class: center, middle, inverse, title-slide .title[ # Dimension Reduction</br>Manifolds ] .author[ ### Anastasios Panagiotelis ] .institute[ ### University of Sydney ] --- <script type="text/x-mathjax-config"> MathJax.Hub.Config({ TeX: { Macros: { bA: "{\\mathbf{A}}", bC: "{\\mathbf{C}}", bv: "{\\mathbf{v}}", bw: "{\\mathbf{w}}", bx: "{\\mathbf{x}}", bX: "{\\mathbf{X}}", by: "{\\mathbf{y}}", bY: "{\\mathbf{Y}}", bw: "{\\mathbf{w}}", bW: "{\\mathbf{W}}", bK: "{\\mathbf{K}}", bz: "{\\mathbf{z}}", bU: "{\\mathbf{U}}", bS: "{\\mathbf{S}}", bff: "{\\mathbf{f}}", bD: "{\\mathbf{D}}", bL: "{\\mathbf{L}}", calL: "{\\mathcal{L}}", calM: "{\\mathcal{M}}", bbR: "{\\mathbb{R}}", bB: "{\\mathbf{B}}", bbb: "{\\mathbf{b}}", bLambda: "{\\boldsymbol{\\Lambda}}", bDelta: "{\\boldsymbol{\\Delta}}", bH: "{\\mathbf{H}}", bI: "{\\mathbf{I}}", biota: "{\\boldsymbol{\\iota}}", bN: "{\\mathbf{N}}", bQ: "{\\mathbf{Q}}" } } }); </script> #Outline - Topology -- + Neighbourhoods -- - Geometry -- + Riemannian + 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DcIv5hpgz+g7is+G3CVPjmq0j9+6aG9+QahPoby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\npL8hJBy+IjPaPwJvfD3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2 1\n// File 1 is the vertex shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\n\nattribute vec3 aPos;\nattribute vec4 aCol;\nuniform mat4 mvMatrix;\nuniform mat4 prMatrix;\nvarying vec4 vCol;\nvarying vec4 vPosition;\n\n#ifdef NEEDS_VNORMAL\nattribute vec3 aNorm;\nuniform mat4 normMatrix;\nvarying vec4 vNormal;\n#endif\n\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nattribute vec2 aTexcoord;\nvarying vec2 vTexcoord;\n#endif\n\n#ifdef FIXED_SIZE\nuniform vec3 textScale;\n#endif\n\n#ifdef FIXED_QUADS\nattribute vec3 aOfs;\n#endif\n\n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\nvarying float normz;\nuniform mat4 invPrMatrix;\n#else\nattribute vec3 aPos1;\nattribute vec3 aPos2;\nvarying float normz;\n#endif\n#endif // IS_TWOSIDED\n\n#ifdef FAT_LINES\nattribute vec3 aNext;\nattribute vec2 aPoint;\nvarying vec2 vPoint;\nvarying float vLength;\nuniform float uAspect;\nuniform float uLwd;\n#endif\n\n\nvoid main(void) {\n \n#ifndef IS_BRUSH\n#if defined(NCLIPPLANES) || !defined(FIXED_QUADS) || defined(HAS_FOG)\n vPosition = mvMatrix * vec4(aPos, 1.);\n#endif\n \n#ifndef FIXED_QUADS\n gl_Position = prMatrix * vPosition;\n#endif\n#endif // !IS_BRUSH\n \n#ifdef IS_POINTS\n gl_PointSize = POINTSIZE;\n#endif\n \n vCol = aCol;\n \n#ifdef NEEDS_VNORMAL\n vNormal = normMatrix * vec4(-aNorm, dot(aNorm, aPos));\n#endif\n \n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\n /* normz should be calculated *after* projection */\n normz = (invPrMatrix*vNormal).z;\n#else\n vec4 pos1 = prMatrix*(mvMatrix*vec4(aPos1, 1.));\n pos1 = pos1/pos1.w - gl_Position/gl_Position.w;\n vec4 pos2 = prMatrix*(mvMatrix*vec4(aPos2, 1.));\n pos2 = pos2/pos2.w - gl_Position/gl_Position.w;\n normz = pos1.x*pos2.y - pos1.y*pos2.x;\n#endif\n#endif // IS_TWOSIDED\n \n#ifdef NEEDS_VNORMAL\n vNormal = vec4(normalize(vNormal.xyz/vNormal.w), 1);\n#endif\n \n#if defined(HAS_TEXTURE) || defined(IS_TEXT)\n vTexcoord = aTexcoord;\n#endif\n \n#if defined(FIXED_SIZE) && !defined(ROTATING)\n vec4 pos = prMatrix * mvMatrix * vec4(aPos, 1.);\n pos = pos/pos.w;\n gl_Position = pos + vec4(aOfs*textScale, 0.);\n#endif\n \n#if defined(IS_SPRITES) && !defined(FIXED_SIZE)\n vec4 pos = mvMatrix * vec4(aPos, 1.);\n pos = pos/pos.w + vec4(aOfs, 0.);\n gl_Position = prMatrix*pos;\n#endif\n \n#ifdef FAT_LINES\n /* This code was inspired by Matt Deslauriers' code in \n https://mattdesl.svbtle.com/drawing-lines-is-hard */\n vec2 aspectVec = vec2(uAspect, 1.0);\n mat4 projViewModel = prMatrix * mvMatrix;\n vec4 currentProjected = projViewModel * vec4(aPos, 1.0);\n currentProjected = currentProjected/currentProjected.w;\n vec4 nextProjected = projViewModel * vec4(aNext, 1.0);\n vec2 currentScreen = currentProjected.xy * aspectVec;\n vec2 nextScreen = (nextProjected.xy / nextProjected.w) * aspectVec;\n float len = uLwd;\n vec2 dir = vec2(1.0, 0.0);\n vPoint = aPoint;\n vLength = length(nextScreen - currentScreen)/2.0;\n vLength = vLength/(vLength 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mvMatrix;\n#endif\n\n#ifdef IS_LIT\nuniform vec3 emission;\nuniform float shininess;\n#if NLIGHTS > 0\nuniform vec3 ambient[NLIGHTS];\nuniform vec3 specular[NLIGHTS]; // light*material\nuniform vec3 diffuse[NLIGHTS];\nuniform vec3 lightDir[NLIGHTS];\nuniform bool viewpoint[NLIGHTS];\nuniform bool finite[NLIGHTS];\n#endif\n#endif // IS_LIT\n\n#ifdef IS_TWOSIDED\nuniform bool front;\nvarying float normz;\n#endif\n\n#ifdef FAT_LINES\nvarying vec2 vPoint;\nvarying float vLength;\n#endif\n\nvoid main(void) {\n vec4 fragColor;\n#ifdef FAT_LINES\n vec2 point = vPoint;\n bool neg = point.y < 0.0;\n point.y = neg ? 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XBFz+9QNW/tT8HYh7Bu/ATwDQnf0E5d/lAek/bQGCL8UBmLxbBHojLQJmT\nakHCxiA/8/WrQKAHTEDn/BLAz3WYQK25f0E9s05Bq+yHQHNhbUEZiLxA5hVJQeHDBkFspAi+\nO9YVwZhLf0Gz0zrAp6zFQDgrP0GIh7y+dykFwbsP9EDTOLPAP3bDQJ1P0kEO1RNANBslQYC4\ntEF8tQRBOoSaQMcHS0GqaKRAa8t3QJMotEDzvCnBfa8KQeyIvD9ynCRB7POMQCaBv0F01lFB\nMMiuQOlPU0HK8yLBbNCjQNX69EDkmJlAyX4+QQVs10GOh6dAJ6AAwB9/RUHWfCrBFYzowJdI\nOUHYFp1AUFFfQI+V7UGQoITAHAUxQJzZikFR3i3BYY6TP1hcRUH9aZnAeXykQNGDT0GtC5xA\nkRgJwa1+OkGycqXAhc98P0u7LkGuYpbAqSFIQVD8D0FcVytAWrqnQD2oqUFxWZNAcdrrwPmr\nij0/WZlAMa26QB7e4EDJimVAEgHnwGjkvkEDkZ5Ao75EQVYvqECgamBAaroQwY2sm0EbJto/\nnZwBwb+hkEHSYrrAZpkWwej0jkGlwky9VsdGQcErH0F8zbS/b2bMQOUDf0FuakFBelhjQLf7\nMUG/wcxAsecawPZSNUGlvvhAJKPUwD9DN0AXpLdA7VDYwFu/sEEXovjACBT+QEumGz9EnS5B\nh9VCQbOXAUFgyoJACG2QQNpGdEFFB1JB8L4XwcHtpkCO1Ia/qdwNweMGXUCAzRJApzTLQBBU\npEHc6os/xKAuQcP+Y0Gzn+1AFnFnv6FTikFn9SzBOE4hQfKOm0F5OM/ApZWUQDLXPEF0I69A\nE5kSwbqDpUE+S1TAvZLKQG2Ms0HjoBo/yyzHQAkq5EC34Q1A95XowMsD/ED6951A5eqdQK2B\nI0A2E6FASL9vQLDBzUDC1YPAVs9fP+cukUGmt2FBkmdGQdaDyEHJjVq/nLm/QG1vX0HBT0pA\n+rkfPhwof0EkmZjAFJUOwa4230GA4YvAhH/+wLkkOkHb6MTAKBEWQYZH7UEwAOzAbpVJQZBn\nnD+Hu+M/RfnaPrLSgkFjt19BnvXewLu/QUFVdatAnDLAQJllA0GJ3Ki/cugNQSvhuEG3uSBB\nY+tXwHGGD0BZhCHBnQawQGxreT/tlQXAiuWWQI7VxUHFrk9BblN5QHThzEE1Z3rAtpAAQUtz\n30HvEyxBk5G7QFMkdUHzfrK/l9TCQCjxnz/74Ya/jLuxQK56p0GvkCHBBlmPQNdqf0CY6FBB\nxfIFQNS2nUCjMulAX0hmQPQ5QkCMYIPAJCTGQKvAoUAciAJAn5qRwBMsMEEcUBfBDYZzQIdk\ntkGeYcJAR/w+QTljq0E7BjvAtIbBPxQJx0FG/JjA6TkDwXYwukFpqrTAGwU4QTrUdj9jv8dA\nmlsHwUDys0ArjKPAmTwRwfCtT0AlNt4/kt7HQCggH0ELTLo/COBCQb2bwEFlloFAbombQD1k\n+j+eqSXBbpUVwSAgdEFqbu2/irbmQPTJgUCiChHBqFQfQSDGq0ErTtfAatNSwOom2UFcriLB\n0urmwHdtoUH6xejAJJQVQD2mIkCKapPA3yNHQYcoD0BkOyVAbUDNQEXjrkFUH0o8xnqgQK5X\n5EE/JzfA/nSFPxKeokHNaJjA2q8JwVZ3z0HevZ3AcWSNQM9Ye0GAFLNAkayrwJ6XrEE6VdVA\nW+KtQDu5NEHqDAnATpf3QFTbEEEhQwzBtf+JPzYa3T+NITHByQ/6vQhTjUHjATDBs5gOPomg\nt0EcpGBBEfOuQDVVqkEC6grApmCJQKNAqUCrB2bA1+GEwNfAuD5DwRzBULEtQfhEkEGpP6rA\nfGFbwJZnrUEYffBAGG3JQFa5ukDvt46+dXoXwSSlQUEbv7K/Phe4QGZezEFqNcm/KLnVvZ1/\n2UHlgfxANPXIQLkXuz55Vt0/UWaDwPE8DUE1LxzBdfs+QBn2fEGHUovAQmj6v+C+70GCQyrB\nB9CAQBqtM0CEDsJAEM4/wAbF3EBNZiXB4fZ4P5+xDkG2D/VA82cOwZthgkHrzBFA5UlHQYU4\nnkBfz4i/Qz9fQNl4HEEOOlZBus8KQRnpzUHGeCRBxqIaQTUiGkF9xBNBFxo7P7J0rEFKGJnA\nlka3wG38xkE5EwrBMxM1PxKa3UHX8ZzAQ4/kwDtit0HvpevAvZLLQBtpDUGnB8U/0IOjQFNL\nyEAxwSjAQVi9QCtRCkEtC1BAGb7wQL2OtT+aiQ7BTrvSwA4O4j+yrLZAzGqQwDUUuEFJhRbB\nSqLfPtXURkFHV5rAEwUAQNXp1kFkjO1AIT8yQVDchkAB0ZrAG+63wISYvUGnDAvBo0YVwUb4\nVEF68EvAxSO+QNDFz0GR3JK/tnG0wE+mO0HnigvBPOnywPTnXT/CK9PAPALFQPKUvkHhli9A\ncs/DQFg4eEHS6j+/VSA8QSgYTkC/QblAQAYoQIgM/EA0kJDASxZJQQMaskE4aAM/oh/XwPL6\nzkG6t69AEZULwWYw40GmyiFACQY4QXvp+ECs9MpAIEXzQHduIUDC5Q7BtTTKQHswcEDYeBvB\n5TxDP9aXrUGZNGFBHmZdP8r3zUHdHPdA56hJQbzYwkGxHs09nCkBQFShgkEJVS/BCX71QEKl\nc0AvcDRB9YUDv0RK9ECtQy7B5cYSPzASnkH+519B8LBoPxlnOkDVP5zAfHUWQRQyCEFcM+rA\nOvfEQCpe1EHeIidANSDIP0P1vkEf1l1BNvuwv7hyVkHvaCzBrqkUQX2U2UHTjOrAujwuwFqD\nDkH+HijBW2yhwCLDiUGmi9xAIbBIQfxPvkEIVipAeIKqP2pBLkEm4DDB4S4XwQtNsEHybPm/\n1zG3Pzbos0GMZfRAK+ykwKDDCkHVO9ZAGvHqwKg0tED0/J5A2yXEP3wNuUEn/JjAOFdmQLVd\nkkG5HoPARQ2lQHqTgUD+LCDANDMHQPkknUEa2ZTAmbH2P9JXIkFow+pAUbNDwLX16EErDvRA\nwyoPwYACv0GGGAtAYQhTQP4JJUGwwldBTh0+QXlsBkBKhkzA/mQqQVt140HgLrnAYskWwee/\ny0GipAU/fbo2QX5mWUEL8ojAXu4Uwekn70DH0EE/xNvyQN9bl0ECszRB1cqMQEX0o0HHz7RA\nSnuAQJm3kkCCbnPAeUEXwc2jhkCXR5K/R6ooQKGGp0HO4Y3ANcCqQKKLYUHoXxPAbXmhPxT4\nMUCGq5fAJOjGP3yMFUGf1l5B4ywLwXFEWEBQTCJA37B2QHKAG0An43bA/SXNQKrbr0HWeTY/\n7SpJQfygSEGqqJw+V3vIQFJSbEHJRRw/OYwjQHdJ7ECio5LA/xYHQVKzm0C1wAPB7Z7FQJhz\nbEH+YGQ+NiOjQCnNfUGUIJ1AZ1LDQJiA10GBziW/JMs+P/e170HFUmBBgSNSQH60PEH5n9RA\nLg6EQJ20wEDEFFJB+suiP4GhckHfpPJAbyoNwRh4NkGFaB9AEUurPlNciEEIGpfASgr5wONl\nE0FS945A8LcwQSevv0AyWt5A2PMSwTmrx0GqjUTAj4SYQF+SukEB4kbASGRAQaGXBEACIzLA\nrbDLQF/wikH4LNE/2hrMQEh4vUFqV5Y/UyuYQEzFckAf0ifB17C0wABW40F5X85AjOUgQap/\nakFHD9XASwV3v5F9XEF8Oy3BIDIEwQpJekHNW7nADX0PQdGzQkD6evPAL8IpP2oMi0Gt75nA\nPMwYwTCC30E37bW/TEs3QdAojEFnrchAgLrxwJZpQUH65ZdAmn7NvwkygkF0Ev9A+wzvwAq9\nM0ExvZlAcVc3QY+5nkFQs4TADLbMQIrAvkGEGUBBC8Q2QLhe7j6lKJDAgz85QYcJtUEVt8ZA\nV8HDQFo3F0FqwS9AJKKeQJT6gEC8eaFAr/3lQNIsUD9SZDhBwzn5wDP7rkE2DYpAMYZAQQGI\nukAdV5RADSEAPzfTvkENnDHB5Y2OwChjg0HML+VA1awuQayx3UCMTO9AxQsSwSiExkGGXWjA\nPgkVwTFRzUDuTUY/4WFCQJ3Po0ArR9ZAOY0VwfrgckByzTc/N8XIQO6YzkEvrhrBN8XswIQj\nGEFHv9vA+/e/QJZlpUGLTUJARahCQckxr0BcRotADX+4wGx3skG0MwnBfn4UwQYAzEGrmkXA\nXKq8QLXin0Fg/8W/TF+2wNeqNkEtAAvBk/+7P0MM7EEeTJjA5TN8wHbnvUEbEu1AbaRFQD66\nkkDY2YzA9Z71wA8uoUCXtdPAjsoSwaEVL0EcFGfAAgu+wJCmlkDR4MRAD3eeQBG9pUEv2DrA\njBzBQIyFekE9UU1AtmOGQNfwIkE9vLlAkUsUweyuskEzaks/7hnOvjW/s0FhDS/ByxzwP8Tp\ng0EK3pbAmo4/PGS+rkAGdftAuaAJwXGxtEHx1z5AznZKQZKAuj5AUOo//ucPwZDF30EsfHHA\nx+gAQWHwbkE9ui5ByHHUQKjbhEEqfBnBse1BQT4LjEGqLCPAV7kVwZS4oEE6zRY/t0EXwY0Z\npj9CNim/uZUUwayBkT/y1IM/BLXFQHvKgUGeJwi9KXIWweYy3EFOf/a/OPqxQPD4kkEenAHA\nwXo2QT7E5EFyi4PAw+oEP7FT50E74JnAhEEHwfLqwEBR3k5AcvzUP53Iw0D3UpnACxgaQXJN\nyEErOODAnkDCQD5HskEOpIu/jHe+QLJ4OUFvMY+/zUehQIzwoED56C7Abp4iQG5cs0AJNeJA\n2qz3wOCKhkEPh41Aa3BbQOrpKUH7/oPATrLdv30NrEFsuSvBBG/iQCnFrT5T6jhByIUaQDQK\n5EFu0VpBLOwUweWSOkE8vkDAofONQE6TlkH3bFFBb0jHQIOPaEFyFMm+gc6jv+gOmkDcW/xA\nhM0xPpVE5EG4DfxA4+k+QS0M60BQlZ9AAVFQQKo6IEGKvy3BS5hXQLCSCEE+yi3BGOesQFB9\ncECVEhLAMBh4QMyfqEGr7nfALaQ+QfgjuEFUWj/AGVJAQHm3o0HCEttAr9T2QOVj5EHg4Q3B\nP+rBwNrUikEmT8RAeUQZwcAzeUG9f6S/cmjNQArLgUFfn1k/HGFhwJH7l0HPW+9AMpaFQC7x\nBEEtZL1AE3fSwMmoMUH00bhA1Kr1QIKDj0HCCA3BuGhHQOQXrUHGvInAY6UAQQICV0EoYgrB\nWbxbQPlJskD/OIXApbcpQem8PkEZ3/9AnUwawE5TpEDb8/pARNZiQD/k/0BEJYLAJkn9wNOl\nMEAOy4dAE5F9QMLiQkFVzMFAAGEsQOGdEUCbNY7AwTIRwaGMvUC9O/4/6RQwQXbKgkGN96fA\n9poPwe++G0DpDYHA037FQAJOkkE2BBpAb2F2wIKfLkEloutAEadxwP0NqkFbqh/BkxUAQLru\nY0HVuZjAsXGJPw6GWz/q35rAzTgVwdiT00FpIS/ASt2xwLwnqEHRMNFAltL5P3MtX0Asb11B\nZ2IWwTwVKEDsCug+TuAWwauvyEGCFfm+NIWLwKiLiEG5AOVAc6kqwO0Wc0DED/hA8ci4QL+r\n9UDCA3tAaj1HQZ/Ca0CiZ0VAFYMTP1IvlEGamZrAj91KQF3Ci0HXN1pBTs0UwUEGh0G0Y1I/\nWYwVweFdCUFKwkM/9yo7QVtxxkGq0a5AKtk8QYjjq0GN8K9AmDU5Qc08VECTV3TAYyIKwfwl\nPEB6r5bAbbplwGok4j+wuu1AaZQUwdGs+UBm0SvAwJ46QAJ14EDmPNxA7j7/wHZZwUFWv8fA\nrsqZQPy7G0FrzEHAPbwUwe+BkUEPnCjAfuBIQOXpyUA8cdhADBv7wJ+mC0EXAcrAORSWQDbb\nzEGSoEfA0OxbP0o2w0GelV9B2CvMQCFt1kCQobE/Px6mQMVD0UHwqZZA3dB1QGTlv0BQX3/A\n4Ys2QDh370Hym1tBno8Rwf4z20Gd2NA/LI21wDRs7kG2+AzBBw6ewC7HpUErb9xALwwXwepd\ni0A5uTDA55MMQcMt10Hvf/vAFcyYwGn4vUBdw99ALe2av6jPl0HrOi7BzzeSQOjE1EGD6rFA\neCsRwaqjsEH+y88/qEHmP396zUE2sTHBjmFJQU9k7D+Tc/A/HPHHQALhL0EzqQxAdpU+QANu\nXT9ghi7BIuy0wA/snEG6t9BAbAgXwVNg4D/0tRTAKN+9wHn8w0FHzsRAFS7lv+aaqkGg9CvB\nvHttPvZESEAAkJbAPnUzQeT7pEGOCpfAF2jBQBrDg0F7BkRBKm3BQMqy5EGEi0G/zG+Av5tO\nJEDPmi3BX1TgQA0sJD9KXxXBI/8HwcV+o0GTlqbABNgUQGVJ20HtnJTA5VovQPAH4kHkAy7B\nPVYWwI/8okE3SSjBIM1HQEHC5UEa0dhAKXYjQCP6eUGY1ZHA86hQQHNfrUH+JdZAESdKQdH/\nGUCOcls/KfcJP0ACHUDQ/2BBgEViv4a4JECeoPtAm1M0Pyt8UUCU55rAlU5BQRC520Fx1IxA\nsO4NwUa8lEF7D4rAAT/xwIWdtUGj+5NALOikQCHN0kG8O5dADXOMQIdA6EF2VbZAvrU5QVfv\niUHA7oPAmcjHQPWOCEH0EB9Ao+CeQGH3AEFWF55AQNu2QA+y1EFyJXtAa8E7PnVe+0Ak3WJB\ne5NfQDJ2EkDtidJAzCFwPyPOcEGx9pjASzhIQQdm8kCjUyVAuaWwQJ10FEAOxhXAUHojQYeQ\ntUF9FQhB5Qdcv0DAz0Amtf1ApzZIQXuHOkHDKcI+eoIgQNwTLkGG4pHAAQbyP0AjiUHLA5fA\ny1SnQKxpCkFFrCHBZpoaQIBRg0CVtC7BAFaywKIYxEHPQ85A0mYsQLjimkEtuN9A9vMXQKs1\n0kH/bJPAtW87QS+eK0FumWjAekX0QKIKw0HqZg3BLtMVwX9p5UGqJbE+za3OwDgytkGoLwLB\n4okAwJZjbUFnjynBbHiwQK9HUEGjEQvA884AwN1zVECOFyvBCXc1QBqb2kFKdFtBQMYUwbzl\nEEDEkxI/UVJzQNTOmkEO/HLAmXC8QBugPj/l6FRAHIjhwMmEOUFsS+7AVRdtwPTTuEBgCvJA\nM4tJQSkKFUAQ4Mg/ztiOPxzokkF1r19BfZ8HwZ2gwEGF06nAhD5GQWSoDkFeCmdAfPNGQaa1\nlT/36nK/PkmoP0DV60Hou/NA+XM1QSaST0FCVtVAzPizQC08gUFmwkdBOpnCwFsPv0Fj2cVA\nhcQWwSZro0GyNui/hw/tQCpktEGONhDBJBKmQO8dnEGNI5JAkGZvQGw4h0H1k4DAScQFwekj\nsEGVpqvAAtZav8Gv9UCcBP5ASgr4wEh6IEGgJY1AiJ5EQeOB60HVEYRAAd/DwNACTEGrdgbB\nWWQ5QbgPg0GisoHAdtm9QILAFkByl0ZB1oi7wJWaiz4umQnBrrBKQYtgbkFa+ok/slTdP8eC\nqkDYopfA6ixRQOhHLkG0LVhB9ouPQFhDf0FHmVXAcIIsQe+sY0F4PLDArCeuQMPzOkExCATA\nzRlLQAHYTEELrCvB/NP/QDRs4UHsiwjBhp9sQN1ovUGXv3fAsmd+wJdXokGRaO1AxWF4QAbq\nIkGl9cRA1Ni5wJhYgkH5GMtAa47CQF2gv0DGP1a/lhCrPiH+ykFw5y/BV6sJwYrDhkDK7zVA\nEUyAQOWF3UE63sNAGUOMQBBpq0C0s7lA2m6WwFSJ0kFLIuJArQBEQYqeikH5X1hAyiVbwPQu\nfkEmPfFA76hFQTqL3kH8nnBAQ1ohwC0Z20ErHPhAyTiEQBSAOEGLR71AwxDnwHg8lkGeuJ9A\n+HDGQMYh7UF0EtM/MwfmwO8Qk0HNwaRApQ1iwB7PA0FmcPFARzbBwHnj60A1E8VAwKwgQQh6\nVkE6BdDAywYIwTRKeUGItE5A/D3KQEJBV0EfYQ8/6VdCQQo2ikAws4ZAaAuuQGxsj0HoDBjA\nknVIQXaVskELNbk/25RIQPPdokGuqYbApDa2wOgXjkGAnM1Al3koQVv6hEGw27zAwbTwQMTT\n50ESjg/BgDuNQDub+0CpRbdA8heTwJoR30C9VRfBgqoOQBq25kGRxy7Bwi2WP2eqm0FL8C/B\nwTw6QcfZRkEaNHzARUWUwLCulUESdBfBsx24wO/QlEFoMMtAisD6vsXdw0G7dvpASq9+vkIz\nxEElLC/BXwI8QdTAxkG9PnfALC1aQFsEiEGw+4TApa8fQbJmJ0HjodXAlZQRwbdWm0HLonbA\nfT+pQOGXKT+EQBvAJLQlQV4d9z9rbARBoW7RwFmNgkHHZrRAZtqMQJ2WAEEbglBB2DCaQEu3\nu0ELNj7AD0bIv2W7t0GZ7PpAiRXvwC28sEESNNvAWp/cP8ZPGEB5oJfAid8EQf8z5UFOQSpB\nDtkPQankokFgjPjA3s0EwXd5vkG387bA/dGHwIZnt0E7CBzBbas0QQiyuUHJ7dVAMmVKQSJT\nN0EWtvq+/eQ+QQNRTz0t4KlA7PGHv0y6N0F7Ai/Bor5CwK6DNED1zyPBdd6VQMP72kEvcFLA\n0wo2QNgNsUHwAC/BxTvPwO3bsUGB/QDBMqqtQLVWiT+GbBHAvBzAQBGUuECjtI2/415uwCsD\nMUHsUfBAl9OPQGcJzEENw7NA7vEcQPbPxUF+ZOZAH/O7QH8tQEEHcVlAzkZIQWdcq0HTv18/\nDysJwb+95EGyvjlAD3eqP+uLpkEru5rAkqwtv/sV2EE0aC3BamcEwCSGx0GhV/tA+FHIP0kE\noUHf3i7Bto0kQPrOp0FYBJPAW81GQaU3G0H7K1NA3FG5QKFsqUGrRMG/kNMQPsdZ7UBx15XA\nojoVwaAS6kE4uHM/dlIYQARxz0E/Xy/Brp0TwbbJmUEMCDI/+B9xP6bIh0HtLPhAOOOGQH7V\n+kDJBsFAG0AmQa38l0BZRQJB1NvAQEoAr0Fw/4W/EdCQP8PIF0HrXfJA7FsFwZPO5UHk3ldA\n0mUJwaGnD0ENK57AqNYSwaKFYEFNt6U/mL4cwCiPekEZVynBX+xHQZO3FkCp7RdALobmwNAz\nRkFllKRAUGq+v4KROUD/SS3B3VSJQGXDqkE+vLtAgatGQYCz6EE82lBAVXwJwZNWpD8gnZvA\niRP4QAJW7UE3XAzB8NUVQbzuMEABRRlB093WwGN9Wz/bvfrAAO4iQHzF3EAD9uBA3qTIv7k6\nPUG8RvtA8LQTPmAVjkGdmzDBUSjOQJRptUF/ds8/NiTnwHSarEAohaBArqovQXdSpkHDcabA\nkWxtQATHpEH2qHjAcGTEQFQXekEZZCFAwydBQbXDPEDu9iXA3QiLv5ivskE8dvxA4MwUPx1R\ndEAKey/BQlNCQFii9kDnuozA1AvHwBArHkGLdsJAFhmuwM6yi0DbAw/BVtETP4Sex0E3d/dA\nzoHTv/fL2UDDz/1AxrrDQHuizkGIWi5AuC7CQOF8mkCFdiBAtkLKPSQUv0CaVWNBfTlEPzu9\nn0H0wJrA8vLEQN062UGw69C+jg3EQCvqkEG1LC5Au6vGQG7Sr0AEY3U9pdNGQcHGu0BvOae/\neh8AQZodzUDlRy5B9wqkQBi0wEG/9S3AC38HwRWYvUHiKKnAwL4UwZZ1UUFBmiDAPqUoQUkT\nSUBAI7jAMwn9wI+nvEE0ZsvA+5bFvwRRr0GAxSvBeqPvPtiHaEHt8GBB0hDMwKlGg0GWb7tA\ny6gDwcalj0GybV5APHAWweOQlUFLhoM+86HZPgmKs0CzmGFBx9LuwDxsH0EsnN/AusDGwAmo\nrkHswAXBvEAVwTafwEGVZD8/5g4MwdD8zkF0hCtAczQ7P+TIM0G/N5rALYwhQfjTr0E6KQpB\nseLfwPr3x0EHHqpAm+pCQf1sZUHTcwfAZOxoQNC+ikHfg4LAGrh5QAro1EFo5yrB8KC8P/bn\nnz81jZvAIKopQXoYk0GNTbTAHJ4tQde0m0A0Xu9AuxbGQCTkb0EVgSlARVoUwXlNBkH8RDnA\nfzW6wExgn0H0bQrBYH7awO0n0UEeE69AwGYaQRd95UEhkuXAxjerQDfx4kGm+5FAxQE+QRwz\nzUEfLlDA7dIEwclJjUHTBlxAttsuvTBMnkHSjDDBcO2xQAX2Rz8AZQLAbLY/wFIy0kGT/yTB\nDR1HQZqC6UGVn9G+qgY+P+7T7kHYsvNAfhkYwRN5nEHOPB+/IwrVwN59a0HKYfrAz49IQRX1\nhUGtbOk+Kp4pQERMs0EMzY/AiZO6QLvRF0EVirm/2eu+wHuI1UG0/cVANUObQHk8zUEfkD7A\nlCjTwOjh5UFoBv3AipCXQLTsyEEd0KhAEZY9QX1mlD+bCKxAz+lGQduM6EFHC0ZAQzWiP2vs\njEH+0/VAc6cqQOuAvkHig1tBn7TPQJmCVj/CiEBByB25P9wJPL1FE2BBdLAJwTQpBUHjUkVA\niZwUQPdjkEGKxi/BC8lIQcT8gkEAY9M/8lLxwJzXs0BvYNrAoq5OQBrMN0Ebo9VA15tJQDUd\nqEGdsovALnsVwa5h7EDFcCXApBUMwU7TZUFemC5AlbjdP0TQiEEma5jABedIQWI1tUH3doO+\nQtk8QU5JYkBBALRARORkQFkYokE4ZIDAKWIcQVOM0kCZBNrAy8uKvwqEw0Efm/9AXW8TwUwM\nZ0Af9E7AksTbvgdltEEN5/1A9RhgQEvc70HI3CvBJEo3QRbPk0HpLMtAQ7vOPs2VEUHrBZbA\nycZqwKaHGUFv+exA8cA2QWsYIEAqqc9AcbVIQczoKEDRpSu/D5PXQN+V4EBy5j1BJKw3QMcv\n20HCsttAzUXuwP9auEH1ld/A1sx5QPqHJD+/8MRALmu3QBgj40EWTum/0oFIQbCv3z1mu3i+\nXIfSv8AJ0UE8GyvBrXY8QczDwkFF4V7AH9TFQEziFEEMrhlATtvGPwGNokG5jS/B09MAwAqf\ndUFwLvlAlpA9QMz+4EESdtdAU2PNQPx8zEFwVIA/STstQTxq5kFTxavAIToGPxdQbzySBjDB\nNLiGwDKESkEZROhADo/6wC9SV0CnvsXAO/EtQbFN1UF9HanAMUjEQFMVcUFurzZAUBkrP9nJ\nbkD3BjDBU8NEQeVYrkCbAgDA7a02wN7xHUGwRiTB6kW5QCLfzkGLMua/sK/bQDFtBUHYYDxB\n0qPtQJCbDr21fQ/B1XYHwdHTbUFqp1FA08bOQAN8dUHUIhvB+SWZQP2E7EHPIalA1KgewCvv\nz0G9qCfBW+oFPkTKukECcS7Bu/hpwPYe2UHECSHBvIHxQO6sj0DyTA7Bv9ehvymcBUA2JSzB\nyp3tQNWxR0FQQxDBHTHUwEo6vkHwgbVAXNGmQEcMn0GtDiXAuzPawKCr3EFZ3/HAtmPJQMB3\nsEEIPHe9gTQTwa2qiUCCx6E/Ncl8QP5XzkEpsSjBJKNGQegBFEEYPUpAosaaQCDS4EBHCCbB\nkanXP2IQx0Fzyy/B0/6twEElLUCHcg/BQFA9P7X4w0GhrDDBTbAXQD7vmUGzJ+NAEtkFv7B4\nrkFzOvtA2eaJwPw3wUDfmBzBE+CNQPwiBEFma1rAZPgIwVTvYkEQij9AV7hEQX3V+0AHnW9A\nd+pnPJKBqkErOpfADwHwwGnr10GzgdzAR2qNPstlXUEUTvlA5wd5QDKHSkFxKHjA0kP8wGkY\nM0FUJMrA13FJQRMAoEGPN6A/qfbjwOmKq0EFb+3Asir0wKHjPUELpI1AToLAwFfWJkHoAsZA\ncLNVQCImNkHbxNNANB8JQSSXpEDhNSdB9jANQbKJS0ElhvvATgk0QSxgd0GmudhAwNzoQNyh\n0kFg/RPB7kwzQZ9d5ECK95TAmpXwwA8tckHsSJJAzlatwNuduEEruQ7BTT/VwOXeqkHI7PvA\niPsNwRxf00CN3BFA6zsUwGmcdEFN/ijBtYe8P/ql10Fl0JjABxYYQS1d3EEKV+XAXC3CQCO0\nbUEMJIO/E2uqQJp4qEGOGRXAcLeCwK3FCz/k8xvBs6OxwCg1MEEaMw3BEz7HQGjMj0HZQyZA\nWH6gQIfpt0F6jp9Ax98LP9P7gECdNGJBbGsXwU4fWEGP9xS/7tYyQbQv40FEW9lA02bCQIuN\nhkG510W/D2A5wDG2xUFLYfVAiKt8QP4yLEHt/VJBHaIUwQoInz+UZ0c+znTzQEnK5UHyaTFB\n+tQwPx1icEFqovpA7wyqQL3K2EDBdpNAtJNzQGWVpUESAHvAvjyeQNI1k0CeLznAI7jSP9J9\noEGxt5fAi5gPQd1gP0GwqvTA3p/eQNsrhUGjzTtBnojTwCXRvkHHJf3AahC5QErU6ECSmXVA\nej6MQKdg2ECgLGTAHjs2QAZmpkFZSo7AovekQJSKUEF7zptAXvlJQTiS7EFFc3Y/QYY+QKTu\ntEB4jo3A2K3MQCSlhkGfEhI9s3UlQFf8KkGvI1pBzkwiQajwOEHJHczA7bvjQDCnu0CxkhPB\n3BRBQZjVmEGLcyrAN4kwwKpn70HlWfZAAiS2QAgTjEHC/Ny/SRajQA4PvD9dCphATXQMwY14\nfkArg5bANcTHQIFtN0ASuiRA4ntDQRPB6kHOc4dAQV0XwdJ8o0FoWEG/k7FRQPsxb0Gi8YrA\njbSXQFqkgUEJCknAnzaCQA9+YUGHOynBZXrGQJOTtEFF4xZAEJFnwKJNKUHfN+5AimE/QaNS\npEEjLkLAo/OGP+MIjUCIWPRArR62QDHglEHWQkhBs+meQJlvfUFwfU5BQ1nFwDDlbUHPKMFA\nNU8kQfg5mUEUIgdBiuJVP97uHEGz7THB++I+QWs9qUBXUkDANkrwPjqSS0GxqmJBgzIXweD2\n2UFA1xq+xqwXwWVEpj8AEADAn6RKQe9ImEFEHqk/yhKsPsDkwEBDUmJBBAYWwSZZkkAyxgXA\nDkJHQUwCtUGZc2m/TgopQXDrhEEXOrvAHrDPwEM/yT/IhLlArHiVQPT3WEGJGyjBeApQPym/\nPkGyeTHBw3IDQd0FgUGSPypBB6NFQf+9MEEpJlpAWL3FQDm0tEHfvvK+PLclQJFLhUGKyo/A\nsq7UPhLHxEHngprAj6QBQNyaYj9TY+1A0YgDQNCN3EEO3lxByw82QEzT3EFs747ADw3MQADG\nrkHQQrM/R58FQdWnwEHIMCpBA7i0QN5t2kHqTn9AOK95wO1axUCYn/BA/j2DwHB+10EgLuxA\nbE2aPhK750F7kzLBoZT8QO8xGkHxqy5BRn8wQNBl4UHcb99AGTq2QIUxAUHkfnBAv60SwVOb\nnkHaaEHAX42AP+v8rEEM0i/Bv1BCwOBVpkGcdvdA/7dIQRThrUESDhNA2YZDQXpIvEFaYf2/\nkzrUv9U5XEGhWPtA6IpGwCNY7z8XMPVAbEs3QcAE1kFwU8pA7TkrQWtHAEFgqrPAOmTAQPZI\nqkGjzXK//FjowLFikUGVDufAKQwnQPzckkEoGJDApfMJQSBFwUEEsyRBVu3MQE5tpkDS4T4/\nIJESwQ8x0kEQ07U/3PZiQABXo0AEwMxAJW3Hv68IrEEcwP5ATbbFQGQrjEE3Y+y+g8vRQIzJ\nyUEUKRrB0bvRwH1sjEF4EbdAP0sFQJ38GkGdJjDBGymIQCaudT4SP7pAET4tQUKGv0HwwfBA\n6A49QZEdm0EKHlLAF8lmQOpMlUHE6MhANbiPQAO9gUBsA7VAQcbFQKfqd0HcDENBL3wqQa75\noz/17vNAiKqvwCyAr0HeIdFAFDDHPpl8ikDzPvZAxOxnQAdH70EkOcxAqmaCQIZn40HmEyrB\nt5TWwADNkkGk7rRA3YwcQVjXrEHQ/djAZMlIQRPjuEETJQU/wWsdQcIt6kFpKtnAefoIQR26\n5j6bOQPB2RGnQKZjBkFNhyLBXMTiwHFa10Ggm6ZAVZFEQX2d70EV3mZAX9loPbcbk0Hxwi/B\nizS7QKHAv0Fzpl5AJ5SMQLlJDEFN113AvREmwPMh9kB5R/dAQ4QaQLDyMEFcJVtB2mq0wBx6\n60Dx5s1Ag0mZQGswoUFwCibBXonMQKiJy0FWVPw+B7KiP2+yvUEDaC/BkAS9wKGxLEHZVAnB\ngAzZwHVFGEHwcrFA8e4XwQPeyUAfWKi/z/TjwNqLNUHpgOnAwRZFQWtSmEHaaXVA/Wt6wPZa\nhUGjw+pAXR02QetMyEGKnM5AlqsdP3ziGUGf5fdAriIMweOfnEGXvxpAFeqjwDLlpEEAnxHB\nY8BFvOOAN0G6jS/BFr8mQfc0VUBqm77AQ0kXwVBRT0Baiqq9n3rGQLsvRkFkFBBAEW5YQG/w\nu0Bs9yvB3370v/TuUkGihv1Ayea5Pstyi0GfafdADJObwJHHxkGqfd5Ap36HwOUc5EGYS+VA\nEqW3QLy3LEEXEmZAxaeoQFsBAkFFFpZAhizNvuYLjUF1ni3BoBxMQHSV70HxRonAlRmLQMM1\nxUEsdGDATml2wHYxEUEBMB7BAIf4viTzSEFv0C7BAvL0wBSDqEEOrY1Arbf/P67ykkFRkpbA\nV8HdQDNiSUH0nDlBYT7gwBu+jUFQw/HA4F3NwGq81UFumgDBMQDvwDP+4UHiRZpA9GMeQR10\n00Ebtg5BAIBTPhZHBkEx3mFBEhXawPIS5EHZma1Ahp0EwT1H10EKKLXA4oc9QYdUmUEpNkjA\nz03KQN8we0Et3I4/yiDMQJzfY0E09Vc//4QPwPmm20FPsflA7Pi7QNFkokH671BAqd8SwfMk\nqEHf+l7A23eSwLAXnUFkfeNABNn4wEYou0ARs9DAZlErQBokwEGFvS3BNt9SQJwph0E2d1hB\nGl7MQOis2EGQH8k++qDVwPT210GDFbRAYinBP9X2o0HrqTDBhdvxv8eBS0HWNivBbAtwQGXj\nQkHVPcdARwu1QGRH3D++AX9Af6d2QIE2g0F/T8ZAjeKGQIxr50ESlL1AFmkev0oYvUF+6S7B\nvFwOwcSoVT7vyoLA9voWwWryPEFZkeu+YdrPQGycoUAnvD9BhJ6KQIyCj0Fwh7hACqAKwfee\nyUGbj53AqgZ/wKGKj0EMwBzBb+IXwUGiBkE7Lbq/9+MgQc6mDkFWJQpBgokNQFxrsEAXfTDB\n0kI1wGmO0UEv0yTBRhynQD4olEG/qSPB272hP4SCeUH/9JnAsHgOQXd2ZkGRtvnAtJhJQZ7h\neUHgL/s+71IsQe/AtkHQE/NAundlQDhkiUGXX89A83bCQK/IeEHlS2W/Im8+PRb2OkHAcDDB\nYRLAQEq12kG8VEVBWc8PQXlEAUBvYR5BGS4PwXYFf0EZCQJAqX1VQFyilUEKmSrByRRbQFbf\nqUGaKyvB+MXqwIuINUCc+J9AnRc5QQ3ym0EzvIDAgHY3wFk+iUBWHiXBHOGQwFEzbEFV+hfB\nvmEJQF+1T0E2P+hAdyT8QArrG0GbZArBwd2bwCQnfEG5lRTB0cJ5QMVxOj/EXsVAnXqLv5F1\nDEFI2/xAkTPqP5gj40E/2+lA3KRGQcmLhkEsTz2/ZkFHQZ2I/UDBOXq/9vUTP9NjVUEll5jA\nlx/KP/Z2eEFRS5rA0zSgQLLJukEuNCbBd4qIP345okCyTfRAsinGQLcu30HrGRRA5CDJQOAF\ngUALyss/Hl/GP2nm4UHZN+1AjgxXwK3HHUGmdyHB/hxJQWnWxEGZtSU/zscBwdwKf0EtZ2xA\nY7EeQYH6EECOd9zAwQODwGGkDUHq2BvBEXpOQM5RgEHoZdJAX910QIusWkG2gyvBzC2lQCNv\nlkHR8JlAqGsMwZb/6UDHApDAMRAFwf113kHFBWBAA8GvP0ZWl0ETkTHBmi9IQSpgI0BLADZA\nQwnMQJnVHUFRzL4/0PlywF7eJkBXcO1A5UT5wO24x0HUec7AxpsuQRgdgUFn2fFABudFQb7r\n5EFhDVBA+HcTwfoco0FPn1DAD9+ZwPa16UEmaBXB0JDiQE61gT70dRXBM5WQv9DjzUERVP5A\noxiSQNQVmEFxD69AeEsNwcxloEHpRyVAA0X+QDvMWkAF9i1BNEVeQOepr0HxzM9AriSfwLaC\n50ENttpAdFsPQZO9j0EsuiFB+P8oQWC+LUCudv9A60bgP3QcoEC1Te1Ay+/nwAr7n0Fs2p9A\nH+YzQdErNkBhadlADv3KQK/k4UGVYyQ/ZETKQALym0HBZqQ+yXgkQR8XgEGkQsTA1mvcwFBE\nnEAQB6tAMoolQFmU2kHPLuJAIsspQUqrpkDwv7bA2mAvQe9WV0FN6+dAGG8RwRdR4EEmx9k/\nCzQkQWuFfUHx1cjAHTK2QOuaq0GJfMu/Tg1GQecAakH8+U1AJgSJQPuVt0A0TyjBBrSHQA0Q\n1UHak2nAFU75QCrMKkHEygzBpWEAQCnWYUFjkJfAIn9zPxvoL0E8CZjAoaWhP4nAdkGpqZjA\n8fx+P+ksckGDPZrAcFLKQNQuvT5SEv8+PAspQTGklUG3Lv5AV764QKqSv0H3DiHBVlhCQYBg\nzkCdSINAwMm2QGpTiEAqMSDBWrDxP2/2aUFfzOtA0G8oQXs5y0FMD/xAxEoAP2o7dEE0wZnA\nz+kAv0D2NkGe9S/BLMxOwFLH5j/iyyLBDRvHwOHr2UFqrgXBUJ7IQO2mvkGKC/c/Fhbvv/rX\nH0EY0yrBxZBWP1lVf0Efa/ZAqOUoQbyrZ0HneL3A6ABhPw1AnkFCp5vAuNkWQEYFs0FR1pPA\nyrI/QWGhG0HRuKBArOOaQN6Y1UHSbSXB8LuWQFnr1EHUF0/AePKAQHv9O0GJdXjAbmb5QBke\nOkGrmTFB3LPIQOKdhUG+UmW+5fTLQE4FskG5RcY8P3U+QIWQL0BF9tpA7d4EQHiJC0CC/JXA\noJWuQMp+qECndodA/ptTP5tgckAX85jAec+FvmO54UFCqC/B/2rQQGgEukHudxnBtn1DQTg8\n0EFCCXpAlHUhQVvWZEA8AM7AhOYRQV+4bEFN/fLAFi0mP+spgD3twy/BWB5GQTW/KEGZtKi/\n9B58wNKl7UBpxuxAw/cQwZbR1kHWvXTAc+MTwdY+h0Ekb7g/fbDpP8S2TEA1czDBYSL9P0zI\nmUG8uJXAcHELwUTFwUGHFZXARzOMQIVjq0FM7mDAQ8xOQNBPmkHNqC3BOvTGQHaDMkGBXga+\nui6TO/hv5UB8+fpAVZEhP6v1tEHgL5jA5WvKv2/1l712xPxAwrg4PzsDsUGW9i/BpkWoQAj2\nZ0D/lkpBJKMIwdS+9UDKxUdAlPcTQXx93EECuxpBnQxFPzvJikEl/pbAW6o2P4bDA0G2J/VA\nxl+NQCjeiECkDSjBD88RwUI9qUH752nAFRzMQELUCkHsVpI+AhSJQA+WgkH7/FJBXCZVQMr/\nNEHUw4fAu+X3wFxenD2gb4xAH4vYwAgFE0G40rJAzDWHPgnVyEAk6/tA0925QEEIeUFXR72/\n2BwRwS0KvUHgqOo/DNaxQE0TkUA+TwjAObtKQSp4ZUGgDvg/8U3EQBUlXT8SNEVBZdCkP70A\nF0HoI5rAELi9PmMcXUES4ZfAKSdIQTrnyEGw00JAbmdVwPT6qEHwVCPBdH9rwG+7xUG/Fx/B\nd5k1Qa+BkT/cD9BAO2t9QPxyvkBaLsVAEtstQF2eqEH9GI/AALuOQEX1HUEqsFzAyVQcP3X3\nNUCw+vpAN1ElQQD8+0BWR8bAcfRDQD78fkF9MthAsF9VwA6paUHz8O9A71cXwegn0UGM8ou+\nJ7ieQPUHpEEjAzzA8IUSwRdMXUDViM4/Ju+JwHKne0CAkBrBds0pP3l2V0FK8WBBX/cXwfg8\nYUEg7dy++E6qPYND4kFYXi/BxnySQKY13kH8u65ACjcBQczLJ0HSwAfBXfYtQbXYkEFA4upA\nzN9hQIZraEElL9BArBwVwQil6j+kURvAC4YPwJ6050HtFPZA42DaQOspn0FyhDxB9dwyP6hz\n0UAfePdAlmr6wEM9O0E3zohAs70XwWt/kkG9er2/NhhGQcgBGUHkonRA+M79QJZcpEECCwvB\nXVcJPyJaVkE5IzHB3lLXveNLAkEBFPxA9nc2QUWzG0G5pM1AJh3bwCwwpUGdzapAahtLQTa2\noEFi+QNAaikhQL9KgUHjxo/AXB09QbTfrUGlGVXAYbs1QMJuaEAqfI7AXi4XQCk46EG5JltB\n8E84QcEmykEqx4XAXkMOQA6L2kHHL5XA+0n2QN+1DEFbpwzBzIj4QKdH0UGLiAzBhDccQWsp\nkEFQ2uDAUlwQQWHN5kH/XvnA4h6SQDnWx0AiWrJAKSA/QVkm20AfiVfAlldIQXxgx0AX1JI9\nMglYv/9QfD7I0vtADawLwR8wpUHVfTFAcoC6QPdi1EA7K1lABnkjQIYIhEE3s5HAYlCKwErs\nikDtaOZAoMnqv22HtkEy8vlA17dDQSlT10ET+4FAcxWvQAtcNkHsR4xArpPJQIbO0EHlyxJA\n8nQCwQE6ikERHXNAMkAVwcKL7kEmqSA+1dEQwUWj5D/+fHTA4sOJwGHS7UFYSOZADHSRwM38\nN0C4bOBAEOYXwRuMfz8wx6S/Ls4SQbhMpkHHm/TAge2mQJY8YEGYNExBKjgFQXrIE0GC0QTB\nrnCzQFNujkGpkvK/aBDHQLZz10DkSz6/LScsQSheUkGQx7PARDuKv0457UEy/PxAEZ62vtsm\n10GtzftA52jJQILhjEF7FK4+86iuQAtkgEGSPCLBFfSrQJKGt0GUVCLBytydQLPL8EBNDDfA\nFXgmwDc6D0FeQyfBS4wrQdG8NkFiEq/Aj1JAQd1MzkHQGJ5Ahc+bQI+FA0E0XqRAQoLgQNXp\nJUGEKjlBGnr/QATKCEF+IAjBPi8RwfsGKUGX4XrAXM8VwUvio0Ffzhi/NU+kQOH52kGiLpdA\nVIwLwOo0iEGmHSnB781LwL0QJUFe9CLBEHq3wJJ+vkEUKM5AmXYXQAOgX0GfU+NAYpWewI5Y\neEE0ydlAg7ALwAl1jkD9lPpATeAiQALXA0G2hZTANoY3vxB5bEGPBftAtRN4QAuXzEDpknjA\n0l+CQCtJmEEbqCnBepXtQDLwLj9SaDZBDmaPwMGg6kGhlORAH85hPw3WIUE4/y/B6PQWwRXL\nMEGpB8w+cs6YQBh4NkBe6D/ASh/EwNRSnj+mIMJAmPoJQZOhw0BeggDBlY5IQU/Mj0ECLoy+\ng1eVP9parEHSk2BBljN5QGeFukGkdnjAxJX8wLizm0GQlMnA/njAP/qpC0Hf3vBA+s8SwV/d\neUAEwaY/JYE0QeMXmUB3GpHA3kw1QeMaNUB0H5PAqqCTQIOtLkDatyTBhPxFQRX9j0HoajBA\nbWmFQIlItUH7PlNBikhNwOTbRkHjS/RAu/4XwRocr0HK3yu/+a2lQLO2EkGEZCzAUNdIQcw9\n7EBLLh8/1tjiwAy93kGK8fLAbv32QJvQz0E8kw3ByDUqQTxLPEFuL7LAs2MSQeq0F0E6cO/A\nGagPwVnGx0E9AdU/cu4TwV4sxkETDjPAAgn0v8XS3kF3ginBl80pQQFo7EF8FwBB8nPKQMdu\n4kGAo64/4oyrvzkKv0FuyfxA29mSQClSe0HqmLJARdX4wCbI2kFhvsnA5M9CQZhd0EFCQ35A\nI/3KQLzCgkGgW2I/IcUsQdrYdUCZQfNARAvgvky4gUGPQPxANRogQMd4iUHoSpXAErQGwZ5p\nIkEK1EpAG6sMQXt/zkFo2SFBJ3eEQJmO3UGJhHTAfO5awBGBy0FOwu5A1/aJQLvgKkETE71A\ndVqhP17Xjz9nAJvAEJE6QRqS1EEnrnXADYHKQIqDy0H1Btw/FZeqQLIogEGQ6iLBWirDQGni\nvUGpwypAE5oaQLpenkGueS/BCh9CQCvuA0HdgYzAnALNwL8U1UETx71A/2uiQJO3cUGiiUtB\nXQ3OQKxomUDGXUFBn23cPv1Xz0G63JrAO0ICQIZBl0FI3JPAWuQPweWp4UEFO33AGtfIPaUY\n3kEB7y/BnY3CQFaDCUH7kUpAsD/Sv4PfwEC+nP1AZjHDQNTF0EGbhzhAOGj5v9Nhs0H/IivB\nWSM6QF1pBkFgUS3BpLMXweiOLUGnsca/oGZAQbrvIkGOmJpAbbY2QJ3R1EFEwtxAkVg4Qayj\n1UFpqXvAENPvPx5P0EF1mi7Bc2agQDwFBUGV9p5APWcTQPMhnkFtdTDBc/qjQLcsi0AKiDXA\narI+wLImykBOcPVAUV+fQCYebEA+lj3ACW6SQAEgW0G07axAc/1XQHYx3UFMvNRA3U/DP8lC\n40FvzpfA22U0QW3jj0ESiZfA+ib7QEWC3kERJgzBIOvkwP6rl0BRA+nAJFmcPxhZaEHvLvNA\nwRzOQCPeMUHhsBnBzEKVQIJ4kEFzcLBAQqDNwKe/hUEmsrpApW/KQPBcCkEr7wJAHQc5QWd9\n6EC/SYTAETddQLvSa0CFxM1ALMv9wMvEHUGknIdAdUH8vyQA50FxffxARlbvwP8ydUAljN7A\n31CKwA4/H0A+MhzB1EToQGxOfkEBFjhBz/CAQAQT2kHAayrB6NUUQaQfP0FiyBpBLKgFwVxz\nAUFdQl5AuEK4QMPP7UEYT3NA2076v21zeUERWinBM6bxwPD8/UAV+tXAbNapQFkqekFSzZFA\nxRWUQJ/U+UBNq7BAXXGwP9wuEEEzSPJAdKItQHz8qUGMXI3AgBnMwOtlv0G2y7xA+KIvP2II\nxUDV7C/BSzy1QDawrEFhmcy/kFk9Qf3uwEGL31LAiLhIQZapaUHXoPc/bk0JQObg30FO3C7B\nLH+XQKWlwUHuyqZAK8U2Qa+A2UGFJMdAypIRQWSJ0UGLDB9BxjqiQLthskHMw5hAIBDNQOCe\nyUD7UkY/+b7GvmHwmkEu+PpADVwQwNNJlEEzOijBoDQVwUeJoUEK0yTA/ywOPWTUVj/+HpXA\nipi+QI9btkGm30NA2s+XQB36hkGGkyTBGg+xQNahxT+1ioZAD3ReQEd32kHD81dB3Mf2QP3S\nKUFvMzJBxFXMQP6IpUGljkJBYGf6QKzxQ0FznTBBBJJDQGn1gkEoTC7BrRVCQcfVxUGDCI1A\n9onwwEP+qEEsaJhAIjY7QQ2xtEHPV17AWjmHwP4mu0GR6+lAjzODwKxUsUD0chzB9cqUQFiF\n4kEwR65AMmjCQBWdR0EPdBy/BeY7QShJgEHBJG/AP+pIQWdNpUGm28M+1WVCQcglrUE0HhTA\nOHaHQBg20UFGNW/AIUbEQAi8o0HRTTVA85IUv1yJWEEPhS7B+k4QwZwzmUG5+QhAaOopQJWT\npEFPYC/BR6a9wH4Vk0CthgnBgMyRQLil3EFaQLFAD6cMwS2VJ0FJrZrArjYZQclTNkAwJeXA\ny7a8QECRH0BgTEVBnSVFQeZFOEFFlWhAFVEPQSj41EHVRiBBdsD6QKVXHEFouAvBG6bRv+4S\nvkG1iflAzRQSwYsRy0B0ZG3AtW8ZQeH//kAPqN/Ab8fCQNHuEkE1IGi/mxmQQAj15UFHul3A\nH+fLwJbxv0ENEgLBT9wLwZf+xkGT2JbAzRUjQKyNjEGC+ZHAGsrGvzatn0HeVP1A8dDnwJEk\n3EEitp9AXaXNP52s3UGjOu9A4Q7QQOLqaT+OhRnBkmBbQD2YvUG3coTAswPJQHTl60Az6QZA\nfqj/QF7Gu0FBpgrBYlaKQH+ho0GpZFJB4HkOv7xHykCO9P1As3UKwTIW2kHx3TFANcYUwUTh\n0kBL+BI/MT1ZPxMP6EBVH/VA7HYhQUXVkUB23ghBm2oPwZ3CkkHneAdAKGCIv/WVrEEkfvtA\nkQ1KQedVr0Gpve4/4xuXv0r60EGJsS3BPceawKjfkUFWrxTB9lzxwFj0mUB5KZNASYAPwfKb\nrEHUI9Y/7LtAQbbit0EINh7ApiNJQW5byEHBWQhA/uFuQCBDsUFrCyvBfog4wJRAg0H+EibB\nvaS8P/xhd0GePvBASzAlQU0m8D+RHAJBh7OfQPug30AFyE5BHRX7wBC4oUFcmYRA0KQ9QWt7\nqj+nu7BAOlmIQGmlJ0HYkblAk4vDQGQSvEFxOxxA5yoDwGGsgj/DQSvBPEVKQd+A/0BcGV8/\nV+N9QFAYhEDj1lRBSMIXwUcZ4EGSsQK/p61IQdwRy0FsVnQ++doYwd+Hr0F1lATApz+qQALF\nHj/gQElBD5CQQI+f7kGOpK1A75+pu0h/FEHXeDDBycIHwel31UBJClJA6voLwQ3M7T8eyjRA\nqV7JQJ1CUUHO/gZAqBS2wBSoz0H30s1AgCmOQDrFOUGyVl3AN8WTQLxtxEBwDU9B94kzQQlU\nf0EvSp7AFNwTwVL/lUE/s0fAVRRKQZSk5kEPrl09e4wtQVBnn0G10utAEa/2wEpbSr1lPdbA\n26THwIC3y0E1PwPBLUVPwFXTJ0FugvNA7uYHwcJRcUEWFKnAnZioQOpmpkEhkiPAEJ5OQDio\nqkGc+InAywz8QMLu20GJhS5BDlxyQE1q4UHzOsNAdOHJQMvUcEGqBBrBPbATwalxvEF0YYk/\n8uKywKahp0AdTc1AM+YLQM+LgEBMlVxBZTWpQGpet0BGgyLBvEkVwdj9Z0GUQx3AgM0WwZye\nykHlUvK/86fWQOESlkAfchjBUHaDQN2PakHia2zAuG/DQNn8S0FdZD1ANIfQwDLNVkHf67lA\nb203QYSTA0GG8onAKqZCQYK/pEEAASDAIUVZwD43oEHXTSHB/N2nwCkw/UCFAtdAZ/iVPwbM\n2EEcp/NAMVLvwCGcIEHECJpAdekdQUuJy0DOYtvABUgTwf8fakFVH0TACowWwZRcPkG8kf2/\nofo9QYmO4EFh3KlAHGedQD+NIEGElKJA0BZHQWaMIUETF15AiMHiwDUUBUEGSO/A/6vnQH4o\n40A8mDdBq/LCQN3rIUAZzjNAl4VsQM/d40Gz8SvBIkdEQXvazEFcLYRABnclQbPO10G79wRB\n8cW1QJf3pUHxTUdBndPFQI9J30H9zBzBowhYPiyICkCooWFB3k0fQLuQwkAx0C/B0iC8vwAY\nckGF7C3BUw6mPxpYBkH+XJbAJ5wXQRyjKj956xRBxWVIQQ7L9D4ijza+n8XdQNYEmEHm+BbB\nGlyvQMuu3kEhSEpB46ThwAtWnkGA6aZAFhPt/2GNif+w8y3/mQK0/xAA+v+HmnD/rKlV/1PJ\ncv9eU6j/vfUm/7qVWP+80jj/Mu1w/1mngP93s2v/dhm6/0kV0v/EzDf/ls1O/9ksfv+D2FL/\nIdSG/8DiLv8Qi7T/MrSN/+w6bf+2R4L/cIWG/ytkuv/1hUL/Sjq//yqslv/gTWn/7iV3/9U4\nev+ITJf/fYOA/0L5Yv8QPtv/3684/zvxav/kk0T/OE++/3txiv/KLIb/wlJ2/2MnvP9F/l7/\nAvyB/4lmif/KKob/1ZJM/zRusP+vHJv/WpiH/+SzM/+MhXf/mVeI/0HAgP9DeaL/E2DI/0Me\n0v/f2SP/6yR4/+hHaP95GLn/LcuE/1HsYf+VGar/ttY5/xmNrv8f+XT/98Mi/4FHnf8o9nH/\nv8Q+/05zof/SMn7/ByPt//AZe/8BJPD/AHrF//lWWP8Nd7//Z6t3/4qga/8xbbL/JPZz/0vF\neP+NinT/ZGSd/3Ovb//DKYr/qSCc/+0de/9STbL/T+Jn/3P/Rv/BtEX/m7NZ/+jpFv8N54b/\nSQba//tdU//4xCD/zOsj/zHbev/8HHT/jgm1/5KPcP9cvHT/831I//MUff+yLZH/l8ZR/2He\nYP/w/gf/Cu6F/x2zmf+kAa//aJ99/6sMpv8WMN//RouY/1Zynf+lEab/0TJ//0txo//f2CP/\nPBzV/5gcp/8YPNj/1AOV/4mNdf/hTGn/+PYH/wvqhv/zSGL/tplY/0CVlv9Gqoj/3UFx/5Zz\nfP+4QoT/jpJw/25Rof+oRYr/Fw7w/3QMwv/Nglj/oxek/zP5av+tyEX/F5uo/1vmX//38wn/\nFWnC/3t8hf+t4Tj/ObuG/1NRr//lCIr/Ymmb/143t/9n5ln/OruG/zZpsv8GWNP/MtB//wj3\ngf/zmDn/KyDc/z0F4f8f+nT/HzHa/1cayf+mh2n/xlJ0/0R+oP+XQpT/wBGY/yYB7//kujD/\nyiKK/zxPvP8J5Yn/TdFx/4XDXP9TJ8T/7K0z/9FZa/+D/j7/Qi3K/x3mf/9/Ja//wr4//0kW\n0v/y/gf/iSep/1J4nP+H+z7/uK1N/3HUXf+xTIL/PjnG/+VyVP/Hpkn/DRbw/0wjyv+7zDv/\nAyft//WHQf+Fb4f/co6A/3Fmlf9VZKT/h5Zy/7sclf/V9hn/IF7C/0sqx/+YqV//JGi7/wns\nhv/F8yP/qdk+/2ZYov9Q8l//HfB6/8LkLP9ed5b/Civn/wzCmv/RwDb/Mme1/7pbdv+z4TX/\n22td/w+TsP9co4D/gnSG/+Qvd/9x/0f/4GZd/1iPjf8evpP/Qnui/xoy3P9mCsn/BsSc/x70\nd/9wFL//OB/W/7fQPP8623X/bVGi/xe1m/+JFbL/Fft4/7SMYP8w827/z4xS/yMg4P9aG8f/\n/zBo/w3Xj/9TWKv/2/AZ/6AhoP9D1nT/udA6/50eo/8/tIf/mhOr/91DcP/F4yv/cXOO/+K8\nMP/RxDX/QnCo/52wWf9KSrf/94NC/ydDzP/Agl7/uRiY/4Eqq/+4Unv/nwGx/zv4Zv+KuF//\nRz++/41FmP//xhz/Lg7k/++NQf8hM9j/yt8q//Y4af8tJ9j/eFOb/9hSa//3qS//f3iE/xQC\n9/+g1EX/l0iR/+hNZf9d4GH/351B/0drqP/4InP/3Cl+/6w/i//D1jP/cCK4/7Z7Z//ymzn/\nh/hA/1i8dv93QaX/4twf//rJHf8nm6D/x3Bk/6GLav9m0GX/Zh3A/6XpOP/3QmP/S1qu/+QN\niP+5u0b/MaeV/95Paf/s3xn/bKl1/3Zvjv/SY2X/1u4d/5ZciP+ZO5f/T2Kp/2OHi/8f7Xr/\nSp+M/3u6Zf8Sy5L/+r8j/4lWkf/+jTr/j6lk/wtZz/8gkqj/gmCP/4PAXv8zI9b/hf0+/xtd\nxf9m5Vr/B3LF/9vAMv/YCZD/uole/xLLkv+dKZ7/o3dz/65be/9rAMz/ZoaK/8ESl//kzCb/\nhkKd/4+sYv/7nTP/Fqei/40FuP88Nsn/4Vhj/3Qjtv9d71r/EtuK/2HXZP8VCvP/qO40/yR8\nsf+kFKX/VKuB/42Ybv9d1Wf/tvEs/7jyKv+zrFD/S+Rp/+78Cf8izYn/Y1ak/8vHNv8x+Gv/\nhvVC/zw5x/908kz/w6dK/7GtUP/bokH/P8l8/5sCs/9mkYX/Xr1z/zY6yf9LgZv/cTqr/+Zu\nVf8ExJ3/I2y6/yi4kf90YpX/JJej/9o1ef96tGn/pbdR/+5lVv+zVnv//Rd2/640kP+t2zv/\nO818/yC3lf/OR3b/65NA/+oiev9uTKP/p0aK/xODtv+79Sb/TMp1/x8Y5v9bfJX//sQd/2YL\nyf9Jipf/vXVn/ycS5v9Yu3b/hCqq/xCDuP/OrUH/cAnF/4+Hdf9lM7X/M07B/1o8tv9DLsn/\noQur/4DEXv9jymn/Qkm7/0OnjP9YV6r/RHqi/z/Nev/jcVb/R6mI//fOHP8Mq6X/eLpn/xju\nff8h6nv/79Ef/5z8M/8lb7f/qk+E/87pI//fS2v/GMeR/xDhiP+/n1D/F23A/0m9ff9C5mz/\nFYW0/wIs6/+vi2P/ogat/9lhY/8HRtv/BTvi/x7Akv/8vSL/PWqt//KgNv9SjpH/Axvz/9ET\nj/8t83D/IdyB/0sX0P/ZiE//LC/U/9FPcP+I/D3/1/gX/9yxOP8f+XT/K8CL/3xXl/8rmZ//\nZ4SL/7hOff8Kqqf/CqOq/4/2Pf/HTHf/G+GC/xsq4P+iDKr/T0+y/w14v/8l+nH/U7B//7EZ\nnP8uKdf/ra5S/2sqt/94607/yTOC/9a5OP9ivnD/1g2P/4Vvh/8ZvZX/xCON//DLIf/+qiv/\n6+MX/5oqn/91dov/H9iF/93xF//TJIX/30ht/5E/mP9OcaH/qvot/1YdyP/9OmT/rS6T/6r/\nKv9lG8H/YWya/4lBnP9h3WH/PWys/9qAU//oR2j/1Q6P/zKQn/8tnJ3/c+tR/yKonP+CA7//\nrH1r/1DgaP/Hh1j/nm95/wrWkf/mLnb/E7ac/wy5n/+HXY//P7uD/30urP8aIOX/iPVB/35E\noP9I1HL/h4h5/2Ypuv9AkJn/3zR2/8DnLP9rQav/MLSP/wzshP/M9h3/cLds/0E/wf/l4Bz/\naqV5/2JvmP/8E3n/lLFd/2kGyv9uP6r/Yo6I/10G0P9M2m3/tT6H/wFwyf88Osf/y29j/yzc\nfP+lenD/mpBr/5iAdP9V0W3/h/JD/19Irv9hXaL/GGy//7yXVv8F7of/Rd1v/4H2RP8sgqr/\nHXm2/68vkv955VH/k6hj/6XFSv9kQq7/sIlj/74ti/88NMn/Q2+o/xZA1/82FN3/mv0z/9XT\nK/92N6r/hwC9/+2MQ/9jkYb//cMf/wrYj/+M/jr/Z26W/0YlzP/F6yf/EqGn/wgh7v/S9Rv/\n2hWJ/+3uEf+DJK7/Cybq/7K4Sv8h9nT/KU3G/xkT7P8rM9P/Xp6D/8JGff+2zj3/1AiT/8aQ\nVf8I4oz/L46i/xt6tv9VMb//zd0q/xG2nv+BhX3/IryR/7bEQv/mojv/rJVf/xYN8f8S2or/\nuSuO//Mdef+tBqf/3Y5K/4VDnf+3aHH/YCDB/02+e/8OrKT/l6pf/8T/Hf+1IJb/LRfg/wOf\nsP+ZyE//uGB0/zEp1P9mhIz/2SOC/+dVYv8EMuf/S5+L/4cQtv//pS3/GUXT/zqjkv9MUrL/\ninl//yvSgv9T+Fr/2+wb/1LpYv+4BaP/1JpI/+sEif/DlVT/SjHE/zUe2P9KOMD/DL2c/w9s\nxP/Enk//agLL/+VOZ/8jyYr/yppN/3GJg//dJX//ZJuB/weTtP/KNoD/hCes/xzhgv9CDtr/\nvdY2/9xtW//xeEv/QuJu/xW9mP8gupT/uf4k/9tSav/Q1S3/i69j/yHveP9BqYv/p/4s/xgF\n9P9Jw3r/4zV0/8v8G/9yp3T/58Iq/0yjif+SZoT/y9ot/12te/+6hWD/v1B5/0lnqf8wb7H/\nxAia/5wTqf8iHuL/pwuo/1ZOr//3X1T/y3le/1j5V/8SzZH/8sci/9h+VP9zy2H/P32i/6Hv\nN/+vQ4f/Jxbj/yOCrv+yD6H/dyC2/xcH8/9P/Fr/HXi3/xUV7f+7Loz/atVg/30trP8+Ddz/\nKcCM/30rrf+HP57/5Sh6///+AP9kSKv/M/dr/4FQmP9heJT/kQG4/09xof8z5HX/1IhR/8Yb\nkP8SzpD/kzGf/8kvhP8gtZb/8WlT/33FX/91qHL/hZB2/xnCk/+UBLX/7YNH/5biQ/9ncJX/\nilqO/15wmf+oy0b/yvIh/wQP+f/A4i7/UDa+/yJA0f8H8IX/unJq/zLfeP/Lq0T/i2SJ/zvl\ncP/TilH/OH2m/yxJx/8gfrL/3Lk0/1CTj/+wN43/Lt56/72aVP/YiE//qiSa/2Gag//7CH//\nymJq/ycQ5v8rk6L/XYmN/yhquP+wHJv/hTii/1ZEtP++fWL/v6lL/4wKtv8uVcD/wHZl/wTY\nk//uikP/f+5J/426XP+Vz03/q35s/wuBu/8KfL7/iiun/+qFSP+cIaL/88sf//YDhP8zdq3/\nMwnk/9XEM/++Jo//Yia9/ysd3v8wS8T/kHGA/1kTy/+3plH/A/CH//L6CP9jiIv/n/Y0/3sp\nr/8pWsD/8lRd/z7fcf9Vsn3/SbKD/x8f4/+zFZ3/xM42/61Khf/yvif/lWqB/4SDff+KLqX/\nomF//0ZEvP9ebJv/mL1V/7gRnP9yvmj/LhPh/2bmWf8rXb3/RBPW/xdyvf9nRav/Ew/x/zF6\nq/+LyFb/FIux/5s1mf9dYqH/tKBV/3gLwP8HBfz/4YdL/7Noc/8e+3T/Fn63/9WBVf+SY4b/\nIV7C/0E7w/8g24P/nQOx/5T5Of+PfXr/SX2d/9PgJf+24DT/HMyM/xiNrv8PYcr/Qoic/ztK\nv//OkVD/UxvK/5uHb/82ScL/SpKT/9obhv/P/Rj/OTHN/94+cv8zFd7//voC/+l7Tf/+mzP/\nsGZ1/yWHq//lwSz/M2W1/6GnXP/hQm7/u3tl/9quO/8Q2Iz/XjO5/wixpP+maHn/D4a2/9Bq\nY/+1pVL/GwH0/6/KQ/+M80D/8ydz/xanov8Gu6D/ro5i/+kNhv/wsS//rKRX//RKYf+FDrj/\nuEmA/xTWi/8V/nf/FVjL/xwE8v/q3hv/noxr/8BxZ//gP3D/90Nj/5LLUf9INcP/RUC//+I7\ncv9D/1//FEjU/4EFvv9A2nP/EyDp/8HnK/83WLr/Y9Vj/10NzP+SCrP/SreA/yKwl//QaGT/\npUuI/98Mi/9bzWz/z705//R/Rv/CmFP/f6Vu/28huv8cpaD/6foN/xR+uP+lFaT/Bjni/2KW\nhP8xYbj/E9iL/539Mv/MjlL/S9xs/wrSkv/7UFr/buNX/4n0Qf/Kamb/roVn/7+9Qf+lPo//\nkBSv/7qPW/9BWLT/VHGe//rdE/9smX7/i8xU/xXzfP8CmrP/f9dV/y0K5v9d+VX/hxmx/3jI\nYP9jIMD/bbJx/+++KP/KFZH/rWJ5/1ZGs/+KaYf/MybV/9irPv8jd7T/60Vo/y1Eyf/fZV7/\nk9xI/4dhjf/t3Br/6l1c/2JErv+gb3j//TFp/5xve/9GYa7/Pmqt/3HFZf+EdoP/ci2x/yTe\nf/+ZH6X/v9g0/60Sof+WaYH/jcZW//a9Jf9CQ7//PJ6U//WvLf+mrVb/asxl/56eYv+faX3/\nz1dt/9GpQv/UzC//kBOw/1nEcf+kimn/BR/w/xDnhf+LbIX/RPZj/8YbkP/DWnH/vJNY/xQJ\n9P/07Q7/rcFI/8qQU//Dn07/xeMr/2HTZv8A4JD/Yah8/xmio//qGn7/vLFJ/76YVf8KIO3/\nMSbW/15iof/ZQ3L/0kxx/2Y5sv+21jn/8ndL/7IHpP/lqDj/1Fxo/6uuU/+yDqH/Utxp/7Qj\nlf8/AeL/+X1E/92wOf+kfW//kFKQ/0NEvv8o53n/uiWR/1FRsP/0dUv/TI6U/3d8h/+GpGv/\nFNmK/2lvlf8ZpqH/tUSE//fcFf8KjbX//L4i/xfqgP8Gl7L/Oku+/2Raof+Xql//wTGH/y5v\nsv+xyUP/rxWf/4U1pP8Zz43/vlh1/yCrm/9CENn/VGui/yWbof/TU23/OVq3/9w2d/8pNdP/\nM/9n/6kEqv/nKXj/mjWZ/y4r1f8x0n//Nu5u/80di//Jj1T/b4eG/xvHkP/IklL/u6ZP/3v+\nQv+La4X/mXR6/6B/cf8v/mn/VJSM/7qZVv/NfVv/3HdW/2AEz/+76C3/1G5e/3nQW/+TFK7/\n4bM1/wsI+f+cyE3/KeV5/4A1pv9HiJn/qppe/95tWv/0wyP/8T5p/9rNK/+XdXr/p6pX/wch\n7v/goj7/+NQZ//5SWP+mgWz/fZd2/47VTv+/Dpr/UCTH/+NqWf/aHIb/9Zc5/9ZBdf8K4Iv/\n99sV/5ZRjf/K+h3/B/KE/wH8gf9GdqL/mbBb/4zYTf8vk5//Ykms/7IQoP8/h57/eneI/5EJ\ntP/B1DX/HuGB/6wUof83xIP/z1ls/x6Jrf/AVnX//7Im/53iP/9NAtv/UmGn/xXihf8X04v/\nPPFq/+lLZv/ElFT/BUbc//Eidv8B1Jb/36Y9/87NMf9PNMD/rK5S/4Nckf/wSmP/2S98//XI\nIP8Aq6v/bGOZ/xySqv/jyCn/fzam/yCsm/8u0IH/U6OF/9wigf9H8WT/Ab2i/351hv+DumL/\n/EFh/92kP//Hqkf/56A8/ya9j/8Sp6X/ar1t/8psZf+pHp3/65Y//7wqjf8lfLH/27Q4/07b\na/87toj/1K4+/xebqP/QrEH/pEyI/7lXeP8zn5j/RhnS/3h2if9C3HH/tQCm/+WUQ/92VJz/\naxXB/16SiP+q1z7/tpVa/2Rxlv9YaqD/YEit/yvtdP9swWn/g+NM/+C8Mf88yn3/gXGI/8Sb\nUP+2l1n/OHmp/4Kkbf/lCIr/6sMo/34mr/+zH5j/BaCv/16bhP+ZNZr/xEB//yL+cP9zgYb/\n8eMU/44npv/SX2f/W/dW/wp/vf/07w3/gFOY/zo+xv+vFZ//Jhzh/6oJp/9lwW3/jfFA/8qX\nT/8+O8X/OhjZ/7AQof9wP6r/+9cW/zAQ4v+PK6T/W/pV/2PFbP8yvIn/o89H//5eUf+VIqX/\nDD7d/yGNqv8YNdv/+d4T/66CaP+AErj/ihuv/3i0av/ANIb/WmGj/67OQf8lUcb/nvM2/4b1\nQv9/a4z/ouc6/1SsgP8szoP/bP5K/+eATP8Lhbn/oddD/zP+Z/8mhav/wNM2/4zHVv8NbMX/\ndLVr/2Wsd/+J7UT/Xdxj/8EpjP+NDrP/0AKY/wdO1//q+wz/6g+E/7oxi//M7SL/6Dtu/zRi\ntv/lY1z/9qsu/1LuYP/wS2L/RTrC/6mIZ/+4rE3/sV94/7naNv/I0DP/dVuZ/xBgyv/k4hz/\nRMd6/7Umk/+blWj/nA6s/87sIv8sLdX/33tS/ytHyP+2Wnj/lCij/9a6N/+VbID/U69//wJE\n3//M5Sf/pc1H/59Hjv8jQ8//g/JF/wvliP+7aG//JVTF//5HXf/ytCz/nG18/7jEQf/F1TL/\n+cQg/wTAn/9Ht4H/5m5W///cEf+cql3/zDl+/0oY0P9BXbL/XvpT/z9orf+qtk//2C1+/8mt\nRP9cmob/UW2i/zWDpf9glYb/ot1A/41iif/V4iP/UlOv/6d4cf+vnFr/Yap7/xzGj/8bgLT/\naTSz/zKyj/9wW5v/k1ON/9NlY//yZFX/XDq2/0U+v/+WqWD//xF4/9IYi/9MoIr/a6l2/7Nx\nbv+cC67/avFS/5aWav/jmEL/8HBQ/+DoGv9H/13/8m1Q/+SQRf+jzUf/hS+n/3kurv/qXV3/\nrTiO/7KJYv+nZXr/MZKf/8ywQf+P+Tv/5Sx4/+ZsVv+urlL/bKV4/2dGqv8OO93/i0aY//VE\nY//JqUb/Aou7/2WBjv8s8nH/mEOT/9eNTf+Yn2T/R4Sb/0zoZv8ur5L/36M+/563Vf+EB7z/\nesFi/4XVUv/D5Sv/kkeU/4Unq/9jqnn/6fMR/xHrgv+HeoD/n7JX/7SyTP8Yb77/pstH/ySj\nnf9+nnL/b02j/1K+eP+GnW7/Bkbc/0xZr//xTmD/kNNO/0PSdf9yA8f/gwm7/8e2Qf8rUcP/\n7TRv/yIy2P/xT2D/VKGG/9HWLP+IdIL/E8SV/0ufi/+HSJn/dLNs/58/kf8+jJz/7XVP/6Gt\nWP8W2oj/VDC//xZixf/Ukkz/ieVI//PbF/+tiWX/+J00/wK8ov/aWGb/okKO/6p4b/8d7nv/\nukh///ZmUv+Z6z3/F+aC/ypOxf+qb3T/GeOC//Atcf+mLJj/h8ZZ/yputf/oS2b/LMeH/3Lk\nVP/uekv/h8ZZ/7cjlP9821T/MbSO/+IXhP9bvnT/eAvA/14G0P+EB7z/gQW+/wMt6v+f5jz/\ny7g9/zfddv8kuJP/fE6b/9jmIP+CAr//Yal7/w+iqf/nmT//yzOB/1SlhP+HUpT/e8df/6cF\nq/++DZv/U99n/+O2M//iGoL/ZBbE/2LvV/+OKqX/vSuN/xdK0f8SC/P/LDzO/yAE8P/wqTL/\nxro//93dIv8exY//fsJg/wCrq/9Z0mv/P2Kw/+SKSP+Qe3v/G66c/6QLqf/OjVL/thiZ/6Sy\nVP9eKr3/PVW4/8EEnv8AWtT/u6xM/x70d/9BdqX/6uoU/5QEtf9GUrX/JLWU/7SKYf9KLMf/\ni/Y+/2ASyf8Bccj/Tm2j/zVUvf+EJK3/yXpe/yYg3/952Vf/B/OD/1AH1v91Asb/1tsn/7Oi\nVf/SoEb/CeOL/zNFxf+zD6D/VBnL/xhTzP9Cxnz/iEmY/3xgkv/fgFD/rhyc/x17tf8hnqH/\nc/5H/3iBhP/xqjL/7EJp/1m+dP+a5UD/e0if/xCGtv/2XVb/qfEy/zdSvf9jcpb/nIRw/1Hd\naf+uvkn/cqxx/0VVtP9S4mb/r21y/6vZPf+JDrb/uc08/x8P6//3+gb/18su/+gMh/9Kvnz/\n4L0w/5nEUf/2wSP/NEPG/zvNfP811Xv/AljV/693bf85Ocn/jQ60/yVkvf/CW3L/5d0d/2E9\nsv/eNHf/k3R9//5/Qf8PirT//WRP/xlkw/8Ig7z/scJG/3f1Sv9Pv3n/lyKk/zkn0f9wyGT/\n/FlV/+VWYv+VLKD/iLdg/8O3Qv8/HNT/TKOJ/2LIa//b3yL/RkC+/1jwXP9Ivn3/WoqO/66B\naP/pPmz/kaVl/1eihP/KaWb/eEyf/4Rmi/8lXMH/RQ3Z/35Ylv83Fdz/orRU/wXvhv/4ZFH/\nVqx//15+kv8YG+j/C2rH/zTAhv+Z1En/t/0l/8YVk/+lkmT/S1C0/yF8s/8oyof/GMqP/xe2\nmv+Z2kb/wfcj/2pgnP+6gWL/Th3M/z/Wdv/tlj7/3b0y/2THav9Qwnf/1HpY/9KHU//spTb/\n++YO//Ewb//MWW3/hUKd/+iSQv/d3SL/iy6k/yHlff+KV5D/kg2y/1V2m//b7Bv/6xZ//9hh\nZP9bRLH/CQf6/+LMKP/YMnv/iLdg/8o1gf+psFP/RxDW/+JrWf+B9UT/KPJz/9wDkf+hC6v/\n8ItC/+yqNP9JN8H/M1q6/942dv+/pU3/R7GE/1uEkf9X32X/4kpq/+LMKP/erzn/R0C+/6iw\nVP8kHeH/Nl+3/yAc5P90Qqb/60hm//IIg/+ayk7/7b4q/yiVov97UZv/Xrp0/5lCk/+ObIP/\nSjPD/z7LfP8gR87/U3Ke//ZcV/8hlKf/Fp+n/4jwQ//otDH/ZepY/0R1pP/9OmT/hqVq/0OT\nlf+FPqD/QkK//0xQs/+1Dp//zGtk/zSrkf+3I5T/zs0y/33ZVf/urzD/zkF5/+fiGv/f6xr/\nvT+C/zUu0P+kVoP/nqRe/6uHZ/8HAP//wjeE/5C2Xf8OPN3/6fgO/1rvW/+v8i7/aO5U/4ux\nYf/S3if/s3Bu/7/NOf/HY2v/Lp+a//FCZ/9rKLj/iMxW/6/VPf+3zzz/3heG/642jv9zqXL/\nonly/6+wUP8mmqH/6kJq/1mNjf8Zw5P/FfN8/2LcYP/i6xj/U754/8pabv82iqH/RMN8/04n\nx//0GXr/zZhN/9ONT/+UDbD/qlp+/+pvU//rT2P/CLqg/8oSk/8+M8n/yL48/672Lf82V7v/\n6HdQ/zh+pv89Urr/Jud5/5t5dv+3WHj/utg2/9+nPP+bnWT/KXG0/7d6Z//Ezzb/1dko/7yz\nSP+Lo2n/hFCX/xDnhf889Wf/rHJx/wvgi/9ZRLP/yDWC/wmlqv9E1nP/I/dz/+6BSP/X1Sn/\nu4Vg/wT0hP/9QmD/T6qE/zl2qv8Pd77/bzOw/91pXf9jGcT/NPZr/4jJV/+fiGz/9dUa/6nl\nOP8Ak7j/2JhH/1lgpP+Ajnn/sR6Z/7URnf/r7hL/8EZl/4C6Y//IfF3/LWi3/yL7cv8xt43/\ne4Z//9eFUv8nu5D/fBe4/2w3sP9ybJL/Rst4/7DPQP+roVn/RGes/+dRZP9VcJ7/NsSD/32I\nfv9lhYz/7uAX/1ZBtv9W3Gf/R5aS/z3wav8VNtz/8rMs/9rdI//m5xj/sPMt/+25LP8T/3f/\nNLCP/4GmbP9IB9r/BemJ/wPUlf+iu1H/7PQO/6hudf867mBALWcpQP3xg8BMUgvB1b83QXo2\nmMCMB7lAQcWlQf9hRUFiNhM+ReGPQYd1l8AqiKg9uA/qP18fmMBmELnAex19QUDyCcGmCgi/\neqmiQWkcL8Fb7S9BCP8aQZWfp8CWZuQ+DlMxQTLe9kAgxadADrCxQQlMTEETKefA03yuQZuK\n5cAAr0ZBl3+xQZIngL+9awZBCO68QMgRKkEF1Ze/RgkoQVIaLcHqFm1AAV5hQVO9KsETMpBA\nYw5fQUoGWcBXS3NAlyAKQRbUfsCtUDtBeye5Qba2ZsBJ1zxBauyMQXTnUsAYmctAF9XLQfWz\nuT50j0lBagh3QYz4wD9+HEtBA8d8QI8BKL47+zZB8A61QTdnyUC2UxHBW5jjP1j7fsD3LIpA\nwZu9QAylKMFU8bhAQ33dQVWBb0DmW2tA956qQfJxyUAafBfBEmdTQcNmAMD35InAF+aiQNWB\n6EBK+xfBI5vmQdAf/L8Z7LpApCcMQTLicEBqNVQ/6F2cQCxaMcHd0QNAX47SQbmq50CcL75A\nBOreQTXBpL9Kfb1ApgrIQVOTVEAu3yNATlCAQQrv40DgdRfBF7RrQdakl78E7DdA3C33QPIJ\nWkHXY6hAqnn0P9wDlEBfqANAYQbSQZ3NMMHMBdVAvVHdQOxqPkEVy+/A6njWQW8/2sCOMNQ/\nDwDSQKuh7ED1AvbAY1lpQXVIkEDqXcpAdmK9QbgliT6ihz4/MM22Qd9l+ECR7cFA/CU6QSN9\nQb980RE/GsoBQfGlYkGbU+Y/SyqBPhmaXkHpAJ3AC5eAQd7g3UBgOcpAtBa/Qa5KeL7Iv/vA\nD1bJQeaiy8BXO+LAJt/DQNTnqUAf9aBA5WelQSLrOMCH+8zAUREqQZzRAsEKunpAvqLWQQ9Y\nK8F1mhbBpwSEQdoI+L8cBTK/8iSQQbtB/kAakglBFW/2QBydAMG2qQ/Bn+n9QCtYAEC0MlHA\neqoTQPGS9UDZWKNA+Gf3QHbBLMCTFklBr7/RQcTF9z/SpLpA3N/cQZpLtb9aQWtAZEfaQTZu\nzUCuFY1ArYRlQWurXsDdwTZBfj+pQKoEjcDarQlB9roZQVSvJEHNR5FADayMQYm0WcDj+klB\npTyqQZtTBz8YIwzBzOM/QP+hkcDf4E9AcAFxQDHoV0EkTxpBJxvoQeku4MAr23BADdNyQT2c\nyECwJ5JAh9OVQG7NUEH4mB1BuE+zQXFj1cCPUwDBrukTQTSmf0CbU8dAYNPFQXox3T/pB7lA\nnipeP4hG2r/ag5FAkh3iQVB0VMDtFLxAotTOPVsYxb9krQ/BXJKVPboa8j96pWa+yNrpQZTO\n+0AgCQzBitzPP/FrM0APFPk+XzZBQZ5vMcEq+H/ABQSCQbGAHcEGpd7AYdC4QLNTrUBzXYtA\n1V2IQFlNUkFiSSBBiHMNQYU+1MBJ8xDB2H2FQZjvdsCT1Y3A4f48QXVV5kAQkxJAT3hYQZx9\nL8EK/sZAMrC4QTqf+r520q5AUTyfQbQoE8DaLqNAUmffQS5xMcC0mxBA5/UYQTkf5UBIezdB\ndhwWQWcDykBsmL29x95aQWFGYUHI3oJAAdy1QeQsKsHth3dAfPWQQXQzKsF+XRhBHDzbQVKv\nFkEHvyJBGYrAP/TRBEHf9o4/A84JQRDFmMCeIxzA6LzsQTSG+UDHUB1BJLXpQSCQ18BdJRJB\nEqfAQR/EHUGRskZB+bK4QDwWQEBP7aFAKY/tQWhBMsDhJ9E/SNaFQSHCl8AP+wbBSQ+KQYfP\np8B9K+xAc9orQVGWEcFpchPB837kQZurgj9PSGdA78XkQacZgsBCRstAn1anQXpFGz+77SVB\nAdmOQc8Zw8B0akFBV243QRPflUADTaE+rpvhQeIDYkGNUABBSN+NP78vL0Eh8GFAmepeQJOB\nK8FGH1I+kLqZQYNDl8Dt8YrAGN5DQVNFG8EYKQpAiTigQdOKksBYpMlA2s4mQGUyrD9xvw7B\ntj8EQQpsgMA0OvvAOv0hQdgbh0DrH0ZAG6SaQaS3iMDVZcpAJrPFQSiG6j95mfbAvu4MQSeU\ni0DyC0pBUrDRQUE7tT+z0p1ALELjQFsSNcAj1p9ASBSPQeY1PMDCG65A3KU1QEFnh0Cvp/w+\ndp7HQfzol8DY5QnBVoSBQeamm8BBQRlAjfHSQXLx4kA5aI5ACnPoQSWAUkH9qxdBGqarP2B3\nFUHej15AsY7lQcSOz0BD0sbAvZGqQYIZBcH1/N3AcMLxQNSi7MCrWTc8cuAEQTryMMFpXJlA\nR/DQQReKqUD5Tv7AoFuNQSLDfkCSf5dAcuCtQS7Sq0Dgx/bAeriFQfbz0sCuEJ0/dS5QQb1D\n9UBOhX9A0YaeQTjYwUBMrCNAmyUoQG+pkcB6CBFAqYNZQVmNk8CODxfBya3AQUL1Wb+r3YdA\nh76ZQV3qZMAZlzxAYgDBQH+EWkEQ8i1BhLChQWb9p8BXkqvAjlAvQHG6DsF6KilBj00sQc5h\n/0BDBLlAvnXpQVWpR0HEXrrAK3MdQOydykAVPRLBVmRoQSp9oD+m5TxBwzKjQUGptkCKZtpA\nu3bZQEGbF8EFIo8/xxkaQaCo9kDPxLs/URnXQfCZmsCId7nAscA4QemVyEAg9cNAGXgwQc51\nPkCFZShBni9BQROL/UC4qtxAZE/bQKoyFcEVgbjAswXIQHVWzkDAiGK/6X9GP6zI/EBiIURB\nMFq7QO6CCMCnL4hA09aDP9PjUkGj38vAxxjlQVYqBMEmG69AqWejQAvvC8D4fGY//IXmQLmH\nl8DW3iFABKBlQERpW0GPjspALYBrQIO6uz+1HpRAbnsjQV8HVMAg+RPBwS+cQRpFMsAvR2o/\npsO5QT2Q9EBHnBTBrH3/QNQZIT9cuZBAAaWNQVB1q0CzfU5AM9GzQTulicAUTWs+uMiQQLZ8\nmMBbv9RA8vHWQe5cGMFAebRA4d29QWpT/b8BxdE/rm3iQMzc7UDa7StBBiaNP4SE8kAsREZB\neWkQQVU2w7/NnxhBErt5QSuz48C3lsJAA2MdQXKpSr8nu50/KJ/dQV1UMcFL7Ye/7l/FQZKt\n+0CRSAI/aL53QbbmYEGCocxAbS71QC/FOT/ZXylB/oxcQKDd/0A0I8FAisxvQbePmL93FvlA\nRwe3QTI6DMEhrYBAXy0HQQNfeMBCcBE/WcTiQYsnYkFK2MJA5OuAQXBvU7+WAg3BIVwZQWx8\nJUDyZg1AT0h/QV2LW0F2CJA/4t2tQf5JMMHd2khBISpWQbZTqLxzrhlAWACmQWHC5ECUx7pA\nBoHoQIHlX0CZyPfAQALYQTAlh0DHKbK/OLi6QfeZK8HTaoJAHarHP5lNaMASNLZAJEkOQcM0\n0r/fETxBN8uwQaUXZ8DNocFAYQjkPhyVVL9ibxbBgEfmQe7sK8B+cOTA/Ft4QeXmpEAGyQbB\nYqpYQW6WpMDVnp3AZVpUQV5n3kA5q47AwUcfQY3f4EDhI+DAW4F/Qdrm8MCUz59ASWKwQflk\nN8AweoxAHfjHQQsOUUGAfibAB8l0QCvh+EA0R8dAP3INQWMBzLwev42+0OmOQQTJLsF+ga/A\nMCCIQGUG0UCguwtBvD+JPx2VIkHnS71AOI25QVR+REGyLEhB/gyfQYbSEUATblm/TbQ/QR7b\n/kAJAshAY8cVQZj4QkFdH+BAvmNcQCR4OUEsCzBBwhe3QTFF5UBQNgrBDTMyQVhePUCqfcpA\nV9uaP/YdTD539RVBMt26P1k57MC+vwpBabfEQchKAMGfeKTA4GO6QCAS10Bhyea/84muQczq\n/UBscDpBAe2oQaD9vECX2MXAKv7OQbBTwkDIuOzA+OvkP2Y/28BNADDAn+8sQW10JsEv8wLB\n1yh0QTHkbkBbVslAHovXQdkBcT88wAA+56dUQV0qY0HclaDAOlLTQcRj3EDdUgjBHw0lQZ7P\nqsC0Qv1AFxdaQFMvC8FeABPBpcb7QFQdtj8aZ8tAS0BCQDWp5T8XYAFApOo/Qbg/lsDbVx1B\nkAI+PyQA2sBYXq9AARlnQA7fSUEQ/2tA53lUQRADecBFBKtA89XWQDING8AIUUNByFOsQXZu\nE8B8nUdBwpjbQBvlU0CsJno/gE9MQTui9EA+/ohA5jotQOWFKMHoJXdAsTeAQVXyeMA20wJA\n0C0ZQF48XUFxrQ7BBDOqQespkcAteLRA4IK2QI4NR0HL+QvB2DHDQbtHj8DYS6xAyXSGQH5/\nEsAyGJpAjdQpQWqSRsDmcMlAgefvQWT2qT9zg0lB0FS7P01hhD+qWoi/fkUbQXok+kDUh+BA\nYkjOQbhMOUHQTbVACU2WQd5w/b/VeUlBSTX7QBbSQD9G3ERB282uQav/47+ZtKVA4RWUQaMW\nJsBgdIRAQz7uQFtqJ8Ht/2JAL0SQQSy4g8CToI5At8XPQYCStkBLfTZBq0K5QbsD1kBEX/7A\nTNZVQebDgkBOyOxAHdfUQT7bEMHi3xtBn+rEQTCh3cBv8u3ANmf5QF2dm0BafhxAprSTQVOV\nL8G7MkRApQYMQeOO3ECObBjBHxDpQYZ0nL+iH5BAVUGVQJUQtkDZYBfB2PK0Qf1Ahb9IU4pA\ny26uQRwMZsCAT8hAt6pyQfvVV71Ot1s/EAuuQS5g80DuDXc+79qVQY7HlcA0KFtAX4HdQCU+\nV0EvbrRAqHSBQfDSH8E3D6VA9eQHQQFNl0AikIVA4ayEQdnqwEDBfSRB3M/vQWvnxcCvNyRA\nQASuQDGhj8B8sgjB0F3hQYnFn8Bd6cdArth4QMLS9T++zT9BD/i9QQxbo0BnTr1A15DnQZXI\nTECHfcVAimepQGelRr9gvzM/40piQfYb+kDbA3U/QWLLQc9u9UAqdAO/WQfoQbRzLcFi9AzB\n4fltQRDpFEBBvKg+3UcYQFz+lsBmz0ZBZvCVQYi/nL7C4ltAVkGOQeSM0ECU2wtAhb3ZQe+V\n5UBWBz5BzjUvQSWdsEACgp3A47XRQaCPFcEENcjAMjEGQQGKwEArRblARl7pQbFI6r8WmcZA\n/tDOQZAgmr4vvaJArB2iQU/Jm0BT8klBVjK3Qa4lBj9B57VA6rpRQQ+h5b+rMxLBogurQSdP\nvD8/KLHAdz7jQaEjDcGOxm1ArI9+QWu7VkHC3edAxbcnQYS1EcEO95dAAw5gQR/+p0B5BkRB\nOZzUQXv0b0DXaDFBFTDsQbTDncBOrrDAvCGTQEPeDsGqpfDAHKO7Qbl+lUCDCRDB81KYQdBr\nfcApLkNBJ9hBQR74C8BswaRAk7I+QbaCL8DffxtB6B+bQcKKEkEqlZJAJ9zoQZg8rkCrj7W/\ndf4OQdlb/kDAaBxAyh7XQYhSlMCjHdRAvd6tQaGSF8HRLKW/vca4QGaNLcFI7tk/VkrRQbux\n70Bsi0BBz1jeQdRAl0BJR7i+0wNNQbwWLsHjGezAcmVfQUnomkAiRojAVDXFQbnC50CzFv9A\nkKvJQUgjLkGJTPy/JTyMQdpo/UDVqbZA3EOQQW12fkB3gmrAZnAVQY9Q7UADUBTBAKs5QfYR\nLsDECwRBHONpQPZgKUExQILA0pQLQUsRHcEUf8tA4dZpQVzoGsHyyTZBr9EPQO/LisC2gwJB\nOdHqQQ1/B8GW01S++76BQY/k+UDEFgvB0d3uQTYUl8B8mw6/zE+GQUdZLsFHUay/7WKfP66l\n/EA1r/jA4yN0QFF0zMCkyFLATNd1Qb3u8kByDQhBYR54QTJSA8Egl7dAsP/AQPNExr8/IW8/\nHxB7QTsPYUECiRLAdJRNQDbk+kCmBi1Bh6I/Qa/17kB4s/fA/Go5P/7Jh0D0RQlBLvPNQUk9\nAMFga9I/KZHKQcoLmMCGaxLB0WSvQYq0XMABhzZBlFoHQM9kh8C/Y8ZAnISTQUElvb5O2QnB\ndDuZQVhBMkAB/+u/FUmkQQmx+UAWTAY+HoBKQaULl8BSoBfBPSJBQcdvCMAa/ldA7Zy1QQIc\nhsBFUjxBgIrWQWkiZMDNEpFAk4l7QY/lrkAZQok/iC2GQS6nMcEroJ7AvwDsQV3NE8H8Ypa/\nmrooQD1+LcFx9kc/8L+EQXEymcC+LsRAUtLhQB78LECK1Xu/oN7TQcCJ/0ATtLhAc9FZQT3h\nw7/JK/RAy/cvQb1VM0E7CUZB7WoMQPxyUUCHbklBHWU3QUaahj+8c+I/jwIhQNQmmMB+Z/tA\nvIqeQb4xL0HNRRTBPHOIQISEjT+6am5AU1WaQTSFgsBi5vU+l3ofQWzQMcF/6s3AuNqEQWSe\nAcHRUElB2VUwQYAWxj4csdlA1CirQeIiPUGL6MdAmy6tQWwOQkF2+4E/vHCoQXAvMMFLvi9B\nlJkOQRkW6kB8iLk/GmzfQVMaYEFArjxB2+SAQF8TXsBKHEm+DpY6QaKB+kC9/ClB9Xm+Qdpy\ntcBa3G1AS7m6QBETVUHj4aVAesl8QcOsTEGWwrxAtjnkQNHXXEBsB8NAkeRaQTwJREGj7ZG/\nNbK3Qf4wLcG5cpQ/43imQcEaMcHlzlLA8tvNQS0AI8HZFjFBvZzuQLwCoMCfWME+fAKSQeSA\nmMAEHwDBJKlBQYsKxcCzVetA8/IwQZXcEcHomLhAeTnNQILnaUDdHBjB6PoLQT6gzr542rlA\nZphVQUxrbkDdCuLABa7YQeBrqUAz0RtBrOLjPpMD3cDrYtLAr06CQK5QtEATErdAFM6UQLo5\nH8FFoHzAWflZQXs97UCdwNTAvrWJQP7G+8Dc9chAxlLMQWhoIkAZP4FAdt5lQcbyKsEeb65A\nCZ+bQetlIcHmDpTAab/fQbQV3kDWpMG+osyoQTp7/EBAxYRAStvtQY5qa8AMJ8dAS2OjQZc+\nE0CtDEdB1I6iQYHKTkA9kDtBdBbgQBnqacCHNqlAdD5xQEFaI8En0WxA9yzCQS1SykC+gPbA\n7nPdQWwj08AdvLdAe+HbQeSX7r/WxxlAuDRQQRRt50BefW9AlUedQS0fyECnMxfB/7EPQFoG\njb/7KJhAQzywQTZATkEm5jNBHy4QQR+glMAsBo1A6PRqQAqyXcDPnhPBmUYsQa25iD/AWx5B\ns63uQarQ2cCJUAJAueJAQfimlcATnBDB6X8IQZucbcDmZwfBZfuxQYDTVEDvKExA11CQQLsO\nicCALNtAJOUlQeAuFsHer8lA+E13QZ1NUb6sIhbBhJrqP9mdqr+Qc7A/ZwbCQZAaMcFIvtk/\npSZUQVjNlMAdIxbBL1WHQfICGMCBZctAs5Q+QX449T/IX94/AcLAQAB66kDoQrNAs+0qQcTT\ngUDWUMxA/Lb6QPtRfD8k3whAol+XQZw+k8DwPBxBpNNwQayu3MCVnTNBirU6Qazwk8AvREFA\nhtr7QAAm3EDqaqC/UZ/8QB0pK8GLkvC+BJYlQZql+0BuXA/BSdQBQfpI/j/tsz5BPIjvQCSt\nTsBKvPDAM6TVQdLNkUBHqb2+gv0EQd60L8HqpD9Bbz/oQczQP8D8KAw/8kqwP6k7MMFpxdRA\n7atfQVOpF8Fu0/5ABHQ6QMbKLUH05hVBaHV4QOKVF0Eu4UNB0dPgQa2c0b/TcNg/9vmSQRAS\nX0FdIujAphWNQMpnokCUxOQ/1safQfcv7UDKghtBLxTCQU9YEUFmcChAt2XSQX8z4EA/HytB\ndOs5QA68tsAa8jpBFanwP8BRuUCFY4PAmN60QRGxG8F5VtfA3IgtQF04s0BWTfRArT4KQTHn\nDcFbpyVBlr71QHSiAUGKxhfBdT0iQOCV/L+ej8lAROeLPoAghT4J4w7BCkSkQU6rhcBlNpY/\n69qYQRdqncChUGfAtcnLQbX260B7/3hAtvpPPwQxxEDWhrRA2/QXP/NwgkDHFQdBHd1fQFC0\nA8HQXfRAYcntQWocDsFgib7AZJjkQMsZyECM42zAs3njQbYuHsEt6AfBSJkaQUWCo8D1gpdA\nJWWkPmrYRMBHVGdADyHEQTNYhMDemcJA+ZyoQG1ZQ0FmqUNBGe18QJCNakC9b4dAXYAOQQIk\nZcBnKBXBoOzMQeonPsDUDMlAcfKlQGcnfj/DCew/8qzEQdoR7kDUK7w/6rd/QU8JX0HDyG1A\nVqzKQYsTVkHRBzpAdmXPQcJXLcEoBzRAsG1qQAzxWUGAsQpBM7SiQDsxAsGPBUO/RWVqQdsd\n+0B1ncLAPkejQKQLBsGHcxbBaXZDQRn/y7/rV/g/y96sQSfW6UDNz709j3WPPxSbL8Ee+SLA\nIsueP3KhJ8H8fo1AnaOFQdEUUkEDFxhAz2m7QUg35EDrUzlBAfJFQPbvukB7schAd8pLQAkI\nJr5oKBZAnQ+ZQR01lcDJyOY/ZrgVQU0p7EDp4QzB+bjHPylkIUAYNytAEOSIQIMLW0G7WRxA\niZscQZY6L8HjiY1AU7amQdv1VcDqo8ZAUYepQEqP7b5g++U/4ZuiQX8qL8EEr8dAwE9KQQ17\n9738VhJBGuJiQf7sG0FrzclA2Vm9QfDNBkCeycRAKuLIQYm0HME/jP1AcoQ3QSaDCsHpsRVA\nrEvJQaKRlcANBOXAn9l5QQm1p0AX6fRA2qdGQOtoDcH2CrVAE8q4QboN1r9UGDlBMdnhQc+x\nhMAFWkO9x5nvQXkXMcG/izNBHmHdQfr42kDsYMhAl5eQQS+lCb6zMwjBiCFdQUr7T0ADYElB\nLopoQJjV3D+CbtNAhcrPQTZsPUFYmbxAjDjGQd5Cu7+29FVAZgXRQVurz0Aqm6JAEFGIQb+1\nnkAV9PbA/PoRQWGQjEBa9RRAnxOfQdGtW0GWn6JA5dAgQcJxN8CSQrdAuAXuQfOAcUA4/MpA\nxo2jQX76Xz/F6Im9F6mfQWM3YkFZ/ZhAji09Qao0S8AkLM/AnhA3QXbIuECUt5lA0Y2BQTaI\nqEDGy0NBUMQ3QbIYdEB7xdDAV3PqQMfKuEBYXxbBrqnMQV0Sh75YzWhAh0zaQY1OzEA9KC1A\n9DDJQSeWj8CohwDBe5u8QMmIvcBy7K3Ac+qmQIOoD8GFMxFBCD1XQR98HUFydzK/+c+AQNCE\nLcHbGv8+Dr91QcWzm8CTCxTB4hGiQfMeej9/9DxBqAQXQeHKrUCJixbBCem6Qc08JsDsHunA\nj3WUQWtHoUAV4UlB9Y6XP0mOTj+FDMpAzgTYQRVUUz/Q/51AOzwSQGc4JcEXP71A1b+1Pwdi\nHsG78BPANCd/QTl3+UB6T9tAYIvxQGYvFsEeiMtAmZNqQcLGID/z9atAoAdMQOf8EsDPdZhA\nrbl/QT2zTkGr7IdAc2FtQRmIvEDmFUlB4cMGQWykCL471hXBmEt/QbPTOsCnrMVAOCs/QYiH\nvL53KQXBuw/0QNM4s8A/dsNAnU/SQQ7VE0A0GyVBgLi0QXy1BEE6hJpAxwdLQapopEBry3dA\nkyi0QPO8KcF9rwpB7Ii8P3KcJEHs84xAJoG/QXTWUUEwyK5A6U9TQcrzIsFs0KNA1fr0QOSY\nmUDJfj5BBWzXQY6Hp0AnoADAH39FQdZ8KsEVjOjAl0g5QdgWnUBQUV9Aj5XtQZCghMAcBTFA\nnNmKQVHeLcFhjpM/WFxFQf1pmcB5fKRA0YNPQa0LnECRGAnBrX46QbJypcCFz3w/S7suQa5i\nlsCpIUhBUPwPQVxXK0BauqdAPaipQXFZk0Bx2uvA+auKPT9ZmUAxrbpAHt7gQMmKZUASAefA\naOS+QQORnkCjvkRBVi+oQKBqYEBquhDBjaybQRsm2j+dnAHBv6GQQdJiusBmmRbB6PSOQaXC\nTL1Wx0ZBwSsfQXzNtL9vZsxA5QN/QW5qQUF6WGNAt/sxQb/BzECx5xrA9lI1QaW++EAko9TA\nP0M3QBekt0DtUNjAW7+wQRei+MAIFP5AS6YbP0SdLkGH1UJBs5cBQWDKgkAIbZBA2kZ0QUUH\nUkHwvhfBwe2mQI7Uhr+p3A3B4wZdQIDNEkCnNMtAEFSkQdzqiz/EoC5Bw/5jQbOf7UAWcWe/\noVOKQWf1LME4TiFB8o6bQXk4z8CllZRAMtc8QXQjr0ATmRLBuoOlQT5LVMC9kspAbYyzQeOg\nGj/LLMdACSrkQLfhDUD3lejAywP8QPr3nUDl6p1ArYEjQDYToUBIv29AsMHNQMLVg8BWz18/\n5y6RQaa3YUGSZ0ZB1oPIQcmNWr+cub9AbW9fQcFPSkD6uR8+HCh/QSSZmMAUlQ7BrjbfQYDh\ni8CEf/7AuSQ6QdvoxMAoERZBhkftQTAA7MBulUlBkGecP4e74z9F+do+stKCQWO3X0Ge9d7A\nu79BQVV1q0CcMsBAmWUDQYncqL9y6A1BK+G4Qbe5IEFj61fAcYYPQFmEIcGdBrBAbGt5P+2V\nBcCK5ZZAjtXFQcWuT0FuU3lAdOHMQTVnesC2kABBS3PfQe8TLEGTkbtAUyR1QfN+sr+X1MJA\nKPGfP/vhhr+Mu7FArnqnQa+QIcEGWY9A12p/QJjoUEHF8gVA1LadQKMy6UBfSGZA9DlCQIxg\ng8AkJMZAq8ChQByIAkCfmpHAEywwQRxQF8ENhnNAh2S2QZ5hwkBH/D5BOWOrQTsGO8C0hsE/\nFAnHQUb8mMDpOQPBdjC6QWmqtMAbBThBOtR2P2O/x0CaWwfBQPKzQCuMo8CZPBHB8K1PQCU2\n3j+S3sdAKCAfQQtMuj8I4EJBvZvAQWWWgUBuiZtAPWT6P56pJcFulRXBICB0QWpu7b+KtuZA\n9MmBQKIKEcGoVB9BIMarQStO18Bq01LA6ibZQVyuIsHS6ubAd22hQfrF6MAklBVAPaYiQIpq\nk8DfI0dBhygPQGQ7JUBtQM1AReOuQVQfSjzGeqBArlfkQT8nN8D+dIU/Ep6iQc1omMDarwnB\nVnfPQd69ncBxZI1Az1h7QYAUs0CRrKvAnpesQTpV1UBb4q1AO7k0QeoMCcBOl/dAVNsQQSFD\nDMG1/4k/NhrdP40hMcHJD/q9CFONQeMBMMGzmA4+iaC3QRykYEER865ANVWqQQLqCsCmYIlA\no0CpQKsHZsDX4YTA18C4PkPBHMFQsS1B+ESQQak/qsB8YVvAlmetQRh98EAYbclAVrm6QO+3\njr51ehfBJKVBQRu/sr8+F7hAZl7MQWo1yb8oudW9nX/ZQeWB/EA09chAuRe7PnlW3T9RZoPA\n8TwNQTUvHMF1+z5AGfZ8QYdSi8BCaPq/4L7vQYJDKsEH0IBAGq0zQIQOwkAQzj/ABsXcQE1m\nJcHh9ng/n7EOQbYP9UDzZw7Bm2GCQevMEUDlSUdBhTieQF/PiL9DP19A2XgcQQ46VkG6zwpB\nGenNQcZ4JEHGohpBNSIaQX3EE0EXGjs/snSsQUoYmcCWRrfAbfzGQTkTCsEzEzU/EprdQdfx\nnMBDj+TAO2K3Qe+l68C9kstAG2kNQacHxT/Qg6NAU0vIQDHBKMBBWL1AK1EKQS0LUEAZvvBA\nvY61P5qJDsFOu9LADg7iP7KstkDMapDANRS4QUmFFsFKot8+1dRGQUdXmsATBQBA1enWQWSM\n7UAhPzJBUNyGQAHRmsAb7rfAhJi9QacMC8GjRhXBRvhUQXrwS8DFI75A0MXPQZHckr+2cbTA\nT6Y7QeeKC8E86fLA9OddP8Ir08A8AsVA8pS+QeGWL0Byz8NAWDh4QdLqP79VIDxBKBhOQL9B\nuUBABihAiAz8QDSQkMBLFklBAxqyQThoAz+iH9fA8vrOQbq3r0ARlQvBZjDjQabKIUAJBjhB\ne+n4QKz0ykAgRfNAd24hQMLlDsG1NMpAezBwQNh4G8HlPEM/1petQZk0YUEeZl0/yvfNQd0c\n90DnqElBvNjCQbEezT2cKQFAVKGCQQlVL8EJfvVAQqVzQC9wNEH1hQO/REr0QK1DLsHlxhI/\nMBKeQf7nX0HwsGg/GWc6QNU/nMB8dRZBFDIIQVwz6sA698RAKl7UQd4iJ0A1IMg/Q/W+QR/W\nXUE2+7C/uHJWQe9oLMGuqRRBfZTZQdOM6sC6PC7AWoMOQf4eKMFbbKHAIsOJQaaL3EAhsEhB\n/E++QQhWKkB4gqo/akEuQSbgMMHhLhfBC02wQfJs+b/XMbc/NuizQYxl9EAr7KTAoMMKQdU7\n1kAa8erAqDS0QPT8nkDbJcQ/fA25QSf8mMA4V2ZAtV2SQbkeg8BFDaVAepOBQP4sIMA0MwdA\n+SSdQRrZlMCZsfY/0lciQWjD6kBRs0PAtfXoQSsO9EDDKg/BgAK/QYYYC0BhCFNA/gklQbDC\nV0FOHT5BeWwGQEqGTMD+ZCpBW3XjQeAuucBiyRbB57/LQaKkBT99ujZBfmZZQQvyiMBe7hTB\n6SfvQMfQQT/E2/JA31uXQQKzNEHVyoxARfSjQcfPtEBKe4BAmbeSQIJuc8B5QRfBzaOGQJdH\nkr9HqihAoYanQc7hjcA1wKpAoothQehfE8BteaE/FPgxQIarl8Ak6MY/fIwVQZ/WXkHjLAvB\ncURYQFBMIkDfsHZAcoAbQCfjdsD9Jc1AqtuvQdZ5Nj/tKklB/KBIQaqonD5Xe8hAUlJsQclF\nHD85jCNAd0nsQKKjksD/FgdBUrObQLXAA8HtnsVAmHNsQf5gZD42I6NAKc19QZQgnUBnUsNA\nmIDXQYHOJb8kyz4/97XvQcVSYEGBI1JAfrQ8Qfmf1EAuDoRAnbTAQMQUUkH6y6I/gaFyQd+k\n8kBvKg3BGHg2QYVoH0ARS6s+U1yIQQgal8BKCvnA42UTQVL3jkDwtzBBJ6+/QDJa3kDY8xLB\nOavHQaqNRMCPhJhAX5K6QQHiRsBIZEBBoZcEQAIjMsCtsMtAX/CKQfgs0T/aGsxASHi9QWpX\nlj9TK5hATMVyQB/SJ8HXsLTAAFbjQXlfzkCM5SBBqn9qQUcP1cBLBXe/kX1cQXw7LcEgMgTB\nCkl6Qc1bucANfQ9B0bNCQPp688Avwik/agyLQa3vmcA8zBjBMILfQTfttb9MSzdB0CiMQWet\nyECAuvHAlmlBQfrll0Cafs2/CTKCQXQS/0D7DO/ACr0zQTG9mUBxVzdBj7meQVCzhMAMtsxA\nisC+QYQZQEELxDZAuF7uPqUokMCDPzlBhwm1QRW3xkBXwcNAWjcXQWrBL0Akop5AlPqAQLx5\noUCv/eVA0ixQP1JkOEHDOfnAM/uuQTYNikAxhkBBAYi6QB1XlEANIQA/N9O+QQ2cMcHljY7A\nKGODQcwv5UDVrC5BrLHdQIxM70DFCxLBKITGQYZdaMA+CRXBMVHNQO5NRj/hYUJAnc+jQCtH\n1kA5jRXB+uByQHLNNz83xchA7pjOQS+uGsE3xezAhCMYQUe/28D7979AlmWlQYtNQkBFqEJB\nyTGvQFxGi0ANf7jAbHeyQbQzCcF+fhTBBgDMQauaRcBcqrxAteKfQWD/xb9MX7bA16o2QS0A\nC8GT/7s/QwzsQR5MmMDlM3zAdue9QRsS7UBtpEVAPrqSQNjZjMD1nvXADy6hQJe108COyhLB\noRUvQRwUZ8ACC77AkKaWQNHgxEAPd55AEb2lQS/YOsCMHMFAjIV6QT1RTUC2Y4ZA1/AiQT28\nuUCRSxTB7K6yQTNqSz/uGc6+Nb+zQWENL8HLHPA/xOmDQQrelsCajj88ZL6uQAZ1+0C5oAnB\ncbG0QfHXPkDOdkpBkoC6PkBQ6j/+5w/BkMXfQSx8ccDH6ABBYfBuQT26LkHIcdRAqNuEQSp8\nGcGx7UFBPguMQaosI8BXuRXBlLigQTrNFj+3QRfBjRmmP0I2Kb+5lRTBrIGRP/LUgz8EtcVA\ne8qBQZ4nCL0pchbB5jLcQU5/9r84+rFA8PiSQR6cAcDBejZBPsTkQXKLg8DD6gQ/sVPnQTvg\nmcCEQQfB8urAQFHeTkBy/NQ/ncjDQPdSmcALGBpBck3IQSs44MCeQMJAPkeyQQ6ki7+Md75A\nsng5QW8xj7/NR6FAjPCgQPnoLsBuniJAblyzQAk14kDarPfA4IqGQQ+HjUBrcFtA6ukpQfv+\ng8BOst2/fQ2sQWy5K8EEb+JAKcWtPlPqOEHIhRpANArkQW7RWkEs7BTB5ZI6QTy+QMCh841A\nTpOWQfdsUUFvSMdAg49oQXIUyb6BzqO/6A6aQNxb/ECEzTE+lUTkQbgN/EDj6T5BLQzrQFCV\nn0ABUVBAqjogQYq/LcFLmFdAsJIIQT7KLcEY56xAUH1wQJUSEsAwGHhAzJ+oQavud8AtpD5B\n+CO4QVRaP8AZUkBAebejQcIS20Cv1PZA5WPkQeDhDcE/6sHA2tSKQSZPxEB5RBnBwDN5Qb1/\npL9yaM1ACsuBQV+fWT8cYWHAkfuXQc9b70AyloVALvEEQS1kvUATd9LAyagxQfTRuEDUqvVA\ngoOPQcIIDcG4aEdA5BetQca8icBjpQBBAgJXQShiCsFZvFtA+UmyQP84hcCltylB6bw+QRnf\n/0CdTBrATlOkQNvz+kBE1mJAP+T/QEQlgsAmSf3A06UwQA7Lh0ATkX1AwuJCQVXMwUAAYSxA\n4Z0RQJs1jsDBMhHBoYy9QL07/j/pFDBBdsqCQY33p8D2mg/B774bQOkNgcDTfsVAAk6SQTYE\nGkBvYXbAgp8uQSWi60ARp3HA/Q2qQVuqH8GTFQBAuu5jQdW5mMCxcYk/DoZbP+rfmsDNOBXB\n2JPTQWkhL8BK3bHAvCeoQdEw0UCW0vk/cy1fQCxvXUFnYhbBPBUoQOwK6D5O4BbBq6/IQYIV\n+b40hYvAqIuIQbkA5UBzqSrA7RZzQMQP+EDxyLhAv6v1QMIDe0BqPUdBn8JrQKJnRUAVgxM/\nUi+UQZqZmsCP3UpAXcKLQdc3WkFOzRTBQQaHQbRjUj9ZjBXB4V0JQUrCQz/3KjtBW3HGQarR\nrkAq2TxBiOOrQY3wr0CYNTlBzTxUQJNXdMBjIgrB/CU8QHqvlsBtumXAaiTiP7C67UBplBTB\n0az5QGbRK8DAnjpAAnXgQOY83EDuPv/AdlnBQVa/x8CuyplA/LsbQWvMQcA9vBTB74GRQQ+c\nKMB+4EhA5enJQDxx2EAMG/vAn6YLQRcBysA5FJZANtvMQZKgR8DQ7Fs/SjbDQZ6VX0HYK8xA\nIW3WQJChsT8/HqZAxUPRQfCplkDd0HVAZOW/QFBff8DhizZAOHfvQfKbW0GejxHB/jPbQZ3Y\n0D8sjbXANGzuQbb4DMEHDp7ALselQStv3EAvDBfB6l2LQDm5MMDnkwxBwy3XQe9/+8AVzJjA\nafi9QF3D30At7Zq/qM+XQes6LsHPN5JA6MTUQYPqsUB4KxHBqqOwQf7Lzz+oQeY/f3rNQTax\nMcGOYUlBT2TsP5Nz8D8c8cdAAuEvQTOpDEB2lT5AA25dP2CGLsEi7LTAD+ycQbq30EBsCBfB\nU2DgP/S1FMAo373AefzDQUfOxEAVLuW/5pqqQaD0K8G8e20+9kRIQACQlsA+dTNB5PukQY4K\nl8AXaMFAGsODQXsGREEqbcFAyrLkQYSLQb/Mb4C/m04kQM+aLcFfVOBADSwkP0pfFcEj/wfB\nxX6jQZOWpsAE2BRAZUnbQe2clMDlWi9A8AfiQeQDLsE9VhbAj/yiQTdJKMEgzUdAQcLlQRrR\n2EApdiNAI/p5QZjVkcDzqFBAc1+tQf4l1kARJ0pB0f8ZQI5yWz8p9wk/QAIdQND/YEGARWK/\nhrgkQJ6g+0CbUzQ/K3xRQJTnmsCVTkFBELnbQXHUjECw7g3BRryUQXsPisABP/HAhZ21QaP7\nk0As6KRAIc3SQbw7l0ANc4xAh0DoQXZVtkC+tTlBV++JQcDug8CZyMdA9Y4IQfQQH0Cj4J5A\nYfcAQVYXnkBA27ZAD7LUQXIle0BrwTs+dV77QCTdYkF7k19AMnYSQO2J0kDMIXA/I85wQbH2\nmMBLOEhBB2byQKNTJUC5pbBAnXQUQA7GFcBQeiNBh5C1QX0VCEHlB1y/QMDPQCa1/UCnNkhB\ne4c6QcMpwj56giBA3BMuQYbikcABBvI/QCOJQcsDl8DLVKdArGkKQUWsIcFmmhpAgFGDQJW0\nLsEAVrLAohjEQc9DzkDSZixAuOKaQS2430D28xdAqzXSQf9sk8C1bztBL54rQW6ZaMB6RfRA\nogrDQepmDcEu0xXBf2nlQaolsT7Nrc7AODK2QagvAsHiiQDAlmNtQWePKcFseLBAr0dQQaMR\nC8DzzgDA3XNUQI4XK8EJdzVAGpvaQUp0W0FAxhTBvOUQQMSTEj9RUnNA1M6aQQ78csCZcLxA\nG6A+P+XoVEAciOHAyYQ5QWxL7sBVF23A9NO4QGAK8kAzi0lBKQoVQBDgyD/O2I4/HOiSQXWv\nX0F9nwfBnaDAQYXTqcCEPkZBZKgOQV4KZ0B880ZBprWVP/fqcr8+Sag/QNXrQei780D5czVB\nJpJPQUJW1UDM+LNALTyBQWbCR0E6mcLAWw+/QWPZxUCFxBbBJmujQbI26L+HD+1AKmS0QY42\nEMEkEqZA7x2cQY0jkkCQZm9AbDiHQfWTgMBJxAXB6SOwQZWmq8AC1lq/wa/1QJwE/kBKCvjA\nSHogQaAljUCInkRB44HrQdURhEAB38PA0AJMQat2BsFZZDlBuA+DQaKygcB22b1AgsAWQHKX\nRkHWiLvAlZqLPi6ZCcGusEpBi2BuQVr6iT+yVN0/x4KqQNiil8DqLFFA6EcuQbQtWEH2i49A\nWEN/QUeZVcBwgixB76xjQXg8sMCsJ65Aw/M6QTEIBMDNGUtAAdhMQQusK8H80/9ANGzhQeyL\nCMGGn2xA3Wi9QZe/d8CyZ37Al1eiQZFo7UDFYXhABuoiQaX1xEDU2LnAmFiCQfkYy0BrjsJA\nXaC/QMY/Vr+WEKs+If7KQXDnL8FXqwnBisOGQMrvNUARTIBA5YXdQTrew0AZQ4xAEGmrQLSz\nuUDabpbAVInSQUsi4kCtAERBip6KQflfWEDKJVvA9C5+QSY98UDvqEVBOoveQfyecEBDWiHA\nLRnbQSsc+EDJOIRAFIA4QYtHvUDDEOfAeDyWQZ64n0D4cMZAxiHtQXQS0z8zB+bA7xCTQc3B\npEClDWLAHs8DQWZw8UBHNsHAeePrQDUTxUDArCBBCHpWQToF0MDLBgjBNEp5QYi0TkD8PcpA\nQkFXQR9hDz/pV0JBCjaKQDCzhkBoC65AbGyPQegMGMCSdUhBdpWyQQs1uT/blEhA892iQa6p\nhsCkNrbA6BeOQYCczUCXeShBW/qEQbDbvMDBtPBAxNPnQRKOD8GAO41AO5v7QKlFt0DyF5PA\nmhHfQL1VF8GCqg5AGrbmQZHHLsHCLZY/Z6qbQUvwL8HBPDpBx9lGQRo0fMBFRZTAsK6VQRJ0\nF8GzHbjA79CUQWgwy0CKwPq+xd3DQbt2+kBKr36+QjPEQSUsL8FfAjxB1MDGQb0+d8AsLVpA\nWwSIQbD7hMClrx9BsmYnQeOh1cCVlBHBt1abQcuidsB9P6lA4ZcpP4RAG8AktCVBXh33P2ts\nBEGhbtHAWY2CQcdmtEBm2oxAnZYAQRuCUEHYMJpAS7e7QQs2PsAPRsi/Zbu3QZns+kCJFe/A\nLbywQRI028Ban9w/xk8YQHmgl8CJ3wRB/zPlQU5BKkEO2Q9BqeSiQWCM+MDezQTBd3m+Qbfz\ntsD90YfAhme3QTsIHMFtqzRBCLK5Qcnt1UAyZUpBIlM3QRa2+r795D5BA1FPPS3gqUDs8Ye/\nTLo3QXsCL8GivkLAroM0QPXPI8F13pVAw/vaQS9wUsDTCjZA2A2xQfAAL8HFO8/A7duxQYH9\nAMEyqq1AtVaJP4ZsEcC8HMBAEZS4QKO0jb/jXm7AKwMxQexR8ECX049AZwnMQQ3Ds0Du8RxA\n9s/FQX5k5kAf87tAfy1AQQdxWUDORkhBZ1yrQdO/Xz8PKwnBv73kQbK+OUAPd6o/64umQSu7\nmsCSrC2/+xXYQTRoLcFqZwTAJIbHQaFX+0D4Ucg/SQShQd/eLsG2jSRA+s6nQVgEk8BbzUZB\npTcbQfsrU0DcUblAoWypQatEwb+Q0xA+x1ntQHHXlcCiOhXBoBLqQTi4cz92UhhABHHPQT9f\nL8GunRPBtsmZQQwIMj/4H3E/psiHQe0s+EA444ZAftX6QMkGwUAbQCZBrfyXQFlFAkHU28BA\nSgCvQXD/hb8R0JA/w8gXQetd8kDsWwXBk87lQeTeV0DSZQnBoacPQQ0rnsCo1hLBooVgQU23\npT+YvhzAKI96QRlXKcFf7EdBk7cWQKntF0AuhubA0DNGQWWUpEBQar6/gpE5QP9JLcHdVIlA\nZcOqQT68u0CBq0ZBgLPoQTzaUEBVfAnBk1akPyCdm8CJE/hAAlbtQTdcDMHw1RVBvO4wQAFF\nGUHT3dbAY31bP9u9+sAA7iJAfMXcQAP24EDepMi/uTo9QbxG+0DwtBM+YBWOQZ2bMMFRKM5A\nlGm1QX92zz82JOfAdJqsQCiFoECuqi9Bd1KmQcNxpsCRbG1ABMekQfaoeMBwZMRAVBd6QRlk\nIUDDJ0FBtcM8QO72JcDdCIu/mK+yQTx2/EDgzBQ/HVF0QAp7L8FCU0JAWKL2QOe6jMDUC8fA\nECseQYt2wkAWGa7AzrKLQNsDD8FW0RM/hJ7HQTd390DOgdO/98vZQMPP/UDGusNAe6LOQYha\nLkC4LsJA4XyaQIV2IEC2Qso9JBS/QJpVY0F9OUQ/O72fQfTAmsDy8sRA3TrZQbDr0L6ODcRA\nK+qQQbUsLkC7q8ZAbtKvQARjdT2l00ZBwca7QG85p796HwBBmh3NQOVHLkH3CqRAGLTAQb/1\nLcALfwfBFZi9QeIoqcDAvhTBlnVRQUGaIMA+pShBSRNJQEAjuMAzCf3Aj6e8QTRmy8D7lsW/\nBFGvQYDFK8F6o+8+2IdoQe3wYEHSEMzAqUaDQZZvu0DLqAPBxqWPQbJtXkA8cBbB45CVQUuG\ngz7zodk+CYqzQLOYYUHH0u7APGwfQSyc38C6wMbACaiuQezABcG8QBXBNp/AQZVkPz/mDgzB\n0PzOQXSEK0BzNDs/5MgzQb83msAtjCFB+NOvQTopCkGx4t/A+vfHQQceqkCb6kJB/WxlQdNz\nB8Bk7GhA0L6KQd+DgsAauHlACujUQWjnKsHwoLw/9uefPzWNm8AgqilBehiTQY1NtMAcni1B\n17SbQDRe70C7FsZAJORvQRWBKUBFWhTBeU0GQfxEOcB/NbrATGCfQfRtCsFgftrA7SfRQR4T\nr0DAZhpBF33lQSGS5cDGN6tAN/HiQab7kUDFAT5BHDPNQR8uUMDt0gTByUmNQdMGXEC22y69\nMEyeQdKMMMFw7bFABfZHPwBlAsBstj/AUjLSQZP/JMENHUdBmoLpQZWf0b6qBj4/7tPuQdiy\n80B+GRjBE3mcQc48H78jCtXA3n1rQcph+sDPj0hBFfWFQa1s6T4qnilAREyzQQzNj8CJk7pA\nu9EXQRWKub/Z677Ae4jVQbT9xUA1Q5tAeTzNQR+QPsCUKNPA6OHlQWgG/cCKkJdAtOzIQR3Q\nqEARlj1BfWaUP5sIrEDP6UZB24zoQUcLRkBDNaI/a+yMQf7T9UBzpypA64C+QeKDW0GftM9A\nmYJWP8KIQEHIHbk/3Ak8vUUTYEF0sAnBNCkFQeNSRUCJnBRA92OQQYrGL8ELyUhBxPyCQQBj\n0z/yUvHAnNezQG9g2sCirk5AGsw3QRuj1UDXm0lANR2oQZ2yi8AuexXBrmHsQMVwJcCkFQzB\nTtNlQV6YLkCVuN0/RNCIQSZrmMAF50hBYjW1Qfd2g75C2TxBTkliQEEAtEBE5GRAWRiiQThk\ngMApYhxBU4zSQJkE2sDLy4q/CoTDQR+b/0BdbxPBTAxnQB/0TsCSxNu+B2W0QQ3n/UD1GGBA\nS9zvQcjcK8EkSjdBFs+TQeksy0BDu84+zZURQesFlsDJxmrApocZQW/57EDxwDZBaxggQCqp\nz0BxtUhBzOgoQNGlK78Pk9dA35XgQHLmPUEkrDdAxy/bQcKy20DNRe7A/1q4QfWV38DWzHlA\n+ockP7/wxEAua7dAGCPjQRZO6b/SgUhBsK/fPWa7eL5ch9K/wAnRQTwbK8GtdjxBzMPCQUXh\nXsAf1MVATOIUQQyuGUBO28Y/AY2iQbmNL8HT0wDACp91QXAu+UCWkD1AzP7gQRJ210BTY81A\n/HzMQXBUgD9JOy1BPGrmQVPFq8AhOgY/F1BvPJIGMME0uIbAMoRKQRlE6EAOj/rAL1JXQKe+\nxcA78S1BsU3VQX0dqcAxSMRAUxVxQW6vNkBQGSs/2cluQPcGMMFTw0RB5ViuQJsCAMDtrTbA\n3vEdQbBGJMHqRblAIt/OQYsy5r+wr9tAMW0FQdhgPEHSo+1AkJsOvbV9D8HVdgfB0dNtQWqn\nUUDTxs5AA3x1QdQiG8H5JZlA/YTsQc8hqUDUqB7AK+/PQb2oJ8Fb6gU+RMq6QQJxLsG7+GnA\n9h7ZQcQJIcG8gfFA7qyPQPJMDsG/16G/KZwFQDYlLMHKne1A1bFHQVBDEMEdMdTASjq+QfCB\ntUBc0aZARwyfQa0OJcC7M9rAoKvcQVnf8cC2Y8lAwHewQQg8d72BNBPBraqJQILHoT81yXxA\n/lfOQSmxKMEko0ZB6AEUQRg9SkCixppAINLgQEcIJsGRqdc/YhDHQXPLL8HT/q3AQSUtQIdy\nD8FAUD0/tfjDQaGsMMFNsBdAPu+ZQbMn40AS2QW/sHiuQXM6+0DZ5onA/DfBQN+YHMET4I1A\n/CIEQWZrWsBk+AjBVO9iQRCKP0BXuERBfdX7QAedb0B36mc8koGqQSs6l8APAfDAaevXQbOB\n3MBHao0+y2VdQRRO+UDnB3lAModKQXEoeMDSQ/zAaRgzQVQkysDXcUlBEwCgQY83oD+p9uPA\n6YqrQQVv7cCyKvTAoeM9QQukjUBOgsDAV9YmQegCxkBws1VAIiY2QdvE00A0HwlBJJekQOE1\nJ0H2MA1BsolLQSWG+8BOCTRBLGB3Qaa52EDA3OhA3KHSQWD9E8HuTDNBn13kQIr3lMCalfDA\nDy1yQexIkkDOVq3A2524QSu5DsFNP9XA5d6qQcjs+8CI+w3BHF/TQI3cEUDrOxTAaZx0QU3+\nKMG1h7w/+qXXQWXQmMAHFhhBLV3cQQpX5cBcLcJAI7RtQQwkg78Ta6pAmnioQY4ZFcBwt4LA\nrcULP+TzG8Gzo7HAKDUwQRozDcETPsdAaMyPQdlDJkBYfqBAh+m3QXqOn0DH3ws/0/uAQJ00\nYkFsaxfBTh9YQY/3FL/u1jJBtC/jQURb2UDTZsJAi42GQbnXRb8PYDnAMbbFQUth9UCIq3xA\n/jIsQe39UkEdohTBCgifP5RnRz7OdPNAScrlQfJpMUH61DA/HWJwQWqi+kDvDKpAvcrYQMF2\nk0C0k3NAZZWlQRIAe8C+PJ5A0jWTQJ4vOcAjuNI/0n2gQbG3l8CLmA9B3WA/QbCq9MDen95A\n2yuFQaPNO0GeiNPAJdG+Qccl/cBqELlAStToQJKZdUB6PoxAp2DYQKAsZMAeOzZABmamQVlK\njsCi96RAlIpQQXvOm0Be+UlBOJLsQUVzdj9Bhj5ApO60QHiOjcDYrcxAJKWGQZ8SEj2zdSVA\nV/wqQa8jWkHOTCJBqPA4QckdzMDtu+NAMKe7QLGSE8HcFEFBmNWYQYtzKsA3iTDAqmfvQeVZ\n9kACJLZACBOMQcL83L9JFqNADg+8P10KmEBNdAzBjXh+QCuDlsA1xMdAgW03QBK6JEDie0NB\nE8HqQc5zh0BBXRfB0nyjQWhYQb+TsVFA+zFvQaLxisCNtJdAWqSBQQkKScCfNoJAD35hQYc7\nKcFlesZAk5O0QUXjFkAQkWfAok0pQd837kCKYT9Bo1KkQSMuQsCj84Y/4wiNQIhY9ECtHrZA\nMeCUQdZCSEGz6Z5AmW99QXB9TkFDWcXAMOVtQc8owUA1TyRB+DmZQRQiB0GK4lU/3u4cQbPt\nMcH74j5Baz2pQFdSQMA2SvA+OpJLQbGqYkGDMhfB4PbZQUDXGr7GrBfBZUSmPwAQAMCfpEpB\n70iYQUQeqT/KEqw+wOTAQENSYkEEBhbBJlmSQDLGBcAOQkdBTAK1QZlzab9OCilBcOuEQRc6\nu8AesM/AQz/JP8iEuUCseJVA9PdYQYkbKMF4ClA/Kb8+QbJ5McHDcgNB3QWBQZI/KkEHo0VB\n/70wQSkmWkBYvcVAObS0Qd++8r48tyVAkUuFQYrKj8CyrtQ+EsfEQeeCmsCPpAFA3JpiP1Nj\n7UDRiANA0I3cQQ7eXEHLDzZATNPcQWzvjsAPDcxAAMauQdBCsz9HnwVB1afAQcgwKkEDuLRA\n3m3aQepOf0A4r3nA7VrFQJif8ED+PYPAcH7XQSAu7EBsTZo+ErvnQXuTMsGhlPxA7zEaQfGr\nLkFGfzBA0GXhQdxv30AZOrZAhTEBQeR+cEC/rRLBU5ueQdpoQcBfjYA/6/ysQQzSL8G/UELA\n4FWmQZx290D/t0hBFOGtQRIOE0DZhkNBeki8QVph/b+TOtS/1TlcQaFY+0DoikbAI1jvPxcw\n9UBsSzdBwATWQXBTykDtOStBa0cAQWCqs8A6ZMBA9kiqQaPNcr/8WOjAsWKRQZUO58ApDCdA\n/NySQSgYkMCl8wlBIEXBQQSzJEFW7cxATm2mQNLhPj8gkRLBDzHSQRDTtT/c9mJAAFejQATA\nzEAlbce/rwisQRzA/kBNtsVAZCuMQTdj7L6Dy9FAjMnJQRQpGsHRu9HAfWyMQXgRt0A/SwVA\nnfwaQZ0mMMEbKYhAJq51PhI/ukARPi1BQoa/QfDB8EDoDj1BkR2bQQoeUsAXyWZA6kyVQcTo\nyEA1uI9AA72BQGwDtUBBxsVAp+p3QdwMQ0EvfCpBrvmjP/Xu80CIqq/ALICvQd4h0UAUMMc+\nmXyKQPM+9kDE7GdAB0fvQSQ5zECqZoJAhmfjQeYTKsG3lNbAAM2SQaTutEDdjBxBWNesQdD9\n2MBkyUhBE+O4QRMlBT/Bax1Bwi3qQWkq2cB5+ghBHbrmPps5A8HZEadApmMGQU2HIsFcxOLA\ncVrXQaCbpkBVkURBfZ3vQRXeZkBf2Wg9txuTQfHCL8GLNLtAocC/QXOmXkAnlIxAuUkMQU3X\nXcC9ESbA8yH2QHlH90BDhBpAsPIwQVwlW0HaarTAHHrrQPHmzUCDSZlAazChQXAKJsFeicxA\nqInLQVZU/D4HsqI/b7K9QQNoL8GQBL3AobEsQdlUCcGADNnAdUUYQfBysUDx7hfBA97JQB9Y\nqL/P9OPA2os1QemA6cDBFkVBa1KYQdppdUD9a3rA9lqFQaPD6kBdHTZB60zIQYqczkCWqx0/\nfOIZQZ/l90CuIgzB45+cQZe/GkAV6qPAMuWkQQCfEcFjwEW844A3QbqNL8EWvyZB9zRVQGqb\nvsBDSRfBUFFPQFqKqr2fesZAuy9GQWQUEEARblhAb/C7QGz3K8HffvS/9O5SQaKG/UDJ5rk+\ny3KLQZ9p90AMk5vAkcfGQap93kCnfofA5RzkQZhL5UASpbdAvLcsQRcSZkDFp6hAWwECQUUW\nlkCGLM2+5guNQXWeLcGgHExAdJXvQfFGicCVGYtAwzXFQSx0YMBOaXbAdjERQQEwHsEAh/i+\nJPNIQW/QLsEC8vTAFIOoQQ6tjUCtt/8/rvKSQVGSlsBXwd1AM2JJQfScOUFhPuDAG76NQVDD\n8cDgXc3AarzVQW6aAMExAO/AM/7hQeJFmkD0Yx5BHXTTQRu2DkEAgFM+FkcGQTHeYUESFdrA\n8hLkQdmZrUCGnQTBPUfXQQootcDihz1Bh1SZQSk2SMDPTcpA3zB7QS3cjj/KIMxAnN9jQTT1\nVz//hA/A+abbQU+x+UDs+LtA0WSiQfrvUECp3xLB8ySoQd/6XsDbd5LAsBedQWR940AE2fjA\nRii7QBGz0MBmUStAGiTAQYW9LcE231JAnCmHQTZ3WEEaXsxA6KzYQZAfyT76oNXA9PbXQYMV\ntEBiKcE/1fajQeupMMGF2/G/x4FLQdY2K8FsC3BAZeNCQdU9x0BHC7VAZEfcP74Bf0B/p3ZA\ngTaDQX9PxkCN4oZAjGvnQRKUvUAWaR6/Shi9QX7pLsG8XA7BxKhVPu/KgsD2+hbBavI8QVmR\n675h2s9AbJyhQCe8P0GEnopAjIKPQXCHuEAKoArB957JQZuPncCqBn/AoYqPQQzAHMFv4hfB\nQaIGQTstur/34yBBzqYOQVYlCkGCiQ1AXGuwQBd9MMHSQjXAaY7RQS/TJMFGHKdAPiiUQb+p\nI8HbvaE/hIJ5Qf/0mcCweA5Bd3ZmQZG2+cC0mElBnuF5QeAv+z7vUixB78C2QdAT80C6d2VA\nOGSJQZdfz0DzdsJAr8h4QeVLZb8ibz49FvY6QcBwMMFhEsBASrXaQbxURUFZzw9BeUQBQG9h\nHkEZLg/BdgV/QRkJAkCpfVVAXKKVQQqZKsHJFFtAVt+pQZorK8H4xerAi4g1QJz4n0CdFzlB\nDfKbQTO8gMCAdjfAWT6JQFYeJcEc4ZDAUTNsQVX6F8G+YQlAX7VPQTY/6EB3JPxACusbQZtk\nCsHB3ZvAJCd8QbmVFMHRwnlAxXE6P8RexUCdeou/kXUMQUjb/ECRM+o/mCPjQT/b6UDcpEZB\nyYuGQSxPPb9mQUdBnYj9QME5er/29RM/02NVQSWXmMCXH8o/9nZ4QVFLmsDTNKBAssm6QS40\nJsF3iog/fjmiQLJN9ECyKcZAty7fQesZFEDkIMlA4AWBQAvKyz8eX8Y/aebhQdk37UCODFfA\nrccdQaZ3IcH+HElBadbEQZm1JT/OxwHB3Ap/QS1nbEBjsR5BgfoQQI533MDBA4PAYaQNQerY\nG8ERek5AzlGAQehl0kBf3XRAi6xaQbaDK8HMLaVAI2+WQdHwmUCoawzBlv/pQMcCkMAxEAXB\n/XXeQcUFYEADwa8/RlaXQRORMcGaL0hBKmAjQEsANkBDCcxAmdUdQVHMvj/Q+XLAXt4mQFdw\n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2 1\n// File 1 is the vertex shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\n\nattribute vec3 aPos;\nattribute vec4 aCol;\nuniform mat4 mvMatrix;\nuniform mat4 prMatrix;\nvarying vec4 vCol;\nvarying vec4 vPosition;\n\n#ifdef NEEDS_VNORMAL\nattribute vec3 aNorm;\nuniform mat4 normMatrix;\nvarying vec4 vNormal;\n#endif\n\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nattribute vec2 aTexcoord;\nvarying vec2 vTexcoord;\n#endif\n\n#ifdef FIXED_SIZE\nuniform vec3 textScale;\n#endif\n\n#ifdef FIXED_QUADS\nattribute vec3 aOfs;\n#endif\n\n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\nvarying float normz;\nuniform mat4 invPrMatrix;\n#else\nattribute vec3 aPos1;\nattribute vec3 aPos2;\nvarying float normz;\n#endif\n#endif // IS_TWOSIDED\n\n#ifdef FAT_LINES\nattribute vec3 aNext;\nattribute vec2 aPoint;\nvarying vec2 vPoint;\nvarying float vLength;\nuniform float uAspect;\nuniform float uLwd;\n#endif\n\n\nvoid main(void) {\n \n#ifndef IS_BRUSH\n#if defined(NCLIPPLANES) || !defined(FIXED_QUADS) || defined(HAS_FOG)\n vPosition = mvMatrix * vec4(aPos, 1.);\n#endif\n \n#ifndef FIXED_QUADS\n gl_Position = prMatrix * vPosition;\n#endif\n#endif // !IS_BRUSH\n \n#ifdef IS_POINTS\n gl_PointSize = POINTSIZE;\n#endif\n \n vCol = aCol;\n \n#ifdef NEEDS_VNORMAL\n vNormal = normMatrix * vec4(-aNorm, dot(aNorm, aPos));\n#endif\n \n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\n /* normz should be calculated *after* projection */\n normz = (invPrMatrix*vNormal).z;\n#else\n vec4 pos1 = prMatrix*(mvMatrix*vec4(aPos1, 1.));\n pos1 = pos1/pos1.w - gl_Position/gl_Position.w;\n vec4 pos2 = prMatrix*(mvMatrix*vec4(aPos2, 1.));\n pos2 = pos2/pos2.w - gl_Position/gl_Position.w;\n normz = pos1.x*pos2.y - pos1.y*pos2.x;\n#endif\n#endif // IS_TWOSIDED\n \n#ifdef NEEDS_VNORMAL\n vNormal = vec4(normalize(vNormal.xyz/vNormal.w), 1);\n#endif\n \n#if defined(HAS_TEXTURE) || defined(IS_TEXT)\n vTexcoord = aTexcoord;\n#endif\n \n#if defined(FIXED_SIZE) && !defined(ROTATING)\n vec4 pos = prMatrix * mvMatrix * vec4(aPos, 1.);\n pos = pos/pos.w;\n gl_Position = pos + vec4(aOfs*textScale, 0.);\n#endif\n \n#if defined(IS_SPRITES) && !defined(FIXED_SIZE)\n vec4 pos = mvMatrix * vec4(aPos, 1.);\n pos = pos/pos.w + vec4(aOfs, 0.);\n gl_Position = prMatrix*pos;\n#endif\n \n#ifdef FAT_LINES\n /* This code was inspired by Matt Deslauriers' code in \n https://mattdesl.svbtle.com/drawing-lines-is-hard */\n vec2 aspectVec = vec2(uAspect, 1.0);\n mat4 projViewModel = prMatrix * mvMatrix;\n vec4 currentProjected = projViewModel * vec4(aPos, 1.0);\n currentProjected = currentProjected/currentProjected.w;\n vec4 nextProjected = projViewModel * vec4(aNext, 1.0);\n vec2 currentScreen = currentProjected.xy * aspectVec;\n vec2 nextScreen = (nextProjected.xy / nextProjected.w) * aspectVec;\n float len = uLwd;\n vec2 dir = vec2(1.0, 0.0);\n vPoint = aPoint;\n vLength = length(nextScreen - currentScreen)/2.0;\n vLength = vLength/(vLength + len);\n if (vLength > 0.0) {\n dir = normalize(nextScreen - currentScreen);\n }\n vec2 normal = vec2(-dir.y, dir.x);\n dir.x /= uAspect;\n normal.x /= uAspect;\n vec4 offset = vec4(len*(normal*aPoint.x*aPoint.y - dir), 0.0, 0.0);\n gl_Position = currentProjected + offset;\n#endif\n \n#ifdef IS_BRUSH\n gl_Position = vec4(aPos, 1.);\n#endif\n}","fragmentShader":"#line 2 2\n// File 2 is the fragment shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\nvarying vec4 vCol; // carries alpha\nvarying vec4 vPosition;\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nvarying vec2 vTexcoord;\nuniform sampler2D uSampler;\n#endif\n\n#ifdef HAS_FOG\nuniform int uFogMode;\nuniform vec3 uFogColor;\nuniform vec4 uFogParms;\n#endif\n\n#if defined(IS_LIT) && !defined(FIXED_QUADS)\nvarying vec4 vNormal;\n#endif\n\n#if NCLIPPLANES > 0\nuniform vec4 vClipplane[NCLIPPLANES];\n#endif\n\n#if NLIGHTS > 0\nuniform mat4 mvMatrix;\n#endif\n\n#ifdef IS_LIT\nuniform vec3 emission;\nuniform float shininess;\n#if NLIGHTS > 0\nuniform vec3 ambient[NLIGHTS];\nuniform vec3 specular[NLIGHTS]; // light*material\nuniform vec3 diffuse[NLIGHTS];\nuniform vec3 lightDir[NLIGHTS];\nuniform bool viewpoint[NLIGHTS];\nuniform bool finite[NLIGHTS];\n#endif\n#endif // IS_LIT\n\n#ifdef IS_TWOSIDED\nuniform bool front;\nvarying float normz;\n#endif\n\n#ifdef FAT_LINES\nvarying vec2 vPoint;\nvarying float vLength;\n#endif\n\nvoid main(void) {\n vec4 fragColor;\n#ifdef FAT_LINES\n vec2 point = vPoint;\n bool neg = point.y < 0.0;\n point.y = neg ? 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IqQS+nZgEwH3jBsDX2HM9q1pKP2rPpT8XUE4/tDDXvjkeg7/0+iU+zZIQQPJI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\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QAA/wAAmP8AAPD/AAB6//MAAP+5AAD/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2 1\n// File 1 is the vertex shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\n\nattribute vec3 aPos;\nattribute vec4 aCol;\nuniform mat4 mvMatrix;\nuniform mat4 prMatrix;\nvarying vec4 vCol;\nvarying vec4 vPosition;\n\n#ifdef NEEDS_VNORMAL\nattribute vec3 aNorm;\nuniform mat4 normMatrix;\nvarying vec4 vNormal;\n#endif\n\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nattribute vec2 aTexcoord;\nvarying vec2 vTexcoord;\n#endif\n\n#ifdef FIXED_SIZE\nuniform vec3 textScale;\n#endif\n\n#ifdef FIXED_QUADS\nattribute vec3 aOfs;\n#endif\n\n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\nvarying float normz;\nuniform mat4 invPrMatrix;\n#else\nattribute vec3 aPos1;\nattribute vec3 aPos2;\nvarying float normz;\n#endif\n#endif // IS_TWOSIDED\n\n#ifdef FAT_LINES\nattribute vec3 aNext;\nattribute vec2 aPoint;\nvarying vec2 vPoint;\nvarying float vLength;\nuniform float uAspect;\nuniform float uLwd;\n#endif\n\n\nvoid main(void) {\n \n#ifndef IS_BRUSH\n#if defined(NCLIPPLANES) || !defined(FIXED_QUADS) || defined(HAS_FOG)\n vPosition = mvMatrix * vec4(aPos, 1.);\n#endif\n \n#ifndef FIXED_QUADS\n gl_Position = prMatrix * vPosition;\n#endif\n#endif // !IS_BRUSH\n \n#ifdef IS_POINTS\n gl_PointSize = POINTSIZE;\n#endif\n \n vCol = aCol;\n \n#ifdef NEEDS_VNORMAL\n vNormal = normMatrix * vec4(-aNorm, dot(aNorm, aPos));\n#endif\n \n#ifdef IS_TWOSIDED\n#ifdef HAS_NORMALS\n /* normz should be calculated *after* projection */\n normz = (invPrMatrix*vNormal).z;\n#else\n vec4 pos1 = prMatrix*(mvMatrix*vec4(aPos1, 1.));\n pos1 = pos1/pos1.w - gl_Position/gl_Position.w;\n vec4 pos2 = prMatrix*(mvMatrix*vec4(aPos2, 1.));\n pos2 = pos2/pos2.w - gl_Position/gl_Position.w;\n normz = pos1.x*pos2.y - pos1.y*pos2.x;\n#endif\n#endif // IS_TWOSIDED\n \n#ifdef NEEDS_VNORMAL\n vNormal = vec4(normalize(vNormal.xyz/vNormal.w), 1);\n#endif\n \n#if defined(HAS_TEXTURE) || defined(IS_TEXT)\n vTexcoord = aTexcoord;\n#endif\n \n#if defined(FIXED_SIZE) && !defined(ROTATING)\n vec4 pos = prMatrix * mvMatrix * vec4(aPos, 1.);\n pos = pos/pos.w;\n gl_Position = pos + vec4(aOfs*textScale, 0.);\n#endif\n \n#if defined(IS_SPRITES) && !defined(FIXED_SIZE)\n vec4 pos = mvMatrix * vec4(aPos, 1.);\n pos = pos/pos.w + vec4(aOfs, 0.);\n gl_Position = prMatrix*pos;\n#endif\n \n#ifdef FAT_LINES\n /* This code was inspired by Matt Deslauriers' code in \n https://mattdesl.svbtle.com/drawing-lines-is-hard */\n vec2 aspectVec = vec2(uAspect, 1.0);\n mat4 projViewModel = prMatrix * mvMatrix;\n vec4 currentProjected = projViewModel * vec4(aPos, 1.0);\n currentProjected = currentProjected/currentProjected.w;\n vec4 nextProjected = projViewModel * vec4(aNext, 1.0);\n vec2 currentScreen = currentProjected.xy * aspectVec;\n vec2 nextScreen = (nextProjected.xy / nextProjected.w) * aspectVec;\n float len = uLwd;\n vec2 dir = vec2(1.0, 0.0);\n vPoint = aPoint;\n vLength = length(nextScreen - currentScreen)/2.0;\n vLength = vLength/(vLength + len);\n if (vLength > 0.0) {\n dir = normalize(nextScreen - currentScreen);\n }\n vec2 normal = vec2(-dir.y, dir.x);\n dir.x /= uAspect;\n normal.x /= uAspect;\n vec4 offset = vec4(len*(normal*aPoint.x*aPoint.y - dir), 0.0, 0.0);\n gl_Position = currentProjected + offset;\n#endif\n \n#ifdef IS_BRUSH\n gl_Position = vec4(aPos, 1.);\n#endif\n}","fragmentShader":"#line 2 2\n// File 2 is the fragment shader\n#ifdef GL_ES\n#ifdef GL_FRAGMENT_PRECISION_HIGH\nprecision highp float;\n#else\nprecision mediump float;\n#endif\n#endif\nvarying vec4 vCol; // carries alpha\nvarying vec4 vPosition;\n#if defined(HAS_TEXTURE) || defined (IS_TEXT)\nvarying vec2 vTexcoord;\nuniform sampler2D uSampler;\n#endif\n\n#ifdef HAS_FOG\nuniform int uFogMode;\nuniform vec3 uFogColor;\nuniform vec4 uFogParms;\n#endif\n\n#if defined(IS_LIT) && !defined(FIXED_QUADS)\nvarying vec4 vNormal;\n#endif\n\n#if NCLIPPLANES > 0\nuniform vec4 vClipplane[NCLIPPLANES];\n#endif\n\n#if NLIGHTS > 0\nuniform mat4 mvMatrix;\n#endif\n\n#ifdef IS_LIT\nuniform vec3 emission;\nuniform float shininess;\n#if NLIGHTS > 0\nuniform vec3 ambient[NLIGHTS];\nuniform vec3 specular[NLIGHTS]; // light*material\nuniform vec3 diffuse[NLIGHTS];\nuniform vec3 lightDir[NLIGHTS];\nuniform bool viewpoint[NLIGHTS];\nuniform bool finite[NLIGHTS];\n#endif\n#endif // IS_LIT\n\n#ifdef IS_TWOSIDED\nuniform bool front;\nvarying float normz;\n#endif\n\n#ifdef FAT_LINES\nvarying vec2 vPoint;\nvarying float vLength;\n#endif\n\nvoid main(void) {\n vec4 fragColor;\n#ifdef FAT_LINES\n vec2 point = vPoint;\n bool neg = point.y < 0.0;\n point.y = neg ? (point.y + vLength)/(1.0 - vLength) :\n -(point.y - vLength)/(1.0 - vLength);\n#if defined(IS_TRANSPARENT) && defined(IS_LINESTRIP)\n if (neg && length(point) <= 1.0) discard;\n#endif\n point.y = min(point.y, 0.0);\n if (length(point) > 1.0) discard;\n#endif // FAT_LINES\n \n#ifdef ROUND_POINTS\n vec2 coord = gl_PointCoord - vec2(0.5);\n if (length(coord) > 0.5) discard;\n#endif\n \n#if NCLIPPLANES > 0\n for (int i = 0; i < NCLIPPLANES; i++)\n if (dot(vPosition, vClipplane[i]) < 0.0) discard;\n#endif\n \n#ifdef FIXED_QUADS\n vec3 n = vec3(0., 0., 1.);\n#elif defined(IS_LIT)\n vec3 n = normalize(vNormal.xyz);\n#endif\n \n#ifdef IS_TWOSIDED\n if ((normz <= 0.) != front) discard;\n#endif\n \n#ifdef IS_LIT\n vec3 eye = normalize(-vPosition.xyz/vPosition.w);\n vec3 lightdir;\n vec4 colDiff;\n vec3 halfVec;\n vec4 lighteffect = vec4(emission, 0.);\n vec3 col;\n float nDotL;\n#ifdef FIXED_QUADS\n n = -faceforward(n, n, eye);\n#endif\n \n#if NLIGHTS > 0\n for (int i=0;i<NLIGHTS;i++) {\n colDiff = vec4(vCol.rgb * diffuse[i], vCol.a);\n lightdir = lightDir[i];\n if (!viewpoint[i])\n lightdir = (mvMatrix * vec4(lightdir, 1.)).xyz;\n if (!finite[i]) {\n halfVec = normalize(lightdir + eye);\n } else {\n lightdir = normalize(lightdir - vPosition.xyz/vPosition.w);\n halfVec = normalize(lightdir + eye);\n }\n col = ambient[i];\n nDotL = dot(n, lightdir);\n col = col + max(nDotL, 0.) * colDiff.rgb;\n col = col + pow(max(dot(halfVec, n), 0.), shininess) * specular[i];\n lighteffect = lighteffect + vec4(col, colDiff.a);\n }\n#endif\n \n#else // not IS_LIT\n vec4 colDiff = vCol;\n vec4 lighteffect = colDiff;\n#endif\n \n#ifdef IS_TEXT\n vec4 textureColor = lighteffect*texture2D(uSampler, vTexcoord);\n#endif\n \n#ifdef HAS_TEXTURE\n#ifdef TEXTURE_rgb\n vec4 textureColor = lighteffect*vec4(texture2D(uSampler, vTexcoord).rgb, 1.);\n#endif\n \n#ifdef TEXTURE_rgba\n vec4 textureColor = lighteffect*texture2D(uSampler, vTexcoord);\n#endif\n \n#ifdef TEXTURE_alpha\n vec4 textureColor = texture2D(uSampler, vTexcoord);\n float luminance = dot(vec3(1.,1.,1.), textureColor.rgb)/3.;\n textureColor = vec4(lighteffect.rgb, lighteffect.a*luminance);\n#endif\n \n#ifdef TEXTURE_luminance\n vec4 textureColor = vec4(lighteffect.rgb*dot(texture2D(uSampler, vTexcoord).rgb, vec3(1.,1.,1.))/3., lighteffect.a);\n#endif\n \n#ifdef TEXTURE_luminance_alpha\n vec4 textureColor = texture2D(uSampler, vTexcoord);\n float luminance = dot(vec3(1.,1.,1.),textureColor.rgb)/3.;\n textureColor = vec4(lighteffect.rgb*luminance, lighteffect.a*textureColor.a);\n#endif\n \n fragColor = textureColor;\n\n#elif defined(IS_TEXT)\n if (textureColor.a < 0.1)\n discard;\n else\n fragColor = textureColor;\n#else\n fragColor = lighteffect;\n#endif // HAS_TEXTURE\n \n#ifdef HAS_FOG\n // uFogParms elements: x = near, y = far, z = fogscale, w = (1-sin(FOV/2))/(1+sin(FOV/2))\n // In Exp and Exp2: use density = density/far\n // fogF will be the proportion of fog\n // Initialize it to the linear value\n float fogF;\n if (uFogMode > 0) {\n fogF = (uFogParms.y - vPosition.z/vPosition.w)/(uFogParms.y - uFogParms.x);\n if (uFogMode > 1)\n fogF = mix(uFogParms.w, 1.0, fogF);\n fogF = fogF*uFogParms.z;\n if (uFogMode == 2)\n fogF = 1.0 - exp(-fogF);\n // Docs are wrong: use (density*c)^2, not density*c^2\n // https://gitlab.freedesktop.org/mesa/mesa/-/blob/master/src/mesa/swrast/s_fog.c#L58\n else if (uFogMode == 3)\n fogF = 1.0 - exp(-fogF*fogF);\n fogF = clamp(fogF, 0.0, 1.0);\n gl_FragColor = vec4(mix(fragColor.rgb, uFogColor, fogF), fragColor.a);\n } else gl_FragColor = fragColor;\n#else\n gl_FragColor = fragColor;\n#endif // HAS_FOG\n \n}","players":[],"webGLoptions":{"preserveDrawingBuffer":true}},"evals":[],"jsHooks":[]}</script> --- # Intuition - Some object embedded in an *ambient* higher dimensional space. -- - These examples are 1 or 2 dimensional manifolds, the ambient space is `\(\mathbb{R}^3\)`. -- - By the *Whitney Embedding Theorem* a manifold of dimension `\(m\)` can be embedded in `\(\bbR^{2m}\)`. -- - In manifold learning the ambient space is typically very high-dimensional. --- # Formal definition - A manifold is a topological space that is locally homeomorphic to Euclidean space. -- + What do we mean by topological space? + What do we mean by local? + What do we mean by homeomorphic? --- # Topological space A set `\(X\)` where each point `\(x\in X\)` has a collection of sets `\(\bN(x)\)` called neighborhoods which satisfy some axioms --- # Axiom 1 - Each point belongs to every one of its neighbourhoods -- + If `\(N\in\bN(x)\)` then -- `\(x\in N\)`. -- <img src="06Manifolds_files/figure-html/unnamed-chunk-5-1.png" height="450" style="display: block; margin: auto;" /> --- # Axiom 1 - Each point belongs to every one of its neighbourhoods + If `\(N\in\bN(x)\)` then `\(x\in N\)`. <img src="06Manifolds_files/figure-html/unnamed-chunk-6-1.png" height="450" style="display: block; margin: auto;" /> --- # Axiom 2 - Every superset of a neighbourhood of `\(x\)` is again a neighbourhood of `\(x\)` -- + If `\(N_1\in\bN(x)\)` -- and `\(N_2\supset N_1\)` -- then `\(N_2\in\bN(x)\)`. -- <img src="06Manifolds_files/figure-html/unnamed-chunk-7-1.png" height="450" style="display: block; margin: auto;" /> --- # Axiom 2 - Every superset of a neighbourhood of `\(x\)` is again a neighbourhood of `\(x\)` + If `\(N_1\in\bN(x)\)` and `\(N_2\supset N_1\)` then `\(N_2\in\bN(x)\)`. <img src="06Manifolds_files/figure-html/unnamed-chunk-8-1.png" height="450" style="display: block; margin: auto;" /> --- # Axiom 3 - The intersection of two neighbourhoods of `\(x\)` is a neighbourhood of `\(x\)` -- + If `\(N_1,N_2\in\bN(x)\)` -- then `\(N_1\cap N_2\in\bN(x)\)`. -- <img src="06Manifolds_files/figure-html/unnamed-chunk-9-1.png" height="450" style="display: block; margin: auto;" /> --- # Axiom 4 - Every neighbourhood of `\(x\)` contains a subset s.t. every point in that subset has the original set as its neighbourhood. -- + If `\(N\in \bN(x)\)` -- there exists `\(Z\subset N\)` -- such that for all `\(z\in Z\)` -- it holds that `\(N\in\bN(z)\)`. -- <img src="06Manifolds_files/figure-html/unnamed-chunk-10-1.png" height="400" style="display: block; margin: auto;" /> --- # Axiom 4 - Every neighbourhood of `\(x\)` contains a subset s.t. every point in that subset has the original set as its neighbourhood. + If `\(N\in \bN(x)\)` there exists `\(Z\subset N\)` such that for all `\(z\in Z\)` it holds that `\(N\in\bN(z)\)`. <img src="06Manifolds_files/figure-html/unnamed-chunk-11-1.png" height="400" style="display: block; margin: auto;" /> --- # Neighbours - Emphasise here that topology is all about neighbours. -- - Similarly manifold learning techniques often start by finding nearest neighbours. -- - Later on we will discuss how the fidelity of a manifold learning algorithm can be understood in terms of how well it preserves neighbourhood structure. --- # Homeomorphic - A homeomorphism is a mapping `\(f:X\rightarrow Y\)` between two topological spaces that -- + Is a bijection + It is continuous + It has a continuous inverse -- - A homeomorphism preserves neighbourhood structure --- # Local and Euclidean - Let `\(x\)` be a point on a manifold `\(\calM\)` and let `\(U\)` be a neighbourhood of `\(x\)`. -- - Locally homeomorphic to Euclidean space, means that there is a mapping (called a chart) `\(\phi:U\rightarrow \bbR^m\)` -- - A collection of charts covering the whole manifold is called an atlas. --- # Chart <img src="img/chart.jpg" width="5376" height="550" style="display: block; margin: auto;" /> --- # Terminology - Consider earth as a sphere. -- - Taking a patch of the earth (e.g. Australia) and mapping each point onto a flat 2-d page is a *chart*. -- - Doing the same with the rest of the world, in a way that covers the whole world gives an *atlas*. -- - Cannot map the whole earth with one chart without "cutting". Need at least 2 charts. --- # Earth <img src="img/earth.jpeg" width="428" style="display: block; margin: auto;" /> -- <img src="img/earth2poles.jpeg" width="367" style="display: block; margin: auto;" /> --- # Manifold learning - Is manifold learning about finding a chart? -- - Reading between the lines of the literature can lead to this conclusion but they are not the same. -- - However, many toy examples (S-curve, Swiss Roll) can be covered by a single chart. -- - Manifold learning is also motivated by preserving distance. --- class: center, inverse, middle #Geometry --- # Riemannian manifold - So far we have not discussed the geometric properties of a manifold. -- - To do this we must add some more structure to the manifold. -- - In our context, this extra structure will be the Riemannian. -- - Manifolds with this structure are called Riemannian manifolds. --- # Riemannian - The Riemannian metric of a manifold `\(M\)` defined at the point `\(x\)` is an inner product `\(g_x:T_xM\times T_xM\rightarrow\bbR\)` defined on the tangent space of `\(M\)`. -- - What is an inner product? -- - What is a tangent space? --- # Inner product - The inner product you are probably familiar with is the inner product in Euclidean space. -- - For vectors `\(\bv\)` and `\(\bw\)` the inner product is `\(\bv'\bw\)` -- - The inner product tells us something about the angle between two vectors. -- - The inner product of `\(\bv\)` and itself tells us something about the length of the vector. -- - Inner products are associated with geometric properties. --- # Tangent space - Suppose `\(\gamma(t):(-1,1)\rightarrow M\)` and `\(\gamma(0)=x\)`. -- - Also let `\(\varphi\)` be a chart around `\(x\)`. -- - The equivalence class of curves `\(\gamma\)` for which -- `$$\frac{d}{dt}\left[\left.(\varphi\circ\gamma)(t)\right]\right|_{t=0}$$` -- evaluates to the same value are known as tangent vectors `\(\gamma'\)`. -- - Together these make up the tangent space. --- # Picture <img src="img/tangentvector.jpg" width="5376" height="550" style="display: block; margin: auto;" /> --- # Informally - Informally imagine you are moving along the manifold. -- - Suppose you characterise the direction of movement and speed of movement at the point `\(x\)` by a vector. -- - The collection of all such vectors is a tangent space. --- # Geodesic distance - A useful application of these ideas is to find the geodesic. -- - Let `\(\gamma:(a,b)\rightarrow M\)` be a path along the manifold with `\(\gamma(a)=x_1\)` and `\(\gamma(b)=x_2\)`. The geodesic distance from `\(x_1\)` to `\(x_2\)` is given by -- `$$\delta(x_1,x_2)=\underset{\gamma(t)}{\inf}\int_{a}^{b} g_{\gamma(t)}(\gamma'(t),\gamma'(t))dt$$` --- # Geodesics in real life <img src="img/geodesic.jpeg" width="367" height="450" style="display: block; margin: auto;" /> --- # Isometries A mapping `\(f:\calM\rightarrow\bbR^m\)` is isometric if `$$d_\calM(x_1,x_2)=d(f(x_1),f(x_2))$$` where the distance on the RHS is Euclidean. -- - This is not always possible. -- - The *Nash embedding theorem* states that there is an isometry between an `\(m\)` dimensional manifold and `\(\bbR^{m(3m+11)/2}\)` -- - Against the spirit of dimension reduction. --- # Summary - In data science we are trying to uncover the manifold we do not compute charts and tangent spaces and geodesics using these formal definitions. -- - Nonetheless these ideas are important to understand the logic behind manifold learning algorithms -- - Geodesics, tangent spaces, isometries do arise in the manifold learning literature --- class: center, middle, inverse #Questions?