{ "cells": [ { "cell_type": "markdown", "id": "de57e233", "metadata": {}, "source": [ "# HepMC" ] }, { "cell_type": "code", "execution_count": 1, "id": "a17fdd78", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.10.0\n" ] } ], "source": [ "import pyhepmc\n", "print(pyhepmc.__version__)" ] }, { "cell_type": "code", "execution_count": 55, "id": "c3cccf39-acd2-4b10-83d6-43c837b87101", "metadata": {}, "outputs": [], "source": [ "def rec_track(p, nchildren=-1):\n", " ps = [p]\n", " if len(p.children)==0 or (nchildren >0 and len(p.children) != nchildren):\n", " return ps\n", " for pss in p.children:\n", " ps = ps + rec_track(pss,nchildren)\n", " return ps" ] }, { "cell_type": "code", "execution_count": 56, "id": "0cc5c3e9", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "incoming:\n", "GenParticle(FourVector(0, 0, -117, 117), mass=0, pid=3, status=21) 187\n", "[187]\n", "GenParticle(FourVector(0, 0, 183, 183), mass=0, pid=2, status=21) 188\n", "[188]\n", "outgoing:\n", "GenParticle(FourVector(-33.6, -15, 133, 138), mass=1.90735e-06, pid=2, status=23) 189\n", "[189, 192]\n", "GenParticle(FourVector(51.1, 18.9, -106, 119), mass=1.3487e-06, pid=3, status=23) 190\n", "[190, 361, 505, 592, 647, 648]\n", "GenParticle(FourVector(-17.5, -3.92, 39, 43), mass=4.76837e-07, pid=22, status=23) 191\n", "[191, 362, 506, 593]\n" ] } ], "source": [ "with pyhepmc.open(\"example.HepMC\") as f: \n", " for event in f:\n", " print(\"incoming:\")\n", " for p in event.particles:\n", " if p.status == 21:\n", " print(p, p.id)\n", " print([pp.id for pp in rec_track(p,1)])\n", " print(\"outgoing:\")\n", " for p in event.particles:\n", " if p.status == 23:\n", " print(p,p.id)\n", " print([pp.id for pp in rec_track(p,1)])\n", " \n", " break" ] }, { "cell_type": "code", "execution_count": 3, "id": "7152a177", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n", 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"\n", "\n", "\n", "\n", "\n", "-142->out_243\n", "\n", "\n", "\n", "\n", "\n", "\n", "π⁺ 59 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_246\n", "\n", "\n", "\n", "\n", "\n", "\n", "n 7.4 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_249\n", "\n", "\n", "\n", "\n", "\n", "\n", "π⁻ 4.8 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_251\n", "\n", "\n", "\n", "\n", "\n", "\n", "π⁻ 1.6 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_257\n", "\n", "\n", "\n", "\n", "\n", "\n", "K⁻ 2.3 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_259\n", "\n", "\n", "\n", "\n", "\n", "\n", "K⁺ 6.6 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_262\n", "\n", "\n", "\n", "\n", "\n", "\n", "π⁻ 16 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_264\n", "\n", "\n", "\n", "\n", "\n", "\n", "π⁻ 11 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", "-142->out_265\n", "\n", "\n", "\n", "\n", "\n", "\n", "π⁺ 6.9 GeV\n", "\n", "\n", "\n", "\n", "\n", "\n", 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status=41), GenParticle(FourVector(0, 0, 140, 140), mass=0, pid=2, status=31), GenParticle(FourVector(2.4e-12, 5.14e-11, 108, 108), mass=0, pid=21, status=41), GenParticle(FourVector(0, 0, 50.4, 50.4), mass=0, pid=-2, status=31), GenParticle(FourVector(1.97e-11, -5.08e-11, -766, 766), mass=0, pid=1, status=42), GenParticle(FourVector(0, 0, -766, 766), mass=0, pid=1, status=31), GenParticle(FourVector(0, 0, 0.0118, 0.0118), mass=0, pid=21, status=31), GenParticle(FourVector(-0.203, 1.67, -65.8, 65.8), mass=0, pid=21, status=33), GenParticle(FourVector(0.203, -1.67, -700, 700), mass=0.33, pid=1, status=33), GenParticle(FourVector(0.252, -1.8, -761, 761), mass=0.33, pid=1, status=44), GenParticle(FourVector(0.187, -2.53, -762, 762), mass=0.33, pid=1, status=44), GenParticle(FourVector(0.181, -2.44, -737, 737), mass=0.33, pid=1, status=52), GenParticle(FourVector(-0.232, -2.65, -646, 646), mass=0.33, pid=1, status=51), GenParticle(FourVector(0.523, 0.371, -96.8, 96.8), mass=0, pid=21, status=51), GenParticle(FourVector(0.522, -4.14, -646, 646), mass=0.33, pid=1, status=62), GenParticle(FourVector(0.522, -4.14, -646, 646), mass=0.33, pid=1, status=71), GenParticle(FourVector(-0.469, -1.38, -255, 255), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.582, -0.986, -141, 141), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.128, -0.0969, -32.3, 32.3), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.0943, -0.471, -48, 48), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.118, -1.04, -113, 113), mass=0.49368, pid=321, status=1), GenParticle(FourVector(0.937, -0.552, -45.8, 45.8), mass=0.54785, pid=221, status=2), GenParticle(FourVector(-0.746, 0.191, -7.84, 7.9), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(-0.217, 0.363, -0.305, 0.996), mass=0.848268, pid=113, status=2), GenParticle(FourVector(0.591, -0.356, -1.24, 1.5), mass=0.49761, pid=311, status=2), GenParticle(FourVector(-0.464, 0.199, -0.23, 1.06), mass=0.904869, pid=-313, status=2), GenParticle(FourVector(0.339, 0.174, 0.211, 0.7), mass=0.54785, pid=221, status=2), GenParticle(FourVector(0.0345, -0.395, 0.246, 0.487), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.0781, 0.457, 2.13, 2.18), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.694, 0.168, 6.75, 6.81), mass=0.54785, pid=221, status=2), GenParticle(FourVector(0.652, -0.351, 20.4, 20.4), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.295, -0.695, 7.28, 7.32), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.0411, 0.483, 52.5, 52.5), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.372, -0.429, 40.2, 40.2), mass=1.23275, pid=2224, status=2), GenParticle(FourVector(-0.441, 0.411, 11.5, 11.6), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.201, -0.0966, 54.4, 54.4), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(-0.334, 0.593, 176, 176), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.266, -0.0618, 1.12e+03, 1.12e+03), mass=0.958295, pid=331, status=2), GenParticle(FourVector(-0.384, 0.54, 2.82e+03, 2.82e+03), mass=1.21793, pid=2114, status=2), GenParticle(FourVector(5.11e-14, 2.68e-16, -118, 118), mass=0, pid=3, status=53), GenParticle(FourVector(1.82e-16, 1.73e-16, -613, 613), mass=0, pid=21, status=42), GenParticle(FourVector(-1.33e-14, -5.69e-15, -129, 129), mass=0, pid=21, status=53), GenParticle(FourVector(0, 0, -8.39, 8.39), mass=0, pid=21, status=31), GenParticle(FourVector(1.15, -1.15, 1.13, 1.98), mass=0, pid=21, status=43), GenParticle(FourVector(0.0656, 0.733, -0.729, 1.04), mass=0, pid=21, status=43), GenParticle(FourVector(0, 0, -0.133, 0.133), mass=0, pid=21, status=31), GenParticle(FourVector(0.173, -0.913, -405, 405), mass=0, pid=21, status=43), GenParticle(FourVector(4.58e-14, -4.86e-13, -613, 613), mass=0, pid=21, status=41), GenParticle(FourVector(0, 0, -4.08, 4.08), mass=0, pid=21, status=31), GenParticle(FourVector(-0.414, 2.76, -609, 609), mass=0, pid=21, status=43), GenParticle(FourVector(-0.414, 2.76, -609, 609), mass=0, pid=21, status=44), GenParticle(FourVector(-0.401, 2.67, -590, 590), mass=0, pid=21, status=52), GenParticle(FourVector(-0.401, 2.67, -590, 590), mass=0, pid=21, status=44), GenParticle(FourVector(-1.67, 3.15, -590, 590), mass=0, pid=21, status=62), GenParticle(FourVector(-1.67, 3.15, -590, 590), mass=0, pid=21, status=71), GenParticle(FourVector(0.173, -0.913, -405, 405), mass=0, pid=21, status=52), GenParticle(FourVector(0.173, -0.913, -405, 405), mass=0, pid=21, status=52), GenParticle(FourVector(0.307, 0.0788, -306, 306), mass=0, pid=21, status=51), GenParticle(FourVector(-0.134, -0.991, -99.1, 99.1), mass=0, pid=21, status=51), GenParticle(FourVector(1.96, 1.26, -306, 306), mass=0, pid=21, status=62), GenParticle(FourVector(0.636, 0.148, -96.7, 96.8), mass=0, pid=21, status=62), GenParticle(FourVector(2.59, 1.41, -403, 403), mass=0.446511, pid=21, status=73), GenParticle(FourVector(2.59, 1.41, -403, 403), mass=0.446511, pid=21, status=71), GenParticle(FourVector(-0.134, -0.987, -98.7, 98.7), mass=0, pid=21, status=52), GenParticle(FourVector(-0.127, -0.939, -93.8, 93.8), mass=0, pid=21, status=52), GenParticle(FourVector(0.378, -0.577, -93.9, 93.9), mass=0, pid=21, status=62), GenParticle(FourVector(0.378, -0.577, -93.9, 93.9), mass=0, pid=21, status=71), GenParticle(FourVector(-1.45e-14, -2.85e-15, -129, 129), mass=0, pid=21, status=41), GenParticle(FourVector(1.41e-16, 5.64e-16, -71, 71), mass=0, pid=21, status=42), GenParticle(FourVector(1.32, 0.256, -57.9, 57.9), mass=0, pid=21, status=43), GenParticle(FourVector(1.67, 0.361, -57.9, 57.9), mass=0, pid=21, status=62), GenParticle(FourVector(1.67, 0.361, -57.9, 57.9), mass=0, pid=21, status=71), GenParticle(FourVector(0.304, 0.366, -4.92, 4.94), mass=0, pid=21, status=44), GenParticle(FourVector(0.297, 0.357, -4.8, 4.82), mass=0, pid=21, status=52), GenParticle(FourVector(1.25, 0.0118, -3.47, 3.69), mass=0, pid=21, status=51), GenParticle(FourVector(-1.05, 0.189, -1.03, 1.48), mass=0, pid=21, status=51), GenParticle(FourVector(1.25, 0.00837, -3.48, 3.69), mass=0, pid=21, status=44), GenParticle(FourVector(0.745, -0.843, -3.04, 3.24), mass=0, pid=21, status=51), GenParticle(FourVector(0.511, 0.767, -25.9, 25.9), mass=0, pid=21, status=51), GenParticle(FourVector(0.745, -0.939, -3.54, 3.74), mass=0, pid=21, status=51), GenParticle(FourVector(0.106, 0.254, -4.81, 4.82), mass=0, pid=21, status=51), GenParticle(FourVector(0.111, 0.243, -4.81, 4.81), mass=0, pid=21, status=62), GenParticle(FourVector(-0.178, 3.28, -3.41, 4.74), mass=0, pid=21, status=33), GenParticle(FourVector(0.236, 0.524, -4.06, 4.1), mass=0, pid=21, status=44), GenParticle(FourVector(0.236, 0.524, -4.06, 4.1), mass=0, pid=21, status=44), GenParticle(FourVector(0.573, 0.791, -17.1, 17.1), mass=0, pid=21, status=51), GenParticle(FourVector(-0.35, -0.18, -6.02, 6.04), mass=0, pid=21, status=51), GenParticle(FourVector(0.573, 0.791, -17.1, 17.1), mass=0, pid=21, status=44), GenParticle(FourVector(0.536, 0.805, -17.1, 17.1), mass=0, pid=21, status=62), GenParticle(FourVector(0.647, 1.05, -21.9, 21.9), mass=0.0800991, pid=21, status=73), GenParticle(FourVector(0.401, 0.602, -20.3, 20.3), mass=0, pid=21, status=52), GenParticle(FourVector(0.296, 0.444, -15, 15), mass=0, pid=21, status=52), GenParticle(FourVector(0.314, 0.409, -15, 15), mass=0, pid=21, status=62), GenParticle(FourVector(0.961, 1.46, -36.9, 36.9), mass=0.415536, pid=21, status=73), GenParticle(FourVector(0.961, 1.46, -36.9, 36.9), mass=0.415536, pid=21, status=71), GenParticle(FourVector(-3.34e-16, -7.93e-14, -71, 71), mass=0, pid=21, status=41), GenParticle(FourVector(0, 0, -0.671, 0.671), mass=0, pid=21, status=31), GenParticle(FourVector(-0.154, -2.31, -70.3, 70.3), mass=0, pid=21, status=43), GenParticle(FourVector(-0.153, -2.31, -70, 70), mass=0, pid=21, status=44), GenParticle(FourVector(-1.45, -2.56, -70, 70.1), mass=0, pid=21, status=44), GenParticle(FourVector(-1.32, -3.24, -67.5, 67.6), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0901, 0.621, -2.5, 2.58), mass=0, pid=21, status=51), GenParticle(FourVector(-0.916, -3.12, -67.5, 67.5), mass=0, pid=21, status=62), GenParticle(FourVector(-0.916, -3.12, -67.5, 67.5), mass=0, pid=21, status=71), GenParticle(FourVector(0.419, -1.44, 45.7, 45.7), mass=0.33, pid=-2, status=33), GenParticle(FourVector(0.402, -1.35, 39.4, 39.4), mass=0.33, pid=-2, status=44), GenParticle(FourVector(-0.48, -0.678, 28.5, 28.5), mass=0.33, pid=-2, status=51), GenParticle(FourVector(0.882, -0.672, 10.9, 10.9), mass=0, pid=21, status=51), GenParticle(FourVector(0.977, -1.36, 9.38, 9.53), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0948, 0.683, 1.36, 1.53), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0947, 0.682, 1.36, 1.53), mass=0, pid=21, status=52), GenParticle(FourVector(-0.259, 0.844, -0.0612, 0.885), mass=0, pid=21, status=51), GenParticle(FourVector(0.164, -0.166, 1.02, 1.04), mass=0, pid=21, status=51), GenParticle(FourVector(-0.367, -0.0174, -0.133, 0.391), mass=0, pid=21, status=51), GenParticle(FourVector(0.36, 0.407, 1.11, 1.24), mass=0, pid=21, status=51), GenParticle(FourVector(-0.382, 0.471, -0.709, 0.932), mass=0, pid=21, status=51), GenParticle(FourVector(0.00824, -0.536, -4.25, 4.28), mass=0, pid=21, status=51), GenParticle(FourVector(-0.381, 0.0321, -4.07, 4.08), mass=0, pid=21, status=51), GenParticle(FourVector(0.2, -0.335, -0.535, 0.662), mass=0, pid=21, status=51), GenParticle(FourVector(-0.359, 0.0477, -4.07, 4.08), mass=0, pid=21, status=62), GenParticle(FourVector(-0.35, -0.18, -6.02, 6.04), mass=0, pid=21, status=44), GenParticle(FourVector(-0.363, -0.176, -6.02, 6.04), mass=0, pid=21, status=62), GenParticle(FourVector(-0.722, -0.128, -10.1, 10.1), mass=0.245201, pid=21, status=73), GenParticle(FourVector(-0.722, -0.128, -10.1, 10.1), mass=0.245201, pid=21, status=71), GenParticle(FourVector(-0.0765, 0.527, -2.12, 2.19), mass=0, pid=21, status=52), GenParticle(FourVector(-0.0621, 0.531, -2.12, 2.18), mass=0, pid=21, status=62), GenParticle(FourVector(-0.0621, 0.531, -2.12, 2.18), mass=0, pid=21, status=71), GenParticle(FourVector(-0.192, 0.237, -0.357, 0.469), mass=0, pid=21, status=52), GenParticle(FourVector(-0.19, 0.238, -0.355, 0.467), mass=0, pid=21, status=62), GenParticle(FourVector(2.23, -1.61, -8.15, 8.6), mass=0, pid=21, status=33), GenParticle(FourVector(1.08, -0.461, -8.43, 8.51), mass=0, pid=21, status=44), GenParticle(FourVector(2.06, 0.784, -7.81, 8.11), mass=0, pid=21, status=51), GenParticle(FourVector(-0.996, -1.23, 0.699, 1.73), mass=0, pid=21, status=51), GenParticle(FourVector(-1.29, 0.158, 0.513, 1.4), mass=0, pid=21, status=51), GenParticle(FourVector(0.201, -1.32, 6.07, 6.22), mass=0, pid=21, status=51), GenParticle(FourVector(-0.401, -0.493, 0.655, 0.912), mass=0, pid=21, status=51), GenParticle(FourVector(-0.644, 0.746, -1.08, 1.46), mass=0, pid=21, status=51), GenParticle(FourVector(-0.382, 1.29, -2.01, 2.42), mass=0, pid=21, status=51), GenParticle(FourVector(0.424, -0.281, -1.67, 1.75), mass=0, pid=21, status=51), GenParticle(FourVector(-0.308, 1.04, -1.62, 1.95), mass=0, pid=21, status=52), GenParticle(FourVector(-0.592, 0.895, -1.63, 1.95), mass=0, pid=21, status=62), GenParticle(FourVector(-0.781, 1.13, -1.98, 2.42), mass=0.131022, pid=21, status=73), GenParticle(FourVector(-0.781, 1.13, -1.98, 2.42), mass=0.131022, pid=21, status=71), GenParticle(FourVector(-1.05, 0.188, -1.03, 1.48), mass=0, pid=21, status=44), GenParticle(FourVector(-0.868, 0.433, -1.45, 1.75), mass=0, pid=21, status=51), GenParticle(FourVector(-0.00266, -0.473, -0.436, 0.644), mass=0, pid=21, status=51), GenParticle(FourVector(-0.869, 0.426, -1.46, 1.75), mass=0, pid=21, status=62), GenParticle(FourVector(-0.869, 0.426, -1.46, 1.75), mass=0, pid=21, status=71), GenParticle(FourVector(2.51e-14, 1.34e-16, -118, 118), mass=0, pid=3, status=53), GenParticle(FourVector(6.13e-16, 6.7e-17, -117, 117), mass=0, pid=3, status=42), GenParticle(FourVector(0, 0, -117, 117), mass=0, pid=3, status=21), GenParticle(FourVector(0, 0, 183, 183), mass=0, pid=2, status=21), GenParticle(FourVector(-33.6, -15, 133, 138), mass=1.90735e-06, pid=2, status=23), GenParticle(FourVector(51.1, 18.9, -106, 119), mass=1.3487e-06, pid=3, status=23), GenParticle(FourVector(-17.5, -3.92, 39, 43), mass=4.76837e-07, pid=22, status=23), GenParticle(FourVector(-31, -10.2, 137, 141), mass=1.90735e-06, pid=2, status=44), GenParticle(FourVector(-25.6, -12.1, 91.6, 95.9), mass=1.90735e-06, pid=2, status=51), GenParticle(FourVector(-5.43, 1.86, 44.7, 45.1), mass=0, pid=21, status=51), GenParticle(FourVector(-3.76, -2.34, 21.8, 22.2), mass=0, pid=21, status=51), GenParticle(FourVector(-1.67, 4.21, 22.7, 23.1), mass=0, pid=21, status=51), GenParticle(FourVector(-1.62, 4.38, 22.7, 23.1), mass=0, pid=21, status=44), GenParticle(FourVector(-0.347, 0.617, 0.805, 1.07), mass=0, pid=21, status=51), GenParticle(FourVector(-1.98, 3.35, 26, 26.3), mass=0, pid=21, status=51), GenParticle(FourVector(-0.343, 0.616, 0.808, 1.07), mass=0, pid=21, status=62), GenParticle(FourVector(-0.343, 0.616, 0.808, 1.07), mass=0, pid=21, status=71), GenParticle(FourVector(0.153, 0.228, 0.494, 0.565), mass=0, pid=21, status=51), GenParticle(FourVector(0.144, 0.229, 0.473, 0.545), mass=0, pid=21, status=62), GenParticle(FourVector(0.366, 0.391, 1.12, 1.24), mass=0, pid=21, status=62), GenParticle(FourVector(0.51, 0.62, 1.59, 1.78), mass=0.0936287, pid=21, status=73), GenParticle(FourVector(-0.711, 3.19, 19.6, 19.8), mass=0, pid=21, status=33), GenParticle(FourVector(-0.68, 3.66, 23.4, 23.7), mass=0, pid=21, status=44), GenParticle(FourVector(-0.217, 5.77, 23.3, 24), mass=0, pid=21, status=44), GenParticle(FourVector(-0.223, 5.77, 23.3, 24), mass=0, pid=21, status=44), GenParticle(FourVector(0.125, 3.74, 11.7, 12.3), mass=0, pid=21, status=51), GenParticle(FourVector(-0.388, 1.86, 12.3, 12.5), mass=0, pid=21, status=51), GenParticle(FourVector(-0.388, 3.23, 11.5, 11.9), mass=0, pid=21, status=51), GenParticle(FourVector(0.513, 0.507, -0.108, 0.73), mass=0, pid=21, status=51), GenParticle(FourVector(0.369, 0.642, -0.118, 0.75), mass=0, pid=21, status=51), GenParticle(FourVector(0.0882, 0.328, 1.65, 1.69), mass=0, pid=21, status=51), GenParticle(FourVector(0.161, 0.318, 1.65, 1.69), mass=0, pid=21, status=62), GenParticle(FourVector(0.671, 0.938, 3.24, 3.47), mass=0.475402, pid=21, status=73), GenParticle(FourVector(0.671, 0.938, 3.24, 3.47), mass=0.475402, pid=21, status=71), GenParticle(FourVector(-0.332, 2.77, 9.81, 10.2), mass=0, pid=21, status=52), GenParticle(FourVector(0.107, 2.7, 9.83, 10.2), mass=0, pid=21, status=62), GenParticle(FourVector(0.107, 2.7, 9.83, 10.2), mass=0, pid=21, status=71), GenParticle(FourVector(-0.419, 1.44, 4.57, 4.81), mass=0, pid=21, status=33), GenParticle(FourVector(-0.575, 2.26, 10.9, 11.2), mass=0, pid=21, status=44), GenParticle(FourVector(-0.524, 2.11, 10.9, 11.1), mass=0, pid=21, status=62), GenParticle(FourVector(-0.642, 1.37, 6.56, 6.74), mass=0, pid=21, status=51), GenParticle(FourVector(-0.351, 1.33, 6.58, 6.72), mass=0, pid=21, status=62), GenParticle(FourVector(-0.874, 3.44, 17.5, 17.9), mass=0.0906697, pid=21, status=73), GenParticle(FourVector(-0.874, 3.44, 17.5, 17.9), mass=0.0906697, pid=21, status=71), GenParticle(FourVector(-1.42, 2.41, 18.7, 18.9), mass=0, pid=21, status=52), GenParticle(FourVector(-1.32, 2.41, 18.7, 18.9), mass=0, pid=21, status=62), GenParticle(FourVector(-1.32, 2.41, 18.7, 18.9), mass=0, pid=21, status=71), GenParticle(FourVector(-3.72, -2.17, 21.8, 22.2), mass=0, pid=21, status=44), GenParticle(FourVector(-3.01, -1.76, 17.7, 18), mass=0, pid=21, status=52), GenParticle(FourVector(-3, -1.43, 13.9, 14.3), mass=0, pid=21, status=51), GenParticle(FourVector(-0.567, 0.603, 11.1, 11.1), mass=0, pid=21, status=51), GenParticle(FourVector(-0.503, 0.6, 11.1, 11.1), mass=0, pid=21, status=62), GenParticle(FourVector(-0.503, 0.6, 11.1, 11.1), mass=0, pid=21, status=71), GenParticle(FourVector(-2.92, -1.43, 13.9, 14.3), mass=0, pid=21, status=62), GenParticle(FourVector(-2.92, -1.43, 13.9, 14.3), mass=0, pid=21, status=71), GenParticle(FourVector(-25.4, -11.4, 91.7, 95.8), mass=1.90735e-06, pid=2, status=44), GenParticle(FourVector(-24.9, -11.4, 91.9, 95.9), mass=1.90735e-06, pid=2, status=62), GenParticle(FourVector(-24.9, -11.4, 91.9, 95.9), mass=1.90735e-06, pid=2, status=71), GenParticle(FourVector(-15.2, -7.13, 56.1, 58.6), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-9.2, -4.31, 35.9, 37.3), mass=0.737765, pid=-213, status=2), GenParticle(FourVector(-1.79, -0.802, 9.67, 9.91), mass=0.922101, pid=113, status=2), GenParticle(FourVector(-0.641, 0.273, 7.35, 7.44), mass=0.93957, pid=2112, status=1), GenParticle(FourVector(-0.955, 0.337, 4.46, 4.64), mass=0.750213, pid=113, status=2), GenParticle(FourVector(-1.38, 1.81, 15, 15.2), mass=1.17808, pid=-1114, status=2), GenParticle(FourVector(0.249, 1.03, 4.68, 4.81), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.748, 0.951, 7.72, 7.85), mass=0.807814, pid=213, status=2), GenParticle(FourVector(-0.274, 0.303, 1.56, 1.62), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.559, 1.38, 6.04, 6.27), mass=0.772591, pid=223, status=2), GenParticle(FourVector(-0.947, 2.74, 15.5, 15.8), mass=0.778453, pid=213, status=2), GenParticle(FourVector(0.201, 0.196, 0.367, 0.717), mass=0.54785, pid=221, status=2), GenParticle(FourVector(0.263, 0.693, 1.83, 2.43), mass=1.42059, pid=-213, status=2), GenParticle(FourVector(-0.884, 0.947, -0.433, 1.65), mass=0.932584, pid=323, status=2), GenParticle(FourVector(-0.0801, 0.306, -2.2, 2.27), mass=0.49368, pid=-321, status=1), GenParticle(FourVector(-1.15, 1.04, -2.43, 2.89), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.256, -0.143, -6.59, 6.62), mass=0.49368, pid=321, status=1), GenParticle(FourVector(-0.532, -0.762, -16.5, 16.5), mass=0.86033, pid=-313, status=2), GenParticle(FourVector(0.0209, 0.161, -1.67, 1.68), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.489, -0.805, -16.4, 16.5), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.395, -0.15, -10, 10.1), mass=0.85511, pid=213, status=2), GenParticle(FourVector(0.252, -0.401, -11.2, 11.2), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.0902, 0.407, -6.87, 6.88), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.805, -0.109, -47, 47), mass=0.93957, pid=2112, status=1), GenParticle(FourVector(-0.371, 0.284, -26.5, 26.6), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(1.55, -0.195, -65.5, 65.5), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.484, 0.0409, -70.8, 70.8), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(1.13, 1.11, -284, 284), mass=1.44684, pid=2224, status=2), GenParticle(FourVector(0.159, -0.187, -12.4, 12.4), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.00507, 1.96, -409, 409), mass=1.24406, pid=-2214, status=2), GenParticle(FourVector(0.211, -0.332, -238, 238), mass=0.54785, pid=221, status=2), GenParticle(FourVector(-0.208, 1.9, -394, 394), mass=1.27805, pid=2214, status=2), GenParticle(FourVector(0.103, 0.0141, -367, 367), mass=0.721701, pid=213, status=2), GenParticle(FourVector(-2.23, 1.61, 139, 139), mass=0.33, pid=2, status=33), GenParticle(FourVector(-2.23, 1.62, 138, 138), mass=0.33, pid=2, status=44), GenParticle(FourVector(-2.21, 1.6, 137, 137), mass=0.33, pid=2, status=52), GenParticle(FourVector(-2.11, 1.53, 131, 131), mass=0.33, pid=2, status=52), GenParticle(FourVector(-1.9, 1.37, 117, 117), mass=0.33, pid=2, status=52), GenParticle(FourVector(-2.46, 2.29, 118, 118), mass=0.33, pid=2, status=62), GenParticle(FourVector(-2.46, 2.29, 118, 118), mass=0.33, pid=2, status=71), GenParticle(FourVector(-0.222, 0.0216, 3.29, 3.3), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.473, 0.335, 28.7, 28.7), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.229, 0.618, 16.6, 16.6), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.932, 0.208, 21, 21), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.0622, 0.34, 24.7, 24.7), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.091, 1.15, 16.7, 16.7), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.939, -0.283, 4.97, 5.15), mass=0.93827, pid=2212, status=1), GenParticle(FourVector(0.545, -0.143, -0.44, 1.18), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(-0.489, 0.202, 0.108, 1.08), mass=0.930506, pid=213, status=2), GenParticle(FourVector(0.396, -0.081, -1.12, 1.47), mass=0.862382, pid=223, status=2), GenParticle(FourVector(-0.0301, 0.184, -0.0951, 0.249), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.267, -0.441, -1.36, 1.46), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.242, 0.19, -1.06, 1.3), mass=0.685137, pid=213, status=2), GenParticle(FourVector(-0.49, 0.325, -4.47, 4.57), mass=0.770007, pid=223, status=2), GenParticle(FourVector(0.216, -0.383, -5.37, 5.39), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.129, -0.105, -2.81, 2.82), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.00633, 0.171, -18.5, 18.5), mass=0.737758, pid=113, status=2), GenParticle(FourVector(0.687, -0.0205, -94.1, 94.1), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.596, 0.342, -27.4, 27.4), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.564, -0.195, -40, 40), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.07, -0.117, -388, 388), mass=0.944601, pid=113, status=2), GenParticle(FourVector(-0.193, -0.146, -295, 295), mass=0.49761, pid=311, status=2), GenParticle(FourVector(-0.4, -0.0781, -835, 835), mass=0.762345, pid=-323, status=2), GenParticle(FourVector(0.232, 0.51, -2.02e+03, 2.02e+03), mass=0.894908, pid=323, status=2), GenParticle(FourVector(-3.51, -6.52, 1.84, 7.63), mass=0, pid=21, status=43), GenParticle(FourVector(-1.2, -2.07, 449, 449), mass=0, pid=21, status=51), GenParticle(FourVector(0.791, 0.547, 9.04, 9.09), mass=0, pid=21, status=51), GenParticle(FourVector(-1.01e-13, 6.75e-13, 957, 957), mass=0, pid=21, status=42), GenParticle(FourVector(-1.87, -1.23, 155, 155), mass=0, pid=21, status=43), GenParticle(FourVector(-0.00818, 0.449, 89.8, 89.8), mass=0, pid=21, status=62), GenParticle(FourVector(4.99e-15, 7.65e-14, 24.7, 24.7), mass=0, pid=21, status=42), GenParticle(FourVector(-0.485, -2.21, 9.37, 9.64), mass=0, pid=21, status=43), GenParticle(FourVector(-0.557, 1.43, 108, 108), mass=0, pid=21, status=43), GenParticle(FourVector(-0.0356, -0.4, -41.5, 41.5), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0587, -0.0714, -6.56, 6.56), mass=0, pid=22, status=1), GenParticle(FourVector(0.342, -0.0487, -13, 13), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.441, -0.417, -25, 25), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.154, -0.0863, -7.84, 7.84), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.746, 0.191, -7.84, 7.9), mass=0.49761, pid=130, status=1), GenParticle(FourVector(0.138, 0.476, -0.0375, 0.516), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.355, -0.113, -0.267, 0.479), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.591, -0.356, -1.24, 1.5), mass=0.49761, pid=310, status=2), GenParticle(FourVector(-0.302, 0.414, -0.258, 0.759), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(-0.161, -0.215, 0.0278, 0.302), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.375, 0.334, 0.175, 0.532), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0358, -0.16, 0.0362, 0.168), mass=0, pid=22, status=1), GenParticle(FourVector(-0.491, -0.139, 4.63, 4.65), mass=0, pid=22, status=1), GenParticle(FourVector(-0.203, 0.307, 2.12, 2.15), mass=0, pid=22, status=1), GenParticle(FourVector(0.279, -0.127, 10.2, 10.2), mass=0, pid=22, status=1), GenParticle(FourVector(0.373, -0.224, 10.2, 10.2), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0207, 0.113, 7.4, 7.4), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0204, 0.37, 45.1, 45.1), mass=0, pid=22, status=1), GenParticle(FourVector(0.264, -0.118, 26.3, 26.4), mass=0.93827, pid=2212, status=1), GenParticle(FourVector(0.109, -0.311, 13.9, 13.9), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.0201, 0.0318, 68.4, 68.4), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.0823, -0.131, 280, 280), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.164, 0.0373, 775, 775), mass=0.54785, pid=221, status=2), GenParticle(FourVector(-0.316, 0.272, 1.79e+03, 1.79e+03), mass=0.93957, pid=2112, status=1), GenParticle(FourVector(-0.068, 0.268, 1.03e+03, 1.03e+03), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.38, 0.0568, -0.93, 1.01), mass=0, pid=21, status=51), GenParticle(FourVector(1.86, -1.08, 0.793, 2.3), mass=0, pid=21, status=51), GenParticle(FourVector(0.0637, 0.728, -0.722, 1.03), mass=0, pid=21, status=62), GenParticle(FourVector(0, 0, 957, 957), mass=0, pid=21, status=31), GenParticle(FourVector(0.178, -3.28, 956, 956), mass=0, pid=21, status=33), GenParticle(FourVector(0.564, -0.712, -2.68, 2.83), mass=0, pid=21, status=52), GenParticle(FourVector(0, 0, 24.7, 24.7), mass=0, pid=21, status=31), GenParticle(FourVector(0.711, -3.19, 4.46, 5.53), mass=0, pid=21, status=33), GenParticle(FourVector(-0.412, -0.593, 24.7, 24.7), mass=0.33, pid=-2, status=52), GenParticle(FourVector(0.477, -1.46, 11, 11.1), mass=0, pid=21, status=51), GenParticle(FourVector(0.432, 0.0146, 2.16, 2.2), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0884, 0.288, -0.0209, 0.302), mass=0, pid=21, status=52), GenParticle(FourVector(0.203, -0.333, -0.537, 0.664), mass=0, pid=21, status=62), GenParticle(FourVector(1.72, 0.656, -6.54, 6.79), mass=0, pid=21, status=52), GenParticle(FourVector(-0.123, -1.22, 5.06, 5.21), mass=0, pid=21, status=51), GenParticle(FourVector(0.108, 0.0601, 14.4, 14.4), mass=0, pid=21, status=51), GenParticle(FourVector(-0.628, -0.47, -0.232, 0.818), mass=0, pid=21, status=51), GenParticle(FourVector(0.152, -0.419, -1.68, 1.74), mass=0, pid=21, status=62), GenParticle(FourVector(-0.00399, -0.476, -0.441, 0.649), mass=0, pid=21, status=62), GenParticle(FourVector(51.2, 19.2, -104, 118), mass=1.3487e-06, pid=3, status=44), GenParticle(FourVector(-16.7, -2.45, 40.4, 43.8), mass=4.76837e-07, pid=22, status=44), GenParticle(FourVector(0.194, 0.208, 6.92, 6.93), mass=0, pid=21, status=51), GenParticle(FourVector(-0.089, 0.817, -0.656, 1.05), mass=0, pid=21, status=51), GenParticle(FourVector(0.458, -0.175, -0.392, 0.628), mass=0, pid=21, status=51), GenParticle(FourVector(-3.77, -2.02, 14.2, 14.9), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-5.42, -2.29, 21.7, 22.5), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.404, -0.634, 3.37, 3.45), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-1.38, -0.168, 6.3, 6.46), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.994, 0.329, 3.28, 3.45), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.0388, 0.00851, 1.18, 1.19), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.968, 1.56, 11.9, 12.1), mass=0.93957, pid=-2112, status=1), GenParticle(FourVector(-0.41, 0.256, 3.09, 3.13), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.886, 0.805, 6.09, 6.21), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.138, 0.146, 1.63, 1.65), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.478, 0.814, 2.87, 3.02), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.00881, 0.5, 2.28, 2.33), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.072, 0.0643, 0.894, 0.909), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.679, 1.49, 6.93, 7.13), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.268, 1.25, 8.55, 8.65), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.129, -0.107, 0.0896, 0.19), mass=0, pid=22, status=1), GenParticle(FourVector(0.33, 0.303, 0.278, 0.527), mass=0, pid=22, status=1), GenParticle(FourVector(0.0353, -0.388, 0.201, 0.46), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.228, 1.08, 1.63, 1.97), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.616, 0.97, -0.497, 1.35), mass=0.49368, pid=321, status=1), GenParticle(FourVector(-0.268, -0.0231, 0.0649, 0.308), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.248, 0.26, -0.657, 0.748), mass=0, pid=22, status=1), GenParticle(FourVector(-0.907, 0.781, -1.77, 2.14), mass=0, pid=22, status=1), GenParticle(FourVector(-0.648, -0.608, -12.4, 12.4), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(0.116, -0.154, -4.12, 4.13), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.0735, 0.0828, -1.1, 1.1), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0526, 0.0783, -0.57, 0.578), mass=0, pid=22, status=1), GenParticle(FourVector(-0.378, -0.336, -9.16, 9.17), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.017, 0.186, -0.863, 0.894), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.616, 0.938, -241, 241), mass=0.93827, pid=2212, status=1), GenParticle(FourVector(0.518, 0.168, -43.3, 43.3), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.177, 1.37, -270, 270), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(0.171, 0.589, -139, 139), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.0695, 0.153, -53.4, 53.4), mass=0, pid=22, status=1), GenParticle(FourVector(0.141, -0.485, -184, 184), mass=0, pid=22, status=1), GenParticle(FourVector(0.00384, 1.49, -341, 341), mass=0.93827, pid=2212, status=1), GenParticle(FourVector(-0.212, 0.408, -53.5, 53.5), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.371, 0.0411, -156, 156), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.268, -0.027, -211, 211), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.118, 0.0124, 0.873, 0.881), mass=0, pid=22, status=1), GenParticle(FourVector(-0.103, 0.00922, 2.42, 2.42), mass=0, pid=22, status=1), GenParticle(FourVector(-0.326, 0.258, 23, 23), mass=0, pid=22, status=1), GenParticle(FourVector(-0.147, 0.0779, 5.72, 5.72), mass=0, pid=22, status=1), GenParticle(FourVector(-0.557, 0.066, 11.5, 11.5), mass=0, pid=22, status=1), GenParticle(FourVector(-0.376, 0.142, 9.52, 9.53), mass=0, pid=22, status=1), GenParticle(FourVector(0.0179, 5.73e-05, 3.24, 3.24), mass=0, pid=22, status=1), GenParticle(FourVector(0.0443, 0.34, 21.4, 21.4), mass=0, pid=22, status=1), GenParticle(FourVector(-0.215, -0.24, -0.25, 0.431), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.274, 0.442, 0.357, 0.645), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.241, 0.181, -0.206, 0.391), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.106, -0.163, -0.864, 0.896), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.0482, -0.0985, -0.0464, 0.18), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.0434, 0.117, -0.123, 0.175), mass=0, pid=22, status=1), GenParticle(FourVector(0.0133, 0.0666, 0.028, 0.0735), mass=0, pid=22, status=1), GenParticle(FourVector(-0.191, 0.141, -0.548, 0.614), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.433, 0.0486, -0.514, 0.687), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.48, 0.1, -1.68, 1.75), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.0773, 0.0817, -1.61, 1.62), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.0674, 0.143, -1.18, 1.2), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.204, -0.242, -3.94, 3.96), mass=0, pid=22, status=1), GenParticle(FourVector(0.0125, -0.141, -1.43, 1.44), mass=0, pid=22, status=1), GenParticle(FourVector(-0.141, -0.0545, -2.42, 2.43), mass=0, pid=22, status=1), GenParticle(FourVector(0.0118, -0.0506, -0.389, 0.392), mass=0, pid=22, status=1), GenParticle(FourVector(-0.238, 0.119, -15.5, 15.5), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.232, 0.0525, -3, 3.02), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.496, -0.17, -31.4, 31.4), mass=0, pid=22, status=1), GenParticle(FourVector(0.0685, -0.0246, -8.58, 8.58), mass=0, pid=22, status=1), GenParticle(FourVector(-0.224, -0.376, -323, 323), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.154, 0.258, -64.9, 64.9), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.193, -0.146, -295, 295), mass=0.49761, pid=310, status=2), GenParticle(FourVector(-0.158, -0.201, -539, 539), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(-0.242, 0.123, -296, 296), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.113, -0.00408, -1.07e+03, 1.07e+03), mass=0.49368, pid=321, status=1), GenParticle(FourVector(0.119, 0.514, -950, 950), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-2.94, -8.87, -0.999, 9.4), mass=0, pid=21, status=51), GenParticle(FourVector(3.32, 3.82, -5.07, 7.16), mass=0, pid=21, status=51), GenParticle(FourVector(0.15, -1.17, 185, 185), mass=0, pid=21, status=51), GenParticle(FourVector(-1.31, -0.879, 264, 264), mass=0, pid=21, status=51), GenParticle(FourVector(0.758, 0.524, 8.66, 8.71), mass=0, pid=21, status=52), GenParticle(FourVector(-1.58, -1.04, 131, 131), mass=0, pid=21, status=52), GenParticle(FourVector(0.178, -3.29, 957, 957), mass=0, pid=21, status=44), GenParticle(FourVector(2.05, -2.06, 957, 957), mass=0, pid=21, status=44), GenParticle(FourVector(1.77, -1.09, 371, 371), mass=0, pid=21, status=51), GenParticle(FourVector(-0.00907, -1.16, 610, 610), mass=0, pid=21, status=51), GenParticle(FourVector(1.35, -1.53, 454, 454), mass=0, pid=21, status=51), GenParticle(FourVector(0.413, 0.156, 64.9, 64.9), mass=0, pid=21, status=51), GenParticle(FourVector(0.403, 0.136, 64.9, 64.9), mass=0, pid=21, status=44), GenParticle(FourVector(0.271, 0.217, 64.9, 64.9), mass=0, pid=21, status=62), GenParticle(FourVector(0.263, 0.666, 155, 155), mass=0.34905, pid=21, status=73), GenParticle(FourVector(-0.488, -2.21, 9.38, 9.65), mass=0, pid=21, status=44), GenParticle(FourVector(-0.117, 2.14, 106, 106), mass=0, pid=21, status=51), GenParticle(FourVector(-0.432, -0.694, 1.33, 1.56), mass=0, pid=21, status=51), GenParticle(FourVector(0.0402, 0.0236, -0.807, 0.808), mass=0, pid=22, status=1), GenParticle(FourVector(0.302, -0.0722, -12.2, 12.2), mass=0, pid=22, status=1), GenParticle(FourVector(0.0455, 0.000719, -2.24, 2.24), mass=0, pid=22, status=1), GenParticle(FourVector(0.396, -0.417, -22.7, 22.8), mass=0, pid=22, status=1), GenParticle(FourVector(0.0388, 0.0162, -0.584, 0.586), mass=0, pid=22, status=1), GenParticle(FourVector(0.115, -0.103, -7.25, 7.25), mass=0, pid=22, status=1), GenParticle(FourVector(0.0167, -0.0211, -0.405, 0.428), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.575, -0.335, -0.834, 1.08), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.302, 0.414, -0.258, 0.759), mass=0.49761, pid=310, status=2), GenParticle(FourVector(0.00661, -0.00756, -0.0277, 0.0295), mass=0, pid=22, status=1), GenParticle(FourVector(-0.168, -0.207, 0.0555, 0.272), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0482, -0.0227, 7.86, 7.86), mass=0, pid=22, status=1), GenParticle(FourVector(0.212, 0.06, 767, 767), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0388, 0.0335, 371, 371), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0292, 0.235, 657, 657), mass=0, pid=22, status=1), GenParticle(FourVector(-0.237, -0.279, -1.05, 1.11), mass=0, pid=21, status=51), GenParticle(FourVector(0.3, 0.0779, 0.31, 0.439), mass=0, pid=21, status=51), GenParticle(FourVector(1.42, -0.826, 0.604, 1.75), mass=0, pid=21, status=52), GenParticle(FourVector(1.22, 2.11, 0.252, 2.45), mass=0, pid=21, status=51), GenParticle(FourVector(1.22, 2.12, 0.243, 2.46), mass=0, pid=21, status=44), GenParticle(FourVector(1.38, 0.473, -0.137, 1.47), mass=0, pid=21, status=51), GenParticle(FourVector(0.0843, 1.75, -0.371, 1.79), mass=0, pid=21, status=51), GenParticle(FourVector(0.0346, -0.229, 0.087, 0.247), mass=0, pid=21, status=51), GenParticle(FourVector(0.365, 2.1, -1.43, 2.57), mass=0, pid=21, status=51), GenParticle(FourVector(0.266, 1.53, -1.04, 1.87), mass=0, pid=21, status=52), GenParticle(FourVector(0.388, 1.73, -2.51, 3.07), mass=0, pid=21, status=51), GenParticle(FourVector(0.202, 0.093, 0.0921, 0.241), mass=0, pid=21, status=51), GenParticle(FourVector(0.355, 1.73, -2.51, 3.07), mass=0, pid=21, status=62), GenParticle(FourVector(0.418, 2.46, -3.23, 4.1), mass=0.342786, pid=21, status=73), GenParticle(FourVector(0.566, -0.72, -2.68, 2.83), mass=0, pid=21, status=62), GenParticle(FourVector(0.833, -1.35, 0.511, 1.67), mass=0, pid=21, status=44), GenParticle(FourVector(-0.299, -0.936, 24.7, 24.7), mass=0.33, pid=-2, status=62), GenParticle(FourVector(0.527, -1.61, 11, 11.1), mass=0, pid=21, status=62), GenParticle(FourVector(0.442, -0.0157, 2.16, 2.21), mass=0, pid=21, status=62), GenParticle(FourVector(-0.0869, 0.287, -0.0184, 0.3), mass=0, pid=21, status=62), GenParticle(FourVector(1.3, 0.443, -0.128, 1.37), mass=0, pid=21, status=52), GenParticle(FourVector(0.252, -0.162, -0.653, 0.718), mass=0, pid=21, status=51), GenParticle(FourVector(0.902, 0.205, 0.56, 1.08), mass=0, pid=21, status=51), GenParticle(FourVector(0.244, -0.162, -0.655, 0.718), mass=0, pid=21, status=62), GenParticle(FourVector(0.447, -0.496, -1.19, 1.38), mass=0.20441, pid=21, status=73), GenParticle(FourVector(1.47, 0.562, -5.6, 5.81), mass=0, pid=21, status=52), GenParticle(FourVector(-0.159, -1.19, 5.13, 5.26), mass=0, pid=21, status=62), GenParticle(FourVector(0.0395, 0.172, 14.3, 14.3), mass=0, pid=21, status=62), GenParticle(FourVector(-0.713, -0.51, -0.158, 0.891), mass=0, pid=21, status=62), GenParticle(FourVector(0.718, -1.14, -4.36, 4.57), mass=0.253674, pid=21, status=73), GenParticle(FourVector(-0.409, -0.366, -1.01, 1.15), mass=0, pid=21, status=62), GenParticle(FourVector(-0.413, -0.842, -1.45, 1.8), mass=0.500638, pid=21, status=73), GenParticle(FourVector(47.3, 17.7, -96.1, 109), mass=1.3487e-06, pid=3, status=52), GenParticle(FourVector(-16.6, -2.13, 40.4, 43.7), mass=4.76837e-07, pid=22, status=44), GenParticle(FourVector(0.303, -0.0939, 8.48, 8.48), mass=0, pid=21, status=51), GenParticle(FourVector(-0.239, -0.285, 0.931, 1), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0752, 0.818, -0.651, 1.05), mass=0, pid=21, status=62), GenParticle(FourVector(0.466, -0.175, -0.401, 0.64), mass=0, pid=21, status=62), GenParticle(FourVector(-3.04, -1.35, 12.2, 12.6), mass=0, pid=22, status=1), GenParticle(FourVector(-2.38, -0.935, 9.51, 9.84), mass=0, pid=22, status=1), GenParticle(FourVector(0.105, 0.0884, 0.587, 0.603), mass=0, pid=22, status=1), GenParticle(FourVector(0.0331, 0.0579, 1.04, 1.04), mass=0, pid=22, status=1), GenParticle(FourVector(0.039, 0.0935, 0.376, 0.389), mass=0, pid=22, status=1), GenParticle(FourVector(0.033, -0.0291, 0.518, 0.52), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0895, 0.24, 1.46, 1.48), mass=0, pid=22, status=1), GenParticle(FourVector(-0.178, 1.01, 7.09, 7.16), mass=0, pid=22, status=1), GenParticle(FourVector(0.215, 0.964, 1.52, 1.81), mass=0, pid=22, status=1), GenParticle(FourVector(0.0127, 0.117, 0.11, 0.161), mass=0, pid=22, status=1), GenParticle(FourVector(-0.147, -0.0719, 0.0682, 0.177), mass=0, pid=22, status=1), GenParticle(FourVector(-0.121, 0.0488, -0.00339, 0.131), mass=0, pid=22, status=1), GenParticle(FourVector(-0.648, -0.608, -12.4, 12.4), mass=0.49761, pid=310, status=2), GenParticle(FourVector(0.117, -0.158, -4.12, 4.12), mass=0, pid=22, status=1), GenParticle(FourVector(-0.00149, 0.00363, -0.00279, 0.00481), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0674, 0.0719, -0.274, 0.291), mass=0, pid=22, status=1), GenParticle(FourVector(0.0504, 0.114, -0.589, 0.602), mass=0, pid=22, status=1), GenParticle(FourVector(0.157, 0.486, -125, 125), mass=0, pid=22, status=1), GenParticle(FourVector(0.0143, 0.103, -14.5, 14.5), mass=0, pid=22, status=1), GenParticle(FourVector(-0.114, 0.336, -42.1, 42.1), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0983, 0.0713, -11.4, 11.4), mass=0, pid=22, status=1), GenParticle(FourVector(-0.261, -0.0559, -176, 176), mass=0, pid=22, status=1), GenParticle(FourVector(-0.00716, 0.0289, -35.5, 35.5), mass=0, pid=22, status=1), GenParticle(FourVector(-0.103, 0.067, 0.109, 0.164), mass=0, pid=22, status=1), GenParticle(FourVector(-0.172, 0.375, 0.248, 0.481), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0245, 0.00988, 0.0203, 0.0334), mass=0, pid=22, status=1), GenParticle(FourVector(0.0728, -0.108, -0.0668, 0.147), mass=0, pid=22, status=1), GenParticle(FourVector(0.424, 0.0583, -0.445, 0.618), mass=0, pid=22, status=1), GenParticle(FourVector(0.0095, -0.00974, -0.0682, 0.0695), mass=0, pid=22, status=1), GenParticle(FourVector(0.0983, 0.103, -1.03, 1.04), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0309, 0.0399, -0.147, 0.156), mass=0, pid=22, status=1), GenParticle(FourVector(-0.282, -0.173, -154, 154), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.0894, 0.0272, -141, 141), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.158, -0.201, -539, 539), mass=0.49761, pid=130, status=1), GenParticle(FourVector(0.0688, 0.477, -853, 853), mass=0, pid=22, status=1), GenParticle(FourVector(0.0501, 0.0371, -97.8, 97.8), mass=0, pid=22, status=1), GenParticle(FourVector(-2.61, -7.88, -0.888, 8.35), mass=0, pid=21, status=52), GenParticle(FourVector(1.77, 0.715, -5.44, 5.76), mass=0, pid=21, status=51), GenParticle(FourVector(1.24, -1.23, 185, 185), mass=0, pid=21, status=62), GenParticle(FourVector(-1.24, -1.22, 245, 245), mass=0, pid=21, status=51), GenParticle(FourVector(0.013, 0.395, 20.2, 20.2), mass=0, pid=21, status=51), GenParticle(FourVector(0.676, 0.467, 7.72, 7.76), mass=0, pid=21, status=52), GenParticle(FourVector(-1.6, -1.08, 131, 131), mass=0, pid=21, status=44), GenParticle(FourVector(-0.00687, -0.878, 462, 462), mass=0, pid=21, status=52), GenParticle(FourVector(1.28, -1.66, 454, 454), mass=0, pid=21, status=44), GenParticle(FourVector(0.263, 0.666, 155, 155), mass=0.34905, pid=21, status=71), GenParticle(FourVector(-0.448, -2.04, 8.62, 8.87), mass=0, pid=21, status=52), GenParticle(FourVector(-0.117, 2.14, 106, 106), mass=0, pid=21, status=44), GenParticle(FourVector(-0.335, -0.538, 1.03, 1.21), mass=0, pid=21, status=52), GenParticle(FourVector(-0.0131, 0.0546, -0.156, 0.166), mass=0, pid=22, status=1), GenParticle(FourVector(0.0298, -0.0757, -0.249, 0.262), mass=0, pid=22, status=1), GenParticle(FourVector(0.034, 0.000814, -0.0899, 0.0961), mass=0, pid=22, status=1), GenParticle(FourVector(0.541, -0.336, -0.744, 0.979), mass=0, pid=22, status=1), GenParticle(FourVector(-0.161, 0.0559, -0.272, 0.35), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.142, 0.358, 0.014, 0.41), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.288, 0.0755, 0.284, 0.412), mass=0, pid=21, status=62), GenParticle(FourVector(1.22, -0.709, 0.519, 1.5), mass=0, pid=21, status=52), GenParticle(FourVector(0.0346, -0.229, 0.0868, 0.247), mass=0, pid=21, status=62), GenParticle(FourVector(0.202, 0.0928, 0.0902, 0.24), mass=0, pid=21, status=62), GenParticle(FourVector(0.418, 2.46, -3.23, 4.1), mass=0.342786, pid=21, status=71), GenParticle(FourVector(0.855, -1.26, 0.565, 1.62), mass=0, pid=21, status=44), GenParticle(FourVector(-0.299, -0.936, 24.7, 24.7), mass=0.33, pid=-2, status=71), GenParticle(FourVector(0.527, -1.61, 11, 11.1), mass=0, pid=21, status=71), GenParticle(FourVector(0.675, -0.149, 8.47, 8.49), mass=0, pid=21, status=62), GenParticle(FourVector(1.12, -0.164, 10.6, 10.7), mass=0.531225, pid=21, status=73), GenParticle(FourVector(0.115, 0.379, 0.0718, 0.54), mass=0.359459, pid=21, status=73), GenParticle(FourVector(0.903, 0.205, 0.552, 1.08), mass=0, pid=21, status=62), GenParticle(FourVector(0.447, -0.496, -1.19, 1.38), mass=0.20441, pid=21, status=71), GenParticle(FourVector(0.788, 0.3, -2.99, 3.11), mass=0, pid=21, status=52), GenParticle(FourVector(-0.388, -1.76, 7.46, 7.67), mass=0, pid=21, status=52), GenParticle(FourVector(-0.259, -1.17, 4.97, 5.12), mass=0, pid=21, status=52), GenParticle(FourVector(-0.0372, -1.21, 4.97, 5.12), mass=0, pid=21, status=62), GenParticle(FourVector(-0.196, -2.39, 10.1, 10.4), mass=0.131253, pid=21, status=73), GenParticle(FourVector(0.132, 0.389, 20.2, 20.2), mass=0, pid=21, status=62), GenParticle(FourVector(0.171, 0.561, 34.6, 34.6), mass=0.139246, pid=21, status=73), GenParticle(FourVector(-0.152, -0.322, -0.298, 0.465), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0444, -0.0937, -0.0869, 0.135), mass=0, pid=21, status=52), GenParticle(FourVector(-0.0622, -0.102, -0.0784, 0.143), mass=0, pid=21, status=62), GenParticle(FourVector(-0.775, -0.613, -0.237, 1.03), mass=0.192735, pid=21, status=73), GenParticle(FourVector(0.718, -1.14, -4.36, 4.57), mass=0.253674, pid=21, status=71), GenParticle(FourVector(-0.413, -0.842, -1.45, 1.8), mass=0.500638, pid=21, status=71), GenParticle(FourVector(47.4, 17.8, -96.2, 109), mass=1.3487e-06, pid=3, status=44), GenParticle(FourVector(-16.4, -2.15, 40.6, 43.8), mass=4.76837e-07, pid=22, status=1), GenParticle(FourVector(-0.196, -0.291, 0.934, 0.998), mass=0, pid=21, status=62), GenParticle(FourVector(1.14, 0.506, -2.61, 2.89), mass=0, pid=21, status=51), GenParticle(FourVector(-0.0796, 0.322, -0.236, 0.407), mass=0, pid=21, status=51), GenParticle(FourVector(1.11, -0.0448, -2.58, 2.81), mass=0, pid=21, status=51), GenParticle(FourVector(-0.131, 0.297, -0.241, 0.404), mass=0, pid=21, status=62), GenParticle(FourVector(-0.206, 1.11, -0.893, 1.45), mass=0.167661, pid=21, status=73), GenParticle(FourVector(0.845, -1.26, 0.559, 1.61), mass=0, pid=21, status=44), GenParticle(FourVector(0.804, -1.2, 0.532, 1.54), mass=0, pid=21, status=52), GenParticle(FourVector(0.0676, -0.26, 0.655, 0.708), mass=0, pid=21, status=51), GenParticle(FourVector(0.722, -0.841, -0.501, 1.22), mass=0, pid=21, status=51), GenParticle(FourVector(0.743, -0.842, -0.519, 1.24), mass=0, pid=21, status=62), GenParticle(FourVector(1.21, -1.02, -0.92, 1.88), mass=0.422251, pid=21, status=73), GenParticle(FourVector(-0.0696, -0.207, -5.14, 5.15), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.579, -0.401, -7.23, 7.27), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-2.6, -7.85, -0.855, 8.32), mass=0, pid=21, status=44), GenParticle(FourVector(1.77, 0.717, -5.44, 5.77), mass=0, pid=21, status=44), GenParticle(FourVector(1.24, -1.23, 185, 185), mass=0, pid=21, status=71), GenParticle(FourVector(0.195, -1.29, 245, 245), mass=0, pid=21, status=62), GenParticle(FourVector(0.721, 0.465, 7.71, 7.76), mass=0, pid=21, status=62), GenParticle(FourVector(-1.87, -0.914, 131, 131), mass=0, pid=21, status=62), GenParticle(FourVector(-0.0792, -1.02, 462, 462), mass=0, pid=21, status=44), GenParticle(FourVector(0.361, -1.1, 454, 454), mass=0, pid=21, status=62), GenParticle(FourVector(-1.02, -0.442, 462, 462), mass=0, pid=21, status=62), GenParticle(FourVector(-1.02, -0.442, 462, 462), mass=0, pid=21, status=71), GenParticle(FourVector(-2.13, -0.104, 106, 106), mass=0, pid=21, status=62), GenParticle(FourVector(-2.13, -0.104, 106, 106), mass=0, pid=21, status=71), GenParticle(FourVector(-0.553, -0.853, 1.96, 2.22), mass=0.239204, pid=21, status=73), GenParticle(FourVector(-0.553, -0.853, 1.96, 2.22), mass=0.239204, pid=21, status=71), GenParticle(FourVector(0.0976, -0.265, 0.652, 0.711), mass=0, pid=21, status=62), GenParticle(FourVector(0.0976, -0.265, 0.652, 0.711), mass=0, pid=21, status=71), GenParticle(FourVector(-2.59, -7.81, -0.849, 8.27), mass=0, pid=21, status=52), GenParticle(FourVector(-1.12, -3.89, -1.21, 4.22), mass=0, pid=21, status=51), GenParticle(FourVector(-1.38, -3.89, 0.349, 4.14), mass=0, pid=21, status=51), GenParticle(FourVector(-1.15, -3.89, -1.2, 4.23), mass=0, pid=21, status=62), GenParticle(FourVector(-1.15, -3.89, -1.2, 4.23), mass=0, pid=21, status=71), GenParticle(FourVector(-1.24, -3.49, 0.313, 3.72), mass=0, pid=21, status=52), GenParticle(FourVector(-1.25, -3.49, 0.326, 3.72), mass=0, pid=21, status=62), GenParticle(FourVector(-1.25, -3.49, 0.326, 3.72), mass=0, pid=21, status=71), GenParticle(FourVector(1.14, -0.742, 0.46, 1.43), mass=0, pid=21, status=62), GenParticle(FourVector(1.14, -0.742, 0.46, 1.43), mass=0, pid=21, status=71), GenParticle(FourVector(1.19, 0.28, 0.836, 1.49), mass=0.149999, pid=21, status=73), GenParticle(FourVector(1.19, 0.28, 0.836, 1.49), mass=0.149999, pid=21, status=71), GenParticle(FourVector(0.685, -0.262, -2.65, 2.75), mass=0, pid=21, status=62), GenParticle(FourVector(0.685, -0.262, -2.65, 2.75), mass=0, pid=21, status=71), GenParticle(FourVector(1.53, 0.618, -4.69, 4.97), mass=0, pid=21, status=52), GenParticle(FourVector(1.21, 0.49, -3.72, 3.94), mass=0, pid=21, status=52), GenParticle(FourVector(0.366, 0.198, -0.0937, 0.427), mass=0, pid=21, status=51), GenParticle(FourVector(0.944, 0.861, -4.01, 4.21), mass=0, pid=21, status=51), GenParticle(FourVector(0.62, 0.566, -2.64, 2.77), mass=0, pid=21, status=52), GenParticle(FourVector(0.587, 0.563, -2.64, 2.77), mass=0, pid=21, status=62), GenParticle(FourVector(0.587, 0.563, -2.64, 2.77), mass=0, pid=21, status=71), GenParticle(FourVector(0.364, 0.198, -0.0971, 0.425), mass=0, pid=21, status=62), GenParticle(FourVector(0.364, 0.198, -0.0971, 0.425), mass=0, pid=21, status=71), GenParticle(FourVector(46.1, 17.6, -96.7, 109), mass=1.3487e-06, pid=3, status=62), GenParticle(FourVector(46.1, 17.6, -96.7, 109), mass=1.3487e-06, pid=3, status=71), GenParticle(FourVector(0.115, 0.379, 0.0718, 0.54), mass=0.359459, pid=21, status=71), GenParticle(FourVector(-0.206, 1.11, -0.893, 1.45), mass=0.167661, pid=21, status=71), GenParticle(FourVector(0.0346, -0.229, 0.0868, 0.247), mass=0, pid=21, status=71), GenParticle(FourVector(1.21, -1.02, -0.92, 1.88), mass=0.422251, pid=21, status=71), GenParticle(FourVector(-0.775, -0.613, -0.237, 1.03), mass=0.192735, pid=21, status=71), GenParticle(FourVector(-0.196, -2.39, 10.1, 10.4), mass=0.131253, pid=21, status=71), GenParticle(FourVector(1.12, -0.164, 10.6, 10.7), mass=0.531225, pid=21, status=71), GenParticle(FourVector(0.721, 0.465, 7.71, 7.76), mass=0, pid=21, status=71), GenParticle(FourVector(0.171, 0.561, 34.6, 34.6), mass=0.139246, pid=21, status=71), GenParticle(FourVector(-1.87, -0.914, 131, 131), mass=0, pid=21, status=71), GenParticle(FourVector(0.361, -1.1, 454, 454), mass=0, pid=21, status=71), GenParticle(FourVector(0.195, -1.29, 245, 245), mass=0, pid=21, status=71), GenParticle(FourVector(8.51, 3.18, -17.8, 20), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(25.4, 9.4, -53.2, 59.7), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(3.86, 2.16, -8.08, 9.21), mass=0.13957, pid=211, status=1), GenParticle(FourVector(4.39, 1.33, -9.51, 10.6), mass=0.621575, pid=223, status=2), GenParticle(FourVector(4.48, 1.92, -9.63, 10.8), mass=0.93957, pid=2112, status=1), GenParticle(FourVector(0.156, 0.477, -0.0331, 0.705), mass=0.49368, pid=-321, status=1), GenParticle(FourVector(0.513, 2.3, -3.36, 4.33), mass=1.38827, pid=-3114, status=2), GenParticle(FourVector(0.214, 0.247, -0.166, 0.618), mass=0.49761, pid=311, status=2), GenParticle(FourVector(-0.0612, 0.53, -1.55, 1.71), mass=0.49368, pid=-321, status=1), GenParticle(FourVector(0.831, -0.177, -1.02, 1.68), mass=1.03089, pid=213, status=2), GenParticle(FourVector(0.18, 0.182, -1.31, 1.35), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.127, -0.0238, 0.0358, 0.194), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.764, -1.48, -3.14, 3.68), mass=0.93957, pid=2112, status=1), GenParticle(FourVector(0.234, -0.608, -1.22, 1.67), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(0.768, -0.233, -1.7, 2.04), mass=0.78684, pid=213, status=2), GenParticle(FourVector(0.082, 0.0794, -0.859, 0.878), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.0211, -0.899, -0.907, 1.5), mass=0.781437, pid=223, status=2), GenParticle(FourVector(0.288, 0.12, 0.32, 0.469), mass=0.13957, pid=211, status=1), GenParticle(FourVector(1.47, -0.946, 0.36, 1.95), mass=0.779605, pid=-213, status=2), GenParticle(FourVector(-0.744, -0.356, 0.274, 0.88), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.198, -1.06, 0.146, 1.1), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.122, -0.944, -0.32, 1.01), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.607, -1.3, -0.355, 1.71), mass=0.849917, pid=-213, status=2), GenParticle(FourVector(-0.797, -2.24, -0.568, 2.49), mass=0.49368, pid=321, status=1), GenParticle(FourVector(-0.0973, -0.836, 1.18, 1.7), mass=0.888143, pid=-313, status=2), GenParticle(FourVector(-0.461, -0.512, 0.593, 1.38), mass=1.03501, pid=-213, status=2), GenParticle(FourVector(-0.133, -0.815, 0.541, 0.996), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.17, -0.964, 3.94, 4.17), mass=0.95828, pid=331, status=2), GenParticle(FourVector(-0.23, -0.576, 2.42, 2.67), mass=0.953393, pid=213, status=2), GenParticle(FourVector(0.317, -0.75, 2.53, 2.77), mass=0.769773, pid=-213, status=2), GenParticle(FourVector(-0.0837, -0.247, 0.69, 0.751), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.202, -0.399, 4.92, 4.94), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.244, -1.15, 4.14, 4.31), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.15, 0.0168, 0.208, 0.292), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.205, -0.107, 1.73, 1.75), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.826, 0.176, 4.85, 4.93), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.757, -0.735, 25.4, 25.5), mass=0.958065, pid=313, status=2), GenParticle(FourVector(-0.35, 0.745, 42.4, 42.4), mass=0.49368, pid=-321, status=1), GenParticle(FourVector(-0.596, -0.298, 30.4, 30.5), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.411, -0.616, 61.8, 61.8), mass=0.49761, pid=311, status=2), GenParticle(FourVector(-0.258, 0.343, 31.5, 31.5), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(-0.771, 0.102, 83.7, 83.7), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.295, 0.479, 50.3, 50.3), mass=0.790408, pid=223, status=2), GenParticle(FourVector(-1.33, -1.07, 305, 305), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.435, -0.108, 227, 227), mass=0.54785, pid=221, status=2), GenParticle(FourVector(0.166, -0.403, 231, 231), mass=0.904612, pid=313, status=2), GenParticle(FourVector(-0.413, -0.844, 188, 189), mass=0.894094, pid=-313, status=2), GenParticle(FourVector(-0.401, -0.0402, 113, 113), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.537, -0.735, 206, 206), mass=0.719941, pid=113, status=2), GenParticle(FourVector(0.418, -1.14, 139, 139), mass=1.16184, pid=2214, status=2), GenParticle(FourVector(0.34, -0.86, 75.7, 75.7), mass=1.20898, pid=-2214, status=2), GenParticle(FourVector(-0.335, -0.538, 1.03, 1.21), mass=0, pid=21, status=44), GenParticle(FourVector(-0.356, -0.562, 1.02, 1.22), mass=0, pid=21, status=62), GenParticle(FourVector(-0.0926, -0.195, -4.95, 4.95), mass=0, pid=22, status=1), GenParticle(FourVector(0.023, -0.0112, -0.195, 0.197), mass=0, pid=22, status=1), GenParticle(FourVector(-0.343, -0.316, -4.74, 4.76), mass=0, pid=22, status=1), GenParticle(FourVector(-0.236, -0.0852, -2.49, 2.5), mass=0, pid=22, status=1), GenParticle(FourVector(8.51, 3.18, -17.8, 20), mass=0.49761, pid=130, status=1), GenParticle(FourVector(0.858, 0.153, -1.89, 2.09), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.906, 0.376, -1.81, 2.06), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(2.63, 0.804, -5.8, 6.42), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.294, 1.64, -2.7, 3.36), mass=1.11568, pid=-3122, status=2), GenParticle(FourVector(0.219, 0.661, -0.658, 0.968), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.214, 0.247, -0.166, 0.618), mass=0.49761, pid=310, status=2), GenParticle(FourVector(0.913, 0.144, -0.914, 1.31), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.0816, -0.321, -0.104, 0.373), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.582, 0.159, -0.671, 0.913), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.185, -0.392, -1.03, 1.12), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.28, -0.325, -0.294, 0.538), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.212, -0.455, -0.562, 0.767), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.0461, -0.118, -0.0508, 0.192), mass=0.13498, pid=111, status=2), GenParticle(FourVector(1.14, -0.467, -0.0227, 1.24), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.335, -0.479, 0.383, 0.712), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.437, -0.222, 0.231, 0.542), mass=0, pid=22, status=1), GenParticle(FourVector(-0.307, -0.133, 0.0434, 0.338), mass=0, pid=22, status=1), GenParticle(FourVector(0.133, -0.611, 0.0193, 0.625), mass=0, pid=22, status=1), GenParticle(FourVector(0.0649, -0.454, 0.126, 0.476), mass=0, pid=22, status=1), GenParticle(FourVector(-0.689, -0.868, 0.0109, 1.12), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.0825, -0.432, -0.366, 0.588), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.0423, -0.392, 0.999, 1.18), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(-0.14, -0.444, 0.184, 0.519), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.0361, -0.463, -0.117, 0.499), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.497, -0.0493, 0.71, 0.879), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.128, -0.377, 0.276, 0.484), mass=0, pid=22, status=1), GenParticle(FourVector(-0.00465, -0.438, 0.266, 0.512), mass=0, pid=22, status=1), GenParticle(FourVector(0.014, -0.113, 0.902, 0.919), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.0269, -0.33, 0.664, 0.755), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.157, -0.521, 2.38, 2.5), mass=0.54785, pid=221, status=2), GenParticle(FourVector(-0.45, -0.541, 1, 1.23), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.22, -0.0357, 1.42, 1.44), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.0781, -0.659, 1.77, 1.89), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.395, -0.0911, 0.766, 0.877), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.0265, -0.0797, 0.429, 0.437), mass=0, pid=22, status=1), GenParticle(FourVector(-0.179, -0.0276, 1.3, 1.31), mass=0, pid=22, status=1), GenParticle(FourVector(0.17, -0.334, 16, 16), mass=0.49368, pid=321, status=1), GenParticle(FourVector(0.588, -0.401, 9.4, 9.43), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.411, -0.616, 61.8, 61.8), mass=0.49761, pid=130, status=1), GenParticle(FourVector(-0.258, 0.343, 31.5, 31.5), mass=0.49761, pid=130, status=1), GenParticle(FourVector(-0.248, -0.0208, 30.2, 30.2), mass=0, pid=22, status=1), GenParticle(FourVector(-0.522, 0.122, 53.5, 53.5), mass=0, pid=22, status=1), GenParticle(FourVector(-0.301, 0.288, 19.2, 19.2), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.144, 0.129, 24.6, 24.6), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.138, 0.0614, 6.43, 6.43), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-1.22, -0.969, 283, 283), mass=0, pid=22, status=1), GenParticle(FourVector(-0.115, -0.103, 21.5, 21.5), mass=0, pid=22, status=1), GenParticle(FourVector(0.1, -0.197, 30.7, 30.7), mass=0, pid=22, status=1), GenParticle(FourVector(0.335, 0.0893, 197, 197), mass=0, pid=22, status=1), GenParticle(FourVector(-0.00791, -0.188, 199, 199), mass=0.49368, pid=321, status=1), GenParticle(FourVector(0.174, -0.215, 32.5, 32.5), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(-0.562, -0.719, 165, 165), mass=0.49761, pid=-311, status=2), GenParticle(FourVector(0.149, -0.125, 23.6, 23.6), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.0748, 0.04, 28.9, 28.9), mass=0.13957, pid=211, status=1), GenParticle(FourVector(0.612, -0.775, 177, 177), mass=0.13957, pid=-211, status=1), GenParticle(FourVector(0.217, -0.918, 101, 101), mass=0.93827, pid=2212, status=1), GenParticle(FourVector(0.2, -0.227, 37.7, 37.7), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.454, -0.712, 57.6, 57.6), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(-0.113, -0.148, 18.2, 18.2), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.264, 0.0554, -0.497, 0.566), mass=0, pid=22, status=1), GenParticle(FourVector(2.36, 0.749, -5.3, 5.86), mass=0, pid=22, status=1), GenParticle(FourVector(0.349, 1.46, -2.36, 2.95), mass=0.93827, pid=-2212, status=1), GenParticle(FourVector(-0.0554, 0.178, -0.336, 0.409), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.118, 0.0979, -0.086, 0.222), mass=0.13498, pid=111, status=2), GenParticle(FourVector(0.332, 0.149, -0.0801, 0.397), mass=0.13498, pid=111, status=2), GenParticle(FourVector(-0.0672, -0.23, -0.00847, 0.239), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0144, -0.0915, -0.0958, 0.133), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0125, -0.0835, -0.249, 0.263), mass=0, pid=22, status=1), GenParticle(FourVector(0.198, -0.308, -0.779, 0.86), mass=0, pid=22, status=1), GenParticle(FourVector(0.0872, -0.0807, -0.00331, 0.119), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0412, -0.0374, -0.0475, 0.0731), mass=0, pid=22, status=1), GenParticle(FourVector(0.223, -0.201, 0.187, 0.354), mass=0, pid=22, status=1), GenParticle(FourVector(0.112, -0.278, 0.196, 0.358), mass=0, pid=22, status=1), GenParticle(FourVector(0.0163, -0.0165, -0.0691, 0.0729), mass=0, pid=22, status=1), GenParticle(FourVector(0.0662, -0.416, -0.297, 0.515), mass=0, pid=22, status=1), GenParticle(FourVector(0.0423, -0.392, 0.999, 1.18), mass=0.49761, pid=130, status=1), GenParticle(FourVector(-0.154, -0.281, 0.13, 0.346), mass=0, pid=22, status=1), GenParticle(FourVector(0.0148, -0.163, 0.0541, 0.173), mass=0, pid=22, status=1), GenParticle(FourVector(-0.492, -0.0681, 0.669, 0.833), mass=0, pid=22, status=1), GenParticle(FourVector(-0.00524, 0.0187, 0.0414, 0.0458), mass=0, pid=22, status=1), GenParticle(FourVector(-0.32, -0.486, 2.07, 2.15), mass=0, pid=22, status=1), GenParticle(FourVector(0.163, -0.0352, 0.313, 0.355), mass=0, pid=22, status=1), GenParticle(FourVector(0.197, -0.0351, 1.4, 1.41), mass=0, pid=22, status=1), GenParticle(FourVector(0.0231, -0.000527, 0.0235, 0.0329), mass=0, pid=22, status=1), GenParticle(FourVector(0.212, -0.107, 0.358, 0.43), mass=0, pid=22, status=1), GenParticle(FourVector(0.183, 0.0162, 0.408, 0.447), mass=0, pid=22, status=1), GenParticle(FourVector(-0.153, 0.0744, 6.18, 6.18), mass=0, pid=22, status=1), GenParticle(FourVector(0.0158, -0.013, 0.253, 0.253), mass=0, pid=22, status=1), GenParticle(FourVector(-0.562, -0.719, 165, 165), mass=0.49761, pid=310, status=2), GenParticle(FourVector(0.0459, -0.00904, 1.72, 1.72), mass=0, pid=22, status=1), GenParticle(FourVector(0.103, -0.116, 21.9, 21.9), mass=0, pid=22, status=1), GenParticle(FourVector(0.15, -0.235, 30.7, 30.7), mass=0, pid=22, status=1), GenParticle(FourVector(0.0499, 0.00878, 7.05, 7.05), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0692, -0.0259, 11.2, 11.2), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0442, -0.122, 6.95, 6.95), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0597, 0.0234, -0.107, 0.125), mass=0, pid=22, status=1), GenParticle(FourVector(-0.0582, 0.0745, 0.021, 0.0969), mass=0, pid=22, status=1), GenParticle(FourVector(0.226, 0.034, -0.0217, 0.229), mass=0, pid=22, status=1), GenParticle(FourVector(0.107, 0.115, -0.0585, 0.167), mass=0, pid=22, status=1), GenParticle(FourVector(-0.134, -0.49, 74, 74), mass=0.13957, pid=211, status=1), GenParticle(FourVector(-0.428, -0.23, 90.9, 90.9), mass=0.13957, pid=-211, status=1)], vertices=[GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), 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GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-0.000305, -0.000129, 0.00122, 0.00127)), GenVertex(FourVector(6.37e-06, 6.77e-06, 7.53e-05, 7.61e-05)), GenVertex(FourVector(1.3e-05, 1.16e-05, 0.000161, 0.000164)), GenVertex(FourVector(-4.7e-05, 0.00022, 0.0015, 0.00152)), GenVertex(FourVector(1.58e-05, 7.46e-05, 0.000113, 0.000136)), GenVertex(FourVector(-2.94e-05, -2.53e-06, 7.12e-06, 3.38e-05)), GenVertex(FourVector(-7.67e-17, -7.19e-17, -1.47e-15, 1.47e-15)), GenVertex(FourVector(1.05e-05, -1.39e-05, -0.000372, 0.000373)), GenVertex(FourVector(-4.84e-07, 5.31e-06, -2.46e-05, 2.55e-05)), GenVertex(FourVector(7.29e-05, 0.00025, -0.0591, 0.0591)), GenVertex(FourVector(-4.49e-05, 8.63e-05, -0.0113, 0.0113)), GenVertex(FourVector(-2.34e-05, -2.36e-06, -0.0184, 0.0184)), GenVertex(FourVector(-7.69e-05, 0.000124, 0.0001, 0.000181)), GenVertex(FourVector(8.45e-06, -1.73e-05, -8.13e-06, 3.15e-05)), GenVertex(FourVector(0.000388, 4.35e-05, -0.000459, 0.000615)), GenVertex(FourVector(4.62e-06, 9.78e-06, -8.07e-05, 8.19e-05)), GenVertex(FourVector(-1.74, -1.31, -2.66e+03, 2.66e+03)), GenVertex(FourVector(-1.93e-17, -2.45e-17, -6.58e-14, 6.58e-14)), GenVertex(FourVector(3.39e-05, 0.000146, -0.271, 0.271)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(45, -27.1, -94.2, 114)), GenVertex(FourVector(45, -27.1, -94.2, 114)), GenVertex(FourVector(-2.27, 3.12, -1.94, 5.72)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-11.4, -10.7, -218, 219)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), 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GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-11.4, -10.7, -218, 219)), GenVertex(FourVector(-11.4, -10.7, -218, 219)), GenVertex(FourVector(6.1e-14, 2.28e-14, -1.28e-13, 1.44e-13)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(8.12e-16, 9.34e-16, -6.29e-16, 2.34e-15)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-6.73e-05, -3.22e-05, 2.48e-05, 7.95e-05)), GenVertex(FourVector(7.15e-06, -3.85e-05, 5.27e-06, 3.98e-05)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-0.000108, -0.000665, 0.000442, 0.000813)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-4.14e-05, -2.17e-05, 0.000349, 0.000353)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-2.79e-15, -4.18e-15, 4.2e-13, 4.2e-13)), GenVertex(FourVector(-1.83e-16, 2.44e-16, 2.24e-14, 2.24e-14)), GenVertex(FourVector(-1.22e-06, 1.61e-07, 0.000133, 0.000133)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(-0.000133, -0.000107, 0.0305, 0.0305)), GenVertex(FourVector(2.48e-08, -6.13e-09, 1.3e-05, 1.3e-05)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0, 0, 0, 0)), GenVertex(FourVector(0.000309, 9.46e-05, -0.000683, 0.000756)), GenVertex(FourVector(2.98, 16.6, -27.4, 34.1)), GenVertex(FourVector(12.2, 14, -9.43, 35.1)), GenVertex(FourVector(-8.56e-06, -3.37e-05, -1.09e-05, 3.91e-05)), GenVertex(FourVector(1.01e-05, -2.13e-05, -5.58e-05, 6.1e-05)), GenVertex(FourVector(9.31e-06, -2.38e-05, -1.03e-05, 3.88e-05)), GenVertex(FourVector(1.11e-05, -1.59e-05, 1.27e-05, 2.36e-05)), GenVertex(FourVector(5.18e-06, -2.71e-05, -2.29e-05, 3.69e-05)), GenVertex(FourVector(9.76e-18, -9.04e-17, 2.3e-16, 2.73e-16)), GenVertex(FourVector(-4.57e-05, -0.000145, 6.03e-05, 0.00017)), GenVertex(FourVector(-2.29e-05, -2.28e-06, 3.28e-05, 4.05e-05)), GenVertex(FourVector(-3.55e-08, -1.18e-07, 5.38e-07, 5.66e-07)), GenVertex(FourVector(6.14e-05, -9.96e-06, 0.000396, 0.000403)), GenVertex(FourVector(0.000167, -3.86e-05, 0.000325, 0.000372)), GenVertex(FourVector(-2.5e-05, 1.12e-05, 0.00117, 0.00117)), GenVertex(FourVector(-8.93e-16, -1.14e-15, 2.62e-13, 2.62e-13)), GenVertex(FourVector(2.11e-05, -1.77e-05, 0.00335, 0.00335)), GenVertex(FourVector(5.97e-05, -6.75e-05, 0.0113, 0.0113)), GenVertex(FourVector(-2.07e-06, -2.71e-06, 0.000332, 0.000333)), GenVertex(FourVector(12.2, 14, -9.43, 35.1)), GenVertex(FourVector(12.2, 14, -9.43, 35.1)), GenVertex(FourVector(-16, -20.5, 4.71e+03, 4.71e+03))], run_info=GenRunInfo(tools=[], weight_names=['Default', 'W1', 'W2'], attributes={}))" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "event" ] }, { "cell_type": "code", "execution_count": null, "id": "4030be05", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 75, "id": "cd2644a3-5f91-4ed1-b058-5e3e2d6cc4e5", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2212 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2103 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2203 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -211 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 211 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 111 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 321 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 221 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -311 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 113 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 311 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -313 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2224 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -2212 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 331 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2114 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -213 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2112 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -1114 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 213 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 223 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 323 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -321 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -2214 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 2214 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -323 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 130 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 310 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -2112 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -3114 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid 313 \n", " warnings.warn(\n", "/home/apn/data/de.neuwirthinformatik.Alexander/Development/git/feynml/feynml/pdgid.py:70: UserWarning: Inferring type from pdgid not implemented for pdgid -3122 \n", " warnings.warn(\n" ] } ], "source": [ "import pyfeyn2.interface.hepmc as hepmc\n", "\n", "from pyfeyn2.render.latex.tikzfeynman import TikzFeynmanRender\n", "from pyfeyn2.render.pyx.pyxrender import PyxRender\n", "from pyfeyn2.feynmandiagram import FeynML\n", "\n", "from pyfeyn2.auto.bend import auto_bend\n", "from pyfeyn2.auto.label import auto_label\n", "from pyfeyn2.auto.position import feynman_adjust_points,remove_unnecessary_vertices\n", "\n", "fd = hepmc.event_to_feynman(event)\n", "fd.legs[0].with_xy(7,-7).with_external(r\"$\\textcolor{green}{p}$\").style.color = \"green\"\n", "fd.legs[1].with_xy(-6,6).with_external(r\"$\\textcolor{green}{p}$\").style.color = \"green\"\n", "\n", "props=[]\n", "for prop in fd.propagators:\n", " if prop.id in [\"Propagator\" + str(ii) for ii in [\n", " 187,\n", " 188,\n", " 189, 192,\n", " 190, 361, 505, 592, 647, 648,\n", " 191, 362, 506, 593]]:\n", " prop.style.color=\"red\"\n", " props += [prop]\n", " \n", "for p in props:\n", " fd.remove_propagator(p)\n", "fd.propagators += props \n", "\n", "for prop in fd.legs:\n", " if prop.id in [\"Leg\" + str(ii) for ii in [\n", " 187,\n", " 188,\n", " 189, 192,\n", " 190, 361, 505, 592, 647, 648,\n", " 191, 362, 506, 593]]:\n", " prop.style.color=\"blue\"\n", " if prop.pdgid == 22:\n", " prop.with_xy(0,6).with_external(r\"$\\textcolor{blue}{\\gamma}$\")\n", "\n", "\n", "\n", "\n", "d = remove_unnecessary_vertices(fd)\n", "d = feynman_adjust_points(d,size=15)\n", "auto_bend(d)\n", "auto_label(d.propagators)\n", "auto_label(d.legs)\n", "#print(d)\n", "t = TikzFeynmanRender(d)\n", "#print(t.get_src())\n", "#t.src_diag" ] }, { "cell_type": "code", "execution_count": 76, "id": "f0280e22-5384-4fee-bd25-f7b57ba2deb6", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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qi8eWUXs/dBKOxu3az3rVVQeThzCQ+uGMQMnrU3PG1Ne8VbmT/OKRdquqVBkG9DjqdupsQfMHbBaOnF7tiS1GCTyieypsQvHgIG3MYqNF+qHjgERq3U2gZaubiSCiPmrzZtXlVsegH4UzvR7iclTqYeNzwSWgud1TxTM4XCs1UzkgXL5qWKnBUSJgrjZgL4pvUb1nUwdAuZM+QlQ231EbvqVWpbVqG97vjZmtQc5No7U9WyNlHV/pkVq32/qZdDKtDfh5TPozr23EoTg0NVGCv26Ta4hFb/pEw7zp0TZLbzQgbU5v0+drVj5JMjayzcEDusPM0p4aR0VZonHitgVYrtX2nWRUG21fc47kt7VTa6NaGjhtMEy7KNJl04siwSSJ/JQWTKBZanErytio2f4o8pEPoQWFQkUvB6UXf1AqXK97EFAlHuykh64WierIYacd7XN1KvyRBlJGQw0pj3Pp0mt/PaGs3SWQNqKkuoEdEodgTSS7U8h9Qo9G5ZgQ02WdToa8aF96Oo70Dfw38d4Y3nhN/XWS2n2vDqQ6s1I/RjKO90sTcOV2oPCllbTKxLLHeUIPYSsXsf2oHqpACqGDQWEOQDAqlxpQpwNaG+QRYV2DgI3esUpj2c+myuYYykGdaoFXBWmVZYMueRCMoVQSKp7GBIJTz5i+h8EyJgbhIXlZx2LZWowYYxO1bYyLzcaAxPzIOHh7dKZx3AbUNK74uPsMKB8FLwMBoNXCCS6sCBvOOPzLmwWN4lglotW45KDgj7MFdElDW/pLunXp10APWxlFflWE35SgUOWCrIsaGGYOhS2os8zr8i41YrbE4iFlcvSgR1DZ7LwX3xH4qeKLayvifugxzjahVuXKluuggYgHR5OA02nHEHr6lktuAHyxofQIJJhqXjhCB9mIBPUHQvvX3dLJEmRD567EJr1zqcDsElw/aYJ0NwQGoeC6PplsdalN2oYLa3GxJLE0OV3hd93UEbyqPjHkT1W431BD+vrXCwVeJsAOdDBd49JldS67a76WYqJRs/iBRDJMBwFHhxI0TaoU/TwTrM9+KXYWjbXpjl50K4HhlvXOZDGxOKcYZHCnQdpm+Bp3UpZpLl8TqZ/EcO7w6QJj8OxAXYc1J2LeT3LujIZsGn0zvRvtGt0G0kLzWdZMhnxA2svQ8lcsBpdAOfRUk6KjTsYIG26fMiS9RgdlBNOIg83uNjeO1Z7wLpuFA4Jp6wBquH6vMGTQnDkeageEoUKG7tldF7QcDrotghZPaG/PTHQIirQK9M4wWRA0hc9AKTtVRZlTgHONxV60KgRggRlQdhderYmQTNrjBcEyxWhmfC1EH0VZmzLb15B0X04neDq9CFp+0Y6L7D/84tF+dztKkq5rpU0bsstBsDqK7zB9I/brckLq1Kjk0vaYi/4Mv9U2xAbo5sYbSpvyPtxm4KNtLIal99oDS5cfD2dlu+3X8OxDa8sJoHE4LVB+lDSCppJWMl86ClEah5ZgmUD1kASIpB0uA7T90K2PvjkZaOhc/Z0bR38NCfhox+d2Rz/Yy2hQphOL5LCFb26xWHIO4iiWw2cIh/h9t9umHhyA28zJm7atOYehDW1xuC0d2P4gN4k4Gn5ARP2ecYjWGEcOLI494nCmIIsXbAoNMXknXWfFJvY0v9xCfC7ar5wOM5BwP7Q8J2gPYnGzQS7z5nHnuuP0NwMZOxsn24W7LjJyezhVCM3nc8UkXfjiAgAkkTZgOz0W2D8kFFJdF9KEXDbxhlovfe895nQJ85LXGyhfOH30mInue0ShXygR9DKEpFhASdEREHQHtoZ7zw2RE/KSRqM5mTMBHa0OJaABs6RYtPJbNcgnhTKJoMWhRm7fcY/DkZRtRPoX7ZEEyEutirUAAIAASURBVHja7L15mFxHdff/KWP2tW321WmzhdWkFcISgpO0AoTEr1lagdjJ64SkFYckrwP4nYl/JHEch7cnBCshgDPDIghgwQxGYAyCzCSywUEGppFt8AbMyEJBkmVZbVmWLclL/f4453RV3769zfRM90j3PM99Zrr73rp1q+pWnTrne77Hee/JJJNMMskkk0GKc64CjHnva4OuSyZHvxw36ApkkkkmmWSSCTAPTA66EpkcG5IpP5lkkkkmmQxcvPcTQM45Vxx0XTI5+uX4QVcgk0wyySSTY1ucczlgBMB7PzPo+mRy9Etm+ckkk0wyyWRgopaeWQDv/apB1yeTY0Myy08mmWSSSSYDEVV8xoE13vvqoOuTybEjmeUnk0wyySSTQUkZGF1Kxcc5V3TO5Qf9oJkMl2TKTyaZZJJJJoOSKlBY4nvkESUrk0zqkik/mWSSSSaZDEomgJJzbikVoBxLr2BlssLkmFR+HC7ncCMON+5wRYcrOVzFsaQvYCaZZNKFOEfFObxz7HNOFi3nyDlHadB1y6S/ooSGa4BpjfhalDjncs65SefcnHNu2jk3jSg+Y4N+1kyGS45J5QcoefwY8lLUPH4KmEFDLTPJ5FgR59xQuQOcowzMeI8DTia4K0reMzXo+mXSXpxzFeecd87tM2uOKiQtFVfF+4zRn/l3BKh670/23q/WY00WPp9JUo5V5WfK4XJAzlMH2uUR82gmmRxLknfOzS6x26EXqXrPDID31IAZ58gDWcqDIRdVpGe89ymKq++kuE7QP9dUNlYy6SjHpPLj8TWgiFh7TAqJz5lkctSL934UAZ0OBauu91QTn6eQRTR7N4dfqmZhUXfWjEZZtVVG1N01CfQj4muGDN+TSRdyTCo/KgUklwxqBSoiu49MMlmxohiHXs4vsgLGvlqBMhliSYarq7WnpeJqLjLgNuA73vvRTi6yLuowwxIp8s65Qq/vVybDK8ey8lMEcLgiUAHWqEUok0xWtHTLaaJuCiOYG8qxry6vjPxuBUva2NKx9yJEMVoFPEF/6sZF1kmWZCybcpflHjs65JhkeFZLDx4/5nB5j1876DplkkmfpIrg1+bbnaQK0giwalgVH5WkezqTFSI6xloprgeBJ1s6C+dcVy6ylHvEYez2/5KMZ71XjQwicVTIsWr5qU+oHj+/yLIyyaRvYqZ159z4IiKxurH8FIGpIVd8APLek72jK1OKtFZ+tsQfOrnI0iTKCWauW4MyrOnnQ+g7Oa73mvfeZ2HzR4Ecc5YfdXMVgJzDFT1ZCGQmwyPe+6pzbg0yRifpHYvTLWPuFMKtMjLkk/mwK2eZtJa89+mbS+/9vHNuPjn+elTGi0hqjCWjQHDOTSIWpSnvMw/B0STHnPKjyk6m8GQytBJFyixk4a/RBWWD977mnFsNjCuIcyhxP95n5HQrWDqNp7WIAl5FLDa9YrtqdGflXJAYtsd7v3opGymTwcix6vbKJJOhFuXdWQjQ1zA/HcV7X/Per0GsQLODfuZMji7pZFFUZXstArpv5yJrJcsR1j50G4JM+iOZ8pNJJksoi8gmvZDFwBaUnu7pvZ8A5oeI6DCTY0Q0gqoK/GorF1mHa5cs8srC5vuRdiOT4ZNM+ckkkyUSnTSnF6hU5Fh4iHevETNlIJfkackkk6UWfTcKwM0LLKLlWF9Iqo0UmSJLe3RUyjGv/GhS00yzz6TvEiVtnFzA7nEeqDjnSgvgFan1yPVTBoYS15AlMz16xTk3goD613rvz+/i/JIqNBWNhpyF9Hxvi0y1EcsYZGPwaJRjXvlBdtjTmQKUyVJIlLSxJ2ZYdUVZ8t0RDX+fc85Vuri8K9yP7oDLwOphBDurFJ1jNlOCjh5R64tlW1/VTdJRVWZGkLE9gyg9qzU9S5osKNVGUvTaYX03MlmEOO/9oOswcHHUX6w1UaLTTDLpm6jSkltsuKzudte0w0foveZVgWpX1iQwMewZrzXTe957RhddWCYDF+XM6YkvR8f0zGLGqpYx1q2ir9baEaCQRXwdfZJZfgCPn8DcEyyYWC6TTFqK7lDziyAuNOkmlL3biK8pxLW2ZOHCixVNbzHCkOcey6QnydPCXdVG5ukDuLkbxcc5V9SNwSzyvvWVNDGT4ZBM+VFRi89qoOxwGcAtk6WQNUB5kbmB8l0Ak7va2Sr2YQwlOxx04yTFOSzb92jG8nxUyRSST7EXWVRYe4dUG/F5FVTZ9t6f7L3v2lLUDxnG9/BolUz5iURTXawGCg43Puj6ZDIYUUxC360hMa/JQsrXa7pRArpleTYFaBVQ6BJPtJwyAsx437OVIJMhFnXH1noZb+rmXQwVQ7fUEQXErbzkruAWQRCZ8rNMkik/CfH4msevAXC4DAh9bIqFqI/3m+NDrTajLCwCrKvdqypZXZcdkR0OG6g4y+h+9MoowqHTlRV0IWDlhOS75BF6OrBvkeHx3TzPJDLHzOpRUWUwG+/LJJny00I007vkPyIjfzuWxHs/770/mZAlut/lTyFm/F6ti/NAqUveoJ4UKwWhDpuFZQyoOEdFsT+ZHCWiCnpqGLkqG+Ma4TjrnPPIu7IYwHs3WJ8ysAnBly0mPL7TffKIMrZKs9qvJqRcykD9yySZ8tNGFAg9hgChMwXoGBK1yiw0xURHUQD0Qkz/o4TQd69/08qY79aypIpPDoYrj5b3VBGXXA2Ydq5nnEgmwy2tFNoyUPPer1YFwen/C1ZAuowsq3rv34W4yHIsMDy+y+euu9XU8jrjvR/NiEaXTzLlp4N4/BRZJNixKJP0EBa7QDHTf9fjyns/5b1fo4uBQ8ZmWhRZVxgJU5y0zKHjM/GemveMec/J8pxk7+BRIDruSqRbOhbDbr5giRSPCYK1p0yWCPuolEz56UI0EmwVEgmW7T6PcumWJ2exEjFAjyw0r5aWMU/zLrpb3E+ZlWVqz6K+VrA45wrOuTn92Ipcs2vA/hJK/d1Zgk1BgYw4ceBy/KArsFLE42sOtxqoaCTYqGf4dsqZ9EWKLFO6B+/9vHPOUmCsWuBEm6MZr2OWn06ugiqiAA2VyyspavHJeZ/twleqqBt2EommamfZmWEAUU+6ASkj7/+qbsPj25Q3TqMSZ2O3xJCmkzmWJLP89CAaCbYWwyBkkWBHq9Rg+dwrC02BEUkhJTS3WwvJGiTMfXpYyQ6do4j0R0Y2t7KlgLA0t1Uoeo1WXKxozrA5NH2G8vvU6D48Pq3MPPJexqBmK2tNl5FnmSyhZMrPAsTjRxG/8GwGhD4qxXA0c31gZO5K1MVW1d1iP6QrzE8U5j7BwjPQL7WMAGu9z1wFK1yqCMatSbHRCK+iHsu28dDxPoK44NYkXN3dhsenSRqoeSoDNQ+PZMrPAiWREmPY+FEyWYToRLUW2a0V+6iQdLrvWhaWAqOJlFEn7V64fqYQ7M8wjuVcL8+SyXBKFN4+ad9FGKBJRAkpIorDcrmF8og1Kk3JyZTto1iyxKaLFLX8jAMTqhBlcpTJciYA1V2xJS/taoeoBGyGkbAs1FWgrHxFvTznzFIDvXtvE+wdqwJTGe5nZYtuJmre+1Ej9usnj06PdckDk+qa6me5I9B1iH0mA5BM+emDKPZnEphXTFAmR4lEysjq5fLTqyl+cqH3jICbvwH8QpfJHMehbn0aSnGOkj7XvPcMbT0zaS/2TnnvT16uyMoO9ZlGaC16VqojUHMOcTVX9a+50jJsz5BK5vbqgygQejWAw01mQOijSirA1HJOYotMgWHXTyHRnN1w/Qy94iP1Y8p7zb3nBh4KnckCRZXxmirpi0pY2icZYwEBDglQ88lI3j6jnVibKT7DLZny00dRq08ViQQbysiZo0mcc3nNidOK5Xix5ZcQ0OOy8+BEKTAW+lw5wCEg5pZ5ivT7/LArPqG+dfxPtrCsQLHUFYirq6rWlq7yey2VaB0WooAlQc3z3vsJBTUPjWtW58hsPUpIpvz0WTx+DIucySLBllpqyOSzoJ1bF1KBwblXTOlaoGL3h8A12jbt8hTVEJD1Spkc1UWRgVFXmqjSPY3gfeL3aqCW8iGNcOzXs+WRdz7bLCQkU36WQBKRYBkd/xJJlBNnKXdZg15kLQVGr1FYOeBzUHczpOYpivKFTRtIc1hFc3vNeM9QAbIz6SwRKP8CNKedWW0ZUEJd5feZRIkXF1DESmBqHmHICUwHJZnys0SSSIkx1IvKSpfFMrG2kTFgVifpgexOVXH5HoL/2R+5r9Z1UIgOAHei5vx2eYr0t1UI2eGyhPUvUErer6hUHJkEKQPrgb8huC1nEKDxslpXo/D6IhLFeXK7yErNMD+rvF/TOh8Y+H4giluXz5kHisMWvTkskik/Syia/kIAmgz1orLSZUmUH500LAR2dgHWl0WLcv5cqvXYB/yZ/vT8DuHBE8A64GW2ywae1yryKyI7zDnnBorBaN8eQ8lDlElnqQG/DIwqJmZiGay2raSCUEms7XT/NqDmAsMPas6sPm0kU36WWDQSbA2Aw81mkWBLJkvSrqoUjCJK7CCAg1VdJKrA/wN+QetwqEO9p3SyfjCyw94BPErN/Kmi1q0m19gQyWqg7ByzWXb3FSf2Dv3yoCuCjPFulZZlBzX3I3gjs/p0lkz5WSbRSLAMCL0EopNQPjJL79NjQaHiLe4xH/9dxmerQn0yywMPAN8GHhfhJtopAt/V9rkX2bWmWk60naYRN8BQ0u97z7yGuq8Bis6RWVNXiOh7sw34uUHXBXFVHe0WxMzq00GyrO7LKB4/4XDzCBB6rWd4wiFXunjvm+jwdQfVl4zlWtbA/PsRMHnUObcNONRlCH5N3Vh5zSDfpNgkFJ+h3yl6zzywxjnmBl2XTHqSuxDcz6BlAh3vXZy7EkDNDRJZfVYEfcWgJFN+llk8fsbhLBJsLEuJsaRihGOLElUeiixhviFVrooEMGgOTVMRKzk6sf0dsM45V+jCSmOWKlOC0s4vM4RpLdq3F2WWBuSeSQ+iAPxCl2PnPu/9FYOus24CZpxzddoHff/MGlQlMDWXWeI8Y/pOx9bbQuT6Wgj7dWb16UIy5WcA4vFVh1uFkiFqlvhM+i/9AkKPIwDJJdkBqlIypbmOyt77CefcSIu8QEUEg/AlJAKsE4V+DdkF1vMotThvxWDRlN25gvAXZTJYmQfGnXN0sUgP0xgzYsOpyFJyMtQVuiLLBGqOrLro/SsLJVbNrD7dS6b8DEg0EmyVw41rJNiofpdJ/6RAf1xVtX7hYJRLJ20RmNFJd14nsFYTbl4nyz/Q6DNTgFqNnSqNDLpp500gYO5phjyCRRmeNe/ZynJHHI3iva8550bR5M4dTh8K5Uc3G7F1JAlqNstPP+/ZlWW3D5JZfbqUTPkZsHj8WoerIFag1ZkC1HfpR3vOa5TU6GIVg3ZZnp1z4977tTo5t6p3LSprShWmdkzUNQJ1/wyyS48/m2K31hh4nXOjg8qy3YUUEKLDzOU1BKJg+xG6IwkcmFKtuLYy4tqqIe/ysmAue7TsLuY+mdWnB8mivYZA1O01AcxlkWB9lSlkMZ/UKDD7vyceG+W/mdGy2hIe6u8xIdpsN7nHojBzk9Q6JidM3TXmWpUfW6x0sl9F2OUWgRHn3Kz+PoUsYn3Pk9ZHqSKRXhlx6ABFc3RNo1i4TpbRbikiloJQNAL05xD39eqE4tNus7FoMaqKLi27LMISlFl9epBM+RkSUeDzagQIfbSHYS6LRCSFEwiT7GpEIeo5RFq5PQxjksqVE+3wVsX308m204QWsy/H1ppuZC3tU2DUy4pSghjZ3BpChm2799CKurpWAXnnmNOUF5ksv2iqEb+mS2toL9w6/Z7/SoR3y6gwJp1zI1Eww3JYgcpGy0Gf37OM16d3yZSfIRJNibEaGMlygvVHkvm/1LqxYPO7KjH5Fr/1tMNLyIRZdcwN1cszohabFkkau3ER1XSHPAnDnULCe2resxZRgnIZ389AJE/veLpuFvx5+p/lvQY8EwU1e+9PIFhIishGZUndqN1adhchmdWnR8mUnyETj59HFKBSlhJjyWTBrkW1rnRSaHre4SUBy71ii/T8tQgAOuk2qHVw9Vk95xAlbFjxPolnpoZM+CslI/3RJBPIWDvJOVfuIjN6ah855/JqgZmM8m31dRHX8Xwq8K3ou6r3fkytn8sx3hdj2W0rmdVnYZIpP0MomhJjNYDDTWcpMfoni0mC2gW4eDl2eC1FFa4xmt1yLRUpfaYq4gocXYETaDdRRpn0WVRh+AywBbUAaSRjK2myguq7OK0fx9Qqs6bfVhh9Jx8GbB9gky3YstuFZFafBUim/AyxaEoMAdqy7Dml+i7OuZICgQeWJZ3FWQnG6RwKvmQ7vG5ElZf5RHb2dvWIQ29XVASV4n3mvR/ezNpHudwN3AKM6ILeyVWffG8MI7dgt5POKZ3e6WlEsf/nQTXUYi27bZ4/s/osUDLlZ8jF48cQrX7F5wTT3eIqZCEe1LNUkTxglhdri3POO+fuMtO9RrI0gC4t/LyL8Nil3OF1JRrqWohyflVpzbFSRQChNwJfcc69c7nruxBxjiJQVOxPJoORPHAlQelpp4Skjb9247IXmW4F9tdNwIpiL+9RMqvPAiVTflaAeOohyJNHCRC6X8zLPYvuwFbp/Z8DfBHBWE0DF+lppRQcgClNxS7Kjz8PittEgPMBi9EKpF3Tc38GfB5YN6D69irLFaGTSWt5KPA6unM7Nr3zujkoLsYKrO/pGCkRYkb/0GcSwaGRzOqzOMmUnxUiGgm2CigrKeJKlUnEvz+wkGqNAJsC3ue9f79acz4M7NMJpZZ2DaKAjihvz7JheRb6jFrfSTrssL338+p6+EvgygG6JHuRCaDkHBXnMsDzYkWtoF7DwFtaQKPzS8DbaUyw23ZDk3zndZz9CMlVt9B6G8niWMr3RYY8cnGRkll9FiGZ8rOCRNmfVwP5lRgJphNSbVh2KgmcQR64mUbMTtP5yt0zhoSVD7UVTp9vDLFqrerysnkG55Ls4dmY12eqAdOqBK0EpW3oRMfxjPfeIfnSbFxfgij7ScLOTcjC+yrgOovYov1CnE/cM6dlfAB4dAewdKt6jyMWn1Xxu6wbkzJCvjjUvFULlczqs3jJlJ8VJhoJJsR0uNkVFglWYngjc+pm+U4TplqKVjPcTMhW1wlEmbury0tWhPIjz0bNe8a852TEsjXUyugQSzXiwaoheebOBK5IEnYi78jrESUpp/iyZwK3dggZT75TJeBJSJ/dRI99pwpbTglEa9H3BUJgwlGp+KjUlU2lCqikHENtnR60ZLm9Vqh4/Kjif6Ydbq26xYZdqshOsm+JQvssD6V7LFKBFYI50ZxCb3TOFbpo92Qi1JUiFrGWSY+SHBOaM64CjCUIO2Niw4ciCsta4LldWCBqUFdaSsAvI5Fi6zTXVa8bCYtSrEuUxqJjuo2VLMkcXv3OEXasSGb5WcGiKTFGESD00C9Yig2wDOKzS+U26hW/oFID/hh4qHOuGB25lPJzyO5yJU06/0p3aQOqrBDLj4lzFJCFeCX1x9CLWk5iws5rIi6p10B9IW5rYYnewRFkbK0F/gX48iLcNhMIWLqiZZviM3o0KT5puQKRCLsfDbpuK10y5WeFi8fPYKkNVkAkmPd+Sk3oa4BSvxWgNviFUgez/ATwAPAixPJhx3TKuQbaXkmT7AxdKDW64K0Y5UdxPpPAGmV8zmSRYkSgKYSdz4KGCMECgtnpZAE1DqkcwuszT7OFtad3KaqDJVj9hJY9rG71nqVFrsD/BI54798w6PqtdMncXkeBeHzV4VajZIiaJX6oxXs/75yboP8LbdWUEu99zTk3083uVM/9etKErBNr/Lmg56+oSVbbu9uoqKpzLj/AMP1epAxMeb+yCBqHXIxGoCVhp74va5D3LfXdUqtMEXgqcBhwwO845z6vrtiijskSC7Da6X3XOueuBh7vvX/ToBuun2I4rITr8RcW0laZNEtm+TlKRIHQkugRNznsQOgo2qOvuJk0/AJtIrgS5x7tk8pMB9efyUpyfRUY8kz0K1BM8e1E2PkiRKlpkoTVYgvCIfVJ4AELjVfMSo5F5JNTV9oJwHf73Qjqcsqry3yQVnVzPb4KeOFK23gNq2TKz1EmmhJjHrECDbMCNIK4p5YFNLyIyI9CopwqYhmZG/ZQ9xTpyvXFIiK+nHOFThYm59x4HyNRRhG+n3Flfc5k8VKD9oSdatX5GC2itLz3M977qlotjgA7gOsRBbwYnVdd6Lup79+fAQdZGj4fwzzVgPIgoqcSrse3Adcudx16qGsxwigNPRVLpvwchaJurwlgdilTYuiuaHoh1yEYnCV3zy0mkalK07Va79VIConZLjJaD4vM0F0kV5WF50DLIekG2rVJsV9Kr/fMe88qfbYR55qSumbSo7SzgOo7P6sfP+u9v6xDcWUkoegjEGWiRh+i8nR8vR+YBX5ticLa5wnvyyiDobYoIwpjHngpQwRV0bFQds5NOufmEPflPLDGItGGWZz3ftB1yGSJRBWfSWBUU2T0/x7OTdJj7hzdQRWXSfkxAPSC8Cv6Uq9udb26kUre+zVL/Sx9ao9ZuiB/c87NqstiIfcoAJPe+5Nb/DayVO3lHONIstOj3YU5EInfd+fcSAdFycDopvS8BHgibd6nLutQAL4BXOm9f0sfny2HLOAFROmZR5SeAmKpHl2oe24xdVJ81TiyKVnwXNan+sTtA7LpmFphwR9AZvk5qkW5fyTHE70zqHYpowh3Ty+7uSoS6TW+DFaTxQJ3R4FxDTO1Yy7CzvQrOeNyyQzdhbwDdRdVr89XhpaZ1ossbV63PCuEf2kFyzx0hZH7OyRC7HXA44ETETbmxSg+RjPxdeDHfX6uaZTLSBX3CUR5KyAK27IqPlAHltfZnJdb8TH27si6Y+/vau/9Ku/9iqUWyJSfo1w8fh5RgIpLkRJDX8YpZGfU7TU1nVyqCOdPJzfJYmRR5nALzY8PBPhpCsQkw8tanSZ13I+arFspNvNqoasCDa69Vq5OBYaOa7u1surVE5Lq+X1THJ2jglh9VuRkvEJkDNkMdPO+vhj4U+C7aqF5fR/cU9PI+/bnRDw/fZKaLuaGSxpBFvm1A458XLYcXsaHppueOUTRBAm1P1nbYupoYM/OlJ9jQDQSbDWAw/UdCK0LXbFXBUZ3MpYra0mwGksZwaUT78wgdoQt6jPSqQ8UaxPjflphluYJjL7d4jRM8Wnn789HO8Uigg/qAwaEEkd/IsuBi/bdGmCyC+qER8fjbbEKhCrWMzpv1Mwtq7i7fsxp+aicIhKFNlC6h+XI4aVBCiO6qZklsNev0g3fSuM060oy5ecYEo0Em0L5gPpc/Chhl9CrrAQ+mVjySITJcuGWSl2GqBfpTkmZVx6fCWQ8pIGgZ4BXIjvtjlF5qkA9lTaWNn2GejmqNM7Qg9WwjZTJiA6XRXQh7AYAPGOYu8Xe0yw8yfdNP/dkeW4jcTk9uYeXUPpu9bHQ/ci6Y8+8Vq07o0eLdaedZMrPMSaaEmMMUYD65mrSxbG6kOzMiNK0knbseeDBLB+2pIZY1ua6PLeTzBDYtYuku+1ejuzwR9MUvJSw3xrwFOBJbcJcC0R4H1WY+oUBqrEyc5KtVOkmcnCKPigQ0Thd6jliDA3d1/mstsD5rC/ST6uPWncqGvDQgG3y3q9R685K24QuTrz32XEMHngKeObwlPtWplgd5pBsy91eM4JEBg28TXqocwU4R5+10svzLvK+sx1+n+6ynILWfTqt7sjEOIdgINKun0Qm5bR2uRrY1qr+OkYMtDqXVs7C2sbnwU+DnwXftzGdHan9mNe+HOni3Ju7HZctri/auGnzLs726x2M34mFzGd9budxWNj8rH1U1nd1Tv+WEbfzwMfQMByZ5ecYFS+RYKuAsqM/oEEvZtIJeuPDsMzQK0kMcPlT4HeQyJMlFbW09MsMXULSAbQLea8heKA0N1qrHaLhhI5P4kHss95vGpj3suvsJ9+P5YwrOkfP/FOZdBZ1P00jANhu3TE/WeC9CogCsDY5TtV1M41EkhWAuR6SGKfeS58tZ/fSv8YQv5g269nCvhCrT0wyiCg7eQJQeY0fQLTYMEum/BzD4omSA+LG+wGE1gmxMAg21OUS770t3L+K5Np5Zg95s1qKTlyWvTnZF/10DRaAO5xzp7Z6PsQV9Xi6YHqOFqIi8Arg72nGfxUJ7L7VHhbOnkSVoDVSr8wN1k9R5SCPAGGnWpxj0UK2CP8Y2L+Ae0UJa1PBtmXgPuBc33sSY7tHIYF7sfkwln4AqccXwAbfEeuTEoZuJIMrPgx9OSRTfo5x8RIJthZ58fsVCdYLG+oYYmGo9EOBWG7R3eFfsHCwd1zWqA8UAHFouRE19msimwE88LlWUTJeIrYOIyy6nWQSwQ+sUcVwguZFwyJIqgh+acn62jkKyCKdTfz9lQJiSWiXyNSiheYRK9wP6dFiqWPSrEvt+nC3WQ61Tl0lMY5knATuRe9fds5dqApFrQ+K+mqE0qOrMd/O6hMplq3C0Cf8UQ5U7pdkyk8mQCIlxvPceg0f3beQRcr3AH7WF3wVlo+sv7wdy9N2usvs1dTeRoxd1qSvxH06mW9CLDuvbXPqe4GHdtGPFhKPtkOFZtdY0Uu+pxqiHE/2k+Mn3LuOJxr1WeRXv6VTZF7Rh2ih2MXSqxJqSkk7l88E8PQYXO8TSYxVSfA6j6W5xHKx21XH40Vaxs8DX/CLjOaMEjjP9+Byqlt94jD0BMngUR2GvhySKT+Z1MVLJNgaPkURjylDC3UdjCLJADsucF44OybU6pFfoS6ztcjublELeoSNiSfKGS27nDh3QffS605EEk6+t431Zwa4l3TXV3xNPURYF6MCEY5LF55qVO4UgT2331IBprxnKLiXjiZRpbnmljBppZb9HGS8t1JabM5YrfVpwKZ5YUU2JegE4FPAx1Qp/2DkEpt3zm2KrM4lxG075oWU8a2LfBazhEGzO63VNacA/wuBDqSFoR81JIODlkz5yaRBPL7KKzgdqPA+HsICE1zqyzlGD+4gncDMZL6ixC+A6bqFNHDhaNkzwE1IGpGaTtaGiYilG3xOAZmQq8CnkWzbhRbnFpEd8G69Z0Un9NcC7zIl1QeSy036OQmkbgpnt139EjB7F32W12vJRN2htLDQzqf0Z4Eu3VBqYSzQA47HRzw/iSTGVbM0eu//EjgFccHFiVg/BTyfQGaYBx5GeP8W7JpVJS6HWGhGu1FWtO2+jGRun/HHchj6Mkim/GTSJN5ygr2AN/I2XrfgchT70YMlZwQxd6/IF10n4tIiF/Qc6Znk34hgKG5B8Vk042raWoISINIxYAuy051PObeCWFG+D3xKJ3Dj/FmPJJWMlbS3Ar9OOmdQkUSuL12oesFndCs15/pCeJdJaxklPQJqJu37btwyaqkpAe9ZBI6nrmTH94wiJV9EcImVgBuB2xNl7KY/hIl5hCOrHelnJbJsWVj6O7z3r+sGsJ3J4iRTfjJJFY+vcTrvBHC4yRgI3SMOqCvm5+XM9L7EspY2YG/14bdTBqvILnZEQ1djc34VeEwEwEwqWZ2UxgKyI67qpPu3CKi5rK4DizTbBZyBLBRX0LwDbrqP9/4WYB9wZsp9G5LLJsKl+63orgbyzjHnHBXFAGXSXymRrqBP0DwmO7a/jsUKEqV0RaLMBhxP4jrLJVdErMytkhjX88lFLrGqvk9m8UGf6UrEirlY8s0Z2sx7+l4X9V2s6DOu6hf1QyadJVN+Mmkn83yOx/BGnsBvMueOczUNaZ7sFpisE8xUF+eXWVksz62e15hh24W2WnhqLuX6KQJepoi09ZwqQgUESG4LTHKib6tIaN3yzrlzkV3mWxHl5+te8iSNKY7iMd77Z6gi2hB51kFuBn4vkQS17sbTxcowEKt64TDpvv2pec9aBEQPS5Qz7lgU7b9JRPlZk/J72jjJdyizgPRRO84pfArPD6JA1yI3a6vrC8A2YIeOvz2owk9kadV3LwdcAHyORaSViPBRrea9MvAtnU9zGpqe4XiWUwbNspgdw30gk1eRT3ChMkIXkAlitocyjCk13+accaAy6OftU5t1ZIZFQ4K7LK+ATPS2QzROnenEeR2ZdLWsI8AZ+tnKtFQTeWAjMB6dP5kooxj3VaJ+xh5diMovRX3ckRW4v33h9w16PBwNR9SvI9F3OR07BuxtGtPtxqTNI7Rh+dbxWEr5vtLtWEJoHT4NXILk5NtKG7ZjfdbNfZoHUp8PwdptZ4EMztmx+COz/GTSVrzwtsz4P/DvRbM54ynRA1bDB/BzO+vPKIIPWrGcP4nnbcl0bRgE332Iqll0CsDT9dqezOMW9osoKfuA9ynJ4REtt6xl5oEP6zXjWsdCm3JHkJ37mA+kapb1O0fkcqD/+J4OzywYsuW851EsI0jEkYVgWwoUo2EwYr0Ya9PS5RVZbiY6jOV27qduXGqG97kPeALw/yGWzXZsxwXgmYttsGgeaHBzO+cuAh4HvNkvYbb2TNpLpvxk0rV4A0JDmefwrJ6u7QB+9hKVsVbLN86fFRHybrTyiedJZbrWRaNXtmbDWFj7f63H+hlJokXQ/ABZDD7gvf8b4DdodE8UfWNUT5rSklOXRYkEVsEHLMVr9LNdP4a4G/od4ZXyzBS1bivelTokUqNRCc4jisuoD/xNSWkX6VVBxmSnxb8Vjsfer/EOlA+mfN+kdfkW1N+JBlFyw23AHwLv1s8LTm2h7/4IjW7fceB3gd/rYfOTyRJIpvxk0pN4/Dywml08y9GZ7yMmGgP+FaF6P6kVIaAqQZZ5fkUoP8hCn7agpzFdKwFfTxOfRUuNAYeAf9RJ+sVdTs5V3xhBMwF8D3ieKiL3IlFd0LjIWVRPNUURzQPvIT2vkoX5PpkIqKr3NqvQUjI8G9HhWp8RHfZLLJLRxluN7kLBW0US4rsLbkjtPx/x/CAbpVYKkIH8xwjRaE3Z5hXLVETwb6/w3n9Jz+t5nOpmaBpRfNZ47y1ibRp4ADio5WcyQMmUn0x6Fo+vcRef5Dd5jftjt8093G1UUO6svvRAqsXhjciEcrHvHMrZxHczrOIDR0jy+xkkVDcOnc118exJKXjvqzrh/yrwCWQSBfjDTmDyFEWrgHD1vA1xWV2CuMLsXANcm8UpudBVgacBH0f66AJCiPMHtfzVhJQWybr0kv5kIVIAZrzP0lv0S1RxNSLPgrlDO1hdmn7TOaFuWezivmMdfq/z/CTuY9bYIkqcqpuq1wNPQiK6Kpofy/iq1gC/mHjmnt5VLauCBg94ieYqotGNSJ6zzNU1BJIpP5ksVEbZxD9zH1fxHzwPzxovEUPzkZUgaXGYQaIoXtZu56/KQs+4lkGJPu8R59z6FAuJuXry0fk984jE5fqQA+xW4LHAGd24CBPRVp/y3l+OKDY/Rq095uZS641F9RgWyO5fA+7U/lmDZLifd86dB7yKELlTbNGHVfqTMLKV6MJMxbmFE9Vl0iiq8KwmRNB1ynjeQFiq1t4yXbId9yBNPEDqihv13jsvrMg2DjcAW/T7Ud24xJbbGWWWnnbOlRbgmioiXGX1FBuIMrRGNz0lMuVnKCRTfjJZkJh7yq/3v8dr+Atg0uEafPzJiUNf/rfRhvtHlYQyUXqEFSDzwFXAg0nsQFPA3spD4+Z6wBOsQRQo4+EZ14Vkkx7Hd1nOODLxTiCurHEk59BnkV18Reu/BzisbgWA59Hs1jsQPd8apM/OBX7dC5dKQ0oLE633LEu4AHgJd19F3SXCeMb30zdJpl3phN+ahwYun7W+TyHdUeh9RwuRnm/Emg2uOFWAZpxz56tCdAIyR42klNHJYjmBvKsnad3yyGagGlnCM1fsEEim/BxjoiR704rD6QsTrqduAZjk13hpx/O9/6TWJQ33U0Z2TitmgtDJ8/NIGG3a73WwdwLYXewmT5K6vNZ4obtfTTDzPwuxtNynp3bapVoC0tOAs/Q7UzJrSOjt1cA/AA/V70ve+w/TBvugSm4VccWdqF83ROnoQjVNIHNb8igs7xnznpORxW7J8lEdK6LWxVlgLMqF1W7M5fS6mFm8L67IKFqs2s6FZu4vtXhOElmjEzIK/GmUW6+KWDM7JUdtEJ0LNiCpNOy9tbkss/oMkWTKzzEmupCuRpSVvu2GNRJsFc/jFN7Fu9POSeTeaZUIdAYBVvYrQ/qyiE6ov01rosFRBOyd0/PnFWPQc+STYYkQQPGLgb/v8tIpZAEYBb6pi0ZOd7OHgd9HlJfXAU9UN5ZN3POtXJW6KP4SAmif1L5LprSYRZTa1X4RrM7qyvLOsc85c9WRc45248XI6zJZoOgY+TBwDaJ4TyJWw3YWlzywl8Dm3U8MliawbX1/HYcVNEpSQ/FbnZ8Dfoq8o0W10vyIRsxi2zxj0T3fDnyFaMwllKrF9kXJLTKBciaZ8nMsy2Lp25vE42tUeTsbKbhPusvdie58ZTKe1QzFf0hgU01NBBrhSIrq5ll0pvRllCPA3alto0zX8fPqTnKhz5ZDyNvu65YrRCf+OxGckF1TQxS2MeAu4IuI++5m4DEEwHKVRutPXnfAhmn4NPDviEVrBHhpQsmpdVvPVuIc6jYgZTGixWKEWR2yHfcCRfv4lYir83NqgVzVjasJeD+ipPS7/buJNisikZXdWJLNfXs81K21G1HrD0IvUQbeDbxd56Vz4k1a5DZeDfwpjRubfnJOGcVEJouQTPk5dqWwFK4H/x1/Bdt4L5dxIn/CO3g5H1Eg9FqEVbi+IPoWiUDVOhWnKFgpLotdKBamhYzp8+ZVoRtn4dimIqIAHafkhV9GFIIms7yZ/VUBfQyi3PzQObcOYcmdAH4GvEwvWY0sLK9V/I5N6l+J+iqPJIZE+/d4tWbNAx/S+8b9Ot8HN2vVe8vRhCa97JgcVflkMrLDRUgeiQYc7XHOWEVn69CCROeOXAeen3m6p8uwiKyPREEa1QgQ/ddqAdoK3KL3v9t7PxW5dHP6LoC821VoyOPVLwVwpofnyqSVDJpiOjuW/0DTESxBuUZ3L6kNPGVLiaG//yjlmiKdKfD7Xtc+P7eliLgIUYDM7VMkQaGvv1kqiK7SeSTP03LH9V7XaJmXIladOWBT4lxr/7L+/SBipfo0jWkq9gMb9X9j8L0wepb1hLQX+4io+WlMe1BBds3x70b131c6f/AV8LkWvxXBD/XYWQmH9v0twLoe54Idy/TuzZKSSkbrMNfh+g0Id9Z+BO82a+9nPF9G/2/R980wT5b2o6z3G7fP0TXlbt/1Fs8wgtBRXKDPO8cAUsUcbUdm+Tl2Jd9Pojnd3ZgVAefciMdPYKR2uBICqG0Q3zkR6Ah9ds8tgUwhk+AfAjsJebKKCIZgLvL5TwEPB87yi8tgXwMuQ1xYZaRtd6G52JxzZ+t5VaSvCwTczh2IpacIDQD1xyDuLvS3XcCNXsKGZxB8kRG23RtXxjfu7k8DTiUy8/sQFTbSb4JD79smtBz2sTP0on1/GXB6D5cVgc8uQ91GCeSFyd/UOpiOH3TOXYCM/1cD53rvX0HApY1G5ZgFJw/s9iHT/NNQIDcy1mcRS9fJvtHKM8LC3a5/o/f6JeD3gDcA7yC4qzNZqAxa+8qOwRyEBJnThKSE5ZTzcqiVQo94R1OKvj+Pxt1SfceFp4BnlpO4oUVdzMqQS3xfpIcEqkvQRgXaJEBMaad9pOw0Sez8EILBI8BJXdajknKvWeAKZCc6gkyEB5Cd7EeAy+3e+tcsNhsICto6BItj5XotN4dkwR5P3HfO6qP3rScwjc45D1GMCq2ehT7tWMHnwZfa/J4DPw1+EnyxH/c8Vg/gDOAzPZxfT2i7DHWbpIVF0eaoNnUs0pjUt814CnMB4v4yV5fNYdMp1xRJJAbu8dluRq2xcXnxvbNjYUdm+TlGxUtiv9V6rCIAVZPn1bzsgkZozsVjO+4JxGoQSyDFs5xgR3iW+yc3HYWfTqqvvEQK+JnFYWI6itbBwv7TrBEGquwmz5jt7uZTclclCdiuBP4T2Noix1Be61ZRvE0h+lzWPlmFhNffgSgrj0asOacj0Vpf0GeqOedOAl7jnLtUz/u8l93s7sStjXzw+8D3fXMIcTV6trtoTGBqUV9l4EM+JapFr40TnS5W2oL2vfD9rNZ+GXGO6YzvZ8GyBWFG7lb62c+pEmFtaol5yd4hyzjfaozMI3NPnNS3HX4sr2Vfh+B+jMwTL9igtBB4m9s6PUc5eW2EZdpj33mxwq6J753JAmXQ2ld2DM9BC/84MpHtiz5XECvBfgKeZB2NOxSfUk6BVzPH73MjJ3A+suPKEbJDN1gS6NLqgyeHZwTPOJ4inhKeimGNunjutj55RAkrtvndnsGsZOXE76m7YMRVdSkpFpTk9W36pRLdYx8SWjyp320BrkMi0G7V/tqOWHVKet9Lte1HgHcik/+Freqh55TQXa5eZ1alSeDyZFtF7TLXrh17H6++JxwF+JFer8mOzvNDi/dhSS22RFiblDG6j4Cry3coZyvCx9PwPrU496MEvE2+TZ0KUTt0bDN9byoEvFApmpfWddvu2dHbkVl+MgHq/BStdmr1XZzuph6CRBadRPC1P4KAF4GU3Zb3vuqv8ifzKT7J7fwWnpoP+XPyKPdPdMm80cx3qH7JI1nUgZrHT2l9u40uamkNUOtJqzQNJjExY0MqCJUGVtmIdO3BiAvsMPDNLthj7XoLMX8H8NrIevRwBPT8BOfcBsQS9CHgvxEw9vcRQsSPatus9t6/RZ9/QvvvWuAJLW5dBX6LEMVS0OvseWvAK+K20vabRXbnJ/v+pizpdeebW8A1mQSZ7xKvteRWH+SdG/WRxUejCXPAyV5xO74zp9S3ELJQaM5cT6LslyHWzlpauV6snWsI0akdsT5q3SloXY38tKSRmSMId9ZMF3NgJj1KpvxkYtKUhDLxW1UnvnOAv/cS1myAwrxem1Nz8wgS1p0qqqhMANOaEkO+T4CfvZAAjhE4f1pNAFMOlwNynrq7JU/3HDo5orDUxATf9lmS1+vfYsrvRvNvuX9WAecD/wX8DwKk7AoA7YMr8m2I+X0CmZgfhLjTHgb8G+IWeyViDfoG8PPaLm9GFJ95Lc+Sps4geJ03tbj1PPD8aOJ/Bsqaq583IKH3sdJZBib8koQ7d+yXuighYsawuzhJcj21kuUAmtdIf8+qvjd30N8Clyr7epzUF2hIoVFA01TQRoG233VjUB9vWk6a67yBDFTnVWNzP1nftW7SiGTSo2TKTyYm7SasImFX9DMii4oPkQ8zunPJIYtdWz+3jyLBEikx1iIRQcaEPBPtiCopeBohV2zebbZT5tLEJrQigvGx+3TDzzGjdSu3mHirSNSXKW8559wZiDLxPuA1SNh5elulKEU6kR4AHq9fvRRxbX0WweN8Cvg14DcQXNDjgb/Tcw+2WSDWAA9VdudkPaoIZgiEDO4jSL9b/X4Jzeoepe1IUwaXVSKiwzXeZ5YfZQhO4kvyrjOZaLe8OUtu+bExp7hBq7clDu2lnBrRJim26OgcMI1EcNXTVPj2rNJmfXoxjXm8ppF5bS5h4e2GbDZLzrsEkik/mZjYAm3AWiPjM8WnqgpN6gQTTQxd77y8pcR4BS/iN/n/9OsCQjP/3zG7s05K7cqtZ5BWK1CR7nf59V2kPuNfEhH6dTL1q8WknrAUeIRz7szo91FCOLyFwK8j4Gx2Ak/psb+KiJXHJAf8m/f+Ci/pSzYi1p7jEQvROxDz/jXALznnUidw7bt1wNktLG1blRzxycCfJhaCIvDvarHLqTI4hbhLBklUOQJMeH/shr0n+rKKLMTxImwZ19vJPB0WYn1fn9TpvH6IboqqyGYl50NIeldWEp3jLDx9JvkbmgqmG4usApYNu/gthBPrbZpLsQT8AJmPVun5c/pONKXKMJLSyD1epLP1OZMeJVN+jkKJopimu+VU0RfcODNAiRCRRXPGJhYfeHzK+reer0tfdFOcunI5eXyN43kNx/NM91K3A5mEv464cJ6FWpl0RzXvW+fGKQI4XBHBDa1Ri1A3YolHpzV65M8RBWwL8FVkcp12zrXkqFFz9aj3/mSE+fhfE79P6e+jyER2LXAb4mK6DLGW9GIhKSCkbA/XCXI3cJ5z7oPa9ruRbOwXIZP4byHurvcBFwOvb6OQfAUFbqb8Ng/8DsIofVfit3y0c65jn3SRKrjus9j3W3Jkub3qba99tJrGTUzdtRJFHyWZ19PwbEkpIriyZbGwqfId8/xM0MH6o/OUKRVrk8pNnKaiG4yanl/UNq1Gx0larwJwROcAc1mvQjZEJyfrhmDkzBKfRXYtlQwacZ0dSxoR0RR51OP1I0hk0EhKuRbt08CDQxQV1vP9JEJrFo9Zbq5DFLBUHqDouhxeokvwnTl5enj+C5FJvEyIiKpHY7S5roBgeNq16wgSGfUNfcYCPUTIINF2ZUSJmkYUtc8hitdBJLLrs4SF/2rgFEJESh4BZlZa1P8QKZFZWu+9yM62GH1fIkR91e8R/d5V5MvSvAc+B34c/Cz4vjJMr5TD3qPoc1PfE0UsRv2YfPe30iaCSueGa5fxuRqYw+Nx2OaauRZj2zLFj9MDh45ec4qWu0Pb6JyoPtchpKbdlGXWoIGPmaP9yCw/R78siAVUrRBvQ3Yv5v4yS08OASFXgJd53e3rOQv29Xv8KAqERrAZWwjWnzHfevdTv69n4RnDU+QK4JOIklH0sstcS2fwYQ04oc3vBgB+JPBshFOnioDH666IVtFfsSsS4QCZAl4CfMx7//Pe+0ciFp5f0LYr6bO8nDr2xVsy00KibMvYfTXpu/cqYtZ/PfCo6PuC1r+QuIfJwCwvXvh+1iJ4poJzzB5LfD9qCXw28A9qmb1S2sWPRu6VCnATkrhT281XaXaF7QQ2RWXnEy61IvDMZXous07/ALHcWsh4R3e3b3ZzmcVlynu/1vdmaakim4EJ5D18GvB/tE3zCE7uy12WlVl4lkky5efolgVHXejk8BjvvdPJwJL9zetn58V8e0t02aIzxXsBQo8Ck3yXTchE8txW5aqbqwDk9P9+t99hxJxdVsWgRGeFcgT4iYFIky6EaGJ9JmL+fpziBXajiU/rz+fcFiVhvF9B0iDuq9t8whUJ/GZUhwkk9QUIJf6vI4rbvyIuKMsZVI3uVdFnXoXkEkpzH1QRpecaBBtkUkTceKb4xOWOIIvUYtJ5LFq8Z16VoF5oEFa86Hj7PLKZORG41QcCy5io9JtIqodYkm6uHyCA+JjeoKzA45P0u9n4Ah3bfRV9n76AKBaP1K/HvERIdZqDZuKIRHXH2rjtORpQ58E8MleUgE8gG495ROn/Ug/K1MADBI4ZGbTpKTuW1CS8YDcDC6Blp9m03hXJYGpZkhJjjodxgEAEeCldpJroY/tVUPM4MoldBezvcI256CrAWbR3IcwmrptEdtVGUvhDJOcQiAXuBv1/p5WFuhkR9+R0VN4IYjkrIy6sueg5LkYWqKTbwyfqM93iGfdp+TcSXIKzJMgc9Znt+6Gh4lf314LH5ko8EBqCO2lMyVCikVS0oH0ap2LxiXKKwOaUsWy8NOuT4wZx5cRpcSYXMzdEZaS6bbu4NiZWHafLVBEEHGQD6amWt1XLvCExB7ZNmdHiPnPD9L4crUdm+TnKpVvgcZ8kBrzCIrgpvEWC/QF3cRz/CwFRvgb4+DI+UxwFVgOuB67pELlkdPZVBBiMXp/mQqg55ywEPo8oKy8BflFJCj1wolpkfgO43jn3GSQyzFyRxkt0POqKdM6dovd6stblHuCxujPPIeDnMd8cxTIVcSy1i+ypIpQHd2h55nZMcq+Mo9EyfkgAm84xDsz4Yy/y6ySE5HIesdSUkQjOejvo/8l3K9lO8wg5Z90qqGWZlWMHjdZEKy+eCwq+s3Wmk8wjVuGe5wIdi3+PKCw13z2guEIICqnou1tAlL5vIArmwxNz4EKs4RYZmskSSqb8HN0yAcw65+yYS/BitBQvbq55vWYuih5rMslGjMM1zdtV1qipReFvPL7mP+KfwmV8mSfyZDzPA76jz9TWNGyh+n1ov4I+/z7EbXAECWG9pEU7mtl6D/D8xG8N9fESkm5RNkUEk3IEiXZ7Ocqho8eE976ERIf8nA+uyBmdbG/ywRX5NsQl8BOd1D+JuAd+grgtbm3xvGsJCyO0ZpatAm9HFtQJrfuM17D3hHI4NJmnnaME5L0frPttQPJk4MeI1e+vgZ/36ezH3wRe1IqsVK95CjTkzyojY7eIWAWf5Jy7SDE4s4hSbLw8HV3x3UQ96jj/md63J9Hy/xpRfLoaC/qu57xQeRhJaRVRfPIIRq5MM19Xw4YwmkfTDnNHZ26v5ZBBm56yY3kP5GVdUH4jEjm+lrXeb2ILZ7NLI8Hq7pQ2dS3TIepjAc9fIZjbt2gdcinnWd6sw8Cm6HvLmj6HmM9nCTmIioSM6vv0uy0pZW9JfJ6O/9r/SPTJLFHmeCR67VB073JK+fXoGVIyYmvb34IspOv0u7mUdppF3H6pbTSYse+nwS+b23SYDh17F2mfWnRgU99ovxv2K9eirGlEKRqLxqyNmwrilr2BFNeWzj8jHeratbu+l3Oj+8/quzCb8nuBlFx8tMgOT3CFbQZ2pt2vizqV9J7TOjd0vCY7Fn9klp9jTxa8E/eafmIgtd7Ib3IJD+InbMMDAkJGLVrNrM8CXCymWX/0moWYy42s8GkEq85/J8vysjM8GYme+Tm93+nAjV52jGNerD5T+ncMzWDvg/l9DHh+Avz8WuDb0eeKPuM+lHlZ63IXcB7wPeC7uqusINxF2xG25wcj6S6Sz1jTth1BrFLF6H6GS/owsus+nLaT13aa0TaaoTFf2yBlns5EfkedqKXjEHC3D0SlT0SsdkkX7gzqlvKtXUFVxIK4hpDTzlyfzwJ2AQ/16a6ttszrOn67mqN07HV7bk4tkv8LYUb/JRJWI733pJZZTFi6SyTGuf42ibyrXwf+PXlfn2CD1nqMqMusqBbyC5B5da0XwHZGaLgMkik/x54sOALMtU9+uqTiva+xn/fyy3wPmMRT9IGYcTKRT8pkjPSFd4oFLsi6ePwzsmj8GHH97HLOXaVKjikaIBFTdyBKyBuBv7UJWxUJm7gtMWpVJ2BbeMo0Lk5/hBAiGs5iRo+TEYUMZMf6Jv3+1cADSBTW7Qih4tMQnp59wGktlMAi1JPOxriNktbz/QRG6qZFQaWKmPxHUbbnhfd+30RdL8w5R+UYCncvIta646EhOvARNLti54Fn6wJtLuxk380DLwIeiriA84R55cmIYt0qCWonvE/XCg2NOfVaitZjGsHN/Q/wHi84n+R9LO/ehJdouDHEDbxP22Yq5fwx3RSW6Y5RvqTKTQFRePIIqWrBd07C2ldRfOAxmzojU35WuHRL5R5JrzmvYlmObM0txXs/wa0czytZD4w4XFknnlUINmc6Xsx1ks8lMQQ2+fTIqJxsh2chiskuRJl6CvBtnVQNR1BFSAhfBnxWJ0+rc55gRasRws/ryqmeX4sWn2d776+0sn2gH6gBD9aJzNKMTCAZ49+IZHv/BeB3gfsRl8czEXxCg9KoiluFkOBxhgBunUJC8WMQa4EoMaOWYWH0E9F1A59kvfD9GLsuwPQxogClbXimEE6ftPf5DsL4Sus7A8P/O/BdRLE4Q8u6D8GU7aWZQypW+FtJjj5alyMuoK8B/+El9UorXFFDO3nJK7jGe3+CXZfShiPOubMI2LtOMhXjh/S7FzE4HqyBv5eDkkz5WaGi4LhpxOrRixUj7xceeZP3HRKWLoOcz9W8i+fzGaDkcONeKOPXIJPRbAKkO0Y6p8soC+d6qSHuo9cjANFPIfnA1iT4fGaA3wYOeO+v0EkvnmwskmwCWThmkXQiTfXUa2tR2XFETRHJp2TWIDunpu6LNyFcSQY+/S9kkr8nKiOnlP8Aq6Ly62kPdHKfQpS+nwCPoxnQaXisCe/9jNatwgCV5qREStA8R3FUjVpuDE/2OERhNyXkNODp0edY6qBbnSsa3vlIeZ/Sc38d4doxrNAY8AKa27YIVFulz1DpxTJtZJ+tnt/ctGsQkkHbCE0iSvxcwqrVk2Vb35EJxG3V1byYcBGi172JJX4/FJxueRtH9LmPaWB1pvysXMmhpF70lsl4ylwz8cvQ5bU1jRYr6cS67C+PWj5O5mbOxMmE43DTDpdTJcIICcedJDucgeadnuGXFuiOmUCinf4cMaWPAH+LmNS/mLjXIxGMDDQqJzWixUGtUasQosN3Oecu1oWrjOyu3+e9/82UusxH5ZGm2CrW4RmIgrYXcX88Ghk3hi8YQUz+DWHp2k7F6PMogcHaQuntPvXs6Uik2LSWu8Z3kSNpOcW5utXqqA15V8vFqPfeIa7a7fpTAcH/OP09abHYBLzHObfNObcRURRsrojHQlXLOhWNjAR+pH39AM2Lq+WjG/EhR2By7mlr+XHN2eerLc6zsTiqGwAL4z9Hv1uLzBUWzWnszr1uDKcQMtFe8/JZm38dscr2TK7YrUQKX41ASZDXdhiq93JZZdCI6+zoSyRHT6RhNGYXL9IDWRghMqGi1zXkcFrGZw5RSZ4RzQkWk4tVtG7GAD2XUoaR8/UcjYRGzQGb9bORv63X+1pCw71IpM0+4NSo7qVW7YZM0N+O2rmChMCPpJxrO/urSCFT03sdRFxgllNsvX63Tq/NazkjLeqTJK+0xKl30EhqaG1iJHJDmaNIc33NHUtEh9rPRrg53WbsGQGiJbadbXHepJUJXIlE9u3Qd8D6v+Hdit6LmEQxGSnYlnCQRuLRBrLBlHLKie++BNzT4h0pLrBdK/q+Tvdwzay+K8bl5W3+trmhz33f8t0+lo/jl1y7ymQ5xLhlLLt6nrD4Vn2Cy8InAIfOOejSBeRDtIhda9aJZeVO8d7XnHOrgWkcE3jGgGmHW+PxVS95i8xFM4NYIso+oq/33s875yzVQa/1zyGEhF/XzzXgMYgrYRUy+dYQoPHHCODrK5DJrd1O727gm3G/OeduB/6KBO9KJCeQvgsuAz8CXqF1fhbC9Pt0RAEz5fDZchtXS6mb4X7iex9GosbinWNVn/FqBAMxaBdpKxkHxvyxR3Ro8mxgk3PueIIlwHLFzSNWiBn9vhWOZR5Jp5JDxtbzEEX/Ofrb1Yir7RPOuZsR68hxwK8SLFDQjDnpxS2fB17unGuITFNL53w8jnWeejrwymQheu1CLSC/g7zTXY2lyGpVA76KpIl5G/KerqXz3LAQqdEBU+Scm/YSeXrMSOb2OjpkAsGFlPTFN4LBNQgTcCfXzjvRkGnzw6tfvht3Wo5BRoCpmwtxY6wBJh11luKql9BykEnvr1OKGSORT6tLGUMUgHKUwHAdIVJrNRJZtQ9xj31Rz71D2yy1jSPG2OQEuBXY3cZFmWSWNSkimIKS3vd1yHtfIJAorkZM7x44O2W81HE/akKfRRSIbb7ZRTaDuAB/YwFg/OWSgvdL52YYZtH+ey/i+rzGN1IuPBYYd84dQNy17wY+kjJGDcP1cOA/taxHIVFeO4E/AD6AAOsP6bm3IQrRPcBL24yNXtxOTwTenFB8LJXKWv1sIe45YLX3/po+tWPOObcJ2XTc6rskS0SCDu4F/hD4O2Te+CPgic45D3xgAXNwJ+lGMcstczaAgUum/BwFoi//GoKl52Qv4Zo1AgNvquhCd0ivP5nAg1Lqcude9AP0G0eKRgFHGbG6lN273SZjGtaJ6V3Ao5xzm1OubxUS305GvACJjenVWGPjcl+NcO4chwCE5xGuHeMISmtjSwmRVGTyCIV+ucUkdW+LetaQ3am0kew2X49EgY0r3qGg9b0d+DVEka4rg2opLESRYGuQMP9LU/pjFGERfiiwfkgn1HkNdT/WIl0KXnBAn0WA9Sc6574K3KrzwDe84INejEQvHg88t8U8MI9YkF6HRHj9G6Lo/wyxBOWBDyHWwRwy/h6NbAiuhTreJwbuxxGQbUXPfSERV08E4q0rPqgF1veeqb2TTCPv8Wu7VXycc2ci5IpHgA/pPL0WeS8/jMxDL6b3OXjBogrW2YhV7CM94D9XvGTKz1EiPoAbJ5Lfk6L8KHDQXGWPJ1gsZrqdhPT6gQPmvEQ1icnWUQFW8wF+yquxaBdrh5cBq5xzmxOLe2pIfA/3ntJJ7C4k6ipZrzuBE7yA0+8nEZYetecIrd1FeURxmaBZUcvT6EqIZS0B2/SfwC8jeY1OQ1x9a5A8RTmrMzIm0pSW53jvLRKsJVhY2/P/IJP85KI7uM/iPauRxXvaOcaXM9xdrbOV6O9y8R8llem3e+9PRcbmW5H3/0vSPv4WRJl5Li3mAR9yv70IwX6djGB/TkfG8ISes0rLOAnJLbaV4GY7l0ZXap7uAejjwPW2SYgspqvVJR5HHfbVJa9l34ekj7mmh0t3I6zzr/Xefyb6PqatuIUe5uAupYgEd+Q0UGWLc26/c24vEqRxHmKl+yJDMJ8vl2TKz7EhFnJs4a/TyKJkKQws2aGFjv4DsrPvRoYiYSWAmbpxVDx+LRu4jBfyZ+7J7hz9/RZkh3UHMJ0wKY/SzHbbtajycALwK1FkzKS29U7gyc65S7Rdf0AiLF2lE7ttzqdzFLW0YKgCZpEtHtnRH0FdhIi7AmQcfEutZTXfTER3GLFamXTiizLMSG4Y3V/eM+E9JyPtPbvY8roR7bOyblKMP2dZ3h/fSEcQUy58Hnhhsr+1fvuARybCpCsEK+BxiFLzADK+Xg/sT1iC70CwcT8DHqJlr0XGxokJRb/bcfIOZNHeo89TQKMMVfEpRZ/77t7Utvp5JM9gL2Kkhk3lqbIT83ulzQ9tRfvJiFarzrkbnHPbEA6mUW2TM4ATgf/tvX+89/6R3vtneO/fpJu4YwYHlwGejw0ZQ/iAQF4wYyXFOTcHvAUxX9uCehJwqXNuwrenWq8iStMcYdGuIrutgSS09N6v1TD3ce/9WvdFt523UnG/7B7vr/LvJeQjegvwfp0o1+oENOOcG0l75ghEbmILAATSt89r+fEkXgPeg5jIc4hb6X3A21LM8BOIUpbXPop/n0HcVAVEeZpSS9EOAmlfOzHQ43rgDO/9agWEWxqL1yG4qH9vsVP+CvC/kXB5aANMjdwNGxBKgKFJbqr1yyP9pcr+/cct0z6wTCMfTIFAJrmcEi+sv9fmvN3A8733nyQKCHDOVTSg4LFIAt63ADcjCsFMdF4ZsUi+hsRCru9b8n7d4AefheDTRoDfjULa7R0eQRT51Us1B+k97wTe7pz7RLf30foVnHN5n84unWyjbqzvxq5dQFJ3PFx/sjl5BgF/m4WsiGCUvrQUbbOiZNDhZtkx2ANxoZSjz3kCOLbr8M3o2jItwmOX+bkM+J3ju5zOiznEG7hIf6snPUUmUQuJtxDdjqHvNIbrWth9q0SQOWA/Ega8CbgOOKvNuRamP5LSvkZPsBExVe9EUl5Mt6lrQcuzsPjxqM5XI2Hw++mccPJAXEab+m/V55yjBwqGZRoXcVtU4Itb4CO7rE2W+N4eDTHXvlz0e6LtXe6mnQlJcC2c3RL1GtVBnHT3OuCHwK5WYx9hCN+i/1+KuHR3IZivXUgAwNWI9WcTCUqN5PNrXYodnvUgcLaOwXVECXrjd36J+9EoHcoLmCNTE7tGbVrRcXKAxvD3s/SZ7d7TiGVuOqrLejqE7Gtf91Tno/UYeAWyY8ADILGQ6Ut0HoIv2bGQiYQeMy0v4bPZhJ7jvziVF3IXZ/Fpq2O0ENWzxOvkMp5SjnH12IS0DuXjIOJQadPG+5BQ4JwuGte1W7BM+SQl83r0+5wqPv/V6v462c1F9Z7VxcM4V0zxW6+/xe2QT5RlHEYb2tTrBsQd0RVv1DKPh1xjW/gy+Fn97SbgL9v0w+xinwnYF/0/0ofyctGiWehCeZ2O/i8RMrIXo/FhisSltODBiu55OXBF4h25TeeNg8A2VYLuAy7W88a13BGaM6dPd6j/JELbUNSxu5XAKzXdSiFfgnEUzx2z9MBzRouNg7aHAbYvRHB5W/W59tjz6XnFtHmZLvl84nF4LB+Z2+sYFy8pCMbV/ZMn+Ia/CTyVHjlw3DImP1Xzc9G3iIjwYpovA9P8Gqs5jV9mhqvdRncfIe3FWi9+7lXOuS1ItMVDnXMvRdzCjwCu9d47vZ/lvXq+995cQPNIuPw8rXP8bAce4QWT8DNEaZl0zq3xKX52PW8KoSpoMpPr76PAPyGTcSuxZKRVbYvdCKbLQL9/heB+Xoy43aYIZvRp59xo1L5fAx6GRLH9U0p/FLWsd/oh4fjROpk7Nx/aAss/Zi7DxyKLd1IsrLsf2eltPEIzb1JcZ6ubSZ2zRt8vc6veaSdo/07SmgcKGkHsxrxd57hxjUl3j/OBB6tIc/62WQTLc49z7hYES+aBB7z3z3DOfRp4FaJUPgrhusKLW7qAuMaTbp2W2LUoCsmA/X+AbCamEMVgwi8BvielHkUEoDwf1anbCLUCouDEfGxmzTXw+N0IzcCXkU3NZcATu3yfUoNb7F7RHJLkeStZvXyfweHDLBngeQXJArhouhULkwf4Fx8Aif9C7/lfliUCTIG5s0ikUsuIGZ0QJ4BpLmM7/8Or+RPezDco8RCeGwPBgT9DolXuQsDLU8Dvee/frmXF0XCfiO4xjygTeUL4eHKhvAN4iNb7ETqZCS9RCiA4WgAfi06uyf7XMh6tdbXrkv01g3A4nYRwizwTwUNYdJ9heZ6E4oy8RA6Oaf3itr0XGSeP9enAyKrW94VL3f/diC5OFW2/Gf1rvExKC0FN29Uj6TqSfVD0IQt3HJad0xxJXYO5vURA2SLdEt+ifWC552YSi7ottBMIqWYsneaHuK45miP64qS7e/W7anydjq8pxAp4H/AgxMJzNeL2ukrb5FPI5uHpwPU0pkip+nQ8Syp2JlIaDB/1mwgu8YvIRm1sORQfayPgJsU55tHoslYn6xiZds7dicwZj0bexzmUoVqfe8J7/wIvvGSf1MvfhZCo3qZlpfGC2Tgsk9L/ijGaQ+aZ8UjhivvTNrjGiRSXffTSQQza9JQdXZlK88iLso9lcicQXB9pZu+WdPAskz+ZRpfVZBfnlwlm/gInUqPCLTxE0lNE5xUQBWgncAspJm1tm3YU/AbCNBdCHsHU3Ii4E8wdcCmSF6kpFYRe/9G4nbX/feK4HeFpupzA2NzgUtCxcwuC4biTyDROo+vkR4k6lKLfcgg/y8+AjW2e/RxkETxtifo9F7XhIcQSUKE5/ca0/r5Z+30axURoe1TAT4OfhJtPBy5BFIuztLwS4t7bRHCX5aPyDTfUlYvXytT/i53GrJ6zL6U/CokyYwyN71DmXPS/YZ+KcZtF9477fTalHoY1+yrwQSQa8HuI0mTuqOsR7Mp/o+6xDs+7kQR+iYBNs3peq+Vv1TosG6aMEJ3XLj1IgZAC6Ef63l8Vxlyjy0rLLCbKKEfP+10towKcE50zomXuQbB/NyKuxuR7sBdRTKe1nD3ROGxwA0dzheEh63PY0XgMvALZ0dVLV44W0q4AuX160S1Fww1636v0OwNFzqZcZ8ksiywwX84C6toVcFTbcR/m1nkseziFeziDs+OXX/+eqeduS1FMOiqgpAPJa9EEeKZOWFcTMEflqJ6TNGI0ctG1cU627wG3Iq4RUp7DwKyG79mrysmpiboWSCiuWn5Jjzmt60Wdnh/hexlbgn4u6uS9Q5/HrBempN+gys4Bfc5you932QJiygz4oihBRzbDc25DlEMDBH8VcRPOJcqqYyt6UH5GorYc6fQO6z0mE/VPYrBKtAEQp72bic9JrNtI9H089pI5uiraB0XENbMTUcSnESLOa3XcXa7frwfu6FC30wng6UJUlzpIWr8/qOXt7+c82E0/mkITvY+W28yA1jYvmvJ8tbZBq5x59k5OEgG1Cfiri/X7kv5/bTSWxhHlfEM0H6ynEb9pSmKsEI0TcFeTtM4XOMdRDoweeAWyo+eXtGFRXYb75aOXehuwJ/qtKaFqtEhbRIKBRfue/JQIdJjyW450q43teEUBehAHeQGH8I0RbjqZbIkmoEkrM00ZIgJE63nbSER00ZwgtAjsjeo7qxPiNAJKriT6IXmtWXnuRlwQ6yNFZ330vF7LH0csMx64OdEmlZTFcY7I6kFIa9EpoqTvCjohmeoNpIM9bQHaoG1nkUtxG16i7bRV+6dGXeH0ZZjejbgYYgtbLUXpsHZpsOBEC0pHS2QXz2ubiLbJd2kDIE4rs00Z69LerWh8mzVjFlG279f/f6RtdKO2x2eAq6NxdTBt7KfUYRMEK6y2cSl6H+2dulXru7WPY6se/dnhvNsQS2MNUbK3IUr2FTRbx811+Jmo3ZIWn/p7ov0XK5wFRNE/JeqD9dZXwAWkW+XtPaggCmIx5Tlsbm4XpJHv9zs8bMfAK5AdPb+oaTt0c+nUrQdLcV/9uy9x356tIH2oiy0y+2zi0nvYIjAbHZUWbWgKUJkHcTt/x095O1+jcfdrLhMrdw6xfNjnik7aG/T/dchOrwJsatEOsStpHXBD9Ps2hC9lC7J7PqvF8+dodF1dhZAneq3LlrjcxP3HdVJMjqHpFt/V3R6mUHTom64WkgX0eZEWofPxIhnXXf/a2LDdbDw2TqeucPoiTHpgezTGTNmrJMqOlcE4HNki5zoqiF08ryeQkHZaqArdLFRtlJ98SvvVQ+gJLkB71q8jRJljCFP4Xh2716Fu3KheX+1mDtAxuyHx/NbORp9wiyofZWBHn8ZVW5qKxLuzHjhF6zAdzRVN8AD9/Z3Ru2O0ArnonslNlCkuZmmN2yMOhb+HNi6/+rwWRaRmR0o7DboC2bGgF9Z2hbYg2+4v32pxIlgn7iFYKU4lcPp0fEmSk2SLSTPCVNR3NYteDFKexeo9h4AfJ6N2iXetMc4hntBjBeg8HIe4nm/hG8zGxls0GU0qu2i0JiQtXyWdHM9KqbctIhbdsZMIP6P3Ol2f5Wf6exO+iGaMy7T25Tbt11l09524ZhZR6Jr4SfS3NMuPseV+VCf/Tq6VpbLyFfX50pSfJqsCwWWX03bcrN/v00Vpvf6ehxNqcP1dsPp+QkqO86MFx1xDZm0zq1Ip0Xd2/iSLwKIQqBEKUdmt3muz2pW6WMDbWX6SvFWxq+n8aBEvAB9BrB0b9TtTBkxBvZLg3huJnmm8Td22oeHw+tkTsCnTiIJ1DpJMF8Sl1DGsu8u5pJMbt87/pefvodlSZtYUs7DanFF/H4jcSa3uqe1mQGhruwZrM11uJulyc9pqrh/0OrfUx8ArkB0LGpj2EqZxsYzTvKMw/ghbXI3k7kr7vcv7lmjeBc8SsAzm5jITueFOloz3p9NEoPUxV1QDJ0qkAJV0wt7Bz1iPZ5rH1AnU5hC3kteF0RbCrbT25deAk9ImFNQio33wcRTnELWvKYw7EPyETZjxrjIJQN2s5W1FdqbjWtd4l2njpRzVsQ4uJd3yU4jKvRc14bdp6yJLhBPQttmFKI/TiAXulLT2iOpiAPcbkTxSOcR6YEryOuAQXHEYNl2EWPHs2EcjMNQsfaZEpgHU60p1og3nSAG1dxjTk4nvGnBHid+64m2BZgJAUkhJk4smwWJmC/s48DdIaLSVe0fUVrsRF2ODEthuHiByUerz74rK3k+wZmwj4BEXNa/ESk2H88YRULe9R61ckPFmNCaSjIMW8vSoGJPAe9GFwhbda7rFczdhyBLPa3PfUJGU9nVOGXQFsqPPHao7h8R3pxHMtjnqO14+QAqGpU3ZTS+dTkqTyZc8mtDa7vj68LxJcGbMkDyrC7cpfg0TenT9HLKr3ANsZYQP801uwJNHCAnPVWUkR1DoLiKFhVl/M3bjSZotUbujtjlTFwqL0vooQVGtIC60SV2ky1H/JpWUW/T72PqwP1IAzH1ii/kpqNuAoAjGVqE068o9qniU2vRFW4beRfSxLSqGxbkCcZMcQiwAvsN19xJclRuihXwaKuvhi4cJLk5btA4QSObMmmaKouE1kkDSCpHFJurnArQnwkzUu+5SSbx7aQtZx8ixRLnxQryRdNxIUxSZfneWKR06Vm+MzjdFyBSKbUnlhOAaqwdMEPAppjScqe9aCeGV2k+j5WRb9H74hYyndvNZyjkWqDBHD2M7eq8axskC6pinEdRs73Q7JmxrnwtoVqLjzVCTQq11ji3dMUHqyFK834M6Mp6fo0y8cL8UNcldXnkb1iFcEjchA9sS511Ibwn0phAyvzjJYQmJ7Bn1jQkNQThCTmUJkzd65ZtRrgtbxAFWeeHMOA5JhJhHyAvLSgaX1xxFVYTo7kyt7yHGeAKv4W+5mit5JTuQ0OqbrK2U+2KLXldQHo+81iMPfMJLBvcxdJGNuIgs4/R1yO75K8gk806EE8Vcba8D/ln77Q8RYCmkJ398FvA0JLfSWu2XIwTelKcj3CgFrd/ZwF3OuaI+fxlZ7E/ygUyvTrKnXCD3AI+nRdZtyzGUMgYWJREnzzcRrMkh4Hbv/SuBv9Zn3pG4puCc24eMzbcA/0Fg0P1TZLxfA7wcHvRqvexVwIe8kEdepN/t9d6v9t6fgHDMTDrnCl54nUa1XytRHYsoh1LUbjP62fhc6u2l1zZwrmhZReD1zrlPRG2bQ97rSoJ7pUgzaV3FOeedc/uMh0g5i5JyKoHosJNUkQ3C4xE+pBMQxR0ERG5cUxVkntiC8GXVnw1RWv8emS9WI4STq5H3xNr0/yH5xv4MeAXwUr8EObq0PUrAmL6/uZRzCogC/HVkPpnpUGZBkxnvI5BULjjHmHL6TGt7W3BDGQFej8TvqJ3vnFuv7f8rwP9FEsDGMq7tPorweI1EY8TmnrVQn1uNi6xMRNB4VMigta/s6P9BowsqqdmbG6huYl7ATiTehRg4Ly0CZwSJlppDdtbTqKuiz8/bzg14FmLR2YYs4LZQeWuLqIyteu56YJxncimeOd7HRYi7MPb75xLtbe6ztJDkujtI28EAopcji3kNuCRxzdUEN8uVBGtFWlSW7eRK+lyXA7fob1cRcF523KH1PVvP8Yi1qhaVGbtuLEy8ndtiSaIQtY/OIexGi4g14AiB5ycNq2RYGMvZ1oCJ0e8vljHz8UNwzRE473rEXbMXwZElLRe2E7Z3azNhV17nkUq0SSW6LpcoJ829ZeHnO7QehS7aJ7ZAXUgjd8941IdJF0ytxXvbFEKvz7qfxtBzs8ici7gWY46YcSKXblTuegLmLeY9MrDvOUhEX1Mou16/jUb3Y9e5zVLGqz1Hq5Q2O1GLVpdldmUd0joX2vxm1sZtNFvTR6zPEUvreDQOxrUO5xJc/TGFRpNbOjEWm9y50Tl9xW0OwzHwCmTHMne4vDxjBNeXTUCFhQ5uWiQTJJjAJ3WRmkV2i21JApfgmedQ8rpoEtiH7Ey3RYtSThedTTpJ78CT40vczJvYEk26lRbPOq2LQEs3gt770sR159HMJTON7JTjCX4WcWEmlStTrM5GeFCMVG0WUYRupVHJ26KL2XodD14XcR+VGf9vEWTtkpkuCf8UwS0SL9rjBFzOX6UoNfECXEz0gyeA3m8O4/GVF8PndsPOg/COC/X8fYlnNKLRJIHkeFR+jPeIwdHW/i8hgIMbkgdH7XiRvjNFOgPMkwrahYnP9fccUfYsMnELgmW7FwHX30IExKUxhD6OoLwkZUEuo+R/iXbZmTJO9kRtU4zqaJujPYhiu4OEa0zP3aHP8dHEO90xt1mr8arX7ov+t83ENnpQqgiudLPSpM2JsQLd1uWoz3p5u/dMx8l4VOdKyrPO6nmtoiUN03ZUKTcd+2vQFciOZe5wmdD2ENwrtvBO6tFzdADtLQINDKY0YnLG6WNUAc2ZqW3i3ELYWX4VcSFdoJPUVmiKdDmk11wNjPNyTuUl7MAzznHsQHJXtarD12hmzk1OWHMp18UcQ6ZIfRs4NzrHLEzJCLPp6PknCeH55yDuvO8iOcxsodoYLYJzOh4aMBSJ/39ECg4l+n3RSTrbtKdx94wTwq4no+dN41yyZJdzibb7NsGCMaLtYolux4HdUP4hHDTrxGSiXEssmcTjjBOiDbdJOexAFKV4kX0N8ABwfVq7ReXXrTm0V7ZtvJvlqQHTk6h7kiTTLGOGXbs05TqzHsQ4kT0tyq/RqBTanJJka95PRBCo36/XttqNbJJKBGvFSMp4WI9YYlNxfF3OE2YprSsF0ftgyktPWEWi8PaorOS7GrNVN1gLSSi7BNyfKaLTKePdlPIjtMloT4tkqMfyMfAKZMcAOl0W9lmdsBoUEHrcwdMioqDLa2OG08XyoqRlpo65cCxap2FHRgKYSXAZ3h4tasIh5Knwh+zmwY3m/JS6xLvH8yE1Qi6XUv/YtWOulQ8m6tsAQtTvTPmxKKbzEDdVLnqmOJKmguCYrkIsIWfpOT6uY/T/IcQK1cpUvyhQZ4sybVKfQ6wSWxGrmqWssEV8X2L8WqhwA+eV9uMOBOx9FcEK9HbEzXJY7vGpG2H9ZhpDzeuKVMqCa30dA6LrnETaJ8ZGfZCgmNs5cd/ui/szund9V0/CCpbSbqYQ7baxjbg5N9FsQTMl7xQ6RKNpnf8fKfw60T13Elxa0yltNaJ9V4raJodYoG7TfjCrXNI1Zu/vNj2u0OfaFb0rPvrfjjQS1m06nsaje9UjuViAJVOvqaIby2gsJokMk+41U4CaNjYEZbUbUsKOXEXZkWizQVcgOwbQ6YE59vwWE1nX2A3oPoqlQxmtMEo9pcloMXG2xAXoongjYl0wa9RZulAd0InyBqsXv8YmXsNB3tDZxE5gWT0t5fuk66C+a48m39P07xdSnnEuej5TfsylU9L6r4vKqxEU3m36/x0krD0k2IIJecla8cz0ndQwseCfhCg8Owj5kvbo4mUAUItoM8JLT/MO2aL/tqB8MggWyhSSb8HZW+HADfDMdYlFKHalJXFiZilohQ9ap+PoboQVuUgCb5aoo1n9YqXoNP1uZ6TUTJKuQNv4N0qFMcTiZfQTsXVma3TdubTZxFiZRLiwxNi9GMEbzSKWxXU0W9/sPaxEY2ur9u/1URuPR/dMe09iS2fXuc2ia8yFHVvPWuZM62KsmpXnn1P61DZ4TSzP0TnWN8ln7RpnQwelODtS2mzQFciO4TpIDx23HXhaaKTtfGMQ9IK4IQjAujnCbtl2iNPdvNzJiTOanAx4mjSj5xAX2M3IDtgmq8sQ6880EjFhC+wI/8xpPJMj+K7qs0EXv/XRd8kdcRoQ0SxQm3WBbtXucTqM2FqxiUZ8xdWEBLlmAdtHo4XHk2AL1nrsabUwpi3ifRiDtss3JehCVX5qyO56LxKpZAzf63VB20Sw/Iyn1HOdXmv4kutUKbkUnrMH9tbAt0qJYla16WQ99f+5lGewqJ8ykjPsXl3sW2EvKqqsrCckB71YlZ44Sa7VZbJNnxgT+TjiSqq/B9G4T6Zy6RT2vQeJksun3C92Y20h5KFKur6s/ta31q+79fM27aNdOh7vpVHZvJZgIUsCs3dA2xQapqyehbiT5mi2yrYkik0pzxTvTomODWLQyiVldCGxxaqJdLRDXXpSfkik5Ina55hhhB54BbJj+A4CyLSBC4LETi46v05qSMCdLBgAS0jGaTsmwwhYjq1W5FxNmakJUS6pi1R07Uj03Ga2PkJIpjlFHDnxXNZzNrvwXTGtnqPPchABjJ6WWETHae9yaHJ1Rc9rCT03EFx0s7rg3U8Asm5GXGhFrcM7EStKbAnwKffeoOW3ShPSd1JDgrk/thLkVAm6Tp9rhy6QxoZr46MUtUudKTdaUCzyy3hQrpff/vE+uPGv2tSprpAl3pOCjtfZlLEUK0cbEUvbOALWnQXeqP16n46NTfps+xE80s262N9CIBLdrWWViHKTJepqFrwiosQbO3PcnjH78oXA/g794RG80mcJGxOzDu4jcn8T+LXy0MwyTLCmGmvzXcBn9bdL9fiotu12ff/mCFFg+6PniIHZu2kDeiakoKnoPc9OOadlJvNoHrQNUl8wi3rPnpQOgoXP5rmu51sas8Y3RAQOeu1ZziPj+ckkTdbo33mE32ICwAsfyIzyT9TFez/lhednrf5dgygLhZ7uGsqb98JDsUq/Mp/4Wi132jk3nuA7gUbOohphYYol3+KeY144XUZ94OX4AYLZeS/wbOBBwP9xzl3Ij/gy/8YjKfBP7pPu8g7P889eeH/OAn4NUT7ieuQ6XF/VZx+P+Ui0P1YjC9MpyKIw5YXf6B+AnwLOC5fKe4A3euEq+QQKvKUzB1MBwcOkcZyUgYkeu7dbsSSy8/as3vv3eu9fgli5ng78ELEyFIE3AC9CeGGsXYxfJ4eMmxzwNq13fJ9XwMPvgOef5Fx6X+j4GPWNnDg1LX8SmNIxWdF7rCHi9UEsb49ElLaTkEX9K9q2/6T98RpEWXHa7t8AHqP9+0HgfwM/8d6/yQtX12FEQa+Ljo97ozH8gqjv4vpMeO/H9F1+PfDatOd2zl0InIiMpR3AY7VuJa0DSDj4PMKdlQMeATxGv5tC3l0rr4BwAj0BUWQvQCysT1SOGo8otf+hffPniKL+ceBvtT2+q/MD3vu1et53kPe11OI5csDvI0Bp9HnfkzjHxkpZuX/mIn4ugPOdc4blWq3zXT84iHJRW7YV5YdKpluxebrTu2xS1XkgntONzPGYkUz5OUqlFdFZUnFJE11oRr33Eykv1AwJpUbJ2Sb1sN8W/DLpJBTX42RkIbsKmSy/CzwTqDrntjrnLtZF58lATv//I2TS/m1koivo9yQmtHYyCTwFUSyegSxaJyHh1R/Gs4HvM80Ir3G73UaH66TETCGkfA54lHPut/SnMaCii2epxbUziKIxmfjJCACfDxyvz19A3Dl7gGc659Yhk/5To+uehVgWYknrr2cii1mSSM+i+LqatLsVrbspFKsRErp4XIEsUGOI5eCftA0eRbCU2NiZ0EWyilgG7gA+jBD1PQUZo0+Rcv78Ofr8s85t3uTcs9bpuGo3Vsb03kZmOa9t9WyC5aUa1flTiCL9SkTheDfwF1rGwxDl9ULgoYjiYwSMn0eUmLuBK3ScTOtzvNQ5d5a+7yXgi8APtN6nIkpGEzFd9F6PI0SH1yT7Qe9RBH6CWF12Im6otwFv0HueHV1mRIVPQTdQep+qllfWfv0houA8i8C6XQWOeO/fCnwJwRbNeO8v03JfjCTvhcQ41c3B6/XeheSmSBWfryHv3Vt1Tqkii34xOtXwQFXdMKzW8nY653YjVrl+Kj1xHfNdnlpCiDNto9Zqnm4p+uzxZyO97StB6dDLoE1P2dH/gyU0axL85hZ2XMfj2Gc9b8F5dwi4n2QCzzwCzKzqcZEeOxEf/pk0Yo+KyK4xdnvN9visFyOYnc8gypfhFI4gi8sssIGzuRTPLL5jniAD5X6cBIkZAa/SkiyNFDyLfh8/Y4x72oWY+keQnfFnaMSwxBFxaZm970xrM73fohNLJsq0iBdzYV2AuFR2Im6hHfr8XyXgJOKIrlZkm3W3ImJZuB5xy1yh/bg+nPuUjfC5rXD7PnjOrQQ3y0Ud6j6i9ckjStjNNIJ9zeV2ErKI3qv3vg9RLN6vbboDTUpLIphA675D+/BGQsqRg9HzbaTRlbkdGkKp0zLUp7VZMhVGHXyr4/aUZJkEcPdINEZmESX8dsTV9ENEaT1IcEmaO2q6xXObO93A4mku2Er0PCMEcPXZWt8azQDxyeiZytF9YvJFcxmfS58jGhPvUi/A5r6+d3H7HUvHwCuQHUvyMqVlGu86h1c35RMYRZMRCsYxsygsSDR5WRhxA2BQFY/duogc1EXeooIsIWiFAPpUNt/e20CvjxdZo5jfpZPrdcAsnjKeOXydH8UWxDjqLEmuNpuyIDUkx0ypTyrnjpZ9amIRmUOwJIZ1qelvZpmIF5mk8lPURSONOK3vpIZEIfPAGaocbNYF3bBbZcRCYMpAPnqe2RblGmZqXBfnsl57UBddS9b5UVWIxuEju+BH6/X6s9CcbF2ME0sn81N9hiQTb17HaTKCrwR8S8fURn3WC6O+LKiitE3L34OQV15B4Ooya+tZUf9NJvoz2ZcVvacBsQ0btZcoczmNitwWGvEvFkZvSYCNTHG93vO/td0tVP06AhjflJrNBKWpED13Dtl0WP47T/r7UorK20jA9twQv2Na3vnaTlsJblGbt2YJyYG7CrLow7jvRfnpe67Efq4NK+k4nkyOOvEpZk11+Yz1sfzVLX6eQvApue5LTL1HDXHzTEQ5Z2adczOIebaGAEYNXHkikn/ry0hOm8cggMZ5JN/VeuDhiBk7iUWa8e3z9owhOKMpr+4U59ybgJchpvZZ4OdxzONZw/l8g8fyAPv5hD5DxTlXQyaZKX02vPdV59xq/X0azbOk37drnjVan3nf6HZaiyRi/ZB+rgEPAV7hJWfVDPA4zQmUA54EvCK61wmJ+7wDWbSSJv5S/Bxa3pRfvCtg3ns/r26KC4DfQNwZf4jgYf5N63KPc+58fT7L//Vm4MGar200MZaqwMnqFnomkjftHxCw7ROQaL5fQnJJ/Rvk98PZdyN5qEDcij9IVlbH0RrgFxBXieVVKyJu0r/U5xhD3gt0DNyJuD9jeS6SXwzETftKRLl5wDlnSVwfQKxgb0LGstNzb0TA669CrCsvds5tRJS7nznnyl5xeykyg7jq3oi8B2uj8WHPWcde6f8G9LbnuQKxxL5cn/tS/e1RiCJktApvRpTCLQg+yDB5NeDNifdirZZR1naoap0O0zweC9HzWWDCfh0vr9brV6vbbQRRHD8H/Jd+fjYSxfYqHR+XIvnH1tJn0TFobWcQghJdzs3e+xlz3/dRihxrLi/ILD/HysEymTUJGa+N9XUbMjn2xUpAo2toA7KQGFHbRsQadCkhp1gyQicO8TSA5T3IztPM7xtptmglOUUKyK5yh97zDkRRuJ8Hs53b2Iqv72QNw9LSZE2IILEop/Eu2zlp5VtPoyvrYmTy3xA9+8WEHXccdZa0/FyLuE2Soc2xhaatlarHvk11e0T3MWveWVqHTyML2acRBfgsetitI+6ndTQSJs7Bd68E34mKYET7fr+2p0/pz0qbfr6HYAH8PKLYWA62B7TPXqPPdT8hIuwQoqzdRwj3n0RcYZu1n+M+jS2PTc8RnXca4qp7JyFironYUf/PR7/VrRYIruyw3vNUfc4r9bfvaluNR+03QgcLsdYjGc7elO8qPhexBv93/L5H4zZpfc0jlq/rtH0v7GbsLHB8G2mqufrq1ukey0mOtUWFrS/X2jBsx8ArkB3L0MnLbNYkmMBN+fgMwe3QFzOyvtybdDGYRbA/VZ3E9uhEVtOJrab1OCeaqM9B8+bo/21xUaS4evR5btCF6G5CuO4kT+IcPJP4erlzCN7D3AoVxC1SV4gIbrBaNxMiwZ2TS9TTTPpzqsDUCCSBu4BN0fmxOyO5wO+nOT9Tg9m9F2Wjw7OUdPKe1n7cSnvOFstJZniznarIJNsjTnC6jhAyfr0qGxcTXDjTcPv58LV90JSSJZm09Dxt1xyCN9uRqF/qWNfztyMuvTsRS8X9+izbEQX6AR3Xt2kf3Kq/1/Q5zRWcR5LeHtZzjSwwFQdFG2oCAi3AFdE7Mk7YbNh3lajfzf19ivbHVmQjMKPvxLrovP2ouzKqyyRR/rR2fR39vzvRN5a3zFy8Blq+EbGKzaUoP7NRX2zV+WJROBq6wFPSqJT2vBkkhPTHtAqLxncu9tlX6jHwCmTHMnRySqbxAdUjzqUzspAJIFHeZsTc/1qdXA/QmGjyo4jl6U5Vhu7RxX8zYiGJkz52xEXROs9SQSfQw7oQBBCoZxzPNI8RDIKe/1pVmnZrW6yncWe91Ra3Lvv2gD7fEULG83sIu/OrdWE9X9v9xuj6dpafuwk532wBjZmoy7Qg2uuxHw0YazvhUxBuG+O0aRq/usB9QH/boItdMnVJnGbkYn2eH+t40HQWDZaROTiyGYqnksAP0Wz5W6djyfA2VcKuu0BCaUyUNal9sV0VHTsMAG0WILNKfkf/v5Wg9K3V+34cBVerYuSBr+p98inPMZ1SH2OVrug7E3MBVWhUkEei34zPyJTH/dq+NwPvQ5Sx87Uf57Xd4wCGffSIDQT2Rv9bbr4bkU2PRQpeS8B03U7IZVhBNkyGB9pJlAZmkfNax+ewtqIFYWxi3JYQ65nNlxZYkrRkLym+cwFt0VfC0yWt66ArkB3LMiCHyqxJI4nhgq1BOsFdqi/81arojCA78e0IUPI0nUyu1N9v0r8xvb0t7B2zzdMijxVhd3uXLt5BqfCUuY2tPKoOvpyNFtxxxF0QuxFMGZvrNIkhUSiXaTmWpPNr2h7nEpS79Wg6E6IUBUQMvAlFqKjPcn5Ut/piSrCELUqpJsqEHpV5qfbtdbqQ1Qkvo+v2EnKStcugbQDWOcTCd6cumAYe3tPY/1/cAn4Sfv66RFkxceKI/rWov3hhukK/SyWGjMoy1+1hbef7EevNR7RuHyAo7btVUbB67tN634ko/zXE4jOpv9UTsNLsPkxTfka0zWd1wd0cLdJntLimEN3P+u4BVSbO0evv1nbZq2NnjEYrThVV1HoYL3tpzCW2n5DfK06bcbvOAdZXc/pc9+kcUNHPi80p2PE90Pqcr305S+NYTyr1MWv0fuD0lPLMGldqcb+O89ginzlm3a+/eywBGHtJ16FBVyA7lqGTh9isSbM16BxScnylXGeRSPVkpjrZmdXndMQVZgzIFyGgzo266G3Rv7ELqKOSSBs8DoEQcDewreG3t3MBf0GN57Kexp2bmeLNxVAgpG04hS7o87Wc/0QAnK/VhfNSAoboTMTyYe6/HQQM0CaCJSdWfj6qC82F0aJSj3qjh/xHHeqdzGN1ji7s23WxqCbOtf7uNgVBCbGM/YiQ9+sAolSdglgnCo33OO8Gx/77TuOrpyT61lxyGxKLrbHsbtcF2Xbu3Yynuwjh1Dt0fB5BlNd7EGuP9ZulhfgvPecabaOder1FSF6EKPt1JTt+vpQ6nKXnnq7v4nZCpOQIrZW4uahO1+pibW1xg75fB6I+SzJhb4jfvy77816CReQGq2PKO7pVx24u+m4HYkW7xOadPozfSdIjL60vzM09ou9hMnXMdKLecZb3bTQrr3aOJWNNY/jeSMhl1yoZcS7tN7rADxFczUkm/nFWEEv0wCuQHdmhL1T8Il1KlHuHdEtLJTl56WRhCR1j/pFLCGbuy3WyNyVgh07259E9QLDlTg+xNN2L7EYniS1cb2CEv6DGy+sg0LoiRQRG1bbYBNwWPWvLiUzPuUnP+QLwNwRLxIaoHSb1PpsgNc1BPBFfrYuZYUFiAGzfQc76fx1XpYcl9JwlKMgGtB6P6m18U3MEILulWbHvLbR/H+L22Ekg2EuOo+IHeevavZy4zYd7WKi9WZPOI+EO0jaL8ENd5X4zHqH1iJLjEQvKfQRXmFnbPo0oS0cQgP13EOVnK824L3vuXKv2Toznd9qimvhtE3Bmq74jcF/9BLE45hFA9l2IYnlO4pq6O1fb/soex8udWt8PIgr6V6Epj9slqNuRgAWyNBjxWFms1bLJ3UXjZq5CBzcQAQQ9TjOuzBS82M0cK0dN1iMaaQ+aMIFROaYcjSe+t3udouOqQCOGrCnFEYHWY0ktTn1fcwZdgezIjhaTyqQqM19T5SQGXeZ0Uvhg4rrNwI/0f9upJ/N9bSSYwTch5HKWP+hWugMutoya0d/X6aJ0rSkO4YUjx9M5hK8rRfHEZROgTdb/Sdjl2SSettP7CKJwbUMsT4cRS8c6RLm7Kqq38dDMRt/VQaxRmbcjVo7YHReDXfsFXLddseFNNqack0tZlG3iN8Uwjj67Fwkxt8i5uagdy6pEWLqGEq1At5DzMOtDtvSky+KSRJtcTXAHxYuKga7TMrGb62sLQfE5oMrIHYg7bDuiTB/U/7+tY/164NtRe2zVMTerSsKNdKf8mHWxlPJby75GNin3EMDqH9R2vw9Rfj6ack2sbFdog41K6e+faBvdoWNzElH0q/ZuaF32I9Yvc83kCZurWSKM3SLGbcwNZO/Vgtz4Wu+099q4nmL+pWR/lqJxWUawcqckyqgk7hUrUJNRf8RW9B2IYruDRlel5cWrj3NWkMLT0HaDrkB2ZEeHCWZEX/5v68T+E/1seJ+P6rl5Qui6mezNbN+KPG1TNKl8VxegHYgi1Mnt1m5RyKkichspO1sewmbWczlv4IYkI7QtrtFnM29XCNFi9QlHf78KURLLwP+nC6b9XkKVH/08R+Besd3hpD1TdN4RZGdulql4gu2Hu8CsE9O6cFo01sFObR+VYZnTDUg6ogtflaBAV1VROBVxR16MKMDfUqVjc8vnEeVnzje6TizPnEUPXq7Kyg5C2Hlyp2wKXmxFi3EotxNAz3er8nC/fjYr4j4Ef3MfotjOITiSHGGH/zWCZeOjhOi32K3nU9rRXGrrW/xWbNP+F2sdDul3l+gz3Njimhg3ZpajfId+Luk7+VVCbrSD+twXRe97heAujF0z9o6X9dpFE3TqXLNFy+o5MWmX9zAXYqqLKjqvHI29dSm/2/iz9yVpJYwtqkVEcb5O730bomyeor9PIsSu5lLvSFcwrMfAK5Ad2dHDRDCO4FD+h4BL2N7huqRyEVtaTCnK6yJku/mrdBHdQ8Jsn6jPdLLMuGydIPckFSCdQM7kRGq8n1v4G05qVfdIialEE479bzu1jxAiXfII0eOsTvRlXRBKUb0sqqruokn8LRBSJ5QJ1P/9AjlbObGLyP6vadtvJ7ju4j4zxaOEWDY+qwrINlUSLDWEtdVp+v1OLXuzLgBXIQp1g2UuPnbDLZOJnS2Bs2kWUbQnCbw4TQoxjTgpC/uu0GgZOk+VnLt0UTfrhtdrNmgfGpv5/kSbXIlsDMyaGeNqGsLbaWHl0jodbvF9sc01tgBu0+8+QKR8t7guZlNOtThF48QUpNP0Xtv0fncSNjdm3ZlElKOLojKSymjdXbqAcWv3u1n7oMwSWj1YQCoLWuOPLHVHWmBAKeoLszIVozps0uedRQD9SYU6th51zS806GPgFciO7Ojx5V6nC9i25ALUp/JNydoOfB/Z1e8iPepiGrEi1AnTEr8biHSPTpixWVkUoGdyEw/mAX6Hv0pbZGiMpjDXyziBRM6UmRg7VESsAjfqd6chSmPssjkbuER/N9eWKT8XEWFJtP6nQd9Azsm0GrbI7dB+vVef1SxNMWYnXsjviZQcw3NYGPF6Qq6tacRieADBoYxoe5zUqo7XwIaPhajANDJJC7PeRxsSwahty1H7mrtgRMfPzUiI+PVa12sRt65F09ysdT9b73HI6q7l/BSxwExrvyUV/n3xmG3TLzenfNdO+RlHIgo3aVucqf33Y9pEKhKsEHO0AIbr9zUdE7MEa9Y2AuDZaBEu0bIacFjROxqnQOkJqxaNQbMena9zQ19DuglKsVlDzYW2LC4lbZsyNGD76iHzNLrkCyltZO9hKgh7GI+BVyA7sqPHlzTGnliun506+Vpo66InjGjS24y4Sw4DPyMCf+pkvzP6vI/Az2LHDv3trpTfRHk5mSu4jiP8YX3nXkjUIxnxYQvHWboI3AxsjtrEcmBtjdqqFv1vOahq+jlp+fmWKgemvJmLoV8g53LKM1UQN2YFseQkd5+mMJajdnmAFHwDwQ10jpazVdv7djS1Ah0S3B6UMWXuwDQyyY2k5LHTdr2REDZubpEkUPXKaHE/G1Gwr0GwPjtUwVmvbX+/jj9TzDcj2I5rtZ/O0X66lBQXXqJ+7ZSfuZTv2ik/hqkzd940YvkxN1Q9Ii5xXV77xK6PLVU5AlA9mZR1m7aHjf2tNFoQm6KNiKK66AGrRiOTfB24TJ82AClzzT6953IpO6ZojdNoRSxG7VVO/NYunN82ZitC8fHecxyZZLKypJ63zEs+rirwQiRXD8ikeKNzbtxyeC0kF47XHF7e+19Fcv6sQ3IgfcI5V3POnQv8b+Arzrmy5qOaQHKe2TGB5CM7B8m3tRrJy7QOIX07Dsgxxwm8mFfyLxzmQh4DbHHOVZxzeR/yZ8X5yKaA/wD+Fngxktfsl5xzG5BcWKchuaG+ARQ1p9HjgJKWMwU8ETg+aqO4/OcjisIU8P8QHqEKQqzXD8nrPYvRfUve+7d470e997+FcMKUNedZXutSAn5fv7sSsRC9LurjM4A/Qib0I8BDvfervfcvQxSNX0SU0BLtchk5l3sE3PNUuNc5txf4lej+OOeKiGLzId+cz2weccseQJQX9FlWAyNazwoSnZdHFJvH6LO8APhjZDF8sI6v/0bwFw9CxngNwWHsBF6i1/0jonR813u/xtrDOTfnnJtF8tnNar0f3aZfLK9at5LT8WnWxnmtT9V7P++9X21tFou22SOAn0TjO6d5r2aRd3oU+I4P+b5mkDQg25Hx+HfA9d77k73k2ssjik0yh9kM8CLn3EejcqKudjl9fwt6jDvntgN/BjxN61HVNtyg9xilv1IAJrz39Xx5Syk6DgraP1UkT+C4tn+FKA9dPL59m9x93vuq936Vb51Dbvhk0NpXdmRHi12JmVjN3BzzqljYalOWdsLueA+yU7yKHrlEOtStiOAv7kMm+i9pPU+heQdl7pjtNFoo7LccYsoXf3qe8znAVVzCbUjkjFkNzoaWXCtlBB/yQWQnbJaN9QTuFwOIxzilOcQ90ZTnC1mQZ4G3I0rEWfQB5KxlF6L6GHv0HEpR0GFMHCbswDcT0kRME9x+04glZCc0caiUEeWnif8meeyGc3bAobPFtWbWhngsXq39YkBm20nv1TFX1fG3N/p/B6K4HNRzz0YUm50Eq+G9iGJ0P6J41ghh77ciFqId2q+36v+7CO4JA1jHjOFmDTMrWDtyvDiisqzjqJXlx9yRVQIgvs7bRBtrIWKl2kTg5zLwt7mo6oEKUX22If1hYPNkpGSM7RlBNhlbdIzbmE6mLbHxvwOxpJWjtpyL2uMk7be+MxgTrGTmXltSdxcpOCsiLF3choNeC5Z0nRl0BbIjOxIvoe1KIJiz00B8HyTQ1MdHcvK+AQFH7mEBSQSjycKiiWxiPB8JRb9HJ9YdiXuPJK6vtPnNrBsjwCwf5zBXMcfv1lNlTOrEa9EqZRpdY+v0nJsIuJGzCG6tAkrmp+fZs1h0W4VG4Oi9uiDF0XCLTo9CwO8YviEGSd5LyNGUBA3HbixTYnYh1o71+myGz5ki5Maq0cjgbQpAGveJJYo1nqC518F5X4Ad18Gh1RJSHYfUb9W2uws4OyrHFEjDtZg7aJt+v0HbvYgoQnFerv8huEQt2sue5RwCSeNBRPE5Eo37UtTGsVs4SaewG7g4+hyD6tcRIsisjPWoSzWlP03R3EWCfJIIB9Li2vUEkPY+ggJUSdY7GjfbEJes5e+y99L6rhS1h2FYbGzvoRHLMoK4DnfRjHXJ0UzIuBHYukRz3vn6/KZAtkqjY2OpI4uyllOfSxO/NYXMH4vHwCuQHdnR4uWNo5d6AjMTwl7tuBrZYd+tC8cldO/7b8A8RBNkrGj9f9HkfZ1OqJdEi189SoqEAqafkyDZq7iY73AdhziFr+rkfL0uTjVdBKcIAOHbECXvVkQZ20SwrthE1FsHrwAAgABJREFUfwEhAsySrF6ni/fpBCXMeFrW6eJ6MX3COMRKB43pIk5FLCT36Of12obbImUliRHabUqK1vU8besNaLhvtJDsIuCkziYdFxNjHaajfp7+OFxyhSgp66M+sxQcVybGx2YCYeHF0QJsvE+36XVfJaTamNa+uw9JAnyv/r9T/xob+QZto88CP9Axd3qiXUcIHDizNCpmOb12J1H4tF5ji+VmVWhiEsxaq/bS5/949J1FBbbFf2gbHUEU9tcS8D/WXiWC0mOW3ro1T9vQcprtUEWmqm2Vj/rpcm37zxKsjRYo0DC2iWgAaFYid9FnPAvB4rNZ37sYU9ZAakojs/M4tMwxGFshYwB1MXqWFRma3vc1ZtAVyI7saDExbCXk7zGzeiqAsouyYqtLWSfN3SifDy12QWhOqMTksk//TwtrLhEIE88kuETMhWcTtSlEtjgnlR/hKLmITRxiB29mPaK4bUUUmw8jCt1B4Id6zQd1EjVr2A062a+PFkYzq1u9xhGX2ccJINPv6aJ8NaJw9QXkbM+V8t05yM7/2qhtKlrv9YRotm3aZ6YUf1sViTmiNAk0KlWWI22vtoVZY04iRAvFC4wR5eX0XiWg/DRYf5NmuNc2OqT3MBbseNEqE6w3xUTZa7Ufp/S7y3VRtUzuX9BnuwdRgH6si3oeAVHfq8eNSMjxfTSD6LciCt5mgvI9QkgCu1HrYDnxzEporrFvaV3Xax2LpHMDWT/F0VSxhXQk8d4kI4R+giiIF1r7JN6jutITfX+z3u9cYL9+Z4zGn0lRFmp6WPSZT5yTJAD00f82fmzjcjV9sH4m7t3S/UqInDKusyT7c9KiZ9bRkvbttkRZRhpbI6ICOJaPDPCcydCJc+50hHNkFQLynEYWjNVewYYK6JxVUOe0/j/dDtzsA4j5eUierxkEjDrvnLtEQZNWBwujndHPFmptYMBqdK5dV0BAyHuBf0CTOepzGFj4eOAvkcnsO8CLgKclAMc54Dm8i2t5KKdzKb/Ce9iDLHYnIqDmaxHQ6MOcc9cBz9CyDmsbrUesFc9HAI15L2DEeQK54TWI5eeFek+A5yBA7BcjO/N+gZxbyauAUe/9SxErxjiyGN8KPFLPyWs/TCCT+O/os70DAaX+FqLsWduN6vUFPc5GQLhj3vsx4NnIIlAFJqO2X0NQkO7Razkffm9zaKd/QJSPCeAJwBe1fSvOuaqOpzuAu3wjuHYeASafA/yCjpl/RsC7PwMcmkdN2/8I8CyCdempWu492kfbELfrAT3XMrr/p/f+YsSiUtQ6nIBEkZW0jY9DQPHWphdpHR+tbbMHONE5N9Km36zNYlCs4X/y+rwoiHYcAXvPKbi4jChZu4Dn6rUzzrlzFcxeBlZ779f6RpDtXfr3ROAb2m+vQt6jLd77qt5zRNvyfuDhwHne+5N1DFSj8uL/k5+L2j4jyDv/BN8G8NutKMh/Tj+u9t5PpZ2n/TZBiChc7RvB0GuRdwFtz2lgjZb3A+DRNi9pWWOIgl0BXpw2T0bg7+Jin3NFyKC1r+zIjuRBWIBs4bqKRiDe6cjkVs87QxtwHm2sRTTSwu9HFlFLjRDjUtLC2C9v89uhlO/MtZN2vlmGrkUWs4sQt1QBT46b2M/H+BaCCzGLmAFk9yKLodf6n4nsVH+IWEV26/mGC5nW9rOkrwcJTMn3IRaYvfTRPE6wiBjGw8gBPbI4mnvLrFUjBMvNZsRiUUEUgW9H/T6pdT2JgE+yJIvGJGyEiGZFsmc3IsodifFwKcrh829w9a0SWWdWjn0kcs4RmIZv0HsdImRXL2ud7yDkLbOoJuMKuhNZqPfocRcB73NY++RsfdYHdAx9XMfHd7QOX9H77iBgYDzifq3q/6cQLIIeUT5y+v+7EauiuQiNvdhcPmnUBEnepYbcb0Q4Mv0+T4jE205wa51OSITaCiNU0OeIs4kb+d7pOuaNk+la7cNJhAPpOh0jlvqjY/AEjbmx6tnKWaALmEAJUE/Ou8j3qUBIZ3MDjVYgG9vTif6IE5UmLUcx6WRLlyUpmLyVegy8AtmRHWkThf61CedMGsHENnGdgURL9YwLajOhXK4KRU0XovN1ct1CIJkr6uS6juC6qhIwJ/+jvxURU/1FOklfrxP/5qicDXrt+focB9CdLBJuLsrIiWxjMzv4tGSyRywIhwh4ga26iF1OiC66SH+/GtmJ79J6naQT3EZdQA4j7q7NurjuR1xK/QA5x5N+TMZo4ONDNLpILNrFOIYMC2LRVhv1OW1BPUXLmEN2t9aupxLSZti9zfxfIrBvlxDl77yoDrPAa18EV/kovYX+1kSUFykbBpTdr4vPeUQEmdFiX0LcUFt0PJgyYm6suwgRXj76Gx8PaL3vJt31Zdm5D+oYu4ygnF1AcJ9t1HY6n4Ahy+v/Xt+vjTQrP5OI+ynmQppM9PttJBjYiZL56uerCK66yTbjyN4Ve65zCGlFbqcRuGz4oGsI1r9ztJyRFu99GvOxKagxG/pC3O4jWs+r+zhHWvoOw/mYsjlCUPrbERPW09RoGfto5NBK8lrF7uR2ylGhH/PGsqwzg65AdizqBYgzoR9VIDaaE5I2hO5GL7ftzDb06b4WifRXujAd0kn07dE5tsAag/BpUZ3ORNxadUbi6PzzVNG4C1Hccjrpb9DzzyUw2lp0y12IW+QqYB3/xCG+z/2cwH79/js0Zj+3nFbbCdFcl+v1N+rCPKfXbNMy7taF6n8QC8SRhUzyLdozmcrBdpc5XXDvJ2CQJpG8VSdpP++OJuSC1msbivfQ70f0udZHv28j5CabRLhyDukivo2gXNei82sEAHUFGPkabPbpwNJkWLVhXWyB8AR8zTZCZJJhmbYQ8FuXaRscAv5e+8uUnfsRJeiILvTfRMD1acqQKUL3pvx2WPt2HwEQ/VN95tujuh9CctwVo+c4HZqjj3S81dmZ4/cyOmcbEcWDfhdHcdWVRvutzTgqaX9equ/EDn2uSxHFJ4mb22VzAgsInoifmQSuqce5ZFbruI0+hcnbOEtZC3rKrE6jcpQMfbf3yus4uSEaJ2eRrhwZbnCu23Ye5HE8XYr6D/M6CFYOkdHRLTlkYK5CsAvm41+xoiRrI8Av6ecygWSsBPyBfn8KIXkpyILZ670qiEUkB8x78ZcXCb7/9Yg14QPAx5xz/4JMYv+DLBLmYvh5oKp1f5oXXInV/Xhk0htDcA2/qt8VEUK+p2ndH49gdh5AsAbPQRa9X0bM9b8HjPh3+4e5P3N3Mcth/pLNfJlfAv4vgke5ESVM0+9+g2AFuR9xl9yHkOpdAvwb8PuI2+VxwKP0ue/R5+6HFKwsxWjMI3iFdyFEfoeQCXsNMpb/Xtv2DcCTEAUI/e067/2qCDcC8DZkEv4D59yvAH/jvf+s9sUkIR3EqxHXzgk+YCdGEOVzJ/AQbYNVyEI78hDBb52DcwUasSJjKI5Kx4olFx1B8qrZ9w8CXoaQK34RUXiS8mfaN/cDb0HwOfchuJwHtAyvf5+HYFzuQfBesTxC2+oR2o8xnvMhOr7uRyKrbtE2LgP32XzunDsAPD1qs90Ivur5wN4IJxLjxgwHY+SZRH39Pe/9NdF3ZWDGB+xMBcF7WX9UnXMF39jWJr+r93yu1v8g8Afe+xnF0GxO3OcyhODzNIQQ8X0IKWSNDqJ1LwGroj4uO+dA5qF6O6SthdEcVtIx917g/7Z4rk71yKXM6U0kndqmPb2z3vu19k76ZnLFGqJMTyDzyG1eyCTL+vf5+oyj+rzTCKZqjbbZtHNuxi8DaeOCpccdnPm9jwqf39F00CJHzko9aI6WMUuKkZaZidej/u8ey28bwk46EdgVyKR7GNm17yCQqdk1yTD2bYnvkmkb4izXFyMTrVmDvo8sdD9AMAt3IpP8vbyOA+zmAGv4rp5/qraDhQrbDmxS62cusD2EHFdGqGcYE+OW6duujWD5auB90boeJOzcNxKU2d36/T3R+SOkW2F2EkLbLUrI3FxziCJxtV5/vvZHbLU5i8ATtI9g2pc+g6K6viq+eadbju4TZxafJKQsKOjzbGoxBi/Xvt1LsApeTrDYmCXuEGKl20Vwn+5ELGVHEFzLHcB79DyzGp2rz/MNArZrDrEEGq7oOsRieQOy6H1Jx/YPEXfoz2i0XlUQd+541D9JV2BaqonYgpKWBy0tSszadyvwae2nj9KINapHTBKsb9YXpwNHont2nCNJkCEm+6yLebhOzUDkIiK4qDq+XwTrW5xiIxe1Y9/JFhP3L0T1sLx5DZYz2mCEaLSclbt55uU+urb8+CjKpttrMllWsciEFS8abVDzjTse22VepP9/A9n1W0jyzzrtyKLyLfOwjWlLomn3+aFPUNjrNc9ArCt/hISbPw15sR3C25JGfX+C152ulhG/c0Xv/ahzznZH+5HF6RTv/ds16u3vkUXoq4gl5EnATr7BM/lL/pX38ye8gtN4F2/WMvKEEN8jyIL3fL3vU7X8A8gO+pGIhan+mEiUUmoEygKlRlBcp6I+HQHu996/RaNzzI0IopS9Wuv5It1JloAx7eOq935Kx8n1iMUM/W4G+D+IleRfgV9DIn7eCTwZWdQvdM5Z5M/zgX/WfthHMqpG6nsyct9ZnFuNpG6oIbtinHPzyGIxr2NpBpn8x7z3Ve3fp+q5Fb2urOc9FLEcHqfP+3DgZERx+RrinjyIKL5PQpSW/0IsSr9GcJntRJSlMmKZPFGv+7E+yS/rGPCIRetk4OX63Q0IhuZexKryq/rdw4B/QaxTh6L3xSxdeS+Wl5MQN1osRe99PVLQIoh8sPqMI9a+WGaAC+z9RDYCM4g17tMEK+nrEWoH80jkECtPBXgsEklmYPmTkHfWxmIhcU/rE1PQj9PnHlFLelepLLQe4/pxtY6Fca0LmmbkgPZNN1FjZQSYfxfC9P0nSKqcGs1Ra30XKz96X+e1nWLr0mqt59qU+ph1dFzbfPVS1nch0rXyk8lwi/e+pjmnijohGcNpGX3ZvIRcD7XoC/a/gQdr2GsOMeVfqYtyVSfSO5HJ7K+QBexBWkRd8VE3mU12E9HE+5c0mo3jEPZHEUJqrU5FZDG1drzGOXcZopRY6PkmYJ9z7iTv/S3mAgPuT4SOvhB4ibponCo4J+k5R5Dw6RP083OAn0N23iYv02eHDVzGtfyQb/Nufo3vcwofTzTneYTd/FMQ68Kpeo9H6P0eQqOL5I197tJRZKdaS4y/HLBBzehj6qpY7VuEE6uCNEPIC2Y70TVAJfr9S9qH9yNurCciO9O1iJXkBMSi9F+q7PwHYro35SzdTO/9KKLklPWZop/8hHNup3PuIYQcV7/tvX+qc+4SROF4iXPuYuDNwG8j7iWAV+j/5gJ8mPaPQ1x/Xp/n0dpPr0JygD1CrzkOUZiegyiz30SsHU6v+XfESvPz+t1DEEUiljcjIfxnIdajh2i7WeTZAUQBMfkjfcaSjvO/QkKrczoPpeVOGyG4Pyva1skFM4dQLHwTWBX3hXPuoYjCcyvweO/9+7XtzY261jn3WsTdtQ/JA7YKYebequdWnXMN1A1Rv4865y5EUrqMe+/Pp0vR5ykhLrwp/W494rp/KKKU/pHW81Lg5c65P9E6xmKWzxcgyoIp0kVtj37nFOtZ4j7R/8daneecW430+2o/hO6vhSg/vSS+y2R5ZRTB/thAmwBO1oE4bv7aQVeyldhEhLz0dyIm+yuBlyReOvNVT/iQGNEDf52wFtXbQXditqN8DXBl1B4lYI3e/xZU+dFJHGRxeDoy9nepYnk2ovD8G6LkHIcoSF9xzj2A7EAfqX8/gCwkaBnvRhSPRyOL3wkEpePnEHdXEdnpP1zLuAexXDyZgMd4IzdwOo8DXsgbeSFv5EfUuJcHkB3vIS0vlkP6fHdp/Y5DdvzHI4tpX99vbfcpmvmCasiu+O+UH8dwJGYlS1p4qq0mW004+WUkiuk7iDXoPAT07QlukO36+3ORBfH2yJphlph2Yla1NPltRMmb0XOeoliUKeCd+g6WEQvMi7Q/r9bzP4Uopwe1rAe0Lx6CKCwHkUXU6fdPREDcv6h9d79efwBJnGv9/CiE2fhZCD3Aqwhu29t1DLwMsYb9Xy0HgvLzBORdAXicc84iIR+LKFv3AR/Rdv0Kgmv6VQJHjvWPWX1sU1aiUZmKLSdvamPVuAt5X/64xe+XAZd5738vKvdFiAXQLLwvd86ZNewdCGVAzjl3NjJGtwAvbeHhyOu50/r5BGTjtQeZN/7ROTep7fsgxF01j8xnpyHv8rP1u7dqH6TJj5ANz3k6bixFx8CUnwj71LXo+zpwha3lM6lPrpdGqE9K+tlywyyaACqTpROdgMpesz4Ps6gis47AuLup3a5Hn+0r3vuHR9+VECtQNXGuhVj/CHFNvALdheqkNoq6xHSs2yReQRaY3Yj15qGJahxGFvMvIZP/h5HInBcDD/feP9I59xlk8Xki4nLYiyxWnyJsRF6ALHBG8ncc8GPv/SvVhFxGsEcfiRSDvcDreAW/z4k8mRm2cJgTkcXyRkRhegSBNNCUjWqsLDrnLgLO9N4/cZH9Z1bHeQLA+bVxuZE5/On67A8FPhwpIyME90CeSNFNud808FJEAXozYvHZg+BjXqL9ALIZ+G/9/1uEnXVJx0DriVrG0wgdrKcRGWbFe39C4vsPIovab+hzX40shk9Es9AjCojXvnsQomw82IpBLDmP1ed9PKLgzOh42oUo4PciFr+fR6wgluT3NERRORFRvLchrly71y699qmICxbEbfZYLesKbd8RLeN1CHC+gFjg5pHx/HEvpIJx/4yp8jOOjLuGTZi6hcZauVx1TvhH4M+jPozlBOAX9P9YiX0VoviZPA1RkkDA31fq/2dpe9yiz/zNNt38E62LEWqCjPciAiR/ITLeY8tVBRrgI9577+hCdI2dTbSp4aGKiMWpXwEKreqQBKuvfFkAEMqSzk1Hf1OTBWbHcB30MVXBEtbRIk0sPPWiTvVGQabR5zIpXBPIZLWO4PuPuV0KBICe8V8Yrb2BdS9BLDSbCbw+lmvHI5Ppev3f+EbM7fH/0ISSBMzSHYQUBBuAM/T38xDXxddJAH0Rpej0xHMZoPI6TudS3s09PIobEIXM0jgUu3k/iUKEF9B3FvUxSwADjyNh9OVE/8wS0fsT+IB6Au1rG38djbzT7y4icDXdBZyfuK8Bwy30u327QF5Bz13zl9AcDn8hAZRrHDpnEsKJq4iS8j1EEbqLwNlzM4ED6B4CluuI9vHdOpZicsS7CZxSP9L2uAuxNtyGKH9HCMrWfdo2Fnn2df39TgTPs1uvW6/9+lH9rkIIFvCINTQer0UaKStmW7RVJyDxDVq/M1v8Po3gnmIiPwPjFgmpXeIgB3vfT9H2tPxm7UhRR3Rc/UTrtB/ZfNxASDlzdbQu2rE+0S6+x3FeH0+EdBcGNm/IA7ZE8/JRE0xTf6Z+Ng5ZFNhQH7oQJrOeT+ukNd3N4rgMdVwH7Nb/LYJqDtomSTTGV2MpzbU5twSpOabijO2WXdwUmY2IK6Wg9zgvMaEX9bxzSRCKEViBC3pOHLHhCZEsRjB3A8Ir9H2tR0EnU+Px2KbPuE0XzF26oN2hE2+FNzDCe7mdR3HrAtr/dC2n58lUx1e5wznGbmzKoeVwKrbqmw7lzemCa4uOtam5aO5QpWK/3ideHGe7ug+M+4Ul1zUOKuNwqiARZ0e0z6/X/rtf63eLLqwHdCG/Q/vfkp56Xaj36zX36jj4L0QpMlbxI/rbLgSXdgeiZF2m5dxPY0SYRxSmPXrdER1TpgjNI0Bdi0LbhkSIfR1R2o240qP51xLjP16kk/nwyp36HAFjN+RQSxlTRmsw26FP4og1iwq8HfimnlNoMT/EnD3raWb5rkf3taljrPx0N/aax5O9L8l8cuMp15RJRKAuYl4eWWwZw3Zkub2OLRkDxtUMbTiItV7Mr1XkZRm0vBFZ+CFYaKaQyaOVFKNza7SPeisAEyk+/RxQU5yGlXUr4sb6LRp5VS5G+D5y0T2t7MuQqIyK3uPRiFm6qu1cz4mELDLvQPKXfQDZTd6J4ChuRkDCVQR78TrEUnCL1vUeZPL+NuJG+WPgM977Uf81P8Y43+AFPMzheupT7/2XkPD3yV6us7bwnTFlBgyteYmaOplgRSvQO0bAcEA/0HY6GXHB/BBx5xxCxvXnaHSDpoFyW8lC8A7m7isjStnv6D1fiuBwzkVcnOaKNKbmw4jy82AEh1NAxp7N1WcTXKQHERfVSxC31fEEZeZ4xBX0PC3755BxXK+its/11oV6j+ORsfU4ZHweh2DPHoVYgD6JuMqehfBPnRS1za3A43zIsRVjfUZodrMaN1JLV7y+Q2cDX/StQbPGFzSDBESkjnkdb6N2aL1riOLzK3pOlQifpvmu1iFKz6MRjqwtOm7HEP6fdcim5avRs5dsDtC8elMIXiivbdErJ8+89/5kPdb6RgzkBBLtlrN2VTeiRcha7jnvnNtnuez02Upd3n9J3WoDkX5pUURWhexYuoNgsVmwlSbtWmSCHxhLNMHK42nkD3ktwa3UtIvR6+o7Lm2bTm6ypvw0BD4a893nECXgbwgJN/chk6VPHGbFuTPlt6qWL5iR8Jz7CZT7pyI76OuRBeVi/WxmeY/sNs8n0PU3MNbSmIcsB+zkJM5giirruVzPP12PdpYx46up0YOpmxSG3zbl922e0DY1195mZJEyt9t2ZAE3Rd+iB0dI5DZqe0BJ3V49c5UQwvzLOoYqUZ+Zy8vcV0e0/7+gnzfrNddH42krYp15gGDpMSvNaxGLjicwPZsbbAvBbbaVRuuRlX1Yjw/TmG7DIy6zn+pYPUKwph3Udt2MWC/vIDBeJzmekjxJdd6nFm03rsfpKJdTi/FUif6/OapTQx6vlGsvpg1cA6FH2G/vQqvxou3z0RbzWXK+KrAEFnYCv1Ql2a4IrumCqN3NUlfudz1W0tHPxh8Kt8nRfEQDe5oUM2cfyh96TFCrlz75HLR3k8VYjNgUbq4XUzCvNeVFz12vSom5um7W7z6ii8p3EXfA6Qgg0hKZfgK4KSrnUyjxmn62RfFWxOW1Tss115pP1N8mryJwrv5vyQwNg/RZDJ/xNrbyR2zjMazTReqUdu0ZPWsdR9PiXMNVGJniPkJCz1yb/hohmORL3c4b0f2MZt8wRnsIRIDmfnynLuT/pYt9alLSrg/B/Ux6mPY9uAQTY21O62XPbdFo5l66UcfPTj13FyH5q6W02KUKxt0IgNkjlqLLtT2O6LmWLPUBVXC+Q0hVsB8Js/42AVv0ACGX3CaC0uR1XB4gEGbu1zbdqnU9g0AgeV00NqejPk/LDdYuGbEpPnlE+dtDtCmKxoPlVCtqe0yihJJ0cNVofUsp35+n7+5uIlxgizIuRziQ4u9KLDEGp9VYI2VjrP0zmaifKX5zndrpaD16jvZqJYrirxG4OCztQD0yLJPFifFo6P+zvs+8PclIDIsQI6TRaDC3DoOoC2/GR2ZZNZUXvPerW1xT8iFa0XamFvlT8MI7U0KwBj/13r9dz70Y+Jz3/krn3LWIS8DyeI0jSs7Xta2eg7gKfhdxVT0K5aRBXB2/jfCtfAx4P+Lu2YyQGX5R67MDmfQv1LLntY6TiCvwV/WRdgOv896/QKOKjLSxpv03gVeW1q/xR7yRt/kWkU3OuYqXSLccshjf6L3/1Vbn6n1GvYTkznnvT1azfokEv0dEg28pOKoE9tg1vgNxm5ZrVqmitssbvFAfnKHt6Qhs1TsRkLnxy8z5KGJmgQPOlMtVdHgXtC/muij1AWSxvR1xU92hY+RW/f4ZiFLzNALj838ikYqPTynPLDgWLWj8QYf0Xo8kuL1i8chY/SGNLrJDeu5fAX+BuNN2okl3vfdvdM5tR0Lkf+i9X60h3xPaV5O+MVJpBHnPmtxdUVqSeb1+EuXP0XfS+J0mgFci1lnjX8oh798V+l3Bt44ea6iD9tWfI1FfAO/13n845bqYEPV3tJ1uRlybIG7NWwjRcoWU29t38Xiv+iXk8VE3mJVfQRTit2s9Z0nwKh0L0k+Sw1GCywCCP31c2VSPnhC5wYktaCCMm4VOC0aPYqychr+YQUKMZ4aBayIWraMd8wlyx5jxdSJl7BWAqSgHzwyCa3i/llXSyfafkEneQue3eu8tNPZhBGLF07Rfvo4oPecimAmTPGIVKiAhtL+LLCZ3I1ieGS+h9g9HCNwshP2xyET6Xv3OdsLfRyaw1fr3KsTaFD/fGAHD9XEc7+BV7OADfIU3M2NjJwpLr18b4aG2IgSMIz7h849YsmNlYsbO1TxIyfEyjkz4xnBsStMUssh1UkzmEYvNqC5e/wt4sbbLXdqe9yAKwQ7gj7xiTPQ5Fz8HeT+D8BLZ+9HmVD9PpGCoQvAjNN8b8OuIi+a3EOX2t3ScnIBYJR6BuCwMgPxGhFfmicj4+qK24/2IYrIVGYMP1fMfrfc3CoiHI4veTxGFKk0ehZB2OoJF6GFazydrGQ/Ruj0UYaEGeCaiANiY+kXt+3EaMTRmXW3amETK8RSqNBEpxarITGn55yIWjeu1bv9Hx/O49vNbovuZmOLyWIQd/pPOuU1a14chOKudyDv3Lufch1r0cU3b9hTtG69lvgHZMMUkqTN+OPItrkXmipr2S9F7f4u20RQyjuINpG18YQg3vX2RZTDFZVFgi29DwyvEOWMqpLh2WCSyn2BCzqV8v+LcYm3GpJl8i4grYSchZNf+rkcWkyLNvvvvIiBb49uYjMreiuAvSgT3zlU044XuIER/nYa4FuI8YDuAU6PP4wTMirkUziRgpc4kRJWdo79bdm5RFJ/ENIfYwUXNuaas/ok+34a4Z5LP35RLjpBXqY75iH4r02h6N9zNNJoNusu+i3MlzUVlbyFkL9+KgGQno3qN0w/zPhQU/9Ozi1/7Ic5ofoTAZWUYt12IgnS6PkdB++AqPe8aHTcjUZkHte+vRqw0tiAf1nFt+KDbEeXnEKIk3h+db2SJh2l0ed1HCJ2f1nvdT3ALFQk59rYQsGsHEcqBycT4aIiGTBk79r60jNrUNrkesbgY1m4vYgXaq/Ws0pyPzMblD7Q9dyIWtCpide3KVaX3N3eb1zJLtMEXDdNBc46ufDy3R+1fpwgYdJ2XpB2WoaGXPAnb0X7QCJKcI2RUtpDhOAGgKUl9b3OixIQr/aAx5NnatKSL5r7oea9ocf110UKWDLW/KVaYiBIvRucnOUe+RnNySFNqbOKOQd3JpJCeZjxETheoffF1eHLcxH58aqLQpEJjwNU4tN/A34b1KSXuayDkQuJZimn9QOvwYANxjiTKjxM+2uJrYf9lRMmc04V8hy6O30hpHwt3HqebDRrkVPFZ0GYu6oeiLraG9/kYgULhIAGb82k9f7Mu9p8mRFhNEhTbPQQw/qwqLBayboqQKTHmEpwjhLrvQxSuWOmxI+YNqmj9DiLA6gNavzyBSsD+P0frEivzTQkwozEwp9cY1qcdZixOkGsWaaOE2KvfnZbyjpT1Offp/+fTBh9IwP4VUupqQQc9BVsMw0EKD1qk8DQkUY36LY03rbiS1/blaOijUmsc8MCNs+XazvkcNJJHB+XkEtw7mXXZwMJWhxUHeFeFZzz6/DVgfTQhXEBzZFgDHw2Nu79rSWSYj8+3iYUEMRlKZpe4zhboffH5+v2+6Dyz9qTVcwfBUlK3fvAEtuIZxzcC56PFJN4t70KsP9doXxvuwqJ5OgLwk2Ony77x+mw30AgcLiAWhhqygx/RxW4rYtE4oAvwj1VxqCH4pThD9pxeZylPOlufBPC8YOsRAZBqZIsjCL3BIa3jZsRlsl+f47ME4PN+VXIqCOh4E2IRMsCzcf7coQrN3QQAePL4gY4p3+I4qH39AAFAfTcC1r5brz2EWNnyWu+t2paXRPWsJMZVmrJtysTp2iatIrOMXDe5MMegZzvK+t1XCQBzIyndEd2rnZKVi+ZZC8m39zZWvHoKthiGo00bW7LalmtOoi/GiYhKU66z9WEoN8zL0dBZFFh/27MhbDRaIOPdcIMZs4/3NgCnKTxmpjYCvr5HoC3HRECjQjcLnBb9ZpaFXOKa2BIS7/42AQdT+sysdNZv+xLlbaYxssxcNbno/33R9WbtMxBomvKzGbi0xbiR+nsqeGbxbcPfzVJxhChSjMjCqOOh1KGMSaIw/ei3uvIRLTJ5ZBd/sy6sdyFuFBvr5+giu5Vg7TwnWsC/ilg2vq3nmOU0r7/LZA4VD97DvjdKmHxFLTxNz3JAlLCGxXcR426b1utGxDp3KyGqaU6VC4vgKui42q/Hbv28jhDqXkOUJLPy/JigDJo1x0Lb79N7mDXIQuctOuwAIVx+H8FCZGSLu/Tveq3bdm2Xi7XeV2h91hFcJ2nMzqb4nNFKaUjMb60shE0kf/qdsWbv0bp8CyEsbSJbbFFmJTHWGyxXNl5T5pOh3vDT+ybE5o5SpPDYe5+61iTWitlEW5ZYAG1E39thORqa4I6ZjY6+WyaOlYNmTof6hEzgE0l1URFcKfGCnet2MBJ4S9L89kNv8k2pcxwiXqHZxF3f/SXaMLbkTCZ+O5icyLVfDKcRs0mbcnMxUVoJPb+UKCPVPUPCEhRNMGbdOBPNwRTV8a76e/kkbuE1HOS5YvFq0U7X6jGdaB9jr25rbYzOvTYat5MEpcfYs2M81gVR+e/URbcpfDqaX16rysF5iLJ2WBfh0xPzUQWYux7Oq7uwROEZB276Mvxrsv4vh9O3w5G6grSwd9b63BTBOg6KgBk5QmClNqbxcVVIXhMpNxchLlpLc3G1Luzr9Jn/FsG0mFVoJ41usLsJGJ85Pa9GUILsuEvvdxhx596OuLzu1vsVEAWzgqTmOIgoiaWo32Ol20DHZp25kNY4IGMDX0cHhVPrHo+fJJv3Vn2erXThtqTZclVXmKO5wtPISWZRn+aqHkqLxwLnSdtslRNtNKn9n3Qp24ZlFnHTjuu5phQNvG0GuugM+uFX8mGLadqkoAPufJpdBf9NSOjZd7IrEjiPYT+IQNy0JjCbTPkuTwLvk/jtYkilyDfFMU0p3Yxy9ujnEs0KVCVxX/s/zSx9qr1jSFbx+DdL7hpyBXmKeObwTdYjW6iu04Xt2wQwdQGxzFyrSkqpTTtvR/iQDpgyQnDpmavWa72uJuAqSnrOVr12l97PLGklHdN7EGzPJp1oa7qwJi1709oPI2+HDzbUFUrPhR3nSESeWdUMJDv5ITj3ANzwMdjmGy2BI3TYPNg5BLJLC+lOS/cwqf03Ht3/M4g1aw7BL80hLrMf6fcbkHxbI9o+OxDLzGHE+vMzbUezAtn3pgCZdcesQHfrXwM4342A/28luL02631vQqw9d+l4uDHq99hNZFaiC/X7MVLwJIhbypTifNR+rVxU4wQyywaeG4Jb7gAhCGGSADRvhy2Kg0v8oOerYToIuL4iYmHbEc0v2xF2+mQ7GkxjKDwEg2y8owY8O2yHDrgxwo7YdoA3IBiJGwkYlQbkfx9eiGS0UMxsO1TuTxJ4nzbnpFlb+rr7I8WiQKO1oEEZ0onHlIYYs5SnGc+RBFLndWFsZIn2FNQFZkqR7c4NB7SHkBDzC1H5nZJSxkDUmwlWACt7PLrHGbrg1qO19NxPq+JzHnBV9P0mVQC+oAv0tdEka4peXE7srmyq9zjsyEWkddrOJWvD58E5X4QtXoDP9Ug/FrCbJQEWT/S7uVnMpTdOiNi6gOBO2K71u5FAwHmB9tUHEYXwPiT82/J6xVgeS4xqCU4P0ugKOxJ9vhRJbmqK06wqPFWETNK4f/bTjCO6VJ/j7pTfxqMx/jUtZzON1tY6Bkc/n0Jwxc4BU4k2jAk4r6DZPZVqJUq896Z4znKMbdYJFru5lLZLY+y+QcfntTRa/oY2SniQjTvUftGVfESDs6IT03RiItmJ5KGxibYvSknivjG41HAzQ+XqjJWLDud1zvy9+HrkSLcyNWFkorZu5X4sRn1QbPE8l0fnBpO1J6cKkC0M8QS3DbEg3JpYvCajexog9yP6/yadFOsKT/Rc5vKxqK0qsuvfYIt+dO+tBObeGC9VI7gTqwRr13oEM2MZ1M21Nk6wwDQpP58U5exuAujdwLTx37yHwiEpO3bDxaZ/W1w7Jdk1XJeFeMdRfYb3sb7eT8DzzCCKokWQXar1/mj03t+uSoqPFBhTfg5rvxjux9xclu7iMKIwWTj8QcTyc4f+vkMXOq/zyUEkr929hKzvV2i9L9Wx81kEr/RjgqJmz29RYqbUNy2aWu6FyAbO3HUfJ1BJWPtdFM09Z5FuhTXlsabj+ZC231xUztUIDqureWKB82VDNNkyz38tU20QQt3NQlkHh0OjSzBl3klz18cZ6YdiEzzIhSdTfpa2fdthc0aIzJIp1yzYIkcAP6ftaOeGZeAvZKJYonJjEHSqlWkJ7rmeDhYQrmWaq5iLgdCE/FDJ4wAhCqyIYEG26v87Ua4iGlMenInma9KFegdivdiHKE+z0bkFXTTrGJ+oTpciO01z5ZnStxuxCI3reDSsj2GPmnEmkC/J85yHWDTeGClTFgZctnN/JnU2xSvGtcRgz8kOfRGHF9d5VWh0Fcxpn92ji77X59uqi7ZZh25TpaNuzQA+ROC+2UFzJndTfA5Fn01R+jzBWnSflr1X/7+OwA+0TxWavQS+KXNLnq1j4FJVnuLoQyMpreg516a0TYwF26HPvJ5GV6Yp3HldqK/S/4Oy2lhuEThb/6+nwtB7rSe4DLcTUnf0dd6iMZrsQm27ZZsbSYS2J35LA5DH+NKe5vHofWiK1hvonD7AxSQ2S8e7xswVtvRtn9PJ7o2EXFbjOgFtIIXUrtPg7vC77V6XZAd1NB0sj5Xp/GjRLtDMhyKLyBfZYpFgBDO4b3EkSTHrYfCJ783ysw3Z6Zu53MbI7QRQrkU+TSMYGFvUkxPzQcQiYTtVU24264K9LlZ2iDBbDQeUnw136DmbEJfRNq1L4yIB0+8VJc+wd7HrMd7ppnHNxIu/BYDEQQuxkmgWpxLCPHwIYWg2t9TFeu1Gre9/abuaAmOkhfeocuQR690DiGXHlJ37CMBmc3Vdhrga7fdpAkZoROtieKFrtX7WVgXts72q+FxOIz9PDnHL2bOvS2mrKhJyX8fyEJTsyaitzkRwR7fpeWlh/DaWrtW/VS3XFCWzBpaBP9Xn2osoU2dBf8kL9T4bCFG62/tcvimMhRa/zUb9YGDkusWNdFyibY4XQvDZks9rYHNtnyZTT4/RQ9oYBmoz3+qKIIlaxoXQ8DKtwLgWcl5qc33DxBr9tpmQEsB2b4a92EMIYzWNvVUYquESZlPuYb/bDmNFhsMPoN+X1MqU0k8GKi1EfSluy/dwC7s5wPc4laDApik/SeCuAZgtw7YpW2aJMcvFPbrYxtiwsi7gF0ATeHUkpf4xqNKiptYhIOEtCF6olXk/X/+tcR66VBf+GLsgoc4SDj9O4DuZTdRzLqrLeKKeRk4Yk+XFhIvGmWVzqe2Wb9R2mtFF+S5VOmZUsdgJvE/f4/v0nL3a/sbo/ClCZndPUJKMAdqUHnOBnU/gDboPsfBZNNrt2n93a12mERfSPdp+BT1vK5KiI8lTtQXZZMWcOabwmfVrL1EQgP5mi/ZViGJruammEbfaVlUqLkAUnHO1L83FdLHOfcbEvkPPvwxReGMSzX0E11xN58R+0Bzk9d7bouf3fX7PY0qSpGWngWBVv7Oo7GMm0Wk/FudYk1909BCZO6y+AEYKQ5OZkcCEakzPaaHVZnoep5mMq6AT3hcQs+u2aBGsILuobdHkbLuvYtTncaqBkZR7jEeLkj3PdoILYjdiPs+sQUNw0Lgzr1uEeDsfZAeH8A3ga8OG2NGKOG0WwU4YR8112u8HVTnZoQvLnmispFmM6lngU+4RA8OrCIbDAKvtSNjs92lgbj1sjuayWa1bA6FeCarXhxDeOSLupei8fVEZ8fw4F933vG7mOgLe53QCh9d1+v39+o5eGr2HRxDywa8TXFY/1u8NzOwJ+B77bJYir3/vVgUi5gkyBeku/W4bITJsI2It2UhIyXEEsTJtQ5TRiioaO4FdKX1xA8G6VyfRjM7JI67MWX2mO5DEtXE5pyGKlUV3mWvNPAw2/5gVydyz6/UZLwfO17LqSj1ixdoS1W/DAt8xcxttohFy4KP/S3S2plu0VbnFPeKyjZvH8vhNtxtvg56Hlm2+W+RkmYaQX1T0UDcTwrFw0JzOYDb6LZk3qSFnTqRoxBN3rIjY+R+MfjdOjZxOtAdQgjz9/RydzC7Vl24rzTuKuksi7SXTe1xH2JVvB95NAEe3DD3NjiUfbxdYn0bHNp2k86ziEnZzC75uwfkbGlMh1NN9JMZDPRJKJ+xLVDn4BqLw1HQx/Ww0drfqIrQPGlikYzLEJOmkLXIHozE4iSharaw+8Ttj3CRmefkoaXgdsfrEC0t9kxF9Z88c41Lq2Cq9x2n0EEFEAEfHDO8G5j6gC/M6/fwJ7btbaExhYW6w2wmh7GbpMaXpbgKY2ELaDyEutVv0u58RorruVyXkHsT1ZIrPz7Re41H7jmsbb9ZzKojlyjZCewluvIu1XU8lhP/P6TNcpuVdreM2Oe4MO2ZWKrPwmPLltQ6bdRyaxdM2lCOIqyvJnTUd9cWNyTmLNgBmne9qUT9t1P9NuTICzbry12EsGCA5CUZuisSKrjGr7mIwnYviiRumY6kW7QUvYMkBlx0N7Tob/U0OblN47AVKKqbJnEhpOwYDV9rkNZd4IU8jmPn3k+4XtvJTmb2jeyTTO8Shpxn2a/nH18W6kBSj43Qk+kl27c9kHZ5pfsqlyO7dFJ97dXGsjysak72Won69U6+5WMekKT9mct8YKw6EHWsMKK4r1rpQzQK5v4XZEvjTYN7L99uBrW2eOQ7lt+ieAwguJB17JZFeDfm9onKmCalIjM06H7WBhfPv1b8WgVaiUelMe6/WAZ95D9zye3Drn8CGv5a63q8Lq0ewQA8gbqa7EbzMXbrwm6J6G6Ko/DWiwMTRYPfptffRyAe0T9/3XYSIsW8SLEf2nZV9QJWOGxL9bxaXrVq2pSipIER4N+v/a5GILVPC4o3gLYgry5Lunk06xucSbd+0FB+7tY47EOWnAnwyGq9WtuGMctFYNNdxJTFnrSdECBYQxcqsh3u1/a6iUXG+Sd+DvQh/VjveIbMA/guyabiOxrx/swQFZ0ncVnTh6WHAEWw9Pc9SLNKLvD5Tflq3TVOqhcTvZtbMdyij3e95QoLOU/X806KXfB9isk/N1USL0OwenjFmf20igcuOvo6nmAvF+rYJQ0ZEqAnk+Hf2s4+ryTUsKHcTciadirgnzNVhi4hl/74nWlCu1sUwZr9uIEWL/reFsBTVVXLKQX5Syr7jzbD+0xKi/D+d5qNoUbFyc7SwPut7UfByTHuY/qrwzUzSDMK+kgCytXdqnx6msF0Ytzkh2mtf/P5onWZfAN/XZ7z91TD/frFsGADZXFz36/W7tU8+rX2xHbE03KPHPGIlu04VmBlVOOKEqAaAtkzwhgn6MfB9An/QYcSCa1agnYgSexXBUneKtvF2xC35AAHonNPzb0I2XXeq8jACfEn7cQuC6bkb+K4qDNt0zG3Rv2foudcDv6X1vJiQwf0a/f0HOuYM1/Mxfb6TCHm8Nuk4ts+nEKxVZjUyxaMM/JBACXCLtsk2/VykMcDA3rkbdQyclBiL5uK1tjPFuoK4M42oM6ZgsDG8ZHgdOnh6bD6JnnOosUNOK9oXcc7ltYGmFlGG8T7UCJMGwJj3fqJvlT0GxDlnO80asNp7X3XO5RCFYqrDtQZIB8FRzAB2zSzw68B/Aqu89zXt+/Ho/JLec34R9beJoICQNk5572uDbtejRZxzs0i/jhGU1gnE5XQz8GHkfR6LrhGrkGeeKuOsQZY/kXuRRePlyELwl/r9KPBc4MvA/wL+CVm8QNypzyHk7ZrUOlh9Vluf69i1CRdkHK/SiuX2w94a3Pw9+MkauV8eUULWpo1DHbN57/1M4vv9iEVg1K7Tcw3UO+a9n8K50h1w8TvgK18UxWDe2so5Z6kqfokA6s4hBIpPdc6Vgb9DQMglZFE2EtKz9B4zUZuf/SQ44WfwC1fAo2bAV+A4RBkysf/3Aq9ClInnIkDohyKL+8/reQ/Svw8BnJ77VOCRiFvsiYmyDQ/kkIX9UYRIr/1a3omIpWk1sAZ4G6LcPBl4O6JoPJ5gLfoC8AZtl8cCjwH+FVGgPum9n3fOnavP8m4dGy9AXO8/BH4ReJGe/wTE8vUrSLvEci3wHkTJeZI+66OR+eu1WqfjtT77ddz9AHg6Mue9Ve/xDO/9Kh2HX/PevzLqnzMQpe5OZLP4S1rGP+p3fwC8BFE2t2ldfwfFlel4r+rbVEPey5r3vkob0Tm+2s2au9D1QM8Zib6at7XYObeRoOzdCTzGez+qv81570/uVK+BSZ81w7ZWhx7KMbN7gx9z0JriSjoIoZReB7sluDyHRfpnaaT+t913HSwb3b8v4aFkLrGlGB8FGiORbBf5WkJE0hmQygEiu7s/4VrmlBc6WIAeQAgOxxGXxG5kVz+OKAGWeuEsHUMHEIxKbFm0BKcnEbFQa71agqKfB+dcBOO74Zb3yIS8G3FHpIGkT0GUhCtQvqGo3H1EebcSY76BMfrP4dvXyHvWxCRNtCOP2vwgIXXFVv3uOsR6cQNi2bg6UdccYiXwT4BrSuA/Bne9WdrbrDH29x7EKvFVZCEfRxQQS6A6hbjJjNfHFBgjPEwjPbxP632vtpmxQt+GWFT26He7EdJBmxPW6e/b9FnNJXq11tFSppxl7R61dYXAtfMZ/f1ebaMbtI9uQyxF5oo5CVHcyshCfFDb47va5j9ElI7N+v29Ojf+sY7JHxHyyN2D8g5pv98T94v2VzLf39eRTcMlBBfjEW2bPdof1hZb9F3YQCJnVo/vcRNZJyFyspT4blHBSaRHdVr9bY5OBXEP49HvCbWvXAiJso8pevE+tNeFicFuptLxlHN7ArHFLxwt+BtYAoWVRpdYKntxdnT/rtIcIVjSydn4bTYnfjfrh5nht1PQjGDlJlzFLCGtgeFpHkB23VVdbLck3+t4zBAwbrt0YT2dEOpsIOjKn8PI3bI4bQJKHkp/Jjv1jS0Wh4Iuylu0/CPReN6C4oQSdakzOBMpXd+FGycDS3EchJDKJK0L+l6kfjUSGcZ1sd+W7K83w/p7pV++Ctx0BtTKjRFaxt2zV9vX0loYyHmflr1O+2S3XnODKgmG/9mGuI3M/WUK0u363Q4992e6mB/W4yBi9TmiZRhf0O2qEFxNiJbyiDvuLIIrKcaIGYHifn0Wq8N9iBvr41rWldqGplRNIelXNuuz/kAVkHlE+bMots0E9uoaoqT7lONw1C8euD7Rjxu0fy/W9rxX62zJYG9HFClTdJNJqBe9XtLo+mqYG2mkF1hUcBKRchp9906aySZXjPLTYB50zpWdc+Nq5moS51xOzymQLmaeztN/yS2+iGNKNno1m3txG0wgQMEt8Ulqfp/x3jvgZOQFAnkpWplCq8jLgPe+6sV8WnDOVZxzW5xzm7WcGefciN4n55wbc879JT2Ic66oYy7nva957ye8mFKngBHn3Kw+QyZdiLanRQ0Vtc9yANrfb0XcAbuAE61t1WQ+jbR7DnGJPZYqsIqAUhAx8OwdyAT7PMTCUwGepX8/jChAqxNVnHHOlfR/i+j5GbJovw/Ia33HgKd570c/CBP/BHe+BZ42Aa94H/zFh2Th+ReC+zwpB4BrvJjorwQKzrlJxN1zRcr589peYR5yrvxUOLImkBDGLooJgrUo/v5dBDLAv/Per/LBvTWOLKjfU1eKzckj18O1H4cbivCb74Edj4ZHTIhCY66vxyMuqeuBxyFWjCcgbqUrELfStcAr9NzHIy6vP0VcYncDD0asJydE5d6PuIQei7i2HqN9+3g9/3jEorIdeBiipDxN2/fziBvrGXr9HYg7sQb8M6IwHQf8GWJlPMU5twNxbe0H3oK4u+5E8D47/n/23j3OrvOq7/7uXEgI10lIwj1mDARebqJj7tAIGBco1K+AjgvELaaFMa5pEVAzxgXq+jUwAmJRNyBGThA0jpWMogocOUoYEdmxiBRnJmPZsWTJnhnJsiVZkjW636Xn/WOtddba++xzm7uk83w++zNnztmXZz+39XvW5beA/6TPvB8xcR1K7g7x/QiweUrf658RoPQN2iajwBcC363veRoxdf0cYrJCx+MHta6f0vnyHgTYvC3LsqEsy8YQk9iPAL+nfZzpYbnLzuB+cF+AgNIb9N2Hta/fwTSLru3LcAf7G1NKt+mYWql1IxXMZzrXexHzWjOlO56r68KX4a4QkB/nZf8vrFLYDRkyLeOuiJTtVbwyhXuUkt6Fc4wjo9QjHM/Bk8vGPN9I8Uo/EOBTFSXWyo4AZ/mMDn/mnDyALLqb9fM6ZGdnEWCT+lvT5iuqExD2lPw+0Mo9r9VD28mca/vwsF4j2+sinzfLGG97cFOFmVFP4ezHkhFsFacZ5GW+guf1nEWIMN+LhxFb1E+V2Sr5DtNIAI3s8H7EbHEK2XEbU29vkuirDuDwz8DgW0SImbO1mWO3lTznDjw1xDHc6fuW0B6RXsKYo2V3K07PY8lzH1W0poX2TuSdly2YYA9iCjHfpkFc82Hr6HvwyLH7gHQDnH9znpwwHpa36yJwUO+1GgFuJpAv6TpwEs8V9hLO53NZ5+11eBb4MlOYkSxuxpmnzyF+XcsQTcir+vkOPO3FOkQLYwmXJ/BEqHfrOx9CNITdiMnrRQS4vKp1OoyACgMYRY2NkWUeLfnNtDKmFVuPADVLGzKOh8lbrrEJRHu1E4/2GtD3P4CE3n8CYazuQnzaNhXkVzEcvzRcfobneyfVdCOVnIC0oHnCTdE2fjvKrsc5mkpTHC2kI1a6Hq+Ms5vm/y8SUEXejDLSu8hqajl2iguGsaYar4XZJi1qooMrIIxuoR3aduuaPLeUroB8yPKEDXDIZenOTQ5dtO5VoRV5howfZajZyR/GRJXZC48mapvEytsul8Yi/h/m5SIcmFSyyCNA4gDuizeEmEssR9RZRKu4l7/gKEfZyVs4ANxfWHC79bxN+pxaUVXm3zOGc8hYfqojWt8E3P0UrL4ERx+GQ+8sScuCR1mVmWaNCXpTWLPsOAJV2ax79bk9CQZTPvHjETwDvEX0DOORXcbePIZHx9gmsIqsTut9EBj5czizFs7/e+mD8zhdgPlYme/PpfDdJb3HCcSMdA4BG5fwkPXLKoBPIMDSwNMZZNduIetl4MrMUGf1++NIdNUoHi01goCv7XrOXgScfgoxe31c2+tZ3JR2Avcz2qL1OoSD6M04AD+h338IN/V9Eg+nX46Am49o3Y5rPXaEd9mD+ATFdjyLmMw+G95lOQK+JnBz3iso2SECzi0/WDfiO9dwvaVBdvkZmPeRIiL6TT4NvKeF+yR8I2SRZ301zq2ZMHUhHY0EYLQd9pa8oAEZE3hl2VyLDL9dJffoqHPOIC5kh5Ad3xkKzJ5Xy9Fo4NBAqFNbm3Y3sgPrbPDsMQKtf/gtl/MlnBvp6fvDZ/u+4ptR55ktT37yArK/MGYiodeU2cavpoNyHx+b4wZULST9b3VxXKXfH8adPwfx9AO3qKD6cOjrs/xPPsNezvI9nMbDeG1Ts16F2pHQ5/WoG4p+BrbmXAT6/xdMJkjhGEq116oybXYK4/ZeFYzrdI3ZjbOa2xjtAwYfgRO/JOakyElkqRBsl9xRqEMZABtAtGqLSn4bAv7gL+EVe7/dcPFP4eKXCjAygX1BQcI5RNNiwCimsdiAkxMe0PY/gYd7m99OBDQREMXD/INMg3IUAR2f1Xu+hACNV7W/jyEgw3K2nUYA0ctIyLxpfh7TcfeQvtMeRKPyCR2LqxCTVkIA9DG9/gXEVHsaMcNsRYDS8/puE4jGZ1zrMIBolrbj9CGT+sx1iPbK3v2kjglzXo4O1kfIO8uP4Zv1blpkgQ7zaghYOkPz3vyAiv5G9wGPNnkPCwKIypErPgCp0UsbhXYtE0jM/VQWUVHM7dRdck7MP1WPnK8vdOTisMhcNWaO8H5lJIamWauVR6srXFvm1PzPOnEnCczN4ffFOrn3IdEKw+TVtuv02iKTtO1qd+siY/wlLTvzkQc0fc30La5FqroON4mV5je7Fg7yjpBV5GNh3plG5T79/3FES/MePEeXmb0WaXu/S4XVWHjWPuAyN3CRcS5zIxdwkGDm7IdwrVM/eS1zzDE0QCFaC0+ceR/wgT+FCwXwY8dYEvNUJEYcQ3bwllDS/CUsqe8kTrq3DtksVPIjxfG4Gm46BfvSNJxWcfPJK8DflPzeD3z6/fIuVe/4fjj3dQJMT+CMzc/ihINGTmhO4nvwKKdV+r+BniO4KcscqS1re5l57bw+dzeyWRpFzI179RojSf04HoH2IgJU/hDR4OzBI1KNTPMUApzsOSfwbPHH9F4Glmy9msDN6s+Euj+vffc3CCA7rM8/om1+EPFj+QNtr88i/ktbEEBnAPAoro3aGda/PcCWwti0cd0df2txXHTiZJ+zYsq3ed/CuUUrTi2iXNvMViwCC/WYUZ6fWkUdpMdTDY4W/b0b4XEp4+OwnSkI/4Vxb1i49RXPAaTvOIw4xZnJ4Ybw2xCwMqW0Up1PO1JKtxWuvS2ltFGd6SaT8y2YUJpAhNZ/RXY+P52co2cEIRTbhvCz/DLiNAiyqP0u8K+QxWiQwOGTZdlNyMJldf8NhEfjx5EF/lcR59IBmihaH/M3GUEcshv2b7jOHGbXIE5/4NrDjdqOC9sZbwaKOiX24U7KdkwiY2VSx0YMYHgQ4SRZhQiKL0H8Py7o/9+LaA5WI3P2MW3XTwE/q+dnwCv8AJe/9Vf4qvf2cvm1cPGL4MRZeNNr4NI3weG3iiNqVTkN+98Ez74A73gZvv4L4dT3wudehreNwzd9Hew+A1/4KrztnXD5rcI5U6/sBl64AK8bge++AF/wxXDsi+HkK/DVXwt7DsLbX4IvPQ27roddn4af/Hb455+QeVWrvAH49whQfL6VvtkE3/UMfP83wVM/Ak/9DdzaAx/6KhHsAGyDd3wcfuFGOPcv5Fm5Mgn8C8QDea+AheyL4PIXwmuug1f/Czy3E74vwWteAxcu6T1eAxd+Hf7qr+GODC5fhtddhtdmkN4Ix47AxTF4/U740j2QHRKwVVZifjCr3zGE78f8a87j/D+v0bFhGqCj+v87cE3SaxGH5tfp+acQjc03I8DmrXr91+hvf6O/vxcBq9frmN+NOO+/V5vp9bh57su1rgcRh/BRfYcYAJS0blYuSjPztdrf36x1PQL8SpKgD9NefQbhE/o3CLcQBG6cspJlWVdxTQq8Vn3IOrgmTYNDr3BvM9EtS873Y2skBJmqnFUbU57vy7TtN5bc+0hK6c362fx/JpF1d8q8bzNe5ht9zdDO1pleF0CdpvMu4XP0d6qYD8PvQ7hPhpkGTSs0iqt0DRg9h6v3O5Fd0HZkF78dzYGEmpDw8MmlyM7ulvDsmAcsl1cs7BQex1W4h3FH55bMULi2oMq81cTuKTpjm0knqpavWpMYrpUzzUclw3gYK92hXa2Nh7XPzXejGwG8Q9qnA4gD8jAi0EYQYTSCmwg+i6c8OI7s+BOiJbJ+ME2Q5VuKpqNoTu3Tukwiwmo7AsIuAMufgtU1ND8pwXASp+g4r/qWwM4Pwu0JujfCLT8Jx7s9LUbluz+CexN01znWJziQ4A8bnFc5dsKSHhj5JXhsI9xi3/8R3BvrZd/dCJc+CXvK3u9XIf06XB6Ei98Ho2+Bs98I6V/BuVvh0Z+CIz8If9cJx6+Dy9fB5a+D018GF78Kjl0HF98Ml94Ml75UQNPlt8Cpr4CXvw6OXAfnr4PLX1Gu+TmNaE8uIBsmy41lebksI/ot+nktvqEZw7WFm3FtyZCOl2d1bDwDXNDftiDmr+U69l5FtCMW5XQB1wAnRCvThThGGx3Aer2n+ao9hpjrkq5/D+K0Aetwh+klSIZ701J9Uv9fj2woJ/XdJwpzcEWd+Wlrkc27wQbzuZt8wMBMZJe3dTz6AsU13cy9ieBHiWvUk/5+S6Geke+qaLWJVCqD032Hab3/fC/SM7jYm2PhVePoGgZe9KUZxEGNOYBW8gKFAbhXD1P153wedGEwB8qDYVCaEIq24lqZg+v9PhDqZw6excispicweeBiE6qp66n2KzKn1CnV5Uo4KPfxiUELWxFtYBG0Duhi/nLos1OI9ucAAm7MIXhMhdefqTD6NO44fUk/n9RjD2oyIJ+cc5C8M3wnwrsyEJ5xRP//c63DS3rNuofg80VQ8Cn4zFJ4sE7bmJA0ENyPCHVrG9uplo8JSacxrGa1vmj60vrnkk0Wnl0VgVMQHNFNYAAYKDN7fQ4u/rIAkxdwTUp0Sp7UfrOoPvMDmkR8ev4Kj3CyKK3TKvhXIRqcD1MeVWZ+P+bvcxxhcL4FAcZbFRRsRgCS+c/s0e+NINGcmJ8CPqbn7kZARa/+TXh6HXPEH9Lr3oNrc1/BIxlNKNv7HkJC6bsRk76ZCLciwC3p+P0TrePLYf0z4kVbN44im7m9YT3bjJpyQ7/1EvyBQv+aI7yBjpYiosinpJl2YAeeW67oRtHQpQTfWNuanEuxQTXvj22q+4q/zcsaOctCe04zv+K73Xlt1GnU39KD1GpTm4DDhUFVlck3DLSa1AR2bYPB3TAPWIP+6KxxX6tX3QzGdZ5bM/y9wbXFiLHFhXtd8T5khIi7wnvvUcG3V//eV7jOgPWdKqzMGXRChcSTutD36zmP4hqdk8iOeBRxHD5lCyEOzlfj/kQW/WWCwEzfpqmL/mYrEOA0pPe3oIfhfbAiqSPwX8PWt0hdV7e6Buh7/JkKrYofU9XhIe69+n93Afz0h/ceLnlOLuquqUNAVkqQnoFP9IiWzTYvMUT9KA5MEq6hsWiqy7gz80XcCdkA05O4f9dWRONbjPSKh0XhGaHhae2jAwgQMk3OOe1D06KsRgDPPbgP1yQein8SZ2FOiLbmKZytOiFmxsPhGRbybs+5DgHq53HTmfkgXQR2h/4w/6HjuH+SAXxjsLLNZq+2y61hfX2uMNcMBBzTsTqMU340yr1opq6aCagLc7oS2MEMbuC0/ku1HoPan+b/ZpuECh1NkDfbTS7o/4tL3s82xvO64ZyNhXfaNNoz1HG5rOFXwoE7NOcGBgVwg4fXGqdCTliUTKQFqw1jmklMdaFZhWivVtECeCHvKN2PONFa+y9ojoo6i6G9j4GKIwgYGcYdwbtxbpuYkblPBZJtXrbg4eBLdSG/Q5+zVhf0MwiYSeT5YJ7U3w2IrcV5QvarYJpAIsse1nqfQrhSlpAHFKOoJkef/YIKqt6fgiM9YmYzwbKbKTiJ6nvYunWYwq49pcQgDByGyf/igK63BPz0kjdXF7VvObNAE+tYT4Lep2D1V2noNB6qbIAkaXvfiUdrWcqLVdruOxDQZL8fR8w8e8k7EL+Kg9IIej5DbW6hs3rdQTyc/iSioTMT1CcR89NNuCZqs9ZjMW4ev4Boah5DgIpprE7oOLD5aabWrfqsozrG9un5+7SNjuLh8x36zv+MRL89hCfbfRZPo3IMYYo+pGN0uZ67VO+xqdBHp3BzbgQuQzqeV4U5WRXIgfPi2NxtdUM35fQ/1EhCjYCZY9pe67WPP0AANRQ2CPr+p3ANWC8L2LVgNhbgadFoz2A9bBe5oDPL1lg0LQLOwE4tcFOJRJnv+s9Qf22lxfB0XIvUgYCXvbTAHRTuEU1qD6pAnjH7+hy0n/HZmEZliy7wK3RBWlU433JPRfqCm1SoLEec3FeR19Llcu3p79t1UTxFnhDP+FI2IbmTbGdtwvZs+P9zKnyOq6CytAP363td0PcwcLILASu9KhBfQgBY3Q0PTuCaMxno+x5D6CDuJ5hq7dgJ65+Ewyk/J2/9AVjxvNQnblYsp9gdCOjoLbR7sykFzAG1DzELXRf6wsxals39GJ7S4gSumTmLgJI1uGbohH7/HPl8XgZmLuKpLewwoGL/W1qLCJAuIRqWndoGz+AJLye1n8y/p1f71PwV/wIBLKf1MA1a0jZLVOdas7xvjyAmK+MfS/p+9yEm2GW6ttyL+7st0uv2AucLa0FCTGndet77gkDfjIB3s2h0a/seREDYaqhLEGvuGWM6N2y96mMGNutBdjT0acQ171UaJh1328n7S9r5psEt8qzZ2LxT59IQC3njPUcL87z4VOAakgUfEq8TIy6gUSMyY+zWNGGSbOacWRwnxnw7iQjvRU1M9rjzNqLFKdnFCwvU01oHU1kv2DGE8/TY4neHCpPl2paHC+NrrNh+eAj5GJ6LKDoe94fPq4Ig60B2yWZWWaOC9/N4RNB9OOfTfm3Tu/UZa1TY7kd2nIf1PhZefAEBWFFwvqx9Yz4sdxfGsJmHo8ZrrOR3Y69ehwONiUpbCYP08N9Vg5gxREs2sF3OjyHOW8PYO4D7vFURvzaxfvVrG34ONXfpbx/QPoisyyO4f419dz60rZEgHtff9uHRWmfDb8YhZPeJn8+Sd3oe1c8xQaqB1eX67CEEcBnoOo+kkNimbWimENOQnNLrN2mduvXvHWE89tf4fETPtXHcpfdfDdyk54zreO3TdpzEQe2dev3D+v+95P3i/lD79EV9jzEEwCzCNWZVawXV2p2HEW3SOloM5mhy7CzG87ZtKKlP9BE1k95A+H+Mco1Qv/bbusL3lRD3+V4Lm26juVqY51kwGDPxFdMxYRDOGHKmCZNkM+fM0XvfijO8nkX8S/qL7REnsf6fSvq+Je6gwoJlIGoYMalsWojjSOtnqRkit82kLrB7CaRrOBtxJSEnVFHhmw+dpaYw5+AjCLDZjzidTuDJKI359zTue7JP77ciLPQGPm7Xuu3DtUUncZK+Y4jafR1wKoyPVYhpxBJpdpMHasOh/+z7mN7DomcSAmwMoLhZSkxaY8mZnSN/lJkw+pOzO/eS3ylHp1uLhmpWG2l8Ryu0HYZVmBk7/i2I5iayLhvnj2lnDiEmwnN6/QU8Cu8yYqp6NpyfqPbtif9HbdA57as9+kwjPjTQtTnU2QDFQdw8Zs7WI8BtlCcWLR6WjsXoGSKBrpmtd+Am27VhvJ0s3GtPGAMW4boo1MuOi4X/zxAyuiOAzBK2mgbHgNe6sH7U1O5QzVXWlNlL61/PR7Rf32mbziMjLa7yEQ3XNApySYgGca9+twgJdLD3KwVNC/GYi0V5zk1edepxVYTET6MNGpokmzlnHurdqwJyqwpCAyP9qGknnJtq3COmvxikRTAXFth9ODXArOTkmWIbDVEgBNTvV+H0/BEYdYa2sHDhelFIjyHArxfxxTiHRNh8GiemW6SC7pmw4H4eAQcjKpyXFu47hO/wLdP7n+B+KJcQ7cJq/WsCz3wzthF22uG9YshuZ+GZ0Sm5T59v/FBi5pQorrHkQm4SD9k1n58OYOysAL8uPMx6kV7zKAKYuwjmadzEWss8YlGdHXi0XQdOInhAjwhazlLtj5Nwkj7L1L40CPWDuMP0WfKMzmX3KwNEF3B6BMuHZc/cgvA/GRD+rI4B+/90eM4F3Ew6ioCTrWjm8LI1irwZzJz1i9FFtyNawq3a5qYJygEH3OF+ER4EYaauCmmf1iWaeyr/I6SfH8O1Qod03PznFudyMSijLBrLHJErGpvCu4yVnL9N57H579SKRizT+BQ3xaM6r3dTvXm+Itww5kpwLRgkiAvABWuLnOP2aGiSbOacOaqrCcshXWx78OSptvvOaThq3CeGubecT0ef+7AubMdo0dF6FvtxZ8kiGXN45TRnQQgswWkJkrbLQ2HR30A+X9sZ3HfGhPC6wr1ts9GvAsh2v92FdrQdu6VFMK2B7bTNR+WkCutTKhAndQwMIeCjX5/ZG+rdkFdK38mjsgT4DCTJ3RXNhGtxv6KDuLNsz6dlDPTjDsWmZdxFnp7CtG0mhKtSAhX7Cc/P1asC65y2xcu4OesyAkQvIZqeo+Sdnncijreb9HPCo7zO6PnG2WOgqQzs2Pc79T2f0mvO6TywBKEXtH/s8/PaJmcRR+K9eu4e/f45JP+W/W8g8jrqpPshBHPo5zsJm9swXg0w1tKS2LgZDM8vlVtUA4315MPXK9odrdMKbZtj+nkqa02Rr+weHWsG4peT98kr9bXBteDLyLsFNKwTTW6Kbd7XaON5lyG5Os3FojzfL1lD+F2xIfFz3T/z0U5h4epHdpC7gwB9GXfmXIaCD13gH8L9VUz49lADnDBF7qBw/VK99jyicr9lrttK6/HX1NZ6mUq6KqIuLNxmAuhBwNABPMv4izhfjKm+X9Y++QcViEcQjY9pSEzDYoJ+AAFRZnp6Do84O4KAmkdxv5R4PKfC2ThtVuH+OmMIE/km/Ww5uQZLFuxuyne7R4Cud8GyCzCa8toDc059AA/rPYcAtAGg7whs1TxfZ3CH7kOIhrAHB589oU0q4cBhvN+iAr+YtPdRve957ecXEMD3SdwXxwDNBcQ/6ByeysLSXBiPjpnJTLt2DtGMbCXvA2TO0BbKbuBnHE8Suh8BrUf13AnyWdOf1Xud0fExoOecQMDhLwIfRQDlKzofLfy8QntQZ/5W5qx+Xo4n3j2l43EVhbyRoS8i507Z3Eh46pd+4EdwrYvdu6EGWPv2UGivgWauK5Fb/dp2m8M72L1qpjeqc88pk75SOwH2kdAntmGtmeJq3mTfHCzKCzLairx3+hUVEj+DbdDQnNXMObNcxwTcHiZqB7Lj7EeiiEzorcLNDdGRLwqcuJh2l7xn3GFNhXzsftwkMWeaIF38xmvNNdyhtEw9Plz4/wgeLWcai4t6DxPUR/T/k7iGIWlfLMPDks+iUWbA+3F/kFPAX+K+InfosydwNt7i8UlE+2KaPnM4Xk8+W/0YhWzVQfANAXvvkOcakOkDVv007DsAJ37fw8m7EY1Vv46tHXqPJSq81mO7XOj/dTHLbSNPQGoEo4dxh+8K95E+x8Kh9+LRbnv1OjNH9uAh3BMIaDHtyhEEVFr28zOIeemcjkPLtG7t1YP7/Zhjc5m2J/5vTsxRC2T/b8Q1SMaLY3Wx5xjA2qXv9Av6nuYHdAviWPwJXCO7X9u3C/fhqhUqHs1Xt+PuDWYKHdTvH9C67aWGOSncJ5p5liBgcxSnUlhMa8Albub2ItQBRfA1JTlEwZw9xXsUSV+byatYK1m1aTsNVMUk1/PK6pyr53xXYL4PrrCQ+Bl+94YmyWbOmeW+MYZVs8k/TJ5nwxiFLfJnFNnB2kJTluG7jzwXR047hGtBhptdCErarCr57Cy1URWoabF9+0u+S3hy27tV2HaTp2JYizPlWsj1K2FBN42NOfqe1GtewdNdjKiAfBXR2J2ivsPrTQgQMR+X/fqsDaEfD1Md1t9ri+5PSzLSdJfUtw8Y3gh/twf2JwdJthvej2gd+xRIDOChydv13kNPwer/KNdt0XO69N0GtX73qJB/EAddNrbMjPaoCsjHEC3KNhW6Ywgbs5mMTuNRcCuQcO3z4buYb+uS3nMnrsX7iAKRHVgSWk9DEh2az4T+jeYvu/9ZnGzSosde1Xs/i5tUjFizT9vzKO7YfgjXUN2pc7dT28vmX4W2gnwkZg4I4QDftJhmyjLG8sf0/JsoSaBdGC+dCFiNDsgDus5MaSNIPqqyQ+dUsa6V57V476p1bhrrSUyEXC+ped1NMTWcsVlA2eDnvQIL4SAfEj9fIfktC9kZeO6CNHkVJrUt2qbafYR81FIqXNODhh43s1BRXzu0BAcyLbGoMgcASBeg4Wm2b3/J98YXZEDxBfJA8U9xZ+ODiMbnTxFH6DEEfJ5Fkkpa9M3nEL4U0wKYhucC4hT9CRV+xeiaeFh4tfm4mG/Iw9oWBtSOUa3Z2wQ8vwfOJ2VL/rdw8kVY+yI89vVKahjesVf7/yDBgRQPjTcz3eHfhIO7BJQtQ0DSEOL4GrVlO/W9o7DuxxmXt+G77neHMWxml6VhHlxCEheDaDMiMPn78PkITnOwSPvUgIuZoiLHTy2nZmt7y65uflhGavcHiDbsIAJw9iJmUTNZm+ntOdw0eRABQesQE85Wvf/t5H2tirQVXeF7A0LP6/Pup8SUVZyHFExg+l1Z6omukvkSo/iapgIpzjU8hD+npbK6tDiPc8EK5POANfR7q3PfmvnEmOKmWN/X2mxeLS7z9uCFeOCId87MPDh5lE3wWmybtvuYSQrzhtquZs6ZxbYxX5VFKtCMr2NLXERqLDRRjTsV23pRO7RCF+qnaZI7iFkGQFrHKfUPTt9vZq6K8y3OF7QUN23Z+etUeBnJ3YuUp1bZjGg/zP9iGwJYLgLr9TwT8EfwaBoz1VjahAiGTuK8LCaIj+MAow/RAo2Tz481BBz5bXjZgE+CdAku7xIwvRjYo/cwyoB9oT6mvjc/nX4EqO1DosK6T3g0ndWrK4xF80O5iDut9iDaCPPReZp8RJPxVZkmbgXuQGt0AGaSM5CyDjdDHsA5dUzL9jBOGvh53HxmjtEXqB3hFY/zCPgZRADHXuBn9PvP4clDDegdwpmWx4H/i7M2H9R6mc9TzlRSMp9iOofF2ueb9dmlfjSUpxlZrM+2cPhBGqwTCIDeoGuQ9euo9lEjx/qalBy43JlyYAkO2oumpgoAn8Y6UwVAmeKmOPTh2FTvMWPr53w+fCEeeJTKjAKNOs/rsYlDcI4sCJIxPAy3VJgWBueC8qqfRtsknSwP4ZEzfYTsyTUWtmKiySlRv4d7FLVDRnJ2WBfCerl66gIgysFuZzMLAyVOmk1ccyuyO7e0FQdxk8KwClMzGRqPzGK9dhAJXU7aBkZsdyyMYWujvYhfzCQCfE4h5pCl+kzT0pi/z5ieP1Gorzm/PoOzGL+sYGFM++Fx4J9wbdQqBKBdhzk5Q8c5OBnBT4K0E46+1bPGb1eQMKxttB7RRCQV8kZotwfPS7X+p+DwB+T6f8azfI8rmHgOASGPIyDv3XqPx7QNJxCTz03kmYONB+lB4GJoDwMtp/S623HnZCOa3K/zZDHuY2UmlbMI6Piwnm8ansPathbNdwk3T0VQZBFlZv4awjVBY3j6DEtxMYEAnyf096cRwPERnTv78SgvMwnGqM5idGIvHml5BNEYWSLcWj5vQ2EsRe3OKgrJfRvIhR6ajHqqsc73h3fYXrLG2DrV8uabkvD98FtL6TIaPMfAy16mSPVBi3xrsyZf5rsCC/UIA3FOVXOEVBa4P1Ix83bRT6OiFSKYikqEiKlB++s8v3NBDEz198F5OXrxHb6ZOYz+vxmgEHl+Wg5vr9Ge9+jiew5hKa7nPFkPtJaZnhpSw1PtR2ARXUM17tmNgsgw1sxPwsbORcQZ2fJ/jYfr340zBt+pQvWECsMDCKhZj5MHfg6P6jIBO4yYgLbpNZv03mv1vL5CnQdUSB9GwMmTOi6eVuF1SoWwaTom8HB348r56HI4XgQ+djwpwOQ6fffnEQ1EtwrsE/qMcyooTyHgaztKIPd22PS4AIZTQUgeRADNCJ7JPuk5O7UN79D3HtVx+RLiN2Pg81Z97k4EfJnJK4bO23WWluIcAmqXI865Bk5v1Xf8DG5ujKato9pf5pcTHZstR9dlBGSaNvCAvttpnPTurNZhN57U1IgQ1+h9N+Bmpm695oNhLEYH2SEdK6OURGXh4dsTOkauK8z5Xpwxfoe29y24VqpiAsOBkWl7zefIzKC1Is5iuHnVteG8VYjmzvilylIWzXiACSVrJL5+TknbxAxsKuf7mPcKzJEgtUnQKsdCJTP6HNfVJk9pJBrB/8QEWIng7C15D9tVDlAuHCPDZ/9MtmWLbdCvi/CJ0BabVHDcF97JIhxazeAdwztnJPQyLJxddZ5ZCwBV8b3Ywt/EWDHHzwpFPk64VwQSgyZ49P+x0J+HVTicxpOXvoBqYnDCwFu0b2x3fxl4n55zSn97Ffc5sTxdFl59DgEYxgg8osL1IrC15B1NCzuKaD02IeDMUimsR/xKKhwvkAvdP3Y9nD0F52qBn2fgzA/ITnYtArSeRgDHCcR3Z1DreTuisXgkzJOTKSUmBAxtwYHlqTAubNffD3nOJa3vBW03yz5+i/bpXgR0GC/LCgQ0FZMeG8HlB7T+ZxHAc1r7YkI/b8PzcZk2x3x+zHRUzNVl51heryUIODqq/deJmNsuab+aFmpQPx/VfviAfv4LXOtibbEJ0QIZ47exitv8/iBwTxPCeJOONQPdBpaWFPrA1jmbB10IsH23zVX92xfnd51nrw5ra9W1hTVgVXivOXH+DXPXoueiH09fo3WmSdlqYG/eCY2brvt8V2COOj7SoLfkIwG5kPgFgW7DgjdWY5LZYO/G7cldJb/H7ypRQ0GAFAVyBQzSYgLSFt7NHG2HgLX63T1h0dpKtVCfqv05OvRN+11okEaFGgAIZyUuhvA2ZKLWZ5ofhyU1NZNJ0ek3qZDrouAsrYLjFvKOl6YlMy2KaSTvxkkJj6tgNZ6WYwhoSiqI3huE7UVEa2LpMSxNwkkVoGXA0Hxt7iRv7jyHh9SfRABCkVukC7j0YbgQwc4kXF4LF+6E8R8QQLEV0SZ2I4CjB0+8aQDR6mFJRs2EcR7J/5Vw0sUh8uDnQWvrIPBjYtUn8JDyz+LMxAYWzRfrQWBHjXG1BwFOx/DQd/M/OobwA13WttqNkxwa389B8olLzV9ob+G7x/X7M9q/S7TdViMgqxNxfL8A/A7OyzSgfWwgYZW2+5LC2LX1xQB9r82PJufgGK6dqqnVoKANCWvbu/EIrOiDVcukVjkPj0gt1d5Abb+fOZAZRq5ZxedDcEKegbU7hssvaPeLea/AHHR6VeLLaQq2KyIkHt/9lybkJO9LVKY9qqQJKJwfoxtmLI+L1sF2aRZNsV4F8oAKIjOnGFtqZTcdPrcMYqhW4U550uK+M7U0Z7UAUA8F/6VmFn1cJW9hvdYWZTxG53CNxV7yPiZlrKwDiLnEIpE6g5BLuLbF2s/8Rk7qswwwWILNUwhH0wE8PHqRnVdoi4pjJe7rtiGccxbR0JzTd7F8T4MIwLsIpNsV8OyBC8vhxI3up3KakMAUz1m2EzENTiKA4lZd1CMr7k04iHkc+NgmA0Gp4tNwAk80ukrf0/xpiik4LNz9CJ6j6wDCfbMW92FKCGj8POIHF5mMzWF5PQKSzNRo5q2j2jYn8LQSZoY6SHVOr4RrhUzLdlLb7pLeZ0LraEDwFLBE67QO5ziykP/HcXPXGJ4iYRLPxRY3m4txM+5a8trs7hrrWvQXWkftPFVVZicdP0brUMkV14R8sX4fCHXorjFX5wX8tCIjZ+B+RReDBUNsmKvnfFdgDjp2xgYcbma6KvKDBeHSW+N3E9Sl/k+4hsEW4VUqjCaDEK5yEtRzc75F5B3++nFyPNtV1kteOiMTt1CHKWdxxzlHSqkTqA2Ayvy5+qmvch9rNBbxHfUHEK3NQfLmsjvwJJrmf2Ksy0/iBHlDyG79ORV8BwjEkiroTDCaJsjIDf9UBfgjKjD/icD4XBgXBsrNF8lCvn8B11qdRUxNa7U9J7Re2/S6sT+Clz4Pl39OhPZyBQUT+pxJRINT6SO9z2at52PkM3HvUeEf/aUe0PZIz8OulAcz92qdH8R3w+/HI+Xu0fv06fg+SMhdVug/074ZYFqi72vanWNUZ1WPoCWyZh/V/19CwJkl+FyNp52IXD5FUGTHA9p2z1gbIg7tp/X/v9IxNKHv9UFtP+tza/Nh/d7GYldhzJp5cK/e6zo8PLwSal5or6EwphfhAKq70KbdJfN2q973/mbWlTAeYoLg7sL3xlpd1DZNmaZihuVAbpNVWAenpRUnn1h6weRCTKkNfqZ6T5uoV4x9cxrv2l0ctPjurUgRH5M3dobfbfCb/0YfojWo4tTQifcknnhxBN9l2r1ToY4z7pNF3o49pZ0LJSbHkvtXheWSV7eXZmAOvx9poh65VA/a3sdUkCxTITek7WzO88OID8uewrWWZHYLHsX1vF77BKKBsDQGCY9AOoD46hgQWKf1mCBvzqqAcfJmOUuFMYwAnhV4KHi3fnce+ECCjgFIQ3DgnWKKMjPQ01rnXh1Xm8NcXqXP2IMTzg3pe67T7ydVkA8gAMQ0NWfeD2d/TfyB1ukxhPiRHAPu0HcwzULCM7VbuoNV+n1PoS0ews1CZYEMZibervd8FTdlXYdrhVI4DBg9SF7ztR3Rell6CiOvvKBz0TRBq3DQbE7eAwjAPAP8tr5XQsDZPQjAMa3T7bgZxjR8YwhgHCyM/YovnY676PdX6henY/oU6q8Vzq34EtW4znxgrJ+2NzG3+grXWjueQkzJFlm5CqfPqARrzPf6XhhrZimoaMCZIQ0/Qbs+3+9aqdN8V2AOOnVW0DbBvMECQrNz0J62M488OPchtvK6QAEPx7Rrh1X4DSPOtgcQzcDHdAF7XBe8o/X6kFkAP+HeMapmKia1Lmqr3qsAECX+P9TR/hDydeG7LFP7my+CjdOe8E47VKAdVoE+SgA6WrcLVJsGupHd8bPan0sRrcO79Dn34Q6xu3En2s9onUwY3YkAkAPAx4rvo2NkBw6gd+qYuV8Fipk0bKeegIM/BC9sg3MDMm4eR8DOIGJmO66AYJPWa5M+q/cr4Pn/DZ/bCKO/r+lUfhNu+qiAgWHE/LUJNzH2670/Duz5Mzj3s9Im27WetmkwIGR+WRtwbche3NHY2IcntF+2qABep8+um3dO+2Kv1tU0OMf0s/n+FI+X8E3KJ3CgY1F8JxFgexo3g53Dc+lNkM97NYikITFtlJnrLGnppPb3aQSsdhfmyTAlgAPXAq3T/jYzmmkFixqdQQQc79cxlvPd0bocpHrjUeSqOtrsnA9rm82fu7X/N4VzxsK9F5zM0PqX+SpNmU9sIR/zXoEZ6LCa4YmFCTEraDs8f87ZKpkC0+gMPTPa3g3Rl4ZXN3nPVSooj6qAsp3nEV2Un8ZzAM36jom8RsGE7wqtx3laBLxhkY7qfvNRKQNAOf8fnLW6nu+WgcnIgBtzcRktgPFFWZ1u0XOGyTu0rwMu1XjeJO70uhrnXDGNzaj+thlxcD6u9beorX2Ib4ppQPYU5uq9KiTtfoPAgdAWp/AQ+SEESF38Zdi7By78Ow9LP4eY3v4QZ4aeUEDwTHjX/g0CqgafgK1LBGj1JOhN8vsmFegbyGupHtB371gLhxLcX2irmv4OBK1gENhmGrBcV6V9XmeMvYBrIp4G/hhhoTZ/oeJxAcnNtQsPmTeSRNPSmAnsIgJGn9H//wDR6o0iQM1A4SodG0ZwaWHxt+t82g/8HSXaTH2Hw5SkdyDPiH0TrmWxMWu+PjFoY5/WLfou9mqdzc/J6mnzs7Mw1ivjuoX5bo7PK9Bccfp9mm95OcX1sItyraOtjQsiEKjl95rvCkyzUyLSrhliGDpwtph25yMkPibe6wiTfsYjsArPHZrJwV6rD5HomztxP4LTeLLG1dTI0N1gMTKNgjlHm1+ORc6NkV8IK07UKoz2IaG6U4p2C9d1hjFjQqMIgCraHpy5eLDOfY/gWhNzGB4OfVbqGxHaxz53BKG+v8Y470I0KEcQjc7q8CyL1LNzl+P+KRZN9GxoXyOqi9qrc8Dj4blHVVj3I7v20+T9awb/HM5+Hk79SxH6R8lnFz+n1zytz9ukwv3uyvtBx9th03m5/y3ARIKBJO25GA8736FjwfyM9gE9QzCZ8sCokhKjwdiPPnVm3jJSzaY2VUFIn0eAzFJtUzNxlQGfM4jZ6pxea6H2ZqI0p+iEUxcYKDqp/59DgMgR8tqV1eQpEsxk2aGAwAjyLO+ZmTPN18x8esr85e7XsbkJB3qm8SxGpxpdwEN4QEX0URzRw/J29YVnmyN/Tc1tnf4YCO1QMxXPlXSEeV90Zu5ngfgutfxO812BGeqYuiGGc1SH6OQ660gYpsY02kJ7mv23yLDa0MdkBvrwVgrOg3jKib266B5DVPKTKoS2AJ9GtA2WMmEoHJHjowcHQ42chWPet7grND+HVhdGixo0IWecTWUAKKacGNaFuiyKxARL5DKp+Gnp54GS9xrF/RKO6TtOaJuaRiJynUQTmyX+tGi8sdBfg+EZ1qfdOCtzBJzrFEDswLUfCddIvQvRNOzW3w7p7wPAkrfDpkFI74Pz3w2/qELsnN7rQRXYe/X6ZxFH5mGUlC62yV/B2pUCfoaAE0fhUKGNN2l9t2gbW7qLoQNwKUF6rwB26+NmgMsqPJWGgVYD341ILm2e7tH+s3xdp7QdnqPc3+ciolE1zfFHyHP8xASnq/BUJhdCmxqoMhbvIvdQjPw6EsZlJwKuzKwZtTI2L4zXq8wnrgN3tn+6URtr2+wN47vou2iJU8e0HU7hJsu4IahsdmxM11kvbL25l3wqnisSJISxZgC1v9COA62sgQvlmPcKzFDH1A0xnOO62MI354OBGfI/wqNtzCnRIoNKyRGn+SwTkOv1eauRcOhNeHTRYfJgZrMK7nO64H8KCdtdHYSqLUB9Ux0TNEFvwBRAUFhIzKnQPucAEO7/Y8BwJ5SmPxlsoo2PFN5rQgXCfmT3vRfxV9mE+MpEn4rNiI+GEROaCejpUPex8KwKcC2MzSg8irxT+4Cb9H/LeN2Hm1asXw0M9/0QPP80nL1bxoGlpXgA96EZCp9P6HusRrVKFCkBoP/P5F6f+VbYvlWThyZpr03h+Tkg+XOwKjlb9GFaYBDX8b26lXFZGBsGRvcj5H6WZX0/7qAcgY85pS/S645rm+wIbWTh7AacLoXjWLjXcgT4nMQ3CaZB3YMzeu/VNtmpz7oHJ5IcQLS8MVjCxp2lFClu9FYhGq5ufcZW8hudIfKA7xgCWM0JOZ5nKUZeQMDdBR1LlpDXfJyWIybUU7hZd5Xedz++CTus7/ssYuozc/2DCBjqLjnmNcHnDKzhVXPiSjgyrfwVW7Is60AW/xuzLDPwc9cCqJMl73tyDh/9LkRwTad8GfCTSO6f+N236OfPhO+/AJn84ymlkSbaxRwjzWQxrj+dRHaqHwbeor/9NSJ8RrIs60wpjde451LgLmQB+nLgH5HF6x+Bb8Q1LF16ybgeG7Xe4yX3NC1eB3BbrWcXrjGfsm5gWUppZYPzzYehA/hd4Pf0pxEEBN2YUprUMd0P3Kh/vx/4S7u//t6TUrqtzrMGgZGU0rIsy0zL9BfaJjcBNyOL9zMIOd/b9Jpleou/B74QeD3wUeDrgR9CBMBvINqOtyACYhwRgtbOnfpOXw38hxrt3QP8V0RIvQV4ByKUvxL4IgQY/6XW+02If83HDsH7fgXOPCoA+C+Ab0XC4XcgGpr/F/g2ZB7+uI6luF5YRNI9wJolsPXn4W0fgjPfDl91o7A/b/9z+OzL8C8RMPG1wJ+llO7Ruvf9MfzG78n3Vm6jpP/12cbAPZJS2phl2WGEIbulNSvLsn5k/K7MsqxP33s38F3aP69BhPFXad+Z384e/f9D2i9/CLwRmSsHgS/V/y/qoy7pvV6PCPav0O9IKb0uy7K1wPchYPiyjUMdZ3+NmCB/DPgm4H8C36zPeguSC+0V4EsQp/dbwvsZMFij4+mulNIa/W0F8PM6Tk37dXOtNUjH8hodi10ppZsLfdKv4/+t+u4/rP9vQIDvc4jv1HJ9n4eR9ebX9LtvRubnZ7XOF7XNViNr5xv1unOFqnVRUlJKN7YyFhZCybJsDLghpTSp/1vy3k5gzXzL5NI6XwXgpw9AF3bLNjuvg0c7vg/ZZT00R4/9SmQSfmqa9/nXyIL5/ibO/SZEUBn3yjiyoE6ii3uT7TXtPlRh0IOAzQN4XqURZPKN63lmhjF7fqz3OM7LsTKltKyVOuj9WwVBffq8m/GUJZ9GdosGgAwk3YVoxS6nlL4h3GMMuEH/NV6USb3mg8APWHtmWTYE3KbPGtfz+pEonRu1P0f02pv1t2XIgv6PwG+owF2EmJDegJgflyAg5TSwkjyA6wH+BviPQYBZlNG/Ad6JAKiVCAC6M6X0t/reSxEw82PWFn8K/+2n4Py/hQM74XWI0L45pTSubfH7wP8BMkTgbAZ+Qa/vA34EEWy/C/wmIsBOAO/9JXhyGD66Cy5+BVxO8PpX5RkfRYD+cgT0P6dj5+nd8M53wNtDt46T0vWFfjb22zX6lZm59iCA4wa9nzEaTwIba42fLMsGtH/OAf+AgIPJLMtuAt6HgJSjeu/XIFqHn0Y2GQfsNki9/wH4WZzbJ0NAyfVajzfr+ccRwPt27aetyBw6h3M82Zz7VuC/6HW36jn9iDbpaErpB3Rc9Om4G0LmXAT13Smlu3SsDNrvOi4WA3+j/1fuY8K30FaWrPqGcJ81Jef1I5uiSTyQ4yCytr4G4S5aaXXV/vtLBGRv0TZ+vT7jl5Co1T0oSA116Wx2bbxSiradraU92o7LdE4O6eeF9c7zrXqaAZVbVaqAeVb/GZfEnNaDOon3ytoMJwnLqeiZBiMnbsIyZ+Lh0B6VXEaz1YfkybmMr6Mv1KMfahIu3oqH25vfh3ESNe1cXbin+W8047thzs/mlLmUvAnMfBP6KJDh4eayYfI+OrehjMLhOyOki+/2I8iCvxbfrS0i+D3otZuRXa/Z/vcAr+pvlvLC6hvTExhJnTExWx89qGNwGNkkGEHfrXqP1QjAknpIdvbBbTCkmdj7tS3eE+63AzdZ9Gq/Po0I6/U4QaMJ4jOIaW1TeM/tiNDbq/c1M545zVaSBP8ArDCTVzz+StoypgQphmTbuBzETTFmbjYNUc1cSdpuRsMwUBgLy/XdPotTAoxr31kai5O46eZ53BdoCE9tcUnb9zTuPG5mtPM6Rk9o/c3saX5nBjIvICagyOV1FvcHsrWiQ+v2GMHpuDC3h8K5Q4gJyjY9uflS0l7R56iUNyvUxbROS3An+3VhbJup+j6t84T+/yCwL4zdoona5kTu3a6WA+c6KqbpaSr59JzXd74rcDUcQdBV5VOawzo0PbhscQqLpfn1zIrnPvkoq6JPTg91wA5TSKRaELDmZ2K7avNLiLw3Vb49VHMSDYWFqx9Y2sK7N0yiikRPWQSFgZm7cd+bSj42FTb7yDsdjoXrV+mCbPmvoi/FScTXYlgX9X4VImvD2DD/qpyDIx6BZG16Ss/rQ0wuy0vmRXTANsfSI8jO/YQKUosgOqHC0sLyP2b3/FHYegK2Jx+3BrLv0XPv0POXIpxTlr7jQ7ivhvl/xPxS6/R3G5Njob4J0W4Y+aG1Y6++Q3+ScPhUPCZFE2J1tL40/5ITiHna+nUSAZYRLJbmZwttG2kNjGBwQO9lTuOXtd7GGWQ+MMbb87f6nG0I0HkZJ6Xch4DGpH1yEnmnz+nvOxHwdFnbdpISXyeEt+t04btVeq8I7LfjxJDvxjdmRSdlyxG2SOeBpdcwosrBOmuCpWjpq3OeMXpHp/wV2m8TuNP+Jm2T4wiYM8CUwjyKXFtGZxDfeUGmfZiF9b+DBURuWKnXfFfgSj4oEbLzWJemSagoj6KwiJw5Id8i0L2Tj84ywWO+OtNJShudkYusyT26WJ5QQXl3M++OmNN2I+YnAxsNI+xoAILw3eQWZLd9q97/ARwAmWZxsQoba5se3On/dv3tfvK5knaqADysgnYDspPfh/hxbcIJ+WKCUEvMuVMFjkWBWei37b6XhPpUzDcl/WFCypxpL+BpJY6rEP5gXDQ/C3cchslfb8IxGM9xthgBRqN6zzEEDO0tqc86lD4hfL8HzTIf+6wgRMcSDJaBHz0i+2+ysYJrbIwS4BSSr2szznxdlZ+tZP6Ypug6FcD3IADwlL7zGVxrMYBoYJKOsfPhXgZATRNm/boBd+Z9BfhfOIgyzZHRUPQgmpCdhI2BjplLVDu/bwrj5R48wnCxjsuPhf4cK7z7x3EQuRfX2KwiJGiuNTZCn/Y0GEsWDXdR50AfTlDZofU+DjwX+iSFa218VdGg2HoQ18L5lmezvN4bDUcvC0TrNe8VuFIPXFuwYBmecdNFcTe2IEMuyZvNBhGQsR83m+2bSlvrIpQDHqH/+sIzTbNTakLENRcRSFl4so2FRqG3jUBQv773XgTIjCHmGgNA/aE9zDehAsDK7qt13KkCaxOeaXu9go/ndUE/SzXJ2wRumjmGa4EeUGFqC/gSJALngArFLYjZZSD8/il91lZty6OIBqRXhesB/d8yond8FD71NJx9p+agaqKvDRDEEGpLZdGvn4uRZlHDZeOgktuJvPmxJ3w/pCBn+Ahs3QMnj8Ij7xOOoN7kvCh2/+6Svj6Oh37bODVBYRuDUkGNh3GfUyFtQM40Na/gRIWnEQ2PafZ249o4A0pP6XkncW4l40myDPCH8ESpRpdwCQfOBmzN9GVg6iSuMTTwOIxrubbr+JpAHKGjGbCKPgTXghov0yY8Ae9erVdVpGd4Zk3zV5jrtlYcAh7Wz/dpOx3TZ3wCAWEbdIy/1GgNCM8wLXJTtAhX8oFzUc25S0jNOs13Ba60A7fFzwmfzzTquQoBDmOI/8GyMKmviLDEIIzM/JSoNj/1NNsPep8tKmy2Qk3G5JivrA/ZjdZMVKrXWaoH87Go5V/UH+pi46irpJ7mI/OA3u9x8qSFSxF/g0djO1ACbG2s4mBvqQqNQzo2zIfjXEldJtBs6uSJzVapkLXopd2IVukU4rx8n95vg/bV49r2L+BakHX6e6+O1eNaNyNCPLkUPvWD4qh7U0l7V7F949qU1bjmpR9xIh/VekYzipkYY+hxB9D5FphYDR/7COxN2i4/ACs2wqi1R+zXT8KGVMg3hZt7DSSbKXAFrlF5tVCnyPZszvnDVGsPzM/mVgSYTCI+M8/pPV9AAPRy8pqXI8DO8P8Jvc5yZ5kZ8BUc9OzUNjQgsx74c/19NwFUar9arrVRZBNmyWIrWhBce2U+TveHvrAxO6Tj6s6SOWJ+cAYgLLv6dVrfteR9Dwd1XJhDfz3zV2RKP0p1+P4zuG/gIzpen9N+bkpLjfveXdXAZ6Eer6NdmioaEmm+CLelefJcD/WwEiMJbOK9HQnX/Lsk0RK9wANZlv04MuGulFDKNyCh3ZWSPGrJQMktwO4sy74Kceo8jOwCR1J16OsdSOTGR4HvBvqyLFuGRl/oPTv03I1ImOp/BP47sshbEsaN2g+d9owkUSZ/kWXZG4DfAv4V0K/nrSFEnOn5G/U+3cBAlmUjaHSE1uU7kQipJYifwdcAb8qybDsSZj6MRJz8KiJU+hAH5zdpxJM9qxMBFt36v/mYnEGoAf4FIhzfiyzeH8my7AU8OuNHgWeyLDuIRLJM6rNOI5nZfwf4AQSELUYiAE8Cv47sin8UcbS9DYms+k08IugBrXsXEmackMivC8gY/u2/kPfo1XeNpZIpO8sykkfv/CDiB/JFwM9o+4/rWLpV37lP29v8P65P1VFCkyuy7HO/CIcPuZaD34LXvAxv1GirXMTQm+HoNjGLxnt1IdFyHTqWh/T/mxAA8bNI6Pk7NBKoH/heJMLsW3XcTAI3ZFk2qM+d1PY7mGXZbiSUfC8CGr8Bidz7l9qnPwd8MQJcLBL1S4DPa9v8FhLd9UU6Jt6o/39O+w483P3bEAD73TqeflS//0Idn49mWfbPCC3GV2t/fiHwE4hW8AYEUNkcGMmybA0Chm4DRvT9urWOf6Bt/PXAr2ZZ9o2FOdKjz3k3AvrH9b67syyztv5E8vB70/gsQrRLbwC+KMuydTpGjWaiG+jIsmxc3yXTetwAvBYxu43oeRuRdeGwtn2Hvlekiigt2q+3McdFI7P6dBzdmJwCojuVRMFdtWW+0deVcOBe+gsmuRuysBRVuqYqX0awqdv5813nKbyj+QQlfbfhknddkXwXdTdim1+OmxqG8SzUu1ByN71mANECrUcdZ8NvvYhWYh+yW1yM+5OYeeY92s5Ff6LY7iZgbfe5Sc/pDPfrCfc9QN701IcsrM8jpoEj+tf8f55CFmIzkZxFFne7/9PIzv0xPZZrHU5TSG+Ba2RGEfX9ROiD9+PJGi3ibAkCmC7iGoH9yI7/GJ4o00xG9+Hh0pP6+wTwAcRkcau+01mMYDBVNDdlJqNuBNBOhnoe0/axlAcDiAbgmPaZRbmZAKitNZToso4UfU5g4NdlPBRZbvtuhfXvk/eJue+GwngaxU0/e3A/nIP2zvq5U/tpPXkn/FtQk6D+P6hj8CBubjyj1y7X7/fhvlVndQ6cBf4U12ZMarvv0nHxAp709gwCHj+OR1id17rcgjtY36T9/6w+826dN6cQTdAKvdcSqn14omPwrXr/E3gSU/ObMdLDyBU2htBbrC1ZPyokoSXfmxn5I3i6j+0IiNyEOH9vQLRaW3QNeQVxoLdNZtTwbUJAsqXuWJDrLU2kRWIeckbOS1vMdwUW8oFnE64kpFwIh9bLQl1jLiAbqIM6WRc0+KG5pLTrdVGpmDgK7xrPjWk5oo/GPl2EX9W/p7T9juoCfbfWwRwZF6mAsLDwziDEbHduwvYAYt5ZiqvdY1ivnb9FBcAuFRgvIUJ/orAYHQpjrjO810697nEcAPUhGpcT2t/DeEbt/SrYLBrHQr3PaTuYX8S7cf+Jw4jJqluvWY77XxUB3gQCNFM4LIlpjwrGl7SNDQQd1nY4jYC5Ma37Q+SdrM/q7+8J7VkEP736PhXTodazDwcTowgw3KvPb93cq8lNw/9jNcZyx1J48GMhZF6/NzPhmLa1OTonbb89Og724gCoWwXvzkK7D+p5/6DvfxAPk1+s49yA/xYEdDyD++hYGhMLcR9DCCwP6e9HETD7EvlM7lu0v81vw8xeBpCX6ve36zOjOXAzbp5br+N3kLzflWWIv0ff6e+0nif0nfbhKUpW4Yl1DciOAscK60CkDCgDQP3axmZSX44Dgfci2sMVOn7O63x4AQFan9Q6dxbut1zrd5IFuN5a2xT+z6VFYp5yRs5LW8x3BRbioYOhEo0x3/UpqV8/ngtpQBeMFXh0jzkKRmCwoJycySc0XaqT7oEa7xojkO7Wd+0Pv9nCswHnYVka+vAPEA2Ihc13IiaXg7pYWU4rW3DPoHwdoR4JJ0ZM5Hf9CdHAjOLRTOuKi2Ph72J9j7NaT0snsiMsQhUQpHV/WOv4rNbzOb12i97HnEMfU4HxEu47cU7f9wIeYm4gzBa7vdoOn0aAylO66J9ABLf1wSLcITYel7ROIzgIO4/srifxcOadeH6oy9pWpgXbrHW9F9/xr6DcOfwEok0yU4n5j3TgqRTW6j1PA9e1PFYlnL1fP3cm2+2X7YKhK1HF7WJO6kXwNqRz2HhibsHBh83vm0rG4FncOfjVMIeGtc1W42HV6/T8Pm0DC/f/GT3H+mmvjvkjiHbjpI6hUUTr80lgsz5nTK85DLyIawJtXB8Ln20tMvqGTh0Pj5a0x4e0zz6v4/hvdWwc0/HWoe97Qj8vxikIdiJg+aC2w34dMzFKMjrAr8M1j5vxTcNm8hsd21xep+/6J9oW+3UePY0DsHtRWgZEu3URpTOY77W2SXlibTNrOSMX2jHvFVhIR1io5j10vUE9zQlwkU7c68gT3Zlq3QRn30IdvLqIrQ717Ct5V4uEKQvRLzqBGoiomCnxvDqWI6tMcI8iO75LJb9ZWPfvEO+FAACAAElEQVRGvdctOMjqUaFhkS8P47mzonP2Jn12kZxwBQKWRlVQHcHDnSM3TuTaOYaAmzO66E+ooHgMTyq6DU/8mvAonnsR00LCgUbMdN+N8+EYX4xlRd+uwrBWpnBzfl2jbfNZraOZ9M6hocEI+HwSMb9YrjPr6/Vaz0kVOCcQIDZE3gyUVPgdIW/KqMyBMCbO4Jwwzc9t6E6a3T1B30uwbRVs+g5pw+p7FcBPg7UmIT435h9ipIqlfFs6bo/p5we0fT6DAIadKqAfxbWYltDzIs6+vCfMiwPAfSb0wtjfjzs6m2lyN04yeEyv/SR5wswB8hqYSG5qgOhp4HiN9ujBU0f0IRudi3husN3AnkK/bka0W+d0TmzHM8WvC8+19fGvcLOxOS/H9eWvdHyO6f1W6e978DxlhxFt2S7UsR6nf9ijc2+9ttFhWHgEf/XW0LLfuQJAXMvvPd8VWChHUcjMd30a1DXhfg1D9QavLmoddX6fV/susjtage+yzP/ATGH2ruvK3pU8mFhOeQb2Cb23scOuRsw7S/TzOV3MhhEtxX4EiHxCF/oPaD1exbVNE3qOJfncioANS875NO57sVoXylHct8Duc0dYoPcEoXUggAHzT7HxuUgFwSmtw0t47qbFeq8YCWNMyKtD++zFQ9lP6UJv/W98OyYAL+n4KAOG8TinddygQinhiSe36TsZLUBFI4JrCAwArUIAz1jom71I7rpI7mem3yPavq/iTNVmMrSooIOUmPCaOsTvpxPofjtsSr5Lrr5XE2RuYSye17bZq/VfhW8CyhiIexEQ+rSOtT06niZ0DEzWejdtAzOnjYZ15Bb9fAue+8s0dhdws2k01x3WObuavKZzBQLyK+bnsMZYX+/R+9YjNo2a3nU4qLhO6xK1rqM6Voyc8Smcs8zM6mbSMd8vM4ct0fZ8QH83/zpjIn+3nv/ucE4vAlTPIECzLNHwYjyR62ncbLaaFqJT52j9bajVYYGDtym/+3xXYL6PsDgOzvWgxHdNRyjn8TC/kt5CfU8Aq8JknBJ7JvNs31UhfloXkjt1cUixbrpodNV6V/I7u8li3YOAX4KbgG7BGXE3ItqMp1XQjuLh26uRHbYt+rusD/TvXiSP0nq9/lkEOEzqew2pMNih/x/DM9Jv0/fepH8HEZPDJ/W+Rgi2DicSXIxrJvuRvF3nVGgZn8smrVvCQYWZm27Vd3pI22BU631ax9QJ3BxwDgFYl8ibqIy3pdaxGPdHOYtE1ezTNjBhuRbfmVs/W/j3BM42boBqibbdDq1fdKA+qH+3E8y9oY0szH4V7jw7pc0NgQMK51lajgv3/j0CnHvr3MMc1a1/l+I8PZbE8wg1fA31OZZH67j21QlEK2Sh5TlmaJzF2/LundJ2shQVWxDgaCkuXtF+tnFwXvvwGA7MK6Y8nHvqQb3/YGHNegLX3HVrfzxeZ00cC58f1nfdpu1yCncqtj5eimh7zEHbGJjvwX1+LNjgn3X82Vr3AR3/HTioWRLqswzXplo4/tPAK/rdACUbsvCuZgp/r77DDl0DiqSuXTXao0t/n5UNuY3nOr9flSavlK5h8IMDj/lMSWFcNVWEW7gpwHaJNtFX68SJi1upmQ7nsrCFtgoYFP6fln0XT5XR7HEKcZJdpQuagQwzT60APl14Ru5dyRPDPYn7INhurw8Rsg/i6v4uFZYf1wXdoki2qkApCvRVuMlmGwLUHkLAwXpdoO/AUyKM4E7Ef6ifX8KdfO1dV2j9ViPRMv2Iyv0sIkTX6b3/kXxqjnv02jFEU2XAx4DKj+B+Fmu17p/Hd58vkwc1JjQNCJrZa4Ne+zRuPjunAuIlfc/oS3Q0tPFenPPItG1/jGtgzMdiTPt6uZ53TPv0UUTgPoYIy0mEvdjMiWZS7ArPG4WqPGYJ91fZwzR833C/rw4EPO4kzw/U/UqBRLHkHpY+wcj9BnGyyfOoJiYIUVsfVoUxfXsYm5M6FvYD+8P43qn9t0PH+m5t04vaB2YOe17HgzmnG6HhuP41JnAb08MIr80B8uvVkM6NMu6s96PmtTBnz9c4t588ueQ9WtdbcXLET+t7dZasP+dxk+keHFxv0rHTq/W3nHTdiLlwt46zX6R6LTaQYsDy3QiVBoS0M6EOkRTTnLlH9bf78Lx015EndbX2HUDWl4Hw7CmD9gZjupHJq+mckVfaEQfjNZFnJEywBeXXEyd9+P8+PApqAvcLeKjk2qGye4bPHY0GerjXXKW4MDu/7RzvsMmvv+/AzV9dxXfV9phUIbsFD/nuBw6G81eT3811ILvR83rdIB5ebCa4/Yg/xgC+Ozbz2YjWycjh7sDV+hf0nc7rsyyNxiM4s+wd+t3qcN8JfRdTu6/HHY5Nbb4DMcV9SBfQUV3U9+q1BmYu6Hs8gQCpsyoIzPmzCyeos6g3W2RPktcAmMbmnD7nkr73vfp+EYxEQG7gZADXuk3qswYRYWsh42tDnx5DAMJ5AnEjIlg347vwmJvN0kWYr9dwOC7gGopdFPKPtThej4TPFSff3CGsz10Nxnx/aLceBHwfUAFsJlFboyxpq/kD/Q/tcwOvyxFg/4SOWTOLjmrf7tCxc1H/nkM0hvvxpK4n8USmZkpN2nYv6u+79Z1Nw7qh8F7dBH+fwm+2QbHx0IUAjfUl5xpYNg1ZdNaOm55BnZf94ehFQNtRBCC9H/c1+4i21ZiuG5ZWpUvn4GEE5HeH9SS6AdyDa34txL/iJEzebFvU1vVpn+1EgOei0L89JeOjG9FQ2SZpzOZKjfHUzdSTQUci0ES1+8O6+ZaNsyh/Kp7wOSfBq/EIi+OC9Oshv4PYTqD01wVyAudiiXmIBvT7fvI73+HC/RtGrtEEQGryXWyRt2NtqHMP+V3tgC4ou5Ad3oguPgnZmd6u43NReNcJZCcb+T4ic+yRIIT/oPDbsC50l/Bw6h7EwdJ8RY4gQvtO3HHzFKKhOUJeM2RcKst1se3U/+9HQEgX7mfRDdWcNeFzzLZuppUh3O/lEKKBuoBofA7g5ghLNHkZASgX9bcLwL9DhORjuK/IpAq6HbiTfFJBd06ve1kFyTldwPfofRfZGNP3nSTvjGzz7CUERPXhzrN/p58th1eftqnljeoDng732qr1Ne3OLTjhaA81fGT02g069oxF+t5pjOnecIziu/MKrcGHYDQ1l4Yj1n8XHtFkAN7Ma71h7D6Apya5X/vkFR1/Y7gTtnE7mX/Naf2bcLPVfkRTauDgBG5CfVHP36Bj5jzu8H5E/y+O4fttjDe5Bt+pz3gEBxvvI8+dE0HiZvLh8dGJOoW1ZTEe2m9aMTN9T2i7r9JrhrV97w7z+916n53knasrwRi45tg0i7Yera0zDu1dtoe5FtPu1DM9WTLjokYqyrOq9CktjutS9wcWELfdLMjbChLvoIZqLSzECy7su8mXbGqQzWO9zJfAgOioLkbFHURZ3iZzhB2mQNVOPkN3M8k3Z9y+awsTru4fw8HNHZDjsjHz12Hcx2VC320SJyE7he5I8J3aw2Ex3BQm8BYExAzimpV9iBno87iJ7V2FRWWvLvxd4bv9+j6W8PE5hOV4Ak/WuBfhTrmIA8AO4HBx0Y79FD6XqdwjLYDV11JMGJAx59Syw0xipxDTlkXzdCM+DydxLYp9f68KANMCXEJ8mp4mnxTTMpafQUDTBC5g/1bbYQzZ8Z5BBOdZnGKgC/fDsh2y7frtnY8hQt7qMVm2FuGguuIrp/eysXCQaWh+Cs86iJvOTXD0/l/YklqcQ3jakgrQCb9Z2P6kttkSHCCfxU3iEzgnVR8ClD6Oh8bvQ8DOOcQsehiJtFuHAJsndM05Uhg3B/SzzUNj94455roRAH1fk+/bhQB4A10fQAC2pdWo+LjgAn4Doi3qjvNI/x4p3P8A4sPUGdpwi47f6LO2WJ//uM6BSzq+zTx1PtSjKhF0yXv10wAsUDsasXRTjoPtTaHNbV2xjYdRcAzVae962shrJrw9Hpm+LFChvSaldJf+3xEae40O/JtTddqABVkKKSnuSrNA3a3P6KE8nUKja213twZfqNfod+PWD+F8E5w3hL4BSbcxqZTqG1NKK7Ms60hK2Z9lWReywPz7enXU+mxMIQ3DNNumGwFkbw7f9SCL3htwx+JOPOXBBeDvU0rjev2bUkqPZFn2Z8B/RojGFuvtbGx+MZJW4QOINugvgZ/S+/4n4MOIgO5C6PhjWZlSui3LMgtXj2V1SumXtM7fhtj6XwO8Awmv7UTs9pZuxKJFXoMs5I/o95PAb6SUvi7LspsQ00VMUfKfEBNXB5JS41j47Z1ISobXI6kCQKj/v04/n9K/b0BSE7y2pCsuIov+FyNU/Ze1juPILv9dwO+klP4iy7JJ4E163zcimqavxVlw3wR8LqX0PdqfZqZ4E/ALwNuQMbwL0frsRgTXzyKmK5D5shEZ759CUjGMazut1La5CwGsTyHpPC4gi/1uba9dOg+6tD3+G5I+4n34WvV6fY+X9Hl9CHP0zc2M31h0bRxJKa3RcXkHkvpkOKV0vZ4zsBle80PwKoW5W3I/01gBfDsinC/iaTy6EBB5l/bbaR0HLyNj3bQ092t7HNd2/n/1Hp3AFyDaoOsR4boYAesXkfQZr9V2/1I9dxDhAHqjjqcvxKP9HtH2XKLjYKlea4K4E1lfHmqyPbchgOzbEcDxfQgAW4WkKLF0LBuBv0Y0Y8YY/aUIgN+FbGC+xvpU17CXESLI7QiAGUHm4x8Avwt8I5IWZgIBPd+u4+Z6/f87dVz+GLIG1O3LQp92NTpf1+4hZO1ZGb4zWbUMGcNDuJP67SmlL9P0H7ZeLiPPA3YI+P2kqZeCjPgeZI48n1L6gRp16tV7rFRZ0o+kEpkM53Qi82eSq6GUoFJzQKzYXMPvuaR9BY2BEWstCM0KIRpgFp9R8aOhyWR2hevLmE6rHJNLdhdG/lbkxIlcJ0XV6gEamDZnuq20roPh/5rOc7h2yHay5oNihGf7EH+XodC3Zh4aRpxhVyMCwDQGm5FF29idDyAAxnx6DuFms+WIKv5OJOLqIrLQdyM77+U4Q/RJZIE9hyzWps62cHOLkkkIGNqDmw02Iaa8VYhK/ilkR7oHEdLP4gv7Tn3vraE97LgFEXxr9RmncX+fpJ8tiuustksnstNP+h6Xw7l2/7/DI3wmECH3OMLZsx8xJ9wa+tf4jh7FNcgdOCuv7VaXkGf+7UYAqY3XmC3dAhFGEUF7Fg+jN66ZVYjAH0LA4jacLHMY0cwYv9CtOlY6Yh1aHMebKJjZKGhqgLEkfECNnEjN9BoZwSe0zSb1vQ7pux/HTbMWZXYMJ+Q8p332pzoul4e15SHgrP5/RMfReQQAPa/t+i5to8/iJIhGaWAaoCdwzd0x4GihPsP6rIqmpIk2TXi6lE/gjvBRI2LAahUeJbhc581h7YdTiJYrxwOm42J7GFs7dW6YZmyVzuFX9L5ngL/QfjA/qU065lfj/kVD1FhDCX5oTcqOqvVY6/cwzgBua9l+Cgzl2sdR/uzDyVzNirBV58F12ncrSuoyim9uLOBgeXwX8nKn1vtbwMuCyohQsw9qTMxBPcpYVYuOjSaILMpmXpmEcWE46x1Quvi1CJ5moU4WMmx5f/ZRbdosU9l26GSbMfBKA4LCBtcu1kXNOHf2I7u8HYj6/m8Qgf4EIpA36sTdpM/digv4S3qPgzrJzQxjDoWbdfG3hW+/ChVTlR/SZ17Q6w4Bv484Jd+J+CRtQbQof6oLzUf0/FeCwLLF1BalXeQBjW06umr0Twzj3q51teicMTwLtwkti+a5jXzmcovMsvOMrM4E5u3kNz09uNp9Eg/v3o+Ami7ywKYX36UnrcdRNPomzhdqpCDQMWMM3Nv0mRVzlz77A3r9bvKcNTeFfu4qGZMtz7uyuW39Fuo7lKB7mztvV5nhCuDHOJwmcObt83rsRwT2JQQc9OCmnlOIkDPCS3Pa79FxNYEI9mOI46xpRG2sWBqNQ6GdPqHj8dkwdiYRgbgBd1Y2oG8+LxV/KwQk760j7GN7nMVNWMYCXmYS7tJxboDTQu7N4T7pOMlxnuHpWsycu1rnp62DpnU3klFbH35b+2GvjrkuBByaadvWslqysZU1rhQA6W82NswtwsL3TUMzQDUY6sFNz4OEkP4wLw+SBzXP6ngaQkDQ4zq2BgrjfKBQ556SuWAbmT6aJPtcUOCniQ6zhcrCNHMdTondk7yNcnAqi08T9YopKeYkci0ufjYR57tDtR6bkJ3eJkLobJgAAyXfRce5GfHt0oWpNyxMG8iHupvj8AROmW+HRagcRDQYE+R3w8d1sT6k5z6EaFH2IgLZgM+n9fnrUW4RHY970Agw8k7iHdpuE/r/Cl18z6sgMZW1CSIjVDsGPBPusRXPa7VPP9vCZAt0BAzmy/OgLtSrEVDyrC6+O7UuD2mbWBTYBl2kt+t3RkxoWqDzOu/u0MVtUH+3/E2XEXAxhGjJniUPQvoREN2P+AHtwIWYCZ3cYqiL51lcoG/DNWOHcKEZx1xxMe3CI7ssceZ6POLIEoAacDwe5v8ubZdagKWl9YHgN1T2Pa61HOqEe86731J03i3mR+vSujyImFBH8LQjZxFAs0f73tLX9CNRRxM4lcF1uMlsb5hTW7W/jGNps/a18fk8gjuj92r7HdE+soi+RdqWW3Et1QACpvprtMeLVAPOuL6Y719CBO39+r7rCH6nOEAZw7V/FgRyJDzvCLA1Pic8d7O+f4e+x8eo1hCZT54BuuOI5uVjOOHqKEFjQm0LSAXMTwUA4QmGTcNpdbTfJ3Q8WOCAndtZ0taVqNnC8/boOLlH3/dwoS3WIUERTxRBTUHW1gzvD+MkAtEFR5Q4VaFmC38tbpmYR8UGmw2y/plsCPLAak6j1Vig4KeJepsWwHYQcaKVTuwwiHtoAryGhakmQWGN66ITuO0iYpSF7arNVPUqAnq262JlKvtLCK/M07im5aj+fwLxHdqvQseyksfDmGAvlPy2VwXLKsTk8EjJOYcQ4JF0MTH229Lxou2zCucjmdRFdwPwZ7jD9lkE5NyPA7G12g4W1m5cPM/pe9pO/lUVTgaOTCtmUWTLba6Get2j7fcBFSCR3dhM3UVN8GlEYO9GNGp79dnv1sX7PoJ2ubBomuZ5HyIcu/ReL+Imvv1677jbNMfQtXh6hFphxy2tP7XWujAOo2NtRwpBDEXBWHL9o4i5agRPMXEQAbtbqNYMmpa9Ag71Pga4+nScP6v3fQGP+DOAdBT3AxvWPrE583+0TgcRQXiM/Hjo1t/KtMd9WueiKacoD4wDy0zc+3GHbRPeQzoet4fnWhqQw6FfchteglkGWatG8TDuYTyE/4Nal1tRcK/XrEMA0DHU/zKumeGdihYQey9LnPxAC+PLZOYZZNNj8tXqNFTn2jIn+U7qkybu0bVkU0k9LCnucvLs3UYdEQMvrJ9Ktfq43J+xDfWMysFZEq69hRcv7uqqTC+4x3vTfjrkdxRzbmNkgScPrVPvrjCYy3ZwZVm8bZHppwkTli1MJf1ez+foHpy3x6J1YtSHmfSisDkQPj+DCPSP6yJ/Qhe/FQhY+LDe45xe84r+vg7ZgY/odQ8ju8aXdaHcgWiTbkeE61OIz42ZLq5DzG8mmExYbVHBYvnA1ul3lr4jIUL8AM6Ma2ZCEw57EMFvod5m2jFBeJ9efxQRdifxPF7HESF4Hg9hvoSAo+dxv47/jCc13Ypoy8xMYe/UrDDfh6e2eFm/ez8CylZon5g2IUdUFxZUM88d0/MW47nPzKx3Ttu1uNscQADSckIkVkF4DzYxR8w8Y5qt5s3Brn0x/5J3FdcGfNOWdBx2I5qWAwjoW4qAAvPVS+T5rt6NgGqbH5bqw4DXQ9pWp3Ucn0eA6McQ0+wmJC+YMXEb+DGtwHJE02Ykl7YB+YD22736/M24H94QYqouCuMjOFAxZu+e8Ns2SjbFFIAqLmw/gefS2kSQMbgZMem9X0KA9wUdL0e0bY9pnd+P+6V1h3H0ss5J27Tb2IybRIu26i/UoaZ7QQMAZMSXRuZomqSiSXks9HfNzeoUZUM/GuIf1pje8P9Qoc6NOK0qhLML7ZhNAWsdWbZA9hQasRK2p//XDc3G1YOz6mAd6hURbi6/FFdA8tApvHdnmIA2AfoK7dLIqTOXhDJcV8thPmp7Ug2hVeQx6sFJCE+giQj1N8vfFX0NtuFmIWMpvgV3NDfOlP2I0H1Zr9uFgKc/xZlub9c6R83jMO7IPIwI7YSbRj6MmM4GcJbdTbgfwjJ97j6t6yFdtA0AdBSe925cq3JJBdyLuKbH3tO0V5YWwVIiGIj4gL7/Ca3bJQQ8vajHDr3+E4hQvIUaQF/b7jF9ZmTZfkyffxAnWrSM5jbvoyrd0iXs17rs0nferm3zsp6/HHcSNv6YHYgAP1Jj/RlrMHaLjretOUm7SdeSxG4rrBlm8jP25BM6ZsyRuS+0x3IdZ+dtXdTjIO6L06/te0T7cpOOC9OorEBA92rclPi09v9mnXcGKicQMGSs4ftx89vDWr8J3B9rWO8xiWtFixvbCrlmeH97j88iwH2T3mNxoR96CmvKn+OknwkBxTYn70aAY8LJHh/XeXSOAHz1fR6DurnQDuFM6pVNTQGI2IZw2hrGwntXtD9hnTFtqW2OxpBN2UxaUhaRJ2ws85krrs2m7FhQxMEN33UeBexAaLAytV2Zvd7MNFMmdGqhfnGyGvLtq3Fu3eShs1S/WoycMwLAcD+dwZIJUMUJhQvw7lC3hmSMQRBEtt4jJXUpcwJeoQvzCQQ4RAA9oYt9Jd2FPteikN6P27+N/8Mchv+bLq63IqklzqoQ2qX3uUQAcvrZIrKexSMersPJD3eqIBlFnKUfRFJf9BQWj8N6zhASbvtoYV6YI+Z1KixMXb4LZ2E2UJP0mQfJkx6exxOjWiqADn3PQ1rXPdpWoyokTuA73GVah46ScbFTBYtRF9yNa3SreHG0bma6Ml+qmBRzWOvyGJ4o1nyHluuz+hCA8YD2oWn0apmqamoutY0jk3PkCSp1YC4DP98g7XoSN4Pei28kBoKQWYoAln04V9MFRIt5SvupoknA00jEOpqmIulYeBUxXe3Ud40a0K14Xq+PI+DD2uscAhwv61gwsNWl4+aMvvdelHMH14wdRIDpQVpYC3FB34mAuQnyviLWXr1a/08jG48JPGx/K8JdNESBa0jn8Dk9niTPaPxqnXEQ8+LZ2jWsbdoMiWX0X2rJ54W8T9Kwtn1ZdG8/ssYNFJ5rgKllUETjXF8V7Q/VgKxljdd8HvP7cOV4qTMpbBKYnfkALYaTz1AdbXIuCM0O85SQFN/9RNJCU/ue0gU77hqMBM1C0os28oq2p9DvDcPj9bwLyI7/dgIJp/bZ0wRKeJwI7gQilLtx1uX1uCP1RVxTcgwPDX8C2fmu1f9Xh0XgJjy9xpDeazPuXJoKxziiyTlX8ts5FZR9OKu3+VoZi+9yXAvyKX2eLfDRn8fMWh9CAESXCjoDQufwdAbHEWF9FN9pxrDhEZxo7hROtBf7bi0OyAbC5ws4g3ExMa2xQ5/TvzuApeG34dCnpuZ/EvcV2anCb7f2ozkNR5baCvgKYKG7xhjvK4y/SJZY04E5d8DgEqlX7Ndj5M1WHaGdTNt2CdEufk7b+Ef07yqc2sFAsplPrW7mYL4Jj647qufcqs/Yj9MpnENA1BjiG3ZCn39G+9o0QO/HQbX5eS1GwLZplvbhwSx1if5wbYmRr8as69YmmwrXxI3LOR2HL2l9h7Qt9ukYi30UN2LjOPjfTF5DVEsGdWj73xnuZ1Gki5pcL23sNbVZ12cWTaQjOuct4s/kkbXXRJgjFTcQCqbqJp/fTAqkqLjoK3nngVaeOW9ytJVGYRY1DTUGQfR838o8IMqwiHY3O4DnoE5zzsgZFq2oEVqhn1dR7jxnE9XUt+Y3ZH4G26gGSCPUCY/XcyZU6J0kOJyGc+5BgLItxl149FtCHJRNZT+IgIitKhSeCwvj+4PQOI3sNPfrAmq7q5sQLYSBjq36fu/Sc14J7XAbstM+joCqp/SZ+xAwZSRvJvAHcD8o8y/o0Dr8M+KQeR4RmJdx/x4DVTG6pwyEvaTnlv32cBhbjyKCdVTrdwkhaow8V/0IcFmuwunTep8leB6lXAZs8v4LD+G5vmzHHJ3do/nyMb33SX3eVv1/Hc71Y6DFtEpR41S5b41xnvPjw5NpNvR5Sinxl3CguzzjfdER2CLozFRnSWIHcKdxSyK6OsyLDh0TveTz2l1ENJUWKm9am1HcifcMbg5dr+11SseZaY5+GgEIlutqe+G9OwtzPOcUTO2ACQNPkd/I/IBMpmygTpoMrdcntS0m8CjfB6kRYo2bribxCM1HaS4dx03anjECcl24VyPfx5asApSH+1c4pcJhIMfSthxD1lSj7xjS/puoUSczZR8lL88farKeHXV+sznTlH/dvMnRFgTfnGsaCnVomZxsBp7Zge/uqwblQjqamYjTbX8oDam0idg0MNRF2fxXigApIWDkAO5fsAoBBi+H7z8PrA3vXgHmujh9AoniMKFhZqgtKgj2IqDD+ENO4E6QXeTzBa3Do2lO67UWQWMOvON4lnrzaVmE87FYBNNTiCbmYV20jIitW+v6IK552aOCaz9uVhzWhdt23esQMHAaMZkZI6+Bn3MISBhGuJBMu2QOnfa7mc+OIIBpqb67cR4dxCO5LuNanQnE98jGwnIVpKYxW6ttcIY8qFhNHpgssTke+iuCGLv/CtxZO2p4BqCK2DOGTRedVQdqjM0KUMIBm/nudIb71/J56u2H1FsOfnI+SLg5dggBf9eFcWJ9WMVXpudM6Djere1yf5gvpglcgmh9XtGxuk/7/SDuBH0IMU0ex0HwpI7lTeF53WGu1dKaWQBALWA5FtrPtAfRmdgyoO+htjmqYobHTWEWfbmeAvjBI7pGta12IkECu1FqiibWq1XaJp2Fd32QEreNaa6z5m8ZtTzdZe0R2rOrrE/wDVrRX/Mgrl0eZYblOfkEwwsuyqtSzyZfZk40DXi0gh1mX68idJojQFEaZr0Qj+lOQNwfocwHq56wmHJG4Rr3KobHT+iitg83zwzhWal3I7veARW8owggMcbYXQhg+htEo/NBBIDYTtCE4yE9ehBOHDNtWfTIBAKA1iFg4YL+XY/ziJzEGXWNx8VMREsQIDBKcOjHd/Jm0tiEm8/2BuG4RH+/T4XcpAqvW7UuD2idz2sbncUdnw9oO+3Ggctx3D9kQr83Vucl2j6PaB0SHnl0VK+zOv13vd8mXDNjgDJmKC9q5yaCQDWQMhiuNWffw3qfm3Citz3kQcXaIDQM4OzBQWQxl1InIvzvCwKi6MRZJFxsmNFd+/x4J6TOcvBj2inTPhjo3ULepGzgrej71q/z47Qen9Vx/igC9s/i+fDMhDWhfXe3fj6t378rzDfj9rHIrqOIBvRZHYurQl+ZU7/5m5hmfkLHZU2BF9q6iiVZf1sbxksZjUrOF1Tf1bjADOzvxTc65k9XyX2FR2ltokkXCu2ngzp3i5ncr8M3gDMFHuJm0CLRynxgm3HcX45vHMwVYXE4x8yuOXkexuOUZDxXgN/PtIQtM6xpIK/+7CS/85uPUPaGyewWwsEMAFFre/LRRMYFVMpoOgvvUfT36cTZbP+RkOwVN8NFR2tLcnoSd7o9g2hlnkN2fccRn5FuXWyNqG4LeUe+KOy2ICa6Hl34X1FhvBR4Vc85hoCqcQRkDCG7qycQwDWJaHtq+S8twukh9pJ33t6kdb8b5+iwKKHteFSambdiklMTDpZ53oTcQdxU9nm954sqHHv03cz/w4TtVm3XEwgAMC4YY4zuRsDgIq1zvYjNFBbf/tDuq3D/lTMIILN3+Szu71IEFceA9yLCfAyn7De/GNM2bKcclHQ2GJsxo3sZw+0iPCt90jaawM26xnr9KHnTxRY8aWwkAIxO9Dv1vc4hWrWoGdqIAMSntQ8tKe9HcD8how8w2oTHcTJRA8kWofiqjm/LHv95HUP9iHnupN7rIb3vOn3/VbjmsGUQoPc3J+paAS9Ru2cAeRLRpHZpnT+o93pRx/AoznBv4GdA36OVUPQ+rV+RIDEyfM8ayS7lAH24iTY1oN1HedCIbRrMT8jcTYyDa07W/nmRm9MRVDPcuQtas7KQDxp46IfFolRLQzlRVneYzHPiZB6fhQOwzbqoPYSrZ011e5gCBYG+5xlEK2HO2D26oD+pn19VYX0B5445r0KlH/E72ICbrx5BwM4iPS9qA48iIOec3s8i0Pq1fk8hAGK0znsPa71WoOasQr8dQ8gUh5HIoKdwJ85TiC+ROXPGqLXoy/MC4iOUEABo6SduQaJ+tuq1T6kAexDXsLyKmJoG9J6Wg2oYcTY3sHUU18o9SbX2JO5mjazwJRz09eHReDv03otx5uqD4f5lAOYSAsa2U/D/0HacqHHdkRbHadQw2WZhQsdBHHMVwYFza0X/jTFtsyU4v5Ttzse0/dfqdZaby0DPE+T9vLaGNoypCMxZ3c57GjdhWuoGM5Ve1jF0FNih93hY62FcQ/twjYpFnk3i0YBNR/zgTuymJb2XvJZiabHdC9eO6fucw81ZB3TNOIkA8AdxM4xZERYTNlIt9vsq8tFVRfLDyLU0k6mChkvabrDBNRUNJXV8dvW3UUKqquL71JAnNU2cV8Ix1Y6YLZPXgvWpWchHo3bDtTfRUS76HrRG4jbz9Y9RGet1IetHTFWm0t6ChFh36+I1hvulFPNQPYfveHboYmRCyQje7tVFfSu+416E7G5jEtHNVDNATyLq5GdUWDyMmMweDPOjW783s1UtJ9AeFU7rcFbZKLSNE2gtAo4e1HONg2UvAhIu47mgLpccl/Aots24k/YGHOAkFXwJ0SaZ78i9CFgxtmjTqpzEE72atmM1nv9pS9liqQv3cpxd3EKmzQnTFuEIFD6sz/5flDNq23ERByZmQjQHzAdrXDPUaH6Rp2IwrphKio6S8TwcBLQBJMvLZP4tPdqHryCA9AJOumes25PapqsQ8HKMPIu5afIsHHpr6B8DJee0HS7pb+u1n8+rMPwbBEyZKfcSziY+gZtuBxCAYeAsaZ9tJ6TRoWQzVSK4x/CABANWA6HPV2j9iiSHRTZxM22P6n0mEOC9pHDtUHju3To2WnKlwIFNxQ0j9nHh3F5mjnakLAKsu1H98Q1s9NldjPtKRh+5h6gR+UZB64S7SFQCWeZbBk7leA1TKxaVM5Olc4bvdy2VyQa/9wEbU0p3pZSu1++Gsyzry7KsHxhPKY3PV+VTShsRYLMM+EpcQF4A3plSyoDXIws1wC8iHDmfz7KsE9GAWPkxxLTwUyhFfkrpxpTSeErpLmRBPQDcjCzcX6XX3wZ8BfBJPf8uPX4YeCsy3j+OgKcexNb/tYjvxC7gjfpctC27Ed+hEeAb67x+F/Bm4OuA78YFJFmWDeg5X4KAj736fv+ACLSvRFT+/wIRHl+i518CssJxXL8H+CF919cCP4kIjJMIcHij/v1qhA14HwLybtV6XQZ+C7gR+AJcaF5CANPP6/O+Hvh2fQ8DAx36/D7g1xGBcWNKaWNKaQ3wLdpefwx8JqU0iZtr7D1+Tt+3WCbwdCdd+t0p4G2I1so0fltLrm20lk3qe1j01MNZlhmAuUHHVaXoeN6oz1yDCAhwX55lOh7XIMDmTdqWr9N2/i7gO4H/q79/FWLOeT3w18D7EAG/V9vdiAJvQMDOw8h8t/56nd5zTP/+lPbr67S/fxY1u6aUvhgBY1+gf1/AaQiWAT+ZUrotpXR9SilLKX0rkg3920MTjFN/PR8Ebk4p3az3RMcTCGBZmVK6HQF8vxCuuxnozbJszOaGtv0vIikvbtCx8daSMTKidVqGzLWvB34iy7JbaLJov6J925FlWV9KaUT7uK9w7krt35koXfrMYl26syzrz7KsOxwdhXPGgT8ABrMsG0J89BZlWfYoLje6gT/U9a5MDtwFDGRZ1qPt3q/9d5e2f4fO8SurzIamocG1tisu2i9Ls8i3j6Z3BhY2WuYoWLYzMTtwH/PgT1Woi6mlzeHTGFVtF7gYD/+uJFgMu5C4K7kfUYWvQxOXFscuskvcTiGqq079bMJbNMstyI59sf7+OOoEqv8v0cOivCr+RCV9kDNzJd81btXnmm/FImQBN/PYWQSkDOBagzE8h5fx+FzAwYlpDCy7t4XnR9Zr8/f4PZz00KKvXsFTg+xGFs9unONpAicgNF+S/ZQ4weLRYtE0th8JKd+NM3UvRzRfD+p77UJCnVN4l2Ohbz9GniHZNG+TuMNxkV8p8syU+kaE/jKH3a4GYyYSsh7GqRduwX3pYgqDHn3XkTCOhrXft+kYOhN+Mw3eBWQjMBjGzglEo2faVOvjn8KZm20MGKHhCr3+PYgWycy+li3exv/TJe/ajUQcRgbnelw/UWtQNLNU+JP03c/XuIfVzdpjq9bBfJ/M3ysGT0Sz3CKds8co0YY3kF/WZxVHembRNwbKQ8bDeO2v1Z517rkf5SqiCXlO/XyeRQ6sBRvhlav3FDtjSnY+8uoy43ewtABXpOpsIRyE3DS4n46BhAVLOlUQJmaWMnNB5JDpI/AIUUJBgAPA/ZDjcymCvg0qiDbp/4n6KnpT91cI+pCddW9o+wmcCyaq8833oxNq5rK7o+S3AX3G7YjWoxMxe5mAs7xlxm9jav/DKtyM+n8rTtpoQs7MJScQE8YruM+HmdLWI75F4ygdgD53E54CwcwellrjOO5TY/4gp8Lz79N7LEGccdfHRVOv+RweuWeJZZ/V659ToXYBAa7GZ2REjeZr9bS2R2+493rtm+1IPqsiAeFmCvkIC/1xHR7Z1LKA0/47iERkRXqIShJQ3H9qfRjPRsWwTr8/r+//fOjDs4g2I5qxk35njuHHcdBzMRxJ+zs6nJ/VZ67CWaItHP1lvc5MKQbwDmvf21pe1+cHD2apCuG2eRM+j0LdfIAWqHFA2+huHdNmTrWNVEzZsxrPCTaBaM1yvjxNrLfWR+avV2r+muE1PkZCHylbtwhrY4P7bSGskzNQvyE8mfAVIcvnWtgNsEBYkq+WIwrlEsFqXCcLLkotCADj/DFbeozmMk1QvwrDKpI6XXSMqbaKXZa8ZsF8SZ4I12+ntj9OFKDmLFmJRNF634probYRfB8avHupnxUFsKXv9y4VhMuRCJazKgjfj1MAbNaFPBIuPkk+Asw0HjGNgoGhSf3ucypIPoRoc87oQnkID3v/LJ5O4RweXn9aF+Ud2kcH9BjV+2zH03Y8jbM0G9PxkJ5rUVMGsJ4MdTZn7pdwRmfTaD2jz1ui9zuPgKlTeBTRKZwqwPyWOnVMGOCKu9h7tH13MT2Nt7XHQTyqZhQB4xEsP4iAw7MqlI9onfdou76odbeEpfeUPMs0clsRc8nLev45RKt2VNv6IgKkTKAaeDbfsWfxUOntCIDcpWNyEI9GGw7vVJX/cArrQiXiixqRX3pud2g7o8V4Wd8jx6Qd5vAQsrGI/XAAMSU3FXAT5mbkKOqiicCTGV5Da3FNNfJh60QA9YxpqnCqiitGvs+1wGtHc02t3SJNet3Mxwv9wJ1BbeeUyxwczusn77CY4kQLk3hIBX9n4dpiQtrtKmgtnLqSjJbaEXDFsFYDQFFNH1MWWFbrenmjhmv1F3lHygoXitZ9HR7KfwS4qL+txokhTaBfVOFpgMZC0S31Q9J7nMVTHbyggs9C6M2X6rK2lzlm2/X/pIL6GJ4exJKoLkfMda8ggPC8/mYCZ7EK8h691+1hAR3VeiStg6UjOI+HXT+hdTYem8Naz5PkOUy26/kRAPfh3EdmorOUJAdwjYCNyw36PkVQZII+Z7prMPY342DGorjOItoK09i+W+t1Hx7y3qPtYO9soLNe7rINOt6tvdbhdAFGBrpdx4+BwV3a1waSbfyZefgsHureg6dJWYFr8ntD2zSTA8vmlG1+jGIjRioNUG5uMe2OhbFv17FzXSO5Qz5svlffrWkNCEGjTgBAc7yWltEBdBbGaVmU11JEC3lNu5nMteBrKaS0fVTZmM20YxqTyu5ovuvZxHvk+IMKi1AZ/0RN8BN+H6Oab6UsIa0JmqpErDXqaukwylJrDBf+jwtNJZqp5J49ZfUtvE9Ma2EL6zKoGdkUD/N1uIQzIJsGqHiuMT9frnGvy3jyy6QCcTGy87+MAJpLJdddUiFiyRgtrYCRQq7Xd+tR0LEHz2xvZs/H9LnGbn1M3+0P9P224ESR/bjZ7RC+QTCCyCN6zUOhnXsRIHhKz3k5PHutgoujuCnWzMlF8GNh5T00ufnANQY3kTe9VXIkIUDLCBoPIcBuiwp1y0t3gkI6mfAMM4mM4HxQRhNg/bNDn3mfnnsMjz6ztnta++0lPGmpgdIdoR+PxjlXGO+NopEGyLNHG/gZ1vFmHE2LqNZuV1Gj4Lm47ilpk45612vbNNTaFu4RqQyM2mBO/CepwTJOiJqmdmaGDRQ2zdShQrlaj7kWfm3NT+2B3E9tEFDUinThu6XpkhvW5H+YwferODS3eE0ux1KY3A0dFHEOkTuQHX1TixJ1dnFUh3zmzLjU4N6gjpkrLFKRA8ZMbQZubyXPcZTw3FuHcdZrS/ZoztCm9TG/nr2478eLuCnJeHvMD+SC3tcAzs/oOZ36/x8j5pTPaJ3/TK+5qOPI7vMRXLthYOykAgyrY05oIEBrh76ngQAjjDTAcQrR+Azi2qD3A6dCP5gp5F0q3M1pfULbawQBY8OFtj4BPFLsc8pzfpnAaHVcR6G7D3XuDv3bjUQQ7UGivB5EwN8oDmy2ldz7FgSMrNV3eQb35TKzp3EDfafe38LZN+vnx3B/wcUIELVNxOMIUK2MZ4J/Yck8asRDE83Hdk+bA0f0+fb9QapBbJnPywptp4M6TiqknLXms9Z1L3CgIK96dLzVmrfFzU9OWzzLMqOnxvtH8FMrM8NDuKuBgW+bZzU101fbMVudYipcm8jGqnlNNOoU2sz8PHJZzinkJJqF585qzjYKDs0lv5eZp4bIq7vNPHUrvjNsqF7GWV33oWaVBud3IOrgvZQDn+JCV4uFtnhO3cWEPPDJOU3iiWRjygiL6FqBA6EX8cSVJwIgMC3OfhUmz+Kmi2M4eeAq3ERmGpzL+ruBA4t0u4xzLU2EtpsA/hZxlP5cGEu3ImDHzGfmp/EAzjNUAZUIz9IoYo7ZhRPp/SGiARlAwNEWPH/Yq4jGJIX79IfPEcA8qp+XaRscwHN4JX12BLgW6VbMbZfCc1rNnD1kghyJTpzEfX5Mc7M//D+q49LMTZtQEsKS+xrR5Um9xgCnma2O40D3HAJ2jFeoqEUdxEPE70P9gwrrvK3xttkwLVnDdsHTdVTM4IXfonn5Jn23mAGg4swczruDPGCzsT1KtcuAmdwsr95+HVdmwosRVPVyjfUWxsusO/xSO8WKtUtf6I/uQrs2SsZ6TVhoZrpDrOFtIpjT6pQd4K72A/IOywTitNluN5hazjbymd1r7YpKzVLh9zLzVNnurAsBJWM0aZPXNt2q19zeqA31/OV47qyau8TC+/WGsV4RBqGNxuq1JXngU5k7YRxYdJcBj9W6OL8XcQIewskNJ1To7Ufs+aZpOR/+FgkQTctzRoWiORibVuaoCsUxBAhZgsz9+ttZbd9ePLv6GAJ+DMCNIeabD+PmW8uJdFrrNRrOtyzkK8L5S/Qd9yDarVN6zhiyw38GT/a6Q+uzS9tkBAE4BsInEPBg6SZ26F9zsj2GcENZXQxgdpeMhwoZY8n82BMEe26e6LsnvcejCEC09dKiZizqsUvPmcSj/g6jhJqFtXe1Pvc+rddufdZyHMwe0+MjWr+qxJm49mUHAqYtvYkRXxqw3avtOUreaXuMoEme4tpUpvE+QNjI4BpzC+ywzw9r/W0tNbNq1QZcf3+X/v2g1vumRnUpkXmx/WY9F2V4bowAs5QURTZ1A+9NmWi5Riw0M90hTdu/20duoeks+a6PefCcx5Ph1fLFidENJuCjQ2m3Lq6P0ITGCgcPVaALd2QcbOZe4boHVECY8GgU/WCRIhV+mJJxHXOO3aNCYRLXQmwB7g1tWM/M1aULdDFKJiY7jX5eZh54Gt9V36vCzsDNcWQnvwaPgDqOa3JOI1qW44g27JwKrYsIOFmBO0+P6X3/Dgclx/TcTQjo2Yf7oyzXNjpiwja86y6957MIiO0M723Ei5cQbdUWPadK/a7zIeHApx9xDjZn9lPA/9B6W9JQ0ypG0GrgyyKJihoG08LYuDMelZzGUedHlYDHTSjGHzOEaKgOENI1aJsb0Owrqd8v4olmj2ifGn/SAa27CfQxfeZy/X03nhbFAguMfXsYMY9VfMwKdV+FmxWfwM2kS/U5n8Q1Cyf1nrGfzCw9QIsaEJwDzsZ4kVV4Z625jIfdbw3jYYDgL0SJ6wV5/p9I0RA18HVNmxT8E8P46C++2yyv3T1QMzLOQHRDmdJovbxajtkQnDNiMmkfszZBKrmHavw+ijszlkVhFTUgBoaiA3ZDEri4SIQFJprgbAfZ0oKh9ZkoCKpGec9GCbm3qHauLpo8+tFopZJ2PYkSxoXvowbUeICO4iRjFY1RaGMDQpUIMzxz/RE9ZzUe0XQIT49wSv/fQF7bcwjXAJwnn+ZidxDIlvPMTHHvQYDKP2m9T+r5p3E/mR/Ra7vDdTaGLOfZMgQ4rkLAkzlUDyHA7hTqd0G1psV2sea8bhqVnsLve4MwM5NVNJUMFO4bfSRykTIl51m7m3AfRgksw3GAYDoN/b8cNz8N47QBKbRB5Obaq989iIe3GzWBgXTTCPbo710I+LToukkEAB3WtrWosi4K5mg8CtO0JYv0fc0ElxBt4xk8FUrSvoy0GoPh3ZvySQz1GQ7tWnnPuO4U15/CfSqkrQhIryLmg1In6aLmxiLPBhuNi8I9OgvfDSNaWlvLBphlYEFt8NOpa0UzOdfa4GcKDd/PLKPb9tGwD3rrLA4GVGyHUxQEdxAcKcMEtsW21J5NPqNxT7PjgHKywqYcmuvc70grYxAnUstFluFag+14Qk0TkmMqzJbgpqthJPXAK+SBjvm+VULqCZEw+ltMlJhr43CtaSoeUgE7oELoURWKR1ToTaqQOqD3MqflXYg/zXaqGY5N25NqHCcRgPMCAoo+ove/rM87j5AQJjyX1hpkF25JMAcQ7cF+vWZ7EMoGevcgIOvh8N5mXixG6xnT9b0qgIcRTdAmAmjX53aHudHfaAy2MHZW6Xts0nru1r6oii4qzL8uXJMVjyNhri1BQPx+PDLtMKpp0evtXc8iGpmDehi5pZk2z+g9LL+VAWpzNjfzXvS1ixnqDyO+XBd0HCxGtFlbgmCvpSVuhnCvssnBHXGtzyNBoWk8J6Amk33UiK1HQHaOGqPGGhCBVqeOxU2Fe1u/lT27ikxW3+Wo1rcf50eaFQUBjcH7libvM1hoj4p2fr7l24y21ww3ftMJMpmDKKOr7dD26a7zu4WOGhAp+iKUhZkboV6HLpzvKnmmqfhLF/WSSdasU3IkK7wJ981oeZJRoJtv8hpbYG8NC383sD38PobkYorXDAH/jICCLYgGxdhiN1GDOyjcIzrgxkinKv+BUKditFenCiUjG2x07FWh+N+13ub0bJFYhxDtSzST3RJ+t2Of/l2MgJ7/hYdAf1KF8024lsKOo1p346p5l35/DNEGWUb7bSq41+nzLb1CNF18XOsYnXsNdESgVfSnqwChQvuOhbbtq9Fn0b/EGOojz0u3vkcl3UCD+bGkTl9dQECtMZ3fHgToEhxUr9Z5+RIe1fdxBOia35YxQT+H+6hF3zLbbKxFtJkTBKdvvb+Z0Pbh/lETOEt6jgKibNw2mIdHyGe67y/M6T9BwJttHg6gJubCvDQNqQGlSR0bW3FA1Fujb4um7k3kwU/0x+qsN69rrE1xAzNW8rs5f0+ZL4gaEXBhrf1Yk/exzayt+UOhb64a+TyVBrbdQnFn2zStNbMcZXSlHtQXmDETclmupKJfShlJX1l0gA3qMWDDFOo8EMaB+Uk0NUFC3UzVfvcU260u8KE8qmybCtuO8B6R+LALMTmsQMDR7QjQMRLAz6sAMIHSVGQe7vNSRYdPDTNBXFT12lPIDngU8W86hmhcunAH6HVInitjRd6hf0/i5qbIjnwOMZPdotclxOdnibaVnb9an7VI2+8pff4onm09+jHZBmdIhecBrcMTWjfT0Nyj97Cs4htwcsPFeGj1oL6H9eVjev4pHGCZGaUYnl7LJGCmoFKNZXiXGEFj2r4igWLUDtajNrAw47IjakDNrLdK23+JXjuifXoZ+FXE3HUB99fZr7+d0Xa/mzrCNbyXvVvk3tmA8ww9S+DhCdeP4gDG+sC0dqbBq2jySp5t2qzOkrlrvEImc04CT4V1sRsBi+YoHlniLS2JEX2WgheqyUvHEO1P00AET8IbU1HE8TEUntUXrqlouqkBJJt8fk2Nu7X/dOUTV5FJbCoNkNPuhA5rZZBMKcroaj70/W1xKhOAcbdW3L1V2ZzD5I+AqR4vTgctMJyGiTvlsE59D7PzTymcn8bApyyq7IEyIYD7THTjPijHdbGd0MVsUzg/Fdq6mUgK00oUHcVrmRRj/ivr514V+gMqdF4IwuewCtDHEE3eSZzY7iICHF7CTWQWEp9C+1iy0r9VwWnRYyMIqNqL7Iyf0nsv1u/3BwF3H86i3KPHPdqupo34rArW+7Wer+Bmmn4E/JzBzWcGOJL2y348geqgtoEByyHyyWYrCzfVjvUmpIfCemZC3ARqUWBbpFSkJugKz6hr+tW+K2rVTiCavKgN3aftM6FtOqh9M4aHcF9GwORebcO1CFiZ1H7apW2YM7E2mJdj2l+D2o4v63Me1HMGQz0tbYiBNtt4JWTTEOkfWkqBQNB0hmeN4YDf/HNs3EcAE5OY7kX4qvoop6iIfWfmqRy9RZP1NT88668IEKP20sZylX8kJRoqXDtUtUEKbXRCn21BK+twxm0DtZZTrSWZHZ51bYOfWRL+Lft4XE0H7i9jmoHeQtsUfRVsgeqnvvCftSgDmlRrl1w3ZYfmkvs0ZerCd4jvUqEc1f7mGGsL0j8jmpDjqPZHz92K+M2Yz0TUtDVk2g6LcbF/S81dYSHMOT/bPNT77VEhsDqcY5FcZ4C/0rH1qn6/CI+GOYFoBEz4xuiWsypQ3ouDkJNWT23D/fr821W47NTr1+nvW4GDJW1wCfeT6UUcei2iyPJYmcOyJaI1QJIQ4PY5hPvnCWAytNVAuK8xSlsfm9mizKxo49EEtwE2S33xHoLWAuVCKc5NPOS7wlzcYM2ztv+g9tHTWudJbYtJPSyE/WVEs/ef9fcO7UPL93ZGx+8FRDtpzufbKSQIbqJuYwir9zqE0NJoDwZxE5PRB5zR764jT9dxhGqNSiNy0qJ58Xj43cyK2wrfGyP5QQT8dYb32EU+OKFmTiwcGAzimsaWLRJxroc53mzusBx7M3ntUFEzV7SirNVz7sc3IkW/yv7Qti1lCGj2Ha6Eo9UOnTW1F03smq/mg+ody3AYpKVaGzw8c16czK2eLV5jO/hp9zeFKKkG5w4gJoODuFOuaZ36EFBjJrwnEBW5CY6teCoG65O4mDalAdPnjFINZGuZu3L+AfrcdYgZznIgjeKJLE1TYQ7N5xAz1hAe3XVWv38GOKr3TXi+qzF998uIhugJbbPP4RwxFg12WJ9/ToXcHh2Ph/S6yGNkUWCjKuQ34UltLWLsMb3XYf3fnLYPap0O6Pv/sz7D8rXdGtrnIVzbM6zCuDOM1zJOnqWIFmsXebNJtz7DgPE2HIgOhncq5vyq+LI1mvPknX0rzsP4ZsginDpxP54n9PNz2vdWJ2NxvkBeMxwjsU61ML8s/cdFBGg9re0wGdanTm2/F3FgGsFHwjcPpSkZCuM7aidMOO8L/W3ElDae7TnWZku0fgYilwEnCnOqFvixTU3UslT4pqawPkXunVad6St+ZVSbV6M2uExrtKywPh2p85ymNNbh/FlRfsyL/GqxM1vqwBbue02bvBoIy76pTLw5rKPZ/3upv6Ory/Y8hefWJRLDsyz3q6C1jONP4loSc2I1wWBCZDn5aIcVhESjJc+qGX5bOO8gsLmkjwfrvGNvyfkDCgKWAX8aBGYfkjHdIoSM3v+YvvuriPlrEs/hdBPukLwcdyY+gZuxOvS6c3rtP2mf78WBljEH79XrP4qAtBOIxmifPn+DCqa9iDbhcTwha9LndOA+LK8igMnSFFh/rdbzDiNRXib8HiYf/l7LgblH7/tpxJfLQsOjNm9Q62umA0va2qPPP6j9sA3XNjUVYq/fl4GxXQiAs/cZ1Xc0sr4zOOPyWX3fvdrXl7Xt9+txGAG5J3Tt3kBJWowGc2iCwE+k32/DzV+mgY4gJAL2ySCo6yZhLlxnwHARnlvMgPIjOqa3kU8NMhau7ddxNoaY7XrDmOitVwfK/Y5alnu4tsb8As2s2lT0FAV25nprDnl+pR3AurjuNnhGS+AH175d0ZHddRsEV7PZTmhWwvQoUJS3j3kYCLWj7+6o1z86GXZSw4ylE92ioWYE4FIAPuSBTtzl2vi9B/d5WKwLqWl+cqCN8miM5RTMN4XzG+6GEM3SwbJnUVurN1bn/SOD+t4wb48h2p5Pan8+oEJvNWLCs1110n5ZSz71wSXEx+cMolkw59XDuI+Kmb6O4H46Bm43KkgwIJRwh3BjiD6LaBQ24NxIx3DnbNvtX8DJFU/j+cPO6F9L0WA+MKcKArSoObMd+C1aNzMhDiJh6kfJJ5hNeu6A/j2Ha2kew7l4TEvRE4Rs3RD7OuPkbm276LQbx7olIr1Ox/Gd+p6P4HxPxcjAQzoHzhIynjNFkzgCFrfhmtKi9mGoMFYfJ5gTS+5n5hnTOlp+us3aFg/p7/drO5/AiRonceBlfWD9MaH3XIwDsKqExSWyr8whvKks9YX7WIodW2e2hDk0oeN1+RTXwFW4n49xXy0ObVmaky70eww2aQX8GDaoG9F6JRy1XtBI66JAmbVUC7N13/bRsN0tk/PdUBp9ZzT50R8i5vBZhqifr9PzKzxC4V7DuvjOiPYK2enGCMMil04ZkFiFO0aOIZqcWmCuTNuyGtja7Pkl59yjgvv2wvc1SeCoHy5tIbOpieN5rf/fIqDG8jCdVGFpi/FlRLvyLoSj51LhPgcQsJK0bg8gPjUTOMh6jOoQ9wrgwzmBXtKxlXSMRMK/f8ZJ+07gfDVrtQ7DOCv0x3XBt/e5QCE3m/bP7fiu2GgbTgahOYYS+MU+xf16Dug1B7Qte7VuSwt90hGOhiH2dcbTgyq8exGg864wv8zMaP0zqcdBxPHdQt7PItqf49rmZwv1Nb+cUo0mnjzZWK6LebfupXqjY5rUw4hp2eRHT2yjwjXRhGMJTW8Nv5v2cjMShdih73ur/n4wrFe2mRhDeIlsA2++Sd1M3YTVTeuO2jGiq2p9wlPqtLQpJO+0vBx4PHxva7qZSysamvD+tm52chVocKYsS2o07pza9Wgxyqh9NNWm5g/UVeP36DC9l7zPUQ+ibo6OwYt0AY2+SLuAO0qeG5lae6mhwWjiHWwiG9A5hjP4Ntx56DtuwKnuGzmg1uLgGEOTeJa9a4M+sBDvV4tjnjp+QtTWCMWoJXN4Np8Q08B0IwDPwvvNTLMzCIg/Ia+xGQ5CZBmi8eu3Pg+LZ9K/Fom0SM97UL8/gACWDvJsvx16r5dUeEe/GhNYF/FUJ5ayIwEXw+K+EyfgO4dnKt+OAKF95CPybkGASgRECYk0O4hkSx/Gc4B1kg+Vvx8YJx/tdgfVEUjRQbVXz7NxOolsMLoajL9uXPt0WI8JnM3a5uQq/TyhbWTmtkE0wggxkY3o76eA/SVz33xbynLZHQlCNPoilWYu13Y6p/1wFNmkHAjjJecXF559APerMq6syHu1WZ87CSwJz7I5vQvRInaWvJ/NBdMIDZA3c087/LtOX/ZSJ/dh6O8tjdalsnWt8H8lWpqgpdcxvAEBSDb/b8d5h6w9rknw8xrKy0bmsKSUls3l8670kmVZR5ZlPVmWddX6HZ/8A1mW9ZecNgDcllK6C/hOoNfOSymtQSbLX6eURvT8n0AE6iQuIDallP4y3jSlNJlSugHRHtymf1t9v64sy47gauMRxOH2+ZTS16WU7koprUkpjZdc25llWV+WZQbAvhX4tpTSbSmlRuO6H7ir8F2PvsMLJef3UZgr1oZZlplj9zOIUPi9cM4iZJF6OMuyzpJ3eAnJ2j1Z8sxubQ/7/Awwom0xGdrkWxDH2JOIieSLEA3cz+v1/4T4BjwOjGufWf0TslAe0GusdGkfbwTeAGRIPq2fBb43nLdL6z4OdOg4/WWc7fbTyAIM8Cb9fCjc26LJ3og726L3e6vWD0T78TDwY4hZ7HXA/wG+QecAwLfjvkpWziJasLciGowu4Du0jdYiqTq+MKW0EvhaRKt1GfEhuUGvO6f9b2MkjoMfRVKX3KVtfRH4r8CjWZb1lvR3h47XHq3PRn3OeeDj2jfjiBB7HfB9wFfgPE3mwzWeUvr9lNINKaUfxUHvLgQEWenFx7mN72JZqeNrXN9jGR4td6ONTa37IPDjiL/Z3Yi59BuAtyAmq4eAH0bWAysD+vftwC/h68obdcwM6Bj9DgREvFHrTUrptxFen3cCb9O2eC7LsoEwn8bDXJjUNa0bWJlSul7fZwTozrJsiBkuOnZGkPV3TI/BLMu6w2mT2k6TLd57pPD/Gm2bjQjwsfe+DfhK4KcRsPyi/jXOrG5kXPSrPOnOsuzOLMsezbJsqGysXlVlvtFX+6i5I6ilsYmRYKVRUwRVNr4jjH4DZaHzdp5FKIyW1Km/Xv1wVav5Dg0RKPun0R6lu82Scyw6pA/RTNS175fVPfxv5r19qBal5JoyNf7y0I6LEGG/Vz/36W/HEDOL1bfCc6TP/DTUpKmP2hSL/uoLbWDaiv2I0OlDhPduXHjdo/exRKadhXeKUTMryO+YbSdvqvN7EB+cDyNmiaW4ZirW1RJTTiJaifj9q2hahlCPzyOEeqO45uegtuVfIMDglTA27sXV/LvD/Ye1TjEc/QPIjthybZUdn0OAQULypQ0jDtpmenscd4bOmS4Q89/jeIj9WQSIXkd1DijTxF2kmr/lVh0rRhR4Qvu2W9vwEq4ZquUY26FttbewPlgYdz0HZKMHsDWhKsiAPLHjCq3vY1rnxfpuy3D+mSI7tpkWB3S87tD+i/nLIpt1b2HOvkvHleUuG9O5P0bB54UavldMUTM9xXW9SGx6Psx908YU8641zIYQ3rGZKMOYQsS0YssRLdR+BLSN6ti6ov166rbDfFegfVQNTFPZVuXeCgIlRiIVnX9rkeXZpBqgvqmmCzEVFBfihjQHNMFtMsUFo1aovzkVmvmulASyyeeYT0BMzroO2e1/AFhcOL8sl0+3Lh62cK9AdsH78SiJLsRUNVros8jZZOCiDGAWzXJVamvc1HJd6LtPhMW0q/DecfxY3rKnUFMJbqIwMGD+KH148sxbcd+OPSrwolPxYjx9xr7wvHvxyJQ9oY4bEKdaS8Xxbn1OhwrXbfr5Xjz6Z48+4+nw3mbeiT44phldR22GZWP6PoEAvOsQM5SBwE0qkK2tl4YxYIDJ8kwZiOtAzIP3FMbMCjQooKS/1+Har0MIMN6uQtN8kxplHJ/QOkYQO9aMoGxi/BmgL01/gAQavKR1NvPXEb3GTPO92t87EZPieRy4jKB+PTouy6KxJnSeWSCAzeXH9F5xM1gEH00FLMzgejZUeP52rZNpum0OxXQddbMh0GK0NHlCR3NPqKQVCeNmLbTO43alHPNegfZRNTCL1PJFuvZaifmiNqijxr27aAKcUCO6iwY7JGYojL3kvsXFqio8PZ5L68AnOl1GIrtNeFh8F3nQaarjTvK7plG97lVkx19xWA332VYUPBSY0ikHNV0UgC0ePhsdS1cjZrNKf9Z59yUqrG/S//eqoHwczTpfON8AQvR32QnVaR7wnbiN38f02rtDu9suPZfxWsfgJhX4O/TzSf1/P/Db2r6jChAs6uw8okGoaAHDXKo44OLOxEXgUyRlNMH8uD73XgRknQ3v8CJ5/p/jONCwthhSQbeevP+NcTWZRuTBwji7DgE/z+Bs4+8pzP1aHFGrVKiuCuOrwvQ71fWpxvypRAUXxvSkvlMxX1cf1X5SBm63IYDQIg1Ng2bjvL/wjAl9x1N6nYErS+RqjM0V1u5wfcOAhRley4rgsWYUbNk6Rkk2hFrrdZ069BXaoGytj7nWOkPbL1jalZb7Yr4r0D6qF62SQRgjrmpFKdkiMe3BCTWjjIYbXccsOM/hO8TS8PTCeS0v7OQBZ4XDQoXVckJCSD0nRzKGp3sYVgHZh/hoGD9LzNHUr/etZda0BIxlTqVV5Hm42cA0FT1al+XhfqmJYwwxXx1BtDRFs6gthknPM4C4TP/P3aswJizUfTBcZ+lc4nUThb4cR8CMCa8X8KjDET1sUbZQ+csIKLq9pF1N6Fo7/V1JO6wu6ZM+BGCdRLRAu7TP70XMY3sglyPOWLWP4WzRnfouw4g2xMDRKgTcfBDRED1jv4V2fxYBmPeRB7U23hfjgQGD2m4XFUTUTORZYw7VS9wZ54DxGXXVmVc9eFqYnvBsmzujuCajG9GylaafKIynnsL/BnDvw1m9y7SytlGI43NOTF6h/QZLvoumLtvU1cvQngMh0Fq0NM0Ff9gmwXwXx1p9zkI/5r0C7aOpwWqe/HOCunHzTCVDNU0kroXm+UyarEcPvoPvp3F01xAtqvKp5lGx6KcBXUhf0slv4dj2eROi7TG1eh+ulbJkjOtxU5otbpOUpBjAQU+FKqDG+xXBcS1NYH+D985xdiFampMqjPupH4lmpooBBOzlUj+UnF+X1C0I7lziSxXe94f2OYiaH3EmaQt7P6NC/0cQDcCrVIPHsjxKEfg8TF77FLVpd+J+JAkxUx1GzFsnC++yAwdkxxAAbWHqx3G+ohM6fv4cj2I7hGduN/PtKgR8jSLO7fYc82+zNBw9NKnxxHOWGdC3zZWNwTLNZGSNtmuLmgybAx24D1ARiJgp8kF9rx6tz3Ul4MaSDVvI+iACOm1TYX1gY+egtnd3yZwoagENPE4pi/oU19Vm8v/Z3BoseY9ulOAz3rfFejTMr0a1v96ctNFcHvNegfax8A7cEfYMEhrZrQtyownTM13wg+f2sYW4FX6UqeQZK/Mh2INzv5j/SK+2yRYVXqbtOImbjDoUFI3heZAigHxE751bnINgqWee6iA4rYZFqcwvrGEIry5uZgoYJjD56v/vqdf25J2eTavTctgw1Y7mkWm7aF4bLlwbs90fAN6tn1co+CnTXg2U3COhzvHktQJRS2TC2TRW12lfb0IA7ftwTc4raM4xBJj1KQiw6KxDiIZqFeRYiRPis3RA72Fh7ebjYylFzAG5s9gOU5hrNj4rXD7aDqZ9vJ0CKNfrTGMT+840SsandAgHa90BfPTr73XXC1zr3RfG2xHEBGmg7ZC2yz36+0M6lqMZ1uZXfL+OUJem0+RMc22rGn915oRtBkxbaX3wMAIYp+ynhFM5ROBflYGeq8jEVdoO812B9rGwDp2g5shZ6mCn/8fIhP4wOaeyCNvuzlS+va1MPHv+TC1GunjerYvMsyqA9uki8bIK1jv13ZerYLNs7UPIznS0pM1KtSNFAFCjrquBQyV90F+jPZrx7TJfjU7yGhdzJC9LAmqL8iDKuKvfT5U8rqiBivwzk+H73K6ZaqfNs+G3Vdr+ZcC26PC6nHxG+zLtmmlZjC14A06WeBqJcruodTyMRKqdx8kjX9Bzn0M0PwZm9iEmsCWI5mcTzlp9CQHQJxEt0+MUop3CGJ6tfIt36lwoe6aZ5Ypg0QBOBEXmZxQzwZs2uY/aGsMIWCxSqlMBwCncBL5C+8CYwis8UmVjZx7XVgOVFlBha2dxvMV2LBJFGpFhRTMzQ3Ur8jDZpqhmWp8r/Zj3CrSPhXXgu0GbfGUOdrbD6y4cHeEejXLomB9PDE9v2VmaJsLg6zx/WBfOp1UQGdGdcbpMIjvLzyDh1UmF3c/guyfTUk3iGiHb5ReBQ02A0Ogd9D33U+3vUObs2rLvFUGzgmh9tlBCgIdrQxLi79PBNCJmKNHu4CzJveEohpObBiYSatp9TiFOyEa3UKETKL6TCvi9xTaN5+KpFZLe2wTDR/A0G0lB0REEMF9EANhlHQ8bgwDfp9+/qn/NF+geHTdHqNZQdeE7dGP47Y/vPUvrQRmANBNTmcAsS/ZqWp6ils80G7XSXpjwtb9RM7EONz8OIBxSZxEwewaqIpcWHJEuThpZNB3WBDY46Ky7vk6xLg2TM19Nx7xXoH0svKM4EQgOdip0HkTV2TWuNVbhwaJQx6M5jKl5yruXsHhOReNgZqjteALJUV1An8bNHR9UYTWhAGeLXt+n7WB28ccQk9bfIY6XA/XatKQ+jRifbYdbNBF113i3VvIQGVjdjyeRfA8OTsuoE44U6j6lnXWz96GcU6krAB7zCbGcYEUBbKG795BPubFU+9v8VAZ0bK7CuW3Wat8amPknJLTfzFeXKXcityzsZ/TYjIetn8GTwd4U3t+ilaK5JzIsW1+17N82xf7ppdpJ18xIuWgkHDgWtXSmocuZaXG+oZrmL33fMsfsfm1H8yezPuvUfoprTqTEWHC+KxS0jVA3EWkuZcYM1qFvLsbTQjpeR7u0SyjKQDqJsvlaSSlNKnvqEMII+44sywZSSrcVbmHM0RuBNcoSOpRl2c1JmEfNXHBfEmbSqdbThMDNqZwJud61Ru8+CbwD+Cb9fEZP+aeU0posy5YAN+v3bwRei5gj0OtvTimNa13eiYCeg8hCcnPhsUUW4FxJKS1TVlXToln9OlGmZMSx8y3hHX44pXQz0yjKpNuJaLfMTPOtSL6glVmWbUQAZrHcFRhgexAt0FRK6X2UaXpE+6FbP+f6OeWZblcipqPXAN+NCO3xwILeC7xe++dlYEeWZT8NfBcClkDG07/RNv5lJB/aMgTQfjUCrE4BPwh8o7bVMPBtCFN1sbxB/75G2/b/QZybO4D/hGgZvxz4rSzL/g3wk3rP2xAtpAGJjcAN4f1HmKOiY6BTGahtrpt2Z2WhDzbiGrYb4n107egp1L1L54+N9bLn13tXY4BHn/kx7cMVcazoWjSnWQtaLJGVGWTc9oc6V9iqk2dDGEf6wdrXNGud2pa3tbgudjH1OXxllvlGX+1jTncYpbso/S3m5BrFkzxWTF5Uk4XleIUIIbqFe0efiUpUzzTew8xuLe3icFPKDsS88ClEfW6JAZ8A1oc6n0AEXxdqHsHV7FGrsBnRZnXreWURWA3NE7g5oejYa86eFqrbgWamr3Gfp4Bfa3I8mKlrEI9oehAx1eymTvLVcJ8p+fvUuw/VzsYN748TIp5DNCx78CgqA8umTdmqzzuoxzBifjqt107o3y79/oD+PY4AlId07HwG9+8pOy7ps05oXW7VsXJBvzuqz38RMdksSCdTPKLMEp0a/YCFZZuGKlFtKq3QVBS+T2FdaYWXq5K+J/x/lpC9/Uo5KA9/NxqBmFS8KiCCPGFlJEhs2czXah9cDce8V6B9zNkki0yeZX4cW3BOjjGci2Qp7pAcTWExE7M58DX0+8BNC1NSsQaQ1lRkEdW+RSsUxBiI2KXHu5Cd/fsDqNtTWBwsI3qM1LpOhe27cMK6MnbsZtrGhPNw4bvhwjMHtL9qOYpO0lxIrdHcm+AfgBx9fi0umOiAmfP7aLEvZ+Q+hfuNaR/0hbZbi/PqGHjfjpi7TuN+FJsQzc5FhHzxMu6UvFj72bRjlxGN4ASegDUe54GP6uejOq5eUSC2Qe/Xv5ABT5NtbhnTK2zEeBi8aVgNFBXDtm1NKgs6sLFZSUAawI6Nf9N27AzPvKKcc2mSHsTmY5P3bMjGX3JNTGVyTYCgea9A+5iRCRR3ALUcYC1qK5frS39brwtIjiRRf5tEbOn7EX+Jig9CYWLWctCzKK4h8hEOU/HTaYrEsATwxNQXOUZXFXRbkCidE7hDa29oo0pkUcmz9iFmvH7EHHiegs8NDezp+M7YKP8t/Lksy7ylE6jH5L1O69UK62tZaoVaPkUta2XqjI1p36fJZw0r6LDQ+IPaTsfwCLMxJAnkZf3tkvbnLv3tNKKxuYDTHHwMeL4AfE7jjN9/oHNom5571eZKKllzDBRZH5sfk4GiQUry78V5jjsF2/32K4jcpW1qmkqb87bWXBHtTAv+cq0AmmaB0rV8zHsF2kfDQWyLcmnyQkKoKx4tUwwJLnMWtTD1HSooa4GXxxA7/XKcr6Yh4WC4vunkok3ca4DajpGmnTJNRpUzdRFMILvvkwro9ijw2R/AZNxp1gpR30Q+fHdZyXmlJq/QNwMUHB4DWCuG+w4jppOBOu1kqRRaMSVU1Oax3vM9/mdhHi1WwbtKx/3LiHbzOKIxGlRAHB2ZX9B58gIe3fV+xBT2tI6dV/XcpwKAjrwyM858fqUduNbXNkCWZsQCJDrDRmDKzrdXCvAprNnWJpVow5K1pmk6D8oDTUrTkFyrR6YN0y4LtKjjG4hWYQBxMlypv5kDcsUZUh1hBwrX3JhKHAfVkfT/Az6aUvrjOs/fmMRpcCr1H2IKTskl9xkASMHBOjhR9oT3XZPyzoPmHG27zT0IeSGIAPsKxLflbYjguhkBJePIQvwTiEPr43iuohHEOfBzSDTYupTSiDqF3hjfVes4mFLKOYCGtrmr2Dfxe3UG7kWcTQe1fr3aJ2v0/ubo+HbEYfe1yEJ5VwvtaxExN+tzjciurN492kYj1lY2Jhdy0XcaRHy9PsY7WcZ3ch1reA74GsSs9SgC2H9LL/u8/v8WxDH+LAJydgNfqZ/v0XO/Hvg+ZAwu+PZYKEX7xTRCI0j7zZlT90IoOo8th5aZ1m8Iv/dBzuG50f369X42R7uQ9dEIHqcVKHFVlPlGX+2jIYIvJvGLlPQ1fV9wVXGjHC51QyabuUeD+w/QpH9OnXsUtVtGzW/sp511rrVw+LWIGWMbvsM6jfj/rKeQHBD37+kHNuh3kR9mOR723oUQ2CVEUEa/mYeosYtFtEbmZ2W+VmNUh8mb2dFMNjmzmNbxQUST0bRWrqQ+polaSm1NY01G5ivh0HecBB7nLexmhMus5BJwi/bXfbjDtDkpb9G+GiUfaj42lbamRjqP9tE+whgphr83ZG2vsW6WacBnJEDhSj/mvQLtY0oTw8w70xY6FPhQ6kwgc1osCvdZTXmhz7cEo00BnsL1ln19BPiktttmxGQxijgs10ukuBdh4I1Rb93Izj8mnzyD79wGwvc1o7wQ1uYtTbzDoNajS9sz+mvF6LuZiLjqRPyfltapSxUj83zPiSm84wHE5PkB3s85Hqzw71xCfHrW4k7xpl2MZoSeqWwKrnTw2D7mbIyWRXza2mfmqyk5JtNC2qCr+XgN7XLFlZTSspTSjWkaPDmhdDb4fRx3SJ0Efg7oVfNafxN1mEQESEsly7KuLMtWIRmydyI+FzemlG7Q9x8P53ZkWdatquN4D3uuff88wp3xdYj58LuBX0fUwWV16AVOpJT+HvgjhJNmCBGMbwD+nf7/VuCNKaXxJCavjVqX12t/jVNe3g98S+CiKauDOZ0/p1/1hPpOqW3rFa3r3cAtof1iqfAV6TtOpmmaNGeqZFnWk2VZf/jbW3ae9tNXAudTSv+e/8RX8jXsYhOv5208idAE/HxKaVKPNXpE7pg1aWqm4F7y462Lhc1B0y5zXIrrGFS4im4j77vTr+tPq2WSxuv+VV/aJIfXUNFJZSGoIBNoI3BXOMdszmZz/x3ghZTS9QZ49JrbKSza+ntf+Mom6l3hd+MFWZMKPilZlr0b+A5EwI4jBHTdKaXHGryaRYV0KSnfXSqoTFD3Ib5NH0R8OhYFQdZDgZAtlNsRTRcIUDFSsYo/QkrpLvNHCt+tUdBygBrASsu4HmWkiAa+fhb4AuDDem5XELr2buhz+nEiuimXJMR2HQg55Y3atkaeNhnAXF3ixrks6rPUm1K6Uf8vEuoVz+8Mv/fzrznNq/wxr/AzwD/MYlV78PmwoMBjuyyYUgqIk/hBVfkHZlnWlVrzkdqIbGAn0fX5WhyDbc3PtVWMNfdGPTL9OwKQZdkgnmzQCMxOA78AwvKMTJwR4HuonqADwHciAvsdCMC5PmiHzHn6eqAjggYFC6uQqJsfR4TtTzUBfEAFit53HBjWe/ch5qK3IekadiDRWOYc3qt1rJr4Kkxfg3C1gAj+xTgLsbWZAbyyxecHYxsF53W0PceBb8AdtuPzFyOmvn3Av1WgGLU+thh26ee7gE4V+tMuSRwrR1C/MpzI7niWZR/QtqsLMOa4tKpR6QJGgiP9DenN6R6EKXooo7Y2bpplQYLHdllQpaWx1yLwMS2SMURvvBaBjzVE+7hGDhpnDm+GiK8LARFPlPxmwtIizmIen0qYOc4OuxX1XUJ8R9YBv4aYeJp2AqWc26gbWIQ4rW7GM5dH/p2aDqtav4/gxJCbkEifQ3jW+1FE4G6KddBn3Yrzx/Rpe6wG7tB6dCHEiOeodnDuQPhnHiipU1etPmUK5GZTGEPmdG9JOheEvw8lCVIbnL+cEufylBIkekiMkWae7I06yVrbR/uIayXON9ZdZ51q8/lMtZ3nuwLtY04nVV1HtwBcSkn5cK6UTxDSLYTfjwG3FJ43qIK+stDjvB7Gp7Ncz1mu93hkBt61G+Fe2aGfjWzRBGQPNXgzdPGpcB/pArQWiRQbDt93I06y1xWu70X8ZooOyce1zZ7R605Rzm5blemaao4i66exwjvPGvjBI5R6FMgtmCzQtJBoNYDLu2svjHQpAJo1x9CFBB7bx8I6yLNjG1N5MQ1GS9w/7SN/tM1e11YZAbrVmbi75Hfz6elEzFLDBafXPuAfkUin2xDV6ZA6HPchPDnfrvc3gGOMx2uS+ML0Iqp+U/3vQpyO/zfwH5Gw87NTfUGtSz8Cur4YIWm0d70xucmhaCaJpRe4JznfzWnge9GkjcnVzL+MCN3dhes7Ea3Tp4FvzbJsOeJk/TwSSdWp131RKiSGVTOMOTcOhPb/D8CL2idjOBv0DVmW9arjYx/Bf2sWiqnHvwi4EfjdWXxWq+UubYe65jjtz2HgXKrBbQWQSCOIH9ZARrnjdKvFnLH1c2my1nZpFxAXgyRO9XfpcQNi1i6axNrjZ4ql7fB8FRYVmJ2p2hY8jphjupHMwX3kCQiPAt+VUvp+vY9lZL8RDfVGQMo79fw1uKlrHPgfwH9HtDgGjgYRu7KRc/UhgnMIEdQbgUe0Tp9K4kA8lQiGSGK3BmHnXZ5KiP5sAUkl0TqW8T2J/xAo/w/ij/SV5H00FiOmumI5i2iHbgYeUYH3EwjQ24OAorJnG9eQOe3epe10g7bn3yPaikhoOaz3uivNPjGcOVhbFu5/UgfzqUY+zVhJgVRQx3VZ+9r4+C3gvzS8J2kkI7sB8QEiMW3iQus386GatnN6u1xbpTDHR/ANkq3h48h6O97yza+x0gY/V1mxKB39PImCG40s+WngWxHBPB7BjQrUbyRoDpJE/YAIWJDF2nxpxhB/ld3AnyMkfL+p370hCMMbsiwbUEAziTIwZ1k2mZyhuAvRiqBajZZD+FXb04Ps1seRSK2tNU5vpPVZE9ry+5E8UJ9CIsb+Xn9bBLwZuKTMzh363A7gTXqNlS6cEXgnAmZy0V0WrYQAw9j+nVmWLdN7ri1oCvooiZqbjaIC26LJ1iBj6C79fjDLshvma8HVvh/R8VSqUdGxblF1xiTcsCTSZEZ2I+oEnUhTBiypSXbedmmXYtG1KEc9oev6DbiDtEVl2preBkD1ynzb3drHlOzBXUgIds7nRn+zKKdeRAAfQxxyh/TvcmSCWFLBk4jvyXlgtPCMKlZRxPdlvT5nQp9xCiX902d016hzdDYeRjQnluxwSnlncH+imEupH8neXpaRvCpZaOH36Bd0D26m6tK2tLpuR9ibK35B+tci5boK7/og8CyiQdpOnr3VHBy7SurTg/gt5ZyqU5p9H5+ydiE4PIffmspMPYt1iwlSPwYsLvm9kuuIKbIqkxggtX0s2se8jPHuZueYju95m49XyjHvFWgfU5oIQzoZeguLehceUWWRRpY4sD98108+VUNnQVibY3OPPitGbd1EyJys59h3wzTpgKd1uH+6k7REEFvdO+o8t7fGb72Fd12HJy3tAJ7Wz4vIOxp34fm1bjUgo99dhzOzrtDze/B0HQYmemrUZwwJ17+1rK0UaE05CWSTbWwAs1v7vb/wewcLIOpE63GEPAu5JdLsKLTZ1NhxBQANktqOyu1jTsd204CGaaYkulaOtsPzlVnWpJQ2JvFzWInw2vQgC31FLZ/EaW4lbkopJt0cU26f6MQLbk5Zk8T/ZFIdbbuQHEjLUJbQJBw+P4gkV70hpabNAhuBL8SdkadU9JnRv8PqXsbdYxEUtUxePdqeZob64uSmim5EqwDivxPv0at1sOSEx7UvehDCvLfq5w9rndcgDuWdet6aFJiyla3aANRvIbml/oFy/o/bEMKyWWNs1bGxEQFjK5Oa2YKj+wDijDmsTsczyjrdQrHkmB3A+5QhnCRcVnE8tEoK520hZq8RxAw2X+/ZLtdeWYMEq/Tq+lBv7Fli5napV+YbfbWPGdkVVJmokN3tTZSbUnoR8GLaiTHcbFOqOcG1QJbPahOe62tVuLZWotVIy24ZxM0cMaVEnCXPaGTS6qDGjkjbYqjQBjGkvV/rbO3VGc4dCueN4tq3bsTMOIonSjVN0jBiAhsoe4fwbOP6qJmDjXkwO2k9zdxopj7jUppSws9p1se0Pikc+0vGcd1cdk0/L9FLYpg0t+/ZPq7dI6zzps0co1wbPO9a2CvhaDs8XwUlldCeI6kV/gbYnWXZOHBb8t3v1yOh1sZSLBEtotnpoERzkkQzYY7AvUi6h4vAncCf6Wk9KVVHxKh2oOhkPJ5SWqYO1caaPN3SV+8+yRmqy0ovqvXBtUcjet1GPJ9VD/loit5wz0ngm7XtSSlZjq9zeg+yLNug9ziEpPK4sVCPTm2ncdU+/SrwAQRoVL1bE9qs2SoDiBZoZXA4HkdCzse1XWbdETsU0/rE8pVaz+hcPiO74kRamZFNIhqgmxOzHmnXLtd4Ka7zIQVNZyo4NxuVSZrnKMwFXeYbfbWPae0EbKddpt0ZAVbr55yGBQm33lxyTS9NOIIiAsSiynoR1uJK1vOS84eozVA6Y855THFHT559ups67MD6Ljkfo/C5B3hYz4maG4tEG0M0Eu+mhnYE0RQlJLv4xxGt0RLg1sJ5pj0ba6bPZmHsDRfGVmyHOfUBolzrE4/ox5Xzd5v2s50MccbZoNtH+2hi7JcFvfTqOJ+TYIgr9Whrfq7sYpnWB7Msez/wpH7/r5Gw9YGgzXk9ksvoLPBG4P8Ub5ZSOY+J7jAseWjMlL4MEeB36e6/ltZlHEk6anW26KlxBKTNiIYgKT/OFErU+vTXqo9qcTpS2E2lvIasG3GSju0E8Hac32gMuBehICju1nqRxKv/FuEpuh5hin5bquax6UbylM0bV4z6JW0k+JJpG3Xr535EOzTb/gdlWh+QubGSvFasgxnMp5WEC+hmYDAjW5amzwXULu3SSulM1Vr69hhsorTBz5VdupNkW38DIgDGEW6bnwTuS2KSGMPJBEFMAZ9uUSBZ5nCbVCNB2G3KsiwhxH5rEIBlvjUmdDbi/kWT0wAps1V6ED4iS7xaSzj2hTZA378Dd0T+N/q7kQCCgLuf0/uOZ1l2HAEtI/o8A7A36rnjiBbjL4EH9Luio3M3YsacN6fGJIyzuRK4ltboO40jwLzCNzXT9dD2/43w1aQ+f2MYf7F0zTRgTDNPhtgu7dKwqGmrbdaaYmlHe13BJTkL8dcAP4bk3PpG4MMpJfPDmUwStbVRj4emIDQ7UFCgR8yK/keIhuJ2RIMCYv6KgsfAzyQLJws44R3W4GH7y2qcZ4BuZeG7ccQn5++1nT6JZLzvgYqv1FngF7Ms+yzwpILSXm3TTNuvN4lN/32I1uc/6GM+CPxgIR3JSGjrBVH0fbp1TI4gAHmlgiRjhp6N8j7gDcDfIgDrzSml22oAn1kriWQAtjcj65/LZ7fLNVtsTW2XKZS25ufqKOMo4+5s3p/qXcaIajDM6feUmj3KJmQnohXpZu6dc+sVM0cNkHcKL5Yyp+JfBf4+pfQrWZY9DrwXUUPnAJT+/k/At6SUvie2nf4+mWWZOUd/CAGzdyFs0I8X+1XNjMNZlnWnhePQ2AvcqGbWfvKO3CtR1vGZLJoH7UsRs2BDIWDsz7PVAMnZoPszsoE0DTbodmmXJso40K/rxpq5BvxXemmDn6uj1IuUGs+ybMq8JlpKd+7hnhZtMK5JPL9cAREI2BlBTD1r1DSyIEoQhj2IhqwekDCQFMsnge9Rgf9N1E+meR1wULlnvgPh+bF0GKYR60IixX5Dv/9JvW9ZuQ0JL7+ehVHM+b6mSW6mwJpq3AZo3YRa2SnbOJzpDYNqgG7LyAYyskHgNv2uXdplRouCHUvp0ub1abG0zV5XQUlCZlhrgTUBO537jyDCrVaJAmUp8ItIos0bkfxXy4K5aLwkM/F8lT4kqWovdZJMhnxRuQVG26UL+J/AR7WNijmlLJXIzQg3kvnLLNP2MSLJlQiB5O2Ic/oh4E+AH9Ns4P2a56tffayGtC27lWywZ57b8gZEM1YhncyyrCtkoO8EepRYc8oAOOSuG5+C707F2VlBz6y1mWp9xmmTIbbLLBd1RWiDnxZLpqFx7XIVlBBpY4kbbTfectLJgo9JF+LHc0Od83uB08CP6N83pZRuy7LsbjwKrQsBGjfMhvPrFNpqEI0IqqcyVhbslak8C/wmRKvzJ4iw606BARkR1MsQoWufDZCOA/8S+BbgXcD3Ai8g0XgPIIDi/eFx3w58Hunb30TYn6+jBr/SDLdXD9J/BvjG6z1Tx49x7Ewi4eY3apv06/UtcTspaK7wC03hHYbwRL/d2m6zaprKyHqRMX9zoi2g2qVdFkppm72ukqLCfBiPRjLw0lJ23yC0NpLXYjQyL5hQfBh4D7Asy7KHge9D/DLQ+90438BHS5/WubMB8LG8ZxsDbYCVDsSEBe40HbVa/cBncYZoM/0NKDDsBv4Y+F9I6osJYBfw71NK78myrC8CrizLLiI8QIsQJ+p+rcP5LMt6yt4jy7L+6Zp2LOO8mZgUCDUyo/YjQGNEweMaqPg3LUOAZ9PgR9t+ENEoTtW3IYYFz6r/j5UkZIjQJkNsl3ZZUKWt+bmKSpZlYyECbKr3MLbelgWMCdosy4ZTSjdoiHPnAgE7xbquA76TBuBQ26OMzdnKQeD7U0o36/mdGtLeD/wU8MUEs59qPgZVC9INPJhS+gY9/0PAZiQtw93hGV3argeBf0gp/VrQoEwCB1JKf1Gos4XQ/4M6XBfpB1ppq0EkMs3eYYwG2rssy46geccoMVFlWTZMCddRjXv1EMDUFPu7C3gI+EP9qq/Z589EyaiAtzYAapd2WQCl7fNzdZWZ8vafqo+CCcPJgtlsIZYLNCDgK6SO6ES0DrkDeBsBECnw6UE0C1+KgIRooimmw3hb+PxNwIuIKeuCAhWjCQA4nFL6NX2Oper4MuDlUOdiCP0i/alnGhqTHjy9RyfiaNwI0N6m9V5pwEd9k/rV/NSJUPMP1Bsr+j59CEidDmi4D9ittA9rELLKOTNDKeC5GdEALSiagnZpl2uxtM1eV1GZociVNZSQ+dUqKgx7w/8DiGAbBx4jZEpfKEWFbUcTPic9aJ4zZafurHHODeHeMdS7LLx7pQEHNQk9ptF4y7IsW4TkSzsMvFPP78ZB5csF89YI8EvktVEHkOzPBihek2XZCuArsyybKvvrZAAKFSBUr6SQC07bxfyfNiIgYFgJOnuQcN1lRXCmGqxupmkq1TG6GCGhnDdyOCVDvJ42GWK7tMu8lzb4aZdcUYHcitZmCAE3cVdukTR/geT9WjCLfAiTvrnRuQWgsBH3o7J7dZFnu7Z736YaIAOSd4V7FoX4M7j/yU8Au4G34qa2KKhvQ7QlFnnWjZi8JsP9H0Ei2KyO9vHuaQCIuwJ1wVST0PYjQHKZpuewqKs1WZaNICahCJYG9OOUgE8hlL0HOFZo03kxPQUuoKGMrDMxa9xc7dIu7VKntMFPu+SKCvCmhI0xHJdpUIx4i2mG2c9CyWVsb6GMUM11VNSC5KLC1E9nLMuyes+bRDh/OhCQ9Drg4aAF6Vbn6B4FCsuAtVmWXULMZLvVf2YSAWKlwnQ6mpOSvGJT0ZpYKpY+bbcbw/3HsyyrmNRwDp8pR2JZ22ubTgJvCNqrbuDmWk7is13aZIjt0i7zX9rg5xouKnD7yEcoddHkzl7NQZ3hft14qP2PMnUtwWy9bzcihG9ocF6HvkdktS4jEquYvMwxusSsdBcFHqGgWevWe/xH4GnEZPVG8olVxwskZuPAopRSphqTHsSfp1Y7fxlCxjjVNqs4wAe+o6kAqTXq6zNOuTZnHPh6VAPUahh8Sb2jxuxJ4KR+14nTQMybI36bDLFd2mV+Sxv8XNulBwEq00mSuVGFyiQazq2fly1A4q2aGdsLxbKET+KmrkkCkIsmr5DXqgxUbUR9okLiT0tgOo7mg0L4e9YhzspRCN4MFaDZo+cu0+fv0nPqtfMo0zPxmEmvBwEMU9JSNOGP9gMo8J4hzqJo2vomJEfaZIhY60zlLNSd0xm3Cpyb1rQl0m2aC2woI7uxDYDapV3mprTBz7VdOilhLm6xjOB+KaWZtIvZy9WvaMqh11MpTWRsj2USEZT1tA/dSAb7Ln23siznFql0l57XVUZFoGku7gB+qSg0DVwFc9My5RwaAJ6isQZjWsJ8uhqYZkqWZT+N+Dn9zHTSX5iWSv/txv26DKhWQGAN4GPgfarPNnNbX5ZlK1sAQHdpBFgbALVLu8xRaYe6X9slhlE3XTSlQncwc43jObKK51ZlL9ef5szfIsuyX0NSbjQr2IoEj2WlB/gExt0SBJ2ClTFt2xsttJraGpoR4BQlmdqDtucGzVa+UYFjTKBaz0H9ShCknwbGqJ9CpW4JZseyUPYuGuQ+MjPZVH2jCukyVtJiFnuN/FoJDCsnULu0S7vMYmlrfq7hEjQITZVgton+JyPBlDBSkkS1VvbyuRTK9wN/1vROXOpb01Sk9X8t8D5EEzMSfutHhHiRPHEEMbuVlV7EHPcbGskVtR/myDxZOD9yBdUUlnOhuZlu0XHxw0gkW8vh+Ea3kFJ6s/5fDGVvJrFvX4tJUot1qDzTqBFaTSisbNAjwGCbDbpd2mV2Sxv8tEsrJpFSs00opv2J5oXiAm5Mt0ezLBufSROY+R4VwEgnwpvz6Rlssw7gOLClhqAeL0mCagKxowSEWUTXMwhAiqSJG5UIMArSIlfQFR8tpO0jIeCtA6Bi1F3F30fHVl0QYf5b03yFYvj8Ggpzoal2EC6gmxEAtKzNBdQu7TI7pQ1+rqGigiBqCSz6pdkyWWs3qyDDyA1rPT9qLJYhgv42ZiAxp4Z7jwCdIcx+IyKAds9wU3YDr9Rw4l0GDKvPR7EtzMwY83U1Qxp4GzCQZdmNKaXJEr+gheZYPqUyDQA0SX7cVULZ9bdGACQHXHSe9CLjeaUCzE5EOxSj9mr5GBkonVL2egVAN9AmQ2yXdpm10vb5uUaK7m6HkUXajklKHHXrFHNuJsuyrizLhpTHZgjhZhmnPqGhRTmZGWdGTGD6bpY/aiVC8vddwP+HhNx/PTNEamfZwKkR9aTvVZUvLADPKq0PsEXNj4OURKOpGawSNXY1F2s/oDcQKwJCfKh9XSxrEK6kbr0mhrKXURQUS5HbKlIHGE9VZNpu5GNE4dr4DgbO67cDoR2YGohql3ZplzolpdQ+rpEDSSkwnes7gSH9PIAIiVbv0Ys469r//YjgmE69LPFlGcDrnMH260Acc7uabKt+bachva6/5H4H9bfeZt5xvsfQHI7VDu3L3jDeEjBQ55qu8LlT/w426i/tn+7CszuAsfDdgJ2jfXsk/NZdVi+bK4XzBuOzGrZDooPEAKn2e7eP9tE+Wj/aZq92aaVM1vjcSqkKvU7Tz/puPhsdNB/O3nJJYpa5oVF9VTsxiJjAoqarWG4HvgR4Z6176r16KZhVrvaS8iawdwP/Un/qybLsrrL2SuWh7M04HY8U7mPcTdEHrTu5yaumj1GhdBTua5xYzbdDngxxALgrtUPh26Vdpl3aZq9rqKQGzMaxaAbuATVtDalpaxgXCBUTWIslmg6MbbfZOvVpnfoKpgMTPpNMI1y6yTZsRvCMo4R6KaV64dOLgI9REhat5pEhRHs0klK6vgkhflUVbbdncOADAihaMf9NGaTbBx1r4/rZ/IiKPkYb9beZeHZ1W0gKjEnED2ihpYxpl3a54kpb89MutUovIsBLw3+TpDto2Rch5UOvm86urSR/5sjcBQyGpJ2V6KoaPiFzWlL9yC57H/MBuoHyEPg+6uTquhaK+kHdWvJTL01wNlk6jiYeZZFZcSxuRLRMlubExqD5tPXXS5fRKrBvpqQ2GWK7tMuMlTb4aZdapR4pn5XxVrlMCqUV9uFuPA3HRiTFg5H9xecviMinJrRsPUgOq0nKnadXIgBv2QyYBa+4omanWhqeziaTkjYkN4RKZFZf4buNmjutQz+v1O+tL27TsV8rXUYzUXwtlyRcQABjCoCuKW1gu7TLTJW22atdapUq9meN8OrOsqzfyPymaYppRaiX+grZ89VMZ/mnroTSSZ3IOH2vlZREDF0LRUHF9XiuuGJpxvTVivZlTdEfR8fXePhcpBioly6js+h7ZilOgO5mIr5qto2Evt+IcAHNu6azXdrlSixZkiiEdmmXqpJl2VhSUkP1P4m+DhuZeobvVuvRAQxGE1xwKo5CZxzRpsyKw3O7zF9RTVAPeT+z6+tpDrMsG27Rz62PQCA5jbpuAf613SfLsv7ZMF8q8BkE2mSI7dIuLZa22atd6pUoWDpTfXbnaZeQPgNkx74R8cfoo3oH3wvc1YTpo12ugqKaoJWWygJYCqwH/p8ZfMay6bI9K1DfOhebgiRkiKYBapMhtku7tFDa4KddgIqDZpHxOX6eLPFrmMnndyC8QaZp6kKA0CCicSr6xUxyZSTtbJcZLDr+7gLuyrJsfZZlAyEEvVLUhNXyWG3GjKsaojJz5Eb1Dzo3Z+1BGlcANJSRdSauXQf5dmmXVkrb7NUuAGRZdgTxMbGQcQhmLXMITbOUKNMyxDdrHlAzSOe1HA3VLpWIMIoAaC7HR9BGWflhJPEtwFFkk2mgajxNM5VLaR0k/H0AmNSw+HZpl3apU9rgp12ASm6sG+uEZnciLLZTznzd4PktgSvVDPWllK4Z4r92KS9lAEhNqC0TXqpv2zcCb0ZAyxng9cAF4KMppV9p4h45H58sy5YDO5DNxKxGZykRIrTJENulXeqWdrRXu1hZQ/1IqRlZSDVirLeEj6dVXpRJrtFIqHbJFwM9BoK0TNV3Zxnwb1NKXwb8VkrpK4A/Bt4HfIfmspvIsuxklmWn9PNwlmWbsizbUBzXas79/hAS39dqhVpqiymSIWq0ZNm8bJd2uSpLW/PTLqVFw8Z7cIDRCSybjspe79mHODJ3IgLKHJZ7ajlUqwApCo2e6danXa6uEjVAMVKxxXsYg/T3AluBH0LG6SiwHfgx4FngIvDZlNLKLMvuAd6YUrpLwcOfp5R+VO/XC/xKSukH9P8YQTl7PnRUeJJyZIj6fjmmcptfof7ds2Xebpd2WSilDX7apaqEMPLbZjJsXIVTJRQ9sBx3IiaK8RrXWVqNHJnhbAmOdrlyi46xrwC+dCom2izLehXQHAR+CgH/3w18D6IVMvLPHmQ8jiPA/DICkG4Hvhb4z3rurwCPmxksy7KUUsrULLesCELKzM41yDzjb11l8zR7JVvKl/M7vIElkQyxGNJf9I+aKnBsl3a5kko72qtdqooy3sIM0/NTIH7TxbcZcNXVCl9Lu1zTZQT4a4Asy/4xpfSv6p2sIKQbBzXvzLLsD4C3IADnHYgW6DWI6esT+t0Nes07gC8CLiFj+b2Ij9C4Hr9X8sxuBOwb+DDywz6E2DGea9rXSa3rSqN30PvYb0PIxmJluO40/4X38nt8KvuT7N70QEWbs1KfZX5JRXP3lUIU2i7tMuXS9vlpl1rlLmbep2aqi+rGLMuWZ1mWsiw7Yn4JgdW5Xa7xkmXZkizLjqLAR0t3lmWXsix7qIxRWcHDGgXWy1RT9PfATmAXAmY+BXyp/r2s3+1AHKI3Ap8DvhLYjeQhO6G3/xrgfwMvFB47gpiYIuifVNDSWahfJwL8DfCsRCK6rAwhGtCN+lt/1XUPpGX8CffyO/xRhsyVAuhql3a5Jksb/LRLaUkprZmKWUnTX1gm+Er29RaSTJaVi8C+lFKG7IwtrLiZ/E7tchWXLMuWZll2HFgLfAlgdvzLemTALwE7syx7NILllNJG1XJ2IXnqOoEnkEzyH0Y0Qt8MfAGyERhExnAP8EbgpxHNzzuAdwO/g4S4XwL+Evh5xFzbkWVZp5qbiuZb6syzDqAv+OnYvYzl+jacyygGDOSveyAt48d4Lce4T32BwJO5QvW8bOcLa5ervrR9ftplRkuWZWOAhZ93k3eavnkqob5Zlq0CXgk+CeZv0dUGP9deCU7J/w14E7KJSwjQAQEf5/XvFyPm/YQAk8PAWeCvgHMIgPkW4DlEmwMS6v4KosX5F/rbAQSEr0FA1u3AkwgguowAn29EIq0OAD+u97o+pTRuAEvrPV42bs0fqM579yB0E28ufG/A7I8QsJYLqbfrSFyPaIvWJNKyLMuGzC9KfaWWIfN1vD2v2uVqL23w0y4zVnRH2juT3Du6sA8gPhIrw/dVDqPtcnWXEPX3HxBTVEJAypciwOYLEfOTmaGuA44h/jsgIOkL9PMe/fxJ4DtTSl06fn8a+JGU0g1Zlt0CPBDBRpZltwLv0ueuQXx1NgI/AfwZYjb7BwTkdBfBTD3+oSbAz5A+cw2I+Sr4C30r8OUppV8pRmxFf6BIhkiW96UzgNaeU+1yLZS22atdZrKY0+iUS5Zlg8qlMqSLtiUvrdqJthfpa6OoyWgACTF/N/AG4CngRf0MMAa8hACfIwi42annPIloe3Yi2p7ngG9Axuv3A2/IsmwU+J96/wsaAfXtiL9ZT5Zl/VmWbQAmlOhwJKU0ooC8G1iEALPXItqf11rdw3t0I0Cl7B27a3zfodxYfSiA0XHfq9FhVoc3Ab9g36Gm4XgdQCJNJnRz8hHeHp+l92rPqXa5Jkob/LTLlEoNZ0lT7U/nnh0ppetTSjeG465CSHDFv0GFUtsR+ios6j82AGxCgMg5BFR8BHEofgti0vpd4NuAX0NAwJsQ09MlBOB8A2Lu+Wq919cCH0O0Q9cDX4c4Lh8A3qrnncaJEt8A/DISufVTSr3QrwD9aSSs/V+llP4SMYn9V8SE9hLie9MTxuPrgH8Z3rFXtUH/f3tvHubaWtX5f2qV0KUAAFQmSURBVF69chEVCSJcFQRz5EEU5WKOMjUypWzRbqDBVIuiTHZKRLsF1JQDDqA+KUXwp9LXKpDrDFZE1J9A25VGkBYUKwIiCGIVF0GBy+WGeYbVf6z1Jm927SR7p1KVodbnefZzTqWSPSXnvN+s4bviz7Xk79Fr6ztt65sQrAJ/i0atIh9B65Di66v2+mNr3a+mQkyQLT7JlYFwWMYM0XHWBW91d0pjdT3HiQjpMqxnOI0/SNHIUR39Rt5EUwjblhJpo0WgDTc/XF0sCtJC/3/6FNo6fkfguagQuR8qgj5mf38N8DvAQ9BOrJuh6a4vQaMwf23PfRcqkjpoXdr1qKD5ETTi8zHbnomKnTqaGnsx8I92Tk+3z1v0A3oBGlmK/DTwf+ycng78LvAZEXl8cm1fb3+vAu2YVjN7iTawETu20H9bPdRwcRf13urYfu4QQrifiLwMjXjB6L+f46T252R93CN4Hd9BB3WD3vBxGM5Fwmt+nNKEEA5jrUAyfR00FXCqQskiBmtxdlIIoZZT2OmF0CuKidkm8HZUhNwLHQx6PSpQnoN2Y/0Xe8nd0NET34F2O70S7fr6z8BL7LF/Rn14Hgw8FvgtdF7XH9vPVwA/iYr2J6J1RO8Fng98H9rifkfbz1eLyO1jhBKd9/WyApf2AeABSWfZc0TkbpaSqjMcLRNdzH8C9RM6tOu/RbKvd4rIl9r9utYeexLwIuD9IvIgE05vZvTL7XH67yoOYxWRbesAawGbqRmi46wznvZySmH/eadGhT1LS23PSXAUifz047HTB+34TYoZJzpLQDJT6giNdPwx8HVosfJn0JbxHVTU/B6jwqeGtpO3LC36FWgU5ub2nGO0u+vBto/vRFNjscvrF4F/A56CCoy/RWuHbgH8ICqE/hg1NHwh8CUx5WUFy5+DDgMOcUP9sTYzj10DHFp6q2HnBMPP8Z79+4nFzq+2f1dBRCr2+CbqB/Sl8d5Z7dGd7T48EvhXEzUN4DvTc8j5QtHA/p0IsodGTPcD7v3jXAxc/DiliGLnLI+RZ0iXOYedKb/38P2SY6KnjUY3qsAz0CjIvYAPAy9H00Mxnfk44Ifs5Xez9/h3gBss/fRQNMLyETS9Bbq439n+7Nv++2hU532oYLgGTWt9M/AfULHzdLRt/ibAD6D1QNg5XgF8lYm1x6EiKqXCySHAO7Y1GaZsY8QnrfGZJDyaDB2ZU64wv6JjG/BaIXGBnsCo2zrSRQXWfjRDdJx1xsWPszCsoLWdbLtowfNMRdNpIbSznCSdW4f20JNRAfDtaOTlKjSNs4PWuNRQP5/fsuffzVq822gE57/b448i36wvDs+to9GNtonnfwb+DhVWHTSy82ngCegcr89G01pfgabNHod6+9wVdW1+OJqaa4YQdpNurbyp7m27nkt2Ti1UaIHW97QtZZsr+rMdWxlGhFaRji27dyeElKW8NoFWYoboOGuJix9nIVh9RxtNTXRti6MGZuU0LtLOGWLt2rto11UP2EAX+yegjspfDrzO3v9+8rwd1O4AhsKnhtbrvCyJXtyboSszMIwA2nMGn40QQsOiJN+Amh3uohGT/4tGhG6Njot4N5oSewHw1Wgt0F+jRdi3srTT16Kf3Zi6+xRqrBhpYHO8bNtCxdb/xYaVJinjLpraGgz+NV+h3I4tI0bQJt37tJuswgR/LBNAG0AzEFo4zpri4sdZFFVg2+odunE77T590vtyEcedoEK3h9bP1FBx88/2tNsCl0Vkx0TxPhqZ6KKFyzcwTHWBFj5/CniaHaOKTnH/Lfv9dckp9JIUUxOL/tjvXoGKr19HIx7/gEagBBVjN7Wf348WUfdRF+cvAH4mhPCX6GeuY8aeG2i90DUhhBeYSOuTzMgz8XFzrBPL2uWjoHkUapAYqaGpv/jvopbz+S6V4o0ibOJztOtrA6gHwm6xPTvOauHix1kUfcYYvp1yn84SYEXMB2iKZwcVF1U03fVPqBh5BBqF2ExSWU104e0zFD73ToZxxmjE79jYiAraAv8xe/1dk3NooOMefsL21TDx0LX93BQVUb+Itsc/Cp3gvoEKnI+jEaXbA/8qIjXgp2yfd0OF3E+YgKnbvv8ENWC8Ae3YeiLmuWMi7CeBdwK7JvT6qH/PU9Fi7hfb/p6AisAfBG4MIQhD0Rav78zSvGaGqKMvXAA5a4i3ujsL4SxGYTiLxxb0Fhqt2DGBEh/roO7KP4D5M9lr4myqYxHZsohJnvCpoiaFnwG+Pnn8EBXSG3acd6Apqy5aq3NzEfk2E2PbaKr1GBUObTQK9XrgMXYemxaV2UVre+6YMdm8GhVKP4QKmecA9wTeg43TEJFNE1/PFpFb2DUdAg8RkT8bzNvSOqBvAx5oabQTM7xM1HVid2NsUwfujhZ334qhCIpp5LRmp5b+vqwHlomfGuBeQM76ICK++baQDThY9Dn4Nvf3tImmgkDrXY4Y1tQ0UaFRTZ5fs+c0k5+vB96IFr+PfF6A16ERnPTxj6CiowW8FXgV6nNzLSpu/t2e9+P2uzYqGt5pf38rOgZjNzmfODPrJfHnnGsVtHanh0a1fs4e+0vgkclz6sm9qdjfW/Hzb8eR9Hozr6uhhdrZ4+/an+0p70n71O+r0EQ4REbfE998W9Vt4Sfg28Xc7D90Fz9ruKHFxXEuW3XC81qpsDCxdL0JmWrmuU3UUPAg51gfA/bt50MTLNckzzkw8VUBjuyxl5hougZ4nomNt9vjj0fng/2qnVPdzrORiLiafnccEXnt5Pc3mAh6X851V+ycamPuSwO4MfNY9rrbiZA6c/EjMhBAR0j+efvm2yptPt7COXMsxRXrFfrJn2fqF+ScL5aOifUhOzKmgD1p/66ghc59S439DDq+4gFysrC3itbZ/Fscr2Kvv639vmfHvwsqaP4peW0PTS3dBfhACOEv0FTR29HxGM+0n9+Bzt16NfBU9PP5UhHphhA20K6v7xeR+6eePKLjJrqomDtEC/lvFUI4Bj5haasdGZ3CPqlWJ8/TJ1s0PbZj66wQZC8QjlEvIHeDdlYaL3h2zoM61sYuw2GlmyL+n+c6kHj3HKAGexsThE/s9OrbZyAu4HFw6QPGfC6+CPhjEflqdOHfAD5ov7sS9eJpoVGgewD3DyEcmlB6OPBLqOh4k+3rAPX2eQcqpP438GjU0LAL3AltWX9uCOGhJsZ+G7gqhLArJ93F+6I1TNomHsI/o2Msbm1PiQ7PseamBxyYkEnvzzhPn37mWOnPE79ETPt9GWTUDLF+2v05zqLwgmfnzLHIT32e/wk7i8cW7haaptmRKYW0VsjbRodzdpPHaySFxmOOc4h2V1XRKMhVaGfWY1FzwptxclDzO9CBpPcEvjDzu9eKztd6Klro/Bjg2aj4eb5d16vtmJ/FsJg6UkfTViGz33id9wAeioqqXbQF/plom3sH+A201mggFOPkd4skVe3vx/a7wTy9ZcDGYOwCe4IPEXZWD4/8OOdB7EBx1gSLUESX5ssFhE8bFQ8bZYSP0UYjSn20MLqLtpBfgToxX4+muTZQgfEZtKD5u9EF+nkMx1q8Gx2DcUvrEvsfaH1O1fb5MDQq00VF0xHwv9BI0ZUwiKTsJeefXmcdje48WXSe1lVouuxxqPB5oD31lfbnceZ1cSxF1tNnqbqsZNQM0d2gnZXDxY9z5ojOHXLxswYkQ0irqOjZnlR7Yi7FB2hx7uV0QS8ifOw5dVEDxArqmVNDDRIfjBYm34A6L/fROV2fhRYwPwI1Lvxre85LgdugIuTL0TTYzYGrUZH0QjvsL5nAuQE1NbwCFTsPBq60+qRoTNi1lF+sedpHU1xi3jxfh4qEK+287o36Hv0tJqpCCD+e87rUlXkpx7bI0Ayx4V5AzqrhaS/HcaZikYkWVqguBZy0E3FzIiVWMOJDCOGtqCh5NzpK4vX2q69EU1WfbY/dALwFLXZ+jT3nBjTC8jrgv6Lmg1Xgx9CIyy8Dny8iG8kIiJqdb9fE1guBT9pzmmg7+zejKa3rgL+y6+hOS+vaPbwWbY/fEZHXmrBpoWm03NShRdl6y/wFIoofQbYWfS6OUwSP/DiOM5YQwtUhhFdgTs1WpFxE+LQYiptZhc8LgbeJyJNEh5He2/6soJGf9wG3RFNSl1Bh8x32+HVovc/XoX4+H0OHlMbusKo9FvkNtHbpc+3YFYtoPQuNEoEKpucCfwD8f2gUKUY/qjbgdKSAOUV0hMvtgLcBLwghNGU4jX0DuGcI4Z3JoN8YXaous/CBoegJhIPA+HvgOMuCix/HcXKxAtyXo6MdNooswJbm2kUjGZez4qaE8LkD2p7+WPv5WuC2lnL7XtSw8GaoKPt8dEzF3wPfhUZ4BPhN4L0icg3qyHxXtCsMtAbna5JDfh860qKGpqXqoMXHwBfYgFFQsfNvWB0S0LLuq0373cEkAWT73EYLqZ8QQnhPCOHf7Z68G61fejAqzA5DCNewIpYQJoA6gAsgZ+lx8eM4zgksDfQU1KTvuwq+psqwjX0jWwtUVPgYzwTeIDoeo462tT8XFSbPQedy7ZqQqKFi4kbgX9B6mg+j4iid+v45qFlgFy2CvkNyvB7wC2ga7cVJ4TFAAF5vkZsdrEgZq8uJRc9JIfRhthA6i92b+wF/BPz/aCTqESJyV+BX0GLt3wbefd5+PqfBOr/2UAE079l9jjM3XPw4jjMgLVAG/g/w8wVf10CFz05e7UsZ4WMi6n7YhHMTK/cCXoQKj9uiHV0vMmEUO8EqaAToNmjKKzUTjNPaf9v2+WdopOc29vtPop1ZHwM2kgGqoEXRI1iqCuCOaLosPr5H9MEJk7ugLGL0eNvXtl1T3Ecf9T266Xze2fPDBNAO6gXkAshZSlz8OI4DDATKIRot2QbuM62F3V7XQRe7jUzEJN1v0YgPaETl/cBHQwh1S/38L4au0HcEbgI8GR0u+gkTX3dFC6HvgBY/fzNwL4tifTkawbmznVMULB8LIeygzs7fgkZdbgM8yZ5XRTvGDmMtDtbmbqLlBjTVNsCu8TJqdjgyiX0CVeCjdsw6w9b2udf62HVICOHGGKEy0ds47b4H9wDp4GaIzhLj4sdxnDiNPQqUHYaT2YvwNaiwqOXst5TwsYX/i4FPJymml6KdWbdHRcEVaITnClTMvMNE14+h9Tg3RdNkDxSRJ9q1/Jm9JhYR38r+/FW0zf2rgVeJyE8BTweiM3MDFXY76NiJkYXcBNCVsd09eTwWQlemFUIbdeC1IYSH2vlso8aMd5uWQiuDvc9dM2e8xHD6eyNPuJ4G8wLaBHbdC8hZNlz8OM4FxxbuBlagbAt1XPTT51VMnGT5N9S8r5Uu1DNEfECjO6/AhJd1lsVI1I2WAruEpqc+C60viiLtjsAb0PQVSb1QTCH9IvDgEMIvM0xlvcuO8Vo02oSIPMvOfwf4KuBBdi8ukT+W4nXJfRxgaa0tphRCJ11dL0SjSv9q9+2+aMH3c0IIjRBCzSJhVWanB9TNS+gIOLb9fWKekZ/BPSCJgrkAcpYIFz+Oc0GxmVyHnCxQjvOl+ulz0ZRYK4RwZHOz2iGEfdSDJoqUqj2/tPCxqEQPTWkNok52Hu8Eft8W6Pei9Ui3QIVSJNb4vCt5rG77qqEF0x9H29f37Lq7dq5PyDmlx6Mt9d04T8vETIfRKFcFFWe1TK1QPP9phdBVO0bHzu/nUSH61Wjd02dQ4dZGRenBKYRKjdHITxWN/txi3pGfwfUPzRCbboboLAs+1d1xLiAWEdlFDQs7yeMx6pOdI9VEC4t37HlVTOiYgIgpoZ0ZhU+cE7YxxkfozgxFzOehKaE3Myp0aqjIeEzmsS4qWF6DztqK557WMz0LTVFV0Tqi61E/n29ExVZKn2HHF6iI6tvk94MQQl9E9uw+9M3LZy+EEKNG25laqj4ajakBn4j7s3u7bRPjG7HI2s5x166pLL34ntg5d4EHcMYO0iaALgfCbiDsuhmis2g88uM4FwyLTrRRcZJdQE9EfRIGC2QcWZIInyZm9od2fZVJdaXHHWegGCM43wO8xI5zd0YFTNVe/ybg65PX9VER9FE0JfY4dHbWtl1Lz56zh06X/1rgW61e6Grg7jHSYn8eJwNHB6Mnkjqfp4UQPojWDg2iNHacS2gh9G8m97KHptVaaC3SX4UQ3hhCeHB6bem9n/W9z3lPenZPzsVE0c0QnWXBxY/jXBCsZmcfFQIbOQaEubU+U/ZZ56Tw2S4jfExANKaMh9hA00sfR4VK166hn5xHXMDfDXxJUu/TM5HXBu4E3CppVQcgRrSAjwAPS87/2WihdKwf6mWiNg1Opui+laEz9NMZbYXv23T2egjhz5PHO+ae/YUi8nloOu+PzAW6a9ee3vOvtLTjSA3WDJ1cdbTu6dy8hEwAdXEzRGeBuPhxnAuALYQH6OK9OWaxa6GplGpOce64ItuYVoJhGm1qe3yG2N00Fot27KBt6LdhWGcUqTOauvkrNMLTTdI8v4J2gd11zDF6Fs3qJ4/9gu07RrqyUZcToydsP9vAFjolPm+Bvz9wn2yRdLKPLXQg6w/Ye9ezOqsjtBbpo3a9g9fP2Ml1N7Sb7lwRZAc3Q3QWiIsfx1lzkjb27STCkX1OjPrcCV1Q962wede8ampjxlvsAf8ZnaW1V1b4xMhFwWLbD6GRmQeioiAVFakIAxU/NeCNmX10gM8q0Hqefc2JTiW7L5NEW4XR2qABJqKeD9x1nABCI0evsudvichlEbkkIg8HrrR7dmxdYG2G71vNBNyrQghPYOgZlMetWdDEeDdDdBaJix/HWWNsUWyi3UOT6jpi1Od2tshuiMgle6yLpp3yaKD+O1cCj5/Bk2YXjZAU4UbgLSJyFfBiko4rO98oNB4I/DDa+v61UWBZeq0CfBHw3BIt49HjJ72vFdTNepKwiIaII+3/IYSWvS+vQqNY35g1Q7Q01T+hojNPnHQsCvS16Py1FtoV1kFriirAPYHbMbme5y2nqSE6LRkzRBdAzrnh4sdx1hCr8zgEMDHTn/RcVMT8DZkoQSxqzi6QSf3QE4C/Q52RX4tGHgpFVWzB75RYfO/NsLurSk5Ew/Z5czQyEkTk4VH0JRPUN4E3Fz2u3btY2D14bMo9jSmoHrCXpKxiK3wXnZ32h8DL0BqgVGDdH7gPOuMs75y2TZy+BvjNJNX1HaioejxDr6RJAq1v72VznmaKZUjMEPfdC8g5L1z8OM6akYyp2JtSRByJUZ8PFdx/3fb/RnSi+uPQ6Mg3UfD/lCLF1bFQ14p4D9Eox2MtYnMiImLpoypwD+BTYwwZQdM8ZRf6PZLC5QLUGY7B2E5SVpsismOCrIsKzgejk+qbJkIqqBh4MfCmPO+ghLegY0Cq6DiPTwI/BfwImiKcltKKk+n37B62WABuhuicNy5+HGeNsMUreuzsTXheJYnQ1BmKkGlDR9tYmzw6EmLPIip94AMU7xxqMxxImnecJiqwonHhk4FX2vNbnHSf3gVIirlj6/gJLOJTyiU5Cq2S0ZHBMex+t5OtiUauPoSKoOehHV4/gI7c+DQq4hrAEycc96fRVF4Ufm9D02CHtq9p4iftROuRU9t0XmTMEIvORHOcmXDx4zhrgC2uu6hYuDyp1dzqSQ7RFNX1qGlg9P7pjXlNLU2joQtuJTE9PETTXrdmCraQ18YVXxstu45owngPhrUr1SRSEdNv6aT1OAk+HWCaJY51KENu4fMYdtBIzqEJ0opF4VpoOmwvs9+b2r2/LypGP4Smw96E1gVFZ+0RERRdp63maRuti/oY8CfAVxVI7VWn/HyuCNIX9PPlbtDOWeLix3FWnKSNvT+hjT2lgUaGNtDW7zjEdGvMVPYYTdo2x+EYadi237fRBf0xaCHuNIEwrUsKEpdjI+3m6lv05Gq77mORXMfgLTtWHj0yQ0qnYYKlXqSmydrdN9AIGajZ4bMZnUXWB56KFmZ3UU+gI+Bz0bqlq9C6oHgtk64n8rmo+/VL0BTYSpKYIe67F5BzFrj4cZwVxiIbA2FS8GUVG2Aai3L/zIqaT5geJqaIabdYdGOOzx+4HGM1JDnnGc33PgSDkRiTzPd6md99eXK8LTS68XK0HbySlxaK88bGiLHBHLKSdBiTTsvDUoI7aD3LIxntvOqjQ1EfBvwL8HpUFP4m8FZ0uv2voUXeB6jZ4jTegIq6JvA5IYQD21r2PmSvuTfl54VhAkhHgrgAcuaNiPjmm28ruKFRgEM0DVTmdQf259G416IL6BFaDJt9/DDzWM2e27Sfd+Pf7ec49+sO6AT4P4iPTzjHBrCbPefkeIfJ8RrA0Zj9VPN+h6btDma455Xs9Rd8XRWdGt+yvx+iIvTEuQLXAmLPf5fdz2cCf5++HwyHku7aPWigk+FfZff7zcCr0dlkn0Tdsd9vWzvZT6wXaqGGiAv/bI/cF6GJcIiU+5z75tukzSM/jrNiWMTkAF2Ixw0CHTw35+FqEvXJa2EfFDVLUpeTpLuyoyFip07dzusaRqMjPXRxfTU6if2vLQIxNj0nmn47Ec1JhqbuiNXN2HP7Y/ZzjKbiWpnH+8BdSpodxtf1CqT2srTQVFacMxYLt7Pn+s9o/U8XeAg6vb6Gjsy4JaPDTGt2D+poOq2DRpI+JBqlexoaCfpF4HdQAfUL9j50kuNuoZ+lPTmjye6nQdQM0d2gnbniU90dZ4XIW/zHPK+C1QGZ0DhmmNI4xiao5+x7FxVFl3N2m013DTBRsGmi4JcYppu6qJDqowv7y9Ci3tsxuc09CoS8ax8ZmlqgcHkHOAwhDLrLkjb4NsVNFtP97TM6VHXSe1ZFXbDjnLFeMsV+O2ffvwl8QEReFkL4YlT0/DoasUnpRhEpw5TkG9AuPETk94Dfs/v2GYbpyR6ZkRtSbgjtuSPIXiD0UC+gTWG5z9dZfjzy4zgrQjKmYmIbu1FDRUx0ao7DJI+BF5GJ+iRFzW+RnNohW0DrMr2uKC5KO7YdoCJhG7ipiPwkuvDeSZKC5hBC1ZyPd61zLC2orgNfRo7wMVpMECJ2nGytThv4boZRsMLYfetP8BHK0kQjMumcsdit1szs+2V2LbcPIbwK+H50SOor7b69MnNd6UBXcn6Ox38NGnU7twGm80aGZogH7gXknBYXP46z5CRt7A2mtLGPQ7TwNrZY/yAWdUlSaDU0dfW2MbuYOnw06Tr736hQuQ74NUulNBkKlJ8D7hlTTknrPahI2RA1BYzX+a0MU3x5114vIAZ3gIZdb4tht1cd+J8hhAcn96OImWEZ08M+cBdOFhN30n1Ep2VUvLzfXvMvwN+JyH2B7wG+OITwTitibgP3y+y3LiJ78RrsHsexHjDscEs9iKpmrrj0gsIE0CXcDNE5JS5+HGeJsbRGbGPfkGIGgjDGwTit9UlER0cmtMgnrexjZ0SZ8Pkj4E+B/4oKpYejQgt0kY/1JHcCfpth23YNqy+SzFR1O99vA54fI1VxNlbcgJvZ38dGYmyfe6j7cROdmxUnoH8v8Jx4nmndSxRLFpGqR8dpNIJWn5Zys3OqALcFfjyE8Oe2jyhI6knbfisRcW8EPox2eL3SruH30QnsgnaBHQPfDrwnOeSxHTNG9aKY6gH/AXgQ8I/AM0II/xRCiAXV1XguBT9fC0PcDNGZA8Gq/R3HWTJMnLTRNvZShahxgc5GRGy+1MPRGVB11Dn5QclToqMyDOuE9tGI06RZVu9CO4p+P02NWcTq3cBtrLCWEEJb1C/oEBVJdbQWppPZZ9t+93PAPcal3Ox5UVz1UFEzTsi9H/gNYD9TN/RCtLPqpRnx07RIyiHqg9QzcdG0Y1UKpAKz72nd7vNGUoPURDvvYqqvj4qafwC+Afh5O482Gp37YTQF9L3AdTI0m6zAcJ5XCKGSqXN6OBpVuhL1EfpsVFhvmSDbFfUnWnqs/b0NQ18gxynMotvNfPPNt5Mbwzb2WsHnHaJt0rv22Ik2dnTBfoE9t53Zh6DuwNfaY3H21iGaShl3/Coqjj4MXJ3z+zrwdpIWaqxdm2GL/KOxtvbket5vr3sNWi/zqin3IZ5vvPbmmHO5jqSFPvP7dwIPzdlvhaRd3u5j7LY7ItOyXvD93U/vq513+p4IOvOrb/f4BXas59nxa3Z/3sRQoJY+j3is5O+l2/8XvSHsIuwjs12/bxdz88iP4ywRSTt5H4349Kc8/wiLythrawyLnbOmhTegIuVxMhz/0EQjRF17/UtF5G4xEgE6mHPMsVvoQhy7tlpodKSbPKcCvAN4iOSkzZI0SwMtyu7bPr9KRO4bR0Og0YlJ4zCy93BfMhGMJNK0S45FQAjhWnQ460iUK0ZrZBi52rV7tpMXYbMaqmncC205j8aFsRA6Rn5EREII4W+A59pzuujYis+zn4/R6e8PA+5MyShUcr43isgt47nLikR+Rq6BQZRwQyicGnYuMN7q7jhLQtLKvVd0oUcX3j4MUh1xWni632vQzqaboC7CbUur9Eha101AXWfpj8/BCqzHnOeuvX4gFEIIPdt3Q4bjJhrAnzEcoZFlB430vAcVArtoWudpSYt+moorwgkPIRNRr7ffPd2Os5H8vopOUX+VvQepAKjZeURhVU/uyx7DjjbsPk4UD4ng3EoeawC1pAX+w5amej7qz/NdonVaT0IjZxv2+w/Y759O+Un1kfReVWOqLJ6TbR2ZXlS+MATZtgLoA2uFnzbTzLngeMGz4ywBmTb2osKnyH6fCvwnNGXyiyJyf3Qh2xAdGjoiKkTkv6CRl28nE3lKDBDjOI2t9PcynGcVxQa2r5+wx04UJNvrnw5cjS7ie8ANFiWaaIQ4gSaJiZ8Jiu8D3mcL+KvRVvL0fGLd0R7axt7K/C6efzR/jILzGDU9PHFtYya5g4qbf0ger4rWGcUUWx94jGjx96+gxc33SM5lMOAVeAta+/MUdNTHLKRCYQc4sohiLJzeQQerLnTo6TTEzRCdEnjkx3EWjKVRqkwpKs55XWXK79q23x8DfgB4WRJNmcTdgffIaOFvHY2WdER9gyZxjM7bimmz4xDCDhb9scfTqMK/Ah9FC45H2r8pOXzU9l2X0UGnbXQ0xMftfHohhM9nNBpVTdJgW6gpYvRFwlJcVckfoLrHsKtqgL2X2yEEQdNsXbuPXXT0xO3QKF88xpZF1fYyn4No0vhKRqNxXawTEHVzfnoIoSajhdw1mW6NUI3PEy2qPkbTjOl+OuhnaakjKuJmiE5BXPw4zoKwhXofMyOc8rwDdOGJLr3p37PPj+mzjqVHDrBoii2+k7q27ovWjzzMfo41SBU0wjCuHbpr+2+iC/QGifmg/a4VQngk8LP2eIxwHdhjP4jW5KRTz084PU+hxmjUJ3ZWZVNuXwK8IYRQtyhTGsHqhxA27R4+Lb5WxowRsWvbNXGUrSOKoyfSa6oDL8qrz5Ex7tkmHn8XeEAadQohbNj9vj3aufXqEMLL0MnuoFGsaam4TTSyMyKmLf11mRVDkF4gRDPEbYsIOc4oi6649s23i7gxHBzaLPDcNqODQmtopKHJyeGYsduplhznLxkOM62TdBXlHOuNwBPs7y1yhpumx8r83CQZ2EmmE8qO3YuvY9jtFc+1AfxlZp9R+BXq5GE49LRhPx/Ga+ZkN1Xu0NPkOc9Du812mdDxllx7e8x7t5953hMYdui1ilybXcP1TO68iyaTnybpvGOGQaz2usF1Zz+Dq7AhVGwg6kqdt2/ns3nNj+OcM1ZPEmtHin4rHUQUxNITtsVi42oy7DR1R26hLsHZaMq487o18IQQwoeBJ6IFtVPN7yw61cK8a6xYdsRvRzT68Unga/PmdImm2d6TOg3LMCVUKPpj+9q2c74BrYOJoiulZ/vuhjHOxiLyCOAGe253wmGx97GRk4qsoTVBVes264jIs0QjKpv2fh3a/ZhEDRWmrXFPkGHN1XuB5yTn0p+xXie95127vt2C3WwLR9wM0ZmAix/HOSesAHafocHdXOoRTGgcoLUiW3JyeOePihVR2zG3cvZRAf4H6h1zJeqFcxXqrLwh01uoKySdZ6jgyDNmfC7ann1A/pyubXJSMAXuQTuEcGiFui3gG4HPRV2nByMe4gwxhim3WIs0jpgSKiIe4hiPlJhmPDHJXXTkyLadw8RRGfb+XY8Kx2dMuA9VtIZKC3+H9/FUxcom/rpMSdEuG4kAqgTC7qLPx1keXPw4zvnSlQmjJMaQ2/WUzPxqomIqKzZa6PT3kddKfu3KC9EawL8AHge8OFscbcIhHStRS/+ORjgOQwj3Q9Ml46IlNwF+TPLrW47RhTtdqCYKIRN5HYum7Nji/HHgqSLy/eiiXREtVq6gIrGTHK+b6e5Kz6ePCrL9Au9TLHxOzytOcu9wspg7UqiVX0Q2UWfnrRDC/hiB2GDYlh7b8P8x3sM4u8zet9a0Y2aOvyMlncaXAUH6Yg7QgbBrztDOBcdNDh1nSbDFqIFFURguiA3JdFgl3Ve5nkD2+9a0b+nREBCNlDxAtBNqV7TzqA6Db/15r21nI0KJN83rRdvq867v34HbicjdJpzXASpkutHwr8D9q9m9uwr42XjPLNq2N+E6Kmj9zdhuu5j2mxYBMzHaFZGOvaZqoiX+/siuK051r6L1WNM66LLnEjvyNjO/O0BtCHr2cxMdYXITNP1ZZTgGpIEKs50JxwEVj/15RSoXiZshOhGP/DjO8lBHF65LaGoqRl2yTsVthjVD4zyB0tROLrYw/j1wN9saIYTXAI+0RfRZwLPLDLs0gfF24IvSOhYTBXU0cvGlwG2mpJK2gF0TJhPrbRKadvynoPO7orioTarZMcHTYXI9TawjmtZ6n6a+8iI62ehPm5w05BR2gDsAX5zzuz5JpMxE1i8D7wP+m4hcEvV36qCRoUlRkD1s4CmzGyguFYJsM/QC8gjQBcZb3R1nuYjFvzH9MyBtjScZipmlQMSmynCExhuBv2IYEegD3ygiDw8h/Cpw5wL1Pum+a2iRcPy5gk4ivxXwCeD70cU7OhnnLvyibdwTBUnmuBXUr6aFCrovsl+l4zcmEb10diakJLeA/RDC2AiRRaqeZa7adWzKuj0+Msnd3t+JwmzMMfohhOuAm465jt0QAuhnKQq7a4A/CiFsSPHi8WO05mmtEPUCAjgKhA1xL6CLyaLbzXzzzbfpG7qIH5EMCJ3w3APGtEQzHBzasO0g8/v7oYt2NCKsljzPNvByht5A16Pt4pWc5+YNX02HrMa29deOu26GbfMt4Gdsn/dj2NrfLnLPkue2C7wPBwWes1vwmDdSsoWcoUXAWye9P/Y+NpP3O2tFUJ92Leu8IdQQjpDJw4N9W89t4Sfgm2++TfgHqgJin4JeN7YwHuQ8XreFr00yqTxHfOwmz48iqGlippEsou3MOcZJ4x8ErrXHDoG3TjjXEZFgP9eTfe4Cjwc+MmEf7czzm/ZzNbkfR3YP20z36zlxT3Kes88Y76PkOQORMeV5MQp3RAE/oWTf9TzxOub5A5FDvhdTu+jna5k28/Fp2VT3OkIDoV1GzCQCyL2ALtjmNT+Os9zEmVNF0xUjaZ5kHlcbrSeK87paaFdQ2s0VW8LTY9dE60aiU3HsWqolr2nZc56Gdlk9ieGwz8+Ma1uP+01+P/DTkeGQ1g8C7y5Qd1RDRUt0lI7+QD3RGqodtIaqYR1p4+o9prW+g6a/mlO8eboF9oNou/uWnWMXHQw79nV2zL7o3K+OPTatDqnCMJ26Z3+P3Wvbdl+2Cn6+lomGIDuYjYAgHQre94hoyit6ATWLvs5ZAxatvnzzzbf5bGQci9HIwBEnnZjr5Lj+ootGy/4e3YKjIDrM7DdGiAZRIOB1wEfQyEKMwExMO9kxJzlOPw/4n3YdVdvayXZgf/aBnyt4nyZGgCgW/YkRpcqY31eY4B495T08mPL71BW7xhQHZyxql/NYodTcsm4W+akgyWdeaCLlU3mJG3R70dfl2/lsHvlxnPWhBeyYH88+Q/+fQcFyMqsrd0CnZMwQRaMB6SRxGO1iqib7vRVqLPiJ5Pk9Jg8nHeeMnPIBO99dMWPAuCXnsSsiP1nwPk2bF7bNqM/QCez+dFAhlff7PhPcoyeQ50ad7veYYeF1LFrvTTlOXTL+PGIDWm0fK4kw9rNZqoA82dcGUHUzxIuBix/HWQPiNHM04nCADTWVk4aGMd2VO0Az83N8bbZlO2+B+VngZvb3Z6LuwnHS+diWdslpM0/cmt8G3BN4lP3+tjkpoS9EI1FFOrrifarIBM8aKZhOMvFVnSA89pji3Jw5t9gBN3HkiWjK65K9JwfA2xjjim2PjRvIuvICCP0sHgNY63p92v0bh6gZ4qbty80Q1xwXP46zHvwSOtW7ipr1nXDitcW8LiVa143st+t0enkPuBMaZXoUQzfjy2j31S7T3Yt3sOhPxq35r4CXAG8SNWu8F1prk4qp+5HjYj2BqeIiOacitSNjx1/I0GiwqEdOk0wd1iRE63cuAw9jjE+RDEedHOXN5FoDAVQHCIQ4vHZTTmleKOoG3ce9gNYad3h2nBUmiRY8GnikTPCMMXfhTSnp1GueNd+ARpXeB9wOre/pod+622j04U+Bu9rvbwJ8BfBkKTC8NeugbILhh+147xGRn7LHY0fYZlEX68xxDk1YFXnuwGV6yvMadh6Xx/yuHkVGgeNtFRU/yeuOUBF0iKY5j8c8rzrhd7t2/8saLi4MEyYHglwOhKpQ7r4V2H+TmDp2N+i1wyM/jrOi2OJ/CCAiV00RPm3GpLsKHOM5trDvoGmWV5jgOEYXh98GXoSmoK5HRcvnAY8tInyMQfTHfm6i/j63QDu+sOvcQweUNtCoUtko1rGl1YoM+pxa+2Pn1EHre9pjflcveLweJYe6Ju9rnynRqkmiakUjQIOI5LyFj+0zzkc7ChSO3jkrgkd+HGfFSIqWKxSIFFgUZZ8Js6sKHDPOzfoZtAPrdtiMJLTb6JJFLn4NrfnZmhYxybmmPwDehbbK74vIRgjheQAi8ojkuVVUKPyWiDxxhnvXZOhh1EOjO70xz99FU3lFoleHqJ1AN/N4C60zmjYXLEbxGqiw7DAUNuPek5H3ddw5lLg/KxEBsjRXrHHrCLNdb8Fjxfu8Ke4GvT4sut3MN998K76hi+MRU0z2Mq85pIB53pR9pOaHf44uBlFIxN8N3KNL7rvC0Hzx7cCLGbbcvwAVH+nz45T7Z57ymirAM4C3T3jOiH3AlP3ltr8zQ9s7w5b+wwnPOeHkzRxcm1GTyhfbvlbK+PDM/t25GeLabZ72cpwVIIRQs8hKDf2mX7S7qY1OGZ/5m3HG/PCHgC8TkU0ZtsHHqEgHuDWTh2Xm0YBBce7vA9+QXN/N0UhQShsVgfcpYPA36ZpaIvIk4IPjjAVFo2qFWtZFo0c7DA0E4+Ol297FWvqnPG3Q6ZS8rkv5VGCWJwHfBDwb7dorPNh2XRE3Q1w7XPw4zpITQng5uqDuJKKjyOtqlGgDn0AT+GsTXx/HBpcmE9Oje3AP+DTakdUuUbuS1sPsoX5BA0Tk5ck1xWjEHqOT34vey4qJkCcn9+jfGE5iz2ObgrU4dl79HDG1M+UYeedaZ7of0X72WFKyrivnGvpoWvMP7fiFHZPXGdG6oiiA/J6sOC5+HGeJCSFE+/7LM0Rv2sxnbMEfAv8JjSA9nKFBYoOTbePvlWHX02GJNm9gWJQ7IUoyKHKWodFgmcnvcRTHlwF3RwXJHiW9iKZwYvyFXVe/ZKSqxQThatexYec2V0Skb5GniaaLFw0ZmiHW3AxxtXHx4zhLQOJxk+UWwAfKChiLBhyfJt0Vzwv4I0bdn2OqpQl04rknjsPYwrlFMcGQXVxfn/e6MR1rvwFshRCutWhTM3l+wx6L3V2p4eC7gavJcT8eQ7YbbSz2Xm2iUZlKdh8F73vN9jXx/TORMvdOp+R+Px8XPyNIxgxx0efjzIaLH8dZMEnLesvM6PZDCC1byL8ZuGnJ/cVJ7Ket/QCNHu1JptvJFudPoEW3+1jbsYx67sTRF9Gx+SiEcGB/H9SSmPio2FiOFjogNdbI1JNrOpHCE5Hr7PFH2/HT84yCcc8EQhrd6aHCsp/8PJay0R/JGX9hQqZo23uDGcY0zIvoTwS8mcmpt7L7bYcQJIRwYxR4Jp4LO2EvC2JmiIFw6GaIK8iiK6598+2ibwzFQxVN6/wN8Fbb3kaJzi7b3wElO65mOOc/B65j/GDPJiroHspwCGccdtoa85pa3B/DAZ4HyT1qjnldHfhYul9UPFxr53Bk9+Sddk/jIFYBrkFrmF5o5zxtoOnUoac570Uzc1+mDs+0azq0rfDx5vTeVuw6a4x288XxEbUZ9xsNKuO+BsNxF/1v8FT3S4epHiLeGbdKm/v8OM6CCSEcifrk7KMRiD2Z3Y+nhS5Om2d9zgCiM6ayvxs64w79Z6JP0LGd39RUk6XR7gP8dyY4OVsE6U7A16H1GHV0uvw/iUgvhNAUkb0Qwu8B75Chi/Qhmpp7L/CV9roGWli+N+ZYTTv/Qj44lvYaOC8nPxfyXLIoUX/Wz8MsWCSyISJbdr5tTtZEVaSgU3ay30FxvP3cQD/vhT4Py4x1gLVwL6CVwcWP4yyYEMKBqKHfATp+YlbhUwd+D7jzWS6WUQCg6ZATrtEhhBuBS+k5hBB2bTGtw/RaFntNFa3/eRcTxnLYfesCHwJ+AbjDONGFCpxYe3OcXXRtsd+XCSMzTPiNHSOR8/yR8Rcm1o6luPv1uWL3IN7T3Llp8TM7h2O1KTebbWlxM8TVwmt+HOccsHqWdghhZDCnLYxxEY0L9KzEgukiNSWnoY5Gp7bHCJIuWuwba35Sn6D0PIvwaeDVMrl9O7aEXw98FHWKjjRNaMUIyhYqhvbGRBuiqJvENkktzzTk5PiLHRZYz1PgfGNHE2jHXp5twdw+Y+sgfGDgBaSF7qxeDdNFw8WP45wxyTfpPrpo7FvRbxut8YkRgB7lhEGWCvCzZEz25nwtVbQGZawYsZTbHkOzwybDxb5PcYF3L+AK4KoJ5xOFT5wm/6vAA62INld0iUhvwoIbW9/HIsMC7cLvlaXa6iGEupxhh9a8sHPcTtKag8+U3ddTn38ypmRtSARQy80QlxtPeznOGWNpoqokjr1RRKDpj+htU0cLQqfNgIoOx8e2xQWkYbVDR3m1OHO6ljYaQSlsnBhCqGRSYNUii38I4WVoJOcKxkxXt/OppjVOIYQb0GLsDoCI7Fj6q40uTE27Z1X7/V7ynhwUuXczTpQ/9Yy1RRDFe5K2O/E5TT6TfTQl2LPXjbUSsH8X3WUXgjPdMwZfeDpC8X8rzvnhkR/HOXtOfMNN/sOvmkdOHV2UJy6K9ryqiARbpLfRqEoXeLIV8Z5l8WieseFEsgt9QeFTB74AeB2Tp5XXOBk9eA5wB+DNMvQm6mG+QyIShVSHk5GhQvcuCrGS0Z/c8RcrQJvRNF0fqFkqtxpCeAZaNH5L4BJDJ+vGlELmQiJ4FZGhGWLdvYCWExc/jnP2VMmkCaxIN/rYxK1bIKIyknKwBfUYFQdPQCd6z8Pf5wS20PfOKWqxi4qYKDSO07oTE4xtu2/VKEIselMBvgi4NoRwdXKvjknSijL07on00NTUYUHfmS1Kpm1k/PiLpSQvammfuR76Hu0Ct0e75Q7tKd3YpTZl9ysT/ZoFUTPEDXAzxGXE016OMwfsP/sWwyhPJwn9H2ZTKbN2yyTGgGnK4QgVPWfaLmyt591zOM5IMfGsYm7MvWozTHvlFj3be1Y5q6hE0u4+toNtGYhpQIq35Q+G6K5TF9c8MPFTAzYsKuQsGI/8OM58aKMRmG37s2Ut34fkz2c6jSPsif88z0GQTKzfmONxsk7OM4uDpMh44CRsRby3xIaVjnndmRYky/jxF8tGFRXxRRfrkWiPC58hom7Qe8CBu0EvBy5+HGc+1KyWpCcie6LT128pIpdm8XNJ5mUNFm8jr0Omk42WnAENzraWKJKNGJx2Ad1GUzPxGoCRdOFCkJzxF0tITAPG2WjTqFu0c+26uOaBIHuoADo0TyBngbj4cZxTYuKk7ELam1Ise8iwFijO/BLyh5XuoIvUmbTWxmnonLH4sftRmaf5n92rbgjhGrtHDROUTSZMTD8PLDJVDSE8epHnMeH8+tbhdQwchBB2p0SqouDxSfBjMAG0hXoBuQBaIC5+HOf0zPJNd+wiYiKgaymabYsiXbIOrxP1L4kpXeuM0ig14HOA5hmnaXbRhWHqPSrJDvAtDDvjsOjcMizQW8BTFpn+sihjMxNhHGD36hIqgiYV7sbC83sy7GI8a8PNlUOQLm6GuHBc/DhOAWyBOLAIzJGlAhrJBPXuhNe27bVxO4SpIx5KpXtMAHU5nUP0JP4AXfwOz2KhtrRdJ1NrU6RjqOi9+VF0kGa/yGiN88Kud4/JouLMiFG9xOtoUhdah8mCdBv9t3BvhlHL/XGi6iLjZoiL54pFn4DjrAhNtM17Ixb/2hYfz11QY6swp5jZVQRbtOroAjRv6pixoV17jTmOZ7DF8XuAr8n+bl7RGRHpmFhtlTFoPA/svh6Y+/Nc7muSqowcJwKnwVAkfyA5j54N1x13f1I38rzr6JBJjZqojQNMnQRBeoGwgRZBx5SYc064+HGcYlQZOgZHf5giNTDRxbmM8CkyXwoYLGTRhO5UzsHJvgYGjPZnF4jCp7TJYQEaaBS6sMngjGwB14UQrgJexPl5FhVhG42SzMX92faxbXViGxlRFfe/x9CQMJKbpkqGsc7y/rjwGYMgfRNA+4FQs64w5xxw8eM4xajO+K28C/ySRWay1v9thovNsf2+hy5IUz2AbEGqUWLC+BSak/ZlPj+dOR0ryw8DuyGE3lm1mYtIP4TwB8B3A7ew4y3FqAn7THTQaM1condx7ln6uY2DdGPtWAihyH6q2OiUGU6jxvzF8loR3aADYTcQdl0AnQ9e8+M4CcmoiSyzFm7eBfiMiAQy1v9opGPTzA47DId+bhUUADXU3HBuYmGC8GmQcfotSwihFkLYtxRPO4TQsv02gFeii2RaADr3WhEReTzwH4GHoPd8aepR0uGnc9plnSQ9aSnYXiaVmI3K5EVpaswekaut6wiLeRNFTyC4F9A54JEfxzEsslFJ/t5FIzKn+c//FcAzYRB5iNb/tyVJu8SW7JL77qKRgs2Sr5uFJqOdWLMQ2+XjUNE6Jvbs5wajEa+zXDT7zK+bbJ5sobU1l+ewrxrDURP7aFQvO2etk3RlpeaSKV20k3AX9WAq8770TeCmx+0vSafd0iHIlhVAHwSCu0GfIR75cRwGof2atZVvWog/drd0i0Y8LLpRTyJIDRJRYzUTTeDvOeXiHgt35zknakJnToxKnYaKiHRE5FhEBq38tt82GgVL78nc/+O3dGNsqa8tU+cXDAq843iI01Jn+L71Ge9ovYV+znPHfSR+Pz20Lmma30/Kph0/FuTX0XSjt3iPITFDPHAvoLPDIz+Oo1TJRF7KRmOSGpz0W20cZZDlQ3M67y3UgK43h4W8OuEb+Q66aNUp/+1/0j1rYRGfNCphi+uXzekepRygi3y3SL3LgthBLQU6s0ZIYr0PluZKur9yRXyR41i32J69Z7sUiDgmQ1Cz53bWxe0rjSB7gXCMFkJvWmu8M0c88uM4SlwsTkMNjV5sJ9sOEKNB1cT6P04hb4cQJIRwYzqDqug3YxMMOyTTyqdhtTZHdtzoPXTEhMXIxnbEb/8HcxynEeuessLnALjVPD2FbNHuJg7SS5lSsHsR01+zEo0ye7bP2OZ+wlPGPm+t6HxdwCn8tAuxGx8WIGOGOK86MMdw8eNcKOw/97b9mS6sJyI/M9An8x+7+aY0sXA/8A/AU+znd6EL1Ili6KItxck3+kKRmMSU8bI5Rm/YdqlIas8W0cuooKtNOE4tx903b9HrkThTJ8JnD/hlxqRq5kTFPgt5M9QWikXxeqdIaWYjkKDiNk9Ut2wuXdeeM1acJF2Kp+ngmse/tQtBYoa462aI88XFj3PRaDEsuD2MkQ8mp3yKEoujU6pWQ7RtXV2/LiJfZ1GUV8RUVXRoNsEwNSJh39bb2NT4EvOwqpzS32baa60wdhdNkx0lrtZ59STbdr0HIYSrGaalYt3DPGtD9tCxCweWetlA37OYhmnb+c70Lfu0UbwcttGRIoUjJSbi2nY9cdxEFL0V8geVDq438bAaR7Q7OI14yRNmzhhMAF0Gmi6A5oiI+Obbhdiw6EvmsSo6jXpe+29nHjvI/Nyaso82uki1AQFuRAtzsccbds5H8bkznOPBKa+zMWkfqCAbe/5jXvNo4JPAD2Ue3x33mlO+T4fZ9yr53f4M+2zGz5Fd5258/Czv9ZzuR9vep4NJ93oenx3bzz6jBdD1ef0bXOcNoYJwiIz+H+bbbJtHfpyLxDGZb7VinUdz2v9I1CcvjSLFRis0mJwOa6LfvrelZATntNdqEYM2k9veb0b5dN49gX8Ersw83uGkC/GpEO00u0wSGUk4ZrYW+EHBuZSM4k051w7aLn4m6b8QQsU+R7dEI02TjjOviM02FoVKtuYc68jWEkH6glwGCISFzIJbJ1z8OBeGeQodmxOVHVZaZ7QWokKJdvakGHraQtqlRIFz5hinrWtpM91Y8QNlhIClyW4CfJr8jrvKGU0Hr+ScUw2ttSmVwpJMyjQRqfP4vG2h4uAsfIkG12PXMOl93UNrvfZPY8Ro/w7TpoBtu8alqblaZsTNEOeCix/HmY026sS8gX6TjYtG04qp6wzri4pS56QD74mF1ARB10RDLrEmKBFnbftmvc/pilXrMr0Y+4OTzj9znrvArYBvQmt98u5X3gyqU2HHPc45Xo2ht9PMhejJtc9rTtfcJ7+boKybkK9bl9fYyKSo3090I2/Z52pei2/heXbOQAB1US8gF0Az4D4/jjMbx0n0Y5ehAIrOxVU0NVVGaFQnRVTShVREtm3xGbcgN9FFfNP+jJGTPTmdR8+eFYjHb+rx2/oxw4Lv3EUsKwRMgHwZcGe03X2cUOygxek78xATtshXgc2ckQ8V4LVp5Cpx5S587CSKNxdkOPm9tACbQF9ENk3A1Ip+Vu34nTJ+PwXwIuiSCLITCNosQNgS9wIqhYsfx5mNkTRMkk47ZvZUx7i00LiFNHrB5C2GFVR89W2/czElNNHVAP4SHQ76KNSwMQo+yBjp5Z1/ErW6ksnCJwqQ2KY9jyGZTeDb0eLzbWvLb1k91jFwdQhhIERFR0C0mRAVyWFkrtaciIaW3TlGlAapyRl2ET9b86Ay4zlcaETNEPu4GWJpPO3lOLNxnNShzGUBmFAMXSdf/NRZwHwq++b/OHRExy+jkZO0hiMrtEbO34REVXSsQmw1n8ZcUl9Jy/dDk+vpxX0nAmg3mj9aPdddSwqO6ikjbHn3/djuw1l6HxXC7mOLcoJwEn3UauDAR1+UQ5AOboZYGhc/jjMb0SvoPBhZSK0+4wCNhJzHUNNx/C36bX1aoerg/C3NVE/OextoTKpfgsHC3z9twbbtZwf4aeCu6Tkmz9mRxPwR+F7gbiWLrs+kfsXE2Twnv8/KPtML38uwZ/vbmGNa78IgboZYGhc/jjMFG0tRDyE8MoTwI1br0ES7grITq8+CdPRDGy22jgv0icXHntMC/nhOZnvjuDvjo1Inzt+ET5NkjpcMh2Zigm4Sc2l7t9qW5wNXhRAOCwiqbwT+hRJit6ClwaxsoZGphRS6JnVScxMp9jnwtNcpEDdDLIXX/DjOBGxhPAD+FE2VvA/9d/MO9NtvlcmeN6dGhtPba2i31eXk/CoMi5tBC4g/hqZuHg483s6vUbL4ughfCTxtWjrIinVPCJ/Mc7ashbo57jxFZM/SUJU51Ly8FHg/Nl6DyQKuCtx0WRZn0UGlHSYMKj1j8iwCnCVAkH4gbGAT4WNbvHMSj/w4zgQS75PfR117v0JEbic6oiLOxDqXRdHOpZL5xr9vf3bRBfxTwHtRkfFaTmm2ZxGjo6T+JY4D6QCvKyKopgmfDNN+Xzj6Y+39h+mIjdj2b1GLCnBH4E5Mrl1ZuoXevHEaC5pHFv1+DpYg/eZkcDPEgizaYto335Z9Yziuob0E59IiGb8AHBZ4zcgYDEqMnrDjZUd21IG3UmC0BlqXdDTpuXbsAzhp2589VzQK81amjLywc4zX1ozXknlODXg7cHWBfZ3piIkZPwv1Iu//GR9/39676qLvh28575Gwi7CPlBuDcxE2j/w4zhRE5LIMnWgXfS47aOFvHAVQKCohFnGxKEwZA78TLtWika7PMKUGxqISbbSVvT/hOUdoW/5W5ncnzlW0xulfC1xvVzQ9VGPYmZcWjVfRhfuhohGySRyjozCWykxOhmaXCxkLYfd4E406LrwDzTmJaNqrh5shnsDFj+OsHjHlEecjjSXHY6fsDKo++SJHW2tD2M3rgjLRsc8UDx900dyS/PTZuHN9OcWnvTdtH9lrjEXjU31RZNhiHtNmB1aftAwL/g6LS39FSo1xcc4XQXbQz+9B4EzGxKwkLn4cZ3Up8h/ZSDeWlJ9BlbuoiUhPtA1cv1WGYXdJCeETGecIPe5cn4nWnEyLPKXO1vFeTD3umHPZEa3v2hAd8bCDRoMWKoBMFG6hYu7csfd6XuaTzhkhyB76mT0ILFQoLw0ufhxnBUja7Z8BvAHtVqqT7+6cUshsT9RFuWlFwk07VgVd2CaN3NhD22t3bBDo+4E/QSNDxwXa63fQtu3Cbfi24O8wvfA5FXV9Rv2IdtD5VLvTRNSYc+jZvV/4QmKRrTOb/D4O+3xEkbt0ReHOKDJqhrjwz+2icfHjOEtOkur5XeD+aNv9HdB0w7Q6pH6Bffds4YwjGaqo6NlHZ5hN+1bfAD4KPAQtTH61iYOpc6jseRuoEJkYvcik8OK4i0nsWY1UPM6gpsgiV5fJiVyVYJnSPXHy+3mmNZporZaPVFgRZGiGeHDRvYDc58dxlp8a2sL+GCnZVi/Tzfai4KmjYqFL+RlLdwH+Ak1H/SgMhErRYuzjEMybJIT6hGsczMuS4cDRSb5A/exxcp6zZ545hzYzq4yYWZphnHY/ttFZbxvndNg+KriKCGRnSRCkFwiXUAEUU2IXDo/8OM7yE7/Nn0WU4VQzqMzn5T7A1WgBcadAHdEJTKhMGxmSPdc9ihc+FzmHsvdhacSPnX8HTX+dyzd6EzwbnN+YF2dOCNJH37tmYDHdgovGxY/jLD894LVod9W821X7mT/L8mx0Mvs12W//ZepALOVVY3INUzaS07PXzly/YPfzgNkGdI7rhFsk22gK8VzamkXkeBksIJzyJAKochHNEF38OM5q8GY0kjLXb2kF0mJjsQX2i4FfSYVPTnv9xH2YY3TF/JTGCqYx53raeV9t1EtoltD/HlqsvW+F4u0QQuO8hMeYexTb8i/cYuaUR9QNegsgEPYvkheQix/HWSJMDNQzhat1oG/fsKunGSlgi/NRMvJh16IuDUqkcJKISQ+dMp4936L7iuJjphlEJlrqswgOixhVZ41cmMnfJVRsxPEicRbcwjCReBaDbJ01xQTQMRfIDNHFj+MsCbYYH6LGf7vJHK1KEvXoMcXYcApxxtYl86vpoAv35ZLtyvuoaLmvvT4KqQrl6oiqQMdEX3PGFFaRzq9xxz51i7aJoK7VO23PY59zYItzTH85q48g21wgM0QXP46zPFTQ1uGNzLZl4qCNCp+ZU1UwWtibLNxl6nN20Rb4bdvHnkVAjtGoR5nFfw94AfALMfU0g1/NHjOMV7AC4WOLgs0zSrJwwWHvsY+dcEphnV9RAK21F5CLH8dZckwMHNqPRSajn+W57ALkpani3DFKuP2aAHk18B0hhJoVMZeq4bGFvjdLOtAEnHa9aKRt4cJlXti11X3yulMGE0Brb4bo4sdxlgSLwIzUnyTmg3G46lIKH/t9rKEpe4591BV632qHZgm5z5r6ih1LG2hK8VRt4iY0lqb9HU1/7a6TqHPOnotghujix3GWm2NmSKNYmqwVR1XEx5ixNbuA8BmMOpjxOt+NCpiZohQWQcoWXi+KZaj5AUbGcHj6yymFCaBLqBfQ2gmgICKLPgfHcSZgtT6lXHTtNRV0IU5FT6dsW/c04ZM853iW1nmrt/lO4L7onLB9Gz1Rdj8ttDi8dPeWGQM2ZzluZj8VNEXZQSNAfbRTb2HRoOScig6adZwB1v11AHStKHotcPHjOGuIiZ9u2XEYOftpMuwQ60943pEVPU86nzrDeVhRmMXF+LFo2uoeqIiaNrA17xgV4HDSeYx5XQONjMylnsrOo85w6GmVYepyIbPALPrXPq24cy4mJoDaMGiLX3lc/DjOGmKipXeab/pFhY8994gxkQVbePsi0ouzuEIILRHZSSJU26hIOD6NALEIVLeMeLJz3zhLYWL3cmZPoTmdgy5e7sjszEjiBL1tDtEri9f8OM4aYu3n5yJ8jC20YHk3W3djhdw9K4g+tt9HoVEDtkWkb5PWT/sf6h6zFS2fdUHwMiwUO8CjTzMOxLnYWNSnzxqYIbr4cRxnhBmET+p23EMND/MESNPScKm5YI85juwwwVcpWfi8iXZEtc+wK6rG2QymLXNv+sB1qEh1AeTMRMYMcWUFkIsfx3EGzCJ8UqyY+jKZ7qKcTrO6PX8bnUR+OEfhUSr6Y4Jpw348PCNfnBolptyfIR8keri4AHJmJDFDPFxVLyAXP47jAMOiWM7GSLHJcPHvMywGjgJIv0nORwB1gFIDRi3tto0JgzlfezzGQiM/yXlEDxcXQM7MrLoZ4hWLPgHHcRaPLYK7zEf4tFEBkrIX92v1PyMdI1YEXUU7vmaZsJ7uqx9C6My4rwpnE6E5DiEcosJve9Et5/YebKPpvnNxDY9WBDm/OnVXorMYBOkFQhRAOyaIVgLv9nKcC44Jn33m4ANjbeNNc0wu87oq6kUzl3Zw218pvyB7zcE87sOEY9Q4ZUfbKY9/kL43p01zOg6MeAHtrYoA8siP41xg5il8jDZa81PmHOpo1GlrXqkhETkOIfRDCPUiUYXEofpMozKLjvjknM9eCAE05TizAJrk4+St9euPIP1A2MAmwq+CGaLX/DjOBSWEcF/mKHySDqvC+X+LFLXtHEobG05hj+LzvpqU9AdaF6xIfeaaKxOvHYuy7VhkqSMiGy58Lg7m+7MBVBM/oKXFxY/jXFz+FHjJvKIRFrXZAlpW31GENhrxmXtEJJn3VWRB76NF0ms3w6gIJoC6zGA7MMXHyblACNIXZBPUEHGZW+Fd/DjOBcQEwZuAB83T28YWwo0SM762Oduuow4F2t5t8d9gxsGv60CM0sRZbjOQ5+PkXEBWwQzRC54dZ42xb+Fx8T9GUzvHmc6b/iwDSed4jjU4m3qYWed9rSvZgucxz5k6yDbnNRW0wHzD0mB1T3k5Ng1eC+qXbByGR34cZ73ZRb+BxW/kuzbLqo6OO1g4NtbiTAqBrYC3a7VFTgGi6CkZARrr4+RcXBIzxKNl8wLyyI/jrDEhhMO8dm/7pt5GF6m1bnO2SERTRGsRLjJFIj/2vGHrskxvXQ4hVNLPUAihuiymjs7iMeGjzRUsR8ejR34cZ02xBayf83gT9dQ5FpHL6yx8QOuQgFrJeV8XGvtMbADNIkXg2c+QCx8nxQRPNENciqYC9/lxnPWlRkb8JKZ2ay96MrwKeFEI4afQuqeLdO0zYU7Z6t0SAkUiQI4zDnOD3kAFEIs2Q/TIj+OsOCGESgihblsa3chrOa6iXiwXbfF/B9rdVkOHl3oUqACZCJDXTTmnQpBj4ueJUNpWYZ54zY/jrDghhAMg5tFrDEVPFa3nOU6eWwfaZcY+rAtW6L2BRr56F9HQsGjNT87r5u0E7lxgrP19F+hbW/y545Efx1lhLIJREZFt2zasrXtTRC5lay+s/qVr4wguGh1UENYYikWnAD4J3pknWTPERZyDix/HWW2q5Czkk9Ja5r9StyjQ2mNpwTh76lN2D7wgtyQZAXTtos/HWX2iGWIgHJ63GaKLH8dZfWap39kCio6gWFlM9BzajxvAt6ARIGcGEgH0UK+bcuaBDUHV2XLnKIC828txVpsTHV0FqbPm85eSWqhBZ9u49n+nODbH62/QCNBae0Q554Mge4EAcBgI5+IF5OLHcVaAEMI+o3OnetgwTjSiUXQ/VdTcsIJ+g19L0lqozK/20EW7iYq/PjqBvPB/thZNatlrN0wMVNCRDmsZVcqMSQFdO94DvDGEsCMiv7Loc3RWGxNAPbQV/swFkKe9HGfJsQLTqhkSXrZOrQ46TmCjaP2KzfM6QH1u1vobu92TSnZoq43SuIQKvw4qgHaLFvGaaOqKSAAuMRQEjXUVPqD3Mymq30a75R4E/DTwyHkOx3UuLhkzxDO1VvDIj+MsPxWGc5OAQddWYWxxb3CxzA07aITmxIDNOPPL7k0VTQMW+aY5mENmJoBde/3K39OkKLyCisKYIuyNG1IqInshBFBRfeHsE5z5kzFDrBQ1Q7R6oSYaIe+gn98a0MmLInnkx3GWn3kUllbQRWzlF+milOhqq1OwCDqbHrNoTzrUcyWxe9SxqOKOeQF1LEI4cTq7OT/3Sg5CdZyxZMwQizZmNATZweogBYnR8dzXu/hxnOUnz6m5FBYpql9Aj5ZtRmtVRrD70T9t6/uqi0oR6VrtUg04tmjW8YTnb2d+nmUSvOOMRRi4i9cLegF1LPpTSSI9VfSL3wlc/DjOkhBCaIcQjkIIB/b3OFKgwXwiC9Gj5SLVZ8T0zTganKL13UTCOhkmNk0ol07luQBy5o2ZIW7AdDNEE0t1Rv+vrDHm/04XP46zBFjaoZoU4/YYuhFvzcOUz1I2e2i319pj9/TArnkSpxGDRWuFlh4TxWmKtbQJZiKALsRnzDkf4giMAmaINSxiac+rM+bfv4sfx1kOBv9oRaQvIp2ku2Zu9SQisoNGO9YWG/B6ZNe5OaULaw+ohRButIhbbIMvSnWN3KLT2qU++pmchVhrVeY+Os5ETABNM0OsAwR0hiGwaRGhE3i3l+MsBxVmjCCU8Z2xBWktIhVj7kXD7kWhAZwmXDaT19eBVgghFvJOY6VrfTLsxdol+wzNNHDSuuA2gIMS99FxpjLJDDEKIkF2AqE6bWCqR34cZ3kovZAW9Z0JIdTM8bjBGpsbotGK7Vknj8fBrxRMhVkkbS3IFm2fJqJl+9JuHY8AOXPEWt+30Fb4NDo5qPexbrGJeOTHcc4RMxqMKa4ewzRDA5hlIZ3qO2OLTxMVBSvdkl2AY04WPZZl3QXiuZBEgA5DCP11NoF0zhdBuoEQzRC3GaZpK4FQF6b/PxdEZNHX4TgXAmsjbqMiJxpwxW8unXmlBywNtpPMszrigpgbWrrvkIJpr5zX14C2+dysHSGEg/O+Nrun+8z4njjOOCzyswvsFTVDjHjkx3HOjwYqcuK3kjP7JnwRhM6467ZalV1mcxw+Veu7cxKrH4o2Cy6AnLmRuEEfmBt04ei51/w4zvlypp1BY3xnOlyQ9nYY1O0cn8LQsXrBvJDOHBM8m6xXgbizBMxghgi4+HGc82QeYyqmccJ3xtx4q+MKT81QUazdu2aPVaxzapWZRcDEb477GcPJtRFDBcZ9nAk2VHZdbAGcJaKMGWLExY/jzBnrrGqZ30y6aNbOoeB4nO/MJtrCPbKIr9uU8hBCNYSwD+WHv9pr+uattJEYTsaBiY7jLDGJGeJUAeTix3Hmzz66YNZRr5NDKzo+DzGRm1awGqAeJ43relEkxEnnqzil3CJVu+i974rIXLq17J54tMJxVgRBtqZ5/IAXPDvOWXA8bRL2WTHOd8Za7KvZaEjelPLYLbaI8z8Fh2iH20zGfFPw1nfHWTM88uM4c8RqZpammyUZ9VBFiwILsYLdYsdn4SQ8r6nvjuMsFx75cZw5YpGUpRA/iblh4fbiFZ5SXgkh1M6gjbrB6QwTHcdZQjzy4zjrSwOb9VXiNas6pXwb9fYZy4xdbX10SOdCOqQcxzkbXPw4zvrSx6Ycl2Alp5RbLVNvQjv/TF1tVkPVQWdUHVj7+/46tb47zkXExY/jrC/bQNtSWUVZtVqflB002pXHzF1tIrInIptJ+3sPnRzvOM6K4uLHcdYUi+Bso+3fRV+zal1eKWOjMXldbWj0x+t5HOcC4uLHcdYYW+THpoPWAavbaaMir5TFwIxdbQ1g7p1l58Qq1nM5ztxx8eM460+f2UY9LD0meg7tx8tn3dW2Bq3vx6x2atNx5oK3ujvOmmJFuS206Lmwx8+qYNGsKip6yi7odWZLea1qNxyg9UuLPgfHWQY88uM4a4i1b8eIyMYKmhYWoQp0Zry2WbvaemjrezNndpvjOCuCix/HWTNM+LRQ0bO9psIHNHIzay3TTPfEOsa2UOHVYDj9vTbL/hzHWQxBRBZ9Do7jzBGrg6mc0ZyrpcImuPcW2aVmYrN+Ee6346wLHvlxnDXDhqpWpzgXrwtbqAHhItNPFbyI2HFWCo/8OM4aEsXAGqe80mtto+7NC/HsCSEcovPTVrUDzHEuHB75cZw1RET6F0T4VIAaC4q8rEHru+NcSFz8OI6zklir+yFa87Oo9vMaK9z67jgXFRc/juOsFCGEWgjhCBUeG1bjtCi6QC2EcGjpN8dxVgCv+XEcZ6UIIdyIih6PuDiOMxMe+XEcZ9Xook7LjuM4M+GRH8dxVgorcj4QkcuLPhfHcVaT/wc7ZsgomuP/zQAAACV0RVh0ZGF0ZTpjcmVhdGUAMjAyMy0wMy0xOVQyMDoyMTo0MCswMDowMB7lkC4AAAAldEVYdGRhdGU6bW9kaWZ5ADIwMjMtMDMtMTlUMjA6MjE6NDArMDA6MDBvuCiSAAAAKHRFWHRkYXRlOnRpbWVzdGFtcAAyMDIzLTAzLTE5VDIwOjIxOjQwKzAwOjAwOK0JTQAAAC10RVh0aWNjOmNvcHlyaWdodABDb3B5cmlnaHQgQXJ0aWZleCBTb2Z0d2FyZSAyMDExCLrFtAAAADF0RVh0aWNjOmRlc2NyaXB0aW9uAEFydGlmZXggU29mdHdhcmUgc1JHQiBJQ0MgUHJvZmlsZRMMAYYAAAATdEVYdHBkZjpWZXJzaW9uAFBERi0xLjVTNlrBAAAASnRFWHRzaWduYXR1cmUAYjBkMDRkYTY0YjZhZmE0ZjdhNmYyMGVlZmU4NzFmYTgxZDNhNmYzYTI0ZmExZWQxMWE4NGFhNzY4Y2E4MzUxN+6uWZIAAAAASUVORK5CYII=\n", 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