{"nbformat_minor": 0, "worksheets": [{"cells": [{"source": ["Mathematical Morphology\n", "=======================\n", "\n*Important:* Please read the [installation page](http://gpeyre.github.io/numerical-tours/installation_matlab/) for details about how to install the toolboxes.\n", "$\\newcommand{\\dotp}[2]{\\langle #1, #2 \\rangle}$\n", "$\\newcommand{\\enscond}[2]{\\lbrace #1, #2 \\rbrace}$\n", "$\\newcommand{\\pd}[2]{ \\frac{ \\partial #1}{\\partial #2} }$\n", "$\\newcommand{\\umin}[1]{\\underset{#1}{\\min}\\;}$\n", "$\\newcommand{\\umax}[1]{\\underset{#1}{\\max}\\;}$\n", "$\\newcommand{\\umin}[1]{\\underset{#1}{\\min}\\;}$\n", "$\\newcommand{\\uargmin}[1]{\\underset{#1}{argmin}\\;}$\n", "$\\newcommand{\\norm}[1]{\\|#1\\|}$\n", "$\\newcommand{\\abs}[1]{\\left|#1\\right|}$\n", "$\\newcommand{\\choice}[1]{ \\left\\{  \\begin{array}{l} #1 \\end{array} \\right. }$\n", "$\\newcommand{\\pa}[1]{\\left(#1\\right)}$\n", "$\\newcommand{\\diag}[1]{{diag}\\left( #1 \\right)}$\n", "$\\newcommand{\\qandq}{\\quad\\text{and}\\quad}$\n", "$\\newcommand{\\qwhereq}{\\quad\\text{where}\\quad}$\n", "$\\newcommand{\\qifq}{ \\quad \\text{if} \\quad }$\n", "$\\newcommand{\\qarrq}{ \\quad \\Longrightarrow \\quad }$\n", "$\\newcommand{\\ZZ}{\\mathbb{Z}}$\n", "$\\newcommand{\\CC}{\\mathbb{C}}$\n", "$\\newcommand{\\RR}{\\mathbb{R}}$\n", "$\\newcommand{\\EE}{\\mathbb{E}}$\n", "$\\newcommand{\\Zz}{\\mathcal{Z}}$\n", "$\\newcommand{\\Ww}{\\mathcal{W}}$\n", "$\\newcommand{\\Vv}{\\mathcal{V}}$\n", "$\\newcommand{\\Nn}{\\mathcal{N}}$\n", "$\\newcommand{\\NN}{\\mathcal{N}}$\n", "$\\newcommand{\\Hh}{\\mathcal{H}}$\n", "$\\newcommand{\\Bb}{\\mathcal{B}}$\n", "$\\newcommand{\\Ee}{\\mathcal{E}}$\n", "$\\newcommand{\\Cc}{\\mathcal{C}}$\n", "$\\newcommand{\\Gg}{\\mathcal{G}}$\n", "$\\newcommand{\\Ss}{\\mathcal{S}}$\n", "$\\newcommand{\\Pp}{\\mathcal{P}}$\n", "$\\newcommand{\\Ff}{\\mathcal{F}}$\n", "$\\newcommand{\\Xx}{\\mathcal{X}}$\n", "$\\newcommand{\\Mm}{\\mathcal{M}}$\n", "$\\newcommand{\\Ii}{\\mathcal{I}}$\n", "$\\newcommand{\\Dd}{\\mathcal{D}}$\n", "$\\newcommand{\\Ll}{\\mathcal{L}}$\n", "$\\newcommand{\\Tt}{\\mathcal{T}}$\n", "$\\newcommand{\\si}{\\sigma}$\n", "$\\newcommand{\\al}{\\alpha}$\n", "$\\newcommand{\\la}{\\lambda}$\n", "$\\newcommand{\\ga}{\\gamma}$\n", "$\\newcommand{\\Ga}{\\Gamma}$\n", "$\\newcommand{\\La}{\\Lambda}$\n", "$\\newcommand{\\si}{\\sigma}$\n", "$\\newcommand{\\Si}{\\Sigma}$\n", "$\\newcommand{\\be}{\\beta}$\n", "$\\newcommand{\\de}{\\delta}$\n", "$\\newcommand{\\De}{\\Delta}$\n", "$\\newcommand{\\phi}{\\varphi}$\n", "$\\newcommand{\\th}{\\theta}$\n", "$\\newcommand{\\om}{\\omega}$\n", "$\\newcommand{\\Om}{\\Omega}$\n"], "metadata": {}, "cell_type": "markdown"}, {"source": ["This numerical tour explores mathematical morphology of binary images."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "text": ["[\bWarning: Function isrow has the same name as a MATLAB builtin. We suggest you\n", "rename the function to avoid a potential name conflict.]\b \n", "[\b> In path at 110\n", "  In addpath at 87\n", "  In pymat_eval at 38\n", "  In matlabserver at 27]\b \n", "[\bWarning: Function isrow has the same name as a MATLAB builtin. We suggest you\n", "rename the function to avoid a potential name conflict.]\b \n", "[\b> In path at 110\n", "  In addpath at 87\n", "  In pymat_eval at 38\n", "  In matlabserver at 27]\b \n"], "output_type": "display_data"}], "prompt_number": 2, "cell_type": "code", "language": "python", "metadata": {}, "input": ["addpath('toolbox_signal')\n", "addpath('toolbox_general')\n", "addpath('solutions/denoisingadv_5_mathmorph')"]}, {"source": ["Binary Images and Structuring Element\n", "-------------------------------------\n", "Here we process binary images using local operator defined using a\n", "structuring element, which is here chosen to be a discrete disk of\n", "varying radius.\n", "\n", "\n", "Load an image"], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 3, "cell_type": "code", "language": "python", "metadata": {}, "input": ["n = 256;\n", "M = rescale( load_image('cortex',n) );"]}, {"source": ["Display."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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l02g0osOBiYHIgE2NlVgi0ul0WBRF3kQsFiuVSji53W6DWw8DgINoVUy9JU6Y\nnWLgzLHMC1v/dDo9ODjAaPF4PJFIwPi9+OKLjz32mIj8+Mc/vnz5Mv0nTIz3ZR40MR6PK5UK7fdk\nMiG5A2YGfH3MttPpTCYTzGc8HuOg53ks4ga1hFYfJ0ynU3rb+Xy+3+9/8g3YQ/w/6dxBc2AKhUKh\nmEuoB6b4aEEl8mQyCZdid3d3c3OTYkjwV9BwBG7KdDodjUZgIX7mM58BK/2NN96o1WrwGFhI+36g\nZMbtOrl48V9dXUUiamNjw3EcXOLg4IAu3WQygTwEMlg4CDcRXghVMFDmbJLUGanDreGKiM4hdIaR\nbdumwIe5XIPBwFS4kFnYEB4Ywol0dLC8mCTjioPBAIHBWCwG/6lUKtXrdXy2LAt/rVQqkUgExHcR\nSSaT8IQ8z8OU+v3+5cuXuea8CzpSk8kkEonAl41EIrwRxlcty/I8DyuGcOKR1gGTyaTb7cLbxo8E\nl9AMk+JOoAZM8SCA3iKMXDUaDSScMpkMsjViNBrGfo19P5/Pk7zQbDZxMnWV7gq2bYPBLyIbGxso\n0kqlUtSSHwwGYRjCeCC0JbNGzxRZp9wfldfJOJeZ2BVDfzAzIObgBGhbwF4WCgVojuASLPkC2UGM\nDB/KvMwMFv4UiUQYV6RRgTFjZzUM63leoVBAVs9xHCxjq9VyHAfZLMuycrkcjJnv+6xSiEQib7/9\ntoggAcabpeGkwR6NRsyiRSIRvGFgPRHvBX2fCSSa5263CxsJxX2sCR66QvHB0BCiQqFQKOYS6oEp\nHgRyuZzneazPFZG1tTURsW0b1ANUE5s+BE6+cePG5uamiBweHtJXGw6HfH9/TxzRdMDneDxeKpWg\no1EoFOAOdrtdSiziA/wJx3FwCWp/4IQwDEEVA3dDZjFSzhxiu7g1OJGmBHAkEhmNRmDoFYtFhM4g\n9YtzEonEeDzGmvAWEDPkJSjmKzOiBxaE0TkuTr/f39vbwyQLhQIuB39IRDKZjG3bcIXBmYTLyAkX\nCoWTJ08i4Hn16lWG9cyWZlSzLBQKjuNgcAgKiwjED8lJgegwrg5PazgctlotXCKXyyUSCZQiqAem\nuBOoAftU4GMU6cGGhVAhdqXRaOT7PmrCms0mdjq0q2eEKh6Pw869/PLLMGDvl/RiMxQkorizs5xr\nPB4vLi6KyLlz55577jl8vnr1KmNrsDoyIxkeSRRNJpNYLIad3bZtNpYcj8ek5CFpJyK9Xi8MQ5gE\n2qfRaMSoYDabdV0XO77jOMgeIfKGuGIkEkmlUpR64hqShT7lyQcAACAASURBVIjYIGnuvAt2+ERt\nHI7XajVaNSqD+L4PM5PL5Zi9azabrVaL60Adr5deeul73/ueiPzd3/3drVu38A5BI5ROp2kOY7EY\no6NBEMA+xePxIAhwXdwXLtFsNhl0RSQT914oFFDScHh4iDloJkzxAVAD9vADrPSPRep7Op3ihdp1\n3Xq9ji3J8zzf96HmFwQBJoZeU3hVRyIEJuHw8JApJe7Lk8kE9sx13a9+9atI7aCjGBwO27a5aX7u\nc5976aWXZMbSRgFZrVbDt1g1jNEcx6HKIgkL3W7X1J3C51QqRStCq+n7fqfTQbU1RQJRF4yrICeE\nXd6yLFjxtbW1kydPItUUBAFKwUSk3W7jW51Ohx4hVgnmQWZ2HYKNsLio7sIJ0NqXmUuEk4MgILOG\ndWCtVqvVamHCpJ90u91XXnnl6aefFpG//uu/fu2116CedfXqVTzKRCJRKBRYp9zpdCgrhReFxcXF\nmzdvovghnU7btk1dRFg+XB1PLRqNuq6L57KysoJfyAe72opPOTQHplAoFIq5hHpgDz9AOv9YQjFU\nbIISOd6+U6mU67pwX2KxGEOIruvCXYjH42EYQjzi8PCQ7+DT6RQu2smTJ/H+7vv+X/3VX33hC18Q\nkUqlcvPmTShUDQYDfD2ZTH7nO99Bq60bN2787Gc/gxBUPp/HggwGg6WlJVw3CIK9vT18sdFowJFC\nGJDMQ/pSmUwGTh4cGkYsUQ8gIuPxGNkyOI4Uv2et9Llz51544QVMkh7hrVu3Njc3MR/2bgYbEEFC\neJ9wdJixGwwGbBEJgh9cKGoTe55nipvAZUwkEo7jIP/U6/WYg8RtYs2r1SpiuS+88MKZM2e2trZE\n5I033vjv//5vEXnnnXd2d3fxUBDLZTgXheqZTMayLDzrMAw9z0PUNJvNItDabDbfeecduIb1ep23\nWSqVLl68KOqBKT4QasA+FXjw1osxN+yqaBuPfdnzPNu2uZmS8jCZTEhJaLVaYDqY+1exWHz00UdF\n5Pvf/z4+7O7uxmKxX/ziF/jMQjH2E6lWq6+99hoiVIgEImoXjUZxLegu0j6hsElE0uk0lUFktoCI\nwrEJMo0EW0UjH4bPDC0iz8Syp0qlghMKhQKGunDhwsWLF//v//4Pl+j3+9SHxLe63S7zcJgtDAza\nN4sR8JRZ42MKU5HOTmvHYDLvmo+MfSxpj007nUqlnnjiCRE5c+bMZz/7WRH50Y9+9J//+Z+cDPNw\n3W4XQ9Xr9Ww2y7I2JgvDMIRII8rIUMbQ6/UajQZij0tLS+gXeuvWrfvVvFTx8EENmOIjAXbAfD6/\nvLwsIjdv3mQ3XhGJxWLsKczKIb6/I5tyxOjatn369Gn0Hzl//jx4ent7e/V6HS4CZHkxGktxgyC4\ncOECEi1MsIlBHplOp91ulztvNBolucCUVsLMYb0oyIRhO50OqRBwIEg+xLXAvuNduK6LPTqdToOf\n8s4771y5cgV3USqVoBkoIqy7chwHzEyZ0TdwiXg8Tptk6jyNRiMKzuLS+NaRKi4Ye57Jp8Nyb3S+\nxiWq1WqlUsHJ8XgcVXTf/e53FxYWfvrTn4oIDDMWJ5fLIe8FZ44WiD4l3htwv6urq0z1BUGAJ1su\nl+H73rx5805/c4pPH/TVRqFQKBRzCfXAFB8J6IGBhXh4eNhsNk11BoSVYrEYZXBxRGav7fCKSEFc\nXFx89NFHIU3b7/fRvPHatWuDwQDcbsgUsWyLfZybzSbcAsgU0bdgWVW/38ccmIQTQ7jWdV0GA3ka\nPuO6QRAwcwMGIMOnuCO6HTKLK8Izm0wmCKPt7e01Gg2zGIBkS7qD5r8cjcFAU86KsUqsJGn0dMs4\n/mAw4LJDgIpzMAvCsA7NZnMwGOAJOo6DDFahUPjiF7+IAOAvfvGLfr8Ph8/3fdAg0YMUnyHDwY4t\nvMd4PI5l7/f7o9EIiUP0dxal0Ss+EGrAFB8J2JQEBgMMaWyFZiDOsizaiWg0ik2t1+uNRiPK/WHA\njY2NRx55BGGlCxcu/OxnPxORfr/PqimGwkQkDEOaHJYeQ0qK8k48U2b68SimZrSQttOUOmTrLwbB\nGO6TWfkz26mYrd04H1S5yaw5i4i0223eL0wsjSvtMbNoZmE1bxNV1WbKjXYCEwOnn9XHuBeYNIpC\n0aiYBdSU1EI7MXweDofgaDz66KOPPvro+fPnReTatWs7OzuUtsIqBUEQBAGeNRJgZOqTvING2DLL\nJjI5CjOP8rIP/TtUPNzQEKJCoVAo5hLqgSk+EiByWCwWyUonNcC2bXQxxpk4CLIignLtdtt0X8CC\ne/bZZ8vlMmjc//M//wMCRblcpqAtO0mKCGn6IuI4Dpy80WjERlkkC6AdJZWiSOczleDZT1lmzZFF\npNPpmJUA1FAPw5DKSdSzZ2kwpDpws7Zts2GYqdtL9Vssmoj0+306WFgZuH3j8Zh14gjW8XJmzFNm\nni5pKYzfjkYjrDkk8HFdavIilgj/tVqtUoDftm18a2trazweg5r4ta997Ze//OXvfvc7zBz+E9xf\nUiUhSoJL4FrQZ+Gwtm0jILm7uwsW4tLS0ubm5nv2FlAo1IAp7jOwe6L0ajAYXLhwQUQajQbljvAv\npQihgI4mwggfIdjFvfsHP/iBiJw/f77T6bz22msiUq1W0dx5OBzCSMgs68M0DyOBNJyQGaR9wvie\n57FgC/IQjFyhXTKCZtQ6siwLJ7daLWrGU0ffdV3f93EJGlT8FXeNwCP2bsuyMDhid5SPYmkBJ8lw\nK0czDR7WnJk85hcBzNZM71H7EZ1ZbpeHJyMxFouNx2PIgkCqHyc4joNV2t3d/Y//+I/vf//7IvK9\n733v3Llz//7v/y4iP/7xj/FcMpkMlboguo91cBwH7yX8K+8XV9na2oJa5unTp/f29hh4vMsfo+Ih\nhxowxX2GbduRSATJql6vh1d10BywcUPBCOaBeaZGo4F8Cf7TsiwYsx/+8IfQ4rt8+fKVK1fggaEY\nVkR2d3dHoxGcKjDgMSCo7TJrOMKC4vF4jH2Tuzw8MDOLRncNO75ZA46EEJw/OlUoXsYcUqkUczbo\nPyKzXtJshrKwsMCcHF1SUjMSiUSr1SIh3ixkZgYRVBExXLdkMuk4DoY1BXP5reFwyAoBepy9Xs/z\nPMw8DEO2TibNJJlMRiIR8PshVolhQWzB/U6nUzDms9nsc889h9HG4zEqnSuVShiGNFoyM0LD4RAE\nFhHxPI/rz9K3RqOB6r1jx46xUOz2ntGKTzk0B6ZQKBSKuYR6YIr7DM/zlpaWoMN0+fJlvNQXCgVI\n5cqMjYa3aSqjw7Ewg2+QWfr+97+PLNrrr79+cHAA3yIej7PjcDwehycEhhu8HzpViIZRxmk4HFIG\nFx5ev9+HtyEzbj3Dd6RBcoQj6TE4c+l0OpPJsJcxu0G2221MrFqtUkz5zJkzKysrSBQVCgXIgti2\nffHiRTiXqDHAlBgnRAbrCIdQjCAk7vdIXFFEKG4yHo9BmpcZ4VNmpQL4DAV65saovoHiYl4XaxKL\nxXCw1WodP34c3jbYhlBI+cEPfoAA4N/8zd9YlgUXzXEcz/PgO45GI7jgJgsRCUgGQiH6lcvlcrkc\nnEu6pAoFoAZMcZ/hOE4ymUTciV1LfN9ntgM0B9otxBht2+52u/iMSOCf/umfikg8Hoe8ITZB7Las\nEgOFgfbJ3PG5cbON/WAwYGiRkzGZBUc47uz+nEgkKIbEqiaaXmzKJHEMBoMjPbFgqGASNjY2Dg8P\nIcDx1FNPoXUIsnQw+aPRiCL0sViMpHmzcI2RQ74TBEFAA4ZUk9nADGsSjUZxFzQYAFnyKHXACTjY\n6XTa7TabsLCcgKnEhYWFjY0NRHTRCA2XOHbs2Je+9CUR+fnPf/6zn/2MNXlk6kej0WKxKCKtVosi\nIxgf60DD2el0crkcGDcQGbmnX6fi4YIaMMV9AzZTcNigZMj2WqivwuaFEisq+2FPjEajpMnZtn3+\n/PnHH39cRLa3t9nxkjl8kiZM3T+0ecQGSlcMZzLvIoZII4ZCrS5dFm7uQRBQ4o9lVaYwEv2YaDSK\nrJ7M0kt0F1jyTNFC27bJWRgMBjDz0M2CHwMXENs0M4JwSVmhTD1GaBWKSDweh+3k8uIEkjlZRmYe\nhNfL8jKSDzkU3CPOnF4pqS6ZTIatQUHQwJo4jgPn8vnnn798+TJoIJDIosyjSU3ExKLRaDQaZZU3\nnOxms5nP52l61YApTGgOTKFQKBRzCfXAFPcNDKmJCHyL6XTKnJO8u0syXAT0AZGZYwFvwPf9z33u\ncyiWevPNN5EscRyHNVjkfENy12QJ8lrMWjH4hhAW/opaNJ5w+xfNCioKzIOATi4fxfUTiQRJ6uTy\nQdueQ8GdQlgSXmm73YZSbaVS6XQ6zD9xBLNFNYWpMAeuJBwadNckTdEsiWN6yVSowp8Q8TP9WvyJ\nzaYRUKWrFIvFyE5k/s+yLLjIqVTK931yO/H4zp49u7S0BA8M8UNmFm/nxIOWiZEHgwEc2Xa7jf47\nIhKNRumVKhSiBkxxH4E9K5PJTKdT7FlMKZm5KBgM7ERsEgbVPpiBlZWVz3/+89gWX331VZjAVCrF\nDL+ZwmEA0BQM5HXFaPpshtGYA6M0lMzYJRgBQTkc5wckn1jkC+IGdnMqCvZ6Pez+NJaQs8J/ep7n\ned7CwoKIVCqVW7duyaxwG8HARCKRyWRg58RI75EcD9PLTBKu63keK8kQAMTlII4l724bbRZrsyaM\nty+G4UwkEtTpdxwnlUqxmxfTigcHB+C4r66uopW2zMg1InL69OnFxUWQVmT2FoKFIjeEEmJIwuGL\nyWQSUehutzscDnEwHo/jbUahADSEqFAoFIq5hHpgivsAsAmgUO77fr1exzs1A2sogz0S18IJ8MAa\njQY1lpaXl6fT6VtvvSUizWaTtbEU2KV8FC5HMaThcMjAIMhs8FfYNIvOhxl15GRARwR3AJoa8m43\nBVQ9shDBo0NTLpDyB4MBORqMzoEngklev349l8vheLfbxbcQbIR0BZpVshgAQ+VyObD1ZEaHYRgQ\nI6BvNZt1cZ05iOmBUWwezE+cnE6nzYWiZspkMsEDWlpaKpfL9KcpQ0xyTSKRYPkEH0oymVxZWWEo\nlU4ww7mZTAY9PPmroP9KbzuZTJLYWa/XGd68k1+m4uGGGjDFfcB0Ol1dXWXZ082bN7EDFgoFlvVA\nl0hmexNp8WT9mbGs69evIzBVLBaxVVUqFTYESaVSzLXwIIZiHgh7YjKZzOVyiFaZ1gXUQXxmFBHs\nc5zcaDSYlGIHZGgv4daSySQ7s0BrQ2Z8QlPFSt4tZi8iw+EQphG9NOXdFWxgBlIhHl/pdru1Wo11\nYGYyD9eC6gdltKjaRalDEUmn02bnFJlZEa6emQzjhEul0vHjx3G/w+EQcd1ms4kcJ9QR8QTz+Xyt\nVkNhA21wNBp9/PHH19fXRWRnZ4d69rlcjrnGXC6H2XY6nVqthlV1XRdvM0jCMa6YTqcRWlQoRA2Y\n4h6BXS+Xy0WjUbyVV6tVtqEajUbY3Uz3yLIs3/dBs15cXCTDAq2hZOaBUYOK9PfprEsyhGVlxqQw\neQpsPQWL0mw2maCCYSDn3pTgo0PDmiRWcUUiEThenDmcDJkRVTCUydrnHZFxQEfTcZxer1cul0Uk\nlUqxOwmvW6/XTe4G1xluqMwqjk1ZQs4cHyB7iIVqt9vktZudU3DdIAj4AoH1xAOiRc9msydOnIBN\nqlQqlUoFq8qe0WEYVqtVCgrLjKvCLF0ul/vKV76CP/3kJz95++238SOZTqfwX/v9fjQaRf4P9BOs\nHqrZcLDb7dLrXV1dVQOmIDQHplAoFIq5hHpginsCXrRXVlaGwyE13S3LgsNBXXPHcYIgINmMOuth\nGOKFejKZlEql06dPi8iTTz5JwVmGs5AswQj1eh0ZI/R+pPdAej0jhFD6IG+QqSBo+Mq7/ScxKObU\nCoFoLzM39CN5O6YUL1ThMbLnefBXwKyD31ar1Xq93nPPPSci8Xgc914sFsn1r9Vqtm2Dw0lXAyNw\nwrZtk2MJMF4nM8l8Vl6z2tpsgkwl/lgsRhImF4FaVr7vt9ttJAWhykH5fJwJP+/YsWMi8sgjjyws\nLMDZxVdw3XK5/LWvfQ13kclkfvrTn4pIt9sln77f72Nx4Mcz5omhut3u3t4e7j2bzZZKJVR812o1\nTYMp1IApPjym0ykSFcVicX9/3+QOwH5wA4VpYZaFwvO9Xu/g4EBExuNxuVxGuiWXy+3v73McBsdo\nnzzPYxMWajpAJoPpLra2knfXn2E09vVAzIpMB8dx3rP/r6mFCEtDSfjhcMgaLJhDCjbiu77vJxIJ\nZvIgzC8iv/zlL9EdZm1tbXl5GYmxvb29VCqFGCONN2KM2NlhLNlCmgQWztx1XTZPoTAj3iR4m9TR\nJ0vevBzDkohV4nbQ7IZBYHzR87xsNvvII4+ISDqdHgwGoLnTujQaDdJAisXi0tISzE+326URZcMw\nMcK57BvQ7Xbr9ToDocViEYtTrVbVgCnUgCk+PCaTycrKiojkcrm9vb3bS1NpG+BhkJXHlA9f6l3X\nLZVK2JsikQh8F5n5NzKrUqIvxZ6Q4/GYNlJmzgFVX02JW2TRmOahnBKnDb+QGSxu1vTbaDnE0Fvq\n9/vMCWE+VFnkLk/aZKvVAldTRHZ2dsCJOHbsWDKZhBeCPB/2bua94KawbycnTOfJpJ/IrLMM7uj2\n26R/dgRcajiaOAjSo4h0u12uKnxo/DWfz8NUowsMHhwfHzKIeC9xXTeZTMKY8UFAF5htXOgdsp0N\nar9gF33fz+VyqEWjqVMz9mmG5sAUCoVCMZdQD0zxYcD0D/q+Q2zefMenB0ABJFOGla4MEx7QpwAz\nbTKZsN8xk0P8IEbHxdFoBOa6zNR+2UwSPgSkKOA/md1SZEbbC8OQLhqoehR9Z/aOHhhuhz1f4DfQ\n/ZKZ68NqAbhQ8CSQqAuCIJFIkO+OE3K5XD6fp4YFiens8yIGGxNUPRZs4UxIIcMDg2AuiwQYkeND\nYcYOXiZrwrgmdNcmk4nneTiIMKbZeRKzgoqViGxvb3e7XTbVxNXhOLL5MvmN9Bfj8TgFjuECMkmJ\nEdLpdKfTwe+k1Wp1u12MFovFsKSKTzPUgCk+PEqlEhL4lUqlVquZ4kDIUcm7Y3rMJE0mE8QAacAW\nFxdXVlZAyA6CoNvtYg9l3gUZGmygvu9ju0cqxew3j/2R+Sd8hbuzWQqNE1C0S6YD0z80dWhZgs+o\nOKZBwgYKQUIcRK0bI4ekgQRBgJN93z9+/DhCan/yJ3+yvb0tIrlczvd93MX6+jo7NTPNU6/XXddF\n6My2bbNmjnE2hPjEIM4AZjDwSA4M7BWELpPJJIOfg8GAay4zE4hvUZOQ2k4igt7KqGajZcXjqNVq\nnU4HdtpU4h8Oh4gKwpyzpQt6hpkPKJvN1ut1nNBsNre3t8+cOSMi+XweHdQ0hPhphoYQFQqFQjGX\nUA9McddgBv748eMo5oVmPA4mk8ljx44htHh4eAgnA34MvTHHceCBbW5u4lX9kUceWV5exnv3zZs3\nO50OW/eSGU8PwPd9Br583welHi4IT4bnAdY7TkaEEPyCfr9PjWD6T2YIy/d9ykexNxiCYBgN85dZ\nlAyeR7fbbTabuItCoQAHBcNiYqurq2fOnGFRMxyL69evMwBr23apVEKVdzKZZCyx0+mwuxgpIWDt\ni0gQBPRloRWCS1NDBDq5JNTwOU4mE7hH5XK53+/DK6KqbyQSoTYxGgsgfJfJZOC3hWHY7XbpqpIR\nyqDfZDKpVqtoSZrNZukmchpw+xB4hAQzu1Gj5BliV3THDw8P0fR5bW3txo0bYjBZFJ9CqAFT3DUi\nkQj01JeXl69fvy4ily5dosZSIpFIJpPYp7a2tqAIVSqV2B14NBolEgkQ8MIwhCH5+te/fu7cOWzo\nly5dcl0X4US2J06lUmztccTMsPkIG6MwEgWJRUrt2baN2CYyOiKSTqeRwMPBIAhwCXZh7nQ6FIWC\nbgWKnKCRKLNAHOWjotEomJnxeJzyHK7rUrq+UChgQ3/99ddhTTExpvo6nQ6sfj6fx8FyucyIGboS\ns+Mlrtvr9UajEYxKPB4nOZ7hRFhoXI5NWEwNe7Mejt9CTgufs9ksg6K2bWPAQqHQbrdhqxAMxAi1\nWo01cJZlMcWVTCaR5pxOpzjoum6j0cBz930/lUqBpTkcDvf29nC/TFJikpDwP378+Nramojs7e3d\nxygiE4SKuYAaMMVdw3VdZHF839/c3JTZFszMytWrV7EttlotbNzxeLzf72P7w5+wR1uWBep8vV6v\nVquwOidOnCAtgmSEfD5P+kO326UwYK/XIzvfzIdh281kMsPhEDssWPj0fvDWf6RhmEmUpw9BVjpu\nk4K2pCHAL8ElUqnU6uoqJokT0C0M3yqVSr7v/+Y3vxGR3d1dEuWDIIAfmUqlMpkMlRVxa71ej35G\nMpkkOZ5F06lUih1kaJBkln6TWTEAaSm4R/AvYN03NzdpDvkegHSmmXfEZ74TFItFVnmjZpxNvFjm\n5boui+TS6TRq1S9evIheaNVqlapRaLbCxQRQFM/U2ng8vnLlioisr6/jR7i7u3sfTY5J5Vd88qE5\nMIVCoVDMJdQDU3wY4A19b28PkhlQuWWoZzweU6Ec3DlTpxUOBN/xMcI//dM/VavVs2fPisjKykq3\n24Vvl81m4YTBFWCiyFTfwEXNfpWmuLt5LXoho9EIb/oQs8DJePVmn2UGvswsC6pxRaTX68EdyWQy\n4ILLTEseZ6Kxp8wUdZeXl0Xk/Pnz8Xj8zTffxHwweebtZMa6ZD9JKkKFYUhHh3dHziRXg7fMymsW\nDlMrORqNUqAE4sIyy+RRRJjF48zDidHokg1QGNWUWbU1nV0sLySsEEb2PC+XyyG++vjjj9MDW1xc\nxCQtywqCgElKDBuGIUsX4B7h+OHhIdKQnudRPPreoSHE+YIaMMXdAQLw2AHr9Tptktnry7Ql2FWR\nX2HBltk5BTv72tpaJpNB8gblTdidY7EYyQs0gTLbu9HBC0d4msw00WVWTsSNngaMAvNI25BZwIil\nKSfIvsa4L6a7cBAROZq9TCZDGgL26EuXLq2srCC1E41GB4MBIqVPP/00wobtdns4HGKEwWBQq9Vw\nCbba8n2fUVNERBGpM/U1eLIYVXfMvaGVDMwAqRZi5KLQV4Vmj62ZgyCAnXBdl1lMotVq0bqYbBcx\nCsuYA2u324lEAtnTjY0NrD8yl3x2g8GAJtAs1GNWj09qa2sLfPpsNlupVMzKAcWnB2rAFHeHaDTK\nVljb29s0VGYVs9k+kR1DQJ8TEdd1qVokIk888YSIPPPMMwsLCyx74oZO7wddHE0GncwKb1llTPtE\npV0xFBRhfuhbkA/CYTHtI9pLqB7DyWbHRUoLYmTMNpfLFQoF1gvjzP39/VgsRsfi2rVrMD8bGxvw\nMjFn9sHa29ujoiPnwO6XMLd0ejABWBESWMzqbxhLTPs9a8NZ8oXnYj5r02Khkpo8UppYMmtGo5HZ\nVoaeLt9mUDmHSS4vL4Okc3BwgMprXo6MRE5SZq8gFPcSkVqthqefSqVo8hWfNmgOTKFQKBRzCfXA\nFHeHRCJRKBQQ0qlUKgw6sczI7FoiMw8M7D7G2UgytG37C1/4goi8+OKLzWYTzOmdnZ0wDBG5Ym9G\nMTQX6NyAts5rUT9XZjQ8uGXkEDI4xq9AG5eNSNg2Gk1hZBZPY7SQQrem7Kyp2+s4Dnn2yDlBaINZ\nw5/85Ce49DPPPIP4XrVaHQwGWBzLkO2nHImINJtNxNbgaeG46R7xlk0iJVnyWAeqZDESC3dZZrr+\nXDpqTVFc3xyBLiDmz/aY9Myi0Sg7W1I2Bbpf8ERLpdKpU6ewICxdkFn7SjHUls0aA/jKnBtO8Dzv\niOOo+PRADZjiToH9ApW8aFhFnnc8HkeprMyU0Y+EdLjnishkMmF10blz59Bvfmtr6+bNmyB0oFMw\nQkzFYhE7WqPRQAmUGFLxIpJKpbCPd7vdTqdDLT5mqljVa/ZzicfjZKhzx2dIUERGoxHVkkz5RBIo\nZGY2OCURqdfr29vbsDTFYhF7dLlcTiQSqD+7cOHCZDKB/tb29jYY4c1mk0a03W57noc9utlsWrMm\nLHw/AJhNhNlLJpO0DTCc4FBQOguZJGpCmu2bWeXN9B4lFlOpFC06850ys9My63xt1uGZRB4+NeS9\nwNFAk7NCofDkk0+KyH/913+1222Tp4OrUOcQvyvcGqKg+GE8+uij4AehtRhpOO/1y1U8tNA3F4VC\noVDMJdQDU9wp8KrOPrkikkqlSOCmTDj6/JIyB9K5GVcMw3BnZwcvyydPnkTY8MqVK2zjm8lkIpEI\nRZLgmvi+T6EHkh7BLIAH0Ov1er0eIld0aMB6Z+kxWQaMO6XTaRDTZVb+zC+SQMHImMnVJg0kDMN2\nuw2f5gjxBBPDbEE4HAwG7Ntp6veHYQhpEghqUJgKJ7iuu7CwgIOdToescZYT0CGTmVtGvgkDsLFY\n7HYSBzsg9/t9emPs/myKm5jsfLNoHboq8u4wJomd+Dp/DKyVPn78OEomnnzyyUuXLuFZmywbkhvh\nIuMzHgomSaXjQqHQ7XbRFpV9yBSfEqgBU9wpELrxfX84HKIAiIqF0+mU9HFu6/LuiiJT6J20vXK5\nDANWqVSYSer3+0yYbW9vQxgwlUqlUilsx+12m40TwdATkdFoRF358XhM9UImzBAAxAm2bTOVRS3E\nyWRC9nYsFkPmptlskqwP6XrG3HA7aMcM+4Rp4xK1Wg3fggwHCfrNZvPq1asikk6nl5aWRGRxcXE8\nHsN+j8fjdruNwim0VhGRQqEQhiGFCqnHOJlM8K1Op0MNCwQbaXVwUYjNk8eIv8Zisel0iqcG0Ug+\nIDZh4dNHrRtzb2b+iRlEshbZyLRUKvG1A9RQcu7PbzIzOgAAIABJREFUnTsnIl//+td3d3cxsfF4\nTE5jOp1G0BU3i9WDAgjizNvb27jEZz/72Xw+j98Au/AoPiVQA6a4U0DFzvM8dhIhQz0Wi2WzWXKd\ngyBgNoIZI4oWQvwJRTzr6+tIp2Hn4os/bJiIRCIRbNyotMU+1Ww2meti5oaUCjE47hiKIrZ8f+f5\n2Lgp5mvbNjNJsAe+78diMTZfbrfbVBfEHMA+p2vC3dZxHNgGlJFhl8/lcs888wzM/29/+1vo1ZZK\nJVq4arXaarXovmCq7XabuTeT747SK5xDRxN+DEsLzMU5AtSbm4sDi4uaMDzraDRqKkmytQqsS6FQ\noGqXGLR7zsqyLDZsy2Qyvu/TLGFxnn766cXFRZQToFsNXHbToeft4Bx8kfZ4a2trbW0Nb1dhGEJd\nWvEpgebAFAqFQjGXUA9M8fuBZAn1h/h+nclkKNNucuQYwqJOK6JS9MBEBIq3Rwhm9KKgDCszdXaZ\nEepIn4OvALI7L8FYH0OU8DBYhkwStmVZoOknEgneDkagXAWdSBLB0QUYc6BPc8T/Q5hRRDzPg6+A\nji04OBqNWq0W5haJRHZ2dkSk0WggmicirVZrOBxiwmTigWhOEjy9sVgsBs8jkUgUi0WqkJBCmUgk\n4L9C7IMzZ64LjFDcO9NOXDHGY+XdOTAIjohIoVDIZDJmzo+ZSywIpKHAts9ms9Fo1JQLEZGNjY2z\nZ88igwXuKCvfmdLjQ4cKDH4Y/L1BOBiXGA6H6oF9qqAGTHFHILd7MBgwjMZiHbTawplMeokRBLNt\nm9R2sLShIIUQk8wk72iKmKMaDodUQGfpj+u6pCHcnrmRWbxL3l01JUb5F9Ua4/E47SLEPmBdyE+Z\nTCaJRIIsiUajgQmbclliqL/TTpsMi1gsRt45QqYi0u/3QdxoNpu0cFTfMIFhWQvFXJTrulCoymaz\n2WyWik2DwQC2M5vNsh6LnBHO3BSl5GxlptolMxV8ajCysi2TyYDCHovFYrEYjEckEmH5BDUYO51O\npVLBCWDkM/jM9N65c+d+97vficjW1la/38dzj0QiWGcI7bOSjzpYXCXoV2FiyWSS4veaDPs0QA2Y\n4o7g+z4NWKfTMQtLZVYPS5Ib8/am/iENmGVZ8XgcBoyFq0csjeM42IaOZLC4mbJyi2W5ZK+J4flh\njzYll8gtpBNDe4BxuBXy1rAt4t4bjQYJHTSHnDlry8So9gXDgkVj/X4fc+v1emzQ5bounDzQXmhU\nML7pO+JdAU5PMplEM5pcLpdMJpmsYucaNqCB/eMdYVgcpJQwE2b08Pr9PvuiYc1hlkqlEjw/k/oR\niURIwUDbM5npH3L1KCXF8jLP85599tk33ngDl9vZ2aG0FTuKxeNx82mSwIKZgwGL+0XLTRIvFQ89\nNAemUCgUirmEemCK34/pdJrL5fCSC4cJ6Ha7CL5BHQqvxmCN4+240WjALQCZkAqwy8vLcB2azSb8\nnmQy6XmeKQvL2Bf9NroOo9EIGSx06zD7NJpkfZlpRmAopLjokeBGkK25Pe8lM1csk8kUi0VWkvHf\nSqViKvGbzg25fIgWYlZYHDNZCHUM3iNGQwTsiKIEcpD0RKGnLCKLi4sg4nuel0ql8K10Os3nQu8T\nq8cR2GvGtm3E9zzP63a7rDfAt5A2AxsQfjOzWaht6M+AebJ4rtfr4da63W6r1cIJSB/ieDKZxPoP\nh8Nnn30Wsv1BEDQaDXapxmQODw+LxSLbkPIRu66LibXb7YODAwR+M5lMPp9nkFbx0EMNmOKOkEql\nUOpUq9X6/T5p3Ca7AREzJEWww9ZqNZPdzj36mWeewY5zeHjIRFEYhkzXcw+l0UKIcjprcYIECZjZ\n1GDkCWwZDGvKamuOTykpmdHcZaaxxEgpNuuFhQU0g5ZZzgknNBoNbMEwTpgtKR4yEw+UWQCQ7AbK\nw5PrTzMmM7lFWFzGNvP5vOM4SJiJSDKZPHHihIi89NJLiMRCaxEnoJobI1D5HgbSzBHiX/Toktui\nlAzV9vt9RlYty0J0FJVYIlIqldj2DHcHpah6vQ7yCAwnRRoZ/KzVarDojUbjxo0bMDnpdPrkyZMg\ndARBwIhopVLBouVyuWKxiAlfv34dP0jHcVqtFsxeMplcXFy8fPmyvFsYTPGwQkOICoVCoZhLqAem\n+CDg3Xl5eTkajTLmZts2QmoLCwsI5VmWxf5MvV6vXq9DS6Lb7eIEOEyIO506derMmTO7u7sighd2\nEQE5gkE5atdSFUkMniGJ4BDRoM4TqXTkgDSbzUajQQI6GR+JRAI8OvDs4WD5vp9Op+lgkZdB1ahM\nJnPq1KlHHnlERBYXF//t3/5NRA4ODhjXikQi5K1QJh9MB3JMzK5mcEfMI2IUIbAjcyQSOTw8xBqe\nPn362Wef/fznPy8ijzzyiDlJKlclEgnc5ubmJg6S3slL4OqpVIoKYeYc2Co6Go1SXZduMfn0YRgm\nEgmKjLCMIRqN4rlDdpkyWrzleDyOn9DVq1evXr16/fp1/FrAQBGRer1O8ohlWTiYTqdLpdIf/MEf\niMirr776z//8zzKTR8Fvr9/vZzIZUPxBr7+D37hijqEGTPFBwKaGtAq2IWwlZotImWm3MxTGtAd7\ni1iW5Xne448/LiJf/OIXS6XS22+/LSJUoIBeAwl+pLNPp1MKW0xnIn4MFZppLTNBAkMi7xZ/Qi9j\nyinhdlzXpWrR8vLy0tIS5nDhwgVm+7gdF4tF3/cRHf2Lv/iLxcVFEXn55ZevXbuGiJnruqVSCbcM\nET+MQMEL0CZZl0aLQn19aDtRxQp/bbVap06dwsZ97ty5crmMNRmPxwgbIitGQSxKPfm+D4MRhqHZ\nspl8UWYu0YLyiIWD6CJPMFvkoNwKUVC+avi+z6VGWguKhQyfkqoKkywiuVzuK1/5Ctb85s2bb7/9\nNk547bXXzBgy/m2321evXn3sscdEZGVlBSL35iXa7bbv+5CMaTabGkV86KEGTPG+oIDhwsLC4eEh\nuwBzL6M2rmVZZutk5oFisRjLhF944YUvfvGLIvLUU0/duHEDO286nSb9IZFIwBNCsoSysLc32zVd\nolwuxwprlhm1223MPJvNJpNJFtVS9pAFs0cyQ2aFGVyEdDqdy+WQD4MNYB7umWeewRxeffVVVDLB\n48FdjEYj9kLjvyjGYlWT2ciKNcKu68IxRUkyVux73/sexLcoF4nFMXsZ059jcYLMUmu4dxpOdoph\ntbWZJLNm/WUgCQZrappb3gLYOvgNsIxMDHo9G6/gZLO1DSgY6XSacszlcjmZTObzedzFa6+9dmTY\nfr+/t7f3q1/9Cr9JcmpY0hCNRknwUXwaoDkwhUKhUMwl1ANTfBDgeSQSCTNBRfEFKgNB/R3v0UEQ\n8PWfrtixY8eef/75p556SkQWFxdv3rxJP4av2KTt4QUflygWi4jviUGpl1njEihQwANAugtzgDAV\nZmjNujCbKviDwYDv7AjriUi3263X65h8p9PBi3w6nU6lUvAbEGfDydTWWl1dtW0bdbuvv/76pUuX\nQNWjdonpQU6MVpzM2JnSEpZlsTvz6dOncWt//Md/fPLkScwB60y5CjY7JqcR8VVMEh1MZFaGTNKj\nGXQ1y6XN0myZ5RqZ4mJ3Zl4LjUz51FqtFnNRdLCo7RSNRpn64vNFPxdMEgpV6AJ67tw5KPyy6zcQ\nhiFoipyY53mmGgtFQFgUoZmwhxhqwBTvi+l0Ss436dSIs7EuBxtWEAS9Xg/GAz2iGDGD+Tl79uzj\njz++trYmIpAkR6TI7G6MEJPMCpWQajpx4gRKncDGPtIyOJ1Op9NpUKjRW8TU45BZQohKUQx1siAJ\n3U9wa91ud39/n41aMHPP8yDKLjOuP3uS4RK+76+vrzP42W63t7e3xQjEMeHEOfCz2ZmFIVPHcdCl\n+vz587jWM888w1YyEPjAHZHuwdySzEKpbMGFhzKZTExLwwyiqQFG9jyBr5jTY/CT1A9m7CDziNjm\ncDhEIgrnY3HQKI5hTDxfvLVQ9jAajYJc8+ijj4INT6MoM9sMzj0qKGRWU0HLats2LheNRhm+Vjys\nUAOm+CBgZ+l0Os1mk0l17IYi4jgOiAatVgtNUvhFsuOQcv/yl7984sQJmATXdU+dOgXWw87ODlke\nyFdxWLxfLy4unjx5UkR836dZYg8wNMGiXm2tVmPiCgcrlQrV/MQo+aLhjMfjVMlqt9uVSgUj93o9\nSurxWzKT65V3q81Go9GVlRURga19+eWXRWR7e5v10TQwg8HgSKm1zLJflB88fvz4l7/8ZRE5f/48\nlrFQKAwGA9wRQJ1GTBLOnNk3kpK43P2ZjgrDkELJtm1jnXu9Hr0xLhdq7EyBSibqaLCTySRq0VAd\niJtiN7VKpTKdTsF2QTKSCTPWhudyOZYVksO5sbEB0sr169f39/dNJioJrvB6B4NBvV6nWxyJRPBu\nFI/Hqbv4Pr9uxdxDc2AKhUKhmEuoB6Z4X0ynU7hE8Loow8r2Ir1eD6IMiIyZX8Qb8enTp//8z/9c\nRF566SVWkolIIpF44oknRGR9fR0xLhDQ8U6dz+dHo9GtW7dEZHNz85VXXhGRVCqVz+cRmMrlctSM\nn06nyLJsbW01Gg2Umn35y1/G1//hH/5hOBzCRUDLElxuNBohVIiQHWbb6XTYRhl8NjG6D8sston/\njEajlJ2lg+U4zje/+U2oZP34xz8GNdHkmps0epk5YcgtYbTHHnvsL//yL5EH4qo2Gg02KGF1FEZg\n304qRaETDZ5LvV439bfYxoUeDztMWpbVarXogfGW0SEanxcWFrCSx44dg5eD5tG4VqvVosCu7/uo\n89vd3S2VSngokEfhaKChRiIRZBlFxPO8eDyO+ZTLZcQSX3/99ZdffhnPAvFMzI3dwNvttllI57ou\nvWFqlygeVqgBU3wQsKNVq1WmE1BljP+8fPnykaQUYFkWNpFvfvObn/nMZ0QEgT5G50imKBaLCLsl\nk0mTQcACps3NzWvXrolIGIapVArBqEceeQQMC9/3B4MBeNWbm5uxWOz06dMiUi6Xjx07JiJvvvlm\nr9d78sknRcTzvHa7/dZbb4kIO8L0+/1qtcrPnU6HhQEsfzZ13OPxOKJn0+kUgTiYGZOv8fzzz4vI\nxsbGP/7jP4rIK6+8sr+/jy04nU5Td8qyLAZCS6XS2bNnReQ73/lOsVhk7TAWJBKJsF6beSwx8nBh\nGNL8oIPJlStXRGR7e5s5P7RZEcOAWZY1Ho/xLuK6bq/XY7IQl+50Op7noXD77NmzxWIRV+x2u3go\nV69eZdAVjWAYYyTlp9fr4WXiCPATCoIgDEPMoVgslstl/HJOnDiBROC3vvWtCxcu7O3tyczSI/WF\n+nERKRQKVA5rt9uvvPIKRoOJVTzc0BCiQqFQKOYS6oEp3heRSARhnJ2dHYaVIpGIWWmLV/LTp09X\nKhV4JAiRffvb3xaR73znO4gONZtNy7LwUry2tpZOpxn7wrBwDkjPu3Llyr/+67+KyPb2NgNuaMcl\nIpcuXcKZqVRqaWkJigzPPvss1RnCMMQL/le/+tXt7W3qSiBgKDN6vczaMB4h34vIZDIBaWJrawsS\nsSKSyWQ8z2O0ivxyemC2bfd6PVwik8l897vfFZHjx4+/+eabcFkSicQzzzyDuf385z+Hx/PYY489\n/fTTL774oogkk0lQZsRQHIZLAdYD2OEkobB+PAgC0GFarVan00EglOwGFBvgqVG7JJ1O07E7ceJE\nqVRCfI9izfl8nqHLYrHYbrdBbX/nnXfwQWYNP8XoGCez4mKZtfUyFcJIvMSHer3e6/Vwvzs7O7Zt\n40fy3HPPfeMb3xCRP/uzP9vd3f3Rj34kIleuXIH2Cq67tbUlIisrK4gki0i73W61WnCycVxm7dkU\nDyXUgCneF57nmQQ5ltdw9zx37tw3v/lNESkUCn//938PRTvLsh5//PGvfe1rIrK8vIw9EWEr7JWN\nRuPg4IBdB7GbDwYDRLREpNPpbG1tYd/JZrPYuAFWj7Hm7Nq1aygMOjw83NnZQeRweXkZ36rValeu\nXEGSjO1LZGYMZGbqGDqTWVzOcRxcYmdnh7s84lfMP9F4cGJYJZzALotf+MIXTpw4cenSJRG5devW\n888/D4PU7XYhrP78888fP37cmnW5HAwG2NyZbzPjkyh14o0witjr9WCfqtVqp9PhJNkWkmV2UOgX\nEbxGwAyI0Wd5eXkZucZisRgEwd/+7d+KyI0bN3zfxwisjkgkEuhOIDNOoxmcFJF+v89GMIjK4rl3\nu10mRBFWxclBEGDC169fRxT085///Llz5958802ZdU7BstOy7uzsUDQS7XXwNJE0xbAmP1bxMEEN\n2Ccd+N/+Y6ECs58vdii+OzuOg3fb9fV17BGoKsXJnudtbGyAyDAYDGA8KpVKs9mETUKnDLIe+IJM\nEnYYhpPJBI7XYDDACfRyZNYHRGYlTdgKt7a2Wq0WXDSOD18BpgiU8SPKfvF4nN2ZIYDEGmFcazAY\ngKogIr7v8zZpD8QoT8a0j7DV0+l0sVjEgCj9xvFyuYz0Uj6fZ4+uVquVSqUoc8X75RZs/hh43Waz\nubu7CwNWq9Vgw8SolR4MBmwrw54m0Ovit1BRICLJZBKW9fHHH0+n0zgYhiEtK2vDUR14RCnYfJSw\nWLc3bAuCgNLDfB+CxhUnCUvWbDZ938fPKZ/PHxwcYPUymQzLz1mWDrCDjPnqo3gooTkwhUKhUMwl\n1ANTvAfwTp3L5fDij1da1u1GIhEKBeH1GS2AkRMqFArr6+sgxLfbbfDHtra26vU6HAuIWbCnIuuF\nxQjEsTszcx5HVC0Yy4pEIvQAgiBANuXw8BAn9Pt9tjJB6shkrosIRPQ5LKN2vAS6geDWcO+InjGL\nNp1B3u0mRqNRqrBHIhH2UB6NRnCPCoUCHAt0P2EgjoOQMo4ALMUmmGFiYrLf7zcaDei712q1ZrOJ\npaazJYYAB4WMZdYJEwe73S6cHtA1RSSVSp08eRLU+d3dXYjT44tU4ohEIniCmDk9IYrr06m1jIaW\nMqNTIthIr4tqv8ySggmJkCYinPg9LC4uIt+5s7NjKk3LLOJtqpQpHlboA/6kg8rfDxK4YiaTwb7Q\n6/WYfofYAT/DttVqtV6vhyTZ4uLi+vo69pqDgwOkWLa2tqj3c8RW8T/JVjf3HWoPIuiHE0j9QOER\nN1NWdLXbbdY8ofxLZgE3bKb9ft/s40xeO6upzK7EzWbTFILCCYlEgs+FJgcfcHI8HmcHNWz0IpLL\n5RjrW15eRiQWNoD1cDLb3GnAsPiYORaEehbswdZsNhkM7PV6jNpRfZ9rPhqNKPrFGKOpkjUYDHD+\n/v4+q7hWV1fJ02F0Djknxnh5m2i9xisynMjXAvO6tKyI8cLSl0olZgpjsRgNGB/W2traCy+8ICKX\nLl1688038Z5EUTERCcOQslW3NzRQPBxQA6Y4Cu7Rk8kE+4JlWb7vU4aVHD8260JKA24Zyl2xd2xv\nb4PZwfbwMtvlj7RGpE2SmS+FEUAdFBEKEopIt9vFwXg8zn4r2Pq5X5v/yfQMq7uYuUEWB9NDdxhc\nBW1NcGav14MpajablFtE90vzFjBb6mzJTAoZan64XCwWOzg42NnZEZEnnnjC3O75TiCGAcM4rDuW\nGcEPcwiCgIpclUoFibper2c6uDS9SEGJ0bsS9eYs3GYrGao4Oo6zubmJcuDRaETRSBJwzORcJBIh\nX8P0EfmGYVo4tm7BiwKFoOLxONJv5XIZP6der0d2SS6Xg660iCwuLm5sbIgIfP033ngDJ9NWsbwM\nmlJmik7x0EBzYAqFQqGYS6gHpjgKRmyi0ShSSo7jpNNpUykDsZq3334bH/b394MggNj82tpaqVSC\nT1Or1UjBJ9+s3+8jNSUimUwGPke/32cZFvwqyjvhA3on0ikx45Bmc0vMPJPJ0MGC2K7MvAGy4Bh8\n4wgQX8fEmNoRoykMHAvEuDKZDL51hOrGb9Ed+X/svUmPXNlx/h05Z96cay4Wq8hiN9UDe1BraEkW\nBEveGPbCgBa2t175a/krGIZkAwIsC7IEST1ZPZPNqYtF1jzkPFfmf/Hr+yCqKMl6312VTywa2Vk3\n7z333MsT54l44gmYdWrIYmZAJYFO3yaGdBeXuHBaUGAqlYqiiPOcnJw8fPjQzD777LODgwOmdzab\nqV2AkC55Jo1BHMJut8upoihSQNJitNdut0ejEY+S7pdSJyEI2W63S6WSgoG+oo45p5G3yI0KDksK\nGQ49BywsLMzPz4PANL0ooZB3XFtbu3XrFmL/Jycn7777rpmtrKwsLy+TDzs8PGw2mwohqt+KmgEF\nu2IWHFiwczabzVKpFAtop9OBbpBOp0VnJ61CcKbdblOss7+/j/6TufS7mZVKJaXiVZYLV0L+g1UG\n7UF96RvV+x7KShExwkKhMBgMdN1qtcpKl0wmRZ3P5/OSZlfkajqd4nqhhnMGL1SvMCnBPRFYLE60\ntFot+nqsrKyo50g+n2+1WgrKPZ8tM7NEIsEBzWYTGS0yc3ga/cpc+hPHgPtBiZ8xPHv2DMnBdrtN\npZfF6S5l9bxMu1qrqD5akl0EOeWfVDjx+uuvX79+3eJuNXzf7XaJLe/t7ckV9Xo9diEWe1ndmmgv\nBId5LtSGr62tqdSPMCZjOzk5UZs09k9mdvPmzTt37qgbtSoE9O5Vq9VGo8FL22w2iTGurq4OBgPP\nFQp2ZSyEEIMFCxYs2KW0gMCCnTMAFtvndrut/XuxWGR7Lt62maXTaaBAt9tdX1+nqDmdTh8dHXGG\njY0NOGxEukQiYL9sZsViUaoTaq0L2OLSq6urgC3IGqKrqWmhVIDpPMmZC4UC8KjVaomJR4xL7Sj5\nEho9t8ZFRX/w4UquCyxjL08zYm6B+JsOVjxQKln6BiVfUfk5FVLIkquQQBczg6movNvtSgB+b29P\njEfxFCBb+uZtjGQwGEjeSSNPpVLQQGg1yXgGgwGTcOfOnR/84AcInXz66ac7Ozs8bgnql0olWOwW\nU04k3cKR2WxWxRiAXWK8m5ubPEEkV2C7oMlLpLRcLhNLpGcmAiv5fH44HH7wwQdm9sknn+hXe3t7\n/CqZTC4tLTHgJ0+e8O7xrIWn/8x/CMEuhQUHFuyckeq40PWRDh2EDeGwaaVj8aJ3s5qhqOtgtVol\njNPpdLSAQtuTr9JVvJ5FFEXi42llVEgtl8sRlcL9kKg7Pj5utVpEyd5++22ic71eb3t7W4VKPo0n\nSqRKzYhWeSK7xTx7SR1anOU6OjrCi0RRtLKyIgcWRZHI3PqVCqRUgWAxXdBi/p4nGf7BhA1LcLfb\nJVjHrDLP6B96kidnUFyx0+koKqu4IvPGPOMtuLVcLkft182bN7e2tiRKqUnLZDK8DP1+Xy9GtVrl\nPWE8ShCqYqFcLi8tLW1ubprZm2++ySw9fPjwwYMHamQK59PczqZQKDx79ozHXSwWX3zxRRiJd+/e\n/elPf2pmKysrnU5HU009hpnVajXevf39/adPnwbXdSUtOLBg5wz4xYpD3xM7LyALDFKZkXb6xWIR\nn7GxscEuGxMrWqJ5ZNdZKz06McezF+db6nmsxUo1sfuGV83KTtMs1qmjo6ObN29yXUlJXVjCVBQl\nb+HVZi0mMoDPfD0Tc9JqtWDDIy0oErwGqfpcfzl/ntlshvNgehketPILqRogoH4lT48oFx8ET/3l\n9OWF1JqwmrKJAFzGU6lUWPrH4/HHH3/Mbfp6RNViHx4e9no9kHexWJQG43Q6VdFFPp/ngGq1Ojc3\nB/AaDAZojJFC8yXhql7gqY3H48PDQ+5idXU1m83yZH/1q19pSiXExZMSf0cFGNoPiWIT7GpYyIEF\nCxYsWLBLaQGBBTtn2Ww2l8v5WJnFsECbeiEAn6QplUpQmZeXl8vlMpmV6XQKf2xtbS2ZTBLvYp+u\nUlztoxU6I+AmhMQwUOLw4USOzGazQmOj0UhojERIqVRaWFiQuuvZ2Zlig2zPSXqpbtdX2kpcw2JS\nnz94MBiQZqvVap1Oh9tEX0oYggsJ8ch0y/4SXjVKWEc5P50BJQ7QSb/fF7HQn+cCXNNpL3xJHbp6\nzaTTaaDz2toaOafT09NHjx4BDZHk1zD4gLqKwJZwpLelpSXOhvwx0O3p06ew4RF5kRiYRJzVAWA0\nGsFxNbPhcHjt2jU6Xqrsmicl6rxkmgeDATFeavCJcwYEdsUsOLBg54wImI90WZz2V2RMfHdvlUpF\nkSKLWR6pVEoU6nw+r2BUr9e7wJWghZVkDzOZjPJSSm94nT0CUORg4Hmvra1Vq1XG/F//9V/vv/++\nmb399tsbGxtKSqnHsXItiURCOb9MJuNdo2cleJE9TGz44XBIW2G+Jx1oscaHnS/z8jEuaRKSAFPD\n5eelj2auU8l4PKa4ymIJSkZOAk8/USjvApvDmw9ynp2dLS0tvfTSS2b24osvsif47LPPms2m0mOq\n3vOiHmqKRnkf85BMJpnqbDb76quvvvDCC2a2s7Ozu7vLxsLMEPhoNpulUknRwmncXUx1h1wXQTK4\n/qRaK5WKlEfMRWULhQJzMhqNPvvsMzO7ffu2eEnMW7ArY8GBBTtnvV6v1WrN4o71XijPb5NZXGgO\nwg+vXbuGr5rNZkdHR3SRV/uS+fn5mzdvAlNqtdre3h6rT6PR4LRIN2lPPZlMWCsFB8mcqaMVun+P\nHj0aj8dcYm1tbXV1FeLZ06dPWSi/8Y1v3L59m/UxnU7v7u6ywlKzbOeRHxqDSvWRHGLhk0AiTs4c\n/eRCjZe5vmIcSQsx+adSqaSkkUSnvHfRwb7fmMVoDMFiVn/lnBKJRC6X43ivn6sxUFnM0zw7O8O7\n9Hq9bDYL6ioUCisrK/iGTCZDmdfh4WE2m+VUjUZjNBpJ40pPJ5FIgLbp5sWNRFHEg/jud7/7gx/8\nALfx7NkzkQyVeqSST5MgP63TUuKmzinNZhOkKdfmAAAgAElEQVSCyQsvvEAh88nJCZrIFgMsiZCp\nlPDs7EzamHqTg10BCzmwYMGCBQt2KS0gsGDnjASMAAGhpEKh0O12Jb8rBKZAYrFYXFxcJL3x6aef\nfvzxx7ScT6VSFGa9/fbb6+vr7J0rlcr8/Dy78larxWb/+PhY+2JwA/jm+PiYA1KpVKFQAOQtLy8T\nppufn1dgcGtr68GDB2Jv37p1y2IxX+6iUqk0m03CierrQeRNdVeZTAa4JkUib9QP8MOzszMgwsHB\nQa1WU7tqBcSUDEN2RApVknTy8sRKUBGZVI2BEmNUufFlp9MhgtrpdICJ4CRJSQmBCXXpnIzHp4KE\nGp89e8YZDg8PuZ3V1dXhcAhWpt7uglQHpXsE8Xq9HoK/TPUrr7xiZhsbGx999NHHH39sZicnJ7Al\nLY43Wpzj5NYIUyuxyhuys7NTqVSUcjs8PAQmLi0t8WW1Wq1UKoxhMpn0ej1BOlWDtFotnnuAX1fM\nggML9pVJXojFy8wUS8xkMuVyWRL1voETR8IjJ2d+fHz8wQcfiBSudbnRaECAXllZqdfr//Ef/8HZ\n/vqv/9rM+v3+/v4+63Kr1Wo2m/hIf93JZELk8Pj4mAgVUlX4J+JyXFfk+48//jiZTKqoWTL20iEk\nCeebs+BdOp0OayLZOwXfWKYtrvw1x7OweMVUWgiDpJCMG0CXy2VVcXkBfrmffr/PHSlbNhgMCoWC\nvxBjULARvXzfIEYJS63XakwjosTc3BzPxczQV2QLImcZRZFavhGu1F2wL0EaionCceq6W1tbZvbo\n0aNms6nicTWpUROW0WjkI8PUJFhczmFxtbVubTwe8w5IOZPAr1y+fHM6naaug8pFpTb/938JwS6P\nhRBisGDBggW7lBYQWDCzWMLc4jAOmfbxeKz2uIlEgi1zu93u9/uEccrlsiAagRqL21+xhc/lcsTT\npJVuZtVq9dq1a2y6j46OwFL1el0atY1G4+7du3R4EnHAK2IIeYxGIwneIzEMMlDXqN3d3WQyyciR\nbuIMxWKRA+BDqnFULpcDMpZKJXAb3Sw5AAUKgUvPnRM0EcHBz60QGKe6wGmkkFmBRxE+Z3+olynB\nT8EUXUKI0Bye45wWS5bwWdM4HA5brRb3W6lUdLZer4fASj6fX19fJ0p5eHg4Ho8ZWKFQ4MNwODw9\nPVWdg2oe2u226PuC6ePxeDgcSghfDTzFRCWEq16aRAK5UxUeCEfqS4rieWN50H6uLAZ2oTvzlbTw\nUIOZOXkhKPJaffhru92uVCoKG9II0VwOjEYb4u+l02mpIcj9NJtNyNAQ7r/5zW+a2fHxMadFFQly\n3dHR0eHhoZZF0ir4V66IADmXLhaLEjj3kTrlfnSPhJKkyqFbSMV9nEkU6QxwJqFxi99v8brpq5c8\n199iFqL+186XgqnXiRJg1FcpjKZB6ueeH2/ndRrVrtpid0W4TEL4vteJnrW0H2ezmfYiiURCZ9A8\n12o1dhhzc3NKsw2HQ2lgKuFUKBRgq1oc77XzRRdsO/RZI8xkMngpHjEnHA6HGowmysuY+RmjeNHi\n9qcKCHOqWq3m/Wiwq2TBgQU7Zyw3LMdiyXc6Hfkk1ke1g+JXHKk1WhvewWAgxHN2dsbxR0dHrVaL\nZTGTybDKAOAAPQcHB8fHxyJqA6roxqK6Xf4qhGHnt+e6BRZrIR4lbC6UsomboGVxNpupotnv+kVk\n8JxyX3pscaLFey9fCpZOp0lxqc0K51ettM7j9Rj1JcKJkifWl+Abi4vGOEBlbYxQxWEq+5U3TafT\n4ozIH08mEzWHK5VK3W6XHQZ6jBZLWDFRlK9Jf4sBDIfDbrf7B/NPqiSjiwpfqouN0lrAPrkfOW9l\nLsnzaZ/kC+bINarSwIJdOQs5sGDBggULdiktILBg58zXKYtTTl9j9tREzJTqENDxCMzXzEpQw2LA\ndHp6enx8DKU+n8+rQ0en0yGLdnR0BBQzsyiKoBdGUTSZTNRMUpy9C2E6vpdCVTabFTMN2Q6SJRaj\nLlEcLQ7l+baQFieoND8egak2FqEmHcOcCCIwMEGrRCJBcLJUKikIqYmC580Y/mDaBnoeOTkBLNie\nPqmm8QBoYPr5em2LM2fCK0pxaVY5gNukyQCXa7fb8BVHo5FCfFR2q1oAYDcajTwtUPhJQc5kMinJ\nfA+R9VD6/b4k/P20qPWll0dhehU9Fpjzql1e8jjYZbfgwIJ9ZfwLz2Qy2WxWfos/RVEkFgAUABY1\nBXba7bbaasBHUHiNRaTf72vhOD4+3t/fxy3RZsViZymeiIQwSqUSOguInSsxJs0Oi3MnmUxGK76/\nnOJ7BJoI3/neVwqd4bklSuT1tDhzsVgsl8sM+PT0VAFMJu2PTaxCdharYHBrtVpN5HutsITy9MPn\nH1CxWKxWq7QUSafTWqOn0ynzIDlHc2E0quguyDyWSqV0Ok2ZnZlls1m8jij7UE54KMfHx7u7u1RK\nNBoNuQ0lKblNOW8NPp/Pa1fhNVwU9BNxo9vt0hfGYgEUi4PA6mMwm80IaV7YMegR+0oy5TtV9sdr\nFsKJV8aCAwtmZjaLm7KXSqUoiiSkqw/ValW7/lQqxRKcz+ep3LK4ntRiISKlH9SLK5VK8fn4+PjR\no0fkwCxel6MoGg6HXrcJRCIExo6b69brddamTqcj5iFgQmkerkXySau8h0F8SQ7Gi+oKpnAtVBNV\nC2WxM1teXlYrk36/f4EtYjHotNh58JnlXvJOSlBls1mtsEItQjxwI3XCXC7HVOfzeQAlYowMGHcI\nVB0MBp6aqDGI2QFnxM53yZFYMEq7TNR0Oj08PAQZq6HlcDjs9/tMi98KwEi0GNip9k7wSLsN9MOY\nSRVfWwwcOYA+lgxS5A5fGFcul1Ue1+12k3GDU8bQbrcHg4GItcF7XSULObBgwYIFC3YpLSCwYF+Z\neINqV+gVJVAwMrNut9vv99km+/2sl0sQ6Mnn8/DWTk5OyuWyqPDPnj17+PChmb366qvQuBGo5eCz\ns7Nqtcr+Wt2HfQbF4rBhoVBAT9biEJYgIyOE2C0E4NM/ULeTyaTAk8SfzGlNVSoVSdD2er2TkxPQ\nj7JHURQVi0XNldd/UuZP3G6hOoshi8UwUSFczXm/3+dLgKZqv+r1+srKipnV63UhYEkDwzaUJoig\niSJ1Algk5/xT9rIdFifnCCFS5CBgp+bO0tSwmNHOvXMJ2KQMBr1mDiiVSqDS2Wym+j+Kw1QYoD4v\nkizh52rfrKFWKhVOO5lMWq2WD32bWTab5fb5LGZssCtgwYEF+8qUJx+PxziSwWBA+I6+yUo7kbcw\nx3Qws3a7jW9oNpu+kJkmYbg9CZCPx+OPPvrIzMbj8V/8xV+Y2bVr1+T2jo6OlE05Pj7+9NNPzaxU\nKo3HY1Y6ymw5lbTvcCSkuJTKoqJWPG+fH5IpYQM5RSxtEUbEMvBLZ6fT4cPa2tq1a9foOWJmvV7v\neSEoJagQh8QVUfWsYUhzS35LgUffptlrQqqQPJFIKNWEKjwH42st3gcos8UkkNqUOKHFiSWROJAQ\nQ7rp4OCg0+koq6R6BlE/2Liwy1GMkVbI8sqKUkoLEUlJ7TBEZqEs3eIkGY8YTy8aCOfM5/P5fN5z\nhbh3bX08u0eV7MGuhoUQYrBgwYIFu5QWEFiwr0x9jVVxLMEFBdwwMeZF94iiSL9qtVrD4ZBtMrJS\nZoZGO/vo0WgkWvnnn39OdG5zc1MsuHq9/vTpU4JC+XyeTT0Ij43/YDCQlrwGBndfXD6+9CgHRgkD\nVnUtmIyzUZKsulfRuM/OzjiAiJyADvTI5eXlSqXiY4980K7/gvCxunnNzc2JhiCGRa/XI2BoTuzD\nc9yBg/BW5ufnuS4aIgpC6gGJL1oul6W3pK5dQF6vG+LlgC0mlDLnKDsLy0pxQ/gVjC4sq1p4aWtR\nJ84Bam5AfbrAvSTNqtWqqrzVkwxqKJMj9JlKpWhix2n1liL+wuyJ6dNoNAIL8SpZcGDBvjL+VbNG\nw9JuNBoSVtCi5mURRBWDyCf9IXGsVQsF200OrNlsEt1Kp9M0Xun3+9VqVdxo35GZxcs3JZnNZlyC\n1Vz5GJEefaNhlRxJScRcgZovmbpQySSlIrWFJCekMeAbSqWSD5Ep9SU6nA8AmksU+S89f1JaEt6R\neBai8nMqCMPNiJSv1JcScsyMfLN4kgrVIh/la7b0FHyBmu7I59vkzDKZDFHWSqXCwE5PTxuNhuSj\nzBXJyVn64jB9Vp2DmPcWJykVodWrq7Iz4szKgXmpjgvyKMGuhgUHFuwr08oieSEhAxXMWlxqI8YH\nX7LRFgFdSk5+LZYeHRWmSqqzwQcfKOuTTqfV+0MLqPJwXozR79+12mqppaLZU8kvQDS8i5JDz/cc\nwYtoKZQjSaVSzJL0BjVycTQ8btMB+Xye2/QJMJWdmWujrGUXx+kr2/CdlUoFh4HiMH9FEpfPJC8t\nLhsQgUXgxt+mfxnkRUR7SToxZb0t+BtlzrLZLN5ldXUVxEOG0gtxXShDFga1eLsjir8Go/oH6gfI\ny+p+/R6Fsms5MD/a4MCupIXHGSxYsGDBLqUFBBbsK/MhHcEm/kRdqpQpaBBsTqoD9XchMA/X+ACP\nXNvkfr9Pwkz5Jzr/ckIgi6p9OQNI64JMBn8V6pIKg5Jw3W5XETOAlDb+ukc/Wt2FyPde68ijkGw2\nSxS0WCwKgfFXqfIrzqnbsZjax236CKGyVs8/GtJp3CYAi/lfXl4Gjuzt7akUmhgm4LjZbApgDYdD\nzZ7OLCSETodgMZlF8DG/AlGpi40CnspBTiYTVELMbGFhgeMfP34sOM7INVeqLvc6Gv6/3M5oNGq1\nWjzoSqVy7do1RMiEX8HuGo9ivwJz0CC9GFWwK2PBgQX7yrRwK2rna7wkKQQPgqVZsbV8Pn/Bu3Cw\nSM8KHFnMm1BVGYl3wpJExqIoiqJIgUEF/byz8XFFvlH/eDPrdDpcywcM1cKK/2qh9JExmZIx3ALR\nQuja6pXFGi2qhQw3nMlk4NYnz2vVj0YjjUF7AoX1isWisokXZCPEXM/n84xnY2ODKoXf//73Ftft\nEaFl/pVAKpfLpVLpeZWswWCAIyGtdSF0yXNkJufm5iBccIPsP3z7knw+X6vVuOUoisSqyOfzKj+Y\nxm3PRB6hlzcvw4WQJpMA5YTT3rhx48UXX+TeRXtpNps7Oztiu/iuMbxaM9eD7UKz7GCX3UIIMViw\nYMGCXUoLCCzYVyaiHXIG5uqUkaAVqEomk2yZO50OO9/RaKQEPtqARJYUToRDL/qDgpBe5dbi6Jbq\nZO186y/QoZkVCgU29eZKUxk56GcymTAYeAHJuEdlLpdTtbVApIJacEN01xInFITiryCS9fX1l156\nycxo9SloOJ1OQSfFYlHkOiEDX40gTr/FjHaL0acUSXSwSoDVq5PPSErWajUVL4OlRHIRlVz4NRGr\n3cMdVQmBiov9l6PRiEhpKpUCZ1tcCGHnpQ5ns5kIh2oBmslkFhcXQUKdTkcF3UtLS0QFedDCsjrz\n/v4+91upVF5++eXNzU0z29jYWF9fZzwvvPACj3g0GuXzeeFpvZN2PirOdQMCu2IWHFgwo/iGf+2D\nwUCq8GLD0zqExZfSH3j2YiEOBgOpYKRSqdPTU+Js6XSaFbZcLksyYzweq2BLAvOosKuiyJPjVRSl\nmiQvso50iMVlRqy8EnJFiZxLEJrDmS0uLjKARqMhJYgL6u8YC59iaxYvi8vLy8iiJ8536Oj1ehd4\nfZC/xQyMouj5ji1+ryC6pooQqtWqZPs99306nb7wwgtmtrm5ef/+fWXREuf7L1u8w1BlglZ2LejJ\nZFI7DGXscHUKvcrLNhoN9buRV+v1esPhUDUPykFq2+EZ89JH5lnzGTfPgG/duvXaa6+Z2fr6+vz8\nvNJaR0dHHPzCCy/cuHHDzB48eOCn13cJ4LpHR0d+QoJdJQsOLJiZS1aBNpSy4p99oVDIZrPyauPx\nGHmhVqvFcpPP51988cXV1VUzGwwGm5ubjx8/NrNnz54BR2A0qB4okUjgDiuVivQAPfpRuZUo+x4q\nWbw2jUYjoR+ScN5tWEwe4boQvpNx+yvWblpFq02zwBaCTBbXAuu0s9kMP720tKQU14XJBE8UCgU1\nf0m6li7ilAuWQS734MDTynWAbllJrCiK1tbWzOz27dvb29vacEwmE0nIqzFbMpkke+Q55Th4iwGW\nnIqcJfdiZs1mU6XZErtKJBKtVou7mJubW1hYYGeTy+V4ASiGU/Pl8XgMdvd12RrkwsLC8vLy1772\nNTN744034Kc8fPjw7t27tHE5Pj5uNptsiV588UWc99bWVrPZ5HUilShH7mvVA43+Slp4nMGCBQsW\n7FJaQGDBzMwKhYICgKPRSIiEv4IVtI9Op9OkoI6Pj9nkrq2tSTrh7OxMcunj8RihjZ2dnWazyWnh\nlV2gEXrkp2ycnVfaFRozR6AXS9travgSYIuDdQAs8e8ZDLFT6UqYEzXmVOA2JecmkwkgY2VlRf0h\nfRmyPbfN9zoaHmy1Wi3gaaFQ0E8UbfPz3+v1FEoVsjSzTqdDQmh5eblcLpO5JMYrDjpnAIF5zRGO\nVB9OwKtaUyoq6yXzNSSlNnl8oLSlpaW5uTkGKXKjxWLwFndn1uNWirFQKPC23Lx589atW+Cq6XT6\nwQcfmNn777+/s7Mj3ia8Ry4HA1PsSt4BL+evJ6gM4h+MEge7vBYcWDCzWJDC4vXRUyos1sTjM/mG\nC3nycrn89OnTra0tM6O7I+HEUqnE6lapVESmSCQSFxjkGoZckQ+1+cyNfNs0bpSsJQn1Da/vYPHi\npWuxjvMnraS+7k1yShqtHyRf4unFIvHjUcxK4+EAPwb1qxTZnfI1xbj0wwtuLxmrQ0kdYzQaERWs\nVCrFYhG+BhkyiX08f++K6Znz0+J36I4054rIJWO9K694Uq1WCaXOzc1RA2Bxo0uN1pfrqaxCYerF\nxcX19XUzW15ejqKIu3j27Bn9Cra3t3HzFgeWmTTx+3lqPuDMmfX+8Kvguq6kBQcWzMyR3PwCKptO\np/1+PxlL7YkWYXHLj1wud//+fYgbnU4nmUySYF9eXgZtFAqFRNxtK51Oq/eKlhV8gFgSymTYeW8q\nSSdpC8l5+DH7umDlnzz9Qevy1GkPclE5MCEev/yplYl63vvZ0zJqjuznx8P5WYJ9c2H5J88WMUcb\ngQxpjqjJf5nGUqlUqVR2d3ctdmDkhFKplBeo5Le+5NnXmfk5n8Y16bqFC1XeGnm1WiVZFUVRMm6u\nBqHDXLmeziAcn4g7ca+vr5PJy+Vyp6en9+/fN7MvvvgC7M7kez7h9LlualBULPaLajvHyIGJF3Y2\nwa6GhRxYsGDBggW7lBYQWDCzGBlYHCEEXqikxkMceNWNRoPvCRUmk8nT01OpP+TzeUkZSVuIKKKZ\ndbvd3d3de/fumdnh4SFAh0yGwBaceHPKtqANITCGfXZ2psqqpFPdVUEYCEywxmuI6Ma1waecSJk8\n0eREieRI2POlUknbeeEJjdDOp1t0hslkokaL4kz6NptkBzUGviTPJ8Dhw5vgjHK5fPPmzYODAzM7\nPT31dERqsMge6TY1bMEUhO25hDJYkDy5lqK+dj5k2uv1oAg2Gg1BNLXR8fq8XtJpFrdNeemll15/\n/XXOvLOz8+WXX0JfVKdpBOa9HLBXEbO4xFABSSEw6ZzxjYrVLNgVsuDAgn0lukMAEPkiUbpncSv3\nRCIhOaXZbCa+AMW8pVJpZ2dHOu7D4ZDFNJ1OkzEys1wuR97o2rVrm5ubxBg/+OCDL7/80swGg4Ff\nm0StVmWruaCcROuJjHl+gWdsc4yKppEqT8RdkuXD5HWIMUqDSqR/LbvJZHJxcfHmzZvmCgAwDu52\nu5L7U4WvpxUgysU8NBqNZNyxJYoizgDL3McJ+UCY0WKNKzk8MkYLCwu3bt0ihDgejw8PD8Wb4DAk\n86VMr3ClPCvuTQXOEn+Sk+OvCoRyXcq55BUU55QPpo2O9iLpdBr3WS6XyXutrKw8evRIuxm/ZxKn\n32Knm0qlzs7OCE6Wy2WoH6urq9vb21JxHAwGumuNikp8M1M6LdjVsBBCDBYsWLBgl9ICAgv2FbkO\nmJLNZr1SAx9KpdLp6an4bL5/IwisXq8fHh6yNWaPLD4eccWjo6NKpaIGWnNzc/Pz82b2V3/1VyTt\n79271+l0BFnEAvB1qeaE55W0t3iTTmxNMUbt3MvlMoDSS6ErXAklUnG22WzGIMvlsgqHxRGo1Wq3\nbt3a2Niw80FXi+OrIDzduyidGjAxPW5zMBgQfEOuiflXtzA7HyVrt9uCR1JOshixEUMD7EJHnLk+\nooy2UCgoKCr2/HA4ZE5os3khQuv7lHqWTT6f5/FZTPCxuHUyZxZfsdfrZbNZhe8ymQzPolar8eWH\nH364tbUFoDcXMRYDE+ESvXIKJ9KA2+KWb3qZhePVxxnSvwLgf+QfQbBLacGBBTNzfGtIX4q/YSw9\nrOwitpnZ3Nwci8jh4WG321V8TwTxRqOhQFC/31ei4uDggNW2Wq2y5C0sLGQyGRwJqRc+ewaaqrss\ndhg4KgqzyuVyPp/n4KOjIyKi9Xp9YWHBuyLlgbzYkkjkKo1SnxeiYSy79Xr92rVr3IVkk3BUz9ei\nWewJ+FIL+tbWFgmefr9P0I9yLsjopVJpMpkQwfOxx5OTE8aALIhSUHKW5XIZzzocDieTyd7eHpdj\nkKjCi1vvC6e8YKPIhxo/RXsXnrs8mTYBFrdx8ZVn9pz2oHKQR0dHpNn4oBIObQv6/b4kxBRGZkel\n56JSCiUIfRhZOTBOKMERC3aFLDiwYGZu0z0735VYB6hQaTwea8+7uLjITnx/f1+LmoRTzWEIlTlb\nzPJQ0kLIL5fLqYPGZDIh7aF62GlsFoMtixnSOpUurQ9nZ2fa3fuCYiVFSKsk4hZfmgpqhy1ODuFR\nqNXVfp8RJlybMblVO99YWTz7RqNxcnKCb/bZO9Xn4vtBnzhmJv+CnBUfVM/Qbrfr9TpZJaSQ0Soc\nDAZsOyAyaMDPV/X60gVfViUPhNsTy4bJ4a/JuHObZ7UwY7lcTrcGNlI7FUZ+4aFMXcNr1Yn74gf/\nHvJhbm5uf39fdQWFQoF3stFokKhT9bS5TtzBroaFHFiwYMGCBbuUFvYjwczMJDafzWansc6TxdGh\npGvJ6GWTqtWqOGMKRgE4vMy5xSR4Bb7G47EUm9iJAxS8HoQO1q7Zq9CexT1WpnH7EkCV+juriaUA\nFoW0yqWJZKg7Aicxnmw2q9spFosIyF6/fr1er6vi2xf5ei2P5wsAhsMhQHBvb+/o6EhFvlyr0+lI\nbP4s7uNsLq5bKBRE8GN6BRmVBUTj38yKxWKtVkMApdvtCsf4mmUMcONLsEUy1P96/RRz5eQKG5pD\nnPo+6RrQCGz5t8gjLWlGT50si8Kk5uJ+iIlMY/F7AUp/Uz6cqDHo9p8Xmgp2qS04sGBmzjfwwa8j\nOkbJElGrRf6mako8b3EWpGFBMw6dVkGqbDYrCoDWJgqk9Nn7CS/VYbE3VfDNK2L45V7exStc6Hb8\nuqm1W8QB+BH4g1qtFkURnsYLfGiifHpJA+v1es1mk7zX/v6+mmaZa7Lc7XbV80UpH5+YhAevM+vp\nMM9QG8SwqFQqhB87nY6UOOSnvbvVl2wvLkiIMZ/6lT4rtKj6KjsfnVMalQnxPkYPSNsUXybhH5DI\nOyoAYDzi/Yvf7zdPyqL5TZgeVlCjv2IWHFgwSyQSqq4F3DwvJaW10gsVimRIQkIyd1rH1fZJi765\nbvEWdzOxuJ7J4zl/aXOoyxzBz2sscV0tZGpMJWaHuayPSrvof6Y1WqW4hUKBDX6v15MbZoX1qSM/\nhxbT9pQJo9z7KDYzOzw8pC8JBzM54EhmcjQaVatVVVuLQwj50NyewBwbk7SlVLtqtdry8jKDZwzm\nEofCjtlsVoBPVWsWd5DhJ91u10M0ngs+koGdnJwwHhiYHKZmNDQRlW7vhZ0HRw6HQwEjzb8OEJDV\nlxfuIpfLSQ0ZpolXseIAmrbY+bRfsCtgYT8SLFiwYMEupQUEFuyrlIYXX9dm3NPqlPbwpWAcgCyF\nYjsKECnG2O/3VYal3oNm1mq1FDrze20fkORLhI6ksaT9dblc9oJMIh8CaMg8qQDAgz8lyYQXkWkX\n+RBe+40bN2azGZw6GqCI9Mh5hsOh0Gcqbl5sZr1eD5b848eP9/f3T05OOINEqsjPWVyoJMjY6XQu\noBCCiirtUvts3YVmwMyKxWK9Xmfw+/v7zANU/gtINJ/PF4tFKsnUbQBTNFKQiNaUhFLr9TofTk5O\nBN2mrptoMplkxkqlkp6Fj3PqFSoWixfie9NYL1gZRE0sD8uXG1ospKKZ9ARUBSQF0RhJsCtjwYEF\nM4uzO2aWSqV6vR7/zmexIjvNhfnMKn9h1ev1eu122ysV4aVgUdv50M1oNPKLKSZ2AP+VmpHF7tOv\nsHIe5LegTVPxKkknYmiDweBC42NllcTtTsUt7Sl7guMeRRE+4Dvf+Y4EqP5gBoWF0teBMTlPnz5F\nT313d/fw8JBQHvruGg9nwDnJ/Uv4X7620Wi0Wi0GVq1W1aQmiiLlwDTD2Wy2Xq+/+OKLmp8L8y8N\nezYEhI6JteqOuIVEIkGoUOPk4NlsRgl2q9VKJpPEG/3GxddRiC/DXsS7Iov3QzxcT8T3RRe8DxbX\nWuCnoyhSezlzEmLej+oMfn+m9OrzrJZgl85CCDFYsGDBgl1KCwgsmJlr4LSwsKC438OHDwVTTk9P\ntblWKC+dToPbgBfsxMXt5gDg0cLCwmg0YrNMJ6fnZY0sBgpIZgD4oihSTj4Zd2KUfPtwOBS5A6TF\n50KhwGAODw/Veww1dEXPkAKBHgn4AJ/x+caNG5xhe3v72rVr3EWpVBLbJYoisQw0IdwjjT0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xaHTKWzlclkmJyXX355fX3dzLrd7mQyQXRjaWmpXq9TvfA///M/nKFSqQhxonhC5YAmgSeo+KoC\njMGugAUHFszMVRx3u918Pi/FJr5U3y+Lw4msrXt7e//yL/9iZrVa7Yc//OG3vvUtM1tYWHj48CFn\nUL6nUqkgCs7ZGo0Gn5UHwkmwDLFAszwhZmhmuVxO1ACf4df6SADq+TpZc02/cDaMwZc8E77r9/vp\ndJrIValUYh306SKEkcT5Vp5P3cvwVayV+XyebBll3YwhlUoRB+MAiuEajUan01GcTTk5hRBx0tTt\n5nK58XjMxuLw8JCRI8eugB6t0biEXL5yYKLA0BIaf1AoFJhhDvC9x6axUpfirtKSh77P+fVXc/Xg\n6XRadXjq2mXOoXKzzPny8vL8/DyPu9/vP378mHvs9/ukWhcXF+fn56l6fvjwIVOK01L2bjqdUnYm\nQcjhcNjpdHgWoRPYFbMQQgwWLFiwYJfSAgIL9pV5/pg0kBSEuRDrQxzozp07165dM7NGo3FwcMDe\n+fbt20tLS4S2stksO3R6PoEbGo2GeG6CKahViYbQ7/f54SzukwmyYTxRFIkWWK/XAVuIPImdDzTp\ndru5XE6EC2leiNxoMY/DYiwl8QuOhPmm0/roGYMRlcDOFwVrxgqFgnBkOp0ulUpUGet+veQ8AJex\nqdVWsVgsl8vJWJ5/Op0yhiiK1BmgWCx6IgOXWFpa4oC9vT2v5qUbf75BmrmKci8ulc1mnydz8oZo\nctDl4gCRCSVNAmYVd4Z7XF5erlarhA3hpIBKnzx5AtLiQtzF/v5+vV5H+XdhYUFcTb2oxLc1BjW2\n1tNUW7tgV8OCAwt2ziRRaC7ewgqFnygWiwohNhoNFg7o2urzm06nWUDFaR4MBloBOYDve72eaGnm\nKOmi1yfilsEz13xZdVfebUzjbpnmxJDgTGrRFAFvOp1yWlZS+SQRxJX7oWxLKS6tiV51wpwTiqKI\nkSuuVSwWkXeyuJ0KazdtZfjyQjNJzSSDWVhYWFhYYEFvt9sS3ZCMFpLwihAOBgP2CnK9mlU/yZ4a\nKqdlTmuKlKH2Cn7a5fakwEK8USefOl0xeRcd4CsLp9MpoidkEPE06k1qMQnT4lzs9evXGeSvf/1r\nM6MsT2+ChKlmsxlvLKHjC8Vhwa6GBQcW7Jz50lTfhkpVTV48kJyQmZFj0A5dooUi4pNRl0DfdDpl\nnZpOpxLrEz9i6iRZlSyZxcb3fhXmAzkYxiA2B+wJIYCEa4UlvCJYQNbkD67RnoDuRXV1CY1HBWQU\nMJlZLpeTj7TYTXKkfqXTAiBUOKUvVQslb2px6ku3I1ekXmXHx8ceJuq0/JxquQuyVRYLHFvMqpAD\n86KFfqMg6oevtlY6zc6Xys1iDTAOoJpbrH3JNNPmxlzFm8USi2QQBc0nk4lYRbqungVviJeEtmBX\nyEIOLFiwYMGCXUoLCCzYRVM1qNcZEjGaQJz66hIqnEwmjUZDsuXHx8eKFImFODc3J1mpcrlM8iyT\nyVD+bGbdbtfLOynl43fis1gzV1EpePB2vphXcS2L6XMWKydpRy9woCOBgIqzSTNCJHjx9e18ObB2\n/dPplACpxmOx+oZwj86cz+eBpJ1OR0JcPhCnSUgkEr1eD7DryX4WwykYnnpqZsbBk8lEHHev2qVI\n7AXqoE4rGOoFfH2VguKrAj1Eay+okExdjxUvXKL5R+pXE6tKCUFDnilBV9KHsDHV8YBriQX6PEue\nqfPx3mBXxoIDC3bOstlsuVxmjWg0GoqzSTmJNANr9I9+9KO/+7u/M7N2u727uyupiFarpcgePmlp\naWllZQVufbFYrFart2/fNrNcLkerJ+SaVEGlUFKr1RIjXMVDonGzwsofaLFut9taVc0tnXLJXvVD\nh7FGSx1D9HGR4FFQZGAicfgSKwoPLsTZzHUXSyaTvV6P+N7KygrpnLOzs8PDQ82YyB1KcVksyWix\nQ1WGT4P0ahR2nkNhsV+8wNfgQiLEez/tpar8rkK5KGUQ1VfaXBzSdy/TbHA5OTP5QlUmcLBq4NSQ\npVKpwLOfn58vl8uqUiCtCEfGq7FcCC8Ph0M5MB/sDXYFLDiwYOcsn8/Pz8/jXZ4+ferRj097KPVF\nheloNHr48KFKgiRxpDohmtPDXaxWq6urq7AMHj58yKmuXbuWiAV24UAKxwBTarVaLpcT8vNCukoO\nqRRX9V6ZTEYUNS2pDNKnuMRZkKSTKBjmRKFglDBIT3/QupzJZNTATL4QPoiu22q1BFW5brVaHQ6H\nBwcHFuf/0EDivzyUTqfj5axUJqzCOIupej4XWKlUcP/AUMEUz3DRo/eeRk7Ccx9U+ubvsVwuqwHN\nzLWzwZC49Hmss7jRqArFzs7OpFimMShlmEgkarUab04ul+v3+0D2/f19fgVo83SeWaw0DV+x2+0K\nfg0Gg5AGu0oWcmDBggULFuxSWkBgwc5Zo9HY2dlhw5vNZtnDnp6eCk+wpwam7O/v379/38yOj49P\nT09FZE8kEuyvIeCZ2XA4pCmwmbVardPTUwJEURR985vfNLNUKnV4eEiz3W6322g0CG1tbGxAhoa3\nJmUQBlMoFES4R3FcY+D8BJdUFSDwoYyU/moxxFRIjSOBAl7LnLSfRKrg8mlgnvzNBzCTEnXqFFMo\nFG7evGlmc3NzygmdnZ0tLi4SHBMVE9gn9CloKLUkkoJgC8JlDDWVSinWqnCibo3CBqBqv9+X1JPi\nq6T3+NV4PFa2L5FIMEKyYiqEEIQajUaanJTrEar5Fy2Q//KIlW9jkkHemUxGul9EYoGq29vbaIgQ\nD1B1hMUIrF6vc+97e3teJUvpxmBXwIIDC3bOJpPJ6enpvXv3zOz69eskw05OTli/LGaB4+EymYwE\nkLxKkMW87Xw+7+t8FTpDg5zjv/jiCzM7PT3tdDrEG/v9/ng8xgOpPpe17wLPXjx+i7P9cmyMPJFI\ntFotBf38ncpReWcm+XbCenyve0ekkTMr5UZai5AazAJGLsrDcDjUKp/L5XK5HGMeDAZMo5TXzazb\n7VarVb8QM1RxQ/C4umumtNVqicxCKlFKg3oQy8vLPJper0eQdjQaSUXQXPlXNpvFo0yn06OjIzJ2\nZI88799cGNZiMoU0GHE/4/G42WyqVEtByFQqJQ1GvU4oK3LX3mkdHx/zOZfLLS4ucsv6slQqIa9l\nMXVlFrcLx9U9e/bMyzAG73WVLIQQgwULFizYpbSAwIKdMypq2dum0+nV1VUze/DggaKC8NbYXw+H\nQ/bybN5FKFBoS3QAH75DQFaBKWlNqbgYLSXFvjiAU3E2tZvy8hAJp6OvuCK6tAoSUplrLhDndd8h\nFFyIMY5GI7H2KRuQ/hOwiRkT2U8lyZPJxHc+EyuSsKeZFYtFL6Ek9Q2BD4ldgUfFaxiNRtx+s9lU\nbYOUlz0aVlCuVCotLCyoLSQ/F3A0s0KhoBLss7MzHqs5Ogx3JzqMNETK5TLzf6EKQvPvm4QpfJfP\n57m7KIpUtgEXBog2Go3AbQnXhYA3BES4vb3NB2LaHuhztlwuB93j+WLqYFfGggMLds6opOHffKfT\nIZRUKBQuVFOxHHQ6HVaZ1dXVTCYjp6KMjkTlyWAp7TGbzdRf2NPZn1em8J1KFLAiKGdxW2RfQTWN\n2yiTIBFx0WIXouoi5X58n0wx4vx1FZFDUIMfeneiYjUGo1Ce/KK5eKAKpzKZjNJ7XolDNHrft7NQ\nKLDiT+NWyMye4my+aM+PgUvwdKQPyWjhTHKkb4MJ79zOS095wRFPLFxcXGT2dnZ2Tk9PGY/0O/r9\nfj6fJ0KYz+cHgwFnVqdTqjIUrU3ETZ8VJkW6zO9RpIvIAVEUKb3Hf9Vi5g+GjoNdJQsOLNg584pN\n6jniC3h9qmM0GqFit76+HkWROlZoybhQXavlz9fqaun3akbKxyiTxHVFhfdezVc+ScmQXy0sLAjQ\nsFjLC3oSgWgIVEabo3STb1P9mUaoIq1+vy+dXG5HtbrPIzBuXFBJOFWjms1meERz+MnzU9hhSJpW\nilnaCnh3KCc6m82azeaFX3naBfOvbYF6j6ncDb+r3YZKCKIokrYT+SqLe5JZTFsXJ2Xm+kqLF6NE\nnTkHJl4GtWjKIGazWalkSR1KDmwat2ozV2rmS+CDM7tiFnJgwYIFCxbsUlpAYMHOWTabjaJIPDp4\nXL1eTzE3KHlquEyyJJlM1ut1tsZnZ2fKpqjRMPtoidhK20LpDS9gYa4pMPRunYp9PVw+Oy/j5OuU\nReOOoqhQKAhYqKBV+bZMJsO+3mIdXk9KtFhYS9pLvV4PGn2tVmPkcCY1e9JAkhoF1daK1KXTaWKt\nqmgm/wQ46PV6QDqLg6IWdwNRzFMRS69dKxxDTsiHHzmDEJgehK9Thi4P+hyPxxzAwBSlNCf6zgHk\nvTY2NsysWq0qD9dqtaS+32g0uAs1lDEH8vxLohwnX0r4X+9bqVQqlUrb29tm1mg0vNCJh1bC7jqt\nT69asCtkwYEFO2fJZLJQKNAAdxY3Z/L/7GGusxiNRqOnT5/yYXFxkeQEToWEjZdmUJiIFrqcs1Qq\nifosjT5o3Hig4+NjyCPUAyk/r0CTQnYE3xRaJO/S7/dVf6aT2Hm1pGQyKSdq8ToL/5vB6LoY3r1W\nqzGwdrvtu3U8rz3oY5uk05T6kmcdDAYk7ZCRVCtn5Rr9/HtPr3ov/ReXLB0TRURFKvEqkaLbUGLF\n2ZTvxJ3L9eppSodwNBp9/vnnb7/9tpl94xvfWFhYYNrfe+89jqzVamJ8KBRsTm+T+VcYU1HTZNww\nrNfr9Xo96hHn5uYKhcLe3p6ZdbtdeTif81Mgejab4cXp9eMzoMGujAUHFuyc9ft9tZb31VTPnj3j\nHz/4QIsyy+54PF5eXoZTB0WQxUUqPoAJVRx3Op1E3NWeI1l6lIuS7xyPx6x0NHXkEktLSyxSDx48\naDabeBTOz1qfTCa57tOnT7VwgyeEAFhJwWeCUDpAiBBYwGKay+XUR7HVagHFNjc3j4+PT05OzKzR\naCgflkwmmb1KpSLSSqfTWV9fB7Ls7u5++eWXZlYqlXq9nnYJ/X4fnS0PLuVxcTO+WQyXkPv36o7s\nFcwsm80yDM2/OalAi7tnseJ3u124OUpEmVk+n9ecsMuxeIuDmuWdO3e+9rWvwczM5XKffPIJ97uw\nsCC0reyddjO1Wm08HpNJpQz8Ak1xf38/k8mQZoui6ODg4LPPPmNOeO707tEJC4UC3o4Mn53vCRfs\nilnIgQULFixYsEtpAYEFO2cws8FVs9lsYWHBzNbW1rRNBtBIKfzZs2dm9t57733ve98T0EEYwuJG\nIRYLW7B/z2aza2trXE7ZFGTIxSVT0qJarSpzVqvVaMLy4osvSs325OTEk9zY4He7XeHFk5MTbodI\nnajhkr7N5XKKK/ITM2u1WiozUg7m+vXrt2/fBqbs7Oxw3Xw+v76+zsGoZBF75Bszi6JIDYijKPrR\nj3509+5dM3vnnXeQQl5YWKjX65JL9+VZmqVms6l6ANVjnZ2dKddVKpWkLSK2Os0eLY5nMmndblfn\nl4YFUUdxCxV0FSS9wBFV1+mVlRXugsHwwvzlX/4lT+qDDz44PDwUTVQhXIn5Hh8f1+t1gPUoNmYV\nFDiZTN566y1emEaj8fHHHz9+/JhJA6KdnJwMh0OvtkyEVjk2C5HDq2vBgQU7ZywBaBLOzc2xRi8v\nL6+urvraYfkPvNrdu3dfeOEFLaaS+8vn83wYjUb6K3wBrdfyT0rgUxMtvT4OQFycwupyuYyTWF9f\nX1paUhHrbDYjrKfS4/F4vLOzs7+/b2adTmc6nTKeYrGoUKG/tFraS62KwCZrYr1eL5VKrJvZbJYl\nmGIDlOM3NjbEvGg0Giy1NB1m4b59+3YURWqihpxSrVZDRYmBrayscMuKp5EyVAbLZxb5QPDNtzVR\nVkw5uV6vpxCuKpq9uP4s7uYl2noURfV6XYFHc+XYzFIymXz55Zfv3LnDXbRaLd6H8Xi8vr7Odb/4\n4gul9EajkTp0EyalFpsJgbmj6DRHvvTSS2+99RbO7OnTp/fv32cmc7nc0dGRXkjxZer1Oi9tv9/X\njPmsYbCrZCGEGCxYsGDBLqUFAZnCKgAAIABJREFUBBbsoqmgVRyNXq+Xz+e9XC8iPfPz89Jsbbfb\nJPAh4guBicTBvthiJSS+LxaLPnwnlrYfjwKPNOQ1s1KpxAiRhmKQ0hq286JHyWSSL4+PjxuNhqiS\nXBeM4mt1OY8qAbg17heWPAgsmUxyZKvVklR/NptNJBIcUKvVCHxBXgDoEJpjPDD0LGYZzOIuVgsL\nC6r2ZQYgVXrBe9CwArCJREIAS8/If4BPKCo8957NZj0fREQS1YkXCoV6vQ4a813NRLhfXl5+6623\n4KoMBoNGoyGwK27O/Py85xMyqsFgwCT0+/3BYODJpeLLEIS8efNmr9eD7fL06dPBYMA7YHGwV/QN\n7uj69evMSavVUiGzj38Gu0oWHFiwiya5BBY1M2s0GpJTgrnO+pVIJIit9fv94+NjXFQul5ODoWGH\nxeRvMdelSaiAm3dgxLL4oZQ4OK0cmFh2o9FIQUhJWrAsWszSZjGNoqjf7yuTx5deJkO0Q3OdSkaj\nkVh5FMPph+rNKBo9U8d46vU6EUK6SkqRpNfrEftCNcpiSqRCpul0mpnUSp1Op+fm5piHbrerJJb0\nllis5cDUD0V7Di9Zgra9xU6az3D6NasKG0oPEzcsEUUm59q1a6urqzjap0+fPnnyhMLB0WgEn57w\nrGRB9NzL5TLuh0oyPSyJVFWr1ZdeesnMisXikydPqP06PDyUrr88tCcZZjIZytEYpCKlomsGu2IW\nHFiwiyYEhmqRmTWbTdUOe/0hebVOp7O7u0sCv1Qq1et1EcG1f5enYRVTdzGJ54q4gatjGRIdo1gs\nVqtV9R+Rwu9sNmNgvhlHr9eD1+6VdrmuVLKE81QOrNJmc0Va0+mUKmCLs3eCbsKLqqDCcaqSCT73\n5uZmvV7H0yeTyX6/D/NFyy7MexUvi/c/Pz8vWCaewnA4lCPp9/vU4TUaDTkwQOeFdifsA/CLURSB\nlWezmSq6kslks9n0YpUW+2aQ0Gw229vbU0UXbm9ubq5UKrEnePDgwdbWFsUPYnmQwuQt4my8D/l8\nngNarVar1cIFAnAZcBRFr7/+Ogf85je/ganfaDT0cgr1Ujmu10kKyCowDwyOK2whBxYsWLBgwS6l\nBQQW7I8azRUtbgICdV4EaIu1xs2s2WxubW1BPINX/eDBAzPb398HhRCtEsTJ5/OiyakhiMUhRBQi\ntNEG2G1ubl6/fp3xENazOEskLp8U8R8+fIheA7r4ItqJDSimuDAZJsgoVSRQHWdA1EMl2NJTR8bC\nYuo2QKfZbJI529/fn5uboxT3lVdeKRaLDFJtgrvd7nA4BDLS6FlyFbO4P4g0rjKZDIIUDPJXv/qV\nmd29e1el2RKyMqeVjGQXwGt5eZlO0CA54cV2u62D+TmxUwiW1WpV2le9Xo85pwwctL23t7e/v89n\n34ZUDTypf+ctKpVKnBacpOJrqinMbHFxEXZ+KpVqNpuql0+n04RPRWTFvH6/3g1flfH/5cUPdmks\nOLBgf9RarZa6Z9VqNYp1+v1+s9lkRTg9PSWBn0qlvvzySwSoFhcXX3755bfeesvMfvnLX+KHCoWC\nhMaTyaR6R0l9Y35+vlKpSDlpb2+PVX5zc/OHP/yhmd28eTOTyRChUptg1kSWwkqlMhgMyME8fPgQ\n51GpVC7E1qRxNYu7WCUSCd8tRVLxfAlhQYpNhUJB+SEcmHjhFsu0802hUFDb6K2trUePHpnZycnJ\njRs3WJrv37/PtZrN5snJyf379xmwKBIicezv7/d6PcKnlUpFYlSqDCOeJt6/pJV8u+parYYCyBtv\nvPHmm29a3DKG9BJJR51Bs7S9vf3kyRMze+WVV+bm5jhDpVIhrjg/P396espmpdlsqs9yKpWSloeo\nHxa7STM7PDzEk0VRpN0MfHe2R8qzfvnll3A3LFZF8aR8TjuNG3zX6/Ver8feRWFqrhjsSlpwYMH+\nqAkGHRwcoORkZpVKpd1us9FWY8l6vb6/v099bi6Xe+211/7pn/7JzO7cufOb3/zGzIbDIUuVxQ0V\nWfHVDnFxcXFpaQmAlc1mG40GZ7558yYkgna7vb+/Ty5EUlWTyaRYLLKyj8fj/f39zz//3MyOjo5w\nvaI7WpwPE5FB7mcwGEhUKZ/PCzqoMGsymTCYbrerDlteT8vv8cUZ6Xa7XKter5P6MrMnT5588skn\nrLzlclndUtrtNr55Op2Kw+kRxtnZGQvx0dFRsVhk9R+NRugqDYdDiRZ6U8cWSqxE9mOExWJxc3OT\nR9nv90ulkvKR/IoWOUzp2toaysjcBWzD7e3t2WxGSs+rdjFpmhzfHUb7A6a33+8Ph0O2QaBhzrC+\nvk5672c/+xku1hygtLjynbd0cXERzzo/P9/tdnFg4Pg/5z0Pdnkt5MCCBQsWLNiltIDAgv0pEzv8\n8PBQ7RkrlQqsPIWq2LwDEZ48efLuu+9+//vfN7O1tbVvfvObZrayspLNZgVuKDAys0KhwKl2d3eF\n53K53Kuvvir6otJpyLaa231XKpVKpQILbmtr68GDBwTiJKGEoLu6pQimtFotruvbJU8mk263y22K\nzJZOp0ulEl+idkEIS/1lfNtfoJjomhJ3F0s+n8/TYpjbVA6s3W4D0dLp9MnJiUq+wBDtdjudTnOb\n5orqZrMZ+IlmxypCUCGExd0dGZVuSipZy8vLm5ubZrazsyPlXxUhoM4FNGy1WtPplMDg7u4uX+7u\n7qqxJyE7PutURClV86f2mFJm4RIiPSaTSYKTL7300sOHD83st7/9bbfbVUhTIE9ta8ysWq2K5Nlu\nt5ko3ywm2FW14MCC/SnDoyBkztKfy+Wq1SpRGmVrcF1qsfHw4cMPPvjAzK5fv46jmp+flzgQ+RjW\nL9/RKpPJqKKLNd3MvvjiCxay0WiUz+cJnUkcaG1trVKp3Lt3z8zu3r27vb2tjBT+iXNOXS9pFtNO\np8O1oihSjItCKBHQ5dvkAukTrf5kioZZTEJJpVJirivfZi7Vd+3ateXlZVU1icjQ6/XkVLrdLtOu\ndiHENsXL8H5C9U8qDOAbOVfVj0dRJOaFig2ka9VsNlVoPBwOdTsKhCqwyS3jm8fjsVp/eUkniC32\nXBRUIc1MJiNNr3w+T8IykUjMz88jTFUoFN59910z29vbU8kdZ/DSVsyzgp8nJyf7+/tq9q1qxT/j\nTQ92KS2EEIMFCxYs2KW0gMCC/VFLJBISdFDUjmbKYopLjYJYkJn1er2tra2trS0ze+2114jnPHz4\nUOXPZnZ6eqr+vGpoGUWR+kZubW2hHvTkyROiVYTyQAOJRALixvLy8mw2Q3r44OCAeJo5MRF1orKY\nIq9mXV6mXfRIi7ELjactZrJIL5h2kXxWOQFNkC3Wbgc5eX2pWdxccWNjo1wuw5iXngXzrKkWv86T\nDMXhhAqhomZBExFJaB6mO9KvCoWC+kpLq340GnFAtVp9nv2IajA4EsqJ5Oo5AOUtL9Osxsfq4ywR\nMoqp1bOU2YPzcuPGDTObn5+/du3arVu3zOyLL774+OOPNeeK0NJP1b+l0qkyM8CrtL7+9Osd7ApY\ncGDB/ncj9yBtBVZDM2s2m6Jr53I56Urs7+8jxC6ZwUePHon0rK4rFhfumFmpVCqXy+qz/OjRIxxY\ns9nEeURRpMxKOp0m8FWv17e2tnBg6JpLgMqX/uizl2xQKkWKgng1uSVl7LwDo/2KOS0JziYNxmw2\nS6QukUjoSIUTNzY2CoWCL2KTKXQpSacLw5bH1caCqJ09V+okT6OQJrk3ziD/B1VddFBpzHe7XVVu\nZbNZ4pzlclnESwXlSARqtEr1SQDMq0MxSLXMFhVzcXGRS1y/fn1hYYEb+eSTTyA38l7ptPKyMrRL\npLMlh+o1EoNdVQsOLNj/bgAa9fYtFArK7mCj0Ugdgcfj8enpKfTudrvN4rW3tydvl0gkut0uS5LA\n3NzcHCsRv9rb25OaIqeFfyG9pevXr5tZPp+/f/8+hUpUdCkH4zfg8i6S6FWGn2QYY6DHCjBOyrZ4\nOC2gnU6HsyknBIgRsCgUCjjXcrkMO7xareqAGzduZDIZafWyFvsqLnPdon06TeKQ6gKj7y122IKn\nunG1icnlcuVyWY1I+H44HEpdV1XqzAlkjX6/v7S09MILL3BAq9XSJZQYMwdwpQmp+c9ms5J89JT6\nbrfLhCwvL9++fZsS+Lm5ubOzsw8//NDM3n//fY6s1WpUL1icpBR7Xj57MBhoSgU61Y8t2BW2gLKD\nBQsWLNiltIDAgv0pY5ObzWaFwKACIrqxtbUlOpziS7D+PvnkEzN77733vvvd75pZoVDY2dmR6PjZ\n2Rl7f7HUyJmpg0kymVSTQ0Gl8XgMp/HGjRvAgsePH7/zzjvABcR8JenENhwBX4k+ZLNZhbDUkaTf\n73OtSqWysrIC+/Hjjz8mUyVxCsapkUdRxP0CMoCkYDgwUKlUIp2zsrLiK3BbrRZiSO12mw+Q95S1\nEpZSxq5SqXiKpnCM2n5Cj1SKUeXAUn8vFArw/cxl7CzuHWqx+gaqXbLJZPLGG2+8+uqrfD49PRUy\nEwQsl8vcBR23xX5k3iqVSrVaVdcYNbQsFArf+MY3zOxb3/pWMplEP+XDDz989OjRRx99ZE6E7AIY\npauLOS2V0WjUarX0pYS4RCgNdoUtOLBgf8qk7SQdB1IaJC1efvllHFU6nW42m/iJbDZbr9dZkn7y\nk5+88sorZvbaa6+1Wi3I95DCOX+73Rb1QEVCFmv3WSyfYXGnDPzWd77zHY78xS9+8eWXX3pXx6/S\n6TSujjgeRUKFQkFKekdHR6xuxWIRDSQzW1pa+v73v894dnd34XYTulTmTIzt4+NjcRMuJKvw091u\nFw2RxcVFf2udTocDOp2Oeo+pqmw2mxWLRUlXyIEpg0W+R35a+ocKqbGy48wUT7t+/fr6+jrMl+l0\nim9mAMrkLS0toXH15ptvKu+4tLTEjN2/f//zzz8nWgtnh3ukU4GmV0FRHjEKljyUwWCQyWTQY9zY\n2OBl+Ld/+zcVxm1tbT18+JCtjLQo8azsKuQ4ubU33njDzFBKVMYrmUwGEfr/OxYcWLA/ZawCg8FA\nCkmTyUR5oPn5eXwDakys8mTIWDd/9rOffe973zOzH//4x4Jln3/+ucqwlNYyM2EXlmC1fSKTtLm5\neePGDZIliUQCTalOpyOYwq/klkjPLCwsbGxs4FkTiQS9NC0mrXEkFWYWwxQW98FgwP3Sk1PgUiVQ\n6twBA5CFu9/vU+htZq1WCx5dsVhcWVlRPZacmfR5EYFkkIAYUfjUtka1aOZgq5SZqCRjEYdIwvSq\nWwqYVfXC5Pkmk8nh4SE+CYFK2IDr6+u4XjNrNpvU4W1vbx8fH0tIV7QX0UDYMeixcmudTqfdbqvD\nZxRF3ObR0dF///d/m9m9e/eKxaJUsk5PT3HJkjym3Jvr9vt9+elKpQJE42FpD5FOp/Vwg115CxA7\nWLBgwYJdSgsILNifZYlEQsVDSMea2eLiIlv1R48eKXQGbQ9BoJOTk//8z/80s29/+9svvfQScC2V\nSr333ntsk2u1mhRv1VqFbTjf53I5woavvfba4uIiZzAzUM4rr7yytbUlXatUKqU0j2iBxWJRkvlq\ndCm12dlsVigUuIvr16+Xy2X4kzT/tZhgKVa6uniImkjtlxqCkArizMDE3//+95ubm6jN1mo1RSxF\nRyQIKWHfXC7HpXu9Hqfq9Xqj0UjiF/1+H0TSarUYQxRFekCMh1lKJpPc+9LSUi6X41e9Xo8PPCmA\nXTKZPDo64qE8efKEQF8ikTg4OFChnlTqkS9hEjKZjHq7iCIoxY1Go3F0dMQgc7lcFEU8uJWVlX/8\nx3/kVP/6r//67//+72a2v7+vni/ZbFaR2E6nI+ahxfnIcrnMyzA3NzedTon3drtdyXYE+79gwYEF\n+7Ps7OzMB/2I+VSrVcI4jUZDPVagORBQqlartBH5+c9//rd/+7dw38vl8tnZ2TvvvGNm/X6fBcti\noaAL11V/k5OTE7EPVNF848aNjY0NKsZI74s7AM1kYWFBGurE1uApLC4uqppYzUGWlpbUXmQ0Gsnd\niq1OQbeKAcRwUbkVGlfKw3Ekayu+YWlpqVQqMYZCoSAaiBdv1OXoj8X0ivfvdafkMBgV6zv5MM5Q\nLpfpQ1apVPL5PGNA8tHibJz47qTizFWPwbOnFB2vqTPwdOglzWdcu56gSq2lP0ntBAmzxcVFBvbR\nRx/RzMxcAxpzLbNHo5Fvn51KpXiy6XSaaXz55ZfFMDo+PvYF3X/Oix3sUlsIIQYLFixYsEtpAYEF\n+3NNzOzJZELUrlKpgLTq9Xq32xVtTCR1CVsQRvv6179uZisrK2+//TYktO3tbXbfEi+3WLJBeA4p\nqbOzMxHQk8kku++lpaVXX32Vvfbp6elwOASi1Wo1ooILCwvlcpldPwRr6YCon/Lq6irsu3K53Ov1\n4E8KcUIMUcdF1cwq+AYDXtXW2Wz2T/C8z87Ovva1rzF4BbuopAYmdjodUVEEJvr9vmqEaaAFIlGc\nDSQkBV6ROCqVCiFEyR+bI86g3suUplIpqR4LO04mk3a7DXW+2+2KBKiBicFhMSWS/5Wu2Hg89l0I\nxM3J5/MIbfzyl7+8d++e+oV6ErzuVyNPp9NRFAH6+/0+A0MmnwOk9BHs/4gFBxbszzItPahyEINS\nv3l481JhmM1meLharcbS/+DBg3fffZc1ularff3rX4ctfXJyoiCYv5wCdMPhkN6Jh4eHh4eHhLPU\nmb5ard65c4dL7O7uKiek5Fy9XpfOEwR05WMYTBRFN2/eJJxVKBQODw9ZFuUPyIGpMEt8d0XDvM4T\nOR61o1SwUdVjHEkQzGI1Kaq4SC+J/m6u+MxH5/Be6vlCLBeeJF9ya5Ael5aWcGDwJLU/kG9otVqE\nUslmScufnxM/ZM5hOSq95yOEDNKHEwmKWizJ4Ztq8uDMjH4FP//5z588ecIgRUM1J9jofWQ2m63V\nahy8v79PdHoymShRFwq//q9ZcGDB/neDgK7tuTSfJFQIFBPjQISC09NT8l79fv8Xv/iFlsIf//jH\nf/M3f2NmZ2dn77//vpkhU4SPLBQKYqt7XSV1loJ5YWavv/76ysoKn2/dutXtdlmC6fliMZtAq22/\n32eR1TI6Nzf36quvkoejQkAlUPyKGxHAKpfLgEUlZnAe6m5VqVT4Xn2r8aBqEra0tCTdo6OjIzNb\nW1srFApyWhJLlNQhgEZ+UQ51Op2Cn1A3lhNVFcHS0hJoj/4yOoNkl6WAzLaDs3W7XYki0qfNzqfW\npJWM0i4zCeUEZ5PP59U9DuUwvqzVajjvTqfz3nvvmdnR0ZHIO77qfDabqf+ZLIqilZUVaCD9fp9W\n0R9++KF0OEPe6/+ahQ1LsGDBggW7lBYQWLA/14hWFYtFlGHN6SoVi8VqteqbdLAXhjJnZqVSaW9v\n72c/+5mZffrppwcHB//8z/9sZv/wD/9A8exPf/rT3d1dDq5Wq6VSCRzT6XT4AKQA/WxtbZF7W11d\nrdfrEoISROv1emourLwXcIGDaWFsZgsLC9euXQP5HR8fP3v2DBQiCVpwITgjn89Ty2xm29vbotGr\nkBnQQEZNGhao7AuWzWYzsjhSoDDX25q2MqoC5kvwmdq7SJ1d8JQ2mzyU5eXlxcVFr/xr56U6EKE3\ns5OTEzRWLC6TELgkbDsYDHTvvjlkKpXicfjWLaVSST1oJOXl68QJ1QITf/3rX//qV78ys+l0KuUR\npksS/spmqSqD+yLmSfdLi6OUovX//3y5g11OCw4s2J9rxHnQdlKLdygPLJqE8g4PD6WRmMvl+FW3\n2/1/7Z3Jjxxn+cefXqurq/ee7vHM2B7H4yV2Fos4DhAgP2GBQAo5wA2unBAHJCRA/B9IXBFKuMCF\nRWIJJMSOREJglDixY3u8zeqxZ3p6767q9Xf4qr56GTvGkzgTKn4+B9R0uqveqh6/Tz3b90mn09hf\nKpXKL3/5SyTJfvjDH546dUpEksnk/Pz85cuXRWR9ff3WrVuIFJVKJYpNoH4BrzGuBQUR3M2pMcFS\nC8TTOP2ZE0yi0eiBAwdEZHp6mjmhVqu1vLyMTZytTtz0RWQwGLCIgNm7RqPBkVej0Yh155yAnMvl\nGFNllg5Q071QKCBpt76+zmQV52BFIpFut8txNswVua7LzFmxWMSdPHLkyNTUFH6LdruNYplarTY7\nO8txX9TRp53odDrmuGTWoVDTHZ151GNEoC+VSlH2UIwhauI/cHie1+v1Dh8+LCLlcrnT6UBs/pVX\nXsGRLcuChD/WQ4X+RqNB657L5RAIhfVC3JVpNjxV8OFpR3/SStBRA6bcL+ZIC+44KHlABQE2snw+\n3+128QiP0SoiAhE8dFZFo9FqtfqLX/wCr3/wgx+IyLFjxwqFwhNPPCEiqAfB6TY3N9HmhZ4n7Lbj\n8RjdWufOnSuXy1hMtVptNpuwW9So9Twvk8mYwr4cAwY/CR3E2OWvX7++ublJ9SZctWVZzD8hKYUv\nzs3NraysiEij0WBnMQSosPNms1mKb7G5OJvNdrtdWDjXdbHtoqARtQnpdDoej8M8UBJpNBpx/ghL\nS8QvzRCRZDJ54sSJz3zmMzjCeDxG6WYkEqHnBC1jMUpDcUy8Zo2J+KWD4rtlWAyKUzhWBo8Xhw4d\nYsFOrVZDw7X4hhw/yuHDh3HH1tbWLl68+Pbbb+N9/DH0er12u40bhTY+3CheeywWK5VKsEy1Wg0T\nv8QYRoMEIc6rBuxhQ3NgiqIoSiBRD0y5XzgUYzwec0Qk3kTDEKJGlmVNT09TFIojg7vdLh7wU6lU\nLpdDG9Crr7565MgREQmHwxisLCJHjhx5+umn8cVf/epXHMDB6kemOhqNxo0bN5A1wTh51hAi14Um\nJLOcnbryLGG/ffs2avrX1taolD8YDNiaxhLBcDjc6/Vwimw2y6K+TqfD4GSv14PzZ9s2p5MkEglK\nhDiOw/o6ppQgs4SFmapR+NhoNEKYUUTG4zGiqVgPrn1mZubQoUPsJKvVanB8eVjIaOF01GXG1TEA\naGaScI3Qj8cpsBg4XpOTk1BVzufztm2jCaHdbjcaDXhjW1tbcKSOHz8+Ozt75coVEfn3v/997do1\nfACzK/EXwpQe1Pc5cJmO7Hg8RmQ4FApxTOj6+jpliMWP8SoPG2rAlB1Dk8DyZYhLYRNBjzAyOhji\nJSIYdEIzgDINEbl58+Zrr72GY9ZqNSSNMpmMZVmIHK6srGCzRkKIPVjYH5vN5o0bNyh1KP4+22q1\ncChUN1BbiAXo1Deq1WqLi4vYCjc2NtjYRF0rdI8x9zMej1HMwsgkBK5oWTmsq1ar0bpnMhlU6mNV\nMCps2jWljwaDAWvB+QKzbGBZO50OFaQikQgCcbOzs5gLIyKwItjxRQRl6/F4fGtrC2fn3C/LsijM\nyJ9G/Jlk4htILHJrayufz+No6F4Qv4WAw19Y3VMoFHC9jz766OLi4qVLl0RkcXGxVquxHZ6F+AwA\nosyEA2Kwfs/z+v0+7lg+n9+zZw8eTVqtljl8x7yTysODhhAVRVGUQKIemLJj+MjMGVeIK7KZlHML\nM5kMasbgPLGgALX4IlKv15HVTyaTlmXhW3jqh1eEmmnx/ZVtIcRut7u+vs4BUfSrGIXDaEfKW7AV\nl9UNa2tri4uLKDlBiSCf/VnuIb5DANcEHiG9T8oNA3pgrVaL+h2JRIJt4CICX4q19ZxnJiJUwxJj\noGU6nWb5PsRE6CGhnWDv3r3hcBj3CgMeWRBPVV+GE+mBZbNZRBrFd0m3tQPjN+X052QyiS/u2bMH\nDjTazykfFY/H4YGJCIo8p6am/vWvfy0sLIhIpVIZDAZwGelp4We9RwAQqitwskulUrlc5u3ijWLJ\nj/KwoQZM2TGsrnYcxxzfjp3Odd1IJIIdZ8+ePTBgYlSxD4dDs9gMgkCPPfbYY489hjq6kydPdrtd\nzCKhbBJCeYy2UQUDSRTxO6howBBDS6VSqVSKWx5ljUKhEBZ25cqVxcVF1BDiXLRwDPRRoIgHx8o5\nPJNbv6n51O12EXjkssUfvYhrxwwU3lWW8pujL/HmxMSE67roWIDd5bDNmZkZ3GfqesB64VbXajW8\nmJ6eRp8cDgs7tHfvXkwwEV+Jg+uhCglDmvl8fnp6Gj/rcDhEwnI0GnFENcpQ8VySTCaRGFtfX3/t\ntdcwEhPTWPCBwWBA6/5B1gvnLZfLhw8fpn7/aDRCB8Xm5iZuo3l7lYcNNWDKh4FtuXigTiQS2WyW\nYonc3FOpFFpQV1dX+aiOAbvwQhKJBHyFS5cu5fN5DM2KxWKFQgE7YCqVwgdMnVyOSBYRz/Owmbqu\nWywWsdNlMhkK6VLZFv4TawfQc3b9+nXTCzHF9DhnhI1ikDeEAUOBvvgjm9msZn4Y3hsaD2B4YGNg\nfmzbpvYg03vwmfCanc7of6JKluM4uPx8Pv/oo49i5SgxF5FGo9FsNpGo44tMJtNut/FMwEeNgwcP\n2raNCotKpcJrx1Qz8VXBUK9x+PDhYrGIo509exaHSiaTMzMzsGqxWCwcDuNnLZfLSGG+/PLLb775\nJg0n++HEz1ZuE38yByt/4QtfEJHTp0/bto2uiWvXrl2+fBlPPOLrgbE4RXkI0RyYoiiKEkjUA1M+\nDHjmReRN/FQTnr6RNcGj9OTk5OOPPy4itm2vrq7iuR4RSDgZxWIRz+83b97805/+hHzYuXPnvve9\n7508eVJE1tfXz58/L36Mi420TDtZlmUqzMI94rDjcDicTqepW4G6cCwSMcbNzU2WRyIphQ9zuiMi\nVPSlRIQjjFlHFwqFOJWYKlbMFMLdhHs6Go1u3Lhx9OhREXEcBw5Nt9ulNDDCmIizcShJtVpdWVnB\n6SYmJhzHQarpyJEj8EIWFxcrlQrcu3q9jgWISLvdxjjNSCRi2zZ8qVwuh9U6jvPcc88hIvfOO+9s\nbGyg/blSqeA+w8XEeTHGGadkAAAfDklEQVQNgFOScXNGo9HFixcpYTUzM4OcXKFQOHfunIj8+te/\n3traQkkqBmkiUccIrRk/xJ3Eb3HixImvfe1rIlIul8+cOYPxp8vLy51OB5ecTCaxWuVhRg2Y8uEJ\nhUJQTEin05Srj8VibB7qdDqwapOTk9RYwoAMGLNbt27BgO3bt4+VFy+//LLneT/5yU9E5IUXXsCh\nLly4UKvVaLfwSRFxHAfbcTQa5eyV4XBI9TyKu0PWCOuxLAtvNptNaBGJLzxBq4zzij9zWfxZaHhz\nNBrBBJpiiQhdMtZHOUfxpSU6nY7jOJB/LBQKSGuhg4qxtXA4zGkmeGdzc7NWq1GBPpvNQpzpyJEj\nuArMfKF1p0g8wpu4z1tbWwcPHsQBYbTeeuutEydOPPvss7jGpaUlvD8YDGAbkOPEMswYI29OKBSq\nVquwcxjdgqv485///Jvf/EZErl69um/fPnygXq/3+33eVTZg8LCQKMMPl81mkTl7/fXX5+fnYfZ6\nvZ4ZOuYzyn/5M1U+vehvryiKogQS9cCUDw8FzsWIuWFmI95fWlrC0/fs7Kxt28j8Ly4uckrhaDRC\njKvf71M8sNPpnD17FoPEvvvd737+858XEcdxFhcXIVrISKD4DgdeoFxCRNLpNAQ+JiYmKI2fTqdz\nuRw8gOXlZTgZqLJjHSOkzcWoJkANCMtP6ARwTiYKNCgXQm9MfP1+VmqISLfbbbfb8MwSiQRjjM1m\nk7OVWSeCxmQRiUQi2WwWp0Ohiilui4Mz8AgBZTi77XYbATfP8y5duoQjlMtlXGM2m200Gu+9956I\noFQdscdWq4UfBSObcSts26ZmB/sZOp1OuVyGiPDExMTa2hqO9tprr6ELolQqxeNx3GrMlWYVIq7O\n9J9yuRzLcDzPu3DhgohgWCWVXziKzBx0qTy0qAFTHgDtdtsMxDHQxwoxqNxi/kW3211cXKTNoIBs\np9PBPgXx9b///e8iUiqVnnvuORE5cuRIqVRCNdrCwgI2bgiZ0xYyFzU3N3fo0CEs4OrVq0jS5PN5\nCMOLSLPZhJGwLItDllF9B+uCriZ+gIJYYogaU7eCo4oRImN2h/r9bHWigK/4o0HFF9pggo0JM34S\nGsTsIbNtG4HQWCzGKtBWq3WnGgWb0iKRSKVSwQTIbreL2sXnn38+Ho/jmQA1hFgPbbPneWgSwGpR\nkCm+zRaRycnJJ598Evf83Llz58+fR21npVJBMiwcDlerVWYQgRgRYCwYfxilUqlQKODutdttmH/c\nW2pusdUP/1V5yFEDpnwkTNfEfJ9dt3iobzab2AFFJJfLNRoNFq8DVKJTqDAWi2FjPXPmDHbVY8eO\npdNp5H4SiQSyNd1ul/4T+oXh8B08eBA7+9LS0vLyMooIzL4rzAkTv1mYBoxF8GhWE79ZmxJWzMEw\nGcb0mPi2DV80O7t5CkxFYRkI228jkQjNv9wtr0NLD2vHHl52rYlvumCG2ccNA8a2cRFZXV3F/y2V\nStPT03DR4GWy05ntCuzYw/KoKonM5dzcXDKZhFLU/Pz84uIiCkl4KFgsGn5W39AmjcfjbDbL5gdW\n3zSbTfhtruv2ej1cGlS7zFutPORoDkxRFEUJJOqBKQ8AlOeZEkQMZ8HzaLVafJZPpVJ79uxBbR4L\n7pG+gieBdA5ct/n5eeSQms3mk08+OTc3JyITExMsH2+321TEyGazEJmdnZ3Fg/zq6mqj0aB+BNfD\n1E4kEqFbgIp5+o70wBiI438VkXa7zQmTvA9IDtGXogSw+MXo3W6Xg9NYiokl0ZMzB0visKbOE3Jy\nuGSKUEAuyxzsSX0NnBdRQXygUqkwOPm5z30O8zlxRritGCEtIp7nJZNJ6tmPx2N+DAogMzMzKysr\nmK18+fJlRoxTqRQ1kelo4ubwBjLUOTExgRAi5LJQ9Li1tcUkpRkUpaSWqRuiPLSoAVMeGIwOib8h\nxuNx7IlIa2FbjEQi5XIZu/bFixep37EtCIkvbm1tIRm2sLDw9NNPnz59WkS++c1vfulLXxKRqamp\nK1euYDfPZDKFQgEGzLZtKEH0er1Dhw7hTcdxut0uwmiVSoVKht1ul3J/NFEcQWnbNoyc+NMXOVAR\nJhbBT4o0plIpBMRisRi2fihQUHB9bm6OgTgcASEy1ilwSAoSXbhjLB5BsQzzQCijd10XBRci0ul0\nOJBafOs4GAzS6TRuKZsf3n33Xfbh9ft9ZtRKpRKFoDgC1PO8VCoFa7d3715c47lz51566SXc6nw+\nn06nOW8TVSTIjOJhhfMwTSKRSLFYZMqt1WqhOaHVapkS9RxJimaynfxVKp9m1IApD5jhcMhR95wz\nUqvVuA1BdwqDOdrtNuoyMJWDiSLHcbCZJpNJbKCbm5t/+ctf3nrrLRGZn5//0Y9+JCJHjx6dm5vD\njoYWYDZTo8Uqm80eO3YMR8DwMOy2ly9fpkov258xOplTzeCmNJvNdDqN1JrjOIPBAPV1tVoNHhJc\nAdO6UGuKo8Vo9iYnJ5999ll88fLly0gEQiARmzh3ajGmQpuCgZCSwiKpFNVoNDY2NnA0yFmxNZv6\nk41Gg3UiOH61Wn377bfRdzU1NTUcDnHYffv24eue5125cgX34eDBg8ePH4cBG41Gf/3rX0XkpZde\nunXrFo6AHjhOMqPcMC0rbhTdKcpZUU2x1+uxnpPXiwZ5+nOs3VD3SxHNgSmKoigBRT0w5QGDKBwS\nGMVikQ/UVKaAK4Zn+cOHD8PnWFlZgVgUDkKBBky/FJHp6enhcIiY2+9//3s0Kv34xz9+4okn4Dfg\nAZ9VfGgjg3cFD2BjY2NlZQX+U6vVorhDKBTCGpBewsM+50dDhoMl9YlEAgXiLFvnJ7EGTlcZDAY8\nVCgUQszts5/97MrKyu9+9zsRefXVVxFbgzIT4pyTk5MrKysIIXqeR8mueDxunoV6wQi4ra6uVioV\nNpyZahdmqg+uaqvVggs4HA7Pnz+PaOFXv/pVlHGKCFWV4/F4MplEDWe5XK5UKmfPnhWRt99+e35+\nHkc4dOgQHLtGo2GO4uTK+T4Wg9fJZBKyIPl83vM8OHmtVotCXL1eD4tMpVLhcBiX2e/31fFSTNSA\nKQ8YlkeLSLfbRbUFptRjZ2+329VqFXs3Vedt2759+zZbf7AXi0g2m6W8Ico0RKTZbL7xxhsi8tOf\n/vTb3/72888/jyM0Gg2U11+6dAlvptPpfr+PfEytVqtUKniNQcAi0mq1UqkUdnzUKbC5GOan0+mw\nb9d1XY60dxwHnbZijG9GCTvDiazIT6VSGHXmed7Pf/5zfBEDzESkXq9XKpUnnnhCRE6cOHH9+nVs\n4tlsFjcTtpbzlMfjMe7exsYGesM3NzcbjQbHnjH22Ov1KFRYqVRg9Xu9HhYGPS3ch2g0ura2hvtv\nWdYzzzwjIidPnjxx4gTCtq+88srZs2dh/l3XZWdCpVJBWtEsJGEGjiMIxLfu+AX379+PwGOtVrt5\n8yaO0Ov1GM4djUacIcCOBbVeyjY0hKgoiqIEEvXAlI8RhtfMbl8RGY1G8IQsy4JDMzExQWGkjY0N\nKmKwRdrzPEoDMxL1/vvvv/jiiyhe2Ldvn+d5EEGvVqv/93//J34AihpX4hdJRqNRuIaDwYA1AmK0\nx9q2TX9R/IJABBsRQnQcB24QmrXpN4hf/h4Oh9lNzCbuXq9Hl2X//v3wLTY2Nq5evQrtq8cff/z8\n+fOYcJbJZMyhz6g1z+fzLDDZ2tpC4zCcPC5+NBrBhxsMBlCgP3r06LVr1+hcsp+h1+thDeFweG1t\n7c033xSR1dVVOLgvvPDCuXPnIMu7sLDAAopcLocjtNvtVqtFD4l+rel1id9GncvlWAmZSCQQ1221\nWpubm3ht9iZDAEVEOp2O53k6slK5K2rAlI8FBhJhBpLJJHuwYJMouIAdzXGcVCrFXFS1WsUu32q1\nWM/W6/UQWqTuYigUWl5e/uMf/ygixWIxFoth4y6VSrCFqHVE+G5yctJ1XcS42u22OUvabFTC+jml\nRfxZmlhkLpdjsxQsyvLycq1W4wQT7t3pdJpy8pTnRyyRxZbMdd26dWthYUFEvvzlL586deqVV14R\n33biNpZKpQMHDuAqotEobPa2gBs72BjSjEQiyL1NTU3V63XKZODSbNs2R6vMzMwgMbm0tITWrpWV\nldXV1YsXL4rfGMfONlwvOhAYMCTRaNScd4NfoVAo8FmBI7Pb7TYfVvBcQkVHvMkgp6LciRow5eMF\nOykthPg7LHalZrOJDTQcDtu2zTRPOBymEi5LAGhgEokExQDb7TZSSrZtJ5NJ1Lsnk8l3330Xhy2X\nyzA/FMAVkdu3b+Ow2WzW8zycq91us0zAsixWOrC6AUYLWRzLsmAXbdtm5izqI77bhOu1bRsLKxaL\n+XyeCUJcb7/fr1QqsBPPPPPM8ePHV1ZWxB96Avbv34+ylGw2C8kr+c9mXtO75Wy2TCaDjuNyubyx\nsQFnNxQKUU04lUrBuqDjmLlALODatWue5+Ge44bQVWXZBTNq/JnMxYTDYcgEi9/djHvCIhoW3Itv\nWalcBfM/HA419aV8EJoDUxRFUQKJemDKxwgnQNbr9Xg8fqcSeavVgjfQ6/VKpRJ8mkKhEAqFMJqS\neRdEIPG0Tll0JKXoq2G0sYi4rotG5gsXLpw+fRoSwJlMJp1Oww9bXFxEANC27c3NzcXFRRFZW1tD\nT7EY6rqI/iFhViwWp6en4Tb1ej24YsVicWNjA+G+UCjkOA68H3hCOEWxWIQnND09jaJ/Eel2u3DL\nRqMReopF5NSpU9/4xje+/vWvi8ibb77JUSbT09NwlSBARbkTqlKJIboRiUQQDHz00UchPF8qlVCp\nKEaPdjgc3rdvH2T7l5aW3n///dXVVdxJeFqtVsu2bVwmsmXwnzhwAKNhTA+JgsIUviqXy7hjo9GI\nTc2VSgU/UCgUYmM1+8FFhJpSinIP1IA9FFDLfPfTCdQ17/f7iBbm83kWymNTwwcYIRyPx4lEAoXa\nnuexvYmxL8a1sN/BYGAWFz6wvr4O+3f58uXXX38dBmxubu7w4cOolZicnERKKRKJLCwswFbt378f\nWhsicvv2bRqJfD6PxczMzBQKBZpknHdubm48HiMxVq1WbduGhV5ZWcHGffLkySeffBKdVQsLC2fO\nnIGdKBQKnE5C0/uHP/zhwIED+JmOHTuG6Nzjjz/ueR6SgqFQKJPJIM42Go1wqEajgU47ESmXywcO\nHHjqqaewNtjIcDh8/Phx2Ox6vQ6TjyIUxFr/9re/zc/P432YYfHVvNgMwGjheDxGDswsWhkOh+zk\ng8Y8bmk2m8WJ6vV6vV5H8Q7NHoafYeXhcJhJ02azuS0aqSh3EtIE6W6CHeETYVt52CcC557QC6EB\ng4wTMzeFQgE7YL/fR3VDs9lkhYVJOBym5CB2QBFJJBLoC+71eqhpxJsTExNHjx4VkWeeeQauCeo+\n4NxMTk6WSiX+i8AL7Nrcl13XxXY8Go1wWI5HEZF2u42xWCLiOM7JkydF5KmnnopEIpCw+tnPfvbb\n3/6WqlFw7NCYDNtQLBaTySTuw3e+8x2c4vvf//54PMbWD+eGWT3cvX/84x+dTgeppj179tDpEZGr\nV6+KXzSBPrBKpYJqjuvXr7/77rvIRSHVRKcTjztQn2Klieu6LMMxp3SadwwLm56eRptXv9+/efMm\nFbNYZ8hnESpGyn+qSj6cdktlHneK5sAURVGUQKIe2K7yCXpg/wuYj+oIbSGoKL6GuhlCfOSRR0Rk\namoKmZtr167RCduWdIGLgJwTP4BbPTExgTGJItLr9dB1JCLRaBRxxaNHjx46dIjV9ul0Gm1ehUKB\nwTdz2Zz5kkwm4RL1er1MJsMLuXDhAnzHRx55hBNh3nvvvXfeeUdEzpw5c+PGDYZzTQ8Grx3HmZ2d\nRcHhqVOncDlf/OIX5+bmsDBk7OBX2bb9la98BZe5tbUFmYzl5eXbt2+zewGppqWlpZWVFYRVq9Uq\nbmmn0xmNRsiWWZZFR9NsJ4jFYma8kdyZ90KtP+8kXMPr169vbW0xs2WWSuJyksmk67rwPFBd+XD6\nXkA9sJ2iBmxXecgNmAkiSOhfFhHP8zhhazwej0YjBMRmZ2dx01zXheSSiFSr1Q/a5swtUkRisRhN\nEYoFEPviTKxYLJbJZBCyi8fj8XicfcoIbe3du3d6eho2yXGceDyOuF+hUOB232q1sLClpaVIJPKt\nb31LRCzLevHFF0Xkn//8Z71eZ//ZG2+8QcFGnAIpPbw5NTW1d+9eWD4OLSsUCo888giyd8lkstFo\nwIBduHCBQVc2U2OEMW5CPB7Hwmq1WiKR4OQamLfhcJhIJNjnQLlFFlC4rvtfzQnTXbhLOEWj0UBd\nTL1e33YE2mmYfOgfPsxGy0QN2E7REKKiKIoSSNQD21XUAyPUkKX6BiNXeIH38/k8Ct/z+XwoFILb\ntLa2BrGlezy54z9hErFZEE/pegQAUXRuzjXGeYfDIb6Vy+Wy2Sy8LqgJs2YELzKZDIYgi4jrujMz\nM6hvfO+99yCD67quZVlwOHq93uuvv85iP3ifKKDAB1B8wdGUuJZoNMojIBxHAXh8AGIivORIJEJf\nCndsOBw6jsNLgxuK4kl4YK7rUnkElYFyHx7YaDQqFou43nw+PxqNEGm8efMmfiCzDRmaXjgLizjQ\n1a4eGFAPbKdoGb3yycDWJYpKmF1NqCwXkUajAUNi23YqlUIwcDgcsg8Jw0q2HZyPZciKUTUKs4/F\nGOoovgg6DotliN92hhVWq1XKQ6RSKRgz1uwlk0lTgCoSiSDN9tZbbyHnFI1GbdvG5UQikVwuB/th\nVtzRkJsBQA51RHyVV0e5CtoDdIbhTQjA4zKpIhiNRhGY5RF4c/ABvOB9u2vBpwlnkxaLRVjWwWDQ\narVQcMiQqRiC9KYy/WAwYL5TrZfyoVEDpnyScKtFMTptFRvFer0e+p8sy0ILlPgP+yKysbGB9iMR\nMceJcU+E1CFeDwYDatdyYhYSQlQUjEQiMGBw3cTX6uVuW61WWaHOjB3kpkQE2SB4ThcuXOBIMwoK\nQ/IRbgqbuCntKCLdbpeTkWOxGJuleKNghzhbGcYDBeimZjF9WRw2EonwWYFaiIPBAP6ZGDNWtv06\nd32HjRAQ1sJ9QI8X/FqaW9hm2ktOMuO51HopHwXNgSmKoiiBRHNgu4rmwO4N/BjHcRzHYQiR4SwK\nwFOfF/4ZXLRarUZ/4q7P9dFoNBaL4TOsnQuHw6aDhc+ISCKRwCm63e5oNDKHwsB7i8fj8Dy63W63\n2+XgaZQFiojrujgUUmtYEhVGRKTValHPwqzUj0Qi+LCpuYWRyuIHXVl5z8RYr9djMJbxT/EdMqQY\nGXjkAujYfZAntK2tm44XB1rWarX19XURqdfrkFMxv55IJBzHQYQWo0HvehYFaA5sp6gB21XUgN0b\n/jValoVI3Xg8hn1Cggpb8NTUFGKJsVgsl8vhW4hfoWqc1dvbJgLfecZYLMY8EAJ92PqTySTMDwav\nwAwg1keTAAODd6gBiKoQMaKjTMKJiG3bLEXhehAFxTpxXQjEmeUP8p/jsrZJYOBCzFDqva/aPMg9\nPjYajSzLQqNYKpWKx+OcdQLrXqvVFhYWEBHlDcdl4pPNZtMctqIBw3ujBmynqAHbVdSA3SesOOD8\nrVqtxjwNCxYcxzlw4AB2WFTiwRPitI7V1dVt6ZZteyj2+m3dY+IbMxHp9/vRaJQGwxzeeKcVYXpJ\n/tPeiO/35HI5y7JgZbFUfnHbcbYt8s4377xjd379fkokeHCm3JC4EhHHcTKZDLxex3GoS+l5HsyS\n67rmzBeOuRERPHZojcaOUAO2UzQHpiiKogQS9cB2FfXAdsp4PEbexbIsOkDQQMJ/TafTZoyLvVDw\nhKrVarPZZFeT67r0e+4aQLsz8nZv3+iuC773J1OpFGcNf9zeSTgc5rTJu/5LZy4Q/W1MkiF8iq4A\nFFW2223Wvnuex2rDcDhMVTBOA6jX6/iWul87Qj2wnaIGbFdRA/ahQVUFW3HZBut5HgoZbNtOJBJ8\nzQAg02AYCAJj1mw2Ic3OiN9uQm3GXdjfmd6zLIuZPCwglUqxwkL8ChoxtBDRVIC260ajwVjreDxG\nD/V4PLZtG5NiMOsLZSn4X2WnqAHbKRpCVBRFUQKJNjIrwQAVHPAS4GyJCOrXUdRnjoXkJzGhih2+\niUSCQlBwJkxlJkwc5muWznO2shhlGhT1ML0olCOy29c8xbbPYJHUVTKdG9ZQ0DfyPM8sMuShxuMx\nfCkch4pZsViMlw+PMxqNZjIZng5fj8fj4/GYsiChUIiV+iywZM0kZzHz1PhAIpGAv1Wv1zloVFF2\nBzVgSjCAFcEOyyAYXmBvhcqGOZBF/LAYDRgQkXg8jjJ9BNawX+MIOIUpOsXDovoRx2y327AlCFFS\ndIMGhlaEUhSAivgU4DCPAMPJLjcYjFarFYvFaF3EqFnHfRiPx9S2R407BbFoihzHMUOpIoKMICKE\nFNMSQ+fJFPXYFu3kbYzFYggn8oYoyq6hObBdRXNgDwTUbogIpoEgc0CpJBEJhUJQLMxkMkzt3JV0\nOo0mX/GlpGD5XNeFYwEDhv19MBhwKEmj0eDEFpooaNTSZtCIsntMfG0qMQyb2ayG7yKTxwYAtADT\nxlCG0bIsrKHb7VqWhUtGNbxpgUSk3++zBKbb7cJo1Wo1OF73vtWsrTfrU7CAdDodiUQg+aj1Gh8d\nzYHtFM2BKYqiKIFEPbBdRT2wBwX+bjGvkvE9Vid6ngdXBjMq8RUU1zEgRsFchuxs206n0/Dtut0u\nCsHT6TSnPkKuiUIb+BamseC8GAWJU1uWZUoG8x8ax1SmUikcylw5uDMWxwAdHD6K/JoaV9TyHwwG\nHMUCL3Bra2tzc5MJQh72v4pxjMdjjLOxLMscmU3P7yGfofxgUQ9sp2gOTAkk2DT7/f76+jrHmliW\nxbQTtduh+Lfti+Px2NwsuHeHw2HGHjlSKx6PY7/u9/uu68JOOI6D3bzf73ueB6uAvitOTsEnTfsU\njUbz+Tzep7AFDAMWZtt2r9dDiT+KLHCura0thBBhFCmEgUci2EKaMQpi8drr9TqVFc1CjLvKiLAP\nDMdhJ1kymcRrZs7UeimfLOqB7SrqgX0c3NlojKZm8RULWafAT1Ib94OOhh1c/PoIc5QJXtu2jV8T\njdKsynMcZ5sEoim/G41Gy+UyUlz1ep12sdfrwZhhyqWZCcO3qO5oYs5Y4ZvIqG2rvLirmYHrCYto\nHoEOFiwinDnUTLJ+8q66XMpHRD2wnaI5MEVRFCWQqAe2q6gHtjuMx2M4Fvl83qySp9fFUnIRSSQS\njBZyIMsnBRw+Dp6GiwMVjDs/jKJHuT+BK5b1M9hoyuQjQXg/GvbKx4d6YDtFc2DKpxNkiarVKjqR\n8SZ7hGnhwuEwdafET0GJiOu6bPO6/ylWsCg4RTgcZvMvW77QKP1B1kj8zmsED13XZSu02Q3NbjaM\nkxa//8wcuMwqD3wFzWGsNIGd5hwZonZLCRYaQlQURVECiXpgyqcQxtYoDSW+YtO2qofxeOy6Ln0m\nFseLX25OgSV+AP8XAzbF93jYyIyqRTEko6CXwVOYUh3U1A+FQqzOp+gGqwRRXXnXgZb4ViwW40Rm\nTDLD+5Tljcfj9AjNsWoP/tYryi6iBkz5dMItfltY7M54oOd5lGmHNpIYIhcICbK+PBKJsPbdtE80\nP/1+H61XNHXhcJghxEgkQoVDtpeZ4hqQBUEhPhcP88P1mNqMCITCFrLQkethqi8cDkO5X3xpKEX5\nFKAGTHm4uGuaB/YAw1bwAQ4XRgqNjk4kEmGhB6cP07GDaWHDFlWsqNUbjUZt28bpkskkrAvagVmI\nPxqNYMBopUajkVlwwaug1KGIDIdDmMDhcDgcDrHgaDRqNqs9qHuoKP8jaA5MURRFCSRaRr+raBl9\nUHgg/y7unJbJWsSPeOQPUe+uTcf/+2gZ/U7REKKi3IUHst3fWSVxn21b94+aJeVhRg2YonxcqHVR\nlI8VzYEpiqIogUQNmKIoihJI1IApiqIogUQNmKIoihJI1IApiqIogUQNmKIoihJI1IApiqIogUQN\nmKIoihJI1IApiqIogUQNmKIoihJI1IApiqIogUQNmKIoihJIdJyKoiiKEkjUA1MURVECiRowRVEU\nJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRow\nRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVEC\niRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMU\nRVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCo\nAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEU\nJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZCoAVMURVECiRowRVEUJZD8P4iTBngm1hJY\nAAAAAElFTkSuQmCC\n", "output_type": "display_data"}], "prompt_number": 4, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(M);"]}, {"source": ["Make it binary."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 5, "cell_type": "code", "language": "python", "metadata": {}, "input": ["M = double(M>.45);"]}, {"source": ["Display."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 6, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(M);"]}, {"source": ["Round structuring element."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 7, "cell_type": "code", "language": "python", "metadata": {}, "input": ["wmax = 7;\n", "[Y,X] = meshgrid(-wmax:wmax, -wmax:wmax);\n", "normalize = @(x)x/sum(x(:));\n", "strel = @(w)normalize( double( X.^2+Y.^2<=w^2 ) );"]}, {"source": ["__Exercise 1__\n", "\n", "Display structuring elements of increasing sizes."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 8, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo1()"]}, {"collapsed": false, "outputs": [], "prompt_number": 9, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}, {"source": ["Dillation\n", "---------\n", "A dilation corresponds to take the maximum value of the image aroung each pixel,\n", "in a region equal to the structuring element.\n", "\n", "\n", "It can be implemented using a convolution with the structuring element\n", "followed by a thresholding."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 10, "cell_type": "code", "language": "python", "metadata": {}, "input": ["dillation=@(x,w)double(perform_convolution(x,strel(w))>0);\n", "Md = dillation(M,2);"]}, {"source": ["Display."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 11, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(Md);"]}, {"source": ["__Exercise 2__\n", "\n", "Test with structing elements of increasing size."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 12, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo2()"]}, {"collapsed": false, "outputs": [], "prompt_number": 13, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}, {"source": ["Errosion\n", "--------\n", "An errosion corresponds to take the maximum value of the image aroung each pixel,\n", "in a region equal to the structuring element.\n", "\n", "\n", "It can be implemented using a convolution with the structuring element\n", "followed by a thresholding."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 14, "cell_type": "code", "language": "python", "metadata": {}, "input": ["errosion=@(x,w)double( perform_convolution(x,strel(w))>=.999 );\n", "Me = errosion(M,2);"]}, {"source": ["Display."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 15, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(Me);"]}, {"source": ["__Exercise 3__\n", "\n", "Test with structing elements of increasing size."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 16, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo3()"]}, {"collapsed": false, "outputs": [], "prompt_number": 17, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}, {"source": ["Opening\n", "-------\n", "An opening smooth the boundary of object (and remove small object) by\n", "performing an errosion and then a dillation.\n", "\n", "\n", "Define a shortcut."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 18, "cell_type": "code", "language": "python", "metadata": {}, "input": ["opening = @(x,w)dillation(errosion(x,w),w);"]}, {"source": ["Perform the opening, here using a very small disk."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [], "prompt_number": 19, "cell_type": "code", "language": "python", "metadata": {}, "input": ["w = 1;\n", "Mo = opening(M,w);"]}, {"source": ["Display."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 20, "cell_type": "code", "language": "python", "metadata": {}, "input": ["clf;\n", "imageplot(Mo);"]}, {"source": ["__Exercise 4__\n", "\n", "Test with structing elements of increasing size."], "metadata": {}, "cell_type": "markdown"}, {"collapsed": false, "outputs": [{"metadata": {}, "png": 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"output_type": "display_data"}], "prompt_number": 21, "cell_type": "code", "language": "python", "metadata": {}, "input": ["exo4()"]}, {"collapsed": false, "outputs": [], "prompt_number": 22, "cell_type": "code", "language": "python", "metadata": {}, "input": ["%% Insert your code here."]}], "metadata": {}}], "nbformat": 3, "metadata": {"kernelspec": {"name": "matlab_kernel", "language": "matlab", "display_name": "Matlab"}, "language_info": {"mimetype": "text/x-matlab", "name": "matlab", "file_extension": ".m", "help_links": [{"url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md", "text": "MetaKernel Magics"}]}}}