaN=`adCNZTfu>hv5I3qO&W=?)iDpW~+PHH0D;?mO06tF4zDM`sN1u03%
z$puhOL16({UOz8CCqF%3LBF^(skpMZBsJG6IX|yBKPOc|KQk}6C^a`VuOu<YDlcC_
zzaS+EITi|1l9Uwma}$#@GV@ZcJdG{P6!i0njVLa?n4r|0)WqV{nB2t7JiYv+EM%el
zl++xMm>nW6lJj$OK`AUJGcQ#^DJL^88<Y+d9PmU8mrrJ1c4l6>o}L~T7Z(>&@=?%L
zFi=P>D#|a?DAv?bFi<E@ECLnS8pWDiqcH%A6pCWN(7+6mHMl@IEfZ9mg5m%i)5!$|
zT%g>ZqX%Lk#gLDupSOaQLRw-;Vh$v36ny-=4Gk>}trU_I^YZdb!1+lbGq0eu1ez<M
z$ykZY6%>~WsTHZorQn<kOCMMw-VkCqX2gRE!%;jM0;3@?8UmvsFd71*AuyssU}F!*
z0v?78h7vu{h|-Ai`lx3|Ltw;*05f=O0~`#XL6*_+KZeoqKZXNhu))32@xRgWKhR{r
z==dLGdPJ{abo>uI#ydI!3!5i{XN}SEKX5Z*lo$<x(GVC7fzc2c4S~@R80;Z1I{r7<
zV`$WUqai@M5a3{7X7Kg#0xfMF9sdK5g^rH@jgJ38R|Jl(|HByM7+wE2y8aKe#&dN1
z4<l=gj{niFnKEkfXb6mkz-S1JhQMeDjD`ReLtu3LkBWggYSd^546zWvw*NYuA(J7G
zAqBiInvi#t7?>DAX9R%u9)mC;^&ojg5CPqP?8y+o;K>lrkj9Y6ki(Dzwi&ed9i)U9
zEWyCU2-?pL8oVUder=G!X!aK~Br@bO6foovwd)*Y00fIMFv0h~6KlUINGpc@1z^AD
zfl1;+K#GBh5o9k6gN!DG?Li8l_A@iEGQjqJb2{fF78fJ-p9;WsXDcLwBvOkZ+fpGU
z4oMusXggcw!}E)>iwhEyQx(*~o66O#6pR%Lit@8klS?#;H6d2;Lia9$x4l6v$0kOc
zX&jz;Y554x3Av<}rRL-pq!uXz6y>LsCYKa*g=H3(Cgy-P4a*{!AnEj?#N6D}BK2Yg
z_tMOiR57R2bjV(Jg~<F;umK<ylJG6Gi3-6bi6xoI3O<=hMTtd~>@KM#iJ3XYw&2~l
z3c;x*p#6Hq3ht?SsYQt;sVNHK8L4?7!xX?~q$(sTV7fpms5DPEBr`V^W~@R`YFcVh
zYF=`xtYc0=Mq*Mb$WFJ?Jn(L7ge<qKLP<tZerbA!f*WJ7g0ntoTeMGNUV3R_dMbDa
zGgtuZ*38smk>HZVyp+VE6i`UO?BcXZ&IfJHudowBa#=8V7k)8!u#2|>l+6!f`}?@U
z_$mQ8i6v?IMY%c(!7ko9VC!65ycJyXlS{$-Y(cxYd0>h_YUEuKOA?b3iy=<)O)V}?
zOb2aD4o)p9%S=u!)<o>@4i5BD00~245fllKXbQ>C&&kd#kqOU8EKx63@JlUM$jnnf
zQf;PZsuqw~RH9(4prC-HDlNZA!7(K_GcU8aq$sf@zo=LYq{}t0WOV=c=>G5Y(e<Cu
zJ^rKPzoX;7pk~A<9u0xf5Eu=C(GVC7fzc2cdLb}6{yX&IY}Cc0AwaDVh&&8A(^nie
z)~2fvo|$KCqyRmrj2kKrIbo55!8rgjNQX;3E^+V}Z3D>FAl55Z(0DC~^&89riHkyQ
zQh>R@B{iuu9i)a4uRb;ok>FsbAO=PTZU*O&#G>@n63>#<TwD&pZ52ocY8Z1$Y5^mI
z2!pdrYC&pVN@`wmrE`8>Nn&PRY7tZkD~E`SS2)oMA<7}-==k60_}}RHkFbLsN6&wR
z9SKR%>4WfvxufSlf{w_<aa1buahudWfpc{IC#VJ;#iJoG8UmvsFd71*Aut*OgFXaC
z$NvU>6pcD?Gz4fC0<iHvF~~(K@WD6e@E;dM7=82)hiV+cpfNmbBYq+f!{K(q2mFu~
z!+Z`Mc0(WL!(k;z7gPsXLv*9#f1~UFM%Vw1-v2Us|I6qNJjC9>GdlhUs&z;4Xb6mk
zz-S1JhQMeDjE2CV4}sC~zd;{GqYfMm0h)yXZ2V6GzSkGF{0=$-$ODr=9|Odx1E&P8
zaX>Mc75GO2K}!Zf;Q$@iLmvsmX)Q<(4l6)XP~(UmCL~%RWU(KF42Mt<a&-OQ==#6W
z^?#%5|3G&=BQHoBUH><vZ{Qvs{{vO0qj)p~MnhmU1V%$(Gz3ONV9<xa==k5DkD^fr
zj)nluLI8IDBDofDk#YW^7sxW``Gd|3ISh#m#SFy^VGNlJsSM=|3JfHkKS}cWiy=t%
zyD+3OBr%jSq%)*5q%stNWJtn7WcWW0WCPUyE)4k$$qc0oxeTccc?=~C#UMEnum}Sa
zBNqb$0~-SaI2?%4ngLP-wI4SA%M3pSl7WGNkqxpk6Qqs<HaH97Amji485r{NK<DzI
zjTqw`h#ejO9UcE2J^vAMw(02j@96mN==iUKesO71ab<ByYOYmseqQnD_-}rZf{&lK
zp`nGLl|pi2US58QLViJNo<e3`L1_v2AY=ulg2Dp5oXjL8F4v->{33<aiqzy%(0RfN
zIhlFcpv~`kTwGjS(Bo7<d<9(vLxoh3VvS-=9R&l0^28!g&8<<a32Hka*XpC}(GVC7
zfzc2c4S~@R7!85p9|EJ}zr#O{M}0UN0=Pnek%5(g89a6fK0nbpr`RngB{(NP33e$A
zNF!qd(tsdi1ImzKUOIf$CUnK<==dLGm=Bp8UH>_H|4Wb^OL1XQ$>{iBPG*uqddled
z-{|<?==h(Hr=Pcil|ou#Nn#FUh;DTJ57gus#iJoG8UmvsFd71*Aut*Ov<rdJ@ju#y
z?WoD4Au!lOfD1hO2XdtZ0|Nsq1ET{c=%$mR{2X0pkSJ)=H3tKu120U}sVFru8z#fV
zz|bHHx~;dQvLIE#H?ue~Co??{bgM5&9|*HDFdPtYOioTME>;N3%+E;#-S!KT0AV%;
zh6B8wc?tobYly*%89<^SEY84ifYUEu!8bKGzo-%<0>ZKk3<rcgb8=GC6LS<i^NLG~
zO2IcBgXBP1m4V@agkOGMa(-S(W?pGxQckLZYejNu0kWlPU_<iC5_2+B6kIZk3-XII
zk>z_B7!HU!78NB{Dmdkr=A{&ajYv&NO#xW}!o3U(2gKZR@)JuGTvGG$i*gfl6#NTP
zixTtTO8OWW4v0XNWR_*7q$(s;Dnz9g<%9Hta6dwUXI^SWVseQ>P-<~$P6<d7geNdC
z91w??;0bjs*bZc;PGn#>zz0#|UzS>wmXlu&(h9<p7#I!+LZpIA5|gtPoHJ6Bvq3T-
zJeh&v06#=FG%p2J=M<3dJo8FY(^HEST(CNRDkxH6O3-bd2GSo;lv$RUlbW8If-Ro@
zg4_*p7P@XzMur2tE<QdAe)%N|ZlLf7xfg_;7#R*of@D1NGD|WOb26*IX-UB?F*64d
zH_64h55y7oLxb+M#z+C6)XM@|GaH^*lAK}4z`zD(7{M6EFop>O!%GGRhTjYz`$zA8
z9=-p0^!{h#(fgmlE9xAaNAG_Im7}A0Gz3ONU^E0qLtr!nMnhoeg}~_e-_VP*Q5TPf
z0JTDZ4Lr7y&%nSiI{pW_343(>kKuqAY;bRM{BLyp&(G2{CdAb@AZB#@Z*=@`bo>vz
v!&YH*{Eu2KkWq6+Ltr!nMnhmU1V%$(Gz91!0;A)9^bYY+`$j`x@Pq&W&pl1}
literal 0
HcmV?d00001
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/Makefile b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/Makefile
new file mode 100644
index 00000000..89b45db8
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/Makefile
@@ -0,0 +1,33 @@
+# Must set these gl and glut locations to build 'falling'
+
+GL_INCPATH = -I/usr/local/include/
+GL_LIBPATH = -L/usr/local/lib/ -L/usr/X11R6/lib/
+GL_LIBS = -lglut -lGLU -lGL -lXext -lXmu -lXi -lX11
+
+.SUFFIXES: .cpp
+
+CC = g++
+CFLAGS = -O2 -I. -I../../include $(GL_INCPATH)
+LDFLAGS = -L. -L../../lib $(GL_LIBPATH)
+LDLIBS = -lPQP -lm $(GL_LIBS)
+
+SRCS = main.cpp model.cpp
+
+OBJECTS = main.o model.o
+
+TARGET = falling
+
+CLEAN = $(OBJECTS) $(TARGET)
+
+.cpp.o:
+ $(CC) ${CFLAGS} -c $<
+
+$(TARGET): $(OBJECTS)
+ $(CC) $(CFLAGS) -o $(TARGET) $(OBJECTS) -L. $(LDFLAGS) $(LDLIBS)
+
+run: $(TARGET)
+ $(TARGET)
+
+clean:
+ /bin/rm -f $(CLEAN)
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/MatVec.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/MatVec.h
new file mode 100644
index 00000000..3d90522f
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/MatVec.h
@@ -0,0 +1,881 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_MATVEC_H
+#define PQP_MATVEC_H
+
+#include <math.h>
+#include <stdio.h>
+#include "PQP_Compile.h"
+
+#ifndef M_PI
+const double M_PI = 3.14159265359;
+#endif
+
+#ifdef gnu
+#include "zzzz.h"
+
+#ifdef hppa
+#define myfabs(x) \
+ ({double __value, __arg = (x); \
+ asm("fabs,dbl %1, %0": "=f" (__value): "f" (__arg)); \
+ __value; \
+});
+#endif
+
+#ifdef mips
+#define myfabs(x) \
+ ({double __value, __arg = (x); \
+ asm("abs.d %0, %1": "=f" (__value): "f" (__arg)); \
+ __value; \
+});
+#endif
+
+#else
+
+#define myfabs(x) ((x < 0) ? -x : x)
+
+#endif
+
+
+inline
+void
+Mprintg(const PQP_REAL M[3][3])
+{
+ printf("%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+
+inline
+void
+Mfprint(FILE *f, const PQP_REAL M[3][3])
+{
+ fprintf(f, "%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+inline
+void
+Mprint(const PQP_REAL M[3][3])
+{
+ printf("%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+inline
+void
+Vprintg(const PQP_REAL V[3])
+{
+ printf("%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Vfprint(FILE *f, const PQP_REAL V[3])
+{
+ fprintf(f, "%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Vprint(const PQP_REAL V[3])
+{
+ printf("%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Midentity(PQP_REAL M[3][3])
+{
+ M[0][0] = M[1][1] = M[2][2] = 1.0;
+ M[0][1] = M[1][2] = M[2][0] = 0.0;
+ M[0][2] = M[1][0] = M[2][1] = 0.0;
+}
+
+inline
+void
+Videntity(PQP_REAL T[3])
+{
+ T[0] = T[1] = T[2] = 0.0;
+}
+
+inline
+void
+McM(PQP_REAL Mr[3][3], const PQP_REAL M[3][3])
+{
+ Mr[0][0] = M[0][0]; Mr[0][1] = M[0][1]; Mr[0][2] = M[0][2];
+ Mr[1][0] = M[1][0]; Mr[1][1] = M[1][1]; Mr[1][2] = M[1][2];
+ Mr[2][0] = M[2][0]; Mr[2][1] = M[2][1]; Mr[2][2] = M[2][2];
+}
+
+inline
+void
+MTcM(PQP_REAL Mr[3][3], const PQP_REAL M[3][3])
+{
+ Mr[0][0] = M[0][0]; Mr[1][0] = M[0][1]; Mr[2][0] = M[0][2];
+ Mr[0][1] = M[1][0]; Mr[1][1] = M[1][1]; Mr[2][1] = M[1][2];
+ Mr[0][2] = M[2][0]; Mr[1][2] = M[2][1]; Mr[2][2] = M[2][2];
+}
+
+inline
+void
+VcV(PQP_REAL Vr[3], const PQP_REAL V[3])
+{
+ Vr[0] = V[0]; Vr[1] = V[1]; Vr[2] = V[2];
+}
+
+inline
+void
+McolcV(PQP_REAL Vr[3], const PQP_REAL M[3][3], int c)
+{
+ Vr[0] = M[0][c];
+ Vr[1] = M[1][c];
+ Vr[2] = M[2][c];
+}
+
+inline
+void
+McolcMcol(PQP_REAL Mr[3][3], int cr, const PQP_REAL M[3][3], int c)
+{
+ Mr[0][cr] = M[0][c];
+ Mr[1][cr] = M[1][c];
+ Mr[2][cr] = M[2][c];
+}
+
+inline
+void
+MxMpV(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3], const PQP_REAL T[3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[1][0] +
+ M1[0][2] * M2[2][0] +
+ T[0]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[1][2] * M2[2][0] +
+ T[1]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[1][0] +
+ M1[2][2] * M2[2][0] +
+ T[2]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[2][1] +
+ T[0]);
+ Mr[1][1] = (M1[1][0] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[2][1] +
+ T[1]);
+ Mr[2][1] = (M1[2][0] * M2[0][1] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[2][1] +
+ T[2]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[0][1] * M2[1][2] +
+ M1[0][2] * M2[2][2] +
+ T[0]);
+ Mr[1][2] = (M1[1][0] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[1][2] * M2[2][2] +
+ T[1]);
+ Mr[2][2] = (M1[2][0] * M2[0][2] +
+ M1[2][1] * M2[1][2] +
+ M1[2][2] * M2[2][2] +
+ T[2]);
+}
+
+inline
+void
+MxM(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[1][0] +
+ M1[0][2] * M2[2][0]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[1][2] * M2[2][0]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[1][0] +
+ M1[2][2] * M2[2][0]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[2][1]);
+ Mr[1][1] = (M1[1][0] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[2][1]);
+ Mr[2][1] = (M1[2][0] * M2[0][1] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[2][1]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[0][1] * M2[1][2] +
+ M1[0][2] * M2[2][2]);
+ Mr[1][2] = (M1[1][0] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[1][2] * M2[2][2]);
+ Mr[2][2] = (M1[2][0] * M2[0][2] +
+ M1[2][1] * M2[1][2] +
+ M1[2][2] * M2[2][2]);
+}
+
+
+inline
+void
+MxMT(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[0][1] +
+ M1[0][2] * M2[0][2]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[0][1] +
+ M1[1][2] * M2[0][2]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[0][1] +
+ M1[2][2] * M2[0][2]);
+ Mr[0][1] = (M1[0][0] * M2[1][0] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[1][2]);
+ Mr[1][1] = (M1[1][0] * M2[1][0] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[1][2]);
+ Mr[2][1] = (M1[2][0] * M2[1][0] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[1][2]);
+ Mr[0][2] = (M1[0][0] * M2[2][0] +
+ M1[0][1] * M2[2][1] +
+ M1[0][2] * M2[2][2]);
+ Mr[1][2] = (M1[1][0] * M2[2][0] +
+ M1[1][1] * M2[2][1] +
+ M1[1][2] * M2[2][2]);
+ Mr[2][2] = (M1[2][0] * M2[2][0] +
+ M1[2][1] * M2[2][1] +
+ M1[2][2] * M2[2][2]);
+}
+
+inline
+void
+MTxM(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[1][0] * M2[1][0] +
+ M1[2][0] * M2[2][0]);
+ Mr[1][0] = (M1[0][1] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[2][1] * M2[2][0]);
+ Mr[2][0] = (M1[0][2] * M2[0][0] +
+ M1[1][2] * M2[1][0] +
+ M1[2][2] * M2[2][0]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[1][0] * M2[1][1] +
+ M1[2][0] * M2[2][1]);
+ Mr[1][1] = (M1[0][1] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[2][1] * M2[2][1]);
+ Mr[2][1] = (M1[0][2] * M2[0][1] +
+ M1[1][2] * M2[1][1] +
+ M1[2][2] * M2[2][1]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[1][0] * M2[1][2] +
+ M1[2][0] * M2[2][2]);
+ Mr[1][2] = (M1[0][1] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[2][1] * M2[2][2]);
+ Mr[2][2] = (M1[0][2] * M2[0][2] +
+ M1[1][2] * M2[1][2] +
+ M1[2][2] * M2[2][2]);
+}
+
+inline
+void
+MxV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]);
+ Vr[1] = (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]);
+ Vr[2] = (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+
+inline
+void
+MxVpV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2] +
+ V2[0]);
+ Vr[1] = (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2] +
+ V2[1]);
+ Vr[2] = (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2] +
+ V2[2]);
+}
+
+
+inline
+void
+sMxVpV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = s1 * (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]) +
+ V2[0];
+ Vr[1] = s1 * (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]) +
+ V2[1];
+ Vr[2] = s1 * (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]) +
+ V2[2];
+}
+
+inline
+void
+MTxV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[1][0] * V1[1] +
+ M1[2][0] * V1[2]);
+ Vr[1] = (M1[0][1] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[2][1] * V1[2]);
+ Vr[2] = (M1[0][2] * V1[0] +
+ M1[1][2] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+inline
+void
+sMTxV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = s1*(M1[0][0] * V1[0] +
+ M1[1][0] * V1[1] +
+ M1[2][0] * V1[2]);
+ Vr[1] = s1*(M1[0][1] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[2][1] * V1[2]);
+ Vr[2] = s1*(M1[0][2] * V1[0] +
+ M1[1][2] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+inline
+void
+sMxV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = s1*(M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]);
+ Vr[1] = s1*(M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]);
+ Vr[2] = s1*(M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+
+inline
+void
+VmV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[0] - V2[0];
+ Vr[1] = V1[1] - V2[1];
+ Vr[2] = V1[2] - V2[2];
+}
+
+inline
+void
+VpV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[0] + V2[0];
+ Vr[1] = V1[1] + V2[1];
+ Vr[2] = V1[2] + V2[2];
+}
+
+inline
+void
+VpVxS(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3], PQP_REAL s)
+{
+ Vr[0] = V1[0] + V2[0] * s;
+ Vr[1] = V1[1] + V2[1] * s;
+ Vr[2] = V1[2] + V2[2] * s;
+}
+
+inline
+void
+MskewV(PQP_REAL M[3][3], const PQP_REAL v[3])
+{
+ M[0][0] = M[1][1] = M[2][2] = 0.0;
+ M[1][0] = v[2];
+ M[0][1] = -v[2];
+ M[0][2] = v[1];
+ M[2][0] = -v[1];
+ M[1][2] = -v[0];
+ M[2][1] = v[0];
+}
+
+
+inline
+void
+VcrossV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[1]*V2[2] - V1[2]*V2[1];
+ Vr[1] = V1[2]*V2[0] - V1[0]*V2[2];
+ Vr[2] = V1[0]*V2[1] - V1[1]*V2[0];
+}
+
+
+inline
+PQP_REAL
+Vlength(PQP_REAL V[3])
+{
+ return sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+}
+
+inline
+void
+Vnormalize(PQP_REAL V[3])
+{
+ PQP_REAL d = (PQP_REAL)1.0 / sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+ V[0] *= d;
+ V[1] *= d;
+ V[2] *= d;
+}
+
+
+inline
+PQP_REAL
+VdotV(const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ return (V1[0]*V2[0] + V1[1]*V2[1] + V1[2]*V2[2]);
+}
+
+
+inline
+PQP_REAL
+VdistV2(const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ return ( (V1[0]-V2[0]) * (V1[0]-V2[0]) +
+ (V1[1]-V2[1]) * (V1[1]-V2[1]) +
+ (V1[2]-V2[2]) * (V1[2]-V2[2]));
+}
+
+inline
+void
+VxS(PQP_REAL Vr[3], const PQP_REAL V[3], PQP_REAL s)
+{
+ Vr[0] = V[0] * s;
+ Vr[1] = V[1] * s;
+ Vr[2] = V[2] * s;
+}
+
+inline
+void
+MRotZ(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[0][0] = cos(t);
+ Mr[1][0] = sin(t);
+ Mr[0][1] = -Mr[1][0];
+ Mr[1][1] = Mr[0][0];
+ Mr[2][0] = Mr[2][1] = 0.0;
+ Mr[0][2] = Mr[1][2] = 0.0;
+ Mr[2][2] = 1.0;
+}
+
+
+inline
+void
+MRotX(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[1][1] = cos(t);
+ Mr[2][1] = sin(t);
+ Mr[1][2] = -Mr[2][1];
+ Mr[2][2] = Mr[1][1];
+ Mr[0][1] = Mr[0][2] = 0.0;
+ Mr[1][0] = Mr[2][0] = 0.0;
+ Mr[0][0] = 1.0;
+}
+
+inline
+void
+MRotY(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[2][2] = cos(t);
+ Mr[0][2] = sin(t);
+ Mr[2][0] = -Mr[0][2];
+ Mr[0][0] = Mr[2][2];
+ Mr[1][2] = Mr[1][0] = 0.0;
+ Mr[2][1] = Mr[0][1] = 0.0;
+ Mr[1][1] = 1.0;
+}
+
+inline
+void
+MVtoOGL(double oglm[16], const PQP_REAL R[3][3], const PQP_REAL T[3])
+{
+ oglm[0] = (double)R[0][0];
+ oglm[1] = (double)R[1][0];
+ oglm[2] = (double)R[2][0];
+ oglm[3] = 0.0;
+ oglm[4] = (double)R[0][1];
+ oglm[5] = (double)R[1][1];
+ oglm[6] = (double)R[2][1];
+ oglm[7] = 0.0;
+ oglm[8] = (double)R[0][2];
+ oglm[9] = (double)R[1][2];
+ oglm[10] = (double)R[2][2];
+ oglm[11] = 0.0;
+ oglm[12] = (double)T[0];
+ oglm[13] = (double)T[1];
+ oglm[14] = (double)T[2];
+ oglm[15] = 1.0;
+}
+
+inline
+void
+OGLtoMV(PQP_REAL R[3][3], PQP_REAL T[3], const double oglm[16])
+{
+ R[0][0] = (PQP_REAL)oglm[0];
+ R[1][0] = (PQP_REAL)oglm[1];
+ R[2][0] = (PQP_REAL)oglm[2];
+
+ R[0][1] = (PQP_REAL)oglm[4];
+ R[1][1] = (PQP_REAL)oglm[5];
+ R[2][1] = (PQP_REAL)oglm[6];
+
+ R[0][2] = (PQP_REAL)oglm[8];
+ R[1][2] = (PQP_REAL)oglm[9];
+ R[2][2] = (PQP_REAL)oglm[10];
+
+ T[0] = (PQP_REAL)oglm[12];
+ T[1] = (PQP_REAL)oglm[13];
+ T[2] = (PQP_REAL)oglm[14];
+}
+
+// taken from quatlib, written by Richard Holloway
+const int QX = 0;
+const int QY = 1;
+const int QZ = 2;
+const int QW = 3;
+
+inline
+void
+MRotQ(PQP_REAL destMatrix[3][3], PQP_REAL srcQuat[4])
+{
+ PQP_REAL s;
+ PQP_REAL xs, ys, zs,
+ wx, wy, wz,
+ xx, xy, xz,
+ yy, yz, zz;
+
+ /*
+ * For unit srcQuat, just set s = 2.0; or set xs = srcQuat[QX] +
+ * srcQuat[QX], etc.
+ */
+
+ s = (PQP_REAL)2.0 / (srcQuat[QX]*srcQuat[QX] + srcQuat[QY]*srcQuat[QY] +
+ srcQuat[QZ]*srcQuat[QZ] + srcQuat[QW]*srcQuat[QW]);
+
+ xs = srcQuat[QX] * s; ys = srcQuat[QY] * s; zs = srcQuat[QZ] * s;
+ wx = srcQuat[QW] * xs; wy = srcQuat[QW] * ys; wz = srcQuat[QW] * zs;
+ xx = srcQuat[QX] * xs; xy = srcQuat[QX] * ys; xz = srcQuat[QX] * zs;
+ yy = srcQuat[QY] * ys; yz = srcQuat[QY] * zs; zz = srcQuat[QZ] * zs;
+
+ destMatrix[QX][QX] = (PQP_REAL)1.0 - (yy + zz);
+ destMatrix[QX][QY] = xy + wz;
+ destMatrix[QX][QZ] = xz - wy;
+
+ destMatrix[QY][QX] = xy - wz;
+ destMatrix[QY][QY] = (PQP_REAL)1.0 - (xx + zz);
+ destMatrix[QY][QZ] = yz + wx;
+
+ destMatrix[QZ][QX] = xz + wy;
+ destMatrix[QZ][QY] = yz - wx;
+ destMatrix[QZ][QZ] = (PQP_REAL)1.0 - (xx + yy);
+}
+
+inline
+void
+Mqinverse(PQP_REAL Mr[3][3], PQP_REAL m[3][3])
+{
+ int i,j;
+
+ for(i=0; i<3; i++)
+ for(j=0; j<3; j++)
+ {
+ int i1 = (i+1)%3;
+ int i2 = (i+2)%3;
+ int j1 = (j+1)%3;
+ int j2 = (j+2)%3;
+ Mr[i][j] = (m[j1][i1]*m[j2][i2] - m[j1][i2]*m[j2][i1]);
+ }
+}
+
+// Meigen from Numerical Recipes in C
+
+#if 0
+
+#define rfabs(x) ((x < 0) ? -x : x)
+
+#define ROT(a,i,j,k,l) g=a[i][j]; h=a[k][l]; a[i][j]=g-s*(h+g*tau); a[k][l]=h+s*(g-h*tau);
+
+int
+inline
+Meigen(PQP_REAL vout[3][3], PQP_REAL dout[3], PQP_REAL a[3][3])
+{
+ int i;
+ PQP_REAL tresh,theta,tau,t,sm,s,h,g,c;
+ int nrot;
+ PQP_REAL b[3];
+ PQP_REAL z[3];
+ PQP_REAL v[3][3];
+ PQP_REAL d[3];
+
+ v[0][0] = v[1][1] = v[2][2] = 1.0;
+ v[0][1] = v[1][2] = v[2][0] = 0.0;
+ v[0][2] = v[1][0] = v[2][1] = 0.0;
+
+ b[0] = a[0][0]; d[0] = a[0][0]; z[0] = 0.0;
+ b[1] = a[1][1]; d[1] = a[1][1]; z[1] = 0.0;
+ b[2] = a[2][2]; d[2] = a[2][2]; z[2] = 0.0;
+
+ nrot = 0;
+
+
+ for(i=0; i<50; i++)
+ {
+
+ printf("2\n");
+
+ sm=0.0; sm+=fabs(a[0][1]); sm+=fabs(a[0][2]); sm+=fabs(a[1][2]);
+ if (sm == 0.0) { McM(vout,v); VcV(dout,d); return i; }
+
+ if (i < 3) tresh=0.2*sm/(3*3); else tresh=0.0;
+
+ {
+ g = 100.0*rfabs(a[0][1]);
+ if (i>3 && rfabs(d[0])+g==rfabs(d[0]) && rfabs(d[1])+g==rfabs(d[1]))
+ a[0][1]=0.0;
+ else if (rfabs(a[0][1])>tresh)
+ {
+ h = d[1]-d[0];
+ if (rfabs(h)+g == rfabs(h)) t=(a[0][1])/h;
+ else
+ {
+ theta=0.5*h/(a[0][1]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[0][1];
+ z[0] -= h; z[1] += h; d[0] -= h; d[1] += h;
+ a[0][1]=0.0;
+ ROT(a,0,2,1,2); ROT(v,0,0,0,1); ROT(v,1,0,1,1); ROT(v,2,0,2,1);
+ nrot++;
+ }
+ }
+
+ {
+ g = 100.0*rfabs(a[0][2]);
+ if (i>3 && rfabs(d[0])+g==rfabs(d[0]) && rfabs(d[2])+g==rfabs(d[2]))
+ a[0][2]=0.0;
+ else if (rfabs(a[0][2])>tresh)
+ {
+ h = d[2]-d[0];
+ if (rfabs(h)+g == rfabs(h)) t=(a[0][2])/h;
+ else
+ {
+ theta=0.5*h/(a[0][2]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[0][2];
+ z[0] -= h; z[2] += h; d[0] -= h; d[2] += h;
+ a[0][2]=0.0;
+ ROT(a,0,1,1,2); ROT(v,0,0,0,2); ROT(v,1,0,1,2); ROT(v,2,0,2,2);
+ nrot++;
+ }
+ }
+
+
+ {
+ g = 100.0*rfabs(a[1][2]);
+ if (i>3 && rfabs(d[1])+g==rfabs(d[1]) && rfabs(d[2])+g==rfabs(d[2]))
+ a[1][2]=0.0;
+ else if (rfabs(a[1][2])>tresh)
+ {
+ h = d[2]-d[1];
+ if (rfabs(h)+g == rfabs(h)) t=(a[1][2])/h;
+ else
+ {
+ theta=0.5*h/(a[1][2]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[1][2];
+ z[1] -= h; z[2] += h; d[1] -= h; d[2] += h;
+ a[1][2]=0.0;
+ ROT(a,0,1,0,2); ROT(v,0,1,0,2); ROT(v,1,1,1,2); ROT(v,2,1,2,2);
+ nrot++;
+ }
+ }
+
+ b[0] += z[0]; d[0] = b[0]; z[0] = 0.0;
+ b[1] += z[1]; d[1] = b[1]; z[1] = 0.0;
+ b[2] += z[2]; d[2] = b[2]; z[2] = 0.0;
+
+ }
+
+ fprintf(stderr, "eigen: too many iterations in Jacobi transform (%d).\n", i);
+
+ return i;
+}
+
+#else
+
+
+
+#define ROTATE(a,i,j,k,l) g=a[i][j]; h=a[k][l]; a[i][j]=g-s*(h+g*tau); a[k][l]=h+s*(g-h*tau);
+
+void
+inline
+Meigen(PQP_REAL vout[3][3], PQP_REAL dout[3], PQP_REAL a[3][3])
+{
+ int n = 3;
+ int j,iq,ip,i;
+ PQP_REAL tresh,theta,tau,t,sm,s,h,g,c;
+ int nrot;
+ PQP_REAL b[3];
+ PQP_REAL z[3];
+ PQP_REAL v[3][3];
+ PQP_REAL d[3];
+
+ Midentity(v);
+ for(ip=0; ip<n; ip++)
+ {
+ b[ip] = a[ip][ip];
+ d[ip] = a[ip][ip];
+ z[ip] = 0.0;
+ }
+
+ nrot = 0;
+
+ for(i=0; i<50; i++)
+ {
+
+ sm=0.0;
+ for(ip=0;ip<n;ip++) for(iq=ip+1;iq<n;iq++) sm+=fabs(a[ip][iq]);
+ if (sm == 0.0)
+ {
+ McM(vout, v);
+ VcV(dout, d);
+ return;
+ }
+
+
+ if (i < 3) tresh=(PQP_REAL)0.2*sm/(n*n);
+ else tresh=0.0;
+
+ for(ip=0; ip<n; ip++) for(iq=ip+1; iq<n; iq++)
+ {
+ g = (PQP_REAL)100.0*fabs(a[ip][iq]);
+ if (i>3 &&
+ fabs(d[ip])+g==fabs(d[ip]) &&
+ fabs(d[iq])+g==fabs(d[iq]))
+ a[ip][iq]=0.0;
+ else if (fabs(a[ip][iq])>tresh)
+ {
+ h = d[iq]-d[ip];
+ if (fabs(h)+g == fabs(h)) t=(a[ip][iq])/h;
+ else
+ {
+ theta=(PQP_REAL)0.5*h/(a[ip][iq]);
+ t=(PQP_REAL)(1.0/(fabs(theta)+sqrt(1.0+theta*theta)));
+ if (theta < 0.0) t = -t;
+ }
+ c=(PQP_REAL)1.0/sqrt(1+t*t);
+ s=t*c;
+ tau=s/((PQP_REAL)1.0+c);
+ h=t*a[ip][iq];
+ z[ip] -= h;
+ z[iq] += h;
+ d[ip] -= h;
+ d[iq] += h;
+ a[ip][iq]=0.0;
+ for(j=0;j<ip;j++) { ROTATE(a,j,ip,j,iq); }
+ for(j=ip+1;j<iq;j++) { ROTATE(a,ip,j,j,iq); }
+ for(j=iq+1;j<n;j++) { ROTATE(a,ip,j,iq,j); }
+ for(j=0;j<n;j++) { ROTATE(v,j,ip,j,iq); }
+ nrot++;
+ }
+ }
+ for(ip=0;ip<n;ip++)
+ {
+ b[ip] += z[ip];
+ d[ip] = b[ip];
+ z[ip] = 0.0;
+ }
+ }
+
+ fprintf(stderr, "eigen: too many iterations in Jacobi transform.\n");
+
+ return;
+}
+
+
+#endif
+
+#endif
+/* MATVEC_H */
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.dsp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.dsp
new file mode 100644
index 00000000..f7108cdd
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.dsp
@@ -0,0 +1,95 @@
+# Microsoft Developer Studio Project File - Name="falling" - Package Owner=<4>
+# Microsoft Developer Studio Generated Build File, Format Version 5.00
+# ** DO NOT EDIT **
+
+# TARGTYPE "Win32 (x86) Console Application" 0x0103
+
+CFG=falling - Win32 Debug
+!MESSAGE This is not a valid makefile. To build this project using NMAKE,
+!MESSAGE use the Export Makefile command and run
+!MESSAGE
+!MESSAGE NMAKE /f "falling.mak".
+!MESSAGE
+!MESSAGE You can specify a configuration when running NMAKE
+!MESSAGE by defining the macro CFG on the command line. For example:
+!MESSAGE
+!MESSAGE NMAKE /f "falling.mak" CFG="falling - Win32 Debug"
+!MESSAGE
+!MESSAGE Possible choices for configuration are:
+!MESSAGE
+!MESSAGE "falling - Win32 Release" (based on "Win32 (x86) Console Application")
+!MESSAGE "falling - Win32 Debug" (based on "Win32 (x86) Console Application")
+!MESSAGE
+
+# Begin Project
+# PROP Scc_ProjName ""
+# PROP Scc_LocalPath ""
+CPP=xicl5.exe
+RSC=rc.exe
+
+!IF "$(CFG)" == "falling - Win32 Release"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 0
+# PROP BASE Output_Dir "Release"
+# PROP BASE Intermediate_Dir "Release"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 0
+# PROP Output_Dir "./"
+# PROP Intermediate_Dir "Release"
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /GX /O2 /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "NDEBUG"
+# ADD RSC /l 0x409 /d "NDEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=xilink5.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /machine:I386
+# ADD LINK32 glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /machine:I386 /libpath:"..\..\lib"
+
+!ELSEIF "$(CFG)" == "falling - Win32 Debug"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 1
+# PROP BASE Output_Dir "Debug"
+# PROP BASE Intermediate_Dir "Debug"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 1
+# PROP Output_Dir "./"
+# PROP Intermediate_Dir "Debug"
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /Gm /GX /Zi /Od /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /Gm /GX /Zi /Od /I "..\..\include" /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "_DEBUG"
+# ADD RSC /l 0x409 /d "_DEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=xilink5.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept
+# ADD LINK32 glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept /libpath:"..\..\lib"
+
+!ENDIF
+
+# Begin Target
+
+# Name "falling - Win32 Release"
+# Name "falling - Win32 Debug"
+# Begin Source File
+
+SOURCE=.\main.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\model.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\model.h
+# End Source File
+# End Target
+# End Project
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.plg b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.plg
new file mode 100644
index 00000000..b133bcb0
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/falling.plg
@@ -0,0 +1,21 @@
+--------------------Configuration: falling - Win32 Release--------------------
+Begining build with project "C:\WIN95\DESKTOP\PQP_v1.2.1\demos\falling\falling.dsp", at root.
+Active configuration is Win32 (x86) Console Application (based on Win32 (x86) Console Application)
+
+Project's tools are:
+ "32-bit C/C++ Compiler for 80x86" with flags "/nologo /ML /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /Fp"Release/falling.pch" /YX /Fo"Release/" /Fd"Release/" /FD /c "
+ "Win32 Resource Compiler" with flags "/l 0x409 /d "NDEBUG" "
+ "Browser Database Maker" with flags "/nologo /o"./falling.bsc" "
+ "COFF Linker for 80x86" with flags "glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /incremental:no /pdb:"./falling.pdb" /machine:I386 /out:"./falling.exe" /libpath:"..\..\lib" "
+ "Custom Build" with flags ""
+ "<Component 0xa>" with flags ""
+
+Creating temp file "C:\WIN95\TEMP\RSP4360.TMP" with contents <glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /incremental:no /pdb:"./falling.pdb" /machine:I386 /out:"./falling.exe" /libpath:"..\..\lib"
+.\Release\main.obj
+.\Release\model.obj>
+Creating command line "link.exe @C:\WIN95\TEMP\RSP4360.TMP"
+Linking...
+
+
+
+falling.exe - 0 error(s), 0 warning(s)
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/main.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/main.cpp
new file mode 100644
index 00000000..ee0ea92e
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/main.cpp
@@ -0,0 +1,537 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include <GL/glut.h>
+#include "model.h"
+#include "PQP.h"
+#include "MatVec.h"
+
+PQP_Model *torus1_tested,*torus2_tested;
+Model *torus1_drawn, *torus2_drawn;
+
+int mode;
+double beginx, beginy;
+double dis = 10.0, azim = 0.0, elev = 0.0;
+double ddis = 0.0, dazim = 0.0, delev = 0.0;
+
+int animating = 1;
+int step = 0;
+int number_of_steps;
+int query_type = 0;
+double tolerance = .05;
+
+PQP_REAL (*R1)[3][3];
+PQP_REAL (*T1)[3];
+PQP_REAL (*R2)[3][3];
+PQP_REAL (*T2)[3];
+
+void
+init_viewer_window()
+{
+ GLfloat Ambient[] = { 0.2f, 0.2f, 0.2f, 1.0f };
+ GLfloat Diffuse[] = { 0.8f, 0.8f, 0.8f, 1.0f };
+ GLfloat Specular[] = { 0.1f, 0.1f, 0.1f, 1.0f };
+ GLfloat SpecularExp[] = { 50 };
+ GLfloat Emission[] = { 0.1f, 0.1f, 0.1f, 1.0f };
+
+ glMaterialfv(GL_FRONT, GL_AMBIENT, Ambient);
+ glMaterialfv(GL_FRONT, GL_DIFFUSE, Diffuse);
+ glMaterialfv(GL_FRONT, GL_SPECULAR, Specular);
+ glMaterialfv(GL_FRONT, GL_SHININESS, SpecularExp);
+ glMaterialfv(GL_FRONT, GL_EMISSION, Emission);
+
+ glMaterialfv(GL_BACK, GL_AMBIENT, Ambient);
+ glMaterialfv(GL_BACK, GL_DIFFUSE, Diffuse);
+ glMaterialfv(GL_BACK, GL_SPECULAR, Specular);
+ glMaterialfv(GL_BACK, GL_SHININESS, SpecularExp);
+ glMaterialfv(GL_BACK, GL_EMISSION, Emission);
+
+ glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE);
+
+ glEnable(GL_COLOR_MATERIAL);
+
+ GLfloat light_position[] = { 1.0, 1.0, 1.0, 0.0 };
+ glLightfv(GL_LIGHT0, GL_POSITION, light_position);
+ glEnable(GL_LIGHT0);
+ glEnable(GL_LIGHTING);
+ glLightModeli(GL_LIGHT_MODEL_TWO_SIDE, GL_TRUE);
+
+ glDepthFunc(GL_LEQUAL);
+ glEnable(GL_DEPTH_TEST);
+ glEnable(GL_CULL_FACE);
+ glCullFace(GL_BACK);
+
+ glShadeModel(GL_FLAT);
+ glClearColor(0.0, 0.0, 0.0, 0.0);
+
+ glMatrixMode(GL_PROJECTION);
+ glLoadIdentity();
+ glFrustum(-0.004,0.004,-0.004,0.004,.01,100.0);
+
+ glMatrixMode(GL_MODELVIEW);
+}
+
+void
+cb_mouse(int _b, int _s, int _x, int _y)
+{
+ if (_s == GLUT_UP)
+ {
+ dis += ddis;
+ if (dis < .1) dis = .1;
+ azim += dazim;
+ elev += delev;
+ ddis = 0.0;
+ dazim = 0.0;
+ delev = 0.0;
+ return;
+ }
+
+ if (_b == GLUT_RIGHT_BUTTON)
+ {
+ mode = 0;
+ beginy = _y;
+ return;
+ }
+ else
+ {
+ mode = 1;
+ beginx = _x;
+ beginy = _y;
+ }
+}
+
+void
+cb_motion(int _x, int _y)
+{
+ if (mode == 0)
+ {
+ ddis = dis * (double)(_y - beginy)/200.0;
+ }
+ else
+ {
+ dazim = (_x - beginx)/5;
+ delev = (_y - beginy)/5;
+ }
+
+ glutPostRedisplay();
+}
+
+void cb_keyboard(unsigned char key, int x, int y)
+{
+ switch(key)
+ {
+ case 'q':
+ delete torus1_drawn;
+ delete torus2_drawn;
+ delete torus1_tested;
+ delete torus2_tested;
+ delete [] R1;
+ delete [] T1;
+ delete [] R2;
+ delete [] T2;
+ exit(0);
+ case '0': query_type = 0; break;
+ case '1': query_type = 1; break;
+ case '2': query_type = 2; break;
+ case '3': query_type = 3; break;
+ case '-':
+ tolerance -= .01;
+ if (tolerance < 0.0) tolerance = 0.0;
+ break;
+ case '=':
+ tolerance += .01;
+ break;
+ default: animating = 1 - animating;
+ }
+
+ glutPostRedisplay();
+}
+
+void cb_idle()
+{
+ if (animating)
+ {
+ step = (step + 1) % number_of_steps;
+ glutPostRedisplay();
+ }
+}
+
+void
+BeginDraw()
+{
+ glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
+
+ glLoadIdentity();
+ glTranslatef(0.0, 0.0, -(dis+ddis));
+ glRotated(elev+delev, 1.0, 0.0, 0.0);
+ glRotated(azim+dazim, 0.0, 1.0, 0.0);
+ glRotated(90.0,-1.0,0.0,0.0);
+}
+
+void
+EndDraw()
+{
+ glFlush();
+ glutSwapBuffers();
+}
+
+inline void glVertex3v(float V[3]) { glVertex3fv(V); }
+inline void glVertex3v(double V[3]) { glVertex3dv(V); }
+
+void
+cb_display()
+{
+ BeginDraw();
+
+ int i;
+ PQP_CollideResult cres;
+ PQP_DistanceResult dres;
+ PQP_ToleranceResult tres;
+ double oglm[16];
+
+ switch(query_type)
+ {
+ case 0:
+
+ // draw model 1
+
+ glColor3f(1,1,1); // setup color and transform
+ MVtoOGL(oglm,R1[step],T1[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus1_drawn->Draw(); // do gl rendering
+ glPopMatrix(); // restore transform
+
+ // draw model 2
+
+ MVtoOGL(oglm,R2[step],T2[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus2_drawn->Draw();
+ glPopMatrix();
+
+ break;
+
+ case 1:
+
+ // perform collision query
+
+ PQP_Collide(&cres,R1[step],T1[step],torus1_tested,
+ R2[step],T2[step],torus2_tested,
+ PQP_ALL_CONTACTS);
+
+ // draw model 1 and its overlapping tris
+
+ MVtoOGL(oglm,R1[step],T1[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ glColor3f(1,1,1);
+ torus1_drawn->Draw();
+ glColor3f(1,0,0);
+ for(i = 0; i < cres.NumPairs(); i++)
+ {
+ torus1_drawn->DrawTri(cres.Id1(i));
+ }
+ glPopMatrix();
+
+ // draw model 2 and its overlapping tris
+
+ MVtoOGL(oglm,R2[step],T2[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ glColor3f(1,1,1);
+ torus2_drawn->Draw();
+ glColor3f(1,0,0);
+ for(i = 0; i < cres.NumPairs(); i++)
+ {
+ torus2_drawn->DrawTri(cres.Id2(i));
+ }
+ glPopMatrix();
+
+ break;
+
+ case 2:
+
+ // perform distance query
+
+ PQP_Distance(&dres,R1[step],T1[step],torus1_tested,
+ R2[step],T2[step],torus2_tested,
+ 0.0,0.0);
+
+ // draw models
+
+ glColor3f(1,1,1);
+
+ MVtoOGL(oglm,R1[step],T1[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus1_drawn->Draw();
+ glPopMatrix();
+
+ MVtoOGL(oglm,R2[step],T2[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus2_drawn->Draw();
+ glPopMatrix();
+
+ // draw the closest points as small spheres
+
+ glColor3f(0,1,0);
+
+ PQP_REAL P1[3],P2[3],V1[3],V2[3];
+ VcV(P1,dres.P1());
+ VcV(P2,dres.P2());
+
+ // each point is in the space of its model;
+ // transform to world space
+
+ MxVpV(V1,R1[step],P1,T1[step]);
+
+ glPushMatrix();
+ glTranslated(V1[0],V1[1],V1[2]);
+ glutSolidSphere(.01,15,15);
+ glPopMatrix();
+
+ MxVpV(V2,R2[step],P2,T2[step]);
+
+ glPushMatrix();
+ glTranslated(V2[0],V2[1],V2[2]);
+ glutSolidSphere(.01,15,15);
+ glPopMatrix();
+
+ // draw the line between the closest points
+
+ glDisable(GL_LIGHTING);
+ glBegin(GL_LINES);
+ glVertex3v(V1);
+ glVertex3v(V2);
+ glEnd();
+ glEnable(GL_LIGHTING);
+ break;
+
+ case 3:
+
+ // perform tolerance query
+
+ PQP_Tolerance(&tres,R1[step],T1[step],torus1_tested,
+ R2[step],T2[step],torus2_tested,
+ tolerance);
+
+ if (tres.CloserThanTolerance())
+ glColor3f(0,0,1);
+ else
+ glColor3f(1,1,1);
+
+ // draw models
+
+ MVtoOGL(oglm,R1[step],T1[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus1_drawn->Draw();
+ glPopMatrix();
+
+ MVtoOGL(oglm,R2[step],T2[step]);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus2_drawn->Draw();
+ glPopMatrix();
+
+ break;
+
+ }
+
+ EndDraw();
+}
+
+void LoadPath(PQP_REAL (* &R)[3][3], PQP_REAL (* &T)[3], char *filename)
+{
+ FILE *fp;
+ if ( (fp = fopen(filename, "r")) == NULL )
+ {
+ fprintf(stderr, "Error opening file %s\n", filename);
+ exit(1);
+ }
+ fscanf(fp, "%d", &number_of_steps);
+
+ R = new PQP_REAL[number_of_steps][3][3];
+ T = new PQP_REAL[number_of_steps][3];
+
+ for (int i = 0; i < number_of_steps; i++)
+ {
+ double a, b, c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ R[i][0][0] = (PQP_REAL)a;
+ R[i][0][1] = (PQP_REAL)b;
+ R[i][0][2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ R[i][1][0] = (PQP_REAL)a;
+ R[i][1][1] = (PQP_REAL)b;
+ R[i][1][2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ R[i][2][0] = (PQP_REAL)a;
+ R[i][2][1] = (PQP_REAL)b;
+ R[i][2][2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ T[i][0] = (PQP_REAL)a;
+ T[i][1] = (PQP_REAL)b;
+ T[i][2] = (PQP_REAL)c;
+ }
+
+ fclose(fp);
+}
+
+void main(int argc, char **argv)
+{
+ // init glut
+
+ glutInit(&argc, argv);
+ glutInitDisplayMode(GLUT_DOUBLE | GLUT_RGB | GLUT_DEPTH | GLUT_MULTISAMPLE);
+
+ // create the window
+
+ glutCreateWindow("PQP Demo - Falling");
+
+ // set OpenGL graphics state -- material props, perspective, etc.
+
+ init_viewer_window();
+
+ // set the callbacks
+
+ glutDisplayFunc(cb_display);
+ glutMouseFunc(cb_mouse);
+ glutMotionFunc(cb_motion);
+ glutKeyboardFunc(cb_keyboard);
+ glutIdleFunc(cb_idle);
+
+ // create models
+
+ FILE *fp;
+ int ntris, i;
+ double a,b,c;
+ PQP_REAL p1[3],p2[3],p3[3];
+
+ // model 1
+
+ torus1_drawn = new Model("torus1.tris");
+
+ torus1_tested = new PQP_Model();
+
+ fp = fopen("torus1.tris","r");
+ fscanf(fp,"%d",&ntris);
+
+ torus1_tested->BeginModel();
+ for (i = 0; i < ntris; i++)
+ {
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ p1[0] = (PQP_REAL)a;
+ p1[1] = (PQP_REAL)b;
+ p1[2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ p2[0] = (PQP_REAL)a;
+ p2[1] = (PQP_REAL)b;
+ p2[2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ p3[0] = (PQP_REAL)a;
+ p3[1] = (PQP_REAL)b;
+ p3[2] = (PQP_REAL)c;
+ torus1_tested->AddTri(p1,p2,p3,i);
+ }
+ torus1_tested->EndModel();
+
+ fclose(fp);
+
+ // model 2
+
+ torus2_drawn = new Model("torus2.tris");
+
+ torus2_tested = new PQP_Model();
+
+ fp = fopen("torus2.tris","r");
+ fscanf(fp,"%d",&ntris);
+
+ torus2_tested->BeginModel();
+ for (i = 0; i < ntris; i++)
+ {
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ p1[0] = (PQP_REAL)a;
+ p1[1] = (PQP_REAL)b;
+ p1[2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ p2[0] = (PQP_REAL)a;
+ p2[1] = (PQP_REAL)b;
+ p2[2] = (PQP_REAL)c;
+ fscanf(fp,"%lf %lf %lf",&a,&b,&c);
+ p3[0] = (PQP_REAL)a;
+ p3[1] = (PQP_REAL)b;
+ p3[2] = (PQP_REAL)c;
+ torus2_tested->AddTri(p1,p2,p3,i);
+ }
+ torus2_tested->EndModel();
+
+ fclose(fp);
+
+ // load paths
+
+ LoadPath(R1,T1,"torus1.path");
+ LoadPath(R2,T2,"torus2.path");
+
+ // print instructions
+
+ printf("PQP Demo - Falling:\n"
+ "Press:\n"
+ "0 - no proximity query, just animation\n"
+ "1 - collision query\n"
+ " overlapping triangles shown in red.\n"
+ "2 - distance query\n"
+ " closest points connected by a line.\n"
+ "3 - tolerance query\n"
+ " reduce/increase tolerance with -/= keys.\n"
+ " models turn blue when closer than the tolerance.\n"
+ "any other key to toggle animation on/off\n");
+
+ // Enter the main loop.
+
+ glutMainLoop();
+}
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.cpp
new file mode 100644
index 00000000..e145b31b
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.cpp
@@ -0,0 +1,144 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include "GL/glut.h"
+#include "model.h"
+
+inline
+void
+VmV(double Vr[3], const double V1[3], const double V2[3])
+{
+ Vr[0] = V1[0] - V2[0];
+ Vr[1] = V1[1] - V2[1];
+ Vr[2] = V1[2] - V2[2];
+}
+
+inline
+void
+VcrossV(double Vr[3], const double V1[3], const double V2[3])
+{
+ Vr[0] = V1[1]*V2[2] - V1[2]*V2[1];
+ Vr[1] = V1[2]*V2[0] - V1[0]*V2[2];
+ Vr[2] = V1[0]*V2[1] - V1[1]*V2[0];
+}
+
+inline
+void
+Vnormalize(double V[3])
+{
+ double d = 1.0 / sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+ V[0] *= d;
+ V[1] *= d;
+ V[2] *= d;
+}
+
+Model::Model(char *tris_file)
+{
+ FILE *fp = fopen(tris_file,"r");
+ if (fp == NULL)
+ {
+ fprintf(stderr,"Model Constructor: Couldn't open %s\n",tris_file);
+ exit(-1);
+ }
+
+ fscanf(fp,"%d",&ntris);
+ tri = new ModelTri[ntris];
+
+ int i;
+
+ for (i = 0; i < ntris; i++)
+ {
+ // read the tri verts
+
+ fscanf(fp,"%lf %lf %lf %lf %lf %lf %lf %lf %lf",
+ &tri[i].p0[0], &tri[i].p0[1], &tri[i].p0[2],
+ &tri[i].p1[0], &tri[i].p1[1], &tri[i].p1[2],
+ &tri[i].p2[0], &tri[i].p2[1], &tri[i].p2[2]);
+
+ // set the normal
+
+ double a[3],b[3];
+ VmV(a,tri[i].p1,tri[i].p0);
+ VmV(b,tri[i].p2,tri[i].p0);
+ VcrossV(tri[i].n,a,b);
+ Vnormalize(tri[i].n);
+ }
+
+ fclose(fp);
+
+ // generate display list
+
+ display_list = glGenLists(1);
+ glNewList(display_list,GL_COMPILE);
+ glBegin(GL_TRIANGLES);
+ for (i = 0; i < ntris; i++)
+ {
+ glNormal3dv(tri[i].n);
+ glVertex3dv(tri[i].p0);
+ glVertex3dv(tri[i].p1);
+ glVertex3dv(tri[i].p2);
+ }
+ glEnd();
+ glEndList();
+}
+
+Model::~Model()
+{
+ delete [] tri;
+}
+
+void
+Model::Draw()
+{
+ glCallList(display_list);
+}
+
+void
+Model::DrawTri(int index)
+{
+ glBegin(GL_TRIANGLES);
+ glVertex3dv(tri[index].p0);
+ glVertex3dv(tri[index].p1);
+ glVertex3dv(tri[index].p2);
+ glEnd();
+}
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.h
new file mode 100644
index 00000000..df352e4e
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/model.h
@@ -0,0 +1,63 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef MODEL_H
+#define MODEL_H
+
+struct ModelTri
+{
+ double p0[3], p1[3], p2[3];
+ double n[3];
+};
+
+class Model
+{
+ int ntris;
+ ModelTri *tri;
+ int display_list;
+
+public:
+ Model(char *tris_file);
+ ~Model();
+ void Draw();
+ void DrawTri(int index);
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.path b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.path
new file mode 100644
index 00000000..3cc39f84
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.path
@@ -0,0 +1,11991 @@
+2398
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559976
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559927
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559855
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559758
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559637
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559492
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559323
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.559129
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.558912
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.55867
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.558404
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.558114
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.557799
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.557461
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.557098
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.556711
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.5563
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.555864
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.555405
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.554921
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.554413
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.553881
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.553325
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.552744
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.55214
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.551511
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.550858
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.550181
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.549479
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.548754
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.548004
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.54723
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.546432
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.54561
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.544763
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.543892
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.542998
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.542079
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.541135
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.540168
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.539176
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.53816
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.537121
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.536056
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.534968
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.533855
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.532719
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.531558
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.530373
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.529163
+
+0.990268 0.139173 0
+-0.139173 0.990268 0
+0 0 1
+0 0 0.52793
+
+0.989936 0.141515 0.000593893
+-0.141515 0.989936 -0.000519689
+-0.00066146 0.000430414 1
+7.91318e-05 -5.04108e-06 0.526793
+
+0.989158 0.146842 0.00196527
+-0.146839 0.989159 -0.00174679
+-0.00220047 0.00143928 0.999997
+0.000262615 -2.14122e-05 0.525795
+
+0.987984 0.154504 0.00392549
+-0.154491 0.987988 -0.00349908
+-0.00441897 0.00285059 0.999986
+0.000525427 -4.36487e-05 0.524893
+
+0.986747 0.16216 0.00588377
+-0.16213 0.986755 -0.00525338
+-0.00665773 0.00422982 0.999969
+0.000788239 -6.58851e-05 0.523967
+
+0.985446 0.169809 0.00784009
+-0.169755 0.985461 -0.00700965
+-0.00891641 0.00557674 0.999945
+0.00105105 -8.81216e-05 0.523016
+
+0.984081 0.177449 0.00979444
+-0.177366 0.984106 -0.0087679
+-0.0111946 0.00689113 0.999914
+0.00131386 -0.000110358 0.522042
+
+0.982653 0.185082 0.0117468
+-0.184963 0.982689 -0.0105281
+-0.013492 0.00817276 0.999876
+0.00157667 -0.000132595 0.521043
+
+0.981161 0.192706 0.0136971
+-0.192544 0.981211 -0.0122903
+-0.0158082 0.00942143 0.999831
+0.00183949 -0.000154831 0.52002
+
+0.979606 0.20032 0.0156455
+-0.200109 0.979673 -0.0140543
+-0.0181428 0.0106369 0.999779
+0.0021023 -0.000177067 0.518973
+
+0.977987 0.207924 0.0175917
+-0.207658 0.978073 -0.0158203
+-0.0204955 0.011819 0.99972
+0.00236511 -0.000199304 0.517902
+
+0.976304 0.215518 0.019536
+-0.215191 0.976414 -0.0175882
+-0.0228658 0.0129675 0.999654
+0.00262792 -0.00022154 0.516807
+
+0.974559 0.223101 0.0214781
+-0.222706 0.974694 -0.019358
+-0.0252534 0.0140822 0.999582
+0.00289073 -0.000243777 0.515687
+
+0.97275 0.230673 0.0234182
+-0.230203 0.972913 -0.0211297
+-0.0276579 0.015163 0.999502
+0.00315355 -0.000266013 0.514543
+
+0.970877 0.238232 0.0253562
+-0.237682 0.971073 -0.0229032
+-0.030079 0.0162095 0.999416
+0.00341636 -0.00028825 0.513375
+
+0.970015 0.241539 0.0270236
+-0.240942 0.970254 -0.0235414
+-0.0319059 0.0163244 0.999358
+0.00374567 -0.000166828 0.512364
+
+0.970626 0.238937 0.028192
+-0.238356 0.970918 -0.0224596
+-0.0327385 0.0150802 0.99935
+0.00415481 0.00018866 0.511615
+
+0.972572 0.230798 0.0289044
+-0.230293 0.972921 -0.0197626
+-0.0326829 0.012564 0.999387
+0.00464566 0.000736041 0.511103
+
+0.975424 0.218374 0.0293345
+-0.217984 0.975822 -0.015928
+-0.0321035 0.00914215 0.999443
+0.00520252 0.00142812 0.510747
+
+0.978118 0.205913 0.0297574
+-0.205637 0.978554 -0.0120928
+-0.0316093 0.00570899 0.999484
+0.00575937 0.0021202 0.510367
+
+0.980652 0.193418 0.0301732
+-0.193255 0.981114 -0.00825704
+-0.0312004 0.00226616 0.999511
+0.00631622 0.00281228 0.509962
+
+0.983028 0.18089 0.0305819
+-0.18084 0.983503 -0.00442071
+-0.030877 -0.00118475 0.999522
+0.00687307 0.00350436 0.509534
+
+0.984714 0.17126 0.0317495
+-0.171305 0.985217 -0.00132122
+-0.0315065 -0.00413782 0.999495
+0.00753812 0.00418046 0.50924
+
+0.985627 0.165506 0.0338726
+-0.16563 0.986188 0.000877665
+-0.0332595 -0.00647538 0.999426
+0.00834163 0.00484375 0.50912
+
+0.985859 0.163451 0.0369643
+-0.163642 0.986517 0.00216961
+-0.0361113 -0.00818783 0.999314
+0.00928208 0.00549153 0.509174
+
+0.985392 0.165289 0.0410211
+-0.165532 0.986201 0.00256789
+-0.0400306 -0.00932065 0.999155
+0.0103621 0.00612824 0.509401
+
+0.984357 0.170116 0.0458363
+-0.170396 0.985373 0.00223921
+-0.0447849 -0.0100145 0.998946
+0.0115527 0.00675158 0.509761
+
+0.983276 0.174935 0.0506501
+-0.175254 0.984521 0.00190724
+-0.0495325 -0.010752 0.998715
+0.0127432 0.00737492 0.510097
+
+0.982149 0.179744 0.0554625
+-0.180107 0.983646 0.00157196
+-0.0542729 -0.0115331 0.99846
+0.0139338 0.00799827 0.510409
+
+0.980974 0.184545 0.0602734
+-0.184954 0.982746 0.00123339
+-0.0590058 -0.0123577 0.998181
+0.0151243 0.00862161 0.510697
+
+0.979753 0.189335 0.0650825
+-0.189794 0.981823 0.000891545
+-0.0637307 -0.0132258 0.997879
+0.0163149 0.00924495 0.510961
+
+0.978486 0.194116 0.0698898
+-0.194629 0.980877 0.00054642
+-0.0684472 -0.0141372 0.997555
+0.0175054 0.0098683 0.5112
+
+0.977172 0.198885 0.0746952
+-0.199457 0.979907 0.000198027
+-0.0731549 -0.015092 0.997206
+0.018696 0.0104916 0.511415
+
+0.975812 0.203644 0.0794986
+-0.204279 0.978913 -0.000153627
+-0.0778534 -0.01609 0.996835
+0.0198865 0.011115 0.511606
+
+0.974406 0.208392 0.0842998
+-0.209094 0.977895 -0.000508535
+-0.0825423 -0.0171311 0.99644
+0.0210771 0.0117383 0.511773
+
+0.972953 0.213127 0.0890987
+-0.213902 0.976855 -0.000866689
+-0.0872212 -0.0182152 0.996022
+0.0222677 0.0123617 0.511916
+
+0.971455 0.21785 0.0938953
+-0.218704 0.97579 -0.00122808
+-0.0918897 -0.0193422 0.995581
+0.0234582 0.012985 0.512034
+
+0.969911 0.222561 0.0986894
+-0.223498 0.974703 -0.0015927
+-0.0965473 -0.0205121 0.995117
+0.0246488 0.0136084 0.512128
+
+0.968321 0.227258 0.103481
+-0.228286 0.973592 -0.00196055
+-0.101194 -0.0217248 0.99463
+0.0258393 0.0142317 0.512199
+
+0.966685 0.231942 0.10827
+-0.233066 0.972458 -0.00233161
+-0.105828 -0.0229801 0.994119
+0.0270299 0.014855 0.512244
+
+0.965004 0.236612 0.113056
+-0.237839 0.971301 -0.00270588
+-0.110451 -0.0242778 0.993585
+0.0282204 0.0154784 0.512266
+
+0.963278 0.241268 0.117839
+-0.242604 0.97012 -0.00308334
+-0.115061 -0.025618 0.993028
+0.029411 0.0161017 0.512264
+
+0.961506 0.245909 0.122618
+-0.247362 0.968917 -0.003464
+-0.119659 -0.0270005 0.992448
+0.0306015 0.0167251 0.512237
+
+0.959689 0.250534 0.127395
+-0.252112 0.96769 -0.00384784
+-0.124243 -0.0284251 0.991845
+0.0317921 0.0173484 0.512186
+
+0.957827 0.255144 0.132169
+-0.256854 0.966441 -0.00423486
+-0.128814 -0.0298918 0.991218
+0.0329826 0.0179718 0.512111
+
+0.95592 0.259738 0.136939
+-0.261589 0.965168 -0.00462504
+-0.13337 -0.0314004 0.990569
+0.0341732 0.0185951 0.512012
+
+0.953969 0.264316 0.141705
+-0.266315 0.963873 -0.00501838
+-0.137912 -0.0329508 0.989896
+0.0353637 0.0192184 0.511889
+
+0.951973 0.268877 0.146468
+-0.271033 0.962555 -0.00541486
+-0.14244 -0.0345428 0.989201
+0.0365543 0.0198418 0.511741
+
+0.949932 0.27342 0.151227
+-0.275742 0.961214 -0.00581449
+-0.146952 -0.0361763 0.988482
+0.0377448 0.0204651 0.511569
+
+0.947848 0.277946 0.155983
+-0.280443 0.959851 -0.00621725
+-0.151448 -0.0378512 0.98774
+0.0389354 0.0210885 0.511373
+
+0.945719 0.282454 0.160734
+-0.285135 0.958464 -0.00662314
+-0.155928 -0.0395673 0.986976
+0.040126 0.0217118 0.511153
+
+0.943546 0.286944 0.165481
+-0.289819 0.957056 -0.00703213
+-0.160393 -0.0413245 0.986188
+0.0413165 0.0223352 0.510909
+
+0.941329 0.291415 0.170224
+-0.294494 0.955624 -0.00744424
+-0.16484 -0.0431225 0.985377
+0.0425071 0.0229585 0.51064
+
+0.939069 0.295866 0.174963
+-0.29916 0.954171 -0.00785944
+-0.16927 -0.0449614 0.984544
+0.0436976 0.0235818 0.510348
+
+0.936766 0.300298 0.179697
+-0.303817 0.952695 -0.00827773
+-0.173683 -0.0468408 0.983687
+0.0448882 0.0242052 0.510031
+
+0.934419 0.30471 0.184427
+-0.308464 0.951196 -0.00869909
+-0.178077 -0.0487606 0.982808
+0.0460787 0.0248285 0.50969
+
+0.932029 0.309102 0.189152
+-0.313103 0.949676 -0.00912353
+-0.182454 -0.0507207 0.981905
+0.0472693 0.0254519 0.509325
+
+0.929596 0.313472 0.193873
+-0.317731 0.948133 -0.00955103
+-0.186811 -0.0527209 0.98098
+0.0484598 0.0260752 0.508935
+
+0.92712 0.317822 0.198588
+-0.322351 0.946568 -0.00998157
+-0.19115 -0.054761 0.980032
+0.0496504 0.0266986 0.508522
+
+0.924602 0.32215 0.203299
+-0.32696 0.944981 -0.0104152
+-0.195469 -0.0568408 0.979061
+0.0508409 0.0273219 0.508084
+
+0.922042 0.326456 0.208004
+-0.33156 0.943372 -0.0108518
+-0.199768 -0.0589602 0.978068
+0.0520315 0.0279453 0.507622
+
+0.919439 0.33074 0.212705
+-0.33615 0.941741 -0.0112914
+-0.204047 -0.0611189 0.977051
+0.053222 0.0285686 0.507136
+
+0.916794 0.335001 0.2174
+-0.34073 0.940088 -0.0117341
+-0.208306 -0.0633168 0.976012
+0.0544126 0.0291919 0.506625
+
+0.914108 0.339239 0.222089
+-0.345299 0.938414 -0.0121797
+-0.212543 -0.0655537 0.97495
+0.0556031 0.0298153 0.506091
+
+0.91138 0.343453 0.226773
+-0.349859 0.936717 -0.0126284
+-0.21676 -0.0678294 0.973866
+0.0567937 0.0304386 0.505532
+
+0.908611 0.347644 0.231452
+-0.354408 0.934999 -0.01308
+-0.220954 -0.0701437 0.972758
+0.0579843 0.031062 0.504949
+
+0.905801 0.35181 0.236124
+-0.358947 0.93326 -0.0135346
+-0.225127 -0.0724963 0.971629
+0.0591748 0.0316853 0.504342
+
+0.90295 0.355952 0.240791
+-0.363475 0.931499 -0.0139922
+-0.229277 -0.0748872 0.970476
+0.0603654 0.0323087 0.503711
+
+0.900058 0.360068 0.245452
+-0.367992 0.929717 -0.0144528
+-0.233405 -0.077316 0.969301
+0.0615559 0.032932 0.503055
+
+0.897126 0.36416 0.250106
+-0.372499 0.927913 -0.0149162
+-0.237509 -0.0797826 0.968103
+0.0627465 0.0335553 0.502376
+
+0.894153 0.368226 0.254755
+-0.376994 0.926088 -0.0153826
+-0.24159 -0.0822867 0.966883
+0.063937 0.0341787 0.501672
+
+0.891141 0.372265 0.259397
+-0.381479 0.924242 -0.015852
+-0.245647 -0.0848281 0.965641
+0.0651276 0.034802 0.500944
+
+0.888088 0.376278 0.264033
+-0.385952 0.922374 -0.0163242
+-0.24968 -0.0874067 0.964376
+0.0663181 0.0354254 0.500191
+
+0.884997 0.380265 0.268662
+-0.390414 0.920486 -0.0167994
+-0.253688 -0.0900221 0.963088
+0.0675087 0.0360487 0.499415
+
+0.882963 0.382894 0.271603
+-0.393034 0.919341 -0.0183206
+-0.256711 -0.090573 0.962235
+0.0686088 0.0366123 0.49888
+
+0.882191 0.384232 0.272222
+-0.39373 0.918983 -0.021151
+-0.258294 -0.0885226 0.962002
+0.0695979 0.0370989 0.498681
+
+0.882693 0.384285 0.270516
+-0.392514 0.919398 -0.0252899
+-0.25843 -0.0838582 0.962383
+0.0704762 0.0375077 0.498817
+
+0.884286 0.383 0.267114
+-0.389492 0.920526 -0.0304723
+-0.257556 -0.0770925 0.963183
+0.0712643 0.0378552 0.499194
+
+0.886629 0.380739 0.262538
+-0.385207 0.922113 -0.0363728
+-0.255939 -0.0688823 0.964236
+0.0719974 0.038164 0.49973
+
+0.888961 0.378431 0.257951
+-0.380927 0.923638 -0.0422742
+-0.254251 -0.0606805 0.965233
+0.0727305 0.0384729 0.500241
+
+0.891279 0.376077 0.253353
+-0.376654 0.925101 -0.048176
+-0.252495 -0.0524879 0.966174
+0.0734636 0.0387818 0.500729
+
+0.893584 0.373676 0.248744
+-0.372387 0.926501 -0.0540781
+-0.250669 -0.0443056 0.967059
+0.0741968 0.0390906 0.501192
+
+0.895876 0.371228 0.244124
+-0.368128 0.927838 -0.0599799
+-0.248774 -0.0361343 0.967887
+0.0749299 0.0393995 0.501631
+
+0.898153 0.368733 0.239494
+-0.363877 0.929114 -0.0658813
+-0.24681 -0.0279749 0.96866
+0.075663 0.0397083 0.502046
+
+0.901867 0.362712 0.234682
+-0.356305 0.93169 -0.0707163
+-0.244301 -0.0198416 0.969497
+0.0764947 0.0402186 0.502622
+
+0.905528 0.356625 0.229864
+-0.348728 0.934174 -0.0755532
+-0.241677 -0.0117446 0.970286
+0.0773265 0.0407288 0.503173
+
+0.909134 0.350473 0.225041
+-0.341148 0.936566 -0.0803919
+-0.238941 -0.00368536 0.971027
+0.0781582 0.0412391 0.503701
+
+0.912685 0.344256 0.220212
+-0.333567 0.938866 -0.0852321
+-0.236092 0.00433451 0.971721
+0.07899 0.0417494 0.504204
+
+0.916179 0.337975 0.215379
+-0.325984 0.941074 -0.0900735
+-0.23313 0.0123134 0.972368
+0.0798217 0.0422596 0.504684
+
+0.919616 0.331631 0.21054
+-0.318402 0.943192 -0.0949161
+-0.230057 0.0202498 0.972966
+0.0806534 0.0427699 0.505139
+
+0.922994 0.325223 0.205697
+-0.310822 0.945218 -0.0997594
+-0.226873 0.0281422 0.973518
+0.0814852 0.0432801 0.505569
+
+0.926313 0.318753 0.20085
+-0.303244 0.947154 -0.104603
+-0.223579 0.0359888 0.974021
+0.0823169 0.0437904 0.505976
+
+0.929571 0.312222 0.195999
+-0.295671 0.949 -0.109448
+-0.220175 0.0437883 0.974477
+0.0831486 0.0443006 0.506358
+
+0.932767 0.305629 0.191143
+-0.288102 0.950755 -0.114292
+-0.216661 0.0515391 0.974885
+0.0839804 0.0448109 0.506717
+
+0.935901 0.298976 0.186285
+-0.28054 0.95242 -0.119136
+-0.21304 0.0592397 0.975246
+0.0848121 0.0453211 0.507051
+
+0.938972 0.292263 0.181422
+-0.272985 0.953996 -0.12398
+-0.209311 0.0668885 0.975559
+0.0856438 0.0458314 0.507361
+
+0.941978 0.285492 0.176557
+-0.265439 0.955482 -0.128824
+-0.205475 0.074484 0.975824
+0.0864756 0.0463416 0.507646
+
+0.944918 0.278662 0.171688
+-0.257902 0.95688 -0.133666
+-0.201533 0.0820248 0.976041
+0.0873073 0.0468519 0.507908
+
+0.947793 0.271774 0.166817
+-0.250377 0.958189 -0.138508
+-0.197485 0.0895094 0.976211
+0.088139 0.0473621 0.508145
+
+0.9506 0.264829 0.161944
+-0.242863 0.959411 -0.143348
+-0.193334 0.0969362 0.976333
+0.0889708 0.0478724 0.508358
+
+0.953338 0.257829 0.157068
+-0.235363 0.960544 -0.148187
+-0.189078 0.104304 0.976407
+0.0898025 0.0483826 0.508547
+
+0.956008 0.250773 0.152191
+-0.227877 0.96159 -0.153024
+-0.184719 0.111611 0.976433
+0.0906342 0.0488929 0.508712
+
+0.958607 0.243662 0.147311
+-0.220406 0.96255 -0.157859
+-0.180259 0.118856 0.976412
+0.091466 0.0494031 0.508853
+
+0.961136 0.236498 0.142431
+-0.212952 0.963423 -0.162691
+-0.175697 0.126038 0.976343
+0.0922977 0.0499134 0.508969
+
+0.963593 0.229281 0.137549
+-0.205515 0.96421 -0.167522
+-0.171035 0.133154 0.976226
+0.0931294 0.0504236 0.509061
+
+0.965977 0.222012 0.132666
+-0.198097 0.964911 -0.172349
+-0.166274 0.140205 0.976061
+0.0939612 0.0509339 0.509129
+
+0.968287 0.214691 0.127782
+-0.190698 0.965528 -0.177174
+-0.161415 0.147188 0.975849
+0.0947929 0.0514441 0.509173
+
+0.970523 0.20732 0.122897
+-0.18332 0.96606 -0.181996
+-0.156458 0.154101 0.975589
+0.0956246 0.0519544 0.509193
+
+0.972684 0.199899 0.118013
+-0.175964 0.966508 -0.186814
+-0.151404 0.160945 0.975281
+0.0964564 0.0524646 0.509188
+
+0.974768 0.19243 0.113128
+-0.168631 0.966872 -0.191628
+-0.146256 0.167716 0.974926
+0.0972881 0.0529749 0.509159
+
+0.976776 0.184912 0.108244
+-0.161322 0.967154 -0.196439
+-0.141012 0.174415 0.974523
+0.0981199 0.0534851 0.509107
+
+0.978705 0.177348 0.10336
+-0.154038 0.967353 -0.201246
+-0.135676 0.181039 0.974072
+0.0989516 0.0539954 0.509029
+
+0.980557 0.169738 0.0984764
+-0.146779 0.967471 -0.206048
+-0.130247 0.187588 0.973574
+0.0997833 0.0545056 0.508928
+
+0.982329 0.162082 0.0935939
+-0.139548 0.967507 -0.210846
+-0.124727 0.194059 0.973028
+0.100615 0.0550159 0.508803
+
+0.98402 0.154383 0.0887126
+-0.132344 0.967463 -0.215639
+-0.119117 0.200453 0.972435
+0.101447 0.0555261 0.508653
+
+0.985631 0.14664 0.0838327
+-0.12517 0.967339 -0.220428
+-0.113418 0.206767 0.971794
+0.102279 0.0560364 0.508479
+
+0.98716 0.138854 0.0789544
+-0.118025 0.967135 -0.22521
+-0.107631 0.213 0.971106
+0.10311 0.0565466 0.508281
+
+0.988607 0.131028 0.074078
+-0.110911 0.966853 -0.229988
+-0.101757 0.219152 0.97037
+0.103942 0.0570569 0.508059
+
+0.989971 0.123161 0.0692036
+-0.103829 0.966492 -0.23476
+-0.095798 0.22522 0.969587
+0.104774 0.0575671 0.507813
+
+0.991251 0.115255 0.0643316
+-0.0967799 0.966054 -0.239526
+-0.0897543 0.231204 0.968756
+0.105605 0.0580774 0.507542
+
+0.992446 0.10731 0.0594622
+-0.0897644 0.96554 -0.244285
+-0.0836274 0.237102 0.967879
+0.106437 0.0585876 0.507247
+
+0.993556 0.0993281 0.0545956
+-0.0827835 0.964949 -0.249039
+-0.0774185 0.242914 0.966953
+0.107269 0.0590979 0.506928
+
+0.99458 0.0913098 0.049732
+-0.0758382 0.964283 -0.253786
+-0.0711288 0.248639 0.965981
+0.108101 0.0596081 0.506585
+
+0.995517 0.0832562 0.0448717
+-0.0689293 0.963542 -0.258526
+-0.0647597 0.254274 0.964962
+0.108932 0.0601184 0.506218
+
+0.996368 0.0751683 0.040015
+-0.0620577 0.962727 -0.263259
+-0.0583122 0.259819 0.963895
+0.109764 0.0606286 0.505826
+
+0.99713 0.0670473 0.035162
+-0.0552244 0.961839 -0.267984
+-0.0517878 0.265274 0.962781
+0.110596 0.0611389 0.505411
+
+0.997804 0.0588941 0.030313
+-0.0484301 0.960879 -0.272703
+-0.0451877 0.270636 0.961621
+0.111428 0.0616491 0.504971
+
+0.998389 0.0507099 0.0254682
+-0.0416757 0.959846 -0.277413
+-0.0385132 0.275905 0.960413
+0.112259 0.0621594 0.504507
+
+0.998884 0.0424957 0.0206279
+-0.0349621 0.958743 -0.282116
+-0.0317656 0.28108 0.959159
+0.113091 0.0626696 0.504019
+
+0.999288 0.0342527 0.0157923
+-0.02829 0.95757 -0.28681
+-0.0249462 0.286159 0.957857
+0.113923 0.0631799 0.503506
+
+0.999602 0.0259818 0.0109616
+-0.0216604 0.956327 -0.291496
+-0.0180565 0.291143 0.956509
+0.114755 0.0636901 0.50297
+
+0.999825 0.0176843 0.00613613
+-0.015074 0.955015 -0.296174
+-0.0110977 0.296029 0.955114
+0.115586 0.0642004 0.502409
+
+0.999955 0.00936119 0.00131605
+-0.00853163 0.953636 -0.300842
+-0.00407127 0.300818 0.953673
+0.116418 0.0647106 0.501824
+
+0.999993 0.00101369 -0.00349839
+-0.002034 0.952189 -0.305502
+0.00302145 0.305507 0.952185
+0.11725 0.0652209 0.501215
+
+0.999938 -0.0073571 -0.00830696
+0.00441808 0.950677 -0.310152
+0.0101791 0.310096 0.950651
+0.118081 0.0657311 0.500581
+
+0.99979 -0.01575 -0.0131094
+0.0108239 0.949099 -0.314793
+0.0174001 0.314585 0.94907
+0.118913 0.0662414 0.499924
+
+0.999548 -0.024164 -0.0179055
+0.0171826 0.947456 -0.319424
+0.0246832 0.318972 0.947443
+0.119745 0.0667516 0.499242
+
+0.999211 -0.0325977 -0.022695
+0.0234936 0.94575 -0.324045
+0.032027 0.323256 0.945769
+0.120577 0.0672619 0.498536
+
+0.998779 -0.0410502 -0.0274778
+0.0297562 0.943981 -0.328656
+0.0394298 0.327437 0.94405
+0.121408 0.0677721 0.497806
+
+0.998252 -0.0495201 -0.0322534
+0.0359695 0.94215 -0.333256
+0.0468904 0.331514 0.942284
+0.12224 0.0682824 0.497052
+
+0.99763 -0.0580063 -0.0370218
+0.0421331 0.940258 -0.337846
+0.0544073 0.335485 0.940473
+0.123072 0.0687926 0.496273
+
+0.996911 -0.0665076 -0.0417827
+0.0482461 0.938306 -0.342425
+0.0619788 0.339352 0.938616
+0.123904 0.0693029 0.495471
+
+0.996095 -0.0750229 -0.0465359
+0.0543079 0.936294 -0.346993
+0.0696037 0.343111 0.936712
+0.124735 0.0698131 0.494644
+
+0.995183 -0.0835509 -0.051281
+0.0603179 0.934224 -0.35155
+0.0772803 0.346764 0.934763
+0.125567 0.0703234 0.493793
+
+0.994174 -0.0920904 -0.056018
+0.0662755 0.932096 -0.356095
+0.0850072 0.350308 0.932769
+0.126399 0.0708336 0.492917
+
+0.993067 -0.10064 -0.0607466
+0.07218 0.929912 -0.360629
+0.0927828 0.353744 0.930729
+0.127231 0.0713439 0.492018
+
+0.991862 -0.109199 -0.0654665
+0.0780309 0.927672 -0.365151
+0.100606 0.357071 0.928644
+0.128062 0.0718541 0.491094
+
+0.990559 -0.117766 -0.0701775
+0.0838275 0.925378 -0.369661
+0.108474 0.360288 0.926513
+0.128894 0.0723644 0.490147
+
+0.989157 -0.126339 -0.0748793
+0.0895693 0.923029 -0.374158
+0.116387 0.363394 0.924337
+0.129726 0.0728746 0.489175
+
+0.987657 -0.134918 -0.0795719
+0.0952557 0.920628 -0.378643
+0.124342 0.366389 0.922116
+0.130558 0.0733849 0.488179
+
+0.986057 -0.143501 -0.0842548
+0.100886 0.918175 -0.383115
+0.132338 0.369273 0.91985
+0.131389 0.0738951 0.487158
+
+0.984358 -0.152087 -0.088928
+0.10646 0.915671 -0.387574
+0.140374 0.372044 0.917539
+0.132221 0.0744054 0.486114
+
+0.98256 -0.160674 -0.0935911
+0.111977 0.913117 -0.392019
+0.148447 0.374703 0.915184
+0.133053 0.0749156 0.485045
+
+0.980662 -0.169262 -0.098244
+0.117437 0.910513 -0.396452
+0.156557 0.377248 0.912784
+0.133884 0.0754259 0.483952
+
+0.978664 -0.177849 -0.102886
+0.122839 0.907862 -0.400871
+0.164701 0.379679 0.910339
+0.134716 0.0759361 0.482835
+
+0.976567 -0.186434 -0.107518
+0.128182 0.905163 -0.405276
+0.172879 0.381997 0.90785
+0.135548 0.0764464 0.481694
+
+0.974368 -0.195015 -0.112139
+0.133467 0.902419 -0.409667
+0.181087 0.3842 0.905317
+0.13638 0.0769566 0.480528
+
+0.97207 -0.203592 -0.116748
+0.138692 0.899629 -0.414044
+0.189326 0.386287 0.902739
+0.137211 0.0774669 0.479339
+
+0.969671 -0.212163 -0.121347
+0.143858 0.896795 -0.418406
+0.197593 0.388259 0.900118
+0.138043 0.0779771 0.478125
+
+0.967171 -0.220727 -0.125933
+0.148963 0.893918 -0.422754
+0.205887 0.390116 0.897452
+0.138875 0.0784874 0.476887
+
+0.964571 -0.229282 -0.130508
+0.154008 0.890999 -0.427086
+0.214206 0.391856 0.894743
+0.139707 0.0789976 0.475625
+
+0.96187 -0.237827 -0.135071
+0.158992 0.888038 -0.431404
+0.222548 0.39348 0.89199
+0.140538 0.0795079 0.474338
+
+0.959068 -0.246361 -0.139621
+0.163914 0.885038 -0.435707
+0.230912 0.394986 0.889194
+0.14137 0.0800181 0.473028
+
+0.956166 -0.254883 -0.144159
+0.168776 0.881998 -0.439994
+0.239295 0.396376 0.886354
+0.142202 0.0805284 0.471693
+
+0.953162 -0.263392 -0.148685
+0.173575 0.87892 -0.444265
+0.247698 0.397649 0.883471
+0.143034 0.0810386 0.470334
+
+0.950057 -0.271885 -0.153197
+0.178312 0.875805 -0.448521
+0.256117 0.398803 0.880545
+0.143865 0.0815489 0.468951
+
+0.946852 -0.280363 -0.157696
+0.182986 0.872654 -0.45276
+0.264551 0.39984 0.877576
+0.144697 0.0820592 0.467544
+
+0.943546 -0.288822 -0.162182
+0.187598 0.869467 -0.456983
+0.272999 0.400759 0.874565
+0.145529 0.0825694 0.466112
+
+0.940139 -0.297263 -0.166655
+0.192146 0.866247 -0.46119
+0.281459 0.40156 0.87151
+0.14636 0.0830797 0.464657
+
+0.937184 -0.303427 -0.172101
+0.194251 0.863729 -0.465015
+0.289747 0.402374 0.868414
+0.147179 0.0834856 0.463277
+
+0.93481 -0.306825 -0.178852
+0.193376 0.862145 -0.468307
+0.297885 0.403193 0.865275
+0.147988 0.0837531 0.462008
+
+0.933022 -0.307466 -0.186907
+0.189534 0.861501 -0.471054
+0.305854 0.404079 0.862075
+0.148787 0.0838815 0.460849
+
+0.931795 -0.305351 -0.196261
+0.182729 0.861775 -0.473238
+0.313636 0.405098 0.858794
+0.149575 0.0838704 0.4598
+
+0.930469 -0.303247 -0.205595
+0.175903 0.862022 -0.475369
+0.321381 0.406152 0.855427
+0.150362 0.0838593 0.458726
+
+0.929043 -0.301154 -0.214909
+0.169056 0.862243 -0.477449
+0.329089 0.407239 0.851972
+0.15115 0.0838482 0.457628
+
+0.927518 -0.299073 -0.224202
+0.162188 0.862437 -0.479476
+0.336758 0.40836 0.848431
+0.151938 0.0838371 0.456506
+
+0.925894 -0.297004 -0.233473
+0.1553 0.862604 -0.481451
+0.344388 0.409515 0.844805
+0.152725 0.083826 0.45536
+
+0.924171 -0.294948 -0.242721
+0.148392 0.862745 -0.483374
+0.351977 0.410702 0.841092
+0.153513 0.0838148 0.45419
+
+0.92235 -0.292905 -0.251945
+0.141466 0.862859 -0.485244
+0.359524 0.411923 0.837295
+0.154301 0.0838037 0.452995
+
+0.920465 -0.29082 -0.261091
+0.134587 0.863057 -0.486846
+0.366921 0.412985 0.833554
+0.155122 0.0839105 0.451855
+
+0.918571 -0.28857 -0.2701
+0.127758 0.863443 -0.488
+0.374038 0.413755 0.830001
+0.156001 0.0842083 0.45083
+
+0.91673 -0.286029 -0.278913
+0.120983 0.864122 -0.488524
+0.380747 0.414101 0.826772
+0.156958 0.0847693 0.449982
+
+0.914948 -0.283188 -0.287531
+0.114266 0.865093 -0.488424
+0.387057 0.414028 0.823874
+0.157994 0.0855925 0.449312
+
+0.913188 -0.28018 -0.29595
+0.10776 0.866349 -0.487676
+0.393033 0.413448 0.821332
+0.159121 0.0867206 0.448842
+
+0.911449 -0.277018 -0.304175
+0.101481 0.867876 -0.486306
+0.398701 0.412375 0.819136
+0.160329 0.0881093 0.448551
+
+0.909666 -0.273879 -0.312247
+0.0955343 0.8696 -0.484426
+0.404204 0.410836 0.817211
+0.161606 0.0897242 0.448407
+
+0.907851 -0.270654 -0.32024
+0.0896604 0.871406 -0.482299
+0.409595 0.409142 0.815374
+0.162919 0.0914543 0.44832
+
+0.905963 -0.267413 -0.328209
+0.0837959 0.873184 -0.480134
+0.414981 0.407481 0.81348
+0.164231 0.0931844 0.448209
+
+0.904003 -0.264156 -0.336155
+0.0779415 0.874932 -0.477933
+0.420361 0.405852 0.81153
+0.165544 0.0949145 0.448074
+
+0.901971 -0.260884 -0.344076
+0.0720973 0.876651 -0.475695
+0.425736 0.404256 0.809522
+0.166857 0.0966446 0.447915
+
+0.899866 -0.257598 -0.351972
+0.0662638 0.878341 -0.47342
+0.431103 0.402692 0.807459
+0.168169 0.0983747 0.447731
+
+0.897689 -0.254298 -0.359842
+0.0604415 0.880002 -0.471109
+0.436464 0.40116 0.805338
+0.169482 0.100105 0.447524
+
+0.89544 -0.250984 -0.367687
+0.0546307 0.881634 -0.468762
+0.441817 0.399661 0.803162
+0.170794 0.101835 0.447292
+
+0.89312 -0.247657 -0.375504
+0.0488319 0.883236 -0.466379
+0.447161 0.398195 0.800929
+0.172107 0.103565 0.447036
+
+0.890727 -0.244318 -0.383295
+0.0430454 0.88481 -0.463959
+0.452496 0.396762 0.798641
+0.17342 0.105295 0.446756
+
+0.888262 -0.240966 -0.391057
+0.0372716 0.886355 -0.461505
+0.457822 0.395362 0.796296
+0.174732 0.107025 0.446452
+
+0.885726 -0.237603 -0.398791
+0.0315109 0.88787 -0.459014
+0.463138 0.393994 0.793896
+0.176045 0.108755 0.446123
+
+0.883118 -0.234229 -0.406497
+0.0257637 0.889356 -0.456488
+0.468443 0.39266 0.791441
+0.177358 0.110485 0.445771
+
+0.880438 -0.230845 -0.414172
+0.0200304 0.890813 -0.453927
+0.473737 0.391359 0.78893
+0.17867 0.112216 0.445394
+
+0.877688 -0.227451 -0.421818
+0.0143115 0.892242 -0.451332
+0.479019 0.390091 0.786365
+0.179983 0.113946 0.444993
+
+0.874866 -0.224047 -0.429433
+0.00860718 0.893641 -0.448701
+0.484289 0.388857 0.783744
+0.181296 0.115676 0.444567
+
+0.871973 -0.220634 -0.437017
+0.00291798 0.89501 -0.446036
+0.489545 0.387656 0.781069
+0.182608 0.117406 0.444118
+
+0.869009 -0.217213 -0.444569
+-0.00275575 0.896351 -0.443336
+0.494789 0.386488 0.778339
+0.183921 0.119136 0.443644
+
+0.865974 -0.213783 -0.452089
+-0.00841363 0.897663 -0.440602
+0.500017 0.385354 0.775555
+0.185233 0.120866 0.443147
+
+0.862869 -0.210347 -0.459577
+-0.0140553 0.898946 -0.437834
+0.505232 0.384253 0.772716
+0.186546 0.122596 0.442625
+
+0.859694 -0.206903 -0.467031
+-0.0196803 0.9002 -0.435032
+0.510431 0.383186 0.769824
+0.187859 0.124326 0.442078
+
+0.856448 -0.203453 -0.474451
+-0.0252883 0.901425 -0.432197
+0.515614 0.382152 0.766878
+0.189171 0.126056 0.441508
+
+0.853132 -0.199998 -0.481837
+-0.0308789 0.902621 -0.429328
+0.52078 0.381152 0.763879
+0.190484 0.127787 0.440914
+
+0.849747 -0.196536 -0.489187
+-0.0364518 0.903788 -0.426426
+0.52593 0.380185 0.760827
+0.191797 0.129517 0.440295
+
+0.846291 -0.19307 -0.496503
+-0.0420065 0.904926 -0.42349
+0.531062 0.379253 0.757721
+0.193109 0.131247 0.439652
+
+0.842767 -0.1896 -0.503782
+-0.0475427 0.906036 -0.420522
+0.536176 0.378353 0.754562
+0.194422 0.132977 0.438985
+
+0.839173 -0.186126 -0.511025
+-0.05306 0.907116 -0.417522
+0.541271 0.377488 0.751351
+0.195734 0.134707 0.438294
+
+0.83551 -0.182648 -0.518231
+-0.058558 0.908168 -0.414489
+0.546347 0.376656 0.748088
+0.197047 0.136437 0.437578
+
+0.831778 -0.179168 -0.525399
+-0.0640364 0.909192 -0.411424
+0.551403 0.375858 0.744772
+0.19836 0.138167 0.436839
+
+0.827978 -0.175685 -0.53253
+-0.0694947 0.910187 -0.408327
+0.556438 0.375093 0.741405
+0.199672 0.139897 0.436075
+
+0.824109 -0.1722 -0.539622
+-0.0749327 0.911153 -0.405198
+0.561453 0.374362 0.737986
+0.200985 0.141627 0.435287
+
+0.820172 -0.168714 -0.546674
+-0.08035 0.912091 -0.402038
+0.566446 0.373665 0.734515
+0.202298 0.143358 0.434474
+
+0.816168 -0.165228 -0.553688
+-0.0857461 0.913 -0.398846
+0.571417 0.373002 0.730994
+0.20361 0.145088 0.433638
+
+0.812096 -0.16174 -0.560661
+-0.0911208 0.913881 -0.395623
+0.576366 0.372372 0.727421
+0.204923 0.146818 0.432777
+
+0.807957 -0.158254 -0.567593
+-0.0964736 0.914734 -0.39237
+0.581291 0.371776 0.723798
+0.206235 0.148548 0.431893
+
+0.80375 -0.154767 -0.574485
+-0.101804 0.915559 -0.389086
+0.586192 0.371213 0.720125
+0.207548 0.150278 0.430984
+
+0.799477 -0.151282 -0.581335
+-0.107112 0.916355 -0.385771
+0.59107 0.370684 0.716401
+0.208861 0.152008 0.430051
+
+0.795138 -0.147799 -0.588142
+-0.112398 0.917124 -0.382427
+0.595922 0.370188 0.712628
+0.210173 0.153738 0.429093
+
+0.790732 -0.144318 -0.594908
+-0.11766 0.917865 -0.379052
+0.600749 0.369726 0.708805
+0.211486 0.155468 0.428112
+
+0.786261 -0.140839 -0.60163
+-0.122898 0.918577 -0.375648
+0.60555 0.369297 0.704932
+0.212799 0.157198 0.427106
+
+0.781724 -0.137364 -0.608309
+-0.128112 0.919262 -0.372215
+0.610324 0.368901 0.701011
+0.214111 0.158928 0.426076
+
+0.777121 -0.133892 -0.614944
+-0.133302 0.91992 -0.368752
+0.615072 0.368539 0.697041
+0.215424 0.160659 0.425022
+
+0.772454 -0.130424 -0.621534
+-0.138468 0.920549 -0.365261
+0.619791 0.36821 0.693022
+0.216736 0.162389 0.423944
+
+0.767722 -0.126961 -0.628079
+-0.143608 0.921152 -0.361741
+0.624483 0.367914 0.688956
+0.218049 0.164119 0.422842
+
+0.762926 -0.123503 -0.634579
+-0.148724 0.921726 -0.358192
+0.629146 0.367651 0.684841
+0.219362 0.165849 0.421715
+
+0.758066 -0.120051 -0.641033
+-0.153813 0.922274 -0.354616
+0.63378 0.367422 0.680679
+0.220674 0.167579 0.420564
+
+0.753143 -0.116605 -0.647441
+-0.158877 0.922794 -0.351011
+0.638384 0.367225 0.67647
+0.221987 0.169309 0.419389
+
+0.748156 -0.113165 -0.653802
+-0.163914 0.923288 -0.347379
+0.642958 0.367061 0.672214
+0.2233 0.171039 0.41819
+
+0.743106 -0.109732 -0.660115
+-0.168925 0.923754 -0.34372
+0.647501 0.36693 0.667911
+0.224612 0.172769 0.416967
+
+0.737994 -0.106307 -0.666381
+-0.173908 0.924193 -0.340033
+0.652013 0.366831 0.663561
+0.225925 0.174499 0.415719
+
+0.732819 -0.10289 -0.672599
+-0.178864 0.924606 -0.33632
+0.656493 0.366766 0.659166
+0.227238 0.17623 0.414447
+
+0.727583 -0.0994813 -0.678768
+-0.183793 0.924992 -0.332579
+0.660941 0.366732 0.654725
+0.22855 0.17796 0.413151
+
+0.722286 -0.0960816 -0.684888
+-0.188694 0.925352 -0.328813
+0.665356 0.366731 0.650239
+0.229863 0.17969 0.411831
+
+0.716927 -0.0926912 -0.690959
+-0.193566 0.925685 -0.325021
+0.669737 0.366763 0.645707
+0.231175 0.18142 0.410487
+
+0.711508 -0.0893107 -0.696979
+-0.19841 0.925993 -0.321203
+0.674085 0.366826 0.641131
+0.232488 0.18315 0.409119
+
+0.706028 -0.0859406 -0.70295
+-0.203225 0.926274 -0.317359
+0.678398 0.366922 0.63651
+0.233801 0.18488 0.407726
+
+0.700489 -0.0825812 -0.708869
+-0.208011 0.926529 -0.31349
+0.682676 0.367049 0.631845
+0.235113 0.18661 0.406309
+
+0.69489 -0.0792332 -0.714737
+-0.212767 0.926758 -0.309596
+0.686919 0.367208 0.627137
+0.236426 0.18834 0.404868
+
+0.689233 -0.0758968 -0.720554
+-0.217494 0.926961 -0.305678
+0.691126 0.367399 0.622385
+0.237739 0.19007 0.403403
+
+0.683516 -0.0725726 -0.726318
+-0.22219 0.927139 -0.301735
+0.695296 0.367622 0.61759
+0.239051 0.191801 0.401913
+
+0.677742 -0.069261 -0.73203
+-0.226856 0.927292 -0.297768
+0.69943 0.367876 0.612752
+0.240364 0.193531 0.4004
+
+0.67191 -0.0659626 -0.73769
+-0.231492 0.927419 -0.293777
+0.703526 0.368161 0.607872
+0.241676 0.195261 0.398862
+
+0.66602 -0.0626776 -0.743296
+-0.236096 0.927521 -0.289763
+0.707584 0.368477 0.60295
+0.242989 0.196991 0.3973
+
+0.660074 -0.0594067 -0.748848
+-0.240669 0.927599 -0.285726
+0.711604 0.368825 0.597987
+0.244302 0.198721 0.395714
+
+0.654071 -0.0561501 -0.754346
+-0.245211 0.927651 -0.281665
+0.715585 0.369203 0.592981
+0.245614 0.200451 0.394104
+
+0.648013 -0.0529085 -0.759789
+-0.24972 0.927679 -0.277582
+0.719527 0.369612 0.587935
+0.246927 0.202181 0.392469
+
+0.641899 -0.0496821 -0.765178
+-0.254198 0.927682 -0.273477
+0.723429 0.370051 0.582849
+0.24824 0.203911 0.39081
+
+0.636342 -0.0469435 -0.769977
+-0.258604 0.927406 -0.270263
+0.726768 0.3711 0.578008
+0.249431 0.205625 0.389206
+
+0.632721 -0.0455115 -0.773041
+-0.263187 0.926209 -0.269943
+0.728283 0.374253 0.574054
+0.250255 0.207244 0.387854
+
+0.632129 -0.0448178 -0.773566
+-0.269659 0.923198 -0.273842
+0.726427 0.381703 0.571495
+0.250536 0.208776 0.386888
+
+0.634605 -0.0446989 -0.771543
+-0.278155 0.918213 -0.281983
+0.721045 0.393557 0.57027
+0.250276 0.210225 0.386309
+
+0.639578 -0.0450972 -0.767402
+-0.287971 0.911531 -0.293571
+0.71275 0.408751 0.570009
+0.249587 0.211568 0.38605
+
+0.645059 -0.0453201 -0.762788
+-0.297999 0.904281 -0.305732
+0.703631 0.424525 0.569809
+0.248821 0.212902 0.385824
+
+0.65061 -0.0453565 -0.758057
+-0.30782 0.896784 -0.317846
+0.694229 0.440139 0.569494
+0.248055 0.214235 0.385575
+
+0.656226 -0.0452036 -0.753209
+-0.317428 0.889043 -0.329912
+0.684549 0.455587 0.569064
+0.247289 0.215569 0.385301
+
+0.661902 -0.0448589 -0.748247
+-0.326818 0.881065 -0.341926
+0.674593 0.470863 0.568518
+0.246522 0.216903 0.385003
+
+0.667634 -0.0443198 -0.743169
+-0.335984 0.872856 -0.353888
+0.664364 0.485961 0.567858
+0.245756 0.218237 0.384681
+
+0.673415 -0.0435839 -0.737979
+-0.34492 0.864421 -0.365795
+0.653867 0.500876 0.567081
+0.24499 0.219571 0.384335
+
+0.679241 -0.0426491 -0.732675
+-0.353621 0.855767 -0.377645
+0.643105 0.515601 0.56619
+0.244223 0.220905 0.383964
+
+0.685106 -0.0415131 -0.72726
+-0.362081 0.846898 -0.389436
+0.632082 0.530132 0.565184
+0.243457 0.222239 0.383569
+
+0.691004 -0.0401742 -0.721733
+-0.370296 0.837823 -0.401166
+0.620801 0.544462 0.564063
+0.242691 0.223573 0.383151
+
+0.696931 -0.0386304 -0.716097
+-0.37826 0.828546 -0.412832
+0.609268 0.558586 0.562827
+0.241925 0.224907 0.382707
+
+0.70288 -0.0368802 -0.710352
+-0.385969 0.819075 -0.424434
+0.597485 0.572499 0.561477
+0.241158 0.226241 0.38224
+
+0.708136 -0.0346436 -0.705226
+-0.39332 0.810124 -0.43474
+0.586381 0.585234 0.560052
+0.240329 0.227422 0.381852
+
+0.711334 -0.0327033 -0.702093
+-0.398653 0.803922 -0.441346
+0.578862 0.593835 0.558819
+0.239272 0.228218 0.381777
+
+0.712106 -0.0301868 -0.701423
+-0.403051 0.800459 -0.443638
+0.574853 0.598626 0.557845
+0.237992 0.228481 0.382041
+
+0.710434 -0.0270889 -0.703243
+-0.406665 0.799742 -0.441629
+0.574376 0.599732 0.557147
+0.236482 0.228214 0.382644
+
+0.706452 -0.0232477 -0.707379
+-0.409781 0.801464 -0.435585
+0.577065 0.59759 0.55667
+0.234745 0.227458 0.383563
+
+0.700685 -0.019316 -0.71321
+-0.411863 0.805306 -0.42644
+0.582589 0.592545 0.55631
+0.232829 0.226345 0.384719
+
+0.694884 -0.0153254 -0.718958
+-0.413857 0.809091 -0.417246
+0.588097 0.587484 0.555882
+0.230914 0.225232 0.385852
+
+0.689053 -0.0112765 -0.724623
+-0.415764 0.812818 -0.408004
+0.593588 0.582408 0.555386
+0.228998 0.224119 0.38696
+
+0.683191 -0.00716952 -0.730204
+-0.417583 0.816487 -0.398714
+0.599061 0.577319 0.554823
+0.227082 0.223006 0.388044
+
+0.677301 -0.00300493 -0.7357
+-0.419314 0.820097 -0.389379
+0.604516 0.572216 0.554192
+0.225167 0.221893 0.389104
+
+0.671381 0.00121689 -0.741111
+-0.420958 0.823648 -0.379998
+0.609952 0.5671 0.553494
+0.223251 0.22078 0.390139
+
+0.665435 0.00549552 -0.746436
+-0.422513 0.827138 -0.370574
+0.615369 0.561971 0.552729
+0.221335 0.219667 0.391151
+
+0.659462 0.00983053 -0.751674
+-0.42398 0.830568 -0.361106
+0.620766 0.556831 0.551896
+0.21942 0.218554 0.392138
+
+0.653463 0.0142215 -0.756825
+-0.42536 0.833936 -0.351597
+0.626143 0.551679 0.550996
+0.217504 0.217441 0.393101
+
+0.64744 0.018668 -0.761887
+-0.426651 0.837241 -0.342047
+0.631498 0.546515 0.550028
+0.215588 0.216328 0.39404
+
+0.641394 0.0231695 -0.766862
+-0.427854 0.840483 -0.332458
+0.636832 0.541342 0.548994
+0.213673 0.215214 0.394955
+
+0.635325 0.0277256 -0.771747
+-0.428969 0.843662 -0.322831
+0.642143 0.536158 0.547893
+0.211757 0.214101 0.395845
+
+0.629234 0.0323359 -0.776543
+-0.429996 0.846777 -0.313166
+0.647432 0.530965 0.546725
+0.209841 0.212988 0.396711
+
+0.623123 0.0369999 -0.781248
+-0.430935 0.849826 -0.303465
+0.652697 0.525763 0.54549
+0.207926 0.211875 0.397553
+
+0.616992 0.041717 -0.785863
+-0.431785 0.85281 -0.29373
+0.657938 0.520553 0.544189
+0.20601 0.210762 0.398371
+
+0.610842 0.0464868 -0.790386
+-0.432547 0.855727 -0.28396
+0.663155 0.515334 0.542822
+0.204094 0.209649 0.399165
+
+0.604675 0.0513087 -0.794818
+-0.433222 0.858578 -0.274158
+0.668347 0.510109 0.541389
+0.202179 0.208536 0.399935
+
+0.598491 0.0561824 -0.799157
+-0.433808 0.861361 -0.264325
+0.673513 0.504877 0.539889
+0.200263 0.207423 0.40068
+
+0.592291 0.0611072 -0.803403
+-0.434306 0.864076 -0.254461
+0.678652 0.499638 0.538324
+0.198347 0.20631 0.401401
+
+0.586077 0.0660826 -0.807556
+-0.434717 0.866722 -0.244568
+0.683766 0.494394 0.536693
+0.196432 0.205197 0.402098
+
+0.579848 0.0711081 -0.811615
+-0.43504 0.869299 -0.234647
+0.688851 0.489145 0.534997
+0.194516 0.204084 0.402771
+
+0.573607 0.0761831 -0.81558
+-0.435275 0.871806 -0.224699
+0.69391 0.483891 0.533235
+0.1926 0.202971 0.40342
+
+0.567354 0.0813071 -0.81945
+-0.435423 0.874243 -0.214726
+0.698939 0.478633 0.531408
+0.190685 0.201857 0.404044
+
+0.561091 0.0864795 -0.823225
+-0.435483 0.876608 -0.204728
+0.70394 0.473371 0.529517
+0.188769 0.200744 0.404645
+
+0.554817 0.0916998 -0.826903
+-0.435456 0.878901 -0.194706
+0.708912 0.468107 0.52756
+0.186854 0.199631 0.405221
+
+0.548534 0.0969673 -0.830486
+-0.435342 0.881122 -0.184663
+0.713854 0.46284 0.52554
+0.184938 0.198518 0.405772
+
+0.542244 0.102282 -0.833972
+-0.435142 0.883271 -0.174599
+0.718765 0.457571 0.523455
+0.183022 0.197405 0.4063
+
+0.535947 0.107642 -0.837361
+-0.434854 0.885345 -0.164515
+0.723645 0.452302 0.521307
+0.181107 0.196292 0.406804
+
+0.529644 0.113048 -0.840653
+-0.43448 0.887346 -0.154413
+0.728495 0.447031 0.519094
+0.179191 0.195179 0.407283
+
+0.523336 0.118498 -0.843847
+-0.43402 0.889273 -0.144293
+0.733312 0.44176 0.516819
+0.177275 0.194066 0.407738
+
+0.517023 0.123993 -0.846943
+-0.433474 0.891124 -0.134157
+0.738097 0.43649 0.51448
+0.17536 0.192953 0.408169
+
+0.510708 0.129532 -0.84994
+-0.432842 0.8929 -0.124006
+0.742849 0.431221 0.512078
+0.173444 0.19184 0.408576
+
+0.504391 0.135113 -0.852839
+-0.432125 0.894599 -0.113841
+0.747568 0.425953 0.509614
+0.171528 0.190727 0.408959
+
+0.498073 0.140737 -0.855638
+-0.431322 0.896223 -0.103664
+0.752253 0.420688 0.507087
+0.169613 0.189614 0.409317
+
+0.491755 0.146403 -0.858338
+-0.430435 0.897768 -0.0934748
+0.756903 0.415425 0.504499
+0.167697 0.188501 0.409651
+
+0.485438 0.152109 -0.860937
+-0.429463 0.899237 -0.0832759
+0.76152 0.410166 0.501849
+0.165781 0.187387 0.409961
+
+0.479122 0.157856 -0.863437
+-0.428406 0.900627 -0.073068
+0.766101 0.40491 0.499137
+0.163866 0.186274 0.410247
+
+0.47281 0.163642 -0.865836
+-0.427266 0.901939 -0.0628523
+0.770646 0.399659 0.496364
+0.16195 0.185161 0.410509
+
+0.468566 0.168641 -0.867183
+-0.428821 0.90163 -0.056365
+0.772372 0.398277 0.494789
+0.159582 0.184 0.411088
+
+0.466335 0.172795 -0.867568
+-0.433146 0.899727 -0.0536244
+0.771308 0.40079 0.49442
+0.156762 0.182792 0.411985
+
+0.464077 0.176933 -0.867944
+-0.437458 0.897798 -0.050883
+0.770236 0.403303 0.494048
+0.153942 0.181585 0.412858
+
+0.46179 0.181056 -0.868314
+-0.441757 0.895842 -0.0481409
+0.769156 0.405814 0.493674
+0.151121 0.180377 0.413707
+
+0.459476 0.185163 -0.868675
+-0.446043 0.89386 -0.0453981
+0.768068 0.408326 0.493297
+0.148301 0.179169 0.414532
+
+0.457133 0.189254 -0.869029
+-0.450315 0.89185 -0.0426546
+0.766972 0.410836 0.492918
+0.145481 0.177962 0.415332
+
+0.454763 0.193329 -0.869376
+-0.454574 0.889814 -0.0399105
+0.765867 0.413346 0.492537
+0.142661 0.176754 0.416108
+
+0.452366 0.197387 -0.869715
+-0.45882 0.887752 -0.0371657
+0.764755 0.415855 0.492154
+0.139841 0.175547 0.41686
+
+0.449941 0.201429 -0.870046
+-0.463051 0.885663 -0.0344203
+0.763634 0.418363 0.491768
+0.13702 0.174339 0.417588
+
+0.447488 0.205455 -0.870369
+-0.467269 0.883548 -0.0316744
+0.762505 0.42087 0.49138
+0.1342 0.173132 0.418292
+
+0.44485 0.207233 -0.8713
+-0.468428 0.883021 -0.0291398
+0.763337 0.421104 0.489885
+0.131658 0.171882 0.419024
+
+0.441911 0.205936 -0.873101
+-0.465429 0.884676 -0.0269057
+0.766871 0.418256 0.486797
+0.129488 0.170569 0.419777
+
+0.438724 0.201618 -0.875712
+-0.458221 0.888487 -0.0250052
+0.773017 0.41224 0.482186
+0.127685 0.169196 0.420561
+
+0.435194 0.194802 -0.87901
+-0.447416 0.89402 -0.023385
+0.781297 0.40346 0.47623
+0.126205 0.167773 0.421377
+
+0.431223 0.18554 -0.882962
+-0.432941 0.901152 -0.0220783
+0.791587 0.391791 0.468925
+0.125047 0.166302 0.422227
+
+0.426853 0.174992 -0.887228
+-0.416265 0.909001 -0.0209824
+0.80282 0.378278 0.460853
+0.124075 0.164805 0.423092
+
+0.422213 0.164637 -0.891421
+-0.39943 0.916547 -0.0199091
+0.813751 0.364466 0.452739
+0.123103 0.163309 0.423934
+
+0.417308 0.154482 -0.895539
+-0.382443 0.923787 -0.0188586
+0.824373 0.350362 0.444584
+0.12213 0.161812 0.424752
+
+0.412144 0.144533 -0.899582
+-0.365308 0.930716 -0.0178308
+0.834678 0.335974 0.436388
+0.121158 0.160316 0.425545
+
+0.406726 0.134798 -0.90355
+-0.348032 0.937332 -0.016826
+0.844658 0.321308 0.428151
+0.120186 0.158819 0.426314
+
+0.401062 0.125284 -0.907443
+-0.33062 0.943631 -0.0158441
+0.854307 0.306373 0.419876
+0.119213 0.157323 0.427059
+
+0.395158 0.115996 -0.91126
+-0.313078 0.949611 -0.0148853
+0.863616 0.291178 0.411562
+0.118241 0.155827 0.42778
+
+0.389019 0.106941 -0.915001
+-0.295412 0.955268 -0.0139496
+0.87258 0.275729 0.403209
+0.117269 0.15433 0.428477
+
+0.382654 0.0981249 -0.918666
+-0.277628 0.9606 -0.0130371
+0.881191 0.260036 0.39482
+0.116296 0.152834 0.429149
+
+0.376069 0.089554 -0.922254
+-0.259732 0.965604 -0.012148
+0.889444 0.244107 0.386394
+0.115324 0.151337 0.429798
+
+0.369272 0.081234 -0.925764
+-0.24173 0.970278 -0.0112822
+0.897332 0.227951 0.377933
+0.114351 0.149841 0.430422
+
+0.362269 0.0731703 -0.929197
+-0.223629 0.974618 -0.0104399
+0.904849 0.211578 0.369437
+0.113379 0.148345 0.431022
+
+0.355067 0.0653683 -0.932552
+-0.205435 0.978624 -0.00962109
+0.911989 0.194995 0.360906
+0.112407 0.146848 0.431597
+
+0.347676 0.0578332 -0.93583
+-0.187153 0.982291 -0.00882591
+0.918747 0.178212 0.352343
+0.111434 0.145352 0.432149
+
+0.340101 0.05057 -0.939028
+-0.168791 0.985619 -0.00805438
+0.925117 0.161239 0.343746
+0.110462 0.143855 0.432676
+
+0.332352 0.0435835 -0.942148
+-0.150355 0.988605 -0.00730659
+0.931094 0.144085 0.335118
+0.10949 0.142359 0.433179
+
+0.324436 0.0368782 -0.945189
+-0.131851 0.991248 -0.0065826
+0.936673 0.12676 0.326458
+0.108517 0.140862 0.433658
+
+0.31636 0.0304585 -0.94815
+-0.113287 0.993545 -0.00588246
+0.94185 0.109274 0.317769
+0.107545 0.139366 0.434113
+
+0.308134 0.0243286 -0.951032
+-0.0946674 0.995495 -0.00520623
+0.946621 0.0916359 0.309049
+0.106573 0.13787 0.434544
+
+0.299766 0.0184922 -0.953833
+-0.0760003 0.997097 -0.00455398
+0.950981 0.0738568 0.300301
+0.1056 0.136373 0.43495
+
+0.291264 0.0129533 -0.956555
+-0.0572921 0.99835 -0.00392576
+0.954926 0.0559465 0.291525
+0.104628 0.134877 0.435332
+
+0.282636 0.00771517 -0.959196
+-0.0385494 0.999251 -0.00332162
+0.958452 0.0379153 0.282722
+0.103656 0.13338 0.43569
+
+0.273892 0.00278114 -0.961756
+-0.0197791 0.999801 -0.00274161
+0.961557 0.0197736 0.273892
+0.102683 0.131884 0.436024
+
+0.26504 -0.00184578 -0.964236
+-0.00098787 0.999997 -0.00218577
+0.964237 0.00153186 0.265037
+0.101711 0.130388 0.436334
+
+0.256088 -0.0061628 -0.966634
+0.0178174 0.99984 -0.00165416
+0.966489 -0.0167993 0.256157
+0.100739 0.128891 0.436619
+
+0.247046 -0.0101674 -0.96895
+0.03663 0.999328 -0.00114682
+0.968311 -0.0352093 0.247253
+0.0997663 0.127395 0.436881
+
+0.237923 -0.0138571 -0.971185
+0.0554429 0.998462 -0.000663794
+0.9697 -0.0536874 0.238325
+0.098794 0.125898 0.437118
+
+0.230184 -0.018568 -0.97297
+0.0738513 0.997268 -0.00156006
+0.970341 -0.071496 0.230927
+0.0975447 0.124407 0.437402
+
+0.224051 -0.0245159 -0.974269
+0.0915416 0.995793 -0.00400585
+0.970269 -0.0882886 0.225353
+0.0959736 0.122926 0.437742
+
+0.219473 -0.0318306 -0.975099
+0.108742 0.994038 -0.00797353
+0.96954 -0.104284 0.221626
+0.0940799 0.121444 0.438144
+
+0.214713 -0.0390071 -0.975898
+0.125896 0.991971 -0.0119505
+0.968529 -0.120295 0.2179
+0.0921862 0.119962 0.438521
+
+0.209777 -0.0460413 -0.976665
+0.142998 0.989595 -0.0159366
+0.967236 -0.136318 0.214178
+0.0902925 0.11848 0.438874
+
+0.204666 -0.0529292 -0.9774
+0.160042 0.986909 -0.0199317
+0.96566 -0.152345 0.210457
+0.0883988 0.116999 0.439202
+
+0.199384 -0.0596666 -0.978103
+0.177022 0.983916 -0.0239357
+0.963799 -0.168373 0.20674
+0.0865051 0.115517 0.439507
+
+0.193936 -0.0662498 -0.978775
+0.193933 0.980617 -0.0279483
+0.961654 -0.184397 0.203025
+0.0846114 0.114035 0.439787
+
+0.188324 -0.0726749 -0.979414
+0.210769 0.977013 -0.0319696
+0.959224 -0.200409 0.199313
+0.0827177 0.112553 0.440043
+
+0.182553 -0.0789381 -0.980022
+0.227524 0.973107 -0.0359993
+0.956508 -0.216407 0.195604
+0.080824 0.111071 0.440275
+
+0.176626 -0.0850358 -0.980598
+0.244192 0.9689 -0.0400373
+0.953506 -0.232383 0.191898
+0.0789302 0.10959 0.440483
+
+0.170547 -0.0909644 -0.981142
+0.260769 0.964394 -0.0440835
+0.950217 -0.248333 0.188195
+0.0770365 0.108108 0.440667
+
+0.164321 -0.0967203 -0.981654
+0.277248 0.959592 -0.0481377
+0.946643 -0.264251 0.184496
+0.0751428 0.106626 0.440826
+
+0.15795 -0.1023 -0.982134
+0.293624 0.954495 -0.0521997
+0.942781 -0.280133 0.180801
+0.0732491 0.105144 0.440961
+
+0.151441 -0.107701 -0.982581
+0.309891 0.949106 -0.0562695
+0.938634 -0.295971 0.177109
+0.0713554 0.103662 0.441072
+
+0.145715 -0.111971 -0.98297
+0.326326 0.943408 -0.0590901
+0.933958 -0.312159 0.174008
+0.0693565 0.102413 0.441301
+
+0.141095 -0.114846 -0.983312
+0.343025 0.937391 -0.0602626
+0.928669 -0.328798 0.171656
+0.0672365 0.10153 0.441711
+
+0.137566 -0.116456 -0.983623
+0.359663 0.931155 -0.0599428
+0.922886 -0.345527 0.16998
+0.0650016 0.10097 0.442278
+
+0.135236 -0.116805 -0.983904
+0.376178 0.924726 -0.0580741
+0.916625 -0.362269 0.168995
+0.0626428 0.100733 0.442999
+
+0.133788 -0.116324 -0.984159
+0.392656 0.918032 -0.05513
+0.909902 -0.37906 0.168497
+0.0602082 0.100742 0.443832
+
+0.132857 -0.115431 -0.98439
+0.408871 0.911129 -0.051657
+0.902869 -0.395626 0.168247
+0.0577362 0.100873 0.444711
+
+0.131993 -0.114538 -0.984611
+0.424961 0.903928 -0.0481837
+0.895537 -0.412062 0.167986
+0.0552642 0.101005 0.445566
+
+0.131193 -0.113647 -0.984821
+0.44092 0.896432 -0.04471
+0.887906 -0.428362 0.167715
+0.0527921 0.101137 0.446396
+
+0.130459 -0.112761 -0.985021
+0.456743 0.888643 -0.0412362
+0.879981 -0.444521 0.167434
+0.0503201 0.101269 0.447203
+
+0.129788 -0.111882 -0.985209
+0.472423 0.880563 -0.0377623
+0.871763 -0.460535 0.167142
+0.0478481 0.1014 0.447985
+
+0.129182 -0.11101 -0.985388
+0.487956 0.872194 -0.0342882
+0.863256 -0.476396 0.16684
+0.0453761 0.101532 0.448743
+
+0.12864 -0.110149 -0.985555
+0.503336 0.863541 -0.0308141
+0.854462 -0.492102 0.166528
+0.0429041 0.101664 0.449476
+
+0.128161 -0.1093 -0.985712
+0.518558 0.854605 -0.0273401
+0.845383 -0.507645 0.166205
+0.040432 0.101795 0.450186
+
+0.127744 -0.108465 -0.985858
+0.533616 0.84539 -0.0238662
+0.836024 -0.523021 0.165872
+0.03796 0.101927 0.450871
+
+0.127389 -0.107645 -0.985994
+0.548505 0.835899 -0.0203925
+0.826386 -0.538225 0.165529
+0.035488 0.102059 0.451532
+
+0.127096 -0.106844 -0.986119
+0.56322 0.826134 -0.0169189
+0.816474 -0.553252 0.165175
+0.033016 0.102191 0.452169
+
+0.126863 -0.106061 -0.986234
+0.577756 0.816099 -0.0134457
+0.80629 -0.568096 0.16481
+0.0305439 0.102322 0.452782
+
+0.12669 -0.1053 -0.986337
+0.592107 0.805798 -0.00997286
+0.795838 -0.582754 0.164436
+0.0280719 0.102454 0.453371
+
+0.126577 -0.104563 -0.98643
+0.606269 0.795233 -0.00650042
+0.785122 -0.59722 0.164051
+0.0255999 0.102586 0.453935
+
+0.126521 -0.10385 -0.986513
+0.620237 0.784409 -0.00302846
+0.774144 -0.611489 0.163656
+0.0231279 0.102717 0.454475
+
+0.126523 -0.103163 -0.986585
+0.634005 0.773328 0.000442957
+0.762908 -0.625556 0.16325
+0.0206559 0.102849 0.454991
+
+0.126581 -0.102506 -0.986646
+0.64757 0.761996 0.00391376
+0.751419 -0.639417 0.162834
+0.0181838 0.102981 0.455483
+
+0.126695 -0.101878 -0.986696
+0.660925 0.750415 0.0073839
+0.73968 -0.653068 0.162408
+0.0157118 0.103112 0.455951
+
+0.126864 -0.101282 -0.986736
+0.674068 0.73859 0.0108533
+0.727694 -0.666504 0.161971
+0.0132398 0.103244 0.456394
+
+0.127086 -0.100719 -0.986765
+0.686992 0.726524 0.0143219
+0.715466 -0.679719 0.161524
+0.0107678 0.103376 0.456813
+
+0.127361 -0.100191 -0.986783
+0.699693 0.714222 0.0177897
+0.703 -0.692711 0.161067
+0.00829575 0.103508 0.457209
+
+0.127686 -0.0997003 -0.986791
+0.712168 0.701688 0.0212565
+0.690299 -0.705475 0.160599
+0.00582373 0.103639 0.457579
+
+0.128062 -0.0992475 -0.986788
+0.724411 0.688925 0.0247223
+0.677369 -0.718006 0.160121
+0.0033517 0.103771 0.457926
+
+0.128487 -0.0988345 -0.986774
+0.736418 0.675939 0.0281871
+0.664213 -0.7303 0.159633
+0.000879681 0.103903 0.458249
+
+0.12896 -0.0984628 -0.986749
+0.748185 0.662734 0.0316508
+0.650836 -0.742353 0.159135
+-0.00159234 0.104034 0.458547
+
+0.129479 -0.0981339 -0.986714
+0.759709 0.649315 0.0351133
+0.637242 -0.754162 0.158626
+-0.00406436 0.104166 0.458821
+
+0.130044 -0.0978491 -0.986668
+0.770984 0.635685 0.0385746
+0.623436 -0.765722 0.158107
+-0.00653639 0.104298 0.459071
+
+0.130652 -0.0976101 -0.986612
+0.782007 0.62185 0.0420345
+0.609422 -0.777029 0.157578
+-0.00900841 0.10443 0.459297
+
+0.131302 -0.097418 -0.986544
+0.792775 0.607815 0.0454931
+0.595204 -0.788081 0.157038
+-0.0114804 0.104561 0.459499
+
+0.131994 -0.0972744 -0.986466
+0.803282 0.593584 0.0489503
+0.580788 -0.798872 0.156488
+-0.0139525 0.104693 0.459676
+
+0.132725 -0.0971805 -0.986377
+0.813527 0.579161 0.052406
+0.566179 -0.8094 0.155928
+-0.0164245 0.104825 0.459829
+
+0.133494 -0.0971375 -0.986278
+0.823504 0.564553 0.0558601
+0.55138 -0.819661 0.155358
+-0.0188965 0.104956 0.459958
+
+0.1343 -0.0971468 -0.986167
+0.833211 0.549764 0.0593127
+0.536398 -0.829651 0.154777
+-0.0213685 0.105088 0.460063
+
+0.13514 -0.0972096 -0.986046
+0.842645 0.5348 0.0627635
+0.521236 -0.839368 0.154186
+-0.0238405 0.10522 0.460144
+
+0.136015 -0.097327 -0.985915
+0.851801 0.519665 0.0662126
+0.505901 -0.848809 0.153585
+-0.0263126 0.105352 0.460201
+
+0.136921 -0.0975002 -0.985772
+0.860677 0.504364 0.0696599
+0.490396 -0.857969 0.152974
+-0.0287846 0.105483 0.460233
+
+0.137857 -0.0977302 -0.985619
+0.869269 0.488903 0.0731053
+0.474728 -0.866846 0.152352
+-0.0312566 0.105615 0.460241
+
+0.138821 -0.0980181 -0.985455
+0.877576 0.473288 0.0765488
+0.458901 -0.875438 0.151721
+-0.0337286 0.105747 0.460225
+
+0.139813 -0.098365 -0.98528
+0.885593 0.457523 0.0799903
+0.44292 -0.88374 0.151079
+-0.0362007 0.105878 0.460185
+
+0.140829 -0.0987718 -0.985095
+0.893317 0.441615 0.0834297
+0.426792 -0.891751 0.150427
+-0.0386727 0.10601 0.46012
+
+0.141869 -0.0992394 -0.984898
+0.900748 0.425568 0.0868671
+0.41052 -0.899469 0.149765
+-0.0411447 0.106142 0.460032
+
+0.142931 -0.0997688 -0.984691
+0.90788 0.409388 0.0903022
+0.394112 -0.906889 0.149092
+-0.0436167 0.106274 0.459919
+
+0.144012 -0.100361 -0.984474
+0.914714 0.393081 0.0937351
+0.377571 -0.91401 0.14841
+-0.0460887 0.106405 0.459782
+
+0.145111 -0.101016 -0.984245
+0.921244 0.376653 0.0971657
+0.360904 -0.92083 0.147717
+-0.0485608 0.106537 0.459621
+
+0.146227 -0.101736 -0.984006
+0.927471 0.360109 0.100594
+0.344115 -0.927346 0.147014
+-0.0510328 0.106669 0.459435
+
+0.147356 -0.10252 -0.983756
+0.933391 0.343455 0.10402
+0.327212 -0.933557 0.146301
+-0.0535048 0.1068 0.459226
+
+0.148498 -0.10337 -0.983495
+0.939002 0.326697 0.107443
+0.310198 -0.939459 0.145578
+-0.0559768 0.106932 0.458992
+
+0.149651 -0.104286 -0.983224
+0.944303 0.30984 0.110864
+0.293081 -0.945052 0.144845
+-0.0584489 0.107064 0.458734
+
+0.150812 -0.105269 -0.982942
+0.949292 0.292891 0.114282
+0.275864 -0.950333 0.144102
+-0.0609209 0.107196 0.458452
+
+0.15198 -0.106319 -0.982649
+0.953966 0.275855 0.117697
+0.258555 -0.955301 0.143349
+-0.0633929 0.107327 0.458146
+
+0.15422 -0.105785 -0.982357
+0.957264 0.262203 0.122046
+0.244666 -0.959197 0.141701
+-0.0656746 0.107471 0.457855
+
+0.158443 -0.102205 -0.982064
+0.958356 0.255259 0.128053
+0.237593 -0.961456 0.138393
+-0.0675955 0.107608 0.457658
+
+0.16534 -0.0941131 -0.981736
+0.956417 0.258233 0.13632
+0.240687 -0.961488 0.132707
+-0.0690151 0.107766 0.457587
+
+0.173448 -0.0838426 -0.981268
+0.953042 0.265444 0.145779
+0.248249 -0.960474 0.125946
+-0.0701972 0.107937 0.457542
+
+0.181395 -0.0734487 -0.980664
+0.949541 0.272538 0.155226
+0.255867 -0.959337 0.11918
+-0.0713792 0.108107 0.457473
+
+0.189178 -0.0629346 -0.979924
+0.945917 0.279514 0.164661
+0.263539 -0.958077 0.112409
+-0.0725612 0.108278 0.45738
+
+0.196793 -0.0523033 -0.979049
+0.942172 0.286369 0.174082
+0.271264 -0.956691 0.105634
+-0.0737433 0.108449 0.457263
+
+0.204238 -0.0415581 -0.978039
+0.938309 0.293102 0.183487
+0.279039 -0.955178 0.0988568
+-0.0749253 0.108619 0.457122
+
+0.211511 -0.030702 -0.976893
+0.93433 0.29971 0.192876
+0.286863 -0.953536 0.0920779
+-0.0761073 0.10879 0.456956
+
+0.21861 -0.0197385 -0.975613
+0.930238 0.306192 0.202248
+0.294733 -0.951765 0.0852982
+-0.0772894 0.108961 0.456766
+
+0.225532 -0.00867086 -0.974197
+0.926035 0.312546 0.2116
+0.302647 -0.949863 0.0785187
+-0.0784714 0.109131 0.456553
+
+0.232274 0.00249758 -0.972647
+0.921723 0.318771 0.220932
+0.310603 -0.947829 0.0717402
+-0.0796534 0.109302 0.456314
+
+0.238836 0.0137634 -0.970962
+0.917307 0.324864 0.230242
+0.3186 -0.945661 0.0649638
+-0.0808355 0.109472 0.456052
+
+0.245213 0.0251231 -0.969144
+0.912787 0.330824 0.23953
+0.326634 -0.943358 0.0581903
+-0.0820175 0.109643 0.455766
+
+0.251405 0.0365732 -0.967191
+0.908168 0.336649 0.248793
+0.334703 -0.94092 0.0514208
+-0.0831995 0.109814 0.455455
+
+0.257409 0.0481102 -0.965104
+0.903451 0.342339 0.258031
+0.342807 -0.938344 0.044656
+-0.0843816 0.109984 0.45512
+
+0.263224 0.0597305 -0.962884
+0.89864 0.347891 0.267242
+0.350941 -0.93563 0.037897
+-0.0855636 0.110155 0.454761
+
+0.268847 0.0714304 -0.960531
+0.893737 0.353304 0.276426
+0.359104 -0.932778 0.0311447
+-0.0867456 0.110326 0.454378
+
+0.274277 0.0832063 -0.958044
+0.888745 0.358576 0.28558
+0.367294 -0.929785 0.0244
+-0.0879277 0.110496 0.453971
+
+0.279511 0.0950544 -0.955426
+0.883667 0.363707 0.294703
+0.375508 -0.926651 0.0176638
+-0.0891097 0.110667 0.453539
+
+0.284549 0.106971 -0.952675
+0.878506 0.368695 0.303795
+0.383744 -0.923375 0.0109371
+-0.0902917 0.110838 0.453083
+
+0.289388 0.118953 -0.949792
+0.873265 0.373539 0.312854
+0.391999 -0.919956 0.00422077
+-0.0914738 0.111008 0.452603
+
+0.294028 0.130995 -0.946778
+0.867946 0.378238 0.321878
+0.400272 -0.916393 -0.00248425
+-0.0926558 0.111179 0.452099
+
+0.298465 0.143095 -0.943633
+0.862553 0.38279 0.330868
+0.408559 -0.912686 -0.00917704
+-0.0938378 0.11135 0.451571
+
+0.3027 0.155247 -0.940357
+0.857089 0.387195 0.33982
+0.416858 -0.908833 -0.0158567
+-0.0950199 0.11152 0.451018
+
+0.306731 0.167449 -0.936951
+0.851557 0.391452 0.348735
+0.425167 -0.904835 -0.0225222
+-0.0962019 0.111691 0.450442
+
+0.310556 0.179697 -0.933415
+0.845959 0.39556 0.35761
+0.433483 -0.900689 -0.0291728
+-0.0973839 0.111862 0.449841
+
+0.314175 0.191986 -0.92975
+0.8403 0.399518 0.366445
+0.441804 -0.896397 -0.0358075
+-0.098566 0.112032 0.449216
+
+0.317585 0.204312 -0.925957
+0.834581 0.403325 0.375239
+0.450127 -0.891956 -0.0424253
+-0.099748 0.112203 0.448567
+
+0.320787 0.216672 -0.922035
+0.828806 0.40698 0.383989
+0.45845 -0.887367 -0.0490254
+-0.10093 0.112373 0.447893
+
+0.323779 0.229062 -0.917986
+0.822978 0.410483 0.392696
+0.466769 -0.882629 -0.0556069
+-0.102112 0.112544 0.447195
+
+0.326561 0.241476 -0.913809
+0.817101 0.413833 0.401357
+0.475083 -0.877742 -0.0621688
+-0.103294 0.112715 0.446474
+
+0.329131 0.253912 -0.909506
+0.811177 0.417031 0.409973
+0.483389 -0.872705 -0.0687103
+-0.104476 0.112885 0.445728
+
+0.331489 0.266366 -0.905077
+0.805209 0.420074 0.41854
+0.491684 -0.867518 -0.0752304
+-0.105658 0.113056 0.444958
+
+0.333634 0.278832 -0.900523
+0.799202 0.422963 0.427059
+0.499965 -0.86218 -0.0817283
+-0.10684 0.113227 0.444163
+
+0.335565 0.291307 -0.895844
+0.793157 0.425697 0.435528
+0.508231 -0.856692 -0.088203
+-0.108022 0.113397 0.443345
+
+0.337283 0.303787 -0.891041
+0.787078 0.428277 0.443945
+0.516477 -0.851054 -0.0946537
+-0.109204 0.113568 0.442502
+
+0.338787 0.316268 -0.886114
+0.780968 0.430701 0.452311
+0.524702 -0.845264 -0.101079
+-0.110386 0.113739 0.441635
+
+0.340076 0.328746 -0.881064
+0.774831 0.432971 0.460623
+0.532903 -0.839323 -0.107479
+-0.111568 0.113909 0.440744
+
+0.34115 0.341215 -0.875893
+0.768669 0.435085 0.468881
+0.541077 -0.833231 -0.113853
+-0.11275 0.11408 0.439829
+
+0.342009 0.353673 -0.8706
+0.762486 0.437043 0.477082
+0.549221 -0.826988 -0.120198
+-0.113932 0.114251 0.438889
+
+0.342654 0.366115 -0.865187
+0.756286 0.438846 0.485227
+0.557333 -0.820593 -0.126516
+-0.115114 0.114421 0.437925
+
+0.343083 0.378537 -0.859653
+0.75007 0.440494 0.493315
+0.56541 -0.814048 -0.132803
+-0.116296 0.114592 0.436938
+
+0.343297 0.390934 -0.854001
+0.743843 0.441987 0.501343
+0.573449 -0.807352 -0.139061
+-0.117479 0.114763 0.435926
+
+0.343296 0.403303 -0.84823
+0.737608 0.443325 0.509311
+0.581448 -0.800506 -0.145288
+-0.118661 0.114933 0.434889
+
+0.343081 0.415639 -0.842342
+0.731368 0.444508 0.517217
+0.589404 -0.793509 -0.151483
+-0.119843 0.115104 0.433829
+
+0.342652 0.427938 -0.836336
+0.725125 0.445537 0.525062
+0.597313 -0.786362 -0.157645
+-0.121025 0.115274 0.432744
+
+0.342009 0.440196 -0.830215
+0.718884 0.446413 0.532842
+0.605174 -0.779066 -0.163773
+-0.122207 0.115445 0.431636
+
+0.341153 0.452409 -0.823979
+0.712648 0.447135 0.540559
+0.612983 -0.77162 -0.169867
+-0.123389 0.115616 0.430503
+
+0.340084 0.464572 -0.817629
+0.706419 0.447704 0.54821
+0.620738 -0.764025 -0.175925
+-0.124571 0.115786 0.429346
+
+0.338803 0.476681 -0.811165
+0.700201 0.448121 0.555794
+0.628436 -0.756283 -0.181948
+-0.125753 0.115957 0.428164
+
+0.337311 0.488732 -0.804588
+0.693997 0.448386 0.563311
+0.636074 -0.748392 -0.187933
+-0.126935 0.116128 0.426959
+
+0.335608 0.500722 -0.7979
+0.68781 0.4485 0.570758
+0.64365 -0.740355 -0.193881
+-0.128117 0.116298 0.425729
+
+0.333696 0.512645 -0.791102
+0.681643 0.448465 0.578137
+0.65116 -0.732171 -0.19979
+-0.129299 0.116469 0.424475
+
+0.331576 0.524498 -0.784194
+0.6755 0.44828 0.585444
+0.658603 -0.723841 -0.205659
+-0.130481 0.11664 0.423197
+
+0.329248 0.536277 -0.777176
+0.669383 0.447948 0.59268
+0.665975 -0.715367 -0.211489
+-0.131663 0.11681 0.421895
+
+0.326714 0.547977 -0.770052
+0.663296 0.447468 0.599843
+0.673273 -0.706749 -0.217277
+-0.132845 0.116981 0.420568
+
+0.323975 0.559595 -0.76282
+0.657241 0.446842 0.606932
+0.680496 -0.697987 -0.223023
+-0.134027 0.117152 0.419218
+
+0.321032 0.571126 -0.755482
+0.651223 0.44607 0.613946
+0.687639 -0.689084 -0.228727
+-0.135209 0.117322 0.417843
+
+0.317887 0.582567 -0.74804
+0.645243 0.445155 0.620885
+0.694701 -0.680039 -0.234387
+-0.136391 0.117493 0.416444
+
+0.314542 0.593913 -0.740494
+0.639304 0.444098 0.627748
+0.701679 -0.670854 -0.240003
+-0.137573 0.117663 0.415021
+
+0.310997 0.60516 -0.732845
+0.633411 0.442899 0.634532
+0.70857 -0.66153 -0.245574
+-0.138755 0.117834 0.413573
+
+0.307255 0.616305 -0.725095
+0.627565 0.44156 0.641239
+0.715371 -0.652068 -0.2511
+-0.139937 0.118005 0.412102
+
+0.303318 0.627344 -0.717243
+0.62177 0.440083 0.647865
+0.722081 -0.642469 -0.256578
+-0.141119 0.118175 0.410606
+
+0.299186 0.638272 -0.709293
+0.616028 0.438468 0.654412
+0.728695 -0.632735 -0.26201
+-0.142301 0.118346 0.409086
+
+0.294863 0.649087 -0.701243
+0.610343 0.436719 0.660877
+0.735213 -0.622867 -0.267393
+-0.143483 0.118517 0.407542
+
+0.29035 0.659783 -0.693097
+0.604717 0.434835 0.66726
+0.74163 -0.612866 -0.272728
+-0.144665 0.118687 0.405974
+
+0.285648 0.670358 -0.684854
+0.599153 0.432819 0.67356
+0.747944 -0.602734 -0.278013
+-0.145847 0.118858 0.404381
+
+0.280761 0.680807 -0.676517
+0.593654 0.430673 0.679777
+0.754154 -0.592472 -0.283248
+-0.147029 0.119029 0.402765
+
+0.275691 0.691127 -0.668085
+0.588222 0.428398 0.685908
+0.760256 -0.582081 -0.288431
+-0.148211 0.119199 0.401124
+
+0.270439 0.701315 -0.65956
+0.582861 0.425996 0.691954
+0.766248 -0.571564 -0.293563
+-0.149393 0.11937 0.399459
+
+0.265009 0.711366 -0.650944
+0.577573 0.423469 0.697914
+0.772127 -0.560921 -0.298643
+-0.150575 0.119541 0.39777
+
+0.259402 0.721277 -0.642238
+0.57236 0.420819 0.703786
+0.777891 -0.550155 -0.303669
+-0.151758 0.119711 0.396056
+
+0.253621 0.731045 -0.633443
+0.567226 0.418048 0.709571
+0.783538 -0.539267 -0.308642
+-0.15294 0.119882 0.394319
+
+0.247669 0.740666 -0.624559
+0.562172 0.415158 0.715266
+0.789064 -0.528259 -0.31356
+-0.154122 0.120053 0.392557
+
+0.242405 0.748854 -0.616813
+0.559174 0.411709 0.719597
+0.79282 -0.51934 -0.318939
+-0.155205 0.120025 0.390868
+
+0.238742 0.75448 -0.61136
+0.559959 0.407397 0.721439
+0.793378 -0.514575 -0.325215
+-0.156057 0.119643 0.389368
+
+0.237198 0.756785 -0.609109
+0.565723 0.402112 0.719906
+0.789743 -0.515347 -0.33275
+-0.156609 0.118756 0.388122
+
+0.237592 0.756058 -0.609858
+0.575937 0.395928 0.715219
+0.782207 -0.52117 -0.341372
+-0.156853 0.117419 0.387133
+
+0.239718 0.753131 -0.612642
+0.589314 0.388603 0.708306
+0.771521 -0.530832 -0.350675
+-0.156891 0.115772 0.386324
+
+0.241913 0.749801 -0.615854
+0.603126 0.380994 0.700773
+0.760077 -0.540963 -0.360057
+-0.156886 0.114047 0.38553
+
+0.244027 0.746529 -0.618988
+0.616745 0.373103 0.693123
+0.748382 -0.550898 -0.369371
+-0.156882 0.112322 0.384712
+
+0.246062 0.743315 -0.622042
+0.630166 0.364933 0.685357
+0.73644 -0.560631 -0.378616
+-0.156877 0.110597 0.383869
+
+0.248022 0.740161 -0.625017
+0.643383 0.356491 0.677475
+0.724254 -0.570154 -0.38779
+-0.156872 0.108871 0.383003
+
+0.249908 0.73707 -0.627912
+0.656389 0.347779 0.66948
+0.711828 -0.579463 -0.396892
+-0.156868 0.107146 0.382112
+
+0.251724 0.734043 -0.630727
+0.669178 0.338804 0.661372
+0.699168 -0.588551 -0.40592
+-0.156863 0.105421 0.381197
+
+0.253472 0.731081 -0.63346
+0.681744 0.329571 0.653152
+0.686278 -0.597414 -0.414873
+-0.156859 0.103696 0.380258
+
+0.255156 0.728187 -0.636113
+0.694082 0.320084 0.644823
+0.673161 -0.606044 -0.42375
+-0.156854 0.101971 0.379294
+
+0.256778 0.725362 -0.638683
+0.706185 0.310349 0.636385
+0.659824 -0.614438 -0.432549
+-0.15685 0.100245 0.378307
+
+0.258341 0.722606 -0.641171
+0.718049 0.300372 0.627839
+0.64627 -0.622589 -0.441269
+-0.156845 0.0985202 0.377295
+
+0.259848 0.719922 -0.643577
+0.729668 0.290158 0.619187
+0.632505 -0.630492 -0.449908
+-0.156841 0.096795 0.376259
+
+0.261303 0.717311 -0.645899
+0.741037 0.279713 0.61043
+0.618534 -0.638142 -0.458464
+-0.156836 0.0950698 0.375199
+
+0.262708 0.714774 -0.648138
+0.75215 0.269042 0.60157
+0.604363 -0.645535 -0.466938
+-0.156832 0.0933446 0.374115
+
+0.264067 0.712311 -0.650293
+0.763003 0.258152 0.592608
+0.589996 -0.652664 -0.475326
+-0.156827 0.0916194 0.373007
+
+0.265382 0.709925 -0.652364
+0.773591 0.247049 0.583545
+0.575439 -0.659525 -0.483628
+-0.156823 0.0898941 0.371874
+
+0.266658 0.707615 -0.654351
+0.783908 0.235739 0.574382
+0.560698 -0.666114 -0.491843
+-0.156818 0.0881689 0.370717
+
+0.267114 0.705583 -0.656356
+0.793398 0.225565 0.565368
+0.546965 -0.671769 -0.499556
+-0.15687 0.0865726 0.369573
+
+0.264576 0.704458 -0.658589
+0.800628 0.22024 0.557216
+0.537582 -0.67471 -0.505738
+-0.157075 0.0853706 0.368448
+
+0.258688 0.704298 -0.661093
+0.805475 0.220491 0.550085
+0.533189 -0.674795 -0.510256
+-0.157463 0.0846317 0.367363
+
+0.248952 0.705192 -0.663872
+0.807781 0.226984 0.544029
+0.534334 -0.671701 -0.513133
+-0.158038 0.0843957 0.366333
+
+0.235364 0.706957 -0.666945
+0.807434 0.23973 0.539055
+0.540975 -0.665388 -0.514398
+-0.158804 0.084661 0.365359
+
+0.218248 0.709257 -0.670315
+0.80436 0.25821 0.535101
+0.552606 -0.655959 -0.514144
+-0.159756 0.0853834 0.364424
+
+0.19784 0.711762 -0.673984
+0.798388 0.281913 0.532073
+0.568715 -0.643366 -0.512488
+-0.160883 0.0865224 0.363523
+
+0.175326 0.714012 -0.677826
+0.790158 0.308652 0.529512
+0.587291 -0.628427 -0.510068
+-0.162135 0.0879543 0.362692
+
+0.151032 0.715775 -0.681803
+0.779577 0.337846 0.52737
+0.607823 -0.611167 -0.506977
+-0.163474 0.0896062 0.361883
+
+0.126793 0.716697 -0.685762
+0.767936 0.366667 0.525195
+0.627852 -0.593212 -0.503886
+-0.164813 0.0912581 0.36105
+
+0.102641 0.716782 -0.689702
+0.755248 0.395078 0.522986
+0.647353 -0.574575 -0.500797
+-0.166152 0.0929101 0.360192
+
+0.078603 0.716037 -0.693623
+0.741527 0.423041 0.520743
+0.666302 -0.555273 -0.497708
+-0.167491 0.094562 0.359311
+
+0.0547093 0.714468 -0.697526
+0.726791 0.450519 0.518467
+0.684677 -0.53532 -0.494621
+-0.16883 0.0962139 0.358405
+
+0.0309882 0.712085 -0.701409
+0.711055 0.477475 0.516157
+0.702453 -0.514735 -0.491535
+-0.170169 0.0978658 0.357475
+
+0.00746794 0.708896 -0.705273
+0.694339 0.503874 0.513814
+0.719609 -0.493536 -0.488451
+-0.171508 0.0995177 0.356521
+
+-0.0148007 0.704709 -0.709342
+0.677224 0.528991 0.511405
+0.735628 -0.472815 -0.485076
+-0.172943 0.101169 0.355557
+
+-0.0357923 0.699623 -0.713615
+0.659816 0.552852 0.508918
+0.750574 -0.452639 -0.48141
+-0.174475 0.102817 0.354581
+
+-0.0554881 0.693735 -0.71809
+0.642213 0.575484 0.50634
+0.764515 -0.433071 -0.477458
+-0.176104 0.10446 0.353593
+
+-0.0734221 0.687098 -0.722845
+0.62482 0.596611 0.503641
+0.777309 -0.41467 -0.473117
+-0.177876 0.106089 0.352605
+
+-0.0893401 0.679742 -0.72799
+0.607831 0.616233 0.500798
+0.789025 -0.397753 -0.468222
+-0.179839 0.107717 0.351623
+
+-0.103367 0.671772 -0.733511
+0.591254 0.634522 0.497795
+0.799833 -0.382236 -0.462777
+-0.181993 0.109342 0.35065
+
+-0.117069 0.663473 -0.738985
+0.574168 0.652355 0.494736
+0.810325 -0.366383 -0.457316
+-0.184147 0.110967 0.349652
+
+-0.130438 0.654856 -0.744412
+0.556584 0.669718 0.491622
+0.820488 -0.350201 -0.451839
+-0.186301 0.112593 0.34863
+
+-0.143466 0.645933 -0.749792
+0.538515 0.686598 0.488452
+0.830313 -0.333698 -0.446348
+-0.188456 0.114218 0.347584
+
+-0.156144 0.636714 -0.755125
+0.519974 0.702981 0.485227
+0.839789 -0.31688 -0.440842
+-0.19061 0.115843 0.346513
+
+-0.168466 0.627213 -0.760409
+0.500976 0.718853 0.481947
+0.848906 -0.299755 -0.435322
+-0.192764 0.117468 0.345418
+
+-0.180424 0.617442 -0.765646
+0.481535 0.734203 0.478612
+0.857654 -0.282332 -0.429788
+-0.194918 0.119093 0.3443
+
+-0.192012 0.607411 -0.770833
+0.461665 0.749019 0.475223
+0.866024 -0.264618 -0.424241
+-0.197073 0.120719 0.343157
+
+-0.203223 0.597135 -0.775971
+0.44138 0.763288 0.471779
+0.874004 -0.246622 -0.418681
+-0.199227 0.122344 0.341989
+
+-0.214052 0.586625 -0.781059
+0.420697 0.776998 0.468281
+0.881587 -0.228353 -0.41311
+-0.201381 0.123969 0.340798
+
+-0.224493 0.575894 -0.786097
+0.399631 0.79014 0.46473
+0.888762 -0.20982 -0.407526
+-0.203535 0.125594 0.339582
+
+-0.234541 0.564956 -0.791085
+0.378196 0.802703 0.461125
+0.895521 -0.191033 -0.40193
+-0.205689 0.12722 0.338343
+
+-0.244191 0.553823 -0.796022
+0.35641 0.814675 0.457467
+0.901855 -0.172002 -0.396324
+-0.207844 0.128845 0.337079
+
+-0.253439 0.542508 -0.800908
+0.334289 0.826049 0.453755
+0.907755 -0.152736 -0.390707
+-0.209998 0.13047 0.335791
+
+-0.262281 0.531025 -0.805742
+0.31185 0.836814 0.449992
+0.913213 -0.133246 -0.38508
+-0.212152 0.132095 0.334478
+
+-0.270714 0.519388 -0.810525
+0.289108 0.846962 0.446175
+0.918221 -0.113544 -0.379444
+-0.214306 0.133721 0.333142
+
+-0.278735 0.507609 -0.815255
+0.266082 0.856484 0.442306
+0.922771 -0.0936387 -0.373798
+-0.21646 0.135346 0.331781
+
+-0.286341 0.495702 -0.819932
+0.242789 0.865373 0.438386
+0.926856 -0.0735429 -0.368143
+-0.218615 0.136971 0.330396
+
+-0.29353 0.48368 -0.824556
+0.219247 0.873622 0.434414
+0.930468 -0.0532676 -0.36248
+-0.220769 0.138596 0.328987
+
+-0.300301 0.471558 -0.829127
+0.195472 0.881224 0.43039
+0.933601 -0.0328247 -0.356809
+-0.222923 0.140222 0.327554
+
+-0.30368 0.462147 -0.833186
+0.182623 0.886504 0.425159
+0.935108 -0.0230462 -0.353612
+-0.224833 0.14144 0.326115
+
+-0.303294 0.456114 -0.836644
+0.183996 0.889509 0.418234
+0.934964 -0.0270914 -0.353706
+-0.226407 0.14211 0.324631
+
+-0.299136 0.453764 -0.839414
+0.200933 0.889925 0.409463
+0.932815 -0.0461807 -0.357385
+-0.227617 0.142195 0.323122
+
+-0.29236 0.454167 -0.841581
+0.229086 0.887668 0.399455
+0.928464 -0.0760094 -0.363562
+-0.228574 0.14188 0.321615
+
+-0.285231 0.455083 -0.84353
+0.259346 0.883904 0.38917
+0.922704 -0.107763 -0.37014
+-0.229479 0.141485 0.320076
+
+-0.278295 0.455947 -0.845378
+0.289491 0.879036 0.378801
+0.915831 -0.13931 -0.376624
+-0.230383 0.14109 0.318512
+
+-0.271551 0.456773 -0.847124
+0.319479 0.873069 0.368352
+0.907851 -0.170612 -0.383013
+-0.231287 0.140694 0.316924
+
+-0.264994 0.457573 -0.848767
+0.34927 0.86601 0.357823
+0.898771 -0.201628 -0.389304
+-0.232192 0.140299 0.315312
+
+-0.25862 0.458359 -0.850307
+0.378821 0.857867 0.347216
+0.8886 -0.232317 -0.395498
+-0.233096 0.139904 0.313675
+
+-0.252423 0.459145 -0.851744
+0.408093 0.848649 0.336534
+0.87735 -0.262642 -0.401593
+-0.234 0.139508 0.312015
+
+-0.246398 0.459941 -0.853078
+0.437045 0.838368 0.325777
+0.865032 -0.292563 -0.407587
+-0.234904 0.139113 0.31033
+
+-0.240538 0.46076 -0.854308
+0.465636 0.827037 0.314948
+0.85166 -0.32204 -0.413481
+-0.235809 0.138718 0.308621
+
+-0.234837 0.461612 -0.855433
+0.493828 0.814671 0.304048
+0.837249 -0.351036 -0.419272
+-0.236713 0.138322 0.306888
+
+-0.229286 0.462508 -0.856454
+0.521582 0.801284 0.293079
+0.821815 -0.379512 -0.424959
+-0.237617 0.137927 0.305131
+
+-0.224827 0.464736 -0.856431
+0.542954 0.789585 0.285929
+0.809107 -0.400718 -0.42985
+-0.238088 0.137587 0.303711
+
+-0.221166 0.468896 -0.855115
+0.55689 0.780536 0.283967
+0.800599 -0.413402 -0.433751
+-0.237986 0.137293 0.302746
+
+-0.218363 0.475308 -0.852291
+0.562491 0.774991 0.288085
+0.797447 -0.416499 -0.436586
+-0.237214 0.137062 0.30232
+
+-0.216344 0.484016 -0.847894
+0.560016 0.772908 0.29832
+0.799736 -0.410294 -0.438271
+-0.235766 0.136882 0.302428
+
+-0.215186 0.494484 -0.842129
+0.550954 0.773461 0.31338
+0.806315 -0.396539 -0.438876
+-0.233777 0.136757 0.302947
+
+-0.215066 0.505768 -0.835431
+0.537708 0.775432 0.331022
+0.81524 -0.378026 -0.438725
+-0.231497 0.136661 0.303689
+
+-0.215338 0.517012 -0.828449
+0.524338 0.776904 0.348553
+0.823832 -0.359331 -0.438386
+-0.229218 0.136566 0.304407
+
+-0.216003 0.528201 -0.821186
+0.51086 0.777875 0.365967
+0.832084 -0.340461 -0.43786
+-0.226939 0.13647 0.305101
+
+-0.21706 0.539322 -0.813644
+0.49729 0.778342 0.383258
+0.839993 -0.321427 -0.437146
+-0.22466 0.136375 0.305771
+
+-0.218509 0.550362 -0.805826
+0.483642 0.778303 0.400419
+0.847552 -0.302236 -0.436244
+-0.22238 0.136279 0.306416
+
+-0.220351 0.561306 -0.797735
+0.469932 0.777756 0.417444
+0.854757 -0.282897 -0.435155
+-0.220101 0.136184 0.307038
+
+-0.222584 0.572142 -0.789373
+0.456176 0.776701 0.434326
+0.861603 -0.263419 -0.433879
+-0.217822 0.136088 0.307635
+
+-0.225207 0.582856 -0.780744
+0.442391 0.775135 0.45106
+0.868085 -0.243812 -0.432416
+-0.215543 0.135992 0.308208
+
+-0.228218 0.593434 -0.77185
+0.428592 0.77306 0.46764
+0.8742 -0.224084 -0.430767
+-0.213263 0.135897 0.308757
+
+-0.231615 0.603863 -0.762695
+0.414794 0.770476 0.484059
+0.879943 -0.204246 -0.428933
+-0.210984 0.135801 0.309281
+
+-0.235395 0.61413 -0.753282
+0.401014 0.767382 0.500312
+0.885312 -0.184306 -0.426913
+-0.208705 0.135706 0.309782
+
+-0.239554 0.624221 -0.743615
+0.387269 0.763782 0.516392
+0.890302 -0.164275 -0.424708
+-0.206426 0.13561 0.310258
+
+-0.244089 0.634122 -0.733696
+0.373573 0.759675 0.532294
+0.89491 -0.144161 -0.422319
+-0.204146 0.135514 0.31071
+
+-0.248997 0.643821 -0.72353
+0.359943 0.755066 0.548012
+0.899134 -0.123976 -0.419748
+-0.201867 0.135419 0.311138
+
+-0.254272 0.653305 -0.713119
+0.346395 0.749956 0.56354
+0.902971 -0.103729 -0.416994
+-0.199588 0.135323 0.311542
+
+-0.259909 0.662559 -0.702469
+0.332945 0.744349 0.578872
+0.906419 -0.0834292 -0.414059
+-0.197309 0.135228 0.311921
+
+-0.268702 0.668737 -0.693246
+0.319552 0.740844 0.590794
+0.908673 -0.0627805 -0.412762
+-0.194904 0.134723 0.312371
+
+-0.27864 0.671707 -0.686418
+0.306614 0.739539 0.599225
+0.910136 -0.0434971 -0.41202
+-0.192738 0.133913 0.312882
+
+-0.290101 0.671185 -0.682167
+0.29338 0.740873 0.604182
+0.910917 -0.0248611 -0.41184
+-0.190921 0.132811 0.313516
+
+-0.303026 0.66727 -0.680387
+0.279915 0.744784 0.60576
+0.910946 -0.00688984 -0.412468
+-0.189474 0.131379 0.314304
+
+-0.317476 0.659585 -0.68129
+0.266127 0.751559 0.603602
+0.910157 0.01032 -0.414135
+-0.188459 0.129579 0.31527
+
+-0.329685 0.650936 -0.683805
+0.252306 0.758705 0.60059
+0.909752 0.025477 -0.414369
+-0.188185 0.127823 0.316356
+
+-0.339519 0.641415 -0.687978
+0.238507 0.766228 0.596665
+0.909858 0.0384915 -0.413131
+-0.188657 0.126107 0.31755
+
+-0.347212 0.631037 -0.693712
+0.224577 0.77416 0.591813
+0.910499 0.0496932 -0.410514
+-0.189833 0.124425 0.318833
+
+-0.353394 0.619728 -0.70075
+0.210023 0.782523 0.58613
+0.911594 0.0599616 -0.406696
+-0.191634 0.122773 0.320218
+
+-0.358672 0.607386 -0.708828
+0.194369 0.791303 0.579707
+0.913003 0.0701504 -0.401875
+-0.193933 0.121162 0.321687
+
+-0.363067 0.593992 -0.717882
+0.177574 0.800445 0.572499
+0.914686 0.080378 -0.396093
+-0.196604 0.119616 0.32317
+
+-0.367087 0.580502 -0.726818
+0.160596 0.809186 0.565178
+0.916218 0.0907459 -0.390268
+-0.199274 0.118069 0.324628
+
+-0.370729 0.566925 -0.735633
+0.143442 0.817523 0.557746
+0.917597 0.101252 -0.384401
+-0.201945 0.116523 0.326062
+
+-0.373991 0.553273 -0.744325
+0.126124 0.825451 0.550203
+0.918816 0.111893 -0.378492
+-0.204616 0.114977 0.327472
+
+-0.37687 0.539555 -0.752894
+0.108652 0.832966 0.542552
+0.919872 0.122668 -0.372544
+-0.207287 0.113431 0.328857
+
+-0.379365 0.525783 -0.761337
+0.0910347 0.840066 0.534792
+0.920758 0.133573 -0.366556
+-0.209957 0.111884 0.330219
+
+-0.37961 0.513644 -0.769459
+0.0791384 0.846695 0.52616
+0.921756 0.138842 -0.362063
+-0.2125 0.110078 0.331531
+
+-0.377106 0.503831 -0.777139
+0.0753685 0.853 0.51644
+0.923098 0.136181 -0.359645
+-0.214869 0.107929 0.332815
+
+-0.372068 0.496317 -0.784369
+0.0799169 0.859029 0.50565
+0.924759 0.125452 -0.359282
+-0.21706 0.105441 0.334072
+
+-0.367118 0.488672 -0.79147
+0.0845723 0.864895 0.494778
+0.926322 0.114706 -0.358847
+-0.219252 0.102953 0.335305
+
+-0.362259 0.480897 -0.79844
+0.0893323 0.870594 0.483824
+0.927787 0.103943 -0.35834
+-0.221443 0.100465 0.336513
+
+-0.357492 0.472995 -0.805279
+0.0941947 0.876125 0.472791
+0.929154 0.0931663 -0.357762
+-0.223634 0.0979768 0.337698
+
+-0.352821 0.464969 -0.811986
+0.099157 0.881486 0.461681
+0.930422 0.0823768 -0.357112
+-0.225825 0.0954886 0.338858
+
+-0.348247 0.45682 -0.818559
+0.104217 0.886675 0.450496
+0.931592 0.0715764 -0.35639
+-0.228017 0.0930004 0.339994
+
+-0.343773 0.448552 -0.824998
+0.109371 0.891689 0.439237
+0.932662 0.0607667 -0.355597
+-0.230208 0.0905122 0.341106
+
+-0.339401 0.440166 -0.831301
+0.114618 0.896526 0.427906
+0.933632 0.0499495 -0.354733
+-0.232399 0.0880241 0.342194
+
+-0.335133 0.431666 -0.837466
+0.119955 0.901184 0.416506
+0.934503 0.0391265 -0.353798
+-0.234591 0.0855359 0.343258
+
+-0.330972 0.423054 -0.843494
+0.125379 0.905662 0.405038
+0.935274 0.0282995 -0.352791
+-0.236782 0.0830477 0.344297
+
+-0.326919 0.414333 -0.849383
+0.130888 0.909958 0.393504
+0.935945 0.01747 -0.351714
+-0.238973 0.0805596 0.345312
+
+-0.322977 0.405505 -0.855133
+0.136478 0.914069 0.381906
+0.936515 0.00664 -0.350566
+-0.241165 0.0780714 0.346303
+
+-0.319147 0.396573 -0.860741
+0.142147 0.917993 0.370246
+0.936984 -0.00418893 -0.349347
+-0.243356 0.0755832 0.34727
+
+-0.315432 0.387541 -0.866207
+0.147893 0.92173 0.358526
+0.937353 -0.015015 -0.348058
+-0.245547 0.073095 0.348213
+
+-0.311834 0.37841 -0.87153
+0.153712 0.925277 0.346748
+0.93762 -0.0258365 -0.346699
+-0.247739 0.0706069 0.349131
+
+-0.308354 0.369184 -0.87671
+0.159601 0.928633 0.334914
+0.937787 -0.0366517 -0.34527
+-0.24993 0.0681187 0.350025
+
+-0.304995 0.359866 -0.881745
+0.165558 0.931796 0.323027
+0.937853 -0.0474589 -0.343772
+-0.252121 0.0656305 0.350895
+
+-0.301757 0.350458 -0.886635
+0.17158 0.934765 0.311087
+0.937818 -0.0582562 -0.342203
+-0.254312 0.0631424 0.351741
+
+-0.298643 0.340964 -0.891379
+0.177663 0.937538 0.299097
+0.937682 -0.069042 -0.340566
+-0.256504 0.0606542 0.352563
+
+-0.295655 0.331387 -0.895975
+0.183805 0.940113 0.287059
+0.937445 -0.0798145 -0.33886
+-0.258695 0.058166 0.353361
+
+-0.292794 0.321729 -0.900423
+0.190003 0.94249 0.274976
+0.937107 -0.090572 -0.337085
+-0.260886 0.0556778 0.354134
+
+-0.290062 0.311994 -0.904723
+0.196253 0.944667 0.262848
+0.936669 -0.101313 -0.335242
+-0.263078 0.0531897 0.354883
+
+-0.28746 0.302185 -0.908873
+0.202553 0.946643 0.250679
+0.93613 -0.112035 -0.333331
+-0.265269 0.0507015 0.355608
+
+-0.28499 0.292305 -0.912874
+0.208899 0.948416 0.23847
+0.93549 -0.122737 -0.331352
+-0.26746 0.0482133 0.356309
+
+-0.282653 0.282358 -0.916723
+0.215289 0.949986 0.226223
+0.93475 -0.133417 -0.329305
+-0.269652 0.0457252 0.356985
+
+-0.280451 0.272345 -0.920421
+0.221718 0.951352 0.213941
+0.93391 -0.144074 -0.327191
+-0.271843 0.043237 0.357638
+
+-0.278991 0.262288 -0.92378
+0.222757 0.953413 0.203426
+0.9341 -0.149025 -0.32442
+-0.273836 0.0408039 0.358475
+
+-0.278833 0.252179 -0.926638
+0.212712 0.957157 0.196478
+0.936486 -0.142322 -0.320528
+-0.275427 0.0384417 0.359693
+
+-0.279551 0.242186 -0.929084
+0.192336 0.962175 0.19294
+0.940669 -0.12476 -0.315558
+-0.276639 0.0361987 0.361277
+
+-0.28109 0.232126 -0.931185
+0.162111 0.967848 0.192329
+0.94589 -0.0968939 -0.309682
+-0.277523 0.0340301 0.363182
+
+-0.28244 0.222153 -0.933207
+0.129838 0.972716 0.192262
+0.950458 -0.066863 -0.303578
+-0.278343 0.0318856 0.365132
+
+-0.283436 0.212304 -0.935196
+0.0974171 0.976517 0.19216
+0.95403 -0.036639 -0.297462
+-0.279163 0.029741 0.367058
+
+-0.284086 0.20259 -0.937151
+0.0648842 0.979244 0.192021
+0.956601 -0.00625577 -0.291335
+-0.279983 0.0275965 0.36896
+
+-0.284683 0.194509 -0.938681
+0.0364446 0.980687 0.19216
+0.957929 0.0204949 -0.286274
+-0.280635 0.0253554 0.370828
+
+-0.285788 0.190211 -0.939226
+0.0192841 0.981046 0.192813
+0.958099 0.0369914 -0.284039
+-0.280897 0.0228399 0.372714
+
+-0.2876 0.1896 -0.938796
+0.0135443 0.980916 0.193957
+0.957655 0.0430668 -0.28468
+-0.280779 0.0200481 0.374629
+
+-0.290203 0.19267 -0.937369
+0.0192183 0.980498 0.195586
+0.956772 0.0387449 -0.288246
+-0.280274 0.0169804 0.376563
+
+-0.29317 0.197639 -0.935409
+0.0301464 0.979824 0.197575
+0.955585 0.0297237 -0.293213
+-0.27956 0.0137908 0.378461
+
+-0.296058 0.202676 -0.93342
+0.0410755 0.979026 0.199551
+0.954286 0.0207378 -0.298173
+-0.278845 0.0106012 0.380335
+
+-0.298866 0.207781 -0.9314
+0.0520041 0.978104 0.201513
+0.952877 0.0117886 -0.303127
+-0.278131 0.00741154 0.382185
+
+-0.301593 0.212952 -0.929351
+0.0629307 0.977058 0.203461
+0.951358 0.00287774 -0.308075
+-0.277417 0.00422193 0.38401
+
+-0.304237 0.218188 -0.927272
+0.0738537 0.975888 0.205396
+0.949729 -0.00599335 -0.313015
+-0.276702 0.00103232 0.385812
+
+-0.306798 0.223488 -0.925164
+0.0847717 0.974594 0.207317
+0.947992 -0.0148232 -0.317949
+-0.275988 -0.00215729 0.387589
+
+-0.309274 0.228851 -0.923026
+0.0956832 0.973175 0.209225
+0.946147 -0.0236102 -0.322875
+-0.275273 -0.00534691 0.389342
+
+-0.311665 0.234275 -0.920858
+0.106587 0.971632 0.211118
+0.944195 -0.032353 -0.327794
+-0.274559 -0.00853652 0.391071
+
+-0.313969 0.23976 -0.918661
+0.117481 0.969964 0.212998
+0.942137 -0.0410502 -0.332705
+-0.273845 -0.0117261 0.392775
+
+-0.316185 0.245303 -0.916435
+0.128363 0.968172 0.214863
+0.939973 -0.0497002 -0.337609
+-0.27313 -0.0149157 0.394455
+
+-0.318312 0.250903 -0.91418
+0.139234 0.966255 0.216715
+0.937705 -0.0583017 -0.342505
+-0.272416 -0.0181054 0.396112
+
+-0.32035 0.25656 -0.911895
+0.15009 0.964214 0.218552
+0.935333 -0.0668532 -0.347393
+-0.271702 -0.021295 0.397744
+
+-0.322297 0.262271 -0.909582
+0.160931 0.962048 0.220376
+0.932859 -0.0753534 -0.352273
+-0.270987 -0.0244846 0.399351
+
+-0.324152 0.268035 -0.907239
+0.171755 0.959757 0.222184
+0.930283 -0.0838008 -0.357144
+-0.270273 -0.0276742 0.400935
+
+-0.325915 0.273852 -0.904867
+0.18256 0.957343 0.223979
+0.927605 -0.0921941 -0.362007
+-0.269559 -0.0308638 0.402495
+
+-0.327584 0.279719 -0.902467
+0.193345 0.954804 0.225759
+0.924828 -0.100532 -0.366861
+-0.268844 -0.0340534 0.40403
+
+-0.329159 0.285635 -0.900037
+0.204108 0.952141 0.227525
+0.921951 -0.108813 -0.371706
+-0.26813 -0.037243 0.405541
+
+-0.330638 0.291599 -0.897579
+0.214848 0.949354 0.229276
+0.918977 -0.117036 -0.376542
+-0.267416 -0.0404326 0.407028
+
+-0.332021 0.297609 -0.895093
+0.225564 0.946443 0.231013
+0.915906 -0.125199 -0.381369
+-0.266701 -0.0436222 0.40849
+
+-0.333307 0.303663 -0.892578
+0.236253 0.943408 0.232735
+0.912738 -0.133302 -0.386186
+-0.265987 -0.0468119 0.409929
+
+-0.334496 0.309761 -0.890034
+0.246915 0.94025 0.234442
+0.909475 -0.141343 -0.390994
+-0.265273 -0.0500015 0.411343
+
+-0.335586 0.315901 -0.887462
+0.257547 0.936969 0.236134
+0.906119 -0.14932 -0.395793
+-0.264558 -0.0531911 0.412733
+
+-0.336576 0.322081 -0.884862
+0.268149 0.933564 0.237812
+0.90267 -0.157233 -0.400581
+-0.263844 -0.0563807 0.414099
+
+-0.337466 0.3283 -0.882233
+0.278718 0.930036 0.239475
+0.899129 -0.16508 -0.405359
+-0.263129 -0.0595703 0.415441
+
+-0.338256 0.334556 -0.879577
+0.289254 0.926386 0.241123
+0.895497 -0.17286 -0.410127
+-0.262415 -0.0627599 0.416759
+
+-0.338944 0.340847 -0.876892
+0.299755 0.922614 0.242756
+0.891776 -0.180572 -0.414885
+-0.261701 -0.0659495 0.418052
+
+-0.338589 0.348025 -0.874206
+0.309607 0.918555 0.245766
+0.888539 -0.187447 -0.418763
+-0.261081 -0.0687217 0.419527
+
+-0.33698 0.356162 -0.871546
+0.318348 0.914269 0.250533
+0.886058 -0.19303 -0.421474
+-0.260591 -0.0709582 0.42125
+
+-0.333985 0.36533 -0.8689
+0.325666 0.909789 0.257343
+0.884531 -0.197023 -0.422832
+-0.260259 -0.0726189 0.423215
+
+-0.329636 0.375379 -0.866274
+0.330798 0.905314 0.26642
+0.884258 -0.19874 -0.422598
+-0.260113 -0.0736649 0.425422
+
+-0.323963 0.386338 -0.863592
+0.334239 0.900694 0.277552
+0.88506 -0.19873 -0.420921
+-0.260125 -0.0741353 0.427873
+
+-0.317637 0.397629 -0.860813
+0.336464 0.896016 0.289736
+0.886509 -0.197602 -0.418396
+-0.260225 -0.0743092 0.43044
+
+-0.311243 0.408843 -0.85789
+0.338592 0.891195 0.301873
+0.887966 -0.196519 -0.415809
+-0.260326 -0.0744831 0.432983
+
+-0.304782 0.419979 -0.854825
+0.340622 0.88623 0.313962
+0.889429 -0.195483 -0.413161
+-0.260427 -0.0746569 0.435502
+
+-0.298256 0.431035 -0.851617
+0.342553 0.881125 0.326
+0.890899 -0.194493 -0.410453
+-0.260528 -0.0748308 0.437996
+
+-0.291667 0.442009 -0.848268
+0.344383 0.875881 0.337985
+0.892374 -0.19355 -0.407685
+-0.260628 -0.0750047 0.440467
+
+-0.285015 0.452899 -0.844778
+0.34611 0.870498 0.349916
+0.893854 -0.192655 -0.404858
+-0.260729 -0.0751786 0.442913
+
+-0.278302 0.463704 -0.841146
+0.347734 0.864979 0.361791
+0.895337 -0.191809 -0.401971
+-0.26083 -0.0753525 0.445335
+
+-0.27153 0.474421 -0.837375
+0.349254 0.859325 0.373607
+0.896824 -0.191012 -0.399026
+-0.260931 -0.0755264 0.447733
+
+-0.264699 0.485048 -0.833464
+0.350669 0.853538 0.385362
+0.898313 -0.190264 -0.396022
+-0.261031 -0.0757003 0.450107
+
+-0.257813 0.495585 -0.829414
+0.351976 0.84762 0.397056
+0.899803 -0.189568 -0.392961
+-0.261132 -0.0758742 0.452456
+
+-0.250871 0.506028 -0.825226
+0.353176 0.841572 0.408685
+0.901294 -0.188922 -0.389843
+-0.261233 -0.0760481 0.454782
+
+-0.243876 0.516377 -0.820901
+0.354266 0.835396 0.420248
+0.902784 -0.188329 -0.386668
+-0.261334 -0.076222 0.457083
+
+-0.23683 0.52663 -0.816439
+0.355247 0.829094 0.431744
+0.904274 -0.187787 -0.383438
+-0.261434 -0.0763958 0.45936
+
+-0.229733 0.536784 -0.811841
+0.356116 0.822668 0.44317
+0.905762 -0.187299 -0.380151
+-0.261535 -0.0765697 0.461612
+
+-0.222588 0.546838 -0.807107
+0.356873 0.816119 0.454524
+0.907246 -0.186864 -0.37681
+-0.261636 -0.0767436 0.463841
+
+-0.215396 0.556791 -0.802239
+0.357517 0.809449 0.465804
+0.908728 -0.186482 -0.373414
+-0.261737 -0.0769175 0.466046
+
+-0.208158 0.566641 -0.797238
+0.358048 0.802661 0.477009
+0.910204 -0.186156 -0.369965
+-0.261837 -0.0770914 0.468226
+
+-0.200877 0.576386 -0.792103
+0.358463 0.795755 0.488137
+0.911676 -0.185884 -0.366462
+-0.261938 -0.0772653 0.470382
+
+-0.193554 0.586025 -0.786836
+0.358762 0.788735 0.499187
+0.913141 -0.185668 -0.362906
+-0.262039 -0.0774392 0.472514
+
+-0.186191 0.595556 -0.781439
+0.358945 0.781601 0.510155
+0.914599 -0.185507 -0.359299
+-0.26214 -0.0776131 0.474621
+
+-0.178789 0.604977 -0.77591
+0.35901 0.774356 0.521041
+0.916049 -0.185404 -0.355639
+-0.26224 -0.077787 0.476705
+
+-0.17135 0.614288 -0.770253
+0.358957 0.767003 0.531843
+0.91749 -0.185357 -0.351929
+-0.262341 -0.0779609 0.478764
+
+-0.163876 0.623487 -0.764467
+0.358785 0.759542 0.542558
+0.918922 -0.185367 -0.348169
+-0.262442 -0.0781348 0.480799
+
+-0.156369 0.632571 -0.758553
+0.358493 0.751976 0.553186
+0.920343 -0.185435 -0.344358
+-0.262543 -0.0783086 0.48281
+
+-0.148831 0.641541 -0.752513
+0.358081 0.744307 0.563724
+0.921752 -0.185561 -0.340499
+-0.262643 -0.0784825 0.484797
+
+-0.141262 0.650394 -0.746347
+0.357548 0.736537 0.574172
+0.923149 -0.185746 -0.336591
+-0.262744 -0.0786564 0.48676
+
+-0.133666 0.659129 -0.740056
+0.356892 0.728668 0.584526
+0.924533 -0.185989 -0.332636
+-0.262845 -0.0788303 0.488698
+
+-0.126043 0.667744 -0.733642
+0.356115 0.720703 0.594785
+0.925903 -0.186292 -0.328633
+-0.262946 -0.0790042 0.490612
+
+-0.118396 0.67624 -0.727105
+0.355214 0.712643 0.604949
+0.927257 -0.186654 -0.324584
+-0.263046 -0.0791781 0.492502
+
+-0.110727 0.684613 -0.720447
+0.35419 0.704491 0.615014
+0.928595 -0.187077 -0.320489
+-0.263147 -0.079352 0.494368
+
+-0.103036 0.692864 -0.713669
+0.353042 0.696248 0.62498
+0.929917 -0.187559 -0.316349
+-0.263248 -0.0795259 0.49621
+
+-0.0953275 0.70099 -0.706771
+0.351769 0.687918 0.634845
+0.93122 -0.188102 -0.312164
+-0.263349 -0.0796998 0.498027
+
+-0.0876016 0.708991 -0.699755
+0.350372 0.679501 0.644607
+0.932505 -0.188706 -0.307936
+-0.263449 -0.0798737 0.49982
+
+-0.0798606 0.716865 -0.692623
+0.348849 0.671001 0.654264
+0.93377 -0.189371 -0.303664
+-0.26355 -0.0800475 0.501589
+
+-0.0721064 0.724612 -0.685374
+0.3472 0.66242 0.663816
+0.935015 -0.190097 -0.29935
+-0.263651 -0.0802214 0.503334
+
+-0.0643409 0.732231 -0.678011
+0.345426 0.65376 0.67326
+0.936238 -0.190884 -0.294995
+-0.263752 -0.0803953 0.505055
+
+-0.056566 0.739719 -0.670534
+0.343525 0.645022 0.682596
+0.937439 -0.191733 -0.290598
+-0.263852 -0.0805692 0.506751
+
+-0.0487837 0.747077 -0.662945
+0.341497 0.636211 0.691821
+0.938616 -0.192644 -0.286161
+-0.263953 -0.0807431 0.508424
+
+-0.0409958 0.754303 -0.655245
+0.339343 0.627327 0.700933
+0.939769 -0.193617 -0.281685
+-0.264054 -0.080917 0.510072
+
+-0.0332042 0.761397 -0.647435
+0.337061 0.618373 0.709933
+0.940897 -0.194653 -0.27717
+-0.264155 -0.0810909 0.511696
+
+-0.025411 0.768357 -0.639517
+0.334653 0.609352 0.718817
+0.941999 -0.19575 -0.272617
+-0.264255 -0.0812648 0.513296
+
+-0.0176179 0.775183 -0.631492
+0.332117 0.600265 0.727585
+0.943074 -0.19691 -0.268027
+-0.264356 -0.0814387 0.514871
+
+-0.00982712 0.781873 -0.62336
+0.329453 0.591116 0.736235
+0.944121 -0.198133 -0.2634
+-0.264457 -0.0816126 0.516423
+
+-0.00204042 0.788427 -0.615125
+0.326662 0.581906 0.744766
+0.945139 -0.199418 -0.258737
+-0.264558 -0.0817865 0.51795
+
+0.0057402 0.794845 -0.606786
+0.323744 0.572638 0.753177
+0.946127 -0.200767 -0.254039
+-0.264658 -0.0819603 0.519453
+
+0.0135128 0.801125 -0.598345
+0.320698 0.563315 0.761465
+0.947085 -0.202178 -0.249307
+-0.264759 -0.0821342 0.520932
+
+0.0212753 0.807267 -0.589803
+0.317525 0.553938 0.769631
+0.948011 -0.203651 -0.244542
+-0.26486 -0.0823081 0.522386
+
+0.0290259 0.813269 -0.581163
+0.314224 0.54451 0.777671
+0.948905 -0.205188 -0.239744
+-0.26496 -0.082482 0.523817
+
+0.0367626 0.819133 -0.572425
+0.310796 0.535034 0.785586
+0.949765 -0.206787 -0.234914
+-0.265061 -0.0826559 0.525223
+
+0.0444833 0.824856 -0.563591
+0.307241 0.525511 0.793373
+0.950592 -0.20845 -0.230053
+-0.265162 -0.0828298 0.526605
+
+0.0521861 0.830438 -0.554662
+0.303559 0.515945 0.801032
+0.951383 -0.210175 -0.225161
+-0.265263 -0.0830037 0.527963
+
+0.0598691 0.835879 -0.545639
+0.29975 0.506338 0.808562
+0.952137 -0.211963 -0.22024
+-0.265363 -0.0831776 0.529297
+
+0.0675303 0.841178 -0.536525
+0.295814 0.496692 0.81596
+0.952855 -0.213814 -0.215291
+-0.265464 -0.0833515 0.530607
+
+0.0751676 0.846335 -0.52732
+0.291753 0.48701 0.823226
+0.953536 -0.215727 -0.210313
+-0.265565 -0.0835254 0.531892
+
+0.0827792 0.85135 -0.518026
+0.287566 0.477294 0.83036
+0.954177 -0.217703 -0.205309
+-0.265666 -0.0836992 0.533153
+
+0.090363 0.856221 -0.508645
+0.283253 0.467546 0.837358
+0.954779 -0.219741 -0.200278
+-0.265766 -0.0838731 0.53439
+
+0.0979171 0.860949 -0.499178
+0.278815 0.45777 0.844221
+0.95534 -0.221842 -0.195222
+-0.265867 -0.084047 0.535603
+
+0.10544 0.865533 -0.489627
+0.274252 0.447967 0.850947
+0.95586 -0.224005 -0.190141
+-0.265968 -0.0842209 0.536792
+
+0.112928 0.869973 -0.479993
+0.269565 0.43814 0.857536
+0.956338 -0.22623 -0.185036
+-0.266069 -0.0843948 0.537956
+
+0.120381 0.874269 -0.470278
+0.264755 0.428291 0.863986
+0.956772 -0.228516 -0.179909
+-0.266169 -0.0845687 0.539096
+
+0.127797 0.878421 -0.460483
+0.259821 0.418424 0.870296
+0.957163 -0.230864 -0.174759
+-0.26627 -0.0847426 0.540212
+
+0.135173 0.882428 -0.45061
+0.254765 0.40854 0.876465
+0.957509 -0.233274 -0.169588
+-0.266371 -0.0849165 0.541304
+
+0.142507 0.88629 -0.440661
+0.249587 0.398641 0.882492
+0.957809 -0.235745 -0.164397
+-0.266472 -0.0850904 0.542372
+
+0.149798 0.890007 -0.430637
+0.244288 0.388731 0.888376
+0.958063 -0.238277 -0.159186
+-0.266572 -0.0852643 0.543415
+
+0.157044 0.893579 -0.42054
+0.238867 0.378812 0.894116
+0.958269 -0.240869 -0.153957
+-0.266673 -0.0854381 0.544435
+
+0.164242 0.897006 -0.410371
+0.233327 0.368886 0.899712
+0.958427 -0.243522 -0.148709
+-0.266774 -0.085612 0.54543
+
+0.171392 0.900288 -0.400132
+0.227668 0.358956 0.905162
+0.958536 -0.246234 -0.143445
+-0.266875 -0.0857859 0.546401
+
+0.17849 0.903426 -0.389825
+0.221891 0.349024 0.910465
+0.958596 -0.249007 -0.138165
+-0.266975 -0.0859598 0.547348
+
+0.185534 0.906418 -0.379452
+0.215995 0.339092 0.915621
+0.958605 -0.251839 -0.132869
+-0.267076 -0.0861337 0.54827
+
+0.192524 0.909265 -0.369013
+0.209983 0.329164 0.920629
+0.958562 -0.25473 -0.127559
+-0.267177 -0.0863076 0.549169
+
+0.199457 0.911968 -0.358512
+0.203856 0.319241 0.925488
+0.958467 -0.25768 -0.122235
+-0.267278 -0.0864815 0.550043
+
+0.206331 0.914527 -0.347949
+0.197613 0.309326 0.930197
+0.95832 -0.260688 -0.116899
+-0.267378 -0.0866554 0.550893
+
+0.213145 0.916941 -0.337326
+0.191256 0.299422 0.934755
+0.958118 -0.263754 -0.111551
+-0.267479 -0.0868293 0.551719
+
+0.219896 0.919211 -0.326646
+0.184787 0.28953 0.939162
+0.957862 -0.266878 -0.106192
+-0.26758 -0.0870032 0.55252
+
+0.226582 0.921337 -0.315909
+0.178205 0.279654 0.943417
+0.957551 -0.270059 -0.100822
+-0.267681 -0.0871771 0.553298
+
+0.233203 0.92332 -0.305117
+0.171513 0.269795 0.94752
+0.957183 -0.273296 -0.0954443
+-0.267781 -0.0873509 0.554051
+
+0.239755 0.92516 -0.294273
+0.164711 0.259957 0.951469
+0.956759 -0.27659 -0.0900578
+-0.267882 -0.0875248 0.55478
+
+0.246238 0.926857 -0.283378
+0.1578 0.25014 0.955264
+0.956277 -0.279939 -0.0846639
+-0.267983 -0.0876987 0.555485
+
+0.252648 0.928412 -0.272433
+0.150781 0.240349 0.958904
+0.955737 -0.283343 -0.0792635
+-0.268084 -0.0878726 0.556166
+
+0.258986 0.929825 -0.261441
+0.143657 0.230585 0.962389
+0.955138 -0.286803 -0.0738575
+-0.268184 -0.0880465 0.556822
+
+0.265247 0.931097 -0.250404
+0.136427 0.22085 0.965719
+0.95448 -0.290316 -0.0684468
+-0.268285 -0.0882204 0.557455
+
+0.271432 0.932228 -0.239322
+0.129093 0.211147 0.968892
+0.953761 -0.293883 -0.0630322
+-0.268386 -0.0883943 0.558063
+
+0.277538 0.933219 -0.228198
+0.121657 0.201478 0.971908
+0.952981 -0.297504 -0.0576146
+-0.268487 -0.0885682 0.558647
+
+0.283564 0.93407 -0.217035
+0.114119 0.191846 0.974768
+0.952139 -0.301177 -0.0521949
+-0.268587 -0.0887421 0.559207
+
+0.289507 0.934783 -0.205832
+0.106482 0.182253 0.977469
+0.951235 -0.304902 -0.046774
+-0.268688 -0.088916 0.559742
+
+0.30059 0.93341 -0.195938
+0.101288 0.173035 0.979694
+0.94836 -0.314332 -0.0425304
+-0.268654 -0.0893457 0.560497
+
+0.316784 0.929807 -0.187367
+0.0984063 0.164257 0.981497
+0.943379 -0.329361 -0.039465
+-0.268485 -0.0900341 0.561466
+
+0.337988 0.923756 -0.180107
+0.0976895 0.155901 0.98293
+0.936067 -0.349814 -0.0375484
+-0.268176 -0.0909779 0.562652
+
+0.359051 0.917176 -0.172832
+0.0966682 0.147639 0.984306
+0.928298 -0.370124 -0.0356518
+-0.267866 -0.0919218 0.563813
+
+0.379959 0.91007 -0.165543
+0.095346 0.139479 0.985624
+0.920076 -0.39028 -0.0337752
+-0.267557 -0.0928657 0.56495
+
+0.400698 0.902442 -0.15824
+0.0937267 0.131431 0.986885
+0.911404 -0.410274 -0.0319188
+-0.267247 -0.0938096 0.566062
+
+0.421254 0.894297 -0.150924
+0.0918143 0.123504 0.988087
+0.902283 -0.430093 -0.0300827
+-0.266938 -0.0947535 0.567151
+
+0.441614 0.885639 -0.143596
+0.0896134 0.115707 0.989233
+0.892718 -0.449727 -0.0282671
+-0.266628 -0.0956974 0.568215
+
+0.461765 0.876475 -0.136255
+0.0871284 0.10805 0.99032
+0.882713 -0.469167 -0.0264721
+-0.266319 -0.0966413 0.569255
+
+0.481694 0.866808 -0.128902
+0.0843643 0.100541 0.99135
+0.872269 -0.488401 -0.0246978
+-0.266009 -0.0975851 0.570271
+
+0.501386 0.856645 -0.121539
+0.0813263 0.0931885 0.992321
+0.861393 -0.507421 -0.0229443
+-0.2657 -0.098529 0.571263
+
+0.52083 0.845992 -0.114164
+0.0780198 0.0860018 0.993235
+0.850088 -0.526214 -0.0212118
+-0.26539 -0.0994729 0.572231
+
+0.540013 0.834856 -0.10678
+0.0744506 0.0789891 0.994091
+0.838358 -0.544772 -0.0195004
+-0.265081 -0.100417 0.573174
+
+0.558921 0.823243 -0.0993856
+0.0706245 0.0721587 0.99489
+0.826208 -0.563084 -0.0178102
+-0.264771 -0.101361 0.574094
+
+0.577543 0.811162 -0.0919823
+0.0665478 0.0655185 0.99563
+0.813643 -0.58114 -0.0161413
+-0.264462 -0.102305 0.574989
+
+0.595866 0.798618 -0.0845704
+0.0622269 0.0590766 0.996312
+0.800669 -0.598931 -0.0144938
+-0.264152 -0.103248 0.575859
+
+0.613879 0.785621 -0.0771504
+0.0576684 0.0528405 0.996936
+0.787291 -0.616447 -0.0128679
+-0.263843 -0.104192 0.576706
+
+0.631569 0.772178 -0.0697227
+0.0528793 0.0468178 0.997503
+0.773514 -0.633679 -0.0112636
+-0.263533 -0.105136 0.577529
+
+0.648925 0.758298 -0.0622879
+0.0478668 0.0410157 0.998011
+0.759345 -0.650616 -0.00968118
+-0.263224 -0.10608 0.578327
+
+0.665936 0.74399 -0.0548466
+0.042638 0.0354413 0.998462
+0.74479 -0.66725 -0.00812062
+-0.262914 -0.107024 0.579101
+
+0.68259 0.729263 -0.0473991
+0.0372007 0.0301016 0.998854
+0.729854 -0.683571 -0.00658206
+-0.262605 -0.107968 0.579851
+
+0.698876 0.714126 -0.039946
+0.0315625 0.025003 0.999189
+0.714546 -0.69957 -0.00506562
+-0.262295 -0.108912 0.580577
+
+0.714785 0.698589 -0.0324878
+0.0257315 0.020152 0.999466
+0.698871 -0.715239 -0.00357141
+-0.261986 -0.109856 0.581278
+
+0.730305 0.682663 -0.025025
+0.0197157 0.0155547 0.999685
+0.682837 -0.730568 -0.00209952
+-0.261676 -0.1108 0.581956
+
+0.745427 0.666356 -0.0175581
+0.0135236 0.0112171 0.999846
+0.66645 -0.745549 -0.000650061
+-0.261367 -0.111743 0.582609
+
+0.76014 0.649681 -0.0100877
+0.00716369 0.0071447 0.999949
+0.64972 -0.760173 0.00077686
+-0.261057 -0.112687 0.583238
+
+0.774436 0.632647 -0.00261415
+0.000644591 0.00334301 0.999994
+0.632652 -0.774433 0.00218114
+-0.260748 -0.113631 0.583843
+
+0.788304 0.615266 0.00486197
+-0.00602479 -0.000182871 0.999982
+0.615256 -0.788319 0.00356269
+-0.260438 -0.114575 0.584424
+
+0.801737 0.597549 0.0123402
+-0.0128354 -0.00342806 0.999912
+0.597539 -0.801825 0.0049214
+-0.260129 -0.115519 0.58498
+
+0.814725 0.579508 0.01982
+-0.0197782 -0.00638797 0.999784
+0.579509 -0.814941 0.00625718
+-0.259819 -0.116463 0.585512
+
+0.827261 0.561154 0.0273008
+-0.0268438 -0.00905827 0.999599
+0.561176 -0.827662 0.00756994
+-0.25951 -0.117407 0.58602
+
+0.839335 0.5425 0.0347823
+-0.0340227 -0.0114349 0.999356
+0.542548 -0.839978 0.00885957
+-0.2592 -0.118351 0.586504
+
+0.850942 0.523557 0.0422638
+-0.0413054 -0.0135141 0.999055
+0.523634 -0.851883 0.010126
+-0.258891 -0.119295 0.586964
+
+0.862072 0.504339 0.0497449
+-0.0486822 -0.0152925 0.998697
+0.504442 -0.863371 0.0113691
+-0.258581 -0.120238 0.5874
+
+0.872719 0.484857 0.0572251
+-0.0561433 -0.0167667 0.998282
+0.484983 -0.874433 0.0125888
+-0.258272 -0.121182 0.587811
+
+0.882878 0.465124 0.0647039
+-0.0636789 -0.017934 0.997809
+0.465266 -0.885064 0.0137851
+-0.257962 -0.122126 0.588198
+
+0.89254 0.445154 0.0721808
+-0.0712789 -0.0187917 0.997279
+0.445299 -0.895257 0.0149578
+-0.257653 -0.12307 0.588561
+
+0.901701 0.42496 0.0796553
+-0.0789333 -0.0193375 0.996692
+0.425094 -0.905006 0.0161068
+-0.257343 -0.124014 0.5889
+
+0.910354 0.404554 0.087127
+-0.0866319 -0.0195695 0.996048
+0.40466 -0.914305 0.0172321
+-0.257034 -0.124958 0.589215
+
+0.918495 0.383951 0.0945952
+-0.0943645 -0.019486 0.995347
+0.384008 -0.923148 0.0183336
+-0.256724 -0.125902 0.589505
+
+0.926119 0.363163 0.10206
+-0.102121 -0.0190855 0.994589
+0.363146 -0.93153 0.0194112
+-0.256415 -0.126846 0.589771
+
+0.933221 0.342206 0.10952
+-0.109891 -0.018367 0.993774
+0.342087 -0.939446 0.0204648
+-0.256105 -0.12779 0.590013
+
+0.939796 0.321091 0.116975
+-0.117664 -0.0173298 0.992902
+0.320839 -0.94689 0.0214944
+-0.255796 -0.128733 0.590231
+
+0.945842 0.299834 0.124424
+-0.125429 -0.0159733 0.991974
+0.299415 -0.953858 0.0224998
+-0.255486 -0.129677 0.590425
+
+0.951355 0.278448 0.131868
+-0.133177 -0.0142975 0.990989
+0.277825 -0.960345 0.0234811
+-0.255177 -0.130621 0.590594
+
+0.956332 0.256948 0.139306
+-0.140897 -0.0123025 0.989948
+0.256079 -0.966347 0.0244381
+-0.254867 -0.131565 0.59074
+
+0.96077 0.235347 0.146737
+-0.148579 -0.00998877 0.98885
+0.234189 -0.97186 0.0253707
+-0.254558 -0.132509 0.590861
+
+0.964668 0.213661 0.154161
+-0.156211 -0.00735718 0.987696
+0.212166 -0.97688 0.026279
+-0.254248 -0.133453 0.590958
+
+0.968022 0.191902 0.161576
+-0.163784 -0.0044088 0.986486
+0.190021 -0.981404 0.0271627
+-0.253939 -0.134397 0.59103
+
+0.970832 0.170086 0.168984
+-0.171288 -0.00114507 0.98522
+0.167766 -0.985429 0.028022
+-0.253629 -0.135341 0.591079
+
+0.973097 0.148227 0.176383
+-0.178711 0.00243228 0.983899
+0.145411 -0.98895 0.0288566
+-0.25332 -0.136285 0.591103
+
+0.974816 0.126339 0.183772
+-0.186044 0.00632118 0.982521
+0.122969 -0.991967 0.0296666
+-0.25301 -0.137228 0.591104
+
+0.975989 0.104437 0.191152
+-0.193277 0.0105193 0.981088
+0.100451 -0.994476 0.0304518
+-0.252701 -0.138172 0.59108
+
+0.976615 0.0825344 0.198522
+-0.200398 0.0150239 0.979599
+0.077868 -0.996475 0.0312123
+-0.252391 -0.139116 0.591031
+
+0.976696 0.0606467 0.205881
+-0.207399 0.019832 0.978055
+0.0552328 -0.997962 0.0319479
+-0.252082 -0.14006 0.590959
+
+0.976232 0.0387879 0.213229
+-0.214269 0.0249404 0.976456
+0.0325567 -0.998936 0.0326587
+-0.251772 -0.141004 0.590863
+
+0.975224 0.0169724 0.220566
+-0.220998 0.0303454 0.974802
+0.00985155 -0.999395 0.0333444
+-0.251463 -0.141948 0.590742
+
+0.973675 -0.00478566 0.22789
+-0.227577 0.0360432 0.973093
+-0.0128708 -0.999339 0.0340052
+-0.251153 -0.142892 0.590597
+
+0.971586 -0.0264719 0.235202
+-0.233995 0.0420295 0.971329
+-0.0355983 -0.998766 0.034641
+-0.250844 -0.143836 0.590428
+
+0.968959 -0.0480722 0.242501
+-0.240243 0.0482998 0.969511
+-0.0583192 -0.997675 0.0352516
+-0.250534 -0.14478 0.590235
+
+0.965798 -0.0695724 0.249786
+-0.246311 0.0548495 0.967638
+-0.0810215 -0.996068 0.0358371
+-0.250225 -0.145723 0.590017
+
+0.962106 -0.0909584 0.257058
+-0.25219 0.0616733 0.96571
+-0.103693 -0.993943 0.0363974
+-0.249915 -0.146667 0.589775
+
+0.957886 -0.112216 0.264315
+-0.257871 0.0687659 0.963729
+-0.126322 -0.991302 0.0369324
+-0.249606 -0.147611 0.58951
+
+0.953142 -0.133333 0.271557
+-0.263345 0.0761216 0.961694
+-0.148896 -0.988144 0.0374422
+-0.249296 -0.148555 0.58922
+
+0.947878 -0.154293 0.278784
+-0.268603 0.0837347 0.959605
+-0.171404 -0.98447 0.0379266
+-0.248987 -0.149499 0.588905
+
+0.9421 -0.175084 0.285996
+-0.273636 0.0915987 0.957462
+-0.193833 -0.980283 0.0383857
+-0.248677 -0.150443 0.588567
+
+0.935812 -0.195693 0.293191
+-0.278435 0.0997073 0.955266
+-0.216172 -0.975583 0.0388194
+-0.248368 -0.151387 0.588204
+
+0.929019 -0.216106 0.300369
+-0.282992 0.108054 0.953016
+-0.238408 -0.970372 0.0392277
+-0.248058 -0.152331 0.587818
+
+0.921728 -0.236309 0.30753
+-0.2873 0.116631 0.950714
+-0.26053 -0.964653 0.0396105
+-0.247749 -0.153275 0.587407
+
+0.913945 -0.256291 0.314674
+-0.291348 0.125432 0.948358
+-0.282525 -0.958427 0.0399677
+-0.24744 -0.154218 0.586971
+
+0.905676 -0.276037 0.321799
+-0.295131 0.134448 0.94595
+-0.304383 -0.951697 0.0402995
+-0.24713 -0.155162 0.586512
+
+0.896927 -0.295536 0.328907
+-0.298641 0.143674 0.943489
+-0.32609 -0.944466 0.0406057
+-0.246821 -0.156106 0.586029
+
+0.887707 -0.314775 0.335995
+-0.301869 0.153099 0.940976
+-0.347636 -0.936738 0.0408863
+-0.246511 -0.15705 0.585521
+
+0.878023 -0.333742 0.343064
+-0.304809 0.162717 0.938411
+-0.369009 -0.928515 0.0411413
+-0.246202 -0.157994 0.584989
+
+0.867882 -0.352424 0.350113
+-0.307454 0.172518 0.935794
+-0.390197 -0.919802 0.0413706
+-0.245892 -0.158938 0.584433
+
+0.857292 -0.370811 0.357141
+-0.309797 0.182494 0.933125
+-0.411189 -0.910602 0.0415743
+-0.245583 -0.159882 0.583853
+
+0.846263 -0.388889 0.36415
+-0.311833 0.192636 0.930404
+-0.431973 -0.90092 0.0417523
+-0.245273 -0.160826 0.583248
+
+0.834802 -0.406649 0.371136
+-0.313553 0.202935 0.927632
+-0.452537 -0.89076 0.0419046
+-0.244964 -0.161769 0.58262
+
+0.822919 -0.424079 0.378102
+-0.314953 0.213382 0.924809
+-0.472872 -0.880128 0.0420311
+-0.244654 -0.162713 0.581967
+
+0.810624 -0.441168 0.385045
+-0.316028 0.223967 0.921936
+-0.492966 -0.869028 0.0421319
+-0.244345 -0.163657 0.58129
+
+0.797926 -0.457905 0.391966
+-0.316771 0.234681 0.919011
+-0.512807 -0.857466 0.042207
+-0.244035 -0.164601 0.580589
+
+0.784835 -0.474281 0.398864
+-0.317177 0.245513 0.916036
+-0.532385 -0.845447 0.0422563
+-0.243726 -0.165545 0.579863
+
+0.77136 -0.490285 0.405739
+-0.317242 0.256454 0.913011
+-0.551689 -0.832978 0.0422798
+-0.243416 -0.166489 0.579114
+
+0.757514 -0.505907 0.41259
+-0.316962 0.267494 0.909935
+-0.570708 -0.820064 0.0422775
+-0.243107 -0.167433 0.57834
+
+0.743306 -0.521138 0.419417
+-0.316331 0.278622 0.90681
+-0.589432 -0.806712 0.0422495
+-0.242797 -0.168377 0.577542
+
+0.735017 -0.528839 0.424358
+-0.315826 0.286793 0.904436
+-0.600003 -0.798799 0.0437763
+-0.242406 -0.168991 0.576993
+
+0.73475 -0.527186 0.42687
+-0.315892 0.290969 0.903078
+-0.600296 -0.798381 0.0472553
+-0.241928 -0.169177 0.576796
+
+0.74326 -0.515311 0.426637
+-0.316809 0.290569 0.902885
+-0.589234 -0.806241 0.0527129
+-0.24135 -0.168901 0.576982
+
+0.757578 -0.49596 0.424382
+-0.318243 0.287006 0.90352
+-0.56991 -0.819543 0.0595933
+-0.240689 -0.168299 0.57742
+
+0.771391 -0.476235 0.422085
+-0.319672 0.283519 0.904117
+-0.550241 -0.832356 0.0664645
+-0.240029 -0.167697 0.577835
+
+0.784691 -0.45615 0.419746
+-0.321099 0.280105 0.904675
+-0.530241 -0.84467 0.0733261
+-0.239368 -0.167094 0.578225
+
+0.797468 -0.435719 0.417366
+-0.322529 0.276763 0.905195
+-0.509922 -0.856476 0.0801777
+-0.238707 -0.166492 0.578591
+
+0.809713 -0.414953 0.414945
+-0.323966 0.273492 0.905676
+-0.489297 -0.867765 0.0870189
+-0.238047 -0.16589 0.578933
+
+0.821417 -0.393869 0.412482
+-0.325413 0.270288 0.906118
+-0.468381 -0.878528 0.0938491
+-0.237386 -0.165288 0.579251
+
+0.832572 -0.37248 0.409979
+-0.326875 0.267151 0.906523
+-0.447187 -0.888757 0.100668
+-0.236726 -0.164685 0.579545
+
+0.843171 -0.3508 0.407435
+-0.328355 0.264077 0.906888
+-0.42573 -0.898445 0.107475
+-0.236065 -0.164083 0.579814
+
+0.853205 -0.328844 0.40485
+-0.329858 0.261065 0.907215
+-0.404024 -0.907583 0.11427
+-0.235404 -0.163481 0.580059
+
+0.862668 -0.306627 0.402224
+-0.331386 0.258111 0.907503
+-0.382083 -0.916165 0.121052
+-0.234744 -0.162879 0.580281
+
+0.871553 -0.284163 0.399559
+-0.332944 0.255214 0.907752
+-0.359923 -0.924185 0.127822
+-0.234083 -0.162276 0.580477
+
+0.879853 -0.261469 0.396853
+-0.334534 0.252369 0.907963
+-0.337558 -0.931635 0.134577
+-0.233422 -0.161674 0.58065
+
+0.887563 -0.238559 0.394107
+-0.336161 0.249575 0.908135
+-0.315003 -0.93851 0.141319
+-0.232762 -0.161072 0.580799
+
+0.894678 -0.215449 0.391322
+-0.337826 0.246827 0.908267
+-0.292275 -0.944806 0.148047
+-0.232101 -0.16047 0.580923
+
+0.901192 -0.192155 0.388496
+-0.339534 0.244124 0.908361
+-0.269388 -0.950516 0.154759
+-0.231441 -0.159867 0.581023
+
+0.9071 -0.168692 0.385632
+-0.341287 0.241461 0.908416
+-0.246358 -0.955636 0.161457
+-0.23078 -0.159265 0.581099
+
+0.912399 -0.145077 0.382728
+-0.343088 0.238835 0.908432
+-0.223201 -0.960162 0.168139
+-0.230119 -0.158663 0.581151
+
+0.917084 -0.121324 0.379785
+-0.344939 0.236242 0.908409
+-0.199933 -0.96409 0.174804
+-0.229459 -0.158061 0.581178
+
+0.921153 -0.0974515 0.376803
+-0.346843 0.233679 0.908347
+-0.176571 -0.967418 0.181453
+-0.228798 -0.157458 0.581182
+
+0.924602 -0.0734742 0.373783
+-0.348803 0.231141 0.908246
+-0.153129 -0.970142 0.188086
+-0.228137 -0.156856 0.581161
+
+0.927428 -0.0494088 0.370724
+-0.35082 0.228626 0.908106
+-0.129625 -0.97226 0.194701
+-0.227477 -0.156254 0.581116
+
+0.92963 -0.0252717 0.367626
+-0.352896 0.226129 0.907926
+-0.106076 -0.97377 0.201298
+-0.226816 -0.155652 0.581047
+
+0.931206 -0.00107911 0.364491
+-0.355034 0.223645 0.907708
+-0.082496 -0.97467 0.207876
+-0.226156 -0.155049 0.580954
+
+0.932155 0.0231524 0.361317
+-0.357235 0.221171 0.907451
+-0.0589033 -0.97496 0.214437
+-0.225495 -0.154447 0.580836
+
+0.932476 0.0474065 0.358106
+-0.3595 0.218703 0.907154
+-0.0353139 -0.974639 0.220978
+-0.224834 -0.153845 0.580694
+
+0.932169 0.0716666 0.354858
+-0.361832 0.216236 0.906819
+-0.0117443 -0.973707 0.227499
+-0.224174 -0.153243 0.580528
+
+0.931234 0.0959163 0.351572
+-0.364231 0.213765 0.906444
+0.0117888 -0.972165 0.234001
+-0.223513 -0.15264 0.580338
+
+0.929671 0.120139 0.348249
+-0.366697 0.211287 0.90603
+0.035269 -0.970012 0.240483
+-0.222852 -0.152038 0.580124
+
+0.927482 0.144319 0.34489
+-0.369233 0.208797 0.905577
+0.0586797 -0.967252 0.246943
+-0.222192 -0.151436 0.579886
+
+0.924668 0.168439 0.341493
+-0.371839 0.206291 0.905085
+0.0820043 -0.963884 0.253383
+-0.221531 -0.150834 0.579623
+
+0.921231 0.192482 0.33806
+-0.374515 0.203763 0.904555
+0.105227 -0.959912 0.2598
+-0.220871 -0.150231 0.579336
+
+0.917172 0.216434 0.334591
+-0.377262 0.20121 0.903985
+0.12833 -0.955338 0.266196
+-0.22021 -0.149629 0.579025
+
+0.912496 0.240277 0.331086
+-0.380079 0.198626 0.903376
+0.151298 -0.950166 0.27257
+-0.219549 -0.149027 0.57869
+
+0.907205 0.263995 0.327546
+-0.382967 0.196007 0.902728
+0.174114 -0.944398 0.27892
+-0.218889 -0.148425 0.57833
+
+0.901302 0.287573 0.323969
+-0.385925 0.193349 0.902041
+0.196763 -0.93804 0.285247
+-0.218228 -0.147822 0.577947
+
+0.894793 0.310994 0.320358
+-0.388954 0.190646 0.901315
+0.219228 -0.931095 0.291551
+-0.217568 -0.14722 0.577539
+
+0.88768 0.334242 0.316711
+-0.392052 0.187894 0.90055
+0.241494 -0.923568 0.29783
+-0.216907 -0.146618 0.577107
+
+0.87997 0.357302 0.31303
+-0.395218 0.185089 0.899747
+0.263543 -0.915466 0.304085
+-0.216246 -0.146016 0.576651
+
+0.871667 0.380159 0.309314
+-0.398453 0.182225 0.898905
+0.285362 -0.906793 0.310315
+-0.215586 -0.145413 0.576171
+
+0.862778 0.402796 0.305564
+-0.401754 0.179298 0.898023
+0.306934 -0.897556 0.31652
+-0.214925 -0.144811 0.575666
+
+0.853308 0.4252 0.301779
+-0.40512 0.176304 0.897104
+0.328243 -0.887762 0.322699
+-0.214264 -0.144209 0.575138
+
+0.843264 0.447354 0.297961
+-0.408549 0.173238 0.896145
+0.349276 -0.877419 0.328851
+-0.213604 -0.143607 0.574585
+
+0.832653 0.469243 0.294109
+-0.412041 0.170095 0.895148
+0.370016 -0.866532 0.334978
+-0.212943 -0.143004 0.574008
+
+0.821482 0.490854 0.290224
+-0.415593 0.166871 0.894112
+0.390449 -0.855112 0.341077
+-0.212283 -0.142402 0.573406
+
+0.809759 0.512172 0.286306
+-0.419203 0.163561 0.893038
+0.410561 -0.843165 0.347149
+-0.211622 -0.1418 0.572781
+
+0.797492 0.533182 0.282354
+-0.422868 0.160161 0.891925
+0.430336 -0.830702 0.353193
+-0.210961 -0.141198 0.572131
+
+0.784689 0.55387 0.278371
+-0.426587 0.156667 0.890774
+0.449762 -0.817731 0.359209
+-0.210301 -0.140595 0.571458
+
+0.77136 0.574224 0.274354
+-0.430357 0.153074 0.889585
+0.468824 -0.804261 0.365196
+-0.20964 -0.139993 0.57076
+
+0.759474 0.592015 0.269661
+-0.432754 0.150274 0.888899
+0.485718 -0.791793 0.370327
+-0.208856 -0.139638 0.570232
+
+0.750783 0.605555 0.26387
+-0.432816 0.149216 0.889047
+0.498994 -0.781689 0.374123
+-0.207937 -0.13966 0.569934
+
+0.745696 0.614745 0.256955
+-0.430487 0.150173 0.890016
+0.508545 -0.774297 0.376623
+-0.20685 -0.140084 0.569887
+
+0.744347 0.619661 0.248933
+-0.425768 0.153194 0.89177
+0.51446 -0.769774 0.377862
+-0.205593 -0.140908 0.570088
+
+0.745612 0.621615 0.240121
+-0.419352 0.157651 0.89403
+0.517888 -0.767294 0.378222
+-0.204163 -0.142043 0.570515
+
+0.746808 0.623525 0.231289
+-0.412926 0.16213 0.896218
+0.521315 -0.764808 0.37855
+-0.202733 -0.143178 0.570918
+
+0.747936 0.62539 0.222438
+-0.406493 0.16663 0.898331
+0.524742 -0.762314 0.378845
+-0.201303 -0.144312 0.571296
+
+0.748997 0.62721 0.213568
+-0.400052 0.171151 0.90037
+0.528169 -0.759812 0.379108
+-0.199873 -0.145447 0.571651
+
+0.749989 0.628985 0.204681
+-0.393604 0.175693 0.902335
+0.531594 -0.757304 0.379339
+-0.198443 -0.146582 0.571981
+
+0.750913 0.630715 0.195777
+-0.38715 0.180255 0.904225
+0.535019 -0.754789 0.379537
+-0.197013 -0.147716 0.572287
+
+0.751769 0.632399 0.186857
+-0.38069 0.184837 0.906041
+0.538442 -0.752268 0.379703
+-0.195583 -0.148851 0.572568
+
+0.752556 0.634037 0.177921
+-0.374225 0.189439 0.907782
+0.541863 -0.74974 0.379836
+-0.194153 -0.149986 0.572826
+
+0.753275 0.63563 0.168971
+-0.367755 0.19406 0.909449
+0.545282 -0.747205 0.379937
+-0.192723 -0.15112 0.573059
+
+0.753926 0.637176 0.160007
+-0.361281 0.1987 0.91104
+0.548699 -0.744665 0.380005
+-0.191293 -0.152255 0.573268
+
+0.754509 0.638675 0.151029
+-0.354804 0.203359 0.912556
+0.552114 -0.742118 0.380041
+-0.189863 -0.15339 0.573453
+
+0.755024 0.640128 0.14204
+-0.348324 0.208036 0.913998
+0.555526 -0.739566 0.380044
+-0.188433 -0.154524 0.573614
+
+0.755471 0.641533 0.133038
+-0.341842 0.21273 0.915363
+0.558935 -0.737008 0.380015
+-0.187003 -0.155659 0.573751
+
+0.755849 0.642892 0.124025
+-0.335358 0.217442 0.916653
+0.562341 -0.734445 0.379953
+-0.185573 -0.156794 0.573863
+
+0.756159 0.644203 0.115003
+-0.328874 0.222172 0.917868
+0.565743 -0.731876 0.379859
+-0.184143 -0.157928 0.573951
+
+0.756402 0.645467 0.105971
+-0.322389 0.226917 0.919007
+0.569142 -0.729302 0.379732
+-0.182713 -0.159063 0.574015
+
+0.756576 0.646682 0.0969296
+-0.315904 0.23168 0.92007
+0.572536 -0.726723 0.379573
+-0.181283 -0.160197 0.574055
+
+0.756682 0.64785 0.0878807
+-0.30942 0.236458 0.921058
+0.575927 -0.72414 0.379381
+-0.179853 -0.161332 0.574071
+
+0.75672 0.648969 0.0788246
+-0.302937 0.241251 0.921969
+0.579313 -0.721552 0.379157
+-0.178423 -0.162467 0.574062
+
+0.756691 0.65004 0.0697621
+-0.296456 0.24606 0.922804
+0.582694 -0.718959 0.3789
+-0.176993 -0.163601 0.57403
+
+0.756593 0.651063 0.0606938
+-0.289978 0.250884 0.923564
+0.586071 -0.716362 0.378611
+-0.175563 -0.164736 0.573973
+
+0.756428 0.652036 0.0516205
+-0.283503 0.255722 0.924247
+0.589442 -0.713761 0.37829
+-0.174133 -0.165871 0.573892
+
+0.756196 0.652961 0.0425431
+-0.277032 0.260574 0.924854
+0.592808 -0.711156 0.377936
+-0.172703 -0.167005 0.573787
+
+0.755896 0.653837 0.0334622
+-0.270565 0.265439 0.925385
+0.596168 -0.708548 0.37755
+-0.171273 -0.16814 0.573657
+
+0.755528 0.654663 0.0243786
+-0.264103 0.270318 0.925839
+0.599522 -0.705936 0.377131
+-0.169843 -0.169275 0.573504
+
+0.755093 0.655439 0.015293
+-0.257647 0.275209 0.926217
+0.60287 -0.70332 0.376681
+-0.168413 -0.170409 0.573326
+
+0.754591 0.656166 0.00620624
+-0.251197 0.280113 0.926519
+0.606212 -0.700701 0.376198
+-0.166983 -0.171544 0.573124
+
+0.754021 0.656843 -0.00288097
+-0.244753 0.285029 0.926744
+0.609547 -0.69808 0.375682
+-0.165552 -0.172679 0.572898
+
+0.753385 0.657471 -0.0119679
+-0.238317 0.289956 0.926893
+0.612875 -0.695455 0.375135
+-0.164122 -0.173813 0.572647
+
+0.752682 0.658048 -0.0210537
+-0.231889 0.294895 0.926965
+0.616196 -0.692828 0.374556
+-0.162692 -0.174948 0.572373
+
+0.751912 0.658574 -0.0301377
+-0.225469 0.299844 0.926961
+0.619509 -0.690198 0.373944
+-0.161262 -0.176083 0.572074
+
+0.751076 0.65905 -0.0392192
+-0.219058 0.304803 0.926881
+0.622815 -0.687566 0.373301
+-0.159832 -0.177217 0.571751
+
+0.750173 0.659476 -0.0482973
+-0.212657 0.309773 0.926724
+0.626113 -0.684932 0.372625
+-0.158402 -0.178352 0.571404
+
+0.749203 0.659851 -0.0573713
+-0.206266 0.314752 0.926491
+0.629403 -0.682296 0.371918
+-0.156972 -0.179486 0.571033
+
+0.748168 0.660175 -0.0664406
+-0.199886 0.31974 0.926181
+0.632685 -0.679659 0.371179
+-0.155542 -0.180621 0.570637
+
+0.747066 0.660447 -0.0755042
+-0.193517 0.324737 0.925795
+0.635958 -0.677019 0.370408
+-0.154112 -0.181756 0.570218
+
+0.745899 0.660669 -0.0845615
+-0.18716 0.329742 0.925333
+0.639223 -0.674379 0.369605
+-0.152682 -0.18289 0.569774
+
+0.744666 0.66084 -0.0936118
+-0.180816 0.334755 0.924795
+0.642478 -0.671737 0.368771
+-0.151252 -0.184025 0.569306
+
+0.743368 0.660959 -0.102654
+-0.174484 0.339775 0.92418
+0.645724 -0.669094 0.367905
+-0.149822 -0.18516 0.568813
+
+0.742004 0.661026 -0.111688
+-0.168167 0.344802 0.923489
+0.64896 -0.66645 0.367007
+-0.148392 -0.186294 0.568297
+
+0.740576 0.661042 -0.120712
+-0.161863 0.349836 0.922722
+0.652187 -0.663806 0.366078
+-0.146962 -0.187429 0.567756
+
+0.739082 0.661006 -0.129727
+-0.155575 0.354876 0.921878
+0.655404 -0.661162 0.365118
+-0.145532 -0.188564 0.567192
+
+0.737524 0.660918 -0.13873
+-0.149301 0.359921 0.920959
+0.658611 -0.658517 0.364126
+-0.144102 -0.189698 0.566603
+
+0.735901 0.660778 -0.147722
+-0.143044 0.364972 0.919964
+0.661807 -0.655872 0.363104
+-0.142672 -0.190833 0.56599
+
+0.734214 0.660586 -0.156702
+-0.136803 0.370028 0.918893
+0.664992 -0.653227 0.36205
+-0.141242 -0.191968 0.565352
+
+0.732463 0.660343 -0.165669
+-0.130579 0.375088 0.917746
+0.668167 -0.650582 0.360965
+-0.139812 -0.193102 0.564691
+
+0.730648 0.660046 -0.174622
+-0.124373 0.380152 0.916524
+0.671331 -0.647938 0.359849
+-0.138382 -0.194237 0.564005
+
+0.728769 0.659698 -0.18356
+-0.118185 0.385219 0.915226
+0.674483 -0.645295 0.358702
+-0.136952 -0.195372 0.563295
+
+0.726827 0.659297 -0.192483
+-0.112015 0.39029 0.913853
+0.677624 -0.642652 0.357525
+-0.135522 -0.196506 0.562561
+
+0.724822 0.658843 -0.20139
+-0.105865 0.395363 0.912404
+0.680753 -0.640011 0.356316
+-0.134092 -0.197641 0.561803
+
+0.722755 0.658337 -0.21028
+-0.0997347 0.400438 0.91088
+0.68387 -0.63737 0.355078
+-0.132662 -0.198776 0.56102
+
+0.720624 0.657779 -0.219153
+-0.0936246 0.405515 0.909281
+0.686975 -0.634732 0.353809
+-0.131232 -0.19991 0.560214
+
+0.718431 0.657168 -0.228007
+-0.0875354 0.410594 0.907607
+0.690068 -0.632095 0.352509
+-0.129802 -0.201045 0.559383
+
+0.716177 0.656503 -0.236843
+-0.0814676 0.415673 0.905858
+0.693148 -0.629459 0.351179
+-0.128372 -0.202179 0.558528
+
+0.71386 0.655787 -0.245658
+-0.0754218 0.420753 0.904035
+0.696215 -0.626826 0.349819
+-0.126942 -0.203314 0.557649
+
+0.711482 0.655017 -0.254454
+-0.0693984 0.425833 0.902137
+0.699269 -0.624195 0.348429
+-0.125512 -0.204449 0.556745
+
+0.709042 0.654194 -0.263228
+-0.0633981 0.430912 0.900164
+0.70231 -0.621566 0.347009
+-0.124082 -0.205583 0.555818
+
+0.706542 0.653319 -0.27198
+-0.0574213 0.43599 0.898118
+0.705338 -0.61894 0.34556
+-0.122652 -0.206718 0.554866
+
+0.703981 0.65239 -0.28071
+-0.0514687 0.441067 0.895997
+0.708352 -0.616317 0.34408
+-0.121222 -0.207853 0.55389
+
+0.701359 0.651409 -0.289416
+-0.0455406 0.446142 0.893803
+0.711352 -0.613697 0.342572
+-0.119792 -0.208987 0.55289
+
+0.698678 0.650374 -0.298098
+-0.0396376 0.451215 0.891535
+0.714338 -0.61108 0.341033
+-0.118362 -0.210122 0.551866
+
+0.695937 0.649287 -0.306756
+-0.0337602 0.456285 0.889193
+0.717309 -0.608466 0.339466
+-0.116932 -0.211257 0.550817
+
+0.693136 0.648146 -0.315387
+-0.0279091 0.461352 0.886778
+0.720266 -0.605856 0.337869
+-0.115502 -0.212391 0.549745
+
+0.690276 0.646952 -0.323993
+-0.0220846 0.466415 0.88429
+0.723209 -0.603249 0.336243
+-0.114071 -0.213526 0.548648
+
+0.687358 0.645705 -0.332572
+-0.0162872 0.471474 0.881729
+0.726137 -0.600647 0.334588
+-0.112641 -0.214661 0.547527
+
+0.68438 0.644406 -0.341123
+-0.0105176 0.476529 0.879096
+0.729049 -0.598048 0.332905
+-0.111211 -0.215795 0.546382
+
+0.681345 0.643052 -0.349646
+-0.0047761 0.481579 0.87639
+0.731947 -0.595454 0.331193
+-0.109781 -0.21693 0.545212
+
+0.678252 0.641646 -0.35814
+0.000936686 0.486623 0.873612
+0.734829 -0.592865 0.329452
+-0.108351 -0.218065 0.544019
+
+0.675102 0.640187 -0.366604
+0.00662029 0.491661 0.870762
+0.737695 -0.59028 0.327683
+-0.106921 -0.219199 0.542801
+
+0.67269 0.637839 -0.375032
+0.0117018 0.497618 0.867317
+0.739832 -0.587824 0.327279
+-0.105572 -0.220158 0.54158
+
+0.671243 0.634374 -0.383408
+0.0160485 0.504695 0.863149
+0.741063 -0.585536 0.328592
+-0.104328 -0.2209 0.540371
+
+0.670405 0.630191 -0.391685
+0.0190635 0.513077 0.858131
+0.741751 -0.582762 0.331956
+-0.103195 -0.221377 0.539175
+
+0.670332 0.625118 -0.399855
+0.0208713 0.522747 0.852232
+0.741768 -0.579624 0.337367
+-0.102182 -0.22159 0.537994
+
+0.671071 0.619063 -0.407952
+0.0221842 0.533237 0.845675
+0.741061 -0.576558 0.344107
+-0.101257 -0.221635 0.536828
+
+0.671789 0.612908 -0.415985
+0.0235237 0.543642 0.838987
+0.740369 -0.573408 0.350795
+-0.100332 -0.221679 0.535637
+
+0.672485 0.606654 -0.423952
+0.0248892 0.553961 0.83217
+0.739692 -0.570174 0.357431
+-0.0994076 -0.221724 0.534422
+
+0.673158 0.600301 -0.431853
+0.0262803 0.564192 0.825225
+0.739031 -0.566856 0.364014
+-0.0984829 -0.221769 0.533183
+
+0.673809 0.593851 -0.439685
+0.0276964 0.574332 0.818153
+0.738386 -0.563457 0.370543
+-0.0975582 -0.221813 0.53192
+
+0.674437 0.587303 -0.447448
+0.0291372 0.584382 0.810956
+0.737758 -0.559976 0.377016
+-0.0966334 -0.221858 0.530633
+
+0.675041 0.58066 -0.455141
+0.030602 0.594338 0.803633
+0.737146 -0.556413 0.383433
+-0.0957087 -0.221902 0.529321
+
+0.675621 0.573923 -0.462762
+0.0320904 0.6042 0.796186
+0.73655 -0.55277 0.389793
+-0.094784 -0.221947 0.527986
+
+0.676177 0.567091 -0.470311
+0.0336017 0.613965 0.788617
+0.735972 -0.549048 0.396094
+-0.0938593 -0.221992 0.526626
+
+0.676709 0.560167 -0.477785
+0.0351356 0.623633 0.780927
+0.735412 -0.545247 0.402336
+-0.0929346 -0.222036 0.525242
+
+0.677215 0.55315 -0.485184
+0.0366914 0.633202 0.773116
+0.734869 -0.541368 0.408518
+-0.0920099 -0.222081 0.523833
+
+0.677697 0.546043 -0.492508
+0.0382685 0.64267 0.765187
+0.734345 -0.537412 0.414639
+-0.0910852 -0.222126 0.522401
+
+0.678153 0.538847 -0.499753
+0.0398665 0.652036 0.757139
+0.733839 -0.533379 0.420698
+-0.0901605 -0.22217 0.520944
+
+0.678583 0.531561 -0.506921
+0.0414847 0.661298 0.748975
+0.733352 -0.529271 0.426694
+-0.0892358 -0.222215 0.519463
+
+0.678986 0.524188 -0.514008
+0.0431225 0.670455 0.740696
+0.732883 -0.525088 0.432625
+-0.0883111 -0.22226 0.517958
+
+0.679364 0.516728 -0.521015
+0.0447795 0.679505 0.732303
+0.732434 -0.520831 0.438492
+-0.0873864 -0.222304 0.516429
+
+0.679714 0.509183 -0.52794
+0.0464549 0.688447 0.723797
+0.732004 -0.516501 0.444293
+-0.0864617 -0.222349 0.514876
+
+0.680038 0.501554 -0.534783
+0.0481482 0.69728 0.71518
+0.731594 -0.512098 0.450028
+-0.085537 -0.222394 0.513298
+
+0.680334 0.493841 -0.541541
+0.0498588 0.706002 0.706453
+0.731204 -0.507624 0.455695
+-0.0846122 -0.222438 0.511697
+
+0.680602 0.486046 -0.548215
+0.051586 0.714612 0.697617
+0.730835 -0.50308 0.461293
+-0.0836875 -0.222483 0.510071
+
+0.680843 0.47817 -0.554803
+0.0533293 0.723108 0.688673
+0.730485 -0.498466 0.466823
+-0.0827628 -0.222528 0.508421
+
+0.681056 0.470215 -0.561303
+0.055088 0.731489 0.679624
+0.730156 -0.493783 0.472282
+-0.0818381 -0.222572 0.506746
+
+0.68124 0.462181 -0.567716
+0.0568616 0.739755 0.67047
+0.729849 -0.489032 0.47767
+-0.0809134 -0.222617 0.505048
+
+0.681395 0.454069 -0.57404
+0.0586492 0.747902 0.661213
+0.729562 -0.484215 0.482986
+-0.0799887 -0.222662 0.503325
+
+0.681522 0.445881 -0.580274
+0.0604504 0.755931 0.651854
+0.729296 -0.479331 0.48823
+-0.079064 -0.222706 0.501578
+
+0.68162 0.437618 -0.586417
+0.0622645 0.76384 0.642395
+0.729052 -0.474382 0.493401
+-0.0781393 -0.222751 0.499807
+
+0.681689 0.429282 -0.592468
+0.0640908 0.771628 0.632837
+0.72883 -0.46937 0.498497
+-0.0772146 -0.222796 0.498012
+
+0.681728 0.420872 -0.598426
+0.0659286 0.779293 0.623182
+0.728629 -0.464294 0.503518
+-0.0762899 -0.22284 0.496193
+
+0.681737 0.412392 -0.604291
+0.0677774 0.786835 0.613431
+0.728451 -0.459156 0.508464
+-0.0753652 -0.222885 0.494349
+
+0.681717 0.403841 -0.610061
+0.0696363 0.794252 0.603585
+0.728295 -0.453957 0.513333
+-0.0744405 -0.22293 0.492481
+
+0.681667 0.395222 -0.615736
+0.0715049 0.801542 0.593647
+0.728161 -0.448697 0.518124
+-0.0735157 -0.222974 0.490589
+
+0.681586 0.386535 -0.621314
+0.0733823 0.808706 0.583617
+0.728049 -0.443379 0.522838
+-0.072591 -0.223019 0.488673
+
+0.681475 0.377782 -0.626795
+0.075268 0.815742 0.573498
+0.72796 -0.438002 0.527473
+-0.0716663 -0.223064 0.486733
+
+0.681334 0.368964 -0.632178
+0.0771611 0.822648 0.56329
+0.727894 -0.432569 0.532029
+-0.0707416 -0.223108 0.484768
+
+0.681163 0.360082 -0.637463
+0.0790611 0.829424 0.552996
+0.727851 -0.427079 0.536504
+-0.0698169 -0.223153 0.482779
+
+0.68096 0.351138 -0.642647
+0.0809673 0.836069 0.542617
+0.727831 -0.421534 0.540899
+-0.0688922 -0.223198 0.480767
+
+0.680727 0.342133 -0.647731
+0.0828789 0.842581 0.532154
+0.727834 -0.415935 0.545212
+-0.0679675 -0.223242 0.47873
+
+0.680463 0.333069 -0.652714
+0.0847953 0.84896 0.52161
+0.72786 -0.410283 0.549443
+-0.0670428 -0.223287 0.476668
+
+0.680168 0.323946 -0.657595
+0.0867158 0.855204 0.510985
+0.727909 -0.404579 0.553591
+-0.0661181 -0.223332 0.474583
+
+0.679842 0.314766 -0.662373
+0.0886397 0.861314 0.500282
+0.727982 -0.398825 0.557656
+-0.0651934 -0.223376 0.472473
+
+0.679484 0.30553 -0.667047
+0.0905662 0.867287 0.489502
+0.728079 -0.393021 0.561637
+-0.0642687 -0.223421 0.470339
+
+0.679096 0.296241 -0.671618
+0.0924947 0.873122 0.478646
+0.728199 -0.387168 0.565533
+-0.063344 -0.223466 0.468181
+
+0.678676 0.286898 -0.676083
+0.0944245 0.87882 0.467717
+0.728343 -0.381267 0.569344
+-0.0624193 -0.22351 0.465999
+
+0.678225 0.277504 -0.680443
+0.0963549 0.884379 0.456716
+0.72851 -0.37532 0.573069
+-0.0614945 -0.223555 0.463793
+
+0.677742 0.26806 -0.684696
+0.0982851 0.889798 0.445645
+0.728701 -0.369328 0.576707
+-0.0605698 -0.2236 0.461562
+
+0.677228 0.258568 -0.688843
+0.100214 0.895077 0.434505
+0.728916 -0.363291 0.580259
+-0.0596451 -0.223644 0.459307
+
+0.676683 0.249028 -0.692882
+0.102142 0.900214 0.423299
+0.729155 -0.357212 0.583723
+-0.0587204 -0.223689 0.457029
+
+0.676106 0.239442 -0.696813
+0.104068 0.905209 0.412028
+0.729418 -0.35109 0.587099
+-0.0577957 -0.223734 0.454725
+
+0.675498 0.229812 -0.700635
+0.10599 0.910061 0.400693
+0.729705 -0.344928 0.590386
+-0.056871 -0.223778 0.452398
+
+0.674858 0.220139 -0.704347
+0.107909 0.91477 0.389297
+0.730015 -0.338725 0.593585
+-0.0559463 -0.223823 0.450047
+
+0.674187 0.210425 -0.70795
+0.109824 0.919334 0.37784
+0.73035 -0.332485 0.596694
+-0.0550216 -0.223868 0.447671
+
+0.673485 0.20067 -0.711442
+0.111733 0.923754 0.366326
+0.730708 -0.326207 0.599712
+-0.0540969 -0.223912 0.445271
+
+0.672751 0.190877 -0.714823
+0.113636 0.928028 0.354756
+0.73109 -0.319892 0.602641
+-0.0531722 -0.223957 0.442847
+
+0.671986 0.181046 -0.718093
+0.115533 0.932155 0.343131
+0.731497 -0.313543 0.605478
+-0.0522475 -0.224002 0.440399
+
+0.671189 0.17118 -0.72125
+0.117423 0.936136 0.331453
+0.731927 -0.307159 0.608224
+-0.0513228 -0.224046 0.437926
+
+0.670362 0.161279 -0.724295
+0.119305 0.939969 0.319725
+0.732381 -0.300743 0.610878
+-0.0503981 -0.224091 0.43543
+
+0.669503 0.151346 -0.727227
+0.121178 0.943655 0.307947
+0.732858 -0.294296 0.61344
+-0.0494733 -0.224136 0.432909
+
+0.668614 0.141381 -0.730046
+0.123042 0.947192 0.296122
+0.73336 -0.287818 0.61591
+-0.0485486 -0.22418 0.430364
+
+0.667693 0.131387 -0.73275
+0.124896 0.95058 0.284252
+0.733885 -0.281311 0.618286
+-0.0476239 -0.224225 0.427795
+
+0.668726 0.114621 -0.734621
+0.140123 0.950911 0.275922
+0.730186 -0.287453 0.619838
+-0.0468975 -0.224124 0.425726
+
+0.6714 0.091107 -0.735473
+0.168814 0.947523 0.271482
+0.721612 -0.306431 0.620787
+-0.0464084 -0.223891 0.424192
+
+0.67474 0.0619723 -0.735449
+0.208431 0.939907 0.270427
+0.708013 -0.335758 0.621276
+-0.0461226 -0.22354 0.423109
+
+0.677201 0.0338412 -0.735019
+0.246341 0.930866 0.269822
+0.693336 -0.363789 0.622047
+-0.0458736 -0.223121 0.422062
+
+0.680357 0.0113884 -0.732792
+0.276513 0.921992 0.271055
+0.678716 -0.387041 0.624135
+-0.0458147 -0.222405 0.421239
+
+0.685413 -0.00318407 -0.728148
+0.296014 0.914849 0.27464
+0.665271 -0.403783 0.627992
+-0.0459716 -0.22126 0.420737
+
+0.692625 -0.0103399 -0.721224
+0.305435 0.91003 0.280277
+0.653438 -0.414414 0.633467
+-0.0463295 -0.21973 0.420531
+
+0.701977 -0.010841 -0.712117
+0.305973 0.907498 0.2878
+0.643125 -0.419918 0.640359
+-0.0468901 -0.217856 0.420568
+
+0.711217 -0.0114638 -0.702879
+0.306401 0.904947 0.295277
+0.632683 -0.425369 0.647127
+-0.0474507 -0.215982 0.42058
+
+0.720343 -0.0122076 -0.693511
+0.306722 0.902381 0.302705
+0.622115 -0.430766 0.653768
+-0.0480113 -0.214108 0.420569
+
+0.729351 -0.0130715 -0.684014
+0.306934 0.8998 0.310083
+0.611423 -0.436107 0.660282
+-0.048572 -0.212234 0.420533
+
+0.73824 -0.0140545 -0.674392
+0.307039 0.897205 0.31741
+0.600607 -0.44139 0.666668
+-0.0491326 -0.21036 0.420472
+
+0.747005 -0.0151558 -0.664645
+0.307037 0.8946 0.324684
+0.589671 -0.446612 0.672924
+-0.0496932 -0.208485 0.420388
+
+0.755645 -0.0163743 -0.654776
+0.306928 0.891983 0.331905
+0.578615 -0.451771 0.679049
+-0.0502538 -0.206611 0.420279
+
+0.764158 -0.017709 -0.644786
+0.306713 0.889359 0.33907
+0.567442 -0.456867 0.685042
+-0.0508145 -0.204737 0.420147
+
+0.77254 -0.0191588 -0.634677
+0.306392 0.886727 0.346178
+0.556153 -0.461896 0.690902
+-0.0513751 -0.202863 0.41999
+
+0.780788 -0.0207225 -0.624452
+0.305966 0.88409 0.353228
+0.544752 -0.466857 0.696628
+-0.0519357 -0.200989 0.419809
+
+0.788902 -0.0223991 -0.614111
+0.305435 0.881449 0.360219
+0.533239 -0.471748 0.702218
+-0.0524963 -0.199115 0.419603
+
+0.796877 -0.0241872 -0.603657
+0.3048 0.878805 0.367149
+0.521617 -0.476567 0.707672
+-0.053057 -0.197241 0.419374
+
+0.804711 -0.0260856 -0.593093
+0.304062 0.876161 0.374017
+0.509888 -0.481313 0.712988
+-0.0536176 -0.195367 0.41912
+
+0.812403 -0.0280929 -0.582419
+0.303221 0.873517 0.380822
+0.498054 -0.485983 0.718166
+-0.0541782 -0.193493 0.418842
+
+0.81995 -0.0302079 -0.571638
+0.302278 0.870875 0.387563
+0.486118 -0.490575 0.723205
+-0.0547388 -0.191619 0.41854
+
+0.827349 -0.032429 -0.560752
+0.301234 0.868237 0.394237
+0.474081 -0.495089 0.728103
+-0.0552995 -0.189744 0.418214
+
+0.834598 -0.0347549 -0.549763
+0.300089 0.865604 0.400845
+0.461945 -0.499522 0.73286
+-0.0558601 -0.18787 0.417864
+
+0.841694 -0.037184 -0.538673
+0.298845 0.862977 0.407385
+0.449714 -0.503873 0.737475
+-0.0564207 -0.185996 0.417489
+
+0.848636 -0.0397148 -0.527484
+0.297501 0.860359 0.413855
+0.437389 -0.508139 0.741947
+-0.0569813 -0.184122 0.41709
+
+0.855422 -0.0423457 -0.516198
+0.29606 0.85775 0.420254
+0.424973 -0.51232 0.746275
+-0.057542 -0.182248 0.416667
+
+0.862048 -0.0450751 -0.504818
+0.294522 0.855152 0.426581
+0.412468 -0.516414 0.750458
+-0.0581026 -0.180374 0.41622
+
+0.868514 -0.0479014 -0.493345
+0.292887 0.852567 0.432836
+0.399876 -0.520418 0.754496
+-0.0586632 -0.1785 0.415749
+
+0.874816 -0.0508228 -0.481782
+0.291157 0.849995 0.439016
+0.3872 -0.524333 0.758387
+-0.0592238 -0.176626 0.415253
+
+0.880953 -0.0538375 -0.47013
+0.289333 0.847439 0.445121
+0.374443 -0.528155 0.762132
+-0.0597845 -0.174752 0.414734
+
+0.886923 -0.0569439 -0.458393
+0.287416 0.8449 0.45115
+0.361606 -0.531885 0.765728
+-0.0603451 -0.172877 0.41419
+
+0.892651 -0.0573978 -0.44708
+0.283537 0.84255 0.457947
+0.350402 -0.535551 0.768377
+-0.060717 -0.171209 0.413691
+
+0.898175 -0.054825 -0.436207
+0.277406 0.840412 0.465568
+0.341068 -0.539168 0.770045
+-0.0608965 -0.169743 0.413221
+
+0.90345 -0.0477868 -0.426021
+0.26806 0.838496 0.474413
+0.334546 -0.542808 0.770349
+-0.060793 -0.168582 0.412811
+
+0.908355 -0.0362333 -0.416628
+0.255613 0.836588 0.484544
+0.33099 -0.546633 0.76918
+-0.0603766 -0.167755 0.412485
+
+0.91275 -0.0206592 -0.407995
+0.240528 0.834436 0.495846
+0.330202 -0.550718 0.7666
+-0.0596741 -0.16723 0.412218
+
+0.916522 -0.00149687 -0.399981
+0.223131 0.831849 0.508173
+0.331964 -0.555 0.762742
+-0.0587226 -0.166979 0.412004
+
+0.919859 0.0176757 -0.391852
+0.205747 0.828784 0.52037
+0.333958 -0.559289 0.758728
+-0.0577711 -0.166727 0.411766
+
+0.922761 0.0368477 -0.383608
+0.188389 0.825241 0.532435
+0.336188 -0.563578 0.754558
+-0.0568196 -0.166476 0.411504
+
+0.925229 0.0560085 -0.375253
+0.171071 0.821219 0.544366
+0.338654 -0.567858 0.750234
+-0.0558681 -0.166224 0.411217
+
+0.927265 0.0751471 -0.366788
+0.153805 0.81672 0.556159
+0.341356 -0.572121 0.745757
+-0.0549166 -0.165973 0.410906
+
+0.92887 0.094253 -0.358214
+0.136606 0.811744 0.567813
+0.344296 -0.576358 0.741128
+-0.0539651 -0.165721 0.410571
+
+0.930045 0.113316 -0.349535
+0.119487 0.806292 0.579323
+0.347474 -0.580562 0.736349
+-0.0530137 -0.16547 0.410212
+
+0.930794 0.132324 -0.340753
+0.102462 0.800368 0.590688
+0.35089 -0.584723 0.73142
+-0.0520622 -0.165218 0.409829
+
+0.931118 0.151268 -0.331868
+0.0855427 0.793972 0.601906
+0.354543 -0.588834 0.726342
+-0.0511107 -0.164967 0.409422
+
+0.93102 0.170138 -0.322884
+0.0687442 0.787108 0.612972
+0.358434 -0.592886 0.721118
+-0.0501592 -0.164715 0.40899
+
+0.930503 0.188922 -0.313803
+0.0520791 0.779779 0.623885
+0.362562 -0.59687 0.715748
+-0.0492077 -0.164464 0.408534
+
+0.92957 0.20761 -0.304626
+0.0355609 0.771987 0.634643
+0.366925 -0.600778 0.710233
+-0.0482562 -0.164212 0.408054
+
+0.928225 0.226193 -0.295356
+0.0192025 0.763736 0.645243
+0.371523 -0.604602 0.704575
+-0.0473047 -0.163961 0.40755
+
+0.926471 0.244661 -0.285995
+0.00301707 0.755031 0.655682
+0.376355 -0.608333 0.698776
+-0.0463532 -0.163709 0.407021
+
+0.924312 0.263003 -0.276545
+-0.0129824 0.745876 0.665958
+0.381417 -0.611963 0.692837
+-0.0454017 -0.163458 0.406469
+
+0.921753 0.281209 -0.267009
+-0.0287831 0.736276 0.676069
+0.386709 -0.615483 0.686758
+-0.0444502 -0.163206 0.405892
+
+0.918797 0.299271 -0.257388
+-0.0443724 0.726235 0.686013
+0.392228 -0.618885 0.680542
+-0.0434987 -0.162955 0.405291
+
+0.915451 0.317178 -0.247686
+-0.0597376 0.715761 0.695786
+0.397972 -0.622162 0.674191
+-0.0425472 -0.162703 0.404666
+
+0.911718 0.334921 -0.237904
+-0.0748662 0.704857 0.705388
+0.403937 -0.625304 0.667705
+-0.0415958 -0.162452 0.404016
+
+0.907605 0.352491 -0.228044
+-0.0897461 0.693531 0.714815
+0.410121 -0.628303 0.661087
+-0.0406443 -0.1622 0.403343
+
+0.903116 0.369879 -0.21811
+-0.104365 0.681789 0.724066
+0.416521 -0.631152 0.654337
+-0.0396928 -0.161949 0.402645
+
+0.898269 0.386885 -0.208403
+-0.11851 0.669944 0.732892
+0.423164 -0.633637 0.64764
+-0.0389186 -0.161829 0.402024
+
+0.893115 0.403459 -0.198916
+-0.132151 0.658021 0.741312
+0.42998 -0.63579 0.641006
+-0.0383501 -0.161876 0.401499
+
+0.887662 0.419632 -0.189645
+-0.145313 0.646038 0.749345
+0.436967 -0.637608 0.634442
+-0.0379878 -0.162086 0.401075
+
+0.882066 0.435043 -0.180823
+-0.157701 0.634313 0.756821
+0.443948 -0.63905 0.628112
+-0.0379708 -0.162549 0.400851
+
+0.875661 0.45123 -0.172074
+-0.170544 0.622298 0.763977
+0.45181 -0.639638 0.621876
+-0.0383214 -0.163369 0.400838
+
+0.868585 0.467797 -0.163479
+-0.183516 0.610104 0.770776
+0.460306 -0.639484 0.615775
+-0.0390729 -0.164562 0.401084
+
+0.860243 0.48584 -0.154733
+-0.197436 0.597184 0.777425
+0.470108 -0.638224 0.609646
+-0.0401167 -0.166074 0.40151
+
+0.851358 0.503854 -0.146018
+-0.211146 0.583937 0.783859
+0.480216 -0.636513 0.603526
+-0.0413162 -0.167724 0.402034
+
+0.842072 0.521608 -0.13726
+-0.224474 0.570315 0.79016
+0.490435 -0.63456 0.597333
+-0.0425156 -0.169375 0.402534
+
+0.832393 0.539092 -0.128459
+-0.237408 0.556329 0.796326
+0.500758 -0.632359 0.591069
+-0.043715 -0.171026 0.40301
+
+0.822329 0.556297 -0.119617
+-0.249939 0.541991 0.802357
+0.51118 -0.629905 0.584735
+-0.0449144 -0.172676 0.403462
+
+0.811889 0.573213 -0.110736
+-0.262055 0.527311 0.808251
+0.521693 -0.627192 0.578332
+-0.0461138 -0.174327 0.40389
+
+0.801081 0.589833 -0.101816
+-0.273747 0.512302 0.814009
+0.53229 -0.624215 0.57186
+-0.0473133 -0.175978 0.404294
+
+0.789913 0.606148 -0.0928603
+-0.285004 0.496974 0.819628
+0.542965 -0.620969 0.565321
+-0.0485127 -0.177628 0.404673
+
+0.778394 0.622148 -0.0838691
+-0.295819 0.48134 0.825108
+0.553709 -0.617449 0.558715
+-0.0497121 -0.179279 0.405028
+
+0.766535 0.637826 -0.074844
+-0.306181 0.465412 0.830449
+0.564515 -0.613652 0.552045
+-0.0509115 -0.18093 0.405359
+
+0.754344 0.653175 -0.0657867
+-0.316081 0.449204 0.835649
+0.575376 -0.609572 0.54531
+-0.0521109 -0.18258 0.405666
+
+0.741831 0.668186 -0.0566985
+-0.325513 0.432727 0.840707
+0.586284 -0.605206 0.538513
+-0.0533104 -0.184231 0.405949
+
+0.729005 0.682853 -0.0475809
+-0.334467 0.415995 0.845624
+0.59723 -0.60055 0.531654
+-0.0545098 -0.185882 0.406207
+
+0.715877 0.697168 -0.0384354
+-0.342936 0.399022 0.850398
+0.608207 -0.595599 0.524734
+-0.0557092 -0.187532 0.406441
+
+0.702456 0.711125 -0.0292634
+-0.350913 0.38182 0.855028
+0.619205 -0.590351 0.517755
+-0.0569086 -0.189183 0.406651
+
+0.688754 0.724717 -0.0200664
+-0.358391 0.364405 0.859515
+0.630217 -0.584803 0.510717
+-0.058108 -0.190834 0.406837
+
+0.674781 0.737939 -0.0108458
+-0.365363 0.346789 0.863856
+0.641234 -0.57895 0.503622
+-0.0593075 -0.192484 0.406999
+
+0.660546 0.750784 -0.00160326
+-0.371824 0.328988 0.868052
+0.652247 -0.572792 0.496471
+-0.0605069 -0.194135 0.407136
+
+0.646061 0.763247 0.00765989
+-0.377768 0.311015 0.872102
+0.663247 -0.566325 0.489265
+-0.0617063 -0.195786 0.40725
+
+0.631338 0.775323 0.0169421
+-0.383189 0.292885 0.876005
+0.674224 -0.559547 0.482005
+-0.0629057 -0.197436 0.407339
+
+0.616386 0.787007 0.026242
+-0.388084 0.274613 0.87976
+0.685171 -0.552456 0.474692
+-0.0641051 -0.199087 0.407404
+
+0.601217 0.798294 0.035558
+-0.392447 0.256215 0.883368
+0.696078 -0.545051 0.467328
+-0.0653046 -0.200738 0.407445
+
+0.585842 0.809181 0.0448887
+-0.396274 0.237704 0.886828
+0.706934 -0.537329 0.459914
+-0.066504 -0.202388 0.407461
+
+0.570273 0.819663 0.0542325
+-0.399562 0.219096 0.890139
+0.717732 -0.529291 0.452451
+-0.0677034 -0.204039 0.407454
+
+0.555082 0.829389 0.0632231
+-0.403275 0.201861 0.892537
+0.727498 -0.520927 0.446521
+-0.0688806 -0.205447 0.407416
+
+0.541949 0.837379 0.071336
+-0.408103 0.188017 0.893365
+0.734672 -0.51327 0.443632
+-0.0700284 -0.206379 0.407374
+
+0.530342 0.844157 0.0783368
+-0.415034 0.177947 0.892234
+0.739246 -0.505702 0.444726
+-0.0711125 -0.206701 0.407334
+
+0.51973 0.850172 0.0841915
+-0.424318 0.171343 0.889155
+0.741509 -0.497844 0.449795
+-0.0721164 -0.206415 0.407298
+
+0.51076 0.855116 0.0888893
+-0.435654 0.168299 0.88424
+0.741168 -0.490359 0.458495
+-0.0730546 -0.205567 0.407272
+
+0.502587 0.859534 0.0927803
+-0.448465 0.167456 0.877973
+0.739111 -0.482867 0.469633
+-0.0739404 -0.204338 0.407244
+
+0.494866 0.863635 0.0961387
+-0.462167 0.167892 0.870755
+0.735873 -0.475339 0.482228
+-0.0747867 -0.202868 0.40719
+
+0.489701 0.866267 0.0988697
+-0.474685 0.169771 0.863627
+0.731347 -0.469851 0.49434
+-0.0755749 -0.201575 0.407167
+
+0.489055 0.866423 0.100681
+-0.485338 0.174392 0.856758
+0.724757 -0.467866 0.505795
+-0.0762188 -0.200603 0.407253
+
+0.492997 0.86408 0.101589
+-0.494068 0.181934 0.850175
+0.716136 -0.469325 0.516607
+-0.0767225 -0.199955 0.407446
+
+0.501632 0.859097 0.101581
+-0.500703 0.192576 0.843926
+0.705452 -0.474202 0.526754
+-0.0770587 -0.199662 0.407767
+
+0.515829 0.850775 0.100507
+-0.50465 0.206955 0.838152
+0.692278 -0.483064 0.536097
+-0.0772311 -0.199776 0.408223
+
+0.535429 0.838833 0.0983566
+-0.505657 0.225107 0.832849
+0.676481 -0.495667 0.544691
+-0.0772336 -0.200295 0.408804
+
+0.559937 0.823057 0.0951154
+-0.503465 0.246827 0.828009
+0.658022 -0.51152 0.552588
+-0.07709 -0.20119 0.409481
+
+0.587565 0.804028 0.0911443
+-0.49853 0.27097 0.823433
+0.637366 -0.529259 0.560045
+-0.0768468 -0.20234 0.41022
+
+0.614564 0.784032 0.0872083
+-0.492537 0.295004 0.818767
+0.616213 -0.546138 0.567464
+-0.0766037 -0.20349 0.410935
+
+0.6409 0.763091 0.0833076
+-0.485489 0.318883 0.814011
+0.594599 -0.562144 0.574844
+-0.0763605 -0.20464 0.411625
+
+0.666538 0.741226 0.0794429
+-0.47739 0.342562 0.809166
+0.572561 -0.577265 0.582185
+-0.0761173 -0.20579 0.412292
+
+0.691445 0.718461 0.0756144
+-0.468247 0.365998 0.804232
+0.550135 -0.591489 0.589485
+-0.0758741 -0.20694 0.412934
+
+0.715588 0.69482 0.0718227
+-0.458069 0.389147 0.799211
+0.527358 -0.604805 0.596744
+-0.0756309 -0.20809 0.413552
+
+0.738935 0.670329 0.0680682
+-0.446865 0.411964 0.794102
+0.504268 -0.617207 0.603961
+-0.0753877 -0.209239 0.414146
+
+0.761456 0.645014 0.0643512
+-0.434648 0.434406 0.788906
+0.480901 -0.628687 0.611135
+-0.0751445 -0.210389 0.414716
+
+0.78312 0.618904 0.0606723
+-0.421431 0.45643 0.783624
+0.457296 -0.639241 0.618265
+-0.0749013 -0.211539 0.415261
+
+0.803897 0.592028 0.0570318
+-0.40723 0.477994 0.778257
+0.433489 -0.648864 0.62535
+-0.0746582 -0.212689 0.415782
+
+0.82376 0.564415 0.0534301
+-0.392063 0.499057 0.772806
+0.409519 -0.657555 0.632389
+-0.074415 -0.213839 0.416279
+
+0.842682 0.536097 0.0498677
+-0.375949 0.519576 0.76727
+0.385422 -0.665313 0.639382
+-0.0741718 -0.214989 0.416752
+
+0.860636 0.507107 0.0463449
+-0.358907 0.539511 0.761652
+0.361235 -0.672138 0.646327
+-0.0739286 -0.216139 0.417201
+
+0.877598 0.477478 0.0428621
+-0.340962 0.558824 0.75595
+0.336997 -0.678034 0.653224
+-0.0736854 -0.217288 0.417626
+
+0.893543 0.447244 0.0394196
+-0.322137 0.577475 0.750167
+0.312744 -0.683005 0.660072
+-0.0734422 -0.218438 0.418026
+
+0.90845 0.41644 0.036018
+-0.302458 0.595426 0.744303
+0.288511 -0.687056 0.66687
+-0.073199 -0.219588 0.418402
+
+0.922296 0.385102 0.0326575
+-0.281951 0.612642 0.738359
+0.264336 -0.690193 0.673617
+-0.0729559 -0.220738 0.418754
+
+0.935062 0.353268 0.0293385
+-0.260647 0.629085 0.732335
+0.240254 -0.692426 0.680312
+-0.0727127 -0.221888 0.419082
+
+0.946729 0.320974 0.0260614
+-0.238575 0.644723 0.726233
+0.216299 -0.693763 0.686955
+-0.0724695 -0.223038 0.419386
+
+0.95728 0.28826 0.0228265
+-0.215768 0.659522 0.720052
+0.192508 -0.694217 0.693544
+-0.0722263 -0.224187 0.419665
+
+0.966698 0.255164 0.0196342
+-0.192257 0.67345 0.713795
+0.168912 -0.693799 0.70008
+-0.0719831 -0.225337 0.41992
+
+0.97497 0.221726 0.0164849
+-0.168079 0.686476 0.707461
+0.145546 -0.692524 0.70656
+-0.0717399 -0.226487 0.420151
+
+0.98208 0.187986 0.0133788
+-0.143268 0.698571 0.701051
+0.122442 -0.690406 0.712985
+-0.0714967 -0.227637 0.420358
+
+0.988019 0.153986 0.0103163
+-0.117863 0.709707 0.694568
+0.0996322 -0.687462 0.719354
+-0.0712535 -0.228787 0.420541
+
+0.992775 0.119766 0.00729769
+-0.0918997 0.719859 0.68801
+0.0771471 -0.68371 0.725665
+-0.0710104 -0.229937 0.4207
+
+0.99634 0.0853687 0.00432335
+-0.0654191 0.729001 0.681379
+0.0550167 -0.679168 0.731918
+-0.0707672 -0.231087 0.420834
+
+0.998706 0.0508354 0.00139357
+-0.0384613 0.737111 0.674676
+0.0332702 -0.673857 0.738112
+-0.070524 -0.232236 0.420944
+
+0.999868 0.016209 -0.00149135
+-0.0110676 0.744167 0.667902
+0.0119358 -0.667797 0.744247
+-0.0702808 -0.233386 0.42103
+
+0.99982 -0.018468 -0.00433109
+0.0167199 0.750148 0.661058
+-0.00895947 -0.661012 0.750322
+-0.0700376 -0.234536 0.421092
+
+0.998561 -0.0531526 -0.00712537
+0.0448578 0.755038 0.654144
+-0.0293896 -0.653523 0.756336
+-0.0697944 -0.235686 0.421129
+
+0.996089 -0.0878018 -0.0098739
+0.0733025 0.75882 0.647162
+-0.0493295 -0.645355 0.762288
+-0.0695512 -0.236836 0.421143
+
+0.992405 -0.122372 -0.0125764
+0.102009 0.761479 0.640112
+-0.0687555 -0.636533 0.768178
+-0.0693081 -0.237986 0.421132
+
+0.98751 -0.156821 -0.0152326
+0.130933 0.763003 0.632996
+-0.0876448 -0.627084 0.774005
+-0.0690649 -0.239136 0.421097
+
+0.981407 -0.191105 -0.0178422
+0.160027 0.76338 0.625813
+-0.105976 -0.617033 0.779769
+-0.0688217 -0.240285 0.421038
+
+0.974103 -0.225182 -0.0204049
+0.189247 0.762602 0.618566
+-0.123729 -0.606409 0.785468
+-0.0685785 -0.241435 0.420955
+
+0.965603 -0.259007 -0.0229205
+0.218544 0.760661 0.611255
+-0.140885 -0.595239 0.791102
+-0.0683353 -0.242585 0.420847
+
+0.955917 -0.292539 -0.0253888
+0.247872 0.757553 0.603881
+-0.157425 -0.583553 0.79667
+-0.0680921 -0.243735 0.420715
+
+0.945052 -0.325734 -0.0278094
+0.277185 0.753274 0.596445
+-0.173335 -0.57138 0.802172
+-0.0678489 -0.244885 0.42056
+
+0.933022 -0.358552 -0.0301822
+0.306433 0.747822 0.588948
+-0.188598 -0.55875 0.807607
+-0.0676057 -0.246035 0.420379
+
+0.919838 -0.39095 -0.0325069
+0.335571 0.741199 0.581391
+-0.203201 -0.545694 0.812975
+-0.0673626 -0.247185 0.420175
+
+0.905515 -0.422886 -0.0347833
+0.36455 0.733407 0.573775
+-0.217131 -0.532242 0.818274
+-0.0671194 -0.248334 0.419947
+
+0.890069 -0.454321 -0.0370112
+0.393323 0.724449 0.566101
+-0.230379 -0.518426 0.823505
+-0.0668762 -0.249484 0.419694
+
+0.873517 -0.485213 -0.0391903
+0.421843 0.714333 0.55837
+-0.242933 -0.504278 0.828666
+-0.066633 -0.250634 0.419417
+
+0.855879 -0.515523 -0.0413205
+0.450062 0.703067 0.550582
+-0.254787 -0.489828 0.833758
+-0.0663898 -0.251784 0.419116
+
+0.837174 -0.545213 -0.0434015
+0.477933 0.690661 0.54274
+-0.265933 -0.47511 0.838779
+-0.0661466 -0.252934 0.418791
+
+0.817424 -0.574242 -0.0454332
+0.505411 0.677128 0.534843
+-0.276366 -0.460156 0.843729
+-0.0659034 -0.254084 0.418442
+
+0.796652 -0.602575 -0.0474153
+0.53245 0.66248 0.526894
+-0.286082 -0.444997 0.848608
+-0.0656602 -0.255234 0.418068
+
+0.774884 -0.630175 -0.0493477
+0.559003 0.646735 0.518892
+-0.295078 -0.429667 0.853414
+-0.0654171 -0.256383 0.41767
+
+0.752144 -0.657005 -0.0512302
+0.585027 0.62991 0.51084
+-0.303354 -0.414196 0.858148
+-0.0651739 -0.257533 0.417248
+
+0.72846 -0.68303 -0.0530627
+0.610477 0.612024 0.502737
+-0.310909 -0.398617 0.862809
+-0.0649307 -0.258683 0.416802
+
+0.70386 -0.708218 -0.0548449
+0.635309 0.5931 0.494586
+-0.317746 -0.382963 0.867397
+-0.0646875 -0.259833 0.416332
+
+0.678375 -0.732534 -0.0565767
+0.659482 0.573159 0.486386
+-0.323867 -0.367264 0.87191
+-0.0644443 -0.260983 0.415838
+
+0.652035 -0.755947 -0.058258
+0.682954 0.552228 0.47814
+-0.329277 -0.351552 0.876349
+-0.0642011 -0.262133 0.415319
+
+0.624873 -0.778426 -0.0598886
+0.705684 0.530332 0.469848
+-0.333981 -0.335858 0.880713
+-0.0639579 -0.263283 0.414776
+
+0.596921 -0.799942 -0.0614684
+0.727633 0.5075 0.461511
+-0.337987 -0.320212 0.885002
+-0.0637148 -0.264432 0.414209
+
+0.568213 -0.820466 -0.0629972
+0.748763 0.483763 0.453131
+-0.341303 -0.304645 0.889215
+-0.0634716 -0.265582 0.413618
+
+0.538786 -0.839972 -0.0644749
+0.769035 0.45915 0.444708
+-0.343939 -0.289186 0.893352
+-0.0632284 -0.266732 0.413002
+
+0.508676 -0.858432 -0.0659015
+0.788415 0.433696 0.436244
+-0.345904 -0.273864 0.897412
+-0.0629852 -0.267882 0.412363
+
+0.47792 -0.875823 -0.0672767
+0.806868 0.407435 0.427739
+-0.347213 -0.258708 0.901395
+-0.062742 -0.269032 0.411699
+
+0.446556 -0.892122 -0.0686006
+0.82436 0.380403 0.419194
+-0.347877 -0.243745 0.905301
+-0.0624988 -0.270182 0.411011
+
+0.414623 -0.907307 -0.0698729
+0.84086 0.352636 0.410612
+-0.347911 -0.229002 0.909129
+-0.0622556 -0.271332 0.410299
+
+0.382161 -0.921357 -0.0710936
+0.856337 0.324174 0.401992
+-0.347331 -0.214506 0.912879
+-0.0620124 -0.272481 0.409563
+
+0.349212 -0.934253 -0.0722627
+0.870763 0.295056 0.393336
+-0.346154 -0.200281 0.916551
+-0.0617693 -0.273631 0.408802
+
+0.315815 -0.945979 -0.07338
+0.884111 0.265324 0.384644
+-0.344396 -0.186353 0.920143
+-0.0615261 -0.274781 0.408017
+
+0.282014 -0.956518 -0.0744454
+0.896354 0.235018 0.375919
+-0.342077 -0.172744 0.923657
+-0.0612829 -0.275931 0.407208
+
+0.258169 -0.963345 -0.0729101
+0.904119 0.214321 0.369642
+-0.340466 -0.16135 0.926309
+-0.0613301 -0.27691 0.406779
+
+0.247294 -0.96652 -0.0684478
+0.907269 0.206175 0.366545
+-0.340161 -0.152745 0.927879
+-0.0617279 -0.277686 0.406832
+
+0.252394 -0.965751 -0.0601927
+0.90522 0.213681 0.36731
+-0.341868 -0.147194 0.928149
+-0.0625032 -0.278137 0.407507
+
+0.26761 -0.962253 -0.0495414
+0.899646 0.231127 0.37043
+-0.344997 -0.1437 0.927538
+-0.0635643 -0.278444 0.408565
+
+0.282717 -0.958415 -0.0388787
+0.893736 0.248487 0.373483
+-0.348291 -0.140337 0.926822
+-0.0646255 -0.27875 0.4096
+
+0.297706 -0.954241 -0.0282058
+0.887494 0.265755 0.376468
+-0.351745 -0.137109 0.926
+-0.0656866 -0.279057 0.41061
+
+0.31257 -0.949733 -0.0175242
+0.880921 0.282923 0.379386
+-0.355357 -0.134022 0.925073
+-0.0667478 -0.279363 0.411596
+
+0.327301 -0.944895 -0.00683523
+0.874017 0.299985 0.382235
+-0.359121 -0.13108 0.92404
+-0.0678089 -0.27967 0.412558
+
+0.341892 -0.939731 0.00385977
+0.866785 0.316934 0.385015
+-0.363034 -0.128288 0.922902
+-0.0688701 -0.279976 0.413495
+
+0.356334 -0.934245 0.0145594
+0.859227 0.333763 0.387727
+-0.367091 -0.12565 0.921659
+-0.0699312 -0.280283 0.414409
+
+0.37062 -0.928441 0.0252624
+0.851344 0.350465 0.390369
+-0.371288 -0.123171 0.920312
+-0.0709923 -0.280589 0.415298
+
+0.384742 -0.922323 0.0359672
+0.843139 0.367034 0.392941
+-0.37562 -0.120856 0.91886
+-0.0720535 -0.280896 0.416163
+
+0.398694 -0.915896 0.0466727
+0.834614 0.383463 0.395444
+-0.380083 -0.118707 0.917304
+-0.0731146 -0.281202 0.417004
+
+0.412468 -0.909164 0.0573774
+0.825772 0.399744 0.397876
+-0.384671 -0.11673 0.915643
+-0.0741758 -0.281509 0.417821
+
+0.426056 -0.902132 0.0680799
+0.816615 0.415873 0.400237
+-0.389379 -0.114929 0.913879
+-0.0752369 -0.281815 0.418613
+
+0.439453 -0.894805 0.0787789
+0.807146 0.431841 0.402528
+-0.394204 -0.113306 0.912012
+-0.0762981 -0.282122 0.419382
+
+0.452651 -0.887188 0.089473
+0.797368 0.447643 0.404747
+-0.399139 -0.111866 0.910041
+-0.0773592 -0.282428 0.420126
+
+0.465643 -0.879286 0.100161
+0.787284 0.463271 0.406895
+-0.404179 -0.110613 0.907967
+-0.0784203 -0.282734 0.420846
+
+0.478423 -0.871106 0.110841
+0.776897 0.47872 0.408972
+-0.40932 -0.109549 0.905791
+-0.0794815 -0.283041 0.421542
+
+0.490984 -0.862652 0.121513
+0.766211 0.493984 0.410976
+-0.414554 -0.108678 0.903512
+-0.0805426 -0.283347 0.422213
+
+0.503321 -0.853931 0.132174
+0.755228 0.509055 0.412907
+-0.419878 -0.108003 0.901131
+-0.0816038 -0.283654 0.422861
+
+0.515427 -0.844948 0.142824
+0.743954 0.523929 0.414767
+-0.425286 -0.107528 0.898649
+-0.0826649 -0.28396 0.423484
+
+0.527296 -0.835709 0.15346
+0.73239 0.538598 0.416553
+-0.430771 -0.107254 0.896065
+-0.083726 -0.284267 0.424083
+
+0.538922 -0.82622 0.164083
+0.720542 0.553056 0.418267
+-0.436328 -0.107185 0.893381
+-0.0847872 -0.284573 0.424658
+
+0.550299 -0.816489 0.17469
+0.708414 0.567299 0.419907
+-0.441951 -0.107322 0.890596
+-0.0858483 -0.28488 0.425209
+
+0.5561 -0.810629 0.183396
+0.700245 0.575842 0.421974
+-0.447671 -0.106238 0.887865
+-0.0867753 -0.284988 0.425904
+
+0.551883 -0.812448 0.188026
+0.700128 0.573899 0.424808
+-0.453042 -0.102802 0.885542
+-0.0873661 -0.284711 0.426928
+
+0.537549 -0.821878 0.188567
+0.708048 0.561385 0.428387
+-0.45794 -0.0967645 0.883701
+-0.0876187 -0.284049 0.428277
+
+0.51479 -0.836932 0.185837
+0.72199 0.540112 0.432445
+-0.4623 -0.0884455 0.882302
+-0.0876391 -0.283065 0.42988
+
+0.491615 -0.851348 0.183088
+0.735302 0.518472 0.436483
+-0.466525 -0.0799563 0.880887
+-0.0876596 -0.282081 0.431458
+
+0.468043 -0.865113 0.18032
+0.747973 0.496483 0.4405
+-0.470608 -0.0712984 0.879457
+-0.08768 -0.281098 0.433012
+
+0.444092 -0.878217 0.177532
+0.759994 0.474165 0.444497
+-0.474544 -0.0624738 0.878012
+-0.0877005 -0.280114 0.434542
+
+0.41978 -0.890649 0.174726
+0.771355 0.451535 0.448473
+-0.478327 -0.0534845 0.876552
+-0.087721 -0.27913 0.436048
+
+0.395128 -0.902399 0.1719
+0.782048 0.428615 0.452428
+-0.481949 -0.0443325 0.875077
+-0.0877414 -0.278147 0.437529
+
+0.370154 -0.913458 0.169056
+0.792065 0.405423 0.456361
+-0.485406 -0.0350205 0.873587
+-0.0877619 -0.277163 0.438987
+
+0.344878 -0.923818 0.166193
+0.801399 0.381979 0.460274
+-0.488692 -0.025551 0.872082
+-0.0877824 -0.276179 0.44042
+
+0.319319 -0.933469 0.163312
+0.810043 0.358304 0.464165
+-0.491799 -0.0159268 0.870563
+-0.0878028 -0.275196 0.441829
+
+0.293497 -0.942405 0.160412
+0.817991 0.334417 0.468035
+-0.494723 -0.00615108 0.869029
+-0.0878233 -0.274212 0.443214
+
+0.267433 -0.950618 0.157494
+0.825237 0.31034 0.471883
+-0.497457 0.00377296 0.86748
+-0.0878438 -0.273228 0.444574
+
+0.241147 -0.958102 0.154558
+0.831776 0.286092 0.475709
+-0.499996 0.0138418 0.865917
+-0.0878642 -0.272245 0.445911
+
+0.21466 -0.964851 0.151604
+0.837605 0.261695 0.479514
+-0.502333 0.0240518 0.86434
+-0.0878847 -0.271261 0.447223
+
+0.187992 -0.970859 0.148632
+0.842719 0.237169 0.483296
+-0.504463 0.0343991 0.862748
+-0.0879052 -0.270277 0.448511
+
+0.161164 -0.976122 0.145642
+0.847115 0.212536 0.487056
+-0.506381 0.0448795 0.861141
+-0.0879256 -0.269294 0.449775
+
+0.134198 -0.980636 0.142635
+0.850791 0.187816 0.490794
+-0.50808 0.0554887 0.859521
+-0.0879461 -0.26831 0.451015
+
+0.107114 -0.984396 0.13961
+0.853745 0.16303 0.49451
+-0.509554 0.0662222 0.857886
+-0.0879666 -0.267327 0.45223
+
+0.0799337 -0.987401 0.136567
+0.855976 0.138201 0.498203
+-0.5108 0.0770752 0.856238
+-0.087987 -0.266343 0.453421
+
+0.052678 -0.989647 0.133508
+0.857482 0.113348 0.501873
+-0.51181 0.088043 0.854575
+-0.0880075 -0.265359 0.454588
+
+0.0253686 -0.991133 0.130431
+0.858264 0.0884934 0.505521
+-0.512581 0.0991202 0.852899
+-0.088028 -0.264376 0.455731
+
+-0.0019733 -0.991857 0.127338
+0.858323 0.0636581 0.509146
+-0.513106 0.110302 0.851208
+-0.0880484 -0.263392 0.45685
+
+-0.0293262 -0.99182 0.124227
+0.85766 0.0388632 0.512747
+-0.513381 0.121582 0.849504
+-0.0880689 -0.262408 0.457945
+
+-0.0566688 -0.991021 0.1211
+0.856276 0.01413 0.516326
+-0.513401 0.132955 0.847787
+-0.0880893 -0.261425 0.459015
+
+-0.0839797 -0.989461 0.117957
+0.854174 -0.0105206 0.519881
+-0.513161 0.144415 0.846055
+-0.0881098 -0.260441 0.460061
+
+-0.111237 -0.987141 0.114797
+0.851357 -0.0350676 0.523413
+-0.512657 0.155956 0.844311
+-0.0881303 -0.259457 0.461083
+
+-0.138421 -0.984063 0.11162
+0.847829 -0.0594901 0.526921
+-0.511884 0.167572 0.842553
+-0.0881507 -0.258474 0.462081
+
+-0.165508 -0.98023 0.108428
+0.843595 -0.0837672 0.530406
+-0.510837 0.179256 0.840781
+-0.0881712 -0.25749 0.463055
+
+-0.192479 -0.975644 0.105219
+0.838658 -0.107878 0.533867
+-0.509513 0.191001 0.838996
+-0.0881917 -0.256506 0.464004
+
+-0.219312 -0.970309 0.101995
+0.833026 -0.131803 0.537304
+-0.507908 0.202802 0.837198
+-0.0882121 -0.255523 0.464929
+
+-0.245986 -0.96423 0.0987547
+0.826703 -0.155522 0.540718
+-0.506018 0.21465 0.835387
+-0.0882326 -0.254539 0.465831
+
+-0.27248 -0.95741 0.095499
+0.819696 -0.179013 0.544107
+-0.503838 0.226538 0.833563
+-0.0882531 -0.253555 0.466707
+
+-0.298773 -0.949857 0.0922278
+0.812014 -0.202258 0.547472
+-0.501366 0.23846 0.831726
+-0.0882735 -0.252572 0.46756
+
+-0.324846 -0.941576 0.0889413
+0.803663 -0.225236 0.550813
+-0.498599 0.250408 0.829876
+-0.088294 -0.251588 0.468389
+
+-0.350677 -0.932572 0.0856395
+0.794652 -0.247928 0.554129
+-0.495533 0.262374 0.828014
+-0.0883145 -0.250604 0.469193
+
+-0.376247 -0.922855 0.0823228
+0.784991 -0.270316 0.557421
+-0.492166 0.274351 0.826138
+-0.0883349 -0.249621 0.469973
+
+-0.401536 -0.91243 0.0789911
+0.774689 -0.29238 0.560688
+-0.488494 0.28633 0.82425
+-0.0883554 -0.248637 0.470729
+
+-0.426524 -0.901308 0.0756446
+0.763756 -0.314101 0.563931
+-0.484515 0.298304 0.82235
+-0.0883759 -0.247653 0.471461
+
+-0.451191 -0.889495 0.0722835
+0.752202 -0.335461 0.567149
+-0.480228 0.310264 0.820437
+-0.0883963 -0.24667 0.472169
+
+-0.475518 -0.877003 0.068908
+0.74004 -0.356442 0.570342
+-0.47563 0.322202 0.818512
+-0.0884168 -0.245686 0.472852
+
+-0.499487 -0.863841 0.0655181
+0.72728 -0.377028 0.57351
+-0.470719 0.33411 0.816575
+-0.0884372 -0.244702 0.473511
+
+-0.523078 -0.850018 0.0621139
+0.713936 -0.397199 0.576653
+-0.465494 0.34598 0.814625
+-0.0884577 -0.243719 0.474146
+
+-0.546274 -0.835547 0.0586958
+0.70002 -0.41694 0.57977
+-0.459953 0.357802 0.812663
+-0.0884782 -0.242735 0.474757
+
+-0.569057 -0.820439 0.0552637
+0.685545 -0.436233 0.582862
+-0.454095 0.369567 0.810689
+-0.0884986 -0.241751 0.475344
+
+-0.591408 -0.804706 0.0518178
+0.670525 -0.455064 0.585929
+-0.44792 0.381268 0.808704
+-0.0885191 -0.240768 0.475906
+
+-0.613311 -0.78836 0.0483583
+0.654975 -0.473415 0.588971
+-0.441427 0.392896 0.806706
+-0.0885396 -0.239784 0.476445
+
+-0.634748 -0.771414 0.0448852
+0.638908 -0.491272 0.591987
+-0.434616 0.40444 0.804697
+-0.08856 -0.2388 0.476959
+
+-0.655704 -0.753882 0.0413989
+0.622341 -0.50862 0.594977
+-0.427486 0.415893 0.802676
+-0.0885805 -0.237817 0.477449
+
+-0.676161 -0.735778 0.0378993
+0.605288 -0.525445 0.597941
+-0.420038 0.427245 0.800644
+-0.088601 -0.236833 0.477914
+
+-0.696105 -0.717116 0.0343867
+0.587767 -0.541732 0.60088
+-0.412272 0.438487 0.7986
+-0.0886214 -0.235849 0.478356
+
+-0.715519 -0.697911 0.0308612
+0.569792 -0.557469 0.603792
+-0.404189 0.449609 0.796544
+-0.0886419 -0.234866 0.478773
+
+-0.73439 -0.678178 0.0273228
+0.551382 -0.572642 0.606679
+-0.39579 0.460604 0.794477
+-0.0886624 -0.233882 0.479167
+
+-0.752701 -0.657933 0.0237719
+0.532553 -0.587239 0.609539
+-0.387076 0.471461 0.7924
+-0.0886828 -0.232898 0.479536
+
+-0.770441 -0.637191 0.0202085
+0.513323 -0.601247 0.612373
+-0.378049 0.482171 0.79031
+-0.0887033 -0.231915 0.47988
+
+-0.787594 -0.61597 0.0166327
+0.49371 -0.614657 0.615181
+-0.36871 0.492724 0.78821
+-0.0887238 -0.230931 0.480201
+
+-0.804148 -0.594287 0.0130448
+0.473731 -0.627456 0.617963
+-0.359062 0.503113 0.786099
+-0.0887442 -0.229947 0.480497
+
+-0.82009 -0.572157 0.00944478
+0.453406 -0.639634 0.620718
+-0.349107 0.513327 0.783977
+-0.0887647 -0.228964 0.48077
+
+-0.835408 -0.549599 0.00583289
+0.432754 -0.651183 0.623446
+-0.338847 0.523356 0.781845
+-0.0887851 -0.22798 0.481018
+
+-0.850091 -0.526631 0.00220924
+0.411793 -0.662092 0.626148
+-0.328286 0.533193 0.779701
+-0.0888056 -0.226996 0.481242
+
+-0.864127 -0.503271 -0.00142601
+0.390543 -0.672352 0.628823
+-0.317427 0.542826 0.777547
+-0.0888261 -0.226013 0.481441
+
+-0.877507 -0.479537 -0.00507272
+0.369023 -0.681957 0.631472
+-0.306273 0.552249 0.775382
+-0.0888465 -0.225029 0.481617
+
+-0.890219 -0.455448 -0.00873074
+0.347254 -0.690898 0.634093
+-0.294829 0.56145 0.773207
+-0.088867 -0.224045 0.481768
+
+-0.902255 -0.431023 -0.0123999
+0.325255 -0.699169 0.636688
+-0.283097 0.570422 0.771022
+-0.0888875 -0.223062 0.481895
+
+-0.913606 -0.406282 -0.0160801
+0.303048 -0.706764 0.639255
+-0.271083 0.579154 0.768827
+-0.0889079 -0.222078 0.481998
+
+-0.924263 -0.381244 -0.0197712
+0.280651 -0.713676 0.641796
+-0.258791 0.587639 0.766621
+-0.0889284 -0.221094 0.482077
+
+-0.934219 -0.355928 -0.023473
+0.258086 -0.719901 0.644309
+-0.246226 0.595867 0.764405
+-0.0889489 -0.220111 0.482132
+
+-0.943465 -0.330355 -0.0271854
+0.235374 -0.725434 0.646795
+-0.233393 0.60383 0.762179
+-0.0889693 -0.219127 0.482162
+
+-0.951996 -0.304545 -0.0309082
+0.212536 -0.730273 0.649254
+-0.220298 0.611518 0.759944
+-0.0889898 -0.218143 0.482168
+
+-0.959806 -0.278517 -0.0346412
+0.189592 -0.734412 0.651685
+-0.206946 0.618924 0.757698
+-0.0890103 -0.21716 0.48215
+
+-0.966889 -0.252293 -0.0383844
+0.166563 -0.737851 0.654089
+-0.193344 0.626038 0.755443
+-0.0890307 -0.216176 0.482108
+
+-0.97324 -0.225894 -0.0421376
+0.143471 -0.740587 0.656466
+-0.179498 0.632853 0.753178
+-0.0890512 -0.215192 0.482042
+
+-0.978855 -0.199339 -0.0459006
+0.120338 -0.742619 0.658814
+-0.165414 0.63936 0.750904
+-0.0890717 -0.214209 0.481951
+
+-0.98373 -0.17265 -0.0496733
+0.0971828 -0.743946 0.661136
+-0.1511 0.645552 0.74862
+-0.0890921 -0.213225 0.481837
+
+-0.987862 -0.145848 -0.0534555
+0.0740284 -0.744568 0.663429
+-0.136561 0.651419 0.746327
+-0.0891126 -0.212241 0.481698
+
+-0.991248 -0.118953 -0.0572471
+0.0508955 -0.744486 0.665695
+-0.121806 0.656955 0.744025
+-0.0891331 -0.211258 0.481535
+
+-0.993887 -0.0919876 -0.061048
+0.0278054 -0.743702 0.667933
+-0.106843 0.662152 0.741713
+-0.0891535 -0.210274 0.481347
+
+-0.995777 -0.0649717 -0.0648579
+0.00477916 -0.742217 0.670143
+-0.0916789 0.667003 0.739393
+-0.089174 -0.20929 0.481136
+
+-0.996918 -0.0379266 -0.0686768
+-0.0181621 -0.740033 0.672325
+-0.0763221 0.6715 0.737064
+-0.0891944 -0.208307 0.4809
+
+-0.997309 -0.0108737 -0.0725045
+-0.0409975 -0.737155 0.674479
+-0.0607811 0.675636 0.734725
+-0.0892149 -0.207323 0.48064
+
+-0.996951 0.0161661 -0.0763407
+-0.063706 -0.733585 0.676605
+-0.0450644 0.679405 0.732378
+-0.0892354 -0.206339 0.480356
+
+-0.995845 0.0431717 -0.0801855
+-0.086267 -0.729329 0.678703
+-0.0291809 0.6828 0.730023
+-0.0892558 -0.205356 0.480048
+
+-0.993992 0.070122 -0.0840386
+-0.10866 -0.724391 0.680772
+-0.0131397 0.685814 0.727658
+-0.0892763 -0.204372 0.479716
+
+-0.991396 0.0969961 -0.0879
+-0.130864 -0.718777 0.682814
+0.00304984 0.688442 0.725285
+-0.0892968 -0.203388 0.479359
+
+-0.988058 0.123773 -0.0917693
+-0.152859 -0.712493 0.684827
+0.0193782 0.690676 0.722904
+-0.0893172 -0.202405 0.478979
+
+-0.983983 0.150432 -0.0956465
+-0.174625 -0.705546 0.686812
+0.0358356 0.692513 0.720515
+-0.0893377 -0.201421 0.478574
+
+-0.979174 0.176953 -0.0995315
+-0.196142 -0.697945 0.688768
+0.0524121 0.693946 0.718117
+-0.0893582 -0.200437 0.478145
+
+-0.973636 0.203315 -0.103424
+-0.217391 -0.689696 0.690696
+0.0690975 0.69497 0.715711
+-0.0893786 -0.199454 0.477691
+
+-0.967374 0.229497 -0.107324
+-0.238352 -0.680808 0.692595
+0.0858815 0.69558 0.713297
+-0.0893991 -0.19847 0.477214
+
+-0.960395 0.25548 -0.111231
+-0.259006 -0.671292 0.694466
+0.102754 0.695771 0.710876
+-0.0894196 -0.197486 0.476712
+
+-0.952703 0.281243 -0.115146
+-0.279334 -0.661156 0.696309
+0.119703 0.69554 0.708446
+-0.08944 -0.196503 0.476186
+
+-0.944308 0.306767 -0.119067
+-0.299318 -0.650411 0.698122
+0.136718 0.694881 0.706009
+-0.0894605 -0.195519 0.475636
+
+-0.935215 0.332032 -0.122995
+-0.318939 -0.639068 0.699907
+0.153789 0.693792 0.703564
+-0.089481 -0.194535 0.475062
+
+-0.925433 0.357019 -0.12693
+-0.33818 -0.627139 0.701663
+0.170904 0.692268 0.701111
+-0.0895014 -0.193552 0.474464
+
+-0.915328 0.380831 -0.130928
+-0.356429 -0.614801 0.703547
+0.187437 0.690643 0.698484
+-0.0894758 -0.192644 0.47388
+
+-0.905429 0.402432 -0.13508
+-0.373001 -0.602324 0.705745
+0.202652 0.689387 0.69547
+-0.0893501 -0.191889 0.473339
+
+-0.896235 0.42109 -0.139451
+-0.387434 -0.590018 0.70836
+0.216004 0.688885 0.691939
+-0.0890729 -0.191355 0.472888
+
+-0.888262 0.436152 -0.144089
+-0.39933 -0.578227 0.711469
+0.226993 0.68951 0.687786
+-0.0885977 -0.191111 0.472574
+
+-0.881301 0.448485 -0.148898
+-0.409258 -0.566843 0.71498
+0.236256 0.69105 0.683105
+-0.0879014 -0.19121 0.472471
+
+-0.875688 0.457699 -0.153887
+-0.417026 -0.556177 0.718858
+0.243432 0.69367 0.67791
+-0.0869727 -0.191685 0.472611
+
+-0.87176 0.463377 -0.159113
+-0.422422 -0.546377 0.723209
+0.248182 0.697677 0.67205
+-0.0858474 -0.192455 0.47288
+
+-0.869036 0.466606 -0.164483
+-0.426197 -0.5372 0.727854
+0.251261 0.702634 0.665713
+-0.0845783 -0.193444 0.47325
+
+-0.867378 0.467717 -0.169987
+-0.428621 -0.528567 0.732735
+0.252863 0.708419 0.658941
+-0.0831815 -0.19461 0.473699
+
+-0.865715 0.468769 -0.175478
+-0.431001 -0.519877 0.737541
+0.254509 0.714132 0.652105
+-0.0817848 -0.195776 0.474124
+
+-0.864049 0.46976 -0.180955
+-0.433339 -0.511129 0.74227
+0.256197 0.719773 0.645206
+-0.080388 -0.196942 0.474525
+
+-0.862379 0.470692 -0.186418
+-0.435632 -0.502325 0.746923
+0.257928 0.725341 0.638243
+-0.0789912 -0.198108 0.474902
+
+-0.860706 0.471564 -0.191866
+-0.437882 -0.493466 0.751499
+0.2597 0.730835 0.631218
+-0.0775945 -0.199274 0.475255
+
+-0.859031 0.472376 -0.197299
+-0.440087 -0.484552 0.755998
+0.261514 0.736254 0.624132
+-0.0761977 -0.20044 0.475583
+
+-0.857354 0.473129 -0.202715
+-0.442246 -0.475585 0.760419
+0.263368 0.741598 0.616984
+-0.0748009 -0.201606 0.475887
+
+-0.855675 0.473823 -0.208115
+-0.44436 -0.466566 0.764762
+0.265262 0.746866 0.609777
+-0.0734042 -0.202772 0.476167
+
+-0.853996 0.474457 -0.213498
+-0.446428 -0.457495 0.769026
+0.267195 0.752056 0.60251
+-0.0720074 -0.203938 0.476423
+
+-0.852316 0.475033 -0.218863
+-0.448449 -0.448374 0.773211
+0.269168 0.757169 0.595184
+-0.0706106 -0.205104 0.476655
+
+-0.850636 0.47555 -0.224211
+-0.450422 -0.439203 0.777316
+0.271179 0.762202 0.587801
+-0.0692139 -0.20627 0.476862
+
+-0.848957 0.476009 -0.229539
+-0.452349 -0.429984 0.781341
+0.273227 0.767157 0.58036
+-0.0678171 -0.207435 0.477045
+
+-0.847278 0.476409 -0.234848
+-0.454227 -0.420717 0.785286
+0.275313 0.772031 0.572862
+-0.0664203 -0.208601 0.477204
+
+-0.845602 0.476751 -0.240138
+-0.456057 -0.411404 0.789151
+0.277435 0.776824 0.565309
+-0.0650236 -0.209767 0.477339
+
+-0.843927 0.477035 -0.245408
+-0.457838 -0.402045 0.792934
+0.279593 0.781535 0.557701
+-0.0636268 -0.210933 0.47745
+
+-0.842254 0.477262 -0.250656
+-0.45957 -0.392641 0.796636
+0.281786 0.786164 0.550039
+-0.06223 -0.212099 0.477536
+
+-0.840585 0.477431 -0.255884
+-0.461252 -0.383194 0.800256
+0.284014 0.790709 0.542323
+-0.0608333 -0.213265 0.477599
+
+-0.838919 0.477543 -0.261089
+-0.462884 -0.373705 0.803793
+0.286276 0.795171 0.534555
+-0.0594365 -0.214431 0.477637
+
+-0.837257 0.477599 -0.266272
+-0.464465 -0.364174 0.807248
+0.288571 0.799548 0.526735
+-0.0580397 -0.215597 0.477651
+
+-0.835599 0.477597 -0.271433
+-0.465996 -0.354602 0.81062
+0.290899 0.80384 0.518863
+-0.056643 -0.216763 0.477641
+
+-0.833946 0.477539 -0.276569
+-0.467475 -0.344991 0.813909
+0.293259 0.808046 0.510942
+-0.0552462 -0.217929 0.477606
+
+-0.832298 0.477425 -0.281683
+-0.468903 -0.335342 0.817114
+0.295651 0.812165 0.50297
+-0.0538494 -0.219095 0.477548
+
+-0.830656 0.477255 -0.286771
+-0.470279 -0.325655 0.820236
+0.298073 0.816196 0.49495
+-0.0524527 -0.220261 0.477465
+
+-0.829021 0.477029 -0.291835
+-0.471603 -0.315932 0.823273
+0.300525 0.82014 0.486882
+-0.0510559 -0.221427 0.477358
+
+-0.827392 0.476748 -0.296873
+-0.472874 -0.306173 0.826225
+0.303007 0.823996 0.478767
+-0.0496591 -0.222593 0.477227
+
+-0.82577 0.476413 -0.301886
+-0.474092 -0.296381 0.829093
+0.305517 0.827762 0.470606
+-0.0482624 -0.223759 0.477071
+
+-0.824156 0.476022 -0.306872
+-0.475257 -0.286555 0.831876
+0.308056 0.831438 0.462399
+-0.0468656 -0.224925 0.476892
+
+-0.82255 0.475577 -0.311831
+-0.476368 -0.276698 0.834573
+0.310621 0.835024 0.454147
+-0.0454688 -0.226091 0.476688
+
+-0.820952 0.475078 -0.316762
+-0.477426 -0.266809 0.837184
+0.313213 0.838519 0.445852
+-0.0440721 -0.227257 0.47646
+
+-0.819363 0.474526 -0.321666
+-0.478429 -0.25689 0.83971
+0.315831 0.841922 0.437514
+-0.0426753 -0.228423 0.476208
+
+-0.817784 0.47392 -0.326542
+-0.479378 -0.246943 0.842149
+0.318474 0.845233 0.429133
+-0.0412786 -0.229589 0.475932
+
+-0.816214 0.473261 -0.331388
+-0.480273 -0.236968 0.844502
+0.321142 0.848452 0.420711
+-0.0398818 -0.230755 0.475631
+
+-0.814655 0.47255 -0.336205
+-0.481112 -0.226966 0.846769
+0.323833 0.851577 0.412249
+-0.038485 -0.231921 0.475307
+
+-0.813107 0.471786 -0.340992
+-0.481897 -0.216939 0.848948
+0.326547 0.854609 0.403746
+-0.0370883 -0.233087 0.474958
+
+-0.811569 0.47097 -0.345749
+-0.482626 -0.206887 0.851041
+0.329283 0.857546 0.395206
+-0.0356915 -0.234253 0.474585
+
+-0.810043 0.470103 -0.350476
+-0.483299 -0.196812 0.853046
+0.332041 0.860389 0.386627
+-0.0342947 -0.235419 0.474188
+
+-0.80853 0.469184 -0.35517
+-0.483917 -0.186715 0.854963
+0.33482 0.863136 0.378011
+-0.032898 -0.236585 0.473766
+
+-0.807028 0.468215 -0.359834
+-0.484479 -0.176596 0.856793
+0.337618 0.865788 0.369358
+-0.0315012 -0.237751 0.473321
+
+-0.80554 0.467195 -0.364464
+-0.484984 -0.166458 0.858535
+0.340435 0.868343 0.360671
+-0.0301044 -0.238917 0.472851
+
+-0.802535 0.470615 -0.366686
+-0.484686 -0.155921 0.860679
+0.347874 0.868453 0.353232
+-0.0288835 -0.23981 0.472556
+
+-0.797867 0.478862 -0.366196
+-0.483301 -0.145036 0.863357
+0.360317 0.865827 0.347154
+-0.0278499 -0.240389 0.47246
+
+-0.791088 0.492579 -0.362693
+-0.48062 -0.133738 0.866671
+0.378398 0.85993 0.342542
+-0.0270188 -0.240619 0.472593
+
+-0.782152 0.510853 -0.356745
+-0.476782 -0.122088 0.870502
+0.401144 0.850954 0.339057
+-0.0263621 -0.240575 0.472901
+
+-0.772009 0.530637 -0.349895
+-0.472292 -0.110498 0.874489
+0.425374 0.840366 0.335921
+-0.0257482 -0.240421 0.47327
+
+-0.761304 0.550221 -0.343036
+-0.467491 -0.0991868 0.878416
+0.449298 0.829108 0.332734
+-0.0251343 -0.240267 0.473615
+
+-0.750042 0.569586 -0.336167
+-0.46239 -0.0881645 0.882283
+0.472898 0.81719 0.329498
+-0.0245204 -0.240113 0.473935
+
+-0.738228 0.588717 -0.32929
+-0.456999 -0.0774393 0.88609
+0.496156 0.804621 0.326211
+-0.0239064 -0.23996 0.474232
+
+-0.725866 0.607597 -0.322404
+-0.451333 -0.0670191 0.889836
+0.519054 0.791413 0.322875
+-0.0232925 -0.239806 0.474504
+
+-0.712962 0.626209 -0.315511
+-0.445401 -0.0569115 0.893521
+0.541575 0.777575 0.31949
+-0.0226786 -0.239652 0.474752
+
+-0.699522 0.644538 -0.308611
+-0.439216 -0.0471237 0.897145
+0.563701 0.763119 0.316056
+-0.0220647 -0.239498 0.474976
+
+-0.685552 0.662566 -0.301704
+-0.432792 -0.0376624 0.900707
+0.585415 0.748056 0.312573
+-0.0214507 -0.239344 0.475176
+
+-0.671059 0.680278 -0.294792
+-0.426139 -0.028534 0.904207
+0.606701 0.732399 0.309041
+-0.0208368 -0.23919 0.475352
+
+-0.656051 0.697657 -0.287875
+-0.419272 -0.0197443 0.907646
+0.627542 0.71616 0.305461
+-0.0202229 -0.239036 0.475503
+
+-0.640535 0.714689 -0.280954
+-0.412203 -0.0112988 0.911022
+0.647923 0.699351 0.301834
+-0.0196089 -0.238882 0.47563
+
+-0.624521 0.731357 -0.274028
+-0.404944 -0.00320249 0.914336
+0.667828 0.681988 0.298159
+-0.018995 -0.238728 0.475733
+
+-0.608016 0.747645 -0.2671
+-0.39751 0.00454014 0.917586
+0.687242 0.664083 0.294436
+-0.0183811 -0.238575 0.475812
+
+-0.591032 0.76354 -0.260169
+-0.389914 0.011925 0.920774
+0.706151 0.64565 0.290667
+-0.0177672 -0.238421 0.475867
+
+-0.573576 0.779026 -0.253236
+-0.382169 0.0189484 0.923898
+0.72454 0.626705 0.286851
+-0.0171532 -0.238267 0.475897
+
+-0.55566 0.794089 -0.246301
+-0.374288 0.0256073 0.926959
+0.742395 0.607262 0.282989
+-0.0165393 -0.238113 0.475904
+
+-0.537295 0.808714 -0.239366
+-0.366285 0.0318988 0.929956
+0.759704 0.587337 0.27908
+-0.0159254 -0.237959 0.475886
+
+-0.518491 0.822887 -0.232431
+-0.358173 0.0378209 0.932889
+0.776453 0.566945 0.275126
+-0.0153115 -0.237805 0.475844
+
+-0.499261 0.836594 -0.225496
+-0.349967 0.0433715 0.935757
+0.792629 0.546104 0.271127
+-0.0146975 -0.237651 0.475777
+
+-0.479617 0.849823 -0.218562
+-0.34168 0.0485496 0.938561
+0.808222 0.524828 0.267082
+-0.0140836 -0.237497 0.475687
+
+-0.45957 0.862559 -0.21163
+-0.333326 0.0533541 0.941301
+0.823219 0.503135 0.262993
+-0.0134697 -0.237343 0.475572
+
+-0.439135 0.874791 -0.2047
+-0.324917 0.0577848 0.943975
+0.837609 0.481043 0.258859
+-0.0128557 -0.23719 0.475434
+
+-0.418324 0.886505 -0.197773
+-0.316469 0.0618416 0.946585
+0.851383 0.458568 0.254682
+-0.0122418 -0.237036 0.475271
+
+-0.397151 0.89769 -0.19085
+-0.307994 0.065525 0.949129
+0.864529 0.435728 0.25046
+-0.0116279 -0.236882 0.475083
+
+-0.37563 0.908334 -0.183931
+-0.299507 0.0688362 0.951608
+0.877039 0.412541 0.246195
+-0.011014 -0.236728 0.474872
+
+-0.353776 0.918427 -0.177016
+-0.29102 0.0717765 0.954021
+0.888904 0.389025 0.241887
+-0.0104 -0.236574 0.474636
+
+-0.331604 0.927956 -0.170107
+-0.282547 0.0743478 0.956368
+0.900114 0.365199 0.237537
+-0.00978611 -0.23642 0.474377
+
+-0.309129 0.936912 -0.163204
+-0.274101 0.0765524 0.958649
+0.910663 0.341081 0.233144
+-0.00917219 -0.236266 0.474093
+
+-0.286366 0.945284 -0.156307
+-0.265696 0.0783932 0.960864
+0.920543 0.316689 0.228709
+-0.00855826 -0.236112 0.473785
+
+-0.263332 0.953064 -0.149418
+-0.257345 0.0798733 0.963013
+0.929747 0.292044 0.224233
+-0.00794433 -0.235958 0.473452
+
+-0.240042 0.960241 -0.142536
+-0.24906 0.0809965 0.965095
+0.938269 0.267163 0.219715
+-0.00733041 -0.235805 0.473096
+
+-0.216513 0.966808 -0.135663
+-0.240855 0.0817668 0.967111
+0.946103 0.242067 0.215157
+-0.00671648 -0.235651 0.472715
+
+-0.192762 0.972756 -0.128798
+-0.232741 0.0821887 0.96906
+0.953244 0.216775 0.210558
+-0.00610255 -0.235497 0.47231
+
+-0.168806 0.978077 -0.121944
+-0.224733 0.0822673 0.970941
+0.959687 0.191305 0.205919
+-0.00548862 -0.235343 0.471881
+
+-0.144662 0.982764 -0.115099
+-0.216841 0.0820079 0.972756
+0.965429 0.165679 0.20124
+-0.0048747 -0.235189 0.471428
+
+-0.120348 0.986811 -0.108265
+-0.209077 0.0814162 0.974504
+0.970465 0.139916 0.196522
+-0.00426077 -0.235035 0.470951
+
+-0.0958818 0.99021 -0.101442
+-0.201455 0.0804984 0.976184
+0.974794 0.114034 0.191764
+-0.00364684 -0.234881 0.470449
+
+-0.0761349 0.992567 -0.0949439
+-0.19559 0.0785036 0.977539
+0.977726 0.0929949 0.18816
+-0.00295799 -0.234556 0.469966
+
+-0.0668634 0.9938 -0.0888262
+-0.193424 0.0744261 0.978288
+0.978834 0.0825929 0.187249
+-0.0021043 -0.233847 0.469536
+
+-0.0693505 0.994119 -0.083177
+-0.19523 0.0682407 0.978381
+0.978302 0.0840898 0.189349
+-0.00106004 -0.23271 0.469155
+
+-0.0826554 0.993524 -0.0779646
+-0.20048 0.0600563 0.977855
+0.976205 0.0964554 0.194218
+0.000154671 -0.231192 0.468852
+
+-0.0959815 0.99272 -0.0727579
+-0.20555 0.0517525 0.977277
+0.973929 0.108756 0.199086
+0.00136938 -0.229674 0.468526
+
+-0.109325 0.991708 -0.0675571
+-0.210436 0.0433328 0.976647
+0.971476 0.120989 0.203954
+0.0025841 -0.228156 0.468175
+
+-0.122683 0.990485 -0.0623624
+-0.215137 0.0348009 0.975964
+0.968847 0.133151 0.208821
+0.00379881 -0.226638 0.4678
+
+-0.136051 0.989051 -0.0571742
+-0.219651 0.0261605 0.975228
+0.966045 0.145239 0.213687
+0.00501352 -0.22512 0.467401
+
+-0.149427 0.987405 -0.0519927
+-0.223975 0.0174153 0.974439
+0.963072 0.157252 0.218551
+0.00622823 -0.223602 0.466978
+
+-0.162805 0.985547 -0.0468182
+-0.228107 0.00856909 0.973598
+0.959928 0.169186 0.223415
+0.00744294 -0.222084 0.466531
+
+-0.176183 0.983476 -0.0416511
+-0.232045 -0.000374304 0.972705
+0.956616 0.181039 0.228276
+0.00865766 -0.220566 0.466059
+
+-0.189557 0.981191 -0.0364915
+-0.235786 -0.00941103 0.971759
+0.953138 0.192808 0.233136
+0.00987237 -0.219048 0.465563
+
+-0.202923 0.978693 -0.0313399
+-0.23933 -0.0185372 0.970761
+0.949496 0.204491 0.237993
+0.0110871 -0.21753 0.465043
+
+-0.216278 0.97598 -0.0261964
+-0.242675 -0.0277489 0.969711
+0.945692 0.216085 0.242847
+0.0123018 -0.216012 0.464499
+
+-0.229618 0.973053 -0.0210613
+-0.245817 -0.0370421 0.968608
+0.941727 0.227587 0.247699
+0.0135165 -0.214494 0.463931
+
+-0.242939 0.969911 -0.015935
+-0.248757 -0.0464128 0.967453
+0.937604 0.238996 0.252547
+0.0147312 -0.212976 0.463338
+
+-0.256237 0.966553 -0.0108178
+-0.251491 -0.055857 0.966246
+0.933324 0.250309 0.257392
+0.0159459 -0.211458 0.462722
+
+-0.269509 0.962981 -0.00570979
+-0.254019 -0.0653707 0.964987
+0.928891 0.261523 0.262234
+0.0171606 -0.20994 0.462081
+
+-0.282751 0.959193 -0.000611417
+-0.25634 -0.0749496 0.963677
+0.924306 0.272637 0.267071
+0.0183754 -0.208422 0.461416
+
+-0.295959 0.95519 0.00447709
+-0.258451 -0.0845897 0.962314
+0.919571 0.283648 0.271905
+0.0195901 -0.206904 0.460726
+
+-0.30913 0.950972 0.00955545
+-0.260351 -0.0942868 0.960899
+0.914689 0.294555 0.276733
+0.0208048 -0.205386 0.460013
+
+-0.322258 0.946539 0.0146234
+-0.26204 -0.104037 0.959433
+0.909662 0.305353 0.281558
+0.0220195 -0.203868 0.459275
+
+-0.335342 0.941891 0.0196806
+-0.263516 -0.113835 0.957915
+0.904492 0.316043 0.286377
+0.0232342 -0.20235 0.458513
+
+-0.348377 0.937028 0.0247268
+-0.264778 -0.123678 0.956345
+0.899181 0.326622 0.291191
+0.0244489 -0.200832 0.457727
+
+-0.361359 0.931952 0.0297618
+-0.265824 -0.133561 0.954724
+0.893732 0.337087 0.295999
+0.0256636 -0.199314 0.456917
+
+-0.374284 0.926661 0.0347852
+-0.266656 -0.14348 0.953052
+0.888148 0.347437 0.300802
+0.0268783 -0.197796 0.456083
+
+-0.387149 0.921158 0.0397967
+-0.26727 -0.15343 0.951329
+0.88243 0.35767 0.305598
+0.028093 -0.196278 0.455224
+
+-0.39995 0.915442 0.0447962
+-0.267667 -0.163407 0.949554
+0.876581 0.367784 0.310388
+0.0293078 -0.19476 0.454341
+
+-0.412683 0.909513 0.0497833
+-0.267846 -0.173408 0.947728
+0.870604 0.377777 0.315172
+0.0305225 -0.193242 0.453435
+
+-0.425344 0.903374 0.0547578
+-0.267807 -0.183426 0.945851
+0.864501 0.387648 0.319949
+0.0317372 -0.191724 0.452503
+
+-0.43793 0.897024 0.0597193
+-0.267548 -0.193459 0.943923
+0.858275 0.397394 0.324719
+0.0329519 -0.190206 0.451548
+
+-0.450436 0.890464 0.0646677
+-0.26707 -0.203502 0.941945
+0.851928 0.407015 0.329481
+0.0341666 -0.188688 0.450569
+
+-0.462859 0.883695 0.0696025
+-0.266372 -0.21355 0.939916
+0.845463 0.416509 0.334236
+0.0353813 -0.18717 0.449565
+
+-0.475196 0.876719 0.0745236
+-0.265455 -0.223599 0.937836
+0.838882 0.425873 0.338982
+0.036596 -0.185652 0.448537
+
+-0.487441 0.869535 0.0794308
+-0.264317 -0.233645 0.935706
+0.832188 0.435107 0.343721
+0.0378107 -0.184134 0.447485
+
+-0.499593 0.862146 0.0843236
+-0.262959 -0.243683 0.933526
+0.825385 0.444209 0.348451
+0.0390255 -0.182616 0.446409
+
+-0.511646 0.854553 0.0892019
+-0.261381 -0.253709 0.931296
+0.818473 0.453179 0.353173
+0.0402402 -0.181098 0.445308
+
+-0.523598 0.846757 0.0940653
+-0.259583 -0.263718 0.929015
+0.811457 0.462013 0.357886
+0.0414549 -0.17958 0.444184
+
+-0.535444 0.838758 0.0989137
+-0.257565 -0.273706 0.926685
+0.804338 0.470712 0.362589
+0.0426696 -0.178062 0.443035
+
+-0.547182 0.830559 0.103747
+-0.255327 -0.283669 0.924305
+0.79712 0.479273 0.367283
+0.0438843 -0.176544 0.441862
+
+-0.558806 0.822161 0.108564
+-0.252871 -0.293602 0.921875
+0.789805 0.487697 0.371967
+0.045099 -0.175026 0.440665
+
+-0.570314 0.813566 0.113366
+-0.250196 -0.303501 0.919396
+0.782396 0.495981 0.376642
+0.0463137 -0.173508 0.439444
+
+-0.581702 0.804775 0.118151
+-0.247302 -0.313361 0.916868
+0.774896 0.504125 0.381306
+0.0475284 -0.17199 0.438198
+
+-0.592967 0.79579 0.12292
+-0.244192 -0.323178 0.91429
+0.767308 0.512127 0.385959
+0.0487432 -0.170472 0.436928
+
+-0.604104 0.786612 0.127672
+-0.240864 -0.332948 0.911663
+0.759633 0.519988 0.390602
+0.0499579 -0.168954 0.435634
+
+-0.615111 0.777243 0.132408
+-0.237321 -0.342667 0.908987
+0.751876 0.527705 0.395234
+0.0511726 -0.167436 0.434316
+
+-0.625983 0.767686 0.137126
+-0.233563 -0.352329 0.906263
+0.744039 0.535278 0.399855
+0.0523873 -0.165918 0.432974
+
+-0.636717 0.757942 0.141827
+-0.22959 -0.361931 0.90349
+0.736125 0.542706 0.404464
+0.053602 -0.1644 0.431608
+
+-0.647311 0.748013 0.14651
+-0.225405 -0.371469 0.900669
+0.728136 0.549988 0.409061
+0.0548167 -0.162882 0.430217
+
+-0.657759 0.737902 0.151175
+-0.221007 -0.380937 0.897799
+0.720075 0.557125 0.413647
+0.0560314 -0.161364 0.428802
+
+-0.66806 0.727609 0.155822
+-0.216399 -0.390332 0.894881
+0.711946 0.564114 0.41822
+0.0572461 -0.159846 0.427363
+
+-0.674445 0.720622 0.160708
+-0.212543 -0.397951 0.892447
+0.707071 0.567749 0.421559
+0.0582775 -0.15859 0.42599
+
+-0.675602 0.718333 0.166011
+-0.20982 -0.403193 0.890736
+0.70678 0.566951 0.423118
+0.0590674 -0.15767 0.42466
+
+-0.67186 0.720507 0.171678
+-0.208226 -0.406173 0.889756
+0.710806 0.562044 0.42292
+0.0596244 -0.157091 0.423378
+
+-0.662116 0.728009 0.17778
+-0.208124 -0.406531 0.889616
+0.719921 0.552029 0.420687
+0.059886 -0.156919 0.422184
+
+-0.64689 0.739996 0.184225
+-0.209377 -0.404647 0.890181
+0.733276 0.537277 0.4167
+0.0599034 -0.157081 0.421037
+
+-0.626671 0.755528 0.190946
+-0.211701 -0.400865 0.891341
+0.749977 0.518154 0.411157
+0.0597087 -0.157542 0.419942
+
+-0.60602 0.770508 0.197632
+-0.213958 -0.397191 0.892447
+0.766135 0.498556 0.405561
+0.059514 -0.158003 0.418822
+
+-0.584951 0.784922 0.204281
+-0.216153 -0.393624 0.893498
+0.781736 0.478496 0.399914
+0.0593193 -0.158464 0.417679
+
+-0.56348 0.798758 0.210895
+-0.218294 -0.390166 0.894493
+0.796767 0.457992 0.394214
+0.0591246 -0.158925 0.416511
+
+-0.541624 0.812004 0.217471
+-0.220386 -0.386818 0.895434
+0.811217 0.437061 0.388464
+0.0589298 -0.159386 0.415319
+
+-0.519398 0.824649 0.22401
+-0.222438 -0.383579 0.896319
+0.825074 0.415718 0.382663
+0.0587351 -0.159847 0.414103
+
+-0.49682 0.836681 0.23051
+-0.224455 -0.38045 0.89715
+0.838326 0.393983 0.376813
+0.0585404 -0.160308 0.412862
+
+-0.473906 0.84809 0.236971
+-0.226444 -0.377431 0.897925
+0.850962 0.371872 0.370912
+0.0583457 -0.160769 0.411598
+
+-0.450675 0.858866 0.243394
+-0.228412 -0.374521 0.898644
+0.862972 0.349403 0.364963
+0.058151 -0.16123 0.410309
+
+-0.427143 0.869 0.249776
+-0.230365 -0.37172 0.899309
+0.874346 0.326594 0.358965
+0.0579562 -0.161691 0.408996
+
+-0.403329 0.878481 0.256117
+-0.232311 -0.369026 0.899918
+0.885075 0.303464 0.352919
+0.0577615 -0.162152 0.407659
+
+-0.379251 0.887302 0.262418
+-0.234254 -0.366437 0.900471
+0.89515 0.280033 0.346826
+0.0575668 -0.162612 0.406298
+
+-0.354928 0.895455 0.268676
+-0.236203 -0.363954 0.900969
+0.904563 0.256317 0.340686
+0.0573721 -0.163073 0.404912
+
+-0.330378 0.902931 0.274893
+-0.238162 -0.361573 0.901412
+0.913307 0.232338 0.3345
+0.0571774 -0.163534 0.403503
+
+-0.305621 0.909724 0.281067
+-0.240139 -0.359293 0.901799
+0.921373 0.208114 0.328268
+0.0569826 -0.163995 0.402069
+
+-0.280676 0.915827 0.287198
+-0.242139 -0.357112 0.902131
+0.928757 0.183664 0.32199
+0.0567879 -0.164456 0.400611
+
+-0.255562 0.921234 0.293284
+-0.244169 -0.355026 0.902407
+0.935452 0.15901 0.315668
+0.0565932 -0.164917 0.399129
+
+-0.230299 0.925941 0.299327
+-0.246234 -0.353033 0.902627
+0.941452 0.134169 0.309301
+0.0563985 -0.165378 0.397622
+
+-0.205633 0.929806 0.305249
+-0.247967 -0.35124 0.902853
+0.946693 0.109964 0.302787
+0.0562952 -0.165941 0.396141
+
+-0.182052 0.932811 0.311001
+-0.249142 -0.349725 0.903117
+0.951202 0.0869306 0.296071
+0.0563439 -0.166673 0.394716
+
+-0.159582 0.935046 0.316579
+-0.249766 -0.348498 0.903419
+0.955066 0.0650989 0.289157
+0.056547 -0.167574 0.393345
+
+-0.138156 0.936608 0.32199
+-0.249873 -0.347553 0.903753
+0.958372 0.0444026 0.28205
+0.056904 -0.168646 0.392027
+
+-0.11756 0.937552 0.327378
+-0.249673 -0.346979 0.904029
+0.961167 0.0245403 0.274872
+0.0574211 -0.169871 0.390788
+
+-0.0978071 0.937932 0.332742
+-0.249174 -0.346775 0.904245
+0.963507 0.00553099 0.267625
+0.0581005 -0.17125 0.389623
+
+-0.07862 0.937812 0.338124
+-0.248545 -0.346903 0.904369
+0.965424 -0.0129375 0.260362
+0.0588832 -0.172713 0.388498
+
+-0.0594208 0.937285 0.343462
+-0.24799 -0.347144 0.904429
+0.966939 -0.0314331 0.253064
+0.0596658 -0.174177 0.387349
+
+-0.0402184 0.936351 0.348755
+-0.247512 -0.347495 0.904425
+0.96805 -0.0499465 0.245734
+0.0604485 -0.175641 0.386175
+
+-0.0210218 0.935008 0.354002
+-0.247116 -0.347953 0.904357
+0.968758 -0.0684684 0.238371
+0.0612312 -0.177104 0.384978
+
+-0.00191559 0.934076 0.357068
+-0.249015 -0.346266 0.904484
+0.968498 -0.0871827 0.233262
+0.0621564 -0.178178 0.383841
+
+0.0174172 0.933731 0.357551
+-0.253712 -0.341773 0.904887
+0.967123 -0.106476 0.230946
+0.0632541 -0.178777 0.382776
+
+0.0356611 0.934142 0.355115
+-0.261242 -0.334271 0.905547
+0.964614 -0.125064 0.232117
+0.06459 -0.178826 0.381788
+
+0.0525532 0.935517 0.349352
+-0.271895 -0.323214 0.906425
+0.960891 -0.142622 0.237376
+0.0662096 -0.178241 0.38089
+
+0.0690899 0.936828 0.342899
+-0.282877 -0.311216 0.907263
+0.956665 -0.159681 0.243505
+0.0678971 -0.177528 0.379982
+
+0.0857292 0.937797 0.336434
+-0.293515 -0.298919 0.908018
+0.952103 -0.176592 0.249631
+0.0695846 -0.176816 0.37905
+
+0.102463 0.938419 0.329957
+-0.303802 -0.286333 0.90869
+0.947209 -0.193349 0.255755
+0.0712722 -0.176103 0.378093
+
+0.119284 0.93869 0.32347
+-0.31373 -0.273467 0.909279
+0.94199 -0.209945 0.261875
+0.0729597 -0.17539 0.377113
+
+0.136184 0.938607 0.316971
+-0.323292 -0.260331 0.909786
+0.936449 -0.226373 0.267991
+0.0746473 -0.174677 0.376108
+
+0.153155 0.938166 0.310463
+-0.33248 -0.246934 0.910209
+0.930591 -0.242626 0.274103
+0.0763348 -0.173965 0.37508
+
+0.170189 0.937365 0.303946
+-0.341288 -0.233286 0.910549
+0.924423 -0.258698 0.280209
+0.0780223 -0.173252 0.374027
+
+0.187277 0.936199 0.297419
+-0.349709 -0.219397 0.910807
+0.917949 -0.274583 0.28631
+0.0797099 -0.172539 0.372949
+
+0.20441 0.934667 0.290885
+-0.357737 -0.205276 0.910981
+0.911175 -0.290274 0.292404
+0.0813974 -0.171826 0.371848
+
+0.221581 0.932765 0.284342
+-0.365365 -0.190936 0.911072
+0.904107 -0.305765 0.298492
+0.0830849 -0.171113 0.370723
+
+0.23878 0.930492 0.277793
+-0.372589 -0.176385 0.91108
+0.896751 -0.321051 0.304573
+0.0847725 -0.170401 0.369573
+
+0.256 0.927844 0.271238
+-0.379401 -0.161635 0.911004
+0.889111 -0.336125 0.310646
+0.08646 -0.169688 0.368399
+
+0.27323 0.92482 0.264676
+-0.385797 -0.146697 0.910846
+0.881196 -0.350982 0.316711
+0.0881476 -0.168975 0.367201
+
+0.290462 0.921418 0.25811
+-0.391772 -0.131581 0.910605
+0.87301 -0.365617 0.322767
+0.0898351 -0.168262 0.365979
+
+0.307688 0.917636 0.251538
+-0.397322 -0.116298 0.91028
+0.86456 -0.380024 0.328813
+0.0915226 -0.16755 0.364732
+
+0.324897 0.913474 0.244963
+-0.402441 -0.10086 0.909873
+0.855852 -0.394198 0.33485
+0.0932102 -0.166837 0.363462
+
+0.342082 0.90893 0.238384
+-0.407125 -0.0852785 0.909382
+0.846894 -0.408135 0.340876
+0.0948977 -0.166124 0.362167
+
+0.359232 0.904002 0.231803
+-0.411372 -0.0695643 0.908809
+0.837691 -0.42183 0.346891
+0.0965853 -0.165411 0.360848
+
+0.376339 0.898691 0.225219
+-0.415176 -0.0537291 0.908153
+0.82825 -0.435279 0.352895
+0.0982728 -0.164698 0.359504
+
+0.393393 0.892996 0.218633
+-0.418536 -0.0377845 0.907414
+0.818578 -0.448476 0.358887
+0.0999603 -0.163986 0.358137
+
+0.410385 0.886916 0.212046
+-0.421447 -0.0217424 0.906592
+0.808682 -0.461418 0.364866
+0.101648 -0.163273 0.356746
+
+0.427306 0.880452 0.205459
+-0.423908 -0.00561455 0.905688
+0.798569 -0.474101 0.370832
+0.103335 -0.16256 0.35533
+
+0.444145 0.873604 0.198872
+-0.425916 0.0105872 0.904701
+0.788245 -0.486521 0.376784
+0.105023 -0.161847 0.35389
+
+0.460895 0.866373 0.192285
+-0.427468 0.026851 0.903631
+0.777719 -0.498675 0.382723
+0.10671 -0.161134 0.352426
+
+0.477545 0.858759 0.1857
+-0.428564 0.0431646 0.90248
+0.766996 -0.510559 0.388646
+0.108398 -0.160422 0.350937
+
+0.494086 0.850762 0.179117
+-0.429202 0.0595162 0.901246
+0.756085 -0.52217 0.394555
+0.110086 -0.159709 0.349425
+
+0.510508 0.842385 0.172536
+-0.42938 0.0758935 0.89993
+0.744993 -0.533505 0.400447
+0.111773 -0.158996 0.347888
+
+0.526803 0.833629 0.165958
+-0.429098 0.0922845 0.898531
+0.733726 -0.544561 0.406324
+0.113461 -0.158283 0.346327
+
+0.54296 0.824495 0.159384
+-0.428355 0.108677 0.897052
+0.722293 -0.555336 0.412184
+0.115148 -0.157571 0.344742
+
+0.55897 0.814985 0.152814
+-0.427151 0.125059 0.89549
+0.7107 -0.565826 0.418026
+0.116836 -0.156858 0.343133
+
+0.574824 0.805102 0.146249
+-0.425487 0.141418 0.893847
+0.698955 -0.576031 0.423851
+0.118523 -0.156145 0.3415
+
+0.590512 0.794848 0.139689
+-0.423363 0.157742 0.892122
+0.687066 -0.585948 0.429657
+0.120211 -0.155432 0.339842
+
+0.603342 0.786164 0.133884
+-0.421468 0.171818 0.890418
+0.677011 -0.593654 0.435008
+0.121792 -0.154869 0.338226
+
+0.611863 0.780335 0.129231
+-0.420392 0.182434 0.888813
+0.669996 -0.598159 0.439671
+0.123136 -0.154555 0.336738
+
+0.612113 0.780527 0.126867
+-0.421619 0.186407 0.887406
+0.668996 -0.596683 0.443187
+0.124019 -0.154734 0.335488
+
+0.604145 0.78674 0.126686
+-0.425254 0.183853 0.886204
+0.67392 -0.589269 0.445638
+0.124487 -0.155386 0.334456
+
+0.587768 0.79873 0.128683
+-0.431203 0.174702 0.88518
+0.684539 -0.575768 0.447099
+0.124537 -0.156511 0.333638
+
+0.564054 0.815033 0.132531
+-0.438693 0.159807 0.884313
+0.699565 -0.556941 0.447689
+0.124266 -0.158032 0.332999
+
+0.535655 0.83318 0.137426
+-0.446587 0.141387 0.883498
+0.716683 -0.534623 0.447822
+0.123737 -0.159788 0.332482
+
+0.506647 0.850327 0.142313
+-0.453747 0.122631 0.882652
+0.733091 -0.511768 0.447964
+0.123208 -0.161544 0.331942
+
+0.477067 0.866453 0.147192
+-0.46016 0.103568 0.881775
+0.748772 -0.488397 0.448116
+0.122678 -0.1633 0.331377
+
+0.44695 0.88154 0.152061
+-0.465813 0.0842271 0.880866
+0.763711 -0.464535 0.448278
+0.122149 -0.165057 0.330788
+
+0.416333 0.895568 0.156922
+-0.470695 0.0646365 0.879925
+0.77789 -0.440205 0.44845
+0.12162 -0.166813 0.330175
+
+0.385255 0.90852 0.161773
+-0.474795 0.0448265 0.878954
+0.791295 -0.41543 0.448631
+0.12109 -0.168569 0.329538
+
+0.353751 0.92038 0.166615
+-0.478106 0.0248272 0.877951
+0.803912 -0.390236 0.448822
+0.120561 -0.170325 0.328876
+
+0.321863 0.931134 0.171448
+-0.480618 0.00466912 0.876918
+0.815727 -0.364648 0.449022
+0.120032 -0.172081 0.32819
+
+0.289628 0.940768 0.17627
+-0.482324 -0.0156169 0.875853
+0.826728 -0.338691 0.449232
+0.119502 -0.173837 0.327481
+
+0.257087 0.949271 0.181082
+-0.483221 -0.0359998 0.874758
+0.836902 -0.312391 0.449452
+0.118973 -0.175593 0.326747
+
+0.224279 0.956633 0.185884
+-0.483301 -0.0564482 0.873632
+0.846238 -0.285775 0.449682
+0.118443 -0.17735 0.325988
+
+0.191245 0.962844 0.190676
+-0.482564 -0.0769305 0.872476
+0.854727 -0.258869 0.449921
+0.117914 -0.179106 0.325206
+
+0.158025 0.967897 0.195456
+-0.481006 -0.0974151 0.871289
+0.862358 -0.231701 0.45017
+0.117385 -0.180862 0.324399
+
+0.124661 0.971787 0.200226
+-0.478626 -0.11787 0.870071
+0.869124 -0.204298 0.450429
+0.116855 -0.182618 0.323568
+
+0.0911946 0.974507 0.204985
+-0.475426 -0.138264 0.868823
+0.875016 -0.176687 0.450697
+0.116326 -0.184374 0.322713
+
+0.0576662 0.976057 0.209732
+-0.471406 -0.158564 0.867545
+0.880029 -0.148897 0.450975
+0.115797 -0.18613 0.321834
+
+0.0241175 0.976433 0.214468
+-0.466569 -0.17874 0.866236
+0.884156 -0.120956 0.451263
+0.115267 -0.187886 0.320931
+
+-0.00940982 0.975636 0.219192
+-0.460919 -0.198758 0.864898
+0.887392 -0.0928913 0.45156
+0.114738 -0.189643 0.320003
+
+-0.0428742 0.973668 0.223904
+-0.454462 -0.218588 0.863529
+0.889734 -0.0647328 0.451867
+0.114209 -0.191399 0.319052
+
+-0.0762342 0.97053 0.228604
+-0.447204 -0.238199 0.862131
+0.891177 -0.0365088 0.452184
+0.113679 -0.193155 0.318076
+
+-0.109448 0.966228 0.233292
+-0.439152 -0.257558 0.860703
+0.891721 -0.00824795 0.45251
+0.11315 -0.194911 0.317076
+
+-0.142476 0.960767 0.237967
+-0.430315 -0.276635 0.859245
+0.891364 0.0200207 0.452846
+0.11262 -0.196667 0.316051
+
+-0.175275 0.954154 0.24263
+-0.420703 -0.295399 0.857758
+0.890106 0.0482684 0.453191
+0.112091 -0.198423 0.315003
+
+-0.207805 0.946399 0.247279
+-0.410327 -0.31382 0.856241
+0.887947 0.076466 0.453546
+0.111562 -0.20018 0.31393
+
+-0.240026 0.937511 0.251915
+-0.399199 -0.331867 0.854695
+0.884888 0.104585 0.453911
+0.111032 -0.201936 0.312833
+
+-0.271898 0.927502 0.256539
+-0.387334 -0.349512 0.85312
+0.880934 0.132595 0.454285
+0.110503 -0.203692 0.311712
+
+-0.303381 0.916385 0.261148
+-0.374745 -0.366726 0.851515
+0.876086 0.160469 0.454668
+0.109974 -0.205448 0.310567
+
+-0.334435 0.904175 0.265744
+-0.361448 -0.383479 0.849882
+0.870349 0.188178 0.455062
+0.109444 -0.207204 0.309398
+
+-0.363313 0.892129 0.268534
+-0.349486 -0.397684 0.848356
+0.863634 0.21437 0.45627
+0.108875 -0.208669 0.308356
+
+-0.389632 0.880805 0.269017
+-0.339587 -0.408922 0.847032
+0.856077 0.238676 0.458439
+0.10825 -0.20976 0.307478
+
+-0.412929 0.870946 0.26635
+-0.332834 -0.416525 0.846007
+0.847768 0.260691 0.461876
+0.107509 -0.21033 0.306859
+
+-0.43389 0.86249 0.260481
+-0.329166 -0.420879 0.845287
+0.838683 0.28102 0.466518
+0.10666 -0.210383 0.306506
+
+-0.453206 0.85521 0.251437
+-0.328392 -0.42241 0.844825
+0.828712 0.30031 0.472282
+0.105746 -0.209954 0.306402
+
+-0.471824 0.848205 0.240689
+-0.329098 -0.422679 0.844415
+0.817971 0.319205 0.478572
+0.104803 -0.209278 0.306418
+
+-0.490229 0.840729 0.229892
+-0.329884 -0.423112 0.843891
+0.806754 0.337862 0.484765
+0.10386 -0.208601 0.30641
+
+-0.508408 0.83279 0.219047
+-0.330744 -0.423715 0.843252
+0.795066 0.356268 0.49086
+0.102917 -0.207925 0.306378
+
+-0.524713 0.82543 0.208184
+-0.332071 -0.423648 0.842764
+0.78384 0.373078 0.496395
+0.101919 -0.207328 0.30632
+
+-0.535206 0.82133 0.197414
+-0.334814 -0.420821 0.843095
+0.775535 0.385132 0.500219
+0.100725 -0.20701 0.306229
+
+-0.538508 0.82167 0.186726
+-0.339444 -0.414366 0.84444
+0.771224 0.391355 0.502051
+0.0992853 -0.207047 0.306119
+
+-0.533555 0.827205 0.17621
+-0.346112 -0.403655 0.846917
+0.771703 0.390889 0.501678
+0.0975659 -0.207474 0.305973
+
+-0.524589 0.835059 0.165778
+-0.35346 -0.390773 0.849919
+0.774514 0.387262 0.500156
+0.095714 -0.208104 0.3058
+
+-0.51383 0.84371 0.155345
+-0.36091 -0.376865 0.853063
+0.778282 0.382264 0.498148
+0.0938099 -0.208816 0.3056
+
+-0.502902 0.852113 0.144888
+-0.368078 -0.362798 0.856094
+0.782054 0.377201 0.496096
+0.0919058 -0.209528 0.305375
+
+-0.491811 0.860265 0.134408
+-0.374963 -0.348576 0.85901
+0.785827 0.372073 0.494001
+0.0900017 -0.210239 0.305125
+
+-0.480563 0.868163 0.123906
+-0.381559 -0.334208 0.861811
+0.789602 0.366877 0.491863
+0.0880976 -0.210951 0.304852
+
+-0.469164 0.875802 0.113384
+-0.387863 -0.319698 0.864497
+0.793377 0.361613 0.489682
+0.0861935 -0.211663 0.304554
+
+-0.457619 0.883181 0.102844
+-0.393873 -0.305052 0.867068
+0.797151 0.35628 0.487458
+0.0842893 -0.212375 0.304233
+
+-0.445935 0.890295 0.0922857
+-0.399584 -0.290278 0.869524
+0.800921 0.350875 0.485192
+0.0823852 -0.213087 0.303887
+
+-0.434117 0.897143 0.0817114
+-0.404994 -0.27538 0.871863
+0.804688 0.345398 0.482885
+0.0804811 -0.213798 0.303517
+
+-0.422171 0.903722 0.0711222
+-0.4101 -0.260367 0.874087
+0.808449 0.339847 0.480535
+0.078577 -0.21451 0.303122
+
+-0.410104 0.910028 0.0605195
+-0.414898 -0.245243 0.876194
+0.812203 0.334221 0.478145
+0.0766729 -0.215222 0.302704
+
+-0.397923 0.916061 0.0499045
+-0.419387 -0.230016 0.878184
+0.815949 0.32852 0.475713
+0.0747688 -0.215934 0.302261
+
+-0.385632 0.921816 0.0392787
+-0.423564 -0.214693 0.880057
+0.819684 0.322741 0.473241
+0.0728646 -0.216645 0.301794
+
+-0.373238 0.927293 0.0286434
+-0.427426 -0.199279 0.881813
+0.823408 0.316884 0.470728
+0.0709605 -0.217357 0.301303
+
+-0.360749 0.932489 0.0179999
+-0.430971 -0.183782 0.883452
+0.827118 0.310947 0.468175
+0.0690564 -0.218069 0.300788
+
+-0.34817 0.937403 0.00734948
+-0.434198 -0.168208 0.884974
+0.830813 0.30493 0.465583
+0.0671523 -0.218781 0.300249
+
+-0.335507 0.942032 -0.00330644
+-0.437103 -0.152564 0.886378
+0.834492 0.298831 0.462951
+0.0652482 -0.219493 0.299685
+
+-0.322767 0.946375 -0.0139665
+-0.439686 -0.136857 0.887664
+0.838151 0.29265 0.460281
+0.0633441 -0.220204 0.299097
+
+-0.309957 0.950431 -0.0246295
+-0.441944 -0.121095 0.888832
+0.841791 0.286385 0.457572
+0.06144 -0.220916 0.298485
+
+-0.297083 0.954199 -0.0352939
+-0.443876 -0.105283 0.889882
+0.845408 0.280035 0.454824
+0.0595358 -0.221628 0.297849
+
+-0.284152 0.957677 -0.0459586
+-0.445482 -0.089429 0.890813
+0.849002 0.2736 0.452039
+0.0576317 -0.22234 0.297189
+
+-0.27117 0.960865 -0.056622
+-0.446759 -0.07354 0.891627
+0.852569 0.267079 0.449216
+0.0557276 -0.223051 0.296504
+
+-0.258144 0.963761 -0.067283
+-0.447706 -0.0576229 0.892322
+0.856108 0.260471 0.446357
+0.0538235 -0.223763 0.295796
+
+-0.245081 0.966365 -0.0779402
+-0.448323 -0.041685 0.892899
+0.859617 0.253775 0.44346
+0.0519194 -0.224475 0.295063
+
+-0.231987 0.968676 -0.0885922
+-0.448609 -0.0257332 0.893357
+0.863094 0.246991 0.440527
+0.0500153 -0.225187 0.294306
+
+-0.218869 0.970695 -0.0992377
+-0.448564 -0.00977484 0.893697
+0.866537 0.240117 0.437558
+0.0481111 -0.225899 0.293524
+
+-0.205734 0.97242 -0.109875
+-0.448187 0.00618308 0.893919
+0.869944 0.233154 0.434554
+0.046207 -0.22661 0.292719
+
+-0.192587 0.973853 -0.120504
+-0.447477 0.0221333 0.894022
+0.873312 0.2261 0.431514
+0.0443029 -0.227322 0.291889
+
+-0.179437 0.974992 -0.131122
+-0.446435 0.0380688 0.894006
+0.87664 0.218955 0.42844
+0.0423988 -0.228034 0.291035
+
+-0.16629 0.975839 -0.141728
+-0.445061 0.0539821 0.893872
+0.879925 0.211719 0.425331
+0.0404947 -0.228746 0.290157
+
+-0.153152 0.976393 -0.152321
+-0.443354 0.0698663 0.893619
+0.883166 0.204392 0.422188
+0.0385906 -0.229457 0.289255
+
+-0.140029 0.976655 -0.1629
+-0.441317 0.085714 0.893248
+0.886359 0.196972 0.419012
+0.0366865 -0.230169 0.288329
+
+-0.12693 0.976627 -0.173463
+-0.438948 0.101518 0.892759
+0.889502 0.189459 0.415802
+0.0347823 -0.230881 0.287378
+
+-0.11386 0.976308 -0.184009
+-0.436248 0.117271 0.892152
+0.892594 0.181854 0.41256
+0.0328782 -0.231593 0.286404
+
+-0.100825 0.9757 -0.194537
+-0.433219 0.132967 0.891426
+0.895631 0.174155 0.409285
+0.0309741 -0.232305 0.285405
+
+-0.0863614 0.97523 -0.203639
+-0.428616 0.148149 0.891258
+0.89935 0.164253 0.405205
+0.0289455 -0.232887 0.284545
+
+-0.0705999 0.974918 -0.211071
+-0.422176 0.16251 0.891828
+0.90376 0.152072 0.400114
+0.0267647 -0.233314 0.283855
+
+-0.053518 0.974734 -0.216862
+-0.41387 0.17599 0.893162
+0.908761 0.137553 0.393995
+0.0244319 -0.233586 0.283335
+
+-0.0361891 0.974408 -0.221854
+-0.404477 0.188721 0.894864
+0.913832 0.122119 0.387296
+0.0220221 -0.233777 0.282884
+
+-0.0189198 0.973747 -0.226847
+-0.39475 0.20118 0.896493
+0.918594 0.106509 0.38058
+0.0196122 -0.233968 0.282409
+
+-0.00171713 0.972752 -0.231841
+-0.384696 0.213357 0.898047
+0.923042 0.0907301 0.373847
+0.0172024 -0.23416 0.28191
+
+0.0154121 0.971428 -0.236834
+-0.374321 0.225243 0.899527
+0.927171 0.0747884 0.367097
+0.0147925 -0.234351 0.281387
+
+0.0324611 0.969776 -0.241827
+-0.363634 0.236832 0.900933
+0.930976 0.0586913 0.360332
+0.0123827 -0.234542 0.280839
+
+0.0494231 0.9678 -0.246819
+-0.352642 0.248114 0.902265
+0.934452 0.0424461 0.35355
+0.00997283 -0.234734 0.280268
+
+0.0662917 0.965504 -0.25181
+-0.341354 0.259083 0.903523
+0.937594 0.0260603 0.346753
+0.00756298 -0.234925 0.279672
+
+0.0830603 0.962889 -0.2568
+-0.329777 0.26973 0.904706
+0.940398 0.00954144 0.339942
+0.00515314 -0.235116 0.279052
+
+0.0997225 0.95996 -0.261787
+-0.31792 0.280047 0.905815
+0.942859 -0.00710283 0.333117
+0.00274329 -0.235307 0.278408
+
+0.116272 0.95672 -0.266772
+-0.305791 0.290029 0.906849
+0.944972 -0.0238647 0.326278
+0.000333447 -0.235499 0.277739
+
+0.132703 0.953173 -0.271755
+-0.293399 0.299668 0.907808
+0.946735 -0.0407361 0.319427
+-0.0020764 -0.23569 0.277047
+
+0.149008 0.949323 -0.276734
+-0.280753 0.308958 0.908693
+0.948142 -0.0577091 0.312563
+-0.00448624 -0.235881 0.27633
+
+0.159357 0.946123 -0.28188
+-0.27139 0.316512 0.908937
+0.949185 -0.0683464 0.307207
+-0.00683254 -0.235791 0.275549
+
+0.162205 0.944007 -0.287299
+-0.266578 0.322251 0.908345
+0.950066 -0.0707509 0.303922
+-0.00909708 -0.235326 0.274676
+
+0.157643 0.943042 -0.292952
+-0.266474 0.326281 0.906936
+0.950863 -0.0649079 0.302732
+-0.0112835 -0.234487 0.273708
+
+0.145722 0.943101 -0.298873
+-0.271178 0.328604 0.9047
+0.951435 -0.0507866 0.303633
+-0.0133911 -0.233273 0.272649
+
+0.128299 0.943681 -0.304967
+-0.279567 0.329452 0.901833
+0.951515 -0.0304459 0.306091
+-0.0154415 -0.231778 0.271515
+
+0.110916 0.943898 -0.311052
+-0.288067 0.330081 0.898924
+0.951165 -0.010101 0.308517
+-0.0174919 -0.230282 0.270357
+
+0.0935792 0.943754 -0.317129
+-0.296671 0.330489 0.895971
+0.950384 0.0102385 0.310911
+-0.0195423 -0.228787 0.269175
+
+0.0762974 0.943251 -0.323196
+-0.305372 0.33067 0.892975
+0.949171 0.0305635 0.313272
+-0.0215927 -0.227291 0.267968
+
+0.0590785 0.942391 -0.329255
+-0.314167 0.330623 0.889937
+0.947528 0.0508647 0.315601
+-0.0236431 -0.225796 0.266738
+
+0.0419303 0.941177 -0.335303
+-0.323047 0.330343 0.886856
+0.945453 0.0711327 0.317896
+-0.0256935 -0.2243 0.265483
+
+0.0248607 0.93961 -0.341342
+-0.332009 0.329827 0.883733
+0.942949 0.0913583 0.320159
+-0.0277439 -0.222805 0.264204
+
+0.00787739 0.937695 -0.34737
+-0.341045 0.329072 0.880568
+0.940014 0.111532 0.322388
+-0.0297943 -0.221309 0.262901
+
+-0.00901191 0.935434 -0.353388
+-0.350149 0.328076 0.877361
+0.936651 0.131645 0.324584
+-0.0318447 -0.219814 0.261573
+
+-0.0239634 0.933268 -0.358381
+-0.357832 0.326726 0.874761
+0.933479 0.149202 0.326123
+-0.0340058 -0.218225 0.260352
+
+-0.0325674 0.932186 -0.360511
+-0.361216 0.325344 0.873884
+0.931913 0.158683 0.326125
+-0.0364237 -0.216342 0.259454
+
+-0.0342085 0.932431 -0.359726
+-0.360104 0.324261 0.874746
+0.932285 0.159463 0.324679
+-0.0390894 -0.214159 0.258881
+
+-0.0341696 0.933134 -0.357901
+-0.35755 0.322994 0.876261
+0.933269 0.157909 0.322606
+-0.0418702 -0.211883 0.258411
+
+-0.0341246 0.933835 -0.356072
+-0.354996 0.32172 0.877767
+0.934245 0.156357 0.320529
+-0.0446511 -0.209608 0.257917
+
+-0.0340737 0.934534 -0.354239
+-0.35244 0.320439 0.879264
+0.935214 0.154808 0.318448
+-0.0474319 -0.207333 0.257399
+
+-0.0340168 0.93523 -0.352404
+-0.349883 0.31915 0.880752
+0.936176 0.153261 0.316365
+-0.0502127 -0.205057 0.256857
+
+-0.0339539 0.935923 -0.350565
+-0.347325 0.317854 0.882232
+0.93713 0.151715 0.314277
+-0.0529936 -0.202782 0.25629
+
+-0.033885 0.936613 -0.348724
+-0.344767 0.316551 0.883703
+0.938077 0.150173 0.312186
+-0.0557744 -0.200506 0.2557
+
+-0.0338101 0.9373 -0.346879
+-0.342207 0.31524 0.885166
+0.939016 0.148632 0.310092
+-0.0585552 -0.198231 0.255085
+
+-0.0337293 0.937985 -0.345031
+-0.339646 0.313923 0.886619
+0.939948 0.147093 0.307995
+-0.0613361 -0.195955 0.254446
+
+-0.0336424 0.938667 -0.34318
+-0.337085 0.312597 0.888064
+0.940873 0.145557 0.305894
+-0.0641169 -0.19368 0.253782
+
+-0.0335496 0.939346 -0.341325
+-0.334522 0.311265 0.889499
+0.94179 0.144023 0.30379
+-0.0668977 -0.191405 0.253095
+
+-0.0334507 0.940023 -0.339468
+-0.331959 0.309925 0.890926
+0.9427 0.142492 0.301682
+-0.0696785 -0.189129 0.252383
+
+-0.0333459 0.940696 -0.337608
+-0.329396 0.308578 0.892344
+0.943603 0.140962 0.299571
+-0.0724594 -0.186854 0.251647
+
+-0.0332351 0.941367 -0.335744
+-0.326831 0.307224 0.893753
+0.944498 0.139436 0.297457
+-0.0752402 -0.184578 0.250887
+
+-0.0331183 0.942034 -0.333878
+-0.324266 0.305862 0.895154
+0.945386 0.137911 0.29534
+-0.078021 -0.182303 0.250103
+
+-0.0329956 0.942699 -0.332008
+-0.3217 0.304494 0.896545
+0.946267 0.136389 0.293219
+-0.0808019 -0.180027 0.249295
+
+-0.0328668 0.943361 -0.330136
+-0.319133 0.303118 0.897927
+0.94714 0.134869 0.291095
+-0.0835827 -0.177752 0.248462
+
+-0.0327321 0.94402 -0.328261
+-0.316566 0.301734 0.899301
+0.948005 0.133352 0.288968
+-0.0863635 -0.175477 0.247605
+
+-0.0325914 0.944676 -0.326383
+-0.313999 0.300344 0.900665
+0.948864 0.131838 0.286838
+-0.0891443 -0.173201 0.246725
+
+-0.0324447 0.945329 -0.324501
+-0.311431 0.298947 0.902021
+0.949715 0.130325 0.284705
+-0.0919252 -0.170926 0.245819
+
+-0.0334242 0.945755 -0.323157
+-0.308704 0.297758 0.903351
+0.950571 0.129954 0.282006
+-0.094602 -0.168752 0.24489
+
+-0.0358703 0.94549 -0.323671
+-0.304493 0.298139 0.904653
+0.951839 0.131006 0.2772
+-0.0969965 -0.166959 0.24394
+
+-0.0402045 0.944436 -0.326228
+-0.298704 0.300201 0.9059
+0.953499 0.133867 0.270037
+-0.0990861 -0.165584 0.242957
+
+-0.0471117 0.942436 -0.331051
+-0.291327 0.304047 0.907019
+0.955463 0.139175 0.260233
+-0.100848 -0.164662 0.241924
+
+-0.0567694 0.939402 -0.338084
+-0.28247 0.309682 0.907914
+0.957595 0.14704 0.247773
+-0.102271 -0.164191 0.24085
+
+-0.0680597 0.935853 -0.345755
+-0.273463 0.315787 0.908569
+0.959472 0.156388 0.234429
+-0.103557 -0.163857 0.239754
+
+-0.0793989 0.932123 -0.35333
+-0.264548 0.322036 0.909014
+0.961098 0.165648 0.221022
+-0.104844 -0.163524 0.238634
+
+-0.0907833 0.928211 -0.36081
+-0.255731 0.328428 0.909251
+0.962476 0.174815 0.207556
+-0.106131 -0.16319 0.237489
+
+-0.102209 0.924115 -0.368191
+-0.247015 0.334959 0.909278
+0.963606 0.183885 0.194034
+-0.107418 -0.162857 0.236321
+
+-0.113673 0.919836 -0.375472
+-0.238404 0.341626 0.909096
+0.964491 0.192854 0.180459
+-0.108705 -0.162523 0.235128
+
+-0.125171 0.915374 -0.382652
+-0.229902 0.348426 0.908705
+0.965131 0.201716 0.166834
+-0.109992 -0.16219 0.233911
+
+-0.1367 0.910728 -0.389728
+-0.221514 0.355357 0.908104
+0.965528 0.210468 0.153162
+-0.111279 -0.161856 0.23267
+
+-0.148255 0.905897 -0.3967
+-0.213243 0.362413 0.907295
+0.965685 0.219105 0.139447
+-0.112565 -0.161523 0.231405
+
+-0.159833 0.900882 -0.403564
+-0.205094 0.369593 0.906277
+0.965603 0.227621 0.125692
+-0.113852 -0.161189 0.230115
+
+-0.17143 0.895683 -0.410321
+-0.197069 0.376893 0.90505
+0.965285 0.236014 0.1119
+-0.115139 -0.160856 0.228802
+
+-0.183043 0.8903 -0.416967
+-0.189173 0.38431 0.903615
+0.964733 0.244279 0.0980753
+-0.116426 -0.160522 0.227464
+
+-0.194667 0.884732 -0.423502
+-0.181409 0.391839 0.901972
+0.963948 0.252411 0.08422
+-0.117713 -0.160189 0.226102
+
+-0.206299 0.87898 -0.429924
+-0.17378 0.399477 0.900121
+0.962934 0.260406 0.0703379
+-0.119 -0.159855 0.224716
+
+-0.217934 0.873045 -0.436231
+-0.166291 0.407221 0.898063
+0.961692 0.26826 0.0564322
+-0.120287 -0.159522 0.223305
+
+-0.22957 0.866926 -0.442422
+-0.158945 0.415067 0.895799
+0.960226 0.27597 0.0425063
+-0.121573 -0.159189 0.221871
+
+-0.241203 0.860624 -0.448495
+-0.151744 0.42301 0.893329
+0.958538 0.28353 0.0285635
+-0.12286 -0.158855 0.220412
+
+-0.252827 0.854139 -0.45445
+-0.144693 0.431047 0.890653
+0.956631 0.290937 0.0146072
+-0.124147 -0.158522 0.218929
+
+-0.258613 0.850094 -0.458758
+-0.134775 0.438516 0.88856
+0.956533 0.291623 0.0011655
+-0.125288 -0.157849 0.217641
+
+-0.254749 0.850401 -0.46035
+-0.119799 0.444635 0.887665
+0.959558 0.281281 -0.0113936
+-0.126227 -0.156619 0.216689
+
+-0.24512 0.85328 -0.46025
+-0.101767 0.449464 0.887483
+0.964137 0.264378 -0.0233368
+-0.12695 -0.155003 0.215975
+
+-0.230347 0.858258 -0.458622
+-0.0810607 0.452734 0.887953
+0.969726 0.241714 -0.0347151
+-0.127469 -0.153034 0.215473
+
+-0.211769 0.864449 -0.455942
+-0.0583959 0.454497 0.888832
+0.975574 0.214852 -0.0457679
+-0.12793 -0.150862 0.215069
+
+-0.192995 0.870245 -0.45324
+-0.0356913 0.455392 0.889575
+0.98055 0.187861 -0.0568283
+-0.128391 -0.148691 0.21464
+
+-0.174035 0.875641 -0.450516
+-0.0129782 0.455418 0.890183
+0.984654 0.16077 -0.0678946
+-0.128852 -0.146519 0.214188
+
+-0.154897 0.880629 -0.447771
+0.0097122 0.454577 0.890655
+0.987883 0.13361 -0.0789652
+-0.129312 -0.144348 0.213711
+
+-0.135588 0.885204 -0.445005
+0.0323486 0.452869 0.89099
+0.990237 0.106412 -0.0900385
+-0.129773 -0.142176 0.21321
+
+-0.116117 0.889359 -0.442219
+0.0549 0.450297 0.891189
+0.991717 0.0792043 -0.101113
+-0.130234 -0.140005 0.212685
+
+-0.101835 0.892087 -0.440239
+0.0726686 0.448028 0.891061
+0.992144 0.05875 -0.110452
+-0.130669 -0.137553 0.21208
+
+-0.0959101 0.893112 -0.439492
+0.0829893 0.447165 0.890593
+0.991924 0.0489438 -0.117006
+-0.131042 -0.134653 0.211304
+
+-0.0992741 0.892403 -0.440183
+0.0851638 0.448365 0.889784
+0.991409 0.0508449 -0.120512
+-0.131364 -0.131252 0.210387
+
+-0.108812 0.890528 -0.441724
+0.0819769 0.450887 0.888808
+0.990676 0.0605018 -0.122065
+-0.131651 -0.127529 0.209361
+
+-0.118326 0.888549 -0.44326
+0.0787488 0.453387 0.887828
+0.989847 0.0701468 -0.12362
+-0.131939 -0.123806 0.20831
+
+-0.127815 0.886467 -0.444792
+0.0754796 0.455864 0.886843
+0.988922 0.0797791 -0.125176
+-0.132226 -0.120083 0.207236
+
+-0.137278 0.884282 -0.446319
+0.0721695 0.458317 0.885854
+0.9879 0.0893976 -0.126735
+-0.132514 -0.11636 0.206137
+
+-0.146714 0.881994 -0.447842
+0.0688186 0.460745 0.88486
+0.986782 0.0990013 -0.128295
+-0.132801 -0.112637 0.205014
+
+-0.156121 0.879603 -0.44936
+0.0654272 0.463148 0.883863
+0.985569 0.108589 -0.129857
+-0.133089 -0.108914 0.203867
+
+-0.165499 0.877111 -0.450873
+0.0619955 0.465526 0.88286
+0.984259 0.118161 -0.131421
+-0.133376 -0.105191 0.202696
+
+-0.174847 0.874517 -0.452381
+0.0585235 0.467877 0.881854
+0.982855 0.127714 -0.132987
+-0.133664 -0.101468 0.2015
+
+-0.187641 0.871649 -0.45279
+0.0533981 0.469349 0.881397
+0.980785 0.141208 -0.134614
+-0.134053 -0.0979454 0.200374
+
+-0.204946 0.86828 -0.45176
+0.046074 0.469604 0.881674
+0.977688 0.159881 -0.136248
+-0.134651 -0.0947225 0.199335
+
+-0.227074 0.86418 -0.449033
+0.0366062 0.468325 0.882798
+0.973189 0.184023 -0.137979
+-0.135425 -0.0918104 0.19841
+
+-0.253677 0.859023 -0.444665
+0.0252847 0.465434 0.884721
+0.966958 0.21319 -0.13979
+-0.136338 -0.0891812 0.197589
+
+-0.284016 0.852512 -0.438815
+0.0126027 0.460941 0.887341
+0.958737 0.246488 -0.141658
+-0.137364 -0.0867967 0.196854
+
+-0.314176 0.844899 -0.432941
+0.00023174 0.456101 0.889928
+0.949365 0.279494 -0.143492
+-0.138391 -0.0844121 0.196095
+
+-0.344119 0.83619 -0.427045
+-0.0118187 0.450929 0.892481
+0.938852 0.312167 -0.145291
+-0.139417 -0.0820275 0.195311
+
+-0.373803 0.826392 -0.421127
+-0.0235396 0.445442 0.895001
+0.927209 0.344467 -0.147055
+-0.140444 -0.0796429 0.194504
+
+-0.403188 0.815512 -0.415186
+-0.034923 0.439655 0.897488
+0.914451 0.376355 -0.148783
+-0.141471 -0.0772583 0.193672
+
+-0.432233 0.803561 -0.409224
+-0.0459613 0.433584 0.89994
+0.90059 0.407793 -0.150477
+-0.142497 -0.0748737 0.192816
+
+-0.4609 0.790549 -0.403241
+-0.0566478 0.427247 0.902359
+0.885642 0.43874 -0.152135
+-0.143524 -0.0724891 0.191936
+
+-0.489149 0.776489 -0.397238
+-0.0669765 0.420658 0.904743
+0.869625 0.46916 -0.153758
+-0.14455 -0.0701046 0.191032
+
+-0.516941 0.761396 -0.391214
+-0.076942 0.413836 0.907094
+0.852556 0.499015 -0.155345
+-0.145577 -0.06772 0.190103
+
+-0.544237 0.745285 -0.38517
+-0.0865398 0.406797 0.90941
+0.834456 0.528267 -0.156897
+-0.146603 -0.0653354 0.189151
+
+-0.571 0.728173 -0.379107
+-0.0957659 0.399557 0.911692
+0.815345 0.556882 -0.158413
+-0.14763 -0.0629508 0.188174
+
+-0.597193 0.710079 -0.373026
+-0.104617 0.392134 0.91394
+0.795246 0.584824 -0.159893
+-0.148656 -0.0605662 0.187173
+
+-0.622779 0.691022 -0.366925
+-0.113092 0.384544 0.916153
+0.774181 0.612057 -0.161337
+-0.149683 -0.0581816 0.186148
+
+-0.647722 0.671024 -0.360807
+-0.121187 0.376805 0.918331
+0.752176 0.638549 -0.162746
+-0.150709 -0.055797 0.185098
+
+-0.671988 0.650108 -0.354672
+-0.128902 0.368932 0.920475
+0.729257 0.664266 -0.164118
+-0.151736 -0.0534125 0.184025
+
+-0.695542 0.628297 -0.348519
+-0.136237 0.360943 0.922583
+0.705451 0.689176 -0.165453
+-0.152762 -0.0510279 0.182927
+
+-0.71835 0.605616 -0.342349
+-0.143192 0.352854 0.924657
+0.680786 0.713249 -0.166753
+-0.153789 -0.0486433 0.181805
+
+-0.74038 0.582092 -0.336164
+-0.149768 0.344681 0.926695
+0.655291 0.736454 -0.168016
+-0.154815 -0.0462587 0.180659
+
+-0.761601 0.557753 -0.329962
+-0.155967 0.336441 0.928699
+0.628997 0.758762 -0.169243
+-0.155842 -0.0438741 0.179488
+
+-0.781983 0.532627 -0.323746
+-0.161792 0.32815 0.930667
+0.601935 0.780145 -0.170433
+-0.156869 -0.0414895 0.178294
+
+-0.801495 0.506745 -0.317514
+-0.167244 0.319823 0.9326
+0.574138 0.800577 -0.171586
+-0.157895 -0.0391049 0.177075
+
+-0.82011 0.480137 -0.311268
+-0.172329 0.311476 0.934498
+0.545639 0.820031 -0.172703
+-0.158922 -0.0367203 0.175832
+
+-0.8378 0.452836 -0.305008
+-0.17705 0.303124 0.93636
+0.516473 0.838484 -0.173783
+-0.159948 -0.0343358 0.174565
+
+-0.85454 0.424875 -0.298735
+-0.181412 0.294782 0.938186
+0.486674 0.855912 -0.174826
+-0.160975 -0.0319512 0.173274
+
+-0.868839 0.400481 -0.29109
+-0.18273 0.287047 0.940326
+0.46014 0.870183 -0.176218
+-0.162163 -0.0298064 0.171981
+
+-0.880145 0.382263 -0.281461
+-0.179658 0.280581 0.942867
+0.439395 0.880426 -0.178275
+-0.163593 -0.0280218 0.170704
+
+-0.888825 0.370364 -0.269852
+-0.172361 0.275437 0.945741
+0.424596 0.887111 -0.180979
+-0.165273 -0.0265905 0.16944
+
+-0.895441 0.363692 -0.256737
+-0.161759 0.27148 0.948753
+0.414753 0.891082 -0.184264
+-0.167153 -0.0254303 0.168187
+
+-0.899794 0.361677 -0.244051
+-0.149572 0.269762 0.95124
+0.409877 0.892423 -0.188633
+-0.16871 -0.024463 0.167117
+
+-0.903033 0.359988 -0.234392
+-0.139479 0.270364 0.952601
+0.406297 0.892923 -0.193937
+-0.169497 -0.0234946 0.166311
+
+-0.90486 0.359365 -0.228222
+-0.131667 0.273563 0.9528
+0.404836 0.8922 -0.200219
+-0.16949 -0.0225905 0.165778
+
+-0.905356 0.359416 -0.226164
+-0.126664 0.279782 0.951671
+0.405322 0.890249 -0.207777
+-0.16865 -0.0218277 0.165561
+
+-0.904486 0.360465 -0.22797
+-0.124184 0.288771 0.94931
+0.408024 0.886948 -0.216426
+-0.167004 -0.0211824 0.165636
+
+-0.902441 0.362393 -0.232964
+-0.123673 0.300074 0.945865
+0.412681 0.882398 -0.225981
+-0.164634 -0.0205949 0.165969
+
+-0.899123 0.365348 -0.241036
+-0.124935 0.313559 0.941314
+0.419486 0.876471 -0.236284
+-0.161648 -0.0201124 0.166516
+
+-0.895776 0.36817 -0.249072
+-0.126014 0.32701 0.936581
+0.42627 0.870353 -0.246533
+-0.158662 -0.0196298 0.167039
+
+-0.890564 0.376284 -0.255552
+-0.123352 0.340983 0.931941
+0.437814 0.861476 -0.257252
+-0.155812 -0.0194025 0.16755
+
+-0.8831 0.39052 -0.260054
+-0.115988 0.355355 0.927507
+0.454622 0.849245 -0.268519
+-0.153083 -0.0194862 0.168045
+
+-0.873345 0.410136 -0.262787
+-0.104097 0.369878 0.92323
+0.475849 0.833654 -0.280337
+-0.150441 -0.0198477 0.16852
+
+-0.863166 0.42947 -0.26552
+-0.091585 0.383972 0.918791
+0.496545 0.817387 -0.292099
+-0.147799 -0.0202092 0.168971
+
+-0.852572 0.448511 -0.268252
+-0.0784673 0.397614 0.914191
+0.516686 0.800463 -0.303801
+-0.145156 -0.0205706 0.169398
+
+-0.841572 0.467252 -0.270982
+-0.0647609 0.410781 0.909431
+0.536248 0.782901 -0.315442
+-0.142514 -0.0209321 0.1698
+
+-0.830176 0.485685 -0.273711
+-0.0504834 0.423451 0.904511
+0.555211 0.764721 -0.32702
+-0.139872 -0.0212936 0.170178
+
+-0.818393 0.503802 -0.276437
+-0.0356533 0.435603 0.899432
+0.573552 0.745945 -0.338532
+-0.13723 -0.021655 0.170532
+
+-0.806232 0.521594 -0.27916
+-0.0202897 0.447216 0.894196
+0.591252 0.726593 -0.349977
+-0.134588 -0.0220165 0.170862
+
+-0.793702 0.539055 -0.28188
+-0.00441256 0.458271 0.888802
+0.60829 0.706688 -0.361352
+-0.131946 -0.022378 0.171168
+
+-0.780815 0.556177 -0.284596
+0.0119573 0.468747 0.883252
+0.624648 0.686253 -0.372655
+-0.129303 -0.0227394 0.17145
+
+-0.767579 0.572954 -0.287308
+0.0287987 0.478626 0.877546
+0.640307 0.665312 -0.383884
+-0.126661 -0.0231009 0.171707
+
+-0.754005 0.58938 -0.290015
+0.0460895 0.487892 0.871687
+0.65525 0.643889 -0.395037
+-0.124019 -0.0234623 0.17194
+
+-0.740102 0.605447 -0.292716
+0.063807 0.496526 0.865673
+0.669461 0.622009 -0.406112
+-0.121377 -0.0238238 0.172149
+
+-0.725881 0.621151 -0.295412
+0.081928 0.504513 0.859508
+0.682923 0.599698 -0.417106
+-0.118735 -0.0241853 0.172334
+
+-0.711352 0.636485 -0.298101
+0.100429 0.511839 0.853191
+0.695624 0.576982 -0.428019
+-0.116092 -0.0245467 0.172495
+
+-0.698348 0.650404 -0.298806
+0.119149 0.517279 0.847482
+0.705771 0.556235 -0.438736
+-0.113613 -0.0251775 0.172748
+
+-0.688496 0.661893 -0.296429
+0.137345 0.520334 0.842846
+0.712116 0.539583 -0.449156
+-0.111379 -0.0262308 0.17317
+
+-0.681902 0.671078 -0.29097
+0.154802 0.521199 0.839278
+0.714875 0.527263 -0.459291
+-0.109392 -0.0277033 0.173764
+
+-0.678586 0.677798 -0.283038
+0.170926 0.520473 0.836595
+0.714356 0.519324 -0.469039
+-0.107618 -0.0295153 0.174497
+
+-0.678597 0.682052 -0.272601
+0.185659 0.518357 0.834767
+0.710659 0.51586 -0.478385
+-0.106061 -0.0316626 0.175373
+
+-0.681186 0.684288 -0.26026
+0.199203 0.515321 0.833524
+0.704488 0.515941 -0.487342
+-0.104692 -0.0340669 0.176346
+
+-0.683584 0.686497 -0.24786
+0.212716 0.512238 0.832084
+0.698187 0.516076 -0.496187
+-0.103322 -0.0364712 0.177294
+
+-0.68579 0.688678 -0.235404
+0.226194 0.50911 0.830447
+0.691757 0.516265 -0.504918
+-0.101952 -0.0388755 0.178219
+
+-0.687804 0.690828 -0.222895
+0.239635 0.505938 0.828615
+0.685201 0.516511 -0.513533
+-0.100583 -0.0412798 0.179119
+
+-0.689624 0.692948 -0.210335
+0.253036 0.502721 0.826586
+0.678521 0.516812 -0.52203
+-0.0992132 -0.0436841 0.179995
+
+-0.691252 0.695036 -0.197728
+0.266393 0.499462 0.824362
+0.671718 0.517168 -0.530407
+-0.0978435 -0.0460884 0.180847
+
+-0.692686 0.697089 -0.185077
+0.279703 0.496161 0.821943
+0.664795 0.517582 -0.538661
+-0.0964739 -0.0484927 0.181674
+
+-0.693925 0.699108 -0.172384
+0.292963 0.492819 0.81933
+0.657754 0.518052 -0.546793
+-0.0951042 -0.050897 0.182478
+
+-0.695887 0.700136 -0.159846
+0.30495 0.489599 0.816883
+0.65019 0.519713 -0.554212
+-0.0937306 -0.0532104 0.183223
+
+-0.701231 0.69739 -0.148062
+0.311691 0.486671 0.816089
+0.64119 0.526117 -0.558638
+-0.0923667 -0.055058 0.183855
+
+-0.710785 0.689894 -0.137226
+0.312024 0.48408 0.817501
+0.630418 0.53825 -0.55934
+-0.0910027 -0.0563243 0.184308
+
+-0.724869 0.676988 -0.127484
+0.305515 0.481784 0.821307
+0.617434 0.556392 -0.55606
+-0.0896362 -0.0569611 0.184573
+
+-0.742111 0.659689 -0.118663
+0.293658 0.479135 0.827161
+0.602524 0.578999 -0.549295
+-0.0882797 -0.0570485 0.184687
+
+-0.761053 0.639202 -0.11054
+0.278264 0.475619 0.834479
+0.585976 0.604324 -0.539838
+-0.0869418 -0.0567198 0.184697
+
+-0.779882 0.617453 -0.102644
+0.26217 0.471141 0.842196
+0.568376 0.629903 -0.529312
+-0.085611 -0.056253 0.184636
+
+-0.798093 0.595033 -0.0947803
+0.24654 0.466024 0.849729
+0.549787 0.654796 -0.51863
+-0.0842802 -0.0557862 0.184551
+
+-0.815661 0.571958 -0.086951
+0.2314 0.460293 0.857079
+0.530236 0.678966 -0.507794
+-0.0829493 -0.0553194 0.184441
+
+-0.830354 0.551503 -0.0797292
+0.217762 0.452857 0.864581
+0.512925 0.700546 -0.496128
+-0.0815555 -0.054932 0.184415
+
+-0.840487 0.536799 -0.0736772
+0.20634 0.442833 0.872538
+0.501004 0.718154 -0.482959
+-0.080023 -0.0547232 0.184549
+
+-0.846491 0.527939 -0.0688002
+0.196848 0.430422 0.880902
+0.494676 0.732132 -0.468272
+-0.0783572 -0.0546994 0.184841
+
+-0.849864 0.523013 -0.0647224
+0.188514 0.416389 0.889428
+0.492132 0.743692 -0.452469
+-0.0766204 -0.0547961 0.185247
+
+-0.853232 0.517994 -0.0606398
+0.180327 0.402118 0.897654
+0.489363 0.754973 -0.436509
+-0.0748837 -0.0548928 0.185629
+
+-0.856595 0.51288 -0.0565538
+0.172294 0.387616 0.905576
+0.486373 0.765969 -0.420396
+-0.0731469 -0.0549895 0.185987
+
+-0.859951 0.507673 -0.0524658
+0.16442 0.372887 0.913193
+0.483167 0.776674 -0.404137
+-0.0714101 -0.0550862 0.186321
+
+-0.863298 0.502371 -0.0483771
+0.156711 0.35794 0.9205
+0.479749 0.787084 -0.387736
+-0.0696734 -0.0551829 0.18663
+
+-0.866634 0.496975 -0.0442892
+0.14917 0.342781 0.927496
+0.476124 0.797193 -0.371199
+-0.0679366 -0.0552796 0.186916
+
+-0.869958 0.491485 -0.0402034
+0.141803 0.327416 0.934179
+0.472298 0.806995 -0.354533
+-0.0661998 -0.0553763 0.187177
+
+-0.873268 0.485899 -0.0361211
+0.134616 0.311853 0.940546
+0.468275 0.816486 -0.337741
+-0.0644631 -0.055473 0.187414
+
+-0.876563 0.480219 -0.0320438
+0.127612 0.296099 0.946594
+0.464061 0.82566 -0.320831
+-0.0627263 -0.0555697 0.187627
+
+-0.879841 0.474444 -0.0279728
+0.120796 0.280161 0.952323
+0.459661 0.834513 -0.303808
+-0.0609895 -0.0556664 0.187815
+
+-0.8831 0.468575 -0.0239095
+0.114173 0.264046 0.957729
+0.45508 0.843041 -0.286678
+-0.0592528 -0.0557631 0.18798
+
+-0.886339 0.46261 -0.0198553
+0.107747 0.247762 0.962811
+0.450325 0.851238 -0.269446
+-0.057516 -0.0558598 0.18812
+
+-0.889557 0.456551 -0.0158116
+0.101521 0.231316 0.967567
+0.445401 0.859101 -0.252118
+-0.0557792 -0.0559565 0.188236
+
+-0.89275 0.450398 -0.0117797
+0.0955003 0.214716 0.971996
+0.440314 0.866625 -0.234701
+-0.0540425 -0.0560532 0.188328
+
+-0.895919 0.44415 -0.00776104
+0.0896878 0.19797 0.976096
+0.43507 0.873807 -0.2172
+-0.0523057 -0.0561499 0.188396
+
+-0.89906 0.437808 -0.003757
+0.0840873 0.181086 0.979866
+0.429674 0.880643 -0.199621
+-0.0505689 -0.0562466 0.188439
+
+-0.902174 0.431373 0.000231085
+0.0787023 0.164071 0.983304
+0.424133 0.887129 -0.181971
+-0.0488322 -0.0563433 0.188458
+
+-0.905257 0.424845 0.00420184
+0.0735358 0.146934 0.986409
+0.418453 0.893262 -0.164254
+-0.0470954 -0.0564401 0.188454
+
+-0.908308 0.418223 0.00815392
+0.0685911 0.129682 0.98918
+0.412641 0.899039 -0.146478
+-0.0453586 -0.0565368 0.188425
+
+-0.911325 0.411509 0.012086
+0.0638709 0.112324 0.991617
+0.406702 0.904457 -0.128648
+-0.0436219 -0.0566335 0.188371
+
+-0.914308 0.404703 0.0159967
+0.059378 0.0948687 0.993717
+0.400643 0.909514 -0.11077
+-0.0418851 -0.0567302 0.188294
+
+-0.917254 0.397806 0.0198846
+0.055115 0.0773232 0.995482
+0.394471 0.914205 -0.0928501
+-0.0401483 -0.0568269 0.188192
+
+-0.920162 0.390818 0.0237486
+0.0510841 0.0596965 0.996909
+0.388192 0.91853 -0.074895
+-0.0384116 -0.0569236 0.188066
+
+-0.923029 0.38374 0.0275872
+0.0472876 0.0419969 0.997998
+0.381813 0.922486 -0.0569105
+-0.0366748 -0.0570203 0.187916
+
+-0.925855 0.376572 0.0313991
+0.0437275 0.0242329 0.99875
+0.37534 0.92607 -0.0389027
+-0.034938 -0.057117 0.187742
+
+-0.928638 0.369315 0.0351831
+0.0404055 0.00641299 0.999163
+0.36878 0.929282 -0.0208777
+-0.0332013 -0.0572137 0.187544
+
+-0.928479 0.369179 0.040417
+0.0393824 -0.0103414 0.999171
+0.369291 0.929301 -0.00493734
+-0.0316171 -0.057663 0.187276
+
+-0.924199 0.378901 0.0478505
+0.0411831 -0.0256866 0.998821
+0.379683 0.925081 0.00813521
+-0.0302225 -0.0585942 0.186884
+
+-0.915484 0.398226 0.0574968
+0.0454191 -0.0397053 0.998179
+0.399783 0.916428 0.0182625
+-0.029007 -0.0600023 0.186352
+
+-0.902951 0.424237 0.068574
+0.0509077 -0.0528525 0.997304
+0.426718 0.904007 0.0261262
+-0.0279528 -0.061758 0.185741
+
+-0.889597 0.449745 0.0796659
+0.0556925 -0.0663105 0.996244
+0.453338 0.890692 0.0339422
+-0.0268986 -0.0635137 0.185105
+
+-0.875443 0.474721 0.0907704
+0.0597592 -0.0800483 0.994998
+0.479613 0.876489 0.0417088
+-0.0258443 -0.0652693 0.184446
+
+-0.860512 0.499138 0.101885
+0.0630948 -0.0940341 0.993568
+0.505508 0.861405 0.0494244
+-0.0247901 -0.067025 0.183762
+
+-0.844826 0.52297 0.113008
+0.0656878 -0.108236 0.991953
+0.530993 0.845451 0.0570875
+-0.0237359 -0.0687807 0.183054
+
+-0.828411 0.546192 0.124137
+0.0675279 -0.12262 0.990154
+0.556035 0.828637 0.0646966
+-0.0226817 -0.0705363 0.182322
+
+-0.811291 0.568779 0.13527
+0.0686062 -0.137154 0.988171
+0.580604 0.810974 0.07225
+-0.0216274 -0.072292 0.181565
+
+-0.793492 0.590709 0.146404
+0.0689153 -0.151804 0.986005
+0.604666 0.792476 0.0797463
+-0.0205732 -0.0740477 0.180785
+
+-0.775041 0.611959 0.157538
+0.0684491 -0.166536 0.983657
+0.628193 0.773157 0.0871839
+-0.019519 -0.0758033 0.17998
+
+-0.755965 0.632508 0.16867
+0.067203 -0.181315 0.981126
+0.651153 0.753033 0.0945613
+-0.0184648 -0.077559 0.179151
+
+-0.736294 0.652338 0.179796
+0.0651739 -0.196107 0.978414
+0.673516 0.732118 0.101877
+-0.0174105 -0.0793147 0.178298
+
+-0.716055 0.671428 0.190916
+0.0623602 -0.210877 0.975521
+0.695253 0.710433 0.10913
+-0.0163563 -0.0810703 0.177421
+
+-0.706871 0.678795 0.198921
+0.0624046 -0.220281 0.973438
+0.704584 0.700509 0.11335
+-0.0149716 -0.0835053 0.176444
+
+-0.709076 0.675109 0.203566
+0.0657442 -0.224138 0.972337
+0.702061 0.702844 0.114546
+-0.0132197 -0.0866432 0.175382
+
+-0.720306 0.662419 0.205819
+0.0721623 -0.223546 0.972018
+0.689893 0.715003 0.11322
+-0.0112604 -0.0903053 0.174195
+
+-0.731304 0.649539 0.208073
+0.0785769 -0.222803 0.971692
+0.67751 0.726951 0.111898
+-0.00930107 -0.0939675 0.172983
+
+-0.742067 0.636474 0.210328
+0.0849848 -0.221908 0.971357
+0.664917 0.738686 0.11058
+-0.00734178 -0.0976296 0.171748
+
+-0.752591 0.623229 0.212584
+0.0913828 -0.220863 0.971014
+0.652116 0.750203 0.109267
+-0.00538249 -0.101292 0.170488
+
+-0.762875 0.609808 0.214841
+0.0977675 -0.219666 0.970664
+0.639112 0.761499 0.107958
+-0.0034232 -0.104954 0.169204
+
+-0.772913 0.596215 0.2171
+0.104136 -0.218319 0.970305
+0.625908 0.77257 0.106655
+-0.00146391 -0.108616 0.167896
+
+-0.782705 0.582455 0.219359
+0.110484 -0.216822 0.969939
+0.612508 0.783412 0.105355
+0.000495381 -0.112278 0.166563
+
+-0.792246 0.568533 0.22162
+0.116809 -0.215174 0.969565
+0.598917 0.794022 0.104061
+0.00245467 -0.11594 0.165207
+
+-0.801535 0.554453 0.223882
+0.123109 -0.213376 0.969183
+0.585137 0.804396 0.10277
+0.00441396 -0.119602 0.163826
+
+-0.810568 0.54022 0.226145
+0.129378 -0.211429 0.968793
+0.571174 0.814531 0.101485
+0.00637325 -0.123264 0.162421
+
+-0.819344 0.525838 0.228409
+0.135615 -0.209333 0.968395
+0.557032 0.824424 0.100204
+0.00833254 -0.126927 0.160992
+
+-0.827859 0.511312 0.230674
+0.141816 -0.207088 0.967989
+0.542714 0.834071 0.098928
+0.0102918 -0.130589 0.159539
+
+-0.836111 0.496647 0.23294
+0.147977 -0.204696 0.967575
+0.528225 0.84347 0.0976565
+0.0122511 -0.134251 0.158061
+
+-0.844097 0.481848 0.235207
+0.154096 -0.202157 0.967154
+0.51357 0.852617 0.0963897
+0.0142104 -0.137913 0.156559
+
+-0.851817 0.466919 0.237475
+0.160169 -0.199472 0.966725
+0.498752 0.861509 0.0951277
+0.0161697 -0.141575 0.155034
+
+-0.859267 0.451867 0.239743
+0.166194 -0.196642 0.966287
+0.483777 0.870143 0.0938704
+0.018129 -0.145237 0.153484
+
+-0.866446 0.436694 0.242013
+0.172167 -0.193667 0.965843
+0.468648 0.878516 0.0926178
+0.0200883 -0.148899 0.151909
+
+-0.873351 0.421407 0.244283
+0.178084 -0.190549 0.96539
+0.45337 0.886627 0.09137
+0.0220476 -0.152562 0.150311
+
+-0.879981 0.406011 0.246554
+0.183943 -0.187288 0.964929
+0.437948 0.894471 0.090127
+0.0240069 -0.156224 0.148688
+
+-0.886334 0.39051 0.248826
+0.189741 -0.183886 0.964461
+0.422387 0.902047 0.0888887
+0.0259662 -0.159886 0.147041
+
+-0.892408 0.374909 0.251099
+0.195474 -0.180344 0.963984
+0.406691 0.909351 0.0876553
+0.0279254 -0.163548 0.14537
+
+-0.898202 0.359215 0.253372
+0.20114 -0.176663 0.9635
+0.390865 0.916381 0.0864267
+0.0298847 -0.16721 0.143675
+
+-0.903715 0.34343 0.255646
+0.206735 -0.172844 0.963008
+0.374914 0.923136 0.085203
+0.031844 -0.170872 0.141956
+
+-0.91083 0.323509 0.25638
+0.211711 -0.167069 0.962947
+0.354355 0.931359 0.0836816
+0.0338208 -0.174315 0.140313
+
+-0.919276 0.299351 0.255579
+0.215946 -0.159316 0.96332
+0.329089 0.940748 0.0818114
+0.0358136 -0.177539 0.138746
+
+-0.928144 0.272222 0.253858
+0.219568 -0.150305 0.963949
+0.300565 0.950423 0.0797334
+0.0378165 -0.180633 0.13722
+
+-0.936206 0.244829 0.252144
+0.222854 -0.141216 0.964569
+0.271761 0.959227 0.0776466
+0.0398194 -0.183727 0.13567
+
+-0.943455 0.217195 0.250438
+0.225802 -0.132062 0.96518
+0.242705 0.967154 0.075551
+0.0418222 -0.186821 0.134095
+
+-0.949883 0.189344 0.248738
+0.228413 -0.122852 0.965782
+0.213423 0.974195 0.0734469
+0.0438251 -0.189916 0.132496
+
+-0.955484 0.161301 0.247046
+0.230684 -0.113601 0.966375
+0.183942 0.980345 0.0713341
+0.045828 -0.19301 0.130874
+
+-0.960252 0.133091 0.245361
+0.232616 -0.104318 0.966958
+0.154289 0.985599 0.0692127
+0.0478308 -0.196104 0.129226
+
+-0.964183 0.104738 0.243684
+0.234209 -0.0950166 0.967532
+0.124491 0.98995 0.0670828
+0.0498337 -0.199198 0.127555
+
+-0.967271 0.0762679 0.242014
+0.235462 -0.0857079 0.968097
+0.0945771 0.993397 0.0649445
+0.0518366 -0.202292 0.12586
+
+-0.969513 0.0477053 0.240351
+0.236378 -0.0764036 0.968653
+0.0645736 0.995935 0.0627978
+0.0538394 -0.205386 0.12414
+
+-0.970565 0.0262406 0.239405
+0.237076 -0.0709322 0.968898
+0.042406 0.997136 0.0626233
+0.0557031 -0.208159 0.122233
+
+-0.970826 0.0128127 0.239444
+0.238005 -0.0699991 0.968738
+0.029173 0.997465 0.0649075
+0.0573994 -0.210539 0.120094
+
+-0.970533 0.00965439 0.240775
+0.239408 -0.0749041 0.968025
+0.0273807 0.997144 0.0703855
+0.0588808 -0.21241 0.117683
+
+-0.969791 0.0166851 0.243367
+0.241121 -0.0856411 0.966709
+0.0369718 0.996186 0.0790308
+0.0601482 -0.213771 0.114996
+
+-0.968538 0.0313436 0.246885
+0.242684 -0.1008 0.964854
+0.0551281 0.994413 0.0900224
+0.061248 -0.214743 0.112071
+
+-0.966618 0.0514627 0.251001
+0.243599 -0.119118 0.962533
+0.0794333 0.991546 0.102605
+0.062224 -0.215443 0.108968
+
+-0.967215 0.0497953 0.249029
+0.240993 -0.129357 0.961868
+0.0801103 0.990347 0.113116
+0.0633086 -0.215282 0.106378
+
+-0.970538 0.022965 0.239853
+0.23496 -0.130368 0.963223
+0.0533896 0.9912 0.121131
+0.0644592 -0.214128 0.104394
+
+-0.973352 -0.00902488 0.22914
+0.228352 -0.129757 0.964893
+0.0210244 0.991505 0.12836
+0.0656721 -0.212782 0.102521
+
+-0.975001 -0.0411024 0.218364
+0.221906 -0.129643 0.966411
+-0.0114124 0.990708 0.135523
+0.0668849 -0.211437 0.100625
+
+-0.975485 -0.0732229 0.207528
+0.215647 -0.130017 0.967777
+-0.0438813 0.988804 0.14262
+0.0680978 -0.210092 0.0987047
+
+-0.974802 -0.105342 0.196632
+0.209602 -0.130866 0.96899
+-0.0763424 0.985788 0.149649
+0.0693107 -0.208747 0.09676
+
+-0.972954 -0.137414 0.18568
+0.203794 -0.132178 0.97005
+-0.108755 0.981655 0.156608
+0.0705235 -0.207402 0.0947912
+
+-0.970064 -0.168457 0.174922
+0.198434 -0.134605 0.970827
+-0.139997 0.976475 0.164004
+0.0717013 -0.20598 0.0927488
+
+-0.966323 -0.1979 0.164485
+0.193681 -0.138471 0.971243
+-0.169433 0.970392 0.172138
+0.0728298 -0.204439 0.0906146
+
+-0.96189 -0.225708 0.154346
+0.189576 -0.143708 0.971292
+-0.197048 0.963537 0.18102
+0.0739105 -0.202778 0.0883875
+
+-0.956582 -0.25332 0.144151
+0.185869 -0.14923 0.971176
+-0.224507 0.955803 0.189835
+0.0749913 -0.201117 0.0861361
+
+-0.95111 -0.277612 0.135354
+0.183285 -0.154601 0.970827
+-0.248588 0.948172 0.197925
+0.0757862 -0.1997 0.0838478
+
+-0.946434 -0.296106 0.128777
+0.181978 -0.159689 0.970249
+-0.266733 0.941712 0.20502
+0.0759278 -0.19868 0.081525
+
+-0.942826 -0.308999 0.124898
+0.182178 -0.163995 0.969493
+-0.27909 0.936817 0.210911
+0.075365 -0.198142 0.0791609
+
+-0.940623 -0.316011 0.123958
+0.183863 -0.167336 0.968604
+-0.285347 0.933882 0.215503
+0.0739933 -0.198139 0.0767646
+
+-0.942395 -0.31023 0.1251
+0.183964 -0.168321 0.968414
+-0.279374 0.935642 0.215696
+0.0721486 -0.198356 0.0747142
+
+-0.948261 -0.290716 0.127614
+0.181481 -0.166517 0.969194
+-0.260511 0.942208 0.210661
+0.0699926 -0.198635 0.0730666
+
+-0.95734 -0.257535 0.13106
+0.176507 -0.162059 0.970867
+-0.228793 0.952582 0.200602
+0.0677218 -0.198886 0.0717877
+
+-0.966577 -0.218223 0.134567
+0.17079 -0.156617 0.972781
+-0.191208 0.96325 0.188653
+0.0653713 -0.199108 0.0706184
+
+-0.97421 -0.178535 0.137985
+0.165699 -0.15096 0.974554
+-0.153162 0.972284 0.17665
+0.0630208 -0.199329 0.0694248
+
+-0.980223 -0.138538 0.141314
+0.161243 -0.145128 0.976186
+-0.11473 0.979666 0.164596
+0.0606703 -0.19955 0.0682071
+
+-0.984602 -0.0982978 0.144554
+0.15743 -0.139162 0.977676
+-0.0759871 0.985379 0.152494
+0.0583198 -0.199771 0.0669651
+
+-0.987337 -0.0578816 0.147703
+0.154262 -0.133101 0.979024
+-0.037008 0.989411 0.140345
+0.0559693 -0.199992 0.065699
+
+-0.988418 -0.0173573 0.150761
+0.151742 -0.126988 0.980229
+0.0021308 0.991752 0.128151
+0.0536187 -0.200213 0.0644087
+
+-0.987841 0.0232069 0.153728
+0.149869 -0.120863 0.981291
+0.0413528 0.992398 0.115916
+0.0512682 -0.200435 0.0630942
+
+-0.985603 0.0637425 0.156602
+0.148641 -0.114767 0.982209
+0.0805813 0.991345 0.10364
+0.0489177 -0.200656 0.0617556
+
+-0.981704 0.104181 0.159385
+0.148052 -0.108741 0.982983
+0.11974 0.988596 0.0913269
+0.0465672 -0.200877 0.0603927
+
+-0.976148 0.144453 0.162074
+0.148097 -0.102824 0.983613
+0.158751 0.984155 0.0789781
+0.0442167 -0.201098 0.0590057
+
+-0.971191 0.175032 0.161714
+0.147024 -0.0939496 0.984661
+0.18754 0.98007 0.065509
+0.0419028 -0.200894 0.0578148
+
+-0.968846 0.191523 0.157024
+0.1439 -0.080699 0.986296
+0.20157 0.978165 0.0506248
+0.039552 -0.200057 0.0568944
+
+-0.96946 0.195321 0.148316
+0.138438 -0.0633685 0.988342
+0.202443 0.97869 0.0343934
+0.0372455 -0.198663 0.0562264
+
+-0.97002 0.198964 0.139554
+0.133001 -0.0459936 0.990048
+0.203403 0.978927 0.0181522
+0.034939 -0.197269 0.0555341
+
+-0.970526 0.202452 0.13074
+0.127592 -0.0285803 0.991415
+0.20445 0.978875 0.00190659
+0.0326325 -0.195875 0.0548177
+
+-0.970979 0.205783 0.121878
+0.122212 -0.0111346 0.992442
+0.205584 0.978534 -0.0143377
+0.030326 -0.194481 0.0540771
+
+-0.971378 0.208956 0.11297
+0.116863 0.00633735 0.993128
+0.206804 0.977905 -0.0305752
+0.0280194 -0.193087 0.0533123
+
+-0.971724 0.211971 0.104021
+0.111547 0.0238294 0.993473
+0.208108 0.976985 -0.0468002
+0.0257129 -0.191693 0.0525233
+
+-0.972018 0.214826 0.0950317
+0.106265 0.0413353 0.993478
+0.209497 0.975777 -0.0630073
+0.0234064 -0.190299 0.0517101
+
+-0.972259 0.217522 0.0860066
+0.10102 0.0588492 0.993142
+0.210969 0.97428 -0.0791908
+0.0210999 -0.188905 0.0508728
+
+-0.972447 0.220058 0.0769485
+0.0958133 0.0763647 0.992466
+0.212524 0.972493 -0.0953451
+0.0187933 -0.187511 0.0500113
+
+-0.972584 0.222432 0.0678605
+0.0906464 0.0938759 0.991449
+0.21416 0.970418 -0.111465
+0.0164868 -0.186116 0.0491255
+
+-0.972668 0.224646 0.0587457
+0.0855213 0.111376 0.990092
+0.215877 0.968055 -0.127544
+0.0141803 -0.184722 0.0482156
+
+-0.972701 0.226697 0.0496072
+0.0804397 0.12886 0.988395
+0.217674 0.965403 -0.143578
+0.0118738 -0.183328 0.0472815
+
+-0.972683 0.228586 0.0404482
+0.0754034 0.146322 0.986359
+0.21955 0.962465 -0.159561
+0.00956725 -0.181934 0.0463233
+
+-0.972614 0.230313 0.0312718
+0.070414 0.163754 0.983985
+0.221504 0.95924 -0.175486
+0.00726072 -0.18054 0.0453408
+
+-0.972494 0.231877 0.0220812
+0.0654733 0.181151 0.981273
+0.223535 0.955729 -0.19135
+0.0049542 -0.179146 0.0443342
+
+-0.972325 0.233278 0.0128795
+0.060583 0.198507 0.978225
+0.225642 0.951933 -0.207146
+0.00264768 -0.177752 0.0433033
+
+-0.97057 0.24067 0.00843772
+0.0608034 0.211003 0.975592
+0.233016 0.947394 -0.219427
+5.07454e-05 -0.175651 0.0420046
+
+-0.967123 0.254157 0.00876584
+0.0662905 0.218672 0.973544
+0.245516 0.942118 -0.228331
+-0.0028259 -0.172842 0.0404392
+
+-0.962892 0.269603 0.0123942
+0.0750216 0.223262 0.971867
+0.259251 0.936733 -0.235203
+-0.00584945 -0.169559 0.0386868
+
+-0.958394 0.285001 0.016006
+0.083893 0.22763 0.970127
+0.272843 0.931106 -0.242069
+-0.008873 -0.166276 0.0369102
+
+-0.953629 0.300346 0.0196009
+0.0928997 0.231772 0.968324
+0.286289 0.925243 -0.248927
+-0.0118966 -0.162993 0.0351095
+
+-0.948598 0.315634 0.0231787
+0.102036 0.235686 0.966458
+0.299584 0.919145 -0.255777
+-0.0149201 -0.15971 0.0332845
+
+-0.943301 0.330859 0.0267391
+0.111298 0.239368 0.964529
+0.312722 0.912817 -0.26262
+-0.0179437 -0.156428 0.0314354
+
+-0.93774 0.346017 0.0302819
+0.120679 0.242814 0.962537
+0.325701 0.906264 -0.269454
+-0.0209672 -0.153145 0.0295621
+
+-0.931913 0.361102 0.0338068
+0.130174 0.246023 0.960483
+0.338515 0.899487 -0.276278
+-0.0239908 -0.149862 0.0276646
+
+-0.925823 0.376111 0.0373137
+0.139777 0.248992 0.958366
+0.351161 0.892493 -0.283094
+-0.0270143 -0.146579 0.0257429
+
+-0.91947 0.391037 0.0408023
+0.149483 0.251716 0.956187
+0.363634 0.885285 -0.289899
+-0.0300379 -0.143296 0.023797
+
+-0.912855 0.405876 0.0442722
+0.159286 0.254195 0.953946
+0.37593 0.877866 -0.296694
+-0.0330614 -0.140014 0.021827
+
+-0.905979 0.420623 0.0477234
+0.169181 0.256426 0.951643
+0.388046 0.870242 -0.303478
+-0.036085 -0.136731 0.0198327
+
+-0.895509 0.442244 0.0498384
+0.179318 0.256059 0.949884
+0.407318 0.859566 -0.308605
+-0.0389347 -0.133765 0.017916
+
+-0.880566 0.471231 0.05044
+0.189535 0.252614 0.948822
+0.434373 0.84506 -0.311758
+-0.0416017 -0.131163 0.016101
+
+-0.859985 0.507918 0.0494485
+0.199617 0.245633 0.948587
+0.469658 0.825642 -0.31263
+-0.0440712 -0.128967 0.0144001
+
+-0.833944 0.549821 0.0472654
+0.209287 0.235858 0.948984
+0.510623 0.801291 -0.311763
+-0.0464191 -0.127057 0.0128131
+
+-0.80586 0.590387 0.0450911
+0.218481 0.22571 0.949379
+0.550324 0.774918 -0.310879
+-0.0487669 -0.125147 0.0112019
+
+-0.775801 0.629515 0.0429256
+0.227184 0.215213 0.949774
+0.588659 0.746588 -0.309978
+-0.0511148 -0.123237 0.00956646
+
+-0.743843 0.66711 0.0407692
+0.235384 0.204391 0.950168
+0.625534 0.716372 -0.309061
+-0.0534626 -0.121327 0.00790687
+
+-0.710062 0.70308 0.0386219
+0.243069 0.193266 0.950561
+0.660855 0.684344 -0.308128
+-0.0558105 -0.119417 0.00622309
+
+-0.674541 0.737335 0.0364837
+0.250229 0.181865 0.950952
+0.694535 0.650586 -0.307178
+-0.0581584 -0.117506 0.00451513
+
+-0.637369 0.769793 0.0343549
+0.256855 0.170212 0.951343
+0.726489 0.615181 -0.306213
+-0.0605062 -0.115596 0.00278298
+
+-0.598635 0.800373 0.0322356
+0.262937 0.158331 0.951733
+0.756637 0.578216 -0.30523
+-0.0628541 -0.113686 0.00102665
+
+-0.558435 0.829001 0.0301257
+0.26847 0.146248 0.952121
+0.784904 0.539786 -0.304232
+-0.065202 -0.111776 -0.000753867
+
+-0.516867 0.855607 0.0280255
+0.273447 0.133989 0.952509
+0.811218 0.499984 -0.303218
+-0.0675498 -0.109866 -0.00255857
+
+-0.474034 0.880125 0.025935
+0.277864 0.121578 0.952896
+0.835514 0.458911 -0.302187
+-0.0698977 -0.107956 -0.00438746
+
+-0.43004 0.902495 0.0238543
+0.281717 0.109042 0.953281
+0.85773 0.416669 -0.301141
+-0.0722456 -0.106045 -0.00624054
+
+-0.384992 0.922663 0.0217835
+0.285004 0.0964059 0.953666
+0.877812 0.373362 -0.300078
+-0.0745934 -0.104135 -0.0081178
+
+-0.340357 0.940104 0.0190091
+0.287345 0.0847395 0.954071
+0.895315 0.330187 -0.298976
+-0.0767607 -0.102296 -0.0100135
+
+-0.299842 0.953887 0.0139433
+0.28799 0.0765726 0.954567
+0.909482 0.290234 -0.29767
+-0.0784753 -0.100712 -0.0119413
+
+-0.264263 0.964429 0.00650153
+0.287353 0.0722991 0.955092
+0.920648 0.254264 -0.296237
+-0.0796638 -0.0993982 -0.0139041
+
+-0.241834 0.970314 -0.00268097
+0.284062 0.0734388 0.955989
+0.927807 0.230429 -0.293389
+-0.0803765 -0.098718 -0.0158427
+
+-0.238306 0.971106 -0.0127552
+0.277127 0.0805818 0.957448
+0.930812 0.224631 -0.288323
+-0.0806789 -0.0989003 -0.0176681
+
+-0.253754 0.966988 -0.0232948
+0.266271 0.092986 0.959403
+0.929897 0.237249 -0.281077
+-0.0806285 -0.0999462 -0.0193827
+
+-0.285709 0.957721 -0.033771
+0.251425 0.108918 0.961729
+0.924746 0.266284 -0.271914
+-0.0803722 -0.101729 -0.0209924
+
+-0.323835 0.945108 -0.0436087
+0.234248 0.12475 0.96414
+0.916656 0.302006 -0.261788
+-0.0801389 -0.103792 -0.0225622
+
+-0.361309 0.930911 -0.0534878
+0.216215 0.139442 0.966337
+0.907032 0.337582 -0.251658
+-0.0799056 -0.105856 -0.0241563
+
+-0.398065 0.915163 -0.0634059
+0.197389 0.152946 0.968321
+0.895869 0.372939 -0.241526
+-0.0796723 -0.107919 -0.0257745
+
+-0.434035 0.897904 -0.0733607
+0.177837 0.165223 0.97009
+0.883169 0.408007 -0.231393
+-0.0794389 -0.109983 -0.0274169
+
+-0.469155 0.879174 -0.08335
+0.157628 0.176232 0.971646
+0.868935 0.442714 -0.221262
+-0.0792056 -0.112046 -0.0290835
+
+-0.50336 0.859017 -0.0933715
+0.136833 0.18594 0.972987
+0.853174 0.476986 -0.211136
+-0.0789723 -0.11411 -0.0307743
+
+-0.536591 0.83748 -0.103423
+0.115524 0.194315 0.974113
+0.835897 0.510753 -0.201017
+-0.0787389 -0.116173 -0.0324893
+
+-0.568791 0.814613 -0.113502
+0.0937768 0.20133 0.975024
+0.817119 0.543941 -0.190907
+-0.0785056 -0.118237 -0.0342284
+
+-0.599902 0.790468 -0.123606
+0.0716664 0.206963 0.97572
+0.796857 0.576478 -0.180808
+-0.0782723 -0.1203 -0.0359918
+
+-0.629873 0.765098 -0.133733
+0.04927 0.211194 0.976202
+0.775134 0.608294 -0.170722
+-0.0780389 -0.122364 -0.0377793
+
+-0.658654 0.738562 -0.143881
+0.026666 0.214009 0.976468
+0.751973 0.639318 -0.160652
+-0.0778056 -0.124428 -0.039591
+
+-0.686197 0.710917 -0.154048
+0.0039332 0.215397 0.976519
+0.727405 0.669478 -0.150601
+-0.0775723 -0.126491 -0.0414269
+
+-0.712337 0.682596 -0.16321
+-0.0180745 0.214628 0.976529
+0.701604 0.698568 -0.14055
+-0.0772701 -0.128375 -0.0433055
+
+-0.737245 0.653795 -0.170359
+-0.0385126 0.211073 0.976711
+0.674527 0.726637 -0.130433
+-0.0767802 -0.129875 -0.0452488
+
+-0.762541 0.622765 -0.175203
+-0.0574042 0.204616 0.977158
+0.644389 0.75518 -0.120279
+-0.0760484 -0.130931 -0.0473149
+
+-0.788856 0.588636 -0.176678
+-0.0739573 0.194466 0.978117
+0.610112 0.78466 -0.109872
+-0.0751018 -0.131395 -0.0495273
+
+-0.815816 0.551194 -0.175011
+-0.0879464 0.180857 0.979569
+0.571585 0.81454 -0.0990707
+-0.0739541 -0.131306 -0.0518686
+
+-0.84099 0.512512 -0.173397
+-0.100849 0.166378 0.980891
+0.531568 0.842407 -0.0882357
+-0.0728064 -0.131216 -0.054234
+
+-0.86432 0.472676 -0.171835
+-0.112614 0.1511 0.982083
+0.490172 0.868185 -0.0773685
+-0.0716587 -0.131126 -0.0566237
+
+-0.885754 0.431775 -0.170325
+-0.123196 0.135099 0.983143
+0.447507 0.891806 -0.0664709
+-0.070511 -0.131036 -0.0590375
+
+-0.905242 0.389899 -0.168868
+-0.132555 0.118452 0.984072
+0.403692 0.913207 -0.0555447
+-0.0693633 -0.130946 -0.0614755
+
+-0.922739 0.347142 -0.167464
+-0.140653 0.10124 0.984869
+0.358844 0.932332 -0.0445916
+-0.0682156 -0.130856 -0.0639377
+
+-0.938207 0.3036 -0.166113
+-0.147458 0.0835442 0.985534
+0.313086 0.94913 -0.0336135
+-0.0670679 -0.130766 -0.0664241
+
+-0.951611 0.25937 -0.164816
+-0.152945 0.0654484 0.986065
+0.266542 0.963558 -0.0226122
+-0.0659202 -0.130676 -0.0689347
+
+-0.962919 0.21455 -0.163572
+-0.157091 0.0470375 0.986463
+0.219339 0.97558 -0.0115894
+-0.0647725 -0.130586 -0.0714694
+
+-0.972106 0.16924 -0.162382
+-0.159881 0.0283975 0.986728
+0.171606 0.985166 -0.00054709
+-0.0636248 -0.130496 -0.0740284
+
+-0.979151 0.123543 -0.161246
+-0.161302 0.00961533 0.986858
+0.12347 0.992293 0.0105129
+-0.0624772 -0.130406 -0.0766115
+
+-0.984039 0.0775601 -0.160164
+-0.161349 -0.00922168 0.986854
+0.0750636 0.996945 0.0215887
+-0.0613295 -0.130316 -0.0792188
+
+-0.986757 0.0313939 -0.159136
+-0.160021 -0.028026 0.986716
+0.0265169 0.999114 0.0326785
+-0.0601818 -0.130226 -0.0818503
+
+-0.987301 -0.0148523 -0.158163
+-0.157322 -0.0467101 0.986442
+-0.0220387 0.998798 0.0437803
+-0.0590341 -0.130136 -0.084506
+
+-0.985669 -0.0610751 -0.157244
+-0.153263 -0.0651869 0.986033
+-0.0704723 0.996002 0.0548922
+-0.0578864 -0.130046 -0.0871858
+
+-0.981865 -0.107171 -0.156379
+-0.147857 -0.0833702 0.985489
+-0.118654 0.990739 0.0660124
+-0.0567387 -0.129956 -0.0898899
+
+-0.977573 -0.144507 -0.153194
+-0.139807 -0.0986966 0.985248
+-0.157495 0.984569 0.07628
+-0.0557854 -0.130291 -0.0927365
+
+-0.976365 -0.156564 -0.148993
+-0.133317 -0.106311 0.985355
+-0.17011 0.98193 0.0829252
+-0.0545726 -0.131084 -0.0956326
+
+-0.979501 -0.140795 -0.144062
+-0.129901 -0.105107 0.98594
+-0.153957 0.984444 0.0846629
+-0.0530278 -0.132182 -0.0984333
+
+-0.984539 -0.107019 -0.138671
+-0.12852 -0.0965616 0.986995
+-0.119018 0.989557 0.0813145
+-0.0513939 -0.13307 -0.101023
+
+-0.988914 -0.0629051 -0.134505
+-0.129073 -0.0836618 0.9881
+-0.0734095 0.994507 0.074615
+-0.0495523 -0.1335 -0.103401
+
+-0.991285 -0.014173 -0.130973
+-0.129706 -0.0689191 0.989154
+-0.0230458 0.997522 0.0664801
+-0.0476137 -0.13373 -0.105701
+
+-0.991234 0.0346574 -0.12749
+-0.129246 -0.0543043 0.990124
+0.0273919 0.997923 0.0583076
+-0.0456752 -0.13396 -0.108026
+
+-0.988758 0.083465 -0.124058
+-0.127707 -0.0398876 0.99101
+0.0777663 0.995712 0.0500983
+-0.0437366 -0.13419 -0.110375
+
+-0.98386 0.132128 -0.120675
+-0.125107 -0.0257385 0.991809
+0.12794 0.990898 0.0418532
+-0.041798 -0.13442 -0.112748
+
+-0.976545 0.180527 -0.117344
+-0.121468 -0.011925 0.992524
+0.177778 0.983498 0.0335736
+-0.0398594 -0.13465 -0.115145
+
+-0.96683 0.228539 -0.114064
+-0.116818 0.00148639 0.993152
+0.227143 0.973534 0.0252603
+-0.0379208 -0.13488 -0.117566
+
+-0.954733 0.276044 -0.110835
+-0.111186 0.014431 0.993695
+0.275903 0.961037 0.0169144
+-0.0359822 -0.13511 -0.120012
+
+-0.940281 0.322925 -0.107659
+-0.104607 0.0268463 0.994151
+0.323927 0.946044 0.00853703
+-0.0340436 -0.13534 -0.122482
+
+-0.923507 0.369063 -0.104535
+-0.0971184 0.0386717 0.994521
+0.371084 0.928599 0.000129252
+-0.032105 -0.13557 -0.124976
+
+-0.904448 0.414342 -0.101463
+-0.088763 0.0498494 0.994805
+0.417247 0.908755 -0.00830787
+-0.0301664 -0.135801 -0.127494
+
+-0.883148 0.458649 -0.0984454
+-0.0795855 0.060324 0.995001
+0.462295 0.886568 -0.0167732
+-0.0282278 -0.136031 -0.130036
+
+-0.859656 0.501871 -0.0954811
+-0.0696343 0.0700433 0.995111
+0.506105 0.862102 -0.0252657
+-0.0262892 -0.136261 -0.132603
+
+-0.834029 0.543899 -0.0925707
+-0.0589609 0.0789578 0.995133
+0.548561 0.835428 -0.0337843
+-0.0243506 -0.136491 -0.135194
+
+-0.806327 0.584627 -0.0897147
+-0.0476198 0.0870214 0.995068
+0.589551 0.806622 -0.0423278
+-0.0224121 -0.136721 -0.137808
+
+-0.776615 0.623952 -0.0869133
+-0.0356683 0.0941913 0.994915
+0.628965 0.775766 -0.0508951
+-0.0204735 -0.136951 -0.140447
+
+-0.744965 0.661773 -0.084167
+-0.023166 0.100429 0.994675
+0.666701 0.742947 -0.0594851
+-0.0185349 -0.137181 -0.143111
+
+-0.711453 0.697994 -0.081476
+-0.0101751 0.105697 0.994346
+0.70266 0.70826 -0.0680966
+-0.0165963 -0.137411 -0.145798
+
+-0.676161 0.732524 -0.0788407
+0.0032402 0.109966 0.99393
+0.736747 0.671801 -0.0767285
+-0.0146577 -0.137641 -0.14851
+
+-0.639173 0.765273 -0.0762614
+0.0170139 0.113208 0.993426
+0.768875 0.633673 -0.0853796
+-0.0127191 -0.137871 -0.151246
+
+-0.60058 0.796157 -0.0737384
+0.0310782 0.115398 0.992833
+0.79896 0.593984 -0.0940488
+-0.0107805 -0.138101 -0.154006
+
+-0.560477 0.825098 -0.071272
+0.0453639 0.116517 0.992152
+0.826927 0.552845 -0.102735
+-0.00884191 -0.138332 -0.15679
+
+-0.518961 0.85202 -0.0688626
+0.0598008 0.116551 0.991383
+0.852704 0.510371 -0.111437
+-0.00690332 -0.138562 -0.159598
+
+-0.476135 0.876854 -0.0665104
+0.0743176 0.115487 0.990525
+0.876226 0.46668 -0.120153
+-0.00496473 -0.138792 -0.162431
+
+-0.432103 0.899535 -0.0642157
+0.0888423 0.11332 0.989578
+0.897437 0.421895 -0.128883
+-0.00302614 -0.139022 -0.165288
+
+-0.386975 0.920005 -0.0619787
+0.103303 0.110048 0.988543
+0.916285 0.376139 -0.137625
+-0.00108754 -0.139252 -0.168168
+
+-0.340862 0.938209 -0.0597998
+0.117626 0.105671 0.98742
+0.932726 0.32954 -0.146377
+0.000851048 -0.139482 -0.171074
+
+-0.301223 0.951905 -0.0560577
+0.129424 0.099058 0.986629
+0.94473 0.28994 -0.153038
+0.00262781 -0.140104 -0.173928
+
+-0.269768 0.961622 -0.0500891
+0.1378 0.0900353 0.986359
+0.953014 0.259186 -0.1568
+0.00417783 -0.141289 -0.176746
+
+-0.246876 0.968154 -0.0415926
+0.142487 0.0787213 0.986661
+0.958514 0.237656 -0.157383
+0.00550381 -0.143083 -0.179507
+
+-0.232165 0.972192 -0.0306764
+0.143894 0.0655197 0.987422
+0.961974 0.224831 -0.155104
+0.00660755 -0.145437 -0.182222
+
+-0.225148 0.974168 -0.0174803
+0.142423 0.0506543 0.988509
+0.963859 0.220071 -0.150149
+0.00749814 -0.148306 -0.184896
+
+-0.223334 0.974739 -0.00243456
+0.138689 0.0342486 0.989744
+0.964825 0.220705 -0.142834
+0.00821727 -0.151619 -0.187567
+
+-0.221575 0.975062 0.0126141
+0.134896 0.0178377 0.990699
+0.965768 0.221216 -0.135484
+0.0089364 -0.154931 -0.190262
+
+-0.219874 0.975136 0.0276614
+0.131045 0.00142614 0.991375
+0.966686 0.221603 -0.128101
+0.00965553 -0.158244 -0.192981
+
+-0.218232 0.974962 0.0427031
+0.127138 -0.0149813 0.991772
+0.96758 0.221865 -0.120685
+0.0103747 -0.161556 -0.195724
+
+-0.216648 0.974541 0.0577349
+0.123175 -0.0313799 0.991889
+0.968448 0.222003 -0.113241
+0.0110938 -0.164868 -0.198492
+
+-0.215126 0.973873 0.0727528
+0.119157 -0.047765 0.991726
+0.96929 0.222015 -0.105769
+0.0118129 -0.168181 -0.201284
+
+-0.213665 0.972958 0.0877523
+0.115086 -0.0641319 0.991283
+0.970104 0.221901 -0.0982712
+0.012532 -0.171493 -0.2041
+
+-0.212266 0.971797 0.102729
+0.110962 -0.0804758 0.990561
+0.970892 0.221662 -0.0907507
+0.0132512 -0.174805 -0.20694
+
+-0.210931 0.970391 0.11768
+0.106787 -0.0967922 0.989559
+0.97165 0.221296 -0.0832092
+0.0139703 -0.178118 -0.209804
+
+-0.209661 0.968741 0.132599
+0.102562 -0.113076 0.988279
+0.97238 0.220803 -0.0756487
+0.0146894 -0.18143 -0.212693
+
+-0.208456 0.966848 0.147484
+0.0982883 -0.129324 0.986719
+0.97308 0.220184 -0.0680716
+0.0154086 -0.184743 -0.215606
+
+-0.207318 0.964712 0.162329
+0.0939665 -0.145529 0.984881
+0.97375 0.219437 -0.0604798
+0.0161277 -0.188055 -0.218542
+
+-0.206247 0.962334 0.17713
+0.0895981 -0.161689 0.982766
+0.974389 0.218563 -0.0528755
+0.0168468 -0.191367 -0.221504
+
+-0.205244 0.959716 0.191885
+0.0851843 -0.177797 0.980373
+0.974997 0.217562 -0.0452609
+0.0175659 -0.19468 -0.224489
+
+-0.204311 0.956859 0.206587
+0.0807265 -0.19385 0.977704
+0.975572 0.216433 -0.0376381
+0.0182851 -0.197992 -0.227498
+
+-0.203448 0.953764 0.221233
+0.0762258 -0.209844 0.974759
+0.976114 0.215176 -0.0300093
+0.0190042 -0.201304 -0.230532
+
+-0.21053 0.948639 0.236136
+0.0756968 -0.225006 0.971413
+0.974652 0.222386 -0.0244385
+0.0196158 -0.204268 -0.233494
+
+-0.2262 0.941116 0.251265
+0.0799555 -0.239142 0.967687
+0.970794 0.238981 -0.0211536
+0.0201132 -0.206838 -0.236363
+
+-0.251182 0.93049 0.266637
+0.0899627 -0.251834 0.96358
+0.96375 0.266021 -0.0204532
+0.0204913 -0.208962 -0.239147
+
+-0.284953 0.916045 0.282247
+0.10599 -0.262538 0.959083
+0.952663 0.303209 -0.022281
+0.0207566 -0.210641 -0.241842
+
+-0.319813 0.899454 0.29783
+0.124009 -0.271898 0.954302
+0.93933 0.342132 -0.024584
+0.0210038 -0.212226 -0.24455
+
+-0.353754 0.881295 0.313333
+0.142853 -0.280157 0.949265
+0.924365 0.380567 -0.0267893
+0.021251 -0.21381 -0.247282
+
+-0.374454 0.868347 0.325204
+0.157383 -0.286112 0.945183
+0.913791 0.405109 -0.0295268
+0.021653 -0.214891 -0.250338
+
+-0.377559 0.864513 0.331763
+0.164865 -0.289797 0.942782
+0.911191 0.410652 -0.0331126
+0.0222568 -0.215229 -0.253865
+
+-0.36314 0.870321 0.332672
+0.164543 -0.291531 0.942303
+0.91709 0.396927 -0.0373382
+0.0230364 -0.214777 -0.2579
+
+-0.333717 0.883422 0.328936
+0.157585 -0.291749 0.943424
+0.929408 0.366672 -0.0418528
+0.0240052 -0.213709 -0.262327
+
+-0.297506 0.898316 0.323292
+0.148059 -0.291116 0.945161
+0.94317 0.329057 -0.0463951
+0.0250514 -0.212401 -0.266927
+
+-0.260652 0.911693 0.317611
+0.138797 -0.290178 0.946854
+0.955404 0.290883 -0.0509052
+0.0260976 -0.211093 -0.271552
+
+-0.227806 0.922332 0.312102
+0.132814 -0.288101 0.948345
+0.964606 0.25749 -0.0568679
+0.0271029 -0.209548 -0.27616
+
+-0.202454 0.929919 0.307023
+0.132125 -0.284711 0.949464
+0.970338 0.232788 -0.0652245
+0.0280361 -0.207622 -0.280762
+
+-0.184937 0.935093 0.302322
+0.136653 -0.280171 0.950174
+0.973203 0.217035 -0.0759697
+0.0288935 -0.205316 -0.285359
+
+-0.175496 0.938304 0.297972
+0.146304 -0.274451 0.950406
+0.973548 0.210387 -0.0891126
+0.0296726 -0.202631 -0.289954
+
+-0.166077 0.941406 0.293554
+0.156027 -0.268852 0.95046
+0.973691 0.203652 -0.102235
+0.0304517 -0.199945 -0.294573
+
+-0.156683 0.944399 0.289069
+0.16582 -0.263375 0.950335
+0.973629 0.196835 -0.115334
+0.0312309 -0.19726 -0.299216
+
+-0.147314 0.947285 0.284518
+0.175679 -0.258023 0.950032
+0.973363 0.189937 -0.128408
+0.03201 -0.194574 -0.303884
+
+-0.137974 0.950062 0.279901
+0.185601 -0.252796 0.949551
+0.97289 0.182963 -0.141453
+0.0327891 -0.191889 -0.308575
+
+-0.128664 0.952733 0.27522
+0.195582 -0.247697 0.948891
+0.97221 0.175916 -0.154468
+0.0335683 -0.189203 -0.313291
+
+-0.119385 0.955296 0.270475
+0.20562 -0.242728 0.948053
+0.971323 0.168798 -0.16745
+0.0343474 -0.186518 -0.318031
+
+-0.11014 0.957752 0.265668
+0.21571 -0.237889 0.947036
+0.970226 0.161614 -0.180396
+0.0351265 -0.183832 -0.322795
+
+-0.10093 0.960103 0.260799
+0.22585 -0.233183 0.945842
+0.968919 0.154366 -0.193304
+0.0359057 -0.181147 -0.327583
+
+-0.091758 0.962347 0.255869
+0.236035 -0.228611 0.944471
+0.967403 0.147057 -0.206171
+0.0366848 -0.178461 -0.332395
+
+-0.0826248 0.964486 0.250879
+0.246263 -0.224173 0.942921
+0.965675 0.139691 -0.218995
+0.0374639 -0.175776 -0.337232
+
+-0.0735325 0.96652 0.245831
+0.25653 -0.219873 0.941195
+0.963735 0.132271 -0.231774
+0.0382431 -0.17309 -0.342093
+
+-0.0644828 0.968449 0.240724
+0.266833 -0.21571 0.939292
+0.961583 0.124801 -0.244504
+0.0390222 -0.170405 -0.346978
+
+-0.0554776 0.970275 0.235561
+0.277167 -0.211686 0.937213
+0.959219 0.117284 -0.257184
+0.0398013 -0.167719 -0.351887
+
+-0.0465186 0.971997 0.230341
+0.28753 -0.207803 0.934957
+0.956641 0.109723 -0.269811
+0.0405805 -0.165034 -0.35682
+
+-0.0376076 0.973617 0.225067
+0.297917 -0.204061 0.932526
+0.953851 0.102121 -0.282383
+0.0413596 -0.162348 -0.361778
+
+-0.0287462 0.975135 0.219739
+0.308326 -0.200461 0.92992
+0.950846 0.0944828 -0.294897
+0.0421387 -0.159663 -0.366759
+
+-0.0199362 0.976552 0.214358
+0.318752 -0.197004 0.927139
+0.947628 0.0868106 -0.307351
+0.0429179 -0.156977 -0.371765
+
+-0.0100919 0.977739 0.209582
+0.328226 -0.194741 0.924307
+0.944545 0.0781183 -0.318954
+0.0436216 -0.154466 -0.376831
+
+0.00335289 0.978403 0.206679
+0.334769 -0.195852 0.921722
+0.942294 0.0660991 -0.328196
+0.0441257 -0.152464 -0.382012
+
+0.0206299 0.978401 0.205682
+0.33829 -0.200423 0.919451
+0.940816 0.050612 -0.335118
+0.0444395 -0.150972 -0.387296
+
+0.0426871 0.977489 0.206625
+0.338461 -0.208733 0.917537
+0.940012 0.0307676 -0.339752
+0.0445532 -0.150014 -0.392709
+
+0.0693838 0.975332 0.209556
+0.335112 -0.220643 0.915978
+0.93962 0.00667072 -0.342155
+0.0444602 -0.149587 -0.398247
+
+0.0999077 0.971701 0.214045
+0.328676 -0.235275 0.914668
+0.939143 -0.0210311 -0.342881
+0.0441981 -0.149573 -0.403887
+
+0.133505 0.966343 0.219902
+0.319342 -0.252 0.913519
+0.938188 -0.0517352 -0.342237
+0.0437911 -0.149907 -0.40962
+
+0.166863 0.959789 0.225749
+0.309266 -0.268353 0.912327
+0.936222 -0.0824172 -0.341608
+0.0433841 -0.150241 -0.415377
+
+0.199939 0.952047 0.231585
+0.298463 -0.284303 0.911094
+0.933244 -0.113043 -0.340994
+0.0429771 -0.150575 -0.421158
+
+0.232689 0.943129 0.23741
+0.286948 -0.299821 0.909818
+0.929256 -0.14358 -0.340394
+0.0425701 -0.150909 -0.426964
+
+0.26507 0.933049 0.243224
+0.274738 -0.314875 0.9085
+0.92426 -0.173993 -0.339808
+0.0421631 -0.151243 -0.432794
+
+0.297041 0.92182 0.249027
+0.261852 -0.329438 0.907141
+0.91826 -0.20425 -0.339237
+0.0417561 -0.151577 -0.438648
+
+0.328559 0.90946 0.254817
+0.248308 -0.343481 0.90574
+0.911259 -0.234316 -0.33868
+0.0413491 -0.151911 -0.444526
+
+0.359584 0.895985 0.260595
+0.234128 -0.356975 0.904297
+0.903263 -0.264158 -0.338138
+0.0409421 -0.152245 -0.450428
+
+0.390074 0.881416 0.266361
+0.219334 -0.369894 0.902813
+0.894279 -0.293742 -0.33761
+0.0405351 -0.152579 -0.456354
+
+0.419992 0.865772 0.272114
+0.203947 -0.382213 0.901288
+0.884315 -0.323036 -0.337098
+0.0401281 -0.152913 -0.462305
+
+0.449296 0.849076 0.277854
+0.187992 -0.393905 0.899721
+0.873379 -0.352007 -0.3366
+0.0397211 -0.153247 -0.46828
+
+0.477951 0.831352 0.28358
+0.171494 -0.404946 0.898114
+0.861483 -0.380622 -0.336116
+0.0393141 -0.153581 -0.474279
+
+0.505917 0.812624 0.289292
+0.154479 -0.415314 0.896466
+0.848637 -0.408848 -0.335648
+0.0389071 -0.153915 -0.480302
+
+0.53316 0.792919 0.294991
+0.136973 -0.424986 0.894777
+0.834852 -0.436653 -0.335194
+0.0385001 -0.154249 -0.486349
+
+0.559644 0.772265 0.300675
+0.119005 -0.433941 0.893047
+0.820144 -0.464007 -0.334756
+0.0380931 -0.154583 -0.492421
+
+0.585335 0.75069 0.306344
+0.100602 -0.442158 0.891277
+0.804526 -0.490877 -0.334332
+0.0376861 -0.154917 -0.498517
+
+0.6102 0.728226 0.311999
+0.0817953 -0.449619 0.889468
+0.788014 -0.517233 -0.333923
+0.0372791 -0.155251 -0.504637
+
+0.634207 0.704903 0.317638
+0.0626139 -0.456306 0.887617
+0.770624 -0.543045 -0.333529
+0.0368721 -0.155585 -0.510781
+
+0.657325 0.680754 0.323261
+0.0430894 -0.462201 0.885727
+0.752374 -0.568282 -0.33315
+0.0364651 -0.155918 -0.516949
+
+0.679526 0.655812 0.328869
+0.0232533 -0.467291 0.883798
+0.733283 -0.592916 -0.332786
+0.0360581 -0.156252 -0.523141
+
+0.70078 0.630114 0.334461
+0.00313824 -0.47156 0.881828
+0.713371 -0.616918 -0.332437
+0.0356511 -0.156586 -0.529358
+
+0.721061 0.603694 0.340036
+-0.0172229 -0.474996 0.87982
+0.692658 -0.64026 -0.332103
+0.0352441 -0.15692 -0.535599
+
+0.740344 0.57659 0.345595
+-0.0377965 -0.477586 0.877772
+0.671165 -0.662915 -0.331785
+0.0348371 -0.157254 -0.541864
+
+0.758604 0.548838 0.351137
+-0.0585484 -0.479321 0.875684
+0.648917 -0.684856 -0.331481
+0.0344301 -0.157588 -0.548153
+
+0.775818 0.520479 0.356661
+-0.0794442 -0.480192 0.873558
+0.625935 -0.706057 -0.331193
+0.0340231 -0.157922 -0.554467
+
+0.791967 0.491551 0.362168
+-0.100449 -0.480191 0.871393
+0.602245 -0.726494 -0.33092
+0.0336162 -0.158256 -0.560804
+
+0.807029 0.462095 0.367657
+-0.121527 -0.479312 0.86919
+0.577871 -0.746142 -0.330662
+0.0332092 -0.15859 -0.567166
+
+0.820987 0.432152 0.373128
+-0.142643 -0.47755 0.866948
+0.552841 -0.764977 -0.330419
+0.0328022 -0.158924 -0.573552
+
+0.833825 0.401763 0.378581
+-0.163762 -0.474902 0.864668
+0.52718 -0.782978 -0.330192
+0.0323952 -0.159258 -0.579962
+
+0.845526 0.37097 0.384015
+-0.184846 -0.471366 0.862349
+0.500917 -0.800122 -0.32998
+0.0319882 -0.159592 -0.586396
+
+0.856078 0.339817 0.38943
+-0.20586 -0.466941 0.859993
+0.474081 -0.816389 -0.329783
+0.0315812 -0.159926 -0.592855
+
+0.865468 0.308346 0.394825
+-0.226768 -0.461628 0.857599
+0.4467 -0.831759 -0.329601
+0.0311742 -0.16026 -0.599338
+
+0.873688 0.276601 0.400202
+-0.247533 -0.45543 0.855167
+0.418804 -0.846212 -0.329435
+0.0307672 -0.160594 -0.605845
+
+0.880727 0.244627 0.405558
+-0.26812 -0.44835 0.852698
+0.390425 -0.859733 -0.329285
+0.0303602 -0.160928 -0.612376
+
+0.886579 0.212467 0.410895
+-0.288491 -0.440394 0.850192
+0.361593 -0.872302 -0.329149
+0.0299532 -0.161262 -0.618931
+
+0.89124 0.180166 0.416211
+-0.308612 -0.431568 0.847648
+0.332341 -0.883906 -0.329029
+0.0295462 -0.161596 -0.62551
+
+0.894705 0.147768 0.421507
+-0.328446 -0.421881 0.845068
+0.3027 -0.894528 -0.328925
+0.0291392 -0.16193 -0.632114
+
+0.896972 0.115319 0.426782
+-0.347957 -0.411342 0.842451
+0.272704 -0.904157 -0.328836
+0.0287322 -0.162264 -0.638742
+
+0.898041 0.0828634 0.432036
+-0.367111 -0.399962 0.839798
+0.242387 -0.912778 -0.328762
+0.0283252 -0.162598 -0.645394
+
+0.897915 0.0504456 0.437269
+-0.385873 -0.387754 0.837108
+0.211781 -0.920382 -0.328704
+0.0279182 -0.162932 -0.65207
+
+0.896595 0.0181105 0.44248
+-0.404208 -0.374731 0.834382
+0.180922 -0.926957 -0.328662
+0.0275112 -0.163266 -0.65877
+
+0.894088 -0.0140973 0.447669
+-0.422082 -0.360909 0.83162
+0.149844 -0.932495 -0.328635
+0.0271042 -0.1636 -0.665495
+
+0.890399 -0.0461336 0.452837
+-0.439463 -0.346304 0.828822
+0.118583 -0.936987 -0.328623
+0.0266972 -0.163934 -0.672244
+
+0.885537 -0.0779543 0.457981
+-0.456316 -0.330935 0.825989
+0.0871727 -0.940428 -0.328627
+0.0262902 -0.164268 -0.679017
+
+0.879512 -0.109516 0.463104
+-0.472612 -0.31482 0.82312
+0.0556498 -0.942812 -0.328647
+0.0258832 -0.164602 -0.685814
+
+0.872335 -0.140774 0.468203
+-0.488317 -0.297981 0.820216
+0.02405 -0.944135 -0.328682
+0.0254762 -0.164935 -0.692635
+
+0.86402 -0.171688 0.473279
+-0.503401 -0.280439 0.817277
+-0.00759084 -0.944393 -0.328732
+0.0250692 -0.165269 -0.699481
+
+0.854581 -0.202214 0.478332
+-0.517835 -0.262217 0.814303
+-0.0392366 -0.943585 -0.328799
+0.0246622 -0.165603 -0.70635
+
+0.844034 -0.23231 0.483362
+-0.531589 -0.24334 0.811295
+-0.0708511 -0.94171 -0.32888
+0.0242552 -0.165937 -0.713244
+
+0.832398 -0.261936 0.488367
+-0.544635 -0.223833 0.808252
+-0.102398 -0.93877 -0.328978
+0.0238482 -0.166271 -0.720162
+
+0.819693 -0.291052 0.493349
+-0.556947 -0.203723 0.805175
+-0.133841 -0.934765 -0.329091
+0.0234412 -0.166605 -0.727104
+
+0.805938 -0.319617 0.498306
+-0.568499 -0.183038 0.802064
+-0.165144 -0.9297 -0.329219
+0.0230342 -0.166939 -0.734071
+
+0.791157 -0.347593 0.503238
+-0.579265 -0.161807 0.798919
+-0.196271 -0.923578 -0.329363
+0.0226272 -0.167273 -0.741061
+
+0.775374 -0.374943 0.508146
+-0.589221 -0.14006 0.79574
+-0.227186 -0.916406 -0.329523
+0.0222202 -0.167607 -0.748076
+
+0.758614 -0.401629 0.513029
+-0.598344 -0.117828 0.792528
+-0.257853 -0.908191 -0.329699
+0.0218132 -0.167941 -0.755115
+
+0.740904 -0.427616 0.517886
+-0.606614 -0.0951429 0.789283
+-0.288237 -0.89894 -0.32989
+0.0214062 -0.168275 -0.762178
+
+0.722272 -0.452868 0.522718
+-0.61401 -0.0720375 0.786004
+-0.318301 -0.888662 -0.330096
+0.0209992 -0.168609 -0.769266
+
+0.702746 -0.477353 0.527524
+-0.620512 -0.0485457 0.782693
+-0.348012 -0.87737 -0.330319
+0.0205922 -0.168943 -0.776377
+
+0.682359 -0.501037 0.532304
+-0.626103 -0.0247021 0.779349
+-0.377334 -0.865073 -0.330557
+0.0201852 -0.169277 -0.783513
+
+0.661142 -0.523889 0.537058
+-0.630766 -0.000542091 0.775973
+-0.406232 -0.851786 -0.33081
+0.0197782 -0.169611 -0.790673
+
+0.639128 -0.545879 0.541785
+-0.634487 0.0238983 0.772564
+-0.434674 -0.837523 -0.331079
+0.0193712 -0.169945 -0.797857
+
+0.616351 -0.566978 0.546486
+-0.637251 0.0485823 0.769123
+-0.462626 -0.822299 -0.331364
+0.0189642 -0.170279 -0.805065
+
+0.592846 -0.587159 0.55116
+-0.639046 0.0734724 0.765651
+-0.490054 -0.80613 -0.331664
+0.0185572 -0.170613 -0.812298
+
+0.56865 -0.606396 0.555807
+-0.639862 0.0985308 0.762147
+-0.516927 -0.789035 -0.33198
+0.0181502 -0.170947 -0.819554
+
+0.5438 -0.624663 0.560426
+-0.639689 0.123719 0.758612
+-0.543212 -0.771032 -0.332312
+0.0177432 -0.171281 -0.826835
+
+0.518334 -0.641938 0.565018
+-0.638519 0.148998 0.755045
+-0.568878 -0.752141 -0.332659
+0.0173362 -0.171615 -0.83414
+
+0.492292 -0.658198 0.569582
+-0.636346 0.174329 0.751447
+-0.593896 -0.732383 -0.333021
+0.0169292 -0.171949 -0.841469
+
+0.465712 -0.673425 0.574118
+-0.633165 0.199671 0.747819
+-0.618234 -0.71178 -0.3334
+0.0165222 -0.172283 -0.848823
+
+0.438636 -0.687598 0.578626
+-0.628973 0.224986 0.74416
+-0.641865 -0.690356 -0.333794
+0.0161152 -0.172617 -0.8562
+
+0.411105 -0.700701 0.583105
+-0.623768 0.250232 0.740471
+-0.66476 -0.668134 -0.334203
+0.0157082 -0.172951 -0.863602
+
+0.383161 -0.712718 0.587555
+-0.617551 0.27537 0.736752
+-0.686891 -0.64514 -0.334628
+0.0153012 -0.173285 -0.871028
+
+0.354846 -0.723635 0.591977
+-0.610321 0.300359 0.733002
+-0.708232 -0.621399 -0.335069
+0.0148942 -0.173619 -0.878478
+
+0.326203 -0.733441 0.596369
+-0.602084 0.325159 0.729223
+-0.728757 -0.596939 -0.335525
+0.0144872 -0.173952 -0.885952
+
+0.297276 -0.742124 0.600733
+-0.592843 0.349729 0.725415
+-0.748441 -0.571788 -0.335996
+0.0140802 -0.174286 -0.893451
+
+0.268108 -0.749675 0.605066
+-0.582604 0.37403 0.721577
+-0.767261 -0.545975 -0.336484
+0.0136732 -0.17462 -0.900974
+
+0.238744 -0.756088 0.60937
+-0.571377 0.39802 0.717711
+-0.785194 -0.519529 -0.336986
+0.0132662 -0.174954 -0.90852
+
+0.209227 -0.761357 0.613644
+-0.559169 0.421661 0.713815
+-0.802218 -0.49248 -0.337504
+0.0128592 -0.175288 -0.916091
+
+0.179603 -0.765479 0.617888
+-0.545992 0.444912 0.709891
+-0.818312 -0.464861 -0.338038
+0.0124522 -0.175622 -0.923687
+
+0.149916 -0.76845 0.622101
+-0.53186 0.467735 0.705939
+-0.833457 -0.436702 -0.338587
+0.0120452 -0.175956 -0.931306
+
+0.12021 -0.770272 0.626284
+-0.516785 0.49009 0.701958
+-0.847634 -0.408036 -0.339151
+0.0116382 -0.17629 -0.93895
+
+0.0905299 -0.770945 0.630435
+-0.500784 0.511939 0.69795
+-0.860825 -0.378898 -0.339731
+0.0112312 -0.176624 -0.946618
+
+0.0609206 -0.770472 0.634556
+-0.483875 0.533244 0.693914
+-0.873014 -0.34932 -0.340326
+0.0108242 -0.176958 -0.95431
+
+0.0314264 -0.768859 0.638646
+-0.466076 0.553968 0.68985
+-0.884187 -0.319337 -0.340937
+0.0104172 -0.177292 -0.962026
+
+0.00209117 -0.766111 0.642704
+-0.447407 0.574074 0.685759
+-0.894328 -0.288984 -0.341563
+0.0100102 -0.177626 -0.969766
+
+-0.0270411 -0.762239 0.646731
+-0.427891 0.593527 0.681641
+-0.903426 -0.258298 -0.342205
+0.00960321 -0.17796 -0.977531
+
+-0.0559269 -0.75725 0.650726
+-0.40755 0.612291 0.677497
+-0.911469 -0.227313 -0.342861
+0.00919621 -0.178294 -0.985319
+
+-0.0845233 -0.751158 0.654689
+-0.38641 0.630333 0.673326
+-0.918446 -0.196067 -0.343533
+0.00878921 -0.178628 -0.993132
+
+-0.112788 -0.743975 0.658619
+-0.364497 0.647618 0.669128
+-0.924349 -0.164596 -0.34422
+0.00838221 -0.178962 -1.00097
+
+-0.140678 -0.735717 0.662518
+-0.341839 0.664114 0.664905
+-0.92917 -0.132937 -0.344923
+0.00797521 -0.179296 -1.00883
+
+-0.168153 -0.726401 0.666383
+-0.318463 0.679791 0.660656
+-0.932902 -0.101127 -0.345641
+0.00756822 -0.17963 -1.01672
+
+-0.195172 -0.716043 0.670216
+-0.294401 0.694617 0.656381
+-0.935541 -0.0692049 -0.346374
+0.00716122 -0.179964 -1.02463
+
+-0.221695 -0.704666 0.674016
+-0.269683 0.708563 0.65208
+-0.937082 -0.0372079 -0.347122
+0.00675422 -0.180298 -1.03256
+
+-0.247683 -0.692289 0.677783
+-0.244344 0.721602 0.647755
+-0.937523 -0.00517393 -0.347885
+0.00634722 -0.180632 -1.04052
+
+-0.273097 -0.678936 0.681516
+-0.218415 0.733706 0.643405
+-0.936863 0.0268589 -0.348663
+0.00594022 -0.180966 -1.0485
+
+-0.297901 -0.664631 0.685216
+-0.191933 0.744851 0.63903
+-0.935102 0.0588523 -0.349457
+0.00553322 -0.1813 -1.05651
+
+-0.322058 -0.6494 0.688882
+-0.164933 0.755011 0.634631
+-0.932242 0.0907684 -0.350265
+0.00512622 -0.181634 -1.06454
+
+-0.345533 -0.63327 0.692514
+-0.137453 0.764163 0.630207
+-0.928285 0.122569 -0.351088
+0.00471922 -0.181968 -1.07259
+
+-0.368291 -0.616271 0.696112
+-0.109531 0.772287 0.62576
+-0.923236 0.154216 -0.351927
+0.00431222 -0.182302 -1.08067
+
+-0.390299 -0.598431 0.699676
+-0.081205 0.779363 0.621289
+-0.9171 0.185671 -0.35278
+0.00390522 -0.182636 -1.08877
+
+-0.411526 -0.579783 0.703205
+-0.0525158 0.785371 0.616794
+-0.909884 0.216898 -0.353649
+0.00349823 -0.18297 -1.0969
+
+-0.431942 -0.560358 0.7067
+-0.023504 0.790294 0.612276
+-0.901595 0.247857 -0.354532
+0.00309123 -0.183303 -1.10505
+
+-0.451516 -0.540191 0.71016
+0.00578903 0.794118 0.607736
+-0.892244 0.278513 -0.35543
+0.00268423 -0.183637 -1.11323
+
+-0.470221 -0.519316 0.713585
+0.035321 0.796829 0.603172
+-0.881842 0.308829 -0.356343
+0.00227723 -0.183971 -1.12143
+
+-0.488031 -0.497769 0.716974
+0.0650492 0.798413 0.598586
+-0.870399 0.338767 -0.357271
+0.00187023 -0.184305 -1.12965
+
+-0.50492 -0.475587 0.720329
+0.09493 0.79886 0.593978
+-0.85793 0.368292 -0.358213
+0.00146323 -0.184639 -1.1379
+
+-0.520865 -0.452808 0.723647
+0.12492 0.798163 0.589348
+-0.84445 0.397368 -0.35917
+0.00105623 -0.184973 -1.14617
+
+-0.535843 -0.42947 0.72693
+0.154974 0.796312 0.584697
+-0.829973 0.425961 -0.360142
+0.000649232 -0.185307 -1.15447
+
+-0.549835 -0.405614 0.730178
+0.185047 0.793303 0.580023
+-0.814518 0.454034 -0.361128
+0.000242233 -0.185641 -1.16279
+
+-0.562821 -0.381279 0.733389
+0.215095 0.789133 0.575329
+-0.798102 0.481556 -0.362129
+-0.000164766 -0.185975 -1.17114
+
+-0.574784 -0.356507 0.736564
+0.245072 0.783798 0.570614
+-0.780745 0.508491 -0.363145
+-0.000571764 -0.186309 -1.1795
+
+-0.585709 -0.33134 0.739702
+0.274933 0.777299 0.565878
+-0.762468 0.534808 -0.364175
+-0.000978763 -0.186643 -1.1879
+
+-0.595581 -0.30582 0.742804
+0.304632 0.769638 0.561121
+-0.743292 0.560475 -0.365219
+-0.00138576 -0.186977 -1.19632
+
+-0.604388 -0.279989 0.745869
+0.334123 0.760817 0.556345
+-0.723241 0.58546 -0.366278
+-0.00179276 -0.187311 -1.20476
+
+-0.61212 -0.253892 0.748898
+0.36336 0.750842 0.551548
+-0.702338 0.609733 -0.367351
+-0.00219976 -0.187645 -1.21322
+
+-0.618768 -0.227573 0.751889
+0.392298 0.73972 0.546732
+-0.680609 0.633265 -0.368439
+-0.00260676 -0.187979 -1.22171
+
+-0.624324 -0.201074 0.754843
+0.420892 0.72746 0.541896
+-0.65808 0.656027 -0.36954
+-0.00301376 -0.188313 -1.23023
+
+-0.628784 -0.174441 0.75776
+0.449096 0.714072 0.537041
+-0.634778 0.677991 -0.370656
+-0.00342076 -0.188647 -1.23877
+
+-0.632145 -0.147719 0.760639
+0.476866 0.699569 0.532168
+-0.610731 0.69913 -0.371787
+-0.00382776 -0.188981 -1.24733
+
+-0.634403 -0.120951 0.763481
+0.504157 0.683964 0.527275
+-0.585968 0.719419 -0.372931
+-0.00423476 -0.189315 -1.25592
+
+-0.635561 -0.0941826 0.766285
+0.530924 0.667274 0.522365
+-0.56052 0.738834 -0.374089
+-0.00464175 -0.189649 -1.26453
+
+-0.635618 -0.0674586 0.769051
+0.557125 0.649516 0.517436
+-0.534417 0.757349 -0.375262
+-0.00504875 -0.189983 -1.27316
+
+-0.63458 -0.0408234 0.771778
+0.582717 0.630711 0.512489
+-0.50769 0.774943 -0.376448
+-0.00545575 -0.190317 -1.28182
+
+-0.632452 -0.0143215 0.774468
+0.607656 0.610878 0.507525
+-0.480374 0.791595 -0.377648
+-0.00586275 -0.190651 -1.2905
+
+-0.62924 0.0120031 0.777118
+0.631903 0.590041 0.502544
+-0.4525 0.807284 -0.378862
+-0.00626975 -0.190985 -1.29921
+
+-0.624954 0.0381064 0.779731
+0.655415 0.568225 0.497545
+-0.424103 0.82199 -0.38009
+-0.00667675 -0.191319 -1.30794
+
+-0.619605 0.063945 0.782304
+0.678154 0.545456 0.49253
+-0.395218 0.835697 -0.381332
+-0.00708375 -0.191653 -1.3167
+
+-0.613206 0.089476 0.784839
+0.700079 0.521761 0.487498
+-0.365879 0.848387 -0.382587
+-0.00749075 -0.191987 -1.32548
+
+-0.60577 0.114657 0.787335
+0.721154 0.49717 0.48245
+-0.336123 0.860044 -0.383856
+-0.00789775 -0.19232 -1.33429
+
+-0.597314 0.139446 0.789791
+0.741342 0.471714 0.477387
+-0.305986 0.870655 -0.385139
+-0.00830475 -0.192654 -1.34311
+
+-0.587856 0.163801 0.792209
+0.760606 0.445426 0.472307
+-0.275506 0.880207 -0.386435
+-0.00871174 -0.192988 -1.35197
+
+-0.577415 0.187683 0.794586
+0.778913 0.418339 0.467212
+-0.244719 0.888688 -0.387744
+-0.00911874 -0.193322 -1.36084
+
+-0.566011 0.211052 0.796924
+0.796228 0.39049 0.462102
+-0.213663 0.896089 -0.389067
+-0.00952574 -0.193656 -1.36975
+
+-0.553668 0.233869 0.799223
+0.812521 0.361914 0.456977
+-0.182377 0.902399 -0.390403
+-0.00993274 -0.19399 -1.37867
+
+-0.54041 0.256095 0.801481
+0.82776 0.33265 0.451838
+-0.1509 0.907612 -0.391753
+-0.0103397 -0.194324 -1.38762
+
+-0.526262 0.277695 0.8037
+0.841916 0.302738 0.446684
+-0.119268 0.911721 -0.393116
+-0.0107467 -0.194658 -1.39659
+
+-0.511252 0.298633 0.805878
+0.854963 0.272218 0.441516
+-0.0875232 0.914722 -0.394491
+-0.0111537 -0.194992 -1.40559
+
+-0.495408 0.318873 0.808017
+0.866872 0.241131 0.436335
+-0.0557029 0.916611 -0.39588
+-0.0115607 -0.195326 -1.41461
+
+-0.478761 0.338382 0.810114
+0.877621 0.209522 0.43114
+-0.0238467 0.917387 -0.397282
+-0.0119677 -0.19566 -1.42366
+
+-0.461342 0.357129 0.812172
+0.887186 0.177433 0.425932
+0.00800599 0.917048 -0.398697
+-0.0123747 -0.195994 -1.43273
+
+-0.443183 0.375081 0.814188
+0.895546 0.144911 0.420711
+0.0398159 0.915595 -0.400125
+-0.0127817 -0.196328 -1.44183
+
+-0.424319 0.392211 0.816164
+0.902682 0.112001 0.415477
+0.0715437 0.913032 -0.401566
+-0.0131887 -0.196662 -1.45094
+
+-0.404785 0.408488 0.818099
+0.908575 0.0787489 0.410231
+0.10315 0.90936 -0.403019
+-0.0135957 -0.196996 -1.46009
+
+-0.384617 0.423888 0.819993
+0.91321 0.0452037 0.404973
+0.134597 0.904586 -0.404485
+-0.0140027 -0.19733 -1.46926
+
+-0.363853 0.438384 0.821846
+0.916573 0.0114134 0.399704
+0.165844 0.898716 -0.405963
+-0.0144097 -0.197664 -1.47845
+
+-0.342532 0.451952 0.823657
+0.918652 -0.0225731 0.394423
+0.196853 0.891757 -0.407455
+-0.0148167 -0.197998 -1.48766
+
+-0.320691 0.464571 0.825427
+0.919436 -0.0567062 0.389131
+0.227586 0.883718 -0.408958
+-0.0152237 -0.198332 -1.4969
+
+-0.298373 0.476221 0.827156
+0.918916 -0.0909356 0.383828
+0.258005 0.874611 -0.410474
+-0.0156307 -0.198666 -1.50617
+
+-0.275618 0.486882 0.828843
+0.917087 -0.125211 0.378514
+0.288072 0.864447 -0.412003
+-0.0160377 -0.199 -1.51545
+
+-0.252468 0.496537 0.830488
+0.913945 -0.159481 0.37319
+0.31775 0.853239 -0.413543
+-0.0164447 -0.199334 -1.52477
+
+-0.228966 0.505171 0.832092
+0.909486 -0.193695 0.367857
+0.347002 0.841002 -0.415096
+-0.0168517 -0.199668 -1.5341
+
+-0.205155 0.51277 0.833654
+0.90371 -0.227801 0.362513
+0.375793 0.827752 -0.416661
+-0.0172587 -0.200002 -1.54346
+
+-0.181079 0.519323 0.835173
+0.896618 -0.261748 0.35716
+0.404086 0.813506 -0.418237
+-0.0176657 -0.200336 -1.55285
+
+-0.156783 0.524819 0.83665
+0.888216 -0.295484 0.351798
+0.431847 0.798282 -0.419826
+-0.0180727 -0.20067 -1.56226
+
+-0.13231 0.529251 0.838085
+0.878507 -0.328957 0.346428
+0.459041 0.7821 -0.421427
+-0.0184797 -0.201004 -1.57169
+
+-0.107706 0.532612 0.839478
+0.867501 -0.362117 0.341049
+0.485636 0.764981 -0.423039
+-0.0188867 -0.201338 -1.58115
+
+-0.0830171 0.534898 0.840828
+0.855206 -0.394911 0.335661
+0.511597 0.746947 -0.424663
+-0.0192937 -0.201671 -1.59063
+
+-0.0582878 0.536106 0.842136
+0.841634 -0.427289 0.330266
+0.536893 0.728021 -0.426299
+-0.0197007 -0.202005 -1.60014
+
+-0.0335642 0.536235 0.843401
+0.8268 -0.459201 0.324864
+0.561494 0.708228 -0.427946
+-0.0201077 -0.202339 -1.60967
+
+-0.00889178 0.535287 0.844623
+0.810719 -0.490596 0.319454
+0.585368 0.687593 -0.429605
+-0.0205147 -0.202673 -1.61922
+
+0.0156838 0.533265 0.845803
+0.793409 -0.521424 0.314037
+0.608487 0.666143 -0.431275
+-0.0209217 -0.203007 -1.6288
+
+0.040117 0.530174 0.846939
+0.77489 -0.551636 0.308613
+0.630821 0.643905 -0.432957
+-0.0213287 -0.203341 -1.6384
+
+0.0643626 0.526021 0.848033
+0.755184 -0.581185 0.303184
+0.652345 0.620908 -0.434649
+-0.0217357 -0.203675 -1.64803
+
+0.0883756 0.520814 0.849083
+0.734315 -0.610022 0.297748
+0.673031 0.597181 -0.436353
+-0.0221427 -0.204009 -1.65768
+
+0.112111 0.514565 0.85009
+0.712309 -0.638101 0.292306
+0.692855 0.572756 -0.438068
+-0.0225497 -0.204343 -1.66736
+
+0.135526 0.507286 0.851054
+0.689192 -0.665376 0.28686
+0.711791 0.547663 -0.439793
+-0.0229567 -0.204677 -1.67705
+
+0.158575 0.498992 0.851975
+0.664995 -0.691803 0.281408
+0.729819 0.521935 -0.44153
+-0.0233637 -0.205011 -1.68678
+
+0.181216 0.489698 0.852852
+0.63975 -0.717336 0.275951
+0.746914 0.495605 -0.443277
+-0.0237707 -0.205345 -1.69653
+
+0.203407 0.479424 0.853685
+0.613488 -0.741935 0.27049
+0.763058 0.468707 -0.445035
+-0.0241777 -0.205679 -1.7063
+
+0.225105 0.468188 0.854475
+0.586246 -0.765557 0.265025
+0.778231 0.441274 -0.446804
+-0.0245847 -0.206013 -1.71609
+
+0.246271 0.456012 0.855222
+0.55806 -0.788163 0.259556
+0.792414 0.413344 -0.448583
+-0.0249917 -0.206347 -1.72591
+
+0.266863 0.44292 0.855924
+0.528967 -0.809713 0.254083
+0.805592 0.38495 -0.450373
+-0.0253987 -0.206681 -1.73576
+
+0.286844 0.428936 0.856583
+0.499009 -0.830171 0.248608
+0.817747 0.356131 -0.452172
+-0.0258057 -0.207015 -1.74563
+
+0.306174 0.414089 0.857198
+0.468226 -0.849501 0.24313
+0.828868 0.326922 -0.453982
+-0.0262127 -0.207349 -1.75552
+
+0.324818 0.398404 0.857769
+0.436661 -0.867669 0.237649
+0.83894 0.297362 -0.455803
+-0.0266197 -0.207683 -1.76544
+
+0.34274 0.381913 0.858296
+0.404359 -0.884643 0.232166
+0.847952 0.267487 -0.457633
+-0.0270267 -0.208017 -1.77538
+
+0.359905 0.364647 0.858778
+0.371366 -0.900391 0.226681
+0.855895 0.237337 -0.459473
+-0.0274337 -0.208351 -1.78534
+
+0.376281 0.346639 0.859217
+0.337728 -0.914884 0.221194
+0.862759 0.20695 -0.461323
+-0.0278407 -0.208685 -1.79533
+
+0.391835 0.327922 0.859612
+0.303494 -0.928096 0.215707
+0.868537 0.176365 -0.463183
+-0.0282477 -0.209019 -1.80535
+
+0.406537 0.308533 0.859962
+0.268713 -0.940001 0.210219
+0.873224 0.145621 -0.465052
+-0.0286547 -0.209353 -1.81539
+
+0.420359 0.288509 0.860268
+0.233436 -0.950575 0.20473
+0.876816 0.114757 -0.466931
+-0.0290617 -0.209687 -1.82545
+
+0.433273 0.267886 0.86053
+0.197714 -0.959798 0.199241
+0.879309 0.0838135 -0.468819
+-0.0294687 -0.210021 -1.83553
+
+0.445254 0.246705 0.860747
+0.161601 -0.967649 0.193752
+0.880701 0.0528288 -0.470717
+-0.0298757 -0.210355 -1.84564
+
+0.456277 0.225007 0.86092
+0.125149 -0.974112 0.188263
+0.880993 0.0218428 -0.472624
+-0.0302827 -0.210688 -1.85578
+
+0.46632 0.202832 0.861049
+0.0884121 -0.979171 0.182776
+0.880187 -0.00910486 -0.47454
+-0.0306897 -0.211022 -1.86594
+
+0.475364 0.180222 0.861133
+0.051446 -0.982813 0.177289
+0.878284 -0.0399749 -0.476465
+-0.0310967 -0.211356 -1.87612
+
+0.483388 0.157222 0.861172
+0.014306 -0.985027 0.171804
+0.875289 -0.0707281 -0.478399
+-0.0315037 -0.21169 -1.88633
+
+0.490376 0.133876 0.861167
+-0.0229519 -0.985805 0.166321
+0.871209 -0.101325 -0.480342
+-0.0319107 -0.212024 -1.89656
+
+0.496314 0.110227 0.861117
+-0.0602713 -0.985138 0.16084
+0.866049 -0.131728 -0.482294
+-0.0323177 -0.212358 -1.90682
+
+0.501187 0.0863219 0.861023
+-0.0975953 -0.983025 0.155362
+0.859818 -0.161897 -0.484254
+-0.0327247 -0.212692 -1.9171
+
+0.504984 0.0622067 0.860884
+-0.134867 -0.979462 0.149886
+0.852527 -0.191795 -0.486223
+-0.0331317 -0.213026 -1.9274
+
+0.507697 0.0379279 0.8607
+-0.172028 -0.974449 0.144414
+0.844186 -0.221383 -0.4882
+-0.0335387 -0.21336 -1.93773
+
+0.509318 0.0135326 0.860472
+-0.209023 -0.96799 0.138945
+0.834808 -0.250625 -0.490186
+-0.0339457 -0.213694 -1.94808
+
+0.509841 -0.0109318 0.860199
+-0.245792 -0.960088 0.13348
+0.824408 -0.279484 -0.492179
+-0.0343527 -0.214028 -1.95846
+
+0.509264 -0.0354176 0.859881
+-0.28228 -0.950752 0.12802
+0.813 -0.307923 -0.494181
+-0.0347597 -0.214362 -1.96886
+
+0.507584 -0.059877 0.859519
+-0.318429 -0.93999 0.122563
+0.800601 -0.335907 -0.496191
+-0.0351667 -0.214696 -1.97928
+
+0.504804 -0.0842621 0.859112
+-0.354182 -0.927815 0.117112
+0.787228 -0.3634 -0.498208
+-0.0355737 -0.21503 -1.98973
+
+0.500925 -0.108525 0.85866
+-0.389482 -0.91424 0.111667
+0.772902 -0.390369 -0.500234
+-0.0359807 -0.215364 -2.0002
+
+0.495952 -0.132617 0.858163
+-0.424275 -0.899281 0.106226
+0.757643 -0.41678 -0.502266
+-0.0363877 -0.215698 -2.0107
+
+0.489893 -0.156492 0.857622
+-0.458504 -0.882958 0.100792
+0.741471 -0.4426 -0.504307
+-0.0367947 -0.216032 -2.02122
+
+0.482755 -0.180102 0.857036
+-0.492114 -0.865291 0.0953642
+0.724411 -0.467797 -0.506355
+-0.0372017 -0.216366 -2.03177
+
+0.474552 -0.203398 0.856405
+-0.525052 -0.846304 0.089943
+0.706485 -0.49234 -0.50841
+-0.0376087 -0.2167 -2.04234
+
+0.465294 -0.226336 0.85573
+-0.557265 -0.826021 0.0845289
+0.687718 -0.516199 -0.510472
+-0.0380157 -0.217034 -2.05293
+
+0.454998 -0.248869 0.855009
+-0.588701 -0.80447 0.0791221
+0.668138 -0.539345 -0.512541
+-0.0384227 -0.217368 -2.06355
+
+0.44368 -0.270951 0.854244
+-0.619307 -0.78168 0.0737231
+0.647771 -0.561749 -0.514618
+-0.0388297 -0.217702 -2.0742
+
+0.43136 -0.292537 0.853435
+-0.649035 -0.757684 0.0683321
+0.626644 -0.583384 -0.516701
+-0.0392367 -0.218036 -2.08486
+
+0.418057 -0.313583 0.852581
+-0.677834 -0.732515 0.0629497
+0.604788 -0.604225 -0.51879
+-0.0396437 -0.21837 -2.09555
+
+0.403796 -0.334046 0.851682
+-0.705659 -0.706208 0.057576
+0.582232 -0.624246 -0.520887
+-0.0400507 -0.218704 -2.10627
+
+0.388601 -0.353884 0.850738
+-0.732462 -0.678803 0.0522115
+0.559007 -0.643423 -0.52299
+-0.0404577 -0.219038 -2.11701
+
+0.372498 -0.373054 0.84975
+-0.758199 -0.650337 0.0468565
+0.535144 -0.661734 -0.525099
+-0.0408647 -0.219372 -2.12777
+
+0.355515 -0.391518 0.848718
+-0.782827 -0.620854 0.0415114
+0.510677 -0.679157 -0.527214
+-0.0412717 -0.219705 -2.13856
+
+0.337684 -0.409236 0.847641
+-0.806303 -0.590395 0.0361765
+0.485638 -0.695672 -0.529336
+-0.0416787 -0.220039 -2.14937
+
+0.319035 -0.42617 0.846519
+-0.828589 -0.559007 0.0308522
+0.460062 -0.71126 -0.531463
+-0.0420857 -0.220373 -2.16021
+
+0.299603 -0.442284 0.845354
+-0.849646 -0.526735 0.0255388
+0.433982 -0.725903 -0.533596
+-0.0424927 -0.220707 -2.17107
+
+0.279421 -0.457543 0.844144
+-0.869437 -0.493629 0.0202368
+0.407434 -0.739584 -0.535735
+-0.0428997 -0.221041 -2.18195
+
+0.258528 -0.471913 0.842889
+-0.887929 -0.459738 0.0149463
+0.380455 -0.75229 -0.53788
+-0.0433067 -0.221375 -2.19286
+
+0.23696 -0.485361 0.84159
+-0.905089 -0.425113 0.00966796
+0.353079 -0.764005 -0.54003
+-0.0437137 -0.221709 -2.20379
+
+0.214758 -0.497859 0.840247
+-0.920886 -0.389808 0.00440195
+0.325343 -0.774717 -0.542185
+-0.0441207 -0.222043 -2.21475
+
+0.191963 -0.509376 0.83886
+-0.935292 -0.353876 -0.000851335
+0.297286 -0.784416 -0.544346
+-0.0445277 -0.222377 -2.22573
+
+0.168616 -0.519885 0.837429
+-0.948282 -0.317372 -0.00609153
+0.268943 -0.793092 -0.546512
+-0.0449347 -0.222711 -2.23674
+
+0.144762 -0.529362 0.835954
+-0.95983 -0.280353 -0.0113183
+0.240354 -0.800736 -0.548682
+-0.0453417 -0.223045 -2.24777
+
+0.120444 -0.537783 0.834435
+-0.969917 -0.242876 -0.0165312
+0.211554 -0.807341 -0.550858
+-0.0457487 -0.223379 -2.25882
+
+0.0957082 -0.545127 0.832872
+-0.978521 -0.205 -0.02173
+0.182584 -0.812903 -0.553038
+-0.0461557 -0.223713 -2.2699
+
+0.0706016 -0.551373 0.831266
+-0.985626 -0.166783 -0.0269142
+0.153481 -0.817417 -0.555223
+-0.0465627 -0.224047 -2.281
+
+0.0451714 -0.556505 0.829616
+-0.991218 -0.128286 -0.0320836
+0.124283 -0.820881 -0.557412
+-0.0469696 -0.224381 -2.29213
+
+0.0194661 -0.560506 0.827922
+-0.995284 -0.0895695 -0.0372377
+0.0950285 -0.823293 -0.559606
+-0.0473766 -0.224715 -2.30328
+
+-0.00646536 -0.563363 0.826184
+-0.997815 -0.0506945 -0.0423762
+0.0657562 -0.824653 -0.561804
+-0.0477836 -0.225049 -2.31445
+
+-0.0325732 -0.565064 0.824404
+-0.998803 -0.0117226 -0.0474988
+0.0365041 -0.824964 -0.564006
+-0.0481906 -0.225383 -2.32565
+
+-0.058807 -0.565601 0.82258
+-0.998243 0.027284 -0.0526051
+0.00731026 -0.824227 -0.566212
+-0.0485976 -0.225717 -2.33687
+
+-0.0851162 -0.564966 0.820712
+-0.996133 0.066263 -0.0576947
+-0.0217873 -0.822449 -0.568421
+-0.0490046 -0.226051 -2.34812
+
+-0.11145 -0.563154 0.818802
+-0.992473 0.105152 -0.0627672
+-0.050751 -0.819634 -0.570635
+-0.0494116 -0.226385 -2.35939
+
+-0.137756 -0.560163 0.816848
+-0.987267 0.143888 -0.0678224
+-0.0795435 -0.81579 -0.572851
+-0.0498186 -0.226719 -2.37069
+
+-0.163983 -0.555991 0.814852
+-0.980519 0.18241 -0.0728598
+-0.108128 -0.810926 -0.575072
+-0.0502256 -0.227053 -2.38201
+
+-0.190079 -0.55064 0.812813
+-0.972238 0.220654 -0.0778792
+-0.136467 -0.805051 -0.577295
+-0.0506326 -0.227387 -2.39335
+
+-0.215993 -0.544116 0.810731
+-0.962434 0.258559 -0.0828801
+-0.164525 -0.798176 -0.579522
+-0.0510396 -0.227721 -2.40472
+
+-0.241674 -0.536422 0.808607
+-0.951119 0.296062 -0.0878621
+-0.192267 -0.790315 -0.581752
+-0.0514466 -0.228055 -2.41611
+
+-0.267068 -0.527569 0.80644
+-0.93831 0.333103 -0.0928251
+-0.219656 -0.781482 -0.583984
+-0.0518536 -0.228389 -2.42753
+
+-0.292126 -0.517566 0.804231
+-0.924024 0.369622 -0.0977685
+-0.24666 -0.77169 -0.58622
+-0.0522606 -0.228723 -2.43897
+
+-0.316797 -0.506426 0.80198
+-0.908283 0.405557 -0.102692
+-0.273242 -0.760957 -0.588458
+-0.0526676 -0.229056 -2.45043
+
+-0.34103 -0.494165 0.799687
+-0.891109 0.440849 -0.107595
+-0.299372 -0.749301 -0.590698
+-0.0530746 -0.22939 -2.46192
+
+-0.364776 -0.4808 0.797352
+-0.872527 0.475442 -0.112478
+-0.325015 -0.73674 -0.592941
+-0.0534816 -0.229724 -2.47344
+
+-0.387985 -0.46635 0.794975
+-0.852566 0.509276 -0.11734
+-0.35014 -0.723295 -0.595186
+-0.0538886 -0.230058 -2.48497
+
+-0.41061 -0.450836 0.792557
+-0.831256 0.542297 -0.12218
+-0.374717 -0.708986 -0.597433
+-0.0542956 -0.230392 -2.49654
+
+-0.432602 -0.434283 0.790097
+-0.808629 0.574448 -0.126999
+-0.398716 -0.693836 -0.599682
+-0.0547026 -0.230726 -2.50812
+
+-0.453916 -0.416717 0.787596
+-0.784721 0.605676 -0.131796
+-0.422106 -0.677867 -0.601932
+-0.0551096 -0.23106 -2.51973
+
+-0.474506 -0.398164 0.785054
+-0.759568 0.635929 -0.136571
+-0.44486 -0.661105 -0.604185
+-0.0555166 -0.231394 -2.53137
+
+-0.494328 -0.378656 0.78247
+-0.733209 0.665155 -0.141323
+-0.466952 -0.643574 -0.606439
+-0.0559236 -0.231728 -2.54302
+
+-0.513338 -0.358223 0.779846
+-0.705687 0.693307 -0.146052
+-0.488354 -0.625302 -0.608694
+-0.0563306 -0.232062 -2.55471
+
+-0.531495 -0.3369 0.777182
+-0.677045 0.720335 -0.150757
+-0.509041 -0.606314 -0.610951
+-0.0567376 -0.232396 -2.56641
+
+-0.548759 -0.314721 0.774477
+-0.647328 0.746193 -0.155439
+-0.528989 -0.586639 -0.613208
+-0.0571446 -0.23273 -2.57814
+
+-0.56509 -0.291726 0.771731
+-0.616584 0.770839 -0.160097
+-0.548176 -0.566307 -0.615467
+-0.0575516 -0.233064 -2.5899
+
+-0.580452 -0.267952 0.768946
+-0.584862 0.794229 -0.164731
+-0.56658 -0.545345 -0.617726
+-0.0579586 -0.233398 -2.60168
+
+-0.594808 -0.24344 0.766121
+-0.552213 0.816324 -0.169339
+-0.584179 -0.523786 -0.619987
+-0.0583656 -0.233732 -2.61348
+
+-0.608124 -0.218233 0.763255
+-0.518689 0.837086 -0.173923
+-0.600954 -0.501659 -0.622247
+-0.0587726 -0.234066 -2.62531
+
+-0.62037 -0.192375 0.760351
+-0.484346 0.856477 -0.178482
+-0.616888 -0.478997 -0.624509
+-0.0591796 -0.2344 -2.63716
+
+-0.631513 -0.165912 0.757407
+-0.449239 0.874466 -0.183014
+-0.631962 -0.455832 -0.62677
+-0.0595866 -0.234734 -2.64904
+
+-0.641525 -0.138889 0.754424
+-0.413425 0.891019 -0.187521
+-0.646162 -0.432197 -0.629032
+-0.0599936 -0.235068 -2.66094
+
+-0.650381 -0.111356 0.751402
+-0.376964 0.906109 -0.192001
+-0.659472 -0.408125 -0.631293
+-0.0604006 -0.235402 -2.67286
+
+-0.658055 -0.0833609 0.748341
+-0.339914 0.919709 -0.196454
+-0.671879 -0.38365 -0.633555
+-0.0608076 -0.235736 -2.68481
+
+-0.664526 -0.0549551 0.745242
+-0.302338 0.931793 -0.200881
+-0.683372 -0.358805 -0.635816
+-0.0612146 -0.23607 -2.69678
+
+-0.669773 -0.02619 0.742104
+-0.264297 0.942342 -0.20528
+-0.693939 -0.333626 -0.638077
+-0.0616216 -0.236404 -2.70878
+
+-0.673778 0.00288213 0.738928
+-0.225854 0.951334 -0.209651
+-0.703572 -0.308148 -0.640337
+-0.0620286 -0.236738 -2.7208
+
+-0.676525 0.0322078 0.735715
+-0.187073 0.958755 -0.213994
+-0.712262 -0.282404 -0.642596
+-0.0624356 -0.237072 -2.73285
+
+-0.678001 0.0617328 0.732464
+-0.148018 0.964589 -0.218309
+-0.720003 -0.256432 -0.644855
+-0.0628426 -0.237406 -2.74492
+
+-0.678196 0.0914025 0.729175
+-0.108756 0.968826 -0.222595
+-0.726789 -0.230265 -0.647113
+-0.0632496 -0.23774 -2.75701
+
+-0.677099 0.121161 0.725849
+-0.0693511 0.971457 -0.226852
+-0.732617 -0.20394 -0.649369
+-0.0636566 -0.238073 -2.76913
+
+-0.674704 0.150954 0.722487
+-0.0298702 0.972476 -0.23108
+-0.737483 -0.177492 -0.651625
+-0.0640636 -0.238407 -2.78127
+
+-0.671009 0.180723 0.719087
+0.00962062 0.97188 -0.235279
+-0.741387 -0.150956 -0.653879
+-0.0644706 -0.238741 -2.79344
+
+-0.66601 0.210413 0.715651
+0.0490547 0.969669 -0.239447
+-0.744328 -0.124368 -0.656131
+-0.0648776 -0.239075 -2.80563
+
+-0.659709 0.239968 0.712179
+0.0883653 0.965846 -0.243585
+-0.746308 -0.0977635 -0.658382
+-0.0652846 -0.239409 -2.81784
+
+-0.65211 0.269329 0.708671
+0.127486 0.960414 -0.247693
+-0.747329 -0.0711772 -0.660631
+-0.0656916 -0.239743 -2.83008
+
+-0.643217 0.298441 0.705127
+0.16635 0.953383 -0.25177
+-0.747395 -0.0446443 -0.662878
+-0.0660986 -0.240077 -2.84234
+
+-0.63304 0.327248 0.701548
+0.204892 0.944763 -0.255815
+-0.746512 -0.0181993 -0.665123
+-0.0665056 -0.240411 -2.85463
+
+-0.621588 0.355692 0.697934
+0.243046 0.934568 -0.259829
+-0.744685 0.00812338 -0.667366
+-0.0669126 -0.240745 -2.86694
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.tris b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.tris
new file mode 100644
index 00000000..cfb261e3
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus1.tris
@@ -0,0 +1,5329 @@
+1332
+0.46 0 0
+0.453383 0.0777404 0.033314
+0.453969 0 0.034202
+
+0.447439 0.0767212 0.067516
+0.453969 0 0.034202
+0.453383 0.0777404 0.033314
+
+0.453969 0 0.034202
+0.447439 0.0767212 0.067516
+0.436604 0 0.0642788
+
+0.430324 0.0737865 0.0975927
+0.436604 0 0.0642788
+0.447439 0.0767212 0.067516
+
+0.436604 0 0.0642788
+0.430324 0.0737865 0.0975927
+0.41 0 0.0866025
+
+0.404103 0.0692903 0.119917
+0.41 0 0.0866025
+0.430324 0.0737865 0.0975927
+
+0.41 0 0.0866025
+0.404103 0.0692903 0.119917
+0.377365 0 0.0984808
+
+0.371937 0.063775 0.131795
+0.377365 0 0.0984808
+0.404103 0.0692903 0.119917
+
+0.377365 0 0.0984808
+0.371937 0.063775 0.131795
+0.342635 0 0.0984808
+
+0.337707 0.0579056 0.131795
+0.342635 0 0.0984808
+0.371937 0.063775 0.131795
+
+0.342635 0 0.0984808
+0.337707 0.0579056 0.131795
+0.31 0 0.0866025
+
+0.305541 0.0523903 0.119917
+0.31 0 0.0866025
+0.337707 0.0579056 0.131795
+
+0.31 0 0.0866025
+0.305541 0.0523903 0.119917
+0.283396 0 0.0642788
+
+0.279319 0.0478941 0.0975927
+0.283396 0 0.0642788
+0.305541 0.0523903 0.119917
+
+0.283396 0 0.0642788
+0.279319 0.0478941 0.0975927
+0.266031 0 0.034202
+
+0.262204 0.0449594 0.067516
+0.266031 0 0.034202
+0.279319 0.0478941 0.0975927
+
+0.266031 0 0.034202
+0.262204 0.0449594 0.067516
+0.26 0 0
+
+0.25626 0.0439402 0.033314
+0.26 0 0
+0.262204 0.0449594 0.067516
+
+0.26 0 0
+0.25626 0.0439402 0.033314
+0.266031 0 -0.034202
+
+0.262204 0.0449594 -0.000888035
+0.266031 0 -0.034202
+0.25626 0.0439402 0.033314
+
+0.266031 0 -0.034202
+0.262204 0.0449594 -0.000888035
+0.283396 0 -0.0642788
+
+0.279319 0.0478941 -0.0309648
+0.283396 0 -0.0642788
+0.262204 0.0449594 -0.000888035
+
+0.283396 0 -0.0642788
+0.279319 0.0478941 -0.0309648
+0.31 0 -0.0866025
+
+0.305541 0.0523903 -0.0532886
+0.31 0 -0.0866025
+0.279319 0.0478941 -0.0309648
+
+0.31 0 -0.0866025
+0.305541 0.0523903 -0.0532886
+0.342635 0 -0.0984808
+
+0.337707 0.0579056 -0.0651668
+0.342635 0 -0.0984808
+0.305541 0.0523903 -0.0532886
+
+0.342635 0 -0.0984808
+0.337707 0.0579056 -0.0651668
+0.377365 0 -0.0984808
+
+0.371937 0.063775 -0.0651668
+0.377365 0 -0.0984808
+0.337707 0.0579056 -0.0651668
+
+0.377365 0 -0.0984808
+0.371937 0.063775 -0.0651668
+0.41 0 -0.0866025
+
+0.404103 0.0692903 -0.0532886
+0.41 0 -0.0866025
+0.371937 0.063775 -0.0651668
+
+0.41 0 -0.0866025
+0.404103 0.0692903 -0.0532886
+0.436604 0 -0.0642788
+
+0.430324 0.0737865 -0.0309648
+0.436604 0 -0.0642788
+0.404103 0.0692903 -0.0532886
+
+0.436604 0 -0.0642788
+0.430324 0.0737865 -0.0309648
+0.453969 0 -0.034202
+
+0.447439 0.0767212 -0.000888035
+0.453969 0 -0.034202
+0.430324 0.0737865 -0.0309648
+
+0.453969 0 -0.034202
+0.447439 0.0767212 -0.000888035
+0.46 0 0
+
+0.453383 0.0777404 0.033314
+0.46 0 0
+0.447439 0.0767212 -0.000888035
+
+0.453383 0.0777404 0.033314
+0.433724 0.153244 0.062822
+0.447439 0.0767212 0.067516
+
+0.428037 0.151235 0.097024
+0.447439 0.0767212 0.067516
+0.433724 0.153244 0.062822
+
+0.447439 0.0767212 0.067516
+0.428037 0.151235 0.097024
+0.430324 0.0737865 0.0975927
+
+0.411664 0.14545 0.127101
+0.430324 0.0737865 0.0975927
+0.428037 0.151235 0.097024
+
+0.430324 0.0737865 0.0975927
+0.411664 0.14545 0.127101
+0.404103 0.0692903 0.119917
+
+0.38658 0.136587 0.149425
+0.404103 0.0692903 0.119917
+0.411664 0.14545 0.127101
+
+0.404103 0.0692903 0.119917
+0.38658 0.136587 0.149425
+0.371937 0.063775 0.131795
+
+0.355809 0.125715 0.161303
+0.371937 0.063775 0.131795
+0.38658 0.136587 0.149425
+
+0.371937 0.063775 0.131795
+0.355809 0.125715 0.161303
+0.337707 0.0579056 0.131795
+
+0.323063 0.114145 0.161303
+0.337707 0.0579056 0.131795
+0.355809 0.125715 0.161303
+
+0.337707 0.0579056 0.131795
+0.323063 0.114145 0.161303
+0.305541 0.0523903 0.119917
+
+0.292292 0.103273 0.149425
+0.305541 0.0523903 0.119917
+0.323063 0.114145 0.161303
+
+0.305541 0.0523903 0.119917
+0.292292 0.103273 0.149425
+0.279319 0.0478941 0.0975927
+
+0.267207 0.0944103 0.127101
+0.279319 0.0478941 0.0975927
+0.292292 0.103273 0.149425
+
+0.279319 0.0478941 0.0975927
+0.267207 0.0944103 0.127101
+0.262204 0.0449594 0.067516
+
+0.250834 0.0886254 0.097024
+0.262204 0.0449594 0.067516
+0.267207 0.0944103 0.127101
+
+0.262204 0.0449594 0.067516
+0.250834 0.0886254 0.097024
+0.25626 0.0439402 0.033314
+
+0.245148 0.0866163 0.062822
+0.25626 0.0439402 0.033314
+0.250834 0.0886254 0.097024
+
+0.25626 0.0439402 0.033314
+0.245148 0.0866163 0.062822
+0.262204 0.0449594 -0.000888035
+
+0.250834 0.0886254 0.02862
+0.262204 0.0449594 -0.000888035
+0.245148 0.0866163 0.062822
+
+0.262204 0.0449594 -0.000888035
+0.250834 0.0886254 0.02862
+0.279319 0.0478941 -0.0309648
+
+0.267207 0.0944103 -0.00145676
+0.279319 0.0478941 -0.0309648
+0.250834 0.0886254 0.02862
+
+0.279319 0.0478941 -0.0309648
+0.267207 0.0944103 -0.00145676
+0.305541 0.0523903 -0.0532886
+
+0.292292 0.103273 -0.0237805
+0.305541 0.0523903 -0.0532886
+0.267207 0.0944103 -0.00145676
+
+0.305541 0.0523903 -0.0532886
+0.292292 0.103273 -0.0237805
+0.337707 0.0579056 -0.0651668
+
+0.323063 0.114145 -0.0356588
+0.337707 0.0579056 -0.0651668
+0.292292 0.103273 -0.0237805
+
+0.337707 0.0579056 -0.0651668
+0.323063 0.114145 -0.0356588
+0.371937 0.063775 -0.0651668
+
+0.355809 0.125715 -0.0356588
+0.371937 0.063775 -0.0651668
+0.323063 0.114145 -0.0356588
+
+0.371937 0.063775 -0.0651668
+0.355809 0.125715 -0.0356588
+0.404103 0.0692903 -0.0532886
+
+0.38658 0.136587 -0.0237805
+0.404103 0.0692903 -0.0532886
+0.355809 0.125715 -0.0356588
+
+0.404103 0.0692903 -0.0532886
+0.38658 0.136587 -0.0237805
+0.430324 0.0737865 -0.0309648
+
+0.411664 0.14545 -0.00145676
+0.430324 0.0737865 -0.0309648
+0.38658 0.136587 -0.0237805
+
+0.430324 0.0737865 -0.0309648
+0.411664 0.14545 -0.00145676
+0.447439 0.0767212 -0.000888035
+
+0.428037 0.151235 0.02862
+0.447439 0.0767212 -0.000888035
+0.411664 0.14545 -0.00145676
+
+0.447439 0.0767212 -0.000888035
+0.428037 0.151235 0.02862
+0.453383 0.0777404 0.033314
+
+0.433724 0.153244 0.062822
+0.453383 0.0777404 0.033314
+0.428037 0.151235 0.02862
+
+0.433724 0.153244 0.062822
+0.401586 0.22434 0.0851529
+0.428037 0.151235 0.097024
+
+0.396322 0.221399 0.119355
+0.428037 0.151235 0.097024
+0.401586 0.22434 0.0851529
+
+0.428037 0.151235 0.097024
+0.396322 0.221399 0.119355
+0.411664 0.14545 0.127101
+
+0.381162 0.21293 0.149432
+0.411664 0.14545 0.127101
+0.396322 0.221399 0.119355
+
+0.411664 0.14545 0.127101
+0.381162 0.21293 0.149432
+0.38658 0.136587 0.149425
+
+0.357936 0.199955 0.171755
+0.38658 0.136587 0.149425
+0.381162 0.21293 0.149432
+
+0.38658 0.136587 0.149425
+0.357936 0.199955 0.171755
+0.355809 0.125715 0.161303
+
+0.329445 0.184039 0.183634
+0.355809 0.125715 0.161303
+0.357936 0.199955 0.171755
+
+0.355809 0.125715 0.161303
+0.329445 0.184039 0.183634
+0.323063 0.114145 0.161303
+
+0.299125 0.167101 0.183634
+0.323063 0.114145 0.161303
+0.329445 0.184039 0.183634
+
+0.323063 0.114145 0.161303
+0.299125 0.167101 0.183634
+0.292292 0.103273 0.149425
+
+0.270634 0.151185 0.171755
+0.292292 0.103273 0.149425
+0.299125 0.167101 0.183634
+
+0.292292 0.103273 0.149425
+0.270634 0.151185 0.171755
+0.267207 0.0944103 0.127101
+
+0.247408 0.138211 0.149432
+0.267207 0.0944103 0.127101
+0.270634 0.151185 0.171755
+
+0.267207 0.0944103 0.127101
+0.247408 0.138211 0.149432
+0.250834 0.0886254 0.097024
+
+0.232249 0.129742 0.119355
+0.250834 0.0886254 0.097024
+0.247408 0.138211 0.149432
+
+0.250834 0.0886254 0.097024
+0.232249 0.129742 0.119355
+0.245148 0.0866163 0.062822
+
+0.226984 0.126801 0.0851529
+0.245148 0.0866163 0.062822
+0.232249 0.129742 0.119355
+
+0.245148 0.0866163 0.062822
+0.226984 0.126801 0.0851529
+0.250834 0.0886254 0.02862
+
+0.232249 0.129742 0.0509509
+0.250834 0.0886254 0.02862
+0.226984 0.126801 0.0851529
+
+0.250834 0.0886254 0.02862
+0.232249 0.129742 0.0509509
+0.267207 0.0944103 -0.00145676
+
+0.247408 0.138211 0.0208742
+0.267207 0.0944103 -0.00145676
+0.232249 0.129742 0.0509509
+
+0.267207 0.0944103 -0.00145676
+0.247408 0.138211 0.0208742
+0.292292 0.103273 -0.0237805
+
+0.270634 0.151185 -0.00144963
+0.292292 0.103273 -0.0237805
+0.247408 0.138211 0.0208742
+
+0.292292 0.103273 -0.0237805
+0.270634 0.151185 -0.00144963
+0.323063 0.114145 -0.0356588
+
+0.299125 0.167101 -0.0133279
+0.323063 0.114145 -0.0356588
+0.270634 0.151185 -0.00144963
+
+0.323063 0.114145 -0.0356588
+0.299125 0.167101 -0.0133279
+0.355809 0.125715 -0.0356588
+
+0.329445 0.184039 -0.0133279
+0.355809 0.125715 -0.0356588
+0.299125 0.167101 -0.0133279
+
+0.355809 0.125715 -0.0356588
+0.329445 0.184039 -0.0133279
+0.38658 0.136587 -0.0237805
+
+0.357936 0.199955 -0.00144963
+0.38658 0.136587 -0.0237805
+0.329445 0.184039 -0.0133279
+
+0.38658 0.136587 -0.0237805
+0.357936 0.199955 -0.00144963
+0.411664 0.14545 -0.00145676
+
+0.381162 0.21293 0.0208742
+0.411664 0.14545 -0.00145676
+0.357936 0.199955 -0.00144963
+
+0.411664 0.14545 -0.00145676
+0.381162 0.21293 0.0208742
+0.428037 0.151235 0.02862
+
+0.396322 0.221399 0.0509509
+0.428037 0.151235 0.02862
+0.381162 0.21293 0.0208742
+
+0.428037 0.151235 0.02862
+0.396322 0.221399 0.0509509
+0.433724 0.153244 0.062822
+
+0.401586 0.22434 0.0851529
+0.433724 0.153244 0.062822
+0.396322 0.221399 0.0509509
+
+0.401586 0.22434 0.0851529
+0.357896 0.288981 0.0977555
+0.396322 0.221399 0.119355
+
+0.353204 0.285193 0.131958
+0.396322 0.221399 0.119355
+0.357896 0.288981 0.0977555
+
+0.396322 0.221399 0.119355
+0.353204 0.285193 0.131958
+0.381162 0.21293 0.149432
+
+0.339694 0.274284 0.162034
+0.381162 0.21293 0.149432
+0.353204 0.285193 0.131958
+
+0.381162 0.21293 0.149432
+0.339694 0.274284 0.162034
+0.357936 0.199955 0.171755
+
+0.318995 0.25757 0.184358
+0.357936 0.199955 0.171755
+0.339694 0.274284 0.162034
+
+0.357936 0.199955 0.171755
+0.318995 0.25757 0.184358
+0.329445 0.184039 0.183634
+
+0.293603 0.237068 0.196236
+0.329445 0.184039 0.183634
+0.318995 0.25757 0.184358
+
+0.329445 0.184039 0.183634
+0.293603 0.237068 0.196236
+0.299125 0.167101 0.183634
+
+0.266582 0.21525 0.196236
+0.299125 0.167101 0.183634
+0.293603 0.237068 0.196236
+
+0.299125 0.167101 0.183634
+0.266582 0.21525 0.196236
+0.270634 0.151185 0.171755
+
+0.241191 0.194748 0.184358
+0.270634 0.151185 0.171755
+0.266582 0.21525 0.196236
+
+0.270634 0.151185 0.171755
+0.241191 0.194748 0.184358
+0.247408 0.138211 0.149432
+
+0.220492 0.178035 0.162034
+0.247408 0.138211 0.149432
+0.241191 0.194748 0.184358
+
+0.247408 0.138211 0.149432
+0.220492 0.178035 0.162034
+0.232249 0.129742 0.119355
+
+0.206981 0.167126 0.131958
+0.232249 0.129742 0.119355
+0.220492 0.178035 0.162034
+
+0.232249 0.129742 0.119355
+0.206981 0.167126 0.131958
+0.226984 0.126801 0.0851529
+
+0.202289 0.163337 0.0977555
+0.226984 0.126801 0.0851529
+0.206981 0.167126 0.131958
+
+0.226984 0.126801 0.0851529
+0.202289 0.163337 0.0977555
+0.232249 0.129742 0.0509509
+
+0.206981 0.167126 0.0635535
+0.232249 0.129742 0.0509509
+0.202289 0.163337 0.0977555
+
+0.232249 0.129742 0.0509509
+0.206981 0.167126 0.0635535
+0.247408 0.138211 0.0208742
+
+0.220492 0.178035 0.0334768
+0.247408 0.138211 0.0208742
+0.206981 0.167126 0.0635535
+
+0.247408 0.138211 0.0208742
+0.220492 0.178035 0.0334768
+0.270634 0.151185 -0.00144963
+
+0.241191 0.194748 0.011153
+0.270634 0.151185 -0.00144963
+0.220492 0.178035 0.0334768
+
+0.270634 0.151185 -0.00144963
+0.241191 0.194748 0.011153
+0.299125 0.167101 -0.0133279
+
+0.266582 0.21525 -0.000725251
+0.299125 0.167101 -0.0133279
+0.241191 0.194748 0.011153
+
+0.299125 0.167101 -0.0133279
+0.266582 0.21525 -0.000725251
+0.329445 0.184039 -0.0133279
+
+0.293603 0.237068 -0.000725251
+0.329445 0.184039 -0.0133279
+0.266582 0.21525 -0.000725251
+
+0.329445 0.184039 -0.0133279
+0.293603 0.237068 -0.000725251
+0.357936 0.199955 -0.00144963
+
+0.318995 0.25757 0.011153
+0.357936 0.199955 -0.00144963
+0.293603 0.237068 -0.000725251
+
+0.357936 0.199955 -0.00144963
+0.318995 0.25757 0.011153
+0.381162 0.21293 0.0208742
+
+0.339694 0.274284 0.0334768
+0.381162 0.21293 0.0208742
+0.318995 0.25757 0.011153
+
+0.381162 0.21293 0.0208742
+0.339694 0.274284 0.0334768
+0.396322 0.221399 0.0509509
+
+0.353204 0.285193 0.0635535
+0.396322 0.221399 0.0509509
+0.339694 0.274284 0.0334768
+
+0.396322 0.221399 0.0509509
+0.353204 0.285193 0.0635535
+0.401586 0.22434 0.0851529
+
+0.357896 0.288981 0.0977555
+0.401586 0.22434 0.0851529
+0.353204 0.285193 0.0635535
+
+0.357896 0.288981 0.0977555
+0.30391 0.345309 0.09919
+0.353204 0.285193 0.131958
+
+0.299926 0.340782 0.133392
+0.353204 0.285193 0.131958
+0.30391 0.345309 0.09919
+
+0.353204 0.285193 0.131958
+0.299926 0.340782 0.133392
+0.339694 0.274284 0.162034
+
+0.288454 0.327747 0.163469
+0.339694 0.274284 0.162034
+0.299926 0.340782 0.133392
+
+0.339694 0.274284 0.162034
+0.288454 0.327747 0.163469
+0.318995 0.25757 0.184358
+
+0.270877 0.307776 0.185793
+0.318995 0.25757 0.184358
+0.288454 0.327747 0.163469
+
+0.318995 0.25757 0.184358
+0.270877 0.307776 0.185793
+0.293603 0.237068 0.196236
+
+0.249315 0.283277 0.197671
+0.293603 0.237068 0.196236
+0.270877 0.307776 0.185793
+
+0.293603 0.237068 0.196236
+0.249315 0.283277 0.197671
+0.266582 0.21525 0.196236
+
+0.22637 0.257207 0.197671
+0.266582 0.21525 0.196236
+0.249315 0.283277 0.197671
+
+0.266582 0.21525 0.196236
+0.22637 0.257207 0.197671
+0.241191 0.194748 0.184358
+
+0.204809 0.232708 0.185793
+0.241191 0.194748 0.184358
+0.22637 0.257207 0.197671
+
+0.241191 0.194748 0.184358
+0.204809 0.232708 0.185793
+0.220492 0.178035 0.162034
+
+0.187232 0.212737 0.163469
+0.220492 0.178035 0.162034
+0.204809 0.232708 0.185793
+
+0.220492 0.178035 0.162034
+0.187232 0.212737 0.163469
+0.206981 0.167126 0.131958
+
+0.17576 0.199702 0.133392
+0.206981 0.167126 0.131958
+0.187232 0.212737 0.163469
+
+0.206981 0.167126 0.131958
+0.17576 0.199702 0.133392
+0.202289 0.163337 0.0977555
+
+0.171775 0.195175 0.09919
+0.202289 0.163337 0.0977555
+0.17576 0.199702 0.133392
+
+0.202289 0.163337 0.0977555
+0.171775 0.195175 0.09919
+0.206981 0.167126 0.0635535
+
+0.17576 0.199702 0.064988
+0.206981 0.167126 0.0635535
+0.171775 0.195175 0.09919
+
+0.206981 0.167126 0.0635535
+0.17576 0.199702 0.064988
+0.220492 0.178035 0.0334768
+
+0.187232 0.212737 0.0349113
+0.220492 0.178035 0.0334768
+0.17576 0.199702 0.064988
+
+0.220492 0.178035 0.0334768
+0.187232 0.212737 0.0349113
+0.241191 0.194748 0.011153
+
+0.204809 0.232708 0.0125875
+0.241191 0.194748 0.011153
+0.187232 0.212737 0.0349113
+
+0.241191 0.194748 0.011153
+0.204809 0.232708 0.0125875
+0.266582 0.21525 -0.000725251
+
+0.22637 0.257207 0.000709268
+0.266582 0.21525 -0.000725251
+0.204809 0.232708 0.0125875
+
+0.266582 0.21525 -0.000725251
+0.22637 0.257207 0.000709268
+0.293603 0.237068 -0.000725251
+
+0.249315 0.283277 0.000709268
+0.293603 0.237068 -0.000725251
+0.22637 0.257207 0.000709268
+
+0.293603 0.237068 -0.000725251
+0.249315 0.283277 0.000709268
+0.318995 0.25757 0.011153
+
+0.270877 0.307776 0.0125875
+0.318995 0.25757 0.011153
+0.249315 0.283277 0.000709268
+
+0.318995 0.25757 0.011153
+0.270877 0.307776 0.0125875
+0.339694 0.274284 0.0334768
+
+0.288454 0.327747 0.0349113
+0.339694 0.274284 0.0334768
+0.270877 0.307776 0.0125875
+
+0.339694 0.274284 0.0334768
+0.288454 0.327747 0.0349113
+0.353204 0.285193 0.0635535
+
+0.299926 0.340782 0.064988
+0.353204 0.285193 0.0635535
+0.288454 0.327747 0.0349113
+
+0.353204 0.285193 0.0635535
+0.299926 0.340782 0.064988
+0.357896 0.288981 0.0977555
+
+0.30391 0.345309 0.09919
+0.357896 0.288981 0.0977555
+0.299926 0.340782 0.064988
+
+0.30391 0.345309 0.09919
+0.241181 0.391703 0.0892926
+0.299926 0.340782 0.133392
+
+0.238019 0.386568 0.123495
+0.299926 0.340782 0.133392
+0.241181 0.391703 0.0892926
+
+0.299926 0.340782 0.133392
+0.238019 0.386568 0.123495
+0.288454 0.327747 0.163469
+
+0.228915 0.371781 0.153571
+0.288454 0.327747 0.163469
+0.238019 0.386568 0.123495
+
+0.288454 0.327747 0.163469
+0.228915 0.371781 0.153571
+0.270877 0.307776 0.185793
+
+0.214966 0.349127 0.175895
+0.270877 0.307776 0.185793
+0.228915 0.371781 0.153571
+
+0.270877 0.307776 0.185793
+0.214966 0.349127 0.175895
+0.249315 0.283277 0.197671
+
+0.197855 0.321337 0.187773
+0.249315 0.283277 0.197671
+0.214966 0.349127 0.175895
+
+0.249315 0.283277 0.197671
+0.197855 0.321337 0.187773
+0.22637 0.257207 0.197671
+
+0.179646 0.291764 0.187773
+0.22637 0.257207 0.197671
+0.197855 0.321337 0.187773
+
+0.22637 0.257207 0.197671
+0.179646 0.291764 0.187773
+0.204809 0.232708 0.185793
+
+0.162535 0.263974 0.175895
+0.204809 0.232708 0.185793
+0.179646 0.291764 0.187773
+
+0.204809 0.232708 0.185793
+0.162535 0.263974 0.175895
+0.187232 0.212737 0.163469
+
+0.148586 0.24132 0.153571
+0.187232 0.212737 0.163469
+0.162535 0.263974 0.175895
+
+0.187232 0.212737 0.163469
+0.148586 0.24132 0.153571
+0.17576 0.199702 0.133392
+
+0.139482 0.226533 0.123495
+0.17576 0.199702 0.133392
+0.148586 0.24132 0.153571
+
+0.17576 0.199702 0.133392
+0.139482 0.226533 0.123495
+0.171775 0.195175 0.09919
+
+0.13632 0.221398 0.0892926
+0.171775 0.195175 0.09919
+0.139482 0.226533 0.123495
+
+0.171775 0.195175 0.09919
+0.13632 0.221398 0.0892926
+0.17576 0.199702 0.064988
+
+0.139482 0.226533 0.0550906
+0.17576 0.199702 0.064988
+0.13632 0.221398 0.0892926
+
+0.17576 0.199702 0.064988
+0.139482 0.226533 0.0550906
+0.187232 0.212737 0.0349113
+
+0.148586 0.24132 0.0250138
+0.187232 0.212737 0.0349113
+0.139482 0.226533 0.0550906
+
+0.187232 0.212737 0.0349113
+0.148586 0.24132 0.0250138
+0.204809 0.232708 0.0125875
+
+0.162535 0.263974 0.00269005
+0.204809 0.232708 0.0125875
+0.148586 0.24132 0.0250138
+
+0.204809 0.232708 0.0125875
+0.162535 0.263974 0.00269005
+0.22637 0.257207 0.000709268
+
+0.179646 0.291764 -0.00918819
+0.22637 0.257207 0.000709268
+0.162535 0.263974 0.00269005
+
+0.22637 0.257207 0.000709268
+0.179646 0.291764 -0.00918819
+0.249315 0.283277 0.000709268
+
+0.197855 0.321337 -0.00918819
+0.249315 0.283277 0.000709268
+0.179646 0.291764 -0.00918819
+
+0.249315 0.283277 0.000709268
+0.197855 0.321337 -0.00918819
+0.270877 0.307776 0.0125875
+
+0.214966 0.349127 0.00269005
+0.270877 0.307776 0.0125875
+0.197855 0.321337 -0.00918819
+
+0.270877 0.307776 0.0125875
+0.214966 0.349127 0.00269005
+0.288454 0.327747 0.0349113
+
+0.228915 0.371781 0.0250138
+0.288454 0.327747 0.0349113
+0.214966 0.349127 0.00269005
+
+0.288454 0.327747 0.0349113
+0.228915 0.371781 0.0250138
+0.299926 0.340782 0.064988
+
+0.238019 0.386568 0.0550906
+0.299926 0.340782 0.064988
+0.228915 0.371781 0.0250138
+
+0.299926 0.340782 0.064988
+0.238019 0.386568 0.0550906
+0.30391 0.345309 0.09919
+
+0.241181 0.391703 0.0892926
+0.30391 0.345309 0.09919
+0.238019 0.386568 0.0550906
+
+0.241181 0.391703 0.0892926
+0.171514 0.426829 0.0691939
+0.238019 0.386568 0.123495
+
+0.169265 0.421233 0.103396
+0.238019 0.386568 0.123495
+0.171514 0.426829 0.0691939
+
+0.238019 0.386568 0.123495
+0.169265 0.421233 0.103396
+0.228915 0.371781 0.153571
+
+0.162791 0.40512 0.133473
+0.228915 0.371781 0.153571
+0.169265 0.421233 0.103396
+
+0.228915 0.371781 0.153571
+0.162791 0.40512 0.133473
+0.214966 0.349127 0.175895
+
+0.152871 0.380435 0.155796
+0.214966 0.349127 0.175895
+0.162791 0.40512 0.133473
+
+0.214966 0.349127 0.175895
+0.152871 0.380435 0.155796
+0.197855 0.321337 0.187773
+
+0.140703 0.350153 0.167675
+0.197855 0.321337 0.187773
+0.152871 0.380435 0.155796
+
+0.197855 0.321337 0.187773
+0.140703 0.350153 0.167675
+0.179646 0.291764 0.187773
+
+0.127754 0.317927 0.167675
+0.179646 0.291764 0.187773
+0.140703 0.350153 0.167675
+
+0.179646 0.291764 0.187773
+0.127754 0.317927 0.167675
+0.162535 0.263974 0.175895
+
+0.115586 0.287646 0.155796
+0.162535 0.263974 0.175895
+0.127754 0.317927 0.167675
+
+0.162535 0.263974 0.175895
+0.115586 0.287646 0.155796
+0.148586 0.24132 0.153571
+
+0.105666 0.26296 0.133473
+0.148586 0.24132 0.153571
+0.115586 0.287646 0.155796
+
+0.148586 0.24132 0.153571
+0.105666 0.26296 0.133473
+0.139482 0.226533 0.123495
+
+0.0991913 0.246847 0.103396
+0.139482 0.226533 0.123495
+0.105666 0.26296 0.133473
+
+0.139482 0.226533 0.123495
+0.0991913 0.246847 0.103396
+0.13632 0.221398 0.0892926
+
+0.0969427 0.241251 0.0691939
+0.13632 0.221398 0.0892926
+0.0991913 0.246847 0.103396
+
+0.13632 0.221398 0.0892926
+0.0969427 0.241251 0.0691939
+0.139482 0.226533 0.0550906
+
+0.0991913 0.246847 0.0349919
+0.139482 0.226533 0.0550906
+0.0969427 0.241251 0.0691939
+
+0.139482 0.226533 0.0550906
+0.0991913 0.246847 0.0349919
+0.148586 0.24132 0.0250138
+
+0.105666 0.26296 0.00491513
+0.148586 0.24132 0.0250138
+0.0991913 0.246847 0.0349919
+
+0.148586 0.24132 0.0250138
+0.105666 0.26296 0.00491513
+0.162535 0.263974 0.00269005
+
+0.115586 0.287646 -0.0174087
+0.162535 0.263974 0.00269005
+0.105666 0.26296 0.00491513
+
+0.162535 0.263974 0.00269005
+0.115586 0.287646 -0.0174087
+0.179646 0.291764 -0.00918819
+
+0.127754 0.317927 -0.0292869
+0.179646 0.291764 -0.00918819
+0.115586 0.287646 -0.0174087
+
+0.179646 0.291764 -0.00918819
+0.127754 0.317927 -0.0292869
+0.197855 0.321337 -0.00918819
+
+0.140703 0.350153 -0.0292869
+0.197855 0.321337 -0.00918819
+0.127754 0.317927 -0.0292869
+
+0.197855 0.321337 -0.00918819
+0.140703 0.350153 -0.0292869
+0.214966 0.349127 0.00269005
+
+0.152871 0.380435 -0.0174087
+0.214966 0.349127 0.00269005
+0.140703 0.350153 -0.0292869
+
+0.214966 0.349127 0.00269005
+0.152871 0.380435 -0.0174087
+0.228915 0.371781 0.0250138
+
+0.162791 0.40512 0.00491513
+0.228915 0.371781 0.0250138
+0.152871 0.380435 -0.0174087
+
+0.228915 0.371781 0.0250138
+0.162791 0.40512 0.00491513
+0.238019 0.386568 0.0550906
+
+0.169265 0.421233 0.0349919
+0.238019 0.386568 0.0550906
+0.162791 0.40512 0.00491513
+
+0.238019 0.386568 0.0550906
+0.169265 0.421233 0.0349919
+0.241181 0.391703 0.0892926
+
+0.171514 0.426829 0.0691939
+0.241181 0.391703 0.0892926
+0.169265 0.421233 0.0349919
+
+0.171514 0.426829 0.0691939
+0.0969125 0.449675 0.0411901
+0.169265 0.421233 0.103396
+
+0.0956419 0.44378 0.0753921
+0.169265 0.421233 0.103396
+0.0969125 0.449675 0.0411901
+
+0.169265 0.421233 0.103396
+0.0956419 0.44378 0.0753921
+0.162791 0.40512 0.133473
+
+0.0919835 0.426805 0.105469
+0.162791 0.40512 0.133473
+0.0956419 0.44378 0.0753921
+
+0.162791 0.40512 0.133473
+0.0919835 0.426805 0.105469
+0.152871 0.380435 0.155796
+
+0.0863785 0.400798 0.127793
+0.152871 0.380435 0.155796
+0.0919835 0.426805 0.105469
+
+0.152871 0.380435 0.155796
+0.0863785 0.400798 0.127793
+0.140703 0.350153 0.167675
+
+0.0795029 0.368895 0.139671
+0.140703 0.350153 0.167675
+0.0863785 0.400798 0.127793
+
+0.140703 0.350153 0.167675
+0.0795029 0.368895 0.139671
+0.127754 0.317927 0.167675
+
+0.0721861 0.334945 0.139671
+0.127754 0.317927 0.167675
+0.0795029 0.368895 0.139671
+
+0.127754 0.317927 0.167675
+0.0721861 0.334945 0.139671
+0.115586 0.287646 0.155796
+
+0.0653106 0.303042 0.127793
+0.115586 0.287646 0.155796
+0.0721861 0.334945 0.139671
+
+0.115586 0.287646 0.155796
+0.0653106 0.303042 0.127793
+0.105666 0.26296 0.133473
+
+0.0597056 0.277035 0.105469
+0.105666 0.26296 0.133473
+0.0653106 0.303042 0.127793
+
+0.105666 0.26296 0.133473
+0.0597056 0.277035 0.105469
+0.0991913 0.246847 0.103396
+
+0.0560472 0.26006 0.0753921
+0.0991913 0.246847 0.103396
+0.0597056 0.277035 0.105469
+
+0.0991913 0.246847 0.103396
+0.0560472 0.26006 0.0753921
+0.0969427 0.241251 0.0691939
+
+0.0547766 0.254164 0.0411901
+0.0969427 0.241251 0.0691939
+0.0560472 0.26006 0.0753921
+
+0.0969427 0.241251 0.0691939
+0.0547766 0.254164 0.0411901
+0.0991913 0.246847 0.0349919
+
+0.0560472 0.26006 0.00698811
+0.0991913 0.246847 0.0349919
+0.0547766 0.254164 0.0411901
+
+0.0991913 0.246847 0.0349919
+0.0560472 0.26006 0.00698811
+0.105666 0.26296 0.00491513
+
+0.0597056 0.277035 -0.0230886
+0.105666 0.26296 0.00491513
+0.0560472 0.26006 0.00698811
+
+0.105666 0.26296 0.00491513
+0.0597056 0.277035 -0.0230886
+0.115586 0.287646 -0.0174087
+
+0.0653106 0.303042 -0.0454124
+0.115586 0.287646 -0.0174087
+0.0597056 0.277035 -0.0230886
+
+0.115586 0.287646 -0.0174087
+0.0653106 0.303042 -0.0454124
+0.127754 0.317927 -0.0292869
+
+0.0721861 0.334945 -0.0572907
+0.127754 0.317927 -0.0292869
+0.0653106 0.303042 -0.0454124
+
+0.127754 0.317927 -0.0292869
+0.0721861 0.334945 -0.0572907
+0.140703 0.350153 -0.0292869
+
+0.0795029 0.368895 -0.0572907
+0.140703 0.350153 -0.0292869
+0.0721861 0.334945 -0.0572907
+
+0.140703 0.350153 -0.0292869
+0.0795029 0.368895 -0.0572907
+0.152871 0.380435 -0.0174087
+
+0.0863785 0.400798 -0.0454124
+0.152871 0.380435 -0.0174087
+0.0795029 0.368895 -0.0572907
+
+0.152871 0.380435 -0.0174087
+0.0863785 0.400798 -0.0454124
+0.162791 0.40512 0.00491513
+
+0.0919835 0.426805 -0.0230886
+0.162791 0.40512 0.00491513
+0.0863785 0.400798 -0.0454124
+
+0.162791 0.40512 0.00491513
+0.0919835 0.426805 -0.0230886
+0.169265 0.421233 0.0349919
+
+0.0956419 0.44378 0.00698811
+0.169265 0.421233 0.0349919
+0.0919835 0.426805 -0.0230886
+
+0.169265 0.421233 0.0349919
+0.0956419 0.44378 0.00698811
+0.171514 0.426829 0.0691939
+
+0.0969125 0.449675 0.0411901
+0.171514 0.426829 0.0691939
+0.0956419 0.44378 0.00698811
+
+0.0969125 0.449675 0.0411901
+0.019523 0.459586 0.00848059
+0.0956419 0.44378 0.0753921
+
+0.019267 0.45356 0.0426826
+0.0956419 0.44378 0.0753921
+0.019523 0.459586 0.00848059
+
+0.0956419 0.44378 0.0753921
+0.019267 0.45356 0.0426826
+0.0919835 0.426805 0.105469
+
+0.01853 0.436211 0.0727594
+0.0919835 0.426805 0.105469
+0.019267 0.45356 0.0426826
+
+0.0919835 0.426805 0.105469
+0.01853 0.436211 0.0727594
+0.0863785 0.400798 0.127793
+
+0.0174009 0.409631 0.0950831
+0.0863785 0.400798 0.127793
+0.01853 0.436211 0.0727594
+
+0.0863785 0.400798 0.127793
+0.0174009 0.409631 0.0950831
+0.0795029 0.368895 0.139671
+
+0.0160158 0.377025 0.106961
+0.0795029 0.368895 0.139671
+0.0174009 0.409631 0.0950831
+
+0.0795029 0.368895 0.139671
+0.0160158 0.377025 0.106961
+0.0721861 0.334945 0.139671
+
+0.0145418 0.342326 0.106961
+0.0721861 0.334945 0.139671
+0.0160158 0.377025 0.106961
+
+0.0721861 0.334945 0.139671
+0.0145418 0.342326 0.106961
+0.0653106 0.303042 0.127793
+
+0.0131568 0.309721 0.0950831
+0.0653106 0.303042 0.127793
+0.0145418 0.342326 0.106961
+
+0.0653106 0.303042 0.127793
+0.0131568 0.309721 0.0950831
+0.0597056 0.277035 0.105469
+
+0.0120276 0.28314 0.0727594
+0.0597056 0.277035 0.105469
+0.0131568 0.309721 0.0950831
+
+0.0597056 0.277035 0.105469
+0.0120276 0.28314 0.0727594
+0.0560472 0.26006 0.0753921
+
+0.0112907 0.265791 0.0426826
+0.0560472 0.26006 0.0753921
+0.0120276 0.28314 0.0727594
+
+0.0560472 0.26006 0.0753921
+0.0112907 0.265791 0.0426826
+0.0547766 0.254164 0.0411901
+
+0.0110347 0.259766 0.00848059
+0.0547766 0.254164 0.0411901
+0.0112907 0.265791 0.0426826
+
+0.0547766 0.254164 0.0411901
+0.0110347 0.259766 0.00848059
+0.0560472 0.26006 0.00698811
+
+0.0112907 0.265791 -0.0257214
+0.0560472 0.26006 0.00698811
+0.0110347 0.259766 0.00848059
+
+0.0560472 0.26006 0.00698811
+0.0112907 0.265791 -0.0257214
+0.0597056 0.277035 -0.0230886
+
+0.0120276 0.28314 -0.0557982
+0.0597056 0.277035 -0.0230886
+0.0112907 0.265791 -0.0257214
+
+0.0597056 0.277035 -0.0230886
+0.0120276 0.28314 -0.0557982
+0.0653106 0.303042 -0.0454124
+
+0.0131568 0.309721 -0.0781219
+0.0653106 0.303042 -0.0454124
+0.0120276 0.28314 -0.0557982
+
+0.0653106 0.303042 -0.0454124
+0.0131568 0.309721 -0.0781219
+0.0721861 0.334945 -0.0572907
+
+0.0145418 0.342326 -0.0900002
+0.0721861 0.334945 -0.0572907
+0.0131568 0.309721 -0.0781219
+
+0.0721861 0.334945 -0.0572907
+0.0145418 0.342326 -0.0900002
+0.0795029 0.368895 -0.0572907
+
+0.0160158 0.377025 -0.0900002
+0.0795029 0.368895 -0.0572907
+0.0145418 0.342326 -0.0900002
+
+0.0795029 0.368895 -0.0572907
+0.0160158 0.377025 -0.0900002
+0.0863785 0.400798 -0.0454124
+
+0.0174009 0.409631 -0.0781219
+0.0863785 0.400798 -0.0454124
+0.0160158 0.377025 -0.0900002
+
+0.0863785 0.400798 -0.0454124
+0.0174009 0.409631 -0.0781219
+0.0919835 0.426805 -0.0230886
+
+0.01853 0.436211 -0.0557982
+0.0919835 0.426805 -0.0230886
+0.0174009 0.409631 -0.0781219
+
+0.0919835 0.426805 -0.0230886
+0.01853 0.436211 -0.0557982
+0.0956419 0.44378 0.00698811
+
+0.019267 0.45356 -0.0257214
+0.0956419 0.44378 0.00698811
+0.01853 0.436211 -0.0557982
+
+0.0956419 0.44378 0.00698811
+0.019267 0.45356 -0.0257214
+0.0969125 0.449675 0.0411901
+
+0.019523 0.459586 0.00848059
+0.0969125 0.449675 0.0411901
+0.019267 0.45356 -0.0257214
+
+0.019523 0.459586 0.00848059
+-0.0584282 0.456274 -0.0251978
+0.019267 0.45356 0.0426826
+
+-0.0576622 0.450292 0.00900421
+0.019267 0.45356 0.0426826
+-0.0584282 0.456274 -0.0251978
+
+0.019267 0.45356 0.0426826
+-0.0576622 0.450292 0.00900421
+0.01853 0.436211 0.0727594
+
+-0.0554565 0.433068 0.039081
+0.01853 0.436211 0.0727594
+-0.0576622 0.450292 0.00900421
+
+0.01853 0.436211 0.0727594
+-0.0554565 0.433068 0.039081
+0.0174009 0.409631 0.0950831
+
+-0.0520773 0.406679 0.0614047
+0.0174009 0.409631 0.0950831
+-0.0554565 0.433068 0.039081
+
+0.0174009 0.409631 0.0950831
+-0.0520773 0.406679 0.0614047
+0.0160158 0.377025 0.106961
+
+-0.0479321 0.374308 0.073283
+0.0160158 0.377025 0.106961
+-0.0520773 0.406679 0.0614047
+
+0.0160158 0.377025 0.106961
+-0.0479321 0.374308 0.073283
+0.0145418 0.342326 0.106961
+
+-0.0435208 0.33986 0.073283
+0.0145418 0.342326 0.106961
+-0.0479321 0.374308 0.073283
+
+0.0145418 0.342326 0.106961
+-0.0435208 0.33986 0.073283
+0.0131568 0.309721 0.0950831
+
+-0.0393755 0.307489 0.0614047
+0.0131568 0.309721 0.0950831
+-0.0435208 0.33986 0.073283
+
+0.0131568 0.309721 0.0950831
+-0.0393755 0.307489 0.0614047
+0.0120276 0.28314 0.0727594
+
+-0.0359963 0.2811 0.039081
+0.0120276 0.28314 0.0727594
+-0.0393755 0.307489 0.0614047
+
+0.0120276 0.28314 0.0727594
+-0.0359963 0.2811 0.039081
+0.0112907 0.265791 0.0426826
+
+-0.0337906 0.263876 0.00900421
+0.0112907 0.265791 0.0426826
+-0.0359963 0.2811 0.039081
+
+0.0112907 0.265791 0.0426826
+-0.0337906 0.263876 0.00900421
+0.0110347 0.259766 0.00848059
+
+-0.0330246 0.257894 -0.0251978
+0.0110347 0.259766 0.00848059
+-0.0337906 0.263876 0.00900421
+
+0.0110347 0.259766 0.00848059
+-0.0330246 0.257894 -0.0251978
+0.0112907 0.265791 -0.0257214
+
+-0.0337906 0.263876 -0.0593998
+0.0112907 0.265791 -0.0257214
+-0.0330246 0.257894 -0.0251978
+
+0.0112907 0.265791 -0.0257214
+-0.0337906 0.263876 -0.0593998
+0.0120276 0.28314 -0.0557982
+
+-0.0359963 0.2811 -0.0894766
+0.0120276 0.28314 -0.0557982
+-0.0337906 0.263876 -0.0593998
+
+0.0120276 0.28314 -0.0557982
+-0.0359963 0.2811 -0.0894766
+0.0131568 0.309721 -0.0781219
+
+-0.0393755 0.307489 -0.1118
+0.0131568 0.309721 -0.0781219
+-0.0359963 0.2811 -0.0894766
+
+0.0131568 0.309721 -0.0781219
+-0.0393755 0.307489 -0.1118
+0.0145418 0.342326 -0.0900002
+
+-0.0435208 0.33986 -0.123679
+0.0145418 0.342326 -0.0900002
+-0.0393755 0.307489 -0.1118
+
+0.0145418 0.342326 -0.0900002
+-0.0435208 0.33986 -0.123679
+0.0160158 0.377025 -0.0900002
+
+-0.0479321 0.374308 -0.123679
+0.0160158 0.377025 -0.0900002
+-0.0435208 0.33986 -0.123679
+
+0.0160158 0.377025 -0.0900002
+-0.0479321 0.374308 -0.123679
+0.0174009 0.409631 -0.0781219
+
+-0.0520773 0.406679 -0.1118
+0.0174009 0.409631 -0.0781219
+-0.0479321 0.374308 -0.123679
+
+0.0174009 0.409631 -0.0781219
+-0.0520773 0.406679 -0.1118
+0.01853 0.436211 -0.0557982
+
+-0.0554565 0.433068 -0.0894766
+0.01853 0.436211 -0.0557982
+-0.0520773 0.406679 -0.1118
+
+0.01853 0.436211 -0.0557982
+-0.0554565 0.433068 -0.0894766
+0.019267 0.45356 -0.0257214
+
+-0.0576622 0.450292 -0.0593998
+0.019267 0.45356 -0.0257214
+-0.0554565 0.433068 -0.0894766
+
+0.019267 0.45356 -0.0257214
+-0.0576622 0.450292 -0.0593998
+0.019523 0.459586 0.00848059
+
+-0.0584282 0.456274 -0.0251978
+0.019523 0.459586 0.00848059
+-0.0576622 0.450292 -0.0593998
+
+-0.0584282 0.456274 -0.0251978
+-0.134698 0.439837 -0.0559975
+-0.0576622 0.450292 0.00900421
+
+-0.132933 0.43407 -0.0217955
+-0.0576622 0.450292 0.00900421
+-0.134698 0.439837 -0.0559975
+
+-0.0576622 0.450292 0.00900421
+-0.132933 0.43407 -0.0217955
+-0.0554565 0.433068 0.039081
+
+-0.127848 0.417467 0.00828128
+-0.0554565 0.433068 0.039081
+-0.132933 0.43407 -0.0217955
+
+-0.0554565 0.433068 0.039081
+-0.127848 0.417467 0.00828128
+-0.0520773 0.406679 0.0614047
+
+-0.120057 0.392028 0.0306051
+-0.0520773 0.406679 0.0614047
+-0.127848 0.417467 0.00828128
+
+-0.0520773 0.406679 0.0614047
+-0.120057 0.392028 0.0306051
+-0.0479321 0.374308 0.073283
+
+-0.110501 0.360824 0.0424833
+-0.0479321 0.374308 0.073283
+-0.120057 0.392028 0.0306051
+
+-0.0479321 0.374308 0.073283
+-0.110501 0.360824 0.0424833
+-0.0435208 0.33986 0.073283
+
+-0.100331 0.327616 0.0424833
+-0.0435208 0.33986 0.073283
+-0.110501 0.360824 0.0424833
+
+-0.0435208 0.33986 0.073283
+-0.100331 0.327616 0.0424833
+-0.0393755 0.307489 0.0614047
+
+-0.0907751 0.296412 0.0306051
+-0.0393755 0.307489 0.0614047
+-0.100331 0.327616 0.0424833
+
+-0.0393755 0.307489 0.0614047
+-0.0907751 0.296412 0.0306051
+-0.0359963 0.2811 0.039081
+
+-0.0829847 0.270973 0.00828128
+-0.0359963 0.2811 0.039081
+-0.0907751 0.296412 0.0306051
+
+-0.0359963 0.2811 0.039081
+-0.0829847 0.270973 0.00828128
+-0.0337906 0.263876 0.00900421
+
+-0.0778999 0.25437 -0.0217955
+-0.0337906 0.263876 0.00900421
+-0.0829847 0.270973 0.00828128
+
+-0.0337906 0.263876 0.00900421
+-0.0778999 0.25437 -0.0217955
+-0.0330246 0.257894 -0.0251978
+
+-0.0761339 0.248603 -0.0559975
+-0.0330246 0.257894 -0.0251978
+-0.0778999 0.25437 -0.0217955
+
+-0.0330246 0.257894 -0.0251978
+-0.0761339 0.248603 -0.0559975
+-0.0337906 0.263876 -0.0593998
+
+-0.0778999 0.25437 -0.0901995
+-0.0337906 0.263876 -0.0593998
+-0.0761339 0.248603 -0.0559975
+
+-0.0337906 0.263876 -0.0593998
+-0.0778999 0.25437 -0.0901995
+-0.0359963 0.2811 -0.0894766
+
+-0.0829847 0.270973 -0.120276
+-0.0359963 0.2811 -0.0894766
+-0.0778999 0.25437 -0.0901995
+
+-0.0359963 0.2811 -0.0894766
+-0.0829847 0.270973 -0.120276
+-0.0393755 0.307489 -0.1118
+
+-0.0907751 0.296412 -0.1426
+-0.0393755 0.307489 -0.1118
+-0.0829847 0.270973 -0.120276
+
+-0.0393755 0.307489 -0.1118
+-0.0907751 0.296412 -0.1426
+-0.0435208 0.33986 -0.123679
+
+-0.100331 0.327616 -0.154478
+-0.0435208 0.33986 -0.123679
+-0.0907751 0.296412 -0.1426
+
+-0.0435208 0.33986 -0.123679
+-0.100331 0.327616 -0.154478
+-0.0479321 0.374308 -0.123679
+
+-0.110501 0.360824 -0.154478
+-0.0479321 0.374308 -0.123679
+-0.100331 0.327616 -0.154478
+
+-0.0479321 0.374308 -0.123679
+-0.110501 0.360824 -0.154478
+-0.0520773 0.406679 -0.1118
+
+-0.120057 0.392028 -0.1426
+-0.0520773 0.406679 -0.1118
+-0.110501 0.360824 -0.154478
+
+-0.0520773 0.406679 -0.1118
+-0.120057 0.392028 -0.1426
+-0.0554565 0.433068 -0.0894766
+
+-0.127848 0.417467 -0.120276
+-0.0554565 0.433068 -0.0894766
+-0.120057 0.392028 -0.1426
+
+-0.0554565 0.433068 -0.0894766
+-0.127848 0.417467 -0.120276
+-0.0576622 0.450292 -0.0593998
+
+-0.132933 0.43407 -0.0901995
+-0.0576622 0.450292 -0.0593998
+-0.127848 0.417467 -0.120276
+
+-0.0576622 0.450292 -0.0593998
+-0.132933 0.43407 -0.0901995
+-0.0584282 0.456274 -0.0251978
+
+-0.134698 0.439837 -0.0559975
+-0.0584282 0.456274 -0.0251978
+-0.132933 0.43407 -0.0901995
+
+-0.134698 0.439837 -0.0559975
+-0.207094 0.410746 -0.0803997
+-0.132933 0.43407 -0.0217955
+
+-0.204379 0.405361 -0.0461977
+-0.132933 0.43407 -0.0217955
+-0.207094 0.410746 -0.0803997
+
+-0.132933 0.43407 -0.0217955
+-0.204379 0.405361 -0.0461977
+-0.127848 0.417467 0.00828128
+
+-0.196561 0.389855 -0.016121
+-0.127848 0.417467 0.00828128
+-0.204379 0.405361 -0.0461977
+
+-0.127848 0.417467 0.00828128
+-0.196561 0.389855 -0.016121
+-0.120057 0.392028 0.0306051
+
+-0.184584 0.3661 0.00620283
+-0.120057 0.392028 0.0306051
+-0.196561 0.389855 -0.016121
+
+-0.120057 0.392028 0.0306051
+-0.184584 0.3661 0.00620283
+-0.110501 0.360824 0.0424833
+
+-0.169891 0.336959 0.0180811
+-0.110501 0.360824 0.0424833
+-0.184584 0.3661 0.00620283
+
+-0.110501 0.360824 0.0424833
+-0.169891 0.336959 0.0180811
+-0.100331 0.327616 0.0424833
+
+-0.154256 0.305948 0.0180811
+-0.100331 0.327616 0.0424833
+-0.169891 0.336959 0.0180811
+
+-0.100331 0.327616 0.0424833
+-0.154256 0.305948 0.0180811
+-0.0907751 0.296412 0.0306051
+
+-0.139563 0.276807 0.00620283
+-0.0907751 0.296412 0.0306051
+-0.154256 0.305948 0.0180811
+
+-0.0907751 0.296412 0.0306051
+-0.139563 0.276807 0.00620283
+-0.0829847 0.270973 0.00828128
+
+-0.127586 0.253051 -0.016121
+-0.0829847 0.270973 0.00828128
+-0.139563 0.276807 0.00620283
+
+-0.0829847 0.270973 0.00828128
+-0.127586 0.253051 -0.016121
+-0.0778999 0.25437 -0.0217955
+
+-0.119768 0.237546 -0.0461977
+-0.0778999 0.25437 -0.0217955
+-0.127586 0.253051 -0.016121
+
+-0.0778999 0.25437 -0.0217955
+-0.119768 0.237546 -0.0461977
+-0.0761339 0.248603 -0.0559975
+
+-0.117053 0.232161 -0.0803997
+-0.0761339 0.248603 -0.0559975
+-0.119768 0.237546 -0.0461977
+
+-0.0761339 0.248603 -0.0559975
+-0.117053 0.232161 -0.0803997
+-0.0778999 0.25437 -0.0901995
+
+-0.119768 0.237546 -0.114602
+-0.0778999 0.25437 -0.0901995
+-0.117053 0.232161 -0.0803997
+
+-0.0778999 0.25437 -0.0901995
+-0.119768 0.237546 -0.114602
+-0.0829847 0.270973 -0.120276
+
+-0.127586 0.253051 -0.144678
+-0.0829847 0.270973 -0.120276
+-0.119768 0.237546 -0.114602
+
+-0.0829847 0.270973 -0.120276
+-0.127586 0.253051 -0.144678
+-0.0907751 0.296412 -0.1426
+
+-0.139563 0.276807 -0.167002
+-0.0907751 0.296412 -0.1426
+-0.127586 0.253051 -0.144678
+
+-0.0907751 0.296412 -0.1426
+-0.139563 0.276807 -0.167002
+-0.100331 0.327616 -0.154478
+
+-0.154256 0.305948 -0.17888
+-0.100331 0.327616 -0.154478
+-0.139563 0.276807 -0.167002
+
+-0.100331 0.327616 -0.154478
+-0.154256 0.305948 -0.17888
+-0.110501 0.360824 -0.154478
+
+-0.169891 0.336959 -0.17888
+-0.110501 0.360824 -0.154478
+-0.154256 0.305948 -0.17888
+
+-0.110501 0.360824 -0.154478
+-0.169891 0.336959 -0.17888
+-0.120057 0.392028 -0.1426
+
+-0.184584 0.3661 -0.167002
+-0.120057 0.392028 -0.1426
+-0.169891 0.336959 -0.17888
+
+-0.120057 0.392028 -0.1426
+-0.184584 0.3661 -0.167002
+-0.127848 0.417467 -0.120276
+
+-0.196561 0.389855 -0.144678
+-0.127848 0.417467 -0.120276
+-0.184584 0.3661 -0.167002
+
+-0.127848 0.417467 -0.120276
+-0.196561 0.389855 -0.144678
+-0.132933 0.43407 -0.0901995
+
+-0.204379 0.405361 -0.114602
+-0.132933 0.43407 -0.0901995
+-0.196561 0.389855 -0.144678
+
+-0.132933 0.43407 -0.0901995
+-0.204379 0.405361 -0.114602
+-0.134698 0.439837 -0.0559975
+
+-0.207094 0.410746 -0.0803997
+-0.134698 0.439837 -0.0559975
+-0.204379 0.405361 -0.114602
+
+-0.207094 0.410746 -0.0803997
+-0.273531 0.369839 -0.0956167
+-0.204379 0.405361 -0.0461977
+
+-0.269945 0.36499 -0.0614147
+-0.204379 0.405361 -0.0461977
+-0.273531 0.369839 -0.0956167
+
+-0.204379 0.405361 -0.0461977
+-0.269945 0.36499 -0.0614147
+-0.196561 0.389855 -0.016121
+
+-0.259619 0.351029 -0.0313379
+-0.196561 0.389855 -0.016121
+-0.269945 0.36499 -0.0614147
+
+-0.196561 0.389855 -0.016121
+-0.259619 0.351029 -0.0313379
+-0.184584 0.3661 0.00620283
+
+-0.2438 0.329639 -0.00901413
+-0.184584 0.3661 0.00620283
+-0.259619 0.351029 -0.0313379
+
+-0.184584 0.3661 0.00620283
+-0.2438 0.329639 -0.00901413
+-0.169891 0.336959 0.0180811
+
+-0.224394 0.3034 0.0028641
+-0.169891 0.336959 0.0180811
+-0.2438 0.329639 -0.00901413
+
+-0.169891 0.336959 0.0180811
+-0.224394 0.3034 0.0028641
+-0.154256 0.305948 0.0180811
+
+-0.203742 0.275478 0.0028641
+-0.154256 0.305948 0.0180811
+-0.224394 0.3034 0.0028641
+
+-0.154256 0.305948 0.0180811
+-0.203742 0.275478 0.0028641
+-0.139563 0.276807 0.00620283
+
+-0.184336 0.249239 -0.00901413
+-0.139563 0.276807 0.00620283
+-0.203742 0.275478 0.0028641
+
+-0.139563 0.276807 0.00620283
+-0.184336 0.249239 -0.00901413
+-0.127586 0.253051 -0.016121
+
+-0.168516 0.227849 -0.0313379
+-0.127586 0.253051 -0.016121
+-0.184336 0.249239 -0.00901413
+
+-0.127586 0.253051 -0.016121
+-0.168516 0.227849 -0.0313379
+-0.119768 0.237546 -0.0461977
+
+-0.158191 0.213888 -0.0614147
+-0.119768 0.237546 -0.0461977
+-0.168516 0.227849 -0.0313379
+
+-0.119768 0.237546 -0.0461977
+-0.158191 0.213888 -0.0614147
+-0.117053 0.232161 -0.0803997
+
+-0.154605 0.209039 -0.0956167
+-0.117053 0.232161 -0.0803997
+-0.158191 0.213888 -0.0614147
+
+-0.117053 0.232161 -0.0803997
+-0.154605 0.209039 -0.0956167
+-0.119768 0.237546 -0.114602
+
+-0.158191 0.213888 -0.129819
+-0.119768 0.237546 -0.114602
+-0.154605 0.209039 -0.0956167
+
+-0.119768 0.237546 -0.114602
+-0.158191 0.213888 -0.129819
+-0.127586 0.253051 -0.144678
+
+-0.168516 0.227849 -0.159895
+-0.127586 0.253051 -0.144678
+-0.158191 0.213888 -0.129819
+
+-0.127586 0.253051 -0.144678
+-0.168516 0.227849 -0.159895
+-0.139563 0.276807 -0.167002
+
+-0.184336 0.249239 -0.182219
+-0.139563 0.276807 -0.167002
+-0.168516 0.227849 -0.159895
+
+-0.139563 0.276807 -0.167002
+-0.184336 0.249239 -0.182219
+-0.154256 0.305948 -0.17888
+
+-0.203742 0.275478 -0.194097
+-0.154256 0.305948 -0.17888
+-0.184336 0.249239 -0.182219
+
+-0.154256 0.305948 -0.17888
+-0.203742 0.275478 -0.194097
+-0.169891 0.336959 -0.17888
+
+-0.224394 0.3034 -0.194097
+-0.169891 0.336959 -0.17888
+-0.203742 0.275478 -0.194097
+
+-0.169891 0.336959 -0.17888
+-0.224394 0.3034 -0.194097
+-0.184584 0.3661 -0.167002
+
+-0.2438 0.329639 -0.182219
+-0.184584 0.3661 -0.167002
+-0.224394 0.3034 -0.194097
+
+-0.184584 0.3661 -0.167002
+-0.2438 0.329639 -0.182219
+-0.196561 0.389855 -0.144678
+
+-0.259619 0.351029 -0.159895
+-0.196561 0.389855 -0.144678
+-0.2438 0.329639 -0.182219
+
+-0.196561 0.389855 -0.144678
+-0.259619 0.351029 -0.159895
+-0.204379 0.405361 -0.114602
+
+-0.269945 0.36499 -0.129819
+-0.204379 0.405361 -0.114602
+-0.259619 0.351029 -0.159895
+
+-0.204379 0.405361 -0.114602
+-0.269945 0.36499 -0.129819
+-0.207094 0.410746 -0.0803997
+
+-0.273531 0.369839 -0.0956167
+-0.207094 0.410746 -0.0803997
+-0.269945 0.36499 -0.129819
+
+-0.273531 0.369839 -0.0956167
+-0.3321 0.318292 -0.0999099
+-0.269945 0.36499 -0.0614147
+
+-0.327746 0.314119 -0.0657079
+-0.269945 0.36499 -0.0614147
+-0.3321 0.318292 -0.0999099
+
+-0.269945 0.36499 -0.0614147
+-0.327746 0.314119 -0.0657079
+-0.259619 0.351029 -0.0313379
+
+-0.315209 0.302104 -0.0356311
+-0.259619 0.351029 -0.0313379
+-0.327746 0.314119 -0.0657079
+
+-0.259619 0.351029 -0.0313379
+-0.315209 0.302104 -0.0356311
+-0.2438 0.329639 -0.00901413
+
+-0.296002 0.283695 -0.0133074
+-0.2438 0.329639 -0.00901413
+-0.315209 0.302104 -0.0356311
+
+-0.2438 0.329639 -0.00901413
+-0.296002 0.283695 -0.0133074
+-0.224394 0.3034 0.0028641
+
+-0.272441 0.261113 -0.00142912
+-0.224394 0.3034 0.0028641
+-0.296002 0.283695 -0.0133074
+
+-0.224394 0.3034 0.0028641
+-0.272441 0.261113 -0.00142912
+-0.203742 0.275478 0.0028641
+
+-0.247368 0.237083 -0.00142912
+-0.203742 0.275478 0.0028641
+-0.272441 0.261113 -0.00142912
+
+-0.203742 0.275478 0.0028641
+-0.247368 0.237083 -0.00142912
+-0.184336 0.249239 -0.00901413
+
+-0.223806 0.214501 -0.0133074
+-0.184336 0.249239 -0.00901413
+-0.247368 0.237083 -0.00142912
+
+-0.184336 0.249239 -0.00901413
+-0.223806 0.214501 -0.0133074
+-0.168516 0.227849 -0.0313379
+
+-0.204599 0.196092 -0.0356311
+-0.168516 0.227849 -0.0313379
+-0.223806 0.214501 -0.0133074
+
+-0.168516 0.227849 -0.0313379
+-0.204599 0.196092 -0.0356311
+-0.158191 0.213888 -0.0614147
+
+-0.192063 0.184077 -0.0657079
+-0.158191 0.213888 -0.0614147
+-0.204599 0.196092 -0.0356311
+
+-0.158191 0.213888 -0.0614147
+-0.192063 0.184077 -0.0657079
+-0.154605 0.209039 -0.0956167
+
+-0.187709 0.179904 -0.0999099
+-0.154605 0.209039 -0.0956167
+-0.192063 0.184077 -0.0657079
+
+-0.154605 0.209039 -0.0956167
+-0.187709 0.179904 -0.0999099
+-0.158191 0.213888 -0.129819
+
+-0.192063 0.184077 -0.134112
+-0.158191 0.213888 -0.129819
+-0.187709 0.179904 -0.0999099
+
+-0.158191 0.213888 -0.129819
+-0.192063 0.184077 -0.134112
+-0.168516 0.227849 -0.159895
+
+-0.204599 0.196092 -0.164189
+-0.168516 0.227849 -0.159895
+-0.192063 0.184077 -0.134112
+
+-0.168516 0.227849 -0.159895
+-0.204599 0.196092 -0.164189
+-0.184336 0.249239 -0.182219
+
+-0.223806 0.214501 -0.186512
+-0.184336 0.249239 -0.182219
+-0.204599 0.196092 -0.164189
+
+-0.184336 0.249239 -0.182219
+-0.223806 0.214501 -0.186512
+-0.203742 0.275478 -0.194097
+
+-0.247368 0.237083 -0.198391
+-0.203742 0.275478 -0.194097
+-0.223806 0.214501 -0.186512
+
+-0.203742 0.275478 -0.194097
+-0.247368 0.237083 -0.198391
+-0.224394 0.3034 -0.194097
+
+-0.272441 0.261113 -0.198391
+-0.224394 0.3034 -0.194097
+-0.247368 0.237083 -0.198391
+
+-0.224394 0.3034 -0.194097
+-0.272441 0.261113 -0.198391
+-0.2438 0.329639 -0.182219
+
+-0.296002 0.283695 -0.186512
+-0.2438 0.329639 -0.182219
+-0.272441 0.261113 -0.198391
+
+-0.2438 0.329639 -0.182219
+-0.296002 0.283695 -0.186512
+-0.259619 0.351029 -0.159895
+
+-0.315209 0.302104 -0.164189
+-0.259619 0.351029 -0.159895
+-0.296002 0.283695 -0.186512
+
+-0.259619 0.351029 -0.159895
+-0.315209 0.302104 -0.164189
+-0.269945 0.36499 -0.129819
+
+-0.327746 0.314119 -0.134112
+-0.269945 0.36499 -0.129819
+-0.315209 0.302104 -0.164189
+
+-0.269945 0.36499 -0.129819
+-0.327746 0.314119 -0.134112
+-0.273531 0.369839 -0.0956167
+
+-0.3321 0.318292 -0.0999099
+-0.273531 0.369839 -0.0956167
+-0.327746 0.314119 -0.134112
+
+-0.3321 0.318292 -0.0999099
+-0.381114 0.257588 -0.0927889
+-0.327746 0.314119 -0.0657079
+
+-0.376118 0.254211 -0.0585869
+-0.327746 0.314119 -0.0657079
+-0.381114 0.257588 -0.0927889
+
+-0.327746 0.314119 -0.0657079
+-0.376118 0.254211 -0.0585869
+-0.315209 0.302104 -0.0356311
+
+-0.361731 0.244487 -0.0285101
+-0.315209 0.302104 -0.0356311
+-0.376118 0.254211 -0.0585869
+
+-0.315209 0.302104 -0.0356311
+-0.361731 0.244487 -0.0285101
+-0.296002 0.283695 -0.0133074
+
+-0.339689 0.22959 -0.00618636
+-0.296002 0.283695 -0.0133074
+-0.361731 0.244487 -0.0285101
+
+-0.296002 0.283695 -0.0133074
+-0.339689 0.22959 -0.00618636
+-0.272441 0.261113 -0.00142912
+
+-0.31265 0.211315 0.00569187
+-0.272441 0.261113 -0.00142912
+-0.339689 0.22959 -0.00618636
+
+-0.272441 0.261113 -0.00142912
+-0.31265 0.211315 0.00569187
+-0.247368 0.237083 -0.00142912
+
+-0.283877 0.191867 0.00569187
+-0.247368 0.237083 -0.00142912
+-0.31265 0.211315 0.00569187
+
+-0.247368 0.237083 -0.00142912
+-0.283877 0.191867 0.00569187
+-0.223806 0.214501 -0.0133074
+
+-0.256838 0.173592 -0.00618636
+-0.223806 0.214501 -0.0133074
+-0.283877 0.191867 0.00569187
+
+-0.223806 0.214501 -0.0133074
+-0.256838 0.173592 -0.00618636
+-0.204599 0.196092 -0.0356311
+
+-0.234796 0.158694 -0.0285101
+-0.204599 0.196092 -0.0356311
+-0.256838 0.173592 -0.00618636
+
+-0.204599 0.196092 -0.0356311
+-0.234796 0.158694 -0.0285101
+-0.192063 0.184077 -0.0657079
+
+-0.220409 0.148971 -0.0585869
+-0.192063 0.184077 -0.0657079
+-0.234796 0.158694 -0.0285101
+
+-0.192063 0.184077 -0.0657079
+-0.220409 0.148971 -0.0585869
+-0.187709 0.179904 -0.0999099
+
+-0.215413 0.145593 -0.0927889
+-0.187709 0.179904 -0.0999099
+-0.220409 0.148971 -0.0585869
+
+-0.187709 0.179904 -0.0999099
+-0.215413 0.145593 -0.0927889
+-0.192063 0.184077 -0.134112
+
+-0.220409 0.148971 -0.126991
+-0.192063 0.184077 -0.134112
+-0.215413 0.145593 -0.0927889
+
+-0.192063 0.184077 -0.134112
+-0.220409 0.148971 -0.126991
+-0.204599 0.196092 -0.164189
+
+-0.234796 0.158694 -0.157068
+-0.204599 0.196092 -0.164189
+-0.220409 0.148971 -0.126991
+
+-0.204599 0.196092 -0.164189
+-0.234796 0.158694 -0.157068
+-0.223806 0.214501 -0.186512
+
+-0.256838 0.173592 -0.179391
+-0.223806 0.214501 -0.186512
+-0.234796 0.158694 -0.157068
+
+-0.223806 0.214501 -0.186512
+-0.256838 0.173592 -0.179391
+-0.247368 0.237083 -0.198391
+
+-0.283877 0.191867 -0.19127
+-0.247368 0.237083 -0.198391
+-0.256838 0.173592 -0.179391
+
+-0.247368 0.237083 -0.198391
+-0.283877 0.191867 -0.19127
+-0.272441 0.261113 -0.198391
+
+-0.31265 0.211315 -0.19127
+-0.272441 0.261113 -0.198391
+-0.283877 0.191867 -0.19127
+
+-0.272441 0.261113 -0.198391
+-0.31265 0.211315 -0.19127
+-0.296002 0.283695 -0.186512
+
+-0.339689 0.22959 -0.179391
+-0.296002 0.283695 -0.186512
+-0.31265 0.211315 -0.19127
+
+-0.296002 0.283695 -0.186512
+-0.339689 0.22959 -0.179391
+-0.315209 0.302104 -0.164189
+
+-0.361731 0.244487 -0.157068
+-0.315209 0.302104 -0.164189
+-0.339689 0.22959 -0.179391
+
+-0.315209 0.302104 -0.164189
+-0.361731 0.244487 -0.157068
+-0.327746 0.314119 -0.134112
+
+-0.376118 0.254211 -0.126991
+-0.327746 0.314119 -0.134112
+-0.361731 0.244487 -0.157068
+
+-0.327746 0.314119 -0.134112
+-0.376118 0.254211 -0.126991
+-0.3321 0.318292 -0.0999099
+
+-0.381114 0.257588 -0.0927889
+-0.3321 0.318292 -0.0999099
+-0.376118 0.254211 -0.126991
+
+-0.381114 0.257588 -0.0927889
+-0.419165 0.189475 -0.0750672
+-0.376118 0.254211 -0.0585869
+
+-0.41367 0.186991 -0.0408652
+-0.376118 0.254211 -0.0585869
+-0.419165 0.189475 -0.0750672
+
+-0.376118 0.254211 -0.0585869
+-0.41367 0.186991 -0.0408652
+-0.361731 0.244487 -0.0285101
+
+-0.397846 0.179838 -0.0107885
+-0.361731 0.244487 -0.0285101
+-0.41367 0.186991 -0.0408652
+
+-0.361731 0.244487 -0.0285101
+-0.397846 0.179838 -0.0107885
+-0.339689 0.22959 -0.00618636
+
+-0.373604 0.16888 0.0115353
+-0.339689 0.22959 -0.00618636
+-0.397846 0.179838 -0.0107885
+
+-0.339689 0.22959 -0.00618636
+-0.373604 0.16888 0.0115353
+-0.31265 0.211315 0.00569187
+
+-0.343866 0.155437 0.0234135
+-0.31265 0.211315 0.00569187
+-0.373604 0.16888 0.0115353
+
+-0.31265 0.211315 0.00569187
+-0.343866 0.155437 0.0234135
+-0.283877 0.191867 0.00569187
+
+-0.312219 0.141132 0.0234135
+-0.283877 0.191867 0.00569187
+-0.343866 0.155437 0.0234135
+
+-0.283877 0.191867 0.00569187
+-0.312219 0.141132 0.0234135
+-0.256838 0.173592 -0.00618636
+
+-0.282481 0.127689 0.0115353
+-0.256838 0.173592 -0.00618636
+-0.312219 0.141132 0.0234135
+
+-0.256838 0.173592 -0.00618636
+-0.282481 0.127689 0.0115353
+-0.234796 0.158694 -0.0285101
+
+-0.258238 0.116731 -0.0107885
+-0.234796 0.158694 -0.0285101
+-0.282481 0.127689 0.0115353
+
+-0.234796 0.158694 -0.0285101
+-0.258238 0.116731 -0.0107885
+-0.220409 0.148971 -0.0585869
+
+-0.242415 0.109578 -0.0408652
+-0.220409 0.148971 -0.0585869
+-0.258238 0.116731 -0.0107885
+
+-0.220409 0.148971 -0.0585869
+-0.242415 0.109578 -0.0408652
+-0.215413 0.145593 -0.0927889
+
+-0.236919 0.107094 -0.0750672
+-0.215413 0.145593 -0.0927889
+-0.242415 0.109578 -0.0408652
+
+-0.215413 0.145593 -0.0927889
+-0.236919 0.107094 -0.0750672
+-0.220409 0.148971 -0.126991
+
+-0.242415 0.109578 -0.109269
+-0.220409 0.148971 -0.126991
+-0.236919 0.107094 -0.0750672
+
+-0.220409 0.148971 -0.126991
+-0.242415 0.109578 -0.109269
+-0.234796 0.158694 -0.157068
+
+-0.258238 0.116731 -0.139346
+-0.234796 0.158694 -0.157068
+-0.242415 0.109578 -0.109269
+
+-0.234796 0.158694 -0.157068
+-0.258238 0.116731 -0.139346
+-0.256838 0.173592 -0.179391
+
+-0.282481 0.127689 -0.16167
+-0.256838 0.173592 -0.179391
+-0.258238 0.116731 -0.139346
+
+-0.256838 0.173592 -0.179391
+-0.282481 0.127689 -0.16167
+-0.283877 0.191867 -0.19127
+
+-0.312219 0.141132 -0.173548
+-0.283877 0.191867 -0.19127
+-0.282481 0.127689 -0.16167
+
+-0.283877 0.191867 -0.19127
+-0.312219 0.141132 -0.173548
+-0.31265 0.211315 -0.19127
+
+-0.343866 0.155437 -0.173548
+-0.31265 0.211315 -0.19127
+-0.312219 0.141132 -0.173548
+
+-0.31265 0.211315 -0.19127
+-0.343866 0.155437 -0.173548
+-0.339689 0.22959 -0.179391
+
+-0.373604 0.16888 -0.16167
+-0.339689 0.22959 -0.179391
+-0.343866 0.155437 -0.173548
+
+-0.339689 0.22959 -0.179391
+-0.373604 0.16888 -0.16167
+-0.361731 0.244487 -0.157068
+
+-0.397846 0.179838 -0.139346
+-0.361731 0.244487 -0.157068
+-0.373604 0.16888 -0.16167
+
+-0.361731 0.244487 -0.157068
+-0.397846 0.179838 -0.139346
+-0.376118 0.254211 -0.126991
+
+-0.41367 0.186991 -0.109269
+-0.376118 0.254211 -0.126991
+-0.397846 0.179838 -0.139346
+
+-0.376118 0.254211 -0.126991
+-0.41367 0.186991 -0.109269
+-0.381114 0.257588 -0.0927889
+
+-0.419165 0.189475 -0.0750672
+-0.381114 0.257588 -0.0927889
+-0.41367 0.186991 -0.109269
+
+-0.419165 0.189475 -0.0750672
+-0.445157 0.11591 -0.0487695
+-0.41367 0.186991 -0.0408652
+
+-0.439321 0.11439 -0.0145675
+-0.41367 0.186991 -0.0408652
+-0.445157 0.11591 -0.0487695
+
+-0.41367 0.186991 -0.0408652
+-0.439321 0.11439 -0.0145675
+-0.397846 0.179838 -0.0107885
+
+-0.422517 0.110015 0.0155093
+-0.397846 0.179838 -0.0107885
+-0.439321 0.11439 -0.0145675
+
+-0.397846 0.179838 -0.0107885
+-0.422517 0.110015 0.0155093
+-0.373604 0.16888 0.0115353
+
+-0.396771 0.103311 0.037833
+-0.373604 0.16888 0.0115353
+-0.422517 0.110015 0.0155093
+
+-0.373604 0.16888 0.0115353
+-0.396771 0.103311 0.037833
+-0.343866 0.155437 0.0234135
+
+-0.365188 0.0950877 0.0497113
+-0.343866 0.155437 0.0234135
+-0.396771 0.103311 0.037833
+
+-0.343866 0.155437 0.0234135
+-0.365188 0.0950877 0.0497113
+-0.312219 0.141132 0.0234135
+
+-0.331579 0.0863365 0.0497113
+-0.312219 0.141132 0.0234135
+-0.365188 0.0950877 0.0497113
+
+-0.312219 0.141132 0.0234135
+-0.331579 0.0863365 0.0497113
+-0.282481 0.127689 0.0115353
+
+-0.299997 0.0781132 0.037833
+-0.282481 0.127689 0.0115353
+-0.331579 0.0863365 0.0497113
+
+-0.282481 0.127689 0.0115353
+-0.299997 0.0781132 0.037833
+-0.258238 0.116731 -0.0107885
+
+-0.274251 0.0714095 0.0155093
+-0.258238 0.116731 -0.0107885
+-0.299997 0.0781132 0.037833
+
+-0.258238 0.116731 -0.0107885
+-0.274251 0.0714095 0.0155093
+-0.242415 0.109578 -0.0408652
+
+-0.257447 0.0670339 -0.0145675
+-0.242415 0.109578 -0.0408652
+-0.274251 0.0714095 0.0155093
+
+-0.242415 0.109578 -0.0408652
+-0.257447 0.0670339 -0.0145675
+-0.236919 0.107094 -0.0750672
+
+-0.251611 0.0655143 -0.0487695
+-0.236919 0.107094 -0.0750672
+-0.257447 0.0670339 -0.0145675
+
+-0.236919 0.107094 -0.0750672
+-0.251611 0.0655143 -0.0487695
+-0.242415 0.109578 -0.109269
+
+-0.257447 0.0670339 -0.0829715
+-0.242415 0.109578 -0.109269
+-0.251611 0.0655143 -0.0487695
+
+-0.242415 0.109578 -0.109269
+-0.257447 0.0670339 -0.0829715
+-0.258238 0.116731 -0.139346
+
+-0.274251 0.0714095 -0.113048
+-0.258238 0.116731 -0.139346
+-0.257447 0.0670339 -0.0829715
+
+-0.258238 0.116731 -0.139346
+-0.274251 0.0714095 -0.113048
+-0.282481 0.127689 -0.16167
+
+-0.299997 0.0781132 -0.135372
+-0.282481 0.127689 -0.16167
+-0.274251 0.0714095 -0.113048
+
+-0.282481 0.127689 -0.16167
+-0.299997 0.0781132 -0.135372
+-0.312219 0.141132 -0.173548
+
+-0.331579 0.0863365 -0.14725
+-0.312219 0.141132 -0.173548
+-0.299997 0.0781132 -0.135372
+
+-0.312219 0.141132 -0.173548
+-0.331579 0.0863365 -0.14725
+-0.343866 0.155437 -0.173548
+
+-0.365188 0.0950877 -0.14725
+-0.343866 0.155437 -0.173548
+-0.331579 0.0863365 -0.14725
+
+-0.343866 0.155437 -0.173548
+-0.365188 0.0950877 -0.14725
+-0.373604 0.16888 -0.16167
+
+-0.396771 0.103311 -0.135372
+-0.373604 0.16888 -0.16167
+-0.365188 0.0950877 -0.14725
+
+-0.373604 0.16888 -0.16167
+-0.396771 0.103311 -0.135372
+-0.397846 0.179838 -0.139346
+
+-0.422517 0.110015 -0.113048
+-0.397846 0.179838 -0.139346
+-0.396771 0.103311 -0.135372
+
+-0.397846 0.179838 -0.139346
+-0.422517 0.110015 -0.113048
+-0.41367 0.186991 -0.109269
+
+-0.439321 0.11439 -0.0829715
+-0.41367 0.186991 -0.109269
+-0.422517 0.110015 -0.113048
+
+-0.41367 0.186991 -0.109269
+-0.439321 0.11439 -0.0829715
+-0.419165 0.189475 -0.0750672
+
+-0.445157 0.11591 -0.0487695
+-0.419165 0.189475 -0.0750672
+-0.439321 0.11439 -0.0829715
+
+-0.445157 0.11591 -0.0487695
+-0.458343 0.0390107 -0.0169001
+-0.439321 0.11439 -0.0145675
+
+-0.452334 0.0384993 0.0173019
+-0.439321 0.11439 -0.0145675
+-0.458343 0.0390107 -0.0169001
+
+-0.439321 0.11439 -0.0145675
+-0.452334 0.0384993 0.0173019
+-0.422517 0.110015 0.0155093
+
+-0.435032 0.0370266 0.0473787
+-0.422517 0.110015 0.0155093
+-0.452334 0.0384993 0.0173019
+
+-0.422517 0.110015 0.0155093
+-0.435032 0.0370266 0.0473787
+-0.396771 0.103311 0.037833
+
+-0.408523 0.0347704 0.0697025
+-0.396771 0.103311 0.037833
+-0.435032 0.0370266 0.0473787
+
+-0.396771 0.103311 0.037833
+-0.408523 0.0347704 0.0697025
+-0.365188 0.0950877 0.0497113
+
+-0.376005 0.0320028 0.0815807
+-0.365188 0.0950877 0.0497113
+-0.408523 0.0347704 0.0697025
+
+-0.365188 0.0950877 0.0497113
+-0.376005 0.0320028 0.0815807
+-0.331579 0.0863365 0.0497113
+
+-0.341401 0.0290575 0.0815807
+-0.331579 0.0863365 0.0497113
+-0.376005 0.0320028 0.0815807
+
+-0.331579 0.0863365 0.0497113
+-0.341401 0.0290575 0.0815807
+-0.299997 0.0781132 0.037833
+
+-0.308883 0.0262898 0.0697025
+-0.299997 0.0781132 0.037833
+-0.341401 0.0290575 0.0815807
+
+-0.299997 0.0781132 0.037833
+-0.308883 0.0262898 0.0697025
+-0.274251 0.0714095 0.0155093
+
+-0.282375 0.0240336 0.0473787
+-0.274251 0.0714095 0.0155093
+-0.308883 0.0262898 0.0697025
+
+-0.274251 0.0714095 0.0155093
+-0.282375 0.0240336 0.0473787
+-0.257447 0.0670339 -0.0145675
+
+-0.265072 0.022561 0.0173019
+-0.257447 0.0670339 -0.0145675
+-0.282375 0.0240336 0.0473787
+
+-0.257447 0.0670339 -0.0145675
+-0.265072 0.022561 0.0173019
+-0.251611 0.0655143 -0.0487695
+
+-0.259063 0.0220495 -0.0169001
+-0.251611 0.0655143 -0.0487695
+-0.265072 0.022561 0.0173019
+
+-0.251611 0.0655143 -0.0487695
+-0.259063 0.0220495 -0.0169001
+-0.257447 0.0670339 -0.0829715
+
+-0.265072 0.022561 -0.0511021
+-0.257447 0.0670339 -0.0829715
+-0.259063 0.0220495 -0.0169001
+
+-0.257447 0.0670339 -0.0829715
+-0.265072 0.022561 -0.0511021
+-0.274251 0.0714095 -0.113048
+
+-0.282375 0.0240336 -0.0811788
+-0.274251 0.0714095 -0.113048
+-0.265072 0.022561 -0.0511021
+
+-0.274251 0.0714095 -0.113048
+-0.282375 0.0240336 -0.0811788
+-0.299997 0.0781132 -0.135372
+
+-0.308883 0.0262898 -0.103503
+-0.299997 0.0781132 -0.135372
+-0.282375 0.0240336 -0.0811788
+
+-0.299997 0.0781132 -0.135372
+-0.308883 0.0262898 -0.103503
+-0.331579 0.0863365 -0.14725
+
+-0.341401 0.0290575 -0.115381
+-0.331579 0.0863365 -0.14725
+-0.308883 0.0262898 -0.103503
+
+-0.331579 0.0863365 -0.14725
+-0.341401 0.0290575 -0.115381
+-0.365188 0.0950877 -0.14725
+
+-0.376005 0.0320028 -0.115381
+-0.365188 0.0950877 -0.14725
+-0.341401 0.0290575 -0.115381
+
+-0.365188 0.0950877 -0.14725
+-0.376005 0.0320028 -0.115381
+-0.396771 0.103311 -0.135372
+
+-0.408523 0.0347704 -0.103503
+-0.396771 0.103311 -0.135372
+-0.376005 0.0320028 -0.115381
+
+-0.396771 0.103311 -0.135372
+-0.408523 0.0347704 -0.103503
+-0.422517 0.110015 -0.113048
+
+-0.435032 0.0370266 -0.0811788
+-0.422517 0.110015 -0.113048
+-0.408523 0.0347704 -0.103503
+
+-0.422517 0.110015 -0.113048
+-0.435032 0.0370266 -0.0811788
+-0.439321 0.11439 -0.0829715
+
+-0.452334 0.0384993 -0.0511021
+-0.439321 0.11439 -0.0829715
+-0.435032 0.0370266 -0.0811788
+
+-0.439321 0.11439 -0.0829715
+-0.452334 0.0384993 -0.0511021
+-0.445157 0.11591 -0.0487695
+
+-0.458343 0.0390107 -0.0169001
+-0.445157 0.11591 -0.0487695
+-0.452334 0.0384993 -0.0511021
+
+-0.458343 0.0390107 -0.0169001
+-0.458343 -0.0390107 0.0169001
+-0.452334 0.0384993 0.0173019
+
+-0.452334 -0.0384993 0.0511021
+-0.452334 0.0384993 0.0173019
+-0.458343 -0.0390107 0.0169001
+
+-0.452334 0.0384993 0.0173019
+-0.452334 -0.0384993 0.0511021
+-0.435032 0.0370266 0.0473787
+
+-0.435032 -0.0370266 0.0811788
+-0.435032 0.0370266 0.0473787
+-0.452334 -0.0384993 0.0511021
+
+-0.435032 0.0370266 0.0473787
+-0.435032 -0.0370266 0.0811788
+-0.408523 0.0347704 0.0697025
+
+-0.408523 -0.0347704 0.103503
+-0.408523 0.0347704 0.0697025
+-0.435032 -0.0370266 0.0811788
+
+-0.408523 0.0347704 0.0697025
+-0.408523 -0.0347704 0.103503
+-0.376005 0.0320028 0.0815807
+
+-0.376005 -0.0320028 0.115381
+-0.376005 0.0320028 0.0815807
+-0.408523 -0.0347704 0.103503
+
+-0.376005 0.0320028 0.0815807
+-0.376005 -0.0320028 0.115381
+-0.341401 0.0290575 0.0815807
+
+-0.341401 -0.0290575 0.115381
+-0.341401 0.0290575 0.0815807
+-0.376005 -0.0320028 0.115381
+
+-0.341401 0.0290575 0.0815807
+-0.341401 -0.0290575 0.115381
+-0.308883 0.0262898 0.0697025
+
+-0.308883 -0.0262898 0.103503
+-0.308883 0.0262898 0.0697025
+-0.341401 -0.0290575 0.115381
+
+-0.308883 0.0262898 0.0697025
+-0.308883 -0.0262898 0.103503
+-0.282375 0.0240336 0.0473787
+
+-0.282375 -0.0240336 0.0811788
+-0.282375 0.0240336 0.0473787
+-0.308883 -0.0262898 0.103503
+
+-0.282375 0.0240336 0.0473787
+-0.282375 -0.0240336 0.0811788
+-0.265072 0.022561 0.0173019
+
+-0.265072 -0.022561 0.0511021
+-0.265072 0.022561 0.0173019
+-0.282375 -0.0240336 0.0811788
+
+-0.265072 0.022561 0.0173019
+-0.265072 -0.022561 0.0511021
+-0.259063 0.0220495 -0.0169001
+
+-0.259063 -0.0220495 0.0169001
+-0.259063 0.0220495 -0.0169001
+-0.265072 -0.022561 0.0511021
+
+-0.259063 0.0220495 -0.0169001
+-0.259063 -0.0220495 0.0169001
+-0.265072 0.022561 -0.0511021
+
+-0.265072 -0.022561 -0.0173019
+-0.265072 0.022561 -0.0511021
+-0.259063 -0.0220495 0.0169001
+
+-0.265072 0.022561 -0.0511021
+-0.265072 -0.022561 -0.0173019
+-0.282375 0.0240336 -0.0811788
+
+-0.282375 -0.0240336 -0.0473787
+-0.282375 0.0240336 -0.0811788
+-0.265072 -0.022561 -0.0173019
+
+-0.282375 0.0240336 -0.0811788
+-0.282375 -0.0240336 -0.0473787
+-0.308883 0.0262898 -0.103503
+
+-0.308883 -0.0262898 -0.0697025
+-0.308883 0.0262898 -0.103503
+-0.282375 -0.0240336 -0.0473787
+
+-0.308883 0.0262898 -0.103503
+-0.308883 -0.0262898 -0.0697025
+-0.341401 0.0290575 -0.115381
+
+-0.341401 -0.0290575 -0.0815807
+-0.341401 0.0290575 -0.115381
+-0.308883 -0.0262898 -0.0697025
+
+-0.341401 0.0290575 -0.115381
+-0.341401 -0.0290575 -0.0815807
+-0.376005 0.0320028 -0.115381
+
+-0.376005 -0.0320028 -0.0815807
+-0.376005 0.0320028 -0.115381
+-0.341401 -0.0290575 -0.0815807
+
+-0.376005 0.0320028 -0.115381
+-0.376005 -0.0320028 -0.0815807
+-0.408523 0.0347704 -0.103503
+
+-0.408523 -0.0347704 -0.0697025
+-0.408523 0.0347704 -0.103503
+-0.376005 -0.0320028 -0.0815807
+
+-0.408523 0.0347704 -0.103503
+-0.408523 -0.0347704 -0.0697025
+-0.435032 0.0370266 -0.0811788
+
+-0.435032 -0.0370266 -0.0473787
+-0.435032 0.0370266 -0.0811788
+-0.408523 -0.0347704 -0.0697025
+
+-0.435032 0.0370266 -0.0811788
+-0.435032 -0.0370266 -0.0473787
+-0.452334 0.0384993 -0.0511021
+
+-0.452334 -0.0384993 -0.0173019
+-0.452334 0.0384993 -0.0511021
+-0.435032 -0.0370266 -0.0473787
+
+-0.452334 0.0384993 -0.0511021
+-0.452334 -0.0384993 -0.0173019
+-0.458343 0.0390107 -0.0169001
+
+-0.458343 -0.0390107 0.0169001
+-0.458343 0.0390107 -0.0169001
+-0.452334 -0.0384993 -0.0173019
+
+-0.458343 -0.0390107 0.0169001
+-0.445157 -0.11591 0.0487695
+-0.452334 -0.0384993 0.0511021
+
+-0.439321 -0.11439 0.0829715
+-0.452334 -0.0384993 0.0511021
+-0.445157 -0.11591 0.0487695
+
+-0.452334 -0.0384993 0.0511021
+-0.439321 -0.11439 0.0829715
+-0.435032 -0.0370266 0.0811788
+
+-0.422517 -0.110015 0.113048
+-0.435032 -0.0370266 0.0811788
+-0.439321 -0.11439 0.0829715
+
+-0.435032 -0.0370266 0.0811788
+-0.422517 -0.110015 0.113048
+-0.408523 -0.0347704 0.103503
+
+-0.396771 -0.103311 0.135372
+-0.408523 -0.0347704 0.103503
+-0.422517 -0.110015 0.113048
+
+-0.408523 -0.0347704 0.103503
+-0.396771 -0.103311 0.135372
+-0.376005 -0.0320028 0.115381
+
+-0.365188 -0.0950877 0.14725
+-0.376005 -0.0320028 0.115381
+-0.396771 -0.103311 0.135372
+
+-0.376005 -0.0320028 0.115381
+-0.365188 -0.0950877 0.14725
+-0.341401 -0.0290575 0.115381
+
+-0.331579 -0.0863365 0.14725
+-0.341401 -0.0290575 0.115381
+-0.365188 -0.0950877 0.14725
+
+-0.341401 -0.0290575 0.115381
+-0.331579 -0.0863365 0.14725
+-0.308883 -0.0262898 0.103503
+
+-0.299997 -0.0781132 0.135372
+-0.308883 -0.0262898 0.103503
+-0.331579 -0.0863365 0.14725
+
+-0.308883 -0.0262898 0.103503
+-0.299997 -0.0781132 0.135372
+-0.282375 -0.0240336 0.0811788
+
+-0.274251 -0.0714095 0.113048
+-0.282375 -0.0240336 0.0811788
+-0.299997 -0.0781132 0.135372
+
+-0.282375 -0.0240336 0.0811788
+-0.274251 -0.0714095 0.113048
+-0.265072 -0.022561 0.0511021
+
+-0.257447 -0.0670339 0.0829715
+-0.265072 -0.022561 0.0511021
+-0.274251 -0.0714095 0.113048
+
+-0.265072 -0.022561 0.0511021
+-0.257447 -0.0670339 0.0829715
+-0.259063 -0.0220495 0.0169001
+
+-0.251611 -0.0655143 0.0487695
+-0.259063 -0.0220495 0.0169001
+-0.257447 -0.0670339 0.0829715
+
+-0.259063 -0.0220495 0.0169001
+-0.251611 -0.0655143 0.0487695
+-0.265072 -0.022561 -0.0173019
+
+-0.257447 -0.0670339 0.0145675
+-0.265072 -0.022561 -0.0173019
+-0.251611 -0.0655143 0.0487695
+
+-0.265072 -0.022561 -0.0173019
+-0.257447 -0.0670339 0.0145675
+-0.282375 -0.0240336 -0.0473787
+
+-0.274251 -0.0714095 -0.0155093
+-0.282375 -0.0240336 -0.0473787
+-0.257447 -0.0670339 0.0145675
+
+-0.282375 -0.0240336 -0.0473787
+-0.274251 -0.0714095 -0.0155093
+-0.308883 -0.0262898 -0.0697025
+
+-0.299997 -0.0781132 -0.037833
+-0.308883 -0.0262898 -0.0697025
+-0.274251 -0.0714095 -0.0155093
+
+-0.308883 -0.0262898 -0.0697025
+-0.299997 -0.0781132 -0.037833
+-0.341401 -0.0290575 -0.0815807
+
+-0.331579 -0.0863365 -0.0497113
+-0.341401 -0.0290575 -0.0815807
+-0.299997 -0.0781132 -0.037833
+
+-0.341401 -0.0290575 -0.0815807
+-0.331579 -0.0863365 -0.0497113
+-0.376005 -0.0320028 -0.0815807
+
+-0.365188 -0.0950877 -0.0497113
+-0.376005 -0.0320028 -0.0815807
+-0.331579 -0.0863365 -0.0497113
+
+-0.376005 -0.0320028 -0.0815807
+-0.365188 -0.0950877 -0.0497113
+-0.408523 -0.0347704 -0.0697025
+
+-0.396771 -0.103311 -0.037833
+-0.408523 -0.0347704 -0.0697025
+-0.365188 -0.0950877 -0.0497113
+
+-0.408523 -0.0347704 -0.0697025
+-0.396771 -0.103311 -0.037833
+-0.435032 -0.0370266 -0.0473787
+
+-0.422517 -0.110015 -0.0155093
+-0.435032 -0.0370266 -0.0473787
+-0.396771 -0.103311 -0.037833
+
+-0.435032 -0.0370266 -0.0473787
+-0.422517 -0.110015 -0.0155093
+-0.452334 -0.0384993 -0.0173019
+
+-0.439321 -0.11439 0.0145675
+-0.452334 -0.0384993 -0.0173019
+-0.422517 -0.110015 -0.0155093
+
+-0.452334 -0.0384993 -0.0173019
+-0.439321 -0.11439 0.0145675
+-0.458343 -0.0390107 0.0169001
+
+-0.445157 -0.11591 0.0487695
+-0.458343 -0.0390107 0.0169001
+-0.439321 -0.11439 0.0145675
+
+-0.445157 -0.11591 0.0487695
+-0.419165 -0.189475 0.0750672
+-0.439321 -0.11439 0.0829715
+
+-0.41367 -0.186991 0.109269
+-0.439321 -0.11439 0.0829715
+-0.419165 -0.189475 0.0750672
+
+-0.439321 -0.11439 0.0829715
+-0.41367 -0.186991 0.109269
+-0.422517 -0.110015 0.113048
+
+-0.397846 -0.179838 0.139346
+-0.422517 -0.110015 0.113048
+-0.41367 -0.186991 0.109269
+
+-0.422517 -0.110015 0.113048
+-0.397846 -0.179838 0.139346
+-0.396771 -0.103311 0.135372
+
+-0.373604 -0.16888 0.16167
+-0.396771 -0.103311 0.135372
+-0.397846 -0.179838 0.139346
+
+-0.396771 -0.103311 0.135372
+-0.373604 -0.16888 0.16167
+-0.365188 -0.0950877 0.14725
+
+-0.343866 -0.155437 0.173548
+-0.365188 -0.0950877 0.14725
+-0.373604 -0.16888 0.16167
+
+-0.365188 -0.0950877 0.14725
+-0.343866 -0.155437 0.173548
+-0.331579 -0.0863365 0.14725
+
+-0.312219 -0.141132 0.173548
+-0.331579 -0.0863365 0.14725
+-0.343866 -0.155437 0.173548
+
+-0.331579 -0.0863365 0.14725
+-0.312219 -0.141132 0.173548
+-0.299997 -0.0781132 0.135372
+
+-0.282481 -0.127689 0.16167
+-0.299997 -0.0781132 0.135372
+-0.312219 -0.141132 0.173548
+
+-0.299997 -0.0781132 0.135372
+-0.282481 -0.127689 0.16167
+-0.274251 -0.0714095 0.113048
+
+-0.258238 -0.116731 0.139346
+-0.274251 -0.0714095 0.113048
+-0.282481 -0.127689 0.16167
+
+-0.274251 -0.0714095 0.113048
+-0.258238 -0.116731 0.139346
+-0.257447 -0.0670339 0.0829715
+
+-0.242415 -0.109578 0.109269
+-0.257447 -0.0670339 0.0829715
+-0.258238 -0.116731 0.139346
+
+-0.257447 -0.0670339 0.0829715
+-0.242415 -0.109578 0.109269
+-0.251611 -0.0655143 0.0487695
+
+-0.236919 -0.107094 0.0750672
+-0.251611 -0.0655143 0.0487695
+-0.242415 -0.109578 0.109269
+
+-0.251611 -0.0655143 0.0487695
+-0.236919 -0.107094 0.0750672
+-0.257447 -0.0670339 0.0145675
+
+-0.242415 -0.109578 0.0408652
+-0.257447 -0.0670339 0.0145675
+-0.236919 -0.107094 0.0750672
+
+-0.257447 -0.0670339 0.0145675
+-0.242415 -0.109578 0.0408652
+-0.274251 -0.0714095 -0.0155093
+
+-0.258238 -0.116731 0.0107885
+-0.274251 -0.0714095 -0.0155093
+-0.242415 -0.109578 0.0408652
+
+-0.274251 -0.0714095 -0.0155093
+-0.258238 -0.116731 0.0107885
+-0.299997 -0.0781132 -0.037833
+
+-0.282481 -0.127689 -0.0115353
+-0.299997 -0.0781132 -0.037833
+-0.258238 -0.116731 0.0107885
+
+-0.299997 -0.0781132 -0.037833
+-0.282481 -0.127689 -0.0115353
+-0.331579 -0.0863365 -0.0497113
+
+-0.312219 -0.141132 -0.0234135
+-0.331579 -0.0863365 -0.0497113
+-0.282481 -0.127689 -0.0115353
+
+-0.331579 -0.0863365 -0.0497113
+-0.312219 -0.141132 -0.0234135
+-0.365188 -0.0950877 -0.0497113
+
+-0.343866 -0.155437 -0.0234135
+-0.365188 -0.0950877 -0.0497113
+-0.312219 -0.141132 -0.0234135
+
+-0.365188 -0.0950877 -0.0497113
+-0.343866 -0.155437 -0.0234135
+-0.396771 -0.103311 -0.037833
+
+-0.373604 -0.16888 -0.0115353
+-0.396771 -0.103311 -0.037833
+-0.343866 -0.155437 -0.0234135
+
+-0.396771 -0.103311 -0.037833
+-0.373604 -0.16888 -0.0115353
+-0.422517 -0.110015 -0.0155093
+
+-0.397846 -0.179838 0.0107885
+-0.422517 -0.110015 -0.0155093
+-0.373604 -0.16888 -0.0115353
+
+-0.422517 -0.110015 -0.0155093
+-0.397846 -0.179838 0.0107885
+-0.439321 -0.11439 0.0145675
+
+-0.41367 -0.186991 0.0408652
+-0.439321 -0.11439 0.0145675
+-0.397846 -0.179838 0.0107885
+
+-0.439321 -0.11439 0.0145675
+-0.41367 -0.186991 0.0408652
+-0.445157 -0.11591 0.0487695
+
+-0.419165 -0.189475 0.0750672
+-0.445157 -0.11591 0.0487695
+-0.41367 -0.186991 0.0408652
+
+-0.419165 -0.189475 0.0750672
+-0.381114 -0.257588 0.0927889
+-0.41367 -0.186991 0.109269
+
+-0.376118 -0.254211 0.126991
+-0.41367 -0.186991 0.109269
+-0.381114 -0.257588 0.0927889
+
+-0.41367 -0.186991 0.109269
+-0.376118 -0.254211 0.126991
+-0.397846 -0.179838 0.139346
+
+-0.361731 -0.244487 0.157068
+-0.397846 -0.179838 0.139346
+-0.376118 -0.254211 0.126991
+
+-0.397846 -0.179838 0.139346
+-0.361731 -0.244487 0.157068
+-0.373604 -0.16888 0.16167
+
+-0.339689 -0.22959 0.179391
+-0.373604 -0.16888 0.16167
+-0.361731 -0.244487 0.157068
+
+-0.373604 -0.16888 0.16167
+-0.339689 -0.22959 0.179391
+-0.343866 -0.155437 0.173548
+
+-0.31265 -0.211315 0.19127
+-0.343866 -0.155437 0.173548
+-0.339689 -0.22959 0.179391
+
+-0.343866 -0.155437 0.173548
+-0.31265 -0.211315 0.19127
+-0.312219 -0.141132 0.173548
+
+-0.283877 -0.191867 0.19127
+-0.312219 -0.141132 0.173548
+-0.31265 -0.211315 0.19127
+
+-0.312219 -0.141132 0.173548
+-0.283877 -0.191867 0.19127
+-0.282481 -0.127689 0.16167
+
+-0.256838 -0.173592 0.179391
+-0.282481 -0.127689 0.16167
+-0.283877 -0.191867 0.19127
+
+-0.282481 -0.127689 0.16167
+-0.256838 -0.173592 0.179391
+-0.258238 -0.116731 0.139346
+
+-0.234796 -0.158694 0.157068
+-0.258238 -0.116731 0.139346
+-0.256838 -0.173592 0.179391
+
+-0.258238 -0.116731 0.139346
+-0.234796 -0.158694 0.157068
+-0.242415 -0.109578 0.109269
+
+-0.220409 -0.148971 0.126991
+-0.242415 -0.109578 0.109269
+-0.234796 -0.158694 0.157068
+
+-0.242415 -0.109578 0.109269
+-0.220409 -0.148971 0.126991
+-0.236919 -0.107094 0.0750672
+
+-0.215413 -0.145593 0.0927889
+-0.236919 -0.107094 0.0750672
+-0.220409 -0.148971 0.126991
+
+-0.236919 -0.107094 0.0750672
+-0.215413 -0.145593 0.0927889
+-0.242415 -0.109578 0.0408652
+
+-0.220409 -0.148971 0.0585869
+-0.242415 -0.109578 0.0408652
+-0.215413 -0.145593 0.0927889
+
+-0.242415 -0.109578 0.0408652
+-0.220409 -0.148971 0.0585869
+-0.258238 -0.116731 0.0107885
+
+-0.234796 -0.158694 0.0285101
+-0.258238 -0.116731 0.0107885
+-0.220409 -0.148971 0.0585869
+
+-0.258238 -0.116731 0.0107885
+-0.234796 -0.158694 0.0285101
+-0.282481 -0.127689 -0.0115353
+
+-0.256838 -0.173592 0.00618636
+-0.282481 -0.127689 -0.0115353
+-0.234796 -0.158694 0.0285101
+
+-0.282481 -0.127689 -0.0115353
+-0.256838 -0.173592 0.00618636
+-0.312219 -0.141132 -0.0234135
+
+-0.283877 -0.191867 -0.00569187
+-0.312219 -0.141132 -0.0234135
+-0.256838 -0.173592 0.00618636
+
+-0.312219 -0.141132 -0.0234135
+-0.283877 -0.191867 -0.00569187
+-0.343866 -0.155437 -0.0234135
+
+-0.31265 -0.211315 -0.00569187
+-0.343866 -0.155437 -0.0234135
+-0.283877 -0.191867 -0.00569187
+
+-0.343866 -0.155437 -0.0234135
+-0.31265 -0.211315 -0.00569187
+-0.373604 -0.16888 -0.0115353
+
+-0.339689 -0.22959 0.00618636
+-0.373604 -0.16888 -0.0115353
+-0.31265 -0.211315 -0.00569187
+
+-0.373604 -0.16888 -0.0115353
+-0.339689 -0.22959 0.00618636
+-0.397846 -0.179838 0.0107885
+
+-0.361731 -0.244487 0.0285101
+-0.397846 -0.179838 0.0107885
+-0.339689 -0.22959 0.00618636
+
+-0.397846 -0.179838 0.0107885
+-0.361731 -0.244487 0.0285101
+-0.41367 -0.186991 0.0408652
+
+-0.376118 -0.254211 0.0585869
+-0.41367 -0.186991 0.0408652
+-0.361731 -0.244487 0.0285101
+
+-0.41367 -0.186991 0.0408652
+-0.376118 -0.254211 0.0585869
+-0.419165 -0.189475 0.0750672
+
+-0.381114 -0.257588 0.0927889
+-0.419165 -0.189475 0.0750672
+-0.376118 -0.254211 0.0585869
+
+-0.381114 -0.257588 0.0927889
+-0.3321 -0.318292 0.0999099
+-0.376118 -0.254211 0.126991
+
+-0.327746 -0.314119 0.134112
+-0.376118 -0.254211 0.126991
+-0.3321 -0.318292 0.0999099
+
+-0.376118 -0.254211 0.126991
+-0.327746 -0.314119 0.134112
+-0.361731 -0.244487 0.157068
+
+-0.315209 -0.302104 0.164189
+-0.361731 -0.244487 0.157068
+-0.327746 -0.314119 0.134112
+
+-0.361731 -0.244487 0.157068
+-0.315209 -0.302104 0.164189
+-0.339689 -0.22959 0.179391
+
+-0.296002 -0.283695 0.186512
+-0.339689 -0.22959 0.179391
+-0.315209 -0.302104 0.164189
+
+-0.339689 -0.22959 0.179391
+-0.296002 -0.283695 0.186512
+-0.31265 -0.211315 0.19127
+
+-0.272441 -0.261113 0.198391
+-0.31265 -0.211315 0.19127
+-0.296002 -0.283695 0.186512
+
+-0.31265 -0.211315 0.19127
+-0.272441 -0.261113 0.198391
+-0.283877 -0.191867 0.19127
+
+-0.247368 -0.237083 0.198391
+-0.283877 -0.191867 0.19127
+-0.272441 -0.261113 0.198391
+
+-0.283877 -0.191867 0.19127
+-0.247368 -0.237083 0.198391
+-0.256838 -0.173592 0.179391
+
+-0.223806 -0.214501 0.186512
+-0.256838 -0.173592 0.179391
+-0.247368 -0.237083 0.198391
+
+-0.256838 -0.173592 0.179391
+-0.223806 -0.214501 0.186512
+-0.234796 -0.158694 0.157068
+
+-0.204599 -0.196092 0.164189
+-0.234796 -0.158694 0.157068
+-0.223806 -0.214501 0.186512
+
+-0.234796 -0.158694 0.157068
+-0.204599 -0.196092 0.164189
+-0.220409 -0.148971 0.126991
+
+-0.192063 -0.184077 0.134112
+-0.220409 -0.148971 0.126991
+-0.204599 -0.196092 0.164189
+
+-0.220409 -0.148971 0.126991
+-0.192063 -0.184077 0.134112
+-0.215413 -0.145593 0.0927889
+
+-0.187709 -0.179904 0.0999099
+-0.215413 -0.145593 0.0927889
+-0.192063 -0.184077 0.134112
+
+-0.215413 -0.145593 0.0927889
+-0.187709 -0.179904 0.0999099
+-0.220409 -0.148971 0.0585869
+
+-0.192063 -0.184077 0.0657079
+-0.220409 -0.148971 0.0585869
+-0.187709 -0.179904 0.0999099
+
+-0.220409 -0.148971 0.0585869
+-0.192063 -0.184077 0.0657079
+-0.234796 -0.158694 0.0285101
+
+-0.204599 -0.196092 0.0356311
+-0.234796 -0.158694 0.0285101
+-0.192063 -0.184077 0.0657079
+
+-0.234796 -0.158694 0.0285101
+-0.204599 -0.196092 0.0356311
+-0.256838 -0.173592 0.00618636
+
+-0.223806 -0.214501 0.0133074
+-0.256838 -0.173592 0.00618636
+-0.204599 -0.196092 0.0356311
+
+-0.256838 -0.173592 0.00618636
+-0.223806 -0.214501 0.0133074
+-0.283877 -0.191867 -0.00569187
+
+-0.247368 -0.237083 0.00142912
+-0.283877 -0.191867 -0.00569187
+-0.223806 -0.214501 0.0133074
+
+-0.283877 -0.191867 -0.00569187
+-0.247368 -0.237083 0.00142912
+-0.31265 -0.211315 -0.00569187
+
+-0.272441 -0.261113 0.00142912
+-0.31265 -0.211315 -0.00569187
+-0.247368 -0.237083 0.00142912
+
+-0.31265 -0.211315 -0.00569187
+-0.272441 -0.261113 0.00142912
+-0.339689 -0.22959 0.00618636
+
+-0.296002 -0.283695 0.0133074
+-0.339689 -0.22959 0.00618636
+-0.272441 -0.261113 0.00142912
+
+-0.339689 -0.22959 0.00618636
+-0.296002 -0.283695 0.0133074
+-0.361731 -0.244487 0.0285101
+
+-0.315209 -0.302104 0.0356311
+-0.361731 -0.244487 0.0285101
+-0.296002 -0.283695 0.0133074
+
+-0.361731 -0.244487 0.0285101
+-0.315209 -0.302104 0.0356311
+-0.376118 -0.254211 0.0585869
+
+-0.327746 -0.314119 0.0657079
+-0.376118 -0.254211 0.0585869
+-0.315209 -0.302104 0.0356311
+
+-0.376118 -0.254211 0.0585869
+-0.327746 -0.314119 0.0657079
+-0.381114 -0.257588 0.0927889
+
+-0.3321 -0.318292 0.0999099
+-0.381114 -0.257588 0.0927889
+-0.327746 -0.314119 0.0657079
+
+-0.3321 -0.318292 0.0999099
+-0.273531 -0.369839 0.0956167
+-0.327746 -0.314119 0.134112
+
+-0.269945 -0.36499 0.129819
+-0.327746 -0.314119 0.134112
+-0.273531 -0.369839 0.0956167
+
+-0.327746 -0.314119 0.134112
+-0.269945 -0.36499 0.129819
+-0.315209 -0.302104 0.164189
+
+-0.259619 -0.351029 0.159895
+-0.315209 -0.302104 0.164189
+-0.269945 -0.36499 0.129819
+
+-0.315209 -0.302104 0.164189
+-0.259619 -0.351029 0.159895
+-0.296002 -0.283695 0.186512
+
+-0.2438 -0.329639 0.182219
+-0.296002 -0.283695 0.186512
+-0.259619 -0.351029 0.159895
+
+-0.296002 -0.283695 0.186512
+-0.2438 -0.329639 0.182219
+-0.272441 -0.261113 0.198391
+
+-0.224394 -0.3034 0.194097
+-0.272441 -0.261113 0.198391
+-0.2438 -0.329639 0.182219
+
+-0.272441 -0.261113 0.198391
+-0.224394 -0.3034 0.194097
+-0.247368 -0.237083 0.198391
+
+-0.203742 -0.275478 0.194097
+-0.247368 -0.237083 0.198391
+-0.224394 -0.3034 0.194097
+
+-0.247368 -0.237083 0.198391
+-0.203742 -0.275478 0.194097
+-0.223806 -0.214501 0.186512
+
+-0.184336 -0.249239 0.182219
+-0.223806 -0.214501 0.186512
+-0.203742 -0.275478 0.194097
+
+-0.223806 -0.214501 0.186512
+-0.184336 -0.249239 0.182219
+-0.204599 -0.196092 0.164189
+
+-0.168516 -0.227849 0.159895
+-0.204599 -0.196092 0.164189
+-0.184336 -0.249239 0.182219
+
+-0.204599 -0.196092 0.164189
+-0.168516 -0.227849 0.159895
+-0.192063 -0.184077 0.134112
+
+-0.158191 -0.213888 0.129819
+-0.192063 -0.184077 0.134112
+-0.168516 -0.227849 0.159895
+
+-0.192063 -0.184077 0.134112
+-0.158191 -0.213888 0.129819
+-0.187709 -0.179904 0.0999099
+
+-0.154605 -0.209039 0.0956167
+-0.187709 -0.179904 0.0999099
+-0.158191 -0.213888 0.129819
+
+-0.187709 -0.179904 0.0999099
+-0.154605 -0.209039 0.0956167
+-0.192063 -0.184077 0.0657079
+
+-0.158191 -0.213888 0.0614147
+-0.192063 -0.184077 0.0657079
+-0.154605 -0.209039 0.0956167
+
+-0.192063 -0.184077 0.0657079
+-0.158191 -0.213888 0.0614147
+-0.204599 -0.196092 0.0356311
+
+-0.168516 -0.227849 0.0313379
+-0.204599 -0.196092 0.0356311
+-0.158191 -0.213888 0.0614147
+
+-0.204599 -0.196092 0.0356311
+-0.168516 -0.227849 0.0313379
+-0.223806 -0.214501 0.0133074
+
+-0.184336 -0.249239 0.00901413
+-0.223806 -0.214501 0.0133074
+-0.168516 -0.227849 0.0313379
+
+-0.223806 -0.214501 0.0133074
+-0.184336 -0.249239 0.00901413
+-0.247368 -0.237083 0.00142912
+
+-0.203742 -0.275478 -0.0028641
+-0.247368 -0.237083 0.00142912
+-0.184336 -0.249239 0.00901413
+
+-0.247368 -0.237083 0.00142912
+-0.203742 -0.275478 -0.0028641
+-0.272441 -0.261113 0.00142912
+
+-0.224394 -0.3034 -0.0028641
+-0.272441 -0.261113 0.00142912
+-0.203742 -0.275478 -0.0028641
+
+-0.272441 -0.261113 0.00142912
+-0.224394 -0.3034 -0.0028641
+-0.296002 -0.283695 0.0133074
+
+-0.2438 -0.329639 0.00901413
+-0.296002 -0.283695 0.0133074
+-0.224394 -0.3034 -0.0028641
+
+-0.296002 -0.283695 0.0133074
+-0.2438 -0.329639 0.00901413
+-0.315209 -0.302104 0.0356311
+
+-0.259619 -0.351029 0.0313379
+-0.315209 -0.302104 0.0356311
+-0.2438 -0.329639 0.00901413
+
+-0.315209 -0.302104 0.0356311
+-0.259619 -0.351029 0.0313379
+-0.327746 -0.314119 0.0657079
+
+-0.269945 -0.36499 0.0614147
+-0.327746 -0.314119 0.0657079
+-0.259619 -0.351029 0.0313379
+
+-0.327746 -0.314119 0.0657079
+-0.269945 -0.36499 0.0614147
+-0.3321 -0.318292 0.0999099
+
+-0.273531 -0.369839 0.0956167
+-0.3321 -0.318292 0.0999099
+-0.269945 -0.36499 0.0614147
+
+-0.273531 -0.369839 0.0956167
+-0.207094 -0.410746 0.0803997
+-0.269945 -0.36499 0.129819
+
+-0.204379 -0.405361 0.114602
+-0.269945 -0.36499 0.129819
+-0.207094 -0.410746 0.0803997
+
+-0.269945 -0.36499 0.129819
+-0.204379 -0.405361 0.114602
+-0.259619 -0.351029 0.159895
+
+-0.196561 -0.389855 0.144678
+-0.259619 -0.351029 0.159895
+-0.204379 -0.405361 0.114602
+
+-0.259619 -0.351029 0.159895
+-0.196561 -0.389855 0.144678
+-0.2438 -0.329639 0.182219
+
+-0.184584 -0.3661 0.167002
+-0.2438 -0.329639 0.182219
+-0.196561 -0.389855 0.144678
+
+-0.2438 -0.329639 0.182219
+-0.184584 -0.3661 0.167002
+-0.224394 -0.3034 0.194097
+
+-0.169891 -0.336959 0.17888
+-0.224394 -0.3034 0.194097
+-0.184584 -0.3661 0.167002
+
+-0.224394 -0.3034 0.194097
+-0.169891 -0.336959 0.17888
+-0.203742 -0.275478 0.194097
+
+-0.154256 -0.305948 0.17888
+-0.203742 -0.275478 0.194097
+-0.169891 -0.336959 0.17888
+
+-0.203742 -0.275478 0.194097
+-0.154256 -0.305948 0.17888
+-0.184336 -0.249239 0.182219
+
+-0.139563 -0.276807 0.167002
+-0.184336 -0.249239 0.182219
+-0.154256 -0.305948 0.17888
+
+-0.184336 -0.249239 0.182219
+-0.139563 -0.276807 0.167002
+-0.168516 -0.227849 0.159895
+
+-0.127586 -0.253051 0.144678
+-0.168516 -0.227849 0.159895
+-0.139563 -0.276807 0.167002
+
+-0.168516 -0.227849 0.159895
+-0.127586 -0.253051 0.144678
+-0.158191 -0.213888 0.129819
+
+-0.119768 -0.237546 0.114602
+-0.158191 -0.213888 0.129819
+-0.127586 -0.253051 0.144678
+
+-0.158191 -0.213888 0.129819
+-0.119768 -0.237546 0.114602
+-0.154605 -0.209039 0.0956167
+
+-0.117053 -0.232161 0.0803997
+-0.154605 -0.209039 0.0956167
+-0.119768 -0.237546 0.114602
+
+-0.154605 -0.209039 0.0956167
+-0.117053 -0.232161 0.0803997
+-0.158191 -0.213888 0.0614147
+
+-0.119768 -0.237546 0.0461977
+-0.158191 -0.213888 0.0614147
+-0.117053 -0.232161 0.0803997
+
+-0.158191 -0.213888 0.0614147
+-0.119768 -0.237546 0.0461977
+-0.168516 -0.227849 0.0313379
+
+-0.127586 -0.253051 0.016121
+-0.168516 -0.227849 0.0313379
+-0.119768 -0.237546 0.0461977
+
+-0.168516 -0.227849 0.0313379
+-0.127586 -0.253051 0.016121
+-0.184336 -0.249239 0.00901413
+
+-0.139563 -0.276807 -0.00620283
+-0.184336 -0.249239 0.00901413
+-0.127586 -0.253051 0.016121
+
+-0.184336 -0.249239 0.00901413
+-0.139563 -0.276807 -0.00620283
+-0.203742 -0.275478 -0.0028641
+
+-0.154256 -0.305948 -0.0180811
+-0.203742 -0.275478 -0.0028641
+-0.139563 -0.276807 -0.00620283
+
+-0.203742 -0.275478 -0.0028641
+-0.154256 -0.305948 -0.0180811
+-0.224394 -0.3034 -0.0028641
+
+-0.169891 -0.336959 -0.0180811
+-0.224394 -0.3034 -0.0028641
+-0.154256 -0.305948 -0.0180811
+
+-0.224394 -0.3034 -0.0028641
+-0.169891 -0.336959 -0.0180811
+-0.2438 -0.329639 0.00901413
+
+-0.184584 -0.3661 -0.00620283
+-0.2438 -0.329639 0.00901413
+-0.169891 -0.336959 -0.0180811
+
+-0.2438 -0.329639 0.00901413
+-0.184584 -0.3661 -0.00620283
+-0.259619 -0.351029 0.0313379
+
+-0.196561 -0.389855 0.016121
+-0.259619 -0.351029 0.0313379
+-0.184584 -0.3661 -0.00620283
+
+-0.259619 -0.351029 0.0313379
+-0.196561 -0.389855 0.016121
+-0.269945 -0.36499 0.0614147
+
+-0.204379 -0.405361 0.0461977
+-0.269945 -0.36499 0.0614147
+-0.196561 -0.389855 0.016121
+
+-0.269945 -0.36499 0.0614147
+-0.204379 -0.405361 0.0461977
+-0.273531 -0.369839 0.0956167
+
+-0.207094 -0.410746 0.0803997
+-0.273531 -0.369839 0.0956167
+-0.204379 -0.405361 0.0461977
+
+-0.207094 -0.410746 0.0803997
+-0.134698 -0.439837 0.0559975
+-0.204379 -0.405361 0.114602
+
+-0.132933 -0.43407 0.0901995
+-0.204379 -0.405361 0.114602
+-0.134698 -0.439837 0.0559975
+
+-0.204379 -0.405361 0.114602
+-0.132933 -0.43407 0.0901995
+-0.196561 -0.389855 0.144678
+
+-0.127848 -0.417467 0.120276
+-0.196561 -0.389855 0.144678
+-0.132933 -0.43407 0.0901995
+
+-0.196561 -0.389855 0.144678
+-0.127848 -0.417467 0.120276
+-0.184584 -0.3661 0.167002
+
+-0.120057 -0.392028 0.1426
+-0.184584 -0.3661 0.167002
+-0.127848 -0.417467 0.120276
+
+-0.184584 -0.3661 0.167002
+-0.120057 -0.392028 0.1426
+-0.169891 -0.336959 0.17888
+
+-0.110501 -0.360824 0.154478
+-0.169891 -0.336959 0.17888
+-0.120057 -0.392028 0.1426
+
+-0.169891 -0.336959 0.17888
+-0.110501 -0.360824 0.154478
+-0.154256 -0.305948 0.17888
+
+-0.100331 -0.327616 0.154478
+-0.154256 -0.305948 0.17888
+-0.110501 -0.360824 0.154478
+
+-0.154256 -0.305948 0.17888
+-0.100331 -0.327616 0.154478
+-0.139563 -0.276807 0.167002
+
+-0.0907751 -0.296412 0.1426
+-0.139563 -0.276807 0.167002
+-0.100331 -0.327616 0.154478
+
+-0.139563 -0.276807 0.167002
+-0.0907751 -0.296412 0.1426
+-0.127586 -0.253051 0.144678
+
+-0.0829847 -0.270973 0.120276
+-0.127586 -0.253051 0.144678
+-0.0907751 -0.296412 0.1426
+
+-0.127586 -0.253051 0.144678
+-0.0829847 -0.270973 0.120276
+-0.119768 -0.237546 0.114602
+
+-0.0778999 -0.25437 0.0901995
+-0.119768 -0.237546 0.114602
+-0.0829847 -0.270973 0.120276
+
+-0.119768 -0.237546 0.114602
+-0.0778999 -0.25437 0.0901995
+-0.117053 -0.232161 0.0803997
+
+-0.0761339 -0.248603 0.0559975
+-0.117053 -0.232161 0.0803997
+-0.0778999 -0.25437 0.0901995
+
+-0.117053 -0.232161 0.0803997
+-0.0761339 -0.248603 0.0559975
+-0.119768 -0.237546 0.0461977
+
+-0.0778999 -0.25437 0.0217955
+-0.119768 -0.237546 0.0461977
+-0.0761339 -0.248603 0.0559975
+
+-0.119768 -0.237546 0.0461977
+-0.0778999 -0.25437 0.0217955
+-0.127586 -0.253051 0.016121
+
+-0.0829847 -0.270973 -0.00828128
+-0.127586 -0.253051 0.016121
+-0.0778999 -0.25437 0.0217955
+
+-0.127586 -0.253051 0.016121
+-0.0829847 -0.270973 -0.00828128
+-0.139563 -0.276807 -0.00620283
+
+-0.0907751 -0.296412 -0.0306051
+-0.139563 -0.276807 -0.00620283
+-0.0829847 -0.270973 -0.00828128
+
+-0.139563 -0.276807 -0.00620283
+-0.0907751 -0.296412 -0.0306051
+-0.154256 -0.305948 -0.0180811
+
+-0.100331 -0.327616 -0.0424833
+-0.154256 -0.305948 -0.0180811
+-0.0907751 -0.296412 -0.0306051
+
+-0.154256 -0.305948 -0.0180811
+-0.100331 -0.327616 -0.0424833
+-0.169891 -0.336959 -0.0180811
+
+-0.110501 -0.360824 -0.0424833
+-0.169891 -0.336959 -0.0180811
+-0.100331 -0.327616 -0.0424833
+
+-0.169891 -0.336959 -0.0180811
+-0.110501 -0.360824 -0.0424833
+-0.184584 -0.3661 -0.00620283
+
+-0.120057 -0.392028 -0.0306051
+-0.184584 -0.3661 -0.00620283
+-0.110501 -0.360824 -0.0424833
+
+-0.184584 -0.3661 -0.00620283
+-0.120057 -0.392028 -0.0306051
+-0.196561 -0.389855 0.016121
+
+-0.127848 -0.417467 -0.00828128
+-0.196561 -0.389855 0.016121
+-0.120057 -0.392028 -0.0306051
+
+-0.196561 -0.389855 0.016121
+-0.127848 -0.417467 -0.00828128
+-0.204379 -0.405361 0.0461977
+
+-0.132933 -0.43407 0.0217955
+-0.204379 -0.405361 0.0461977
+-0.127848 -0.417467 -0.00828128
+
+-0.204379 -0.405361 0.0461977
+-0.132933 -0.43407 0.0217955
+-0.207094 -0.410746 0.0803997
+
+-0.134698 -0.439837 0.0559975
+-0.207094 -0.410746 0.0803997
+-0.132933 -0.43407 0.0217955
+
+-0.134698 -0.439837 0.0559975
+-0.0584282 -0.456274 0.0251978
+-0.132933 -0.43407 0.0901995
+
+-0.0576622 -0.450292 0.0593998
+-0.132933 -0.43407 0.0901995
+-0.0584282 -0.456274 0.0251978
+
+-0.132933 -0.43407 0.0901995
+-0.0576622 -0.450292 0.0593998
+-0.127848 -0.417467 0.120276
+
+-0.0554565 -0.433068 0.0894766
+-0.127848 -0.417467 0.120276
+-0.0576622 -0.450292 0.0593998
+
+-0.127848 -0.417467 0.120276
+-0.0554565 -0.433068 0.0894766
+-0.120057 -0.392028 0.1426
+
+-0.0520773 -0.406679 0.1118
+-0.120057 -0.392028 0.1426
+-0.0554565 -0.433068 0.0894766
+
+-0.120057 -0.392028 0.1426
+-0.0520773 -0.406679 0.1118
+-0.110501 -0.360824 0.154478
+
+-0.0479321 -0.374308 0.123679
+-0.110501 -0.360824 0.154478
+-0.0520773 -0.406679 0.1118
+
+-0.110501 -0.360824 0.154478
+-0.0479321 -0.374308 0.123679
+-0.100331 -0.327616 0.154478
+
+-0.0435208 -0.33986 0.123679
+-0.100331 -0.327616 0.154478
+-0.0479321 -0.374308 0.123679
+
+-0.100331 -0.327616 0.154478
+-0.0435208 -0.33986 0.123679
+-0.0907751 -0.296412 0.1426
+
+-0.0393755 -0.307489 0.1118
+-0.0907751 -0.296412 0.1426
+-0.0435208 -0.33986 0.123679
+
+-0.0907751 -0.296412 0.1426
+-0.0393755 -0.307489 0.1118
+-0.0829847 -0.270973 0.120276
+
+-0.0359963 -0.2811 0.0894766
+-0.0829847 -0.270973 0.120276
+-0.0393755 -0.307489 0.1118
+
+-0.0829847 -0.270973 0.120276
+-0.0359963 -0.2811 0.0894766
+-0.0778999 -0.25437 0.0901995
+
+-0.0337906 -0.263876 0.0593998
+-0.0778999 -0.25437 0.0901995
+-0.0359963 -0.2811 0.0894766
+
+-0.0778999 -0.25437 0.0901995
+-0.0337906 -0.263876 0.0593998
+-0.0761339 -0.248603 0.0559975
+
+-0.0330246 -0.257894 0.0251978
+-0.0761339 -0.248603 0.0559975
+-0.0337906 -0.263876 0.0593998
+
+-0.0761339 -0.248603 0.0559975
+-0.0330246 -0.257894 0.0251978
+-0.0778999 -0.25437 0.0217955
+
+-0.0337906 -0.263876 -0.00900421
+-0.0778999 -0.25437 0.0217955
+-0.0330246 -0.257894 0.0251978
+
+-0.0778999 -0.25437 0.0217955
+-0.0337906 -0.263876 -0.00900421
+-0.0829847 -0.270973 -0.00828128
+
+-0.0359963 -0.2811 -0.039081
+-0.0829847 -0.270973 -0.00828128
+-0.0337906 -0.263876 -0.00900421
+
+-0.0829847 -0.270973 -0.00828128
+-0.0359963 -0.2811 -0.039081
+-0.0907751 -0.296412 -0.0306051
+
+-0.0393755 -0.307489 -0.0614047
+-0.0907751 -0.296412 -0.0306051
+-0.0359963 -0.2811 -0.039081
+
+-0.0907751 -0.296412 -0.0306051
+-0.0393755 -0.307489 -0.0614047
+-0.100331 -0.327616 -0.0424833
+
+-0.0435208 -0.33986 -0.073283
+-0.100331 -0.327616 -0.0424833
+-0.0393755 -0.307489 -0.0614047
+
+-0.100331 -0.327616 -0.0424833
+-0.0435208 -0.33986 -0.073283
+-0.110501 -0.360824 -0.0424833
+
+-0.0479321 -0.374308 -0.073283
+-0.110501 -0.360824 -0.0424833
+-0.0435208 -0.33986 -0.073283
+
+-0.110501 -0.360824 -0.0424833
+-0.0479321 -0.374308 -0.073283
+-0.120057 -0.392028 -0.0306051
+
+-0.0520773 -0.406679 -0.0614047
+-0.120057 -0.392028 -0.0306051
+-0.0479321 -0.374308 -0.073283
+
+-0.120057 -0.392028 -0.0306051
+-0.0520773 -0.406679 -0.0614047
+-0.127848 -0.417467 -0.00828128
+
+-0.0554565 -0.433068 -0.039081
+-0.127848 -0.417467 -0.00828128
+-0.0520773 -0.406679 -0.0614047
+
+-0.127848 -0.417467 -0.00828128
+-0.0554565 -0.433068 -0.039081
+-0.132933 -0.43407 0.0217955
+
+-0.0576622 -0.450292 -0.00900421
+-0.132933 -0.43407 0.0217955
+-0.0554565 -0.433068 -0.039081
+
+-0.132933 -0.43407 0.0217955
+-0.0576622 -0.450292 -0.00900421
+-0.134698 -0.439837 0.0559975
+
+-0.0584282 -0.456274 0.0251978
+-0.134698 -0.439837 0.0559975
+-0.0576622 -0.450292 -0.00900421
+
+-0.0584282 -0.456274 0.0251978
+0.019523 -0.459586 -0.00848059
+-0.0576622 -0.450292 0.0593998
+
+0.019267 -0.45356 0.0257214
+-0.0576622 -0.450292 0.0593998
+0.019523 -0.459586 -0.00848059
+
+-0.0576622 -0.450292 0.0593998
+0.019267 -0.45356 0.0257214
+-0.0554565 -0.433068 0.0894766
+
+0.01853 -0.436211 0.0557982
+-0.0554565 -0.433068 0.0894766
+0.019267 -0.45356 0.0257214
+
+-0.0554565 -0.433068 0.0894766
+0.01853 -0.436211 0.0557982
+-0.0520773 -0.406679 0.1118
+
+0.0174009 -0.409631 0.0781219
+-0.0520773 -0.406679 0.1118
+0.01853 -0.436211 0.0557982
+
+-0.0520773 -0.406679 0.1118
+0.0174009 -0.409631 0.0781219
+-0.0479321 -0.374308 0.123679
+
+0.0160158 -0.377025 0.0900002
+-0.0479321 -0.374308 0.123679
+0.0174009 -0.409631 0.0781219
+
+-0.0479321 -0.374308 0.123679
+0.0160158 -0.377025 0.0900002
+-0.0435208 -0.33986 0.123679
+
+0.0145418 -0.342326 0.0900002
+-0.0435208 -0.33986 0.123679
+0.0160158 -0.377025 0.0900002
+
+-0.0435208 -0.33986 0.123679
+0.0145418 -0.342326 0.0900002
+-0.0393755 -0.307489 0.1118
+
+0.0131568 -0.309721 0.0781219
+-0.0393755 -0.307489 0.1118
+0.0145418 -0.342326 0.0900002
+
+-0.0393755 -0.307489 0.1118
+0.0131568 -0.309721 0.0781219
+-0.0359963 -0.2811 0.0894766
+
+0.0120276 -0.28314 0.0557982
+-0.0359963 -0.2811 0.0894766
+0.0131568 -0.309721 0.0781219
+
+-0.0359963 -0.2811 0.0894766
+0.0120276 -0.28314 0.0557982
+-0.0337906 -0.263876 0.0593998
+
+0.0112907 -0.265791 0.0257214
+-0.0337906 -0.263876 0.0593998
+0.0120276 -0.28314 0.0557982
+
+-0.0337906 -0.263876 0.0593998
+0.0112907 -0.265791 0.0257214
+-0.0330246 -0.257894 0.0251978
+
+0.0110347 -0.259766 -0.00848059
+-0.0330246 -0.257894 0.0251978
+0.0112907 -0.265791 0.0257214
+
+-0.0330246 -0.257894 0.0251978
+0.0110347 -0.259766 -0.00848059
+-0.0337906 -0.263876 -0.00900421
+
+0.0112907 -0.265791 -0.0426826
+-0.0337906 -0.263876 -0.00900421
+0.0110347 -0.259766 -0.00848059
+
+-0.0337906 -0.263876 -0.00900421
+0.0112907 -0.265791 -0.0426826
+-0.0359963 -0.2811 -0.039081
+
+0.0120276 -0.28314 -0.0727594
+-0.0359963 -0.2811 -0.039081
+0.0112907 -0.265791 -0.0426826
+
+-0.0359963 -0.2811 -0.039081
+0.0120276 -0.28314 -0.0727594
+-0.0393755 -0.307489 -0.0614047
+
+0.0131568 -0.309721 -0.0950831
+-0.0393755 -0.307489 -0.0614047
+0.0120276 -0.28314 -0.0727594
+
+-0.0393755 -0.307489 -0.0614047
+0.0131568 -0.309721 -0.0950831
+-0.0435208 -0.33986 -0.073283
+
+0.0145418 -0.342326 -0.106961
+-0.0435208 -0.33986 -0.073283
+0.0131568 -0.309721 -0.0950831
+
+-0.0435208 -0.33986 -0.073283
+0.0145418 -0.342326 -0.106961
+-0.0479321 -0.374308 -0.073283
+
+0.0160158 -0.377025 -0.106961
+-0.0479321 -0.374308 -0.073283
+0.0145418 -0.342326 -0.106961
+
+-0.0479321 -0.374308 -0.073283
+0.0160158 -0.377025 -0.106961
+-0.0520773 -0.406679 -0.0614047
+
+0.0174009 -0.409631 -0.0950831
+-0.0520773 -0.406679 -0.0614047
+0.0160158 -0.377025 -0.106961
+
+-0.0520773 -0.406679 -0.0614047
+0.0174009 -0.409631 -0.0950831
+-0.0554565 -0.433068 -0.039081
+
+0.01853 -0.436211 -0.0727594
+-0.0554565 -0.433068 -0.039081
+0.0174009 -0.409631 -0.0950831
+
+-0.0554565 -0.433068 -0.039081
+0.01853 -0.436211 -0.0727594
+-0.0576622 -0.450292 -0.00900421
+
+0.019267 -0.45356 -0.0426826
+-0.0576622 -0.450292 -0.00900421
+0.01853 -0.436211 -0.0727594
+
+-0.0576622 -0.450292 -0.00900421
+0.019267 -0.45356 -0.0426826
+-0.0584282 -0.456274 0.0251978
+
+0.019523 -0.459586 -0.00848059
+-0.0584282 -0.456274 0.0251978
+0.019267 -0.45356 -0.0426826
+
+0.019523 -0.459586 -0.00848059
+0.0969125 -0.449675 -0.0411901
+0.019267 -0.45356 0.0257214
+
+0.0956419 -0.44378 -0.00698811
+0.019267 -0.45356 0.0257214
+0.0969125 -0.449675 -0.0411901
+
+0.019267 -0.45356 0.0257214
+0.0956419 -0.44378 -0.00698811
+0.01853 -0.436211 0.0557982
+
+0.0919835 -0.426805 0.0230886
+0.01853 -0.436211 0.0557982
+0.0956419 -0.44378 -0.00698811
+
+0.01853 -0.436211 0.0557982
+0.0919835 -0.426805 0.0230886
+0.0174009 -0.409631 0.0781219
+
+0.0863785 -0.400798 0.0454124
+0.0174009 -0.409631 0.0781219
+0.0919835 -0.426805 0.0230886
+
+0.0174009 -0.409631 0.0781219
+0.0863785 -0.400798 0.0454124
+0.0160158 -0.377025 0.0900002
+
+0.0795029 -0.368895 0.0572907
+0.0160158 -0.377025 0.0900002
+0.0863785 -0.400798 0.0454124
+
+0.0160158 -0.377025 0.0900002
+0.0795029 -0.368895 0.0572907
+0.0145418 -0.342326 0.0900002
+
+0.0721861 -0.334945 0.0572907
+0.0145418 -0.342326 0.0900002
+0.0795029 -0.368895 0.0572907
+
+0.0145418 -0.342326 0.0900002
+0.0721861 -0.334945 0.0572907
+0.0131568 -0.309721 0.0781219
+
+0.0653106 -0.303042 0.0454124
+0.0131568 -0.309721 0.0781219
+0.0721861 -0.334945 0.0572907
+
+0.0131568 -0.309721 0.0781219
+0.0653106 -0.303042 0.0454124
+0.0120276 -0.28314 0.0557982
+
+0.0597056 -0.277035 0.0230886
+0.0120276 -0.28314 0.0557982
+0.0653106 -0.303042 0.0454124
+
+0.0120276 -0.28314 0.0557982
+0.0597056 -0.277035 0.0230886
+0.0112907 -0.265791 0.0257214
+
+0.0560472 -0.26006 -0.00698811
+0.0112907 -0.265791 0.0257214
+0.0597056 -0.277035 0.0230886
+
+0.0112907 -0.265791 0.0257214
+0.0560472 -0.26006 -0.00698811
+0.0110347 -0.259766 -0.00848059
+
+0.0547766 -0.254164 -0.0411901
+0.0110347 -0.259766 -0.00848059
+0.0560472 -0.26006 -0.00698811
+
+0.0110347 -0.259766 -0.00848059
+0.0547766 -0.254164 -0.0411901
+0.0112907 -0.265791 -0.0426826
+
+0.0560472 -0.26006 -0.0753921
+0.0112907 -0.265791 -0.0426826
+0.0547766 -0.254164 -0.0411901
+
+0.0112907 -0.265791 -0.0426826
+0.0560472 -0.26006 -0.0753921
+0.0120276 -0.28314 -0.0727594
+
+0.0597056 -0.277035 -0.105469
+0.0120276 -0.28314 -0.0727594
+0.0560472 -0.26006 -0.0753921
+
+0.0120276 -0.28314 -0.0727594
+0.0597056 -0.277035 -0.105469
+0.0131568 -0.309721 -0.0950831
+
+0.0653106 -0.303042 -0.127793
+0.0131568 -0.309721 -0.0950831
+0.0597056 -0.277035 -0.105469
+
+0.0131568 -0.309721 -0.0950831
+0.0653106 -0.303042 -0.127793
+0.0145418 -0.342326 -0.106961
+
+0.0721861 -0.334945 -0.139671
+0.0145418 -0.342326 -0.106961
+0.0653106 -0.303042 -0.127793
+
+0.0145418 -0.342326 -0.106961
+0.0721861 -0.334945 -0.139671
+0.0160158 -0.377025 -0.106961
+
+0.0795029 -0.368895 -0.139671
+0.0160158 -0.377025 -0.106961
+0.0721861 -0.334945 -0.139671
+
+0.0160158 -0.377025 -0.106961
+0.0795029 -0.368895 -0.139671
+0.0174009 -0.409631 -0.0950831
+
+0.0863785 -0.400798 -0.127793
+0.0174009 -0.409631 -0.0950831
+0.0795029 -0.368895 -0.139671
+
+0.0174009 -0.409631 -0.0950831
+0.0863785 -0.400798 -0.127793
+0.01853 -0.436211 -0.0727594
+
+0.0919835 -0.426805 -0.105469
+0.01853 -0.436211 -0.0727594
+0.0863785 -0.400798 -0.127793
+
+0.01853 -0.436211 -0.0727594
+0.0919835 -0.426805 -0.105469
+0.019267 -0.45356 -0.0426826
+
+0.0956419 -0.44378 -0.0753921
+0.019267 -0.45356 -0.0426826
+0.0919835 -0.426805 -0.105469
+
+0.019267 -0.45356 -0.0426826
+0.0956419 -0.44378 -0.0753921
+0.019523 -0.459586 -0.00848059
+
+0.0969125 -0.449675 -0.0411901
+0.019523 -0.459586 -0.00848059
+0.0956419 -0.44378 -0.0753921
+
+0.0969125 -0.449675 -0.0411901
+0.171514 -0.426829 -0.0691939
+0.0956419 -0.44378 -0.00698811
+
+0.169265 -0.421233 -0.0349919
+0.0956419 -0.44378 -0.00698811
+0.171514 -0.426829 -0.0691939
+
+0.0956419 -0.44378 -0.00698811
+0.169265 -0.421233 -0.0349919
+0.0919835 -0.426805 0.0230886
+
+0.162791 -0.40512 -0.00491513
+0.0919835 -0.426805 0.0230886
+0.169265 -0.421233 -0.0349919
+
+0.0919835 -0.426805 0.0230886
+0.162791 -0.40512 -0.00491513
+0.0863785 -0.400798 0.0454124
+
+0.152871 -0.380435 0.0174087
+0.0863785 -0.400798 0.0454124
+0.162791 -0.40512 -0.00491513
+
+0.0863785 -0.400798 0.0454124
+0.152871 -0.380435 0.0174087
+0.0795029 -0.368895 0.0572907
+
+0.140703 -0.350153 0.0292869
+0.0795029 -0.368895 0.0572907
+0.152871 -0.380435 0.0174087
+
+0.0795029 -0.368895 0.0572907
+0.140703 -0.350153 0.0292869
+0.0721861 -0.334945 0.0572907
+
+0.127754 -0.317927 0.0292869
+0.0721861 -0.334945 0.0572907
+0.140703 -0.350153 0.0292869
+
+0.0721861 -0.334945 0.0572907
+0.127754 -0.317927 0.0292869
+0.0653106 -0.303042 0.0454124
+
+0.115586 -0.287646 0.0174087
+0.0653106 -0.303042 0.0454124
+0.127754 -0.317927 0.0292869
+
+0.0653106 -0.303042 0.0454124
+0.115586 -0.287646 0.0174087
+0.0597056 -0.277035 0.0230886
+
+0.105666 -0.26296 -0.00491513
+0.0597056 -0.277035 0.0230886
+0.115586 -0.287646 0.0174087
+
+0.0597056 -0.277035 0.0230886
+0.105666 -0.26296 -0.00491513
+0.0560472 -0.26006 -0.00698811
+
+0.0991913 -0.246847 -0.0349919
+0.0560472 -0.26006 -0.00698811
+0.105666 -0.26296 -0.00491513
+
+0.0560472 -0.26006 -0.00698811
+0.0991913 -0.246847 -0.0349919
+0.0547766 -0.254164 -0.0411901
+
+0.0969427 -0.241251 -0.0691939
+0.0547766 -0.254164 -0.0411901
+0.0991913 -0.246847 -0.0349919
+
+0.0547766 -0.254164 -0.0411901
+0.0969427 -0.241251 -0.0691939
+0.0560472 -0.26006 -0.0753921
+
+0.0991913 -0.246847 -0.103396
+0.0560472 -0.26006 -0.0753921
+0.0969427 -0.241251 -0.0691939
+
+0.0560472 -0.26006 -0.0753921
+0.0991913 -0.246847 -0.103396
+0.0597056 -0.277035 -0.105469
+
+0.105666 -0.26296 -0.133473
+0.0597056 -0.277035 -0.105469
+0.0991913 -0.246847 -0.103396
+
+0.0597056 -0.277035 -0.105469
+0.105666 -0.26296 -0.133473
+0.0653106 -0.303042 -0.127793
+
+0.115586 -0.287646 -0.155796
+0.0653106 -0.303042 -0.127793
+0.105666 -0.26296 -0.133473
+
+0.0653106 -0.303042 -0.127793
+0.115586 -0.287646 -0.155796
+0.0721861 -0.334945 -0.139671
+
+0.127754 -0.317927 -0.167675
+0.0721861 -0.334945 -0.139671
+0.115586 -0.287646 -0.155796
+
+0.0721861 -0.334945 -0.139671
+0.127754 -0.317927 -0.167675
+0.0795029 -0.368895 -0.139671
+
+0.140703 -0.350153 -0.167675
+0.0795029 -0.368895 -0.139671
+0.127754 -0.317927 -0.167675
+
+0.0795029 -0.368895 -0.139671
+0.140703 -0.350153 -0.167675
+0.0863785 -0.400798 -0.127793
+
+0.152871 -0.380435 -0.155796
+0.0863785 -0.400798 -0.127793
+0.140703 -0.350153 -0.167675
+
+0.0863785 -0.400798 -0.127793
+0.152871 -0.380435 -0.155796
+0.0919835 -0.426805 -0.105469
+
+0.162791 -0.40512 -0.133473
+0.0919835 -0.426805 -0.105469
+0.152871 -0.380435 -0.155796
+
+0.0919835 -0.426805 -0.105469
+0.162791 -0.40512 -0.133473
+0.0956419 -0.44378 -0.0753921
+
+0.169265 -0.421233 -0.103396
+0.0956419 -0.44378 -0.0753921
+0.162791 -0.40512 -0.133473
+
+0.0956419 -0.44378 -0.0753921
+0.169265 -0.421233 -0.103396
+0.0969125 -0.449675 -0.0411901
+
+0.171514 -0.426829 -0.0691939
+0.0969125 -0.449675 -0.0411901
+0.169265 -0.421233 -0.103396
+
+0.171514 -0.426829 -0.0691939
+0.241181 -0.391703 -0.0892926
+0.169265 -0.421233 -0.0349919
+
+0.238019 -0.386568 -0.0550906
+0.169265 -0.421233 -0.0349919
+0.241181 -0.391703 -0.0892926
+
+0.169265 -0.421233 -0.0349919
+0.238019 -0.386568 -0.0550906
+0.162791 -0.40512 -0.00491513
+
+0.228915 -0.371781 -0.0250138
+0.162791 -0.40512 -0.00491513
+0.238019 -0.386568 -0.0550906
+
+0.162791 -0.40512 -0.00491513
+0.228915 -0.371781 -0.0250138
+0.152871 -0.380435 0.0174087
+
+0.214966 -0.349127 -0.00269005
+0.152871 -0.380435 0.0174087
+0.228915 -0.371781 -0.0250138
+
+0.152871 -0.380435 0.0174087
+0.214966 -0.349127 -0.00269005
+0.140703 -0.350153 0.0292869
+
+0.197855 -0.321337 0.00918819
+0.140703 -0.350153 0.0292869
+0.214966 -0.349127 -0.00269005
+
+0.140703 -0.350153 0.0292869
+0.197855 -0.321337 0.00918819
+0.127754 -0.317927 0.0292869
+
+0.179646 -0.291764 0.00918819
+0.127754 -0.317927 0.0292869
+0.197855 -0.321337 0.00918819
+
+0.127754 -0.317927 0.0292869
+0.179646 -0.291764 0.00918819
+0.115586 -0.287646 0.0174087
+
+0.162535 -0.263974 -0.00269005
+0.115586 -0.287646 0.0174087
+0.179646 -0.291764 0.00918819
+
+0.115586 -0.287646 0.0174087
+0.162535 -0.263974 -0.00269005
+0.105666 -0.26296 -0.00491513
+
+0.148586 -0.24132 -0.0250138
+0.105666 -0.26296 -0.00491513
+0.162535 -0.263974 -0.00269005
+
+0.105666 -0.26296 -0.00491513
+0.148586 -0.24132 -0.0250138
+0.0991913 -0.246847 -0.0349919
+
+0.139482 -0.226533 -0.0550906
+0.0991913 -0.246847 -0.0349919
+0.148586 -0.24132 -0.0250138
+
+0.0991913 -0.246847 -0.0349919
+0.139482 -0.226533 -0.0550906
+0.0969427 -0.241251 -0.0691939
+
+0.13632 -0.221398 -0.0892926
+0.0969427 -0.241251 -0.0691939
+0.139482 -0.226533 -0.0550906
+
+0.0969427 -0.241251 -0.0691939
+0.13632 -0.221398 -0.0892926
+0.0991913 -0.246847 -0.103396
+
+0.139482 -0.226533 -0.123495
+0.0991913 -0.246847 -0.103396
+0.13632 -0.221398 -0.0892926
+
+0.0991913 -0.246847 -0.103396
+0.139482 -0.226533 -0.123495
+0.105666 -0.26296 -0.133473
+
+0.148586 -0.24132 -0.153571
+0.105666 -0.26296 -0.133473
+0.139482 -0.226533 -0.123495
+
+0.105666 -0.26296 -0.133473
+0.148586 -0.24132 -0.153571
+0.115586 -0.287646 -0.155796
+
+0.162535 -0.263974 -0.175895
+0.115586 -0.287646 -0.155796
+0.148586 -0.24132 -0.153571
+
+0.115586 -0.287646 -0.155796
+0.162535 -0.263974 -0.175895
+0.127754 -0.317927 -0.167675
+
+0.179646 -0.291764 -0.187773
+0.127754 -0.317927 -0.167675
+0.162535 -0.263974 -0.175895
+
+0.127754 -0.317927 -0.167675
+0.179646 -0.291764 -0.187773
+0.140703 -0.350153 -0.167675
+
+0.197855 -0.321337 -0.187773
+0.140703 -0.350153 -0.167675
+0.179646 -0.291764 -0.187773
+
+0.140703 -0.350153 -0.167675
+0.197855 -0.321337 -0.187773
+0.152871 -0.380435 -0.155796
+
+0.214966 -0.349127 -0.175895
+0.152871 -0.380435 -0.155796
+0.197855 -0.321337 -0.187773
+
+0.152871 -0.380435 -0.155796
+0.214966 -0.349127 -0.175895
+0.162791 -0.40512 -0.133473
+
+0.228915 -0.371781 -0.153571
+0.162791 -0.40512 -0.133473
+0.214966 -0.349127 -0.175895
+
+0.162791 -0.40512 -0.133473
+0.228915 -0.371781 -0.153571
+0.169265 -0.421233 -0.103396
+
+0.238019 -0.386568 -0.123495
+0.169265 -0.421233 -0.103396
+0.228915 -0.371781 -0.153571
+
+0.169265 -0.421233 -0.103396
+0.238019 -0.386568 -0.123495
+0.171514 -0.426829 -0.0691939
+
+0.241181 -0.391703 -0.0892926
+0.171514 -0.426829 -0.0691939
+0.238019 -0.386568 -0.123495
+
+0.241181 -0.391703 -0.0892926
+0.30391 -0.345309 -0.09919
+0.238019 -0.386568 -0.0550906
+
+0.299926 -0.340782 -0.064988
+0.238019 -0.386568 -0.0550906
+0.30391 -0.345309 -0.09919
+
+0.238019 -0.386568 -0.0550906
+0.299926 -0.340782 -0.064988
+0.228915 -0.371781 -0.0250138
+
+0.288454 -0.327747 -0.0349113
+0.228915 -0.371781 -0.0250138
+0.299926 -0.340782 -0.064988
+
+0.228915 -0.371781 -0.0250138
+0.288454 -0.327747 -0.0349113
+0.214966 -0.349127 -0.00269005
+
+0.270877 -0.307776 -0.0125875
+0.214966 -0.349127 -0.00269005
+0.288454 -0.327747 -0.0349113
+
+0.214966 -0.349127 -0.00269005
+0.270877 -0.307776 -0.0125875
+0.197855 -0.321337 0.00918819
+
+0.249315 -0.283277 -0.000709268
+0.197855 -0.321337 0.00918819
+0.270877 -0.307776 -0.0125875
+
+0.197855 -0.321337 0.00918819
+0.249315 -0.283277 -0.000709268
+0.179646 -0.291764 0.00918819
+
+0.22637 -0.257207 -0.000709268
+0.179646 -0.291764 0.00918819
+0.249315 -0.283277 -0.000709268
+
+0.179646 -0.291764 0.00918819
+0.22637 -0.257207 -0.000709268
+0.162535 -0.263974 -0.00269005
+
+0.204809 -0.232708 -0.0125875
+0.162535 -0.263974 -0.00269005
+0.22637 -0.257207 -0.000709268
+
+0.162535 -0.263974 -0.00269005
+0.204809 -0.232708 -0.0125875
+0.148586 -0.24132 -0.0250138
+
+0.187232 -0.212737 -0.0349113
+0.148586 -0.24132 -0.0250138
+0.204809 -0.232708 -0.0125875
+
+0.148586 -0.24132 -0.0250138
+0.187232 -0.212737 -0.0349113
+0.139482 -0.226533 -0.0550906
+
+0.17576 -0.199702 -0.064988
+0.139482 -0.226533 -0.0550906
+0.187232 -0.212737 -0.0349113
+
+0.139482 -0.226533 -0.0550906
+0.17576 -0.199702 -0.064988
+0.13632 -0.221398 -0.0892926
+
+0.171775 -0.195175 -0.09919
+0.13632 -0.221398 -0.0892926
+0.17576 -0.199702 -0.064988
+
+0.13632 -0.221398 -0.0892926
+0.171775 -0.195175 -0.09919
+0.139482 -0.226533 -0.123495
+
+0.17576 -0.199702 -0.133392
+0.139482 -0.226533 -0.123495
+0.171775 -0.195175 -0.09919
+
+0.139482 -0.226533 -0.123495
+0.17576 -0.199702 -0.133392
+0.148586 -0.24132 -0.153571
+
+0.187232 -0.212737 -0.163469
+0.148586 -0.24132 -0.153571
+0.17576 -0.199702 -0.133392
+
+0.148586 -0.24132 -0.153571
+0.187232 -0.212737 -0.163469
+0.162535 -0.263974 -0.175895
+
+0.204809 -0.232708 -0.185793
+0.162535 -0.263974 -0.175895
+0.187232 -0.212737 -0.163469
+
+0.162535 -0.263974 -0.175895
+0.204809 -0.232708 -0.185793
+0.179646 -0.291764 -0.187773
+
+0.22637 -0.257207 -0.197671
+0.179646 -0.291764 -0.187773
+0.204809 -0.232708 -0.185793
+
+0.179646 -0.291764 -0.187773
+0.22637 -0.257207 -0.197671
+0.197855 -0.321337 -0.187773
+
+0.249315 -0.283277 -0.197671
+0.197855 -0.321337 -0.187773
+0.22637 -0.257207 -0.197671
+
+0.197855 -0.321337 -0.187773
+0.249315 -0.283277 -0.197671
+0.214966 -0.349127 -0.175895
+
+0.270877 -0.307776 -0.185793
+0.214966 -0.349127 -0.175895
+0.249315 -0.283277 -0.197671
+
+0.214966 -0.349127 -0.175895
+0.270877 -0.307776 -0.185793
+0.228915 -0.371781 -0.153571
+
+0.288454 -0.327747 -0.163469
+0.228915 -0.371781 -0.153571
+0.270877 -0.307776 -0.185793
+
+0.228915 -0.371781 -0.153571
+0.288454 -0.327747 -0.163469
+0.238019 -0.386568 -0.123495
+
+0.299926 -0.340782 -0.133392
+0.238019 -0.386568 -0.123495
+0.288454 -0.327747 -0.163469
+
+0.238019 -0.386568 -0.123495
+0.299926 -0.340782 -0.133392
+0.241181 -0.391703 -0.0892926
+
+0.30391 -0.345309 -0.09919
+0.241181 -0.391703 -0.0892926
+0.299926 -0.340782 -0.133392
+
+0.30391 -0.345309 -0.09919
+0.357896 -0.288981 -0.0977555
+0.299926 -0.340782 -0.064988
+
+0.353204 -0.285193 -0.0635535
+0.299926 -0.340782 -0.064988
+0.357896 -0.288981 -0.0977555
+
+0.299926 -0.340782 -0.064988
+0.353204 -0.285193 -0.0635535
+0.288454 -0.327747 -0.0349113
+
+0.339694 -0.274284 -0.0334768
+0.288454 -0.327747 -0.0349113
+0.353204 -0.285193 -0.0635535
+
+0.288454 -0.327747 -0.0349113
+0.339694 -0.274284 -0.0334768
+0.270877 -0.307776 -0.0125875
+
+0.318995 -0.25757 -0.011153
+0.270877 -0.307776 -0.0125875
+0.339694 -0.274284 -0.0334768
+
+0.270877 -0.307776 -0.0125875
+0.318995 -0.25757 -0.011153
+0.249315 -0.283277 -0.000709268
+
+0.293603 -0.237068 0.000725251
+0.249315 -0.283277 -0.000709268
+0.318995 -0.25757 -0.011153
+
+0.249315 -0.283277 -0.000709268
+0.293603 -0.237068 0.000725251
+0.22637 -0.257207 -0.000709268
+
+0.266582 -0.21525 0.000725251
+0.22637 -0.257207 -0.000709268
+0.293603 -0.237068 0.000725251
+
+0.22637 -0.257207 -0.000709268
+0.266582 -0.21525 0.000725251
+0.204809 -0.232708 -0.0125875
+
+0.241191 -0.194748 -0.011153
+0.204809 -0.232708 -0.0125875
+0.266582 -0.21525 0.000725251
+
+0.204809 -0.232708 -0.0125875
+0.241191 -0.194748 -0.011153
+0.187232 -0.212737 -0.0349113
+
+0.220492 -0.178035 -0.0334768
+0.187232 -0.212737 -0.0349113
+0.241191 -0.194748 -0.011153
+
+0.187232 -0.212737 -0.0349113
+0.220492 -0.178035 -0.0334768
+0.17576 -0.199702 -0.064988
+
+0.206981 -0.167126 -0.0635535
+0.17576 -0.199702 -0.064988
+0.220492 -0.178035 -0.0334768
+
+0.17576 -0.199702 -0.064988
+0.206981 -0.167126 -0.0635535
+0.171775 -0.195175 -0.09919
+
+0.202289 -0.163337 -0.0977555
+0.171775 -0.195175 -0.09919
+0.206981 -0.167126 -0.0635535
+
+0.171775 -0.195175 -0.09919
+0.202289 -0.163337 -0.0977555
+0.17576 -0.199702 -0.133392
+
+0.206981 -0.167126 -0.131958
+0.17576 -0.199702 -0.133392
+0.202289 -0.163337 -0.0977555
+
+0.17576 -0.199702 -0.133392
+0.206981 -0.167126 -0.131958
+0.187232 -0.212737 -0.163469
+
+0.220492 -0.178035 -0.162034
+0.187232 -0.212737 -0.163469
+0.206981 -0.167126 -0.131958
+
+0.187232 -0.212737 -0.163469
+0.220492 -0.178035 -0.162034
+0.204809 -0.232708 -0.185793
+
+0.241191 -0.194748 -0.184358
+0.204809 -0.232708 -0.185793
+0.220492 -0.178035 -0.162034
+
+0.204809 -0.232708 -0.185793
+0.241191 -0.194748 -0.184358
+0.22637 -0.257207 -0.197671
+
+0.266582 -0.21525 -0.196236
+0.22637 -0.257207 -0.197671
+0.241191 -0.194748 -0.184358
+
+0.22637 -0.257207 -0.197671
+0.266582 -0.21525 -0.196236
+0.249315 -0.283277 -0.197671
+
+0.293603 -0.237068 -0.196236
+0.249315 -0.283277 -0.197671
+0.266582 -0.21525 -0.196236
+
+0.249315 -0.283277 -0.197671
+0.293603 -0.237068 -0.196236
+0.270877 -0.307776 -0.185793
+
+0.318995 -0.25757 -0.184358
+0.270877 -0.307776 -0.185793
+0.293603 -0.237068 -0.196236
+
+0.270877 -0.307776 -0.185793
+0.318995 -0.25757 -0.184358
+0.288454 -0.327747 -0.163469
+
+0.339694 -0.274284 -0.162034
+0.288454 -0.327747 -0.163469
+0.318995 -0.25757 -0.184358
+
+0.288454 -0.327747 -0.163469
+0.339694 -0.274284 -0.162034
+0.299926 -0.340782 -0.133392
+
+0.353204 -0.285193 -0.131958
+0.299926 -0.340782 -0.133392
+0.339694 -0.274284 -0.162034
+
+0.299926 -0.340782 -0.133392
+0.353204 -0.285193 -0.131958
+0.30391 -0.345309 -0.09919
+
+0.357896 -0.288981 -0.0977555
+0.30391 -0.345309 -0.09919
+0.353204 -0.285193 -0.131958
+
+0.357896 -0.288981 -0.0977555
+0.401586 -0.22434 -0.0851529
+0.353204 -0.285193 -0.0635535
+
+0.396322 -0.221399 -0.0509509
+0.353204 -0.285193 -0.0635535
+0.401586 -0.22434 -0.0851529
+
+0.353204 -0.285193 -0.0635535
+0.396322 -0.221399 -0.0509509
+0.339694 -0.274284 -0.0334768
+
+0.381162 -0.21293 -0.0208742
+0.339694 -0.274284 -0.0334768
+0.396322 -0.221399 -0.0509509
+
+0.339694 -0.274284 -0.0334768
+0.381162 -0.21293 -0.0208742
+0.318995 -0.25757 -0.011153
+
+0.357936 -0.199955 0.00144963
+0.318995 -0.25757 -0.011153
+0.381162 -0.21293 -0.0208742
+
+0.318995 -0.25757 -0.011153
+0.357936 -0.199955 0.00144963
+0.293603 -0.237068 0.000725251
+
+0.329445 -0.184039 0.0133279
+0.293603 -0.237068 0.000725251
+0.357936 -0.199955 0.00144963
+
+0.293603 -0.237068 0.000725251
+0.329445 -0.184039 0.0133279
+0.266582 -0.21525 0.000725251
+
+0.299125 -0.167101 0.0133279
+0.266582 -0.21525 0.000725251
+0.329445 -0.184039 0.0133279
+
+0.266582 -0.21525 0.000725251
+0.299125 -0.167101 0.0133279
+0.241191 -0.194748 -0.011153
+
+0.270634 -0.151185 0.00144963
+0.241191 -0.194748 -0.011153
+0.299125 -0.167101 0.0133279
+
+0.241191 -0.194748 -0.011153
+0.270634 -0.151185 0.00144963
+0.220492 -0.178035 -0.0334768
+
+0.247408 -0.138211 -0.0208742
+0.220492 -0.178035 -0.0334768
+0.270634 -0.151185 0.00144963
+
+0.220492 -0.178035 -0.0334768
+0.247408 -0.138211 -0.0208742
+0.206981 -0.167126 -0.0635535
+
+0.232249 -0.129742 -0.0509509
+0.206981 -0.167126 -0.0635535
+0.247408 -0.138211 -0.0208742
+
+0.206981 -0.167126 -0.0635535
+0.232249 -0.129742 -0.0509509
+0.202289 -0.163337 -0.0977555
+
+0.226984 -0.126801 -0.0851529
+0.202289 -0.163337 -0.0977555
+0.232249 -0.129742 -0.0509509
+
+0.202289 -0.163337 -0.0977555
+0.226984 -0.126801 -0.0851529
+0.206981 -0.167126 -0.131958
+
+0.232249 -0.129742 -0.119355
+0.206981 -0.167126 -0.131958
+0.226984 -0.126801 -0.0851529
+
+0.206981 -0.167126 -0.131958
+0.232249 -0.129742 -0.119355
+0.220492 -0.178035 -0.162034
+
+0.247408 -0.138211 -0.149432
+0.220492 -0.178035 -0.162034
+0.232249 -0.129742 -0.119355
+
+0.220492 -0.178035 -0.162034
+0.247408 -0.138211 -0.149432
+0.241191 -0.194748 -0.184358
+
+0.270634 -0.151185 -0.171755
+0.241191 -0.194748 -0.184358
+0.247408 -0.138211 -0.149432
+
+0.241191 -0.194748 -0.184358
+0.270634 -0.151185 -0.171755
+0.266582 -0.21525 -0.196236
+
+0.299125 -0.167101 -0.183634
+0.266582 -0.21525 -0.196236
+0.270634 -0.151185 -0.171755
+
+0.266582 -0.21525 -0.196236
+0.299125 -0.167101 -0.183634
+0.293603 -0.237068 -0.196236
+
+0.329445 -0.184039 -0.183634
+0.293603 -0.237068 -0.196236
+0.299125 -0.167101 -0.183634
+
+0.293603 -0.237068 -0.196236
+0.329445 -0.184039 -0.183634
+0.318995 -0.25757 -0.184358
+
+0.357936 -0.199955 -0.171755
+0.318995 -0.25757 -0.184358
+0.329445 -0.184039 -0.183634
+
+0.318995 -0.25757 -0.184358
+0.357936 -0.199955 -0.171755
+0.339694 -0.274284 -0.162034
+
+0.381162 -0.21293 -0.149432
+0.339694 -0.274284 -0.162034
+0.357936 -0.199955 -0.171755
+
+0.339694 -0.274284 -0.162034
+0.381162 -0.21293 -0.149432
+0.353204 -0.285193 -0.131958
+
+0.396322 -0.221399 -0.119355
+0.353204 -0.285193 -0.131958
+0.381162 -0.21293 -0.149432
+
+0.353204 -0.285193 -0.131958
+0.396322 -0.221399 -0.119355
+0.357896 -0.288981 -0.0977555
+
+0.401586 -0.22434 -0.0851529
+0.357896 -0.288981 -0.0977555
+0.396322 -0.221399 -0.119355
+
+0.401586 -0.22434 -0.0851529
+0.433724 -0.153244 -0.062822
+0.396322 -0.221399 -0.0509509
+
+0.428037 -0.151235 -0.02862
+0.396322 -0.221399 -0.0509509
+0.433724 -0.153244 -0.062822
+
+0.396322 -0.221399 -0.0509509
+0.428037 -0.151235 -0.02862
+0.381162 -0.21293 -0.0208742
+
+0.411664 -0.14545 0.00145676
+0.381162 -0.21293 -0.0208742
+0.428037 -0.151235 -0.02862
+
+0.381162 -0.21293 -0.0208742
+0.411664 -0.14545 0.00145676
+0.357936 -0.199955 0.00144963
+
+0.38658 -0.136587 0.0237805
+0.357936 -0.199955 0.00144963
+0.411664 -0.14545 0.00145676
+
+0.357936 -0.199955 0.00144963
+0.38658 -0.136587 0.0237805
+0.329445 -0.184039 0.0133279
+
+0.355809 -0.125715 0.0356588
+0.329445 -0.184039 0.0133279
+0.38658 -0.136587 0.0237805
+
+0.329445 -0.184039 0.0133279
+0.355809 -0.125715 0.0356588
+0.299125 -0.167101 0.0133279
+
+0.323063 -0.114145 0.0356588
+0.299125 -0.167101 0.0133279
+0.355809 -0.125715 0.0356588
+
+0.299125 -0.167101 0.0133279
+0.323063 -0.114145 0.0356588
+0.270634 -0.151185 0.00144963
+
+0.292292 -0.103273 0.0237805
+0.270634 -0.151185 0.00144963
+0.323063 -0.114145 0.0356588
+
+0.270634 -0.151185 0.00144963
+0.292292 -0.103273 0.0237805
+0.247408 -0.138211 -0.0208742
+
+0.267207 -0.0944103 0.00145676
+0.247408 -0.138211 -0.0208742
+0.292292 -0.103273 0.0237805
+
+0.247408 -0.138211 -0.0208742
+0.267207 -0.0944103 0.00145676
+0.232249 -0.129742 -0.0509509
+
+0.250834 -0.0886254 -0.02862
+0.232249 -0.129742 -0.0509509
+0.267207 -0.0944103 0.00145676
+
+0.232249 -0.129742 -0.0509509
+0.250834 -0.0886254 -0.02862
+0.226984 -0.126801 -0.0851529
+
+0.245148 -0.0866163 -0.062822
+0.226984 -0.126801 -0.0851529
+0.250834 -0.0886254 -0.02862
+
+0.226984 -0.126801 -0.0851529
+0.245148 -0.0866163 -0.062822
+0.232249 -0.129742 -0.119355
+
+0.250834 -0.0886254 -0.097024
+0.232249 -0.129742 -0.119355
+0.245148 -0.0866163 -0.062822
+
+0.232249 -0.129742 -0.119355
+0.250834 -0.0886254 -0.097024
+0.247408 -0.138211 -0.149432
+
+0.267207 -0.0944103 -0.127101
+0.247408 -0.138211 -0.149432
+0.250834 -0.0886254 -0.097024
+
+0.247408 -0.138211 -0.149432
+0.267207 -0.0944103 -0.127101
+0.270634 -0.151185 -0.171755
+
+0.292292 -0.103273 -0.149425
+0.270634 -0.151185 -0.171755
+0.267207 -0.0944103 -0.127101
+
+0.270634 -0.151185 -0.171755
+0.292292 -0.103273 -0.149425
+0.299125 -0.167101 -0.183634
+
+0.323063 -0.114145 -0.161303
+0.299125 -0.167101 -0.183634
+0.292292 -0.103273 -0.149425
+
+0.299125 -0.167101 -0.183634
+0.323063 -0.114145 -0.161303
+0.329445 -0.184039 -0.183634
+
+0.355809 -0.125715 -0.161303
+0.329445 -0.184039 -0.183634
+0.323063 -0.114145 -0.161303
+
+0.329445 -0.184039 -0.183634
+0.355809 -0.125715 -0.161303
+0.357936 -0.199955 -0.171755
+
+0.38658 -0.136587 -0.149425
+0.357936 -0.199955 -0.171755
+0.355809 -0.125715 -0.161303
+
+0.357936 -0.199955 -0.171755
+0.38658 -0.136587 -0.149425
+0.381162 -0.21293 -0.149432
+
+0.411664 -0.14545 -0.127101
+0.381162 -0.21293 -0.149432
+0.38658 -0.136587 -0.149425
+
+0.381162 -0.21293 -0.149432
+0.411664 -0.14545 -0.127101
+0.396322 -0.221399 -0.119355
+
+0.428037 -0.151235 -0.097024
+0.396322 -0.221399 -0.119355
+0.411664 -0.14545 -0.127101
+
+0.396322 -0.221399 -0.119355
+0.428037 -0.151235 -0.097024
+0.401586 -0.22434 -0.0851529
+
+0.433724 -0.153244 -0.062822
+0.401586 -0.22434 -0.0851529
+0.428037 -0.151235 -0.097024
+
+0.433724 -0.153244 -0.062822
+0.453383 -0.0777404 -0.033314
+0.428037 -0.151235 -0.02862
+
+0.447439 -0.0767212 0.000888035
+0.428037 -0.151235 -0.02862
+0.453383 -0.0777404 -0.033314
+
+0.428037 -0.151235 -0.02862
+0.447439 -0.0767212 0.000888035
+0.411664 -0.14545 0.00145676
+
+0.430324 -0.0737865 0.0309648
+0.411664 -0.14545 0.00145676
+0.447439 -0.0767212 0.000888035
+
+0.411664 -0.14545 0.00145676
+0.430324 -0.0737865 0.0309648
+0.38658 -0.136587 0.0237805
+
+0.404103 -0.0692903 0.0532886
+0.38658 -0.136587 0.0237805
+0.430324 -0.0737865 0.0309648
+
+0.38658 -0.136587 0.0237805
+0.404103 -0.0692903 0.0532886
+0.355809 -0.125715 0.0356588
+
+0.371937 -0.063775 0.0651668
+0.355809 -0.125715 0.0356588
+0.404103 -0.0692903 0.0532886
+
+0.355809 -0.125715 0.0356588
+0.371937 -0.063775 0.0651668
+0.323063 -0.114145 0.0356588
+
+0.337707 -0.0579056 0.0651668
+0.323063 -0.114145 0.0356588
+0.371937 -0.063775 0.0651668
+
+0.323063 -0.114145 0.0356588
+0.337707 -0.0579056 0.0651668
+0.292292 -0.103273 0.0237805
+
+0.305541 -0.0523903 0.0532886
+0.292292 -0.103273 0.0237805
+0.337707 -0.0579056 0.0651668
+
+0.292292 -0.103273 0.0237805
+0.305541 -0.0523903 0.0532886
+0.267207 -0.0944103 0.00145676
+
+0.279319 -0.0478941 0.0309648
+0.267207 -0.0944103 0.00145676
+0.305541 -0.0523903 0.0532886
+
+0.267207 -0.0944103 0.00145676
+0.279319 -0.0478941 0.0309648
+0.250834 -0.0886254 -0.02862
+
+0.262204 -0.0449594 0.000888035
+0.250834 -0.0886254 -0.02862
+0.279319 -0.0478941 0.0309648
+
+0.250834 -0.0886254 -0.02862
+0.262204 -0.0449594 0.000888035
+0.245148 -0.0866163 -0.062822
+
+0.25626 -0.0439402 -0.033314
+0.245148 -0.0866163 -0.062822
+0.262204 -0.0449594 0.000888035
+
+0.245148 -0.0866163 -0.062822
+0.25626 -0.0439402 -0.033314
+0.250834 -0.0886254 -0.097024
+
+0.262204 -0.0449594 -0.067516
+0.250834 -0.0886254 -0.097024
+0.25626 -0.0439402 -0.033314
+
+0.250834 -0.0886254 -0.097024
+0.262204 -0.0449594 -0.067516
+0.267207 -0.0944103 -0.127101
+
+0.279319 -0.0478941 -0.0975927
+0.267207 -0.0944103 -0.127101
+0.262204 -0.0449594 -0.067516
+
+0.267207 -0.0944103 -0.127101
+0.279319 -0.0478941 -0.0975927
+0.292292 -0.103273 -0.149425
+
+0.305541 -0.0523903 -0.119917
+0.292292 -0.103273 -0.149425
+0.279319 -0.0478941 -0.0975927
+
+0.292292 -0.103273 -0.149425
+0.305541 -0.0523903 -0.119917
+0.323063 -0.114145 -0.161303
+
+0.337707 -0.0579056 -0.131795
+0.323063 -0.114145 -0.161303
+0.305541 -0.0523903 -0.119917
+
+0.323063 -0.114145 -0.161303
+0.337707 -0.0579056 -0.131795
+0.355809 -0.125715 -0.161303
+
+0.371937 -0.063775 -0.131795
+0.355809 -0.125715 -0.161303
+0.337707 -0.0579056 -0.131795
+
+0.355809 -0.125715 -0.161303
+0.371937 -0.063775 -0.131795
+0.38658 -0.136587 -0.149425
+
+0.404103 -0.0692903 -0.119917
+0.38658 -0.136587 -0.149425
+0.371937 -0.063775 -0.131795
+
+0.38658 -0.136587 -0.149425
+0.404103 -0.0692903 -0.119917
+0.411664 -0.14545 -0.127101
+
+0.430324 -0.0737865 -0.0975927
+0.411664 -0.14545 -0.127101
+0.404103 -0.0692903 -0.119917
+
+0.411664 -0.14545 -0.127101
+0.430324 -0.0737865 -0.0975927
+0.428037 -0.151235 -0.097024
+
+0.447439 -0.0767212 -0.067516
+0.428037 -0.151235 -0.097024
+0.430324 -0.0737865 -0.0975927
+
+0.428037 -0.151235 -0.097024
+0.447439 -0.0767212 -0.067516
+0.433724 -0.153244 -0.062822
+
+0.453383 -0.0777404 -0.033314
+0.433724 -0.153244 -0.062822
+0.447439 -0.0767212 -0.067516
+
+0.453383 -0.0777404 -0.033314
+0.46 0 0
+0.447439 -0.0767212 0.000888035
+
+0.453969 0 0.034202
+0.447439 -0.0767212 0.000888035
+0.46 0 0
+
+0.447439 -0.0767212 0.000888035
+0.453969 0 0.034202
+0.430324 -0.0737865 0.0309648
+
+0.436604 0 0.0642788
+0.430324 -0.0737865 0.0309648
+0.453969 0 0.034202
+
+0.430324 -0.0737865 0.0309648
+0.436604 0 0.0642788
+0.404103 -0.0692903 0.0532886
+
+0.41 0 0.0866025
+0.404103 -0.0692903 0.0532886
+0.436604 0 0.0642788
+
+0.404103 -0.0692903 0.0532886
+0.41 0 0.0866025
+0.371937 -0.063775 0.0651668
+
+0.377365 0 0.0984808
+0.371937 -0.063775 0.0651668
+0.41 0 0.0866025
+
+0.371937 -0.063775 0.0651668
+0.377365 0 0.0984808
+0.337707 -0.0579056 0.0651668
+
+0.342635 0 0.0984808
+0.337707 -0.0579056 0.0651668
+0.377365 0 0.0984808
+
+0.337707 -0.0579056 0.0651668
+0.342635 0 0.0984808
+0.305541 -0.0523903 0.0532886
+
+0.31 0 0.0866025
+0.305541 -0.0523903 0.0532886
+0.342635 0 0.0984808
+
+0.305541 -0.0523903 0.0532886
+0.31 0 0.0866025
+0.279319 -0.0478941 0.0309648
+
+0.283396 0 0.0642788
+0.279319 -0.0478941 0.0309648
+0.31 0 0.0866025
+
+0.279319 -0.0478941 0.0309648
+0.283396 0 0.0642788
+0.262204 -0.0449594 0.000888035
+
+0.266031 0 0.034202
+0.262204 -0.0449594 0.000888035
+0.283396 0 0.0642788
+
+0.262204 -0.0449594 0.000888035
+0.266031 0 0.034202
+0.25626 -0.0439402 -0.033314
+
+0.26 0 0
+0.25626 -0.0439402 -0.033314
+0.266031 0 0.034202
+
+0.25626 -0.0439402 -0.033314
+0.26 0 0
+0.262204 -0.0449594 -0.067516
+
+0.266031 0 -0.034202
+0.262204 -0.0449594 -0.067516
+0.26 0 0
+
+0.262204 -0.0449594 -0.067516
+0.266031 0 -0.034202
+0.279319 -0.0478941 -0.0975927
+
+0.283396 0 -0.0642788
+0.279319 -0.0478941 -0.0975927
+0.266031 0 -0.034202
+
+0.279319 -0.0478941 -0.0975927
+0.283396 0 -0.0642788
+0.305541 -0.0523903 -0.119917
+
+0.31 0 -0.0866025
+0.305541 -0.0523903 -0.119917
+0.283396 0 -0.0642788
+
+0.305541 -0.0523903 -0.119917
+0.31 0 -0.0866025
+0.337707 -0.0579056 -0.131795
+
+0.342635 0 -0.0984808
+0.337707 -0.0579056 -0.131795
+0.31 0 -0.0866025
+
+0.337707 -0.0579056 -0.131795
+0.342635 0 -0.0984808
+0.371937 -0.063775 -0.131795
+
+0.377365 0 -0.0984808
+0.371937 -0.063775 -0.131795
+0.342635 0 -0.0984808
+
+0.371937 -0.063775 -0.131795
+0.377365 0 -0.0984808
+0.404103 -0.0692903 -0.119917
+
+0.41 0 -0.0866025
+0.404103 -0.0692903 -0.119917
+0.377365 0 -0.0984808
+
+0.404103 -0.0692903 -0.119917
+0.41 0 -0.0866025
+0.430324 -0.0737865 -0.0975927
+
+0.436604 0 -0.0642788
+0.430324 -0.0737865 -0.0975927
+0.41 0 -0.0866025
+
+0.430324 -0.0737865 -0.0975927
+0.436604 0 -0.0642788
+0.447439 -0.0767212 -0.067516
+
+0.453969 0 -0.034202
+0.447439 -0.0767212 -0.067516
+0.436604 0 -0.0642788
+
+0.447439 -0.0767212 -0.067516
+0.453969 0 -0.034202
+0.453383 -0.0777404 -0.033314
+
+0.46 0 0
+0.453383 -0.0777404 -0.033314
+0.453969 0 -0.034202
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.path b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.path
new file mode 100644
index 00000000..54752acc
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.path
@@ -0,0 +1,11991 @@
+2398
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
+1 0 0
+0 1 0
+0 0 1
+0 0 0
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.tris b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.tris
new file mode 100644
index 00000000..115e4e2d
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/falling/torus2.tris
@@ -0,0 +1,12961 @@
+3240
+1 0 0
+1.05291 0.110666 0
+0.992183 0 0.0668786
+
+1.04357 0.109683 0.0804188
+0.992183 0 0.0668786
+1.05291 0.110666 0
+
+0.992183 0 0.0668786
+1.04357 0.109683 0.0804188
+0.969153 0 0.130152
+
+1.01602 0.106789 0.156502
+0.969153 0 0.130152
+1.04357 0.109683 0.0804188
+
+0.969153 0 0.130152
+1.01602 0.106789 0.156502
+0.932153 0 0.186408
+
+0.971777 0.102138 0.224149
+0.932153 0 0.186408
+1.01602 0.106789 0.156502
+
+0.932153 0 0.186408
+0.971777 0.102138 0.224149
+0.883176 0 0.232616
+
+0.913207 0.0959819 0.279711
+0.883176 0 0.232616
+0.971777 0.102138 0.224149
+
+0.883176 0 0.232616
+0.913207 0.0959819 0.279711
+0.824863 0 0.266283
+
+0.843472 0.0886525 0.320194
+0.824863 0 0.266283
+0.913207 0.0959819 0.279711
+
+0.824863 0 0.266283
+0.843472 0.0886525 0.320194
+0.760358 0 0.285594
+
+0.766332 0.0805448 0.343415
+0.760358 0 0.285594
+0.843472 0.0886525 0.320194
+
+0.760358 0 0.285594
+0.766332 0.0805448 0.343415
+0.693138 0 0.289509
+
+0.685946 0.0720958 0.348123
+0.693138 0 0.289509
+0.766332 0.0805448 0.343415
+
+0.693138 0 0.289509
+0.685946 0.0720958 0.348123
+0.626827 0 0.277817
+
+0.606646 0.0637611 0.334064
+0.626827 0 0.277817
+0.685946 0.0720958 0.348123
+
+0.626827 0 0.277817
+0.606646 0.0637611 0.334064
+0.565 0 0.251147
+
+0.532709 0.05599 0.301995
+0.565 0 0.251147
+0.606646 0.0637611 0.334064
+
+0.565 0 0.251147
+0.532709 0.05599 0.301995
+0.51099 0 0.210938
+
+0.46812 0.0492014 0.253645
+0.51099 0 0.210938
+0.532709 0.05599 0.301995
+
+0.51099 0 0.210938
+0.46812 0.0492014 0.253645
+0.467709 0 0.159358
+
+0.416361 0.0437613 0.191621
+0.467709 0 0.159358
+0.46812 0.0492014 0.253645
+
+0.467709 0 0.159358
+0.416361 0.0437613 0.191621
+0.437489 0 0.0991858
+
+0.380222 0.039963 0.119267
+0.437489 0 0.0991858
+0.416361 0.0437613 0.191621
+
+0.437489 0 0.0991858
+0.380222 0.039963 0.119267
+0.421961 0 0.0336669
+
+0.361653 0.0380112 0.0404831
+0.421961 0 0.0336669
+0.380222 0.039963 0.119267
+
+0.421961 0 0.0336669
+0.361653 0.0380112 0.0404831
+0.421961 0 -0.0336669
+
+0.361653 0.0380112 -0.0404831
+0.421961 0 -0.0336669
+0.361653 0.0380112 0.0404831
+
+0.421961 0 -0.0336669
+0.361653 0.0380112 -0.0404831
+0.437489 0 -0.0991858
+
+0.380222 0.039963 -0.119267
+0.437489 0 -0.0991858
+0.361653 0.0380112 -0.0404831
+
+0.437489 0 -0.0991858
+0.380222 0.039963 -0.119267
+0.467709 0 -0.159358
+
+0.416361 0.0437613 -0.191621
+0.467709 0 -0.159358
+0.380222 0.039963 -0.119267
+
+0.467709 0 -0.159358
+0.416361 0.0437613 -0.191621
+0.51099 0 -0.210938
+
+0.46812 0.0492014 -0.253645
+0.51099 0 -0.210938
+0.416361 0.0437613 -0.191621
+
+0.51099 0 -0.210938
+0.46812 0.0492014 -0.253645
+0.565 0 -0.251147
+
+0.532709 0.05599 -0.301995
+0.565 0 -0.251147
+0.46812 0.0492014 -0.253645
+
+0.565 0 -0.251147
+0.532709 0.05599 -0.301995
+0.626827 0 -0.277817
+
+0.606646 0.0637611 -0.334064
+0.626827 0 -0.277817
+0.532709 0.05599 -0.301995
+
+0.626827 0 -0.277817
+0.606646 0.0637611 -0.334064
+0.693138 0 -0.289509
+
+0.685946 0.0720958 -0.348123
+0.693138 0 -0.289509
+0.606646 0.0637611 -0.334064
+
+0.693138 0 -0.289509
+0.685946 0.0720958 -0.348123
+0.760358 0 -0.285594
+
+0.766332 0.0805448 -0.343415
+0.760358 0 -0.285594
+0.685946 0.0720958 -0.348123
+
+0.760358 0 -0.285594
+0.766332 0.0805448 -0.343415
+0.824863 0 -0.266283
+
+0.843472 0.0886525 -0.320194
+0.824863 0 -0.266283
+0.766332 0.0805448 -0.343415
+
+0.824863 0 -0.266283
+0.843472 0.0886525 -0.320194
+0.883176 0 -0.232616
+
+0.913207 0.0959819 -0.279711
+0.883176 0 -0.232616
+0.843472 0.0886525 -0.320194
+
+0.883176 0 -0.232616
+0.913207 0.0959819 -0.279711
+0.932153 0 -0.186408
+
+0.971777 0.102138 -0.224149
+0.932153 0 -0.186408
+0.913207 0.0959819 -0.279711
+
+0.932153 0 -0.186408
+0.971777 0.102138 -0.224149
+0.969153 0 -0.130152
+
+1.01602 0.106789 -0.156502
+0.969153 0 -0.130152
+0.971777 0.102138 -0.224149
+
+0.969153 0 -0.130152
+1.01602 0.106789 -0.156502
+0.992183 0 -0.0668786
+
+1.04357 0.109683 -0.0804188
+0.992183 0 -0.0668786
+1.01602 0.106789 -0.156502
+
+0.992183 0 -0.0668786
+1.04357 0.109683 -0.0804188
+1 0 0
+
+1.05291 0.110666 0
+1 0 0
+1.04357 0.109683 -0.0804188
+
+1.05291 0.110666 0
+1.08739 0.231131 0
+1.04357 0.109683 0.0804188
+
+1.0768 0.22888 0.0926336
+1.04357 0.109683 0.0804188
+1.08739 0.231131 0
+
+1.04357 0.109683 0.0804188
+1.0768 0.22888 0.0926336
+1.01602 0.106789 0.156502
+
+1.04559 0.222248 0.180273
+1.01602 0.106789 0.156502
+1.0768 0.22888 0.0926336
+
+1.01602 0.106789 0.156502
+1.04559 0.222248 0.180273
+0.971777 0.102138 0.224149
+
+0.995465 0.211593 0.258194
+0.971777 0.102138 0.224149
+1.04559 0.222248 0.180273
+
+0.971777 0.102138 0.224149
+0.995465 0.211593 0.258194
+0.913207 0.0959819 0.279711
+
+0.929109 0.197488 0.322196
+0.913207 0.0959819 0.279711
+0.995465 0.211593 0.258194
+
+0.913207 0.0959819 0.279711
+0.929109 0.197488 0.322196
+0.843472 0.0886525 0.320194
+
+0.850105 0.180695 0.368828
+0.843472 0.0886525 0.320194
+0.929109 0.197488 0.322196
+
+0.843472 0.0886525 0.320194
+0.850105 0.180695 0.368828
+0.766332 0.0805448 0.343415
+
+0.762711 0.162119 0.395577
+0.766332 0.0805448 0.343415
+0.850105 0.180695 0.368828
+
+0.766332 0.0805448 0.343415
+0.762711 0.162119 0.395577
+0.685946 0.0720958 0.348123
+
+0.67164 0.142761 0.401
+0.685946 0.0720958 0.348123
+0.762711 0.162119 0.395577
+
+0.685946 0.0720958 0.348123
+0.67164 0.142761 0.401
+0.606646 0.0637611 0.334064
+
+0.581799 0.123665 0.384804
+0.606646 0.0637611 0.334064
+0.67164 0.142761 0.401
+
+0.606646 0.0637611 0.334064
+0.581799 0.123665 0.384804
+0.532709 0.05599 0.301995
+
+0.498034 0.10586 0.347864
+0.532709 0.05599 0.301995
+0.581799 0.123665 0.384804
+
+0.532709 0.05599 0.301995
+0.498034 0.10586 0.347864
+0.46812 0.0492014 0.253645
+
+0.424859 0.0903067 0.292171
+0.46812 0.0492014 0.253645
+0.498034 0.10586 0.347864
+
+0.46812 0.0492014 0.253645
+0.424859 0.0903067 0.292171
+0.416361 0.0437613 0.191621
+
+0.36622 0.0778425 0.220726
+0.416361 0.0437613 0.191621
+0.424859 0.0903067 0.292171
+
+0.416361 0.0437613 0.191621
+0.36622 0.0778425 0.220726
+0.380222 0.039963 0.119267
+
+0.325278 0.06914 0.137382
+0.380222 0.039963 0.119267
+0.36622 0.0778425 0.220726
+
+0.380222 0.039963 0.119267
+0.325278 0.06914 0.137382
+0.361653 0.0380112 0.0404831
+
+0.30424 0.0646682 0.0466321
+0.361653 0.0380112 0.0404831
+0.325278 0.06914 0.137382
+
+0.361653 0.0380112 0.0404831
+0.30424 0.0646682 0.0466321
+0.361653 0.0380112 -0.0404831
+
+0.30424 0.0646682 -0.0466321
+0.361653 0.0380112 -0.0404831
+0.30424 0.0646682 0.0466321
+
+0.361653 0.0380112 -0.0404831
+0.30424 0.0646682 -0.0466321
+0.380222 0.039963 -0.119267
+
+0.325278 0.06914 -0.137382
+0.380222 0.039963 -0.119267
+0.30424 0.0646682 -0.0466321
+
+0.380222 0.039963 -0.119267
+0.325278 0.06914 -0.137382
+0.416361 0.0437613 -0.191621
+
+0.36622 0.0778425 -0.220726
+0.416361 0.0437613 -0.191621
+0.325278 0.06914 -0.137382
+
+0.416361 0.0437613 -0.191621
+0.36622 0.0778425 -0.220726
+0.46812 0.0492014 -0.253645
+
+0.424859 0.0903067 -0.292171
+0.46812 0.0492014 -0.253645
+0.36622 0.0778425 -0.220726
+
+0.46812 0.0492014 -0.253645
+0.424859 0.0903067 -0.292171
+0.532709 0.05599 -0.301995
+
+0.498034 0.10586 -0.347864
+0.532709 0.05599 -0.301995
+0.424859 0.0903067 -0.292171
+
+0.532709 0.05599 -0.301995
+0.498034 0.10586 -0.347864
+0.606646 0.0637611 -0.334064
+
+0.581799 0.123665 -0.384804
+0.606646 0.0637611 -0.334064
+0.498034 0.10586 -0.347864
+
+0.606646 0.0637611 -0.334064
+0.581799 0.123665 -0.384804
+0.685946 0.0720958 -0.348123
+
+0.67164 0.142761 -0.401
+0.685946 0.0720958 -0.348123
+0.581799 0.123665 -0.384804
+
+0.685946 0.0720958 -0.348123
+0.67164 0.142761 -0.401
+0.766332 0.0805448 -0.343415
+
+0.762711 0.162119 -0.395577
+0.766332 0.0805448 -0.343415
+0.67164 0.142761 -0.401
+
+0.766332 0.0805448 -0.343415
+0.762711 0.162119 -0.395577
+0.843472 0.0886525 -0.320194
+
+0.850105 0.180695 -0.368828
+0.843472 0.0886525 -0.320194
+0.762711 0.162119 -0.395577
+
+0.843472 0.0886525 -0.320194
+0.850105 0.180695 -0.368828
+0.913207 0.0959819 -0.279711
+
+0.929109 0.197488 -0.322196
+0.913207 0.0959819 -0.279711
+0.850105 0.180695 -0.368828
+
+0.913207 0.0959819 -0.279711
+0.929109 0.197488 -0.322196
+0.971777 0.102138 -0.224149
+
+0.995465 0.211593 -0.258194
+0.971777 0.102138 -0.224149
+0.929109 0.197488 -0.322196
+
+0.971777 0.102138 -0.224149
+0.995465 0.211593 -0.258194
+1.01602 0.106789 -0.156502
+
+1.04559 0.222248 -0.180273
+1.01602 0.106789 -0.156502
+0.995465 0.211593 -0.258194
+
+1.01602 0.106789 -0.156502
+1.04559 0.222248 -0.180273
+1.04357 0.109683 -0.0804188
+
+1.0768 0.22888 -0.0926336
+1.04357 0.109683 -0.0804188
+1.04559 0.222248 -0.180273
+
+1.04357 0.109683 -0.0804188
+1.0768 0.22888 -0.0926336
+1.05291 0.110666 0
+
+1.08739 0.231131 0
+1.05291 0.110666 0
+1.0768 0.22888 -0.0926336
+
+1.08739 0.231131 0
+1.09725 0.356517 0
+1.0768 0.22888 0.0926336
+
+1.08587 0.352821 0.102327
+1.0768 0.22888 0.0926336
+1.09725 0.356517 0
+
+1.0768 0.22888 0.0926336
+1.08587 0.352821 0.102327
+1.04559 0.222248 0.180273
+
+1.05236 0.341932 0.199138
+1.04559 0.222248 0.180273
+1.08587 0.352821 0.102327
+
+1.04559 0.222248 0.180273
+1.05236 0.341932 0.199138
+0.995465 0.211593 0.258194
+
+0.998518 0.324438 0.285213
+0.995465 0.211593 0.258194
+1.05236 0.341932 0.199138
+
+0.995465 0.211593 0.258194
+0.998518 0.324438 0.285213
+0.929109 0.197488 0.322196
+
+0.927249 0.301281 0.355913
+0.929109 0.197488 0.322196
+0.998518 0.324438 0.285213
+
+0.929109 0.197488 0.322196
+0.927249 0.301281 0.355913
+0.850105 0.180695 0.368828
+
+0.842394 0.273711 0.407425
+0.850105 0.180695 0.368828
+0.927249 0.301281 0.355913
+
+0.850105 0.180695 0.368828
+0.842394 0.273711 0.407425
+0.762711 0.162119 0.395577
+
+0.748529 0.243212 0.436972
+0.762711 0.162119 0.395577
+0.842394 0.273711 0.407425
+
+0.762711 0.162119 0.395577
+0.748529 0.243212 0.436972
+0.67164 0.142761 0.401
+
+0.650713 0.21143 0.442963
+0.67164 0.142761 0.401
+0.748529 0.243212 0.436972
+
+0.67164 0.142761 0.401
+0.650713 0.21143 0.442963
+0.581799 0.123665 0.384804
+
+0.55422 0.180077 0.425073
+0.581799 0.123665 0.384804
+0.650713 0.21143 0.442963
+
+0.581799 0.123665 0.384804
+0.55422 0.180077 0.425073
+0.498034 0.10586 0.347864
+
+0.464252 0.150845 0.384267
+0.498034 0.10586 0.347864
+0.55422 0.180077 0.425073
+
+0.498034 0.10586 0.347864
+0.464252 0.150845 0.384267
+0.424859 0.0903067 0.292171
+
+0.385659 0.125308 0.322745
+0.424859 0.0903067 0.292171
+0.464252 0.150845 0.384267
+
+0.424859 0.0903067 0.292171
+0.385659 0.125308 0.322745
+0.36622 0.0778425 0.220726
+
+0.322677 0.104844 0.243824
+0.36622 0.0778425 0.220726
+0.385659 0.125308 0.322745
+
+0.36622 0.0778425 0.220726
+0.322677 0.104844 0.243824
+0.325278 0.06914 0.137382
+
+0.278703 0.0905562 0.151759
+0.325278 0.06914 0.137382
+0.322677 0.104844 0.243824
+
+0.325278 0.06914 0.137382
+0.278703 0.0905562 0.151759
+0.30424 0.0646682 0.0466321
+
+0.256107 0.0832143 0.051512
+0.30424 0.0646682 0.0466321
+0.278703 0.0905562 0.151759
+
+0.30424 0.0646682 0.0466321
+0.256107 0.0832143 0.051512
+0.30424 0.0646682 -0.0466321
+
+0.256107 0.0832143 -0.051512
+0.30424 0.0646682 -0.0466321
+0.256107 0.0832143 0.051512
+
+0.30424 0.0646682 -0.0466321
+0.256107 0.0832143 -0.051512
+0.325278 0.06914 -0.137382
+
+0.278703 0.0905562 -0.151759
+0.325278 0.06914 -0.137382
+0.256107 0.0832143 -0.051512
+
+0.325278 0.06914 -0.137382
+0.278703 0.0905562 -0.151759
+0.36622 0.0778425 -0.220726
+
+0.322677 0.104844 -0.243824
+0.36622 0.0778425 -0.220726
+0.278703 0.0905562 -0.151759
+
+0.36622 0.0778425 -0.220726
+0.322677 0.104844 -0.243824
+0.424859 0.0903067 -0.292171
+
+0.385659 0.125308 -0.322745
+0.424859 0.0903067 -0.292171
+0.322677 0.104844 -0.243824
+
+0.424859 0.0903067 -0.292171
+0.385659 0.125308 -0.322745
+0.498034 0.10586 -0.347864
+
+0.464252 0.150845 -0.384267
+0.498034 0.10586 -0.347864
+0.385659 0.125308 -0.322745
+
+0.498034 0.10586 -0.347864
+0.464252 0.150845 -0.384267
+0.581799 0.123665 -0.384804
+
+0.55422 0.180077 -0.425073
+0.581799 0.123665 -0.384804
+0.464252 0.150845 -0.384267
+
+0.581799 0.123665 -0.384804
+0.55422 0.180077 -0.425073
+0.67164 0.142761 -0.401
+
+0.650713 0.21143 -0.442963
+0.67164 0.142761 -0.401
+0.55422 0.180077 -0.425073
+
+0.67164 0.142761 -0.401
+0.650713 0.21143 -0.442963
+0.762711 0.162119 -0.395577
+
+0.748529 0.243212 -0.436972
+0.762711 0.162119 -0.395577
+0.650713 0.21143 -0.442963
+
+0.762711 0.162119 -0.395577
+0.748529 0.243212 -0.436972
+0.850105 0.180695 -0.368828
+
+0.842394 0.273711 -0.407425
+0.850105 0.180695 -0.368828
+0.748529 0.243212 -0.436972
+
+0.850105 0.180695 -0.368828
+0.842394 0.273711 -0.407425
+0.929109 0.197488 -0.322196
+
+0.927249 0.301281 -0.355913
+0.929109 0.197488 -0.322196
+0.842394 0.273711 -0.407425
+
+0.929109 0.197488 -0.322196
+0.927249 0.301281 -0.355913
+0.995465 0.211593 -0.258194
+
+0.998518 0.324438 -0.285213
+0.995465 0.211593 -0.258194
+0.927249 0.301281 -0.355913
+
+0.995465 0.211593 -0.258194
+0.998518 0.324438 -0.285213
+1.04559 0.222248 -0.180273
+
+1.05236 0.341932 -0.199138
+1.04559 0.222248 -0.180273
+0.998518 0.324438 -0.285213
+
+1.04559 0.222248 -0.180273
+1.05236 0.341932 -0.199138
+1.0768 0.22888 -0.0926336
+
+1.08587 0.352821 -0.102327
+1.0768 0.22888 -0.0926336
+1.05236 0.341932 -0.199138
+
+1.0768 0.22888 -0.0926336
+1.08587 0.352821 -0.102327
+1.08739 0.231131 0
+
+1.09725 0.356517 0
+1.08739 0.231131 0
+1.08587 0.352821 -0.102327
+
+1.09725 0.356517 0
+1.07862 0.480234 0
+1.08587 0.352821 0.102327
+
+1.06703 0.475074 0.108551
+1.08587 0.352821 0.102327
+1.07862 0.480234 0
+
+1.08587 0.352821 0.102327
+1.06703 0.475074 0.108551
+1.05236 0.341932 0.199138
+
+1.03289 0.45987 0.21125
+1.05236 0.341932 0.199138
+1.06703 0.475074 0.108551
+
+1.05236 0.341932 0.199138
+1.03289 0.45987 0.21125
+0.998518 0.324438 0.285213
+
+0.978021 0.435443 0.302561
+0.998518 0.324438 0.285213
+1.03289 0.45987 0.21125
+
+0.998518 0.324438 0.285213
+0.978021 0.435443 0.302561
+0.927249 0.301281 0.355913
+
+0.905399 0.40311 0.37756
+0.927249 0.301281 0.355913
+0.978021 0.435443 0.302561
+
+0.927249 0.301281 0.355913
+0.905399 0.40311 0.37756
+0.842394 0.273711 0.407425
+
+0.818934 0.364613 0.432205
+0.842394 0.273711 0.407425
+0.905399 0.40311 0.37756
+
+0.842394 0.273711 0.407425
+0.818934 0.364613 0.432205
+0.748529 0.243212 0.436972
+
+0.723287 0.322028 0.46355
+0.748529 0.243212 0.436972
+0.818934 0.364613 0.432205
+
+0.748529 0.243212 0.436972
+0.723287 0.322028 0.46355
+0.650713 0.21143 0.442963
+
+0.623615 0.277651 0.469904
+0.650713 0.21143 0.442963
+0.723287 0.322028 0.46355
+
+0.650713 0.21143 0.442963
+0.623615 0.277651 0.469904
+0.55422 0.180077 0.425073
+
+0.52529 0.233874 0.450926
+0.55422 0.180077 0.425073
+0.623615 0.277651 0.469904
+
+0.55422 0.180077 0.425073
+0.52529 0.233874 0.450926
+0.464252 0.150845 0.384267
+
+0.433614 0.193057 0.407639
+0.464252 0.150845 0.384267
+0.52529 0.233874 0.450926
+
+0.464252 0.150845 0.384267
+0.433614 0.193057 0.407639
+0.385659 0.125308 0.322745
+
+0.353529 0.157401 0.342375
+0.385659 0.125308 0.322745
+0.433614 0.193057 0.407639
+
+0.385659 0.125308 0.322745
+0.353529 0.157401 0.342375
+0.322677 0.104844 0.243824
+
+0.289352 0.128828 0.258654
+0.322677 0.104844 0.243824
+0.353529 0.157401 0.342375
+
+0.322677 0.104844 0.243824
+0.289352 0.128828 0.258654
+0.278703 0.0905562 0.151759
+
+0.244543 0.108878 0.160989
+0.278703 0.0905562 0.151759
+0.289352 0.128828 0.258654
+
+0.278703 0.0905562 0.151759
+0.244543 0.108878 0.160989
+0.256107 0.0832143 0.051512
+
+0.221518 0.0986263 0.054645
+0.256107 0.0832143 0.051512
+0.244543 0.108878 0.160989
+
+0.256107 0.0832143 0.051512
+0.221518 0.0986263 0.054645
+0.256107 0.0832143 -0.051512
+
+0.221518 0.0986263 -0.054645
+0.256107 0.0832143 -0.051512
+0.221518 0.0986263 0.054645
+
+0.256107 0.0832143 -0.051512
+0.221518 0.0986263 -0.054645
+0.278703 0.0905562 -0.151759
+
+0.244543 0.108878 -0.160989
+0.278703 0.0905562 -0.151759
+0.221518 0.0986263 -0.054645
+
+0.278703 0.0905562 -0.151759
+0.244543 0.108878 -0.160989
+0.322677 0.104844 -0.243824
+
+0.289352 0.128828 -0.258654
+0.322677 0.104844 -0.243824
+0.244543 0.108878 -0.160989
+
+0.322677 0.104844 -0.243824
+0.289352 0.128828 -0.258654
+0.385659 0.125308 -0.322745
+
+0.353529 0.157401 -0.342375
+0.385659 0.125308 -0.322745
+0.289352 0.128828 -0.258654
+
+0.385659 0.125308 -0.322745
+0.353529 0.157401 -0.342375
+0.464252 0.150845 -0.384267
+
+0.433614 0.193057 -0.407639
+0.464252 0.150845 -0.384267
+0.353529 0.157401 -0.342375
+
+0.464252 0.150845 -0.384267
+0.433614 0.193057 -0.407639
+0.55422 0.180077 -0.425073
+
+0.52529 0.233874 -0.450926
+0.55422 0.180077 -0.425073
+0.433614 0.193057 -0.407639
+
+0.55422 0.180077 -0.425073
+0.52529 0.233874 -0.450926
+0.650713 0.21143 -0.442963
+
+0.623615 0.277651 -0.469904
+0.650713 0.21143 -0.442963
+0.52529 0.233874 -0.450926
+
+0.650713 0.21143 -0.442963
+0.623615 0.277651 -0.469904
+0.748529 0.243212 -0.436972
+
+0.723287 0.322028 -0.46355
+0.748529 0.243212 -0.436972
+0.623615 0.277651 -0.469904
+
+0.748529 0.243212 -0.436972
+0.723287 0.322028 -0.46355
+0.842394 0.273711 -0.407425
+
+0.818934 0.364613 -0.432205
+0.842394 0.273711 -0.407425
+0.723287 0.322028 -0.46355
+
+0.842394 0.273711 -0.407425
+0.818934 0.364613 -0.432205
+0.927249 0.301281 -0.355913
+
+0.905399 0.40311 -0.37756
+0.927249 0.301281 -0.355913
+0.818934 0.364613 -0.432205
+
+0.927249 0.301281 -0.355913
+0.905399 0.40311 -0.37756
+0.998518 0.324438 -0.285213
+
+0.978021 0.435443 -0.302561
+0.998518 0.324438 -0.285213
+0.905399 0.40311 -0.37756
+
+0.998518 0.324438 -0.285213
+0.978021 0.435443 -0.302561
+1.05236 0.341932 -0.199138
+
+1.03289 0.45987 -0.21125
+1.05236 0.341932 -0.199138
+0.978021 0.435443 -0.302561
+
+1.05236 0.341932 -0.199138
+1.03289 0.45987 -0.21125
+1.08587 0.352821 -0.102327
+
+1.06703 0.475074 -0.108551
+1.08587 0.352821 -0.102327
+1.03289 0.45987 -0.21125
+
+1.08587 0.352821 -0.102327
+1.06703 0.475074 -0.108551
+1.09725 0.356517 0
+
+1.07862 0.480234 0
+1.09725 0.356517 0
+1.06703 0.475074 -0.108551
+
+1.07862 0.480234 0
+1.03057 0.595 0
+1.06703 0.475074 0.108551
+
+1.01937 0.588531 0.110696
+1.06703 0.475074 0.108551
+1.03057 0.595 0
+
+1.06703 0.475074 0.108551
+1.01937 0.588531 0.110696
+1.03289 0.45987 0.21125
+
+0.986354 0.569472 0.215424
+1.03289 0.45987 0.21125
+1.01937 0.588531 0.110696
+
+1.03289 0.45987 0.21125
+0.986354 0.569472 0.215424
+0.978021 0.435443 0.302561
+
+0.933317 0.538851 0.308538
+0.978021 0.435443 0.302561
+0.986354 0.569472 0.215424
+
+0.978021 0.435443 0.302561
+0.933317 0.538851 0.308538
+0.905399 0.40311 0.37756
+
+0.863112 0.498318 0.385019
+0.905399 0.40311 0.37756
+0.933317 0.538851 0.308538
+
+0.905399 0.40311 0.37756
+0.863112 0.498318 0.385019
+0.818934 0.364613 0.432205
+
+0.779525 0.450059 0.440744
+0.818934 0.364613 0.432205
+0.863112 0.498318 0.385019
+
+0.818934 0.364613 0.432205
+0.779525 0.450059 0.440744
+0.723287 0.322028 0.46355
+
+0.687062 0.396676 0.472708
+0.723287 0.322028 0.46355
+0.779525 0.450059 0.440744
+
+0.723287 0.322028 0.46355
+0.687062 0.396676 0.472708
+0.623615 0.277651 0.469904
+
+0.590708 0.341045 0.479188
+0.623615 0.277651 0.469904
+0.687062 0.396676 0.472708
+
+0.623615 0.277651 0.469904
+0.590708 0.341045 0.479188
+0.52529 0.233874 0.450926
+
+0.495656 0.286167 0.459835
+0.52529 0.233874 0.450926
+0.590708 0.341045 0.479188
+
+0.52529 0.233874 0.450926
+0.495656 0.286167 0.459835
+0.433614 0.193057 0.407639
+
+0.407032 0.235 0.415692
+0.433614 0.193057 0.407639
+0.495656 0.286167 0.459835
+
+0.433614 0.193057 0.407639
+0.407032 0.235 0.415692
+0.353529 0.157401 0.342375
+
+0.329613 0.190302 0.349139
+0.353529 0.157401 0.342375
+0.407032 0.235 0.415692
+
+0.353529 0.157401 0.342375
+0.329613 0.190302 0.349139
+0.289352 0.128828 0.258654
+
+0.267572 0.154483 0.263764
+0.289352 0.128828 0.258654
+0.329613 0.190302 0.349139
+
+0.289352 0.128828 0.258654
+0.267572 0.154483 0.263764
+0.244543 0.108878 0.160989
+
+0.224255 0.129474 0.16417
+0.244543 0.108878 0.160989
+0.267572 0.154483 0.263764
+
+0.244543 0.108878 0.160989
+0.224255 0.129474 0.16417
+0.221518 0.0986263 0.054645
+
+0.201997 0.116623 0.0557246
+0.221518 0.0986263 0.054645
+0.224255 0.129474 0.16417
+
+0.221518 0.0986263 0.054645
+0.201997 0.116623 0.0557246
+0.221518 0.0986263 -0.054645
+
+0.201997 0.116623 -0.0557246
+0.221518 0.0986263 -0.054645
+0.201997 0.116623 0.0557246
+
+0.221518 0.0986263 -0.054645
+0.201997 0.116623 -0.0557246
+0.244543 0.108878 -0.160989
+
+0.224255 0.129474 -0.16417
+0.244543 0.108878 -0.160989
+0.201997 0.116623 -0.0557246
+
+0.244543 0.108878 -0.160989
+0.224255 0.129474 -0.16417
+0.289352 0.128828 -0.258654
+
+0.267572 0.154483 -0.263764
+0.289352 0.128828 -0.258654
+0.224255 0.129474 -0.16417
+
+0.289352 0.128828 -0.258654
+0.267572 0.154483 -0.263764
+0.353529 0.157401 -0.342375
+
+0.329613 0.190302 -0.349139
+0.353529 0.157401 -0.342375
+0.267572 0.154483 -0.263764
+
+0.353529 0.157401 -0.342375
+0.329613 0.190302 -0.349139
+0.433614 0.193057 -0.407639
+
+0.407032 0.235 -0.415692
+0.433614 0.193057 -0.407639
+0.329613 0.190302 -0.349139
+
+0.433614 0.193057 -0.407639
+0.407032 0.235 -0.415692
+0.52529 0.233874 -0.450926
+
+0.495656 0.286167 -0.459835
+0.52529 0.233874 -0.450926
+0.407032 0.235 -0.415692
+
+0.52529 0.233874 -0.450926
+0.495656 0.286167 -0.459835
+0.623615 0.277651 -0.469904
+
+0.590708 0.341045 -0.479188
+0.623615 0.277651 -0.469904
+0.495656 0.286167 -0.459835
+
+0.623615 0.277651 -0.469904
+0.590708 0.341045 -0.479188
+0.723287 0.322028 -0.46355
+
+0.687062 0.396676 -0.472708
+0.723287 0.322028 -0.46355
+0.590708 0.341045 -0.479188
+
+0.723287 0.322028 -0.46355
+0.687062 0.396676 -0.472708
+0.818934 0.364613 -0.432205
+
+0.779525 0.450059 -0.440744
+0.818934 0.364613 -0.432205
+0.687062 0.396676 -0.472708
+
+0.818934 0.364613 -0.432205
+0.779525 0.450059 -0.440744
+0.905399 0.40311 -0.37756
+
+0.863112 0.498318 -0.385019
+0.905399 0.40311 -0.37756
+0.779525 0.450059 -0.440744
+
+0.905399 0.40311 -0.37756
+0.863112 0.498318 -0.385019
+0.978021 0.435443 -0.302561
+
+0.933317 0.538851 -0.308538
+0.978021 0.435443 -0.302561
+0.863112 0.498318 -0.385019
+
+0.978021 0.435443 -0.302561
+0.933317 0.538851 -0.308538
+1.03289 0.45987 -0.21125
+
+0.986354 0.569472 -0.215424
+1.03289 0.45987 -0.21125
+0.933317 0.538851 -0.308538
+
+1.03289 0.45987 -0.21125
+0.986354 0.569472 -0.215424
+1.06703 0.475074 -0.108551
+
+1.01937 0.588531 -0.110696
+1.06703 0.475074 -0.108551
+0.986354 0.569472 -0.215424
+
+1.06703 0.475074 -0.108551
+1.01937 0.588531 -0.110696
+1.07862 0.480234 0
+
+1.03057 0.595 0
+1.07862 0.480234 0
+1.01937 0.588531 -0.110696
+
+1.03057 0.595 0
+0.955207 0.693998 0
+1.01937 0.588531 0.110696
+
+0.944942 0.686541 0.108551
+1.01937 0.588531 0.110696
+0.955207 0.693998 0
+
+1.01937 0.588531 0.110696
+0.944942 0.686541 0.108551
+0.986354 0.569472 0.215424
+
+0.914702 0.66457 0.21125
+0.986354 0.569472 0.215424
+0.944942 0.686541 0.108551
+
+0.986354 0.569472 0.215424
+0.914702 0.66457 0.21125
+0.933317 0.538851 0.308538
+
+0.866116 0.62927 0.302561
+0.933317 0.538851 0.308538
+0.914702 0.66457 0.21125
+
+0.933317 0.538851 0.308538
+0.866116 0.62927 0.302561
+0.863112 0.498318 0.385019
+
+0.801803 0.582544 0.37756
+0.863112 0.498318 0.385019
+0.866116 0.62927 0.302561
+
+0.863112 0.498318 0.385019
+0.801803 0.582544 0.37756
+0.779525 0.450059 0.440744
+
+0.725231 0.526911 0.432205
+0.779525 0.450059 0.440744
+0.801803 0.582544 0.37756
+
+0.779525 0.450059 0.440744
+0.725231 0.526911 0.432205
+0.687062 0.396676 0.472708
+
+0.640528 0.465371 0.46355
+0.687062 0.396676 0.472708
+0.725231 0.526911 0.432205
+
+0.687062 0.396676 0.472708
+0.640528 0.465371 0.46355
+0.590708 0.341045 0.479188
+
+0.55226 0.401241 0.469904
+0.590708 0.341045 0.479188
+0.640528 0.465371 0.46355
+
+0.590708 0.341045 0.479188
+0.55226 0.401241 0.469904
+0.495656 0.286167 0.459835
+
+0.465186 0.337977 0.450926
+0.495656 0.286167 0.459835
+0.55226 0.401241 0.469904
+
+0.495656 0.286167 0.459835
+0.465186 0.337977 0.450926
+0.407032 0.235 0.415692
+
+0.384 0.278992 0.407639
+0.407032 0.235 0.415692
+0.465186 0.337977 0.450926
+
+0.407032 0.235 0.415692
+0.384 0.278992 0.407639
+0.329613 0.190302 0.349139
+
+0.313078 0.227464 0.342375
+0.329613 0.190302 0.349139
+0.384 0.278992 0.407639
+
+0.329613 0.190302 0.349139
+0.313078 0.227464 0.342375
+0.267572 0.154483 0.263764
+
+0.256244 0.186172 0.258654
+0.267572 0.154483 0.263764
+0.313078 0.227464 0.342375
+
+0.267572 0.154483 0.263764
+0.256244 0.186172 0.258654
+0.224255 0.129474 0.16417
+
+0.216563 0.157342 0.160989
+0.224255 0.129474 0.16417
+0.256244 0.186172 0.258654
+
+0.224255 0.129474 0.16417
+0.216563 0.157342 0.160989
+0.201997 0.116623 0.0557246
+
+0.196172 0.142527 0.054645
+0.201997 0.116623 0.0557246
+0.216563 0.157342 0.160989
+
+0.201997 0.116623 0.0557246
+0.196172 0.142527 0.054645
+0.201997 0.116623 -0.0557246
+
+0.196172 0.142527 -0.054645
+0.201997 0.116623 -0.0557246
+0.196172 0.142527 0.054645
+
+0.201997 0.116623 -0.0557246
+0.196172 0.142527 -0.054645
+0.224255 0.129474 -0.16417
+
+0.216563 0.157342 -0.160989
+0.224255 0.129474 -0.16417
+0.196172 0.142527 -0.054645
+
+0.224255 0.129474 -0.16417
+0.216563 0.157342 -0.160989
+0.267572 0.154483 -0.263764
+
+0.256244 0.186172 -0.258654
+0.267572 0.154483 -0.263764
+0.216563 0.157342 -0.160989
+
+0.267572 0.154483 -0.263764
+0.256244 0.186172 -0.258654
+0.329613 0.190302 -0.349139
+
+0.313078 0.227464 -0.342375
+0.329613 0.190302 -0.349139
+0.256244 0.186172 -0.258654
+
+0.329613 0.190302 -0.349139
+0.313078 0.227464 -0.342375
+0.407032 0.235 -0.415692
+
+0.384 0.278992 -0.407639
+0.407032 0.235 -0.415692
+0.313078 0.227464 -0.342375
+
+0.407032 0.235 -0.415692
+0.384 0.278992 -0.407639
+0.495656 0.286167 -0.459835
+
+0.465186 0.337977 -0.450926
+0.495656 0.286167 -0.459835
+0.384 0.278992 -0.407639
+
+0.495656 0.286167 -0.459835
+0.465186 0.337977 -0.450926
+0.590708 0.341045 -0.479188
+
+0.55226 0.401241 -0.469904
+0.590708 0.341045 -0.479188
+0.465186 0.337977 -0.450926
+
+0.590708 0.341045 -0.479188
+0.55226 0.401241 -0.469904
+0.687062 0.396676 -0.472708
+
+0.640528 0.465371 -0.46355
+0.687062 0.396676 -0.472708
+0.55226 0.401241 -0.469904
+
+0.687062 0.396676 -0.472708
+0.640528 0.465371 -0.46355
+0.779525 0.450059 -0.440744
+
+0.725231 0.526911 -0.432205
+0.779525 0.450059 -0.440744
+0.640528 0.465371 -0.46355
+
+0.779525 0.450059 -0.440744
+0.725231 0.526911 -0.432205
+0.863112 0.498318 -0.385019
+
+0.801803 0.582544 -0.37756
+0.863112 0.498318 -0.385019
+0.725231 0.526911 -0.432205
+
+0.863112 0.498318 -0.385019
+0.801803 0.582544 -0.37756
+0.933317 0.538851 -0.308538
+
+0.866116 0.62927 -0.302561
+0.933317 0.538851 -0.308538
+0.801803 0.582544 -0.37756
+
+0.933317 0.538851 -0.308538
+0.866116 0.62927 -0.302561
+0.986354 0.569472 -0.215424
+
+0.914702 0.66457 -0.21125
+0.986354 0.569472 -0.215424
+0.866116 0.62927 -0.302561
+
+0.986354 0.569472 -0.215424
+0.914702 0.66457 -0.21125
+1.01937 0.588531 -0.110696
+
+0.944942 0.686541 -0.108551
+1.01937 0.588531 -0.110696
+0.914702 0.66457 -0.21125
+
+1.01937 0.588531 -0.110696
+0.944942 0.686541 -0.108551
+1.03057 0.595 0
+
+0.955207 0.693998 0
+1.03057 0.595 0
+0.944942 0.686541 -0.108551
+
+0.955207 0.693998 0
+0.857376 0.771985 0
+0.944942 0.686541 0.108551
+
+0.848488 0.763982 0.102327
+0.944942 0.686541 0.108551
+0.857376 0.771985 0
+
+0.944942 0.686541 0.108551
+0.848488 0.763982 0.102327
+0.914702 0.66457 0.21125
+
+0.822302 0.740404 0.199138
+0.914702 0.66457 0.21125
+0.848488 0.763982 0.102327
+
+0.914702 0.66457 0.21125
+0.822302 0.740404 0.199138
+0.866116 0.62927 0.302561
+
+0.780231 0.702523 0.285213
+0.866116 0.62927 0.302561
+0.822302 0.740404 0.199138
+
+0.866116 0.62927 0.302561
+0.780231 0.702523 0.285213
+0.801803 0.582544 0.37756
+
+0.724542 0.65238 0.355913
+0.801803 0.582544 0.37756
+0.780231 0.702523 0.285213
+
+0.801803 0.582544 0.37756
+0.724542 0.65238 0.355913
+0.725231 0.526911 0.432205
+
+0.658237 0.59268 0.407425
+0.725231 0.526911 0.432205
+0.724542 0.65238 0.355913
+
+0.725231 0.526911 0.432205
+0.658237 0.59268 0.407425
+0.640528 0.465371 0.46355
+
+0.584892 0.526639 0.436972
+0.640528 0.465371 0.46355
+0.658237 0.59268 0.407425
+
+0.640528 0.465371 0.46355
+0.584892 0.526639 0.436972
+0.55226 0.401241 0.469904
+
+0.50846 0.457819 0.442963
+0.55226 0.401241 0.469904
+0.584892 0.526639 0.436972
+
+0.55226 0.401241 0.469904
+0.50846 0.457819 0.442963
+0.465186 0.337977 0.450926
+
+0.433061 0.38993 0.425073
+0.465186 0.337977 0.450926
+0.50846 0.457819 0.442963
+
+0.465186 0.337977 0.450926
+0.433061 0.38993 0.425073
+0.384 0.278992 0.407639
+
+0.362761 0.326632 0.384267
+0.384 0.278992 0.407639
+0.433061 0.38993 0.425073
+
+0.384 0.278992 0.407639
+0.362761 0.326632 0.384267
+0.313078 0.227464 0.342375
+
+0.301349 0.271336 0.322745
+0.313078 0.227464 0.342375
+0.362761 0.326632 0.384267
+
+0.313078 0.227464 0.342375
+0.301349 0.271336 0.322745
+0.256244 0.186172 0.258654
+
+0.252136 0.227025 0.243824
+0.256244 0.186172 0.258654
+0.301349 0.271336 0.322745
+
+0.256244 0.186172 0.258654
+0.252136 0.227025 0.243824
+0.216563 0.157342 0.160989
+
+0.217776 0.196086 0.151759
+0.216563 0.157342 0.160989
+0.252136 0.227025 0.243824
+
+0.216563 0.157342 0.160989
+0.217776 0.196086 0.151759
+0.196172 0.142527 0.054645
+
+0.200119 0.180188 0.051512
+0.196172 0.142527 0.054645
+0.217776 0.196086 0.151759
+
+0.196172 0.142527 0.054645
+0.200119 0.180188 0.051512
+0.196172 0.142527 -0.054645
+
+0.200119 0.180188 -0.051512
+0.196172 0.142527 -0.054645
+0.200119 0.180188 0.051512
+
+0.196172 0.142527 -0.054645
+0.200119 0.180188 -0.051512
+0.216563 0.157342 -0.160989
+
+0.217776 0.196086 -0.151759
+0.216563 0.157342 -0.160989
+0.200119 0.180188 -0.051512
+
+0.216563 0.157342 -0.160989
+0.217776 0.196086 -0.151759
+0.256244 0.186172 -0.258654
+
+0.252136 0.227025 -0.243824
+0.256244 0.186172 -0.258654
+0.217776 0.196086 -0.151759
+
+0.256244 0.186172 -0.258654
+0.252136 0.227025 -0.243824
+0.313078 0.227464 -0.342375
+
+0.301349 0.271336 -0.322745
+0.313078 0.227464 -0.342375
+0.252136 0.227025 -0.243824
+
+0.313078 0.227464 -0.342375
+0.301349 0.271336 -0.322745
+0.384 0.278992 -0.407639
+
+0.362761 0.326632 -0.384267
+0.384 0.278992 -0.407639
+0.301349 0.271336 -0.322745
+
+0.384 0.278992 -0.407639
+0.362761 0.326632 -0.384267
+0.465186 0.337977 -0.450926
+
+0.433061 0.38993 -0.425073
+0.465186 0.337977 -0.450926
+0.362761 0.326632 -0.384267
+
+0.465186 0.337977 -0.450926
+0.433061 0.38993 -0.425073
+0.55226 0.401241 -0.469904
+
+0.50846 0.457819 -0.442963
+0.55226 0.401241 -0.469904
+0.433061 0.38993 -0.425073
+
+0.55226 0.401241 -0.469904
+0.50846 0.457819 -0.442963
+0.640528 0.465371 -0.46355
+
+0.584892 0.526639 -0.436972
+0.640528 0.465371 -0.46355
+0.50846 0.457819 -0.442963
+
+0.640528 0.465371 -0.46355
+0.584892 0.526639 -0.436972
+0.725231 0.526911 -0.432205
+
+0.658237 0.59268 -0.407425
+0.725231 0.526911 -0.432205
+0.584892 0.526639 -0.436972
+
+0.725231 0.526911 -0.432205
+0.658237 0.59268 -0.407425
+0.801803 0.582544 -0.37756
+
+0.724542 0.65238 -0.355913
+0.801803 0.582544 -0.37756
+0.658237 0.59268 -0.407425
+
+0.801803 0.582544 -0.37756
+0.724542 0.65238 -0.355913
+0.866116 0.62927 -0.302561
+
+0.780231 0.702523 -0.285213
+0.866116 0.62927 -0.302561
+0.724542 0.65238 -0.355913
+
+0.866116 0.62927 -0.302561
+0.780231 0.702523 -0.285213
+0.914702 0.66457 -0.21125
+
+0.822302 0.740404 -0.199138
+0.914702 0.66457 -0.21125
+0.780231 0.702523 -0.285213
+
+0.914702 0.66457 -0.21125
+0.822302 0.740404 -0.199138
+0.944942 0.686541 -0.108551
+
+0.848488 0.763982 -0.102327
+0.944942 0.686541 -0.108551
+0.822302 0.740404 -0.199138
+
+0.944942 0.686541 -0.108551
+0.848488 0.763982 -0.102327
+0.955207 0.693998 0
+
+0.857376 0.771985 0
+0.955207 0.693998 0
+0.848488 0.763982 -0.102327
+
+0.857376 0.771985 0
+0.743859 0.826139 0
+0.848488 0.763982 0.102327
+
+0.736614 0.818092 0.0926336
+0.848488 0.763982 0.102327
+0.743859 0.826139 0
+
+0.848488 0.763982 0.102327
+0.736614 0.818092 0.0926336
+0.822302 0.740404 0.199138
+
+0.71527 0.794387 0.180273
+0.822302 0.740404 0.199138
+0.736614 0.818092 0.0926336
+
+0.822302 0.740404 0.199138
+0.71527 0.794387 0.180273
+0.780231 0.702523 0.285213
+
+0.680977 0.756302 0.258194
+0.780231 0.702523 0.285213
+0.71527 0.794387 0.180273
+
+0.780231 0.702523 0.285213
+0.680977 0.756302 0.258194
+0.724542 0.65238 0.355913
+
+0.635585 0.705888 0.322196
+0.724542 0.65238 0.355913
+0.680977 0.756302 0.258194
+
+0.724542 0.65238 0.355913
+0.635585 0.705888 0.322196
+0.658237 0.59268 0.407425
+
+0.581539 0.645865 0.368828
+0.658237 0.59268 0.407425
+0.635585 0.705888 0.322196
+
+0.658237 0.59268 0.407425
+0.581539 0.645865 0.368828
+0.584892 0.526639 0.436972
+
+0.521755 0.579468 0.395577
+0.584892 0.526639 0.436972
+0.581539 0.645865 0.368828
+
+0.584892 0.526639 0.436972
+0.521755 0.579468 0.395577
+0.50846 0.457819 0.442963
+
+0.459455 0.510276 0.401
+0.50846 0.457819 0.442963
+0.521755 0.579468 0.395577
+
+0.50846 0.457819 0.442963
+0.459455 0.510276 0.401
+0.433061 0.38993 0.425073
+
+0.397997 0.44202 0.384804
+0.433061 0.38993 0.425073
+0.459455 0.510276 0.401
+
+0.433061 0.38993 0.425073
+0.397997 0.44202 0.384804
+0.362761 0.326632 0.384267
+
+0.340695 0.37838 0.347864
+0.362761 0.326632 0.384267
+0.397997 0.44202 0.384804
+
+0.362761 0.326632 0.384267
+0.340695 0.37838 0.347864
+0.301349 0.271336 0.322745
+
+0.290638 0.322786 0.292171
+0.301349 0.271336 0.322745
+0.340695 0.37838 0.347864
+
+0.301349 0.271336 0.322745
+0.290638 0.322786 0.292171
+0.252136 0.227025 0.243824
+
+0.250524 0.278235 0.220726
+0.252136 0.227025 0.243824
+0.290638 0.322786 0.292171
+
+0.252136 0.227025 0.243824
+0.250524 0.278235 0.220726
+0.217776 0.196086 0.151759
+
+0.222516 0.247129 0.137382
+0.217776 0.196086 0.151759
+0.250524 0.278235 0.220726
+
+0.217776 0.196086 0.151759
+0.222516 0.247129 0.137382
+0.200119 0.180188 0.051512
+
+0.208124 0.231145 0.0466321
+0.200119 0.180188 0.051512
+0.222516 0.247129 0.137382
+
+0.200119 0.180188 0.051512
+0.208124 0.231145 0.0466321
+0.200119 0.180188 -0.051512
+
+0.208124 0.231145 -0.0466321
+0.200119 0.180188 -0.051512
+0.208124 0.231145 0.0466321
+
+0.200119 0.180188 -0.051512
+0.208124 0.231145 -0.0466321
+0.217776 0.196086 -0.151759
+
+0.222516 0.247129 -0.137382
+0.217776 0.196086 -0.151759
+0.208124 0.231145 -0.0466321
+
+0.217776 0.196086 -0.151759
+0.222516 0.247129 -0.137382
+0.252136 0.227025 -0.243824
+
+0.250524 0.278235 -0.220726
+0.252136 0.227025 -0.243824
+0.222516 0.247129 -0.137382
+
+0.252136 0.227025 -0.243824
+0.250524 0.278235 -0.220726
+0.301349 0.271336 -0.322745
+
+0.290638 0.322786 -0.292171
+0.301349 0.271336 -0.322745
+0.250524 0.278235 -0.220726
+
+0.301349 0.271336 -0.322745
+0.290638 0.322786 -0.292171
+0.362761 0.326632 -0.384267
+
+0.340695 0.37838 -0.347864
+0.362761 0.326632 -0.384267
+0.290638 0.322786 -0.292171
+
+0.362761 0.326632 -0.384267
+0.340695 0.37838 -0.347864
+0.433061 0.38993 -0.425073
+
+0.397997 0.44202 -0.384804
+0.433061 0.38993 -0.425073
+0.340695 0.37838 -0.347864
+
+0.433061 0.38993 -0.425073
+0.397997 0.44202 -0.384804
+0.50846 0.457819 -0.442963
+
+0.459455 0.510276 -0.401
+0.50846 0.457819 -0.442963
+0.397997 0.44202 -0.384804
+
+0.50846 0.457819 -0.442963
+0.459455 0.510276 -0.401
+0.584892 0.526639 -0.436972
+
+0.521755 0.579468 -0.395577
+0.584892 0.526639 -0.436972
+0.459455 0.510276 -0.401
+
+0.584892 0.526639 -0.436972
+0.521755 0.579468 -0.395577
+0.658237 0.59268 -0.407425
+
+0.581539 0.645865 -0.368828
+0.658237 0.59268 -0.407425
+0.521755 0.579468 -0.395577
+
+0.658237 0.59268 -0.407425
+0.581539 0.645865 -0.368828
+0.724542 0.65238 -0.355913
+
+0.635585 0.705888 -0.322196
+0.724542 0.65238 -0.355913
+0.581539 0.645865 -0.368828
+
+0.724542 0.65238 -0.355913
+0.635585 0.705888 -0.322196
+0.780231 0.702523 -0.285213
+
+0.680977 0.756302 -0.258194
+0.780231 0.702523 -0.285213
+0.635585 0.705888 -0.322196
+
+0.780231 0.702523 -0.285213
+0.680977 0.756302 -0.258194
+0.822302 0.740404 -0.199138
+
+0.71527 0.794387 -0.180273
+0.822302 0.740404 -0.199138
+0.680977 0.756302 -0.258194
+
+0.822302 0.740404 -0.199138
+0.71527 0.794387 -0.180273
+0.848488 0.763982 -0.102327
+
+0.736614 0.818092 -0.0926336
+0.848488 0.763982 -0.102327
+0.71527 0.794387 -0.180273
+
+0.848488 0.763982 -0.102327
+0.736614 0.818092 -0.0926336
+0.857376 0.771985 0
+
+0.743859 0.826139 0
+0.857376 0.771985 0
+0.736614 0.818092 -0.0926336
+
+0.743859 0.826139 0
+0.622296 0.856517 0
+0.736614 0.818092 0.0926336
+
+0.616771 0.848913 0.0804188
+0.736614 0.818092 0.0926336
+0.622296 0.856517 0
+
+0.736614 0.818092 0.0926336
+0.616771 0.848913 0.0804188
+0.71527 0.794387 0.180273
+
+0.600494 0.826509 0.156502
+0.71527 0.794387 0.180273
+0.616771 0.848913 0.0804188
+
+0.71527 0.794387 0.180273
+0.600494 0.826509 0.156502
+0.680977 0.756302 0.258194
+
+0.574343 0.790515 0.224149
+0.680977 0.756302 0.258194
+0.600494 0.826509 0.156502
+
+0.680977 0.756302 0.258194
+0.574343 0.790515 0.224149
+0.635585 0.705888 0.322196
+
+0.539726 0.742869 0.279711
+0.635585 0.705888 0.322196
+0.574343 0.790515 0.224149
+
+0.635585 0.705888 0.322196
+0.539726 0.742869 0.279711
+0.581539 0.645865 0.368828
+
+0.498511 0.686142 0.320194
+0.581539 0.645865 0.368828
+0.539726 0.742869 0.279711
+
+0.581539 0.645865 0.368828
+0.498511 0.686142 0.320194
+0.521755 0.579468 0.395577
+
+0.45292 0.623391 0.343415
+0.521755 0.579468 0.395577
+0.498511 0.686142 0.320194
+
+0.521755 0.579468 0.395577
+0.45292 0.623391 0.343415
+0.459455 0.510276 0.401
+
+0.40541 0.557999 0.348123
+0.459455 0.510276 0.401
+0.45292 0.623391 0.343415
+
+0.459455 0.510276 0.401
+0.40541 0.557999 0.348123
+0.397997 0.44202 0.384804
+
+0.358542 0.493491 0.334064
+0.397997 0.44202 0.384804
+0.40541 0.557999 0.348123
+
+0.397997 0.44202 0.384804
+0.358542 0.493491 0.334064
+0.340695 0.37838 0.347864
+
+0.314843 0.433345 0.301995
+0.340695 0.37838 0.347864
+0.358542 0.493491 0.334064
+
+0.340695 0.37838 0.347864
+0.314843 0.433345 0.301995
+0.290638 0.322786 0.292171
+
+0.27667 0.380803 0.253645
+0.290638 0.322786 0.292171
+0.314843 0.433345 0.301995
+
+0.290638 0.322786 0.292171
+0.27667 0.380803 0.253645
+0.250524 0.278235 0.220726
+
+0.246079 0.338698 0.191621
+0.250524 0.278235 0.220726
+0.27667 0.380803 0.253645
+
+0.250524 0.278235 0.220726
+0.246079 0.338698 0.191621
+0.222516 0.247129 0.137382
+
+0.22472 0.309301 0.119267
+0.222516 0.247129 0.137382
+0.246079 0.338698 0.191621
+
+0.222516 0.247129 0.137382
+0.22472 0.309301 0.119267
+0.208124 0.231145 0.0466321
+
+0.213745 0.294195 0.0404831
+0.208124 0.231145 0.0466321
+0.22472 0.309301 0.119267
+
+0.208124 0.231145 0.0466321
+0.213745 0.294195 0.0404831
+0.208124 0.231145 -0.0466321
+
+0.213745 0.294195 -0.0404831
+0.208124 0.231145 -0.0466321
+0.213745 0.294195 0.0404831
+
+0.208124 0.231145 -0.0466321
+0.213745 0.294195 -0.0404831
+0.222516 0.247129 -0.137382
+
+0.22472 0.309301 -0.119267
+0.222516 0.247129 -0.137382
+0.213745 0.294195 -0.0404831
+
+0.222516 0.247129 -0.137382
+0.22472 0.309301 -0.119267
+0.250524 0.278235 -0.220726
+
+0.246079 0.338698 -0.191621
+0.250524 0.278235 -0.220726
+0.22472 0.309301 -0.119267
+
+0.250524 0.278235 -0.220726
+0.246079 0.338698 -0.191621
+0.290638 0.322786 -0.292171
+
+0.27667 0.380803 -0.253645
+0.290638 0.322786 -0.292171
+0.246079 0.338698 -0.191621
+
+0.290638 0.322786 -0.292171
+0.27667 0.380803 -0.253645
+0.340695 0.37838 -0.347864
+
+0.314843 0.433345 -0.301995
+0.340695 0.37838 -0.347864
+0.27667 0.380803 -0.253645
+
+0.340695 0.37838 -0.347864
+0.314843 0.433345 -0.301995
+0.397997 0.44202 -0.384804
+
+0.358542 0.493491 -0.334064
+0.397997 0.44202 -0.384804
+0.314843 0.433345 -0.301995
+
+0.397997 0.44202 -0.384804
+0.358542 0.493491 -0.334064
+0.459455 0.510276 -0.401
+
+0.40541 0.557999 -0.348123
+0.459455 0.510276 -0.401
+0.358542 0.493491 -0.334064
+
+0.459455 0.510276 -0.401
+0.40541 0.557999 -0.348123
+0.521755 0.579468 -0.395577
+
+0.45292 0.623391 -0.343415
+0.521755 0.579468 -0.395577
+0.40541 0.557999 -0.348123
+
+0.521755 0.579468 -0.395577
+0.45292 0.623391 -0.343415
+0.581539 0.645865 -0.368828
+
+0.498511 0.686142 -0.320194
+0.581539 0.645865 -0.368828
+0.45292 0.623391 -0.343415
+
+0.581539 0.645865 -0.368828
+0.498511 0.686142 -0.320194
+0.635585 0.705888 -0.322196
+
+0.539726 0.742869 -0.279711
+0.635585 0.705888 -0.322196
+0.498511 0.686142 -0.320194
+
+0.635585 0.705888 -0.322196
+0.539726 0.742869 -0.279711
+0.680977 0.756302 -0.258194
+
+0.574343 0.790515 -0.224149
+0.680977 0.756302 -0.258194
+0.539726 0.742869 -0.279711
+
+0.680977 0.756302 -0.258194
+0.574343 0.790515 -0.224149
+0.71527 0.794387 -0.180273
+
+0.600494 0.826509 -0.156502
+0.71527 0.794387 -0.180273
+0.574343 0.790515 -0.224149
+
+0.71527 0.794387 -0.180273
+0.600494 0.826509 -0.156502
+0.736614 0.818092 -0.0926336
+
+0.616771 0.848913 -0.0804188
+0.736614 0.818092 -0.0926336
+0.600494 0.826509 -0.156502
+
+0.736614 0.818092 -0.0926336
+0.616771 0.848913 -0.0804188
+0.743859 0.826139 0
+
+0.622296 0.856517 0
+0.743859 0.826139 0
+0.616771 0.848913 -0.0804188
+
+0.622296 0.856517 0
+0.5 0.866025 0
+0.616771 0.848913 0.0804188
+
+0.496092 0.859256 0.0668786
+0.616771 0.848913 0.0804188
+0.5 0.866025 0
+
+0.616771 0.848913 0.0804188
+0.496092 0.859256 0.0668786
+0.600494 0.826509 0.156502
+
+0.484577 0.839312 0.130152
+0.600494 0.826509 0.156502
+0.496092 0.859256 0.0668786
+
+0.600494 0.826509 0.156502
+0.484577 0.839312 0.130152
+0.574343 0.790515 0.224149
+
+0.466076 0.807268 0.186408
+0.574343 0.790515 0.224149
+0.484577 0.839312 0.130152
+
+0.574343 0.790515 0.224149
+0.466076 0.807268 0.186408
+0.539726 0.742869 0.279711
+
+0.441588 0.764853 0.232616
+0.539726 0.742869 0.279711
+0.466076 0.807268 0.186408
+
+0.539726 0.742869 0.279711
+0.441588 0.764853 0.232616
+0.498511 0.686142 0.320194
+
+0.412432 0.714352 0.266283
+0.498511 0.686142 0.320194
+0.441588 0.764853 0.232616
+
+0.498511 0.686142 0.320194
+0.412432 0.714352 0.266283
+0.45292 0.623391 0.343415
+
+0.380179 0.658489 0.285594
+0.45292 0.623391 0.343415
+0.412432 0.714352 0.266283
+
+0.45292 0.623391 0.343415
+0.380179 0.658489 0.285594
+0.40541 0.557999 0.348123
+
+0.346569 0.600275 0.289509
+0.40541 0.557999 0.348123
+0.380179 0.658489 0.285594
+
+0.40541 0.557999 0.348123
+0.346569 0.600275 0.289509
+0.358542 0.493491 0.334064
+
+0.313414 0.542848 0.277817
+0.358542 0.493491 0.334064
+0.346569 0.600275 0.289509
+
+0.358542 0.493491 0.334064
+0.313414 0.542848 0.277817
+0.314843 0.433345 0.301995
+
+0.2825 0.489304 0.251147
+0.314843 0.433345 0.301995
+0.313414 0.542848 0.277817
+
+0.314843 0.433345 0.301995
+0.2825 0.489304 0.251147
+0.27667 0.380803 0.253645
+
+0.255495 0.44253 0.210938
+0.27667 0.380803 0.253645
+0.2825 0.489304 0.251147
+
+0.27667 0.380803 0.253645
+0.255495 0.44253 0.210938
+0.246079 0.338698 0.191621
+
+0.233854 0.405047 0.159358
+0.246079 0.338698 0.191621
+0.255495 0.44253 0.210938
+
+0.246079 0.338698 0.191621
+0.233854 0.405047 0.159358
+0.22472 0.309301 0.119267
+
+0.218745 0.378877 0.0991858
+0.22472 0.309301 0.119267
+0.233854 0.405047 0.159358
+
+0.22472 0.309301 0.119267
+0.218745 0.378877 0.0991858
+0.213745 0.294195 0.0404831
+
+0.21098 0.365429 0.0336669
+0.213745 0.294195 0.0404831
+0.218745 0.378877 0.0991858
+
+0.213745 0.294195 0.0404831
+0.21098 0.365429 0.0336669
+0.213745 0.294195 -0.0404831
+
+0.21098 0.365429 -0.0336669
+0.213745 0.294195 -0.0404831
+0.21098 0.365429 0.0336669
+
+0.213745 0.294195 -0.0404831
+0.21098 0.365429 -0.0336669
+0.22472 0.309301 -0.119267
+
+0.218745 0.378877 -0.0991858
+0.22472 0.309301 -0.119267
+0.21098 0.365429 -0.0336669
+
+0.22472 0.309301 -0.119267
+0.218745 0.378877 -0.0991858
+0.246079 0.338698 -0.191621
+
+0.233854 0.405047 -0.159358
+0.246079 0.338698 -0.191621
+0.218745 0.378877 -0.0991858
+
+0.246079 0.338698 -0.191621
+0.233854 0.405047 -0.159358
+0.27667 0.380803 -0.253645
+
+0.255495 0.44253 -0.210938
+0.27667 0.380803 -0.253645
+0.233854 0.405047 -0.159358
+
+0.27667 0.380803 -0.253645
+0.255495 0.44253 -0.210938
+0.314843 0.433345 -0.301995
+
+0.2825 0.489304 -0.251147
+0.314843 0.433345 -0.301995
+0.255495 0.44253 -0.210938
+
+0.314843 0.433345 -0.301995
+0.2825 0.489304 -0.251147
+0.358542 0.493491 -0.334064
+
+0.313414 0.542848 -0.277817
+0.358542 0.493491 -0.334064
+0.2825 0.489304 -0.251147
+
+0.358542 0.493491 -0.334064
+0.313414 0.542848 -0.277817
+0.40541 0.557999 -0.348123
+
+0.346569 0.600275 -0.289509
+0.40541 0.557999 -0.348123
+0.313414 0.542848 -0.277817
+
+0.40541 0.557999 -0.348123
+0.346569 0.600275 -0.289509
+0.45292 0.623391 -0.343415
+
+0.380179 0.658489 -0.285594
+0.45292 0.623391 -0.343415
+0.346569 0.600275 -0.289509
+
+0.45292 0.623391 -0.343415
+0.380179 0.658489 -0.285594
+0.498511 0.686142 -0.320194
+
+0.412432 0.714352 -0.266283
+0.498511 0.686142 -0.320194
+0.380179 0.658489 -0.285594
+
+0.498511 0.686142 -0.320194
+0.412432 0.714352 -0.266283
+0.539726 0.742869 -0.279711
+
+0.441588 0.764853 -0.232616
+0.539726 0.742869 -0.279711
+0.412432 0.714352 -0.266283
+
+0.539726 0.742869 -0.279711
+0.441588 0.764853 -0.232616
+0.574343 0.790515 -0.224149
+
+0.466076 0.807268 -0.186408
+0.574343 0.790515 -0.224149
+0.441588 0.764853 -0.232616
+
+0.574343 0.790515 -0.224149
+0.466076 0.807268 -0.186408
+0.600494 0.826509 -0.156502
+
+0.484577 0.839312 -0.130152
+0.600494 0.826509 -0.156502
+0.466076 0.807268 -0.186408
+
+0.600494 0.826509 -0.156502
+0.484577 0.839312 -0.130152
+0.616771 0.848913 -0.0804188
+
+0.496092 0.859256 -0.0668786
+0.616771 0.848913 -0.0804188
+0.484577 0.839312 -0.130152
+
+0.616771 0.848913 -0.0804188
+0.496092 0.859256 -0.0668786
+0.622296 0.856517 0
+
+0.5 0.866025 0
+0.622296 0.856517 0
+0.496092 0.859256 -0.0668786
+
+0.5 0.866025 0
+0.382856 0.859908 0
+0.496092 0.859256 0.0668786
+
+0.38032 0.854213 0.0533384
+0.496092 0.859256 0.0668786
+0.382856 0.859908 0
+
+0.496092 0.859256 0.0668786
+0.38032 0.854213 0.0533384
+0.484577 0.839312 0.130152
+
+0.37285 0.837434 0.103801
+0.484577 0.839312 0.130152
+0.38032 0.854213 0.0533384
+
+0.484577 0.839312 0.130152
+0.37285 0.837434 0.103801
+0.466076 0.807268 0.186408
+
+0.360847 0.810476 0.148668
+0.466076 0.807268 0.186408
+0.37285 0.837434 0.103801
+
+0.466076 0.807268 0.186408
+0.360847 0.810476 0.148668
+0.441588 0.764853 0.232616
+
+0.344959 0.774791 0.18552
+0.441588 0.764853 0.232616
+0.360847 0.810476 0.148668
+
+0.441588 0.764853 0.232616
+0.344959 0.774791 0.18552
+0.412432 0.714352 0.266283
+
+0.326043 0.732305 0.212371
+0.412432 0.714352 0.266283
+0.344959 0.774791 0.18552
+
+0.412432 0.714352 0.266283
+0.326043 0.732305 0.212371
+0.380179 0.658489 0.285594
+
+0.305119 0.685308 0.227773
+0.380179 0.658489 0.285594
+0.326043 0.732305 0.212371
+
+0.380179 0.658489 0.285594
+0.305119 0.685308 0.227773
+0.346569 0.600275 0.289509
+
+0.283313 0.636332 0.230895
+0.346569 0.600275 0.289509
+0.305119 0.685308 0.227773
+
+0.346569 0.600275 0.289509
+0.283313 0.636332 0.230895
+0.313414 0.542848 0.277817
+
+0.261803 0.588018 0.22157
+0.313414 0.542848 0.277817
+0.283313 0.636332 0.230895
+
+0.313414 0.542848 0.277817
+0.261803 0.588018 0.22157
+0.2825 0.489304 0.251147
+
+0.241747 0.542972 0.2003
+0.2825 0.489304 0.251147
+0.261803 0.588018 0.22157
+
+0.2825 0.489304 0.251147
+0.241747 0.542972 0.2003
+0.255495 0.44253 0.210938
+
+0.224226 0.503621 0.168232
+0.255495 0.44253 0.210938
+0.241747 0.542972 0.2003
+
+0.255495 0.44253 0.210938
+0.224226 0.503621 0.168232
+0.233854 0.405047 0.159358
+
+0.210186 0.472086 0.127094
+0.233854 0.405047 0.159358
+0.224226 0.503621 0.168232
+
+0.233854 0.405047 0.159358
+0.210186 0.472086 0.127094
+0.218745 0.378877 0.0991858
+
+0.200383 0.450069 0.0791047
+0.218745 0.378877 0.0991858
+0.210186 0.472086 0.127094
+
+0.218745 0.378877 0.0991858
+0.200383 0.450069 0.0791047
+0.21098 0.365429 0.0336669
+
+0.195346 0.438755 0.0268508
+0.21098 0.365429 0.0336669
+0.200383 0.450069 0.0791047
+
+0.21098 0.365429 0.0336669
+0.195346 0.438755 0.0268508
+0.21098 0.365429 -0.0336669
+
+0.195346 0.438755 -0.0268508
+0.21098 0.365429 -0.0336669
+0.195346 0.438755 0.0268508
+
+0.21098 0.365429 -0.0336669
+0.195346 0.438755 -0.0268508
+0.218745 0.378877 -0.0991858
+
+0.200383 0.450069 -0.0791047
+0.218745 0.378877 -0.0991858
+0.195346 0.438755 -0.0268508
+
+0.218745 0.378877 -0.0991858
+0.200383 0.450069 -0.0791047
+0.233854 0.405047 -0.159358
+
+0.210186 0.472086 -0.127094
+0.233854 0.405047 -0.159358
+0.200383 0.450069 -0.0791047
+
+0.233854 0.405047 -0.159358
+0.210186 0.472086 -0.127094
+0.255495 0.44253 -0.210938
+
+0.224226 0.503621 -0.168232
+0.255495 0.44253 -0.210938
+0.210186 0.472086 -0.127094
+
+0.255495 0.44253 -0.210938
+0.224226 0.503621 -0.168232
+0.2825 0.489304 -0.251147
+
+0.241747 0.542972 -0.2003
+0.2825 0.489304 -0.251147
+0.224226 0.503621 -0.168232
+
+0.2825 0.489304 -0.251147
+0.241747 0.542972 -0.2003
+0.313414 0.542848 -0.277817
+
+0.261803 0.588018 -0.22157
+0.313414 0.542848 -0.277817
+0.241747 0.542972 -0.2003
+
+0.313414 0.542848 -0.277817
+0.261803 0.588018 -0.22157
+0.346569 0.600275 -0.289509
+
+0.283313 0.636332 -0.230895
+0.346569 0.600275 -0.289509
+0.261803 0.588018 -0.22157
+
+0.346569 0.600275 -0.289509
+0.283313 0.636332 -0.230895
+0.380179 0.658489 -0.285594
+
+0.305119 0.685308 -0.227773
+0.380179 0.658489 -0.285594
+0.283313 0.636332 -0.230895
+
+0.380179 0.658489 -0.285594
+0.305119 0.685308 -0.227773
+0.412432 0.714352 -0.266283
+
+0.326043 0.732305 -0.212371
+0.412432 0.714352 -0.266283
+0.305119 0.685308 -0.227773
+
+0.412432 0.714352 -0.266283
+0.326043 0.732305 -0.212371
+0.441588 0.764853 -0.232616
+
+0.344959 0.774791 -0.18552
+0.441588 0.764853 -0.232616
+0.326043 0.732305 -0.212371
+
+0.441588 0.764853 -0.232616
+0.344959 0.774791 -0.18552
+0.466076 0.807268 -0.186408
+
+0.360847 0.810476 -0.148668
+0.466076 0.807268 -0.186408
+0.344959 0.774791 -0.18552
+
+0.466076 0.807268 -0.186408
+0.360847 0.810476 -0.148668
+0.484577 0.839312 -0.130152
+
+0.37285 0.837434 -0.103801
+0.484577 0.839312 -0.130152
+0.360847 0.810476 -0.148668
+
+0.484577 0.839312 -0.130152
+0.37285 0.837434 -0.103801
+0.496092 0.859256 -0.0668786
+
+0.38032 0.854213 -0.0533384
+0.496092 0.859256 -0.0668786
+0.37285 0.837434 -0.103801
+
+0.496092 0.859256 -0.0668786
+0.38032 0.854213 -0.0533384
+0.5 0.866025 0
+
+0.382856 0.859908 0
+0.5 0.866025 0
+0.38032 0.854213 -0.0533384
+
+0.382856 0.859908 0
+0.274506 0.844843 0
+0.38032 0.854213 0.0533384
+
+0.273021 0.840272 0.0411236
+0.38032 0.854213 0.0533384
+0.274506 0.844843 0
+
+0.38032 0.854213 0.0533384
+0.273021 0.840272 0.0411236
+0.37285 0.837434 0.103801
+
+0.268645 0.826804 0.0800302
+0.37285 0.837434 0.103801
+0.273021 0.840272 0.0411236
+
+0.37285 0.837434 0.103801
+0.268645 0.826804 0.0800302
+0.360847 0.810476 0.148668
+
+0.261614 0.805166 0.114622
+0.360847 0.810476 0.148668
+0.268645 0.826804 0.0800302
+
+0.360847 0.810476 0.148668
+0.261614 0.805166 0.114622
+0.344959 0.774791 0.18552
+
+0.252308 0.776524 0.143035
+0.344959 0.774791 0.18552
+0.261614 0.805166 0.114622
+
+0.344959 0.774791 0.18552
+0.252308 0.776524 0.143035
+0.326043 0.732305 0.212371
+
+0.241228 0.742423 0.163737
+0.326043 0.732305 0.212371
+0.252308 0.776524 0.143035
+
+0.326043 0.732305 0.212371
+0.241228 0.742423 0.163737
+0.305119 0.685308 0.227773
+
+0.228971 0.7047 0.175612
+0.305119 0.685308 0.227773
+0.241228 0.742423 0.163737
+
+0.305119 0.685308 0.227773
+0.228971 0.7047 0.175612
+0.283313 0.636332 0.230895
+
+0.216198 0.665389 0.178019
+0.283313 0.636332 0.230895
+0.228971 0.7047 0.175612
+
+0.283313 0.636332 0.230895
+0.216198 0.665389 0.178019
+0.261803 0.588018 0.22157
+
+0.203598 0.62661 0.170829
+0.261803 0.588018 0.22157
+0.216198 0.665389 0.178019
+
+0.261803 0.588018 0.22157
+0.203598 0.62661 0.170829
+0.241747 0.542972 0.2003
+
+0.19185 0.590454 0.15443
+0.241747 0.542972 0.2003
+0.203598 0.62661 0.170829
+
+0.241747 0.542972 0.2003
+0.19185 0.590454 0.15443
+0.224226 0.503621 0.168232
+
+0.181587 0.558868 0.129706
+0.224226 0.503621 0.168232
+0.19185 0.590454 0.15443
+
+0.224226 0.503621 0.168232
+0.181587 0.558868 0.129706
+0.210186 0.472086 0.127094
+
+0.173363 0.533557 0.0979889
+0.210186 0.472086 0.127094
+0.181587 0.558868 0.129706
+
+0.210186 0.472086 0.127094
+0.173363 0.533557 0.0979889
+0.200383 0.450069 0.0791047
+
+0.167621 0.515885 0.0609893
+0.200383 0.450069 0.0791047
+0.173363 0.533557 0.0979889
+
+0.200383 0.450069 0.0791047
+0.167621 0.515885 0.0609893
+0.195346 0.438755 0.0268508
+
+0.164671 0.506804 0.0207018
+0.195346 0.438755 0.0268508
+0.167621 0.515885 0.0609893
+
+0.195346 0.438755 0.0268508
+0.164671 0.506804 0.0207018
+0.195346 0.438755 -0.0268508
+
+0.164671 0.506804 -0.0207018
+0.195346 0.438755 -0.0268508
+0.164671 0.506804 0.0207018
+
+0.195346 0.438755 -0.0268508
+0.164671 0.506804 -0.0207018
+0.200383 0.450069 -0.0791047
+
+0.167621 0.515885 -0.0609893
+0.200383 0.450069 -0.0791047
+0.164671 0.506804 -0.0207018
+
+0.200383 0.450069 -0.0791047
+0.167621 0.515885 -0.0609893
+0.210186 0.472086 -0.127094
+
+0.173363 0.533557 -0.0979889
+0.210186 0.472086 -0.127094
+0.167621 0.515885 -0.0609893
+
+0.210186 0.472086 -0.127094
+0.173363 0.533557 -0.0979889
+0.224226 0.503621 -0.168232
+
+0.181587 0.558868 -0.129706
+0.224226 0.503621 -0.168232
+0.173363 0.533557 -0.0979889
+
+0.224226 0.503621 -0.168232
+0.181587 0.558868 -0.129706
+0.241747 0.542972 -0.2003
+
+0.19185 0.590454 -0.15443
+0.241747 0.542972 -0.2003
+0.181587 0.558868 -0.129706
+
+0.241747 0.542972 -0.2003
+0.19185 0.590454 -0.15443
+0.261803 0.588018 -0.22157
+
+0.203598 0.62661 -0.170829
+0.261803 0.588018 -0.22157
+0.19185 0.590454 -0.15443
+
+0.261803 0.588018 -0.22157
+0.203598 0.62661 -0.170829
+0.283313 0.636332 -0.230895
+
+0.216198 0.665389 -0.178019
+0.283313 0.636332 -0.230895
+0.203598 0.62661 -0.170829
+
+0.283313 0.636332 -0.230895
+0.216198 0.665389 -0.178019
+0.305119 0.685308 -0.227773
+
+0.228971 0.7047 -0.175612
+0.305119 0.685308 -0.227773
+0.216198 0.665389 -0.178019
+
+0.305119 0.685308 -0.227773
+0.228971 0.7047 -0.175612
+0.326043 0.732305 -0.212371
+
+0.241228 0.742423 -0.163737
+0.326043 0.732305 -0.212371
+0.228971 0.7047 -0.175612
+
+0.326043 0.732305 -0.212371
+0.241228 0.742423 -0.163737
+0.344959 0.774791 -0.18552
+
+0.252308 0.776524 -0.143035
+0.344959 0.774791 -0.18552
+0.241228 0.742423 -0.163737
+
+0.344959 0.774791 -0.18552
+0.252308 0.776524 -0.143035
+0.360847 0.810476 -0.148668
+
+0.261614 0.805166 -0.114622
+0.360847 0.810476 -0.148668
+0.252308 0.776524 -0.143035
+
+0.360847 0.810476 -0.148668
+0.261614 0.805166 -0.114622
+0.37285 0.837434 -0.103801
+
+0.268645 0.826804 -0.0800302
+0.37285 0.837434 -0.103801
+0.261614 0.805166 -0.114622
+
+0.37285 0.837434 -0.103801
+0.268645 0.826804 -0.0800302
+0.38032 0.854213 -0.0533384
+
+0.273021 0.840272 -0.0411236
+0.38032 0.854213 -0.0533384
+0.268645 0.826804 -0.0800302
+
+0.38032 0.854213 -0.0533384
+0.273021 0.840272 -0.0411236
+0.382856 0.859908 0
+
+0.274506 0.844843 0
+0.382856 0.859908 0
+0.273021 0.840272 -0.0411236
+
+0.274506 0.844843 0
+0.175953 0.827793 0
+0.273021 0.840272 0.0411236
+
+0.175189 0.8242 0.0314299
+0.273021 0.840272 0.0411236
+0.175953 0.827793 0
+
+0.273021 0.840272 0.0411236
+0.175189 0.8242 0.0314299
+0.268645 0.826804 0.0800302
+
+0.172939 0.813614 0.0611654
+0.268645 0.826804 0.0800302
+0.175189 0.8242 0.0314299
+
+0.268645 0.826804 0.0800302
+0.172939 0.813614 0.0611654
+0.261614 0.805166 0.114622
+
+0.169324 0.796605 0.0876034
+0.261614 0.805166 0.114622
+0.172939 0.813614 0.0611654
+
+0.261614 0.805166 0.114622
+0.169324 0.796605 0.0876034
+0.252308 0.776524 0.143035
+
+0.164538 0.774091 0.109319
+0.252308 0.776524 0.143035
+0.169324 0.796605 0.0876034
+
+0.252308 0.776524 0.143035
+0.164538 0.774091 0.109319
+0.241228 0.742423 0.163737
+
+0.15884 0.747286 0.125141
+0.241228 0.742423 0.163737
+0.164538 0.774091 0.109319
+
+0.241228 0.742423 0.163737
+0.15884 0.747286 0.125141
+0.228971 0.7047 0.175612
+
+0.152538 0.717634 0.134216
+0.228971 0.7047 0.175612
+0.15884 0.747286 0.125141
+
+0.228971 0.7047 0.175612
+0.152538 0.717634 0.134216
+0.216198 0.665389 0.178019
+
+0.14597 0.686734 0.136056
+0.216198 0.665389 0.178019
+0.152538 0.717634 0.134216
+
+0.216198 0.665389 0.178019
+0.14597 0.686734 0.136056
+0.203598 0.62661 0.170829
+
+0.139491 0.656251 0.130561
+0.203598 0.62661 0.170829
+0.14597 0.686734 0.136056
+
+0.203598 0.62661 0.170829
+0.139491 0.656251 0.130561
+0.19185 0.590454 0.15443
+
+0.133449 0.627831 0.118028
+0.19185 0.590454 0.15443
+0.139491 0.656251 0.130561
+
+0.19185 0.590454 0.15443
+0.133449 0.627831 0.118028
+0.181587 0.558868 0.129706
+
+0.128172 0.603003 0.0991314
+0.181587 0.558868 0.129706
+0.133449 0.627831 0.118028
+
+0.181587 0.558868 0.129706
+0.128172 0.603003 0.0991314
+0.173363 0.533557 0.0979889
+
+0.123943 0.583107 0.0748908
+0.173363 0.533557 0.0979889
+0.128172 0.603003 0.0991314
+
+0.173363 0.533557 0.0979889
+0.123943 0.583107 0.0748908
+0.167621 0.515885 0.0609893
+
+0.120991 0.569216 0.0466128
+0.167621 0.515885 0.0609893
+0.123943 0.583107 0.0748908
+
+0.167621 0.515885 0.0609893
+0.120991 0.569216 0.0466128
+0.164671 0.506804 0.0207018
+
+0.119473 0.562078 0.0158219
+0.164671 0.506804 0.0207018
+0.120991 0.569216 0.0466128
+
+0.164671 0.506804 0.0207018
+0.119473 0.562078 0.0158219
+0.164671 0.506804 -0.0207018
+
+0.119473 0.562078 -0.0158219
+0.164671 0.506804 -0.0207018
+0.119473 0.562078 0.0158219
+
+0.164671 0.506804 -0.0207018
+0.119473 0.562078 -0.0158219
+0.167621 0.515885 -0.0609893
+
+0.120991 0.569216 -0.0466128
+0.167621 0.515885 -0.0609893
+0.119473 0.562078 -0.0158219
+
+0.167621 0.515885 -0.0609893
+0.120991 0.569216 -0.0466128
+0.173363 0.533557 -0.0979889
+
+0.123943 0.583107 -0.0748908
+0.173363 0.533557 -0.0979889
+0.120991 0.569216 -0.0466128
+
+0.173363 0.533557 -0.0979889
+0.123943 0.583107 -0.0748908
+0.181587 0.558868 -0.129706
+
+0.128172 0.603003 -0.0991314
+0.181587 0.558868 -0.129706
+0.123943 0.583107 -0.0748908
+
+0.181587 0.558868 -0.129706
+0.128172 0.603003 -0.0991314
+0.19185 0.590454 -0.15443
+
+0.133449 0.627831 -0.118028
+0.19185 0.590454 -0.15443
+0.128172 0.603003 -0.0991314
+
+0.19185 0.590454 -0.15443
+0.133449 0.627831 -0.118028
+0.203598 0.62661 -0.170829
+
+0.139491 0.656251 -0.130561
+0.203598 0.62661 -0.170829
+0.133449 0.627831 -0.118028
+
+0.203598 0.62661 -0.170829
+0.139491 0.656251 -0.130561
+0.216198 0.665389 -0.178019
+
+0.14597 0.686734 -0.136056
+0.216198 0.665389 -0.178019
+0.139491 0.656251 -0.130561
+
+0.216198 0.665389 -0.178019
+0.14597 0.686734 -0.136056
+0.228971 0.7047 -0.175612
+
+0.152538 0.717634 -0.134216
+0.228971 0.7047 -0.175612
+0.14597 0.686734 -0.136056
+
+0.228971 0.7047 -0.175612
+0.152538 0.717634 -0.134216
+0.241228 0.742423 -0.163737
+
+0.15884 0.747286 -0.125141
+0.241228 0.742423 -0.163737
+0.152538 0.717634 -0.134216
+
+0.241228 0.742423 -0.163737
+0.15884 0.747286 -0.125141
+0.252308 0.776524 -0.143035
+
+0.164538 0.774091 -0.109319
+0.252308 0.776524 -0.143035
+0.15884 0.747286 -0.125141
+
+0.252308 0.776524 -0.143035
+0.164538 0.774091 -0.109319
+0.261614 0.805166 -0.114622
+
+0.169324 0.796605 -0.0876034
+0.261614 0.805166 -0.114622
+0.164538 0.774091 -0.109319
+
+0.261614 0.805166 -0.114622
+0.169324 0.796605 -0.0876034
+0.268645 0.826804 -0.0800302
+
+0.172939 0.813614 -0.0611654
+0.268645 0.826804 -0.0800302
+0.169324 0.796605 -0.0876034
+
+0.268645 0.826804 -0.0800302
+0.172939 0.813614 -0.0611654
+0.273021 0.840272 -0.0411236
+
+0.175189 0.8242 -0.0314299
+0.273021 0.840272 -0.0411236
+0.172939 0.813614 -0.0611654
+
+0.273021 0.840272 -0.0411236
+0.175189 0.8242 -0.0314299
+0.274506 0.844843 0
+
+0.175953 0.827793 0
+0.274506 0.844843 0
+0.175189 0.8242 -0.0314299
+
+0.175953 0.827793 0
+0.0856401 0.814811 0
+0.175189 0.8242 0.0314299
+
+0.0853321 0.811881 0.0252061
+0.175189 0.8242 0.0314299
+0.0856401 0.814811 0
+
+0.175189 0.8242 0.0314299
+0.0853321 0.811881 0.0252061
+0.172939 0.813614 0.0611654
+
+0.0844249 0.803249 0.0490534
+0.172939 0.813614 0.0611654
+0.0853321 0.811881 0.0252061
+
+0.172939 0.813614 0.0611654
+0.0844249 0.803249 0.0490534
+0.169324 0.796605 0.0876034
+
+0.0829672 0.78938 0.0702562
+0.169324 0.796605 0.0876034
+0.0844249 0.803249 0.0490534
+
+0.169324 0.796605 0.0876034
+0.0829672 0.78938 0.0702562
+0.164538 0.774091 0.109319
+
+0.0810377 0.771022 0.0876715
+0.164538 0.774091 0.109319
+0.0829672 0.78938 0.0702562
+
+0.164538 0.774091 0.109319
+0.0810377 0.771022 0.0876715
+0.15884 0.747286 0.125141
+
+0.0787404 0.749165 0.10036
+0.15884 0.747286 0.125141
+0.0810377 0.771022 0.0876715
+
+0.15884 0.747286 0.125141
+0.0787404 0.749165 0.10036
+0.152538 0.717634 0.134216
+
+0.0761991 0.724986 0.107639
+0.152538 0.717634 0.134216
+0.0787404 0.749165 0.10036
+
+0.152538 0.717634 0.134216
+0.0761991 0.724986 0.107639
+0.14597 0.686734 0.136056
+
+0.0735509 0.69979 0.109114
+0.14597 0.686734 0.136056
+0.0761991 0.724986 0.107639
+
+0.14597 0.686734 0.136056
+0.0735509 0.69979 0.109114
+0.139491 0.656251 0.130561
+
+0.0709385 0.674935 0.104708
+0.139491 0.656251 0.130561
+0.0735509 0.69979 0.109114
+
+0.139491 0.656251 0.130561
+0.0709385 0.674935 0.104708
+0.133449 0.627831 0.118028
+
+0.0685028 0.65176 0.0946559
+0.133449 0.627831 0.118028
+0.0709385 0.674935 0.104708
+
+0.133449 0.627831 0.118028
+0.0685028 0.65176 0.0946559
+0.128172 0.603003 0.0991314
+
+0.066375 0.631516 0.0795014
+0.128172 0.603003 0.0991314
+0.0685028 0.65176 0.0946559
+
+0.128172 0.603003 0.0991314
+0.066375 0.631516 0.0795014
+0.123943 0.583107 0.0748908
+
+0.0646699 0.615293 0.0600609
+0.123943 0.583107 0.0748908
+0.066375 0.631516 0.0795014
+
+0.123943 0.583107 0.0748908
+0.0646699 0.615293 0.0600609
+0.120991 0.569216 0.0466128
+
+0.0634793 0.603965 0.0373825
+0.120991 0.569216 0.0466128
+0.0646699 0.615293 0.0600609
+
+0.120991 0.569216 0.0466128
+0.0634793 0.603965 0.0373825
+0.119473 0.562078 0.0158219
+
+0.0628676 0.598145 0.0126889
+0.119473 0.562078 0.0158219
+0.0634793 0.603965 0.0373825
+
+0.119473 0.562078 0.0158219
+0.0628676 0.598145 0.0126889
+0.119473 0.562078 -0.0158219
+
+0.0628676 0.598145 -0.0126889
+0.119473 0.562078 -0.0158219
+0.0628676 0.598145 0.0126889
+
+0.119473 0.562078 -0.0158219
+0.0628676 0.598145 -0.0126889
+0.120991 0.569216 -0.0466128
+
+0.0634793 0.603965 -0.0373825
+0.120991 0.569216 -0.0466128
+0.0628676 0.598145 -0.0126889
+
+0.120991 0.569216 -0.0466128
+0.0634793 0.603965 -0.0373825
+0.123943 0.583107 -0.0748908
+
+0.0646699 0.615293 -0.0600609
+0.123943 0.583107 -0.0748908
+0.0634793 0.603965 -0.0373825
+
+0.123943 0.583107 -0.0748908
+0.0646699 0.615293 -0.0600609
+0.128172 0.603003 -0.0991314
+
+0.066375 0.631516 -0.0795014
+0.128172 0.603003 -0.0991314
+0.0646699 0.615293 -0.0600609
+
+0.128172 0.603003 -0.0991314
+0.066375 0.631516 -0.0795014
+0.133449 0.627831 -0.118028
+
+0.0685028 0.65176 -0.0946559
+0.133449 0.627831 -0.118028
+0.066375 0.631516 -0.0795014
+
+0.133449 0.627831 -0.118028
+0.0685028 0.65176 -0.0946559
+0.139491 0.656251 -0.130561
+
+0.0709385 0.674935 -0.104708
+0.139491 0.656251 -0.130561
+0.0685028 0.65176 -0.0946559
+
+0.139491 0.656251 -0.130561
+0.0709385 0.674935 -0.104708
+0.14597 0.686734 -0.136056
+
+0.0735509 0.69979 -0.109114
+0.14597 0.686734 -0.136056
+0.0709385 0.674935 -0.104708
+
+0.14597 0.686734 -0.136056
+0.0735509 0.69979 -0.109114
+0.152538 0.717634 -0.134216
+
+0.0761991 0.724986 -0.107639
+0.152538 0.717634 -0.134216
+0.0735509 0.69979 -0.109114
+
+0.152538 0.717634 -0.134216
+0.0761991 0.724986 -0.107639
+0.15884 0.747286 -0.125141
+
+0.0787404 0.749165 -0.10036
+0.15884 0.747286 -0.125141
+0.0761991 0.724986 -0.107639
+
+0.15884 0.747286 -0.125141
+0.0787404 0.749165 -0.10036
+0.164538 0.774091 -0.109319
+
+0.0810377 0.771022 -0.0876715
+0.164538 0.774091 -0.109319
+0.0787404 0.749165 -0.10036
+
+0.164538 0.774091 -0.109319
+0.0810377 0.771022 -0.0876715
+0.169324 0.796605 -0.0876034
+
+0.0829672 0.78938 -0.0702562
+0.169324 0.796605 -0.0876034
+0.0810377 0.771022 -0.0876715
+
+0.169324 0.796605 -0.0876034
+0.0829672 0.78938 -0.0702562
+0.172939 0.813614 -0.0611654
+
+0.0844249 0.803249 -0.0490534
+0.172939 0.813614 -0.0611654
+0.0829672 0.78938 -0.0702562
+
+0.172939 0.813614 -0.0611654
+0.0844249 0.803249 -0.0490534
+0.175189 0.8242 -0.0314299
+
+0.0853321 0.811881 -0.0252061
+0.175189 0.8242 -0.0314299
+0.0844249 0.803249 -0.0490534
+
+0.175189 0.8242 -0.0314299
+0.0853321 0.811881 -0.0252061
+0.175953 0.827793 0
+
+0.0856401 0.814811 0
+0.175953 0.827793 0
+0.0853321 0.811881 -0.0252061
+
+0.0856401 0.814811 0
+1.79856e-16 0.81 0
+0.0853321 0.811881 0.0252061
+
+1.79258e-16 0.807304 0.0230616
+0.0853321 0.811881 0.0252061
+1.79856e-16 0.81 0
+
+0.0853321 0.811881 0.0252061
+1.79258e-16 0.807304 0.0230616
+0.0844249 0.803249 0.0490534
+
+1.77494e-16 0.799363 0.0448799
+0.0844249 0.803249 0.0490534
+1.79258e-16 0.807304 0.0230616
+
+0.0844249 0.803249 0.0490534
+1.77494e-16 0.799363 0.0448799
+0.0829672 0.78938 0.0702562
+
+1.74661e-16 0.786604 0.0642788
+0.0829672 0.78938 0.0702562
+1.77494e-16 0.799363 0.0448799
+
+0.0829672 0.78938 0.0702562
+1.74661e-16 0.786604 0.0642788
+0.0810377 0.771022 0.0876715
+
+1.70911e-16 0.769716 0.0802123
+0.0810377 0.771022 0.0876715
+1.74661e-16 0.786604 0.0642788
+
+0.0810377 0.771022 0.0876715
+1.70911e-16 0.769716 0.0802123
+0.0787404 0.749165 0.10036
+
+1.66446e-16 0.749608 0.0918216
+0.0787404 0.749165 0.10036
+1.70911e-16 0.769716 0.0802123
+
+0.0787404 0.749165 0.10036
+1.66446e-16 0.749608 0.0918216
+0.0761991 0.724986 0.107639
+
+1.61507e-16 0.727365 0.0984808
+0.0761991 0.724986 0.107639
+1.66446e-16 0.749608 0.0918216
+
+0.0761991 0.724986 0.107639
+1.61507e-16 0.727365 0.0984808
+0.0735509 0.69979 0.109114
+
+1.56361e-16 0.704186 0.0998308
+0.0735509 0.69979 0.109114
+1.61507e-16 0.727365 0.0984808
+
+0.0735509 0.69979 0.109114
+1.56361e-16 0.704186 0.0998308
+0.0709385 0.674935 0.104708
+
+1.51283e-16 0.68132 0.095799
+0.0709385 0.674935 0.104708
+1.56361e-16 0.704186 0.0998308
+
+0.0709385 0.674935 0.104708
+1.51283e-16 0.68132 0.095799
+0.0685028 0.65176 0.0946559
+
+1.46549e-16 0.66 0.0866025
+0.0685028 0.65176 0.0946559
+1.51283e-16 0.68132 0.095799
+
+0.0685028 0.65176 0.0946559
+1.46549e-16 0.66 0.0866025
+0.066375 0.631516 0.0795014
+
+1.42414e-16 0.641376 0.0727374
+0.066375 0.631516 0.0795014
+1.46549e-16 0.66 0.0866025
+
+0.066375 0.631516 0.0795014
+1.42414e-16 0.641376 0.0727374
+0.0646699 0.615293 0.0600609
+
+1.391e-16 0.626451 0.0549509
+0.0646699 0.615293 0.0600609
+1.42414e-16 0.641376 0.0727374
+
+0.0646699 0.615293 0.0600609
+1.391e-16 0.626451 0.0549509
+0.0634793 0.603965 0.0373825
+
+1.36786e-16 0.616031 0.034202
+0.0634793 0.603965 0.0373825
+1.391e-16 0.626451 0.0549509
+
+0.0634793 0.603965 0.0373825
+1.36786e-16 0.616031 0.034202
+0.0628676 0.598145 0.0126889
+
+1.35597e-16 0.610676 0.0116093
+0.0628676 0.598145 0.0126889
+1.36786e-16 0.616031 0.034202
+
+0.0628676 0.598145 0.0126889
+1.35597e-16 0.610676 0.0116093
+0.0628676 0.598145 -0.0126889
+
+1.35597e-16 0.610676 -0.0116093
+0.0628676 0.598145 -0.0126889
+1.35597e-16 0.610676 0.0116093
+
+0.0628676 0.598145 -0.0126889
+1.35597e-16 0.610676 -0.0116093
+0.0634793 0.603965 -0.0373825
+
+1.36786e-16 0.616031 -0.034202
+0.0634793 0.603965 -0.0373825
+1.35597e-16 0.610676 -0.0116093
+
+0.0634793 0.603965 -0.0373825
+1.36786e-16 0.616031 -0.034202
+0.0646699 0.615293 -0.0600609
+
+1.391e-16 0.626451 -0.0549509
+0.0646699 0.615293 -0.0600609
+1.36786e-16 0.616031 -0.034202
+
+0.0646699 0.615293 -0.0600609
+1.391e-16 0.626451 -0.0549509
+0.066375 0.631516 -0.0795014
+
+1.42414e-16 0.641376 -0.0727374
+0.066375 0.631516 -0.0795014
+1.391e-16 0.626451 -0.0549509
+
+0.066375 0.631516 -0.0795014
+1.42414e-16 0.641376 -0.0727374
+0.0685028 0.65176 -0.0946559
+
+1.46549e-16 0.66 -0.0866025
+0.0685028 0.65176 -0.0946559
+1.42414e-16 0.641376 -0.0727374
+
+0.0685028 0.65176 -0.0946559
+1.46549e-16 0.66 -0.0866025
+0.0709385 0.674935 -0.104708
+
+1.51283e-16 0.68132 -0.095799
+0.0709385 0.674935 -0.104708
+1.46549e-16 0.66 -0.0866025
+
+0.0709385 0.674935 -0.104708
+1.51283e-16 0.68132 -0.095799
+0.0735509 0.69979 -0.109114
+
+1.56361e-16 0.704186 -0.0998308
+0.0735509 0.69979 -0.109114
+1.51283e-16 0.68132 -0.095799
+
+0.0735509 0.69979 -0.109114
+1.56361e-16 0.704186 -0.0998308
+0.0761991 0.724986 -0.107639
+
+1.61507e-16 0.727365 -0.0984808
+0.0761991 0.724986 -0.107639
+1.56361e-16 0.704186 -0.0998308
+
+0.0761991 0.724986 -0.107639
+1.61507e-16 0.727365 -0.0984808
+0.0787404 0.749165 -0.10036
+
+1.66446e-16 0.749608 -0.0918216
+0.0787404 0.749165 -0.10036
+1.61507e-16 0.727365 -0.0984808
+
+0.0787404 0.749165 -0.10036
+1.66446e-16 0.749608 -0.0918216
+0.0810377 0.771022 -0.0876715
+
+1.70911e-16 0.769716 -0.0802123
+0.0810377 0.771022 -0.0876715
+1.66446e-16 0.749608 -0.0918216
+
+0.0810377 0.771022 -0.0876715
+1.70911e-16 0.769716 -0.0802123
+0.0829672 0.78938 -0.0702562
+
+1.74661e-16 0.786604 -0.0642788
+0.0829672 0.78938 -0.0702562
+1.70911e-16 0.769716 -0.0802123
+
+0.0829672 0.78938 -0.0702562
+1.74661e-16 0.786604 -0.0642788
+0.0844249 0.803249 -0.0490534
+
+1.77494e-16 0.799363 -0.0448799
+0.0844249 0.803249 -0.0490534
+1.74661e-16 0.786604 -0.0642788
+
+0.0844249 0.803249 -0.0490534
+1.77494e-16 0.799363 -0.0448799
+0.0853321 0.811881 -0.0252061
+
+1.79258e-16 0.807304 -0.0230616
+0.0853321 0.811881 -0.0252061
+1.77494e-16 0.799363 -0.0448799
+
+0.0853321 0.811881 -0.0252061
+1.79258e-16 0.807304 -0.0230616
+0.0856401 0.814811 0
+
+1.79856e-16 0.81 0
+0.0856401 0.814811 0
+1.79258e-16 0.807304 -0.0230616
+
+1.79856e-16 0.81 0
+-0.0856401 0.814811 0
+1.79258e-16 0.807304 0.0230616
+
+-0.0853321 0.811881 0.0252061
+1.79258e-16 0.807304 0.0230616
+-0.0856401 0.814811 0
+
+1.79258e-16 0.807304 0.0230616
+-0.0853321 0.811881 0.0252061
+1.77494e-16 0.799363 0.0448799
+
+-0.0844249 0.803249 0.0490534
+1.77494e-16 0.799363 0.0448799
+-0.0853321 0.811881 0.0252061
+
+1.77494e-16 0.799363 0.0448799
+-0.0844249 0.803249 0.0490534
+1.74661e-16 0.786604 0.0642788
+
+-0.0829672 0.78938 0.0702562
+1.74661e-16 0.786604 0.0642788
+-0.0844249 0.803249 0.0490534
+
+1.74661e-16 0.786604 0.0642788
+-0.0829672 0.78938 0.0702562
+1.70911e-16 0.769716 0.0802123
+
+-0.0810377 0.771022 0.0876715
+1.70911e-16 0.769716 0.0802123
+-0.0829672 0.78938 0.0702562
+
+1.70911e-16 0.769716 0.0802123
+-0.0810377 0.771022 0.0876715
+1.66446e-16 0.749608 0.0918216
+
+-0.0787404 0.749165 0.10036
+1.66446e-16 0.749608 0.0918216
+-0.0810377 0.771022 0.0876715
+
+1.66446e-16 0.749608 0.0918216
+-0.0787404 0.749165 0.10036
+1.61507e-16 0.727365 0.0984808
+
+-0.0761991 0.724986 0.107639
+1.61507e-16 0.727365 0.0984808
+-0.0787404 0.749165 0.10036
+
+1.61507e-16 0.727365 0.0984808
+-0.0761991 0.724986 0.107639
+1.56361e-16 0.704186 0.0998308
+
+-0.0735509 0.69979 0.109114
+1.56361e-16 0.704186 0.0998308
+-0.0761991 0.724986 0.107639
+
+1.56361e-16 0.704186 0.0998308
+-0.0735509 0.69979 0.109114
+1.51283e-16 0.68132 0.095799
+
+-0.0709385 0.674935 0.104708
+1.51283e-16 0.68132 0.095799
+-0.0735509 0.69979 0.109114
+
+1.51283e-16 0.68132 0.095799
+-0.0709385 0.674935 0.104708
+1.46549e-16 0.66 0.0866025
+
+-0.0685028 0.65176 0.0946559
+1.46549e-16 0.66 0.0866025
+-0.0709385 0.674935 0.104708
+
+1.46549e-16 0.66 0.0866025
+-0.0685028 0.65176 0.0946559
+1.42414e-16 0.641376 0.0727374
+
+-0.066375 0.631516 0.0795014
+1.42414e-16 0.641376 0.0727374
+-0.0685028 0.65176 0.0946559
+
+1.42414e-16 0.641376 0.0727374
+-0.066375 0.631516 0.0795014
+1.391e-16 0.626451 0.0549509
+
+-0.0646699 0.615293 0.0600609
+1.391e-16 0.626451 0.0549509
+-0.066375 0.631516 0.0795014
+
+1.391e-16 0.626451 0.0549509
+-0.0646699 0.615293 0.0600609
+1.36786e-16 0.616031 0.034202
+
+-0.0634793 0.603965 0.0373825
+1.36786e-16 0.616031 0.034202
+-0.0646699 0.615293 0.0600609
+
+1.36786e-16 0.616031 0.034202
+-0.0634793 0.603965 0.0373825
+1.35597e-16 0.610676 0.0116093
+
+-0.0628676 0.598145 0.0126889
+1.35597e-16 0.610676 0.0116093
+-0.0634793 0.603965 0.0373825
+
+1.35597e-16 0.610676 0.0116093
+-0.0628676 0.598145 0.0126889
+1.35597e-16 0.610676 -0.0116093
+
+-0.0628676 0.598145 -0.0126889
+1.35597e-16 0.610676 -0.0116093
+-0.0628676 0.598145 0.0126889
+
+1.35597e-16 0.610676 -0.0116093
+-0.0628676 0.598145 -0.0126889
+1.36786e-16 0.616031 -0.034202
+
+-0.0634793 0.603965 -0.0373825
+1.36786e-16 0.616031 -0.034202
+-0.0628676 0.598145 -0.0126889
+
+1.36786e-16 0.616031 -0.034202
+-0.0634793 0.603965 -0.0373825
+1.391e-16 0.626451 -0.0549509
+
+-0.0646699 0.615293 -0.0600609
+1.391e-16 0.626451 -0.0549509
+-0.0634793 0.603965 -0.0373825
+
+1.391e-16 0.626451 -0.0549509
+-0.0646699 0.615293 -0.0600609
+1.42414e-16 0.641376 -0.0727374
+
+-0.066375 0.631516 -0.0795014
+1.42414e-16 0.641376 -0.0727374
+-0.0646699 0.615293 -0.0600609
+
+1.42414e-16 0.641376 -0.0727374
+-0.066375 0.631516 -0.0795014
+1.46549e-16 0.66 -0.0866025
+
+-0.0685028 0.65176 -0.0946559
+1.46549e-16 0.66 -0.0866025
+-0.066375 0.631516 -0.0795014
+
+1.46549e-16 0.66 -0.0866025
+-0.0685028 0.65176 -0.0946559
+1.51283e-16 0.68132 -0.095799
+
+-0.0709385 0.674935 -0.104708
+1.51283e-16 0.68132 -0.095799
+-0.0685028 0.65176 -0.0946559
+
+1.51283e-16 0.68132 -0.095799
+-0.0709385 0.674935 -0.104708
+1.56361e-16 0.704186 -0.0998308
+
+-0.0735509 0.69979 -0.109114
+1.56361e-16 0.704186 -0.0998308
+-0.0709385 0.674935 -0.104708
+
+1.56361e-16 0.704186 -0.0998308
+-0.0735509 0.69979 -0.109114
+1.61507e-16 0.727365 -0.0984808
+
+-0.0761991 0.724986 -0.107639
+1.61507e-16 0.727365 -0.0984808
+-0.0735509 0.69979 -0.109114
+
+1.61507e-16 0.727365 -0.0984808
+-0.0761991 0.724986 -0.107639
+1.66446e-16 0.749608 -0.0918216
+
+-0.0787404 0.749165 -0.10036
+1.66446e-16 0.749608 -0.0918216
+-0.0761991 0.724986 -0.107639
+
+1.66446e-16 0.749608 -0.0918216
+-0.0787404 0.749165 -0.10036
+1.70911e-16 0.769716 -0.0802123
+
+-0.0810377 0.771022 -0.0876715
+1.70911e-16 0.769716 -0.0802123
+-0.0787404 0.749165 -0.10036
+
+1.70911e-16 0.769716 -0.0802123
+-0.0810377 0.771022 -0.0876715
+1.74661e-16 0.786604 -0.0642788
+
+-0.0829672 0.78938 -0.0702562
+1.74661e-16 0.786604 -0.0642788
+-0.0810377 0.771022 -0.0876715
+
+1.74661e-16 0.786604 -0.0642788
+-0.0829672 0.78938 -0.0702562
+1.77494e-16 0.799363 -0.0448799
+
+-0.0844249 0.803249 -0.0490534
+1.77494e-16 0.799363 -0.0448799
+-0.0829672 0.78938 -0.0702562
+
+1.77494e-16 0.799363 -0.0448799
+-0.0844249 0.803249 -0.0490534
+1.79258e-16 0.807304 -0.0230616
+
+-0.0853321 0.811881 -0.0252061
+1.79258e-16 0.807304 -0.0230616
+-0.0844249 0.803249 -0.0490534
+
+1.79258e-16 0.807304 -0.0230616
+-0.0853321 0.811881 -0.0252061
+1.79856e-16 0.81 0
+
+-0.0856401 0.814811 0
+1.79856e-16 0.81 0
+-0.0853321 0.811881 -0.0252061
+
+-0.0856401 0.814811 0
+-0.175953 0.827793 0
+-0.0853321 0.811881 0.0252061
+
+-0.175189 0.8242 0.0314299
+-0.0853321 0.811881 0.0252061
+-0.175953 0.827793 0
+
+-0.0853321 0.811881 0.0252061
+-0.175189 0.8242 0.0314299
+-0.0844249 0.803249 0.0490534
+
+-0.172939 0.813614 0.0611654
+-0.0844249 0.803249 0.0490534
+-0.175189 0.8242 0.0314299
+
+-0.0844249 0.803249 0.0490534
+-0.172939 0.813614 0.0611654
+-0.0829672 0.78938 0.0702562
+
+-0.169324 0.796605 0.0876034
+-0.0829672 0.78938 0.0702562
+-0.172939 0.813614 0.0611654
+
+-0.0829672 0.78938 0.0702562
+-0.169324 0.796605 0.0876034
+-0.0810377 0.771022 0.0876715
+
+-0.164538 0.774091 0.109319
+-0.0810377 0.771022 0.0876715
+-0.169324 0.796605 0.0876034
+
+-0.0810377 0.771022 0.0876715
+-0.164538 0.774091 0.109319
+-0.0787404 0.749165 0.10036
+
+-0.15884 0.747286 0.125141
+-0.0787404 0.749165 0.10036
+-0.164538 0.774091 0.109319
+
+-0.0787404 0.749165 0.10036
+-0.15884 0.747286 0.125141
+-0.0761991 0.724986 0.107639
+
+-0.152538 0.717634 0.134216
+-0.0761991 0.724986 0.107639
+-0.15884 0.747286 0.125141
+
+-0.0761991 0.724986 0.107639
+-0.152538 0.717634 0.134216
+-0.0735509 0.69979 0.109114
+
+-0.14597 0.686734 0.136056
+-0.0735509 0.69979 0.109114
+-0.152538 0.717634 0.134216
+
+-0.0735509 0.69979 0.109114
+-0.14597 0.686734 0.136056
+-0.0709385 0.674935 0.104708
+
+-0.139491 0.656251 0.130561
+-0.0709385 0.674935 0.104708
+-0.14597 0.686734 0.136056
+
+-0.0709385 0.674935 0.104708
+-0.139491 0.656251 0.130561
+-0.0685028 0.65176 0.0946559
+
+-0.133449 0.627831 0.118028
+-0.0685028 0.65176 0.0946559
+-0.139491 0.656251 0.130561
+
+-0.0685028 0.65176 0.0946559
+-0.133449 0.627831 0.118028
+-0.066375 0.631516 0.0795014
+
+-0.128172 0.603003 0.0991314
+-0.066375 0.631516 0.0795014
+-0.133449 0.627831 0.118028
+
+-0.066375 0.631516 0.0795014
+-0.128172 0.603003 0.0991314
+-0.0646699 0.615293 0.0600609
+
+-0.123943 0.583107 0.0748908
+-0.0646699 0.615293 0.0600609
+-0.128172 0.603003 0.0991314
+
+-0.0646699 0.615293 0.0600609
+-0.123943 0.583107 0.0748908
+-0.0634793 0.603965 0.0373825
+
+-0.120991 0.569216 0.0466128
+-0.0634793 0.603965 0.0373825
+-0.123943 0.583107 0.0748908
+
+-0.0634793 0.603965 0.0373825
+-0.120991 0.569216 0.0466128
+-0.0628676 0.598145 0.0126889
+
+-0.119473 0.562078 0.0158219
+-0.0628676 0.598145 0.0126889
+-0.120991 0.569216 0.0466128
+
+-0.0628676 0.598145 0.0126889
+-0.119473 0.562078 0.0158219
+-0.0628676 0.598145 -0.0126889
+
+-0.119473 0.562078 -0.0158219
+-0.0628676 0.598145 -0.0126889
+-0.119473 0.562078 0.0158219
+
+-0.0628676 0.598145 -0.0126889
+-0.119473 0.562078 -0.0158219
+-0.0634793 0.603965 -0.0373825
+
+-0.120991 0.569216 -0.0466128
+-0.0634793 0.603965 -0.0373825
+-0.119473 0.562078 -0.0158219
+
+-0.0634793 0.603965 -0.0373825
+-0.120991 0.569216 -0.0466128
+-0.0646699 0.615293 -0.0600609
+
+-0.123943 0.583107 -0.0748908
+-0.0646699 0.615293 -0.0600609
+-0.120991 0.569216 -0.0466128
+
+-0.0646699 0.615293 -0.0600609
+-0.123943 0.583107 -0.0748908
+-0.066375 0.631516 -0.0795014
+
+-0.128172 0.603003 -0.0991314
+-0.066375 0.631516 -0.0795014
+-0.123943 0.583107 -0.0748908
+
+-0.066375 0.631516 -0.0795014
+-0.128172 0.603003 -0.0991314
+-0.0685028 0.65176 -0.0946559
+
+-0.133449 0.627831 -0.118028
+-0.0685028 0.65176 -0.0946559
+-0.128172 0.603003 -0.0991314
+
+-0.0685028 0.65176 -0.0946559
+-0.133449 0.627831 -0.118028
+-0.0709385 0.674935 -0.104708
+
+-0.139491 0.656251 -0.130561
+-0.0709385 0.674935 -0.104708
+-0.133449 0.627831 -0.118028
+
+-0.0709385 0.674935 -0.104708
+-0.139491 0.656251 -0.130561
+-0.0735509 0.69979 -0.109114
+
+-0.14597 0.686734 -0.136056
+-0.0735509 0.69979 -0.109114
+-0.139491 0.656251 -0.130561
+
+-0.0735509 0.69979 -0.109114
+-0.14597 0.686734 -0.136056
+-0.0761991 0.724986 -0.107639
+
+-0.152538 0.717634 -0.134216
+-0.0761991 0.724986 -0.107639
+-0.14597 0.686734 -0.136056
+
+-0.0761991 0.724986 -0.107639
+-0.152538 0.717634 -0.134216
+-0.0787404 0.749165 -0.10036
+
+-0.15884 0.747286 -0.125141
+-0.0787404 0.749165 -0.10036
+-0.152538 0.717634 -0.134216
+
+-0.0787404 0.749165 -0.10036
+-0.15884 0.747286 -0.125141
+-0.0810377 0.771022 -0.0876715
+
+-0.164538 0.774091 -0.109319
+-0.0810377 0.771022 -0.0876715
+-0.15884 0.747286 -0.125141
+
+-0.0810377 0.771022 -0.0876715
+-0.164538 0.774091 -0.109319
+-0.0829672 0.78938 -0.0702562
+
+-0.169324 0.796605 -0.0876034
+-0.0829672 0.78938 -0.0702562
+-0.164538 0.774091 -0.109319
+
+-0.0829672 0.78938 -0.0702562
+-0.169324 0.796605 -0.0876034
+-0.0844249 0.803249 -0.0490534
+
+-0.172939 0.813614 -0.0611654
+-0.0844249 0.803249 -0.0490534
+-0.169324 0.796605 -0.0876034
+
+-0.0844249 0.803249 -0.0490534
+-0.172939 0.813614 -0.0611654
+-0.0853321 0.811881 -0.0252061
+
+-0.175189 0.8242 -0.0314299
+-0.0853321 0.811881 -0.0252061
+-0.172939 0.813614 -0.0611654
+
+-0.0853321 0.811881 -0.0252061
+-0.175189 0.8242 -0.0314299
+-0.0856401 0.814811 0
+
+-0.175953 0.827793 0
+-0.0856401 0.814811 0
+-0.175189 0.8242 -0.0314299
+
+-0.175953 0.827793 0
+-0.274506 0.844843 0
+-0.175189 0.8242 0.0314299
+
+-0.273021 0.840272 0.0411236
+-0.175189 0.8242 0.0314299
+-0.274506 0.844843 0
+
+-0.175189 0.8242 0.0314299
+-0.273021 0.840272 0.0411236
+-0.172939 0.813614 0.0611654
+
+-0.268645 0.826804 0.0800302
+-0.172939 0.813614 0.0611654
+-0.273021 0.840272 0.0411236
+
+-0.172939 0.813614 0.0611654
+-0.268645 0.826804 0.0800302
+-0.169324 0.796605 0.0876034
+
+-0.261614 0.805166 0.114622
+-0.169324 0.796605 0.0876034
+-0.268645 0.826804 0.0800302
+
+-0.169324 0.796605 0.0876034
+-0.261614 0.805166 0.114622
+-0.164538 0.774091 0.109319
+
+-0.252308 0.776524 0.143035
+-0.164538 0.774091 0.109319
+-0.261614 0.805166 0.114622
+
+-0.164538 0.774091 0.109319
+-0.252308 0.776524 0.143035
+-0.15884 0.747286 0.125141
+
+-0.241228 0.742423 0.163737
+-0.15884 0.747286 0.125141
+-0.252308 0.776524 0.143035
+
+-0.15884 0.747286 0.125141
+-0.241228 0.742423 0.163737
+-0.152538 0.717634 0.134216
+
+-0.228971 0.7047 0.175612
+-0.152538 0.717634 0.134216
+-0.241228 0.742423 0.163737
+
+-0.152538 0.717634 0.134216
+-0.228971 0.7047 0.175612
+-0.14597 0.686734 0.136056
+
+-0.216198 0.665389 0.178019
+-0.14597 0.686734 0.136056
+-0.228971 0.7047 0.175612
+
+-0.14597 0.686734 0.136056
+-0.216198 0.665389 0.178019
+-0.139491 0.656251 0.130561
+
+-0.203598 0.62661 0.170829
+-0.139491 0.656251 0.130561
+-0.216198 0.665389 0.178019
+
+-0.139491 0.656251 0.130561
+-0.203598 0.62661 0.170829
+-0.133449 0.627831 0.118028
+
+-0.19185 0.590454 0.15443
+-0.133449 0.627831 0.118028
+-0.203598 0.62661 0.170829
+
+-0.133449 0.627831 0.118028
+-0.19185 0.590454 0.15443
+-0.128172 0.603003 0.0991314
+
+-0.181587 0.558868 0.129706
+-0.128172 0.603003 0.0991314
+-0.19185 0.590454 0.15443
+
+-0.128172 0.603003 0.0991314
+-0.181587 0.558868 0.129706
+-0.123943 0.583107 0.0748908
+
+-0.173363 0.533557 0.0979889
+-0.123943 0.583107 0.0748908
+-0.181587 0.558868 0.129706
+
+-0.123943 0.583107 0.0748908
+-0.173363 0.533557 0.0979889
+-0.120991 0.569216 0.0466128
+
+-0.167621 0.515885 0.0609893
+-0.120991 0.569216 0.0466128
+-0.173363 0.533557 0.0979889
+
+-0.120991 0.569216 0.0466128
+-0.167621 0.515885 0.0609893
+-0.119473 0.562078 0.0158219
+
+-0.164671 0.506804 0.0207018
+-0.119473 0.562078 0.0158219
+-0.167621 0.515885 0.0609893
+
+-0.119473 0.562078 0.0158219
+-0.164671 0.506804 0.0207018
+-0.119473 0.562078 -0.0158219
+
+-0.164671 0.506804 -0.0207018
+-0.119473 0.562078 -0.0158219
+-0.164671 0.506804 0.0207018
+
+-0.119473 0.562078 -0.0158219
+-0.164671 0.506804 -0.0207018
+-0.120991 0.569216 -0.0466128
+
+-0.167621 0.515885 -0.0609893
+-0.120991 0.569216 -0.0466128
+-0.164671 0.506804 -0.0207018
+
+-0.120991 0.569216 -0.0466128
+-0.167621 0.515885 -0.0609893
+-0.123943 0.583107 -0.0748908
+
+-0.173363 0.533557 -0.0979889
+-0.123943 0.583107 -0.0748908
+-0.167621 0.515885 -0.0609893
+
+-0.123943 0.583107 -0.0748908
+-0.173363 0.533557 -0.0979889
+-0.128172 0.603003 -0.0991314
+
+-0.181587 0.558868 -0.129706
+-0.128172 0.603003 -0.0991314
+-0.173363 0.533557 -0.0979889
+
+-0.128172 0.603003 -0.0991314
+-0.181587 0.558868 -0.129706
+-0.133449 0.627831 -0.118028
+
+-0.19185 0.590454 -0.15443
+-0.133449 0.627831 -0.118028
+-0.181587 0.558868 -0.129706
+
+-0.133449 0.627831 -0.118028
+-0.19185 0.590454 -0.15443
+-0.139491 0.656251 -0.130561
+
+-0.203598 0.62661 -0.170829
+-0.139491 0.656251 -0.130561
+-0.19185 0.590454 -0.15443
+
+-0.139491 0.656251 -0.130561
+-0.203598 0.62661 -0.170829
+-0.14597 0.686734 -0.136056
+
+-0.216198 0.665389 -0.178019
+-0.14597 0.686734 -0.136056
+-0.203598 0.62661 -0.170829
+
+-0.14597 0.686734 -0.136056
+-0.216198 0.665389 -0.178019
+-0.152538 0.717634 -0.134216
+
+-0.228971 0.7047 -0.175612
+-0.152538 0.717634 -0.134216
+-0.216198 0.665389 -0.178019
+
+-0.152538 0.717634 -0.134216
+-0.228971 0.7047 -0.175612
+-0.15884 0.747286 -0.125141
+
+-0.241228 0.742423 -0.163737
+-0.15884 0.747286 -0.125141
+-0.228971 0.7047 -0.175612
+
+-0.15884 0.747286 -0.125141
+-0.241228 0.742423 -0.163737
+-0.164538 0.774091 -0.109319
+
+-0.252308 0.776524 -0.143035
+-0.164538 0.774091 -0.109319
+-0.241228 0.742423 -0.163737
+
+-0.164538 0.774091 -0.109319
+-0.252308 0.776524 -0.143035
+-0.169324 0.796605 -0.0876034
+
+-0.261614 0.805166 -0.114622
+-0.169324 0.796605 -0.0876034
+-0.252308 0.776524 -0.143035
+
+-0.169324 0.796605 -0.0876034
+-0.261614 0.805166 -0.114622
+-0.172939 0.813614 -0.0611654
+
+-0.268645 0.826804 -0.0800302
+-0.172939 0.813614 -0.0611654
+-0.261614 0.805166 -0.114622
+
+-0.172939 0.813614 -0.0611654
+-0.268645 0.826804 -0.0800302
+-0.175189 0.8242 -0.0314299
+
+-0.273021 0.840272 -0.0411236
+-0.175189 0.8242 -0.0314299
+-0.268645 0.826804 -0.0800302
+
+-0.175189 0.8242 -0.0314299
+-0.273021 0.840272 -0.0411236
+-0.175953 0.827793 0
+
+-0.274506 0.844843 0
+-0.175953 0.827793 0
+-0.273021 0.840272 -0.0411236
+
+-0.274506 0.844843 0
+-0.382856 0.859908 0
+-0.273021 0.840272 0.0411236
+
+-0.38032 0.854213 0.0533384
+-0.273021 0.840272 0.0411236
+-0.382856 0.859908 0
+
+-0.273021 0.840272 0.0411236
+-0.38032 0.854213 0.0533384
+-0.268645 0.826804 0.0800302
+
+-0.37285 0.837434 0.103801
+-0.268645 0.826804 0.0800302
+-0.38032 0.854213 0.0533384
+
+-0.268645 0.826804 0.0800302
+-0.37285 0.837434 0.103801
+-0.261614 0.805166 0.114622
+
+-0.360847 0.810476 0.148668
+-0.261614 0.805166 0.114622
+-0.37285 0.837434 0.103801
+
+-0.261614 0.805166 0.114622
+-0.360847 0.810476 0.148668
+-0.252308 0.776524 0.143035
+
+-0.344959 0.774791 0.18552
+-0.252308 0.776524 0.143035
+-0.360847 0.810476 0.148668
+
+-0.252308 0.776524 0.143035
+-0.344959 0.774791 0.18552
+-0.241228 0.742423 0.163737
+
+-0.326043 0.732305 0.212371
+-0.241228 0.742423 0.163737
+-0.344959 0.774791 0.18552
+
+-0.241228 0.742423 0.163737
+-0.326043 0.732305 0.212371
+-0.228971 0.7047 0.175612
+
+-0.305119 0.685308 0.227773
+-0.228971 0.7047 0.175612
+-0.326043 0.732305 0.212371
+
+-0.228971 0.7047 0.175612
+-0.305119 0.685308 0.227773
+-0.216198 0.665389 0.178019
+
+-0.283313 0.636332 0.230895
+-0.216198 0.665389 0.178019
+-0.305119 0.685308 0.227773
+
+-0.216198 0.665389 0.178019
+-0.283313 0.636332 0.230895
+-0.203598 0.62661 0.170829
+
+-0.261803 0.588018 0.22157
+-0.203598 0.62661 0.170829
+-0.283313 0.636332 0.230895
+
+-0.203598 0.62661 0.170829
+-0.261803 0.588018 0.22157
+-0.19185 0.590454 0.15443
+
+-0.241747 0.542972 0.2003
+-0.19185 0.590454 0.15443
+-0.261803 0.588018 0.22157
+
+-0.19185 0.590454 0.15443
+-0.241747 0.542972 0.2003
+-0.181587 0.558868 0.129706
+
+-0.224226 0.503621 0.168232
+-0.181587 0.558868 0.129706
+-0.241747 0.542972 0.2003
+
+-0.181587 0.558868 0.129706
+-0.224226 0.503621 0.168232
+-0.173363 0.533557 0.0979889
+
+-0.210186 0.472086 0.127094
+-0.173363 0.533557 0.0979889
+-0.224226 0.503621 0.168232
+
+-0.173363 0.533557 0.0979889
+-0.210186 0.472086 0.127094
+-0.167621 0.515885 0.0609893
+
+-0.200383 0.450069 0.0791047
+-0.167621 0.515885 0.0609893
+-0.210186 0.472086 0.127094
+
+-0.167621 0.515885 0.0609893
+-0.200383 0.450069 0.0791047
+-0.164671 0.506804 0.0207018
+
+-0.195346 0.438755 0.0268508
+-0.164671 0.506804 0.0207018
+-0.200383 0.450069 0.0791047
+
+-0.164671 0.506804 0.0207018
+-0.195346 0.438755 0.0268508
+-0.164671 0.506804 -0.0207018
+
+-0.195346 0.438755 -0.0268508
+-0.164671 0.506804 -0.0207018
+-0.195346 0.438755 0.0268508
+
+-0.164671 0.506804 -0.0207018
+-0.195346 0.438755 -0.0268508
+-0.167621 0.515885 -0.0609893
+
+-0.200383 0.450069 -0.0791047
+-0.167621 0.515885 -0.0609893
+-0.195346 0.438755 -0.0268508
+
+-0.167621 0.515885 -0.0609893
+-0.200383 0.450069 -0.0791047
+-0.173363 0.533557 -0.0979889
+
+-0.210186 0.472086 -0.127094
+-0.173363 0.533557 -0.0979889
+-0.200383 0.450069 -0.0791047
+
+-0.173363 0.533557 -0.0979889
+-0.210186 0.472086 -0.127094
+-0.181587 0.558868 -0.129706
+
+-0.224226 0.503621 -0.168232
+-0.181587 0.558868 -0.129706
+-0.210186 0.472086 -0.127094
+
+-0.181587 0.558868 -0.129706
+-0.224226 0.503621 -0.168232
+-0.19185 0.590454 -0.15443
+
+-0.241747 0.542972 -0.2003
+-0.19185 0.590454 -0.15443
+-0.224226 0.503621 -0.168232
+
+-0.19185 0.590454 -0.15443
+-0.241747 0.542972 -0.2003
+-0.203598 0.62661 -0.170829
+
+-0.261803 0.588018 -0.22157
+-0.203598 0.62661 -0.170829
+-0.241747 0.542972 -0.2003
+
+-0.203598 0.62661 -0.170829
+-0.261803 0.588018 -0.22157
+-0.216198 0.665389 -0.178019
+
+-0.283313 0.636332 -0.230895
+-0.216198 0.665389 -0.178019
+-0.261803 0.588018 -0.22157
+
+-0.216198 0.665389 -0.178019
+-0.283313 0.636332 -0.230895
+-0.228971 0.7047 -0.175612
+
+-0.305119 0.685308 -0.227773
+-0.228971 0.7047 -0.175612
+-0.283313 0.636332 -0.230895
+
+-0.228971 0.7047 -0.175612
+-0.305119 0.685308 -0.227773
+-0.241228 0.742423 -0.163737
+
+-0.326043 0.732305 -0.212371
+-0.241228 0.742423 -0.163737
+-0.305119 0.685308 -0.227773
+
+-0.241228 0.742423 -0.163737
+-0.326043 0.732305 -0.212371
+-0.252308 0.776524 -0.143035
+
+-0.344959 0.774791 -0.18552
+-0.252308 0.776524 -0.143035
+-0.326043 0.732305 -0.212371
+
+-0.252308 0.776524 -0.143035
+-0.344959 0.774791 -0.18552
+-0.261614 0.805166 -0.114622
+
+-0.360847 0.810476 -0.148668
+-0.261614 0.805166 -0.114622
+-0.344959 0.774791 -0.18552
+
+-0.261614 0.805166 -0.114622
+-0.360847 0.810476 -0.148668
+-0.268645 0.826804 -0.0800302
+
+-0.37285 0.837434 -0.103801
+-0.268645 0.826804 -0.0800302
+-0.360847 0.810476 -0.148668
+
+-0.268645 0.826804 -0.0800302
+-0.37285 0.837434 -0.103801
+-0.273021 0.840272 -0.0411236
+
+-0.38032 0.854213 -0.0533384
+-0.273021 0.840272 -0.0411236
+-0.37285 0.837434 -0.103801
+
+-0.273021 0.840272 -0.0411236
+-0.38032 0.854213 -0.0533384
+-0.274506 0.844843 0
+
+-0.382856 0.859908 0
+-0.274506 0.844843 0
+-0.38032 0.854213 -0.0533384
+
+-0.382856 0.859908 0
+-0.5 0.866025 0
+-0.38032 0.854213 0.0533384
+
+-0.496092 0.859256 0.0668786
+-0.38032 0.854213 0.0533384
+-0.5 0.866025 0
+
+-0.38032 0.854213 0.0533384
+-0.496092 0.859256 0.0668786
+-0.37285 0.837434 0.103801
+
+-0.484577 0.839312 0.130152
+-0.37285 0.837434 0.103801
+-0.496092 0.859256 0.0668786
+
+-0.37285 0.837434 0.103801
+-0.484577 0.839312 0.130152
+-0.360847 0.810476 0.148668
+
+-0.466076 0.807268 0.186408
+-0.360847 0.810476 0.148668
+-0.484577 0.839312 0.130152
+
+-0.360847 0.810476 0.148668
+-0.466076 0.807268 0.186408
+-0.344959 0.774791 0.18552
+
+-0.441588 0.764853 0.232616
+-0.344959 0.774791 0.18552
+-0.466076 0.807268 0.186408
+
+-0.344959 0.774791 0.18552
+-0.441588 0.764853 0.232616
+-0.326043 0.732305 0.212371
+
+-0.412432 0.714352 0.266283
+-0.326043 0.732305 0.212371
+-0.441588 0.764853 0.232616
+
+-0.326043 0.732305 0.212371
+-0.412432 0.714352 0.266283
+-0.305119 0.685308 0.227773
+
+-0.380179 0.658489 0.285594
+-0.305119 0.685308 0.227773
+-0.412432 0.714352 0.266283
+
+-0.305119 0.685308 0.227773
+-0.380179 0.658489 0.285594
+-0.283313 0.636332 0.230895
+
+-0.346569 0.600275 0.289509
+-0.283313 0.636332 0.230895
+-0.380179 0.658489 0.285594
+
+-0.283313 0.636332 0.230895
+-0.346569 0.600275 0.289509
+-0.261803 0.588018 0.22157
+
+-0.313414 0.542848 0.277817
+-0.261803 0.588018 0.22157
+-0.346569 0.600275 0.289509
+
+-0.261803 0.588018 0.22157
+-0.313414 0.542848 0.277817
+-0.241747 0.542972 0.2003
+
+-0.2825 0.489304 0.251147
+-0.241747 0.542972 0.2003
+-0.313414 0.542848 0.277817
+
+-0.241747 0.542972 0.2003
+-0.2825 0.489304 0.251147
+-0.224226 0.503621 0.168232
+
+-0.255495 0.44253 0.210938
+-0.224226 0.503621 0.168232
+-0.2825 0.489304 0.251147
+
+-0.224226 0.503621 0.168232
+-0.255495 0.44253 0.210938
+-0.210186 0.472086 0.127094
+
+-0.233854 0.405047 0.159358
+-0.210186 0.472086 0.127094
+-0.255495 0.44253 0.210938
+
+-0.210186 0.472086 0.127094
+-0.233854 0.405047 0.159358
+-0.200383 0.450069 0.0791047
+
+-0.218745 0.378877 0.0991858
+-0.200383 0.450069 0.0791047
+-0.233854 0.405047 0.159358
+
+-0.200383 0.450069 0.0791047
+-0.218745 0.378877 0.0991858
+-0.195346 0.438755 0.0268508
+
+-0.21098 0.365429 0.0336669
+-0.195346 0.438755 0.0268508
+-0.218745 0.378877 0.0991858
+
+-0.195346 0.438755 0.0268508
+-0.21098 0.365429 0.0336669
+-0.195346 0.438755 -0.0268508
+
+-0.21098 0.365429 -0.0336669
+-0.195346 0.438755 -0.0268508
+-0.21098 0.365429 0.0336669
+
+-0.195346 0.438755 -0.0268508
+-0.21098 0.365429 -0.0336669
+-0.200383 0.450069 -0.0791047
+
+-0.218745 0.378877 -0.0991858
+-0.200383 0.450069 -0.0791047
+-0.21098 0.365429 -0.0336669
+
+-0.200383 0.450069 -0.0791047
+-0.218745 0.378877 -0.0991858
+-0.210186 0.472086 -0.127094
+
+-0.233854 0.405047 -0.159358
+-0.210186 0.472086 -0.127094
+-0.218745 0.378877 -0.0991858
+
+-0.210186 0.472086 -0.127094
+-0.233854 0.405047 -0.159358
+-0.224226 0.503621 -0.168232
+
+-0.255495 0.44253 -0.210938
+-0.224226 0.503621 -0.168232
+-0.233854 0.405047 -0.159358
+
+-0.224226 0.503621 -0.168232
+-0.255495 0.44253 -0.210938
+-0.241747 0.542972 -0.2003
+
+-0.2825 0.489304 -0.251147
+-0.241747 0.542972 -0.2003
+-0.255495 0.44253 -0.210938
+
+-0.241747 0.542972 -0.2003
+-0.2825 0.489304 -0.251147
+-0.261803 0.588018 -0.22157
+
+-0.313414 0.542848 -0.277817
+-0.261803 0.588018 -0.22157
+-0.2825 0.489304 -0.251147
+
+-0.261803 0.588018 -0.22157
+-0.313414 0.542848 -0.277817
+-0.283313 0.636332 -0.230895
+
+-0.346569 0.600275 -0.289509
+-0.283313 0.636332 -0.230895
+-0.313414 0.542848 -0.277817
+
+-0.283313 0.636332 -0.230895
+-0.346569 0.600275 -0.289509
+-0.305119 0.685308 -0.227773
+
+-0.380179 0.658489 -0.285594
+-0.305119 0.685308 -0.227773
+-0.346569 0.600275 -0.289509
+
+-0.305119 0.685308 -0.227773
+-0.380179 0.658489 -0.285594
+-0.326043 0.732305 -0.212371
+
+-0.412432 0.714352 -0.266283
+-0.326043 0.732305 -0.212371
+-0.380179 0.658489 -0.285594
+
+-0.326043 0.732305 -0.212371
+-0.412432 0.714352 -0.266283
+-0.344959 0.774791 -0.18552
+
+-0.441588 0.764853 -0.232616
+-0.344959 0.774791 -0.18552
+-0.412432 0.714352 -0.266283
+
+-0.344959 0.774791 -0.18552
+-0.441588 0.764853 -0.232616
+-0.360847 0.810476 -0.148668
+
+-0.466076 0.807268 -0.186408
+-0.360847 0.810476 -0.148668
+-0.441588 0.764853 -0.232616
+
+-0.360847 0.810476 -0.148668
+-0.466076 0.807268 -0.186408
+-0.37285 0.837434 -0.103801
+
+-0.484577 0.839312 -0.130152
+-0.37285 0.837434 -0.103801
+-0.466076 0.807268 -0.186408
+
+-0.37285 0.837434 -0.103801
+-0.484577 0.839312 -0.130152
+-0.38032 0.854213 -0.0533384
+
+-0.496092 0.859256 -0.0668786
+-0.38032 0.854213 -0.0533384
+-0.484577 0.839312 -0.130152
+
+-0.38032 0.854213 -0.0533384
+-0.496092 0.859256 -0.0668786
+-0.382856 0.859908 0
+
+-0.5 0.866025 0
+-0.382856 0.859908 0
+-0.496092 0.859256 -0.0668786
+
+-0.5 0.866025 0
+-0.622296 0.856517 0
+-0.496092 0.859256 0.0668786
+
+-0.616771 0.848913 0.0804188
+-0.496092 0.859256 0.0668786
+-0.622296 0.856517 0
+
+-0.496092 0.859256 0.0668786
+-0.616771 0.848913 0.0804188
+-0.484577 0.839312 0.130152
+
+-0.600494 0.826509 0.156502
+-0.484577 0.839312 0.130152
+-0.616771 0.848913 0.0804188
+
+-0.484577 0.839312 0.130152
+-0.600494 0.826509 0.156502
+-0.466076 0.807268 0.186408
+
+-0.574343 0.790515 0.224149
+-0.466076 0.807268 0.186408
+-0.600494 0.826509 0.156502
+
+-0.466076 0.807268 0.186408
+-0.574343 0.790515 0.224149
+-0.441588 0.764853 0.232616
+
+-0.539726 0.742869 0.279711
+-0.441588 0.764853 0.232616
+-0.574343 0.790515 0.224149
+
+-0.441588 0.764853 0.232616
+-0.539726 0.742869 0.279711
+-0.412432 0.714352 0.266283
+
+-0.498511 0.686142 0.320194
+-0.412432 0.714352 0.266283
+-0.539726 0.742869 0.279711
+
+-0.412432 0.714352 0.266283
+-0.498511 0.686142 0.320194
+-0.380179 0.658489 0.285594
+
+-0.45292 0.623391 0.343415
+-0.380179 0.658489 0.285594
+-0.498511 0.686142 0.320194
+
+-0.380179 0.658489 0.285594
+-0.45292 0.623391 0.343415
+-0.346569 0.600275 0.289509
+
+-0.40541 0.557999 0.348123
+-0.346569 0.600275 0.289509
+-0.45292 0.623391 0.343415
+
+-0.346569 0.600275 0.289509
+-0.40541 0.557999 0.348123
+-0.313414 0.542848 0.277817
+
+-0.358542 0.493491 0.334064
+-0.313414 0.542848 0.277817
+-0.40541 0.557999 0.348123
+
+-0.313414 0.542848 0.277817
+-0.358542 0.493491 0.334064
+-0.2825 0.489304 0.251147
+
+-0.314843 0.433345 0.301995
+-0.2825 0.489304 0.251147
+-0.358542 0.493491 0.334064
+
+-0.2825 0.489304 0.251147
+-0.314843 0.433345 0.301995
+-0.255495 0.44253 0.210938
+
+-0.27667 0.380803 0.253645
+-0.255495 0.44253 0.210938
+-0.314843 0.433345 0.301995
+
+-0.255495 0.44253 0.210938
+-0.27667 0.380803 0.253645
+-0.233854 0.405047 0.159358
+
+-0.246079 0.338698 0.191621
+-0.233854 0.405047 0.159358
+-0.27667 0.380803 0.253645
+
+-0.233854 0.405047 0.159358
+-0.246079 0.338698 0.191621
+-0.218745 0.378877 0.0991858
+
+-0.22472 0.309301 0.119267
+-0.218745 0.378877 0.0991858
+-0.246079 0.338698 0.191621
+
+-0.218745 0.378877 0.0991858
+-0.22472 0.309301 0.119267
+-0.21098 0.365429 0.0336669
+
+-0.213745 0.294195 0.0404831
+-0.21098 0.365429 0.0336669
+-0.22472 0.309301 0.119267
+
+-0.21098 0.365429 0.0336669
+-0.213745 0.294195 0.0404831
+-0.21098 0.365429 -0.0336669
+
+-0.213745 0.294195 -0.0404831
+-0.21098 0.365429 -0.0336669
+-0.213745 0.294195 0.0404831
+
+-0.21098 0.365429 -0.0336669
+-0.213745 0.294195 -0.0404831
+-0.218745 0.378877 -0.0991858
+
+-0.22472 0.309301 -0.119267
+-0.218745 0.378877 -0.0991858
+-0.213745 0.294195 -0.0404831
+
+-0.218745 0.378877 -0.0991858
+-0.22472 0.309301 -0.119267
+-0.233854 0.405047 -0.159358
+
+-0.246079 0.338698 -0.191621
+-0.233854 0.405047 -0.159358
+-0.22472 0.309301 -0.119267
+
+-0.233854 0.405047 -0.159358
+-0.246079 0.338698 -0.191621
+-0.255495 0.44253 -0.210938
+
+-0.27667 0.380803 -0.253645
+-0.255495 0.44253 -0.210938
+-0.246079 0.338698 -0.191621
+
+-0.255495 0.44253 -0.210938
+-0.27667 0.380803 -0.253645
+-0.2825 0.489304 -0.251147
+
+-0.314843 0.433345 -0.301995
+-0.2825 0.489304 -0.251147
+-0.27667 0.380803 -0.253645
+
+-0.2825 0.489304 -0.251147
+-0.314843 0.433345 -0.301995
+-0.313414 0.542848 -0.277817
+
+-0.358542 0.493491 -0.334064
+-0.313414 0.542848 -0.277817
+-0.314843 0.433345 -0.301995
+
+-0.313414 0.542848 -0.277817
+-0.358542 0.493491 -0.334064
+-0.346569 0.600275 -0.289509
+
+-0.40541 0.557999 -0.348123
+-0.346569 0.600275 -0.289509
+-0.358542 0.493491 -0.334064
+
+-0.346569 0.600275 -0.289509
+-0.40541 0.557999 -0.348123
+-0.380179 0.658489 -0.285594
+
+-0.45292 0.623391 -0.343415
+-0.380179 0.658489 -0.285594
+-0.40541 0.557999 -0.348123
+
+-0.380179 0.658489 -0.285594
+-0.45292 0.623391 -0.343415
+-0.412432 0.714352 -0.266283
+
+-0.498511 0.686142 -0.320194
+-0.412432 0.714352 -0.266283
+-0.45292 0.623391 -0.343415
+
+-0.412432 0.714352 -0.266283
+-0.498511 0.686142 -0.320194
+-0.441588 0.764853 -0.232616
+
+-0.539726 0.742869 -0.279711
+-0.441588 0.764853 -0.232616
+-0.498511 0.686142 -0.320194
+
+-0.441588 0.764853 -0.232616
+-0.539726 0.742869 -0.279711
+-0.466076 0.807268 -0.186408
+
+-0.574343 0.790515 -0.224149
+-0.466076 0.807268 -0.186408
+-0.539726 0.742869 -0.279711
+
+-0.466076 0.807268 -0.186408
+-0.574343 0.790515 -0.224149
+-0.484577 0.839312 -0.130152
+
+-0.600494 0.826509 -0.156502
+-0.484577 0.839312 -0.130152
+-0.574343 0.790515 -0.224149
+
+-0.484577 0.839312 -0.130152
+-0.600494 0.826509 -0.156502
+-0.496092 0.859256 -0.0668786
+
+-0.616771 0.848913 -0.0804188
+-0.496092 0.859256 -0.0668786
+-0.600494 0.826509 -0.156502
+
+-0.496092 0.859256 -0.0668786
+-0.616771 0.848913 -0.0804188
+-0.5 0.866025 0
+
+-0.622296 0.856517 0
+-0.5 0.866025 0
+-0.616771 0.848913 -0.0804188
+
+-0.622296 0.856517 0
+-0.743859 0.826139 0
+-0.616771 0.848913 0.0804188
+
+-0.736614 0.818092 0.0926336
+-0.616771 0.848913 0.0804188
+-0.743859 0.826139 0
+
+-0.616771 0.848913 0.0804188
+-0.736614 0.818092 0.0926336
+-0.600494 0.826509 0.156502
+
+-0.71527 0.794387 0.180273
+-0.600494 0.826509 0.156502
+-0.736614 0.818092 0.0926336
+
+-0.600494 0.826509 0.156502
+-0.71527 0.794387 0.180273
+-0.574343 0.790515 0.224149
+
+-0.680977 0.756302 0.258194
+-0.574343 0.790515 0.224149
+-0.71527 0.794387 0.180273
+
+-0.574343 0.790515 0.224149
+-0.680977 0.756302 0.258194
+-0.539726 0.742869 0.279711
+
+-0.635585 0.705888 0.322196
+-0.539726 0.742869 0.279711
+-0.680977 0.756302 0.258194
+
+-0.539726 0.742869 0.279711
+-0.635585 0.705888 0.322196
+-0.498511 0.686142 0.320194
+
+-0.581539 0.645865 0.368828
+-0.498511 0.686142 0.320194
+-0.635585 0.705888 0.322196
+
+-0.498511 0.686142 0.320194
+-0.581539 0.645865 0.368828
+-0.45292 0.623391 0.343415
+
+-0.521755 0.579468 0.395577
+-0.45292 0.623391 0.343415
+-0.581539 0.645865 0.368828
+
+-0.45292 0.623391 0.343415
+-0.521755 0.579468 0.395577
+-0.40541 0.557999 0.348123
+
+-0.459455 0.510276 0.401
+-0.40541 0.557999 0.348123
+-0.521755 0.579468 0.395577
+
+-0.40541 0.557999 0.348123
+-0.459455 0.510276 0.401
+-0.358542 0.493491 0.334064
+
+-0.397997 0.44202 0.384804
+-0.358542 0.493491 0.334064
+-0.459455 0.510276 0.401
+
+-0.358542 0.493491 0.334064
+-0.397997 0.44202 0.384804
+-0.314843 0.433345 0.301995
+
+-0.340695 0.37838 0.347864
+-0.314843 0.433345 0.301995
+-0.397997 0.44202 0.384804
+
+-0.314843 0.433345 0.301995
+-0.340695 0.37838 0.347864
+-0.27667 0.380803 0.253645
+
+-0.290638 0.322786 0.292171
+-0.27667 0.380803 0.253645
+-0.340695 0.37838 0.347864
+
+-0.27667 0.380803 0.253645
+-0.290638 0.322786 0.292171
+-0.246079 0.338698 0.191621
+
+-0.250524 0.278235 0.220726
+-0.246079 0.338698 0.191621
+-0.290638 0.322786 0.292171
+
+-0.246079 0.338698 0.191621
+-0.250524 0.278235 0.220726
+-0.22472 0.309301 0.119267
+
+-0.222516 0.247129 0.137382
+-0.22472 0.309301 0.119267
+-0.250524 0.278235 0.220726
+
+-0.22472 0.309301 0.119267
+-0.222516 0.247129 0.137382
+-0.213745 0.294195 0.0404831
+
+-0.208124 0.231145 0.0466321
+-0.213745 0.294195 0.0404831
+-0.222516 0.247129 0.137382
+
+-0.213745 0.294195 0.0404831
+-0.208124 0.231145 0.0466321
+-0.213745 0.294195 -0.0404831
+
+-0.208124 0.231145 -0.0466321
+-0.213745 0.294195 -0.0404831
+-0.208124 0.231145 0.0466321
+
+-0.213745 0.294195 -0.0404831
+-0.208124 0.231145 -0.0466321
+-0.22472 0.309301 -0.119267
+
+-0.222516 0.247129 -0.137382
+-0.22472 0.309301 -0.119267
+-0.208124 0.231145 -0.0466321
+
+-0.22472 0.309301 -0.119267
+-0.222516 0.247129 -0.137382
+-0.246079 0.338698 -0.191621
+
+-0.250524 0.278235 -0.220726
+-0.246079 0.338698 -0.191621
+-0.222516 0.247129 -0.137382
+
+-0.246079 0.338698 -0.191621
+-0.250524 0.278235 -0.220726
+-0.27667 0.380803 -0.253645
+
+-0.290638 0.322786 -0.292171
+-0.27667 0.380803 -0.253645
+-0.250524 0.278235 -0.220726
+
+-0.27667 0.380803 -0.253645
+-0.290638 0.322786 -0.292171
+-0.314843 0.433345 -0.301995
+
+-0.340695 0.37838 -0.347864
+-0.314843 0.433345 -0.301995
+-0.290638 0.322786 -0.292171
+
+-0.314843 0.433345 -0.301995
+-0.340695 0.37838 -0.347864
+-0.358542 0.493491 -0.334064
+
+-0.397997 0.44202 -0.384804
+-0.358542 0.493491 -0.334064
+-0.340695 0.37838 -0.347864
+
+-0.358542 0.493491 -0.334064
+-0.397997 0.44202 -0.384804
+-0.40541 0.557999 -0.348123
+
+-0.459455 0.510276 -0.401
+-0.40541 0.557999 -0.348123
+-0.397997 0.44202 -0.384804
+
+-0.40541 0.557999 -0.348123
+-0.459455 0.510276 -0.401
+-0.45292 0.623391 -0.343415
+
+-0.521755 0.579468 -0.395577
+-0.45292 0.623391 -0.343415
+-0.459455 0.510276 -0.401
+
+-0.45292 0.623391 -0.343415
+-0.521755 0.579468 -0.395577
+-0.498511 0.686142 -0.320194
+
+-0.581539 0.645865 -0.368828
+-0.498511 0.686142 -0.320194
+-0.521755 0.579468 -0.395577
+
+-0.498511 0.686142 -0.320194
+-0.581539 0.645865 -0.368828
+-0.539726 0.742869 -0.279711
+
+-0.635585 0.705888 -0.322196
+-0.539726 0.742869 -0.279711
+-0.581539 0.645865 -0.368828
+
+-0.539726 0.742869 -0.279711
+-0.635585 0.705888 -0.322196
+-0.574343 0.790515 -0.224149
+
+-0.680977 0.756302 -0.258194
+-0.574343 0.790515 -0.224149
+-0.635585 0.705888 -0.322196
+
+-0.574343 0.790515 -0.224149
+-0.680977 0.756302 -0.258194
+-0.600494 0.826509 -0.156502
+
+-0.71527 0.794387 -0.180273
+-0.600494 0.826509 -0.156502
+-0.680977 0.756302 -0.258194
+
+-0.600494 0.826509 -0.156502
+-0.71527 0.794387 -0.180273
+-0.616771 0.848913 -0.0804188
+
+-0.736614 0.818092 -0.0926336
+-0.616771 0.848913 -0.0804188
+-0.71527 0.794387 -0.180273
+
+-0.616771 0.848913 -0.0804188
+-0.736614 0.818092 -0.0926336
+-0.622296 0.856517 0
+
+-0.743859 0.826139 0
+-0.622296 0.856517 0
+-0.736614 0.818092 -0.0926336
+
+-0.743859 0.826139 0
+-0.857376 0.771985 0
+-0.736614 0.818092 0.0926336
+
+-0.848488 0.763982 0.102327
+-0.736614 0.818092 0.0926336
+-0.857376 0.771985 0
+
+-0.736614 0.818092 0.0926336
+-0.848488 0.763982 0.102327
+-0.71527 0.794387 0.180273
+
+-0.822302 0.740404 0.199138
+-0.71527 0.794387 0.180273
+-0.848488 0.763982 0.102327
+
+-0.71527 0.794387 0.180273
+-0.822302 0.740404 0.199138
+-0.680977 0.756302 0.258194
+
+-0.780231 0.702523 0.285213
+-0.680977 0.756302 0.258194
+-0.822302 0.740404 0.199138
+
+-0.680977 0.756302 0.258194
+-0.780231 0.702523 0.285213
+-0.635585 0.705888 0.322196
+
+-0.724542 0.65238 0.355913
+-0.635585 0.705888 0.322196
+-0.780231 0.702523 0.285213
+
+-0.635585 0.705888 0.322196
+-0.724542 0.65238 0.355913
+-0.581539 0.645865 0.368828
+
+-0.658237 0.59268 0.407425
+-0.581539 0.645865 0.368828
+-0.724542 0.65238 0.355913
+
+-0.581539 0.645865 0.368828
+-0.658237 0.59268 0.407425
+-0.521755 0.579468 0.395577
+
+-0.584892 0.526639 0.436972
+-0.521755 0.579468 0.395577
+-0.658237 0.59268 0.407425
+
+-0.521755 0.579468 0.395577
+-0.584892 0.526639 0.436972
+-0.459455 0.510276 0.401
+
+-0.50846 0.457819 0.442963
+-0.459455 0.510276 0.401
+-0.584892 0.526639 0.436972
+
+-0.459455 0.510276 0.401
+-0.50846 0.457819 0.442963
+-0.397997 0.44202 0.384804
+
+-0.433061 0.38993 0.425073
+-0.397997 0.44202 0.384804
+-0.50846 0.457819 0.442963
+
+-0.397997 0.44202 0.384804
+-0.433061 0.38993 0.425073
+-0.340695 0.37838 0.347864
+
+-0.362761 0.326632 0.384267
+-0.340695 0.37838 0.347864
+-0.433061 0.38993 0.425073
+
+-0.340695 0.37838 0.347864
+-0.362761 0.326632 0.384267
+-0.290638 0.322786 0.292171
+
+-0.301349 0.271336 0.322745
+-0.290638 0.322786 0.292171
+-0.362761 0.326632 0.384267
+
+-0.290638 0.322786 0.292171
+-0.301349 0.271336 0.322745
+-0.250524 0.278235 0.220726
+
+-0.252136 0.227025 0.243824
+-0.250524 0.278235 0.220726
+-0.301349 0.271336 0.322745
+
+-0.250524 0.278235 0.220726
+-0.252136 0.227025 0.243824
+-0.222516 0.247129 0.137382
+
+-0.217776 0.196086 0.151759
+-0.222516 0.247129 0.137382
+-0.252136 0.227025 0.243824
+
+-0.222516 0.247129 0.137382
+-0.217776 0.196086 0.151759
+-0.208124 0.231145 0.0466321
+
+-0.200119 0.180188 0.051512
+-0.208124 0.231145 0.0466321
+-0.217776 0.196086 0.151759
+
+-0.208124 0.231145 0.0466321
+-0.200119 0.180188 0.051512
+-0.208124 0.231145 -0.0466321
+
+-0.200119 0.180188 -0.051512
+-0.208124 0.231145 -0.0466321
+-0.200119 0.180188 0.051512
+
+-0.208124 0.231145 -0.0466321
+-0.200119 0.180188 -0.051512
+-0.222516 0.247129 -0.137382
+
+-0.217776 0.196086 -0.151759
+-0.222516 0.247129 -0.137382
+-0.200119 0.180188 -0.051512
+
+-0.222516 0.247129 -0.137382
+-0.217776 0.196086 -0.151759
+-0.250524 0.278235 -0.220726
+
+-0.252136 0.227025 -0.243824
+-0.250524 0.278235 -0.220726
+-0.217776 0.196086 -0.151759
+
+-0.250524 0.278235 -0.220726
+-0.252136 0.227025 -0.243824
+-0.290638 0.322786 -0.292171
+
+-0.301349 0.271336 -0.322745
+-0.290638 0.322786 -0.292171
+-0.252136 0.227025 -0.243824
+
+-0.290638 0.322786 -0.292171
+-0.301349 0.271336 -0.322745
+-0.340695 0.37838 -0.347864
+
+-0.362761 0.326632 -0.384267
+-0.340695 0.37838 -0.347864
+-0.301349 0.271336 -0.322745
+
+-0.340695 0.37838 -0.347864
+-0.362761 0.326632 -0.384267
+-0.397997 0.44202 -0.384804
+
+-0.433061 0.38993 -0.425073
+-0.397997 0.44202 -0.384804
+-0.362761 0.326632 -0.384267
+
+-0.397997 0.44202 -0.384804
+-0.433061 0.38993 -0.425073
+-0.459455 0.510276 -0.401
+
+-0.50846 0.457819 -0.442963
+-0.459455 0.510276 -0.401
+-0.433061 0.38993 -0.425073
+
+-0.459455 0.510276 -0.401
+-0.50846 0.457819 -0.442963
+-0.521755 0.579468 -0.395577
+
+-0.584892 0.526639 -0.436972
+-0.521755 0.579468 -0.395577
+-0.50846 0.457819 -0.442963
+
+-0.521755 0.579468 -0.395577
+-0.584892 0.526639 -0.436972
+-0.581539 0.645865 -0.368828
+
+-0.658237 0.59268 -0.407425
+-0.581539 0.645865 -0.368828
+-0.584892 0.526639 -0.436972
+
+-0.581539 0.645865 -0.368828
+-0.658237 0.59268 -0.407425
+-0.635585 0.705888 -0.322196
+
+-0.724542 0.65238 -0.355913
+-0.635585 0.705888 -0.322196
+-0.658237 0.59268 -0.407425
+
+-0.635585 0.705888 -0.322196
+-0.724542 0.65238 -0.355913
+-0.680977 0.756302 -0.258194
+
+-0.780231 0.702523 -0.285213
+-0.680977 0.756302 -0.258194
+-0.724542 0.65238 -0.355913
+
+-0.680977 0.756302 -0.258194
+-0.780231 0.702523 -0.285213
+-0.71527 0.794387 -0.180273
+
+-0.822302 0.740404 -0.199138
+-0.71527 0.794387 -0.180273
+-0.780231 0.702523 -0.285213
+
+-0.71527 0.794387 -0.180273
+-0.822302 0.740404 -0.199138
+-0.736614 0.818092 -0.0926336
+
+-0.848488 0.763982 -0.102327
+-0.736614 0.818092 -0.0926336
+-0.822302 0.740404 -0.199138
+
+-0.736614 0.818092 -0.0926336
+-0.848488 0.763982 -0.102327
+-0.743859 0.826139 0
+
+-0.857376 0.771985 0
+-0.743859 0.826139 0
+-0.848488 0.763982 -0.102327
+
+-0.857376 0.771985 0
+-0.955207 0.693998 0
+-0.848488 0.763982 0.102327
+
+-0.944942 0.686541 0.108551
+-0.848488 0.763982 0.102327
+-0.955207 0.693998 0
+
+-0.848488 0.763982 0.102327
+-0.944942 0.686541 0.108551
+-0.822302 0.740404 0.199138
+
+-0.914702 0.66457 0.21125
+-0.822302 0.740404 0.199138
+-0.944942 0.686541 0.108551
+
+-0.822302 0.740404 0.199138
+-0.914702 0.66457 0.21125
+-0.780231 0.702523 0.285213
+
+-0.866116 0.62927 0.302561
+-0.780231 0.702523 0.285213
+-0.914702 0.66457 0.21125
+
+-0.780231 0.702523 0.285213
+-0.866116 0.62927 0.302561
+-0.724542 0.65238 0.355913
+
+-0.801803 0.582544 0.37756
+-0.724542 0.65238 0.355913
+-0.866116 0.62927 0.302561
+
+-0.724542 0.65238 0.355913
+-0.801803 0.582544 0.37756
+-0.658237 0.59268 0.407425
+
+-0.725231 0.526911 0.432205
+-0.658237 0.59268 0.407425
+-0.801803 0.582544 0.37756
+
+-0.658237 0.59268 0.407425
+-0.725231 0.526911 0.432205
+-0.584892 0.526639 0.436972
+
+-0.640528 0.465371 0.46355
+-0.584892 0.526639 0.436972
+-0.725231 0.526911 0.432205
+
+-0.584892 0.526639 0.436972
+-0.640528 0.465371 0.46355
+-0.50846 0.457819 0.442963
+
+-0.55226 0.401241 0.469904
+-0.50846 0.457819 0.442963
+-0.640528 0.465371 0.46355
+
+-0.50846 0.457819 0.442963
+-0.55226 0.401241 0.469904
+-0.433061 0.38993 0.425073
+
+-0.465186 0.337977 0.450926
+-0.433061 0.38993 0.425073
+-0.55226 0.401241 0.469904
+
+-0.433061 0.38993 0.425073
+-0.465186 0.337977 0.450926
+-0.362761 0.326632 0.384267
+
+-0.384 0.278992 0.407639
+-0.362761 0.326632 0.384267
+-0.465186 0.337977 0.450926
+
+-0.362761 0.326632 0.384267
+-0.384 0.278992 0.407639
+-0.301349 0.271336 0.322745
+
+-0.313078 0.227464 0.342375
+-0.301349 0.271336 0.322745
+-0.384 0.278992 0.407639
+
+-0.301349 0.271336 0.322745
+-0.313078 0.227464 0.342375
+-0.252136 0.227025 0.243824
+
+-0.256244 0.186172 0.258654
+-0.252136 0.227025 0.243824
+-0.313078 0.227464 0.342375
+
+-0.252136 0.227025 0.243824
+-0.256244 0.186172 0.258654
+-0.217776 0.196086 0.151759
+
+-0.216563 0.157342 0.160989
+-0.217776 0.196086 0.151759
+-0.256244 0.186172 0.258654
+
+-0.217776 0.196086 0.151759
+-0.216563 0.157342 0.160989
+-0.200119 0.180188 0.051512
+
+-0.196172 0.142527 0.054645
+-0.200119 0.180188 0.051512
+-0.216563 0.157342 0.160989
+
+-0.200119 0.180188 0.051512
+-0.196172 0.142527 0.054645
+-0.200119 0.180188 -0.051512
+
+-0.196172 0.142527 -0.054645
+-0.200119 0.180188 -0.051512
+-0.196172 0.142527 0.054645
+
+-0.200119 0.180188 -0.051512
+-0.196172 0.142527 -0.054645
+-0.217776 0.196086 -0.151759
+
+-0.216563 0.157342 -0.160989
+-0.217776 0.196086 -0.151759
+-0.196172 0.142527 -0.054645
+
+-0.217776 0.196086 -0.151759
+-0.216563 0.157342 -0.160989
+-0.252136 0.227025 -0.243824
+
+-0.256244 0.186172 -0.258654
+-0.252136 0.227025 -0.243824
+-0.216563 0.157342 -0.160989
+
+-0.252136 0.227025 -0.243824
+-0.256244 0.186172 -0.258654
+-0.301349 0.271336 -0.322745
+
+-0.313078 0.227464 -0.342375
+-0.301349 0.271336 -0.322745
+-0.256244 0.186172 -0.258654
+
+-0.301349 0.271336 -0.322745
+-0.313078 0.227464 -0.342375
+-0.362761 0.326632 -0.384267
+
+-0.384 0.278992 -0.407639
+-0.362761 0.326632 -0.384267
+-0.313078 0.227464 -0.342375
+
+-0.362761 0.326632 -0.384267
+-0.384 0.278992 -0.407639
+-0.433061 0.38993 -0.425073
+
+-0.465186 0.337977 -0.450926
+-0.433061 0.38993 -0.425073
+-0.384 0.278992 -0.407639
+
+-0.433061 0.38993 -0.425073
+-0.465186 0.337977 -0.450926
+-0.50846 0.457819 -0.442963
+
+-0.55226 0.401241 -0.469904
+-0.50846 0.457819 -0.442963
+-0.465186 0.337977 -0.450926
+
+-0.50846 0.457819 -0.442963
+-0.55226 0.401241 -0.469904
+-0.584892 0.526639 -0.436972
+
+-0.640528 0.465371 -0.46355
+-0.584892 0.526639 -0.436972
+-0.55226 0.401241 -0.469904
+
+-0.584892 0.526639 -0.436972
+-0.640528 0.465371 -0.46355
+-0.658237 0.59268 -0.407425
+
+-0.725231 0.526911 -0.432205
+-0.658237 0.59268 -0.407425
+-0.640528 0.465371 -0.46355
+
+-0.658237 0.59268 -0.407425
+-0.725231 0.526911 -0.432205
+-0.724542 0.65238 -0.355913
+
+-0.801803 0.582544 -0.37756
+-0.724542 0.65238 -0.355913
+-0.725231 0.526911 -0.432205
+
+-0.724542 0.65238 -0.355913
+-0.801803 0.582544 -0.37756
+-0.780231 0.702523 -0.285213
+
+-0.866116 0.62927 -0.302561
+-0.780231 0.702523 -0.285213
+-0.801803 0.582544 -0.37756
+
+-0.780231 0.702523 -0.285213
+-0.866116 0.62927 -0.302561
+-0.822302 0.740404 -0.199138
+
+-0.914702 0.66457 -0.21125
+-0.822302 0.740404 -0.199138
+-0.866116 0.62927 -0.302561
+
+-0.822302 0.740404 -0.199138
+-0.914702 0.66457 -0.21125
+-0.848488 0.763982 -0.102327
+
+-0.944942 0.686541 -0.108551
+-0.848488 0.763982 -0.102327
+-0.914702 0.66457 -0.21125
+
+-0.848488 0.763982 -0.102327
+-0.944942 0.686541 -0.108551
+-0.857376 0.771985 0
+
+-0.955207 0.693998 0
+-0.857376 0.771985 0
+-0.944942 0.686541 -0.108551
+
+-0.955207 0.693998 0
+-1.03057 0.595 0
+-0.944942 0.686541 0.108551
+
+-1.01937 0.588531 0.110696
+-0.944942 0.686541 0.108551
+-1.03057 0.595 0
+
+-0.944942 0.686541 0.108551
+-1.01937 0.588531 0.110696
+-0.914702 0.66457 0.21125
+
+-0.986354 0.569472 0.215424
+-0.914702 0.66457 0.21125
+-1.01937 0.588531 0.110696
+
+-0.914702 0.66457 0.21125
+-0.986354 0.569472 0.215424
+-0.866116 0.62927 0.302561
+
+-0.933317 0.538851 0.308538
+-0.866116 0.62927 0.302561
+-0.986354 0.569472 0.215424
+
+-0.866116 0.62927 0.302561
+-0.933317 0.538851 0.308538
+-0.801803 0.582544 0.37756
+
+-0.863112 0.498318 0.385019
+-0.801803 0.582544 0.37756
+-0.933317 0.538851 0.308538
+
+-0.801803 0.582544 0.37756
+-0.863112 0.498318 0.385019
+-0.725231 0.526911 0.432205
+
+-0.779525 0.450059 0.440744
+-0.725231 0.526911 0.432205
+-0.863112 0.498318 0.385019
+
+-0.725231 0.526911 0.432205
+-0.779525 0.450059 0.440744
+-0.640528 0.465371 0.46355
+
+-0.687062 0.396676 0.472708
+-0.640528 0.465371 0.46355
+-0.779525 0.450059 0.440744
+
+-0.640528 0.465371 0.46355
+-0.687062 0.396676 0.472708
+-0.55226 0.401241 0.469904
+
+-0.590708 0.341045 0.479188
+-0.55226 0.401241 0.469904
+-0.687062 0.396676 0.472708
+
+-0.55226 0.401241 0.469904
+-0.590708 0.341045 0.479188
+-0.465186 0.337977 0.450926
+
+-0.495656 0.286167 0.459835
+-0.465186 0.337977 0.450926
+-0.590708 0.341045 0.479188
+
+-0.465186 0.337977 0.450926
+-0.495656 0.286167 0.459835
+-0.384 0.278992 0.407639
+
+-0.407032 0.235 0.415692
+-0.384 0.278992 0.407639
+-0.495656 0.286167 0.459835
+
+-0.384 0.278992 0.407639
+-0.407032 0.235 0.415692
+-0.313078 0.227464 0.342375
+
+-0.329613 0.190302 0.349139
+-0.313078 0.227464 0.342375
+-0.407032 0.235 0.415692
+
+-0.313078 0.227464 0.342375
+-0.329613 0.190302 0.349139
+-0.256244 0.186172 0.258654
+
+-0.267572 0.154483 0.263764
+-0.256244 0.186172 0.258654
+-0.329613 0.190302 0.349139
+
+-0.256244 0.186172 0.258654
+-0.267572 0.154483 0.263764
+-0.216563 0.157342 0.160989
+
+-0.224255 0.129474 0.16417
+-0.216563 0.157342 0.160989
+-0.267572 0.154483 0.263764
+
+-0.216563 0.157342 0.160989
+-0.224255 0.129474 0.16417
+-0.196172 0.142527 0.054645
+
+-0.201997 0.116623 0.0557246
+-0.196172 0.142527 0.054645
+-0.224255 0.129474 0.16417
+
+-0.196172 0.142527 0.054645
+-0.201997 0.116623 0.0557246
+-0.196172 0.142527 -0.054645
+
+-0.201997 0.116623 -0.0557246
+-0.196172 0.142527 -0.054645
+-0.201997 0.116623 0.0557246
+
+-0.196172 0.142527 -0.054645
+-0.201997 0.116623 -0.0557246
+-0.216563 0.157342 -0.160989
+
+-0.224255 0.129474 -0.16417
+-0.216563 0.157342 -0.160989
+-0.201997 0.116623 -0.0557246
+
+-0.216563 0.157342 -0.160989
+-0.224255 0.129474 -0.16417
+-0.256244 0.186172 -0.258654
+
+-0.267572 0.154483 -0.263764
+-0.256244 0.186172 -0.258654
+-0.224255 0.129474 -0.16417
+
+-0.256244 0.186172 -0.258654
+-0.267572 0.154483 -0.263764
+-0.313078 0.227464 -0.342375
+
+-0.329613 0.190302 -0.349139
+-0.313078 0.227464 -0.342375
+-0.267572 0.154483 -0.263764
+
+-0.313078 0.227464 -0.342375
+-0.329613 0.190302 -0.349139
+-0.384 0.278992 -0.407639
+
+-0.407032 0.235 -0.415692
+-0.384 0.278992 -0.407639
+-0.329613 0.190302 -0.349139
+
+-0.384 0.278992 -0.407639
+-0.407032 0.235 -0.415692
+-0.465186 0.337977 -0.450926
+
+-0.495656 0.286167 -0.459835
+-0.465186 0.337977 -0.450926
+-0.407032 0.235 -0.415692
+
+-0.465186 0.337977 -0.450926
+-0.495656 0.286167 -0.459835
+-0.55226 0.401241 -0.469904
+
+-0.590708 0.341045 -0.479188
+-0.55226 0.401241 -0.469904
+-0.495656 0.286167 -0.459835
+
+-0.55226 0.401241 -0.469904
+-0.590708 0.341045 -0.479188
+-0.640528 0.465371 -0.46355
+
+-0.687062 0.396676 -0.472708
+-0.640528 0.465371 -0.46355
+-0.590708 0.341045 -0.479188
+
+-0.640528 0.465371 -0.46355
+-0.687062 0.396676 -0.472708
+-0.725231 0.526911 -0.432205
+
+-0.779525 0.450059 -0.440744
+-0.725231 0.526911 -0.432205
+-0.687062 0.396676 -0.472708
+
+-0.725231 0.526911 -0.432205
+-0.779525 0.450059 -0.440744
+-0.801803 0.582544 -0.37756
+
+-0.863112 0.498318 -0.385019
+-0.801803 0.582544 -0.37756
+-0.779525 0.450059 -0.440744
+
+-0.801803 0.582544 -0.37756
+-0.863112 0.498318 -0.385019
+-0.866116 0.62927 -0.302561
+
+-0.933317 0.538851 -0.308538
+-0.866116 0.62927 -0.302561
+-0.863112 0.498318 -0.385019
+
+-0.866116 0.62927 -0.302561
+-0.933317 0.538851 -0.308538
+-0.914702 0.66457 -0.21125
+
+-0.986354 0.569472 -0.215424
+-0.914702 0.66457 -0.21125
+-0.933317 0.538851 -0.308538
+
+-0.914702 0.66457 -0.21125
+-0.986354 0.569472 -0.215424
+-0.944942 0.686541 -0.108551
+
+-1.01937 0.588531 -0.110696
+-0.944942 0.686541 -0.108551
+-0.986354 0.569472 -0.215424
+
+-0.944942 0.686541 -0.108551
+-1.01937 0.588531 -0.110696
+-0.955207 0.693998 0
+
+-1.03057 0.595 0
+-0.955207 0.693998 0
+-1.01937 0.588531 -0.110696
+
+-1.03057 0.595 0
+-1.07862 0.480234 0
+-1.01937 0.588531 0.110696
+
+-1.06703 0.475074 0.108551
+-1.01937 0.588531 0.110696
+-1.07862 0.480234 0
+
+-1.01937 0.588531 0.110696
+-1.06703 0.475074 0.108551
+-0.986354 0.569472 0.215424
+
+-1.03289 0.45987 0.21125
+-0.986354 0.569472 0.215424
+-1.06703 0.475074 0.108551
+
+-0.986354 0.569472 0.215424
+-1.03289 0.45987 0.21125
+-0.933317 0.538851 0.308538
+
+-0.978021 0.435443 0.302561
+-0.933317 0.538851 0.308538
+-1.03289 0.45987 0.21125
+
+-0.933317 0.538851 0.308538
+-0.978021 0.435443 0.302561
+-0.863112 0.498318 0.385019
+
+-0.905399 0.40311 0.37756
+-0.863112 0.498318 0.385019
+-0.978021 0.435443 0.302561
+
+-0.863112 0.498318 0.385019
+-0.905399 0.40311 0.37756
+-0.779525 0.450059 0.440744
+
+-0.818934 0.364613 0.432205
+-0.779525 0.450059 0.440744
+-0.905399 0.40311 0.37756
+
+-0.779525 0.450059 0.440744
+-0.818934 0.364613 0.432205
+-0.687062 0.396676 0.472708
+
+-0.723287 0.322028 0.46355
+-0.687062 0.396676 0.472708
+-0.818934 0.364613 0.432205
+
+-0.687062 0.396676 0.472708
+-0.723287 0.322028 0.46355
+-0.590708 0.341045 0.479188
+
+-0.623615 0.277651 0.469904
+-0.590708 0.341045 0.479188
+-0.723287 0.322028 0.46355
+
+-0.590708 0.341045 0.479188
+-0.623615 0.277651 0.469904
+-0.495656 0.286167 0.459835
+
+-0.52529 0.233874 0.450926
+-0.495656 0.286167 0.459835
+-0.623615 0.277651 0.469904
+
+-0.495656 0.286167 0.459835
+-0.52529 0.233874 0.450926
+-0.407032 0.235 0.415692
+
+-0.433614 0.193057 0.407639
+-0.407032 0.235 0.415692
+-0.52529 0.233874 0.450926
+
+-0.407032 0.235 0.415692
+-0.433614 0.193057 0.407639
+-0.329613 0.190302 0.349139
+
+-0.353529 0.157401 0.342375
+-0.329613 0.190302 0.349139
+-0.433614 0.193057 0.407639
+
+-0.329613 0.190302 0.349139
+-0.353529 0.157401 0.342375
+-0.267572 0.154483 0.263764
+
+-0.289352 0.128828 0.258654
+-0.267572 0.154483 0.263764
+-0.353529 0.157401 0.342375
+
+-0.267572 0.154483 0.263764
+-0.289352 0.128828 0.258654
+-0.224255 0.129474 0.16417
+
+-0.244543 0.108878 0.160989
+-0.224255 0.129474 0.16417
+-0.289352 0.128828 0.258654
+
+-0.224255 0.129474 0.16417
+-0.244543 0.108878 0.160989
+-0.201997 0.116623 0.0557246
+
+-0.221518 0.0986263 0.054645
+-0.201997 0.116623 0.0557246
+-0.244543 0.108878 0.160989
+
+-0.201997 0.116623 0.0557246
+-0.221518 0.0986263 0.054645
+-0.201997 0.116623 -0.0557246
+
+-0.221518 0.0986263 -0.054645
+-0.201997 0.116623 -0.0557246
+-0.221518 0.0986263 0.054645
+
+-0.201997 0.116623 -0.0557246
+-0.221518 0.0986263 -0.054645
+-0.224255 0.129474 -0.16417
+
+-0.244543 0.108878 -0.160989
+-0.224255 0.129474 -0.16417
+-0.221518 0.0986263 -0.054645
+
+-0.224255 0.129474 -0.16417
+-0.244543 0.108878 -0.160989
+-0.267572 0.154483 -0.263764
+
+-0.289352 0.128828 -0.258654
+-0.267572 0.154483 -0.263764
+-0.244543 0.108878 -0.160989
+
+-0.267572 0.154483 -0.263764
+-0.289352 0.128828 -0.258654
+-0.329613 0.190302 -0.349139
+
+-0.353529 0.157401 -0.342375
+-0.329613 0.190302 -0.349139
+-0.289352 0.128828 -0.258654
+
+-0.329613 0.190302 -0.349139
+-0.353529 0.157401 -0.342375
+-0.407032 0.235 -0.415692
+
+-0.433614 0.193057 -0.407639
+-0.407032 0.235 -0.415692
+-0.353529 0.157401 -0.342375
+
+-0.407032 0.235 -0.415692
+-0.433614 0.193057 -0.407639
+-0.495656 0.286167 -0.459835
+
+-0.52529 0.233874 -0.450926
+-0.495656 0.286167 -0.459835
+-0.433614 0.193057 -0.407639
+
+-0.495656 0.286167 -0.459835
+-0.52529 0.233874 -0.450926
+-0.590708 0.341045 -0.479188
+
+-0.623615 0.277651 -0.469904
+-0.590708 0.341045 -0.479188
+-0.52529 0.233874 -0.450926
+
+-0.590708 0.341045 -0.479188
+-0.623615 0.277651 -0.469904
+-0.687062 0.396676 -0.472708
+
+-0.723287 0.322028 -0.46355
+-0.687062 0.396676 -0.472708
+-0.623615 0.277651 -0.469904
+
+-0.687062 0.396676 -0.472708
+-0.723287 0.322028 -0.46355
+-0.779525 0.450059 -0.440744
+
+-0.818934 0.364613 -0.432205
+-0.779525 0.450059 -0.440744
+-0.723287 0.322028 -0.46355
+
+-0.779525 0.450059 -0.440744
+-0.818934 0.364613 -0.432205
+-0.863112 0.498318 -0.385019
+
+-0.905399 0.40311 -0.37756
+-0.863112 0.498318 -0.385019
+-0.818934 0.364613 -0.432205
+
+-0.863112 0.498318 -0.385019
+-0.905399 0.40311 -0.37756
+-0.933317 0.538851 -0.308538
+
+-0.978021 0.435443 -0.302561
+-0.933317 0.538851 -0.308538
+-0.905399 0.40311 -0.37756
+
+-0.933317 0.538851 -0.308538
+-0.978021 0.435443 -0.302561
+-0.986354 0.569472 -0.215424
+
+-1.03289 0.45987 -0.21125
+-0.986354 0.569472 -0.215424
+-0.978021 0.435443 -0.302561
+
+-0.986354 0.569472 -0.215424
+-1.03289 0.45987 -0.21125
+-1.01937 0.588531 -0.110696
+
+-1.06703 0.475074 -0.108551
+-1.01937 0.588531 -0.110696
+-1.03289 0.45987 -0.21125
+
+-1.01937 0.588531 -0.110696
+-1.06703 0.475074 -0.108551
+-1.03057 0.595 0
+
+-1.07862 0.480234 0
+-1.03057 0.595 0
+-1.06703 0.475074 -0.108551
+
+-1.07862 0.480234 0
+-1.09725 0.356517 0
+-1.06703 0.475074 0.108551
+
+-1.08587 0.352821 0.102327
+-1.06703 0.475074 0.108551
+-1.09725 0.356517 0
+
+-1.06703 0.475074 0.108551
+-1.08587 0.352821 0.102327
+-1.03289 0.45987 0.21125
+
+-1.05236 0.341932 0.199138
+-1.03289 0.45987 0.21125
+-1.08587 0.352821 0.102327
+
+-1.03289 0.45987 0.21125
+-1.05236 0.341932 0.199138
+-0.978021 0.435443 0.302561
+
+-0.998518 0.324438 0.285213
+-0.978021 0.435443 0.302561
+-1.05236 0.341932 0.199138
+
+-0.978021 0.435443 0.302561
+-0.998518 0.324438 0.285213
+-0.905399 0.40311 0.37756
+
+-0.927249 0.301281 0.355913
+-0.905399 0.40311 0.37756
+-0.998518 0.324438 0.285213
+
+-0.905399 0.40311 0.37756
+-0.927249 0.301281 0.355913
+-0.818934 0.364613 0.432205
+
+-0.842394 0.273711 0.407425
+-0.818934 0.364613 0.432205
+-0.927249 0.301281 0.355913
+
+-0.818934 0.364613 0.432205
+-0.842394 0.273711 0.407425
+-0.723287 0.322028 0.46355
+
+-0.748529 0.243212 0.436972
+-0.723287 0.322028 0.46355
+-0.842394 0.273711 0.407425
+
+-0.723287 0.322028 0.46355
+-0.748529 0.243212 0.436972
+-0.623615 0.277651 0.469904
+
+-0.650713 0.21143 0.442963
+-0.623615 0.277651 0.469904
+-0.748529 0.243212 0.436972
+
+-0.623615 0.277651 0.469904
+-0.650713 0.21143 0.442963
+-0.52529 0.233874 0.450926
+
+-0.55422 0.180077 0.425073
+-0.52529 0.233874 0.450926
+-0.650713 0.21143 0.442963
+
+-0.52529 0.233874 0.450926
+-0.55422 0.180077 0.425073
+-0.433614 0.193057 0.407639
+
+-0.464252 0.150845 0.384267
+-0.433614 0.193057 0.407639
+-0.55422 0.180077 0.425073
+
+-0.433614 0.193057 0.407639
+-0.464252 0.150845 0.384267
+-0.353529 0.157401 0.342375
+
+-0.385659 0.125308 0.322745
+-0.353529 0.157401 0.342375
+-0.464252 0.150845 0.384267
+
+-0.353529 0.157401 0.342375
+-0.385659 0.125308 0.322745
+-0.289352 0.128828 0.258654
+
+-0.322677 0.104844 0.243824
+-0.289352 0.128828 0.258654
+-0.385659 0.125308 0.322745
+
+-0.289352 0.128828 0.258654
+-0.322677 0.104844 0.243824
+-0.244543 0.108878 0.160989
+
+-0.278703 0.0905562 0.151759
+-0.244543 0.108878 0.160989
+-0.322677 0.104844 0.243824
+
+-0.244543 0.108878 0.160989
+-0.278703 0.0905562 0.151759
+-0.221518 0.0986263 0.054645
+
+-0.256107 0.0832143 0.051512
+-0.221518 0.0986263 0.054645
+-0.278703 0.0905562 0.151759
+
+-0.221518 0.0986263 0.054645
+-0.256107 0.0832143 0.051512
+-0.221518 0.0986263 -0.054645
+
+-0.256107 0.0832143 -0.051512
+-0.221518 0.0986263 -0.054645
+-0.256107 0.0832143 0.051512
+
+-0.221518 0.0986263 -0.054645
+-0.256107 0.0832143 -0.051512
+-0.244543 0.108878 -0.160989
+
+-0.278703 0.0905562 -0.151759
+-0.244543 0.108878 -0.160989
+-0.256107 0.0832143 -0.051512
+
+-0.244543 0.108878 -0.160989
+-0.278703 0.0905562 -0.151759
+-0.289352 0.128828 -0.258654
+
+-0.322677 0.104844 -0.243824
+-0.289352 0.128828 -0.258654
+-0.278703 0.0905562 -0.151759
+
+-0.289352 0.128828 -0.258654
+-0.322677 0.104844 -0.243824
+-0.353529 0.157401 -0.342375
+
+-0.385659 0.125308 -0.322745
+-0.353529 0.157401 -0.342375
+-0.322677 0.104844 -0.243824
+
+-0.353529 0.157401 -0.342375
+-0.385659 0.125308 -0.322745
+-0.433614 0.193057 -0.407639
+
+-0.464252 0.150845 -0.384267
+-0.433614 0.193057 -0.407639
+-0.385659 0.125308 -0.322745
+
+-0.433614 0.193057 -0.407639
+-0.464252 0.150845 -0.384267
+-0.52529 0.233874 -0.450926
+
+-0.55422 0.180077 -0.425073
+-0.52529 0.233874 -0.450926
+-0.464252 0.150845 -0.384267
+
+-0.52529 0.233874 -0.450926
+-0.55422 0.180077 -0.425073
+-0.623615 0.277651 -0.469904
+
+-0.650713 0.21143 -0.442963
+-0.623615 0.277651 -0.469904
+-0.55422 0.180077 -0.425073
+
+-0.623615 0.277651 -0.469904
+-0.650713 0.21143 -0.442963
+-0.723287 0.322028 -0.46355
+
+-0.748529 0.243212 -0.436972
+-0.723287 0.322028 -0.46355
+-0.650713 0.21143 -0.442963
+
+-0.723287 0.322028 -0.46355
+-0.748529 0.243212 -0.436972
+-0.818934 0.364613 -0.432205
+
+-0.842394 0.273711 -0.407425
+-0.818934 0.364613 -0.432205
+-0.748529 0.243212 -0.436972
+
+-0.818934 0.364613 -0.432205
+-0.842394 0.273711 -0.407425
+-0.905399 0.40311 -0.37756
+
+-0.927249 0.301281 -0.355913
+-0.905399 0.40311 -0.37756
+-0.842394 0.273711 -0.407425
+
+-0.905399 0.40311 -0.37756
+-0.927249 0.301281 -0.355913
+-0.978021 0.435443 -0.302561
+
+-0.998518 0.324438 -0.285213
+-0.978021 0.435443 -0.302561
+-0.927249 0.301281 -0.355913
+
+-0.978021 0.435443 -0.302561
+-0.998518 0.324438 -0.285213
+-1.03289 0.45987 -0.21125
+
+-1.05236 0.341932 -0.199138
+-1.03289 0.45987 -0.21125
+-0.998518 0.324438 -0.285213
+
+-1.03289 0.45987 -0.21125
+-1.05236 0.341932 -0.199138
+-1.06703 0.475074 -0.108551
+
+-1.08587 0.352821 -0.102327
+-1.06703 0.475074 -0.108551
+-1.05236 0.341932 -0.199138
+
+-1.06703 0.475074 -0.108551
+-1.08587 0.352821 -0.102327
+-1.07862 0.480234 0
+
+-1.09725 0.356517 0
+-1.07862 0.480234 0
+-1.08587 0.352821 -0.102327
+
+-1.09725 0.356517 0
+-1.08739 0.231131 0
+-1.08587 0.352821 0.102327
+
+-1.0768 0.22888 0.0926336
+-1.08587 0.352821 0.102327
+-1.08739 0.231131 0
+
+-1.08587 0.352821 0.102327
+-1.0768 0.22888 0.0926336
+-1.05236 0.341932 0.199138
+
+-1.04559 0.222248 0.180273
+-1.05236 0.341932 0.199138
+-1.0768 0.22888 0.0926336
+
+-1.05236 0.341932 0.199138
+-1.04559 0.222248 0.180273
+-0.998518 0.324438 0.285213
+
+-0.995465 0.211593 0.258194
+-0.998518 0.324438 0.285213
+-1.04559 0.222248 0.180273
+
+-0.998518 0.324438 0.285213
+-0.995465 0.211593 0.258194
+-0.927249 0.301281 0.355913
+
+-0.929109 0.197488 0.322196
+-0.927249 0.301281 0.355913
+-0.995465 0.211593 0.258194
+
+-0.927249 0.301281 0.355913
+-0.929109 0.197488 0.322196
+-0.842394 0.273711 0.407425
+
+-0.850105 0.180695 0.368828
+-0.842394 0.273711 0.407425
+-0.929109 0.197488 0.322196
+
+-0.842394 0.273711 0.407425
+-0.850105 0.180695 0.368828
+-0.748529 0.243212 0.436972
+
+-0.762711 0.162119 0.395577
+-0.748529 0.243212 0.436972
+-0.850105 0.180695 0.368828
+
+-0.748529 0.243212 0.436972
+-0.762711 0.162119 0.395577
+-0.650713 0.21143 0.442963
+
+-0.67164 0.142761 0.401
+-0.650713 0.21143 0.442963
+-0.762711 0.162119 0.395577
+
+-0.650713 0.21143 0.442963
+-0.67164 0.142761 0.401
+-0.55422 0.180077 0.425073
+
+-0.581799 0.123665 0.384804
+-0.55422 0.180077 0.425073
+-0.67164 0.142761 0.401
+
+-0.55422 0.180077 0.425073
+-0.581799 0.123665 0.384804
+-0.464252 0.150845 0.384267
+
+-0.498034 0.10586 0.347864
+-0.464252 0.150845 0.384267
+-0.581799 0.123665 0.384804
+
+-0.464252 0.150845 0.384267
+-0.498034 0.10586 0.347864
+-0.385659 0.125308 0.322745
+
+-0.424859 0.0903067 0.292171
+-0.385659 0.125308 0.322745
+-0.498034 0.10586 0.347864
+
+-0.385659 0.125308 0.322745
+-0.424859 0.0903067 0.292171
+-0.322677 0.104844 0.243824
+
+-0.36622 0.0778425 0.220726
+-0.322677 0.104844 0.243824
+-0.424859 0.0903067 0.292171
+
+-0.322677 0.104844 0.243824
+-0.36622 0.0778425 0.220726
+-0.278703 0.0905562 0.151759
+
+-0.325278 0.06914 0.137382
+-0.278703 0.0905562 0.151759
+-0.36622 0.0778425 0.220726
+
+-0.278703 0.0905562 0.151759
+-0.325278 0.06914 0.137382
+-0.256107 0.0832143 0.051512
+
+-0.30424 0.0646682 0.0466321
+-0.256107 0.0832143 0.051512
+-0.325278 0.06914 0.137382
+
+-0.256107 0.0832143 0.051512
+-0.30424 0.0646682 0.0466321
+-0.256107 0.0832143 -0.051512
+
+-0.30424 0.0646682 -0.0466321
+-0.256107 0.0832143 -0.051512
+-0.30424 0.0646682 0.0466321
+
+-0.256107 0.0832143 -0.051512
+-0.30424 0.0646682 -0.0466321
+-0.278703 0.0905562 -0.151759
+
+-0.325278 0.06914 -0.137382
+-0.278703 0.0905562 -0.151759
+-0.30424 0.0646682 -0.0466321
+
+-0.278703 0.0905562 -0.151759
+-0.325278 0.06914 -0.137382
+-0.322677 0.104844 -0.243824
+
+-0.36622 0.0778425 -0.220726
+-0.322677 0.104844 -0.243824
+-0.325278 0.06914 -0.137382
+
+-0.322677 0.104844 -0.243824
+-0.36622 0.0778425 -0.220726
+-0.385659 0.125308 -0.322745
+
+-0.424859 0.0903067 -0.292171
+-0.385659 0.125308 -0.322745
+-0.36622 0.0778425 -0.220726
+
+-0.385659 0.125308 -0.322745
+-0.424859 0.0903067 -0.292171
+-0.464252 0.150845 -0.384267
+
+-0.498034 0.10586 -0.347864
+-0.464252 0.150845 -0.384267
+-0.424859 0.0903067 -0.292171
+
+-0.464252 0.150845 -0.384267
+-0.498034 0.10586 -0.347864
+-0.55422 0.180077 -0.425073
+
+-0.581799 0.123665 -0.384804
+-0.55422 0.180077 -0.425073
+-0.498034 0.10586 -0.347864
+
+-0.55422 0.180077 -0.425073
+-0.581799 0.123665 -0.384804
+-0.650713 0.21143 -0.442963
+
+-0.67164 0.142761 -0.401
+-0.650713 0.21143 -0.442963
+-0.581799 0.123665 -0.384804
+
+-0.650713 0.21143 -0.442963
+-0.67164 0.142761 -0.401
+-0.748529 0.243212 -0.436972
+
+-0.762711 0.162119 -0.395577
+-0.748529 0.243212 -0.436972
+-0.67164 0.142761 -0.401
+
+-0.748529 0.243212 -0.436972
+-0.762711 0.162119 -0.395577
+-0.842394 0.273711 -0.407425
+
+-0.850105 0.180695 -0.368828
+-0.842394 0.273711 -0.407425
+-0.762711 0.162119 -0.395577
+
+-0.842394 0.273711 -0.407425
+-0.850105 0.180695 -0.368828
+-0.927249 0.301281 -0.355913
+
+-0.929109 0.197488 -0.322196
+-0.927249 0.301281 -0.355913
+-0.850105 0.180695 -0.368828
+
+-0.927249 0.301281 -0.355913
+-0.929109 0.197488 -0.322196
+-0.998518 0.324438 -0.285213
+
+-0.995465 0.211593 -0.258194
+-0.998518 0.324438 -0.285213
+-0.929109 0.197488 -0.322196
+
+-0.998518 0.324438 -0.285213
+-0.995465 0.211593 -0.258194
+-1.05236 0.341932 -0.199138
+
+-1.04559 0.222248 -0.180273
+-1.05236 0.341932 -0.199138
+-0.995465 0.211593 -0.258194
+
+-1.05236 0.341932 -0.199138
+-1.04559 0.222248 -0.180273
+-1.08587 0.352821 -0.102327
+
+-1.0768 0.22888 -0.0926336
+-1.08587 0.352821 -0.102327
+-1.04559 0.222248 -0.180273
+
+-1.08587 0.352821 -0.102327
+-1.0768 0.22888 -0.0926336
+-1.09725 0.356517 0
+
+-1.08739 0.231131 0
+-1.09725 0.356517 0
+-1.0768 0.22888 -0.0926336
+
+-1.08739 0.231131 0
+-1.05291 0.110666 0
+-1.0768 0.22888 0.0926336
+
+-1.04357 0.109683 0.0804188
+-1.0768 0.22888 0.0926336
+-1.05291 0.110666 0
+
+-1.0768 0.22888 0.0926336
+-1.04357 0.109683 0.0804188
+-1.04559 0.222248 0.180273
+
+-1.01602 0.106789 0.156502
+-1.04559 0.222248 0.180273
+-1.04357 0.109683 0.0804188
+
+-1.04559 0.222248 0.180273
+-1.01602 0.106789 0.156502
+-0.995465 0.211593 0.258194
+
+-0.971777 0.102138 0.224149
+-0.995465 0.211593 0.258194
+-1.01602 0.106789 0.156502
+
+-0.995465 0.211593 0.258194
+-0.971777 0.102138 0.224149
+-0.929109 0.197488 0.322196
+
+-0.913207 0.0959819 0.279711
+-0.929109 0.197488 0.322196
+-0.971777 0.102138 0.224149
+
+-0.929109 0.197488 0.322196
+-0.913207 0.0959819 0.279711
+-0.850105 0.180695 0.368828
+
+-0.843472 0.0886525 0.320194
+-0.850105 0.180695 0.368828
+-0.913207 0.0959819 0.279711
+
+-0.850105 0.180695 0.368828
+-0.843472 0.0886525 0.320194
+-0.762711 0.162119 0.395577
+
+-0.766332 0.0805448 0.343415
+-0.762711 0.162119 0.395577
+-0.843472 0.0886525 0.320194
+
+-0.762711 0.162119 0.395577
+-0.766332 0.0805448 0.343415
+-0.67164 0.142761 0.401
+
+-0.685946 0.0720958 0.348123
+-0.67164 0.142761 0.401
+-0.766332 0.0805448 0.343415
+
+-0.67164 0.142761 0.401
+-0.685946 0.0720958 0.348123
+-0.581799 0.123665 0.384804
+
+-0.606646 0.0637611 0.334064
+-0.581799 0.123665 0.384804
+-0.685946 0.0720958 0.348123
+
+-0.581799 0.123665 0.384804
+-0.606646 0.0637611 0.334064
+-0.498034 0.10586 0.347864
+
+-0.532709 0.05599 0.301995
+-0.498034 0.10586 0.347864
+-0.606646 0.0637611 0.334064
+
+-0.498034 0.10586 0.347864
+-0.532709 0.05599 0.301995
+-0.424859 0.0903067 0.292171
+
+-0.46812 0.0492014 0.253645
+-0.424859 0.0903067 0.292171
+-0.532709 0.05599 0.301995
+
+-0.424859 0.0903067 0.292171
+-0.46812 0.0492014 0.253645
+-0.36622 0.0778425 0.220726
+
+-0.416361 0.0437613 0.191621
+-0.36622 0.0778425 0.220726
+-0.46812 0.0492014 0.253645
+
+-0.36622 0.0778425 0.220726
+-0.416361 0.0437613 0.191621
+-0.325278 0.06914 0.137382
+
+-0.380222 0.039963 0.119267
+-0.325278 0.06914 0.137382
+-0.416361 0.0437613 0.191621
+
+-0.325278 0.06914 0.137382
+-0.380222 0.039963 0.119267
+-0.30424 0.0646682 0.0466321
+
+-0.361653 0.0380112 0.0404831
+-0.30424 0.0646682 0.0466321
+-0.380222 0.039963 0.119267
+
+-0.30424 0.0646682 0.0466321
+-0.361653 0.0380112 0.0404831
+-0.30424 0.0646682 -0.0466321
+
+-0.361653 0.0380112 -0.0404831
+-0.30424 0.0646682 -0.0466321
+-0.361653 0.0380112 0.0404831
+
+-0.30424 0.0646682 -0.0466321
+-0.361653 0.0380112 -0.0404831
+-0.325278 0.06914 -0.137382
+
+-0.380222 0.039963 -0.119267
+-0.325278 0.06914 -0.137382
+-0.361653 0.0380112 -0.0404831
+
+-0.325278 0.06914 -0.137382
+-0.380222 0.039963 -0.119267
+-0.36622 0.0778425 -0.220726
+
+-0.416361 0.0437613 -0.191621
+-0.36622 0.0778425 -0.220726
+-0.380222 0.039963 -0.119267
+
+-0.36622 0.0778425 -0.220726
+-0.416361 0.0437613 -0.191621
+-0.424859 0.0903067 -0.292171
+
+-0.46812 0.0492014 -0.253645
+-0.424859 0.0903067 -0.292171
+-0.416361 0.0437613 -0.191621
+
+-0.424859 0.0903067 -0.292171
+-0.46812 0.0492014 -0.253645
+-0.498034 0.10586 -0.347864
+
+-0.532709 0.05599 -0.301995
+-0.498034 0.10586 -0.347864
+-0.46812 0.0492014 -0.253645
+
+-0.498034 0.10586 -0.347864
+-0.532709 0.05599 -0.301995
+-0.581799 0.123665 -0.384804
+
+-0.606646 0.0637611 -0.334064
+-0.581799 0.123665 -0.384804
+-0.532709 0.05599 -0.301995
+
+-0.581799 0.123665 -0.384804
+-0.606646 0.0637611 -0.334064
+-0.67164 0.142761 -0.401
+
+-0.685946 0.0720958 -0.348123
+-0.67164 0.142761 -0.401
+-0.606646 0.0637611 -0.334064
+
+-0.67164 0.142761 -0.401
+-0.685946 0.0720958 -0.348123
+-0.762711 0.162119 -0.395577
+
+-0.766332 0.0805448 -0.343415
+-0.762711 0.162119 -0.395577
+-0.685946 0.0720958 -0.348123
+
+-0.762711 0.162119 -0.395577
+-0.766332 0.0805448 -0.343415
+-0.850105 0.180695 -0.368828
+
+-0.843472 0.0886525 -0.320194
+-0.850105 0.180695 -0.368828
+-0.766332 0.0805448 -0.343415
+
+-0.850105 0.180695 -0.368828
+-0.843472 0.0886525 -0.320194
+-0.929109 0.197488 -0.322196
+
+-0.913207 0.0959819 -0.279711
+-0.929109 0.197488 -0.322196
+-0.843472 0.0886525 -0.320194
+
+-0.929109 0.197488 -0.322196
+-0.913207 0.0959819 -0.279711
+-0.995465 0.211593 -0.258194
+
+-0.971777 0.102138 -0.224149
+-0.995465 0.211593 -0.258194
+-0.913207 0.0959819 -0.279711
+
+-0.995465 0.211593 -0.258194
+-0.971777 0.102138 -0.224149
+-1.04559 0.222248 -0.180273
+
+-1.01602 0.106789 -0.156502
+-1.04559 0.222248 -0.180273
+-0.971777 0.102138 -0.224149
+
+-1.04559 0.222248 -0.180273
+-1.01602 0.106789 -0.156502
+-1.0768 0.22888 -0.0926336
+
+-1.04357 0.109683 -0.0804188
+-1.0768 0.22888 -0.0926336
+-1.01602 0.106789 -0.156502
+
+-1.0768 0.22888 -0.0926336
+-1.04357 0.109683 -0.0804188
+-1.08739 0.231131 0
+
+-1.05291 0.110666 0
+-1.08739 0.231131 0
+-1.04357 0.109683 -0.0804188
+
+-1.05291 0.110666 0
+-1 4.44089e-16 0
+-1.04357 0.109683 0.0804188
+
+-0.992183 4.40618e-16 0.0668786
+-1.04357 0.109683 0.0804188
+-1 4.44089e-16 0
+
+-1.04357 0.109683 0.0804188
+-0.992183 4.40618e-16 0.0668786
+-1.01602 0.106789 0.156502
+
+-0.969153 4.30391e-16 0.130152
+-1.01602 0.106789 0.156502
+-0.992183 4.40618e-16 0.0668786
+
+-1.01602 0.106789 0.156502
+-0.969153 4.30391e-16 0.130152
+-0.971777 0.102138 0.224149
+
+-0.932153 4.13959e-16 0.186408
+-0.971777 0.102138 0.224149
+-0.969153 4.30391e-16 0.130152
+
+-0.971777 0.102138 0.224149
+-0.932153 4.13959e-16 0.186408
+-0.913207 0.0959819 0.279711
+
+-0.883176 3.92209e-16 0.232616
+-0.913207 0.0959819 0.279711
+-0.932153 4.13959e-16 0.186408
+
+-0.913207 0.0959819 0.279711
+-0.883176 3.92209e-16 0.232616
+-0.843472 0.0886525 0.320194
+
+-0.824863 3.66313e-16 0.266283
+-0.843472 0.0886525 0.320194
+-0.883176 3.92209e-16 0.232616
+
+-0.843472 0.0886525 0.320194
+-0.824863 3.66313e-16 0.266283
+-0.766332 0.0805448 0.343415
+
+-0.760358 3.37667e-16 0.285594
+-0.766332 0.0805448 0.343415
+-0.824863 3.66313e-16 0.266283
+
+-0.766332 0.0805448 0.343415
+-0.760358 3.37667e-16 0.285594
+-0.685946 0.0720958 0.348123
+
+-0.693138 3.07815e-16 0.289509
+-0.685946 0.0720958 0.348123
+-0.760358 3.37667e-16 0.285594
+
+-0.685946 0.0720958 0.348123
+-0.693138 3.07815e-16 0.289509
+-0.606646 0.0637611 0.334064
+
+-0.626827 2.78367e-16 0.277817
+-0.606646 0.0637611 0.334064
+-0.693138 3.07815e-16 0.289509
+
+-0.606646 0.0637611 0.334064
+-0.626827 2.78367e-16 0.277817
+-0.532709 0.05599 0.301995
+
+-0.565 2.5091e-16 0.251147
+-0.532709 0.05599 0.301995
+-0.626827 2.78367e-16 0.277817
+
+-0.532709 0.05599 0.301995
+-0.565 2.5091e-16 0.251147
+-0.46812 0.0492014 0.253645
+
+-0.51099 2.26925e-16 0.210938
+-0.46812 0.0492014 0.253645
+-0.565 2.5091e-16 0.251147
+
+-0.46812 0.0492014 0.253645
+-0.51099 2.26925e-16 0.210938
+-0.416361 0.0437613 0.191621
+
+-0.467709 2.07704e-16 0.159358
+-0.416361 0.0437613 0.191621
+-0.51099 2.26925e-16 0.210938
+
+-0.416361 0.0437613 0.191621
+-0.467709 2.07704e-16 0.159358
+-0.380222 0.039963 0.119267
+
+-0.437489 1.94284e-16 0.0991858
+-0.380222 0.039963 0.119267
+-0.467709 2.07704e-16 0.159358
+
+-0.380222 0.039963 0.119267
+-0.437489 1.94284e-16 0.0991858
+-0.361653 0.0380112 0.0404831
+
+-0.421961 1.87388e-16 0.0336669
+-0.361653 0.0380112 0.0404831
+-0.437489 1.94284e-16 0.0991858
+
+-0.361653 0.0380112 0.0404831
+-0.421961 1.87388e-16 0.0336669
+-0.361653 0.0380112 -0.0404831
+
+-0.421961 1.87388e-16 -0.0336669
+-0.361653 0.0380112 -0.0404831
+-0.421961 1.87388e-16 0.0336669
+
+-0.361653 0.0380112 -0.0404831
+-0.421961 1.87388e-16 -0.0336669
+-0.380222 0.039963 -0.119267
+
+-0.437489 1.94284e-16 -0.0991858
+-0.380222 0.039963 -0.119267
+-0.421961 1.87388e-16 -0.0336669
+
+-0.380222 0.039963 -0.119267
+-0.437489 1.94284e-16 -0.0991858
+-0.416361 0.0437613 -0.191621
+
+-0.467709 2.07704e-16 -0.159358
+-0.416361 0.0437613 -0.191621
+-0.437489 1.94284e-16 -0.0991858
+
+-0.416361 0.0437613 -0.191621
+-0.467709 2.07704e-16 -0.159358
+-0.46812 0.0492014 -0.253645
+
+-0.51099 2.26925e-16 -0.210938
+-0.46812 0.0492014 -0.253645
+-0.467709 2.07704e-16 -0.159358
+
+-0.46812 0.0492014 -0.253645
+-0.51099 2.26925e-16 -0.210938
+-0.532709 0.05599 -0.301995
+
+-0.565 2.5091e-16 -0.251147
+-0.532709 0.05599 -0.301995
+-0.51099 2.26925e-16 -0.210938
+
+-0.532709 0.05599 -0.301995
+-0.565 2.5091e-16 -0.251147
+-0.606646 0.0637611 -0.334064
+
+-0.626827 2.78367e-16 -0.277817
+-0.606646 0.0637611 -0.334064
+-0.565 2.5091e-16 -0.251147
+
+-0.606646 0.0637611 -0.334064
+-0.626827 2.78367e-16 -0.277817
+-0.685946 0.0720958 -0.348123
+
+-0.693138 3.07815e-16 -0.289509
+-0.685946 0.0720958 -0.348123
+-0.626827 2.78367e-16 -0.277817
+
+-0.685946 0.0720958 -0.348123
+-0.693138 3.07815e-16 -0.289509
+-0.766332 0.0805448 -0.343415
+
+-0.760358 3.37667e-16 -0.285594
+-0.766332 0.0805448 -0.343415
+-0.693138 3.07815e-16 -0.289509
+
+-0.766332 0.0805448 -0.343415
+-0.760358 3.37667e-16 -0.285594
+-0.843472 0.0886525 -0.320194
+
+-0.824863 3.66313e-16 -0.266283
+-0.843472 0.0886525 -0.320194
+-0.760358 3.37667e-16 -0.285594
+
+-0.843472 0.0886525 -0.320194
+-0.824863 3.66313e-16 -0.266283
+-0.913207 0.0959819 -0.279711
+
+-0.883176 3.92209e-16 -0.232616
+-0.913207 0.0959819 -0.279711
+-0.824863 3.66313e-16 -0.266283
+
+-0.913207 0.0959819 -0.279711
+-0.883176 3.92209e-16 -0.232616
+-0.971777 0.102138 -0.224149
+
+-0.932153 4.13959e-16 -0.186408
+-0.971777 0.102138 -0.224149
+-0.883176 3.92209e-16 -0.232616
+
+-0.971777 0.102138 -0.224149
+-0.932153 4.13959e-16 -0.186408
+-1.01602 0.106789 -0.156502
+
+-0.969153 4.30391e-16 -0.130152
+-1.01602 0.106789 -0.156502
+-0.932153 4.13959e-16 -0.186408
+
+-1.01602 0.106789 -0.156502
+-0.969153 4.30391e-16 -0.130152
+-1.04357 0.109683 -0.0804188
+
+-0.992183 4.40618e-16 -0.0668786
+-1.04357 0.109683 -0.0804188
+-0.969153 4.30391e-16 -0.130152
+
+-1.04357 0.109683 -0.0804188
+-0.992183 4.40618e-16 -0.0668786
+-1.05291 0.110666 0
+
+-1 4.44089e-16 0
+-1.05291 0.110666 0
+-0.992183 4.40618e-16 -0.0668786
+
+-1 4.44089e-16 0
+-0.93613 -0.0983913 0
+-0.992183 4.40618e-16 0.0668786
+
+-0.92993 -0.0977396 0.0533384
+-0.992183 4.40618e-16 0.0668786
+-0.93613 -0.0983913 0
+
+-0.992183 4.40618e-16 0.0668786
+-0.92993 -0.0977396 0.0533384
+-0.969153 4.30391e-16 0.130152
+
+-0.911664 -0.0958197 0.103801
+-0.969153 4.30391e-16 0.130152
+-0.92993 -0.0977396 0.0533384
+
+-0.969153 4.30391e-16 0.130152
+-0.911664 -0.0958197 0.103801
+-0.932153 4.13959e-16 0.186408
+
+-0.882316 -0.0927351 0.148668
+-0.932153 4.13959e-16 0.186408
+-0.911664 -0.0958197 0.103801
+
+-0.932153 4.13959e-16 0.186408
+-0.882316 -0.0927351 0.148668
+-0.883176 3.92209e-16 0.232616
+
+-0.843469 -0.0886521 0.18552
+-0.883176 3.92209e-16 0.232616
+-0.882316 -0.0927351 0.148668
+
+-0.883176 3.92209e-16 0.232616
+-0.843469 -0.0886521 0.18552
+-0.824863 3.66313e-16 0.266283
+
+-0.797217 -0.0837909 0.212371
+-0.824863 3.66313e-16 0.266283
+-0.843469 -0.0886521 0.18552
+
+-0.824863 3.66313e-16 0.266283
+-0.797217 -0.0837909 0.212371
+-0.760358 3.37667e-16 0.285594
+
+-0.746053 -0.0784133 0.227773
+-0.760358 3.37667e-16 0.285594
+-0.797217 -0.0837909 0.212371
+
+-0.760358 3.37667e-16 0.285594
+-0.746053 -0.0784133 0.227773
+-0.693138 3.07815e-16 0.289509
+
+-0.692736 -0.0728095 0.230895
+-0.693138 3.07815e-16 0.289509
+-0.746053 -0.0784133 0.227773
+
+-0.693138 3.07815e-16 0.289509
+-0.692736 -0.0728095 0.230895
+-0.626827 2.78367e-16 0.277817
+
+-0.64014 -0.0672814 0.22157
+-0.626827 2.78367e-16 0.277817
+-0.692736 -0.0728095 0.230895
+
+-0.626827 2.78367e-16 0.277817
+-0.64014 -0.0672814 0.22157
+-0.565 2.5091e-16 0.251147
+
+-0.591101 -0.0621272 0.2003
+-0.565 2.5091e-16 0.251147
+-0.64014 -0.0672814 0.22157
+
+-0.565 2.5091e-16 0.251147
+-0.591101 -0.0621272 0.2003
+-0.51099 2.26925e-16 0.210938
+
+-0.548261 -0.0576246 0.168232
+-0.51099 2.26925e-16 0.210938
+-0.591101 -0.0621272 0.2003
+
+-0.51099 2.26925e-16 0.210938
+-0.548261 -0.0576246 0.168232
+-0.467709 2.07704e-16 0.159358
+
+-0.513932 -0.0540164 0.127094
+-0.467709 2.07704e-16 0.159358
+-0.548261 -0.0576246 0.168232
+
+-0.467709 2.07704e-16 0.159358
+-0.513932 -0.0540164 0.127094
+-0.437489 1.94284e-16 0.0991858
+
+-0.489963 -0.0514972 0.0791047
+-0.437489 1.94284e-16 0.0991858
+-0.513932 -0.0540164 0.127094
+
+-0.437489 1.94284e-16 0.0991858
+-0.489963 -0.0514972 0.0791047
+-0.421961 1.87388e-16 0.0336669
+
+-0.477646 -0.0502026 0.0268508
+-0.421961 1.87388e-16 0.0336669
+-0.489963 -0.0514972 0.0791047
+
+-0.421961 1.87388e-16 0.0336669
+-0.477646 -0.0502026 0.0268508
+-0.421961 1.87388e-16 -0.0336669
+
+-0.477646 -0.0502026 -0.0268508
+-0.421961 1.87388e-16 -0.0336669
+-0.477646 -0.0502026 0.0268508
+
+-0.421961 1.87388e-16 -0.0336669
+-0.477646 -0.0502026 -0.0268508
+-0.437489 1.94284e-16 -0.0991858
+
+-0.489963 -0.0514972 -0.0791047
+-0.437489 1.94284e-16 -0.0991858
+-0.477646 -0.0502026 -0.0268508
+
+-0.437489 1.94284e-16 -0.0991858
+-0.489963 -0.0514972 -0.0791047
+-0.467709 2.07704e-16 -0.159358
+
+-0.513932 -0.0540164 -0.127094
+-0.467709 2.07704e-16 -0.159358
+-0.489963 -0.0514972 -0.0791047
+
+-0.467709 2.07704e-16 -0.159358
+-0.513932 -0.0540164 -0.127094
+-0.51099 2.26925e-16 -0.210938
+
+-0.548261 -0.0576246 -0.168232
+-0.51099 2.26925e-16 -0.210938
+-0.513932 -0.0540164 -0.127094
+
+-0.51099 2.26925e-16 -0.210938
+-0.548261 -0.0576246 -0.168232
+-0.565 2.5091e-16 -0.251147
+
+-0.591101 -0.0621272 -0.2003
+-0.565 2.5091e-16 -0.251147
+-0.548261 -0.0576246 -0.168232
+
+-0.565 2.5091e-16 -0.251147
+-0.591101 -0.0621272 -0.2003
+-0.626827 2.78367e-16 -0.277817
+
+-0.64014 -0.0672814 -0.22157
+-0.626827 2.78367e-16 -0.277817
+-0.591101 -0.0621272 -0.2003
+
+-0.626827 2.78367e-16 -0.277817
+-0.64014 -0.0672814 -0.22157
+-0.693138 3.07815e-16 -0.289509
+
+-0.692736 -0.0728095 -0.230895
+-0.693138 3.07815e-16 -0.289509
+-0.64014 -0.0672814 -0.22157
+
+-0.693138 3.07815e-16 -0.289509
+-0.692736 -0.0728095 -0.230895
+-0.760358 3.37667e-16 -0.285594
+
+-0.746053 -0.0784133 -0.227773
+-0.760358 3.37667e-16 -0.285594
+-0.692736 -0.0728095 -0.230895
+
+-0.760358 3.37667e-16 -0.285594
+-0.746053 -0.0784133 -0.227773
+-0.824863 3.66313e-16 -0.266283
+
+-0.797217 -0.0837909 -0.212371
+-0.824863 3.66313e-16 -0.266283
+-0.746053 -0.0784133 -0.227773
+
+-0.824863 3.66313e-16 -0.266283
+-0.797217 -0.0837909 -0.212371
+-0.883176 3.92209e-16 -0.232616
+
+-0.843469 -0.0886521 -0.18552
+-0.883176 3.92209e-16 -0.232616
+-0.797217 -0.0837909 -0.212371
+
+-0.883176 3.92209e-16 -0.232616
+-0.843469 -0.0886521 -0.18552
+-0.932153 4.13959e-16 -0.186408
+
+-0.882316 -0.0927351 -0.148668
+-0.932153 4.13959e-16 -0.186408
+-0.843469 -0.0886521 -0.18552
+
+-0.932153 4.13959e-16 -0.186408
+-0.882316 -0.0927351 -0.148668
+-0.969153 4.30391e-16 -0.130152
+
+-0.911664 -0.0958197 -0.103801
+-0.969153 4.30391e-16 -0.130152
+-0.882316 -0.0927351 -0.148668
+
+-0.969153 4.30391e-16 -0.130152
+-0.911664 -0.0958197 -0.103801
+-0.992183 4.40618e-16 -0.0668786
+
+-0.92993 -0.0977396 -0.0533384
+-0.992183 4.40618e-16 -0.0668786
+-0.911664 -0.0958197 -0.103801
+
+-0.992183 4.40618e-16 -0.0668786
+-0.92993 -0.0977396 -0.0533384
+-1 4.44089e-16 0
+
+-0.93613 -0.0983913 0
+-1 4.44089e-16 0
+-0.92993 -0.0977396 -0.0533384
+
+-0.93613 -0.0983913 0
+-0.868909 -0.184692 0
+-0.92993 -0.0977396 0.0533384
+
+-0.864207 -0.183693 0.0411236
+-0.92993 -0.0977396 0.0533384
+-0.868909 -0.184692 0
+
+-0.92993 -0.0977396 0.0533384
+-0.864207 -0.183693 0.0411236
+-0.911664 -0.0958197 0.103801
+
+-0.850356 -0.180749 0.0800302
+-0.911664 -0.0958197 0.103801
+-0.864207 -0.183693 0.0411236
+
+-0.911664 -0.0958197 0.103801
+-0.850356 -0.180749 0.0800302
+-0.882316 -0.0927351 0.148668
+
+-0.828101 -0.176018 0.114622
+-0.882316 -0.0927351 0.148668
+-0.850356 -0.180749 0.0800302
+
+-0.882316 -0.0927351 0.148668
+-0.828101 -0.176018 0.114622
+-0.843469 -0.0886521 0.18552
+
+-0.798644 -0.169757 0.143035
+-0.843469 -0.0886521 0.18552
+-0.828101 -0.176018 0.114622
+
+-0.843469 -0.0886521 0.18552
+-0.798644 -0.169757 0.143035
+-0.797217 -0.0837909 0.212371
+
+-0.763571 -0.162302 0.163737
+-0.797217 -0.0837909 0.212371
+-0.798644 -0.169757 0.143035
+
+-0.797217 -0.0837909 0.212371
+-0.763571 -0.162302 0.163737
+-0.746053 -0.0784133 0.227773
+
+-0.724773 -0.154055 0.175612
+-0.746053 -0.0784133 0.227773
+-0.763571 -0.162302 0.163737
+
+-0.746053 -0.0784133 0.227773
+-0.724773 -0.154055 0.175612
+-0.692736 -0.0728095 0.230895
+
+-0.684343 -0.145462 0.178019
+-0.692736 -0.0728095 0.230895
+-0.724773 -0.154055 0.175612
+
+-0.692736 -0.0728095 0.230895
+-0.684343 -0.145462 0.178019
+-0.64014 -0.0672814 0.22157
+
+-0.644459 -0.136984 0.170829
+-0.64014 -0.0672814 0.22157
+-0.684343 -0.145462 0.178019
+
+-0.64014 -0.0672814 0.22157
+-0.644459 -0.136984 0.170829
+-0.591101 -0.0621272 0.2003
+
+-0.607273 -0.12908 0.15443
+-0.591101 -0.0621272 0.2003
+-0.644459 -0.136984 0.170829
+
+-0.591101 -0.0621272 0.2003
+-0.607273 -0.12908 0.15443
+-0.548261 -0.0576246 0.168232
+
+-0.574788 -0.122175 0.129706
+-0.548261 -0.0576246 0.168232
+-0.607273 -0.12908 0.15443
+
+-0.548261 -0.0576246 0.168232
+-0.574788 -0.122175 0.129706
+-0.513932 -0.0540164 0.127094
+
+-0.548756 -0.116642 0.0979889
+-0.513932 -0.0540164 0.127094
+-0.574788 -0.122175 0.129706
+
+-0.513932 -0.0540164 0.127094
+-0.548756 -0.116642 0.0979889
+-0.489963 -0.0514972 0.0791047
+
+-0.53058 -0.112778 0.0609893
+-0.489963 -0.0514972 0.0791047
+-0.548756 -0.116642 0.0979889
+
+-0.489963 -0.0514972 0.0791047
+-0.53058 -0.112778 0.0609893
+-0.477646 -0.0502026 0.0268508
+
+-0.52124 -0.110793 0.0207018
+-0.477646 -0.0502026 0.0268508
+-0.53058 -0.112778 0.0609893
+
+-0.477646 -0.0502026 0.0268508
+-0.52124 -0.110793 0.0207018
+-0.477646 -0.0502026 -0.0268508
+
+-0.52124 -0.110793 -0.0207018
+-0.477646 -0.0502026 -0.0268508
+-0.52124 -0.110793 0.0207018
+
+-0.477646 -0.0502026 -0.0268508
+-0.52124 -0.110793 -0.0207018
+-0.489963 -0.0514972 -0.0791047
+
+-0.53058 -0.112778 -0.0609893
+-0.489963 -0.0514972 -0.0791047
+-0.52124 -0.110793 -0.0207018
+
+-0.489963 -0.0514972 -0.0791047
+-0.53058 -0.112778 -0.0609893
+-0.513932 -0.0540164 -0.127094
+
+-0.548756 -0.116642 -0.0979889
+-0.513932 -0.0540164 -0.127094
+-0.53058 -0.112778 -0.0609893
+
+-0.513932 -0.0540164 -0.127094
+-0.548756 -0.116642 -0.0979889
+-0.548261 -0.0576246 -0.168232
+
+-0.574788 -0.122175 -0.129706
+-0.548261 -0.0576246 -0.168232
+-0.548756 -0.116642 -0.0979889
+
+-0.548261 -0.0576246 -0.168232
+-0.574788 -0.122175 -0.129706
+-0.591101 -0.0621272 -0.2003
+
+-0.607273 -0.12908 -0.15443
+-0.591101 -0.0621272 -0.2003
+-0.574788 -0.122175 -0.129706
+
+-0.591101 -0.0621272 -0.2003
+-0.607273 -0.12908 -0.15443
+-0.64014 -0.0672814 -0.22157
+
+-0.644459 -0.136984 -0.170829
+-0.64014 -0.0672814 -0.22157
+-0.607273 -0.12908 -0.15443
+
+-0.64014 -0.0672814 -0.22157
+-0.644459 -0.136984 -0.170829
+-0.692736 -0.0728095 -0.230895
+
+-0.684343 -0.145462 -0.178019
+-0.692736 -0.0728095 -0.230895
+-0.644459 -0.136984 -0.170829
+
+-0.692736 -0.0728095 -0.230895
+-0.684343 -0.145462 -0.178019
+-0.746053 -0.0784133 -0.227773
+
+-0.724773 -0.154055 -0.175612
+-0.746053 -0.0784133 -0.227773
+-0.684343 -0.145462 -0.178019
+
+-0.746053 -0.0784133 -0.227773
+-0.724773 -0.154055 -0.175612
+-0.797217 -0.0837909 -0.212371
+
+-0.763571 -0.162302 -0.163737
+-0.797217 -0.0837909 -0.212371
+-0.724773 -0.154055 -0.175612
+
+-0.797217 -0.0837909 -0.212371
+-0.763571 -0.162302 -0.163737
+-0.843469 -0.0886521 -0.18552
+
+-0.798644 -0.169757 -0.143035
+-0.843469 -0.0886521 -0.18552
+-0.763571 -0.162302 -0.163737
+
+-0.843469 -0.0886521 -0.18552
+-0.798644 -0.169757 -0.143035
+-0.882316 -0.0927351 -0.148668
+
+-0.828101 -0.176018 -0.114622
+-0.882316 -0.0927351 -0.148668
+-0.798644 -0.169757 -0.143035
+
+-0.882316 -0.0927351 -0.148668
+-0.828101 -0.176018 -0.114622
+-0.911664 -0.0958197 -0.103801
+
+-0.850356 -0.180749 -0.0800302
+-0.911664 -0.0958197 -0.103801
+-0.828101 -0.176018 -0.114622
+
+-0.911664 -0.0958197 -0.103801
+-0.850356 -0.180749 -0.0800302
+-0.92993 -0.0977396 -0.0533384
+
+-0.864207 -0.183693 -0.0411236
+-0.92993 -0.0977396 -0.0533384
+-0.850356 -0.180749 -0.0800302
+
+-0.92993 -0.0977396 -0.0533384
+-0.864207 -0.183693 -0.0411236
+-0.93613 -0.0983913 0
+
+-0.868909 -0.184692 0
+-0.93613 -0.0983913 0
+-0.864207 -0.183693 -0.0411236
+
+-0.868909 -0.184692 0
+-0.804867 -0.261517 0
+-0.864207 -0.183693 0.0411236
+
+-0.801373 -0.260382 0.0314299
+-0.864207 -0.183693 0.0411236
+-0.804867 -0.261517 0
+
+-0.864207 -0.183693 0.0411236
+-0.801373 -0.260382 0.0314299
+-0.850356 -0.180749 0.0800302
+
+-0.79108 -0.257037 0.0611654
+-0.850356 -0.180749 0.0800302
+-0.801373 -0.260382 0.0314299
+
+-0.850356 -0.180749 0.0800302
+-0.79108 -0.257037 0.0611654
+-0.828101 -0.176018 0.114622
+
+-0.774542 -0.251664 0.0876034
+-0.828101 -0.176018 0.114622
+-0.79108 -0.257037 0.0611654
+
+-0.828101 -0.176018 0.114622
+-0.774542 -0.251664 0.0876034
+-0.798644 -0.169757 0.143035
+
+-0.752652 -0.244551 0.109319
+-0.798644 -0.169757 0.143035
+-0.774542 -0.251664 0.0876034
+
+-0.798644 -0.169757 0.143035
+-0.752652 -0.244551 0.109319
+-0.763571 -0.162302 0.163737
+
+-0.726589 -0.236083 0.125141
+-0.763571 -0.162302 0.163737
+-0.752652 -0.244551 0.109319
+
+-0.763571 -0.162302 0.163737
+-0.726589 -0.236083 0.125141
+-0.724773 -0.154055 0.175612
+
+-0.697758 -0.226715 0.134216
+-0.724773 -0.154055 0.175612
+-0.726589 -0.236083 0.125141
+
+-0.724773 -0.154055 0.175612
+-0.697758 -0.226715 0.134216
+-0.684343 -0.145462 0.178019
+
+-0.667714 -0.216953 0.136056
+-0.684343 -0.145462 0.178019
+-0.697758 -0.226715 0.134216
+
+-0.684343 -0.145462 0.178019
+-0.667714 -0.216953 0.136056
+-0.644459 -0.136984 0.170829
+
+-0.638076 -0.207323 0.130561
+-0.644459 -0.136984 0.170829
+-0.667714 -0.216953 0.136056
+
+-0.644459 -0.136984 0.170829
+-0.638076 -0.207323 0.130561
+-0.607273 -0.12908 0.15443
+
+-0.610442 -0.198345 0.118028
+-0.607273 -0.12908 0.15443
+-0.638076 -0.207323 0.130561
+
+-0.607273 -0.12908 0.15443
+-0.610442 -0.198345 0.118028
+-0.574788 -0.122175 0.129706
+
+-0.586302 -0.190501 0.0991314
+-0.574788 -0.122175 0.129706
+-0.610442 -0.198345 0.118028
+
+-0.574788 -0.122175 0.129706
+-0.586302 -0.190501 0.0991314
+-0.548756 -0.116642 0.0979889
+
+-0.566957 -0.184216 0.0748908
+-0.548756 -0.116642 0.0979889
+-0.586302 -0.190501 0.0991314
+
+-0.548756 -0.116642 0.0979889
+-0.566957 -0.184216 0.0748908
+-0.53058 -0.112778 0.0609893
+
+-0.553451 -0.179827 0.0466128
+-0.53058 -0.112778 0.0609893
+-0.566957 -0.184216 0.0748908
+
+-0.53058 -0.112778 0.0609893
+-0.553451 -0.179827 0.0466128
+-0.52124 -0.110793 0.0207018
+
+-0.54651 -0.177572 0.0158219
+-0.52124 -0.110793 0.0207018
+-0.553451 -0.179827 0.0466128
+
+-0.52124 -0.110793 0.0207018
+-0.54651 -0.177572 0.0158219
+-0.52124 -0.110793 -0.0207018
+
+-0.54651 -0.177572 -0.0158219
+-0.52124 -0.110793 -0.0207018
+-0.54651 -0.177572 0.0158219
+
+-0.52124 -0.110793 -0.0207018
+-0.54651 -0.177572 -0.0158219
+-0.53058 -0.112778 -0.0609893
+
+-0.553451 -0.179827 -0.0466128
+-0.53058 -0.112778 -0.0609893
+-0.54651 -0.177572 -0.0158219
+
+-0.53058 -0.112778 -0.0609893
+-0.553451 -0.179827 -0.0466128
+-0.548756 -0.116642 -0.0979889
+
+-0.566957 -0.184216 -0.0748908
+-0.548756 -0.116642 -0.0979889
+-0.553451 -0.179827 -0.0466128
+
+-0.548756 -0.116642 -0.0979889
+-0.566957 -0.184216 -0.0748908
+-0.574788 -0.122175 -0.129706
+
+-0.586302 -0.190501 -0.0991314
+-0.574788 -0.122175 -0.129706
+-0.566957 -0.184216 -0.0748908
+
+-0.574788 -0.122175 -0.129706
+-0.586302 -0.190501 -0.0991314
+-0.607273 -0.12908 -0.15443
+
+-0.610442 -0.198345 -0.118028
+-0.607273 -0.12908 -0.15443
+-0.586302 -0.190501 -0.0991314
+
+-0.607273 -0.12908 -0.15443
+-0.610442 -0.198345 -0.118028
+-0.644459 -0.136984 -0.170829
+
+-0.638076 -0.207323 -0.130561
+-0.644459 -0.136984 -0.170829
+-0.610442 -0.198345 -0.118028
+
+-0.644459 -0.136984 -0.170829
+-0.638076 -0.207323 -0.130561
+-0.684343 -0.145462 -0.178019
+
+-0.667714 -0.216953 -0.136056
+-0.684343 -0.145462 -0.178019
+-0.638076 -0.207323 -0.130561
+
+-0.684343 -0.145462 -0.178019
+-0.667714 -0.216953 -0.136056
+-0.724773 -0.154055 -0.175612
+
+-0.697758 -0.226715 -0.134216
+-0.724773 -0.154055 -0.175612
+-0.667714 -0.216953 -0.136056
+
+-0.724773 -0.154055 -0.175612
+-0.697758 -0.226715 -0.134216
+-0.763571 -0.162302 -0.163737
+
+-0.726589 -0.236083 -0.125141
+-0.763571 -0.162302 -0.163737
+-0.697758 -0.226715 -0.134216
+
+-0.763571 -0.162302 -0.163737
+-0.726589 -0.236083 -0.125141
+-0.798644 -0.169757 -0.143035
+
+-0.752652 -0.244551 -0.109319
+-0.798644 -0.169757 -0.143035
+-0.726589 -0.236083 -0.125141
+
+-0.798644 -0.169757 -0.143035
+-0.752652 -0.244551 -0.109319
+-0.828101 -0.176018 -0.114622
+
+-0.774542 -0.251664 -0.0876034
+-0.828101 -0.176018 -0.114622
+-0.752652 -0.244551 -0.109319
+
+-0.828101 -0.176018 -0.114622
+-0.774542 -0.251664 -0.0876034
+-0.850356 -0.180749 -0.0800302
+
+-0.79108 -0.257037 -0.0611654
+-0.850356 -0.180749 -0.0800302
+-0.774542 -0.251664 -0.0876034
+
+-0.850356 -0.180749 -0.0800302
+-0.79108 -0.257037 -0.0611654
+-0.864207 -0.183693 -0.0411236
+
+-0.801373 -0.260382 -0.0314299
+-0.864207 -0.183693 -0.0411236
+-0.79108 -0.257037 -0.0611654
+
+-0.864207 -0.183693 -0.0411236
+-0.801373 -0.260382 -0.0314299
+-0.868909 -0.184692 0
+
+-0.804867 -0.261517 0
+-0.868909 -0.184692 0
+-0.801373 -0.260382 -0.0314299
+
+-0.804867 -0.261517 0
+-0.748467 -0.333239 0
+-0.801373 -0.260382 0.0314299
+
+-0.745776 -0.332041 0.0252061
+-0.801373 -0.260382 0.0314299
+-0.748467 -0.333239 0
+
+-0.801373 -0.260382 0.0314299
+-0.745776 -0.332041 0.0252061
+-0.79108 -0.257037 0.0611654
+
+-0.737846 -0.32851 0.0490534
+-0.79108 -0.257037 0.0611654
+-0.745776 -0.332041 0.0252061
+
+-0.79108 -0.257037 0.0611654
+-0.737846 -0.32851 0.0490534
+-0.774542 -0.251664 0.0876034
+
+-0.725107 -0.322838 0.0702562
+-0.774542 -0.251664 0.0876034
+-0.737846 -0.32851 0.0490534
+
+-0.774542 -0.251664 0.0876034
+-0.725107 -0.322838 0.0702562
+-0.752652 -0.244551 0.109319
+
+-0.708243 -0.31533 0.0876715
+-0.752652 -0.244551 0.109319
+-0.725107 -0.322838 0.0702562
+
+-0.752652 -0.244551 0.109319
+-0.708243 -0.31533 0.0876715
+-0.726589 -0.236083 0.125141
+
+-0.688166 -0.306391 0.10036
+-0.726589 -0.236083 0.125141
+-0.708243 -0.31533 0.0876715
+
+-0.726589 -0.236083 0.125141
+-0.688166 -0.306391 0.10036
+-0.697758 -0.226715 0.134216
+
+-0.665956 -0.296503 0.107639
+-0.697758 -0.226715 0.134216
+-0.688166 -0.306391 0.10036
+
+-0.697758 -0.226715 0.134216
+-0.665956 -0.296503 0.107639
+-0.667714 -0.216953 0.136056
+
+-0.642812 -0.286198 0.109114
+-0.667714 -0.216953 0.136056
+-0.665956 -0.296503 0.107639
+
+-0.667714 -0.216953 0.136056
+-0.642812 -0.286198 0.109114
+-0.638076 -0.207323 0.130561
+
+-0.61998 -0.276033 0.104708
+-0.638076 -0.207323 0.130561
+-0.642812 -0.286198 0.109114
+
+-0.638076 -0.207323 0.130561
+-0.61998 -0.276033 0.104708
+-0.610442 -0.198345 0.118028
+
+-0.598692 -0.266555 0.0946559
+-0.610442 -0.198345 0.118028
+-0.61998 -0.276033 0.104708
+
+-0.610442 -0.198345 0.118028
+-0.598692 -0.266555 0.0946559
+-0.586302 -0.190501 0.0991314
+
+-0.580096 -0.258275 0.0795014
+-0.586302 -0.190501 0.0991314
+-0.598692 -0.266555 0.0946559
+
+-0.586302 -0.190501 0.0991314
+-0.580096 -0.258275 0.0795014
+-0.566957 -0.184216 0.0748908
+
+-0.565194 -0.251641 0.0600609
+-0.566957 -0.184216 0.0748908
+-0.580096 -0.258275 0.0795014
+
+-0.566957 -0.184216 0.0748908
+-0.565194 -0.251641 0.0600609
+-0.553451 -0.179827 0.0466128
+
+-0.554789 -0.247008 0.0373825
+-0.553451 -0.179827 0.0466128
+-0.565194 -0.251641 0.0600609
+
+-0.553451 -0.179827 0.0466128
+-0.554789 -0.247008 0.0373825
+-0.54651 -0.177572 0.0158219
+
+-0.549443 -0.244628 0.0126889
+-0.54651 -0.177572 0.0158219
+-0.554789 -0.247008 0.0373825
+
+-0.54651 -0.177572 0.0158219
+-0.549443 -0.244628 0.0126889
+-0.54651 -0.177572 -0.0158219
+
+-0.549443 -0.244628 -0.0126889
+-0.54651 -0.177572 -0.0158219
+-0.549443 -0.244628 0.0126889
+
+-0.54651 -0.177572 -0.0158219
+-0.549443 -0.244628 -0.0126889
+-0.553451 -0.179827 -0.0466128
+
+-0.554789 -0.247008 -0.0373825
+-0.553451 -0.179827 -0.0466128
+-0.549443 -0.244628 -0.0126889
+
+-0.553451 -0.179827 -0.0466128
+-0.554789 -0.247008 -0.0373825
+-0.566957 -0.184216 -0.0748908
+
+-0.565194 -0.251641 -0.0600609
+-0.566957 -0.184216 -0.0748908
+-0.554789 -0.247008 -0.0373825
+
+-0.566957 -0.184216 -0.0748908
+-0.565194 -0.251641 -0.0600609
+-0.586302 -0.190501 -0.0991314
+
+-0.580096 -0.258275 -0.0795014
+-0.586302 -0.190501 -0.0991314
+-0.565194 -0.251641 -0.0600609
+
+-0.586302 -0.190501 -0.0991314
+-0.580096 -0.258275 -0.0795014
+-0.610442 -0.198345 -0.118028
+
+-0.598692 -0.266555 -0.0946559
+-0.610442 -0.198345 -0.118028
+-0.580096 -0.258275 -0.0795014
+
+-0.610442 -0.198345 -0.118028
+-0.598692 -0.266555 -0.0946559
+-0.638076 -0.207323 -0.130561
+
+-0.61998 -0.276033 -0.104708
+-0.638076 -0.207323 -0.130561
+-0.598692 -0.266555 -0.0946559
+
+-0.638076 -0.207323 -0.130561
+-0.61998 -0.276033 -0.104708
+-0.667714 -0.216953 -0.136056
+
+-0.642812 -0.286198 -0.109114
+-0.667714 -0.216953 -0.136056
+-0.61998 -0.276033 -0.104708
+
+-0.667714 -0.216953 -0.136056
+-0.642812 -0.286198 -0.109114
+-0.697758 -0.226715 -0.134216
+
+-0.665956 -0.296503 -0.107639
+-0.697758 -0.226715 -0.134216
+-0.642812 -0.286198 -0.109114
+
+-0.697758 -0.226715 -0.134216
+-0.665956 -0.296503 -0.107639
+-0.726589 -0.236083 -0.125141
+
+-0.688166 -0.306391 -0.10036
+-0.726589 -0.236083 -0.125141
+-0.665956 -0.296503 -0.107639
+
+-0.726589 -0.236083 -0.125141
+-0.688166 -0.306391 -0.10036
+-0.752652 -0.244551 -0.109319
+
+-0.708243 -0.31533 -0.0876715
+-0.752652 -0.244551 -0.109319
+-0.688166 -0.306391 -0.10036
+
+-0.752652 -0.244551 -0.109319
+-0.708243 -0.31533 -0.0876715
+-0.774542 -0.251664 -0.0876034
+
+-0.725107 -0.322838 -0.0702562
+-0.774542 -0.251664 -0.0876034
+-0.708243 -0.31533 -0.0876715
+
+-0.774542 -0.251664 -0.0876034
+-0.725107 -0.322838 -0.0702562
+-0.79108 -0.257037 -0.0611654
+
+-0.737846 -0.32851 -0.0490534
+-0.79108 -0.257037 -0.0611654
+-0.725107 -0.322838 -0.0702562
+
+-0.79108 -0.257037 -0.0611654
+-0.737846 -0.32851 -0.0490534
+-0.801373 -0.260382 -0.0314299
+
+-0.745776 -0.332041 -0.0252061
+-0.801373 -0.260382 -0.0314299
+-0.737846 -0.32851 -0.0490534
+
+-0.801373 -0.260382 -0.0314299
+-0.745776 -0.332041 -0.0252061
+-0.804867 -0.261517 0
+
+-0.748467 -0.333239 0
+-0.804867 -0.261517 0
+-0.745776 -0.332041 -0.0252061
+
+-0.748467 -0.333239 0
+-0.701481 -0.405 0
+-0.745776 -0.332041 0.0252061
+
+-0.699146 -0.403652 0.0230616
+-0.745776 -0.332041 0.0252061
+-0.701481 -0.405 0
+
+-0.745776 -0.332041 0.0252061
+-0.699146 -0.403652 0.0230616
+-0.737846 -0.32851 0.0490534
+
+-0.692269 -0.399682 0.0448799
+-0.737846 -0.32851 0.0490534
+-0.699146 -0.403652 0.0230616
+
+-0.737846 -0.32851 0.0490534
+-0.692269 -0.399682 0.0448799
+-0.725107 -0.322838 0.0702562
+
+-0.681219 -0.393302 0.0642788
+-0.725107 -0.322838 0.0702562
+-0.692269 -0.399682 0.0448799
+
+-0.725107 -0.322838 0.0702562
+-0.681219 -0.393302 0.0642788
+-0.708243 -0.31533 0.0876715
+
+-0.666593 -0.384858 0.0802123
+-0.708243 -0.31533 0.0876715
+-0.681219 -0.393302 0.0642788
+
+-0.708243 -0.31533 0.0876715
+-0.666593 -0.384858 0.0802123
+-0.688166 -0.306391 0.10036
+
+-0.64918 -0.374804 0.0918216
+-0.688166 -0.306391 0.10036
+-0.666593 -0.384858 0.0802123
+
+-0.688166 -0.306391 0.10036
+-0.64918 -0.374804 0.0918216
+-0.665956 -0.296503 0.107639
+
+-0.629916 -0.363682 0.0984808
+-0.665956 -0.296503 0.107639
+-0.64918 -0.374804 0.0918216
+
+-0.665956 -0.296503 0.107639
+-0.629916 -0.363682 0.0984808
+-0.642812 -0.286198 0.109114
+
+-0.609843 -0.352093 0.0998308
+-0.642812 -0.286198 0.109114
+-0.629916 -0.363682 0.0984808
+
+-0.642812 -0.286198 0.109114
+-0.609843 -0.352093 0.0998308
+-0.61998 -0.276033 0.104708
+
+-0.59004 -0.34066 0.095799
+-0.61998 -0.276033 0.104708
+-0.609843 -0.352093 0.0998308
+
+-0.61998 -0.276033 0.104708
+-0.59004 -0.34066 0.095799
+-0.598692 -0.266555 0.0946559
+
+-0.571577 -0.33 0.0866025
+-0.598692 -0.266555 0.0946559
+-0.59004 -0.34066 0.095799
+
+-0.598692 -0.266555 0.0946559
+-0.571577 -0.33 0.0866025
+-0.580096 -0.258275 0.0795014
+
+-0.555448 -0.320688 0.0727374
+-0.580096 -0.258275 0.0795014
+-0.571577 -0.33 0.0866025
+
+-0.580096 -0.258275 0.0795014
+-0.555448 -0.320688 0.0727374
+-0.565194 -0.251641 0.0600609
+
+-0.542523 -0.313226 0.0549509
+-0.565194 -0.251641 0.0600609
+-0.555448 -0.320688 0.0727374
+
+-0.565194 -0.251641 0.0600609
+-0.542523 -0.313226 0.0549509
+-0.554789 -0.247008 0.0373825
+
+-0.533498 -0.308015 0.034202
+-0.554789 -0.247008 0.0373825
+-0.542523 -0.313226 0.0549509
+
+-0.554789 -0.247008 0.0373825
+-0.533498 -0.308015 0.034202
+-0.549443 -0.244628 0.0126889
+
+-0.528861 -0.305338 0.0116093
+-0.549443 -0.244628 0.0126889
+-0.533498 -0.308015 0.034202
+
+-0.549443 -0.244628 0.0126889
+-0.528861 -0.305338 0.0116093
+-0.549443 -0.244628 -0.0126889
+
+-0.528861 -0.305338 -0.0116093
+-0.549443 -0.244628 -0.0126889
+-0.528861 -0.305338 0.0116093
+
+-0.549443 -0.244628 -0.0126889
+-0.528861 -0.305338 -0.0116093
+-0.554789 -0.247008 -0.0373825
+
+-0.533498 -0.308015 -0.034202
+-0.554789 -0.247008 -0.0373825
+-0.528861 -0.305338 -0.0116093
+
+-0.554789 -0.247008 -0.0373825
+-0.533498 -0.308015 -0.034202
+-0.565194 -0.251641 -0.0600609
+
+-0.542523 -0.313226 -0.0549509
+-0.565194 -0.251641 -0.0600609
+-0.533498 -0.308015 -0.034202
+
+-0.565194 -0.251641 -0.0600609
+-0.542523 -0.313226 -0.0549509
+-0.580096 -0.258275 -0.0795014
+
+-0.555448 -0.320688 -0.0727374
+-0.580096 -0.258275 -0.0795014
+-0.542523 -0.313226 -0.0549509
+
+-0.580096 -0.258275 -0.0795014
+-0.555448 -0.320688 -0.0727374
+-0.598692 -0.266555 -0.0946559
+
+-0.571577 -0.33 -0.0866025
+-0.598692 -0.266555 -0.0946559
+-0.555448 -0.320688 -0.0727374
+
+-0.598692 -0.266555 -0.0946559
+-0.571577 -0.33 -0.0866025
+-0.61998 -0.276033 -0.104708
+
+-0.59004 -0.34066 -0.095799
+-0.61998 -0.276033 -0.104708
+-0.571577 -0.33 -0.0866025
+
+-0.61998 -0.276033 -0.104708
+-0.59004 -0.34066 -0.095799
+-0.642812 -0.286198 -0.109114
+
+-0.609843 -0.352093 -0.0998308
+-0.642812 -0.286198 -0.109114
+-0.59004 -0.34066 -0.095799
+
+-0.642812 -0.286198 -0.109114
+-0.609843 -0.352093 -0.0998308
+-0.665956 -0.296503 -0.107639
+
+-0.629916 -0.363682 -0.0984808
+-0.665956 -0.296503 -0.107639
+-0.609843 -0.352093 -0.0998308
+
+-0.665956 -0.296503 -0.107639
+-0.629916 -0.363682 -0.0984808
+-0.688166 -0.306391 -0.10036
+
+-0.64918 -0.374804 -0.0918216
+-0.688166 -0.306391 -0.10036
+-0.629916 -0.363682 -0.0984808
+
+-0.688166 -0.306391 -0.10036
+-0.64918 -0.374804 -0.0918216
+-0.708243 -0.31533 -0.0876715
+
+-0.666593 -0.384858 -0.0802123
+-0.708243 -0.31533 -0.0876715
+-0.64918 -0.374804 -0.0918216
+
+-0.708243 -0.31533 -0.0876715
+-0.666593 -0.384858 -0.0802123
+-0.725107 -0.322838 -0.0702562
+
+-0.681219 -0.393302 -0.0642788
+-0.725107 -0.322838 -0.0702562
+-0.666593 -0.384858 -0.0802123
+
+-0.725107 -0.322838 -0.0702562
+-0.681219 -0.393302 -0.0642788
+-0.737846 -0.32851 -0.0490534
+
+-0.692269 -0.399682 -0.0448799
+-0.737846 -0.32851 -0.0490534
+-0.681219 -0.393302 -0.0642788
+
+-0.737846 -0.32851 -0.0490534
+-0.692269 -0.399682 -0.0448799
+-0.745776 -0.332041 -0.0252061
+
+-0.699146 -0.403652 -0.0230616
+-0.745776 -0.332041 -0.0252061
+-0.692269 -0.399682 -0.0448799
+
+-0.745776 -0.332041 -0.0252061
+-0.699146 -0.403652 -0.0230616
+-0.748467 -0.333239 0
+
+-0.701481 -0.405 0
+-0.748467 -0.333239 0
+-0.699146 -0.403652 -0.0230616
+
+-0.701481 -0.405 0
+-0.662827 -0.481572 0
+-0.699146 -0.403652 0.0230616
+
+-0.660444 -0.47984 0.0252061
+-0.699146 -0.403652 0.0230616
+-0.662827 -0.481572 0
+
+-0.699146 -0.403652 0.0230616
+-0.660444 -0.47984 0.0252061
+-0.692269 -0.399682 0.0448799
+
+-0.653421 -0.474739 0.0490534
+-0.692269 -0.399682 0.0448799
+-0.660444 -0.47984 0.0252061
+
+-0.692269 -0.399682 0.0448799
+-0.653421 -0.474739 0.0490534
+-0.681219 -0.393302 0.0642788
+
+-0.64214 -0.466542 0.0702562
+-0.681219 -0.393302 0.0642788
+-0.653421 -0.474739 0.0490534
+
+-0.681219 -0.393302 0.0642788
+-0.64214 -0.466542 0.0702562
+-0.666593 -0.384858 0.0802123
+
+-0.627206 -0.455692 0.0876715
+-0.666593 -0.384858 0.0802123
+-0.64214 -0.466542 0.0702562
+
+-0.666593 -0.384858 0.0802123
+-0.627206 -0.455692 0.0876715
+-0.64918 -0.374804 0.0918216
+
+-0.609425 -0.442773 0.10036
+-0.64918 -0.374804 0.0918216
+-0.627206 -0.455692 0.0876715
+
+-0.64918 -0.374804 0.0918216
+-0.609425 -0.442773 0.10036
+-0.629916 -0.363682 0.0984808
+
+-0.589757 -0.428483 0.107639
+-0.629916 -0.363682 0.0984808
+-0.609425 -0.442773 0.10036
+
+-0.629916 -0.363682 0.0984808
+-0.589757 -0.428483 0.107639
+-0.609843 -0.352093 0.0998308
+
+-0.569261 -0.413592 0.109114
+-0.609843 -0.352093 0.0998308
+-0.589757 -0.428483 0.107639
+
+-0.609843 -0.352093 0.0998308
+-0.569261 -0.413592 0.109114
+-0.59004 -0.34066 0.095799
+
+-0.549042 -0.398902 0.104708
+-0.59004 -0.34066 0.095799
+-0.569261 -0.413592 0.109114
+
+-0.59004 -0.34066 0.095799
+-0.549042 -0.398902 0.104708
+-0.571577 -0.33 0.0866025
+
+-0.53019 -0.385205 0.0946559
+-0.571577 -0.33 0.0866025
+-0.549042 -0.398902 0.104708
+
+-0.571577 -0.33 0.0866025
+-0.53019 -0.385205 0.0946559
+-0.555448 -0.320688 0.0727374
+
+-0.513721 -0.37324 0.0795014
+-0.555448 -0.320688 0.0727374
+-0.53019 -0.385205 0.0946559
+
+-0.555448 -0.320688 0.0727374
+-0.513721 -0.37324 0.0795014
+-0.542523 -0.313226 0.0549509
+
+-0.500524 -0.363652 0.0600609
+-0.542523 -0.313226 0.0549509
+-0.513721 -0.37324 0.0795014
+
+-0.542523 -0.313226 0.0549509
+-0.500524 -0.363652 0.0600609
+-0.533498 -0.308015 0.034202
+
+-0.49131 -0.356957 0.0373825
+-0.533498 -0.308015 0.034202
+-0.500524 -0.363652 0.0600609
+
+-0.533498 -0.308015 0.034202
+-0.49131 -0.356957 0.0373825
+-0.528861 -0.305338 0.0116093
+
+-0.486575 -0.353517 0.0126889
+-0.528861 -0.305338 0.0116093
+-0.49131 -0.356957 0.0373825
+
+-0.528861 -0.305338 0.0116093
+-0.486575 -0.353517 0.0126889
+-0.528861 -0.305338 -0.0116093
+
+-0.486575 -0.353517 -0.0126889
+-0.528861 -0.305338 -0.0116093
+-0.486575 -0.353517 0.0126889
+
+-0.528861 -0.305338 -0.0116093
+-0.486575 -0.353517 -0.0126889
+-0.533498 -0.308015 -0.034202
+
+-0.49131 -0.356957 -0.0373825
+-0.533498 -0.308015 -0.034202
+-0.486575 -0.353517 -0.0126889
+
+-0.533498 -0.308015 -0.034202
+-0.49131 -0.356957 -0.0373825
+-0.542523 -0.313226 -0.0549509
+
+-0.500524 -0.363652 -0.0600609
+-0.542523 -0.313226 -0.0549509
+-0.49131 -0.356957 -0.0373825
+
+-0.542523 -0.313226 -0.0549509
+-0.500524 -0.363652 -0.0600609
+-0.555448 -0.320688 -0.0727374
+
+-0.513721 -0.37324 -0.0795014
+-0.555448 -0.320688 -0.0727374
+-0.500524 -0.363652 -0.0600609
+
+-0.555448 -0.320688 -0.0727374
+-0.513721 -0.37324 -0.0795014
+-0.571577 -0.33 -0.0866025
+
+-0.53019 -0.385205 -0.0946559
+-0.571577 -0.33 -0.0866025
+-0.513721 -0.37324 -0.0795014
+
+-0.571577 -0.33 -0.0866025
+-0.53019 -0.385205 -0.0946559
+-0.59004 -0.34066 -0.095799
+
+-0.549042 -0.398902 -0.104708
+-0.59004 -0.34066 -0.095799
+-0.53019 -0.385205 -0.0946559
+
+-0.59004 -0.34066 -0.095799
+-0.549042 -0.398902 -0.104708
+-0.609843 -0.352093 -0.0998308
+
+-0.569261 -0.413592 -0.109114
+-0.609843 -0.352093 -0.0998308
+-0.549042 -0.398902 -0.104708
+
+-0.609843 -0.352093 -0.0998308
+-0.569261 -0.413592 -0.109114
+-0.629916 -0.363682 -0.0984808
+
+-0.589757 -0.428483 -0.107639
+-0.629916 -0.363682 -0.0984808
+-0.569261 -0.413592 -0.109114
+
+-0.629916 -0.363682 -0.0984808
+-0.589757 -0.428483 -0.107639
+-0.64918 -0.374804 -0.0918216
+
+-0.609425 -0.442773 -0.10036
+-0.64918 -0.374804 -0.0918216
+-0.589757 -0.428483 -0.107639
+
+-0.64918 -0.374804 -0.0918216
+-0.609425 -0.442773 -0.10036
+-0.666593 -0.384858 -0.0802123
+
+-0.627206 -0.455692 -0.0876715
+-0.666593 -0.384858 -0.0802123
+-0.609425 -0.442773 -0.10036
+
+-0.666593 -0.384858 -0.0802123
+-0.627206 -0.455692 -0.0876715
+-0.681219 -0.393302 -0.0642788
+
+-0.64214 -0.466542 -0.0702562
+-0.681219 -0.393302 -0.0642788
+-0.627206 -0.455692 -0.0876715
+
+-0.681219 -0.393302 -0.0642788
+-0.64214 -0.466542 -0.0702562
+-0.692269 -0.399682 -0.0448799
+
+-0.653421 -0.474739 -0.0490534
+-0.692269 -0.399682 -0.0448799
+-0.64214 -0.466542 -0.0702562
+
+-0.692269 -0.399682 -0.0448799
+-0.653421 -0.474739 -0.0490534
+-0.699146 -0.403652 -0.0230616
+
+-0.660444 -0.47984 -0.0252061
+-0.699146 -0.403652 -0.0230616
+-0.653421 -0.474739 -0.0490534
+
+-0.699146 -0.403652 -0.0230616
+-0.660444 -0.47984 -0.0252061
+-0.701481 -0.405 0
+
+-0.662827 -0.481572 0
+-0.701481 -0.405 0
+-0.660444 -0.47984 -0.0252061
+
+-0.662827 -0.481572 0
+-0.628914 -0.566276 0
+-0.660444 -0.47984 0.0252061
+
+-0.626184 -0.563818 0.0314299
+-0.660444 -0.47984 0.0252061
+-0.628914 -0.566276 0
+
+-0.660444 -0.47984 0.0252061
+-0.626184 -0.563818 0.0314299
+-0.653421 -0.474739 0.0490534
+
+-0.618141 -0.556576 0.0611654
+-0.653421 -0.474739 0.0490534
+-0.626184 -0.563818 0.0314299
+
+-0.653421 -0.474739 0.0490534
+-0.618141 -0.556576 0.0611654
+-0.64214 -0.466542 0.0702562
+
+-0.605218 -0.544941 0.0876034
+-0.64214 -0.466542 0.0702562
+-0.618141 -0.556576 0.0611654
+
+-0.64214 -0.466542 0.0702562
+-0.605218 -0.544941 0.0876034
+-0.627206 -0.455692 0.0876715
+
+-0.588114 -0.52954 0.109319
+-0.627206 -0.455692 0.0876715
+-0.605218 -0.544941 0.0876034
+
+-0.627206 -0.455692 0.0876715
+-0.588114 -0.52954 0.109319
+-0.609425 -0.442773 0.10036
+
+-0.567748 -0.511203 0.125141
+-0.609425 -0.442773 0.10036
+-0.588114 -0.52954 0.109319
+
+-0.609425 -0.442773 0.10036
+-0.567748 -0.511203 0.125141
+-0.589757 -0.428483 0.107639
+
+-0.54522 -0.490918 0.134216
+-0.589757 -0.428483 0.107639
+-0.567748 -0.511203 0.125141
+
+-0.589757 -0.428483 0.107639
+-0.54522 -0.490918 0.134216
+-0.569261 -0.413592 0.109114
+
+-0.521744 -0.46978 0.136056
+-0.569261 -0.413592 0.109114
+-0.54522 -0.490918 0.134216
+
+-0.569261 -0.413592 0.109114
+-0.521744 -0.46978 0.136056
+-0.549042 -0.398902 0.104708
+
+-0.498585 -0.448928 0.130561
+-0.549042 -0.398902 0.104708
+-0.521744 -0.46978 0.136056
+
+-0.549042 -0.398902 0.104708
+-0.498585 -0.448928 0.130561
+-0.53019 -0.385205 0.0946559
+
+-0.476992 -0.429486 0.118028
+-0.53019 -0.385205 0.0946559
+-0.498585 -0.448928 0.130561
+
+-0.53019 -0.385205 0.0946559
+-0.476992 -0.429486 0.118028
+-0.513721 -0.37324 0.0795014
+
+-0.45813 -0.412502 0.0991314
+-0.513721 -0.37324 0.0795014
+-0.476992 -0.429486 0.118028
+
+-0.513721 -0.37324 0.0795014
+-0.45813 -0.412502 0.0991314
+-0.500524 -0.363652 0.0600609
+
+-0.443014 -0.398892 0.0748908
+-0.500524 -0.363652 0.0600609
+-0.45813 -0.412502 0.0991314
+
+-0.500524 -0.363652 0.0600609
+-0.443014 -0.398892 0.0748908
+-0.49131 -0.356957 0.0373825
+
+-0.43246 -0.389389 0.0466128
+-0.49131 -0.356957 0.0373825
+-0.443014 -0.398892 0.0748908
+
+-0.49131 -0.356957 0.0373825
+-0.43246 -0.389389 0.0466128
+-0.486575 -0.353517 0.0126889
+
+-0.427037 -0.384506 0.0158219
+-0.486575 -0.353517 0.0126889
+-0.43246 -0.389389 0.0466128
+
+-0.486575 -0.353517 0.0126889
+-0.427037 -0.384506 0.0158219
+-0.486575 -0.353517 -0.0126889
+
+-0.427037 -0.384506 -0.0158219
+-0.486575 -0.353517 -0.0126889
+-0.427037 -0.384506 0.0158219
+
+-0.486575 -0.353517 -0.0126889
+-0.427037 -0.384506 -0.0158219
+-0.49131 -0.356957 -0.0373825
+
+-0.43246 -0.389389 -0.0466128
+-0.49131 -0.356957 -0.0373825
+-0.427037 -0.384506 -0.0158219
+
+-0.49131 -0.356957 -0.0373825
+-0.43246 -0.389389 -0.0466128
+-0.500524 -0.363652 -0.0600609
+
+-0.443014 -0.398892 -0.0748908
+-0.500524 -0.363652 -0.0600609
+-0.43246 -0.389389 -0.0466128
+
+-0.500524 -0.363652 -0.0600609
+-0.443014 -0.398892 -0.0748908
+-0.513721 -0.37324 -0.0795014
+
+-0.45813 -0.412502 -0.0991314
+-0.513721 -0.37324 -0.0795014
+-0.443014 -0.398892 -0.0748908
+
+-0.513721 -0.37324 -0.0795014
+-0.45813 -0.412502 -0.0991314
+-0.53019 -0.385205 -0.0946559
+
+-0.476992 -0.429486 -0.118028
+-0.53019 -0.385205 -0.0946559
+-0.45813 -0.412502 -0.0991314
+
+-0.53019 -0.385205 -0.0946559
+-0.476992 -0.429486 -0.118028
+-0.549042 -0.398902 -0.104708
+
+-0.498585 -0.448928 -0.130561
+-0.549042 -0.398902 -0.104708
+-0.476992 -0.429486 -0.118028
+
+-0.549042 -0.398902 -0.104708
+-0.498585 -0.448928 -0.130561
+-0.569261 -0.413592 -0.109114
+
+-0.521744 -0.46978 -0.136056
+-0.569261 -0.413592 -0.109114
+-0.498585 -0.448928 -0.130561
+
+-0.569261 -0.413592 -0.109114
+-0.521744 -0.46978 -0.136056
+-0.589757 -0.428483 -0.107639
+
+-0.54522 -0.490918 -0.134216
+-0.589757 -0.428483 -0.107639
+-0.521744 -0.46978 -0.136056
+
+-0.589757 -0.428483 -0.107639
+-0.54522 -0.490918 -0.134216
+-0.609425 -0.442773 -0.10036
+
+-0.567748 -0.511203 -0.125141
+-0.609425 -0.442773 -0.10036
+-0.54522 -0.490918 -0.134216
+
+-0.609425 -0.442773 -0.10036
+-0.567748 -0.511203 -0.125141
+-0.627206 -0.455692 -0.0876715
+
+-0.588114 -0.52954 -0.109319
+-0.627206 -0.455692 -0.0876715
+-0.567748 -0.511203 -0.125141
+
+-0.627206 -0.455692 -0.0876715
+-0.588114 -0.52954 -0.109319
+-0.64214 -0.466542 -0.0702562
+
+-0.605218 -0.544941 -0.0876034
+-0.64214 -0.466542 -0.0702562
+-0.588114 -0.52954 -0.109319
+
+-0.64214 -0.466542 -0.0702562
+-0.605218 -0.544941 -0.0876034
+-0.653421 -0.474739 -0.0490534
+
+-0.618141 -0.556576 -0.0611654
+-0.653421 -0.474739 -0.0490534
+-0.605218 -0.544941 -0.0876034
+
+-0.653421 -0.474739 -0.0490534
+-0.618141 -0.556576 -0.0611654
+-0.660444 -0.47984 -0.0252061
+
+-0.626184 -0.563818 -0.0314299
+-0.660444 -0.47984 -0.0252061
+-0.618141 -0.556576 -0.0611654
+
+-0.660444 -0.47984 -0.0252061
+-0.626184 -0.563818 -0.0314299
+-0.662827 -0.481572 0
+
+-0.628914 -0.566276 0
+-0.662827 -0.481572 0
+-0.626184 -0.563818 -0.0314299
+
+-0.628914 -0.566276 0
+-0.594403 -0.660151 0
+-0.626184 -0.563818 0.0314299
+
+-0.591186 -0.656579 0.0411236
+-0.626184 -0.563818 0.0314299
+-0.594403 -0.660151 0
+
+-0.626184 -0.563818 0.0314299
+-0.591186 -0.656579 0.0411236
+-0.618141 -0.556576 0.0611654
+
+-0.581711 -0.646055 0.0800302
+-0.618141 -0.556576 0.0611654
+-0.591186 -0.656579 0.0411236
+
+-0.618141 -0.556576 0.0611654
+-0.581711 -0.646055 0.0800302
+-0.605218 -0.544941 0.0876034
+
+-0.566487 -0.629148 0.114622
+-0.605218 -0.544941 0.0876034
+-0.581711 -0.646055 0.0800302
+
+-0.605218 -0.544941 0.0876034
+-0.566487 -0.629148 0.114622
+-0.588114 -0.52954 0.109319
+
+-0.546336 -0.606767 0.143035
+-0.588114 -0.52954 0.109319
+-0.566487 -0.629148 0.114622
+
+-0.588114 -0.52954 0.109319
+-0.546336 -0.606767 0.143035
+-0.567748 -0.511203 0.125141
+
+-0.522343 -0.580121 0.163737
+-0.567748 -0.511203 0.125141
+-0.546336 -0.606767 0.143035
+
+-0.567748 -0.511203 0.125141
+-0.522343 -0.580121 0.163737
+-0.54522 -0.490918 0.134216
+
+-0.495802 -0.550644 0.175612
+-0.54522 -0.490918 0.134216
+-0.522343 -0.580121 0.163737
+
+-0.54522 -0.490918 0.134216
+-0.495802 -0.550644 0.175612
+-0.521744 -0.46978 0.136056
+
+-0.468145 -0.519928 0.178019
+-0.521744 -0.46978 0.136056
+-0.495802 -0.550644 0.175612
+
+-0.521744 -0.46978 0.136056
+-0.468145 -0.519928 0.178019
+-0.498585 -0.448928 0.130561
+
+-0.440861 -0.489626 0.170829
+-0.498585 -0.448928 0.130561
+-0.468145 -0.519928 0.178019
+
+-0.498585 -0.448928 0.130561
+-0.440861 -0.489626 0.170829
+-0.476992 -0.429486 0.118028
+
+-0.415423 -0.461374 0.15443
+-0.476992 -0.429486 0.118028
+-0.440861 -0.489626 0.170829
+
+-0.476992 -0.429486 0.118028
+-0.415423 -0.461374 0.15443
+-0.45813 -0.412502 0.0991314
+
+-0.3932 -0.436693 0.129706
+-0.45813 -0.412502 0.0991314
+-0.415423 -0.461374 0.15443
+
+-0.45813 -0.412502 0.0991314
+-0.3932 -0.436693 0.129706
+-0.443014 -0.398892 0.0748908
+
+-0.375392 -0.416916 0.0979889
+-0.443014 -0.398892 0.0748908
+-0.3932 -0.436693 0.129706
+
+-0.443014 -0.398892 0.0748908
+-0.375392 -0.416916 0.0979889
+-0.43246 -0.389389 0.0466128
+
+-0.362959 -0.403106 0.0609893
+-0.43246 -0.389389 0.0466128
+-0.375392 -0.416916 0.0979889
+
+-0.43246 -0.389389 0.0466128
+-0.362959 -0.403106 0.0609893
+-0.427037 -0.384506 0.0158219
+
+-0.35657 -0.396011 0.0207018
+-0.427037 -0.384506 0.0158219
+-0.362959 -0.403106 0.0609893
+
+-0.427037 -0.384506 0.0158219
+-0.35657 -0.396011 0.0207018
+-0.427037 -0.384506 -0.0158219
+
+-0.35657 -0.396011 -0.0207018
+-0.427037 -0.384506 -0.0158219
+-0.35657 -0.396011 0.0207018
+
+-0.427037 -0.384506 -0.0158219
+-0.35657 -0.396011 -0.0207018
+-0.43246 -0.389389 -0.0466128
+
+-0.362959 -0.403106 -0.0609893
+-0.43246 -0.389389 -0.0466128
+-0.35657 -0.396011 -0.0207018
+
+-0.43246 -0.389389 -0.0466128
+-0.362959 -0.403106 -0.0609893
+-0.443014 -0.398892 -0.0748908
+
+-0.375392 -0.416916 -0.0979889
+-0.443014 -0.398892 -0.0748908
+-0.362959 -0.403106 -0.0609893
+
+-0.443014 -0.398892 -0.0748908
+-0.375392 -0.416916 -0.0979889
+-0.45813 -0.412502 -0.0991314
+
+-0.3932 -0.436693 -0.129706
+-0.45813 -0.412502 -0.0991314
+-0.375392 -0.416916 -0.0979889
+
+-0.45813 -0.412502 -0.0991314
+-0.3932 -0.436693 -0.129706
+-0.476992 -0.429486 -0.118028
+
+-0.415423 -0.461374 -0.15443
+-0.476992 -0.429486 -0.118028
+-0.3932 -0.436693 -0.129706
+
+-0.476992 -0.429486 -0.118028
+-0.415423 -0.461374 -0.15443
+-0.498585 -0.448928 -0.130561
+
+-0.440861 -0.489626 -0.170829
+-0.498585 -0.448928 -0.130561
+-0.415423 -0.461374 -0.15443
+
+-0.498585 -0.448928 -0.130561
+-0.440861 -0.489626 -0.170829
+-0.521744 -0.46978 -0.136056
+
+-0.468145 -0.519928 -0.178019
+-0.521744 -0.46978 -0.136056
+-0.440861 -0.489626 -0.170829
+
+-0.521744 -0.46978 -0.136056
+-0.468145 -0.519928 -0.178019
+-0.54522 -0.490918 -0.134216
+
+-0.495802 -0.550644 -0.175612
+-0.54522 -0.490918 -0.134216
+-0.468145 -0.519928 -0.178019
+
+-0.54522 -0.490918 -0.134216
+-0.495802 -0.550644 -0.175612
+-0.567748 -0.511203 -0.125141
+
+-0.522343 -0.580121 -0.163737
+-0.567748 -0.511203 -0.125141
+-0.495802 -0.550644 -0.175612
+
+-0.567748 -0.511203 -0.125141
+-0.522343 -0.580121 -0.163737
+-0.588114 -0.52954 -0.109319
+
+-0.546336 -0.606767 -0.143035
+-0.588114 -0.52954 -0.109319
+-0.522343 -0.580121 -0.163737
+
+-0.588114 -0.52954 -0.109319
+-0.546336 -0.606767 -0.143035
+-0.605218 -0.544941 -0.0876034
+
+-0.566487 -0.629148 -0.114622
+-0.605218 -0.544941 -0.0876034
+-0.546336 -0.606767 -0.143035
+
+-0.605218 -0.544941 -0.0876034
+-0.566487 -0.629148 -0.114622
+-0.618141 -0.556576 -0.0611654
+
+-0.581711 -0.646055 -0.0800302
+-0.618141 -0.556576 -0.0611654
+-0.566487 -0.629148 -0.114622
+
+-0.618141 -0.556576 -0.0611654
+-0.581711 -0.646055 -0.0800302
+-0.626184 -0.563818 -0.0314299
+
+-0.591186 -0.656579 -0.0411236
+-0.626184 -0.563818 -0.0314299
+-0.581711 -0.646055 -0.0800302
+
+-0.626184 -0.563818 -0.0314299
+-0.591186 -0.656579 -0.0411236
+-0.628914 -0.566276 0
+
+-0.594403 -0.660151 0
+-0.628914 -0.566276 0
+-0.591186 -0.656579 -0.0411236
+
+-0.594403 -0.660151 0
+-0.553274 -0.761517 0
+-0.591186 -0.656579 0.0411236
+
+-0.54961 -0.756473 0.0533384
+-0.591186 -0.656579 0.0411236
+-0.553274 -0.761517 0
+
+-0.591186 -0.656579 0.0411236
+-0.54961 -0.756473 0.0533384
+-0.581711 -0.646055 0.0800302
+
+-0.538814 -0.741614 0.103801
+-0.581711 -0.646055 0.0800302
+-0.54961 -0.756473 0.0533384
+
+-0.581711 -0.646055 0.0800302
+-0.538814 -0.741614 0.103801
+-0.566487 -0.629148 0.114622
+
+-0.521469 -0.71774 0.148668
+-0.566487 -0.629148 0.114622
+-0.538814 -0.741614 0.103801
+
+-0.566487 -0.629148 0.114622
+-0.521469 -0.71774 0.148668
+-0.546336 -0.606767 0.143035
+
+-0.498509 -0.686139 0.18552
+-0.546336 -0.606767 0.143035
+-0.521469 -0.71774 0.148668
+
+-0.546336 -0.606767 0.143035
+-0.498509 -0.686139 0.18552
+-0.522343 -0.580121 0.163737
+
+-0.471173 -0.648515 0.212371
+-0.522343 -0.580121 0.163737
+-0.498509 -0.686139 0.18552
+
+-0.522343 -0.580121 0.163737
+-0.471173 -0.648515 0.212371
+-0.495802 -0.550644 0.175612
+
+-0.440934 -0.606894 0.227773
+-0.495802 -0.550644 0.175612
+-0.471173 -0.648515 0.212371
+
+-0.495802 -0.550644 0.175612
+-0.440934 -0.606894 0.227773
+-0.468145 -0.519928 0.178019
+
+-0.409423 -0.563522 0.230895
+-0.468145 -0.519928 0.178019
+-0.440934 -0.606894 0.227773
+
+-0.468145 -0.519928 0.178019
+-0.409423 -0.563522 0.230895
+-0.440861 -0.489626 0.170829
+
+-0.378338 -0.520737 0.22157
+-0.440861 -0.489626 0.170829
+-0.409423 -0.563522 0.230895
+
+-0.440861 -0.489626 0.170829
+-0.378338 -0.520737 0.22157
+-0.415423 -0.461374 0.15443
+
+-0.349354 -0.480845 0.2003
+-0.415423 -0.461374 0.15443
+-0.378338 -0.520737 0.22157
+
+-0.415423 -0.461374 0.15443
+-0.349354 -0.480845 0.2003
+-0.3932 -0.436693 0.129706
+
+-0.324035 -0.445996 0.168232
+-0.3932 -0.436693 0.129706
+-0.349354 -0.480845 0.2003
+
+-0.3932 -0.436693 0.129706
+-0.324035 -0.445996 0.168232
+-0.375392 -0.416916 0.0979889
+
+-0.303746 -0.41807 0.127094
+-0.375392 -0.416916 0.0979889
+-0.324035 -0.445996 0.168232
+
+-0.375392 -0.416916 0.0979889
+-0.303746 -0.41807 0.127094
+-0.362959 -0.403106 0.0609893
+
+-0.289579 -0.398572 0.0791047
+-0.362959 -0.403106 0.0609893
+-0.303746 -0.41807 0.127094
+
+-0.362959 -0.403106 0.0609893
+-0.289579 -0.398572 0.0791047
+-0.35657 -0.396011 0.0207018
+
+-0.2823 -0.388552 0.0268508
+-0.35657 -0.396011 0.0207018
+-0.289579 -0.398572 0.0791047
+
+-0.35657 -0.396011 0.0207018
+-0.2823 -0.388552 0.0268508
+-0.35657 -0.396011 -0.0207018
+
+-0.2823 -0.388552 -0.0268508
+-0.35657 -0.396011 -0.0207018
+-0.2823 -0.388552 0.0268508
+
+-0.35657 -0.396011 -0.0207018
+-0.2823 -0.388552 -0.0268508
+-0.362959 -0.403106 -0.0609893
+
+-0.289579 -0.398572 -0.0791047
+-0.362959 -0.403106 -0.0609893
+-0.2823 -0.388552 -0.0268508
+
+-0.362959 -0.403106 -0.0609893
+-0.289579 -0.398572 -0.0791047
+-0.375392 -0.416916 -0.0979889
+
+-0.303746 -0.41807 -0.127094
+-0.375392 -0.416916 -0.0979889
+-0.289579 -0.398572 -0.0791047
+
+-0.375392 -0.416916 -0.0979889
+-0.303746 -0.41807 -0.127094
+-0.3932 -0.436693 -0.129706
+
+-0.324035 -0.445996 -0.168232
+-0.3932 -0.436693 -0.129706
+-0.303746 -0.41807 -0.127094
+
+-0.3932 -0.436693 -0.129706
+-0.324035 -0.445996 -0.168232
+-0.415423 -0.461374 -0.15443
+
+-0.349354 -0.480845 -0.2003
+-0.415423 -0.461374 -0.15443
+-0.324035 -0.445996 -0.168232
+
+-0.415423 -0.461374 -0.15443
+-0.349354 -0.480845 -0.2003
+-0.440861 -0.489626 -0.170829
+
+-0.378338 -0.520737 -0.22157
+-0.440861 -0.489626 -0.170829
+-0.349354 -0.480845 -0.2003
+
+-0.440861 -0.489626 -0.170829
+-0.378338 -0.520737 -0.22157
+-0.468145 -0.519928 -0.178019
+
+-0.409423 -0.563522 -0.230895
+-0.468145 -0.519928 -0.178019
+-0.378338 -0.520737 -0.22157
+
+-0.468145 -0.519928 -0.178019
+-0.409423 -0.563522 -0.230895
+-0.495802 -0.550644 -0.175612
+
+-0.440934 -0.606894 -0.227773
+-0.495802 -0.550644 -0.175612
+-0.409423 -0.563522 -0.230895
+
+-0.495802 -0.550644 -0.175612
+-0.440934 -0.606894 -0.227773
+-0.522343 -0.580121 -0.163737
+
+-0.471173 -0.648515 -0.212371
+-0.522343 -0.580121 -0.163737
+-0.440934 -0.606894 -0.227773
+
+-0.522343 -0.580121 -0.163737
+-0.471173 -0.648515 -0.212371
+-0.546336 -0.606767 -0.143035
+
+-0.498509 -0.686139 -0.18552
+-0.546336 -0.606767 -0.143035
+-0.471173 -0.648515 -0.212371
+
+-0.546336 -0.606767 -0.143035
+-0.498509 -0.686139 -0.18552
+-0.566487 -0.629148 -0.114622
+
+-0.521469 -0.71774 -0.148668
+-0.566487 -0.629148 -0.114622
+-0.498509 -0.686139 -0.18552
+
+-0.566487 -0.629148 -0.114622
+-0.521469 -0.71774 -0.148668
+-0.581711 -0.646055 -0.0800302
+
+-0.538814 -0.741614 -0.103801
+-0.581711 -0.646055 -0.0800302
+-0.521469 -0.71774 -0.148668
+
+-0.581711 -0.646055 -0.0800302
+-0.538814 -0.741614 -0.103801
+-0.591186 -0.656579 -0.0411236
+
+-0.54961 -0.756473 -0.0533384
+-0.591186 -0.656579 -0.0411236
+-0.538814 -0.741614 -0.103801
+
+-0.591186 -0.656579 -0.0411236
+-0.54961 -0.756473 -0.0533384
+-0.594403 -0.660151 0
+
+-0.553274 -0.761517 0
+-0.594403 -0.660151 0
+-0.54961 -0.756473 -0.0533384
+
+-0.553274 -0.761517 0
+-0.5 -0.866025 0
+-0.54961 -0.756473 0.0533384
+
+-0.496092 -0.859256 0.0668786
+-0.54961 -0.756473 0.0533384
+-0.5 -0.866025 0
+
+-0.54961 -0.756473 0.0533384
+-0.496092 -0.859256 0.0668786
+-0.538814 -0.741614 0.103801
+
+-0.484577 -0.839312 0.130152
+-0.538814 -0.741614 0.103801
+-0.496092 -0.859256 0.0668786
+
+-0.538814 -0.741614 0.103801
+-0.484577 -0.839312 0.130152
+-0.521469 -0.71774 0.148668
+
+-0.466076 -0.807268 0.186408
+-0.521469 -0.71774 0.148668
+-0.484577 -0.839312 0.130152
+
+-0.521469 -0.71774 0.148668
+-0.466076 -0.807268 0.186408
+-0.498509 -0.686139 0.18552
+
+-0.441588 -0.764853 0.232616
+-0.498509 -0.686139 0.18552
+-0.466076 -0.807268 0.186408
+
+-0.498509 -0.686139 0.18552
+-0.441588 -0.764853 0.232616
+-0.471173 -0.648515 0.212371
+
+-0.412432 -0.714352 0.266283
+-0.471173 -0.648515 0.212371
+-0.441588 -0.764853 0.232616
+
+-0.471173 -0.648515 0.212371
+-0.412432 -0.714352 0.266283
+-0.440934 -0.606894 0.227773
+
+-0.380179 -0.658489 0.285594
+-0.440934 -0.606894 0.227773
+-0.412432 -0.714352 0.266283
+
+-0.440934 -0.606894 0.227773
+-0.380179 -0.658489 0.285594
+-0.409423 -0.563522 0.230895
+
+-0.346569 -0.600275 0.289509
+-0.409423 -0.563522 0.230895
+-0.380179 -0.658489 0.285594
+
+-0.409423 -0.563522 0.230895
+-0.346569 -0.600275 0.289509
+-0.378338 -0.520737 0.22157
+
+-0.313414 -0.542848 0.277817
+-0.378338 -0.520737 0.22157
+-0.346569 -0.600275 0.289509
+
+-0.378338 -0.520737 0.22157
+-0.313414 -0.542848 0.277817
+-0.349354 -0.480845 0.2003
+
+-0.2825 -0.489304 0.251147
+-0.349354 -0.480845 0.2003
+-0.313414 -0.542848 0.277817
+
+-0.349354 -0.480845 0.2003
+-0.2825 -0.489304 0.251147
+-0.324035 -0.445996 0.168232
+
+-0.255495 -0.44253 0.210938
+-0.324035 -0.445996 0.168232
+-0.2825 -0.489304 0.251147
+
+-0.324035 -0.445996 0.168232
+-0.255495 -0.44253 0.210938
+-0.303746 -0.41807 0.127094
+
+-0.233854 -0.405047 0.159358
+-0.303746 -0.41807 0.127094
+-0.255495 -0.44253 0.210938
+
+-0.303746 -0.41807 0.127094
+-0.233854 -0.405047 0.159358
+-0.289579 -0.398572 0.0791047
+
+-0.218745 -0.378877 0.0991858
+-0.289579 -0.398572 0.0791047
+-0.233854 -0.405047 0.159358
+
+-0.289579 -0.398572 0.0791047
+-0.218745 -0.378877 0.0991858
+-0.2823 -0.388552 0.0268508
+
+-0.21098 -0.365429 0.0336669
+-0.2823 -0.388552 0.0268508
+-0.218745 -0.378877 0.0991858
+
+-0.2823 -0.388552 0.0268508
+-0.21098 -0.365429 0.0336669
+-0.2823 -0.388552 -0.0268508
+
+-0.21098 -0.365429 -0.0336669
+-0.2823 -0.388552 -0.0268508
+-0.21098 -0.365429 0.0336669
+
+-0.2823 -0.388552 -0.0268508
+-0.21098 -0.365429 -0.0336669
+-0.289579 -0.398572 -0.0791047
+
+-0.218745 -0.378877 -0.0991858
+-0.289579 -0.398572 -0.0791047
+-0.21098 -0.365429 -0.0336669
+
+-0.289579 -0.398572 -0.0791047
+-0.218745 -0.378877 -0.0991858
+-0.303746 -0.41807 -0.127094
+
+-0.233854 -0.405047 -0.159358
+-0.303746 -0.41807 -0.127094
+-0.218745 -0.378877 -0.0991858
+
+-0.303746 -0.41807 -0.127094
+-0.233854 -0.405047 -0.159358
+-0.324035 -0.445996 -0.168232
+
+-0.255495 -0.44253 -0.210938
+-0.324035 -0.445996 -0.168232
+-0.233854 -0.405047 -0.159358
+
+-0.324035 -0.445996 -0.168232
+-0.255495 -0.44253 -0.210938
+-0.349354 -0.480845 -0.2003
+
+-0.2825 -0.489304 -0.251147
+-0.349354 -0.480845 -0.2003
+-0.255495 -0.44253 -0.210938
+
+-0.349354 -0.480845 -0.2003
+-0.2825 -0.489304 -0.251147
+-0.378338 -0.520737 -0.22157
+
+-0.313414 -0.542848 -0.277817
+-0.378338 -0.520737 -0.22157
+-0.2825 -0.489304 -0.251147
+
+-0.378338 -0.520737 -0.22157
+-0.313414 -0.542848 -0.277817
+-0.409423 -0.563522 -0.230895
+
+-0.346569 -0.600275 -0.289509
+-0.409423 -0.563522 -0.230895
+-0.313414 -0.542848 -0.277817
+
+-0.409423 -0.563522 -0.230895
+-0.346569 -0.600275 -0.289509
+-0.440934 -0.606894 -0.227773
+
+-0.380179 -0.658489 -0.285594
+-0.440934 -0.606894 -0.227773
+-0.346569 -0.600275 -0.289509
+
+-0.440934 -0.606894 -0.227773
+-0.380179 -0.658489 -0.285594
+-0.471173 -0.648515 -0.212371
+
+-0.412432 -0.714352 -0.266283
+-0.471173 -0.648515 -0.212371
+-0.380179 -0.658489 -0.285594
+
+-0.471173 -0.648515 -0.212371
+-0.412432 -0.714352 -0.266283
+-0.498509 -0.686139 -0.18552
+
+-0.441588 -0.764853 -0.232616
+-0.498509 -0.686139 -0.18552
+-0.412432 -0.714352 -0.266283
+
+-0.498509 -0.686139 -0.18552
+-0.441588 -0.764853 -0.232616
+-0.521469 -0.71774 -0.148668
+
+-0.466076 -0.807268 -0.186408
+-0.521469 -0.71774 -0.148668
+-0.441588 -0.764853 -0.232616
+
+-0.521469 -0.71774 -0.148668
+-0.466076 -0.807268 -0.186408
+-0.538814 -0.741614 -0.103801
+
+-0.484577 -0.839312 -0.130152
+-0.538814 -0.741614 -0.103801
+-0.466076 -0.807268 -0.186408
+
+-0.538814 -0.741614 -0.103801
+-0.484577 -0.839312 -0.130152
+-0.54961 -0.756473 -0.0533384
+
+-0.496092 -0.859256 -0.0668786
+-0.54961 -0.756473 -0.0533384
+-0.484577 -0.839312 -0.130152
+
+-0.54961 -0.756473 -0.0533384
+-0.496092 -0.859256 -0.0668786
+-0.553274 -0.761517 0
+
+-0.5 -0.866025 0
+-0.553274 -0.761517 0
+-0.496092 -0.859256 -0.0668786
+
+-0.5 -0.866025 0
+-0.430617 -0.967183 0
+-0.496092 -0.859256 0.0668786
+
+-0.426794 -0.958596 0.0804188
+-0.496092 -0.859256 0.0668786
+-0.430617 -0.967183 0
+
+-0.496092 -0.859256 0.0668786
+-0.426794 -0.958596 0.0804188
+-0.484577 -0.839312 0.130152
+
+-0.415531 -0.933298 0.156502
+-0.484577 -0.839312 0.130152
+-0.426794 -0.958596 0.0804188
+
+-0.484577 -0.839312 0.130152
+-0.415531 -0.933298 0.156502
+-0.466076 -0.807268 0.186408
+
+-0.397435 -0.892653 0.224149
+-0.466076 -0.807268 0.186408
+-0.415531 -0.933298 0.156502
+
+-0.466076 -0.807268 0.186408
+-0.397435 -0.892653 0.224149
+-0.441588 -0.764853 0.232616
+
+-0.373481 -0.838851 0.279711
+-0.441588 -0.764853 0.232616
+-0.397435 -0.892653 0.224149
+
+-0.441588 -0.764853 0.232616
+-0.373481 -0.838851 0.279711
+-0.412432 -0.714352 0.266283
+
+-0.344961 -0.774795 0.320194
+-0.412432 -0.714352 0.266283
+-0.373481 -0.838851 0.279711
+
+-0.412432 -0.714352 0.266283
+-0.344961 -0.774795 0.320194
+-0.380179 -0.658489 0.285594
+
+-0.313412 -0.703936 0.343415
+-0.380179 -0.658489 0.285594
+-0.344961 -0.774795 0.320194
+
+-0.380179 -0.658489 0.285594
+-0.313412 -0.703936 0.343415
+-0.346569 -0.600275 0.289509
+
+-0.280536 -0.630094 0.348123
+-0.346569 -0.600275 0.289509
+-0.313412 -0.703936 0.343415
+
+-0.346569 -0.600275 0.289509
+-0.280536 -0.630094 0.348123
+-0.313414 -0.542848 0.277817
+
+-0.248104 -0.557252 0.334064
+-0.313414 -0.542848 0.277817
+-0.280536 -0.630094 0.348123
+
+-0.313414 -0.542848 0.277817
+-0.248104 -0.557252 0.334064
+-0.2825 -0.489304 0.251147
+
+-0.217866 -0.489335 0.301995
+-0.2825 -0.489304 0.251147
+-0.248104 -0.557252 0.334064
+
+-0.2825 -0.489304 0.251147
+-0.217866 -0.489335 0.301995
+-0.255495 -0.44253 0.210938
+
+-0.19145 -0.430004 0.253645
+-0.255495 -0.44253 0.210938
+-0.217866 -0.489335 0.301995
+
+-0.255495 -0.44253 0.210938
+-0.19145 -0.430004 0.253645
+-0.233854 -0.405047 0.159358
+
+-0.170282 -0.38246 0.191621
+-0.233854 -0.405047 0.159358
+-0.19145 -0.430004 0.253645
+
+-0.233854 -0.405047 0.159358
+-0.170282 -0.38246 0.191621
+-0.218745 -0.378877 0.0991858
+
+-0.155502 -0.349264 0.119267
+-0.218745 -0.378877 0.0991858
+-0.170282 -0.38246 0.191621
+
+-0.218745 -0.378877 0.0991858
+-0.155502 -0.349264 0.119267
+-0.21098 -0.365429 0.0336669
+
+-0.147908 -0.332206 0.0404831
+-0.21098 -0.365429 0.0336669
+-0.155502 -0.349264 0.119267
+
+-0.21098 -0.365429 0.0336669
+-0.147908 -0.332206 0.0404831
+-0.21098 -0.365429 -0.0336669
+
+-0.147908 -0.332206 -0.0404831
+-0.21098 -0.365429 -0.0336669
+-0.147908 -0.332206 0.0404831
+
+-0.21098 -0.365429 -0.0336669
+-0.147908 -0.332206 -0.0404831
+-0.218745 -0.378877 -0.0991858
+
+-0.155502 -0.349264 -0.119267
+-0.218745 -0.378877 -0.0991858
+-0.147908 -0.332206 -0.0404831
+
+-0.218745 -0.378877 -0.0991858
+-0.155502 -0.349264 -0.119267
+-0.233854 -0.405047 -0.159358
+
+-0.170282 -0.38246 -0.191621
+-0.233854 -0.405047 -0.159358
+-0.155502 -0.349264 -0.119267
+
+-0.233854 -0.405047 -0.159358
+-0.170282 -0.38246 -0.191621
+-0.255495 -0.44253 -0.210938
+
+-0.19145 -0.430004 -0.253645
+-0.255495 -0.44253 -0.210938
+-0.170282 -0.38246 -0.191621
+
+-0.255495 -0.44253 -0.210938
+-0.19145 -0.430004 -0.253645
+-0.2825 -0.489304 -0.251147
+
+-0.217866 -0.489335 -0.301995
+-0.2825 -0.489304 -0.251147
+-0.19145 -0.430004 -0.253645
+
+-0.2825 -0.489304 -0.251147
+-0.217866 -0.489335 -0.301995
+-0.313414 -0.542848 -0.277817
+
+-0.248104 -0.557252 -0.334064
+-0.313414 -0.542848 -0.277817
+-0.217866 -0.489335 -0.301995
+
+-0.313414 -0.542848 -0.277817
+-0.248104 -0.557252 -0.334064
+-0.346569 -0.600275 -0.289509
+
+-0.280536 -0.630094 -0.348123
+-0.346569 -0.600275 -0.289509
+-0.248104 -0.557252 -0.334064
+
+-0.346569 -0.600275 -0.289509
+-0.280536 -0.630094 -0.348123
+-0.380179 -0.658489 -0.285594
+
+-0.313412 -0.703936 -0.343415
+-0.380179 -0.658489 -0.285594
+-0.280536 -0.630094 -0.348123
+
+-0.380179 -0.658489 -0.285594
+-0.313412 -0.703936 -0.343415
+-0.412432 -0.714352 -0.266283
+
+-0.344961 -0.774795 -0.320194
+-0.412432 -0.714352 -0.266283
+-0.313412 -0.703936 -0.343415
+
+-0.412432 -0.714352 -0.266283
+-0.344961 -0.774795 -0.320194
+-0.441588 -0.764853 -0.232616
+
+-0.373481 -0.838851 -0.279711
+-0.441588 -0.764853 -0.232616
+-0.344961 -0.774795 -0.320194
+
+-0.441588 -0.764853 -0.232616
+-0.373481 -0.838851 -0.279711
+-0.466076 -0.807268 -0.186408
+
+-0.397435 -0.892653 -0.224149
+-0.466076 -0.807268 -0.186408
+-0.373481 -0.838851 -0.279711
+
+-0.466076 -0.807268 -0.186408
+-0.397435 -0.892653 -0.224149
+-0.484577 -0.839312 -0.130152
+
+-0.415531 -0.933298 -0.156502
+-0.484577 -0.839312 -0.130152
+-0.397435 -0.892653 -0.224149
+
+-0.484577 -0.839312 -0.130152
+-0.415531 -0.933298 -0.156502
+-0.496092 -0.859256 -0.0668786
+
+-0.426794 -0.958596 -0.0804188
+-0.496092 -0.859256 -0.0668786
+-0.415531 -0.933298 -0.156502
+
+-0.496092 -0.859256 -0.0668786
+-0.426794 -0.958596 -0.0804188
+-0.5 -0.866025 0
+
+-0.430617 -0.967183 0
+-0.5 -0.866025 0
+-0.426794 -0.958596 -0.0804188
+
+-0.430617 -0.967183 0
+-0.343528 -1.05727 0
+-0.426794 -0.958596 0.0804188
+
+-0.340182 -1.04697 0.0926336
+-0.426794 -0.958596 0.0804188
+-0.343528 -1.05727 0
+
+-0.426794 -0.958596 0.0804188
+-0.340182 -1.04697 0.0926336
+-0.415531 -0.933298 0.156502
+
+-0.330325 -1.01664 0.180273
+-0.415531 -0.933298 0.156502
+-0.340182 -1.04697 0.0926336
+
+-0.415531 -0.933298 0.156502
+-0.330325 -1.01664 0.180273
+-0.397435 -0.892653 0.224149
+
+-0.314488 -0.967894 0.258194
+-0.397435 -0.892653 0.224149
+-0.330325 -1.01664 0.180273
+
+-0.397435 -0.892653 0.224149
+-0.314488 -0.967894 0.258194
+-0.373481 -0.838851 0.279711
+
+-0.293525 -0.903376 0.322196
+-0.373481 -0.838851 0.279711
+-0.314488 -0.967894 0.258194
+
+-0.373481 -0.838851 0.279711
+-0.293525 -0.903376 0.322196
+-0.344961 -0.774795 0.320194
+
+-0.268566 -0.82656 0.368828
+-0.344961 -0.774795 0.320194
+-0.293525 -0.903376 0.322196
+
+-0.344961 -0.774795 0.320194
+-0.268566 -0.82656 0.368828
+-0.313412 -0.703936 0.343415
+
+-0.240956 -0.741587 0.395577
+-0.313412 -0.703936 0.343415
+-0.268566 -0.82656 0.368828
+
+-0.313412 -0.703936 0.343415
+-0.240956 -0.741587 0.395577
+-0.280536 -0.630094 0.348123
+
+-0.212185 -0.653038 0.401
+-0.280536 -0.630094 0.348123
+-0.240956 -0.741587 0.395577
+
+-0.280536 -0.630094 0.348123
+-0.212185 -0.653038 0.401
+-0.248104 -0.557252 0.334064
+
+-0.183802 -0.565686 0.384804
+-0.248104 -0.557252 0.334064
+-0.212185 -0.653038 0.401
+
+-0.248104 -0.557252 0.334064
+-0.183802 -0.565686 0.384804
+-0.217866 -0.489335 0.301995
+
+-0.157339 -0.48424 0.347864
+-0.217866 -0.489335 0.301995
+-0.183802 -0.565686 0.384804
+
+-0.217866 -0.489335 0.301995
+-0.157339 -0.48424 0.347864
+-0.19145 -0.430004 0.253645
+
+-0.134222 -0.413092 0.292171
+-0.19145 -0.430004 0.253645
+-0.157339 -0.48424 0.347864
+
+-0.19145 -0.430004 0.253645
+-0.134222 -0.413092 0.292171
+-0.170282 -0.38246 0.191621
+
+-0.115697 -0.356077 0.220726
+-0.170282 -0.38246 0.191621
+-0.134222 -0.413092 0.292171
+
+-0.170282 -0.38246 0.191621
+-0.115697 -0.356077 0.220726
+-0.155502 -0.349264 0.119267
+
+-0.102762 -0.316269 0.137382
+-0.155502 -0.349264 0.119267
+-0.115697 -0.356077 0.220726
+
+-0.155502 -0.349264 0.119267
+-0.102762 -0.316269 0.137382
+-0.147908 -0.332206 0.0404831
+
+-0.0961157 -0.295814 0.0466321
+-0.147908 -0.332206 0.0404831
+-0.102762 -0.316269 0.137382
+
+-0.147908 -0.332206 0.0404831
+-0.0961157 -0.295814 0.0466321
+-0.147908 -0.332206 -0.0404831
+
+-0.0961157 -0.295814 -0.0466321
+-0.147908 -0.332206 -0.0404831
+-0.0961157 -0.295814 0.0466321
+
+-0.147908 -0.332206 -0.0404831
+-0.0961157 -0.295814 -0.0466321
+-0.155502 -0.349264 -0.119267
+
+-0.102762 -0.316269 -0.137382
+-0.155502 -0.349264 -0.119267
+-0.0961157 -0.295814 -0.0466321
+
+-0.155502 -0.349264 -0.119267
+-0.102762 -0.316269 -0.137382
+-0.170282 -0.38246 -0.191621
+
+-0.115697 -0.356077 -0.220726
+-0.170282 -0.38246 -0.191621
+-0.102762 -0.316269 -0.137382
+
+-0.170282 -0.38246 -0.191621
+-0.115697 -0.356077 -0.220726
+-0.19145 -0.430004 -0.253645
+
+-0.134222 -0.413092 -0.292171
+-0.19145 -0.430004 -0.253645
+-0.115697 -0.356077 -0.220726
+
+-0.19145 -0.430004 -0.253645
+-0.134222 -0.413092 -0.292171
+-0.217866 -0.489335 -0.301995
+
+-0.157339 -0.48424 -0.347864
+-0.217866 -0.489335 -0.301995
+-0.134222 -0.413092 -0.292171
+
+-0.217866 -0.489335 -0.301995
+-0.157339 -0.48424 -0.347864
+-0.248104 -0.557252 -0.334064
+
+-0.183802 -0.565686 -0.384804
+-0.248104 -0.557252 -0.334064
+-0.157339 -0.48424 -0.347864
+
+-0.248104 -0.557252 -0.334064
+-0.183802 -0.565686 -0.384804
+-0.280536 -0.630094 -0.348123
+
+-0.212185 -0.653038 -0.401
+-0.280536 -0.630094 -0.348123
+-0.183802 -0.565686 -0.384804
+
+-0.280536 -0.630094 -0.348123
+-0.212185 -0.653038 -0.401
+-0.313412 -0.703936 -0.343415
+
+-0.240956 -0.741587 -0.395577
+-0.313412 -0.703936 -0.343415
+-0.212185 -0.653038 -0.401
+
+-0.313412 -0.703936 -0.343415
+-0.240956 -0.741587 -0.395577
+-0.344961 -0.774795 -0.320194
+
+-0.268566 -0.82656 -0.368828
+-0.344961 -0.774795 -0.320194
+-0.240956 -0.741587 -0.395577
+
+-0.344961 -0.774795 -0.320194
+-0.268566 -0.82656 -0.368828
+-0.373481 -0.838851 -0.279711
+
+-0.293525 -0.903376 -0.322196
+-0.373481 -0.838851 -0.279711
+-0.268566 -0.82656 -0.368828
+
+-0.373481 -0.838851 -0.279711
+-0.293525 -0.903376 -0.322196
+-0.397435 -0.892653 -0.224149
+
+-0.314488 -0.967894 -0.258194
+-0.397435 -0.892653 -0.224149
+-0.293525 -0.903376 -0.322196
+
+-0.397435 -0.892653 -0.224149
+-0.314488 -0.967894 -0.258194
+-0.415531 -0.933298 -0.156502
+
+-0.330325 -1.01664 -0.180273
+-0.415531 -0.933298 -0.156502
+-0.314488 -0.967894 -0.258194
+
+-0.415531 -0.933298 -0.156502
+-0.330325 -1.01664 -0.180273
+-0.426794 -0.958596 -0.0804188
+
+-0.340182 -1.04697 -0.0926336
+-0.426794 -0.958596 -0.0804188
+-0.330325 -1.01664 -0.180273
+
+-0.426794 -0.958596 -0.0804188
+-0.340182 -1.04697 -0.0926336
+-0.430617 -0.967183 0
+
+-0.343528 -1.05727 0
+-0.430617 -0.967183 0
+-0.340182 -1.04697 -0.0926336
+
+-0.343528 -1.05727 0
+-0.23987 -1.1285 0
+-0.340182 -1.04697 0.0926336
+
+-0.237384 -1.1168 0.102327
+-0.340182 -1.04697 0.0926336
+-0.23987 -1.1285 0
+
+-0.340182 -1.04697 0.0926336
+-0.237384 -1.1168 0.102327
+-0.330325 -1.01664 0.180273
+
+-0.230058 -1.08234 0.199138
+-0.330325 -1.01664 0.180273
+-0.237384 -1.1168 0.102327
+
+-0.330325 -1.01664 0.180273
+-0.230058 -1.08234 0.199138
+-0.314488 -0.967894 0.258194
+
+-0.218287 -1.02696 0.285213
+-0.314488 -0.967894 0.258194
+-0.230058 -1.08234 0.199138
+
+-0.314488 -0.967894 0.258194
+-0.218287 -1.02696 0.285213
+-0.293525 -0.903376 0.322196
+
+-0.202707 -0.953662 0.355913
+-0.293525 -0.903376 0.322196
+-0.218287 -1.02696 0.285213
+
+-0.293525 -0.903376 0.322196
+-0.202707 -0.953662 0.355913
+-0.268566 -0.82656 0.368828
+
+-0.184157 -0.86639 0.407425
+-0.268566 -0.82656 0.368828
+-0.202707 -0.953662 0.355913
+
+-0.268566 -0.82656 0.368828
+-0.184157 -0.86639 0.407425
+-0.240956 -0.741587 0.395577
+
+-0.163637 -0.769851 0.436972
+-0.240956 -0.741587 0.395577
+-0.184157 -0.86639 0.407425
+
+-0.240956 -0.741587 0.395577
+-0.163637 -0.769851 0.436972
+-0.212185 -0.653038 0.401
+
+-0.142253 -0.669249 0.442963
+-0.212185 -0.653038 0.401
+-0.163637 -0.769851 0.436972
+
+-0.212185 -0.653038 0.401
+-0.142253 -0.669249 0.442963
+-0.183802 -0.565686 0.384804
+
+-0.121159 -0.570007 0.425073
+-0.183802 -0.565686 0.384804
+-0.142253 -0.669249 0.442963
+
+-0.183802 -0.565686 0.384804
+-0.121159 -0.570007 0.425073
+-0.157339 -0.48424 0.347864
+
+-0.101491 -0.477476 0.384267
+-0.157339 -0.48424 0.347864
+-0.121159 -0.570007 0.425073
+
+-0.157339 -0.48424 0.347864
+-0.101491 -0.477476 0.384267
+-0.134222 -0.413092 0.292171
+
+-0.0843093 -0.396644 0.322745
+-0.134222 -0.413092 0.292171
+-0.101491 -0.477476 0.384267
+
+-0.134222 -0.413092 0.292171
+-0.0843093 -0.396644 0.322745
+-0.115697 -0.356077 0.220726
+
+-0.0705409 -0.331869 0.243824
+-0.115697 -0.356077 0.220726
+-0.0843093 -0.396644 0.322745
+
+-0.115697 -0.356077 0.220726
+-0.0705409 -0.331869 0.243824
+-0.102762 -0.316269 0.137382
+
+-0.0609277 -0.286642 0.151759
+-0.102762 -0.316269 0.137382
+-0.0705409 -0.331869 0.243824
+
+-0.102762 -0.316269 0.137382
+-0.0609277 -0.286642 0.151759
+-0.0961157 -0.295814 0.0466321
+
+-0.0559879 -0.263402 0.051512
+-0.0961157 -0.295814 0.0466321
+-0.0609277 -0.286642 0.151759
+
+-0.0961157 -0.295814 0.0466321
+-0.0559879 -0.263402 0.051512
+-0.0961157 -0.295814 -0.0466321
+
+-0.0559879 -0.263402 -0.051512
+-0.0961157 -0.295814 -0.0466321
+-0.0559879 -0.263402 0.051512
+
+-0.0961157 -0.295814 -0.0466321
+-0.0559879 -0.263402 -0.051512
+-0.102762 -0.316269 -0.137382
+
+-0.0609277 -0.286642 -0.151759
+-0.102762 -0.316269 -0.137382
+-0.0559879 -0.263402 -0.051512
+
+-0.102762 -0.316269 -0.137382
+-0.0609277 -0.286642 -0.151759
+-0.115697 -0.356077 -0.220726
+
+-0.0705409 -0.331869 -0.243824
+-0.115697 -0.356077 -0.220726
+-0.0609277 -0.286642 -0.151759
+
+-0.115697 -0.356077 -0.220726
+-0.0705409 -0.331869 -0.243824
+-0.134222 -0.413092 -0.292171
+
+-0.0843093 -0.396644 -0.322745
+-0.134222 -0.413092 -0.292171
+-0.0705409 -0.331869 -0.243824
+
+-0.134222 -0.413092 -0.292171
+-0.0843093 -0.396644 -0.322745
+-0.157339 -0.48424 -0.347864
+
+-0.101491 -0.477476 -0.384267
+-0.157339 -0.48424 -0.347864
+-0.0843093 -0.396644 -0.322745
+
+-0.157339 -0.48424 -0.347864
+-0.101491 -0.477476 -0.384267
+-0.183802 -0.565686 -0.384804
+
+-0.121159 -0.570007 -0.425073
+-0.183802 -0.565686 -0.384804
+-0.101491 -0.477476 -0.384267
+
+-0.183802 -0.565686 -0.384804
+-0.121159 -0.570007 -0.425073
+-0.212185 -0.653038 -0.401
+
+-0.142253 -0.669249 -0.442963
+-0.212185 -0.653038 -0.401
+-0.121159 -0.570007 -0.425073
+
+-0.212185 -0.653038 -0.401
+-0.142253 -0.669249 -0.442963
+-0.240956 -0.741587 -0.395577
+
+-0.163637 -0.769851 -0.436972
+-0.240956 -0.741587 -0.395577
+-0.142253 -0.669249 -0.442963
+
+-0.240956 -0.741587 -0.395577
+-0.163637 -0.769851 -0.436972
+-0.268566 -0.82656 -0.368828
+
+-0.184157 -0.86639 -0.407425
+-0.268566 -0.82656 -0.368828
+-0.163637 -0.769851 -0.436972
+
+-0.268566 -0.82656 -0.368828
+-0.184157 -0.86639 -0.407425
+-0.293525 -0.903376 -0.322196
+
+-0.202707 -0.953662 -0.355913
+-0.293525 -0.903376 -0.322196
+-0.184157 -0.86639 -0.407425
+
+-0.293525 -0.903376 -0.322196
+-0.202707 -0.953662 -0.355913
+-0.314488 -0.967894 -0.258194
+
+-0.218287 -1.02696 -0.285213
+-0.314488 -0.967894 -0.258194
+-0.202707 -0.953662 -0.355913
+
+-0.314488 -0.967894 -0.258194
+-0.218287 -1.02696 -0.285213
+-0.330325 -1.01664 -0.180273
+
+-0.230058 -1.08234 -0.199138
+-0.330325 -1.01664 -0.180273
+-0.218287 -1.02696 -0.285213
+
+-0.330325 -1.01664 -0.180273
+-0.230058 -1.08234 -0.199138
+-0.340182 -1.04697 -0.0926336
+
+-0.237384 -1.1168 -0.102327
+-0.340182 -1.04697 -0.0926336
+-0.230058 -1.08234 -0.199138
+
+-0.340182 -1.04697 -0.0926336
+-0.237384 -1.1168 -0.102327
+-0.343528 -1.05727 0
+
+-0.23987 -1.1285 0
+-0.343528 -1.05727 0
+-0.237384 -1.1168 -0.102327
+
+-0.23987 -1.1285 0
+-0.123417 -1.17423 0
+-0.237384 -1.1168 0.102327
+
+-0.122091 -1.16161 0.108551
+-0.237384 -1.1168 0.102327
+-0.123417 -1.17423 0
+
+-0.237384 -1.1168 0.102327
+-0.122091 -1.16161 0.108551
+-0.230058 -1.08234 0.199138
+
+-0.118183 -1.12444 0.21125
+-0.230058 -1.08234 0.199138
+-0.122091 -1.16161 0.108551
+
+-0.230058 -1.08234 0.199138
+-0.118183 -1.12444 0.21125
+-0.218287 -1.02696 0.285213
+
+-0.111906 -1.06471 0.302561
+-0.218287 -1.02696 0.285213
+-0.118183 -1.12444 0.21125
+
+-0.218287 -1.02696 0.285213
+-0.111906 -1.06471 0.302561
+-0.202707 -0.953662 0.355913
+
+-0.103596 -0.985654 0.37756
+-0.202707 -0.953662 0.355913
+-0.111906 -1.06471 0.302561
+
+-0.202707 -0.953662 0.355913
+-0.103596 -0.985654 0.37756
+-0.184157 -0.86639 0.407425
+
+-0.093703 -0.891524 0.432205
+-0.184157 -0.86639 0.407425
+-0.103596 -0.985654 0.37756
+
+-0.184157 -0.86639 0.407425
+-0.093703 -0.891524 0.432205
+-0.163637 -0.769851 0.436972
+
+-0.082759 -0.787399 0.46355
+-0.163637 -0.769851 0.436972
+-0.093703 -0.891524 0.432205
+
+-0.163637 -0.769851 0.436972
+-0.082759 -0.787399 0.46355
+-0.142253 -0.669249 0.442963
+
+-0.0713544 -0.678892 0.469904
+-0.142253 -0.669249 0.442963
+-0.082759 -0.787399 0.46355
+
+-0.142253 -0.669249 0.442963
+-0.0713544 -0.678892 0.469904
+-0.121159 -0.570007 0.425073
+
+-0.060104 -0.571852 0.450926
+-0.121159 -0.570007 0.425073
+-0.0713544 -0.678892 0.469904
+
+-0.121159 -0.570007 0.425073
+-0.060104 -0.571852 0.450926
+-0.101491 -0.477476 0.384267
+
+-0.0496144 -0.472049 0.407639
+-0.101491 -0.477476 0.384267
+-0.060104 -0.571852 0.450926
+
+-0.101491 -0.477476 0.384267
+-0.0496144 -0.472049 0.407639
+-0.0843093 -0.396644 0.322745
+
+-0.040451 -0.384866 0.342375
+-0.0843093 -0.396644 0.322745
+-0.0496144 -0.472049 0.407639
+
+-0.0843093 -0.396644 0.322745
+-0.040451 -0.384866 0.342375
+-0.0705409 -0.331869 0.243824
+
+-0.0331079 -0.315 0.258654
+-0.0705409 -0.331869 0.243824
+-0.040451 -0.384866 0.342375
+
+-0.0705409 -0.331869 0.243824
+-0.0331079 -0.315 0.258654
+-0.0609277 -0.286642 0.151759
+
+-0.0279808 -0.26622 0.160989
+-0.0609277 -0.286642 0.151759
+-0.0331079 -0.315 0.258654
+
+-0.0609277 -0.286642 0.151759
+-0.0279808 -0.26622 0.160989
+-0.0559879 -0.263402 0.051512
+
+-0.0253463 -0.241154 0.054645
+-0.0559879 -0.263402 0.051512
+-0.0279808 -0.26622 0.160989
+
+-0.0559879 -0.263402 0.051512
+-0.0253463 -0.241154 0.054645
+-0.0559879 -0.263402 -0.051512
+
+-0.0253463 -0.241154 -0.054645
+-0.0559879 -0.263402 -0.051512
+-0.0253463 -0.241154 0.054645
+
+-0.0559879 -0.263402 -0.051512
+-0.0253463 -0.241154 -0.054645
+-0.0609277 -0.286642 -0.151759
+
+-0.0279808 -0.26622 -0.160989
+-0.0609277 -0.286642 -0.151759
+-0.0253463 -0.241154 -0.054645
+
+-0.0609277 -0.286642 -0.151759
+-0.0279808 -0.26622 -0.160989
+-0.0705409 -0.331869 -0.243824
+
+-0.0331079 -0.315 -0.258654
+-0.0705409 -0.331869 -0.243824
+-0.0279808 -0.26622 -0.160989
+
+-0.0705409 -0.331869 -0.243824
+-0.0331079 -0.315 -0.258654
+-0.0843093 -0.396644 -0.322745
+
+-0.040451 -0.384866 -0.342375
+-0.0843093 -0.396644 -0.322745
+-0.0331079 -0.315 -0.258654
+
+-0.0843093 -0.396644 -0.322745
+-0.040451 -0.384866 -0.342375
+-0.101491 -0.477476 -0.384267
+
+-0.0496144 -0.472049 -0.407639
+-0.101491 -0.477476 -0.384267
+-0.040451 -0.384866 -0.342375
+
+-0.101491 -0.477476 -0.384267
+-0.0496144 -0.472049 -0.407639
+-0.121159 -0.570007 -0.425073
+
+-0.060104 -0.571852 -0.450926
+-0.121159 -0.570007 -0.425073
+-0.0496144 -0.472049 -0.407639
+
+-0.121159 -0.570007 -0.425073
+-0.060104 -0.571852 -0.450926
+-0.142253 -0.669249 -0.442963
+
+-0.0713544 -0.678892 -0.469904
+-0.142253 -0.669249 -0.442963
+-0.060104 -0.571852 -0.450926
+
+-0.142253 -0.669249 -0.442963
+-0.0713544 -0.678892 -0.469904
+-0.163637 -0.769851 -0.436972
+
+-0.082759 -0.787399 -0.46355
+-0.163637 -0.769851 -0.436972
+-0.0713544 -0.678892 -0.469904
+
+-0.163637 -0.769851 -0.436972
+-0.082759 -0.787399 -0.46355
+-0.184157 -0.86639 -0.407425
+
+-0.093703 -0.891524 -0.432205
+-0.184157 -0.86639 -0.407425
+-0.082759 -0.787399 -0.46355
+
+-0.184157 -0.86639 -0.407425
+-0.093703 -0.891524 -0.432205
+-0.202707 -0.953662 -0.355913
+
+-0.103596 -0.985654 -0.37756
+-0.202707 -0.953662 -0.355913
+-0.093703 -0.891524 -0.432205
+
+-0.202707 -0.953662 -0.355913
+-0.103596 -0.985654 -0.37756
+-0.218287 -1.02696 -0.285213
+
+-0.111906 -1.06471 -0.302561
+-0.218287 -1.02696 -0.285213
+-0.103596 -0.985654 -0.37756
+
+-0.218287 -1.02696 -0.285213
+-0.111906 -1.06471 -0.302561
+-0.230058 -1.08234 -0.199138
+
+-0.118183 -1.12444 -0.21125
+-0.230058 -1.08234 -0.199138
+-0.111906 -1.06471 -0.302561
+
+-0.230058 -1.08234 -0.199138
+-0.118183 -1.12444 -0.21125
+-0.237384 -1.1168 -0.102327
+
+-0.122091 -1.16161 -0.108551
+-0.237384 -1.1168 -0.102327
+-0.118183 -1.12444 -0.21125
+
+-0.237384 -1.1168 -0.102327
+-0.122091 -1.16161 -0.108551
+-0.23987 -1.1285 0
+
+-0.123417 -1.17423 0
+-0.23987 -1.1285 0
+-0.122091 -1.16161 -0.108551
+
+-0.123417 -1.17423 0
+0 -1.19 0
+-0.122091 -1.16161 0.108551
+
+0 -1.17706 0.110696
+-0.122091 -1.16161 0.108551
+0 -1.19 0
+
+-0.122091 -1.16161 0.108551
+0 -1.17706 0.110696
+-0.118183 -1.12444 0.21125
+
+0 -1.13894 0.215424
+-0.118183 -1.12444 0.21125
+0 -1.17706 0.110696
+
+-0.118183 -1.12444 0.21125
+0 -1.13894 0.215424
+-0.111906 -1.06471 0.302561
+
+0 -1.0777 0.308538
+-0.111906 -1.06471 0.302561
+0 -1.13894 0.215424
+
+-0.111906 -1.06471 0.302561
+0 -1.0777 0.308538
+-0.103596 -0.985654 0.37756
+
+0 -0.996636 0.385019
+-0.103596 -0.985654 0.37756
+0 -1.0777 0.308538
+
+-0.103596 -0.985654 0.37756
+0 -0.996636 0.385019
+-0.093703 -0.891524 0.432205
+
+0 -0.900118 0.440744
+-0.093703 -0.891524 0.432205
+0 -0.996636 0.385019
+
+-0.093703 -0.891524 0.432205
+0 -0.900118 0.440744
+-0.082759 -0.787399 0.46355
+
+0 -0.793351 0.472708
+-0.082759 -0.787399 0.46355
+0 -0.900118 0.440744
+
+-0.082759 -0.787399 0.46355
+0 -0.793351 0.472708
+-0.0713544 -0.678892 0.469904
+
+0 -0.68209 0.479188
+-0.0713544 -0.678892 0.469904
+0 -0.793351 0.472708
+
+-0.0713544 -0.678892 0.469904
+0 -0.68209 0.479188
+-0.060104 -0.571852 0.450926
+
+0 -0.572334 0.459835
+-0.060104 -0.571852 0.450926
+0 -0.68209 0.479188
+
+-0.060104 -0.571852 0.450926
+0 -0.572334 0.459835
+-0.0496144 -0.472049 0.407639
+
+0 -0.47 0.415692
+-0.0496144 -0.472049 0.407639
+0 -0.572334 0.459835
+
+-0.0496144 -0.472049 0.407639
+0 -0.47 0.415692
+-0.040451 -0.384866 0.342375
+
+0 -0.380604 0.349139
+-0.040451 -0.384866 0.342375
+0 -0.47 0.415692
+
+-0.040451 -0.384866 0.342375
+0 -0.380604 0.349139
+-0.0331079 -0.315 0.258654
+
+0 -0.308966 0.263764
+-0.0331079 -0.315 0.258654
+0 -0.380604 0.349139
+
+-0.0331079 -0.315 0.258654
+0 -0.308966 0.263764
+-0.0279808 -0.26622 0.160989
+
+0 -0.258948 0.16417
+-0.0279808 -0.26622 0.160989
+0 -0.308966 0.263764
+
+-0.0279808 -0.26622 0.160989
+0 -0.258948 0.16417
+-0.0253463 -0.241154 0.054645
+
+0 -0.233246 0.0557246
+-0.0253463 -0.241154 0.054645
+0 -0.258948 0.16417
+
+-0.0253463 -0.241154 0.054645
+0 -0.233246 0.0557246
+-0.0253463 -0.241154 -0.054645
+
+0 -0.233246 -0.0557246
+-0.0253463 -0.241154 -0.054645
+0 -0.233246 0.0557246
+
+-0.0253463 -0.241154 -0.054645
+0 -0.233246 -0.0557246
+-0.0279808 -0.26622 -0.160989
+
+0 -0.258948 -0.16417
+-0.0279808 -0.26622 -0.160989
+0 -0.233246 -0.0557246
+
+-0.0279808 -0.26622 -0.160989
+0 -0.258948 -0.16417
+-0.0331079 -0.315 -0.258654
+
+0 -0.308966 -0.263764
+-0.0331079 -0.315 -0.258654
+0 -0.258948 -0.16417
+
+-0.0331079 -0.315 -0.258654
+0 -0.308966 -0.263764
+-0.040451 -0.384866 -0.342375
+
+0 -0.380604 -0.349139
+-0.040451 -0.384866 -0.342375
+0 -0.308966 -0.263764
+
+-0.040451 -0.384866 -0.342375
+0 -0.380604 -0.349139
+-0.0496144 -0.472049 -0.407639
+
+0 -0.47 -0.415692
+-0.0496144 -0.472049 -0.407639
+0 -0.380604 -0.349139
+
+-0.0496144 -0.472049 -0.407639
+0 -0.47 -0.415692
+-0.060104 -0.571852 -0.450926
+
+0 -0.572334 -0.459835
+-0.060104 -0.571852 -0.450926
+0 -0.47 -0.415692
+
+-0.060104 -0.571852 -0.450926
+0 -0.572334 -0.459835
+-0.0713544 -0.678892 -0.469904
+
+0 -0.68209 -0.479188
+-0.0713544 -0.678892 -0.469904
+0 -0.572334 -0.459835
+
+-0.0713544 -0.678892 -0.469904
+0 -0.68209 -0.479188
+-0.082759 -0.787399 -0.46355
+
+0 -0.793351 -0.472708
+-0.082759 -0.787399 -0.46355
+0 -0.68209 -0.479188
+
+-0.082759 -0.787399 -0.46355
+0 -0.793351 -0.472708
+-0.093703 -0.891524 -0.432205
+
+0 -0.900118 -0.440744
+-0.093703 -0.891524 -0.432205
+0 -0.793351 -0.472708
+
+-0.093703 -0.891524 -0.432205
+0 -0.900118 -0.440744
+-0.103596 -0.985654 -0.37756
+
+0 -0.996636 -0.385019
+-0.103596 -0.985654 -0.37756
+0 -0.900118 -0.440744
+
+-0.103596 -0.985654 -0.37756
+0 -0.996636 -0.385019
+-0.111906 -1.06471 -0.302561
+
+0 -1.0777 -0.308538
+-0.111906 -1.06471 -0.302561
+0 -0.996636 -0.385019
+
+-0.111906 -1.06471 -0.302561
+0 -1.0777 -0.308538
+-0.118183 -1.12444 -0.21125
+
+0 -1.13894 -0.215424
+-0.118183 -1.12444 -0.21125
+0 -1.0777 -0.308538
+
+-0.118183 -1.12444 -0.21125
+0 -1.13894 -0.215424
+-0.122091 -1.16161 -0.108551
+
+0 -1.17706 -0.110696
+-0.122091 -1.16161 -0.108551
+0 -1.13894 -0.215424
+
+-0.122091 -1.16161 -0.108551
+0 -1.17706 -0.110696
+-0.123417 -1.17423 0
+
+0 -1.19 0
+-0.123417 -1.17423 0
+0 -1.17706 -0.110696
+
+0 -1.19 0
+0.123417 -1.17423 0
+0 -1.17706 0.110696
+
+0.122091 -1.16161 0.108551
+0 -1.17706 0.110696
+0.123417 -1.17423 0
+
+0 -1.17706 0.110696
+0.122091 -1.16161 0.108551
+0 -1.13894 0.215424
+
+0.118183 -1.12444 0.21125
+0 -1.13894 0.215424
+0.122091 -1.16161 0.108551
+
+0 -1.13894 0.215424
+0.118183 -1.12444 0.21125
+0 -1.0777 0.308538
+
+0.111906 -1.06471 0.302561
+0 -1.0777 0.308538
+0.118183 -1.12444 0.21125
+
+0 -1.0777 0.308538
+0.111906 -1.06471 0.302561
+0 -0.996636 0.385019
+
+0.103596 -0.985654 0.37756
+0 -0.996636 0.385019
+0.111906 -1.06471 0.302561
+
+0 -0.996636 0.385019
+0.103596 -0.985654 0.37756
+0 -0.900118 0.440744
+
+0.093703 -0.891524 0.432205
+0 -0.900118 0.440744
+0.103596 -0.985654 0.37756
+
+0 -0.900118 0.440744
+0.093703 -0.891524 0.432205
+0 -0.793351 0.472708
+
+0.082759 -0.787399 0.46355
+0 -0.793351 0.472708
+0.093703 -0.891524 0.432205
+
+0 -0.793351 0.472708
+0.082759 -0.787399 0.46355
+0 -0.68209 0.479188
+
+0.0713544 -0.678892 0.469904
+0 -0.68209 0.479188
+0.082759 -0.787399 0.46355
+
+0 -0.68209 0.479188
+0.0713544 -0.678892 0.469904
+0 -0.572334 0.459835
+
+0.060104 -0.571852 0.450926
+0 -0.572334 0.459835
+0.0713544 -0.678892 0.469904
+
+0 -0.572334 0.459835
+0.060104 -0.571852 0.450926
+0 -0.47 0.415692
+
+0.0496144 -0.472049 0.407639
+0 -0.47 0.415692
+0.060104 -0.571852 0.450926
+
+0 -0.47 0.415692
+0.0496144 -0.472049 0.407639
+0 -0.380604 0.349139
+
+0.040451 -0.384866 0.342375
+0 -0.380604 0.349139
+0.0496144 -0.472049 0.407639
+
+0 -0.380604 0.349139
+0.040451 -0.384866 0.342375
+0 -0.308966 0.263764
+
+0.0331079 -0.315 0.258654
+0 -0.308966 0.263764
+0.040451 -0.384866 0.342375
+
+0 -0.308966 0.263764
+0.0331079 -0.315 0.258654
+0 -0.258948 0.16417
+
+0.0279808 -0.26622 0.160989
+0 -0.258948 0.16417
+0.0331079 -0.315 0.258654
+
+0 -0.258948 0.16417
+0.0279808 -0.26622 0.160989
+0 -0.233246 0.0557246
+
+0.0253463 -0.241154 0.054645
+0 -0.233246 0.0557246
+0.0279808 -0.26622 0.160989
+
+0 -0.233246 0.0557246
+0.0253463 -0.241154 0.054645
+0 -0.233246 -0.0557246
+
+0.0253463 -0.241154 -0.054645
+0 -0.233246 -0.0557246
+0.0253463 -0.241154 0.054645
+
+0 -0.233246 -0.0557246
+0.0253463 -0.241154 -0.054645
+0 -0.258948 -0.16417
+
+0.0279808 -0.26622 -0.160989
+0 -0.258948 -0.16417
+0.0253463 -0.241154 -0.054645
+
+0 -0.258948 -0.16417
+0.0279808 -0.26622 -0.160989
+0 -0.308966 -0.263764
+
+0.0331079 -0.315 -0.258654
+0 -0.308966 -0.263764
+0.0279808 -0.26622 -0.160989
+
+0 -0.308966 -0.263764
+0.0331079 -0.315 -0.258654
+0 -0.380604 -0.349139
+
+0.040451 -0.384866 -0.342375
+0 -0.380604 -0.349139
+0.0331079 -0.315 -0.258654
+
+0 -0.380604 -0.349139
+0.040451 -0.384866 -0.342375
+0 -0.47 -0.415692
+
+0.0496144 -0.472049 -0.407639
+0 -0.47 -0.415692
+0.040451 -0.384866 -0.342375
+
+0 -0.47 -0.415692
+0.0496144 -0.472049 -0.407639
+0 -0.572334 -0.459835
+
+0.060104 -0.571852 -0.450926
+0 -0.572334 -0.459835
+0.0496144 -0.472049 -0.407639
+
+0 -0.572334 -0.459835
+0.060104 -0.571852 -0.450926
+0 -0.68209 -0.479188
+
+0.0713544 -0.678892 -0.469904
+0 -0.68209 -0.479188
+0.060104 -0.571852 -0.450926
+
+0 -0.68209 -0.479188
+0.0713544 -0.678892 -0.469904
+0 -0.793351 -0.472708
+
+0.082759 -0.787399 -0.46355
+0 -0.793351 -0.472708
+0.0713544 -0.678892 -0.469904
+
+0 -0.793351 -0.472708
+0.082759 -0.787399 -0.46355
+0 -0.900118 -0.440744
+
+0.093703 -0.891524 -0.432205
+0 -0.900118 -0.440744
+0.082759 -0.787399 -0.46355
+
+0 -0.900118 -0.440744
+0.093703 -0.891524 -0.432205
+0 -0.996636 -0.385019
+
+0.103596 -0.985654 -0.37756
+0 -0.996636 -0.385019
+0.093703 -0.891524 -0.432205
+
+0 -0.996636 -0.385019
+0.103596 -0.985654 -0.37756
+0 -1.0777 -0.308538
+
+0.111906 -1.06471 -0.302561
+0 -1.0777 -0.308538
+0.103596 -0.985654 -0.37756
+
+0 -1.0777 -0.308538
+0.111906 -1.06471 -0.302561
+0 -1.13894 -0.215424
+
+0.118183 -1.12444 -0.21125
+0 -1.13894 -0.215424
+0.111906 -1.06471 -0.302561
+
+0 -1.13894 -0.215424
+0.118183 -1.12444 -0.21125
+0 -1.17706 -0.110696
+
+0.122091 -1.16161 -0.108551
+0 -1.17706 -0.110696
+0.118183 -1.12444 -0.21125
+
+0 -1.17706 -0.110696
+0.122091 -1.16161 -0.108551
+0 -1.19 0
+
+0.123417 -1.17423 0
+0 -1.19 0
+0.122091 -1.16161 -0.108551
+
+0.123417 -1.17423 0
+0.23987 -1.1285 0
+0.122091 -1.16161 0.108551
+
+0.237384 -1.1168 0.102327
+0.122091 -1.16161 0.108551
+0.23987 -1.1285 0
+
+0.122091 -1.16161 0.108551
+0.237384 -1.1168 0.102327
+0.118183 -1.12444 0.21125
+
+0.230058 -1.08234 0.199138
+0.118183 -1.12444 0.21125
+0.237384 -1.1168 0.102327
+
+0.118183 -1.12444 0.21125
+0.230058 -1.08234 0.199138
+0.111906 -1.06471 0.302561
+
+0.218287 -1.02696 0.285213
+0.111906 -1.06471 0.302561
+0.230058 -1.08234 0.199138
+
+0.111906 -1.06471 0.302561
+0.218287 -1.02696 0.285213
+0.103596 -0.985654 0.37756
+
+0.202707 -0.953662 0.355913
+0.103596 -0.985654 0.37756
+0.218287 -1.02696 0.285213
+
+0.103596 -0.985654 0.37756
+0.202707 -0.953662 0.355913
+0.093703 -0.891524 0.432205
+
+0.184157 -0.86639 0.407425
+0.093703 -0.891524 0.432205
+0.202707 -0.953662 0.355913
+
+0.093703 -0.891524 0.432205
+0.184157 -0.86639 0.407425
+0.082759 -0.787399 0.46355
+
+0.163637 -0.769851 0.436972
+0.082759 -0.787399 0.46355
+0.184157 -0.86639 0.407425
+
+0.082759 -0.787399 0.46355
+0.163637 -0.769851 0.436972
+0.0713544 -0.678892 0.469904
+
+0.142253 -0.669249 0.442963
+0.0713544 -0.678892 0.469904
+0.163637 -0.769851 0.436972
+
+0.0713544 -0.678892 0.469904
+0.142253 -0.669249 0.442963
+0.060104 -0.571852 0.450926
+
+0.121159 -0.570007 0.425073
+0.060104 -0.571852 0.450926
+0.142253 -0.669249 0.442963
+
+0.060104 -0.571852 0.450926
+0.121159 -0.570007 0.425073
+0.0496144 -0.472049 0.407639
+
+0.101491 -0.477476 0.384267
+0.0496144 -0.472049 0.407639
+0.121159 -0.570007 0.425073
+
+0.0496144 -0.472049 0.407639
+0.101491 -0.477476 0.384267
+0.040451 -0.384866 0.342375
+
+0.0843093 -0.396644 0.322745
+0.040451 -0.384866 0.342375
+0.101491 -0.477476 0.384267
+
+0.040451 -0.384866 0.342375
+0.0843093 -0.396644 0.322745
+0.0331079 -0.315 0.258654
+
+0.0705409 -0.331869 0.243824
+0.0331079 -0.315 0.258654
+0.0843093 -0.396644 0.322745
+
+0.0331079 -0.315 0.258654
+0.0705409 -0.331869 0.243824
+0.0279808 -0.26622 0.160989
+
+0.0609277 -0.286642 0.151759
+0.0279808 -0.26622 0.160989
+0.0705409 -0.331869 0.243824
+
+0.0279808 -0.26622 0.160989
+0.0609277 -0.286642 0.151759
+0.0253463 -0.241154 0.054645
+
+0.0559879 -0.263402 0.051512
+0.0253463 -0.241154 0.054645
+0.0609277 -0.286642 0.151759
+
+0.0253463 -0.241154 0.054645
+0.0559879 -0.263402 0.051512
+0.0253463 -0.241154 -0.054645
+
+0.0559879 -0.263402 -0.051512
+0.0253463 -0.241154 -0.054645
+0.0559879 -0.263402 0.051512
+
+0.0253463 -0.241154 -0.054645
+0.0559879 -0.263402 -0.051512
+0.0279808 -0.26622 -0.160989
+
+0.0609277 -0.286642 -0.151759
+0.0279808 -0.26622 -0.160989
+0.0559879 -0.263402 -0.051512
+
+0.0279808 -0.26622 -0.160989
+0.0609277 -0.286642 -0.151759
+0.0331079 -0.315 -0.258654
+
+0.0705409 -0.331869 -0.243824
+0.0331079 -0.315 -0.258654
+0.0609277 -0.286642 -0.151759
+
+0.0331079 -0.315 -0.258654
+0.0705409 -0.331869 -0.243824
+0.040451 -0.384866 -0.342375
+
+0.0843093 -0.396644 -0.322745
+0.040451 -0.384866 -0.342375
+0.0705409 -0.331869 -0.243824
+
+0.040451 -0.384866 -0.342375
+0.0843093 -0.396644 -0.322745
+0.0496144 -0.472049 -0.407639
+
+0.101491 -0.477476 -0.384267
+0.0496144 -0.472049 -0.407639
+0.0843093 -0.396644 -0.322745
+
+0.0496144 -0.472049 -0.407639
+0.101491 -0.477476 -0.384267
+0.060104 -0.571852 -0.450926
+
+0.121159 -0.570007 -0.425073
+0.060104 -0.571852 -0.450926
+0.101491 -0.477476 -0.384267
+
+0.060104 -0.571852 -0.450926
+0.121159 -0.570007 -0.425073
+0.0713544 -0.678892 -0.469904
+
+0.142253 -0.669249 -0.442963
+0.0713544 -0.678892 -0.469904
+0.121159 -0.570007 -0.425073
+
+0.0713544 -0.678892 -0.469904
+0.142253 -0.669249 -0.442963
+0.082759 -0.787399 -0.46355
+
+0.163637 -0.769851 -0.436972
+0.082759 -0.787399 -0.46355
+0.142253 -0.669249 -0.442963
+
+0.082759 -0.787399 -0.46355
+0.163637 -0.769851 -0.436972
+0.093703 -0.891524 -0.432205
+
+0.184157 -0.86639 -0.407425
+0.093703 -0.891524 -0.432205
+0.163637 -0.769851 -0.436972
+
+0.093703 -0.891524 -0.432205
+0.184157 -0.86639 -0.407425
+0.103596 -0.985654 -0.37756
+
+0.202707 -0.953662 -0.355913
+0.103596 -0.985654 -0.37756
+0.184157 -0.86639 -0.407425
+
+0.103596 -0.985654 -0.37756
+0.202707 -0.953662 -0.355913
+0.111906 -1.06471 -0.302561
+
+0.218287 -1.02696 -0.285213
+0.111906 -1.06471 -0.302561
+0.202707 -0.953662 -0.355913
+
+0.111906 -1.06471 -0.302561
+0.218287 -1.02696 -0.285213
+0.118183 -1.12444 -0.21125
+
+0.230058 -1.08234 -0.199138
+0.118183 -1.12444 -0.21125
+0.218287 -1.02696 -0.285213
+
+0.118183 -1.12444 -0.21125
+0.230058 -1.08234 -0.199138
+0.122091 -1.16161 -0.108551
+
+0.237384 -1.1168 -0.102327
+0.122091 -1.16161 -0.108551
+0.230058 -1.08234 -0.199138
+
+0.122091 -1.16161 -0.108551
+0.237384 -1.1168 -0.102327
+0.123417 -1.17423 0
+
+0.23987 -1.1285 0
+0.123417 -1.17423 0
+0.237384 -1.1168 -0.102327
+
+0.23987 -1.1285 0
+0.343528 -1.05727 0
+0.237384 -1.1168 0.102327
+
+0.340182 -1.04697 0.0926336
+0.237384 -1.1168 0.102327
+0.343528 -1.05727 0
+
+0.237384 -1.1168 0.102327
+0.340182 -1.04697 0.0926336
+0.230058 -1.08234 0.199138
+
+0.330325 -1.01664 0.180273
+0.230058 -1.08234 0.199138
+0.340182 -1.04697 0.0926336
+
+0.230058 -1.08234 0.199138
+0.330325 -1.01664 0.180273
+0.218287 -1.02696 0.285213
+
+0.314488 -0.967894 0.258194
+0.218287 -1.02696 0.285213
+0.330325 -1.01664 0.180273
+
+0.218287 -1.02696 0.285213
+0.314488 -0.967894 0.258194
+0.202707 -0.953662 0.355913
+
+0.293525 -0.903376 0.322196
+0.202707 -0.953662 0.355913
+0.314488 -0.967894 0.258194
+
+0.202707 -0.953662 0.355913
+0.293525 -0.903376 0.322196
+0.184157 -0.86639 0.407425
+
+0.268566 -0.82656 0.368828
+0.184157 -0.86639 0.407425
+0.293525 -0.903376 0.322196
+
+0.184157 -0.86639 0.407425
+0.268566 -0.82656 0.368828
+0.163637 -0.769851 0.436972
+
+0.240956 -0.741587 0.395577
+0.163637 -0.769851 0.436972
+0.268566 -0.82656 0.368828
+
+0.163637 -0.769851 0.436972
+0.240956 -0.741587 0.395577
+0.142253 -0.669249 0.442963
+
+0.212185 -0.653038 0.401
+0.142253 -0.669249 0.442963
+0.240956 -0.741587 0.395577
+
+0.142253 -0.669249 0.442963
+0.212185 -0.653038 0.401
+0.121159 -0.570007 0.425073
+
+0.183802 -0.565686 0.384804
+0.121159 -0.570007 0.425073
+0.212185 -0.653038 0.401
+
+0.121159 -0.570007 0.425073
+0.183802 -0.565686 0.384804
+0.101491 -0.477476 0.384267
+
+0.157339 -0.48424 0.347864
+0.101491 -0.477476 0.384267
+0.183802 -0.565686 0.384804
+
+0.101491 -0.477476 0.384267
+0.157339 -0.48424 0.347864
+0.0843093 -0.396644 0.322745
+
+0.134222 -0.413092 0.292171
+0.0843093 -0.396644 0.322745
+0.157339 -0.48424 0.347864
+
+0.0843093 -0.396644 0.322745
+0.134222 -0.413092 0.292171
+0.0705409 -0.331869 0.243824
+
+0.115697 -0.356077 0.220726
+0.0705409 -0.331869 0.243824
+0.134222 -0.413092 0.292171
+
+0.0705409 -0.331869 0.243824
+0.115697 -0.356077 0.220726
+0.0609277 -0.286642 0.151759
+
+0.102762 -0.316269 0.137382
+0.0609277 -0.286642 0.151759
+0.115697 -0.356077 0.220726
+
+0.0609277 -0.286642 0.151759
+0.102762 -0.316269 0.137382
+0.0559879 -0.263402 0.051512
+
+0.0961157 -0.295814 0.0466321
+0.0559879 -0.263402 0.051512
+0.102762 -0.316269 0.137382
+
+0.0559879 -0.263402 0.051512
+0.0961157 -0.295814 0.0466321
+0.0559879 -0.263402 -0.051512
+
+0.0961157 -0.295814 -0.0466321
+0.0559879 -0.263402 -0.051512
+0.0961157 -0.295814 0.0466321
+
+0.0559879 -0.263402 -0.051512
+0.0961157 -0.295814 -0.0466321
+0.0609277 -0.286642 -0.151759
+
+0.102762 -0.316269 -0.137382
+0.0609277 -0.286642 -0.151759
+0.0961157 -0.295814 -0.0466321
+
+0.0609277 -0.286642 -0.151759
+0.102762 -0.316269 -0.137382
+0.0705409 -0.331869 -0.243824
+
+0.115697 -0.356077 -0.220726
+0.0705409 -0.331869 -0.243824
+0.102762 -0.316269 -0.137382
+
+0.0705409 -0.331869 -0.243824
+0.115697 -0.356077 -0.220726
+0.0843093 -0.396644 -0.322745
+
+0.134222 -0.413092 -0.292171
+0.0843093 -0.396644 -0.322745
+0.115697 -0.356077 -0.220726
+
+0.0843093 -0.396644 -0.322745
+0.134222 -0.413092 -0.292171
+0.101491 -0.477476 -0.384267
+
+0.157339 -0.48424 -0.347864
+0.101491 -0.477476 -0.384267
+0.134222 -0.413092 -0.292171
+
+0.101491 -0.477476 -0.384267
+0.157339 -0.48424 -0.347864
+0.121159 -0.570007 -0.425073
+
+0.183802 -0.565686 -0.384804
+0.121159 -0.570007 -0.425073
+0.157339 -0.48424 -0.347864
+
+0.121159 -0.570007 -0.425073
+0.183802 -0.565686 -0.384804
+0.142253 -0.669249 -0.442963
+
+0.212185 -0.653038 -0.401
+0.142253 -0.669249 -0.442963
+0.183802 -0.565686 -0.384804
+
+0.142253 -0.669249 -0.442963
+0.212185 -0.653038 -0.401
+0.163637 -0.769851 -0.436972
+
+0.240956 -0.741587 -0.395577
+0.163637 -0.769851 -0.436972
+0.212185 -0.653038 -0.401
+
+0.163637 -0.769851 -0.436972
+0.240956 -0.741587 -0.395577
+0.184157 -0.86639 -0.407425
+
+0.268566 -0.82656 -0.368828
+0.184157 -0.86639 -0.407425
+0.240956 -0.741587 -0.395577
+
+0.184157 -0.86639 -0.407425
+0.268566 -0.82656 -0.368828
+0.202707 -0.953662 -0.355913
+
+0.293525 -0.903376 -0.322196
+0.202707 -0.953662 -0.355913
+0.268566 -0.82656 -0.368828
+
+0.202707 -0.953662 -0.355913
+0.293525 -0.903376 -0.322196
+0.218287 -1.02696 -0.285213
+
+0.314488 -0.967894 -0.258194
+0.218287 -1.02696 -0.285213
+0.293525 -0.903376 -0.322196
+
+0.218287 -1.02696 -0.285213
+0.314488 -0.967894 -0.258194
+0.230058 -1.08234 -0.199138
+
+0.330325 -1.01664 -0.180273
+0.230058 -1.08234 -0.199138
+0.314488 -0.967894 -0.258194
+
+0.230058 -1.08234 -0.199138
+0.330325 -1.01664 -0.180273
+0.237384 -1.1168 -0.102327
+
+0.340182 -1.04697 -0.0926336
+0.237384 -1.1168 -0.102327
+0.330325 -1.01664 -0.180273
+
+0.237384 -1.1168 -0.102327
+0.340182 -1.04697 -0.0926336
+0.23987 -1.1285 0
+
+0.343528 -1.05727 0
+0.23987 -1.1285 0
+0.340182 -1.04697 -0.0926336
+
+0.343528 -1.05727 0
+0.430617 -0.967183 0
+0.340182 -1.04697 0.0926336
+
+0.426794 -0.958596 0.0804188
+0.340182 -1.04697 0.0926336
+0.430617 -0.967183 0
+
+0.340182 -1.04697 0.0926336
+0.426794 -0.958596 0.0804188
+0.330325 -1.01664 0.180273
+
+0.415531 -0.933298 0.156502
+0.330325 -1.01664 0.180273
+0.426794 -0.958596 0.0804188
+
+0.330325 -1.01664 0.180273
+0.415531 -0.933298 0.156502
+0.314488 -0.967894 0.258194
+
+0.397435 -0.892653 0.224149
+0.314488 -0.967894 0.258194
+0.415531 -0.933298 0.156502
+
+0.314488 -0.967894 0.258194
+0.397435 -0.892653 0.224149
+0.293525 -0.903376 0.322196
+
+0.373481 -0.838851 0.279711
+0.293525 -0.903376 0.322196
+0.397435 -0.892653 0.224149
+
+0.293525 -0.903376 0.322196
+0.373481 -0.838851 0.279711
+0.268566 -0.82656 0.368828
+
+0.344961 -0.774795 0.320194
+0.268566 -0.82656 0.368828
+0.373481 -0.838851 0.279711
+
+0.268566 -0.82656 0.368828
+0.344961 -0.774795 0.320194
+0.240956 -0.741587 0.395577
+
+0.313412 -0.703936 0.343415
+0.240956 -0.741587 0.395577
+0.344961 -0.774795 0.320194
+
+0.240956 -0.741587 0.395577
+0.313412 -0.703936 0.343415
+0.212185 -0.653038 0.401
+
+0.280536 -0.630094 0.348123
+0.212185 -0.653038 0.401
+0.313412 -0.703936 0.343415
+
+0.212185 -0.653038 0.401
+0.280536 -0.630094 0.348123
+0.183802 -0.565686 0.384804
+
+0.248104 -0.557252 0.334064
+0.183802 -0.565686 0.384804
+0.280536 -0.630094 0.348123
+
+0.183802 -0.565686 0.384804
+0.248104 -0.557252 0.334064
+0.157339 -0.48424 0.347864
+
+0.217866 -0.489335 0.301995
+0.157339 -0.48424 0.347864
+0.248104 -0.557252 0.334064
+
+0.157339 -0.48424 0.347864
+0.217866 -0.489335 0.301995
+0.134222 -0.413092 0.292171
+
+0.19145 -0.430004 0.253645
+0.134222 -0.413092 0.292171
+0.217866 -0.489335 0.301995
+
+0.134222 -0.413092 0.292171
+0.19145 -0.430004 0.253645
+0.115697 -0.356077 0.220726
+
+0.170282 -0.38246 0.191621
+0.115697 -0.356077 0.220726
+0.19145 -0.430004 0.253645
+
+0.115697 -0.356077 0.220726
+0.170282 -0.38246 0.191621
+0.102762 -0.316269 0.137382
+
+0.155502 -0.349264 0.119267
+0.102762 -0.316269 0.137382
+0.170282 -0.38246 0.191621
+
+0.102762 -0.316269 0.137382
+0.155502 -0.349264 0.119267
+0.0961157 -0.295814 0.0466321
+
+0.147908 -0.332206 0.0404831
+0.0961157 -0.295814 0.0466321
+0.155502 -0.349264 0.119267
+
+0.0961157 -0.295814 0.0466321
+0.147908 -0.332206 0.0404831
+0.0961157 -0.295814 -0.0466321
+
+0.147908 -0.332206 -0.0404831
+0.0961157 -0.295814 -0.0466321
+0.147908 -0.332206 0.0404831
+
+0.0961157 -0.295814 -0.0466321
+0.147908 -0.332206 -0.0404831
+0.102762 -0.316269 -0.137382
+
+0.155502 -0.349264 -0.119267
+0.102762 -0.316269 -0.137382
+0.147908 -0.332206 -0.0404831
+
+0.102762 -0.316269 -0.137382
+0.155502 -0.349264 -0.119267
+0.115697 -0.356077 -0.220726
+
+0.170282 -0.38246 -0.191621
+0.115697 -0.356077 -0.220726
+0.155502 -0.349264 -0.119267
+
+0.115697 -0.356077 -0.220726
+0.170282 -0.38246 -0.191621
+0.134222 -0.413092 -0.292171
+
+0.19145 -0.430004 -0.253645
+0.134222 -0.413092 -0.292171
+0.170282 -0.38246 -0.191621
+
+0.134222 -0.413092 -0.292171
+0.19145 -0.430004 -0.253645
+0.157339 -0.48424 -0.347864
+
+0.217866 -0.489335 -0.301995
+0.157339 -0.48424 -0.347864
+0.19145 -0.430004 -0.253645
+
+0.157339 -0.48424 -0.347864
+0.217866 -0.489335 -0.301995
+0.183802 -0.565686 -0.384804
+
+0.248104 -0.557252 -0.334064
+0.183802 -0.565686 -0.384804
+0.217866 -0.489335 -0.301995
+
+0.183802 -0.565686 -0.384804
+0.248104 -0.557252 -0.334064
+0.212185 -0.653038 -0.401
+
+0.280536 -0.630094 -0.348123
+0.212185 -0.653038 -0.401
+0.248104 -0.557252 -0.334064
+
+0.212185 -0.653038 -0.401
+0.280536 -0.630094 -0.348123
+0.240956 -0.741587 -0.395577
+
+0.313412 -0.703936 -0.343415
+0.240956 -0.741587 -0.395577
+0.280536 -0.630094 -0.348123
+
+0.240956 -0.741587 -0.395577
+0.313412 -0.703936 -0.343415
+0.268566 -0.82656 -0.368828
+
+0.344961 -0.774795 -0.320194
+0.268566 -0.82656 -0.368828
+0.313412 -0.703936 -0.343415
+
+0.268566 -0.82656 -0.368828
+0.344961 -0.774795 -0.320194
+0.293525 -0.903376 -0.322196
+
+0.373481 -0.838851 -0.279711
+0.293525 -0.903376 -0.322196
+0.344961 -0.774795 -0.320194
+
+0.293525 -0.903376 -0.322196
+0.373481 -0.838851 -0.279711
+0.314488 -0.967894 -0.258194
+
+0.397435 -0.892653 -0.224149
+0.314488 -0.967894 -0.258194
+0.373481 -0.838851 -0.279711
+
+0.314488 -0.967894 -0.258194
+0.397435 -0.892653 -0.224149
+0.330325 -1.01664 -0.180273
+
+0.415531 -0.933298 -0.156502
+0.330325 -1.01664 -0.180273
+0.397435 -0.892653 -0.224149
+
+0.330325 -1.01664 -0.180273
+0.415531 -0.933298 -0.156502
+0.340182 -1.04697 -0.0926336
+
+0.426794 -0.958596 -0.0804188
+0.340182 -1.04697 -0.0926336
+0.415531 -0.933298 -0.156502
+
+0.340182 -1.04697 -0.0926336
+0.426794 -0.958596 -0.0804188
+0.343528 -1.05727 0
+
+0.430617 -0.967183 0
+0.343528 -1.05727 0
+0.426794 -0.958596 -0.0804188
+
+0.430617 -0.967183 0
+0.5 -0.866025 0
+0.426794 -0.958596 0.0804188
+
+0.496092 -0.859256 0.0668786
+0.426794 -0.958596 0.0804188
+0.5 -0.866025 0
+
+0.426794 -0.958596 0.0804188
+0.496092 -0.859256 0.0668786
+0.415531 -0.933298 0.156502
+
+0.484577 -0.839312 0.130152
+0.415531 -0.933298 0.156502
+0.496092 -0.859256 0.0668786
+
+0.415531 -0.933298 0.156502
+0.484577 -0.839312 0.130152
+0.397435 -0.892653 0.224149
+
+0.466076 -0.807268 0.186408
+0.397435 -0.892653 0.224149
+0.484577 -0.839312 0.130152
+
+0.397435 -0.892653 0.224149
+0.466076 -0.807268 0.186408
+0.373481 -0.838851 0.279711
+
+0.441588 -0.764853 0.232616
+0.373481 -0.838851 0.279711
+0.466076 -0.807268 0.186408
+
+0.373481 -0.838851 0.279711
+0.441588 -0.764853 0.232616
+0.344961 -0.774795 0.320194
+
+0.412432 -0.714352 0.266283
+0.344961 -0.774795 0.320194
+0.441588 -0.764853 0.232616
+
+0.344961 -0.774795 0.320194
+0.412432 -0.714352 0.266283
+0.313412 -0.703936 0.343415
+
+0.380179 -0.658489 0.285594
+0.313412 -0.703936 0.343415
+0.412432 -0.714352 0.266283
+
+0.313412 -0.703936 0.343415
+0.380179 -0.658489 0.285594
+0.280536 -0.630094 0.348123
+
+0.346569 -0.600275 0.289509
+0.280536 -0.630094 0.348123
+0.380179 -0.658489 0.285594
+
+0.280536 -0.630094 0.348123
+0.346569 -0.600275 0.289509
+0.248104 -0.557252 0.334064
+
+0.313414 -0.542848 0.277817
+0.248104 -0.557252 0.334064
+0.346569 -0.600275 0.289509
+
+0.248104 -0.557252 0.334064
+0.313414 -0.542848 0.277817
+0.217866 -0.489335 0.301995
+
+0.2825 -0.489304 0.251147
+0.217866 -0.489335 0.301995
+0.313414 -0.542848 0.277817
+
+0.217866 -0.489335 0.301995
+0.2825 -0.489304 0.251147
+0.19145 -0.430004 0.253645
+
+0.255495 -0.44253 0.210938
+0.19145 -0.430004 0.253645
+0.2825 -0.489304 0.251147
+
+0.19145 -0.430004 0.253645
+0.255495 -0.44253 0.210938
+0.170282 -0.38246 0.191621
+
+0.233854 -0.405047 0.159358
+0.170282 -0.38246 0.191621
+0.255495 -0.44253 0.210938
+
+0.170282 -0.38246 0.191621
+0.233854 -0.405047 0.159358
+0.155502 -0.349264 0.119267
+
+0.218745 -0.378877 0.0991858
+0.155502 -0.349264 0.119267
+0.233854 -0.405047 0.159358
+
+0.155502 -0.349264 0.119267
+0.218745 -0.378877 0.0991858
+0.147908 -0.332206 0.0404831
+
+0.21098 -0.365429 0.0336669
+0.147908 -0.332206 0.0404831
+0.218745 -0.378877 0.0991858
+
+0.147908 -0.332206 0.0404831
+0.21098 -0.365429 0.0336669
+0.147908 -0.332206 -0.0404831
+
+0.21098 -0.365429 -0.0336669
+0.147908 -0.332206 -0.0404831
+0.21098 -0.365429 0.0336669
+
+0.147908 -0.332206 -0.0404831
+0.21098 -0.365429 -0.0336669
+0.155502 -0.349264 -0.119267
+
+0.218745 -0.378877 -0.0991858
+0.155502 -0.349264 -0.119267
+0.21098 -0.365429 -0.0336669
+
+0.155502 -0.349264 -0.119267
+0.218745 -0.378877 -0.0991858
+0.170282 -0.38246 -0.191621
+
+0.233854 -0.405047 -0.159358
+0.170282 -0.38246 -0.191621
+0.218745 -0.378877 -0.0991858
+
+0.170282 -0.38246 -0.191621
+0.233854 -0.405047 -0.159358
+0.19145 -0.430004 -0.253645
+
+0.255495 -0.44253 -0.210938
+0.19145 -0.430004 -0.253645
+0.233854 -0.405047 -0.159358
+
+0.19145 -0.430004 -0.253645
+0.255495 -0.44253 -0.210938
+0.217866 -0.489335 -0.301995
+
+0.2825 -0.489304 -0.251147
+0.217866 -0.489335 -0.301995
+0.255495 -0.44253 -0.210938
+
+0.217866 -0.489335 -0.301995
+0.2825 -0.489304 -0.251147
+0.248104 -0.557252 -0.334064
+
+0.313414 -0.542848 -0.277817
+0.248104 -0.557252 -0.334064
+0.2825 -0.489304 -0.251147
+
+0.248104 -0.557252 -0.334064
+0.313414 -0.542848 -0.277817
+0.280536 -0.630094 -0.348123
+
+0.346569 -0.600275 -0.289509
+0.280536 -0.630094 -0.348123
+0.313414 -0.542848 -0.277817
+
+0.280536 -0.630094 -0.348123
+0.346569 -0.600275 -0.289509
+0.313412 -0.703936 -0.343415
+
+0.380179 -0.658489 -0.285594
+0.313412 -0.703936 -0.343415
+0.346569 -0.600275 -0.289509
+
+0.313412 -0.703936 -0.343415
+0.380179 -0.658489 -0.285594
+0.344961 -0.774795 -0.320194
+
+0.412432 -0.714352 -0.266283
+0.344961 -0.774795 -0.320194
+0.380179 -0.658489 -0.285594
+
+0.344961 -0.774795 -0.320194
+0.412432 -0.714352 -0.266283
+0.373481 -0.838851 -0.279711
+
+0.441588 -0.764853 -0.232616
+0.373481 -0.838851 -0.279711
+0.412432 -0.714352 -0.266283
+
+0.373481 -0.838851 -0.279711
+0.441588 -0.764853 -0.232616
+0.397435 -0.892653 -0.224149
+
+0.466076 -0.807268 -0.186408
+0.397435 -0.892653 -0.224149
+0.441588 -0.764853 -0.232616
+
+0.397435 -0.892653 -0.224149
+0.466076 -0.807268 -0.186408
+0.415531 -0.933298 -0.156502
+
+0.484577 -0.839312 -0.130152
+0.415531 -0.933298 -0.156502
+0.466076 -0.807268 -0.186408
+
+0.415531 -0.933298 -0.156502
+0.484577 -0.839312 -0.130152
+0.426794 -0.958596 -0.0804188
+
+0.496092 -0.859256 -0.0668786
+0.426794 -0.958596 -0.0804188
+0.484577 -0.839312 -0.130152
+
+0.426794 -0.958596 -0.0804188
+0.496092 -0.859256 -0.0668786
+0.430617 -0.967183 0
+
+0.5 -0.866025 0
+0.430617 -0.967183 0
+0.496092 -0.859256 -0.0668786
+
+0.5 -0.866025 0
+0.553274 -0.761517 0
+0.496092 -0.859256 0.0668786
+
+0.54961 -0.756473 0.0533384
+0.496092 -0.859256 0.0668786
+0.553274 -0.761517 0
+
+0.496092 -0.859256 0.0668786
+0.54961 -0.756473 0.0533384
+0.484577 -0.839312 0.130152
+
+0.538814 -0.741614 0.103801
+0.484577 -0.839312 0.130152
+0.54961 -0.756473 0.0533384
+
+0.484577 -0.839312 0.130152
+0.538814 -0.741614 0.103801
+0.466076 -0.807268 0.186408
+
+0.521469 -0.71774 0.148668
+0.466076 -0.807268 0.186408
+0.538814 -0.741614 0.103801
+
+0.466076 -0.807268 0.186408
+0.521469 -0.71774 0.148668
+0.441588 -0.764853 0.232616
+
+0.498509 -0.686139 0.18552
+0.441588 -0.764853 0.232616
+0.521469 -0.71774 0.148668
+
+0.441588 -0.764853 0.232616
+0.498509 -0.686139 0.18552
+0.412432 -0.714352 0.266283
+
+0.471173 -0.648515 0.212371
+0.412432 -0.714352 0.266283
+0.498509 -0.686139 0.18552
+
+0.412432 -0.714352 0.266283
+0.471173 -0.648515 0.212371
+0.380179 -0.658489 0.285594
+
+0.440934 -0.606894 0.227773
+0.380179 -0.658489 0.285594
+0.471173 -0.648515 0.212371
+
+0.380179 -0.658489 0.285594
+0.440934 -0.606894 0.227773
+0.346569 -0.600275 0.289509
+
+0.409423 -0.563522 0.230895
+0.346569 -0.600275 0.289509
+0.440934 -0.606894 0.227773
+
+0.346569 -0.600275 0.289509
+0.409423 -0.563522 0.230895
+0.313414 -0.542848 0.277817
+
+0.378338 -0.520737 0.22157
+0.313414 -0.542848 0.277817
+0.409423 -0.563522 0.230895
+
+0.313414 -0.542848 0.277817
+0.378338 -0.520737 0.22157
+0.2825 -0.489304 0.251147
+
+0.349354 -0.480845 0.2003
+0.2825 -0.489304 0.251147
+0.378338 -0.520737 0.22157
+
+0.2825 -0.489304 0.251147
+0.349354 -0.480845 0.2003
+0.255495 -0.44253 0.210938
+
+0.324035 -0.445996 0.168232
+0.255495 -0.44253 0.210938
+0.349354 -0.480845 0.2003
+
+0.255495 -0.44253 0.210938
+0.324035 -0.445996 0.168232
+0.233854 -0.405047 0.159358
+
+0.303746 -0.41807 0.127094
+0.233854 -0.405047 0.159358
+0.324035 -0.445996 0.168232
+
+0.233854 -0.405047 0.159358
+0.303746 -0.41807 0.127094
+0.218745 -0.378877 0.0991858
+
+0.289579 -0.398572 0.0791047
+0.218745 -0.378877 0.0991858
+0.303746 -0.41807 0.127094
+
+0.218745 -0.378877 0.0991858
+0.289579 -0.398572 0.0791047
+0.21098 -0.365429 0.0336669
+
+0.2823 -0.388552 0.0268508
+0.21098 -0.365429 0.0336669
+0.289579 -0.398572 0.0791047
+
+0.21098 -0.365429 0.0336669
+0.2823 -0.388552 0.0268508
+0.21098 -0.365429 -0.0336669
+
+0.2823 -0.388552 -0.0268508
+0.21098 -0.365429 -0.0336669
+0.2823 -0.388552 0.0268508
+
+0.21098 -0.365429 -0.0336669
+0.2823 -0.388552 -0.0268508
+0.218745 -0.378877 -0.0991858
+
+0.289579 -0.398572 -0.0791047
+0.218745 -0.378877 -0.0991858
+0.2823 -0.388552 -0.0268508
+
+0.218745 -0.378877 -0.0991858
+0.289579 -0.398572 -0.0791047
+0.233854 -0.405047 -0.159358
+
+0.303746 -0.41807 -0.127094
+0.233854 -0.405047 -0.159358
+0.289579 -0.398572 -0.0791047
+
+0.233854 -0.405047 -0.159358
+0.303746 -0.41807 -0.127094
+0.255495 -0.44253 -0.210938
+
+0.324035 -0.445996 -0.168232
+0.255495 -0.44253 -0.210938
+0.303746 -0.41807 -0.127094
+
+0.255495 -0.44253 -0.210938
+0.324035 -0.445996 -0.168232
+0.2825 -0.489304 -0.251147
+
+0.349354 -0.480845 -0.2003
+0.2825 -0.489304 -0.251147
+0.324035 -0.445996 -0.168232
+
+0.2825 -0.489304 -0.251147
+0.349354 -0.480845 -0.2003
+0.313414 -0.542848 -0.277817
+
+0.378338 -0.520737 -0.22157
+0.313414 -0.542848 -0.277817
+0.349354 -0.480845 -0.2003
+
+0.313414 -0.542848 -0.277817
+0.378338 -0.520737 -0.22157
+0.346569 -0.600275 -0.289509
+
+0.409423 -0.563522 -0.230895
+0.346569 -0.600275 -0.289509
+0.378338 -0.520737 -0.22157
+
+0.346569 -0.600275 -0.289509
+0.409423 -0.563522 -0.230895
+0.380179 -0.658489 -0.285594
+
+0.440934 -0.606894 -0.227773
+0.380179 -0.658489 -0.285594
+0.409423 -0.563522 -0.230895
+
+0.380179 -0.658489 -0.285594
+0.440934 -0.606894 -0.227773
+0.412432 -0.714352 -0.266283
+
+0.471173 -0.648515 -0.212371
+0.412432 -0.714352 -0.266283
+0.440934 -0.606894 -0.227773
+
+0.412432 -0.714352 -0.266283
+0.471173 -0.648515 -0.212371
+0.441588 -0.764853 -0.232616
+
+0.498509 -0.686139 -0.18552
+0.441588 -0.764853 -0.232616
+0.471173 -0.648515 -0.212371
+
+0.441588 -0.764853 -0.232616
+0.498509 -0.686139 -0.18552
+0.466076 -0.807268 -0.186408
+
+0.521469 -0.71774 -0.148668
+0.466076 -0.807268 -0.186408
+0.498509 -0.686139 -0.18552
+
+0.466076 -0.807268 -0.186408
+0.521469 -0.71774 -0.148668
+0.484577 -0.839312 -0.130152
+
+0.538814 -0.741614 -0.103801
+0.484577 -0.839312 -0.130152
+0.521469 -0.71774 -0.148668
+
+0.484577 -0.839312 -0.130152
+0.538814 -0.741614 -0.103801
+0.496092 -0.859256 -0.0668786
+
+0.54961 -0.756473 -0.0533384
+0.496092 -0.859256 -0.0668786
+0.538814 -0.741614 -0.103801
+
+0.496092 -0.859256 -0.0668786
+0.54961 -0.756473 -0.0533384
+0.5 -0.866025 0
+
+0.553274 -0.761517 0
+0.5 -0.866025 0
+0.54961 -0.756473 -0.0533384
+
+0.553274 -0.761517 0
+0.594403 -0.660151 0
+0.54961 -0.756473 0.0533384
+
+0.591186 -0.656579 0.0411236
+0.54961 -0.756473 0.0533384
+0.594403 -0.660151 0
+
+0.54961 -0.756473 0.0533384
+0.591186 -0.656579 0.0411236
+0.538814 -0.741614 0.103801
+
+0.581711 -0.646055 0.0800302
+0.538814 -0.741614 0.103801
+0.591186 -0.656579 0.0411236
+
+0.538814 -0.741614 0.103801
+0.581711 -0.646055 0.0800302
+0.521469 -0.71774 0.148668
+
+0.566487 -0.629148 0.114622
+0.521469 -0.71774 0.148668
+0.581711 -0.646055 0.0800302
+
+0.521469 -0.71774 0.148668
+0.566487 -0.629148 0.114622
+0.498509 -0.686139 0.18552
+
+0.546336 -0.606767 0.143035
+0.498509 -0.686139 0.18552
+0.566487 -0.629148 0.114622
+
+0.498509 -0.686139 0.18552
+0.546336 -0.606767 0.143035
+0.471173 -0.648515 0.212371
+
+0.522343 -0.580121 0.163737
+0.471173 -0.648515 0.212371
+0.546336 -0.606767 0.143035
+
+0.471173 -0.648515 0.212371
+0.522343 -0.580121 0.163737
+0.440934 -0.606894 0.227773
+
+0.495802 -0.550644 0.175612
+0.440934 -0.606894 0.227773
+0.522343 -0.580121 0.163737
+
+0.440934 -0.606894 0.227773
+0.495802 -0.550644 0.175612
+0.409423 -0.563522 0.230895
+
+0.468145 -0.519928 0.178019
+0.409423 -0.563522 0.230895
+0.495802 -0.550644 0.175612
+
+0.409423 -0.563522 0.230895
+0.468145 -0.519928 0.178019
+0.378338 -0.520737 0.22157
+
+0.440861 -0.489626 0.170829
+0.378338 -0.520737 0.22157
+0.468145 -0.519928 0.178019
+
+0.378338 -0.520737 0.22157
+0.440861 -0.489626 0.170829
+0.349354 -0.480845 0.2003
+
+0.415423 -0.461374 0.15443
+0.349354 -0.480845 0.2003
+0.440861 -0.489626 0.170829
+
+0.349354 -0.480845 0.2003
+0.415423 -0.461374 0.15443
+0.324035 -0.445996 0.168232
+
+0.3932 -0.436693 0.129706
+0.324035 -0.445996 0.168232
+0.415423 -0.461374 0.15443
+
+0.324035 -0.445996 0.168232
+0.3932 -0.436693 0.129706
+0.303746 -0.41807 0.127094
+
+0.375392 -0.416916 0.0979889
+0.303746 -0.41807 0.127094
+0.3932 -0.436693 0.129706
+
+0.303746 -0.41807 0.127094
+0.375392 -0.416916 0.0979889
+0.289579 -0.398572 0.0791047
+
+0.362959 -0.403106 0.0609893
+0.289579 -0.398572 0.0791047
+0.375392 -0.416916 0.0979889
+
+0.289579 -0.398572 0.0791047
+0.362959 -0.403106 0.0609893
+0.2823 -0.388552 0.0268508
+
+0.35657 -0.396011 0.0207018
+0.2823 -0.388552 0.0268508
+0.362959 -0.403106 0.0609893
+
+0.2823 -0.388552 0.0268508
+0.35657 -0.396011 0.0207018
+0.2823 -0.388552 -0.0268508
+
+0.35657 -0.396011 -0.0207018
+0.2823 -0.388552 -0.0268508
+0.35657 -0.396011 0.0207018
+
+0.2823 -0.388552 -0.0268508
+0.35657 -0.396011 -0.0207018
+0.289579 -0.398572 -0.0791047
+
+0.362959 -0.403106 -0.0609893
+0.289579 -0.398572 -0.0791047
+0.35657 -0.396011 -0.0207018
+
+0.289579 -0.398572 -0.0791047
+0.362959 -0.403106 -0.0609893
+0.303746 -0.41807 -0.127094
+
+0.375392 -0.416916 -0.0979889
+0.303746 -0.41807 -0.127094
+0.362959 -0.403106 -0.0609893
+
+0.303746 -0.41807 -0.127094
+0.375392 -0.416916 -0.0979889
+0.324035 -0.445996 -0.168232
+
+0.3932 -0.436693 -0.129706
+0.324035 -0.445996 -0.168232
+0.375392 -0.416916 -0.0979889
+
+0.324035 -0.445996 -0.168232
+0.3932 -0.436693 -0.129706
+0.349354 -0.480845 -0.2003
+
+0.415423 -0.461374 -0.15443
+0.349354 -0.480845 -0.2003
+0.3932 -0.436693 -0.129706
+
+0.349354 -0.480845 -0.2003
+0.415423 -0.461374 -0.15443
+0.378338 -0.520737 -0.22157
+
+0.440861 -0.489626 -0.170829
+0.378338 -0.520737 -0.22157
+0.415423 -0.461374 -0.15443
+
+0.378338 -0.520737 -0.22157
+0.440861 -0.489626 -0.170829
+0.409423 -0.563522 -0.230895
+
+0.468145 -0.519928 -0.178019
+0.409423 -0.563522 -0.230895
+0.440861 -0.489626 -0.170829
+
+0.409423 -0.563522 -0.230895
+0.468145 -0.519928 -0.178019
+0.440934 -0.606894 -0.227773
+
+0.495802 -0.550644 -0.175612
+0.440934 -0.606894 -0.227773
+0.468145 -0.519928 -0.178019
+
+0.440934 -0.606894 -0.227773
+0.495802 -0.550644 -0.175612
+0.471173 -0.648515 -0.212371
+
+0.522343 -0.580121 -0.163737
+0.471173 -0.648515 -0.212371
+0.495802 -0.550644 -0.175612
+
+0.471173 -0.648515 -0.212371
+0.522343 -0.580121 -0.163737
+0.498509 -0.686139 -0.18552
+
+0.546336 -0.606767 -0.143035
+0.498509 -0.686139 -0.18552
+0.522343 -0.580121 -0.163737
+
+0.498509 -0.686139 -0.18552
+0.546336 -0.606767 -0.143035
+0.521469 -0.71774 -0.148668
+
+0.566487 -0.629148 -0.114622
+0.521469 -0.71774 -0.148668
+0.546336 -0.606767 -0.143035
+
+0.521469 -0.71774 -0.148668
+0.566487 -0.629148 -0.114622
+0.538814 -0.741614 -0.103801
+
+0.581711 -0.646055 -0.0800302
+0.538814 -0.741614 -0.103801
+0.566487 -0.629148 -0.114622
+
+0.538814 -0.741614 -0.103801
+0.581711 -0.646055 -0.0800302
+0.54961 -0.756473 -0.0533384
+
+0.591186 -0.656579 -0.0411236
+0.54961 -0.756473 -0.0533384
+0.581711 -0.646055 -0.0800302
+
+0.54961 -0.756473 -0.0533384
+0.591186 -0.656579 -0.0411236
+0.553274 -0.761517 0
+
+0.594403 -0.660151 0
+0.553274 -0.761517 0
+0.591186 -0.656579 -0.0411236
+
+0.594403 -0.660151 0
+0.628914 -0.566276 0
+0.591186 -0.656579 0.0411236
+
+0.626184 -0.563818 0.0314299
+0.591186 -0.656579 0.0411236
+0.628914 -0.566276 0
+
+0.591186 -0.656579 0.0411236
+0.626184 -0.563818 0.0314299
+0.581711 -0.646055 0.0800302
+
+0.618141 -0.556576 0.0611654
+0.581711 -0.646055 0.0800302
+0.626184 -0.563818 0.0314299
+
+0.581711 -0.646055 0.0800302
+0.618141 -0.556576 0.0611654
+0.566487 -0.629148 0.114622
+
+0.605218 -0.544941 0.0876034
+0.566487 -0.629148 0.114622
+0.618141 -0.556576 0.0611654
+
+0.566487 -0.629148 0.114622
+0.605218 -0.544941 0.0876034
+0.546336 -0.606767 0.143035
+
+0.588114 -0.52954 0.109319
+0.546336 -0.606767 0.143035
+0.605218 -0.544941 0.0876034
+
+0.546336 -0.606767 0.143035
+0.588114 -0.52954 0.109319
+0.522343 -0.580121 0.163737
+
+0.567748 -0.511203 0.125141
+0.522343 -0.580121 0.163737
+0.588114 -0.52954 0.109319
+
+0.522343 -0.580121 0.163737
+0.567748 -0.511203 0.125141
+0.495802 -0.550644 0.175612
+
+0.54522 -0.490918 0.134216
+0.495802 -0.550644 0.175612
+0.567748 -0.511203 0.125141
+
+0.495802 -0.550644 0.175612
+0.54522 -0.490918 0.134216
+0.468145 -0.519928 0.178019
+
+0.521744 -0.46978 0.136056
+0.468145 -0.519928 0.178019
+0.54522 -0.490918 0.134216
+
+0.468145 -0.519928 0.178019
+0.521744 -0.46978 0.136056
+0.440861 -0.489626 0.170829
+
+0.498585 -0.448928 0.130561
+0.440861 -0.489626 0.170829
+0.521744 -0.46978 0.136056
+
+0.440861 -0.489626 0.170829
+0.498585 -0.448928 0.130561
+0.415423 -0.461374 0.15443
+
+0.476992 -0.429486 0.118028
+0.415423 -0.461374 0.15443
+0.498585 -0.448928 0.130561
+
+0.415423 -0.461374 0.15443
+0.476992 -0.429486 0.118028
+0.3932 -0.436693 0.129706
+
+0.45813 -0.412502 0.0991314
+0.3932 -0.436693 0.129706
+0.476992 -0.429486 0.118028
+
+0.3932 -0.436693 0.129706
+0.45813 -0.412502 0.0991314
+0.375392 -0.416916 0.0979889
+
+0.443014 -0.398892 0.0748908
+0.375392 -0.416916 0.0979889
+0.45813 -0.412502 0.0991314
+
+0.375392 -0.416916 0.0979889
+0.443014 -0.398892 0.0748908
+0.362959 -0.403106 0.0609893
+
+0.43246 -0.389389 0.0466128
+0.362959 -0.403106 0.0609893
+0.443014 -0.398892 0.0748908
+
+0.362959 -0.403106 0.0609893
+0.43246 -0.389389 0.0466128
+0.35657 -0.396011 0.0207018
+
+0.427037 -0.384506 0.0158219
+0.35657 -0.396011 0.0207018
+0.43246 -0.389389 0.0466128
+
+0.35657 -0.396011 0.0207018
+0.427037 -0.384506 0.0158219
+0.35657 -0.396011 -0.0207018
+
+0.427037 -0.384506 -0.0158219
+0.35657 -0.396011 -0.0207018
+0.427037 -0.384506 0.0158219
+
+0.35657 -0.396011 -0.0207018
+0.427037 -0.384506 -0.0158219
+0.362959 -0.403106 -0.0609893
+
+0.43246 -0.389389 -0.0466128
+0.362959 -0.403106 -0.0609893
+0.427037 -0.384506 -0.0158219
+
+0.362959 -0.403106 -0.0609893
+0.43246 -0.389389 -0.0466128
+0.375392 -0.416916 -0.0979889
+
+0.443014 -0.398892 -0.0748908
+0.375392 -0.416916 -0.0979889
+0.43246 -0.389389 -0.0466128
+
+0.375392 -0.416916 -0.0979889
+0.443014 -0.398892 -0.0748908
+0.3932 -0.436693 -0.129706
+
+0.45813 -0.412502 -0.0991314
+0.3932 -0.436693 -0.129706
+0.443014 -0.398892 -0.0748908
+
+0.3932 -0.436693 -0.129706
+0.45813 -0.412502 -0.0991314
+0.415423 -0.461374 -0.15443
+
+0.476992 -0.429486 -0.118028
+0.415423 -0.461374 -0.15443
+0.45813 -0.412502 -0.0991314
+
+0.415423 -0.461374 -0.15443
+0.476992 -0.429486 -0.118028
+0.440861 -0.489626 -0.170829
+
+0.498585 -0.448928 -0.130561
+0.440861 -0.489626 -0.170829
+0.476992 -0.429486 -0.118028
+
+0.440861 -0.489626 -0.170829
+0.498585 -0.448928 -0.130561
+0.468145 -0.519928 -0.178019
+
+0.521744 -0.46978 -0.136056
+0.468145 -0.519928 -0.178019
+0.498585 -0.448928 -0.130561
+
+0.468145 -0.519928 -0.178019
+0.521744 -0.46978 -0.136056
+0.495802 -0.550644 -0.175612
+
+0.54522 -0.490918 -0.134216
+0.495802 -0.550644 -0.175612
+0.521744 -0.46978 -0.136056
+
+0.495802 -0.550644 -0.175612
+0.54522 -0.490918 -0.134216
+0.522343 -0.580121 -0.163737
+
+0.567748 -0.511203 -0.125141
+0.522343 -0.580121 -0.163737
+0.54522 -0.490918 -0.134216
+
+0.522343 -0.580121 -0.163737
+0.567748 -0.511203 -0.125141
+0.546336 -0.606767 -0.143035
+
+0.588114 -0.52954 -0.109319
+0.546336 -0.606767 -0.143035
+0.567748 -0.511203 -0.125141
+
+0.546336 -0.606767 -0.143035
+0.588114 -0.52954 -0.109319
+0.566487 -0.629148 -0.114622
+
+0.605218 -0.544941 -0.0876034
+0.566487 -0.629148 -0.114622
+0.588114 -0.52954 -0.109319
+
+0.566487 -0.629148 -0.114622
+0.605218 -0.544941 -0.0876034
+0.581711 -0.646055 -0.0800302
+
+0.618141 -0.556576 -0.0611654
+0.581711 -0.646055 -0.0800302
+0.605218 -0.544941 -0.0876034
+
+0.581711 -0.646055 -0.0800302
+0.618141 -0.556576 -0.0611654
+0.591186 -0.656579 -0.0411236
+
+0.626184 -0.563818 -0.0314299
+0.591186 -0.656579 -0.0411236
+0.618141 -0.556576 -0.0611654
+
+0.591186 -0.656579 -0.0411236
+0.626184 -0.563818 -0.0314299
+0.594403 -0.660151 0
+
+0.628914 -0.566276 0
+0.594403 -0.660151 0
+0.626184 -0.563818 -0.0314299
+
+0.628914 -0.566276 0
+0.662827 -0.481572 0
+0.626184 -0.563818 0.0314299
+
+0.660444 -0.47984 0.0252061
+0.626184 -0.563818 0.0314299
+0.662827 -0.481572 0
+
+0.626184 -0.563818 0.0314299
+0.660444 -0.47984 0.0252061
+0.618141 -0.556576 0.0611654
+
+0.653421 -0.474739 0.0490534
+0.618141 -0.556576 0.0611654
+0.660444 -0.47984 0.0252061
+
+0.618141 -0.556576 0.0611654
+0.653421 -0.474739 0.0490534
+0.605218 -0.544941 0.0876034
+
+0.64214 -0.466542 0.0702562
+0.605218 -0.544941 0.0876034
+0.653421 -0.474739 0.0490534
+
+0.605218 -0.544941 0.0876034
+0.64214 -0.466542 0.0702562
+0.588114 -0.52954 0.109319
+
+0.627206 -0.455692 0.0876715
+0.588114 -0.52954 0.109319
+0.64214 -0.466542 0.0702562
+
+0.588114 -0.52954 0.109319
+0.627206 -0.455692 0.0876715
+0.567748 -0.511203 0.125141
+
+0.609425 -0.442773 0.10036
+0.567748 -0.511203 0.125141
+0.627206 -0.455692 0.0876715
+
+0.567748 -0.511203 0.125141
+0.609425 -0.442773 0.10036
+0.54522 -0.490918 0.134216
+
+0.589757 -0.428483 0.107639
+0.54522 -0.490918 0.134216
+0.609425 -0.442773 0.10036
+
+0.54522 -0.490918 0.134216
+0.589757 -0.428483 0.107639
+0.521744 -0.46978 0.136056
+
+0.569261 -0.413592 0.109114
+0.521744 -0.46978 0.136056
+0.589757 -0.428483 0.107639
+
+0.521744 -0.46978 0.136056
+0.569261 -0.413592 0.109114
+0.498585 -0.448928 0.130561
+
+0.549042 -0.398902 0.104708
+0.498585 -0.448928 0.130561
+0.569261 -0.413592 0.109114
+
+0.498585 -0.448928 0.130561
+0.549042 -0.398902 0.104708
+0.476992 -0.429486 0.118028
+
+0.53019 -0.385205 0.0946559
+0.476992 -0.429486 0.118028
+0.549042 -0.398902 0.104708
+
+0.476992 -0.429486 0.118028
+0.53019 -0.385205 0.0946559
+0.45813 -0.412502 0.0991314
+
+0.513721 -0.37324 0.0795014
+0.45813 -0.412502 0.0991314
+0.53019 -0.385205 0.0946559
+
+0.45813 -0.412502 0.0991314
+0.513721 -0.37324 0.0795014
+0.443014 -0.398892 0.0748908
+
+0.500524 -0.363652 0.0600609
+0.443014 -0.398892 0.0748908
+0.513721 -0.37324 0.0795014
+
+0.443014 -0.398892 0.0748908
+0.500524 -0.363652 0.0600609
+0.43246 -0.389389 0.0466128
+
+0.49131 -0.356957 0.0373825
+0.43246 -0.389389 0.0466128
+0.500524 -0.363652 0.0600609
+
+0.43246 -0.389389 0.0466128
+0.49131 -0.356957 0.0373825
+0.427037 -0.384506 0.0158219
+
+0.486575 -0.353517 0.0126889
+0.427037 -0.384506 0.0158219
+0.49131 -0.356957 0.0373825
+
+0.427037 -0.384506 0.0158219
+0.486575 -0.353517 0.0126889
+0.427037 -0.384506 -0.0158219
+
+0.486575 -0.353517 -0.0126889
+0.427037 -0.384506 -0.0158219
+0.486575 -0.353517 0.0126889
+
+0.427037 -0.384506 -0.0158219
+0.486575 -0.353517 -0.0126889
+0.43246 -0.389389 -0.0466128
+
+0.49131 -0.356957 -0.0373825
+0.43246 -0.389389 -0.0466128
+0.486575 -0.353517 -0.0126889
+
+0.43246 -0.389389 -0.0466128
+0.49131 -0.356957 -0.0373825
+0.443014 -0.398892 -0.0748908
+
+0.500524 -0.363652 -0.0600609
+0.443014 -0.398892 -0.0748908
+0.49131 -0.356957 -0.0373825
+
+0.443014 -0.398892 -0.0748908
+0.500524 -0.363652 -0.0600609
+0.45813 -0.412502 -0.0991314
+
+0.513721 -0.37324 -0.0795014
+0.45813 -0.412502 -0.0991314
+0.500524 -0.363652 -0.0600609
+
+0.45813 -0.412502 -0.0991314
+0.513721 -0.37324 -0.0795014
+0.476992 -0.429486 -0.118028
+
+0.53019 -0.385205 -0.0946559
+0.476992 -0.429486 -0.118028
+0.513721 -0.37324 -0.0795014
+
+0.476992 -0.429486 -0.118028
+0.53019 -0.385205 -0.0946559
+0.498585 -0.448928 -0.130561
+
+0.549042 -0.398902 -0.104708
+0.498585 -0.448928 -0.130561
+0.53019 -0.385205 -0.0946559
+
+0.498585 -0.448928 -0.130561
+0.549042 -0.398902 -0.104708
+0.521744 -0.46978 -0.136056
+
+0.569261 -0.413592 -0.109114
+0.521744 -0.46978 -0.136056
+0.549042 -0.398902 -0.104708
+
+0.521744 -0.46978 -0.136056
+0.569261 -0.413592 -0.109114
+0.54522 -0.490918 -0.134216
+
+0.589757 -0.428483 -0.107639
+0.54522 -0.490918 -0.134216
+0.569261 -0.413592 -0.109114
+
+0.54522 -0.490918 -0.134216
+0.589757 -0.428483 -0.107639
+0.567748 -0.511203 -0.125141
+
+0.609425 -0.442773 -0.10036
+0.567748 -0.511203 -0.125141
+0.589757 -0.428483 -0.107639
+
+0.567748 -0.511203 -0.125141
+0.609425 -0.442773 -0.10036
+0.588114 -0.52954 -0.109319
+
+0.627206 -0.455692 -0.0876715
+0.588114 -0.52954 -0.109319
+0.609425 -0.442773 -0.10036
+
+0.588114 -0.52954 -0.109319
+0.627206 -0.455692 -0.0876715
+0.605218 -0.544941 -0.0876034
+
+0.64214 -0.466542 -0.0702562
+0.605218 -0.544941 -0.0876034
+0.627206 -0.455692 -0.0876715
+
+0.605218 -0.544941 -0.0876034
+0.64214 -0.466542 -0.0702562
+0.618141 -0.556576 -0.0611654
+
+0.653421 -0.474739 -0.0490534
+0.618141 -0.556576 -0.0611654
+0.64214 -0.466542 -0.0702562
+
+0.618141 -0.556576 -0.0611654
+0.653421 -0.474739 -0.0490534
+0.626184 -0.563818 -0.0314299
+
+0.660444 -0.47984 -0.0252061
+0.626184 -0.563818 -0.0314299
+0.653421 -0.474739 -0.0490534
+
+0.626184 -0.563818 -0.0314299
+0.660444 -0.47984 -0.0252061
+0.628914 -0.566276 0
+
+0.662827 -0.481572 0
+0.628914 -0.566276 0
+0.660444 -0.47984 -0.0252061
+
+0.662827 -0.481572 0
+0.701481 -0.405 0
+0.660444 -0.47984 0.0252061
+
+0.699146 -0.403652 0.0230616
+0.660444 -0.47984 0.0252061
+0.701481 -0.405 0
+
+0.660444 -0.47984 0.0252061
+0.699146 -0.403652 0.0230616
+0.653421 -0.474739 0.0490534
+
+0.692269 -0.399682 0.0448799
+0.653421 -0.474739 0.0490534
+0.699146 -0.403652 0.0230616
+
+0.653421 -0.474739 0.0490534
+0.692269 -0.399682 0.0448799
+0.64214 -0.466542 0.0702562
+
+0.681219 -0.393302 0.0642788
+0.64214 -0.466542 0.0702562
+0.692269 -0.399682 0.0448799
+
+0.64214 -0.466542 0.0702562
+0.681219 -0.393302 0.0642788
+0.627206 -0.455692 0.0876715
+
+0.666593 -0.384858 0.0802123
+0.627206 -0.455692 0.0876715
+0.681219 -0.393302 0.0642788
+
+0.627206 -0.455692 0.0876715
+0.666593 -0.384858 0.0802123
+0.609425 -0.442773 0.10036
+
+0.64918 -0.374804 0.0918216
+0.609425 -0.442773 0.10036
+0.666593 -0.384858 0.0802123
+
+0.609425 -0.442773 0.10036
+0.64918 -0.374804 0.0918216
+0.589757 -0.428483 0.107639
+
+0.629916 -0.363682 0.0984808
+0.589757 -0.428483 0.107639
+0.64918 -0.374804 0.0918216
+
+0.589757 -0.428483 0.107639
+0.629916 -0.363682 0.0984808
+0.569261 -0.413592 0.109114
+
+0.609843 -0.352093 0.0998308
+0.569261 -0.413592 0.109114
+0.629916 -0.363682 0.0984808
+
+0.569261 -0.413592 0.109114
+0.609843 -0.352093 0.0998308
+0.549042 -0.398902 0.104708
+
+0.59004 -0.34066 0.095799
+0.549042 -0.398902 0.104708
+0.609843 -0.352093 0.0998308
+
+0.549042 -0.398902 0.104708
+0.59004 -0.34066 0.095799
+0.53019 -0.385205 0.0946559
+
+0.571577 -0.33 0.0866025
+0.53019 -0.385205 0.0946559
+0.59004 -0.34066 0.095799
+
+0.53019 -0.385205 0.0946559
+0.571577 -0.33 0.0866025
+0.513721 -0.37324 0.0795014
+
+0.555448 -0.320688 0.0727374
+0.513721 -0.37324 0.0795014
+0.571577 -0.33 0.0866025
+
+0.513721 -0.37324 0.0795014
+0.555448 -0.320688 0.0727374
+0.500524 -0.363652 0.0600609
+
+0.542523 -0.313226 0.0549509
+0.500524 -0.363652 0.0600609
+0.555448 -0.320688 0.0727374
+
+0.500524 -0.363652 0.0600609
+0.542523 -0.313226 0.0549509
+0.49131 -0.356957 0.0373825
+
+0.533498 -0.308015 0.034202
+0.49131 -0.356957 0.0373825
+0.542523 -0.313226 0.0549509
+
+0.49131 -0.356957 0.0373825
+0.533498 -0.308015 0.034202
+0.486575 -0.353517 0.0126889
+
+0.528861 -0.305338 0.0116093
+0.486575 -0.353517 0.0126889
+0.533498 -0.308015 0.034202
+
+0.486575 -0.353517 0.0126889
+0.528861 -0.305338 0.0116093
+0.486575 -0.353517 -0.0126889
+
+0.528861 -0.305338 -0.0116093
+0.486575 -0.353517 -0.0126889
+0.528861 -0.305338 0.0116093
+
+0.486575 -0.353517 -0.0126889
+0.528861 -0.305338 -0.0116093
+0.49131 -0.356957 -0.0373825
+
+0.533498 -0.308015 -0.034202
+0.49131 -0.356957 -0.0373825
+0.528861 -0.305338 -0.0116093
+
+0.49131 -0.356957 -0.0373825
+0.533498 -0.308015 -0.034202
+0.500524 -0.363652 -0.0600609
+
+0.542523 -0.313226 -0.0549509
+0.500524 -0.363652 -0.0600609
+0.533498 -0.308015 -0.034202
+
+0.500524 -0.363652 -0.0600609
+0.542523 -0.313226 -0.0549509
+0.513721 -0.37324 -0.0795014
+
+0.555448 -0.320688 -0.0727374
+0.513721 -0.37324 -0.0795014
+0.542523 -0.313226 -0.0549509
+
+0.513721 -0.37324 -0.0795014
+0.555448 -0.320688 -0.0727374
+0.53019 -0.385205 -0.0946559
+
+0.571577 -0.33 -0.0866025
+0.53019 -0.385205 -0.0946559
+0.555448 -0.320688 -0.0727374
+
+0.53019 -0.385205 -0.0946559
+0.571577 -0.33 -0.0866025
+0.549042 -0.398902 -0.104708
+
+0.59004 -0.34066 -0.095799
+0.549042 -0.398902 -0.104708
+0.571577 -0.33 -0.0866025
+
+0.549042 -0.398902 -0.104708
+0.59004 -0.34066 -0.095799
+0.569261 -0.413592 -0.109114
+
+0.609843 -0.352093 -0.0998308
+0.569261 -0.413592 -0.109114
+0.59004 -0.34066 -0.095799
+
+0.569261 -0.413592 -0.109114
+0.609843 -0.352093 -0.0998308
+0.589757 -0.428483 -0.107639
+
+0.629916 -0.363682 -0.0984808
+0.589757 -0.428483 -0.107639
+0.609843 -0.352093 -0.0998308
+
+0.589757 -0.428483 -0.107639
+0.629916 -0.363682 -0.0984808
+0.609425 -0.442773 -0.10036
+
+0.64918 -0.374804 -0.0918216
+0.609425 -0.442773 -0.10036
+0.629916 -0.363682 -0.0984808
+
+0.609425 -0.442773 -0.10036
+0.64918 -0.374804 -0.0918216
+0.627206 -0.455692 -0.0876715
+
+0.666593 -0.384858 -0.0802123
+0.627206 -0.455692 -0.0876715
+0.64918 -0.374804 -0.0918216
+
+0.627206 -0.455692 -0.0876715
+0.666593 -0.384858 -0.0802123
+0.64214 -0.466542 -0.0702562
+
+0.681219 -0.393302 -0.0642788
+0.64214 -0.466542 -0.0702562
+0.666593 -0.384858 -0.0802123
+
+0.64214 -0.466542 -0.0702562
+0.681219 -0.393302 -0.0642788
+0.653421 -0.474739 -0.0490534
+
+0.692269 -0.399682 -0.0448799
+0.653421 -0.474739 -0.0490534
+0.681219 -0.393302 -0.0642788
+
+0.653421 -0.474739 -0.0490534
+0.692269 -0.399682 -0.0448799
+0.660444 -0.47984 -0.0252061
+
+0.699146 -0.403652 -0.0230616
+0.660444 -0.47984 -0.0252061
+0.692269 -0.399682 -0.0448799
+
+0.660444 -0.47984 -0.0252061
+0.699146 -0.403652 -0.0230616
+0.662827 -0.481572 0
+
+0.701481 -0.405 0
+0.662827 -0.481572 0
+0.699146 -0.403652 -0.0230616
+
+0.701481 -0.405 0
+0.748467 -0.333239 0
+0.699146 -0.403652 0.0230616
+
+0.745776 -0.332041 0.0252061
+0.699146 -0.403652 0.0230616
+0.748467 -0.333239 0
+
+0.699146 -0.403652 0.0230616
+0.745776 -0.332041 0.0252061
+0.692269 -0.399682 0.0448799
+
+0.737846 -0.32851 0.0490534
+0.692269 -0.399682 0.0448799
+0.745776 -0.332041 0.0252061
+
+0.692269 -0.399682 0.0448799
+0.737846 -0.32851 0.0490534
+0.681219 -0.393302 0.0642788
+
+0.725107 -0.322838 0.0702562
+0.681219 -0.393302 0.0642788
+0.737846 -0.32851 0.0490534
+
+0.681219 -0.393302 0.0642788
+0.725107 -0.322838 0.0702562
+0.666593 -0.384858 0.0802123
+
+0.708243 -0.31533 0.0876715
+0.666593 -0.384858 0.0802123
+0.725107 -0.322838 0.0702562
+
+0.666593 -0.384858 0.0802123
+0.708243 -0.31533 0.0876715
+0.64918 -0.374804 0.0918216
+
+0.688166 -0.306391 0.10036
+0.64918 -0.374804 0.0918216
+0.708243 -0.31533 0.0876715
+
+0.64918 -0.374804 0.0918216
+0.688166 -0.306391 0.10036
+0.629916 -0.363682 0.0984808
+
+0.665956 -0.296503 0.107639
+0.629916 -0.363682 0.0984808
+0.688166 -0.306391 0.10036
+
+0.629916 -0.363682 0.0984808
+0.665956 -0.296503 0.107639
+0.609843 -0.352093 0.0998308
+
+0.642812 -0.286198 0.109114
+0.609843 -0.352093 0.0998308
+0.665956 -0.296503 0.107639
+
+0.609843 -0.352093 0.0998308
+0.642812 -0.286198 0.109114
+0.59004 -0.34066 0.095799
+
+0.61998 -0.276033 0.104708
+0.59004 -0.34066 0.095799
+0.642812 -0.286198 0.109114
+
+0.59004 -0.34066 0.095799
+0.61998 -0.276033 0.104708
+0.571577 -0.33 0.0866025
+
+0.598692 -0.266555 0.0946559
+0.571577 -0.33 0.0866025
+0.61998 -0.276033 0.104708
+
+0.571577 -0.33 0.0866025
+0.598692 -0.266555 0.0946559
+0.555448 -0.320688 0.0727374
+
+0.580096 -0.258275 0.0795014
+0.555448 -0.320688 0.0727374
+0.598692 -0.266555 0.0946559
+
+0.555448 -0.320688 0.0727374
+0.580096 -0.258275 0.0795014
+0.542523 -0.313226 0.0549509
+
+0.565194 -0.251641 0.0600609
+0.542523 -0.313226 0.0549509
+0.580096 -0.258275 0.0795014
+
+0.542523 -0.313226 0.0549509
+0.565194 -0.251641 0.0600609
+0.533498 -0.308015 0.034202
+
+0.554789 -0.247008 0.0373825
+0.533498 -0.308015 0.034202
+0.565194 -0.251641 0.0600609
+
+0.533498 -0.308015 0.034202
+0.554789 -0.247008 0.0373825
+0.528861 -0.305338 0.0116093
+
+0.549443 -0.244628 0.0126889
+0.528861 -0.305338 0.0116093
+0.554789 -0.247008 0.0373825
+
+0.528861 -0.305338 0.0116093
+0.549443 -0.244628 0.0126889
+0.528861 -0.305338 -0.0116093
+
+0.549443 -0.244628 -0.0126889
+0.528861 -0.305338 -0.0116093
+0.549443 -0.244628 0.0126889
+
+0.528861 -0.305338 -0.0116093
+0.549443 -0.244628 -0.0126889
+0.533498 -0.308015 -0.034202
+
+0.554789 -0.247008 -0.0373825
+0.533498 -0.308015 -0.034202
+0.549443 -0.244628 -0.0126889
+
+0.533498 -0.308015 -0.034202
+0.554789 -0.247008 -0.0373825
+0.542523 -0.313226 -0.0549509
+
+0.565194 -0.251641 -0.0600609
+0.542523 -0.313226 -0.0549509
+0.554789 -0.247008 -0.0373825
+
+0.542523 -0.313226 -0.0549509
+0.565194 -0.251641 -0.0600609
+0.555448 -0.320688 -0.0727374
+
+0.580096 -0.258275 -0.0795014
+0.555448 -0.320688 -0.0727374
+0.565194 -0.251641 -0.0600609
+
+0.555448 -0.320688 -0.0727374
+0.580096 -0.258275 -0.0795014
+0.571577 -0.33 -0.0866025
+
+0.598692 -0.266555 -0.0946559
+0.571577 -0.33 -0.0866025
+0.580096 -0.258275 -0.0795014
+
+0.571577 -0.33 -0.0866025
+0.598692 -0.266555 -0.0946559
+0.59004 -0.34066 -0.095799
+
+0.61998 -0.276033 -0.104708
+0.59004 -0.34066 -0.095799
+0.598692 -0.266555 -0.0946559
+
+0.59004 -0.34066 -0.095799
+0.61998 -0.276033 -0.104708
+0.609843 -0.352093 -0.0998308
+
+0.642812 -0.286198 -0.109114
+0.609843 -0.352093 -0.0998308
+0.61998 -0.276033 -0.104708
+
+0.609843 -0.352093 -0.0998308
+0.642812 -0.286198 -0.109114
+0.629916 -0.363682 -0.0984808
+
+0.665956 -0.296503 -0.107639
+0.629916 -0.363682 -0.0984808
+0.642812 -0.286198 -0.109114
+
+0.629916 -0.363682 -0.0984808
+0.665956 -0.296503 -0.107639
+0.64918 -0.374804 -0.0918216
+
+0.688166 -0.306391 -0.10036
+0.64918 -0.374804 -0.0918216
+0.665956 -0.296503 -0.107639
+
+0.64918 -0.374804 -0.0918216
+0.688166 -0.306391 -0.10036
+0.666593 -0.384858 -0.0802123
+
+0.708243 -0.31533 -0.0876715
+0.666593 -0.384858 -0.0802123
+0.688166 -0.306391 -0.10036
+
+0.666593 -0.384858 -0.0802123
+0.708243 -0.31533 -0.0876715
+0.681219 -0.393302 -0.0642788
+
+0.725107 -0.322838 -0.0702562
+0.681219 -0.393302 -0.0642788
+0.708243 -0.31533 -0.0876715
+
+0.681219 -0.393302 -0.0642788
+0.725107 -0.322838 -0.0702562
+0.692269 -0.399682 -0.0448799
+
+0.737846 -0.32851 -0.0490534
+0.692269 -0.399682 -0.0448799
+0.725107 -0.322838 -0.0702562
+
+0.692269 -0.399682 -0.0448799
+0.737846 -0.32851 -0.0490534
+0.699146 -0.403652 -0.0230616
+
+0.745776 -0.332041 -0.0252061
+0.699146 -0.403652 -0.0230616
+0.737846 -0.32851 -0.0490534
+
+0.699146 -0.403652 -0.0230616
+0.745776 -0.332041 -0.0252061
+0.701481 -0.405 0
+
+0.748467 -0.333239 0
+0.701481 -0.405 0
+0.745776 -0.332041 -0.0252061
+
+0.748467 -0.333239 0
+0.804867 -0.261517 0
+0.745776 -0.332041 0.0252061
+
+0.801373 -0.260382 0.0314299
+0.745776 -0.332041 0.0252061
+0.804867 -0.261517 0
+
+0.745776 -0.332041 0.0252061
+0.801373 -0.260382 0.0314299
+0.737846 -0.32851 0.0490534
+
+0.79108 -0.257037 0.0611654
+0.737846 -0.32851 0.0490534
+0.801373 -0.260382 0.0314299
+
+0.737846 -0.32851 0.0490534
+0.79108 -0.257037 0.0611654
+0.725107 -0.322838 0.0702562
+
+0.774542 -0.251664 0.0876034
+0.725107 -0.322838 0.0702562
+0.79108 -0.257037 0.0611654
+
+0.725107 -0.322838 0.0702562
+0.774542 -0.251664 0.0876034
+0.708243 -0.31533 0.0876715
+
+0.752652 -0.244551 0.109319
+0.708243 -0.31533 0.0876715
+0.774542 -0.251664 0.0876034
+
+0.708243 -0.31533 0.0876715
+0.752652 -0.244551 0.109319
+0.688166 -0.306391 0.10036
+
+0.726589 -0.236083 0.125141
+0.688166 -0.306391 0.10036
+0.752652 -0.244551 0.109319
+
+0.688166 -0.306391 0.10036
+0.726589 -0.236083 0.125141
+0.665956 -0.296503 0.107639
+
+0.697758 -0.226715 0.134216
+0.665956 -0.296503 0.107639
+0.726589 -0.236083 0.125141
+
+0.665956 -0.296503 0.107639
+0.697758 -0.226715 0.134216
+0.642812 -0.286198 0.109114
+
+0.667714 -0.216953 0.136056
+0.642812 -0.286198 0.109114
+0.697758 -0.226715 0.134216
+
+0.642812 -0.286198 0.109114
+0.667714 -0.216953 0.136056
+0.61998 -0.276033 0.104708
+
+0.638076 -0.207323 0.130561
+0.61998 -0.276033 0.104708
+0.667714 -0.216953 0.136056
+
+0.61998 -0.276033 0.104708
+0.638076 -0.207323 0.130561
+0.598692 -0.266555 0.0946559
+
+0.610442 -0.198345 0.118028
+0.598692 -0.266555 0.0946559
+0.638076 -0.207323 0.130561
+
+0.598692 -0.266555 0.0946559
+0.610442 -0.198345 0.118028
+0.580096 -0.258275 0.0795014
+
+0.586302 -0.190501 0.0991314
+0.580096 -0.258275 0.0795014
+0.610442 -0.198345 0.118028
+
+0.580096 -0.258275 0.0795014
+0.586302 -0.190501 0.0991314
+0.565194 -0.251641 0.0600609
+
+0.566957 -0.184216 0.0748908
+0.565194 -0.251641 0.0600609
+0.586302 -0.190501 0.0991314
+
+0.565194 -0.251641 0.0600609
+0.566957 -0.184216 0.0748908
+0.554789 -0.247008 0.0373825
+
+0.553451 -0.179827 0.0466128
+0.554789 -0.247008 0.0373825
+0.566957 -0.184216 0.0748908
+
+0.554789 -0.247008 0.0373825
+0.553451 -0.179827 0.0466128
+0.549443 -0.244628 0.0126889
+
+0.54651 -0.177572 0.0158219
+0.549443 -0.244628 0.0126889
+0.553451 -0.179827 0.0466128
+
+0.549443 -0.244628 0.0126889
+0.54651 -0.177572 0.0158219
+0.549443 -0.244628 -0.0126889
+
+0.54651 -0.177572 -0.0158219
+0.549443 -0.244628 -0.0126889
+0.54651 -0.177572 0.0158219
+
+0.549443 -0.244628 -0.0126889
+0.54651 -0.177572 -0.0158219
+0.554789 -0.247008 -0.0373825
+
+0.553451 -0.179827 -0.0466128
+0.554789 -0.247008 -0.0373825
+0.54651 -0.177572 -0.0158219
+
+0.554789 -0.247008 -0.0373825
+0.553451 -0.179827 -0.0466128
+0.565194 -0.251641 -0.0600609
+
+0.566957 -0.184216 -0.0748908
+0.565194 -0.251641 -0.0600609
+0.553451 -0.179827 -0.0466128
+
+0.565194 -0.251641 -0.0600609
+0.566957 -0.184216 -0.0748908
+0.580096 -0.258275 -0.0795014
+
+0.586302 -0.190501 -0.0991314
+0.580096 -0.258275 -0.0795014
+0.566957 -0.184216 -0.0748908
+
+0.580096 -0.258275 -0.0795014
+0.586302 -0.190501 -0.0991314
+0.598692 -0.266555 -0.0946559
+
+0.610442 -0.198345 -0.118028
+0.598692 -0.266555 -0.0946559
+0.586302 -0.190501 -0.0991314
+
+0.598692 -0.266555 -0.0946559
+0.610442 -0.198345 -0.118028
+0.61998 -0.276033 -0.104708
+
+0.638076 -0.207323 -0.130561
+0.61998 -0.276033 -0.104708
+0.610442 -0.198345 -0.118028
+
+0.61998 -0.276033 -0.104708
+0.638076 -0.207323 -0.130561
+0.642812 -0.286198 -0.109114
+
+0.667714 -0.216953 -0.136056
+0.642812 -0.286198 -0.109114
+0.638076 -0.207323 -0.130561
+
+0.642812 -0.286198 -0.109114
+0.667714 -0.216953 -0.136056
+0.665956 -0.296503 -0.107639
+
+0.697758 -0.226715 -0.134216
+0.665956 -0.296503 -0.107639
+0.667714 -0.216953 -0.136056
+
+0.665956 -0.296503 -0.107639
+0.697758 -0.226715 -0.134216
+0.688166 -0.306391 -0.10036
+
+0.726589 -0.236083 -0.125141
+0.688166 -0.306391 -0.10036
+0.697758 -0.226715 -0.134216
+
+0.688166 -0.306391 -0.10036
+0.726589 -0.236083 -0.125141
+0.708243 -0.31533 -0.0876715
+
+0.752652 -0.244551 -0.109319
+0.708243 -0.31533 -0.0876715
+0.726589 -0.236083 -0.125141
+
+0.708243 -0.31533 -0.0876715
+0.752652 -0.244551 -0.109319
+0.725107 -0.322838 -0.0702562
+
+0.774542 -0.251664 -0.0876034
+0.725107 -0.322838 -0.0702562
+0.752652 -0.244551 -0.109319
+
+0.725107 -0.322838 -0.0702562
+0.774542 -0.251664 -0.0876034
+0.737846 -0.32851 -0.0490534
+
+0.79108 -0.257037 -0.0611654
+0.737846 -0.32851 -0.0490534
+0.774542 -0.251664 -0.0876034
+
+0.737846 -0.32851 -0.0490534
+0.79108 -0.257037 -0.0611654
+0.745776 -0.332041 -0.0252061
+
+0.801373 -0.260382 -0.0314299
+0.745776 -0.332041 -0.0252061
+0.79108 -0.257037 -0.0611654
+
+0.745776 -0.332041 -0.0252061
+0.801373 -0.260382 -0.0314299
+0.748467 -0.333239 0
+
+0.804867 -0.261517 0
+0.748467 -0.333239 0
+0.801373 -0.260382 -0.0314299
+
+0.804867 -0.261517 0
+0.868909 -0.184692 0
+0.801373 -0.260382 0.0314299
+
+0.864207 -0.183693 0.0411236
+0.801373 -0.260382 0.0314299
+0.868909 -0.184692 0
+
+0.801373 -0.260382 0.0314299
+0.864207 -0.183693 0.0411236
+0.79108 -0.257037 0.0611654
+
+0.850356 -0.180749 0.0800302
+0.79108 -0.257037 0.0611654
+0.864207 -0.183693 0.0411236
+
+0.79108 -0.257037 0.0611654
+0.850356 -0.180749 0.0800302
+0.774542 -0.251664 0.0876034
+
+0.828101 -0.176018 0.114622
+0.774542 -0.251664 0.0876034
+0.850356 -0.180749 0.0800302
+
+0.774542 -0.251664 0.0876034
+0.828101 -0.176018 0.114622
+0.752652 -0.244551 0.109319
+
+0.798644 -0.169757 0.143035
+0.752652 -0.244551 0.109319
+0.828101 -0.176018 0.114622
+
+0.752652 -0.244551 0.109319
+0.798644 -0.169757 0.143035
+0.726589 -0.236083 0.125141
+
+0.763571 -0.162302 0.163737
+0.726589 -0.236083 0.125141
+0.798644 -0.169757 0.143035
+
+0.726589 -0.236083 0.125141
+0.763571 -0.162302 0.163737
+0.697758 -0.226715 0.134216
+
+0.724773 -0.154055 0.175612
+0.697758 -0.226715 0.134216
+0.763571 -0.162302 0.163737
+
+0.697758 -0.226715 0.134216
+0.724773 -0.154055 0.175612
+0.667714 -0.216953 0.136056
+
+0.684343 -0.145462 0.178019
+0.667714 -0.216953 0.136056
+0.724773 -0.154055 0.175612
+
+0.667714 -0.216953 0.136056
+0.684343 -0.145462 0.178019
+0.638076 -0.207323 0.130561
+
+0.644459 -0.136984 0.170829
+0.638076 -0.207323 0.130561
+0.684343 -0.145462 0.178019
+
+0.638076 -0.207323 0.130561
+0.644459 -0.136984 0.170829
+0.610442 -0.198345 0.118028
+
+0.607273 -0.12908 0.15443
+0.610442 -0.198345 0.118028
+0.644459 -0.136984 0.170829
+
+0.610442 -0.198345 0.118028
+0.607273 -0.12908 0.15443
+0.586302 -0.190501 0.0991314
+
+0.574788 -0.122175 0.129706
+0.586302 -0.190501 0.0991314
+0.607273 -0.12908 0.15443
+
+0.586302 -0.190501 0.0991314
+0.574788 -0.122175 0.129706
+0.566957 -0.184216 0.0748908
+
+0.548756 -0.116642 0.0979889
+0.566957 -0.184216 0.0748908
+0.574788 -0.122175 0.129706
+
+0.566957 -0.184216 0.0748908
+0.548756 -0.116642 0.0979889
+0.553451 -0.179827 0.0466128
+
+0.53058 -0.112778 0.0609893
+0.553451 -0.179827 0.0466128
+0.548756 -0.116642 0.0979889
+
+0.553451 -0.179827 0.0466128
+0.53058 -0.112778 0.0609893
+0.54651 -0.177572 0.0158219
+
+0.52124 -0.110793 0.0207018
+0.54651 -0.177572 0.0158219
+0.53058 -0.112778 0.0609893
+
+0.54651 -0.177572 0.0158219
+0.52124 -0.110793 0.0207018
+0.54651 -0.177572 -0.0158219
+
+0.52124 -0.110793 -0.0207018
+0.54651 -0.177572 -0.0158219
+0.52124 -0.110793 0.0207018
+
+0.54651 -0.177572 -0.0158219
+0.52124 -0.110793 -0.0207018
+0.553451 -0.179827 -0.0466128
+
+0.53058 -0.112778 -0.0609893
+0.553451 -0.179827 -0.0466128
+0.52124 -0.110793 -0.0207018
+
+0.553451 -0.179827 -0.0466128
+0.53058 -0.112778 -0.0609893
+0.566957 -0.184216 -0.0748908
+
+0.548756 -0.116642 -0.0979889
+0.566957 -0.184216 -0.0748908
+0.53058 -0.112778 -0.0609893
+
+0.566957 -0.184216 -0.0748908
+0.548756 -0.116642 -0.0979889
+0.586302 -0.190501 -0.0991314
+
+0.574788 -0.122175 -0.129706
+0.586302 -0.190501 -0.0991314
+0.548756 -0.116642 -0.0979889
+
+0.586302 -0.190501 -0.0991314
+0.574788 -0.122175 -0.129706
+0.610442 -0.198345 -0.118028
+
+0.607273 -0.12908 -0.15443
+0.610442 -0.198345 -0.118028
+0.574788 -0.122175 -0.129706
+
+0.610442 -0.198345 -0.118028
+0.607273 -0.12908 -0.15443
+0.638076 -0.207323 -0.130561
+
+0.644459 -0.136984 -0.170829
+0.638076 -0.207323 -0.130561
+0.607273 -0.12908 -0.15443
+
+0.638076 -0.207323 -0.130561
+0.644459 -0.136984 -0.170829
+0.667714 -0.216953 -0.136056
+
+0.684343 -0.145462 -0.178019
+0.667714 -0.216953 -0.136056
+0.644459 -0.136984 -0.170829
+
+0.667714 -0.216953 -0.136056
+0.684343 -0.145462 -0.178019
+0.697758 -0.226715 -0.134216
+
+0.724773 -0.154055 -0.175612
+0.697758 -0.226715 -0.134216
+0.684343 -0.145462 -0.178019
+
+0.697758 -0.226715 -0.134216
+0.724773 -0.154055 -0.175612
+0.726589 -0.236083 -0.125141
+
+0.763571 -0.162302 -0.163737
+0.726589 -0.236083 -0.125141
+0.724773 -0.154055 -0.175612
+
+0.726589 -0.236083 -0.125141
+0.763571 -0.162302 -0.163737
+0.752652 -0.244551 -0.109319
+
+0.798644 -0.169757 -0.143035
+0.752652 -0.244551 -0.109319
+0.763571 -0.162302 -0.163737
+
+0.752652 -0.244551 -0.109319
+0.798644 -0.169757 -0.143035
+0.774542 -0.251664 -0.0876034
+
+0.828101 -0.176018 -0.114622
+0.774542 -0.251664 -0.0876034
+0.798644 -0.169757 -0.143035
+
+0.774542 -0.251664 -0.0876034
+0.828101 -0.176018 -0.114622
+0.79108 -0.257037 -0.0611654
+
+0.850356 -0.180749 -0.0800302
+0.79108 -0.257037 -0.0611654
+0.828101 -0.176018 -0.114622
+
+0.79108 -0.257037 -0.0611654
+0.850356 -0.180749 -0.0800302
+0.801373 -0.260382 -0.0314299
+
+0.864207 -0.183693 -0.0411236
+0.801373 -0.260382 -0.0314299
+0.850356 -0.180749 -0.0800302
+
+0.801373 -0.260382 -0.0314299
+0.864207 -0.183693 -0.0411236
+0.804867 -0.261517 0
+
+0.868909 -0.184692 0
+0.804867 -0.261517 0
+0.864207 -0.183693 -0.0411236
+
+0.868909 -0.184692 0
+0.93613 -0.0983913 0
+0.864207 -0.183693 0.0411236
+
+0.92993 -0.0977396 0.0533384
+0.864207 -0.183693 0.0411236
+0.93613 -0.0983913 0
+
+0.864207 -0.183693 0.0411236
+0.92993 -0.0977396 0.0533384
+0.850356 -0.180749 0.0800302
+
+0.911664 -0.0958197 0.103801
+0.850356 -0.180749 0.0800302
+0.92993 -0.0977396 0.0533384
+
+0.850356 -0.180749 0.0800302
+0.911664 -0.0958197 0.103801
+0.828101 -0.176018 0.114622
+
+0.882316 -0.0927351 0.148668
+0.828101 -0.176018 0.114622
+0.911664 -0.0958197 0.103801
+
+0.828101 -0.176018 0.114622
+0.882316 -0.0927351 0.148668
+0.798644 -0.169757 0.143035
+
+0.843469 -0.0886521 0.18552
+0.798644 -0.169757 0.143035
+0.882316 -0.0927351 0.148668
+
+0.798644 -0.169757 0.143035
+0.843469 -0.0886521 0.18552
+0.763571 -0.162302 0.163737
+
+0.797217 -0.0837909 0.212371
+0.763571 -0.162302 0.163737
+0.843469 -0.0886521 0.18552
+
+0.763571 -0.162302 0.163737
+0.797217 -0.0837909 0.212371
+0.724773 -0.154055 0.175612
+
+0.746053 -0.0784133 0.227773
+0.724773 -0.154055 0.175612
+0.797217 -0.0837909 0.212371
+
+0.724773 -0.154055 0.175612
+0.746053 -0.0784133 0.227773
+0.684343 -0.145462 0.178019
+
+0.692736 -0.0728095 0.230895
+0.684343 -0.145462 0.178019
+0.746053 -0.0784133 0.227773
+
+0.684343 -0.145462 0.178019
+0.692736 -0.0728095 0.230895
+0.644459 -0.136984 0.170829
+
+0.64014 -0.0672814 0.22157
+0.644459 -0.136984 0.170829
+0.692736 -0.0728095 0.230895
+
+0.644459 -0.136984 0.170829
+0.64014 -0.0672814 0.22157
+0.607273 -0.12908 0.15443
+
+0.591101 -0.0621272 0.2003
+0.607273 -0.12908 0.15443
+0.64014 -0.0672814 0.22157
+
+0.607273 -0.12908 0.15443
+0.591101 -0.0621272 0.2003
+0.574788 -0.122175 0.129706
+
+0.548261 -0.0576246 0.168232
+0.574788 -0.122175 0.129706
+0.591101 -0.0621272 0.2003
+
+0.574788 -0.122175 0.129706
+0.548261 -0.0576246 0.168232
+0.548756 -0.116642 0.0979889
+
+0.513932 -0.0540164 0.127094
+0.548756 -0.116642 0.0979889
+0.548261 -0.0576246 0.168232
+
+0.548756 -0.116642 0.0979889
+0.513932 -0.0540164 0.127094
+0.53058 -0.112778 0.0609893
+
+0.489963 -0.0514972 0.0791047
+0.53058 -0.112778 0.0609893
+0.513932 -0.0540164 0.127094
+
+0.53058 -0.112778 0.0609893
+0.489963 -0.0514972 0.0791047
+0.52124 -0.110793 0.0207018
+
+0.477646 -0.0502026 0.0268508
+0.52124 -0.110793 0.0207018
+0.489963 -0.0514972 0.0791047
+
+0.52124 -0.110793 0.0207018
+0.477646 -0.0502026 0.0268508
+0.52124 -0.110793 -0.0207018
+
+0.477646 -0.0502026 -0.0268508
+0.52124 -0.110793 -0.0207018
+0.477646 -0.0502026 0.0268508
+
+0.52124 -0.110793 -0.0207018
+0.477646 -0.0502026 -0.0268508
+0.53058 -0.112778 -0.0609893
+
+0.489963 -0.0514972 -0.0791047
+0.53058 -0.112778 -0.0609893
+0.477646 -0.0502026 -0.0268508
+
+0.53058 -0.112778 -0.0609893
+0.489963 -0.0514972 -0.0791047
+0.548756 -0.116642 -0.0979889
+
+0.513932 -0.0540164 -0.127094
+0.548756 -0.116642 -0.0979889
+0.489963 -0.0514972 -0.0791047
+
+0.548756 -0.116642 -0.0979889
+0.513932 -0.0540164 -0.127094
+0.574788 -0.122175 -0.129706
+
+0.548261 -0.0576246 -0.168232
+0.574788 -0.122175 -0.129706
+0.513932 -0.0540164 -0.127094
+
+0.574788 -0.122175 -0.129706
+0.548261 -0.0576246 -0.168232
+0.607273 -0.12908 -0.15443
+
+0.591101 -0.0621272 -0.2003
+0.607273 -0.12908 -0.15443
+0.548261 -0.0576246 -0.168232
+
+0.607273 -0.12908 -0.15443
+0.591101 -0.0621272 -0.2003
+0.644459 -0.136984 -0.170829
+
+0.64014 -0.0672814 -0.22157
+0.644459 -0.136984 -0.170829
+0.591101 -0.0621272 -0.2003
+
+0.644459 -0.136984 -0.170829
+0.64014 -0.0672814 -0.22157
+0.684343 -0.145462 -0.178019
+
+0.692736 -0.0728095 -0.230895
+0.684343 -0.145462 -0.178019
+0.64014 -0.0672814 -0.22157
+
+0.684343 -0.145462 -0.178019
+0.692736 -0.0728095 -0.230895
+0.724773 -0.154055 -0.175612
+
+0.746053 -0.0784133 -0.227773
+0.724773 -0.154055 -0.175612
+0.692736 -0.0728095 -0.230895
+
+0.724773 -0.154055 -0.175612
+0.746053 -0.0784133 -0.227773
+0.763571 -0.162302 -0.163737
+
+0.797217 -0.0837909 -0.212371
+0.763571 -0.162302 -0.163737
+0.746053 -0.0784133 -0.227773
+
+0.763571 -0.162302 -0.163737
+0.797217 -0.0837909 -0.212371
+0.798644 -0.169757 -0.143035
+
+0.843469 -0.0886521 -0.18552
+0.798644 -0.169757 -0.143035
+0.797217 -0.0837909 -0.212371
+
+0.798644 -0.169757 -0.143035
+0.843469 -0.0886521 -0.18552
+0.828101 -0.176018 -0.114622
+
+0.882316 -0.0927351 -0.148668
+0.828101 -0.176018 -0.114622
+0.843469 -0.0886521 -0.18552
+
+0.828101 -0.176018 -0.114622
+0.882316 -0.0927351 -0.148668
+0.850356 -0.180749 -0.0800302
+
+0.911664 -0.0958197 -0.103801
+0.850356 -0.180749 -0.0800302
+0.882316 -0.0927351 -0.148668
+
+0.850356 -0.180749 -0.0800302
+0.911664 -0.0958197 -0.103801
+0.864207 -0.183693 -0.0411236
+
+0.92993 -0.0977396 -0.0533384
+0.864207 -0.183693 -0.0411236
+0.911664 -0.0958197 -0.103801
+
+0.864207 -0.183693 -0.0411236
+0.92993 -0.0977396 -0.0533384
+0.868909 -0.184692 0
+
+0.93613 -0.0983913 0
+0.868909 -0.184692 0
+0.92993 -0.0977396 -0.0533384
+
+0.93613 -0.0983913 0
+1 -8.88178e-16 0
+0.92993 -0.0977396 0.0533384
+
+0.992183 -8.81236e-16 0.0668786
+0.92993 -0.0977396 0.0533384
+1 -8.88178e-16 0
+
+0.92993 -0.0977396 0.0533384
+0.992183 -8.81236e-16 0.0668786
+0.911664 -0.0958197 0.103801
+
+0.969153 -8.60781e-16 0.130152
+0.911664 -0.0958197 0.103801
+0.992183 -8.81236e-16 0.0668786
+
+0.911664 -0.0958197 0.103801
+0.969153 -8.60781e-16 0.130152
+0.882316 -0.0927351 0.148668
+
+0.932153 -8.27918e-16 0.186408
+0.882316 -0.0927351 0.148668
+0.969153 -8.60781e-16 0.130152
+
+0.882316 -0.0927351 0.148668
+0.932153 -8.27918e-16 0.186408
+0.843469 -0.0886521 0.18552
+
+0.883176 -7.84418e-16 0.232616
+0.843469 -0.0886521 0.18552
+0.932153 -8.27918e-16 0.186408
+
+0.843469 -0.0886521 0.18552
+0.883176 -7.84418e-16 0.232616
+0.797217 -0.0837909 0.212371
+
+0.824863 -7.32626e-16 0.266283
+0.797217 -0.0837909 0.212371
+0.883176 -7.84418e-16 0.232616
+
+0.797217 -0.0837909 0.212371
+0.824863 -7.32626e-16 0.266283
+0.746053 -0.0784133 0.227773
+
+0.760358 -6.75334e-16 0.285594
+0.746053 -0.0784133 0.227773
+0.824863 -7.32626e-16 0.266283
+
+0.746053 -0.0784133 0.227773
+0.760358 -6.75334e-16 0.285594
+0.692736 -0.0728095 0.230895
+
+0.693138 -6.1563e-16 0.289509
+0.692736 -0.0728095 0.230895
+0.760358 -6.75334e-16 0.285594
+
+0.692736 -0.0728095 0.230895
+0.693138 -6.1563e-16 0.289509
+0.64014 -0.0672814 0.22157
+
+0.626827 -5.56734e-16 0.277817
+0.64014 -0.0672814 0.22157
+0.693138 -6.1563e-16 0.289509
+
+0.64014 -0.0672814 0.22157
+0.626827 -5.56734e-16 0.277817
+0.591101 -0.0621272 0.2003
+
+0.565 -5.01821e-16 0.251147
+0.591101 -0.0621272 0.2003
+0.626827 -5.56734e-16 0.277817
+
+0.591101 -0.0621272 0.2003
+0.565 -5.01821e-16 0.251147
+0.548261 -0.0576246 0.168232
+
+0.51099 -4.5385e-16 0.210938
+0.548261 -0.0576246 0.168232
+0.565 -5.01821e-16 0.251147
+
+0.548261 -0.0576246 0.168232
+0.51099 -4.5385e-16 0.210938
+0.513932 -0.0540164 0.127094
+
+0.467709 -4.15409e-16 0.159358
+0.513932 -0.0540164 0.127094
+0.51099 -4.5385e-16 0.210938
+
+0.513932 -0.0540164 0.127094
+0.467709 -4.15409e-16 0.159358
+0.489963 -0.0514972 0.0791047
+
+0.437489 -3.88568e-16 0.0991858
+0.489963 -0.0514972 0.0791047
+0.467709 -4.15409e-16 0.159358
+
+0.489963 -0.0514972 0.0791047
+0.437489 -3.88568e-16 0.0991858
+0.477646 -0.0502026 0.0268508
+
+0.421961 -3.74777e-16 0.0336669
+0.477646 -0.0502026 0.0268508
+0.437489 -3.88568e-16 0.0991858
+
+0.477646 -0.0502026 0.0268508
+0.421961 -3.74777e-16 0.0336669
+0.477646 -0.0502026 -0.0268508
+
+0.421961 -3.74777e-16 -0.0336669
+0.477646 -0.0502026 -0.0268508
+0.421961 -3.74777e-16 0.0336669
+
+0.477646 -0.0502026 -0.0268508
+0.421961 -3.74777e-16 -0.0336669
+0.489963 -0.0514972 -0.0791047
+
+0.437489 -3.88568e-16 -0.0991858
+0.489963 -0.0514972 -0.0791047
+0.421961 -3.74777e-16 -0.0336669
+
+0.489963 -0.0514972 -0.0791047
+0.437489 -3.88568e-16 -0.0991858
+0.513932 -0.0540164 -0.127094
+
+0.467709 -4.15409e-16 -0.159358
+0.513932 -0.0540164 -0.127094
+0.437489 -3.88568e-16 -0.0991858
+
+0.513932 -0.0540164 -0.127094
+0.467709 -4.15409e-16 -0.159358
+0.548261 -0.0576246 -0.168232
+
+0.51099 -4.5385e-16 -0.210938
+0.548261 -0.0576246 -0.168232
+0.467709 -4.15409e-16 -0.159358
+
+0.548261 -0.0576246 -0.168232
+0.51099 -4.5385e-16 -0.210938
+0.591101 -0.0621272 -0.2003
+
+0.565 -5.01821e-16 -0.251147
+0.591101 -0.0621272 -0.2003
+0.51099 -4.5385e-16 -0.210938
+
+0.591101 -0.0621272 -0.2003
+0.565 -5.01821e-16 -0.251147
+0.64014 -0.0672814 -0.22157
+
+0.626827 -5.56734e-16 -0.277817
+0.64014 -0.0672814 -0.22157
+0.565 -5.01821e-16 -0.251147
+
+0.64014 -0.0672814 -0.22157
+0.626827 -5.56734e-16 -0.277817
+0.692736 -0.0728095 -0.230895
+
+0.693138 -6.1563e-16 -0.289509
+0.692736 -0.0728095 -0.230895
+0.626827 -5.56734e-16 -0.277817
+
+0.692736 -0.0728095 -0.230895
+0.693138 -6.1563e-16 -0.289509
+0.746053 -0.0784133 -0.227773
+
+0.760358 -6.75334e-16 -0.285594
+0.746053 -0.0784133 -0.227773
+0.693138 -6.1563e-16 -0.289509
+
+0.746053 -0.0784133 -0.227773
+0.760358 -6.75334e-16 -0.285594
+0.797217 -0.0837909 -0.212371
+
+0.824863 -7.32626e-16 -0.266283
+0.797217 -0.0837909 -0.212371
+0.760358 -6.75334e-16 -0.285594
+
+0.797217 -0.0837909 -0.212371
+0.824863 -7.32626e-16 -0.266283
+0.843469 -0.0886521 -0.18552
+
+0.883176 -7.84418e-16 -0.232616
+0.843469 -0.0886521 -0.18552
+0.824863 -7.32626e-16 -0.266283
+
+0.843469 -0.0886521 -0.18552
+0.883176 -7.84418e-16 -0.232616
+0.882316 -0.0927351 -0.148668
+
+0.932153 -8.27918e-16 -0.186408
+0.882316 -0.0927351 -0.148668
+0.883176 -7.84418e-16 -0.232616
+
+0.882316 -0.0927351 -0.148668
+0.932153 -8.27918e-16 -0.186408
+0.911664 -0.0958197 -0.103801
+
+0.969153 -8.60781e-16 -0.130152
+0.911664 -0.0958197 -0.103801
+0.932153 -8.27918e-16 -0.186408
+
+0.911664 -0.0958197 -0.103801
+0.969153 -8.60781e-16 -0.130152
+0.92993 -0.0977396 -0.0533384
+
+0.992183 -8.81236e-16 -0.0668786
+0.92993 -0.0977396 -0.0533384
+0.969153 -8.60781e-16 -0.130152
+
+0.92993 -0.0977396 -0.0533384
+0.992183 -8.81236e-16 -0.0668786
+0.93613 -0.0983913 0
+
+1 -8.88178e-16 0
+0.93613 -0.0983913 0
+0.992183 -8.81236e-16 -0.0668786
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/Makefile b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/Makefile
new file mode 100644
index 00000000..fff3b2a8
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/Makefile
@@ -0,0 +1,28 @@
+CC = g++
+
+CFLAGS = -O2 -I. -I../../include
+LDFLAGS = -L. -L../../lib
+LDLIBS = -lPQP -lm
+
+.SUFFIXES: .cpp
+
+SRCS = main.cpp
+
+OBJECTS = main.o
+
+TARGET = sample
+
+CLEAN = $(OBJECTS) $(TARGET)
+
+.cpp.o:
+ $(CC) ${CFLAGS} -c $<
+
+$(TARGET): $(OBJECTS)
+ $(CC) $(CFLAGS) -o $(TARGET) $(OBJECTS) -L. $(LDFLAGS) $(LDLIBS)
+
+run: $(TARGET)
+ $(TARGET)
+
+clean:
+ /bin/rm -f $(CLEAN)
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/main.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/main.cpp
new file mode 100644
index 00000000..f81dfdba
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/main.cpp
@@ -0,0 +1,301 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <math.h>
+#include "PQP.h"
+
+#define PI 3.14159265359
+#define LISTS 0
+
+main()
+{
+ // initialize PQP model pointers
+
+ PQP_Model *b1 = new PQP_Model;
+ PQP_Model *b2 = new PQP_Model;
+
+ // Add trianges to form tori
+
+ fprintf(stderr, "loading tris into PQP_Model objects..."); fflush(stderr);
+
+ PQP_REAL a = (PQP_REAL)1.0; // major radius of the tori
+ PQP_REAL b = (PQP_REAL)0.2; // minor radius of the tori
+
+ int n1 = 50; // tori will have n1*n2*2 triangles each
+ int n2 = 50;
+
+ int uc, vc;
+ int count = 0;
+
+ b1->BeginModel();
+ b2->BeginModel();
+ for(uc=0; uc<n1; uc++)
+ {
+ for(vc=0; vc<n2; vc++)
+ {
+ PQP_REAL u1 = (PQP_REAL)(2.0*PI*uc) / n1;
+ PQP_REAL u2 = (PQP_REAL)(2.0*PI*(uc+1)) / n1;
+ PQP_REAL v1 = (PQP_REAL)(2.0*PI*vc) / n2;
+ PQP_REAL v2 = (PQP_REAL)(2.0*PI*(vc+1)) / n2;
+
+ PQP_REAL p1[3], p2[3], p3[3], p4[3];
+
+ p1[0] = (a - b * cos(v1)) * cos(u1);
+ p2[0] = (a - b * cos(v1)) * cos(u2);
+ p3[0] = (a - b * cos(v2)) * cos(u1);
+ p4[0] = (a - b * cos(v2)) * cos(u2);
+ p1[1] = (a - b * cos(v1)) * sin(u1);
+ p2[1] = (a - b * cos(v1)) * sin(u2);
+ p3[1] = (a - b * cos(v2)) * sin(u1);
+ p4[1] = (a - b * cos(v2)) * sin(u2);
+ p1[2] = b * sin(v1);
+ p2[2] = b * sin(v1);
+ p3[2] = b * sin(v2);
+ p4[2] = b * sin(v2);
+
+ b1->AddTri(p1, p2, p3, count);
+ b1->AddTri(p4, p2, p3, count+1);
+ b2->AddTri(p1, p2, p3, count);
+ b2->AddTri(p4, p2, p3, count+1);
+
+ count += 2;
+ }
+ }
+
+ fprintf(stderr, "done\n"); fflush(stderr);
+ fprintf(stderr, "Tori have %d triangles each.\n", count);
+ fprintf(stderr, "building hierarchies..."); fflush(stderr);
+ b1->EndModel();
+ b2->EndModel();
+ fprintf(stderr, "done.\n");
+ b1->MemUsage(1);
+ b2->MemUsage(1);
+ fflush(stderr);
+
+ // now we are free to call the proximity routines.
+ // but first, construct the transformations that define the placement
+ // of our two hierarchies in world space:
+
+ // this placement causes them to overlap a large amount.
+
+ PQP_REAL R1[3][3], R2[3][3], T1[3], T2[3];
+
+ R1[0][0] = R1[1][1] = R1[2][2] = 1.0;
+ R1[0][1] = R1[1][0] = R1[2][0] = 0.0;
+ R1[0][2] = R1[1][2] = R1[2][1] = 0.0;
+
+ R2[0][0] = R2[1][1] = R2[2][2] = 1.0;
+ R2[0][1] = R2[1][0] = R2[2][0] = 0.0;
+ R2[0][2] = R2[1][2] = R2[2][1] = 0.0;
+
+ T1[0] = 1.0; T1[1] = 0.0; T1[2] = 0.0;
+ T2[0] = 0.0; T2[1] = 0.0; T2[2] = 0.0;
+
+ // perform a collision query
+
+ PQP_CollideResult cres;
+ PQP_Collide(&cres, R1, T1, b1, R2, T2, b2, PQP_ALL_CONTACTS);
+
+ // looking at the report, we can see where all the contacts were, and
+ // also how many tests were necessary:
+
+ printf("\nAll contact collision query between overlapping tori:\n");
+ printf("Num BV tests: %d\n", cres.NumBVTests());
+ printf("Num Tri tests: %d\n", cres.NumTriTests());
+ printf("Num contact pairs: %d\n", cres.NumPairs());
+#if LISTS
+ int i;
+ for(i=0; i<cres.NumPairs(); i++)
+ {
+ printf("\t contact %4d: tri %4d and tri %4d\n",
+ i,
+ cres.Id1(i),
+ cres.Id2(i));
+ }
+#endif
+
+ // Notice the PQP_ALL_CONTACTS flag we used in the call to PQP_Collide.
+ // The alternative is to use the PQP_FIRST_CONTACT flag, instead.
+ // The result is that the collide routine searches for any contact,
+ // but not all of them. It can take many many fewer tests to locate a single
+ // contact.
+
+ PQP_Collide(&cres, R1, T1, b1, R2, T2, b2, PQP_FIRST_CONTACT);
+
+ printf("\nFirst contact collision query between overlapping tori:\n");
+ printf("Num BV tests: %d\n", cres.NumBVTests());
+ printf("Num Tri tests: %d\n", cres.NumTriTests());
+ printf("Num contact pairs: %d\n", cres.NumPairs());
+#if LISTS
+ for(i=0; i<cres.NumPairs(); i++)
+ {
+ printf("\t contact %4d: tri %4d and tri %4d\n",
+ i,
+ cres.Id1(i),
+ cres.Id2(i));
+ }
+#endif
+
+ // Perform a distance query, which should return a distance of 0.0
+
+ PQP_DistanceResult dres;
+ PQP_Distance(&dres, R1, T1, b1, R2, T2, b2, 0.0, 0.0);
+
+ printf("\nDistance query between overlapping tori\n");
+ printf("Num BV tests: %d\n", dres.NumBVTests());
+ printf("Num Tri tests: %d\n", dres.NumTriTests());
+ printf("Distance: %lf\n", dres.Distance());
+
+ // by rotating one of them around the x-axis 90 degrees, they
+ // are now interlocked, but not quite touching.
+
+ R1[0][0] = 1.0; R1[0][1] = 0.0; R1[0][2] = 0.0;
+ R1[1][0] = 0.0; R1[1][1] = 0.0; R1[1][2] =-1.0;
+ R1[2][0] = 0.0; R1[2][1] = 1.0; R1[2][2] = 0.0;
+
+ PQP_Collide(&cres, R1, T1, b1, R2, T2, b2, PQP_FIRST_CONTACT);
+
+ printf("\nCollision query between interlocked but nontouching tori:\n");
+ printf("Num BV tests: %d\n", cres.NumBVTests());
+ printf("Num Tri tests: %d\n", cres.NumTriTests());
+ printf("Num contact pairs: %d\n", cres.NumPairs());
+#if LISTS
+ for(i=0; i<cres.NumPairs(); i++)
+ {
+ printf("\t contact %4d: tri %4d and tri %4d\n",
+ i,
+ cres.Id1(i),
+ cres.Id2(i));
+ }
+#endif
+
+ // Perform a distance query - the distance found should be greater than zero
+
+ PQP_Distance(&dres, R1, T1, b1, R2, T2, b2, 0.0, 0.0);
+
+ printf("\nDistance query between interlocked but nontouching tori\n");
+ printf("Num BV tests: %d\n", dres.NumBVTests());
+ printf("Num Tri tests: %d\n", dres.NumTriTests());
+ printf("Distance: %lf\n", dres.Distance());
+
+ // Perform two tolerance queries. One tolerance setting is greater than the
+ // distance between the models, and one tolerance is less than the distance.
+
+ PQP_ToleranceResult tres;
+ PQP_REAL tolerance = (PQP_REAL).60;
+ PQP_Tolerance(&tres, R1, T1, b1, R2, T2, b2, tolerance);
+
+ printf("\nTolerance query between interlocked but nontouching tori\n"
+ "with tolerance %lf\n", tolerance);
+ printf("Num BV tests: %d\n", tres.NumBVTests());
+ printf("Num Tri tests: %d\n", tres.NumTriTests());
+ printf("Closer than tolerance? ",tolerance);
+ if (tres.CloserThanTolerance()) printf("yes.\n"); else printf("no.\n");
+
+ tolerance = (PQP_REAL).40;
+ PQP_Tolerance(&tres, R1, T1, b1, R2, T2, b2, tolerance);
+
+ printf("\nTolerance query between interlocked but nontouching tori\n"
+ "with tolerance %lf\n", tolerance);
+ printf("Num BV tests: %d\n", tres.NumBVTests());
+ printf("Num Tri tests: %d\n", tres.NumTriTests());
+ printf("Closer than tolerance? ",tolerance);
+ if (tres.CloserThanTolerance()) printf("yes.\n"); else printf("no.\n");
+
+ // by moving one of the tori closer to the other, they
+ // almost touch. This is the case that requires a lot
+ // of work wiht methods which use bounding boxes of limited
+ // aspect ratio. Oriented bounding boxes are more efficient
+ // at determining noncontact than spheres, octree, or axis-aligned
+ // bounding boxes for scenarios like this. In this case, the interlocked
+ // tori are separated by 0.0001 at their closest point.
+
+
+ T1[0] = (PQP_REAL)1.5999;
+
+ PQP_Collide(&cres, R1, T1, b1, R2, T2, b2, PQP_FIRST_CONTACT);
+
+ printf("\nCollision query on interlocked and almost touching tori:\n");
+ printf("Num BV tests: %d\n", cres.NumBVTests());
+ printf("Num Tri tests: %d\n", cres.NumTriTests());
+ printf("Num contact pairs: %d\n", cres.NumPairs());
+#if LISTS
+ for(i=0; i<cres.NumPairs(); i++)
+ {
+ printf("\t contact %4d: tri %4d and tri %4d\n",
+ i,
+ cres.Id1(i),
+ cres.Id2(i));
+ }
+#endif
+
+ PQP_Distance(&dres, R1, T1, b1, R2, T2, b2, 0.0, 0.0);
+
+ printf("\nDistance query between interlocked and almost touching tori\n");
+ printf("Num BV tests: %d\n", dres.NumBVTests());
+ printf("Num Tri tests: %d\n", dres.NumTriTests());
+ printf("Distance: %lf\n", dres.Distance());
+
+ tolerance = (PQP_REAL)0.00015;
+ PQP_Tolerance(&tres, R1, T1, b1, R2, T2, b2, tolerance);
+
+ printf("\nTolerance query between interlocked and almost touching tori\n"
+ "with tolerance %lf\n", tolerance);
+ printf("Num BV tests: %d\n", tres.NumBVTests());
+ printf("Num Tri tests: %d\n", tres.NumTriTests());
+ printf("Closer than tolerance? ",tolerance);
+ if (tres.CloserThanTolerance()) printf("yes.\n"); else printf("no.\n");
+
+ tolerance = (PQP_REAL)0.00005;
+ PQP_Tolerance(&tres, R1, T1, b1, R2, T2, b2, tolerance);
+
+ printf("\nTolerance query between interlocked and almost touching tori\n"
+ "with tolerance %lf\n", tolerance);
+ printf("Num BV tests: %d\n", tres.NumBVTests());
+ printf("Num Tri tests: %d\n", tres.NumTriTests());
+ printf("Closer than tolerance? ",tolerance);
+ if (tres.CloserThanTolerance()) printf("yes.\n"); else printf("no.\n");
+
+ delete b1;
+ delete b2;
+
+ return 0;
+}
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.dsp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.dsp
new file mode 100644
index 00000000..aec7603d
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.dsp
@@ -0,0 +1,91 @@
+# Microsoft Developer Studio Project File - Name="sample" - Package Owner=<4>
+# Microsoft Developer Studio Generated Build File, Format Version 5.00
+# ** DO NOT EDIT **
+
+# TARGTYPE "Win32 (x86) Console Application" 0x0103
+
+CFG=sample - Win32 Debug
+!MESSAGE This is not a valid makefile. To build this project using NMAKE,
+!MESSAGE use the Export Makefile command and run
+!MESSAGE
+!MESSAGE NMAKE /f "sample.mak".
+!MESSAGE
+!MESSAGE You can specify a configuration when running NMAKE
+!MESSAGE by defining the macro CFG on the command line. For example:
+!MESSAGE
+!MESSAGE NMAKE /f "sample.mak" CFG="sample - Win32 Debug"
+!MESSAGE
+!MESSAGE Possible choices for configuration are:
+!MESSAGE
+!MESSAGE "sample - Win32 Release" (based on "Win32 (x86) Console Application")
+!MESSAGE "sample - Win32 Debug" (based on "Win32 (x86) Console Application")
+!MESSAGE
+
+# Begin Project
+# PROP Scc_ProjName ""
+# PROP Scc_LocalPath ""
+CPP=cl.exe
+RSC=rc.exe
+
+!IF "$(CFG)" == "sample - Win32 Release"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 0
+# PROP BASE Output_Dir "Release"
+# PROP BASE Intermediate_Dir "Release"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 0
+# PROP Output_Dir "./"
+# PROP Intermediate_Dir "Release"
+# PROP Ignore_Export_Lib 0
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /GX /O2 /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "NDEBUG"
+# ADD RSC /l 0x409 /d "NDEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=link.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /machine:I386
+# ADD LINK32 pqp.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib PQP.lib /nologo /subsystem:console /machine:I386 /libpath:"..\..\lib"
+# SUBTRACT LINK32 /nodefaultlib
+
+!ELSEIF "$(CFG)" == "sample - Win32 Debug"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 1
+# PROP BASE Output_Dir "Debug"
+# PROP BASE Intermediate_Dir "Debug"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 1
+# PROP Output_Dir "./"
+# PROP Intermediate_Dir "Debug"
+# PROP Ignore_Export_Lib 0
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /Gm /GX /Zi /Od /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /Od /I "..\..\include" /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "_DEBUG"
+# ADD RSC /l 0x409 /d "_DEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=link.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept
+# ADD LINK32 PQP.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept /libpath:"..\..\lib"
+# SUBTRACT LINK32 /nodefaultlib
+
+!ENDIF
+
+# Begin Target
+
+# Name "sample - Win32 Release"
+# Name "sample - Win32 Debug"
+# Begin Source File
+
+SOURCE=.\main.cpp
+# End Source File
+# End Target
+# End Project
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.plg b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.plg
new file mode 100644
index 00000000..958f67ae
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/sample/sample.plg
@@ -0,0 +1,20 @@
+--------------------Configuration: sample - Win32 Release--------------------
+Begining build with project "C:\Win95\Desktop\PQP_v1.2.1\demos\sample\sample.dsp", at root.
+Active configuration is Win32 (x86) Console Application (based on Win32 (x86) Console Application)
+
+Project's tools are:
+ "32-bit C/C++ Compiler for 80x86" with flags "/nologo /ML /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /Fp"Release/sample.pch" /YX /Fo"Release/" /Fd"Release/" /FD /c "
+ "Win32 Resource Compiler" with flags "/l 0x409 /d "NDEBUG" "
+ "Browser Database Maker" with flags "/nologo /o"./sample.bsc" "
+ "COFF Linker for 80x86" with flags "pqp.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib PQP.lib /nologo /subsystem:console /incremental:no /pdb:"./sample.pdb" /machine:I386 /out:"./sample.exe" /libpath:"..\..\lib" "
+ "Custom Build" with flags ""
+ "<Component 0xa>" with flags ""
+
+Creating temp file "C:\WIN95\TEMP\RSP6314.TMP" with contents <pqp.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib PQP.lib /nologo /subsystem:console /incremental:no /pdb:"./sample.pdb" /machine:I386 /out:"./sample.exe" /libpath:"..\..\lib"
+.\Release\main.obj>
+Creating command line "link.exe @C:\WIN95\TEMP\RSP6314.TMP"
+Linking...
+
+
+
+sample.exe - 0 error(s), 0 warning(s)
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/Makefile b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/Makefile
new file mode 100644
index 00000000..9289a9b1
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/Makefile
@@ -0,0 +1,36 @@
+# Must set these gl and glut locations to build 'spinning'
+
+CC = g++
+
+GL_INCPATH = -I/usr/include/
+GL_LIBPATH = -L/usr/lib/ -L/usr/X11R6/lib/
+GL_LIBS = -lGLU -lGL -lXext -lXmu -lXi -lX11 -lglut
+
+.SUFFIXES: .cpp
+
+CC = g++
+CFLAGS = -g -O2 -I. -I../../include $(GL_INCPATH)
+LDFLAGS = -L. -L../../lib -L/usr/lib/ -L/usr/X11R6/lib/
+LDLIBS = -lPQP -lm $(GL_LIBS)
+
+OBJS = main.o model.o
+TARGET = spinning
+
+.cpp.o:
+ $(CC) ${CFLAGS} -c $<
+
+$(TARGET): $(OBJS)
+ $(CC) $(CFLAGS) $(OBJS) -o $(TARGET) $(LDFLAGS) $(LDLIBS)
+
+run: $(TARGET)
+ $(TARGET)
+
+clean:
+ rm -f *~ $(OBJS) $(TARGET)
+
+
+
+
+
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/MatVec.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/MatVec.h
new file mode 100644
index 00000000..3d90522f
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/MatVec.h
@@ -0,0 +1,881 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_MATVEC_H
+#define PQP_MATVEC_H
+
+#include <math.h>
+#include <stdio.h>
+#include "PQP_Compile.h"
+
+#ifndef M_PI
+const double M_PI = 3.14159265359;
+#endif
+
+#ifdef gnu
+#include "zzzz.h"
+
+#ifdef hppa
+#define myfabs(x) \
+ ({double __value, __arg = (x); \
+ asm("fabs,dbl %1, %0": "=f" (__value): "f" (__arg)); \
+ __value; \
+});
+#endif
+
+#ifdef mips
+#define myfabs(x) \
+ ({double __value, __arg = (x); \
+ asm("abs.d %0, %1": "=f" (__value): "f" (__arg)); \
+ __value; \
+});
+#endif
+
+#else
+
+#define myfabs(x) ((x < 0) ? -x : x)
+
+#endif
+
+
+inline
+void
+Mprintg(const PQP_REAL M[3][3])
+{
+ printf("%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+
+inline
+void
+Mfprint(FILE *f, const PQP_REAL M[3][3])
+{
+ fprintf(f, "%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+inline
+void
+Mprint(const PQP_REAL M[3][3])
+{
+ printf("%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+inline
+void
+Vprintg(const PQP_REAL V[3])
+{
+ printf("%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Vfprint(FILE *f, const PQP_REAL V[3])
+{
+ fprintf(f, "%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Vprint(const PQP_REAL V[3])
+{
+ printf("%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Midentity(PQP_REAL M[3][3])
+{
+ M[0][0] = M[1][1] = M[2][2] = 1.0;
+ M[0][1] = M[1][2] = M[2][0] = 0.0;
+ M[0][2] = M[1][0] = M[2][1] = 0.0;
+}
+
+inline
+void
+Videntity(PQP_REAL T[3])
+{
+ T[0] = T[1] = T[2] = 0.0;
+}
+
+inline
+void
+McM(PQP_REAL Mr[3][3], const PQP_REAL M[3][3])
+{
+ Mr[0][0] = M[0][0]; Mr[0][1] = M[0][1]; Mr[0][2] = M[0][2];
+ Mr[1][0] = M[1][0]; Mr[1][1] = M[1][1]; Mr[1][2] = M[1][2];
+ Mr[2][0] = M[2][0]; Mr[2][1] = M[2][1]; Mr[2][2] = M[2][2];
+}
+
+inline
+void
+MTcM(PQP_REAL Mr[3][3], const PQP_REAL M[3][3])
+{
+ Mr[0][0] = M[0][0]; Mr[1][0] = M[0][1]; Mr[2][0] = M[0][2];
+ Mr[0][1] = M[1][0]; Mr[1][1] = M[1][1]; Mr[2][1] = M[1][2];
+ Mr[0][2] = M[2][0]; Mr[1][2] = M[2][1]; Mr[2][2] = M[2][2];
+}
+
+inline
+void
+VcV(PQP_REAL Vr[3], const PQP_REAL V[3])
+{
+ Vr[0] = V[0]; Vr[1] = V[1]; Vr[2] = V[2];
+}
+
+inline
+void
+McolcV(PQP_REAL Vr[3], const PQP_REAL M[3][3], int c)
+{
+ Vr[0] = M[0][c];
+ Vr[1] = M[1][c];
+ Vr[2] = M[2][c];
+}
+
+inline
+void
+McolcMcol(PQP_REAL Mr[3][3], int cr, const PQP_REAL M[3][3], int c)
+{
+ Mr[0][cr] = M[0][c];
+ Mr[1][cr] = M[1][c];
+ Mr[2][cr] = M[2][c];
+}
+
+inline
+void
+MxMpV(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3], const PQP_REAL T[3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[1][0] +
+ M1[0][2] * M2[2][0] +
+ T[0]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[1][2] * M2[2][0] +
+ T[1]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[1][0] +
+ M1[2][2] * M2[2][0] +
+ T[2]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[2][1] +
+ T[0]);
+ Mr[1][1] = (M1[1][0] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[2][1] +
+ T[1]);
+ Mr[2][1] = (M1[2][0] * M2[0][1] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[2][1] +
+ T[2]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[0][1] * M2[1][2] +
+ M1[0][2] * M2[2][2] +
+ T[0]);
+ Mr[1][2] = (M1[1][0] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[1][2] * M2[2][2] +
+ T[1]);
+ Mr[2][2] = (M1[2][0] * M2[0][2] +
+ M1[2][1] * M2[1][2] +
+ M1[2][2] * M2[2][2] +
+ T[2]);
+}
+
+inline
+void
+MxM(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[1][0] +
+ M1[0][2] * M2[2][0]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[1][2] * M2[2][0]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[1][0] +
+ M1[2][2] * M2[2][0]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[2][1]);
+ Mr[1][1] = (M1[1][0] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[2][1]);
+ Mr[2][1] = (M1[2][0] * M2[0][1] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[2][1]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[0][1] * M2[1][2] +
+ M1[0][2] * M2[2][2]);
+ Mr[1][2] = (M1[1][0] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[1][2] * M2[2][2]);
+ Mr[2][2] = (M1[2][0] * M2[0][2] +
+ M1[2][1] * M2[1][2] +
+ M1[2][2] * M2[2][2]);
+}
+
+
+inline
+void
+MxMT(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[0][1] +
+ M1[0][2] * M2[0][2]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[0][1] +
+ M1[1][2] * M2[0][2]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[0][1] +
+ M1[2][2] * M2[0][2]);
+ Mr[0][1] = (M1[0][0] * M2[1][0] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[1][2]);
+ Mr[1][1] = (M1[1][0] * M2[1][0] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[1][2]);
+ Mr[2][1] = (M1[2][0] * M2[1][0] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[1][2]);
+ Mr[0][2] = (M1[0][0] * M2[2][0] +
+ M1[0][1] * M2[2][1] +
+ M1[0][2] * M2[2][2]);
+ Mr[1][2] = (M1[1][0] * M2[2][0] +
+ M1[1][1] * M2[2][1] +
+ M1[1][2] * M2[2][2]);
+ Mr[2][2] = (M1[2][0] * M2[2][0] +
+ M1[2][1] * M2[2][1] +
+ M1[2][2] * M2[2][2]);
+}
+
+inline
+void
+MTxM(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[1][0] * M2[1][0] +
+ M1[2][0] * M2[2][0]);
+ Mr[1][0] = (M1[0][1] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[2][1] * M2[2][0]);
+ Mr[2][0] = (M1[0][2] * M2[0][0] +
+ M1[1][2] * M2[1][0] +
+ M1[2][2] * M2[2][0]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[1][0] * M2[1][1] +
+ M1[2][0] * M2[2][1]);
+ Mr[1][1] = (M1[0][1] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[2][1] * M2[2][1]);
+ Mr[2][1] = (M1[0][2] * M2[0][1] +
+ M1[1][2] * M2[1][1] +
+ M1[2][2] * M2[2][1]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[1][0] * M2[1][2] +
+ M1[2][0] * M2[2][2]);
+ Mr[1][2] = (M1[0][1] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[2][1] * M2[2][2]);
+ Mr[2][2] = (M1[0][2] * M2[0][2] +
+ M1[1][2] * M2[1][2] +
+ M1[2][2] * M2[2][2]);
+}
+
+inline
+void
+MxV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]);
+ Vr[1] = (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]);
+ Vr[2] = (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+
+inline
+void
+MxVpV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2] +
+ V2[0]);
+ Vr[1] = (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2] +
+ V2[1]);
+ Vr[2] = (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2] +
+ V2[2]);
+}
+
+
+inline
+void
+sMxVpV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = s1 * (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]) +
+ V2[0];
+ Vr[1] = s1 * (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]) +
+ V2[1];
+ Vr[2] = s1 * (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]) +
+ V2[2];
+}
+
+inline
+void
+MTxV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[1][0] * V1[1] +
+ M1[2][0] * V1[2]);
+ Vr[1] = (M1[0][1] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[2][1] * V1[2]);
+ Vr[2] = (M1[0][2] * V1[0] +
+ M1[1][2] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+inline
+void
+sMTxV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = s1*(M1[0][0] * V1[0] +
+ M1[1][0] * V1[1] +
+ M1[2][0] * V1[2]);
+ Vr[1] = s1*(M1[0][1] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[2][1] * V1[2]);
+ Vr[2] = s1*(M1[0][2] * V1[0] +
+ M1[1][2] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+inline
+void
+sMxV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = s1*(M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]);
+ Vr[1] = s1*(M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]);
+ Vr[2] = s1*(M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+
+inline
+void
+VmV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[0] - V2[0];
+ Vr[1] = V1[1] - V2[1];
+ Vr[2] = V1[2] - V2[2];
+}
+
+inline
+void
+VpV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[0] + V2[0];
+ Vr[1] = V1[1] + V2[1];
+ Vr[2] = V1[2] + V2[2];
+}
+
+inline
+void
+VpVxS(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3], PQP_REAL s)
+{
+ Vr[0] = V1[0] + V2[0] * s;
+ Vr[1] = V1[1] + V2[1] * s;
+ Vr[2] = V1[2] + V2[2] * s;
+}
+
+inline
+void
+MskewV(PQP_REAL M[3][3], const PQP_REAL v[3])
+{
+ M[0][0] = M[1][1] = M[2][2] = 0.0;
+ M[1][0] = v[2];
+ M[0][1] = -v[2];
+ M[0][2] = v[1];
+ M[2][0] = -v[1];
+ M[1][2] = -v[0];
+ M[2][1] = v[0];
+}
+
+
+inline
+void
+VcrossV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[1]*V2[2] - V1[2]*V2[1];
+ Vr[1] = V1[2]*V2[0] - V1[0]*V2[2];
+ Vr[2] = V1[0]*V2[1] - V1[1]*V2[0];
+}
+
+
+inline
+PQP_REAL
+Vlength(PQP_REAL V[3])
+{
+ return sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+}
+
+inline
+void
+Vnormalize(PQP_REAL V[3])
+{
+ PQP_REAL d = (PQP_REAL)1.0 / sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+ V[0] *= d;
+ V[1] *= d;
+ V[2] *= d;
+}
+
+
+inline
+PQP_REAL
+VdotV(const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ return (V1[0]*V2[0] + V1[1]*V2[1] + V1[2]*V2[2]);
+}
+
+
+inline
+PQP_REAL
+VdistV2(const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ return ( (V1[0]-V2[0]) * (V1[0]-V2[0]) +
+ (V1[1]-V2[1]) * (V1[1]-V2[1]) +
+ (V1[2]-V2[2]) * (V1[2]-V2[2]));
+}
+
+inline
+void
+VxS(PQP_REAL Vr[3], const PQP_REAL V[3], PQP_REAL s)
+{
+ Vr[0] = V[0] * s;
+ Vr[1] = V[1] * s;
+ Vr[2] = V[2] * s;
+}
+
+inline
+void
+MRotZ(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[0][0] = cos(t);
+ Mr[1][0] = sin(t);
+ Mr[0][1] = -Mr[1][0];
+ Mr[1][1] = Mr[0][0];
+ Mr[2][0] = Mr[2][1] = 0.0;
+ Mr[0][2] = Mr[1][2] = 0.0;
+ Mr[2][2] = 1.0;
+}
+
+
+inline
+void
+MRotX(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[1][1] = cos(t);
+ Mr[2][1] = sin(t);
+ Mr[1][2] = -Mr[2][1];
+ Mr[2][2] = Mr[1][1];
+ Mr[0][1] = Mr[0][2] = 0.0;
+ Mr[1][0] = Mr[2][0] = 0.0;
+ Mr[0][0] = 1.0;
+}
+
+inline
+void
+MRotY(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[2][2] = cos(t);
+ Mr[0][2] = sin(t);
+ Mr[2][0] = -Mr[0][2];
+ Mr[0][0] = Mr[2][2];
+ Mr[1][2] = Mr[1][0] = 0.0;
+ Mr[2][1] = Mr[0][1] = 0.0;
+ Mr[1][1] = 1.0;
+}
+
+inline
+void
+MVtoOGL(double oglm[16], const PQP_REAL R[3][3], const PQP_REAL T[3])
+{
+ oglm[0] = (double)R[0][0];
+ oglm[1] = (double)R[1][0];
+ oglm[2] = (double)R[2][0];
+ oglm[3] = 0.0;
+ oglm[4] = (double)R[0][1];
+ oglm[5] = (double)R[1][1];
+ oglm[6] = (double)R[2][1];
+ oglm[7] = 0.0;
+ oglm[8] = (double)R[0][2];
+ oglm[9] = (double)R[1][2];
+ oglm[10] = (double)R[2][2];
+ oglm[11] = 0.0;
+ oglm[12] = (double)T[0];
+ oglm[13] = (double)T[1];
+ oglm[14] = (double)T[2];
+ oglm[15] = 1.0;
+}
+
+inline
+void
+OGLtoMV(PQP_REAL R[3][3], PQP_REAL T[3], const double oglm[16])
+{
+ R[0][0] = (PQP_REAL)oglm[0];
+ R[1][0] = (PQP_REAL)oglm[1];
+ R[2][0] = (PQP_REAL)oglm[2];
+
+ R[0][1] = (PQP_REAL)oglm[4];
+ R[1][1] = (PQP_REAL)oglm[5];
+ R[2][1] = (PQP_REAL)oglm[6];
+
+ R[0][2] = (PQP_REAL)oglm[8];
+ R[1][2] = (PQP_REAL)oglm[9];
+ R[2][2] = (PQP_REAL)oglm[10];
+
+ T[0] = (PQP_REAL)oglm[12];
+ T[1] = (PQP_REAL)oglm[13];
+ T[2] = (PQP_REAL)oglm[14];
+}
+
+// taken from quatlib, written by Richard Holloway
+const int QX = 0;
+const int QY = 1;
+const int QZ = 2;
+const int QW = 3;
+
+inline
+void
+MRotQ(PQP_REAL destMatrix[3][3], PQP_REAL srcQuat[4])
+{
+ PQP_REAL s;
+ PQP_REAL xs, ys, zs,
+ wx, wy, wz,
+ xx, xy, xz,
+ yy, yz, zz;
+
+ /*
+ * For unit srcQuat, just set s = 2.0; or set xs = srcQuat[QX] +
+ * srcQuat[QX], etc.
+ */
+
+ s = (PQP_REAL)2.0 / (srcQuat[QX]*srcQuat[QX] + srcQuat[QY]*srcQuat[QY] +
+ srcQuat[QZ]*srcQuat[QZ] + srcQuat[QW]*srcQuat[QW]);
+
+ xs = srcQuat[QX] * s; ys = srcQuat[QY] * s; zs = srcQuat[QZ] * s;
+ wx = srcQuat[QW] * xs; wy = srcQuat[QW] * ys; wz = srcQuat[QW] * zs;
+ xx = srcQuat[QX] * xs; xy = srcQuat[QX] * ys; xz = srcQuat[QX] * zs;
+ yy = srcQuat[QY] * ys; yz = srcQuat[QY] * zs; zz = srcQuat[QZ] * zs;
+
+ destMatrix[QX][QX] = (PQP_REAL)1.0 - (yy + zz);
+ destMatrix[QX][QY] = xy + wz;
+ destMatrix[QX][QZ] = xz - wy;
+
+ destMatrix[QY][QX] = xy - wz;
+ destMatrix[QY][QY] = (PQP_REAL)1.0 - (xx + zz);
+ destMatrix[QY][QZ] = yz + wx;
+
+ destMatrix[QZ][QX] = xz + wy;
+ destMatrix[QZ][QY] = yz - wx;
+ destMatrix[QZ][QZ] = (PQP_REAL)1.0 - (xx + yy);
+}
+
+inline
+void
+Mqinverse(PQP_REAL Mr[3][3], PQP_REAL m[3][3])
+{
+ int i,j;
+
+ for(i=0; i<3; i++)
+ for(j=0; j<3; j++)
+ {
+ int i1 = (i+1)%3;
+ int i2 = (i+2)%3;
+ int j1 = (j+1)%3;
+ int j2 = (j+2)%3;
+ Mr[i][j] = (m[j1][i1]*m[j2][i2] - m[j1][i2]*m[j2][i1]);
+ }
+}
+
+// Meigen from Numerical Recipes in C
+
+#if 0
+
+#define rfabs(x) ((x < 0) ? -x : x)
+
+#define ROT(a,i,j,k,l) g=a[i][j]; h=a[k][l]; a[i][j]=g-s*(h+g*tau); a[k][l]=h+s*(g-h*tau);
+
+int
+inline
+Meigen(PQP_REAL vout[3][3], PQP_REAL dout[3], PQP_REAL a[3][3])
+{
+ int i;
+ PQP_REAL tresh,theta,tau,t,sm,s,h,g,c;
+ int nrot;
+ PQP_REAL b[3];
+ PQP_REAL z[3];
+ PQP_REAL v[3][3];
+ PQP_REAL d[3];
+
+ v[0][0] = v[1][1] = v[2][2] = 1.0;
+ v[0][1] = v[1][2] = v[2][0] = 0.0;
+ v[0][2] = v[1][0] = v[2][1] = 0.0;
+
+ b[0] = a[0][0]; d[0] = a[0][0]; z[0] = 0.0;
+ b[1] = a[1][1]; d[1] = a[1][1]; z[1] = 0.0;
+ b[2] = a[2][2]; d[2] = a[2][2]; z[2] = 0.0;
+
+ nrot = 0;
+
+
+ for(i=0; i<50; i++)
+ {
+
+ printf("2\n");
+
+ sm=0.0; sm+=fabs(a[0][1]); sm+=fabs(a[0][2]); sm+=fabs(a[1][2]);
+ if (sm == 0.0) { McM(vout,v); VcV(dout,d); return i; }
+
+ if (i < 3) tresh=0.2*sm/(3*3); else tresh=0.0;
+
+ {
+ g = 100.0*rfabs(a[0][1]);
+ if (i>3 && rfabs(d[0])+g==rfabs(d[0]) && rfabs(d[1])+g==rfabs(d[1]))
+ a[0][1]=0.0;
+ else if (rfabs(a[0][1])>tresh)
+ {
+ h = d[1]-d[0];
+ if (rfabs(h)+g == rfabs(h)) t=(a[0][1])/h;
+ else
+ {
+ theta=0.5*h/(a[0][1]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[0][1];
+ z[0] -= h; z[1] += h; d[0] -= h; d[1] += h;
+ a[0][1]=0.0;
+ ROT(a,0,2,1,2); ROT(v,0,0,0,1); ROT(v,1,0,1,1); ROT(v,2,0,2,1);
+ nrot++;
+ }
+ }
+
+ {
+ g = 100.0*rfabs(a[0][2]);
+ if (i>3 && rfabs(d[0])+g==rfabs(d[0]) && rfabs(d[2])+g==rfabs(d[2]))
+ a[0][2]=0.0;
+ else if (rfabs(a[0][2])>tresh)
+ {
+ h = d[2]-d[0];
+ if (rfabs(h)+g == rfabs(h)) t=(a[0][2])/h;
+ else
+ {
+ theta=0.5*h/(a[0][2]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[0][2];
+ z[0] -= h; z[2] += h; d[0] -= h; d[2] += h;
+ a[0][2]=0.0;
+ ROT(a,0,1,1,2); ROT(v,0,0,0,2); ROT(v,1,0,1,2); ROT(v,2,0,2,2);
+ nrot++;
+ }
+ }
+
+
+ {
+ g = 100.0*rfabs(a[1][2]);
+ if (i>3 && rfabs(d[1])+g==rfabs(d[1]) && rfabs(d[2])+g==rfabs(d[2]))
+ a[1][2]=0.0;
+ else if (rfabs(a[1][2])>tresh)
+ {
+ h = d[2]-d[1];
+ if (rfabs(h)+g == rfabs(h)) t=(a[1][2])/h;
+ else
+ {
+ theta=0.5*h/(a[1][2]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[1][2];
+ z[1] -= h; z[2] += h; d[1] -= h; d[2] += h;
+ a[1][2]=0.0;
+ ROT(a,0,1,0,2); ROT(v,0,1,0,2); ROT(v,1,1,1,2); ROT(v,2,1,2,2);
+ nrot++;
+ }
+ }
+
+ b[0] += z[0]; d[0] = b[0]; z[0] = 0.0;
+ b[1] += z[1]; d[1] = b[1]; z[1] = 0.0;
+ b[2] += z[2]; d[2] = b[2]; z[2] = 0.0;
+
+ }
+
+ fprintf(stderr, "eigen: too many iterations in Jacobi transform (%d).\n", i);
+
+ return i;
+}
+
+#else
+
+
+
+#define ROTATE(a,i,j,k,l) g=a[i][j]; h=a[k][l]; a[i][j]=g-s*(h+g*tau); a[k][l]=h+s*(g-h*tau);
+
+void
+inline
+Meigen(PQP_REAL vout[3][3], PQP_REAL dout[3], PQP_REAL a[3][3])
+{
+ int n = 3;
+ int j,iq,ip,i;
+ PQP_REAL tresh,theta,tau,t,sm,s,h,g,c;
+ int nrot;
+ PQP_REAL b[3];
+ PQP_REAL z[3];
+ PQP_REAL v[3][3];
+ PQP_REAL d[3];
+
+ Midentity(v);
+ for(ip=0; ip<n; ip++)
+ {
+ b[ip] = a[ip][ip];
+ d[ip] = a[ip][ip];
+ z[ip] = 0.0;
+ }
+
+ nrot = 0;
+
+ for(i=0; i<50; i++)
+ {
+
+ sm=0.0;
+ for(ip=0;ip<n;ip++) for(iq=ip+1;iq<n;iq++) sm+=fabs(a[ip][iq]);
+ if (sm == 0.0)
+ {
+ McM(vout, v);
+ VcV(dout, d);
+ return;
+ }
+
+
+ if (i < 3) tresh=(PQP_REAL)0.2*sm/(n*n);
+ else tresh=0.0;
+
+ for(ip=0; ip<n; ip++) for(iq=ip+1; iq<n; iq++)
+ {
+ g = (PQP_REAL)100.0*fabs(a[ip][iq]);
+ if (i>3 &&
+ fabs(d[ip])+g==fabs(d[ip]) &&
+ fabs(d[iq])+g==fabs(d[iq]))
+ a[ip][iq]=0.0;
+ else if (fabs(a[ip][iq])>tresh)
+ {
+ h = d[iq]-d[ip];
+ if (fabs(h)+g == fabs(h)) t=(a[ip][iq])/h;
+ else
+ {
+ theta=(PQP_REAL)0.5*h/(a[ip][iq]);
+ t=(PQP_REAL)(1.0/(fabs(theta)+sqrt(1.0+theta*theta)));
+ if (theta < 0.0) t = -t;
+ }
+ c=(PQP_REAL)1.0/sqrt(1+t*t);
+ s=t*c;
+ tau=s/((PQP_REAL)1.0+c);
+ h=t*a[ip][iq];
+ z[ip] -= h;
+ z[iq] += h;
+ d[ip] -= h;
+ d[iq] += h;
+ a[ip][iq]=0.0;
+ for(j=0;j<ip;j++) { ROTATE(a,j,ip,j,iq); }
+ for(j=ip+1;j<iq;j++) { ROTATE(a,ip,j,j,iq); }
+ for(j=iq+1;j<n;j++) { ROTATE(a,ip,j,iq,j); }
+ for(j=0;j<n;j++) { ROTATE(v,j,ip,j,iq); }
+ nrot++;
+ }
+ }
+ for(ip=0;ip<n;ip++)
+ {
+ b[ip] += z[ip];
+ d[ip] = b[ip];
+ z[ip] = 0.0;
+ }
+ }
+
+ fprintf(stderr, "eigen: too many iterations in Jacobi transform.\n");
+
+ return;
+}
+
+
+#endif
+
+#endif
+/* MATVEC_H */
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/bunny.tris b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/bunny.tris
new file mode 100644
index 00000000..5df21722
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/bunny.tris
@@ -0,0 +1,8817 @@
+2204
+-0.61915501 0.44778999 0.11374
+-0.65483498 0.44209999 0.23309999
+-0.54955502 0.46242001 0.21086
+
+-0.67527496 -0.04277 0.26872
+-0.69119499 -0.03813 0.21893999
+-0.70878502 -0.09154 0.23915001
+
+-0.369095 -0.54116001 0.13157
+-0.38878502 -0.53153 0.12594
+-0.41275501 -0.52455002 0.07158
+
+-0.75503502 0.05844 0.12856
+-0.73905502 0.04444 0.0987
+-0.75351501 0.04522 0.14867
+
+-0.66683502 0.43922001 0.22899
+-0.65483498 0.44209999 0.23309999
+-0.61915501 0.44778999 0.11374
+
+0.100405 0.1927 0.26025
+0.21620501 0.20631001 0.22993
+0.147305 0.21093 0.16179001
+
+-0.49363499 0.44341 -0.49014
+-0.47512501 0.32431999 -0.07113
+-0.51723499 0.35522999 -0.21364
+
+-0.33272499 -0.76374001 -0.11234
+-0.31717501 -0.73977997 -0.10929
+-0.31505501 -0.76257004 -0.12831
+
+0.013465 -0.32881001 0.57973
+-0.006605 -0.27245001 0.59221001
+-0.042595 -0.29021999 0.57817001
+
+-0.478615 0.61969002 -0.45830002
+-0.55654499 0.64793999 -0.39986
+-0.541525 0.60362999 -0.27988001
+
+-0.69841499 -0.28159 0.17025999
+-0.67350502 -0.31801001 0.21348
+-0.70689499 -0.24051001 0.17004999
+
+-0.53543499 0.41438 -0.43537998
+-0.52343498 0.42028999 -0.45174999
+-0.52669498 0.41201 -0.43175999
+
+-0.73406502 0.22117001 0.0777
+-0.69706497 0.27559999 0.04741
+-0.67165497 0.20761999 -0.01075
+
+0.032965 0.15014 0.30976
+0.119035 0.13868 0.35504002
+0.100405 0.1927 0.26025
+
+-0.48884499 0.70297997 -0.56327
+-0.543125 0.70637001 -0.51022999
+-0.478615 0.61969002 -0.45830002
+
+-0.56956501 0.37901001 0.42835999
+-0.62949501 0.42409 0.33152
+-0.62565498 0.37287998 0.41800999
+
+-0.69841499 -0.28159 0.17025999
+-0.67290497 -0.32478001 0.06036
+-0.67019501 -0.33046001 0.17235001
+
+0.26532499 0.11682 0.36832001
+0.279865 0.18177999 0.28193001
+0.185485 0.15646 0.33446999
+
+0.100405 0.1927 0.26025
+0.19949499 0.18938999 0.2817
+0.21620501 0.20631001 0.22993
+
+-0.051545 0.75455002 -0.12812
+-0.075495 0.73363998 -0.09516
+-0.036455 0.74396004 -0.12342
+
+-0.085275 0.1548 0.17931
+-0.087935 0.12239 0.26698
+0.014575 0.18521999 0.18579
+
+0.100405 0.1927 0.26025
+0.147305 0.21093 0.16179001
+0.014575 0.18521999 0.18579
+
+-0.440755 0.59640999 -0.59333
+-0.43966499 0.60813999 -0.59201
+-0.44141499 0.60801998 -0.58164001
+
+0.068505 0.67084 -0.27976999
+0.073585 0.64028999 -0.27017
+0.046245 0.64051003 -0.26128
+
+-0.722985 0.29028 0.13737
+-0.65177498 0.38554001 0.03709
+-0.685625 0.31711 0.06703
+
+-0.53012501 0.29573 0.48049
+-0.59655499 0.21528 0.54181
+-0.52195499 0.23915001 0.49179001
+
+-0.49343498 0.53766998 -0.56959999
+-0.46016499 0.52960999 -0.57521999
+-0.49435501 0.49361 -0.54973999
+
+0.62454498 -0.39271999 0.04435
+0.59800499 -0.28384001 -0.03253
+0.616395 -0.19808001 0.01714
+
+-0.40461498 0.42754002 0.32105999
+-0.45004501 0.41863998 0.36409
+-0.43137501 0.38099998 0.37743
+
+-0.62663502 0.17285 0.54678001
+-0.59655499 0.21528 0.54181
+-0.65234497 0.19790001 0.53490002
+
+-0.59655499 0.21528 0.54181
+-0.60633499 0.29861 0.49606998
+-0.65054497 0.23882 0.51790001
+
+0.63150501 -0.32306999 0.09721
+0.62454498 -0.39271999 0.04435
+0.616395 -0.19808001 0.01714
+
+-0.087935 0.12239 0.26698
+0.100405 0.1927 0.26025
+0.014575 0.18521999 0.18579
+
+-0.40461498 0.42754002 0.32105999
+-0.38591499 0.35167 0.31952
+-0.36774502 0.40701 0.25933001
+
+-0.62663502 0.17285 0.54678001
+-0.59962502 0.11646 0.54145
+-0.59655499 0.21528 0.54181
+
+-0.48044498 -0.07672 -0.15554
+-0.40962502 -0.24707001 -0.19660999
+-0.39932499 -0.27525 -0.19733
+
+-0.67873497 0.42423 0.10789
+-0.61915501 0.44778999 0.11374
+-0.65177498 0.41154999 0.04812
+
+-0.71519501 -0.22723 0.07012
+-0.68001503 -0.24351 -0.00998
+-0.63365501 -0.34187 -0.01984
+
+-0.112925 0.44946999 -0.01904
+-0.29133499 0.43453999 0.10392
+-0.28335501 0.37535999 0.07935
+
+0.20192499 0.21209999 0.08168
+0.267075 0.20905001 0.1627
+0.30644501 0.19247999 0.06287
+
+-0.31738501 0.43448002 0.11911
+-0.049325 0.62575001 -0.12564
+-0.112215 0.62556 -0.07594
+
+-0.50442501 0.51681 -0.12221
+-0.497005 0.44953999 -0.01774
+-0.462285 0.43570999 -0.09058
+
+0.147305 0.21093 0.16179001
+0.21620501 0.20631001 0.22993
+0.267075 0.20905001 0.1627
+
+-0.38455502 -0.62816002 0.13858
+-0.35919498 -0.65380997 0.20221001
+-0.334715 -0.61401001 0.18212
+
+-0.17445499 -0.76107002 0.26183001
+-0.189415 -0.75043999 0.19530001
+-0.18321501 -0.75733002 0.1487
+
+-0.43966499 0.60813999 -0.59201
+-0.440755 0.59640999 -0.59333
+-0.43943501 0.61122002 -0.59380001
+
+-0.68663498 0.30483 0.43856998
+-0.66231499 0.29212999 0.47123001
+-0.62565498 0.37287998 0.41800999
+
+-0.58244499 0.64759003 -0.39550999
+-0.541525 0.60362999 -0.27988001
+-0.55654499 0.64793999 -0.39986
+
+0.61706501 -0.15582 0.06717
+0.63150501 -0.32306999 0.09721
+0.616395 -0.19808001 0.01714
+
+0.119035 0.13868 0.35504002
+0.185485 0.15646 0.33446999
+0.19949499 0.18938999 0.2817
+
+-0.439925 0.61355999 -0.59553001
+-0.44219501 0.62398998 -0.59071999
+-0.43966499 0.60813999 -0.59201
+
+-0.297925 -0.53887001 -0.09417
+-0.26883499 -0.37657001 -0.16448
+-0.238365 -0.47976002 -0.11273
+
+-0.67350502 -0.31801001 0.21348
+-0.65677498 -0.28486 0.31427999
+-0.71858498 -0.18570999 0.23955999
+
+-0.445825 0.62064999 -0.60304001
+-0.44350498 0.63459 -0.59969002
+-0.439925 0.61355999 -0.59553001
+
+0.36023499 -0.12728 -0.21188999
+0.38315498 -0.105 -0.19958
+0.44883499 -0.17316 -0.18752001
+
+0.004935 0.49839001 -0.08707
+-0.112925 0.44946999 -0.01904
+-0.34072498 0.34067001 0.0194
+
+-0.52690498 0.36866001 0.4325
+-0.56956501 0.37901001 0.42835999
+-0.60633499 0.29861 0.49606998
+
+-0.722985 0.29028 0.13737
+-0.69845497 0.34506001 0.09724
+-0.65177498 0.38554001 0.03709
+
+0.21620501 0.20631001 0.22993
+0.31116501 0.18573 0.23601
+0.267075 0.20905001 0.1627
+
+-0.53012501 0.29573 0.48049
+-0.52690498 0.36866001 0.4325
+-0.60633499 0.29861 0.49606998
+
+0.66172501 -0.52612 -0.03485
+0.66172501 -0.51227001 -0.03209
+0.701595 -0.51362999 -0.01377
+
+-0.27186501 0.17989 0.1998
+-0.28657499 0.21525999 0.16419001
+-0.318915 0.22754999 0.2701
+
+-0.096095 0.71514 -0.06997
+-0.236595 0.58076 0.04404
+-0.166485 0.62580002 -0.00026
+
+0.38503502 0.15941 0.19188999
+0.41226501 0.13985 0.08791
+0.30644501 0.19247999 0.06287
+
+0.046245 0.64051003 -0.26128
+-0.027095 0.51598 -0.13203
+-0.048255 0.52195999 -0.13641
+
+0.059645 0.68377998 -0.28246
+0.068505 0.67084 -0.27976999
+0.046245 0.64051003 -0.26128
+
+-0.44495499 0.61160999 -0.60196999
+-0.45517502 0.62153999 -0.60337002
+-0.445825 0.62064999 -0.60304001
+
+-0.040395 -0.02881 -0.20667999
+0.027045 -0.06751 -0.21985001
+0.074325 -0.09863 -0.22704
+
+0.100405 0.1927 0.26025
+0.119035 0.13868 0.35504002
+0.19949499 0.18938999 0.2817
+
+0.17338499 -0.16284 0.56652
+0.223505 -0.23148001 0.58157001
+0.25977501 -0.2282 0.57007
+
+-0.52043499 0.07819 -0.06974
+-0.43113499 0.13668 -0.06854
+-0.43526501 0.09176 -0.08455
+
+-0.551175 -0.15953 0.43046001
+-0.50651501 -0.10104 0.42856998
+-0.57303501 -0.09277 0.39316002
+
+0.63273499 -0.64609001 0.00875
+0.63202499 -0.59748001 -0.03384
+0.68647499 -0.58339001 -0.0017
+
+-0.50564499 -0.26843 0.44533001
+-0.44656502 -0.19707001 0.46938
+-0.51212502 -0.2273 0.45049999
+
+0.143465 0.09524 0.39535999
+0.119035 0.13868 0.35504002
+0.013225 0.0811 0.38118
+
+0.093335 -0.54011002 0.55001999
+0.133365 -0.51195999 0.55555
+0.093385 -0.48191002 0.57638
+
+0.26328501 -0.13812 0.51595001
+0.25977501 -0.2282 0.57007
+0.27328501 -0.16485001 0.53637001
+
+0.26328501 -0.13812 0.51595001
+0.27328501 -0.16485001 0.53637001
+0.327005 -0.16132 0.50963001
+
+0.61706501 -0.15582 0.06717
+0.58518501 -0.07291 0.16698
+0.61038502 -0.18419001 0.23695999
+
+0.32314499 0.16155001 -0.00588
+0.232845 0.19128 0.00246
+0.30644501 0.19247999 0.06287
+
+-0.74736504 0.31806 0.17700001
+-0.72976501 0.37284 0.12714
+-0.69845497 0.34506001 0.09724
+
+-0.32939499 -0.58321999 0.36421001
+-0.296705 -0.61009998 0.40333
+-0.256665 -0.55305 0.4109
+
+-0.51212502 -0.2273 0.45049999
+-0.44656502 -0.19707001 0.46938
+-0.55939499 -0.21372999 0.42647999
+
+-0.522085 0.42964001 -0.46967999
+-0.52343498 0.42028999 -0.45174999
+-0.52310501 0.42203999 -0.45536999
+
+0.56855499 -0.27214001 -0.1024
+0.595695 -0.19973 -0.04273
+0.59800499 -0.28384001 -0.03253
+
+-0.106735 0.07859 0.32783001
+0.013225 0.0811 0.38118
+0.032965 0.15014 0.30976
+
+-0.50564499 -0.26843 0.44533001
+-0.51212502 -0.2273 0.45049999
+-0.54116501 -0.33391998 0.39556
+
+-0.65483498 0.44209999 0.23309999
+-0.567505 0.44047001 0.32217999
+-0.54955502 0.46242001 0.21086
+
+-0.446595 -0.28271999 0.45134998
+-0.50564499 -0.26843 0.44533001
+-0.437295 -0.37362999 0.41646999
+
+0.26304501 -0.48462002 0.55549999
+0.163435 -0.53869999 0.56303001
+0.263435 -0.55469002 0.54113998
+
+0.182565 -0.11096 0.51632
+0.154285 -0.09136 0.45977001
+0.079635 -0.11564 0.52494999
+
+-0.150585 -0.30923 -0.29997999
+-0.119055 -0.34823002 -0.33359001
+-0.107915 -0.53838001 -0.23878
+
+-0.49363499 0.44341 -0.49014
+-0.49435501 0.49361 -0.54973999
+-0.46016499 0.52960999 -0.57521999
+
+-0.45953499 0.45066002 -0.34074001
+-0.44795502 0.48275002 -0.23052
+-0.45510502 0.35847 -0.05053
+
+0.583465 -0.60224998 0.34046001
+0.55329498 -0.58823002 0.33521
+0.49892502 -0.66067001 0.30966
+
+-0.35919498 -0.65380997 0.20221001
+-0.404995 -0.67698997 0.19254
+-0.41561501 -0.69004997 0.22243999
+
+-0.722985 0.29028 0.13737
+-0.74114502 0.29077999 0.20722
+-0.74736504 0.31806 0.17700001
+
+-0.49363499 0.44341 -0.49014
+-0.45953499 0.45066002 -0.34074001
+-0.47512501 0.32431999 -0.07113
+
+-0.50564499 -0.26843 0.44533001
+-0.446595 -0.28271999 0.45134998
+-0.44656502 -0.19707001 0.46938
+
+-0.38665501 -0.15554 0.46
+-0.436525 -0.08632 0.43841
+-0.44656502 -0.19707001 0.46938
+
+0.053215 -0.32796001 0.58986
+0.133395 -0.34088001 0.60337002
+0.043465 -0.23129 0.58570999
+
+0.293375 0.02494 0.40310001
+0.32342499 -0.00259 0.41494999
+0.37462502 0.09203 0.35064999
+
+0.293375 0.02494 0.40310001
+0.23304501 0.00794 0.42648998
+0.154285 -0.09136 0.45977001
+
+-0.436525 -0.08632 0.43841
+-0.551175 -0.15953 0.43046001
+-0.44656502 -0.19707001 0.46938
+
+0.136995 -0.12943 0.54544998
+0.182745 -0.12148 0.53138
+0.182565 -0.11096 0.51632
+
+-0.437295 -0.37362999 0.41646999
+-0.37656502 -0.29565001 0.46369999
+-0.446595 -0.28271999 0.45134998
+
+0.035725 -0.09047 0.45244999
+0.079635 -0.11564 0.52494999
+0.154285 -0.09136 0.45977001
+
+0.262635 -0.34882 0.57363998
+0.276035 -0.42984001 0.55702
+0.336675 -0.44263 0.52173
+
+-0.47702499 -0.74514 -0.06318
+-0.52946499 -0.75737999 -0.02987
+-0.50606499 -0.70516998 -0.03412
+
+-0.37656502 -0.29565001 0.46369999
+-0.33655499 -0.23921 0.47109001
+-0.446595 -0.28271999 0.45134998
+
+-0.436525 -0.08632 0.43841
+-0.50651501 -0.10104 0.42856998
+-0.551175 -0.15953 0.43046001
+
+0.103425 -0.39764999 0.58700001
+0.17356501 -0.39825001 0.58146
+0.153475 -0.35493 0.60167
+
+0.153435 -0.64473 0.48566002
+0.19356501 -0.64248001 0.49592999
+0.203395 -0.59640999 0.54062
+
+0.153435 -0.64473 0.48566002
+0.203395 -0.59640999 0.54062
+0.153405 -0.58124001 0.55702
+
+-0.41656502 -0.18295 0.46936001
+-0.44656502 -0.19707001 0.46938
+-0.446595 -0.28271999 0.45134998
+
+0.103425 -0.39764999 0.58700001
+0.133395 -0.34088001 0.60337002
+0.053215 -0.32796001 0.58986
+
+0.293375 0.02494 0.40310001
+0.37462502 0.09203 0.35064999
+0.26532499 0.11682 0.36832001
+
+-0.53415501 0.42109001 -0.44837002
+-0.531875 0.43505001 -0.47442001
+-0.52310501 0.42203999 -0.45536999
+
+-0.192925 0.12158 0.28837999
+-0.106735 0.07859 0.32783001
+-0.138135 0.15368 0.18959999
+
+-0.297925 -0.53887001 -0.09417
+-0.157915 -0.5673 -0.08973
+-0.24751499 -0.60999001 -0.0966
+
+-0.116545 0.01205 -0.16351999
+-0.160285 -0.07244 -0.20541
+-0.190415 -0.01619 -0.18384001
+
+-0.436525 -0.08632 0.43841
+-0.38654499 -0.07216 0.43530998
+-0.336605 -0.00365 0.39479
+
+-0.42501499 0.0966 0.42016998
+-0.44178501 0.09654 0.43144001
+-0.44835499 0.03677 0.38549
+
+0.37462502 0.09203 0.35064999
+0.368885 0.12605 0.31459999
+0.29845501 0.12968 0.34632999
+
+-0.406185 -0.64178001 0.44240002
+-0.40703499 -0.68030998 0.47273998
+-0.35189499 -0.67195 0.46866001
+
+-0.46279499 0.65877998 -0.53924999
+-0.48884499 0.70297997 -0.56327
+-0.478615 0.61969002 -0.45830002
+
+-0.49119499 0.00697 0.39306
+-0.436525 -0.08632 0.43841
+-0.336605 -0.00365 0.39479
+
+0.053525 -0.59877998 0.51932999
+0.153435 -0.64473 0.48566002
+0.153405 -0.58124001 0.55702
+
+-0.43119499 -0.63069 0.39651001
+-0.45441502 -0.64302002 0.36220001
+-0.46994499 -0.66989998 0.39380001
+
+-0.083505 0.68447998 -0.17287001
+-0.073375 0.61046001 -0.18223
+-0.18282499 0.59498001 -0.13044
+
+-0.41656502 -0.18295 0.46936001
+-0.446595 -0.28271999 0.45134998
+-0.33655499 -0.23921 0.47109001
+
+-0.430355 -0.10442 -0.17239
+-0.420495 -0.13227 -0.18625
+-0.40962502 -0.24707001 -0.19660999
+
+0.203305 0.06761 0.41046001
+0.23304501 0.00794 0.42648998
+0.293375 0.02494 0.40310001
+
+0.57196499 -0.49865002 0.31608
+0.59136501 -0.44555 0.29172001
+0.57273499 -0.37573002 0.33617001
+
+-0.141445 -0.71961998 0.33926998
+-0.129625 -0.75866997 0.17889999
+-0.097395 -0.72411003 0.17242001
+
+0.74039497 -0.56462002 0.06716
+0.757565 -0.47983002 0.05688
+0.77457497 -0.49212002 0.10691
+
+0.046245 0.64051003 -0.26128
+0.066055 0.59167999 -0.23388
+-0.027095 0.51598 -0.13203
+
+-0.33655499 -0.23921 0.47109001
+-0.37656502 -0.29565001 0.46369999
+-0.326595 -0.31034 0.45616001
+
+-0.44656502 -0.19707001 0.46938
+-0.41656502 -0.18295 0.46936001
+-0.38665501 -0.15554 0.46
+
+-0.406535 0.02358 0.37558998
+-0.33633499 0.03778 0.36269001
+-0.343685 0.08148 0.34409
+
+0.26532499 0.11682 0.36832001
+0.185485 0.15646 0.33446999
+0.143465 0.09524 0.39535999
+
+0.154285 -0.09136 0.45977001
+0.253855 -0.08411 0.48338001
+0.32342499 -0.00259 0.41494999
+
+0.37626499 -0.10669 0.47582001
+0.32317501 -0.0705 0.47466
+0.352155 -0.22743 0.51053001
+
+-0.40703499 -0.68030998 0.47273998
+-0.363685 -0.71358002 0.48608002
+-0.35189499 -0.67195 0.46866001
+
+0.32317501 -0.0705 0.47466
+0.42301498 -0.09387 0.43786999
+0.42587502 -0.0541 0.4068
+
+-0.38665501 -0.15554 0.46
+-0.41656502 -0.18295 0.46936001
+-0.33655499 -0.23921 0.47109001
+
+-0.406535 0.02358 0.37558998
+-0.49119499 0.00697 0.39306
+-0.336605 -0.00365 0.39479
+
+0.103345 -0.42644001 0.57532001
+0.17356501 -0.39825001 0.58146
+0.103425 -0.39764999 0.58700001
+
+-0.326595 -0.31034 0.45616001
+-0.306675 -0.36883999 0.43159
+-0.24657499 -0.24148001 0.44134998
+
+0.55329498 -0.58823002 0.33521
+0.52557499 -0.56825001 0.33627998
+0.49892502 -0.66067001 0.30966
+
+0.63363499 -0.56191002 0.33492001
+0.59330502 -0.54569 0.33654999
+0.583465 -0.60224998 0.34046001
+
+0.143455 0.01272 0.43963001
+0.093525 -0.02874 0.45459
+0.154285 -0.09136 0.45977001
+
+-0.34806499 -0.62027 0.40410999
+-0.354585 -0.59728001 0.33195
+-0.39304501 -0.61914001 0.39880001
+
+-0.30634501 -0.15582 0.45601002
+-0.306255 -0.14151 0.45530998
+-0.38665501 -0.15554 0.46
+
+-0.306255 -0.14151 0.45530998
+-0.38654499 -0.07216 0.43530998
+-0.38665501 -0.15554 0.46
+
+0.327005 -0.16132 0.50963001
+0.33553501 -0.21408001 0.52173
+0.352155 -0.22743 0.51053001
+
+-0.74114502 0.29077999 0.20722
+-0.72123497 0.26363001 0.29735001
+-0.74582497 0.34598999 0.25691
+
+-0.74152496 0.38702 0.23667
+-0.72732498 0.41339001 0.20645
+-0.74042503 0.40042999 0.17667999
+
+0.40009499 -0.18596001 0.49257999
+0.37626499 -0.10669 0.47582001
+0.352155 -0.22743 0.51053001
+
+0.583465 -0.60224998 0.34046001
+0.49892502 -0.66067001 0.30966
+0.57481499 -0.63938 0.32445999
+
+-0.43943501 0.61122002 -0.59380001
+-0.44495499 0.61160999 -0.60196999
+-0.439925 0.61355999 -0.59553001
+
+-0.336605 -0.00365 0.39479
+-0.306255 -0.14151 0.45530998
+-0.266535 -0.03076 0.41641998
+
+-0.33633499 0.03778 0.36269001
+-0.406535 0.02358 0.37558998
+-0.336605 -0.00365 0.39479
+
+0.203305 0.06761 0.41046001
+0.143465 0.09524 0.39535999
+0.143455 0.01272 0.43963001
+
+-0.49363499 0.44341 -0.49014
+-0.52519501 0.43825001 -0.48328999
+-0.49435501 0.49361 -0.54973999
+
+0.143465 0.09524 0.39535999
+0.013225 0.0811 0.38118
+0.043555 0.01225 0.43209
+
+-0.266625 -0.63647999 0.42265999
+-0.296705 -0.61009998 0.40333
+-0.35189499 -0.67195 0.46866001
+
+-0.306255 -0.14151 0.45530998
+-0.246605 -0.2133 0.44130001
+-0.216565 -0.08709 0.42601002
+
+-0.306255 -0.14151 0.45530998
+-0.30634501 -0.15582 0.45601002
+-0.246605 -0.2133 0.44130001
+
+-0.336605 -0.00365 0.39479
+-0.38654499 -0.07216 0.43530998
+-0.306255 -0.14151 0.45530998
+
+0.061495 0.71106003 -0.27132
+0.036155 0.71919998 -0.22396
+0.077465 0.65564003 -0.25237
+
+-0.51220501 0.43668999 -0.48354
+-0.52519501 0.43825001 -0.48328999
+-0.49363499 0.44341 -0.49014
+
+0.182565 -0.11096 0.51632
+0.23345501 -0.11154 0.49640999
+0.154285 -0.09136 0.45977001
+
+0.032965 0.15014 0.30976
+0.013225 0.0811 0.38118
+0.119035 0.13868 0.35504002
+
+0.20192499 0.21209999 0.08168
+0.147305 0.21093 0.16179001
+0.267075 0.20905001 0.1627
+
+-0.50442501 0.51681 -0.12221
+-0.541525 0.60362999 -0.27988001
+-0.55648499 0.57926998 -0.21315001
+
+-0.30634501 -0.15582 0.45601002
+-0.38665501 -0.15554 0.46
+-0.33655499 -0.23921 0.47109001
+
+0.293375 0.02494 0.40310001
+0.26532499 0.11682 0.36832001
+0.203305 0.06761 0.41046001
+
+0.153405 -0.58124001 0.55702
+0.163435 -0.53869999 0.56303001
+0.133365 -0.51195999 0.55555
+
+-0.296705 -0.61009998 0.40333
+-0.34806499 -0.62027 0.40410999
+-0.406185 -0.64178001 0.44240002
+
+-0.306675 -0.36883999 0.43159
+-0.21644501 -0.28254 0.45178001
+-0.24657499 -0.24148001 0.44134998
+
+-0.266535 -0.03076 0.41641998
+-0.216565 -0.08709 0.42601002
+-0.236425 0.01018 0.38021999
+
+0.154285 -0.09136 0.45977001
+0.32342499 -0.00259 0.41494999
+0.293375 0.02494 0.40310001
+
+-0.72732498 0.41339001 0.20645
+-0.67873497 0.42423 0.10789
+-0.70818497 0.41217999 0.12753
+
+-0.216555 -0.65108002 0.42185001
+-0.35189499 -0.67195 0.46866001
+-0.363685 -0.71358002 0.48608002
+
+-0.256665 -0.55305 0.4109
+-0.272745 -0.45799 0.41743
+-0.32939499 -0.58321999 0.36421001
+
+-0.363685 -0.71358002 0.48608002
+-0.37914501 -0.74181999 0.48116001
+-0.307395 -0.74459 0.46473999
+
+-0.296705 -0.61009998 0.40333
+-0.406185 -0.64178001 0.44240002
+-0.35189499 -0.67195 0.46866001
+
+-0.21657499 -0.42470001 0.43263
+-0.256665 -0.55305 0.4109
+-0.206465 -0.52480999 0.41360001
+
+-0.192925 0.12158 0.28837999
+-0.28057501 0.13838 0.25653999
+-0.308445 0.09557 0.30705999
+
+-0.192925 0.12158 0.28837999
+-0.308445 0.09557 0.30705999
+-0.33633499 0.03778 0.36269001
+
+-0.43411499 -0.75475998 0.44608002
+-0.33710499 -0.76268997 0.2824
+-0.257085 -0.75538002 0.41583
+
+-0.216555 -0.65108002 0.42185001
+-0.266625 -0.63647999 0.42265999
+-0.35189499 -0.67195 0.46866001
+
+-0.216555 -0.65108002 0.42185001
+-0.22651501 -0.56736 0.40914001
+-0.266625 -0.63647999 0.42265999
+
+-0.306675 -0.36883999 0.43159
+-0.326595 -0.31034 0.45616001
+-0.37656502 -0.29565001 0.46369999
+
+-0.246605 -0.2133 0.44130001
+-0.30634501 -0.15582 0.45601002
+-0.24657499 -0.24148001 0.44134998
+
+-0.216565 -0.08709 0.42601002
+-0.266535 -0.03076 0.41641998
+-0.306255 -0.14151 0.45530998
+
+-0.192925 0.12158 0.28837999
+-0.33633499 0.03778 0.36269001
+-0.236425 0.01018 0.38021999
+
+-0.43119499 -0.63069 0.39651001
+-0.42884499 -0.63210999 0.34209
+-0.45441502 -0.64302002 0.36220001
+
+-0.47864498 -0.74934998 0.25862
+-0.47838501 -0.72314003 0.26280001
+-0.45761501 -0.71341003 0.26252001
+
+-0.69706497 0.27559999 0.04741
+-0.685625 0.31711 0.06703
+-0.62156502 0.28177999 -0.03207
+
+-0.363685 -0.71358002 0.48608002
+-0.307395 -0.74459 0.46473999
+-0.232635 -0.74156998 0.44324001
+
+-0.33655499 -0.23921 0.47109001
+-0.326595 -0.31034 0.45616001
+-0.24657499 -0.24148001 0.44134998
+
+-0.206455 -0.16997 0.45382999
+-0.146535 -0.15527 0.46143002
+-0.136605 -0.09948 0.44941002
+
+0.066055 0.59167999 -0.23388
+0.075975 0.58987 -0.22885
+0.068865 0.56655998 -0.20183001
+
+-0.22651501 -0.56736 0.40914001
+-0.256665 -0.55305 0.4109
+-0.296705 -0.61009998 0.40333
+
+-0.306675 -0.36883999 0.43159
+-0.21657499 -0.42470001 0.43263
+-0.21644501 -0.28254 0.45178001
+
+0.17338499 -0.16284 0.56652
+0.053405 -0.17601 0.57659
+0.223505 -0.23148001 0.58157001
+
+-0.54392502 0.40847 -0.42164001
+-0.53543499 0.41438 -0.43537998
+-0.52669498 0.41201 -0.43175999
+
+0.153405 -0.58124001 0.55702
+0.133365 -0.51195999 0.55555
+0.093335 -0.54011002 0.55001999
+
+-0.256665 -0.55305 0.4109
+-0.22651501 -0.56736 0.40914001
+-0.206465 -0.52480999 0.41360001
+
+-0.21644501 -0.28254 0.45178001
+-0.246605 -0.2133 0.44130001
+-0.24657499 -0.24148001 0.44134998
+
+-0.206455 -0.16997 0.45382999
+-0.136605 -0.09948 0.44941002
+-0.216565 -0.08709 0.42601002
+
+-0.216565 -0.08709 0.42601002
+-0.136605 -0.09948 0.44941002
+-0.096575 0.02365 0.37799999
+
+0.26328501 -0.13812 0.51595001
+0.17338499 -0.16284 0.56652
+0.25977501 -0.2282 0.57007
+
+-0.30634501 -0.15582 0.45601002
+-0.33655499 -0.23921 0.47109001
+-0.24657499 -0.24148001 0.44134998
+
+-0.21644501 -0.28254 0.45178001
+-0.176625 -0.22690001 0.44397999
+-0.206455 -0.16997 0.45382999
+
+-0.266535 -0.03076 0.41641998
+-0.236425 0.01018 0.38021999
+-0.336605 -0.00365 0.39479
+
+-0.21657499 -0.42470001 0.43263
+-0.16668501 -0.42550999 0.42176998
+-0.156665 -0.36923 0.42314999
+
+-0.21644501 -0.28254 0.45178001
+-0.206455 -0.16997 0.45382999
+-0.246605 -0.2133 0.44130001
+
+0.23304501 0.00794 0.42648998
+0.143455 0.01272 0.43963001
+0.154285 -0.09136 0.45977001
+
+0.24317499 -0.62743 0.50932999
+0.203395 -0.59640999 0.54062
+0.19356501 -0.64248001 0.49592999
+
+-0.014785 0.14532 -0.02397
+-0.060175 0.08937 -0.1052
+-0.138675 0.11073 -0.06666
+
+-0.216555 -0.65108002 0.42185001
+-0.140305 -0.57868999 0.38641998
+-0.22651501 -0.56736 0.40914001
+
+-0.206465 -0.52480999 0.41360001
+-0.22651501 -0.56736 0.40914001
+-0.140305 -0.57868999 0.38641998
+
+-0.156665 -0.36923 0.42314999
+-0.16668501 -0.42550999 0.42176998
+-0.116605 -0.52758999 0.38146999
+
+-0.156565 -0.18361 0.45839001
+-0.146535 -0.15527 0.46143002
+-0.206455 -0.16997 0.45382999
+
+-0.136605 -0.09948 0.44941002
+0.013225 0.0811 0.38118
+-0.096575 0.02365 0.37799999
+
+0.72791496 -0.59351002 0.06742
+0.67806503 -0.65469002 0.13749
+0.67858498 -0.64014999 0.05778
+
+-0.044845 -0.65685997 0.5468
+-0.043565 -0.73834 0.55035999
+0.065805 -0.69416 0.51382
+
+0.23345501 -0.11154 0.49640999
+0.182745 -0.12148 0.53138
+0.26328501 -0.13812 0.51595001
+
+-0.21657499 -0.42470001 0.43263
+-0.272745 -0.45799 0.41743
+-0.256665 -0.55305 0.4109
+
+0.59330502 -0.54569 0.33654999
+0.64346497 -0.49037998 0.32360001
+0.57196499 -0.49865002 0.31608
+
+-0.49023499 0.31427999 -0.06865
+-0.54886501 0.33823002 -0.12392
+-0.47512501 0.32431999 -0.07113
+
+-0.59239498 0.37070999 -0.07326
+-0.54886501 0.33823002 -0.12392
+-0.54577499 0.32955002 -0.08891
+
+-0.22651501 -0.56736 0.40914001
+-0.296705 -0.61009998 0.40333
+-0.266625 -0.63647999 0.42265999
+
+-0.140305 -0.57868999 0.38641998
+-0.116605 -0.52758999 0.38146999
+-0.206465 -0.52480999 0.41360001
+
+0.25977501 -0.2282 0.57007
+0.276535 -0.21360001 0.55987
+0.27328501 -0.16485001 0.53637001
+
+-0.43966499 0.60813999 -0.59201
+-0.43943501 0.61122002 -0.59380001
+-0.439925 0.61355999 -0.59553001
+
+-0.176625 -0.22690001 0.44397999
+-0.21644501 -0.28254 0.45178001
+-0.156665 -0.36923 0.42314999
+
+-0.146535 -0.15527 0.46143002
+-0.093355 -0.17006001 0.46999001
+-0.136605 -0.09948 0.44941002
+
+-0.44350498 0.63459 -0.59969002
+-0.45517502 0.62153999 -0.60337002
+-0.44495499 0.61160999 -0.60196999
+
+-0.137875 -0.2701 0.43911999
+-0.116605 -0.52758999 0.38146999
+-0.096085 -0.45277 0.41069
+
+-0.21644501 -0.28254 0.45178001
+-0.21657499 -0.42470001 0.43263
+-0.156665 -0.36923 0.42314999
+
+-0.176625 -0.22690001 0.44397999
+-0.156665 -0.36923 0.42314999
+-0.137875 -0.2701 0.43911999
+
+-0.136565 -0.18389 0.45653999
+-0.137875 -0.2701 0.43911999
+-0.119785 -0.23910999 0.46998001
+
+-0.137875 -0.2701 0.43911999
+-0.136565 -0.18389 0.45653999
+-0.156565 -0.18361 0.45839001
+
+-0.137875 -0.2701 0.43911999
+-0.156565 -0.18361 0.45839001
+-0.176625 -0.22690001 0.44397999
+
+-0.16668501 -0.42550999 0.42176998
+-0.206465 -0.52480999 0.41360001
+-0.116605 -0.52758999 0.38146999
+
+-0.137875 -0.2701 0.43911999
+-0.096085 -0.45277 0.41069
+-0.029985 -0.49078999 0.50139999
+
+-0.192925 0.12158 0.28837999
+-0.236425 0.01018 0.38021999
+-0.096575 0.02365 0.37799999
+
+-0.106735 0.07859 0.32783001
+-0.192925 0.12158 0.28837999
+-0.096575 0.02365 0.37799999
+
+0.133395 -0.34088001 0.60337002
+0.223505 -0.23148001 0.58157001
+0.043465 -0.23129 0.58570999
+
+0.253855 -0.08411 0.48338001
+0.23345501 -0.11154 0.49640999
+0.26328501 -0.13812 0.51595001
+
+-0.166485 0.62580002 -0.00026
+-0.112215 0.62556 -0.07594
+-0.036455 0.74396004 -0.12342
+
+-0.16668501 -0.42550999 0.42176998
+-0.21657499 -0.42470001 0.43263
+-0.206465 -0.52480999 0.41360001
+
+0.52557499 -0.56825001 0.33627998
+0.47058498 -0.56601002 0.39771999
+0.465905 -0.63949001 0.35477001
+
+-0.156565 -0.18361 0.45839001
+-0.136565 -0.18389 0.45653999
+-0.146535 -0.15527 0.46143002
+
+-0.146535 -0.15527 0.46143002
+-0.136565 -0.18389 0.45653999
+-0.093355 -0.17006001 0.46999001
+
+-0.136605 -0.09948 0.44941002
+0.043555 0.01225 0.43209
+0.013225 0.0811 0.38118
+
+-0.236425 0.01018 0.38021999
+-0.216565 -0.08709 0.42601002
+-0.096575 0.02365 0.37799999
+
+0.069325 0.57973999 -0.17223
+0.060495 0.54880001 -0.17709
+0.068865 0.56655998 -0.20183001
+
+0.145115 -0.74193001 0.48983002
+0.268925 -0.75015999 0.45092999
+0.253395 -0.73496002 0.46985001
+
+-0.531875 0.43505001 -0.47442001
+-0.522085 0.42964001 -0.46967999
+-0.52310501 0.42203999 -0.45536999
+
+-0.50442501 0.51681 -0.12221
+-0.55648499 0.57926998 -0.21315001
+-0.53754501 0.46978001 -0.00341
+
+-0.74152496 0.38702 0.23667
+-0.74582497 0.34598999 0.25691
+-0.72876503 0.31882 0.31702
+
+-0.522085 0.42964001 -0.46967999
+-0.51220501 0.43668999 -0.48354
+-0.51262501 0.42702 -0.46618999
+
+-0.246605 -0.2133 0.44130001
+-0.206455 -0.16997 0.45382999
+-0.216565 -0.08709 0.42601002
+
+-0.51262501 0.42702 -0.46618999
+-0.51220501 0.43668999 -0.48354
+-0.49363499 0.44341 -0.49014
+
+-0.136605 -0.09948 0.44941002
+-0.093355 -0.17006001 0.46999001
+-0.080705 -0.14328 0.45655998
+
+0.163435 -0.53869999 0.56303001
+0.153405 -0.58124001 0.55702
+0.203395 -0.59640999 0.54062
+
+0.185485 0.15646 0.33446999
+0.119035 0.13868 0.35504002
+0.143465 0.09524 0.39535999
+
+0.32342499 -0.00259 0.41494999
+0.253855 -0.08411 0.48338001
+0.32317501 -0.0705 0.47466
+
+0.21620501 0.20631001 0.22993
+0.19949499 0.18938999 0.2817
+0.279865 0.18177999 0.28193001
+
+-0.080705 -0.14328 0.45655998
+-0.106555 -0.0996 0.45023998
+-0.136605 -0.09948 0.44941002
+
+-0.036705 -0.58948002 0.47154999
+-0.106135 -0.61624001 0.49498001
+-0.056445 -0.62691002 0.52630001
+
+-0.100065 -0.67837997 0.54858002
+-0.106135 -0.61624001 0.49498001
+-0.16275499 -0.66514 0.49737
+
+-0.056445 -0.62691002 0.52630001
+-0.044845 -0.65685997 0.5468
+0.023435 -0.61555 0.49417
+
+-0.40218498 -0.59438999 0.01163
+-0.41205502 -0.60668999 0.06219
+-0.40209499 -0.53867001 0.05158
+
+-0.119005 -0.73551003 0.54847
+-0.055935 -0.72981003 0.55643002
+-0.100065 -0.67837997 0.54858002
+
+-0.106135 -0.61624001 0.49498001
+-0.036705 -0.58948002 0.47154999
+-0.143465 -0.60214001 0.43403999
+
+0.30644501 0.19247999 0.06287
+0.368895 0.14748 0.00937
+0.32314499 0.16155001 -0.00588
+
+0.19949499 0.18938999 0.2817
+0.185485 0.15646 0.33446999
+0.279865 0.18177999 0.28193001
+
+0.21620501 0.20631001 0.22993
+0.279865 0.18177999 0.28193001
+0.31116501 0.18573 0.23601
+
+0.093385 -0.48191002 0.57638
+0.203465 -0.48157001 0.57987
+0.17356501 -0.39825001 0.58146
+
+-0.69313499 0.39777 0.31554001
+-0.65483498 0.44209999 0.23309999
+-0.72732498 0.41339001 0.20645
+
+0.279865 0.18177999 0.28193001
+0.362635 0.14925 0.26934
+0.31116501 0.18573 0.23601
+
+-0.029165 -0.1302 0.47558998
+-0.029335 -0.10314 0.45814999
+-0.106555 -0.0996 0.45023998
+
+-0.156585 -0.76415001 0.10611
+-0.152885 -0.76372002 0.12453
+-0.166565 -0.76378998 0.10376
+
+0.145115 -0.74193001 0.48983002
+0.253395 -0.73496002 0.46985001
+0.242435 -0.69941002 0.47040001
+
+0.093385 -0.48191002 0.57638
+0.133365 -0.51195999 0.55555
+0.203465 -0.48157001 0.57987
+
+0.63363499 -0.56191002 0.33492001
+0.68953499 -0.50616001 0.3109
+0.64346497 -0.49037998 0.32360001
+
+-0.118055 -0.56602001 0.3798
+-0.140305 -0.57868999 0.38641998
+-0.036705 -0.58948002 0.47154999
+
+-0.49872501 0.43931999 0.33116001
+-0.567505 0.44047001 0.32217999
+-0.56956501 0.37901001 0.42835999
+
+-0.49872501 0.43931999 0.33116001
+-0.40461498 0.42754002 0.32105999
+-0.45608501 0.45756001 0.24393999
+
+-0.574305 0.39730999 -0.30334999
+-0.54327499 0.39124001 -0.37567001
+-0.55800499 0.38182999 -0.29503
+
+0.066055 0.59167999 -0.23388
+0.068865 0.56655998 -0.20183001
+0.060495 0.54880001 -0.17709
+
+-0.20724501 -0.69445999 -0.26997999
+-0.166175 -0.74779999 -0.29483
+-0.20123501 -0.75469002 -0.29017
+
+0.013465 -0.32881001 0.57973
+-0.019855 -0.37563999 0.55806
+0.053215 -0.32796001 0.58986
+
+-0.042475 -0.24874001 0.57685001
+-0.042595 -0.29021999 0.57817001
+-0.006605 -0.27245001 0.59221001
+
+-0.47262501 0.31153 -0.0592
+-0.39040501 0.27885 -0.0233
+-0.43113499 0.13668 -0.06854
+
+-0.107915 -0.53838001 -0.23878
+-0.158205 -0.50859001 -0.11002
+-0.16091499 -0.46264999 -0.1489
+
+0.32317501 -0.0705 0.47466
+0.253855 -0.08411 0.48338001
+0.26328501 -0.13812 0.51595001
+
+-0.036455 0.74396004 -0.12342
+-0.020145 0.67031998 -0.15351
+0.036155 0.71919998 -0.22396
+
+0.242435 -0.69941002 0.47040001
+0.073435 -0.62984001 0.4934
+0.065805 -0.69416 0.51382
+
+0.253305 -0.66041 0.46727001
+0.19356501 -0.64248001 0.49592999
+0.153435 -0.64473 0.48566002
+
+-0.056445 -0.62691002 0.52630001
+0.023435 -0.61555 0.49417
+-0.016705 -0.60248001 0.48320999
+
+-0.212425 0.4907 -0.10495
+-0.40245499 0.42946999 0.00582
+-0.23320499 0.5352 -0.10464
+
+-0.029165 -0.1302 0.47558998
+0.035725 -0.09047 0.45244999
+-0.029335 -0.10314 0.45814999
+
+0.17338499 -0.16284 0.56652
+0.136995 -0.12943 0.54544998
+0.053405 -0.17601 0.57659
+
+0.52557499 -0.56825001 0.33627998
+0.55329498 -0.58823002 0.33521
+0.57196499 -0.49865002 0.31608
+
+0.203465 -0.48157001 0.57987
+0.133365 -0.51195999 0.55555
+0.163435 -0.53869999 0.56303001
+
+0.26304501 -0.48462002 0.55549999
+0.203465 -0.48157001 0.57987
+0.163435 -0.53869999 0.56303001
+
+0.279865 0.18177999 0.28193001
+0.29845501 0.12968 0.34632999
+0.362635 0.14925 0.26934
+
+-0.19886499 -0.37626999 -0.16464001
+-0.238365 -0.47976002 -0.11273
+-0.26883499 -0.37657001 -0.16448
+
+0.075455 0.60136002 -0.24311001
+0.080755 0.61445999 -0.2476
+0.075975 0.58987 -0.22885
+
+-0.52343498 0.42028999 -0.45174999
+-0.515135 0.41865002 -0.44709
+-0.52669498 0.41201 -0.43175999
+
+0.267075 0.20905001 0.1627
+0.38503502 0.15941 0.19188999
+0.30644501 0.19247999 0.06287
+
+0.035725 -0.09047 0.45244999
+0.093525 -0.02874 0.45459
+0.043555 0.01225 0.43209
+
+-0.77178497 0.08616 0.18837
+-0.77828499 0.14011 0.20802999
+-0.77015503 0.16722 0.17794001
+
+-0.019855 -0.37563999 0.55806
+0.053355 -0.41346001 0.56433998
+0.053215 -0.32796001 0.58986
+
+-0.006605 -0.27245001 0.59221001
+0.013465 -0.32881001 0.57973
+0.043465 -0.23129 0.58570999
+
+0.053405 -0.17601 0.57659
+-0.008315 -0.16797001 0.55435001
+-0.042475 -0.24874001 0.57685001
+
+0.035725 -0.09047 0.45244999
+-0.009275 -0.14155 0.52644001
+0.079635 -0.11564 0.52494999
+
+0.073435 -0.62984001 0.4934
+0.023435 -0.61555 0.49417
+-0.044845 -0.65685997 0.5468
+
+-0.019855 -0.37563999 0.55806
+-0.085865 -0.32016998 0.52319
+-0.029985 -0.49078999 0.50139999
+
+-0.075765 -0.16964001 0.4948
+-0.057925 -0.20864 0.54856998
+-0.008315 -0.16797001 0.55435001
+
+-0.51262501 0.42702 -0.46618999
+-0.49363499 0.44341 -0.49014
+-0.515135 0.41865002 -0.44709
+
+-0.136605 -0.09948 0.44941002
+-0.106555 -0.0996 0.45023998
+0.043555 0.01225 0.43209
+
+0.053525 -0.59877998 0.51932999
+0.023435 -0.61555 0.49417
+0.073435 -0.62984001 0.4934
+
+0.053355 -0.41346001 0.56433998
+-0.019855 -0.37563999 0.55806
+0.031045 -0.48976002 0.55334
+
+0.103425 -0.39764999 0.58700001
+0.053215 -0.32796001 0.58986
+0.053355 -0.41346001 0.56433998
+
+0.043465 -0.23129 0.58570999
+0.013465 -0.32881001 0.57973
+0.053215 -0.32796001 0.58986
+
+0.47058498 -0.56601002 0.39771999
+0.44266499 -0.61000999 0.39195
+0.465905 -0.63949001 0.35477001
+
+0.26532499 0.11682 0.36832001
+0.29845501 0.12968 0.34632999
+0.279865 0.18177999 0.28193001
+
+0.053525 -0.59877998 0.51932999
+0.073435 -0.62984001 0.4934
+0.153435 -0.64473 0.48566002
+
+-0.39039501 -0.65042 0.25218
+-0.354585 -0.59728001 0.33195
+-0.35820499 -0.59717999 0.29188
+
+0.68647499 -0.58339001 -0.0017
+0.701595 -0.51362999 -0.01377
+0.74039497 -0.56462002 0.06716
+
+0.77457497 -0.49212002 0.10691
+0.76139503 -0.53476002 0.19711
+0.74088501 -0.59263 0.15724
+
+0.043555 0.01225 0.43209
+0.093525 -0.02874 0.45459
+0.143455 0.01272 0.43963001
+
+0.013225 0.0811 0.38118
+-0.106735 0.07859 0.32783001
+-0.096575 0.02365 0.37799999
+
+-0.087935 0.12239 0.26698
+-0.106735 0.07859 0.32783001
+0.032965 0.15014 0.30976
+
+0.103345 -0.42644001 0.57532001
+0.093385 -0.48191002 0.57638
+0.17356501 -0.39825001 0.58146
+
+0.242435 -0.69941002 0.47040001
+0.153435 -0.64473 0.48566002
+0.073435 -0.62984001 0.4934
+
+0.103345 -0.42644001 0.57532001
+0.103425 -0.39764999 0.58700001
+0.053355 -0.41346001 0.56433998
+
+0.616395 -0.19808001 0.01714
+0.595695 -0.19973 -0.04273
+0.61706501 -0.15582 0.06717
+
+-0.029335 -0.10314 0.45814999
+0.043555 0.01225 0.43209
+-0.106555 -0.0996 0.45023998
+
+0.143455 0.01272 0.43963001
+0.143465 0.09524 0.39535999
+0.043555 0.01225 0.43209
+
+0.26532499 0.11682 0.36832001
+0.143465 0.09524 0.39535999
+0.203305 0.06761 0.41046001
+
+0.587925 -0.08729 0.02727
+0.57723499 -0.16372999 -0.05665
+0.53067501 -0.0586 -0.06884
+
+0.103425 -0.39764999 0.58700001
+0.153475 -0.35493 0.60167
+0.133395 -0.34088001 0.60337002
+
+0.153405 -0.58124001 0.55702
+0.093335 -0.54011002 0.55001999
+0.053525 -0.59877998 0.51932999
+
+0.223505 -0.23148001 0.58157001
+0.133395 -0.34088001 0.60337002
+0.153475 -0.35493 0.60167
+
+0.263435 -0.55469002 0.54113998
+0.307425 -0.55289001 0.51352001
+0.26304501 -0.48462002 0.55549999
+
+0.242435 -0.69941002 0.47040001
+0.065805 -0.69416 0.51382
+0.145115 -0.74193001 0.48983002
+
+0.036155 0.71919998 -0.22396
+-0.020145 0.67031998 -0.15351
+0.069325 0.57973999 -0.17223
+
+-0.18914499 -0.31829 -0.17997
+-0.178825 -0.39007 -0.16848
+-0.19886499 -0.37626999 -0.16464001
+
+0.70712502 -0.44008999 0.28386
+0.64346497 -0.49037998 0.32360001
+0.68953499 -0.50616001 0.3109
+
+-0.17994499 -0.75432999 0.36115002
+-0.21356501 -0.75926003 0.30533001
+-0.17445499 -0.76107002 0.26183001
+
+-0.009545 0.50974998 -0.05037
+-0.084295 0.46479 -0.01832
+0.004935 0.49839001 -0.08707
+
+0.263435 -0.55469002 0.54113998
+0.354795 -0.58098999 0.47644001
+0.307425 -0.55289001 0.51352001
+
+0.44975498 -0.50793999 -0.1924
+0.42197498 -0.58331001 -0.20099001
+0.391745 -0.56583 -0.23886999
+
+0.583465 -0.60224998 0.34046001
+0.59330502 -0.54569 0.33654999
+0.55329498 -0.58823002 0.33521
+
+0.59800499 -0.28384001 -0.03253
+0.62454498 -0.39271999 0.04435
+0.611035 -0.42883999 0.02128
+
+0.369995 -0.75161003 -0.02044
+0.38144501 -0.72870003 -0.01149
+0.37226501 -0.75335999 0.0004
+
+-0.50698502 0.14098 0.53110001
+-0.52195499 0.23915001 0.49179001
+-0.59655499 0.21528 0.54181
+
+0.154285 -0.09136 0.45977001
+0.23345501 -0.11154 0.49640999
+0.253855 -0.08411 0.48338001
+
+-0.48429501 0.08465 0.51129002
+-0.44178501 0.09654 0.43144001
+-0.429935 0.13929 0.43106998
+
+-0.52690498 0.36866001 0.4325
+-0.53012501 0.29573 0.48049
+-0.499935 0.33810001 0.43618999
+
+0.34578499 -0.27997 0.53634998
+0.33553501 -0.21408001 0.52173
+0.262635 -0.34882 0.57363998
+
+-0.199305 -0.2299 -0.22021999
+-0.153045 -0.23818001 -0.25016001
+-0.167955 -0.26533001 -0.23986
+
+0.016075 0.68472 -0.25462
+0.046245 0.64051003 -0.26128
+-0.048255 0.52195999 -0.13641
+
+0.17356501 -0.39825001 0.58146
+0.262635 -0.34882 0.57363998
+0.25977501 -0.2282 0.57007
+
+-0.51295502 0.12691 0.53984001
+-0.516045 0.07047 0.53485001
+-0.48429501 0.08465 0.51129002
+
+-0.53012501 0.29573 0.48049
+-0.60633499 0.29861 0.49606998
+-0.59655499 0.21528 0.54181
+
+-0.53012501 0.29573 0.48049
+-0.48616501 0.21021999 0.45523998
+-0.499935 0.33810001 0.43618999
+
+0.253305 -0.66041 0.46727001
+0.253395 -0.73496002 0.46985001
+0.329505 -0.71892998 0.45332001
+
+-0.51295502 0.12691 0.53984001
+-0.50698502 0.14098 0.53110001
+-0.59655499 0.21528 0.54181
+
+-0.51295502 0.12691 0.53984001
+-0.48429501 0.08465 0.51129002
+-0.50698502 0.14098 0.53110001
+
+-0.166485 0.62580002 -0.00026
+-0.236595 0.58076 0.04404
+-0.31738501 0.43448002 0.11911
+
+0.051805 0.5825 -0.15508
+-0.049325 0.62575001 -0.12564
+-0.22710501 0.49293999 0.03888
+
+-0.51295502 0.12691 0.53984001
+-0.54655499 0.08835 0.54924999
+-0.516045 0.07047 0.53485001
+
+-0.48616501 0.21021999 0.45523998
+-0.44947498 0.27966999 0.36776001
+-0.499935 0.33810001 0.43618999
+
+0.57196499 -0.49865002 0.31608
+0.57273499 -0.37573002 0.33617001
+0.51838501 -0.48213001 0.39742001
+
+0.72546501 -0.5941 0.22735001
+0.70681503 -0.56171001 0.28268
+0.68346497 -0.63983002 0.21789
+
+0.49573502 -0.1589 0.41981998
+0.486665 -0.19856001 0.44179001
+0.55290501 -0.18681999 0.36167999
+
+0.70884499 -0.36710999 0.13567
+0.64000504 -0.36174 0.16885
+0.64128502 -0.37016998 0.18415001
+
+0.49573502 -0.1589 0.41981998
+0.56959499 -0.12199 0.29812
+0.55259499 -0.04642 0.27702
+
+-0.54655499 0.08835 0.54924999
+-0.51295502 0.12691 0.53984001
+-0.59655499 0.21528 0.54181
+
+0.55290501 -0.18681999 0.36167999
+0.486665 -0.19856001 0.44179001
+0.54806499 -0.22674 0.37215
+
+0.61429501 -0.26823 0.25707001
+0.56959499 -0.12199 0.29812
+0.54806499 -0.22674 0.37215
+
+-0.48616501 0.21021999 0.45523998
+-0.52195499 0.23915001 0.49179001
+-0.50698502 0.14098 0.53110001
+
+-0.53012501 0.29573 0.48049
+-0.52195499 0.23915001 0.49179001
+-0.48616501 0.21021999 0.45523998
+
+0.53676498 -0.34728001 0.38973
+0.427565 -0.38834 0.46021
+0.51838501 -0.48213001 0.39742001
+
+0.42587502 -0.0541 0.4068
+0.43314499 -0.00056 0.38240002
+0.32342499 -0.00259 0.41494999
+
+0.54806499 -0.22674 0.37215
+0.50891499 -0.266 0.42063
+0.58010502 -0.29504 0.32986
+
+-0.44178501 0.09654 0.43144001
+-0.48429501 0.08465 0.51129002
+-0.44835499 0.03677 0.38549
+
+0.069325 0.57973999 -0.17223
+0.046465 0.53513 -0.12086
+0.060495 0.54880001 -0.17709
+
+-0.48429501 0.08465 0.51129002
+-0.429935 0.13929 0.43106998
+-0.50698502 0.14098 0.53110001
+
+0.486665 -0.19856001 0.44179001
+0.49573502 -0.1589 0.41981998
+0.40009499 -0.18596001 0.49257999
+
+-0.43137501 0.38099998 0.37743
+-0.45004501 0.41863998 0.36409
+-0.52690498 0.36866001 0.4325
+
+-0.41858501 0.32521999 -0.01536
+-0.401735 0.37047001 -0.00194
+-0.352155 0.32740002 0.01621
+
+-0.329715 0.31518 0.05937
+-0.363535 0.29777 0.01081
+-0.34072498 0.34067001 0.0194
+
+-0.089315 -0.30382 -0.35894001
+-0.049465 -0.37333 -0.3702
+-0.099045 -0.37569 -0.34127998
+
+0.42301498 -0.09387 0.43786999
+0.32317501 -0.0705 0.47466
+0.37626499 -0.10669 0.47582001
+
+0.47968498 -0.06731 0.37938999
+0.42301498 -0.09387 0.43786999
+0.49573502 -0.1589 0.41981998
+
+-0.406535 0.02358 0.37558998
+-0.44835499 0.03677 0.38549
+-0.49119499 0.00697 0.39306
+
+-0.49119499 0.00697 0.39306
+-0.44835499 0.03677 0.38549
+-0.527495 0.03341 0.50833
+
+-0.429935 0.13929 0.43106998
+-0.48616501 0.21021999 0.45523998
+-0.50698502 0.14098 0.53110001
+
+0.335285 -0.62630001 0.44756001
+0.367225 -0.65199997 0.44060001
+0.44266499 -0.61000999 0.39195
+
+-0.44178501 0.09654 0.43144001
+-0.42501499 0.0966 0.42016998
+-0.429935 0.13929 0.43106998
+
+-0.44947498 0.27966999 0.36776001
+-0.39515499 0.30839001 0.32299999
+-0.44827499 0.33785 0.38784
+
+-0.49363499 0.44341 -0.49014
+-0.47018501 0.48946999 -0.51748001
+-0.44885502 0.48257999 -0.32057999
+
+-0.43594501 0.20952999 0.40491001
+-0.48616501 0.21021999 0.45523998
+-0.429935 0.13929 0.43106998
+
+-0.229725 -0.20162001 -0.21724001
+-0.32967499 -0.20312 -0.20150999
+-0.310175 -0.08771 -0.20037001
+
+0.44266499 -0.61000999 0.39195
+0.43657501 -0.53799 0.43675999
+0.335285 -0.62630001 0.44756001
+
+0.47968498 -0.06731 0.37938999
+0.43314499 -0.00056 0.38240002
+0.42587502 -0.0541 0.4068
+
+-0.57997501 0.39771 -0.2633
+-0.51723499 0.35522999 -0.21364
+-0.54886501 0.33823002 -0.12392
+
+-0.48429501 0.08465 0.51129002
+-0.527495 0.03341 0.50833
+-0.44835499 0.03677 0.38549
+
+-0.43594501 0.20952999 0.40491001
+-0.429935 0.13929 0.43106998
+-0.38712502 0.13965 0.40511002
+
+-0.614795 0.37119999 -0.013
+-0.58929501 0.35665001 -0.05348
+-0.57147499 0.29725 -0.05187
+
+-0.35580502 0.52299 0.06101
+-0.30827499 0.55255001 0.0553
+-0.247845 0.62541 -0.03466
+
+0.558475 -0.70769997 0.03611
+0.59227501 -0.64189003 -0.02401
+0.63273499 -0.64609001 0.00875
+
+0.38605499 -0.52320999 0.48705002
+0.51838501 -0.48213001 0.39742001
+0.427565 -0.38834 0.46021
+
+-0.35817501 0.08173 0.3584
+-0.42501499 0.0966 0.42016998
+-0.40279499 0.05291 0.38118999
+
+-0.43594501 0.20952999 0.40491001
+-0.44947498 0.27966999 0.36776001
+-0.48616501 0.21021999 0.45523998
+
+-0.38712502 0.13965 0.40511002
+-0.336045 0.18141001 0.33853001
+-0.39515499 0.30839001 0.32299999
+
+-0.44947498 0.27966999 0.36776001
+-0.44827499 0.33785 0.38784
+-0.499935 0.33810001 0.43618999
+
+0.70681503 -0.56171001 0.28268
+0.63936501 -0.64530998 0.26995001
+0.68346497 -0.63983002 0.21789
+
+-0.036705 -0.58948002 0.47154999
+-0.056445 -0.62691002 0.52630001
+-0.016705 -0.60248001 0.48320999
+
+-0.28335501 0.37535999 0.07935
+-0.32425499 0.33021 0.07945
+-0.259715 0.37625999 0.05013
+
+-0.37914501 -0.74181999 0.48116001
+-0.363685 -0.71358002 0.48608002
+-0.40310501 -0.70723999 0.48404999
+
+-0.25884501 -0.74322998 -0.26056
+-0.20724501 -0.69445999 -0.26997999
+-0.20123501 -0.75469002 -0.29017
+
+0.41008499 -0.30582001 0.50618
+0.38686501 -0.42890999 0.48895
+0.427565 -0.38834 0.46021
+
+0.308475 -0.66796997 0.46055
+0.367225 -0.65199997 0.44060001
+0.335285 -0.62630001 0.44756001
+
+-0.45004501 0.41863998 0.36409
+-0.56956501 0.37901001 0.42835999
+-0.52690498 0.36866001 0.4325
+
+-0.272745 -0.45799 0.41743
+-0.21657499 -0.42470001 0.43263
+-0.306675 -0.36883999 0.43159
+
+0.42587502 -0.0541 0.4068
+0.42301498 -0.09387 0.43786999
+0.47968498 -0.06731 0.37938999
+
+-0.38591499 0.35167 0.31952
+-0.43137501 0.38099998 0.37743
+-0.44827499 0.33785 0.38784
+
+0.55259499 -0.04642 0.27702
+0.47858501 0.02572 0.32499001
+0.47968498 -0.06731 0.37938999
+
+-0.44219501 0.62398998 -0.59071999
+-0.455145 0.56103001 -0.45051998
+-0.44630501 0.55679001 -0.57491001
+
+-0.67350502 -0.31801001 0.21348
+-0.71858498 -0.18570999 0.23955999
+-0.72665497 -0.19900999 0.19982
+
+-0.44835499 0.03677 0.38549
+-0.406535 0.02358 0.37558998
+-0.40279499 0.05291 0.38118999
+
+-0.40461498 0.42754002 0.32105999
+-0.36774502 0.40701 0.25933001
+-0.38813499 0.43208 0.28315001
+
+-0.71858498 -0.18570999 0.23955999
+-0.69847504 -0.16400999 0.28132
+-0.71903503 -0.1047 0.21924999
+
+-0.39515499 0.30839001 0.32299999
+-0.44947498 0.27966999 0.36776001
+-0.43594501 0.20952999 0.40491001
+
+-0.429935 0.13929 0.43106998
+-0.42501499 0.0966 0.42016998
+-0.38712502 0.13965 0.40511002
+
+-0.34358501 0.26857 0.25934
+-0.35530499 0.32993999 0.20927
+-0.38591499 0.35167 0.31952
+
+-0.39515499 0.30839001 0.32299999
+-0.34358501 0.26857 0.25934
+-0.38591499 0.35167 0.31952
+
+-0.216555 -0.65108002 0.42185001
+-0.363685 -0.71358002 0.48608002
+-0.232635 -0.74156998 0.44324001
+
+0.72546501 -0.5941 0.22735001
+0.76139503 -0.53476002 0.19711
+0.76070503 -0.52106998 0.2173
+
+-0.42501499 0.0966 0.42016998
+-0.44835499 0.03677 0.38549
+-0.40279499 0.05291 0.38118999
+
+-0.38591499 0.35167 0.31952
+-0.44827499 0.33785 0.38784
+-0.39515499 0.30839001 0.32299999
+
+0.49892502 -0.66067001 0.30966
+0.52557499 -0.56825001 0.33627998
+0.465905 -0.63949001 0.35477001
+
+0.336675 -0.44263 0.52173
+0.38686501 -0.42890999 0.48895
+0.358755 -0.33319 0.53729
+
+-0.35817501 0.08173 0.3584
+-0.38712502 0.13965 0.40511002
+-0.42501499 0.0966 0.42016998
+
+0.47058498 -0.56601002 0.39771999
+0.38605499 -0.52320999 0.48705002
+0.43657501 -0.53799 0.43675999
+
+0.33553501 -0.21408001 0.52173
+0.25977501 -0.2282 0.57007
+0.262635 -0.34882 0.57363998
+
+0.61429501 -0.26823 0.25707001
+0.64128502 -0.37016998 0.18415001
+0.64000504 -0.36174 0.16885
+
+-0.020145 0.67031998 -0.15351
+-0.112215 0.62556 -0.07594
+-0.049325 0.62575001 -0.12564
+
+-0.308445 0.09557 0.30705999
+-0.336045 0.18141001 0.33853001
+-0.38712502 0.13965 0.40511002
+
+-0.35817501 0.08173 0.3584
+-0.308445 0.09557 0.30705999
+-0.38712502 0.13965 0.40511002
+
+0.327005 -0.16132 0.50963001
+0.276535 -0.21360001 0.55987
+0.33553501 -0.21408001 0.52173
+
+0.327005 -0.16132 0.50963001
+0.27328501 -0.16485001 0.53637001
+0.276535 -0.21360001 0.55987
+
+0.307425 -0.55289001 0.51352001
+0.354795 -0.58098999 0.47644001
+0.38605499 -0.52320999 0.48705002
+
+0.336675 -0.44263 0.52173
+0.307425 -0.55289001 0.51352001
+0.38605499 -0.52320999 0.48705002
+
+-0.406535 0.02358 0.37558998
+-0.343685 0.08148 0.34409
+-0.35817501 0.08173 0.3584
+
+-0.28057501 0.13838 0.25653999
+-0.27186501 0.17989 0.1998
+-0.318915 0.22754999 0.2701
+
+-0.38712502 0.13965 0.40511002
+-0.39515499 0.30839001 0.32299999
+-0.43594501 0.20952999 0.40491001
+
+-0.112215 0.62556 -0.07594
+-0.020145 0.67031998 -0.15351
+-0.036455 0.74396004 -0.12342
+
+-0.559795 0.4541 0.06169
+-0.53754501 0.46978001 -0.00341
+-0.579935 0.46213001 -0.01038
+
+0.327005 -0.16132 0.50963001
+0.32317501 -0.0705 0.47466
+0.26328501 -0.13812 0.51595001
+
+0.473535 -0.68335999 0.30688
+0.49892502 -0.66067001 0.30966
+0.43405499 -0.71273003 0.30693001
+
+-0.343685 0.08148 0.34409
+-0.33633499 0.03778 0.36269001
+-0.308445 0.09557 0.30705999
+
+-0.33633499 0.03778 0.36269001
+-0.336605 -0.00365 0.39479
+-0.236425 0.01018 0.38021999
+
+0.67806503 -0.65469002 0.13749
+0.74088501 -0.59263 0.15724
+0.68346497 -0.63983002 0.21789
+
+0.263435 -0.55469002 0.54113998
+0.24317499 -0.62743 0.50932999
+0.354795 -0.58098999 0.47644001
+
+-0.386665 -0.56747002 0.10225
+-0.38455502 -0.62816002 0.13858
+-0.334715 -0.61401001 0.18212
+
+-0.406535 0.02358 0.37558998
+-0.35817501 0.08173 0.3584
+-0.40279499 0.05291 0.38118999
+
+0.486665 -0.19856001 0.44179001
+0.40009499 -0.18596001 0.49257999
+0.50891499 -0.266 0.42063
+
+0.41008499 -0.30582001 0.50618
+0.358755 -0.33319 0.53729
+0.38686501 -0.42890999 0.48895
+
+0.24317499 -0.62743 0.50932999
+0.253305 -0.66041 0.46727001
+0.335285 -0.62630001 0.44756001
+
+0.066055 0.59167999 -0.23388
+0.060495 0.54880001 -0.17709
+-0.027095 0.51598 -0.13203
+
+-0.44141499 0.60801998 -0.58164001
+-0.44219501 0.62398998 -0.59071999
+-0.44630501 0.55679001 -0.57491001
+
+-0.35817501 0.08173 0.3584
+-0.343685 0.08148 0.34409
+-0.308445 0.09557 0.30705999
+
+0.470495 0.07129 0.2808
+0.47858501 0.02572 0.32499001
+0.55259499 -0.04642 0.27702
+
+0.40009499 -0.18596001 0.49257999
+0.352155 -0.22743 0.51053001
+0.34578499 -0.27997 0.53634998
+
+-0.049325 0.62575001 -0.12564
+0.051805 0.5825 -0.15508
+0.069325 0.57973999 -0.17223
+
+-0.055935 -0.72981003 0.55643002
+-0.044845 -0.65685997 0.5468
+-0.100065 -0.67837997 0.54858002
+
+-0.47512501 0.32431999 -0.07113
+-0.47262501 0.31153 -0.0592
+-0.49023499 0.31427999 -0.06865
+
+-0.52343498 0.42028999 -0.45174999
+-0.53415501 0.42109001 -0.44837002
+-0.52310501 0.42203999 -0.45536999
+
+0.004935 0.49839001 -0.08707
+-0.34072498 0.34067001 0.0194
+-0.027095 0.51598 -0.13203
+
+0.53676498 -0.34728001 0.38973
+0.50891499 -0.266 0.42063
+0.41008499 -0.30582001 0.50618
+
+-0.468335 0.32449001 -0.06341
+-0.47512501 0.32431999 -0.07113
+-0.45510502 0.35847 -0.05053
+
+0.17356501 -0.39825001 0.58146
+0.223505 -0.23148001 0.58157001
+0.153475 -0.35493 0.60167
+
+-0.096095 0.71514 -0.06997
+-0.075495 0.73363998 -0.09516
+-0.247845 0.62541 -0.03466
+
+-0.29133499 0.43453999 0.10392
+-0.165655 0.49323002 0.03954
+-0.22710501 0.49293999 0.03888
+
+-0.55654499 0.64793999 -0.39986
+-0.478615 0.61969002 -0.45830002
+-0.543125 0.70637001 -0.51022999
+
+0.276035 -0.42984001 0.55702
+0.203465 -0.48157001 0.57987
+0.26304501 -0.48462002 0.55549999
+
+0.336675 -0.44263 0.52173
+0.276035 -0.42984001 0.55702
+0.307425 -0.55289001 0.51352001
+
+0.56959499 -0.12199 0.29812
+0.49573502 -0.1589 0.41981998
+0.55290501 -0.18681999 0.36167999
+
+-0.39515499 0.30839001 0.32299999
+-0.318915 0.22754999 0.2701
+-0.34358501 0.26857 0.25934
+
+0.253305 -0.66041 0.46727001
+0.308475 -0.66796997 0.46055
+0.335285 -0.62630001 0.44756001
+
+0.76550499 -0.45125 0.21715
+0.74180496 -0.46634998 0.26339001
+0.76070503 -0.52106998 0.2173
+
+-0.096095 0.71514 -0.06997
+-0.247845 0.62541 -0.03466
+-0.30827499 0.55255001 0.0553
+
+0.276035 -0.42984001 0.55702
+0.17356501 -0.39825001 0.58146
+0.203465 -0.48157001 0.57987
+
+-0.137245 -0.71829002 0.35676998
+-0.141445 -0.71961998 0.33926998
+-0.126875 -0.71792 0.35866001
+
+0.253305 -0.66041 0.46727001
+0.329505 -0.71892998 0.45332001
+0.308475 -0.66796997 0.46055
+
+0.32317501 -0.0705 0.47466
+0.42587502 -0.0541 0.4068
+0.32342499 -0.00259 0.41494999
+
+0.38605499 -0.52320999 0.48705002
+0.354795 -0.58098999 0.47644001
+0.43657501 -0.53799 0.43675999
+
+-0.166485 0.62580002 -0.00026
+-0.036455 0.74396004 -0.12342
+-0.096095 0.71514 -0.06997
+
+-0.502845 -0.67873001 0.11659
+-0.54426498 -0.71963997 0.10263
+-0.45942501 -0.75005997 0.21047001
+
+-0.166485 0.62580002 -0.00026
+-0.31738501 0.43448002 0.11911
+-0.112215 0.62556 -0.07594
+
+0.61429501 -0.26823 0.25707001
+0.58010502 -0.29504 0.32986
+0.60397499 -0.40557999 0.27521
+
+0.465905 -0.63949001 0.35477001
+0.44266499 -0.61000999 0.39195
+0.390485 -0.69848 0.41848
+
+0.19356501 -0.64248001 0.49592999
+0.253305 -0.66041 0.46727001
+0.24317499 -0.62743 0.50932999
+
+0.427565 -0.38834 0.46021
+0.53676498 -0.34728001 0.38973
+0.41008499 -0.30582001 0.50618
+
+-0.044845 -0.65685997 0.5468
+-0.055935 -0.72981003 0.55643002
+-0.043565 -0.73834 0.55035999
+
+-0.081355 0.49502998 0.00394
+-0.084295 0.46479 -0.01832
+-0.009545 0.50974998 -0.05037
+
+-0.39040501 0.27885 -0.0233
+-0.41858501 0.32521999 -0.01536
+-0.352155 0.32740002 0.01621
+
+0.544925 -0.67612 0.29681999
+0.57144501 -0.70275002 0.21681
+0.63936501 -0.64530998 0.26995001
+
+0.49573502 -0.1589 0.41981998
+0.42301498 -0.09387 0.43786999
+0.40009499 -0.18596001 0.49257999
+
+-0.29133499 0.43453999 0.10392
+-0.31738501 0.43448002 0.11911
+-0.34077499 0.36119999 0.14935
+
+0.558475 -0.70769997 0.03611
+0.63273499 -0.64609001 0.00875
+0.67858498 -0.64014999 0.05778
+
+0.55259499 -0.04642 0.27702
+0.58518501 -0.07291 0.16698
+0.54476501 -0.0057 0.22294001
+
+0.70712502 -0.44008999 0.28386
+0.74180496 -0.46634998 0.26339001
+0.74194504 -0.41438999 0.23629999
+
+-0.165655 0.49323002 0.03954
+0.051805 0.5825 -0.15508
+-0.22710501 0.49293999 0.03888
+
+-0.34072498 0.34067001 0.0194
+-0.212425 0.4907 -0.10495
+-0.027095 0.51598 -0.13203
+
+-0.069995 -0.13285 -0.23166
+-0.229725 -0.20162001 -0.21724001
+-0.160285 -0.07244 -0.20541
+
+0.63363499 -0.56191002 0.33492001
+0.583465 -0.60224998 0.34046001
+0.62594501 -0.60432999 0.32353001
+
+0.58010502 -0.29504 0.32986
+0.61429501 -0.26823 0.25707001
+0.54806499 -0.22674 0.37215
+
+0.37462502 0.09203 0.35064999
+0.29845501 0.12968 0.34632999
+0.26532499 0.11682 0.36832001
+
+0.58010502 -0.29504 0.32986
+0.53676498 -0.34728001 0.38973
+0.57273499 -0.37573002 0.33617001
+
+0.47058498 -0.56601002 0.39771999
+0.51838501 -0.48213001 0.39742001
+0.38605499 -0.52320999 0.48705002
+
+-0.044845 -0.65685997 0.5468
+-0.056445 -0.62691002 0.52630001
+-0.100065 -0.67837997 0.54858002
+
+-0.216555 -0.65108002 0.42185001
+-0.232635 -0.74156998 0.44324001
+-0.222955 -0.69486 0.43347
+
+-0.547775 -0.01096 0.39499001
+-0.57050499 -0.03053 0.38844002
+-0.49119499 0.00697 0.39306
+
+0.63363499 -0.56191002 0.33492001
+0.70681503 -0.56171001 0.28268
+0.68953499 -0.50616001 0.3109
+
+-0.019895 -0.21881001 -0.36255001
+-0.000905 -0.16063999 -0.32273998
+0.061575 -0.19306999 -0.34928001
+
+0.073585 0.64028999 -0.27017
+0.075455 0.60136002 -0.24311001
+0.046245 0.64051003 -0.26128
+
+0.42301498 -0.09387 0.43786999
+0.37626499 -0.10669 0.47582001
+0.40009499 -0.18596001 0.49257999
+
+0.47858501 0.02572 0.32499001
+0.43314499 -0.00056 0.38240002
+0.47968498 -0.06731 0.37938999
+
+-0.36774502 0.40701 0.25933001
+-0.36813499 0.44145 0.14507
+-0.38813499 0.43208 0.28315001
+
+0.60397499 -0.40557999 0.27521
+0.57273499 -0.37573002 0.33617001
+0.59136501 -0.44555 0.29172001
+
+0.59330502 -0.54569 0.33654999
+0.63363499 -0.56191002 0.33492001
+0.64346497 -0.49037998 0.32360001
+
+0.263435 -0.55469002 0.54113998
+0.203395 -0.59640999 0.54062
+0.24317499 -0.62743 0.50932999
+
+-0.31738501 0.43448002 0.11911
+-0.34386501 0.40557999 0.15052
+-0.34077499 0.36119999 0.14935
+
+-0.17994499 -0.75432999 0.36115002
+-0.17445499 -0.76107002 0.26183001
+-0.129625 -0.75866997 0.17889999
+
+0.17356501 -0.39825001 0.58146
+0.25977501 -0.2282 0.57007
+0.223505 -0.23148001 0.58157001
+
+0.38686501 -0.42890999 0.48895
+0.38605499 -0.52320999 0.48705002
+0.427565 -0.38834 0.46021
+
+0.253305 -0.66041 0.46727001
+0.242435 -0.69941002 0.47040001
+0.253395 -0.73496002 0.46985001
+
+0.24317499 -0.62743 0.50932999
+0.335285 -0.62630001 0.44756001
+0.354795 -0.58098999 0.47644001
+
+0.40009499 -0.18596001 0.49257999
+0.41008499 -0.30582001 0.50618
+0.50891499 -0.266 0.42063
+
+0.163435 -0.53869999 0.56303001
+0.203395 -0.59640999 0.54062
+0.263435 -0.55469002 0.54113998
+
+0.47058498 -0.56601002 0.39771999
+0.52557499 -0.56825001 0.33627998
+0.51838501 -0.48213001 0.39742001
+
+0.64000504 -0.36174 0.16885
+0.63150501 -0.32306999 0.09721
+0.61706501 -0.15582 0.06717
+
+-0.18282499 0.59498001 -0.13044
+-0.126565 0.67811996 -0.13629
+-0.083505 0.68447998 -0.17287001
+
+0.358755 -0.33319 0.53729
+0.41008499 -0.30582001 0.50618
+0.34578499 -0.27997 0.53634998
+
+0.63273499 -0.64609001 0.00875
+0.68647499 -0.58339001 -0.0017
+0.67858498 -0.64014999 0.05778
+
+0.32317501 -0.0705 0.47466
+0.327005 -0.16132 0.50963001
+0.352155 -0.22743 0.51053001
+
+0.55329498 -0.58823002 0.33521
+0.59330502 -0.54569 0.33654999
+0.57196499 -0.49865002 0.31608
+
+0.51838501 -0.48213001 0.39742001
+0.52557499 -0.56825001 0.33627998
+0.57196499 -0.49865002 0.31608
+
+-0.31738501 0.43448002 0.11911
+-0.354445 0.43800999 0.1358
+-0.34386501 0.40557999 0.15052
+
+-0.29133499 0.43453999 0.10392
+-0.34077499 0.36119999 0.14935
+-0.28335501 0.37535999 0.07935
+
+0.262635 -0.34882 0.57363998
+0.336675 -0.44263 0.52173
+0.358755 -0.33319 0.53729
+
+0.23304501 0.00794 0.42648998
+0.203305 0.06761 0.41046001
+0.143455 0.01272 0.43963001
+
+-0.078115 -0.62351002 -0.25240999
+0.002175 -0.65117996 -0.26294001
+-0.152975 -0.66613998 -0.27448999
+
+0.50891499 -0.266 0.42063
+0.54806499 -0.22674 0.37215
+0.486665 -0.19856001 0.44179001
+
+0.34578499 -0.27997 0.53634998
+0.352155 -0.22743 0.51053001
+0.33553501 -0.21408001 0.52173
+
+0.25977501 -0.2282 0.57007
+0.33553501 -0.21408001 0.52173
+0.276535 -0.21360001 0.55987
+
+0.57273499 -0.37573002 0.33617001
+0.53676498 -0.34728001 0.38973
+0.51838501 -0.48213001 0.39742001
+
+-0.44495499 0.61160999 -0.60196999
+-0.440755 0.59640999 -0.59333
+-0.46016499 0.52960999 -0.57521999
+
+-0.334715 -0.61401001 0.18212
+-0.35919498 -0.65380997 0.20221001
+-0.35820499 -0.59717999 0.29188
+
+-0.36254501 -0.75091003 -0.10707
+-0.420145 -0.75016998 -0.08755
+-0.47012501 -0.68793999 -0.04621
+
+0.002175 -0.65117996 -0.26294001
+-0.166175 -0.74779999 -0.29483
+-0.152975 -0.66613998 -0.27448999
+
+-0.20724501 -0.69445999 -0.26997999
+-0.152975 -0.66613998 -0.27448999
+-0.166175 -0.74779999 -0.29483
+
+0.62594501 -0.60432999 0.32353001
+0.57481499 -0.63938 0.32445999
+0.63936501 -0.64530998 0.26995001
+
+0.276035 -0.42984001 0.55702
+0.26304501 -0.48462002 0.55549999
+0.307425 -0.55289001 0.51352001
+
+0.62594501 -0.60432999 0.32353001
+0.583465 -0.60224998 0.34046001
+0.57481499 -0.63938 0.32445999
+
+0.329505 -0.71892998 0.45332001
+0.390485 -0.69848 0.41848
+0.367225 -0.65199997 0.44060001
+
+-0.550975 0.20959 -0.06745
+-0.57065498 0.15109 -0.06724
+-0.60123501 0.19448 -0.05578
+
+0.595695 -0.19973 -0.04273
+0.616395 -0.19808001 0.01714
+0.59800499 -0.28384001 -0.03253
+
+0.43657501 -0.53799 0.43675999
+0.354795 -0.58098999 0.47644001
+0.335285 -0.62630001 0.44756001
+
+0.67858498 -0.64014999 0.05778
+0.67806503 -0.65469002 0.13749
+0.59101501 -0.70407997 0.1113
+
+-0.44606499 -0.76600998 -0.07796
+-0.420145 -0.75016998 -0.08755
+-0.43560501 -0.76556 -0.07625
+
+0.262635 -0.34882 0.57363998
+0.358755 -0.33319 0.53729
+0.34578499 -0.27997 0.53634998
+
+0.50891499 -0.266 0.42063
+0.53676498 -0.34728001 0.38973
+0.58010502 -0.29504 0.32986
+
+-0.165655 0.49323002 0.03954
+-0.009545 0.50974998 -0.05037
+0.051805 0.5825 -0.15508
+
+-0.44842499 -0.42519001 -0.09399
+-0.40871498 -0.39304001 -0.14109
+-0.388325 -0.45629002 -0.06645
+
+-0.049325 0.62575001 -0.12564
+0.069325 0.57973999 -0.17223
+-0.020145 0.67031998 -0.15351
+
+-0.192925 0.12158 0.28837999
+-0.208305 0.15802 0.22305
+-0.28057501 0.13838 0.25653999
+
+-0.34077499 0.36119999 0.14935
+-0.32425499 0.33021 0.07945
+-0.28335501 0.37535999 0.07935
+
+-0.081355 0.49502998 0.00394
+-0.165655 0.49323002 0.03954
+-0.29133499 0.43453999 0.10392
+
+0.465905 -0.63949001 0.35477001
+0.390485 -0.69848 0.41848
+0.43405499 -0.71273003 0.30693001
+
+0.49573502 -0.1589 0.41981998
+0.55259499 -0.04642 0.27702
+0.47968498 -0.06731 0.37938999
+
+-0.31738501 0.43448002 0.11911
+-0.29133499 0.43453999 0.10392
+-0.22710501 0.49293999 0.03888
+
+0.43314499 -0.00056 0.38240002
+0.37462502 0.09203 0.35064999
+0.32342499 -0.00259 0.41494999
+
+-0.075495 0.73363998 -0.09516
+-0.096095 0.71514 -0.06997
+-0.036455 0.74396004 -0.12342
+
+0.44266499 -0.61000999 0.39195
+0.47058498 -0.56601002 0.39771999
+0.43657501 -0.53799 0.43675999
+
+0.38686501 -0.42890999 0.48895
+0.336675 -0.44263 0.52173
+0.38605499 -0.52320999 0.48705002
+
+0.57144501 -0.70275002 0.21681
+0.63408501 -0.68242996 0.15461
+0.68346497 -0.63983002 0.21789
+
+0.093335 -0.54011002 0.55001999
+0.093385 -0.48191002 0.57638
+0.031045 -0.48976002 0.55334
+
+-0.34806499 -0.62027 0.40410999
+-0.39304501 -0.61914001 0.39880001
+-0.406185 -0.64178001 0.44240002
+
+-0.59962502 0.11646 0.54145
+-0.54655499 0.08835 0.54924999
+-0.59655499 0.21528 0.54181
+
+0.077465 0.65564003 -0.25237
+0.036155 0.71919998 -0.22396
+0.069325 0.57973999 -0.17223
+
+-0.522085 0.42964001 -0.46967999
+-0.51262501 0.42702 -0.46618999
+-0.52343498 0.42028999 -0.45174999
+
+0.40009499 -0.18596001 0.49257999
+0.34578499 -0.27997 0.53634998
+0.41008499 -0.30582001 0.50618
+
+0.276035 -0.42984001 0.55702
+0.262635 -0.34882 0.57363998
+0.17356501 -0.39825001 0.58146
+
+-0.71519501 -0.22723 0.07012
+-0.72489502 -0.13198 0.11954
+-0.68935501 -0.17514999 0.00979
+
+-0.141445 -0.71961998 0.33926998
+-0.097395 -0.72411003 0.17242001
+0.034255 -0.70801003 0.40098999
+
+-0.47262501 0.31153 -0.0592
+-0.52155499 0.29777 -0.06353
+-0.49023499 0.31427999 -0.06865
+
+-0.455145 0.56103001 -0.45051998
+-0.44795502 0.48275002 -0.23052
+-0.44885502 0.48257999 -0.32057999
+
+-0.58654499 0.0687 0.53747002
+-0.627995 0.04726 0.49209
+-0.60431499 0.04708 0.51540001
+
+-0.74453499 0.0457 0.23389999
+-0.77178497 0.08616 0.18837
+-0.75351501 0.04522 0.14867
+
+-0.76138496 0.14034 0.29812
+-0.773265 0.14032 0.25822001
+-0.76094498 0.07262 0.24841
+
+-0.76094498 0.07262 0.24841
+-0.773265 0.14032 0.25822001
+-0.77178497 0.08616 0.18837
+
+-0.70774498 0.00346 0.16879
+-0.69119499 -0.03813 0.21893999
+-0.67764503 0.00206 0.26896999
+
+-0.238545 -0.76138 0.28424
+-0.17994499 -0.75432999 0.36115002
+-0.257085 -0.75538002 0.41583
+
+-0.46994499 -0.66989998 0.39380001
+-0.47614498 -0.66900002 0.34229
+-0.49865501 -0.72585999 0.36729
+
+0.247805 -0.73291 -0.06195
+0.222605 -0.71620003 -0.04485
+0.231395 -0.71984001 -0.09604
+
+-0.67350502 -0.31801001 0.21348
+-0.72665497 -0.19900999 0.19982
+-0.70689499 -0.24051001 0.17004999
+
+-0.233095 -0.62811001 -0.12729
+-0.24751499 -0.60999001 -0.0966
+-0.16779499 -0.59556999 -0.09223
+
+-0.71903503 -0.1047 0.21924999
+-0.69850502 -0.02457 0.14891
+-0.72112503 -0.09155 0.13937
+
+-0.71519501 -0.22723 0.07012
+-0.69344498 -0.26929001 0.08014
+-0.70689499 -0.24051001 0.17004999
+
+0.44724499 -0.56456001 -0.18232
+0.50467499 -0.54449001 -0.10164
+0.45115501 -0.60699001 -0.15207
+
+-0.77015503 0.16722 0.17794001
+-0.722985 0.29028 0.13737
+-0.73406502 0.22117001 0.0777
+
+0.108785 -0.70753998 0.38001999
+0.071735 -0.70736 0.39019001
+0.034255 -0.70801003 0.40098999
+
+-0.212425 0.4907 -0.10495
+-0.073375 0.61046001 -0.18223
+-0.048255 0.52195999 -0.13641
+
+0.54445499 -0.48500999 -0.09213
+0.44975498 -0.50793999 -0.1924
+0.554575 -0.42790001 -0.10218
+
+-0.45953499 0.45066002 -0.34074001
+-0.45510502 0.35847 -0.05053
+-0.47512501 0.32431999 -0.07113
+
+-0.75427498 0.12566 0.09816
+-0.77015503 0.16722 0.17794001
+-0.73406502 0.22117001 0.0777
+
+0.72791496 -0.59351002 0.06742
+0.74088501 -0.59263 0.15724
+0.67806503 -0.65469002 0.13749
+
+-0.65483498 0.44209999 0.23309999
+-0.66683502 0.43922001 0.22899
+-0.72732498 0.41339001 0.20645
+
+-0.47864498 -0.74934998 0.25862
+-0.45761501 -0.71341003 0.26252001
+-0.45211498 -0.74226997 0.21997999
+
+0.069325 0.57973999 -0.17223
+0.080755 0.61445999 -0.2476
+0.077465 0.65564003 -0.25237
+
+-0.67873497 0.42423 0.10789
+-0.65177498 0.41154999 0.04812
+-0.72976501 0.37284 0.12714
+
+-0.65177498 0.41154999 0.04812
+-0.65177498 0.38554001 0.03709
+-0.72976501 0.37284 0.12714
+
+0.72394501 -0.43584999 0.02906
+0.72512497 -0.40280998 0.05526
+0.756455 -0.42445 0.07686
+
+-0.33072498 -0.58639999 0.18187
+-0.334715 -0.61401001 0.18212
+-0.35820499 -0.59717999 0.29188
+
+0.051805 0.5825 -0.15508
+0.046465 0.53513 -0.12086
+0.069325 0.57973999 -0.17223
+
+-0.59834499 0.43923 0.01644
+-0.579935 0.46213001 -0.01038
+-0.61525501 0.41305 0.00652
+
+-0.158205 -0.50859001 -0.11002
+-0.178085 -0.52410999 -0.09604
+-0.238365 -0.47976002 -0.11273
+
+-0.21439501 -0.74724998 0.25917999
+-0.19824499 -0.74849998 0.24569
+-0.17445499 -0.76107002 0.26183001
+
+-0.247845 0.62541 -0.03466
+-0.29095501 0.58248001 -0.04404
+-0.40747501 0.47915001 0.0356
+
+-0.44820499 0.36980999 -0.02461
+-0.47220501 0.42382 -0.00262
+-0.44782501 0.38021 -0.01581
+
+-0.37405499 -0.52716 0.21347
+-0.37755501 -0.52604 0.2115
+-0.360765 -0.53513 0.20674
+
+-0.52155499 0.29777 -0.06353
+-0.54577499 0.32955002 -0.08891
+-0.49023499 0.31427999 -0.06865
+
+-0.329715 0.31518 0.05937
+-0.32425499 0.33021 0.07945
+-0.30900499 0.25450001 0.12933
+
+-0.73949501 0.19546 0.40769001
+-0.76541496 0.19517 0.23780001
+-0.76138496 0.14034 0.29812
+
+-0.75975502 0.14085 0.40800999
+-0.76138496 0.14034 0.29812
+-0.76316498 0.10037 0.37827
+
+-0.069995 -0.13285 -0.23166
+-0.040395 -0.02881 -0.20667999
+0.074325 -0.09863 -0.22704
+
+-0.462365 -0.76483002 -0.06405
+-0.47280499 -0.76528 -0.06571
+-0.47702499 -0.74514 -0.06318
+
+-0.77015503 0.16722 0.17794001
+-0.76541496 0.19517 0.23780001
+-0.722985 0.29028 0.13737
+
+0.47530499 -0.39273998 -0.18283001
+0.44975498 -0.50793999 -0.1924
+0.458255 -0.43664001 -0.18388
+
+-0.139575 -0.71986 0.03333
+-0.204055 -0.71999001 -0.05273
+-0.098815 -0.71488998 -0.14756
+
+0.56943501 -0.51193001 -0.02993
+0.54107498 -0.55365002 -0.04656
+0.54445499 -0.48500999 -0.09213
+
+0.372915 -0.65777 -0.19226999
+0.382645 -0.65669998 -0.17177999
+0.39260502 -0.67114998 -0.11193
+
+0.756455 -0.42445 0.07686
+0.757565 -0.47983002 0.05688
+0.73838501 -0.45884998 0.0331
+
+-0.579935 0.46213001 -0.01038
+-0.55648499 0.57926998 -0.21315001
+-0.58244499 0.64759003 -0.39550999
+
+-0.75503502 0.05844 0.12856
+-0.75427498 0.12566 0.09816
+-0.73905502 0.04444 0.0987
+
+0.56943501 -0.51193001 -0.02993
+0.554575 -0.42790001 -0.10218
+0.611035 -0.42883999 0.02128
+
+-0.67290497 -0.32478001 0.06036
+-0.63462502 -0.37513 0.05758
+-0.67019501 -0.33046001 0.17235001
+
+-0.57005501 0.04798 -0.05057
+-0.67421501 -0.09452 -0.01072
+-0.66189499 0.00042 0.02855
+
+0.54445499 -0.48500999 -0.09213
+0.54107498 -0.55365002 -0.04656
+0.50467499 -0.54449001 -0.10164
+
+0.39172501 -0.75321999 0.22577
+0.34790501 -0.74143997 0.42344002
+0.268925 -0.75015999 0.45092999
+
+0.30606501 -0.05008 -0.17846001
+0.259195 0.02269 -0.176
+0.359175 -0.0197 -0.15061
+
+-0.75427498 0.12566 0.09816
+-0.75503502 0.05844 0.12856
+-0.77178497 0.08616 0.18837
+
+-0.33072498 -0.58639999 0.18187
+-0.33488499 -0.55792 0.17202
+-0.386665 -0.56747002 0.10225
+
+0.329505 -0.71892998 0.45332001
+0.367225 -0.65199997 0.44060001
+0.308475 -0.66796997 0.46055
+
+0.004935 0.49839001 -0.08707
+-0.027095 0.51598 -0.13203
+0.060495 0.54880001 -0.17709
+
+0.44320499 -0.65613998 -0.05025
+0.522575 -0.68685997 -0.0156
+0.40176498 -0.71222 -0.03167
+
+0.51241501 -0.64007004 -0.04479
+0.44320499 -0.65613998 -0.05025
+0.50317501 -0.58196999 -0.06143
+
+0.008635 0.76769997 -0.20617001
+-0.006815 0.77167 -0.18312
+0.036155 0.71919998 -0.22396
+
+-0.573535 -0.42264999 0.23674
+-0.57746498 -0.38132 0.32298
+-0.63988499 -0.38061001 0.17080999
+
+0.329505 -0.71892998 0.45332001
+0.34790501 -0.74143997 0.42344002
+0.390485 -0.69848 0.41848
+
+0.59800499 -0.28384001 -0.03253
+0.611035 -0.42883999 0.02128
+0.554575 -0.42790001 -0.10218
+
+-0.73905502 0.04444 0.0987
+-0.68397499 0.00246 0.06858
+-0.70774498 0.00346 0.16879
+
+-0.73406502 0.22117001 0.0777
+-0.722985 0.29028 0.13737
+-0.685625 0.31711 0.06703
+
+-0.53066502 0.00663 -0.09101
+-0.47079498 0.02284 -0.11794
+-0.48044498 -0.07672 -0.15554
+
+-0.69932503 0.13755 -0.00205
+-0.75427498 0.12566 0.09816
+-0.73406502 0.22117001 0.0777
+
+0.080755 0.61445999 -0.2476
+0.073585 0.64028999 -0.27017
+0.077465 0.65564003 -0.25237
+
+0.066055 0.59167999 -0.23388
+0.075455 0.60136002 -0.24311001
+0.075975 0.58987 -0.22885
+
+-0.502845 -0.67873001 0.11659
+-0.38455502 -0.62816002 0.13858
+-0.50359501 -0.65364998 0.07231
+
+-0.72489502 -0.13198 0.11954
+-0.70828499 -0.11964 0.0597
+-0.68935501 -0.17514999 0.00979
+
+0.56943501 -0.51193001 -0.02993
+0.54445499 -0.48500999 -0.09213
+0.554575 -0.42790001 -0.10218
+
+-0.515135 0.41865002 -0.44709
+-0.49363499 0.44341 -0.49014
+-0.51723499 0.35522999 -0.21364
+
+-0.49023499 0.31427999 -0.06865
+-0.54577499 0.32955002 -0.08891
+-0.54886501 0.33823002 -0.12392
+
+0.59800499 -0.28384001 -0.03253
+0.554575 -0.42790001 -0.10218
+0.47530499 -0.39273998 -0.18283001
+
+-0.47018501 0.48946999 -0.51748001
+-0.455145 0.56103001 -0.45051998
+-0.44885502 0.48257999 -0.32057999
+
+0.372915 -0.65777 -0.19226999
+0.39260502 -0.67114998 -0.11193
+0.35073502 -0.73208 -0.14142
+
+0.54107498 -0.55365002 -0.04656
+0.50317501 -0.58196999 -0.06143
+0.50467499 -0.54449001 -0.10164
+
+-0.77178497 0.08616 0.18837
+-0.773265 0.14032 0.25822001
+-0.77828499 0.14011 0.20802999
+
+0.44975498 -0.50793999 -0.1924
+0.47530499 -0.39273998 -0.18283001
+0.554575 -0.42790001 -0.10218
+
+-0.70818497 0.41217999 0.12753
+-0.72976501 0.37284 0.12714
+-0.74042503 0.40042999 0.17667999
+
+-0.63988499 -0.38061001 0.17080999
+-0.67019501 -0.33046001 0.17235001
+-0.63462502 -0.37513 0.05758
+
+-0.722985 0.29028 0.13737
+-0.74736504 0.31806 0.17700001
+-0.69845497 0.34506001 0.09724
+
+0.74039497 -0.56462002 0.06716
+0.77457497 -0.49212002 0.10691
+0.74088501 -0.59263 0.15724
+
+-0.20123501 -0.75469002 -0.29017
+-0.23188499 -0.76166 -0.28009001
+-0.25884501 -0.74322998 -0.26056
+
+-0.16091499 -0.46264999 -0.1489
+-0.158205 -0.50859001 -0.11002
+-0.19886499 -0.37626999 -0.16464001
+
+0.40481499 -0.73542999 0.28509001
+0.473535 -0.68335999 0.30688
+0.43405499 -0.71273003 0.30693001
+
+0.061495 0.71106003 -0.27132
+0.008635 0.76769997 -0.20617001
+0.036155 0.71919998 -0.22396
+
+-0.67165497 0.20761999 -0.01075
+-0.67093498 0.16365 -0.02486
+-0.69932503 0.13755 -0.00205
+
+-0.70828499 -0.11964 0.0597
+-0.72489502 -0.13198 0.11954
+-0.72112503 -0.09155 0.13937
+
+-0.531875 0.43505001 -0.47442001
+-0.49343498 0.53766998 -0.56959999
+-0.49435501 0.49361 -0.54973999
+
+-0.67873497 0.42423 0.10789
+-0.72976501 0.37284 0.12714
+-0.70818497 0.41217999 0.12753
+
+-0.19886499 -0.37626999 -0.16464001
+-0.158205 -0.50859001 -0.11002
+-0.238365 -0.47976002 -0.11273
+
+0.32443501 -0.74949997 -0.15917
+0.35073502 -0.73208 -0.14142
+0.369995 -0.75161003 -0.02044
+
+0.40176498 -0.71222 -0.03167
+0.39260502 -0.67114998 -0.11193
+0.44320499 -0.65613998 -0.05025
+
+-0.41561501 -0.69004997 0.22243999
+-0.39039501 -0.65042 0.25218
+-0.35919498 -0.65380997 0.20221001
+
+0.55953499 -0.19656 -0.10231
+0.52969501 -0.24299 -0.15367
+0.53496498 -0.20222 -0.13642
+
+0.44975498 -0.50793999 -0.1924
+0.44724499 -0.56456001 -0.18232
+0.42197498 -0.58331001 -0.20099001
+
+-0.42884499 -0.63210999 0.34209
+-0.47553501 -0.68308998 0.30209
+-0.45441502 -0.64302002 0.36220001
+
+-0.178825 -0.39007 -0.16848
+-0.156355 -0.32272999 -0.27996
+-0.107915 -0.53838001 -0.23878
+
+0.141325 -0.71446999 0.04894
+-0.113155 -0.72134003 0.07626
+-0.031635 -0.71653999 -0.15134
+
+-0.23188499 -0.76166 -0.28009001
+-0.249135 -0.76183998 -0.26459
+-0.25884501 -0.74322998 -0.26056
+
+-0.34072498 0.34067001 0.0194
+-0.352155 0.32740002 0.01621
+-0.312335 0.41512001 -0.03359
+
+0.72791496 -0.59351002 0.06742
+0.74039497 -0.56462002 0.06716
+0.74088501 -0.59263 0.15724
+
+-0.43119499 -0.63069 0.39651001
+-0.39304501 -0.61914001 0.39880001
+-0.42884499 -0.63210999 0.34209
+
+-0.69344498 -0.26929001 0.08014
+-0.71519501 -0.22723 0.07012
+-0.63365501 -0.34187 -0.01984
+
+0.40176498 -0.71222 -0.03167
+0.38144501 -0.72870003 -0.01149
+0.369995 -0.75161003 -0.02044
+
+0.061495 0.71106003 -0.27132
+0.077465 0.65564003 -0.25237
+0.068505 0.67084 -0.27976999
+
+-0.336045 0.18141001 0.33853001
+-0.308445 0.09557 0.30705999
+-0.28057501 0.13838 0.25653999
+
+0.141225 -0.72126999 0.18233999
+0.145855 -0.70772003 0.36983002
+0.034255 -0.70801003 0.40098999
+
+0.44975498 -0.50793999 -0.1924
+0.50467499 -0.54449001 -0.10164
+0.44724499 -0.56456001 -0.18232
+
+-0.44219501 0.62398998 -0.59071999
+-0.46279499 0.65877998 -0.53924999
+-0.455145 0.56103001 -0.45051998
+
+0.60656502 -0.14218 0.20698999
+0.61038502 -0.18419001 0.23695999
+0.58518501 -0.07291 0.16698
+
+-0.089315 -0.30382 -0.35894001
+-0.049555 -0.31667 -0.37383999
+-0.049465 -0.37333 -0.3702
+
+-0.152975 -0.66613998 -0.27448999
+-0.117175 -0.61290001 -0.22316
+-0.078115 -0.62351002 -0.25240999
+
+-0.67093498 0.16365 -0.02486
+-0.67165497 0.20761999 -0.01075
+-0.60123501 0.19448 -0.05578
+
+-0.57746498 -0.38132 0.32298
+-0.63135502 -0.33622002 0.29066999
+-0.63988499 -0.38061001 0.17080999
+
+-0.72375504 -0.14514 0.19955999
+-0.72112503 -0.09155 0.13937
+-0.72489502 -0.13198 0.11954
+
+0.269445 -0.75794998 -0.18476999
+0.302465 -0.72740997 -0.204
+0.32443501 -0.74949997 -0.15917
+
+-0.440755 0.59640999 -0.59333
+-0.44141499 0.60801998 -0.58164001
+-0.44630501 0.55679001 -0.57491001
+
+0.60397499 -0.40557999 0.27521
+0.58010502 -0.29504 0.32986
+0.57273499 -0.37573002 0.33617001
+
+0.61038502 -0.18419001 0.23695999
+0.60656502 -0.14218 0.20698999
+0.56959499 -0.12199 0.29812
+
+0.55259499 -0.04642 0.27702
+0.56959499 -0.12199 0.29812
+0.60656502 -0.14218 0.20698999
+
+0.55259499 -0.04642 0.27702
+0.60656502 -0.14218 0.20698999
+0.58518501 -0.07291 0.16698
+
+-0.165655 0.49323002 0.03954
+-0.081355 0.49502998 0.00394
+-0.009545 0.50974998 -0.05037
+
+0.075455 0.60136002 -0.24311001
+0.066055 0.59167999 -0.23388
+0.046245 0.64051003 -0.26128
+
+-0.44795502 0.48275002 -0.23052
+-0.462285 0.43570999 -0.09058
+-0.45510502 0.35847 -0.05053
+
+-0.36774502 0.40701 0.25933001
+-0.34386501 0.40557999 0.15052
+-0.36813499 0.44145 0.14507
+
+-0.71858498 -0.18570999 0.23955999
+-0.72375504 -0.14514 0.19955999
+-0.72665497 -0.19900999 0.19982
+
+-0.39515499 0.30839001 0.32299999
+-0.336045 0.18141001 0.33853001
+-0.318915 0.22754999 0.2701
+
+0.54445499 -0.48500999 -0.09213
+0.50467499 -0.54449001 -0.10164
+0.44975498 -0.50793999 -0.1924
+
+-0.32425499 0.33021 0.07945
+-0.329715 0.31518 0.05937
+-0.31918501 0.34056 0.04058
+
+0.61429501 -0.26823 0.25707001
+0.61038502 -0.18419001 0.23695999
+0.56959499 -0.12199 0.29812
+
+-0.199305 -0.2299 -0.22021999
+-0.105115 -0.16202 -0.24193001
+-0.153045 -0.23818001 -0.25016001
+
+0.70681503 -0.56171001 0.28268
+0.62594501 -0.60432999 0.32353001
+0.63936501 -0.64530998 0.26995001
+
+0.72546501 -0.5941 0.22735001
+0.74088501 -0.59263 0.15724
+0.76139503 -0.53476002 0.19711
+
+0.70681503 -0.56171001 0.28268
+0.72546501 -0.5941 0.22735001
+0.76070503 -0.52106998 0.2173
+
+0.76070503 -0.52106998 0.2173
+0.76139503 -0.53476002 0.19711
+0.77713501 -0.47799 0.15698
+
+-0.52343498 0.42028999 -0.45174999
+-0.51262501 0.42702 -0.46618999
+-0.515135 0.41865002 -0.44709
+
+-0.112925 0.44946999 -0.01904
+-0.28335501 0.37535999 0.07935
+-0.259715 0.37625999 0.05013
+
+-0.34077499 0.36119999 0.14935
+-0.30900499 0.25450001 0.12933
+-0.32425499 0.33021 0.07945
+
+0.587925 -0.08729 0.02727
+0.61706501 -0.15582 0.06717
+0.57723499 -0.16372999 -0.05665
+
+-0.105115 -0.16202 -0.24193001
+-0.129445 -0.21128 -0.28048
+-0.153045 -0.23818001 -0.25016001
+
+0.74180496 -0.46634998 0.26339001
+0.70681503 -0.56171001 0.28268
+0.76070503 -0.52106998 0.2173
+
+0.51815498 0.03883 0.06995
+0.554645 -0.00877 0.1262
+0.587925 -0.08729 0.02727
+
+0.61706501 -0.15582 0.06717
+0.595695 -0.19973 -0.04273
+0.57723499 -0.16372999 -0.05665
+
+0.70681503 -0.56171001 0.28268
+0.63363499 -0.56191002 0.33492001
+0.62594501 -0.60432999 0.32353001
+
+0.74180496 -0.46634998 0.26339001
+0.68953499 -0.50616001 0.3109
+0.70681503 -0.56171001 0.28268
+
+-0.45953499 0.45066002 -0.34074001
+-0.49363499 0.44341 -0.49014
+-0.44885502 0.48257999 -0.32057999
+
+0.77457497 -0.49212002 0.10691
+0.77608498 -0.45037998 0.12685
+0.77713501 -0.47799 0.15698
+
+0.63408501 -0.68242996 0.15461
+0.67806503 -0.65469002 0.13749
+0.68346497 -0.63983002 0.21789
+
+0.74180496 -0.46634998 0.26339001
+0.70712502 -0.44008999 0.28386
+0.68953499 -0.50616001 0.3109
+
+-0.35530499 0.32993999 0.20927
+-0.34358501 0.26857 0.25934
+-0.318915 0.22754999 0.2701
+
+0.76210503 -0.40971001 0.18714001
+0.74194504 -0.41438999 0.23629999
+0.76550499 -0.45125 0.21715
+
+0.76139503 -0.53476002 0.19711
+0.77457497 -0.49212002 0.10691
+0.77713501 -0.47799 0.15698
+
+0.76550499 -0.45125 0.21715
+0.76070503 -0.52106998 0.2173
+0.77713501 -0.47799 0.15698
+
+-0.31738501 0.43448002 0.11911
+-0.22710501 0.49293999 0.03888
+-0.049325 0.62575001 -0.12564
+
+0.61038502 -0.18419001 0.23695999
+0.64000504 -0.36174 0.16885
+0.61706501 -0.15582 0.06717
+
+0.61038502 -0.18419001 0.23695999
+0.61429501 -0.26823 0.25707001
+0.64000504 -0.36174 0.16885
+
+0.372915 -0.65777 -0.19226999
+0.35073502 -0.73208 -0.14142
+0.32443501 -0.74949997 -0.15917
+
+-0.019855 -0.37563999 0.55806
+0.013465 -0.32881001 0.57973
+-0.042595 -0.29021999 0.57817001
+
+-0.19960501 -0.25952999 -0.2083
+-0.199305 -0.2299 -0.22021999
+-0.167955 -0.26533001 -0.23986
+
+-0.34386501 0.40557999 0.15052
+-0.35530499 0.32993999 0.20927
+-0.34077499 0.36119999 0.14935
+
+-0.54955502 0.46242001 0.21086
+-0.50165501 0.46126999 0.24231001
+-0.45608501 0.45756001 0.24393999
+
+-0.75427498 0.12566 0.09816
+-0.77178497 0.08616 0.18837
+-0.77015503 0.16722 0.17794001
+
+-0.69841499 -0.28159 0.17025999
+-0.69344498 -0.26929001 0.08014
+-0.67290497 -0.32478001 0.06036
+
+-0.457075 0.67668999 -0.58800999
+-0.48884499 0.70297997 -0.56327
+-0.46279499 0.65877998 -0.53924999
+
+-0.49433498 0.69546997 -0.58514
+-0.47459499 0.69324997 -0.58602001
+-0.457075 0.67668999 -0.58800999
+
+-0.46279499 0.65877998 -0.53924999
+-0.44219501 0.62398998 -0.59071999
+-0.457075 0.67668999 -0.58800999
+
+0.77608498 -0.45037998 0.12685
+0.76210503 -0.40971001 0.18714001
+0.77713501 -0.47799 0.15698
+
+0.76210503 -0.40971001 0.18714001
+0.72683502 -0.37872002 0.20152
+0.74194504 -0.41438999 0.23629999
+
+0.74180496 -0.46634998 0.26339001
+0.76550499 -0.45125 0.21715
+0.74194504 -0.41438999 0.23629999
+
+0.77608498 -0.45037998 0.12685
+0.77457497 -0.49212002 0.10691
+0.756455 -0.42445 0.07686
+
+0.77608498 -0.45037998 0.12685
+0.761605 -0.39966999 0.14054
+0.76210503 -0.40971001 0.18714001
+
+0.756455 -0.42445 0.07686
+0.72512497 -0.40280998 0.05526
+0.74167503 -0.40138 0.07409
+
+0.761605 -0.39966999 0.14054
+0.74167503 -0.40138 0.07409
+0.72733498 -0.37303001 0.14242
+
+0.761605 -0.39966999 0.14054
+0.72683502 -0.37872002 0.20152
+0.76210503 -0.40971001 0.18714001
+
+0.72683502 -0.37872002 0.20152
+0.70692497 -0.40130001 0.25292999
+0.74194504 -0.41438999 0.23629999
+
+0.49892502 -0.66067001 0.30966
+0.544925 -0.67612 0.29681999
+0.57481499 -0.63938 0.32445999
+
+-0.44795502 0.48275002 -0.23052
+-0.46693501 0.51418999 -0.19490999
+-0.462285 0.43570999 -0.09058
+
+0.025515 0.74473999 -0.25292999
+-0.016475 0.76692001 -0.19555
+0.008635 0.76769997 -0.20617001
+
+0.761605 -0.39966999 0.14054
+0.72733498 -0.37303001 0.14242
+0.72683502 -0.37872002 0.20152
+
+0.67144501 -0.41029999 0.26914
+0.70712502 -0.44008999 0.28386
+0.70692497 -0.40130001 0.25292999
+
+0.72683502 -0.37872002 0.20152
+0.671035 -0.38804001 0.23941999
+0.70692497 -0.40130001 0.25292999
+
+0.72733498 -0.37303001 0.14242
+0.68963501 -0.36695999 0.18777
+0.72683502 -0.37872002 0.20152
+
+0.68963501 -0.36695999 0.18777
+0.64128502 -0.37016998 0.18415001
+0.671035 -0.38804001 0.23941999
+
+0.67144501 -0.41029999 0.26914
+0.70692497 -0.40130001 0.25292999
+0.671035 -0.38804001 0.23941999
+
+0.761605 -0.39966999 0.14054
+0.77608498 -0.45037998 0.12685
+0.756455 -0.42445 0.07686
+
+0.72733498 -0.37303001 0.14242
+0.70884499 -0.36710999 0.13567
+0.68963501 -0.36695999 0.18777
+
+0.62960499 -0.39731998 0.23868999
+0.60397499 -0.40557999 0.27521
+0.59136501 -0.44555 0.29172001
+
+-0.559795 0.4541 0.06169
+-0.579935 0.46213001 -0.01038
+-0.59834499 0.43923 0.01644
+
+0.72683502 -0.37872002 0.20152
+0.68963501 -0.36695999 0.18777
+0.671035 -0.38804001 0.23941999
+
+-0.53754501 0.46978001 -0.00341
+-0.559795 0.4541 0.06169
+-0.50223499 0.44608002 0.02426
+
+0.62960499 -0.39731998 0.23868999
+0.67144501 -0.41029999 0.26914
+0.671035 -0.38804001 0.23941999
+
+0.67144501 -0.41029999 0.26914
+0.59136501 -0.44555 0.29172001
+0.57196499 -0.49865002 0.31608
+
+0.62960499 -0.39731998 0.23868999
+0.59136501 -0.44555 0.29172001
+0.67144501 -0.41029999 0.26914
+
+-0.61915501 0.44778999 0.11374
+-0.559795 0.4541 0.06169
+-0.59834499 0.43923 0.01644
+
+0.64128502 -0.37016998 0.18415001
+0.62960499 -0.39731998 0.23868999
+0.671035 -0.38804001 0.23941999
+
+-0.28657499 0.21525999 0.16419001
+-0.35530499 0.32993999 0.20927
+-0.318915 0.22754999 0.2701
+
+-0.42884499 -0.63210999 0.34209
+-0.39304501 -0.61914001 0.39880001
+-0.354585 -0.59728001 0.33195
+
+0.56959499 -0.12199 0.29812
+0.55290501 -0.18681999 0.36167999
+0.54806499 -0.22674 0.37215
+
+-0.087935 0.12239 0.26698
+0.032965 0.15014 0.30976
+0.100405 0.1927 0.26025
+
+-0.31738501 0.43448002 0.11911
+-0.236595 0.58076 0.04404
+-0.354445 0.43800999 0.1358
+
+-0.69313499 0.39777 0.31554001
+-0.62949501 0.42409 0.33152
+-0.65483498 0.44209999 0.23309999
+
+-0.74471497 0.23594 0.22754
+-0.74114502 0.29077999 0.20722
+-0.722985 0.29028 0.13737
+
+0.70884499 -0.36710999 0.13567
+0.64561501 -0.37198002 0.10372
+0.64000504 -0.36174 0.16885
+
+0.60397499 -0.40557999 0.27521
+0.62960499 -0.39731998 0.23868999
+0.64128502 -0.37016998 0.18415001
+
+-0.72665497 -0.19900999 0.19982
+-0.71519501 -0.22723 0.07012
+-0.70689499 -0.24051001 0.17004999
+
+-0.36813499 0.44145 0.14507
+-0.34386501 0.40557999 0.15052
+-0.354445 0.43800999 0.1358
+
+-0.43739498 0.45532001 0.06203
+-0.46518501 0.44868 0.07372
+-0.54955502 0.46242001 0.21086
+
+0.76210503 -0.40971001 0.18714001
+0.76550499 -0.45125 0.21715
+0.77713501 -0.47799 0.15698
+
+-0.138135 0.15368 0.18959999
+-0.250515 0.18847 0.08946
+-0.24738501 0.17902 0.16450001
+
+-0.76094498 0.07262 0.24841
+-0.74453499 0.0457 0.23389999
+-0.70928497 0.03538 0.30452
+
+0.64561501 -0.37198002 0.10372
+0.63150501 -0.32306999 0.09721
+0.64000504 -0.36174 0.16885
+
+-0.72665497 -0.19900999 0.19982
+-0.72489502 -0.13198 0.11954
+-0.71519501 -0.22723 0.07012
+
+-0.096095 0.71514 -0.06997
+-0.30827499 0.55255001 0.0553
+-0.236595 0.58076 0.04404
+
+-0.53754501 0.46978001 -0.00341
+-0.50223499 0.44608002 0.02426
+-0.497005 0.44953999 -0.01774
+
+-0.404995 -0.67698997 0.19254
+-0.45211498 -0.74226997 0.21997999
+-0.41561501 -0.69004997 0.22243999
+
+-0.66683502 0.43922001 0.22899
+-0.61915501 0.44778999 0.11374
+-0.67873497 0.42423 0.10789
+
+-0.45004501 0.41863998 0.36409
+-0.49872501 0.43931999 0.33116001
+-0.56956501 0.37901001 0.42835999
+
+-0.567505 0.44047001 0.32217999
+-0.50165501 0.46126999 0.24231001
+-0.54955502 0.46242001 0.21086
+
+-0.208305 0.15802 0.22305
+-0.138135 0.15368 0.18959999
+-0.24738501 0.17902 0.16450001
+
+-0.44795502 0.48275002 -0.23052
+-0.455145 0.56103001 -0.45051998
+-0.478615 0.61969002 -0.45830002
+
+-0.50442501 0.51681 -0.12221
+-0.48107498 0.54027 -0.21445999
+-0.541525 0.60362999 -0.27988001
+
+-0.74582497 0.34598999 0.25691
+-0.74042503 0.40042999 0.17667999
+-0.74736504 0.31806 0.17700001
+
+-0.301705 0.19448999 0.02741
+-0.250515 0.18847 0.08946
+-0.221775 0.16362 -0.02269
+
+-0.28657499 0.21525999 0.16419001
+-0.30900499 0.25450001 0.12933
+-0.35530499 0.32993999 0.20927
+
+-0.36774502 0.40701 0.25933001
+-0.35530499 0.32993999 0.20927
+-0.34386501 0.40557999 0.15052
+
+-0.084295 0.46479 -0.01832
+-0.081355 0.49502998 0.00394
+-0.112925 0.44946999 -0.01904
+
+-0.250515 0.18847 0.08946
+-0.106075 0.15324 0.06919
+-0.221775 0.16362 -0.02269
+
+-0.62949501 0.42409 0.33152
+-0.567505 0.44047001 0.32217999
+-0.65483498 0.44209999 0.23309999
+
+-0.025365 0.17524 0.11324
+0.014575 0.18521999 0.18579
+0.147305 0.21093 0.16179001
+
+-0.58244499 0.64759003 -0.39550999
+-0.55654499 0.64793999 -0.39986
+-0.543125 0.70637001 -0.51022999
+
+-0.35530499 0.32993999 0.20927
+-0.36774502 0.40701 0.25933001
+-0.38591499 0.35167 0.31952
+
+-0.352155 0.32740002 0.01621
+-0.401735 0.37047001 -0.00194
+-0.312335 0.41512001 -0.03359
+
+-0.44827499 0.33785 0.38784
+-0.43137501 0.38099998 0.37743
+-0.52690498 0.36866001 0.4325
+
+-0.27186501 0.17989 0.1998
+-0.28057501 0.13838 0.25653999
+-0.24738501 0.17902 0.16450001
+
+-0.085275 0.1548 0.17931
+-0.025365 0.17524 0.11324
+-0.106075 0.15324 0.06919
+
+-0.497005 0.44953999 -0.01774
+-0.50223499 0.44608002 0.02426
+-0.47220501 0.42382 -0.00262
+
+-0.61915501 0.44778999 0.11374
+-0.59834499 0.43923 0.01644
+-0.65177498 0.41154999 0.04812
+
+-0.48884499 0.70297997 -0.56327
+-0.51963501 0.70806 -0.56443001
+-0.543125 0.70637001 -0.51022999
+
+-0.295275 0.20636 0.05543
+-0.28657499 0.21525999 0.16419001
+-0.250515 0.18847 0.08946
+
+-0.44820499 0.36980999 -0.02461
+-0.462285 0.43570999 -0.09058
+-0.47220501 0.42382 -0.00262
+
+-0.36813499 0.44145 0.14507
+-0.30827499 0.55255001 0.0553
+-0.35580502 0.52299 0.06101
+
+-0.478615 0.61969002 -0.45830002
+-0.541525 0.60362999 -0.27988001
+-0.48107498 0.54027 -0.21445999
+
+-0.46693501 0.51418999 -0.19490999
+-0.50442501 0.51681 -0.12221
+-0.462285 0.43570999 -0.09058
+
+-0.478615 0.61969002 -0.45830002
+-0.455145 0.56103001 -0.45051998
+-0.46279499 0.65877998 -0.53924999
+
+-0.386665 -0.56747002 0.10225
+-0.369095 -0.54116001 0.13157
+-0.41275501 -0.52455002 0.07158
+
+-0.301705 0.19448999 0.02741
+-0.295275 0.20636 0.05543
+-0.250515 0.18847 0.08946
+
+-0.50442501 0.51681 -0.12221
+-0.53754501 0.46978001 -0.00341
+-0.497005 0.44953999 -0.01774
+
+-0.74114502 0.29077999 0.20722
+-0.74471497 0.23594 0.22754
+-0.72123497 0.26363001 0.29735001
+
+-0.74736504 0.31806 0.17700001
+-0.74114502 0.29077999 0.20722
+-0.74582497 0.34598999 0.25691
+
+-0.39786499 0.47005001 0.10535
+-0.40865501 0.45254002 0.17395
+-0.36813499 0.44145 0.14507
+
+-0.69119499 -0.03813 0.21893999
+-0.71903503 -0.1047 0.21924999
+-0.70878502 -0.09154 0.23915001
+
+-0.73905502 0.04444 0.0987
+-0.70774498 0.00346 0.16879
+-0.75351501 0.04522 0.14867
+
+-0.121325 0.14207 0.02081
+-0.138675 0.11073 -0.06666
+-0.221775 0.16362 -0.02269
+
+-0.74042503 0.40042999 0.17667999
+-0.72732498 0.41339001 0.20645
+-0.70818497 0.41217999 0.12753
+
+-0.40865501 0.45254002 0.17395
+-0.54955502 0.46242001 0.21086
+-0.45608501 0.45756001 0.24393999
+
+0.060925 -0.75339996 0.44673
+0.134945 -0.75379997 0.42655998
+0.023935 -0.75346001 0.45659
+
+0.061495 0.71106003 -0.27132
+0.047165 0.73010002 -0.26747
+0.008635 0.76769997 -0.20617001
+
+-0.47512501 0.32431999 -0.07113
+-0.54886501 0.33823002 -0.12392
+-0.51723499 0.35522999 -0.21364
+
+-0.140345 -0.05789 -0.20672001
+-0.105925 -0.01889 -0.19115
+-0.040395 -0.02881 -0.20667999
+
+-0.025365 0.17524 0.11324
+-0.085275 0.1548 0.17931
+0.014575 0.18521999 0.18579
+
+-0.192925 0.12158 0.28837999
+-0.138135 0.15368 0.18959999
+-0.208305 0.15802 0.22305
+
+-0.329715 0.31518 0.05937
+-0.34072498 0.34067001 0.0194
+-0.31918501 0.34056 0.04058
+
+0.54476501 -0.0057 0.22294001
+0.470495 0.07129 0.2808
+0.55259499 -0.04642 0.27702
+
+0.49233501 0.07108 0.18927999
+0.54476501 -0.0057 0.22294001
+0.554645 -0.00877 0.1262
+
+-0.085275 0.1548 0.17931
+-0.106075 0.15324 0.06919
+-0.138135 0.15368 0.18959999
+
+-0.40865501 0.45254002 0.17395
+-0.43739498 0.45532001 0.06203
+-0.54955502 0.46242001 0.21086
+
+0.51815498 0.03883 0.06995
+0.48769501 0.07898 0.11616
+0.49233501 0.07108 0.18927999
+
+0.49233501 0.07108 0.18927999
+0.470495 0.07129 0.2808
+0.54476501 -0.0057 0.22294001
+
+-0.121325 0.14207 0.02081
+-0.025365 0.17524 0.11324
+0.078115 0.18864 0.02789
+
+-0.46518501 0.44868 0.07372
+-0.559795 0.4541 0.06169
+-0.54955502 0.46242001 0.21086
+
+-0.559795 0.4541 0.06169
+-0.61915501 0.44778999 0.11374
+-0.54955502 0.46242001 0.21086
+
+-0.138135 0.15368 0.18959999
+-0.106075 0.15324 0.06919
+-0.250515 0.18847 0.08946
+
+-0.50165501 0.46126999 0.24231001
+-0.49872501 0.43931999 0.33116001
+-0.45608501 0.45756001 0.24393999
+
+-0.438055 -0.66690002 0.44669998
+-0.43119499 -0.63069 0.39651001
+-0.46994499 -0.66989998 0.39380001
+
+0.51815498 0.03883 0.06995
+0.49233501 0.07108 0.18927999
+0.554645 -0.00877 0.1262
+
+0.54476501 -0.0057 0.22294001
+0.58518501 -0.07291 0.16698
+0.554645 -0.00877 0.1262
+
+-0.38813499 0.43208 0.28315001
+-0.40865501 0.45254002 0.17395
+-0.45608501 0.45756001 0.24393999
+
+-0.087935 0.12239 0.26698
+-0.085275 0.1548 0.17931
+-0.138135 0.15368 0.18959999
+
+-0.34746498 -0.54298 0.16158001
+-0.33488499 -0.55792 0.17202
+-0.34688499 -0.54231998 0.18309999
+
+-0.28057501 0.13838 0.25653999
+-0.208305 0.15802 0.22305
+-0.24738501 0.17902 0.16450001
+
+0.047165 0.73010002 -0.26747
+0.061495 0.71106003 -0.27132
+0.059645 0.68377998 -0.28246
+
+0.554645 -0.00877 0.1262
+0.58518501 -0.07291 0.16698
+0.587925 -0.08729 0.02727
+
+-0.50442501 0.51681 -0.12221
+-0.46693501 0.51418999 -0.19490999
+-0.48107498 0.54027 -0.21445999
+
+-0.139575 -0.71986 0.03333
+-0.152335 -0.71831001 0.01116
+-0.204055 -0.71999001 -0.05273
+
+0.48769501 0.07898 0.11616
+0.41226501 0.13985 0.08791
+0.49233501 0.07108 0.18927999
+
+-0.036455 0.74396004 -0.12342
+0.036155 0.71919998 -0.22396
+-0.006815 0.77167 -0.18312
+
+-0.58244499 0.64759003 -0.39550999
+-0.543125 0.70637001 -0.51022999
+-0.597435 0.68508003 -0.47937
+
+-0.38813499 0.43208 0.28315001
+-0.36813499 0.44145 0.14507
+-0.40865501 0.45254002 0.17395
+
+-0.45004501 0.41863998 0.36409
+-0.40461498 0.42754002 0.32105999
+-0.49872501 0.43931999 0.33116001
+
+0.37462502 0.09203 0.35064999
+0.43314499 -0.00056 0.38240002
+0.47858501 0.02572 0.32499001
+
+0.49725498 0.02933 -0.02307
+0.51815498 0.03883 0.06995
+0.587925 -0.08729 0.02727
+
+0.51815498 0.03883 0.06995
+0.45834499 0.08214 0.00486
+0.48769501 0.07898 0.11616
+
+-0.336045 0.18141001 0.33853001
+-0.28057501 0.13838 0.25653999
+-0.318915 0.22754999 0.2701
+
+-0.40461498 0.42754002 0.32105999
+-0.43137501 0.38099998 0.37743
+-0.38591499 0.35167 0.31952
+
+0.136995 -0.12943 0.54544998
+0.182565 -0.11096 0.51632
+0.079635 -0.11564 0.52494999
+
+-0.499935 0.33810001 0.43618999
+-0.44827499 0.33785 0.38784
+-0.52690498 0.36866001 0.4325
+
+-0.49872501 0.43931999 0.33116001
+-0.50165501 0.46126999 0.24231001
+-0.567505 0.44047001 0.32217999
+
+0.23345501 -0.11154 0.49640999
+0.182565 -0.11096 0.51632
+0.182745 -0.12148 0.53138
+
+0.182745 -0.12148 0.53138
+0.17338499 -0.16284 0.56652
+0.26328501 -0.13812 0.51595001
+
+0.70712502 -0.44008999 0.28386
+0.67144501 -0.41029999 0.26914
+0.64346497 -0.49037998 0.32360001
+
+-0.19938499 -0.27365 -0.20799
+-0.176745 -0.32091 -0.21965
+-0.18914499 -0.31829 -0.17997
+
+0.430765 0.12101 0.23743
+0.362635 0.14925 0.26934
+0.368885 0.12605 0.31459999
+
+0.70884499 -0.36710999 0.13567
+0.64128502 -0.37016998 0.18415001
+0.68963501 -0.36695999 0.18777
+
+0.45834499 0.08214 0.00486
+0.41226501 0.13985 0.08791
+0.48769501 0.07898 0.11616
+
+0.60397499 -0.40557999 0.27521
+0.64128502 -0.37016998 0.18415001
+0.61429501 -0.26823 0.25707001
+
+-0.72375504 -0.14514 0.19955999
+-0.71903503 -0.1047 0.21924999
+-0.72112503 -0.09155 0.13937
+
+0.17338499 -0.16284 0.56652
+0.182745 -0.12148 0.53138
+0.136995 -0.12943 0.54544998
+
+0.38503502 0.15941 0.19188999
+0.430765 0.12101 0.23743
+0.49233501 0.07108 0.18927999
+
+0.368885 0.12605 0.31459999
+0.37462502 0.09203 0.35064999
+0.470495 0.07129 0.2808
+
+0.368885 0.12605 0.31459999
+0.470495 0.07129 0.2808
+0.430765 0.12101 0.23743
+
+-0.36813499 0.44145 0.14507
+-0.354445 0.43800999 0.1358
+-0.30827499 0.55255001 0.0553
+
+-0.46693501 0.51418999 -0.19490999
+-0.44795502 0.48275002 -0.23052
+-0.48107498 0.54027 -0.21445999
+
+0.430765 0.12101 0.23743
+0.470495 0.07129 0.2808
+0.49233501 0.07108 0.18927999
+
+-0.30900499 0.25450001 0.12933
+-0.34077499 0.36119999 0.14935
+-0.35530499 0.32993999 0.20927
+
+-0.27186501 0.17989 0.1998
+-0.24738501 0.17902 0.16450001
+-0.250515 0.18847 0.08946
+
+-0.56956501 0.37901001 0.42835999
+-0.567505 0.44047001 0.32217999
+-0.62949501 0.42409 0.33152
+
+0.41226501 0.13985 0.08791
+0.38503502 0.15941 0.19188999
+0.49233501 0.07108 0.18927999
+
+-0.40461498 0.42754002 0.32105999
+-0.38813499 0.43208 0.28315001
+-0.45608501 0.45756001 0.24393999
+
+0.035725 -0.09047 0.45244999
+0.154285 -0.09136 0.45977001
+0.093525 -0.02874 0.45459
+
+0.37462502 0.09203 0.35064999
+0.47858501 0.02572 0.32499001
+0.470495 0.07129 0.2808
+
+-0.67165497 0.20761999 -0.01075
+-0.69932503 0.13755 -0.00205
+-0.73406502 0.22117001 0.0777
+
+0.223505 -0.23148001 0.58157001
+0.053405 -0.17601 0.57659
+0.043465 -0.23129 0.58570999
+
+0.61706501 -0.15582 0.06717
+0.587925 -0.08729 0.02727
+0.58518501 -0.07291 0.16698
+
+0.362635 0.14925 0.26934
+0.430765 0.12101 0.23743
+0.38503502 0.15941 0.19188999
+
+-0.106735 0.07859 0.32783001
+-0.087935 0.12239 0.26698
+-0.138135 0.15368 0.18959999
+
+-0.48107498 0.54027 -0.21445999
+-0.44795502 0.48275002 -0.23052
+-0.478615 0.61969002 -0.45830002
+
+0.28172501 -0.75823997 -0.05062
+0.369995 -0.75161003 -0.02044
+0.37226501 -0.75335999 0.0004
+
+0.40085499 0.10826 -0.02869
+0.32314499 0.16155001 -0.00588
+0.368895 0.14748 0.00937
+
+-0.51963501 0.70806 -0.56443001
+-0.572925 0.70330002 -0.52133999
+-0.543125 0.70637001 -0.51022999
+
+-0.68001503 -0.24351 -0.00998
+-0.68935501 -0.17514999 0.00979
+-0.660215 -0.19101 -0.05073
+
+0.41226501 0.13985 0.08791
+0.45834499 0.08214 0.00486
+0.40085499 0.10826 -0.02869
+
+0.41226501 0.13985 0.08791
+0.40085499 0.10826 -0.02869
+0.368895 0.14748 0.00937
+
+0.267075 0.20905001 0.1627
+0.31116501 0.18573 0.23601
+0.38503502 0.15941 0.19188999
+
+0.29845501 0.12968 0.34632999
+0.368885 0.12605 0.31459999
+0.362635 0.14925 0.26934
+
+-0.28657499 0.21525999 0.16419001
+-0.27186501 0.17989 0.1998
+-0.250515 0.18847 0.08946
+
+-0.56052502 -0.45873001 0.12908
+-0.53317501 -0.47806999 0.18746
+-0.63988499 -0.38061001 0.17080999
+
+-0.52155499 0.29777 -0.06353
+-0.54156502 0.29757 -0.05975
+-0.54577499 0.32955002 -0.08891
+
+0.41226501 0.13985 0.08791
+0.368895 0.14748 0.00937
+0.30644501 0.19247999 0.06287
+
+0.362635 0.14925 0.26934
+0.38503502 0.15941 0.19188999
+0.31116501 0.18573 0.23601
+
+-0.080705 -0.14328 0.45655998
+-0.075765 -0.16964001 0.4948
+-0.029165 -0.1302 0.47558998
+
+0.043465 -0.23129 0.58570999
+0.053405 -0.17601 0.57659
+-0.042475 -0.24874001 0.57685001
+
+-0.036705 -0.58948002 0.47154999
+-0.029985 -0.49078999 0.50139999
+-0.096085 -0.45277 0.41069
+
+-0.406185 -0.64178001 0.44240002
+-0.39304501 -0.61914001 0.39880001
+-0.43119499 -0.63069 0.39651001
+
+-0.100065 -0.67837997 0.54858002
+-0.158775 -0.70517998 0.52299
+-0.119005 -0.73551003 0.54847
+
+-0.008315 -0.16797001 0.55435001
+-0.057925 -0.20864 0.54856998
+-0.042475 -0.24874001 0.57685001
+
+-0.62411499 0.60556 -0.39534
+-0.608685 0.60671001 -0.42444
+-0.61443501 0.52313 -0.27403999
+
+-0.100065 -0.67837997 0.54858002
+-0.056445 -0.62691002 0.52630001
+-0.106135 -0.61624001 0.49498001
+
+-0.051545 0.75455002 -0.12812
+-0.29095501 0.58248001 -0.04404
+-0.247845 0.62541 -0.03466
+
+-0.158775 -0.70517998 0.52299
+-0.100065 -0.67837997 0.54858002
+-0.16275499 -0.66514 0.49737
+
+-0.597435 0.68508003 -0.47937
+-0.579935 0.46213001 -0.01038
+-0.58244499 0.64759003 -0.39550999
+
+-0.57147499 0.29725 -0.05187
+-0.54156502 0.29757 -0.05975
+-0.52155499 0.29777 -0.06353
+
+-0.44782501 0.38021 -0.01581
+-0.41858501 0.32521999 -0.01536
+-0.44820499 0.36980999 -0.02461
+
+-0.116605 -0.52758999 0.38146999
+-0.140305 -0.57868999 0.38641998
+-0.118055 -0.56602001 0.3798
+
+-0.35253502 -0.54191002 0.28164
+-0.354585 -0.59728001 0.33195
+-0.32939499 -0.58321999 0.36421001
+
+0.35949501 -0.21177999 -0.24714001
+0.290105 -0.15098 -0.25101999
+0.28848499 -0.13418 -0.22884001
+
+-0.44495499 0.61160999 -0.60196999
+-0.43943501 0.61122002 -0.59380001
+-0.440755 0.59640999 -0.59333
+
+0.053525 -0.59877998 0.51932999
+0.093335 -0.54011002 0.55001999
+0.031045 -0.48976002 0.55334
+
+-0.43739498 0.45532001 0.06203
+-0.247845 0.62541 -0.03466
+-0.40747501 0.47915001 0.0356
+
+-0.34072498 0.34067001 0.0194
+-0.363535 0.29777 0.01081
+-0.352155 0.32740002 0.01621
+
+-0.47512501 0.32431999 -0.07113
+-0.468335 0.32449001 -0.06341
+-0.47262501 0.31153 -0.0592
+
+-0.199305 -0.2299 -0.22021999
+-0.19938499 -0.27365 -0.20799
+-0.249485 -0.24631001 -0.19802999
+
+-0.32425499 0.33021 0.07945
+-0.31918501 0.34056 0.04058
+-0.259715 0.37625999 0.05013
+
+-0.60170502 0.42654999 -0.05351
+-0.59239498 0.37070999 -0.07326
+-0.614795 0.37119999 -0.013
+
+-0.34414501 -0.48889999 0.33360001
+-0.35253502 -0.54191002 0.28164
+-0.32939499 -0.58321999 0.36421001
+
+-0.009275 -0.14155 0.52644001
+-0.008315 -0.16797001 0.55435001
+0.053405 -0.17601 0.57659
+
+-0.068205 -0.24886999 0.56009998
+-0.042475 -0.24874001 0.57685001
+-0.057925 -0.20864 0.54856998
+
+-0.17994499 -0.75432999 0.36115002
+-0.129625 -0.75866997 0.17889999
+-0.141445 -0.71961998 0.33926998
+
+-0.35181499 -0.54046001 0.20204
+-0.34688499 -0.54231998 0.18309999
+-0.33072498 -0.58639999 0.18187
+
+-0.009545 0.50974998 -0.05037
+0.004935 0.49839001 -0.08707
+0.046465 0.53513 -0.12086
+
+-0.029165 -0.1302 0.47558998
+-0.106555 -0.0996 0.45023998
+-0.080705 -0.14328 0.45655998
+
+-0.068205 -0.24886999 0.56009998
+-0.093355 -0.17006001 0.46999001
+-0.119785 -0.23910999 0.46998001
+
+-0.068205 -0.24886999 0.56009998
+-0.057925 -0.20864 0.54856998
+-0.075765 -0.16964001 0.4948
+
+-0.074085 -0.30458 0.55348
+-0.068205 -0.24886999 0.56009998
+-0.119785 -0.23910999 0.46998001
+
+0.031045 -0.48976002 0.55334
+-0.019855 -0.37563999 0.55806
+-0.016705 -0.60248001 0.48320999
+
+-0.119785 -0.23910999 0.46998001
+-0.137875 -0.2701 0.43911999
+-0.085865 -0.32016998 0.52319
+
+-0.38665501 -0.15554 0.46
+-0.38654499 -0.07216 0.43530998
+-0.436525 -0.08632 0.43841
+
+0.035725 -0.09047 0.45244999
+-0.029165 -0.1302 0.47558998
+-0.009275 -0.14155 0.52644001
+
+-0.019855 -0.37563999 0.55806
+-0.042595 -0.29021999 0.57817001
+-0.074085 -0.30458 0.55348
+
+-0.330975 0.52471001 -0.03259
+-0.18282499 0.59498001 -0.13044
+-0.23320499 0.5352 -0.10464
+
+0.093385 -0.48191002 0.57638
+0.103345 -0.42644001 0.57532001
+0.053355 -0.41346001 0.56433998
+
+-0.54655499 0.08835 0.54924999
+-0.58654499 0.0687 0.53747002
+-0.54197498 0.03751 0.51964001
+
+-0.137875 -0.2701 0.43911999
+-0.029985 -0.49078999 0.50139999
+-0.085865 -0.32016998 0.52319
+
+-0.029165 -0.1302 0.47558998
+-0.075765 -0.16964001 0.4948
+-0.009275 -0.14155 0.52644001
+
+-0.35181499 -0.54046001 0.20204
+-0.40862499 -0.51027 0.23212
+-0.382085 -0.52368999 0.21750999
+
+-0.288985 -0.33368 -0.16805
+-0.328545 -0.40797001 -0.12829
+-0.37912498 -0.31878 -0.18186001
+
+-0.455145 0.56103001 -0.45051998
+-0.47018501 0.48946999 -0.51748001
+-0.44630501 0.55679001 -0.57491001
+
+-0.080705 -0.14328 0.45655998
+-0.093355 -0.17006001 0.46999001
+-0.075765 -0.16964001 0.4948
+
+-0.40862499 -0.51027 0.23212
+-0.37079498 -0.49140999 0.28962999
+-0.403395 -0.47771 0.30250999
+
+-0.35181499 -0.54046001 0.20204
+-0.37079498 -0.49140999 0.28962999
+-0.40862499 -0.51027 0.23212
+
+-0.42102501 -0.74413002 0.47407001
+-0.44044498 -0.72050003 0.46478001
+-0.47779499 -0.74220001 0.42571999
+
+-0.51212502 -0.2273 0.45049999
+-0.55939499 -0.21372999 0.42647999
+-0.61961498 -0.25518 0.37487
+
+-0.40703499 -0.68030998 0.47273998
+-0.406185 -0.64178001 0.44240002
+-0.438055 -0.66690002 0.44669998
+
+-0.35181499 -0.54046001 0.20204
+-0.35253502 -0.54191002 0.28164
+-0.37079498 -0.49140999 0.28962999
+
+-0.60170502 0.42654999 -0.05351
+-0.579935 0.46213001 -0.01038
+-0.62411499 0.60556 -0.39534
+
+-0.140345 -0.05789 -0.20672001
+-0.040395 -0.02881 -0.20667999
+-0.069995 -0.13285 -0.23166
+
+-0.62949501 0.42409 0.33152
+-0.69313499 0.39777 0.31554001
+-0.62565498 0.37287998 0.41800999
+
+-0.259715 0.37625999 0.05013
+-0.31918501 0.34056 0.04058
+-0.112925 0.44946999 -0.01904
+
+-0.677295 0.16986 0.51804001
+-0.62663502 0.17285 0.54678001
+-0.65234497 0.19790001 0.53490002
+
+-0.49433498 0.69546997 -0.58514
+-0.457075 0.67668999 -0.58800999
+-0.47443501 0.65209999 -0.59683998
+
+-0.50058498 -0.72952003 0.32737999
+-0.47553501 -0.68308998 0.30209
+-0.47838501 -0.72314003 0.26280001
+
+0.38315498 -0.105 -0.19958
+0.44600498 -0.11718 -0.16657
+0.44883499 -0.17316 -0.18752001
+
+-0.65234497 0.19790001 0.53490002
+-0.65054497 0.23882 0.51790001
+-0.68966499 0.23750999 0.48583
+
+-0.45441502 -0.64302002 0.36220001
+-0.47614498 -0.66900002 0.34229
+-0.46994499 -0.66989998 0.39380001
+
+-0.55939499 -0.21372999 0.42647999
+-0.551175 -0.15953 0.43046001
+-0.61401501 -0.18775999 0.38139999
+
+-0.042595 -0.29021999 0.57817001
+-0.042475 -0.24874001 0.57685001
+-0.068205 -0.24886999 0.56009998
+
+-0.152975 -0.66613998 -0.27448999
+-0.17661501 -0.63981998 -0.23927999
+-0.117175 -0.61290001 -0.22316
+
+-0.272745 -0.45799 0.41743
+-0.34414501 -0.48889999 0.33360001
+-0.32939499 -0.58321999 0.36421001
+
+-0.029985 -0.49078999 0.50139999
+-0.036705 -0.58948002 0.47154999
+-0.016705 -0.60248001 0.48320999
+
+-0.136565 -0.18389 0.45653999
+-0.119785 -0.23910999 0.46998001
+-0.093355 -0.17006001 0.46999001
+
+-0.096085 -0.45277 0.41069
+-0.116605 -0.52758999 0.38146999
+-0.118055 -0.56602001 0.3798
+
+-0.59962502 0.11646 0.54145
+-0.62663502 0.17285 0.54678001
+-0.677295 0.16986 0.51804001
+
+-0.65526497 -0.16193001 0.33708
+-0.61401501 -0.18775999 0.38139999
+-0.60681499 -0.05331 0.35605999
+
+-0.40862499 -0.51027 0.23212
+-0.406595 -0.51327 0.22797001
+-0.406595 -0.51174999 0.23107
+
+-0.39039501 -0.65042 0.25218
+-0.42884499 -0.63210999 0.34209
+-0.354585 -0.59728001 0.33195
+
+-0.54392502 0.40847 -0.42164001
+-0.52669498 0.41201 -0.43175999
+-0.54327499 0.39124001 -0.37567001
+
+-0.61961498 -0.25518 0.37487
+-0.55939499 -0.21372999 0.42647999
+-0.61401501 -0.18775999 0.38139999
+
+-0.420495 -0.13227 -0.18625
+-0.36962502 -0.20292999 -0.20726999
+-0.40962502 -0.24707001 -0.19660999
+
+-0.48429501 0.08465 0.51129002
+-0.516045 0.07047 0.53485001
+-0.527495 0.03341 0.50833
+
+-0.16779499 -0.59556999 -0.09223
+-0.132525 -0.59215 -0.16823
+-0.228515 -0.64073997 -0.19774
+
+-0.49343498 0.53766998 -0.56959999
+-0.44495499 0.61160999 -0.60196999
+-0.46016499 0.52960999 -0.57521999
+
+-0.363685 -0.71358002 0.48608002
+-0.40703499 -0.68030998 0.47273998
+-0.40310501 -0.70723999 0.48404999
+
+-0.65234497 0.19790001 0.53490002
+-0.59655499 0.21528 0.54181
+-0.65054497 0.23882 0.51790001
+
+-0.74907501 0.12734 0.44921001
+-0.70310501 0.07475 0.49027
+-0.677295 0.16986 0.51804001
+
+-0.16779499 -0.59556999 -0.09223
+-0.228515 -0.64073997 -0.19774
+-0.233095 -0.62811001 -0.12729
+
+-0.75975502 0.14085 0.40800999
+-0.754655 0.10016 0.44153999
+-0.74907501 0.12734 0.44921001
+
+-0.17445499 -0.76107002 0.26183001
+-0.18321501 -0.75733002 0.1487
+-0.129625 -0.75866997 0.17889999
+
+-0.156665 -0.36923 0.42314999
+-0.116605 -0.52758999 0.38146999
+-0.137875 -0.2701 0.43911999
+
+-0.58818501 -0.35695 -0.06415
+-0.60820499 -0.28396 -0.08675
+-0.579235 -0.25250999 -0.13211
+
+-0.158205 -0.50859001 -0.11002
+-0.157915 -0.5673 -0.08973
+-0.178085 -0.52410999 -0.09604
+
+-0.438055 -0.66690002 0.44669998
+-0.406185 -0.64178001 0.44240002
+-0.43119499 -0.63069 0.39651001
+
+-0.437295 -0.37362999 0.41646999
+-0.50172501 -0.31013 0.42847
+-0.50455502 -0.31641001 0.42362999
+
+-0.56019501 -0.74653 0.0799
+-0.54426498 -0.71963997 0.10263
+-0.54181499 -0.69334 0.08588
+
+-0.019855 -0.37563999 0.55806
+-0.029985 -0.49078999 0.50139999
+-0.016705 -0.60248001 0.48320999
+
+-0.143465 -0.60214001 0.43403999
+-0.140305 -0.57868999 0.38641998
+-0.216555 -0.65108002 0.42185001
+
+0.046465 0.53513 -0.12086
+0.004935 0.49839001 -0.08707
+0.060495 0.54880001 -0.17709
+
+-0.32939499 -0.58321999 0.36421001
+-0.34806499 -0.62027 0.40410999
+-0.296705 -0.61009998 0.40333
+
+0.70712502 -0.44008999 0.28386
+0.74194504 -0.41438999 0.23629999
+0.70692497 -0.40130001 0.25292999
+
+-0.382085 -0.52368999 0.21750999
+-0.37405499 -0.52716 0.21347
+-0.360765 -0.53513 0.20674
+
+-0.236595 0.58076 0.04404
+-0.30827499 0.55255001 0.0553
+-0.354445 0.43800999 0.1358
+
+-0.18321501 -0.75733002 0.1487
+-0.252265 -0.76543999 0.06978
+-0.20473499 -0.76521004 0.06109
+
+-0.54181499 -0.69334 0.08588
+-0.502845 -0.67873001 0.11659
+-0.50359501 -0.65364998 0.07231
+
+-0.44044498 -0.72050003 0.46478001
+-0.40703499 -0.68030998 0.47273998
+-0.438055 -0.66690002 0.44669998
+
+-0.099435 -0.2215 -0.33507999
+-0.129445 -0.21128 -0.28048
+-0.068905 -0.17981001 -0.32354
+
+-0.44842499 -0.42519001 -0.09399
+-0.48772499 -0.47484001 -0.01301
+-0.51724499 -0.39648998 -0.08125
+
+-0.53066502 0.00663 -0.09101
+-0.48044498 -0.07672 -0.15554
+-0.59998501 -0.08147 -0.08608
+
+-0.143465 -0.60214001 0.43403999
+-0.16275499 -0.66514 0.49737
+-0.106135 -0.61624001 0.49498001
+
+-0.65054497 0.23882 0.51790001
+-0.66231499 0.29212999 0.47123001
+-0.68966499 0.23750999 0.48583
+
+-0.074085 -0.30458 0.55348
+-0.119785 -0.23910999 0.46998001
+-0.085865 -0.32016998 0.52319
+
+-0.551175 -0.15953 0.43046001
+-0.55939499 -0.21372999 0.42647999
+-0.44656502 -0.19707001 0.46938
+
+-0.419095 -0.61935001 0.07249
+-0.47767502 -0.65098999 0.02223
+-0.50359501 -0.65364998 0.07231
+
+-0.009275 -0.14155 0.52644001
+0.053405 -0.17601 0.57659
+0.079635 -0.11564 0.52494999
+
+-0.60025501 0.10649 -0.05573
+-0.67093498 0.16365 -0.02486
+-0.60123501 0.19448 -0.05578
+
+-0.068205 -0.24886999 0.56009998
+-0.075765 -0.16964001 0.4948
+-0.093355 -0.17006001 0.46999001
+
+-0.67091499 0.06852 0.50094002
+-0.648545 0.03328 0.48077
+-0.627995 0.04726 0.49209
+
+-0.71903503 -0.1047 0.21924999
+-0.69847504 -0.16400999 0.28132
+-0.70878502 -0.09154 0.23915001
+
+-0.60633499 0.29861 0.49606998
+-0.56956501 0.37901001 0.42835999
+-0.62565498 0.37287998 0.41800999
+
+-0.50359501 -0.65364998 0.07231
+-0.51823502 -0.66611 0.04218
+-0.54181499 -0.69334 0.08588
+
+-0.65526497 -0.16193001 0.33708
+-0.69847504 -0.16400999 0.28132
+-0.71858498 -0.18570999 0.23955999
+
+-0.009545 0.50974998 -0.05037
+0.046465 0.53513 -0.12086
+0.051805 0.5825 -0.15508
+
+-0.036705 -0.58948002 0.47154999
+-0.140305 -0.57868999 0.38641998
+-0.143465 -0.60214001 0.43403999
+
+-0.54181499 -0.69334 0.08588
+-0.54426498 -0.71963997 0.10263
+-0.502845 -0.67873001 0.11659
+
+-0.042595 -0.29021999 0.57817001
+-0.068205 -0.24886999 0.56009998
+-0.074085 -0.30458 0.55348
+
+-0.156565 -0.18361 0.45839001
+-0.206455 -0.16997 0.45382999
+-0.176625 -0.22690001 0.44397999
+
+-0.603685 0.00224 0.46230999
+-0.66449501 0.01509 0.45601002
+-0.58873501 -0.02668 0.38175999
+
+-0.35253502 -0.54191002 0.28164
+-0.35820499 -0.59717999 0.29188
+-0.354585 -0.59728001 0.33195
+
+-0.46994499 -0.66989998 0.39380001
+-0.49865501 -0.72585999 0.36729
+-0.47779499 -0.74220001 0.42571999
+
+-0.21126499 -0.66814003 0.43307999
+-0.16275499 -0.66514 0.49737
+-0.143465 -0.60214001 0.43403999
+
+-0.31935499 -0.27489 -0.19740999
+-0.249485 -0.24631001 -0.19802999
+-0.288985 -0.33368 -0.16805
+
+-0.65371498 -0.08158 0.31889
+-0.67527496 -0.04277 0.26872
+-0.70878502 -0.09154 0.23915001
+
+-0.124945 -0.75449997 0.44332001
+-0.204825 -0.74662003 0.45456001
+-0.17994499 -0.75432999 0.36115002
+
+-0.627995 0.04726 0.49209
+-0.58654499 0.0687 0.53747002
+-0.677295 0.16986 0.51804001
+
+-0.49940498 -0.74658997 0.33923
+-0.50058498 -0.72952003 0.32737999
+-0.47864498 -0.74934998 0.25862
+
+-0.69313499 0.39777 0.31554001
+-0.72732498 0.41339001 0.20645
+-0.74152496 0.38702 0.23667
+
+-0.56019501 -0.74653 0.0799
+-0.51762501 -0.76198997 0.10242
+-0.51126499 -0.75096001 0.14734
+
+-0.45942501 -0.75005997 0.21047001
+-0.54426498 -0.71963997 0.10263
+-0.51126499 -0.75096001 0.14734
+
+-0.19960501 -0.25952999 -0.2083
+-0.167955 -0.26533001 -0.23986
+-0.176745 -0.32091 -0.21965
+
+-0.69847504 -0.16400999 0.28132
+-0.65371498 -0.08158 0.31889
+-0.70878502 -0.09154 0.23915001
+
+0.031045 -0.48976002 0.55334
+0.093385 -0.48191002 0.57638
+0.053355 -0.41346001 0.56433998
+
+-0.109575 -0.27684 -0.3468
+-0.099435 -0.2215 -0.33507999
+-0.059835 -0.23341 -0.35984001
+
+-0.21126499 -0.66814003 0.43307999
+-0.143465 -0.60214001 0.43403999
+-0.216555 -0.65108002 0.42185001
+
+-0.33072498 -0.58639999 0.18187
+-0.386665 -0.56747002 0.10225
+-0.334715 -0.61401001 0.18212
+
+-0.66231499 0.29212999 0.47123001
+-0.60633499 0.29861 0.49606998
+-0.62565498 0.37287998 0.41800999
+
+-0.009275 -0.14155 0.52644001
+-0.075765 -0.16964001 0.4948
+-0.008315 -0.16797001 0.55435001
+
+-0.603685 0.00224 0.46230999
+-0.58873501 -0.02668 0.38175999
+-0.547775 -0.01096 0.39499001
+
+-0.65371498 -0.08158 0.31889
+-0.65526497 -0.16193001 0.33708
+-0.60681499 -0.05331 0.35605999
+
+-0.65054497 0.23882 0.51790001
+-0.60633499 0.29861 0.49606998
+-0.66231499 0.29212999 0.47123001
+
+-0.69313499 0.39777 0.31554001
+-0.71621498 0.319 0.37698002
+-0.68663498 0.30483 0.43856998
+
+-0.47904499 -0.33529999 -0.1591
+-0.42914501 -0.31971001 -0.17452999
+-0.458685 -0.37923 -0.13846
+
+-0.71858498 -0.18570999 0.23955999
+-0.71903503 -0.1047 0.21924999
+-0.72375504 -0.14514 0.19955999
+
+-0.40703499 -0.68030998 0.47273998
+-0.44044498 -0.72050003 0.46478001
+-0.40310501 -0.70723999 0.48404999
+
+-0.60681499 -0.05331 0.35605999
+-0.57050499 -0.03053 0.38844002
+-0.58873501 -0.02668 0.38175999
+
+-0.403615 -0.76533997 0.20007999
+-0.51762501 -0.76198997 0.10242
+-0.38783501 -0.76627998 0.13294
+
+-0.45211498 -0.74226997 0.21997999
+-0.502845 -0.67873001 0.11659
+-0.45942501 -0.75005997 0.21047001
+
+0.047165 0.73010002 -0.26747
+0.025515 0.74473999 -0.25292999
+0.008635 0.76769997 -0.20617001
+
+0.053525 -0.59877998 0.51932999
+0.031045 -0.48976002 0.55334
+-0.016705 -0.60248001 0.48320999
+
+-0.048255 0.52195999 -0.13641
+-0.027095 0.51598 -0.13203
+-0.212425 0.4907 -0.10495
+
+-0.35253502 -0.54191002 0.28164
+-0.34414501 -0.48889999 0.33360001
+-0.37079498 -0.49140999 0.28962999
+
+-0.019855 -0.37563999 0.55806
+-0.074085 -0.30458 0.55348
+-0.085865 -0.32016998 0.52319
+
+-0.39786499 0.47005001 0.10535
+-0.36813499 0.44145 0.14507
+-0.35580502 0.52299 0.06101
+
+-0.51762501 -0.76198997 0.10242
+-0.54935501 -0.75695999 0.01981
+-0.499095 -0.76375999 -0.05418
+
+-0.462365 -0.76483002 -0.06405
+-0.47702499 -0.74514 -0.06318
+-0.44606499 -0.76600998 -0.07796
+
+-0.68397499 0.00246 0.06858
+-0.72147499 0.057 0.05831
+-0.66189499 0.00042 0.02855
+
+-0.65526497 -0.16193001 0.33708
+-0.61961498 -0.25518 0.37487
+-0.61401501 -0.18775999 0.38139999
+
+-0.76316498 0.10037 0.37827
+-0.756325 0.07345 0.41839001
+-0.754655 0.10016 0.44153999
+
+-0.006605 -0.27245001 0.59221001
+0.043465 -0.23129 0.58570999
+-0.042475 -0.24874001 0.57685001
+
+-0.54426498 -0.71963997 0.10263
+-0.56019501 -0.74653 0.0799
+-0.51126499 -0.75096001 0.14734
+
+-0.50876499 -0.69231003 -0.00193
+-0.51823502 -0.66611 0.04218
+-0.47767502 -0.65098999 0.02223
+
+-0.056505 -0.75303001 -0.26643
+-0.176455 -0.76629997 -0.28367001
+-0.166175 -0.74779999 -0.29483
+
+-0.61401501 -0.18775999 0.38139999
+-0.551175 -0.15953 0.43046001
+-0.57303501 -0.09277 0.39316002
+
+-0.098815 -0.71488998 -0.14756
+-0.204055 -0.71999001 -0.05273
+-0.212265 -0.71635002 -0.05771
+
+-0.707295 0.05002 0.47198002
+-0.70310501 0.07475 0.49027
+-0.754655 0.10016 0.44153999
+
+0.51838501 -0.73889 0.11006
+0.51719501 -0.72348999 0.03903
+0.558475 -0.70769997 0.03611
+
+-0.386665 -0.56747002 0.10225
+-0.419095 -0.61935001 0.07249
+-0.38455502 -0.62816002 0.13858
+
+-0.176455 -0.76629997 -0.28367001
+-0.20123501 -0.75469002 -0.29017
+-0.166175 -0.74779999 -0.29483
+
+-0.297925 -0.53887001 -0.09417
+-0.34724499 -0.58544998 -0.05828
+-0.357915 -0.49792999 -0.07636
+
+-0.65526497 -0.16193001 0.33708
+-0.65677498 -0.28486 0.31427999
+-0.61961498 -0.25518 0.37487
+
+0.053405 -0.17601 0.57659
+0.136995 -0.12943 0.54544998
+0.079635 -0.11564 0.52494999
+
+-0.677295 0.16986 0.51804001
+-0.68966499 0.23750999 0.48583
+-0.74907501 0.12734 0.44921001
+
+-0.69313499 0.39777 0.31554001
+-0.68663498 0.30483 0.43856998
+-0.62565498 0.37287998 0.41800999
+
+-0.47614498 -0.66900002 0.34229
+-0.50058498 -0.72952003 0.32737999
+-0.49865501 -0.72585999 0.36729
+
+-0.60681499 -0.05331 0.35605999
+-0.61401501 -0.18775999 0.38139999
+-0.57303501 -0.09277 0.39316002
+
+-0.677295 0.16986 0.51804001
+-0.65234497 0.19790001 0.53490002
+-0.68966499 0.23750999 0.48583
+
+-0.73949501 0.19546 0.40769001
+-0.75975502 0.14085 0.40800999
+-0.74907501 0.12734 0.44921001
+
+-0.69313499 0.39777 0.31554001
+-0.74152496 0.38702 0.23667
+-0.71621498 0.319 0.37698002
+
+-0.036705 -0.58948002 0.47154999
+-0.096085 -0.45277 0.41069
+-0.118055 -0.56602001 0.3798
+
+-0.38455502 -0.62816002 0.13858
+-0.419095 -0.61935001 0.07249
+-0.50359501 -0.65364998 0.07231
+
+-0.157915 -0.5673 -0.08973
+-0.16779499 -0.59556999 -0.09223
+-0.24751499 -0.60999001 -0.0966
+
+0.458255 -0.43664001 -0.18388
+0.37158501 -0.45105999 -0.26129999
+0.42092499 -0.38223 -0.23412001
+
+-0.627995 0.04726 0.49209
+-0.677295 0.16986 0.51804001
+-0.67091499 0.06852 0.50094002
+
+-0.016705 -0.60248001 0.48320999
+0.023435 -0.61555 0.49417
+0.053525 -0.59877998 0.51932999
+
+-0.45211498 -0.74226997 0.21997999
+-0.404995 -0.67698997 0.19254
+-0.502845 -0.67873001 0.11659
+
+-0.33488499 -0.55792 0.17202
+-0.34746498 -0.54298 0.16158001
+-0.369095 -0.54116001 0.13157
+
+-0.363535 0.29777 0.01081
+-0.39040501 0.27885 -0.0233
+-0.352155 0.32740002 0.01621
+
+-0.36962502 -0.20292999 -0.20726999
+-0.32967499 -0.20312 -0.20150999
+-0.31935499 -0.27489 -0.19740999
+
+-0.51823502 -0.66611 0.04218
+-0.50876499 -0.69231003 -0.00193
+-0.547785 -0.71860001 0.02244
+
+-0.68966499 0.23750999 0.48583
+-0.73949501 0.19546 0.40769001
+-0.74907501 0.12734 0.44921001
+
+-0.68663498 0.30483 0.43856998
+-0.68966499 0.23750999 0.48583
+-0.66231499 0.29212999 0.47123001
+
+0.232845 0.19128 0.00246
+0.20192499 0.21209999 0.08168
+0.30644501 0.19247999 0.06287
+
+-0.58654499 0.0687 0.53747002
+-0.54655499 0.08835 0.54924999
+-0.59962502 0.11646 0.54145
+
+0.27865499 -0.11254 -0.21181999
+0.131915 -0.11946 -0.26507999
+0.074325 -0.09863 -0.22704
+
+-0.47443501 0.65209999 -0.59683998
+-0.44350498 0.63459 -0.59969002
+-0.44495499 0.61160999 -0.60196999
+
+-0.35253502 -0.54191002 0.28164
+-0.33072498 -0.58639999 0.18187
+-0.35820499 -0.59717999 0.29188
+
+-0.531875 0.43505001 -0.47442001
+-0.49435501 0.49361 -0.54973999
+-0.52519501 0.43825001 -0.48328999
+
+-0.56290501 0.68952003 -0.53467999
+-0.51963501 0.70806 -0.56443001
+-0.51469501 0.68051003 -0.57174
+
+-0.386665 -0.56747002 0.10225
+-0.33488499 -0.55792 0.17202
+-0.369095 -0.54116001 0.13157
+
+-0.47443501 0.65209999 -0.59683998
+-0.49175499 0.59293999 -0.57492001
+-0.51469501 0.68051003 -0.57174
+
+-0.597435 0.68508003 -0.47937
+-0.572925 0.70330002 -0.52133999
+-0.614175 0.66246002 -0.47494999
+
+-0.572925 0.70330002 -0.52133999
+-0.56290501 0.68952003 -0.53467999
+-0.614175 0.66246002 -0.47494999
+
+-0.57066502 0.53661999 -0.36436001
+-0.554105 0.60669998 -0.47487
+-0.53073502 0.52237 -0.47411999
+
+-0.49343498 0.53766998 -0.56959999
+-0.531875 0.43505001 -0.47442001
+-0.53073502 0.52237 -0.47411999
+
+-0.49175499 0.59293999 -0.57492001
+-0.49343498 0.53766998 -0.56959999
+-0.53073502 0.52237 -0.47411999
+
+-0.554105 0.60669998 -0.47487
+-0.49175499 0.59293999 -0.57492001
+-0.53073502 0.52237 -0.47411999
+
+-0.597435 0.68508003 -0.47937
+-0.614175 0.66246002 -0.47494999
+-0.579935 0.46213001 -0.01038
+
+-0.73949501 0.19546 0.40769001
+-0.68966499 0.23750999 0.48583
+-0.71621498 0.319 0.37698002
+
+-0.707295 0.05002 0.47198002
+-0.756325 0.07345 0.41839001
+-0.72276497 0.02686 0.4157
+
+-0.614175 0.66246002 -0.47494999
+-0.608685 0.60671001 -0.42444
+-0.62411499 0.60556 -0.39534
+
+-0.53415501 0.42109001 -0.44837002
+-0.53543499 0.41438 -0.43537998
+-0.54392502 0.40847 -0.42164001
+
+-0.614175 0.66246002 -0.47494999
+-0.56290501 0.68952003 -0.53467999
+-0.554105 0.60669998 -0.47487
+
+-0.73949501 0.19546 0.40769001
+-0.71621498 0.319 0.37698002
+-0.72876503 0.31882 0.31702
+
+-0.55925499 0.46678001 -0.32376999
+-0.57066502 0.53661999 -0.36436001
+-0.53073502 0.52237 -0.47411999
+
+-0.76541496 0.19517 0.23780001
+-0.773265 0.14032 0.25822001
+-0.76138496 0.14034 0.29812
+
+-0.54327499 0.39124001 -0.37567001
+-0.51723499 0.35522999 -0.21364
+-0.55800499 0.38182999 -0.29503
+
+-0.614175 0.66246002 -0.47494999
+-0.62411499 0.60556 -0.39534
+-0.579935 0.46213001 -0.01038
+
+-0.69847504 -0.16400999 0.28132
+-0.65526497 -0.16193001 0.33708
+-0.65371498 -0.08158 0.31889
+
+-0.614175 0.66246002 -0.47494999
+-0.554105 0.60669998 -0.47487
+-0.608685 0.60671001 -0.42444
+
+-0.574305 0.39730999 -0.30334999
+-0.55925499 0.46678001 -0.32376999
+-0.531875 0.43505001 -0.47442001
+
+-0.57066502 0.53661999 -0.36436001
+-0.608685 0.60671001 -0.42444
+-0.554105 0.60669998 -0.47487
+
+-0.35253502 -0.54191002 0.28164
+-0.35181499 -0.54046001 0.20204
+-0.33072498 -0.58639999 0.18187
+
+-0.608685 0.60671001 -0.42444
+-0.57066502 0.53661999 -0.36436001
+-0.61443501 0.52313 -0.27403999
+
+-0.68966499 0.23750999 0.48583
+-0.68663498 0.30483 0.43856998
+-0.71621498 0.319 0.37698002
+
+-0.382085 -0.52368999 0.21750999
+-0.360765 -0.53513 0.20674
+-0.35181499 -0.54046001 0.20204
+
+-0.54392502 0.40847 -0.42164001
+-0.574305 0.39730999 -0.30334999
+-0.531875 0.43505001 -0.47442001
+
+0.012615 -0.75335999 -0.24431999
+0.011285 -0.76453003 -0.22976
+-0.056505 -0.75303001 -0.26643
+
+0.091055 0.16486 -0.04745
+0.078115 0.18864 0.02789
+0.147815 0.19112 0.00398
+
+-0.57997501 0.39771 -0.2633
+-0.59004501 0.41210999 -0.14346
+-0.55925499 0.46678001 -0.32376999
+
+-0.71903503 -0.1047 0.21924999
+-0.69119499 -0.03813 0.21893999
+-0.69850502 -0.02457 0.14891
+
+-0.119055 -0.34823002 -0.33359001
+-0.150585 -0.30923 -0.29997999
+-0.109575 -0.27684 -0.3468
+
+-0.67527496 -0.04277 0.26872
+-0.67764503 0.00206 0.26896999
+-0.69119499 -0.03813 0.21893999
+
+-0.574305 0.39730999 -0.30334999
+-0.57806499 0.41137001 -0.27343
+-0.55925499 0.46678001 -0.32376999
+
+-0.47553501 -0.68308998 0.30209
+-0.50058498 -0.72952003 0.32737999
+-0.47614498 -0.66900002 0.34229
+
+-0.47553501 -0.68308998 0.30209
+-0.45884499 -0.68533997 0.2724
+-0.45761501 -0.71341003 0.26252001
+
+-0.178825 -0.39007 -0.16848
+-0.107915 -0.53838001 -0.23878
+-0.16091499 -0.46264999 -0.1489
+
+-0.089315 -0.30382 -0.35894001
+-0.119055 -0.34823002 -0.33359001
+-0.109575 -0.27684 -0.3468
+
+-0.131875 -0.22559999 -0.29035
+-0.109575 -0.27684 -0.3468
+-0.150585 -0.30923 -0.29997999
+
+-0.119055 -0.34823002 -0.33359001
+-0.099045 -0.37569 -0.34127998
+-0.089125 -0.40429001 -0.33634998
+
+-0.150585 -0.30923 -0.29997999
+-0.156355 -0.32272999 -0.27996
+-0.167955 -0.26533001 -0.23986
+
+-0.131875 -0.22559999 -0.29035
+-0.167955 -0.26533001 -0.23986
+-0.153045 -0.23818001 -0.25016001
+
+-0.150585 -0.30923 -0.29997999
+-0.167955 -0.26533001 -0.23986
+-0.131875 -0.22559999 -0.29035
+
+-0.129445 -0.21128 -0.28048
+-0.099435 -0.2215 -0.33507999
+-0.131875 -0.22559999 -0.29035
+
+-0.078115 -0.62351002 -0.25240999
+-0.117175 -0.61290001 -0.22316
+-0.058185 -0.59312 -0.27127001
+
+-0.18914499 -0.31829 -0.17997
+-0.156355 -0.32272999 -0.27996
+-0.178825 -0.39007 -0.16848
+
+-0.131875 -0.22559999 -0.29035
+-0.099435 -0.2215 -0.33507999
+-0.109575 -0.27684 -0.3468
+
+-0.105115 -0.16202 -0.24193001
+-0.199305 -0.2299 -0.22021999
+-0.229725 -0.20162001 -0.21724001
+
+-0.58244499 0.64759003 -0.39550999
+-0.55648499 0.57926998 -0.21315001
+-0.541525 0.60362999 -0.27988001
+
+-0.45441502 -0.64302002 0.36220001
+-0.47553501 -0.68308998 0.30209
+-0.47614498 -0.66900002 0.34229
+
+-0.74599503 0.0726 0.28837999
+-0.76138496 0.14034 0.29812
+-0.76094498 0.07262 0.24841
+
+0.232845 0.19128 0.00246
+0.23810499 0.17156 -0.03667
+0.147815 0.19112 0.00398
+
+-0.058185 -0.59312 -0.27127001
+-0.119055 -0.34823002 -0.33359001
+-0.028935 -0.47416 -0.34169998
+
+-0.156355 -0.32272999 -0.27996
+-0.176745 -0.32091 -0.21965
+-0.167955 -0.26533001 -0.23986
+
+0.17213499 -0.75156998 0.0888
+0.182815 -0.75714996 0.16868999
+0.141225 -0.72126999 0.18233999
+
+-0.271495 -0.75060997 -0.24094
+-0.264615 -0.75880997 -0.25176001
+-0.271465 -0.75859001 -0.23466
+
+-0.291175 -0.73332001 -0.18757
+-0.271465 -0.75859001 -0.23466
+-0.285585 -0.75900002 -0.19978001
+
+0.35907501 0.07059 -0.10795
+0.293955 0.09814 -0.1175
+0.32314499 0.16155001 -0.00588
+
+-0.25884501 -0.74322998 -0.26056
+-0.271495 -0.75060997 -0.24094
+-0.271465 -0.75859001 -0.23466
+
+-0.18914499 -0.31829 -0.17997
+-0.176745 -0.32091 -0.21965
+-0.156355 -0.32272999 -0.27996
+
+-0.55925499 0.46678001 -0.32376999
+-0.57806499 0.41137001 -0.27343
+-0.57997501 0.39771 -0.2633
+
+0.33996498 -0.09883 -0.20899
+0.36023499 -0.12728 -0.21188999
+0.27865499 -0.11254 -0.21181999
+
+-0.119055 -0.34823002 -0.33359001
+-0.049465 -0.37333 -0.3702
+-0.028935 -0.47416 -0.34169998
+
+-0.47767502 -0.65098999 0.02223
+-0.51823502 -0.66611 0.04218
+-0.50359501 -0.65364998 0.07231
+
+-0.72123497 0.26363001 0.29735001
+-0.74471497 0.23594 0.22754
+-0.76541496 0.19517 0.23780001
+
+-0.107915 -0.53838001 -0.23878
+-0.117175 -0.61290001 -0.22316
+-0.132525 -0.59215 -0.16823
+
+-0.57997501 0.39771 -0.2633
+-0.59239498 0.37070999 -0.07326
+-0.59004501 0.41210999 -0.14346
+
+-0.585895 0.42438999 -0.1235
+-0.61443501 0.52313 -0.27403999
+-0.57066502 0.53661999 -0.36436001
+
+-0.65177498 0.38554001 0.03709
+-0.65177498 0.41154999 0.04812
+-0.61525501 0.41305 0.00652
+
+0.016075 0.68472 -0.25462
+0.059645 0.68377998 -0.28246
+0.046245 0.64051003 -0.26128
+
+-0.249265 -0.69514999 -0.22771999
+-0.27567499 -0.69246002 -0.18768
+-0.228515 -0.64073997 -0.19774
+
+-0.27567499 -0.69246002 -0.18768
+-0.249265 -0.69514999 -0.22771999
+-0.25884501 -0.74322998 -0.26056
+
+-0.27567499 -0.69246002 -0.18768
+-0.291175 -0.73332001 -0.18757
+-0.30734501 -0.71100998 -0.10559
+
+0.074325 -0.09863 -0.22704
+0.131915 -0.11946 -0.26507999
+0.059725 -0.12592 -0.27848
+
+-0.45884499 -0.68533997 0.2724
+-0.41561501 -0.69004997 0.22243999
+-0.45761501 -0.71341003 0.26252001
+
+-0.41561501 -0.69004997 0.22243999
+-0.45884499 -0.68533997 0.2724
+-0.39039501 -0.65042 0.25218
+
+-0.27567499 -0.69246002 -0.18768
+-0.271465 -0.75859001 -0.23466
+-0.291175 -0.73332001 -0.18757
+
+-0.107915 -0.53838001 -0.23878
+-0.132525 -0.59215 -0.16823
+-0.158205 -0.50859001 -0.11002
+
+-0.57997501 0.39771 -0.2633
+-0.55800499 0.38182999 -0.29503
+-0.51723499 0.35522999 -0.21364
+
+-0.59004501 0.41210999 -0.14346
+-0.585895 0.42438999 -0.1235
+-0.55925499 0.46678001 -0.32376999
+
+-0.156355 -0.32272999 -0.27996
+-0.150585 -0.30923 -0.29997999
+-0.107915 -0.53838001 -0.23878
+
+-0.73949501 0.19546 0.40769001
+-0.72123497 0.26363001 0.29735001
+-0.76541496 0.19517 0.23780001
+
+-0.291175 -0.73332001 -0.18757
+-0.285585 -0.75900002 -0.19978001
+-0.31505501 -0.76257004 -0.12831
+
+-0.69706497 0.27559999 0.04741
+-0.73406502 0.22117001 0.0777
+-0.685625 0.31711 0.06703
+
+-0.069995 -0.13285 -0.23166
+-0.105115 -0.16202 -0.24193001
+-0.229725 -0.20162001 -0.21724001
+
+-0.42884499 -0.63210999 0.34209
+-0.45884499 -0.68533997 0.2724
+-0.47553501 -0.68308998 0.30209
+
+-0.67165497 0.20761999 -0.01075
+-0.62156502 0.28177999 -0.03207
+-0.60123501 0.19448 -0.05578
+
+-0.051545 0.75455002 -0.12812
+-0.126565 0.67811996 -0.13629
+-0.29095501 0.58248001 -0.04404
+
+0.40085499 0.10826 -0.02869
+0.35907501 0.07059 -0.10795
+0.32314499 0.16155001 -0.00588
+
+-0.60170502 0.42654999 -0.05351
+-0.61443501 0.52313 -0.27403999
+-0.585895 0.42438999 -0.1235
+
+-0.073375 0.61046001 -0.18223
+-0.23320499 0.5352 -0.10464
+-0.18282499 0.59498001 -0.13044
+
+-0.30734501 -0.71100998 -0.10559
+-0.31505501 -0.76257004 -0.12831
+-0.30720501 -0.73987999 -0.10804
+
+-0.38455502 -0.62816002 0.13858
+-0.404995 -0.67698997 0.19254
+-0.35919498 -0.65380997 0.20221001
+
+-0.45761501 -0.71341003 0.26252001
+-0.41561501 -0.69004997 0.22243999
+-0.45211498 -0.74226997 0.21997999
+
+-0.72732498 0.41339001 0.20645
+-0.66683502 0.43922001 0.22899
+-0.67873497 0.42423 0.10789
+
+-0.132525 -0.59215 -0.16823
+-0.157915 -0.5673 -0.08973
+-0.158205 -0.50859001 -0.11002
+
+-0.105115 -0.16202 -0.24193001
+-0.069995 -0.13285 -0.23166
+-0.068905 -0.17981001 -0.32354
+
+0.68443497 -0.45104 0.0037
+0.72394501 -0.43584999 0.02906
+0.73838501 -0.45884998 0.0331
+
+-0.44044498 -0.72050003 0.46478001
+-0.438055 -0.66690002 0.44669998
+-0.47779499 -0.74220001 0.42571999
+
+-0.76541496 0.19517 0.23780001
+-0.77828499 0.14011 0.20802999
+-0.773265 0.14032 0.25822001
+
+-0.72123497 0.26363001 0.29735001
+-0.72876503 0.31882 0.31702
+-0.74582497 0.34598999 0.25691
+
+-0.30734501 -0.71100998 -0.10559
+-0.291175 -0.73332001 -0.18757
+-0.31505501 -0.76257004 -0.12831
+
+0.33996498 -0.09883 -0.20899
+0.359175 -0.0197 -0.15061
+0.38315498 -0.105 -0.19958
+
+-0.585895 0.42438999 -0.1235
+-0.57066502 0.53661999 -0.36436001
+-0.55925499 0.46678001 -0.32376999
+
+-0.59239498 0.37070999 -0.07326
+-0.595065 0.41257 -0.06351
+-0.585895 0.42438999 -0.1235
+
+-0.124945 -0.75449997 0.44332001
+-0.17994499 -0.75432999 0.36115002
+-0.163815 -0.75672997 0.40183998
+
+-0.18686501 0.0498 -0.14299
+-0.24480499 0.12143 -0.09801
+-0.138675 0.11073 -0.06666
+
+-0.238545 -0.76138 0.28424
+-0.21356501 -0.75926003 0.30533001
+-0.17994499 -0.75432999 0.36115002
+
+-0.77015503 0.16722 0.17794001
+-0.77828499 0.14011 0.20802999
+-0.76541496 0.19517 0.23780001
+
+-0.74152496 0.38702 0.23667
+-0.72876503 0.31882 0.31702
+-0.71621498 0.319 0.37698002
+
+0.42197498 -0.58331001 -0.20099001
+0.44724499 -0.56456001 -0.18232
+0.45115501 -0.60699001 -0.15207
+
+0.293955 0.09814 -0.1175
+0.23810499 0.17156 -0.03667
+0.32314499 0.16155001 -0.00588
+
+0.069325 0.57973999 -0.17223
+0.075975 0.58987 -0.22885
+0.080755 0.61445999 -0.2476
+
+-0.72665497 -0.19900999 0.19982
+-0.72375504 -0.14514 0.19955999
+-0.72489502 -0.13198 0.11954
+
+-0.54156502 0.29757 -0.05975
+-0.58929501 0.35665001 -0.05348
+-0.54577499 0.32955002 -0.08891
+
+-0.69841499 -0.28159 0.17025999
+-0.67019501 -0.33046001 0.17235001
+-0.67350502 -0.31801001 0.21348
+
+-0.46518501 0.44868 0.07372
+-0.50223499 0.44608002 0.02426
+-0.559795 0.4541 0.06169
+
+-0.47553501 -0.68308998 0.30209
+-0.45761501 -0.71341003 0.26252001
+-0.47838501 -0.72314003 0.26280001
+
+-0.41858501 0.32521999 -0.01536
+-0.47262501 0.31153 -0.0592
+-0.468335 0.32449001 -0.06341
+
+-0.468335 0.32449001 -0.06341
+-0.45510502 0.35847 -0.05053
+-0.44820499 0.36980999 -0.02461
+
+0.50467499 -0.54449001 -0.10164
+0.50317501 -0.58196999 -0.06143
+0.45115501 -0.60699001 -0.15207
+
+-0.76541496 0.19517 0.23780001
+-0.74471497 0.23594 0.22754
+-0.722985 0.29028 0.13737
+
+-0.69119499 -0.03813 0.21893999
+-0.70774498 0.00346 0.16879
+-0.69850502 -0.02457 0.14891
+
+-0.595065 0.41257 -0.06351
+-0.60170502 0.42654999 -0.05351
+-0.585895 0.42438999 -0.1235
+
+-0.35820499 -0.59717999 0.29188
+-0.35919498 -0.65380997 0.20221001
+-0.39039501 -0.65042 0.25218
+
+-0.574305 0.39730999 -0.30334999
+-0.55800499 0.38182999 -0.29503
+-0.57806499 0.41137001 -0.27343
+
+-0.76316498 0.10037 0.37827
+-0.754655 0.10016 0.44153999
+-0.75975502 0.14085 0.40800999
+
+-0.70689499 -0.24051001 0.17004999
+-0.69344498 -0.26929001 0.08014
+-0.69841499 -0.28159 0.17025999
+
+-0.59004501 0.41210999 -0.14346
+-0.59239498 0.37070999 -0.07326
+-0.585895 0.42438999 -0.1235
+
+-0.438055 -0.66690002 0.44669998
+-0.46994499 -0.66989998 0.39380001
+-0.47779499 -0.74220001 0.42571999
+
+-0.38455502 -0.62816002 0.13858
+-0.502845 -0.67873001 0.11659
+-0.404995 -0.67698997 0.19254
+
+0.51719501 -0.72348999 0.03903
+0.38144501 -0.72870003 -0.01149
+0.40176498 -0.71222 -0.03167
+
+0.36023499 -0.12728 -0.21188999
+0.44883499 -0.17316 -0.18752001
+0.35949501 -0.21177999 -0.24714001
+
+-0.131875 -0.22559999 -0.29035
+-0.153045 -0.23818001 -0.25016001
+-0.129445 -0.21128 -0.28048
+
+0.259195 0.02269 -0.176
+0.293955 0.09814 -0.1175
+0.35907501 0.07059 -0.10795
+
+0.125885 -0.16028999 -0.32228001
+0.059725 -0.12592 -0.27848
+0.131915 -0.11946 -0.26507999
+
+-0.141615 -0.76162003 0.1249
+-0.129625 -0.75866997 0.17889999
+-0.18321501 -0.75733002 0.1487
+
+-0.60820499 -0.28396 -0.08675
+-0.68001503 -0.24351 -0.00998
+-0.660215 -0.19101 -0.05073
+
+0.68647499 -0.58339001 -0.0017
+0.72791496 -0.59351002 0.06742
+0.67858498 -0.64014999 0.05778
+
+0.49725498 0.02933 -0.02307
+0.587925 -0.08729 0.02727
+0.53067501 -0.0586 -0.06884
+
+-0.60820499 -0.28396 -0.08675
+-0.58818501 -0.35695 -0.06415
+-0.63365501 -0.34187 -0.01984
+
+-0.57005501 0.04798 -0.05057
+-0.59998501 -0.08147 -0.08608
+-0.67421501 -0.09452 -0.01072
+
+-0.040395 -0.02881 -0.20667999
+0.005765 0.04376 -0.15766
+0.027045 -0.06751 -0.21985001
+
+-0.019805 -0.26032 -0.37293999
+0.040165 -0.24620001 -0.37231998
+-0.009285 -0.35868999 -0.37393002
+
+-0.60170502 0.42654999 -0.05351
+-0.614795 0.37119999 -0.013
+-0.61525501 0.41305 0.00652
+
+-0.42247501 -0.65561996 -0.03636
+-0.40218498 -0.59438999 0.01163
+-0.36709499 -0.61487 -0.04815
+
+0.52969501 -0.24299 -0.15367
+0.42092499 -0.38223 -0.23412001
+0.45040501 -0.27245001 -0.20267
+
+-0.68001503 -0.24351 -0.00998
+-0.71519501 -0.22723 0.07012
+-0.68935501 -0.17514999 0.00979
+
+-0.67421501 -0.09452 -0.01072
+-0.68397499 0.00246 0.06858
+-0.66189499 0.00042 0.02855
+
+-0.18686501 0.0498 -0.14299
+-0.138675 0.11073 -0.06666
+-0.060175 0.08937 -0.1052
+
+0.179445 0.04258 -0.17731001
+0.093325 0.13007 -0.09003
+0.232995 0.12265 -0.10369
+
+-0.60170502 0.42654999 -0.05351
+-0.595065 0.41257 -0.06351
+-0.59239498 0.37070999 -0.07326
+
+-0.59239498 0.37070999 -0.07326
+-0.58929501 0.35665001 -0.05348
+-0.614795 0.37119999 -0.013
+
+-0.61525501 0.41305 0.00652
+-0.579935 0.46213001 -0.01038
+-0.60170502 0.42654999 -0.05351
+
+-0.121325 0.14207 0.02081
+0.078115 0.18864 0.02789
+-0.014785 0.14532 -0.02397
+
+-0.19960501 -0.25952999 -0.2083
+-0.176745 -0.32091 -0.21965
+-0.19938499 -0.27365 -0.20799
+
+-0.18686501 0.0498 -0.14299
+-0.116545 0.01205 -0.16351999
+-0.190415 -0.01619 -0.18384001
+
+0.42092499 -0.38223 -0.23412001
+0.370625 -0.38014999 -0.26396999
+0.261315 -0.36248001 -0.31499001
+
+-0.36254501 -0.75091003 -0.10707
+-0.27737499 -0.63951 -0.09283
+-0.30734501 -0.71100998 -0.10559
+
+-0.39643501 -0.51195999 -0.00889
+-0.357915 -0.49792999 -0.07636
+-0.34724499 -0.58544998 -0.05828
+
+-0.58818501 -0.35695 -0.06415
+-0.51724499 -0.39648998 -0.08125
+-0.59931499 -0.38535999 -0.00934
+
+-0.63365501 -0.34187 -0.01984
+-0.59931499 -0.38535999 -0.00934
+-0.63462502 -0.37513 0.05758
+
+-0.59998501 -0.08147 -0.08608
+-0.59406502 -0.18136 -0.12044
+-0.660215 -0.19101 -0.05073
+
+-0.72147499 0.057 0.05831
+-0.75427498 0.12566 0.09816
+-0.69932503 0.13755 -0.00205
+
+-0.65177498 0.38554001 0.03709
+-0.614795 0.37119999 -0.013
+-0.62156502 0.28177999 -0.03207
+
+-0.55648499 0.57926998 -0.21315001
+-0.579935 0.46213001 -0.01038
+-0.53754501 0.46978001 -0.00341
+
+-0.55925499 0.46678001 -0.32376999
+-0.53073502 0.52237 -0.47411999
+-0.531875 0.43505001 -0.47442001
+
+-0.68935501 -0.17514999 0.00979
+-0.67421501 -0.09452 -0.01072
+-0.660215 -0.19101 -0.05073
+
+0.67144501 -0.41029999 0.26914
+0.57196499 -0.49865002 0.31608
+0.64346497 -0.49037998 0.32360001
+
+-0.572925 0.70330002 -0.52133999
+-0.597435 0.68508003 -0.47937
+-0.543125 0.70637001 -0.51022999
+
+-0.75975502 0.14085 0.40800999
+-0.73949501 0.19546 0.40769001
+-0.76138496 0.14034 0.29812
+
+-0.50876499 -0.69231003 -0.00193
+-0.52946499 -0.75737999 -0.02987
+-0.547785 -0.71860001 0.02244
+
+-0.67421501 -0.09452 -0.01072
+-0.70828499 -0.11964 0.0597
+-0.72112503 -0.09155 0.13937
+
+-0.69026497 0.08918 0.00135
+-0.60025501 0.10649 -0.05573
+-0.57005501 0.04798 -0.05057
+
+-0.67421501 -0.09452 -0.01072
+-0.72112503 -0.09155 0.13937
+-0.68397499 0.00246 0.06858
+
+-0.72147499 0.057 0.05831
+-0.69026497 0.08918 0.00135
+-0.66189499 0.00042 0.02855
+
+-0.72147499 0.057 0.05831
+-0.73905502 0.04444 0.0987
+-0.75427498 0.12566 0.09816
+
+-0.72147499 0.057 0.05831
+-0.69932503 0.13755 -0.00205
+-0.69026497 0.08918 0.00135
+
+-0.65177498 0.38554001 0.03709
+-0.61525501 0.41305 0.00652
+-0.614795 0.37119999 -0.013
+
+-0.61525501 0.41305 0.00652
+-0.65177498 0.41154999 0.04812
+-0.59834499 0.43923 0.01644
+
+-0.40209499 -0.53867001 0.05158
+-0.39643501 -0.51195999 -0.00889
+-0.40218498 -0.59438999 0.01163
+
+-0.41205502 -0.60668999 0.06219
+-0.386665 -0.56747002 0.10225
+-0.40209499 -0.53867001 0.05158
+
+-0.59931499 -0.38535999 -0.00934
+-0.63365501 -0.34187 -0.01984
+-0.58818501 -0.35695 -0.06415
+
+-0.60820499 -0.28396 -0.08675
+-0.63365501 -0.34187 -0.01984
+-0.68001503 -0.24351 -0.00998
+
+-0.69026497 0.08918 0.00135
+-0.57005501 0.04798 -0.05057
+-0.66189499 0.00042 0.02855
+
+-0.69026497 0.08918 0.00135
+-0.67093498 0.16365 -0.02486
+-0.60025501 0.10649 -0.05573
+
+-0.65177498 0.38554001 0.03709
+-0.62156502 0.28177999 -0.03207
+-0.685625 0.31711 0.06703
+
+-0.547785 -0.71860001 0.02244
+-0.54181499 -0.69334 0.08588
+-0.51823502 -0.66611 0.04218
+
+-0.60820499 -0.28396 -0.08675
+-0.660215 -0.19101 -0.05073
+-0.59406502 -0.18136 -0.12044
+
+-0.67290497 -0.32478001 0.06036
+-0.63365501 -0.34187 -0.01984
+-0.63462502 -0.37513 0.05758
+
+-0.72112503 -0.09155 0.13937
+-0.69850502 -0.02457 0.14891
+-0.68397499 0.00246 0.06858
+
+-0.72976501 0.37284 0.12714
+-0.65177498 0.38554001 0.03709
+-0.69845497 0.34506001 0.09724
+
+-0.47767502 -0.65098999 0.02223
+-0.47012501 -0.68793999 -0.04621
+-0.50606499 -0.70516998 -0.03412
+
+-0.47767502 -0.65098999 0.02223
+-0.41205502 -0.60668999 0.06219
+-0.42247501 -0.65561996 -0.03636
+
+-0.40218498 -0.59438999 0.01163
+-0.42247501 -0.65561996 -0.03636
+-0.41205502 -0.60668999 0.06219
+
+-0.59931499 -0.38535999 -0.00934
+-0.57057499 -0.43936001 0.05637
+-0.63462502 -0.37513 0.05758
+
+-0.69344498 -0.26929001 0.08014
+-0.63365501 -0.34187 -0.01984
+-0.67290497 -0.32478001 0.06036
+
+-0.59998501 -0.08147 -0.08608
+-0.660215 -0.19101 -0.05073
+-0.67421501 -0.09452 -0.01072
+
+-0.73949501 0.19546 0.40769001
+-0.72876503 0.31882 0.31702
+-0.72123497 0.26363001 0.29735001
+
+-0.47767502 -0.65098999 0.02223
+-0.42247501 -0.65561996 -0.03636
+-0.47012501 -0.68793999 -0.04621
+
+-0.47767502 -0.65098999 0.02223
+-0.419095 -0.61935001 0.07249
+-0.41205502 -0.60668999 0.06219
+
+-0.47012501 -0.68793999 -0.04621
+-0.42247501 -0.65561996 -0.03636
+-0.27737499 -0.63951 -0.09283
+
+-0.41205502 -0.60668999 0.06219
+-0.419095 -0.61935001 0.07249
+-0.386665 -0.56747002 0.10225
+
+-0.41275501 -0.52455002 0.07158
+-0.40209499 -0.53867001 0.05158
+-0.386665 -0.56747002 0.10225
+
+-0.39643501 -0.51195999 -0.00889
+-0.36709499 -0.61487 -0.04815
+-0.40218498 -0.59438999 0.01163
+
+-0.67421501 -0.09452 -0.01072
+-0.68935501 -0.17514999 0.00979
+-0.70828499 -0.11964 0.0597
+
+-0.73905502 0.04444 0.0987
+-0.72147499 0.057 0.05831
+-0.68397499 0.00246 0.06858
+
+0.073585 0.64028999 -0.27017
+0.080755 0.61445999 -0.2476
+0.075455 0.60136002 -0.24311001
+
+0.091085 -0.00535 -0.20563999
+0.074325 -0.09863 -0.22704
+0.027045 -0.06751 -0.21985001
+
+0.239765 -0.07146 -0.19552
+0.20949499 8e-05 -0.18802999
+0.259195 0.02269 -0.176
+
+-0.445825 0.62064999 -0.60304001
+-0.45517502 0.62153999 -0.60337002
+-0.44350498 0.63459 -0.59969002
+
+-0.47443501 0.65209999 -0.59683998
+-0.44495499 0.61160999 -0.60196999
+-0.49343498 0.53766998 -0.56959999
+
+-0.44495499 0.61160999 -0.60196999
+-0.445825 0.62064999 -0.60304001
+-0.439925 0.61355999 -0.59553001
+
+0.44600498 -0.11718 -0.16657
+0.53613499 -0.09893 -0.08599
+0.57723499 -0.16372999 -0.05665
+
+-0.44219501 0.62398998 -0.59071999
+-0.439925 0.61355999 -0.59553001
+-0.44350498 0.63459 -0.59969002
+
+-0.124945 -0.75449997 0.44332001
+-0.088955 -0.75287003 0.51883999
+-0.167295 -0.74737 0.49738998
+
+0.35907501 0.07059 -0.10795
+0.40085499 0.10826 -0.02869
+0.47436501 0.00685 -0.07925
+
+0.23810499 0.17156 -0.03667
+0.093325 0.13007 -0.09003
+0.091055 0.16486 -0.04745
+
+0.027045 -0.06751 -0.21985001
+0.069925 0.02503 -0.17805
+0.091085 -0.00535 -0.20563999
+
+0.35907501 0.07059 -0.10795
+0.47436501 0.00685 -0.07925
+0.47198502 -0.04777 -0.12069
+
+0.200805 -0.34676998 -0.33601002
+0.290415 -0.22259001 -0.29337
+0.261315 -0.36248001 -0.31499001
+
+-0.20724501 -0.69445999 -0.26997999
+-0.25884501 -0.74322998 -0.26056
+-0.249265 -0.69514999 -0.22771999
+
+0.222605 -0.71620003 -0.04485
+0.18418501 -0.71306999 -0.11163
+0.231395 -0.71984001 -0.09604
+
+0.53613499 -0.09893 -0.08599
+0.47198502 -0.04777 -0.12069
+0.53067501 -0.0586 -0.06884
+
+0.47198502 -0.04777 -0.12069
+0.38315498 -0.105 -0.19958
+0.359175 -0.0197 -0.15061
+
+0.44600498 -0.11718 -0.16657
+0.53496498 -0.20222 -0.13642
+0.44883499 -0.17316 -0.18752001
+
+0.72512497 -0.40280998 0.05526
+0.68443497 -0.45104 0.0037
+0.66293503 -0.39085999 0.06263
+
+0.40085499 0.10826 -0.02869
+0.45834499 0.08214 0.00486
+0.47436501 0.00685 -0.07925
+
+0.59800499 -0.28384001 -0.03253
+0.47530499 -0.39273998 -0.18283001
+0.56855499 -0.27214001 -0.1024
+
+0.54107498 -0.55365002 -0.04656
+0.56943501 -0.51193001 -0.02993
+0.58218498 -0.58167 -0.0532
+
+0.69163498 -0.37717999 0.08836
+0.64561501 -0.37198002 0.10372
+0.70884499 -0.36710999 0.13567
+
+-0.106075 0.15324 0.06919
+-0.121325 0.14207 0.02081
+-0.221775 0.16362 -0.02269
+
+0.52969501 -0.24299 -0.15367
+0.56855499 -0.27214001 -0.1024
+0.47530499 -0.39273998 -0.18283001
+
+-0.27737499 -0.63951 -0.09283
+-0.233095 -0.62811001 -0.12729
+-0.27567499 -0.69246002 -0.18768
+
+-0.015555 0.06388 -0.13874
+0.069925 0.02503 -0.17805
+0.005765 0.04376 -0.15766
+
+0.44600498 -0.11718 -0.16657
+0.47198502 -0.04777 -0.12069
+0.53613499 -0.09893 -0.08599
+
+0.091085 -0.00535 -0.20563999
+0.153225 0.01244 -0.18492001
+0.239765 -0.07146 -0.19552
+
+-0.43739498 0.45532001 0.06203
+-0.39786499 0.47005001 0.10535
+-0.35580502 0.52299 0.06101
+
+-0.000905 -0.16063999 -0.32273998
+-0.019895 -0.21881001 -0.36255001
+-0.068905 -0.17981001 -0.32354
+
+0.595695 -0.19973 -0.04273
+0.56855499 -0.27214001 -0.1024
+0.55953499 -0.19656 -0.10231
+
+0.47198502 -0.04777 -0.12069
+0.44600498 -0.11718 -0.16657
+0.38315498 -0.105 -0.19958
+
+0.27865499 -0.11254 -0.21181999
+0.290105 -0.15098 -0.25101999
+0.22540501 -0.15247 -0.28954
+
+0.078115 0.18864 0.02789
+0.20192499 0.21209999 0.08168
+0.147815 0.19112 0.00398
+
+0.45834499 0.08214 0.00486
+0.49725498 0.02933 -0.02307
+0.47436501 0.00685 -0.07925
+
+-0.40865501 0.45254002 0.17395
+-0.39786499 0.47005001 0.10535
+-0.43739498 0.45532001 0.06203
+
+0.57723499 -0.16372999 -0.05665
+0.595695 -0.19973 -0.04273
+0.55953499 -0.19656 -0.10231
+
+0.027045 -0.06751 -0.21985001
+0.005765 0.04376 -0.15766
+0.069925 0.02503 -0.17805
+
+-0.40747501 0.47915001 0.0356
+-0.29095501 0.58248001 -0.04404
+-0.330975 0.52471001 -0.03259
+
+0.74167503 -0.40138 0.07409
+0.69163498 -0.37717999 0.08836
+0.70884499 -0.36710999 0.13567
+
+0.35907501 0.07059 -0.10795
+0.47198502 -0.04777 -0.12069
+0.359175 -0.0197 -0.15061
+
+-0.138675 0.11073 -0.06666
+-0.266325 0.15101 -0.06886
+-0.221775 0.16362 -0.02269
+
+-0.41858501 0.32521999 -0.01536
+-0.468335 0.32449001 -0.06341
+-0.44820499 0.36980999 -0.02461
+
+-0.50223499 0.44608002 0.02426
+-0.46518501 0.44868 0.07372
+-0.46452499 0.41841999 0.00315
+
+-0.46518501 0.44868 0.07372
+-0.43739498 0.45532001 0.06203
+-0.46452499 0.41841999 0.00315
+
+0.23810499 0.17156 -0.03667
+0.232845 0.19128 0.00246
+0.32314499 0.16155001 -0.00588
+
+0.74167503 -0.40138 0.07409
+0.70884499 -0.36710999 0.13567
+0.72733498 -0.37303001 0.14242
+
+0.756455 -0.42445 0.07686
+0.77457497 -0.49212002 0.10691
+0.757565 -0.47983002 0.05688
+
+-0.44713501 0.41133999 0.01059
+-0.47220501 0.42382 -0.00262
+-0.46452499 0.41841999 0.00315
+
+-0.51963501 0.70806 -0.56443001
+-0.48884499 0.70297997 -0.56327
+-0.49433498 0.69546997 -0.58514
+
+-0.462285 0.43570999 -0.09058
+-0.497005 0.44953999 -0.01774
+-0.47220501 0.42382 -0.00262
+
+0.23810499 0.17156 -0.03667
+0.091055 0.16486 -0.04745
+0.147815 0.19112 0.00398
+
+-0.44713501 0.41133999 0.01059
+-0.46452499 0.41841999 0.00315
+-0.43739498 0.45532001 0.06203
+
+0.002175 -0.65117996 -0.26294001
+-0.056505 -0.75303001 -0.26643
+-0.166175 -0.74779999 -0.29483
+
+-0.113155 -0.72134003 0.07626
+-0.123175 -0.72098999 0.07391
+-0.125935 -0.71977997 0.05414
+
+0.72512497 -0.40280998 0.05526
+0.72394501 -0.43584999 0.02906
+0.68443497 -0.45104 0.0037
+
+-0.069995 -0.13285 -0.23166
+-0.000905 -0.16063999 -0.32273998
+-0.068905 -0.17981001 -0.32354
+
+-0.126565 0.67811996 -0.13629
+-0.18282499 0.59498001 -0.13044
+-0.29095501 0.58248001 -0.04404
+
+-0.107665 -0.74504997 0.54255001
+-0.119005 -0.73551003 0.54847
+-0.167295 -0.74737 0.49738998
+
+-0.121325 0.14207 0.02081
+-0.014785 0.14532 -0.02397
+-0.138675 0.11073 -0.06666
+
+-0.59239498 0.37070999 -0.07326
+-0.57997501 0.39771 -0.2633
+-0.54886501 0.33823002 -0.12392
+
+-0.47220501 0.42382 -0.00262
+-0.50223499 0.44608002 0.02426
+-0.46452499 0.41841999 0.00315
+
+-0.44713501 0.41133999 0.01059
+-0.40245499 0.42946999 0.00582
+-0.401735 0.37047001 -0.00194
+
+0.761605 -0.39966999 0.14054
+0.756455 -0.42445 0.07686
+0.74167503 -0.40138 0.07409
+
+-0.060175 0.08937 -0.1052
+-0.015555 0.06388 -0.13874
+0.005765 0.04376 -0.15766
+
+-0.117175 -0.61290001 -0.22316
+-0.17661501 -0.63981998 -0.23927999
+-0.132525 -0.59215 -0.16823
+
+-0.40747501 0.47915001 0.0356
+-0.40245499 0.42946999 0.00582
+-0.44713501 0.41133999 0.01059
+
+-0.41858501 0.32521999 -0.01536
+-0.39040501 0.27885 -0.0233
+-0.47262501 0.31153 -0.0592
+
+0.239765 -0.07146 -0.19552
+0.153225 0.01244 -0.18492001
+0.20949499 8e-05 -0.18802999
+
+-0.000905 -0.16063999 -0.32273998
+0.125885 -0.16028999 -0.32228001
+0.061575 -0.19306999 -0.34928001
+
+0.040165 -0.24620001 -0.37231998
+0.061575 -0.19306999 -0.34928001
+0.125885 -0.16028999 -0.32228001
+
+-0.43526501 0.09176 -0.08455
+-0.31862499 0.11157 -0.10718
+-0.38056499 0.02471 -0.15193
+
+-0.27737499 -0.63951 -0.09283
+-0.27567499 -0.69246002 -0.18768
+-0.30734501 -0.71100998 -0.10559
+
+-0.116545 0.01205 -0.16351999
+-0.105925 -0.01889 -0.19115
+-0.140345 -0.05789 -0.20672001
+
+0.091085 -0.00535 -0.20563999
+0.069925 0.02503 -0.17805
+0.093325 0.13007 -0.09003
+
+-0.18686501 0.0498 -0.14299
+-0.060175 0.08937 -0.1052
+-0.116545 0.01205 -0.16351999
+
+-0.014785 0.14532 -0.02397
+0.093325 0.13007 -0.09003
+-0.015555 0.06388 -0.13874
+
+-0.49363499 0.44341 -0.49014
+-0.46016499 0.52960999 -0.57521999
+-0.47018501 0.48946999 -0.51748001
+
+-0.140345 -0.05789 -0.20672001
+-0.069995 -0.13285 -0.23166
+-0.160285 -0.07244 -0.20541
+
+0.73838501 -0.45884998 0.0331
+0.757565 -0.47983002 0.05688
+0.701595 -0.51362999 -0.01377
+
+-0.44782501 0.38021 -0.01581
+-0.401735 0.37047001 -0.00194
+-0.41858501 0.32521999 -0.01536
+
+-0.014785 0.14532 -0.02397
+0.091055 0.16486 -0.04745
+0.093325 0.13007 -0.09003
+
+0.49725498 0.02933 -0.02307
+0.45834499 0.08214 0.00486
+0.51815498 0.03883 0.06995
+
+-0.116545 0.01205 -0.16351999
+0.005765 0.04376 -0.15766
+-0.105925 -0.01889 -0.19115
+
+0.44883499 -0.17316 -0.18752001
+0.45040501 -0.27245001 -0.20267
+0.420485 -0.22735001 -0.22077999
+
+0.005765 0.04376 -0.15766
+-0.040395 -0.02881 -0.20667999
+-0.105925 -0.01889 -0.19115
+
+-0.019895 -0.21881001 -0.36255001
+-0.059835 -0.23341 -0.35984001
+-0.068905 -0.17981001 -0.32354
+
+-0.65677498 -0.28486 0.31427999
+-0.65526497 -0.16193001 0.33708
+-0.71858498 -0.18570999 0.23955999
+
+0.259195 0.02269 -0.176
+0.35907501 0.07059 -0.10795
+0.359175 -0.0197 -0.15061
+
+-0.49433498 0.69546997 -0.58514
+-0.47443501 0.65209999 -0.59683998
+-0.51469501 0.68051003 -0.57174
+
+-0.20724501 -0.69445999 -0.26997999
+-0.249265 -0.69514999 -0.22771999
+-0.228515 -0.64073997 -0.19774
+
+-0.17661501 -0.63981998 -0.23927999
+-0.152975 -0.66613998 -0.27448999
+-0.20724501 -0.69445999 -0.26997999
+
+0.62454498 -0.39271999 0.04435
+0.63150501 -0.32306999 0.09721
+0.64561501 -0.37198002 0.10372
+
+0.72512497 -0.40280998 0.05526
+0.69163498 -0.37717999 0.08836
+0.74167503 -0.40138 0.07409
+
+-0.31862499 0.11157 -0.10718
+-0.266325 0.15101 -0.06886
+-0.24480499 0.12143 -0.09801
+
+-0.051545 0.75455002 -0.12812
+-0.247845 0.62541 -0.03466
+-0.075495 0.73363998 -0.09516
+
+0.56855499 -0.27214001 -0.1024
+0.52969501 -0.24299 -0.15367
+0.55953499 -0.19656 -0.10231
+
+-0.34418499 0.18421 -0.02241
+-0.301705 0.19448999 0.02741
+-0.266325 0.15101 -0.06886
+
+-0.17661501 -0.63981998 -0.23927999
+-0.228515 -0.64073997 -0.19774
+-0.132525 -0.59215 -0.16823
+
+-0.74042503 0.40042999 0.17667999
+-0.72976501 0.37284 0.12714
+-0.74736504 0.31806 0.17700001
+
+-0.329715 0.31518 0.05937
+-0.30900499 0.25450001 0.12933
+-0.32405499 0.22228001 0.01714
+
+0.72394501 -0.43584999 0.02906
+0.756455 -0.42445 0.07686
+0.73838501 -0.45884998 0.0331
+
+-0.31862499 0.11157 -0.10718
+-0.18686501 0.0498 -0.14299
+-0.35469501 0.06252 -0.13541
+
+-0.43526501 0.09176 -0.08455
+-0.38056499 0.02471 -0.15193
+-0.47079498 0.02284 -0.11794
+
+0.232845 0.19128 0.00246
+0.147815 0.19112 0.00398
+0.20192499 0.21209999 0.08168
+
+-0.30900499 0.25450001 0.12933
+-0.28657499 0.21525999 0.16419001
+-0.295275 0.20636 0.05543
+
+-0.32405499 0.22228001 0.01714
+-0.30900499 0.25450001 0.12933
+-0.295275 0.20636 0.05543
+
+-0.32405499 0.22228001 0.01714
+-0.301705 0.19448999 0.02741
+-0.34418499 0.18421 -0.02241
+
+-0.43526501 0.09176 -0.08455
+-0.43113499 0.13668 -0.06854
+-0.34418499 0.18421 -0.02241
+
+-0.116545 0.01205 -0.16351999
+-0.140345 -0.05789 -0.20672001
+-0.160285 -0.07244 -0.20541
+
+-0.329715 0.31518 0.05937
+-0.32405499 0.22228001 0.01714
+-0.363535 0.29777 0.01081
+
+-0.31862499 0.11157 -0.10718
+-0.24480499 0.12143 -0.09801
+-0.18686501 0.0498 -0.14299
+
+0.44600498 -0.11718 -0.16657
+0.57723499 -0.16372999 -0.05665
+0.53496498 -0.20222 -0.13642
+
+-0.122175 -0.71571999 0.37543999
+-0.126875 -0.71792 0.35866001
+-0.100605 -0.71330002 0.37792
+
+-0.301705 0.19448999 0.02741
+-0.32405499 0.22228001 0.01714
+-0.295275 0.20636 0.05543
+
+0.074325 -0.09863 -0.22704
+0.059725 -0.12592 -0.27848
+-0.000905 -0.16063999 -0.32273998
+
+0.57723499 -0.16372999 -0.05665
+0.53613499 -0.09893 -0.08599
+0.53067501 -0.0586 -0.06884
+
+0.611035 -0.42883999 0.02128
+0.62454498 -0.39271999 0.04435
+0.66293503 -0.39085999 0.06263
+
+0.72512497 -0.40280998 0.05526
+0.66293503 -0.39085999 0.06263
+0.69163498 -0.37717999 0.08836
+
+0.68443497 -0.45104 0.0037
+0.611035 -0.42883999 0.02128
+0.66293503 -0.39085999 0.06263
+
+0.435765 -0.49491001 -0.21247999
+0.44975498 -0.50793999 -0.1924
+0.391745 -0.56583 -0.23886999
+
+-0.31862499 0.11157 -0.10718
+-0.35469501 0.06252 -0.13541
+-0.38056499 0.02471 -0.15193
+
+-0.44141499 0.60801998 -0.58164001
+-0.43966499 0.60813999 -0.59201
+-0.44219501 0.62398998 -0.59071999
+
+0.232995 0.12265 -0.10369
+0.23810499 0.17156 -0.03667
+0.293955 0.09814 -0.1175
+
+0.078115 0.18864 0.02789
+0.147305 0.21093 0.16179001
+0.20192499 0.21209999 0.08168
+
+-0.18686501 0.0498 -0.14299
+-0.190415 -0.01619 -0.18384001
+-0.38056499 0.02471 -0.15193
+
+-0.18686501 0.0498 -0.14299
+-0.38056499 0.02471 -0.15193
+-0.35469501 0.06252 -0.13541
+
+0.078115 0.18864 0.02789
+-0.025365 0.17524 0.11324
+0.147305 0.21093 0.16179001
+
+0.078115 0.18864 0.02789
+0.091055 0.16486 -0.04745
+-0.014785 0.14532 -0.02397
+
+-0.121325 0.14207 0.02081
+-0.106075 0.15324 0.06919
+-0.025365 0.17524 0.11324
+
+0.47436501 0.00685 -0.07925
+0.53067501 -0.0586 -0.06884
+0.47198502 -0.04777 -0.12069
+
+-0.301705 0.19448999 0.02741
+-0.221775 0.16362 -0.02269
+-0.266325 0.15101 -0.06886
+
+-0.38056499 0.02471 -0.15193
+-0.190415 -0.01619 -0.18384001
+-0.310175 -0.08771 -0.20037001
+
+0.293955 0.09814 -0.1175
+0.179445 0.04258 -0.17731001
+0.232995 0.12265 -0.10369
+
+-0.31862499 0.11157 -0.10718
+-0.43526501 0.09176 -0.08455
+-0.34418499 0.18421 -0.02241
+
+-0.45953499 0.45066002 -0.34074001
+-0.44885502 0.48257999 -0.32057999
+-0.44795502 0.48275002 -0.23052
+
+0.53067501 -0.0586 -0.06884
+0.47436501 0.00685 -0.07925
+0.49725498 0.02933 -0.02307
+
+-0.17661501 -0.63981998 -0.23927999
+-0.20724501 -0.69445999 -0.26997999
+-0.228515 -0.64073997 -0.19774
+
+0.074325 -0.09863 -0.22704
+-0.000905 -0.16063999 -0.32273998
+-0.069995 -0.13285 -0.23166
+
+0.069925 0.02503 -0.17805
+-0.015555 0.06388 -0.13874
+0.093325 0.13007 -0.09003
+
+-0.016475 0.76692001 -0.19555
+-0.006815 0.77167 -0.18312
+0.008635 0.76769997 -0.20617001
+
+0.28848499 -0.13418 -0.22884001
+0.36023499 -0.12728 -0.21188999
+0.35949501 -0.21177999 -0.24714001
+
+0.69163498 -0.37717999 0.08836
+0.66293503 -0.39085999 0.06263
+0.64561501 -0.37198002 0.10372
+
+-0.47012501 -0.68793999 -0.04621
+-0.420145 -0.75016998 -0.08755
+-0.47702499 -0.74514 -0.06318
+
+0.153225 0.01244 -0.18492001
+0.091085 -0.00535 -0.20563999
+0.093325 0.13007 -0.09003
+
+0.293955 0.09814 -0.1175
+0.259195 0.02269 -0.176
+0.179445 0.04258 -0.17731001
+
+-0.138675 0.11073 -0.06666
+-0.24480499 0.12143 -0.09801
+-0.266325 0.15101 -0.06886
+
+0.27865499 -0.11254 -0.21181999
+0.28848499 -0.13418 -0.22884001
+0.290105 -0.15098 -0.25101999
+
+0.44883499 -0.17316 -0.18752001
+0.420485 -0.22735001 -0.22077999
+0.35949501 -0.21177999 -0.24714001
+
+0.093325 0.13007 -0.09003
+0.23810499 0.17156 -0.03667
+0.232995 0.12265 -0.10369
+
+-0.21356501 -0.75926003 0.30533001
+-0.21439501 -0.74724998 0.25917999
+-0.17445499 -0.76107002 0.26183001
+
+-0.42247501 -0.65561996 -0.03636
+-0.36709499 -0.61487 -0.04815
+-0.27737499 -0.63951 -0.09283
+
+-0.083505 0.68447998 -0.17287001
+-0.126565 0.67811996 -0.13629
+-0.016475 0.76692001 -0.19555
+
+0.42092499 -0.38223 -0.23412001
+0.261315 -0.36248001 -0.31499001
+0.290415 -0.22259001 -0.29337
+
+0.66293503 -0.39085999 0.06263
+0.62454498 -0.39271999 0.04435
+0.64561501 -0.37198002 0.10372
+
+-0.44782501 0.38021 -0.01581
+-0.47220501 0.42382 -0.00262
+-0.44713501 0.41133999 0.01059
+
+-0.016475 0.76692001 -0.19555
+-0.126565 0.67811996 -0.13629
+-0.051545 0.75455002 -0.12812
+
+-0.016475 0.76692001 -0.19555
+-0.051545 0.75455002 -0.12812
+-0.006815 0.77167 -0.18312
+
+-0.060175 0.08937 -0.1052
+-0.014785 0.14532 -0.02397
+-0.015555 0.06388 -0.13874
+
+0.179445 0.04258 -0.17731001
+0.153225 0.01244 -0.18492001
+0.093325 0.13007 -0.09003
+
+-0.33072498 -0.58639999 0.18187
+-0.34688499 -0.54231998 0.18309999
+-0.33488499 -0.55792 0.17202
+
+0.140395 -0.26084999 -0.35778
+0.100535 -0.31684999 -0.36356998
+0.040165 -0.24620001 -0.37231998
+
+0.22540501 -0.15247 -0.28954
+0.125885 -0.16028999 -0.32228001
+0.131915 -0.11946 -0.26507999
+
+-0.25884501 -0.74322998 -0.26056
+-0.262125 -0.75611 -0.24801001
+-0.271495 -0.75060997 -0.24094
+
+-0.058185 -0.59312 -0.27127001
+-0.107915 -0.53838001 -0.23878
+-0.119055 -0.34823002 -0.33359001
+
+-0.238545 -0.76138 0.28424
+-0.257085 -0.75538002 0.41583
+-0.33710499 -0.76268997 0.2824
+
+-0.57065498 0.15109 -0.06724
+-0.550975 0.20959 -0.06745
+-0.501245 0.20993999 -0.07225
+
+-0.46016499 0.52960999 -0.57521999
+-0.440755 0.59640999 -0.59333
+-0.44630501 0.55679001 -0.57491001
+
+0.701595 -0.51362999 -0.01377
+0.757565 -0.47983002 0.05688
+0.74039497 -0.56462002 0.06716
+
+-0.52043499 0.07819 -0.06974
+-0.60025501 0.10649 -0.05573
+-0.57065498 0.15109 -0.06724
+
+-0.41327499 -0.49464001 -0.01295
+-0.388325 -0.45629002 -0.06645
+-0.357915 -0.49792999 -0.07636
+
+-0.51851501 -0.35137001 -0.13174
+-0.58818501 -0.35695 -0.06415
+-0.579235 -0.25250999 -0.13211
+
+-0.19824499 -0.74849998 0.24569
+-0.189415 -0.75043999 0.19530001
+-0.17445499 -0.76107002 0.26183001
+
+0.58218498 -0.58167 -0.0532
+0.66172501 -0.52612 -0.03485
+0.63202499 -0.59748001 -0.03384
+
+-0.48044498 -0.07672 -0.15554
+-0.430355 -0.10442 -0.17239
+-0.40962502 -0.24707001 -0.19660999
+
+0.102645 -0.75471001 -0.22798
+0.18262501 -0.73998001 -0.2282
+0.269445 -0.75794998 -0.18476999
+
+-0.113155 -0.72134003 0.07626
+-0.125935 -0.71977997 0.05414
+-0.139575 -0.71986 0.03333
+
+-0.501245 0.20993999 -0.07225
+-0.550975 0.20959 -0.06745
+-0.60123501 0.19448 -0.05578
+
+-0.57147499 0.29725 -0.05187
+-0.60123501 0.19448 -0.05578
+-0.62156502 0.28177999 -0.03207
+
+-0.34418499 0.18421 -0.02241
+-0.39040501 0.27885 -0.0233
+-0.32405499 0.22228001 0.01714
+
+0.68443497 -0.45104 0.0037
+0.73838501 -0.45884998 0.0331
+0.701595 -0.51362999 -0.01377
+
+0.66172501 -0.52612 -0.03485
+0.68647499 -0.58339001 -0.0017
+0.63202499 -0.59748001 -0.03384
+
+-0.52043499 0.07819 -0.06974
+-0.57065498 0.15109 -0.06724
+-0.501245 0.20993999 -0.07225
+
+-0.57057499 -0.43936001 0.05637
+-0.51724499 -0.39648998 -0.08125
+-0.48772499 -0.47484001 -0.01301
+
+-0.51851501 -0.35137001 -0.13174
+-0.51724499 -0.39648998 -0.08125
+-0.58818501 -0.35695 -0.06415
+
+0.59227501 -0.64189003 -0.02401
+0.63202499 -0.59748001 -0.03384
+0.63273499 -0.64609001 0.00875
+
+0.54107498 -0.55365002 -0.04656
+0.51241501 -0.64007004 -0.04479
+0.50317501 -0.58196999 -0.06143
+
+0.56943501 -0.51193001 -0.02993
+0.66172501 -0.52612 -0.03485
+0.58218498 -0.58167 -0.0532
+
+-0.41327499 -0.49464001 -0.01295
+-0.44842499 -0.42519001 -0.09399
+-0.388325 -0.45629002 -0.06645
+
+-0.48044498 -0.07672 -0.15554
+-0.47079498 0.02284 -0.11794
+-0.38056499 0.02471 -0.15193
+
+-0.176455 -0.76629997 -0.28367001
+-0.056505 -0.75303001 -0.26643
+0.011285 -0.76453003 -0.22976
+
+-0.501245 0.20993999 -0.07225
+-0.57147499 0.29725 -0.05187
+-0.52155499 0.29777 -0.06353
+
+-0.41327499 -0.49464001 -0.01295
+-0.48772499 -0.47484001 -0.01301
+-0.44842499 -0.42519001 -0.09399
+
+-0.58929501 0.35665001 -0.05348
+-0.59239498 0.37070999 -0.07326
+-0.54577499 0.32955002 -0.08891
+
+-0.420145 -0.75016998 -0.08755
+-0.44606499 -0.76600998 -0.07796
+-0.47702499 -0.74514 -0.06318
+
+-0.166565 -0.76378998 0.10376
+-0.152885 -0.76372002 0.12453
+-0.18321501 -0.75733002 0.1487
+
+0.51241501 -0.64007004 -0.04479
+0.54107498 -0.55365002 -0.04656
+0.58218498 -0.58167 -0.0532
+
+0.558475 -0.70769997 0.03611
+0.522575 -0.68685997 -0.0156
+0.59227501 -0.64189003 -0.02401
+
+0.58218498 -0.58167 -0.0532
+0.63202499 -0.59748001 -0.03384
+0.59227501 -0.64189003 -0.02401
+
+0.44320499 -0.65613998 -0.05025
+0.39260502 -0.67114998 -0.11193
+0.45115501 -0.60699001 -0.15207
+
+-0.47904499 -0.33529999 -0.1591
+-0.48954498 -0.24917 -0.17212999
+-0.39932499 -0.27525 -0.19733
+
+-0.249485 -0.24631001 -0.19802999
+-0.19938499 -0.27365 -0.20799
+-0.18914499 -0.31829 -0.17997
+
+-0.266325 0.15101 -0.06886
+-0.31862499 0.11157 -0.10718
+-0.34418499 0.18421 -0.02241
+
+-0.579235 -0.25250999 -0.13211
+-0.59406502 -0.18136 -0.12044
+-0.48954498 -0.24917 -0.17212999
+
+0.58218498 -0.58167 -0.0532
+0.59227501 -0.64189003 -0.02401
+0.51241501 -0.64007004 -0.04479
+
+0.56943501 -0.51193001 -0.02993
+0.66172501 -0.51227001 -0.03209
+0.66172501 -0.52612 -0.03485
+
+-0.39932499 -0.27525 -0.19733
+-0.42914501 -0.31971001 -0.17452999
+-0.47904499 -0.33529999 -0.1591
+
+-0.42914501 -0.31971001 -0.17452999
+-0.40871498 -0.39304001 -0.14109
+-0.458685 -0.37923 -0.13846
+
+-0.48954498 -0.24917 -0.17212999
+-0.48044498 -0.07672 -0.15554
+-0.39932499 -0.27525 -0.19733
+
+-0.57147499 0.29725 -0.05187
+-0.501245 0.20993999 -0.07225
+-0.60123501 0.19448 -0.05578
+
+-0.47904499 -0.33529999 -0.1591
+-0.51851501 -0.35137001 -0.13174
+-0.579235 -0.25250999 -0.13211
+
+-0.47702499 -0.74514 -0.06318
+-0.50606499 -0.70516998 -0.03412
+-0.47012501 -0.68793999 -0.04621
+
+0.522575 -0.68685997 -0.0156
+0.51241501 -0.64007004 -0.04479
+0.59227501 -0.64189003 -0.02401
+
+-0.49433498 0.69546997 -0.58514
+-0.48884499 0.70297997 -0.56327
+-0.47459499 0.69324997 -0.58602001
+
+0.44320499 -0.65613998 -0.05025
+0.45115501 -0.60699001 -0.15207
+0.50317501 -0.58196999 -0.06143
+
+-0.006815 0.77167 -0.18312
+-0.051545 0.75455002 -0.12812
+-0.036455 0.74396004 -0.12342
+
+-0.190415 -0.01619 -0.18384001
+-0.229725 -0.20162001 -0.21724001
+-0.310175 -0.08771 -0.20037001
+
+-0.44350498 0.63459 -0.59969002
+-0.47443501 0.65209999 -0.59683998
+-0.457075 0.67668999 -0.58800999
+
+-0.49175499 0.59293999 -0.57492001
+-0.554105 0.60669998 -0.47487
+-0.51469501 0.68051003 -0.57174
+
+0.51719501 -0.72348999 0.03903
+0.40176498 -0.71222 -0.03167
+0.522575 -0.68685997 -0.0156
+
+-0.57005501 0.04798 -0.05057
+-0.53066502 0.00663 -0.09101
+-0.59998501 -0.08147 -0.08608
+
+0.073435 -0.62984001 0.4934
+-0.044845 -0.65685997 0.5468
+0.065805 -0.69416 0.51382
+
+0.420485 -0.22735001 -0.22077999
+0.45040501 -0.27245001 -0.20267
+0.42092499 -0.38223 -0.23412001
+
+0.35949501 -0.21177999 -0.24714001
+0.420485 -0.22735001 -0.22077999
+0.290415 -0.22259001 -0.29337
+
+-0.554105 0.60669998 -0.47487
+-0.56290501 0.68952003 -0.53467999
+-0.51469501 0.68051003 -0.57174
+
+-0.47079498 0.02284 -0.11794
+-0.53066502 0.00663 -0.09101
+-0.43526501 0.09176 -0.08455
+
+-0.190415 -0.01619 -0.18384001
+-0.160285 -0.07244 -0.20541
+-0.229725 -0.20162001 -0.21724001
+
+-0.199305 -0.2299 -0.22021999
+-0.19960501 -0.25952999 -0.2083
+-0.19938499 -0.27365 -0.20799
+
+-0.264615 -0.75880997 -0.25176001
+-0.271495 -0.75060997 -0.24094
+-0.262125 -0.75611 -0.24801001
+
+-0.43739498 0.45532001 0.06203
+-0.40747501 0.47915001 0.0356
+-0.44713501 0.41133999 0.01059
+
+-0.34724499 -0.58544998 -0.05828
+-0.24751499 -0.60999001 -0.0966
+-0.27737499 -0.63951 -0.09283
+
+-0.24751499 -0.60999001 -0.0966
+-0.34724499 -0.58544998 -0.05828
+-0.297925 -0.53887001 -0.09417
+
+-0.39643501 -0.51195999 -0.00889
+-0.41327499 -0.49464001 -0.01295
+-0.357915 -0.49792999 -0.07636
+
+0.44320499 -0.65613998 -0.05025
+0.51241501 -0.64007004 -0.04479
+0.522575 -0.68685997 -0.0156
+
+-0.31935499 -0.27489 -0.19740999
+-0.288985 -0.33368 -0.16805
+-0.37912498 -0.31878 -0.18186001
+
+-0.330975 0.52471001 -0.03259
+-0.29095501 0.58248001 -0.04404
+-0.18282499 0.59498001 -0.13044
+
+0.53496498 -0.20222 -0.13642
+0.52969501 -0.24299 -0.15367
+0.44883499 -0.17316 -0.18752001
+
+-0.229725 -0.20162001 -0.21724001
+-0.249485 -0.24631001 -0.19802999
+-0.32967499 -0.20312 -0.20150999
+
+-0.40871498 -0.39304001 -0.14109
+-0.328545 -0.40797001 -0.12829
+-0.388325 -0.45629002 -0.06645
+
+-0.420145 -0.75016998 -0.08755
+-0.418405 -0.76513 -0.09148
+-0.43560501 -0.76556 -0.07625
+
+0.44883499 -0.17316 -0.18752001
+0.52969501 -0.24299 -0.15367
+0.45040501 -0.27245001 -0.20267
+
+-0.18914499 -0.31829 -0.17997
+-0.19886499 -0.37626999 -0.16464001
+-0.288985 -0.33368 -0.16805
+
+-0.39932499 -0.27525 -0.19733
+-0.31935499 -0.27489 -0.19740999
+-0.37912498 -0.31878 -0.18186001
+
+-0.222955 -0.69486 0.43347
+-0.21126499 -0.66814003 0.43307999
+-0.216555 -0.65108002 0.42185001
+
+-0.264615 -0.75880997 -0.25176001
+-0.25884501 -0.74322998 -0.26056
+-0.249135 -0.76183998 -0.26459
+
+-0.029335 -0.10314 0.45814999
+0.035725 -0.09047 0.45244999
+0.043555 0.01225 0.43209
+
+0.251465 -0.18408001 -0.29662001
+0.290105 -0.15098 -0.25101999
+0.35949501 -0.21177999 -0.24714001
+
+0.004935 0.49839001 -0.08707
+-0.084295 0.46479 -0.01832
+-0.112925 0.44946999 -0.01904
+
+0.458255 -0.43664001 -0.18388
+0.44975498 -0.50793999 -0.1924
+0.435765 -0.49491001 -0.21247999
+
+-0.36709499 -0.61487 -0.04815
+-0.39643501 -0.51195999 -0.00889
+-0.34724499 -0.58544998 -0.05828
+
+-0.47443501 0.65209999 -0.59683998
+-0.49343498 0.53766998 -0.56959999
+-0.49175499 0.59293999 -0.57492001
+
+0.382645 -0.65669998 -0.17177999
+0.42197498 -0.58331001 -0.20099001
+0.45115501 -0.60699001 -0.15207
+
+0.259195 0.02269 -0.176
+0.30606501 -0.05008 -0.17846001
+0.239765 -0.07146 -0.19552
+
+0.558475 -0.70769997 0.03611
+0.67858498 -0.64014999 0.05778
+0.59101501 -0.70407997 0.1113
+
+0.37158501 -0.45105999 -0.26129999
+0.370625 -0.38014999 -0.26396999
+0.42092499 -0.38223 -0.23412001
+
+-0.073375 0.61046001 -0.18223
+-0.212425 0.4907 -0.10495
+-0.23320499 0.5352 -0.10464
+
+-0.34724499 -0.58544998 -0.05828
+-0.27737499 -0.63951 -0.09283
+-0.36709499 -0.61487 -0.04815
+
+-0.328545 -0.40797001 -0.12829
+-0.26883499 -0.37657001 -0.16448
+-0.297925 -0.53887001 -0.09417
+
+-0.31717501 -0.73977997 -0.10929
+-0.30720501 -0.73987999 -0.10804
+-0.31505501 -0.76257004 -0.12831
+
+0.435765 -0.49491001 -0.21247999
+0.37158501 -0.45105999 -0.26129999
+0.458255 -0.43664001 -0.18388
+
+0.42092499 -0.38223 -0.23412001
+0.52969501 -0.24299 -0.15367
+0.47530499 -0.39273998 -0.18283001
+
+-0.36962502 -0.20292999 -0.20726999
+-0.39932499 -0.27525 -0.19733
+-0.40962502 -0.24707001 -0.19660999
+
+-0.238365 -0.47976002 -0.11273
+-0.178085 -0.52410999 -0.09604
+-0.157915 -0.5673 -0.08973
+
+0.45115501 -0.60699001 -0.15207
+0.39260502 -0.67114998 -0.11193
+0.382645 -0.65669998 -0.17177999
+
+0.261315 -0.36248001 -0.31499001
+0.37158501 -0.45105999 -0.26129999
+0.251075 -0.40532001 -0.30648001
+
+0.37158501 -0.45105999 -0.26129999
+0.35170502 -0.52154999 -0.26212999
+0.251075 -0.40532001 -0.30648001
+
+-0.52669498 0.41201 -0.43175999
+-0.515135 0.41865002 -0.44709
+-0.54327499 0.39124001 -0.37567001
+
+-0.50876499 -0.69231003 -0.00193
+-0.50606499 -0.70516998 -0.03412
+-0.52946499 -0.75737999 -0.02987
+
+0.372915 -0.65777 -0.19226999
+0.36238499 -0.61118 -0.21527
+0.382645 -0.65669998 -0.17177999
+
+0.391745 -0.56583 -0.23886999
+0.42197498 -0.58331001 -0.20099001
+0.36238499 -0.61118 -0.21527
+
+0.36023499 -0.12728 -0.21188999
+0.33996498 -0.09883 -0.20899
+0.38315498 -0.105 -0.19958
+
+0.322565 -0.66830002 -0.22158001
+0.22237499 -0.68262001 -0.22483
+0.292015 -0.59245998 -0.26313
+
+0.36238499 -0.61118 -0.21527
+0.372915 -0.65777 -0.19226999
+0.322565 -0.66830002 -0.22158001
+
+0.292015 -0.59245998 -0.26313
+0.391745 -0.56583 -0.23886999
+0.36238499 -0.61118 -0.21527
+
+0.37158501 -0.45105999 -0.26129999
+0.391745 -0.56583 -0.23886999
+0.35170502 -0.52154999 -0.26212999
+
+0.458255 -0.43664001 -0.18388
+0.42092499 -0.38223 -0.23412001
+0.47530499 -0.39273998 -0.18283001
+
+-0.26883499 -0.37657001 -0.16448
+-0.328545 -0.40797001 -0.12829
+-0.288985 -0.33368 -0.16805
+
+-0.56290501 0.68952003 -0.53467999
+-0.572925 0.70330002 -0.52133999
+-0.51963501 0.70806 -0.56443001
+
+-0.328545 -0.40797001 -0.12829
+-0.297925 -0.53887001 -0.09417
+-0.388325 -0.45629002 -0.06645
+
+0.391745 -0.56583 -0.23886999
+0.33190498 -0.54949001 -0.26895
+0.35170502 -0.52154999 -0.26212999
+
+0.37158501 -0.45105999 -0.26129999
+0.435765 -0.49491001 -0.21247999
+0.391745 -0.56583 -0.23886999
+
+-0.522085 0.42964001 -0.46967999
+-0.531875 0.43505001 -0.47442001
+-0.52519501 0.43825001 -0.48328999
+
+0.372915 -0.65777 -0.19226999
+0.32443501 -0.74949997 -0.15917
+0.302465 -0.72740997 -0.204
+
+0.611035 -0.42883999 0.02128
+0.68443497 -0.45104 0.0037
+0.66172501 -0.51227001 -0.03209
+
+0.66172501 -0.52612 -0.03485
+0.701595 -0.51362999 -0.01377
+0.68647499 -0.58339001 -0.0017
+
+-0.36254501 -0.75091003 -0.10707
+-0.30734501 -0.71100998 -0.10559
+-0.31717501 -0.73977997 -0.10929
+
+0.42092499 -0.38223 -0.23412001
+0.290415 -0.22259001 -0.29337
+0.420485 -0.22735001 -0.22077999
+
+0.251465 -0.18408001 -0.29662001
+0.35949501 -0.21177999 -0.24714001
+0.290415 -0.22259001 -0.29337
+
+0.292015 -0.59245998 -0.26313
+0.22237499 -0.68262001 -0.22483
+0.19210501 -0.62008999 -0.27941999
+
+0.56943501 -0.51193001 -0.02993
+0.611035 -0.42883999 0.02128
+0.66172501 -0.51227001 -0.03209
+
+0.30606501 -0.05008 -0.17846001
+0.359175 -0.0197 -0.15061
+0.33996498 -0.09883 -0.20899
+
+0.251465 -0.18408001 -0.29662001
+0.290415 -0.22259001 -0.29337
+0.200305 -0.22082001 -0.32242001
+
+-0.67093498 0.16365 -0.02486
+-0.69026497 0.08918 0.00135
+-0.69932503 0.13755 -0.00205
+
+0.290105 -0.15098 -0.25101999
+0.251465 -0.18408001 -0.29662001
+0.22540501 -0.15247 -0.28954
+
+-0.212425 0.4907 -0.10495
+-0.34072498 0.34067001 0.0194
+-0.312335 0.41512001 -0.03359
+
+-0.000905 -0.16063999 -0.32273998
+0.059725 -0.12592 -0.27848
+0.125885 -0.16028999 -0.32228001
+
+-0.233095 -0.62811001 -0.12729
+-0.228515 -0.64073997 -0.19774
+-0.27567499 -0.69246002 -0.18768
+
+-0.44219501 0.62398998 -0.59071999
+-0.44350498 0.63459 -0.59969002
+-0.457075 0.67668999 -0.58800999
+
+-0.019895 -0.21881001 -0.36255001
+0.040165 -0.24620001 -0.37231998
+-0.019805 -0.26032 -0.37293999
+
+0.292015 -0.59245998 -0.26313
+0.33190498 -0.54949001 -0.26895
+0.391745 -0.56583 -0.23886999
+
+-0.27737499 -0.63951 -0.09283
+-0.24751499 -0.60999001 -0.0966
+-0.233095 -0.62811001 -0.12729
+
+-0.42914501 -0.31971001 -0.17452999
+-0.37912498 -0.31878 -0.18186001
+-0.40871498 -0.39304001 -0.14109
+
+-0.40245499 0.42946999 0.00582
+-0.330975 0.52471001 -0.03259
+-0.23320499 0.5352 -0.10464
+
+0.241845 -0.57674 -0.28339001
+0.211805 -0.50487 -0.30047001
+0.33190498 -0.54949001 -0.26895
+
+0.211805 -0.50487 -0.30047001
+0.241845 -0.57674 -0.28339001
+0.21181499 -0.56279999 -0.28535
+
+0.211805 -0.50487 -0.30047001
+0.35170502 -0.52154999 -0.26212999
+0.33190498 -0.54949001 -0.26895
+
+0.251075 -0.40532001 -0.30648001
+0.35170502 -0.52154999 -0.26212999
+0.211805 -0.50487 -0.30047001
+
+0.239765 -0.07146 -0.19552
+0.33996498 -0.09883 -0.20899
+0.27865499 -0.11254 -0.21181999
+
+0.322565 -0.66830002 -0.22158001
+0.292015 -0.59245998 -0.26313
+0.36238499 -0.61118 -0.21527
+
+0.239765 -0.07146 -0.19552
+0.30606501 -0.05008 -0.17846001
+0.33996498 -0.09883 -0.20899
+
+0.322565 -0.66830002 -0.22158001
+0.372915 -0.65777 -0.19226999
+0.302465 -0.72740997 -0.204
+
+0.282605 -0.72681999 -0.21195999
+0.18262501 -0.73998001 -0.2282
+0.22237499 -0.68262001 -0.22483
+
+0.322565 -0.66830002 -0.22158001
+0.282605 -0.72681999 -0.21195999
+0.22237499 -0.68262001 -0.22483
+
+0.292015 -0.59245998 -0.26313
+0.19210501 -0.62008999 -0.27941999
+0.241845 -0.57674 -0.28339001
+
+0.19210501 -0.62008999 -0.27941999
+0.21181499 -0.56279999 -0.28535
+0.241845 -0.57674 -0.28339001
+
+0.151255 -0.47417999 -0.33002998
+0.211805 -0.50487 -0.30047001
+0.21181499 -0.56279999 -0.28535
+
+0.261315 -0.36248001 -0.31499001
+0.370625 -0.38014999 -0.26396999
+0.37158501 -0.45105999 -0.26129999
+
+0.239765 -0.07146 -0.19552
+0.074325 -0.09863 -0.22704
+0.091085 -0.00535 -0.20563999
+
+0.282605 -0.72681999 -0.21195999
+0.269445 -0.75794998 -0.18476999
+0.18262501 -0.73998001 -0.2282
+
+0.200805 -0.34676998 -0.33601002
+0.140395 -0.26084999 -0.35778
+0.200305 -0.22082001 -0.32242001
+
+0.20949499 8e-05 -0.18802999
+0.153225 0.01244 -0.18492001
+0.179445 0.04258 -0.17731001
+
+-0.275595 -0.76456001 -0.06335
+-0.244305 -0.76299004 -0.00343
+-0.38783501 -0.76627998 0.13294
+
+0.172295 -0.65259003 -0.24820999
+0.19210501 -0.62008999 -0.27941999
+0.22237499 -0.68262001 -0.22483
+
+0.261315 -0.36248001 -0.31499001
+0.251075 -0.40532001 -0.30648001
+0.200805 -0.34676998 -0.33601002
+
+-0.57005501 0.04798 -0.05057
+-0.52043499 0.07819 -0.06974
+-0.53066502 0.00663 -0.09101
+
+0.20949499 8e-05 -0.18802999
+0.179445 0.04258 -0.17731001
+0.259195 0.02269 -0.176
+
+-0.46016499 0.52960999 -0.57521999
+-0.44630501 0.55679001 -0.57491001
+-0.47018501 0.48946999 -0.51748001
+
+0.292015 -0.59245998 -0.26313
+0.241845 -0.57674 -0.28339001
+0.33190498 -0.54949001 -0.26895
+
+0.200805 -0.34676998 -0.33601002
+0.200305 -0.22082001 -0.32242001
+0.290415 -0.22259001 -0.29337
+
+-0.57057499 -0.43936001 0.05637
+-0.48772499 -0.47484001 -0.01301
+-0.510555 -0.49130001 0.09622
+
+0.27865499 -0.11254 -0.21181999
+0.22540501 -0.15247 -0.28954
+0.131915 -0.11946 -0.26507999
+
+-0.297925 -0.53887001 -0.09417
+-0.238365 -0.47976002 -0.11273
+-0.157915 -0.5673 -0.08973
+
+-0.44820499 0.36980999 -0.02461
+-0.45510502 0.35847 -0.05053
+-0.462285 0.43570999 -0.09058
+
+0.19929501 -0.75515999 -0.14499
+-0.124075 -0.75598 -0.18927
+0.011285 -0.76453003 -0.22976
+
+0.322565 -0.66830002 -0.22158001
+0.302465 -0.72740997 -0.204
+0.282605 -0.72681999 -0.21195999
+
+0.19210501 -0.62008999 -0.27941999
+0.172295 -0.65259003 -0.24820999
+0.082165 -0.64961998 -0.27099001
+
+0.031555 -0.54588001 -0.32389999
+0.061695 -0.56002998 -0.32155998
+0.002175 -0.65117996 -0.26294001
+
+-0.089315 -0.30382 -0.35894001
+-0.099045 -0.37569 -0.34127998
+-0.119055 -0.34823002 -0.33359001
+
+-0.58929501 0.35665001 -0.05348
+-0.54156502 0.29757 -0.05975
+-0.57147499 0.29725 -0.05187
+
+0.082165 -0.64961998 -0.27099001
+0.172295 -0.65259003 -0.24820999
+0.032345 -0.66652 -0.25143
+
+0.061695 -0.56002998 -0.32155998
+0.151255 -0.47417999 -0.33002998
+0.21181499 -0.56279999 -0.28535
+
+0.131055 -0.41751999 -0.33540001
+0.251075 -0.40532001 -0.30648001
+0.151255 -0.47417999 -0.33002998
+
+0.22540501 -0.15247 -0.28954
+0.251465 -0.18408001 -0.29662001
+0.125885 -0.16028999 -0.32228001
+
+0.51838501 -0.73889 0.11006
+0.59101501 -0.70407997 0.1113
+0.57144501 -0.70275002 0.21681
+
+-0.249485 -0.24631001 -0.19802999
+-0.18914499 -0.31829 -0.17997
+-0.288985 -0.33368 -0.16805
+
+-0.27567499 -0.69246002 -0.18768
+-0.25884501 -0.74322998 -0.26056
+-0.271465 -0.75859001 -0.23466
+
+-0.125935 -0.71977997 0.05414
+-0.136375 -0.72024002 0.05244
+-0.139575 -0.71986 0.03333
+
+-0.36254501 -0.75091003 -0.10707
+-0.47012501 -0.68793999 -0.04621
+-0.27737499 -0.63951 -0.09283
+
+-0.42914501 -0.31971001 -0.17452999
+-0.39932499 -0.27525 -0.19733
+-0.37912498 -0.31878 -0.18186001
+
+0.172295 -0.65259003 -0.24820999
+0.22237499 -0.68262001 -0.22483
+0.032345 -0.66652 -0.25143
+
+0.22237499 -0.68262001 -0.22483
+0.18262501 -0.73998001 -0.2282
+0.032345 -0.66652 -0.25143
+
+0.251075 -0.40532001 -0.30648001
+0.211805 -0.50487 -0.30047001
+0.151255 -0.47417999 -0.33002998
+
+0.200805 -0.34676998 -0.33601002
+0.251075 -0.40532001 -0.30648001
+0.131055 -0.41751999 -0.33540001
+
+-0.215165 -0.74110001 0.12757
+-0.18321501 -0.75733002 0.1487
+-0.19240499 -0.74304001 0.15199
+
+-0.38056499 0.02471 -0.15193
+-0.310175 -0.08771 -0.20037001
+-0.35023499 -0.1021 -0.20283001
+
+-0.112925 0.44946999 -0.01904
+-0.31918501 0.34056 0.04058
+-0.34072498 0.34067001 0.0194
+
+-0.30734501 -0.71100998 -0.10559
+-0.30720501 -0.73987999 -0.10804
+-0.31717501 -0.73977997 -0.10929
+
+0.18262501 -0.73998001 -0.2282
+0.102645 -0.75471001 -0.22798
+0.032345 -0.66652 -0.25143
+
+0.19210501 -0.62008999 -0.27941999
+0.082165 -0.64961998 -0.27099001
+0.061695 -0.56002998 -0.32155998
+
+0.100535 -0.31684999 -0.36356998
+0.140395 -0.26084999 -0.35778
+0.200805 -0.34676998 -0.33601002
+
+-0.40245499 0.42946999 0.00582
+-0.40747501 0.47915001 0.0356
+-0.330975 0.52471001 -0.03259
+
+-0.52043499 0.07819 -0.06974
+-0.501245 0.20993999 -0.07225
+-0.43113499 0.13668 -0.06854
+
+0.19210501 -0.62008999 -0.27941999
+0.061695 -0.56002998 -0.32155998
+0.21181499 -0.56279999 -0.28535
+
+0.200805 -0.34676998 -0.33601002
+0.131055 -0.41751999 -0.33540001
+0.100535 -0.31684999 -0.36356998
+
+-0.52043499 0.07819 -0.06974
+-0.57005501 0.04798 -0.05057
+-0.60025501 0.10649 -0.05573
+
+-0.53066502 0.00663 -0.09101
+-0.52043499 0.07819 -0.06974
+-0.43526501 0.09176 -0.08455
+
+-0.35023499 -0.1021 -0.20283001
+-0.430355 -0.10442 -0.17239
+-0.48044498 -0.07672 -0.15554
+
+0.151255 -0.47417999 -0.33002998
+0.031555 -0.54588001 -0.32389999
+0.041465 -0.48752998 -0.34728001
+
+0.131055 -0.41751999 -0.33540001
+0.151255 -0.47417999 -0.33002998
+0.041465 -0.48752998 -0.34728001
+
+0.125885 -0.16028999 -0.32228001
+0.251465 -0.18408001 -0.29662001
+0.140395 -0.26084999 -0.35778
+
+0.382645 -0.65669998 -0.17177999
+0.36238499 -0.61118 -0.21527
+0.42197498 -0.58331001 -0.20099001
+
+0.68647499 -0.58339001 -0.0017
+0.74039497 -0.56462002 0.06716
+0.72791496 -0.59351002 0.06742
+
+-0.40245499 0.42946999 0.00582
+-0.312335 0.41512001 -0.03359
+-0.401735 0.37047001 -0.00194
+
+0.66172501 -0.51227001 -0.03209
+0.68443497 -0.45104 0.0037
+0.701595 -0.51362999 -0.01377
+
+-0.060175 0.08937 -0.1052
+0.005765 0.04376 -0.15766
+-0.116545 0.01205 -0.16351999
+
+0.061495 0.71106003 -0.27132
+0.068505 0.67084 -0.27976999
+0.059645 0.68377998 -0.28246
+
+-0.26883499 -0.37657001 -0.16448
+-0.288985 -0.33368 -0.16805
+-0.19886499 -0.37626999 -0.16464001
+
+-0.32967499 -0.20312 -0.20150999
+-0.249485 -0.24631001 -0.19802999
+-0.31935499 -0.27489 -0.19740999
+
+0.36023499 -0.12728 -0.21188999
+0.28848499 -0.13418 -0.22884001
+0.27865499 -0.11254 -0.21181999
+
+0.012615 -0.75335999 -0.24431999
+0.032345 -0.66652 -0.25143
+0.102645 -0.75471001 -0.22798
+
+-0.47702499 -0.74514 -0.06318
+-0.499095 -0.76375999 -0.05418
+-0.52946499 -0.75737999 -0.02987
+
+-0.229725 -0.20162001 -0.21724001
+-0.199305 -0.2299 -0.22021999
+-0.249485 -0.24631001 -0.19802999
+
+-0.76138496 0.14034 0.29812
+-0.74599503 0.0726 0.28837999
+-0.76316498 0.10037 0.37827
+
+-0.120215 -0.74757004 0.18886999
+-0.097395 -0.72411003 0.17242001
+-0.129625 -0.75866997 0.17889999
+
+-0.357915 -0.49792999 -0.07636
+-0.388325 -0.45629002 -0.06645
+-0.297925 -0.53887001 -0.09417
+
+-0.18321501 -0.75733002 0.1487
+-0.152885 -0.76372002 0.12453
+-0.141615 -0.76162003 0.1249
+
+-0.21356501 -0.75926003 0.30533001
+-0.238545 -0.76138 0.28424
+-0.21439501 -0.74724998 0.25917999
+
+0.041465 -0.48752998 -0.34728001
+-0.009285 -0.35868999 -0.37393002
+0.100535 -0.31684999 -0.36356998
+
+0.041465 -0.48752998 -0.34728001
+0.100535 -0.31684999 -0.36356998
+0.131055 -0.41751999 -0.33540001
+
+-0.35023499 -0.1021 -0.20283001
+-0.48044498 -0.07672 -0.15554
+-0.38056499 0.02471 -0.15193
+
+-0.50876499 -0.69231003 -0.00193
+-0.47767502 -0.65098999 0.02223
+-0.50606499 -0.70516998 -0.03412
+
+-0.073375 0.61046001 -0.18223
+-0.083505 0.68447998 -0.17287001
+0.016075 0.68472 -0.25462
+
+0.251465 -0.18408001 -0.29662001
+0.200305 -0.22082001 -0.32242001
+0.140395 -0.26084999 -0.35778
+
+0.012615 -0.75335999 -0.24431999
+0.002175 -0.65117996 -0.26294001
+0.032345 -0.66652 -0.25143
+
+0.082165 -0.64961998 -0.27099001
+0.032345 -0.66652 -0.25143
+0.002175 -0.65117996 -0.26294001
+
+0.031555 -0.54588001 -0.32389999
+0.151255 -0.47417999 -0.33002998
+0.061695 -0.56002998 -0.32155998
+
+0.041465 -0.48752998 -0.34728001
+-0.049465 -0.37333 -0.3702
+-0.009285 -0.35868999 -0.37393002
+
+-0.39040501 0.27885 -0.0233
+-0.363535 0.29777 0.01081
+-0.32405499 0.22228001 0.01714
+
+-0.51963501 0.70806 -0.56443001
+-0.49433498 0.69546997 -0.58514
+-0.51469501 0.68051003 -0.57174
+
+-0.48954498 -0.24917 -0.17212999
+-0.59406502 -0.18136 -0.12044
+-0.48044498 -0.07672 -0.15554
+
+-0.54935501 -0.75695999 0.01981
+-0.56031502 -0.74598999 0.02573
+-0.547785 -0.71860001 0.02244
+
+0.102645 -0.75471001 -0.22798
+0.011285 -0.76453003 -0.22976
+0.012615 -0.75335999 -0.24431999
+
+-0.17994499 -0.75432999 0.36115002
+-0.17762501 -0.75689003 0.38146999
+-0.163815 -0.75672997 0.40183998
+
+0.016075 0.68472 -0.25462
+-0.048255 0.52195999 -0.13641
+-0.073375 0.61046001 -0.18223
+
+-0.232635 -0.74156998 0.44324001
+-0.204825 -0.74662003 0.45456001
+-0.222955 -0.69486 0.43347
+
+-0.44782501 0.38021 -0.01581
+-0.44713501 0.41133999 0.01059
+-0.401735 0.37047001 -0.00194
+
+-0.038565 -0.53313 -0.31079
+-0.078115 -0.62351002 -0.25240999
+-0.058185 -0.59312 -0.27127001
+
+-0.049555 -0.31667 -0.37383999
+-0.019805 -0.26032 -0.37293999
+-0.009285 -0.35868999 -0.37393002
+
+-0.579235 -0.25250999 -0.13211
+-0.60820499 -0.28396 -0.08675
+-0.59406502 -0.18136 -0.12044
+
+-0.47904499 -0.33529999 -0.1591
+-0.579235 -0.25250999 -0.13211
+-0.48954498 -0.24917 -0.17212999
+
+0.239765 -0.07146 -0.19552
+0.27865499 -0.11254 -0.21181999
+0.074325 -0.09863 -0.22704
+
+-0.36962502 -0.20292999 -0.20726999
+-0.31935499 -0.27489 -0.19740999
+-0.39932499 -0.27525 -0.19733
+
+0.025515 0.74473999 -0.25292999
+0.047165 0.73010002 -0.26747
+0.059645 0.68377998 -0.28246
+
+-0.038565 -0.53313 -0.31079
+0.031555 -0.54588001 -0.32389999
+0.002175 -0.65117996 -0.26294001
+
+-0.59406502 -0.18136 -0.12044
+-0.59998501 -0.08147 -0.08608
+-0.48044498 -0.07672 -0.15554
+
+-0.32967499 -0.20312 -0.20150999
+-0.35023499 -0.1021 -0.20283001
+-0.310175 -0.08771 -0.20037001
+
+-0.328545 -0.40797001 -0.12829
+-0.40871498 -0.39304001 -0.14109
+-0.37912498 -0.31878 -0.18186001
+
+0.025515 0.74473999 -0.25292999
+0.016075 0.68472 -0.25462
+-0.083505 0.68447998 -0.17287001
+
+-0.016475 0.76692001 -0.19555
+0.025515 0.74473999 -0.25292999
+-0.083505 0.68447998 -0.17287001
+
+-0.44842499 -0.42519001 -0.09399
+-0.458685 -0.37923 -0.13846
+-0.40871498 -0.39304001 -0.14109
+
+0.059645 0.68377998 -0.28246
+0.016075 0.68472 -0.25462
+0.025515 0.74473999 -0.25292999
+
+-0.60123501 0.19448 -0.05578
+-0.57065498 0.15109 -0.06724
+-0.60025501 0.10649 -0.05573
+
+0.031555 -0.54588001 -0.32389999
+-0.038565 -0.53313 -0.31079
+-0.028935 -0.47416 -0.34169998
+
+-0.69706497 0.27559999 0.04741
+-0.62156502 0.28177999 -0.03207
+-0.67165497 0.20761999 -0.01075
+
+-0.36962502 -0.20292999 -0.20726999
+-0.420495 -0.13227 -0.18625
+-0.35023499 -0.1021 -0.20283001
+
+-0.038565 -0.53313 -0.31079
+0.002175 -0.65117996 -0.26294001
+-0.078115 -0.62351002 -0.25240999
+
+-0.009285 -0.35868999 -0.37393002
+-0.049465 -0.37333 -0.3702
+-0.049555 -0.31667 -0.37383999
+
+-0.019805 -0.26032 -0.37293999
+-0.059835 -0.23341 -0.35984001
+-0.019895 -0.21881001 -0.36255001
+
+-0.39040501 0.27885 -0.0233
+-0.34418499 0.18421 -0.02241
+-0.43113499 0.13668 -0.06854
+
+-0.36962502 -0.20292999 -0.20726999
+-0.35023499 -0.1021 -0.20283001
+-0.32967499 -0.20312 -0.20150999
+
+-0.35023499 -0.1021 -0.20283001
+-0.420495 -0.13227 -0.18625
+-0.430355 -0.10442 -0.17239
+
+0.040165 -0.24620001 -0.37231998
+0.125885 -0.16028999 -0.32228001
+0.140395 -0.26084999 -0.35778
+
+0.061695 -0.56002998 -0.32155998
+0.082165 -0.64961998 -0.27099001
+0.002175 -0.65117996 -0.26294001
+
+0.040165 -0.24620001 -0.37231998
+0.100535 -0.31684999 -0.36356998
+-0.009285 -0.35868999 -0.37393002
+
+0.040165 -0.24620001 -0.37231998
+-0.019895 -0.21881001 -0.36255001
+0.061575 -0.19306999 -0.34928001
+
+-0.117175 -0.61290001 -0.22316
+-0.107915 -0.53838001 -0.23878
+-0.058185 -0.59312 -0.27127001
+
+-0.049555 -0.31667 -0.37383999
+-0.109575 -0.27684 -0.3468
+-0.059835 -0.23341 -0.35984001
+
+-0.34806499 -0.62027 0.40410999
+-0.32939499 -0.58321999 0.36421001
+-0.354585 -0.59728001 0.33195
+
+0.002175 -0.65117996 -0.26294001
+0.012615 -0.75335999 -0.24431999
+-0.056505 -0.75303001 -0.26643
+
+0.031555 -0.54588001 -0.32389999
+-0.028935 -0.47416 -0.34169998
+0.041465 -0.48752998 -0.34728001
+
+-0.059835 -0.23341 -0.35984001
+-0.099435 -0.2215 -0.33507999
+-0.068905 -0.17981001 -0.32354
+
+-0.47262501 0.31153 -0.0592
+-0.43113499 0.13668 -0.06854
+-0.501245 0.20993999 -0.07225
+
+0.073585 0.64028999 -0.27017
+0.068505 0.67084 -0.27976999
+0.077465 0.65564003 -0.25237
+
+-0.52155499 0.29777 -0.06353
+-0.47262501 0.31153 -0.0592
+-0.501245 0.20993999 -0.07225
+
+-0.16779499 -0.59556999 -0.09223
+-0.157915 -0.5673 -0.08973
+-0.132525 -0.59215 -0.16823
+
+-0.058185 -0.59312 -0.27127001
+-0.028935 -0.47416 -0.34169998
+-0.038565 -0.53313 -0.31079
+
+0.041465 -0.48752998 -0.34728001
+-0.028935 -0.47416 -0.34169998
+-0.049465 -0.37333 -0.3702
+
+-0.119055 -0.34823002 -0.33359001
+-0.089125 -0.40429001 -0.33634998
+-0.049465 -0.37333 -0.3702
+
+-0.44842499 -0.42519001 -0.09399
+-0.51724499 -0.39648998 -0.08125
+-0.458685 -0.37923 -0.13846
+
+-0.262125 -0.75611 -0.24801001
+-0.25884501 -0.74322998 -0.26056
+-0.264615 -0.75880997 -0.25176001
+
+-0.089125 -0.40429001 -0.33634998
+-0.099045 -0.37569 -0.34127998
+-0.049465 -0.37333 -0.3702
+
+-0.019805 -0.26032 -0.37293999
+-0.049555 -0.31667 -0.37383999
+-0.059835 -0.23341 -0.35984001
+
+-0.16091499 -0.46264999 -0.1489
+-0.19886499 -0.37626999 -0.16464001
+-0.178825 -0.39007 -0.16848
+
+0.57723499 -0.16372999 -0.05665
+0.55953499 -0.19656 -0.10231
+0.53496498 -0.20222 -0.13642
+
+-0.51724499 -0.39648998 -0.08125
+-0.51851501 -0.35137001 -0.13174
+-0.458685 -0.37923 -0.13846
+
+-0.47904499 -0.33529999 -0.1591
+-0.458685 -0.37923 -0.13846
+-0.51851501 -0.35137001 -0.13174
+
+-0.42884499 -0.63210999 0.34209
+-0.39039501 -0.65042 0.25218
+-0.45884499 -0.68533997 0.2724
+
+-0.57303501 -0.09277 0.39316002
+-0.50651501 -0.10104 0.42856998
+-0.49119499 0.00697 0.39306
+
+-0.049555 -0.31667 -0.37383999
+-0.089315 -0.30382 -0.35894001
+-0.109575 -0.27684 -0.3468
+
+-0.129445 -0.21128 -0.28048
+-0.105115 -0.16202 -0.24193001
+-0.068905 -0.17981001 -0.32354
+
+0.27501499 -0.73774002 0.33299999
+0.263195 -0.75384003 0.38103001
+0.25369499 -0.75265999 0.37801998
+
+0.27501499 -0.73774002 0.33299999
+0.307255 -0.75317001 0.29917999
+0.263195 -0.75384003 0.38103001
+
+0.21626499 -0.75853996 0.0299
+0.37226501 -0.75335999 0.0004
+0.37679501 -0.75690002 0.04199
+
+0.217575 -0.76156998 0.10704
+0.182815 -0.75714996 0.16868999
+0.17213499 -0.75156998 0.0888
+
+0.18217501 -0.72101997 0.24479
+0.169515 -0.73176003 0.21563999
+0.22463499 -0.75526001 0.22989
+
+0.46587502 -0.74139 0.21201
+0.57144501 -0.70275002 0.21681
+0.544925 -0.67612 0.29681999
+
+-0.163815 -0.75672997 0.40183998
+-0.149955 -0.75657997 0.42223999
+-0.124945 -0.75449997 0.44332001
+
+0.74088501 -0.59263 0.15724
+0.72546501 -0.5941 0.22735001
+0.68346497 -0.63983002 0.21789
+
+-0.531875 0.43505001 -0.47442001
+-0.53415501 0.42109001 -0.44837002
+-0.54392502 0.40847 -0.42164001
+
+0.145115 -0.74193001 0.48983002
+0.065805 -0.69416 0.51382
+-0.043565 -0.73834 0.55035999
+
+-0.124945 -0.75449997 0.44332001
+-0.149955 -0.75657997 0.42223999
+-0.129735 -0.75664001 0.42655998
+
+-0.53543499 0.41438 -0.43537998
+-0.53415501 0.42109001 -0.44837002
+-0.52343498 0.42028999 -0.45174999
+
+0.247225 -0.73827003 0.07339
+0.230595 -0.75019997 0.08086
+0.214865 -0.76049004 0.08706
+
+0.39461498 -0.74144997 0.14291
+0.43240501 -0.75309998 0.17931999
+0.39172501 -0.75321999 0.22577
+
+0.39461498 -0.74144997 0.14291
+0.39172501 -0.75321999 0.22577
+0.37518501 -0.73981003 0.19209999
+
+0.273465 -0.75255997 0.21926001
+0.34330502 -0.75508003 0.23577999
+0.307255 -0.75317001 0.29917999
+
+0.268925 -0.75015999 0.45092999
+0.33077499 -0.74196999 0.4384
+0.253395 -0.73496002 0.46985001
+
+-0.52519501 0.43825001 -0.48328999
+-0.51220501 0.43668999 -0.48354
+-0.522085 0.42964001 -0.46967999
+
+0.51719501 -0.72348999 0.03903
+0.37226501 -0.75335999 0.0004
+0.38144501 -0.72870003 -0.01149
+
+0.023935 -0.75346001 0.45659
+0.041895 -0.75098 0.44063
+0.060925 -0.75339996 0.44673
+
+0.51838501 -0.73889 0.11006
+0.37679501 -0.75690002 0.04199
+0.51719501 -0.72348999 0.03903
+
+-0.096785 -0.71277 0.39598999
+-0.126875 -0.71792 0.35866001
+0.034255 -0.70801003 0.40098999
+
+0.28172501 -0.75823997 -0.05062
+0.272735 -0.75711998 -0.10985
+0.32443501 -0.74949997 -0.15917
+
+0.21626499 -0.75853996 0.0299
+0.28172501 -0.75823997 -0.05062
+0.37226501 -0.75335999 0.0004
+
+0.098315 -0.75280998 0.43609001
+0.060925 -0.75339996 0.44673
+0.079235 -0.75045998 0.43006001
+
+0.243085 -0.75848 0.18212999
+0.273465 -0.75255997 0.21926001
+0.22463499 -0.75526001 0.22989
+
+0.071735 -0.70736 0.39019001
+0.108785 -0.70753998 0.38001999
+0.092555 -0.70641998 0.39365002
+
+0.217575 -0.76156998 0.10704
+0.227675 -0.76184998 0.16388
+0.182815 -0.75714996 0.16868999
+
+0.23564501 -0.75482002 0.39424999
+0.25369499 -0.75265999 0.37801998
+0.263195 -0.75384003 0.38103001
+
+0.307255 -0.75317001 0.29917999
+0.27501499 -0.73774002 0.33299999
+0.249485 -0.73458 0.28882999
+
+0.129605 -0.70660004 0.38347
+0.108785 -0.70753998 0.38001999
+0.145855 -0.70772003 0.36983002
+
+-0.112925 0.44946999 -0.01904
+-0.081355 0.49502998 0.00394
+-0.29133499 0.43453999 0.10392
+
+-0.167295 -0.74737 0.49738998
+-0.158775 -0.70517998 0.52299
+-0.204825 -0.74662003 0.45456001
+
+-0.70774498 0.00346 0.16879
+-0.68397499 0.00246 0.06858
+-0.69850502 -0.02457 0.14891
+
+-0.168155 -0.75809998 0.38451
+-0.163815 -0.75672997 0.40183998
+-0.17762501 -0.75689003 0.38146999
+
+-0.74453499 0.0457 0.23389999
+-0.75351501 0.04522 0.14867
+-0.70774498 0.00346 0.16879
+
+0.40481499 -0.73542999 0.28509001
+0.46587502 -0.74139 0.21201
+0.544925 -0.67612 0.29681999
+
+0.356045 -0.73796997 0.07649
+0.34848499 -0.74596001 0.06365
+0.372925 -0.74444 0.08579
+
+0.34330502 -0.75508003 0.23577999
+0.37518501 -0.73981003 0.19209999
+0.39172501 -0.75321999 0.22577
+
+0.171975 -0.75398003 0.41638
+0.216595 -0.75247002 0.38827999
+0.268925 -0.75015999 0.45092999
+
+-0.74453499 0.0457 0.23389999
+-0.76094498 0.07262 0.24841
+-0.77178497 0.08616 0.18837
+
+0.38517502 -0.74663002 0.10888
+0.37679501 -0.75690002 0.04199
+0.43240501 -0.75309998 0.17931999
+
+0.307255 -0.75317001 0.29917999
+0.39172501 -0.75321999 0.22577
+0.268925 -0.75015999 0.45092999
+
+0.32443501 -0.74949997 -0.15917
+0.272735 -0.75711998 -0.10985
+0.269445 -0.75794998 -0.18476999
+
+0.23355499 -0.75731003 0.17916
+0.243085 -0.75848 0.18212999
+0.22463499 -0.75526001 0.22989
+
+-0.40862499 -0.51027 0.23212
+-0.406595 -0.51174999 0.23107
+-0.382085 -0.52368999 0.21750999
+
+-0.74453499 0.0457 0.23389999
+-0.67764503 0.00206 0.26896999
+-0.70928497 0.03538 0.30452
+
+-0.74599503 0.0726 0.28837999
+-0.74184502 0.0506 0.33896999
+-0.76316498 0.10037 0.37827
+
+0.071735 -0.70736 0.39019001
+0.055505 -0.70625 0.40381001
+0.034255 -0.70801003 0.40098999
+
+-0.70928497 0.03538 0.30452
+-0.74599503 0.0726 0.28837999
+-0.76094498 0.07262 0.24841
+
+-0.74184502 0.0506 0.33896999
+-0.756325 0.07345 0.41839001
+-0.76316498 0.10037 0.37827
+
+0.38517502 -0.74663002 0.10888
+0.372925 -0.74444 0.08579
+0.37679501 -0.75690002 0.04199
+
+0.307255 -0.75317001 0.29917999
+0.249485 -0.73458 0.28882999
+0.22463499 -0.75526001 0.22989
+
+0.38517502 -0.74663002 0.10888
+0.43240501 -0.75309998 0.17931999
+0.39461498 -0.74144997 0.14291
+
+0.25821501 -0.72514999 0.35438
+0.250725 -0.71367996 0.32457001
+0.27501499 -0.73774002 0.33299999
+
+-0.54392502 0.40847 -0.42164001
+-0.54327499 0.39124001 -0.37567001
+-0.574305 0.39730999 -0.30334999
+
+-0.70928497 0.03538 0.30452
+-0.74184502 0.0506 0.33896999
+-0.74599503 0.0726 0.28837999
+
+-0.19240499 -0.74304001 0.15199
+-0.18321501 -0.75733002 0.1487
+-0.189415 -0.75043999 0.19530001
+
+0.57144501 -0.70275002 0.21681
+0.59101501 -0.70407997 0.1113
+0.63408501 -0.68242996 0.15461
+
+0.59101501 -0.70407997 0.1113
+0.67806503 -0.65469002 0.13749
+0.63408501 -0.68242996 0.15461
+
+-0.74453499 0.0457 0.23389999
+-0.70774498 0.00346 0.16879
+-0.67764503 0.00206 0.26896999
+
+-0.204825 -0.74662003 0.45456001
+-0.232635 -0.74156998 0.44324001
+-0.257085 -0.75538002 0.41583
+
+0.216595 -0.75247002 0.38827999
+0.23564501 -0.75482002 0.39424999
+0.268925 -0.75015999 0.45092999
+
+0.17213499 -0.75156998 0.0888
+0.136425 -0.71731003 0.08693
+0.141325 -0.71446999 0.04894
+
+-0.70928497 0.03538 0.30452
+-0.70194504 0.01583 0.35792
+-0.74184502 0.0506 0.33896999
+
+-0.70928497 0.03538 0.30452
+-0.67764503 0.00206 0.26896999
+-0.64516502 -0.00556 0.3159
+
+-0.756325 0.07345 0.41839001
+-0.74184502 0.0506 0.33896999
+-0.72276497 0.02686 0.4157
+
+0.245315 -0.71125 0.33931999
+0.250725 -0.71367996 0.32457001
+0.25821501 -0.72514999 0.35438
+
+0.275065 -0.74995003 0.05247
+0.247225 -0.73827003 0.07339
+0.214865 -0.76049004 0.08706
+
+0.39172501 -0.75321999 0.22577
+0.40481499 -0.73542999 0.28509001
+0.34790501 -0.74143997 0.42344002
+
+0.307255 -0.75317001 0.29917999
+0.268925 -0.75015999 0.45092999
+0.263195 -0.75384003 0.38103001
+
+0.134945 -0.75379997 0.42655998
+0.171975 -0.75398003 0.41638
+0.268925 -0.75015999 0.45092999
+
+0.307255 -0.75317001 0.29917999
+0.34330502 -0.75508003 0.23577999
+0.39172501 -0.75321999 0.22577
+
+-0.74184502 0.0506 0.33896999
+-0.70194504 0.01583 0.35792
+-0.72276497 0.02686 0.4157
+
+-0.097395 -0.72411003 0.17242001
+-0.113155 -0.72134003 0.07626
+0.141225 -0.72126999 0.18233999
+
+0.18217501 -0.72101997 0.24479
+0.145855 -0.70772003 0.36983002
+0.141225 -0.72126999 0.18233999
+
+0.17213499 -0.75156998 0.0888
+0.141225 -0.72126999 0.18233999
+0.136425 -0.71731003 0.08693
+
+-0.72276497 0.02686 0.4157
+-0.70194504 0.01583 0.35792
+-0.64516502 -0.00556 0.3159
+
+-0.707295 0.05002 0.47198002
+-0.72276497 0.02686 0.4157
+-0.66449501 0.01509 0.45601002
+
+0.134945 -0.75379997 0.42655998
+0.098315 -0.75280998 0.43609001
+0.115885 -0.75144997 0.42055
+
+0.34848499 -0.74596001 0.06365
+0.37679501 -0.75690002 0.04199
+0.372925 -0.74444 0.08579
+
+0.19929501 -0.75515999 -0.14499
+0.231395 -0.71984001 -0.09604
+0.18418501 -0.71306999 -0.11163
+
+0.46587502 -0.74139 0.21201
+0.51838501 -0.73889 0.11006
+0.57144501 -0.70275002 0.21681
+
+-0.72276497 0.02686 0.4157
+-0.64516502 -0.00556 0.3159
+-0.58873501 -0.02668 0.38175999
+
+0.204165 -0.70615997 0.36240002
+0.18334499 -0.70709 0.35896
+0.16710501 -0.70596001 0.37262001
+
+0.43405499 -0.71273003 0.30693001
+0.34790501 -0.74143997 0.42344002
+0.40481499 -0.73542999 0.28509001
+
+0.269445 -0.75794998 -0.18476999
+0.19929501 -0.75515999 -0.14499
+0.011285 -0.76453003 -0.22976
+
+0.46587502 -0.74139 0.21201
+0.43240501 -0.75309998 0.17931999
+0.51838501 -0.73889 0.11006
+
+0.38517502 -0.74663002 0.10888
+0.37738499 -0.74217003 0.10322
+0.372925 -0.74444 0.08579
+
+0.243085 -0.75848 0.18212999
+0.249445 -0.75310997 0.19672001
+0.273465 -0.75255997 0.21926001
+
+0.171975 -0.75398003 0.41638
+0.134945 -0.75379997 0.42655998
+0.153365 -0.75081001 0.40972
+
+0.522575 -0.68685997 -0.0156
+0.558475 -0.70769997 0.03611
+0.51719501 -0.72348999 0.03903
+
+0.145115 -0.74193001 0.48983002
+-0.043565 -0.73834 0.55035999
+-0.088955 -0.75287003 0.51883999
+
+0.182815 -0.75714996 0.16868999
+0.23355499 -0.75731003 0.17916
+0.22463499 -0.75526001 0.22989
+
+-0.67527496 -0.04277 0.26872
+-0.65371498 -0.08158 0.31889
+-0.60681499 -0.05331 0.35605999
+
+0.145855 -0.70772003 0.36983002
+0.108785 -0.70753998 0.38001999
+0.034255 -0.70801003 0.40098999
+
+0.275065 -0.74995003 0.05247
+0.214865 -0.76049004 0.08706
+0.21626499 -0.75853996 0.0299
+
+0.21626499 -0.75853996 0.0299
+0.17213499 -0.75156998 0.0888
+0.141325 -0.71446999 0.04894
+
+-0.64516502 -0.00556 0.3159
+-0.67527496 -0.04277 0.26872
+-0.60681499 -0.05331 0.35605999
+
+-0.707295 0.05002 0.47198002
+-0.66449501 0.01509 0.45601002
+-0.648545 0.03328 0.48077
+
+-0.67091499 0.06852 0.50094002
+-0.70310501 0.07475 0.49027
+-0.707295 0.05002 0.47198002
+
+-0.67091499 0.06852 0.50094002
+-0.707295 0.05002 0.47198002
+-0.648545 0.03328 0.48077
+
+-0.158775 -0.70517998 0.52299
+-0.222955 -0.69486 0.43347
+-0.204825 -0.74662003 0.45456001
+
+-0.516045 0.07047 0.53485001
+-0.54655499 0.08835 0.54924999
+-0.54197498 0.03751 0.51964001
+
+-0.515135 0.41865002 -0.44709
+-0.51723499 0.35522999 -0.21364
+-0.54327499 0.39124001 -0.37567001
+
+-0.113155 -0.72134003 0.07626
+-0.139575 -0.71986 0.03333
+-0.031635 -0.71653999 -0.15134
+
+-0.64516502 -0.00556 0.3159
+-0.67764503 0.00206 0.26896999
+-0.67527496 -0.04277 0.26872
+
+0.43240501 -0.75309998 0.17931999
+0.46587502 -0.74139 0.21201
+0.39172501 -0.75321999 0.22577
+
+0.230595 -0.75019997 0.08086
+0.217575 -0.76156998 0.10704
+0.214865 -0.76049004 0.08706
+
+-0.139575 -0.71986 0.03333
+-0.098815 -0.71488998 -0.14756
+-0.031635 -0.71653999 -0.15134
+
+-0.677295 0.16986 0.51804001
+-0.70310501 0.07475 0.49027
+-0.67091499 0.06852 0.50094002
+
+-0.167295 -0.74737 0.49738998
+-0.204825 -0.74662003 0.45456001
+-0.124945 -0.75449997 0.44332001
+
+-0.212425 0.4907 -0.10495
+-0.312335 0.41512001 -0.03359
+-0.40245499 0.42946999 0.00582
+
+-0.043565 -0.73834 0.55035999
+-0.055935 -0.72981003 0.55643002
+-0.107665 -0.74504997 0.54255001
+
+0.134945 -0.75379997 0.42655998
+0.060925 -0.75339996 0.44673
+0.098315 -0.75280998 0.43609001
+
+-0.60681499 -0.05331 0.35605999
+-0.57303501 -0.09277 0.39316002
+-0.57050499 -0.03053 0.38844002
+
+-0.72276497 0.02686 0.4157
+-0.58873501 -0.02668 0.38175999
+-0.66449501 0.01509 0.45601002
+
+-0.63135502 -0.33622002 0.29066999
+-0.67350502 -0.31801001 0.21348
+-0.63988499 -0.38061001 0.17080999
+
+-0.62156502 0.28177999 -0.03207
+-0.614795 0.37119999 -0.013
+-0.57147499 0.29725 -0.05187
+
+-0.055935 -0.72981003 0.55643002
+-0.119005 -0.73551003 0.54847
+-0.107665 -0.74504997 0.54255001
+
+-0.70194504 0.01583 0.35792
+-0.70928497 0.03538 0.30452
+-0.64516502 -0.00556 0.3159
+
+-0.603685 0.00224 0.46230999
+-0.648545 0.03328 0.48077
+-0.66449501 0.01509 0.45601002
+
+-0.54935501 -0.75695999 0.01981
+-0.52946499 -0.75737999 -0.02987
+-0.499095 -0.76375999 -0.05418
+
+-0.573535 -0.42264999 0.23674
+-0.63988499 -0.38061001 0.17080999
+-0.53317501 -0.47806999 0.18746
+
+-0.57746498 -0.38132 0.32298
+-0.54116501 -0.33391998 0.39556
+-0.61961498 -0.25518 0.37487
+
+-0.088955 -0.75287003 0.51883999
+-0.107665 -0.74504997 0.54255001
+-0.167295 -0.74737 0.49738998
+
+0.49892502 -0.66067001 0.30966
+0.465905 -0.63949001 0.35477001
+0.43405499 -0.71273003 0.30693001
+
+0.23564501 -0.75482002 0.39424999
+0.263195 -0.75384003 0.38103001
+0.268925 -0.75015999 0.45092999
+
+0.268925 -0.75015999 0.45092999
+0.34790501 -0.74143997 0.42344002
+0.33077499 -0.74196999 0.4384
+
+0.34790501 -0.74143997 0.42344002
+0.329505 -0.71892998 0.45332001
+0.33077499 -0.74196999 0.4384
+
+-0.63462502 -0.37513 0.05758
+-0.57057499 -0.43936001 0.05637
+-0.56052502 -0.45873001 0.12908
+
+0.33077499 -0.74196999 0.4384
+0.329505 -0.71892998 0.45332001
+0.253395 -0.73496002 0.46985001
+
+-0.57057499 -0.43936001 0.05637
+-0.59931499 -0.38535999 -0.00934
+-0.51724499 -0.39648998 -0.08125
+
+-0.63135502 -0.33622002 0.29066999
+-0.57746498 -0.38132 0.32298
+-0.65677498 -0.28486 0.31427999
+
+0.068865 0.56655998 -0.20183001
+0.075975 0.58987 -0.22885
+0.069325 0.57973999 -0.17223
+
+0.222605 -0.71620003 -0.04485
+0.141325 -0.71446999 0.04894
+0.18418501 -0.71306999 -0.11163
+
+0.272735 -0.75711998 -0.10985
+0.19929501 -0.75515999 -0.14499
+0.269445 -0.75794998 -0.18476999
+
+0.182815 -0.75714996 0.16868999
+0.169515 -0.73176003 0.21563999
+0.141225 -0.72126999 0.18233999
+
+-0.60681499 -0.05331 0.35605999
+-0.58873501 -0.02668 0.38175999
+-0.64516502 -0.00556 0.3159
+
+-0.54197498 0.03751 0.51964001
+-0.60431499 0.04708 0.51540001
+-0.603685 0.00224 0.46230999
+
+-0.603685 0.00224 0.46230999
+-0.627995 0.04726 0.49209
+-0.648545 0.03328 0.48077
+
+-0.307395 -0.74459 0.46473999
+-0.257085 -0.75538002 0.41583
+-0.232635 -0.74156998 0.44324001
+
+0.214865 -0.76049004 0.08706
+0.17213499 -0.75156998 0.0888
+0.21626499 -0.75853996 0.0299
+
+0.307255 -0.75317001 0.29917999
+0.22463499 -0.75526001 0.22989
+0.273465 -0.75255997 0.21926001
+
+-0.63462502 -0.37513 0.05758
+-0.56052502 -0.45873001 0.12908
+-0.63988499 -0.38061001 0.17080999
+
+0.35073502 -0.73208 -0.14142
+0.39260502 -0.67114998 -0.11193
+0.369995 -0.75161003 -0.02044
+
+-0.603685 0.00224 0.46230999
+-0.547775 -0.01096 0.39499001
+-0.527495 0.03341 0.50833
+
+-0.60431499 0.04708 0.51540001
+-0.627995 0.04726 0.49209
+-0.603685 0.00224 0.46230999
+
+0.023935 -0.75346001 0.45659
+0.134945 -0.75379997 0.42655998
+-0.013045 -0.75356003 0.46638
+
+-0.41275501 -0.52455002 0.07158
+-0.510555 -0.49130001 0.09622
+-0.48772499 -0.47484001 -0.01301
+
+-0.547775 -0.01096 0.39499001
+-0.49119499 0.00697 0.39306
+-0.527495 0.03341 0.50833
+
+-0.57050499 -0.03053 0.38844002
+-0.547775 -0.01096 0.39499001
+-0.58873501 -0.02668 0.38175999
+
+-0.573535 -0.42264999 0.23674
+-0.499585 -0.45534 0.28041
+-0.57746498 -0.38132 0.32298
+
+-0.60170502 0.42654999 -0.05351
+-0.62411499 0.60556 -0.39534
+-0.61443501 0.52313 -0.27403999
+
+0.37679501 -0.75690002 0.04199
+0.33116501 -0.74032997 0.055
+0.275065 -0.74995003 0.05247
+
+-0.54935501 -0.75695999 0.01981
+-0.547785 -0.71860001 0.02244
+-0.52946499 -0.75737999 -0.02987
+
+-0.56019501 -0.74653 0.0799
+-0.555005 -0.74924004 0.06549
+-0.54935501 -0.75695999 0.01981
+
+0.37679501 -0.75690002 0.04199
+0.37226501 -0.75335999 0.0004
+0.51719501 -0.72348999 0.03903
+
+-0.56052502 -0.45873001 0.12908
+-0.57057499 -0.43936001 0.05637
+-0.510555 -0.49130001 0.09622
+
+-0.57746498 -0.38132 0.32298
+-0.61961498 -0.25518 0.37487
+-0.65677498 -0.28486 0.31427999
+
+-0.50651501 -0.10104 0.42856998
+-0.436525 -0.08632 0.43841
+-0.49119499 0.00697 0.39306
+
+-0.603685 0.00224 0.46230999
+-0.527495 0.03341 0.50833
+-0.54197498 0.03751 0.51964001
+
+-0.516045 0.07047 0.53485001
+-0.54197498 0.03751 0.51964001
+-0.527495 0.03341 0.50833
+
+0.182815 -0.75714996 0.16868999
+0.22463499 -0.75526001 0.22989
+0.169515 -0.73176003 0.21563999
+
+-0.555005 -0.74924004 0.06549
+-0.56031502 -0.74598999 0.02573
+-0.54935501 -0.75695999 0.01981
+
+0.249445 -0.75310997 0.19672001
+0.26935499 -0.75383003 0.20142
+0.273465 -0.75255997 0.21926001
+
+-0.54197498 0.03751 0.51964001
+-0.58654499 0.0687 0.53747002
+-0.60431499 0.04708 0.51540001
+
+-0.58654499 0.0687 0.53747002
+-0.59962502 0.11646 0.54145
+-0.677295 0.16986 0.51804001
+
+0.247805 -0.73291 -0.06195
+0.28172501 -0.75823997 -0.05062
+0.21626499 -0.75853996 0.0299
+
+-0.555005 -0.74924004 0.06549
+-0.56019501 -0.74653 0.0799
+-0.547785 -0.71860001 0.02244
+
+0.25369499 -0.75265999 0.37801998
+0.25821501 -0.72514999 0.35438
+0.27501499 -0.73774002 0.33299999
+
+0.231395 -0.71984001 -0.09604
+0.272735 -0.75711998 -0.10985
+0.28172501 -0.75823997 -0.05062
+
+-0.499095 -0.76375999 -0.05418
+-0.47702499 -0.74514 -0.06318
+-0.47280499 -0.76528 -0.06571
+
+-0.53317501 -0.47806999 0.18746
+-0.56052502 -0.45873001 0.12908
+-0.52072498 -0.48604 0.17909
+
+0.51838501 -0.73889 0.11006
+0.558475 -0.70769997 0.03611
+0.59101501 -0.70407997 0.1113
+
+-0.462365 -0.76483002 -0.06405
+-0.499095 -0.76375999 -0.05418
+-0.47280499 -0.76528 -0.06571
+
+-0.555005 -0.74924004 0.06549
+-0.547785 -0.71860001 0.02244
+-0.56031502 -0.74598999 0.02573
+
+-0.57050499 -0.03053 0.38844002
+-0.57303501 -0.09277 0.39316002
+-0.49119499 0.00697 0.39306
+
+-0.56052502 -0.45873001 0.12908
+-0.510555 -0.49130001 0.09622
+-0.52072498 -0.48604 0.17909
+
+-0.126875 -0.71792 0.35866001
+-0.141445 -0.71961998 0.33926998
+0.034255 -0.70801003 0.40098999
+
+0.19929501 -0.75515999 -0.14499
+0.272735 -0.75711998 -0.10985
+0.231395 -0.71984001 -0.09604
+
+0.204165 -0.70615997 0.36240002
+0.16710501 -0.70596001 0.37262001
+0.145855 -0.70772003 0.36983002
+
+-0.275595 -0.76456001 -0.06335
+-0.38783501 -0.76627998 0.13294
+-0.499095 -0.76375999 -0.05418
+
+-0.45211498 -0.74226997 0.21997999
+-0.45942501 -0.75005997 0.21047001
+-0.457565 -0.75337997 0.23136999
+
+-0.39643501 -0.51195999 -0.00889
+-0.40209499 -0.53867001 0.05158
+-0.41327499 -0.49464001 -0.01295
+
+-0.40209499 -0.53867001 0.05158
+-0.41275501 -0.52455002 0.07158
+-0.41327499 -0.49464001 -0.01295
+
+-0.41327499 -0.49464001 -0.01295
+-0.41275501 -0.52455002 0.07158
+-0.48772499 -0.47484001 -0.01301
+
+-0.52077499 -0.38400002 0.37219002
+-0.57746498 -0.38132 0.32298
+-0.47914501 -0.41923 0.35875
+
+-0.52077499 -0.38400002 0.37219002
+-0.54116501 -0.33391998 0.39556
+-0.57746498 -0.38132 0.32298
+
+0.242435 -0.69941002 0.47040001
+0.253305 -0.66041 0.46727001
+0.153435 -0.64473 0.48566002
+
+-0.25963499 -0.76286003 0.28113001
+-0.238545 -0.76138 0.28424
+-0.33710499 -0.76268997 0.2824
+
+-0.43560501 -0.76556 -0.07625
+-0.39801498 -0.76503998 -0.08748
+-0.35171501 -0.76720001 -0.03957
+
+-0.56019501 -0.74653 0.0799
+-0.54935501 -0.75695999 0.01981
+-0.51762501 -0.76198997 0.10242
+
+-0.510555 -0.49130001 0.09622
+-0.40885502 -0.52321999 0.18152
+-0.52072498 -0.48604 0.17909
+
+-0.510555 -0.49130001 0.09622
+-0.41275501 -0.52455002 0.07158
+-0.40885502 -0.52321999 0.18152
+
+-0.65677498 -0.28486 0.31427999
+-0.67350502 -0.31801001 0.21348
+-0.63135502 -0.33622002 0.29066999
+
+-0.16275499 -0.66514 0.49737
+-0.21126499 -0.66814003 0.43307999
+-0.222955 -0.69486 0.43347
+
+-0.154315 -0.75793999 0.40488998
+-0.149955 -0.75657997 0.42223999
+-0.163815 -0.75672997 0.40183998
+
+0.51838501 -0.73889 0.11006
+0.43240501 -0.75309998 0.17931999
+0.37679501 -0.75690002 0.04199
+
+-0.44606499 -0.76600998 -0.07796
+-0.43560501 -0.76556 -0.07625
+-0.462365 -0.76483002 -0.06405
+
+-0.52077499 -0.38400002 0.37219002
+-0.47914501 -0.41923 0.35875
+-0.437295 -0.37362999 0.41646999
+
+0.268925 -0.75015999 0.45092999
+-0.088955 -0.75287003 0.51883999
+-0.013045 -0.75356003 0.46638
+
+-0.379445 -0.76219002 -0.10469
+-0.420145 -0.75016998 -0.08755
+-0.36254501 -0.75091003 -0.10707
+
+-0.39801498 -0.76503998 -0.08748
+-0.43560501 -0.76556 -0.07625
+-0.418405 -0.76513 -0.09148
+
+-0.54116501 -0.33391998 0.39556
+-0.52077499 -0.38400002 0.37219002
+-0.50455502 -0.31641001 0.42362999
+
+0.18418501 -0.71306999 -0.11163
+-0.031635 -0.71653999 -0.15134
+0.19929501 -0.75515999 -0.14499
+
+0.134945 -0.75379997 0.42655998
+0.268925 -0.75015999 0.45092999
+-0.013045 -0.75356003 0.46638
+
+0.27501499 -0.73774002 0.33299999
+0.250725 -0.71367996 0.32457001
+0.249485 -0.73458 0.28882999
+
+-0.379445 -0.76219002 -0.10469
+-0.39801498 -0.76503998 -0.08748
+-0.420145 -0.75016998 -0.08755
+
+-0.39801498 -0.76503998 -0.08748
+-0.418405 -0.76513 -0.09148
+-0.420145 -0.75016998 -0.08755
+
+-0.52077499 -0.38400002 0.37219002
+-0.437295 -0.37362999 0.41646999
+-0.50455502 -0.31641001 0.42362999
+
+-0.48884499 0.70297997 -0.56327
+-0.457075 0.67668999 -0.58800999
+-0.47459499 0.69324997 -0.58602001
+
+0.204165 -0.70615997 0.36240002
+0.250725 -0.71367996 0.32457001
+0.245315 -0.71125 0.33931999
+
+-0.40862499 -0.51027 0.23212
+-0.403395 -0.47771 0.30250999
+-0.499585 -0.45534 0.28041
+
+-0.499585 -0.45534 0.28041
+-0.403395 -0.47771 0.30250999
+-0.47914501 -0.41923 0.35875
+
+0.473535 -0.68335999 0.30688
+0.544925 -0.67612 0.29681999
+0.49892502 -0.66067001 0.30966
+
+0.63936501 -0.64530998 0.26995001
+0.57144501 -0.70275002 0.21681
+0.68346497 -0.63983002 0.21789
+
+0.37679501 -0.75690002 0.04199
+0.34848499 -0.74596001 0.06365
+0.33116501 -0.74032997 0.055
+
+-0.403615 -0.76533997 0.20007999
+-0.51126499 -0.75096001 0.14734
+-0.51762501 -0.76198997 0.10242
+
+-0.41275501 -0.52455002 0.07158
+-0.38878502 -0.53153 0.12594
+-0.40885502 -0.52321999 0.18152
+
+-0.50172501 -0.31013 0.42847
+-0.54116501 -0.33391998 0.39556
+-0.50455502 -0.31641001 0.42362999
+
+-0.437295 -0.37362999 0.41646999
+-0.54116501 -0.33391998 0.39556
+-0.50172501 -0.31013 0.42847
+
+0.250725 -0.71367996 0.32457001
+0.204165 -0.70615997 0.36240002
+0.145855 -0.70772003 0.36983002
+
+-0.34996498 -0.76412003 -0.09704
+-0.39801498 -0.76503998 -0.08748
+-0.379445 -0.76219002 -0.10469
+
+-0.39801498 -0.76503998 -0.08748
+-0.33272499 -0.76374001 -0.11234
+-0.35171501 -0.76720001 -0.03957
+
+-0.52072498 -0.48604 0.17909
+-0.499585 -0.45534 0.28041
+-0.53317501 -0.47806999 0.18746
+
+-0.51212502 -0.2273 0.45049999
+-0.61961498 -0.25518 0.37487
+-0.54116501 -0.33391998 0.39556
+
+0.28172501 -0.75823997 -0.05062
+0.32443501 -0.74949997 -0.15917
+0.369995 -0.75161003 -0.02044
+
+-0.39801498 -0.76503998 -0.08748
+-0.34996498 -0.76412003 -0.09704
+-0.33272499 -0.76374001 -0.11234
+
+-0.33272499 -0.76374001 -0.11234
+-0.34996498 -0.76412003 -0.09704
+-0.36254501 -0.75091003 -0.10707
+
+-0.34996498 -0.76412003 -0.09704
+-0.379445 -0.76219002 -0.10469
+-0.36254501 -0.75091003 -0.10707
+
+-0.403615 -0.76533997 0.20007999
+-0.45942501 -0.75005997 0.21047001
+-0.51126499 -0.75096001 0.14734
+
+-0.244305 -0.76299004 -0.00343
+-0.252265 -0.76543999 0.06978
+-0.31338499 -0.75958 0.08819
+
+-0.43739498 0.45532001 0.06203
+-0.35580502 0.52299 0.06101
+-0.247845 0.62541 -0.03466
+
+-0.158775 -0.70517998 0.52299
+-0.16275499 -0.66514 0.49737
+-0.222955 -0.69486 0.43347
+
+-0.499585 -0.45534 0.28041
+-0.573535 -0.42264999 0.23674
+-0.53317501 -0.47806999 0.18746
+
+0.43405499 -0.71273003 0.30693001
+0.390485 -0.69848 0.41848
+0.34790501 -0.74143997 0.42344002
+
+-0.33272499 -0.76374001 -0.11234
+-0.36254501 -0.75091003 -0.10707
+-0.31717501 -0.73977997 -0.10929
+
+-0.40862499 -0.51027 0.23212
+-0.499585 -0.45534 0.28041
+-0.52072498 -0.48604 0.17909
+
+-0.57746498 -0.38132 0.32298
+-0.499585 -0.45534 0.28041
+-0.47914501 -0.41923 0.35875
+
+-0.457565 -0.75337997 0.23136999
+-0.47864498 -0.74934998 0.25862
+-0.45211498 -0.74226997 0.21997999
+
+0.141225 -0.72126999 0.18233999
+0.169515 -0.73176003 0.21563999
+0.18217501 -0.72101997 0.24479
+
+-0.75503502 0.05844 0.12856
+-0.75351501 0.04522 0.14867
+-0.77178497 0.08616 0.18837
+
+-0.403395 -0.47771 0.30250999
+-0.37079498 -0.49140999 0.28962999
+-0.35775501 -0.44438 0.37122002
+
+-0.249135 -0.76183998 -0.26459
+-0.25644501 -0.76240997 -0.24681999
+-0.264615 -0.75880997 -0.25176001
+
+-0.264615 -0.75880997 -0.25176001
+-0.25644501 -0.76240997 -0.24681999
+-0.271465 -0.75859001 -0.23466
+
+-0.45942501 -0.75005997 0.21047001
+-0.403615 -0.76533997 0.20007999
+-0.457565 -0.75337997 0.23136999
+
+-0.50058498 -0.72952003 0.32737999
+-0.47838501 -0.72314003 0.26280001
+-0.47864498 -0.74934998 0.25862
+
+-0.74582497 0.34598999 0.25691
+-0.74152496 0.38702 0.23667
+-0.74042503 0.40042999 0.17667999
+
+-0.40862499 -0.51027 0.23212
+-0.52072498 -0.48604 0.17909
+-0.40885502 -0.52321999 0.18152
+
+-0.34414501 -0.48889999 0.33360001
+-0.34850498 -0.42101002 0.38814999
+-0.35775501 -0.44438 0.37122002
+
+-0.249135 -0.76183998 -0.26459
+-0.23188499 -0.76166 -0.28009001
+-0.176455 -0.76629997 -0.28367001
+
+-0.25644501 -0.76240997 -0.24681999
+-0.249135 -0.76183998 -0.26459
+-0.271465 -0.75859001 -0.23466
+
+-0.249135 -0.76183998 -0.26459
+-0.285585 -0.75900002 -0.19978001
+-0.271465 -0.75859001 -0.23466
+
+-0.230425 -0.75021004 -0.08579
+-0.275595 -0.76456001 -0.06335
+-0.19269501 -0.75025002 -0.15227
+
+-0.45830502 -0.75790001 0.34023998
+-0.47864498 -0.74934998 0.25862
+-0.457565 -0.75337997 0.23136999
+
+-0.49865501 -0.72585999 0.36729
+-0.50058498 -0.72952003 0.32737999
+-0.49940498 -0.74658997 0.33923
+
+-0.55800499 0.38182999 -0.29503
+-0.57997501 0.39771 -0.2633
+-0.57806499 0.41137001 -0.27343
+
+0.17213499 -0.75156998 0.0888
+0.214865 -0.76049004 0.08706
+0.217575 -0.76156998 0.10704
+
+-0.38783501 -0.76627998 0.13294
+-0.35726501 -0.76607002 0.13902
+-0.37178501 -0.76844002 0.17385
+
+-0.437295 -0.37362999 0.41646999
+-0.34850498 -0.42101002 0.38814999
+-0.306675 -0.36883999 0.43159
+
+0.018465 -0.70608002 0.41395
+-0.096785 -0.71277 0.39598999
+0.034255 -0.70801003 0.40098999
+
+-0.31505501 -0.76257004 -0.12831
+-0.20019501 -0.76468002 -0.19624001
+-0.275595 -0.76456001 -0.06335
+
+-0.31505501 -0.76257004 -0.12831
+-0.285585 -0.75900002 -0.19978001
+-0.20019501 -0.76468002 -0.19624001
+
+-0.33272499 -0.76374001 -0.11234
+-0.31505501 -0.76257004 -0.12831
+-0.275595 -0.76456001 -0.06335
+
+-0.462365 -0.76483002 -0.06405
+-0.275595 -0.76456001 -0.06335
+-0.499095 -0.76375999 -0.05418
+
+-0.56019501 -0.74653 0.0799
+-0.54181499 -0.69334 0.08588
+-0.547785 -0.71860001 0.02244
+
+-0.204825 -0.74662003 0.45456001
+-0.257085 -0.75538002 0.41583
+-0.17994499 -0.75432999 0.36115002
+
+-0.403615 -0.76533997 0.20007999
+-0.38783501 -0.76627998 0.13294
+-0.37178501 -0.76844002 0.17385
+
+-0.47779499 -0.74220001 0.42571999
+-0.49865501 -0.72585999 0.36729
+-0.49940498 -0.74658997 0.33923
+
+-0.403395 -0.47771 0.30250999
+-0.35775501 -0.44438 0.37122002
+-0.47914501 -0.41923 0.35875
+
+-0.437295 -0.37362999 0.41646999
+-0.35775501 -0.44438 0.37122002
+-0.34850498 -0.42101002 0.38814999
+
+-0.43411499 -0.75475998 0.44608002
+-0.47779499 -0.74220001 0.42571999
+-0.49940498 -0.74658997 0.33923
+
+-0.031635 -0.71653999 -0.15134
+-0.124075 -0.75598 -0.18927
+0.19929501 -0.75515999 -0.14499
+
+-0.176455 -0.76629997 -0.28367001
+-0.23188499 -0.76166 -0.28009001
+-0.20123501 -0.75469002 -0.29017
+
+-0.462365 -0.76483002 -0.06405
+-0.35171501 -0.76720001 -0.03957
+-0.275595 -0.76456001 -0.06335
+
+-0.33328499 -0.75277 0.11401
+-0.35726501 -0.76607002 0.13902
+-0.38783501 -0.76627998 0.13294
+
+-0.50564499 -0.26843 0.44533001
+-0.54116501 -0.33391998 0.39556
+-0.437295 -0.37362999 0.41646999
+
+-0.70310501 0.07475 0.49027
+-0.74907501 0.12734 0.44921001
+-0.754655 0.10016 0.44153999
+
+-0.275595 -0.76456001 -0.06335
+-0.35171501 -0.76720001 -0.03957
+-0.33272499 -0.76374001 -0.11234
+
+-0.244305 -0.76299004 -0.00343
+-0.31338499 -0.75958 0.08819
+-0.38783501 -0.76627998 0.13294
+
+-0.31338499 -0.75958 0.08819
+-0.33328499 -0.75277 0.11401
+-0.38783501 -0.76627998 0.13294
+
+-0.31338499 -0.75958 0.08819
+-0.317565 -0.74244003 0.10792
+-0.33328499 -0.75277 0.11401
+
+-0.37656502 -0.29565001 0.46369999
+-0.437295 -0.37362999 0.41646999
+-0.306675 -0.36883999 0.43159
+
+-0.34414501 -0.48889999 0.33360001
+-0.35775501 -0.44438 0.37122002
+-0.37079498 -0.49140999 0.28962999
+
+0.011285 -0.76453003 -0.22976
+0.102645 -0.75471001 -0.22798
+0.269445 -0.75794998 -0.18476999
+
+-0.249135 -0.76183998 -0.26459
+-0.176455 -0.76629997 -0.28367001
+-0.20019501 -0.76468002 -0.19624001
+
+-0.285585 -0.75900002 -0.19978001
+-0.249135 -0.76183998 -0.26459
+-0.20019501 -0.76468002 -0.19624001
+
+-0.462365 -0.76483002 -0.06405
+-0.43560501 -0.76556 -0.07625
+-0.35171501 -0.76720001 -0.03957
+
+-0.272745 -0.45799 0.41743
+-0.306675 -0.36883999 0.43159
+-0.34850498 -0.42101002 0.38814999
+
+-0.707295 0.05002 0.47198002
+-0.754655 0.10016 0.44153999
+-0.756325 0.07345 0.41839001
+
+-0.244305 -0.76299004 -0.00343
+-0.275595 -0.76456001 -0.06335
+-0.25025499 -0.76152 -0.04266
+
+-0.38783501 -0.76627998 0.13294
+-0.51762501 -0.76198997 0.10242
+-0.499095 -0.76375999 -0.05418
+
+-0.302635 -0.74605003 0.09617
+-0.317565 -0.74244003 0.10792
+-0.31338499 -0.75958 0.08819
+
+-0.403615 -0.76533997 0.20007999
+-0.37178501 -0.76844002 0.17385
+-0.457565 -0.75337997 0.23136999
+
+-0.45830502 -0.75790001 0.34023998
+-0.49940498 -0.74658997 0.33923
+-0.47864498 -0.74934998 0.25862
+
+0.39172501 -0.75321999 0.22577
+0.46587502 -0.74139 0.21201
+0.40481499 -0.73542999 0.28509001
+
+-0.230425 -0.75021004 -0.08579
+-0.25025499 -0.76152 -0.04266
+-0.275595 -0.76456001 -0.06335
+
+-0.19269501 -0.75025002 -0.15227
+-0.20012501 -0.73857002 -0.12739
+-0.230425 -0.75021004 -0.08579
+
+-0.230425 -0.75021004 -0.08579
+-0.228295 -0.73980003 -0.05803
+-0.25025499 -0.76152 -0.04266
+
+-0.20019501 -0.76468002 -0.19624001
+-0.19269501 -0.75025002 -0.15227
+-0.275595 -0.76456001 -0.06335
+
+-0.43411499 -0.75475998 0.44608002
+-0.49940498 -0.74658997 0.33923
+-0.45830502 -0.75790001 0.34023998
+
+-0.34414501 -0.48889999 0.33360001
+-0.272745 -0.45799 0.41743
+-0.34850498 -0.42101002 0.38814999
+
+0.141325 -0.71446999 0.04894
+-0.031635 -0.71653999 -0.15134
+0.18418501 -0.71306999 -0.11163
+
+-0.20019501 -0.76468002 -0.19624001
+-0.126185 -0.73445999 -0.17226
+-0.19269501 -0.75025002 -0.15227
+
+-0.244305 -0.76299004 -0.00343
+-0.21838499 -0.76528 0.04031
+-0.252265 -0.76543999 0.06978
+
+0.34330502 -0.75508003 0.23577999
+0.35800499 -0.74028 0.20723
+0.37518501 -0.73981003 0.19209999
+
+0.268925 -0.75015999 0.45092999
+0.145115 -0.74193001 0.48983002
+-0.088955 -0.75287003 0.51883999
+
+-0.437295 -0.37362999 0.41646999
+-0.47914501 -0.41923 0.35875
+-0.35775501 -0.44438 0.37122002
+
+-0.19269501 -0.75025002 -0.15227
+-0.157735 -0.71690002 -0.13885
+-0.20012501 -0.73857002 -0.12739
+
+-0.212265 -0.71635002 -0.05771
+-0.20012501 -0.73857002 -0.12739
+-0.157735 -0.71690002 -0.13885
+
+-0.212265 -0.71635002 -0.05771
+-0.228295 -0.73980003 -0.05803
+-0.230425 -0.75021004 -0.08579
+
+-0.21838499 -0.76528 0.04031
+-0.20473499 -0.76521004 0.06109
+-0.252265 -0.76543999 0.06978
+
+-0.302635 -0.74605003 0.09617
+-0.252265 -0.76543999 0.06978
+-0.23188499 -0.74691002 0.11138
+
+0.18217501 -0.72101997 0.24479
+0.250725 -0.71367996 0.32457001
+0.145855 -0.70772003 0.36983002
+
+-0.20019501 -0.76468002 -0.19624001
+-0.124075 -0.75598 -0.18927
+-0.126185 -0.73445999 -0.17226
+
+-0.212265 -0.71635002 -0.05771
+-0.230425 -0.75021004 -0.08579
+-0.20012501 -0.73857002 -0.12739
+
+-0.23126499 -0.75763 -0.00567
+-0.23070499 -0.76289001 0.01753
+-0.244305 -0.76299004 -0.00343
+
+-0.341875 -0.76486 0.26566999
+-0.33710499 -0.76268997 0.2824
+-0.35217499 -0.76522003 0.26378
+
+-0.43411499 -0.75475998 0.44608002
+-0.257085 -0.75538002 0.41583
+-0.307395 -0.74459 0.46473999
+
+-0.42102501 -0.74413002 0.47407001
+-0.40310501 -0.70723999 0.48404999
+-0.44044498 -0.72050003 0.46478001
+
+0.18217501 -0.72101997 0.24479
+0.22463499 -0.75526001 0.22989
+0.249485 -0.73458 0.28882999
+
+0.222605 -0.71620003 -0.04485
+0.21626499 -0.75853996 0.0299
+0.141325 -0.71446999 0.04894
+
+-0.18956499 -0.71819 -0.03302
+-0.199555 -0.71782997 -0.03538
+-0.204055 -0.71999001 -0.05273
+
+-0.21838499 -0.76528 0.04031
+-0.244305 -0.76299004 -0.00343
+-0.23070499 -0.76289001 0.01753
+
+-0.21987499 -0.76162003 0.01856
+-0.21838499 -0.76528 0.04031
+-0.23070499 -0.76289001 0.01753
+
+-0.457565 -0.75337997 0.23136999
+-0.37178501 -0.76844002 0.17385
+-0.35217499 -0.76522003 0.26378
+
+-0.33710499 -0.76268997 0.2824
+-0.286705 -0.76327003 0.29353001
+-0.25963499 -0.76286003 0.28113001
+
+-0.126185 -0.73445999 -0.17226
+-0.157735 -0.71690002 -0.13885
+-0.19269501 -0.75025002 -0.15227
+
+-0.18640499 -0.71848999 -0.01372
+-0.18956499 -0.71819 -0.03302
+-0.204055 -0.71999001 -0.05273
+
+-0.42102501 -0.74413002 0.47407001
+-0.47779499 -0.74220001 0.42571999
+-0.43411499 -0.75475998 0.44608002
+
+-0.43411499 -0.75475998 0.44608002
+-0.45830502 -0.75790001 0.34023998
+-0.33710499 -0.76268997 0.2824
+
+-0.37914501 -0.74181999 0.48116001
+-0.42102501 -0.74413002 0.47407001
+-0.43411499 -0.75475998 0.44608002
+
+0.250725 -0.71367996 0.32457001
+0.18217501 -0.72101997 0.24479
+0.249485 -0.73458 0.28882999
+
+0.282605 -0.72681999 -0.21195999
+0.302465 -0.72740997 -0.204
+0.269445 -0.75794998 -0.18476999
+
+-0.124075 -0.75598 -0.18927
+-0.031635 -0.71653999 -0.15134
+-0.126185 -0.73445999 -0.17226
+
+-0.21838499 -0.76528 0.04031
+-0.207995 -0.76482002 0.04198
+-0.20473499 -0.76521004 0.06109
+
+-0.302635 -0.74605003 0.09617
+-0.31338499 -0.75958 0.08819
+-0.252265 -0.76543999 0.06978
+
+-0.35217499 -0.76522003 0.26378
+-0.33710499 -0.76268997 0.2824
+-0.45830502 -0.75790001 0.34023998
+
+-0.37914501 -0.74181999 0.48116001
+-0.40310501 -0.70723999 0.48404999
+-0.42102501 -0.74413002 0.47407001
+
+-0.20019501 -0.76468002 -0.19624001
+-0.176455 -0.76629997 -0.28367001
+0.011285 -0.76453003 -0.22976
+
+0.369995 -0.75161003 -0.02044
+0.39260502 -0.67114998 -0.11193
+0.40176498 -0.71222 -0.03167
+
+0.473535 -0.68335999 0.30688
+0.40481499 -0.73542999 0.28509001
+0.544925 -0.67612 0.29681999
+
+-0.031635 -0.71653999 -0.15134
+-0.098815 -0.71488998 -0.14756
+-0.126185 -0.73445999 -0.17226
+
+-0.152335 -0.71831001 0.01116
+-0.176385 -0.71885002 -0.01135
+-0.18640499 -0.71848999 -0.01372
+
+0.44266499 -0.61000999 0.39195
+0.367225 -0.65199997 0.44060001
+0.390485 -0.69848 0.41848
+
+0.136425 -0.71731003 0.08693
+-0.113155 -0.72134003 0.07626
+0.141325 -0.71446999 0.04894
+
+0.023935 -0.75346001 0.45659
+-0.013045 -0.75356003 0.46638
+0.003695 -0.75341003 0.45222
+
+0.21626499 -0.75853996 0.0299
+0.37679501 -0.75690002 0.04199
+0.275065 -0.74995003 0.05247
+
+-0.124075 -0.75598 -0.18927
+-0.20019501 -0.76468002 -0.19624001
+0.011285 -0.76453003 -0.22976
+
+-0.098815 -0.71488998 -0.14756
+-0.157735 -0.71690002 -0.13885
+-0.126185 -0.73445999 -0.17226
+
+-0.152335 -0.71831001 0.01116
+-0.18640499 -0.71848999 -0.01372
+-0.204055 -0.71999001 -0.05273
+
+-0.119005 -0.73551003 0.54847
+-0.158775 -0.70517998 0.52299
+-0.167295 -0.74737 0.49738998
+
+-0.097395 -0.72411003 0.17242001
+0.141225 -0.72126999 0.18233999
+0.034255 -0.70801003 0.40098999
+
+-0.152335 -0.71831001 0.01116
+-0.17276501 -0.71839996 0.00712
+-0.176385 -0.71885002 -0.01135
+
+-0.18067499 -0.76468002 0.08361
+-0.20473499 -0.76521004 0.06109
+-0.183915 -0.76429001 0.06451
+
+0.57481499 -0.63938 0.32445999
+0.544925 -0.67612 0.29681999
+0.63936501 -0.64530998 0.26995001
+
+0.247805 -0.73291 -0.06195
+0.21626499 -0.75853996 0.0299
+0.222605 -0.71620003 -0.04485
+
+-0.166565 -0.76378998 0.10376
+-0.20473499 -0.76521004 0.06109
+-0.18067499 -0.76468002 0.08361
+
+-0.35217499 -0.76522003 0.26378
+-0.45830502 -0.75790001 0.34023998
+-0.457565 -0.75337997 0.23136999
+
+-0.67350502 -0.31801001 0.21348
+-0.67019501 -0.33046001 0.17235001
+-0.63988499 -0.38061001 0.17080999
+
+0.136425 -0.71731003 0.08693
+0.141225 -0.72126999 0.18233999
+-0.113155 -0.72134003 0.07626
+
+-0.088955 -0.75287003 0.51883999
+-0.124945 -0.75449997 0.44332001
+-0.013045 -0.75356003 0.46638
+
+-0.043565 -0.73834 0.55035999
+-0.107665 -0.74504997 0.54255001
+-0.088955 -0.75287003 0.51883999
+
+-0.16981501 -0.76339996 0.08462
+-0.166565 -0.76378998 0.10376
+-0.18067499 -0.76468002 0.08361
+
+-0.18321501 -0.75733002 0.1487
+-0.215165 -0.74110001 0.12757
+-0.23188499 -0.74691002 0.11138
+
+-0.37914501 -0.74181999 0.48116001
+-0.43411499 -0.75475998 0.44608002
+-0.307395 -0.74459 0.46473999
+
+0.247805 -0.73291 -0.06195
+0.231395 -0.71984001 -0.09604
+0.28172501 -0.75823997 -0.05062
+
+0.182815 -0.75714996 0.16868999
+0.227675 -0.76184998 0.16388
+0.23355499 -0.75731003 0.17916
+
+-0.096785 -0.71277 0.39598999
+-0.100605 -0.71330002 0.37792
+-0.126875 -0.71792 0.35866001
+
+-0.212265 -0.71635002 -0.05771
+-0.157735 -0.71690002 -0.13885
+-0.098815 -0.71488998 -0.14756
+
+-0.139575 -0.71986 0.03333
+-0.149585 -0.71949997 0.03095
+-0.152335 -0.71831001 0.01116
+
+-0.18321501 -0.75733002 0.1487
+-0.20473499 -0.76521004 0.06109
+-0.166565 -0.76378998 0.10376
+
+-0.252265 -0.76543999 0.06978
+-0.18321501 -0.75733002 0.1487
+-0.23188499 -0.74691002 0.11138
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/main.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/main.cpp
new file mode 100644
index 00000000..816f1881
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/main.cpp
@@ -0,0 +1,372 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include <GL/glut.h>
+#include "PQP.h"
+#include "model.h"
+#include "MatVec.h"
+
+PQP_Model bunny, torus;
+Model *bunny_to_draw, *torus_to_draw;
+
+int mode;
+double beginx, beginy;
+double dis = 10.0, azim = 0.0, elev = 0.0;
+double ddis = 0.0, dazim = 0.0, delev = 0.0;
+double rot1 = 0.0, rot2 = 0.0, rot3 = 0.0;
+int animate = 0;
+
+void
+InitViewerWindow()
+{
+ GLfloat Ambient[] = { 0.2f, 0.2f, 0.2f, 1.0f };
+ GLfloat Diffuse[] = { 0.8f, 0.8f, 0.8f, 1.0f };
+ GLfloat Specular[] = { 0.2f, 0.2f, 0.2f, 1.0f };
+ GLfloat SpecularExp[] = { 50 };
+ GLfloat Emission[] = { 0.1f, 0.1f, 0.1f, 1.0f };
+
+ glMaterialfv(GL_FRONT, GL_AMBIENT, Ambient);
+ glMaterialfv(GL_FRONT, GL_DIFFUSE, Diffuse);
+ glMaterialfv(GL_FRONT, GL_SPECULAR, Specular);
+ glMaterialfv(GL_FRONT, GL_SHININESS, SpecularExp);
+ glMaterialfv(GL_FRONT, GL_EMISSION, Emission);
+
+ glMaterialfv(GL_BACK, GL_AMBIENT, Ambient);
+ glMaterialfv(GL_BACK, GL_DIFFUSE, Diffuse);
+ glMaterialfv(GL_BACK, GL_SPECULAR, Specular);
+ glMaterialfv(GL_BACK, GL_SHININESS, SpecularExp);
+ glMaterialfv(GL_BACK, GL_EMISSION, Emission);
+
+ glColorMaterial(GL_FRONT_AND_BACK, GL_DIFFUSE);
+
+ glEnable(GL_COLOR_MATERIAL);
+
+ GLfloat light_position[] = { 1.0, 1.0, 1.0, 0.0 };
+ glLightfv(GL_LIGHT0, GL_POSITION, light_position);
+ glEnable(GL_LIGHT0);
+ glEnable(GL_LIGHTING);
+ glLightModeli(GL_LIGHT_MODEL_TWO_SIDE, GL_TRUE);
+
+ glDepthFunc(GL_LEQUAL);
+ glEnable(GL_DEPTH_TEST);
+
+ glShadeModel(GL_FLAT);
+ glClearColor(0.0, 0.0, 0.0, 0.0);
+
+ glEnable(GL_CULL_FACE);
+ glCullFace(GL_BACK);
+ glEnable(GL_NORMALIZE);
+
+ glMatrixMode(GL_PROJECTION);
+ glLoadIdentity();
+ glFrustum(-0.004,0.004,-0.004,0.004,.01,100.0);
+
+ glMatrixMode(GL_MODELVIEW);
+}
+
+void
+KeyboardCB(unsigned char key, int x, int y)
+{
+ switch(key)
+ {
+ case 'q': delete bunny_to_draw; delete torus_to_draw; exit(0);
+ default: animate = 1 - animate;
+ }
+
+ glutPostRedisplay();
+}
+
+void
+MouseCB(int _b, int _s, int _x, int _y)
+{
+ if (_s == GLUT_UP)
+ {
+ dis += ddis;
+ azim += dazim;
+ elev += delev;
+ ddis = 0.0;
+ dazim = 0.0;
+ delev = 0.0;
+ return;
+ }
+
+ if (_b == GLUT_RIGHT_BUTTON)
+ {
+ mode = 0;
+ beginy = _y;
+ return;
+ }
+ else
+ {
+ mode = 1;
+ beginx = _x;
+ beginy = _y;
+ }
+}
+
+void
+MotionCB(int _x, int _y)
+{
+ if (mode == 0)
+ {
+ ddis = dis * (_y - beginy)/200.0;
+ }
+ else
+ {
+ dazim = (_x - beginx)/5.0;
+ delev = (_y - beginy)/5.0;
+ }
+
+ glutPostRedisplay();
+}
+
+inline void glVertex3v(float V[3]) { glVertex3fv(V); }
+inline void glVertex3v(double V[3]) { glVertex3dv(V); }
+
+void
+BeginDraw()
+{
+ glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT);
+
+ glLoadIdentity();
+ glTranslatef(0.0, 0.0, -(dis+ddis));
+ glRotated(elev+delev, 1.0, 0.0, 0.0);
+ glRotated(azim+dazim, 0.0, 1.0, 0.0);
+}
+
+void
+EndDraw()
+{
+ glFlush();
+ glutSwapBuffers();
+}
+
+void
+IdleCB()
+{
+ glutPostRedisplay();
+}
+
+void
+DisplayCB()
+{
+ BeginDraw();
+
+ // set up model transformations
+
+ if (animate)
+ {
+ rot1 += .1;
+ rot2 += .2;
+ rot3 += .3;
+ }
+
+ PQP_REAL R1[3][3],R2[3][3],T1[3],T2[3];
+ PQP_REAL M1[3][3],M2[3][3],M3[3][3];
+
+ T1[0] = -1;
+ T1[1] = 0.0;
+ T1[2] = 0.0;
+
+ T2[0] = 1;
+ T2[1] = 0.0;
+ T2[2] = 0.0;
+
+ MRotX(M1,rot1);
+ MRotY(M2,rot2);
+ MxM(M3,M1,M2);
+ MRotZ(M1,rot3);
+ MxM(R1,M3,M1);
+
+ MRotX(M1,rot3);
+ MRotY(M2,rot1);
+ MxM(M3,M1,M2);
+ MRotZ(M1,rot2);
+ MxM(R2,M3,M1);
+
+ // perform distance query
+
+ PQP_REAL rel_err = 0.0;
+ PQP_REAL abs_err = 0.0;
+ PQP_DistanceResult res;
+ PQP_Distance(&res,R1,T1,&bunny,R2,T2,&torus,rel_err,abs_err);
+
+ // draw the models
+
+ glColor3d(0.0,0.0,1.0);
+ double oglm[16];
+ MVtoOGL(oglm,R1,T1);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ bunny_to_draw->Draw();
+ glPopMatrix();
+
+ glColor3d(0.0,1.0,0.0);
+ MVtoOGL(oglm,R2,T2);
+ glPushMatrix();
+ glMultMatrixd(oglm);
+ torus_to_draw->Draw();
+ glPopMatrix();
+
+ // draw the closest points as small spheres
+
+ glColor3d(1.0,0.0,0.0);
+
+ PQP_REAL P1[3],P2[3],V1[3],V2[3];
+ VcV(P1,res.P1());
+ VcV(P2,res.P2());
+
+ // each point is in the space of its model;
+ // transform to world space
+
+ MxVpV(V1,R1,P1,T1);
+
+ glPushMatrix();
+ glTranslated(V1[0],V1[1],V1[2]);
+ glutSolidSphere(.05,15,15);
+ glPopMatrix();
+
+ MxVpV(V2,R2,P2,T2);
+
+ glPushMatrix();
+ glTranslated(V2[0],V2[1],V2[2]);
+ glutSolidSphere(.05,15,15);
+ glPopMatrix();
+
+ // draw the line between the closest points
+
+ glDisable(GL_LIGHTING);
+ glBegin(GL_LINES);
+ glVertex3v(V1);
+ glVertex3v(V2);
+ glEnd();
+ glEnable(GL_LIGHTING);
+
+ EndDraw();
+}
+
+void main(int argc, char **argv)
+{
+ glutInit(&argc, argv);
+ glutInitDisplayMode (GLUT_DOUBLE | GLUT_RGB | GLUT_DEPTH | GLUT_MULTISAMPLE);
+
+ // create the window
+
+ glutCreateWindow("PQP Demo - Spinning");
+
+ // set OpenGL graphics state -- material props, perspective, etc.
+
+ InitViewerWindow();
+
+ // set the callbacks
+
+ glutDisplayFunc(DisplayCB);
+ glutIdleFunc(IdleCB);
+ glutMouseFunc(MouseCB);
+ glutMotionFunc(MotionCB);
+ glutKeyboardFunc(KeyboardCB);
+
+ // initialize the bunny
+
+ FILE *fp;
+ int i, ntris;
+
+ bunny_to_draw = new Model("bunny.tris");
+
+ fp = fopen("bunny.tris","r");
+ if (fp == NULL) { fprintf(stderr,"Couldn't open bunny.tris\n"); exit(-1); }
+ fscanf(fp,"%d",&ntris);
+
+ bunny.BeginModel();
+ for (i = 0; i < ntris; i++)
+ {
+ double p1x,p1y,p1z,p2x,p2y,p2z,p3x,p3y,p3z;
+ fscanf(fp,"%lf %lf %lf %lf %lf %lf %lf %lf %lf",
+ &p1x,&p1y,&p1z,&p2x,&p2y,&p2z,&p3x,&p3y,&p3z);
+ PQP_REAL p1[3],p2[3],p3[3];
+ p1[0] = (PQP_REAL)p1x; p1[1] = (PQP_REAL)p1y; p1[2] = (PQP_REAL)p1z;
+ p2[0] = (PQP_REAL)p2x; p2[1] = (PQP_REAL)p2y; p2[2] = (PQP_REAL)p2z;
+ p3[0] = (PQP_REAL)p3x; p3[1] = (PQP_REAL)p3y; p3[2] = (PQP_REAL)p3z;
+ bunny.AddTri(p1,p2,p3,i);
+ }
+ bunny.EndModel();
+ fclose(fp);
+
+ // initialize the torus
+
+ torus_to_draw = new Model("torus.tris");
+
+ fp = fopen("torus.tris","r");
+ if (fp == NULL) { fprintf(stderr,"Couldn't open torus.tris\n"); exit(-1); }
+ fscanf(fp,"%d",&ntris);
+
+ torus.BeginModel();
+ for (i = 0; i < ntris; i++)
+ {
+ double p1x,p1y,p1z,p2x,p2y,p2z,p3x,p3y,p3z;
+ fscanf(fp,"%lf %lf %lf %lf %lf %lf %lf %lf %lf",
+ &p1x,&p1y,&p1z,&p2x,&p2y,&p2z,&p3x,&p3y,&p3z);
+ PQP_REAL p1[3],p2[3],p3[3];
+ p1[0] = (PQP_REAL)p1x; p1[1] = (PQP_REAL)p1y; p1[2] = (PQP_REAL)p1z;
+ p2[0] = (PQP_REAL)p2x; p2[1] = (PQP_REAL)p2y; p2[2] = (PQP_REAL)p2z;
+ p3[0] = (PQP_REAL)p3x; p3[1] = (PQP_REAL)p3y; p3[2] = (PQP_REAL)p3z;
+ torus.AddTri(p1,p2,p3,i);
+ }
+ torus.EndModel();
+ fclose(fp);
+
+ // print instructions
+
+ printf("PQP Demo - Spinning:\n"
+ "Press 'q' to quit.\n"
+ "Press any other key to toggle animation.\n"
+ "Left-drag left & right to change angle of view.\n"
+ "Left-drag up & down to change elevation of view.\n"
+ "Right-drag up & down to change distance of view.\n");
+
+ // Enter the main loop.
+
+ glutMainLoop();
+}
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.cpp
new file mode 100644
index 00000000..e145b31b
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.cpp
@@ -0,0 +1,144 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include "GL/glut.h"
+#include "model.h"
+
+inline
+void
+VmV(double Vr[3], const double V1[3], const double V2[3])
+{
+ Vr[0] = V1[0] - V2[0];
+ Vr[1] = V1[1] - V2[1];
+ Vr[2] = V1[2] - V2[2];
+}
+
+inline
+void
+VcrossV(double Vr[3], const double V1[3], const double V2[3])
+{
+ Vr[0] = V1[1]*V2[2] - V1[2]*V2[1];
+ Vr[1] = V1[2]*V2[0] - V1[0]*V2[2];
+ Vr[2] = V1[0]*V2[1] - V1[1]*V2[0];
+}
+
+inline
+void
+Vnormalize(double V[3])
+{
+ double d = 1.0 / sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+ V[0] *= d;
+ V[1] *= d;
+ V[2] *= d;
+}
+
+Model::Model(char *tris_file)
+{
+ FILE *fp = fopen(tris_file,"r");
+ if (fp == NULL)
+ {
+ fprintf(stderr,"Model Constructor: Couldn't open %s\n",tris_file);
+ exit(-1);
+ }
+
+ fscanf(fp,"%d",&ntris);
+ tri = new ModelTri[ntris];
+
+ int i;
+
+ for (i = 0; i < ntris; i++)
+ {
+ // read the tri verts
+
+ fscanf(fp,"%lf %lf %lf %lf %lf %lf %lf %lf %lf",
+ &tri[i].p0[0], &tri[i].p0[1], &tri[i].p0[2],
+ &tri[i].p1[0], &tri[i].p1[1], &tri[i].p1[2],
+ &tri[i].p2[0], &tri[i].p2[1], &tri[i].p2[2]);
+
+ // set the normal
+
+ double a[3],b[3];
+ VmV(a,tri[i].p1,tri[i].p0);
+ VmV(b,tri[i].p2,tri[i].p0);
+ VcrossV(tri[i].n,a,b);
+ Vnormalize(tri[i].n);
+ }
+
+ fclose(fp);
+
+ // generate display list
+
+ display_list = glGenLists(1);
+ glNewList(display_list,GL_COMPILE);
+ glBegin(GL_TRIANGLES);
+ for (i = 0; i < ntris; i++)
+ {
+ glNormal3dv(tri[i].n);
+ glVertex3dv(tri[i].p0);
+ glVertex3dv(tri[i].p1);
+ glVertex3dv(tri[i].p2);
+ }
+ glEnd();
+ glEndList();
+}
+
+Model::~Model()
+{
+ delete [] tri;
+}
+
+void
+Model::Draw()
+{
+ glCallList(display_list);
+}
+
+void
+Model::DrawTri(int index)
+{
+ glBegin(GL_TRIANGLES);
+ glVertex3dv(tri[index].p0);
+ glVertex3dv(tri[index].p1);
+ glVertex3dv(tri[index].p2);
+ glEnd();
+}
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.h
new file mode 100644
index 00000000..df352e4e
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/model.h
@@ -0,0 +1,63 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef MODEL_H
+#define MODEL_H
+
+struct ModelTri
+{
+ double p0[3], p1[3], p2[3];
+ double n[3];
+};
+
+class Model
+{
+ int ntris;
+ ModelTri *tri;
+ int display_list;
+
+public:
+ Model(char *tris_file);
+ ~Model();
+ void Draw();
+ void DrawTri(int index);
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.dsp b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.dsp
new file mode 100644
index 00000000..b31912aa
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.dsp
@@ -0,0 +1,98 @@
+# Microsoft Developer Studio Project File - Name="spinning" - Package Owner=<4>
+# Microsoft Developer Studio Generated Build File, Format Version 5.00
+# ** DO NOT EDIT **
+
+# TARGTYPE "Win32 (x86) Console Application" 0x0103
+
+CFG=spinning - Win32 Debug
+!MESSAGE This is not a valid makefile. To build this project using NMAKE,
+!MESSAGE use the Export Makefile command and run
+!MESSAGE
+!MESSAGE NMAKE /f "spinning.mak".
+!MESSAGE
+!MESSAGE You can specify a configuration when running NMAKE
+!MESSAGE by defining the macro CFG on the command line. For example:
+!MESSAGE
+!MESSAGE NMAKE /f "spinning.mak" CFG="spinning - Win32 Debug"
+!MESSAGE
+!MESSAGE Possible choices for configuration are:
+!MESSAGE
+!MESSAGE "spinning - Win32 Release" (based on\
+ "Win32 (x86) Console Application")
+!MESSAGE "spinning - Win32 Debug" (based on "Win32 (x86) Console Application")
+!MESSAGE
+
+# Begin Project
+# PROP Scc_ProjName ""
+# PROP Scc_LocalPath ""
+CPP=xicl5.exe
+RSC=rc.exe
+
+!IF "$(CFG)" == "spinning - Win32 Release"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 0
+# PROP BASE Output_Dir "Release"
+# PROP BASE Intermediate_Dir "Release"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 0
+# PROP Output_Dir "./"
+# PROP Intermediate_Dir "Release"
+# PROP Ignore_Export_Lib 0
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /GX /O2 /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "NDEBUG"
+# ADD RSC /l 0x409 /d "NDEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=xilink5.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /machine:I386
+# ADD LINK32 glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /pdb:none /machine:I386 /libpath:"..\..\lib"
+
+!ELSEIF "$(CFG)" == "spinning - Win32 Debug"
+
+# PROP BASE Use_MFC 0
+# PROP BASE Use_Debug_Libraries 1
+# PROP BASE Output_Dir "spinning"
+# PROP BASE Intermediate_Dir "spinning"
+# PROP BASE Target_Dir ""
+# PROP Use_MFC 0
+# PROP Use_Debug_Libraries 1
+# PROP Output_Dir "./"
+# PROP Intermediate_Dir "Debug"
+# PROP Ignore_Export_Lib 0
+# PROP Target_Dir ""
+# ADD BASE CPP /nologo /W3 /Gm /GX /Zi /Od /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD CPP /nologo /W3 /GX /Od /I "..\..\include" /D "WIN32" /D "_DEBUG" /D "_CONSOLE" /D "_MBCS" /YX /FD /c
+# ADD BASE RSC /l 0x409 /d "_DEBUG"
+# ADD RSC /l 0x409 /d "_DEBUG"
+BSC32=bscmake.exe
+# ADD BASE BSC32 /nologo
+# ADD BSC32 /nologo
+LINK32=xilink5.exe
+# ADD BASE LINK32 kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib /nologo /subsystem:console /debug /machine:I386 /pdbtype:sept
+# ADD LINK32 glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /pdb:none /debug /machine:I386 /libpath:"..\..\lib"
+
+!ENDIF
+
+# Begin Target
+
+# Name "spinning - Win32 Release"
+# Name "spinning - Win32 Debug"
+# Begin Source File
+
+SOURCE=.\main.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\model.cpp
+# End Source File
+# Begin Source File
+
+SOURCE=.\model.h
+# End Source File
+# End Target
+# End Project
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.plg b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.plg
new file mode 100644
index 00000000..d8ee3728
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/spinning.plg
@@ -0,0 +1,27 @@
+--------------------Configuration: spinning - Win32 Release--------------------
+Begining build with project "C:\WIN95\DESKTOP\PQP_v1.2.1\demos\spinning\spinning.dsp", at root.
+Active configuration is Win32 (x86) Console Application (based on Win32 (x86) Console Application)
+
+Project's tools are:
+ "32-bit C/C++ Compiler for 80x86" with flags "/nologo /ML /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /Fp"Release/spinning.pch" /YX /Fo"Release/" /Fd"Release/" /FD /c "
+ "Win32 Resource Compiler" with flags "/l 0x409 /d "NDEBUG" "
+ "Browser Database Maker" with flags "/nologo /o"./spinning.bsc" "
+ "COFF Linker for 80x86" with flags "glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /pdb:none /machine:I386 /out:"./spinning.exe" /libpath:"..\..\lib" "
+ "Custom Build" with flags ""
+ "<Component 0xa>" with flags ""
+
+Creating temp file "C:\WIN95\TEMP\RSP9380.TMP" with contents </nologo /ML /W3 /GX /O2 /I "..\..\include" /D "WIN32" /D "NDEBUG" /D "_CONSOLE" /D "_MBCS" /Fp"Release/spinning.pch" /YX /Fo"Release/" /Fd"Release/" /FD /c
+"C:\WIN95\DESKTOP\PQP_v1.2.1\demos\spinning\main.cpp"
+>
+Creating command line "cl.exe @C:\WIN95\TEMP\RSP9380.TMP"
+Creating temp file "C:\WIN95\TEMP\RSP9381.TMP" with contents <glut32.lib opengl32.lib kernel32.lib user32.lib gdi32.lib winspool.lib comdlg32.lib advapi32.lib shell32.lib ole32.lib oleaut32.lib uuid.lib odbc32.lib odbccp32.lib pqp.lib /nologo /subsystem:console /pdb:none /machine:I386 /out:"./spinning.exe" /libpath:"..\..\lib"
+.\Release\main.obj
+.\Release\model.obj>
+Creating command line "link.exe @C:\WIN95\TEMP\RSP9381.TMP"
+Compiling...
+main.cpp
+Linking...
+
+
+
+spinning.exe - 0 error(s), 0 warning(s)
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/torus.tris b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/torus.tris
new file mode 100644
index 00000000..a0bc4507
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/demos/spinning/torus.tris
@@ -0,0 +1,5329 @@
+1332
+0.58 0 0
+0.571657 0.0980205 0.033314
+0.569145 0 0.0615636
+
+0.560958 0.0961859 0.0948776
+0.569145 0 0.0615636
+0.571657 0.0980205 0.033314
+
+0.569145 0 0.0615636
+0.560958 0.0961859 0.0948776
+0.537888 0 0.115702
+
+0.530151 0.0909035 0.149016
+0.537888 0 0.115702
+0.560958 0.0961859 0.0948776
+
+0.537888 0 0.115702
+0.530151 0.0909035 0.149016
+0.49 0 0.155885
+
+0.482952 0.0828104 0.189199
+0.49 0 0.155885
+0.530151 0.0909035 0.149016
+
+0.49 0 0.155885
+0.482952 0.0828104 0.189199
+0.431257 0 0.177265
+
+0.425053 0.0728827 0.210579
+0.431257 0 0.177265
+0.482952 0.0828104 0.189199
+
+0.431257 0 0.177265
+0.425053 0.0728827 0.210579
+0.368743 0 0.177265
+
+0.363439 0.0623179 0.210579
+0.368743 0 0.177265
+0.425053 0.0728827 0.210579
+
+0.368743 0 0.177265
+0.363439 0.0623179 0.210579
+0.31 0 0.155885
+
+0.305541 0.0523903 0.189199
+0.31 0 0.155885
+0.363439 0.0623179 0.210579
+
+0.31 0 0.155885
+0.305541 0.0523903 0.189199
+0.262112 0 0.115702
+
+0.258342 0.0442971 0.149016
+0.262112 0 0.115702
+0.305541 0.0523903 0.189199
+
+0.262112 0 0.115702
+0.258342 0.0442971 0.149016
+0.230855 0 0.0615636
+
+0.227535 0.0390147 0.0948776
+0.230855 0 0.0615636
+0.258342 0.0442971 0.149016
+
+0.230855 0 0.0615636
+0.227535 0.0390147 0.0948776
+0.22 0 0
+
+0.216836 0.0371802 0.033314
+0.22 0 0
+0.227535 0.0390147 0.0948776
+
+0.22 0 0
+0.216836 0.0371802 0.033314
+0.230855 0 -0.0615636
+
+0.227535 0.0390147 -0.0282496
+0.230855 0 -0.0615636
+0.216836 0.0371802 0.033314
+
+0.230855 0 -0.0615636
+0.227535 0.0390147 -0.0282496
+0.262112 0 -0.115702
+
+0.258342 0.0442971 -0.0823878
+0.262112 0 -0.115702
+0.227535 0.0390147 -0.0282496
+
+0.262112 0 -0.115702
+0.258342 0.0442971 -0.0823878
+0.31 0 -0.155885
+
+0.305541 0.0523903 -0.122571
+0.31 0 -0.155885
+0.258342 0.0442971 -0.0823878
+
+0.31 0 -0.155885
+0.305541 0.0523903 -0.122571
+0.368743 0 -0.177265
+
+0.363439 0.0623179 -0.143951
+0.368743 0 -0.177265
+0.305541 0.0523903 -0.122571
+
+0.368743 0 -0.177265
+0.363439 0.0623179 -0.143951
+0.431257 0 -0.177265
+
+0.425053 0.0728827 -0.143951
+0.431257 0 -0.177265
+0.363439 0.0623179 -0.143951
+
+0.431257 0 -0.177265
+0.425053 0.0728827 -0.143951
+0.49 0 -0.155885
+
+0.482952 0.0828104 -0.122571
+0.49 0 -0.155885
+0.425053 0.0728827 -0.143951
+
+0.49 0 -0.155885
+0.482952 0.0828104 -0.122571
+0.537888 0 -0.115702
+
+0.530151 0.0909035 -0.0823878
+0.537888 0 -0.115702
+0.482952 0.0828104 -0.122571
+
+0.537888 0 -0.115702
+0.530151 0.0909035 -0.0823878
+0.569145 0 -0.0615636
+
+0.560958 0.0961859 -0.0282496
+0.569145 0 -0.0615636
+0.530151 0.0909035 -0.0823878
+
+0.569145 0 -0.0615636
+0.560958 0.0961859 -0.0282496
+0.58 0 0
+
+0.571657 0.0980205 0.033314
+0.58 0 0
+0.560958 0.0961859 -0.0282496
+
+0.571657 0.0980205 0.033314
+0.546869 0.193221 0.062822
+0.560958 0.0961859 0.0948776
+
+0.536634 0.189605 0.124386
+0.560958 0.0961859 0.0948776
+0.546869 0.193221 0.062822
+
+0.560958 0.0961859 0.0948776
+0.536634 0.189605 0.124386
+0.530151 0.0909035 0.149016
+
+0.507162 0.179192 0.178524
+0.530151 0.0909035 0.149016
+0.536634 0.189605 0.124386
+
+0.530151 0.0909035 0.149016
+0.507162 0.179192 0.178524
+0.482952 0.0828104 0.189199
+
+0.46201 0.163238 0.218707
+0.482952 0.0828104 0.189199
+0.507162 0.179192 0.178524
+
+0.482952 0.0828104 0.189199
+0.46201 0.163238 0.218707
+0.425053 0.0728827 0.210579
+
+0.406622 0.143669 0.240087
+0.425053 0.0728827 0.210579
+0.46201 0.163238 0.218707
+
+0.425053 0.0728827 0.210579
+0.406622 0.143669 0.240087
+0.363439 0.0623179 0.210579
+
+0.34768 0.122843 0.240087
+0.363439 0.0623179 0.210579
+0.406622 0.143669 0.240087
+
+0.363439 0.0623179 0.210579
+0.34768 0.122843 0.240087
+0.305541 0.0523903 0.189199
+
+0.292292 0.103273 0.218707
+0.305541 0.0523903 0.189199
+0.34768 0.122843 0.240087
+
+0.305541 0.0523903 0.189199
+0.292292 0.103273 0.218707
+0.258342 0.0442971 0.149016
+
+0.247139 0.0873199 0.178524
+0.258342 0.0442971 0.149016
+0.292292 0.103273 0.218707
+
+0.258342 0.0442971 0.149016
+0.247139 0.0873199 0.178524
+0.227535 0.0390147 0.0948776
+
+0.217668 0.0769071 0.124386
+0.227535 0.0390147 0.0948776
+0.247139 0.0873199 0.178524
+
+0.227535 0.0390147 0.0948776
+0.217668 0.0769071 0.124386
+0.216836 0.0371802 0.033314
+
+0.207433 0.0732908 0.062822
+0.216836 0.0371802 0.033314
+0.217668 0.0769071 0.124386
+
+0.216836 0.0371802 0.033314
+0.207433 0.0732908 0.062822
+0.227535 0.0390147 -0.0282496
+
+0.217668 0.0769071 0.00125837
+0.227535 0.0390147 -0.0282496
+0.207433 0.0732908 0.062822
+
+0.227535 0.0390147 -0.0282496
+0.217668 0.0769071 0.00125837
+0.258342 0.0442971 -0.0823878
+
+0.247139 0.0873199 -0.0528798
+0.258342 0.0442971 -0.0823878
+0.217668 0.0769071 0.00125837
+
+0.258342 0.0442971 -0.0823878
+0.247139 0.0873199 -0.0528798
+0.305541 0.0523903 -0.122571
+
+0.292292 0.103273 -0.0930626
+0.305541 0.0523903 -0.122571
+0.247139 0.0873199 -0.0528798
+
+0.305541 0.0523903 -0.122571
+0.292292 0.103273 -0.0930626
+0.363439 0.0623179 -0.143951
+
+0.34768 0.122843 -0.114443
+0.363439 0.0623179 -0.143951
+0.292292 0.103273 -0.0930626
+
+0.363439 0.0623179 -0.143951
+0.34768 0.122843 -0.114443
+0.425053 0.0728827 -0.143951
+
+0.406622 0.143669 -0.114443
+0.425053 0.0728827 -0.143951
+0.34768 0.122843 -0.114443
+
+0.425053 0.0728827 -0.143951
+0.406622 0.143669 -0.114443
+0.482952 0.0828104 -0.122571
+
+0.46201 0.163238 -0.0930626
+0.482952 0.0828104 -0.122571
+0.406622 0.143669 -0.114443
+
+0.482952 0.0828104 -0.122571
+0.46201 0.163238 -0.0930626
+0.530151 0.0909035 -0.0823878
+
+0.507162 0.179192 -0.0528798
+0.530151 0.0909035 -0.0823878
+0.46201 0.163238 -0.0930626
+
+0.530151 0.0909035 -0.0823878
+0.507162 0.179192 -0.0528798
+0.560958 0.0961859 -0.0282496
+
+0.536634 0.189605 0.00125837
+0.560958 0.0961859 -0.0282496
+0.507162 0.179192 -0.0528798
+
+0.560958 0.0961859 -0.0282496
+0.536634 0.189605 0.00125837
+0.571657 0.0980205 0.033314
+
+0.546869 0.193221 0.062822
+0.571657 0.0980205 0.033314
+0.536634 0.189605 0.00125837
+
+0.546869 0.193221 0.062822
+0.506348 0.282863 0.0851529
+0.536634 0.189605 0.124386
+
+0.496871 0.277569 0.146717
+0.536634 0.189605 0.124386
+0.506348 0.282863 0.0851529
+
+0.536634 0.189605 0.124386
+0.496871 0.277569 0.146717
+0.507162 0.179192 0.178524
+
+0.469584 0.262325 0.200855
+0.507162 0.179192 0.178524
+0.496871 0.277569 0.146717
+
+0.507162 0.179192 0.178524
+0.469584 0.262325 0.200855
+0.46201 0.163238 0.218707
+
+0.427777 0.238971 0.241037
+0.46201 0.163238 0.218707
+0.469584 0.262325 0.200855
+
+0.46201 0.163238 0.218707
+0.427777 0.238971 0.241037
+0.406622 0.143669 0.240087
+
+0.376493 0.210322 0.262418
+0.406622 0.143669 0.240087
+0.427777 0.238971 0.241037
+
+0.406622 0.143669 0.240087
+0.376493 0.210322 0.262418
+0.34768 0.122843 0.240087
+
+0.321918 0.179834 0.262418
+0.34768 0.122843 0.240087
+0.376493 0.210322 0.262418
+
+0.34768 0.122843 0.240087
+0.321918 0.179834 0.262418
+0.292292 0.103273 0.218707
+
+0.270634 0.151185 0.241037
+0.292292 0.103273 0.218707
+0.321918 0.179834 0.262418
+
+0.292292 0.103273 0.218707
+0.270634 0.151185 0.241037
+0.247139 0.0873199 0.178524
+
+0.228827 0.127831 0.200855
+0.247139 0.0873199 0.178524
+0.270634 0.151185 0.241037
+
+0.247139 0.0873199 0.178524
+0.228827 0.127831 0.200855
+0.217668 0.0769071 0.124386
+
+0.20154 0.112587 0.146717
+0.217668 0.0769071 0.124386
+0.228827 0.127831 0.200855
+
+0.217668 0.0769071 0.124386
+0.20154 0.112587 0.146717
+0.207433 0.0732908 0.062822
+
+0.192063 0.107293 0.0851529
+0.207433 0.0732908 0.062822
+0.20154 0.112587 0.146717
+
+0.207433 0.0732908 0.062822
+0.192063 0.107293 0.0851529
+0.217668 0.0769071 0.00125837
+
+0.20154 0.112587 0.0235893
+0.217668 0.0769071 0.00125837
+0.192063 0.107293 0.0851529
+
+0.217668 0.0769071 0.00125837
+0.20154 0.112587 0.0235893
+0.247139 0.0873199 -0.0528798
+
+0.228827 0.127831 -0.0305489
+0.247139 0.0873199 -0.0528798
+0.20154 0.112587 0.0235893
+
+0.247139 0.0873199 -0.0528798
+0.228827 0.127831 -0.0305489
+0.292292 0.103273 -0.0930626
+
+0.270634 0.151185 -0.0707317
+0.292292 0.103273 -0.0930626
+0.228827 0.127831 -0.0305489
+
+0.292292 0.103273 -0.0930626
+0.270634 0.151185 -0.0707317
+0.34768 0.122843 -0.114443
+
+0.321918 0.179834 -0.0921125
+0.34768 0.122843 -0.114443
+0.270634 0.151185 -0.0707317
+
+0.34768 0.122843 -0.114443
+0.321918 0.179834 -0.0921125
+0.406622 0.143669 -0.114443
+
+0.376493 0.210322 -0.0921125
+0.406622 0.143669 -0.114443
+0.321918 0.179834 -0.0921125
+
+0.406622 0.143669 -0.114443
+0.376493 0.210322 -0.0921125
+0.46201 0.163238 -0.0930626
+
+0.427777 0.238971 -0.0707317
+0.46201 0.163238 -0.0930626
+0.376493 0.210322 -0.0921125
+
+0.46201 0.163238 -0.0930626
+0.427777 0.238971 -0.0707317
+0.507162 0.179192 -0.0528798
+
+0.469584 0.262325 -0.0305489
+0.507162 0.179192 -0.0528798
+0.427777 0.238971 -0.0707317
+
+0.507162 0.179192 -0.0528798
+0.469584 0.262325 -0.0305489
+0.536634 0.189605 0.00125837
+
+0.496871 0.277569 0.0235893
+0.536634 0.189605 0.00125837
+0.469584 0.262325 -0.0305489
+
+0.536634 0.189605 0.00125837
+0.496871 0.277569 0.0235893
+0.546869 0.193221 0.062822
+
+0.506348 0.282863 0.0851529
+0.546869 0.193221 0.062822
+0.496871 0.277569 0.0235893
+
+0.506348 0.282863 0.0851529
+0.451261 0.364368 0.0977555
+0.496871 0.277569 0.146717
+
+0.442815 0.357548 0.159319
+0.496871 0.277569 0.146717
+0.451261 0.364368 0.0977555
+
+0.496871 0.277569 0.146717
+0.442815 0.357548 0.159319
+0.469584 0.262325 0.200855
+
+0.418496 0.337912 0.213457
+0.469584 0.262325 0.200855
+0.442815 0.357548 0.159319
+
+0.469584 0.262325 0.200855
+0.418496 0.337912 0.213457
+0.427777 0.238971 0.241037
+
+0.381238 0.307828 0.25364
+0.427777 0.238971 0.241037
+0.418496 0.337912 0.213457
+
+0.427777 0.238971 0.241037
+0.381238 0.307828 0.25364
+0.376493 0.210322 0.262418
+
+0.335533 0.270924 0.275021
+0.376493 0.210322 0.262418
+0.381238 0.307828 0.25364
+
+0.376493 0.210322 0.262418
+0.335533 0.270924 0.275021
+0.321918 0.179834 0.262418
+
+0.286895 0.231652 0.275021
+0.321918 0.179834 0.262418
+0.335533 0.270924 0.275021
+
+0.321918 0.179834 0.262418
+0.286895 0.231652 0.275021
+0.270634 0.151185 0.241037
+
+0.241191 0.194748 0.25364
+0.270634 0.151185 0.241037
+0.286895 0.231652 0.275021
+
+0.270634 0.151185 0.241037
+0.241191 0.194748 0.25364
+0.228827 0.127831 0.200855
+
+0.203933 0.164664 0.213457
+0.228827 0.127831 0.200855
+0.241191 0.194748 0.25364
+
+0.228827 0.127831 0.200855
+0.203933 0.164664 0.213457
+0.20154 0.112587 0.146717
+
+0.179614 0.145028 0.159319
+0.20154 0.112587 0.146717
+0.203933 0.164664 0.213457
+
+0.20154 0.112587 0.146717
+0.179614 0.145028 0.159319
+0.192063 0.107293 0.0851529
+
+0.171168 0.138208 0.0977555
+0.192063 0.107293 0.0851529
+0.179614 0.145028 0.159319
+
+0.192063 0.107293 0.0851529
+0.171168 0.138208 0.0977555
+0.20154 0.112587 0.0235893
+
+0.179614 0.145028 0.0361919
+0.20154 0.112587 0.0235893
+0.171168 0.138208 0.0977555
+
+0.20154 0.112587 0.0235893
+0.179614 0.145028 0.0361919
+0.228827 0.127831 -0.0305489
+
+0.203933 0.164664 -0.0179462
+0.228827 0.127831 -0.0305489
+0.179614 0.145028 0.0361919
+
+0.228827 0.127831 -0.0305489
+0.203933 0.164664 -0.0179462
+0.270634 0.151185 -0.0707317
+
+0.241191 0.194748 -0.058129
+0.270634 0.151185 -0.0707317
+0.203933 0.164664 -0.0179462
+
+0.270634 0.151185 -0.0707317
+0.241191 0.194748 -0.058129
+0.321918 0.179834 -0.0921125
+
+0.286895 0.231652 -0.0795099
+0.321918 0.179834 -0.0921125
+0.241191 0.194748 -0.058129
+
+0.321918 0.179834 -0.0921125
+0.286895 0.231652 -0.0795099
+0.376493 0.210322 -0.0921125
+
+0.335533 0.270924 -0.0795099
+0.376493 0.210322 -0.0921125
+0.286895 0.231652 -0.0795099
+
+0.376493 0.210322 -0.0921125
+0.335533 0.270924 -0.0795099
+0.427777 0.238971 -0.0707317
+
+0.381238 0.307828 -0.058129
+0.427777 0.238971 -0.0707317
+0.335533 0.270924 -0.0795099
+
+0.427777 0.238971 -0.0707317
+0.381238 0.307828 -0.058129
+0.469584 0.262325 -0.0305489
+
+0.418496 0.337912 -0.0179462
+0.469584 0.262325 -0.0305489
+0.381238 0.307828 -0.058129
+
+0.469584 0.262325 -0.0305489
+0.418496 0.337912 -0.0179462
+0.496871 0.277569 0.0235893
+
+0.442815 0.357548 0.0361919
+0.496871 0.277569 0.0235893
+0.418496 0.337912 -0.0179462
+
+0.496871 0.277569 0.0235893
+0.442815 0.357548 0.0361919
+0.506348 0.282863 0.0851529
+
+0.451261 0.364368 0.0977555
+0.506348 0.282863 0.0851529
+0.442815 0.357548 0.0361919
+
+0.451261 0.364368 0.0977555
+0.383191 0.43539 0.09919
+0.442815 0.357548 0.159319
+
+0.376019 0.427241 0.160754
+0.442815 0.357548 0.159319
+0.383191 0.43539 0.09919
+
+0.442815 0.357548 0.159319
+0.376019 0.427241 0.160754
+0.418496 0.337912 0.213457
+
+0.355369 0.403778 0.214892
+0.418496 0.337912 0.213457
+0.376019 0.427241 0.160754
+
+0.418496 0.337912 0.213457
+0.355369 0.403778 0.214892
+0.381238 0.307828 0.25364
+
+0.323731 0.367829 0.255075
+0.381238 0.307828 0.25364
+0.355369 0.403778 0.214892
+
+0.381238 0.307828 0.25364
+0.323731 0.367829 0.255075
+0.335533 0.270924 0.275021
+
+0.28492 0.323732 0.276455
+0.335533 0.270924 0.275021
+0.323731 0.367829 0.255075
+
+0.335533 0.270924 0.275021
+0.28492 0.323732 0.276455
+0.286895 0.231652 0.275021
+
+0.243619 0.276805 0.276455
+0.286895 0.231652 0.275021
+0.28492 0.323732 0.276455
+
+0.286895 0.231652 0.275021
+0.243619 0.276805 0.276455
+0.241191 0.194748 0.25364
+
+0.204809 0.232708 0.255075
+0.241191 0.194748 0.25364
+0.243619 0.276805 0.276455
+
+0.241191 0.194748 0.25364
+0.204809 0.232708 0.255075
+0.203933 0.164664 0.213457
+
+0.173171 0.19676 0.214892
+0.203933 0.164664 0.213457
+0.204809 0.232708 0.255075
+
+0.203933 0.164664 0.213457
+0.173171 0.19676 0.214892
+0.179614 0.145028 0.159319
+
+0.15252 0.173297 0.160754
+0.179614 0.145028 0.159319
+0.173171 0.19676 0.214892
+
+0.179614 0.145028 0.159319
+0.15252 0.173297 0.160754
+0.171168 0.138208 0.0977555
+
+0.145348 0.165148 0.09919
+0.171168 0.138208 0.0977555
+0.15252 0.173297 0.160754
+
+0.171168 0.138208 0.0977555
+0.145348 0.165148 0.09919
+0.179614 0.145028 0.0361919
+
+0.15252 0.173297 0.0376264
+0.179614 0.145028 0.0361919
+0.145348 0.165148 0.09919
+
+0.179614 0.145028 0.0361919
+0.15252 0.173297 0.0376264
+0.203933 0.164664 -0.0179462
+
+0.173171 0.19676 -0.0165117
+0.203933 0.164664 -0.0179462
+0.15252 0.173297 0.0376264
+
+0.203933 0.164664 -0.0179462
+0.173171 0.19676 -0.0165117
+0.241191 0.194748 -0.058129
+
+0.204809 0.232708 -0.0566945
+0.241191 0.194748 -0.058129
+0.173171 0.19676 -0.0165117
+
+0.241191 0.194748 -0.058129
+0.204809 0.232708 -0.0566945
+0.286895 0.231652 -0.0795099
+
+0.243619 0.276805 -0.0780754
+0.286895 0.231652 -0.0795099
+0.204809 0.232708 -0.0566945
+
+0.286895 0.231652 -0.0795099
+0.243619 0.276805 -0.0780754
+0.335533 0.270924 -0.0795099
+
+0.28492 0.323732 -0.0780754
+0.335533 0.270924 -0.0795099
+0.243619 0.276805 -0.0780754
+
+0.335533 0.270924 -0.0795099
+0.28492 0.323732 -0.0780754
+0.381238 0.307828 -0.058129
+
+0.323731 0.367829 -0.0566945
+0.381238 0.307828 -0.058129
+0.28492 0.323732 -0.0780754
+
+0.381238 0.307828 -0.058129
+0.323731 0.367829 -0.0566945
+0.418496 0.337912 -0.0179462
+
+0.355369 0.403778 -0.0165117
+0.418496 0.337912 -0.0179462
+0.323731 0.367829 -0.0566945
+
+0.418496 0.337912 -0.0179462
+0.355369 0.403778 -0.0165117
+0.442815 0.357548 0.0361919
+
+0.376019 0.427241 0.0376264
+0.442815 0.357548 0.0361919
+0.355369 0.403778 -0.0165117
+
+0.442815 0.357548 0.0361919
+0.376019 0.427241 0.0376264
+0.451261 0.364368 0.0977555
+
+0.383191 0.43539 0.09919
+0.451261 0.364368 0.0977555
+0.376019 0.427241 0.0376264
+
+0.383191 0.43539 0.09919
+0.304098 0.493887 0.0892926
+0.376019 0.427241 0.160754
+
+0.298407 0.484643 0.150856
+0.376019 0.427241 0.160754
+0.304098 0.493887 0.0892926
+
+0.376019 0.427241 0.160754
+0.298407 0.484643 0.150856
+0.355369 0.403778 0.214892
+
+0.282019 0.458027 0.204994
+0.355369 0.403778 0.214892
+0.298407 0.484643 0.150856
+
+0.355369 0.403778 0.214892
+0.282019 0.458027 0.204994
+0.323731 0.367829 0.255075
+
+0.256911 0.417249 0.245177
+0.323731 0.367829 0.255075
+0.282019 0.458027 0.204994
+
+0.323731 0.367829 0.255075
+0.256911 0.417249 0.245177
+0.28492 0.323732 0.276455
+
+0.226111 0.367228 0.266558
+0.28492 0.323732 0.276455
+0.256911 0.417249 0.245177
+
+0.28492 0.323732 0.276455
+0.226111 0.367228 0.266558
+0.243619 0.276805 0.276455
+
+0.193335 0.313996 0.266558
+0.243619 0.276805 0.276455
+0.226111 0.367228 0.266558
+
+0.243619 0.276805 0.276455
+0.193335 0.313996 0.266558
+0.204809 0.232708 0.255075
+
+0.162535 0.263974 0.245177
+0.204809 0.232708 0.255075
+0.193335 0.313996 0.266558
+
+0.204809 0.232708 0.255075
+0.162535 0.263974 0.245177
+0.173171 0.19676 0.214892
+
+0.137427 0.223196 0.204994
+0.173171 0.19676 0.214892
+0.162535 0.263974 0.245177
+
+0.173171 0.19676 0.214892
+0.137427 0.223196 0.204994
+0.15252 0.173297 0.160754
+
+0.121039 0.19658 0.150856
+0.15252 0.173297 0.160754
+0.137427 0.223196 0.204994
+
+0.15252 0.173297 0.160754
+0.121039 0.19658 0.150856
+0.145348 0.165148 0.09919
+
+0.115348 0.187336 0.0892926
+0.145348 0.165148 0.09919
+0.121039 0.19658 0.150856
+
+0.145348 0.165148 0.09919
+0.115348 0.187336 0.0892926
+0.15252 0.173297 0.0376264
+
+0.121039 0.19658 0.027729
+0.15252 0.173297 0.0376264
+0.115348 0.187336 0.0892926
+
+0.15252 0.173297 0.0376264
+0.121039 0.19658 0.027729
+0.173171 0.19676 -0.0165117
+
+0.137427 0.223196 -0.0264092
+0.173171 0.19676 -0.0165117
+0.121039 0.19658 0.027729
+
+0.173171 0.19676 -0.0165117
+0.137427 0.223196 -0.0264092
+0.204809 0.232708 -0.0566945
+
+0.162535 0.263974 -0.066592
+0.204809 0.232708 -0.0566945
+0.137427 0.223196 -0.0264092
+
+0.204809 0.232708 -0.0566945
+0.162535 0.263974 -0.066592
+0.243619 0.276805 -0.0780754
+
+0.193335 0.313996 -0.0879728
+0.243619 0.276805 -0.0780754
+0.162535 0.263974 -0.066592
+
+0.243619 0.276805 -0.0780754
+0.193335 0.313996 -0.0879728
+0.28492 0.323732 -0.0780754
+
+0.226111 0.367228 -0.0879728
+0.28492 0.323732 -0.0780754
+0.193335 0.313996 -0.0879728
+
+0.28492 0.323732 -0.0780754
+0.226111 0.367228 -0.0879728
+0.323731 0.367829 -0.0566945
+
+0.256911 0.417249 -0.066592
+0.323731 0.367829 -0.0566945
+0.226111 0.367228 -0.0879728
+
+0.323731 0.367829 -0.0566945
+0.256911 0.417249 -0.066592
+0.355369 0.403778 -0.0165117
+
+0.282019 0.458027 -0.0264092
+0.355369 0.403778 -0.0165117
+0.256911 0.417249 -0.066592
+
+0.355369 0.403778 -0.0165117
+0.282019 0.458027 -0.0264092
+0.376019 0.427241 0.0376264
+
+0.298407 0.484643 0.027729
+0.376019 0.427241 0.0376264
+0.282019 0.458027 -0.0264092
+
+0.376019 0.427241 0.0376264
+0.298407 0.484643 0.027729
+0.383191 0.43539 0.09919
+
+0.304098 0.493887 0.0892926
+0.383191 0.43539 0.09919
+0.298407 0.484643 0.027729
+
+0.304098 0.493887 0.0892926
+0.216257 0.538176 0.0691939
+0.298407 0.484643 0.150856
+
+0.212209 0.528103 0.130758
+0.298407 0.484643 0.150856
+0.216257 0.538176 0.0691939
+
+0.298407 0.484643 0.150856
+0.212209 0.528103 0.130758
+0.282019 0.458027 0.204994
+
+0.200555 0.4991 0.184896
+0.282019 0.458027 0.204994
+0.212209 0.528103 0.130758
+
+0.282019 0.458027 0.204994
+0.200555 0.4991 0.184896
+0.256911 0.417249 0.245177
+
+0.1827 0.454666 0.225078
+0.256911 0.417249 0.245177
+0.200555 0.4991 0.184896
+
+0.256911 0.417249 0.245177
+0.1827 0.454666 0.225078
+0.226111 0.367228 0.266558
+
+0.160797 0.400158 0.246459
+0.226111 0.367228 0.266558
+0.1827 0.454666 0.225078
+
+0.226111 0.367228 0.266558
+0.160797 0.400158 0.246459
+0.193335 0.313996 0.266558
+
+0.137488 0.342153 0.246459
+0.193335 0.313996 0.266558
+0.160797 0.400158 0.246459
+
+0.193335 0.313996 0.266558
+0.137488 0.342153 0.246459
+0.162535 0.263974 0.245177
+
+0.115586 0.287646 0.225078
+0.162535 0.263974 0.245177
+0.137488 0.342153 0.246459
+
+0.162535 0.263974 0.245177
+0.115586 0.287646 0.225078
+0.137427 0.223196 0.204994
+
+0.0977302 0.243211 0.184896
+0.137427 0.223196 0.204994
+0.115586 0.287646 0.225078
+
+0.137427 0.223196 0.204994
+0.0977302 0.243211 0.184896
+0.121039 0.19658 0.150856
+
+0.0860759 0.214208 0.130758
+0.121039 0.19658 0.150856
+0.0977302 0.243211 0.184896
+
+0.121039 0.19658 0.150856
+0.0860759 0.214208 0.130758
+0.115348 0.187336 0.0892926
+
+0.0820284 0.204136 0.0691939
+0.115348 0.187336 0.0892926
+0.0860759 0.214208 0.130758
+
+0.115348 0.187336 0.0892926
+0.0820284 0.204136 0.0691939
+0.121039 0.19658 0.027729
+
+0.0860759 0.214208 0.00763026
+0.121039 0.19658 0.027729
+0.0820284 0.204136 0.0691939
+
+0.121039 0.19658 0.027729
+0.0860759 0.214208 0.00763026
+0.137427 0.223196 -0.0264092
+
+0.0977302 0.243211 -0.0465079
+0.137427 0.223196 -0.0264092
+0.0860759 0.214208 0.00763026
+
+0.137427 0.223196 -0.0264092
+0.0977302 0.243211 -0.0465079
+0.162535 0.263974 -0.066592
+
+0.115586 0.287646 -0.0866907
+0.162535 0.263974 -0.066592
+0.0977302 0.243211 -0.0465079
+
+0.162535 0.263974 -0.066592
+0.115586 0.287646 -0.0866907
+0.193335 0.313996 -0.0879728
+
+0.137488 0.342153 -0.108072
+0.193335 0.313996 -0.0879728
+0.115586 0.287646 -0.0866907
+
+0.193335 0.313996 -0.0879728
+0.137488 0.342153 -0.108072
+0.226111 0.367228 -0.0879728
+
+0.160797 0.400158 -0.108072
+0.226111 0.367228 -0.0879728
+0.137488 0.342153 -0.108072
+
+0.226111 0.367228 -0.0879728
+0.160797 0.400158 -0.108072
+0.256911 0.417249 -0.066592
+
+0.1827 0.454666 -0.0866907
+0.256911 0.417249 -0.066592
+0.160797 0.400158 -0.108072
+
+0.256911 0.417249 -0.066592
+0.1827 0.454666 -0.0866907
+0.282019 0.458027 -0.0264092
+
+0.200555 0.4991 -0.0465079
+0.282019 0.458027 -0.0264092
+0.1827 0.454666 -0.0866907
+
+0.282019 0.458027 -0.0264092
+0.200555 0.4991 -0.0465079
+0.298407 0.484643 0.027729
+
+0.212209 0.528103 0.00763026
+0.298407 0.484643 0.027729
+0.200555 0.4991 -0.0465079
+
+0.298407 0.484643 0.027729
+0.212209 0.528103 0.00763026
+0.304098 0.493887 0.0892926
+
+0.216257 0.538176 0.0691939
+0.304098 0.493887 0.0892926
+0.212209 0.528103 0.00763026
+
+0.216257 0.538176 0.0691939
+0.122194 0.566982 0.0411901
+0.212209 0.528103 0.130758
+
+0.119907 0.55637 0.102754
+0.212209 0.528103 0.130758
+0.122194 0.566982 0.0411901
+
+0.212209 0.528103 0.130758
+0.119907 0.55637 0.102754
+0.200555 0.4991 0.184896
+
+0.113322 0.525815 0.156892
+0.200555 0.4991 0.184896
+0.119907 0.55637 0.102754
+
+0.200555 0.4991 0.184896
+0.113322 0.525815 0.156892
+0.1827 0.454666 0.225078
+
+0.103233 0.479002 0.197075
+0.1827 0.454666 0.225078
+0.113322 0.525815 0.156892
+
+0.1827 0.454666 0.225078
+0.103233 0.479002 0.197075
+0.160797 0.400158 0.246459
+
+0.0908568 0.421577 0.218456
+0.160797 0.400158 0.246459
+0.103233 0.479002 0.197075
+
+0.160797 0.400158 0.246459
+0.0908568 0.421577 0.218456
+0.137488 0.342153 0.246459
+
+0.0776866 0.360467 0.218456
+0.137488 0.342153 0.246459
+0.0908568 0.421577 0.218456
+
+0.137488 0.342153 0.246459
+0.0776866 0.360467 0.218456
+0.115586 0.287646 0.225078
+
+0.0653106 0.303042 0.197075
+0.115586 0.287646 0.225078
+0.0776866 0.360467 0.218456
+
+0.115586 0.287646 0.225078
+0.0653106 0.303042 0.197075
+0.0977302 0.243211 0.184896
+
+0.0552216 0.256229 0.156892
+0.0977302 0.243211 0.184896
+0.0653106 0.303042 0.197075
+
+0.0977302 0.243211 0.184896
+0.0552216 0.256229 0.156892
+0.0860759 0.214208 0.130758
+
+0.0486364 0.225674 0.102754
+0.0860759 0.214208 0.130758
+0.0552216 0.256229 0.156892
+
+0.0860759 0.214208 0.130758
+0.0486364 0.225674 0.102754
+0.0820284 0.204136 0.0691939
+
+0.0463494 0.215062 0.0411901
+0.0820284 0.204136 0.0691939
+0.0486364 0.225674 0.102754
+
+0.0820284 0.204136 0.0691939
+0.0463494 0.215062 0.0411901
+0.0860759 0.214208 0.00763026
+
+0.0486364 0.225674 -0.0203735
+0.0860759 0.214208 0.00763026
+0.0463494 0.215062 0.0411901
+
+0.0860759 0.214208 0.00763026
+0.0486364 0.225674 -0.0203735
+0.0977302 0.243211 -0.0465079
+
+0.0552216 0.256229 -0.0745116
+0.0977302 0.243211 -0.0465079
+0.0486364 0.225674 -0.0203735
+
+0.0977302 0.243211 -0.0465079
+0.0552216 0.256229 -0.0745116
+0.115586 0.287646 -0.0866907
+
+0.0653106 0.303042 -0.114694
+0.115586 0.287646 -0.0866907
+0.0552216 0.256229 -0.0745116
+
+0.115586 0.287646 -0.0866907
+0.0653106 0.303042 -0.114694
+0.137488 0.342153 -0.108072
+
+0.0776866 0.360467 -0.136075
+0.137488 0.342153 -0.108072
+0.0653106 0.303042 -0.114694
+
+0.137488 0.342153 -0.108072
+0.0776866 0.360467 -0.136075
+0.160797 0.400158 -0.108072
+
+0.0908568 0.421577 -0.136075
+0.160797 0.400158 -0.108072
+0.0776866 0.360467 -0.136075
+
+0.160797 0.400158 -0.108072
+0.0908568 0.421577 -0.136075
+0.1827 0.454666 -0.0866907
+
+0.103233 0.479002 -0.114694
+0.1827 0.454666 -0.0866907
+0.0908568 0.421577 -0.136075
+
+0.1827 0.454666 -0.0866907
+0.103233 0.479002 -0.114694
+0.200555 0.4991 -0.0465079
+
+0.113322 0.525815 -0.0745116
+0.200555 0.4991 -0.0465079
+0.103233 0.479002 -0.114694
+
+0.200555 0.4991 -0.0465079
+0.113322 0.525815 -0.0745116
+0.212209 0.528103 0.00763026
+
+0.119907 0.55637 -0.0203735
+0.212209 0.528103 0.00763026
+0.113322 0.525815 -0.0745116
+
+0.212209 0.528103 0.00763026
+0.119907 0.55637 -0.0203735
+0.216257 0.538176 0.0691939
+
+0.122194 0.566982 0.0411901
+0.216257 0.538176 0.0691939
+0.119907 0.55637 -0.0203735
+
+0.122194 0.566982 0.0411901
+0.0246159 0.579477 0.00848059
+0.119907 0.55637 0.102754
+
+0.0241552 0.568632 0.0700442
+0.119907 0.55637 0.102754
+0.0246159 0.579477 0.00848059
+
+0.119907 0.55637 0.102754
+0.0241552 0.568632 0.0700442
+0.113322 0.525815 0.156892
+
+0.0228286 0.537403 0.124182
+0.113322 0.525815 0.156892
+0.0241552 0.568632 0.0700442
+
+0.113322 0.525815 0.156892
+0.0228286 0.537403 0.124182
+0.103233 0.479002 0.197075
+
+0.0207962 0.489558 0.164365
+0.103233 0.479002 0.197075
+0.0228286 0.537403 0.124182
+
+0.103233 0.479002 0.197075
+0.0207962 0.489558 0.164365
+0.0908568 0.421577 0.218456
+
+0.0183031 0.430868 0.185746
+0.0908568 0.421577 0.218456
+0.0207962 0.489558 0.164365
+
+0.0908568 0.421577 0.218456
+0.0183031 0.430868 0.185746
+0.0776866 0.360467 0.218456
+
+0.0156499 0.368411 0.185746
+0.0776866 0.360467 0.218456
+0.0183031 0.430868 0.185746
+
+0.0776866 0.360467 0.218456
+0.0156499 0.368411 0.185746
+0.0653106 0.303042 0.197075
+
+0.0131568 0.309721 0.164365
+0.0653106 0.303042 0.197075
+0.0156499 0.368411 0.185746
+
+0.0653106 0.303042 0.197075
+0.0131568 0.309721 0.164365
+0.0552216 0.256229 0.156892
+
+0.0111243 0.261876 0.124182
+0.0552216 0.256229 0.156892
+0.0131568 0.309721 0.164365
+
+0.0552216 0.256229 0.156892
+0.0111243 0.261876 0.124182
+0.0486364 0.225674 0.102754
+
+0.00979778 0.230647 0.0700442
+0.0486364 0.225674 0.102754
+0.0111243 0.261876 0.124182
+
+0.0486364 0.225674 0.102754
+0.00979778 0.230647 0.0700442
+0.0463494 0.215062 0.0411901
+
+0.00933706 0.219802 0.00848059
+0.0463494 0.215062 0.0411901
+0.00979778 0.230647 0.0700442
+
+0.0463494 0.215062 0.0411901
+0.00933706 0.219802 0.00848059
+0.0486364 0.225674 -0.0203735
+
+0.00979778 0.230647 -0.053083
+0.0486364 0.225674 -0.0203735
+0.00933706 0.219802 0.00848059
+
+0.0486364 0.225674 -0.0203735
+0.00979778 0.230647 -0.053083
+0.0552216 0.256229 -0.0745116
+
+0.0111243 0.261876 -0.107221
+0.0552216 0.256229 -0.0745116
+0.00979778 0.230647 -0.053083
+
+0.0552216 0.256229 -0.0745116
+0.0111243 0.261876 -0.107221
+0.0653106 0.303042 -0.114694
+
+0.0131568 0.309721 -0.147404
+0.0653106 0.303042 -0.114694
+0.0111243 0.261876 -0.107221
+
+0.0653106 0.303042 -0.114694
+0.0131568 0.309721 -0.147404
+0.0776866 0.360467 -0.136075
+
+0.0156499 0.368411 -0.168785
+0.0776866 0.360467 -0.136075
+0.0131568 0.309721 -0.147404
+
+0.0776866 0.360467 -0.136075
+0.0156499 0.368411 -0.168785
+0.0908568 0.421577 -0.136075
+
+0.0183031 0.430868 -0.168785
+0.0908568 0.421577 -0.136075
+0.0156499 0.368411 -0.168785
+
+0.0908568 0.421577 -0.136075
+0.0183031 0.430868 -0.168785
+0.103233 0.479002 -0.114694
+
+0.0207962 0.489558 -0.147404
+0.103233 0.479002 -0.114694
+0.0183031 0.430868 -0.168785
+
+0.103233 0.479002 -0.114694
+0.0207962 0.489558 -0.147404
+0.113322 0.525815 -0.0745116
+
+0.0228286 0.537403 -0.107221
+0.113322 0.525815 -0.0745116
+0.0207962 0.489558 -0.147404
+
+0.113322 0.525815 -0.0745116
+0.0228286 0.537403 -0.107221
+0.119907 0.55637 -0.0203735
+
+0.0241552 0.568632 -0.053083
+0.119907 0.55637 -0.0203735
+0.0228286 0.537403 -0.107221
+
+0.119907 0.55637 -0.0203735
+0.0241552 0.568632 -0.053083
+0.122194 0.566982 0.0411901
+
+0.0246159 0.579477 0.00848059
+0.122194 0.566982 0.0411901
+0.0241552 0.568632 -0.053083
+
+0.0246159 0.579477 0.00848059
+-0.0736703 0.575302 -0.0251978
+0.0241552 0.568632 0.0700442
+
+-0.0722915 0.564535 0.0363658
+0.0241552 0.568632 0.0700442
+-0.0736703 0.575302 -0.0251978
+
+0.0241552 0.568632 0.0700442
+-0.0722915 0.564535 0.0363658
+0.0228286 0.537403 0.124182
+
+-0.0683214 0.533531 0.090504
+0.0228286 0.537403 0.124182
+-0.0722915 0.564535 0.0363658
+
+0.0228286 0.537403 0.124182
+-0.0683214 0.533531 0.090504
+0.0207962 0.489558 0.164365
+
+-0.0622387 0.486031 0.130687
+0.0207962 0.489558 0.164365
+-0.0683214 0.533531 0.090504
+
+0.0207962 0.489558 0.164365
+-0.0622387 0.486031 0.130687
+0.0183031 0.430868 0.185746
+
+-0.0547773 0.427764 0.152068
+0.0183031 0.430868 0.185746
+-0.0622387 0.486031 0.130687
+
+0.0183031 0.430868 0.185746
+-0.0547773 0.427764 0.152068
+0.0156499 0.368411 0.185746
+
+-0.046837 0.365757 0.152068
+0.0156499 0.368411 0.185746
+-0.0547773 0.427764 0.152068
+
+0.0156499 0.368411 0.185746
+-0.046837 0.365757 0.152068
+0.0131568 0.309721 0.164365
+
+-0.0393755 0.307489 0.130687
+0.0131568 0.309721 0.164365
+-0.046837 0.365757 0.152068
+
+0.0131568 0.309721 0.164365
+-0.0393755 0.307489 0.130687
+0.0111243 0.261876 0.124182
+
+-0.0332929 0.259989 0.090504
+0.0111243 0.261876 0.124182
+-0.0393755 0.307489 0.130687
+
+0.0111243 0.261876 0.124182
+-0.0332929 0.259989 0.090504
+0.00979778 0.230647 0.0700442
+
+-0.0293227 0.228986 0.0363658
+0.00979778 0.230647 0.0700442
+-0.0332929 0.259989 0.090504
+
+0.00979778 0.230647 0.0700442
+-0.0293227 0.228986 0.0363658
+0.00933706 0.219802 0.00848059
+
+-0.0279439 0.218218 -0.0251978
+0.00933706 0.219802 0.00848059
+-0.0293227 0.228986 0.0363658
+
+0.00933706 0.219802 0.00848059
+-0.0279439 0.218218 -0.0251978
+0.00979778 0.230647 -0.053083
+
+-0.0293227 0.228986 -0.0867614
+0.00979778 0.230647 -0.053083
+-0.0279439 0.218218 -0.0251978
+
+0.00979778 0.230647 -0.053083
+-0.0293227 0.228986 -0.0867614
+0.0111243 0.261876 -0.107221
+
+-0.0332929 0.259989 -0.1409
+0.0111243 0.261876 -0.107221
+-0.0293227 0.228986 -0.0867614
+
+0.0111243 0.261876 -0.107221
+-0.0332929 0.259989 -0.1409
+0.0131568 0.309721 -0.147404
+
+-0.0393755 0.307489 -0.181082
+0.0131568 0.309721 -0.147404
+-0.0332929 0.259989 -0.1409
+
+0.0131568 0.309721 -0.147404
+-0.0393755 0.307489 -0.181082
+0.0156499 0.368411 -0.168785
+
+-0.046837 0.365757 -0.202463
+0.0156499 0.368411 -0.168785
+-0.0393755 0.307489 -0.181082
+
+0.0156499 0.368411 -0.168785
+-0.046837 0.365757 -0.202463
+0.0183031 0.430868 -0.168785
+
+-0.0547773 0.427764 -0.202463
+0.0183031 0.430868 -0.168785
+-0.046837 0.365757 -0.202463
+
+0.0183031 0.430868 -0.168785
+-0.0547773 0.427764 -0.202463
+0.0207962 0.489558 -0.147404
+
+-0.0622387 0.486031 -0.181082
+0.0207962 0.489558 -0.147404
+-0.0547773 0.427764 -0.202463
+
+0.0207962 0.489558 -0.147404
+-0.0622387 0.486031 -0.181082
+0.0228286 0.537403 -0.107221
+
+-0.0683214 0.533531 -0.1409
+0.0228286 0.537403 -0.107221
+-0.0622387 0.486031 -0.181082
+
+0.0228286 0.537403 -0.107221
+-0.0683214 0.533531 -0.1409
+0.0241552 0.568632 -0.053083
+
+-0.0722915 0.564535 -0.0867614
+0.0241552 0.568632 -0.053083
+-0.0683214 0.533531 -0.1409
+
+0.0241552 0.568632 -0.053083
+-0.0722915 0.564535 -0.0867614
+0.0246159 0.579477 0.00848059
+
+-0.0736703 0.575302 -0.0251978
+0.0246159 0.579477 0.00848059
+-0.0722915 0.564535 -0.0867614
+
+-0.0736703 0.575302 -0.0251978
+-0.169837 0.554577 -0.0559975
+-0.0722915 0.564535 0.0363658
+
+-0.166659 0.544197 0.00556615
+-0.0722915 0.564535 0.0363658
+-0.169837 0.554577 -0.0559975
+
+-0.0722915 0.564535 0.0363658
+-0.166659 0.544197 0.00556615
+-0.0683214 0.533531 0.090504
+
+-0.157506 0.514311 0.0597043
+-0.0683214 0.533531 0.090504
+-0.166659 0.544197 0.00556615
+
+-0.0683214 0.533531 0.090504
+-0.157506 0.514311 0.0597043
+-0.0622387 0.486031 0.130687
+
+-0.143483 0.468522 0.0998871
+-0.0622387 0.486031 0.130687
+-0.157506 0.514311 0.0597043
+
+-0.0622387 0.486031 0.130687
+-0.143483 0.468522 0.0998871
+-0.0547773 0.427764 0.152068
+
+-0.126282 0.412353 0.121268
+-0.0547773 0.427764 0.152068
+-0.143483 0.468522 0.0998871
+
+-0.0547773 0.427764 0.152068
+-0.126282 0.412353 0.121268
+-0.046837 0.365757 0.152068
+
+-0.107976 0.35258 0.121268
+-0.046837 0.365757 0.152068
+-0.126282 0.412353 0.121268
+
+-0.046837 0.365757 0.152068
+-0.107976 0.35258 0.121268
+-0.0393755 0.307489 0.130687
+
+-0.0907751 0.296412 0.0998871
+-0.0393755 0.307489 0.130687
+-0.107976 0.35258 0.121268
+
+-0.0393755 0.307489 0.130687
+-0.0907751 0.296412 0.0998871
+-0.0332929 0.259989 0.090504
+
+-0.0767524 0.250623 0.0597043
+-0.0332929 0.259989 0.090504
+-0.0907751 0.296412 0.0998871
+
+-0.0332929 0.259989 0.090504
+-0.0767524 0.250623 0.0597043
+-0.0293227 0.228986 0.0363658
+
+-0.0675997 0.220736 0.00556615
+-0.0293227 0.228986 0.0363658
+-0.0767524 0.250623 0.0597043
+
+-0.0293227 0.228986 0.0363658
+-0.0675997 0.220736 0.00556615
+-0.0279439 0.218218 -0.0251978
+
+-0.064421 0.210357 -0.0559975
+-0.0279439 0.218218 -0.0251978
+-0.0675997 0.220736 0.00556615
+
+-0.0279439 0.218218 -0.0251978
+-0.064421 0.210357 -0.0559975
+-0.0293227 0.228986 -0.0867614
+
+-0.0675997 0.220736 -0.117561
+-0.0293227 0.228986 -0.0867614
+-0.064421 0.210357 -0.0559975
+
+-0.0293227 0.228986 -0.0867614
+-0.0675997 0.220736 -0.117561
+-0.0332929 0.259989 -0.1409
+
+-0.0767524 0.250623 -0.171699
+-0.0332929 0.259989 -0.1409
+-0.0675997 0.220736 -0.117561
+
+-0.0332929 0.259989 -0.1409
+-0.0767524 0.250623 -0.171699
+-0.0393755 0.307489 -0.181082
+
+-0.0907751 0.296412 -0.211882
+-0.0393755 0.307489 -0.181082
+-0.0767524 0.250623 -0.171699
+
+-0.0393755 0.307489 -0.181082
+-0.0907751 0.296412 -0.211882
+-0.046837 0.365757 -0.202463
+
+-0.107976 0.35258 -0.233263
+-0.046837 0.365757 -0.202463
+-0.0907751 0.296412 -0.211882
+
+-0.046837 0.365757 -0.202463
+-0.107976 0.35258 -0.233263
+-0.0547773 0.427764 -0.202463
+
+-0.126282 0.412353 -0.233263
+-0.0547773 0.427764 -0.202463
+-0.107976 0.35258 -0.233263
+
+-0.0547773 0.427764 -0.202463
+-0.126282 0.412353 -0.233263
+-0.0622387 0.486031 -0.181082
+
+-0.143483 0.468522 -0.211882
+-0.0622387 0.486031 -0.181082
+-0.126282 0.412353 -0.233263
+
+-0.0622387 0.486031 -0.181082
+-0.143483 0.468522 -0.211882
+-0.0683214 0.533531 -0.1409
+
+-0.157506 0.514311 -0.171699
+-0.0683214 0.533531 -0.1409
+-0.143483 0.468522 -0.211882
+
+-0.0683214 0.533531 -0.1409
+-0.157506 0.514311 -0.171699
+-0.0722915 0.564535 -0.0867614
+
+-0.166659 0.544197 -0.117561
+-0.0722915 0.564535 -0.0867614
+-0.157506 0.514311 -0.171699
+
+-0.0722915 0.564535 -0.0867614
+-0.166659 0.544197 -0.117561
+-0.0736703 0.575302 -0.0251978
+
+-0.169837 0.554577 -0.0559975
+-0.0736703 0.575302 -0.0251978
+-0.166659 0.544197 -0.117561
+
+-0.169837 0.554577 -0.0559975
+-0.261118 0.517897 -0.0803997
+-0.166659 0.544197 0.00556615
+
+-0.256231 0.508204 -0.0188361
+-0.166659 0.544197 0.00556615
+-0.261118 0.517897 -0.0803997
+
+-0.166659 0.544197 0.00556615
+-0.256231 0.508204 -0.0188361
+-0.157506 0.514311 0.0597043
+
+-0.242159 0.480294 0.0353021
+-0.157506 0.514311 0.0597043
+-0.256231 0.508204 -0.0188361
+
+-0.157506 0.514311 0.0597043
+-0.242159 0.480294 0.0353021
+-0.143483 0.468522 0.0998871
+
+-0.2206 0.437534 0.0754849
+-0.143483 0.468522 0.0998871
+-0.242159 0.480294 0.0353021
+
+-0.143483 0.468522 0.0998871
+-0.2206 0.437534 0.0754849
+-0.126282 0.412353 0.121268
+
+-0.194153 0.38508 0.0968657
+-0.126282 0.412353 0.121268
+-0.2206 0.437534 0.0754849
+
+-0.126282 0.412353 0.121268
+-0.194153 0.38508 0.0968657
+-0.107976 0.35258 0.121268
+
+-0.16601 0.32926 0.0968657
+-0.107976 0.35258 0.121268
+-0.194153 0.38508 0.0968657
+
+-0.107976 0.35258 0.121268
+-0.16601 0.32926 0.0968657
+-0.0907751 0.296412 0.0998871
+
+-0.139563 0.276807 0.0754849
+-0.0907751 0.296412 0.0998871
+-0.16601 0.32926 0.0968657
+
+-0.0907751 0.296412 0.0998871
+-0.139563 0.276807 0.0754849
+-0.0767524 0.250623 0.0597043
+
+-0.118004 0.234047 0.0353021
+-0.0767524 0.250623 0.0597043
+-0.139563 0.276807 0.0754849
+
+-0.0767524 0.250623 0.0597043
+-0.118004 0.234047 0.0353021
+-0.0675997 0.220736 0.00556615
+
+-0.103932 0.206137 -0.0188361
+-0.0675997 0.220736 0.00556615
+-0.118004 0.234047 0.0353021
+
+-0.0675997 0.220736 0.00556615
+-0.103932 0.206137 -0.0188361
+-0.064421 0.210357 -0.0559975
+
+-0.0990448 0.196444 -0.0803997
+-0.064421 0.210357 -0.0559975
+-0.103932 0.206137 -0.0188361
+
+-0.064421 0.210357 -0.0559975
+-0.0990448 0.196444 -0.0803997
+-0.0675997 0.220736 -0.117561
+
+-0.103932 0.206137 -0.141963
+-0.0675997 0.220736 -0.117561
+-0.0990448 0.196444 -0.0803997
+
+-0.0675997 0.220736 -0.117561
+-0.103932 0.206137 -0.141963
+-0.0767524 0.250623 -0.171699
+
+-0.118004 0.234047 -0.196101
+-0.0767524 0.250623 -0.171699
+-0.103932 0.206137 -0.141963
+
+-0.0767524 0.250623 -0.171699
+-0.118004 0.234047 -0.196101
+-0.0907751 0.296412 -0.211882
+
+-0.139563 0.276807 -0.236284
+-0.0907751 0.296412 -0.211882
+-0.118004 0.234047 -0.196101
+
+-0.0907751 0.296412 -0.211882
+-0.139563 0.276807 -0.236284
+-0.107976 0.35258 -0.233263
+
+-0.16601 0.32926 -0.257665
+-0.107976 0.35258 -0.233263
+-0.139563 0.276807 -0.236284
+
+-0.107976 0.35258 -0.233263
+-0.16601 0.32926 -0.257665
+-0.126282 0.412353 -0.233263
+
+-0.194153 0.38508 -0.257665
+-0.126282 0.412353 -0.233263
+-0.16601 0.32926 -0.257665
+
+-0.126282 0.412353 -0.233263
+-0.194153 0.38508 -0.257665
+-0.143483 0.468522 -0.211882
+
+-0.2206 0.437534 -0.236284
+-0.143483 0.468522 -0.211882
+-0.194153 0.38508 -0.257665
+
+-0.143483 0.468522 -0.211882
+-0.2206 0.437534 -0.236284
+-0.157506 0.514311 -0.171699
+
+-0.242159 0.480294 -0.196101
+-0.157506 0.514311 -0.171699
+-0.2206 0.437534 -0.236284
+
+-0.157506 0.514311 -0.171699
+-0.242159 0.480294 -0.196101
+-0.166659 0.544197 -0.117561
+
+-0.256231 0.508204 -0.141963
+-0.166659 0.544197 -0.117561
+-0.242159 0.480294 -0.196101
+
+-0.166659 0.544197 -0.117561
+-0.256231 0.508204 -0.141963
+-0.169837 0.554577 -0.0559975
+
+-0.261118 0.517897 -0.0803997
+-0.169837 0.554577 -0.0559975
+-0.256231 0.508204 -0.141963
+
+-0.261118 0.517897 -0.0803997
+-0.344887 0.466318 -0.0956167
+-0.256231 0.508204 -0.0188361
+
+-0.338432 0.457591 -0.034053
+-0.256231 0.508204 -0.0188361
+-0.344887 0.466318 -0.0956167
+
+-0.256231 0.508204 -0.0188361
+-0.338432 0.457591 -0.034053
+-0.242159 0.480294 0.0353021
+
+-0.319846 0.43246 0.0200851
+-0.242159 0.480294 0.0353021
+-0.338432 0.457591 -0.034053
+
+-0.242159 0.480294 0.0353021
+-0.319846 0.43246 0.0200851
+-0.2206 0.437534 0.0754849
+
+-0.29137 0.393959 0.0602679
+-0.2206 0.437534 0.0754849
+-0.319846 0.43246 0.0200851
+
+-0.2206 0.437534 0.0754849
+-0.29137 0.393959 0.0602679
+-0.194153 0.38508 0.0968657
+
+-0.25644 0.346729 0.0816487
+-0.194153 0.38508 0.0968657
+-0.29137 0.393959 0.0602679
+
+-0.194153 0.38508 0.0968657
+-0.25644 0.346729 0.0816487
+-0.16601 0.32926 0.0968657
+
+-0.219267 0.296469 0.0816487
+-0.16601 0.32926 0.0968657
+-0.25644 0.346729 0.0816487
+
+-0.16601 0.32926 0.0968657
+-0.219267 0.296469 0.0816487
+-0.139563 0.276807 0.0754849
+
+-0.184336 0.249239 0.0602679
+-0.139563 0.276807 0.0754849
+-0.219267 0.296469 0.0816487
+
+-0.139563 0.276807 0.0754849
+-0.184336 0.249239 0.0602679
+-0.118004 0.234047 0.0353021
+
+-0.15586 0.210737 0.0200851
+-0.118004 0.234047 0.0353021
+-0.184336 0.249239 0.0602679
+
+-0.118004 0.234047 0.0353021
+-0.15586 0.210737 0.0200851
+-0.103932 0.206137 -0.0188361
+
+-0.137274 0.185607 -0.034053
+-0.103932 0.206137 -0.0188361
+-0.15586 0.210737 0.0200851
+
+-0.103932 0.206137 -0.0188361
+-0.137274 0.185607 -0.034053
+-0.0990448 0.196444 -0.0803997
+
+-0.130819 0.176879 -0.0956167
+-0.0990448 0.196444 -0.0803997
+-0.137274 0.185607 -0.034053
+
+-0.0990448 0.196444 -0.0803997
+-0.130819 0.176879 -0.0956167
+-0.103932 0.206137 -0.141963
+
+-0.137274 0.185607 -0.15718
+-0.103932 0.206137 -0.141963
+-0.130819 0.176879 -0.0956167
+
+-0.103932 0.206137 -0.141963
+-0.137274 0.185607 -0.15718
+-0.118004 0.234047 -0.196101
+
+-0.15586 0.210737 -0.211318
+-0.118004 0.234047 -0.196101
+-0.137274 0.185607 -0.15718
+
+-0.118004 0.234047 -0.196101
+-0.15586 0.210737 -0.211318
+-0.139563 0.276807 -0.236284
+
+-0.184336 0.249239 -0.251501
+-0.139563 0.276807 -0.236284
+-0.15586 0.210737 -0.211318
+
+-0.139563 0.276807 -0.236284
+-0.184336 0.249239 -0.251501
+-0.16601 0.32926 -0.257665
+
+-0.219267 0.296469 -0.272882
+-0.16601 0.32926 -0.257665
+-0.184336 0.249239 -0.251501
+
+-0.16601 0.32926 -0.257665
+-0.219267 0.296469 -0.272882
+-0.194153 0.38508 -0.257665
+
+-0.25644 0.346729 -0.272882
+-0.194153 0.38508 -0.257665
+-0.219267 0.296469 -0.272882
+
+-0.194153 0.38508 -0.257665
+-0.25644 0.346729 -0.272882
+-0.2206 0.437534 -0.236284
+
+-0.29137 0.393959 -0.251501
+-0.2206 0.437534 -0.236284
+-0.25644 0.346729 -0.272882
+
+-0.2206 0.437534 -0.236284
+-0.29137 0.393959 -0.251501
+-0.242159 0.480294 -0.196101
+
+-0.319846 0.43246 -0.211318
+-0.242159 0.480294 -0.196101
+-0.29137 0.393959 -0.251501
+
+-0.242159 0.480294 -0.196101
+-0.319846 0.43246 -0.211318
+-0.256231 0.508204 -0.141963
+
+-0.338432 0.457591 -0.15718
+-0.256231 0.508204 -0.141963
+-0.319846 0.43246 -0.211318
+
+-0.256231 0.508204 -0.141963
+-0.338432 0.457591 -0.15718
+-0.261118 0.517897 -0.0803997
+
+-0.344887 0.466318 -0.0956167
+-0.261118 0.517897 -0.0803997
+-0.338432 0.457591 -0.15718
+
+-0.344887 0.466318 -0.0956167
+-0.418735 0.401325 -0.0999099
+-0.338432 0.457591 -0.034053
+
+-0.410897 0.393813 -0.0383463
+-0.338432 0.457591 -0.034053
+-0.418735 0.401325 -0.0999099
+
+-0.338432 0.457591 -0.034053
+-0.410897 0.393813 -0.0383463
+-0.319846 0.43246 0.0200851
+
+-0.388332 0.372186 0.0157919
+-0.319846 0.43246 0.0200851
+-0.410897 0.393813 -0.0383463
+
+-0.319846 0.43246 0.0200851
+-0.388332 0.372186 0.0157919
+-0.29137 0.393959 0.0602679
+
+-0.353758 0.33905 0.0559747
+-0.29137 0.393959 0.0602679
+-0.388332 0.372186 0.0157919
+
+-0.29137 0.393959 0.0602679
+-0.353758 0.33905 0.0559747
+-0.25644 0.346729 0.0816487
+
+-0.311348 0.298403 0.0773555
+-0.25644 0.346729 0.0816487
+-0.353758 0.33905 0.0559747
+
+-0.25644 0.346729 0.0816487
+-0.311348 0.298403 0.0773555
+-0.219267 0.296469 0.0816487
+
+-0.266216 0.255148 0.0773555
+-0.219267 0.296469 0.0816487
+-0.311348 0.298403 0.0773555
+
+-0.219267 0.296469 0.0816487
+-0.266216 0.255148 0.0773555
+-0.184336 0.249239 0.0602679
+
+-0.223806 0.214501 0.0559747
+-0.184336 0.249239 0.0602679
+-0.266216 0.255148 0.0773555
+
+-0.184336 0.249239 0.0602679
+-0.223806 0.214501 0.0559747
+-0.15586 0.210737 0.0200851
+
+-0.189233 0.181365 0.0157919
+-0.15586 0.210737 0.0200851
+-0.223806 0.214501 0.0559747
+
+-0.15586 0.210737 0.0200851
+-0.189233 0.181365 0.0157919
+-0.137274 0.185607 -0.034053
+
+-0.166667 0.159738 -0.0383463
+-0.137274 0.185607 -0.034053
+-0.189233 0.181365 0.0157919
+
+-0.137274 0.185607 -0.034053
+-0.166667 0.159738 -0.0383463
+-0.130819 0.176879 -0.0956167
+
+-0.15883 0.152227 -0.0999099
+-0.130819 0.176879 -0.0956167
+-0.166667 0.159738 -0.0383463
+
+-0.130819 0.176879 -0.0956167
+-0.15883 0.152227 -0.0999099
+-0.137274 0.185607 -0.15718
+
+-0.166667 0.159738 -0.161474
+-0.137274 0.185607 -0.15718
+-0.15883 0.152227 -0.0999099
+
+-0.137274 0.185607 -0.15718
+-0.166667 0.159738 -0.161474
+-0.15586 0.210737 -0.211318
+
+-0.189233 0.181365 -0.215612
+-0.15586 0.210737 -0.211318
+-0.166667 0.159738 -0.161474
+
+-0.15586 0.210737 -0.211318
+-0.189233 0.181365 -0.215612
+-0.184336 0.249239 -0.251501
+
+-0.223806 0.214501 -0.255794
+-0.184336 0.249239 -0.251501
+-0.189233 0.181365 -0.215612
+
+-0.184336 0.249239 -0.251501
+-0.223806 0.214501 -0.255794
+-0.219267 0.296469 -0.272882
+
+-0.266216 0.255148 -0.277175
+-0.219267 0.296469 -0.272882
+-0.223806 0.214501 -0.255794
+
+-0.219267 0.296469 -0.272882
+-0.266216 0.255148 -0.277175
+-0.25644 0.346729 -0.272882
+
+-0.311348 0.298403 -0.277175
+-0.25644 0.346729 -0.272882
+-0.266216 0.255148 -0.277175
+
+-0.25644 0.346729 -0.272882
+-0.311348 0.298403 -0.277175
+-0.29137 0.393959 -0.251501
+
+-0.353758 0.33905 -0.255794
+-0.29137 0.393959 -0.251501
+-0.311348 0.298403 -0.277175
+
+-0.29137 0.393959 -0.251501
+-0.353758 0.33905 -0.255794
+-0.319846 0.43246 -0.211318
+
+-0.388332 0.372186 -0.215612
+-0.319846 0.43246 -0.211318
+-0.353758 0.33905 -0.255794
+
+-0.319846 0.43246 -0.211318
+-0.388332 0.372186 -0.215612
+-0.338432 0.457591 -0.15718
+
+-0.410897 0.393813 -0.161474
+-0.338432 0.457591 -0.15718
+-0.388332 0.372186 -0.215612
+
+-0.338432 0.457591 -0.15718
+-0.410897 0.393813 -0.161474
+-0.344887 0.466318 -0.0956167
+
+-0.418735 0.401325 -0.0999099
+-0.344887 0.466318 -0.0956167
+-0.410897 0.393813 -0.161474
+
+-0.418735 0.401325 -0.0999099
+-0.480536 0.324785 -0.0927889
+-0.410897 0.393813 -0.0383463
+
+-0.471542 0.318707 -0.0312253
+-0.410897 0.393813 -0.0383463
+-0.480536 0.324785 -0.0927889
+
+-0.410897 0.393813 -0.0383463
+-0.471542 0.318707 -0.0312253
+-0.388332 0.372186 0.0157919
+
+-0.445645 0.301204 0.0229129
+-0.388332 0.372186 0.0157919
+-0.471542 0.318707 -0.0312253
+
+-0.388332 0.372186 0.0157919
+-0.445645 0.301204 0.0229129
+-0.353758 0.33905 0.0559747
+
+-0.40597 0.274388 0.0630957
+-0.353758 0.33905 0.0559747
+-0.445645 0.301204 0.0229129
+
+-0.353758 0.33905 0.0559747
+-0.40597 0.274388 0.0630957
+-0.311348 0.298403 0.0773555
+
+-0.3573 0.241493 0.0844765
+-0.311348 0.298403 0.0773555
+-0.40597 0.274388 0.0630957
+
+-0.311348 0.298403 0.0773555
+-0.3573 0.241493 0.0844765
+-0.266216 0.255148 0.0773555
+
+-0.305507 0.206487 0.0844765
+-0.266216 0.255148 0.0773555
+-0.3573 0.241493 0.0844765
+
+-0.266216 0.255148 0.0773555
+-0.305507 0.206487 0.0844765
+-0.223806 0.214501 0.0559747
+
+-0.256838 0.173592 0.0630957
+-0.223806 0.214501 0.0559747
+-0.305507 0.206487 0.0844765
+
+-0.223806 0.214501 0.0559747
+-0.256838 0.173592 0.0630957
+-0.189233 0.181365 0.0157919
+
+-0.217162 0.146776 0.0229129
+-0.189233 0.181365 0.0157919
+-0.256838 0.173592 0.0630957
+
+-0.189233 0.181365 0.0157919
+-0.217162 0.146776 0.0229129
+-0.166667 0.159738 -0.0383463
+
+-0.191266 0.129273 -0.0312253
+-0.166667 0.159738 -0.0383463
+-0.217162 0.146776 0.0229129
+
+-0.166667 0.159738 -0.0383463
+-0.191266 0.129273 -0.0312253
+-0.15883 0.152227 -0.0999099
+
+-0.182272 0.123194 -0.0927889
+-0.15883 0.152227 -0.0999099
+-0.191266 0.129273 -0.0312253
+
+-0.15883 0.152227 -0.0999099
+-0.182272 0.123194 -0.0927889
+-0.166667 0.159738 -0.161474
+
+-0.191266 0.129273 -0.154353
+-0.166667 0.159738 -0.161474
+-0.182272 0.123194 -0.0927889
+
+-0.166667 0.159738 -0.161474
+-0.191266 0.129273 -0.154353
+-0.189233 0.181365 -0.215612
+
+-0.217162 0.146776 -0.208491
+-0.189233 0.181365 -0.215612
+-0.191266 0.129273 -0.154353
+
+-0.189233 0.181365 -0.215612
+-0.217162 0.146776 -0.208491
+-0.223806 0.214501 -0.255794
+
+-0.256838 0.173592 -0.248673
+-0.223806 0.214501 -0.255794
+-0.217162 0.146776 -0.208491
+
+-0.223806 0.214501 -0.255794
+-0.256838 0.173592 -0.248673
+-0.266216 0.255148 -0.277175
+
+-0.305507 0.206487 -0.270054
+-0.266216 0.255148 -0.277175
+-0.256838 0.173592 -0.248673
+
+-0.266216 0.255148 -0.277175
+-0.305507 0.206487 -0.270054
+-0.311348 0.298403 -0.277175
+
+-0.3573 0.241493 -0.270054
+-0.311348 0.298403 -0.277175
+-0.305507 0.206487 -0.270054
+
+-0.311348 0.298403 -0.277175
+-0.3573 0.241493 -0.270054
+-0.353758 0.33905 -0.255794
+
+-0.40597 0.274388 -0.248673
+-0.353758 0.33905 -0.255794
+-0.3573 0.241493 -0.270054
+
+-0.353758 0.33905 -0.255794
+-0.40597 0.274388 -0.248673
+-0.388332 0.372186 -0.215612
+
+-0.445645 0.301204 -0.208491
+-0.388332 0.372186 -0.215612
+-0.40597 0.274388 -0.248673
+
+-0.388332 0.372186 -0.215612
+-0.445645 0.301204 -0.208491
+-0.410897 0.393813 -0.161474
+
+-0.471542 0.318707 -0.154353
+-0.410897 0.393813 -0.161474
+-0.445645 0.301204 -0.208491
+
+-0.410897 0.393813 -0.161474
+-0.471542 0.318707 -0.154353
+-0.418735 0.401325 -0.0999099
+
+-0.480536 0.324785 -0.0927889
+-0.418735 0.401325 -0.0999099
+-0.471542 0.318707 -0.154353
+
+-0.480536 0.324785 -0.0927889
+-0.528513 0.238903 -0.0750672
+-0.471542 0.318707 -0.0312253
+
+-0.518621 0.234431 -0.0135036
+-0.471542 0.318707 -0.0312253
+-0.528513 0.238903 -0.0750672
+
+-0.471542 0.318707 -0.0312253
+-0.518621 0.234431 -0.0135036
+-0.445645 0.301204 0.0229129
+
+-0.490139 0.221557 0.0406345
+-0.445645 0.301204 0.0229129
+-0.518621 0.234431 -0.0135036
+
+-0.445645 0.301204 0.0229129
+-0.490139 0.221557 0.0406345
+-0.40597 0.274388 0.0630957
+
+-0.446502 0.201832 0.0808173
+-0.40597 0.274388 0.0630957
+-0.490139 0.221557 0.0406345
+
+-0.40597 0.274388 0.0630957
+-0.446502 0.201832 0.0808173
+-0.3573 0.241493 0.0844765
+
+-0.392973 0.177635 0.102198
+-0.3573 0.241493 0.0844765
+-0.446502 0.201832 0.0808173
+
+-0.3573 0.241493 0.0844765
+-0.392973 0.177635 0.102198
+-0.305507 0.206487 0.0844765
+
+-0.336009 0.151886 0.102198
+-0.305507 0.206487 0.0844765
+-0.392973 0.177635 0.102198
+
+-0.305507 0.206487 0.0844765
+-0.336009 0.151886 0.102198
+-0.256838 0.173592 0.0630957
+
+-0.282481 0.127689 0.0808173
+-0.256838 0.173592 0.0630957
+-0.336009 0.151886 0.102198
+
+-0.256838 0.173592 0.0630957
+-0.282481 0.127689 0.0808173
+-0.217162 0.146776 0.0229129
+
+-0.238844 0.107964 0.0406345
+-0.217162 0.146776 0.0229129
+-0.282481 0.127689 0.0808173
+
+-0.217162 0.146776 0.0229129
+-0.238844 0.107964 0.0406345
+-0.191266 0.129273 -0.0312253
+
+-0.210362 0.0950896 -0.0135036
+-0.191266 0.129273 -0.0312253
+-0.238844 0.107964 0.0406345
+
+-0.191266 0.129273 -0.0312253
+-0.210362 0.0950896 -0.0135036
+-0.182272 0.123194 -0.0927889
+
+-0.20047 0.0906183 -0.0750672
+-0.182272 0.123194 -0.0927889
+-0.210362 0.0950896 -0.0135036
+
+-0.182272 0.123194 -0.0927889
+-0.20047 0.0906183 -0.0750672
+-0.191266 0.129273 -0.154353
+
+-0.210362 0.0950896 -0.136631
+-0.191266 0.129273 -0.154353
+-0.20047 0.0906183 -0.0750672
+
+-0.191266 0.129273 -0.154353
+-0.210362 0.0950896 -0.136631
+-0.217162 0.146776 -0.208491
+
+-0.238844 0.107964 -0.190769
+-0.217162 0.146776 -0.208491
+-0.210362 0.0950896 -0.136631
+
+-0.217162 0.146776 -0.208491
+-0.238844 0.107964 -0.190769
+-0.256838 0.173592 -0.248673
+
+-0.282481 0.127689 -0.230952
+-0.256838 0.173592 -0.248673
+-0.238844 0.107964 -0.190769
+
+-0.256838 0.173592 -0.248673
+-0.282481 0.127689 -0.230952
+-0.305507 0.206487 -0.270054
+
+-0.336009 0.151886 -0.252333
+-0.305507 0.206487 -0.270054
+-0.282481 0.127689 -0.230952
+
+-0.305507 0.206487 -0.270054
+-0.336009 0.151886 -0.252333
+-0.3573 0.241493 -0.270054
+
+-0.392973 0.177635 -0.252333
+-0.3573 0.241493 -0.270054
+-0.336009 0.151886 -0.252333
+
+-0.3573 0.241493 -0.270054
+-0.392973 0.177635 -0.252333
+-0.40597 0.274388 -0.248673
+
+-0.446502 0.201832 -0.230952
+-0.40597 0.274388 -0.248673
+-0.392973 0.177635 -0.252333
+
+-0.40597 0.274388 -0.248673
+-0.446502 0.201832 -0.230952
+-0.445645 0.301204 -0.208491
+
+-0.490139 0.221557 -0.190769
+-0.445645 0.301204 -0.208491
+-0.446502 0.201832 -0.230952
+
+-0.445645 0.301204 -0.208491
+-0.490139 0.221557 -0.190769
+-0.471542 0.318707 -0.154353
+
+-0.518621 0.234431 -0.136631
+-0.471542 0.318707 -0.154353
+-0.490139 0.221557 -0.190769
+
+-0.471542 0.318707 -0.154353
+-0.518621 0.234431 -0.136631
+-0.480536 0.324785 -0.0927889
+
+-0.528513 0.238903 -0.0750672
+-0.480536 0.324785 -0.0927889
+-0.518621 0.234431 -0.136631
+
+-0.528513 0.238903 -0.0750672
+-0.561285 0.146147 -0.0487695
+-0.518621 0.234431 -0.0135036
+
+-0.55078 0.143412 0.0127941
+-0.518621 0.234431 -0.0135036
+-0.561285 0.146147 -0.0487695
+
+-0.518621 0.234431 -0.0135036
+-0.55078 0.143412 0.0127941
+-0.490139 0.221557 0.0406345
+
+-0.520532 0.135536 0.0669323
+-0.490139 0.221557 0.0406345
+-0.55078 0.143412 0.0127941
+
+-0.490139 0.221557 0.0406345
+-0.520532 0.135536 0.0669323
+-0.446502 0.201832 0.0808173
+
+-0.474189 0.123469 0.107115
+-0.446502 0.201832 0.0808173
+-0.520532 0.135536 0.0669323
+
+-0.446502 0.201832 0.0808173
+-0.474189 0.123469 0.107115
+-0.392973 0.177635 0.102198
+
+-0.417341 0.108667 0.128496
+-0.392973 0.177635 0.102198
+-0.474189 0.123469 0.107115
+
+-0.392973 0.177635 0.102198
+-0.417341 0.108667 0.128496
+-0.336009 0.151886 0.102198
+
+-0.356845 0.0929152 0.128496
+-0.336009 0.151886 0.102198
+-0.417341 0.108667 0.128496
+
+-0.336009 0.151886 0.102198
+-0.356845 0.0929152 0.128496
+-0.282481 0.127689 0.0808173
+
+-0.299997 0.0781132 0.107115
+-0.282481 0.127689 0.0808173
+-0.356845 0.0929152 0.128496
+
+-0.282481 0.127689 0.0808173
+-0.299997 0.0781132 0.107115
+-0.238844 0.107964 0.0406345
+
+-0.253654 0.0660465 0.0669323
+-0.238844 0.107964 0.0406345
+-0.299997 0.0781132 0.107115
+
+-0.238844 0.107964 0.0406345
+-0.253654 0.0660465 0.0669323
+-0.210362 0.0950896 -0.0135036
+
+-0.223406 0.0581705 0.0127941
+-0.210362 0.0950896 -0.0135036
+-0.253654 0.0660465 0.0669323
+
+-0.210362 0.0950896 -0.0135036
+-0.223406 0.0581705 0.0127941
+-0.20047 0.0906183 -0.0750672
+
+-0.212901 0.0554352 -0.0487695
+-0.20047 0.0906183 -0.0750672
+-0.223406 0.0581705 0.0127941
+
+-0.20047 0.0906183 -0.0750672
+-0.212901 0.0554352 -0.0487695
+-0.210362 0.0950896 -0.136631
+
+-0.223406 0.0581705 -0.110333
+-0.210362 0.0950896 -0.136631
+-0.212901 0.0554352 -0.0487695
+
+-0.210362 0.0950896 -0.136631
+-0.223406 0.0581705 -0.110333
+-0.238844 0.107964 -0.190769
+
+-0.253654 0.0660465 -0.164471
+-0.238844 0.107964 -0.190769
+-0.223406 0.0581705 -0.110333
+
+-0.238844 0.107964 -0.190769
+-0.253654 0.0660465 -0.164471
+-0.282481 0.127689 -0.230952
+
+-0.299997 0.0781132 -0.204654
+-0.282481 0.127689 -0.230952
+-0.253654 0.0660465 -0.164471
+
+-0.282481 0.127689 -0.230952
+-0.299997 0.0781132 -0.204654
+-0.336009 0.151886 -0.252333
+
+-0.356845 0.0929152 -0.226035
+-0.336009 0.151886 -0.252333
+-0.299997 0.0781132 -0.204654
+
+-0.336009 0.151886 -0.252333
+-0.356845 0.0929152 -0.226035
+-0.392973 0.177635 -0.252333
+
+-0.417341 0.108667 -0.226035
+-0.392973 0.177635 -0.252333
+-0.356845 0.0929152 -0.226035
+
+-0.392973 0.177635 -0.252333
+-0.417341 0.108667 -0.226035
+-0.446502 0.201832 -0.230952
+
+-0.474189 0.123469 -0.204654
+-0.446502 0.201832 -0.230952
+-0.417341 0.108667 -0.226035
+
+-0.446502 0.201832 -0.230952
+-0.474189 0.123469 -0.204654
+-0.490139 0.221557 -0.190769
+
+-0.520532 0.135536 -0.164471
+-0.490139 0.221557 -0.190769
+-0.474189 0.123469 -0.204654
+
+-0.490139 0.221557 -0.190769
+-0.520532 0.135536 -0.164471
+-0.518621 0.234431 -0.136631
+
+-0.55078 0.143412 -0.110333
+-0.518621 0.234431 -0.136631
+-0.520532 0.135536 -0.164471
+
+-0.518621 0.234431 -0.136631
+-0.55078 0.143412 -0.110333
+-0.528513 0.238903 -0.0750672
+
+-0.561285 0.146147 -0.0487695
+-0.528513 0.238903 -0.0750672
+-0.55078 0.143412 -0.110333
+
+-0.561285 0.146147 -0.0487695
+-0.577911 0.0491874 -0.0169001
+-0.55078 0.143412 0.0127941
+
+-0.567094 0.0482668 0.0446635
+-0.55078 0.143412 0.0127941
+-0.577911 0.0491874 -0.0169001
+
+-0.55078 0.143412 0.0127941
+-0.567094 0.0482668 0.0446635
+-0.520532 0.135536 0.0669323
+
+-0.53595 0.0456161 0.0988017
+-0.520532 0.135536 0.0669323
+-0.567094 0.0482668 0.0446635
+
+-0.520532 0.135536 0.0669323
+-0.53595 0.0456161 0.0988017
+-0.474189 0.123469 0.107115
+
+-0.488235 0.0415549 0.138984
+-0.474189 0.123469 0.107115
+-0.53595 0.0456161 0.0988017
+
+-0.474189 0.123469 0.107115
+-0.488235 0.0415549 0.138984
+-0.417341 0.108667 0.128496
+
+-0.429703 0.0365731 0.160365
+-0.417341 0.108667 0.128496
+-0.488235 0.0415549 0.138984
+
+-0.417341 0.108667 0.128496
+-0.429703 0.0365731 0.160365
+-0.356845 0.0929152 0.128496
+
+-0.367415 0.0312716 0.160365
+-0.356845 0.0929152 0.128496
+-0.429703 0.0365731 0.160365
+
+-0.356845 0.0929152 0.128496
+-0.367415 0.0312716 0.160365
+-0.299997 0.0781132 0.107115
+
+-0.308883 0.0262898 0.138984
+-0.299997 0.0781132 0.107115
+-0.367415 0.0312716 0.160365
+
+-0.299997 0.0781132 0.107115
+-0.308883 0.0262898 0.138984
+-0.253654 0.0660465 0.0669323
+
+-0.261168 0.0222287 0.0988017
+-0.253654 0.0660465 0.0669323
+-0.308883 0.0262898 0.138984
+
+-0.253654 0.0660465 0.0669323
+-0.261168 0.0222287 0.0988017
+-0.223406 0.0581705 0.0127941
+
+-0.230024 0.0195779 0.0446635
+-0.223406 0.0581705 0.0127941
+-0.261168 0.0222287 0.0988017
+
+-0.223406 0.0581705 0.0127941
+-0.230024 0.0195779 0.0446635
+-0.212901 0.0554352 -0.0487695
+
+-0.219207 0.0186573 -0.0169001
+-0.212901 0.0554352 -0.0487695
+-0.230024 0.0195779 0.0446635
+
+-0.212901 0.0554352 -0.0487695
+-0.219207 0.0186573 -0.0169001
+-0.223406 0.0581705 -0.110333
+
+-0.230024 0.0195779 -0.0784637
+-0.223406 0.0581705 -0.110333
+-0.219207 0.0186573 -0.0169001
+
+-0.223406 0.0581705 -0.110333
+-0.230024 0.0195779 -0.0784637
+-0.253654 0.0660465 -0.164471
+
+-0.261168 0.0222287 -0.132602
+-0.253654 0.0660465 -0.164471
+-0.230024 0.0195779 -0.0784637
+
+-0.253654 0.0660465 -0.164471
+-0.261168 0.0222287 -0.132602
+-0.299997 0.0781132 -0.204654
+
+-0.308883 0.0262898 -0.172785
+-0.299997 0.0781132 -0.204654
+-0.261168 0.0222287 -0.132602
+
+-0.299997 0.0781132 -0.204654
+-0.308883 0.0262898 -0.172785
+-0.356845 0.0929152 -0.226035
+
+-0.367415 0.0312716 -0.194165
+-0.356845 0.0929152 -0.226035
+-0.308883 0.0262898 -0.172785
+
+-0.356845 0.0929152 -0.226035
+-0.367415 0.0312716 -0.194165
+-0.417341 0.108667 -0.226035
+
+-0.429703 0.0365731 -0.194165
+-0.417341 0.108667 -0.226035
+-0.367415 0.0312716 -0.194165
+
+-0.417341 0.108667 -0.226035
+-0.429703 0.0365731 -0.194165
+-0.474189 0.123469 -0.204654
+
+-0.488235 0.0415549 -0.172785
+-0.474189 0.123469 -0.204654
+-0.429703 0.0365731 -0.194165
+
+-0.474189 0.123469 -0.204654
+-0.488235 0.0415549 -0.172785
+-0.520532 0.135536 -0.164471
+
+-0.53595 0.0456161 -0.132602
+-0.520532 0.135536 -0.164471
+-0.488235 0.0415549 -0.172785
+
+-0.520532 0.135536 -0.164471
+-0.53595 0.0456161 -0.132602
+-0.55078 0.143412 -0.110333
+
+-0.567094 0.0482668 -0.0784637
+-0.55078 0.143412 -0.110333
+-0.53595 0.0456161 -0.132602
+
+-0.55078 0.143412 -0.110333
+-0.567094 0.0482668 -0.0784637
+-0.561285 0.146147 -0.0487695
+
+-0.577911 0.0491874 -0.0169001
+-0.561285 0.146147 -0.0487695
+-0.567094 0.0482668 -0.0784637
+
+-0.577911 0.0491874 -0.0169001
+-0.577911 -0.0491874 0.0169001
+-0.567094 0.0482668 0.0446635
+
+-0.567094 -0.0482668 0.0784637
+-0.567094 0.0482668 0.0446635
+-0.577911 -0.0491874 0.0169001
+
+-0.567094 0.0482668 0.0446635
+-0.567094 -0.0482668 0.0784637
+-0.53595 0.0456161 0.0988017
+
+-0.53595 -0.0456161 0.132602
+-0.53595 0.0456161 0.0988017
+-0.567094 -0.0482668 0.0784637
+
+-0.53595 0.0456161 0.0988017
+-0.53595 -0.0456161 0.132602
+-0.488235 0.0415549 0.138984
+
+-0.488235 -0.0415549 0.172785
+-0.488235 0.0415549 0.138984
+-0.53595 -0.0456161 0.132602
+
+-0.488235 0.0415549 0.138984
+-0.488235 -0.0415549 0.172785
+-0.429703 0.0365731 0.160365
+
+-0.429703 -0.0365731 0.194165
+-0.429703 0.0365731 0.160365
+-0.488235 -0.0415549 0.172785
+
+-0.429703 0.0365731 0.160365
+-0.429703 -0.0365731 0.194165
+-0.367415 0.0312716 0.160365
+
+-0.367415 -0.0312716 0.194165
+-0.367415 0.0312716 0.160365
+-0.429703 -0.0365731 0.194165
+
+-0.367415 0.0312716 0.160365
+-0.367415 -0.0312716 0.194165
+-0.308883 0.0262898 0.138984
+
+-0.308883 -0.0262898 0.172785
+-0.308883 0.0262898 0.138984
+-0.367415 -0.0312716 0.194165
+
+-0.308883 0.0262898 0.138984
+-0.308883 -0.0262898 0.172785
+-0.261168 0.0222287 0.0988017
+
+-0.261168 -0.0222287 0.132602
+-0.261168 0.0222287 0.0988017
+-0.308883 -0.0262898 0.172785
+
+-0.261168 0.0222287 0.0988017
+-0.261168 -0.0222287 0.132602
+-0.230024 0.0195779 0.0446635
+
+-0.230024 -0.0195779 0.0784637
+-0.230024 0.0195779 0.0446635
+-0.261168 -0.0222287 0.132602
+
+-0.230024 0.0195779 0.0446635
+-0.230024 -0.0195779 0.0784637
+-0.219207 0.0186573 -0.0169001
+
+-0.219207 -0.0186573 0.0169001
+-0.219207 0.0186573 -0.0169001
+-0.230024 -0.0195779 0.0784637
+
+-0.219207 0.0186573 -0.0169001
+-0.219207 -0.0186573 0.0169001
+-0.230024 0.0195779 -0.0784637
+
+-0.230024 -0.0195779 -0.0446635
+-0.230024 0.0195779 -0.0784637
+-0.219207 -0.0186573 0.0169001
+
+-0.230024 0.0195779 -0.0784637
+-0.230024 -0.0195779 -0.0446635
+-0.261168 0.0222287 -0.132602
+
+-0.261168 -0.0222287 -0.0988017
+-0.261168 0.0222287 -0.132602
+-0.230024 -0.0195779 -0.0446635
+
+-0.261168 0.0222287 -0.132602
+-0.261168 -0.0222287 -0.0988017
+-0.308883 0.0262898 -0.172785
+
+-0.308883 -0.0262898 -0.138984
+-0.308883 0.0262898 -0.172785
+-0.261168 -0.0222287 -0.0988017
+
+-0.308883 0.0262898 -0.172785
+-0.308883 -0.0262898 -0.138984
+-0.367415 0.0312716 -0.194165
+
+-0.367415 -0.0312716 -0.160365
+-0.367415 0.0312716 -0.194165
+-0.308883 -0.0262898 -0.138984
+
+-0.367415 0.0312716 -0.194165
+-0.367415 -0.0312716 -0.160365
+-0.429703 0.0365731 -0.194165
+
+-0.429703 -0.0365731 -0.160365
+-0.429703 0.0365731 -0.194165
+-0.367415 -0.0312716 -0.160365
+
+-0.429703 0.0365731 -0.194165
+-0.429703 -0.0365731 -0.160365
+-0.488235 0.0415549 -0.172785
+
+-0.488235 -0.0415549 -0.138984
+-0.488235 0.0415549 -0.172785
+-0.429703 -0.0365731 -0.160365
+
+-0.488235 0.0415549 -0.172785
+-0.488235 -0.0415549 -0.138984
+-0.53595 0.0456161 -0.132602
+
+-0.53595 -0.0456161 -0.0988017
+-0.53595 0.0456161 -0.132602
+-0.488235 -0.0415549 -0.138984
+
+-0.53595 0.0456161 -0.132602
+-0.53595 -0.0456161 -0.0988017
+-0.567094 0.0482668 -0.0784637
+
+-0.567094 -0.0482668 -0.0446635
+-0.567094 0.0482668 -0.0784637
+-0.53595 -0.0456161 -0.0988017
+
+-0.567094 0.0482668 -0.0784637
+-0.567094 -0.0482668 -0.0446635
+-0.577911 0.0491874 -0.0169001
+
+-0.577911 -0.0491874 0.0169001
+-0.577911 0.0491874 -0.0169001
+-0.567094 -0.0482668 -0.0446635
+
+-0.577911 -0.0491874 0.0169001
+-0.561285 -0.146147 0.0487695
+-0.567094 -0.0482668 0.0784637
+
+-0.55078 -0.143412 0.110333
+-0.567094 -0.0482668 0.0784637
+-0.561285 -0.146147 0.0487695
+
+-0.567094 -0.0482668 0.0784637
+-0.55078 -0.143412 0.110333
+-0.53595 -0.0456161 0.132602
+
+-0.520532 -0.135536 0.164471
+-0.53595 -0.0456161 0.132602
+-0.55078 -0.143412 0.110333
+
+-0.53595 -0.0456161 0.132602
+-0.520532 -0.135536 0.164471
+-0.488235 -0.0415549 0.172785
+
+-0.474189 -0.123469 0.204654
+-0.488235 -0.0415549 0.172785
+-0.520532 -0.135536 0.164471
+
+-0.488235 -0.0415549 0.172785
+-0.474189 -0.123469 0.204654
+-0.429703 -0.0365731 0.194165
+
+-0.417341 -0.108667 0.226035
+-0.429703 -0.0365731 0.194165
+-0.474189 -0.123469 0.204654
+
+-0.429703 -0.0365731 0.194165
+-0.417341 -0.108667 0.226035
+-0.367415 -0.0312716 0.194165
+
+-0.356845 -0.0929152 0.226035
+-0.367415 -0.0312716 0.194165
+-0.417341 -0.108667 0.226035
+
+-0.367415 -0.0312716 0.194165
+-0.356845 -0.0929152 0.226035
+-0.308883 -0.0262898 0.172785
+
+-0.299997 -0.0781132 0.204654
+-0.308883 -0.0262898 0.172785
+-0.356845 -0.0929152 0.226035
+
+-0.308883 -0.0262898 0.172785
+-0.299997 -0.0781132 0.204654
+-0.261168 -0.0222287 0.132602
+
+-0.253654 -0.0660465 0.164471
+-0.261168 -0.0222287 0.132602
+-0.299997 -0.0781132 0.204654
+
+-0.261168 -0.0222287 0.132602
+-0.253654 -0.0660465 0.164471
+-0.230024 -0.0195779 0.0784637
+
+-0.223406 -0.0581705 0.110333
+-0.230024 -0.0195779 0.0784637
+-0.253654 -0.0660465 0.164471
+
+-0.230024 -0.0195779 0.0784637
+-0.223406 -0.0581705 0.110333
+-0.219207 -0.0186573 0.0169001
+
+-0.212901 -0.0554352 0.0487695
+-0.219207 -0.0186573 0.0169001
+-0.223406 -0.0581705 0.110333
+
+-0.219207 -0.0186573 0.0169001
+-0.212901 -0.0554352 0.0487695
+-0.230024 -0.0195779 -0.0446635
+
+-0.223406 -0.0581705 -0.0127941
+-0.230024 -0.0195779 -0.0446635
+-0.212901 -0.0554352 0.0487695
+
+-0.230024 -0.0195779 -0.0446635
+-0.223406 -0.0581705 -0.0127941
+-0.261168 -0.0222287 -0.0988017
+
+-0.253654 -0.0660465 -0.0669323
+-0.261168 -0.0222287 -0.0988017
+-0.223406 -0.0581705 -0.0127941
+
+-0.261168 -0.0222287 -0.0988017
+-0.253654 -0.0660465 -0.0669323
+-0.308883 -0.0262898 -0.138984
+
+-0.299997 -0.0781132 -0.107115
+-0.308883 -0.0262898 -0.138984
+-0.253654 -0.0660465 -0.0669323
+
+-0.308883 -0.0262898 -0.138984
+-0.299997 -0.0781132 -0.107115
+-0.367415 -0.0312716 -0.160365
+
+-0.356845 -0.0929152 -0.128496
+-0.367415 -0.0312716 -0.160365
+-0.299997 -0.0781132 -0.107115
+
+-0.367415 -0.0312716 -0.160365
+-0.356845 -0.0929152 -0.128496
+-0.429703 -0.0365731 -0.160365
+
+-0.417341 -0.108667 -0.128496
+-0.429703 -0.0365731 -0.160365
+-0.356845 -0.0929152 -0.128496
+
+-0.429703 -0.0365731 -0.160365
+-0.417341 -0.108667 -0.128496
+-0.488235 -0.0415549 -0.138984
+
+-0.474189 -0.123469 -0.107115
+-0.488235 -0.0415549 -0.138984
+-0.417341 -0.108667 -0.128496
+
+-0.488235 -0.0415549 -0.138984
+-0.474189 -0.123469 -0.107115
+-0.53595 -0.0456161 -0.0988017
+
+-0.520532 -0.135536 -0.0669323
+-0.53595 -0.0456161 -0.0988017
+-0.474189 -0.123469 -0.107115
+
+-0.53595 -0.0456161 -0.0988017
+-0.520532 -0.135536 -0.0669323
+-0.567094 -0.0482668 -0.0446635
+
+-0.55078 -0.143412 -0.0127941
+-0.567094 -0.0482668 -0.0446635
+-0.520532 -0.135536 -0.0669323
+
+-0.567094 -0.0482668 -0.0446635
+-0.55078 -0.143412 -0.0127941
+-0.577911 -0.0491874 0.0169001
+
+-0.561285 -0.146147 0.0487695
+-0.577911 -0.0491874 0.0169001
+-0.55078 -0.143412 -0.0127941
+
+-0.561285 -0.146147 0.0487695
+-0.528513 -0.238903 0.0750672
+-0.55078 -0.143412 0.110333
+
+-0.518621 -0.234431 0.136631
+-0.55078 -0.143412 0.110333
+-0.528513 -0.238903 0.0750672
+
+-0.55078 -0.143412 0.110333
+-0.518621 -0.234431 0.136631
+-0.520532 -0.135536 0.164471
+
+-0.490139 -0.221557 0.190769
+-0.520532 -0.135536 0.164471
+-0.518621 -0.234431 0.136631
+
+-0.520532 -0.135536 0.164471
+-0.490139 -0.221557 0.190769
+-0.474189 -0.123469 0.204654
+
+-0.446502 -0.201832 0.230952
+-0.474189 -0.123469 0.204654
+-0.490139 -0.221557 0.190769
+
+-0.474189 -0.123469 0.204654
+-0.446502 -0.201832 0.230952
+-0.417341 -0.108667 0.226035
+
+-0.392973 -0.177635 0.252333
+-0.417341 -0.108667 0.226035
+-0.446502 -0.201832 0.230952
+
+-0.417341 -0.108667 0.226035
+-0.392973 -0.177635 0.252333
+-0.356845 -0.0929152 0.226035
+
+-0.336009 -0.151886 0.252333
+-0.356845 -0.0929152 0.226035
+-0.392973 -0.177635 0.252333
+
+-0.356845 -0.0929152 0.226035
+-0.336009 -0.151886 0.252333
+-0.299997 -0.0781132 0.204654
+
+-0.282481 -0.127689 0.230952
+-0.299997 -0.0781132 0.204654
+-0.336009 -0.151886 0.252333
+
+-0.299997 -0.0781132 0.204654
+-0.282481 -0.127689 0.230952
+-0.253654 -0.0660465 0.164471
+
+-0.238844 -0.107964 0.190769
+-0.253654 -0.0660465 0.164471
+-0.282481 -0.127689 0.230952
+
+-0.253654 -0.0660465 0.164471
+-0.238844 -0.107964 0.190769
+-0.223406 -0.0581705 0.110333
+
+-0.210362 -0.0950896 0.136631
+-0.223406 -0.0581705 0.110333
+-0.238844 -0.107964 0.190769
+
+-0.223406 -0.0581705 0.110333
+-0.210362 -0.0950896 0.136631
+-0.212901 -0.0554352 0.0487695
+
+-0.20047 -0.0906183 0.0750672
+-0.212901 -0.0554352 0.0487695
+-0.210362 -0.0950896 0.136631
+
+-0.212901 -0.0554352 0.0487695
+-0.20047 -0.0906183 0.0750672
+-0.223406 -0.0581705 -0.0127941
+
+-0.210362 -0.0950896 0.0135036
+-0.223406 -0.0581705 -0.0127941
+-0.20047 -0.0906183 0.0750672
+
+-0.223406 -0.0581705 -0.0127941
+-0.210362 -0.0950896 0.0135036
+-0.253654 -0.0660465 -0.0669323
+
+-0.238844 -0.107964 -0.0406345
+-0.253654 -0.0660465 -0.0669323
+-0.210362 -0.0950896 0.0135036
+
+-0.253654 -0.0660465 -0.0669323
+-0.238844 -0.107964 -0.0406345
+-0.299997 -0.0781132 -0.107115
+
+-0.282481 -0.127689 -0.0808173
+-0.299997 -0.0781132 -0.107115
+-0.238844 -0.107964 -0.0406345
+
+-0.299997 -0.0781132 -0.107115
+-0.282481 -0.127689 -0.0808173
+-0.356845 -0.0929152 -0.128496
+
+-0.336009 -0.151886 -0.102198
+-0.356845 -0.0929152 -0.128496
+-0.282481 -0.127689 -0.0808173
+
+-0.356845 -0.0929152 -0.128496
+-0.336009 -0.151886 -0.102198
+-0.417341 -0.108667 -0.128496
+
+-0.392973 -0.177635 -0.102198
+-0.417341 -0.108667 -0.128496
+-0.336009 -0.151886 -0.102198
+
+-0.417341 -0.108667 -0.128496
+-0.392973 -0.177635 -0.102198
+-0.474189 -0.123469 -0.107115
+
+-0.446502 -0.201832 -0.0808173
+-0.474189 -0.123469 -0.107115
+-0.392973 -0.177635 -0.102198
+
+-0.474189 -0.123469 -0.107115
+-0.446502 -0.201832 -0.0808173
+-0.520532 -0.135536 -0.0669323
+
+-0.490139 -0.221557 -0.0406345
+-0.520532 -0.135536 -0.0669323
+-0.446502 -0.201832 -0.0808173
+
+-0.520532 -0.135536 -0.0669323
+-0.490139 -0.221557 -0.0406345
+-0.55078 -0.143412 -0.0127941
+
+-0.518621 -0.234431 0.0135036
+-0.55078 -0.143412 -0.0127941
+-0.490139 -0.221557 -0.0406345
+
+-0.55078 -0.143412 -0.0127941
+-0.518621 -0.234431 0.0135036
+-0.561285 -0.146147 0.0487695
+
+-0.528513 -0.238903 0.0750672
+-0.561285 -0.146147 0.0487695
+-0.518621 -0.234431 0.0135036
+
+-0.528513 -0.238903 0.0750672
+-0.480536 -0.324785 0.0927889
+-0.518621 -0.234431 0.136631
+
+-0.471542 -0.318707 0.154353
+-0.518621 -0.234431 0.136631
+-0.480536 -0.324785 0.0927889
+
+-0.518621 -0.234431 0.136631
+-0.471542 -0.318707 0.154353
+-0.490139 -0.221557 0.190769
+
+-0.445645 -0.301204 0.208491
+-0.490139 -0.221557 0.190769
+-0.471542 -0.318707 0.154353
+
+-0.490139 -0.221557 0.190769
+-0.445645 -0.301204 0.208491
+-0.446502 -0.201832 0.230952
+
+-0.40597 -0.274388 0.248673
+-0.446502 -0.201832 0.230952
+-0.445645 -0.301204 0.208491
+
+-0.446502 -0.201832 0.230952
+-0.40597 -0.274388 0.248673
+-0.392973 -0.177635 0.252333
+
+-0.3573 -0.241493 0.270054
+-0.392973 -0.177635 0.252333
+-0.40597 -0.274388 0.248673
+
+-0.392973 -0.177635 0.252333
+-0.3573 -0.241493 0.270054
+-0.336009 -0.151886 0.252333
+
+-0.305507 -0.206487 0.270054
+-0.336009 -0.151886 0.252333
+-0.3573 -0.241493 0.270054
+
+-0.336009 -0.151886 0.252333
+-0.305507 -0.206487 0.270054
+-0.282481 -0.127689 0.230952
+
+-0.256838 -0.173592 0.248673
+-0.282481 -0.127689 0.230952
+-0.305507 -0.206487 0.270054
+
+-0.282481 -0.127689 0.230952
+-0.256838 -0.173592 0.248673
+-0.238844 -0.107964 0.190769
+
+-0.217162 -0.146776 0.208491
+-0.238844 -0.107964 0.190769
+-0.256838 -0.173592 0.248673
+
+-0.238844 -0.107964 0.190769
+-0.217162 -0.146776 0.208491
+-0.210362 -0.0950896 0.136631
+
+-0.191266 -0.129273 0.154353
+-0.210362 -0.0950896 0.136631
+-0.217162 -0.146776 0.208491
+
+-0.210362 -0.0950896 0.136631
+-0.191266 -0.129273 0.154353
+-0.20047 -0.0906183 0.0750672
+
+-0.182272 -0.123194 0.0927889
+-0.20047 -0.0906183 0.0750672
+-0.191266 -0.129273 0.154353
+
+-0.20047 -0.0906183 0.0750672
+-0.182272 -0.123194 0.0927889
+-0.210362 -0.0950896 0.0135036
+
+-0.191266 -0.129273 0.0312253
+-0.210362 -0.0950896 0.0135036
+-0.182272 -0.123194 0.0927889
+
+-0.210362 -0.0950896 0.0135036
+-0.191266 -0.129273 0.0312253
+-0.238844 -0.107964 -0.0406345
+
+-0.217162 -0.146776 -0.0229129
+-0.238844 -0.107964 -0.0406345
+-0.191266 -0.129273 0.0312253
+
+-0.238844 -0.107964 -0.0406345
+-0.217162 -0.146776 -0.0229129
+-0.282481 -0.127689 -0.0808173
+
+-0.256838 -0.173592 -0.0630957
+-0.282481 -0.127689 -0.0808173
+-0.217162 -0.146776 -0.0229129
+
+-0.282481 -0.127689 -0.0808173
+-0.256838 -0.173592 -0.0630957
+-0.336009 -0.151886 -0.102198
+
+-0.305507 -0.206487 -0.0844765
+-0.336009 -0.151886 -0.102198
+-0.256838 -0.173592 -0.0630957
+
+-0.336009 -0.151886 -0.102198
+-0.305507 -0.206487 -0.0844765
+-0.392973 -0.177635 -0.102198
+
+-0.3573 -0.241493 -0.0844765
+-0.392973 -0.177635 -0.102198
+-0.305507 -0.206487 -0.0844765
+
+-0.392973 -0.177635 -0.102198
+-0.3573 -0.241493 -0.0844765
+-0.446502 -0.201832 -0.0808173
+
+-0.40597 -0.274388 -0.0630957
+-0.446502 -0.201832 -0.0808173
+-0.3573 -0.241493 -0.0844765
+
+-0.446502 -0.201832 -0.0808173
+-0.40597 -0.274388 -0.0630957
+-0.490139 -0.221557 -0.0406345
+
+-0.445645 -0.301204 -0.0229129
+-0.490139 -0.221557 -0.0406345
+-0.40597 -0.274388 -0.0630957
+
+-0.490139 -0.221557 -0.0406345
+-0.445645 -0.301204 -0.0229129
+-0.518621 -0.234431 0.0135036
+
+-0.471542 -0.318707 0.0312253
+-0.518621 -0.234431 0.0135036
+-0.445645 -0.301204 -0.0229129
+
+-0.518621 -0.234431 0.0135036
+-0.471542 -0.318707 0.0312253
+-0.528513 -0.238903 0.0750672
+
+-0.480536 -0.324785 0.0927889
+-0.528513 -0.238903 0.0750672
+-0.471542 -0.318707 0.0312253
+
+-0.480536 -0.324785 0.0927889
+-0.418735 -0.401325 0.0999099
+-0.471542 -0.318707 0.154353
+
+-0.410897 -0.393813 0.161474
+-0.471542 -0.318707 0.154353
+-0.418735 -0.401325 0.0999099
+
+-0.471542 -0.318707 0.154353
+-0.410897 -0.393813 0.161474
+-0.445645 -0.301204 0.208491
+
+-0.388332 -0.372186 0.215612
+-0.445645 -0.301204 0.208491
+-0.410897 -0.393813 0.161474
+
+-0.445645 -0.301204 0.208491
+-0.388332 -0.372186 0.215612
+-0.40597 -0.274388 0.248673
+
+-0.353758 -0.33905 0.255794
+-0.40597 -0.274388 0.248673
+-0.388332 -0.372186 0.215612
+
+-0.40597 -0.274388 0.248673
+-0.353758 -0.33905 0.255794
+-0.3573 -0.241493 0.270054
+
+-0.311348 -0.298403 0.277175
+-0.3573 -0.241493 0.270054
+-0.353758 -0.33905 0.255794
+
+-0.3573 -0.241493 0.270054
+-0.311348 -0.298403 0.277175
+-0.305507 -0.206487 0.270054
+
+-0.266216 -0.255148 0.277175
+-0.305507 -0.206487 0.270054
+-0.311348 -0.298403 0.277175
+
+-0.305507 -0.206487 0.270054
+-0.266216 -0.255148 0.277175
+-0.256838 -0.173592 0.248673
+
+-0.223806 -0.214501 0.255794
+-0.256838 -0.173592 0.248673
+-0.266216 -0.255148 0.277175
+
+-0.256838 -0.173592 0.248673
+-0.223806 -0.214501 0.255794
+-0.217162 -0.146776 0.208491
+
+-0.189233 -0.181365 0.215612
+-0.217162 -0.146776 0.208491
+-0.223806 -0.214501 0.255794
+
+-0.217162 -0.146776 0.208491
+-0.189233 -0.181365 0.215612
+-0.191266 -0.129273 0.154353
+
+-0.166667 -0.159738 0.161474
+-0.191266 -0.129273 0.154353
+-0.189233 -0.181365 0.215612
+
+-0.191266 -0.129273 0.154353
+-0.166667 -0.159738 0.161474
+-0.182272 -0.123194 0.0927889
+
+-0.15883 -0.152227 0.0999099
+-0.182272 -0.123194 0.0927889
+-0.166667 -0.159738 0.161474
+
+-0.182272 -0.123194 0.0927889
+-0.15883 -0.152227 0.0999099
+-0.191266 -0.129273 0.0312253
+
+-0.166667 -0.159738 0.0383463
+-0.191266 -0.129273 0.0312253
+-0.15883 -0.152227 0.0999099
+
+-0.191266 -0.129273 0.0312253
+-0.166667 -0.159738 0.0383463
+-0.217162 -0.146776 -0.0229129
+
+-0.189233 -0.181365 -0.0157919
+-0.217162 -0.146776 -0.0229129
+-0.166667 -0.159738 0.0383463
+
+-0.217162 -0.146776 -0.0229129
+-0.189233 -0.181365 -0.0157919
+-0.256838 -0.173592 -0.0630957
+
+-0.223806 -0.214501 -0.0559747
+-0.256838 -0.173592 -0.0630957
+-0.189233 -0.181365 -0.0157919
+
+-0.256838 -0.173592 -0.0630957
+-0.223806 -0.214501 -0.0559747
+-0.305507 -0.206487 -0.0844765
+
+-0.266216 -0.255148 -0.0773555
+-0.305507 -0.206487 -0.0844765
+-0.223806 -0.214501 -0.0559747
+
+-0.305507 -0.206487 -0.0844765
+-0.266216 -0.255148 -0.0773555
+-0.3573 -0.241493 -0.0844765
+
+-0.311348 -0.298403 -0.0773555
+-0.3573 -0.241493 -0.0844765
+-0.266216 -0.255148 -0.0773555
+
+-0.3573 -0.241493 -0.0844765
+-0.311348 -0.298403 -0.0773555
+-0.40597 -0.274388 -0.0630957
+
+-0.353758 -0.33905 -0.0559747
+-0.40597 -0.274388 -0.0630957
+-0.311348 -0.298403 -0.0773555
+
+-0.40597 -0.274388 -0.0630957
+-0.353758 -0.33905 -0.0559747
+-0.445645 -0.301204 -0.0229129
+
+-0.388332 -0.372186 -0.0157919
+-0.445645 -0.301204 -0.0229129
+-0.353758 -0.33905 -0.0559747
+
+-0.445645 -0.301204 -0.0229129
+-0.388332 -0.372186 -0.0157919
+-0.471542 -0.318707 0.0312253
+
+-0.410897 -0.393813 0.0383463
+-0.471542 -0.318707 0.0312253
+-0.388332 -0.372186 -0.0157919
+
+-0.471542 -0.318707 0.0312253
+-0.410897 -0.393813 0.0383463
+-0.480536 -0.324785 0.0927889
+
+-0.418735 -0.401325 0.0999099
+-0.480536 -0.324785 0.0927889
+-0.410897 -0.393813 0.0383463
+
+-0.418735 -0.401325 0.0999099
+-0.344887 -0.466318 0.0956167
+-0.410897 -0.393813 0.161474
+
+-0.338432 -0.457591 0.15718
+-0.410897 -0.393813 0.161474
+-0.344887 -0.466318 0.0956167
+
+-0.410897 -0.393813 0.161474
+-0.338432 -0.457591 0.15718
+-0.388332 -0.372186 0.215612
+
+-0.319846 -0.43246 0.211318
+-0.388332 -0.372186 0.215612
+-0.338432 -0.457591 0.15718
+
+-0.388332 -0.372186 0.215612
+-0.319846 -0.43246 0.211318
+-0.353758 -0.33905 0.255794
+
+-0.29137 -0.393959 0.251501
+-0.353758 -0.33905 0.255794
+-0.319846 -0.43246 0.211318
+
+-0.353758 -0.33905 0.255794
+-0.29137 -0.393959 0.251501
+-0.311348 -0.298403 0.277175
+
+-0.25644 -0.346729 0.272882
+-0.311348 -0.298403 0.277175
+-0.29137 -0.393959 0.251501
+
+-0.311348 -0.298403 0.277175
+-0.25644 -0.346729 0.272882
+-0.266216 -0.255148 0.277175
+
+-0.219267 -0.296469 0.272882
+-0.266216 -0.255148 0.277175
+-0.25644 -0.346729 0.272882
+
+-0.266216 -0.255148 0.277175
+-0.219267 -0.296469 0.272882
+-0.223806 -0.214501 0.255794
+
+-0.184336 -0.249239 0.251501
+-0.223806 -0.214501 0.255794
+-0.219267 -0.296469 0.272882
+
+-0.223806 -0.214501 0.255794
+-0.184336 -0.249239 0.251501
+-0.189233 -0.181365 0.215612
+
+-0.15586 -0.210737 0.211318
+-0.189233 -0.181365 0.215612
+-0.184336 -0.249239 0.251501
+
+-0.189233 -0.181365 0.215612
+-0.15586 -0.210737 0.211318
+-0.166667 -0.159738 0.161474
+
+-0.137274 -0.185607 0.15718
+-0.166667 -0.159738 0.161474
+-0.15586 -0.210737 0.211318
+
+-0.166667 -0.159738 0.161474
+-0.137274 -0.185607 0.15718
+-0.15883 -0.152227 0.0999099
+
+-0.130819 -0.176879 0.0956167
+-0.15883 -0.152227 0.0999099
+-0.137274 -0.185607 0.15718
+
+-0.15883 -0.152227 0.0999099
+-0.130819 -0.176879 0.0956167
+-0.166667 -0.159738 0.0383463
+
+-0.137274 -0.185607 0.034053
+-0.166667 -0.159738 0.0383463
+-0.130819 -0.176879 0.0956167
+
+-0.166667 -0.159738 0.0383463
+-0.137274 -0.185607 0.034053
+-0.189233 -0.181365 -0.0157919
+
+-0.15586 -0.210737 -0.0200851
+-0.189233 -0.181365 -0.0157919
+-0.137274 -0.185607 0.034053
+
+-0.189233 -0.181365 -0.0157919
+-0.15586 -0.210737 -0.0200851
+-0.223806 -0.214501 -0.0559747
+
+-0.184336 -0.249239 -0.0602679
+-0.223806 -0.214501 -0.0559747
+-0.15586 -0.210737 -0.0200851
+
+-0.223806 -0.214501 -0.0559747
+-0.184336 -0.249239 -0.0602679
+-0.266216 -0.255148 -0.0773555
+
+-0.219267 -0.296469 -0.0816487
+-0.266216 -0.255148 -0.0773555
+-0.184336 -0.249239 -0.0602679
+
+-0.266216 -0.255148 -0.0773555
+-0.219267 -0.296469 -0.0816487
+-0.311348 -0.298403 -0.0773555
+
+-0.25644 -0.346729 -0.0816487
+-0.311348 -0.298403 -0.0773555
+-0.219267 -0.296469 -0.0816487
+
+-0.311348 -0.298403 -0.0773555
+-0.25644 -0.346729 -0.0816487
+-0.353758 -0.33905 -0.0559747
+
+-0.29137 -0.393959 -0.0602679
+-0.353758 -0.33905 -0.0559747
+-0.25644 -0.346729 -0.0816487
+
+-0.353758 -0.33905 -0.0559747
+-0.29137 -0.393959 -0.0602679
+-0.388332 -0.372186 -0.0157919
+
+-0.319846 -0.43246 -0.0200851
+-0.388332 -0.372186 -0.0157919
+-0.29137 -0.393959 -0.0602679
+
+-0.388332 -0.372186 -0.0157919
+-0.319846 -0.43246 -0.0200851
+-0.410897 -0.393813 0.0383463
+
+-0.338432 -0.457591 0.034053
+-0.410897 -0.393813 0.0383463
+-0.319846 -0.43246 -0.0200851
+
+-0.410897 -0.393813 0.0383463
+-0.338432 -0.457591 0.034053
+-0.418735 -0.401325 0.0999099
+
+-0.344887 -0.466318 0.0956167
+-0.418735 -0.401325 0.0999099
+-0.338432 -0.457591 0.034053
+
+-0.344887 -0.466318 0.0956167
+-0.261118 -0.517897 0.0803997
+-0.338432 -0.457591 0.15718
+
+-0.256231 -0.508204 0.141963
+-0.338432 -0.457591 0.15718
+-0.261118 -0.517897 0.0803997
+
+-0.338432 -0.457591 0.15718
+-0.256231 -0.508204 0.141963
+-0.319846 -0.43246 0.211318
+
+-0.242159 -0.480294 0.196101
+-0.319846 -0.43246 0.211318
+-0.256231 -0.508204 0.141963
+
+-0.319846 -0.43246 0.211318
+-0.242159 -0.480294 0.196101
+-0.29137 -0.393959 0.251501
+
+-0.2206 -0.437534 0.236284
+-0.29137 -0.393959 0.251501
+-0.242159 -0.480294 0.196101
+
+-0.29137 -0.393959 0.251501
+-0.2206 -0.437534 0.236284
+-0.25644 -0.346729 0.272882
+
+-0.194153 -0.38508 0.257665
+-0.25644 -0.346729 0.272882
+-0.2206 -0.437534 0.236284
+
+-0.25644 -0.346729 0.272882
+-0.194153 -0.38508 0.257665
+-0.219267 -0.296469 0.272882
+
+-0.16601 -0.32926 0.257665
+-0.219267 -0.296469 0.272882
+-0.194153 -0.38508 0.257665
+
+-0.219267 -0.296469 0.272882
+-0.16601 -0.32926 0.257665
+-0.184336 -0.249239 0.251501
+
+-0.139563 -0.276807 0.236284
+-0.184336 -0.249239 0.251501
+-0.16601 -0.32926 0.257665
+
+-0.184336 -0.249239 0.251501
+-0.139563 -0.276807 0.236284
+-0.15586 -0.210737 0.211318
+
+-0.118004 -0.234047 0.196101
+-0.15586 -0.210737 0.211318
+-0.139563 -0.276807 0.236284
+
+-0.15586 -0.210737 0.211318
+-0.118004 -0.234047 0.196101
+-0.137274 -0.185607 0.15718
+
+-0.103932 -0.206137 0.141963
+-0.137274 -0.185607 0.15718
+-0.118004 -0.234047 0.196101
+
+-0.137274 -0.185607 0.15718
+-0.103932 -0.206137 0.141963
+-0.130819 -0.176879 0.0956167
+
+-0.0990448 -0.196444 0.0803997
+-0.130819 -0.176879 0.0956167
+-0.103932 -0.206137 0.141963
+
+-0.130819 -0.176879 0.0956167
+-0.0990448 -0.196444 0.0803997
+-0.137274 -0.185607 0.034053
+
+-0.103932 -0.206137 0.0188361
+-0.137274 -0.185607 0.034053
+-0.0990448 -0.196444 0.0803997
+
+-0.137274 -0.185607 0.034053
+-0.103932 -0.206137 0.0188361
+-0.15586 -0.210737 -0.0200851
+
+-0.118004 -0.234047 -0.0353021
+-0.15586 -0.210737 -0.0200851
+-0.103932 -0.206137 0.0188361
+
+-0.15586 -0.210737 -0.0200851
+-0.118004 -0.234047 -0.0353021
+-0.184336 -0.249239 -0.0602679
+
+-0.139563 -0.276807 -0.0754849
+-0.184336 -0.249239 -0.0602679
+-0.118004 -0.234047 -0.0353021
+
+-0.184336 -0.249239 -0.0602679
+-0.139563 -0.276807 -0.0754849
+-0.219267 -0.296469 -0.0816487
+
+-0.16601 -0.32926 -0.0968657
+-0.219267 -0.296469 -0.0816487
+-0.139563 -0.276807 -0.0754849
+
+-0.219267 -0.296469 -0.0816487
+-0.16601 -0.32926 -0.0968657
+-0.25644 -0.346729 -0.0816487
+
+-0.194153 -0.38508 -0.0968657
+-0.25644 -0.346729 -0.0816487
+-0.16601 -0.32926 -0.0968657
+
+-0.25644 -0.346729 -0.0816487
+-0.194153 -0.38508 -0.0968657
+-0.29137 -0.393959 -0.0602679
+
+-0.2206 -0.437534 -0.0754849
+-0.29137 -0.393959 -0.0602679
+-0.194153 -0.38508 -0.0968657
+
+-0.29137 -0.393959 -0.0602679
+-0.2206 -0.437534 -0.0754849
+-0.319846 -0.43246 -0.0200851
+
+-0.242159 -0.480294 -0.0353021
+-0.319846 -0.43246 -0.0200851
+-0.2206 -0.437534 -0.0754849
+
+-0.319846 -0.43246 -0.0200851
+-0.242159 -0.480294 -0.0353021
+-0.338432 -0.457591 0.034053
+
+-0.256231 -0.508204 0.0188361
+-0.338432 -0.457591 0.034053
+-0.242159 -0.480294 -0.0353021
+
+-0.338432 -0.457591 0.034053
+-0.256231 -0.508204 0.0188361
+-0.344887 -0.466318 0.0956167
+
+-0.261118 -0.517897 0.0803997
+-0.344887 -0.466318 0.0956167
+-0.256231 -0.508204 0.0188361
+
+-0.261118 -0.517897 0.0803997
+-0.169837 -0.554577 0.0559975
+-0.256231 -0.508204 0.141963
+
+-0.166659 -0.544197 0.117561
+-0.256231 -0.508204 0.141963
+-0.169837 -0.554577 0.0559975
+
+-0.256231 -0.508204 0.141963
+-0.166659 -0.544197 0.117561
+-0.242159 -0.480294 0.196101
+
+-0.157506 -0.514311 0.171699
+-0.242159 -0.480294 0.196101
+-0.166659 -0.544197 0.117561
+
+-0.242159 -0.480294 0.196101
+-0.157506 -0.514311 0.171699
+-0.2206 -0.437534 0.236284
+
+-0.143483 -0.468522 0.211882
+-0.2206 -0.437534 0.236284
+-0.157506 -0.514311 0.171699
+
+-0.2206 -0.437534 0.236284
+-0.143483 -0.468522 0.211882
+-0.194153 -0.38508 0.257665
+
+-0.126282 -0.412353 0.233263
+-0.194153 -0.38508 0.257665
+-0.143483 -0.468522 0.211882
+
+-0.194153 -0.38508 0.257665
+-0.126282 -0.412353 0.233263
+-0.16601 -0.32926 0.257665
+
+-0.107976 -0.35258 0.233263
+-0.16601 -0.32926 0.257665
+-0.126282 -0.412353 0.233263
+
+-0.16601 -0.32926 0.257665
+-0.107976 -0.35258 0.233263
+-0.139563 -0.276807 0.236284
+
+-0.0907751 -0.296412 0.211882
+-0.139563 -0.276807 0.236284
+-0.107976 -0.35258 0.233263
+
+-0.139563 -0.276807 0.236284
+-0.0907751 -0.296412 0.211882
+-0.118004 -0.234047 0.196101
+
+-0.0767524 -0.250623 0.171699
+-0.118004 -0.234047 0.196101
+-0.0907751 -0.296412 0.211882
+
+-0.118004 -0.234047 0.196101
+-0.0767524 -0.250623 0.171699
+-0.103932 -0.206137 0.141963
+
+-0.0675997 -0.220736 0.117561
+-0.103932 -0.206137 0.141963
+-0.0767524 -0.250623 0.171699
+
+-0.103932 -0.206137 0.141963
+-0.0675997 -0.220736 0.117561
+-0.0990448 -0.196444 0.0803997
+
+-0.064421 -0.210357 0.0559975
+-0.0990448 -0.196444 0.0803997
+-0.0675997 -0.220736 0.117561
+
+-0.0990448 -0.196444 0.0803997
+-0.064421 -0.210357 0.0559975
+-0.103932 -0.206137 0.0188361
+
+-0.0675997 -0.220736 -0.00556615
+-0.103932 -0.206137 0.0188361
+-0.064421 -0.210357 0.0559975
+
+-0.103932 -0.206137 0.0188361
+-0.0675997 -0.220736 -0.00556615
+-0.118004 -0.234047 -0.0353021
+
+-0.0767524 -0.250623 -0.0597043
+-0.118004 -0.234047 -0.0353021
+-0.0675997 -0.220736 -0.00556615
+
+-0.118004 -0.234047 -0.0353021
+-0.0767524 -0.250623 -0.0597043
+-0.139563 -0.276807 -0.0754849
+
+-0.0907751 -0.296412 -0.0998871
+-0.139563 -0.276807 -0.0754849
+-0.0767524 -0.250623 -0.0597043
+
+-0.139563 -0.276807 -0.0754849
+-0.0907751 -0.296412 -0.0998871
+-0.16601 -0.32926 -0.0968657
+
+-0.107976 -0.35258 -0.121268
+-0.16601 -0.32926 -0.0968657
+-0.0907751 -0.296412 -0.0998871
+
+-0.16601 -0.32926 -0.0968657
+-0.107976 -0.35258 -0.121268
+-0.194153 -0.38508 -0.0968657
+
+-0.126282 -0.412353 -0.121268
+-0.194153 -0.38508 -0.0968657
+-0.107976 -0.35258 -0.121268
+
+-0.194153 -0.38508 -0.0968657
+-0.126282 -0.412353 -0.121268
+-0.2206 -0.437534 -0.0754849
+
+-0.143483 -0.468522 -0.0998871
+-0.2206 -0.437534 -0.0754849
+-0.126282 -0.412353 -0.121268
+
+-0.2206 -0.437534 -0.0754849
+-0.143483 -0.468522 -0.0998871
+-0.242159 -0.480294 -0.0353021
+
+-0.157506 -0.514311 -0.0597043
+-0.242159 -0.480294 -0.0353021
+-0.143483 -0.468522 -0.0998871
+
+-0.242159 -0.480294 -0.0353021
+-0.157506 -0.514311 -0.0597043
+-0.256231 -0.508204 0.0188361
+
+-0.166659 -0.544197 -0.00556615
+-0.256231 -0.508204 0.0188361
+-0.157506 -0.514311 -0.0597043
+
+-0.256231 -0.508204 0.0188361
+-0.166659 -0.544197 -0.00556615
+-0.261118 -0.517897 0.0803997
+
+-0.169837 -0.554577 0.0559975
+-0.261118 -0.517897 0.0803997
+-0.166659 -0.544197 -0.00556615
+
+-0.169837 -0.554577 0.0559975
+-0.0736703 -0.575302 0.0251978
+-0.166659 -0.544197 0.117561
+
+-0.0722915 -0.564535 0.0867614
+-0.166659 -0.544197 0.117561
+-0.0736703 -0.575302 0.0251978
+
+-0.166659 -0.544197 0.117561
+-0.0722915 -0.564535 0.0867614
+-0.157506 -0.514311 0.171699
+
+-0.0683214 -0.533531 0.1409
+-0.157506 -0.514311 0.171699
+-0.0722915 -0.564535 0.0867614
+
+-0.157506 -0.514311 0.171699
+-0.0683214 -0.533531 0.1409
+-0.143483 -0.468522 0.211882
+
+-0.0622387 -0.486031 0.181082
+-0.143483 -0.468522 0.211882
+-0.0683214 -0.533531 0.1409
+
+-0.143483 -0.468522 0.211882
+-0.0622387 -0.486031 0.181082
+-0.126282 -0.412353 0.233263
+
+-0.0547773 -0.427764 0.202463
+-0.126282 -0.412353 0.233263
+-0.0622387 -0.486031 0.181082
+
+-0.126282 -0.412353 0.233263
+-0.0547773 -0.427764 0.202463
+-0.107976 -0.35258 0.233263
+
+-0.046837 -0.365757 0.202463
+-0.107976 -0.35258 0.233263
+-0.0547773 -0.427764 0.202463
+
+-0.107976 -0.35258 0.233263
+-0.046837 -0.365757 0.202463
+-0.0907751 -0.296412 0.211882
+
+-0.0393755 -0.307489 0.181082
+-0.0907751 -0.296412 0.211882
+-0.046837 -0.365757 0.202463
+
+-0.0907751 -0.296412 0.211882
+-0.0393755 -0.307489 0.181082
+-0.0767524 -0.250623 0.171699
+
+-0.0332929 -0.259989 0.1409
+-0.0767524 -0.250623 0.171699
+-0.0393755 -0.307489 0.181082
+
+-0.0767524 -0.250623 0.171699
+-0.0332929 -0.259989 0.1409
+-0.0675997 -0.220736 0.117561
+
+-0.0293227 -0.228986 0.0867614
+-0.0675997 -0.220736 0.117561
+-0.0332929 -0.259989 0.1409
+
+-0.0675997 -0.220736 0.117561
+-0.0293227 -0.228986 0.0867614
+-0.064421 -0.210357 0.0559975
+
+-0.0279439 -0.218218 0.0251978
+-0.064421 -0.210357 0.0559975
+-0.0293227 -0.228986 0.0867614
+
+-0.064421 -0.210357 0.0559975
+-0.0279439 -0.218218 0.0251978
+-0.0675997 -0.220736 -0.00556615
+
+-0.0293227 -0.228986 -0.0363658
+-0.0675997 -0.220736 -0.00556615
+-0.0279439 -0.218218 0.0251978
+
+-0.0675997 -0.220736 -0.00556615
+-0.0293227 -0.228986 -0.0363658
+-0.0767524 -0.250623 -0.0597043
+
+-0.0332929 -0.259989 -0.090504
+-0.0767524 -0.250623 -0.0597043
+-0.0293227 -0.228986 -0.0363658
+
+-0.0767524 -0.250623 -0.0597043
+-0.0332929 -0.259989 -0.090504
+-0.0907751 -0.296412 -0.0998871
+
+-0.0393755 -0.307489 -0.130687
+-0.0907751 -0.296412 -0.0998871
+-0.0332929 -0.259989 -0.090504
+
+-0.0907751 -0.296412 -0.0998871
+-0.0393755 -0.307489 -0.130687
+-0.107976 -0.35258 -0.121268
+
+-0.046837 -0.365757 -0.152068
+-0.107976 -0.35258 -0.121268
+-0.0393755 -0.307489 -0.130687
+
+-0.107976 -0.35258 -0.121268
+-0.046837 -0.365757 -0.152068
+-0.126282 -0.412353 -0.121268
+
+-0.0547773 -0.427764 -0.152068
+-0.126282 -0.412353 -0.121268
+-0.046837 -0.365757 -0.152068
+
+-0.126282 -0.412353 -0.121268
+-0.0547773 -0.427764 -0.152068
+-0.143483 -0.468522 -0.0998871
+
+-0.0622387 -0.486031 -0.130687
+-0.143483 -0.468522 -0.0998871
+-0.0547773 -0.427764 -0.152068
+
+-0.143483 -0.468522 -0.0998871
+-0.0622387 -0.486031 -0.130687
+-0.157506 -0.514311 -0.0597043
+
+-0.0683214 -0.533531 -0.090504
+-0.157506 -0.514311 -0.0597043
+-0.0622387 -0.486031 -0.130687
+
+-0.157506 -0.514311 -0.0597043
+-0.0683214 -0.533531 -0.090504
+-0.166659 -0.544197 -0.00556615
+
+-0.0722915 -0.564535 -0.0363658
+-0.166659 -0.544197 -0.00556615
+-0.0683214 -0.533531 -0.090504
+
+-0.166659 -0.544197 -0.00556615
+-0.0722915 -0.564535 -0.0363658
+-0.169837 -0.554577 0.0559975
+
+-0.0736703 -0.575302 0.0251978
+-0.169837 -0.554577 0.0559975
+-0.0722915 -0.564535 -0.0363658
+
+-0.0736703 -0.575302 0.0251978
+0.0246159 -0.579477 -0.00848059
+-0.0722915 -0.564535 0.0867614
+
+0.0241552 -0.568632 0.053083
+-0.0722915 -0.564535 0.0867614
+0.0246159 -0.579477 -0.00848059
+
+-0.0722915 -0.564535 0.0867614
+0.0241552 -0.568632 0.053083
+-0.0683214 -0.533531 0.1409
+
+0.0228286 -0.537403 0.107221
+-0.0683214 -0.533531 0.1409
+0.0241552 -0.568632 0.053083
+
+-0.0683214 -0.533531 0.1409
+0.0228286 -0.537403 0.107221
+-0.0622387 -0.486031 0.181082
+
+0.0207962 -0.489558 0.147404
+-0.0622387 -0.486031 0.181082
+0.0228286 -0.537403 0.107221
+
+-0.0622387 -0.486031 0.181082
+0.0207962 -0.489558 0.147404
+-0.0547773 -0.427764 0.202463
+
+0.0183031 -0.430868 0.168785
+-0.0547773 -0.427764 0.202463
+0.0207962 -0.489558 0.147404
+
+-0.0547773 -0.427764 0.202463
+0.0183031 -0.430868 0.168785
+-0.046837 -0.365757 0.202463
+
+0.0156499 -0.368411 0.168785
+-0.046837 -0.365757 0.202463
+0.0183031 -0.430868 0.168785
+
+-0.046837 -0.365757 0.202463
+0.0156499 -0.368411 0.168785
+-0.0393755 -0.307489 0.181082
+
+0.0131568 -0.309721 0.147404
+-0.0393755 -0.307489 0.181082
+0.0156499 -0.368411 0.168785
+
+-0.0393755 -0.307489 0.181082
+0.0131568 -0.309721 0.147404
+-0.0332929 -0.259989 0.1409
+
+0.0111243 -0.261876 0.107221
+-0.0332929 -0.259989 0.1409
+0.0131568 -0.309721 0.147404
+
+-0.0332929 -0.259989 0.1409
+0.0111243 -0.261876 0.107221
+-0.0293227 -0.228986 0.0867614
+
+0.00979778 -0.230647 0.053083
+-0.0293227 -0.228986 0.0867614
+0.0111243 -0.261876 0.107221
+
+-0.0293227 -0.228986 0.0867614
+0.00979778 -0.230647 0.053083
+-0.0279439 -0.218218 0.0251978
+
+0.00933706 -0.219802 -0.00848059
+-0.0279439 -0.218218 0.0251978
+0.00979778 -0.230647 0.053083
+
+-0.0279439 -0.218218 0.0251978
+0.00933706 -0.219802 -0.00848059
+-0.0293227 -0.228986 -0.0363658
+
+0.00979778 -0.230647 -0.0700442
+-0.0293227 -0.228986 -0.0363658
+0.00933706 -0.219802 -0.00848059
+
+-0.0293227 -0.228986 -0.0363658
+0.00979778 -0.230647 -0.0700442
+-0.0332929 -0.259989 -0.090504
+
+0.0111243 -0.261876 -0.124182
+-0.0332929 -0.259989 -0.090504
+0.00979778 -0.230647 -0.0700442
+
+-0.0332929 -0.259989 -0.090504
+0.0111243 -0.261876 -0.124182
+-0.0393755 -0.307489 -0.130687
+
+0.0131568 -0.309721 -0.164365
+-0.0393755 -0.307489 -0.130687
+0.0111243 -0.261876 -0.124182
+
+-0.0393755 -0.307489 -0.130687
+0.0131568 -0.309721 -0.164365
+-0.046837 -0.365757 -0.152068
+
+0.0156499 -0.368411 -0.185746
+-0.046837 -0.365757 -0.152068
+0.0131568 -0.309721 -0.164365
+
+-0.046837 -0.365757 -0.152068
+0.0156499 -0.368411 -0.185746
+-0.0547773 -0.427764 -0.152068
+
+0.0183031 -0.430868 -0.185746
+-0.0547773 -0.427764 -0.152068
+0.0156499 -0.368411 -0.185746
+
+-0.0547773 -0.427764 -0.152068
+0.0183031 -0.430868 -0.185746
+-0.0622387 -0.486031 -0.130687
+
+0.0207962 -0.489558 -0.164365
+-0.0622387 -0.486031 -0.130687
+0.0183031 -0.430868 -0.185746
+
+-0.0622387 -0.486031 -0.130687
+0.0207962 -0.489558 -0.164365
+-0.0683214 -0.533531 -0.090504
+
+0.0228286 -0.537403 -0.124182
+-0.0683214 -0.533531 -0.090504
+0.0207962 -0.489558 -0.164365
+
+-0.0683214 -0.533531 -0.090504
+0.0228286 -0.537403 -0.124182
+-0.0722915 -0.564535 -0.0363658
+
+0.0241552 -0.568632 -0.0700442
+-0.0722915 -0.564535 -0.0363658
+0.0228286 -0.537403 -0.124182
+
+-0.0722915 -0.564535 -0.0363658
+0.0241552 -0.568632 -0.0700442
+-0.0736703 -0.575302 0.0251978
+
+0.0246159 -0.579477 -0.00848059
+-0.0736703 -0.575302 0.0251978
+0.0241552 -0.568632 -0.0700442
+
+0.0246159 -0.579477 -0.00848059
+0.122194 -0.566982 -0.0411901
+0.0241552 -0.568632 0.053083
+
+0.119907 -0.55637 0.0203735
+0.0241552 -0.568632 0.053083
+0.122194 -0.566982 -0.0411901
+
+0.0241552 -0.568632 0.053083
+0.119907 -0.55637 0.0203735
+0.0228286 -0.537403 0.107221
+
+0.113322 -0.525815 0.0745116
+0.0228286 -0.537403 0.107221
+0.119907 -0.55637 0.0203735
+
+0.0228286 -0.537403 0.107221
+0.113322 -0.525815 0.0745116
+0.0207962 -0.489558 0.147404
+
+0.103233 -0.479002 0.114694
+0.0207962 -0.489558 0.147404
+0.113322 -0.525815 0.0745116
+
+0.0207962 -0.489558 0.147404
+0.103233 -0.479002 0.114694
+0.0183031 -0.430868 0.168785
+
+0.0908568 -0.421577 0.136075
+0.0183031 -0.430868 0.168785
+0.103233 -0.479002 0.114694
+
+0.0183031 -0.430868 0.168785
+0.0908568 -0.421577 0.136075
+0.0156499 -0.368411 0.168785
+
+0.0776866 -0.360467 0.136075
+0.0156499 -0.368411 0.168785
+0.0908568 -0.421577 0.136075
+
+0.0156499 -0.368411 0.168785
+0.0776866 -0.360467 0.136075
+0.0131568 -0.309721 0.147404
+
+0.0653106 -0.303042 0.114694
+0.0131568 -0.309721 0.147404
+0.0776866 -0.360467 0.136075
+
+0.0131568 -0.309721 0.147404
+0.0653106 -0.303042 0.114694
+0.0111243 -0.261876 0.107221
+
+0.0552216 -0.256229 0.0745116
+0.0111243 -0.261876 0.107221
+0.0653106 -0.303042 0.114694
+
+0.0111243 -0.261876 0.107221
+0.0552216 -0.256229 0.0745116
+0.00979778 -0.230647 0.053083
+
+0.0486364 -0.225674 0.0203735
+0.00979778 -0.230647 0.053083
+0.0552216 -0.256229 0.0745116
+
+0.00979778 -0.230647 0.053083
+0.0486364 -0.225674 0.0203735
+0.00933706 -0.219802 -0.00848059
+
+0.0463494 -0.215062 -0.0411901
+0.00933706 -0.219802 -0.00848059
+0.0486364 -0.225674 0.0203735
+
+0.00933706 -0.219802 -0.00848059
+0.0463494 -0.215062 -0.0411901
+0.00979778 -0.230647 -0.0700442
+
+0.0486364 -0.225674 -0.102754
+0.00979778 -0.230647 -0.0700442
+0.0463494 -0.215062 -0.0411901
+
+0.00979778 -0.230647 -0.0700442
+0.0486364 -0.225674 -0.102754
+0.0111243 -0.261876 -0.124182
+
+0.0552216 -0.256229 -0.156892
+0.0111243 -0.261876 -0.124182
+0.0486364 -0.225674 -0.102754
+
+0.0111243 -0.261876 -0.124182
+0.0552216 -0.256229 -0.156892
+0.0131568 -0.309721 -0.164365
+
+0.0653106 -0.303042 -0.197075
+0.0131568 -0.309721 -0.164365
+0.0552216 -0.256229 -0.156892
+
+0.0131568 -0.309721 -0.164365
+0.0653106 -0.303042 -0.197075
+0.0156499 -0.368411 -0.185746
+
+0.0776866 -0.360467 -0.218456
+0.0156499 -0.368411 -0.185746
+0.0653106 -0.303042 -0.197075
+
+0.0156499 -0.368411 -0.185746
+0.0776866 -0.360467 -0.218456
+0.0183031 -0.430868 -0.185746
+
+0.0908568 -0.421577 -0.218456
+0.0183031 -0.430868 -0.185746
+0.0776866 -0.360467 -0.218456
+
+0.0183031 -0.430868 -0.185746
+0.0908568 -0.421577 -0.218456
+0.0207962 -0.489558 -0.164365
+
+0.103233 -0.479002 -0.197075
+0.0207962 -0.489558 -0.164365
+0.0908568 -0.421577 -0.218456
+
+0.0207962 -0.489558 -0.164365
+0.103233 -0.479002 -0.197075
+0.0228286 -0.537403 -0.124182
+
+0.113322 -0.525815 -0.156892
+0.0228286 -0.537403 -0.124182
+0.103233 -0.479002 -0.197075
+
+0.0228286 -0.537403 -0.124182
+0.113322 -0.525815 -0.156892
+0.0241552 -0.568632 -0.0700442
+
+0.119907 -0.55637 -0.102754
+0.0241552 -0.568632 -0.0700442
+0.113322 -0.525815 -0.156892
+
+0.0241552 -0.568632 -0.0700442
+0.119907 -0.55637 -0.102754
+0.0246159 -0.579477 -0.00848059
+
+0.122194 -0.566982 -0.0411901
+0.0246159 -0.579477 -0.00848059
+0.119907 -0.55637 -0.102754
+
+0.122194 -0.566982 -0.0411901
+0.216257 -0.538176 -0.0691939
+0.119907 -0.55637 0.0203735
+
+0.212209 -0.528103 -0.00763026
+0.119907 -0.55637 0.0203735
+0.216257 -0.538176 -0.0691939
+
+0.119907 -0.55637 0.0203735
+0.212209 -0.528103 -0.00763026
+0.113322 -0.525815 0.0745116
+
+0.200555 -0.4991 0.0465079
+0.113322 -0.525815 0.0745116
+0.212209 -0.528103 -0.00763026
+
+0.113322 -0.525815 0.0745116
+0.200555 -0.4991 0.0465079
+0.103233 -0.479002 0.114694
+
+0.1827 -0.454666 0.0866907
+0.103233 -0.479002 0.114694
+0.200555 -0.4991 0.0465079
+
+0.103233 -0.479002 0.114694
+0.1827 -0.454666 0.0866907
+0.0908568 -0.421577 0.136075
+
+0.160797 -0.400158 0.108072
+0.0908568 -0.421577 0.136075
+0.1827 -0.454666 0.0866907
+
+0.0908568 -0.421577 0.136075
+0.160797 -0.400158 0.108072
+0.0776866 -0.360467 0.136075
+
+0.137488 -0.342153 0.108072
+0.0776866 -0.360467 0.136075
+0.160797 -0.400158 0.108072
+
+0.0776866 -0.360467 0.136075
+0.137488 -0.342153 0.108072
+0.0653106 -0.303042 0.114694
+
+0.115586 -0.287646 0.0866907
+0.0653106 -0.303042 0.114694
+0.137488 -0.342153 0.108072
+
+0.0653106 -0.303042 0.114694
+0.115586 -0.287646 0.0866907
+0.0552216 -0.256229 0.0745116
+
+0.0977302 -0.243211 0.0465079
+0.0552216 -0.256229 0.0745116
+0.115586 -0.287646 0.0866907
+
+0.0552216 -0.256229 0.0745116
+0.0977302 -0.243211 0.0465079
+0.0486364 -0.225674 0.0203735
+
+0.0860759 -0.214208 -0.00763026
+0.0486364 -0.225674 0.0203735
+0.0977302 -0.243211 0.0465079
+
+0.0486364 -0.225674 0.0203735
+0.0860759 -0.214208 -0.00763026
+0.0463494 -0.215062 -0.0411901
+
+0.0820284 -0.204136 -0.0691939
+0.0463494 -0.215062 -0.0411901
+0.0860759 -0.214208 -0.00763026
+
+0.0463494 -0.215062 -0.0411901
+0.0820284 -0.204136 -0.0691939
+0.0486364 -0.225674 -0.102754
+
+0.0860759 -0.214208 -0.130758
+0.0486364 -0.225674 -0.102754
+0.0820284 -0.204136 -0.0691939
+
+0.0486364 -0.225674 -0.102754
+0.0860759 -0.214208 -0.130758
+0.0552216 -0.256229 -0.156892
+
+0.0977302 -0.243211 -0.184896
+0.0552216 -0.256229 -0.156892
+0.0860759 -0.214208 -0.130758
+
+0.0552216 -0.256229 -0.156892
+0.0977302 -0.243211 -0.184896
+0.0653106 -0.303042 -0.197075
+
+0.115586 -0.287646 -0.225078
+0.0653106 -0.303042 -0.197075
+0.0977302 -0.243211 -0.184896
+
+0.0653106 -0.303042 -0.197075
+0.115586 -0.287646 -0.225078
+0.0776866 -0.360467 -0.218456
+
+0.137488 -0.342153 -0.246459
+0.0776866 -0.360467 -0.218456
+0.115586 -0.287646 -0.225078
+
+0.0776866 -0.360467 -0.218456
+0.137488 -0.342153 -0.246459
+0.0908568 -0.421577 -0.218456
+
+0.160797 -0.400158 -0.246459
+0.0908568 -0.421577 -0.218456
+0.137488 -0.342153 -0.246459
+
+0.0908568 -0.421577 -0.218456
+0.160797 -0.400158 -0.246459
+0.103233 -0.479002 -0.197075
+
+0.1827 -0.454666 -0.225078
+0.103233 -0.479002 -0.197075
+0.160797 -0.400158 -0.246459
+
+0.103233 -0.479002 -0.197075
+0.1827 -0.454666 -0.225078
+0.113322 -0.525815 -0.156892
+
+0.200555 -0.4991 -0.184896
+0.113322 -0.525815 -0.156892
+0.1827 -0.454666 -0.225078
+
+0.113322 -0.525815 -0.156892
+0.200555 -0.4991 -0.184896
+0.119907 -0.55637 -0.102754
+
+0.212209 -0.528103 -0.130758
+0.119907 -0.55637 -0.102754
+0.200555 -0.4991 -0.184896
+
+0.119907 -0.55637 -0.102754
+0.212209 -0.528103 -0.130758
+0.122194 -0.566982 -0.0411901
+
+0.216257 -0.538176 -0.0691939
+0.122194 -0.566982 -0.0411901
+0.212209 -0.528103 -0.130758
+
+0.216257 -0.538176 -0.0691939
+0.304098 -0.493887 -0.0892926
+0.212209 -0.528103 -0.00763026
+
+0.298407 -0.484643 -0.027729
+0.212209 -0.528103 -0.00763026
+0.304098 -0.493887 -0.0892926
+
+0.212209 -0.528103 -0.00763026
+0.298407 -0.484643 -0.027729
+0.200555 -0.4991 0.0465079
+
+0.282019 -0.458027 0.0264092
+0.200555 -0.4991 0.0465079
+0.298407 -0.484643 -0.027729
+
+0.200555 -0.4991 0.0465079
+0.282019 -0.458027 0.0264092
+0.1827 -0.454666 0.0866907
+
+0.256911 -0.417249 0.066592
+0.1827 -0.454666 0.0866907
+0.282019 -0.458027 0.0264092
+
+0.1827 -0.454666 0.0866907
+0.256911 -0.417249 0.066592
+0.160797 -0.400158 0.108072
+
+0.226111 -0.367228 0.0879728
+0.160797 -0.400158 0.108072
+0.256911 -0.417249 0.066592
+
+0.160797 -0.400158 0.108072
+0.226111 -0.367228 0.0879728
+0.137488 -0.342153 0.108072
+
+0.193335 -0.313996 0.0879728
+0.137488 -0.342153 0.108072
+0.226111 -0.367228 0.0879728
+
+0.137488 -0.342153 0.108072
+0.193335 -0.313996 0.0879728
+0.115586 -0.287646 0.0866907
+
+0.162535 -0.263974 0.066592
+0.115586 -0.287646 0.0866907
+0.193335 -0.313996 0.0879728
+
+0.115586 -0.287646 0.0866907
+0.162535 -0.263974 0.066592
+0.0977302 -0.243211 0.0465079
+
+0.137427 -0.223196 0.0264092
+0.0977302 -0.243211 0.0465079
+0.162535 -0.263974 0.066592
+
+0.0977302 -0.243211 0.0465079
+0.137427 -0.223196 0.0264092
+0.0860759 -0.214208 -0.00763026
+
+0.121039 -0.19658 -0.027729
+0.0860759 -0.214208 -0.00763026
+0.137427 -0.223196 0.0264092
+
+0.0860759 -0.214208 -0.00763026
+0.121039 -0.19658 -0.027729
+0.0820284 -0.204136 -0.0691939
+
+0.115348 -0.187336 -0.0892926
+0.0820284 -0.204136 -0.0691939
+0.121039 -0.19658 -0.027729
+
+0.0820284 -0.204136 -0.0691939
+0.115348 -0.187336 -0.0892926
+0.0860759 -0.214208 -0.130758
+
+0.121039 -0.19658 -0.150856
+0.0860759 -0.214208 -0.130758
+0.115348 -0.187336 -0.0892926
+
+0.0860759 -0.214208 -0.130758
+0.121039 -0.19658 -0.150856
+0.0977302 -0.243211 -0.184896
+
+0.137427 -0.223196 -0.204994
+0.0977302 -0.243211 -0.184896
+0.121039 -0.19658 -0.150856
+
+0.0977302 -0.243211 -0.184896
+0.137427 -0.223196 -0.204994
+0.115586 -0.287646 -0.225078
+
+0.162535 -0.263974 -0.245177
+0.115586 -0.287646 -0.225078
+0.137427 -0.223196 -0.204994
+
+0.115586 -0.287646 -0.225078
+0.162535 -0.263974 -0.245177
+0.137488 -0.342153 -0.246459
+
+0.193335 -0.313996 -0.266558
+0.137488 -0.342153 -0.246459
+0.162535 -0.263974 -0.245177
+
+0.137488 -0.342153 -0.246459
+0.193335 -0.313996 -0.266558
+0.160797 -0.400158 -0.246459
+
+0.226111 -0.367228 -0.266558
+0.160797 -0.400158 -0.246459
+0.193335 -0.313996 -0.266558
+
+0.160797 -0.400158 -0.246459
+0.226111 -0.367228 -0.266558
+0.1827 -0.454666 -0.225078
+
+0.256911 -0.417249 -0.245177
+0.1827 -0.454666 -0.225078
+0.226111 -0.367228 -0.266558
+
+0.1827 -0.454666 -0.225078
+0.256911 -0.417249 -0.245177
+0.200555 -0.4991 -0.184896
+
+0.282019 -0.458027 -0.204994
+0.200555 -0.4991 -0.184896
+0.256911 -0.417249 -0.245177
+
+0.200555 -0.4991 -0.184896
+0.282019 -0.458027 -0.204994
+0.212209 -0.528103 -0.130758
+
+0.298407 -0.484643 -0.150856
+0.212209 -0.528103 -0.130758
+0.282019 -0.458027 -0.204994
+
+0.212209 -0.528103 -0.130758
+0.298407 -0.484643 -0.150856
+0.216257 -0.538176 -0.0691939
+
+0.304098 -0.493887 -0.0892926
+0.216257 -0.538176 -0.0691939
+0.298407 -0.484643 -0.150856
+
+0.304098 -0.493887 -0.0892926
+0.383191 -0.43539 -0.09919
+0.298407 -0.484643 -0.027729
+
+0.376019 -0.427241 -0.0376264
+0.298407 -0.484643 -0.027729
+0.383191 -0.43539 -0.09919
+
+0.298407 -0.484643 -0.027729
+0.376019 -0.427241 -0.0376264
+0.282019 -0.458027 0.0264092
+
+0.355369 -0.403778 0.0165117
+0.282019 -0.458027 0.0264092
+0.376019 -0.427241 -0.0376264
+
+0.282019 -0.458027 0.0264092
+0.355369 -0.403778 0.0165117
+0.256911 -0.417249 0.066592
+
+0.323731 -0.367829 0.0566945
+0.256911 -0.417249 0.066592
+0.355369 -0.403778 0.0165117
+
+0.256911 -0.417249 0.066592
+0.323731 -0.367829 0.0566945
+0.226111 -0.367228 0.0879728
+
+0.28492 -0.323732 0.0780754
+0.226111 -0.367228 0.0879728
+0.323731 -0.367829 0.0566945
+
+0.226111 -0.367228 0.0879728
+0.28492 -0.323732 0.0780754
+0.193335 -0.313996 0.0879728
+
+0.243619 -0.276805 0.0780754
+0.193335 -0.313996 0.0879728
+0.28492 -0.323732 0.0780754
+
+0.193335 -0.313996 0.0879728
+0.243619 -0.276805 0.0780754
+0.162535 -0.263974 0.066592
+
+0.204809 -0.232708 0.0566945
+0.162535 -0.263974 0.066592
+0.243619 -0.276805 0.0780754
+
+0.162535 -0.263974 0.066592
+0.204809 -0.232708 0.0566945
+0.137427 -0.223196 0.0264092
+
+0.173171 -0.19676 0.0165117
+0.137427 -0.223196 0.0264092
+0.204809 -0.232708 0.0566945
+
+0.137427 -0.223196 0.0264092
+0.173171 -0.19676 0.0165117
+0.121039 -0.19658 -0.027729
+
+0.15252 -0.173297 -0.0376264
+0.121039 -0.19658 -0.027729
+0.173171 -0.19676 0.0165117
+
+0.121039 -0.19658 -0.027729
+0.15252 -0.173297 -0.0376264
+0.115348 -0.187336 -0.0892926
+
+0.145348 -0.165148 -0.09919
+0.115348 -0.187336 -0.0892926
+0.15252 -0.173297 -0.0376264
+
+0.115348 -0.187336 -0.0892926
+0.145348 -0.165148 -0.09919
+0.121039 -0.19658 -0.150856
+
+0.15252 -0.173297 -0.160754
+0.121039 -0.19658 -0.150856
+0.145348 -0.165148 -0.09919
+
+0.121039 -0.19658 -0.150856
+0.15252 -0.173297 -0.160754
+0.137427 -0.223196 -0.204994
+
+0.173171 -0.19676 -0.214892
+0.137427 -0.223196 -0.204994
+0.15252 -0.173297 -0.160754
+
+0.137427 -0.223196 -0.204994
+0.173171 -0.19676 -0.214892
+0.162535 -0.263974 -0.245177
+
+0.204809 -0.232708 -0.255075
+0.162535 -0.263974 -0.245177
+0.173171 -0.19676 -0.214892
+
+0.162535 -0.263974 -0.245177
+0.204809 -0.232708 -0.255075
+0.193335 -0.313996 -0.266558
+
+0.243619 -0.276805 -0.276455
+0.193335 -0.313996 -0.266558
+0.204809 -0.232708 -0.255075
+
+0.193335 -0.313996 -0.266558
+0.243619 -0.276805 -0.276455
+0.226111 -0.367228 -0.266558
+
+0.28492 -0.323732 -0.276455
+0.226111 -0.367228 -0.266558
+0.243619 -0.276805 -0.276455
+
+0.226111 -0.367228 -0.266558
+0.28492 -0.323732 -0.276455
+0.256911 -0.417249 -0.245177
+
+0.323731 -0.367829 -0.255075
+0.256911 -0.417249 -0.245177
+0.28492 -0.323732 -0.276455
+
+0.256911 -0.417249 -0.245177
+0.323731 -0.367829 -0.255075
+0.282019 -0.458027 -0.204994
+
+0.355369 -0.403778 -0.214892
+0.282019 -0.458027 -0.204994
+0.323731 -0.367829 -0.255075
+
+0.282019 -0.458027 -0.204994
+0.355369 -0.403778 -0.214892
+0.298407 -0.484643 -0.150856
+
+0.376019 -0.427241 -0.160754
+0.298407 -0.484643 -0.150856
+0.355369 -0.403778 -0.214892
+
+0.298407 -0.484643 -0.150856
+0.376019 -0.427241 -0.160754
+0.304098 -0.493887 -0.0892926
+
+0.383191 -0.43539 -0.09919
+0.304098 -0.493887 -0.0892926
+0.376019 -0.427241 -0.160754
+
+0.383191 -0.43539 -0.09919
+0.451261 -0.364368 -0.0977555
+0.376019 -0.427241 -0.0376264
+
+0.442815 -0.357548 -0.0361919
+0.376019 -0.427241 -0.0376264
+0.451261 -0.364368 -0.0977555
+
+0.376019 -0.427241 -0.0376264
+0.442815 -0.357548 -0.0361919
+0.355369 -0.403778 0.0165117
+
+0.418496 -0.337912 0.0179462
+0.355369 -0.403778 0.0165117
+0.442815 -0.357548 -0.0361919
+
+0.355369 -0.403778 0.0165117
+0.418496 -0.337912 0.0179462
+0.323731 -0.367829 0.0566945
+
+0.381238 -0.307828 0.058129
+0.323731 -0.367829 0.0566945
+0.418496 -0.337912 0.0179462
+
+0.323731 -0.367829 0.0566945
+0.381238 -0.307828 0.058129
+0.28492 -0.323732 0.0780754
+
+0.335533 -0.270924 0.0795099
+0.28492 -0.323732 0.0780754
+0.381238 -0.307828 0.058129
+
+0.28492 -0.323732 0.0780754
+0.335533 -0.270924 0.0795099
+0.243619 -0.276805 0.0780754
+
+0.286895 -0.231652 0.0795099
+0.243619 -0.276805 0.0780754
+0.335533 -0.270924 0.0795099
+
+0.243619 -0.276805 0.0780754
+0.286895 -0.231652 0.0795099
+0.204809 -0.232708 0.0566945
+
+0.241191 -0.194748 0.058129
+0.204809 -0.232708 0.0566945
+0.286895 -0.231652 0.0795099
+
+0.204809 -0.232708 0.0566945
+0.241191 -0.194748 0.058129
+0.173171 -0.19676 0.0165117
+
+0.203933 -0.164664 0.0179462
+0.173171 -0.19676 0.0165117
+0.241191 -0.194748 0.058129
+
+0.173171 -0.19676 0.0165117
+0.203933 -0.164664 0.0179462
+0.15252 -0.173297 -0.0376264
+
+0.179614 -0.145028 -0.0361919
+0.15252 -0.173297 -0.0376264
+0.203933 -0.164664 0.0179462
+
+0.15252 -0.173297 -0.0376264
+0.179614 -0.145028 -0.0361919
+0.145348 -0.165148 -0.09919
+
+0.171168 -0.138208 -0.0977555
+0.145348 -0.165148 -0.09919
+0.179614 -0.145028 -0.0361919
+
+0.145348 -0.165148 -0.09919
+0.171168 -0.138208 -0.0977555
+0.15252 -0.173297 -0.160754
+
+0.179614 -0.145028 -0.159319
+0.15252 -0.173297 -0.160754
+0.171168 -0.138208 -0.0977555
+
+0.15252 -0.173297 -0.160754
+0.179614 -0.145028 -0.159319
+0.173171 -0.19676 -0.214892
+
+0.203933 -0.164664 -0.213457
+0.173171 -0.19676 -0.214892
+0.179614 -0.145028 -0.159319
+
+0.173171 -0.19676 -0.214892
+0.203933 -0.164664 -0.213457
+0.204809 -0.232708 -0.255075
+
+0.241191 -0.194748 -0.25364
+0.204809 -0.232708 -0.255075
+0.203933 -0.164664 -0.213457
+
+0.204809 -0.232708 -0.255075
+0.241191 -0.194748 -0.25364
+0.243619 -0.276805 -0.276455
+
+0.286895 -0.231652 -0.275021
+0.243619 -0.276805 -0.276455
+0.241191 -0.194748 -0.25364
+
+0.243619 -0.276805 -0.276455
+0.286895 -0.231652 -0.275021
+0.28492 -0.323732 -0.276455
+
+0.335533 -0.270924 -0.275021
+0.28492 -0.323732 -0.276455
+0.286895 -0.231652 -0.275021
+
+0.28492 -0.323732 -0.276455
+0.335533 -0.270924 -0.275021
+0.323731 -0.367829 -0.255075
+
+0.381238 -0.307828 -0.25364
+0.323731 -0.367829 -0.255075
+0.335533 -0.270924 -0.275021
+
+0.323731 -0.367829 -0.255075
+0.381238 -0.307828 -0.25364
+0.355369 -0.403778 -0.214892
+
+0.418496 -0.337912 -0.213457
+0.355369 -0.403778 -0.214892
+0.381238 -0.307828 -0.25364
+
+0.355369 -0.403778 -0.214892
+0.418496 -0.337912 -0.213457
+0.376019 -0.427241 -0.160754
+
+0.442815 -0.357548 -0.159319
+0.376019 -0.427241 -0.160754
+0.418496 -0.337912 -0.213457
+
+0.376019 -0.427241 -0.160754
+0.442815 -0.357548 -0.159319
+0.383191 -0.43539 -0.09919
+
+0.451261 -0.364368 -0.0977555
+0.383191 -0.43539 -0.09919
+0.442815 -0.357548 -0.159319
+
+0.451261 -0.364368 -0.0977555
+0.506348 -0.282863 -0.0851529
+0.442815 -0.357548 -0.0361919
+
+0.496871 -0.277569 -0.0235893
+0.442815 -0.357548 -0.0361919
+0.506348 -0.282863 -0.0851529
+
+0.442815 -0.357548 -0.0361919
+0.496871 -0.277569 -0.0235893
+0.418496 -0.337912 0.0179462
+
+0.469584 -0.262325 0.0305489
+0.418496 -0.337912 0.0179462
+0.496871 -0.277569 -0.0235893
+
+0.418496 -0.337912 0.0179462
+0.469584 -0.262325 0.0305489
+0.381238 -0.307828 0.058129
+
+0.427777 -0.238971 0.0707317
+0.381238 -0.307828 0.058129
+0.469584 -0.262325 0.0305489
+
+0.381238 -0.307828 0.058129
+0.427777 -0.238971 0.0707317
+0.335533 -0.270924 0.0795099
+
+0.376493 -0.210322 0.0921125
+0.335533 -0.270924 0.0795099
+0.427777 -0.238971 0.0707317
+
+0.335533 -0.270924 0.0795099
+0.376493 -0.210322 0.0921125
+0.286895 -0.231652 0.0795099
+
+0.321918 -0.179834 0.0921125
+0.286895 -0.231652 0.0795099
+0.376493 -0.210322 0.0921125
+
+0.286895 -0.231652 0.0795099
+0.321918 -0.179834 0.0921125
+0.241191 -0.194748 0.058129
+
+0.270634 -0.151185 0.0707317
+0.241191 -0.194748 0.058129
+0.321918 -0.179834 0.0921125
+
+0.241191 -0.194748 0.058129
+0.270634 -0.151185 0.0707317
+0.203933 -0.164664 0.0179462
+
+0.228827 -0.127831 0.0305489
+0.203933 -0.164664 0.0179462
+0.270634 -0.151185 0.0707317
+
+0.203933 -0.164664 0.0179462
+0.228827 -0.127831 0.0305489
+0.179614 -0.145028 -0.0361919
+
+0.20154 -0.112587 -0.0235893
+0.179614 -0.145028 -0.0361919
+0.228827 -0.127831 0.0305489
+
+0.179614 -0.145028 -0.0361919
+0.20154 -0.112587 -0.0235893
+0.171168 -0.138208 -0.0977555
+
+0.192063 -0.107293 -0.0851529
+0.171168 -0.138208 -0.0977555
+0.20154 -0.112587 -0.0235893
+
+0.171168 -0.138208 -0.0977555
+0.192063 -0.107293 -0.0851529
+0.179614 -0.145028 -0.159319
+
+0.20154 -0.112587 -0.146717
+0.179614 -0.145028 -0.159319
+0.192063 -0.107293 -0.0851529
+
+0.179614 -0.145028 -0.159319
+0.20154 -0.112587 -0.146717
+0.203933 -0.164664 -0.213457
+
+0.228827 -0.127831 -0.200855
+0.203933 -0.164664 -0.213457
+0.20154 -0.112587 -0.146717
+
+0.203933 -0.164664 -0.213457
+0.228827 -0.127831 -0.200855
+0.241191 -0.194748 -0.25364
+
+0.270634 -0.151185 -0.241037
+0.241191 -0.194748 -0.25364
+0.228827 -0.127831 -0.200855
+
+0.241191 -0.194748 -0.25364
+0.270634 -0.151185 -0.241037
+0.286895 -0.231652 -0.275021
+
+0.321918 -0.179834 -0.262418
+0.286895 -0.231652 -0.275021
+0.270634 -0.151185 -0.241037
+
+0.286895 -0.231652 -0.275021
+0.321918 -0.179834 -0.262418
+0.335533 -0.270924 -0.275021
+
+0.376493 -0.210322 -0.262418
+0.335533 -0.270924 -0.275021
+0.321918 -0.179834 -0.262418
+
+0.335533 -0.270924 -0.275021
+0.376493 -0.210322 -0.262418
+0.381238 -0.307828 -0.25364
+
+0.427777 -0.238971 -0.241037
+0.381238 -0.307828 -0.25364
+0.376493 -0.210322 -0.262418
+
+0.381238 -0.307828 -0.25364
+0.427777 -0.238971 -0.241037
+0.418496 -0.337912 -0.213457
+
+0.469584 -0.262325 -0.200855
+0.418496 -0.337912 -0.213457
+0.427777 -0.238971 -0.241037
+
+0.418496 -0.337912 -0.213457
+0.469584 -0.262325 -0.200855
+0.442815 -0.357548 -0.159319
+
+0.496871 -0.277569 -0.146717
+0.442815 -0.357548 -0.159319
+0.469584 -0.262325 -0.200855
+
+0.442815 -0.357548 -0.159319
+0.496871 -0.277569 -0.146717
+0.451261 -0.364368 -0.0977555
+
+0.506348 -0.282863 -0.0851529
+0.451261 -0.364368 -0.0977555
+0.496871 -0.277569 -0.146717
+
+0.506348 -0.282863 -0.0851529
+0.546869 -0.193221 -0.062822
+0.496871 -0.277569 -0.0235893
+
+0.536634 -0.189605 -0.00125837
+0.496871 -0.277569 -0.0235893
+0.546869 -0.193221 -0.062822
+
+0.496871 -0.277569 -0.0235893
+0.536634 -0.189605 -0.00125837
+0.469584 -0.262325 0.0305489
+
+0.507162 -0.179192 0.0528798
+0.469584 -0.262325 0.0305489
+0.536634 -0.189605 -0.00125837
+
+0.469584 -0.262325 0.0305489
+0.507162 -0.179192 0.0528798
+0.427777 -0.238971 0.0707317
+
+0.46201 -0.163238 0.0930626
+0.427777 -0.238971 0.0707317
+0.507162 -0.179192 0.0528798
+
+0.427777 -0.238971 0.0707317
+0.46201 -0.163238 0.0930626
+0.376493 -0.210322 0.0921125
+
+0.406622 -0.143669 0.114443
+0.376493 -0.210322 0.0921125
+0.46201 -0.163238 0.0930626
+
+0.376493 -0.210322 0.0921125
+0.406622 -0.143669 0.114443
+0.321918 -0.179834 0.0921125
+
+0.34768 -0.122843 0.114443
+0.321918 -0.179834 0.0921125
+0.406622 -0.143669 0.114443
+
+0.321918 -0.179834 0.0921125
+0.34768 -0.122843 0.114443
+0.270634 -0.151185 0.0707317
+
+0.292292 -0.103273 0.0930626
+0.270634 -0.151185 0.0707317
+0.34768 -0.122843 0.114443
+
+0.270634 -0.151185 0.0707317
+0.292292 -0.103273 0.0930626
+0.228827 -0.127831 0.0305489
+
+0.247139 -0.0873199 0.0528798
+0.228827 -0.127831 0.0305489
+0.292292 -0.103273 0.0930626
+
+0.228827 -0.127831 0.0305489
+0.247139 -0.0873199 0.0528798
+0.20154 -0.112587 -0.0235893
+
+0.217668 -0.0769071 -0.00125837
+0.20154 -0.112587 -0.0235893
+0.247139 -0.0873199 0.0528798
+
+0.20154 -0.112587 -0.0235893
+0.217668 -0.0769071 -0.00125837
+0.192063 -0.107293 -0.0851529
+
+0.207433 -0.0732908 -0.062822
+0.192063 -0.107293 -0.0851529
+0.217668 -0.0769071 -0.00125837
+
+0.192063 -0.107293 -0.0851529
+0.207433 -0.0732908 -0.062822
+0.20154 -0.112587 -0.146717
+
+0.217668 -0.0769071 -0.124386
+0.20154 -0.112587 -0.146717
+0.207433 -0.0732908 -0.062822
+
+0.20154 -0.112587 -0.146717
+0.217668 -0.0769071 -0.124386
+0.228827 -0.127831 -0.200855
+
+0.247139 -0.0873199 -0.178524
+0.228827 -0.127831 -0.200855
+0.217668 -0.0769071 -0.124386
+
+0.228827 -0.127831 -0.200855
+0.247139 -0.0873199 -0.178524
+0.270634 -0.151185 -0.241037
+
+0.292292 -0.103273 -0.218707
+0.270634 -0.151185 -0.241037
+0.247139 -0.0873199 -0.178524
+
+0.270634 -0.151185 -0.241037
+0.292292 -0.103273 -0.218707
+0.321918 -0.179834 -0.262418
+
+0.34768 -0.122843 -0.240087
+0.321918 -0.179834 -0.262418
+0.292292 -0.103273 -0.218707
+
+0.321918 -0.179834 -0.262418
+0.34768 -0.122843 -0.240087
+0.376493 -0.210322 -0.262418
+
+0.406622 -0.143669 -0.240087
+0.376493 -0.210322 -0.262418
+0.34768 -0.122843 -0.240087
+
+0.376493 -0.210322 -0.262418
+0.406622 -0.143669 -0.240087
+0.427777 -0.238971 -0.241037
+
+0.46201 -0.163238 -0.218707
+0.427777 -0.238971 -0.241037
+0.406622 -0.143669 -0.240087
+
+0.427777 -0.238971 -0.241037
+0.46201 -0.163238 -0.218707
+0.469584 -0.262325 -0.200855
+
+0.507162 -0.179192 -0.178524
+0.469584 -0.262325 -0.200855
+0.46201 -0.163238 -0.218707
+
+0.469584 -0.262325 -0.200855
+0.507162 -0.179192 -0.178524
+0.496871 -0.277569 -0.146717
+
+0.536634 -0.189605 -0.124386
+0.496871 -0.277569 -0.146717
+0.507162 -0.179192 -0.178524
+
+0.496871 -0.277569 -0.146717
+0.536634 -0.189605 -0.124386
+0.506348 -0.282863 -0.0851529
+
+0.546869 -0.193221 -0.062822
+0.506348 -0.282863 -0.0851529
+0.536634 -0.189605 -0.124386
+
+0.546869 -0.193221 -0.062822
+0.571657 -0.0980205 -0.033314
+0.536634 -0.189605 -0.00125837
+
+0.560958 -0.0961859 0.0282496
+0.536634 -0.189605 -0.00125837
+0.571657 -0.0980205 -0.033314
+
+0.536634 -0.189605 -0.00125837
+0.560958 -0.0961859 0.0282496
+0.507162 -0.179192 0.0528798
+
+0.530151 -0.0909035 0.0823878
+0.507162 -0.179192 0.0528798
+0.560958 -0.0961859 0.0282496
+
+0.507162 -0.179192 0.0528798
+0.530151 -0.0909035 0.0823878
+0.46201 -0.163238 0.0930626
+
+0.482952 -0.0828104 0.122571
+0.46201 -0.163238 0.0930626
+0.530151 -0.0909035 0.0823878
+
+0.46201 -0.163238 0.0930626
+0.482952 -0.0828104 0.122571
+0.406622 -0.143669 0.114443
+
+0.425053 -0.0728827 0.143951
+0.406622 -0.143669 0.114443
+0.482952 -0.0828104 0.122571
+
+0.406622 -0.143669 0.114443
+0.425053 -0.0728827 0.143951
+0.34768 -0.122843 0.114443
+
+0.363439 -0.0623179 0.143951
+0.34768 -0.122843 0.114443
+0.425053 -0.0728827 0.143951
+
+0.34768 -0.122843 0.114443
+0.363439 -0.0623179 0.143951
+0.292292 -0.103273 0.0930626
+
+0.305541 -0.0523903 0.122571
+0.292292 -0.103273 0.0930626
+0.363439 -0.0623179 0.143951
+
+0.292292 -0.103273 0.0930626
+0.305541 -0.0523903 0.122571
+0.247139 -0.0873199 0.0528798
+
+0.258342 -0.0442971 0.0823878
+0.247139 -0.0873199 0.0528798
+0.305541 -0.0523903 0.122571
+
+0.247139 -0.0873199 0.0528798
+0.258342 -0.0442971 0.0823878
+0.217668 -0.0769071 -0.00125837
+
+0.227535 -0.0390147 0.0282496
+0.217668 -0.0769071 -0.00125837
+0.258342 -0.0442971 0.0823878
+
+0.217668 -0.0769071 -0.00125837
+0.227535 -0.0390147 0.0282496
+0.207433 -0.0732908 -0.062822
+
+0.216836 -0.0371802 -0.033314
+0.207433 -0.0732908 -0.062822
+0.227535 -0.0390147 0.0282496
+
+0.207433 -0.0732908 -0.062822
+0.216836 -0.0371802 -0.033314
+0.217668 -0.0769071 -0.124386
+
+0.227535 -0.0390147 -0.0948776
+0.217668 -0.0769071 -0.124386
+0.216836 -0.0371802 -0.033314
+
+0.217668 -0.0769071 -0.124386
+0.227535 -0.0390147 -0.0948776
+0.247139 -0.0873199 -0.178524
+
+0.258342 -0.0442971 -0.149016
+0.247139 -0.0873199 -0.178524
+0.227535 -0.0390147 -0.0948776
+
+0.247139 -0.0873199 -0.178524
+0.258342 -0.0442971 -0.149016
+0.292292 -0.103273 -0.218707
+
+0.305541 -0.0523903 -0.189199
+0.292292 -0.103273 -0.218707
+0.258342 -0.0442971 -0.149016
+
+0.292292 -0.103273 -0.218707
+0.305541 -0.0523903 -0.189199
+0.34768 -0.122843 -0.240087
+
+0.363439 -0.0623179 -0.210579
+0.34768 -0.122843 -0.240087
+0.305541 -0.0523903 -0.189199
+
+0.34768 -0.122843 -0.240087
+0.363439 -0.0623179 -0.210579
+0.406622 -0.143669 -0.240087
+
+0.425053 -0.0728827 -0.210579
+0.406622 -0.143669 -0.240087
+0.363439 -0.0623179 -0.210579
+
+0.406622 -0.143669 -0.240087
+0.425053 -0.0728827 -0.210579
+0.46201 -0.163238 -0.218707
+
+0.482952 -0.0828104 -0.189199
+0.46201 -0.163238 -0.218707
+0.425053 -0.0728827 -0.210579
+
+0.46201 -0.163238 -0.218707
+0.482952 -0.0828104 -0.189199
+0.507162 -0.179192 -0.178524
+
+0.530151 -0.0909035 -0.149016
+0.507162 -0.179192 -0.178524
+0.482952 -0.0828104 -0.189199
+
+0.507162 -0.179192 -0.178524
+0.530151 -0.0909035 -0.149016
+0.536634 -0.189605 -0.124386
+
+0.560958 -0.0961859 -0.0948776
+0.536634 -0.189605 -0.124386
+0.530151 -0.0909035 -0.149016
+
+0.536634 -0.189605 -0.124386
+0.560958 -0.0961859 -0.0948776
+0.546869 -0.193221 -0.062822
+
+0.571657 -0.0980205 -0.033314
+0.546869 -0.193221 -0.062822
+0.560958 -0.0961859 -0.0948776
+
+0.571657 -0.0980205 -0.033314
+0.58 0 0
+0.560958 -0.0961859 0.0282496
+
+0.569145 0 0.0615636
+0.560958 -0.0961859 0.0282496
+0.58 0 0
+
+0.560958 -0.0961859 0.0282496
+0.569145 0 0.0615636
+0.530151 -0.0909035 0.0823878
+
+0.537888 0 0.115702
+0.530151 -0.0909035 0.0823878
+0.569145 0 0.0615636
+
+0.530151 -0.0909035 0.0823878
+0.537888 0 0.115702
+0.482952 -0.0828104 0.122571
+
+0.49 0 0.155885
+0.482952 -0.0828104 0.122571
+0.537888 0 0.115702
+
+0.482952 -0.0828104 0.122571
+0.49 0 0.155885
+0.425053 -0.0728827 0.143951
+
+0.431257 0 0.177265
+0.425053 -0.0728827 0.143951
+0.49 0 0.155885
+
+0.425053 -0.0728827 0.143951
+0.431257 0 0.177265
+0.363439 -0.0623179 0.143951
+
+0.368743 0 0.177265
+0.363439 -0.0623179 0.143951
+0.431257 0 0.177265
+
+0.363439 -0.0623179 0.143951
+0.368743 0 0.177265
+0.305541 -0.0523903 0.122571
+
+0.31 0 0.155885
+0.305541 -0.0523903 0.122571
+0.368743 0 0.177265
+
+0.305541 -0.0523903 0.122571
+0.31 0 0.155885
+0.258342 -0.0442971 0.0823878
+
+0.262112 0 0.115702
+0.258342 -0.0442971 0.0823878
+0.31 0 0.155885
+
+0.258342 -0.0442971 0.0823878
+0.262112 0 0.115702
+0.227535 -0.0390147 0.0282496
+
+0.230855 0 0.0615636
+0.227535 -0.0390147 0.0282496
+0.262112 0 0.115702
+
+0.227535 -0.0390147 0.0282496
+0.230855 0 0.0615636
+0.216836 -0.0371802 -0.033314
+
+0.22 0 0
+0.216836 -0.0371802 -0.033314
+0.230855 0 0.0615636
+
+0.216836 -0.0371802 -0.033314
+0.22 0 0
+0.227535 -0.0390147 -0.0948776
+
+0.230855 0 -0.0615636
+0.227535 -0.0390147 -0.0948776
+0.22 0 0
+
+0.227535 -0.0390147 -0.0948776
+0.230855 0 -0.0615636
+0.258342 -0.0442971 -0.149016
+
+0.262112 0 -0.115702
+0.258342 -0.0442971 -0.149016
+0.230855 0 -0.0615636
+
+0.258342 -0.0442971 -0.149016
+0.262112 0 -0.115702
+0.305541 -0.0523903 -0.189199
+
+0.31 0 -0.155885
+0.305541 -0.0523903 -0.189199
+0.262112 0 -0.115702
+
+0.305541 -0.0523903 -0.189199
+0.31 0 -0.155885
+0.363439 -0.0623179 -0.210579
+
+0.368743 0 -0.177265
+0.363439 -0.0623179 -0.210579
+0.31 0 -0.155885
+
+0.363439 -0.0623179 -0.210579
+0.368743 0 -0.177265
+0.425053 -0.0728827 -0.210579
+
+0.431257 0 -0.177265
+0.425053 -0.0728827 -0.210579
+0.368743 0 -0.177265
+
+0.425053 -0.0728827 -0.210579
+0.431257 0 -0.177265
+0.482952 -0.0828104 -0.189199
+
+0.49 0 -0.155885
+0.482952 -0.0828104 -0.189199
+0.431257 0 -0.177265
+
+0.482952 -0.0828104 -0.189199
+0.49 0 -0.155885
+0.530151 -0.0909035 -0.149016
+
+0.537888 0 -0.115702
+0.530151 -0.0909035 -0.149016
+0.49 0 -0.155885
+
+0.530151 -0.0909035 -0.149016
+0.537888 0 -0.115702
+0.560958 -0.0961859 -0.0948776
+
+0.569145 0 -0.0615636
+0.560958 -0.0961859 -0.0948776
+0.537888 0 -0.115702
+
+0.560958 -0.0961859 -0.0948776
+0.569145 0 -0.0615636
+0.571657 -0.0980205 -0.033314
+
+0.58 0 0
+0.571657 -0.0980205 -0.033314
+0.569145 0 -0.0615636
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/include/BV.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/BV.h
new file mode 100644
index 00000000..cfe42c73
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/BV.h
@@ -0,0 +1,94 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_BV_H
+#define PQP_BV_H
+
+#include <math.h>
+#include "Tri.h"
+#include "PQP_Compile.h"
+
+struct BV
+{
+ PQP_REAL R[3][3]; // orientation of RSS & OBB
+
+#if PQP_BV_TYPE & RSS_TYPE
+ PQP_REAL Tr[3]; // position of rectangle
+ PQP_REAL l[2]; // side lengths of rectangle
+ PQP_REAL r; // radius of sphere summed with rectangle to form RSS
+#endif
+
+#if PQP_BV_TYPE & OBB_TYPE
+ PQP_REAL To[3]; // position of obb
+ PQP_REAL d[3]; // (half) dimensions of obb
+#endif
+
+ int first_child; // positive value is index of first_child bv
+ // negative value is -(index + 1) of triangle
+
+ BV();
+ ~BV();
+ int Leaf() { return first_child < 0; }
+ PQP_REAL GetSize();
+ void FitToTris(PQP_REAL O[3][3], Tri *tris, int num_tris);
+};
+
+inline
+PQP_REAL
+BV::GetSize()
+{
+#if PQP_BV_TYPE & RSS_TYPE
+ return (sqrt(l[0]*l[0] + l[1]*l[1]) + 2*r);
+#else
+ return (d[0]*d[0] + d[1]*d[1] + d[2]*d[2]);
+#endif
+}
+
+int
+BV_Overlap(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2);
+
+#if PQP_BV_TYPE & RSS_TYPE
+PQP_REAL
+BV_Distance(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2);
+#endif
+
+#endif
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP.h
new file mode 100644
index 00000000..f6f3e539
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP.h
@@ -0,0 +1,338 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_H
+#define PQP_H
+
+#include "PQP_Compile.h"
+#include "PQP_Internal.h"
+
+//----------------------------------------------------------------------------
+//
+// PQP API Return Values
+//
+//----------------------------------------------------------------------------
+
+const int PQP_OK = 0;
+ // Used by all API routines upon successful completion except
+ // constructors and destructors
+
+const int PQP_ERR_MODEL_OUT_OF_MEMORY = -1;
+ // Returned when an API function cannot obtain enough memory to
+ // store or process a PQP_Model object.
+
+const int PQP_ERR_OUT_OF_MEMORY = -2;
+ // Returned when a PQP query cannot allocate enough storage to
+ // compute or hold query information. In this case, the returned
+ // data should not be trusted.
+
+const int PQP_ERR_UNPROCESSED_MODEL = -3;
+ // Returned when an unprocessed model is passed to a function which
+ // expects only processed models, such as PQP_Collide() or
+ // PQP_Distance().
+
+const int PQP_ERR_BUILD_OUT_OF_SEQUENCE = -4;
+ // Returned when:
+ // 1. AddTri() is called before BeginModel().
+ // 2. BeginModel() is called immediately after AddTri().
+ // This error code is something like a warning: the invoked
+ // operation takes place anyway, and PQP does what makes "most
+ // sense", but the returned error code may tip off the client that
+ // something out of the ordinary is happenning.
+
+const int PQP_ERR_BUILD_EMPTY_MODEL = -5;
+ // Returned when EndModel() is called on a model to which no
+ // triangles have been added. This is similar in spirit to the
+ // OUT_OF_SEQUENCE return code, except that the requested operation
+ // has FAILED -- the model remains "unprocessed", and the client may
+ // NOT use it in queries.
+
+//----------------------------------------------------------------------------
+//
+// PQP_REAL
+//
+// The floating point type used throughout the package. The type is defined
+// in PQP_Compile.h, and by default is "double"
+//
+//----------------------------------------------------------------------------
+
+//----------------------------------------------------------------------------
+//
+// PQP_Model
+//
+// A PQP_Model stores geometry to be used in a proximity query.
+// The geometry is loaded with a call to BeginModel(), at least one call to
+// AddTri(), and then a call to EndModel().
+//
+// // create a two triangle model, m
+//
+// PQP_Model m;
+//
+// PQP_REAL p1[3],p2[3],p3[3]; // 3 points will make triangle p
+// PQP_REAL q1[3],q2[3],q3[3]; // another 3 points for triangle q
+//
+// // some initialization of these vertices not shown
+//
+// m.BeginModel(); // begin the model
+// m.AddTri(p1,p2,p3,0); // add triangle p
+// m.AddTri(q1,q2,q3,1); // add triangle q
+// m.EndModel(); // end (build) the model
+//
+// The last parameter of AddTri() is the number to be associated with the
+// triangle. These numbers are used to identify the triangles that overlap.
+//
+// AddTri() copies into the PQP_Model the data pointed to by the three vertex
+// pointers, so that it is safe to delete vertex data after you have
+// passed it to AddTri().
+//
+//----------------------------------------------------------------------------
+//
+// class PQP_Model - declaration contained in PQP_Internal.h
+// {
+//
+// public:
+// PQP_Model();
+// ~PQP_Model();
+//
+// int BeginModel(int num_tris = 8); // preallocate for num_tris triangles;
+// // the parameter is optional, since
+// // arrays are reallocated as needed
+//
+// int AddTri(const PQP_REAL *p1, const PQP_REAL *p2, const PQP_REAL *p3,
+// int id);
+//
+// int EndModel();
+// int MemUsage(int msg); // returns model mem usage in bytes
+// // prints message to stderr if msg == TRUE
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_CollideResult
+//
+// This saves and reports results from a collision query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_CollideResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // free the list of contact pairs; ordinarily this list is reused
+// // for each query, and only deleted in the destructor.
+//
+// void FreePairsList();
+//
+// // query results
+//
+// int Colliding();
+// int NumPairs();
+// int Id1(int k);
+// int Id2(int k);
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Collide() - detects collision between two PQP_Models
+//
+//
+// Declare a PQP_CollideResult struct and pass its pointer to collect
+// collision data.
+//
+// [R1, T1] is the placement of model 1 in the world &
+// [R2, T2] is the placement of model 2 in the world.
+// The columns of each 3x3 matrix are the basis vectors for the model
+// in world coordinates, and the matrices are in row-major order:
+// R(row r, col c) = R[r][c].
+//
+// If PQP_ALL_CONTACTS is the flag value, after calling PQP_Collide(),
+// the PQP_CollideResult object will contain an array with all
+// colliding triangle pairs. Suppose CR is a pointer to the
+// PQP_CollideResult object. The number of pairs is gotten from
+// CR->NumPairs(), and the ids of the 15'th pair of colliding
+// triangles is gotten from CR->Id1(14) and CR->Id2(14).
+//
+// If PQP_FIRST_CONTACT is the flag value, the PQP_CollideResult array
+// will only get the first colliding triangle pair found. Thus
+// CR->NumPairs() will be at most 1, and if 1, CR->Id1(0) and
+// CR->Id2(0) give the ids of the colliding triangle pair.
+//
+//----------------------------------------------------------------------------
+
+const int PQP_ALL_CONTACTS = 1; // find all pairwise intersecting triangles
+const int PQP_FIRST_CONTACT = 2; // report first intersecting tri pair found
+
+int
+PQP_Collide(PQP_CollideResult *result,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ int flag = PQP_ALL_CONTACTS);
+
+
+#if PQP_BV_TYPE & RSS_TYPE // this is true by default,
+ // and explained in PQP_Compile.h
+
+//----------------------------------------------------------------------------
+//
+// PQP_DistanceResult
+//
+// This saves and reports results from a distance query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_DistanceResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // The following distance and points established the minimum distance
+// // for the models, within the relative and absolute error bounds
+// // specified.
+//
+// PQP_REAL Distance();
+// const PQP_REAL *P1(); // pointers to three PQP_REALs
+// const PQP_REAL *P2();
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Distance() - computes the distance between two PQP_Models
+//
+//
+// Declare a PQP_DistanceResult struct and pass its pointer to collect
+// distance information.
+//
+// "rel_err" is the relative error margin from actual distance.
+// "abs_err" is the absolute error margin from actual distance. The
+// smaller of the two will be satisfied, so set one large to nullify
+// its effect.
+//
+// "qsize" is an optional parameter controlling the size of a priority
+// queue used to direct the search for closest points. A larger queue
+// can help the algorithm discover the minimum with fewer steps, but
+// will increase the cost of each step. It is not beneficial to increase
+// qsize if the application has frame-to-frame coherence, i.e., the
+// pair of models take small steps between each call, since another
+// speedup trick already accelerates this situation with no overhead.
+//
+// However, a queue size of 100 to 200 has been seen to save time in a
+// planning application with "non-coherent" placements of models.
+//
+//----------------------------------------------------------------------------
+
+int
+PQP_Distance(PQP_DistanceResult *result,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL rel_err, PQP_REAL abs_err,
+ int qsize = 2);
+
+//----------------------------------------------------------------------------
+//
+// PQP_ToleranceResult
+//
+// This saves and reports results from a tolerance query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_ToleranceResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // If the models are closer than ( <= ) tolerance, these points
+// // and distance were what established this. Otherwise,
+// // distance and point values are not meaningful.
+//
+// PQP_REAL Distance();
+// const PQP_REAL *P1();
+// const PQP_REAL *P2();
+//
+// // boolean says whether models are closer than tolerance distance
+//
+// int CloserThanTolerance();
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Tolerance() - checks if distance between PQP_Models is <= tolerance
+//
+//
+// Declare a PQP_ToleranceResult and pass its pointer to collect
+// tolerance information.
+//
+// The algorithm returns whether the true distance is <= or >
+// "tolerance". This routine does not simply compute true distance
+// and compare to the tolerance - models can often be shown closer or
+// farther than the tolerance more trivially. In most cases this
+// query should run faster than a distance query would on the same
+// models and configurations.
+//
+// "qsize" again controls the size of a priority queue used for
+// searching. Not setting qsize is the current recommendation, since
+// increasing it has only slowed down our applications.
+//
+//----------------------------------------------------------------------------
+
+int
+PQP_Tolerance(PQP_ToleranceResult *res,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL tolerance,
+ int qsize = 2);
+
+#endif
+#endif
+
+
+
+
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Compile.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Compile.h
new file mode 100644
index 00000000..f76c9813
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Compile.h
@@ -0,0 +1,101 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_COMPILE_H
+#define PQP_COMPILE_H
+
+// prevents compiler warnings when PQP_REAL is float
+
+#include <math.h>
+inline float sqrt(float x) { return (float)sqrt((double)x); }
+inline float cos(float x) { return (float)cos((double)x); }
+inline float sin(float x) { return (float)sin((double)x); }
+inline float fabs(float x) { return (float)fabs((double)x); }
+
+//-------------------------------------------------------------------------
+//
+// PQP_REAL
+//
+// This is the floating point type used throughout PQP. doubles are
+// recommended, both for their precision and because the software has
+// mainly been tested using them. However, floats appear to be faster
+// (by 60% on some machines).
+//
+//-------------------------------------------------------------------------
+
+typedef double PQP_REAL;
+
+//-------------------------------------------------------------------------
+//
+// PQP_BV_TYPE
+//
+// PQP introduces a bounding volume (BV) type known as the "rectangle
+// swept sphere" (RSS) - the volume created by sweeping a sphere so
+// that its center visits every point on a rectangle; it looks
+// something like a rounded box.
+//
+// In our experiments, the RSS type is comparable to the oriented
+// bounding box (OBB) in terms of the number of BV-pair and triangle-pair
+// tests incurred. However, with our present implementations, overlap
+// tests are cheaper for OBBs, while distance tests are cheaper for the
+// RSS type (we used a public gjk implementation for the OBB distance test).
+//
+// Consequently, PQP is configured to use the RSS type in distance and
+// tolerance queries (which use BV distance tests) and to use OBBs for
+// collision queries (which use BV overlap tests). Using both requires six
+// more PQP_REALs per BV node than using just one type.
+//
+// To save space, you can configure PQP to use only one type, however,
+// with RSS alone, collision queries will typically be slower. With OBB's
+// alone, distance and tolerance queries are currently not supported, since
+// we have not developed our own OBB distance test. The three options are:
+//
+// #define PQP_BV_TYPE RSS_TYPE
+// #define PQP_BV_TYPE OBB_TYPE
+// #define PQP_BV_TYPE RSS_TYPE | OBB_TYPE
+//
+//-------------------------------------------------------------------------
+
+#define RSS_TYPE 1
+#define OBB_TYPE 2
+
+#define PQP_BV_TYPE RSS_TYPE | OBB_TYPE
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Internal.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Internal.h
new file mode 100644
index 00000000..90cedcfa
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/PQP_Internal.h
@@ -0,0 +1,203 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include "Tri.h"
+#include "BV.h"
+
+class PQP_Model
+{
+
+public:
+
+ int build_state;
+
+ Tri *tris;
+ int num_tris;
+ int num_tris_alloced;
+
+ BV *b;
+ int num_bvs;
+ int num_bvs_alloced;
+
+ Tri *last_tri; // closest tri on this model in last distance test
+
+ BV *child(int n) { return &b[n]; }
+
+ PQP_Model();
+ ~PQP_Model();
+
+ int BeginModel(int num_tris = 8); // preallocate for num_tris triangles;
+ // the parameter is optional, since
+ // arrays are reallocated as needed
+ int AddTri(const PQP_REAL *p1, const PQP_REAL *p2, const PQP_REAL *p3,
+ int id);
+ int EndModel();
+ int MemUsage(int msg); // returns model mem usage.
+ // prints message to stderr if msg == TRUE
+};
+
+struct CollisionPair
+{
+ int id1;
+ int id2;
+};
+
+struct PQP_CollideResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ int num_pairs_alloced;
+ int num_pairs;
+ CollisionPair *pairs;
+
+ void SizeTo(int n);
+ void Add(int i1, int i2);
+
+ PQP_CollideResult();
+ ~PQP_CollideResult();
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // free the list of contact pairs; ordinarily this list is reused
+ // for each query, and only deleted in the destructor.
+
+ void FreePairsList();
+
+ // query results
+
+ int Colliding() { return (num_pairs > 0); }
+ int NumPairs() { return num_pairs; }
+ int Id1(int k) { return pairs[k].id1; }
+ int Id2(int k) { return pairs[k].id2; }
+};
+
+#if PQP_BV_TYPE & RSS_TYPE // distance/tolerance are only available with RSS
+
+struct PQP_DistanceResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ PQP_REAL rel_err;
+ PQP_REAL abs_err;
+
+ PQP_REAL distance;
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ int qsize;
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // The following distance and points established the minimum distance
+ // for the models, within the relative and absolute error bounds
+ // specified.
+ // Points are defined: PQP_REAL p1[3], p2[3];
+
+ PQP_REAL Distance() { return distance; }
+ const PQP_REAL *P1() { return p1; }
+ const PQP_REAL *P2() { return p2; }
+};
+
+struct PQP_ToleranceResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ int closer_than_tolerance;
+ PQP_REAL tolerance;
+
+ PQP_REAL distance;
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ int qsize;
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // If the models are closer than ( <= ) tolerance, these points
+ // and distance were what established this. Otherwise,
+ // distance and point values are not meaningful.
+
+ PQP_REAL Distance() { return distance; }
+ const PQP_REAL *P1() { return p1; }
+ const PQP_REAL *P2() { return p2; }
+
+ // boolean says whether models are closer than tolerance distance
+
+ int CloserThanTolerance() { return closer_than_tolerance; }
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/include/Tri.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/Tri.h
new file mode 100644
index 00000000..496cddd9
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/include/Tri.h
@@ -0,0 +1,54 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_TRI_H
+#define PQP_TRI_H
+
+#include "PQP_Compile.h"
+
+struct Tri
+{
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ PQP_REAL p3[3];
+ int id;
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.cpp
new file mode 100644
index 00000000..adbe2fc1
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.cpp
@@ -0,0 +1,323 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdlib.h>
+#include <math.h>
+#include "BV.h"
+#include "MatVec.h"
+#include "RectDist.h"
+#include "OBB_Disjoint.h"
+
+BV::BV()
+{
+ first_child = 0;
+}
+
+BV::~BV()
+{
+}
+
+static
+inline
+PQP_REAL
+MaxOfTwo(PQP_REAL a, PQP_REAL b)
+{
+ if (a > b) return a;
+ return b;
+}
+
+void
+BV::FitToTris(PQP_REAL O[3][3], Tri *tris, int num_tris)
+{
+ // store orientation
+
+ McM(R,O);
+
+ // project points of tris to R coordinates
+
+ int num_points = 3*num_tris;
+ PQP_REAL (*P)[3] = new PQP_REAL[num_points][3];
+ int point = 0;
+ int i;
+ for (i = 0; i < num_tris; i++)
+ {
+ MTxV(P[point],R,tris[i].p1);
+ point++;
+
+ MTxV(P[point],R,tris[i].p2);
+ point++;
+
+ MTxV(P[point],R,tris[i].p3);
+ point++;
+ }
+
+ PQP_REAL minx, maxx, miny, maxy, minz, maxz, c[3];
+
+#if PQP_BV_TYPE & OBB_TYPE
+ minx = maxx = P[0][0];
+ miny = maxy = P[0][1];
+ minz = maxz = P[0][2];
+ for (i = 1; i < num_points; i++)
+ {
+ if (P[i][0] < minx) minx = P[i][0];
+ else if (P[i][0] > maxx) maxx = P[i][0];
+ if (P[i][1] < miny) miny = P[i][1];
+ else if (P[i][1] > maxy) maxy = P[i][1];
+ if (P[i][2] < minz) minz = P[i][2];
+ else if (P[i][2] > maxz) maxz = P[i][2];
+ }
+ c[0] = (PQP_REAL)0.5*(maxx + minx);
+ c[1] = (PQP_REAL)0.5*(maxy + miny);
+ c[2] = (PQP_REAL)0.5*(maxz + minz);
+ MxV(To,R,c);
+
+ d[0] = (PQP_REAL)0.5*(maxx - minx);
+ d[1] = (PQP_REAL)0.5*(maxy - miny);
+ d[2] = (PQP_REAL)0.5*(maxz - minz);
+#endif
+
+#if PQP_BV_TYPE & RSS_TYPE
+
+ // compute thickness, which determines radius, and z of rectangle corner
+
+ PQP_REAL cz,radsqr;
+ minz = maxz = P[0][2];
+ for (i = 1; i < num_points; i++)
+ {
+ if (P[i][2] < minz) minz = P[i][2];
+ else if (P[i][2] > maxz) maxz = P[i][2];
+ }
+ r = (PQP_REAL)0.5*(maxz - minz);
+ radsqr = r*r;
+ cz = (PQP_REAL)0.5*(maxz + minz);
+
+ // compute an initial length of rectangle along x direction
+
+ // find minx and maxx as starting points
+
+ int minindex, maxindex;
+ minindex = maxindex = 0;
+ for (i = 1; i < num_points; i++)
+ {
+ if (P[i][0] < P[minindex][0]) minindex = i;
+ else if (P[i][0] > P[maxindex][0]) maxindex = i;
+ }
+ PQP_REAL x, dz;
+ dz = P[minindex][2] - cz;
+ minx = P[minindex][0] + sqrt(MaxOfTwo(radsqr - dz*dz,0));
+ dz = P[maxindex][2] - cz;
+ maxx = P[maxindex][0] - sqrt(MaxOfTwo(radsqr - dz*dz,0));
+
+ // grow minx
+
+ for (i = 0; i < num_points; i++)
+ {
+ if (P[i][0] < minx)
+ {
+ dz = P[i][2] - cz;
+ x = P[i][0] + sqrt(MaxOfTwo(radsqr - dz*dz,0));
+ if (x < minx) minx = x;
+ }
+ }
+
+ // grow maxx
+
+ for (i = 0; i < num_points; i++)
+ {
+ if (P[i][0] > maxx)
+ {
+ dz = P[i][2] - cz;
+ x = P[i][0] - sqrt(MaxOfTwo(radsqr - dz*dz,0));
+ if (x > maxx) maxx = x;
+ }
+ }
+
+ // compute an initial length of rectangle along y direction
+
+ // find miny and maxy as starting points
+
+ minindex = maxindex = 0;
+ for (i = 1; i < num_points; i++)
+ {
+ if (P[i][1] < P[minindex][1]) minindex = i;
+ else if (P[i][1] > P[maxindex][1]) maxindex = i;
+ }
+ PQP_REAL y;
+ dz = P[minindex][2] - cz;
+ miny = P[minindex][1] + sqrt(MaxOfTwo(radsqr - dz*dz,0));
+ dz = P[maxindex][2] - cz;
+ maxy = P[maxindex][1] - sqrt(MaxOfTwo(radsqr - dz*dz,0));
+
+ // grow miny
+
+ for (i = 0; i < num_points; i++)
+ {
+ if (P[i][1] < miny)
+ {
+ dz = P[i][2] - cz;
+ y = P[i][1] + sqrt(MaxOfTwo(radsqr - dz*dz,0));
+ if (y < miny) miny = y;
+ }
+ }
+
+ // grow maxy
+
+ for (i = 0; i < num_points; i++)
+ {
+ if (P[i][1] > maxy)
+ {
+ dz = P[i][2] - cz;
+ y = P[i][1] - sqrt(MaxOfTwo(radsqr - dz*dz,0));
+ if (y > maxy) maxy = y;
+ }
+ }
+
+ // corners may have some points which are not covered - grow lengths if
+ // necessary
+
+ PQP_REAL dx, dy, u, t;
+ PQP_REAL a = sqrt((PQP_REAL)0.5);
+ for (i = 0; i < num_points; i++)
+ {
+ if (P[i][0] > maxx)
+ {
+ if (P[i][1] > maxy)
+ {
+ dx = P[i][0] - maxx;
+ dy = P[i][1] - maxy;
+ u = dx*a + dy*a;
+ t = (a*u - dx)*(a*u - dx) +
+ (a*u - dy)*(a*u - dy) +
+ (cz - P[i][2])*(cz - P[i][2]);
+ u = u - sqrt(MaxOfTwo(radsqr - t,0));
+ if (u > 0)
+ {
+ maxx += u*a;
+ maxy += u*a;
+ }
+ }
+ else if (P[i][1] < miny)
+ {
+ dx = P[i][0] - maxx;
+ dy = P[i][1] - miny;
+ u = dx*a - dy*a;
+ t = (a*u - dx)*(a*u - dx) +
+ (-a*u - dy)*(-a*u - dy) +
+ (cz - P[i][2])*(cz - P[i][2]);
+ u = u - sqrt(MaxOfTwo(radsqr - t,0));
+ if (u > 0)
+ {
+ maxx += u*a;
+ miny -= u*a;
+ }
+ }
+ }
+ else if (P[i][0] < minx)
+ {
+ if (P[i][1] > maxy)
+ {
+ dx = P[i][0] - minx;
+ dy = P[i][1] - maxy;
+ u = dy*a - dx*a;
+ t = (-a*u - dx)*(-a*u - dx) +
+ (a*u - dy)*(a*u - dy) +
+ (cz - P[i][2])*(cz - P[i][2]);
+ u = u - sqrt(MaxOfTwo(radsqr - t,0));
+ if (u > 0)
+ {
+ minx -= u*a;
+ maxy += u*a;
+ }
+ }
+ else if (P[i][1] < miny)
+ {
+ dx = P[i][0] - minx;
+ dy = P[i][1] - miny;
+ u = -dx*a - dy*a;
+ t = (-a*u - dx)*(-a*u - dx) +
+ (-a*u - dy)*(-a*u - dy) +
+ (cz - P[i][2])*(cz - P[i][2]);
+ u = u - sqrt(MaxOfTwo(radsqr - t,0));
+ if (u > 0)
+ {
+ minx -= u*a;
+ miny -= u*a;
+ }
+ }
+ }
+ }
+
+ c[0] = minx;
+ c[1] = miny;
+ c[2] = cz;
+ MxV(Tr,R,c);
+
+ l[0] = maxx - minx;
+ if (l[0] < 0) l[0] = 0;
+ l[1] = maxy - miny;
+ if (l[1] < 0) l[1] = 0;
+#endif
+
+ delete [] P;
+}
+
+int
+BV_Overlap(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2)
+{
+#if PQP_BV_TYPE & OBB_TYPE
+ return (obb_disjoint(R,T,b1->d,b2->d) == 0);
+#else
+ PQP_REAL dist = RectDist(R,T,b1->l,b2->l);
+ if (dist <= (b1->r + b2->r)) return 1;
+ return 0;
+#endif
+}
+
+#if PQP_BV_TYPE & RSS_TYPE
+PQP_REAL
+BV_Distance(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2)
+{
+ PQP_REAL dist = RectDist(R,T,b1->l,b2->l);
+ dist -= (b1->r + b2->r);
+ return (dist < (PQP_REAL)0.0)? (PQP_REAL)0.0 : dist;
+}
+#endif
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.h
new file mode 100644
index 00000000..cfe42c73
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BV.h
@@ -0,0 +1,94 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_BV_H
+#define PQP_BV_H
+
+#include <math.h>
+#include "Tri.h"
+#include "PQP_Compile.h"
+
+struct BV
+{
+ PQP_REAL R[3][3]; // orientation of RSS & OBB
+
+#if PQP_BV_TYPE & RSS_TYPE
+ PQP_REAL Tr[3]; // position of rectangle
+ PQP_REAL l[2]; // side lengths of rectangle
+ PQP_REAL r; // radius of sphere summed with rectangle to form RSS
+#endif
+
+#if PQP_BV_TYPE & OBB_TYPE
+ PQP_REAL To[3]; // position of obb
+ PQP_REAL d[3]; // (half) dimensions of obb
+#endif
+
+ int first_child; // positive value is index of first_child bv
+ // negative value is -(index + 1) of triangle
+
+ BV();
+ ~BV();
+ int Leaf() { return first_child < 0; }
+ PQP_REAL GetSize();
+ void FitToTris(PQP_REAL O[3][3], Tri *tris, int num_tris);
+};
+
+inline
+PQP_REAL
+BV::GetSize()
+{
+#if PQP_BV_TYPE & RSS_TYPE
+ return (sqrt(l[0]*l[0] + l[1]*l[1]) + 2*r);
+#else
+ return (d[0]*d[0] + d[1]*d[1] + d[2]*d[2]);
+#endif
+}
+
+int
+BV_Overlap(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2);
+
+#if PQP_BV_TYPE & RSS_TYPE
+PQP_REAL
+BV_Distance(PQP_REAL R[3][3], PQP_REAL T[3], BV *b1, BV *b2);
+#endif
+
+#endif
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BVTQ.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BVTQ.h
new file mode 100644
index 00000000..94a6fc78
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/BVTQ.h
@@ -0,0 +1,214 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_BVTQ_H
+#define PQP_BVTQ_H
+
+#include <stdio.h>
+#include <stdlib.h>
+#include "PQP_Compile.h"
+
+inline
+int
+LChild(int p)
+{
+ return (2*p + 1);
+}
+
+inline
+int
+Parent(int c)
+{
+ return ((c - 1)/2);
+}
+
+struct BVT
+{
+ PQP_REAL d; // distance between the bvs
+ int b1, b2; // bv numbers - b1 is from model 1, b2 from model 2
+ PQP_REAL R[3][3]; // the relative rotation from b1 to b2
+ PQP_REAL T[3]; // the relative translation from b1 to b2
+ int pindex; // the index of the pointer that points to this -
+ // needed when filling the hole left by an ExtractMin
+};
+
+class BVTQ
+{
+ int size; // max number of bv tests
+ int numtests; // number of bv tests in queue
+ BVT *bvt; // an array of bv tests - seems faster than 'new' for each
+ BVT **bvtp; // the queue: an array of pointers to elts of bvt
+
+public:
+ BVTQ(int sz)
+ {
+ size = sz;
+ bvt = new BVT[size];
+ bvtp = new BVT*[size];
+ numtests = 0;
+ }
+ ~BVTQ() { delete [] bvt; delete [] bvtp; }
+ int Empty() { return (numtests == 0); }
+ int GetNumTests() { return numtests; }
+ int GetSize() { return size; }
+ PQP_REAL MinTest() { return bvtp[0]->d; }
+ BVT ExtractMinTest();
+ void AddTest(BVT &);
+};
+
+inline
+void
+BVTQ::AddTest(BVT &t)
+{
+ bvtp[numtests] = &bvt[numtests];
+
+ *bvtp[numtests] = t;
+ bvtp[numtests]->pindex = numtests;
+
+ BVT *temp;
+ int c = numtests;
+ int p;
+
+ while ((c != 0) && (bvtp[(p = Parent(c))]->d >= bvtp[c]->d))
+ {
+ // swap p and c pointers
+
+ temp = bvtp[p];
+ bvtp[p] = bvtp[c];
+ bvtp[c] = temp;
+
+ // the bv tests pointed to by p and c need new indices
+
+ bvtp[p]->pindex = p;
+ bvtp[c]->pindex = c;
+
+ c = p;
+ }
+ numtests++;
+}
+
+inline
+BVT
+BVTQ::ExtractMinTest()
+{
+ // store min test to be extracted
+
+ BVT min_test = *bvtp[0];
+
+ // copy last bvt to the empty space;
+ // reset the pointer to this moved bvt
+
+ *bvtp[0] = bvt[numtests-1];
+ bvtp[bvt[numtests-1].pindex] = bvtp[0];
+
+ // copy the last pointer to the first
+
+ bvtp[0] = bvtp[numtests-1];
+
+ numtests--;
+
+ BVT *temp;
+ int p = 0;
+ int c1,c2,c;
+
+ while(1)
+ {
+ c1 = LChild(p);
+ c2 = c1+1;
+
+ if (c1 < numtests)
+ {
+ if (c2 < numtests)
+ {
+ // p has both children, promote the minimum
+
+ if (bvtp[c1]->d < bvtp[c2]->d) c = c1; else c = c2;
+
+ if (bvtp[c]->d < bvtp[p]->d)
+ {
+ temp = bvtp[p];
+ bvtp[p] = bvtp[c];
+ bvtp[c] = temp;
+
+ bvtp[p]->pindex = p;
+ bvtp[c]->pindex = c;
+
+ p = c;
+ }
+ else
+ {
+ break;
+ }
+ }
+ else
+ {
+ // p has only left child
+
+ if (bvtp[c1]->d < bvtp[p]->d)
+ {
+ temp = bvtp[p];
+ bvtp[p] = bvtp[c1];
+ bvtp[c1] = temp;
+
+ bvtp[p]->pindex = p;
+ bvtp[c1]->pindex = c1;
+
+ p = c1;
+ }
+ else
+ {
+ break;
+ }
+ }
+ }
+ else
+ {
+ // p has no children
+
+ break;
+ }
+ }
+
+ return min_test;
+}
+
+#endif
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.cpp
new file mode 100644
index 00000000..4e37b16c
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.cpp
@@ -0,0 +1,551 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <string.h>
+#include "PQP.h"
+#include "MatVec.h"
+
+// If this is set, build routines will use covariance matrix
+// and mean finding code from RAPID 2.
+
+#define RAPID2_FIT 0
+
+#if RAPID2_FIT
+
+struct moment
+{
+ PQP_REAL A;
+ PQP_REAL m[3];
+ PQP_REAL s[3][3];
+};
+
+struct accum
+{
+ PQP_REAL A;
+ PQP_REAL m[3];
+ PQP_REAL s[3][3];
+};
+
+inline
+void
+clear_accum(accum &a)
+{
+ a.m[0] = a.m[1] = a.m[2] = 0.0;
+ a.s[0][0] = a.s[0][1] = a.s[0][2] = 0.0;
+ a.s[1][0] = a.s[1][1] = a.s[1][2] = 0.0;
+ a.s[2][0] = a.s[2][1] = a.s[2][2] = 0.0;
+ a.A = 0.0;
+}
+
+inline
+void
+accum_moment(accum &a, moment &b)
+{
+ a.m[0] += b.m[0] * b.A;
+ a.m[1] += b.m[1] * b.A;
+ a.m[2] += b.m[2] * b.A;
+
+ a.s[0][0] += b.s[0][0];
+ a.s[0][1] += b.s[0][1];
+ a.s[0][2] += b.s[0][2];
+ a.s[1][0] += b.s[1][0];
+ a.s[1][1] += b.s[1][1];
+ a.s[1][2] += b.s[1][2];
+ a.s[2][0] += b.s[2][0];
+ a.s[2][1] += b.s[2][1];
+ a.s[2][2] += b.s[2][2];
+
+ a.A += b.A;
+}
+
+inline
+void
+mean_from_moment(PQP_REAL M[3], moment &m)
+{
+ M[0] = m.m[0];
+ M[1] = m.m[1];
+ M[2] = m.m[2];
+}
+
+inline
+void
+mean_from_accum(PQP_REAL M[3], accum &a)
+{
+ M[0] = a.m[0] / a.A;
+ M[1] = a.m[1] / a.A;
+ M[2] = a.m[2] / a.A;
+}
+
+inline
+void
+covariance_from_accum(PQP_REAL C[3][3], accum &a)
+{
+ int i,j;
+ for(i=0; i<3; i++)
+ for(j=0; j<3; j++)
+ C[i][j] = a.s[i][j] - a.m[i]*a.m[j]/a.A;
+}
+
+inline
+void
+compute_moment(moment &M, PQP_REAL p[3], PQP_REAL q[3], PQP_REAL r[3])
+{
+ PQP_REAL u[3], v[3], w[3];
+
+ // compute the area of the triangle
+ VmV(u, q, p);
+ VmV(v, r, p);
+ VcrossV(w, u, v);
+ M.A = 0.5 * Vlength(w);
+
+ if (M.A == 0.0)
+ {
+ // This triangle has zero area. The second order components
+ // would be eliminated with the usual formula, so, for the
+ // sake of robustness we use an alternative form. These are the
+ // centroid and second-order components of the triangle's vertices.
+
+ // centroid
+ M.m[0] = (p[0] + q[0] + r[0]) /3;
+ M.m[1] = (p[1] + q[1] + r[1]) /3;
+ M.m[2] = (p[2] + q[2] + r[2]) /3;
+
+ // second-order components
+ M.s[0][0] = (p[0]*p[0] + q[0]*q[0] + r[0]*r[0]);
+ M.s[0][1] = (p[0]*p[1] + q[0]*q[1] + r[0]*r[1]);
+ M.s[0][2] = (p[0]*p[2] + q[0]*q[2] + r[0]*r[2]);
+ M.s[1][1] = (p[1]*p[1] + q[1]*q[1] + r[1]*r[1]);
+ M.s[1][2] = (p[1]*p[2] + q[1]*q[2] + r[1]*r[2]);
+ M.s[2][2] = (p[2]*p[2] + q[2]*q[2] + r[2]*r[2]);
+ M.s[2][1] = M.s[1][2];
+ M.s[1][0] = M.s[0][1];
+ M.s[2][0] = M.s[0][2];
+
+ return;
+ }
+
+ // get the centroid
+ M.m[0] = (p[0] + q[0] + r[0])/3;
+ M.m[1] = (p[1] + q[1] + r[1])/3;
+ M.m[2] = (p[2] + q[2] + r[2])/3;
+
+ // get the second order components -- note the weighting by the area
+ M.s[0][0] = M.A*(9*M.m[0]*M.m[0]+p[0]*p[0]+q[0]*q[0]+r[0]*r[0])/12;
+ M.s[0][1] = M.A*(9*M.m[0]*M.m[1]+p[0]*p[1]+q[0]*q[1]+r[0]*r[1])/12;
+ M.s[1][1] = M.A*(9*M.m[1]*M.m[1]+p[1]*p[1]+q[1]*q[1]+r[1]*r[1])/12;
+ M.s[0][2] = M.A*(9*M.m[0]*M.m[2]+p[0]*p[2]+q[0]*q[2]+r[0]*r[2])/12;
+ M.s[1][2] = M.A*(9*M.m[1]*M.m[2]+p[1]*p[2]+q[1]*q[2]+r[1]*r[2])/12;
+ M.s[2][2] = M.A*(9*M.m[2]*M.m[2]+p[2]*p[2]+q[2]*q[2]+r[2]*r[2])/12;
+ M.s[2][1] = M.s[1][2];
+ M.s[1][0] = M.s[0][1];
+ M.s[2][0] = M.s[0][2];
+}
+
+inline
+void
+compute_moments(moment *M, Tri *tris, int num_tris)
+{
+ int i;
+
+ // first collect all the moments, and obtain the area of the
+ // smallest nonzero area triangle.
+
+ PQP_REAL Amin = 0.0;
+ int zero = 0;
+ int nonzero = 0;
+ for(i=0; i<num_tris; i++)
+ {
+ compute_moment(M[i],
+ tris[i].p1,
+ tris[i].p2,
+ tris[i].p3);
+ if (M[i].A == 0.0)
+ {
+ zero = 1;
+ }
+ else
+ {
+ nonzero = 1;
+ if (Amin == 0.0) Amin = M[i].A;
+ else if (M[i].A < Amin) Amin = M[i].A;
+ }
+ }
+
+ if (zero)
+ {
+ fprintf(stderr, "----\n");
+ fprintf(stderr, "Warning! Some triangles have zero area!\n");
+ fprintf(stderr, "----\n");
+
+ // if there are any zero area triangles, go back and set their area
+
+ // if ALL the triangles have zero area, then set the area thingy
+ // to some arbitrary value.
+ if (Amin == 0.0) Amin = 1.0;
+
+ for(i=0; i<num_tris; i++)
+ {
+ if (M[i].A == 0.0) M[i].A = Amin;
+ }
+ }
+}
+
+#else
+
+PQP_REAL max(PQP_REAL a, PQP_REAL b, PQP_REAL c, PQP_REAL d)
+{
+ PQP_REAL t = a;
+ if (b > t) t = b;
+ if (c > t) t = c;
+ if (d > t) t = d;
+ return t;
+}
+
+PQP_REAL min(PQP_REAL a, PQP_REAL b, PQP_REAL c, PQP_REAL d)
+{
+ PQP_REAL t = a;
+ if (b < t) t = b;
+ if (c < t) t = c;
+ if (d < t) t = d;
+ return t;
+}
+
+void
+get_centroid_triverts(PQP_REAL c[3], Tri *tris, int num_tris)
+{
+ int i;
+
+ c[0] = c[1] = c[2] = 0.0;
+
+ // get center of mass
+ for(i=0; i<num_tris; i++)
+ {
+ PQP_REAL *p1 = tris[i].p1;
+ PQP_REAL *p2 = tris[i].p2;
+ PQP_REAL *p3 = tris[i].p3;
+
+ c[0] += p1[0] + p2[0] + p3[0];
+ c[1] += p1[1] + p2[1] + p3[1];
+ c[2] += p1[2] + p2[2] + p3[2];
+ }
+
+ PQP_REAL n = (PQP_REAL)(3 * num_tris);
+
+ c[0] /= n;
+ c[1] /= n;
+ c[2] /= n;
+}
+
+void
+get_covariance_triverts(PQP_REAL M[3][3], Tri *tris, int num_tris)
+{
+ int i;
+ PQP_REAL S1[3];
+ PQP_REAL S2[3][3];
+
+ S1[0] = S1[1] = S1[2] = 0.0;
+ S2[0][0] = S2[1][0] = S2[2][0] = 0.0;
+ S2[0][1] = S2[1][1] = S2[2][1] = 0.0;
+ S2[0][2] = S2[1][2] = S2[2][2] = 0.0;
+
+ // get center of mass
+ for(i=0; i<num_tris; i++)
+ {
+ PQP_REAL *p1 = tris[i].p1;
+ PQP_REAL *p2 = tris[i].p2;
+ PQP_REAL *p3 = tris[i].p3;
+
+ S1[0] += p1[0] + p2[0] + p3[0];
+ S1[1] += p1[1] + p2[1] + p3[1];
+ S1[2] += p1[2] + p2[2] + p3[2];
+
+ S2[0][0] += (p1[0] * p1[0] +
+ p2[0] * p2[0] +
+ p3[0] * p3[0]);
+ S2[1][1] += (p1[1] * p1[1] +
+ p2[1] * p2[1] +
+ p3[1] * p3[1]);
+ S2[2][2] += (p1[2] * p1[2] +
+ p2[2] * p2[2] +
+ p3[2] * p3[2]);
+ S2[0][1] += (p1[0] * p1[1] +
+ p2[0] * p2[1] +
+ p3[0] * p3[1]);
+ S2[0][2] += (p1[0] * p1[2] +
+ p2[0] * p2[2] +
+ p3[0] * p3[2]);
+ S2[1][2] += (p1[1] * p1[2] +
+ p2[1] * p2[2] +
+ p3[1] * p3[2]);
+ }
+
+ PQP_REAL n = (PQP_REAL)(3 * num_tris);
+
+ // now get covariances
+
+ M[0][0] = S2[0][0] - S1[0]*S1[0] / n;
+ M[1][1] = S2[1][1] - S1[1]*S1[1] / n;
+ M[2][2] = S2[2][2] - S1[2]*S1[2] / n;
+ M[0][1] = S2[0][1] - S1[0]*S1[1] / n;
+ M[1][2] = S2[1][2] - S1[1]*S1[2] / n;
+ M[0][2] = S2[0][2] - S1[0]*S1[2] / n;
+ M[1][0] = M[0][1];
+ M[2][0] = M[0][2];
+ M[2][1] = M[1][2];
+}
+
+#endif
+
+// given a list of triangles, a splitting axis, and a coordinate on
+// that axis, partition the triangles into two groups according to
+// where their centroids fall on the axis (under axial projection).
+// Returns the number of tris in the first half
+
+int
+split_tris(Tri *tris, int num_tris, PQP_REAL a[3], PQP_REAL c)
+{
+ int i;
+ int c1 = 0;
+ PQP_REAL p[3];
+ PQP_REAL x;
+ Tri temp;
+
+ for(i = 0; i < num_tris; i++)
+ {
+ // loop invariant: up to (but not including) index c1 in group 1,
+ // then up to (but not including) index i in group 2
+ //
+ // [1] [1] [1] [1] [2] [2] [2] [x] [x] ... [x]
+ // c1 i
+ //
+ VcV(p, tris[i].p1);
+ VpV(p, p, tris[i].p2);
+ VpV(p, p, tris[i].p3);
+ x = VdotV(p, a);
+ x /= 3.0;
+ if (x <= c)
+ {
+ // group 1
+ temp = tris[i];
+ tris[i] = tris[c1];
+ tris[c1] = temp;
+ c1++;
+ }
+ else
+ {
+ // group 2 -- do nothing
+ }
+ }
+
+ // split arbitrarily if one group empty
+
+ if ((c1 == 0) || (c1 == num_tris)) c1 = num_tris/2;
+
+ return c1;
+}
+
+// Fits m->child(bn) to the num_tris triangles starting at first_tri
+// Then, if num_tris is greater than one, partitions the tris into two
+// sets, and recursively builds two children of m->child(bn)
+
+int
+build_recurse(PQP_Model *m, int bn, int first_tri, int num_tris)
+{
+ BV *b = m->child(bn);
+
+ // compute a rotation matrix
+
+ PQP_REAL C[3][3], E[3][3], R[3][3], s[3], axis[3], mean[3], coord;
+
+#if RAPID2_FIT
+ moment *tri_moment = new moment[num_tris];
+ compute_moments(tri_moment, &(m->tris[first_tri]), num_tris);
+ accum acc;
+ clear_accum(acc);
+ for(int i = 0; i < num_tris; i++) accum_moment(acc, tri_moment[i]);
+ delete [] tri_moment;
+ covariance_from_accum(C,acc);
+#else
+ get_covariance_triverts(C,&m->tris[first_tri],num_tris);
+#endif
+
+ Meigen(E, s, C);
+
+ // place axes of E in order of increasing s
+
+ int min, mid, max;
+ if (s[0] > s[1]) { max = 0; min = 1; }
+ else { min = 0; max = 1; }
+ if (s[2] < s[min]) { mid = min; min = 2; }
+ else if (s[2] > s[max]) { mid = max; max = 2; }
+ else { mid = 2; }
+ McolcMcol(R,0,E,max);
+ McolcMcol(R,1,E,mid);
+ R[0][2] = E[1][max]*E[2][mid] - E[1][mid]*E[2][max];
+ R[1][2] = E[0][mid]*E[2][max] - E[0][max]*E[2][mid];
+ R[2][2] = E[0][max]*E[1][mid] - E[0][mid]*E[1][max];
+
+ // fit the BV
+
+ b->FitToTris(R, &m->tris[first_tri], num_tris);
+
+ if (num_tris == 1)
+ {
+ // BV is a leaf BV - first_child will index a triangle
+
+ b->first_child = -(first_tri + 1);
+ }
+ else if (num_tris > 1)
+ {
+ // BV not a leaf - first_child will index a BV
+
+ b->first_child = m->num_bvs;
+ m->num_bvs+=2;
+
+ // choose splitting axis and splitting coord
+
+ McolcV(axis,R,0);
+
+#if RAPID2_FIT
+ mean_from_accum(mean,acc);
+#else
+ get_centroid_triverts(mean,&m->tris[first_tri],num_tris);
+#endif
+ coord = VdotV(axis, mean);
+
+ // now split
+
+ int num_first_half = split_tris(&m->tris[first_tri], num_tris,
+ axis, coord);
+
+ // recursively build the children
+
+ build_recurse(m, m->child(bn)->first_child, first_tri, num_first_half);
+ build_recurse(m, m->child(bn)->first_child + 1,
+ first_tri + num_first_half, num_tris - num_first_half);
+ }
+ return PQP_OK;
+}
+
+// this descends the hierarchy, converting world-relative
+// transforms to parent-relative transforms
+
+void
+make_parent_relative(PQP_Model *m, int bn,
+ const PQP_REAL parentR[3][3]
+#if PQP_BV_TYPE & RSS_TYPE
+ ,const PQP_REAL parentTr[3]
+#endif
+#if PQP_BV_TYPE & OBB_TYPE
+ ,const PQP_REAL parentTo[3]
+#endif
+ )
+{
+ PQP_REAL Rpc[3][3], Tpc[3];
+
+ if (!m->child(bn)->Leaf())
+ {
+ // make children parent-relative
+
+ make_parent_relative(m,m->child(bn)->first_child,
+ m->child(bn)->R
+#if PQP_BV_TYPE & RSS_TYPE
+ ,m->child(bn)->Tr
+#endif
+#if PQP_BV_TYPE & OBB_TYPE
+ ,m->child(bn)->To
+#endif
+ );
+ make_parent_relative(m,m->child(bn)->first_child+1,
+ m->child(bn)->R
+#if PQP_BV_TYPE & RSS_TYPE
+ ,m->child(bn)->Tr
+#endif
+#if PQP_BV_TYPE & OBB_TYPE
+ ,m->child(bn)->To
+#endif
+ );
+ }
+
+ // make self parent relative
+
+ MTxM(Rpc,parentR,m->child(bn)->R);
+ McM(m->child(bn)->R,Rpc);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Tpc,m->child(bn)->Tr,parentTr);
+ MTxV(m->child(bn)->Tr,parentR,Tpc);
+#endif
+#if PQP_BV_TYPE & OBB_TYPE
+ VmV(Tpc,m->child(bn)->To,parentTo);
+ MTxV(m->child(bn)->To,parentR,Tpc);
+#endif
+
+}
+
+int
+build_model(PQP_Model *m)
+{
+ // set num_bvs to 1, the first index for a child bv
+
+ m->num_bvs = 1;
+
+ // build recursively
+
+ build_recurse(m, 0, 0, m->num_tris);
+
+ // change BV orientations from world-relative to parent-relative
+
+ PQP_REAL R[3][3],T[3];
+ Midentity(R);
+ Videntity(T);
+
+ make_parent_relative(m,0,R
+#if PQP_BV_TYPE & RSS_TYPE
+ ,T
+#endif
+#if PQP_BV_TYPE & OBB_TYPE
+ ,T
+#endif
+ );
+
+ return PQP_OK;
+}
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.h
new file mode 100644
index 00000000..bab05dd2
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Build.h
@@ -0,0 +1,49 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_BUILD_H
+#define PQP_BUILD_H
+
+#include "PQP.h"
+
+int
+build_model(PQP_Model *m);
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/GetTime.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/GetTime.h
new file mode 100644
index 00000000..5529a08f
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/GetTime.h
@@ -0,0 +1,71 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_GETTIME_H
+#define PQP_GETTIME_H
+
+#ifdef WIN32
+
+ #include <time.h>
+ #include <sys/timeb.h>
+ inline
+ double
+ GetTime()
+ {
+ struct _timeb thistime;
+ _ftime(&thistime);
+ return (thistime.time + thistime.millitm * 1e-3);
+ }
+
+#else
+
+ #include <sys/time.h>
+ inline
+ double
+ GetTime()
+ {
+ struct timeval thistime;
+ gettimeofday(&thistime, 0);
+ return (thistime.tv_sec + thistime.tv_usec * 1e-6);
+ }
+
+#endif
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/MatVec.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/MatVec.h
new file mode 100644
index 00000000..c0198ad7
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/MatVec.h
@@ -0,0 +1,877 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_MATVEC_H
+#define PQP_MATVEC_H
+
+#include <math.h>
+#include <stdio.h>
+#include "PQP_Compile.h"
+
+#ifndef M_PI
+const PQP_REAL M_PI = (PQP_REAL)3.14159265359;
+#endif
+
+#ifdef gnu
+#include "zzzz.h"
+
+#ifdef hppa
+#define myfabs(x) \
+ ({double __value, __arg = (x); \
+ asm("fabs,dbl %1, %0": "=f" (__value): "f" (__arg)); \
+ __value; \
+});
+#endif
+
+#ifdef mips
+#define myfabs(x) \
+ ({double __value, __arg = (x); \
+ asm("abs.d %0, %1": "=f" (__value): "f" (__arg)); \
+ __value; \
+});
+#endif
+
+#else
+
+#define myfabs(x) ((x < 0) ? -x : x)
+
+#endif
+
+
+inline
+void
+Mprintg(const PQP_REAL M[3][3])
+{
+ printf("%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+
+inline
+void
+Mfprint(FILE *f, const PQP_REAL M[3][3])
+{
+ fprintf(f, "%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+inline
+void
+Mprint(const PQP_REAL M[3][3])
+{
+ printf("%g %g %g\n%g %g %g\n%g %g %g\n",
+ M[0][0], M[0][1], M[0][2],
+ M[1][0], M[1][1], M[1][2],
+ M[2][0], M[2][1], M[2][2]);
+}
+
+inline
+void
+Vprintg(const PQP_REAL V[3])
+{
+ printf("%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Vfprint(FILE *f, const PQP_REAL V[3])
+{
+ fprintf(f, "%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Vprint(const PQP_REAL V[3])
+{
+ printf("%g %g %g\n", V[0], V[1], V[2]);
+}
+
+inline
+void
+Midentity(PQP_REAL M[3][3])
+{
+ M[0][0] = M[1][1] = M[2][2] = 1.0;
+ M[0][1] = M[1][2] = M[2][0] = 0.0;
+ M[0][2] = M[1][0] = M[2][1] = 0.0;
+}
+
+inline
+void
+Videntity(PQP_REAL T[3])
+{
+ T[0] = T[1] = T[2] = 0.0;
+}
+
+inline
+void
+McM(PQP_REAL Mr[3][3], const PQP_REAL M[3][3])
+{
+ Mr[0][0] = M[0][0]; Mr[0][1] = M[0][1]; Mr[0][2] = M[0][2];
+ Mr[1][0] = M[1][0]; Mr[1][1] = M[1][1]; Mr[1][2] = M[1][2];
+ Mr[2][0] = M[2][0]; Mr[2][1] = M[2][1]; Mr[2][2] = M[2][2];
+}
+
+inline
+void
+MTcM(PQP_REAL Mr[3][3], const PQP_REAL M[3][3])
+{
+ Mr[0][0] = M[0][0]; Mr[1][0] = M[0][1]; Mr[2][0] = M[0][2];
+ Mr[0][1] = M[1][0]; Mr[1][1] = M[1][1]; Mr[2][1] = M[1][2];
+ Mr[0][2] = M[2][0]; Mr[1][2] = M[2][1]; Mr[2][2] = M[2][2];
+}
+
+inline
+void
+VcV(PQP_REAL Vr[3], const PQP_REAL V[3])
+{
+ Vr[0] = V[0]; Vr[1] = V[1]; Vr[2] = V[2];
+}
+
+inline
+void
+McolcV(PQP_REAL Vr[3], const PQP_REAL M[3][3], int c)
+{
+ Vr[0] = M[0][c];
+ Vr[1] = M[1][c];
+ Vr[2] = M[2][c];
+}
+
+inline
+void
+McolcMcol(PQP_REAL Mr[3][3], int cr, const PQP_REAL M[3][3], int c)
+{
+ Mr[0][cr] = M[0][c];
+ Mr[1][cr] = M[1][c];
+ Mr[2][cr] = M[2][c];
+}
+
+inline
+void
+MxMpV(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3], const PQP_REAL T[3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[1][0] +
+ M1[0][2] * M2[2][0] +
+ T[0]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[1][2] * M2[2][0] +
+ T[1]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[1][0] +
+ M1[2][2] * M2[2][0] +
+ T[2]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[2][1] +
+ T[0]);
+ Mr[1][1] = (M1[1][0] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[2][1] +
+ T[1]);
+ Mr[2][1] = (M1[2][0] * M2[0][1] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[2][1] +
+ T[2]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[0][1] * M2[1][2] +
+ M1[0][2] * M2[2][2] +
+ T[0]);
+ Mr[1][2] = (M1[1][0] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[1][2] * M2[2][2] +
+ T[1]);
+ Mr[2][2] = (M1[2][0] * M2[0][2] +
+ M1[2][1] * M2[1][2] +
+ M1[2][2] * M2[2][2] +
+ T[2]);
+}
+
+inline
+void
+MxM(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[1][0] +
+ M1[0][2] * M2[2][0]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[1][2] * M2[2][0]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[1][0] +
+ M1[2][2] * M2[2][0]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[2][1]);
+ Mr[1][1] = (M1[1][0] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[2][1]);
+ Mr[2][1] = (M1[2][0] * M2[0][1] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[2][1]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[0][1] * M2[1][2] +
+ M1[0][2] * M2[2][2]);
+ Mr[1][2] = (M1[1][0] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[1][2] * M2[2][2]);
+ Mr[2][2] = (M1[2][0] * M2[0][2] +
+ M1[2][1] * M2[1][2] +
+ M1[2][2] * M2[2][2]);
+}
+
+
+inline
+void
+MxMT(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[0][1] * M2[0][1] +
+ M1[0][2] * M2[0][2]);
+ Mr[1][0] = (M1[1][0] * M2[0][0] +
+ M1[1][1] * M2[0][1] +
+ M1[1][2] * M2[0][2]);
+ Mr[2][0] = (M1[2][0] * M2[0][0] +
+ M1[2][1] * M2[0][1] +
+ M1[2][2] * M2[0][2]);
+ Mr[0][1] = (M1[0][0] * M2[1][0] +
+ M1[0][1] * M2[1][1] +
+ M1[0][2] * M2[1][2]);
+ Mr[1][1] = (M1[1][0] * M2[1][0] +
+ M1[1][1] * M2[1][1] +
+ M1[1][2] * M2[1][2]);
+ Mr[2][1] = (M1[2][0] * M2[1][0] +
+ M1[2][1] * M2[1][1] +
+ M1[2][2] * M2[1][2]);
+ Mr[0][2] = (M1[0][0] * M2[2][0] +
+ M1[0][1] * M2[2][1] +
+ M1[0][2] * M2[2][2]);
+ Mr[1][2] = (M1[1][0] * M2[2][0] +
+ M1[1][1] * M2[2][1] +
+ M1[1][2] * M2[2][2]);
+ Mr[2][2] = (M1[2][0] * M2[2][0] +
+ M1[2][1] * M2[2][1] +
+ M1[2][2] * M2[2][2]);
+}
+
+inline
+void
+MTxM(PQP_REAL Mr[3][3], const PQP_REAL M1[3][3], const PQP_REAL M2[3][3])
+{
+ Mr[0][0] = (M1[0][0] * M2[0][0] +
+ M1[1][0] * M2[1][0] +
+ M1[2][0] * M2[2][0]);
+ Mr[1][0] = (M1[0][1] * M2[0][0] +
+ M1[1][1] * M2[1][0] +
+ M1[2][1] * M2[2][0]);
+ Mr[2][0] = (M1[0][2] * M2[0][0] +
+ M1[1][2] * M2[1][0] +
+ M1[2][2] * M2[2][0]);
+ Mr[0][1] = (M1[0][0] * M2[0][1] +
+ M1[1][0] * M2[1][1] +
+ M1[2][0] * M2[2][1]);
+ Mr[1][1] = (M1[0][1] * M2[0][1] +
+ M1[1][1] * M2[1][1] +
+ M1[2][1] * M2[2][1]);
+ Mr[2][1] = (M1[0][2] * M2[0][1] +
+ M1[1][2] * M2[1][1] +
+ M1[2][2] * M2[2][1]);
+ Mr[0][2] = (M1[0][0] * M2[0][2] +
+ M1[1][0] * M2[1][2] +
+ M1[2][0] * M2[2][2]);
+ Mr[1][2] = (M1[0][1] * M2[0][2] +
+ M1[1][1] * M2[1][2] +
+ M1[2][1] * M2[2][2]);
+ Mr[2][2] = (M1[0][2] * M2[0][2] +
+ M1[1][2] * M2[1][2] +
+ M1[2][2] * M2[2][2]);
+}
+
+inline
+void
+MxV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]);
+ Vr[1] = (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]);
+ Vr[2] = (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+
+inline
+void
+MxVpV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2] +
+ V2[0]);
+ Vr[1] = (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2] +
+ V2[1]);
+ Vr[2] = (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2] +
+ V2[2]);
+}
+
+
+inline
+void
+sMxVpV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = s1 * (M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]) +
+ V2[0];
+ Vr[1] = s1 * (M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]) +
+ V2[1];
+ Vr[2] = s1 * (M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]) +
+ V2[2];
+}
+
+inline
+void
+MTxV(PQP_REAL Vr[3], const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = (M1[0][0] * V1[0] +
+ M1[1][0] * V1[1] +
+ M1[2][0] * V1[2]);
+ Vr[1] = (M1[0][1] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[2][1] * V1[2]);
+ Vr[2] = (M1[0][2] * V1[0] +
+ M1[1][2] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+inline
+void
+sMTxV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = s1*(M1[0][0] * V1[0] +
+ M1[1][0] * V1[1] +
+ M1[2][0] * V1[2]);
+ Vr[1] = s1*(M1[0][1] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[2][1] * V1[2]);
+ Vr[2] = s1*(M1[0][2] * V1[0] +
+ M1[1][2] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+inline
+void
+sMxV(PQP_REAL Vr[3], PQP_REAL s1, const PQP_REAL M1[3][3], const PQP_REAL V1[3])
+{
+ Vr[0] = s1*(M1[0][0] * V1[0] +
+ M1[0][1] * V1[1] +
+ M1[0][2] * V1[2]);
+ Vr[1] = s1*(M1[1][0] * V1[0] +
+ M1[1][1] * V1[1] +
+ M1[1][2] * V1[2]);
+ Vr[2] = s1*(M1[2][0] * V1[0] +
+ M1[2][1] * V1[1] +
+ M1[2][2] * V1[2]);
+}
+
+
+inline
+void
+VmV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[0] - V2[0];
+ Vr[1] = V1[1] - V2[1];
+ Vr[2] = V1[2] - V2[2];
+}
+
+inline
+void
+VpV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[0] + V2[0];
+ Vr[1] = V1[1] + V2[1];
+ Vr[2] = V1[2] + V2[2];
+}
+
+inline
+void
+VpVxS(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3], PQP_REAL s)
+{
+ Vr[0] = V1[0] + V2[0] * s;
+ Vr[1] = V1[1] + V2[1] * s;
+ Vr[2] = V1[2] + V2[2] * s;
+}
+
+inline
+void
+MskewV(PQP_REAL M[3][3], const PQP_REAL v[3])
+{
+ M[0][0] = M[1][1] = M[2][2] = 0.0;
+ M[1][0] = v[2];
+ M[0][1] = -v[2];
+ M[0][2] = v[1];
+ M[2][0] = -v[1];
+ M[1][2] = -v[0];
+ M[2][1] = v[0];
+}
+
+
+inline
+void
+VcrossV(PQP_REAL Vr[3], const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ Vr[0] = V1[1]*V2[2] - V1[2]*V2[1];
+ Vr[1] = V1[2]*V2[0] - V1[0]*V2[2];
+ Vr[2] = V1[0]*V2[1] - V1[1]*V2[0];
+}
+
+inline
+PQP_REAL
+Vlength(PQP_REAL V[3])
+{
+ return sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+}
+
+inline
+void
+Vnormalize(PQP_REAL V[3])
+{
+ PQP_REAL d = (PQP_REAL)1.0 / sqrt(V[0]*V[0] + V[1]*V[1] + V[2]*V[2]);
+ V[0] *= d;
+ V[1] *= d;
+ V[2] *= d;
+}
+
+inline
+PQP_REAL
+VdotV(const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ return (V1[0]*V2[0] + V1[1]*V2[1] + V1[2]*V2[2]);
+}
+
+inline
+PQP_REAL
+VdistV2(const PQP_REAL V1[3], const PQP_REAL V2[3])
+{
+ return ( (V1[0]-V2[0]) * (V1[0]-V2[0]) +
+ (V1[1]-V2[1]) * (V1[1]-V2[1]) +
+ (V1[2]-V2[2]) * (V1[2]-V2[2]));
+}
+
+inline
+void
+VxS(PQP_REAL Vr[3], const PQP_REAL V[3], PQP_REAL s)
+{
+ Vr[0] = V[0] * s;
+ Vr[1] = V[1] * s;
+ Vr[2] = V[2] * s;
+}
+
+inline
+void
+MRotZ(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[0][0] = cos(t);
+ Mr[1][0] = sin(t);
+ Mr[0][1] = -Mr[1][0];
+ Mr[1][1] = Mr[0][0];
+ Mr[2][0] = Mr[2][1] = 0.0;
+ Mr[0][2] = Mr[1][2] = 0.0;
+ Mr[2][2] = 1.0;
+}
+
+inline
+void
+MRotX(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[1][1] = cos(t);
+ Mr[2][1] = sin(t);
+ Mr[1][2] = -Mr[2][1];
+ Mr[2][2] = Mr[1][1];
+ Mr[0][1] = Mr[0][2] = 0.0;
+ Mr[1][0] = Mr[2][0] = 0.0;
+ Mr[0][0] = 1.0;
+}
+
+inline
+void
+MRotY(PQP_REAL Mr[3][3], PQP_REAL t)
+{
+ Mr[2][2] = cos(t);
+ Mr[0][2] = sin(t);
+ Mr[2][0] = -Mr[0][2];
+ Mr[0][0] = Mr[2][2];
+ Mr[1][2] = Mr[1][0] = 0.0;
+ Mr[2][1] = Mr[0][1] = 0.0;
+ Mr[1][1] = 1.0;
+}
+
+inline
+void
+MVtoOGL(double oglm[16], const PQP_REAL R[3][3], const PQP_REAL T[3])
+{
+ oglm[0] = (double)R[0][0];
+ oglm[1] = (double)R[1][0];
+ oglm[2] = (double)R[2][0];
+ oglm[3] = 0.0;
+ oglm[4] = (double)R[0][1];
+ oglm[5] = (double)R[1][1];
+ oglm[6] = (double)R[2][1];
+ oglm[7] = 0.0;
+ oglm[8] = (double)R[0][2];
+ oglm[9] = (double)R[1][2];
+ oglm[10] = (double)R[2][2];
+ oglm[11] = 0.0;
+ oglm[12] = (double)T[0];
+ oglm[13] = (double)T[1];
+ oglm[14] = (double)T[2];
+ oglm[15] = 1.0;
+}
+
+inline
+void
+OGLtoMV(PQP_REAL R[3][3], PQP_REAL T[3], const double oglm[16])
+{
+ R[0][0] = (PQP_REAL)oglm[0];
+ R[1][0] = (PQP_REAL)oglm[1];
+ R[2][0] = (PQP_REAL)oglm[2];
+
+ R[0][1] = (PQP_REAL)oglm[4];
+ R[1][1] = (PQP_REAL)oglm[5];
+ R[2][1] = (PQP_REAL)oglm[6];
+
+ R[0][2] = (PQP_REAL)oglm[8];
+ R[1][2] = (PQP_REAL)oglm[9];
+ R[2][2] = (PQP_REAL)oglm[10];
+
+ T[0] = (PQP_REAL)oglm[12];
+ T[1] = (PQP_REAL)oglm[13];
+ T[2] = (PQP_REAL)oglm[14];
+}
+
+// taken from quatlib, written by Richard Holloway
+const int QX = 0;
+const int QY = 1;
+const int QZ = 2;
+const int QW = 3;
+
+inline
+void
+MRotQ(PQP_REAL destMatrix[3][3], PQP_REAL srcQuat[4])
+{
+ PQP_REAL s;
+ PQP_REAL xs, ys, zs,
+ wx, wy, wz,
+ xx, xy, xz,
+ yy, yz, zz;
+
+ /*
+ * For unit srcQuat, just set s = 2.0; or set xs = srcQuat[QX] +
+ * srcQuat[QX], etc.
+ */
+
+ s = (PQP_REAL)2.0 / (srcQuat[QX]*srcQuat[QX] + srcQuat[QY]*srcQuat[QY] +
+ srcQuat[QZ]*srcQuat[QZ] + srcQuat[QW]*srcQuat[QW]);
+
+ xs = srcQuat[QX] * s; ys = srcQuat[QY] * s; zs = srcQuat[QZ] * s;
+ wx = srcQuat[QW] * xs; wy = srcQuat[QW] * ys; wz = srcQuat[QW] * zs;
+ xx = srcQuat[QX] * xs; xy = srcQuat[QX] * ys; xz = srcQuat[QX] * zs;
+ yy = srcQuat[QY] * ys; yz = srcQuat[QY] * zs; zz = srcQuat[QZ] * zs;
+
+ destMatrix[QX][QX] = (PQP_REAL)1.0 - (yy + zz);
+ destMatrix[QX][QY] = xy + wz;
+ destMatrix[QX][QZ] = xz - wy;
+
+ destMatrix[QY][QX] = xy - wz;
+ destMatrix[QY][QY] = (PQP_REAL)1.0 - (xx + zz);
+ destMatrix[QY][QZ] = yz + wx;
+
+ destMatrix[QZ][QX] = xz + wy;
+ destMatrix[QZ][QY] = yz - wx;
+ destMatrix[QZ][QZ] = (PQP_REAL)1.0 - (xx + yy);
+}
+
+inline
+void
+Mqinverse(PQP_REAL Mr[3][3], PQP_REAL m[3][3])
+{
+ int i,j;
+
+ for(i=0; i<3; i++)
+ for(j=0; j<3; j++)
+ {
+ int i1 = (i+1)%3;
+ int i2 = (i+2)%3;
+ int j1 = (j+1)%3;
+ int j2 = (j+2)%3;
+ Mr[i][j] = (m[j1][i1]*m[j2][i2] - m[j1][i2]*m[j2][i1]);
+ }
+}
+
+// Meigen from Numerical Recipes in C
+
+#if 0
+
+#define rfabs(x) ((x < 0) ? -x : x)
+
+#define ROT(a,i,j,k,l) g=a[i][j]; h=a[k][l]; a[i][j]=g-s*(h+g*tau); a[k][l]=h+s*(g-h*tau);
+
+int
+inline
+Meigen(PQP_REAL vout[3][3], PQP_REAL dout[3], PQP_REAL a[3][3])
+{
+ int i;
+ PQP_REAL tresh,theta,tau,t,sm,s,h,g,c;
+ int nrot;
+ PQP_REAL b[3];
+ PQP_REAL z[3];
+ PQP_REAL v[3][3];
+ PQP_REAL d[3];
+
+ v[0][0] = v[1][1] = v[2][2] = 1.0;
+ v[0][1] = v[1][2] = v[2][0] = 0.0;
+ v[0][2] = v[1][0] = v[2][1] = 0.0;
+
+ b[0] = a[0][0]; d[0] = a[0][0]; z[0] = 0.0;
+ b[1] = a[1][1]; d[1] = a[1][1]; z[1] = 0.0;
+ b[2] = a[2][2]; d[2] = a[2][2]; z[2] = 0.0;
+
+ nrot = 0;
+
+
+ for(i=0; i<50; i++)
+ {
+
+ printf("2\n");
+
+ sm=0.0; sm+=fabs(a[0][1]); sm+=fabs(a[0][2]); sm+=fabs(a[1][2]);
+ if (sm == 0.0) { McM(vout,v); VcV(dout,d); return i; }
+
+ if (i < 3) tresh=0.2*sm/(3*3); else tresh=0.0;
+
+ {
+ g = 100.0*rfabs(a[0][1]);
+ if (i>3 && rfabs(d[0])+g==rfabs(d[0]) && rfabs(d[1])+g==rfabs(d[1]))
+ a[0][1]=0.0;
+ else if (rfabs(a[0][1])>tresh)
+ {
+ h = d[1]-d[0];
+ if (rfabs(h)+g == rfabs(h)) t=(a[0][1])/h;
+ else
+ {
+ theta=0.5*h/(a[0][1]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[0][1];
+ z[0] -= h; z[1] += h; d[0] -= h; d[1] += h;
+ a[0][1]=0.0;
+ ROT(a,0,2,1,2); ROT(v,0,0,0,1); ROT(v,1,0,1,1); ROT(v,2,0,2,1);
+ nrot++;
+ }
+ }
+
+ {
+ g = 100.0*rfabs(a[0][2]);
+ if (i>3 && rfabs(d[0])+g==rfabs(d[0]) && rfabs(d[2])+g==rfabs(d[2]))
+ a[0][2]=0.0;
+ else if (rfabs(a[0][2])>tresh)
+ {
+ h = d[2]-d[0];
+ if (rfabs(h)+g == rfabs(h)) t=(a[0][2])/h;
+ else
+ {
+ theta=0.5*h/(a[0][2]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[0][2];
+ z[0] -= h; z[2] += h; d[0] -= h; d[2] += h;
+ a[0][2]=0.0;
+ ROT(a,0,1,1,2); ROT(v,0,0,0,2); ROT(v,1,0,1,2); ROT(v,2,0,2,2);
+ nrot++;
+ }
+ }
+
+
+ {
+ g = 100.0*rfabs(a[1][2]);
+ if (i>3 && rfabs(d[1])+g==rfabs(d[1]) && rfabs(d[2])+g==rfabs(d[2]))
+ a[1][2]=0.0;
+ else if (rfabs(a[1][2])>tresh)
+ {
+ h = d[2]-d[1];
+ if (rfabs(h)+g == rfabs(h)) t=(a[1][2])/h;
+ else
+ {
+ theta=0.5*h/(a[1][2]);
+ t=1.0/(rfabs(theta)+sqrt(1.0+theta*theta));
+ if (theta < 0.0) t = -t;
+ }
+ c=1.0/sqrt(1+t*t); s=t*c; tau=s/(1.0+c); h=t*a[1][2];
+ z[1] -= h; z[2] += h; d[1] -= h; d[2] += h;
+ a[1][2]=0.0;
+ ROT(a,0,1,0,2); ROT(v,0,1,0,2); ROT(v,1,1,1,2); ROT(v,2,1,2,2);
+ nrot++;
+ }
+ }
+
+ b[0] += z[0]; d[0] = b[0]; z[0] = 0.0;
+ b[1] += z[1]; d[1] = b[1]; z[1] = 0.0;
+ b[2] += z[2]; d[2] = b[2]; z[2] = 0.0;
+
+ }
+
+ fprintf(stderr, "eigen: too many iterations in Jacobi transform (%d).\n", i);
+
+ return i;
+}
+
+#else
+
+
+
+#define ROTATE(a,i,j,k,l) g=a[i][j]; h=a[k][l]; a[i][j]=g-s*(h+g*tau); a[k][l]=h+s*(g-h*tau);
+
+void
+inline
+Meigen(PQP_REAL vout[3][3], PQP_REAL dout[3], PQP_REAL a[3][3])
+{
+ int n = 3;
+ int j,iq,ip,i;
+ PQP_REAL tresh,theta,tau,t,sm,s,h,g,c;
+ int nrot;
+ PQP_REAL b[3];
+ PQP_REAL z[3];
+ PQP_REAL v[3][3];
+ PQP_REAL d[3];
+
+ Midentity(v);
+ for(ip=0; ip<n; ip++)
+ {
+ b[ip] = a[ip][ip];
+ d[ip] = a[ip][ip];
+ z[ip] = 0.0;
+ }
+
+ nrot = 0;
+
+ for(i=0; i<50; i++)
+ {
+
+ sm=0.0;
+ for(ip=0;ip<n;ip++) for(iq=ip+1;iq<n;iq++) sm+=fabs(a[ip][iq]);
+ if (sm == 0.0)
+ {
+ McM(vout, v);
+ VcV(dout, d);
+ return;
+ }
+
+
+ if (i < 3) tresh=(PQP_REAL)0.2*sm/(n*n);
+ else tresh=0.0;
+
+ for(ip=0; ip<n; ip++) for(iq=ip+1; iq<n; iq++)
+ {
+ g = (PQP_REAL)100.0*fabs(a[ip][iq]);
+ if (i>3 &&
+ fabs(d[ip])+g==fabs(d[ip]) &&
+ fabs(d[iq])+g==fabs(d[iq]))
+ a[ip][iq]=0.0;
+ else if (fabs(a[ip][iq])>tresh)
+ {
+ h = d[iq]-d[ip];
+ if (fabs(h)+g == fabs(h)) t=(a[ip][iq])/h;
+ else
+ {
+ theta=(PQP_REAL)0.5*h/(a[ip][iq]);
+ t=(PQP_REAL)(1.0/(fabs(theta)+sqrt(1.0+theta*theta)));
+ if (theta < 0.0) t = -t;
+ }
+ c=(PQP_REAL)1.0/sqrt(1+t*t);
+ s=t*c;
+ tau=s/((PQP_REAL)1.0+c);
+ h=t*a[ip][iq];
+ z[ip] -= h;
+ z[iq] += h;
+ d[ip] -= h;
+ d[iq] += h;
+ a[ip][iq]=0.0;
+ for(j=0;j<ip;j++) { ROTATE(a,j,ip,j,iq); }
+ for(j=ip+1;j<iq;j++) { ROTATE(a,ip,j,j,iq); }
+ for(j=iq+1;j<n;j++) { ROTATE(a,ip,j,iq,j); }
+ for(j=0;j<n;j++) { ROTATE(v,j,ip,j,iq); }
+ nrot++;
+ }
+ }
+ for(ip=0;ip<n;ip++)
+ {
+ b[ip] += z[ip];
+ d[ip] = b[ip];
+ z[ip] = 0.0;
+ }
+ }
+
+ fprintf(stderr, "eigen: too many iterations in Jacobi transform.\n");
+
+ return;
+}
+
+
+#endif
+
+#endif
+// MATVEC_H
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/OBB_Disjoint.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/OBB_Disjoint.h
new file mode 100644
index 00000000..4a732031
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/OBB_Disjoint.h
@@ -0,0 +1,216 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_OBB_DISJOINT
+#define PQP_OBB_DISJOINT
+
+#include "MatVec.h"
+#include "PQP_Compile.h"
+
+// int
+// obb_disjoint(PQP_REAL B[3][3], PQP_REAL T[3], PQP_REAL a[3], PQP_REAL b[3]);
+//
+// This is a test between two boxes, box A and box B. It is assumed that
+// the coordinate system is aligned and centered on box A. The 3x3
+// matrix B specifies box B's orientation with respect to box A.
+// Specifically, the columns of B are the basis vectors (axis vectors) of
+// box B. The center of box B is located at the vector T. The
+// dimensions of box B are given in the array b. The orientation and
+// placement of box A, in this coordinate system, are the identity matrix
+// and zero vector, respectively, so they need not be specified. The
+// dimensions of box A are given in array a.
+
+inline
+int
+obb_disjoint(PQP_REAL B[3][3], PQP_REAL T[3], PQP_REAL a[3], PQP_REAL b[3])
+{
+ register PQP_REAL t, s;
+ register int r;
+ PQP_REAL Bf[3][3];
+ const PQP_REAL reps = (PQP_REAL)1e-6;
+
+ // Bf = fabs(B)
+ Bf[0][0] = myfabs(B[0][0]); Bf[0][0] += reps;
+ Bf[0][1] = myfabs(B[0][1]); Bf[0][1] += reps;
+ Bf[0][2] = myfabs(B[0][2]); Bf[0][2] += reps;
+ Bf[1][0] = myfabs(B[1][0]); Bf[1][0] += reps;
+ Bf[1][1] = myfabs(B[1][1]); Bf[1][1] += reps;
+ Bf[1][2] = myfabs(B[1][2]); Bf[1][2] += reps;
+ Bf[2][0] = myfabs(B[2][0]); Bf[2][0] += reps;
+ Bf[2][1] = myfabs(B[2][1]); Bf[2][1] += reps;
+ Bf[2][2] = myfabs(B[2][2]); Bf[2][2] += reps;
+
+ // if any of these tests are one-sided, then the polyhedra are disjoint
+ r = 1;
+
+ // A1 x A2 = A0
+ t = myfabs(T[0]);
+
+ r &= (t <=
+ (a[0] + b[0] * Bf[0][0] + b[1] * Bf[0][1] + b[2] * Bf[0][2]));
+ if (!r) return 1;
+
+ // B1 x B2 = B0
+ s = T[0]*B[0][0] + T[1]*B[1][0] + T[2]*B[2][0];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (b[0] + a[0] * Bf[0][0] + a[1] * Bf[1][0] + a[2] * Bf[2][0]));
+ if (!r) return 2;
+
+ // A2 x A0 = A1
+ t = myfabs(T[1]);
+
+ r &= ( t <=
+ (a[1] + b[0] * Bf[1][0] + b[1] * Bf[1][1] + b[2] * Bf[1][2]));
+ if (!r) return 3;
+
+ // A0 x A1 = A2
+ t = myfabs(T[2]);
+
+ r &= ( t <=
+ (a[2] + b[0] * Bf[2][0] + b[1] * Bf[2][1] + b[2] * Bf[2][2]));
+ if (!r) return 4;
+
+ // B2 x B0 = B1
+ s = T[0]*B[0][1] + T[1]*B[1][1] + T[2]*B[2][1];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (b[1] + a[0] * Bf[0][1] + a[1] * Bf[1][1] + a[2] * Bf[2][1]));
+ if (!r) return 5;
+
+ // B0 x B1 = B2
+ s = T[0]*B[0][2] + T[1]*B[1][2] + T[2]*B[2][2];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (b[2] + a[0] * Bf[0][2] + a[1] * Bf[1][2] + a[2] * Bf[2][2]));
+ if (!r) return 6;
+
+ // A0 x B0
+ s = T[2] * B[1][0] - T[1] * B[2][0];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[1] * Bf[2][0] + a[2] * Bf[1][0] +
+ b[1] * Bf[0][2] + b[2] * Bf[0][1]));
+ if (!r) return 7;
+
+ // A0 x B1
+ s = T[2] * B[1][1] - T[1] * B[2][1];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[1] * Bf[2][1] + a[2] * Bf[1][1] +
+ b[0] * Bf[0][2] + b[2] * Bf[0][0]));
+ if (!r) return 8;
+
+ // A0 x B2
+ s = T[2] * B[1][2] - T[1] * B[2][2];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[1] * Bf[2][2] + a[2] * Bf[1][2] +
+ b[0] * Bf[0][1] + b[1] * Bf[0][0]));
+ if (!r) return 9;
+
+ // A1 x B0
+ s = T[0] * B[2][0] - T[2] * B[0][0];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[0] * Bf[2][0] + a[2] * Bf[0][0] +
+ b[1] * Bf[1][2] + b[2] * Bf[1][1]));
+ if (!r) return 10;
+
+ // A1 x B1
+ s = T[0] * B[2][1] - T[2] * B[0][1];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[0] * Bf[2][1] + a[2] * Bf[0][1] +
+ b[0] * Bf[1][2] + b[2] * Bf[1][0]));
+ if (!r) return 11;
+
+ // A1 x B2
+ s = T[0] * B[2][2] - T[2] * B[0][2];
+ t = myfabs(s);
+
+ r &= (t <=
+ (a[0] * Bf[2][2] + a[2] * Bf[0][2] +
+ b[0] * Bf[1][1] + b[1] * Bf[1][0]));
+ if (!r) return 12;
+
+ // A2 x B0
+ s = T[1] * B[0][0] - T[0] * B[1][0];
+ t = myfabs(s);
+
+ r &= (t <=
+ (a[0] * Bf[1][0] + a[1] * Bf[0][0] +
+ b[1] * Bf[2][2] + b[2] * Bf[2][1]));
+ if (!r) return 13;
+
+ // A2 x B1
+ s = T[1] * B[0][1] - T[0] * B[1][1];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[0] * Bf[1][1] + a[1] * Bf[0][1] +
+ b[0] * Bf[2][2] + b[2] * Bf[2][0]));
+ if (!r) return 14;
+
+ // A2 x B2
+ s = T[1] * B[0][2] - T[0] * B[1][2];
+ t = myfabs(s);
+
+ r &= ( t <=
+ (a[0] * Bf[1][2] + a[1] * Bf[0][2] +
+ b[0] * Bf[2][1] + b[1] * Bf[2][0]));
+ if (!r) return 15;
+
+ return 0; // should equal 0
+}
+
+#endif
+
+
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.cpp
new file mode 100644
index 00000000..c1857503
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.cpp
@@ -0,0 +1,1376 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include <stdio.h>
+#include <string.h>
+#include "PQP.h"
+#include "BVTQ.h"
+#include "Build.h"
+#include "MatVec.h"
+#include "GetTime.h"
+#include "TriDist.h"
+
+enum BUILD_STATE
+{
+ PQP_BUILD_STATE_EMPTY, // empty state, immediately after constructor
+ PQP_BUILD_STATE_BEGUN, // after BeginModel(), state for adding triangles
+ PQP_BUILD_STATE_PROCESSED // after tree has been built, ready to use
+};
+
+PQP_Model::PQP_Model()
+{
+ // no bounding volume tree yet
+
+ b = 0;
+ num_bvs_alloced = 0;
+ num_bvs = 0;
+
+ // no tri list yet
+
+ tris = 0;
+ num_tris = 0;
+ num_tris_alloced = 0;
+
+ last_tri = 0;
+
+ build_state = PQP_BUILD_STATE_EMPTY;
+}
+
+PQP_Model::~PQP_Model()
+{
+ if (b != NULL)
+ delete [] b;
+ if (tris != NULL)
+ delete [] tris;
+}
+
+int
+PQP_Model::BeginModel(int n)
+{
+ // reset to initial state if necessary
+
+ if (build_state != PQP_BUILD_STATE_EMPTY)
+ {
+ delete [] b;
+ delete [] tris;
+
+ num_tris = num_bvs = num_tris_alloced = num_bvs_alloced = 0;
+ }
+
+ // prepare model for addition of triangles
+
+ if (n <= 0) n = 8;
+ num_tris_alloced = n;
+ tris = new Tri[n];
+ if (!tris)
+ {
+ fprintf(stderr, "PQP Error! Out of memory for tri array on "
+ "BeginModel() call!\n");
+ return PQP_ERR_MODEL_OUT_OF_MEMORY;
+ }
+
+ // give a warning if called out of sequence
+
+ if (build_state != PQP_BUILD_STATE_EMPTY)
+ {
+ fprintf(stderr,
+ "PQP Warning! Called BeginModel() on a PQP_Model that \n"
+ "was not empty. This model was cleared and previous\n"
+ "triangle additions were lost.\n");
+ build_state = PQP_BUILD_STATE_BEGUN;
+ return PQP_ERR_BUILD_OUT_OF_SEQUENCE;
+ }
+
+ build_state = PQP_BUILD_STATE_BEGUN;
+ return PQP_OK;
+}
+
+int
+PQP_Model::AddTri(const PQP_REAL *p1,
+ const PQP_REAL *p2,
+ const PQP_REAL *p3,
+ int id)
+{
+ if (build_state == PQP_BUILD_STATE_EMPTY)
+ {
+ BeginModel();
+ }
+ else if (build_state == PQP_BUILD_STATE_PROCESSED)
+ {
+ fprintf(stderr,"PQP Warning! Called AddTri() on PQP_Model \n"
+ "object that was already ended. AddTri() was\n"
+ "ignored. Must do a BeginModel() to clear the\n"
+ "model for addition of new triangles\n");
+ return PQP_ERR_BUILD_OUT_OF_SEQUENCE;
+ }
+
+ // allocate for new triangles
+
+ if (num_tris >= num_tris_alloced)
+ {
+ Tri *temp;
+ temp = new Tri[num_tris_alloced*2];
+ if (!temp)
+ {
+ fprintf(stderr, "PQP Error! Out of memory for tri array on"
+ " AddTri() call!\n");
+ return PQP_ERR_MODEL_OUT_OF_MEMORY;
+ }
+ memcpy(temp, tris, sizeof(Tri)*num_tris);
+ delete [] tris;
+ tris = temp;
+ num_tris_alloced = num_tris_alloced*2;
+ }
+
+ // initialize the new triangle
+
+ tris[num_tris].p1[0] = p1[0];
+ tris[num_tris].p1[1] = p1[1];
+ tris[num_tris].p1[2] = p1[2];
+
+ tris[num_tris].p2[0] = p2[0];
+ tris[num_tris].p2[1] = p2[1];
+ tris[num_tris].p2[2] = p2[2];
+
+ tris[num_tris].p3[0] = p3[0];
+ tris[num_tris].p3[1] = p3[1];
+ tris[num_tris].p3[2] = p3[2];
+
+ tris[num_tris].id = id;
+
+ num_tris += 1;
+
+ return PQP_OK;
+}
+
+int
+PQP_Model::EndModel()
+{
+ if (build_state == PQP_BUILD_STATE_PROCESSED)
+ {
+ fprintf(stderr,"PQP Warning! Called EndModel() on PQP_Model \n"
+ "object that was already ended. EndModel() was\n"
+ "ignored. Must do a BeginModel() to clear the\n"
+ "model for addition of new triangles\n");
+ return PQP_ERR_BUILD_OUT_OF_SEQUENCE;
+ }
+
+ // report error is no tris
+
+ if (num_tris == 0)
+ {
+ fprintf(stderr,"PQP Error! EndModel() called on model with"
+ " no triangles\n");
+ return PQP_ERR_BUILD_EMPTY_MODEL;
+ }
+
+ // shrink fit tris array
+
+ if (num_tris_alloced > num_tris)
+ {
+ Tri *new_tris = new Tri[num_tris];
+ if (!new_tris)
+ {
+ fprintf(stderr, "PQP Error! Out of memory for tri array "
+ "in EndModel() call!\n");
+ return PQP_ERR_MODEL_OUT_OF_MEMORY;
+ }
+ memcpy(new_tris, tris, sizeof(Tri)*num_tris);
+ delete [] tris;
+ tris = new_tris;
+ num_tris_alloced = num_tris;
+ }
+
+ // create an array of BVs for the model
+
+ b = new BV[2*num_tris - 1];
+ if (!b)
+ {
+ fprintf(stderr,"PQP Error! out of memory for BV array "
+ "in EndModel()\n");
+ return PQP_ERR_MODEL_OUT_OF_MEMORY;
+ }
+ num_bvs_alloced = 2*num_tris - 1;
+ num_bvs = 0;
+
+ // we should build the model now.
+
+ build_model(this);
+ build_state = PQP_BUILD_STATE_PROCESSED;
+
+ last_tri = tris;
+
+ return PQP_OK;
+}
+
+int
+PQP_Model::MemUsage(int msg)
+{
+ int mem_bv_list = sizeof(BV)*num_bvs;
+ int mem_tri_list = sizeof(Tri)*num_tris;
+
+ int total_mem = mem_bv_list + mem_tri_list + sizeof(PQP_Model);
+
+ if (msg)
+ {
+ fprintf(stderr,"Total for model %x: %d bytes\n", this, total_mem);
+ fprintf(stderr,"BVs: %d alloced, take %d bytes each\n",
+ num_bvs, sizeof(BV));
+ fprintf(stderr,"Tris: %d alloced, take %d bytes each\n",
+ num_tris, sizeof(Tri));
+ }
+
+ return total_mem;
+}
+
+// COLLIDE STUFF
+//
+//--------------------------------------------------------------------------
+
+PQP_CollideResult::PQP_CollideResult()
+{
+ pairs = 0;
+ num_pairs = num_pairs_alloced = 0;
+ num_bv_tests = 0;
+ num_tri_tests = 0;
+}
+
+PQP_CollideResult::~PQP_CollideResult()
+{
+ delete [] pairs;
+}
+
+void
+PQP_CollideResult::FreePairsList()
+{
+ num_pairs = num_pairs_alloced = 0;
+ delete [] pairs;
+ pairs = 0;
+}
+
+// may increase OR reduce mem usage
+void
+PQP_CollideResult::SizeTo(int n)
+{
+ CollisionPair *temp;
+
+ if (n < num_pairs)
+ {
+ fprintf(stderr, "PQP Error: Internal error in "
+ "'PQP_CollideResult::SizeTo(int n)'\n");
+ fprintf(stderr, " n = %d, but num_pairs = %d\n", n, num_pairs);
+ return;
+ }
+
+ temp = new CollisionPair[n];
+ memcpy(temp, pairs, num_pairs*sizeof(CollisionPair));
+ delete [] pairs;
+ pairs = temp;
+ num_pairs_alloced = n;
+ return;
+}
+
+void
+PQP_CollideResult::Add(int a, int b)
+{
+ if (num_pairs >= num_pairs_alloced)
+ {
+ // allocate more
+
+ SizeTo(num_pairs_alloced*2+8);
+ }
+
+ // now proceed as usual
+
+ pairs[num_pairs].id1 = a;
+ pairs[num_pairs].id2 = b;
+ num_pairs++;
+}
+
+// TRIANGLE OVERLAP TEST
+
+inline
+PQP_REAL
+max(PQP_REAL a, PQP_REAL b, PQP_REAL c)
+{
+ PQP_REAL t = a;
+ if (b > t) t = b;
+ if (c > t) t = c;
+ return t;
+}
+
+inline
+PQP_REAL
+min(PQP_REAL a, PQP_REAL b, PQP_REAL c)
+{
+ PQP_REAL t = a;
+ if (b < t) t = b;
+ if (c < t) t = c;
+ return t;
+}
+
+int
+project6(PQP_REAL *ax,
+ PQP_REAL *p1, PQP_REAL *p2, PQP_REAL *p3,
+ PQP_REAL *q1, PQP_REAL *q2, PQP_REAL *q3)
+{
+ PQP_REAL P1 = VdotV(ax, p1);
+ PQP_REAL P2 = VdotV(ax, p2);
+ PQP_REAL P3 = VdotV(ax, p3);
+ PQP_REAL Q1 = VdotV(ax, q1);
+ PQP_REAL Q2 = VdotV(ax, q2);
+ PQP_REAL Q3 = VdotV(ax, q3);
+
+ PQP_REAL mx1 = max(P1, P2, P3);
+ PQP_REAL mn1 = min(P1, P2, P3);
+ PQP_REAL mx2 = max(Q1, Q2, Q3);
+ PQP_REAL mn2 = min(Q1, Q2, Q3);
+
+ if (mn1 > mx2) return 0;
+ if (mn2 > mx1) return 0;
+ return 1;
+}
+
+// very robust triangle intersection test
+// uses no divisions
+// works on coplanar triangles
+int
+TriContact(PQP_REAL *P1, PQP_REAL *P2, PQP_REAL *P3,
+ PQP_REAL *Q1, PQP_REAL *Q2, PQP_REAL *Q3)
+{
+
+ // One triangle is (p1,p2,p3). Other is (q1,q2,q3).
+ // Edges are (e1,e2,e3) and (f1,f2,f3).
+ // Normals are n1 and m1
+ // Outwards are (g1,g2,g3) and (h1,h2,h3).
+ //
+ // We assume that the triangle vertices are in the same coordinate system.
+ //
+ // First thing we do is establish a new c.s. so that p1 is at (0,0,0).
+
+ PQP_REAL p1[3], p2[3], p3[3];
+ PQP_REAL q1[3], q2[3], q3[3];
+ PQP_REAL e1[3], e2[3], e3[3];
+ PQP_REAL f1[3], f2[3], f3[3];
+ PQP_REAL g1[3], g2[3], g3[3];
+ PQP_REAL h1[3], h2[3], h3[3];
+ PQP_REAL n1[3], m1[3];
+
+ PQP_REAL ef11[3], ef12[3], ef13[3];
+ PQP_REAL ef21[3], ef22[3], ef23[3];
+ PQP_REAL ef31[3], ef32[3], ef33[3];
+
+ p1[0] = P1[0] - P1[0]; p1[1] = P1[1] - P1[1]; p1[2] = P1[2] - P1[2];
+ p2[0] = P2[0] - P1[0]; p2[1] = P2[1] - P1[1]; p2[2] = P2[2] - P1[2];
+ p3[0] = P3[0] - P1[0]; p3[1] = P3[1] - P1[1]; p3[2] = P3[2] - P1[2];
+
+ q1[0] = Q1[0] - P1[0]; q1[1] = Q1[1] - P1[1]; q1[2] = Q1[2] - P1[2];
+ q2[0] = Q2[0] - P1[0]; q2[1] = Q2[1] - P1[1]; q2[2] = Q2[2] - P1[2];
+ q3[0] = Q3[0] - P1[0]; q3[1] = Q3[1] - P1[1]; q3[2] = Q3[2] - P1[2];
+
+ e1[0] = p2[0] - p1[0]; e1[1] = p2[1] - p1[1]; e1[2] = p2[2] - p1[2];
+ e2[0] = p3[0] - p2[0]; e2[1] = p3[1] - p2[1]; e2[2] = p3[2] - p2[2];
+ e3[0] = p1[0] - p3[0]; e3[1] = p1[1] - p3[1]; e3[2] = p1[2] - p3[2];
+
+ f1[0] = q2[0] - q1[0]; f1[1] = q2[1] - q1[1]; f1[2] = q2[2] - q1[2];
+ f2[0] = q3[0] - q2[0]; f2[1] = q3[1] - q2[1]; f2[2] = q3[2] - q2[2];
+ f3[0] = q1[0] - q3[0]; f3[1] = q1[1] - q3[1]; f3[2] = q1[2] - q3[2];
+
+ VcrossV(n1, e1, e2);
+ VcrossV(m1, f1, f2);
+
+ VcrossV(g1, e1, n1);
+ VcrossV(g2, e2, n1);
+ VcrossV(g3, e3, n1);
+ VcrossV(h1, f1, m1);
+ VcrossV(h2, f2, m1);
+ VcrossV(h3, f3, m1);
+
+ VcrossV(ef11, e1, f1);
+ VcrossV(ef12, e1, f2);
+ VcrossV(ef13, e1, f3);
+ VcrossV(ef21, e2, f1);
+ VcrossV(ef22, e2, f2);
+ VcrossV(ef23, e2, f3);
+ VcrossV(ef31, e3, f1);
+ VcrossV(ef32, e3, f2);
+ VcrossV(ef33, e3, f3);
+
+ // now begin the series of tests
+
+ if (!project6(n1, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(m1, p1, p2, p3, q1, q2, q3)) return 0;
+
+ if (!project6(ef11, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef12, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef13, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef21, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef22, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef23, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef31, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef32, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(ef33, p1, p2, p3, q1, q2, q3)) return 0;
+
+ if (!project6(g1, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(g2, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(g3, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(h1, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(h2, p1, p2, p3, q1, q2, q3)) return 0;
+ if (!project6(h3, p1, p2, p3, q1, q2, q3)) return 0;
+
+ return 1;
+}
+
+inline
+PQP_REAL
+TriDistance(PQP_REAL R[3][3], PQP_REAL T[3], Tri *t1, Tri *t2,
+ PQP_REAL p[3], PQP_REAL q[3])
+{
+ // transform tri 2 into same space as tri 1
+
+ PQP_REAL tri1[3][3], tri2[3][3];
+
+ VcV(tri1[0], t1->p1);
+ VcV(tri1[1], t1->p2);
+ VcV(tri1[2], t1->p3);
+ MxVpV(tri2[0], R, t2->p1, T);
+ MxVpV(tri2[1], R, t2->p2, T);
+ MxVpV(tri2[2], R, t2->p3, T);
+
+ return TriDist(p,q,tri1,tri2);
+}
+
+
+void
+CollideRecurse(PQP_CollideResult *res,
+ PQP_REAL R[3][3], PQP_REAL T[3], // b2 relative to b1
+ PQP_Model *o1, int b1,
+ PQP_Model *o2, int b2, int flag)
+{
+ // first thing, see if we're overlapping
+
+ res->num_bv_tests++;
+
+ if (!BV_Overlap(R, T, o1->child(b1), o2->child(b2))) return;
+
+ // if we are, see if we test triangles next
+
+ int l1 = o1->child(b1)->Leaf();
+ int l2 = o2->child(b2)->Leaf();
+
+ if (l1 && l2)
+ {
+ res->num_tri_tests++;
+
+#if 1
+ // transform the points in b2 into space of b1, then compare
+
+ Tri *t1 = &o1->tris[-o1->child(b1)->first_child - 1];
+ Tri *t2 = &o2->tris[-o2->child(b2)->first_child - 1];
+ PQP_REAL q1[3], q2[3], q3[3];
+ PQP_REAL *p1 = t1->p1;
+ PQP_REAL *p2 = t1->p2;
+ PQP_REAL *p3 = t1->p3;
+ MxVpV(q1, res->R, t2->p1, res->T);
+ MxVpV(q2, res->R, t2->p2, res->T);
+ MxVpV(q3, res->R, t2->p3, res->T);
+ if (TriContact(p1, p2, p3, q1, q2, q3))
+ {
+ // add this to result
+
+ res->Add(t1->id, t2->id);
+ }
+#else
+ PQP_REAL p[3], q[3];
+
+ Tri *t1 = &o1->tris[-o1->child(b1)->first_child - 1];
+ Tri *t2 = &o2->tris[-o2->child(b2)->first_child - 1];
+
+ if (TriDistance(res->R,res->T,t1,t2,p,q) == 0.0)
+ {
+ // add this to result
+
+ res->Add(t1->id, t2->id);
+ }
+#endif
+
+ return;
+ }
+
+ // we dont, so decide whose children to visit next
+
+ PQP_REAL sz1 = o1->child(b1)->GetSize();
+ PQP_REAL sz2 = o2->child(b2)->GetSize();
+
+ PQP_REAL Rc[3][3],Tc[3],Ttemp[3];
+
+ if (l2 || (!l1 && (sz1 > sz2)))
+ {
+ int c1 = o1->child(b1)->first_child;
+ int c2 = c1 + 1;
+
+ MTxM(Rc,o1->child(c1)->R,R);
+#if PQP_BV_TYPE & OBB_TYPE
+ VmV(Ttemp,T,o1->child(c1)->To);
+#else
+ VmV(Ttemp,T,o1->child(c1)->Tr);
+#endif
+ MTxV(Tc,o1->child(c1)->R,Ttemp);
+ CollideRecurse(res,Rc,Tc,o1,c1,o2,b2,flag);
+
+ if ((flag == PQP_FIRST_CONTACT) && (res->num_pairs > 0)) return;
+
+ MTxM(Rc,o1->child(c2)->R,R);
+#if PQP_BV_TYPE & OBB_TYPE
+ VmV(Ttemp,T,o1->child(c2)->To);
+#else
+ VmV(Ttemp,T,o1->child(c2)->Tr);
+#endif
+ MTxV(Tc,o1->child(c2)->R,Ttemp);
+ CollideRecurse(res,Rc,Tc,o1,c2,o2,b2,flag);
+ }
+ else
+ {
+ int c1 = o2->child(b2)->first_child;
+ int c2 = c1 + 1;
+
+ MxM(Rc,R,o2->child(c1)->R);
+#if PQP_BV_TYPE & OBB_TYPE
+ MxVpV(Tc,R,o2->child(c1)->To,T);
+#else
+ MxVpV(Tc,R,o2->child(c1)->Tr,T);
+#endif
+ CollideRecurse(res,Rc,Tc,o1,b1,o2,c1,flag);
+
+ if ((flag == PQP_FIRST_CONTACT) && (res->num_pairs > 0)) return;
+
+ MxM(Rc,R,o2->child(c2)->R);
+#if PQP_BV_TYPE & OBB_TYPE
+ MxVpV(Tc,R,o2->child(c2)->To,T);
+#else
+ MxVpV(Tc,R,o2->child(c2)->Tr,T);
+#endif
+ CollideRecurse(res,Rc,Tc,o1,b1,o2,c2,flag);
+ }
+}
+
+int
+PQP_Collide(PQP_CollideResult *res,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ int flag)
+{
+ double t1 = GetTime();
+
+ // make sure that the models are built
+
+ if (o1->build_state != PQP_BUILD_STATE_PROCESSED)
+ return PQP_ERR_UNPROCESSED_MODEL;
+ if (o2->build_state != PQP_BUILD_STATE_PROCESSED)
+ return PQP_ERR_UNPROCESSED_MODEL;
+
+ // clear the stats
+
+ res->num_bv_tests = 0;
+ res->num_tri_tests = 0;
+
+ // don't release the memory, but reset the num_pairs counter
+
+ res->num_pairs = 0;
+
+ // Okay, compute what transform [R,T] that takes us from cs1 to cs2.
+ // [R,T] = [R1,T1]'[R2,T2] = [R1',-R1'T][R2,T2] = [R1'R2, R1'(T2-T1)]
+ // First compute the rotation part, then translation part
+
+ MTxM(res->R,R1,R2);
+ PQP_REAL Ttemp[3];
+ VmV(Ttemp, T2, T1);
+ MTxV(res->T, R1, Ttemp);
+
+ // compute the transform from o1->child(0) to o2->child(0)
+
+ PQP_REAL Rtemp[3][3], R[3][3], T[3];
+
+ MxM(Rtemp,res->R,o2->child(0)->R);
+ MTxM(R,o1->child(0)->R,Rtemp);
+
+#if PQP_BV_TYPE & OBB_TYPE
+ MxVpV(Ttemp,res->R,o2->child(0)->To,res->T);
+ VmV(Ttemp,Ttemp,o1->child(0)->To);
+#else
+ MxVpV(Ttemp,res->R,o2->child(0)->Tr,res->T);
+ VmV(Ttemp,Ttemp,o1->child(0)->Tr);
+#endif
+
+ MTxV(T,o1->child(0)->R,Ttemp);
+
+ // now start with both top level BVs
+
+ CollideRecurse(res,R,T,o1,0,o2,0,flag);
+
+ double t2 = GetTime();
+ res->query_time_secs = t2 - t1;
+
+ return PQP_OK;
+}
+
+#if PQP_BV_TYPE & RSS_TYPE // distance/tolerance only available with RSS
+ // unless an OBB distance test is supplied in
+ // BV.cpp
+
+// DISTANCE STUFF
+//
+//--------------------------------------------------------------------------
+
+void
+DistanceRecurse(PQP_DistanceResult *res,
+ PQP_REAL R[3][3], PQP_REAL T[3], // b2 relative to b1
+ PQP_Model *o1, int b1,
+ PQP_Model *o2, int b2)
+{
+ PQP_REAL sz1 = o1->child(b1)->GetSize();
+ PQP_REAL sz2 = o2->child(b2)->GetSize();
+ int l1 = o1->child(b1)->Leaf();
+ int l2 = o2->child(b2)->Leaf();
+
+ if (l1 && l2)
+ {
+ // both leaves. Test the triangles beneath them.
+
+ res->num_tri_tests++;
+
+ PQP_REAL p[3], q[3];
+
+ Tri *t1 = &o1->tris[-o1->child(b1)->first_child - 1];
+ Tri *t2 = &o2->tris[-o2->child(b2)->first_child - 1];
+
+ PQP_REAL d = TriDistance(res->R,res->T,t1,t2,p,q);
+
+ if (d < res->distance)
+ {
+ res->distance = d;
+
+ VcV(res->p1, p); // p already in c.s. 1
+ VcV(res->p2, q); // q must be transformed
+ // into c.s. 2 later
+ o1->last_tri = t1;
+ o2->last_tri = t2;
+ }
+
+ return;
+ }
+
+ // First, perform distance tests on the children. Then traverse
+ // them recursively, but test the closer pair first, the further
+ // pair second.
+
+ int a1,a2,c1,c2; // new bv tests 'a' and 'c'
+ PQP_REAL R1[3][3], T1[3], R2[3][3], T2[3], Ttemp[3];
+
+ if (l2 || (!l1 && (sz1 > sz2)))
+ {
+ // visit the children of b1
+
+ a1 = o1->child(b1)->first_child;
+ a2 = b2;
+ c1 = o1->child(b1)->first_child+1;
+ c2 = b2;
+
+ MTxM(R1,o1->child(a1)->R,R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,T,o1->child(a1)->Tr);
+#else
+ VmV(Ttemp,T,o1->child(a1)->To);
+#endif
+ MTxV(T1,o1->child(a1)->R,Ttemp);
+
+ MTxM(R2,o1->child(c1)->R,R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,T,o1->child(c1)->Tr);
+#else
+ VmV(Ttemp,T,o1->child(c1)->To);
+#endif
+ MTxV(T2,o1->child(c1)->R,Ttemp);
+ }
+ else
+ {
+ // visit the children of b2
+
+ a1 = b1;
+ a2 = o2->child(b2)->first_child;
+ c1 = b1;
+ c2 = o2->child(b2)->first_child+1;
+
+ MxM(R1,R,o2->child(a2)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(T1,R,o2->child(a2)->Tr,T);
+#else
+ MxVpV(T1,R,o2->child(a2)->To,T);
+#endif
+
+ MxM(R2,R,o2->child(c2)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(T2,R,o2->child(c2)->Tr,T);
+#else
+ MxVpV(T2,R,o2->child(c2)->To,T);
+#endif
+ }
+
+ res->num_bv_tests += 2;
+
+ PQP_REAL d1 = BV_Distance(R1, T1, o1->child(a1), o2->child(a2));
+ PQP_REAL d2 = BV_Distance(R2, T2, o1->child(c1), o2->child(c2));
+
+ if (d2 < d1)
+ {
+ if ((d2 < (res->distance - res->abs_err)) ||
+ (d2*(1 + res->rel_err) < res->distance))
+ {
+ DistanceRecurse(res, R2, T2, o1, c1, o2, c2);
+ }
+
+ if ((d1 < (res->distance - res->abs_err)) ||
+ (d1*(1 + res->rel_err) < res->distance))
+ {
+ DistanceRecurse(res, R1, T1, o1, a1, o2, a2);
+ }
+ }
+ else
+ {
+ if ((d1 < (res->distance - res->abs_err)) ||
+ (d1*(1 + res->rel_err) < res->distance))
+ {
+ DistanceRecurse(res, R1, T1, o1, a1, o2, a2);
+ }
+
+ if ((d2 < (res->distance - res->abs_err)) ||
+ (d2*(1 + res->rel_err) < res->distance))
+ {
+ DistanceRecurse(res, R2, T2, o1, c1, o2, c2);
+ }
+ }
+}
+
+void
+DistanceQueueRecurse(PQP_DistanceResult *res,
+ PQP_REAL R[3][3], PQP_REAL T[3],
+ PQP_Model *o1, int b1,
+ PQP_Model *o2, int b2)
+{
+ BVTQ bvtq(res->qsize);
+
+ BVT min_test;
+ min_test.b1 = b1;
+ min_test.b2 = b2;
+ McM(min_test.R,R);
+ VcV(min_test.T,T);
+
+ while(1)
+ {
+ int l1 = o1->child(min_test.b1)->Leaf();
+ int l2 = o2->child(min_test.b2)->Leaf();
+
+ if (l1 && l2)
+ {
+ // both leaves. Test the triangles beneath them.
+
+ res->num_tri_tests++;
+
+ PQP_REAL p[3], q[3];
+
+ Tri *t1 = &o1->tris[-o1->child(min_test.b1)->first_child - 1];
+ Tri *t2 = &o2->tris[-o2->child(min_test.b2)->first_child - 1];
+
+ PQP_REAL d = TriDistance(res->R,res->T,t1,t2,p,q);
+
+ if (d < res->distance)
+ {
+ res->distance = d;
+
+ VcV(res->p1, p); // p already in c.s. 1
+ VcV(res->p2, q); // q must be transformed
+ // into c.s. 2 later
+ o1->last_tri = t1;
+ o2->last_tri = t2;
+ }
+ }
+ else if (bvtq.GetNumTests() == bvtq.GetSize() - 1)
+ {
+ // queue can't get two more tests, recur
+
+ DistanceQueueRecurse(res,min_test.R,min_test.T,
+ o1,min_test.b1,o2,min_test.b2);
+ }
+ else
+ {
+ // decide how to descend to children
+
+ PQP_REAL sz1 = o1->child(min_test.b1)->GetSize();
+ PQP_REAL sz2 = o2->child(min_test.b2)->GetSize();
+
+ res->num_bv_tests += 2;
+
+ BVT bvt1,bvt2;
+ PQP_REAL Ttemp[3];
+
+ if (l2 || (!l1 && (sz1 > sz2)))
+ {
+ // put new tests on queue consisting of min_test.b2
+ // with children of min_test.b1
+
+ int c1 = o1->child(min_test.b1)->first_child;
+ int c2 = c1 + 1;
+
+ // init bv test 1
+
+ bvt1.b1 = c1;
+ bvt1.b2 = min_test.b2;
+ MTxM(bvt1.R,o1->child(c1)->R,min_test.R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,min_test.T,o1->child(c1)->Tr);
+#else
+ VmV(Ttemp,min_test.T,o1->child(c1)->To);
+#endif
+ MTxV(bvt1.T,o1->child(c1)->R,Ttemp);
+ bvt1.d = BV_Distance(bvt1.R,bvt1.T,
+ o1->child(bvt1.b1),o2->child(bvt1.b2));
+
+ // init bv test 2
+
+ bvt2.b1 = c2;
+ bvt2.b2 = min_test.b2;
+ MTxM(bvt2.R,o1->child(c2)->R,min_test.R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,min_test.T,o1->child(c2)->Tr);
+#else
+ VmV(Ttemp,min_test.T,o1->child(c2)->To);
+#endif
+ MTxV(bvt2.T,o1->child(c2)->R,Ttemp);
+ bvt2.d = BV_Distance(bvt2.R,bvt2.T,
+ o1->child(bvt2.b1),o2->child(bvt2.b2));
+ }
+ else
+ {
+ // put new tests on queue consisting of min_test.b1
+ // with children of min_test.b2
+
+ int c1 = o2->child(min_test.b2)->first_child;
+ int c2 = c1 + 1;
+
+ // init bv test 1
+
+ bvt1.b1 = min_test.b1;
+ bvt1.b2 = c1;
+ MxM(bvt1.R,min_test.R,o2->child(c1)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(bvt1.T,min_test.R,o2->child(c1)->Tr,min_test.T);
+#else
+ MxVpV(bvt1.T,min_test.R,o2->child(c1)->To,min_test.T);
+#endif
+ bvt1.d = BV_Distance(bvt1.R,bvt1.T,
+ o1->child(bvt1.b1),o2->child(bvt1.b2));
+
+ // init bv test 2
+
+ bvt2.b1 = min_test.b1;
+ bvt2.b2 = c2;
+ MxM(bvt2.R,min_test.R,o2->child(c2)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(bvt2.T,min_test.R,o2->child(c2)->Tr,min_test.T);
+#else
+ MxVpV(bvt2.T,min_test.R,o2->child(c2)->To,min_test.T);
+#endif
+ bvt2.d = BV_Distance(bvt2.R,bvt2.T,
+ o1->child(bvt2.b1),o2->child(bvt2.b2));
+ }
+
+ bvtq.AddTest(bvt1);
+ bvtq.AddTest(bvt2);
+ }
+
+ if (bvtq.Empty())
+ {
+ break;
+ }
+ else
+ {
+ min_test = bvtq.ExtractMinTest();
+
+ if ((min_test.d + res->abs_err >= res->distance) &&
+ ((min_test.d * (1 + res->rel_err)) >= res->distance))
+ {
+ break;
+ }
+ }
+ }
+}
+
+int
+PQP_Distance(PQP_DistanceResult *res,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL rel_err, PQP_REAL abs_err,
+ int qsize)
+{
+
+ double time1 = GetTime();
+
+ // make sure that the models are built
+
+ if (o1->build_state != PQP_BUILD_STATE_PROCESSED)
+ return PQP_ERR_UNPROCESSED_MODEL;
+ if (o2->build_state != PQP_BUILD_STATE_PROCESSED)
+ return PQP_ERR_UNPROCESSED_MODEL;
+
+ // Okay, compute what transform [R,T] that takes us from cs2 to cs1.
+ // [R,T] = [R1,T1]'[R2,T2] = [R1',-R1'T][R2,T2] = [R1'R2, R1'(T2-T1)]
+ // First compute the rotation part, then translation part
+
+ MTxM(res->R,R1,R2);
+ PQP_REAL Ttemp[3];
+ VmV(Ttemp, T2, T1);
+ MTxV(res->T, R1, Ttemp);
+
+ // establish initial upper bound using last triangles which
+ // provided the minimum distance
+
+ PQP_REAL p[3],q[3];
+ res->distance = TriDistance(res->R,res->T,o1->last_tri,o2->last_tri,p,q);
+ VcV(res->p1,p);
+ VcV(res->p2,q);
+
+ // initialize error bounds
+
+ res->abs_err = abs_err;
+ res->rel_err = rel_err;
+
+ // clear the stats
+
+ res->num_bv_tests = 0;
+ res->num_tri_tests = 0;
+
+ // compute the transform from o1->child(0) to o2->child(0)
+
+ PQP_REAL Rtemp[3][3], R[3][3], T[3];
+
+ MxM(Rtemp,res->R,o2->child(0)->R);
+ MTxM(R,o1->child(0)->R,Rtemp);
+
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(Ttemp,res->R,o2->child(0)->Tr,res->T);
+ VmV(Ttemp,Ttemp,o1->child(0)->Tr);
+#else
+ MxVpV(Ttemp,res->R,o2->child(0)->To,res->T);
+ VmV(Ttemp,Ttemp,o1->child(0)->To);
+#endif
+ MTxV(T,o1->child(0)->R,Ttemp);
+
+ // choose routine according to queue size
+
+ if (qsize <= 2)
+ {
+ DistanceRecurse(res,R,T,o1,0,o2,0);
+ }
+ else
+ {
+ res->qsize = qsize;
+
+ DistanceQueueRecurse(res,R,T,o1,0,o2,0);
+ }
+
+ // res->p2 is in cs 1 ; transform it to cs 2
+
+ PQP_REAL u[3];
+ VmV(u, res->p2, res->T);
+ MTxV(res->p2, res->R, u);
+
+ double time2 = GetTime();
+ res->query_time_secs = time2 - time1;
+
+ return PQP_OK;
+}
+
+// Tolerance Stuff
+//
+//---------------------------------------------------------------------------
+void
+ToleranceRecurse(PQP_ToleranceResult *res,
+ PQP_REAL R[3][3], PQP_REAL T[3],
+ PQP_Model *o1, int b1, PQP_Model *o2, int b2)
+{
+ PQP_REAL sz1 = o1->child(b1)->GetSize();
+ PQP_REAL sz2 = o2->child(b2)->GetSize();
+ int l1 = o1->child(b1)->Leaf();
+ int l2 = o2->child(b2)->Leaf();
+
+ if (l1 && l2)
+ {
+ // both leaves - find if tri pair within tolerance
+
+ res->num_tri_tests++;
+
+ PQP_REAL p[3], q[3];
+
+ Tri *t1 = &o1->tris[-o1->child(b1)->first_child - 1];
+ Tri *t2 = &o2->tris[-o2->child(b2)->first_child - 1];
+
+ PQP_REAL d = TriDistance(res->R,res->T,t1,t2,p,q);
+
+ if (d <= res->tolerance)
+ {
+ // triangle pair distance less than tolerance
+
+ res->closer_than_tolerance = 1;
+ res->distance = d;
+ VcV(res->p1, p); // p already in c.s. 1
+ VcV(res->p2, q); // q must be transformed
+ // into c.s. 2 later
+ }
+
+ return;
+ }
+
+ int a1,a2,c1,c2; // new bv tests 'a' and 'c'
+ PQP_REAL R1[3][3], T1[3], R2[3][3], T2[3], Ttemp[3];
+
+ if (l2 || (!l1 && (sz1 > sz2)))
+ {
+ // visit the children of b1
+
+ a1 = o1->child(b1)->first_child;
+ a2 = b2;
+ c1 = o1->child(b1)->first_child+1;
+ c2 = b2;
+
+ MTxM(R1,o1->child(a1)->R,R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,T,o1->child(a1)->Tr);
+#else
+ VmV(Ttemp,T,o1->child(a1)->To);
+#endif
+ MTxV(T1,o1->child(a1)->R,Ttemp);
+
+ MTxM(R2,o1->child(c1)->R,R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,T,o1->child(c1)->Tr);
+#else
+ VmV(Ttemp,T,o1->child(c1)->To);
+#endif
+ MTxV(T2,o1->child(c1)->R,Ttemp);
+ }
+ else
+ {
+ // visit the children of b2
+
+ a1 = b1;
+ a2 = o2->child(b2)->first_child;
+ c1 = b1;
+ c2 = o2->child(b2)->first_child+1;
+
+ MxM(R1,R,o2->child(a2)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(T1,R,o2->child(a2)->Tr,T);
+#else
+ MxVpV(T1,R,o2->child(a2)->To,T);
+#endif
+ MxM(R2,R,o2->child(c2)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(T2,R,o2->child(c2)->Tr,T);
+#else
+ MxVpV(T2,R,o2->child(c2)->To,T);
+#endif
+ }
+
+ res->num_bv_tests += 2;
+
+ PQP_REAL d1 = BV_Distance(R1, T1, o1->child(a1), o2->child(a2));
+ PQP_REAL d2 = BV_Distance(R2, T2, o1->child(c1), o2->child(c2));
+
+ if (d2 < d1)
+ {
+ if (d2 <= res->tolerance) ToleranceRecurse(res, R2, T2, o1, c1, o2, c2);
+ if (res->closer_than_tolerance) return;
+ if (d1 <= res->tolerance) ToleranceRecurse(res, R1, T1, o1, a1, o2, a2);
+ }
+ else
+ {
+ if (d1 <= res->tolerance) ToleranceRecurse(res, R1, T1, o1, a1, o2, a2);
+ if (res->closer_than_tolerance) return;
+ if (d2 <= res->tolerance) ToleranceRecurse(res, R2, T2, o1, c1, o2, c2);
+ }
+}
+
+void
+ToleranceQueueRecurse(PQP_ToleranceResult *res,
+ PQP_REAL R[3][3], PQP_REAL T[3],
+ PQP_Model *o1, int b1,
+ PQP_Model *o2, int b2)
+{
+ BVTQ bvtq(res->qsize);
+ BVT min_test;
+ min_test.b1 = b1;
+ min_test.b2 = b2;
+ McM(min_test.R,R);
+ VcV(min_test.T,T);
+
+ while(1)
+ {
+ int l1 = o1->child(min_test.b1)->Leaf();
+ int l2 = o2->child(min_test.b2)->Leaf();
+
+ if (l1 && l2)
+ {
+ // both leaves - find if tri pair within tolerance
+
+ res->num_tri_tests++;
+
+ PQP_REAL p[3], q[3];
+
+ Tri *t1 = &o1->tris[-o1->child(min_test.b1)->first_child - 1];
+ Tri *t2 = &o2->tris[-o2->child(min_test.b2)->first_child - 1];
+
+ PQP_REAL d = TriDistance(res->R,res->T,t1,t2,p,q);
+
+ if (d <= res->tolerance)
+ {
+ // triangle pair distance less than tolerance
+
+ res->closer_than_tolerance = 1;
+ res->distance = d;
+ VcV(res->p1, p); // p already in c.s. 1
+ VcV(res->p2, q); // q must be transformed
+ // into c.s. 2 later
+ return;
+ }
+ }
+ else if (bvtq.GetNumTests() == bvtq.GetSize() - 1)
+ {
+ // queue can't get two more tests, recur
+
+ ToleranceQueueRecurse(res,min_test.R,min_test.T,
+ o1,min_test.b1,o2,min_test.b2);
+ if (res->closer_than_tolerance == 1) return;
+ }
+ else
+ {
+ // decide how to descend to children
+
+ PQP_REAL sz1 = o1->child(min_test.b1)->GetSize();
+ PQP_REAL sz2 = o2->child(min_test.b2)->GetSize();
+
+ res->num_bv_tests += 2;
+
+ BVT bvt1,bvt2;
+ PQP_REAL Ttemp[3];
+
+ if (l2 || (!l1 && (sz1 > sz2)))
+ {
+ // add two new tests to queue, consisting of min_test.b2
+ // with the children of min_test.b1
+
+ int c1 = o1->child(min_test.b1)->first_child;
+ int c2 = c1 + 1;
+
+ // init bv test 1
+
+ bvt1.b1 = c1;
+ bvt1.b2 = min_test.b2;
+ MTxM(bvt1.R,o1->child(c1)->R,min_test.R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,min_test.T,o1->child(c1)->Tr);
+#else
+ VmV(Ttemp,min_test.T,o1->child(c1)->To);
+#endif
+ MTxV(bvt1.T,o1->child(c1)->R,Ttemp);
+ bvt1.d = BV_Distance(bvt1.R,bvt1.T,
+ o1->child(bvt1.b1),o2->child(bvt1.b2));
+
+ // init bv test 2
+
+ bvt2.b1 = c2;
+ bvt2.b2 = min_test.b2;
+ MTxM(bvt2.R,o1->child(c2)->R,min_test.R);
+#if PQP_BV_TYPE & RSS_TYPE
+ VmV(Ttemp,min_test.T,o1->child(c2)->Tr);
+#else
+ VmV(Ttemp,min_test.T,o1->child(c2)->To);
+#endif
+ MTxV(bvt2.T,o1->child(c2)->R,Ttemp);
+ bvt2.d = BV_Distance(bvt2.R,bvt2.T,
+ o1->child(bvt2.b1),o2->child(bvt2.b2));
+ }
+ else
+ {
+ // add two new tests to queue, consisting of min_test.b1
+ // with the children of min_test.b2
+
+ int c1 = o2->child(min_test.b2)->first_child;
+ int c2 = c1 + 1;
+
+ // init bv test 1
+
+ bvt1.b1 = min_test.b1;
+ bvt1.b2 = c1;
+ MxM(bvt1.R,min_test.R,o2->child(c1)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(bvt1.T,min_test.R,o2->child(c1)->Tr,min_test.T);
+#else
+ MxVpV(bvt1.T,min_test.R,o2->child(c1)->To,min_test.T);
+#endif
+ bvt1.d = BV_Distance(bvt1.R,bvt1.T,
+ o1->child(bvt1.b1),o2->child(bvt1.b2));
+
+ // init bv test 2
+
+ bvt2.b1 = min_test.b1;
+ bvt2.b2 = c2;
+ MxM(bvt2.R,min_test.R,o2->child(c2)->R);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(bvt2.T,min_test.R,o2->child(c2)->Tr,min_test.T);
+#else
+ MxVpV(bvt2.T,min_test.R,o2->child(c2)->To,min_test.T);
+#endif
+ bvt2.d = BV_Distance(bvt2.R,bvt2.T,
+ o1->child(bvt2.b1),o2->child(bvt2.b2));
+ }
+
+ // put children tests in queue
+
+ if (bvt1.d <= res->tolerance) bvtq.AddTest(bvt1);
+ if (bvt2.d <= res->tolerance) bvtq.AddTest(bvt2);
+ }
+
+ if (bvtq.Empty() || (bvtq.MinTest() > res->tolerance))
+ {
+ res->closer_than_tolerance = 0;
+ return;
+ }
+ else
+ {
+ min_test = bvtq.ExtractMinTest();
+ }
+ }
+}
+
+int
+PQP_Tolerance(PQP_ToleranceResult *res,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL tolerance,
+ int qsize)
+{
+ double time1 = GetTime();
+
+ // make sure that the models are built
+
+ if (o1->build_state != PQP_BUILD_STATE_PROCESSED)
+ return PQP_ERR_UNPROCESSED_MODEL;
+ if (o2->build_state != PQP_BUILD_STATE_PROCESSED)
+ return PQP_ERR_UNPROCESSED_MODEL;
+
+ // Compute the transform [R,T] that takes us from cs2 to cs1.
+ // [R,T] = [R1,T1]'[R2,T2] = [R1',-R1'T][R2,T2] = [R1'R2, R1'(T2-T1)]
+
+ MTxM(res->R,R1,R2);
+ PQP_REAL Ttemp[3];
+ VmV(Ttemp, T2, T1);
+ MTxV(res->T, R1, Ttemp);
+
+ // set tolerance, used to prune the search
+
+ if (tolerance < 0.0) tolerance = 0.0;
+ res->tolerance = tolerance;
+
+ // clear the stats
+
+ res->num_bv_tests = 0;
+ res->num_tri_tests = 0;
+
+ // initially assume not closer than tolerance
+
+ res->closer_than_tolerance = 0;
+
+ // compute the transform from o1->child(0) to o2->child(0)
+
+ PQP_REAL Rtemp[3][3], R[3][3], T[3];
+
+ MxM(Rtemp,res->R,o2->child(0)->R);
+ MTxM(R,o1->child(0)->R,Rtemp);
+#if PQP_BV_TYPE & RSS_TYPE
+ MxVpV(Ttemp,res->R,o2->child(0)->Tr,res->T);
+ VmV(Ttemp,Ttemp,o1->child(0)->Tr);
+#else
+ MxVpV(Ttemp,res->R,o2->child(0)->To,res->T);
+ VmV(Ttemp,Ttemp,o1->child(0)->To);
+#endif
+ MTxV(T,o1->child(0)->R,Ttemp);
+
+ // find a distance lower bound for trivial reject
+
+ PQP_REAL d = BV_Distance(R, T, o1->child(0), o2->child(0));
+
+ if (d <= res->tolerance)
+ {
+ // more work needed - choose routine according to queue size
+
+ if (qsize <= 2)
+ {
+ ToleranceRecurse(res, R, T, o1, 0, o2, 0);
+ }
+ else
+ {
+ res->qsize = qsize;
+ ToleranceQueueRecurse(res, R, T, o1, 0, o2, 0);
+ }
+ }
+
+ // res->p2 is in cs 1 ; transform it to cs 2
+
+ PQP_REAL u[3];
+ VmV(u, res->p2, res->T);
+ MTxV(res->p2, res->R, u);
+
+ double time2 = GetTime();
+ res->query_time_secs = time2 - time1;
+
+ return PQP_OK;
+}
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.h
new file mode 100644
index 00000000..f6f3e539
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP.h
@@ -0,0 +1,338 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_H
+#define PQP_H
+
+#include "PQP_Compile.h"
+#include "PQP_Internal.h"
+
+//----------------------------------------------------------------------------
+//
+// PQP API Return Values
+//
+//----------------------------------------------------------------------------
+
+const int PQP_OK = 0;
+ // Used by all API routines upon successful completion except
+ // constructors and destructors
+
+const int PQP_ERR_MODEL_OUT_OF_MEMORY = -1;
+ // Returned when an API function cannot obtain enough memory to
+ // store or process a PQP_Model object.
+
+const int PQP_ERR_OUT_OF_MEMORY = -2;
+ // Returned when a PQP query cannot allocate enough storage to
+ // compute or hold query information. In this case, the returned
+ // data should not be trusted.
+
+const int PQP_ERR_UNPROCESSED_MODEL = -3;
+ // Returned when an unprocessed model is passed to a function which
+ // expects only processed models, such as PQP_Collide() or
+ // PQP_Distance().
+
+const int PQP_ERR_BUILD_OUT_OF_SEQUENCE = -4;
+ // Returned when:
+ // 1. AddTri() is called before BeginModel().
+ // 2. BeginModel() is called immediately after AddTri().
+ // This error code is something like a warning: the invoked
+ // operation takes place anyway, and PQP does what makes "most
+ // sense", but the returned error code may tip off the client that
+ // something out of the ordinary is happenning.
+
+const int PQP_ERR_BUILD_EMPTY_MODEL = -5;
+ // Returned when EndModel() is called on a model to which no
+ // triangles have been added. This is similar in spirit to the
+ // OUT_OF_SEQUENCE return code, except that the requested operation
+ // has FAILED -- the model remains "unprocessed", and the client may
+ // NOT use it in queries.
+
+//----------------------------------------------------------------------------
+//
+// PQP_REAL
+//
+// The floating point type used throughout the package. The type is defined
+// in PQP_Compile.h, and by default is "double"
+//
+//----------------------------------------------------------------------------
+
+//----------------------------------------------------------------------------
+//
+// PQP_Model
+//
+// A PQP_Model stores geometry to be used in a proximity query.
+// The geometry is loaded with a call to BeginModel(), at least one call to
+// AddTri(), and then a call to EndModel().
+//
+// // create a two triangle model, m
+//
+// PQP_Model m;
+//
+// PQP_REAL p1[3],p2[3],p3[3]; // 3 points will make triangle p
+// PQP_REAL q1[3],q2[3],q3[3]; // another 3 points for triangle q
+//
+// // some initialization of these vertices not shown
+//
+// m.BeginModel(); // begin the model
+// m.AddTri(p1,p2,p3,0); // add triangle p
+// m.AddTri(q1,q2,q3,1); // add triangle q
+// m.EndModel(); // end (build) the model
+//
+// The last parameter of AddTri() is the number to be associated with the
+// triangle. These numbers are used to identify the triangles that overlap.
+//
+// AddTri() copies into the PQP_Model the data pointed to by the three vertex
+// pointers, so that it is safe to delete vertex data after you have
+// passed it to AddTri().
+//
+//----------------------------------------------------------------------------
+//
+// class PQP_Model - declaration contained in PQP_Internal.h
+// {
+//
+// public:
+// PQP_Model();
+// ~PQP_Model();
+//
+// int BeginModel(int num_tris = 8); // preallocate for num_tris triangles;
+// // the parameter is optional, since
+// // arrays are reallocated as needed
+//
+// int AddTri(const PQP_REAL *p1, const PQP_REAL *p2, const PQP_REAL *p3,
+// int id);
+//
+// int EndModel();
+// int MemUsage(int msg); // returns model mem usage in bytes
+// // prints message to stderr if msg == TRUE
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_CollideResult
+//
+// This saves and reports results from a collision query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_CollideResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // free the list of contact pairs; ordinarily this list is reused
+// // for each query, and only deleted in the destructor.
+//
+// void FreePairsList();
+//
+// // query results
+//
+// int Colliding();
+// int NumPairs();
+// int Id1(int k);
+// int Id2(int k);
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Collide() - detects collision between two PQP_Models
+//
+//
+// Declare a PQP_CollideResult struct and pass its pointer to collect
+// collision data.
+//
+// [R1, T1] is the placement of model 1 in the world &
+// [R2, T2] is the placement of model 2 in the world.
+// The columns of each 3x3 matrix are the basis vectors for the model
+// in world coordinates, and the matrices are in row-major order:
+// R(row r, col c) = R[r][c].
+//
+// If PQP_ALL_CONTACTS is the flag value, after calling PQP_Collide(),
+// the PQP_CollideResult object will contain an array with all
+// colliding triangle pairs. Suppose CR is a pointer to the
+// PQP_CollideResult object. The number of pairs is gotten from
+// CR->NumPairs(), and the ids of the 15'th pair of colliding
+// triangles is gotten from CR->Id1(14) and CR->Id2(14).
+//
+// If PQP_FIRST_CONTACT is the flag value, the PQP_CollideResult array
+// will only get the first colliding triangle pair found. Thus
+// CR->NumPairs() will be at most 1, and if 1, CR->Id1(0) and
+// CR->Id2(0) give the ids of the colliding triangle pair.
+//
+//----------------------------------------------------------------------------
+
+const int PQP_ALL_CONTACTS = 1; // find all pairwise intersecting triangles
+const int PQP_FIRST_CONTACT = 2; // report first intersecting tri pair found
+
+int
+PQP_Collide(PQP_CollideResult *result,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ int flag = PQP_ALL_CONTACTS);
+
+
+#if PQP_BV_TYPE & RSS_TYPE // this is true by default,
+ // and explained in PQP_Compile.h
+
+//----------------------------------------------------------------------------
+//
+// PQP_DistanceResult
+//
+// This saves and reports results from a distance query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_DistanceResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // The following distance and points established the minimum distance
+// // for the models, within the relative and absolute error bounds
+// // specified.
+//
+// PQP_REAL Distance();
+// const PQP_REAL *P1(); // pointers to three PQP_REALs
+// const PQP_REAL *P2();
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Distance() - computes the distance between two PQP_Models
+//
+//
+// Declare a PQP_DistanceResult struct and pass its pointer to collect
+// distance information.
+//
+// "rel_err" is the relative error margin from actual distance.
+// "abs_err" is the absolute error margin from actual distance. The
+// smaller of the two will be satisfied, so set one large to nullify
+// its effect.
+//
+// "qsize" is an optional parameter controlling the size of a priority
+// queue used to direct the search for closest points. A larger queue
+// can help the algorithm discover the minimum with fewer steps, but
+// will increase the cost of each step. It is not beneficial to increase
+// qsize if the application has frame-to-frame coherence, i.e., the
+// pair of models take small steps between each call, since another
+// speedup trick already accelerates this situation with no overhead.
+//
+// However, a queue size of 100 to 200 has been seen to save time in a
+// planning application with "non-coherent" placements of models.
+//
+//----------------------------------------------------------------------------
+
+int
+PQP_Distance(PQP_DistanceResult *result,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL rel_err, PQP_REAL abs_err,
+ int qsize = 2);
+
+//----------------------------------------------------------------------------
+//
+// PQP_ToleranceResult
+//
+// This saves and reports results from a tolerance query.
+//
+//----------------------------------------------------------------------------
+//
+// struct PQP_ToleranceResult - declaration contained in PQP_Internal.h
+// {
+// // statistics
+//
+// int NumBVTests();
+// int NumTriTests();
+// PQP_REAL QueryTimeSecs();
+//
+// // If the models are closer than ( <= ) tolerance, these points
+// // and distance were what established this. Otherwise,
+// // distance and point values are not meaningful.
+//
+// PQP_REAL Distance();
+// const PQP_REAL *P1();
+// const PQP_REAL *P2();
+//
+// // boolean says whether models are closer than tolerance distance
+//
+// int CloserThanTolerance();
+// };
+
+//----------------------------------------------------------------------------
+//
+// PQP_Tolerance() - checks if distance between PQP_Models is <= tolerance
+//
+//
+// Declare a PQP_ToleranceResult and pass its pointer to collect
+// tolerance information.
+//
+// The algorithm returns whether the true distance is <= or >
+// "tolerance". This routine does not simply compute true distance
+// and compare to the tolerance - models can often be shown closer or
+// farther than the tolerance more trivially. In most cases this
+// query should run faster than a distance query would on the same
+// models and configurations.
+//
+// "qsize" again controls the size of a priority queue used for
+// searching. Not setting qsize is the current recommendation, since
+// increasing it has only slowed down our applications.
+//
+//----------------------------------------------------------------------------
+
+int
+PQP_Tolerance(PQP_ToleranceResult *res,
+ PQP_REAL R1[3][3], PQP_REAL T1[3], PQP_Model *o1,
+ PQP_REAL R2[3][3], PQP_REAL T2[3], PQP_Model *o2,
+ PQP_REAL tolerance,
+ int qsize = 2);
+
+#endif
+#endif
+
+
+
+
+
+
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Compile.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Compile.h
new file mode 100644
index 00000000..f76c9813
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Compile.h
@@ -0,0 +1,101 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_COMPILE_H
+#define PQP_COMPILE_H
+
+// prevents compiler warnings when PQP_REAL is float
+
+#include <math.h>
+inline float sqrt(float x) { return (float)sqrt((double)x); }
+inline float cos(float x) { return (float)cos((double)x); }
+inline float sin(float x) { return (float)sin((double)x); }
+inline float fabs(float x) { return (float)fabs((double)x); }
+
+//-------------------------------------------------------------------------
+//
+// PQP_REAL
+//
+// This is the floating point type used throughout PQP. doubles are
+// recommended, both for their precision and because the software has
+// mainly been tested using them. However, floats appear to be faster
+// (by 60% on some machines).
+//
+//-------------------------------------------------------------------------
+
+typedef double PQP_REAL;
+
+//-------------------------------------------------------------------------
+//
+// PQP_BV_TYPE
+//
+// PQP introduces a bounding volume (BV) type known as the "rectangle
+// swept sphere" (RSS) - the volume created by sweeping a sphere so
+// that its center visits every point on a rectangle; it looks
+// something like a rounded box.
+//
+// In our experiments, the RSS type is comparable to the oriented
+// bounding box (OBB) in terms of the number of BV-pair and triangle-pair
+// tests incurred. However, with our present implementations, overlap
+// tests are cheaper for OBBs, while distance tests are cheaper for the
+// RSS type (we used a public gjk implementation for the OBB distance test).
+//
+// Consequently, PQP is configured to use the RSS type in distance and
+// tolerance queries (which use BV distance tests) and to use OBBs for
+// collision queries (which use BV overlap tests). Using both requires six
+// more PQP_REALs per BV node than using just one type.
+//
+// To save space, you can configure PQP to use only one type, however,
+// with RSS alone, collision queries will typically be slower. With OBB's
+// alone, distance and tolerance queries are currently not supported, since
+// we have not developed our own OBB distance test. The three options are:
+//
+// #define PQP_BV_TYPE RSS_TYPE
+// #define PQP_BV_TYPE OBB_TYPE
+// #define PQP_BV_TYPE RSS_TYPE | OBB_TYPE
+//
+//-------------------------------------------------------------------------
+
+#define RSS_TYPE 1
+#define OBB_TYPE 2
+
+#define PQP_BV_TYPE RSS_TYPE | OBB_TYPE
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Internal.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Internal.h
new file mode 100644
index 00000000..90cedcfa
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/PQP_Internal.h
@@ -0,0 +1,203 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk, E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#include "Tri.h"
+#include "BV.h"
+
+class PQP_Model
+{
+
+public:
+
+ int build_state;
+
+ Tri *tris;
+ int num_tris;
+ int num_tris_alloced;
+
+ BV *b;
+ int num_bvs;
+ int num_bvs_alloced;
+
+ Tri *last_tri; // closest tri on this model in last distance test
+
+ BV *child(int n) { return &b[n]; }
+
+ PQP_Model();
+ ~PQP_Model();
+
+ int BeginModel(int num_tris = 8); // preallocate for num_tris triangles;
+ // the parameter is optional, since
+ // arrays are reallocated as needed
+ int AddTri(const PQP_REAL *p1, const PQP_REAL *p2, const PQP_REAL *p3,
+ int id);
+ int EndModel();
+ int MemUsage(int msg); // returns model mem usage.
+ // prints message to stderr if msg == TRUE
+};
+
+struct CollisionPair
+{
+ int id1;
+ int id2;
+};
+
+struct PQP_CollideResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ int num_pairs_alloced;
+ int num_pairs;
+ CollisionPair *pairs;
+
+ void SizeTo(int n);
+ void Add(int i1, int i2);
+
+ PQP_CollideResult();
+ ~PQP_CollideResult();
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // free the list of contact pairs; ordinarily this list is reused
+ // for each query, and only deleted in the destructor.
+
+ void FreePairsList();
+
+ // query results
+
+ int Colliding() { return (num_pairs > 0); }
+ int NumPairs() { return num_pairs; }
+ int Id1(int k) { return pairs[k].id1; }
+ int Id2(int k) { return pairs[k].id2; }
+};
+
+#if PQP_BV_TYPE & RSS_TYPE // distance/tolerance are only available with RSS
+
+struct PQP_DistanceResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ PQP_REAL rel_err;
+ PQP_REAL abs_err;
+
+ PQP_REAL distance;
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ int qsize;
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // The following distance and points established the minimum distance
+ // for the models, within the relative and absolute error bounds
+ // specified.
+ // Points are defined: PQP_REAL p1[3], p2[3];
+
+ PQP_REAL Distance() { return distance; }
+ const PQP_REAL *P1() { return p1; }
+ const PQP_REAL *P2() { return p2; }
+};
+
+struct PQP_ToleranceResult
+{
+ // stats
+
+ int num_bv_tests;
+ int num_tri_tests;
+ double query_time_secs;
+
+ // xform from model 1 to model 2
+
+ PQP_REAL R[3][3];
+ PQP_REAL T[3];
+
+ int closer_than_tolerance;
+ PQP_REAL tolerance;
+
+ PQP_REAL distance;
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ int qsize;
+
+ // statistics
+
+ int NumBVTests() { return num_bv_tests; }
+ int NumTriTests() { return num_tri_tests; }
+ double QueryTimeSecs() { return query_time_secs; }
+
+ // If the models are closer than ( <= ) tolerance, these points
+ // and distance were what established this. Otherwise,
+ // distance and point values are not meaningful.
+
+ PQP_REAL Distance() { return distance; }
+ const PQP_REAL *P1() { return p1; }
+ const PQP_REAL *P2() { return p2; }
+
+ // boolean says whether models are closer than tolerance distance
+
+ int CloserThanTolerance() { return closer_than_tolerance; }
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/RectDist.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/RectDist.h
new file mode 100644
index 00000000..429d2c71
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/RectDist.h
@@ -0,0 +1,753 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_RECTDIST_H
+#define PQP_RECTDIST_H
+
+#include <math.h>
+#include "MatVec.h"
+#include "PQP_Compile.h"
+
+// ClipToRange
+//
+// clips val between a and b
+
+inline
+void
+ClipToRange(PQP_REAL &val, const PQP_REAL &a, const PQP_REAL &b)
+{
+ if (val < a) val = a;
+ else if (val > b) val = b;
+}
+
+// SegCoords
+//
+// finds the parameters t & u corresponding to the two closest points
+// on a pair of line segments
+//
+// The first segment is defined as
+//
+// Pa + A*t, 0 <= t <= a,
+//
+// where "Pa" is one endpoint of the segment, "A" is a unit vector
+// pointing to the other endpoint, and t is a scalar that produces
+// all the points between the two endpoints. Since "A" is a unit
+// vector, "a" is the segment's length.
+//
+// The second segment is
+//
+// Pb + B*u, 0 <= u <= b
+//
+// In my application, many of the terms needed by the algorithm
+// are already computed for other purposes, so I pass these terms to
+// the function instead of complete specifications of each segment.
+// "T" in the dot products is the vector between Pa and Pb.
+//
+// The algorithm is from
+//
+// Vladimir J. Lumelsky,
+// On fast computation of distance between line segments.
+// In Information Processing Letters, no. 21, pages 55-61, 1985.
+
+inline
+void
+SegCoords(PQP_REAL& t, PQP_REAL& u,
+ const PQP_REAL& a, const PQP_REAL& b,
+ const PQP_REAL& A_dot_B,
+ const PQP_REAL& A_dot_T,
+ const PQP_REAL& B_dot_T)
+{
+ PQP_REAL denom = 1 - (A_dot_B)*(A_dot_B);
+
+ if (denom == 0) t = 0;
+ else
+ {
+ t = (A_dot_T - B_dot_T*A_dot_B)/denom;
+ ClipToRange(t,0,a);
+ }
+
+ u = t*A_dot_B - B_dot_T;
+ if (u < 0)
+ {
+ u = 0;
+ t = A_dot_T;
+ ClipToRange(t,0,a);
+ }
+ else if (u > b)
+ {
+ u = b;
+ t = u*A_dot_B + A_dot_T;
+ ClipToRange(t,0,a);
+ }
+}
+
+// InVoronoi
+//
+// returns whether the nearest point on rectangle edge
+// Pb + B*u, 0 <= u <= b, to the rectangle edge,
+// Pa + A*t, 0 <= t <= a, is within the half space
+// determined by the point Pa and the direction Anorm.
+//
+// A,B, and Anorm are unit vectors.
+// T is the vector between Pa and Pb.
+
+inline
+int
+InVoronoi(const PQP_REAL &a,
+ const PQP_REAL &b,
+ const PQP_REAL &Anorm_dot_B,
+ const PQP_REAL &Anorm_dot_T,
+ const PQP_REAL &A_dot_B,
+ const PQP_REAL &A_dot_T,
+ const PQP_REAL &B_dot_T)
+{
+ if (myfabs(Anorm_dot_B) < 1e-7) return 0;
+
+ PQP_REAL t, u, v;
+
+ u = -Anorm_dot_T / Anorm_dot_B;
+ ClipToRange(u,0,b);
+
+ t = u*A_dot_B + A_dot_T;
+ ClipToRange(t,0,a);
+
+ v = t*A_dot_B - B_dot_T;
+
+ if (Anorm_dot_B > 0)
+ {
+ if (v > (u + 1e-7)) return 1;
+ }
+ else
+ {
+ if (v < (u - 1e-7)) return 1;
+ }
+ return 0;
+}
+
+
+// RectDist
+//
+// Finds the distance between two rectangles A and B. A is assumed
+// to have its corner on the origin, one side aligned with
+// x, the other side aligned with y, and its normal aligned with z.
+//
+// [Rab,Tab] gives the orientation and corner position of rectangle B
+//
+// a[2] are the side lengths of A, b[2] are the side lengths of B
+
+inline
+PQP_REAL
+RectDist(PQP_REAL Rab[3][3], PQP_REAL Tab[3],
+ PQP_REAL a[2], PQP_REAL b[2])
+{
+ PQP_REAL A0_dot_B0, A0_dot_B1, A1_dot_B0, A1_dot_B1;
+
+ A0_dot_B0 = Rab[0][0];
+ A0_dot_B1 = Rab[0][1];
+ A1_dot_B0 = Rab[1][0];
+ A1_dot_B1 = Rab[1][1];
+
+ PQP_REAL aA0_dot_B0, aA0_dot_B1, aA1_dot_B0, aA1_dot_B1;
+ PQP_REAL bA0_dot_B0, bA0_dot_B1, bA1_dot_B0, bA1_dot_B1;
+
+ aA0_dot_B0 = a[0]*A0_dot_B0;
+ aA0_dot_B1 = a[0]*A0_dot_B1;
+ aA1_dot_B0 = a[1]*A1_dot_B0;
+ aA1_dot_B1 = a[1]*A1_dot_B1;
+ bA0_dot_B0 = b[0]*A0_dot_B0;
+ bA1_dot_B0 = b[0]*A1_dot_B0;
+ bA0_dot_B1 = b[1]*A0_dot_B1;
+ bA1_dot_B1 = b[1]*A1_dot_B1;
+
+ PQP_REAL Tba[3];
+ MTxV(Tba,Rab,Tab);
+
+ PQP_REAL S[3], t, u;
+
+ // determine if any edge pair contains the closest points
+
+ PQP_REAL ALL_x, ALU_x, AUL_x, AUU_x;
+ PQP_REAL BLL_x, BLU_x, BUL_x, BUU_x;
+ PQP_REAL LA1_lx, LA1_ux, UA1_lx, UA1_ux, LB1_lx, LB1_ux, UB1_lx, UB1_ux;
+
+ ALL_x = -Tba[0];
+ ALU_x = ALL_x + aA1_dot_B0;
+ AUL_x = ALL_x + aA0_dot_B0;
+ AUU_x = ALU_x + aA0_dot_B0;
+
+ if (ALL_x < ALU_x)
+ {
+ LA1_lx = ALL_x;
+ LA1_ux = ALU_x;
+ UA1_lx = AUL_x;
+ UA1_ux = AUU_x;
+ }
+ else
+ {
+ LA1_lx = ALU_x;
+ LA1_ux = ALL_x;
+ UA1_lx = AUU_x;
+ UA1_ux = AUL_x;
+ }
+
+ BLL_x = Tab[0];
+ BLU_x = BLL_x + bA0_dot_B1;
+ BUL_x = BLL_x + bA0_dot_B0;
+ BUU_x = BLU_x + bA0_dot_B0;
+
+ if (BLL_x < BLU_x)
+ {
+ LB1_lx = BLL_x;
+ LB1_ux = BLU_x;
+ UB1_lx = BUL_x;
+ UB1_ux = BUU_x;
+ }
+ else
+ {
+ LB1_lx = BLU_x;
+ LB1_ux = BLL_x;
+ UB1_lx = BUU_x;
+ UB1_ux = BUL_x;
+ }
+
+ // UA1, UB1
+
+ if ((UA1_ux > b[0]) && (UB1_ux > a[0]))
+ {
+ if (((UA1_lx > b[0]) ||
+ InVoronoi(b[1],a[1],A1_dot_B0,aA0_dot_B0 - b[0] - Tba[0],
+ A1_dot_B1, aA0_dot_B1 - Tba[1],
+ -Tab[1] - bA1_dot_B0))
+ &&
+
+ ((UB1_lx > a[0]) ||
+ InVoronoi(a[1],b[1],A0_dot_B1,Tab[0] + bA0_dot_B0 - a[0],
+ A1_dot_B1,Tab[1] + bA1_dot_B0,Tba[1] - aA0_dot_B1)))
+ {
+ SegCoords(t,u,a[1],b[1],A1_dot_B1,Tab[1] + bA1_dot_B0,
+ Tba[1] - aA0_dot_B1);
+
+ S[0] = Tab[0] + Rab[0][0]*b[0] + Rab[0][1]*u - a[0] ;
+ S[1] = Tab[1] + Rab[1][0]*b[0] + Rab[1][1]*u - t;
+ S[2] = Tab[2] + Rab[2][0]*b[0] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+
+ // UA1, LB1
+
+ if ((UA1_lx < 0) && (LB1_ux > a[0]))
+ {
+ if (((UA1_ux < 0) ||
+ InVoronoi(b[1],a[1],-A1_dot_B0,Tba[0] - aA0_dot_B0,
+ A1_dot_B1, aA0_dot_B1 - Tba[1], -Tab[1]))
+ &&
+
+ ((LB1_lx > a[0]) ||
+ InVoronoi(a[1],b[1],A0_dot_B1,Tab[0] - a[0],
+ A1_dot_B1,Tab[1],Tba[1] - aA0_dot_B1)))
+ {
+ SegCoords(t,u,a[1],b[1],A1_dot_B1,Tab[1],Tba[1] - aA0_dot_B1);
+
+ S[0] = Tab[0] + Rab[0][1]*u - a[0];
+ S[1] = Tab[1] + Rab[1][1]*u - t;
+ S[2] = Tab[2] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA1, UB1
+
+ if ((LA1_ux > b[0]) && (UB1_lx < 0))
+ {
+ if (((LA1_lx > b[0]) ||
+ InVoronoi(b[1],a[1],A1_dot_B0,-Tba[0] - b[0],
+ A1_dot_B1,-Tba[1], -Tab[1] - bA1_dot_B0))
+ &&
+
+ ((UB1_ux < 0) ||
+ InVoronoi(a[1],b[1],-A0_dot_B1, -Tab[0] - bA0_dot_B0,
+ A1_dot_B1, Tab[1] + bA1_dot_B0,Tba[1])))
+ {
+
+ SegCoords(t,u,a[1],b[1],A1_dot_B1,Tab[1] + bA1_dot_B0,Tba[1]);
+
+ S[0] = Tab[0] + Rab[0][0]*b[0] + Rab[0][1]*u;
+ S[1] = Tab[1] + Rab[1][0]*b[0] + Rab[1][1]*u - t;
+ S[2] = Tab[2] + Rab[2][0]*b[0] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA1, LB1
+
+ if ((LA1_lx < 0) && (LB1_lx < 0))
+ {
+ if (((LA1_ux < 0) ||
+ InVoronoi(b[1],a[1],-A1_dot_B0,Tba[0],A1_dot_B1,
+ -Tba[1],-Tab[1]))
+ &&
+
+ ((LB1_ux < 0) ||
+ InVoronoi(a[1],b[1],-A0_dot_B1,-Tab[0],A1_dot_B1,
+ Tab[1], Tba[1])))
+ {
+ SegCoords(t,u,a[1],b[1],A1_dot_B1,Tab[1],Tba[1]);
+
+ S[0] = Tab[0] + Rab[0][1]*u;
+ S[1] = Tab[1] + Rab[1][1]*u - t;
+ S[2] = Tab[2] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ PQP_REAL ALL_y, ALU_y, AUL_y, AUU_y;
+
+ ALL_y = -Tba[1];
+ ALU_y = ALL_y + aA1_dot_B1;
+ AUL_y = ALL_y + aA0_dot_B1;
+ AUU_y = ALU_y + aA0_dot_B1;
+
+ PQP_REAL LA1_ly, LA1_uy, UA1_ly, UA1_uy, LB0_lx, LB0_ux, UB0_lx, UB0_ux;
+
+ if (ALL_y < ALU_y)
+ {
+ LA1_ly = ALL_y;
+ LA1_uy = ALU_y;
+ UA1_ly = AUL_y;
+ UA1_uy = AUU_y;
+ }
+ else
+ {
+ LA1_ly = ALU_y;
+ LA1_uy = ALL_y;
+ UA1_ly = AUU_y;
+ UA1_uy = AUL_y;
+ }
+
+ if (BLL_x < BUL_x)
+ {
+ LB0_lx = BLL_x;
+ LB0_ux = BUL_x;
+ UB0_lx = BLU_x;
+ UB0_ux = BUU_x;
+ }
+ else
+ {
+ LB0_lx = BUL_x;
+ LB0_ux = BLL_x;
+ UB0_lx = BUU_x;
+ UB0_ux = BLU_x;
+ }
+
+ // UA1, UB0
+
+ if ((UA1_uy > b[1]) && (UB0_ux > a[0]))
+ {
+ if (((UA1_ly > b[1]) ||
+ InVoronoi(b[0],a[1],A1_dot_B1, aA0_dot_B1 - Tba[1] - b[1],
+ A1_dot_B0, aA0_dot_B0 - Tba[0], -Tab[1] - bA1_dot_B1))
+ &&
+
+ ((UB0_lx > a[0]) ||
+ InVoronoi(a[1],b[0],A0_dot_B0, Tab[0] - a[0] + bA0_dot_B1,
+ A1_dot_B0, Tab[1] + bA1_dot_B1, Tba[0] - aA0_dot_B0)))
+ {
+ SegCoords(t,u,a[1],b[0],A1_dot_B0,Tab[1] + bA1_dot_B1,
+ Tba[0] - aA0_dot_B0);
+
+ S[0] = Tab[0] + Rab[0][1]*b[1] + Rab[0][0]*u - a[0] ;
+ S[1] = Tab[1] + Rab[1][1]*b[1] + Rab[1][0]*u - t;
+ S[2] = Tab[2] + Rab[2][1]*b[1] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // UA1, LB0
+
+ if ((UA1_ly < 0) && (LB0_ux > a[0]))
+ {
+ if (((UA1_uy < 0) ||
+ InVoronoi(b[0],a[1],-A1_dot_B1, Tba[1] - aA0_dot_B1,A1_dot_B0,
+ aA0_dot_B0 - Tba[0], -Tab[1]))
+ &&
+
+ ((LB0_lx > a[0]) ||
+ InVoronoi(a[1],b[0],A0_dot_B0,Tab[0] - a[0],
+ A1_dot_B0,Tab[1],Tba[0] - aA0_dot_B0)))
+ {
+ SegCoords(t,u,a[1],b[0],A1_dot_B0,Tab[1],Tba[0] - aA0_dot_B0);
+
+ S[0] = Tab[0] + Rab[0][0]*u - a[0];
+ S[1] = Tab[1] + Rab[1][0]*u - t;
+ S[2] = Tab[2] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA1, UB0
+
+ if ((LA1_uy > b[1]) && (UB0_lx < 0))
+ {
+ if (((LA1_ly > b[1]) ||
+ InVoronoi(b[0],a[1],A1_dot_B1,-Tba[1] - b[1],
+ A1_dot_B0, -Tba[0], -Tab[1] - bA1_dot_B1))
+ &&
+
+ ((UB0_ux < 0) ||
+ InVoronoi(a[1],b[0],-A0_dot_B0, -Tab[0] - bA0_dot_B1,A1_dot_B0,
+ Tab[1] + bA1_dot_B1,Tba[0])))
+ {
+ SegCoords(t,u,a[1],b[0],A1_dot_B0,Tab[1] + bA1_dot_B1,Tba[0]);
+
+ S[0] = Tab[0] + Rab[0][1]*b[1] + Rab[0][0]*u;
+ S[1] = Tab[1] + Rab[1][1]*b[1] + Rab[1][0]*u - t;
+ S[2] = Tab[2] + Rab[2][1]*b[1] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA1, LB0
+
+ if ((LA1_ly < 0) && (LB0_lx < 0))
+ {
+ if (((LA1_uy < 0) ||
+ InVoronoi(b[0],a[1],-A1_dot_B1,Tba[1],A1_dot_B0,
+ -Tba[0],-Tab[1]))
+ &&
+
+ ((LB0_ux < 0) ||
+ InVoronoi(a[1],b[0],-A0_dot_B0,-Tab[0],A1_dot_B0,
+ Tab[1],Tba[0])))
+ {
+ SegCoords(t,u,a[1],b[0],A1_dot_B0,Tab[1],Tba[0]);
+
+ S[0] = Tab[0] + Rab[0][0]*u;
+ S[1] = Tab[1] + Rab[1][0]*u - t;
+ S[2] = Tab[2] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ PQP_REAL BLL_y, BLU_y, BUL_y, BUU_y;
+
+ BLL_y = Tab[1];
+ BLU_y = BLL_y + bA1_dot_B1;
+ BUL_y = BLL_y + bA1_dot_B0;
+ BUU_y = BLU_y + bA1_dot_B0;
+
+ PQP_REAL LA0_lx, LA0_ux, UA0_lx, UA0_ux, LB1_ly, LB1_uy, UB1_ly, UB1_uy;
+
+ if (ALL_x < AUL_x)
+ {
+ LA0_lx = ALL_x;
+ LA0_ux = AUL_x;
+ UA0_lx = ALU_x;
+ UA0_ux = AUU_x;
+ }
+ else
+ {
+ LA0_lx = AUL_x;
+ LA0_ux = ALL_x;
+ UA0_lx = AUU_x;
+ UA0_ux = ALU_x;
+ }
+
+ if (BLL_y < BLU_y)
+ {
+ LB1_ly = BLL_y;
+ LB1_uy = BLU_y;
+ UB1_ly = BUL_y;
+ UB1_uy = BUU_y;
+ }
+ else
+ {
+ LB1_ly = BLU_y;
+ LB1_uy = BLL_y;
+ UB1_ly = BUU_y;
+ UB1_uy = BUL_y;
+ }
+
+ // UA0, UB1
+
+ if ((UA0_ux > b[0]) && (UB1_uy > a[1]))
+ {
+ if (((UA0_lx > b[0]) ||
+ InVoronoi(b[1],a[0],A0_dot_B0, aA1_dot_B0 - Tba[0] - b[0],
+ A0_dot_B1,aA1_dot_B1 - Tba[1], -Tab[0] - bA0_dot_B0))
+ &&
+
+ ((UB1_ly > a[1]) ||
+ InVoronoi(a[0],b[1],A1_dot_B1, Tab[1] - a[1] + bA1_dot_B0,
+ A0_dot_B1,Tab[0] + bA0_dot_B0, Tba[1] - aA1_dot_B1)))
+ {
+ SegCoords(t,u,a[0],b[1],A0_dot_B1,Tab[0] + bA0_dot_B0,
+ Tba[1] - aA1_dot_B1);
+
+ S[0] = Tab[0] + Rab[0][0]*b[0] + Rab[0][1]*u - t;
+ S[1] = Tab[1] + Rab[1][0]*b[0] + Rab[1][1]*u - a[1];
+ S[2] = Tab[2] + Rab[2][0]*b[0] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // UA0, LB1
+
+ if ((UA0_lx < 0) && (LB1_uy > a[1]))
+ {
+ if (((UA0_ux < 0) ||
+ InVoronoi(b[1],a[0],-A0_dot_B0, Tba[0] - aA1_dot_B0,A0_dot_B1,
+ aA1_dot_B1 - Tba[1],-Tab[0]))
+ &&
+
+ ((LB1_ly > a[1]) ||
+ InVoronoi(a[0],b[1],A1_dot_B1,Tab[1] - a[1],A0_dot_B1,Tab[0],
+ Tba[1] - aA1_dot_B1)))
+ {
+ SegCoords(t,u,a[0],b[1],A0_dot_B1,Tab[0],Tba[1] - aA1_dot_B1);
+
+ S[0] = Tab[0] + Rab[0][1]*u - t;
+ S[1] = Tab[1] + Rab[1][1]*u - a[1];
+ S[2] = Tab[2] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA0, UB1
+
+ if ((LA0_ux > b[0]) && (UB1_ly < 0))
+ {
+ if (((LA0_lx > b[0]) ||
+ InVoronoi(b[1],a[0],A0_dot_B0,-b[0] - Tba[0],A0_dot_B1,-Tba[1],
+ -bA0_dot_B0 - Tab[0]))
+ &&
+
+ ((UB1_uy < 0) ||
+ InVoronoi(a[0],b[1],-A1_dot_B1, -Tab[1] - bA1_dot_B0,A0_dot_B1,
+ Tab[0] + bA0_dot_B0,Tba[1])))
+ {
+ SegCoords(t,u,a[0],b[1],A0_dot_B1,Tab[0] + bA0_dot_B0,Tba[1]);
+
+ S[0] = Tab[0] + Rab[0][0]*b[0] + Rab[0][1]*u - t;
+ S[1] = Tab[1] + Rab[1][0]*b[0] + Rab[1][1]*u;
+ S[2] = Tab[2] + Rab[2][0]*b[0] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA0, LB1
+
+ if ((LA0_lx < 0) && (LB1_ly < 0))
+ {
+ if (((LA0_ux < 0) ||
+ InVoronoi(b[1],a[0],-A0_dot_B0,Tba[0],A0_dot_B1,-Tba[1],
+ -Tab[0]))
+ &&
+
+ ((LB1_uy < 0) ||
+ InVoronoi(a[0],b[1],-A1_dot_B1,-Tab[1],A0_dot_B1,
+ Tab[0],Tba[1])))
+ {
+ SegCoords(t,u,a[0],b[1],A0_dot_B1,Tab[0],Tba[1]);
+
+ S[0] = Tab[0] + Rab[0][1]*u - t;
+ S[1] = Tab[1] + Rab[1][1]*u;
+ S[2] = Tab[2] + Rab[2][1]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ PQP_REAL LA0_ly, LA0_uy, UA0_ly, UA0_uy, LB0_ly, LB0_uy, UB0_ly, UB0_uy;
+
+ if (ALL_y < AUL_y)
+ {
+ LA0_ly = ALL_y;
+ LA0_uy = AUL_y;
+ UA0_ly = ALU_y;
+ UA0_uy = AUU_y;
+ }
+ else
+ {
+ LA0_ly = AUL_y;
+ LA0_uy = ALL_y;
+ UA0_ly = AUU_y;
+ UA0_uy = ALU_y;
+ }
+
+ if (BLL_y < BUL_y)
+ {
+ LB0_ly = BLL_y;
+ LB0_uy = BUL_y;
+ UB0_ly = BLU_y;
+ UB0_uy = BUU_y;
+ }
+ else
+ {
+ LB0_ly = BUL_y;
+ LB0_uy = BLL_y;
+ UB0_ly = BUU_y;
+ UB0_uy = BLU_y;
+ }
+
+ // UA0, UB0
+
+ if ((UA0_uy > b[1]) && (UB0_uy > a[1]))
+ {
+ if (((UA0_ly > b[1]) ||
+ InVoronoi(b[0],a[0],A0_dot_B1, aA1_dot_B1 - Tba[1] - b[1],
+ A0_dot_B0, aA1_dot_B0 - Tba[0], -Tab[0] - bA0_dot_B1))
+ &&
+
+ ((UB0_ly > a[1]) ||
+ InVoronoi(a[0],b[0],A1_dot_B0,Tab[1] - a[1] + bA1_dot_B1,A0_dot_B0,
+ Tab[0] + bA0_dot_B1, Tba[0] - aA1_dot_B0)))
+ {
+ SegCoords(t,u,a[0],b[0],A0_dot_B0,Tab[0] + bA0_dot_B1,
+ Tba[0] - aA1_dot_B0);
+
+ S[0] = Tab[0] + Rab[0][1]*b[1] + Rab[0][0]*u - t;
+ S[1] = Tab[1] + Rab[1][1]*b[1] + Rab[1][0]*u - a[1];
+ S[2] = Tab[2] + Rab[2][1]*b[1] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // UA0, LB0
+
+ if ((UA0_ly < 0) && (LB0_uy > a[1]))
+ {
+ if (((UA0_uy < 0) ||
+ InVoronoi(b[0],a[0],-A0_dot_B1,Tba[1] - aA1_dot_B1,A0_dot_B0,
+ aA1_dot_B0 - Tba[0],-Tab[0]))
+ &&
+
+ ((LB0_ly > a[1]) ||
+ InVoronoi(a[0],b[0],A1_dot_B0,Tab[1] - a[1],
+ A0_dot_B0,Tab[0],Tba[0] - aA1_dot_B0)))
+ {
+ SegCoords(t,u,a[0],b[0],A0_dot_B0,Tab[0],Tba[0] - aA1_dot_B0);
+
+ S[0] = Tab[0] + Rab[0][0]*u - t;
+ S[1] = Tab[1] + Rab[1][0]*u - a[1];
+ S[2] = Tab[2] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA0, UB0
+
+ if ((LA0_uy > b[1]) && (UB0_ly < 0))
+ {
+ if (((LA0_ly > b[1]) ||
+ InVoronoi(b[0],a[0],A0_dot_B1,-Tba[1] - b[1], A0_dot_B0,-Tba[0],
+ -Tab[0] - bA0_dot_B1))
+ &&
+
+ ((UB0_uy < 0) ||
+ InVoronoi(a[0],b[0],-A1_dot_B0, -Tab[1] - bA1_dot_B1, A0_dot_B0,
+ Tab[0] + bA0_dot_B1,Tba[0])))
+ {
+ SegCoords(t,u,a[0],b[0],A0_dot_B0,Tab[0] + bA0_dot_B1,Tba[0]);
+
+ S[0] = Tab[0] + Rab[0][1]*b[1] + Rab[0][0]*u - t;
+ S[1] = Tab[1] + Rab[1][1]*b[1] + Rab[1][0]*u;
+ S[2] = Tab[2] + Rab[2][1]*b[1] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // LA0, LB0
+
+ if ((LA0_ly < 0) && (LB0_ly < 0))
+ {
+ if (((LA0_uy < 0) ||
+ InVoronoi(b[0],a[0],-A0_dot_B1,Tba[1],A0_dot_B0,
+ -Tba[0],-Tab[0]))
+ &&
+
+ ((LB0_uy < 0) ||
+ InVoronoi(a[0],b[0],-A1_dot_B0,-Tab[1],A0_dot_B0,
+ Tab[0],Tba[0])))
+ {
+ SegCoords(t,u,a[0],b[0],A0_dot_B0,Tab[0],Tba[0]);
+
+ S[0] = Tab[0] + Rab[0][0]*u - t;
+ S[1] = Tab[1] + Rab[1][0]*u;
+ S[2] = Tab[2] + Rab[2][0]*u;
+ return sqrt(VdotV(S,S));
+ }
+ }
+
+ // no edges passed, take max separation along face normals
+
+ PQP_REAL sep1, sep2;
+
+ if (Tab[2] > 0.0)
+ {
+ sep1 = Tab[2];
+ if (Rab[2][0] < 0.0) sep1 += b[0]*Rab[2][0];
+ if (Rab[2][1] < 0.0) sep1 += b[1]*Rab[2][1];
+ }
+ else
+ {
+ sep1 = -Tab[2];
+ if (Rab[2][0] > 0.0) sep1 -= b[0]*Rab[2][0];
+ if (Rab[2][1] > 0.0) sep1 -= b[1]*Rab[2][1];
+ }
+
+ if (Tba[2] < 0)
+ {
+ sep2 = -Tba[2];
+ if (Rab[0][2] < 0.0) sep2 += a[0]*Rab[0][2];
+ if (Rab[1][2] < 0.0) sep2 += a[1]*Rab[1][2];
+ }
+ else
+ {
+ sep2 = Tba[2];
+ if (Rab[0][2] > 0.0) sep2 -= a[0]*Rab[0][2];
+ if (Rab[1][2] > 0.0) sep2 -= a[1]*Rab[1][2];
+ }
+
+ PQP_REAL sep = (sep1 > sep2? sep1 : sep2);
+ return (sep > 0? sep : 0);
+}
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Tri.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Tri.h
new file mode 100644
index 00000000..496cddd9
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/Tri.h
@@ -0,0 +1,54 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: S. Gottschalk
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_TRI_H
+#define PQP_TRI_H
+
+#include "PQP_Compile.h"
+
+struct Tri
+{
+ PQP_REAL p1[3];
+ PQP_REAL p2[3];
+ PQP_REAL p3[3];
+ int id;
+};
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.cpp b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.cpp
new file mode 100644
index 00000000..3cbd438b
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.cpp
@@ -0,0 +1,407 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+//--------------------------------------------------------------------------
+// File: TriDist.cpp
+// Author: Eric Larsen
+// Description:
+// contains SegPoints() for finding closest points on a pair of line
+// segments and TriDist() for finding closest points on a pair of triangles
+//--------------------------------------------------------------------------
+
+#include "MatVec.h"
+#ifdef _WIN32
+#include <float.h>
+#define isnan _isnan
+#endif
+
+//--------------------------------------------------------------------------
+// SegPoints()
+//
+// Returns closest points between an segment pair.
+// Implemented from an algorithm described in
+//
+// Vladimir J. Lumelsky,
+// On fast computation of distance between line segments.
+// In Information Processing Letters, no. 21, pages 55-61, 1985.
+//--------------------------------------------------------------------------
+
+void
+SegPoints(PQP_REAL VEC[3],
+ PQP_REAL X[3], PQP_REAL Y[3], // closest points
+ const PQP_REAL P[3], const PQP_REAL A[3], // seg 1 origin, vector
+ const PQP_REAL Q[3], const PQP_REAL B[3]) // seg 2 origin, vector
+{
+ PQP_REAL T[3], A_dot_A, B_dot_B, A_dot_B, A_dot_T, B_dot_T;
+ PQP_REAL TMP[3];
+
+ VmV(T,Q,P);
+ A_dot_A = VdotV(A,A);
+ B_dot_B = VdotV(B,B);
+ A_dot_B = VdotV(A,B);
+ A_dot_T = VdotV(A,T);
+ B_dot_T = VdotV(B,T);
+
+ // t parameterizes ray P,A
+ // u parameterizes ray Q,B
+
+ PQP_REAL t,u;
+
+ // compute t for the closest point on ray P,A to
+ // ray Q,B
+
+ PQP_REAL denom = A_dot_A*B_dot_B - A_dot_B*A_dot_B;
+
+ t = (A_dot_T*B_dot_B - B_dot_T*A_dot_B) / denom;
+
+ // clamp result so t is on the segment P,A
+
+ if ((t < 0) || isnan(t)) t = 0; else if (t > 1) t = 1;
+
+ // find u for point on ray Q,B closest to point at t
+
+ u = (t*A_dot_B - B_dot_T) / B_dot_B;
+
+ // if u is on segment Q,B, t and u correspond to
+ // closest points, otherwise, clamp u, recompute and
+ // clamp t
+
+ if ((u <= 0) || isnan(u)) {
+
+ VcV(Y, Q);
+
+ t = A_dot_T / A_dot_A;
+
+ if ((t <= 0) || isnan(t)) {
+ VcV(X, P);
+ VmV(VEC, Q, P);
+ }
+ else if (t >= 1) {
+ VpV(X, P, A);
+ VmV(VEC, Q, X);
+ }
+ else {
+ VpVxS(X, P, A, t);
+ VcrossV(TMP, T, A);
+ VcrossV(VEC, A, TMP);
+ }
+ }
+ else if (u >= 1) {
+
+ VpV(Y, Q, B);
+
+ t = (A_dot_B + A_dot_T) / A_dot_A;
+
+ if ((t <= 0) || isnan(t)) {
+ VcV(X, P);
+ VmV(VEC, Y, P);
+ }
+ else if (t >= 1) {
+ VpV(X, P, A);
+ VmV(VEC, Y, X);
+ }
+ else {
+ VpVxS(X, P, A, t);
+ VmV(T, Y, P);
+ VcrossV(TMP, T, A);
+ VcrossV(VEC, A, TMP);
+ }
+ }
+ else {
+
+ VpVxS(Y, Q, B, u);
+
+ if ((t <= 0) || isnan(t)) {
+ VcV(X, P);
+ VcrossV(TMP, T, B);
+ VcrossV(VEC, B, TMP);
+ }
+ else if (t >= 1) {
+ VpV(X, P, A);
+ VmV(T, Q, X);
+ VcrossV(TMP, T, B);
+ VcrossV(VEC, B, TMP);
+ }
+ else {
+ VpVxS(X, P, A, t);
+ VcrossV(VEC, A, B);
+ if (VdotV(VEC, T) < 0) {
+ VxS(VEC, VEC, -1);
+ }
+ }
+ }
+}
+
+//--------------------------------------------------------------------------
+// TriDist()
+//
+// Computes the closest points on two triangles, and returns the
+// distance between them.
+//
+// S and T are the triangles, stored tri[point][dimension].
+//
+// If the triangles are disjoint, P and Q give the closest points of
+// S and T respectively. However, if the triangles overlap, P and Q
+// are basically a random pair of points from the triangles, not
+// coincident points on the intersection of the triangles, as might
+// be expected.
+//--------------------------------------------------------------------------
+
+PQP_REAL
+TriDist(PQP_REAL P[3], PQP_REAL Q[3],
+ const PQP_REAL S[3][3], const PQP_REAL T[3][3])
+{
+ // Compute vectors along the 6 sides
+
+ PQP_REAL Sv[3][3], Tv[3][3];
+ PQP_REAL VEC[3];
+
+ VmV(Sv[0],S[1],S[0]);
+ VmV(Sv[1],S[2],S[1]);
+ VmV(Sv[2],S[0],S[2]);
+
+ VmV(Tv[0],T[1],T[0]);
+ VmV(Tv[1],T[2],T[1]);
+ VmV(Tv[2],T[0],T[2]);
+
+ // For each edge pair, the vector connecting the closest points
+ // of the edges defines a slab (parallel planes at head and tail
+ // enclose the slab). If we can show that the off-edge vertex of
+ // each triangle is outside of the slab, then the closest points
+ // of the edges are the closest points for the triangles.
+ // Even if these tests fail, it may be helpful to know the closest
+ // points found, and whether the triangles were shown disjoint
+
+ PQP_REAL V[3];
+ PQP_REAL Z[3];
+ PQP_REAL minP[3], minQ[3], mindd;
+ int shown_disjoint = 0;
+
+ mindd = VdistV2(S[0],T[0]) + 1; // Set first minimum safely high
+
+ for (int i = 0; i < 3; i++)
+ {
+ for (int j = 0; j < 3; j++)
+ {
+ // Find closest points on edges i & j, plus the
+ // vector (and distance squared) between these points
+
+ SegPoints(VEC,P,Q,S[i],Sv[i],T[j],Tv[j]);
+
+ VmV(V,Q,P);
+ PQP_REAL dd = VdotV(V,V);
+
+ // Verify this closest point pair only if the distance
+ // squared is less than the minimum found thus far.
+
+ if (dd <= mindd)
+ {
+ VcV(minP,P);
+ VcV(minQ,Q);
+ mindd = dd;
+
+ VmV(Z,S[(i+2)%3],P);
+ PQP_REAL a = VdotV(Z,VEC);
+ VmV(Z,T[(j+2)%3],Q);
+ PQP_REAL b = VdotV(Z,VEC);
+
+ if ((a <= 0) && (b >= 0)) return sqrt(dd);
+
+ PQP_REAL p = VdotV(V, VEC);
+
+ if (a < 0) a = 0;
+ if (b > 0) b = 0;
+ if ((p - a + b) > 0) shown_disjoint = 1;
+ }
+ }
+ }
+
+ // No edge pairs contained the closest points.
+ // either:
+ // 1. one of the closest points is a vertex, and the
+ // other point is interior to a face.
+ // 2. the triangles are overlapping.
+ // 3. an edge of one triangle is parallel to the other's face. If
+ // cases 1 and 2 are not true, then the closest points from the 9
+ // edge pairs checks above can be taken as closest points for the
+ // triangles.
+ // 4. possibly, the triangles were degenerate. When the
+ // triangle points are nearly colinear or coincident, one
+ // of above tests might fail even though the edges tested
+ // contain the closest points.
+
+ // First check for case 1
+
+ PQP_REAL Sn[3], Snl;
+ VcrossV(Sn,Sv[0],Sv[1]); // Compute normal to S triangle
+ Snl = VdotV(Sn,Sn); // Compute square of length of normal
+
+ // If cross product is long enough,
+
+ if (Snl > 1e-15)
+ {
+ // Get projection lengths of T points
+
+ PQP_REAL Tp[3];
+
+ VmV(V,S[0],T[0]);
+ Tp[0] = VdotV(V,Sn);
+
+ VmV(V,S[0],T[1]);
+ Tp[1] = VdotV(V,Sn);
+
+ VmV(V,S[0],T[2]);
+ Tp[2] = VdotV(V,Sn);
+
+ // If Sn is a separating direction,
+ // find point with smallest projection
+
+ int point = -1;
+ if ((Tp[0] > 0) && (Tp[1] > 0) && (Tp[2] > 0))
+ {
+ if (Tp[0] < Tp[1]) point = 0; else point = 1;
+ if (Tp[2] < Tp[point]) point = 2;
+ }
+ else if ((Tp[0] < 0) && (Tp[1] < 0) && (Tp[2] < 0))
+ {
+ if (Tp[0] > Tp[1]) point = 0; else point = 1;
+ if (Tp[2] > Tp[point]) point = 2;
+ }
+
+ // If Sn is a separating direction,
+
+ if (point >= 0)
+ {
+ shown_disjoint = 1;
+
+ // Test whether the point found, when projected onto the
+ // other triangle, lies within the face.
+
+ VmV(V,T[point],S[0]);
+ VcrossV(Z,Sn,Sv[0]);
+ if (VdotV(V,Z) > 0)
+ {
+ VmV(V,T[point],S[1]);
+ VcrossV(Z,Sn,Sv[1]);
+ if (VdotV(V,Z) > 0)
+ {
+ VmV(V,T[point],S[2]);
+ VcrossV(Z,Sn,Sv[2]);
+ if (VdotV(V,Z) > 0)
+ {
+ // T[point] passed the test - it's a closest point for
+ // the T triangle; the other point is on the face of S
+
+ VpVxS(P,T[point],Sn,Tp[point]/Snl);
+ VcV(Q,T[point]);
+ return sqrt(VdistV2(P,Q));
+ }
+ }
+ }
+ }
+ }
+
+ PQP_REAL Tn[3], Tnl;
+ VcrossV(Tn,Tv[0],Tv[1]);
+ Tnl = VdotV(Tn,Tn);
+
+ if (Tnl > 1e-15)
+ {
+ PQP_REAL Sp[3];
+
+ VmV(V,T[0],S[0]);
+ Sp[0] = VdotV(V,Tn);
+
+ VmV(V,T[0],S[1]);
+ Sp[1] = VdotV(V,Tn);
+
+ VmV(V,T[0],S[2]);
+ Sp[2] = VdotV(V,Tn);
+
+ int point = -1;
+ if ((Sp[0] > 0) && (Sp[1] > 0) && (Sp[2] > 0))
+ {
+ if (Sp[0] < Sp[1]) point = 0; else point = 1;
+ if (Sp[2] < Sp[point]) point = 2;
+ }
+ else if ((Sp[0] < 0) && (Sp[1] < 0) && (Sp[2] < 0))
+ {
+ if (Sp[0] > Sp[1]) point = 0; else point = 1;
+ if (Sp[2] > Sp[point]) point = 2;
+ }
+
+ if (point >= 0)
+ {
+ shown_disjoint = 1;
+
+ VmV(V,S[point],T[0]);
+ VcrossV(Z,Tn,Tv[0]);
+ if (VdotV(V,Z) > 0)
+ {
+ VmV(V,S[point],T[1]);
+ VcrossV(Z,Tn,Tv[1]);
+ if (VdotV(V,Z) > 0)
+ {
+ VmV(V,S[point],T[2]);
+ VcrossV(Z,Tn,Tv[2]);
+ if (VdotV(V,Z) > 0)
+ {
+ VcV(P,S[point]);
+ VpVxS(Q,S[point],Tn,Sp[point]/Tnl);
+ return sqrt(VdistV2(P,Q));
+ }
+ }
+ }
+ }
+ }
+
+ // Case 1 can't be shown.
+ // If one of these tests showed the triangles disjoint,
+ // we assume case 3 or 4, otherwise we conclude case 2,
+ // that the triangles overlap.
+
+ if (shown_disjoint)
+ {
+ VcV(P,minP);
+ VcV(Q,minQ);
+ return sqrt(mindd);
+ }
+ else return 0;
+}
diff --git a/trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.h b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.h
new file mode 100644
index 00000000..dd20a8c3
--- /dev/null
+++ b/trunk/PQP/build/pqp-tar/PQP_v1.3/src/TriDist.h
@@ -0,0 +1,63 @@
+/*************************************************************************\
+
+ Copyright 1999 The University of North Carolina at Chapel Hill.
+ All Rights Reserved.
+
+ Permission to use, copy, modify and distribute this software and its
+ documentation for educational, research and non-profit purposes, without
+ fee, and without a written agreement is hereby granted, provided that the
+ above copyright notice and the following three paragraphs appear in all
+ copies.
+
+ IN NO EVENT SHALL THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL BE
+ LIABLE TO ANY PARTY FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR
+ CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE
+ USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE UNIVERSITY
+ OF NORTH CAROLINA HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH
+ DAMAGES.
+
+ THE UNIVERSITY OF NORTH CAROLINA SPECIFICALLY DISCLAIM ANY
+ WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
+ MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE
+ PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF
+ NORTH CAROLINA HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT,
+ UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
+
+ The authors may be contacted via:
+
+ US Mail: E. Larsen
+ Department of Computer Science
+ Sitterson Hall, CB #3175
+ University of N. Carolina
+ Chapel Hill, NC 27599-3175
+
+ Phone: (919)962-1749
+
+ EMail: geom@cs.unc.edu
+
+
+\**************************************************************************/
+
+#ifndef PQP_TRIDIST_H
+#define PQP_TRIDIST_H
+
+#include "PQP_Compile.h"
+
+// TriDist()
+//
+// computes the closest points on two triangles, and returns the
+// distance between them.
+//
+// s and t are the triangles, stored tri[point][dimension].
+//
+// If the triangles are disjoint, p and q give the closest points of
+// s and t respectively. However, if the triangles overlap, p and q
+// are basically a random pair of points from the triangles, not
+// coincident points on the intersection of the triangles, as might
+// be expected.
+
+PQP_REAL
+TriDist(PQP_REAL p[3], PQP_REAL q[3],
+ const PQP_REAL s[3][3], const PQP_REAL t[3][3]);
+
+#endif
diff --git a/trunk/PQP/build/pqp-tar/unpacked b/trunk/PQP/build/pqp-tar/unpacked
new file mode 100644
index 00000000..e69de29b
diff --git a/trunk/PQP/installed b/trunk/PQP/installed
new file mode 100644
index 00000000..e69de29b
diff --git a/trunk/PQP/mainpage.dox b/trunk/PQP/mainpage.dox
new file mode 100644
index 00000000..c315b415
--- /dev/null
+++ b/trunk/PQP/mainpage.dox
@@ -0,0 +1,26 @@
+/**
+\mainpage
+\htmlinclude manifest.html
+
+\b PQP is ...
+
+<!--
+Provide an overview of your package.
+-->
+
+
+\section codeapi Code API
+
+<!--
+Provide links to specific auto-generated API documentation within your
+package that is of particular interest to a reader. Doxygen will
+document pretty much every part of your code, so do your best here to
+point the reader to the actual API.
+
+If your codebase is fairly large or has different sets of APIs, you
+should use the doxygen 'group' tag to keep these APIs together. For
+example, the roscpp documentation has 'libros' group.
+-->
+
+
+*/
diff --git a/trunk/PQP/manifest.xml b/trunk/PQP/manifest.xml
new file mode 100644
index 00000000..6e801466
--- /dev/null
+++ b/trunk/PQP/manifest.xml
@@ -0,0 +1,15 @@
+<package>
+ <description brief="PQP">
+ This package is a wrapper on the PQP library available from <a href="http://gamma.cs.unc.edu/software/downloads/SSV">here</a>. This package does not modify the contents of the original library in any manner and only wraps it for easy distribution with the ROS packaging system. PQP is not under BSD license and is optional for FCL. Users can choose to use PQP by setting flag USE_PQP=1 in FCL.
+ </description>
+ <author>Maintained by Jia Pan and Sachin Chitta</author>
+ <license>BSD</license>
+ <review status="unreviewed" notes=""/>
+ <url>http://ros.org/wiki/PQP</url>
+ <export>
+ <cpp cflags="-I${prefix}/PQP/include" lflags="-L${prefix}/PQP/lib -Wl,-rpath,${prefix}/PQP/lib -lPQP"/>
+ </export>
+
+</package>
+
+
diff --git a/trunk/PQP/pqp.diff b/trunk/PQP/pqp.diff
new file mode 100644
index 00000000..9a972d99
--- /dev/null
+++ b/trunk/PQP/pqp.diff
@@ -0,0 +1,10 @@
+--- PQP_v1.3/Makefile 2002-04-21 12:55:38.000000000 -0400
++++ PQP_v1.3/Makefile 2011-09-06 23:17:24.535133167 -0400
+@@ -1,6 +1,6 @@
+ CC = g++
+
+-CFLAGS = -O2 -I.
++CFLAGS = -O2 -fPIC -I.
+
+ .SUFFIXES: .C .cpp
+
diff --git a/trunk/PQP/wiped b/trunk/PQP/wiped
new file mode 100644
index 00000000..e69de29b
diff --git a/trunk/fcl/include/fcl/broad_phase_collision.h b/trunk/fcl/include/fcl/broad_phase_collision.h
index 8d670ea9..13127a34 100644
--- a/trunk/fcl/include/fcl/broad_phase_collision.h
+++ b/trunk/fcl/include/fcl/broad_phase_collision.h
@@ -56,60 +56,84 @@ bool defaultCollisionFunction(CollisionObject* o1, CollisionObject* o2, void* cd
/** \brief return value is whether can stop now */
typedef bool (*CollisionCallBack)(CollisionObject* o1, CollisionObject* o2, void* cdata);
+/** \brief Base class for broad phase collision */
class BroadPhaseCollisionManager
{
public:
+ /** \brief add one object to the manager */
virtual void registerObject(CollisionObject* obj) = 0;
+ /** \brief remove one object from the manager */
virtual void unregisterObject(CollisionObject* obj) = 0;
+ /** \brief initialize the manager, related with the specific type of manager */
virtual void setup() = 0;
+ /** \brief update the condition of manager */
virtual void update() = 0;
+ /** \brief clear the manager */
virtual void clear() = 0;
+ /** \brief return the objects managed by the manager */
virtual void getObjects(std::vector<CollisionObject*>& objs) const = 0;
+ /** \brief perform collision test between one object and all the objects belonging to the manager */
virtual void collide(CollisionObject* obj, void* cdata, CollisionCallBack callback) const = 0;
+ /** \brief perform collision test for the objects belonging to the manager (i.e., N^2 self collision) */
virtual void collide(void* cdata, CollisionCallBack callback) const = 0;
+ /** \brief whether the manager is empty */
virtual bool empty() const = 0;
+ /** \brief the number of objects managed by the manager */
virtual size_t size() const = 0;
};
+/** \brief Brute force N-body collision manager */
class NaiveCollisionManager : public BroadPhaseCollisionManager
{
public:
NaiveCollisionManager() {}
- void unregisterObject(CollisionObject* obj);
-
+ /** \brief remove one object from the manager */
void registerObject(CollisionObject* obj);
+ /** \brief add one object to the manager */
+ void unregisterObject(CollisionObject* obj);
+
+ /** \brief initialize the manager, related with the specific type of manager */
void setup();
+ /** \brief update the condition of manager */
void update();
+ /** \brief clear the manager */
void clear();
+ /** \brief return the objects managed by the manager */
void getObjects(std::vector<CollisionObject*>& objs) const;
+ /** \brief perform collision test between one object and all the objects belonging to the manager */
void collide(CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
+ /** \brief perform collision test for the objects belonging to the manager (i.e., N^2 self collision) */
void collide(void* cdata, CollisionCallBack callback) const;
+ /** \brief whether the manager is empty */
bool empty() const;
+ /** \brief the number of objects managed by the manager */
inline size_t size() const { return objs.size(); }
protected:
+ /** \brief objects belonging to the manager are stored in a list structure */
std::list<CollisionObject*> objs;
};
+/** Rigorous SAP collision manager */
class SaPCollisionManager : public BroadPhaseCollisionManager
{
public:
@@ -126,50 +150,78 @@ public:
clear();
}
- void unregisterObject(CollisionObject* obj);
-
+ /** \brief remove one object from the manager */
void registerObject(CollisionObject* obj);
+ /** \brief add one object to the manager */
+ void unregisterObject(CollisionObject* obj);
+
+ /** \brief initialize the manager, related with the specific type of manager */
void setup();
+ /** \brief update the condition of manager */
void update();
+ /** \brief clear the manager */
void clear();
+ /** \brief return the objects managed by the manager */
void getObjects(std::vector<CollisionObject*>& objs) const;
+ /** \brief perform collision test between one object and all the objects belonging to the manager */
void collide(CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
+ /** \brief perform collision test for the objects belonging to the manager (i.e., N^2 self collision) */
void collide(void* cdata, CollisionCallBack callback) const;
+ /** \brief whether the manager is empty */
bool empty() const;
+ /** \brief the number of objects managed by the manager */
inline size_t size() const { return AABB_arr.size(); }
protected:
struct EndPoint;
+ /** \brief SAP interval for one object */
struct SaPAABB
{
+ /** \brief object */
CollisionObject* obj;
+
+ /** \brief lower bound end point of the interval */
EndPoint* lo;
+
+ /** \brief higher bound end point of the interval */
EndPoint* hi;
+
+ /** \brief cached AABB value */
AABB cached;
};
+ /** \brief End point for an interval */
struct EndPoint
{
+ /** \brief tag for whether it is a lower bound or higher bound of an interval, 0 for lo, and 1 for hi */
char minmax;
+
+ /** \brief back pointer to SAP interval */
SaPAABB* aabb;
+
+ /** \brief the previous end point in the end point list */
EndPoint* prev[3];
+ /** \brief the next end point in the end point list */
EndPoint* next[3];
+
+ /** \brief get the value of the end point */
const Vec3f& getVal() const
{
if(minmax == 0) return aabb->cached.min_;
else return aabb->cached.max_;
}
+ /** \brief set the value of the end point */
Vec3f& getVal()
{
if(minmax == 0) return aabb->cached.min_;
@@ -177,6 +229,7 @@ protected:
}
};
+ /** \brief A pair of objects that are not culling away and should further check collision */
struct SaPPair
{
SaPPair(CollisionObject* a, CollisionObject* b)
@@ -189,6 +242,7 @@ protected:
CollisionObject* obj2;
};
+ /** Functor to help unregister one object */
class isUnregistered
{
CollisionObject* obj;
@@ -205,6 +259,7 @@ protected:
}
};
+ /** Functor to help remove collision pairs no longer valid (i.e., should be culled away) */
class isNotValidPair
{
CollisionObject* obj1;
@@ -223,13 +278,17 @@ protected:
}
};
-
+ /** \brief End point list for x, y, z coordinates */
EndPoint* elist[3];
+
+ /** \brief SAP interval list */
std::list<SaPAABB*> AABB_arr;
+ /** \brief The pair of objects that should further check for collision */
std::list<SaPPair> overlap_pairs;
};
+/** Simple SAP collision manager */
class SSaPCollisionManager : public BroadPhaseCollisionManager
{
public:
@@ -238,28 +297,39 @@ public:
setup_ = false;
}
- void unregisterObject(CollisionObject* obj);
-
+ /** \brief remove one object from the manager */
void registerObject(CollisionObject* obj);
+ /** \brief add one object to the manager */
+ void unregisterObject(CollisionObject* obj);
+
+ /** \brief initialize the manager, related with the specific type of manager */
void setup();
+ /** \brief update the condition of manager */
void update();
+ /** \brief clear the manager */
void clear();
+ /** \brief return the objects managed by the manager */
void getObjects(std::vector<CollisionObject*>& objs) const;
+ /** \brief perform collision test between one object and all the objects belonging to the manager */
void collide(CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
+ /** \brief perform collision test for the objects belonging to the manager (i.e., N^2 self collision) */
void collide(void* cdata, CollisionCallBack callback) const;
+ /** \brief whether the manager is empty */
bool empty() const;
+ /** \brief the number of objects managed by the manager */
inline size_t size() const { return objs_x.size(); }
protected:
+ /** \brief Functor sorting objects according to the AABB lower x bound */
struct SortByXLow
{
bool operator()(const CollisionObject* a, const CollisionObject* b) const
@@ -270,6 +340,7 @@ protected:
}
};
+ /** \brief Functor sorting objects according to the AABB lower y bound */
struct SortByYLow
{
bool operator()(const CollisionObject* a, const CollisionObject* b) const
@@ -280,6 +351,7 @@ protected:
}
};
+ /** \brief Functor sorting objects according to the AABB lower z bound */
struct SortByZLow
{
bool operator()(const CollisionObject* a, const CollisionObject* b) const
@@ -290,6 +362,7 @@ protected:
}
};
+ /** \brief Dummy collision object with a point AABB */
class DummyCollisionObject : public CollisionObject
{
public:
@@ -301,18 +374,25 @@ protected:
void computeAABB() {}
};
+ /** \brief check collision between one object and a list of objects */
void checkColl(std::vector<CollisionObject*>::const_iterator pos_start, std::vector<CollisionObject*>::const_iterator pos_end,
CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
+ /** \brief Objects sorted according to lower x value */
std::vector<CollisionObject*> objs_x;
+
+ /** \brief Objects sorted according to lower y value */
std::vector<CollisionObject*> objs_y;
+
+ /** \brief Objects sorted according to lower z value */
std::vector<CollisionObject*> objs_z;
+ /** \brief tag about whether the environment is maintained suitably (i.e., the objs_x, objs_y, objs_z are sorted correctly */
bool setup_;
};
-
+/** Collision manager based on interval tree */
class IntervalTreeCollisionManager : public BroadPhaseCollisionManager
{
public:
@@ -323,39 +403,57 @@ public:
interval_trees[i] = NULL;
}
- void unregisterObject(CollisionObject* obj);
-
+ /** \brief remove one object from the manager */
void registerObject(CollisionObject* obj);
+ /** \brief add one object to the manager */
+ void unregisterObject(CollisionObject* obj);
+
+ /** \brief initialize the manager, related with the specific type of manager */
void setup();
+ /** \brief update the condition of manager */
void update();
+ /** \brief clear the manager */
void clear();
+ /** \brief return the objects managed by the manager */
void getObjects(std::vector<CollisionObject*>& objs) const;
- void checkColl(std::vector<CollisionObject*>::const_iterator pos_start, std::vector<CollisionObject*>::const_iterator pos_end,
- CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
-
+ /** \brief perform collision test between one object and all the objects belonging to the manager */
void collide(CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
+ /** \brief perform collision test for the objects belonging to the manager (i.e., N^2 self collision) */
void collide(void* cdata, CollisionCallBack callback) const;
+ /** \brief whether the manager is empty */
bool empty() const;
+ /** \brief the number of objects managed by the manager */
inline size_t size() const { return endpoints[0].size() / 2; }
protected:
+ /** \brief check collision between one object and a list of objects */
+ void checkColl(std::vector<CollisionObject*>::const_iterator pos_start, std::vector<CollisionObject*>::const_iterator pos_end,
+ CollisionObject* obj, void* cdata, CollisionCallBack callback) const;
+
+ /** \brief SAP end point */
struct EndPoint
{
- CollisionObject* obj; // pointer to endpoint geometry;
- BVH_REAL value; // endpoint value
- char minmax; // '0' if interval min, '1' if interval max
+ /** \brief object related with the end point */
+ CollisionObject* obj;
+
+ /** \brief end point value */
+ BVH_REAL value;
+
+ /** \brief tag for whether it is a lower bound or higher bound of an interval, 0 for lo, and 1 for hi */
+ char minmax;
};
+ /** \brief Functor for sorting end points */
struct SortByValue
{
bool operator()(const EndPoint& a, const EndPoint& b) const
@@ -366,6 +464,7 @@ protected:
}
};
+ /** \brief Extention interval tree's interval to SAP interval, adding more information */
struct SAPInterval : public Interval
{
CollisionObject* obj;
@@ -377,11 +476,13 @@ protected:
}
};
-
+ /** \brief vector stores all the end points */
std::vector<EndPoint> endpoints[3];
+ /** \brief interval tree manages the intervals */
IntervalTree* interval_trees[3];
+ /** \brief tag for whether the interval tree is maintained suitably */
bool setup_;
};
diff --git a/trunk/fcl/include/fcl/collision_object.h b/trunk/fcl/include/fcl/collision_object.h
index 1ab14930..64acea69 100644
--- a/trunk/fcl/include/fcl/collision_object.h
+++ b/trunk/fcl/include/fcl/collision_object.h
@@ -104,6 +104,16 @@ public:
t.setQuatRotation(q);
}
+ void setTransform(const Vec3f R[3], const Vec3f& T)
+ {
+ t.setTransform(R, T);
+ }
+
+ void setTransform(const SimpleQuaternion& q, const Vec3f& T)
+ {
+ t.setTransform(q, T);
+ }
+
protected:
/** AABB in global coordinate */
diff --git a/trunk/fcl/include/fcl/transform.h b/trunk/fcl/include/fcl/transform.h
index 6e406c8d..42aa00bd 100644
--- a/trunk/fcl/include/fcl/transform.h
+++ b/trunk/fcl/include/fcl/transform.h
@@ -175,6 +175,13 @@ public:
q.fromRotation(R_);
}
+ inline void setTransform(const SimpleQuaternion& q_, const Vec3f& T_)
+ {
+ q = q_;
+ T = T_;
+ q.toRotation(R);
+ }
+
inline void setRotation(const Vec3f R_[3])
{
for(int i = 0; i < 3; ++i)
diff --git a/trunk/svm_light/Makefile b/trunk/svm_light/Makefile
new file mode 100644
index 00000000..3a68c58d
--- /dev/null
+++ b/trunk/svm_light/Makefile
@@ -0,0 +1,37 @@
+all: installed
+
+#
+# Download, extract and compile from a released tarball:
+#
+TARBALL = build/svm_light.tar.gz
+TARBALL_URL = http://download.joachims.org/svm_light/current/svm_light.tar.gz
+TARBALL_PATCH = svm_light.diff
+UNPACK_CMD = mkdir svm_light; tar -C svm_light -xzf
+INITIAL_DIR = build/svm_light
+SOURCE_DIR = build/svm_light-tar
+include $(shell rospack find mk)/download_unpack_build.mk
+
+INSTALL_DIR = svm_light
+CMAKE = cmake
+CMAKE_ARGS = -D CMAKE_BUILD_TYPE="Release" -D CMAKE_INSTALL_PREFIX=`rospack find svm_light`/$(INSTALL_DIR)
+MAKE = make
+
+installed: wiped $(SOURCE_DIR)/unpacked
+ cd $(SOURCE_DIR) && make libsvmlight_hideo $(ROS_PARALLEL_JOBS)
+ mkdir -p $(INSTALL_DIR)/lib
+ mkdir -p $(INSTALL_DIR)/include
+ mkdir -p $(INSTALL_DIR)/include/svm_light
+ cp -r $(SOURCE_DIR)/*.h $(INSTALL_DIR)/include/svm_light
+ cp -r $(SOURCE_DIR)/*.so $(INSTALL_DIR)/lib
+ touch installed
+
+clean:
+ rm -rf build
+ rm -rf $(INSTALL_DIR) installed
+
+wiped: Makefile
+ make wipe
+ touch wiped
+
+wipe: clean
+ rm -rf build patched
diff --git a/trunk/svm_light/build/svm_light-tar/LICENSE.txt b/trunk/svm_light/build/svm_light-tar/LICENSE.txt
new file mode 100755
index 00000000..28d6db09
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/LICENSE.txt
@@ -0,0 +1,59 @@
+SVM-Light
+---------
+
+Available at http://svmlight.joachims.org/
+
+Author: Thorsten Joachims
+ thorsten@joachims.org
+
+ Cornell University
+ Department of Computer Science
+ 4153 Upson Hall
+ Ithaca, NY 14853
+ USA
+
+LICENSING TERMS
+
+This program is granted free of charge for research and education
+purposes. However you must obtain a license from the author to use it
+for commercial purposes.
+
+Scientific results produced using the software provided shall
+acknowledge the use of SVM-Light. Please cite as
+
+ T. Joachims, Making large-Scale SVM Learning
+ Practical. Advances in Kernel Methods - Support Vector
+ Learning, B. Sch�lkopf and C. Burges and A. Smola (ed.),
+ MIT-Press, 1999.
+ http://www-ai.cs.uni-dortmund.de/DOKUMENTE/joachims_99a.pdf
+
+Moreover shall the author of SVM-Light be informed about the
+publication.
+
+The software must not be modified and distributed without prior
+permission of the author.
+
+By using SVM-Light you agree to the licensing terms.
+
+
+NO WARRANTY
+
+BECAUSE THE PROGRAM IS LICENSED FREE OF CHARGE, THERE IS NO WARRANTY
+FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT
+WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER
+PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND,
+EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE
+PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME
+THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY AND/OR
+REDISTRIBUTE THE PROGRAM, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF
+THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO
+LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY
+YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY
+OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED
+OF THE POSSIBILITY OF SUCH DAMAGES.
diff --git a/trunk/svm_light/build/svm_light-tar/Makefile b/trunk/svm_light/build/svm_light-tar/Makefile
new file mode 100755
index 00000000..7bb16482
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/Makefile
@@ -0,0 +1,105 @@
+#
+# makefile for svm_light
+#
+# Thorsten Joachims, 2002
+#
+
+#Use the following to compile under unix or cygwin
+CC = gcc
+LD = gcc
+
+#Uncomment the following line to make CYGWIN produce stand-alone Windows executables
+#SFLAGS= -mno-cygwin
+
+CFLAGS= $(SFLAGS) -fPIC -O3 # release C-Compiler flags
+LFLAGS= $(SFLAGS) -O3 # release linker flags
+#CFLAGS= $(SFLAGS) -pg -Wall -pedantic # debugging C-Compiler flags
+#LFLAGS= $(SFLAGS) -pg # debugging linker flags
+LIBS=-L. -lm # used libraries
+
+all: svm_learn_hideo svm_classify
+
+tidy:
+ rm -f *.o
+ rm -f pr_loqo/*.o
+
+clean: tidy
+ rm -f svm_learn
+ rm -f svm_classify
+ rm -f libsvmlight.so
+
+help: info
+
+info:
+ @echo
+ @echo "make for SVM-light Thorsten Joachims, 1998"
+ @echo
+ @echo "Thanks to Ralf Herbrich for the initial version."
+ @echo
+ @echo "USAGE: make [svm_learn | svm_learn_loqo | svm_learn_hideo | "
+ @echo " libsvmlight_hideo | libsvmlight_loqo | "
+ @echo " svm_classify | all | clean | tidy]"
+ @echo
+ @echo " svm_learn builds the learning module (prefers HIDEO)"
+ @echo " svm_learn_hideo builds the learning module using HIDEO optimizer"
+ @echo " svm_learn_loqo builds the learning module using PR_LOQO optimizer"
+ @echo " svm_classify builds the classfication module"
+ @echo " libsvmlight_hideo builds shared object library that can be linked into"
+ @echo " other code using HIDEO"
+ @echo " libsvmlight_loqo builds shared object library that can be linked into"
+ @echo " other code using PR_LOQO"
+ @echo " all (default) builds svm_learn + svm_classify"
+ @echo " clean removes .o and target files"
+ @echo " tidy removes .o files"
+ @echo
+
+# Create executables svm_learn and svm_classify
+
+svm_learn_hideo: svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o
+ $(LD) $(LFLAGS) svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o -o svm_learn $(LIBS)
+
+#svm_learn_loqo: svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o loqo
+# $(LD) $(LFLAGS) svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o pr_loqo/pr_loqo.o -o svm_learn $(LIBS)
+
+svm_classify: svm_classify.o svm_common.o
+ $(LD) $(LFLAGS) svm_classify.o svm_common.o -o svm_classify $(LIBS)
+
+
+# Create library libsvmlight.so, so that external code can get access to the
+# learning and classification functions of svm-light by linking this library.
+
+svm_learn_hideo_noexe: svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o
+
+libsvmlight_hideo: svm_learn_main.o svm_learn.o svm_common.o svm_hideo.o
+ $(LD) -shared svm_learn.o svm_common.o svm_hideo.o -o libsvmlight.so
+
+#svm_learn_loqo_noexe: svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o loqo
+
+#libsvmlight_loqo: svm_learn_main.o svm_learn.o svm_common.o svm_loqo.o
+# $(LD) -shared svm_learn.o svm_common.o svm_loqo.o pr_loqo/pr_loqo.o -o libsvmlight.so
+
+# Compile components
+
+svm_hideo.o: svm_hideo.c
+ $(CC) -c $(CFLAGS) svm_hideo.c -o svm_hideo.o
+
+#svm_loqo.o: svm_loqo.c
+# $(CC) -c $(CFLAGS) svm_loqo.c -o svm_loqo.o
+
+svm_common.o: svm_common.c svm_common.h kernel.h
+ $(CC) -c $(CFLAGS) svm_common.c -o svm_common.o
+
+svm_learn.o: svm_learn.c svm_common.h
+ $(CC) -c $(CFLAGS) svm_learn.c -o svm_learn.o
+
+svm_learn_main.o: svm_learn_main.c svm_learn.h svm_common.h
+ $(CC) -c $(CFLAGS) svm_learn_main.c -o svm_learn_main.o
+
+svm_classify.o: svm_classify.c svm_common.h kernel.h
+ $(CC) -c $(CFLAGS) svm_classify.c -o svm_classify.o
+
+#loqo: pr_loqo/pr_loqo.o
+
+#pr_loqo/pr_loqo.o: pr_loqo/pr_loqo.c
+# $(CC) -c $(CFLAGS) pr_loqo/pr_loqo.c -o pr_loqo/pr_loqo.o
+
diff --git a/trunk/svm_light/build/svm_light-tar/kernel.h b/trunk/svm_light/build/svm_light-tar/kernel.h
new file mode 100755
index 00000000..0133b006
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/kernel.h
@@ -0,0 +1,40 @@
+/************************************************************************/
+/* */
+/* kernel.h */
+/* */
+/* User defined kernel function. Feel free to plug in your own. */
+/* */
+/* Copyright: Thorsten Joachims */
+/* Date: 16.12.97 */
+/* */
+/************************************************************************/
+
+/* KERNEL_PARM is defined in svm_common.h The field 'custom' is reserved for */
+/* parameters of the user defined kernel. You can also access and use */
+/* the parameters of the other kernels. Just replace the line
+ return((double)(1.0));
+ with your own kernel. */
+
+ /* Example: The following computes the polynomial kernel. sprod_ss
+ computes the inner product between two sparse vectors.
+
+ return((CFLOAT)pow(kernel_parm->coef_lin*sprod_ss(a->words,b->words)
+ +kernel_parm->coef_const,(double)kernel_parm->poly_degree));
+ */
+
+/* If you are implementing a kernel that is not based on a
+ feature/value representation, you might want to make use of the
+ field "userdefined" in SVECTOR. By default, this field will contain
+ whatever string you put behind a # sign in the example file. So, if
+ a line in your training file looks like
+
+ -1 1:3 5:6 #abcdefg
+
+ then the SVECTOR field "words" will contain the vector 1:3 5:6, and
+ "userdefined" will contain the string "abcdefg". */
+
+double custom_kernel(KERNEL_PARM *kernel_parm, SVECTOR *a, SVECTOR *b)
+ /* plug in you favorite kernel */
+{
+ return((double)(1.0));
+}
diff --git a/trunk/svm_light/build/svm_light-tar/svm_classify.c b/trunk/svm_light/build/svm_light-tar/svm_classify.c
new file mode 100755
index 00000000..0b0333b0
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_classify.c
@@ -0,0 +1,197 @@
+/***********************************************************************/
+/* */
+/* svm_classify.c */
+/* */
+/* Classification module of Support Vector Machine. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/************************************************************************/
+
+# include "svm_common.h"
+
+char docfile[200];
+char modelfile[200];
+char predictionsfile[200];
+
+void read_input_parameters(int, char **, char *, char *, char *, long *,
+ long *);
+void print_help(void);
+
+
+int main (int argc, char* argv[])
+{
+ DOC *doc; /* test example */
+ WORD *words;
+ long max_docs,max_words_doc,lld;
+ long totdoc=0,queryid,slackid;
+ long correct=0,incorrect=0,no_accuracy=0;
+ long res_a=0,res_b=0,res_c=0,res_d=0,wnum,pred_format;
+ long j;
+ double t1,runtime=0;
+ double dist,doc_label,costfactor;
+ char *line,*comment;
+ FILE *predfl,*docfl;
+ MODEL *model;
+
+ read_input_parameters(argc,argv,docfile,modelfile,predictionsfile,
+ &verbosity,&pred_format);
+
+ nol_ll(docfile,&max_docs,&max_words_doc,&lld); /* scan size of input file */
+ max_words_doc+=2;
+ lld+=2;
+
+ line = (char *)my_malloc(sizeof(char)*lld);
+ words = (WORD *)my_malloc(sizeof(WORD)*(max_words_doc+10));
+
+ model=read_model(modelfile);
+
+ if(model->kernel_parm.kernel_type == 0) { /* linear kernel */
+ /* compute weight vector */
+ add_weight_vector_to_linear_model(model);
+ }
+
+ if(verbosity>=2) {
+ printf("Classifying test examples.."); fflush(stdout);
+ }
+
+ if ((docfl = fopen (docfile, "r")) == NULL)
+ { perror (docfile); exit (1); }
+ if ((predfl = fopen (predictionsfile, "w")) == NULL)
+ { perror (predictionsfile); exit (1); }
+
+ while((!feof(docfl)) && fgets(line,(int)lld,docfl)) {
+ if(line[0] == '#') continue; /* line contains comments */
+ parse_document(line,words,&doc_label,&queryid,&slackid,&costfactor,&wnum,
+ max_words_doc,&comment);
+ totdoc++;
+ if(model->kernel_parm.kernel_type == 0) { /* linear kernel */
+ for(j=0;(words[j]).wnum != 0;j++) { /* Check if feature numbers */
+ if((words[j]).wnum>model->totwords) /* are not larger than in */
+ (words[j]).wnum=0; /* model. Remove feature if */
+ } /* necessary. */
+ doc = create_example(-1,0,0,0.0,create_svector(words,comment,1.0));
+ t1=get_runtime();
+ dist=classify_example_linear(model,doc);
+ runtime+=(get_runtime()-t1);
+ free_example(doc,1);
+ }
+ else { /* non-linear kernel */
+ doc = create_example(-1,0,0,0.0,create_svector(words,comment,1.0));
+ t1=get_runtime();
+ dist=classify_example(model,doc);
+ runtime+=(get_runtime()-t1);
+ free_example(doc,1);
+ }
+ if(dist>0) {
+ if(pred_format==0) { /* old weired output format */
+ fprintf(predfl,"%.8g:+1 %.8g:-1\n",dist,-dist);
+ }
+ if(doc_label>0) correct++; else incorrect++;
+ if(doc_label>0) res_a++; else res_b++;
+ }
+ else {
+ if(pred_format==0) { /* old weired output format */
+ fprintf(predfl,"%.8g:-1 %.8g:+1\n",-dist,dist);
+ }
+ if(doc_label<0) correct++; else incorrect++;
+ if(doc_label>0) res_c++; else res_d++;
+ }
+ if(pred_format==1) { /* output the value of decision function */
+ fprintf(predfl,"%.8g\n",dist);
+ }
+ if((int)(0.01+(doc_label*doc_label)) != 1)
+ { no_accuracy=1; } /* test data is not binary labeled */
+ if(verbosity>=2) {
+ if(totdoc % 100 == 0) {
+ printf("%ld..",totdoc); fflush(stdout);
+ }
+ }
+ }
+ fclose(predfl);
+ fclose(docfl);
+ free(line);
+ free(words);
+ free_model(model,1);
+
+ if(verbosity>=2) {
+ printf("done\n");
+
+/* Note by Gary Boone Date: 29 April 2000 */
+/* o Timing is inaccurate. The timer has 0.01 second resolution. */
+/* Because classification of a single vector takes less than */
+/* 0.01 secs, the timer was underflowing. */
+ printf("Runtime (without IO) in cpu-seconds: %.2f\n",
+ (float)(runtime/100.0));
+
+ }
+ if((!no_accuracy) && (verbosity>=1)) {
+ printf("Accuracy on test set: %.2f%% (%ld correct, %ld incorrect, %ld total)\n",(float)(correct)*100.0/totdoc,correct,incorrect,totdoc);
+ printf("Precision/recall on test set: %.2f%%/%.2f%%\n",(float)(res_a)*100.0/(res_a+res_b),(float)(res_a)*100.0/(res_a+res_c));
+ }
+
+ return(0);
+}
+
+void read_input_parameters(int argc, char **argv, char *docfile,
+ char *modelfile, char *predictionsfile,
+ long int *verbosity, long int *pred_format)
+{
+ long i;
+
+ /* set default */
+ strcpy (modelfile, "svm_model");
+ strcpy (predictionsfile, "svm_predictions");
+ (*verbosity)=2;
+ (*pred_format)=1;
+
+ for(i=1;(i<argc) && ((argv[i])[0] == '-');i++) {
+ switch ((argv[i])[1])
+ {
+ case 'h': print_help(); exit(0);
+ case 'v': i++; (*verbosity)=atol(argv[i]); break;
+ case 'f': i++; (*pred_format)=atol(argv[i]); break;
+ default: printf("\nUnrecognized option %s!\n\n",argv[i]);
+ print_help();
+ exit(0);
+ }
+ }
+ if((i+1)>=argc) {
+ printf("\nNot enough input parameters!\n\n");
+ print_help();
+ exit(0);
+ }
+ strcpy (docfile, argv[i]);
+ strcpy (modelfile, argv[i+1]);
+ if((i+2)<argc) {
+ strcpy (predictionsfile, argv[i+2]);
+ }
+ if(((*pred_format) != 0) && ((*pred_format) != 1)) {
+ printf("\nOutput format can only take the values 0 or 1!\n\n");
+ print_help();
+ exit(0);
+ }
+}
+
+void print_help(void)
+{
+ printf("\nSVM-light %s: Support Vector Machine, classification module %s\n",VERSION,VERSION_DATE);
+ copyright_notice();
+ printf(" usage: svm_classify [options] example_file model_file output_file\n\n");
+ printf("options: -h -> this help\n");
+ printf(" -v [0..3] -> verbosity level (default 2)\n");
+ printf(" -f [0,1] -> 0: old output format of V1.0\n");
+ printf(" -> 1: output the value of decision function (default)\n\n");
+}
+
+
+
+
diff --git a/trunk/svm_light/build/svm_light-tar/svm_common.c b/trunk/svm_light/build/svm_light-tar/svm_common.c
new file mode 100755
index 00000000..61e72800
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_common.c
@@ -0,0 +1,985 @@
+/************************************************************************/
+/* */
+/* svm_common.c */
+/* */
+/* Definitions and functions used in both svm_learn and svm_classify. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.04 */
+/* */
+/* Copyright (c) 2004 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/************************************************************************/
+
+# include "ctype.h"
+# include "svm_common.h"
+# include "kernel.h" /* this contains a user supplied kernel */
+
+long verbosity; /* verbosity level (0-4) */
+long kernel_cache_statistic;
+
+double classify_example(MODEL *model, DOC *ex)
+ /* classifies one example */
+{
+ register long i;
+ register double dist;
+
+ if((model->kernel_parm.kernel_type == LINEAR) && (model->lin_weights))
+ return(classify_example_linear(model,ex));
+
+ dist=0;
+ for(i=1;i<model->sv_num;i++) {
+ dist+=kernel(&model->kernel_parm,model->supvec[i],ex)*model->alpha[i];
+ }
+ return(dist-model->b);
+}
+
+double classify_example_linear(MODEL *model, DOC *ex)
+ /* classifies example for linear kernel */
+
+ /* important: the model must have the linear weight vector computed */
+ /* use: add_weight_vector_to_linear_model(&model); */
+
+
+ /* important: the feature numbers in the example to classify must */
+ /* not be larger than the weight vector! */
+{
+ double sum=0;
+ SVECTOR *f;
+
+ for(f=ex->fvec;f;f=f->next)
+ sum+=f->factor*sprod_ns(model->lin_weights,f);
+ return(sum-model->b);
+}
+
+
+double kernel(KERNEL_PARM *kernel_parm, DOC *a, DOC *b)
+ /* calculate the kernel function */
+{
+ double sum=0;
+ SVECTOR *fa,*fb;
+
+ /* in case the constraints are sums of feature vector as represented
+ as a list of SVECTOR's with their coefficient factor in the sum,
+ take the kernel between all pairs */
+ for(fa=a->fvec;fa;fa=fa->next) {
+ for(fb=b->fvec;fb;fb=fb->next) {
+ if(fa->kernel_id == fb->kernel_id)
+ sum+=fa->factor*fb->factor*single_kernel(kernel_parm,fa,fb);
+ }
+ }
+ return(sum);
+}
+
+double single_kernel(KERNEL_PARM *kernel_parm, SVECTOR *a, SVECTOR *b)
+ /* calculate the kernel function between two vectors */
+{
+ kernel_cache_statistic++;
+ switch(kernel_parm->kernel_type) {
+ case 0: /* linear */
+ return(sprod_ss(a,b));
+ case 1: /* polynomial */
+ return(pow(kernel_parm->coef_lin*sprod_ss(a,b)+kernel_parm->coef_const,(double)kernel_parm->poly_degree));
+ case 2: /* radial basis function */
+ return(exp(-kernel_parm->rbf_gamma*(a->twonorm_sq-2*sprod_ss(a,b)+b->twonorm_sq)));
+ case 3: /* sigmoid neural net */
+ return(tanh(kernel_parm->coef_lin*sprod_ss(a,b)+kernel_parm->coef_const));
+ case 4: /* custom-kernel supplied in file kernel.h*/
+ return(custom_kernel(kernel_parm,a,b));
+ default: printf("Error: Unknown kernel function\n"); exit(1);
+ }
+}
+
+
+SVECTOR *create_svector(WORD *words,char *userdefined,double factor)
+{
+ SVECTOR *vec;
+ long fnum,i;
+
+ fnum=0;
+ while(words[fnum].wnum) {
+ fnum++;
+ }
+ fnum++;
+ vec = (SVECTOR *)my_malloc(sizeof(SVECTOR));
+ vec->words = (WORD *)my_malloc(sizeof(WORD)*(fnum));
+ for(i=0;i<fnum;i++) {
+ vec->words[i]=words[i];
+ }
+ vec->twonorm_sq=sprod_ss(vec,vec);
+
+ fnum=0;
+ while(userdefined[fnum]) {
+ fnum++;
+ }
+ fnum++;
+ vec->userdefined = (char *)my_malloc(sizeof(char)*(fnum));
+ for(i=0;i<fnum;i++) {
+ vec->userdefined[i]=userdefined[i];
+ }
+ vec->kernel_id=0;
+ vec->next=NULL;
+ vec->factor=factor;
+ return(vec);
+}
+
+SVECTOR *copy_svector(SVECTOR *vec)
+{
+ SVECTOR *newvec=NULL;
+ if(vec) {
+ newvec=create_svector(vec->words,vec->userdefined,vec->factor);
+ newvec->next=copy_svector(vec->next);
+ }
+ return(newvec);
+}
+
+void free_svector(SVECTOR *vec)
+{
+ if(vec) {
+ free(vec->words);
+ if(vec->userdefined)
+ free(vec->userdefined);
+ free_svector(vec->next);
+ free(vec);
+ }
+}
+
+double sprod_ss(SVECTOR *a, SVECTOR *b)
+ /* compute the inner product of two sparse vectors */
+{
+ register double sum=0;
+ register WORD *ai,*bj;
+ ai=a->words;
+ bj=b->words;
+ while (ai->wnum && bj->wnum) {
+ if(ai->wnum > bj->wnum) {
+ bj++;
+ }
+ else if (ai->wnum < bj->wnum) {
+ ai++;
+ }
+ else {
+ sum+=(ai->weight) * (bj->weight);
+ ai++;
+ bj++;
+ }
+ }
+ return((double)sum);
+}
+
+SVECTOR* sub_ss(SVECTOR *a, SVECTOR *b)
+ /* compute the difference a-b of two sparse vectors */
+ /* Note: SVECTOR lists are not followed, but only the first
+ SVECTOR is used */
+{
+ SVECTOR *vec;
+ register WORD *sum,*sumi;
+ register WORD *ai,*bj;
+ long veclength;
+
+ ai=a->words;
+ bj=b->words;
+ veclength=0;
+ while (ai->wnum && bj->wnum) {
+ if(ai->wnum > bj->wnum) {
+ veclength++;
+ bj++;
+ }
+ else if (ai->wnum < bj->wnum) {
+ veclength++;
+ ai++;
+ }
+ else {
+ veclength++;
+ ai++;
+ bj++;
+ }
+ }
+ while (bj->wnum) {
+ veclength++;
+ bj++;
+ }
+ while (ai->wnum) {
+ veclength++;
+ ai++;
+ }
+ veclength++;
+
+ sum=(WORD *)my_malloc(sizeof(WORD)*veclength);
+ sumi=sum;
+ ai=a->words;
+ bj=b->words;
+ while (ai->wnum && bj->wnum) {
+ if(ai->wnum > bj->wnum) {
+ (*sumi)=(*bj);
+ sumi->weight*=(-1);
+ sumi++;
+ bj++;
+ }
+ else if (ai->wnum < bj->wnum) {
+ (*sumi)=(*ai);
+ sumi++;
+ ai++;
+ }
+ else {
+ (*sumi)=(*ai);
+ sumi->weight-=bj->weight;
+ if(sumi->weight != 0)
+ sumi++;
+ ai++;
+ bj++;
+ }
+ }
+ while (bj->wnum) {
+ (*sumi)=(*bj);
+ sumi->weight*=(-1);
+ sumi++;
+ bj++;
+ }
+ while (ai->wnum) {
+ (*sumi)=(*ai);
+ sumi++;
+ ai++;
+ }
+ sumi->wnum=0;
+
+ vec=create_svector(sum,"",1.0);
+ free(sum);
+
+ return(vec);
+}
+
+SVECTOR* add_ss(SVECTOR *a, SVECTOR *b)
+ /* compute the sum a+b of two sparse vectors */
+ /* Note: SVECTOR lists are not followed, but only the first
+ SVECTOR is used */
+{
+ SVECTOR *vec;
+ register WORD *sum,*sumi;
+ register WORD *ai,*bj;
+ long veclength;
+
+ ai=a->words;
+ bj=b->words;
+ veclength=0;
+ while (ai->wnum && bj->wnum) {
+ if(ai->wnum > bj->wnum) {
+ veclength++;
+ bj++;
+ }
+ else if (ai->wnum < bj->wnum) {
+ veclength++;
+ ai++;
+ }
+ else {
+ veclength++;
+ ai++;
+ bj++;
+ }
+ }
+ while (bj->wnum) {
+ veclength++;
+ bj++;
+ }
+ while (ai->wnum) {
+ veclength++;
+ ai++;
+ }
+ veclength++;
+
+ /*** is veclength=lengSequence(a)+lengthSequence(b)? ***/
+
+ sum=(WORD *)my_malloc(sizeof(WORD)*veclength);
+ sumi=sum;
+ ai=a->words;
+ bj=b->words;
+ while (ai->wnum && bj->wnum) {
+ if(ai->wnum > bj->wnum) {
+ (*sumi)=(*bj);
+ sumi++;
+ bj++;
+ }
+ else if (ai->wnum < bj->wnum) {
+ (*sumi)=(*ai);
+ sumi++;
+ ai++;
+ }
+ else {
+ (*sumi)=(*ai);
+ sumi->weight+=bj->weight;
+ if(sumi->weight != 0)
+ sumi++;
+ ai++;
+ bj++;
+ }
+ }
+ while (bj->wnum) {
+ (*sumi)=(*bj);
+ sumi++;
+ bj++;
+ }
+ while (ai->wnum) {
+ (*sumi)=(*ai);
+ sumi++;
+ ai++;
+ }
+ sumi->wnum=0;
+
+ vec=create_svector(sum,"",1.0);
+ free(sum);
+
+ return(vec);
+}
+
+SVECTOR* add_list_ss(SVECTOR *a)
+ /* computes the linear combination of the SVECTOR list weighted
+ by the factor of each SVECTOR */
+{
+ SVECTOR *scaled,*oldsum,*sum,*f;
+ WORD empty[2];
+
+ if(a){
+ sum=smult_s(a,a->factor);
+ for(f=a->next;f;f=f->next) {
+ scaled=smult_s(f,f->factor);
+ oldsum=sum;
+ sum=add_ss(sum,scaled);
+ free_svector(oldsum);
+ free_svector(scaled);
+ }
+ sum->factor=1.0;
+ }
+ else {
+ empty[0].wnum=0;
+ sum=create_svector(empty,"",1.0);
+ }
+ return(sum);
+}
+
+void append_svector_list(SVECTOR *a, SVECTOR *b)
+ /* appends SVECTOR b to the end of SVECTOR a. */
+{
+ SVECTOR *f;
+
+ for(f=a;f->next;f=f->next); /* find end of first vector list */
+ f->next=b; /* append the two vector lists */
+}
+
+SVECTOR* smult_s(SVECTOR *a, double factor)
+ /* scale sparse vector a by factor */
+{
+ SVECTOR *vec;
+ register WORD *sum,*sumi;
+ register WORD *ai;
+ long veclength;
+
+ ai=a->words;
+ veclength=0;
+ while (ai->wnum) {
+ veclength++;
+ ai++;
+ }
+ veclength++;
+
+ sum=(WORD *)my_malloc(sizeof(WORD)*veclength);
+ sumi=sum;
+ ai=a->words;
+ while (ai->wnum) {
+ (*sumi)=(*ai);
+ sumi->weight*=factor;
+ if(sumi->weight != 0)
+ sumi++;
+ ai++;
+ }
+ sumi->wnum=0;
+
+ vec=create_svector(sum,a->userdefined,a->factor);
+ free(sum);
+
+ return(vec);
+}
+
+int featvec_eq(SVECTOR *a, SVECTOR *b)
+ /* tests two sparse vectors for equality */
+{
+ register WORD *ai,*bj;
+ ai=a->words;
+ bj=b->words;
+ while (ai->wnum && bj->wnum) {
+ if(ai->wnum > bj->wnum) {
+ if((bj->weight) != 0)
+ return(0);
+ bj++;
+ }
+ else if (ai->wnum < bj->wnum) {
+ if((ai->weight) != 0)
+ return(0);
+ ai++;
+ }
+ else {
+ if((ai->weight) != (bj->weight))
+ return(0);
+ ai++;
+ bj++;
+ }
+ }
+ return(1);
+}
+
+double model_length_s(MODEL *model, KERNEL_PARM *kernel_parm)
+ /* compute length of weight vector */
+{
+ register long i,j;
+ register double sum=0,alphai;
+ register DOC *supveci;
+
+ for(i=1;i<model->sv_num;i++) {
+ alphai=model->alpha[i];
+ supveci=model->supvec[i];
+ for(j=1;j<model->sv_num;j++) {
+ sum+=alphai*model->alpha[j]
+ *kernel(kernel_parm,supveci,model->supvec[j]);
+ }
+ }
+ return(sqrt(sum));
+}
+
+void clear_vector_n(double *vec, long int n)
+{
+ register long i;
+ for(i=0;i<=n;i++) vec[i]=0;
+}
+
+void add_vector_ns(double *vec_n, SVECTOR *vec_s, double faktor)
+{
+ register WORD *ai;
+ ai=vec_s->words;
+ while (ai->wnum) {
+ vec_n[ai->wnum]+=(faktor*ai->weight);
+ ai++;
+ }
+}
+
+double sprod_ns(double *vec_n, SVECTOR *vec_s)
+{
+ register double sum=0;
+ register WORD *ai;
+ ai=vec_s->words;
+ while (ai->wnum) {
+ sum+=(vec_n[ai->wnum]*ai->weight);
+ ai++;
+ }
+ return(sum);
+}
+
+void add_weight_vector_to_linear_model(MODEL *model)
+ /* compute weight vector in linear case and add to model */
+{
+ long i;
+ SVECTOR *f;
+
+ model->lin_weights=(double *)my_malloc(sizeof(double)*(model->totwords+1));
+ clear_vector_n(model->lin_weights,model->totwords);
+ for(i=1;i<model->sv_num;i++) {
+ for(f=(model->supvec[i])->fvec;f;f=f->next)
+ add_vector_ns(model->lin_weights,f,f->factor*model->alpha[i]);
+ }
+}
+
+
+DOC *create_example(long docnum, long queryid, long slackid,
+ double costfactor, SVECTOR *fvec)
+{
+ DOC *example;
+ example = (DOC *)my_malloc(sizeof(DOC));
+ example->docnum=docnum;
+ example->queryid=queryid;
+ example->slackid=slackid;
+ example->costfactor=costfactor;
+ example->fvec=fvec;
+ return(example);
+}
+
+void free_example(DOC *example, long deep)
+{
+ if(example) {
+ if(deep) {
+ if(example->fvec)
+ free_svector(example->fvec);
+ }
+ free(example);
+ }
+}
+
+void write_model(char *modelfile, MODEL *model)
+{
+ FILE *modelfl;
+ long j,i,sv_num;
+ SVECTOR *v;
+
+ if(verbosity>=1) {
+ printf("Writing model file..."); fflush(stdout);
+ }
+ if ((modelfl = fopen (modelfile, "w")) == NULL)
+ { perror (modelfile); exit (1); }
+ fprintf(modelfl,"SVM-light Version %s\n",VERSION);
+ fprintf(modelfl,"%ld # kernel type\n",
+ model->kernel_parm.kernel_type);
+ fprintf(modelfl,"%ld # kernel parameter -d \n",
+ model->kernel_parm.poly_degree);
+ fprintf(modelfl,"%.8g # kernel parameter -g \n",
+ model->kernel_parm.rbf_gamma);
+ fprintf(modelfl,"%.8g # kernel parameter -s \n",
+ model->kernel_parm.coef_lin);
+ fprintf(modelfl,"%.8g # kernel parameter -r \n",
+ model->kernel_parm.coef_const);
+ fprintf(modelfl,"%s# kernel parameter -u \n",model->kernel_parm.custom);
+ fprintf(modelfl,"%ld # highest feature index \n",model->totwords);
+ fprintf(modelfl,"%ld # number of training documents \n",model->totdoc);
+
+ sv_num=1;
+ for(i=1;i<model->sv_num;i++) {
+ for(v=model->supvec[i]->fvec;v;v=v->next)
+ sv_num++;
+ }
+ fprintf(modelfl,"%ld # number of support vectors plus 1 \n",sv_num);
+ fprintf(modelfl,"%.8g # threshold b, each following line is a SV (starting with alpha*y)\n",model->b);
+
+ for(i=1;i<model->sv_num;i++) {
+ for(v=model->supvec[i]->fvec;v;v=v->next) {
+ fprintf(modelfl,"%.32g ",model->alpha[i]*v->factor);
+ for (j=0; (v->words[j]).wnum; j++) {
+ fprintf(modelfl,"%ld:%.8g ",
+ (long)(v->words[j]).wnum,
+ (double)(v->words[j]).weight);
+ }
+ fprintf(modelfl,"#%s\n",v->userdefined);
+ /* NOTE: this could be made more efficient by summing the
+ alpha's of identical vectors before writing them to the
+ file. */
+ }
+ }
+ fclose(modelfl);
+ if(verbosity>=1) {
+ printf("done\n");
+ }
+}
+
+
+MODEL *read_model(char *modelfile)
+{
+ FILE *modelfl;
+ long i,queryid,slackid;
+ double costfactor;
+ long max_sv,max_words,ll,wpos;
+ char *line,*comment;
+ WORD *words;
+ char version_buffer[100];
+ MODEL *model;
+
+ if(verbosity>=1) {
+ printf("Reading model..."); fflush(stdout);
+ }
+
+ nol_ll(modelfile,&max_sv,&max_words,&ll); /* scan size of model file */
+ max_words+=2;
+ ll+=2;
+
+ words = (WORD *)my_malloc(sizeof(WORD)*(max_words+10));
+ line = (char *)my_malloc(sizeof(char)*ll);
+ model = (MODEL *)my_malloc(sizeof(MODEL));
+
+ if ((modelfl = fopen (modelfile, "r")) == NULL)
+ { perror (modelfile); exit (1); }
+
+ fscanf(modelfl,"SVM-light Version %s\n",version_buffer);
+ if(strcmp(version_buffer,VERSION)) {
+ perror ("Version of model-file does not match version of svm_classify!");
+ exit (1);
+ }
+ fscanf(modelfl,"%ld%*[^\n]\n", &model->kernel_parm.kernel_type);
+ fscanf(modelfl,"%ld%*[^\n]\n", &model->kernel_parm.poly_degree);
+ fscanf(modelfl,"%lf%*[^\n]\n", &model->kernel_parm.rbf_gamma);
+ fscanf(modelfl,"%lf%*[^\n]\n", &model->kernel_parm.coef_lin);
+ fscanf(modelfl,"%lf%*[^\n]\n", &model->kernel_parm.coef_const);
+ fscanf(modelfl,"%[^#]%*[^\n]\n", model->kernel_parm.custom);
+
+ fscanf(modelfl,"%ld%*[^\n]\n", &model->totwords);
+ fscanf(modelfl,"%ld%*[^\n]\n", &model->totdoc);
+ fscanf(modelfl,"%ld%*[^\n]\n", &model->sv_num);
+ fscanf(modelfl,"%lf%*[^\n]\n", &model->b);
+
+ model->supvec = (DOC **)my_malloc(sizeof(DOC *)*model->sv_num);
+ model->alpha = (double *)my_malloc(sizeof(double)*model->sv_num);
+ model->index=NULL;
+ model->lin_weights=NULL;
+
+ for(i=1;i<model->sv_num;i++) {
+ fgets(line,(int)ll,modelfl);
+ if(!parse_document(line,words,&(model->alpha[i]),&queryid,&slackid,
+ &costfactor,&wpos,max_words,&comment)) {
+ printf("\nParsing error while reading model file in SV %ld!\n%s",
+ i,line);
+ exit(1);
+ }
+ model->supvec[i] = create_example(-1,
+ 0,0,
+ 0.0,
+ create_svector(words,comment,1.0));
+ }
+ fclose(modelfl);
+ free(line);
+ free(words);
+ if(verbosity>=1) {
+ fprintf(stdout, "OK. (%d support vectors read)\n",(int)(model->sv_num-1));
+ }
+ return(model);
+}
+
+MODEL *copy_model(MODEL *model)
+{
+ MODEL *newmodel;
+ long i;
+
+ newmodel=(MODEL *)my_malloc(sizeof(MODEL));
+ (*newmodel)=(*model);
+ newmodel->supvec = (DOC **)my_malloc(sizeof(DOC *)*model->sv_num);
+ newmodel->alpha = (double *)my_malloc(sizeof(double)*model->sv_num);
+ newmodel->index = NULL; /* index is not copied */
+ newmodel->supvec[0] = NULL;
+ newmodel->alpha[0] = 0;
+ for(i=1;i<model->sv_num;i++) {
+ newmodel->alpha[i]=model->alpha[i];
+ newmodel->supvec[i]=create_example(model->supvec[i]->docnum,
+ model->supvec[i]->queryid,0,
+ model->supvec[i]->costfactor,
+ copy_svector(model->supvec[i]->fvec));
+ }
+ if(model->lin_weights) {
+ newmodel->lin_weights = (double *)my_malloc(sizeof(double)*(model->totwords+1));
+ for(i=0;i<model->totwords+1;i++)
+ newmodel->lin_weights[i]=model->lin_weights[i];
+ }
+ return(newmodel);
+}
+
+void free_model(MODEL *model, int deep)
+{
+ long i;
+
+ if(model->supvec) {
+ if(deep) {
+ for(i=1;i<model->sv_num;i++) {
+ free_example(model->supvec[i],1);
+ }
+ }
+ free(model->supvec);
+ }
+ if(model->alpha) free(model->alpha);
+ if(model->index) free(model->index);
+ if(model->lin_weights) free(model->lin_weights);
+ free(model);
+}
+
+
+void read_documents(char *docfile, DOC ***docs, double **label,
+ long int *totwords, long int *totdoc)
+{
+ char *line,*comment;
+ WORD *words;
+ long dnum=0,wpos,dpos=0,dneg=0,dunlab=0,queryid,slackid,max_docs;
+ long max_words_doc, ll;
+ double doc_label,costfactor;
+ FILE *docfl;
+
+ if(verbosity>=1) {
+ printf("Scanning examples..."); fflush(stdout);
+ }
+ nol_ll(docfile,&max_docs,&max_words_doc,&ll); /* scan size of input file */
+ max_words_doc+=2;
+ ll+=2;
+ max_docs+=2;
+ if(verbosity>=1) {
+ printf("done\n"); fflush(stdout);
+ }
+
+ (*docs) = (DOC **)my_malloc(sizeof(DOC *)*max_docs); /* feature vectors */
+ (*label) = (double *)my_malloc(sizeof(double)*max_docs); /* target values */
+ line = (char *)my_malloc(sizeof(char)*ll);
+
+ if ((docfl = fopen (docfile, "r")) == NULL)
+ { perror (docfile); exit (1); }
+
+ words = (WORD *)my_malloc(sizeof(WORD)*(max_words_doc+10));
+ if(verbosity>=1) {
+ printf("Reading examples into memory..."); fflush(stdout);
+ }
+ dnum=0;
+ (*totwords)=0;
+ while((!feof(docfl)) && fgets(line,(int)ll,docfl)) {
+ if(line[0] == '#') continue; /* line contains comments */
+ if(!parse_document(line,words,&doc_label,&queryid,&slackid,&costfactor,
+ &wpos,max_words_doc,&comment)) {
+ printf("\nParsing error in line %ld!\n%s",dnum,line);
+ exit(1);
+ }
+ (*label)[dnum]=doc_label;
+ /* printf("docnum=%ld: Class=%f ",dnum,doc_label); */
+ if(doc_label > 0) dpos++;
+ if (doc_label < 0) dneg++;
+ if (doc_label == 0) dunlab++;
+ if((wpos>1) && ((words[wpos-2]).wnum>(*totwords)))
+ (*totwords)=(words[wpos-2]).wnum;
+ if((*totwords) > MAXFEATNUM) {
+ printf("\nMaximum feature number exceeds limit defined in MAXFEATNUM!\n");
+ printf("LINE: %s\n",line);
+ exit(1);
+ }
+ (*docs)[dnum] = create_example(dnum,queryid,slackid,costfactor,
+ create_svector(words,comment,1.0));
+ /* printf("\nNorm=%f\n",((*docs)[dnum]->fvec)->twonorm_sq); */
+ dnum++;
+ if(verbosity>=1) {
+ if((dnum % 100) == 0) {
+ printf("%ld..",dnum); fflush(stdout);
+ }
+ }
+ }
+
+ fclose(docfl);
+ free(line);
+ free(words);
+ if(verbosity>=1) {
+ fprintf(stdout, "OK. (%ld examples read)\n", dnum);
+ }
+ (*totdoc)=dnum;
+}
+
+int parse_document(char *line, WORD *words, double *label,
+ long *queryid, long *slackid, double *costfactor,
+ long int *numwords, long int max_words_doc,
+ char **comment)
+{
+ register long wpos,pos;
+ long wnum;
+ double weight;
+ int numread;
+ char featurepair[1000],junk[1000];
+
+ (*queryid)=0;
+ (*slackid)=0;
+ (*costfactor)=1;
+
+ pos=0;
+ (*comment)=NULL;
+ while(line[pos] ) { /* cut off comments */
+ if((line[pos] == '#') && (!(*comment))) {
+ line[pos]=0;
+ (*comment)=&(line[pos+1]);
+ }
+ if(line[pos] == '\n') { /* strip the CR */
+ line[pos]=0;
+ }
+ pos++;
+ }
+ if(!(*comment)) (*comment)=&(line[pos]);
+ /* printf("Comment: '%s'\n",(*comment)); */
+
+ wpos=0;
+ /* check, that line starts with target value or zero, but not with
+ feature pair */
+ if(sscanf(line,"%s",featurepair) == EOF) return(0);
+ pos=0;
+ while((featurepair[pos] != ':') && featurepair[pos]) pos++;
+ if(featurepair[pos] == ':') {
+ perror ("Line must start with label or 0!!!\n");
+ printf("LINE: %s\n",line);
+ exit (1);
+ }
+ /* read the target value */
+ if(sscanf(line,"%lf",label) == EOF) return(0);
+ pos=0;
+ while(space_or_null((int)line[pos])) pos++;
+ while((!space_or_null((int)line[pos])) && line[pos]) pos++;
+ while(((numread=sscanf(line+pos,"%s",featurepair)) != EOF) &&
+ (numread > 0) &&
+ (wpos<max_words_doc)) {
+ /* printf("%s\n",featurepair); */
+ while(space_or_null((int)line[pos])) pos++;
+ while((!space_or_null((int)line[pos])) && line[pos]) pos++;
+ if(sscanf(featurepair,"qid:%ld%s",&wnum,junk)==1) {
+ /* it is the query id */
+ (*queryid)=(long)wnum;
+ }
+ else if(sscanf(featurepair,"sid:%ld%s",&wnum,junk)==1) {
+ /* it is the slack id */
+ if(wnum > 0)
+ (*slackid)=(long)wnum;
+ else {
+ perror ("Slack-id must be greater or equal to 1!!!\n");
+ printf("LINE: %s\n",line);
+ exit (1);
+ }
+ }
+ else if(sscanf(featurepair,"cost:%lf%s",&weight,junk)==1) {
+ /* it is the example-dependent cost factor */
+ (*costfactor)=(double)weight;
+ }
+ else if(sscanf(featurepair,"%ld:%lf%s",&wnum,&weight,junk)==2) {
+ /* it is a regular feature */
+ if(wnum<=0) {
+ perror ("Feature numbers must be larger or equal to 1!!!\n");
+ printf("LINE: %s\n",line);
+ exit (1);
+ }
+ if((wpos>0) && ((words[wpos-1]).wnum >= wnum)) {
+ perror ("Features must be in increasing order!!!\n");
+ printf("LINE: %s\n",line);
+ exit (1);
+ }
+ (words[wpos]).wnum=wnum;
+ (words[wpos]).weight=(FVAL)weight;
+ wpos++;
+ }
+ else {
+ perror ("Cannot parse feature/value pair!!!\n");
+ printf("'%s' in LINE: %s\n",featurepair,line);
+ exit (1);
+ }
+ }
+ (words[wpos]).wnum=0;
+ (*numwords)=wpos+1;
+ return(1);
+}
+
+double *read_alphas(char *alphafile,long totdoc)
+ /* reads the alpha vector from a file as written by the
+ write_alphas function */
+{
+ FILE *fl;
+ double *alpha;
+ long dnum;
+
+ if ((fl = fopen (alphafile, "r")) == NULL)
+ { perror (alphafile); exit (1); }
+
+ alpha = (double *)my_malloc(sizeof(double)*totdoc);
+ if(verbosity>=1) {
+ printf("Reading alphas..."); fflush(stdout);
+ }
+ dnum=0;
+ while((!feof(fl)) && fscanf(fl,"%lf\n",&alpha[dnum]) && (dnum<totdoc)) {
+ dnum++;
+ }
+ if(dnum != totdoc)
+ { perror ("\nNot enough values in alpha file!"); exit (1); }
+ fclose(fl);
+
+ if(verbosity>=1) {
+ printf("done\n"); fflush(stdout);
+ }
+
+ return(alpha);
+}
+
+void nol_ll(char *file, long int *nol, long int *wol, long int *ll)
+ /* Grep through file and count number of lines, maximum number of
+ spaces per line, and longest line. */
+{
+ FILE *fl;
+ int ic;
+ char c;
+ long current_length,current_wol;
+
+ if ((fl = fopen (file, "r")) == NULL)
+ { perror (file); exit (1); }
+ current_length=0;
+ current_wol=0;
+ (*ll)=0;
+ (*nol)=1;
+ (*wol)=0;
+ while((ic=getc(fl)) != EOF) {
+ c=(char)ic;
+ current_length++;
+ if(space_or_null((int)c)) {
+ current_wol++;
+ }
+ if(c == '\n') {
+ (*nol)++;
+ if(current_length>(*ll)) {
+ (*ll)=current_length;
+ }
+ if(current_wol>(*wol)) {
+ (*wol)=current_wol;
+ }
+ current_length=0;
+ current_wol=0;
+ }
+ }
+ fclose(fl);
+}
+
+long minl(long int a, long int b)
+{
+ if(a<b)
+ return(a);
+ else
+ return(b);
+}
+
+long maxl(long int a, long int b)
+{
+ if(a>b)
+ return(a);
+ else
+ return(b);
+}
+
+long get_runtime(void)
+{
+ clock_t start;
+ start = clock();
+ return((long)((double)start*100.0/(double)CLOCKS_PER_SEC));
+}
+
+
+# ifdef _MSC_VER
+
+int isnan(double a)
+{
+ return(_isnan(a));
+}
+
+# endif
+
+int space_or_null(int c) {
+ if (c==0)
+ return 1;
+ return isspace((unsigned char)c);
+}
+
+void *my_malloc(size_t size)
+{
+ void *ptr;
+ if(size<=0) size=1; /* for AIX compatibility */
+ ptr=(void *)malloc(size);
+ if(!ptr) {
+ perror ("Out of memory!\n");
+ exit (1);
+ }
+ return(ptr);
+}
+
+void copyright_notice(void)
+{
+ printf("\nCopyright: Thorsten Joachims, thorsten@joachims.org\n\n");
+ printf("This software is available for non-commercial use only. It must not\n");
+ printf("be modified and distributed without prior permission of the author.\n");
+ printf("The author is not responsible for implications from the use of this\n");
+ printf("software.\n\n");
+}
diff --git a/trunk/svm_light/build/svm_light-tar/svm_common.h b/trunk/svm_light/build/svm_light-tar/svm_common.h
new file mode 100755
index 00000000..6487fa1d
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_common.h
@@ -0,0 +1,301 @@
+/************************************************************************/
+/* */
+/* svm_common.h */
+/* */
+/* Definitions and functions used in both svm_learn and svm_classify. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/************************************************************************/
+
+#ifndef SVM_COMMON
+#define SVM_COMMON
+
+# include <stdio.h>
+# include <ctype.h>
+# include <math.h>
+# include <string.h>
+# include <stdlib.h>
+# include <time.h>
+# include <float.h>
+
+# define VERSION "V6.02"
+# define VERSION_DATE "14.08.08"
+
+# define CFLOAT float /* the type of float to use for caching */
+ /* kernel evaluations. Using float saves */
+ /* us some memory, but you can use double, too */
+# define FNUM long /* the type used for storing feature ids */
+# define FVAL float /* the type used for storing feature values */
+# define MAXFEATNUM 99999999 /* maximum feature number (must be in
+ valid range of FNUM type and long int!) */
+
+# define LINEAR 0 /* linear kernel type */
+# define POLY 1 /* polynoial kernel type */
+# define RBF 2 /* rbf kernel type */
+# define SIGMOID 3 /* sigmoid kernel type */
+
+# define CLASSIFICATION 1 /* train classification model */
+# define REGRESSION 2 /* train regression model */
+# define RANKING 3 /* train ranking model */
+# define OPTIMIZATION 4 /* train on general set of constraints */
+
+# define MAXSHRINK 50000 /* maximum number of shrinking rounds */
+
+typedef struct word {
+ FNUM wnum; /* word number */
+ FVAL weight; /* word weight */
+} WORD;
+
+typedef struct svector {
+ WORD *words; /* The features/values in the vector by
+ increasing feature-number. Feature
+ numbers that are skipped are
+ interpreted as having value zero. */
+ double twonorm_sq; /* The squared euclidian length of the
+ vector. Used to speed up the RBF kernel. */
+ char *userdefined; /* You can put additional information
+ here. This can be useful, if you are
+ implementing your own kernel that
+ does not work with feature/values
+ representations (for example a
+ string kernel). By default,
+ svm-light will put here the string
+ after the # sign from each line of
+ the input file. */
+ long kernel_id; /* Feature vectors with different
+ kernel_id's are orthogonal (ie. the
+ feature number do not match). This
+ is used for computing component
+ kernels for linear constraints which
+ are a sum of several different
+ weight vectors. (currently not
+ implemented). */
+ struct svector *next; /* Let's you set up a list of SVECTOR's
+ for linear constraints which are a
+ sum of multiple feature
+ vectors. List is terminated by
+ NULL. */
+ double factor; /* Factor by which this feature vector
+ is multiplied in the sum. */
+} SVECTOR;
+
+typedef struct doc {
+ long docnum; /* Document ID. This has to be the position of
+ the document in the training set array. */
+ long queryid; /* for learning rankings, constraints are
+ generated for documents with the same
+ queryID. */
+ double costfactor; /* Scales the cost of misclassifying this
+ document by this factor. The effect of this
+ value is, that the upper bound on the alpha
+ for this example is scaled by this factor.
+ The factors are set by the feature
+ 'cost:<val>' in the training data. */
+ long slackid; /* Index of the slack variable
+ corresponding to this
+ constraint. All constraints with the
+ same slackid share the same slack
+ variable. This can only be used for
+ svm_learn_optimization. */
+ SVECTOR *fvec; /* Feature vector of the example. The
+ feature vector can actually be a
+ list of feature vectors. For
+ example, the list will have two
+ elements, if this DOC is a
+ preference constraint. The one
+ vector that is supposed to be ranked
+ higher, will have a factor of +1,
+ the lower ranked one should have a
+ factor of -1. */
+} DOC;
+
+typedef struct learn_parm {
+ long type; /* selects between regression and
+ classification */
+ double svm_c; /* upper bound C on alphas */
+ double eps; /* regression epsilon (eps=1.0 for
+ classification */
+ double svm_costratio; /* factor to multiply C for positive examples */
+ double transduction_posratio;/* fraction of unlabeled examples to be */
+ /* classified as positives */
+ long biased_hyperplane; /* if nonzero, use hyperplane w*x+b=0
+ otherwise w*x=0 */
+ long sharedslack; /* if nonzero, it will use the shared
+ slack variable mode in
+ svm_learn_optimization. It requires
+ that the slackid is set for every
+ training example */
+ long svm_maxqpsize; /* size q of working set */
+ long svm_newvarsinqp; /* new variables to enter the working set
+ in each iteration */
+ long kernel_cache_size; /* size of kernel cache in megabytes */
+ double epsilon_crit; /* tolerable error for distances used
+ in stopping criterion */
+ double epsilon_shrink; /* how much a multiplier should be above
+ zero for shrinking */
+ long svm_iter_to_shrink; /* iterations h after which an example can
+ be removed by shrinking */
+ long maxiter; /* number of iterations after which the
+ optimizer terminates, if there was
+ no progress in maxdiff */
+ long remove_inconsistent; /* exclude examples with alpha at C and
+ retrain */
+ long skip_final_opt_check; /* do not check KT-Conditions at the end of
+ optimization for examples removed by
+ shrinking. WARNING: This might lead to
+ sub-optimal solutions! */
+ long compute_loo; /* if nonzero, computes leave-one-out
+ estimates */
+ double rho; /* parameter in xi/alpha-estimates and for
+ pruning leave-one-out range [1..2] */
+ long xa_depth; /* parameter in xi/alpha-estimates upper
+ bounding the number of SV the current
+ alpha_t is distributed over */
+ char predfile[200]; /* file for predicitions on unlabeled examples
+ in transduction */
+ char alphafile[200]; /* file to store optimal alphas in. use
+ empty string if alphas should not be
+ output */
+
+ /* you probably do not want to touch the following */
+ double epsilon_const; /* tolerable error on eq-constraint */
+ double epsilon_a; /* tolerable error on alphas at bounds */
+ double opt_precision; /* precision of solver, set to e.g. 1e-21
+ if you get convergence problems */
+
+ /* the following are only for internal use */
+ long svm_c_steps; /* do so many steps for finding optimal C */
+ double svm_c_factor; /* increase C by this factor every step */
+ double svm_costratio_unlab;
+ double svm_unlabbound;
+ double *svm_cost; /* individual upper bounds for each var */
+ long totwords; /* number of features */
+} LEARN_PARM;
+
+typedef struct kernel_parm {
+ long kernel_type; /* 0=linear, 1=poly, 2=rbf, 3=sigmoid, 4=custom */
+ long poly_degree;
+ double rbf_gamma;
+ double coef_lin;
+ double coef_const;
+ char custom[50]; /* for user supplied kernel */
+} KERNEL_PARM;
+
+typedef struct model {
+ long sv_num;
+ long at_upper_bound;
+ double b;
+ DOC **supvec;
+ double *alpha;
+ long *index; /* index from docnum to position in model */
+ long totwords; /* number of features */
+ long totdoc; /* number of training documents */
+ KERNEL_PARM kernel_parm; /* kernel */
+
+ /* the following values are not written to file */
+ double loo_error,loo_recall,loo_precision; /* leave-one-out estimates */
+ double xa_error,xa_recall,xa_precision; /* xi/alpha estimates */
+ double *lin_weights; /* weights for linear case using
+ folding */
+ double maxdiff; /* precision, up to which this
+ model is accurate */
+} MODEL;
+
+typedef struct quadratic_program {
+ long opt_n; /* number of variables */
+ long opt_m; /* number of linear equality constraints */
+ double *opt_ce,*opt_ce0; /* linear equality constraints */
+ double *opt_g; /* hessian of objective */
+ double *opt_g0; /* linear part of objective */
+ double *opt_xinit; /* initial value for variables */
+ double *opt_low,*opt_up; /* box constraints */
+} QP;
+
+typedef struct kernel_cache {
+ long *index; /* cache some kernel evalutations */
+ CFLOAT *buffer; /* to improve speed */
+ long *invindex;
+ long *active2totdoc;
+ long *totdoc2active;
+ long *lru;
+ long *occu;
+ long elems;
+ long max_elems;
+ long time;
+ long activenum;
+ long buffsize;
+} KERNEL_CACHE;
+
+
+typedef struct timing_profile {
+ long time_kernel;
+ long time_opti;
+ long time_shrink;
+ long time_update;
+ long time_model;
+ long time_check;
+ long time_select;
+} TIMING;
+
+typedef struct shrink_state {
+ long *active;
+ long *inactive_since;
+ long deactnum;
+ double **a_history; /* for shrinking with non-linear kernel */
+ long maxhistory;
+ double *last_a; /* for shrinking with linear kernel */
+ double *last_lin; /* for shrinking with linear kernel */
+} SHRINK_STATE;
+
+double classify_example(MODEL *, DOC *);
+double classify_example_linear(MODEL *, DOC *);
+double kernel(KERNEL_PARM *, DOC *, DOC *);
+double single_kernel(KERNEL_PARM *, SVECTOR *, SVECTOR *);
+double custom_kernel(KERNEL_PARM *, SVECTOR *, SVECTOR *);
+SVECTOR *create_svector(WORD *, char *, double);
+SVECTOR *copy_svector(SVECTOR *);
+void free_svector(SVECTOR *);
+double sprod_ss(SVECTOR *, SVECTOR *);
+SVECTOR* sub_ss(SVECTOR *, SVECTOR *);
+SVECTOR* add_ss(SVECTOR *, SVECTOR *);
+SVECTOR* add_list_ss(SVECTOR *);
+void append_svector_list(SVECTOR *a, SVECTOR *b);
+SVECTOR* smult_s(SVECTOR *, double);
+int featvec_eq(SVECTOR *, SVECTOR *);
+double model_length_s(MODEL *, KERNEL_PARM *);
+void clear_vector_n(double *, long);
+void add_vector_ns(double *, SVECTOR *, double);
+double sprod_ns(double *, SVECTOR *);
+void add_weight_vector_to_linear_model(MODEL *);
+DOC *create_example(long, long, long, double, SVECTOR *);
+void free_example(DOC *, long);
+MODEL *read_model(char *);
+MODEL *copy_model(MODEL *);
+void free_model(MODEL *, int);
+void read_documents(char *, DOC ***, double **, long *, long *);
+int parse_document(char *, WORD *, double *, long *, long *, double *, long *, long, char **);
+double *read_alphas(char *,long);
+void nol_ll(char *, long *, long *, long *);
+long minl(long, long);
+long maxl(long, long);
+long get_runtime(void);
+int space_or_null(int);
+void *my_malloc(size_t);
+void copyright_notice(void);
+# ifdef _MSC_VER
+ int isnan(double);
+# endif
+
+extern long verbosity; /* verbosity level (0-4) */
+extern long kernel_cache_statistic;
+
+#endif
diff --git a/trunk/svm_light/build/svm_light-tar/svm_hideo.c b/trunk/svm_light/build/svm_light-tar/svm_hideo.c
new file mode 100755
index 00000000..ffad2d3c
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_hideo.c
@@ -0,0 +1,1062 @@
+/***********************************************************************/
+/* */
+/* svm_hideo.c */
+/* */
+/* The Hildreth and D'Espo solver specialized for SVMs. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/***********************************************************************/
+
+# include <math.h>
+# include "svm_common.h"
+
+/*
+ solve the quadratic programming problem
+
+ minimize g0 * x + 1/2 x' * G * x
+ subject to ce*x = ce0
+ l <= x <= u
+
+ The linear constraint vector ce can only have -1/+1 as entries
+*/
+
+/* Common Block Declarations */
+
+long verbosity;
+
+# define PRIMAL_OPTIMAL 1
+# define DUAL_OPTIMAL 2
+# define MAXITER_EXCEEDED 3
+# define NAN_SOLUTION 4
+# define ONLY_ONE_VARIABLE 5
+
+# define LARGEROUND 0
+# define SMALLROUND 1
+
+/* /////////////////////////////////////////////////////////////// */
+
+# define DEF_PRECISION 1E-5
+# define DEF_MAX_ITERATIONS 200
+# define DEF_LINDEP_SENSITIVITY 1E-8
+# define EPSILON_HIDEO 1E-20
+# define EPSILON_EQ 1E-5
+
+double *optimize_qp(QP *, double *, long, double *, LEARN_PARM *);
+double *primal=0,*dual=0;
+long precision_violations=0;
+double opt_precision=DEF_PRECISION;
+long maxiter=DEF_MAX_ITERATIONS;
+double lindep_sensitivity=DEF_LINDEP_SENSITIVITY;
+double *buffer;
+long *nonoptimal;
+
+long smallroundcount=0;
+long roundnumber=0;
+
+/* /////////////////////////////////////////////////////////////// */
+
+void *my_malloc();
+
+int optimize_hildreth_despo(long,long,double,double,double,long,long,long,double,double *,
+ double *,double *,double *,double *,double *,
+ double *,double *,double *,long *,double *,double *);
+int solve_dual(long,long,double,double,long,double *,double *,double *,
+ double *,double *,double *,double *,double *,double *,
+ double *,double *,double *,double *,long);
+
+void linvert_matrix(double *, long, double *, double, long *);
+void lprint_matrix(double *, long);
+void ladd_matrix(double *, long, double);
+void lcopy_matrix(double *, long, double *);
+void lswitch_rows_matrix(double *, long, long, long);
+void lswitchrk_matrix(double *, long, long, long);
+
+double calculate_qp_objective(long, double *, double *, double *);
+
+
+
+double *optimize_qp(qp,epsilon_crit,nx,threshold,learn_parm)
+QP *qp;
+double *epsilon_crit;
+long nx; /* Maximum number of variables in QP */
+double *threshold;
+LEARN_PARM *learn_parm;
+/* start the optimizer and return the optimal values */
+/* The HIDEO optimizer does not necessarily fully solve the problem. */
+/* Since it requires a strictly positive definite hessian, the solution */
+/* is restricted to a linear independent subset in case the matrix is */
+/* only semi-definite. */
+{
+ long i,j;
+ int result;
+ double eq,progress;
+
+ roundnumber++;
+
+ if(!primal) { /* allocate memory at first call */
+ primal=(double *)my_malloc(sizeof(double)*nx);
+ dual=(double *)my_malloc(sizeof(double)*((nx+1)*2));
+ nonoptimal=(long *)my_malloc(sizeof(long)*(nx));
+ buffer=(double *)my_malloc(sizeof(double)*((nx+1)*2*(nx+1)*2+
+ nx*nx+2*(nx+1)*2+2*nx+1+2*nx+
+ nx+nx+nx*nx));
+ (*threshold)=0;
+ for(i=0;i<nx;i++) {
+ primal[i]=0;
+ }
+ }
+
+ if(verbosity>=4) { /* really verbose */
+ printf("\n\n");
+ eq=qp->opt_ce0[0];
+ for(i=0;i<qp->opt_n;i++) {
+ eq+=qp->opt_xinit[i]*qp->opt_ce[i];
+ printf("%f: ",qp->opt_g0[i]);
+ for(j=0;j<qp->opt_n;j++) {
+ printf("%f ",qp->opt_g[i*qp->opt_n+j]);
+ }
+ printf(": a=%.10f < %f",qp->opt_xinit[i],qp->opt_up[i]);
+ printf(": y=%f\n",qp->opt_ce[i]);
+ }
+ if(qp->opt_m) {
+ printf("EQ: %f*x0",qp->opt_ce[0]);
+ for(i=1;i<qp->opt_n;i++) {
+ printf(" + %f*x%ld",qp->opt_ce[i],i);
+ }
+ printf(" = %f\n\n",-qp->opt_ce0[0]);
+ }
+ }
+
+ result=optimize_hildreth_despo(qp->opt_n,qp->opt_m,
+ opt_precision,(*epsilon_crit),
+ learn_parm->epsilon_a,maxiter,
+ /* (long)PRIMAL_OPTIMAL, */
+ (long)0, (long)0,
+ lindep_sensitivity,
+ qp->opt_g,qp->opt_g0,qp->opt_ce,qp->opt_ce0,
+ qp->opt_low,qp->opt_up,primal,qp->opt_xinit,
+ dual,nonoptimal,buffer,&progress);
+ if(verbosity>=3) {
+ printf("return(%d)...",result);
+ }
+
+ if(learn_parm->totwords < learn_parm->svm_maxqpsize) {
+ /* larger working sets will be linear dependent anyway */
+ learn_parm->svm_maxqpsize=maxl(learn_parm->totwords,(long)2);
+ }
+
+ if(result == NAN_SOLUTION) {
+ lindep_sensitivity*=2; /* throw out linear dependent examples more */
+ /* generously */
+ if(learn_parm->svm_maxqpsize>2) {
+ learn_parm->svm_maxqpsize--; /* decrease size of qp-subproblems */
+ }
+ precision_violations++;
+ }
+
+ /* take one round of only two variable to get unstuck */
+ if((result != PRIMAL_OPTIMAL) || (!(roundnumber % 31)) || (progress <= 0)) {
+
+ smallroundcount++;
+
+ result=optimize_hildreth_despo(qp->opt_n,qp->opt_m,
+ opt_precision,(*epsilon_crit),
+ learn_parm->epsilon_a,(long)maxiter,
+ (long)PRIMAL_OPTIMAL,(long)SMALLROUND,
+ lindep_sensitivity,
+ qp->opt_g,qp->opt_g0,qp->opt_ce,qp->opt_ce0,
+ qp->opt_low,qp->opt_up,primal,qp->opt_xinit,
+ dual,nonoptimal,buffer,&progress);
+ if(verbosity>=3) {
+ printf("return_srd(%d)...",result);
+ }
+
+ if(result != PRIMAL_OPTIMAL) {
+ if(result != ONLY_ONE_VARIABLE)
+ precision_violations++;
+ if(result == MAXITER_EXCEEDED)
+ maxiter+=100;
+ if(result == NAN_SOLUTION) {
+ lindep_sensitivity*=2; /* throw out linear dependent examples more */
+ /* generously */
+ /* results not valid, so return inital values */
+ for(i=0;i<qp->opt_n;i++) {
+ primal[i]=qp->opt_xinit[i];
+ }
+ }
+ }
+ }
+
+
+ if(precision_violations > 50) {
+ precision_violations=0;
+ (*epsilon_crit)*=10.0;
+ if(verbosity>=1) {
+ printf("\nWARNING: Relaxing epsilon on KT-Conditions (%f).\n",
+ (*epsilon_crit));
+ }
+ }
+
+ if((qp->opt_m>0) && (result != NAN_SOLUTION) && (!isnan(dual[1]-dual[0])))
+ (*threshold)=dual[1]-dual[0];
+ else
+ (*threshold)=0;
+
+ if(verbosity>=4) { /* really verbose */
+ printf("\n\n");
+ eq=qp->opt_ce0[0];
+ for(i=0;i<qp->opt_n;i++) {
+ eq+=primal[i]*qp->opt_ce[i];
+ printf("%f: ",qp->opt_g0[i]);
+ for(j=0;j<qp->opt_n;j++) {
+ printf("%f ",qp->opt_g[i*qp->opt_n+j]);
+ }
+ printf(": a=%.30f",primal[i]);
+ printf(": nonopti=%ld",nonoptimal[i]);
+ printf(": y=%f\n",qp->opt_ce[i]);
+ }
+ printf("eq-constraint=%.30f\n",eq);
+ printf("b=%f\n",(*threshold));
+ printf(" smallroundcount=%ld ",smallroundcount);
+ }
+
+ return(primal);
+}
+
+
+
+int optimize_hildreth_despo(n,m,precision,epsilon_crit,epsilon_a,maxiter,goal,
+ smallround,lindep_sensitivity,g,g0,ce,ce0,low,up,
+ primal,init,dual,lin_dependent,buffer,progress)
+ long n; /* number of variables */
+ long m; /* number of linear equality constraints [0,1] */
+ double precision; /* solve at least to this dual precision */
+ double epsilon_crit; /* stop, if KT-Conditions approx fulfilled */
+ double epsilon_a; /* precision of alphas at bounds */
+ long maxiter; /* stop after this many iterations */
+ long goal; /* keep going until goal fulfilled */
+ long smallround; /* use only two variables of steepest descent */
+ double lindep_sensitivity; /* epsilon for detecting linear dependent ex */
+ double *g; /* hessian of objective */
+ double *g0; /* linear part of objective */
+ double *ce,*ce0; /* linear equality constraints */
+ double *low,*up; /* box constraints */
+ double *primal; /* primal variables */
+ double *init; /* initial values of primal */
+ double *dual; /* dual variables */
+ long *lin_dependent;
+ double *buffer;
+ double *progress; /* delta in the objective function between
+ before and after */
+{
+ long i,j,k,from,to,n_indep,changed;
+ double sum,bmin=0,bmax=0;
+ double *d,*d0,*ig,*dual_old,*temp,*start;
+ double *g0_new,*g_new,*ce_new,*ce0_new,*low_new,*up_new;
+ double add,t;
+ int result;
+ double obj_before,obj_after;
+ long b1,b2;
+ double g0_b1,g0_b2,ce0_b;
+
+ g0_new=&(buffer[0]); /* claim regions of buffer */
+ d=&(buffer[n]);
+ d0=&(buffer[n+(n+m)*2*(n+m)*2]);
+ ce_new=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2]);
+ ce0_new=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n]);
+ ig=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m]);
+ dual_old=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m+n*n]);
+ low_new=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m+n*n+(n+m)*2]);
+ up_new=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m+n*n+(n+m)*2+n]);
+ start=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m+n*n+(n+m)*2+n+n]);
+ g_new=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m+n*n+(n+m)*2+n+n+n]);
+ temp=&(buffer[n+(n+m)*2*(n+m)*2+(n+m)*2+n+m+n*n+(n+m)*2+n+n+n+n*n]);
+
+ b1=-1;
+ b2=-1;
+ for(i=0;i<n;i++) { /* get variables with steepest feasible descent */
+ sum=g0[i];
+ for(j=0;j<n;j++)
+ sum+=init[j]*g[i*n+j];
+ sum=sum*ce[i];
+ if(((b1==-1) || (sum<bmin))
+ && (!((init[i]<=(low[i]+epsilon_a)) && (ce[i]<0.0)))
+ && (!((init[i]>=( up[i]-epsilon_a)) && (ce[i]>0.0)))
+ ) {
+ bmin=sum;
+ b1=i;
+ }
+ if(((b2==-1) || (sum>=bmax))
+ && (!((init[i]<=(low[i]+epsilon_a)) && (ce[i]>0.0)))
+ && (!((init[i]>=( up[i]-epsilon_a)) && (ce[i]<0.0)))
+ ) {
+ bmax=sum;
+ b2=i;
+ }
+ }
+ /* in case of unbiased hyperplane, the previous projection on */
+ /* equality constraint can lead to b1 or b2 being -1. */
+ if((b1 == -1) || (b2 == -1)) {
+ b1=maxl(b1,b2);
+ b2=maxl(b1,b2);
+ }
+
+ for(i=0;i<n;i++) {
+ start[i]=init[i];
+ }
+
+ /* in case both example vectors are linearly dependent */
+ /* WARNING: Assumes that ce[] in {-1,1} */
+ add=0;
+ changed=0;
+ if((b1 != b2) && (m==1)) {
+ for(i=0;i<n;i++) { /* fix other vectors */
+ if(i==b1)
+ g0_b1=g0[i];
+ if(i==b2)
+ g0_b2=g0[i];
+ }
+ ce0_b=ce0[0];
+ for(i=0;i<n;i++) {
+ if((i!=b1) && (i!=b2)) {
+ for(j=0;j<n;j++) {
+ if(j==b1)
+ g0_b1+=start[i]*g[i*n+j];
+ if(j==b2)
+ g0_b2+=start[i]*g[i*n+j];
+ }
+ ce0_b-=(start[i]*ce[i]);
+ }
+ }
+ if((g[b1*n+b2] == g[b1*n+b1]) && (g[b1*n+b2] == g[b2*n+b2])) {
+ /* printf("euqal\n"); */
+ if(ce[b1] == ce[b2]) {
+ if(g0_b1 <= g0_b2) { /* set b1 to upper bound */
+ /* printf("case +=<\n"); */
+ changed=1;
+ t=up[b1]-init[b1];
+ if((init[b2]-low[b2]) < t) {
+ t=init[b2]-low[b2];
+ }
+ start[b1]=init[b1]+t;
+ start[b2]=init[b2]-t;
+ }
+ else if(g0_b1 > g0_b2) { /* set b2 to upper bound */
+ /* printf("case +=>\n"); */
+ changed=1;
+ t=up[b2]-init[b2];
+ if((init[b1]-low[b1]) < t) {
+ t=init[b1]-low[b1];
+ }
+ start[b1]=init[b1]-t;
+ start[b2]=init[b2]+t;
+ }
+ }
+ else if(((g[b1*n+b1]>0) || (g[b2*n+b2]>0))) { /* (ce[b1] != ce[b2]) */
+ /* printf("case +!\n"); */
+ t=((ce[b2]/ce[b1])*g0[b1]-g0[b2]+ce0[0]*(g[b1*n+b1]*ce[b2]/ce[b1]-g[b1*n+b2]/ce[b1]))/((ce[b2]*ce[b2]/(ce[b1]*ce[b1]))*g[b1*n+b1]+g[b2*n+b2]-2*(g[b1*n+b2]*ce[b2]/ce[b1]))-init[b2];
+ changed=1;
+ if((up[b2]-init[b2]) < t) {
+ t=up[b2]-init[b2];
+ }
+ if((init[b2]-low[b2]) < -t) {
+ t=-(init[b2]-low[b2]);
+ }
+ if((up[b1]-init[b1]) < t) {
+ t=(up[b1]-init[b1]);
+ }
+ if((init[b1]-low[b1]) < -t) {
+ t=-(init[b1]-low[b1]);
+ }
+ start[b1]=init[b1]+t;
+ start[b2]=init[b2]+t;
+ }
+ }
+ if((-g[b1*n+b2] == g[b1*n+b1]) && (-g[b1*n+b2] == g[b2*n+b2])) {
+ /* printf("diffeuqal\n"); */
+ if(ce[b1] != ce[b2]) {
+ if((g0_b1+g0_b2) < 0) { /* set b1 and b2 to upper bound */
+ /* printf("case -!<\n"); */
+ changed=1;
+ t=up[b1]-init[b1];
+ if((up[b2]-init[b2]) < t) {
+ t=up[b2]-init[b2];
+ }
+ start[b1]=init[b1]+t;
+ start[b2]=init[b2]+t;
+ }
+ else if((g0_b1+g0_b2) >= 0) { /* set b1 and b2 to lower bound */
+ /* printf("case -!>\n"); */
+ changed=1;
+ t=init[b1]-low[b1];
+ if((init[b2]-low[b2]) < t) {
+ t=init[b2]-low[b2];
+ }
+ start[b1]=init[b1]-t;
+ start[b2]=init[b2]-t;
+ }
+ }
+ else if(((g[b1*n+b1]>0) || (g[b2*n+b2]>0))) { /* (ce[b1]==ce[b2]) */
+ /* printf("case -=\n"); */
+ t=((ce[b2]/ce[b1])*g0[b1]-g0[b2]+ce0[0]*(g[b1*n+b1]*ce[b2]/ce[b1]-g[b1*n+b2]/ce[b1]))/((ce[b2]*ce[b2]/(ce[b1]*ce[b1]))*g[b1*n+b1]+g[b2*n+b2]-2*(g[b1*n+b2]*ce[b2]/ce[b1]))-init[b2];
+ changed=1;
+ if((up[b2]-init[b2]) < t) {
+ t=up[b2]-init[b2];
+ }
+ if((init[b2]-low[b2]) < -t) {
+ t=-(init[b2]-low[b2]);
+ }
+ if((up[b1]-init[b1]) < -t) {
+ t=-(up[b1]-init[b1]);
+ }
+ if((init[b1]-low[b1]) < t) {
+ t=init[b1]-low[b1];
+ }
+ start[b1]=init[b1]-t;
+ start[b2]=init[b2]+t;
+ }
+ }
+ }
+ /* if we have a biased hyperplane, then adding a constant to the */
+ /* hessian does not change the solution. So that is done for examples */
+ /* with zero diagonal entry, since HIDEO cannot handle them. */
+ if((m>0)
+ && ((fabs(g[b1*n+b1]) < lindep_sensitivity)
+ || (fabs(g[b2*n+b2]) < lindep_sensitivity))) {
+ /* printf("Case 0\n"); */
+ add+=0.093274;
+ }
+ /* in case both examples are linear dependent */
+ else if((m>0)
+ && (g[b1*n+b2] != 0 && g[b2*n+b2] != 0)
+ && (fabs(g[b1*n+b1]/g[b1*n+b2] - g[b1*n+b2]/g[b2*n+b2])
+ < lindep_sensitivity)) {
+ /* printf("Case lindep\n"); */
+ add+=0.078274;
+ }
+
+ /* special case for zero diagonal entry on unbiased hyperplane */
+ if((m==0) && (b1>=0)) {
+ if(fabs(g[b1*n+b1]) < lindep_sensitivity) {
+ /* printf("Case 0b1\n"); */
+ for(i=0;i<n;i++) { /* fix other vectors */
+ if(i==b1)
+ g0_b1=g0[i];
+ }
+ for(i=0;i<n;i++) {
+ if(i!=b1) {
+ for(j=0;j<n;j++) {
+ if(j==b1)
+ g0_b1+=start[i]*g[i*n+j];
+ }
+ }
+ }
+ if(g0_b1<0)
+ start[b1]=up[b1];
+ if(g0_b1>=0)
+ start[b1]=low[b1];
+ }
+ }
+ if((m==0) && (b2>=0)) {
+ if(fabs(g[b2*n+b2]) < lindep_sensitivity) {
+ /* printf("Case 0b2\n"); */
+ for(i=0;i<n;i++) { /* fix other vectors */
+ if(i==b2)
+ g0_b2=g0[i];
+ }
+ for(i=0;i<n;i++) {
+ if(i!=b2) {
+ for(j=0;j<n;j++) {
+ if(j==b2)
+ g0_b2+=start[i]*g[i*n+j];
+ }
+ }
+ }
+ if(g0_b2<0)
+ start[b2]=up[b2];
+ if(g0_b2>=0)
+ start[b2]=low[b2];
+ }
+ }
+
+ /* printf("b1=%ld,b2=%ld\n",b1,b2); */
+
+ lcopy_matrix(g,n,d);
+ if((m==1) && (add>0.0)) {
+ for(j=0;j<n;j++) {
+ for(k=0;k<n;k++) {
+ d[j*n+k]+=add*ce[j]*ce[k];
+ }
+ }
+ }
+ else {
+ add=0.0;
+ }
+
+ if(n>2) { /* switch, so that variables are better mixed */
+ lswitchrk_matrix(d,n,b1,(long)0);
+ if(b2 == 0)
+ lswitchrk_matrix(d,n,b1,(long)1);
+ else
+ lswitchrk_matrix(d,n,b2,(long)1);
+ }
+ if(smallround == SMALLROUND) {
+ for(i=2;i<n;i++) {
+ lin_dependent[i]=1;
+ }
+ if(m>0) { /* for biased hyperplane, pick two variables */
+ lin_dependent[0]=0;
+ lin_dependent[1]=0;
+ }
+ else { /* for unbiased hyperplane, pick only one variable */
+ lin_dependent[0]=smallroundcount % 2;
+ lin_dependent[1]=(smallroundcount+1) % 2;
+ }
+ }
+ else {
+ for(i=0;i<n;i++) {
+ lin_dependent[i]=0;
+ }
+ }
+ linvert_matrix(d,n,ig,lindep_sensitivity,lin_dependent);
+ if(n>2) { /* now switch back */
+ if(b2 == 0) {
+ lswitchrk_matrix(ig,n,b1,(long)1);
+ i=lin_dependent[1];
+ lin_dependent[1]=lin_dependent[b1];
+ lin_dependent[b1]=i;
+ }
+ else {
+ lswitchrk_matrix(ig,n,b2,(long)1);
+ i=lin_dependent[1];
+ lin_dependent[1]=lin_dependent[b2];
+ lin_dependent[b2]=i;
+ }
+ lswitchrk_matrix(ig,n,b1,(long)0);
+ i=lin_dependent[0];
+ lin_dependent[0]=lin_dependent[b1];
+ lin_dependent[b1]=i;
+ }
+ /* lprint_matrix(d,n); */
+ /* lprint_matrix(ig,n); */
+
+ lcopy_matrix(g,n,g_new); /* restore g_new matrix */
+ if(add>0)
+ for(j=0;j<n;j++) {
+ for(k=0;k<n;k++) {
+ g_new[j*n+k]+=add*ce[j]*ce[k];
+ }
+ }
+
+ for(i=0;i<n;i++) { /* fix linear dependent vectors */
+ g0_new[i]=g0[i]+add*ce0[0]*ce[i];
+ }
+ if(m>0) ce0_new[0]=-ce0[0];
+ for(i=0;i<n;i++) { /* fix linear dependent vectors */
+ if(lin_dependent[i]) {
+ for(j=0;j<n;j++) {
+ if(!lin_dependent[j]) {
+ g0_new[j]+=start[i]*g_new[i*n+j];
+ }
+ }
+ if(m>0) ce0_new[0]-=(start[i]*ce[i]);
+ }
+ }
+ from=0; /* remove linear dependent vectors */
+ to=0;
+ n_indep=0;
+ for(i=0;i<n;i++) {
+ if(!lin_dependent[i]) {
+ g0_new[n_indep]=g0_new[i];
+ ce_new[n_indep]=ce[i];
+ low_new[n_indep]=low[i];
+ up_new[n_indep]=up[i];
+ primal[n_indep]=start[i];
+ n_indep++;
+ }
+ for(j=0;j<n;j++) {
+ if((!lin_dependent[i]) && (!lin_dependent[j])) {
+ ig[to]=ig[from];
+ g_new[to]=g_new[from];
+ to++;
+ }
+ from++;
+ }
+ }
+
+ if(verbosity>=3) {
+ printf("real_qp_size(%ld)...",n_indep);
+ }
+
+ /* cannot optimize with only one variable */
+ if((n_indep<=1) && (m>0) && (!changed)) {
+ for(i=n-1;i>=0;i--) {
+ primal[i]=init[i];
+ }
+ return((int)ONLY_ONE_VARIABLE);
+ }
+
+ if((!changed) || (n_indep>1)) {
+ result=solve_dual(n_indep,m,precision,epsilon_crit,maxiter,g_new,g0_new,
+ ce_new,ce0_new,low_new,up_new,primal,d,d0,ig,
+ dual,dual_old,temp,goal);
+ }
+ else {
+ result=PRIMAL_OPTIMAL;
+ }
+
+ j=n_indep;
+ for(i=n-1;i>=0;i--) {
+ if(!lin_dependent[i]) {
+ j--;
+ primal[i]=primal[j];
+ }
+ else {
+ primal[i]=start[i]; /* leave as is */
+ }
+ temp[i]=primal[i];
+ }
+
+ obj_before=calculate_qp_objective(n,g,g0,init);
+ obj_after=calculate_qp_objective(n,g,g0,primal);
+ (*progress)=obj_before-obj_after;
+ if(verbosity>=3) {
+ printf("before(%.30f)...after(%.30f)...result_sd(%d)...",
+ obj_before,obj_after,result);
+ }
+
+ return((int)result);
+}
+
+
+int solve_dual(n,m,precision,epsilon_crit,maxiter,g,g0,ce,ce0,low,up,primal,
+ d,d0,ig,dual,dual_old,temp,goal)
+ /* Solves the dual using the method of Hildreth and D'Espo. */
+ /* Can only handle problems with zero or exactly one */
+ /* equality constraints. */
+
+ long n; /* number of variables */
+ long m; /* number of linear equality constraints */
+ double precision; /* solve at least to this dual precision */
+ double epsilon_crit; /* stop, if KT-Conditions approx fulfilled */
+ long maxiter; /* stop after that many iterations */
+ double *g;
+ double *g0; /* linear part of objective */
+ double *ce,*ce0; /* linear equality constraints */
+ double *low,*up; /* box constraints */
+ double *primal; /* variables (with initial values) */
+ double *d,*d0,*ig,*dual,*dual_old,*temp; /* buffer */
+ long goal;
+{
+ long i,j,k,iter;
+ double sum,w,maxviol,viol,temp1,temp2,isnantest;
+ double model_b,dist;
+ long retrain,maxfaktor,primal_optimal=0,at_bound,scalemaxiter;
+ double epsilon_a=1E-15,epsilon_hideo;
+ double eq;
+
+ if((m<0) || (m>1))
+ perror("SOLVE DUAL: inappropriate number of eq-constrains!");
+
+ /*
+ printf("\n");
+ for(i=0;i<n;i++) {
+ printf("%f: ",g0[i]);
+ for(j=0;j<n;j++) {
+ printf("%f ",g[i*n+j]);
+ }
+ printf(": a=%.30f",primal[i]);
+ printf(": y=%f\n",ce[i]);
+ }
+ */
+
+ for(i=0;i<2*(n+m);i++) {
+ dual[i]=0;
+ dual_old[i]=0;
+ }
+ for(i=0;i<n;i++) {
+ for(j=0;j<n;j++) { /* dual hessian for box constraints */
+ d[i*2*(n+m)+j]=ig[i*n+j];
+ d[(i+n)*2*(n+m)+j]=-ig[i*n+j];
+ d[i*2*(n+m)+j+n]=-ig[i*n+j];
+ d[(i+n)*2*(n+m)+j+n]=ig[i*n+j];
+ }
+ if(m>0) {
+ sum=0; /* dual hessian for eq constraints */
+ for(j=0;j<n;j++) {
+ sum+=(ce[j]*ig[i*n+j]);
+ }
+ d[i*2*(n+m)+2*n]=sum;
+ d[i*2*(n+m)+2*n+1]=-sum;
+ d[(n+i)*2*(n+m)+2*n]=-sum;
+ d[(n+i)*2*(n+m)+2*n+1]=sum;
+ d[(n+n)*2*(n+m)+i]=sum;
+ d[(n+n+1)*2*(n+m)+i]=-sum;
+ d[(n+n)*2*(n+m)+(n+i)]=-sum;
+ d[(n+n+1)*2*(n+m)+(n+i)]=sum;
+
+ sum=0;
+ for(j=0;j<n;j++) {
+ for(k=0;k<n;k++) {
+ sum+=(ce[k]*ce[j]*ig[j*n+k]);
+ }
+ }
+ d[(n+n)*2*(n+m)+2*n]=sum;
+ d[(n+n)*2*(n+m)+2*n+1]=-sum;
+ d[(n+n+1)*2*(n+m)+2*n]=-sum;
+ d[(n+n+1)*2*(n+m)+2*n+1]=sum;
+ }
+ }
+
+ for(i=0;i<n;i++) { /* dual linear component for the box constraints */
+ w=0;
+ for(j=0;j<n;j++) {
+ w+=(ig[i*n+j]*g0[j]);
+ }
+ d0[i]=up[i]+w;
+ d0[i+n]=-low[i]-w;
+ }
+
+ if(m>0) {
+ sum=0; /* dual linear component for eq constraints */
+ for(j=0;j<n;j++) {
+ for(k=0;k<n;k++) {
+ sum+=(ce[k]*ig[k*n+j]*g0[j]);
+ }
+ }
+ d0[2*n]=ce0[0]+sum;
+ d0[2*n+1]=-ce0[0]-sum;
+ }
+
+ maxviol=999999;
+ iter=0;
+ retrain=1;
+ maxfaktor=1;
+ scalemaxiter=maxiter/5;
+ while((retrain) && (maxviol > 0) && (iter < (scalemaxiter*maxfaktor))) {
+ iter++;
+
+ while((maxviol > precision) && (iter < (scalemaxiter*maxfaktor))) {
+ iter++;
+ maxviol=0;
+ for(i=0;i<2*(n+m);i++) {
+ sum=d0[i];
+ for(j=0;j<2*(n+m);j++) {
+ sum+=d[i*2*(n+m)+j]*dual_old[j];
+ }
+ sum-=d[i*2*(n+m)+i]*dual_old[i];
+ dual[i]=-sum/d[i*2*(n+m)+i];
+ if(dual[i]<0) dual[i]=0;
+
+ viol=fabs(dual[i]-dual_old[i]);
+ if(viol>maxviol)
+ maxviol=viol;
+ dual_old[i]=dual[i];
+ }
+ /*
+ printf("%d) maxviol=%20f precision=%f\n",iter,maxviol,precision);
+ */
+ }
+
+ if(m>0) {
+ for(i=0;i<n;i++) {
+ temp[i]=dual[i]-dual[i+n]+ce[i]*(dual[n+n]-dual[n+n+1])+g0[i];
+ }
+ }
+ else {
+ for(i=0;i<n;i++) {
+ temp[i]=dual[i]-dual[i+n]+g0[i];
+ }
+ }
+ for(i=0;i<n;i++) {
+ primal[i]=0; /* calc value of primal variables */
+ for(j=0;j<n;j++) {
+ primal[i]+=ig[i*n+j]*temp[j];
+ }
+ primal[i]*=-1.0;
+ if(primal[i]<=(low[i])) { /* clip conservatively */
+ primal[i]=low[i];
+ }
+ else if(primal[i]>=(up[i])) {
+ primal[i]=up[i];
+ }
+ }
+
+ if(m>0)
+ model_b=dual[n+n+1]-dual[n+n];
+ else
+ model_b=0;
+
+ epsilon_hideo=EPSILON_HIDEO;
+ for(i=0;i<n;i++) { /* check precision of alphas */
+ dist=-model_b*ce[i];
+ dist+=(g0[i]+1.0);
+ for(j=0;j<i;j++) {
+ dist+=(primal[j]*g[j*n+i]);
+ }
+ for(j=i;j<n;j++) {
+ dist+=(primal[j]*g[i*n+j]);
+ }
+ if((primal[i]<(up[i]-epsilon_hideo)) && (dist < (1.0-epsilon_crit))) {
+ epsilon_hideo=(up[i]-primal[i])*2.0;
+ }
+ else if((primal[i]>(low[i]+epsilon_hideo)) &&(dist>(1.0+epsilon_crit))) {
+ epsilon_hideo=(primal[i]-low[i])*2.0;
+ }
+ }
+ /* printf("\nEPSILON_HIDEO=%.30f\n",epsilon_hideo); */
+
+ for(i=0;i<n;i++) { /* clip alphas to bounds */
+ if(primal[i]<=(low[i]+epsilon_hideo)) {
+ primal[i]=low[i];
+ }
+ else if(primal[i]>=(up[i]-epsilon_hideo)) {
+ primal[i]=up[i];
+ }
+ }
+
+ retrain=0;
+ primal_optimal=1;
+ at_bound=0;
+ for(i=0;(i<n);i++) { /* check primal KT-Conditions */
+ dist=-model_b*ce[i];
+ dist+=(g0[i]+1.0);
+ for(j=0;j<i;j++) {
+ dist+=(primal[j]*g[j*n+i]);
+ }
+ for(j=i;j<n;j++) {
+ dist+=(primal[j]*g[i*n+j]);
+ }
+ if((primal[i]<(up[i]-epsilon_a)) && (dist < (1.0-epsilon_crit))) {
+ retrain=1;
+ primal_optimal=0;
+ }
+ else if((primal[i]>(low[i]+epsilon_a)) && (dist > (1.0+epsilon_crit))) {
+ retrain=1;
+ primal_optimal=0;
+ }
+ if((primal[i]<=(low[i]+epsilon_a)) || (primal[i]>=(up[i]-epsilon_a))) {
+ at_bound++;
+ }
+ /* printf("HIDEOtemp: a[%ld]=%.30f, dist=%.6f, b=%f, at_bound=%ld\n",i,primal[i],dist,model_b,at_bound); */
+ }
+ if(m>0) {
+ eq=-ce0[0]; /* check precision of eq-constraint */
+ for(i=0;i<n;i++) {
+ eq+=(ce[i]*primal[i]);
+ }
+ if((EPSILON_EQ < fabs(eq))
+ /*
+ && !((goal==PRIMAL_OPTIMAL)
+ && (at_bound==n)) */
+ ) {
+ retrain=1;
+ primal_optimal=0;
+ }
+ /* printf("\n eq=%.30f ce0=%f at-bound=%ld\n",eq,ce0[0],at_bound); */
+ }
+
+ if(retrain) {
+ precision/=10;
+ if(((goal == PRIMAL_OPTIMAL) && (maxfaktor < 50000))
+ || (maxfaktor < 5)) {
+ maxfaktor++;
+ }
+ }
+ }
+
+ if(!primal_optimal) {
+ for(i=0;i<n;i++) {
+ primal[i]=0; /* calc value of primal variables */
+ for(j=0;j<n;j++) {
+ primal[i]+=ig[i*n+j]*temp[j];
+ }
+ primal[i]*=-1.0;
+ if(primal[i]<=(low[i]+epsilon_a)) { /* clip conservatively */
+ primal[i]=low[i];
+ }
+ else if(primal[i]>=(up[i]-epsilon_a)) {
+ primal[i]=up[i];
+ }
+ }
+ }
+
+ isnantest=0;
+ for(i=0;i<n;i++) { /* check for isnan */
+ isnantest+=primal[i];
+ }
+
+ if(m>0) {
+ temp1=dual[n+n+1]; /* copy the dual variables for the eq */
+ temp2=dual[n+n]; /* constraints to a handier location */
+ for(i=n+n+1;i>=2;i--) {
+ dual[i]=dual[i-2];
+ }
+ dual[0]=temp2;
+ dual[1]=temp1;
+ isnantest+=temp1+temp2;
+ }
+
+ if(isnan(isnantest)) {
+ return((int)NAN_SOLUTION);
+ }
+ else if(primal_optimal) {
+ return((int)PRIMAL_OPTIMAL);
+ }
+ else if(maxviol == 0.0) {
+ return((int)DUAL_OPTIMAL);
+ }
+ else {
+ return((int)MAXITER_EXCEEDED);
+ }
+}
+
+
+void linvert_matrix(matrix,depth,inverse,lindep_sensitivity,lin_dependent)
+double *matrix;
+long depth;
+double *inverse,lindep_sensitivity;
+long *lin_dependent; /* indicates the active parts of matrix on
+ input and output*/
+{
+ long i,j,k;
+ double factor;
+
+ for(i=0;i<depth;i++) {
+ /* lin_dependent[i]=0; */
+ for(j=0;j<depth;j++) {
+ inverse[i*depth+j]=0.0;
+ }
+ inverse[i*depth+i]=1.0;
+ }
+ for(i=0;i<depth;i++) {
+ if(lin_dependent[i] || (fabs(matrix[i*depth+i])<lindep_sensitivity)) {
+ lin_dependent[i]=1;
+ }
+ else {
+ for(j=i+1;j<depth;j++) {
+ factor=matrix[j*depth+i]/matrix[i*depth+i];
+ for(k=i;k<depth;k++) {
+ matrix[j*depth+k]-=(factor*matrix[i*depth+k]);
+ }
+ for(k=0;k<depth;k++) {
+ inverse[j*depth+k]-=(factor*inverse[i*depth+k]);
+ }
+ }
+ }
+ }
+ for(i=depth-1;i>=0;i--) {
+ if(!lin_dependent[i]) {
+ factor=1/matrix[i*depth+i];
+ for(k=0;k<depth;k++) {
+ inverse[i*depth+k]*=factor;
+ }
+ matrix[i*depth+i]=1;
+ for(j=i-1;j>=0;j--) {
+ factor=matrix[j*depth+i];
+ matrix[j*depth+i]=0;
+ for(k=0;k<depth;k++) {
+ inverse[j*depth+k]-=(factor*inverse[i*depth+k]);
+ }
+ }
+ }
+ }
+}
+
+void lprint_matrix(matrix,depth)
+double *matrix;
+long depth;
+{
+ long i,j;
+ for(i=0;i<depth;i++) {
+ for(j=0;j<depth;j++) {
+ printf("%5.2f ",(double)(matrix[i*depth+j]));
+ }
+ printf("\n");
+ }
+ printf("\n");
+}
+
+void ladd_matrix(matrix,depth,scalar)
+double *matrix;
+long depth;
+double scalar;
+{
+ long i,j;
+ for(i=0;i<depth;i++) {
+ for(j=0;j<depth;j++) {
+ matrix[i*depth+j]+=scalar;
+ }
+ }
+}
+
+void lcopy_matrix(matrix,depth,matrix2)
+double *matrix;
+long depth;
+double *matrix2;
+{
+ long i;
+
+ for(i=0;i<(depth)*(depth);i++) {
+ matrix2[i]=matrix[i];
+ }
+}
+
+void lswitch_rows_matrix(matrix,depth,r1,r2)
+double *matrix;
+long depth,r1,r2;
+{
+ long i;
+ double temp;
+
+ for(i=0;i<depth;i++) {
+ temp=matrix[r1*depth+i];
+ matrix[r1*depth+i]=matrix[r2*depth+i];
+ matrix[r2*depth+i]=temp;
+ }
+}
+
+void lswitchrk_matrix(matrix,depth,rk1,rk2)
+double *matrix;
+long depth,rk1,rk2;
+{
+ long i;
+ double temp;
+
+ for(i=0;i<depth;i++) {
+ temp=matrix[rk1*depth+i];
+ matrix[rk1*depth+i]=matrix[rk2*depth+i];
+ matrix[rk2*depth+i]=temp;
+ }
+ for(i=0;i<depth;i++) {
+ temp=matrix[i*depth+rk1];
+ matrix[i*depth+rk1]=matrix[i*depth+rk2];
+ matrix[i*depth+rk2]=temp;
+ }
+}
+
+double calculate_qp_objective(opt_n,opt_g,opt_g0,alpha)
+long opt_n;
+double *opt_g,*opt_g0,*alpha;
+{
+ double obj;
+ long i,j;
+ obj=0; /* calculate objective */
+ for(i=0;i<opt_n;i++) {
+ obj+=(opt_g0[i]*alpha[i]);
+ obj+=(0.5*alpha[i]*alpha[i]*opt_g[i*opt_n+i]);
+ for(j=0;j<i;j++) {
+ obj+=(alpha[j]*alpha[i]*opt_g[j*opt_n+i]);
+ }
+ }
+ return(obj);
+}
diff --git a/trunk/svm_light/build/svm_light-tar/svm_learn.c b/trunk/svm_light/build/svm_light-tar/svm_learn.c
new file mode 100755
index 00000000..d2b5a89b
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_learn.c
@@ -0,0 +1,4650 @@
+/***********************************************************************/
+/* */
+/* svm_learn.c */
+/* */
+/* Learning module of Support Vector Machine. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/***********************************************************************/
+
+
+# include "svm_common.h"
+# include "svm_learn.h"
+
+
+/* interface to QP-solver */
+double *optimize_qp(QP *, double *, long, double *, LEARN_PARM *);
+
+/*---------------------------------------------------------------------------*/
+
+void svm_learn_classification_extend(DOC **docs, double *class, long int
+ totdoc, long int totwords,
+ LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache,
+ MODEL *model,
+ double *alpha,
+ int* nerrors,
+ double* maxerror)
+{
+ long *inconsistent, i, *label;
+ long inconsistentnum;
+ long misclassified, upsupvecnum;
+ double loss, model_length, example_length;
+ double maxdiff, *lin, *a, *c;
+ long runtime_start, runtime_end;
+ long iterations;
+ long *unlabeled, transduction;
+ long heldout;
+ long loo_count = 0, loo_count_pos = 0, loo_count_neg = 0, trainpos = 0, trainneg = 0;
+ long loocomputed = 0, runtime_start_loo = 0, runtime_start_xa = 0;
+ double heldout_c = 0, r_delta_sq = 0, r_delta, r_delta_avg;
+ long *index, *index2dnum;
+ double *weights;
+ CFLOAT *aicache; /* buffer to keep one row of hessian */
+
+ double *xi_fullset; /* buffer for storing xi on full sample in loo */
+ double *a_fullset; /* buffer for storing alpha on full sample in loo */
+ TIMING timing_profile;
+ SHRINK_STATE shrink_state;
+
+ runtime_start = get_runtime();
+ timing_profile.time_kernel = 0;
+ timing_profile.time_opti = 0;
+ timing_profile.time_shrink = 0;
+ timing_profile.time_update = 0;
+ timing_profile.time_model = 0;
+ timing_profile.time_check = 0;
+ timing_profile.time_select = 0;
+ kernel_cache_statistic = 0;
+
+ learn_parm->totwords = totwords;
+
+ /* make sure -n value is reasonable */
+ if ((learn_parm->svm_newvarsinqp < 2)
+ || (learn_parm->svm_newvarsinqp > learn_parm->svm_maxqpsize))
+ {
+ learn_parm->svm_newvarsinqp = learn_parm->svm_maxqpsize;
+ }
+
+ init_shrink_state(&shrink_state, totdoc, (long)MAXSHRINK);
+
+ label = (long *)my_malloc(sizeof(long) * totdoc);
+ inconsistent = (long *)my_malloc(sizeof(long) * totdoc);
+ unlabeled = (long *)my_malloc(sizeof(long) * totdoc);
+ c = (double *)my_malloc(sizeof(double) * totdoc);
+ a = (double *)my_malloc(sizeof(double) * totdoc);
+ a_fullset = (double *)my_malloc(sizeof(double) * totdoc);
+ xi_fullset = (double *)my_malloc(sizeof(double) * totdoc);
+ lin = (double *)my_malloc(sizeof(double) * totdoc);
+ learn_parm->svm_cost = (double *)my_malloc(sizeof(double) * totdoc);
+ model->supvec = (DOC **)my_malloc(sizeof(DOC *) * (totdoc + 2));
+ model->alpha = (double *)my_malloc(sizeof(double) * (totdoc + 2));
+ model->index = (long *)my_malloc(sizeof(long) * (totdoc + 2));
+
+ model->at_upper_bound = 0;
+ model->b = 0;
+ model->supvec[0] = 0; /* element 0 reserved and empty for now */
+ model->alpha[0] = 0;
+ model->lin_weights = NULL;
+ model->totwords = totwords;
+ model->totdoc = totdoc;
+ model->kernel_parm = (*kernel_parm);
+ model->sv_num = 1;
+ model->loo_error = -1;
+ model->loo_recall = -1;
+ model->loo_precision = -1;
+ model->xa_error = -1;
+ model->xa_recall = -1;
+ model->xa_precision = -1;
+ inconsistentnum = 0;
+ transduction = 0;
+
+ r_delta = estimate_r_delta(docs, totdoc, kernel_parm);
+ r_delta_sq = r_delta * r_delta;
+
+ r_delta_avg = estimate_r_delta_average(docs, totdoc, kernel_parm);
+ if (learn_parm->svm_c == 0.0) /* default value for C */
+ {
+ learn_parm->svm_c = 1.0 / (r_delta_avg * r_delta_avg);
+ if (verbosity >= 1)
+ printf("Setting default regularization parameter C=%.4f\n",
+ learn_parm->svm_c);
+ }
+
+ learn_parm->eps = -1.0; /* equivalent regression epsilon for
+ classification */
+
+ for (i = 0; i < totdoc; i++) /* various inits */
+ {
+ docs[i]->docnum = i;
+ inconsistent[i] = 0;
+ a[i] = 0;
+ lin[i] = 0;
+ c[i] = 0.0;
+ unlabeled[i] = 0;
+ if (class[i] == 0)
+ {
+ unlabeled[i] = 1;
+ label[i] = 0;
+ transduction = 1;
+ }
+ if (class[i] > 0)
+ {
+ learn_parm->svm_cost[i] = learn_parm->svm_c * learn_parm->svm_costratio *
+ docs[i]->costfactor;
+ label[i] = 1;
+ trainpos++;
+ }
+ else if (class[i] < 0)
+ {
+ learn_parm->svm_cost[i] = learn_parm->svm_c * docs[i]->costfactor;
+ label[i] = -1;
+ trainneg++;
+ }
+ else
+ {
+ learn_parm->svm_cost[i] = 0;
+ }
+ }
+ if (verbosity >= 2)
+ {
+ printf("%ld positive, %ld negative, and %ld unlabeled examples.\n", trainpos, trainneg, totdoc - trainpos - trainneg);
+ fflush(stdout);
+ }
+
+ /* caching makes no sense for linear kernel */
+ if (kernel_parm->kernel_type == LINEAR)
+ {
+ kernel_cache = NULL;
+ }
+
+ /* compute starting state for initial alpha values */
+ if (alpha)
+ {
+ if (verbosity >= 1)
+ {
+ printf("Computing starting state...");
+ fflush(stdout);
+ }
+ index = (long *)my_malloc(sizeof(long) * totdoc);
+ index2dnum = (long *)my_malloc(sizeof(long) * (totdoc + 11));
+ weights = (double *)my_malloc(sizeof(double) * (totwords + 1));
+ aicache = (CFLOAT *)my_malloc(sizeof(CFLOAT) * totdoc);
+ for (i = 0; i < totdoc; i++) /* create full index and clip alphas */
+ {
+ index[i] = 1;
+ alpha[i] = fabs(alpha[i]);
+ if (alpha[i] < 0) alpha[i] = 0;
+ if (alpha[i] > learn_parm->svm_cost[i]) alpha[i] = learn_parm->svm_cost[i];
+ }
+ if (kernel_parm->kernel_type != LINEAR)
+ {
+ for (i = 0; i < totdoc; i++) /* fill kernel cache with unbounded SV */
+ if ((alpha[i] > 0) && (alpha[i] < learn_parm->svm_cost[i])
+ && (kernel_cache_space_available(kernel_cache)))
+ cache_kernel_row(kernel_cache, docs, i, kernel_parm);
+ for (i = 0; i < totdoc; i++) /* fill rest of kernel cache with bounded SV */
+ if ((alpha[i] == learn_parm->svm_cost[i])
+ && (kernel_cache_space_available(kernel_cache)))
+ cache_kernel_row(kernel_cache, docs, i, kernel_parm);
+ }
+ (void)compute_index(index, totdoc, index2dnum);
+ update_linear_component(docs, label, index2dnum, alpha, a, index2dnum, totdoc,
+ totwords, kernel_parm, kernel_cache, lin, aicache,
+ weights);
+ (void)calculate_svm_model(docs, label, unlabeled, lin, alpha, a, c,
+ learn_parm, index2dnum, index2dnum, model);
+ for (i = 0; i < totdoc; i++) /* copy initial alphas */
+ {
+ a[i] = alpha[i];
+ }
+ free(index);
+ free(index2dnum);
+ free(weights);
+ free(aicache);
+ if (verbosity >= 1)
+ {
+ printf("done.\n");
+ fflush(stdout);
+ }
+ }
+
+ if (transduction)
+ {
+ learn_parm->svm_iter_to_shrink = 99999999;
+ if (verbosity >= 1)
+ printf("\nDeactivating Shrinking due to an incompatibility with the transductive \nlearner in the current version.\n\n");
+ }
+
+
+ if (transduction && learn_parm->compute_loo)
+ {
+ learn_parm->compute_loo = 0;
+ if (verbosity >= 1)
+ printf("\nCannot compute leave-one-out estimates for transductive learner.\n\n");
+ }
+
+ if (learn_parm->remove_inconsistent && learn_parm->compute_loo)
+ {
+ learn_parm->compute_loo = 0;
+ printf("\nCannot compute leave-one-out estimates when removing inconsistent examples.\n\n");
+ }
+
+ if (learn_parm->compute_loo && ((trainpos == 1) || (trainneg == 1)))
+ {
+ learn_parm->compute_loo = 0;
+ printf("\nCannot compute leave-one-out with only one example in one class.\n\n");
+ }
+
+
+ if (verbosity == 1)
+ {
+ printf("Optimizing");
+ fflush(stdout);
+ }
+
+ /* train the svm */
+ iterations = optimize_to_convergence(docs, label, totdoc, totwords, learn_parm,
+ kernel_parm, kernel_cache, &shrink_state, model,
+ inconsistent, unlabeled, a, lin,
+ c, &timing_profile,
+ &maxdiff, (long) - 1,
+ (long)1);
+
+ misclassified = 0;
+ double maxerror_ = 0;
+ for (i = 0; (i < totdoc); i++) /* get final statistic */
+ {
+ if ((lin[i] - model->b)*(double)label[i] <= 0.0)
+ {
+ misclassified++;
+ if(maxerror_ < -(lin[i] - model->b)*(double)label[i])
+ maxerror_ = -(lin[i] - model->b)*(double)label[i];
+ }
+ }
+
+ *nerrors = misclassified;
+ *maxerror = maxerror_;
+
+ if (verbosity >= 1)
+ {
+ if (verbosity == 1) printf("done. (%ld iterations)\n", iterations);
+
+ misclassified = 0;
+ for (i = 0; (i < totdoc); i++) /* get final statistic */
+ {
+ if ((lin[i] - model->b)*(double)label[i] <= 0.0)
+ misclassified++;
+ }
+
+ printf("Optimization finished (%ld misclassified, maxdiff=%.5f).\n",
+ misclassified, maxdiff);
+
+ runtime_end = get_runtime();
+ if (verbosity >= 2)
+ {
+ printf("Runtime in cpu-seconds: %.2f (%.2f%% for kernel/%.2f%% for optimizer/%.2f%% for final/%.2f%% for update/%.2f%% for model/%.2f%% for check/%.2f%% for select)\n",
+ ((float)runtime_end - (float)runtime_start) / 100.0,
+ (100.0*timing_profile.time_kernel) / (float)(runtime_end - runtime_start),
+ (100.0*timing_profile.time_opti) / (float)(runtime_end - runtime_start),
+ (100.0*timing_profile.time_shrink) / (float)(runtime_end - runtime_start),
+ (100.0*timing_profile.time_update) / (float)(runtime_end - runtime_start),
+ (100.0*timing_profile.time_model) / (float)(runtime_end - runtime_start),
+ (100.0*timing_profile.time_check) / (float)(runtime_end - runtime_start),
+ (100.0*timing_profile.time_select) / (float)(runtime_end - runtime_start));
+ }
+ else
+ {
+ printf("Runtime in cpu-seconds: %.2f\n",
+ (runtime_end - runtime_start) / 100.0);
+ }
+
+ if (learn_parm->remove_inconsistent)
+ {
+ inconsistentnum = 0;
+ for (i = 0; i < totdoc; i++)
+ if (inconsistent[i])
+ inconsistentnum++;
+ printf("Number of SV: %ld (plus %ld inconsistent examples)\n",
+ model->sv_num - 1, inconsistentnum);
+ }
+ else
+ {
+ upsupvecnum = 0;
+ for (i = 1; i < model->sv_num; i++)
+ {
+ if (fabs(model->alpha[i]) >=
+ (learn_parm->svm_cost[(model->supvec[i])->docnum] -
+ learn_parm->epsilon_a))
+ upsupvecnum++;
+ }
+ printf("Number of SV: %ld (including %ld at upper bound)\n",
+ model->sv_num - 1, upsupvecnum);
+ }
+
+ if ((verbosity >= 1) && (!learn_parm->skip_final_opt_check))
+ {
+ loss = 0;
+ model_length = 0;
+ for (i = 0; i < totdoc; i++)
+ {
+ if ((lin[i] - model->b)*(double)label[i] < 1.0 - learn_parm->epsilon_crit)
+ loss += 1.0 - (lin[i] - model->b) * (double)label[i];
+ model_length += a[i] * label[i] * lin[i];
+ }
+ model_length = sqrt(model_length);
+ fprintf(stdout, "L1 loss: loss=%.5f\n", loss);
+ fprintf(stdout, "Norm of weight vector: |w|=%.5f\n", model_length);
+ example_length = estimate_sphere(model, kernel_parm);
+ fprintf(stdout, "Norm of longest example vector: |x|=%.5f\n",
+ length_of_longest_document_vector(docs, totdoc, kernel_parm));
+ fprintf(stdout, "Estimated VCdim of classifier: VCdim<=%.5f\n",
+ estimate_margin_vcdim(model, model_length, example_length,
+ kernel_parm));
+ if ((!learn_parm->remove_inconsistent) && (!transduction))
+ {
+ runtime_start_xa = get_runtime();
+ if (verbosity >= 1)
+ {
+ printf("Computing XiAlpha-estimates...");
+ fflush(stdout);
+ }
+ compute_xa_estimates(model, label, unlabeled, totdoc, docs, lin, a,
+ kernel_parm, learn_parm, &(model->xa_error),
+ &(model->xa_recall), &(model->xa_precision));
+ if (verbosity >= 1)
+ {
+ printf("done\n");
+ }
+ printf("Runtime for XiAlpha-estimates in cpu-seconds: %.2f\n",
+ (get_runtime() - runtime_start_xa) / 100.0);
+
+ fprintf(stdout, "XiAlpha-estimate of the error: error<=%.2f%% (rho=%.2f,depth=%ld)\n",
+ model->xa_error, learn_parm->rho, learn_parm->xa_depth);
+ fprintf(stdout, "XiAlpha-estimate of the recall: recall=>%.2f%% (rho=%.2f,depth=%ld)\n",
+ model->xa_recall, learn_parm->rho, learn_parm->xa_depth);
+ fprintf(stdout, "XiAlpha-estimate of the precision: precision=>%.2f%% (rho=%.2f,depth=%ld)\n",
+ model->xa_precision, learn_parm->rho, learn_parm->xa_depth);
+ }
+ else if (!learn_parm->remove_inconsistent)
+ {
+ estimate_transduction_quality(model, label, unlabeled, totdoc, docs, lin);
+ }
+ }
+ if (verbosity >= 1)
+ {
+ printf("Number of kernel evaluations: %ld\n", kernel_cache_statistic);
+ }
+ }
+
+
+ /* leave-one-out testing starts now */
+ if (learn_parm->compute_loo)
+ {
+ /* save results of training on full dataset for leave-one-out */
+ runtime_start_loo = get_runtime();
+ for (i = 0; i < totdoc; i++)
+ {
+ xi_fullset[i] = 1.0 - ((lin[i] - model->b) * (double)label[i]);
+ if (xi_fullset[i] < 0) xi_fullset[i] = 0;
+ a_fullset[i] = a[i];
+ }
+ if (verbosity >= 1)
+ {
+ printf("Computing leave-one-out");
+ }
+
+ /* repeat this loop for every held-out example */
+ for (heldout = 0; (heldout < totdoc); heldout++)
+ {
+ if (learn_parm->rho*a_fullset[heldout]*r_delta_sq + xi_fullset[heldout]
+ < 1.0)
+ {
+ /* guaranteed to not produce a leave-one-out error */
+ if (verbosity == 1)
+ {
+ printf("+");
+ fflush(stdout);
+ }
+ }
+ else if (xi_fullset[heldout] > 1.0)
+ {
+ /* guaranteed to produce a leave-one-out error */
+ loo_count++;
+ if (label[heldout] > 0) loo_count_pos++;
+ else loo_count_neg++;
+ if (verbosity == 1)
+ {
+ printf("-");
+ fflush(stdout);
+ }
+ }
+ else
+ {
+ loocomputed++;
+ heldout_c = learn_parm->svm_cost[heldout]; /* set upper bound to zero */
+ learn_parm->svm_cost[heldout] = 0;
+ /* make sure heldout example is not currently */
+ /* shrunk away. Assumes that lin is up to date! */
+ shrink_state.active[heldout] = 1;
+ if (verbosity >= 2)
+ printf("\nLeave-One-Out test on example %ld\n", heldout);
+ if (verbosity >= 1)
+ {
+ printf("(?[%ld]", heldout);
+ fflush(stdout);
+ }
+
+ optimize_to_convergence(docs, label, totdoc, totwords, learn_parm,
+ kernel_parm,
+ kernel_cache, &shrink_state, model, inconsistent, unlabeled,
+ a, lin, c, &timing_profile,
+ &maxdiff, heldout, (long)2);
+
+ /* printf("%.20f\n",(lin[heldout]-model->b)*(double)label[heldout]); */
+
+ if (((lin[heldout] - model->b)*(double)label[heldout]) <= 0.0)
+ {
+ loo_count++; /* there was a loo-error */
+ if (label[heldout] > 0) loo_count_pos++;
+ else loo_count_neg++;
+ if (verbosity >= 1)
+ {
+ printf("-)");
+ fflush(stdout);
+ }
+ }
+ else
+ {
+ if (verbosity >= 1)
+ {
+ printf("+)");
+ fflush(stdout);
+ }
+ }
+ /* now we need to restore the original data set*/
+ learn_parm->svm_cost[heldout] = heldout_c; /* restore upper bound */
+ }
+ } /* end of leave-one-out loop */
+
+
+ if (verbosity >= 1)
+ {
+ printf("\nRetrain on full problem");
+ fflush(stdout);
+ }
+ optimize_to_convergence(docs, label, totdoc, totwords, learn_parm,
+ kernel_parm,
+ kernel_cache, &shrink_state, model, inconsistent, unlabeled,
+ a, lin, c, &timing_profile,
+ &maxdiff, (long) - 1, (long)1);
+ if (verbosity >= 1)
+ printf("done.\n");
+
+
+ /* after all leave-one-out computed */
+ model->loo_error = 100.0 * loo_count / (double)totdoc;
+
+ model->loo_recall = (1.0 - (double)loo_count_pos / (double)trainpos) * 100.0;
+ model->loo_precision = (trainpos - loo_count_pos) /
+ (double)(trainpos - loo_count_pos + loo_count_neg) * 100.0;
+ if (verbosity >= 1)
+ {
+ fprintf(stdout, "Leave-one-out estimate of the error: error=%.2f%%\n",
+ model->loo_error);
+ fprintf(stdout, "Leave-one-out estimate of the recall: recall=%.2f%%\n",
+ model->loo_recall);
+ fprintf(stdout, "Leave-one-out estimate of the precision: precision=%.2f%%\n",
+ model->loo_precision);
+ fprintf(stdout, "Actual leave-one-outs computed: %ld (rho=%.2f)\n",
+ loocomputed, learn_parm->rho);
+ printf("Runtime for leave-one-out in cpu-seconds: %.2f\n",
+ (double)(get_runtime() - runtime_start_loo) / 100.0);
+ }
+ }
+
+ if (learn_parm->alphafile[0])
+ write_alphas(learn_parm->alphafile, a, label, totdoc);
+
+ shrink_state_cleanup(&shrink_state);
+ free(label);
+ free(inconsistent);
+ free(unlabeled);
+ free(c);
+ free(a);
+ free(a_fullset);
+ free(xi_fullset);
+ free(lin);
+ free(learn_parm->svm_cost);
+}
+
+
+/* Learns an SVM classification model based on the training data in
+ docs/label. The resulting model is returned in the structure
+ model. */
+
+void svm_learn_classification(DOC **docs, double *class, long int
+ totdoc, long int totwords,
+ LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache,
+ MODEL *model,
+ double *alpha)
+ /* docs: Training vectors (x-part) */
+ /* class: Training labels (y-part, zero if test example for
+ transduction) */
+ /* totdoc: Number of examples in docs/label */
+ /* totwords: Number of features (i.e. highest feature index) */
+ /* learn_parm: Learning paramenters */
+ /* kernel_parm: Kernel paramenters */
+ /* kernel_cache:Initialized Cache of size totdoc, if using a kernel.
+ NULL if linear.*/
+ /* model: Returns learning result (assumed empty before called) */
+ /* alpha: Start values for the alpha variables or NULL
+ pointer. The new alpha values are returned after
+ optimization if not NULL. Array must be of size totdoc. */
+{
+ long *inconsistent,i,*label;
+ long inconsistentnum;
+ long misclassified,upsupvecnum;
+ double loss,model_length,example_length;
+ double maxdiff,*lin,*a,*c;
+ long runtime_start,runtime_end;
+ long iterations;
+ long *unlabeled,transduction;
+ long heldout;
+ long loo_count=0,loo_count_pos=0,loo_count_neg=0,trainpos=0,trainneg=0;
+ long loocomputed=0,runtime_start_loo=0,runtime_start_xa=0;
+ double heldout_c=0,r_delta_sq=0,r_delta,r_delta_avg;
+ long *index,*index2dnum;
+ double *weights;
+ CFLOAT *aicache; /* buffer to keep one row of hessian */
+
+ double *xi_fullset; /* buffer for storing xi on full sample in loo */
+ double *a_fullset; /* buffer for storing alpha on full sample in loo */
+ TIMING timing_profile;
+ SHRINK_STATE shrink_state;
+
+ runtime_start=get_runtime();
+ timing_profile.time_kernel=0;
+ timing_profile.time_opti=0;
+ timing_profile.time_shrink=0;
+ timing_profile.time_update=0;
+ timing_profile.time_model=0;
+ timing_profile.time_check=0;
+ timing_profile.time_select=0;
+ kernel_cache_statistic=0;
+
+ learn_parm->totwords=totwords;
+
+ /* make sure -n value is reasonable */
+ if((learn_parm->svm_newvarsinqp < 2)
+ || (learn_parm->svm_newvarsinqp > learn_parm->svm_maxqpsize)) {
+ learn_parm->svm_newvarsinqp=learn_parm->svm_maxqpsize;
+ }
+
+ init_shrink_state(&shrink_state,totdoc,(long)MAXSHRINK);
+
+ label = (long *)my_malloc(sizeof(long)*totdoc);
+ inconsistent = (long *)my_malloc(sizeof(long)*totdoc);
+ unlabeled = (long *)my_malloc(sizeof(long)*totdoc);
+ c = (double *)my_malloc(sizeof(double)*totdoc);
+ a = (double *)my_malloc(sizeof(double)*totdoc);
+ a_fullset = (double *)my_malloc(sizeof(double)*totdoc);
+ xi_fullset = (double *)my_malloc(sizeof(double)*totdoc);
+ lin = (double *)my_malloc(sizeof(double)*totdoc);
+ learn_parm->svm_cost = (double *)my_malloc(sizeof(double)*totdoc);
+ model->supvec = (DOC **)my_malloc(sizeof(DOC *)*(totdoc+2));
+ model->alpha = (double *)my_malloc(sizeof(double)*(totdoc+2));
+ model->index = (long *)my_malloc(sizeof(long)*(totdoc+2));
+
+ model->at_upper_bound=0;
+ model->b=0;
+ model->supvec[0]=0; /* element 0 reserved and empty for now */
+ model->alpha[0]=0;
+ model->lin_weights=NULL;
+ model->totwords=totwords;
+ model->totdoc=totdoc;
+ model->kernel_parm=(*kernel_parm);
+ model->sv_num=1;
+ model->loo_error=-1;
+ model->loo_recall=-1;
+ model->loo_precision=-1;
+ model->xa_error=-1;
+ model->xa_recall=-1;
+ model->xa_precision=-1;
+ inconsistentnum=0;
+ transduction=0;
+
+ r_delta=estimate_r_delta(docs,totdoc,kernel_parm);
+ r_delta_sq=r_delta*r_delta;
+
+ r_delta_avg=estimate_r_delta_average(docs,totdoc,kernel_parm);
+ if(learn_parm->svm_c == 0.0) { /* default value for C */
+ learn_parm->svm_c=1.0/(r_delta_avg*r_delta_avg);
+ if(verbosity>=1)
+ printf("Setting default regularization parameter C=%.4f\n",
+ learn_parm->svm_c);
+ }
+
+ learn_parm->eps=-1.0; /* equivalent regression epsilon for
+ classification */
+
+ for(i=0;i<totdoc;i++) { /* various inits */
+ docs[i]->docnum=i;
+ inconsistent[i]=0;
+ a[i]=0;
+ lin[i]=0;
+ c[i]=0.0;
+ unlabeled[i]=0;
+ if(class[i] == 0) {
+ unlabeled[i]=1;
+ label[i]=0;
+ transduction=1;
+ }
+ if(class[i] > 0) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*learn_parm->svm_costratio*
+ docs[i]->costfactor;
+ label[i]=1;
+ trainpos++;
+ }
+ else if(class[i] < 0) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*docs[i]->costfactor;
+ label[i]=-1;
+ trainneg++;
+ }
+ else {
+ learn_parm->svm_cost[i]=0;
+ }
+ }
+ if(verbosity>=2) {
+ printf("%ld positive, %ld negative, and %ld unlabeled examples.\n",trainpos,trainneg,totdoc-trainpos-trainneg); fflush(stdout);
+ }
+
+ /* caching makes no sense for linear kernel */
+ if(kernel_parm->kernel_type == LINEAR) {
+ kernel_cache = NULL;
+ }
+
+ /* compute starting state for initial alpha values */
+ if(alpha) {
+ if(verbosity>=1) {
+ printf("Computing starting state..."); fflush(stdout);
+ }
+ index = (long *)my_malloc(sizeof(long)*totdoc);
+ index2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ weights=(double *)my_malloc(sizeof(double)*(totwords+1));
+ aicache = (CFLOAT *)my_malloc(sizeof(CFLOAT)*totdoc);
+ for(i=0;i<totdoc;i++) { /* create full index and clip alphas */
+ index[i]=1;
+ alpha[i]=fabs(alpha[i]);
+ if(alpha[i]<0) alpha[i]=0;
+ if(alpha[i]>learn_parm->svm_cost[i]) alpha[i]=learn_parm->svm_cost[i];
+ }
+ if(kernel_parm->kernel_type != LINEAR) {
+ for(i=0;i<totdoc;i++) /* fill kernel cache with unbounded SV */
+ if((alpha[i]>0) && (alpha[i]<learn_parm->svm_cost[i])
+ && (kernel_cache_space_available(kernel_cache)))
+ cache_kernel_row(kernel_cache,docs,i,kernel_parm);
+ for(i=0;i<totdoc;i++) /* fill rest of kernel cache with bounded SV */
+ if((alpha[i]==learn_parm->svm_cost[i])
+ && (kernel_cache_space_available(kernel_cache)))
+ cache_kernel_row(kernel_cache,docs,i,kernel_parm);
+ }
+ (void)compute_index(index,totdoc,index2dnum);
+ update_linear_component(docs,label,index2dnum,alpha,a,index2dnum,totdoc,
+ totwords,kernel_parm,kernel_cache,lin,aicache,
+ weights);
+ (void)calculate_svm_model(docs,label,unlabeled,lin,alpha,a,c,
+ learn_parm,index2dnum,index2dnum,model);
+ for(i=0;i<totdoc;i++) { /* copy initial alphas */
+ a[i]=alpha[i];
+ }
+ free(index);
+ free(index2dnum);
+ free(weights);
+ free(aicache);
+ if(verbosity>=1) {
+ printf("done.\n"); fflush(stdout);
+ }
+ }
+
+ if(transduction) {
+ learn_parm->svm_iter_to_shrink=99999999;
+ if(verbosity >= 1)
+ printf("\nDeactivating Shrinking due to an incompatibility with the transductive \nlearner in the current version.\n\n");
+ }
+
+ if(transduction && learn_parm->compute_loo) {
+ learn_parm->compute_loo=0;
+ if(verbosity >= 1)
+ printf("\nCannot compute leave-one-out estimates for transductive learner.\n\n");
+ }
+
+ if(learn_parm->remove_inconsistent && learn_parm->compute_loo) {
+ learn_parm->compute_loo=0;
+ printf("\nCannot compute leave-one-out estimates when removing inconsistent examples.\n\n");
+ }
+
+ if(learn_parm->compute_loo && ((trainpos == 1) || (trainneg == 1))) {
+ learn_parm->compute_loo=0;
+ printf("\nCannot compute leave-one-out with only one example in one class.\n\n");
+ }
+
+
+ if(verbosity==1) {
+ printf("Optimizing"); fflush(stdout);
+ }
+
+ /* train the svm */
+ iterations=optimize_to_convergence(docs,label,totdoc,totwords,learn_parm,
+ kernel_parm,kernel_cache,&shrink_state,model,
+ inconsistent,unlabeled,a,lin,
+ c,&timing_profile,
+ &maxdiff,(long)-1,
+ (long)1);
+
+ if(verbosity>=1) {
+ if(verbosity==1) printf("done. (%ld iterations)\n",iterations);
+
+ misclassified=0;
+ for(i=0;(i<totdoc);i++) { /* get final statistic */
+ if((lin[i]-model->b)*(double)label[i] <= 0.0)
+ misclassified++;
+ }
+
+ printf("Optimization finished (%ld misclassified, maxdiff=%.5f).\n",
+ misclassified,maxdiff);
+
+ runtime_end=get_runtime();
+ if(verbosity>=2) {
+ printf("Runtime in cpu-seconds: %.2f (%.2f%% for kernel/%.2f%% for optimizer/%.2f%% for final/%.2f%% for update/%.2f%% for model/%.2f%% for check/%.2f%% for select)\n",
+ ((float)runtime_end-(float)runtime_start)/100.0,
+ (100.0*timing_profile.time_kernel)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_opti)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_shrink)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_update)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_model)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_check)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_select)/(float)(runtime_end-runtime_start));
+ }
+ else {
+ printf("Runtime in cpu-seconds: %.2f\n",
+ (runtime_end-runtime_start)/100.0);
+ }
+
+ if(learn_parm->remove_inconsistent) {
+ inconsistentnum=0;
+ for(i=0;i<totdoc;i++)
+ if(inconsistent[i])
+ inconsistentnum++;
+ printf("Number of SV: %ld (plus %ld inconsistent examples)\n",
+ model->sv_num-1,inconsistentnum);
+ }
+ else {
+ upsupvecnum=0;
+ for(i=1;i<model->sv_num;i++) {
+ if(fabs(model->alpha[i]) >=
+ (learn_parm->svm_cost[(model->supvec[i])->docnum]-
+ learn_parm->epsilon_a))
+ upsupvecnum++;
+ }
+ printf("Number of SV: %ld (including %ld at upper bound)\n",
+ model->sv_num-1,upsupvecnum);
+ }
+
+ if((verbosity>=1) && (!learn_parm->skip_final_opt_check)) {
+ loss=0;
+ model_length=0;
+ for(i=0;i<totdoc;i++) {
+ if((lin[i]-model->b)*(double)label[i] < 1.0-learn_parm->epsilon_crit)
+ loss+=1.0-(lin[i]-model->b)*(double)label[i];
+ model_length+=a[i]*label[i]*lin[i];
+ }
+ model_length=sqrt(model_length);
+ fprintf(stdout,"L1 loss: loss=%.5f\n",loss);
+ fprintf(stdout,"Norm of weight vector: |w|=%.5f\n",model_length);
+ example_length=estimate_sphere(model,kernel_parm);
+ fprintf(stdout,"Norm of longest example vector: |x|=%.5f\n",
+ length_of_longest_document_vector(docs,totdoc,kernel_parm));
+ fprintf(stdout,"Estimated VCdim of classifier: VCdim<=%.5f\n",
+ estimate_margin_vcdim(model,model_length,example_length,
+ kernel_parm));
+ if((!learn_parm->remove_inconsistent) && (!transduction)) {
+ runtime_start_xa=get_runtime();
+ if(verbosity>=1) {
+ printf("Computing XiAlpha-estimates..."); fflush(stdout);
+ }
+ compute_xa_estimates(model,label,unlabeled,totdoc,docs,lin,a,
+ kernel_parm,learn_parm,&(model->xa_error),
+ &(model->xa_recall),&(model->xa_precision));
+ if(verbosity>=1) {
+ printf("done\n");
+ }
+ printf("Runtime for XiAlpha-estimates in cpu-seconds: %.2f\n",
+ (get_runtime()-runtime_start_xa)/100.0);
+
+ fprintf(stdout,"XiAlpha-estimate of the error: error<=%.2f%% (rho=%.2f,depth=%ld)\n",
+ model->xa_error,learn_parm->rho,learn_parm->xa_depth);
+ fprintf(stdout,"XiAlpha-estimate of the recall: recall=>%.2f%% (rho=%.2f,depth=%ld)\n",
+ model->xa_recall,learn_parm->rho,learn_parm->xa_depth);
+ fprintf(stdout,"XiAlpha-estimate of the precision: precision=>%.2f%% (rho=%.2f,depth=%ld)\n",
+ model->xa_precision,learn_parm->rho,learn_parm->xa_depth);
+ }
+ else if(!learn_parm->remove_inconsistent) {
+ estimate_transduction_quality(model,label,unlabeled,totdoc,docs,lin);
+ }
+ }
+ if(verbosity>=1) {
+ printf("Number of kernel evaluations: %ld\n",kernel_cache_statistic);
+ }
+ }
+
+
+ /* leave-one-out testing starts now */
+ if(learn_parm->compute_loo) {
+ /* save results of training on full dataset for leave-one-out */
+ runtime_start_loo=get_runtime();
+ for(i=0;i<totdoc;i++) {
+ xi_fullset[i]=1.0-((lin[i]-model->b)*(double)label[i]);
+ if(xi_fullset[i]<0) xi_fullset[i]=0;
+ a_fullset[i]=a[i];
+ }
+ if(verbosity>=1) {
+ printf("Computing leave-one-out");
+ }
+
+ /* repeat this loop for every held-out example */
+ for(heldout=0;(heldout<totdoc);heldout++) {
+ if(learn_parm->rho*a_fullset[heldout]*r_delta_sq+xi_fullset[heldout]
+ < 1.0) {
+ /* guaranteed to not produce a leave-one-out error */
+ if(verbosity==1) {
+ printf("+"); fflush(stdout);
+ }
+ }
+ else if(xi_fullset[heldout] > 1.0) {
+ /* guaranteed to produce a leave-one-out error */
+ loo_count++;
+ if(label[heldout] > 0) loo_count_pos++; else loo_count_neg++;
+ if(verbosity==1) {
+ printf("-"); fflush(stdout);
+ }
+ }
+ else {
+ loocomputed++;
+ heldout_c=learn_parm->svm_cost[heldout]; /* set upper bound to zero */
+ learn_parm->svm_cost[heldout]=0;
+ /* make sure heldout example is not currently */
+ /* shrunk away. Assumes that lin is up to date! */
+ shrink_state.active[heldout]=1;
+ if(verbosity>=2)
+ printf("\nLeave-One-Out test on example %ld\n",heldout);
+ if(verbosity>=1) {
+ printf("(?[%ld]",heldout); fflush(stdout);
+ }
+
+ optimize_to_convergence(docs,label,totdoc,totwords,learn_parm,
+ kernel_parm,
+ kernel_cache,&shrink_state,model,inconsistent,unlabeled,
+ a,lin,c,&timing_profile,
+ &maxdiff,heldout,(long)2);
+
+ /* printf("%.20f\n",(lin[heldout]-model->b)*(double)label[heldout]); */
+
+ if(((lin[heldout]-model->b)*(double)label[heldout]) <= 0.0) {
+ loo_count++; /* there was a loo-error */
+ if(label[heldout] > 0) loo_count_pos++; else loo_count_neg++;
+ if(verbosity>=1) {
+ printf("-)"); fflush(stdout);
+ }
+ }
+ else {
+ if(verbosity>=1) {
+ printf("+)"); fflush(stdout);
+ }
+ }
+ /* now we need to restore the original data set*/
+ learn_parm->svm_cost[heldout]=heldout_c; /* restore upper bound */
+ }
+ } /* end of leave-one-out loop */
+
+
+ if(verbosity>=1) {
+ printf("\nRetrain on full problem"); fflush(stdout);
+ }
+ optimize_to_convergence(docs,label,totdoc,totwords,learn_parm,
+ kernel_parm,
+ kernel_cache,&shrink_state,model,inconsistent,unlabeled,
+ a,lin,c,&timing_profile,
+ &maxdiff,(long)-1,(long)1);
+ if(verbosity >= 1)
+ printf("done.\n");
+
+
+ /* after all leave-one-out computed */
+ model->loo_error=100.0*loo_count/(double)totdoc;
+ model->loo_recall=(1.0-(double)loo_count_pos/(double)trainpos)*100.0;
+ model->loo_precision=(trainpos-loo_count_pos)/
+ (double)(trainpos-loo_count_pos+loo_count_neg)*100.0;
+ if(verbosity >= 1) {
+ fprintf(stdout,"Leave-one-out estimate of the error: error=%.2f%%\n",
+ model->loo_error);
+ fprintf(stdout,"Leave-one-out estimate of the recall: recall=%.2f%%\n",
+ model->loo_recall);
+ fprintf(stdout,"Leave-one-out estimate of the precision: precision=%.2f%%\n",
+ model->loo_precision);
+ fprintf(stdout,"Actual leave-one-outs computed: %ld (rho=%.2f)\n",
+ loocomputed,learn_parm->rho);
+ printf("Runtime for leave-one-out in cpu-seconds: %.2f\n",
+ (double)(get_runtime()-runtime_start_loo)/100.0);
+ }
+ }
+
+ if(learn_parm->alphafile[0])
+ write_alphas(learn_parm->alphafile,a,label,totdoc);
+
+ shrink_state_cleanup(&shrink_state);
+ free(label);
+ free(inconsistent);
+ free(unlabeled);
+ free(c);
+ free(a);
+ free(a_fullset);
+ free(xi_fullset);
+ free(lin);
+ free(learn_parm->svm_cost);
+}
+
+
+/* Learns an SVM regression model based on the training data in
+ docs/label. The resulting model is returned in the structure
+ model. */
+
+void svm_learn_regression(DOC **docs, double *value, long int totdoc,
+ long int totwords, LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE **kernel_cache, MODEL *model)
+ /* docs: Training vectors (x-part) */
+ /* class: Training value (y-part) */
+ /* totdoc: Number of examples in docs/label */
+ /* totwords: Number of features (i.e. highest feature index) */
+ /* learn_parm: Learning paramenters */
+ /* kernel_parm: Kernel paramenters */
+ /* kernel_cache:Initialized Cache, if using a kernel. NULL if
+ linear. Note that it will be free'd and reassigned */
+ /* model: Returns learning result (assumed empty before called) */
+{
+ long *inconsistent,i,j;
+ long inconsistentnum;
+ long upsupvecnum;
+ double loss,model_length,example_length;
+ double maxdiff,*lin,*a,*c;
+ long runtime_start,runtime_end;
+ long iterations,kernel_cache_size;
+ long *unlabeled;
+ double r_delta_sq=0,r_delta,r_delta_avg;
+ double *xi_fullset; /* buffer for storing xi on full sample in loo */
+ double *a_fullset; /* buffer for storing alpha on full sample in loo */
+ TIMING timing_profile;
+ SHRINK_STATE shrink_state;
+ DOC **docs_org;
+ long *label;
+
+ /* set up regression problem in standard form */
+ docs_org=docs;
+ docs = (DOC **)my_malloc(sizeof(DOC)*2*totdoc);
+ label = (long *)my_malloc(sizeof(long)*2*totdoc);
+ c = (double *)my_malloc(sizeof(double)*2*totdoc);
+ for(i=0;i<totdoc;i++) {
+ j=2*totdoc-1-i;
+ docs[i]=create_example(i,0,0,docs_org[i]->costfactor,docs_org[i]->fvec);
+ label[i]=+1;
+ c[i]=value[i];
+ docs[j]=create_example(j,0,0,docs_org[i]->costfactor,docs_org[i]->fvec);
+ label[j]=-1;
+ c[j]=value[i];
+ }
+ totdoc*=2;
+
+ /* need to get a bigger kernel cache */
+ if(*kernel_cache) {
+ kernel_cache_size=(*kernel_cache)->buffsize*sizeof(CFLOAT)/(1024*1024);
+ kernel_cache_cleanup(*kernel_cache);
+ (*kernel_cache)=kernel_cache_init(totdoc,kernel_cache_size);
+ }
+
+ runtime_start=get_runtime();
+ timing_profile.time_kernel=0;
+ timing_profile.time_opti=0;
+ timing_profile.time_shrink=0;
+ timing_profile.time_update=0;
+ timing_profile.time_model=0;
+ timing_profile.time_check=0;
+ timing_profile.time_select=0;
+ kernel_cache_statistic=0;
+
+ learn_parm->totwords=totwords;
+
+ /* make sure -n value is reasonable */
+ if((learn_parm->svm_newvarsinqp < 2)
+ || (learn_parm->svm_newvarsinqp > learn_parm->svm_maxqpsize)) {
+ learn_parm->svm_newvarsinqp=learn_parm->svm_maxqpsize;
+ }
+
+ init_shrink_state(&shrink_state,totdoc,(long)MAXSHRINK);
+
+ inconsistent = (long *)my_malloc(sizeof(long)*totdoc);
+ unlabeled = (long *)my_malloc(sizeof(long)*totdoc);
+ a = (double *)my_malloc(sizeof(double)*totdoc);
+ a_fullset = (double *)my_malloc(sizeof(double)*totdoc);
+ xi_fullset = (double *)my_malloc(sizeof(double)*totdoc);
+ lin = (double *)my_malloc(sizeof(double)*totdoc);
+ learn_parm->svm_cost = (double *)my_malloc(sizeof(double)*totdoc);
+ model->supvec = (DOC **)my_malloc(sizeof(DOC *)*(totdoc+2));
+ model->alpha = (double *)my_malloc(sizeof(double)*(totdoc+2));
+ model->index = (long *)my_malloc(sizeof(long)*(totdoc+2));
+
+ model->at_upper_bound=0;
+ model->b=0;
+ model->supvec[0]=0; /* element 0 reserved and empty for now */
+ model->alpha[0]=0;
+ model->lin_weights=NULL;
+ model->totwords=totwords;
+ model->totdoc=totdoc;
+ model->kernel_parm=(*kernel_parm);
+ model->sv_num=1;
+ model->loo_error=-1;
+ model->loo_recall=-1;
+ model->loo_precision=-1;
+ model->xa_error=-1;
+ model->xa_recall=-1;
+ model->xa_precision=-1;
+ inconsistentnum=0;
+
+ r_delta=estimate_r_delta(docs,totdoc,kernel_parm);
+ r_delta_sq=r_delta*r_delta;
+
+ r_delta_avg=estimate_r_delta_average(docs,totdoc,kernel_parm);
+ if(learn_parm->svm_c == 0.0) { /* default value for C */
+ learn_parm->svm_c=1.0/(r_delta_avg*r_delta_avg);
+ if(verbosity>=1)
+ printf("Setting default regularization parameter C=%.4f\n",
+ learn_parm->svm_c);
+ }
+
+ for(i=0;i<totdoc;i++) { /* various inits */
+ inconsistent[i]=0;
+ a[i]=0;
+ lin[i]=0;
+ unlabeled[i]=0;
+ if(label[i] > 0) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*learn_parm->svm_costratio*
+ docs[i]->costfactor;
+ }
+ else if(label[i] < 0) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*docs[i]->costfactor;
+ }
+ }
+
+ /* caching makes no sense for linear kernel */
+ if((kernel_parm->kernel_type == LINEAR) && (*kernel_cache)) {
+ printf("WARNING: Using a kernel cache for linear case will slow optimization down!\n");
+ }
+
+ if(verbosity==1) {
+ printf("Optimizing"); fflush(stdout);
+ }
+
+ /* train the svm */
+ iterations=optimize_to_convergence(docs,label,totdoc,totwords,learn_parm,
+ kernel_parm,*kernel_cache,&shrink_state,
+ model,inconsistent,unlabeled,a,lin,c,
+ &timing_profile,&maxdiff,(long)-1,
+ (long)1);
+
+ if(verbosity>=1) {
+ if(verbosity==1) printf("done. (%ld iterations)\n",iterations);
+
+ printf("Optimization finished (maxdiff=%.5f).\n",maxdiff);
+
+ runtime_end=get_runtime();
+ if(verbosity>=2) {
+ printf("Runtime in cpu-seconds: %.2f (%.2f%% for kernel/%.2f%% for optimizer/%.2f%% for final/%.2f%% for update/%.2f%% for model/%.2f%% for check/%.2f%% for select)\n",
+ ((float)runtime_end-(float)runtime_start)/100.0,
+ (100.0*timing_profile.time_kernel)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_opti)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_shrink)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_update)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_model)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_check)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_select)/(float)(runtime_end-runtime_start));
+ }
+ else {
+ printf("Runtime in cpu-seconds: %.2f\n",
+ (runtime_end-runtime_start)/100.0);
+ }
+
+ if(learn_parm->remove_inconsistent) {
+ inconsistentnum=0;
+ for(i=0;i<totdoc;i++)
+ if(inconsistent[i])
+ inconsistentnum++;
+ printf("Number of SV: %ld (plus %ld inconsistent examples)\n",
+ model->sv_num-1,inconsistentnum);
+ }
+ else {
+ upsupvecnum=0;
+ for(i=1;i<model->sv_num;i++) {
+ if(fabs(model->alpha[i]) >=
+ (learn_parm->svm_cost[(model->supvec[i])->docnum]-
+ learn_parm->epsilon_a))
+ upsupvecnum++;
+ }
+ printf("Number of SV: %ld (including %ld at upper bound)\n",
+ model->sv_num-1,upsupvecnum);
+ }
+
+ if((verbosity>=1) && (!learn_parm->skip_final_opt_check)) {
+ loss=0;
+ model_length=0;
+ for(i=0;i<totdoc;i++) {
+ if((lin[i]-model->b)*(double)label[i] < (-learn_parm->eps+(double)label[i]*c[i])-learn_parm->epsilon_crit)
+ loss+=-learn_parm->eps+(double)label[i]*c[i]-(lin[i]-model->b)*(double)label[i];
+ model_length+=a[i]*label[i]*lin[i];
+ }
+ model_length=sqrt(model_length);
+ fprintf(stdout,"L1 loss: loss=%.5f\n",loss);
+ fprintf(stdout,"Norm of weight vector: |w|=%.5f\n",model_length);
+ example_length=estimate_sphere(model,kernel_parm);
+ fprintf(stdout,"Norm of longest example vector: |x|=%.5f\n",
+ length_of_longest_document_vector(docs,totdoc,kernel_parm));
+ }
+ if(verbosity>=1) {
+ printf("Number of kernel evaluations: %ld\n",kernel_cache_statistic);
+ }
+ }
+
+ if(learn_parm->alphafile[0])
+ write_alphas(learn_parm->alphafile,a,label,totdoc);
+
+ /* this makes sure the model we return does not contain pointers to the
+ temporary documents */
+ for(i=1;i<model->sv_num;i++) {
+ j=model->supvec[i]->docnum;
+ if(j >= (totdoc/2)) {
+ j=totdoc-j-1;
+ }
+ model->supvec[i]=docs_org[j];
+ }
+
+ shrink_state_cleanup(&shrink_state);
+ for(i=0;i<totdoc;i++)
+ free_example(docs[i],0);
+ free(docs);
+ free(label);
+ free(inconsistent);
+ free(unlabeled);
+ free(c);
+ free(a);
+ free(a_fullset);
+ free(xi_fullset);
+ free(lin);
+ free(learn_parm->svm_cost);
+}
+
+void svm_learn_ranking(DOC **docs, double *rankvalue, long int totdoc,
+ long int totwords, LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm, KERNEL_CACHE **kernel_cache,
+ MODEL *model)
+ /* docs: Training vectors (x-part) */
+ /* rankvalue: Training target values that determine the ranking */
+ /* totdoc: Number of examples in docs/label */
+ /* totwords: Number of features (i.e. highest feature index) */
+ /* learn_parm: Learning paramenters */
+ /* kernel_parm: Kernel paramenters */
+ /* kernel_cache:Initialized pointer to Cache of size 1*totdoc, if
+ using a kernel. NULL if linear. NOTE: Cache is
+ getting reinitialized in this function */
+ /* model: Returns learning result (assumed empty before called) */
+{
+ DOC **docdiff;
+ long i,j,k,totpair,kernel_cache_size;
+ double *target,*alpha,cost;
+ long *greater,*lesser;
+ MODEL *pairmodel;
+ SVECTOR *flow,*fhigh;
+
+ totpair=0;
+ for(i=0;i<totdoc;i++) {
+ for(j=i+1;j<totdoc;j++) {
+ if((docs[i]->queryid==docs[j]->queryid) && (rankvalue[i] != rankvalue[j])) {
+ totpair++;
+ }
+ }
+ }
+
+ printf("Constructing %ld rank constraints...",totpair); fflush(stdout);
+ docdiff=(DOC **)my_malloc(sizeof(DOC)*totpair);
+ target=(double *)my_malloc(sizeof(double)*totpair);
+ greater=(long *)my_malloc(sizeof(long)*totpair);
+ lesser=(long *)my_malloc(sizeof(long)*totpair);
+
+ k=0;
+ for(i=0;i<totdoc;i++) {
+ for(j=i+1;j<totdoc;j++) {
+ if(docs[i]->queryid == docs[j]->queryid) {
+ cost=(docs[i]->costfactor+docs[j]->costfactor)/2.0;
+ if(rankvalue[i] > rankvalue[j]) {
+ if(kernel_parm->kernel_type == LINEAR)
+ docdiff[k]=create_example(k,0,0,cost,
+ sub_ss(docs[i]->fvec,docs[j]->fvec));
+ else {
+ flow=copy_svector(docs[j]->fvec);
+ flow->factor=-1.0;
+ flow->next=NULL;
+ fhigh=copy_svector(docs[i]->fvec);
+ fhigh->factor=1.0;
+ fhigh->next=flow;
+ docdiff[k]=create_example(k,0,0,cost,fhigh);
+ }
+ target[k]=1;
+ greater[k]=i;
+ lesser[k]=j;
+ k++;
+ }
+ else if(rankvalue[i] < rankvalue[j]) {
+ if(kernel_parm->kernel_type == LINEAR)
+ docdiff[k]=create_example(k,0,0,cost,
+ sub_ss(docs[i]->fvec,docs[j]->fvec));
+ else {
+ flow=copy_svector(docs[j]->fvec);
+ flow->factor=-1.0;
+ flow->next=NULL;
+ fhigh=copy_svector(docs[i]->fvec);
+ fhigh->factor=1.0;
+ fhigh->next=flow;
+ docdiff[k]=create_example(k,0,0,cost,fhigh);
+ }
+ target[k]=-1;
+ greater[k]=i;
+ lesser[k]=j;
+ k++;
+ }
+ }
+ }
+ }
+ printf("done.\n"); fflush(stdout);
+
+ /* need to get a bigger kernel cache */
+ if(*kernel_cache) {
+ kernel_cache_size=(*kernel_cache)->buffsize*sizeof(CFLOAT)/(1024*1024);
+ kernel_cache_cleanup(*kernel_cache);
+ (*kernel_cache)=kernel_cache_init(totpair,kernel_cache_size);
+ }
+
+ /* must use unbiased hyperplane on difference vectors */
+ learn_parm->biased_hyperplane=0;
+ pairmodel=(MODEL *)my_malloc(sizeof(MODEL));
+ svm_learn_classification(docdiff,target,totpair,totwords,learn_parm,
+ kernel_parm,(*kernel_cache),pairmodel,NULL);
+
+ /* Transfer the result into a more compact model. If you would like
+ to output the original model on pairs of documents, see below. */
+ alpha=(double *)my_malloc(sizeof(double)*totdoc);
+ for(i=0;i<totdoc;i++) {
+ alpha[i]=0;
+ }
+ for(i=1;i<pairmodel->sv_num;i++) {
+ alpha[lesser[(pairmodel->supvec[i])->docnum]]-=pairmodel->alpha[i];
+ alpha[greater[(pairmodel->supvec[i])->docnum]]+=pairmodel->alpha[i];
+ }
+ model->supvec = (DOC **)my_malloc(sizeof(DOC *)*(totdoc+2));
+ model->alpha = (double *)my_malloc(sizeof(double)*(totdoc+2));
+ model->index = (long *)my_malloc(sizeof(long)*(totdoc+2));
+ model->supvec[0]=0; /* element 0 reserved and empty for now */
+ model->alpha[0]=0;
+ model->sv_num=1;
+ for(i=0;i<totdoc;i++) {
+ if(alpha[i]) {
+ model->supvec[model->sv_num]=docs[i];
+ model->alpha[model->sv_num]=alpha[i];
+ model->index[i]=model->sv_num;
+ model->sv_num++;
+ }
+ else {
+ model->index[i]=-1;
+ }
+ }
+ model->at_upper_bound=0;
+ model->b=0;
+ model->lin_weights=NULL;
+ model->totwords=totwords;
+ model->totdoc=totdoc;
+ model->kernel_parm=(*kernel_parm);
+ model->loo_error=-1;
+ model->loo_recall=-1;
+ model->loo_precision=-1;
+ model->xa_error=-1;
+ model->xa_recall=-1;
+ model->xa_precision=-1;
+
+ free(alpha);
+ free(greater);
+ free(lesser);
+ free(target);
+
+ /* If you would like to output the original model on pairs of
+ document, replace the following lines with '(*model)=(*pairmodel);' */
+ for(i=0;i<totpair;i++)
+ free_example(docdiff[i],1);
+ free(docdiff);
+ free_model(pairmodel,0);
+}
+
+
+/* The following solves a freely defined and given set of
+ inequalities. The optimization problem is of the following form:
+
+ min 0.5 w*w + C sum_i C_i \xi_i
+ s.t. x_i * w > rhs_i - \xi_i
+
+ This corresponds to the -z o option. */
+
+void svm_learn_optimization(DOC **docs, double *rhs, long int
+ totdoc, long int totwords,
+ LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache, MODEL *model,
+ double *alpha)
+ /* docs: Left-hand side of inequalities (x-part) */
+ /* rhs: Right-hand side of inequalities */
+ /* totdoc: Number of examples in docs/label */
+ /* totwords: Number of features (i.e. highest feature index) */
+ /* learn_parm: Learning paramenters */
+ /* kernel_parm: Kernel paramenters */
+ /* kernel_cache:Initialized Cache of size 1*totdoc, if using a kernel.
+ NULL if linear.*/
+ /* model: Returns solution as SV expansion (assumed empty before called) */
+ /* alpha: Start values for the alpha variables or NULL
+ pointer. The new alpha values are returned after
+ optimization if not NULL. Array must be of size totdoc. */
+{
+ long i,*label;
+ long misclassified,upsupvecnum;
+ double loss,model_length,example_length;
+ double maxdiff,*lin,*a,*c;
+ long runtime_start,runtime_end;
+ long iterations,maxslackid,svsetnum;
+ long *unlabeled,*inconsistent;
+ double r_delta_sq=0,r_delta,r_delta_avg;
+ long *index,*index2dnum;
+ double *weights,*slack,*alphaslack;
+ CFLOAT *aicache; /* buffer to keep one row of hessian */
+
+ TIMING timing_profile;
+ SHRINK_STATE shrink_state;
+
+ runtime_start=get_runtime();
+ timing_profile.time_kernel=0;
+ timing_profile.time_opti=0;
+ timing_profile.time_shrink=0;
+ timing_profile.time_update=0;
+ timing_profile.time_model=0;
+ timing_profile.time_check=0;
+ timing_profile.time_select=0;
+ kernel_cache_statistic=0;
+
+ learn_parm->totwords=totwords;
+
+ /* make sure -n value is reasonable */
+ if((learn_parm->svm_newvarsinqp < 2)
+ || (learn_parm->svm_newvarsinqp > learn_parm->svm_maxqpsize)) {
+ learn_parm->svm_newvarsinqp=learn_parm->svm_maxqpsize;
+ }
+
+ init_shrink_state(&shrink_state,totdoc,(long)MAXSHRINK);
+
+ label = (long *)my_malloc(sizeof(long)*totdoc);
+ unlabeled = (long *)my_malloc(sizeof(long)*totdoc);
+ inconsistent = (long *)my_malloc(sizeof(long)*totdoc);
+ c = (double *)my_malloc(sizeof(double)*totdoc);
+ a = (double *)my_malloc(sizeof(double)*totdoc);
+ lin = (double *)my_malloc(sizeof(double)*totdoc);
+ learn_parm->svm_cost = (double *)my_malloc(sizeof(double)*totdoc);
+ model->supvec = (DOC **)my_malloc(sizeof(DOC *)*(totdoc+2));
+ model->alpha = (double *)my_malloc(sizeof(double)*(totdoc+2));
+ model->index = (long *)my_malloc(sizeof(long)*(totdoc+2));
+
+ model->at_upper_bound=0;
+ model->b=0;
+ model->supvec[0]=0; /* element 0 reserved and empty for now */
+ model->alpha[0]=0;
+ model->lin_weights=NULL;
+ model->totwords=totwords;
+ model->totdoc=totdoc;
+ model->kernel_parm=(*kernel_parm);
+ model->sv_num=1;
+ model->loo_error=-1;
+ model->loo_recall=-1;
+ model->loo_precision=-1;
+ model->xa_error=-1;
+ model->xa_recall=-1;
+ model->xa_precision=-1;
+
+ r_delta=estimate_r_delta(docs,totdoc,kernel_parm);
+ r_delta_sq=r_delta*r_delta;
+
+ r_delta_avg=estimate_r_delta_average(docs,totdoc,kernel_parm);
+ if(learn_parm->svm_c == 0.0) { /* default value for C */
+ learn_parm->svm_c=1.0/(r_delta_avg*r_delta_avg);
+ if(verbosity>=1)
+ printf("Setting default regularization parameter C=%.4f\n",
+ learn_parm->svm_c);
+ }
+
+ learn_parm->biased_hyperplane=0; /* learn an unbiased hyperplane */
+
+ learn_parm->eps=0.0; /* No margin, unless explicitly handcoded
+ in the right-hand side in the training
+ set. */
+
+ for(i=0;i<totdoc;i++) { /* various inits */
+ docs[i]->docnum=i;
+ a[i]=0;
+ lin[i]=0;
+ c[i]=rhs[i]; /* set right-hand side */
+ unlabeled[i]=0;
+ inconsistent[i]=0;
+ learn_parm->svm_cost[i]=learn_parm->svm_c*learn_parm->svm_costratio*
+ docs[i]->costfactor;
+ label[i]=1;
+ }
+ if(learn_parm->sharedslack) /* if shared slacks are used, they must */
+ for(i=0;i<totdoc;i++) /* be used on every constraint */
+ if(!docs[i]->slackid) {
+ perror("Error: Missing shared slacks definitions in some of the examples.");
+ exit(0);
+ }
+
+ /* compute starting state for initial alpha values */
+ if(alpha) {
+ if(verbosity>=1) {
+ printf("Computing starting state..."); fflush(stdout);
+ }
+ index = (long *)my_malloc(sizeof(long)*totdoc);
+ index2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ weights=(double *)my_malloc(sizeof(double)*(totwords+1));
+ aicache = (CFLOAT *)my_malloc(sizeof(CFLOAT)*totdoc);
+ for(i=0;i<totdoc;i++) { /* create full index and clip alphas */
+ index[i]=1;
+ alpha[i]=fabs(alpha[i]);
+ if(alpha[i]<0) alpha[i]=0;
+ if(alpha[i]>learn_parm->svm_cost[i]) alpha[i]=learn_parm->svm_cost[i];
+ }
+ if(kernel_parm->kernel_type != LINEAR) {
+ for(i=0;i<totdoc;i++) /* fill kernel cache with unbounded SV */
+ if((alpha[i]>0) && (alpha[i]<learn_parm->svm_cost[i])
+ && (kernel_cache_space_available(kernel_cache)))
+ cache_kernel_row(kernel_cache,docs,i,kernel_parm);
+ for(i=0;i<totdoc;i++) /* fill rest of kernel cache with bounded SV */
+ if((alpha[i]==learn_parm->svm_cost[i])
+ && (kernel_cache_space_available(kernel_cache)))
+ cache_kernel_row(kernel_cache,docs,i,kernel_parm);
+ }
+ (void)compute_index(index,totdoc,index2dnum);
+ update_linear_component(docs,label,index2dnum,alpha,a,index2dnum,totdoc,
+ totwords,kernel_parm,kernel_cache,lin,aicache,
+ weights);
+ (void)calculate_svm_model(docs,label,unlabeled,lin,alpha,a,c,
+ learn_parm,index2dnum,index2dnum,model);
+ for(i=0;i<totdoc;i++) { /* copy initial alphas */
+ a[i]=alpha[i];
+ }
+ free(index);
+ free(index2dnum);
+ free(weights);
+ free(aicache);
+ if(verbosity>=1) {
+ printf("done.\n"); fflush(stdout);
+ }
+ }
+
+ /* removing inconsistent does not work for general optimization problem */
+ if(learn_parm->remove_inconsistent) {
+ learn_parm->remove_inconsistent = 0;
+ printf("'remove inconsistent' not available in this mode. Switching option off!"); fflush(stdout);
+ }
+
+ /* caching makes no sense for linear kernel */
+ if(kernel_parm->kernel_type == LINEAR) {
+ kernel_cache = NULL;
+ }
+
+ if(verbosity==1) {
+ printf("Optimizing"); fflush(stdout);
+ }
+
+ /* train the svm */
+ if(learn_parm->sharedslack)
+ iterations=optimize_to_convergence_sharedslack(docs,label,totdoc,
+ totwords,learn_parm,kernel_parm,
+ kernel_cache,&shrink_state,model,
+ a,lin,c,&timing_profile,
+ &maxdiff);
+ else
+ iterations=optimize_to_convergence(docs,label,totdoc,
+ totwords,learn_parm,kernel_parm,
+ kernel_cache,&shrink_state,model,
+ inconsistent,unlabeled,
+ a,lin,c,&timing_profile,
+ &maxdiff,(long)-1,(long)1);
+
+ if(verbosity>=1) {
+ if(verbosity==1) printf("done. (%ld iterations)\n",iterations);
+
+ misclassified=0;
+ for(i=0;(i<totdoc);i++) { /* get final statistic */
+ if((lin[i]-model->b)*(double)label[i] <= 0.0)
+ misclassified++;
+ }
+
+ printf("Optimization finished (maxdiff=%.5f).\n",maxdiff);
+
+ runtime_end=get_runtime();
+ if(verbosity>=2) {
+ printf("Runtime in cpu-seconds: %.2f (%.2f%% for kernel/%.2f%% for optimizer/%.2f%% for final/%.2f%% for update/%.2f%% for model/%.2f%% for check/%.2f%% for select)\n",
+ ((float)runtime_end-(float)runtime_start)/100.0,
+ (100.0*timing_profile.time_kernel)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_opti)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_shrink)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_update)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_model)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_check)/(float)(runtime_end-runtime_start),
+ (100.0*timing_profile.time_select)/(float)(runtime_end-runtime_start));
+ }
+ else {
+ printf("Runtime in cpu-seconds: %.2f\n",
+ (runtime_end-runtime_start)/100.0);
+ }
+ }
+ if((verbosity>=1) && (!learn_parm->skip_final_opt_check)) {
+ loss=0;
+ model_length=0;
+ for(i=0;i<totdoc;i++) {
+ if((lin[i]-model->b)*(double)label[i] < c[i]-learn_parm->epsilon_crit)
+ loss+=c[i]-(lin[i]-model->b)*(double)label[i];
+ model_length+=a[i]*label[i]*lin[i];
+ }
+ model_length=sqrt(model_length);
+ fprintf(stdout,"Norm of weight vector: |w|=%.5f\n",model_length);
+ }
+
+ if(learn_parm->sharedslack) {
+ index = (long *)my_malloc(sizeof(long)*totdoc);
+ index2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ maxslackid=0;
+ for(i=0;i<totdoc;i++) { /* create full index */
+ index[i]=1;
+ if(maxslackid<docs[i]->slackid)
+ maxslackid=docs[i]->slackid;
+ }
+ (void)compute_index(index,totdoc,index2dnum);
+ slack=(double *)my_malloc(sizeof(double)*(maxslackid+1));
+ alphaslack=(double *)my_malloc(sizeof(double)*(maxslackid+1));
+ for(i=0;i<=maxslackid;i++) { /* init shared slacks */
+ slack[i]=0;
+ alphaslack[i]=0;
+ }
+ compute_shared_slacks(docs,label,a,lin,c,index2dnum,learn_parm,
+ slack,alphaslack);
+ loss=0;
+ model->at_upper_bound=0;
+ svsetnum=0;
+ for(i=0;i<=maxslackid;i++) { /* create full index */
+ loss+=slack[i];
+ if(alphaslack[i] > (learn_parm->svm_c - learn_parm->epsilon_a))
+ model->at_upper_bound++;
+ if(alphaslack[i] > learn_parm->epsilon_a)
+ svsetnum++;
+ }
+ free(index);
+ free(index2dnum);
+ free(slack);
+ free(alphaslack);
+ }
+
+ if((verbosity>=1) && (!learn_parm->skip_final_opt_check)) {
+ if(learn_parm->sharedslack) {
+ printf("Number of SV: %ld\n",
+ model->sv_num-1);
+ printf("Number of non-zero slack variables: %ld (out of %ld)\n",
+ model->at_upper_bound,svsetnum);
+ fprintf(stdout,"L1 loss: loss=%.5f\n",loss);
+ }
+ else {
+ upsupvecnum=0;
+ for(i=1;i<model->sv_num;i++) {
+ if(fabs(model->alpha[i]) >=
+ (learn_parm->svm_cost[(model->supvec[i])->docnum]-
+ learn_parm->epsilon_a))
+ upsupvecnum++;
+ }
+ printf("Number of SV: %ld (including %ld at upper bound)\n",
+ model->sv_num-1,upsupvecnum);
+ fprintf(stdout,"L1 loss: loss=%.5f\n",loss);
+ }
+ example_length=estimate_sphere(model,kernel_parm);
+ fprintf(stdout,"Norm of longest example vector: |x|=%.5f\n",
+ length_of_longest_document_vector(docs,totdoc,kernel_parm));
+ }
+ if(verbosity>=1) {
+ printf("Number of kernel evaluations: %ld\n",kernel_cache_statistic);
+ }
+
+ if(alpha) {
+ for(i=0;i<totdoc;i++) { /* copy final alphas */
+ alpha[i]=a[i];
+ }
+ }
+
+ if(learn_parm->alphafile[0])
+ write_alphas(learn_parm->alphafile,a,label,totdoc);
+
+ shrink_state_cleanup(&shrink_state);
+ free(label);
+ free(unlabeled);
+ free(inconsistent);
+ free(c);
+ free(a);
+ free(lin);
+ free(learn_parm->svm_cost);
+}
+
+
+long optimize_to_convergence(DOC **docs, long int *label, long int totdoc,
+ long int totwords, LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache,
+ SHRINK_STATE *shrink_state, MODEL *model,
+ long int *inconsistent, long int *unlabeled,
+ double *a, double *lin, double *c,
+ TIMING *timing_profile, double *maxdiff,
+ long int heldout, long int retrain)
+ /* docs: Training vectors (x-part) */
+ /* label: Training labels/value (y-part, zero if test example for
+ transduction) */
+ /* totdoc: Number of examples in docs/label */
+ /* totwords: Number of features (i.e. highest feature index) */
+ /* laern_parm: Learning paramenters */
+ /* kernel_parm: Kernel paramenters */
+ /* kernel_cache: Initialized/partly filled Cache, if using a kernel.
+ NULL if linear. */
+ /* shrink_state: State of active variables */
+ /* model: Returns learning result */
+ /* inconsistent: examples thrown out as inconstistent */
+ /* unlabeled: test examples for transduction */
+ /* a: alphas */
+ /* lin: linear component of gradient */
+ /* c: right hand side of inequalities (margin) */
+ /* maxdiff: returns maximum violation of KT-conditions */
+ /* heldout: marks held-out example for leave-one-out (or -1) */
+ /* retrain: selects training mode (1=regular / 2=holdout) */
+{
+ long *chosen,*key,i,j,jj,*last_suboptimal_at,noshrink;
+ long inconsistentnum,choosenum,already_chosen=0,iteration;
+ long misclassified,supvecnum=0,*active2dnum,inactivenum;
+ long *working2dnum,*selexam;
+ long activenum;
+ double criterion,eq;
+ double *a_old;
+ long t0=0,t1=0,t2=0,t3=0,t4=0,t5=0,t6=0; /* timing */
+ long transductcycle;
+ long transduction;
+ double epsilon_crit_org;
+ double bestmaxdiff;
+ long bestmaxdiffiter,terminate;
+
+ double *selcrit; /* buffer for sorting */
+ CFLOAT *aicache; /* buffer to keep one row of hessian */
+ double *weights; /* buffer for weight vector in linear case */
+ QP qp; /* buffer for one quadratic program */
+
+ epsilon_crit_org=learn_parm->epsilon_crit; /* save org */
+ if(kernel_parm->kernel_type == LINEAR) {
+ learn_parm->epsilon_crit=2.0;
+ kernel_cache=NULL; /* caching makes no sense for linear kernel */
+ }
+ learn_parm->epsilon_shrink=2;
+ (*maxdiff)=1;
+
+ learn_parm->totwords=totwords;
+
+ chosen = (long *)my_malloc(sizeof(long)*totdoc);
+ last_suboptimal_at = (long *)my_malloc(sizeof(long)*totdoc);
+ key = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ selcrit = (double *)my_malloc(sizeof(double)*totdoc);
+ selexam = (long *)my_malloc(sizeof(long)*totdoc);
+ a_old = (double *)my_malloc(sizeof(double)*totdoc);
+ aicache = (CFLOAT *)my_malloc(sizeof(CFLOAT)*totdoc);
+ working2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ active2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ qp.opt_ce = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_ce0 = (double *)my_malloc(sizeof(double));
+ qp.opt_g = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize
+ *learn_parm->svm_maxqpsize);
+ qp.opt_g0 = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_xinit = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_low=(double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_up=(double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ weights=(double *)my_malloc(sizeof(double)*(totwords+1));
+
+ choosenum=0;
+ inconsistentnum=0;
+ transductcycle=0;
+ transduction=0;
+ if(!retrain) retrain=1;
+ iteration=1;
+ bestmaxdiffiter=1;
+ bestmaxdiff=999999999;
+ terminate=0;
+
+ if(kernel_cache) {
+ kernel_cache->time=iteration; /* for lru cache */
+ kernel_cache_reset_lru(kernel_cache);
+ }
+
+ for(i=0;i<totdoc;i++) { /* various inits */
+ chosen[i]=0;
+ a_old[i]=a[i];
+ last_suboptimal_at[i]=1;
+ if(inconsistent[i])
+ inconsistentnum++;
+ if(unlabeled[i]) {
+ transduction=1;
+ }
+ }
+ activenum=compute_index(shrink_state->active,totdoc,active2dnum);
+ inactivenum=totdoc-activenum;
+ clear_index(working2dnum);
+
+ /* repeat this loop until we have convergence */
+ for(;retrain && (!terminate);iteration++) {
+
+ if(kernel_cache)
+ kernel_cache->time=iteration; /* for lru cache */
+ if(verbosity>=2) {
+ printf(
+ "Iteration %ld: ",iteration); fflush(stdout);
+ }
+ else if(verbosity==1) {
+ printf("."); fflush(stdout);
+ }
+
+ if(verbosity>=2) t0=get_runtime();
+ if(verbosity>=3) {
+ printf("\nSelecting working set... "); fflush(stdout);
+ }
+
+ if(learn_parm->svm_newvarsinqp>learn_parm->svm_maxqpsize)
+ learn_parm->svm_newvarsinqp=learn_parm->svm_maxqpsize;
+
+ i=0;
+ for(jj=0;(j=working2dnum[jj])>=0;jj++) { /* clear working set */
+ if((chosen[j]>=(learn_parm->svm_maxqpsize/
+ minl(learn_parm->svm_maxqpsize,
+ learn_parm->svm_newvarsinqp)))
+ || (inconsistent[j])
+ || (j == heldout)) {
+ chosen[j]=0;
+ choosenum--;
+ }
+ else {
+ chosen[j]++;
+ working2dnum[i++]=j;
+ }
+ }
+ working2dnum[i]=-1;
+
+ if(retrain == 2) {
+ choosenum=0;
+ for(jj=0;(j=working2dnum[jj])>=0;jj++) { /* fully clear working set */
+ chosen[j]=0;
+ }
+ clear_index(working2dnum);
+ for(i=0;i<totdoc;i++) { /* set inconsistent examples to zero (-i 1) */
+ if((inconsistent[i] || (heldout==i)) && (a[i] != 0.0)) {
+ chosen[i]=99999;
+ choosenum++;
+ a[i]=0;
+ }
+ }
+ if(learn_parm->biased_hyperplane) {
+ eq=0;
+ for(i=0;i<totdoc;i++) { /* make sure we fulfill equality constraint */
+ eq+=a[i]*label[i];
+ }
+ for(i=0;(i<totdoc) && (fabs(eq) > learn_parm->epsilon_a);i++) {
+ if((eq*label[i] > 0) && (a[i] > 0)) {
+ chosen[i]=88888;
+ choosenum++;
+ if((eq*label[i]) > a[i]) {
+ eq-=(a[i]*label[i]);
+ a[i]=0;
+ }
+ else {
+ a[i]-=(eq*label[i]);
+ eq=0;
+ }
+ }
+ }
+ }
+ compute_index(chosen,totdoc,working2dnum);
+ }
+ else { /* select working set according to steepest gradient */
+ if(iteration % 101) {
+ already_chosen=0;
+ if((minl(learn_parm->svm_newvarsinqp,
+ learn_parm->svm_maxqpsize-choosenum)>=4)
+ && (kernel_parm->kernel_type != LINEAR)) {
+ /* select part of the working set from cache */
+ already_chosen=select_next_qp_subproblem_grad(
+ label,unlabeled,a,lin,c,totdoc,
+ (long)(minl(learn_parm->svm_maxqpsize-choosenum,
+ learn_parm->svm_newvarsinqp)
+ /2),
+ learn_parm,inconsistent,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,1,
+ key,chosen);
+ choosenum+=already_chosen;
+ }
+ choosenum+=select_next_qp_subproblem_grad(
+ label,unlabeled,a,lin,c,totdoc,
+ minl(learn_parm->svm_maxqpsize-choosenum,
+ learn_parm->svm_newvarsinqp-already_chosen),
+ learn_parm,inconsistent,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,0,key,
+ chosen);
+ }
+ else { /* once in a while, select a somewhat random working set
+ to get unlocked of infinite loops due to numerical
+ inaccuracies in the core qp-solver */
+ choosenum+=select_next_qp_subproblem_rand(
+ label,unlabeled,a,lin,c,totdoc,
+ minl(learn_parm->svm_maxqpsize-choosenum,
+ learn_parm->svm_newvarsinqp),
+ learn_parm,inconsistent,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,key,
+ chosen,iteration);
+ }
+ }
+
+ if(verbosity>=2) {
+ printf(" %ld vectors chosen\n",choosenum); fflush(stdout);
+ }
+
+ if(verbosity>=2) t1=get_runtime();
+
+ if(kernel_cache)
+ cache_multiple_kernel_rows(kernel_cache,docs,working2dnum,
+ choosenum,kernel_parm);
+
+ if(verbosity>=2) t2=get_runtime();
+ if(retrain != 2) {
+ optimize_svm(docs,label,unlabeled,inconsistent,0.0,chosen,active2dnum,
+ model,totdoc,working2dnum,choosenum,a,lin,c,learn_parm,
+ aicache,kernel_parm,&qp,&epsilon_crit_org);
+ }
+
+ if(verbosity>=2) t3=get_runtime();
+ update_linear_component(docs,label,active2dnum,a,a_old,working2dnum,totdoc,
+ totwords,kernel_parm,kernel_cache,lin,aicache,
+ weights);
+
+ if(verbosity>=2) t4=get_runtime();
+ supvecnum=calculate_svm_model(docs,label,unlabeled,lin,a,a_old,c,
+ learn_parm,working2dnum,active2dnum,model);
+
+ if(verbosity>=2) t5=get_runtime();
+
+ /* The following computation of the objective function works only */
+ /* relative to the active variables */
+ if(verbosity>=3) {
+ criterion=compute_objective_function(a,lin,c,learn_parm->eps,label,
+ active2dnum);
+ printf("Objective function (over active variables): %.16f\n",criterion);
+ fflush(stdout);
+ }
+
+ for(jj=0;(i=working2dnum[jj])>=0;jj++) {
+ a_old[i]=a[i];
+ }
+
+ if(retrain == 2) { /* reset inconsistent unlabeled examples */
+ for(i=0;(i<totdoc);i++) {
+ if(inconsistent[i] && unlabeled[i]) {
+ inconsistent[i]=0;
+ label[i]=0;
+ }
+ }
+ }
+
+ retrain=check_optimality(model,label,unlabeled,a,lin,c,totdoc,learn_parm,
+ maxdiff,epsilon_crit_org,&misclassified,
+ inconsistent,active2dnum,last_suboptimal_at,
+ iteration,kernel_parm);
+
+ if(verbosity>=2) {
+ t6=get_runtime();
+ timing_profile->time_select+=t1-t0;
+ timing_profile->time_kernel+=t2-t1;
+ timing_profile->time_opti+=t3-t2;
+ timing_profile->time_update+=t4-t3;
+ timing_profile->time_model+=t5-t4;
+ timing_profile->time_check+=t6-t5;
+ }
+
+ /* checking whether optimizer got stuck */
+ if((*maxdiff) < bestmaxdiff) {
+ bestmaxdiff=(*maxdiff);
+ bestmaxdiffiter=iteration;
+ }
+ if(iteration > (bestmaxdiffiter+learn_parm->maxiter)) {
+ /* long time no progress? */
+ terminate=1;
+ retrain=0;
+ if(verbosity>=1)
+ printf("\nWARNING: Relaxing KT-Conditions due to slow progress! Terminating!\n");
+ }
+
+ noshrink=0;
+ if((!retrain) && (inactivenum>0)
+ && ((!learn_parm->skip_final_opt_check)
+ || (kernel_parm->kernel_type == LINEAR))) {
+ if(((verbosity>=1) && (kernel_parm->kernel_type != LINEAR))
+ || (verbosity>=2)) {
+ if(verbosity==1) {
+ printf("\n");
+ }
+ printf(" Checking optimality of inactive variables...");
+ fflush(stdout);
+ }
+ t1=get_runtime();
+ reactivate_inactive_examples(label,unlabeled,a,shrink_state,lin,c,totdoc,
+ totwords,iteration,learn_parm,inconsistent,
+ docs,kernel_parm,kernel_cache,model,aicache,
+ weights,maxdiff);
+ /* Update to new active variables. */
+ activenum=compute_index(shrink_state->active,totdoc,active2dnum);
+ inactivenum=totdoc-activenum;
+ /* reset watchdog */
+ bestmaxdiff=(*maxdiff);
+ bestmaxdiffiter=iteration;
+ /* termination criterion */
+ noshrink=1;
+ retrain=0;
+ if((*maxdiff) > learn_parm->epsilon_crit)
+ retrain=1;
+ timing_profile->time_shrink+=get_runtime()-t1;
+ if(((verbosity>=1) && (kernel_parm->kernel_type != LINEAR))
+ || (verbosity>=2)) {
+ printf("done.\n"); fflush(stdout);
+ printf(" Number of inactive variables = %ld\n",inactivenum);
+ }
+ }
+
+ if((!retrain) && (learn_parm->epsilon_crit>(*maxdiff)))
+ learn_parm->epsilon_crit=(*maxdiff);
+ if((!retrain) && (learn_parm->epsilon_crit>epsilon_crit_org)) {
+ learn_parm->epsilon_crit/=2.0;
+ retrain=1;
+ noshrink=1;
+ }
+ if(learn_parm->epsilon_crit<epsilon_crit_org)
+ learn_parm->epsilon_crit=epsilon_crit_org;
+
+ if(verbosity>=2) {
+ printf(" => (%ld SV (incl. %ld SV at u-bound), max violation=%.5f)\n",
+ supvecnum,model->at_upper_bound,(*maxdiff));
+ fflush(stdout);
+ }
+ if(verbosity>=3) {
+ printf("\n");
+ }
+
+ if((!retrain) && (transduction)) {
+ for(i=0;(i<totdoc);i++) {
+ shrink_state->active[i]=1;
+ }
+ activenum=compute_index(shrink_state->active,totdoc,active2dnum);
+ inactivenum=0;
+ if(verbosity==1) printf("done\n");
+ retrain=incorporate_unlabeled_examples(model,label,inconsistent,
+ unlabeled,a,lin,totdoc,
+ selcrit,selexam,key,
+ transductcycle,kernel_parm,
+ learn_parm);
+ epsilon_crit_org=learn_parm->epsilon_crit;
+ if(kernel_parm->kernel_type == LINEAR)
+ learn_parm->epsilon_crit=1;
+ transductcycle++;
+ /* reset watchdog */
+ bestmaxdiff=(*maxdiff);
+ bestmaxdiffiter=iteration;
+ }
+ else if(((iteration % 10) == 0) && (!noshrink)) {
+ activenum=shrink_problem(docs,learn_parm,shrink_state,kernel_parm,
+ active2dnum,last_suboptimal_at,iteration,totdoc,
+ maxl((long)(activenum/10),
+ maxl((long)(totdoc/500),100)),
+ a,inconsistent);
+ inactivenum=totdoc-activenum;
+ if((kernel_cache)
+ && (supvecnum>kernel_cache->max_elems)
+ && ((kernel_cache->activenum-activenum)>maxl((long)(activenum/10),500))) {
+ kernel_cache_shrink(kernel_cache,totdoc,
+ minl((kernel_cache->activenum-activenum),
+ (kernel_cache->activenum-supvecnum)),
+ shrink_state->active);
+ }
+ }
+
+ if((!retrain) && learn_parm->remove_inconsistent) {
+ if(verbosity>=1) {
+ printf(" Moving training errors to inconsistent examples...");
+ fflush(stdout);
+ }
+ if(learn_parm->remove_inconsistent == 1) {
+ retrain=identify_inconsistent(a,label,unlabeled,totdoc,learn_parm,
+ &inconsistentnum,inconsistent);
+ }
+ else if(learn_parm->remove_inconsistent == 2) {
+ retrain=identify_misclassified(lin,label,unlabeled,totdoc,
+ model,&inconsistentnum,inconsistent);
+ }
+ else if(learn_parm->remove_inconsistent == 3) {
+ retrain=identify_one_misclassified(lin,label,unlabeled,totdoc,
+ model,&inconsistentnum,inconsistent);
+ }
+ if(retrain) {
+ if(kernel_parm->kernel_type == LINEAR) { /* reinit shrinking */
+ learn_parm->epsilon_crit=2.0;
+ }
+ }
+ if(verbosity>=1) {
+ printf("done.\n");
+ if(retrain) {
+ printf(" Now %ld inconsistent examples.\n",inconsistentnum);
+ }
+ }
+ }
+ } /* end of loop */
+
+ free(chosen);
+ free(last_suboptimal_at);
+ free(key);
+ free(selcrit);
+ free(selexam);
+ free(a_old);
+ free(aicache);
+ free(working2dnum);
+ free(active2dnum);
+ free(qp.opt_ce);
+ free(qp.opt_ce0);
+ free(qp.opt_g);
+ free(qp.opt_g0);
+ free(qp.opt_xinit);
+ free(qp.opt_low);
+ free(qp.opt_up);
+ free(weights);
+
+ learn_parm->epsilon_crit=epsilon_crit_org; /* restore org */
+ model->maxdiff=(*maxdiff);
+
+ return(iteration);
+}
+
+long optimize_to_convergence_sharedslack(DOC **docs, long int *label,
+ long int totdoc,
+ long int totwords, LEARN_PARM *learn_parm,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache,
+ SHRINK_STATE *shrink_state, MODEL *model,
+ double *a, double *lin, double *c,
+ TIMING *timing_profile, double *maxdiff)
+ /* docs: Training vectors (x-part) */
+ /* label: Training labels/value (y-part, zero if test example for
+ transduction) */
+ /* totdoc: Number of examples in docs/label */
+ /* totwords: Number of features (i.e. highest feature index) */
+ /* learn_parm: Learning paramenters */
+ /* kernel_parm: Kernel paramenters */
+ /* kernel_cache: Initialized/partly filled Cache, if using a kernel.
+ NULL if linear. */
+ /* shrink_state: State of active variables */
+ /* model: Returns learning result */
+ /* a: alphas */
+ /* lin: linear component of gradient */
+ /* c: right hand side of inequalities (margin) */
+ /* maxdiff: returns maximum violation of KT-conditions */
+{
+ long *chosen,*key,i,j,jj,*last_suboptimal_at,noshrink,*unlabeled;
+ long *inconsistent,choosenum,already_chosen=0,iteration;
+ long misclassified,supvecnum=0,*active2dnum,inactivenum;
+ long *working2dnum,*selexam,*ignore;
+ long activenum,retrain,maxslackid,slackset,jointstep;
+ double criterion,eq_target;
+ double *a_old,*alphaslack;
+ long t0=0,t1=0,t2=0,t3=0,t4=0,t5=0,t6=0; /* timing */
+ double epsilon_crit_org,maxsharedviol;
+ double bestmaxdiff;
+ long bestmaxdiffiter,terminate;
+
+ double *selcrit; /* buffer for sorting */
+ CFLOAT *aicache; /* buffer to keep one row of hessian */
+ double *weights; /* buffer for weight vector in linear case */
+ QP qp; /* buffer for one quadratic program */
+ double *slack; /* vector of slack variables for optimization with
+ shared slacks */
+
+ epsilon_crit_org=learn_parm->epsilon_crit; /* save org */
+ if(kernel_parm->kernel_type == LINEAR) {
+ learn_parm->epsilon_crit=2.0;
+ kernel_cache=NULL; /* caching makes no sense for linear kernel */
+ }
+ learn_parm->epsilon_shrink=2;
+ (*maxdiff)=1;
+
+ learn_parm->totwords=totwords;
+
+ chosen = (long *)my_malloc(sizeof(long)*totdoc);
+ unlabeled = (long *)my_malloc(sizeof(long)*totdoc);
+ inconsistent = (long *)my_malloc(sizeof(long)*totdoc);
+ ignore = (long *)my_malloc(sizeof(long)*totdoc);
+ key = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ selcrit = (double *)my_malloc(sizeof(double)*totdoc);
+ selexam = (long *)my_malloc(sizeof(long)*totdoc);
+ a_old = (double *)my_malloc(sizeof(double)*totdoc);
+ aicache = (CFLOAT *)my_malloc(sizeof(CFLOAT)*totdoc);
+ working2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ active2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ qp.opt_ce = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_ce0 = (double *)my_malloc(sizeof(double));
+ qp.opt_g = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize
+ *learn_parm->svm_maxqpsize);
+ qp.opt_g0 = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_xinit = (double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_low=(double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ qp.opt_up=(double *)my_malloc(sizeof(double)*learn_parm->svm_maxqpsize);
+ weights=(double *)my_malloc(sizeof(double)*(totwords+1));
+ maxslackid=0;
+ for(i=0;i<totdoc;i++) { /* determine size of slack array */
+ if(maxslackid<docs[i]->slackid)
+ maxslackid=docs[i]->slackid;
+ }
+ slack=(double *)my_malloc(sizeof(double)*(maxslackid+1));
+ alphaslack=(double *)my_malloc(sizeof(double)*(maxslackid+1));
+ last_suboptimal_at = (long *)my_malloc(sizeof(long)*(maxslackid+1));
+ for(i=0;i<=maxslackid;i++) { /* init shared slacks */
+ slack[i]=0;
+ alphaslack[i]=0;
+ last_suboptimal_at[i]=1;
+ }
+
+ choosenum=0;
+ retrain=1;
+ iteration=1;
+ bestmaxdiffiter=1;
+ bestmaxdiff=999999999;
+ terminate=0;
+
+ if(kernel_cache) {
+ kernel_cache->time=iteration; /* for lru cache */
+ kernel_cache_reset_lru(kernel_cache);
+ }
+
+ for(i=0;i<totdoc;i++) { /* various inits */
+ chosen[i]=0;
+ unlabeled[i]=0;
+ inconsistent[i]=0;
+ ignore[i]=0;
+ a_old[i]=a[i];
+ }
+ activenum=compute_index(shrink_state->active,totdoc,active2dnum);
+ inactivenum=totdoc-activenum;
+ clear_index(working2dnum);
+
+ /* call to init slack and alphaslack */
+ compute_shared_slacks(docs,label,a,lin,c,active2dnum,learn_parm,
+ slack,alphaslack);
+
+ /* repeat this loop until we have convergence */
+ for(;retrain && (!terminate);iteration++) {
+
+ if(kernel_cache)
+ kernel_cache->time=iteration; /* for lru cache */
+ if(verbosity>=2) {
+ printf(
+ "Iteration %ld: ",iteration); fflush(stdout);
+ }
+ else if(verbosity==1) {
+ printf("."); fflush(stdout);
+ }
+
+ if(verbosity>=2) t0=get_runtime();
+ if(verbosity>=3) {
+ printf("\nSelecting working set... "); fflush(stdout);
+ }
+
+ if(learn_parm->svm_newvarsinqp>learn_parm->svm_maxqpsize)
+ learn_parm->svm_newvarsinqp=learn_parm->svm_maxqpsize;
+
+ /* select working set according to steepest gradient */
+ jointstep=0;
+ eq_target=0;
+ if(iteration % 101) {
+ slackset=select_next_qp_slackset(docs,label,a,lin,slack,alphaslack,c,
+ learn_parm,active2dnum,&maxsharedviol);
+ if((iteration % 2)
+ || (!slackset) || (maxsharedviol<learn_parm->epsilon_crit)){
+ /* do a step with examples from different slack sets */
+ if(verbosity >= 2) {
+ printf("(i-step)"); fflush(stdout);
+ }
+ i=0;
+ for(jj=0;(j=working2dnum[jj])>=0;jj++) { /* clear old part of working set */
+ if((chosen[j]>=(learn_parm->svm_maxqpsize/
+ minl(learn_parm->svm_maxqpsize,
+ learn_parm->svm_newvarsinqp)))) {
+ chosen[j]=0;
+ choosenum--;
+ }
+ else {
+ chosen[j]++;
+ working2dnum[i++]=j;
+ }
+ }
+ working2dnum[i]=-1;
+
+ already_chosen=0;
+ if((minl(learn_parm->svm_newvarsinqp,
+ learn_parm->svm_maxqpsize-choosenum)>=4)
+ && (kernel_parm->kernel_type != LINEAR)) {
+ /* select part of the working set from cache */
+ already_chosen=select_next_qp_subproblem_grad(
+ label,unlabeled,a,lin,c,totdoc,
+ (long)(minl(learn_parm->svm_maxqpsize-choosenum,
+ learn_parm->svm_newvarsinqp)
+ /2),
+ learn_parm,inconsistent,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,
+ (long)1,key,chosen);
+ choosenum+=already_chosen;
+ }
+ choosenum+=select_next_qp_subproblem_grad(
+ label,unlabeled,a,lin,c,totdoc,
+ minl(learn_parm->svm_maxqpsize-choosenum,
+ learn_parm->svm_newvarsinqp-already_chosen),
+ learn_parm,inconsistent,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,
+ (long)0,key,chosen);
+ }
+ else { /* do a step with all examples from same slack set */
+ if(verbosity >= 2) {
+ printf("(j-step on %ld)",slackset); fflush(stdout);
+ }
+ jointstep=1;
+ for(jj=0;(j=working2dnum[jj])>=0;jj++) { /* clear working set */
+ chosen[j]=0;
+ }
+ working2dnum[0]=-1;
+ eq_target=alphaslack[slackset];
+ for(j=0;j<totdoc;j++) { /* mask all but slackset */
+ /* for(jj=0;(j=active2dnum[jj])>=0;jj++) { */
+ if(docs[j]->slackid != slackset)
+ ignore[j]=1;
+ else {
+ ignore[j]=0;
+ learn_parm->svm_cost[j]=learn_parm->svm_c;
+ /* printf("Inslackset(%ld,%ld)",j,shrink_state->active[j]); */
+ }
+ }
+ learn_parm->biased_hyperplane=1;
+ choosenum=select_next_qp_subproblem_grad(
+ label,unlabeled,a,lin,c,totdoc,
+ learn_parm->svm_maxqpsize,
+ learn_parm,ignore,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,
+ (long)0,key,chosen);
+ learn_parm->biased_hyperplane=0;
+ }
+ }
+ else { /* once in a while, select a somewhat random working set
+ to get unlocked of infinite loops due to numerical
+ inaccuracies in the core qp-solver */
+ choosenum+=select_next_qp_subproblem_rand(
+ label,unlabeled,a,lin,c,totdoc,
+ minl(learn_parm->svm_maxqpsize-choosenum,
+ learn_parm->svm_newvarsinqp),
+ learn_parm,inconsistent,active2dnum,
+ working2dnum,selcrit,selexam,kernel_cache,key,
+ chosen,iteration);
+ }
+
+ if(verbosity>=2) {
+ printf(" %ld vectors chosen\n",choosenum); fflush(stdout);
+ }
+
+ if(verbosity>=2) t1=get_runtime();
+
+ if(kernel_cache)
+ cache_multiple_kernel_rows(kernel_cache,docs,working2dnum,
+ choosenum,kernel_parm);
+
+ if(verbosity>=2) t2=get_runtime();
+ if(jointstep) learn_parm->biased_hyperplane=1;
+ optimize_svm(docs,label,unlabeled,ignore,eq_target,chosen,active2dnum,
+ model,totdoc,working2dnum,choosenum,a,lin,c,learn_parm,
+ aicache,kernel_parm,&qp,&epsilon_crit_org);
+ learn_parm->biased_hyperplane=0;
+
+ for(jj=0;(i=working2dnum[jj])>=0;jj++) /* recompute sums of alphas */
+ alphaslack[docs[i]->slackid]+=(a[i]-a_old[i]);
+ for(jj=0;(i=working2dnum[jj])>=0;jj++) { /* reduce alpha to fulfill
+ constraints */
+ if(alphaslack[docs[i]->slackid] > learn_parm->svm_c) {
+ if(a[i] < (alphaslack[docs[i]->slackid]-learn_parm->svm_c)) {
+ alphaslack[docs[i]->slackid]-=a[i];
+ a[i]=0;
+ }
+ else {
+ a[i]-=(alphaslack[docs[i]->slackid]-learn_parm->svm_c);
+ alphaslack[docs[i]->slackid]=learn_parm->svm_c;
+ }
+ }
+ }
+ for(jj=0;(i=active2dnum[jj])>=0;jj++)
+ learn_parm->svm_cost[i]=a[i]+(learn_parm->svm_c
+ -alphaslack[docs[i]->slackid]);
+
+ if(verbosity>=2) t3=get_runtime();
+ update_linear_component(docs,label,active2dnum,a,a_old,working2dnum,totdoc,
+ totwords,kernel_parm,kernel_cache,lin,aicache,
+ weights);
+ compute_shared_slacks(docs,label,a,lin,c,active2dnum,learn_parm,
+ slack,alphaslack);
+
+ if(verbosity>=2) t4=get_runtime();
+ supvecnum=calculate_svm_model(docs,label,unlabeled,lin,a,a_old,c,
+ learn_parm,working2dnum,active2dnum,model);
+
+ if(verbosity>=2) t5=get_runtime();
+
+ /* The following computation of the objective function works only */
+ /* relative to the active variables */
+ if(verbosity>=3) {
+ criterion=compute_objective_function(a,lin,c,learn_parm->eps,label,
+ active2dnum);
+ printf("Objective function (over active variables): %.16f\n",criterion);
+ fflush(stdout);
+ }
+
+ for(jj=0;(i=working2dnum[jj])>=0;jj++) {
+ a_old[i]=a[i];
+ }
+
+ retrain=check_optimality_sharedslack(docs,model,label,a,lin,c,
+ slack,alphaslack,totdoc,learn_parm,
+ maxdiff,epsilon_crit_org,&misclassified,
+ active2dnum,last_suboptimal_at,
+ iteration,kernel_parm);
+
+ if(verbosity>=2) {
+ t6=get_runtime();
+ timing_profile->time_select+=t1-t0;
+ timing_profile->time_kernel+=t2-t1;
+ timing_profile->time_opti+=t3-t2;
+ timing_profile->time_update+=t4-t3;
+ timing_profile->time_model+=t5-t4;
+ timing_profile->time_check+=t6-t5;
+ }
+
+ /* checking whether optimizer got stuck */
+ if((*maxdiff) < bestmaxdiff) {
+ bestmaxdiff=(*maxdiff);
+ bestmaxdiffiter=iteration;
+ }
+ if(iteration > (bestmaxdiffiter+learn_parm->maxiter)) {
+ /* long time no progress? */
+ terminate=1;
+ retrain=0;
+ if(verbosity>=1)
+ printf("\nWARNING: Relaxing KT-Conditions due to slow progress! Terminating!\n");
+ }
+
+ noshrink=0;
+
+ if((!retrain) && (inactivenum>0)
+ && ((!learn_parm->skip_final_opt_check)
+ || (kernel_parm->kernel_type == LINEAR))) {
+ if(((verbosity>=1) && (kernel_parm->kernel_type != LINEAR))
+ || (verbosity>=2)) {
+ if(verbosity==1) {
+ printf("\n");
+ }
+ printf(" Checking optimality of inactive variables...");
+ fflush(stdout);
+ }
+ t1=get_runtime();
+ reactivate_inactive_examples(label,unlabeled,a,shrink_state,lin,c,totdoc,
+ totwords,iteration,learn_parm,inconsistent,
+ docs,kernel_parm,kernel_cache,model,aicache,
+ weights,maxdiff);
+ /* Update to new active variables. */
+ activenum=compute_index(shrink_state->active,totdoc,active2dnum);
+ inactivenum=totdoc-activenum;
+ /* check optimality, since check in reactivate does not work for
+ sharedslacks */
+ retrain=check_optimality_sharedslack(docs,model,label,a,lin,c,
+ slack,alphaslack,totdoc,learn_parm,
+ maxdiff,epsilon_crit_org,&misclassified,
+ active2dnum,last_suboptimal_at,
+ iteration,kernel_parm);
+
+ /* reset watchdog */
+ bestmaxdiff=(*maxdiff);
+ bestmaxdiffiter=iteration;
+ /* termination criterion */
+ noshrink=1;
+ retrain=0;
+ if((*maxdiff) > learn_parm->epsilon_crit)
+ retrain=1;
+ timing_profile->time_shrink+=get_runtime()-t1;
+ if(((verbosity>=1) && (kernel_parm->kernel_type != LINEAR))
+ || (verbosity>=2)) {
+ printf("done.\n"); fflush(stdout);
+ printf(" Number of inactive variables = %ld\n",inactivenum);
+ }
+ }
+
+ if((!retrain) && (learn_parm->epsilon_crit>(*maxdiff)))
+ learn_parm->epsilon_crit=(*maxdiff);
+ if((!retrain) && (learn_parm->epsilon_crit>epsilon_crit_org)) {
+ learn_parm->epsilon_crit/=2.0;
+ retrain=1;
+ noshrink=1;
+ }
+ if(learn_parm->epsilon_crit<epsilon_crit_org)
+ learn_parm->epsilon_crit=epsilon_crit_org;
+
+ if(verbosity>=2) {
+ printf(" => (%ld SV (incl. %ld SV at u-bound), max violation=%.5f)\n",
+ supvecnum,model->at_upper_bound,(*maxdiff));
+ fflush(stdout);
+ }
+ if(verbosity>=3) {
+ printf("\n");
+ }
+
+ if(((iteration % 10) == 0) && (!noshrink)) {
+ activenum=shrink_problem(docs,learn_parm,shrink_state,
+ kernel_parm,active2dnum,
+ last_suboptimal_at,iteration,totdoc,
+ maxl((long)(activenum/10),
+ maxl((long)(totdoc/500),100)),
+ a,inconsistent);
+ inactivenum=totdoc-activenum;
+ if((kernel_cache)
+ && (supvecnum>kernel_cache->max_elems)
+ && ((kernel_cache->activenum-activenum)>maxl((long)(activenum/10),500))) {
+ kernel_cache_shrink(kernel_cache,totdoc,
+ minl((kernel_cache->activenum-activenum),
+ (kernel_cache->activenum-supvecnum)),
+ shrink_state->active);
+ }
+ }
+
+ } /* end of loop */
+
+
+ free(alphaslack);
+ free(slack);
+ free(chosen);
+ free(unlabeled);
+ free(inconsistent);
+ free(ignore);
+ free(last_suboptimal_at);
+ free(key);
+ free(selcrit);
+ free(selexam);
+ free(a_old);
+ free(aicache);
+ free(working2dnum);
+ free(active2dnum);
+ free(qp.opt_ce);
+ free(qp.opt_ce0);
+ free(qp.opt_g);
+ free(qp.opt_g0);
+ free(qp.opt_xinit);
+ free(qp.opt_low);
+ free(qp.opt_up);
+ free(weights);
+
+ learn_parm->epsilon_crit=epsilon_crit_org; /* restore org */
+ model->maxdiff=(*maxdiff);
+
+ return(iteration);
+}
+
+
+double compute_objective_function(double *a, double *lin, double *c,
+ double eps, long int *label,
+ long int *active2dnum)
+ /* Return value of objective function. */
+ /* Works only relative to the active variables! */
+{
+ long i,ii;
+ double criterion;
+ /* calculate value of objective function */
+ criterion=0;
+ for(ii=0;active2dnum[ii]>=0;ii++) {
+ i=active2dnum[ii];
+ criterion=criterion+(eps-(double)label[i]*c[i])*a[i]+0.5*a[i]*label[i]*lin[i];
+ }
+ return(criterion);
+}
+
+void clear_index(long int *index)
+ /* initializes and empties index */
+{
+ index[0]=-1;
+}
+
+void add_to_index(long int *index, long int elem)
+ /* initializes and empties index */
+{
+ register long i;
+ for(i=0;index[i] != -1;i++);
+ index[i]=elem;
+ index[i+1]=-1;
+}
+
+long compute_index(long int *binfeature, long int range, long int *index)
+ /* create an inverted index of binfeature */
+{
+ register long i,ii;
+
+ ii=0;
+ for(i=0;i<range;i++) {
+ if(binfeature[i]) {
+ index[ii]=i;
+ ii++;
+ }
+ }
+ for(i=0;i<4;i++) {
+ index[ii+i]=-1;
+ }
+ return(ii);
+}
+
+
+void optimize_svm(DOC **docs, long int *label, long int *unlabeled,
+ long int *exclude_from_eq_const, double eq_target,
+ long int *chosen, long int *active2dnum, MODEL *model,
+ long int totdoc, long int *working2dnum, long int varnum,
+ double *a, double *lin, double *c, LEARN_PARM *learn_parm,
+ CFLOAT *aicache, KERNEL_PARM *kernel_parm, QP *qp,
+ double *epsilon_crit_target)
+ /* Do optimization on the working set. */
+{
+ long i;
+ double *a_v;
+
+ compute_matrices_for_optimization(docs,label,unlabeled,
+ exclude_from_eq_const,eq_target,chosen,
+ active2dnum,working2dnum,model,a,lin,c,
+ varnum,totdoc,learn_parm,aicache,
+ kernel_parm,qp);
+
+ if(verbosity>=3) {
+ printf("Running optimizer..."); fflush(stdout);
+ }
+ /* call the qp-subsolver */
+ a_v=optimize_qp(qp,epsilon_crit_target,
+ learn_parm->svm_maxqpsize,
+ &(model->b), /* in case the optimizer gives us */
+ /* the threshold for free. otherwise */
+ /* b is calculated in calculate_model. */
+ learn_parm);
+ if(verbosity>=3) {
+ printf("done\n");
+ }
+
+ for(i=0;i<varnum;i++) {
+ a[working2dnum[i]]=a_v[i];
+ /*
+ if(a_v[i]<=(0+learn_parm->epsilon_a)) {
+ a[working2dnum[i]]=0;
+ }
+ else if(a_v[i]>=(learn_parm->svm_cost[working2dnum[i]]-learn_parm->epsilon_a)) {
+ a[working2dnum[i]]=learn_parm->svm_cost[working2dnum[i]];
+ }
+ */
+ }
+}
+
+void compute_matrices_for_optimization(DOC **docs, long int *label,
+ long int *unlabeled, long *exclude_from_eq_const, double eq_target,
+ long int *chosen, long int *active2dnum,
+ long int *key, MODEL *model, double *a, double *lin, double *c,
+ long int varnum, long int totdoc, LEARN_PARM *learn_parm,
+ CFLOAT *aicache, KERNEL_PARM *kernel_parm, QP *qp)
+{
+ register long ki,kj,i,j;
+ register double kernel_temp;
+
+ if(verbosity>=3) {
+ fprintf(stdout,"Computing qp-matrices (type %ld kernel [degree %ld, rbf_gamma %f, coef_lin %f, coef_const %f])...",kernel_parm->kernel_type,kernel_parm->poly_degree,kernel_parm->rbf_gamma,kernel_parm->coef_lin,kernel_parm->coef_const);
+ fflush(stdout);
+ }
+
+ qp->opt_n=varnum;
+ qp->opt_ce0[0]=-eq_target; /* compute the constant for equality constraint */
+ for(j=1;j<model->sv_num;j++) { /* start at 1 */
+ if((!chosen[(model->supvec[j])->docnum])
+ && (!exclude_from_eq_const[(model->supvec[j])->docnum])) {
+ qp->opt_ce0[0]+=model->alpha[j];
+ }
+ }
+ if(learn_parm->biased_hyperplane)
+ qp->opt_m=1;
+ else
+ qp->opt_m=0; /* eq-constraint will be ignored */
+
+ /* init linear part of objective function */
+ for(i=0;i<varnum;i++) {
+ qp->opt_g0[i]=lin[key[i]];
+ }
+
+ for(i=0;i<varnum;i++) {
+ ki=key[i];
+
+ /* Compute the matrix for equality constraints */
+ qp->opt_ce[i]=label[ki];
+ qp->opt_low[i]=0;
+ qp->opt_up[i]=learn_parm->svm_cost[ki];
+
+ kernel_temp=(double)kernel(kernel_parm,docs[ki],docs[ki]);
+ /* compute linear part of objective function */
+ qp->opt_g0[i]-=(kernel_temp*a[ki]*(double)label[ki]);
+ /* compute quadratic part of objective function */
+ qp->opt_g[varnum*i+i]=kernel_temp;
+ for(j=i+1;j<varnum;j++) {
+ kj=key[j];
+ kernel_temp=(double)kernel(kernel_parm,docs[ki],docs[kj]);
+ /* compute linear part of objective function */
+ qp->opt_g0[i]-=(kernel_temp*a[kj]*(double)label[kj]);
+ qp->opt_g0[j]-=(kernel_temp*a[ki]*(double)label[ki]);
+ /* compute quadratic part of objective function */
+ qp->opt_g[varnum*i+j]=(double)label[ki]*(double)label[kj]*kernel_temp;
+ qp->opt_g[varnum*j+i]=(double)label[ki]*(double)label[kj]*kernel_temp;
+ }
+
+ if(verbosity>=3) {
+ if(i % 20 == 0) {
+ fprintf(stdout,"%ld..",i); fflush(stdout);
+ }
+ }
+ }
+
+ for(i=0;i<varnum;i++) {
+ /* assure starting at feasible point */
+ qp->opt_xinit[i]=a[key[i]];
+ /* set linear part of objective function */
+ qp->opt_g0[i]=(learn_parm->eps-(double)label[key[i]]*c[key[i]])+qp->opt_g0[i]*(double)label[key[i]];
+ }
+
+ if(verbosity>=3) {
+ fprintf(stdout,"done\n");
+ }
+}
+
+long calculate_svm_model(DOC **docs, long int *label, long int *unlabeled,
+ double *lin, double *a, double *a_old, double *c,
+ LEARN_PARM *learn_parm, long int *working2dnum,
+ long int *active2dnum, MODEL *model)
+ /* Compute decision function based on current values */
+ /* of alpha. */
+{
+ long i,ii,pos,b_calculated=0,first_low,first_high;
+ double ex_c,b_temp,b_low,b_high;
+
+ if(verbosity>=3) {
+ printf("Calculating model..."); fflush(stdout);
+ }
+
+ if(!learn_parm->biased_hyperplane) {
+ model->b=0;
+ b_calculated=1;
+ }
+
+ for(ii=0;(i=working2dnum[ii])>=0;ii++) {
+ if((a_old[i]>0) && (a[i]==0)) { /* remove from model */
+ pos=model->index[i];
+ model->index[i]=-1;
+ (model->sv_num)--;
+ model->supvec[pos]=model->supvec[model->sv_num];
+ model->alpha[pos]=model->alpha[model->sv_num];
+ model->index[(model->supvec[pos])->docnum]=pos;
+ }
+ else if((a_old[i]==0) && (a[i]>0)) { /* add to model */
+ model->supvec[model->sv_num]=docs[i];
+ model->alpha[model->sv_num]=a[i]*(double)label[i];
+ model->index[i]=model->sv_num;
+ (model->sv_num)++;
+ }
+ else if(a_old[i]==a[i]) { /* nothing to do */
+ }
+ else { /* just update alpha */
+ model->alpha[model->index[i]]=a[i]*(double)label[i];
+ }
+
+ ex_c=learn_parm->svm_cost[i]-learn_parm->epsilon_a;
+ if((a_old[i]>=ex_c) && (a[i]<ex_c)) {
+ (model->at_upper_bound)--;
+ }
+ else if((a_old[i]<ex_c) && (a[i]>=ex_c)) {
+ (model->at_upper_bound)++;
+ }
+
+ if((!b_calculated)
+ && (a[i]>learn_parm->epsilon_a) && (a[i]<ex_c)) { /* calculate b */
+ model->b=((double)label[i]*learn_parm->eps-c[i]+lin[i]);
+ /* model->b=(-(double)label[i]+lin[i]); */
+ b_calculated=1;
+ }
+ }
+
+ /* No alpha in the working set not at bounds, so b was not
+ calculated in the usual way. The following handles this special
+ case. */
+ if(learn_parm->biased_hyperplane
+ && (!b_calculated)
+ && (model->sv_num-1 == model->at_upper_bound)) {
+ first_low=1;
+ first_high=1;
+ b_low=0;
+ b_high=0;
+ for(ii=0;(i=active2dnum[ii])>=0;ii++) {
+ ex_c=learn_parm->svm_cost[i]-learn_parm->epsilon_a;
+ if(a[i]<ex_c) {
+ if(label[i]>0) {
+ b_temp=-(learn_parm->eps-c[i]+lin[i]);
+ if((b_temp>b_low) || (first_low)) {
+ b_low=b_temp;
+ first_low=0;
+ }
+ }
+ else {
+ b_temp=-(-learn_parm->eps-c[i]+lin[i]);
+ if((b_temp<b_high) || (first_high)) {
+ b_high=b_temp;
+ first_high=0;
+ }
+ }
+ }
+ else {
+ if(label[i]<0) {
+ b_temp=-(-learn_parm->eps-c[i]+lin[i]);
+ if((b_temp>b_low) || (first_low)) {
+ b_low=b_temp;
+ first_low=0;
+ }
+ }
+ else {
+ b_temp=-(learn_parm->eps-c[i]+lin[i]);
+ if((b_temp<b_high) || (first_high)) {
+ b_high=b_temp;
+ first_high=0;
+ }
+ }
+ }
+ }
+ if(first_high) {
+ model->b=-b_low;
+ }
+ else if(first_low) {
+ model->b=-b_high;
+ }
+ else {
+ model->b=-(b_high+b_low)/2.0; /* select b as the middle of range */
+ /* printf("\nb_low=%f, b_high=%f,b=%f\n",b_low,b_high,model->b); */
+ }
+ }
+
+ if(verbosity>=3) {
+ printf("done\n"); fflush(stdout);
+ }
+
+ return(model->sv_num-1); /* have to substract one, since element 0 is empty*/
+}
+
+long check_optimality(MODEL *model, long int *label, long int *unlabeled,
+ double *a, double *lin, double *c, long int totdoc,
+ LEARN_PARM *learn_parm, double *maxdiff,
+ double epsilon_crit_org, long int *misclassified,
+ long int *inconsistent, long int *active2dnum,
+ long int *last_suboptimal_at,
+ long int iteration, KERNEL_PARM *kernel_parm)
+ /* Check KT-conditions */
+{
+ long i,ii,retrain;
+ double dist,ex_c,target;
+
+ if(kernel_parm->kernel_type == LINEAR) { /* be optimistic */
+ learn_parm->epsilon_shrink=-learn_parm->epsilon_crit+epsilon_crit_org;
+ }
+ else { /* be conservative */
+ learn_parm->epsilon_shrink=learn_parm->epsilon_shrink*0.7+(*maxdiff)*0.3;
+ }
+ retrain=0;
+ (*maxdiff)=0;
+ (*misclassified)=0;
+ for(ii=0;(i=active2dnum[ii])>=0;ii++) {
+ if((!inconsistent[i]) && label[i]) {
+ dist=(lin[i]-model->b)*(double)label[i];/* 'distance' from
+ hyperplane*/
+ target=-(learn_parm->eps-(double)label[i]*c[i]);
+ ex_c=learn_parm->svm_cost[i]-learn_parm->epsilon_a;
+ if(dist <= 0) {
+ (*misclassified)++; /* does not work due to deactivation of var */
+ }
+ if((a[i]>learn_parm->epsilon_a) && (dist > target)) {
+ if((dist-target)>(*maxdiff)) /* largest violation */
+ (*maxdiff)=dist-target;
+ }
+ else if((a[i]<ex_c) && (dist < target)) {
+ if((target-dist)>(*maxdiff)) /* largest violation */
+ (*maxdiff)=target-dist;
+ }
+ /* Count how long a variable was at lower/upper bound (and optimal).*/
+ /* Variables, which were at the bound and optimal for a long */
+ /* time are unlikely to become support vectors. In case our */
+ /* cache is filled up, those variables are excluded to save */
+ /* kernel evaluations. (See chapter 'Shrinking').*/
+ if((a[i]>(learn_parm->epsilon_a))
+ && (a[i]<ex_c)) {
+ last_suboptimal_at[i]=iteration; /* not at bound */
+ }
+ else if((a[i]<=(learn_parm->epsilon_a))
+ && (dist < (target+learn_parm->epsilon_shrink))) {
+ last_suboptimal_at[i]=iteration; /* not likely optimal */
+ }
+ else if((a[i]>=ex_c)
+ && (dist > (target-learn_parm->epsilon_shrink))) {
+ last_suboptimal_at[i]=iteration; /* not likely optimal */
+ }
+ }
+ }
+ /* termination criterion */
+ if((!retrain) && ((*maxdiff) > learn_parm->epsilon_crit)) {
+ retrain=1;
+ }
+ return(retrain);
+}
+
+long check_optimality_sharedslack(DOC **docs, MODEL *model, long int *label,
+ double *a, double *lin, double *c, double *slack,
+ double *alphaslack,
+ long int totdoc,
+ LEARN_PARM *learn_parm, double *maxdiff,
+ double epsilon_crit_org, long int *misclassified,
+ long int *active2dnum,
+ long int *last_suboptimal_at,
+ long int iteration, KERNEL_PARM *kernel_parm)
+ /* Check KT-conditions */
+{
+ long i,ii,retrain;
+ double dist,ex_c=0,target;
+
+ if(kernel_parm->kernel_type == LINEAR) { /* be optimistic */
+ learn_parm->epsilon_shrink=-learn_parm->epsilon_crit+epsilon_crit_org;
+ }
+ else { /* be conservative */
+ learn_parm->epsilon_shrink=learn_parm->epsilon_shrink*0.7+(*maxdiff)*0.3;
+ }
+
+ retrain=0;
+ (*maxdiff)=0;
+ (*misclassified)=0;
+ for(ii=0;(i=active2dnum[ii])>=0;ii++) {
+ /* 'distance' from hyperplane*/
+ dist=(lin[i]-model->b)*(double)label[i]+slack[docs[i]->slackid];
+ target=-(learn_parm->eps-(double)label[i]*c[i]);
+ ex_c=learn_parm->svm_c-learn_parm->epsilon_a;
+ if((a[i]>learn_parm->epsilon_a) && (dist > target)) {
+ if((dist-target)>(*maxdiff)) { /* largest violation */
+ (*maxdiff)=dist-target;
+ if(verbosity>=5) printf("sid %ld: dist=%.2f, target=%.2f, slack=%.2f, a=%f, alphaslack=%f\n",docs[i]->slackid,dist,target,slack[docs[i]->slackid],a[i],alphaslack[docs[i]->slackid]);
+ if(verbosity>=5) printf(" (single %f)\n",(*maxdiff));
+ }
+ }
+ if((alphaslack[docs[i]->slackid]<ex_c) && (slack[docs[i]->slackid]>0)) {
+ if((slack[docs[i]->slackid])>(*maxdiff)) { /* largest violation */
+ (*maxdiff)=slack[docs[i]->slackid];
+ if(verbosity>=5) printf("sid %ld: dist=%.2f, target=%.2f, slack=%.2f, a=%f, alphaslack=%f\n",docs[i]->slackid,dist,target,slack[docs[i]->slackid],a[i],alphaslack[docs[i]->slackid]);
+ if(verbosity>=5) printf(" (joint %f)\n",(*maxdiff));
+ }
+ }
+ /* Count how long a variable was at lower/upper bound (and optimal).*/
+ /* Variables, which were at the bound and optimal for a long */
+ /* time are unlikely to become support vectors. In case our */
+ /* cache is filled up, those variables are excluded to save */
+ /* kernel evaluations. (See chapter 'Shrinking').*/
+ if((a[i]>(learn_parm->epsilon_a))
+ && (a[i]<ex_c)) {
+ last_suboptimal_at[docs[i]->slackid]=iteration; /* not at bound */
+ }
+ else if((a[i]<=(learn_parm->epsilon_a))
+ && (dist < (target+learn_parm->epsilon_shrink))) {
+ last_suboptimal_at[docs[i]->slackid]=iteration; /* not likely optimal */
+ }
+ else if((a[i]>=ex_c)
+ && (slack[docs[i]->slackid] < learn_parm->epsilon_shrink)) {
+ last_suboptimal_at[docs[i]->slackid]=iteration; /* not likely optimal */
+ }
+ }
+ /* termination criterion */
+ if((!retrain) && ((*maxdiff) > learn_parm->epsilon_crit)) {
+ retrain=1;
+ }
+ return(retrain);
+}
+
+void compute_shared_slacks(DOC **docs, long int *label,
+ double *a, double *lin,
+ double *c, long int *active2dnum,
+ LEARN_PARM *learn_parm,
+ double *slack, double *alphaslack)
+ /* compute the value of shared slacks and the joint alphas */
+{
+ long jj,i;
+ double dist,target;
+
+ for(jj=0;(i=active2dnum[jj])>=0;jj++) { /* clear slack variables */
+ slack[docs[i]->slackid]=0.0;
+ alphaslack[docs[i]->slackid]=0.0;
+ }
+ for(jj=0;(i=active2dnum[jj])>=0;jj++) { /* recompute slack variables */
+ dist=(lin[i])*(double)label[i];
+ target=-(learn_parm->eps-(double)label[i]*c[i]);
+ if((target-dist) > slack[docs[i]->slackid])
+ slack[docs[i]->slackid]=target-dist;
+ alphaslack[docs[i]->slackid]+=a[i];
+ }
+}
+
+
+long identify_inconsistent(double *a, long int *label,
+ long int *unlabeled, long int totdoc,
+ LEARN_PARM *learn_parm,
+ long int *inconsistentnum, long int *inconsistent)
+{
+ long i,retrain;
+
+ /* Throw out examples with multipliers at upper bound. This */
+ /* corresponds to the -i 1 option. */
+ /* ATTENTION: this is just a heuristic for finding a close */
+ /* to minimum number of examples to exclude to */
+ /* make the problem separable with desired margin */
+ retrain=0;
+ for(i=0;i<totdoc;i++) {
+ if((!inconsistent[i]) && (!unlabeled[i])
+ && (a[i]>=(learn_parm->svm_cost[i]-learn_parm->epsilon_a))) {
+ (*inconsistentnum)++;
+ inconsistent[i]=1; /* never choose again */
+ retrain=2; /* start over */
+ if(verbosity>=3) {
+ printf("inconsistent(%ld)..",i); fflush(stdout);
+ }
+ }
+ }
+ return(retrain);
+}
+
+long identify_misclassified(double *lin, long int *label,
+ long int *unlabeled, long int totdoc,
+ MODEL *model, long int *inconsistentnum,
+ long int *inconsistent)
+{
+ long i,retrain;
+ double dist;
+
+ /* Throw out misclassified examples. This */
+ /* corresponds to the -i 2 option. */
+ /* ATTENTION: this is just a heuristic for finding a close */
+ /* to minimum number of examples to exclude to */
+ /* make the problem separable with desired margin */
+ retrain=0;
+ for(i=0;i<totdoc;i++) {
+ dist=(lin[i]-model->b)*(double)label[i]; /* 'distance' from hyperplane*/
+ if((!inconsistent[i]) && (!unlabeled[i]) && (dist <= 0)) {
+ (*inconsistentnum)++;
+ inconsistent[i]=1; /* never choose again */
+ retrain=2; /* start over */
+ if(verbosity>=3) {
+ printf("inconsistent(%ld)..",i); fflush(stdout);
+ }
+ }
+ }
+ return(retrain);
+}
+
+long identify_one_misclassified(double *lin, long int *label,
+ long int *unlabeled,
+ long int totdoc, MODEL *model,
+ long int *inconsistentnum,
+ long int *inconsistent)
+{
+ long i,retrain,maxex=-1;
+ double dist,maxdist=0;
+
+ /* Throw out the 'most misclassified' example. This */
+ /* corresponds to the -i 3 option. */
+ /* ATTENTION: this is just a heuristic for finding a close */
+ /* to minimum number of examples to exclude to */
+ /* make the problem separable with desired margin */
+ retrain=0;
+ for(i=0;i<totdoc;i++) {
+ if((!inconsistent[i]) && (!unlabeled[i])) {
+ dist=(lin[i]-model->b)*(double)label[i];/* 'distance' from hyperplane*/
+ if(dist<maxdist) {
+ maxdist=dist;
+ maxex=i;
+ }
+ }
+ }
+ if(maxex>=0) {
+ (*inconsistentnum)++;
+ inconsistent[maxex]=1; /* never choose again */
+ retrain=2; /* start over */
+ if(verbosity>=3) {
+ printf("inconsistent(%ld)..",i); fflush(stdout);
+ }
+ }
+ return(retrain);
+}
+
+void update_linear_component(DOC **docs, long int *label,
+ long int *active2dnum, double *a,
+ double *a_old, long int *working2dnum,
+ long int totdoc, long int totwords,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache,
+ double *lin, CFLOAT *aicache, double *weights)
+ /* keep track of the linear component */
+ /* lin of the gradient etc. by updating */
+ /* based on the change of the variables */
+ /* in the current working set */
+{
+ register long i,ii,j,jj;
+ register double tec;
+ SVECTOR *f;
+
+ if(kernel_parm->kernel_type==0) { /* special linear case */
+ clear_vector_n(weights,totwords);
+ for(ii=0;(i=working2dnum[ii])>=0;ii++) {
+ if(a[i] != a_old[i]) {
+ for(f=docs[i]->fvec;f;f=f->next)
+ add_vector_ns(weights,f,
+ f->factor*((a[i]-a_old[i])*(double)label[i]));
+ }
+ }
+ for(jj=0;(j=active2dnum[jj])>=0;jj++) {
+ for(f=docs[j]->fvec;f;f=f->next)
+ lin[j]+=f->factor*sprod_ns(weights,f);
+ }
+ }
+ else { /* general case */
+ for(jj=0;(i=working2dnum[jj])>=0;jj++) {
+ if(a[i] != a_old[i]) {
+ get_kernel_row(kernel_cache,docs,i,totdoc,active2dnum,aicache,
+ kernel_parm);
+ for(ii=0;(j=active2dnum[ii])>=0;ii++) {
+ tec=aicache[j];
+ lin[j]+=(((a[i]*tec)-(a_old[i]*tec))*(double)label[i]);
+ }
+ }
+ }
+ }
+}
+
+
+long incorporate_unlabeled_examples(MODEL *model, long int *label,
+ long int *inconsistent,
+ long int *unlabeled,
+ double *a, double *lin,
+ long int totdoc, double *selcrit,
+ long int *select, long int *key,
+ long int transductcycle,
+ KERNEL_PARM *kernel_parm,
+ LEARN_PARM *learn_parm)
+{
+ long i,j,k,j1,j2,j3,j4,unsupaddnum1=0,unsupaddnum2=0;
+ long pos,neg,upos,uneg,orgpos,orgneg,nolabel,newpos,newneg,allunlab;
+ double dist,model_length,posratio,negratio;
+ long check_every=2;
+ double loss;
+ static double switchsens=0.0,switchsensorg=0.0;
+ double umin,umax,sumalpha;
+ long imin=0,imax=0;
+ static long switchnum=0;
+
+ switchsens/=1.2;
+
+ /* assumes that lin[] is up to date -> no inactive vars */
+
+ orgpos=0;
+ orgneg=0;
+ newpos=0;
+ newneg=0;
+ nolabel=0;
+ allunlab=0;
+ for(i=0;i<totdoc;i++) {
+ if(!unlabeled[i]) {
+ if(label[i] > 0) {
+ orgpos++;
+ }
+ else {
+ orgneg++;
+ }
+ }
+ else {
+ allunlab++;
+ if(unlabeled[i]) {
+ if(label[i] > 0) {
+ newpos++;
+ }
+ else if(label[i] < 0) {
+ newneg++;
+ }
+ }
+ }
+ if(label[i]==0) {
+ nolabel++;
+ }
+ }
+
+ if(learn_parm->transduction_posratio >= 0) {
+ posratio=learn_parm->transduction_posratio;
+ }
+ else {
+ posratio=(double)orgpos/(double)(orgpos+orgneg); /* use ratio of pos/neg */
+ } /* in training data */
+ negratio=1.0-posratio;
+
+ learn_parm->svm_costratio=1.0; /* global */
+ if(posratio>0) {
+ learn_parm->svm_costratio_unlab=negratio/posratio;
+ }
+ else {
+ learn_parm->svm_costratio_unlab=1.0;
+ }
+
+ pos=0;
+ neg=0;
+ upos=0;
+ uneg=0;
+ for(i=0;i<totdoc;i++) {
+ dist=(lin[i]-model->b); /* 'distance' from hyperplane*/
+ if(dist>0) {
+ pos++;
+ }
+ else {
+ neg++;
+ }
+ if(unlabeled[i]) {
+ if(dist>0) {
+ upos++;
+ }
+ else {
+ uneg++;
+ }
+ }
+ if((!unlabeled[i]) && (a[i]>(learn_parm->svm_cost[i]-learn_parm->epsilon_a))) {
+ /* printf("Ubounded %ld (class %ld, unlabeled %ld)\n",i,label[i],unlabeled[i]); */
+ }
+ }
+ if(verbosity>=2) {
+ printf("POS=%ld, ORGPOS=%ld, ORGNEG=%ld\n",pos,orgpos,orgneg);
+ printf("POS=%ld, NEWPOS=%ld, NEWNEG=%ld\n",pos,newpos,newneg);
+ printf("pos ratio = %f (%f).\n",(double)(upos)/(double)(allunlab),posratio);
+ fflush(stdout);
+ }
+
+ if(transductcycle == 0) {
+ j1=0;
+ j2=0;
+ j4=0;
+ for(i=0;i<totdoc;i++) {
+ dist=(lin[i]-model->b); /* 'distance' from hyperplane*/
+ if((label[i]==0) && (unlabeled[i])) {
+ selcrit[j4]=dist;
+ key[j4]=i;
+ j4++;
+ }
+ }
+ unsupaddnum1=0;
+ unsupaddnum2=0;
+ select_top_n(selcrit,j4,select,(long)(allunlab*posratio+0.5));
+ for(k=0;(k<(long)(allunlab*posratio+0.5));k++) {
+ i=key[select[k]];
+ label[i]=1;
+ unsupaddnum1++;
+ j1++;
+ }
+ for(i=0;i<totdoc;i++) {
+ if((label[i]==0) && (unlabeled[i])) {
+ label[i]=-1;
+ j2++;
+ unsupaddnum2++;
+ }
+ }
+ for(i=0;i<totdoc;i++) { /* set upper bounds on vars */
+ if(unlabeled[i]) {
+ if(label[i] == 1) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*
+ learn_parm->svm_costratio_unlab*learn_parm->svm_unlabbound;
+ }
+ else if(label[i] == -1) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*
+ learn_parm->svm_unlabbound;
+ }
+ }
+ }
+ if(verbosity>=1) {
+ /* printf("costratio %f, costratio_unlab %f, unlabbound %f\n",
+ learn_parm->svm_costratio,learn_parm->svm_costratio_unlab,
+ learn_parm->svm_unlabbound); */
+ printf("Classifying unlabeled data as %ld POS / %ld NEG.\n",
+ unsupaddnum1,unsupaddnum2);
+ fflush(stdout);
+ }
+ if(verbosity >= 1)
+ printf("Retraining.");
+ if(verbosity >= 2) printf("\n");
+ return((long)3);
+ }
+ if((transductcycle % check_every) == 0) {
+ if(verbosity >= 1)
+ printf("Retraining.");
+ if(verbosity >= 2) printf("\n");
+ j1=0;
+ j2=0;
+ unsupaddnum1=0;
+ unsupaddnum2=0;
+ for(i=0;i<totdoc;i++) {
+ if((unlabeled[i] == 2)) {
+ unlabeled[i]=1;
+ label[i]=1;
+ j1++;
+ unsupaddnum1++;
+ }
+ else if((unlabeled[i] == 3)) {
+ unlabeled[i]=1;
+ label[i]=-1;
+ j2++;
+ unsupaddnum2++;
+ }
+ }
+ for(i=0;i<totdoc;i++) { /* set upper bounds on vars */
+ if(unlabeled[i]) {
+ if(label[i] == 1) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*
+ learn_parm->svm_costratio_unlab*learn_parm->svm_unlabbound;
+ }
+ else if(label[i] == -1) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*
+ learn_parm->svm_unlabbound;
+ }
+ }
+ }
+
+ if(verbosity>=2) {
+ /* printf("costratio %f, costratio_unlab %f, unlabbound %f\n",
+ learn_parm->svm_costratio,learn_parm->svm_costratio_unlab,
+ learn_parm->svm_unlabbound); */
+ printf("%ld positive -> Added %ld POS / %ld NEG unlabeled examples.\n",
+ upos,unsupaddnum1,unsupaddnum2);
+ fflush(stdout);
+ }
+
+ if(learn_parm->svm_unlabbound == 1) {
+ learn_parm->epsilon_crit=0.001; /* do the last run right */
+ }
+ else {
+ learn_parm->epsilon_crit=0.01; /* otherwise, no need to be so picky */
+ }
+
+ return((long)3);
+ }
+ else if(((transductcycle % check_every) < check_every)) {
+ model_length=0;
+ sumalpha=0;
+ loss=0;
+ for(i=0;i<totdoc;i++) {
+ model_length+=a[i]*label[i]*lin[i];
+ sumalpha+=a[i];
+ dist=(lin[i]-model->b); /* 'distance' from hyperplane*/
+ if((label[i]*dist)<(1.0-learn_parm->epsilon_crit)) {
+ loss+=(1.0-(label[i]*dist))*learn_parm->svm_cost[i];
+ }
+ }
+ model_length=sqrt(model_length);
+ if(verbosity>=2) {
+ printf("Model-length = %f (%f), loss = %f, objective = %f\n",
+ model_length,sumalpha,loss,loss+0.5*model_length*model_length);
+ fflush(stdout);
+ }
+ j1=0;
+ j2=0;
+ j3=0;
+ j4=0;
+ unsupaddnum1=0;
+ unsupaddnum2=0;
+ umin=99999;
+ umax=-99999;
+ j4=1;
+ while(j4) {
+ umin=99999;
+ umax=-99999;
+ for(i=0;(i<totdoc);i++) {
+ dist=(lin[i]-model->b);
+ if((label[i]>0) && (unlabeled[i]) && (!inconsistent[i])
+ && (dist<umin)) {
+ umin=dist;
+ imin=i;
+ }
+ if((label[i]<0) && (unlabeled[i]) && (!inconsistent[i])
+ && (dist>umax)) {
+ umax=dist;
+ imax=i;
+ }
+ }
+ if((umin < (umax+switchsens-1E-4))) {
+ j1++;
+ j2++;
+ unsupaddnum1++;
+ unlabeled[imin]=3;
+ inconsistent[imin]=1;
+ unsupaddnum2++;
+ unlabeled[imax]=2;
+ inconsistent[imax]=1;
+ }
+ else
+ j4=0;
+ j4=0;
+ }
+ for(j=0;(j<totdoc);j++) {
+ if(unlabeled[j] && (!inconsistent[j])) {
+ if(label[j]>0) {
+ unlabeled[j]=2;
+ }
+ else if(label[j]<0) {
+ unlabeled[j]=3;
+ }
+ /* inconsistent[j]=1; */
+ j3++;
+ }
+ }
+ switchnum+=unsupaddnum1+unsupaddnum2;
+
+ /* stop and print out current margin
+ printf("switchnum %ld %ld\n",switchnum,kernel_parm->poly_degree);
+ if(switchnum == 2*kernel_parm->poly_degree) {
+ learn_parm->svm_unlabbound=1;
+ }
+ */
+
+ if((!unsupaddnum1) && (!unsupaddnum2)) {
+ if((learn_parm->svm_unlabbound>=1) && ((newpos+newneg) == allunlab)) {
+ for(j=0;(j<totdoc);j++) {
+ inconsistent[j]=0;
+ if(unlabeled[j]) unlabeled[j]=1;
+ }
+ write_prediction(learn_parm->predfile,model,lin,a,unlabeled,label,
+ totdoc,learn_parm);
+ if(verbosity>=1)
+ printf("Number of switches: %ld\n",switchnum);
+ return((long)0);
+ }
+ switchsens=switchsensorg;
+ learn_parm->svm_unlabbound*=1.5;
+ if(learn_parm->svm_unlabbound>1) {
+ learn_parm->svm_unlabbound=1;
+ }
+ model->at_upper_bound=0; /* since upper bound increased */
+ if(verbosity>=1)
+ printf("Increasing influence of unlabeled examples to %f%% .",
+ learn_parm->svm_unlabbound*100.0);
+ }
+ else if(verbosity>=1) {
+ printf("%ld positive -> Switching labels of %ld POS / %ld NEG unlabeled examples.",
+ upos,unsupaddnum1,unsupaddnum2);
+ fflush(stdout);
+ }
+
+ if(verbosity >= 2) printf("\n");
+
+ learn_parm->epsilon_crit=0.5; /* don't need to be so picky */
+
+ for(i=0;i<totdoc;i++) { /* set upper bounds on vars */
+ if(unlabeled[i]) {
+ if(label[i] == 1) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*
+ learn_parm->svm_costratio_unlab*learn_parm->svm_unlabbound;
+ }
+ else if(label[i] == -1) {
+ learn_parm->svm_cost[i]=learn_parm->svm_c*
+ learn_parm->svm_unlabbound;
+ }
+ }
+ }
+
+ return((long)2);
+ }
+
+ return((long)0);
+}
+
+/*************************** Working set selection ***************************/
+
+long select_next_qp_subproblem_grad(long int *label,
+ long int *unlabeled,
+ double *a, double *lin,
+ double *c, long int totdoc,
+ long int qp_size,
+ LEARN_PARM *learn_parm,
+ long int *inconsistent,
+ long int *active2dnum,
+ long int *working2dnum,
+ double *selcrit,
+ long int *select,
+ KERNEL_CACHE *kernel_cache,
+ long int cache_only,
+ long int *key, long int *chosen)
+ /* Use the feasible direction approach to select the next
+ qp-subproblem (see chapter 'Selecting a good working set'). If
+ 'cache_only' is true, then the variables are selected only among
+ those for which the kernel evaluations are cached. */
+{
+ long choosenum,i,j,k,activedoc,inum,valid;
+ double s;
+
+ for(inum=0;working2dnum[inum]>=0;inum++); /* find end of index */
+ choosenum=0;
+ activedoc=0;
+ for(i=0;(j=active2dnum[i])>=0;i++) {
+ s=-label[j];
+ if(kernel_cache && cache_only)
+ valid=(kernel_cache->index[j]>=0);
+ else
+ valid=1;
+ if(valid
+ && (!((a[j]<=(0+learn_parm->epsilon_a)) && (s<0)))
+ && (!((a[j]>=(learn_parm->svm_cost[j]-learn_parm->epsilon_a))
+ && (s>0)))
+ && (!chosen[j])
+ && (label[j])
+ && (!inconsistent[j]))
+ {
+ selcrit[activedoc]=(double)label[j]*(learn_parm->eps-(double)label[j]*c[j]+(double)label[j]*lin[j]);
+ /* selcrit[activedoc]=(double)label[j]*(-1.0+(double)label[j]*lin[j]); */
+ key[activedoc]=j;
+ activedoc++;
+ }
+ }
+ select_top_n(selcrit,activedoc,select,(long)(qp_size/2));
+ for(k=0;(choosenum<(qp_size/2)) && (k<(qp_size/2)) && (k<activedoc);k++) {
+ /* if(learn_parm->biased_hyperplane || (selcrit[select[k]] > 0)) { */
+ i=key[select[k]];
+ chosen[i]=1;
+ working2dnum[inum+choosenum]=i;
+ choosenum+=1;
+ if(kernel_cache)
+ kernel_cache_touch(kernel_cache,i); /* make sure it does not get
+ kicked out of cache */
+ /* } */
+ }
+
+ activedoc=0;
+ for(i=0;(j=active2dnum[i])>=0;i++) {
+ s=label[j];
+ if(kernel_cache && cache_only)
+ valid=(kernel_cache->index[j]>=0);
+ else
+ valid=1;
+ if(valid
+ && (!((a[j]<=(0+learn_parm->epsilon_a)) && (s<0)))
+ && (!((a[j]>=(learn_parm->svm_cost[j]-learn_parm->epsilon_a))
+ && (s>0)))
+ && (!chosen[j])
+ && (label[j])
+ && (!inconsistent[j]))
+ {
+ selcrit[activedoc]=-(double)label[j]*(learn_parm->eps-(double)label[j]*c[j]+(double)label[j]*lin[j]);
+ /* selcrit[activedoc]=-(double)(label[j]*(-1.0+(double)label[j]*lin[j])); */
+ key[activedoc]=j;
+ activedoc++;
+ }
+ }
+ select_top_n(selcrit,activedoc,select,(long)(qp_size/2));
+ for(k=0;(choosenum<qp_size) && (k<(qp_size/2)) && (k<activedoc);k++) {
+ /* if(learn_parm->biased_hyperplane || (selcrit[select[k]] > 0)) { */
+ i=key[select[k]];
+ chosen[i]=1;
+ working2dnum[inum+choosenum]=i;
+ choosenum+=1;
+ if(kernel_cache)
+ kernel_cache_touch(kernel_cache,i); /* make sure it does not get
+ kicked out of cache */
+ /* } */
+ }
+ working2dnum[inum+choosenum]=-1; /* complete index */
+ return(choosenum);
+}
+
+long select_next_qp_subproblem_rand(long int *label,
+ long int *unlabeled,
+ double *a, double *lin,
+ double *c, long int totdoc,
+ long int qp_size,
+ LEARN_PARM *learn_parm,
+ long int *inconsistent,
+ long int *active2dnum,
+ long int *working2dnum,
+ double *selcrit,
+ long int *select,
+ KERNEL_CACHE *kernel_cache,
+ long int *key,
+ long int *chosen,
+ long int iteration)
+/* Use the feasible direction approach to select the next
+ qp-subproblem (see section 'Selecting a good working set'). Chooses
+ a feasible direction at (pseudo) random to help jump over numerical
+ problem. */
+{
+ long choosenum,i,j,k,activedoc,inum;
+ double s;
+
+ for(inum=0;working2dnum[inum]>=0;inum++); /* find end of index */
+ choosenum=0;
+ activedoc=0;
+ for(i=0;(j=active2dnum[i])>=0;i++) {
+ s=-label[j];
+ if((!((a[j]<=(0+learn_parm->epsilon_a)) && (s<0)))
+ && (!((a[j]>=(learn_parm->svm_cost[j]-learn_parm->epsilon_a))
+ && (s>0)))
+ && (!inconsistent[j])
+ && (label[j])
+ && (!chosen[j])) {
+ selcrit[activedoc]=(j+iteration) % totdoc;
+ key[activedoc]=j;
+ activedoc++;
+ }
+ }
+ select_top_n(selcrit,activedoc,select,(long)(qp_size/2));
+ for(k=0;(choosenum<(qp_size/2)) && (k<(qp_size/2)) && (k<activedoc);k++) {
+ i=key[select[k]];
+ chosen[i]=1;
+ working2dnum[inum+choosenum]=i;
+ choosenum+=1;
+ kernel_cache_touch(kernel_cache,i); /* make sure it does not get kicked */
+ /* out of cache */
+ }
+
+ activedoc=0;
+ for(i=0;(j=active2dnum[i])>=0;i++) {
+ s=label[j];
+ if((!((a[j]<=(0+learn_parm->epsilon_a)) && (s<0)))
+ && (!((a[j]>=(learn_parm->svm_cost[j]-learn_parm->epsilon_a))
+ && (s>0)))
+ && (!inconsistent[j])
+ && (label[j])
+ && (!chosen[j])) {
+ selcrit[activedoc]=(j+iteration) % totdoc;
+ key[activedoc]=j;
+ activedoc++;
+ }
+ }
+ select_top_n(selcrit,activedoc,select,(long)(qp_size/2));
+ for(k=0;(choosenum<qp_size) && (k<(qp_size/2)) && (k<activedoc);k++) {
+ i=key[select[k]];
+ chosen[i]=1;
+ working2dnum[inum+choosenum]=i;
+ choosenum+=1;
+ kernel_cache_touch(kernel_cache,i); /* make sure it does not get kicked */
+ /* out of cache */
+ }
+ working2dnum[inum+choosenum]=-1; /* complete index */
+ return(choosenum);
+}
+
+long select_next_qp_slackset(DOC **docs, long int *label,
+ double *a, double *lin,
+ double *slack, double *alphaslack,
+ double *c,
+ LEARN_PARM *learn_parm,
+ long int *active2dnum, double *maxviol)
+ /* returns the slackset with the largest internal violation */
+{
+ long i,ii,maxdiffid;
+ double dist,target,maxdiff,ex_c;
+
+ maxdiff=0;
+ maxdiffid=0;
+ for(ii=0;(i=active2dnum[ii])>=0;ii++) {
+ ex_c=learn_parm->svm_c-learn_parm->epsilon_a;
+ if(alphaslack[docs[i]->slackid] >= ex_c) {
+ dist=(lin[i])*(double)label[i]+slack[docs[i]->slackid]; /* distance */
+ target=-(learn_parm->eps-(double)label[i]*c[i]); /* rhs of constraint */
+ if((a[i]>learn_parm->epsilon_a) && (dist > target)) {
+ if((dist-target)>maxdiff) { /* largest violation */
+ maxdiff=dist-target;
+ maxdiffid=docs[i]->slackid;
+ }
+ }
+ }
+ }
+ (*maxviol)=maxdiff;
+ return(maxdiffid);
+}
+
+
+void select_top_n(double *selcrit, long int range, long int *select,
+ long int n)
+{
+ register long i,j;
+
+ for(i=0;(i<n) && (i<range);i++) { /* Initialize with the first n elements */
+ for(j=i;j>=0;j--) {
+ if((j>0) && (selcrit[select[j-1]]<selcrit[i])){
+ select[j]=select[j-1];
+ }
+ else {
+ select[j]=i;
+ j=-1;
+ }
+ }
+ }
+ if(n>0) {
+ for(i=n;i<range;i++) {
+ if(selcrit[i]>selcrit[select[n-1]]) {
+ for(j=n-1;j>=0;j--) {
+ if((j>0) && (selcrit[select[j-1]]<selcrit[i])) {
+ select[j]=select[j-1];
+ }
+ else {
+ select[j]=i;
+ j=-1;
+ }
+ }
+ }
+ }
+ }
+}
+
+
+/******************************** Shrinking *********************************/
+
+void init_shrink_state(SHRINK_STATE *shrink_state, long int totdoc,
+ long int maxhistory)
+{
+ long i;
+
+ shrink_state->deactnum=0;
+ shrink_state->active = (long *)my_malloc(sizeof(long)*totdoc);
+ shrink_state->inactive_since = (long *)my_malloc(sizeof(long)*totdoc);
+ shrink_state->a_history = (double **)my_malloc(sizeof(double *)*maxhistory);
+ shrink_state->maxhistory=maxhistory;
+ shrink_state->last_lin = (double *)my_malloc(sizeof(double)*totdoc);
+ shrink_state->last_a = (double *)my_malloc(sizeof(double)*totdoc);
+
+ for(i=0;i<totdoc;i++) {
+ shrink_state->active[i]=1;
+ shrink_state->inactive_since[i]=0;
+ shrink_state->last_a[i]=0;
+ shrink_state->last_lin[i]=0;
+ }
+}
+
+void shrink_state_cleanup(SHRINK_STATE *shrink_state)
+{
+ free(shrink_state->active);
+ free(shrink_state->inactive_since);
+ if(shrink_state->deactnum > 0)
+ free(shrink_state->a_history[shrink_state->deactnum-1]);
+ free(shrink_state->a_history);
+ free(shrink_state->last_a);
+ free(shrink_state->last_lin);
+}
+
+long shrink_problem(DOC **docs,
+ LEARN_PARM *learn_parm,
+ SHRINK_STATE *shrink_state,
+ KERNEL_PARM *kernel_parm,
+ long int *active2dnum,
+ long int *last_suboptimal_at,
+ long int iteration,
+ long int totdoc,
+ long int minshrink,
+ double *a,
+ long int *inconsistent)
+ /* Shrink some variables away. Do the shrinking only if at least
+ minshrink variables can be removed. */
+{
+ long i,ii,change,activenum,lastiter;
+ double *a_old;
+
+ activenum=0;
+ change=0;
+ for(ii=0;active2dnum[ii]>=0;ii++) {
+ i=active2dnum[ii];
+ activenum++;
+ if(learn_parm->sharedslack)
+ lastiter=last_suboptimal_at[docs[i]->slackid];
+ else
+ lastiter=last_suboptimal_at[i];
+ if(((iteration-lastiter) > learn_parm->svm_iter_to_shrink)
+ || (inconsistent[i])) {
+ change++;
+ }
+ }
+ if((change>=minshrink) /* shrink only if sufficiently many candidates */
+ && (shrink_state->deactnum<shrink_state->maxhistory)) { /* and enough memory */
+ /* Shrink problem by removing those variables which are */
+ /* optimal at a bound for a minimum number of iterations */
+ if(verbosity>=2) {
+ printf(" Shrinking..."); fflush(stdout);
+ }
+ if(kernel_parm->kernel_type != LINEAR) { /* non-linear case save alphas */
+ a_old=(double *)my_malloc(sizeof(double)*totdoc);
+ shrink_state->a_history[shrink_state->deactnum]=a_old;
+ for(i=0;i<totdoc;i++) {
+ a_old[i]=a[i];
+ }
+ }
+ for(ii=0;active2dnum[ii]>=0;ii++) {
+ i=active2dnum[ii];
+ if(learn_parm->sharedslack)
+ lastiter=last_suboptimal_at[docs[i]->slackid];
+ else
+ lastiter=last_suboptimal_at[i];
+ if(((iteration-lastiter) > learn_parm->svm_iter_to_shrink)
+ || (inconsistent[i])) {
+ shrink_state->active[i]=0;
+ shrink_state->inactive_since[i]=shrink_state->deactnum;
+ }
+ }
+ activenum=compute_index(shrink_state->active,totdoc,active2dnum);
+ shrink_state->deactnum++;
+ if(kernel_parm->kernel_type == LINEAR) {
+ shrink_state->deactnum=0;
+ }
+ if(verbosity>=2) {
+ printf("done.\n"); fflush(stdout);
+ printf(" Number of inactive variables = %ld\n",totdoc-activenum);
+ }
+ }
+ return(activenum);
+}
+
+
+void reactivate_inactive_examples(long int *label,
+ long int *unlabeled,
+ double *a,
+ SHRINK_STATE *shrink_state,
+ double *lin,
+ double *c,
+ long int totdoc,
+ long int totwords,
+ long int iteration,
+ LEARN_PARM *learn_parm,
+ long int *inconsistent,
+ DOC **docs,
+ KERNEL_PARM *kernel_parm,
+ KERNEL_CACHE *kernel_cache,
+ MODEL *model,
+ CFLOAT *aicache,
+ double *weights,
+ double *maxdiff)
+ /* Make all variables active again which had been removed by
+ shrinking. */
+ /* Computes lin for those variables from scratch. */
+{
+ register long i,j,ii,jj,t,*changed2dnum,*inactive2dnum;
+ long *changed,*inactive;
+ register double kernel_val,*a_old,dist;
+ double ex_c,target;
+ SVECTOR *f;
+
+ if(kernel_parm->kernel_type == LINEAR) { /* special linear case */
+ a_old=shrink_state->last_a;
+ clear_vector_n(weights,totwords);
+ for(i=0;i<totdoc;i++) {
+ if(a[i] != a_old[i]) {
+ for(f=docs[i]->fvec;f;f=f->next)
+ add_vector_ns(weights,f,
+ f->factor*((a[i]-a_old[i])*(double)label[i]));
+ a_old[i]=a[i];
+ }
+ }
+ for(i=0;i<totdoc;i++) {
+ if(!shrink_state->active[i]) {
+ for(f=docs[i]->fvec;f;f=f->next)
+ lin[i]=shrink_state->last_lin[i]+f->factor*sprod_ns(weights,f);
+ }
+ shrink_state->last_lin[i]=lin[i];
+ }
+ }
+ else {
+ changed=(long *)my_malloc(sizeof(long)*totdoc);
+ changed2dnum=(long *)my_malloc(sizeof(long)*(totdoc+11));
+ inactive=(long *)my_malloc(sizeof(long)*totdoc);
+ inactive2dnum=(long *)my_malloc(sizeof(long)*(totdoc+11));
+ for(t=shrink_state->deactnum-1;(t>=0) && shrink_state->a_history[t];t--) {
+ if(verbosity>=2) {
+ printf("%ld..",t); fflush(stdout);
+ }
+ a_old=shrink_state->a_history[t];
+ for(i=0;i<totdoc;i++) {
+ inactive[i]=((!shrink_state->active[i])
+ && (shrink_state->inactive_since[i] == t));
+ changed[i]= (a[i] != a_old[i]);
+ }
+ compute_index(inactive,totdoc,inactive2dnum);
+ compute_index(changed,totdoc,changed2dnum);
+
+ for(ii=0;(i=changed2dnum[ii])>=0;ii++) {
+ get_kernel_row(kernel_cache,docs,i,totdoc,inactive2dnum,aicache,
+ kernel_parm);
+ for(jj=0;(j=inactive2dnum[jj])>=0;jj++) {
+ kernel_val=aicache[j];
+ lin[j]+=(((a[i]*kernel_val)-(a_old[i]*kernel_val))*(double)label[i]);
+ }
+ }
+ }
+ free(changed);
+ free(changed2dnum);
+ free(inactive);
+ free(inactive2dnum);
+ }
+ (*maxdiff)=0;
+ for(i=0;i<totdoc;i++) {
+ shrink_state->inactive_since[i]=shrink_state->deactnum-1;
+ if(!inconsistent[i]) {
+ dist=(lin[i]-model->b)*(double)label[i];
+ target=-(learn_parm->eps-(double)label[i]*c[i]);
+ ex_c=learn_parm->svm_cost[i]-learn_parm->epsilon_a;
+ if((a[i]>learn_parm->epsilon_a) && (dist > target)) {
+ if((dist-target)>(*maxdiff)) /* largest violation */
+ (*maxdiff)=dist-target;
+ }
+ else if((a[i]<ex_c) && (dist < target)) {
+ if((target-dist)>(*maxdiff)) /* largest violation */
+ (*maxdiff)=target-dist;
+ }
+ if((a[i]>(0+learn_parm->epsilon_a))
+ && (a[i]<ex_c)) {
+ shrink_state->active[i]=1; /* not at bound */
+ }
+ else if((a[i]<=(0+learn_parm->epsilon_a)) && (dist < (target+learn_parm->epsilon_shrink))) {
+ shrink_state->active[i]=1;
+ }
+ else if((a[i]>=ex_c)
+ && (dist > (target-learn_parm->epsilon_shrink))) {
+ shrink_state->active[i]=1;
+ }
+ else if(learn_parm->sharedslack) { /* make all active when sharedslack */
+ shrink_state->active[i]=1;
+ }
+ }
+ }
+ if(kernel_parm->kernel_type != LINEAR) { /* update history for non-linear */
+ for(i=0;i<totdoc;i++) {
+ (shrink_state->a_history[shrink_state->deactnum-1])[i]=a[i];
+ }
+ for(t=shrink_state->deactnum-2;(t>=0) && shrink_state->a_history[t];t--) {
+ free(shrink_state->a_history[t]);
+ shrink_state->a_history[t]=0;
+ }
+ }
+}
+
+/****************************** Cache handling *******************************/
+
+void get_kernel_row(KERNEL_CACHE *kernel_cache, DOC **docs,
+ long int docnum, long int totdoc,
+ long int *active2dnum, CFLOAT *buffer,
+ KERNEL_PARM *kernel_parm)
+ /* Get's a row of the matrix of kernel values This matrix has the
+ same form as the Hessian, just that the elements are not
+ multiplied by */
+ /* y_i * y_j * a_i * a_j */
+ /* Takes the values from the cache if available. */
+{
+ register long i,j,start;
+ DOC *ex;
+
+ ex=docs[docnum];
+
+ if(kernel_cache->index[docnum] != -1) { /* row is cached? */
+ kernel_cache->lru[kernel_cache->index[docnum]]=kernel_cache->time; /* lru */
+ start=kernel_cache->activenum*kernel_cache->index[docnum];
+ for(i=0;(j=active2dnum[i])>=0;i++) {
+ if(kernel_cache->totdoc2active[j] >= 0) { /* column is cached? */
+ buffer[j]=kernel_cache->buffer[start+kernel_cache->totdoc2active[j]];
+ }
+ else {
+ buffer[j]=(CFLOAT)kernel(kernel_parm,ex,docs[j]);
+ }
+ }
+ }
+ else {
+ for(i=0;(j=active2dnum[i])>=0;i++) {
+ buffer[j]=(CFLOAT)kernel(kernel_parm,ex,docs[j]);
+ }
+ }
+}
+
+
+void cache_kernel_row(KERNEL_CACHE *kernel_cache, DOC **docs,
+ long int m, KERNEL_PARM *kernel_parm)
+ /* Fills cache for the row m */
+{
+ register DOC *ex;
+ register long j,k,l;
+ register CFLOAT *cache;
+
+ if(!kernel_cache_check(kernel_cache,m)) { /* not cached yet*/
+ cache = kernel_cache_clean_and_malloc(kernel_cache,m);
+ if(cache) {
+ l=kernel_cache->totdoc2active[m];
+ ex=docs[m];
+ for(j=0;j<kernel_cache->activenum;j++) { /* fill cache */
+ k=kernel_cache->active2totdoc[j];
+ if((kernel_cache->index[k] != -1) && (l != -1) && (k != m)) {
+ cache[j]=kernel_cache->buffer[kernel_cache->activenum
+ *kernel_cache->index[k]+l];
+ }
+ else {
+ cache[j]=kernel(kernel_parm,ex,docs[k]);
+ }
+ }
+ }
+ else {
+ perror("Error: Kernel cache full! => increase cache size");
+ }
+ }
+}
+
+
+void cache_multiple_kernel_rows(KERNEL_CACHE *kernel_cache, DOC **docs,
+ long int *key, long int varnum,
+ KERNEL_PARM *kernel_parm)
+ /* Fills cache for the rows in key */
+{
+ register long i;
+
+ for(i=0;i<varnum;i++) { /* fill up kernel cache */
+ cache_kernel_row(kernel_cache,docs,key[i],kernel_parm);
+ }
+}
+
+
+void kernel_cache_shrink(KERNEL_CACHE *kernel_cache, long int totdoc,
+ long int numshrink, long int *after)
+ /* Remove numshrink columns in the cache which correspond to
+ examples marked 0 in after. */
+{
+ register long i,j,jj,from=0,to=0,scount;
+ long *keep;
+
+ if(verbosity>=2) {
+ printf(" Reorganizing cache..."); fflush(stdout);
+ }
+
+ keep=(long *)my_malloc(sizeof(long)*totdoc);
+ for(j=0;j<totdoc;j++) {
+ keep[j]=1;
+ }
+ scount=0;
+ for(jj=0;(jj<kernel_cache->activenum) && (scount<numshrink);jj++) {
+ j=kernel_cache->active2totdoc[jj];
+ if(!after[j]) {
+ scount++;
+ keep[j]=0;
+ }
+ }
+
+ for(i=0;i<kernel_cache->max_elems;i++) {
+ for(jj=0;jj<kernel_cache->activenum;jj++) {
+ j=kernel_cache->active2totdoc[jj];
+ if(!keep[j]) {
+ from++;
+ }
+ else {
+ kernel_cache->buffer[to]=kernel_cache->buffer[from];
+ to++;
+ from++;
+ }
+ }
+ }
+
+ kernel_cache->activenum=0;
+ for(j=0;j<totdoc;j++) {
+ if((keep[j]) && (kernel_cache->totdoc2active[j] != -1)) {
+ kernel_cache->active2totdoc[kernel_cache->activenum]=j;
+ kernel_cache->totdoc2active[j]=kernel_cache->activenum;
+ kernel_cache->activenum++;
+ }
+ else {
+ kernel_cache->totdoc2active[j]=-1;
+ }
+ }
+
+ kernel_cache->max_elems=(long)(kernel_cache->buffsize/kernel_cache->activenum);
+ if(kernel_cache->max_elems>totdoc) {
+ kernel_cache->max_elems=totdoc;
+ }
+
+ free(keep);
+
+ if(verbosity>=2) {
+ printf("done.\n"); fflush(stdout);
+ printf(" Cache-size in rows = %ld\n",kernel_cache->max_elems);
+ }
+}
+
+KERNEL_CACHE *kernel_cache_init(long int totdoc, long int buffsize)
+{
+ long i;
+ KERNEL_CACHE *kernel_cache;
+
+ kernel_cache=(KERNEL_CACHE *)my_malloc(sizeof(KERNEL_CACHE));
+ kernel_cache->index = (long *)my_malloc(sizeof(long)*totdoc);
+ kernel_cache->occu = (long *)my_malloc(sizeof(long)*totdoc);
+ kernel_cache->lru = (long *)my_malloc(sizeof(long)*totdoc);
+ kernel_cache->invindex = (long *)my_malloc(sizeof(long)*totdoc);
+ kernel_cache->active2totdoc = (long *)my_malloc(sizeof(long)*totdoc);
+ kernel_cache->totdoc2active = (long *)my_malloc(sizeof(long)*totdoc);
+ kernel_cache->buffer = (CFLOAT *)my_malloc((size_t)(buffsize)*1024*1024);
+
+ kernel_cache->buffsize=(long)(buffsize/sizeof(CFLOAT)*1024*1024);
+
+ kernel_cache->max_elems=(long)(kernel_cache->buffsize/totdoc);
+ if(kernel_cache->max_elems>totdoc) {
+ kernel_cache->max_elems=totdoc;
+ }
+
+ if(verbosity>=2) {
+ printf(" Cache-size in rows = %ld\n",kernel_cache->max_elems);
+ printf(" Kernel evals so far: %ld\n",kernel_cache_statistic);
+ }
+
+ kernel_cache->elems=0; /* initialize cache */
+ for(i=0;i<totdoc;i++) {
+ kernel_cache->index[i]=-1;
+ kernel_cache->lru[i]=0;
+ }
+ for(i=0;i<totdoc;i++) {
+ kernel_cache->occu[i]=0;
+ kernel_cache->invindex[i]=-1;
+ }
+
+ kernel_cache->activenum=totdoc;;
+ for(i=0;i<totdoc;i++) {
+ kernel_cache->active2totdoc[i]=i;
+ kernel_cache->totdoc2active[i]=i;
+ }
+
+ kernel_cache->time=0;
+
+ return(kernel_cache);
+}
+
+void kernel_cache_reset_lru(KERNEL_CACHE *kernel_cache)
+{
+ long maxlru=0,k;
+
+ for(k=0;k<kernel_cache->max_elems;k++) {
+ if(maxlru < kernel_cache->lru[k])
+ maxlru=kernel_cache->lru[k];
+ }
+ for(k=0;k<kernel_cache->max_elems;k++) {
+ kernel_cache->lru[k]-=maxlru;
+ }
+}
+
+void kernel_cache_cleanup(KERNEL_CACHE *kernel_cache)
+{
+ free(kernel_cache->index);
+ free(kernel_cache->occu);
+ free(kernel_cache->lru);
+ free(kernel_cache->invindex);
+ free(kernel_cache->active2totdoc);
+ free(kernel_cache->totdoc2active);
+ free(kernel_cache->buffer);
+ free(kernel_cache);
+}
+
+long kernel_cache_malloc(KERNEL_CACHE *kernel_cache)
+{
+ long i;
+
+ if(kernel_cache_space_available(kernel_cache)) {
+ for(i=0;i<kernel_cache->max_elems;i++) {
+ if(!kernel_cache->occu[i]) {
+ kernel_cache->occu[i]=1;
+ kernel_cache->elems++;
+ return(i);
+ }
+ }
+ }
+ return(-1);
+}
+
+void kernel_cache_free(KERNEL_CACHE *kernel_cache, long int i)
+{
+ kernel_cache->occu[i]=0;
+ kernel_cache->elems--;
+}
+
+long kernel_cache_free_lru(KERNEL_CACHE *kernel_cache)
+ /* remove least recently used cache element */
+{
+ register long k,least_elem=-1,least_time;
+
+ least_time=kernel_cache->time+1;
+ for(k=0;k<kernel_cache->max_elems;k++) {
+ if(kernel_cache->invindex[k] != -1) {
+ if(kernel_cache->lru[k]<least_time) {
+ least_time=kernel_cache->lru[k];
+ least_elem=k;
+ }
+ }
+ }
+ if(least_elem != -1) {
+ kernel_cache_free(kernel_cache,least_elem);
+ kernel_cache->index[kernel_cache->invindex[least_elem]]=-1;
+ kernel_cache->invindex[least_elem]=-1;
+ return(1);
+ }
+ return(0);
+}
+
+
+CFLOAT *kernel_cache_clean_and_malloc(KERNEL_CACHE *kernel_cache,
+ long int docnum)
+ /* Get a free cache entry. In case cache is full, the lru element
+ is removed. */
+{
+ long result;
+ if((result = kernel_cache_malloc(kernel_cache)) == -1) {
+ if(kernel_cache_free_lru(kernel_cache)) {
+ result = kernel_cache_malloc(kernel_cache);
+ }
+ }
+ kernel_cache->index[docnum]=result;
+ if(result == -1) {
+ return(0);
+ }
+ kernel_cache->invindex[result]=docnum;
+ kernel_cache->lru[kernel_cache->index[docnum]]=kernel_cache->time; /* lru */
+ return((CFLOAT *)((long)kernel_cache->buffer
+ +(kernel_cache->activenum*sizeof(CFLOAT)*
+ kernel_cache->index[docnum])));
+}
+
+long kernel_cache_touch(KERNEL_CACHE *kernel_cache, long int docnum)
+ /* Update lru time to avoid removal from cache. */
+{
+ if(kernel_cache && kernel_cache->index[docnum] != -1) {
+ kernel_cache->lru[kernel_cache->index[docnum]]=kernel_cache->time; /* lru */
+ return(1);
+ }
+ return(0);
+}
+
+long kernel_cache_check(KERNEL_CACHE *kernel_cache, long int docnum)
+ /* Is that row cached? */
+{
+ return(kernel_cache->index[docnum] != -1);
+}
+
+long kernel_cache_space_available(KERNEL_CACHE *kernel_cache)
+ /* Is there room for one more row? */
+{
+ return(kernel_cache->elems < kernel_cache->max_elems);
+}
+
+/************************** Compute estimates ******************************/
+
+void compute_xa_estimates(MODEL *model, long int *label,
+ long int *unlabeled, long int totdoc,
+ DOC **docs, double *lin, double *a,
+ KERNEL_PARM *kernel_parm,
+ LEARN_PARM *learn_parm, double *error,
+ double *recall, double *precision)
+ /* Computes xa-estimate of error rate, recall, and precision. See
+ T. Joachims, Estimating the Generalization Performance of an SVM
+ Efficiently, IMCL, 2000. */
+{
+ long i,looerror,looposerror,loonegerror;
+ long totex,totposex;
+ double xi,r_delta,r_delta_sq,sim=0;
+ long *sv2dnum=NULL,*sv=NULL,svnum;
+
+ r_delta=estimate_r_delta(docs,totdoc,kernel_parm);
+ r_delta_sq=r_delta*r_delta;
+
+ looerror=0;
+ looposerror=0;
+ loonegerror=0;
+ totex=0;
+ totposex=0;
+ svnum=0;
+
+ if(learn_parm->xa_depth > 0) {
+ sv = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ for(i=0;i<totdoc;i++)
+ sv[i]=0;
+ for(i=1;i<model->sv_num;i++)
+ if(a[model->supvec[i]->docnum]
+ < (learn_parm->svm_cost[model->supvec[i]->docnum]
+ -learn_parm->epsilon_a)) {
+ sv[model->supvec[i]->docnum]=1;
+ svnum++;
+ }
+ sv2dnum = (long *)my_malloc(sizeof(long)*(totdoc+11));
+ clear_index(sv2dnum);
+ compute_index(sv,totdoc,sv2dnum);
+ }
+
+ for(i=0;i<totdoc;i++) {
+ if(unlabeled[i]) {
+ /* ignore it */
+ }
+ else {
+ xi=1.0-((lin[i]-model->b)*(double)label[i]);
+ if(xi<0) xi=0;
+ if(label[i]>0) {
+ totposex++;
+ }
+ if((learn_parm->rho*a[i]*r_delta_sq+xi) >= 1.0) {
+ if(learn_parm->xa_depth > 0) { /* makes assumptions */
+ sim=distribute_alpha_t_greedily(sv2dnum,svnum,docs,a,i,label,
+ kernel_parm,learn_parm,
+ (double)((1.0-xi-a[i]*r_delta_sq)/(2.0*a[i])));
+ }
+ if((learn_parm->xa_depth == 0) ||
+ ((a[i]*kernel(kernel_parm,docs[i],docs[i])+a[i]*2.0*sim+xi) >= 1.0)) {
+ looerror++;
+ if(label[i]>0) {
+ looposerror++;
+ }
+ else {
+ loonegerror++;
+ }
+ }
+ }
+ totex++;
+ }
+ }
+
+ (*error)=((double)looerror/(double)totex)*100.0;
+ (*recall)=(1.0-(double)looposerror/(double)totposex)*100.0;
+ (*precision)=(((double)totposex-(double)looposerror)
+ /((double)totposex-(double)looposerror+(double)loonegerror))*100.0;
+
+ free(sv);
+ free(sv2dnum);
+}
+
+
+double distribute_alpha_t_greedily(long int *sv2dnum, long int svnum,
+ DOC **docs, double *a,
+ long int docnum,
+ long int *label,
+ KERNEL_PARM *kernel_parm,
+ LEARN_PARM *learn_parm, double thresh)
+ /* Experimental Code improving plain XiAlpha Estimates by
+ computing a better bound using a greedy optimzation strategy. */
+{
+ long best_depth=0;
+ long i,j,k,d,skip,allskip;
+ double best,best_val[101],val,init_val_sq,init_val_lin;
+ long best_ex[101];
+ CFLOAT *cache,*trow;
+
+ cache=(CFLOAT *)my_malloc(sizeof(CFLOAT)*learn_parm->xa_depth*svnum);
+ trow = (CFLOAT *)my_malloc(sizeof(CFLOAT)*svnum);
+
+ for(k=0;k<svnum;k++) {
+ trow[k]=kernel(kernel_parm,docs[docnum],docs[sv2dnum[k]]);
+ }
+
+ init_val_sq=0;
+ init_val_lin=0;
+ best=0;
+
+ for(d=0;d<learn_parm->xa_depth;d++) {
+ allskip=1;
+ if(d>=1) {
+ init_val_sq+=cache[best_ex[d-1]+svnum*(d-1)];
+ for(k=0;k<d-1;k++) {
+ init_val_sq+=2.0*cache[best_ex[k]+svnum*(d-1)];
+ }
+ init_val_lin+=trow[best_ex[d-1]];
+ }
+ for(i=0;i<svnum;i++) {
+ skip=0;
+ if(sv2dnum[i] == docnum) skip=1;
+ for(j=0;j<d;j++) {
+ if(i == best_ex[j]) skip=1;
+ }
+
+ if(!skip) {
+ val=init_val_sq;
+ if(kernel_parm->kernel_type == LINEAR)
+ val+=docs[sv2dnum[i]]->fvec->twonorm_sq;
+ else
+ val+=kernel(kernel_parm,docs[sv2dnum[i]],docs[sv2dnum[i]]);
+ for(j=0;j<d;j++) {
+ val+=2.0*cache[i+j*svnum];
+ }
+ val*=(1.0/(2.0*(d+1.0)*(d+1.0)));
+ val-=((init_val_lin+trow[i])/(d+1.0));
+
+ if(allskip || (val < best_val[d])) {
+ best_val[d]=val;
+ best_ex[d]=i;
+ }
+ allskip=0;
+ if(val < thresh) {
+ i=svnum;
+ /* printf("EARLY"); */
+ }
+ }
+ }
+ if(!allskip) {
+ for(k=0;k<svnum;k++) {
+ cache[d*svnum+k]=kernel(kernel_parm,
+ docs[sv2dnum[best_ex[d]]],
+ docs[sv2dnum[k]]);
+ }
+ }
+ if((!allskip) && ((best_val[d] < best) || (d == 0))) {
+ best=best_val[d];
+ best_depth=d;
+ }
+ if(allskip || (best < thresh)) {
+ d=learn_parm->xa_depth;
+ }
+ }
+
+ free(cache);
+ free(trow);
+
+ /* printf("Distribute[%ld](%ld)=%f, ",docnum,best_depth,best); */
+ return(best);
+}
+
+
+void estimate_transduction_quality(MODEL *model, long int *label,
+ long int *unlabeled,
+ long int totdoc, DOC **docs, double *lin)
+ /* Loo-bound based on observation that loo-errors must have an
+ equal distribution in both training and test examples, given
+ that the test examples are classified correctly. Compare
+ chapter "Constraints on the Transductive Hyperplane" in my
+ Dissertation. */
+{
+ long i,j,l=0,ulab=0,lab=0,labpos=0,labneg=0,ulabpos=0,ulabneg=0,totulab=0;
+ double totlab=0,totlabpos=0,totlabneg=0,labsum=0,ulabsum=0;
+ double r_delta,r_delta_sq,xi,xisum=0,asum=0;
+
+ r_delta=estimate_r_delta(docs,totdoc,&(model->kernel_parm));
+ r_delta_sq=r_delta*r_delta;
+
+ for(j=0;j<totdoc;j++) {
+ if(unlabeled[j]) {
+ totulab++;
+ }
+ else {
+ totlab++;
+ if(label[j] > 0)
+ totlabpos++;
+ else
+ totlabneg++;
+ }
+ }
+ for(j=1;j<model->sv_num;j++) {
+ i=model->supvec[j]->docnum;
+ xi=1.0-((lin[i]-model->b)*(double)label[i]);
+ if(xi<0) xi=0;
+
+ xisum+=xi;
+ asum+=fabs(model->alpha[j]);
+ if(unlabeled[i]) {
+ ulabsum+=(fabs(model->alpha[j])*r_delta_sq+xi);
+ }
+ else {
+ labsum+=(fabs(model->alpha[j])*r_delta_sq+xi);
+ }
+ if((fabs(model->alpha[j])*r_delta_sq+xi) >= 1) {
+ l++;
+ if(unlabeled[model->supvec[j]->docnum]) {
+ ulab++;
+ if(model->alpha[j] > 0)
+ ulabpos++;
+ else
+ ulabneg++;
+ }
+ else {
+ lab++;
+ if(model->alpha[j] > 0)
+ labpos++;
+ else
+ labneg++;
+ }
+ }
+ }
+ printf("xacrit>=1: labeledpos=%.5f labeledneg=%.5f default=%.5f\n",(double)labpos/(double)totlab*100.0,(double)labneg/(double)totlab*100.0,(double)totlabpos/(double)(totlab)*100.0);
+ printf("xacrit>=1: unlabelpos=%.5f unlabelneg=%.5f\n",(double)ulabpos/(double)totulab*100.0,(double)ulabneg/(double)totulab*100.0);
+ printf("xacrit>=1: labeled=%.5f unlabled=%.5f all=%.5f\n",(double)lab/(double)totlab*100.0,(double)ulab/(double)totulab*100.0,(double)l/(double)(totdoc)*100.0);
+ printf("xacritsum: labeled=%.5f unlabled=%.5f all=%.5f\n",(double)labsum/(double)totlab*100.0,(double)ulabsum/(double)totulab*100.0,(double)(labsum+ulabsum)/(double)(totdoc)*100.0);
+ printf("r_delta_sq=%.5f xisum=%.5f asum=%.5f\n",r_delta_sq,xisum,asum);
+}
+
+double estimate_margin_vcdim(MODEL *model, double w, double R,
+ KERNEL_PARM *kernel_parm)
+ /* optional: length of model vector in feature space */
+ /* optional: radius of ball containing the data */
+{
+ double h;
+
+ /* follows chapter 5.6.4 in [Vapnik/95] */
+
+ if(w<0) {
+ w=model_length_s(model,kernel_parm);
+ }
+ if(R<0) {
+ R=estimate_sphere(model,kernel_parm);
+ }
+ h = w*w * R*R +1;
+ return(h);
+}
+
+double estimate_sphere(MODEL *model, KERNEL_PARM *kernel_parm)
+ /* Approximates the radius of the ball containing */
+ /* the support vectors by bounding it with the */
+{ /* length of the longest support vector. This is */
+ register long j; /* pretty good for text categorization, since all */
+ double xlen,maxxlen=0; /* documents have feature vectors of length 1. It */
+ DOC *nulldoc; /* assumes that the center of the ball is at the */
+ WORD nullword; /* origin of the space. */
+
+ nullword.wnum=0;
+ nulldoc=create_example(-2,0,0,0.0,create_svector(&nullword,"",1.0));
+
+ for(j=1;j<model->sv_num;j++) {
+ xlen=sqrt(kernel(kernel_parm,model->supvec[j],model->supvec[j])
+ -2*kernel(kernel_parm,model->supvec[j],nulldoc)
+ +kernel(kernel_parm,nulldoc,nulldoc));
+ if(xlen>maxxlen) {
+ maxxlen=xlen;
+ }
+ }
+
+ free_example(nulldoc,1);
+ return(maxxlen);
+}
+
+double estimate_r_delta(DOC **docs, long int totdoc, KERNEL_PARM *kernel_parm)
+{
+ long i;
+ double maxxlen,xlen;
+ DOC *nulldoc; /* assumes that the center of the ball is at the */
+ WORD nullword; /* origin of the space. */
+
+ nullword.wnum=0;
+ nulldoc=create_example(-2,0,0,0.0,create_svector(&nullword,"",1.0));
+
+ maxxlen=0;
+ for(i=0;i<totdoc;i++) {
+ xlen=sqrt(kernel(kernel_parm,docs[i],docs[i])
+ -2*kernel(kernel_parm,docs[i],nulldoc)
+ +kernel(kernel_parm,nulldoc,nulldoc));
+ if(xlen>maxxlen) {
+ maxxlen=xlen;
+ }
+ }
+
+ free_example(nulldoc,1);
+ return(maxxlen);
+}
+
+double estimate_r_delta_average(DOC **docs, long int totdoc,
+ KERNEL_PARM *kernel_parm)
+{
+ long i;
+ double avgxlen;
+ DOC *nulldoc; /* assumes that the center of the ball is at the */
+ WORD nullword; /* origin of the space. */
+
+ nullword.wnum=0;
+ nulldoc=create_example(-2,0,0,0.0,create_svector(&nullword,"",1.0));
+
+ avgxlen=0;
+ for(i=0;i<totdoc;i++) {
+ avgxlen+=sqrt(kernel(kernel_parm,docs[i],docs[i])
+ -2*kernel(kernel_parm,docs[i],nulldoc)
+ +kernel(kernel_parm,nulldoc,nulldoc));
+ }
+
+ free_example(nulldoc,1);
+ return(avgxlen/totdoc);
+}
+
+double length_of_longest_document_vector(DOC **docs, long int totdoc,
+ KERNEL_PARM *kernel_parm)
+{
+ long i;
+ double maxxlen,xlen;
+
+ maxxlen=0;
+ for(i=0;i<totdoc;i++) {
+ xlen=sqrt(kernel(kernel_parm,docs[i],docs[i]));
+ if(xlen>maxxlen) {
+ maxxlen=xlen;
+ }
+ }
+
+ return(maxxlen);
+}
+
+/****************************** IO-handling **********************************/
+
+void write_prediction(char *predfile, MODEL *model, double *lin,
+ double *a, long int *unlabeled,
+ long int *label, long int totdoc,
+ LEARN_PARM *learn_parm)
+{
+ FILE *predfl;
+ long i;
+ double dist,a_max;
+
+ if(verbosity>=1) {
+ printf("Writing prediction file..."); fflush(stdout);
+ }
+ if ((predfl = fopen (predfile, "w")) == NULL)
+ { perror (predfile); exit (1); }
+ a_max=learn_parm->epsilon_a;
+ for(i=0;i<totdoc;i++) {
+ if((unlabeled[i]) && (a[i]>a_max)) {
+ a_max=a[i];
+ }
+ }
+ for(i=0;i<totdoc;i++) {
+ if(unlabeled[i]) {
+ if((a[i]>(learn_parm->epsilon_a))) {
+ dist=(double)label[i]*(1.0-learn_parm->epsilon_crit-a[i]/(a_max*2.0));
+ }
+ else {
+ dist=(lin[i]-model->b);
+ }
+ if(dist>0) {
+ fprintf(predfl,"%.8g:+1 %.8g:-1\n",dist,-dist);
+ }
+ else {
+ fprintf(predfl,"%.8g:-1 %.8g:+1\n",-dist,dist);
+ }
+ }
+ }
+ fclose(predfl);
+ if(verbosity>=1) {
+ printf("done\n");
+ }
+}
+
+void write_alphas(char *alphafile, double *a,
+ long int *label, long int totdoc)
+{
+ FILE *alphafl;
+ long i;
+
+ if(verbosity>=1) {
+ printf("Writing alpha file..."); fflush(stdout);
+ }
+ if ((alphafl = fopen (alphafile, "w")) == NULL)
+ { perror (alphafile); exit (1); }
+ for(i=0;i<totdoc;i++) {
+ fprintf(alphafl,"%.18g\n",a[i]*(double)label[i]);
+ }
+ fclose(alphafl);
+ if(verbosity>=1) {
+ printf("done\n");
+ }
+}
+
diff --git a/trunk/svm_light/build/svm_light-tar/svm_learn.h b/trunk/svm_light/build/svm_light-tar/svm_learn.h
new file mode 100755
index 00000000..8a1edf7b
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_learn.h
@@ -0,0 +1,173 @@
+/***********************************************************************/
+/* */
+/* svm_learn.h */
+/* */
+/* Declarations for learning module of Support Vector Machine. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/***********************************************************************/
+
+#ifndef SVM_LEARN
+#define SVM_LEARN
+
+void svm_learn_classification_extend(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *, int *, double *);
+void svm_learn_classification(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *);
+void svm_learn_regression(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
+void svm_learn_ranking(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
+void svm_learn_optimization(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *);
+long optimize_to_convergence(DOC **, long *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
+ MODEL *, long *, long *, double *,
+ double *, double *,
+ TIMING *, double *, long, long);
+long optimize_to_convergence_sharedslack(DOC **, long *, long, long,
+ LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
+ MODEL *, double *, double *, double *,
+ TIMING *, double *);
+double compute_objective_function(double *, double *, double *, double,
+ long *, long *);
+void clear_index(long *);
+void add_to_index(long *, long);
+long compute_index(long *,long, long *);
+void optimize_svm(DOC **, long *, long *, long *, double, long *, long *,
+ MODEL *,
+ long, long *, long, double *, double *, double *,
+ LEARN_PARM *, CFLOAT *, KERNEL_PARM *, QP *, double *);
+void compute_matrices_for_optimization(DOC **, long *, long *, long *, double,
+ long *,
+ long *, long *, MODEL *, double *,
+ double *, double *, long, long, LEARN_PARM *,
+ CFLOAT *, KERNEL_PARM *, QP *);
+long calculate_svm_model(DOC **, long *, long *, double *, double *,
+ double *, double *, LEARN_PARM *, long *,
+ long *, MODEL *);
+long check_optimality(MODEL *, long *, long *, double *, double *,
+ double *, long,
+ LEARN_PARM *,double *, double, long *, long *, long *,
+ long *, long, KERNEL_PARM *);
+long check_optimality_sharedslack(DOC **docs, MODEL *model, long int *label,
+ double *a, double *lin, double *c, double *slack,
+ double *alphaslack, long int totdoc,
+ LEARN_PARM *learn_parm, double *maxdiff,
+ double epsilon_crit_org, long int *misclassified,
+ long int *active2dnum,
+ long int *last_suboptimal_at,
+ long int iteration, KERNEL_PARM *kernel_parm);
+void compute_shared_slacks(DOC **docs, long int *label, double *a,
+ double *lin, double *c, long int *active2dnum,
+ LEARN_PARM *learn_parm,
+ double *slack, double *alphaslack);
+long identify_inconsistent(double *, long *, long *, long, LEARN_PARM *,
+ long *, long *);
+long identify_misclassified(double *, long *, long *, long,
+ MODEL *, long *, long *);
+long identify_one_misclassified(double *, long *, long *, long,
+ MODEL *, long *, long *);
+long incorporate_unlabeled_examples(MODEL *, long *,long *, long *,
+ double *, double *, long, double *,
+ long *, long *, long, KERNEL_PARM *,
+ LEARN_PARM *);
+void update_linear_component(DOC **, long *, long *, double *, double *,
+ long *, long, long, KERNEL_PARM *,
+ KERNEL_CACHE *, double *,
+ CFLOAT *, double *);
+long select_next_qp_subproblem_grad(long *, long *, double *,
+ double *, double *, long,
+ long, LEARN_PARM *, long *, long *,
+ long *, double *, long *, KERNEL_CACHE *,
+ long, long *, long *);
+long select_next_qp_subproblem_rand(long *, long *, double *,
+ double *, double *, long,
+ long, LEARN_PARM *, long *, long *,
+ long *, double *, long *, KERNEL_CACHE *,
+ long *, long *, long);
+long select_next_qp_slackset(DOC **docs, long int *label, double *a,
+ double *lin, double *slack, double *alphaslack,
+ double *c, LEARN_PARM *learn_parm,
+ long int *active2dnum, double *maxviol);
+void select_top_n(double *, long, long *, long);
+void init_shrink_state(SHRINK_STATE *, long, long);
+void shrink_state_cleanup(SHRINK_STATE *);
+long shrink_problem(DOC **, LEARN_PARM *, SHRINK_STATE *, KERNEL_PARM *,
+ long *, long *, long, long, long, double *, long *);
+void reactivate_inactive_examples(long *, long *, double *, SHRINK_STATE *,
+ double *, double*, long, long, long, LEARN_PARM *,
+ long *, DOC **, KERNEL_PARM *,
+ KERNEL_CACHE *, MODEL *, CFLOAT *,
+ double *, double *);
+
+/* cache kernel evalutations to improve speed */
+KERNEL_CACHE *kernel_cache_init(long, long);
+void kernel_cache_cleanup(KERNEL_CACHE *);
+void get_kernel_row(KERNEL_CACHE *,DOC **, long, long, long *, CFLOAT *,
+ KERNEL_PARM *);
+void cache_kernel_row(KERNEL_CACHE *,DOC **, long, KERNEL_PARM *);
+void cache_multiple_kernel_rows(KERNEL_CACHE *,DOC **, long *, long,
+ KERNEL_PARM *);
+void kernel_cache_shrink(KERNEL_CACHE *,long, long, long *);
+void kernel_cache_reset_lru(KERNEL_CACHE *);
+long kernel_cache_malloc(KERNEL_CACHE *);
+void kernel_cache_free(KERNEL_CACHE *,long);
+long kernel_cache_free_lru(KERNEL_CACHE *);
+CFLOAT *kernel_cache_clean_and_malloc(KERNEL_CACHE *,long);
+long kernel_cache_touch(KERNEL_CACHE *,long);
+long kernel_cache_check(KERNEL_CACHE *,long);
+long kernel_cache_space_available(KERNEL_CACHE *);
+
+void compute_xa_estimates(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *, double *, double *, double *);
+double xa_estimate_error(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *);
+double xa_estimate_recall(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *);
+double xa_estimate_precision(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *);
+void avg_similarity_of_sv_of_one_class(MODEL *, DOC **, double *, long *, KERNEL_PARM *, double *, double *);
+double most_similar_sv_of_same_class(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *);
+double distribute_alpha_t_greedily(long *, long, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
+double distribute_alpha_t_greedily_noindex(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
+void estimate_transduction_quality(MODEL *, long *, long *, long, DOC **, double *);
+double estimate_margin_vcdim(MODEL *, double, double, KERNEL_PARM *);
+double estimate_sphere(MODEL *, KERNEL_PARM *);
+double estimate_r_delta_average(DOC **, long, KERNEL_PARM *);
+double estimate_r_delta(DOC **, long, KERNEL_PARM *);
+double length_of_longest_document_vector(DOC **, long, KERNEL_PARM *);
+
+
+void write_model(char *, MODEL *);
+void write_prediction(char *, MODEL *, double *, double *, long *, long *,
+ long, LEARN_PARM *);
+void write_alphas(char *, double *, long *, long);
+
+typedef struct cache_parm_s {
+ KERNEL_CACHE *kernel_cache;
+ CFLOAT *cache;
+ DOC **docs;
+ long m;
+ KERNEL_PARM *kernel_parm;
+ long offset,stepsize;
+} cache_parm_t;
+
+#endif
diff --git a/trunk/svm_light/build/svm_light-tar/svm_learn_main.c b/trunk/svm_light/build/svm_light-tar/svm_learn_main.c
new file mode 100755
index 00000000..e2a157da
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_learn_main.c
@@ -0,0 +1,397 @@
+/***********************************************************************/
+/* */
+/* svm_learn_main.c */
+/* */
+/* Command line interface to the learning module of the */
+/* Support Vector Machine. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2000 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/***********************************************************************/
+
+
+/* if svm-learn is used out of C++, define it as extern "C" */
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+# include "svm_common.h"
+# include "svm_learn.h"
+
+#ifdef __cplusplus
+}
+#endif
+
+char docfile[200]; /* file with training examples */
+char modelfile[200]; /* file for resulting classifier */
+char restartfile[200]; /* file with initial alphas */
+
+void read_input_parameters(int, char **, char *, char *, char *, long *,
+ LEARN_PARM *, KERNEL_PARM *);
+void wait_any_key();
+void print_help();
+
+
+
+int main (int argc, char* argv[])
+{
+ DOC **docs; /* training examples */
+ long totwords,totdoc,i;
+ double *target;
+ double *alpha_in=NULL;
+ KERNEL_CACHE *kernel_cache;
+ LEARN_PARM learn_parm;
+ KERNEL_PARM kernel_parm;
+ MODEL *model=(MODEL *)my_malloc(sizeof(MODEL));
+
+ read_input_parameters(argc,argv,docfile,modelfile,restartfile,&verbosity,
+ &learn_parm,&kernel_parm);
+ read_documents(docfile,&docs,&target,&totwords,&totdoc);
+ if(restartfile[0]) alpha_in=read_alphas(restartfile,totdoc);
+
+ if(kernel_parm.kernel_type == LINEAR) { /* don't need the cache */
+ kernel_cache=NULL;
+ }
+ else {
+ /* Always get a new kernel cache. It is not possible to use the
+ same cache for two different training runs */
+ kernel_cache=kernel_cache_init(totdoc,learn_parm.kernel_cache_size);
+ }
+
+ if(learn_parm.type == CLASSIFICATION) {
+ svm_learn_classification(docs,target,totdoc,totwords,&learn_parm,
+ &kernel_parm,kernel_cache,model,alpha_in);
+ }
+ else if(learn_parm.type == REGRESSION) {
+ svm_learn_regression(docs,target,totdoc,totwords,&learn_parm,
+ &kernel_parm,&kernel_cache,model);
+ }
+ else if(learn_parm.type == RANKING) {
+ svm_learn_ranking(docs,target,totdoc,totwords,&learn_parm,
+ &kernel_parm,&kernel_cache,model);
+ }
+ else if(learn_parm.type == OPTIMIZATION) {
+ svm_learn_optimization(docs,target,totdoc,totwords,&learn_parm,
+ &kernel_parm,kernel_cache,model,alpha_in);
+ }
+
+ if(kernel_cache) {
+ /* Free the memory used for the cache. */
+ kernel_cache_cleanup(kernel_cache);
+ }
+
+ /* Warning: The model contains references to the original data 'docs'.
+ If you want to free the original data, and only keep the model, you
+ have to make a deep copy of 'model'. */
+ /* deep_copy_of_model=copy_model(model); */
+ write_model(modelfile,model);
+
+ free(alpha_in);
+ free_model(model,0);
+ for(i=0;i<totdoc;i++)
+ free_example(docs[i],1);
+ free(docs);
+ free(target);
+
+ return(0);
+}
+
+/*---------------------------------------------------------------------------*/
+
+void read_input_parameters(int argc,char *argv[],char *docfile,char *modelfile,
+ char *restartfile,long *verbosity,
+ LEARN_PARM *learn_parm,KERNEL_PARM *kernel_parm)
+{
+ long i;
+ char type[100];
+
+ /* set default */
+ strcpy (modelfile, "svm_model");
+ strcpy (learn_parm->predfile, "trans_predictions");
+ strcpy (learn_parm->alphafile, "");
+ strcpy (restartfile, "");
+ (*verbosity)=1;
+ learn_parm->biased_hyperplane=1;
+ learn_parm->sharedslack=0;
+ learn_parm->remove_inconsistent=0;
+ learn_parm->skip_final_opt_check=0;
+ learn_parm->svm_maxqpsize=10;
+ learn_parm->svm_newvarsinqp=0;
+ learn_parm->svm_iter_to_shrink=-9999;
+ learn_parm->maxiter=100000;
+ learn_parm->kernel_cache_size=40;
+ learn_parm->svm_c=0.0;
+ learn_parm->eps=0.1;
+ learn_parm->transduction_posratio=-1.0;
+ learn_parm->svm_costratio=1.0;
+ learn_parm->svm_costratio_unlab=1.0;
+ learn_parm->svm_unlabbound=1E-5;
+ learn_parm->epsilon_crit=0.001;
+ learn_parm->epsilon_a=1E-15;
+ learn_parm->compute_loo=0;
+ learn_parm->rho=1.0;
+ learn_parm->xa_depth=0;
+ kernel_parm->kernel_type=0;
+ kernel_parm->poly_degree=3;
+ kernel_parm->rbf_gamma=1.0;
+ kernel_parm->coef_lin=1;
+ kernel_parm->coef_const=1;
+ strcpy(kernel_parm->custom,"empty");
+ strcpy(type,"c");
+
+ for(i=1;(i<argc) && ((argv[i])[0] == '-');i++) {
+ switch ((argv[i])[1])
+ {
+ case '?': print_help(); exit(0);
+ case 'z': i++; strcpy(type,argv[i]); break;
+ case 'v': i++; (*verbosity)=atol(argv[i]); break;
+ case 'b': i++; learn_parm->biased_hyperplane=atol(argv[i]); break;
+ case 'i': i++; learn_parm->remove_inconsistent=atol(argv[i]); break;
+ case 'f': i++; learn_parm->skip_final_opt_check=!atol(argv[i]); break;
+ case 'q': i++; learn_parm->svm_maxqpsize=atol(argv[i]); break;
+ case 'n': i++; learn_parm->svm_newvarsinqp=atol(argv[i]); break;
+ case '#': i++; learn_parm->maxiter=atol(argv[i]); break;
+ case 'h': i++; learn_parm->svm_iter_to_shrink=atol(argv[i]); break;
+ case 'm': i++; learn_parm->kernel_cache_size=atol(argv[i]); break;
+ case 'c': i++; learn_parm->svm_c=atof(argv[i]); break;
+ case 'w': i++; learn_parm->eps=atof(argv[i]); break;
+ case 'p': i++; learn_parm->transduction_posratio=atof(argv[i]); break;
+ case 'j': i++; learn_parm->svm_costratio=atof(argv[i]); break;
+ case 'e': i++; learn_parm->epsilon_crit=atof(argv[i]); break;
+ case 'o': i++; learn_parm->rho=atof(argv[i]); break;
+ case 'k': i++; learn_parm->xa_depth=atol(argv[i]); break;
+ case 'x': i++; learn_parm->compute_loo=atol(argv[i]); break;
+ case 't': i++; kernel_parm->kernel_type=atol(argv[i]); break;
+ case 'd': i++; kernel_parm->poly_degree=atol(argv[i]); break;
+ case 'g': i++; kernel_parm->rbf_gamma=atof(argv[i]); break;
+ case 's': i++; kernel_parm->coef_lin=atof(argv[i]); break;
+ case 'r': i++; kernel_parm->coef_const=atof(argv[i]); break;
+ case 'u': i++; strcpy(kernel_parm->custom,argv[i]); break;
+ case 'l': i++; strcpy(learn_parm->predfile,argv[i]); break;
+ case 'a': i++; strcpy(learn_parm->alphafile,argv[i]); break;
+ case 'y': i++; strcpy(restartfile,argv[i]); break;
+ default: printf("\nUnrecognized option %s!\n\n",argv[i]);
+ print_help();
+ exit(0);
+ }
+ }
+ if(i>=argc) {
+ printf("\nNot enough input parameters!\n\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ strcpy (docfile, argv[i]);
+ if((i+1)<argc) {
+ strcpy (modelfile, argv[i+1]);
+ }
+ if(learn_parm->svm_iter_to_shrink == -9999) {
+ if(kernel_parm->kernel_type == LINEAR)
+ learn_parm->svm_iter_to_shrink=2;
+ else
+ learn_parm->svm_iter_to_shrink=100;
+ }
+ if(strcmp(type,"c")==0) {
+ learn_parm->type=CLASSIFICATION;
+ }
+ else if(strcmp(type,"r")==0) {
+ learn_parm->type=REGRESSION;
+ }
+ else if(strcmp(type,"p")==0) {
+ learn_parm->type=RANKING;
+ }
+ else if(strcmp(type,"o")==0) {
+ learn_parm->type=OPTIMIZATION;
+ }
+ else if(strcmp(type,"s")==0) {
+ learn_parm->type=OPTIMIZATION;
+ learn_parm->sharedslack=1;
+ }
+ else {
+ printf("\nUnknown type '%s': Valid types are 'c' (classification), 'r' regession, and 'p' preference ranking.\n",type);
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if((learn_parm->skip_final_opt_check)
+ && (kernel_parm->kernel_type == LINEAR)) {
+ printf("\nIt does not make sense to skip the final optimality check for linear kernels.\n\n");
+ learn_parm->skip_final_opt_check=0;
+ }
+ if((learn_parm->skip_final_opt_check)
+ && (learn_parm->remove_inconsistent)) {
+ printf("\nIt is necessary to do the final optimality check when removing inconsistent \nexamples.\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if((learn_parm->svm_maxqpsize<2)) {
+ printf("\nMaximum size of QP-subproblems not in valid range: %ld [2..]\n",learn_parm->svm_maxqpsize);
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if((learn_parm->svm_maxqpsize<learn_parm->svm_newvarsinqp)) {
+ printf("\nMaximum size of QP-subproblems [%ld] must be larger than the number of\n",learn_parm->svm_maxqpsize);
+ printf("new variables [%ld] entering the working set in each iteration.\n",learn_parm->svm_newvarsinqp);
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if(learn_parm->svm_iter_to_shrink<1) {
+ printf("\nMaximum number of iterations for shrinking not in valid range: %ld [1,..]\n",learn_parm->svm_iter_to_shrink);
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if(learn_parm->svm_c<0) {
+ printf("\nThe C parameter must be greater than zero!\n\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if(learn_parm->transduction_posratio>1) {
+ printf("\nThe fraction of unlabeled examples to classify as positives must\n");
+ printf("be less than 1.0 !!!\n\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if(learn_parm->svm_costratio<=0) {
+ printf("\nThe COSTRATIO parameter must be greater than zero!\n\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if(learn_parm->epsilon_crit<=0) {
+ printf("\nThe epsilon parameter must be greater than zero!\n\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if(learn_parm->rho<0) {
+ printf("\nThe parameter rho for xi/alpha-estimates and leave-one-out pruning must\n");
+ printf("be greater than zero (typically 1.0 or 2.0, see T. Joachims, Estimating the\n");
+ printf("Generalization Performance of an SVM Efficiently, ICML, 2000.)!\n\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+ if((learn_parm->xa_depth<0) || (learn_parm->xa_depth>100)) {
+ printf("\nThe parameter depth for ext. xi/alpha-estimates must be in [0..100] (zero\n");
+ printf("for switching to the conventional xa/estimates described in T. Joachims,\n");
+ printf("Estimating the Generalization Performance of an SVM Efficiently, ICML, 2000.)\n");
+ wait_any_key();
+ print_help();
+ exit(0);
+ }
+}
+
+void wait_any_key()
+{
+ printf("\n(more)\n");
+ (void)getc(stdin);
+}
+
+void print_help()
+{
+ printf("\nSVM-light %s: Support Vector Machine, learning module %s\n",VERSION,VERSION_DATE);
+ copyright_notice();
+ printf(" usage: svm_learn [options] example_file model_file\n\n");
+ printf("Arguments:\n");
+ printf(" example_file-> file with training data\n");
+ printf(" model_file -> file to store learned decision rule in\n");
+
+ printf("General options:\n");
+ printf(" -? -> this help\n");
+ printf(" -v [0..3] -> verbosity level (default 1)\n");
+ printf("Learning options:\n");
+ printf(" -z {c,r,p} -> select between classification (c), regression (r),\n");
+ printf(" and preference ranking (p) (default classification)\n");
+ printf(" -c float -> C: trade-off between training error\n");
+ printf(" and margin (default [avg. x*x]^-1)\n");
+ printf(" -w [0..] -> epsilon width of tube for regression\n");
+ printf(" (default 0.1)\n");
+ printf(" -j float -> Cost: cost-factor, by which training errors on\n");
+ printf(" positive examples outweight errors on negative\n");
+ printf(" examples (default 1) (see [4])\n");
+ printf(" -b [0,1] -> use biased hyperplane (i.e. x*w+b>0) instead\n");
+ printf(" of unbiased hyperplane (i.e. x*w>0) (default 1)\n");
+ printf(" -i [0,1] -> remove inconsistent training examples\n");
+ printf(" and retrain (default 0)\n");
+ printf("Performance estimation options:\n");
+ printf(" -x [0,1] -> compute leave-one-out estimates (default 0)\n");
+ printf(" (see [5])\n");
+ printf(" -o ]0..2] -> value of rho for XiAlpha-estimator and for pruning\n");
+ printf(" leave-one-out computation (default 1.0) (see [2])\n");
+ printf(" -k [0..100] -> search depth for extended XiAlpha-estimator \n");
+ printf(" (default 0)\n");
+ printf("Transduction options (see [3]):\n");
+ printf(" -p [0..1] -> fraction of unlabeled examples to be classified\n");
+ printf(" into the positive class (default is the ratio of\n");
+ printf(" positive and negative examples in the training data)\n");
+ printf("Kernel options:\n");
+ printf(" -t int -> type of kernel function:\n");
+ printf(" 0: linear (default)\n");
+ printf(" 1: polynomial (s a*b+c)^d\n");
+ printf(" 2: radial basis function exp(-gamma ||a-b||^2)\n");
+ printf(" 3: sigmoid tanh(s a*b + c)\n");
+ printf(" 4: user defined kernel from kernel.h\n");
+ printf(" -d int -> parameter d in polynomial kernel\n");
+ printf(" -g float -> parameter gamma in rbf kernel\n");
+ printf(" -s float -> parameter s in sigmoid/poly kernel\n");
+ printf(" -r float -> parameter c in sigmoid/poly kernel\n");
+ printf(" -u string -> parameter of user defined kernel\n");
+ printf("Optimization options (see [1]):\n");
+ printf(" -q [2..] -> maximum size of QP-subproblems (default 10)\n");
+ printf(" -n [2..q] -> number of new variables entering the working set\n");
+ printf(" in each iteration (default n = q). Set n<q to prevent\n");
+ printf(" zig-zagging.\n");
+ printf(" -m [5..] -> size of cache for kernel evaluations in MB (default 40)\n");
+ printf(" The larger the faster...\n");
+ printf(" -e float -> eps: Allow that error for termination criterion\n");
+ printf(" [y [w*x+b] - 1] >= eps (default 0.001)\n");
+ printf(" -y [0,1] -> restart the optimization from alpha values in file\n");
+ printf(" specified by -a option. (default 0)\n");
+ printf(" -h [5..] -> number of iterations a variable needs to be\n");
+ printf(" optimal before considered for shrinking (default 100)\n");
+ printf(" -f [0,1] -> do final optimality check for variables removed\n");
+ printf(" by shrinking. Although this test is usually \n");
+ printf(" positive, there is no guarantee that the optimum\n");
+ printf(" was found if the test is omitted. (default 1)\n");
+ printf(" -y string -> if option is given, reads alphas from file with given\n");
+ printf(" and uses them as starting point. (default 'disabled')\n");
+ printf(" -# int -> terminate optimization, if no progress after this\n");
+ printf(" number of iterations. (default 100000)\n");
+ printf("Output options:\n");
+ printf(" -l string -> file to write predicted labels of unlabeled\n");
+ printf(" examples into after transductive learning\n");
+ printf(" -a string -> write all alphas to this file after learning\n");
+ printf(" (in the same order as in the training set)\n");
+ wait_any_key();
+ printf("\nMore details in:\n");
+ printf("[1] T. Joachims, Making Large-Scale SVM Learning Practical. Advances in\n");
+ printf(" Kernel Methods - Support Vector Learning, B. Sch�lkopf and C. Burges and\n");
+ printf(" A. Smola (ed.), MIT Press, 1999.\n");
+ printf("[2] T. Joachims, Estimating the Generalization performance of an SVM\n");
+ printf(" Efficiently. International Conference on Machine Learning (ICML), 2000.\n");
+ printf("[3] T. Joachims, Transductive Inference for Text Classification using Support\n");
+ printf(" Vector Machines. International Conference on Machine Learning (ICML),\n");
+ printf(" 1999.\n");
+ printf("[4] K. Morik, P. Brockhausen, and T. Joachims, Combining statistical learning\n");
+ printf(" with a knowledge-based approach - A case study in intensive care \n");
+ printf(" monitoring. International Conference on Machine Learning (ICML), 1999.\n");
+ printf("[5] T. Joachims, Learning to Classify Text Using Support Vector\n");
+ printf(" Machines: Methods, Theory, and Algorithms. Dissertation, Kluwer,\n");
+ printf(" 2002.\n\n");
+}
+
+
diff --git a/trunk/svm_light/build/svm_light-tar/svm_loqo.c b/trunk/svm_light/build/svm_light-tar/svm_loqo.c
new file mode 100755
index 00000000..ff31a655
--- /dev/null
+++ b/trunk/svm_light/build/svm_light-tar/svm_loqo.c
@@ -0,0 +1,211 @@
+/***********************************************************************/
+/* */
+/* svm_loqo.c */
+/* */
+/* Interface to the PR_LOQO optimization package for SVM. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 19.07.99 */
+/* */
+/* Copyright (c) 1999 Universitaet Dortmund - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/***********************************************************************/
+
+# include <math.h>
+# include "pr_loqo/pr_loqo.h"
+# include "svm_common.h"
+
+/* Common Block Declarations */
+
+long verbosity;
+
+/* /////////////////////////////////////////////////////////////// */
+
+# define DEF_PRECISION_LINEAR 1E-8
+# define DEF_PRECISION_NONLINEAR 1E-14
+
+double *optimize_qp();
+double *primal=0,*dual=0;
+double init_margin=0.15;
+long init_iter=500,precision_violations=0;
+double model_b;
+double opt_precision=DEF_PRECISION_LINEAR;
+
+/* /////////////////////////////////////////////////////////////// */
+
+void *my_malloc();
+
+double *optimize_qp(qp,epsilon_crit,nx,threshold,learn_parm)
+QP *qp;
+double *epsilon_crit;
+long nx; /* Maximum number of variables in QP */
+double *threshold;
+LEARN_PARM *learn_parm;
+/* start the optimizer and return the optimal values */
+{
+ register long i,j,result;
+ double margin,obj_before,obj_after;
+ double sigdig,dist,epsilon_loqo;
+ int iter;
+
+ if(!primal) { /* allocate memory at first call */
+ primal=(double *)my_malloc(sizeof(double)*nx*3);
+ dual=(double *)my_malloc(sizeof(double)*(nx*2+1));
+ }
+
+ if(verbosity>=4) { /* really verbose */
+ printf("\n\n");
+ for(i=0;i<qp->opt_n;i++) {
+ printf("%f: ",qp->opt_g0[i]);
+ for(j=0;j<qp->opt_n;j++) {
+ printf("%f ",qp->opt_g[i*qp->opt_n+j]);
+ }
+ printf(": a%ld=%.10f < %f",i,qp->opt_xinit[i],qp->opt_up[i]);
+ printf(": y=%f\n",qp->opt_ce[i]);
+ }
+ for(j=0;j<qp->opt_m;j++) {
+ printf("EQ-%ld: %f*a0",j,qp->opt_ce[j]);
+ for(i=1;i<qp->opt_n;i++) {
+ printf(" + %f*a%ld",qp->opt_ce[i],i);
+ }
+ printf(" = %f\n\n",-qp->opt_ce0[0]);
+ }
+}
+
+ obj_before=0; /* calculate objective before optimization */
+ for(i=0;i<qp->opt_n;i++) {
+ obj_before+=(qp->opt_g0[i]*qp->opt_xinit[i]);
+ obj_before+=(0.5*qp->opt_xinit[i]*qp->opt_xinit[i]*qp->opt_g[i*qp->opt_n+i]);
+ for(j=0;j<i;j++) {
+ obj_before+=(qp->opt_xinit[j]*qp->opt_xinit[i]*qp->opt_g[j*qp->opt_n+i]);
+ }
+ }
+
+ result=STILL_RUNNING;
+ qp->opt_ce0[0]*=(-1.0);
+ /* Run pr_loqo. If a run fails, try again with parameters which lead */
+ /* to a slower, but more robust setting. */
+ for(margin=init_margin,iter=init_iter;
+ (margin<=0.9999999) && (result!=OPTIMAL_SOLUTION);) {
+ sigdig=-log10(opt_precision);
+
+ result=pr_loqo((int)qp->opt_n,(int)qp->opt_m,
+ (double *)qp->opt_g0,(double *)qp->opt_g,
+ (double *)qp->opt_ce,(double *)qp->opt_ce0,
+ (double *)qp->opt_low,(double *)qp->opt_up,
+ (double *)primal,(double *)dual,
+ (int)(verbosity-2),
+ (double)sigdig,(int)iter,
+ (double)margin,(double)(qp->opt_up[0])/4.0,(int)0);
+
+ if(isnan(dual[0])) { /* check for choldc problem */
+ if(verbosity>=2) {
+ printf("NOTICE: Restarting PR_LOQO with more conservative parameters.\n");
+ }
+ if(init_margin<0.80) { /* become more conservative in general */
+ init_margin=(4.0*margin+1.0)/5.0;
+ }
+ margin=(margin+1.0)/2.0;
+ (opt_precision)*=10.0; /* reduce precision */
+ if(verbosity>=2) {
+ printf("NOTICE: Reducing precision of PR_LOQO.\n");
+ }
+ }
+ else if(result!=OPTIMAL_SOLUTION) {
+ iter+=2000;
+ init_iter+=10;
+ (opt_precision)*=10.0; /* reduce precision */
+ if(verbosity>=2) {
+ printf("NOTICE: Reducing precision of PR_LOQO due to (%ld).\n",result);
+ }
+ }
+ }
+
+ if(qp->opt_m) /* Thanks to Alex Smola for this hint */
+ model_b=dual[0];
+ else
+ model_b=0;
+
+ /* Check the precision of the alphas. If results of current optimization */
+ /* violate KT-Conditions, relax the epsilon on the bounds on alphas. */
+ epsilon_loqo=1E-10;
+ for(i=0;i<qp->opt_n;i++) {
+ dist=-model_b*qp->opt_ce[i];
+ dist+=(qp->opt_g0[i]+1.0);
+ for(j=0;j<i;j++) {
+ dist+=(primal[j]*qp->opt_g[j*qp->opt_n+i]);
+ }
+ for(j=i;j<qp->opt_n;j++) {
+ dist+=(primal[j]*qp->opt_g[i*qp->opt_n+j]);
+ }
+ /* printf("LOQO: a[%d]=%f, dist=%f, b=%f\n",i,primal[i],dist,dual[0]); */
+ if((primal[i]<(qp->opt_up[i]-epsilon_loqo)) && (dist < (1.0-(*epsilon_crit)))) {
+ epsilon_loqo=(qp->opt_up[i]-primal[i])*2.0;
+ }
+ else if((primal[i]>(0+epsilon_loqo)) && (dist > (1.0+(*epsilon_crit)))) {
+ epsilon_loqo=primal[i]*2.0;
+ }
+ }
+
+ for(i=0;i<qp->opt_n;i++) { /* clip alphas to bounds */
+ if(primal[i]<=(0+epsilon_loqo)) {
+ primal[i]=0;
+ }
+ else if(primal[i]>=(qp->opt_up[i]-epsilon_loqo)) {
+ primal[i]=qp->opt_up[i];
+ }
+ }
+
+ obj_after=0; /* calculate objective after optimization */
+ for(i=0;i<qp->opt_n;i++) {
+ obj_after+=(qp->opt_g0[i]*primal[i]);
+ obj_after+=(0.5*primal[i]*primal[i]*qp->opt_g[i*qp->opt_n+i]);
+ for(j=0;j<i;j++) {
+ obj_after+=(primal[j]*primal[i]*qp->opt_g[j*qp->opt_n+i]);
+ }
+ }
+
+ /* if optimizer returned NAN values, reset and retry with smaller */
+ /* working set. */
+ if(isnan(obj_after) || isnan(model_b)) {
+ for(i=0;i<qp->opt_n;i++) {
+ primal[i]=qp->opt_xinit[i];
+ }
+ model_b=0;
+ if(learn_parm->svm_maxqpsize>2) {
+ learn_parm->svm_maxqpsize--; /* decrease size of qp-subproblems */
+ }
+ }
+
+ if(obj_after >= obj_before) { /* check whether there was progress */
+ (opt_precision)/=100.0;
+ precision_violations++;
+ if(verbosity>=2) {
+ printf("NOTICE: Increasing Precision of PR_LOQO.\n");
+ }
+ }
+
+ if(precision_violations > 500) {
+ (*epsilon_crit)*=10.0;
+ precision_violations=0;
+ if(verbosity>=1) {
+ printf("\nWARNING: Relaxing epsilon on KT-Conditions.\n");
+ }
+ }
+
+ (*threshold)=model_b;
+
+ if(result!=OPTIMAL_SOLUTION) {
+ printf("\nERROR: PR_LOQO did not converge. \n");
+ return(qp->opt_xinit);
+ }
+ else {
+ return(primal);
+ }
+}
+
diff --git a/trunk/svm_light/build/svm_light-tar/unpacked b/trunk/svm_light/build/svm_light-tar/unpacked
new file mode 100644
index 00000000..e69de29b
diff --git a/trunk/svm_light/build/svm_light.tar.gz b/trunk/svm_light/build/svm_light.tar.gz
new file mode 100644
index 0000000000000000000000000000000000000000..8c57097c83079c08b5b70bee20fb4a74ae09d608
GIT binary patch
literal 51026
zcmb2|=3r<j$aiI6eq-~x_?E|~pIM=A{~M&oZ)<4a@!Pb|La|ihwBi1Q0*2$$Z{1zg
zBGF^!6!hi8W4+(`|Lx+-&-a)-dT7yqwr)r0HlA7T{`;5jPQQ`2Jojtcw3&BQ`2Vd~
z&UgObWUD%}Z}aVz`Tyv@^{{f&_U}I!O>A;azRfq0@|SaX|L^i&_BH?76PMU#&bc9&
z%s=V=JGtxJHUDfs{5*I5!`sZYuj9@MFJ2~hI3xDvx^#b=b8lMCPFAtGakqE9m|UN6
zJ$Fv}JG~_14!!ckoLOg@Uo`YS$e&X%|L^=a=G%mBe(|sEO3c~XeB$}M<L7F>ce!tz
zeMc(V-Db<;l!Jd;SdFjoi6zeZ(7`J^{WqWaws|J=?9!em%KUh9<eN?M>d9wvkFVQw
z&-z-$r~c*ry=y-wo;KLE<ow)w+Gd;BmOH0OEZ!--*?>z=x%%J(?V4Yl^EX8vv0V4`
z%-a`}Hb)9<>^Od>Z;s{WznYIPU)d;Z{-M{P_mIM~jVJw@viUSN-&RQFz91v!BXs-g
z%(FJvAJ*|CEJ`>y$+DpD$Dv6LOE0`pW7B)U(#_g0bNyQc+ZBV36G!Im<V%`R#rcr?
zH1o8~H@~K{81SW?+$vl6W_Qu@3*zS|3UB*-kAI!59jj7-j2?SRYLn^Bna6W8O75^+
z=#u=<(wUx;c4^h7;NP}-PZiCxoR71;WahcX+V|ta!e?__w@u!0A$QZYFQ?cZ9^tY0
zFl({TO-=Sy%MDj=Oq6PKoU&p29nU6@vtbujy}7{h@ZA6V)$%RIkIHYSv}>-By&TQG
zOT00Cv(WrmPgl*Vza@F~T!Uvr{^OgQ)764ygS^+TU!T1#+iK&?UwOG)96CYuS$;p?
z1^)l~bLCa($lYGj$Is8ZnPxFp@>r(8M~0_fGFOi-H=g9{&}Y|C$hc>_y5p<|9vAvJ
zIp&)jb;-S~;;QwC-K1F1$MKMb@QT^H3Wat~7Ww+&R_j!TFo~T9mQQf!Ht%DUST{GB
zX#s!!QnM!#3*~N2UvXkVx<$ka#g#k^PEU=hYRfK4@kH&tXg%T2!mD|6`E|{#Hr}|o
z;D6QytJJxQ!fDB}8y`2OZv1DMJ%0<^`ZZd8(h(L;%*is}*{v8Pt}ZWs9k2Yrz?%8=
z>mE0Tw;yD)=gwvPa4qqA(%oyVoXNMY-8`|wVq?{s{tNn64d)839Qrs{Zns2<TgpC$
z^>^*7&0p-XlH54C?)wQTp2*eZTe!O~yF6ZFDp9&danZ+Z#UV>Fcbl@T*?!YCz2uU;
z{8Jr<TTu^;<I1btLl3`FP&n{1CxLfjO~YMF)|R!4wG=MDn<vkxw_pv!!t3&kvl|Q~
z%w7qn^H_#Cx~DMwTWQMh?W^0`!+zVDy_qh(*<t+Zpb$^w^`w@{-+OK|DV<|auf5U0
z%FM{Nq56X4zBGr1l-ILAhq19&a4Yyl?=|b>oOt0#$CXXxe~Tw?RGe_vR_g=H&y<bI
zuWw}aTje|MFc6w1*%T|$boa2}$K|(EZCCTY*v9t$#s#T8Z?|;vGQVDPRZ?N{t-l8u
z7JjK-kfdOGf$z2MsegN}yBe`yn_avhrI+o&n`_z^jGin~D|oz!`ShZUX-nglYF=;*
zQopx1SzNug>{iurzu)e2AD0K|^F(Ykmf^Kh&|ke`Vf%)P_JW4ciFqPN0$*?WdP*v5
z(XrB=@UZhzTXuz-*=)Wg`-kc8f&_(&>lEaCo}RVj;+9eoxW=?nk>$#^e};x4yu7BX
zmYXnMi!<97wC~%hX_9yUO$d3l!Zge9kc1t-u8i%5ssl1cv%+@Q+A%O660~66AUUtu
zv$RTuk@=<S<hMM1Gd4*D9eEtKyxJ~c)f7e6if@jW1yojw6uB0~_ee}ztx|B!vTf-t
z^`H=+o6DwL;?(%Kko9nsd;Y;Q{XARw6mCwmdFjnDsejqW^mdp3!TfK2)jX@J&&crp
zSYMm`XaD^h?LXv`{vEIWI$x@Hxy1kfEO+aV{=fh5reWC)r&kO|4+uQ(*SwI<_HAv;
z*U)X@>)$)h-&icy-BB!75m(^r=-!~1*Ret2O;ZEcq7Bk*jql&8@)+F8y_Pb)FZsYZ
zm3<5%^A{!AM>aj(Y1eAnA)CFwx|FfHm8V<s#F_cma`;mY>BZDb#T@UsU!d-5klook
z_hI4ouUR)zwzkS&dGg3D+HBMQ=`Qs%um0-4xhtJrsZh{#dv>m4;E}X>wUW|z^&6Rv
z>^ZOSM#IH~<Du&6*n|&}+&@KxL{6}(bZE|BGJX1qiJ~E8yRsQ`52&(-99VYSQpPMh
zcJkFdM}Mu9;_=X1W>711b0T+*8N*}dg+>xL`kzmj&hq75g_+C7&C!QF?!0`<XuNF^
z>*})+M|n2APc-?~#D7q4i)0(Kz@KJanYF)+cT_pEMQmd<ip-K?o@4p_5c2_1<<i3k
z_Ol<mX1~*z{|WnTwO*&#;|@_Tsy;?8{xTu=Pja>7g^ax4?~_9=HNHK2gR@_4BKJ$>
zLvE>MwdMz7`ZvXR@QW}^b8MLNb!w?X$)D#vao++TYi?R`L1D(9iK!R1ai7TMIob9q
zSLj~bO{?xik*p`~ZkrnYMb52X?Xseh>HD9VOV+XPRCuat^!~7k2J8C(E@eCBbsK~`
zR{whX_Ui_ffAbquCn+%<X)-7jf49GK3#U?Gy?sY|bK&;?&-`XcE)UaOwr-{mkLm-Z
zhET^;1_l1!0~eZ3=1;KouHMbMq3n>%gd;9iQ#3OogmNY<`Nq;9ASS<zH7)m;o8e3A
zL}kg?Ii0h@XMLJEx5{(piF+~E<wTbRuqaH~_QR!yv9j*W0nS9Jc?oNk6L)++di3Oq
zm!~VTCvzJo@F&0RxXpR}y8^Fw%&Hf{(@kQ^7jobJdR8HS!u`U2o-5qGO76eD2Yp|`
z^KQTP-T%`MuFQNaAn}GHb-}6()A`*h=Ni}lNPJVHx=3i+ErTb|-OiMz$%{nn=c%z}
zH}731`h8o?!5HQ#r6SvxYIQRw8vIdvIFY}a>81TF{;UOWEo}Ny1=$-?`8Y$}^_It+
z)cGp=M<}_G<Jtu48&9UK2?*i78=;uAPUH3seh1(E5l?$Ww}0JwD|+(3r~6jz+Vfcd
z<;&?8muIiuxcLpweu1cE-@hvb`bDjOs_kMd$sKfnw{XM!BTiQ)1+z=tmPsky&0Ary
zU~{hT<<$L`-o%`;wsd2+EbCLq)YY(D5cZ^D;pEB%!f#*b7k`__b>dl#@~WF#Zf)X~
zmWnp@)LpwlaD!BgHdm;*jN)fe-GVKgpU+45oV^wvQWg3oPV)Sf-|5A=^LISi>l0KG
z^iH(5dEV4*R};@wrAA1$X|Iobbl$J_f7OGFJP-JzAD{btU%mI(<75At-DK^)fB*Kn
zbj^R0Z{O;Ft^W7fcHZ4n+bhfJ4a&4<EB!lPWfZV0|DRXDeF5##rj<pmHi|kjrJI7+
zNdCC<XI@0EP3!-f0C$07avOfli@b0Cx;nn~>UDd`6=eeV+(ceXn`1Op;rf)!h~BLV
zxl0NS=RR`}7byK(7;*7#)0-XQ`)=Pn%ejW}XJh>3zCSNh?tRbmz2<r3<_5M`oBKL%
zzB1g%<~2`Zb6{N`?}~>^2ZTCAlfxBX=sA^^$vzJkHwpM;<hbba&cKcDpIzOa^xOP%
z_>cVdo%<dyozRv0y71~ZuYR6S+m4zjocO9ZarRBVt1Ir$x%%k9VQChQ3aKS09&~BR
z^xC&9HBVm?l)7p;S0`Is(~0}L!?G_(&)>?nd`(cD-nA9AyWKBvXH5QmNL#FAXR_v2
zmZy*9X5WZ-(i(oHRi$Zz$lbeF{Bjh2vF|A`<egI?enm#fKgg&s+ttdo;lZMhs+uj!
zB7}vuhfmTdUC=4aAeCm+cs2Av*364LI)Y!WxSuwaYu${^-EACli)88ywr$(i(xu|a
z<osDLX9wRR&7Ny+FVBc|x0P+t;Hk{ztqKe86Ab)z%<*m5?<1$&EFW}NB;LsUf8y09
zF2UHVw?r+siJyD>iT{xn_X&<p+W;^7Af_FQ?y9COoh=nNRZIB$6_H0L4t^355<IhG
zsbuK4d^y%Lti{g^!<2G1)O}*MUlDC`ls)DB@yk<I@g9B3GW%)O-V(!yC82IjOSm0(
z_UW8gsgw~(Kewaz6yuIvY8EprD+-PTnlbOu+^@N4!s)jTx2HV3du+3cj_&Klrkrvs
zc6-g2@Gi1>(II3P@o~!5jjgNnKFnGv^&xnQVeZu4jl6%}%q`z-A>+U8&50}5Rqh6S
zlAiGPNTsO94RP(pp5Q$-N5m70xOcO5@MU|<JHFiY*#tMu0%wi_;j+|f%@5(Sz85$$
zdSU|Cwxqf6Z`s^XBr##WaN4`iuXE%W5BusHmsGcje+$@~xvZq_&_;%fJN`c4Qp<Lo
zSgZYQ|4Ae3R{tOTK~8EhjOsnoVtJoEudWUASUfNNZ`JnsdY|}i$WB#$csWbzSSAPC
zk~WXipP34jk5qlI{g-OA-ivqI`d>F%YniP-^B5HT%{sa+Y);KajjxRncE>`LR<1IC
z=WpuLXqhzs>}{=;{!bX1cCCEM{OnHi)yaDfax>jn%uu&E?(Dw)!wPzPe*Y1=ce1!!
z@0ZtF)_}epsg|vRtXvAt{9(89ax9}iIX^NhD|jLiG2_PLAI|?KncfPYe!jG_Nj3cF
z@p~nna#OSY7D{j3+Q0knHI6-ty{G+{BT_x-T-uzx(0$KsQY!vQvtD1}@<2aHe4FXU
z<xdpy?|jtxx@U&^c~gdxOT6zy*1kTL8WPre!ca_4@Q(Nfhp3QeON%X}88~n6;J&t^
zxGTK;g3+JTg%Ye46CAGa`LoTv_uBAobMi--2YcO*ssGujuw0?%nX3P>O-n<T{dAq6
z)+_qXqbv6=!<LKIyI7^lc|4puxPHhopV;>91^Z5`a$SMuLW@qB1;0}t@y^)$Izatp
z_%_8WajRmNt=xCQ@I~gw6{g30mp<dRS34wX%~!*9r*+Al$dyZ+kNjZyBX8mJ;j6sU
zx2CsKr_TTXW8z)QZ>rJnSkpf#x@-^E+x(wHqnsflZ;oHh&)5rX?Prr?i@oe$<%jN!
zpL&7s^zya!oW0uG?=Je?O;Jr;_VlRknn#t5!G}tlX3hu`bZ9yCa^LsQX=!!uKQFVi
zh?)8L70booIZ5>gMN*&7w>SN6I^SM=+f@A-Tb4-p3Dh6Fl(LkeVVlPsy`*<nPhN>z
zH|59^_v)vIY99W3xAhkr#}@6HDD|$*r946fo)e_{)i?0_ExkRVR=6T`<5{kY_SfrM
z^FHw}m{uaWa^7|R7uOj?iaMA4i~7YeH;>UVo3*m<Y1y?SJKWz#KcDx-Php*=-4{OH
zw%lo7<}A@Ty4vu~s<Up4;vBpcBCLU%w_TDe<Waa@(sJQ(QfuPM_s8P6xo2H(YWgPX
z;T<^p7Q+?^jnA))x-y*19_StD?M-#=G;(@*IjmwKtIDTr*E+F-Nd=pjq@)zXc0VcC
zXOuqD^>t&~<f~_`ew0i+-g%q5Xu9Lw%=Extr|zU3Uh{sM$sVm+<r`IWxpw$6{W*K)
zbei(*#tm9e)Hh%HHbH$#`|732bu+63o}9LbSz;rxeEV$vv+A4U|GZtr^)uW+>-FyL
zd#4XesAMiWc%r7c-XnH_&|9{!BlpuEWEq_MY9MonM|jh{wM&bdxvnnQ-%{A|+evHh
z?-zm}CnO~I2`w>vn_s!8ZPU-2f46=U+P8pfXP5J=EXVyJx*uNs;=Zx$->VDVE8{lb
z^^|9xqyA=L?~*xhZ+kzMJ|Ajq`buG%Nlfpb+S119tUq4Qu{ji*xqgkbXQVspkNJf>
z(dlMl!eNEEFLng|`tTx9(Er`T^D|9S;%gK)eLu8(TZ@2-VYc9}C%;N-FTKCiU>bev
zbVk6kFBfJz{o>yHPISFdP4m&*k8RdW+nzM`Xw}Zh2<j@2e5AV9!?*NGi2F~=*=P5d
z%$xp*<?_m=vx%|o=Y;e$vyKYsbst@S=D_q0t)`x?&nrTULvBu+c&ANf>$cl3BiA~*
zt&|Hmyv}>~lsmHZ>6Tnd-YHWm74$^>x;|~(b3a0ZD`iH<rfE?*M@v(cf_cR4e@)iT
z@SeGB=iYh#J3rphFSyVwXW3bF;di@CuUn*V`0U@dhh=X)mw$RWHLBZtwNJTd!;46_
zKY8^pJGwolG;{6i@OH`5c(O!vw@dxScdjPPzQ)x;)2~EZz7B6{Jtm&;<K~B7y9D*k
zXDl|$Kinbud`IB=|JxQ_pKYNc$?|gP@-uEH7|w?sn5LP<5-qn+RV+7=Z$==~mVZB#
zPiNlun0dp$Fvl>FH@Cfi^XG+5={t3ncP`wd&9#nu@hXx29jh0f_^Z*kVS&_{YXNoQ
zchCAV{VL{|`YYg&ar34xKFOCJO<JLIvOsrxu4(WUtz(C>`!;(AE1gi*U+23@=x1nj
z{-g<;f7O<4S}>na<ir85g(jbCW|c^D>3Vj)wG>#+SU2Tf@{={n)2?%JE;(}c;(4Jh
z$vnL2Z?zfsE@$UFbbC?$^;)*f)}a1H5g*jAI`Q3fiu87rxU%O6XV&C5w<O-L%aID6
zp!9C%2FIKmiqpzW7$R-1-w3Eb*!0$dGeq#s%$jQo$KuQ)7w_r0q5n_tc)VBq%`KC8
zIeA*2Y0668vOBt}Ti}=ay7qz-5>FS-cKOh?IljiJ*Zq~oS<l5B%DG=xH^tX1iq~fq
z&2*8zdNR0-Ir3iAr>%9i|Ng2R%)NbFYd@C+!xPc<jWt;nd22W6RI)4#)_AEcaL6Mk
zTS&K%yE;b0u9o?i-R!Q{mfw#~Ehv8}<J8ak-f==3ujS=QTtbFP%u|oQTEr#pdimF)
zhv5OPUG3(=D;BKdV{^RwVJg$#txI&=FZ!N!x_YX%kcY+QmcZes8}$S=`MTGOY4x1x
z^PP1wv#RO2jNO{5&i~mQcm2J@=T@ej)$C%KB2u<^zuq<Pt&eZ%O6p{~2k!LVc2YC@
z@tjxvN29jg`?=W4U8pg2?ZWb|ZEXo>vidGXNc#w1=YBU~s)6~*$naxxT&ky<3WV9H
zoSx#A%cr{4ddk&r3{FD(ryt;c6UiFauf8$M?_{a()Vm75rY3IidUb<4QkC%(x5SH?
zccXMCi9blp?s_h;USQ_YX1h|K>opm6bElr&voBCa&AriW)zmG{yG@sC&)$4g=6K_b
z#<a&RnYzyw=vJKjd*RM(##JA_KXm?7>-4;A>$ErGZdJ;Kk@*6GJ@=e!u1UYJam^QC
z*GN6ct~Ng?^BHSd(6x+px~73_VfS*cI0pRk$y$+Pm!tLG%RyDPLQu==37^A>o_q$k
z8=q_$?>5^V{F~42e<b-nkBsNP+l`Z}iuo(NCsuBhDwe-}A$vmk8s(CWd)_G8$;vjY
z%-gsoVAsAcYj*EV^3l1paOtW=K1tIOQr~GWx8DE2sHWOMba4=ewL)#Qw9%B(JQ1y5
z8-jJ#ma9MCD$TELV%BhsDd**V*0oc<i}#sLNZ|O%616%s{|vkL(Z?b)7HVzYe@(^G
zTQp@2Pk-)I{;U^SIe-4j{Sn#z#enT_xOHL)lS<Jo>zylgcOE(Evw50Xe9yUmVG95E
zO81@gUwnO%*$Q#zW{Yb(*55Zd_;}fFQ~$2VcE2^VXMDY7_0MYJ>?xg$9jBCSl2_D9
zJt)32!!$<TG>~0u)ovw*HC`(n;{Pamc~y0Xt)B2mBr&0M_icqQd@TD5p1bXQc>0;;
zUWKRyavdr`aedYa^6Tx>7_RBZ?Rhv^{@;;@bKGMRV%FGf@PF74IJ<7Kp7S#`ceULS
zs@G)MH*cI{#@4yK;)#XWXEQnL+_W~;&KaAwzg_8Vk$RBtfn%?JSm4Qw_!}3OzW%>`
zZ~famWpkm1hksYus{dd3R;J%`mFDD4b3Ju}e_P1;KT?;gPO_eS_xQz6TTV>7BIJ50
z=h7sj*Zcq0)dh+(w0fIIi=S5&G~Re3Z$SV9SF6)Py~F;>p?&TPj%j&$tSS7`koA7e
z(^ETU%~@=5u_mGHNq4fe;mQi-W$yppKaw=qu+DO8=*mgvBE0!8m_=d=UUAt-?UQOt
zZ|{>^FiCKgMCBd<_6h5w?)}Y-zA{n&rP$WDAqM6v-l{P(v@_VPO+5Z5R)XblLdLas
zXS=>y8(;jY?v-;<`j!2BkH2DDA6oGp6aK~Q(zPi&yU^tD`<E8;SEsJ3*q!!F`kuuy
zzNNBf=iFZ<z~r!GR+5YHhnD|*W%{kcp}Q)V@Nn8}jMwj+weq@zb^pQFyZ3+Xmgcy$
zL44<lcKL8gjoq_!*D$bG%WrVg&roH(R{p%e)|EYBicCVqBeB#zlMj*FRwtfBX!suJ
zxD^vN^^nezsQt+wLJoMbo^GjbvApJX`&OL*&%1+@INtx7Gwo}owaKlXxiQ*Hxup!U
zH@AFuP*7MiT|g%8y+ebwqWF@j^+rD}uE@ndYr7yhVRzt9-`<Z(^Pk_G^!H)<X3IWR
zmJfRzK8Id<@p0K&cG0%(+-OJkL-D<8E%nyUFXlV;rCp2o!W@3%b;Rr`zJ?CJOba5X
zJa#z0sIFmE>eR#)L0i}Ar)Su&JuIKPFHGpif}OiLzZ52A-{{Gy=gbur&9-gI-gLU-
z*oT~k#T!H10_6kLb_snD{c^;xAk39h_4t{a3@ct2e=n;2H__nAv5Qw)wwCqD)tfxa
zNaE=ZlW|H2xbU&*S6sO4^;2!hOHQp{6Esa`=MTPwBFDJEfaNwp+W%Efp4-&D_K9Q_
z*A$UrCLiw5y;o%d7<G@yu2Q)=H@YHxVsywaYfqsLsoOO%o2#CNTb#_lqOw169tV$4
z^68psjb;;LqyB$&480{>s<n*IrDt{kr+4Am%AmEv>jGGUbA#B!UpDmqn!fvZ)`Q$j
zCl8rOeV)Abt=y^j6TM%zgnUYgb?D`v8T#<%$4RBVY2S{w@b{K2R5O(ixOe!arsZj`
zh##9H!*$A&CR~qt`0;F_^E=+VWk-#Uf9(}Xo>tCWF#Gkvm2roc)wA^(9{K&COE#v+
zA#S#Am-Cg$iyzN<#K}8t|3f3|E!Bc1C%xCKisg36s9S#TfaR6M9XlRo+8<B*{n~z6
ze(|o>i%uPj;#}32f7~dLap!;+i^0Jp5&ret<O1KVh@KRnuxCnPUQ*Kb`HfGP?(LZ7
z)FJ44!kVioYUk!9+a--RH=fkf%sjiOV!`!w1_FJOU$zBIx%@gt&xE^CU+T7OjxtLs
zztpp!O|KiWq>HW?XmjORb>GT0Fxqi#!troX*ZkyUcTYP{EA@!_oa~UGt#2#XkNleU
z!>0b|vPH-D{bF0YX~Cwm>5G?Iwe4IIAr)0KX+l=0yw>e?Os7w|{j<DeCJ}78qh<d$
zEeGL{xtAEvg&aKEP|Wusr8p$x@T311ZYOiMZFXJgm!9%WNS`}=PgCp7*O4c?+a&Vy
zOw0G?t<agZO@ZU%ZA*jO$J^>V)0IEkPQJf2LvLPWW$d=K{g=LIZ{j@o`uwq-cfSgW
ztKHqt!C%<zf5lqnZ9uGeLCKZWGWkN@_{aSFu8H6I%KTmC;L`8krx$!ud(ZUk<G#|%
zY36TN#G6?s+?Eb_emL*u$=5fHmNy48E;GzJeeZnX!#nEX3Livux(~0su_gaPtMvAL
zE8c(p*jE|)^4lNpqLOb{vTwy+EUumAYyL_3pLo$5U!l|c+cvj;nS8D8-I^+uxlK=w
z=*(o6lHj$D?qPf$eA$x8vO(Ya*GZ}8`^wU9m+I#{6WLWOs_(l!Xse@^?uN&WdiUR!
zZ(Yw{J%Q)MquLWHceO6f`!!#V;r!7fwRH=obxo7$Ie&7QS)2QQg_QMS;hnj1?74FB
z%g-i1d~Vbf?>AfHOu&8X=3H-~Ul%$*I#2%l=z~H0j$?P-WZ%B=2>i|;Gmm+FLb>=g
zrador{Nvz{`g`x&V!l6%s~<63UNnKb&%4T>-OqP}Ro>3>`C|6R6Fyv1{C7?9pSRVK
z|4;6{-M;P>1np-FFTGQj_xDo0VBO2`kFxu_`YWae?=U>{yR&wiZGKK7cg5v<H|8JB
zh(D>kbE3CVMDxz3#0OrVzNhEMuXesR`APn{jq_S#8xL?8y?bzQ?;M8$jh8kC^XB@#
z=LnxxDn@2qI&ilFM~Mf#pg)_0Z1f9n1e8~IpD=vU*NUo~jxkM@t6Ej9i9zWW2(
z)s}W9dl*M-->1C4?Eb|0hwGyB*Xx&vu78?m@M)<tr<SoJ)AHTVjAfTZaQ?TP?SF2W
zx4>n~JsZ#MS(=_bbN;#X8OOZ)*W1}#GY&3}d|2#uR$^^JCC{CyTb=p0sWMxp)p~v3
z@w%1c^FqEedk<~gq1Eu;+{~w=P%(=~&*tn`w)uRQ=WS4GNZ)VwneF}*g~JPE0<D=U
z!qdGcWVF?5Rx_;&%?%F7_EAu{Gbgt3<qP4+*2&66A^Lmx<(s>niG2Rl<jdZBckR)}
zH01-XcO*Xk?duTAmtFZHIB{;mTY-Cf>OZzHYTZjqt$1F1V%ApIIF6nG)`eOxQySyX
z1Rd0ov54l@Zunwh%cy31zRR^$u^}$qB|~$mqetS_uIdlYd(vZ<WXVoV^|R7kR>RO6
zyRiD3e4I`F|7W?E0+&zUyrr07%AwuNiw_1xuC?dcV<RUr`|sT3zrSvL|C%8gd-Hhc
zz8xCJni=nN%~n@2pH<4rbbD@NZ2Bq<Yipydg@3fS=3V=n>g5&`^@+7%!}O^uN}?83
zFP8hVV_uhfRzN;$g2RIs55Jgj7N<wIRoN6be+^GqBy{#u>MMt}lV{J0s!wxtmOS^i
z|AkJ}qZuqwmwkip*=5_`aLW##@K$!wjnd3RQp?Q)W*S*Pl>A#DbVFs%0$-*C#jhn^
zR=4D*Ep?TBBN)_d5~aRiaa%$A!H2=8vlu2GY+E|PG<U9Spr7rby5K1h&ySke$G`Gc
ztK#7{W!k~P;Oxj8$+S$ILsIJI&NC+xQu7`g|MULBxAoVT8Jv>yM834F5RsF)+$>xa
zY~aWC&&Gc5+~@HhY|7UgT@1{V?e!MlkZ8B@kGJ%PBj0QPZ(^Bzz@cyB)sp=ViytYw
z{^|ayGTUj@7M5qBbJr|ie8*#hiCWOH<+GflCzmrT%kxC(7`FW8-1p#eVJerF+J-5t
zqIY*&`HN{@tbROIYEMvve3Qbx=J_Ve%nijZ&j^YQJg&(VFQ8kn<;u2;`uvl+Z)#c2
zUOPp@K+~_NwrZ|w*M(;f`qckUcwx{peeF@E*uJw5&3sSUge%R93W>HkpwVM`=gUWh
zd28-A><!pB|L*54l2aWVGhcry$~n1d;itm&)&i`1Jf?mLUjL<Zf|<6W;<x>I*;DlM
zBOXaqT)EWNA*rKcByP{Hp=rNF>*B#9+OGv0t@9iv={^1V_VMLkJ09CPgqJI?e9AS=
z-hO)HIsMZT$6vJ?Y}gU{<3m<ih{FMmBg{#6o368+*=%_GiRAS&#;qF6!e^K}!#J|8
z&P{A#D(%wO-1O|PSa#->0O`6*_jbO2AyS!m;J1{n442i>xLf6-g(Vx;&M#m{+<pE_
z%=>xY`4-LCA#|r~;j1T1J|$h6>wg@66l~}ExcJ@nDrZKUu01N}<&N(<B(Ze*t@^Xu
zn2){m|H1Ws%M7)>Ymc9de6DlTXP$QC*OCa8^H=}>FO1{i)(Otj-9D-K>x#*94m!SE
z5psX`E(WoKUsf-^*>q`EU$4~m-{(`>I?gT=)pHSgz2nn+jcEy+JgZJ_J*g_aWZD{U
z9m(@*H#Md|S^X#BrfpNFZnt69$|p5p8tnZ!f1l`nSRlo*eboV}zxTyY39Y>Lo=ZGF
z%!%dupPF?`JbwJmpP^^uBk=R|S!PZ)&!x94{JILG>Vj;p6+RK#sVHl2(0R&td906h
z2Y+_bM{BX&X==xAFKORyC%4~6zF%9#cF&^X<5%~3*3DYdzFkjtyPoWSIX&4O>+e|Q
z|52J_el4@Gmxq6%Mv_*NZqkpNoYh8_4_`+*G3Et7xaVcTC|McQ!^JV5Eq&(1MN<n~
zP4et>uI~TP=g=z6nyf3K`XW~~Ughh<TO#eRG}x^+9O>badGq(*i?Bz0`l9oU%^$yW
zstB!KR1wK#e?08WM5~mZz>-{N{;Qr%a;iUi&MB-GGICuJ`8c_i=WoPJXKp@uZN6$J
zMU}Tlch6>g-1m~P`+LcKbN78$cl~Z^5~&TJQXyAz(fO%&<8$UOZ|2Xv^}x+)H4p2z
zv*){0Pv3Ck_VyC{nRofy-DPig``#{}z3sjD#f!JM)NarGJ;(R)rOe+3a%nm@XKj2L
zwz;b5_U%Nw&_&-=>Wl?>FYZ0ooDuuWQgy!ZwO!TUSI%gDS$pJ?jzRJwPUAgO_XK;-
zlF5E~&q?=Zvvu}d-}-l74#eNe-xjqa*(v&Ugtf?2CBJQl6139J39_;K{h1g!-E^Iu
zoPpTSQ#+P9t$z@=GxL4jG`Xv7_WN??Ydfv`b)<CmpLf>||Ae6UdxvkXGF|t)<JFFZ
z$L0oHS7FP1)!y|lx72Rglf+wh>Zi=gf8+AY^3riH_Dj-*tbcXNR(L&~d~Z!1n`ryq
z2)=Dwm+fkgifw+iE%#C8g11d`&n7+CzwcY8z(bRu`w==zn2z7cjhAhcJ=<9Oo=<bm
zVVk@2WP@uSJUwQZaq_v1S5*ziy$KIIZ~Ak`JbEA@rF!}4zT6Wm3wa`3kH(74@R&T;
zsb!s(`=Y)b9i}hx*jH)%Rl3>RqTsQs^dak_zXEw-6V)DF5Yf4teV^$|(et$QGizlR
zSLpma^>s%*^RW=&goSENO;=-Dw=UnDDK30B!TDN5N3)s3h4N6ZC2Es-cL=BQB&~b=
zqh4D1@v@|pnDj5}rHmf3F{#Cv$23hlvS|4QY3?Zx+&l{M<E1qIys(j4^?QrbjqvXW
z?FDZ>6`vxZD5kVPX_iCilLqgn)($^cc^y>BZSK9Q@44uzCflUdDUu#ik!;szvE2^p
zON~8#@%aw6BZgD%9{BudXXv+%tYe>UNclG#B-L3QKD4dj-pey$*P<3mL|LUytKGC9
z$F*^1@#YQeH^c)a>ZkM1so~OGny1aDv2|veRaPvQ>b}WG%(9qkT|Yn1zG;`fb7Sql
zqGjhhH`LZKFq`c>kiGhr3D37R@9O?AaBK?oJmi1CZD!DufNNHXGh_^>uj?vM==SQW
zPg2jU+%jXX??HW*HLF)%n6&lZrd^Q|{xVjHzcU@>*4_L%xgr1X5z)))YLk}kd*8HA
zPH$7;!|iK2xOFWiNo}s%R9ASiS^So;*@?Cbmd}r_v?{36N}Jr1uP|x<p7%|D&AdV>
zwQ)WE2e!D)&21`~m3V0Ww5mlc9@lp^h<y;g_F}5pOrA5bmtOJTxTaA#A&0*&ZHmx^
z^OFs&W=;JmvM3?WVOGzV9};H{TrG=V_if^OZAHuIWtSxdFZQi`$r|o0s?g9P-udc^
z(LM>G7mnw%CgkQ`-xAX?HM9LhQ2eut`q%eJ=dBL0U+KZVYdzb!edVhS%2`^y_BH(3
z`_ujBp2@sdPuw_ldfuVLo9*@69?oz7a9;VxbHhKMt+%aFl3OF2wQ<q1D;JMuC~YeB
z;F`wk?aTjcy~mN$wOa*doYGn1V%K(WiAdnFTQ#rkRw^=XNc8KIyg8#pE@K<x)^&-C
z<YpXX_q95uc;>g_qccJs`|IY{%(1o<iWRu9Eox%&f`x)HZmW*gWUV>yr%)zj<>fM;
zX9=ONyrx%$PGG;SCO<pn19R=`@}H-VotL?woYU|7X8Xpy)9!t~&73>$=8+Y1#hyJC
z$yW5=5mS3KUT<Z;a^eh)pP!~(JR_<%(~Y6xplHsq^;y?dByWmtnc5T_xA5EXpJG||
zpVDO4ee)<-_*JU0SW7len0cR6ZpWiUV;*TIYxmTryi6?uO6F`iru!Kqu5b92oafxc
z_`2tjVCvnsm+LviUc~%fQ0gupyM^P(t5W5(5Bd4qdFJ!|TVQ`>);-_e_6c|8RyDV4
zm_^Td#;pB#!cR$qZ%0pcx<0a0X`I|N>)p{)xz4l7VvZh~Ib*l*EcqR?mY?IexpU95
z4)+gB_wLl{Sieg7?7Y@>S7si)u=RdNHuHBa=Xp`Pc87Sqp3U<7vYnF{PkTejQHOvf
zIue^wc3)ez@Ky7oZ!xlBC!cTxGat59VLNWaRO$4>rX~6pU$FYi`MiZ&%XwCAXu8rf
z-<e%%<?2hfqCT@6HGRMD$^?g--&6#T$z`wUFI}>11?%L{4_BiM!yl|v`SA6b82@6)
z8TTK0ay-$Qm-I#A#x1X`Vgu<PrgEi?q3fScOiPWqs@Q+K{9S8b|G~az6$+kT4}bg^
zR~>F^Z)X-}>Tzw;_IbX%#m$fR-gUfS+kBW=S~B?JizT}jY}~iz<*IGvtn%*doigvY
ze*K&*ucRUhYa!KK#UcsFO4>^2kFaPjW!717J2j!r9T^EUMEvV9uz%s%g=?d$t3
zkC#nf=M=n7re1sZo1BBT_gs(8`KkQi>yEzqNSCD9tiM;e9A19-C*RbPwRsaa)G_8R
zwEfn<`IxYogh;L#&+{8S39SnsZ@T%`J%5dK(w!2ws$@HP7iMm;qzAWMbf3zvtn*#J
z_VGK(xP^;6Enb%~@r!Ug{dRHl)Pz4~PP@(C*u`Z%mA^gp`uuNPJz~lKE;cNiVxA`O
zaJru6@ekiW+}zlIH;`umla?Bf!1@<|lFKg??MhvA^kn4&%^L+_({-05oG2?}so4MT
z`HMBXs;#r<R+#r+++57)sW4$e<3a0eb?M$I2Ra?gudb|`xq9uc7`HFA8dq+-)qDB<
zNgL~QyLH#H+QXfuD09`d+ibiQzdJk4*Ra`LkiW_5J)dp=w&x4fuKD>EiSUVS4pwBy
zVfnl8moo>0#UBgyi~VbNwHt)!W`@1Lc|ZF%$9+kM<!d|p15y}nw3IHc`z=tmj(^+j
zso(xRn&hg*<67wMeWI#m%2lRym!0Cnm|Zn`BX6h2F_-(8RtvCR>njTS9clgL>s5VA
zLC?1?C3nwlyT0w;(Phi0ADYv#s;uh8c6G4>MKc?9)|q|Kv9vzqZ4_rOxr=q4qeEV)
zmgH(z<uE~$gNCYCWzM*%KiJ42&h#RD#^M+8YL7*a?GDO#-kmhXcY&CUz1wP6Gp!e8
zT+^O&C>>i-ctj$Qd-L)2>Y@&B!d<oOm2+J*o#!Pvy<GqB;|sl8buYXFn0TIXOq*|R
z8C2muyRKkMr~JR3KkloVE?-TFY*6j^DyOadF8SPsk4J9K?2+sWdAKvSl;v{MN7--#
zGckrPqepQu=e9I+TKZ4*XYBObDmIb#iLCJC-RUc*OQf!OyyoN7Tg&!;(&v(z<09|Y
zzOXTR?winQi<pkRJ$bhJTIkn@fm`^$9eZ0;S8-?hM7g)GO5c@)_qBgKwffMH!lO!@
zi{4N4$<&K6{PN&mq2KjeYE||ML92Kj=kD2J(4i%}W98o|uQ!xWo&NA@6?^g043Y3<
zUl-=>6&2E&Cs0xHcyWeZ<1Ft_%gqzRqm6H5{#m!>;HrK9t+%{0vgj^OwiVv|{Pv=6
zHLDLE-O@XMb^kRR$%C9%k8v5Lhiab+x03p+Hm#Ot$y*20or3%)HYh5ox}0CWOgrj(
z&$Y$Q*A{C@C2rnh`ny==O<~fZ#Xsk0{XMl;Z@a0M`Q;O$`&KO7?tcGn#ocQ={=`n1
z`D5V@58sn=%CnnO_wRmlRb163<l@_Ro8sd|s+Mrsz0uqLnp<dgn5%s0bpF@fkEX1g
z)W7?*`&ZS%ZJ{Ucmrn1meZ*EOv&Zf4<G^)0x;{Mi;!F1~wTbQZQ%T<_zT;$YrLp3%
zn0w(j9$8PkUUBl_t*8?jOy552p1oyH*6c~Pji%f!En7Wjp4i5=R`Ni4y4B+7AA5BE
zd#~}Tu1{JXuwF<#q)FZ|{cu)+@4Q>vyX@y5_W1X-_WMrL#fcB4i!W!%yi<9<Gd1+y
zv*n`3i`Ryyd`c|rWm#TW*tp^L=1=1LvJ-62J+BIwY-*rU&?Z*U8L`GZh(Dus)#f-}
zd7desrGp~<76#aLKlGoM{b}o)9zKVE(++*~bTAhSe%GxW>GI_2ltu^RE1ZHgvTL^I
zwBEUFc$i02$l!-t+onHjU)@Q3wO~oGX0f1l`4YVqOPuZ4x&zlv+OK&1AhS}-hcCx{
zqa^Pi*(;vQl>Kg>gz2r+^P8T&$gmM!xqRK}q!S;4^c|1J_e@Z{W#C=Fn=c?^xGv1~
zyu|{W@1M3$N)FyUTTk><>@)7Q`;T3edXOBpU~3ewc&yO{wU0^1j!wF5;3&Ri&(n`P
zS1I1z%6z{sKGRanpK)f)qNNWM!X}o)PODbPSu;sx&aZ|&Z}x?=e#&e({wt5&t$OS6
z7XeERZm5d?F1MdB`DECk{RfUO@&2c(d7|;!lqoe=mR|0(+`Y8$zr5jOrS`N~jg@TS
zs~;|tI=3VFv@EBui178~JLkU6Fo`}Xo;aiMpbAH?0^5N}@;RE^9%U;746CQ!J@Uj+
zVbkvmDZkWN(t{uW<P%8{KUaOdL``VvA%69Y>PvSjf_j2B@A00Ry&}K!($N@;%-Vx@
zUll9mO`Gt2_jae;9?6q&&9l~eWNq7WxaD|N^tD+LoreV@n<70`ww!XFEt-1hwfF<!
z$zt(`B-Y5S(CbK0+{BaaQ+p>^_1CNU+qylathj!zUK+Hgq4CR^aI*pq-p#j4c_T&Q
zoH=ep&6=dUy&?1Pwrls+zB4T8Dv!IK$fJHRblNZH&Ql-Q&c04utCKbN|B(yFZUkHJ
zc(^`o_3LKcP`R~BWG2<PGcM?v&d?U(!ribUlcDnmugagV9~UIJ8k)70_Fet_=)ob)
z>!+BudbaLr$^52$pY!0-2VA=+rg7wlE4*2ebRcpaS9+($>n;0L_VH_f2%UXhv>>k~
zzej}U=_ko86Dw^$R+s&5zq+Va+w7Xu-TWFp_qAoR5tVZUN(81&`tgRRb@Pu$3YvE$
zWoqYqn{Jw8DKNLnN=^LE%{y)zT<v`dXP>m2`_D`vZq?cNKS>u4)G~Q^-S-PPaq7O&
zJsH=f+;8+(EYP=p7@Yh<w)z^kyqueyYu7^A(jOH@*4*;zo(WZc=UTG!#W|;ALhCZu
zx^r}231noxH~Dn<>79vx_M8*G#<?WywWxG?)8DVZkJoX!Uyr_i)ikp@FE;%8&UOE!
z_Id=~**)oVTGreP<vIe-Gkz6U7cQIos9=@FCf)Q^%k~6Y@2oeN<-gCTU$Ju1t3xu{
zZZ&r8Q;z!WQ@eg%A^H5&yAIki)`Ia*{u^xEo;UB?<tt}{zeuEazAj3haP<`LEM;Yl
zOHNHQ&Ocgb+oQ|cd#7sBKb3h)>?_3-9%*cUw+fEFdTKR&=>MuW<MEtt&*lhe&swW-
zcu)7C3ybZZDZll4&1Anw?_tzM@%8fiKWZg1Bo(X^XEo~hD$&mn`TWT*%Xf2XUI*Se
zviL{P&)$sRYs)?Uv05@M?l7G>Ax=hPg4h<TTaikS7iP*tUD^5MW5~^oCl-aOrz)G>
zw^F%prBa{S{v><n?U|o<M1Fb3q1XFimF%Z4C+$8=e)#;M(P#0XSFr~>TGg*V4nOxX
zCZ<|$hxy^#*KR%Ub6eDFFU#P+y07f5S&YGgbwYb4T)7aSrX>B2C+0_j@JVrlNk=k5
zl$U-yW%`6|V(|9A(%oSfSy#N(Xk9!vJ~1{;|9L#$ah|u85<hg~uU)KJym9(ZDXF~e
z&hsN5+n+nXg#TyTw}8?=(YE|W6(Zl2wy#?|Z?>g%fBuU9d2>Df=g#$L*86%nI{Z@n
zEbUAKPuu)SFJg}@yz=;#g5s_@yU+L)pWZV2)0^ZcH#tvQzuoP&F!to(x5sYnm(uV5
z@P0xyo6oxCGw0krc66q9^4|1-rfFXVAK#EMyu*L5af-UdwBM_j-uz@5rQ$j3UFS*u
zs&sQD8%z1ylZ_3Wj91)=wwoyPexmNI{mM74muYvhY1sEIDY{bK;S}fp>GVp$s4FVV
zO)ehKyz(jVYqtA$xA$gSFB)|4yfOUtJXN~1y6UrP|KtC{I^Rr{Z-4&TC_VX+RNOO`
zuU_k(g=}58-%@m6sn!3=Ip^|g&-Sjb6z!W@_bhF8_Il5fb#ISIS1b^YHk6K7%KoeL
z&w2f~wfp9=2JURj+p$L0h;vQ&a@AYjF2OPvp1plN>${m|TtN8hmnN%xZ5ugTKYD$1
zJ2h!-ghYFM(!<)rZ1F`w#@3aoOnYqF74GEq&P{aV+?vH$a`;u0!s@llzD}uou!>jF
ztYE?tZ?pZIw|(5vB4}z{lD;A;W>paX%OjsJOg(GxvDr4b^tHgc&u{*l9u0Qrs}Sb8
zSMh1ZD#cyA*9)ZAJroySw@~Yt;|z(2Usf*-W0dE!{<<}rx3@r=_o128p<I&|(~AO=
zyw)$i-N3P(QSjeYW+jECT`PSjZ(``>v(;ag<aK4of~~5tZJU%Gl(som_U(MPEmNkx
zUe@|aZb9em2SVEqs^&F&-zh2RoPW$PUP}5z?RqC~8AGi-rI-Gj7hhWc;dyKL#XDE(
zxL)tL{a!U_`y{R3*HV9kzcczX`~Q``tgBorm-TIyzVv_1sf`uRYOAIeA1zt8%RO!~
zXXRn7Uwoz|>zbe4U%M-BZr{7U=ldd-xHe9HwEOi#=S_!IW7B1=Zi!vb_}+5YPGXOz
zZAIXlMy@p)EnH`=P7!zGRJ+pp>vo!VZ*KVQ<F73i%KG@;b6i`Q|GMz_$*l~NQ+wtJ
zJM#9W@vnS%d5whiwUb864SxLm^~+@2M0N8!LcUWzU;a61T}vpd^_?G=Zxqz{`4r!*
z;92+T;x`t-gK`QPOA=Ri{}Hgb-t_QBW}~J<k49~W6PH@b@ua9XybC;krfgon(fr)E
zcbXTI_Q(6&bc|YNeQsI%r|s6u9CBW5SgxTvd)0NXgve*f@A?;6aZjvze$H9wrOrgN
zNAWy0{z6Amk1HN(o|b#~?7X9Y!<~a}^zJd(I4MU?m;3)j?%9kvS<bF{>u&}r{ty&u
zEuMNyr+xeUyHTHJ{;4sE>=pHnKI7N^^SI)@zmjZe>y!Uh)!0fukJ#wJJaGo+wspn(
z6X$C`YvEr}$D9@|o}u_*qi^;iy+2=nFZo>fZu^@YOA~`8xBWAB=B?elGXL<-)amg`
z*XNd0{Y&wCSH(Iv?X;`msnZJ=EnJwRShrPWjrQapZ`h{4+0-@1Ej=n?x5`(AnAYW*
zSL#_-Y4~^jw^)Da$#FlW{P4>wFMeyBH|uIu>2vAF`b93+%vaZ*XK?5JaX@Eff3fPs
zB@-jf%Dum)T?}}%TFhJK_bZFzJTqn1e)Kx~>c&-#=_kFimSx#5$gpHm@H*01a`DA+
zMyAVQM$BLTMg~5c-mrDP$kMxqj<+n?x95nQz{X#9*L_=WaN%#|XQeNe(-V&fbvDTC
z<0$_&Px1Rb2j6LX*_-n^HVf~qw#xWwmaLR~Ono-Tl>?K`{8}w=q2r>>y<@*8?3$jl
zL-2xtrR~Z2vKLcyH%AEHJQn0$a$iCHkoOz0={Iy9^)|~+-`;N`ynS*3Gv~H>uX+zH
zDth^Lk*w%izpgJ&B$yiBSiF}=UmF(^G)v4=OX4Bpdi6)eFYi9Lczi%WH2L!7d0PSk
zIajIjnS4l`Bd?{$*ncTyW4(dR89)EcPwqLc%22asIL!B(`FZf)JK4<nzN<wRzU%&(
zQ)IX#?2h;{)9)Me%sz?SHdp`6k(~Z)VbvaP_Tw)bBHL?L_^s9Oy}dzc2k(Z9qLRt0
z(u`dB4mhtaI`=X6?}Gisf2KrM{mkU(jda#xP2I@C8+U)F=HA0%x2v=jma@&@FE1DU
zsVPzYZBK*L<`;)nt<|?!di&$q#%sJyi=0D?QZBZ5=J*QPuUf=7e^Z|5%|-uLx#zY1
zJiboifbofE+vjiI`t63x#|!fg%kVh=-W4Jzll`5e_i!TrIhBHG!8V6KoH?-EjOpPL
zi2%_|@y{^<T<cbU*0S0-d;44_7uNIB)zemA%2(fP{4#U3{Q74Rn%ku3a9m+oeSz;$
zZk1ZT&IJaMS2Oj~Y&%0Ql>FK2_>M1%iMw=0*aPc#6L&9i6tsROlv}sJ^7Vs{CsL<I
zHCf25xV$`Sk<IRPf6tsWJokR%UDx$y9mkKI`P8*|N1052bK#WSu2aXS&uv-l?_8qP
z_npl#TJhD~f=x;n`Vynov#mX}C2F4Zfj*WP=js|$#-JJdJ6FXDn(bQjO5$N_SI&VT
zg}lhlO5eib0}9y^!s~Pr_Rl}h^{`{LJImCiDbH0SBNkmg99OuL?~k;BzwNQyQnz2x
z)t6VkKhLt5?QO@y46O|o&l}G7t<y*{t2DiO%q_-1gh}~kOxr@<)hdUyR9UZPE%+xO
z#k6;G&*#9vLu+QfyxlG<VZyffDwAwa;PO{&`z}v=6fNkRYc+rB%YPT-Ua;-`vLIs0
zj^`iDJNz|Fcm4cXu;kT&MM3oo?(EYGHedTI;`^N2hYG?g64u!CMLX@>?Dp<~*%!fE
zIaB?v|2p_D&c#QoyU9n3+kfiyOKwwlD;<BI(4blOl8aI4$E4c|j}(6_luFf&&5T`<
zy7?aW+H=kRrv(*m-+k8?-l=NCTA%;Gt|;r>&#xZGCSQHwS*z=`QFL4G)6<Q=UakuA
z@hD54VkN-5Bm0=XbpOM?gYvs}#l7sX`gpH0b@K$nR@1X8J0?{ht=aJ_s`Afu+oyZZ
zUfBOKr}BuP*fHZu33F4;+*=>LWS5@UFxghO>0rUH<$>$oFTBW9P@TnlT=n=OC)tg{
zksQnn$<IG&{+r@fU$rNunA!VysLH1+tY>&l8+6iL=B!qc{;)<)ur7vC_~nf9=B@e9
z(++=_7gjL+$@^sm+qZa@d!)pzcsx7l>jS-0Vy<VST9(fYmhv~0pBZ<4MpKu=(w?w<
zuLB1XgQHU|gXdbFz97|C{Uqz>f`6+*+$BR_C7mv2YEW1?qe9N<`jq0WzKzk!&YH!w
zJ9oVMvm%|Xf7`h^o#N+&-h6ZP=)T;fD!zH~%!iw-XIHjF&%9yrVd+23a_;wOhIe$<
zZQSFbni<aUg&`-#RP(^S!)oicF!S$fT=Oho`nLsnfgfYvsJdDhE>>d7yP)tUyR-7J
ztnIm_D`ID~E}r6e?0u}RnSbUKRjVJ-kD4zFIG;Gvf3(Bx!spNB>>n~y81!2|i_0I3
zKf@3etj~D!(vHN4*f&LU7T*@^3OCubbh~g{YII1&<hK8eH@=;Gq5k{T7nfPnlh#BC
za_p^8)Hd^fxaWVrrmwJuL1oL8>$P9`BhGp*43j?d*7*C@J=<n($>!5H{iJ*UW>wGH
z-dFBDe^~D^tga1^TRBgw;not#b(bAqyg#^<=g#$bhOS37PtpxbuRfZ-^Jl9+vuTyd
zKHID7tTZY=-dE;jJ9eHa@H$V_m8oWohg9}GdLp`7d?RPi!R=*DQ@iRar#NeW+4bXo
zg-&vDXyqFz@d8%vbbaA3vp6?In(^(~d)d5Gbw!bh?e!yqeR*L9{IeHIPPMyjed&!|
z=Go6j)i)_+T}b=7+Ash0Yv1h7rFC|9Hm==u?4i=Pjg<<SOW)2GF}-;+aK;xWr64Q$
zdvPqYn}14e=_oAc73X|fZ0hlSVa~F!FSRyyS@o}uc)1;7?tHYR<+sb7rjsW`uM2xJ
z9DJg=^6(2q9oBk}sb9`^N-v3K{cYU4^)_pDSKX-;3+|cEQrG(Q-FWjUAi`at=HAog
zm#pR*yR3M=Y98;A^Ma8qOF0;>PTw75XMDqkcjH3#*os=y9F_(F=@9O<BL6LC%`Nn)
zO`g);v`6UORkLaOatnNXn)X?p^ErOYeA(WoZ+h)By7!4Zn%C1O6l(5oAeVY>t840>
zTPJ>0g*Q3A-|2HTB-*2JlD}TUyYGr+j4XOH&Zl$B2JE}z6}PGLaL(3(g#mkvwyrMx
z*Ll?@wBn4{%i9dSAO4DG@fnouW^P??R2<OtP+_%N^!uU@tf!t8%&hu9*UzU!-c6aa
z!{8OygpJbfZ|>|C<oDN3&QxQwuVm|9%R2oL)7mx7JasIVMn7G9rM679z4$8C@LA^7
zmJNLQc6-__-et)wesla$#n!^u_NUKXaw4+#Omy;}nr7#ILT9Dr_5UujUS;mEE}aye
zx^7`r=ewXyvnTf{hF#sY#`Va8_z4HTXN$g3U_ZGwL%gfZeqw<*SCSy(nuQ_TBL&@C
zzkgiKSy(8Tw|CdKPnV|LWz}|FCI9-!46lh<hi&!kxBaX*o#b<IVPVVr++6Kr2M)W~
zYaFtzJ^$f}9@G8H2k*+i6PYe{ds^rj53a+L*LBwh_m*F3YKh2_ystdn`lVO+%7B%<
z8Y(WQyM#(Im6osMD$PG7bvDBE<v;Cna>rD%?JCVR%kFnvs1;WF?#po}Tzva%j@zA6
zWgnaS3Vt-`+4a<QOMln>gHuD4FaFkQ`u<g5{e=AF7rTWjc;f?aTu+>P=Rn2vg=<|u
z#ZNMMC*iqU@UYa<KWirK{`-Bg)!8R*y(Vv&l^AW6ws^1CNL-mQ=fj;PItNN0m~M0z
z%)D@F^YP=Ef+sfiG2GTEn#+;=W_e9<@ZlDgYsPZ_wqE>Jvhn<M7q6C>H4Z*q&4PFD
zl`gT3Z(ZWCJFEM0_oh|<7b>l^3tDpK!6Ca8mpK>z+-o|bJ>79@zJreBJFBSv*WY5h
zYoCYSwr#)ZEU|g^clR0cg{j4k!43s{v!fhtg>-CB*j}=OQQt)N!K5giPetp_)h+!t
z<*k^fyyV=k>q1%Q@2&s;=<Dz4`Em9OZx?-)kE%&I8MrU%!b{%RlCGCCjMnz489!dM
zn4yDz#%YmYAAKv{$(L4b-xGcKdPMCBvyK%-KCMg6Ty>bN!F*T#c`Bn#qtIL<j_)dA
z6RR?MckL;4SCj6FObOX>F68B^(lwf@$A59|(PVC!e|*LH=pa77SP@3ElYGYSmUfD4
z)(wi5+WmKC8O!aCyZ<_01fMf%<ajvMY_W9EshHKWt30CL=NL@&{x~UnW6)s{oxL8+
zz1J3OZai{r$z|`^YxiE{y7TXQT%)i4!fTrLE(d0%Y2V^HQjqy2f2T$I<v*XeOBUa9
zsZ@?wJaNw(>DOWzu8lulwcN=6xpSMx)FL^qJ5Mhi*;FQ`Bk<*K@X_^mmsZEG?@9Ci
z{&4^IOS!wQ<UKiMx$DN+v+slF<wiMGy_y-DFVK6#g6&||LZ6vGf4*CgK4EPF>x~s}
zjKgA%3oZyVUUpz^)MLYYb4*Q=xGUP$bhY1oAre`-Td{xowl&W;1-$Qkz`(DhGb3U0
zqLQuF*#XafZhl^0m&mozI;TV9)8PZT*G~KCom)TSs?3^&ekCU|=gx@XU;UVYaowtz
zb4#|Ip1yc(%KxTiN7Jg8a~)gFG}o^GLSGMKi@QVF)#Hoav^-3I{BvT*;eORga?6hw
zzQ31hcj)>1x{8l~{?6X+`8?t8RDoGnCzoqVK5*N#^|i~)CA>0zr5BcjoZozg>%txD
zLlJA89*9p)XpmVhvVeK^&u<P}_Y`j^Hn4c{&S~GIGAAh$j>yFmwRpqWm;4P#<u|Ih
zo>^(h!*nfd<@Vee#U9~e8S>$aczeD@$WGU-TY8K8m><8B+QR$`tL(G5_&;av3kZI3
z=5FfZhHyVFmTg-)9h52^x;#|E)V0`?U%B$#-H=ioQ-6OO<H9NK%xs>0(;hUOSH88V
z^W6%gx9dJ~9hg7SQd}u&!*7dM+()m8f4<4|W5Z3ST$6jI$0nLdcuvhsT;rl}#FEEq
znMes^MqkdA>N$thZb{rc<aNhT!indN((GxEuVz^8lJG5xOyMm*ZdCZUN8L$ox%$gO
zd)s?{{qoC>_g}iYCFbl^tMD%u<i9*QpDWhBLCIo?@8`oMtnpzVa<^Huynn_2XV$q4
zyJbHmMQxjx-%M#zmOZu7VD@28JKGq!#?8{N7B6J{lQdhknOi_#kL|Wl*ChFq3pp2Y
zXnmX{Ki%t?wCvQMTUg#EWz}n$^zNH@dfk*cGuKT~nLO=P{DnO?%M|~uk?M8Y`!w)D
z*$3UmxkXCZHQ7>C1~2k+qhCtTareK-s_eY~Jb$%<?D}UJRqXq;?#6Ot=_MbTc5Lsw
zwi$v88lTCVocY#X;VgV`{}&dMDLH#DFG`85id5fy>*ur$#-9?;9GYLi*X`1K%5>eL
z9a-iFGL*Y|<b<qtN-5Vxep?wF_Bb>-etkAyOG6Hu1qau$qJ}HYGoP;M^LF-qI$`#O
zLzn&8vtLJs?vybLj^7+VYbyJ%^zQV|w5Fcx;j63`E?T0lvF6@~yl*@6n0x9Y&M{q-
zYSDJRa?8|DKYgoGRqRFHm{dX2MVfnpuU>eVvMqnz@+%413wD<|Xfs~EXLP~Cc7^=)
z(u7~1-ZA~tpT0P*Tl;rG>ijrI<1Lpj@U-!_?Vc3(RH}EK^-d?<kKx5k7Y`lFl4Xy$
zy0+fNyPa#*hif}$E{Zf?B+B&b&JXiFQYS8oC}l2u)colAjAe$38pj^{eO=@)yT?g?
z@+*ytyKcU}zehU3IRD;1&${}*kNlbW{-2dzao2rojMRaOzmML3+Rc9WW@)X&D_;HY
zjz#YkGVfYv<Sz_uO%pWe%sp*rBA++A_oj^ftD1wcH;=MqHgp}YJyqX$e{0ObeRf5*
zKUawzEuGF9IP37a#&b@!XW32{%J<2?m2~B5lc{u3R5b6C4-ML^?fEu`#ee(T;B&k?
z=bXKo>CfHoC6yc)$X@bn=8G4d4KtSKR!X$&QCd5BdG@LKJD&6NEOOGVwGdQ1d4?g<
zzx<~9)sMV?|Ll0bxyMxaMhTOT<f(@0J-)NI$Q(Vzxx(RK%Uyx*Eds9BPerjEtx9yB
zxaDL@(A4v~759GnmIg&{Tv+nw`wx-AwIUg80_VOS6X23s^Wa8a6YI$m)5C_bk3CZS
z+&|9D)mBtCKCrT=<&tT#_}bjr0%xLIb}M}S&f1|<ChhQ0_3&NAz&B=<4fjPh-<_2B
z`{|+rKA-T8OZ=A-?%&%o>%okjVk@@2<2uc3f3Q?#mA$rgr?QQS&n#Z?7`a;idFyZK
zo&LAT<58VJ4!az4@2B&}&baBNzL<ILnd1ClyY%+Axd!RCKUl=a9O^XvQc&x>eb3wJ
z$8IOx$^GrNGy1KC>7#<LvfV|N58{en@U0Nrwfp4ejbhER@6;?7>^xR3A*Wfp?%dZm
z6L$&KdpCMs2v!et$X|W^_4^6-%CSZ%PmLniEIY|GW%ow`J>LaF0m8NBtb5OxsL#Ij
zSH`LEO!vi;tvLz2r%i2=cpulk`m^QR<{<C1iuqw-Guan#WuKB%burTDb~``)ZO*Bj
zspi_9<sZI%%H;mST>5R{0qan8bM}Z!tMBpM;NILG;WjZL<aB>`s<)ltl|6Qx7s_u`
zuSz=~rs>D=&(Aeud*g9#8Qv9guSHfpvY&C+VcN?b9%d7bAMJkg@$ikGuZ`Np1LpAk
zV~~%Pys{+rr;FpY_KwYqlO}ENlka5YVL0Lt5tWyjl=nK;pEpTW_R_IuEoq$Rq)OuD
z?>xGECqsJX@`h!dHybTpD<?W}J#xyA-*j;KMK<ZJJGd7sM1?pjMV~q6+szld`M_cW
zChPJQ+cLjiy!)^Fo$}k@Rjso-UK~7bt+`F3p_=(b{HsW&ho9?QN<O|$e_p*}>-X2`
z&p-9N><FniB4)VfD1T*YM|otMR?~0O?js-LQl9jGzcr7gWY6~ODTg;1EtL1tIBs!v
z;wS#n%8+iW+@`H8Q4X^9YeYVuIeX~Yftk{l7p#?b<nEkv_M(PNrBKw*7q|0_3ND_F
zn67Y_DevDJXCr=XXUA@t@+<)zfeCA@r%rvd<cf!0lZcM)3~PbKs#_K(p2=<Dd9+$e
zE7~}dF}f!4fS2)$&WklSy+3hz-S%j@`E-J<+}EwKpI&5tvS5DS`LJeUKldqH6~ngU
z6Mh6NUvuQmBc<Cr3YG48H0kh8W3^&0J$~%mGqok1XHKg#sy_I-R{7=^CC;#;wX=(_
zr<Hn56}~9>WxL$_4$svyjqNy17AZDIoBWY@p_q6#VS(IB?qza1MJ5J?DN|3i9MoS~
z(`dduOZXh)0;!7uQ`mlfymxSK^~q^>|7No<yB~aM#rEmh-+~v`t`z!l|KSpbNgbh_
z5@tgG_qTkw?_hX9D0l0We=}77zx<oJw4km!>EB7eGkncA`dZH$?NLr#-OoPv6@Qw=
zWwod!3*Fc^zdFyH>~=`2bOW<g-JE7&ndk<-gS*yTJyGzaD^2mWQf}p0hO!CCX=`5|
z3tbz%r$i>PvE%5%%M;z6=`<F4ZH-*W-S{cMNouzVn|yEb8~<~6Pl#}MuCx5v$9c$B
zPs~T-X3W{0O?`PAL>l?Ln0zz1mThsoWw9gFs&0czVaCE5i`l(Pk3RVOE$q`L2j`vn
zzYFAftfqB`^3B`%^NO)M%k!8+EWYCE;+|!zb}f52L0|ud+vNF%A$)&J1-Z6ad|T`~
z`J%3m^2~1+t}s6p{Sa_a<Jb<Zt&L~;IyU==>8w*!WO?d3+d#m{{A2>dn{B0hezVK<
zHuh#`3*X&Qe);X}xf`#}oN(*3V>tJ<u!%aHoGxb8&%(reWo0UUx@&%WXZYnXOXh*i
zt!plC=Y7bmT)C)#b6Vc<uRq%_B!AabiR=wsTQt>b-8t<g<uNRKq?w+Xs2tyyK26SY
zeMP~Oi|c!@EXcP$yXWV_--^ACd&{2~R=CT(&t>yJnRemi<_mky=GCtb=M8#usbI3E
zg6!;PXAXOO+V|q=>R5|+vO31E*>Bgp&&rGC{b)ZmRpW8Rn~9kR_V%|HKic(Uw}4wn
z|LncnT_3AY$Y{9`RJ!%_lE-)6vc0amT;lo6-h|(r-EUQ?{mzY(Qz|T@d;4OzuQgS0
z{z^}9YE8;iz9jq1`xaLZ=jut%8j{x;I5TZzQ17^rp1aZI&l{^X&!>HEnWMfl^4esR
zhqj8@J3XHTUr$)A`1<G5k8*lNr_1Y#_BE@--kzR!e~H%YC#UZS&MiqxioI1Dw#M$X
z&Zd`dBh`LBos+8N`_p&YkrURl=gRaQzHWKJ#m`tZJhpmPW#5)?r8zpcei&t*JzZlu
zZ>wU~_lh#E44J2sD~tA6&7J&vp48Wxz#fZ@49P`1gHNshTJy>K=IYnq@3~2DyL<ok
z*W=BPeZBXbw0*{7y?=%7$EZgYNBzX!CHIzXJRw(h_pR6a0N!He*SXr87S;-${5gG-
z+N9gAg~mmX_Fr!Lq3LSX^L(m#nMu6(hBb~$Hby)Q%$mQJ`~8+{xBr@0w||)G6zc8l
zB<WDnugSwKnHPA*n>En4!t7&HeAGwAy_+nj%~^eJ%0`XS2T2{Pjt8;WC!I@Eh*9Nv
zdv(#CYph?Iq7D4imuPOc%Zp6?617Jt`Lgy#K0WCNJn3&Z-g7iRIXP?ZeGfhcVX+N*
zUslew)el=c$D>|HOK<g$`O_3HGB)23<i74;$~`^V#bS?zMc542#?IVJU58sEY%W(M
z6?$pDdvoAuaNm*$8`lTN{(1J^I-R*uXH(~+hh>h5QS(z)317JJ+UMMw-NilcUff-m
zu3NaKcgdc^{|dM7-~K(so<*K_hTq?!e1)!~Yb%Ae+f-gS;nTHoflBbheQwT%cONnu
zl<#1w?!LFK{h!E%>C0qZHCnSsPk+1L^FfFyhxC*!o+bBnW8ZvGmTT*srQ-iU-QWM~
z?b7edOFFX-?Nlo@U;gNy$V!=_Yeha66)mivuPv{y`~B%_eB1kb_SNhA4t)yEbyNK9
zw|0fH>%+}QTVJ=FE74OdD>oGEv|YVZ-#FLBb63CL?=MLevwYPy2XY^oag)*0Nj7)6
zu+s&(YtBZ0cd#wVIWd<>VV11RgBRg%`y|>qY<`y|>~}krm=n%1OKH~HtgU?YEt6x#
zx>9`hd9up0D;cY?9@+Kthr*{7$2Y`&o>z9JvGC;9kF_Ze6<s1{u6t(Mvi9Ydgo)4B
zMzlv9;EUh=cVW_jxr<Ev>Rz9Dq~x2)^;=;5x(HuYxn+5&oKhEmT^F{mk(!?Pw{J?+
z*F)=t<sa6{nqN%SS{(C&$+XJxdugmuX8^x=<@3*`r>}HrD(2s>d^j)0XHP+1l!=<!
z+$jRQF*CRm#LhpF{*<G^tL%Qd@e#w}8P8W`e_N4!K`_AWrby2sjjx3XMh%xtTKyjh
ztM(}JNc6N%S*IByYPWF~)9FQ=ZTdddlS*c+IX!)AWu){Avqv-1g)@rR&S>6stm=Zw
zhtelb>(<pNUX{{y){c!m-k-(G&Q!6E#Z`9p?NyQww2p57Cl(~Zo9e>PkbC*`-Nu=(
z%x-PCxF-9QMz~jrtfPSL*WV_y;}}GHxH}A$&fE$((fMi0^3d6nJXw0JuHAg~LBle%
zW$T7MgK4w2Dpmb&>fjgFu73FH<ONopD3@B<3Y+EyjVTj69lsuqXh>7a*?w(zR>aH|
zR%>^DIlso|Ly@~$MPv3+&48AU7p)h+yC&ovViv#jVAAcfl;GIShHrS^bZvc9d_+3q
z@RLJjbE=i>+I^>$d|ec`xx;+jrn=t64vUXgpMAPJaBq?MDi*mdEb;1ZkEm}*Qqy^U
z)$o1bN0F%kN`{9_ERWuv@@HFQ(qfCkDyEv&^A$OzPG;BEo+?>$&T8AT*G4Hqo2NBy
zOIoh@Vpihn9?q9je$44`{_phMwPoY8lg5T8we%CR*T?@|F+uuut5W3IohwAIZ*jc+
zuQWIG#);mnK#qHBcOQ=}@76Y*{p;p0gEZfF@yU#3lMRBF+J{;FivQsBdhwc)Z?YM)
zMVqHBk_?n?HDBucMnhWLQhR=ur}x|HFazU5x2N4@H}K`vdmwZ;{*c`B_x&#{Bm1u8
z^z^m75Yy;32zpw$%g0(pzQ<GST}IZ?`POc)E-%e#lx5fHXXXE~JZDnTf}qLs9MT($
zi|)qhNh~|<cJ0WKCAP+8We0x*)GRFMJTP-BBXgZ)q0#L3XSd4k3f^cNyDGV6!#bOy
zd^65Xntxlh&cEyXzEOVK<ma<ADhfEy_O5JMofvyoEcEW1@4gdc_eSVlU$L2O{ROQv
z=QcUHy!cigbvl-BVX&&4-uJR;`(~NnXfbcOF3=Jb7xsRC8dGxjrOa!3XRSU4^9!7*
zS=|=W8)j&;gGEWyV7lsBg?S|n^IEj6-%QmG%{&n`sVMF8wKDC@Z>LICZr;>7ci_X>
z$vTpqCvMqjtZ7cWykUdYk9EP8Ju$l{cFax8t%-;ZY3mgA*B92EHZ{b?C#|(3{hY#M
z?z^*JI0xRj$8~be)UA8IW);<j-}uuO_u%61{kuFq?)r0na_Jv4!HQ;=2WGW#TV>DW
zui6wEzWUPSRp&)Ng<Y3^5o4A3)#`7(sM_^&F11IGt-d0pGIQQ5VTRLx(;wVc?Gm&#
z$-8#(h3PfDz_KQn`{oA=9be3T@;0wmr=s;VtN#xXqx7XAn`%W@F8TH@dFS>x-fee^
zxAM-HwwQTH^kuQh@4(x~E1DwNX2nga+Ff`z@v8klroLw<*2wwK-IFo(I`2EzcDu*#
z*7NawI{K?yxNyne;C*}6`)%Y*YhJj9bNS7pz&VHYzgZqx)2zC*@!|9Z$3s%jx}+?B
zvA$x~h0jmUS4N86G+ElCFY!!DPFk2H;EUF=C9h{+$t{Q|<2xpPSgEnT|LT6py7Lcq
zYkZ8;J$Wh3{mEjZw2B2LE7?82X=<w#^sTeCO#UXQB0XoxpE>^Pep=4$$SC{P^m)zW
zCx=@T&Mvxd8g+ifMqRJ6tAF&H_e9rjil|+|xWl|4-bpIb<ZR&AoM)~t8pAKV*komT
zVejV;Rm$f*{&$9LpLtvM{mYJPDU#-qbN&80-cYDwW#$kUu|NJU=i2t5^rWPN+cR3X
za87%&C9`f`(X);Uv#tkwDrY+GQexw~d@0lSqR=O)7`M2vWxf%Iw;xS8Bz#P3rHtoK
zlT96Ox;}=BNqqCa^L$pUV#e+{?<~ybOZ+}#dt=TlpJxh}1yohVe_mSR?HIzo?ybhX
zcl@H>*O%w;FPVDaWVwe+>*winoU4{UdekV{Qn94@h>ZQ(h+Y|EHAVN<lP)vn<jrxJ
z{=sbP`QzFGlasiA9oZmfk~q!Y@4@kv8^bQOZ~bv=wZrXQYghPBSv==WuHUyGH?}FB
znY-uNBJBq){57JAx9%*c{amv#U~$cN)<2b#{<MD6QoDXNrAS@!&8#1~e`HK_$``NJ
zDV!$x-o0q=)ag+LM#ZzGcRrXbq`%ht($(pSoFBi6zBnbDdwl!3h0{_G2&?S58uR}1
zy7=e=1x~8WHyXsNjjX0vI#@Tq((w?wmE~?+m#&zj8ovD24JQv5_JZ2<<8O7d?&n6{
zYw?==pR?Lqt9tfjKhw;qU)93SXKrIi{v>zhXjv9(=i|pBDH9y^W6xc&f67sG;r)bp
z?NjO|2%k3EcdO##D*4Sv6U}u0aVlvl#nwiiJtxiZ&uEqB>9s#rC^#=?G>~25wOcWv
zza_5atLxM|eQz~3-U>EW&NXMhRA_s9@;{aG0-+13hd(ek=_RemJo0yO!)~oRW>+=q
zIGnOx<~&)}ebx5MWlPhyJ@<YJgoYi`zP0k~Jb~03rz2U_*$Ylgm~PDVUcCMP&4u$b
z<e#>L2Xeplz9W67^i`|Nt@%d|T;+{sjk{F6Y~N0;n>!X&Wz>k=?Yy=nb4$%t=bRIH
z2liP%^jQ?|clFb)&Uqd@A;&y*URFFl<m$Oz*rMxj%{J*xt4pVUYg_v;ayR#0re$5y
zvv#gnf8hMxm{sNz6eV=GH~Aj1xo}u=hWz!r#_wA`n|(0bIN|E4?=`)`6KCqBm%U+{
z(d)MQ^_BL=k4;yJU-rNLu4(hJ^~@(CE3Y%U%n??2vAC<D(V^{h+35*^%kST=Yx%!L
zIV5TN`nWr3mc~{!CNb>GG$&8^`%B0saqW?!r%QDc{v2)Ft)<v^-*H=oP;=uc`!lL{
z%%=AQih1uns1hX6a`neakCofQ(xt55iZtzQ|0R=IQ>Xc0!>Xl))ioD8uU*f%bLYXY
z>NUUqZl5sG;#HY#utAsji**HRb0#$SvGmL4mW$4lpR!<{etT9$cAo%WdbrCnFKx#^
zEP<Dj8P;u3pZe&2r}kxmo+p_;nd*PqcCL(2oX$7PT<)syyHfTmQ#LENB`=MYzSb|2
z|An!YyS-t8i*~%$8Lj)7uh!~3xDb=7+5SMwTTp#{#oJ#-7R<-@>{D!gxp~|1-1et7
z(odZi*Op1=|K>WHmOe2cH0_3~b&=JDIV^imDalOiW7)&fEhVZU9(d@NpX$zs9OhOx
z#H;?i`Vq%+H*b5@xdmTKYaG{yd~tI7%V6cVLSA{(#CXRw@wbG2Y-;lR<vH1Z1)qhd
zpxwE}kFNgVp88$wv7&v4#t-w~*5QxBL~plV<qgaJ*tyqcYsO58(}gCy#kU1yZC9!(
z?@D~yBxj|lYk4L4b*548EBVK@+oyil+WsaYF?yP~L;Q`74~yp&@Lpp|-pjWu(qiF*
zv<rK;H-E6{j^Q@w3KAEOK6zSmruU`8i(Eo8y!yUoF(=R3rll9U=#Zkv+s&&_26<1^
z{q-{Yy0X>RvS=3Bz6&#Amlu}JP&qsM*2k0DZh|$(O$)4-NEZf76^>$@=-IOBJugSa
zpM=u0zini-Zq9ME$STTdzdYS$_Qky-dH?rpZrdxm%5l@(bvKnXHQbf+<OAN{Kheba
zi%YhhAxQG}b?vA#Y9;O7r~JI9O%&)cJ#pP&`s|&#vF8O6+&S3uTFj%vrFTr9V=VRV
z;Rb{FrT-!nJ&qq=!e<?ywo<fFX3Hnm7@rlD&Cy*qP5k}Re>};N?b^}Kx@l{%SxQMZ
zkHr?w+DX$NyleiK%X`**%gJYzW+qdmRcEaK@Mgu1eFb`*GT(Xcv!<+dciAf4#@0GL
zdD)h_RY&IVY-9dgy-rR<l}%&Q<jfkubDP)6@o!*roG`&SEN}&zi>I5!iLg(4=igrY
zRHyy3UePPIaMiEhO$-xX$FJMAK678gXY<I5we$54RH;19;k;>5`TcOY*d^}QM`oz$
z@2~!+<-4tVZ`_MRRx{78c>L;gP1vmWm;VUte?MbWR@SHD4HH|FO7hP(7sV~<UO4MZ
z>azcQr~5M_GrpQ@PCezHa`f-7{Pl55Uy0Xh+Fwj-SmHO8y^5p#&w^H#14|yp%vD`9
zE35cGy!D@O@18sE&3!Ld)-L*e+JD35Z`Ngz>>)o)L^)sE{x;vLaO`JIWs1<M!zokd
zUt4`mtLM7&*5-MSKTQrP54gEc>-4pCPnR#;xl3eG_BY4<@n`LyDu0Q*Fo#cX?tHb6
zGZLq6y>V-U(ISbCLtIx+{VF+g$dETbVn)h3ld2~d4!x_LFLOEV{P*{h)pVCf6ucF^
z_%~$vced7>4@=wvw`Cc>oGU)#+TN}AqHfBWhVFjOs^Vv*@6x3{@raXp;-w|hyJbFK
z{;kuOCcDLI`|Hfldoq&GU0OTu?Cn6`x1HO*>r7sw6TZCob?llBmLH5W7VCA@O4O9R
zmDOvXa6co)NAHV@p!<T`pM0JRKL5jZtx7I(`-4Y^tmN(06b#dLS?lkLJAaEm>UOm4
z8~x54v%e8*>Ze@%`u|@)^ApQwKl@_YteIZ!f9tEm;k)wP>4z!Isi)_7tQDB+YIR*=
z*-~$}M~^w&)VzQGV>ol4$-MH%<wd<4Y%?T(CG+^E6|cFo?2DCkNPF3KGj*{oqNe9I
z=>;u`zWZ*~gWnHCdk-dizH(fAX!fI-a`U#i9>~~r%HL>4dn#K^fat<Yt1=>vtVzn+
zwutxQR@*hlQluYVl)AN}Ex&2Q(bspKu6H_~Rxb6k7HWFc{kd|V#siKue3Iuyi@mxo
z|7>y+I-~yJ@Xz~4jV0K1H>|kI|8BPQkyOo`cXj(>X7L2Bo|OFZ(2CfA6HL>x3@ZKW
zDjuHJ{OzT(V5x>HS68F8-|5Lo^RzxS?+?;zjM5AXWnaSoH?E%lQ^gXA1)jBxibre0
z@01_U^_$DMfXlA*&HGE|f;wOLSk$bQ-1+rWU%%nLOOCS?7BSBd{hltT5`6M%$wU>^
zuTc!24trjy^O^Ph62DpmhwsarhNLYOZ=TNhs4QWiEX3#~AXV_k<l6JO8xKrS_jUUu
zzngQX%jen5GH>{+%8uRrcTeqGRPNMQJ!(QzZv_VG?>WuLul6BL{GF%hmGg{2SuAGk
z7H5PsgH=BmF10M0df9^EoZh<SO)(#TxXiX-R?YP~W;T1?su%~^Ufvl~D!$sio)Y}#
z&Z>Jsu>~H&%A1`Zuv`qOQh02)I4hS=#!Ktl4aIG{ciYU?OnforV9^cEb-}K4nS4GR
z*md`(@&SjpYs6+B-;&hRxm4@I!QQTvhHDkVW+{KCFJTN_wtAaV`l7;lSLgk6nC?<_
z|G<kW9>*jeF_jql3m+~$W_Dw4g;_v-*&F8tvu$UyhOY0DJI~mda&FDxx4d6YW-{OS
z(zcf)Ecnx_`gcWbty<v@TR0Y{Es^$QH8wo9B3bIxS&QI}4;hZ++~iwT*)z>RM!jp<
z0pZQQU4c&u-43oXRa5lMa-FE%`N{edYreYGvF_XeKQ)mp&ib-E?1A^xj%xl;YvEp4
zcl5r4@2pPeKhn0f_a#0)I=uH}#rmcHGWiu)Ki!?e%GhmNXS&lQBG~18OmIc<BD0^H
zujX0**>Otk=%+;!A03-&on$G<B<t7u$xX{I?rd7D5Z5=u)FncUX}`TPe!Dzk(0VuJ
z!Zp{4Ykm9<nm*%TX7+9DcVJ&*!)7|gVv~Kd#yo*y(W5*D0j-f&rmf5@;`kM7A(JUD
z{oM8`$Ltl%K7|bTOfz0sMfpwfVak&GI_=LQ!^=1CK3ChP{mhOf<Na9yZJYl&lN#=@
z-tluZ2r^!?YsV42Hm;eEON?GD)i&Mts{dzr=cX^NC)fX(CAapBvFV!-?=FW|iU$|y
zhqUht*8RGarId|HtM{l<c>jvhbKGC$Lr;1w<j7pI=jW=U$D>ys&0KXXGTrs%vTjrF
zsmGVzQ<&K1A~V^wElD<|;Be1EjrN2y)~3rQ-bik#h*x~4l`iv#eO=d+8!J2{?mYd<
zvTvHhVNJ!XA3M#wPkwmbIIG6iykeE$KGUmFe9LB@b<~c!e_7>9?|)N<gK`&_h|SxR
zdSz*+_1$g#p~eTFF}2M~$p0o~y2Yt^ab~LXWKP>@DMH5KdDk3d>O?EN`>K{(o>!1r
zFSLEW%AMi_{_or5<X_xBp!DIph5d=J$*TVts*N0rR`uE3alRC46LH#z%db{)^Cq8-
zVzybQRrU!Usl3GV=ufn=USVwOiFHmsVT!x9g{Vr|#4)jd_U;tkn7CTLe`>f=(~BdL
zS{r_^JQk?CcJ+f5tJb<-))qOq<!JY8@9olxdS%Qm6TitE3ae)>nLBr7ONH#xfLkvD
zysP{d#k@Q0zqqjQRi|ytmoqih+RER;t7JJ7)7pNW%URTBHD69kF{R95=VoE9OctgC
zj`MUCzcbyFwDQ}z?VFOcxOR`+e*U`8i*J^kJjBx>{y1l5<if^6+f7YR4(1p!{tnb#
zWOMJ=-D}DjzYg=?tcjXq^W*Si+sSt$KThAg{M({OJ!T6PAKIr(llmHVXji`L-R))1
z^`94PmRvn`g3YM?usLp+o`#g8k&2-5Imm7;uai&~&cV+F|IWOFMuNt4=Dm~|=
z{YA*wnScMEhwIPxEPRl-=H}HJyJ(%tbB^L}S^7Q&dXvnq-1azlbf=<{iEH2`#g3JF
zKXi)>^}UK&3S>OXS$6D{y8V<@b%WFL9e-qOoTmSLm~(J?m*(=~_B>&m+Jnmr8n+01
z5I-AWSo$Nwb>2&j3E79P-3`kqX8#p^(z}+u$-U`imJ#E}vv2k8NjzElwTAt(QCC35
zGpDbU<ArwY-(UILm+66m+s!^^zf!NYC9%@eZ%<RKj!k`i=GO~@Fy;?+F|!0(*S;&e
z)%;(x?pVIptEAW3ysCSv%~fk1lvuA;Rr0rQ`m-Zqn-Y6wJOiiP4F&nTZ*Q2oFf>%B
zzs_~bDpU-P;F`pBH+C6=B16`!hI*xP&W!C#+=HCcU-Qq_VM+|st*GtlSXO>f{jAjd
zfWj@4*roH#OgsKp2P}&{Jj+k}y;(NrmHp46ocnhDSU;Dmz3Z~>ro(&YNnQV?8Ga$<
z+shC4dt`PV_dPMOJ1?$H#az#^UwXRYv1ctuGr0McJ>zxK&+@hH*~|ZR-Kju>*#ftY
zeZ6^qdJ6CLxP7ADC9x@srswbSJuGCoEI0kto+<oOx0vV!cyk^6D3<Zv)J{XKa+XU!
zuh|NNubwe4!m@l<rYy)?dy+$V|L&`o|GYgNt}k)%q+iWF!?WSb`W&r-`d`mX)4%t{
z@Xh-ylMl<T_prA(toXj1eTC<0*A5NC{|RR2mwTS>dvJI2?vzhFVhI&j|0o|{wqdEr
zmp?HlPbcVjIS9UWymBtX_GHtf6QM~jD++gWgunW>Qqex=dR6<DEZdpAiQ$QAu3f5K
zQ7_zOTqbu#*jn6N9DBN1Y!OeI+S><et}CWK3KTrdRlvQvE9>)QW;M217rwmPyY{}k
z-OV@ZKepd)54N}@>dLSt)1GU^=>{`FfkPgP8;<DosBJb%H#nBPd0OAWlTx*7Bu}L0
z?+sqW829=|vxn&kk4<?ycXdxxs9gQg=rtdsNnFvLIkCly)Jwb1iExL<>K=W~`Lrz2
z?e~8BmP(h+%XcJ2`6-6)IVSV(_}k}2^0!uR@7tFmZTt1-uR#8P-}cx25%|CA|A(Ew
zZ2s)}|FwPvd;jmh>*c@x?*He!xAxE1#s593;)OK-MmkQ|qVlu<X<_Zo>s@#1xN7Pi
zoxioE+}EDp;Q6oK8Xg_rIp&P7)js};=A8KVb92(HZ1!_c5=><;ioV-!`G@8Brl&eH
z{lhlMtB7x&YBhQ8%Ion0>z{A_d6a3<5qr;j@@K^aIB!-6#E4xpe|6@Y%FF+GtM~8y
z+P;2$`*q$Lj%#NxY9*=pd%fyelOEzL9=U7&yj4GKf|5Bc9X_A5*l8d1CaJ7y{+@pa
zj1<+sYL<t3rrgY2*LUA7a}Sqis`k(MH@PNvrcN%Jma;f7Zd%674UbHC*I4r{JbS>i
z<KUF&lmB-+oxlB)C67Nqcg?JiTkqWB_Pf7nhVu5R_E+h?v)F8F@3<HH+nlpoXn0^Z
zOV6UEwlM-{Z$3$~vTm&rmSR%X)$opYe0N2AS@2a!jh#}u2i3mt6xHdRPg_tHF~zNN
z&(sKM)9Xvu+inlM>LDR__7n4lbFVUZq9V(uPul$E^Ym@)SJF5bE`OQDt^M4#q|D;n
z!HCfQMT*O(vl~pyFbq1d;^4`-InguS7xXP#AaeWIAywy^h{S&k&KnNRVXE|<zNUkH
z!}1LqCU53R_3m2C^Tlb3qrn8X_e>`Zk1m|bnJ#qG>tDsf{JewnMPs5j9*RtSZ`z?H
zGHd6gy$Ak@eQ3XSb<0XkD=m?!X(#h1Z?c&4%A#P+CxwkBmFC`4U$hk%Epk8mw?~jq
zgvENE@QG_hlRm%EI=TP<lf+LyPQIUXKkc`2>r2J`kxo4s8J^Ew9`-#dxmWsOxxu!Q
z{l_j`IL`HOhq7?U<9qj>9((_)^?;MTZf)Q5>#NMxnsr7SeXNbY$J1r2XnDf!?1K{v
zJ(ql5FpGVcUc<wte>JQ>#U*6tsqJ6D5uyJ-_j}#-YL-v;ulMi&_bc)L>s;0UU**5a
z-#b-rfAsmXZ&zmDe#NWdIO{rVX>&yF<bJi8=caH(+b`nic^s0PBAjyK{g1G3>`5;7
z8(GZG?r(UJ?qD0O+po~^I`rs1hYzoF^S|!9_bNA@d-dyjr;BEpy|*6hS!KX&ecN}Q
z=CZ!0Ee+qEZaDP%TT$5to5Q~Qw=`bz4Pu<2^qDp7@u9a>T+0^gPfyvS<*?9)LGOOD
zkqK+%g<oR5fg!V3`c~}I5P4F$&qCL$VB)1k3mK*=8s;oK<92`R1xLfE(@x49NnVDR
zj;uMnk2}Eakig$Nt0ZU6+PG_F;(o)rue1OE$t^Spjkf*a#UD6xo!rD41^JC>0R~GJ
znsF>!_&8f~wVaCSf`8$wUM{}gxKiBoVvN>?#yy_-yM!H688>MJ9eR4P!Ex=;Ba4Lc
ztq=RuglGJ)TDz!S;`WM|wdb>|-uBvGoiMp!*KL(V7lldeGLln{)XeaA-+8ce&XjBe
zp$FF!pQLRm$;wKZ`%TDFZPOOn6)#?Y*WX|L^OwKp(T;WR{{%cKS}DtM^Tl+TDIWE+
zzsXdsZms_&IRCBu^C>gEUROtL<^5p(_~j$Ni3<5I=gaMBvFXT~@$`0rU5tL2UJCo2
z#`I@?x~pEOw1$Y-UH?8IZOK>Wn=9tM{pEPc^zPGDvGT$5dH(&{YwukpP|0I({FH`%
zdsct<=5EuuSHoZax$!&mpIe8IcyDR(-DMjB@26VcyqU6P)`ZZbF9qJe)7l+o`arrc
z?LnfNyMpJRdEQeLG|o>5cI7r-<i?>`QNQ5B!e-wMYgRoIT)j)=1y2U=JwZ0NZ(?8b
z0x$0Vm(eq8;@_^`BdZ>LRo=Jf&)@y5=OwQywQ+npS78w?bLyYQ&P%_nkNOIyyj!y4
zWz&2M8!mSh_jOw$ImOM-o)>6e-V=S~#pxRcIsubH{Ji#5FG@OE&_1E^*`b>vDd9bi
zmK6ntQzE&e-wA#AA9mXK;kHNSkI%f?Rd!@s#Kx{<-!sd8iq5*3aivXaNvl;5^KoN0
zQM3FV{0hf-_o#|}N}Vq08O6KoVCuO|d*&!O?w(SR=fU~xL6YO#LkauVAKF~I<&lTw
z(b}DwTK{kCRabg7E$e{$X~ic7a&>bK-<qeNw(7#m4+Rr@qp$ujm#VHmqHU(={^diu
z#uC%@*AtbeJ_)-UUHa%}>9=d_F_)uL*8Kd$wPtJ6&ah91EA9qH?cB_ot?=Y}(&uKC
z#h+L_|Hhnqb~y8N{NH~!3S__hm>ww<eQ)MrYnhkJTzG|@Z>`l-Z}2kim0b29sP%qc
z%FgQ>b$+h*w_*C|+Sfeup<`3=2Pv~?-|rinZ@A?Mx_s<Bd1#Y*mBXqVc~@V?ZrGC5
zv*P!P#fuiqs1amt{2cBb)~lN?^Nh`B(dRjr4w#*sFBss~{NmA~lH9m6A@AhuWOv7w
zZ);2_S4x?+Etr3)<D>N^>%=Yuhp^t~-6VOsacUcLVCa4=wtW#(Umu<s&e-qr(a(0?
zZIyRsBKy5ep4{4&<d~kVeWYpawXhZa^<Le%xmPY|F-A;2mw#u&oJrzGpDIj0er2U{
z%Qg1|vn45&)1B5EmhHPDkvUIk)nApv!Htcar^-B4v|JW?6`E=}rO)SUPc2;Kk;Rz)
z<>tW+e^~w>n#s&BBersfo5iJ+w^!z$d%)qXTNFKE@%G5%slH)6pKnPN9lQ~@&^C5u
z<nF^SdrUgbFNWSODVoV)@|r`(D0l0+yJ5LY{<Bs0@*gWT$O}+>Cl$7_T<x`t%=K&8
zuZ%)?Pvj(~{Pf%9VpP)~dpP9BVVBZ{Q;*j#p2r>Da=9nDEuOW%OoYRUExfX8!NFNQ
z+mtL!c)X2d*8BQQW6>;4bvPzFyJFIz^&y$7*ChUb^T2^qB6BB;?`?a=2kD)cg$n=W
z+Q~MrymCJCf8zS9ew&kanf?;WUGUd`{i%P?FMfOcw*CLb_uu!`?YR5@?&J1^|C|2?
z?A^EZ|4&Z4{cOMG)y`%&>~dT)@4TP?L9=FG>FGZoF|5r`Pic^rVxH*g$`i78=7sZD
z57yfUFS@r@^Ws{~i(4b)wI_5jCqzA&%lWuv=Z1tOq5J3O=Pi4~!O$4L$>`*H(a$r~
z%IDvAEvbu^X<#sx>3cRgl=J`pv-Mp{_ED9NwawBKPiD<gFJHR+(A@{TxBc&>W-njR
zcwR{BRHWAf#@}!Fvtr*=E@ZoqH(TjiMsS|6nqXDK*T9AzhYMdD!!*A0TM4~5y{NTy
z!M#<wm68Vv3?BTM{6sKP?NGAx)ESQx4d<?(=KR{}V$dEdUymtoUg$rJcYoP;b{G3h
zt+!Vq!*tqjeo3mB6u;$2@s}_exu=sWyIDei$Y-og^!H|1=`uIOt;K<TU;QtJi(GX}
zQZj-#j!tm8*tlKO^2F7~^<A>@@B5@KAFg?6v&cE#@aP?BYu+U(hGJp5@*PL^x#;Ad
zWB;Wi%C_a0c&;pqsa>Z<n1P4p<;<)Xx}qhM>r!LfUvBs~b%*N@EsliN+?gD1y1c)%
z_x%3R#pd_->fzs0rz?aB<>arQJ0sC`M@`4X8#jOPI3{cf6%769-nGeO?|z?U3mT6F
z$SZwbH9hj?8I51pPrc|8c#%~!Eq2O+SU)4yw?41;SjJ!Re!RqJ{?sE6r&cikiLRb?
zfc=VM4<p+ItJ$gvxeNMEC#+fUvSj0|X@xw_t(KG5&RwM&zL8^PQ|bX;^}k1^$!&PP
ze%{{d@1Jf@KR<tO{m*AxPwWax+~djUnb{}FY<>A+b)Bb!pI)rev5@oiw`Vt4?8}e;
z^YSfsYoSPZ;@wJ18(EqCToZFTZg0L`U-|Qwzu}P^Up^Z}s6KoVE4kVHe)HaY|HDm>
z_g%c6n*QU`=hy3!{HA11zrFnh_o{0rGwZCP3%Yz_jH`I_U8i^Kl;;ZmR%<3#Rll5>
zz4Aq1jbm9B(?-$hk2Una{%kq)+hImZhjfL!+p~XS`k7_%m*vvfrLvdvrLJMRXxzBw
z+ZA1-&Zbj5T*(JA^|$(T+OB%y(Ro*a<L>cC-%F=Au3mZFxq`P!=a%XR@t2EcXzbW=
zB`ES*K8O49hnYKzTg-J91)X}R`npKV@?lMh#O!?>H+j#eu;i;4?5?exsViTy%ly0G
zBfq5^oQqi7H#lr;s(<mex9+Cnl_&n^pVqlLP29dzZK_z{bPk7>+=H|JU10a*mop5U
zl2x3P?>eulv_Vo+Na(Vkk>0;&76Q9^cqS+*on5dkGDH9LtSqC5ws4=m-pZSsn6Erz
z;TF16$H+JTu(B|tO_19RxmQQjjFg3!NtW^)Q(CGJ@%ID6HEjdOUHiI4n;TD`vtLwI
zbfI57V9~+lIe}uA`#*CDBphO2cCtj?`o%xT+NP#evKq^y8vQ?5-FU*@|ERZ@&B}Fx
z_<uKBe)h{dBLkXvW=Zkw`pdyF_j*s)8eK=VjHypQ=(7Ek`4V3ue_X)q*z^mF<2rVC
zva$&LQsk&DwVHW0sijEdeakuT2WjnmMU_Y5xVJw)c=*HDr2h#OGv>}qTXuIvxY^{I
z*2AXzm%2XNS-SXrZk4(HTz&mHM{h9oT;9ESciZpcSG&VLibyCd?{r{`c(ZkC4d121
zf8YJxCcJA|Nc*Xa6LoHgN50IRP~gK`^MC(4`$GOQ2{rfhy<4CDTX||_SeZ;rDYx~>
zeUI*{$4&L$)pgi!)6<+wtJd#WuYJvUF584Ii6s)BGZ|hhuxX!K^v<N=n<3ZPhbg=Z
zd{!^;D7(&ZE<d@zWPNtP{}o*P{VUBFN~M@ZKV4;;;1=r9yWrcwS+~+R-a4>A`pVqn
zua3>EV9q!`^{+wAKE^3~7THg$H)k;FUblR)8^@d@ucYkmCD@%$W_a@LBEzwu!z=C>
zN-;>fH=d|n$~fV$hQRLMCK4BoxDLGu;8oCBrFg;a8pE+uw<VKy$J(}ZvMXwRyw-do
z%OT?BcDZA%?9N@sLQNyr)F(OZ{G0r1`%5MHvwX|Dyn8Lb)fTPa^SNKst^aa?&w_;b
zwX5WR-`>D0#If>18M}($hk5zY^|sM!KTEb*vFtT+vD&Dv>E!6lvt^H9OpT4*>B-G@
z)vAm9MFck8c(Z-J)eqNm)*;!O^^>1hdPW@PWnqyMIg^@kDy{QQhRF3d{<n8so^gC_
z;8Z(#<`VV=tCtsRpXOyVo7}KjmSJ<DXwAZHCm6RyFrUe~e~n?*dS;hZn@j`JvKM%4
zy(Sg#G}SS5zUl8m-;FWz)Pp+&T1ATf%YC>Yzsb|^82c1uZ%;nY)1hm(1t(0K(Ap3(
zV~KT;wC$1p)UzRnx{l~ZykK}6<;^Sif_1CkBa<(@>@94k6%U!mIhkFX6Y_M$E3MC&
zon87qlG~5$NL*mK`CaRie2+%w3(_ZCJ{L*&9v1$4)q0QHw)HP`W4NCPtka2(aWFr=
zd6(Zj$2)2)eK+-3ems#6u5H{}8v8BElI2s(hZ5^+i{DS#P`As<cLB=^wg10rumAdW
zVT)Ms2?froZ8=pl>^<N49y{6ocI{f*1=mkKE2-JKI$z@J-j$X+V;0Vz5jkNE$G6WZ
zOjSM?eA7k5vUgeCJznwYY}K0R)@;?*U`8>XU7S5W>y59^IV-l|L*T{bZkFN4MP3W;
z63zDc_DPLxN8RKqskS*=l{49nF7mn9utM+4>Pc0<GFgA_cpD%6tm8|8iqV%Feh1GU
zEY|)k;bn2;z+WG(|7XNEOAEEx99fjU=kARc$pVL5-5QUltL>dGBzd-UN0Qeb&e(?D
zqcS2IN0-l;<jVELG(e$(V}D2OoBXentjqWL=+E8!{IcUyn?04^|LMNDX@9@w#OGYo
zMKQ0QI|t8QpuO^@(o(O7yKMC39!y-89pf7y5y)Ww^zO}&zw*3`!cz8xdulu07n*R4
z>%-X{4xa*jbMwCj9liSL$=_*)>fWVRCC};vU(}yk-Zk0h$0ehmcJUf}{Ea6}6j_-r
zaQx%$Cr2BF)^QzmR~OIx^yz2$`XG~p+gbPTNNi79#U_z?qCvWP`|2e>Z>)Rl$0Bxg
z<%#ptqc{G%@P+y0$*Sn+0>vp?5_*)ITi1w{ZnIdR(v~1GOY^C(_qomNVqYxuMNQua
z=Y(783SM~UqI!MywAbf5IegzUJlJhwedpDj9Vc>|byr-rJ2PFmgD?Juk0gipHfe_-
z+gE-U96rVUTyn_El-DQrVe$Hw+PCfE`41hI{^#3Y`RyO8qUoh&)19|ki!GjGy>_<W
z0WX8*-b;6$sLOju2fWLavv*N8IOW40&-yUi;=EXU%BjyP6;ogIw_Lm1dvn{t((=;U
zZih)PekuG|ZJ1=7;F_CUHq%SYz^V0E2vf?hq^0h%$L{|3dh<QjXi1CYnw1|p!!I4S
zU6rUOB2qX1ljo&N-&g-FV|YAu-d(nezs5fcr|4b!nV!>nXN|8-{C5uywe6WnYojJz
zTQoPU`J3H=jfWQ}Uz)W&H-3+D2JfxKPZEqyPqUeGe*S?o{a4)z3KE(HrHidU{M#)u
z?@2?-$6pg_twM6v7w`MN|L%#3=q=|8&V7^6-FtSPX!5y#+izWWn^Gkp{Wx{P%iODr
z3f}bfOp2PPqOiM!-{=9OW{RPWwU(RvJqE{1uaBL`xOnDNUKY3A>51<pGG6VdoZ-0g
zSOTw!<6TegZIAi;zrC{ByZ)H%+t-Ec+2*@!z2Cfzyri|QXvUGvXKOv$gM6-Lnn{}<
z<8{3zwSr-DUSL!TH+!Vjf!*qF4g`G(y0ZJk#(fKB2uSY~{S?++^s}n1@Lj_B?Sk`k
z(#+pm$*lV2ApCDf*`f54^P)0t&$3K<kZbB3mGtNRqnRQBSA-=bDh?+lC8yl!3oM^0
zJ?rGXSD9LO*SY>Wa?0&Q_U6{8*1nvn{>QuaIK5eaK-J0RUiao%^D>Y9ei*kq@7(hi
zi~euFg6BLcGMf~TeCO(IN%p1b@0uKP=5x)x8M@Was@J<nTY>596rDpdPIo5C9=iCO
zd*)5E2u1In9H;x`o^MyVo$@vfWIpiw%e;)-#d00byjT8rar=?KvN$-szWB<&`_CqC
z^7ZTqefxJ!%ZATA`=$0(uI@H3e^oHC^!xw!|NoWmwoKxm?;!CjSRj4+%`Y7W-e!{n
ziv{}U9T75_@Vm>;F38wBIeprZNcI<s9^C=VFD~3H&{dF<X3g1Hzd_C`l9Bb~<n~vL
z3%1H#S;TbZ#is>fRvY%QbA{Ded}CZ-erVG5#}<F9`aVw-*?On_a+U0gr$<V6`;>PX
z*c*v&j&caU9l7-R9v11(Ulxk(&ouI|+qQjD`OaVez9>JN5&5LxT`tex`9~AK&%gOl
zF@AT**RLVD3(Ed{*%8@YFR9UPx`6Bb`+pgQwI!Xh(py;FzOIovp-}ksT9|CpPUj_F
zL3K=a)tik^ZFW3)Mq~TeM_XoGvS<qOK6_U6$rXO_lkJ<&{d~6XR-y3L`nP-wG&Q}y
zS8d&Nt5tpVLsrYkFz;J#%bYpy1&AHIxP&>++2{05tGq?W=TADnTXOxhwP{Qt-%reZ
zx1!0~*rd-+V~@Y`nI#kdc$>SdI>$I?Qec$q>ce+#1kde08qxi!(RkD2$h*0-W9O>q
zn&01dB|+-SHj&oG&rco-&fPzKLW`{J->?--d$!mx&WtE3`Z4F+q{CB_`nxKhn9bEM
zODnx4@gb5;Tu@tesmPPFD+5EKFBZ-0-!3)JKu>1d+JudvZA~RBKFnK|Q5l!TZnGqA
zwaY=J=~jg+_A<C`4i32eSm>b3V&l-@1vT|CQw+Kv|1RC}|Ju}f6+d^s=G}DVz=YMZ
z4CgO;mN|6YUG&pabDPIDnOAR*a{M@(#p$NTd*nc;F=y2A7CQke_SI1~8g|qBG-`i7
zHu5@W!{&D4e~Rs`><wpRbU3X&tj{iK6tYZ{4tf#H{kpMg{<L!!nf=l?w<bwBsO`J5
zc3Xt?Ey3E=JB~B|Gd?#x(vZ>Mp^V1ELs#$DPgl&YVvP>@eph35LSMs?7bo`}7w)ZE
z7jfiAaGRgGYYpcI!w0)#3MUy>%&OK3<2CmEx8mE+ix>ar7a7f#f1p*lZ|a}Ir3MFX
zcWZn|Uv=tb&Lmact=DdIy`TPGG_UKx<t6{y?f)p=@xR)*`Q5TZ;SJ}Lxjty9Ice^j
zx`$<A$G3!|3+JC-7S*}jVUyR*zEtjz7rECKwsY8j5vbFD`E_X{Pt5<lRs!nhV@02=
zYB8%gvv|htRqsA!-Edb7_c^$D?-Tv#PNh?iRDAb^7w?(T>(^&=RQP7bv6t^Z-+XB&
zZ1Y0UOJ(;j(^el#?*m=#h3u{er_|}p*8axclxAM(##Z~Z$aG&r>(W=xvZ~vJO=f&Q
zQoil-%`E}St<sODrtL_wk*hY&d8HZmDJK5?qdWh6{nY$pL_%$6`hVHw?f7Jlu3kpN
zd|y6A{_7W4&U%~Q6(s9Z@^0&XpRn|wN_KN6v>%gtSEKg+-F)jMr<dAQ=$=*nmAdHv
zn(qIX>;HUJmi@nc`&v7J|I4rMKKuXI<eIvNAM158<G8QzCOyqn^POB*o4DrR-==SO
zp8em&d#l*DEmYiHU5r;<?qS<}uH{KT^X5+fChBylVq$NrCi|?KHzxgt%#V27W-wm=
z-okXIVVgsGiR%8>`$2P9mkt(iYA^&U9C=gIQ7HO=d!KaDo4%7brYX+<<*5I6$0>2~
zqZY2&pPi;ioE76fsuwDF=EH&e%Qq*QNv*xo_{ynzyHld;p2I$S+xGwdQ+}lW_^bDl
zN9x-%B_1)RW@gJh4)3el{APLg)ezajEsIxkv~dNdwuwBHd$;@LuGu=_1x62qRNp?B
zG*8d-`B%`q&?LU9J3c{Q*3M60mHd*XzB9{5x__0$jNY$D{(F51kDlg}KKWrv(&8I4
zR{lCQclG)!DO<}gT$h^^n9ZtRdEi0f+-LV!Zaw)<Zk1l`QF(>i{6c(JB;CF>K7Y$+
z)~;U6!1lCr)1glv_T0_f$@{%p%}n5E$AODqlpJ3O9c8pNKK5th1uNUWRgWbe&GwKH
z5SW+0?50-ZXRg;w6Q*|GD_9e{;qFrrdA}E2$+5?0%zSxUHix~e_*X^qa@ma%r`PHR
zY?hPp341Cyqh#gT0}W~iJh|0t7qxu@O<o<k%kd}S)`j#A?iR@n^)0q6CQo(=R2!<V
z-S_L;O$U`z+Z1ZMeBR9qZT`mf+gHI*W~KPrYjc@rRJiQ#wY$yU{&Q2#!zO0FYhhO=
zzq)Rdk|40^UiSQV_wVH=znGk~>y&1c*rlbNZHG=@Yg3-(Jgrdpd*`i3D-5Rb*DRfR
zJ^akxOY3#AJ@#7(TTa;X^yu5n-FA=KX3w@}``IQkE9A1q&fW6bZr2XA*~`4&x}9O^
zlfG4ZihJbVMf|taI&`(CXi?#{*lBy#<~2NA&Yd*<;^l=!w;0%t$Oxz`ncQ$I`OCXC
zZU>te1$-_mWMx&%SIs|}<C?r=g15_gJ9ANP5r@Z9gifi6Es&~pJ*K?nfoWsxuD@H@
z|KEPK^v|*<2Tr<h+H`8F-n_P8+F!;cX%A|bq{bgmGrG_&c9+ALmCrU=sr_KPVh&#v
z-=24y@=yP0%n17Y&iJq5{Iy$?m$Y2e()x9??OAtk=c4qCg6mNokBv9RPWmj<b0)`#
zO>F;ygx(#$6FHS$GCw=B=ji>t+rR!ktUmiM%m1?92_L!^Ig9_>Dp4o4Rw|F_#fCY|
zcAKAEH{a^N>eYf5$yo~+QoO8PKCte(^>kfcQuuBawYBeGUCu5keNs~Tru^#rnE3L(
zDi(K%<g=+d1-%zLAIzQj?$t}4lbq!Xr$zDp_3bV^UK4zK(xaWVk|r*vHr8%^DEU*W
zIsfCtoc%MJjOUs)Ub+$5$@!yg+oUIQcMM+UI{D5QQ+(%p%qzkmkS*D$`GwR^kI4l^
z2D8qbn#11W^-1|w)k{v7-AsN;b(i=O>#R3!`{ksuTD11q=9T;2JTrd$dgi2k-}EQh
z9~Agoxa^+$PU)38+x}0m30|Nkb7{KWryrKy_r#aK=;8=BHZeUt=iJEy$zq%_;Rkut
zQ`a3~v)DFu^U1Efi+d-(k^e0C;(6`wv>ig84(e-<q)!u{e$z9KOMmeZ_NCD}!Mn~m
zg*=ceH<f+f-F)&5kLa6^{eo!~0{4aXhx|6s=84<K=zKNBB))WI_*3Dn3$|aJ+i&wc
zI>YT^p5f}+1uMKZlql~#B(+01W0uqF4#~IeaSG>m=)^E7yqx}X(yaaE`k9T^GQ}+-
zwU2q47tHT!+RS<9#ZoEPy1VZb`uHto&0m+Y`ZUMfLrI~_4JsX8h9pJUF0kJe_+;NM
z&tF?RZFcP4c4Ecb6E7S?cBm=d+0w?)-_a?3ShuiwTW0{{7ljGeWL23=6c6p{Z2uG?
z>6Y94Ki=9Ux?)1Zq`VxnoRgg`F3ZnPYgYKRUitM;&Ln$T)1JR2PaXW&w=KGS^42Q*
zU=QA&sKUP+q<n2Izf#Uv(?8YmMqc=l8yp=Iv-7Jbnnk@^^1!hBq)vrkV*CFY`wExn
zUD%zV<9kDS&4Wc|iUlff;>)Hi`WL%GWY41h>l#%z8RtuX{bD4yJA3Zlh-0gZ{#;Ts
zO*p&EetOx|RiCG<GWHjHmcixno|EhLx+!ayG|OKpTsiS(chklCO99J7!|uL|{c`Jf
zM#+}hwR37$?vDTQ;P3mzvwq)y>;8YC+=}qq{dL#FpZ@y0Ppho@|8L=%x`*HQyUe=I
zR@xk~_e=1;n*U`#UY(7<zvI}R&p9QFZb-*%(hS=z3Yw9-`{Qr^fBu61zuWC&xL3cf
z*LqifFh|4lpP8=6;;<a6;HDSmS^uqAH(y_6{owZR`?r6`x5uA+eSdjYx!o<RTczt-
zo^wC3=l_wfv%jl2nJ264&)h$SM$&Ut?mzL`aB<t`D@t;UdP)|G%JQ%K?pcy=vG<I*
z{yy2d|KE;&o~|)D@Q0Sf{(s%?-fMU7t@}L7+v&tZcZPuFoQdbA@!L;&vU0w5kj+`O
z=D1su>mRJIZOz<#l36Or*qI^OPqaJV!0FZFIDJz~*Y*jkXS;bFQaqS{->xAcY}qA+
zYZqtB28%4S{?;_9BzR-vPYeIl2UAL_=IQlcsj?0VTF~)jvC7B&b@NN?&K<QlRaLcQ
z+4Blx>0{EH>UfTtFb44JC|q99B-DR)Uvsi>#eyf?Z@=!2@_EaBbn_1zrnP@Oq<WkS
z4B|FeDcJgH&g|dgxxCXq{r7R_PhSqK&-kg^J@x3r9TqB2cgitEq?g3Z*1NbuuI|Il
z*L)YHwW|y54y>3zSu3R=eeJh>ETYy<+H5LWm-e=opPe&vi?Qu{n=8k)RGzbyMy<NE
z&5H4Q+()~lmaCPrHZCuG<zBp<vv}TF?+=Cd?y@eLZ>7Z@{r29$$xrfDdCPt~(;3m+
zc=}*6<FgqDBXU1BvV2(hV#cP~$E)w{jNkT0<>WixW6jmkfA2YdGTB*PV6MwEr#RyI
z1OrF=h_kY1bS88kv<-26)wDQ9<WElf;kU<EzHH}ye>8qK*GhG+*?!k{uU-+{VEfID
z&BS#hqnYyL93>gn3(oqwS;tf*RW2y+(b>4QYJ%j6Z(Uy-%Q_F(YA#zazb8!iOXyAe
zb0-(g-Mdug=cE<svNIz-%x<3MtSno<$Ry8i>b+}^7bJXTo?fQoVO`y7o*npy<6U8{
z^YM#qTe7--h!iY6xcj?){9dVje{a9OZe_OIT6L}?w-J*7i|N1oaIdoGZ{>s*r4&fd
zlxdjlF-xcMtW1-y=&Z}pxnk^x19HOR9~|&K&y&ZbW^5qmKZR$yL(RMt!`tx_4^?)0
z)ml&76Wg`c_-O5=H#6Fv?06Bpb?d)IyCqGF?Cvi-G5>rV@BO`%U(L_-Z%+Oid!m^A
z?#VYB?q^%>Ub%0nVe;|E4&w1?dxD=Y-&nih&ZSF{Qk4<0byM6=t&Uu^Zs9Srpj1=-
z><eZJT+Hq2sTED<Tu*OHy?OWTHui;QqeaD9R&EI0$>2ZZ-%X($|Fyr_`?pnv>`Zr;
zR1%tgIp-Er%z}{F?>{v1N^CzWnDcyb%ik$SpQgSsI$N;rdj7rrHUA!YeljzkSMqB{
z*OKa0clED6>`;=7NSelId3SfL<1GK`=>6BrPyOCGsp&I^&(;7w%UyyuXK<|Cu(WN7
z^L_I~M!SkLoyv3EN)sasqD8)F>@a@e+$JD(*wrqs_kwTV*3{{8)}ivX0=z7$bsr7f
z*gfwZ369$Fqe!HDXVw98_Ja7G$?GJ~RNcRl8CiF2o>n49sBA&x^<x|6T+zQ+{Y&^$
z!qpuQh2Of=iyV62zv(5X6`S4cC(qxkcjMgX5ZG-VaEH~7k*8u}!eX-vTk3A#HvGBa
z#05_0h7<P=Fn@A)+2>d5F#qJmtVYe(O21b#xj&y|^YirYcb{*T#5@pWt%+B^X~}ez
zaaNj&dGbB+o|q-k$^k(KjxNzN+4{Pyz+~3TB6I6Lfkm2ZT|aLBUUu{Ht8MY?JkJEa
z+p$%8O<RP^(NkL|JpQEW%;wtI>9DNB|Ktq$cfH@Ibj-LEaA11vG>Psh549V6)&$L%
z_)g+gqqKDJi<M7K9gPe3<Gd-e=;VY+snJ<KcIiHkxt6!x_5YlkUk=Rrc1!m3Dw}Hw
z6K~~yHCruk)78aHS~;oV7jONv>x&JO7W<|LooPL<7raTr%X(6?K(=OA@JdJ5=ehU)
zE{x{Cq$&S$k!8lByNRt1zIG?Vr!3!Cq~Lek^FC*HlSJ<GV|BadJy^5wwyRk4p17c8
zdya+)I(RkI%-K`-ZC3w(%~yfb)r@YidJ3w}>H6H7I!)<H=d)_JQ-&JJ3V~I}YR>wV
zE-qg0&h@Ke!EQA(<(;+$yy0vc?oBldo4Rz@U0J_K4z-C7^iPL<=8~55b6YQ!Z*9`d
z5a{yeWjm{;u&Jz*Q$Y-e0ke@Jmr01fM1_IFZsB5InO9eqTrF&koT)FeXHF9T$*p_i
z7(Q7^Iy-#ablg@%Vkf(ve{$inUCc#XvfYa}F#n(N@9)iMi+7C)i_0>58q>`))0O$F
zH%{EJ-tBbO<y*|F+n?C2oBCGAO#j}#+RxuQMVEIOu6kq`@%E9yeJ>Wi9Qh{`wgu>U
zO8e`bvNAl*^uXwQy;JAkqj?Rl|JK)Eum7{-{J;ILzP^_`^!NSZ_4)7X>nEM}{dM{7
z1=IfLjAxEi#zvTTUN<jj3@Y$Z;ov%1CZW3YTj=w9e<k1at92NP6y2G*pC|76e%5sb
z%ylKUd-5IxzvcMzVpHFNc((Pg<5}-NiT&Uk$9Dfo?gw#+-?JabpL_d`qh`akn4ewd
zR#8h#o-(N#@J#*aa9ZP0;?7yCCvJPFcJyk2l3x4Wb4_}OwtKxUmEXG2?0TuO-K!f0
zpH3Nl*gr9Em8K>0^XJEYiTbz7w1`fT+WA;YX1Bnd!g-w6qqMC}KU80qJn=x|%u@BE
zQ}*hfF1sz*`0DQ3ko+x{+E<)(o389VAS+-VSSRHdzWkYo&Q<M}_}8lizJ`RyfmZ%s
za9ts0{YSw6@~@mvGuzk-*;d5rZOMQ0RZGpY{Do2R(&w5UCaF`Kx6O<Cx%sHkY`yt6
zYTg~0sxi^JB~3+Qox0BN<5BBH8J2nc@npV#V|_|o`C8$Ag~z|Oi_YlZwV(N()o|L1
z4*ty{_B$tDo^LJqugPSc{+f$(1?Beqet7ir_xyWmbDL#XM_Ecdd4BgUGi&zqgy#tb
z7w*n|_WblVxs1?iVYx}qGnR)e-}SK|%I$@<ZN__!s6bKYAj2bvrbJFHp8Hbe@&4a@
zJ0<RN@U)7@><E0nc}wvEe^-Oj;7y6oQ)E=x(xQXvEJ9_kuC210*<y5K-t!I4{-TP8
zd6FAWajrO^u#RhM+5RVAc-$))r%ZqSB8iiCg<6l$-$KD2!&T4Ly<G7xLBZgB7pu$)
zVdLtX3YRxeU-_Snedaue+Ki(~zng1gbK?J+Tih@|+Hy%&>$A>^&+{H-1e~!6_><jy
zLecmO1FK2qg5MV=q=)$}llstH`~QY6=h1Xky%kwXhQYHs-%nQ%n{4nf=a{i}j@zT#
zLa$X${9a_lIA1bMWz9X|humi;r`uOa6r@f~)%N~=TP;xH+WX{M!I?MjO|ejTw%J%;
zRr`7STZ;qc+C~RvRUcRtvt2Igc1M_vTN!Jcgq8I?*6o*rLYAr}Sw+v`JKcXbm;Yt$
z&uzJX_6SUF@95-PZF@Gnpwj&8^w5li2XC``rkD%#Z>T&~e|qocOG533O&fP=2Q0d^
z@#^CX&JPSfGdYRbc$Td4?mwh?Libnnm)P9X`Ts8KNSybLV)64lDa(DtzOQ`lC$6QY
z>t#)NG!hIxG^p-=!tjVkq-y(2sW_j9!Y7`~$-Q5AeQ)TBRq}f-*u9?hCweP`p@mQP
z!kNPRlehw(?%wU|T<%~UbN*Ece@n^I<>#DO=dSygBzWxmv>5ibRad%0{_c-8RY_Wr
znIP5YSss2RM*hl^Nw!lXR{q;%zc+67+os>G{E4e29hUI^?$F3kXuA5r>%qgHZ!WE{
zvX|zX`b2Dk!jkAS?%NDQ_C{UTtb2QL&)oA@-WO<Xxa!m1P_SL*%9-Sa|DV(as=kwQ
zNVN9-Vzch`tn18QVzzN)&sj00xhmR!(ORYZ?;<Kff81WB_x-}}Eo!gXqz&1ZHs<b_
z;aALIYufx`d4);%@BGd}-$S_;Hq#>~`t4afb*^Y;`u`dCQ&~^AnK6Y-dL!Q~p)&u$
zD(|Ssg>udeLZv0Q?U%h@myzQ2W*4j3w|>_MhGeEg+uN8v1+R|_3%T|?kUJ_w`e=4(
zl3x@@W8J$5fj|*E>vrE{L6sEUdFos9*L~BsZ-4yA!QJcZuHUAUS7<i}{}E=EIP&Du
zkyOhWjtn(huU&Z56T@xj_<m8$s(&xNShKZQb6KqY9fTAj58JykcO_bXzo;@_POtw%
zVsVhsSDwPS`8#;dyz0zz%9fj9x<p(*);;ykMUUq(5np^5e#ywLF#XE<YyRGa$HkvL
zu!`7xe|FZan~XDguGrgaGG{85Ze!PVZQrrx;qtiW880*E#r1RLI7dEgjByscI7{m2
zy91k+%66SpiJ!dLaMh-!Z|mHG|215^{9?t;@bD$}`=19kC^{M$MeQ;Ud39R$z?^sY
ze3#x8ezX0|GFdS>!EUP+8+Mtz4!bZp=kv65_3bvl#gA=%7{#J-%#Zs|<@EZP#swEo
z-J1R7hRx0V|KW@B9V_ns?V9;df70Ike?>Qb@7LpJzxK-L6US%0r&Et{Y}TCd!uNyQ
zr_6my40pdAvnx&uvRHj+#*)(}Uk}(jPM@HbGN&wU^2W3ynsJf^0kH~mFaP}X=<v2}
zan1FOw{F|tN{yJePHmO{TAj0h9vjD6Z&-9|Z>hm#HxCI7_Lq(Ps-7H<8_QOv-V<TW
zZF<D|;Igp$RqeQ4rn;UIM_uRZ?q?EKmzsU=-ZVwo-Wl!|5f>EaYHhW6#kuLH&HTR7
zT$Pz@()L%i&fcz-WpJ<+{Vw9UP4w;}{v$lIJ8xTF2u@e)d&AAo#X5y?a<uaO=?b1%
zC!1dLeETago9~oJ$Qg}ik-r!u?!BC<>B85#dWp#5#?7z1Y&_W(-l{0Pvt~+BC1>hd
zn@^{0rH%@$y&q{6_OpCu?9(nCtKzLyioscjwj4apypHMW=EQ#+vwlWaH5=rn`kXqp
zX1jd&ly|zzUjMrJB{Jca!WW+;wG@dR+TNNBaamin4y>OTp%kEUX~Pq31+#!@U;n=L
z*tB@**98{6*%tyzttG8%1vwt{CFZ=7@BCg}_saTQ@Ja^Xi(ZE}#~i#}wCSb6cD>#=
zt{gWM(ioUd^Dy$&%of}@SAMlv-(Inp$Mqo@LB{Lmp8P0xb7zTCdHkJC>1&H*Dp+pB
zetw+Px%$RkYxjf;D{`%t9a|`rmz?wCK<4ga7ANja;<>S7{xJs0{u@iCzF9b1Gu8TV
z=Bpgd!$CR0>W}nv_jRw>dC;q9Yj`g2ja%%0EAopkEE2OyIw~<OY5f$ZqyKivv1qV!
z{d!&A_T@p`^lM+1xV1%PKTsAgw~jgZZkO&dH<|Y81cQnY-G&y|V;*U-+)i9Q1y0_x
z+#F^0SUgvo*X;gE&|22s>DRd`GsUC(r=4fJW%|sybGuSfnseBe@4OfOXlJM7$L-0N
zx%DxJ#r&+vIjb+We=mJ}zxDlQwID&h_%oe5%96cJb67uKI2N6?{$TmTCo7KIaK~)h
z?LC9{MgQ-vk1`+PzpE~`op93qjCc3%1KvLpyBz%4*rUo!pNapt7Ax!*P;@g>?m*$Z
z^G8FMv?*SaOyG3iRdAu<?On_0o%yj7`HmViE*Do6x?J)ph_~r@Rkpa`A{X_Lj-WXK
zc~iG|%se#L^=GEK*q57DZ!$J_@7K0D;M#u8(qw<=^p{PWgAAn1bX$8Yq9;#qQsMfz
zIrc@y10Jir+0H5d7y^$O)U4vDI=TApde*}3`qgXQ4>X-T61mR2I+y93n*aO0$yPfq
zU0K2O?%I3)#SQ$~jMB=BPdDjiAIw_3@U&Cxns%==H_?LA5*I|7dJj6EUUaL|D(DLn
z<5FM0?w1z!(?9IltHgKIt=ed1Zt1j1mzb9=j$t;5YLnpI`P1x+rhr?e@UJbOGe3Cd
zJGp&xQRw@6W|!U+ndmV28_%*L)ob6dIj){x^0;;So8?RL7ylNL5IOUnX`NWtTNPd5
zS51@V9y)h@XGZtKTjs}{%&pAYV%>LrDEMt)`1bYL9iKI?95`qwHn(>2HT7J9rNt}W
zsHkNG=WLn(z~iCOjRU@WWSbUDx3cQ|eQV;sBa((0ueTrhZ|B+@|6tPVv%kgtx12uA
zmBy3Q*lTIhVS1yr<<;uT!F~p7W-pf9-S2kjXvEaRYqrhGvf#KR`Ce>>#+)zt%k19C
zHa=f_GU32og_`Scy_7^7MP^sTi_BcUXKnG>v`ClWg{(zW)-q_ep7J+48D%wdN&06=
z&tDtoq<pyJf1~ZG-9<UGJMoP>Pqx?fH)mQ@o|=_=Ge7kE*=e!6qYumbxu==GSid9K
zOjdG<Qg@2dW~IjYooCV%H+!DYn;YtrE|NWOe~*`N)G7=9*a*4!89Ax1S*Oi<5;K*F
zJIIVDoVoMp-0ICt3O|0n-1Bsw>7(AcWo}Q`v8`IZtUK6v-qR=kWwRV5{`zm5@TFo;
z@%4y%xAJbNzAAMo+*&=C|Nrm)mvRf{yWGi(x!AdRdW@Wxh6bwv-?f7uQWu?e{%~Zz
zHq(Sjef*CO|NmF!&$M!Co}S^fc@~#<O!7Q;aYL7~rirxt=G)fQJ1mQj@z2dNEm!hA
z#Vez*=DJo0v*W}IQCHoji2Yf&afwjMDet*^`<m0k)OTl}eAl>1VbT}B`9H57KU=@t
zOnIa2%q8U)5AfXAmNAfFHWCR6(S4HUbY|a-CY$9N56{^z`|dS&savV?*2s1f<;<U*
z`)fLNXI<ynyr7_7;rPtY)u;d7HTWL6bj3!s*r2OvtC#BE3cRZJ@tJ<K=j(eG6P713
zXu9*YZ7hDV<n<A?)Vr+K_cjI`o-J`J&Rw+Jo=Y=v*8EII$K7ffZ+Fz0W^B@J(rjGE
zP#(pm%Kf~G`<m0vd$YC{yijqk{=#Ru`ylhTrD2D|CG0)+bI+(yGt|C!xc8n}p{MGh
z539wiMW^#JO08P5UF6VX-q-)1FmX(q61byMTRkXX1K08;$*<(?Q#?;?J!!O5y1+u|
zQSN5V^&$UGRd+4mIoqD*eDT@QEj#?1pJrThT;a`gJ-O?<cF@EOkw@<=E+$-iA$EP@
zt+vHyzbw}fbzAuEs{AK&@y;7IN^7^xz4RsHxNiIEGrI2mWmzwrrcKk=VJ>rzdG^q#
zYudEwncXu2*o`$`D@QMP_Dt&ax|4R{(v?ZO&O3Z~I5WGdM)|H`+}X!B^<`JrU-|yg
z#J<IT^-3qDGn?kV+H?M0<|VZiq07}P|E%$;^-YhQdvn)G#*cG_E(Bz!7K>kBRiZy}
z<1Z=B)nCndWB=!^;a*|+WZMM2TfS!6d3*OBjuO7E7&V)Bd&j0*yybe_A~~uDPS$EV
zZ;yZ1k<GW(e1`8YFZGg{-*@kfauSwZvs1FYJ>Iz?IXmH+k@ohtKZMOr2Gm~WTy_1#
zTi?kc-Z$?~y?)o_DsM{JzU88aEO}yucg6^RVPCPq++aua*M+h96&KqJ?-)w|VsO5a
z>}+;-mGG0xHhyJ_^3nz#f}ivR-_L(kebiF>Ua(o{qm@QkaolWq+t2U3=TXhozw5SD
z>^6lt+eG<PERU}06wC3v+Wmgs-|yS?=k2ZkyZ!y5&5J%e?YL-o<wXCdn6(={3!`*|
z-yT_|cD8BvV;4QMgJJRe>OQt?b?sFX-pPA5wc^mBm7lgRo}qEWV*M5c{uA0eES^ei
z&}A1Elac-ZO?I|YsZY50FSor`Qxwjyi7eyU{q~i}?qnMc6YmYD*?*m0c6slUp9MzS
z{+yq~GkK%sg&H#(K9z|FXLwwg@uc#OTZcxF&c;vt8|BjsG?GhV7B}{7l)4b=bS#Bc
zrL|YzWapl)>;kutvpW`Db35^J%c?o^UVJ^aLL#`v%Y4zjLmiP*E%o&{M45hlx))cq
zXV$z6*Jby<FD}2G_WJ?fZT4-4&4M+(3ZB`1J@l$2<M_d~&Z2j`OHwMh`WX85v0psv
z6ms!5?}pXZ+jvht_DxJydY$ljYGYba#;KAUdBOi@+<UIDOkinFpW5;B_q$dICMNTo
z+LTr6G~vZD!K4zF;0nLic`D!EPyIg8FhauWNI;Xy!MCpqR!=ChjJ~w2O}xYEOwWXc
z3gXZ0KOgOp+45iqzw3_lS<K8+Z_L=P`ck9t>7CZxpbJ8uCX46q%e79MI!P_!(S$GU
z%C+vjUxa6c{Ev<1Q8_aI<7&PgT1JLzFVwT{J+{JgiXca|-|q!g_jeb!n{~Sw?7QK%
zQSjo6;6u{eY^Ntj8oEqoX6;wK=e9Wb+~z<#mgp5zt*j<6q@8f?YZJSFEhHd0tG?}O
z^ch(;rnkNi3=Y0o#H(B8(8zK+cb(@VPJ3prnpYdlb{nxqUbgUl5%y;16N8v)g(pim
zdoJyk@BSzpaC>#(53cvK8ojr%pX=lLwMkXubc5W4RJB$PX|<mkv5DL_PjJi2IWOF!
z!*yawtcXa4+2eN$uWo+ugwg9z!!4a<<pH}^J3MN-b$+t5NS;`ySwQ>mSN}w>Pto_g
z!q5K3!v8@O%W>xNom-U``JOyx`J?B6sjb7rcQR$|8-CBUYwTLPMX)Vn+XBHB&d(R_
z^evoukZ=F28*?q^>|M^xXO#Q=X|#UBoOyD5tmTI{EAw&h{jlLe`bzmj^@|JhST~7z
ztL_#z6WZQ1ML&<pvr%NRNx_NR)&0fB8MVI;Zw{|o#e2s1q|%csx0Acy-Tj=ywOie?
z;De0af?UQEP9;6sMeh@W+b2%gJLQSUyoi+TYgIj#T#w?oJSn}p;jg0fDlKz1BZh?`
zoI1*n`LFaXSdnQ`JF97-Tju5o8N1VYHqV;)NlW|U9@a-UCM{n0F5u9yS#xG9_FQn6
z+QsZX*Ii;Km&?lA6T4))Yu08R7wOh4*DE})^uB(!R;k5ouVmA{#aj%eq@THzWb%Z3
z5xqOJN7F$h?H+^PA&FZiI`b|{uaHTQTs=4L%obTqn<aXaYpkMW<uYAk4q7G_Y<qv_
zEBnPcy!<Uf?|#klT$Z>vW_vi#no`wYOK*y+Z@lU9&!)KEPwkTCbN?*Krnz!u(>yAz
z*n|zNLN>}O=meE+u>NWs6{Y2Va7l}!&x;eB2@3)@tY}e>7FFp#spS6cftu6u!ZP`9
zmR?`|ug+g}bVHr&k+<!4r_JDTt!}%z;^5|-bhFIO2h+IOZeF$&TiiHlj=Rf&s5L1{
z61*On(HYCV#2MYQxK;N}wBh8^sr6fz)qjNZycc7`&JX{aiu``>z7hC#4@Yg;{oheS
z>@7|y(~mhbAJ|x!etxx_Z2kK3cMpwYO6L12JiDA^l_}YDp5^0vZsC7#R(=b-a=K@(
zm`|Hl-M;sZ=g-Y{xW8Ab#MS6<YgEnA%zI5!^YrE@Xn&l*U(M0kSIb;=IqS4<zpkh6
z9&L@A2W^!3zifWK{+`YM)4Lyj*T2Vie{V&e>`?=QZwD>xJ=*T?t+xB~@M!efxJNDJ
zTbxtE@|$(}UgoAT{uPT^aFyxm)mW=G^<QnmVIMOLURXY!dLlMvYwy+QwO6<3@Hy&t
zolbvZbhK}G_Q8ym_EN!GM)7)I?y>3zK5Nm>QheOn_ek)3+&}XwtJKp;`wiBu>?+n5
zZx(aR>`prqSK%(Y!IAlF*(bKCb~V!<a(GT$yuB}RS4_paYOA7u0i20PPb}qK9c#+?
zO}UcAA=;_`-~8mdEvC^jU3a!hohv>3P+Np~#&yol^NAmnE8=u@_HnezA23<?@$8P8
zeKA4P=6_IDzE!`{?A7P}Hg9V8{@r@+|ECup-*40WfBNz5Kl=7ZpI@K!|LKce8}fwK
z*YEzLfBX93*KBrIf5vai|GfXsv-+Ka|CX|xdz8Rc^m@1aK54u9&v(o7<5s7a^uDv1
zyfS{?D(7;;+g7(q<%)hue1Dj^&F0hmgKPZw4=;c0x$(U{YiFFT_ndb2$&uTRO!_cm
zVyZfy+=|`yfBe=y-2L$PL-X_Z_6NNG-M_7BfB65qr42U!zg?Z3{{E^UXH-JKjLT~7
z$HRJjTh>oAR^dGp&dV+Eu6FN(HwWDrldhkZ`J(Jn7Jc%5z<JMv({F;~%$l|^Rkg@m
z(NMT-d-rJ0)P|W732y3qs(a6+ahxytc>8+&Z@z>V2CwVHC(d`?f9h#Y<BZJXetx}K
zihn=65xufbYK@o2A)nI>o1aN>rdRxDX0Yy!uHCX`lZ3AJq!edH*5+e5RUMaG?z)(4
z@nYqhU4E<6ulmT_pnG#wUhX{nT5W=(1>dgw`zycN2W)vCw%CUIz&ow%eSaTskEpu6
zcIOTI73)5~dpdt#_2*BspDc`aSJ(aU+Ow(d>zli~r{CXK^N**<RA`rh`-7D1NzVn?
zMGDn*HtGNS^6jYg=5^cVzUr1KE(r^*{q{>=KmNbx;@=n6&hqtN!`%|h|Ji%rpZ^^9
zRVtrcnSJxms|j;Oiz2(1Xvf_b_1ydW^X=*D|2J{iu$`RU$SSpSiA|75mxgYR(1ZJb
z)Oj=u+^@2<NVC^k&fWJ_>yUO!?~%U&aW^)y`JawlFIGEKVC_LgCxal#S@YkxY)H7R
z=;Y#lHTm^ThBwu-16I@|T-~(6L-NeORx>}L>v}Ouy<=~9{g~!9{ffDFhG)ahJio4=
zGT(Be-F!Xw%~-wI(ne2ly%58)-TWJLFZ8WmBkj3{^|IfE=1-5k9Ocx1W-SS;Tv#!O
zxBW?sbV&V*?FaITdo~4~EB>15+9th0!}26sa%)tmMEJuW*&l);{_=m0GB|Sf*p!&i
zz*NIfp7$cxC(E&WWbJl6BouPP{aD2Yro-QuQ*IWWdEg|JW0A1pinZ%(GedTsZF(6o
z0*Z`=k%kuAy_f1`1o3X1a{17UM44Wd%S$u7pS9hJJ}IwXvP~d)=dzZ{Z(D4%6=qL(
zWxnk7(cP(Q)_Di*im&(=oe&s2Y0ZU+vb}x|jDD(`3-)hIz2>~WTx~M1Q_xnaU-`D5
z6W{FZ)691}ab=%>VS75aDyQ5dm91P?#U}BJel?r^@r+gZw#;W|{!A$gU%bK2Am@Yc
z+^K)JdC%<f`LuHL;-r!kH*eE9i7}}O&Og;t@*MN$+;H^DxKQ=@B<lmI3I29@uP=U?
z;l|#q-*vHOs{U0DMp-8J(ASES+E4L>_|~sbZi`xBFA%@+z>*xj{|0|6SbY!H+IW1q
z%u~_&)V)CPVKL{nOZ-3XY?m}PKE|e6cKt$(kJ96#mSq+jzKVU0eOK1=wJ%*cY4<EQ
zOEdq5bLKhzGxq#xyT0$7p}%$-pLtA8UFM;^2DwdbCpBh!NX}SMv+;!9AJHX?nSb7R
zXmiL=*4*Y+_h}Q4gk|hK+wQ1d-rIY6;pWMj8^2zecFb+z?RQ5w#ktw1mkWe#e!`OF
zQvNDu`BgTNp9l0DjM*yUd4lH%Mz_Z*g?G12ZtBq5@>oRm_TGhB#eC*@zc*ZN_DFoU
zLUpck$ytquU)mjG|CW{ZepmC*dtP^1(slMZfAPKj+qC>eqjrC9UMZ7)`pkS+S&M`7
zk4}Hlcbq-J=>5+rx?C0wueZ5vW}RF4(M@u(`;Eqpm-n{rVovw`d}Y>G9^*3|8i|^h
zd+yt8TkI>*A<O@G_xszQ8*T)8M4HSwd)0FN5B0pjUElp;bnS0tZ{U8B_<+;7>cdUz
z=`2&O_^jQ;xiB>?cC+nyTUSndv2@{kU57NM?~x9=bYk;NO}CsKM{MO@veqOzxGwTu
z5gYm3Vd7_ok|o=Oruz#$Wa4d7);X=uRUENXV(H8$JRC<hd$2mq?6|!rGqyqS>&=-_
zj4TYB=S*{#*x&MM=0xMGyKB$NhPo%snW!do=anoQ=h8y~dke|}olT;qsrAmY@L9n;
zTQTr^%cBC3D|&1j9%kr-eJ_r<pX2)I%DLzJHk{eYs<g^y;jf8Xu84Qs)afkOO*5Vm
z{MGN>R-1Vb7CTE{Xmt{p!JErIzbO0UJBE-6%T!ftnihzz(qUw4=+0TPU9jZAiAHxx
z1sApKtDJdip;NAzIxRij{jJ+);{6XEXI~}Rom{rF>}61j-CW<3DH2!sx49Huv%G&t
z{tM6l*_ywi=ZLEA3p_uUZNk=`iHmpKZpm5jAawhqBeO$Ro-}(^<Y`m4h-;zaS+2CN
zLR-4z!;dn#y!)DPMr=u?=9*VEo`$tk-;`hE=(wkwl9goL!WCS4;IBn{c9>`F3)>%p
z$|qJiH;c(M?V6CyW4plaT)9u|*9$z-mqa;csyy*d`1Z#AQ{Bch;zf-vo6WLKOuLL1
za~@=3cw=IJ=9~Vsf4d&ATFK~g6)s}SJ(#md>X=f+{GOujN7rtOoXIUv7Fsdw^v#;S
zCL4*lx=ml#%vMxA*q8e(qik82(TROwi()duxS~)0do%g&kH!j5`Lrp#2Ol{976`v$
z*1BzhO_x{KlgpyrcY>XnvcfOFJ#cQq{Bw2_w*+03Sm7YDAfRZgmEgrSIUydbdqf%p
zw)|PQ-Nr&{UaH%*8RrzzrHjJmoPQ(JXQAiS@@2z}Lv0*+x|dad@;rOK<cDd^**0tM
zD@9d(T6WbBR6{3PZ&5#5v*O%`n=I4b3;b2MP}F$7>W2boUb|Re>W=f?g0JtrHoUmS
z!fSfbiQb0A?RDBee{bHtK7QZ7%fgeo{5~3(JLWge)ZKUMy;9AEyt8WBE|2?e3-+m6
z&pDHJ_0Pp8H37Ocr*>ymzdslDY{HD`7hE<>6La7Eqb=hx%c?+IeYpoa%5_Ed@NJQP
zT(i;X-jgk7t8ViDUAy+J?RNL)Hw)&RpYGmRv3p(YooBpf59ggvyu`w}|92ywSV@GL
zdtQTyOQ+X8!<8?iJ>K>UT|Bm6`i~8~_x$<tGCs9SZ`TU$nUN&o*)n^>1LGp;>AaHK
z!RuA;3S_LFCcy0%%+77ndaFKx-$bM(QgMrsdmzj7<hCQ_Ic-zIy)W#^@K?Mlp}}}X
z>uz|@XQ%Z&n{&Fh%bvd3b!{Jqo5b^@3TIE{9)EsRA)@w8)IxJUwc8(0C^EI}UM}`(
zU+66<j|~^De(B+w@KnX=nPOH<+GKwP)5GsrZ{M00wdU`h-FLT3vt+(JFyCEqEtmYF
zD}2mLm;4FhTVQRoqO@r<f1K%|I?Jck7aHF7w{_jM6w>^-EXcF#rpU68y{;A$)R^Bs
znkh2R-R1nk`g6x_=&rbZHk9={hj$YDwgBa$d=od6@45a%;P}0bhp(Cb)nvJ1FPdCn
zD_~@$Zo*LbFnC+Rakt;>>}L+@6|TMW?D5If;$4@MT>jqBbanY(^wmOXn^gX;y^NW=
zE-kTd$ewF*Q%>g_|D`7n8{WrWdUCPBsiTs;Ofbo}&pYYRGE4tbjV&J(byZjPE_-HY
zlcslYl}te3?Ijm=tS=UH@Gx)uxZt;Vx{8IyskWMFy6qN;hZEKbFXFVgduaJ#PL?@J
z`(o{;9PUtanzZPG(+Ul>sZu&_i&eCr@J?=h6y$CiYGEo;aWOCVPUI@>$tE1XZVG<i
zIaQ}YKc?iK_1iZKeyKH;zbFi<{v}Wu&2?X7@+mdpKUzB^VtlQnvybNS-PSr76fZI5
z*RxN~tUm8oPc5)gn&qSOobT{O#f~Ly5<AYWG7)F)n!c)0l3lu8jBWJ-_8jY@(X(fU
ze3>QI;p1@8C}{S+SN!Xldo)C%8Rf%oN?6><==hZR>=Ww^=Vf-%n@y7aUHE1?uD$#!
z%EnHuwY$DGQ&RKPs>)OK)z**Fb|t=be*f+XM~JlKyPC~^AJ?>awR>!xw_CJuaq)(^
zalv0@-W-`Tb?r5SmaVR)Iv3jQvo>vuGQV>7s!a86du#rxAC^B~e>Xidm#?=-jCVVu
zDf>Rx%bb}#3)dg#P&Q+J8Bi0@WnkQVdn)Uk=P#aJm|1xBkb0Jj-I;=(Z8Kk<F#nP<
zo690!t$XU{>SZq?>=@1_Y05Wv=Y9}4llCM(%VYQM%+$VDvU2;5x_$g}^RxZ_8;X<5
z@+%%bFt%+;ZQAqNef>^F-sSzQtGt`qYxaDVU;iw5YfAI+ItIHcul5}bMz2ISdMCJl
z_~n05x+Ev=WXu7DI-cb@$LB^>S%j>~d9p`JdtvHJ*N7J-n-)Iu@Y=BJhN1Kp+vdk7
zMRgv>Fbn_BSf}W5VDg$6sf`wV7Hn5m@+BQhT~+UQqABUeyT6;iyNFwr7{_0j!J#3u
zxp#3}BWH!H=ee0dv5mz)Ely6{F-3FEjS^$7zn#nM_D|aBA`qXNI%&CH^vyq?nsx^4
znJ^`}^u-VP3&zpTZj2%UHxmzftGp1oa69#oWLe57cXsEA5A;r)kGnY4PiP7AI(<o%
zxkrrduqRlY73SOZ<Co;mCmM$mC)#ba$r26jIiu`x;OWzQLc#$P-*w7NbJ<z3O|3mk
z=UM2=iF+!A7f7c{HCgFY9S^!KaPC)pu3&^`sh^zq?f5KhA*Q%}Jk2YAU6?yv;!5C@
zj$?`@j2x~X9A%T;|BI#w@;+JI{3AlZu4R>ZmE`HI;vbv*Y&R9e_#ED*b8Xhm?Df{x
z56YxhR0vn>zUj#E=O{~7<KpQtn+wBN&Yh7QedyitLz{cK7QL2wBly!&!}?2InoN~*
z>gLL&ex~!U%)9)mRDNRTGVVir4Hy!AWy9Te$p4)do%`lL<E_rcNpsF`bBjN7oaJx5
zT<FjLHFy92x_J2ii|@bw-v289_uWV5FaK}u`}+T9rk#1JeSLA--@fnslb@A3-c<-o
znEc^+l2P1~g4af}>i6%|2cAn`W7Yatz@kE<&*_`v`???N?yO=cZH|b&|M@waZ2dkL
z_Vw?-eNOFoxXaJp{Ke<uW<7iJ7axlsAFfOOlQlQ{T<pubj(LWw<TG5jyyq%MZrrDn
zSSzV!`snn8`vGBkUpdydhO+Zjd#YRdn@#@L{PxM8eZM}cS2P%euW)5LdrITI!-AiI
z_dcJIS37yRan-tik%n)+8};tp>2zsX>`qe)XYXZs{|~0gzlogUvO}XNK;)9eiaOil
zb!zo34h$#FcUmpeYZ2;b)z#i@v5xir{@R~+H-|fa302tqPvvFz_xpd&*3VYCy)OIE
zX;61R{?GT%;`;k48^!+cAN_s(d>lV$+1>W<*A{D5s?1f1+y86+!`avM+w5(se}B3u
zAHO%?z5MPv-ShYUy*zr`yuSKxuk6`*C7OXV_I|qey)s2E=KbT}i8Y@e-G2BzKi;NZ
z^Uvl5TgC4lkJB{Oah4D-`B&k-_}c5r*0{Yjf6sQmZ+{=Rr|$cwzo+Hn_WhS<_*xzK
z>gf0Par>%1SN(WC{r;Yc$0j@Oc8gSh3~ztNp|AZpTe<z=@ygfh@3*tF{k(n8&NBU5
zUs9siC%G?|`0mst`tVK5=?$y?v2uoQ2gAqOH)6#Pc$OB2FeLXnTC|B>VEHonbK*?@
zi<`VBeo?TS#gu!kepZ=P*WS-ZANNHny*jgwPxOUZGh>0v`wxnm`z%lX>J6MOzpIIf
zgHhk$bLkPI(*-=$46;i<$lG!5u7C4-L(i<JGULs^wrn{$U2W@+42eA#mRmj9>%3t0
zDZLK&&<umZc&^{t*RC%Qou}ej(bcVY)kRaR=ACB9lSdc1xT@Wj{gOygin}YuG}kki
zdz;2ftydd2F7;Mz>*;Ijz8M)AdeU~u>8$R_X{BqNjAr+Q2?so>nZtk9)LYvw<WuzQ
zsox6seJz~l6}_{hYThiJ$tz9o=Kg<X-*~uo4!7Kc8#g{4nm6z9+!N)E(sTFT(p<*b
zP?f+qlg;t9g5=WNdUi>c))$P4hi^@9%sCO5dxpDqWk^;hH^0`2&$+ITHB8UCS4L|6
zIiQfty6t}0io}mck7!h|&#E&pzPfDggN2Ki6|(#@I~G>%V<=cuyVA|=;jJR?!&(74
z$4{l~n49^NRno|PUdSPVhy@M7X~)9Wx>y9vS6mno{A{^v_;#H|%@f<Rt9%kmmudW1
zr{-PRJfYraEAKr%cdyNVB$=ZVV>wPX-xh5*cl*aBuKFa4=b0IMt5qw*+E?CeJuJ-D
zG0hPbmy2b02z)=JrkNde`SaPj-J5fp7T>PzP?~xy>+!8uD^@KN%T1r2wQ=$OoKK?0
zpAWv=`Re$xioLx1e}6fyzpL|qDT|u!ZmC;pPSbt&FTOVYO#Kpfaicds9`30)<#J(<
zyG?$#jIGQIUp@7%!*ZP)e*8Rs@OWkU^!GFEzkFkw^5yl)_Q-#QmqU)Ojz94&EAi$X
zpKVX8+5IQ&Ua41n!}#Q_((VZ&-y*hT6djD>5IWF)$i(8Vjo1de-@5jmn-1<>TlZd}
za@HN|4GJcYo*m43r;z$OzCfgId3)lDg1^5^CY^e4G=BbyW7f}Y*}cw7Gkb-I^zD*l
zE?vf?@m(#MfA*FYl8mLNn)n>VcfIS`uH52klM<jBDEWqmNv(I9^0sBV>EfBMou+*(
zFYmn@f9lX0y(Jnmr){c!<~4D_MwY$rmOkrdllR#3t5;Fhu{BBH==FK=tUMw*Q<rQp
zh;_OY+OT)&wBV(4a=&PwZApIUAm0^`VUsFz=gqwxyc->YX9=r6P(89t+<E2MMIsYV
zAMcBA$Yon&t)aKU;EDdpgGu-2Y<=rD)mQ)ACho(2TG0|0{<^ZPpYkm8_Iu{9JjwxG
zkJm>!J}fC?yKS9Qvh;|tK?d(d({DFtOst%%-P6>1u5WXw<;L1C$F9G8wyx)POysKD
zsxHSZqZ6~-*<CHNUYF;19^KU|%a<DvmRmS&?t=3YZ=Yq%V{U4a%6|P~(Gk84@v*+A
zpJtUDI_q#FP42Tbv;WeIe*fP8SLkh;ATX)=<l(y6aT3x0mQPS;ac?mAcCN{7)eb&=
z&sl|&mo&{6*jgE*+G#9Wl~Jn9RHka|x$cnPq}2vfmMD6!Ow_WAmYmjIIAyB@*JN*F
zC$+Y3bAuY|R{1X6t$p%l>w<`e^@`36Hl4GZ>(+~}7c1!Not-3IH=$o@-p0mD;tO2d
z`FVUNHyLi{JF`;ls_ovKE1pr(K@49~#Z396=kNV{@7=>a=aQA@zftS2Ryt7BD#sO9
zrM+(PvHI1^9~XwHi*8!9tgyavw*M8Grq@!x!&d!|**^Q)-exnFwI*Kd>kGsEZh8n^
z_S7zY>F{NmLhP;sB8D~fYs0Rz|BDm<ucf)-ZlA}CIK?9e+LrLP{ETn%$>Vq?uGeG#
zM$__+g0%3?nRj^uE^XcOUW#d#-rF4u1@r<;|F1Yb+hC2=_h~aS_xmhhYdsQD9{fI2
zC%|(4wsIexhgG)EOl*DMroC8E>ZJIqV4Ck5u}eym-M(!;9FiNIwYw>ot4wvP^vqd%
zbRXum%odo@DqXhnyW(cvk9#)U`XMBCW!oiD-WB#=F8!Owdd&Urfp>FD>?N%pPW6_R
zWc(ifQ2t4C;a}gtP}A9q4=;XhWf87i$d|Q@S=H_NV=sr9$BuvWT=gN_Yf0;hf_o`8
zK6hjb3|N*cKHUG3nPF4Goo2sJHS6XvrL!Gg#5t{_)WKR;(krQ4vi9=p6LVFoB6LM_
zI?~slD4!x-uWv1(sQKu|D_N%6^3SRnP6yW-+*!%oFxNX`@9C)N##Q2`2i@e~e!e@)
z)a=(Hqgi{_KU-FG=E>ca4%rv|?Ed!Ys>V9cdctn@)54QSc?Bo8)3qb4L3=Z-`J!)p
zY?%34Wxe&9$ya=zOio?Ky!eKrxut_elFMI5zo}LXCwadd+oH$hn^`sK(BJx9bCzCK
zoRnZ?#bh3O{NT!%xyybpKU#7jxPDWySm&7!OXe2pzZGdO*=WvET9rO?{<+J1t#i_I
zQsy3(+i_$0T<2fLr@qG5t$We9Z_Tq0;oGM79$$I(o_JQp)ePR1k2PzK_D!DAHuv89
z<-c!l+T-ME+g!iB@iqVV$O=Uf_V}$C#{#U6Y&M>ia#Zt~tV{oO=CD;+$;Hv>r*^;F
zp*}Bn+p^iqmxLYNAJcYh!LmEc;`d$OaA=v^VvC%Rs?Q;d&tAT{;o7q;i=!X?-0kAJ
zzTD(}_=<e1?k(l23~WapPAwF0NKlQDY?BOX*m7UKM05MWf7|}4eR-<Gpk5;t%_Y`4
zk2j6qs^LeQ!>@m7ORoK7SQ@{ZJ)&@SO2V{S)5n3PX6zLl*7sgF+~NN8uCI03zxxx7
z%;y9|t&-=e4O+B<$-i-H$DN&X_G~(uzI%DW?!smJa-<p?Fa6pg@ZqxDlkVK`kbAOQ
zgsvo)FP>Vy_tc|54S&{&?A$1F&2_=!u(>zOtTtOS@Krv&_k$yLmHEE_i@kw4w_l#!
zc3XPx-oW^Mi8``fCCZO(EU5{evHJ7JRV~`icV@oe@D5>d^4{@uvFD_|uN&^Sf64xR
zJFA{4)2%&p5o4%6d$UXb3N4rYKJiyf76gg@+_Ce@Ek3zVAC+R{edZjHb(or9$`Lew
zMLQ$&uGb%wtgb0Z{GC|BtjN?OkoGH|@7H-R(<heh9HGHm*bD04e7pQFU2m<K@m!;h
zZL$B3Dlg=FyUO0;@bU>q&M#x^)2Z&6QsB3+b<dVhK5LIAY`E{PDwJ2X=h|MT+sh7Y
z3vTF?+kV3FXyP3u<%Vrt);Dy%Fzw4LE}P%5a>6wCs}^PzOdLl_ix;H(Y?6$wxvjY`
zHZbOEBD3`c*)2Yd&r9Ask7oJ9Z~x}IXvg2&Gs{=if3+-*_)s>x?xc@5e@@={ny-el
z1GL1`^F+kBR2mxcS6MCP2+7~@e?iKzc`s{r3q-H)SKQ&cME}~w&Sw+4%-Q{OyQQaH
z`(@H{x-m&>)knQ`tY44z=orei`ijpGOZsXO`D$j<tUAV3za;-J6%6~pCiUT2k^8=z
z_cni>UR77}&*Rm%yc@6I9@~2__WtYKyRY9axL*4%WdEw`+Z<}w@1DB%-j%&&9_OE3
z*s|sNedb!Z4KCh^yKQ~m^lWeTu`Ad4St6&hq_vd&X`jU8rwgtwdc?n?E}HXMhvA>V
z7Z;7*bLd$4{amM7$Gh;a!{IBglH2?AE^NGDmYcrow(Q0!chYX<rcavF*%J6k?b6J3
zFHGv6bs2to*R|^IhL$z&bfwqdeNcL1lXud_X|9~Hd$S@#CxnZJzrMD4>xWX?_`?}{
zzwYrBc;0WrbL4hqr@e2LUU_qK_T#7b_7;b#g}d8Lt$FlGr%&9Puj@haJBc@ZtJoVK
zg|3rqF}2Y@w{suE>h)<=ccs&+nj2Fqk9^!?D0yeo9{rP_?%bN5TD7RC$LulB`r8c;
zbC39$v!9Gy_xR8;fAip;6#j{;U;J3)Trc}H?7;O^A<5yMmmklt%Ts-yrk19gl2fYu
zR5GH%<oJq?$4ZMYym_#^aH5(-R%5QE`xK{0Q{#CF*2_PgX(_M0Q+UR<cEa1~x+gEr
zcN00IVtDw~rK6_p{o?)0R@L)quX+Bd#<XEJbE(+h!-wClm%n(ht0L~{MXz})n}nx6
z<i2yZ_sI0!SC3t4PT$7;V@2+%s>dH4uDn%Ca_lxVn11);#tF-u&qV}0{LxVJx7t|Y
z*^-m<noZOklmw#|EU04K>&4ZeGULY8zyIDbtO@)QvvND{%7e4qSw8Q+|GoUHx2%Kt
zoXzU<U+lU3{JGT$o~CmXkLYRn^-ui#c$e^#=P&Y>_$&BN?9t&?`nT<|_-)yWr#k$_
zJ13Y&-=4ZTbiYJ)diHO(wCw0J*S=j%%ijGmC%1ZYXlX;darEtTIl1pYy1h7mZJTxU
zZJX%Z|8hPGnVLVS-ErRUYQhTp0?~7?)P#SX`MAo$XZgz;Gt4LbV|yM`$Q<<9Gqum&
zqO8RK%534U&s_L#|2Vu+s(<p{vyDwGL5B@b@u?qt6S2ry?APK%w*%cO(m_9bFShA-
z)-<>;lxLTE|DZ2T^z?yk-#@F~(VZ*y{869Dm%jmr7ar?A8+`jvL0d^p8GCf__Wa2Y
zq+U;6Wpz7Fb}!T0v$`g^zISc@-YQ#Q<|1uTy_22mNZkUFW3{i`W#cuJ(#~{W>@0WB
zxxVVQ!}+M)zt{hor?_Wc+B_4UE{WiWNv|t>d4oC)`_~*iu=&2nJJs7)Ew<Ktc6a@@
z&1sI>>MdI)KI99o{Jk$U>rwaN8M*Dur`Mc`IyL{?xf#DE|2-qoyDQ~)vMR4wd*Pwb
zuk8PJyp5QfX|UuS^Ul94`G2grEKg09_;vcpEs4DFq#d#eJJPPOtd{uEl4-!Du`TP!
zs$<^r0yg%$OR~0Ie4x4@^7!wMpEjJGrug75OZdkh0oA6GA9>4LzD+e_W~u1pW!!hg
zgSnC8-F@W?Yb|tKL^#Y=y4o1suC_ayHc{}Ct?3!B@EGYBcFqm1-+wfj`!%j%l#9)q
z``A{uwP1eV_azq`?@lpiKNoQ9S9s;hgi29~Xr8Jz4TY#*yWZ)gpZR>lp}9VE<CzVM
z&pjxJmlQjrbbk3l(M`@9R5PO9URpl8_V>JX#=fPyc5Gk&ao?pqsmku3!}_Od9?0);
z{qnqYHB-uJkM@s`OlA}W@~=^}(@F1Ql&Nco+^F$kul>Fy`M>@iD^l~>x|U~6+-?r{
z+Dmd=*2%eb^L!5+7nM<r@>-_CT_V@CE!OKyeFW!%TqV!afUOe`?=V=hJnEB)*}?LN
z`6}l&y7*ttt6zSDb<?Y|#p}vH?YhFlc)K8J#o7z6?oKwzeY~PNL8kmSlX%%=0l)jV
zELL86b@@isqMHJ<#T%b4Q+X9~TRii#l2X{)d;`DZwgR#_rdvLlxcO#WW-)6_%6jte
zRL1UmjPG>h_;;u$@wy+cIcsG1uI#VrQnmK|velO#pJLdyBeJHGb0trrQ`Z4jb}PLH
z-g^CeH>rg;bKQTdDS3_Q>xBoBm)Dq@u8B3cF+=+Ht;XC<*=zUAT4TBDij#ACM1I8O
ze@iT7rd?BPIk(hswb5hkNgQ0$vk(57RI^R(?4(uF7m73b&s@pcYiM#eEKvKr&5si2
z+f&l}lrBuSianCK&t}%b#~~`Gu1>R+aX2F(9m}?L;<3WhtBgD^cg}mXIrH6>zMIW?
zlA2mSBi}5o-#G13ug~1gsascWHf8%J|HtcX&D%TMC)|nAzE^gn;`&y<uel+v6Y|U+
zeQ}dtd&GJ5O{dS&iAvRMtHo^EgZ{7|`2O+!Tamvx(<)y^tO^Rb_E+Rl?OTZ-b9S>Q
z$fl@!2|Qu7zjE&1UX$n`p(c^fhFPx!CiGU`Snz+*?fRSu?qgSrx$5o+?sH!5|8v({
zk?qN8b0nPhmwvxHJKTQHfdzj4S5_#W)jFb}))bp^Y37nW#o^L=ho;K>*{Wyv=0ULP
zkzIY3ea?PcRbKpfl(96i^}6@m`@S#Sm0K!X7Vn(uI{&QYT)zd2r(B50IJEh^UASz^
zsxx{wcL@LN+t=bG8+_HsD<u2YwUAymj@^B|Y9bk;voCMcxzamTD8X#GXsV4zz&ZVA
z*(Xa<4aDAB-m$)S`A@Q|`{LzxCjPk>J9m8Wbn^JHsrt5T>o$|AU*ht<g}%T0{Z;J6
zGR8I9i~&tbNgujyWXtw8bGPJjFx*Jm($jKiX^LXGTUNXIs)-4UABbfsSf#!3bX~Z<
zx%p%H#Qrmm0Sb2fe($x?4(UHWcQjq|Z0O8z<=9yQHFJK>3V!x%>gkVXIE#gzC#7e-
z;91#}%OsHVNN1km2WP8@{CRJ0r0>vsX>rf?vtR6*$!QJ~uZG=T*%eyu89Q|e_tm45
zBgAXHRj=yLalIsydn<F1xChIZb7zdpXMKNkQ2v8+db8^B1Y^lh5!LzMqW<ZAzsmT(
z_Jc(HTv^e{GD&O+wRYjb!6)+$J<rydZ{r&!<agXeDeuz7$<eF%W_YY%<i5-?V|vS5
z$L-3G*1h_{#x~hh;`7}323M~>?c4kG-8*Bq6TcGP=7nxt7raK`=nBcb$%jJh3cBA-
z;OqBpn4`4)I`3EcGG2ZEpT6M^`Ng#wTTVYd5Z+f6@<6_~<=!&MpdE=eFIa+(@5pty
zd;6X2jm%_4rvBn6hb_ffocAqD!gD4YHfB1@pHJOCQ95VQgG&n;8T+TK`?u_xZ?$pN
z(%+FW>tc7_wMaQ_@~GU_=)mOjvmLw-yewX`Jnqdeon3*FCuWB!IDY(pxG<$??d=~6
zZr?9z(wPx{tbg%Z)9Z^p4c+x->f5Cjlw4{Q$k}canwju3&FkHwj~NHKycrK(UA8N$
z)>|*_;AO^Sg|xc?4Q)#Lfu)si_s>^3cQEn65s|wqXZhtnGFY8)W@|Xd%2x~~FN$8v
z`ak5+zq-xwI&YR$(!8IobF=jFLK0<#Y?Z|RNjW^c<i+B!^bSY6nzxYdb#wOPJ%5WC
zGz@ZE>#z4dap>Lk_)No_lS?-1o-i<(v8Cj(wRohAKx?c+!e&M$Hl@?TfjmF@H%$0(
z{EDKWpx=Rm>FzJ8uU+ET(OxF;LH5&}gO9t7Ui|OB9^HO$PFz}OR-kkL{PH>1zcK#`
zkZ(DZy>emZX=|gsOD3@ITD7G9tLaqJ82_L>w?BMU50CQnJH6ZUsnf2M(|P%e&ozo<
zuj*1VzPn-B{2RQYu1VKdi(FTGQ|CYF4e0id{%e_DCdK)$%U@}`{PxiG-E=TGajWWz
ztzKKXyv197=e_@=Fd^|%|1%|vLi>+zm8NNIZz^U`{_T;@v$fh?X_duey`*@1-+-bs
z_S-zQSbpX)Kl|;snpNt+!2|t2Q?9<xxV)4-i(%fHl$v_gs)8AsJfeQQF-EI713zCZ
zeWv_>#wCw1--ek?#c_g{#QHxrJKmpIxZ-%iok!nip0_Hw6p;K)LTKlf+qZgdR2~h<
zoY$K2^6r#-h3w0ZUHurYt8eA~`?O~t-|?Jn(Kk<CIQ7aaxcSDcqep}SF3-x$u$cYu
z?83#<7Cc&^KYf$dY|n<o-o2YP6|dN;`_uihlGbhZup_1tTu)iu<l9!ScAC4`aMk)f
zyB}&tX2|QMZr|HoQ2S!Z{=2#UYfo<6$kx#w@Vlu~q%2=uLb7I0ruL1E3va|MTVZ?S
zw6>f2vgx5(yGsPuXmTEmexk^;wv!=y``S2>HlMEnm6mzk?1gVjME9xnw)!l$e`zsa
zzdxuZ^x5m)KRHiwSM5K1aJS%@zS?Nsfa@O??V1sDPx*{EPl<=5(MK-c=B5o(rz@?y
zpTM#*iEHJvhhbAUopW#6_`t%zZ_fTZ*PVr)O%lBHOwMph&x@BUwxv5d*M{ft-9N<Z
zkbio!&eziocVCBn5mG*)pR_i0uV2OlmOI}r@7UdXtZeSz+!fmcF0F_<Q+MAyqlUfb
zz(&Uhjt!HpHO$r6_^st2N9lI<hb(Una8w*;PW^h{sZ{R3<z!jr7w4T@-TrPiH;nkf
zm8NFn_V>k%8-jghDlS`%4NTtVCNowTuTJ9<{dT<JuVHe$WxcgVX$8Nh_m9gwztT@1
zl4%Y+dGMN%TD#$!HPK05x$msdkk8LOe0N3Phj;pR1`~?Kg9{S7&+lEnXulF;>*4i|
z;d6Co6(wuc9&Q%+Qd*pFYvl~v%!{u}+Upja_uBlnReMM5p|-nzTRSYQ{#<`4cbH+?
z^502IG#g7)Lfe~vFPg7+Ezz%4=|+*P$()G&hKWy<kCk5h9_jw$(3HFDw6f!QB-$&!
zuQl9x`@8Vf^^?EuU7loq`~T!qj24|e2Rxq&%n9jnEDrf16u?`3;OXoQU&>NnzCBTL
z<$2LUjq4)%vyxpG_pLuG?3frf*G6wuN_%(NhBfo#rN8H@KM;SVD988HrDF!iW3_1$
z-kfNim=gN%tmEk;txK1+`ZeDBzD;hn`L}L9Ht)uSWHX)C<4ZZD7%lh|WZ5UYaXbHM
tE7Jj+pU?datA6kNd#5hXe*65}=ifg6R!o5Vlhgixy^U?@G6n$_1^|fSZj1l`
literal 0
HcmV?d00001
diff --git a/trunk/svm_light/installed b/trunk/svm_light/installed
new file mode 100644
index 00000000..e69de29b
diff --git a/trunk/svm_light/mainpage.dox b/trunk/svm_light/mainpage.dox
new file mode 100644
index 00000000..c09c7e54
--- /dev/null
+++ b/trunk/svm_light/mainpage.dox
@@ -0,0 +1,26 @@
+/**
+\mainpage
+\htmlinclude manifest.html
+
+\b svm_light is ...
+
+<!--
+Provide an overview of your package.
+-->
+
+
+\section codeapi Code API
+
+<!--
+Provide links to specific auto-generated API documentation within your
+package that is of particular interest to a reader. Doxygen will
+document pretty much every part of your code, so do your best here to
+point the reader to the actual API.
+
+If your codebase is fairly large or has different sets of APIs, you
+should use the doxygen 'group' tag to keep these APIs together. For
+example, the roscpp documentation has 'libros' group.
+-->
+
+
+*/
diff --git a/trunk/svm_light/manifest.xml b/trunk/svm_light/manifest.xml
new file mode 100644
index 00000000..00e23c6a
--- /dev/null
+++ b/trunk/svm_light/manifest.xml
@@ -0,0 +1,15 @@
+<package>
+ <description brief="svm_light">
+ This package is a wrapper on the svm_light library available from <a href="http://svmlight.joachims.org/">here</a>. This package does not modify the contents of the original library in any manner and only wraps it for easy distribution with the ROS packaging system. svm_light is not under BSD license and is optional for FCL. Users can choose to use it by setting flag USE_SVM_LIGHT=1 in FCL.
+ </description>
+ <author>Maintained by Jia Pan and Sachin Chitta</author>
+ <license>BSD</license>
+ <review status="unreviewed" notes=""/>
+ <url>http://ros.org/wiki/svm_light</url>
+ <export>
+ <cpp cflags="-I${prefix}/svm_light/include" lflags="-L${prefix}/svm_light/lib -Wl,-rpath,${prefix}/svm_light/lib -lsvmlight"/>
+ </export>
+
+</package>
+
+
diff --git a/trunk/svm_light/svm_light.diff b/trunk/svm_light/svm_light.diff
new file mode 100644
index 00000000..86410f3f
--- /dev/null
+++ b/trunk/svm_light/svm_light.diff
@@ -0,0 +1,543 @@
+--- Makefile 2011-09-06 22:14:22.363126903 -0400
++++ Makefile 2011-09-06 22:14:53.859177783 -0400
+@@ -11,7 +11,7 @@ LD = gcc
+ #Uncomment the following line to make CYGWIN produce stand-alone Windows executables
+ #SFLAGS= -mno-cygwin
+
+-CFLAGS= $(SFLAGS) -O3 # release C-Compiler flags
++CFLAGS= $(SFLAGS) -fPIC -O3 # release C-Compiler flags
+ LFLAGS= $(SFLAGS) -O3 # release linker flags
+ #CFLAGS= $(SFLAGS) -pg -Wall -pedantic # debugging C-Compiler flags
+ #LFLAGS= $(SFLAGS) -pg # debugging linker flags
+--- svm_learn.c 2011-09-06 22:14:22.363126903 -0400
++++ svm_learn.c 2011-09-06 22:49:10.011383409 -0400
+@@ -26,6 +26,509 @@ double *optimize_qp(QP *, double *, long
+
+ /*---------------------------------------------------------------------------*/
+
++void svm_learn_classification_extend(DOC **docs, double *class, long int
++ totdoc, long int totwords,
++ LEARN_PARM *learn_parm,
++ KERNEL_PARM *kernel_parm,
++ KERNEL_CACHE *kernel_cache,
++ MODEL *model,
++ double *alpha,
++ int* nerrors,
++ double* maxerror)
++{
++ long *inconsistent, i, *label;
++ long inconsistentnum;
++ long misclassified, upsupvecnum;
++ double loss, model_length, example_length;
++ double maxdiff, *lin, *a, *c;
++ long runtime_start, runtime_end;
++ long iterations;
++ long *unlabeled, transduction;
++ long heldout;
++ long loo_count = 0, loo_count_pos = 0, loo_count_neg = 0, trainpos = 0, trainneg = 0;
++ long loocomputed = 0, runtime_start_loo = 0, runtime_start_xa = 0;
++ double heldout_c = 0, r_delta_sq = 0, r_delta, r_delta_avg;
++ long *index, *index2dnum;
++ double *weights;
++ CFLOAT *aicache; /* buffer to keep one row of hessian */
++
++ double *xi_fullset; /* buffer for storing xi on full sample in loo */
++ double *a_fullset; /* buffer for storing alpha on full sample in loo */
++ TIMING timing_profile;
++ SHRINK_STATE shrink_state;
++
++ runtime_start = get_runtime();
++ timing_profile.time_kernel = 0;
++ timing_profile.time_opti = 0;
++ timing_profile.time_shrink = 0;
++ timing_profile.time_update = 0;
++ timing_profile.time_model = 0;
++ timing_profile.time_check = 0;
++ timing_profile.time_select = 0;
++ kernel_cache_statistic = 0;
++
++ learn_parm->totwords = totwords;
++
++ /* make sure -n value is reasonable */
++ if ((learn_parm->svm_newvarsinqp < 2)
++ || (learn_parm->svm_newvarsinqp > learn_parm->svm_maxqpsize))
++ {
++ learn_parm->svm_newvarsinqp = learn_parm->svm_maxqpsize;
++ }
++
++ init_shrink_state(&shrink_state, totdoc, (long)MAXSHRINK);
++
++ label = (long *)my_malloc(sizeof(long) * totdoc);
++ inconsistent = (long *)my_malloc(sizeof(long) * totdoc);
++ unlabeled = (long *)my_malloc(sizeof(long) * totdoc);
++ c = (double *)my_malloc(sizeof(double) * totdoc);
++ a = (double *)my_malloc(sizeof(double) * totdoc);
++ a_fullset = (double *)my_malloc(sizeof(double) * totdoc);
++ xi_fullset = (double *)my_malloc(sizeof(double) * totdoc);
++ lin = (double *)my_malloc(sizeof(double) * totdoc);
++ learn_parm->svm_cost = (double *)my_malloc(sizeof(double) * totdoc);
++ model->supvec = (DOC **)my_malloc(sizeof(DOC *) * (totdoc + 2));
++ model->alpha = (double *)my_malloc(sizeof(double) * (totdoc + 2));
++ model->index = (long *)my_malloc(sizeof(long) * (totdoc + 2));
++
++ model->at_upper_bound = 0;
++ model->b = 0;
++ model->supvec[0] = 0; /* element 0 reserved and empty for now */
++ model->alpha[0] = 0;
++ model->lin_weights = NULL;
++ model->totwords = totwords;
++ model->totdoc = totdoc;
++ model->kernel_parm = (*kernel_parm);
++ model->sv_num = 1;
++ model->loo_error = -1;
++ model->loo_recall = -1;
++ model->loo_precision = -1;
++ model->xa_error = -1;
++ model->xa_recall = -1;
++ model->xa_precision = -1;
++ inconsistentnum = 0;
++ transduction = 0;
++
++ r_delta = estimate_r_delta(docs, totdoc, kernel_parm);
++ r_delta_sq = r_delta * r_delta;
++
++ r_delta_avg = estimate_r_delta_average(docs, totdoc, kernel_parm);
++ if (learn_parm->svm_c == 0.0) /* default value for C */
++ {
++ learn_parm->svm_c = 1.0 / (r_delta_avg * r_delta_avg);
++ if (verbosity >= 1)
++ printf("Setting default regularization parameter C=%.4f\n",
++ learn_parm->svm_c);
++ }
++
++ learn_parm->eps = -1.0; /* equivalent regression epsilon for
++ classification */
++
++ for (i = 0; i < totdoc; i++) /* various inits */
++ {
++ docs[i]->docnum = i;
++ inconsistent[i] = 0;
++ a[i] = 0;
++ lin[i] = 0;
++ c[i] = 0.0;
++ unlabeled[i] = 0;
++ if (class[i] == 0)
++ {
++ unlabeled[i] = 1;
++ label[i] = 0;
++ transduction = 1;
++ }
++ if (class[i] > 0)
++ {
++ learn_parm->svm_cost[i] = learn_parm->svm_c * learn_parm->svm_costratio *
++ docs[i]->costfactor;
++ label[i] = 1;
++ trainpos++;
++ }
++ else if (class[i] < 0)
++ {
++ learn_parm->svm_cost[i] = learn_parm->svm_c * docs[i]->costfactor;
++ label[i] = -1;
++ trainneg++;
++ }
++ else
++ {
++ learn_parm->svm_cost[i] = 0;
++ }
++ }
++ if (verbosity >= 2)
++ {
++ printf("%ld positive, %ld negative, and %ld unlabeled examples.\n", trainpos, trainneg, totdoc - trainpos - trainneg);
++ fflush(stdout);
++ }
++
++ /* caching makes no sense for linear kernel */
++ if (kernel_parm->kernel_type == LINEAR)
++ {
++ kernel_cache = NULL;
++ }
++
++ /* compute starting state for initial alpha values */
++ if (alpha)
++ {
++ if (verbosity >= 1)
++ {
++ printf("Computing starting state...");
++ fflush(stdout);
++ }
++ index = (long *)my_malloc(sizeof(long) * totdoc);
++ index2dnum = (long *)my_malloc(sizeof(long) * (totdoc + 11));
++ weights = (double *)my_malloc(sizeof(double) * (totwords + 1));
++ aicache = (CFLOAT *)my_malloc(sizeof(CFLOAT) * totdoc);
++ for (i = 0; i < totdoc; i++) /* create full index and clip alphas */
++ {
++ index[i] = 1;
++ alpha[i] = fabs(alpha[i]);
++ if (alpha[i] < 0) alpha[i] = 0;
++ if (alpha[i] > learn_parm->svm_cost[i]) alpha[i] = learn_parm->svm_cost[i];
++ }
++ if (kernel_parm->kernel_type != LINEAR)
++ {
++ for (i = 0; i < totdoc; i++) /* fill kernel cache with unbounded SV */
++ if ((alpha[i] > 0) && (alpha[i] < learn_parm->svm_cost[i])
++ && (kernel_cache_space_available(kernel_cache)))
++ cache_kernel_row(kernel_cache, docs, i, kernel_parm);
++ for (i = 0; i < totdoc; i++) /* fill rest of kernel cache with bounded SV */
++ if ((alpha[i] == learn_parm->svm_cost[i])
++ && (kernel_cache_space_available(kernel_cache)))
++ cache_kernel_row(kernel_cache, docs, i, kernel_parm);
++ }
++ (void)compute_index(index, totdoc, index2dnum);
++ update_linear_component(docs, label, index2dnum, alpha, a, index2dnum, totdoc,
++ totwords, kernel_parm, kernel_cache, lin, aicache,
++ weights);
++ (void)calculate_svm_model(docs, label, unlabeled, lin, alpha, a, c,
++ learn_parm, index2dnum, index2dnum, model);
++ for (i = 0; i < totdoc; i++) /* copy initial alphas */
++ {
++ a[i] = alpha[i];
++ }
++ free(index);
++ free(index2dnum);
++ free(weights);
++ free(aicache);
++ if (verbosity >= 1)
++ {
++ printf("done.\n");
++ fflush(stdout);
++ }
++ }
++
++ if (transduction)
++ {
++ learn_parm->svm_iter_to_shrink = 99999999;
++ if (verbosity >= 1)
++ printf("\nDeactivating Shrinking due to an incompatibility with the transductive \nlearner in the current version.\n\n");
++ }
++
++
++ if (transduction && learn_parm->compute_loo)
++ {
++ learn_parm->compute_loo = 0;
++ if (verbosity >= 1)
++ printf("\nCannot compute leave-one-out estimates for transductive learner.\n\n");
++ }
++
++ if (learn_parm->remove_inconsistent && learn_parm->compute_loo)
++ {
++ learn_parm->compute_loo = 0;
++ printf("\nCannot compute leave-one-out estimates when removing inconsistent examples.\n\n");
++ }
++
++ if (learn_parm->compute_loo && ((trainpos == 1) || (trainneg == 1)))
++ {
++ learn_parm->compute_loo = 0;
++ printf("\nCannot compute leave-one-out with only one example in one class.\n\n");
++ }
++
++
++ if (verbosity == 1)
++ {
++ printf("Optimizing");
++ fflush(stdout);
++ }
++
++ /* train the svm */
++ iterations = optimize_to_convergence(docs, label, totdoc, totwords, learn_parm,
++ kernel_parm, kernel_cache, &shrink_state, model,
++ inconsistent, unlabeled, a, lin,
++ c, &timing_profile,
++ &maxdiff, (long) - 1,
++ (long)1);
++
++ misclassified = 0;
++ double maxerror_ = 0;
++ for (i = 0; (i < totdoc); i++) /* get final statistic */
++ {
++ if ((lin[i] - model->b)*(double)label[i] <= 0.0)
++ {
++ misclassified++;
++ if(maxerror_ < -(lin[i] - model->b)*(double)label[i])
++ maxerror_ = -(lin[i] - model->b)*(double)label[i];
++ }
++ }
++
++ *nerrors = misclassified;
++ *maxerror = maxerror_;
++
++ if (verbosity >= 1)
++ {
++ if (verbosity == 1) printf("done. (%ld iterations)\n", iterations);
++
++ misclassified = 0;
++ for (i = 0; (i < totdoc); i++) /* get final statistic */
++ {
++ if ((lin[i] - model->b)*(double)label[i] <= 0.0)
++ misclassified++;
++ }
++
++ printf("Optimization finished (%ld misclassified, maxdiff=%.5f).\n",
++ misclassified, maxdiff);
++
++ runtime_end = get_runtime();
++ if (verbosity >= 2)
++ {
++ printf("Runtime in cpu-seconds: %.2f (%.2f%% for kernel/%.2f%% for optimizer/%.2f%% for final/%.2f%% for update/%.2f%% for model/%.2f%% for check/%.2f%% for select)\n",
++ ((float)runtime_end - (float)runtime_start) / 100.0,
++ (100.0*timing_profile.time_kernel) / (float)(runtime_end - runtime_start),
++ (100.0*timing_profile.time_opti) / (float)(runtime_end - runtime_start),
++ (100.0*timing_profile.time_shrink) / (float)(runtime_end - runtime_start),
++ (100.0*timing_profile.time_update) / (float)(runtime_end - runtime_start),
++ (100.0*timing_profile.time_model) / (float)(runtime_end - runtime_start),
++ (100.0*timing_profile.time_check) / (float)(runtime_end - runtime_start),
++ (100.0*timing_profile.time_select) / (float)(runtime_end - runtime_start));
++ }
++ else
++ {
++ printf("Runtime in cpu-seconds: %.2f\n",
++ (runtime_end - runtime_start) / 100.0);
++ }
++
++ if (learn_parm->remove_inconsistent)
++ {
++ inconsistentnum = 0;
++ for (i = 0; i < totdoc; i++)
++ if (inconsistent[i])
++ inconsistentnum++;
++ printf("Number of SV: %ld (plus %ld inconsistent examples)\n",
++ model->sv_num - 1, inconsistentnum);
++ }
++ else
++ {
++ upsupvecnum = 0;
++ for (i = 1; i < model->sv_num; i++)
++ {
++ if (fabs(model->alpha[i]) >=
++ (learn_parm->svm_cost[(model->supvec[i])->docnum] -
++ learn_parm->epsilon_a))
++ upsupvecnum++;
++ }
++ printf("Number of SV: %ld (including %ld at upper bound)\n",
++ model->sv_num - 1, upsupvecnum);
++ }
++
++ if ((verbosity >= 1) && (!learn_parm->skip_final_opt_check))
++ {
++ loss = 0;
++ model_length = 0;
++ for (i = 0; i < totdoc; i++)
++ {
++ if ((lin[i] - model->b)*(double)label[i] < 1.0 - learn_parm->epsilon_crit)
++ loss += 1.0 - (lin[i] - model->b) * (double)label[i];
++ model_length += a[i] * label[i] * lin[i];
++ }
++ model_length = sqrt(model_length);
++ fprintf(stdout, "L1 loss: loss=%.5f\n", loss);
++ fprintf(stdout, "Norm of weight vector: |w|=%.5f\n", model_length);
++ example_length = estimate_sphere(model, kernel_parm);
++ fprintf(stdout, "Norm of longest example vector: |x|=%.5f\n",
++ length_of_longest_document_vector(docs, totdoc, kernel_parm));
++ fprintf(stdout, "Estimated VCdim of classifier: VCdim<=%.5f\n",
++ estimate_margin_vcdim(model, model_length, example_length,
++ kernel_parm));
++ if ((!learn_parm->remove_inconsistent) && (!transduction))
++ {
++ runtime_start_xa = get_runtime();
++ if (verbosity >= 1)
++ {
++ printf("Computing XiAlpha-estimates...");
++ fflush(stdout);
++ }
++ compute_xa_estimates(model, label, unlabeled, totdoc, docs, lin, a,
++ kernel_parm, learn_parm, &(model->xa_error),
++ &(model->xa_recall), &(model->xa_precision));
++ if (verbosity >= 1)
++ {
++ printf("done\n");
++ }
++ printf("Runtime for XiAlpha-estimates in cpu-seconds: %.2f\n",
++ (get_runtime() - runtime_start_xa) / 100.0);
++
++ fprintf(stdout, "XiAlpha-estimate of the error: error<=%.2f%% (rho=%.2f,depth=%ld)\n",
++ model->xa_error, learn_parm->rho, learn_parm->xa_depth);
++ fprintf(stdout, "XiAlpha-estimate of the recall: recall=>%.2f%% (rho=%.2f,depth=%ld)\n",
++ model->xa_recall, learn_parm->rho, learn_parm->xa_depth);
++ fprintf(stdout, "XiAlpha-estimate of the precision: precision=>%.2f%% (rho=%.2f,depth=%ld)\n",
++ model->xa_precision, learn_parm->rho, learn_parm->xa_depth);
++ }
++ else if (!learn_parm->remove_inconsistent)
++ {
++ estimate_transduction_quality(model, label, unlabeled, totdoc, docs, lin);
++ }
++ }
++ if (verbosity >= 1)
++ {
++ printf("Number of kernel evaluations: %ld\n", kernel_cache_statistic);
++ }
++ }
++
++
++ /* leave-one-out testing starts now */
++ if (learn_parm->compute_loo)
++ {
++ /* save results of training on full dataset for leave-one-out */
++ runtime_start_loo = get_runtime();
++ for (i = 0; i < totdoc; i++)
++ {
++ xi_fullset[i] = 1.0 - ((lin[i] - model->b) * (double)label[i]);
++ if (xi_fullset[i] < 0) xi_fullset[i] = 0;
++ a_fullset[i] = a[i];
++ }
++ if (verbosity >= 1)
++ {
++ printf("Computing leave-one-out");
++ }
++
++ /* repeat this loop for every held-out example */
++ for (heldout = 0; (heldout < totdoc); heldout++)
++ {
++ if (learn_parm->rho*a_fullset[heldout]*r_delta_sq + xi_fullset[heldout]
++ < 1.0)
++ {
++ /* guaranteed to not produce a leave-one-out error */
++ if (verbosity == 1)
++ {
++ printf("+");
++ fflush(stdout);
++ }
++ }
++ else if (xi_fullset[heldout] > 1.0)
++ {
++ /* guaranteed to produce a leave-one-out error */
++ loo_count++;
++ if (label[heldout] > 0) loo_count_pos++;
++ else loo_count_neg++;
++ if (verbosity == 1)
++ {
++ printf("-");
++ fflush(stdout);
++ }
++ }
++ else
++ {
++ loocomputed++;
++ heldout_c = learn_parm->svm_cost[heldout]; /* set upper bound to zero */
++ learn_parm->svm_cost[heldout] = 0;
++ /* make sure heldout example is not currently */
++ /* shrunk away. Assumes that lin is up to date! */
++ shrink_state.active[heldout] = 1;
++ if (verbosity >= 2)
++ printf("\nLeave-One-Out test on example %ld\n", heldout);
++ if (verbosity >= 1)
++ {
++ printf("(?[%ld]", heldout);
++ fflush(stdout);
++ }
++
++ optimize_to_convergence(docs, label, totdoc, totwords, learn_parm,
++ kernel_parm,
++ kernel_cache, &shrink_state, model, inconsistent, unlabeled,
++ a, lin, c, &timing_profile,
++ &maxdiff, heldout, (long)2);
++
++ /* printf("%.20f\n",(lin[heldout]-model->b)*(double)label[heldout]); */
++
++ if (((lin[heldout] - model->b)*(double)label[heldout]) <= 0.0)
++ {
++ loo_count++; /* there was a loo-error */
++ if (label[heldout] > 0) loo_count_pos++;
++ else loo_count_neg++;
++ if (verbosity >= 1)
++ {
++ printf("-)");
++ fflush(stdout);
++ }
++ }
++ else
++ {
++ if (verbosity >= 1)
++ {
++ printf("+)");
++ fflush(stdout);
++ }
++ }
++ /* now we need to restore the original data set*/
++ learn_parm->svm_cost[heldout] = heldout_c; /* restore upper bound */
++ }
++ } /* end of leave-one-out loop */
++
++
++ if (verbosity >= 1)
++ {
++ printf("\nRetrain on full problem");
++ fflush(stdout);
++ }
++ optimize_to_convergence(docs, label, totdoc, totwords, learn_parm,
++ kernel_parm,
++ kernel_cache, &shrink_state, model, inconsistent, unlabeled,
++ a, lin, c, &timing_profile,
++ &maxdiff, (long) - 1, (long)1);
++ if (verbosity >= 1)
++ printf("done.\n");
++
++
++ /* after all leave-one-out computed */
++ model->loo_error = 100.0 * loo_count / (double)totdoc;
++
++ model->loo_recall = (1.0 - (double)loo_count_pos / (double)trainpos) * 100.0;
++ model->loo_precision = (trainpos - loo_count_pos) /
++ (double)(trainpos - loo_count_pos + loo_count_neg) * 100.0;
++ if (verbosity >= 1)
++ {
++ fprintf(stdout, "Leave-one-out estimate of the error: error=%.2f%%\n",
++ model->loo_error);
++ fprintf(stdout, "Leave-one-out estimate of the recall: recall=%.2f%%\n",
++ model->loo_recall);
++ fprintf(stdout, "Leave-one-out estimate of the precision: precision=%.2f%%\n",
++ model->loo_precision);
++ fprintf(stdout, "Actual leave-one-outs computed: %ld (rho=%.2f)\n",
++ loocomputed, learn_parm->rho);
++ printf("Runtime for leave-one-out in cpu-seconds: %.2f\n",
++ (double)(get_runtime() - runtime_start_loo) / 100.0);
++ }
++ }
++
++ if (learn_parm->alphafile[0])
++ write_alphas(learn_parm->alphafile, a, label, totdoc);
++
++ shrink_state_cleanup(&shrink_state);
++ free(label);
++ free(inconsistent);
++ free(unlabeled);
++ free(c);
++ free(a);
++ free(a_fullset);
++ free(xi_fullset);
++ free(lin);
++ free(learn_parm->svm_cost);
++}
++
++
+ /* Learns an SVM classification model based on the training data in
+ docs/label. The resulting model is returned in the structure
+ model. */
+--- svm_learn.h 2011-09-06 22:14:22.363126903 -0400
++++ svm_learn.h 2011-09-06 22:49:59.247171372 -0400
+@@ -19,6 +19,9 @@
+ #ifndef SVM_LEARN
+ #define SVM_LEARN
+
++void svm_learn_classification_extend(DOC **, double *, long, long, LEARN_PARM *,
++ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
++ double *, int *, double *);
+ void svm_learn_classification(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *);
+@@ -152,6 +155,7 @@ double estimate_r_delta_average(DOC **,
+ double estimate_r_delta(DOC **, long, KERNEL_PARM *);
+ double length_of_longest_document_vector(DOC **, long, KERNEL_PARM *);
+
++
+ void write_model(char *, MODEL *);
+ void write_prediction(char *, MODEL *, double *, double *, long *, long *,
+ long, LEARN_PARM *);
diff --git a/trunk/svm_light/svm_light/include/svm_light/kernel.h b/trunk/svm_light/svm_light/include/svm_light/kernel.h
new file mode 100755
index 00000000..0133b006
--- /dev/null
+++ b/trunk/svm_light/svm_light/include/svm_light/kernel.h
@@ -0,0 +1,40 @@
+/************************************************************************/
+/* */
+/* kernel.h */
+/* */
+/* User defined kernel function. Feel free to plug in your own. */
+/* */
+/* Copyright: Thorsten Joachims */
+/* Date: 16.12.97 */
+/* */
+/************************************************************************/
+
+/* KERNEL_PARM is defined in svm_common.h The field 'custom' is reserved for */
+/* parameters of the user defined kernel. You can also access and use */
+/* the parameters of the other kernels. Just replace the line
+ return((double)(1.0));
+ with your own kernel. */
+
+ /* Example: The following computes the polynomial kernel. sprod_ss
+ computes the inner product between two sparse vectors.
+
+ return((CFLOAT)pow(kernel_parm->coef_lin*sprod_ss(a->words,b->words)
+ +kernel_parm->coef_const,(double)kernel_parm->poly_degree));
+ */
+
+/* If you are implementing a kernel that is not based on a
+ feature/value representation, you might want to make use of the
+ field "userdefined" in SVECTOR. By default, this field will contain
+ whatever string you put behind a # sign in the example file. So, if
+ a line in your training file looks like
+
+ -1 1:3 5:6 #abcdefg
+
+ then the SVECTOR field "words" will contain the vector 1:3 5:6, and
+ "userdefined" will contain the string "abcdefg". */
+
+double custom_kernel(KERNEL_PARM *kernel_parm, SVECTOR *a, SVECTOR *b)
+ /* plug in you favorite kernel */
+{
+ return((double)(1.0));
+}
diff --git a/trunk/svm_light/svm_light/include/svm_light/svm_common.h b/trunk/svm_light/svm_light/include/svm_light/svm_common.h
new file mode 100755
index 00000000..6487fa1d
--- /dev/null
+++ b/trunk/svm_light/svm_light/include/svm_light/svm_common.h
@@ -0,0 +1,301 @@
+/************************************************************************/
+/* */
+/* svm_common.h */
+/* */
+/* Definitions and functions used in both svm_learn and svm_classify. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/************************************************************************/
+
+#ifndef SVM_COMMON
+#define SVM_COMMON
+
+# include <stdio.h>
+# include <ctype.h>
+# include <math.h>
+# include <string.h>
+# include <stdlib.h>
+# include <time.h>
+# include <float.h>
+
+# define VERSION "V6.02"
+# define VERSION_DATE "14.08.08"
+
+# define CFLOAT float /* the type of float to use for caching */
+ /* kernel evaluations. Using float saves */
+ /* us some memory, but you can use double, too */
+# define FNUM long /* the type used for storing feature ids */
+# define FVAL float /* the type used for storing feature values */
+# define MAXFEATNUM 99999999 /* maximum feature number (must be in
+ valid range of FNUM type and long int!) */
+
+# define LINEAR 0 /* linear kernel type */
+# define POLY 1 /* polynoial kernel type */
+# define RBF 2 /* rbf kernel type */
+# define SIGMOID 3 /* sigmoid kernel type */
+
+# define CLASSIFICATION 1 /* train classification model */
+# define REGRESSION 2 /* train regression model */
+# define RANKING 3 /* train ranking model */
+# define OPTIMIZATION 4 /* train on general set of constraints */
+
+# define MAXSHRINK 50000 /* maximum number of shrinking rounds */
+
+typedef struct word {
+ FNUM wnum; /* word number */
+ FVAL weight; /* word weight */
+} WORD;
+
+typedef struct svector {
+ WORD *words; /* The features/values in the vector by
+ increasing feature-number. Feature
+ numbers that are skipped are
+ interpreted as having value zero. */
+ double twonorm_sq; /* The squared euclidian length of the
+ vector. Used to speed up the RBF kernel. */
+ char *userdefined; /* You can put additional information
+ here. This can be useful, if you are
+ implementing your own kernel that
+ does not work with feature/values
+ representations (for example a
+ string kernel). By default,
+ svm-light will put here the string
+ after the # sign from each line of
+ the input file. */
+ long kernel_id; /* Feature vectors with different
+ kernel_id's are orthogonal (ie. the
+ feature number do not match). This
+ is used for computing component
+ kernels for linear constraints which
+ are a sum of several different
+ weight vectors. (currently not
+ implemented). */
+ struct svector *next; /* Let's you set up a list of SVECTOR's
+ for linear constraints which are a
+ sum of multiple feature
+ vectors. List is terminated by
+ NULL. */
+ double factor; /* Factor by which this feature vector
+ is multiplied in the sum. */
+} SVECTOR;
+
+typedef struct doc {
+ long docnum; /* Document ID. This has to be the position of
+ the document in the training set array. */
+ long queryid; /* for learning rankings, constraints are
+ generated for documents with the same
+ queryID. */
+ double costfactor; /* Scales the cost of misclassifying this
+ document by this factor. The effect of this
+ value is, that the upper bound on the alpha
+ for this example is scaled by this factor.
+ The factors are set by the feature
+ 'cost:<val>' in the training data. */
+ long slackid; /* Index of the slack variable
+ corresponding to this
+ constraint. All constraints with the
+ same slackid share the same slack
+ variable. This can only be used for
+ svm_learn_optimization. */
+ SVECTOR *fvec; /* Feature vector of the example. The
+ feature vector can actually be a
+ list of feature vectors. For
+ example, the list will have two
+ elements, if this DOC is a
+ preference constraint. The one
+ vector that is supposed to be ranked
+ higher, will have a factor of +1,
+ the lower ranked one should have a
+ factor of -1. */
+} DOC;
+
+typedef struct learn_parm {
+ long type; /* selects between regression and
+ classification */
+ double svm_c; /* upper bound C on alphas */
+ double eps; /* regression epsilon (eps=1.0 for
+ classification */
+ double svm_costratio; /* factor to multiply C for positive examples */
+ double transduction_posratio;/* fraction of unlabeled examples to be */
+ /* classified as positives */
+ long biased_hyperplane; /* if nonzero, use hyperplane w*x+b=0
+ otherwise w*x=0 */
+ long sharedslack; /* if nonzero, it will use the shared
+ slack variable mode in
+ svm_learn_optimization. It requires
+ that the slackid is set for every
+ training example */
+ long svm_maxqpsize; /* size q of working set */
+ long svm_newvarsinqp; /* new variables to enter the working set
+ in each iteration */
+ long kernel_cache_size; /* size of kernel cache in megabytes */
+ double epsilon_crit; /* tolerable error for distances used
+ in stopping criterion */
+ double epsilon_shrink; /* how much a multiplier should be above
+ zero for shrinking */
+ long svm_iter_to_shrink; /* iterations h after which an example can
+ be removed by shrinking */
+ long maxiter; /* number of iterations after which the
+ optimizer terminates, if there was
+ no progress in maxdiff */
+ long remove_inconsistent; /* exclude examples with alpha at C and
+ retrain */
+ long skip_final_opt_check; /* do not check KT-Conditions at the end of
+ optimization for examples removed by
+ shrinking. WARNING: This might lead to
+ sub-optimal solutions! */
+ long compute_loo; /* if nonzero, computes leave-one-out
+ estimates */
+ double rho; /* parameter in xi/alpha-estimates and for
+ pruning leave-one-out range [1..2] */
+ long xa_depth; /* parameter in xi/alpha-estimates upper
+ bounding the number of SV the current
+ alpha_t is distributed over */
+ char predfile[200]; /* file for predicitions on unlabeled examples
+ in transduction */
+ char alphafile[200]; /* file to store optimal alphas in. use
+ empty string if alphas should not be
+ output */
+
+ /* you probably do not want to touch the following */
+ double epsilon_const; /* tolerable error on eq-constraint */
+ double epsilon_a; /* tolerable error on alphas at bounds */
+ double opt_precision; /* precision of solver, set to e.g. 1e-21
+ if you get convergence problems */
+
+ /* the following are only for internal use */
+ long svm_c_steps; /* do so many steps for finding optimal C */
+ double svm_c_factor; /* increase C by this factor every step */
+ double svm_costratio_unlab;
+ double svm_unlabbound;
+ double *svm_cost; /* individual upper bounds for each var */
+ long totwords; /* number of features */
+} LEARN_PARM;
+
+typedef struct kernel_parm {
+ long kernel_type; /* 0=linear, 1=poly, 2=rbf, 3=sigmoid, 4=custom */
+ long poly_degree;
+ double rbf_gamma;
+ double coef_lin;
+ double coef_const;
+ char custom[50]; /* for user supplied kernel */
+} KERNEL_PARM;
+
+typedef struct model {
+ long sv_num;
+ long at_upper_bound;
+ double b;
+ DOC **supvec;
+ double *alpha;
+ long *index; /* index from docnum to position in model */
+ long totwords; /* number of features */
+ long totdoc; /* number of training documents */
+ KERNEL_PARM kernel_parm; /* kernel */
+
+ /* the following values are not written to file */
+ double loo_error,loo_recall,loo_precision; /* leave-one-out estimates */
+ double xa_error,xa_recall,xa_precision; /* xi/alpha estimates */
+ double *lin_weights; /* weights for linear case using
+ folding */
+ double maxdiff; /* precision, up to which this
+ model is accurate */
+} MODEL;
+
+typedef struct quadratic_program {
+ long opt_n; /* number of variables */
+ long opt_m; /* number of linear equality constraints */
+ double *opt_ce,*opt_ce0; /* linear equality constraints */
+ double *opt_g; /* hessian of objective */
+ double *opt_g0; /* linear part of objective */
+ double *opt_xinit; /* initial value for variables */
+ double *opt_low,*opt_up; /* box constraints */
+} QP;
+
+typedef struct kernel_cache {
+ long *index; /* cache some kernel evalutations */
+ CFLOAT *buffer; /* to improve speed */
+ long *invindex;
+ long *active2totdoc;
+ long *totdoc2active;
+ long *lru;
+ long *occu;
+ long elems;
+ long max_elems;
+ long time;
+ long activenum;
+ long buffsize;
+} KERNEL_CACHE;
+
+
+typedef struct timing_profile {
+ long time_kernel;
+ long time_opti;
+ long time_shrink;
+ long time_update;
+ long time_model;
+ long time_check;
+ long time_select;
+} TIMING;
+
+typedef struct shrink_state {
+ long *active;
+ long *inactive_since;
+ long deactnum;
+ double **a_history; /* for shrinking with non-linear kernel */
+ long maxhistory;
+ double *last_a; /* for shrinking with linear kernel */
+ double *last_lin; /* for shrinking with linear kernel */
+} SHRINK_STATE;
+
+double classify_example(MODEL *, DOC *);
+double classify_example_linear(MODEL *, DOC *);
+double kernel(KERNEL_PARM *, DOC *, DOC *);
+double single_kernel(KERNEL_PARM *, SVECTOR *, SVECTOR *);
+double custom_kernel(KERNEL_PARM *, SVECTOR *, SVECTOR *);
+SVECTOR *create_svector(WORD *, char *, double);
+SVECTOR *copy_svector(SVECTOR *);
+void free_svector(SVECTOR *);
+double sprod_ss(SVECTOR *, SVECTOR *);
+SVECTOR* sub_ss(SVECTOR *, SVECTOR *);
+SVECTOR* add_ss(SVECTOR *, SVECTOR *);
+SVECTOR* add_list_ss(SVECTOR *);
+void append_svector_list(SVECTOR *a, SVECTOR *b);
+SVECTOR* smult_s(SVECTOR *, double);
+int featvec_eq(SVECTOR *, SVECTOR *);
+double model_length_s(MODEL *, KERNEL_PARM *);
+void clear_vector_n(double *, long);
+void add_vector_ns(double *, SVECTOR *, double);
+double sprod_ns(double *, SVECTOR *);
+void add_weight_vector_to_linear_model(MODEL *);
+DOC *create_example(long, long, long, double, SVECTOR *);
+void free_example(DOC *, long);
+MODEL *read_model(char *);
+MODEL *copy_model(MODEL *);
+void free_model(MODEL *, int);
+void read_documents(char *, DOC ***, double **, long *, long *);
+int parse_document(char *, WORD *, double *, long *, long *, double *, long *, long, char **);
+double *read_alphas(char *,long);
+void nol_ll(char *, long *, long *, long *);
+long minl(long, long);
+long maxl(long, long);
+long get_runtime(void);
+int space_or_null(int);
+void *my_malloc(size_t);
+void copyright_notice(void);
+# ifdef _MSC_VER
+ int isnan(double);
+# endif
+
+extern long verbosity; /* verbosity level (0-4) */
+extern long kernel_cache_statistic;
+
+#endif
diff --git a/trunk/svm_light/svm_light/include/svm_light/svm_learn.h b/trunk/svm_light/svm_light/include/svm_light/svm_learn.h
new file mode 100755
index 00000000..8a1edf7b
--- /dev/null
+++ b/trunk/svm_light/svm_light/include/svm_light/svm_learn.h
@@ -0,0 +1,173 @@
+/***********************************************************************/
+/* */
+/* svm_learn.h */
+/* */
+/* Declarations for learning module of Support Vector Machine. */
+/* */
+/* Author: Thorsten Joachims */
+/* Date: 02.07.02 */
+/* */
+/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
+/* */
+/* This software is available for non-commercial use only. It must */
+/* not be modified and distributed without prior permission of the */
+/* author. The author is not responsible for implications from the */
+/* use of this software. */
+/* */
+/***********************************************************************/
+
+#ifndef SVM_LEARN
+#define SVM_LEARN
+
+void svm_learn_classification_extend(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *, int *, double *);
+void svm_learn_classification(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *);
+void svm_learn_regression(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
+void svm_learn_ranking(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
+void svm_learn_optimization(DOC **, double *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
+ double *);
+long optimize_to_convergence(DOC **, long *, long, long, LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
+ MODEL *, long *, long *, double *,
+ double *, double *,
+ TIMING *, double *, long, long);
+long optimize_to_convergence_sharedslack(DOC **, long *, long, long,
+ LEARN_PARM *,
+ KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
+ MODEL *, double *, double *, double *,
+ TIMING *, double *);
+double compute_objective_function(double *, double *, double *, double,
+ long *, long *);
+void clear_index(long *);
+void add_to_index(long *, long);
+long compute_index(long *,long, long *);
+void optimize_svm(DOC **, long *, long *, long *, double, long *, long *,
+ MODEL *,
+ long, long *, long, double *, double *, double *,
+ LEARN_PARM *, CFLOAT *, KERNEL_PARM *, QP *, double *);
+void compute_matrices_for_optimization(DOC **, long *, long *, long *, double,
+ long *,
+ long *, long *, MODEL *, double *,
+ double *, double *, long, long, LEARN_PARM *,
+ CFLOAT *, KERNEL_PARM *, QP *);
+long calculate_svm_model(DOC **, long *, long *, double *, double *,
+ double *, double *, LEARN_PARM *, long *,
+ long *, MODEL *);
+long check_optimality(MODEL *, long *, long *, double *, double *,
+ double *, long,
+ LEARN_PARM *,double *, double, long *, long *, long *,
+ long *, long, KERNEL_PARM *);
+long check_optimality_sharedslack(DOC **docs, MODEL *model, long int *label,
+ double *a, double *lin, double *c, double *slack,
+ double *alphaslack, long int totdoc,
+ LEARN_PARM *learn_parm, double *maxdiff,
+ double epsilon_crit_org, long int *misclassified,
+ long int *active2dnum,
+ long int *last_suboptimal_at,
+ long int iteration, KERNEL_PARM *kernel_parm);
+void compute_shared_slacks(DOC **docs, long int *label, double *a,
+ double *lin, double *c, long int *active2dnum,
+ LEARN_PARM *learn_parm,
+ double *slack, double *alphaslack);
+long identify_inconsistent(double *, long *, long *, long, LEARN_PARM *,
+ long *, long *);
+long identify_misclassified(double *, long *, long *, long,
+ MODEL *, long *, long *);
+long identify_one_misclassified(double *, long *, long *, long,
+ MODEL *, long *, long *);
+long incorporate_unlabeled_examples(MODEL *, long *,long *, long *,
+ double *, double *, long, double *,
+ long *, long *, long, KERNEL_PARM *,
+ LEARN_PARM *);
+void update_linear_component(DOC **, long *, long *, double *, double *,
+ long *, long, long, KERNEL_PARM *,
+ KERNEL_CACHE *, double *,
+ CFLOAT *, double *);
+long select_next_qp_subproblem_grad(long *, long *, double *,
+ double *, double *, long,
+ long, LEARN_PARM *, long *, long *,
+ long *, double *, long *, KERNEL_CACHE *,
+ long, long *, long *);
+long select_next_qp_subproblem_rand(long *, long *, double *,
+ double *, double *, long,
+ long, LEARN_PARM *, long *, long *,
+ long *, double *, long *, KERNEL_CACHE *,
+ long *, long *, long);
+long select_next_qp_slackset(DOC **docs, long int *label, double *a,
+ double *lin, double *slack, double *alphaslack,
+ double *c, LEARN_PARM *learn_parm,
+ long int *active2dnum, double *maxviol);
+void select_top_n(double *, long, long *, long);
+void init_shrink_state(SHRINK_STATE *, long, long);
+void shrink_state_cleanup(SHRINK_STATE *);
+long shrink_problem(DOC **, LEARN_PARM *, SHRINK_STATE *, KERNEL_PARM *,
+ long *, long *, long, long, long, double *, long *);
+void reactivate_inactive_examples(long *, long *, double *, SHRINK_STATE *,
+ double *, double*, long, long, long, LEARN_PARM *,
+ long *, DOC **, KERNEL_PARM *,
+ KERNEL_CACHE *, MODEL *, CFLOAT *,
+ double *, double *);
+
+/* cache kernel evalutations to improve speed */
+KERNEL_CACHE *kernel_cache_init(long, long);
+void kernel_cache_cleanup(KERNEL_CACHE *);
+void get_kernel_row(KERNEL_CACHE *,DOC **, long, long, long *, CFLOAT *,
+ KERNEL_PARM *);
+void cache_kernel_row(KERNEL_CACHE *,DOC **, long, KERNEL_PARM *);
+void cache_multiple_kernel_rows(KERNEL_CACHE *,DOC **, long *, long,
+ KERNEL_PARM *);
+void kernel_cache_shrink(KERNEL_CACHE *,long, long, long *);
+void kernel_cache_reset_lru(KERNEL_CACHE *);
+long kernel_cache_malloc(KERNEL_CACHE *);
+void kernel_cache_free(KERNEL_CACHE *,long);
+long kernel_cache_free_lru(KERNEL_CACHE *);
+CFLOAT *kernel_cache_clean_and_malloc(KERNEL_CACHE *,long);
+long kernel_cache_touch(KERNEL_CACHE *,long);
+long kernel_cache_check(KERNEL_CACHE *,long);
+long kernel_cache_space_available(KERNEL_CACHE *);
+
+void compute_xa_estimates(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *, double *, double *, double *);
+double xa_estimate_error(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *);
+double xa_estimate_recall(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *);
+double xa_estimate_precision(MODEL *, long *, long *, long, DOC **,
+ double *, double *, KERNEL_PARM *,
+ LEARN_PARM *);
+void avg_similarity_of_sv_of_one_class(MODEL *, DOC **, double *, long *, KERNEL_PARM *, double *, double *);
+double most_similar_sv_of_same_class(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *);
+double distribute_alpha_t_greedily(long *, long, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
+double distribute_alpha_t_greedily_noindex(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
+void estimate_transduction_quality(MODEL *, long *, long *, long, DOC **, double *);
+double estimate_margin_vcdim(MODEL *, double, double, KERNEL_PARM *);
+double estimate_sphere(MODEL *, KERNEL_PARM *);
+double estimate_r_delta_average(DOC **, long, KERNEL_PARM *);
+double estimate_r_delta(DOC **, long, KERNEL_PARM *);
+double length_of_longest_document_vector(DOC **, long, KERNEL_PARM *);
+
+
+void write_model(char *, MODEL *);
+void write_prediction(char *, MODEL *, double *, double *, long *, long *,
+ long, LEARN_PARM *);
+void write_alphas(char *, double *, long *, long);
+
+typedef struct cache_parm_s {
+ KERNEL_CACHE *kernel_cache;
+ CFLOAT *cache;
+ DOC **docs;
+ long m;
+ KERNEL_PARM *kernel_parm;
+ long offset,stepsize;
+} cache_parm_t;
+
+#endif
diff --git a/trunk/svm_light/wiped b/trunk/svm_light/wiped
new file mode 100644
index 00000000..e69de29b
--
GitLab