Puzzles/Honeycomb.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Honeycomb solver \n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 123,
      "metadata": {},
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "from ortools.sat.python import cp_model as cp\n",
        "import gurobipy as gp\n",
        "from collections import deque\n",
        "from itertools import chain\n",
        "import itertools\n",
        "import math\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.patches import RegularPolygon\n",
        "# THANKS FOR https://www.zhihu.com/question/683403503/answer/15700860878\n",
        "# The formula is : \\delta (n) = n(n - 1) + \\lfloor (n + 1) / 3 \\rfloor\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 132,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "169\n",
            "\t Totally 29 Lines\n",
            "Red: 57 Nodes\n",
            "Blue: 57 Nodes\n",
            "Green: 55 Nodes\n",
            "{(-7, 0, 7): 1, (-7, 3, 4): 2, (-6, 1, 5): 3, (-5, -1, 6): 4, (-4, -3, 7): 5, (-7, 6, 1): 6, (-6, 4, 2): 7, (-5, 2, 3): 8, (-4, 0, 4): 9, (-3, -2, 5): 10, (-2, -4, 6): 11, (-1, -6, 7): 12, (-6, 7, -1): 13, (-5, 5, 0): 14, (-4, 3, 1): 15, (-3, 1, 2): 16, (-2, -1, 3): 17, (-1, -3, 4): 18, (0, -5, 5): 19, (1, -7, 6): 20, (-4, 6, -2): 21, (-3, 4, -1): 22, (-2, 2, 0): 23, (-1, 0, 1): 24, (0, -2, 2): 25, (1, -4, 3): 26, (2, -6, 4): 27, (-3, 7, -4): 28, (-2, 5, -3): 29, (-1, 3, -2): 30, (0, 1, -1): 31, (1, -1, 0): 32, (2, -3, 1): 33, (3, -5, 2): 34, (4, -7, 3): 35, (-1, 6, -5): 36, (0, 4, -4): 37, (1, 2, -3): 38, (2, 0, -2): 39, (3, -2, -1): 40, (4, -4, 0): 41, (5, -6, 1): 42, (0, 7, -7): 43, (1, 5, -6): 44, (2, 3, -5): 45, (3, 1, -4): 46, (4, -1, -3): 47, (5, -3, -2): 48, (6, -5, -1): 49, (7, -7, 0): 50, (3, 4, -7): 51, (4, 2, -6): 52, (5, 0, -5): 53, (6, -2, -4): 54, (7, -4, -3): 55, (6, 1, -7): 56, (7, -1, -6): 57, (-7, 1, 6): 113, (-6, -1, 7): 114, (-7, 4, 3): 115, (-6, 2, 4): 116, (-5, 0, 5): 117, (-4, -2, 6): 118, (-3, -4, 7): 119, (-7, 7, 0): 120, (-6, 5, 1): 121, (-5, 3, 2): 122, (-4, 1, 3): 123, (-3, -1, 4): 124, (-2, -3, 5): 125, (-1, -5, 6): 126, (0, -7, 7): 127, (-5, 6, -1): 128, (-4, 4, 0): 129, (-3, 2, 1): 130, (-2, 0, 2): 131, (-1, -2, 3): 132, (0, -4, 4): 133, (1, -6, 5): 134, (-4, 7, -3): 135, (-3, 5, -2): 136, (-2, 3, -1): 137, (-1, 1, 0): 138, (0, -1, 1): 139, (1, -3, 2): 140, (2, -5, 3): 141, (3, -7, 4): 142, (-2, 6, -4): 143, (-1, 4, -3): 144, (0, 2, -2): 145, (1, 0, -1): 146, (2, -2, 0): 147, (3, -4, 1): 148, (4, -6, 2): 149, (-1, 7, -6): 150, (0, 5, -5): 151, (1, 3, -4): 152, (2, 1, -3): 153, (3, -1, -2): 154, (4, -3, -1): 155, (5, -5, 0): 156, (6, -7, 1): 157, (1, 6, -7): 158, (2, 4, -6): 159, (3, 2, -5): 160, (4, 0, -4): 161, (5, -2, -3): 162, (6, -4, -2): 163, (7, -6, -1): 164, (4, 3, -7): 165, (5, 1, -6): 166, (6, -1, -5): 167, (7, -3, -4): 168, (7, 0, -7): 169, (-7, 2, 5): 58, (-6, 0, 6): 59, (-5, -2, 7): 60, (-7, 5, 2): 61, (-6, 3, 3): 62, (-5, 1, 4): 63, (-4, -1, 5): 64, (-3, -3, 6): 65, (-2, -5, 7): 66, (-6, 6, 0): 67, (-5, 4, 1): 68, (-4, 2, 2): 69, (-3, 0, 3): 70, (-2, -2, 4): 71, (-1, -4, 5): 72, (0, -6, 6): 73, (-5, 7, -2): 74, (-4, 5, -1): 75, (-3, 3, 0): 76, (-2, 1, 1): 77, (-1, -1, 2): 78, (0, -3, 3): 79, (1, -5, 4): 80, (2, -7, 5): 81, (-3, 6, -3): 82, (-2, 4, -2): 83, (-1, 2, -1): 84, (0, 0, 0): 85, (1, -2, 1): 86, (2, -4, 2): 87, (3, -6, 3): 88, (-2, 7, -5): 89, (-1, 5, -4): 90, (0, 3, -3): 91, (1, 1, -2): 92, (2, -1, -1): 93, (3, -3, 0): 94, (4, -5, 1): 95, (5, -7, 2): 96, (0, 6, -6): 97, (1, 4, -5): 98, (2, 2, -4): 99, (3, 0, -3): 100, (4, -2, -2): 101, (5, -4, -1): 102, (6, -6, 0): 103, (2, 5, -7): 104, (3, 3, -6): 105, (4, 1, -5): 106, (5, -1, -4): 107, (6, -3, -3): 108, (7, -5, -2): 109, (5, 2, -7): 110, (6, 0, -6): 111, (7, -2, -5): 112}\n",
            "53\n"
          ]
        },
        {
          "data": {
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REREREZHEmFwiIiIiIiIiIiKJMblEREREREREREQSY3KJiIiIiIiIiIgkxuQSERERERERERFJjMklIiIiIiIiIiKSGJNLREREREREREQkMSaXiIiIiIiIiIhIYkwuERERERERERGRxJhcIiIiIiIiIiIiiTG5REREREREREREEmNyiYiIiIiIiIiIJMbkEhERERERERERSYzJJSIiIiIiIiIikhiTS0REREREREREJDEml4iIiIiIiIiISGJMLhERERERERERkcSYXCIiIiIiIiIiIokxuURERERERERERBJjcomIiIiIiIiIiCTG5BIREREREREREUmMySUiIiIiIiIiIpIYk0tERERERERERCQxJpeIiIiIiIiIiEhiTC4REREREREREZHEmFwiIiIiIiIiIiKJMblEREREREREREQSY3KJiIiIiIiIiIgkxuQSERERERERERFJjMklIiIiIiIiIiKSGJNLREREREREREQkMSaXiIiIiIiIiIhIYkwuERERERERERGRxJhcIiIiIiIiIiIiiTG5REREREREREREEmNyiYgKLUEQpB1CgSEIAs/Xb+C5+j08XznHc/V7eL5yjufq9/B8ERH9HiaXiKjQSUlJgaenJzQ1NeHt7Y2UlBRphyTTHj16hL59+6J379548OCBtMORaampqfDz80OtWrXg5uaG5ORkaYck0549e4aBgwaiW7euuH37trTDkWnp6elYuXIlatWqBUdHRyQmJko7JJn26tUrDB8+HJ06dURQUJC0w5Fp6enpWLduHbS0tGBjY4P4+HhphyTT3r17hzFjxqBt27a4fPmytMMhIiowmFwiokJDEAQcOXIETZo0homJCWpoVoORkRGaNWuKY8eOSTs8mRMREYGFCxeiefPmePnqBd6+fYMWLVpg7ty5CA8Pl3Z4MufkyZNo3rw59PX1Ub1mVZibm6Nx48Y4ePAg73D/R1RUFAwNDdGkSRM8fPAAn798Rps2baCtrY3Pnz9LOzyZc+7cObRq1RJz585FtRpVYG9vj4YNG2LPnj28tv4jNjYWpqamaNSoEYKCriMqJgrt27fH1KlT8eHDB2mHJ3MuXbqEdu3aQVtbG1WqVYKrqysaNGiA7du389r6j/j4eFhbW6NBgwa4cPECkpIT0aVLF0yYMAHBwcHSDo+ISPYJORAdHS0AEKKjo3PSnIgo3z1+/Fjo26+vAEDo3KWjcOz0QeF1yBPh6MkDQsdO7QUAwoCBA4SnT59KO1SpS01NFZYtWyaULVtWKFmypGBmaSw8fX1PePr6nmBhYyKoqZUSSpcuLfj6+gopKSnSDlfqnj9/Lvz992ABgNCuQ1vhyIl9wuuQJ8KJs4eFrt07CwCEXr16CQ8fPpR2qFKXlpYmrF69WtDQ0BBUVVUFI1MD4cnLu8Lztw8EW0dLQb20uqCmpia4u7sLycnJ0g5X6l6/fi2MGDFCACC0at1S2H9kl/A65Ilw5uIxoVefngIAoXv37sKdO3ekHarUpaenCxs2bBAqVaokKKsoC3qLFgiPXtwWXrx7KCxxsRPKlisrlChRQnBychISExOlHa7UvXv3Thg3bpwAQGjWvImw+8B24XXIE+H85ZNCvwF9BABCp04dhRs3bkg7VKkTiUTCtm3bhKpVqwpKSkrCfF0d4cGzm8LL948ENy8nQUOjvKCioiLY2toK8fHx0g6XiChf/U4uiMklIirQIiIiBD09PUFeXl6oUbO6sGrdMuFV8GPhdcgT8c+r4MeC/2pfoXqN6oKCgoJgYGAgREZGSjt0qTh16pTQuHFjQU5OThgzbqRw/U5gpnP1OuSJcOPeZWH8pLGCnJyc0LBhQ+H48ePSDlsqoqOjBWNjY6F48eJCtWpVhWUrfbK8ttZs9BdqaWkK8vLywoIFC4SvX79KO3SpuHDhgtCiRXMBgDBi1FDh6s0LP1xbtx5cEaZMmyjIy8sLdevWEQ4fPiyIRCJph57vYmNjBXNzc0FJSUmoVLmS4L3U/Ydr63XIE2Hj1jVCnbq1BTk5OWHWrFnCly9fpB26VFy+fFlo06aNAEAYPHSgEHj9zA/n6u6j68KMWVMFBQUFoVYtTWHfvn1F8tqKj48XbGxsBBUVFaFCBQ3B3dtZePn+0Q/na1vARqFBw/qCnJycMG3aNOHjx4/SDl0qgoKChE6dOgoAhP4D+woXrpz64Vzde3JD0JmnLSgqKgrVq1cXdu7cWSSvLSIqmn4nFyQnCL/uExsTEwN1dXVER0dDTU0tT3pQERH9jrS0NKxZswZWVlZISkrCAr05mDZzCpSUFH+6TnJSMtat3QR/v1VQVVXFkiVLMHPmTMjLy+dj5NLx6tUrGBoa4uDBg2jTrjWs7czQpGnjbNd5/OgJHGxdcP1qEAYPHgQvL2/UrVs3nyKWnvT0dGzcuBHm5uaIjYvF3PmzoD17OpRVlH+6TkpKCjZv2IalPitQvHhx2NvbQ0dHBwoKCvkYuXS8e/cOxsbG2L17N1q0bA5rOzO0aNU823WePX0ORztXXA68gr79+sLH2wcNGzbMp4ilRyQSYevWrTA1NUVkZARm6cyAznxtqKqq/nSd1NRUbNu8E75eywDIwcbGBvPnz4ei4s/f6wqLkJAQmJiYYPv27WjStDGs7MzQtl3rbNd5/eoNlti54tzZC+jZsyd8fHzQrFmzfIpYegRBQEBAABYvXozPnz9jxqypmLdQByVLlvjpOmlpaQjYsQde7n5ITUmFlZUV9PT0oKSklI+RS8fHjx9hbm6OjRs3okGj+rCyMUPHzu2zXefd2/dwdnDHyROn0aVLZ/j6+qFVq1b5FDERkXT8Ti6IySUiKnDOnj0LfX09PHjwEKPGjoCxiT40KmjkeP3Pn77A3cUL+/YcRPPmzeDr64fu3bvnYcTSExsbiyVLlsDb2xvly5eDqaURBv09AHJycjlaXxAEHDt6Ei6O7vj8+Qv09PRgaWkJdXX1PI5cOi5dugQ9PT3cvn0bQ4f/jcVmi1C5SqUcrx8WFg4vN1/s2rkXjRo1go+PD3r37p2HEUtPfHw8XF1d4e7uDjV1NZiYLcLQEX+jWLGclXMUBAFnTp3DEntXhASHYv78+bC1tUWZMmXyOHLpuH79OhbqLsSNoBsY9Hd/mFoYoWq1qjlePyIiEj6eS7F9SwDq1KkNb28fDBw4MA8jlp7ExER4eHjAxcUFqqoqMDI1wKgxw3N8bQHAuTMX4GTvhjdv3mL27NlwcHBA+fLl8zBq6bl16xb09HRx+fIV9O3XG2ZWxqipWSPH60dHRcPXezm2bNwOTU1NeHp6YsiQITn+nChIkpOT4ePjA0dHRxRXLI5FxroYO37Ub90IuBR4BY62Lnjx/CWmT58OJycnVKxYMQ+jJiKSHiaXiKhQev36NYyNjbFv3z60at0SVnZmaN6iqcTbu3v7HuxtnHH3zj2MGjUK7u7u0NTUzL2ApUgkEmHz5s0wMzNDVHQUdOZqY/bcGVBRUZFoe0mJSVi7egNWLF+DUiVLwcnJCdOmTSs0vb7ev3+PxYsXIyAgAM1bNIWVnRlatW4p8fYePngEextn3Ay6haFDh8LDwwN16tTJxYilRxAEbN++HSYmJggPD4e2zjTMmT8LJUr8vIdEdpKTU7Bx3WYs810JZWVlODg4YNasWYWm11doaCjMzMywZcsWNGrcENZ2ZmjXoa3E23v65DkcbJxw9cp19B/QH95e3mjQoEEuRiw9giBgz549MDIywsePHzF95mTM15uLUqVKSrS9lJQUbNm0HUu9/VGsmDxsbW0xb948FC9ePJcjl45Pnz6Je9/UrVcHlram6NK1k8Tbe/H8JZbYu+Li+Uvo1asXfHx80KRJk1yMWHoEQcDBgwdhaGiI9+/fY/K0CdDVnwf10pLdKElLS8P2rQHw8VyG9LR0WFtbQ1dXt0j0KCSiooXJJSIqVGJjY+Hs7AwvLy+ULVcGi80MMWTYoFy5qyoSiXBo/xG4OnshKjIKxsbGMDU1lfiLsiy4cuUK9PT0cPPmTfw9dBBMLAxRpUrlXNn2p4+f4ebsiQP7DqNly5bw9fVF165dc2Xb0pCQkAA3Nze4ubmhVKmSMDZbhOEjh/xWD4mfEQQB/xw5DmcHd4SHf4W+vj4sLCwK9OfojRs3oKeni6tXr6H/wL4wszRG9RrVcmXbYV/C4O7qg7279qNJk8bw8fHFX3/9lSvbloakpCR4eXnByckJysrKMFysi9HjRuZKQlYQBJw8fhpODu74+OEjFixYABsbG5QuXfrPA5eSO3fuQE9PD4GBgejd9y+YWRqjlpZmrmz769cIeLn7Yee2Xahfvz58fHzQr1+/XNm2NCQnJ8PPzw8ODg6QV5CHgdFCjJ84JlcSsoIg4NzZC1hi54r374IxZ84c2NnZoVy5crkQuXQ8fPgQ+vr6OHPmDLr16AJLG1PUqVs7V7YdFRkFX6/l2Lp5B7S0asHT0wuDBw8ulL2+iKhoYnKJiAqFH+qTzJkJnXkzs61PIqn4+HisXL4Ga1dtRPny5eHi4oIJEybkSpIhv0hSn0RSt2/dgYONM+7dfYCxY8fCzc0NNWrkfBiGtH2rT2JsbIwvX77kqD6JpBITE7Fm5Xqs9F8LdTV1ODs7Y+rUqQXq2pKkPomk7t97CAcbJ9y6eQfDhw+Hh4cHtLS08mRfeUEQBOzbtw9GRoYICQnF1BmTsFBvLtTUc///p+SkZKxfuxnL/VZCVVUVjo6O0NbWLlA9Cr98+QILCwusW7cOderWhqWNKbp275wn+/pvHTlPTy/Uq1cvT/aVFwRBwJEjR7Bo0SK8efMGk6aMh96i+ShdpnSu7+v7OnIKCgqwt7fHnDlzClSPwq9fv8LGxgYrVqxATc0asLAxQc+/uudJ4uf5sxdwsHXB5cAr6NO3D3y8fdCoUaNc3w8RUX5jcomICrxr165BV09X4vokkgp+HwJnR3cc/+ckOnRoD19fP7Rr1y7P9/snEhIS4OHhAVdXV4nrk0hCJBJh/95DcHf2QkxMLBYvXozFixfLfK+vTPVJ+veBmaXRb9UnkdSHDx/husQThw8eRevWreHr64vOnfPmS3RuSUpKgo+PD5YsWYLiisVhuFgPY8ePyvPkhSAIOHzwH7g6eeBreAQMDQ1hZmaGUqVK5el+/9S9e/egr6+P8+fP469e3WFubQKt2rXyfL+fP32Bh6s39u4+gObNm8HHxxc9evTI8/3+iZSUFCxduhT29vaQkwP0DRdiwuSxeT5k7b915HR1dWFlZSXzdeQePXoEfQN9nD51Gl26dYKljSnq1c/7CRb+W0fO29sbffr0yfP9/onU1FSsXLkSNjY2SEtLw0KDeZgybUKeD1nLqo6cjY0NypYtm6f7JSLKS7+TCyo4t02JqEgIDQ3F5MmT0bFjRyQkxGPnns1YusI7XxJLAFC9RjX4r/bF9l2bEBUThfbt22PatGn4+PFjvuz/dwiCgF27dqFhw4ZwdHTEpCnjcCbwOMaMG5kvvWKKFSuGkaOH4fTFY5iuPQUuLi5o0KABduzYgRzct8h3nz59wowZM9C2bVuEfw3Hlp3rsXKtX74klgCgSpXK8F3ugV37tyElNQldunTBhAkTEBwcnC/7/x2CIODAgQNo3LgxrKysMHrcCJy9eAwTJo3Nl14xcnJyGDJsEE6dPwqdedrw9s7oYbJp0yaIRKI83//vCgsLw5w5c9CqVSsEB7/H+s2rsHbTynxJLAFAxUoV4O7tjP2HA1BMvhh69uyJUaNG4c2bN/my/98hCAKOHj2KJk0aY/HixRg6fDDOXjqOqTMm5UstJDk5OQwc3A8nzx2BrsE8+K/wR926dbF27Vqkp6fn+f5/V0REBHR1ddG8eXO8fPkCq9cvx6Zta/MlsQQAGhrl4ezugEPH9kC1pAr69u2LoUOH4uXLl/my/9916tQptGjRAnp6eug3oDfOBB6D9uxp+VILSU5ODr37/oXjZw7D2NQA69evR926deHv74+0tLQ83z8RkbSx5xIRyYTExERxfRIVFRUYmehh1NgRUh3ekZ6ejoAde+Dp5ovUlFSYm5vDwMAAyso/n5I+v2TUJ9FFYOClXK9PIqn374Lh5OCOk8dPoXPnTvD19UPr1nkzLO935GV9EkmJRCLs3X0AHi7eiIuLh6mpKYyMjPJkyOfvylSfpHsXWNrmXn0SSYWGhMLVyRNHDh1Dm7ZtsNRvKTp06CDVmICMHhLLly+Hra0tBEEE3UXzMXnqBKkWjBaJRDh04ChcnTwRFRkFIyMjmJqaomRJyYpi56YnT57AYJEBThw/gU6dO8DS1gwNGkp3WJqs1pFLS0vD6tWrYWVlhZSUFCzQm4OpMyZDSUl6BaO/ryMXFhYOAwMDmakj9/LlSxgaLsKhQ4fRtn0bWNuZoXET6Q5LC/sSBg9XH+zZtR+NGzeCr69fga4jR0RFE3suEVGB8W12oEaNGsLW1hYTJo/FmcBjGDthtNTrhsjLy2PCpLE4e/EYRo8bAWtrazRq1Aj79++XWs+cL1++QFtbG61bt8anz5+wadtarF6/XOqJJQCoUbM6Vq71w5ad6xH+NRxt27bF9OnT8enTJ6nEIwgCDh06hMaNG8PMzAwjRg3F2YvHMHnqBKnXDSlWrBhGjx2B0xePYfK0CXB0dETDhg0REBAgtWvr69evmDdvHpo3b443b19j7aYV2LB1tdQTSwBQtVpV+Pl7YefeLUhMTEDHjh0xefJkhIaGSi2m48ePo1mzpjA0NMSgIf1xJvA4ZmhPlfpMZMWKFcOwEX/j9IWjmDVnOjw8PFC/fn1s3bpVar2+IiMjoa+vj2bNmuHJk8dYuXYptuxcL/XEEgBUqlwRXn5u2HNwO0RCGrp164axY8fi3bt3UovpzJkzaNmyBRYsWIBefXrgzMV/MHvuTKkmloCMnjmD/h6AUxeOYr6uDvyW+qFevXpYv3691K6tmJgYLF68GI0aNcKtW7ewdIUXdu7ZLPXEEgBoVNCAq+cS7D+yC0rKiujVqxdGjBiB169fSzs0IqI8wZ5LRCQ19+7dg56eHi5cuJCv9Ukk9erlazjauuDC+UD89ddf8PHxQdOmTfNl35nqkxSTg/6iBflSn0RSaWlp2Ll9N7zc/ZCelg5LS0vo6elBSUkpX/b/3/okVrZmqFuvTr7sWxJv37yDs6M7Tp04gy5dOsPX1w+tWrXKl31Lqz6JpNLT07EnYB88XH2RmJgIMzMzGBoaQkVFJV/2/+zZMxgsMsCxf46hQ8d2sLIzQ8NGDfJl35IIfh8ClyUeOHb0RL7XkUtPT8eaNWtgaWmJpKQkzFuogxnaU6CknD/vA79LJBLhwL5DcHOSTh25V69ewcjICAcOHECbtq1gZWeOps0a58u+JfHhw0e4OXnh0IEj+V5HTiQSYePGjTAzM0NMbAzmzp+FWTozoKwi/Z7FWflvHblFixbB3Nxc5uvIERGx5xIRybSwsDDo6OigVatWCAkNxoYtq/O1PomkatfRwoatq7Fu00q8ffsGLVq0wNy5cxEeHp5n+/w2O1Cm+iSBx/KtPomkFBQUMGnKeJy9eAwjRw+Dubk5GjdujIMHD+Zpz5yIiAgsXLhQXJ9kzQZ/bNq2VqYTSwCgWasmVq1bhk3b1+Lzl89o06YNtLW18fnz5zzd78mTJ6VWn0RS8vLyGDthNM4EHsPEyeNgb2+Phg0bYs+ePXl6bUVFRcHQ0BBNmjTBwwcPsHyVL7bt2ijTiSUgo47c8lU+2LF7E6JjotG+fXtMnToVHz58yNP9njt3Dq1atcTcuXPRo1c3nLn4D+YumCWziSUgo9fXiFE/1pHbvn17nl5bsbGxMDU1RaNGjXA96Bp8l3sgYN9WmU4sARl15HyWued7HblLly6hbdu2mDlzJjp0aofTF/7BQv15MptYAjLXkZszfxZ8fLxluo4cEZEk2HOJiPJNSkoKli9fDjs7OwiCCHqLFmDS1PEynST5mZSUFGzZtB1+Xv6Ql5eHnZ0d5s6dm6vH8uTJE+gb6OPkiZMyU59EUi+ev4SjnQsCL1xGr1694Ovri8aNc++LU1paGlatWgVra2ukpKRgof5cTJk+SerDSCSRlpaG7VsC4O25FIJIgJWVFXR1dXM14fPixQsYGi7C4cNH0K5DW1jZmsrEMBJJvH79Bk72bjh7+jy6d+8OHx8ftGjRIte2n56ejnXr1sHS0hLx8fGYu3A2tGdNk+kkyc+kp6dj14698HT3RXJSMiwsLHK9jtybN29gZGSEffv2oWWrFrC2N0fzFvnTwzO3vX8XDGdHd5w4dgqdOnWEr68f2rRpk2vbF4lE2Lx5M8zMzBAVFYnZc7WhM29mvvXCy03/rSNnYmICY2PjXK0j9/79e5iYmGDnzp1o1rwJrOzM0bpNy1zbfn4KDf0A1yUe4jpyfr5+6Nixo7TDIiL6we/kgphcIqJ8cezYMRgY6OPFi5cYN3E0DIx0Ua5cwZ+eNzz8K7zd/bBz+240aNAA3t7e6Nev3x9tMzIyEnZ2dli2bBmqVqsCc6vF6NOvF+Tk5HIpaukQBAFnz5zHEjtXBL8Pwdy5c2FnZ/fH0zSfPn0a+vr6ePz4MUaPHQFDE31oaJTPpailJzIyEr6ey7Fty05oadWCl5c3Bg0a9EfXQUxMDBwdHeHj44MKFTRgZmWMAYP6FfhrCwAunAuEo50LXr96A21tbSxZsgQaGhp/ts0LF6Cnp4t79+5j+MghMDZdhEqVK+ZSxNITEx0DPx9/bN6wDdWrV4OHhyeGDx/+R9dBXFwcnJ2d4enpiTJly2Cx2SIMHT64UFxbVy5fg4ONM549fY5p06bB2dkZlSpV+rNtXrkCPT093Lx5E4OHDoSJuSGqVq2SSxFLT2xsHPyXrsKGtZtRsWJFuLu7Y8yYMX90HSQkJMDNzQ1ubm4oWbIEjM0WYcSoofkyK2peC7p+Ew42znj08DEmTpwIFxcXVKtWTdphERGJMblERDLjx/ok5mjYqL60w8p1jx4+hoOtC4Ku3cDgwYPg6ZkxdfrvSEtLw5o1a2BlZYWkpCTM19XBdO2pBbL3TXaSk1OwecNWLPVZAUVFRdjb20NHR+e3i2y/evUKhoaGOHjwYIGoTyKpZ0+fw9HWBZcvXUXffn3h4+2Dhg0b/tY20tPTsXHjRpibmyM2LhZz5mnLdH0SSaWmpmLb5p3w9VoGQA42NjaYP3/+b/f6evv2LRYvXozdu3ejectmsLY1Q8vWLfIkZml69fI1lti54vy5i+jZsyd8fHzQrFmz39qGSCTC1q1bYWpqisjICMzSmQGd+doyMfNhbvpWR87bYylSU1JhaWkJfX39364jFxISAhMTE2zfvh2NmzSClZ0Z2rXPvd5QsiI36sgJgoCAgAAsXrwYnz9/xnTtKZi3UAelSkl/5sPclJ6ejj279sPT1QcJCflfR46IKDtMLhGR1EVFRcHe3h5Lly5F5cqVYGZljH4D+hSKu9g/IwgCjh09CRdHd3z+/AV6enqwtLSEurr6L9c9e/Ys9PX18ODBQ4wcMxzGJvqoULFCPkQtPWFh4fB09cHugH1o1KgRfHx80Lt371+uFxsbiyVLlsDb2xvly5eDqaURBv09oNBfW6dPnsUSe1eEhnzA/PnzYWtrizJlyvxy3UuXLkFPTw+3b9/G0OF/Y7HZIlSu8me9LmRdREQkvD38sGPrLtSpUxve3j4YOHDgL9eLj4+Hi4sLPDw8oKauBhOzRRg64u9C0UMiO+fOXMASO1e8ffsOs2bNgqOjI8qX/3Xvv2vXrkFXTxc3gm5g4OD+MLUwQrXqVfMhYumJioyCn7c/tmzaDk1NTXh6emLIkCG/fP9JTEyEh4cHXFxcoKqqAkMTfYwaM1zqs6LmtcCLl+Fo64KXL15h+vTpcHJyQsWKv+79d+vWLejp6eLy5Svo2683zKyMUVOzRj5ELD0xMbFY7rsSG9dvQZUqVeDu7o5Ro0YV6s82IpJ9TC4RkdR8q09iYWGBhISEAl2fRFJJiUlYu3oDVixfg1IlS2HJkiWYPn16ll8iXr9+DWNj40JRn0RSDx88gr2NM24G3cLQoUPh4eGBOnV+LMCdqT5JdBR05mpj9twZRerubnJyCjas3YTlfqugrKwMBwcHzJo1K8teX+/fv8fixYsREBBQ4OuTSOrJ42dwsHHCtatB6D+gP7y9vNGgwY8FuAVBwPbt22FiYoLw8HDMnD0NcxfMyrdZwmTBf+vI2draYt68eVnWkQsNDYWZmRm2bNmCho0awNrODO075s8MdLLiv3XkfHx80KRJkx/aCYKAPXv2wMjICB8/fsS0GZMxX28O1NSKzixh39eRE6WLYG1t/dM6cp8+fYK5uTk2btyIuvXqwNLWFF26dpJC1NLzfR25bt26wdfXN1fryBER/Q4ml4hIKgprfRJJffzwCW7OXji4/zBatmwJX19fdO3aFUDhrk8iCUEQcPTwMbg4eiA8/CsMDAxgYWEhnqa5sNYnkdSXz1/g4eaLPQH70LRpE/j4+OKvv/4CkLk+SalSJWFkalBo6pNIQhAEnDh2Cs4O7vj48RMWLlwIa2trlC5dGgBw48YN6Onp4urVa+g3oA/MLI1Ro2Z16QYtRd/Xkatfvz58fHzEdeSSkpLg5eUFJycnKCkpwXCxHsaMH1noe9/8zPd15N6/CxbXkStXrhwA4M6dO9DT00NgYCB69ekJc6vFqKWlKd2gpSi7OnLJycnw8/ODg4MD5BXkoW+4ABMmjf3t4dKFycXzl+Bo54JXL1/nWh05IqLfxeQSEeWrt2/fwtjYGHv27EHzls1gY2eOFq2aSzssmXHr5h042Djh/r2HGDNmDDp06AB3d/dCXZ9EUomJiVi9Yj1WrVgLdTV1GBsb49atW9ixYweaNG0MKzsztG3XWtphyox7dx/AwcYZt2/dwbBhw9CjRw94enri8+fPmDFrKuYt1EHJkkWn9012kpOSsW7tJvj7rYKqqiqMjY3x8OFDbNmyBQ0a1oeVrRk6dm4v7TBlxuNHT2Bv44ygazcwaNAg9OvXD15enggJCcXUGZOwUG8u1NT5PyGQ0etr0/qMOnLFixeHkZERXr16hQ0bNqB2HS1Y2piiW48u0g5TZnxfR65Pnz4YOnQofHx88ObNG0yaMh56i+ajdJnS0g5TJvy3jpy1tTUWLFiQq7OHEhFlh8klIspXZcqUgaKSYpGpTyIJkUiE/XsPwXWJByIiItF/YN8iUZ9EUh8+fITrEk8cPngUJUqowsrOHCNHDyuyPSSyIwgCDh04ChdHd3z5EoY+fXsVifokkvr86QvcXbywb89BKKsow8LaBGPHjyrSPSR+5lsdOScHV3wI/Yhu3bvA2t4cWrVrSTs0mRQWFg4vN1/s2rkXiorFYWJuhIlTxmU5tLCoE9eRs3PF+/fBaN+xPewcLVCvfl1phyaTvq8jp6+vD09PT2mHRERFBJNLRJSvVFVVYWxqgGkzJ0s7FJm3bs1GuDh64MW7h9IOpUBo3qgdWrVqjg1b10g7FJm3fWsArMxs8Sr4ibRDKRDateyKWlqaCNi7RdqhyLx9ew7ASN8M95/eZE+4HOjeqQ/KlC6NA//slnYoMu+fIyewYI4+Aq+fRdWqlaUdjswb3H8Eenb/C8uWLZN2KERURPxOLojdC4iIiIiIiIiISGJMLhERERERERERkcSYXCIiIiIiIiIiIokxuURERERERERERBJjcomIiIiIiIiIiCTG5BIREREREREREUmMySUiIiIiIiIiIpIYk0tERERERERERCQxJpeIiIiIiIiIiEhiTC4REREREREREZHEFKQdABERACQmJuL61Rt4+OARHj54jIcPHuFD6EcAgK7BfOgbLvjpup8+fsapk2dw7UoQHj98gk+fPgMANCqUR4tWzTFuwmh06tzhlzGEhYVj9Yp1OHv6PD6EfoSysjLq1q+DkaOGYsz4UZCTk8udg80Hf3I+r18NQuDFK3hw/yHevwtGZGQUEuIToK6uhrr16qBv/94YN2E0lFWU8+tw8pRWtYY5btuhYzts370pR20tTG2xY2sAAKBqtSoIvHZGovjymzSvHWMDM+zdfeCXMT5/+wAKCrL/L0xkZCROnzyHK5eu4dHDxwgN+YD09DSULVsWTZs3wYhRQ9FvQJ9stxF48TICtu/B3Tv3EB7+FXKQQ4WKGmjZqgXGTxyN9h3b5dPR5J8/Oeag6zexZeM23LpxBxEREShVqhQaNKqP0WNHYsiwQfl4FH/uT16LPp7L4Oe9/Jf7OBt4HJq1av50+cMHj7Bu9SZcvxqEiIgIqJdWR8uWzTFlxqQcfa7KshXL1sDdxUv8++uQJz+0efjgEc6cOo+HDx7hzeu3iPgagbi4eJQsWQK162ihx1/dMHHyOJQuUzofIycikk2y/58ZERUJ9+48wIwpOr+93ocPH9G1fS8IgiB+TkVFBYIgICQ4FCHBoThy8B+MHjsCTm72kJeXz3I7D+4/wrSJ2oiMjAIAlCihivj4eNwMuoWbQbdw7OhJrN6wHIqKihIdX36T9HwCwOqV63HuzAXx76qqqlBUVMTXrxH4ejUI164GYcO6zdiwdTW0tGrlVshSU16jfLbL01JTERUVDQBo1rxJjrZ59fJ17Ny2649jkwZZuHaUlJRQSq3UT5cXlERv+5bdkJaWJv5dSUkJCgrF8enTZ3z69BmnTpxB955d4b/aFyoqKpnWFQQBlmZ24gQlACgrZyTlgt+HIPh9CA4dOIIZs6bC0sY0fw4oj/3pMbs6eWKV/1rx72rqaoiJicXlwKu4HHgV/xw5jmUrvQtEYhL4s9fiN8WLF4d6afWfLs/uXARs3w0rc3vxNVxKrRTCw77i5IkzOHnizC8TXLLs9as3OUq+7d65D1s2bRf/rqSkBGVlJURFRePWzTu4dfMONqzdjNUblqNV65Z5GTIRkcwrGJ+uRFQkqKuro3HThmjSpBEaN20ERzsXhH0Jz3YdUboIgiCgU5cOGDFqKDp36YSKlSpAJBLh1cvX8HD1wakTZ7A7YB8qVqqARcZ6P2wjJiYW2tPmIDIyCrXraMHT1xXNmjdBSkoKdm7fjSV2rrh44RIcbJ3h4GSTV4ef6yQ5nwDQuWtHdOveBW3atUJNzZooWbIEgIxeGIf2H4WrkyeC34dgrvZCHDt9CMWKFewR1kF3ArNdvnbVBjg5uAEAxowf9cvtJSYmwnyxNRQUFNCgUX08uPcwV+LMT9K+dgYPGQB3b+dcPSZpSEtLQ/MWzTByzDB0694FNWpWBwCEBIdime8K7Nq5FxfOBcLCxAZefm6Z1t2za784yTJgUD8YmeijlpYmgIwvxq5Onjh14gzWr9mEtu1a/7IHVEHwJ8e8fWuAOLE0eOhAmFkYo3KVSkhOTsGRQ//AxsIBJ4+fhssSjwKVjJP0tfhNq9YtsGPP5t/e7+1bd2BpZof09HT07dcLNg6WqFylEiIjI+Hh6osdWwPg570cdevVxqC/B/z29qVJJBLBxNACycnJaNW6BW7fuvvTts1bNkW16sZo07YVatfRgpq6GgAgPj4eJ46dgrODO75+jYDOzIU4c/EY1LJJihMRFXZMLhGRTGjbvjXuPLqW6Tk3Z6+ftP4/NXU1HDq2B02aNs70fLFixVC3Xh2sXLsUMybr4ML5QGxYuxnzF86BkrJSprZrV61H2JdwKCsrY/3mVaheoxoAQFFREVOmTURcXDw8XLyxc9tuTNeeUiB660h6PgFghvbULJ8vU6YMps6YBEVFRViY2uDF81e4fesu2rRt9cfxyrJdO/cCANq0aw2t2r/+23u4+uDdu/eYr6uDTx8/F7jkEq+d3LMtYCM6dm7/w/PVqleFi4cj5BUUsGNrAA7sOwwjUwNUqVJZ3Gb/noMAgJqaNeC73CNTDxOt2rWwbKU3+vQYhPfvgnH0yPFCkVyS9JjT0tLg47kMANCkaSP4LHUXJy6VlBQxcvQwJCUlwcrMDps3bMOUaRPFiT5Z9ievxT/lssQT6enpqN+gHpau9Ebx4sUBZLyWl7jYIjQ4FBcvXIKrkyf6D+z7017BsmjT+q24dfMOhg7/GzU1a2SbXBoxaliWz5coUQIjRg2DhoYGpk7Uxtfwrzh7+jyGjfg7b4ImIioACvbtZiIqNCT9x1RNrdQPiaXvycnJYfS4EQCA+PgEvHz56oc2+/79QjN46EBxYul7U6dPRIkSqkhPT8fBfUckijO/5eU/+i1aNRc//vTxU57tRxbcunkHL19kXDNjc9Br6c6tu9i0fitqaWlige7cvA4vT/DayT1ZJZa+N2bcSPHj/yYhv3wJAwA0bNQgy6FLxYsXR8NGDQAACfEJfxqqTJD0mB/ef4TwsIzePDNnT8+yR9y4CaOhpq6GtLQ0HNh3KC/Cz3XSSti8fxeMm0G3AACz5kwXJ5a+N3fBLAAZvfCCrt3M1/j+RPD7EHi6+aJMmdKwtP3zHmxF7T2NiCg7TC4RUaGnpPT/nkrp6aJMy16/eiMukNqjZ9cs1y9RogTatGsNALh08XIeRVlw3Aj6/xeJGjVrSDGSvLdrxx4AGbVGBg7ul23b5OQUmBhZQhAEOLna/dBDjorWtZMT2b03fUt0P3n8NFPdpm9SU1Px5PFTAEDTZjmrBSbrJD3m0NAP4sd169XOctvy8vKoVUsTABB48UpuhVwoXQr8//np1iPrz8U27VqLh70GFqDPRbPFVkhISICFjQnKlSv7x9vjexoR0f8xuUREhd61q0EAAEXF4uL6Hd88e/pC/Lhe/bo/3Ub9f5e9ePFjz6eiICkxCW9ev8XypavE9YfatW+T4wLXBVF8fDz+OXIcAPD30IE/FFz+r6U+/nj54hXGjBtZKGfwkpQk186VS9fwV9f+aFC7OZo1aIP+vYbA3sYJb16/zaeo88f1f9+bAKBBw3qZlk2aMh4A8O7te+jNN8LbN+/Ey16/eoOFcwzw/l0watasgRmzsh6OWNDkxjH/N0mXaZkoHQDw/NmLn7YpbF48f4n+vf5Gozot0aRea/TqNgBmxlZ49PDxT9d5/u/nYrny5VC+fLks28jLy0OrtpZ4HwXBzm27cOXSNXTu2vGnw91yIjk5BSHBodi8YRsMdTN6P9XUrIFefXrmUqRERAUTay4RUaEW/D4E27dkFIgd9PcAlCpVMtPyL5+/iB9XrFTxp9v5tiwuNg7x8fEoUaJEHkQrW8K+hKF9q25ZLuvVpyfcvZzyOaL8deTgP4j/d+jN2PGjs2376OFjrF6xDuU1ysPM0jg/wpNpf3rtfPz4CfLy8ihZsiTi4uLw/NkLPH/2Atu37ISlrZk4CVGQxUTHYMXy1QAyauv8t55Xrz49YWlrCjcnTxw7egLHjp4Qz5yWlJQENXU1TJwyDobGej+8rxVUkh5ztWpVxY+fP3uBps1+HCqdkpIiTlbFxsQiISEBqqqqeXxE0hcREYmoqGioqZVCXFw83rx+izev32LXzr2Yt3A2DBfr/7DO538/FytVqpDttitVqoD79/7fXpZ9+vgZzks8oKysjCUudhJto0Ht5khJTvnh+dZtW8FnmTuUlArGbLJERHmFPZeIqNBKSkzC/Dn6SExMRNmyZbDYzPCHNnHx8eLHKirKP93W98vi4+J/2q4wKSYvj/Ia5VFeo3ym4TsDB/eHqYURSpcpLb3g8kHAv0PiGjZqkOWX1W/S0tJgYmiJtLQ02Nibi2cTKsokvXYaN2kEW0dLBF47jaev7+HOo2u4//QG/Ff7ombNGkhJSYW1uT2OHT2ZT0eSN0QiERbpmeDL5zAoKSnB1sEqy3YztKfCf40fyv3beyQpKQlJSUkAgNSUVCTEJyA2Ni7f4s4Pkhxz46aNUF6jPABglf/aLIfUbd6wDXHfrRdXyM7bf2nWqglTCyOcvvgPnry6i9sPr+Hh81vYtG0tmjRrDEEQsNxvFdau2vDDuvH/fi4q/6K35rflBeEz0cLUBrExsdBbNF/iYu4a/76nfZ+U7NipPaxszVC1apXcCpWIqMBicomICqW0tDToLzDCw/uPULx4cXgvdUfFX9yFpczKlSuLoDuBCLoTiMcv7+By0DnM19XBmVPnMLDPMOzYukvaIeaZ589e4O6d+wB+Xch75fI1ePzoCf7q3aPATcmdVyS9dqbNnIwp0yaiarWq4mLGKioq6D+wL/Yd2SmuyePk4ApBEPLteHKbvbUTzp4+DwCwW2KFho3q/9AmMTERC+caQHvqXFSpWhmbtq/FzftXcPP+FWzavhZ16tXG/r2HMHzwGDx5/CyfjyBvSHrMCgoKWKifUUD/5YtX0J46Fw8fPEJKSgrCvoRh9Yp1cHfxzlSYWi6Lot+FybARf2P23JnQ0qolPm5FRUV07d4Zu/dtQ7PmTQEAvl7LEBMTK81Q89yBvYdw7swFNGrcEDNnT5N4O4HXziDoTiAePr+FoLuXYG61GI8fPcXwwWPg7e6XewETERVQhfuTlYiKpPT0dBgsNMbJE2egoKAA76Xu6Nq9c5ZtS343vC0xMemn2/x+WYmShX9I3H/JycmhcpVKMFysD++lbkhNTYWVuZ24uG5h863XkpKSUrZTS794/hLLfFegRAlV2DtZ51d4BUpuXTtlypTBvAWzAQChIR+yrRkjy5wc3LB54zYAgKWtaaYZ477n7OiOo4ePQ6t2LezauxVdu3VG2bJlULZsGXTt1hkBe7aglpYmIiIiYWPpkJ+HkGf+5JgnT52AWTozAAAXL1zCkAGj0ECrOdq36gaXJR6oWq0KZs+dIW6vXoR7GCopK8HIVB9AxiyqVy5dzbT827DvpMTEbLfzbbksfyaGhYXDwdYZ8vLycHKzz3IWQkmUL18O2jrTsXHrasjJyWGp7wqcOX0uV7ZNRFRQMblERIVKeno6DHQX4+jh45CXl4eXn2u2s3xVqPj/3kyfP33+abtvy0qWKlkk6i1lp//AvqhStTJEIhF27dgr7XByXUpKCg7uOwwg41izG+ZmY+GAlJRUzFs4B+rqaoiPj8/0k5aWUUBYEATxc6mpqflyHLLoT6+dlq1biB+/fxeSi5HlDxdHd/EwJHOrxZihnXVR6ri4eOzcthtARtIkq5kHlVWUMWXaRADAzaBbCA//mkdR54/cOGYzK2Ps2r8NI8cMR736dVC5SmU0b9EMhov1cOTEPhQrltEbrmq1KlBULNr1cVp991oKfp/5tVTx38/FT5+yr6X0bXnFirLbK9jN2QuRkVEYN3E0atep9cN79Pfvx9+eS0n5sa7SzzRv2Qxt2rYCAPH1S0RUVLGgNxEVGt96LB05dEycWBo8ZGC269Rv8P8Z4p4/e4E6dbOexvrZv7ML1f3J8qKmUqWK+BD6EW/fvvt14wLm9MmziIiIBPDrIXHBwRlfytxdvODu4vXTdh9CP6Jp/TYAMnqr/CypUBQU5msnO84O7lizaj0AwNTCCNo603/a9s3rt+K6QdnVh9GsVVP8OOR9yE9n9ioIcuuY27RtJf6y/18P7j8EALRq3fJPwy3U6v37ufg1/Cu+fo1AuXJlf2iTnp6O169eAwDq1quTr/H9jpB/E2fbNu/Ets07s2377T162szJsLYzz/E+vk348e7tewmjJCIqHNhziYgKhfT0dOgvMMqUWPp76KBfrldLSxNVqlYGAFw4F5hlm4SEBNwMugUA6NIt6+F1RYkgCOKkSkkZHg4hqW9D4mpq1kD7jm2lHE3h8qfXzp3b98SPv9VfKgicHNwyJZZmz52ZbftixeTEj0NDP/y03fc9d2R5aFJO5PUxh4WFi4d/jRg1VIIIC5fvX0vVqmd+LXXp2kn8+OJPPhdv3biNuH8LeXct4p+Lwe+DAaDI92omImJyiYgKvG89lo4ePv5vjSW3HCWWgIx6MN++aBw5dAwhwaE/tNmycTvi4xMgLy+PoSMG52rssiarWZb+a3fAPoR9CQcAtO/YLq9DylehoR9wOTDjC+jocSMhJyeXbfvAa2fwOuTJT39Gjh4GIGMYzrfnCmuvpT+9dn5VoDsqMgorlq0GAFSuUhmNmzSUMNL85eTglmko3K8SSwBQu7YWlJUzZqjctWNPluc2PT0dO7dlFEZXV1eHVu1auRh1/svLY05PT4eVqS1SUlLRvEUzdOvRJfcCl0G/ei0lJ6fA09UHAKCqqorOXTpkWl6jZnW0adcaALB29cYsh/KuWL4GQMZ7W7sObXIh6ryxY8/mbN+jdQ3mi9t+e+5br6X09PRfnsvLl67i3t0HAMCbEURU5DG5REQyIzoqGhERkeIfkSjjn7qkxMRMz3+bJhn4f42lI4eOQUFBAT7L3H85FO6/tHVmQKNCeSQmJmLmVB08uP8IQEbtna2bd8DbI2MWmHETR0NLq+B8gZPkfN4Muo2xIydh/56D+PjhU6btvXn9Fq5OnrA0tQUA1KxZA6NGD8+348kPu3fug0gkgoKCAkb9mxgqiqRx7RzYewhztBfi2NGTmXqnJCUm4eTx0xg5dDzev8voIWBmaYRiBWC2r+9rLFnYmGQ7FO57yirK4iGZDx88xqxp8/D0yXOIRCKIRCI8efwMM6bo4NbNOwCA6dqTxbPrFVR/eszv3wXDw9UHDx88QnJSMgBAJBLh5o3bmDJBGydPnIGauhrcvZ1+mTSWJZK8FoOu3cCkcdN/eC2mpqbi8qWrGDtikng2zIX6c7OsK2dibgh5eXk8efwUuvMM8eljRt3BqMgoWJnbiXv6mloYFfhr72c+fviEwf1GYPvWALx/F5wp0fThw0esWLYGOjMWQBAElC6tjpmzCueNAyKinGLNJSKSGYP7j0BoyI/DIVavXI/VK9eLfx85ehjcvZ0BZHTNP3LwHwAZvZBsrZbA1mrJT/dhbWf2Q/JJTa0U1m5ciWkTtfHi+SsMHTgKJUuWQHJyiviObdfunWFpY/bHx5ifJDmfAHDj+i3cuJ4xDFBJSQklSqgiISERSUn/nzGvYaMGWLVuGZRVlPPwCPKXSCTCnl37AAA9/uqWqdh7USONayddJMLJ46dx8vhpABk9KpSUFBETE4v09IzC6IpKirCwNvntBLI0hIZ+EJ+rYsWKYZX/OqzyX/fT9rN0pmPWnP/PZmZiboi3b97hwvlA8Y+iUkYR6pTk/xcc/nvoIMzXnZNHR5G//uSY4+Li4L90FfyXrgKQ0bMpISFB/B5epWplrFy79Kd19WSVJK9FQQCuXLqGK5euAQCUlZWhqqqC2Ng48fkoVqwY5syfBZ152lnut3WblnB0toGVuT1OHDuFE8dOQU1dDbExseIki67BfAz6e0CuHq+sefL4qTgprqhYHCVLlkRSUjISEhLEbarXqAb/1b7QqKAhpSiJiGQDk0tEVKB9u4sLZNyVDQ8Lz7Z90r93tP+rabPGOH72MFb5r8XZ0+fx8cMnqKiqoHn9Zhg5aihGjxtZIHpK/KkmzRrDy9cV164G4cH9RwgLC0dUZBQUFRVRs2YNNG7aCP0H9sGAQf0K3d3qy4FX8SH0I4BfF/KmH/3ptdOxUzsYmujjzq27ePXiNSKjohAbG4eSJUuipmYNdOzcHhMmjS0wtZaE796bRCLRL9+b4uMTMv2urKKM9VtW4djRkzi4/zAe3n+Er1+/AnJy/86C1hSjxg7HX7165EX4UvEnx1ytWlUs1J+H61eD8O7te0RGRqJkyRLQqqOFfgP6YOLksVBRUcn/g5KC+g3rwtxqMW7fuotnT58jMiISMTGxUFZRRp26tdG2XWuMmzgGDRrWy3Y7YyeMRuOmjbB21UYEXbuBiIgIlCtfDq1aNceUGZPQqXOHbNcv6CpU1MCylT64fjUId+/ex5dPXxAZGYlixeRRpWplNGzUAL37/oWhwwYXqhstRESSkhN+NZgYQExMDNTV1REdHQ01tZ9PyUxERZOqqiqMTQ0wbeZkaYci89at2QgXRw+8ePdQ2qEUCM0btUOrVs2xYesaaYci87ZvDYCVmS1eBT+RdigFQruWXVFLSxMBe7dIOxSZt2/PARjpm+H+05uFsoh/buveqQ/KlC6NA/9wavpf+efICSyYo4/A62dR9d/JNejnBvcfgZ7d/8KyZcukHQoRFRG/kwsq/LfhiYiIiIiIiIgozzC5REREREREREREEmNyiYiIiIiIiIiIJMbkEhERERERERERSYzJJSIiIiIiIiIikhiTS0REREREREREJDEml4iIiIiIiIiISGJMLhERERERERERkcSYXCIiIiIiIiIiIokxuURERERERERERBJjcomIiIiIiIiIiCTG5BIREREREREREUmMySUi+iOJiYlIT09HQmKitEMpEBITEgEISE5KlnYoMi85OQXp6elITU2TdigFQkJCxmswka/FX0pJSUFaairSeG3lyLdrK4nX1i+lpaUhJSUVqWm8tnLi2/sVr61fS09PR2JCIkJCQqQdChFRlphcIiKJCIKA3bt3o2HDhkhLS4Onqw/MFlsjPPyrtEOTSWFh4TAxsoS3x1IIAvBX1/44dvQkBEGQdmgyRxAEnDx+Gr27D0RiQiKuXL4GYwMzfPn8RdqhyaSIiEhYmtrC2cENcnLF0LNLPxw+eJTX1k+cO3MBfXsORlRUNO7cvgu9+Ub4+OGTtMOSSVGRUbC3doKtpSOKFSuG/r2GYN+eAxCJRNIOTSYFXryM/r2G4POnz3jy+CnmzdZFSHCotMOSSTExsXBycIOpkSXk5Yth1LAJCNixB+np6dIOTSZduxKEQX2H483rtzh48CCGDx+OV69eSTssIqJMmFwiot929+5d9OjRA2PGjEGdelo4fHwv+g3ogz0B+9CjUx+sXb0RKSkp0g5TJiQnp2D1inXo0akv9u05gP6D+sJ/jS9S01IxX0cP40dNwZPHT6Udpsx49vQ5Jo6djjnaC5GYmIjlq3wwZNggHNx/BD0698OKZWvY6+tfqamp2LB2M7p36oOAHXvQu29PrNngDznIQW++EUYNHY8H9x9JO0yZ8erla0ydqI2ZU+cgJjoGvv4eGDl6GI4dPYG/uvbDUh9/JCUmSTtMmZCWloYtm7aje6e+2LJpG7p174x1m1dCSVkJRvpmGDZ4DO7cuivtMGXG2zfvMGvaXEydoI3wsK/w8HHB+IljcObUefTq1h9e7r5ISEiQdpgyIT09HQHbd6N7pz5Yv2YT2ndsi41b1kCtVEmYGVthyIBRuBF0S9phyoyQ4FDMm62LCWOm4sOHj3Bxd4CfvyeCgq6jUaNGMDU1RWxsrLTDJCICAMgJObi1GRMTA3V1dURHR0NNTS0/4iIiGfTlyxdYWlpi7dq1qF1HC1a2ZujavbN4+etXbzBvth6eP3uBGjWrw8beAj17dZdixNIjCALOnj4PO+slCA35gPoN6sF/tS80a9UUt/Hz9sfK5WuQnJyM8RPHwMBYF+XKlZVi1NITGRkJH49l2Lp5BxSVFKEzdyZ0DeajWLGMeyDB74IxV0cPTx49ReUqlWFtZ4Y+/XpBTk5OypFLx4VzgbCzXoK3b96hTt3a8F/tizp1a4uXr/Rfi6Xe/khKSsLIMcNhbKIPjQoaUoxYemKiY+DrvRyb1m9F8eIKmDZzCoxNDcTX1sePnzBXWxcP7j9EhYoasLQxxcDB/YvstXXl8jXYWjjg5cvX0KxVE/6rfNCgUQPx8k3rt8DdxQcJCQkYNmIIFpstQqXKFaUYsfTExsZhud9KrFu9EfLyxTBh8jhY2piKr62wL2GYp6OHO7fuoWy5sjC3WoyhwwcX2Wsr6PpN2Fo64umTZ6heoxqWrfBG0+ZNxMu3bw2As6M74uPiMejv/jC1NEbVqlWkGLH0xMfHY+XyNVi1Yh3kIIfR40bC1sECCgoKADKGE65esR6rVqxFafXScHZ2xpQpU8TXHhFRbvmdXBCTS0T0SykpKVi2bBns7OwgJwfoGy7EhMljUbx48SzbH/vnJCwWWyMqKhpdu3eGla1Zpi++hd2L5y9hb+OEy4FXUaZsGTi72aNv/95Ztk1ISIDBwsU4e/o8lJWVYGCsi8lTJ/z03BY2qamp2L4lAJ5uvkhMTESPnl3hvcwDJUuWyLL92TPnsXiRBSK+RqBDp/awsTdH/Qb18jlq6Xn9+g0cbV1w/uxFqJdWh4OzDQb/PSDLtklJSTA2MMeJY6dQvHhx6C2aj6kzJkNJSTGfo5aO9PR0BOzYA3dnL8TGxqFz105Y6u8JNfWs/48JvHAZRgZmCPsShtZtWsLW0RKNmzTK56il5/27YCyxd8WpE2dQqlQpWNubY+ToYVm2TUlJgZmRJQ4fOgZ5+WJYoDcXM2dNg7KKcv4GLSUikQh7du2H6xJPREdHo137Nli2yhtly2Z9cyDo2g3oLzTGp4+f0axFU9g5WKJ5y2b5HLX0hIaEwtnRHf8cOYGSJUvAzMoY4yeOzbJtWloarMzssG/PQQDA3AWzoTNvJlRUVPIzZKkRiUQ4tP8InBzcEBERiVatW2D5Kp+f3hz48OEjXJd44vDBo2jTpg18fX3RqVOnfI6aiAozJpeIKNf8888/MDDQx8uXrzBh8ljoGy5E2bJlfrmeSCSCu4s3Nq7bjNTUNEydMQm6+vOgXlo9H6KWjqjIKPh6LceWTdtRvHhxzJw9DYuMdXN0J/Hli1eYN1sPL1+8gmatmrCxt0D3nl3zIWrpCbx4GXaWS/D69Rto1a6F5at9Ub9+3V+uJwgCfL2WY9WKtUhJTsGkKeOhb7QAZcr8+rosqGJiYrHMdwU2rN0MeXl5TJ42EWaWRjm6tt69fYe5s/Tw7OlzVK1WBTb2Fvird49C3Xvi2pUg2Fg64MXzl6hZszqWrvRBk6Y5SxT5L12NZX4rkJyUjDHjR8FwsR7Kly+XxxFLT1xcPPyXrsLaVRsgV0wO48aPho2DRY6urZCQD5g3WxePHjxGpUoVYWlrhv4D+xTqa+vmjduwtXTA40dPUbVaVfit8ETLls1ztO661Zvg5eGLxIREjBg1FIvNFqFCxQp5HLH0JCQkYJX/OqxcvgYAMGL0UDg42Yh732Tn86cvmDdbD3fv3EN5jfKwtDHB4CEDC/W1de/OfdhYOeL+3QeoVLkifJZ5oF37Njla90bQLTjYOOPhg0eYMGECXF1dUa1atTyOmIiKAiaXiOiPPX36FAaLDHD82HF06twBlrZmaNDw93uIxETHQHeeIS4FXkHJUiWx2GwRxo4fBXl5+TyIWjrS0tKwY9sueLj4ICEhHl27d4HvMk+UUiv529s6evgYLM3sEB0VjR5/dYOlrSm0tGrlQdTS8/bNOyyxc8GZ0+ehpq4G+yVWGDJs8G9vJy4uHgYLjXH+7EWoqKjAcLFetj3qCqL09HTsCdgHFydPxMbEomPn9ljq74XSZUr/9rZOnjgDM2MrREZEolOXDrC2M0e9HCTzCpLg9yFwcnDDiWOnULJUSVjZmmH02BG/vZ2EhAQY6Zvh1IkzUFJShL7hQkyZPhGKioWn15dIJML+vYfg7OCGqKhotGnbCstW+UiUSLtwLhDGi8wQHvYV7dq3gY2DBRp+N5SuMPjw4SNcHD1w5NA/KFGiBEzMDTFp6vjf3k5ycjJMDC3wz5ETUFBQwEL9eZihPQVKykp5ELV0CIKAwwf/wRJ7V4SHhaNFq+bwX+WLipV+P5F29fJ1LNJdjM+fv6Blq+awdbRC02aN8yBq6fn86QvcXbywb89BqKpmfJZN157629v51qPO09UH8fEJMDU1hZGRUZHp9UVEeYPJJSKSWFRUFOzs7LBs2TJUqVoZ5laLc6W2zaOHj7FgjgHevX2PuvXqwNbBEh07t8+lqKXn8qWrsLV0xKuXr1GrliaWr/LOVJ9EEiKRCK5LPLBpwzakpadh+swpWKg396fDeQqKzPVJ5DFxyjhYWJv8cY2I589fYt4sXbx+9QZaWrVg42iBrt06/3pFGRd07QZsLB3x7OnzLOuTSEIkEsHbYynWrtqA1NRUTJ46AXqL5kuUrJIlv6pPIqnXr99g3qyMOnLVa1SDjYMFev7VvcD3nrh96w5sLR3x8MFjVKlaGb7LPdG6Tcs/3u5SH/+MovvJyRg3cTQWGesV+Dpy32rbrFi2GoIgwtARQ+DkavfH19Z/68hZ2Zqib//eBf7aun/vIWytHHH39j1UrFQR3n5u6NCp3R9vd/WKdfD1Wl6o6sglJyVj3dpNWOrjj/S0dAz6uz9cPZf8cRL722fthrWbUblyZbi7u2P06NEF/toiIulgcomIflt6ejrWrl0LS0tLJCYmYt5CnTy5m7o7YD8cbZ0QGxuHfgP6wNxqMarXKHhdt7+vT6KmVgrW9hYYMWporu4jOioaC+YuwtXL11BKrRRMzBZh9LiRBa7X13/rk7Tv0BbLVnqjTA6GV/6OQweOwNrCATHRMfirdw9Y2phmKqBeUGSuT1ISFtaLMXbC6FzdR2xMHPQXGOLihctQVVWBkakBxk8c88dfmPPbD/VJ2rTA8pU/r08iqWP/nISliQ0iI6MKdB25Tx8/w9XJEwf3H4ZqCVUYmy7C1OkTc3UfCQkJWLRwMc6cPg8lZSUsKqB15ARBwNHDx+Bo54qwL2Fo1qIp/Ff7onLlSrm6n0x15Dq2g7W9hUS9hKUt7EsY3F28sXf3ASgrK0PfaAFm6czI1X0kJSVh8SJzHP/nJIoXVyywdeQEQcDJ46fhYOOMjx8/oVHjhlixxg/VqlfN1f28ef0Wzo7uOH3yLLp27QpfX1+0bPnnSWQiKlqYXCKi33L+/Hno6eni/v0H4juCeVkHIj09HXZWSxCwYw8ECNCZOxNz5s9CiRJZF3GWJf+tTzJ+4hhY25nn6QwtD+4/wsK5Bnj/Lhj1G9SDnaMl2nVom2f7y03f1yepVq0qfH+jPokkRCIRnOxdsXXzTqSnp2PmrKmYrzcXpUr9/hDF/Pbf+iQjRw+DvZN1niZ8nj55hvk6+njz+i1q19GCraMlOnfpmGf7y0337tyHjaUj7t97gMqVK8F7mXuO65NIQiQSwdPVB+vXbkJqahqmTJ8IPYP5BaKOXFJiEtau3oDlfiuRni7CkGGD4ORmn6fD/F69fI15s/Xw4vnLAldH7uGDR7C1dMTtW3dRoaIGPH1c0blr3r0uvtWRW71iLZKTUzBx8jgYGC8sEHXkkpNTsHHdZvh5+yM1NRX9B/aFm9cSKCvnXXH3d2/fYd5sPTx98hxVq1aBtb05evXpWSB65jx98hx21ktw/WoQypUvBzfPJXk+q27gxctwtHXByxevMGPGDDg5OaFChcJb64uIcheTS0SUI2/evIGxsTH27t2Llq1awNreHM1bNM23/YeHhWO+jj5u3byDMmXLwNzSGENH/C2TU+n+UJ+kXWssX+WTr0M+ArbvwRJ7F8TFxWPAoH4wtzJG1Wq5e6czt/xQn8TCEJOm/H59EklFRUZhwRwDXLsaBDV1NZhaGGHUmOEyeW0JgoBDB47CycEN4WHhaNmqOfxX++Zrod/9ew/BzsoRMTGx6N33L1hYm6CmZo182//v+PzpC9ycPbF/7yGoqqr+W59kSr7tPyYmFrrzFuHSxSsoWbIEjM0WYdyE0TLZo1AQBBw7ehKOds74/OkLmjZtjOVr/FC1auV8i+Ho4eOwNLNFdFQ0uvfoCis7M2jVls06cmFh4fB09cXugL1QVlbCAv25mDt/dr7tPy4uHot0jXHuTEYduUXGupg4ZZxM9voSBAGnT56FvY0zPoR+QIOG9eG/2gc1NfOvt+jpk2dhYmRZIOrIRUREwtvdD9u3BkBJSQk682ZCb9GCfNt/Wloatm8JgLfnUggiAdbW1li4cGGhqiNHRHmDySUiylZcXBxcXFzg4eGBMmXLYLHZIgwdPlhqd/1uBN2C/gIjfPzwCU2bN4GdgyVatMq73i2/K3N9kirwXe6RK/VJJJGWlgYbc3vs2X0AADBnnjZ05mtDVVVVKvH8V17VJ5HU3Tv3oTtvEUKCQ9GocQPYOlqhTdtWUoklK5nrk1SAt597rtQnkYRIJIKDjRO2b9sFQSRAW2c65i3UQcmSstGj8Mf6JAPg6ukotS9Hjx8+wfw5+jJbR+7xoyews1qCG0G3oKFRHu4+zujWvYtUYpH1OnIpKSnYtH4rfL2WITklBX379Yanr0ue9r7JzvPnLzF/tl5GLT8tTdg6WKJrd9mpI/f82QvYWS/B1cvXUbZsGbh4OKJ337+kEotIJIKP51KsWSmbdeRSU1OxbfNOeLr7IikxCT17dYeXn5vU3lcjIyPh47EM27cGQEurFry8vDFo0KAC0euLiKSDySUiypJIJML27dthYmKCiIivmKUzQ6YSExvXbYGHqw8SEhIwfOQQLDYzlGh2mdzy8cMnuDp54tCBI3lWn0RSYV/CMG+2Hu7cvoey5crCwtoEQ4ZJ7x/E/9cncUFYWDiaN2+K5XlQn0RS27cGwNnRHfFx8Rg0ZABMLYxQtWoVqcWTqT6JijIMDBdCW2e61OL5XkREBObrGODG9ZsoXVodppbGGDFqqNR6feVXfRJJ7dm1Hw42GXXk+vbvDQtrE6nWkfv6NQKebj4I2L4HSkpKmLdQBwv05kgtnu/FRMdgwdxFuHLpqkzUkRMEAWfPnIe9tRNCgkNRr35d+K/xRa1amlKJ578OHTgCGwsHREfHoGev7rC0MUUtLU2pxRMVGQUfz2XYunkHihcvjllzZ0B/0QKZ6BEaGxMHg4VGuHD+UsaMayb6mDBprFTryF08fwl21kvEw479V/uhbj3ZqNX27OlzONq64PKlq+jbry98vH3QsGFDaYdFRDKIySUi+sH169ehq6eLoOtBGDi4P0wtjGTmy9n3UlJSYGpkiSOHjkFeQR4L9OZCe9a0fJ2mOVN9EpEIQ4YNhpOrnUx2H79+9Qb0Fxrj86fPaNGyOWwcLPJ1aCOQ//VJJJWWlgZLMzvs33MAcnLFMHfBbMyeOyNfp2n+Vp/E12s50tLSMGBQX7h65m19EkndvnUHevONEBryAY2bNITdEiu0ap2/PfaePH4Ge+sluH7tBsqVLwd3Lyf0+KtbvsaQEyKRCLaWjuI6crPnzMTcBflbRy4lJQVbNm2Ht8dSJCclo3ffv+Dp6yIzNw++Jwt15F6+eAV7aydcCryCMmVKw8nNHv0G9MnXGHJCJBLBycEdWzdtl1odubS0NGzfGgBPVx8kJCSie48u8FnuKTO9Gr/39OlzzJ+tl5HQqV0Ltkus8r2O3JvXb+Fo64xzZy9CXV0NDs42GDxkYL7GkBPfhjYusXdFaMgHLFiwADY2NgWi1hcR5R8ml4hI7MOHDzAzM8PmzZvRqHFDWNuZFYhi0CHBoZg7WxePHz5BpUoVYWVnhn4D+uRpz5yM+iQn4GjnklGfpFlj+K9ZiipVZKP3TXbWrtoIb08/JCYkYuToYTA2Ncjzmj0Z9Ul8sDtgH5SVlbHQYB7mzNPO033mhk+fPmPebD3cu3MfGhXKw8LaBIOHDMzzaytTfZJG9bFytR+q16yeZ/vMLZs3boO7sxfi4xMwZNhgmJgbonIevyakXZ9EUuHhXzF/tl5GHbkypWFmZYxhI4bkec+O82cvws56Cd69fY969evAf7WfzNY1+l5GHTlXxMXF5VsdueioaPh6LcfmjdtQvLgCZs6ehkXGejLR+yY7/60jZ2JuiFFjhud5r69LgVdgZ+mIV6/eQKt2LSxb5YMGDWR/NrsD+w7B1nIJYmJi8q2OXExMLJb7rsT6tZsgLy+PyVMnwMzKWOavreTkFGxYuwnL/VZBWVkZDg4OmDVrVoGbPZSI8gaTS0SEpKQkeHl5wcnJCcrKyjBcrFsgp7G/cC4QxovMEB72Fe07tIW1vQUaNqqf6/t5/OgJbC0dcfPGbWhUKA8PbxeZqnGRE8nJyTAxtMA/R05AQUEBugbzMF17aq5P0/ytPomP5zKkpKagX/8+8PBxlsneN9m5cvkaDHVN8PnzF7Rs1QK2jpZo2qxxru/n2dPnsLdxyqhPUq4MXD2WoFefnrm+n7yUkpICC1NbHNx3GPLyxTBvoQ5m6cyAskru/s3/W5/kr97d4eXnjhIlZK/3TXZuBt2C3r915Jo0awx7R6s8qSP3+tUbONg448L5QJQurY4lrvYYMKhvru8nL6WlpcHGwgF7du0HkHd15NLS0rBz+254uHgjPj4eXbt1hu9yL5RSk/2ZJL93784DLJxngJDgUDRs1AC2jpZo2651ru/n7Zt3WGLvijOnzkFNTQ12SywxdPjfub6fvCQSieBo64ztWwMgEgmYOXsa5uvOyfUeV+np6dizaz9cnTwREx2Djp3aY+kKL5mp+5RTXz5/gYebL/YE7EPTpk3g6+uHnj0L1mcVEeU+JpeIijBBELB//34YGi5CSEgops6YJFOFUyXl570cK5evRXJyMsZPHINFi/VQtuyfd93+b32SBXpzMG+hTi5ELD3B74Ixd7Yenjx+iipVq8DK1hR9+vX64545/61PUr9BPfiv9oVmrfybHSgvrPRfi6Xe/khKSsKosSNgZKIPDY3yf7zdTPVJFItj9tyZ0DOYL/N3sbPz8eMnzNXWxYP7D1GxUgVY2phiwKB+udLr6/v6JHXq1ob/al/UqSsb9UkktWn9Fri7ZNSRGzZiCEzMc6eOXEx0DPx8/LFx3RYUL66AaTMmw9hsUYG+tv5bR87canGuTTRx5fI12Fo64uWLV9CsVRP+q3zQoFGDXIhaevKqjlxcXDyW+63EutUbUayYHCZMHgdLG9MCfW3lZR25G0G3YGvpiCePn6J6jWpY6u+FZvk8ND233bv7AA42zrh96w5GjBgBd3d3aGlpSTssIpISJpeIiqj79+9DX18f586dw1+9usPc2qRADI3IqYSEBBgsXIyzp89DWUUZi4x0MWnqeImmaU5JScHmjdvh45lRn6RPv17w8HGWyfokkjp75jxMFlng69cIdOjUHjb25qgv4XCGF89fwt7GCZcDr6JM2TJwdndA3369cjli6UlKSoKxgTlOHDuF4sWLQ2/RfEydMVmiXl/fpnz2cPVBYmIievTsCu9lHjJZn0RSgRcuw8jADGFfwtCmbSvYOlqiUWPJisG+fv0GS2xdMuqTlFaHg5O1TNYnkVRKSgrMjCxxOBfqyKWnp2PXjr1wc/ZEbGwcOnfthKX+ngX+5sH3gq5l1JH79PEzmrdsBlsHS4nryL1/F4wl9q44deIMSqmVgo29BUaMGprLEUtPWloarMzssG/PQcjJyWHO/FnQmTdTojpyIpEIe3cfgIujB6Kjo9GuQxssW+mNsmXL5kHk0nH79l3ozTMU15GzdbSSeObX0NAPcHF0x9HDx1GyZAmYWRlj/MSxuRyx9AiCgEMHjsLN2RMRXyNhaGgIMzMzlCxZsHr6EdGfY3KJqIgJDw+HpaUl1qxZg1q1NGFhYyKTRW9zy8sXrzBvtp74LrStgyW69cj5FNvnzlyAnfUSvH8XnDE70GrfQpWE+54gCPD1Wo5VK9YiJTkFk6aMh77RghwX7Mxcn6T4v/VJdAv0XezsvHv7DnNn6eHZ0+eoWq0KbOwt8FfvHjnuPXEp8ApsLR3x+t/6JMtX+6J+/bp5HLX0+C9djeV+K5CUlIwx40fBcLEeypcvl6N1f6hPMm0izCyNCu21FRLyAfNm6+LRg8eoVKkiLG3N0H9gzuvIXb8aBBtLRzx/9gI1a1bH0pU+aNK0UR5HLT3rVm+Cl4evRHXk4uLisWLZaqxZuR7Fislh7IQxsLE3L7TX1udPXzBvti7uSlhH7tbNO7CxsMfjR09RrVpV+K7wRMuWuT+MU1Zs2bQdbk6eiI9PwN9DB8HUwijHdeQSExOxyn8dVixbDQAYMXooHJxsCm19ooSEBKzyX4c1K9ehTJmycHFxwaRJkwrta4mIfsTkElERkZqaCn9/f9ja2kIkSofuovmYPHWCRD15CqKjh4/B0swO0VHR6PlXN1jYmkJL6+dJolcvX8PBxhkXL1xC6TKlscTVDgMGFqz6JJKKi4uHwUJjnD97ESoqKjAy0ceEyT+fpjlzfZIEdOveGT7LPAtcfRJJnTxxBmbGVoiMiETnrh1hbWeOuvXq/LR9pvok6mqwX2KFIcMG52PE0pOQkAAjfTOcOnEGSkqK0DfSxZRpE346u+IP9Uk6t8dS/4JXn0RS39eRa9e+DWwcLLOtIxcSHApnRzccO3oSJUuVhJWtGUaPHZGPEUvP79aRE4lEOLDvEJwd3BEZGYU2bVth2SqfHCc8C7rMdeSaw9bRKts6ch8/fILLEg8cPngUJUqUgImFISZNGZ+PEUtPWloazBZb4+D+w5Av9us6coIg4Mihf+Bo54rwsHC0aNUc/qt8c2WYa0EQGhIKlyUeOHr4ONq2aws/Xz906NBB2mERUT5gcomoCDh+/DgMDAzw/PlzjJs4GgZGuihXrvB0X88pkUgElyUe2LxhG9LT0zFdewoW6M2FmlopcZuY6Bj4ei/HpvVbUby4AqZrT4GRiUGRvPP2/PlLzJulK+5ZY+Ngga7dMhcu/74+Sa1amli+yrvA1yeRhEgkgrfHUqxdtQGpqamYMm0idA3mZUqCxMbGYbnfSqxfswnFihXDxCnjYGFtUiSvrdev32DeLD08f/YCNWpWh429BXr26p6pTdD1m7C1dMTTJ89QvUY1LFvhjabNm0gpYula6uOPFcvWiOvIGRhnfg9PSEjAyuVrsNJ/LeQgh9HjRsLWwaLQ9pDITvC7YMzV0cOTR09RpWplWNma/VBH7s6tu7CxcsTD+49QpWpl+C7zQOu2raQYtfSsWrEWfl4/ryOXmJiINSvXY8Wy1RCJRBg6YgicXO2K5LX18eMnzJ2liwf3HqJixQqwtP2xjtyD+49ga+mAO7fvoWKlivD2c0OHTu2kGLX0BF27AQdbFzx6+BiTJk2Ci4sLqlbN2xkeiUi6mFwiKsSeP3+ORYsMcPToP+jQsR2s7MzQsAh+8f+v6KhoLJi7CFcvX0MptVIwNTfE8FFDsWfXfrg5eyEuNg5dunaCXyGrTyKpQweOwNrCATHRMfirdw9xwdbCXJ9EUrExcdBfYIiLFy5DVVUFRqYGGDt+FA7uP1Ko65NI6tg/J2FhYoOoyCh07d4Z1nbmUFZRzlSfxNxqMcZNHCPtUKUuISEBixYuxpnT56GsrIxFxrqYOGUc/jlyAk4Oboj4GoFWrVtg+SofaFTQkHa4UpdVHTl1dXW4Onni4P7DUC2hCmPTRZg6faK0Q5W6n9WRO33yDBztXPDlcxiatWgK/9W+qFw5Z0PCCrPAC5dhbGCGL1/C0LpNS9g6WqJCBQ24u/pg7679UFZWhp7hAsyeM0PaoUpdeno69gTsg4erLxITE2Fubo5FixZJVOuLiGQfk0tEhZSHhwfMzc1RqVJFmFoa/1a9jqLiwb2HWDjXAO/fh0BVVQUJCYmoqVkDy1Z6o3GTwlufRBIikQhO9q7Yunkn0tPTIScnB7lichg/cQys7QpvfRJJPX38FPN1DPDmzVvxtVUU6pNIQiQSwcPVGxvWbkZqahrk5eUBACNHD4O9k3WR7CGRnZcvXmGejh5ePn8lvrYqV64E72XuaNe+jbTDkyn/rSNXvHhxiAQRhgwdBCc3+58Oxyyqvq8jp6KijISERFSoqAFPH1d07tpR2uHJHP9lq7HcN6OOnKKSItLT0tF/YF+4eS2BsnLWQ+aKqpiYWCzzXYFN67eiSpUqOHToEJo1aybtsIgolzG5RFRI9e/fH+ERYdi6Y71EMw0VJcv9VsHTzQfTZkyGtb25tMORaVGRURjUbzi+hkfg8o1zRXJ45e9Yv3YTHG1dMHLMcLh7OUk7HJkWExOLv/uPwKePn3Hx6ukiU59EUgHb98BssRUGDuqHZat8pB2OTIuLi8ewQaPx/l0wzl0+iapVK0s7JJl2cP9hGCxcjO49u2HDllXSDkemJSYmoku7v5CcnIyjJ/ejpmZNaYck0548foZBfYdh586dGDu28MyYR0QZficXxNvSRAVMhQoaTCzlwLfZ41q1aSHdQAqA0mVKo2mzJihZqiQTSznwrUZVy1bsrfQramql0LJVC5QoocrEUg5860nSrEVTKUci+0qWLIG27VpDRVWFiaUc6NQl49pq2ow9eH9FRUUFFStVROUqlZlYyoHqNapJOwQikhFMLhERERERERERkcSYXCIiIiIiIiIiIokxuURERERERERERBJjcomIiIiIiIiIiCTG5BIREREREREREUmMySUiIiIiIiIiIpIYk0tERERERERERCQxJpeIiIiIiIiIiEhiTC4REREREREREZHEFKQdABEVXLGxcdi2eQdOnzyLt2/eIS4uDmXLloVmrZpo16EtZmhPgZq6mrTDzDe/ez60qjXM8bY7dGyH7bs35UXYuSoxMRHXr97AwweP8PDBYzx88AgfQj8CAHQN5kPfcMFP1/308TNOnTyDa1eC8PjhE3z69BkAoFGhPFq0ao5xE0ajU+cOv4zhnyMnsG/PATx88AiREVFQUFBApcoV0a59G0yeNgGNGuf8vEtTZGQkTp88hyuXruHRw8cIDfmA9PQ0lC1bFk2bN8GIUUPRb0CfLNf9k79DQRd48TICtu/B3Tv3EB7+FXKQQ4WKGmjZqgXGTxyN9h3b/bDOn5xrWZQXf38LU1vs2BoAAKharQoCr53Jst31q0EIvHgFD+4/xPt3wYiMjEJCfALU1dVQt14d9O3fG+MmjIayirLkB5jPHj54hDOnzuPhg0d48/otIr5GIC4uHiVLlkDtOlro8Vc3TJw8DqXLlM52O2FfwrBl03acP3sRwe9DkZSUhHLly6JOndpo37EdtHWmoXjx4vlzUHks6PpNbNm4Dbdu3EFERARKlSqFBo3qY/TYkRgybNAP7UOCQ9GtY+8cb3/kmOFw93LKzZDzxJ+8Fn08l8HPe/kv93E28Dg0a9XMcllSYhK2bd2JE8dO4+Xzl4iLi4eyijI0NWugW4+umDp9IjQqaEh2cERE/8HkEhFJ5Orl69BbYITwsHAAgKJicSirqODTp8/49Okzrl0NQt/+vdCoiCSXJDkf5TXKZ7vNtNRUREVFAwCaNW+Sd8Hnont3HmDGFJ3fXu/Dh4/o2r4XBEEQP6eiogJBEBASHIqQ4FAcOfgPRo8dASc3e8jLy/+wjeTkFCyYo48zp86JnytRQhWpqal48/ot3rx+i90B+2BmZYyZs6ZJdHz5qX3LbkhLSxP/rqSkBAWF4uJr6tSJM+jesyv8V/tCRUUl07qS/h0KMkEQYGlmJ06AAICyckYCI/h9CILfh+DQgSOYMWsqLG1MM637J+daFuX23//q5evYuW1XjtquXrke585cEP+uqqoKRUVFfP0aga9Xg3DtahA2rNuMDVtXQ0urVq7FmJd279yHLZu2i39XUlKCsrISoqKicevmHdy6eQcb1m7G6g3L0ap1yyy3ceTQPzA3sUFcbJx4G8UVi+ND6Ed8CP2IixcuYeLksSiuXvCTS65Onljlv1b8u5q6GmJiYnE58CouB17FP0eOY9lKbygo/P9rSDH5Yr/8TExOTkZsTCyAwv+Z+L3ixYtDvbT6T5d/fx6/FxoSisnjZ+Ltm3fi50qplUJ8XPy/ia7H2LJpO9asX452Hdr+UYxERACTS0QkgZs3bmPm1DlISkpCvwF9MHfBbDRt1hhycnJITEzE82cvcfrkGZQqVUraoeYLSc9H0J3AbLe7dtUGODm4AQDGjB+VZ/HnNnV1dTRu2hBNmjRC46aN4GjngrAv4dmuI0oXQRAEdOrSASNGDUXnLp1QsVIFiEQivHr5Gh6uPjh14gx2B+xDxUoVsMhY74dt+C9dJU4sTZo6HvMW6KBS5YoQiUR49PAJHGydcTPoFpzs3dCufVs0bdY4T44/t6SlpaF5i2YYOWYYunXvgho1qwPIuMO/zHcFdu3ciwvnAmFhYgMvP7cf1pfk71CQ7dm1X5xYGjCoH4xM9FFLSxMA8PrVG7g6eeLUiTNYv2YT2rZrnakn0p+ea1mUW3//xMREmC+2hoKCAho0qo8H9x5m275z147o1r0L2rRrhZqaNVGyZAkAGb3DDu0/ClcnTwS/D8Fc7YU4dvoQihWT/QoNzVs2RbXqxmjTthVq19ES90CNj4/HiWOn4Ozgjq9fI6AzcyHOXDwGNbXM7/X/HDkO/QXGEIlEGD9xDKbNnIy69eoAAOLi4vH40ROcPH4aCsUL/r/l27cGiBNLg4cOhJmFMSpXqYTk5BQcOfQPbCwccPL4abgs8ciU5K1SpfIvPxNtLR2xeeM2KCsrY+iwwXl6HLnpT1+LrVq3wI49m397v4Z6pnj75h0UFYvD3NoEI0cPQ4kSJZCSkoKL5y/B2twenz59xoK5i3DxyqkC1ZuQiGRTwf8UI6J8lZiYCCN9UyQlJWHq9EmwcbDItFxFRQXNWzRF8xZNpRRh/srL87Fr514AQJt2raFVu2Dc4W/bvjXuPLqW6Tk3Z69frqemroZDx/agSdPMCZ9ixYqhbr06WLl2KWZM1sGF84HYsHYz5i+cAyVlpUxt9+89CABo36Et7JdYZ9pG02aNsXbjCnRu2wPx8Qk4dvSEzCeXtgVsRMfO7X94vlr1qnDxcIS8ggJ2bA3AgX2HYWRqgCpVKovbSPp3KMj278n4+9fUrAHf5R6Z7uZr1a6FZSu90afHILx/F4yjR45nSi79ybmWRbn59/dw9cG7d+8xX1cHnz5+/mVyaYb21CyfL1OmDKbOmARFRUVYmNrgxfNXuH3rLtq0bSVRXPlpxKhhWT5fokQJjBg1DBoaGpg6URtfw7/i7OnzGDbib3GbL5+/wMLEFiKRCObWJtCePS3TNkqWLIF27dugXfs2eXgE+SMtLQ0+nssAAE2aNoLPUndx8lBJSREjRw9DUlISrMzssHnDNkyZNlGcyP2V5KRkHNx/BADQf2CfAjPkXlrvxaEhoQi6fhMAMGf+bEyZNlG8TFFREb37/gUVVRVMHjcD4WHhCLp+E916dMnzuIiocJP920VEJFP27z2E9++CoVGhPEwtjKQdjtTl1fm4dfMOXr54BQAYW4B6LWU1XC0n1NRK/ZBY+p6cnBxGjxsBAIiPT8DLl69+aPPlSxgAoOlPhkuoqZUS92RJiE+QKM78lFWy43tjxo0UP/7vF35J/w4F2be/f8NGDbIcJlK8eHE0bNQAwI9//z8517Iot/7+d27dxab1W1FLSxMLdOfmyjZbtGoufvzp46dc2aa0ZXdMG9dvRXR0NBo3aYiZs7JOvBUWD+8/Eg8Nnzl7epa90sZNGA01dTWkpaXhwL5DOd728WOnEB2dMUy8KHwm/qkvn8PEj5s2z/qztXmLZuLH8QXgM5GIZB+TS0T0W771Dhg4qP8PPUeKorw6H7t27AGQUR9h4OB+ubbdgkxJ6f/nNz1d9MPyGjUy7oA/vP8oy/VjYmLx5vVbAD9PQBUkvzofRU31GtUAAE8eP81UP+mb1NRUPHn8FADQtNnv/f2L4rlOTk6BiZElBEGAk6tdrr2/3Qi6KX5co2aNXNmmtGV3TN8+I4aOGAI5Obl8jSu/hYZ+ED+uW692lm3k5eVRq5YmACDw4pUcb/tbT17NWjWzLMpPmVX/rkfYg3tZfybeu3sfQEbv3sZNCsZEF0Qk25hcIqIcS05OwYP7GXftmzRrjNDQDzBfbI3ObXuifq1maNuiC7SnzcXZM+elG2g+yavzER8fj3+OHAcA/D10YIEoIJwfrl0NApBRLP1bD6TvTZw8TtzO2sIenz5mzDYnCAIePngE7WlzER+fgFatW2QatlJQXf/3fABAg4b1pBiJbJg0ZTwA4N3b99Cbb5SpiO3rV2+wcI4B3r8LRs2aNTDjN3uQFMVzvdTHHy9fvMKYcSP/+Mt8UmIS3rx+i+VLV4nryLVr36bAFGXOSnJyCkKCQ7F5wzYY6mbUDqqpWQO9+vQUtwl+H4LPn78AAJo2bYSnT55Db74R2rfqigZazdCpTQ8snGuAmzduS+UY8lJ2Sdh0UToA4PmzFzna1vt3wbh25TqAzL0Ii4oXz1+if6+/0ahOSzSp1xq9ug2AmbEVHj18/NN1ypcvJx76u3L5amzeuA3x8fEAMhLtp0+ehbG+GQBAe/a0HA9PJCLKDmsuEVGOhYaEIiUlFUDGP3t2Vo6Ii4uHomJxqKiqiOtNnD19HmPHj4KTm32hvlObV+fjyMF/xF3Ux44fnafHUFAEvw/B9i0ZxZoH/T0ApUqV/KHN5GkT8PHjJ6xdtQFbN+3A1k07xLPFpaSkQqNCecyZPwu6+vMK/LCxmOgYrFi+GkBGTY+CUpMrL/Xq0xOWtqZwc/LEsaMncOzoCfFscUlJSVBTV8PEKeNgaKyX5fXzM0XxXD96+BirV6xDeY3yMLM0lmgbYV/C0L5VtyyX9erTs0BMI5+VBrWbIyU55YfnW7dtBZ9l7lBSUhQ/962nJADcvHkHS72XIyUlFcrKylBUUsKnT59x9PBx/HPkBPQNF2Ch/rz8OIQ8U61aVfHj589eZFnXLiUlRZz4jY2JRUJCAlRVVbPd7u6AvRAEAQoKChg5eliuxlwQREREIioqGmpqpRAXFy+e/XTXzr2Yt3A2DBfrZ7mei7sDEhMScfHCJdhaOsLW0lE8W5xIJEL9BvWgt2g+xk7g/xlElDvYc4mIciw6Klr8eLnfSigoKGDZSh88eHYLdx9dR+D1Mxg4uD8AIGDHHqxbs0laoeaLvDofAf8OiWvYqIHMF53OD0mJSZg/Rx+JiYkoW7YMFpsZZtmuWLFiWGy2CK6eS1CiRMaXlfj4BHECMDk5BbGxsUhITMy32POCSCTCIj0TfPkcBiUlJdg6WEk7JJkxQ3sq/Nf4oVz5cgAykkpJSUkAgNSUVCTEJyD236ngc6Ionuu0tDSYGFoiLS0NNvbmEhdOLiYvj/Ia5VFeo3ymYYUDB/eHqYURSpcpnUsR5y+Nf4/p+4RIx07tYWVrhqpVq2Rq+61GEAB4u/uhQsUK2LxjHR4+v4X7T27gxNnD6NCxHQRBgLfHUhz/52S+HUdeaNy0EcprlAcArPJfm+Xw1M0btiHuu9dg3C9ej+np6di76wAAoGev7tCooJF7Acs4zVo1YWphhNMX/8GTV3dx++E1PHx+C5u2rUWTZo0hCAKW+63C2lUbslxfvbQ6Vqz1g7bOdPGNrdiYWIhEGb3KEhISEBERhfT09Hw7JiIq3JhcIqIcEwnC/x+LRHDxcMTAwf1QvHhxAEDVqlXg5+8pLpq7YumqLP+5LCzy4nw8f/YCd+9k1EEoSEVL80paWhr0Fxjh4f1HKF68OLyXuqNipQpZto2IiMSksdNhbGCGlq1bYNf+bbj7OAjXb1/EijV+KFu2DLZt3okRf48VD5kriOytnXD29HkAgN0SKzRsVF+6AcmIxMRELJxrAO2pc1GlamVs2r4WN+9fwc37V7Bp+1rUqVcb+/cewvDBY/Dk8bMcbbMonuuVy9fg8aMn+Kt3Dwz6e4DE2ylXriyC7gQi6E4gHr+8g8tB5zBfVwdnTp3DwD7DsGPrrlyMOv8EXjuDoDuBePj8FoLuXoK51WI8fvQUwwePgbe7X6a2ItH/PyMEQYD/al906dpJXOi6br06WLPRHxoVMhIyft7++XcgeUBBQQEL9TMKv7988QraU+fi4YNHSElJQdiXMKxesQ7uLt7iz0gAkMui6Pf3LpwPxKdPGe/XY8YXrSFxw0b8jdlzZ0JLq5b4nCkqKqJr987YvW8bmjXPmIXW12sZYmJif1j/0cPH6N19ENav2YRJU8bj2OmDePTiNs5fPgkrWzNERUXD3cUL2tPmihNORER/gsklIsqxEiVKiB9r1qqJvv17/9CmWLFimKUzHQAQGRn10+LKhUFenI9vvZaUlJQKRV2gP5Geng6DhcY4eeIMFBQU4L3UHV27d/5peyN9U1y7GoT2Hdpi07a1aNO2FdTUSkGjggb6DeiDXfu3oWzZMnj/Lhhuzp75eCS5x8nBDZs3bgMAWNqaFsn6Iz/j7OiOo4ePQ6t2LezauxVdu3VG2bJlULZsGXTt1hkBe7aglpYmIiIiYWPp8MvtFcVz/eL5SyzzXYESJVRh72Sda9uVk5ND5SqVYLhYH95L3ZCamgorcztxgfWCqnz5ctDWmY6NW1dDTk4OS31X4Mzpc+LlJUv+/zOiU5cOWc6IWaJECUyeOgEA8PTJM4T9O9taQTV56gTM0pkBALh44RKGDBiFBlrN0b5VN7gs8UDValUwe+4McXv1X/SM27U94zOxUqWK6NEz62GWRZGSshKMTPUBZPTQvXLpaqblcXHxmD5ZBx8/fMR83TmwW2KF+g3qQUVFBTVqVsd07SnwX+0LOTk5XDgXiN0B+6RwFERU2DC5REQ5Vum7HiO162j9tF2d72aJ+X72mMImt89HSkoKDu47DADoP7CvxMNRCoP09HQY6C7G0cPHIS8vDy8/12xnzXv54hXOn70IAJmGAHyvfPlyGD5qKADgxLHTEL7reVYQuDi6i4c/mFstxgztwj2t+e+Ii4vHzm27AWR8uc1qZjNlFWVMmTYRAHAz6BbCw7/+dHtF9VzbWDggJSUV8xbOgbq6GuLj4zP9pKVlDJ8RBEH8XGpq6m/to//AvqhStTJEIhF27dibF4eR75q3bIY2bVsBgPg6BJCpl2WdOlnPngYAder+f9mHkIL/mWlmZYxd+7dh5JjhqFe/DipXqYzmLZrBcLEejpzYh2LFMmreVa1WBYqKij/dTlhYOM6euQAAGDlmWIGvlZfbWrVuIX4c/D4k07ID+w4h/N9Epfa/N7j+q3OXjuJZ4gr6kEwikg0s6E1EOVa6TGlUqlRR3EX9Z77/zl6YC3rn9vk4ffIsIiIiARTtIXHfeiwdOXRMnFgaPGRgtuu8eP5K/Di7WW80a9UEkDGEKjz8KzT+rQ8i65wd3LFm1XoAgKmF0U+/LBRVb16/FQ85zcnfHwBC3oeg/L+1mb5XlM91cHDGF1R3Fy+4u3j9tN2H0I9oWr8NgIxeXb+bfKtUqSI+hH7E27fvft24gKhYqSKAjNkKv6lbtw7k5eV/WdMmU567kHxmtmnbSpxw+69vs6y2at0y223s33MQaWlpkJOTw+ixhb/nYG56+e9nYrlyZbOdwECzVk08fPAYIcGh+RUaERVi7LlERL+ly7/Dkl6+ePXTNi+fvxQ/rla9Wp7HJE25eT6+DYmrqVkD7Tu2zaUIC5b09HToLzDKlFj6e+igX65XrNj/v5CFZnPnPzzs/71VvhX9lnVODm6Zkh2z586UckSyJ9PfP5vegd/3Virx3ZClb3iu854gCOIkVsks/gYFVfD7YACZh0srKSuhXfuMJNzLl9l8RrzI+IyQk5NDtepVf9quMAgLCxcP4Rrxb0/Sn9m1M6NnW4dO7bNNGhdVd27fEz/+7/8W3+p6RUREIjGbSSy+fSZ+f90SEUmKySUi+i2jxgwHkHF39uTx0z8sF4lEWPPvcJJKlSqiSdNG+Rpffsut8xEa+gGXAzP+4R49bmSh7vH1M996LB09fPzfGktuOUosAch0Xrdt2Zllm4SEBOzfexAA0KBh/V9Ofy0LnBzcMg3PYrIja7Vra0FZWRkAsGvHniwL56enp2Pntowi0urq6tCqXSvTcp7rjGLVr0Oe/PTn2zTwVatVET/3fa+lnEzgsDtgH8K+ZAzXad+xXZ4cR25KT0//5RDay5eu4t7dBwDww42Bb58RVy5dw8MHP9bci4+Px9bNOwAALVo2Q7lyZXMjbJmUnp4OK1NbpKSkonmLZujWo8tP294IuoXXr94AKJo9eX91zSUnp8DT1QcAoKqqis5dOmRa3vjfz0RBELBtS0CW23j29Dlu3rgNIPMQOyIiSTG5RES/pV37NhgwKKP2jZmxFY4dPSn+QhEa+gF68w3x9EnGTEyGJvriu2eFVW6dj90790EkEkFBQQGj/v0CV1BFR0UjIiJS/PNtxqSkxMRMz8fHx4vX+VZj6cihY1BQUIDPMvdfDoX7XtVqVdGrT08AwJlT57BIdzHevX0PQRCQmpqKWzfvYPzoqXj/LqN3gbbOtNw74Dzyfd0fCxuT3x6eJcnfoaBSVlEWfwF9+OAxZk2bh6dPnkMkEkEkEuHJ42eYMUUHt27eAQBM156cqX7Ln55rWSSNv//NoNsYO3IS9u85iI8fPmVa9ub1W7g6ecLS1BYAULNmDYwaPTzX9p1XPn74hMH9RmD71gC8fxec6Uv/hw8fsWLZGujMWABBEFC6tDpmzso8RHDoiL/RvEUzCIKAebP1cPnSVfHMXC9fvMLs6fMR9iUcxYoVg6GJfn4eWp54/y4YHq4+ePjgEZKTkgFk3GS5eeM2pkzQxskTZ6CmrgZ3b6dsb6Ls+rcnb+nS6ug3oE++xJ5XJHktBl27gUnjpv/wWkpNTcXlS1cxdsQk8cyyC/Xn/lCjccCgvqhQUQMA4OHqjeV+KxEZmTHsPiEhAYcPHsXUidpIS0uDomJxTJ42IU/PAREVDay5RES/zd3bCV/DvyLof+zddVhU2R/H8TchYYC6tq69dueqa6yu7drdrYASAgLS3Slgd3fr2l3Y3S22IN0zvz9QfmI7DMyA5/U8Pg8w99z7veO9E+ee+zmnz2IwyQgNTQ20tbSJiorKWMbQxCDjKndel9XnQyKRsH5t+kwt7dq3oUTJEl9cLrfo0aXvF29Nmzt7IXNnL8z4vd+A3nj7uwNw7sx5tm/ZCaTfGuJg64qDretXt2HnaPVZ55Onryujh0/g6uVrbN64jc0bt6GtrU1KSkqmERUTJ4+lb//eWdnFbBce/izjuVJVVWVO6ALmhC746vITJo1hwuSxmf4my/9DbmYxw5SHDx5x+NDRjH8amulhwclJyRnL/durOwaGkzN+l8dzrYwU9f9/5vQ5zpw+B6TPelmgQH7i4xNITEzMWKZmrRrMWRCMlraW3LabnW5cv5nRKaahkY+CBQuSmJhEfHx8xjK/ly9H6NxAipconqmtqqoqcxcGM3zwGO7cvseIwWPR1tZGPZ86Me+nj8+XLx+OLja0bJV59EluFBsbS+jMOYTOnAOkjxKMj4/PCH4vU7Y0s+fPzBRi/qmYmFh2bt8NQO++PdHU/Hrod24gy7kolaaPdjtx7BQAWlpa5M+vTUxMbMZzqaqqymSDCUzSH//ZuvPnz8+c+cGMH63H27cR+HoF4usVSMGCBYiLi8/oJNXW1sbb351KlSvKe7cFQfgFic4lQRB+Wv78+Vm5bgnrVm9g04at3L51h7i4eEqVKkmT5o0ZNWY4jZt8O6gzL8nq83H86EmehT8Hfs3h/0DGlVxIvzL75jvTcSe+vyL+saJFi7Bx62o2rNvMru27uX79JlHvolBTU6NM2dI0atyAIcMH0bRZY7nXL2/Sj54PiUTy3ecjLi7+m4//CrS0tVi4bA67duxhy6ZtXL18jbdv34KKyvvZqurSf1Af2ndol6mdeK7lp0692vgFenLqZBhXLl/j9es3vIt8h4aGBhUqlKd23Vp06daRrt0755qZv0qULE7w7ABOnwzj4sXLvHrxisjISFRV019XataqwT+d2tOrd4+vdpYVL1Gcrbs2smzxCrZv3cWDBw9JSkyk3O9ladGyOWMnjKJ6jWo5vGfZo1y5skw11uf0yTAePXxMZGQkBQsWoHLVynTu2pFhIwahra39zXVs37IzIydo4C/6nli95h/MsJ3O+XMXuXXzNpERkURHx6ClrUXVP6rQtFljBg8bSI2aXz9u6jesx55D21mxdDUH9x/m/r2HxMbGkj+/Nr+X/52Wf/3JyNHDRJ6VIAhyoyL9gbmYo6Oj0dXVJSoqCh2dX3dqbEFQtC5duqCqDiFzAhRditK7cvkavbr1JyjU96dur/pVTR4/lbNnznP20nFFl6L07ty+S+f2/+Li4cDQ4YMUXY7SM55izpFDRzl/9ZSiS1F6T5+E06bFPyJM/AdZmduyc8duLl0PU3QpSu/16zc0b9iaKUaTmWZupOhylF63jr1JSUlh76Edii5F6cXGxlGvRhNWr17NoEHiPVEQ8pqf6QvK22EogiAIgiAIgiAIgiAIQrYSnUuCIAiCIAiCIAiCIAiCzETnkiAIgiAIgiAIgiAIgiAz0bkkCIIgCIIgCIIgCIIgyEx0LgmCIAiCIAiCIAiCIAgyE51LgiAIgiAIgiAIgiAIgsxE55IgCIIgCIIgCIIgCIIgM9G5JAiCIAiCIAiCIAiCIMhMdC4JgiAIgiAIgiAIgiAIMhOdS4IgCIIgCIIgCIIgCILMROeSIAiCIAiCIAiCIAiCIDPRuSQIgiAIgiAIgiAIgiDITHQuCUIukpqaqugSBEEQBEF5SBVdgCAIAFKpOBkF4VcnOpcEIReQSCQsWbKEY8eOcerEabZv3SnexL/h2bPnhM6cA8Calet58fylgitSXlKplK2bdxB26gzRUdFs3rAViUSi6LKU1quXrwgOnAXA5o3bCH8aruCKlJdUKmXn9t0cO3qC2NhY1q7eII6tb3jz5i2BfsEA7Nj+H48fPVFwRcpLKpWyb88BDu4/THxCPCuXryEtLU3RZSmtyMhIAnxmArB3zwHu33+g4IqU2+GDR3n8+AlPHj9lycLlpKSkKLokpRX1LgpfzwAAXN1cuXbtmmILEgRBoUTnkiAouVOnTtH8z+aMHj2aP1s2I59GPgz1TRnQeyhXr4g38Y8lJCQQ5B9C+7+6cGDfQapX/4NTp8L4+69OBAfOIjEhUdElKpUrl6/Rv9cQjKeYoa6ej8JFCjPNyIK+PQdz6cJlRZenVJISkwgNnku7Vp3ZtWMP1ar/wcXzl2jfuiv+PjOJj49XdIlK5cb1mwzuN4Ipk41BKqXob79haWZDz679OHvmvKLLUyrJycnMn7OIdi07snnTNqpVr8qN6zf5p203vNz9iI2NU3SJSuX2rTuMGDKWiWMNSE5OpkTx4thYOtCtY29OnQhTdHlKJSUlhcULltG2RSfWrt7AH9Wqcv/uAzr93QM3Zy+io2MUXaJSuX/vAWOGT2TMiImoqalRvHgxHO1c6dqhF0ePHFd0eUolLS2NFctW07ZlR5YvXUnTZo2Jjoqifv36GBoaEhERoegSBUFQANG5JAhKKjw8nBEjRtCiRQsSEuJZvX4pi5bN5dS5I5hbmXDj+k16dRuApZktb968VXS5CiWVStmxbRftW3ch0D+EmrVrcOjEXnbt38qh43upVr0a/j4zad+mCzu37/7lR329fvWa6abW9O4+gJs3bmNpY07YxaOEXTiKrYMVd2/fpc+/gzA1suDli1eKLlehpFIpu3ftpUObrvh6BlClaiUOHNnFf/u3cvTUfurUq01w4Cz+/qsLWzZt/+WPrbdvI7C2tKdH575cuXyNaeaGnL18glPnDuPkZsejh08Y2GcYhvqmPHv2XNHlKpRUKuXA/kN0bNcddxdvfi//O3sObue//ds4efYQjZo0ZO6sBbRr2ZEN6zb/8qO+3kW+w9HWlW4de3PuzAWmGOlx9vIJjp85iJevKy+ev2DowFHoTTDkyeOnii5X4Y4ePk6XDj1xsnejZKkS7Ni7md0HtnH6/BFatGzOwnlLaNuyI6tXrP3lR31FR0Xj6uRJp/Y9OHniNBMmjeXC1VMcPb2fgGBv3rx9y6ih4xk/Wo+HDx4pulyFO3n8NN069sbWypEiRYuwZcd61mxczu6D2zG3NGHRokX88ccfhISEiDgHQfjFqEh/4JNwdHQ0urq6REVFoaOjkxN1CcIvKyEhAV9fX9zd3dHW1sbMwoj+g/qipqaWabnExERMjSzZs3sfmhoaGJtOZeSYYWhoaCiocsW4dvU6DjYunDt7gRIli+Mb4Emr1i0+W+7I4WOYG1vx+vUbmjZrjL2zNbVq11RAxYqTlJTM4gVLCfIPJSUlhS7dOuHl54qWllam5ZKTk7EwtWHHtl2oqasx1VifceNHoamlqaDKFePmjds42bly6mQYv/1WFC8/N/7u0Paz5U6dCMPEcDovX7ykQaP6ODjbUK9+HQVUrDjJycksW7ISf5+ZJCUm0aHj3/gFeZI/f/5My6WmpjLDwp4tG7eioqKK3pSJTNQbi7a2toIqV4y7d+7hbO/O0SPHKVKkMK6eTnTp1vGz5c6fu4CRvhnh4c+oU7cWDi42NGrcUAEVK05qaiorl6/B1zOA+PgE2rb7C/+ZPhTSKZhpubS0NBxsXFi7egNSpEzSG8dkgwkUKFBAQZUrxoP7D3Fx9ODg/sPo6urg6GpLz949PlvuyqWrTNUz4fHjp1SvUQ1HFxua/dlUARUrTlpaGmtXbcDLw4+YmBhatvqT4Fn+6Ohm/q4jkUhwdfJkxdLVpKWlMW7CKAyM9ChUqOBX1pw3PXn8FFcnT/b8t49ChQpi6ziD/gP7fLbc61ev8fEMYP3aTdSqVYvAwEA6dOiggIoFQZCHn+kLEp1LgqAkpFIpGzZswMzMjGfPnjFq7HCmGOmho1Pom+0ePHiI/gQjbt+6Q7nfy2LnNIP2HdqhoqKSQ5Urxps3b/HxCGDdmg1oaWkyxVgPPYOJ320XHDib0JlzSEpKYtDQ/phON+a334rmQMWKI5VK2b/3IE52boSHP6NGzeqEzg2gQsUK32z39Ek4ehMNuX71BqVLl8LW0YpOXf7J88dWREQk/t5BrFy+Bk1NDSbpj8do2pTvtps3ZyEBvsEkxCfQf2AfzC1NKF6ieA5UrFiHDhzB0c6VRw8f80e1KoTODaJK1crfbPP8+QsMJhpx6dIVihcvho29Jd3/7Zrnj62od1EE+oewdNEK8uVTZ8z4UZhZGKOq+u2B5EsWrcDbw4/4uHh69fkXixmmlCpdMoeqVpzjx07iYO3MvXsPqFS5IiFzA6lRo9o327x+/YYpk4w5d/YCRYsWYYbtdHr26fHd5zi3i46OISRwNgvnL0FNTY0Ro4ZgZTv9u/u9ZuU6XJ28iI2NpVuPzljZmFO2XNkcqlpxTp8Mw97Ghdu37lC+wu/MnOVP3Xq1v9nmXeQ7DCYbc/rkGXR0dbC0NqP/wD55/tiKi4tjVvA85s5egAoqDBzSH0cXm+/u95XL13C2d+PsmfP07t0bHx8fqlSpkkNVC4IgL6JzSRBymYsXL2JsbMzhw4dp/087ZthNp3LlSj+1jt279jJjuh2Rke/4q3VL7JxmUPWPvPcmnpyczNJFKwjwnUlScjKdOv+Db6DHZ6NvviU+Ph5TI0v27TmAppYmJmZTGTFqaJ4c9XX71h2c7N04cewURYsWwcPHhX86tf+pdRw6cATzaTN4++Ytzf9sip2TNTVrVc+mihUnJSWFFUtX4+sdSGJCIn93aItfkBcFC/74yIfExESmT7Pmv517UFdXx2iaAaPHjURTM+8dW/fvPcDZ3p3Dh46iW1gXVw9HuvXo/FPrOH70JKbGFrx6+ZpGjRvg4GJDnbrf/oKXG6WmprJm1Xq83f2Ii4vnr9YtCAr1/2z0zbckJyczw8KerZu3o6aqioHhZMZPHIOW9o+/9uUWjx4+xtXJk317DqCjo4Ojqw29+vz7U+s4E3YOYwMznj9/Qd36dXB0tqFBo/rZVLHipKWlsX7tJjzdfImOiubPls0InuVP4SKFf3gdqamp2M1wYsO6zQBM1h/PJIPxn408zAvCn4bj5uzNrh27KViwADb2lgwc0v+n1nHhwiWM9Ex5+jScWrVr4OBiS5OmjbKpYsWRSCRs3rgVd2dvIiPf0bhJQ0LmBlKs2G8/vA6pVMr2rTvxcPXh7ZsITExMsLa2plChb184FQRBeYjOJUHIJV6/fo21tTULFiygUuWK2Nhb0vbv1jKvTyKR4OsVyMJ5S0hJSWHkmGEYmRigW1hXjlUrxod8Eic7N54+Cada9T8InRdIpUoVZV7n/XsP0JtgyJ3bd6lQsTz2Tta0a99GfkUr0LvIdwT4BrN86Sry5cvHBL2xGE+bkqUrrIF+wcwJXUBSUhJDhw/CxNyQokWLyLFqxTly6BiOdq48uP+QKlUrEzI3kGrVqsq8viePnjB5oiE3r9+iTNky2Dla8U+n9nliZE50VDRBAaEsXrAMdXV1Ro0djsUM0ywdW7ND5jEzIJTExCQGDOqLqYUxxYsXk2PVinPy+GnsbZy5e+ceFStVIHiWP7XqyH5Lbnj4cwwmGHLlyjVKliqBjb0VXbt3yhPHVmxsHCFBs1kwdzGqqioMHT4IGwerLB1bi+YvxdcrkPj4ePr068l0K1NKliohx6oV50zYORxsXLhx/Sblfi/LzFB/6jesK/P6Xr96jd5EIy6ev8RvvxVlhp0FPXt3zxPHVnx8PHNC5jM7dD4A/Qf2wdHVFnV1dZnXuXL5GtxdvImLjaN7z65YWptRtmwZeZWsUBfPX8LOxpmrl69RukwpAoJ9aNqssczrS0hIYE7oAubOmk/hwkVwd3dn5MiReX7UlyDkBaJzSRCUXHJyMiEhITg6OgJSjKZNYdjIweTLl08u64+JjsXIYBpHjxynQIECmFmaMHjogCx9iFKku3fu4WTnxrGjJyhSpDBuXk507vp5Pomsdu3YjbWFPe/eRdGm7V/YOlp997YeZfXFfJJgXwoVkk/uSFxcHNMMp3Ng32G0tLWYZmbI8FFD5Hbs5rQH9x/i4uDOwQNH0NHVwcXdnh49u8lt/fv2HMDSzIaIiEhatGqOneMMqn/nth5llZFP4u5LTEwsrVq3YGao32f5JLJKTEzEzNiK3f/tRSOfBsamUxg1dniuHVH4+NET3Jy93ueTFMLW0eqL+SSyOnr4OGYmlrx+9YYmTRvh4GKTa3PkJBIJG9dvwcPFm3fvomjavAkhc/wpWlQ+tywnJydjaWbD9q3pOXJTjPQYP2F0rs2RCw9/hoeLNzu2/UeBggWwsjFn6PBBclt/eo6cOS9fvKJBw/rYO1tTv4HsnVaKJJVK2bJpO27OXkS8jaBh4/qEzgmU2y3Lqamp2Fg6sGnDljyRI/fi+Uu83P3YvHEr+fPnx9zSmFFjR8ht/eHhz/B082X7lp00adKEoKAgWrT4PCdTEATlITqXBEGJ7dq1CxMTY+7cucuQ4QMxMcu+0R83r99Ef5IxDx88ouofVXBwsaFlqz+zZVvZ4dN8krETRmM63ShbrnRJJBK83H1ZsnA5KSmpjB43AkNjfbl9cc4Jx46ewNHG5afySWR198499CcaZYzGcHC2oU27v7JlW9nh83ySoVjZmmfbsRXgF8y8WQtJSUlh2IjBGJtNoUiR3DPq69N8kuDZAdSpWytbtvVZjpzjDNr/k3ty5D7NJxk0dAAOztbZdoU+JGg2IUG5N0fu3NkLONg4c+3qDcqWK0NgiE+2hZZ/nCNXqlRJbB2t6Ny1Y645tj6M/pgdMg+pVErf/r1wdrfPtgtH8+csxt83iIT4BPoN6I25pQklSuaeUV+XLl7BwdaFSxcuU6p0SQJmemdbaHlGjtzFKxQvUQxrOwt69OyWa46tpMQk5s9bTHDgLNJS0/i3Z1fcfVyyrXM/7PRZnO3duXb1OsOGDcPDw4Ny5cply7YEQcga0bkkCEro1q1bmEwzYdfOXbRo2RwbB6scy63ZuH4LjnauxETH0LFzB6ztLChf4fcc2bYsUlNTWb1yHT4e/sTFxdG6TSsCQ/x+Kp9EVtFR0UzVn8bxoycpVKgg5lbTGDSk/2ez9SmThw8e4erkyf69B2XOJ5HV9q07sZ3hRNS7KP5u3wZrB8ufzgvLSfLIJ5FVbGwcxlPMOHzw6PuZII0ZOmKQUo8ofPokHDdnT/7buZeChQpiY2fx0/kkstq9ay8zLOyJjIikVesW2DnO4I8s3KqY3eSRTyKrT3PkjE2nMnK0cufIPX/2Ag9XH7Zt2UGBAvmZPsOUEaOG5si2Dx88irmJFW9ySY7ch9waF0dP3rx+Q4OG9QidG5Qjt/clJiZiYWbDru27UVdXx9BEnzHjRyl1jtyrl6/w9vBnw7rNaOfXxsTUkPGTRufItk8cO8k0I0tevXxFw0bpOXLfCwpXJKlUyn879+Li4M6LFy+pXacWoXMDKfd79oe6f3g//jDS2tLSEjMzs1w76ksQ8irRuSQISuTdu3c4OTkxc+ZMSpcuhZWtuUKulEokEhzt3Fizci0SiZQJk8eiN2XiT4UV54QTx0/hYOOSMSImdE4ANWrVyPE6rl65ztTJxjx69IRq1f/AwdmGP1s2y/E6viU78klkIZFIcHfxYdniFaSlpTFm/Mgfmukwp8k7n0RWN2/eZsokY+7fe0DlKpVwcLHhr9Ytc7yOb4mPj2d2yDzmhM4HVOSSTyILiUSCn3cQC+YuTs+RGz0Mo2nKlyN34dxF7G1duHr5GmXKlCYwxIfGCgj4vX/vAfoTjTJGmNk7WfN3h7Y5Xse3JCYkMm/OQkJnziEtTUKvvv/i7uWkkE7WIL8QZofOJykpiSHDBjJtupHS5chduXwNBxtnLpy/RMmSJfAN8lTICORMOXJlSmPraEXHzh2UamROUmISC+cvZWZAKKmpqXTt0RlPH5efmvBDXmaHzmemfyiJiYn0H9QXMyXMkbtx/SaOtq6EnT5LseK/4e3nnqXcT1nFxMQSEjiLRQuWUaZMGby9venfv79SHVuC8CsTnUuCoATS0tJYsGAB1tbWxMfHo284iXHjRyk84+HNm7cYTDLm3JnzFClSGCtbc3r37anwUMXszieR1brVG3B29CA2JpYu3Toyw9YiR67ofUt255PI6l3kO6bqTePkidMU0imE5QxT+g/qq/BRX9mdTyKrLZu2YW/tQnR0NB3+aYe1vSUVK1VQaE3ZnU8iq09z5EwtjBkybKDCR31ldz6JrHbt3IP1dDulypGTSqXs2rEbZwd3Xr18Td16dZg1P4jSpUsptC5lzZF7/eo13p4BbFi7CS0tLaaa6DNZf7xCa4L3OXLmtkS8jeDPls2xd1J8jpxUKmXv7v042bvz/Nlzatauwaw5gfyu4BHan+bIGU0zYNTYEQof9fX2bQT+3kGsWrEWTU1NJhtMwNBEX6E1QXoGopuzF/v3HqRNmzYEBgbSoEEDRZclCL880bkkCAp2+PBhjIwMuXTpMn3798LccprSzU5z7sx5jAzMePbsOXXq1cbR2YaGjRvkeB2xsXHMCp7LvDkLUVVRYeCQ7M0nkUVqaioONi6sW7MRKVIm6Y1jssEEChTI+VFfmfNJyhI0y5eGDZVreu0rl64yRc+EJ4+fUqNmdRxcbGjWvEmO1/Ehn2RW8FyAbM8nkYVEIsHF0YOVy1aTliZh3MTRGBhOplCh7L8F9FOXLlzG3taFyxevZHs+iawy5chVrYyDq61CRnEkJiSy4EM+SZok2/NJZCGRSPB292PxwmWkpKQyauxwjEwMFJIjd+3qdRxsXDh39gIlShTH29+d1m1b5Xgd3/Jpjpy9k7VCRnEkJSWzZOEyAv1CSElJpnPXTnj7uylk9M3XSCQSgvxDmDNrAclJyQwfOURhOXK3bt7G0c6NUydOU/S3Inj5utH+n3Y5Xse3PHzwCP2JRty6eZuy5cpg72StkBy5lJQUli1Zib93EImJSbT/px3+M73Inz9/jtbxPUcOHcPF0YN7d+8zbtw4XF1dKVFCuT5DC8KvRHQuCYKCPHz4EHNzc9avX0+DhvWxc7SiQSPl+uL/qSWLVuDt4Ud8XDy9+vyLxQxTSpUume3b/SyfpGkjQuYE5Eg+iaxev3qNwSRjzp+7SNGiRZhhO52efXrkSEeYIvNJZLV65VrcnLyIjY2jW4/OWNmYU7Zc9o/6kkqlbNuyE1ennM8nkVVERARTJpsQduosurq6WFib0n9gnxw5tl69fIWXux8b129BO782puZGjJ0wKtu3mxWKypH7NJ+kTt1ahM6bSdmypbN927KKjorGUN+UY0dPULBQQabnYI7cmzdv8fUMZO3q9WhpaWJgqIf+1InZvt2s+DhHrl37NtjkUI6cVCpl/96DONm5ER7+jOo1qjFrXiAVKip2NOO3xMbGYTLFjEPvc+RMpxsxdMSgHBn1FRkZib/PTFYsXY2GpgaT9MZhaGKgVBemPrVn936szG0VkiN3+OBRHO1c0zvmq1UhdE4gVf+okiPblkVKSgorl60hwHcmUinY29szZcoUperAF4RfhehcEoQcFhcXh4eHB97e3hQuUhgLq2k51ukgD8nJycwwt2Prlh2oqaliYDiZ8RPHoKWdPVdKlSWfRFZhp85gPHU6L56/oF6Dujg621C/Yb1s2VZCQgLzZi9kVvBc0iQSevVRXD6JLFJTU7Gb4cSGdZsBmGwwgUn647LtSumn+SR+QV60aNU8W7aVHS5cuIShninhT8OpVbsGDi62NMmmcyMpMYkF85cQHDCL1NRUuv3bBS9f11zz4f1DjtzqlWuRSqSMnzQG/amTsi1H7sb1mzjYuHAm7JxC80lkdfXKdabqmfDo4eNsz5FLTk5m6aIVBPjOJCkpmY6dO+AT4K50IyS+RiKR4OHqw9JFOZMjd/vWHZzs3Thx7BRFihbB3duZTp07ZMu2ssPt23fRn2CYniNXuRL2Lta0bpM9I9M+dDr4egWSkJBAu/Zt8J/prXT5kV/zaY7ciFFDMZpmkG2TSty/9wBne3cOHzqKbmFdXNzt6f5v12zZVnaIiIgkwHcmK5etoWrVKvj7B9CtWzdFlyUIvxTRuSQIOUQqlbJy5UosLCx48+YN4yeNVtjtUvIQHv4c/QmGXL1yjZKlSmBjb0XX7p3kNnT7xfOXeLr5smXTNvIXyI+5hQmjxg6Xy7oVYeG8Jfh6B5IQn0Cffj2ZbmUqt9ExUqmUndv/w8XRIz2fpH4dZs1TfD6JrF6+eIX+JCMunr9EseLF0kd99e4ut2Pr03wSo2kGTNQbJ5d1K8LyJavwdPMlLi6OHj27YWljRpky8hkdI5VK2fPfPpzt3Xn+/IXS5JPI6s2bt0yZZMzZM+cpXFgXK9vp9Oknvxy5t28j8PMOZPWKdWhqaqI/dSJTjPTksm5FWLdmIy4O7sTExNK5a0dm2E7n9/LymQJcKpVy8MBhHG1defL4KdWr/0Ho/CAqVaool/XntHeR75iqP42Tx9Nz5CyspjFgcD+5jfp6F/mOQL8Qli1ZSb58+Rg/aQwmZlNzzYWpT23dvB07a2eio6Jp/087bOScI3f0yHEcbVy5fz99MoTQeUFUU+IZJL8lJjoWoymmHD18jPz582NmaSLXHLnoqGhmBs5i0fylqKurM3LMMCytzXLtsXXzxm1cHNw5cfwUnbt0JsA/gBo1cn6yF0H4FYnOJUHIAWFhYRgZGXLq1Gm6du+MpbWZ3D6gK9qRw0cxM57Bm9dvaNqsMfbO1tSqXVPm9SUmJDJ/7iJCgmaTliahZ6/uuHk75ZoREt+SnJyMhakNO7btQk1djanG+lkObv84n6R4ieL4KGE+iaxOnQjDxNCcly9e0aBRfRycbahXv47M60tKSmbxgqUE+YeSkpJMl26d8PJTrnwSWaWmpjLDwp4tG7eioqKK/tSJTJg8NkvTNN+8cRtHO1dOnwzjt9+K4uXnpnSzicnq3JnzGE0x41n4c+rUrYWDiw2NGjeUeX3Jycnp+SQ+M0lKTKJDx7/xC/LMNaNvviU1NRVHW1fWrt4gtxy5u3fu4WzvztEjxylcuDCuXo507dZJjlUrzpVLV5mqZ8Ljx0+pXqMaji42WcojS01NZeXyNRlTsLdp24qAYF8K6eR81pq8SSQSXJ08WbF0NWlpaYybMAoDI70s5cg9uP8QF0cPDu4/jI6uDk6utvTs3UOOVSvOzes3MZhkwoMHD6lStTIOLja0+quFzOtLS0tj7aoNeHn4ERMdQ8u//iR4lr9Cstbk7UNwu6uTJ8+fvWDKlCnY2dkpJOtLEH4lonNJELLR8+fPsbKyYsmSJdSoVR07hxlKN0W9vAQHziJ05lySkpIYNLQ/ptON+e23H5+RLH12oD24OLrz8sWrXJFPIqunT8LRm2DI9Ws3KF26FLaOVnTq8s9Pjcx58+YtPh4BrFuzAS0tTaYY66FnoNz5JLKaN2chAb7BJMQn0H9gH8wtTX5qRrJP80lq1KxG6FzlzieR1fPnL9CfaMTli1coXqIYNvaWdP+3608dWxERkfh7B7Fy+Ro0NTWYpD8eo2lTsrFqxZFHjtyhA0dwtHPl0cPHuSKfRFavX73GYLIx589epEjRIljLkCMX9S6KQP8Qli5aQb586owZPxIzC5NcO0LiW9asXIerk2eWcuSOHzuJg7Uz9+49oFKlioTM8adGrbw3AiMyIpIpk004feoMOro6WFqb/XSO3Icp6hfMW4KamhrDRw5mhp1Fnjy2Nq7fgpOdK9FZyJE7fTIMexsXbt+6Q/ny5Zg5y5+6Wbh4o6ySEpNYOH8pIUGzyZ8/Py4uLowfP17hM9MKQl4lOpcEIRskJiYSEBCAq6srGpoamJobMXCI/IbHK6v4+HhMjSzZt+cAmlqamJhNZcSood8ddXT92g0cbV3f55MUwyfAjTZtc08+iawO7j/MdFNr3r55S/M/m2LnZE3NWtW/2SZTPklyMp06/4NvoEeeGH3zLYmJiUyfZs1/O/egrq6OoYk+Y8aP+u40zZ/mk3j6uPBPp/Y5VLXiHD96ElNjC169fE2jxg1wcLGhTt3a32yTkpLCiqWr8fUOJDEhkb87tMEvKPfkk8gqI0du6w7UVH88R+7TfBJXD0e69eicQ1UrzpmwcxgZmPHi+Qvq1q+Do7PNdyejSE1NZc2q9Xi7+xEXF8dfrVsSFOqfJ0bffMtnOXL645lkMP67I9oePXyMq5Mn+/YcQEenEPbONvTp1zMHKlasCxcuYaRnytOn4dSsVQMHFxuaNmv8zTZpaWmsX7sJTzdfoqOi+bNFM4Jn+2dbLpGykEgkONm7sWrFz+XIPX0SjruLF7t27KFgwQJY21kyaGj/HKpacV6+eIWPpz8b1m2mXr26BAYG0a5dO0WXJQh5juhcEgQ5kkqlbN68GTMzUx4/fsLIMcMwNNbPE0OMf8b9ew/Qm2DIndt3qVCxPPZO1rRr3+az5d6+jcDXK4A1K9fniXwSWQX6BTMndD5JSckMHT4IE3NDihbNPHRbKpVyYP8hnOzc8kQ+iawePXyE/kRjbt64RZmyZbBztOKfTu0/G5nzLvIdAb7BLF+6inz58jFh8hiMTXNvPomsZoXMJThgFomJSQwY1A9TCyOKFy/22XJHDh3D0c6VB/fTb7cImRuYa/NJZBUe/hyDCYZc+U6OXHRUNEEBoSxesAx1dXVGjR2OxQzTX+7YWjR/Kb5e6bdqfStH7uTx09jbOHP3zj0qVCxPyOwAatWR/dbp3OjjHLnfiv2GtZ3FF3PkYmPjCAmazYK5i1FRVWHosIHYOs745Y6t5UtX4emaniPXvWdXLK3NKFu2zGfLnQk7h4ONCzeu36Tc72UJCvWjQTZNmKGs3r6NwGCSMWfDzn0zRy4+Pp7ZIfOYE7oAgP4D++DoaptrJvyQl0sXLuNk786F8xfp168f3t7eVKqU/TM8CsKvQnQuCYKcXLlyBWNjYw4cOEC7v9tgbW9BlaqVFV2WQu3cvhsbS3vevYuibbvW2DpaUblKpc/ySf7p+De+eSSfRFaxsXFMM5zOwf2H0dLWwtTciGEjB5MvXz7u3rmHk50bx46eoEiRwrh6OtIlj+STyGrfngNYmtkQERFJi1bNsXOcQfUa1T7PJ2n3FwEzffL8CIlvSUxMxNTIkj2796GpoYHRtCmMGjscDQ2N9HwSB3cOHjiS5/JJZPW1HLmMfBJ3X2JiYvNUPomsvpUj9+TxU1ydPNnz3z4KFSqEraMV/Qf2UXTJCpUpR65hfRxc0nPkJBIJG9dvwcPFm3fvomjarDEhcwMoWvTHby3Paz7NkdObMpGJeuk5cuHhz/Bw9WHH1l0UKFgAKxtzhg4fpOiSFerc2QsYGZjxLPxZphw5qVTKlk3bcXP2IuJtBA0a1WfW3MCfurU8r/nwnHi6+fIu8h1mZmZYWlpSsOCv+zlBEORFdC4JQha9ffsWW1tb5syZQ8WKFbC2t8gzobfyIJFI8HTzZcnC5aSmpjJoSH9OHD/Fo4eP+aNaVWbNC6JyFXHV6IPbt+9iMNGIe3fvU6lyRZr/2ZS1qzeQL586YyeMxnS60S93FftrJBIJAX7BzJu1kJSUFAYM6suZsHPcv/eASpUrEjI3kBo1qim6TKXx4MFD9CcYcfvWHcr9XpbWbVuxZuV61NTUGDFqKFa25uLY+sjHOXJ9+/fiyuVr6fkkFX4neHYAderWUnSJSuPTHLn2HduxeuU6VFBh0NABODhbi2PrIx/nyPXu25M7t+9w7eoNypYrQ2CIT5bC5fOa589fYDDRiEvvc+S6dO3E6pXrkEol9OnfGxd3+19u9M23fJwj16NnN548ecqlC5cpVbokATO9sxQun9fExcUxJ3Q+82Yv4rfffsPDw4Nhw4aJ1ypByALRuSQIWeTm5oa9vT0W1qY/lC/0q4qOimaq/jSOHz2JhoYGPgEev0Q+iay2b93JDAt74uPiad3m18gnkVVsbBzGBqYcOniUfPny4e7tRO++eT+fRFZ7/tvHdFNrYmJiaNGyOcGz8n4+iaw+5Mjt3bMfdTV1nFxtGTgk7+eTyOrg/sOYGVvy7l0UjRo3YNb8mRQr9puiy1JKH3Lkdu3YjaqqKjPsLBg1Zpiiy1JaJ46dRG+iEbExsdSrX4dZ82dSqtTPhe//KpKTk5kx3Y4tm7ajnk8dU3Njxk8areiylNbTJ+HY2zhzcP9hnj17RunSeW8iGUHIKaJzSRCyyM3NDX9/P8IuHlN0KblC9Ur1+LtDW2bPn6noUpTe/LmL8HDx4e7ja4ouJVeoV7MpjRrVZ/GK+YouRemtWLYaWytH7j+9oehScoUm9VtRuUol1m5cruhSlN7G9ZsxM7bi8s2zeT4MXh5a/9mBokWKsGXXekWXovRcHT1ZMG8xF6+HoaNTSNHlKL261RvTu29PnN3tFV2K0juw/xDjR+mJziVByKKf6QsSYwQFQcgyFRWVn5oW/VcmnqufI56vH5f+XCm6itxDVVVVHFtCthDHlpBdVFRUxC1egiAoLfHqJAiCIAiCIAiCIAiCIMhMdC4JgiAIgiAIgiAIgiAIMhOdS4IgCIIgCIIgCIIgCILMROeSIAiCIAiCIAiCIAiCIDPRuSQIgiAIgiAIgiAIgiDITHQuCYIgCIIgCIIgCIIgCDITnUuCIAiCIAiCIAiCIAiCzETnkiAIgiAIgiAIgiAIgiAz0bkkCIIgCIIgCIIgCIIgyExd0QUIgpAuJiaWFUtXsW/PAR4+eERsbCxFixalYqUKNPuzKWPHj0RHVydj+YSEBE6fPMPVK9e4euU6V69c41n4cwAMTQwwNp2iqF2RSVb258Xzl+zds59TJ8K4fvUGL168BKB4iWI0aFSfwUMH0LLVn19tHx0VzelTZ7h6+RpXr6Zv+/WrNwB4+bnRf2AfOe5pzsiO48Pa0oFVy9cAULZcGY6e2i/XmhWlcrmaP7zsny2asXLdkkx/C/ANJsg/5LttDxz9j4qVKvx0fTktK8fO6ZNhHD1ygiuXr/L40RMiI98RHxePrq4Of1SrSqcu/zB46AC0tLW+W8fDB49YsWw1Rw8f49mzF6SlplGs+G/UqFmdv9q0ZMSooXLb5+wUGRnJvj0HOXHsFNeuXif86TPS0lIpWrQodevXoW//XnTu2vGb6wg7fZZli1dw7swFIiIiKFSoEDVqVWfAoH707N09h/Yk52Rlf1+/fsPcWQs4sO8Qz8Kfo6WlxR/Vq9Kvfy8GDumPiopKDu1F1mXlXMzq69LTJ+GcDTvHlSvXuHblOtev3SA2Ng6AIyf3Ue73sjLulfKYFTwPbw+/jN/vP72RI22VgTw+I8j7XBszfCKHDx0FoPmfTVm1funP75ggCAolOpcEQQmcPH4aoylmvHmd3qGhoZEPLW1tXrx4yYsXLzl1MoxOXTpQ66POpUsXrjB25CRFlSx3su7Ps2fPad28A1KpNONv2traSKVSnj4J5+mTcLZv2cmAQX1x83JCTU3ts3Xs2b2f6dNmZKl+ZSPv4+Pk8dOsXrFWbutTJsWKF/vm46kpKbx7FwVAvfp1vrpcvnz50C2s+9XH1dVzx1tuVo6dubMXcnD/4Yzf8+fPj4aGBm/fRvD2ZBinToaxaMFSFi2fS+XKlb66noXzl+Dl7kdyUjKQfk6rqqrw5PFTnjx+yqmTYbmmc6l5wzakpqZm/K6pqYm6er6M1/e9u/fT9u/WhM4NRFtb+7P2nm6+zAmdn/G7jq4O0dExHD96kuNHT7Jz+38Ez/bPNcfX92Rlf69cvsboYeOJjHwHQIEC+YmLi+Ns2DnOhp1j1449zF0UgoaGRk7tTpbI43Vc1telQL9gNqzbnKVtK7P79x78UOebvNsqi6weW/I+19av3ZTRsSQIQu6VNz6JCEIudvbMecaNmkxiYiKdu3ZEb8pE6tarjYqKCgkJCdy+dZd9e/ZTqFChz9rq6upSu25N6tSpRe26tXBx9MgYcZMbybI/kjQJUqmUln/9Sd/+vWj1V0tKliqBRCLh3t37+HgGsHf3ftat2UjJUiWYZm70xfUUL1GMWrVrUqduLerUrY3eBMPs2MUcJa/jIyEhgRnT7VBXV6dGrepcuXQ1G6pVnLAL3/5AO3/OItycvQAYOKT/V5dr1LhBnrnSKuux06p1C9q0/YsmzRpRoWIFChYsAKSP3tm6aQeebr48efwUvfFT2bVvK6qqn9+dP3/uYtycPFFXV0dvykQGDx3A7+XLARD1LopLF69w7OgJ+e5wNkpNTaV+g3r0G9ibNm3/onyF34H0kSHBgbNYu3oDhw8exdrCHr8gr0xtVy5fk9HR0qNXN6yszSldphRJScls37oTe2tn9vy3Dw9XH2zsLXN83+QtK/sbHR3D+NGTiYx8R5WqlfEN9KRe/TokJyezeuU6XB09OXL4GM4O7ji72Sti92SS1ddxWV+XVFRVqVChPHXq1aJ2nVpIpWQaqZObSSQSLEytSUpKolHjBpw/dzFH2iobWY8teZ9rr1+9xtXREx1dHUqUKM7dO/fksXuCICiA6FwSBAVKSEjAzNiSxMRERo0Zjr2zdabHtbW1qd+gLvUb1P2sbdPmjblw7VSmv3m5594PfrLuj46uDlt3radO3dqZ/q6qqsof1aoye/5Mxo6YxOFDR1k0fykGUyejqaWZadk+/XrmylvfvkWex4ePZwCPHj3GwHASL56/zHOdS9+zdvUGAJo0a0zlKl8fbZNXZOXYGTt+1Bf/XqRIEUaNHY6GhgbWlvbcuX2P8+cu0qRpo0zL3bxxG+/32woM8aVr906ZHtctrEubdn/Rpt1fP7o7CrdizWJatGr+2d/L/V4WDx8X1NTVWbV8DZs3bsPM0oQyZUoD6Z1SAb7BANSpW4uAmd4ZnXGamhr0G9CbxMREbK0cWbpoBSNHD8vouMqNsrq/8+cs5PWrN2hpabFw6ZyMDkkNDQ1Gjh5GbGwcPh7+rF6xjjHjR35z5JyyUOT7vPsnI31PnQjLke3mhCULl3Pu7AV69fmXChXL/1QHUVbaKpOsHFvyPtdsZzgRFRWFu5cTmzduE51LgpCLiUBvQVCgTRu28vjRE4qXKIaltdlPtf3S7V25maz7o6NT6LOOpY+pqKgwYHBfAOLi4rl79/MPLXntuQT57dOFcxdZsnA5lSpXZIqhnlzWmZucO3sh44PuoG+MWspLsvN8aNCofsbPL56/+Ozx0OA5pKSk0Klzh886lnKrL3UsfWzg4H4ZP3/ccXv18rWMW6XHTRzzxVFeg4cOQEdXh9TUVDZv3CqnihUjq/u7cf0WIH3E04cvux8bNWYYBQrkJy0tjS0bt2fDHsifIt+b8uL7IsCTx0/x9QqkSJHC2Dj83Gi/rLRVNln5/5XnubZj2y72/LeP5n82/ebIYEEQcgfRuSQICrTp/Rt0t+5dPhtNI8iPpub/n9u0NIkCK8ldkpKSsTCzQSqV4ubp+Eseo2tXrQegkE4huvXorOBqcr8zYWczfi5foXymx+Lj49m9cy8Avfv1zNG6FOlrr0/h4c8yfv6jWpUvtlVTU6NSpYoAHD2Se24V/JKs7O/9ew8ywojb/d36i20LFChAk2aNATh25Lg8ShZyIavptsTHx2Ntb8FvvxXNsbZ5hTzPtcjISBxsXdHQ1MDVyzFXhe0LgvBl4rY4QVCQpKRkrlxOv0pdp15twsOfERI4m8MHj/LmzVt0dHWo36AuQ0cMon2HdootNpc7dTJ9OL+GRj4qVa6o2GJykZkBody9c49BQ/rTvEUzRZeT4+Li4ti5/T8A/u3V7Ythyx+7c/suXTr8y+NHT1FVVaVkqRI0a96E4aOGULtOrZwoWSklJiTy/PkLdu7YzcyAUACaNW/yWTj6pQtXSElJAaBuvdqcCTvHvNkLOX/2ArFxcZQoUZzmLZoxfuJoqteoluP7kV1On/z/7UY1an55v77VKZ4mSQPg9q078i1MgX52f2/d/P/P1ar/8dW21av/weGDR7nzC912I16X/m/1irWcOHaKVq1b0Ld/7xxrm5fI81xztHXj7Zu3mE43yhW3qQqC8H1i5JIgKEj403CSk9O/SD1+9ISuHXqyeuU63r59i3Z+bd6+ecuBfYcYP0oPK3PbTLOhCT/uyeOnrFy2BoDu/3alUKGCCq4od7h29TpzZy2gWPFiWNmYK7ochdi+ZSdxcfEADBoy4LvLR0REcvfOfbS0NElOTubB/YesWbWenl374+sVkM3VKpfXr15TuVxNKperSa0/GtKhTVd8PQNITkqmQ8e/mT1/5mdtHjx4mPHzjm3/MbjfCPbtOUBSUhL51NV5+iScDWs30bNrf9at2ZiDe5N9oqOimRUyF0jPQPk406tcuf9P9f61jqPk5GQePngEQEx0DPHx8dlYbfbKyv6+evkqY5mSpUp+dRsfHouNiSUuLi7LNecG4nUp3YvnL3F39UFLSwtXD8cca5vXyOtc27/3IFs3b6da9T+YqDdO/oUKgqAQonNJEBQk6v3U5gAhQbNRV1cneHYAV26d4+K10xw9vZ9uPboAsGbVehbMW6KoUnOtxIREDCYbk5CQQNGiRZhuZaroknKF1NRULExtSE1Nxd5pBjq6OoouSSHWvL8lrmatGtSt9/Vcr4qVKmBpbca+Izu5ce8i56+e4urtcyxZMZ869WojlUoJCZrD/DmLcqp0hVNVU6NY8WIUK14s021f3Xp0wdLajMJFCn/WJupddMbPXu5+1KxVg03b1nDl1jmu3DrHxq2rqVGzOikpKVhb2HPpwuWc2JVsI5FImGZkwauXr9HU1MTB2TbT47Xr1qJY8WIAzAmdT2pq6mfrWLpoBbExsRm/f/xzbpOV/Y396MurtrbWV7fx8WNxsXm7c0m8LmVmbWlPTHQMRtMMfjr4Pitt8xp5nGvR0THYWDqgqqqKu5cT+fLlk3+hgiAohOhcEgQFkXw0EkkikeDh40K3Hp0z3mTLli1DUKgvNWvVAGDWzDlf/LAtfFlqairGU8y4evka+fLlw3+mNyVLlVB0WbnC7JB5XL92g/b/tKP7v10VXY5C3L51h4vvOy++F+Tdu++/TNQbR+XKlTLOXw0NDVq3bcW6jSuoVz99tsdAv2Cio2Oyt3Al8dtvRQm7cJSwC0e5fvcCx8MOYmA4if17D9KtY29WLV/7WRuJ9P+3QmlqarJgyWzqN6yX8bcGjeozf8kstLS0SE1NJWTmnBzZl+ziZOfGgX2HAHB0taVmreqZHldXV2eqcXqI/t079xg/So+rV66RnJzM61evmTtrAd4e/pm+mKl8IQQ7t/jV9je7idel/9u8YSsH9x+mVu2ajJs4OsfaCl/m5uTJy5evGD5yCA0bN1B0OYIgyJF4VxYEBSlQoEDGzxUrVaBTl38+W0ZVVZUJk8YAEBn5jquXr+VYfblZWloaJlPN2bN7P+rq6vjP9KZ121aKLitXuHP7LsGBsyhQID9ObnaKLkdhPoxa0tTUpHfff2Vej6aWJmaWxkD6bIUnjp2UR3m5ioqKCqXLlMJ0ujH+M71ISUnBdoYjN67fzLRcwY9eE3v27v7FzuAyZUrTs3d3AE4cO0VaWlr2Fp9N3Jy9WLp4BQA2DpaZZoz72IhRQ5kwaSwARw4fo2fX/tSoXJ/mjdrg4epD2XJlmKg3NmN53Vw+ylDW/f342ElISPzq+j9+rEDBAl9dLq/7lV6XXr9+g7ODO2pqarh5OaGu/uNxs1lpm1dl9Vw7dvQEa1dvoHTpUphZmmRPkYIgKIzoXBIEBSn10RenKlUrf3W5qh/NmvPxbDrCl6WlpWFiOJ0d2/5DTU0NvyBPMcvXT7C3diY5OQX9qZPR1dUhLi4u07/U1PQv81KpNONvH0KY84rk5GS2bNwGQJdunbJ8W2Cjj67MPnn8NEvryu26dOtEmbKlkUgkrF21IdNjH3cmVfnjy7OFAVStVhVIn10uMvJdttSZnTxcvDNuRZphO52x40d9c3krW3PWblpBv4F9qFa9KqXLlKZ+g3qYTjdi++6NqKqmTyletlwZNDQ0sr3+7CbL/pYo+f9j5+WLl19d94fHChYqmOkCz6/oV3ld8nL3IzLyHYOHDaBK1Uqfvad9/P714W/JyclZbptXZfVcmzE9/aKVhbUZKip89pymSdJHsKZJJP//Wy69iCAIvyLRBS8IClK4SGFKlSrJi2+8OQN8nOMtpmn9tg8jlrZv3ZXRsdSjZzdFl5WrPHmS/iXD28MPbw+/ry73LPw5das3AdJHXnzvC3Jusm/PASIiIoHv3xIn/LxSpUryLPw5Dx8+yvT3GjWrf6XFJz56Ucxtr4nuzt7Mm7MQAEtrM8a/H5n6PU2aNqJJ00ZffOzDrKONGjeUT5FK4Gf3t3qN/89adfvWHap+pXPy1vug8D++0Xkp5C1P33ecrVi6mhVLV39z2Q/vaaPHjcDOcUaW2uZVWT3Xnj4JB8B4itk3t3M27FzGczp7/swvju4XBEH5iJFLgqBAf72/VevuN6ZqvXv7bsbP5X4vl+015VZpaWkYTzHL1LH0b6/uii5LyIU+3BJXoWJ5mrdomuX1XTh/KePnX/0clkqlGR2YBT+5LalipQoZYbn3vvGaeOf9a2LBQgUp8oVgcGXl5uyVqWNJHjMkvX79JuOWpr79e2V5fcrua/tbqXJFypQtDcDhg0e/2DY+Pp6zYecA+KuNuE1avC4JshDnmiAI3yJGLgmCAvUf2If1azby6OFj9vy377MrMxKJhHnvb58oVaokderWUkSZSu/DiKUd2/5DXV1djFjKgqOn9n/zcXMTKzas20zZcmW+u2xuFB7+jONH07+8Dhjc77sjY6RS6TeXSUpKxtczAID8+fPT6q8/5VarsklNTf1uJsm6NRt5/eoNAM1bNPvs8X4DeuPvM5Otm3dgbDr1s9ylZ8+es23LTgDatW+Dai4JdHZz9sp0K9yPjlj6lrS0NGwtHUhOTqF+g3q0afdXltepzL61vyoqKvTt34vgwNls37qLqcb6lPu9bKb2yxavJC4uHjU1NXr17ZHT5eco8br0f6vWL/3m4wG+wQT5hwBw/+kNubXNq7J6rn3veRrSfySnT52h+Z9Nv/v8C4KgfHLHpzJByKOaNW9C1+7peUBW5rbs2rEnY0a48PBnGBmYcvPGLQBMLYw/+yIV9S6KiIjIjH8SSfrtIokJCZn+HheXO6ZclmV/PmQsbd+6C3V1dQKCvWXqWPp4/R9uiQKIj4vP9PeEhISs72gOyWvHR05Yt3ojEokEdXV1+g/o/d3lw06dYfjgMWxav4Xnz15k/D0lJYXjx04yqO/wjFnnphrrZTm/KafIcuycDTvPoH7DP3suAB7cf4inmy82lg4AVKhQnv4D+ny23XETR1O2XBkSEhIYN2oyl94/dwCXLlxm/Cg9EhMT0dLSwtBYPxv2XP4+zliytrf4qY6lx4+e4OMZwNUr10hKTALSLzqcPXOekUPHs2f3fnR0dfD2d8t1twh+SVb2d/yksRQvUez9sTOJK+8nwEhOTmb50lX4+wQBMHjYACpXrpSzO5YFspyL8nhdSklJybT+mJj/zygXFZW5pryWu/erkPUzQl491wRByDoxckkQFMzb3423b94SdvosBpOM0NDUQFtLm6ioqIxlDE0M6PeFL7o9uvQl/OnnId9zZy9k7uyFGb/3G9Abb3/3bKlfnmTZn3NnzrP9/UgGFRUVHGxdcbB1/eo27Bytvtj51KReyy8u72DrgoOtS8bvhiYGGJtO+bEdUrC8dnxkN4lEwvq1G4H0UTEfB5d+jVSaPmvZiWOnANDS0iJ/fm1iYmIzvnCpqqoy2WACk/THZ1/xcibrsXPm9DnOnE6/HUJTU5MCBfITH59AYuL/Zw6qWasGcxYEo6Wt9dn68+fPz+Ll8xgxeCzXr92gz7+DKFAgP5A+qxVAgQL5CQjx+WrWhzIJD3+W8XypqqoyJ3QBc0IXfHX5CZPGMGHy/2dDi42NJXTmHEJnzgFAV1eX+Pj4jGOrTNnSzJ4/M1c8Fz8iK/uro1OI+YtnM3rYeO7cvkevbv0pWLAASUnJGe1bt22Fjb1Vzu2QHMhyLsrjdencmQsMHfjlLL1/u2Se3XDl2iX82fLzkYiCcpP1dT6vnmuCIGSd6FwSBAXLnz8/K9ctYd3qDWzasJXbt+4QFxdPqVIladK8MaPGDKdxk7wT1CpvH660QfqV1jev33xz+cT3V8MF4VPHj57kWfhz4MeDvKvX/IMZttM5f+4it27eJjIikujoGLS0taj6RxWaNmvM4GEDqVGzWnaWrhTq1KuNX6Anp06GceXyNV6/fsO7yHdoaGhQoUJ5atetRZduHenavTNqampfXU+VqpX578A2FsxdzN7d+3ny+AlpaRIqV6lEm7Z/MW7iKMqWK/vV9spE+tHrk0Qi+e7r04cOtA/KlSvLVGN9Tp8M49HDx0RGRlKwYAEqV61M564dGTZiENra2tlSuyJkdX/r1qvNfwe2MSd0Pgf2HeL5sxdo59emfvV69OvfiwGD++WaWymzQrwuCdlNnGuCIHyJilT68VxUXxYdHY2uri5RUVHo6OSOIf2CkBVubm74+/sRdvGYokvJFWpUrs/fHdoya16QoktRegvmLcbDxYc7j64qupRcoX6tZjRqVJ9Fy+cpuhSlt3L5GmytHLj35NfI/siqZg1bU6lyRdZsWKboUpTexvWbMTO24vLNs58FsQufa9uyI0UKF2bzznWKLkXpuTp6smDeYi5eD0NHp5Ciy1F69Wo0oU+/Xji62iq6FKV3YP8hxo/S49mzZ5QuXVrR5QhCrvUzfUGiS1kQBEEQBEEQBEEQBEGQmehcEgRBEARBEARBEARBEGQmOpcEQRAEQRAEQRAEQRAEmYnOJUEQBEEQBEEQBEEQBEFmonNJEARBEARBEARBEARBkJnoXBIEQRAEQRAEQRAEQRBkJjqXBEEQBEEQBEEQBEEQBJmJziVBEARBEARBEARBEARBZqJzSRAEQRAEQRAEQRAEQZCZ6FwSBEEQBEEQBEEQBEEQZCY6lwRBEARBEARBEARBEASZic4lQRAEQRAEQRAEQRAEQWaic0kQPpGWlsbp06eJj08gPPyZostReo8ePiYtLY2ItxFIJBJFl6PUJBIJDx88QoqUJ4+fKrocpRf+NJyU5GQiI9+Rlpam6HKUmkQi4cH9h0iBB/cfKrocpff82QsSEhKIjoomNTVV0eUoNalUmnFMPXzwUKG15AavX70mNjaO6JgYkpOTFV2OUpNKpbx69RoQr1s/4u3bCFLT0nj6NJykJHFsfYtUKuX+vYcAXL58WbHFCMIvRHQuCcJHDh48SKNGDdm6dSvJycl0aN2VAN9gEhISFF2a0omNjcPL3Y+O7bqjogJnws7Rq1t/zp+7oOjSlNKZsHP826UfK5auBil0aNsVH88A4uLiFF2a0omPj8ffO4j2rbuSmprK5UtX6dG5L2Gnzii6NKV08fwl+vw7iAVzF6Oqokqnv3vg4eJNTEysoktTOokJiQQHzqJ9684kJiRy6+ZtunboybGjJxRdmlK6euUaA3oPJSRoDmpqqvTqNgAnezei3kUpujSlk5SUzOyQebRt2YnoqGgePnhE5/b/cujAEUWXppRuXL/F0AGj2LZlB+rq6vT9dxB2M5yIiIhUdGlKJzk5mQXzFtO2ZUeSEpM4dOAI/7Ttxt7d+5FKpYouT+ncvXOPUUPH4+bkiYaGBl26dGH8+PG8fPlS0aUJQp4nOpcEAXjw4AH9+vWjffv2qKmrsWn7Wo6c2ket2jWZGRDK3391ZtuWHeJNnPQREuvXbqJdy47MnbWARk0acur8EeydbXj44BH9ew3FeIo5z5+9UHSpSiE8/BlT9acxqO9wHj96grO7PafOH6Fhw/rMDplHu5ad2Lh+sxj1RfqVxi2bttOuVWdCZs6hbr3aHDt9EA9vZ8LDnzG4/0gMJhkR/jRc0aUqhZcvXmFqZEHfnoO5d+cetg5WnL10nOZ/NmX+3PQvImtWrRejvkg/tnZu/4/2bbrg7zOT6tWrcejEXnwDPXn9+g0jh4xjwhh9Hj18rOhSlcLr12+wMLOhV7cB3Lh+k+lW0zh/5TRt2rZi2eIVtG3ZkRXLVotRX6QfW3t37+eftt3w9vCnUuWK7D+8k+DZAUS9i2LsyEmMGT6R+/ceKLpUpRAREYmtlSM9Ovfh0sXLGE0z4PzVU3To+DerVqylbcuOLF6wjJSUFEWXqhQOHThC5/b/4uroSdmyZdh7aAdzFgQTHx/PpHFTGD54DLdv3VF0mUoh6l0UTnZudOnQkzNh59CbMpHLN8/g4GzD+g3rqVatGj4+PmJEoSBkIxXpD3xbjo6ORldXl6ioKHR0dHKiLkHIEbGxsbi7u+Pr60uRokWYbjWNXn16oKKikrHM8WMnMTWy5NXLVzRsVB8HF1vq1qutwKoV5/y5C9hbO3Pt6g3KlitDYIgPjRo3zHg8OTkZawt7tmzajpqaKvpTJzFh0li0tLUUWLViJCQkMHfWQmYFz0UqldC7by9cPR1QV1fPWOZs2HmMppjx/Nlz6tSrjZOLLQ0a1Vdg1Ypz+dJVHGxcuHjhEiVLlSRgphfNWzTLeDw1NRV7a2fWr90EwGT98UwyGE/+/PkVVbLCJCUmsWD+EmYGhJKWmkaPnl3x8HFBQ0MjY5mLFy5jqD+Np0/CqVmrBg4uNjRt1liBVSvO9Ws3cLBx4eyZ8xQvUQwffw9at22V8bhEIsHZwZ1Vy9cgkUgZN3E0BoaTKViwgAKrVozk5GSWLFxOgG8wySnJdO7SEZ8Ad7S0/v8afv3qDabomfDwwSOq/lEFRxdbWrRqrsCqFefWzds42btx8vhpihYtgoePC/90ap/xuEQiwdPNlyULl5OamsrocSMwNNZHR/fX+yydkpLCiqWr8fUOJDEhkfb/tMUvyIsCBf5/nt2+fReDiUbcu3ufSpUr4uBsk+lc/ZXcv/cAZ3t3Dh86SuHCurh6OtK1e+eMxyUSCQG+wcybvZCUlBSGjxyCsekUChcprLiiFSQ1NZXVK9fh4+FPXFwcrdu0IjDEj0I6BTOWiYyMJMAnmJXL11C5ciX8/Pzp3r17ps/7giB82c/0BYnOJeGXJJFIWL58OZaWlkRGRjBh0tjvflGdM2s+QX6hJCYm0n9QX8wsjClevFgOVq04z5+9wNPNl62bt1OgQH7MLKcxasywry///AV64w25cvkqJUuWwMbBkq7dO/8Sb+JSqZTtW3fi6uTJ61dvqN+gLiFzAyldutRX2yxZuAxvjwDi4+Pp3bcn062mUap0yRysWnFevXyFt4c/G9ZtRju/NiamUxk/acxXl3/96jX6k4y4cO4SRX8rygzb6Z91COdVUqmU3bv24uzgwYvnL6hdpxahcwMp93vZr7ZZuXwN7i7exMXG0b1nVyytzShbtkwOVq04b968xc87kDUr16OpqYmB4SQMDCd/dfmIiAgMJplw5vRZChfWxdLGnL79e6GqmvcHeUulUg7sO4STvRtPn4RTrfofhM4LpFKlil9ts37tJpzt3YmJiaFTl3+YYTud8hV+z7miFejDF9UVy1aTL18+JuiNxXjalK8eK9FR0UzVn8bxoycpVKgg061MGTikH2pqajlcuWIcOXQMRztXHtx/SNWqlQmZG8gf1ap+dfntW3dia+VIVFQ0f3doi429JZUqV8y5ghUoOiqaoIBQFi9Yhno+dcaMHYG51bSvHlsxMXGYTDHl8KFj5M+vjamFMUOHD8p0ISsvO3H8FA42Lty9c4+KlSoQOieAGrVqfHX5Wzdv4+LgwfFjJ+nUuRMB/gHUrFkzBysWhNxHdC4JwjecPn2aqYZTORN2hm49umBpbfbNL2cfS0xMxMzEij279pIvnwZG0wwYNXYEmpoa32+cCyUmJDJvzkJCZ84hLU1Crz49cPV0zDRC4luOHj6OmYklr1+9oXGThji42FC7Tq1srlpxrly+hoONMxfOX6JEyRL4BnrQ6q8WP9Q2OTkZKzMbtm3dhZq6GlOM9Bg/YTSaWprZXLViJCUls2j+EoL8Q0lNTaVr9054+rpmGiHxLWGnzmA81ZwXz19Sv2E9HJxtqN+gbjZXrTg3rt/Cyc6V06fOUKz4b3j7udP279Y/1DY1NRUbK0c2rd+CiooKkw0mMEl/HNra2tlctWIkJyezdPFKAnyCSEpKpmOn9vgEevzwKLfz5y5gZGBG+NNn1K5TEwcXWxo3afj9hrnUndt3cbJ34/jRkxQpWgR3Lyc6dfnnh9pKJBIcbF1Zs3IdUqRMnDwOvSkTMo1GyUtSU1NZuWwNPp4BJCQk0Pbv1gQE+/zwKLerV64zZbIxjx89oVr1P3B0sck0QjOvuX//Aa4OHhw8cATdwro4u9nRo2e3H2orkUhwd/Zm2ZKVpKWlMXb8KAyMJqOjUyibq1aMtLQ01q7agKe7L7ExsbRq3YKZoX4/PMrt5s3bGEw04sH9h1SuUgkHFxv+at0ym6tWnMePnuDq5Mne3fsppFMIeydr+vbv9UNtpVIp+/YcwNXJk/Cnz5gyZQr29vYUKVIkm6sWhNxJdC4JwheEh4djZWXFsmXLqFW7JnaOVjT7s6lM63r08BF6E4y4dfM2ZcuVwd7Jmvb/tMszoyekUim7duzGxcGDly9fUbdeHWbND/rm6JtvCZ05l+CgWSQlJjFwSH9MpxtRrNhvcq5acV6/foOPZwDr12xES0uLqSb6TNYfL9O6wp8+Q2+iIdeuXKdUqZLYOFjRpVvHPHVs7d29H2cHd56FP6dmrerMmhvE7zKOeFgwdzF+PkEkxCfQb0BvzC1NKFGyhJyrVpyIiEj8vAJZtWItmpqaTDaYgKGJvkzrevniFfoTDbl44TLFSxTD2s6CHj275ZljC+Dg/sM42rlmfHkPnRtI5SqVZFrXsiUr8XLzJS4unn97dcfS2ozSZWR7DVRGUe+iCPQLYeniFeTLl49xE0czzdxQppFab968xWCiEefOXqBIkcJY2ZrTu2/PPDXq6+iR4zjaunL/3gMqV6lE8JwAatSoJtO61q5aj4uTJ7ExsXTt3gkrm+k/fJErN4iOjiE4cBaL5i9FTU2NEaOHYWVjJtPx8C7yHVP0TDh1IgwdXR0sZpjSf2CfPDXq69SJMBxsXbh96w4VKpZn5ix/6tSV7ULclk3bsLd2ITo6mg4d/8bazoKKlSrIuWLFiY2NY1bwXObNXoiKqgqDhw7E3mmGTMfWh4tcIUFz0NLSwtnZmQkTJvwyo74E4UeJziVB+EhiYiJ+fn64ubmhqamJmYURAwbLZzj63t37sTS3JTIiklatW2DnOOObQ71zg+/lk8gqPj4eM2Mr9u7ej6amBsZmhowcPfSHR0Epo6SkZJYsXEagXwgpKSl06voPPv7uPzz65lsOHzyK+TQr3rx+S7PmTbB3tqbmN4Z65wa3bt7G0c6NUydOU/S3onj6uNCh499ZXm9SUhIWptbs3L4bdXV1phrrM3b8yFw96islJYXlS1bh5x1EYmIi7f9ph/9ML7lkTJ08fppphtN5mYdy5O7dvY+zvTtHDh9LzyfxcqJrt05ZXm9KSgozLOzZsnFbnsmRS01NZdWKtfh6BhAXF0/rtq0IDPbNlE8iq3NnzmNkYMaz9zlyjs42NGzcIOtFK9DDB49wcfTgwL5D6Ojo4OhqQ68+/2Z5vampqTjYuLBuzUakSJmsP57JBhNydY5cWloa69dsxMPNl5joGFq0bM7MWX5yyQG6fPEKU/Sm8fTJ0zyTI/f0SThuzp78t3MvBQsVxNbBigGD+mZ5vRKJBBdHD1YuW51ncuQkEgmbNmzFw8WbyMh3NGnaiOA5AXK5UPnq5St8vAJZv2YjdevWISAgkPbt23+/oSD8IkTnkiCQPkJi48aNmJmZ8vRpOKPGDmeqkZ7cgzQlEgn+PjOZP2cRKSkpjBg1FKNpBrkuVPHNm7f4egWydtV6tLQ0MTDUQ3/qRLlv5/79h+hPMOT2rTuUr/A79k7W/N2hrdy3k50+5JM42rkS/vQZ1WtUY9a8QCpUlP/VwZkBocwKnkdSUhJDhg3ExNyQ334rKvftZKcP+STLl65CU1ODiXrjMDQxkPuohiePnqA3yYgb125Sukxp7Byt6Ni5Q64bmXP44FEc7VwzApND5wZS9Y8qct/Oxzly/Qb2wdzCmOIlist9O9kpOiqaQP8QlixcTr586oweNxJzSxO5H1sf58iVKFkcG3tLuvXokuuOrRPHT2Fv7ZwemFypIiFz/L+ZTyKrJQuX4e0ZQHxc7s2Ri4mJJSRoNgvmLkZNTY1hIwdjbWch92Mrr+TIhZ0+i4ONCzdv3OL38uUInuVP3fp15L6dVSvW4O7sTWxsHN3/7YKljXmuy5GLi4tjdsg85sxagAoqDBzcD3tna7mPmImIiGDKJBPCTp9FV1cXSxsz+g3onetGFF44dxF7G2euXrlOmbKlCQz2oXHTRnLfzqWLV3C2d+f8uQv07dsXb29vKleuLPftCEJuIzqXhF/epUuXMDY25tChQ7Tv0JYZdhYy3xrxo2KiYzGeasaR96GKZpYmDBk2UOmH136WT9K5Az4B7tl+9XTXzj1YW9jzLvIdrdu0wtbRKlu+QMvbZ/kk3s506twhW7cZHx/PNMPp7N97CE0tTaaZGzJi1FDy5cuXrdvNqpSUFFYuW4OvVyAJCQm0a98G/5ne2X719MD+Q1hMs+bt2wj+bNkce6cZVJfx9pWcdP/+A5ztPTh88Ai6hXVwcXeg+79ds3WbiYmJmE+bwe6de3JVjlxaWhprVq3Hy92P2JhY/mrdkqBQ32yfhSs9R86K169e56ocuazkk8gqOTkZK3Nbtm3ZiZqaKlOM9Bg3YbTSj/qSSCSsX7sJT1dfoqKiaPZnE4Jn+1O0aPZ26n+cI1evQV0cnW2o37Betm5THsKfhuPu4s3O7bspWLAAM+ymM3jowGzdZmpqKrYznNi4bjMAelMm5oocOYlEwtZN23F19iIyIpJGTRoQMjsg2zv1L1y4hKHeNMKfPqNW7Ro4utrlihy5F89f4unmy5ZN28hfID/m35lMRh6kUilbN+/Ay92XiLeRTJs2DSsrKwoVyptZX4LwI0TnkvDLev36Nba2tsybN49KlSpibW9Bu/ZtcrSGmzduYTDJmAf3H1KlamUcXGx+ONQ5p8kzn0QWEokEH09/Fs1fSkpKKqPGDsfQWB/dwro5VsOPehf5jkC/EJYtWZnlfBJZ3b1zD/1JRty9nT4rir2T9Q+HOue0o0eO42jjyv376fkkofOCqJaDt4xKpVIC/UOYGzqfpKRkho0YjIn5VKUM7Pw0n2TkmGFYWsuWTyKrRw8foT/BiJs3b1O2bBnsnGbQoePfSjl64tSJMOxtnLlz+26W80lkNSt4LsGBs0hMTGLA4H6YWRgrZY5cbGwcoTPnMH/Ooiznk8gqPPw5+hOmcjUX5MidPXMeBxtnrl+7SblyZQmc5UvDhvVztIaF85bg6x1IQnwCffv3YrrVNKXMkYuPj2dO6AJmh8wDoN+A3ji52eXoBbX0HDkjLl64RLHi6Tly//ZSzhy5SxcuY2/jwuVLVyhVuhQBwd40a94kR2tYtmTV+xy5OHr07IaljRllypTO0Rp+RGJCIvPnLiIkaDZpaRJ69uqOm7dTjsYofDi+581eQJEiRfHw8GD48OG5btSXIMiD6FwSfjkpKSmEhobi4OCARJKG4TQDhY/s2Lh+C052rkRHx/BPp/ZY21lQoWJ5hdXzsXt37+Nk58bRI8cpXKQwrp6OcsknkVV0VDSG+qYcP3aCAgULMt1qGoOG9FeKwM4P+SQ+Hv7ExyfQpm0rAuSUTyKrHdt2YWPlSNS7KNr+3QZbR0sqV865TsFvyZRPoquDk6stPXv3UFg9sbFxmEw159CBI2hra2M63YihIwYpxaivtLQ01q3egKe7X3o+SavmzAyVTz6JrD7OkWv515/YOc6gWvU/FFbPx548foqbsxe7d+2lUKGC2Mgpn0RWCQkJmBlbsmf3fjQ1NDA2ncrIMcOUIkfuQz6Ju7MX795F0aRZY4Jn+yu0A0yZc+SePXuOh4sP27fupECBAlhYmzJ85BCF1ZOcnMx0U2t2bvtP6XLkPozscHP24u2btzRoWI/QuUGUKKm4W2pPnQjDZOp0Xr58qXQ5ci9fvMLL3ZdNG7aSP782ptONGTN+pMLqSU1NZcZ0O7Zs2oaKiir6UycyYfJYpRj1lT6ZzB5cHN15+eIVdevWJmReEGXLKq4DLPxpOB6uPuzY9h9NmzUlKDCIP//8U2H1CIIiiM4l4Zfy33//YWJizO3bdxg0dADTlCiTRiKR4Ozgzqrla5BIpIyfNAb9qZMUFqoY9S6KoIDQjHySMeNHYmYh/3wSWV2/egODycY8eviYP6pVxcHZhhatmiusnuPHTuJg45Lt+SSykEgkeLr6smTRclJTUxkzfmS2ZIr9qE/zSYaPHMyMbMgnkdXt23cxmGiU/n9ZuSIOLja0bpP1oHpZhZ06g72NC7du3qZ8+XLMzKZ8EllIJBICfGYyT0ly5L6UT+LgYqMUnc8ADx48RH+8Ibdv36Xc72Wxd7bm7/ZtFTZ64vy5CzjYuGTkkwSF+NCoifzzSWQVHDiL0JlzSUpKYvCwAUwzN1LYe3ZCQgJzZy1kVvBcpFIJvfr2xM3TUWluZ3/6+Cl6Ew25/j5HztbBkk5d/lHYsXX50lUcbFy4eOESJUuVwD/Imz9bNlNILV8yd/ZCAn2DlSJHLikxiQXzlzAzIJS01DS6/9sVT18Xpeh8hvQcOf0Jhly+fJUSJRSfI3f92g0cbV05E3aOYsWL4RPgRpu2yjMyO+zUGZwdPLh29TrDhw/Hw8ODsmXzzgyPgvAtonNJ+CXcvn0bk2km7Nyxkz9bNMPW0UpproJ+KiIiAoOJxpwJO0fhwrpY2pjTt3+vHPvi/XE+SVxsLK3+ypl8ElmtX7sJZ3s3YmJi6dy1IzNsp/N7+XI5tv1HDx/j6uTJvj0H0NEphF0O5JPIKjoqmil6Jpw4dopCOoWwsJomt9kQf8T/80l8iIqKpvmfTQme46+Ut58BbN28HTtrZ6Kjovm7Q1ts7C2pVLlijm3/03wSazsLBg0dkGPb/xmf5siZWhgzdPigHPvirah8Eln9t3MvMyzsFJYjp4h8Elml58hZsH/vQYXkyEmlUnZs24WLowevX72hfoO6hMwNpHTpUjmy/Z91cP9hpk+bwdu3ETRv0Qx7J2tq1My5HLnXr17j7eHPhnWb0dLWwsR0KuMnjcmx7f+M/+fI7SVfvnwYmugzetzIHMuRk0ql7PlvH8727jx//oJatWsya14Q5X5Xzo6IY0dOYGZsySsF5ci9fRuBr1cAa1auR1NTE/2pk5hiNDnHtv8zPsyG6OOZniM5Y8YMpk2bphSjvgQhO4nOJSFPe/fuHc7OzgQFBVG6dCksbcyVNr/hU+fPXcDIwIzwp8+oXacmjq62NGqcvaGKJ4+fxsHWJSOfJGR2ALXq1MzWbcqDRCLB3saFtavWI0XKxMnj0JsygQIFsm/U16f5JEOHDcTWMWfzSWR15fI1puqZ8PjRE6rXqIajiw3N/myardvMlE/ye1mCQv1okAsCaCUSCe7OXixbsoq0tDTGTRiFgZEehQpl362On+aT9B/YG0fXnM0nkVWmHLkqlXBwtc32HLmL5y9hb+vClUtXKV26FAEhPrli2vH0HLkAFs1fQkpKKiPHDMPIxCBbc+Qy5ZNIJPTs3QM3T0elGSHxLffu3kd/oiF33ufI2TnOyPacxKtXruFg48L5cxcpUbI4vgGetGqtnLmInwr0C2bORzlyxmZTKVo0+zryk5KSWbxgKYF+IaSmptK1eyc8fV3R0lLuUHZ4nyM30ZibN25RpmwZ7HMgR+7mjds42rly+mQYvxX7DW8/txzP/ZTVrJC5BAe8z5Eb1A8zy+zNkUtOTmbZkpX4+8wkKTGJfzq1xzfQI9snk5GHDzmJSxYup2zZMnh7+9CvX79c8T1EEGQhOpeEPCktLY2FCxdibW1NXFwcelMm5IqZZ75k6eIVeLv7ERcXT8/ePbCYYUrpMvK9YvppPomt4wz6D+wj123khDdv3mIw0YhzZy9QpEjh9Gma+/4r1w4fiUTCxvVb8HDx5t27KJo2a0zI3IBsnx0oO6xdtR4XJ09iY2Lp2r0TM2ynU7acfK+Yhoc/S88g2LqLAgUKYGljxrARg+W6jZzwLvIdUyabcOpkGDq6OljMMKX/wD5yHfX1IZ/E1cmTiLcRNGhUn1lzA5V29M23bN64DQcbF6Kjo7MtR07Z8klkFRMdi6G+CceOnqBAgQKYv8+Rk2dnojLmk8hq5/bd2Fja8+5dFG3btcbW0Uruk0u8fv0GH88A1q/ZiJaWJlON9ZlsMEGu28gJsbFxTDOczsH9h9HS1sLU3IhhIwfLddSXVCpl354DONm78yz8GTVqVmfW3EDKK0lu5M/Yt+cAlmY2RGRjjlxERCT+3kGsXL4GTU1NJumPw2jaFLluIyckJiZiamTJnt37sjVH7tCBIzjauWZEIMyaF5Sjk8nIy/37D3Bz8uLAvkO0bduWwMBA6tfP2QkABCEniM4lIc85cuQIRkaGXLx4iT79emJuOY1SpUsquqwsSUlJeR+quB01NVX0p05iwqSxWe4s+yyfZEh/HF1scsXom285G3YeoylmPH/2nLr16+DobEODRll/Ez9/7gL21s5cu3qDsuXKEBjik+2jybJbamoq9tbOrF+7CYDJ+uOZZDA+y1cEM+eTSOnTrycuHg65YvTNt1y6cIWp+iY8fRJOzVo1cHCxkcsomcz5JCUJmOlF8xbKk08ii09z5MZNHI2B4eQs58h9mk/So2dXPHyUJ59EVtev3mCKngkPHzyi6h9VcHSxlUuO3Mf5JMVLFMPH34PWbRWXISYPEokETzdfliyUb45ccnIySxYuJ8A3mJSUZDp16YhPgHuuGH3zLZ/lyDnbyOUYuHXzNk72bpw8fpqivxXB08eVDh3/lkPFiiORSAjwC2berIWkpKQwfOQQjE2nZDlHLiUlhRVLV+PrHUhiQiLt/2mLX5BXto6wzgkPHjxEf4IRt2/dodzvZbFzmkH7Du2yPDLn/r0HONu7c/jQUQoX1k2fTKZ7ZzlVrTiHDx7FxdGDB/cfMn78eFxcXChePPddQBKErxGdS0Ke8ejRI8zNzVm3bh31G9bDzsGKho0bKLosuXr+/AV64w25cvkqJUuWwMbBkq7dO//0m7hEImHLxm24uXgTGRFJ4yYNCZkbqJTTY2fFkoXL8PYIID4+nt59e2Ixw5SSpX5+mubnz17g6ebL1s3bKVAgP+ZW0xg5WjnzSWT1+tVr9CcZceHcJYr+VjR91FefHj99bEmlUrZv3Ymrk+f7fJJ6hM4LpFSp3N3B+6mVy9fg7uJNXGwc3Xt2xdLajLJly/z0el69fJWRT6KdX1up80lkFRERgcEkE86cPpulHDmpVMruXXtxcfBIzyepU5NZc5U3n0RW6Tly7sTExNCpyz/MsJ1O+Qq///R6Ps0nMTCchIGhcuaTyCo6Kpqp+tM4fvQkhXQKMd1yGgOH/HyOnFQq5cC+QzjZu/H0STjVa1QjdF4gFStWyKbKFWPblh3YznDKco5cZGQkAT7BrFi2mnz58jFRbyxG06bk+gtTH4uJicNkiimH5ZAjd+TQMRztXHlw/yFVq1YmZG4gf1Srmg1VK87uXXuZMd2OyMh3/NW6JXZOM2TKkYuOiiYoIJTFC5aRL586o8YOZ7qVaZ46tj50NAb6BQMq2NvbY2BgkOsvkAgCiM4lIQ+Ii4vD09MTb29vdHR1mG5lQu++PfPUG9Gnjh4+jpmJFa9lCFXMlE9SphQBwbkjn0RWycnJWJnZsG3rLtTU1ZhipMf4CaN/aJrmxIRE5s1ZSOjMOaSlSejVpweuuSSfRFZhp85gPNWcF89fUr9hPRycbajfoO4Ptb1y+RoONs5cOH+JEiVL4Bvoke15O4qUmpqKjZUjm9ZvQUVFhckGE5ikP+6HAjuTkpJZNH8JQf6huS6fRFbnz1/ESN80I0fOwcWWxk1+bOTfjeu3cLJz5fSpMxQr9hteuSifRBYSiQQHW1fWrFqHVPpzOXK5OZ9EVlevXGfKZGMeP3pCtep/4Ohi88Mj/+7cvouTvRvHj56kSNEiuHs50anLP9lcseJ8miM3dvwoDIwmo6NT6LttU1NTWblsDT6eASQkJND279YEBPsobFbbnHDz5m0MJhpl5MjZu9jwV+uWP9T2/v0HuDp4cPDAEXQL6+LsZkePnt2yuWLFkUgk+HoFsnDeElJSUn4qRy4tLY21qzbg5e5LTEwsrVq3YGaon9JOJiMPERGR+PsEsWr5Wv74oyr+/gF07dpV0WUJQpaIziUh15JKpaxatYrp06fz5s0bxk0cne0hzsomdOZcQoLSQxUHDumP6XSjr44+evniFZ5uvmzeuJX8+fNjbmnMqLEjcrhixXn6JBz9iUZcu3qdUqVKYuNg9dVw9/R8kt24OHqk55PUq8Os+UFKOztQdpg/ZzH+vkEkxCfQb0BvzC1NKFHyy6O+MueTaDHVRJ/J+uNzuGLFefniFfoTDbl44TLFSxTD2s6CHj27ffXY2rt7P84O7jwLf07NWtWZNTeI32UYmZJbLVuyEi83X+Li4vm3V3csrc2+miMXERGJn1cgq1asRVNTk8n64zGcZpDDFSvOpzlyVrbm37x4cnD/YRztXDM6WULnBubKfBJZfZojZ2Uz/asj295FviPIP5Sli1eQL18+xk0czTRzwzx9Yepj7yLfMUXPhFMnfixH7uiR4zjaunL/3gMqV6lEyNxAqss5j0iZbdm0DXvr9By5Dh3/xtrOgoqVvjyy7UOI86L5S1FTU2PE6GFY2Zj9MsdWTHQshgbTOHbkOAUKFMDM0oTBQwd8ddTXqRNhONi6cPvWHSpU+J2ZswOoUzfnZqFTtBvXb+Hi4M7JE6fp2q0r/n7+VK9eXdFlCYJMROeSkCudOXMGY2MjTpw4SeeuHbGyMZfptoG8ID4+HjNjK/bu2Z8eqmhmyMjRQzNG1yQlJjF/3mKCA2eRlprGvz274p4H8klkdfjgUcynWfHm9VuaNW+CvbMNNWv9/0382tXrONi4cO7sBYqXKI6Pv3uuzyeRVVJSEham1uzcvht1dXWmGuszdvzIjFFfSUnJLFm4jEC/kPR8kq4d8fHP/fkksjpx/BSmhha8fPmKho3q4+BiS916tTMev3XzNo52bpw6cZqivxXF08cl1+eTyColJYUZFvZs3bQNVdXPc+RSUlJYvmQVfj5BeSqfRFbnzpzHyMCMZ8+eU6debRydbTLd9n3v7n2c7d05cvhYej6JlxNdu3VSXMEK9GmO3CT9cUw2mJAxcis1NZVVK9bi8/6W6dZtWxEY7EshneybAVKZpefITePpk6dfzJF7+OARro4e7N93CB0dHRxdbejV518FVqw4EokEFwd3Vn4lR+7D9PMebr7ERMfQomVzZs7yy3JeU25149oNDCb/P0fOwcWGlq3+zHj86ZNw3Jw9+W/nXgoWKoitvSUDBvdTYMWK8+G2b3dnb54/f4GhoSG2trYULlxY0aUJwk8RnUtCrvL8+XNmzJjB4sWLqVGzOrYOVnIJPM0L7t9/iP4EQ27fukP5Cr9j5zSD5KRknO3defHiJbXr1CJ0bmCeyyeRVZB/KLND5pGUlMSQYQMZNXY4C+cvZe2q9WhpaWJgOBn9qZMUXaZSePLoCXqTjLhx7Saly5TGztEKNTU1HO1cCX/6LM/mk8hqzqz5BPmFkpiYSL+BfZgwaQzLl6xi+dJVaGhqMElvHIYmBr/MVexvef78BfoTDLl86SolShbHxt6SggUL4mjnmvGFJHRuoEzZHXnRkoXL8fb0Jz4unl59/kV/6kTWrFqfkU8yetxIzC1NxLHFl3PkipcohoONC/fu3qdipYqEzvGnRq0aii5VKWTKkfu3C1ON9dm4fgsL5i5GTU2NoSMGYWNvKY4t0nPkpkwyIez0WXQL62JpbUb58uVwtHPj5o1b/F6+HMGz/Klbv46iS1UKG9ZtxsnOjZiYGDp27oCJmSE7t+9iduj89MlkBvfD3tk610/4IQ8fJqwIDZpD/vz5cXV1Zdy4cXKdmVYQspPoXBJyjevXr9O8eXPyaeRjmrmh3Kdqzit27dyDjYU9kZHvAChW/De8/dxp+3drxRamhOLj4zGZOp0D+w6RlpaGmpoaHTt3wCfAPU/nk8jqwP5DWEyz5u3bCID0fBJvZzp17qDgypRPYmIi5iYz2L1rD6mp6cdWu/Zt8J/pnafzSWT1cY4c8Evkk8gqOTkZK3Nbtm3ZSWpqKqqqqvzVuiVBob55Op9EVh/nyAHo6BTCzsmavv17Kbgy5ZOamoqtlSMb128mJSX92Gr+Z1OC5/hTpEgRRZendD7OkQMoWLAAM+ymM3joQAVXpnwkEgmOtq6sXrmOlJQUVFVVadS4ASFzAiheQsyW9qmXL17h7eHHxvVb+Oeff9i7d6+iSxKEHyI6l4Rc4+jRo7Rp04YdezZRU1xp/CaJRELXDj15+eo1F6+dVnQ5Su/AvkOMH62Ho4sNI/LYLHDyJpVK6dV9AA/uPeTSjTBxFfs7Tp44xbCBYzCdbpTnZurKDgP6DOP61RtcuXVWHFvfcfniFXr3GMgkvXFYWJspuhylN2LIWM6GnefanfPi2PqO0yfPMGTASJzd7Bg2coiiy1F6bVr8Q0J8AifPHRYXPb/j1q3bdO3QCyvb6UzIYzOjZgcnezeOHj7B3Tt3FV2KIPyQn+kLEu/EglLQ1Pz+LF+/OlVVVUqVLkX+H5i1SiDjqlmRouLK7PeoqKhQpkxpNLU0xRe0H1CsWDFAHFs/qmzZMmhqaohj6wcU/a0oII6tH1WuXFk0xLH1Q3SLpM/uVeoXmsQiKwoWLEjhIoVFx9IPKKxbGIDSpUsqtpBcQnznEfIy8W4sCIIgCIIgCIIgCIIgyEx0LgmCIAiCIAiCIAiCIAgyE51LgiAIgiAIgiAIgiAIgsxE55IgCIIgCIIgCIIgCIIgM9G5JAiCIAiCIAiCIAiCIMhMdC4JgiAIgiAIgiAIgiAIMhOdS4IgCIIgCIIgCIIgCILMROeSIAiCIAiCIAiCIAiCIDPRuSQIgiAIgiAIgiAIgiDITF3RBQiCPCQkJHD65BmuXrnG1SvXuXrlGs/CnwNgaGKAsemUr7aNjorm9KkzXL18jatX09u+fvUGAC8/N/oP7PPNbZubWLFh3ebv1nj74RXU1XP/KVe5XM0fXvbPFs1YuW5JNlajXGJiYlmxdBX79hzg4YNHxMbGUrRoUSpWqkCzP5sydvxIdHR1Pmt39Mhx1qxcz8ULl3jz5i0qqFCiZHEaNmrAkGEDaN6imQL2RjZZORdfPH/J3j37OXUijOtXb/DixUsAipcoRoNG9Rk8dAAtW/353Rr27TnA6pXruHzpKlHvoihcRJf6DeoxdPgg2rVvI58dzQGRkZHs23OQE8dOce3qdcKfPiMtLZWiRYtSt34d+vbvReeuHeXeNreT5Xy6euUa+/ce4uqVazy4/5CItxHExsZRsGABqlStTLv2bRg2YjCFixTO+R2SQVbOw6+xtnRg1fI1AJQtV4ajp/bnaHtFkvX4ePoknDYt/vnh7fQb2AdvPzc5V68YYafPsmzxCs6duUBERASFChWiRq3qDBjUj569u3+z7c7tu9m4fjNXr1wjMuId6urqlCpdkmbNmzBi9FBq1f7xzyGKlpVzMcA3mCD/kO9u48DR/6hYqcIXH0tKSmb1irVs37aLO7fvkpiYSPHixWj1VwvGTRzNH9WqyrZjCrB+7SamT5vx3eWWrlrAX61bZvrb61evCTt9NuP/4NqV67x7FwXAyrVL+LNl7vmcJQjKLPd/0xUE4NKFK4wdOUmmtnt27/+hN6vv0dTUpJBOoa8+rqKikuVtKINixYt98/HUlJSMN+x69evkRElK4eTx0xhNMePN6/SOSQ2NfGhpa/PixUtevHjJqZNhdOrSgVofdS5JpVJsrBwzvnABaGlpAfDk8VOePH7K1s3bGTthFDb2ljm7QzKS9Vx89uw5rZt3QCqVZvxNW1sbqVTK0yfhPH0SzvYtOxkwqC9uXk6oqal9to60tDTMjK3YsmkbkH7O6ejoEPE2kn17DrBvzwFGjRmOvbO17DuYg5o3bENqamrG75qamqir58s4pvbu3k/bv1sTOjcQbW1tubXNrbJyPq1bvZFlS1Zm/K6pqYmWlibv3kVx7uwFzp29wKL5S5m7KIRGjRvmzA5lQVbeE7/k5PHTrF6xVmHtFU3W40NVTfW775lJSUnERMcAeec909PNlzmh8zN+19HVITo6huNHT3L86El2bv+P4Nn+n11wS0pKZspkY/bvPZjxtwIF8pOSksKD+w95cP8h69ZsxMrWnHETRufU7mSJPM7FfPnyoVtY96uPf+3C5etXrxk7chLXrt7IWE/+/PkJf/qMtas3sHnTNjx9XOnVp0eW6stpqqqqFP2t6Fcf19DQ+OxvK5at+aGOOkEQskZ0Lgl5hq6uLrXr1qROnVrUrlsLF0ePjBFI31O8RDFq1a5Jnbq1qFO3NnoTDH96+z16dsXb3/2n2+U2YReOfvPx+XMW4ebsBcDAIf1zoiSFO3vmPONGTSYxMZHOXTuiN2UidevVRkVFhYSEBG7fusu+PfspVChz5+P6tZsyvgh37d4ZMwtjKlWuCMD9ew/wdPNl7+79LJy3hKbNGueakSaynIuSNAlSqZSWf/1J3/69aPVXS0qWKoFEIuHe3fv4eAawd/d+1q3ZSMlSJZhmbvTZOny9AjM6lkaPG8FUYz2KFClCfHw8K5etwcvdjyWLllOhYnlGjxuRLfsuT6mpqdRvUI9+A3vTpu1flK/wO5A+GiI4cBZrV2/g8MGjWFvY4xfkJbe2uVVWzqf6DetS7ndzmjRtRJWqlTNGGMbFxbF7117cnb15+zaCSeOmsv/ILnS+cSFBWWTlPfFjCQkJzJhuh7q6OjVqVefKpas52l4ZyHp8lClT+rvvmQ42LixdvAItLS169c5dX/K/ZOXyNRkdSz16dcPK2pzSZUqRlJTM9q07sbd2Zs9/+/Bw9fmskzd05pyMjqXho4agP2USpUqXRCKRcO3qDZwd3Dkbdg43Jy+aNW9K3Xq1c3z/ZJHVc7FR4wasWr/0p7YplUrRn2jEtas30NLSwt5pBr379kRTS5NXL1/h5e7HxvVbmD5tBpWrVMo1zyVA6TKlfnrko4qKCqXLlH7/Ob8WJUoUx2q6XTZVKAi/LtG5JOQJTZs35sK1U5n+5uXu90Nt+/Tr+d1b34Qft3b1BgCaNGtM5SqVFFxN9ktISMDM2JLExMQvjorR1tamfoO61G9Q97O2m9ZvAaBCxfIEhvhkuvpYuUolgmf707Fddx4/esKO7f/lis4lWc9FHV0dtu5aT526mT/gqqqq8ke1qsyeP5OxIyZx+NBRFs1fisHUyWhqaWYsFxERycL56bdgdurcATvH/49GzJ8/P+MnjeHt2wjmhM4nwC+YfgP7UKhQwazsarZbsWYxLVo1/+zv5X4vi4ePC2rq6qxavobNG7dhZmlCmTKl5dI2t8rK+dS3f+8vrrNAgQL07d+b4sWLM2rYeN6+ecuBfYfo3fffbN2XrMrKe+KnfDwDePToMQaGk3jx/OVPdw5ltb0yyK7jIykxiS2btgPQpVvHL942nZukpqYS4BsMQJ26tQiY6Y2qanq8q6amBv0G9CYxMRFbK0eWLlrByNHDMjq+ATZtSD+Hm//ZFCfX/3/xV1VVpW692sxfPItWTdsRFxfPrh27c0WHiDzPxZ9xYP8hzp29AIC5pQmDhg7IeKxEyRL4BHjw4P5DLpy/hIerDyvWLMr2mhRpitFkjKYZZPz+9Em4AqsRhLxLBHoLecKXbpHJibZCZufOXuDunXsADPpFRi1t2rCVx4+eULxEMSytzX6q7atXrwGoWavGF4e158uXj5q1agAQHxef9WJzgKznk45Ooc86lj6moqLCgMF9AYiLi+fu3XuZHj9x7CTJSckATNAb98V1THr/9+ioaPbu3idTnTnpS51DHxs4uF/Gz59+Yc9K29wqO8+nBo3qZ/z84vmLLFSZM+T1vnbh3EWWLFxOpcoVmWKol+PtcwtZj4//du0lKir9NvK88J559fK1jFvDx00ck9Gx9LHBQwego6tDamoqmzduzfTYh3O47lduD9TRKZQxGjGvvydm1cH9h4H0iyvDRw354jITJo8F4OTxU4SHP8ux2hRBfNYXhJwhOpcEQZCbtavWA1BIpxDdenRWcDU548NoiW7du2QaSfMjfi9fDoAb129mysf5ICUlhRvXbwJQt17eyOLICk3N/z+/aWmSTI+FP/3/B+M//qjyxfaFixTmt2K/AXD08IlsqDBnfev5yM62yio7z6czYWczfi5foXwWqsw9kpKSsTCzQSqV4ubp+NOvb1ltn5vIenx8GOlbsVKFXDVxw9d83EHxR7Uvvw6rqalRqVJFAI4eyfw6XL58+iimq5evfbFtdHQMD+4/BL7eASWk+/CeWKFiefLly/fFZap+9F557PDxHKlLEIS8TXQuCYKcnDh2ivatu1CjSn3q1WhClw49cbJ3y/gglNfFxcWxc/t/APzbq1ueCQn+lqSkZK5cTh/1UadebcLDnzFjuh2tmv5N9Ur1aNrgL8aP1uPA/kNfbD98ZPrVxEcPH2NkYMbDB48yHrt/7wFTJ5vw+NETKlQoz9gJo7J9f5TdqZNhQHpY+oer11+SJkn76mOStPTHbt28LdfaFOH0++cDoEbNajnWVlnJ+3xKSkrm6ZNwli5agalhejZMhYrl6dDx7+zZASUzMyCUu3fuMXBwP5k6PrLaXtll9fh4/OgJp06cBjKPJMwrvtVp/eE1+vatO5n+PmzEYCD9td7O2okXz9NnDJVKpVy9co3xo/WIi4unUeMGSn9rqjzduX2XLh3+pVbVhtSp1pgObbpiZW7LtavXv9s2Le3r74cfP3br5p2vLqdsIt5G0rNrP+pUa0zNKg1o27IjJlOnc+pE2PcbC4KQrUTmkiDIyfPnL1BTU6NgwYLExsZy+9Ydbt+6w8plq7FxsMr44pNXbd+yk7j3w9QHDRnwnaXzhvCn4SQnpwDpXxQcbV2IjY1DQyMf2vm1M/I3Duw7xKAh/XHzcso0a2CHjn9j42CJl5svu3bsZteO3RmzWyUmJqKjq8OwkYMxNTdS+nyg7Pbk8VNWLksPa+7+b9fPno9yv5fN+Pn2zTtf/DL7+tVrIiPfAfDq5avsKzYHREdFMytkLpCe6fEz+WZZaavM5HU+1ahSP+MWy481btqIgGBvNDU/n4kor7l29TpzZy2gWPFiWNmY53h7ZSav42Pdmg1IpVLU1dXpN6C3nKtUjHLlPnodvnXni5lIycnJGR2/MdExxMfHkz9/fgBGjB7K8+cvmD9nEcuXrGL5klUZs8UlJ6dQvEQxJhtMwNBY/5e6zSkiIpJ376LQ0SlEbGxcxsx5a1dvQH/qREynG3/W5sN74qOHj0lKTPriyMGPO/de5qL3xISEBK5euY6uri6pqSkZs4Fu2bSN/oP64ubp+NUZ9ARByF5i5JIgZFHtOrVwcLHh6Kl93Lx/iQvXTnH55hlC5wZSoUJ5kpNTsJvhxK4dexRdarZa8/6WuJq1auSKkE15iHoXlfFzSNBs1NXVCZ4dwJVb57h47TRHT++nW48uQPrzs2Deks/WMXb8KELnBWXcrpWYmEhiYiIAKckpxMfFExMTmwN7o7wSExIxmGxMQkICRYsWYbqV6WfLtGj1Jxrvv9SFzJzzxfWEBP3/77Gxufc5lUgkTDOy4NXL12hqauLgbJsjbXMDeZxPxYsXo1jxYhlfeAFatGyOrYMVg+SprwABAABJREFUZcuWyb7ilURqaioWpjakpqZi7zTjp0Oms9pe2cnj+EhLS2PD2s0A/N2hLcVLFM+OUnNc7bq1KFa8GABzQud/8fbUpYtWEPvROfjxz6qqqky3moanrysFCqQ/v3Fx8RkXcZKSkomJiSE+ISE7d0NpVKxUAUtrM/Yd2cmNexc5f/UUV2+fY8mK+dSpVxupVEpI0Bzmz/k8jLtd+zYAJCUlMX/u54+npaUxO2R+xu+54T2xZMkSGJoYsGPPZm7cS/+8fe3OBdZtXkmr1i0AWL9mIy4OHgquVBB+XaJzSRCyaPS4EYwcPYyy5cpmXEnT1tamS7dObNy+OiMHxM3ZE6lUqshSs83tW3e4eOEykDdCSX+U5KP/T4lEgoePC916dM7INyhbtgxBob4ZIcKzZs7J9GE7ISGBqXomjB+lR5mypVmycj5nL5/g7OUTLFk5n6rVqrBpw1b69BjIjeu3cnbnlERqairGU8y4evka+fLlw3+mNyVLlfhsuaJFizB6zHAAjh05gcnU6dy7e5+UlBTCw5/h6ebLsiUrM/5vVFRy79ufk50bB/YdAsDR1ZaatarnSFtlJ6/z6eip/YRdOMrV2+cIu3iMGbbTuX7tJn16DMTfOygH90gxZofM4/q1G7T/px3d/+2a4+2VnTyOj8OHjvLiRfotXwOH5J1b4tTV1ZlqnB7cfvfOPcaP0uPqlWskJyfz+tVr5s5agLeHf6YMIJWPQr8jIiIZPmgM5iZWNGzcgLWbVnDxehinzx9h1rwgihYtwoqlq+n776CMW+byst59/2Wi3jgqV66U8ZxpaGjQum0r1m1cQb366bPQBvoFEx0dk6lt+w7taNCw3vvHQwiZOYdXL19lZM9NHGvAjes3M9armgveE1u3bYWx6RRq1qqeMUJQTU2Nxk0asmTFfDp27gDA8qWrfplICkFQNsr/SiIIuViRIkXQnzIRSA9X/JH743OjD6OWNDU1f6kchAIFCmT8XLFSBTp1+eezZVRVVZkwaQwAkZHvMgWVurt4s2Pbf1SuUom1G5bTuk0rihYtQtGiRWjdphVr1i+jUuWKREREYm/jnP07pGTS0tIwmWrOnt37UVdXx3+mN63btvrq8maWJvTo1Q2ALZu20bFdd6pXqkfr5h2YEzqfBg3rZcw4p1s4d46mcHP2YuniFQDYOFj+VFZLVtrmBtlxPhUr9hvjJ41h8fK5qKioMDNwFvv3HczmPVGcO7fvEhw4iwIF8uPkZvf9BnJun9vIenysXZn+nlmqVEna/d0mu8vMUSNGDWXCpPRZyI4cPkbPrv2pUbk+zRu1wcPVh7LlyjBRb2zG8rofjWwzM7bk1Mkwmv/ZlCUr5tOkaSN0dApRvERxOnftyNpNKyhatAiPHz3By903x/dNmWhqaWJmaQykj+46cexkpsdVVFSYNW8mNWvVIDU1FV/PAP5s3JbqlerRvVMfDu4/zIhRQ6nx/gJDbh9hqKqqmnELrkQiYf/7iyiCIOQs0bkkCNmsYeMGGT8/fvRUcYVkk+TkZLZs3AZAl26dcv0HlJ9R6qMRNFWqVv7qclU/mjXnw2w6sbFxrF6xDkj/MP6lPAQtbS1Gjh4GwNmwc7x581YudecGaWlpmBhOZ8e2/1BTU8MvyPO7MxCqq6sTFOLLgiWz6dGzK1WqVqZsuTI0bd4YeydrVm9YRmJC+i1SH2Yryk08XLwzbn+YYTudseN/POQ9K21zg+w+n+o3rEeTpo0AMraTF9lbO5OcnIL+1Mno6uoQFxeX6V9qanoAsFQqzfhbSkqK3NrnVj9zfLx+/YYD76eJ7zewd57MDrKyNWftphX0G9iHatWrUrpMaeo3qIfpdCO2796Iqmr6PpctVwYNjfQRKHfv3OPQgSMAjJ80JlM+4QfFiv1Gn/69ANi9a1+eHQ3+oxp99PnyyePPP1+WLFWCjdvW4OLhQJu2f1GhQnkqVEgPnZ+3KBRHV1vevn8d/NYkGblFxUoVKFq0CABPHj1RcDWC8GsSaWeCIGTJvj0HiIiIBH6tW+IgfWr7UqVKZtze8DUff/798IH5wf2HGbfIla/w+1fbVqxUIePnp4+fUux9lkxe9mHE0vatuzI6lnr07PbD7f/u0Ja/O7T94mMfZvdr1KShXGrNKe7O3sybsxAAS2szxr8fDZfdbXOLnDifSpYqCaQH5OZVT56kf0H19vDD28Pvq8s9C39O3epNgPRRcB86K7PaPjf70eNj0/otpKamoqKiwoBBeWv04MeaNG2U0eH2qYzX4cb/fx2+c/texs8/cg4nJCTw5s1bir/PeBK+TFNTg6HDBzF0+KDPHnvz5i3Pwp8D0DiXvScKgqCcxMglQchmF85fyvj5Q/5SXvLhlrgKFcvTvEVTBVeT8/56f5vW3Tv3vrrM3dt3M34u93v6MaCq+v+rsh9GM33Jx6MrChQs8NXl8oq0tDSMp5hl6lj6t1d3uaz72tXrGV9g+r6/+p0buDl7Zeocmqg3Lkfa5iY5cT49eZx+Jfzj22EF4YMfPT7Wrt4AwJ8tm3+zEyWvev36TcYtXB+/Dmc6h59+4xx+/dE5XCD/V5f7FXz8+fLDZ4ufsWVT+qjzUqVK0qJVc7nVpSiPHj7OuNiZFz9vC0JuIEYuCUIWSKXSLw7d/uBd5DtmBadP+V26TGlq16mZU6XliPDwZxw/mv4hccDgft98LvKq/gP7sH7NRh49fMye//Z9lrskkUiY9/52pFKlSlKnbi0AqlSpjJaWFomJiaxdtZ7BQwd8NnVuWloaq1esBUBXVzfPTBn/NR9GLO3Y9h/q6uo/PWLpWxISErC1cgSga/fO37yNUZm4OXtlup3tZ0YdZaVtbpOV8yktLQ1VVdVvvn4dP3aSSxevAOTpTvSjp/Z/83FzEys2rNtM2XJlvrhsVtsrI3keH2fCznH/3gPg1xvpC+nPpa2lA8nJKdRvUI827f7KeOzDeyPAimWrM2Y7+1h8fDybNmwBoEbN6plm7Mtrvvf5MikpGV/PAADy589Pq7/+/Kn1P3r4mOCA2QBMnjLhs9dLZfO950MqleLu4g2k5y+1/6ddDlUmCMLHxMglIc+IehdFRERkxj+JJP1epMSEhEx/j4uL+6ztx49/uOoBEB8Xn+nvCZ9Mf7t5w1Ymj5/Krh17Ml0RT0xIZM9/++jXawiP39/3bWVjhqpq3jrl1q3eiEQiQV1dnf4Deiu6HIVo1rwJXbunZwFZmduya8eejNtzwsOfYWRgys0b6TNTmVoYZxwDWtpaGV8url65zoTR+ty8cRuJRIJEIuHG9VuMHTmJc2cvADBm/Ihck80hy7n4IWNp+9ZdqKurExDs/dMdSxfPXyJk5hzu3L5LcnIykJ4JdvjgUQb2GcbFC5cpXaY0jq628tvZbPRxTpK1vcVPdQ5lpW1ulJXz6fmzF/To3JeVy9fw+NGTTDkuz549Z1bwPCaNnYJUKqVwYV3GTcgdt3Bl5T1R+D95Hh9r34/0LVxYl85dO2Z77Yrw+NETfDwDuHrlGkmJSUD6RZazZ84zcuh49uzej46uDt7+bpk6C8qWK0uHjn8DsH/vQaYZTufRw8dIpVJSUlI4d/YCQwaMyvhMNX7S6BzfN1nJci6GnTrD8MFj2LR+C8+fvcj4e0pKCsePnWRQ3+EZs/RONdb7Yt7lxvWbWb1iLc+fvUAikQAQHR3DmlXr6d97KFFRUbRt15oRo4Zm5+7LRfjTZ/TuPvCz81AikXDh3EXGDJ/Inv/2ATBk+MDPLsZJJJJMz3VUVFTGYzExMZkeS0pKzrkdE4Q8Rrm7qQXhJ/To0veLQ6nnzl7I3NkLM37vN6A33v7umZZpUq/lF9fpYOuCg61Lxu+GJgYYm07J+D1NImHPf/sy3tDy58+PpqYG0dExpKWlB5dqaGpgbWchtxEYykIikbB+7UYA2rVvQ4mSn08P/6vw9nfj7Zu3hJ0+i8EkIzQ0NdDW0s704cXQxIB+n3TAWcww5eGDRxw+dDTjn8b76XWTP/pw82+v7hgYTs6RfZEHWc7Fc2fOs33LTiA9l8rB1hUHW9evbsPO0eqzc+rVq9f4egbg6xmAiooKuro6xMTEZpyL1ar/wfzFs3JFblV4+LOM50pVVZU5oQuYE7rgq8tPmDSGCZPHZrltbpaV8+nG9ZvYWDoAoKGRj4IFC5KYmER8fHzGMr+XL0fo3ECKlyie/TsjB1l5TxQyk8fxERMTy87tuwHo3bdnxlTqeU1sbCyhM+cQOnMOkD5KMD4+PiO4vUzZ0syeP5Oqf1T5rK2nryujh0/g6uVrbN64jc0bt6GtrU1KSkrGRRuAiZPH0rd/7xzZH3mQ5VyUSuHEsVOcOHYKAC0tLfLn1yYmJjbjuVRVVWWywQQm6Y//4navXrnO4gXLAMiXLx/a+bWJiY7J6Jjp2r0zfoGeuWbU+eVLV7h8KX2EoIamBgULFCA2Li7T63v/QX2xd7L+rO2z8Oe0afH5jL4Ak8ZNyfS7l58b/2PvruOiyP84jr9QSrHPbj2727M97+zu7iQkBKS7BSQU7O489ezuwO5usUC6Y/f3Byc/E3FZ2AW/z8fjHg/cnZn97NzM7Mx3vvP+Dhk2UI6VC8KvQzQuCUIWtGnbCmMzQ65evsbjh08Ij4ggOjqGQoUKUaVqZdq0a82oMcPz5LPfZ06dSw+C/BW793+qYMGCrN+yii0bt/HPtl08uP+Q2Ng4ypYtQ4vWzRk/ccw3wzI1C2iyfM0i9u05yM5//uXWjdt8+PABVFT+G12nIUOGD6TLX51z/kvlsI93ciHtzmxoSGiG0yf8d0f8Uw0a1WfajEkEXbjEq1eviYyIpFjxYtSpW4vefXowZPggpe/6/5H0k/UhkUh+uD5iY/9/kZuVeXMzWfen0mVKMX+hLxfOBXHt2g3ev31PeHg4+fLlp3yFctStV4e/u3Wh/4A+aBbQVMyXExRGXtvH7p1703s/D8vDv5kVK1ZgpqEOF84F8fzZC8LDwylUSIvqNarTvWdXRo8dToECBb45b4kSxdm+ayPbtuxg3+4D3Llzj8iISPLnT1vXzZo3YeSY4bRs1TyHv1XOq123JpY2s7ly+Rr37z0gPCycqKhoNAtoUqPm77Rs1ZwRo4dRp26t7y6jT7+eJMQncOXyNd69fU98Qjxly5WleYsmDBk26LPHEpVdyZK/Ye9kzZXL17h75y5hH8KJjIxCQ0OdSpUq0qx5E4aOGPzdEHlBEHKGijQT43hGRUVRtGhRIiMjKVLk1xlmXMh+p06domPHjhw+sTfP58nIw/hRU3j44BFnLx1XdClK7+aN2/TvNQT/QO8812ssO8yYMpNLF69w6foZRZei9B4+eET3Ln1xdrf/5gg8wucM9Uw5efwUV26dV3QpSu/Vy2A6tvk7T4evy5OFqQ179xzg+p0gRZei9O7de0Cvv/uzZEVg+uNnwvf16jqA5ORkDh3fo+hSlN67t+9p06KTON/KJA9Xbw4fPMajh49+PLEgKIGfaQvKWwEwgiAIgiAIgiAIgiAIQo4SjUuCIAiCIAiCIAiCIAiCzETjkiAIgiAIgiAIgiAIgiAz0bgkCIIgCIIgCIIgCIIgyEw0LgmCIAiCIAiCIAiCIAgyE41LgiAIgiAIgiAIgiAIgsxE45IgCIIgCIIgCIIgCIIgM9G4JAiCIAiCIAiCIAiCIMhMNC4JgiAIgiAIgiAIgiAIMhONS4IgCIIgCIIgCIIgCILMROOSIAiCIAiCIAiCIAiCIDPRuCQIgiAIgiAIgiAIgiDITDQuCQqVnJwMgFQqVXAluYNUKkWsqcz5uE2JbSuTxHrKNLFt/Rxx3Mq89G1LrLFMkUql4tiVWeK49dPEusqcj8crsb4yRyqVkpSYpOgyBCFbiMYlQWH27t3LxIkTANCbYUTQ+YuKLUiJRYRH4Gjrytkz53n/7j3uLl5ER8couiylderkGWbpzwbA28OXM6fPKbgi5RUVFY2r0xyOHD5O2IcwnOzdiIyIVHRZSuv82SD0dYwBCJy3iBPHTim4IuUVExOLp7sP+/YcICoyClsrR8LDwxVdltK6dPEK2lP1AVi+ZBVHDh0TF2vfERcXh4/XPP7ZtovY2FgsZtsSGvpB0WUpretXb2BiZAGAnZUT+/YcFNvWdyTEJzDfbwEPHzzkyeOnmBia8/7de0WXpbRu37qDzlR9VFRUcHZwZ9eOPWLb+o7ExCQWBS5lzcr1BAcHM3r0aF69eqXosgRBrkTjkpDj7t27R89ePenduzcVK1Vglqk+wa+CGTFkHHozDAl+FazoEpVGSkoKa1atp1PbbqxZtY627f+gVesWLF20gs5tu7F54zYkEomiy1Qaz54+Z+oEbcaPmkJoyAfGTRxFeEQkY0dMYvpkPV48f6noEpVGamoqm9ZvoVPbrixfsopWrVvQtv0frFq+ls7turF+7SZSU1MVXabSePniFdpT9Rk1bDyvX79h3ITRxMXFM3HsNCaNm86TJ08VXaLSkEgkbNuyg85tu7IocClNmjaiU+f2bFi7mU5turFq+dr0XqsCvH79Bn0dY4YNHM3zZ88ZO34UKSmpTJ2ow7hRk3n44JGiS1QaUqmUXTv28Gf7Hsz3W0D9BvX486/ObN20nc5tu7J08UqSkkSPgI/evX2PsYEZA/sO5+mTZ4weN4LklGR0pxswcsg47t65p+gSlYZUKmXv7gN06dgDH6951KlXh+49u7Jrxx46t+vOgvlLSExIVHSZSiM09APmpjb06zmE+/ceMHLMMPKp5MNQz4Qh/Udy88ZtRZeoNKRSKYcPHqVrp17McZtLlaqVsbA25dChg9SuXRsnJyfi4+MVXaYgyIWKNBPNy1FRURQtWpTIyEiKFCmSE3UJeVBERASOjo7MmzePcuXLYWU7m67d/0JFRYWUlBRsLB3YvmUnADN0pzJdZzIFCxZUcNWKc+b0ORysnXn06AlVq1UhcJEvderVAeDq1evoaxsT/CqYevXrYO9sQ4uWzRRcseJER8cQ4L+QZYtXkj9/PkaNHYG1nTn58uVDIpHgYOvKxvWbkUqkTJk+EZ2Z0ylUSEvRZStM0IVL2Fs7c+/ufSpVrsi8wLk0atIQgFs37zBT24jnz15Qs1YN7J2sadOutYIrVpzY2FgWBixh0YJlqKDC0OGDsHe2RlVVFYlEgpuzF2tWriMlNYVJU8ajZ6BNkSKFFV22wly5fBV7a2du3bxD+Qrl8JvvRfP/jk337z9Ed5oBTx4/pXr1atg5W9GhYzsFV6w48fHxLFm4nMB5i5FKJfQf2BfXOY7p25aP1zyWLlpBcnIyY8ePwmCWLsWKF1N02Qpz4/otHGycuXrlOmXKlmGun0f6senJ46foTDPgwf2HVK5SCVtHS/7s0gkVFRUFV60YiQmJLFu6inm+gaSmpNK7bw88vF1QV1cHwN8nkIUBS0hMTGTE6KHMMjXgt99KKLhqxbl75x721s5cDLpMyVIl8fRxpVPnDgC8fP4S7WkG3L1zj3Lly2HrYJF+7vorSkpKYvWKdfh6zyMxMYluPf7Gy9eNAgUKALBowVL85waSkJDA4GEDMTUzpFTpUgquWnEe3H+Io50rZ0+fp3iJ4rh7OtG1+1/A/89dVyxdTbly5fDy8mLIkCG/7LYlKK+faQsSjUtCtktNTWXp0qVYW1sTFxeHrv4MJk0Zh4amxlfTvn/3Hp1pBly9cp2SJX/D0taMfgN6/1IH2hfPX+Li6MGhA0coXKQwdo5WDBrS/5vTrluzEXdnL2JjY+nTrxfm1iaUL18uhytWHIlEwtbN/+Dh4k1kZCSt/2jJ/IU+FC9R/KtpQ0M/oDfDiEtBlylWrCgWNrMZOLgf+fL9Oh04g18F4+bsyd7dByhUSAtLm9mMGD3sm9Nu2bQdZ3s3oqNj6N6zK5Y2s6lUuWIOV6w4EomEXf/sxtVpDmFh4TRr3oSARb7fPEmOCI9gps4szp25QOEihTGzmMXQEYPJnz+/AipXjLdv3uHh6s3Of/6loFZBTM2MGD9pzDen3bVjN7ZWTkRFRvHnX52wtjOnWvWqOVuwAkmlUvb8uw9nBw9C3ofQqHEDApf4U65c2a+mjY6KwVDPmJMnzlCwYAFMzI0YOXoYqqqqCqhcMULeh+Dp7sO2LTvQ1NTEwFiPaTMmfXPafXsPYmVmR0R4BB06tcPG3oIaNX/P4YoVRyqVcnD/YZzs3Hjz5i316tdhwWJ/Kn7j2B0XF4fRzNkcPXwcTU0NjEz1GTt+FGpqagqoXDE+fAhjrqcfG9dtQUNDA229qcw01PnmtEePHGf2LCvCPoTxR5tW2DpaUadurRyuWHGkUilHjxzH0daVly9eUat2TQKX+FG9erWvpk1ISMDUyJID+w6ipqaOvpEOEyaPQ0NDXQGVK0ZEeAS+3vNZu3oDampqTJ0xEUPjmd8853z65Bluzp4cPniUDh3a4+fnT9OmTRVQtSB8m2hcEpTG8ePHMTQ04Pr1GwweOgATMyPKlC39w/nOnw3CSN+Ud2/f06RZY+ydrGnUuEEOVKw4MTGxBM5bxNJFK1DJp8KIUcOwc7T8YeNHSkoKVub27Ni2ExWVfGjrTWOa9qT0u0h51aWLV7C3duLO7XtUqFgB/wXeNG3a+IfzXb50FQNdY14Hv6FBw3rYO1vTrHne/hGPi4tjUeAyFgYsAWDQ0P44udr98AI1NTUVe2tnNm/chhQp07UnM0N3KlpaebvX1/WrN7CzcebGtZuULVcG3/letGrd4ofz3bx+Cz1tI16+eEXtOrVwcLam1R8tc6BixUmIT2Dp4hUE+C8kNVVC3/69cPN0Su8h8T0SiQRXRw/Wrt5Iamoqk6eOR9dAm8KFC+VQ5Ypx6+Zt7K2duXL5GqVLl8LL1532Hdv+cL57d++jO92Qp0+e8XuN6tg7W9OufZscqFhxEhOTWLlsNf4+gSQnJ9OjV1fmzHVFU1Mzw/kkEgleHj6sWLqa5OQUxk8ag76hDkWLFc2hyhXj3t0HONi6cOFcEL/9VoI5c135869OP5zv0cPH6Ewz4NHDx1StVgU7Rys6/dkhBypWnKSkJNasWo+P1zwSExL5q+ufzPX3+GFvealUit/cABYtWEpSYhKjx43AyGQmxYt/fUMrL3n08DGOtq6cPnWWYsWL4erhQI9e3X443/Nnz9GZZsC9uw+oUKE8to6W/NX1zzx9wzglJYX1azfh7eFLXFw8HTu3x3eeF4WL/Pi37dTJMzjbu/Po4WMmT56Mi4sLpUv/+JpJELKbaFwSFO7Zs2eYmpqydetWmjZrgq2DBY2bNvrp5SxdtAIfr3nEx8czZNhATM2N8lz3WolEwj/bduHmNIeIiEhatGrO/IU+lCz5208t582bt+hOM+D69ZuUKlUSaztzevftmed+xF+/foO7sxe7d+1FS0sLMytjxowb+dPLWbViHZ7uc4mLjaPfgD6YWRpTrvzXPQdyM6lUyr879+Li6EFoSChNmjUmcJFfphp4PxXyPgTdGYZcuXSN4iWKY2ltSv9BffNcr693b98zx82bf7btomDBAhjPNmDilPE/vZxN67fg4jiHmJgYevXpjoW1KRUqVsiGihVHKpWyb89BnB3cePf2PQ0a1idwiT8VKvxcz8nwsHD0Zhhx4fxFihQtgrmVCUOGDcxz21ZISCjeHn5s2bQNTU0N9Ay10dad9tPL2b51J462LkRFRfN3ty5Y2ZpRpWrlbKhYcT7mkzjaufE6+DV16tYmcLEvVapW+anlREVGoa9jzOlTZylUSAtTi1mMGDU0z/UoDAsLx8fTn/VrN6Ghoc50nSkYzNL76eXs+Xcf1ub2REZG0alzB2wcLKj++9e9UnK740dP4mDrkv7od+BiP36vUf2nlhETE4vRTFOOHz1JgQJpvxWjxg7Pc72+IiMi8fMJYPWKdaipqTJpyniMzQx/+vh86MARzE1tCA8Lp237P7B1sKRW7ZrZVLXinD51FgdrZx4/fkq16lUJWOxHnTo/17stJSWF9Ws24eM9D6lEiq2tLTNnzvzhDRtByE6icUlQmJiYGNzd3fHy8qJY8WKYWRrTf2CfLDVwJCQkYGZsxb49B1FVVUXfSIeJU8bnie61X+WTBHjTvEXWetGcOXUOY0Mz3r8LoVnzJtg7W9OgYX05Vaw48fHxLF6wnAXz/8snGdQPVw+HLD0ekpSUhKWZHbt27CZ/vnzo6s9gyrSJaBbI+M54bnDj+i3sbZy59l8+iY//HP5o2ypLy7wYdBlDPRPevH5Lw8YNcHCypkmzH/cWU3Y/yieRRUpKCnaWjmzdsgOAGTpTmK47JU/kyN25fRcHG5dv5pPI6urV6xhoG/PqVTB169XB3tmalq2ay6lixUlKSmLV8rX4zZ1PYlIS3br/jbef+w9732REIpHgZOfK+nV5L0fuwf2HONi6cO7MBUqUKI67lzN/d+uSpWXeuXUX3RmGeS5HLjk5mXWrN+Lt6UdCfAJ//tWRuf6eWdoOJBIJHi5erFqRliM3cfI4ZhpoU6Ro7j/3f/L4KU52bpw4fopixYri5GZP7749srTMBw8eoTvNgMePnqTlyDlZ0aFT7s+RS0lJYeP6LXi5+xAbG0u7Dm3xD5ybpTzBL3PkxowbiaGxXp7IkXv+7AXODu4cOXSMIkWKYO9sxYBB/bK0zPDwcHy95rN+7SaqV6+Gj48vvXr1ynM3jIXcQTQuCTlOIpGwfv16zMzM+PDhA1NnTGS6zhS5Pj7z4vkLtKcacO/ufcpXKI+tgwV/d+uSKw+0X+WTmM9i/MTRcv2MhQFLmOcbSEJCIkOHD8bYzIBSpUrK9TNywv/zSdwJCQmlceOGBCz2+2Y+iayCg9+gO1WfmzdvU6ZsaaztLOjZu1uu3La+zCcxNNFj6vRv55PIasXS1XjP8SMuLo6Bg/sx28L4p3tDKYOv80nqsmCJPxUrya+XUV7KkfvwIQzvOb5sWr8VDQ0NdGZOQ89AW66f8WmOXO9+PTG3MqFChfJy/Yyc8Gk+yauXwen5JNWqVZXbZ4SFhaE7zZCLeSBH7qt8Eu1JGM7Sk+t32br5H5zsXPNEjtzJ46dxsHVJf0wyYLEftWrVkNvyIyMi0dOexbkz53N9jlxUZBT+voGsXLYGVVVVxk8ag5mlsVy3rbyUI3fuzAXsrJ3SH5Ocv8CHeg3qym350VExGM404eTx02k9hM0MGTVmeK7MkYuJiU0fTCZfPhVGjRmOtb2FXLet+/ce4GzvzpnT5+jeozs+c32oW1d+/z8EITNE45KQo4KCgjAw0Of8+Qv06tMDcysTuV6cfenwwaOYm1oT9iGcNu1aY+tgSe2f7HaqKJ/lk0gk9BvQB1cPh2zr7pqQkICxoTkH9x9GXU0dQ2M9xk8ak2u6136WT1KmFN6+HrTrkH05I6dOnMHEyJyQ96G0aNkMe2dr6tXPHT/i/88nCSA5OYUevboxZ65LlnpIZCQpKQkzY2v2/LuP/Kr50TPQZsrUCd8M6ldGn+WTlPyNOd4umconkVVuzpH7Mp/k765/4p2JfBJZ5fYcuU/zSYoXL4brHEe69+yabZ935fJVDHRNCH71OtflyH2ZT9Kpc3t853tRKJuytyQSCXZWTmzetA2pVMq0GZPR1ss9OXJPnzzD2d6NY0dPUrRoERxdbenbv3e2fd7N67eYqW3Ei1yYI5eamsrmDduY4+ZNdHQMbdu3Yf6CudnWCyu358i9eP4SV6c5HNx/mMKFC2PjYMGQYQOz7fM+y5H7vRr2Lja5JkdOIpGwfetO3J09iYiIpGXrFgQs8qFEiewZcfHjo8Iujh4Ev3qNnp4ednZ2eT7rS1AeonFJyBGvX7/GwsKC1atXU7deHWwdLGjdJmuP3WSWRCLBzyeAxYHLSE5OZvTYERia6CntgfbLfJKGDesTIEM+iayePU0LVbx/7wEVK1XA1tGSLn91VtreE1/mk8w01GGG7tQc+/wA/4UE+C8iMTGR4aOGYDzbUGmHaf5WPsmCJX5UrpIzOSyvXgajM82A27fuULZsGWwcLOjes6vSbluf55NoMF1nskz5JLJaumgFPt7ziI+LZ/DQAZiaG1G6jPL2+voyn2TBEv8cy2F5+/YdOtMMuH71BqVKl8TK1ow+/ZT3sYCv8kmmTsB4tkGO9SRavXIdnm5zic0lOXKf5pNU/70a8xf5/nQ+iaxCQz+gO82Ay5euUrx4MSxtZit1jlxUVDQBfgtZvnQV+fPnZ+z4UVjYmOZYvZvWb8XF0Z2YmFh69u6OpY1y58hdOBeEnbUzD+4/pHKVSsxf6EuDhvVy5LMjwiPQm2HE+XNBFClaBDNLY4YMG6i0vb5iY2NZMH8JixcuQwUVho8air2TVY5tWzu278Le2oWoqKhckSN3+dJV7K2duH3rLhUqlscvwCvHGvMTE5NYsXQVAf6L0NTUxNnZmSlTpuTKXl9C7iIal4RslZCQgI+PDy4uLmhoamBsasCwkYrpLh0TE4uhngknjp2iQIECmJgZMmqscnWv/TSfpFSpknj6utGxU3uF1HJw/2EsTG0ID4+gfYe22DpaKtUwzV/lk/T4G2/frOWTyCouLg5jA3MOHzyKhqYGRiYzGTt+lFL1+sqOfBJZnTh2ClMjC0JDP9D6j5bYOlpRt15thdTyLV/nk3Rirv8cheTU5IYcuS/zSZzdHejVp7tCajl7+hyzDMx5/+49TZul5cg1bKQ8OXJf5pO079gO/4C5mRodSN6SkpKwMrNj5z+7yZ9fOXPkvswncXCxpv/AvgqpRdlz5FJTU9m6+R88XL2Jiozij7atmL/ARyE5NbkhR+7Vy2DcnOewb89BChUqhLWdGcNGDlFILdeu3kBfZxavXipnjpxEImHH9l24OXkSHh5B85bNCFjk+9ODycirFid7N9av3YRUImXytAno6s9Qqhy5N6/f4u7ixb8796ClVZDZlsaMHT9KIbW8f/cerzl+bN20nYYNG+Dn58+ff/6pkFqEX4NoXBKyhVQqZceOHRgbz+Lly1eMnzRGaYIe799/iO40A578dwfU3tma9h1+PLxzdvoyn0RXfzq6+jMUWhOk/YjP9fRj2eJVJCcnM27CaAxm6Sp0mOacyCeR1ZPHT9GZps+D+4+oXKUSdo5W2fr4VGbkRD6JrPx9AlgYsJTExERGjh7GrNkGlCih2B6FX+aTBC72p2YtxTeqvnz+Eu1pBty9c09pcuS+zCeZMHkssy1mKcW2tTBwKfN8AklISGDI8EGYmBkqPEfu7Jnz2Fs7p+eTBCz0oa4SPEr7+vVbdKbO5OaNjzly5vTs3V2h21ZO5JPIauWyNXh5+BIXF8eAQf0ws1R8jtzFoMvYWztz9849KlWqgH+gD42bNlRoTZCW6/cxR67EbyXSen1lceCWrIqLi2NhwBIWBS4DYOjwQdg7WyvFjcb1azfh5uxJbIzy5MhdvXwNOxtnbt24Tfny5fAL8KJ5y2YKrQm+zpEztzZl0JD+Cj1GJMQnsGTRcgLnLSI1VUL/QX1x9XBQipEBr1+7iZOdG1cuX2XQoEF4eXlRrVreG+FRUDzRuCTI3Y0bNzA0NOTYsWP82aUTVnZmSjlE7c5/dmNn5URUVBR//d0ZKztzqlb7ueGLs+qrfJJuXfD2c1equ3uQFqpooGfMqROn0dLSwsTciBGjhub4ydiX+SRunk506/F3jtaQGfv2HsRqti0REZF07NQeGweLnx6+OKu+yif5s0NaPokS3d2DtBN9o5mzOXr4OJoFNJllos+Y8SNz/GTsyZOnuNi7p+eTOLnZ0adfrxytITOOHDqGmYkVYR/C+aNta+wccz5H7st8knYd2jAvMPvySWSVkJCAiZEFB/YdQl1NHYNZuoyfNDbHe319mU9i62jJ4KEDcrSGzFCGHLkv80latW7B/GzMJ5FVUlISFibW/LtLsTlywcGvcXf2ZM+/+9EqpIWFtSmjxgzP0Roy48K5ixjONOXd23c0btoIeydrGjfJ2cYvqVTKzn924+o0h7APYTRt3pjARX6UKl0qR+v4kZSUFKwtHPhn6w5UVPIxQ3cq03Um53iO3Ns375jjNpcd23elDSZjZsj4SWNztIbM+DRHrn6Dutg722R5JOWflRZncQAnezfevwuhYaMGLFjqL9fBZORBKpWya8cePFy9CQ8Lx9jYGAsLCwoVyh1ZX0LuIBqXBLkJDQ3FxsaGxYsXU61aVazszOjcpaOiy8qQRCLB2cGd9Ws2pYUq/te9NidCFY8dOYGDrQsvnr+kVu0aBC7OuXwSWd27cw+d6YY8e/qcGjV/x97Zmrbt/sj2z42MiMRvbgCrV65DTU2NydPGM8s05/JJZCGRSPB092HlstUkJ6cwftIYDIx0c+QCXJH5JLJ69PAxOtMM0nt12Dla0enPrA1Znxlf5ZNMGI2FtYnSb1t+PgEsXrCMpMSktGGacyhH7vzZIOxt0vJJqlSpxLwczCeR1ac5chUqlsfO0Youf2d/jlxMTCwL5i9myaLl5FNRYfjIodjlYD6JrALnLWK+/0ISE9Jy5GaZGuTI4y+f55NUwH+BN02bKs9jZ9/yZY6ctb0FPXplf45cfHw8iwKXsWD+YgAGDemPk5udUvS+ycjSRSvx8fbP8Ry569duYm/jzPWrNyhbrgy+8zyVPmxcUTlyCfEJLFuykvl+C0hNldC3fy/cPJ2U6jH/b/k0R65v/96YW5nkSI7c7Vt3sLd25vKlq5QuXQpPHzc6dGqX7Z+bFXFxcSwKXMaShcsoXrwE7u7ujBkzRul/m4TcQTQuCVmWnJxMYGAg9vb2SCSp6M/SZez4UUrRDTSzwsPC0ZthxIXzFylatCjm1iYMHjogWw60jx89wcnOjZMnTlOsWFFc5jjSs1c3uX9Odtq+dScOti5ER0XTtftfWNmaUblKJbl/zuf5JHF06NQOv/neCsknkVVUZBT6OsacPnWWwoULYWoxi+Ejh2RL7tizp89xcfT4JJ/Ehv4D+8j9c7LTnn/3YW3hQGREJJ27dMTa3pzq1eXf6PplPkmbtq2Zt2CuQvJJZBUTE4vRTFOOHz2Z7Tlyr14G4+rkwf69hyhUuBA2duYMHTFY7p+TnQ4eOJKWIxcWTrsObbB1sKSmHIdk/0iZ8klkFRcXh4mhBYcOHEFDQx1DE33GTcieHLkv80nMLE0YM36k3D8nO504dgrTWRaEhnygVesW2DlZZ0uOnFQqZfeuvTg7eBAaEkqTpo0JXOyn8MfyfkZiYiJmxlbs3X0AVVVVZhrqMGnKuGzp9fX+3Xs83X3YtmUHBQoWYJaJAZOnjZf752Sns2fOY6xvxrtszpGTSqXs33sIZ3s33r59R4OG9QhcMi/HBpORh+TkZCzN7Ni5/V/y58+HzszpTJ0+KVty5EJDP+A9x4/NG7aiqamBroE2OnrT5P452Sn4VTDuLl7s+Xc/LVu1xN/Pnz/+yP4bxkLeJhqXhCw5cOAAhoaGPHjwgOGjhjLLVF9pR8rKjKtXr6OvbUzwq2Dq1a+Dg4ut3LrXfppPoqamyoTJ4zA1N8q1dwokEgkOtq5sXL8ZqUTK1BmT0NabJrfHrr7MJwlc5EudenXksmxFuHXzDjO1jXj+7AW1atfE3smaP9rKZ8TEr/JJxo7A2s48V29b7i5erF6xjtTUVCZOGYeegTZFihSWy/I/yyepXJF5gXNplMOPaMhTdubIfcwnWRi4FBVUGDpiMPZOVkrfQ+J70nLk/Fm2eGW25Mh9lk9SoRx+85Ujn0RWaTlyBukjackzR+7TfBKJREL/gX1xneOYa7ctAH+fQBYGLMmWHLmbN25jb+3E1SvXKVOmDHP9PWjTrrVclq0IL5+/RHu6AXdv36Nc+XLYOljQtftfcumZk5iQyPKlq5nnG0hKSgq9+/bAw9tF6XvfZGTRgqX4z82eHLm7d+7hYONC0IVLlCxVEk8fVzp1zv6ew9nlzZu3aE/R5+aNW3LPkUtKSmL1yvX4evmnDSbT/W+8fN1y/LFFeQo6fxFHOzfu3L7L2LFjcXNzo0IF5R3hUVBuonFJkMmDBw8wNp7F7t17aN2mFbYOFtTNxRf+X1q7egMeLt7ExsbSp18vzK1NKF9etrs3qampbNqwFU+3uURHx9C+Q1v8A72VLp9EVqGhH9CbYcSloMsUL14Mc2tTBg7uJ3PDxovnL3Fx9ODQgSMULlIYO0crBg3pL+eqFWfLpu0427sRHR1Dj15dsbQxo2Il2X7EJRIJ27bswN3Zi8jISFr90YL5C5Uvn0RWEeERzNSZxbkzFyhcpDDmlsYMGT5I5l5fn+aTFCqkhaXNbEaMHibnqhVn147d2Fo5ERWZ9Rw5iUTCrn924+rsSdiHMJo1b0LAIl+lyyeRVXRUDIZ6xpw8cQYtrYIYmxkycvQwmRs23r55h4erNzv/+RctrYKYmM9i/MTRcq5acfbtPYiVmR0R4RFZzpGTSqXs3b0fZwd33r8LoVHjBgQuUb58ElnJO0cu5H0Inh6+bNv8D5qamhjM0mWa9mQ5V604Rw8fZ7axFWEfwrKcIyeVSjl04AiOdm68ef2GevXrsGCxPxUrV5Rz1YqRkJCAqZElB/YdQk1NLcs5ch8+hDHX04+N67agoaGBzsxp6Bloy7lqxUnLkbMg5H1IlnPkpFIpx46ewNHWlRfPX1K7dk0Cl/orxWAy8pCamsqWjdvwnuNPfHw8lpaWzJo1K1c3mgmKIRqXhJ8SGRmJk5MT/v7+lC1bBnNr0xzJF1CElJSU/7rX7kJFJR86M6cxdcaknzrQfpZPUrUy8xb4KH0+iawuX7qKga4xr4Pf0KBhPRycbWjavEmm50/PJ1m4nHz5VBg+ahh2jpa5tvdNRlJSUnCwcWHzxm1IkTJdezIzdKeipZX5Xl+XL13FzsqRO7fvUbFiBfxyQT6JrG5ev8VMbSNevHhF7Tq1cHC2/qm8jK/ySYb2x8lV+fNJZCGRSHBx9GDd6o0y58hdv3oDOxtnbly7SdlyZfGdN0fp80lkde/OPXSnG/H06TNq1KiOvYvNT+XIfZlP0q9/b1w9HXN1D4nvkUgkeHn4sGLpGpKTk2XKkfssn6RMKbx83GnfUbGjtWaXRw8fozPdgEcPZMuRS0xMYtXyNfjNDSA5OYkevboxZ64rmpryf8RH0SQSCf4+ASzKQo7c/XsPcLB15fzZC/z2WwnmzHVV+Git2eX5s+doT5U9Ry45OZk1q9Yz19OfxIRE/ur6J3P9PZRuMBl5CZy3mAD/BSQkJDJs5BCMZ/9cjtyjh49xsnPj1MkzFC9eDGcPh1wXZ5FZUVHRzPdbwMpla6hYsQJeXt4MGjQoT17nCdlDNC4JmZKamsqKFSuwtLQkJjYGHb1pTJ46IVueY1Y2b968RXeaAdev36R06VJY25nTq0+PDA+0n+aTFC5cCGt7C4YOH5SDVSvOqhXr8HSfS1xsHP0H9sXM0piy5cp8d/ov80latGrO/IU+uSqfRFYh70PQnWHIlUvXKFGiOJY2s+k3sE+GDWqf55NoYWZlzJhxuSufRFab1m/BxXEOMTEx9OrTHQtrUypU/H6vr6/ySZqljQ6Um/JJZCVLjtz7d++Z4zaX7Vt3UrBgAYxnGzBxSu7KJ5HV9q07cbR1ISqTOXJf5pM0bFifgCX+uSqfRFaf5sgVKlyI2ZnIkQsN/YC3hx+bN6blk+gZaqOtm7vySWT1szlyUqmUo4eP42DrQvCr19SpW5vAxb5UqZqzo9kqwpc5csazDRg1dniGvb7Cw8Px9ZrP2tUb0NBQZ7rOFAxm6eVg1Ypz6MARzH8yR+7EsVM42Lrw7OlzataqQeBivxwfzVYRZMmRi4yIxN83kFXL16KmpsqkqRMwnq3cg8nIy5PHT3F19ODokRN07twZX19fGjfOmzcwBfkSjUvCD506dQoDAwOuXr3KwMH9MDWflWFjQV515tQ5jA3NeP8uhOYtmmLvbE39Bp/3QoqNjWVhwBIWLViGCioMGzEYu1ycTyKrpKQkLGfbsmvnHvLny4eu/gymTJv4VWPkV/kkAd45PoSsMrgYdBlDXRPevHlLo8YNcXC2pnHTRp9NEx8fz5KFy1kwf3FaPsmgfrh6OPxy21ZKSgq2lo5s27IDIH2Y5i/vuH6WT1K2DD7+c+SWcZWbXL16HQNtY179lyNn72xDiy8ygBITElm2dBXzfRf8l0/SEw9v5zzZ+yYjEokERztXNqzLOEfu7p172Fs7czHoMiVLlcTL15WOnXJvPomsbt+6g96MjHPkkpKSWL1iHb7e89LzSbz93PNk75uMZDZH7sH9hzjauXL29HmKlyiOh5czf3froqCqFefBg0foTNVPy5GrXg07Zys6dPx8BK7k5GTWr9mE9xw/4uPj+fOvjsz195Rb7mNuIZFI8PGax9JFK9Jz5PSNdL4anOLJ46c42blx4vgpihUrirO7A736dFdM0Qr05MlTdKZmnCOXmprKxvVb0kefa9+hDf6BPrlqMBl5OXHsFM4O7jx98owpU6bg7OxMqVJ54/F4IXuIxiXhu54/f87s2bPZvHkzjZs2wtbe4qcec8qrFgYsYZ5vIAkJiQwdPhgTc0NKlCielk/iNIewsHCatWhCwMK8k08iq+DgN+hO1efmzdv/hSpa0LN3N969fZ+eT1JQqyCmeSyfRFYrlq7Ge44fcXFxDBzcj9kWxpQuU+rzfJImDQlc7Jdn8klkFfI+BO1pBly7cp3fSv6W1utrQG9CQ0I/zycx1mPajEmKLlfh1q3ZiLuz12c5cuXKleXg/sM42bnx5s1b6tWvy4Il/jJngOUVHz6EoTvdkEtBlylWrCgWNrMZOLgf4eEReTqfRFZbNv2Ds70r0dExdO/ZFUub2VSsVIFjR0/gYOPCq5fB1Kpdk8Alfnkmn0RWkRGR6GnP4tzZ8xQuXBgzi1kMHTGY6Kho/OYGsGbVetTU1Jg6YyKGxjN/iR4SGdm1Yzd2Vk5ERkbR5e/OWP+XI3fq5BkcrF148uQpv9eoTsBiP2plw8iPuUl0VAyGM004efw0BQsWwMTciJGjhxEXG8c8vwWsWLoaVVVVxk8ag5ml8S+/bX2aI9ehUztsHSz5vUZ1zp25gL2NMw8fPKJqtSrMX+BDvQay5TTlFcnJyaxdtQG/ufNRUcmHvb09urq6uWpUcCHniMYl4Zvs7OyYM2cORYoWYbaFEQMGyR7QnBclJCRgbGjOwf2H0VBXp3KVyty7e59y5criG+BFy1bNFV2iUjl54jSmhhaEhITSoGF9Hj54SKrkv3ySOXkzn0RWSUlJmBlbs+fffeRXzU+NGr9z+9YdSpcphbevB+06tFF0iUrl/NkgjPRNeff2PXXr1eHZ0+ckJyf/l0/i8sv1kMhISkoKVub27Ni2ExWVfNSuU4ubN27xW8nfmOPtkmfzSWR15fJV9HVMeB38mtp1avHy5SsSExL5u1sXvP3c82w+iSwkEgl2Vk7pOXL169fl+rWbFC9eDNc5jnTv2VXRJSqVT3PkatT8nXdv3xEXF0+nzu3xmef1S/aQ+B6JRIKr0xzWrtpAamoqjZo05OrlaxQtWhRHVxv69u+t6BKVyr2799GdbsjTJ8+oVr0qYWHhREdF065DG+YFzs0zg8nIw/9z5FaTnJxCk6aNuXL5KoULF8bGwYIhwwYqukSl8uFDGD5e/mxct4VatWqycOEiOnUS5w3C50TjkvBNKioq9B/YF2d3u58KGf7VPHv6nLEjJ/H2zTssbWYzcco4RZek1AL8F+LjNY9ixYuyc++2XyKfRFavXgYzdsQkXr58hbGZwS+TTyKrpYtW4uHqRaFCWuzcu4XKVSoruiSl9fbtO8aOmMTTJ8+Yaaj9y+STyGrVinU4O7ihqanJzj1bqP779/NyfnWhIaGMGzWZB/cfMWnqeMytTMSNqQxsWr8Vawt7SpQozqoNy6gj4yhpv4KI8AgG9BnGq5evGDN+NLYOFmLbysCO7buYPcuSIkWLsnLtkjw7mIw8REVFM7jfCJ4+ecrQ4YNx8XAQ21YG7t65z6Rx0+nVsxfLly9XdDmCkvmZtiCxl/1i/mjTUjQs/UDValUYMXoY+fLlEw1LmaCrPwNVVVVatmohGpZ+oGKlCoyZMBIVFRXRsJQJU6ZPoKBWQZo0bSQaln6gbNkyTJwyDqlUIhqWMmH8xNEUL16cevXrioalHyhZqiRTpk9EIpGgb6QrLtB+YPioIairqzNgUD/RsPQDxYoXo2u3v5BIpMwy1Rfb1g8MGNQPTU1NevfpIRqWfqBIkcL07tsDiUSKkYl4HPVH6tarTYUK5RVdhpAHiD1NEARBEARBEARBEARBkJloXBIEQRAEQRAEQRAEQRBkJhqXBEEQBEEQBEEQBEEQBJmJxiVBEARBEARBEARBEARBZqJxSRAEQRAEQRAEQRAEQZCZaFwSBEEQBEEQBEEQBEEQZCYalwRBEARBEARBEARBEASZicYlQRAEQRAEQRAEQRAEQWaicUkQBEEQBEEQBEEQBEGQmaqiCxB+LeHh4Rw+eIyzp89z+9Ydgl+9JjU1hRIlStCwcQMGDelP955dFV2mQkRHx7Bu9QYOHzzKs6fPiYmJoUSJElStVoVWf7Rk0pRxFClaJH36vLYu4+PjuXDuIrdu3ubWzTvcunmb18FvANA30sXQWO+78759845DB49w/mwQd27d5e3bdwCUKl2SJs0aM2LUUNq2+yPb5ldGWVmfvt7z8fcJ+OFnHD21n6rVqsitZkWpXrFupqf9o00r1m9Z9d33Q96HsGbVeo4fPcnLF8EkJCTwW8kS1KjxO63btGLK9AmoqanJo+xsk5Vt58K5IE6dPMvNG7d48fwl4eERxMXGUbRoEWrWqkG3Hn8zYtRQNAtofjXv+bNBjBo2PtN1GszSw2CW7s9/wRx26+Ztjhw6zq2bt3n65BlhH8KIiYmlUCEtfq9Rnc5dOjJ67AiKFS/23WWEhISyeMEyjh4+zuvgN2hqalKzdg0GD+nPsJFDUFFRybkvlAOCLlxizcp1XL54lbCwMAoXLkyderUZOnww/Qb0/uY8UZFRXDh/kVs3bnPrVtp2G/I+FIA5c10ZMmxgTn4FuVDkcfzunfscPXyMoAuXeHDvIWFh4airq1GhYnnatP2DsRNHUb16Ndm/nBJYMH8Jnu5z0//95NXdr6bZuvkfZs+y/OGyVm9YRvsObeVaX3bKyrb1kazHJVMjC7Zt2fHD5T94dhNVVcVfqspjXYFs5we/2vmYkPspfo8Vfimtm3YkJSUl/d8aGhqoqqrx9u073r59x6EDR+j0ZwcCF/tRoEABBVaas86duYCBngmhIWknwurqamgWKJC+Xs6fC6Jbj7+o90njUl5bl9ev3mTSuOk/Pd/r12/o0PovpFJp+msFChRAKpXy6mUwr14Gs3vnXoYOH4TrHEfy588v1/mVlazr81NqamoULVb0u+8rw0mfPJQsVTLD91OSk4mIiASgUeMG351u9669WJrZERMdA6Ttk2rqarwOfsPr4DecPHGa0WOHo1ZUuRuXsrLtLF64nGNHTqT/u2DBgqirq/PhQxgfzgVx/lwQK5atZsXaxV9dmKqpq/3w/0V8XByxsXFAxv8vlMmWjdtZs2p9+r81NDTQ1NQgIiKSy5eucvnSVVYsXc3iFQE0a970q/lv3rjNhNFTCA+PAEBLqyCxsbFcCrrMpaDL7NtzkMUrAlBXV8+pr5StPFy9WRS4NP3fRYoWISoqmjOnznHm1Dn27t7P/IU+Xx1/Dh44kqlGgNxEUcfxHdv/ZZb+7M9eK1ykMHGxcTy4/4gH9x+xYd0mbB2tGDVmeJbqU5Qnj59m6qL9o3z58lHitxLffT+37X9Z3bbkcVzS0NCgcJHC331fWRrN5bEfZvX84Fc5HxNyP7ElCjkqJSWFxk0aMXjYADp2ak/lKpUAePUymPl+C9i8cRsnjp3CysyOuf5zFFxtzrh08QqTx88gISGB7j27oq03jYaN6qOiokJ8fDwP7j/i8MEjFC78+Q9wXlyXRYsWpX7DujRoUI/6Devh7OCefuf5eySpEqRSKW3b/8GgIf1p174tZcqWRiKR8PjRE7w8fDl04AhbNm2nTNnSzDI1kOv8ykyW9fmpZs2bsGHr6mysUDkEXT2V4ftLF63A1SltHxo2csg3p9m7ez+GeqZIJBJGjh7GhMljqVmrBgAxMbHcuX2Xg/sPo6qWO352Zd122nVoQ8dO7WnRqhlVqlahUCEtIK2n5a5/9uDh6s3LF6/QnjKTfYd3kS/f/5/Ob96i6Q//X0yZoM3Rw8cpV64sHTu3z9qXzCGNmzakYiVTWrRsxu81qqf3QI2NjeXAvkO4OXny4UMY0yfP5MjJfRT55GIrKiqaKRNmEB4ewe81quPt50Gjxg1ISkpi4/otuDh4cPLEaZzs3XBytVPUV5Sb9Ws3pTcs9enfCwsrU8qVL0tiYhK7d+3FzsqJg/sP4+7ihbWd+Vfzlypdknr169KgYT0aNKyP9lT9nP4KcqeI43hKSgrqGur06t2dvv1706JVcwoXLkRSUhIXgy7jZOfGg/sPsbFwoHKVSrmqxw6ARCLBzNiKxMREmjVvwpXL1344T7nyZTl1/kj2F5eDZN225HVc6tOvJ54+bvL8StkmK/uhPM4PfpXzMSH3yx1nuUKesW7TStq0a/3V6xUrVcDdy5n8qqpsWLuJHdv/xcTciPLlyymgypwTHx+PiaE5CQkJjJ84Bjsnq8/eL1CgAI2bNKRxk4ZfzZvX1mXL1s25evv8Z6/NcZv7nan/r0jRIuzat5UGDet/9nq+fPmoWasGC5fOY9LY6Zw4fooVS1ejO3MGGpoacptfWcm6PoWvbd64DYAWrZpT/fevHwN5/+49Vmb2SCQSLG3NmDJtwmfvFyqkRavWLWjVukVOlJtlWdl2Jk359mNtxYsXZ/ykMairq2NlbsfDB4+5cvkaLVo2y3Rd796+58SxtManwcMG5JpehIOGDPjm61paWgwaMoBSpUoxfvQUPoR+4Ojh4wwY1Dd9mqWLlhPyPhRNTU2Wr15EpcoVgbReEuMmjCYmJhYvdx82rtvCxCnjcvVjSikpKfh6zwegQcN6+M7zTG981NBQZ/DQASQkJGBj4cDqFesYN2F0+k0VgIGD++XKR98yoqjjeLPmTThx5hBlypb+7HV1dXXatW/D5u1r6fpnb0Leh7IwYEmua1xatXwtly9dpf/AvlSpWjlTjUt5TVa2rV/puARZW1d57fxAEH5EBHoLOepbjSGfGjZicPrfN6/fyu5yFO6fbbt48fwlpUqXxNzK5KfmzWvrUtYLxSJFCn/VMPQpFRUVho4YBEBsbByPHj2W6/zKKrdceCu7y5eu8uhh2v/z4d/ptbRy+VoiIyOp36Auk6dmPjNIWWXnttOkWeP0v9++eftT827d8g+pqamoqKgwbMS3/1/kRhmtk+1bdwJpvXg+XsB9avzE0WhpFSQ1NZWd23dnb6HZ7NaN2+mPhk+eNvGzXm0fjRg1lCJFi5CSksKO7bs+ey8vHvMU9Z2q/17tq4alTxUpWiQ90/FGLji/+NTLF6/wnuNH8eLFsLb/uvfbryIr29avdFyCrK2rvHZ+IAg/IhqXBKWiofH/HiGpqRIFVpIz/vnvB7pX7x5y7w3zq63LjGR1XYh1+evavGErkJY30qtP929O83E/7j+on9JkRCiri0GX0v+uXKVypueTSqVs3bgdgLbt/6BipQpyr01RvrdOnjx+mh4a2/nPDt+cV0tLixatmgNw+uSZbKwy+wUHv07/u2at3785Tf78+alWrSoAp06ezYmyhO/4+LsoyWW/iRazbYiLi8PKzozfMshQEr7tVzsuZZU4PxB+NeKxOEGpXDgXlP53nbq1FFhJ9ktMTOLmjbQ7fg0a1Sc4+DUBfgs5cewUoaEfKFK0CI2bNGTU2OF0+avzTy//V1qXP3L+v3Whrq5GtepVc3z+3Orhg0f0+KsvL56/Il++fJQpW5pWrVswZvxI6jeop+jysl1sbCx7d+8HoG//Xt8Mxn/54hXv3r0HoGHDety7+4AF8xdz/twFIiMiKVGiBM1bNmX8pLE/9QhYXpIQn8CbN2/Zu+cA83wDAWjVusVPBXKfPxvE8+cvgO/3IMtNEhOTCHkfwtHDx/HxmgdAlaqV+avrn+nT3L/3MP3vWrVrfndZtWvX5MSxUzx8mDt6VWZGRo34qZJUAB7cf/jdaYT/y67j+MdzjNp1vr9tKpuN6zZz9vR52nVo893HVb8n7EM4/XoO5snjZ6SmplK6TCmaNW/K8JFD+KNtq+wpWAnJ87h09vR5unTowevXb1BXU6N8hfK0bf8HY8ePyhPnWvI8P/jVz8eE3EM0LglKIyoyigUBi4G055u/lW2SlwS/CiYpKRmAF89f4mDjTExMLOrqahQoWCA9f+Po4eMMHzkE1zmOmb7r8auty4y8fPGK9Ws2AdC7b08KFy6Uo/PnZmFh4URERFKkSGFiYmJ5+uQZT588Y/PGbejMnIbxbENFl5itdu/cmz4y2fCRQ785zdMnz9L/vnTpKvN8AkhKSkZTUxN1DQ3evn3Hnn/3s3f3AQyN9ZhpqJMTpStcyPsQWjfr+M33/ur6J55zXX9qeR9zr4oXL0a3Hn9nuT5FqfN7Y5ISk756vXnLZvjO90RD4/8jK73/76IEoEzZMt9d5sf3YqJjiI2NRUtLS44V55yKFf/fG+3B/Yc0bPT148pJSUk8e/ocgOioaOLi4ihYsGCO1ZgbZcdxfPeuvdy6eQeA4aO+fWxUNm/fvMPNxQtNTU1c3B1+ev74+Hhu3bxD0aJFSUlJ5uWLV7x88Yqd//zLkOGDcPVw+CVG7JLncenNm7fkz5+fQoUKERMTw4P7D3lw/yHr12zE2t6CMeNGyv8L5CB5nh/86udjQu4hHosTlIJEImGWgRnv34WgoaGBvZONokvKdpH/DW0OEOC/EFVVVeYv9OXm/ctcu32BUxeO0KtPDwA2bdjKsiWrMrXcX3Fdfk9CfAK6MwyJj4+nRInizLYwztH5c6uq1apgbmXC4ZN7ufv4GldunefWg8usWreUBo3qI5VKCfBfxNJFKxRdarba9N8jcXXr1fnmhS5AZOT/92MfT39KlynN6g3LuPXgMjfuXuTA0X/5o00rpFIpPl7z2L/3YI7Urmj58uenZKmSlCxV8rPHSnv16YG5lQnFihfL9LKiIqPS11v/QX1z3ZDfnyr13zr5tEGkTdvW2NhbUKFC+c+mjYmNTf+7QAHN7y7z0/diY2K/O52yq9+wHiVLlQRgUeBSUlJSvppm9Yp16UN5A5/9LXwuu47jT548xdoirXGmRavmuSZE3crcjuioaAxm6X4WBP8jZcqURt9Ilz0Hd3D38XWu3j7P7YdX2bJjPe06tAFg66btONu7Z1fpSkUex6X6Deph72zNqfOHufckbZ3euHeRwMV+VKlSmaSkZGwtHdm3J3f/Xsrj/ECcjwm5jWhcEpSCo60rRw8fB8DBxYa69WortqAcIJFK//+3RIK7lzO9+nRHTU0NgAoVyuMf6E3denUAWDBv0TdPtr/0K67Lb0lJScFQz4RbN26jpqaGzzzPDANK5T1/bjZgUF+maU+mevVq6dujuro6HTq1Y8v2dTRqnDZ6od/c+URFRSuy1Gzz4P5Drl29AWT8GJZE8v/9WCqVErjYj/Yd2qaHEdesVYMlKwMpVTrtotnfJzAbq1Yev/1WgqCrpwi6eoo7j65yJugYuvrTOXLoGL26DmDD2s2ZXtaOf/4lMTERyP2PxJ06f4Sgq6e49eAyQddOY2kzmzu37zGwzzB8PP0VXZ5CqaqqMtNQG4BHDx8zZbw2t27eJikp7RHCxQuW4enuk35MAlD5Rui3kCY7juMh70OYPG4GUZFRlClTGr/5Xt8MXlc2O7bt4tiRE9SrX5fJX4zW9SMdOrXD0FiPuvVqp/cszJ8/P81bNGXVuqV07f4XAGtXb/isp4rwfRMmj2XchNFUqFghPSy7QIEC9OjVje27N6aHhLs6eSD95Fw5t5HH+YE4HxNyG+X/RRDyPFenOaxeuQ4Aa3vzz0Y5y8s+7SJctVqVbz7qkS9fPqZOnwhAeHgEt27cznCZv+q6/FJqaipGM005eOAIqqqq+MzzpEOndjk2f16moamBibkhkDZ63tnT5xRbUDb52GtJQ0Pjs6Hhv1So0P/347bt//jmyINaWlqMHT8KgHt37xPy34hYvwoVFRXKlS+L8WxDfObNITk5GRtLB+7euZep+bf890hck6aNqF0n7+THlSz5G1OmT2Tl2sWoqKgwz28BRw4fS3+/0Ce/EfHxCd9dzqfvaRXKnY/EfTR2/CimTp8EwMkTp+nXcwh1qjemdbOOuLt4UaFieaZpT0qfvmjRIooqNVeT5TgeGvqBMSMm8vzZC0qWKsnaTSsoV75sNleadSEhoTjZu5E/f35c5zjK9dG1fPnyYWFtCqTdJDzy3429vCy7j0vFixdHR28aAMGvXnP71h0ZqlQO2X1+8Kucjwm5i2hcEhTK3dkzvSunpc1sJk35dYbpLPtJL5jfa1T/7nQ1Phk159PRdL70K6/LT6WmpmKkP5s9/+4nf/78zPX3+O4oX9kx/6+gWfMm6X+/fPFKcYVkk6SkJHZu/xeAHr26USSDC9hPe7PVqPHtEa4AatT8/3uvX31/P87revTqRvkK5ZBIJGzesO2H09+6eZvbt+4Cub/X0vc0btooPcx147ot6a+XLvP/bevd23ffnf/je4UKF8q1eUufsrAxZfM/6xg8bCC1ategXPlyNG7SCOPZBuw+sJ18+dJ6OlSoWD5XPyKpaD9zHA8N/cCY4RN4+OAxv5X8jXWbVmR43qJM5rjNJTw8ghGjh/J7jWrExsZ+9l9ycnL6tB9fS0r6Ohfte6pWq0KJEsUBePn8pdzrVzY5cVxq+sm2+eJ57j3HyInzg7x+PibkPnk/eU5QWm5OnixZtBwAcysTpvzXQ+dXUax4McqWLcPbDH6cAT7tEfy9QO9ffV1+9LHH0e5d+9Ibhvr065Vj8wt5w+GDRwkLCwd+3KBRs2YN8ufPT2pqaobTfdaz/xcfjrhs2TK8Dn7Ds2fPfzjtxyBvLa2C9Omfd/fFj+G3z5+9SH/t01G4Htx/+NkFyKfu/zdqWs3vvJ8btWjZ7LujJ30cZbVZ86Y5WdIvKzT0A6OHjf+sYalmrRqKLivTXv13wb1u9UbWrd6Y4bQNa7cA0h7bsnWwzPbacqNf+bj0s8T5gfArEj2XBIVwdZrzWWPINO3JCq5IMdr/96jVowyGan304FH63xUrVfzqfbEu06SmpmKoZ/JZw1Df/r1zbP5fydUr19P//tY2mdt9fCSuStXKtG7TMsNpNTQ1aNU67YLk0aMM9uOHafuxiooKFStV+O50eZ1UKuXly7SLvUI/eFQiIT6BXTv2AGlB4HmhV873vHyR1uPh0+9YrXpVylcoB8CJY6e+OV9cXByXgi4D0L5j3n90NyQkNP3Rj0FD+iu4mtwtM8fxkJDQrxqWMhp+/lf0/NmL9JsRH7OC8rKcOC59um3m5nWaE+cHef18TMh9ROOSkONcneZ89vjWr9oYAqSPsvL82QsO7j/81fsSiYQl/62rsmXL0KBhvc/eF+syzcceR3v+3f9fRtKcn25Yysr8ecmPwjMTE5Pw9vAFoGDBgrRr/0cOVJVzgoNfc+ZU2sXr0BGDv9tb8FMf9+Ozp89z6+bXuWixsbGsXb0BSMsN+u23EnKsWHlkZsCBLZu2E/I+LVOidZtWGU67f+9BoiKjABg+Knc+EpeamvrDferM6XNcv3YT4LPGTBUVlfQGlN279vHqZfBX865ZuZ7Y2Djy589P/0F95Fi58klNTcXG3J6kpGQaN2lEx87tFV2S0pLHcfzTR+FKlirJ+s0rc2XD0oatq3ny6u53/9M30k2f9uNrH3st/Wg9SqVS3Jw9gbT8pS5/d86276Essnpc+tE6jQiPYMH8xQCUK1+O+g3qyqlyxcjK+cGvfj4m5E6icUnIUZ/mAlnZmf2yj2991Kp1C3r2TsvzsTC1Yd+eg+kXaMHBrzHQNebe3fsAGJsZfjYqS15cl5ERkYSFhaf/93GkjYT4+M9ej/1kKNyPGUm7d+1DVVUV3/meP/8oXBbmV2ayrM+g8xcZM2Ii/2zdyZvXb9NfT05O5szpcwwfNCZ9FLWZhtoZ5hHlRls2bkcikaCqqsqQoQMyNU//QX1p3KQRUqkUnWkGnDl9DolEAqT1Spw2UZeQ96Hky5cPYzPD7CtejmTZdi4FXWH44DFfbTsAT588w8PVG2tzewCqVKnMkKEZD2H+sQdZrdo1cu0jUG9ev6VP90GsX7uJF89ffnax8Pr1GxbMX8L0SXpIpVKKFSvK5KmfZ+VNmT6JUqVLEh8fz+Tx07n536AOSUlJrF29AR+vtBHmRoweSvXq1XLui2WTF89f4uXhy62bt0lMSBshUCKRcOniFcaNmsLBA0coUrQInj6u32z4/XTb/NibBCAuNu6z1+Pj43PsO2WVIo7jHz6EpTcslSqd1rCUmx6Fk5fgV68Z0HvYV/uvRCLh6uVrTBwzLf3G4Mgxw6j+e+7aB2XZtiBrx6Ud23YxY8pM9u05SGjoh/TXE+ITOLj/MIP7j+TFf9lVFtYmSjMaoazrKivnB7/6+ZiQO4nMJSHHBAe/ZvHCtMe38uXLx6LAZSwKXPbd6adOn8jUGZO++35e4enjyofQDwRduITudAPUNdQpoFmAyMjI9Gn0jXQZ/MmFbl5dl316DCL4G2GGixcuT/++AIOHDsDTxw2AyxevsHvnXiDtjpq9jQv2Ni7f/QxbB4vPGo+yOr8yk2V9SqVpd9jOnj4PgKamJgULFiA6OiY9+DRfvnzM0J3KdJ0pOfAtco5EImHr5u0AdO7S8bPg0ozky5ePxcvnM2bERB4+eMzYEZMoUKAAqmqqRP83NLCamhoOzta0bZc77izKsu0AXLxwmYsX0h6H0NDQQEurIHFx8SQk/H/koLr16rBo2Xw0C2h+9/OfPX1O0IVLQFoPstzs7p176Y1q6upqFCpUiISEROLi4tKnqVS5IoGL/ShVutRn8xYpUpilKxcyYfQUHj54TP9eQyhUSIvExKT0/bFDp3ZY21nk2PfJTjExMQTOW0TgvEUAFC1alLi4uPTvWr5CORYunffdnJcWjdp+83V7G2fsbZzT/61vpIuhsZ6cq88eijiOr1u9gQf30x7ViY2JY9SwCRnWuGPPZsqXLyfT91N2N67f5Mb1tJ6F6hrqFNLSIiY2lqTE/4d+Dxk+CDtHK0WVKDNZj/NZOS6lSiQc3H84vVGuYMGCaGioExUVnZ5NpK6hjpWtmVKda8m6rrJyfvArn48JuZdoXBJyjFTy/zu2EomE0B8MtxkbG5fh+3lFwYIFWb9lFVs2buOfbbt4cP8hsbFxlC1bhhatmzN+4hiat/j8rr1Yl/8n+WRdJCcn/3BdJPx3N1xe8+c1tevWxNJmNlcuX+P+vQeEh4UTFRWNZgFNatT8nZatmjNi9DDq1M07Q8J/dObUOV4HvwF+fmSyUqVLsWvfdtasXMfuXft4+vQZiQkJVKxUgTZtWzNp6nhq18l76+xTDRrVZ66fB+fPBXHzxm1CQkKJCI9AXV2dKlUqU79hPXr06krP3t3Jnz9/hsvasmk7UqkUdXU1Bg7Ovdk6pcuUYv5CXy6cC+LatRu8f/ue8PBw8uXLT/kK5ahbrw5/d+tC/wF9vtvY1rBRffYf/ZdFgUs5evg4b16/pUDBAjSu3YjBQ/ozdMRgpbm7n1UVK1ZgpqEOF84F8fzZC8LDwylUSIvqNarTvWdXRo8dToECBRRdptLL6nH809/FuLi4zxpCvzl9qkSu9SuLkiV/w97JmiuXr3H3zl3CPoQTGRmFhoY6lSpVpFnzJgwdMfi74fN5mazHpTZtW2FsZsjVy9d4/PAJ4RERREfHUKhQIapUrUybdq0ZNWZ4rs5a+pKs5we/8vmYkHupSH/0QCcQFRVF0aJFiYyMpEgR0eUut1JRUcFtjiPDRw1VdClKL2DeIvznBnD/6Q1Fl5Ir1KnemD//6sSCJf6KLkXpLVuyEndnLx4+v6XoUnKFxvVa0axZY1asXaLoUpTe+rWbsLGw5/HLu4ouJVdo1bQD1apXZdO2NYouRelt37oDE0MLbty79MMgdgHq12zGmHEjsbAxVXQpSs/FwYNlS1Zy7U4QRYoUVnQ5Sq9RnRYMHNwfBxcbRZei9Hy95+HvE8j5yycy3RP5Vzak/ygaN2rC8uXLfzyx8Ev5mbagvHGrSxAEQRAEQRAEQRAEQVAI0bgkCIIgCIIgCIIgCIIgyEw0LgmCIAiCIAiCIAiCIAgyE41LgiAIgiAIgiAIgiAIgsxE45IgCIIgCIIgCIIgCIIgM9G4JAiCIAiCIAiCIAiCIMhMNC4JgiAIgiAIgiAIgiAIMhONS4IgCIIgCIIgCIIgCILMROOSIAiCIAiCIAiCIAiCIDPRuCQIgiAIgiAIgiAIgiDITDQuCYIgCIIgCIIgCIIgCDITjUuCIAiCIAiCIAiCIAiCzETjkiAIgiAIgiAIgiAIgiAz0bj0C5BKpWzduhWA06fOEhUZpeCKlFto6AcunAtCIpVw6sQZRZej1KRSKYcPHiU5OZlnT58TER6h6JKUWnh4OOfPBiGVSjly+BhSqVTRJSm1E8dOkRAfz4sXr/jwIUzR5Si1yIhIzpw6h1QKB/YdEtvWD5w5fY6Y6GjeBL8h5H2IostRatHRMZw6cRYQ21ZmBJ2/SEpKClcuX+XN67eKLkepxcbGcuf2XQD27z2IRCJRcEXK7crlqyQlJXPt2g2CXwUruhylFh8fz43rtwDYv++Q2LZ+4Mb1W7x48YIjR47w+PFjRZcj5GKicSmPu379On/++SdDhw6lQsUK7NtzkE7turFh7WZSU1MVXZ5SSUpKYumiFXRu25VzZy6gqqrK+NFTmDx+Bk+fPFN0eUrnwf2HjB05iWmTdNHU1OThg0d0atuV1SvXkZKSoujylEpycjIrl62hU5tuHD96EnV1NaZO0GH8qCk8eih+xL/05PFTJo6dxsSx01BVVeX5sxd0atuVZUtWkpSUpOjylEpqairr1mykU9uuHNx/CM0CmmhP1Wf0sAncu/tA0eUpnefPXjBtki5jR0wCFRXevHlL53bdWRS4lMREsW19KjU1lU0bttKpbVf+3bkHzQKamBpZMHTAKG7dvK3o8pRO8KtgdKcbMmLIOFTyqXD92k26dOjOfL8FJMQnKLo8pSKRSPhn607+bNed8+eCKFiwAOYm1gzqN4LrV28oujyl8+b1Wwz1TBnSfxQAd+/co0uHnvh4zSMuLk7B1SkXqVTKvzv38Gf77hw/dpICBQtgb+1Mv56DuXTxiqLLUzrv373H1MiCAb2HEhsbR2xcDPXq1cPCwoLo6GhFlyfkQqJxKY8KCQlh+vTpNGvWjFfBL1mxZjGnzh9mx54tFC1aBCtzO3p3G8iFc0GKLlXhpFIpR48cp2vn3rg5e1KpciUOHt/N7QdXmDx1PGdOnaPbn31wc/IkKkocaCPCI7C3dqZX1wFcvngVPQNtbt6/xO6D/1CyVEnsrZ3p+Vc/Tp86q+hSlcKpE2fo8Vc/HO1cKVO2NHsO7eDWgyto603jYtCl9PciIyIVXarCRUVG4eLoQbcufTh35gJTp0/i5v3LHDy2mwoVyuPi4EH3Ln05fvSkoktVCufOXKBX1wHYWDhQ4rcS7NyzlTsPr2IwS5drV2/Qu1vae2Fh4YouVeFiYmLxcPWma+fenDx+ivGTxnDr/mUOn9hD1WpVmOM2l66denHowBHRMwe4GHSZfj2HYGFqQ6FCWmzduYE7D69iamHE3Tv36N9rKOYmNoSEhCq6VIWLi4vDx9OfLh16cvjgUUaOHsqt+5c5duYgtWvXwsdrHl069mDv7gNi2wKuXbnOwL7DMTY0R01dnU3b1nLrwRVs7C149OBx2nsGZrx7+17RpSpcQnwC8/0W0KVDd/bu2c/goQO4ce8ip88fpWGj+gT4L+TP9j3Y+c9usW0BN2/cZkj/URjomgAqrNmwnNsPruDoasvzZy8ZNnA0+jrGvH79RtGlKlxiYhILA5bQuV13dv6zm779e3H5xllOnD3EDN2p+Pr6UKtWLVauXCl6fQk/RUWaiaNRVFQURYsWJTIykiJFiuREXYKMkpKSCAgIwMHBAalUgsEsPcaMH4mamtpn023esBVnRw9iomPo2bsbFtazqVipgoKqVpxHDx/jZOfGqZNnKF68GK5zHOnes+tn00SER6CnbcT5s0EUKVoEM0tjhgwbSP78+RVUtWKkpKSwfu0mvD18iYuLp1Pn9vjM86JwkUKfTbfzn3+xs3ImKiqKv7r+iZWtGVWrVVFQ1Yrz9MkznB3cOXbkBEWLFsHBxYZ+A/p8Nk10VAz6OkacPnUWLS0tTMyNGDFqKKqqqgqqWjFSU1PZvGEbc9znEh0dTdt2fzB/gQ9Fin7+e7N39wGsze2IiIikU+cO2DhYUP33agqqWnFevniFi6MHB/cfpnDhwtg4WDBk2MDPpomJiWWW/myOHTmBZgFNjE0NGD1uxFe/BXmdRCJh+9aduDt7EhERScvWLQhY5EOJEiU+m+7wwaOYm1gTFhZOm3atsXWwpHadWgqqWnGCg1/j7uLFnl370CqkhYW1KaPGDP9smoSEBIwNzDl44DDqauoYGusxftIY1NXVFVS1YkilUnb+sxs3pzl8+BBGk2aNWbDYj1KlS3023ckTpzAxtCQ0JJQWLZth72xNvfp1FVS14rx7+x4PV292bN9FwYIFMTEzYMLkcZ9Nk5SUhJmxNXv+3Ud+1fzMNNRh8pTxaGhqKKhqxZBKpezbcwBnB3fevX1Pw0YNWLDUn3Llyn423fmzQRjpz+bd23c0adYYeydrGjVuoKCqFSckJBRvD1+2bNqOpqYmM410mKEz5bNpUlJSsDSzY+f2Xaio5ENbbxrTtCdRoEABBVWtGFKplEMHjuBk787r4NfUqVebhYv9qVSl0mfTBQe/xsPFi9279tGiRQv8/f1p06aNgqoWFO1n2oJE41Iesm/fPoyMDHn48BEjRg/FyESf334r8d3pU1JSsLNyYuvmfwCYrjOZGbpTKViwYE6VrDCREZH4+QSwesU61NRUmTR1AsazDciX7/ud+a5fvclMnVm8evmKuvXqYO9sTctWzXOwasU5feosDtbOPH78lGrVqxKw2I86GVx4SSQSnO3dWL92ExKJlMnTJqCrP4NChbRysGrFiIqKJsBvIcuXriJ//vyMHT8SC5vZGW5bd27dRU/biGdPn1Oj5u/YO1vTtt0fOVi14lw4F4SdtTMP7j+kcpVKzFvgQ8NG9b87vUQiwcPVm9Ur1pKcnMKEyWPRN9T5qiEqL4qNjWXB/CUsXrgMFVQYPmoo9k5WGW5bDx88QneaAY8ePaFa9arYOVrRsXP7HKxacS5fuoq9tRO3b92lQsXy+AV40ax50+9OL5FI8J07nyULlpOcnMyYcSMxNNajWPFiOVe0gsTHx7MocBkLA5YglUoZOLgfzu72GTZ0P336DJ2pBjy4/5CKlSpg62hJl786o6KikoOVK8b1azext3Hm+tUblClbBt95c2jdplWG8wT4LyTAfxGJiYkMHzUE49mGGZ6j5RWJCYksXbKS+X4LSE1JpU+/nrh7OWfYGPnqZTDaU/W5c/su5cqVxcbBgm49/v4ltq07t+9ib+3MpYtXKFW6JF4+7nTo1C7DeZYuWoGP9zzi4+IZMmwgpuZGXzVy5kWJiUmsWr4Gv7kBJCcn063H33j5uqGpqfnded68eYvuNAOuX79JqVIlsbYzp3ffnr/EtnX/3gMcbF05f/YCJX4rgbunE39365LhPEEXLuFk58btW3cYPXo07u7uVKxYMYcqFpSFaFz6xdy/fx+jWUbs27uPP9q0wsbBkrr1amd6/pD3IehMN+Dq5euU+K0Eljaz6T+wT5480KakpLBpw1Y83eYSGxtL+w5t8Q/0+ar3TUbWr92Em7MnsTGx9O7bA3NrUypUKJ+NVSvO82cvcHZw58ihYxQpUgQHF2v6D+yb6fnDwsLQnW7ExQuXKFasKObWpgwa0j/Di+HcKjU1la2b/8HD1ZuoyCj+aNuK+Qt8furCdOvmf3CycyM6OppuPf7G0mY2lb+4m5RXvHoZjJuzJ/v2HKBQ4UJY25oxbOSQTM8fFRnFTJ1ZnDl1jsKFCzHbwphhIwfnyR6FEomEHdt34ebkSXh4BM1bNCVgsR8lS/6W6WXs3rUXGwsHIiOj+LNLR6zszalePW/2+nrz+i3uLl78u3MPWloFmW1pzNjxozI9f0xMLIa6xpw4fpoCBQpgYmbIqLHD82SPQqlUyu5de3Fx9CDkfShNmjYicLE/ZcqWzvQyDuw7hOVsW8LDI2jfoS22jpbUqPl7NlatOO/fvcfT3YdtW3ZQoGABjIz1mTJ9Qqbnj4uLw9jAnMMHj6KhqYGRyUzGjh+VJ3t9SaVS9u89hLO9G2/fvqN+g3oELvb7qV7yJ46dwtTIgtDQD7T+oyW2jlY/dX6bm4SGfmCupx+b1m9FQ0MDPQNtdGZOy/T8CQkJmBlbsW/PQVRVVdE30mHilPFoaOTNbevo4eM42LoQ/Oo1tevUYsESP6pUzXwv+TOnzmFsaMb7dyE0a94EOyfrDG9s5Wbh4eH4es1n7eoNqGuoM117MvpGupk+F/94fvvxyQVzc3NMTEx+uV5fvzLRuPSLiIiIwNHRkXnz5lGuXFksbEzp3rOrzI1CQecvYjjTlLdv3tG4aSPsnaxp3KShnKtWnHNnLmBn7cSjh4+pWq0K8xf4UK+BbF3TU1JSsLFwYPvWnQBo601jus7kPHOgjYmJJcB/IcsWryRfPhVGjRmOtb2FzI1CV69eR1/bmOBXwdRvUBd7Zxuat/h+D4Lc5mLQZeytnbl75x4VK1VgXqAPjZvKtu9IJBLsbVzYvGELEqmUqdMnoa03Lc/0+oqLi2NhwBIWBS4DYMiwgTi42Mh84X7r5h30Zhjy4vlLatWuiYOz9Q97EOQm165cx9baiVs3blO+fDn8Arxo3rKZTMuSSCS4OXmyZtV6UlNTmTRlPLoGMyhSpLCcq1aMhPgElixaTuC8RaSmSug/qC8u7vYyX7jfu/cAvemGPHn8lN9/r4adszXtO7SVc9WKc/PGbeytnbl65RplypTG299D5h6TEokE7zl+LF+yiuTkZMZNGI3BLF2KFisq56oVIzEhkeVLVzPPN5CUlBR69umOh5dzhj0kMvLk8VO0p+rz8MEjKlephJ2jFX/+1UnOVSvO3Tv3cbBxJujCJUqW+g3PuW50+rODzMvzmzufRYHLSExMZNSY4RiZ6lOiRHE5Vqw4SUlJrF65Hl8vfxITk+ja/S+8fN1kforg5fOXzJimz7079ylfoTy2Dhb83a1Lnrlh/PDBIxztXDlz6hzFSxTHzdOJbt3/knl5CwOXMs8nkISEBIYOH4SxmSGlSpWUY8WKk5yczPo1m/Ce40d8fDyd/+yAz3wvmc8nP/bMX7l8DeXLl8fT05MhQ4bkmW1L+D7RuJTHpaamsmzZMqysrIiLi0NHf7pcn0lfvmQV3p5+xMfFM2hIf2ZbzKJ0mczfxVQ2L56/xNVpTob5JLJ69/Y9OtMMuHb1OiVLlcTK1oy+/Xvl2gNtZvNJZLVm1XrmuHoTGxtH3/69MbcyoVz5sj+eUUkFB7/G3dmTPf/u/24+iaxCQz+gO92QyxevULx4MSxsTBkwqF+u7fX1MZ/E1WkOYR/CaNq8MYGLvs4nkdWWjdtwcnAnJjqGHr26Ymljlqtz5N6+eccct7np+SSm5oaMnzRWLsuOCI9gpvYszp29kJYjZzGLIcMH5dpeXx/zSZzs3Xj/LuS7+SSy+ixH7u/OWNmZ5+ocuZD3IXh6+LJt8z/fzSeRVXRUDAa6szh18kyeyJFLzyexc+P16zfUrV+HBYv8vsonkdW+PQewMkvLkevYqT02Dhb8XqO6XJatCB8+hOHj6c+GdZvR0NBghu5U9I105LLs2Ni0HLmjh9Ny5GaZ6H8zUzQ3OXbkBA62Luk3RwIX+8ktR/DIoWOYmVgR9iGcP9q2xs4xd+fIRYRH4Dc3gDWr1qOmpsbkaROYZaovl3OihIQETAwtOLD/EOpq6hjM0mX8pLG5utfXqZNncLB24cmTp1T/vRqBS/ypVauGXJb99MkzXJ3mcOTQMTp27Iifnx9NmjSRy7IF5SQal/KwEydOYGCgz/XrNxg0pD+m5rN+qvt6ZiUlJTHb2Iq9/+5HVVWVmYY6TJoyLleFKsqSTyKrc2cuMEt/Nu/evadps8bYO9vkuu61P5tPIquUlBQsZtuyc/u/5M+fFqo4dUbuClX8mE+yYP5iAAYN6Y+Tm122XEBdvngFA10TXr9+Q4NG9XFwsqZp8yZy/5zs9Gk+SdlyZfCd50mrP1rK/XNSUlKwt3Zmy6btSJEyQ2dKrsuR+zKfpG+/nrj9IJ9EVjeu3URPOy1Hrk7d2tg7W9OqdQu5f052un3rDvbWzly+dDXT+SSy+DRHLjVVkp4jV7hw5h+pVrQv80m69+yKp4+rzL1vMnLvzj10phvm6hy5L/NJ5ni70OXvznL/HIlEgqfbXFYuX0NycgrjJ43BwEg3V+XIJScns3bVBuZ6+ZMQn0CXvzvjM29Othx7Hz18jM40g/Re6PZO1rkuR+7xoyc42rly6sQZihUvhouHAz17dZP750gkEvzmzmfxwuUkJSal5ciZ6FG8eO7p9ZWSksKGdZvxcvchLi6ejp3a4Tvf+6fiLDLr0xy5ChXLY+doRZe/c1eO3LOnz3FxcOfI4eMUKVoEx28MJiMvJ4+fxtnBncePnjBlyhScnZ0pXTr3dkYQvk80LuVBz549Y/bs2WzZsoUmTRtj62BBk2aNs/1zXz5/ifZ0A+7evke58uWwdbCga/e/lPpA+1U+SctmBCzy/al8ElktXrAMv7kBJCQkMHjYQEzNDJU+VDGr+SQyf+6bt2hP0efmjVuULlMKaztzevXpodTb1sd8EmcHD0JDZMsnkdWq5Wvw8vAlNjaO/gP7YmZpTNlyZbL9c7Pi03ySggULYGSiz+RpE7L9c3NjjtyX+SQNGtYjcMk8KlQol+2fvWHdJtycPInJRTlyoaEf8J7jx+YNW9HU1EBX/+fySWQVFhaG3nQjgi5comjRophbmzB46ACl7lEoj3wSWW3fuhNHWxeioqLp2v0vrGzNlD5HLqv5JLL6MkfO1GIWw0cOUfoehSeOncLB1iW9ITFwsV+OZG7t3rUXG0tHIiMic02OXFRkFH4+AaxavhY1NTUmThmLiZlRtm9bMTGxGOqZcOLYqVyVI3fm9DkcrJ3TBqSoVpWART7UqVcn2z/34P7DWMy2JTwsnHYd2mDrYElNOfX6yS7R0THpcRb58+dn9LgRWNmaZfu2lZyczLrVG/GbOx+pFOzs7NDT08uTOXK/MtG4lIfExsbi7u6Op6cnRYsVxcxiFv0H9c3xE9ljR04we5YlHz6E8UebVtg6WlGnrvJ1r716+Rp2Ns5yySeRVUJCAqazLDmw9xBqamroG+kwYfI4pete+618Erc5jjl+snHqxBlMjSx4/z6E5i2aYu9sTf0G9XK0hsxIyydx4uqV61nOJ5FVUlISlqa27Nq5h/z586FnoM3kqRPQLCD/ngdZ8WU+Sa8+3fHwdkFDI2d7PqblyM3m7Zu3NGrSEAcnaxo3bZSjNWTG3Tv3cLBxkVs+iSxSUlKwsXRk+5YdAMzQncp0nclK1+tL3vkksvo0R65e/brYO1vTIod/azJD3vkkspBIJDjYurJp/WYkEilTZyhnjpy880lkdevmHWZqG/H82Qtq1a6JvZM1f7RVvhy5J0+e4mzvzvGjJylarCjObnb07tszR2uQSCS4u3ixesU6UlNTmThlHHoG2kqXI5eampo+mEx0dMx/g8l453jvtPv3H6I7zSA9R87WyYoOHeXf0zOrXjx/iYujB4cOHKFwkcLYOVoxaEj/HK1BIpEw19OfZYtXpufI6RvpKN3ooRKJJG0wGRdvIiMjafVHC+YvlF+cRWaFhYXj6z2P9Ws2UaPG7/j4+NKrV68crUHIPqJxKQ+QSqWsX78eMzMzQkNDmTJ9AjN0p6KlpdiTsbRQxaUkJiYxetwIjExmKkX32uzMJ5HV82fP0ZlqwL17D6hQoTy2jpb81fVPhfeekEql7N29H2cH92zJJ5FV4PzFBPgtICEhkaHDB2Nibpgjvc1+5Mt8EoNZukzTnqzQmoKD36AzdSa3bt6hbNkyWNmZ07N3N6XYtg4dOIKjnRtvsiGfRFbKmiOXnfkkslLWHDmpVMqxoydwtHXNlnwSWaXlyKWNPtqnXy/MrU0oXz77e5v9SHbmk8jqyxw5c2tTBg5Wjhy57MwnkdWWTdtxsndTuhy5qKho5vstYPnSVajmV2XcxNGYW5ko9P9jRHgEM3Vmce7MBQoXKYy5pbHS5MidPxuEnbUTDx88okrVysxb4EODhoq9gaasOXIxMbEEzlvE0kUrUMmnwohRw7BztFTotvVpjlzBglqYmBsycvQwpej1deniFeytnbhz+x4VK1bAb4E3TZtm/1MtGbl39wHO9m6cPXOeHj174DPXhzp1sr+3mZC9RONSLhcUFISBgT7nz1+gR69uWFibUqlyRUWXlS4mJhajmaYcP3qSAgUKMMtUn9HjRigkVDEhPoFlH/NJUiXZmk8iq8MHj2JmYk14WDht2/+BrYMltWrXVEgtn+aTlC5dCk8ft2zJJ5FVfHw8JoYWHDxwGA11dQyNZzJu4miF/P9MTExi5bLV+PsEZns+iaxOHD+FqZEloSGhtGzVHHtna+rmQJfxb7l39wGOti6cPxfEb7+VwGOuC13+6qyQWr7lyxw5PUNtuQ6E8DOSk5NZs2o9cz39SUxIzNZ8ElmdPxuE0czZvHv3jqbNGmPnZE2jxg0UUsujh49xsnfL9nwSWaWkpGBpZsfO7btQUcmHzkzF5cjlZD6JrC5fvIKBngmvg9/QoGE9HJxtFJYj9/TJM5wd3Dl25ES255PI4sscuenakxV2ozE1NZUtG7fh4TaX6Oho2rRtzbzAuUrVk+Pm9VvoaRvx8oXic+RevniFq9McDuw7ROHChbC2t2Do8EEKqeVbJBIJLo4erFu9kdTUVIXmyEkkEv7Ztgs3pzlERETSolVz5i/0UYobjB/du3MP3elGPH36jBo1qmPnbE279m0UUsvr129wd/Zi9669aGlpYWZlzJhxIxVSy7d8vNHo4jiHN6/foKenh52dHcWKFVN0aYKMRONSLvXmzRssLCxYtWoVderVxtbeUim7Qn/04MEjdKcZ8PjRE6pVr4q9k3WONVQoMp9EFhKJBF/v+SxZuJzk5OS0UEVjvRw7KQsN/YCXhy9bNm5Lyycx0EZHL/vzSWT19OkzdKboc//+QypVroitoyVd/sqZUEWpVMqRQ8dwtHUlODhn80lkNd9vAYHzFpOYmMiI0UOZZWrAb7/lTJfo8PBwfLzmsW71RjQ01JmmMwUDI12F93T5nlcvg9Geqs+d23cpV64sNg4WdOvxd47V+1k+Sa3fCVyUM/kkslq8cDl+3vPTcuSGDsDU3CjHcuQiIyLx8wlg9Yp1qKmpMnHKuBzJJ5HVmzdv0Zmqz43rtyhVuhTWdmb07tszx7atM6fPYW/tnPabnIP5JLJatWIdXu5zFZIjFx0dQ4DfApYtWZWj+SSyCnkfgu4MQ65cukaJEsWxtJlNv4F9cqzeoPMXsbN25v69B1SuXJF5C3xoqKDG5szYtH4LLo5ziImJoVef7lhYm1KhYs70+oqNjWVhwBIWLUgbTGbYiME4uNgo7bYVFhaG3gwjgs6n5ciZWRkzZNjAHKv3yuWr2Fs7c+vmHcpXKId/oHe2DCYjL9u37sTB1oVoBeTIxcfHs3jBchbMX4xUKqH/oH64ejgoRS+qb/kYkRDgv5CCBQvi7OzMlClTlKJHofBzRONSLpOQkICPjw+urq6oqathPNsgV4Q4frRrx27srJyIjIziz786YW1nTrXqVbPt8+7euYe9tTMXgy4rLJ9EVtFRMRjNNOHE8dMULFgAYzNDRo3JvlDFpKQkVq9Yh6/3PBITk+jW42+8fN1yzchs+/cexMrMjvDwCNp3bIutg2W2Xog/uP8QRztXzp4+T/ESxfHwcubvbl2y7fPkKS4uDmN9Mw4fOoaGpgZGJjMZO35UtvX6+hjiONfTPy2fpEtHfOZ5Kl2OyvfkdI7ck8dPcbJ348SxUwrLJ5FVQkICs2dZsX/vAdTU1LM9Ry41NZWN67fg6TaXmJhYheWTyOrMqXMYG5rx/l0IzZo3wd7ZmgYNs2/00OfPXuDi6MHhg0cpUqQwtgrIJ5HVlzlyuvozmDJtYrblyKWmpqblk7h6ExUZRes2LQlY6KtUvW8yktM5csGvgnF18mTfngMUKlQIK9vZDB81NNs+T55SUlKwtXRkWw7lyEkkEnZu/xc3Z0/CwsJp1qIJAQt9lX5Ql4+uXr2OgbYxr14FU69+HeydbbI1R+7N67d4uHqza8duCmoVxNR8FuMnjs62z5OnjzlyG9dvRiqRMmX6RHRmTs+28x+pVMqef/fh7OBOSEgojRs3JGCxn8LjLDLr3dv3eHmkDe7SuHEjfH396Ny5s6LLEn6CaFzKJaRSKTt27MDY2JiXL18ydsIo9A11KFqsqKJL+2kSiQRXJ0/WrlpPamoqk6aMR9dghlxDFT98CGOupx8b121BQ0MDnZnT0DPQltvyc9K9ew/QnWbA0yfP+P33atg5W9O+Q1u5Lf9jPomDjQsvX7yidu2aBC71p1q1qnL7jJwikUjw9vBl+dJVJCenMG7iaAyMdOW6n0SER+DrnTY6kJqaGlNnTMTQeKbS3mnMyONHT9CZZpCe72DnaEXnLh3l+hmnTpzB3saZp0+eKU0+iaw+zZEbNWY4Rqb6lCghvxy5qMgo5vktYMWy1ajmV2X8xNGYKTifRFbPnz1HZ5oh9+7ep0KF8tg4WPB3ty5y7Zlz7swF7G2c07ffgIW+1GtQV27Lz0kLAhYz3/f/OXLGZgaUKlVSbsv/Mp9k1Ohh2DgoNp9EVmk5cvrcunmbMmVLY21nIfccuYtBl7G3dubuHeXJJ5HViqWr8J7jR1xcPAMH92O2hbFcRy2Ni4tjUcBSFgYuBWDw0AE4utoqbQ+JjLx7+x6d6QZcu5KWI2dpM5t+A3rLddu6duU6djbO3Lx+i3Lly+I734uWrZrLbfk5ae3qDXi4eGdbjlxCfAJLF68gwH8hqRIJ/Qb0wdXDQaniLDIrNPQDejOMuBR0mWLFimJhM1vuOXK3bt7G3tqZK5evUbpMKbx9PWjXQTGP42XV9as3cLRz4+qVawwePBhPT0+qVVPuER6FNKJxKRe4efMmhoaGHD16lE6dO2Btb87vNaoruqwsiwiPQE/biPNngyhStAhmlmnda7PSCyspKYk1q9bj4zWPxIRE/ur6J3P9PZQqn0RWn4Uqdv0TK1uzLIcqfppPUvy/fJIeSpRPIqvoqBj0dYw4feocWloF04dpzsrJbkpKCuvXbsLbwzctn6Rze3zneSlVPoms9u4+gLW5HRERkXTq3AEbB4sshx9/mk9StGgRHJQsn0RWMTGxzNKfzbEjJ9AsoImxqUGWc+RSU1PZvGEbc9zT8knatvuD+Qt8ck3vm4wcPngUcxNrwsLCadOuNbYOltSuk7VeXy9fvMLF0YOD+w9TuHAhbBwsGTJsoJwqVpyEhASMDcw5eOAw6mrqGBrrMX7SmCxdSEkkErZv3Ym7sycREZG0bNWcgMW+OT46UHY4eeIUJob/z5Gzc7KiXv2sNS4GB7/G3cWLPbv2oVVICwtrU0aNGS6nihUnKSkJM2Nr9vy7j/yq+ZlpqJPlHDmpVMrOf3bj5jSHDx/CaNKsMQsW++Wa3jcZOX82CCP92bx7+44mzRpjL4ccuXdv3+Ph6p0+mIzxbAMmThknp4oV58scOW29aUzTzlqOnFQqZd+eAzg7uPPu7XsaNqxPwBJ/pY2z+BmXL13FQNc4PUfO3tk6y4/2hYSE4u3hy5ZN29HU1GCmoQ4zdKfKqWLF+XiM8XD1JiI8AhMTE8zNzSlUKPefd+dlonFJiYWGhmJnZ8fChQupWq0KVrZm/PlXJ0WXJXfXr95kpo4Rr14GU7deHeydrWW6i3P86EkcbF14/uxFrsgnkYVEIsHZ3o31azchkUjTQxV/tnvtl/kkk6aMx9jMMFfexc7InVt30dM2Ssusqfk7Ds42tGnX+qeXc/rUWRysnXn8+CnVqlclYLEfdbJ4gaxsJBIJHq7erFq+lpTUFCZMGou+oc5PN3BERUUT4LeQ5UvT8knGjB+Jpc3sPLdtfZkjZ+doRcfO7X96ORfOBWFn7cyD+w9zRT6JLCQSCb5z57NkQdZy5GJjY1kwfwmLFy5DRUWFYcOVO59EVk+fPkNnqgEP7j+kYqUKMufIXbl8FTsrJ27fukuFiuXxC/BS6nwSWX2aIzd81BCMZxv+dI5cfHw8iwKXsTBgCVKphIGD++Psbp8re99kRF45ctev3cTexpnrV29QpmxpfPw9lTr3U1ZLFi3H13s+8XHxDBk2UKYcucSERJZ+HEwmJZXefXvi4a1cg8nIw5s3b9GdZsD16zcpVaok1nbmMuXI3bl9F3trZy5dvEKp0iXx8nFXqsFk5GXVinV4us8lLjaOfgP6YGZpTLnyP/foWlJSEquWr8XXez5JyWlxFt6+7ko1mIw8xMbGsihwKUsWruC3337Dw8ODUaNG5bnf/rxCNC4poeTkZBYsWICdnR2pqanMNNJh3ITsy0NRFuvXbsLN2ZPYmFh69+2BubUpFSqU/+F8Tx4/xcnOjRPH0/JJXNwd6NWnew5UrDhhYWHoTjfi4oVLFCtWFHNrUwYN6f/DA21KSgqbNmzF0y0tGLV9hzb4B/rkid43Gdm6+R+c7NyIjo6mW4+/sbSZnalQxefPXuDs4M6RQ8coUqQwdk7WDBzcLwcqVpyoyChm6szizKlzFC5ciNkWxgwbOfiHPQq/zCf5o00r5i/0yTX5JLLavWsvNhYOaTlyXTpibW+RqRy5z/NJtLC2M2fYyCHZX7ACRUfHYqRn/NM5chKJhB3bd+Hm5El4eATNWzQlYLGfUo0OlB0O7DuE5WzbtBy5Dm2xdcxcjtyn+SRaWgUxyUX5JLKKi4vD2MCcwweP/lSOnFQqZfeuvbg4ehDyPpTGTXJXPomsjh05wWxjKz6EfqD1Hy2xdbSibr3aP5zv/bv3eLqn5aEUKFgAI2N9pkyfkP0FK9D/c+QOoqqqisEs3UzlyEmlUg7sO4STXdpgMvUb1CNwsR8VK+VMWLiiyJojFxr6gbmefmxavxUNDQ109aejqz8jBypWnKSkJCzN7Ni1Yzf582U+R04qlXL08HEc7Vx59TKYWrVrErjEL1fGWfyMVy+DcXfxYu/u/fzxR2v8/Pxp1SrvNWrndqJxSckcOHAAIyMj7t27x4hRQzEy1c/zJ9CfSklJwcbCge1bd6KiopIeqvit7rVf5ZNMGoOZpfEv1ZJ95fJVDHRNCH71mvoN6mLvbEPzFt++M33uzAXsrJ149PAxVatVYf4Cn1ybTyILiUSCvY0Lm9ZvQYqUaTMmo6337WGaY2JiCfBfyLLFK8mXT4VRY4ZjbW/xS21bt27eQW+GIS+ev6RW7Zo4OFvTus23f8Q/yyepVIF5gT40btowhytWHIlEgpuTJ2sykSP3ZT7JkGEDcXCxyXM9JDLyMzly165cx9baiVs3buf6fBJZSCQSvOf4sXzJyrQcuQmjMZj17Ry5hPgElixaTuC8RaRKJPQf0AeXXJpPIqsnj5+iPVU/UzlyN2+k5ZNcvXKNMmVK4+3vQdt2f+RwxYqVliO3jMTExAxz5BITk1ixdBX+PoGkpKTQs093PLyc81wPiYy8eP4C7akG3Lt7n/IVymObQY7c3Tv3cbR14cL5i5Qs+RuePrlnMBl5+TxHbhDGZobfzJFLSkpi9cr1+Hr5k5iYxN/duuDt554n4iwyKzj4DbpT9bmZniNnTs/e3b+5bT188AhHO1fOnDpH8eLFcPN0oluPvxVQteJcOBeEo50bd+/cY9y4cbi5uVG+/I87Iwg5QzQuKYmHDx8ya5YRu3fvodUfLbGxN6d+g3qKLkth3r19j840fa5dvUHJUiWxtjOjT79eqKio/D+fxM2b6OgY2rZvw/wFc/NEPoms1qxazxxXb2Jj4+jbvzfmVibp3Ws/zycpjI2DRZ7IJ5FVaOgHdKcbcvniFYoXL4aFjSkDBqWFKn6VT9K6BQGLfPJEPomsNm/YirOjBzHRMfTs3Q0L69npd16Dg1/j7uzJnn/356l8EllllCP3MTvA1WkOYR/CaNqsMYF5JJ9EVhnlyH2ZT2JiZsiEyWMVXLHiREfFoK87i9Mnz6ClpYWJuREjRg1FVVX163ySRvUJXDKP8j/5iEVeklGOXMj7EDw9fNm2+R80NTWZaaTDDJ0pCq5YcTLKkZNKpRw6cAQnOzdev35DnXq1WbjYn0o5NJy6MsooRy4sLJy5c/zYsG4zGhoazNCdgr6RroIrVpwf5cgdO3ICB1uX/25i1SBwsX+W8x5zs5MnTmNqaEFISCgtWjbD3tk6PUcuMiISv7kBrF65DjU1NSZPG88sU4Nf6qbnpz5eC3p7+pGYkIiVlRVGRka/VIO3shKNSwoWGRmJs7Mzfn5+lClTGnNrU7mPepKbnT1zHmN9M969e0/TZo0ZM24kixYsS8snqVKJ+Qt9adDw122E+1RKSgoWs23Zuf1f8udPC1VMSkpOyydBheGjhmLvZPXL/hB96fLFKxjomvD69RsaNKrPxEljWb50VZ7PJ5FFSkoK9tbObNm0HZAyXWcK+fLl/y+fRMqgIf1xcrP7pXrfZOTTHLk6dWszdfpEVq9az/WrNyhbrgy+8zxp9UdLRZepFL7MkZs0dTyFCxdivv9CUlNS6duvJ25eeS+fRFZ3b99Fd8Z/OXI1qqOtN40N6zbn+XwSWUgkEua4zWXlsjWkpKQwYfJYSpUqib9PIMnJyXTr+TdePm7iYuQ/X+bI6epPZ+vmHZw/e4ESv5VgjrcLXf7urOgylcKXOXKjx46gUpVK+M2dT0J8Al3+7ozPvDm/VO+bjHyaI1ehYnn0jXTZvXMvJ0+cplixorjMcaRnHhhMRl4C/BcS4L+IxMREho0YQp26tfDx8ic2No4OndrhN987z8dZZNbHp1hWLV9LpUoV8faey4ABA8R1tAKJxiUF69q1K2fOnkFbd2qmnrP9VS1asBT/uYHEx8dTUKsgtvYWeT6fRFZv3rxFe6o+N6/fQkVF5ZfJJ5HVquVr8PTwJS42jgIFC2BuZcLY8aMUXZZSCnkfgs50A65evo5UKqVJ00YELvaX67DWecmnOXKamprMMjXI8/kksvo0R04qlf4y+SSy2rZlB462rkRHR6OhocFMQ210Zk5XdFlK6dMcOalUSu06tViwxI8qVbM22mpetXvXXqzN7YmKStu2putMRt9IV9yY+oaYmFgMdY05fvwUklQJNWr+TuDivDeYjLwc3H8YcxMbIiIiUNdQZ+KksZhazBLb1jd8miOXmppK1WpVCFzkS516dRRdmlJ68vgpLg4eHDt6gvXr1zNy5EhFl/TLEo1LCtahYwdKlS6Bt5+HoktReufOXmD0sAksW7UwT46aJ2/DBo7m2dMXBF07pehSlN61qzcY1Hc4vvM96Tegj6LLUXrjRk3h5o1bXL11XtGlKL379x7Q8+/+OLjYiEbLTJg+SY/z5y5w/e5FRZei9F6+eEWntl0xNTdCW2+aostRep3bdUNDQ50DR3cruhSld/fufXp3HcCCJf5079lV0eUovW5/9iEhIYGT5w4ruhSl9/bNO9q27Iy3nzsDB/dXdDlKr1/Pwbx7F8KFKycVXYrSS01NpWaVBqxYsYIJEyYoupxf1s+0BYlmZUGhPo5WJe5wZE6BAgVQVc14hC8hjdi2fk7BggV+OHqckObjNiXWV+YUENtWpn3s9i/WV+aoqqqKR+Ay6eO2JR51zhxVVVU0NDQUXUau8HHbUlNTU3AluYOqqirq6mJdCXmTuOoSBEEQBEEQBEEQBEEQZCYalwRBEARBEARBEARBEASZicYlQRAEQRAEQRAEQRAEQWaicUkQBEEQBEEQBEEQBEGQmWhcEgRBEARBEARBEARBEGQmGpcEQRAEQRAEQRAEQRAEmYnGJUEQBEEQBEEQBEEQBEFmonFJEARBEARBEARBEARBkJloXBIEQRAEQRAEQRAEQRBkpqroAgTZbd38D7NnWf5wutUbltG+Q9uvXk9JSWHblh3s3rWXe3fuExkZhYaGOhUqVqBtuz8YP2kMVapWzo7S5S4+Pp4L5y5y6+Ztbt28w62bt3kd/AYAfSNdDI31vjtvVGQUF85f5NaN29y6lTZvyPtQAObMdWXIsIGZruPZ0+esW7ORUydO8/r1W1JTUilZ6jfq1K1N+45tGTt+VNa+qBI5dfIMm9Zv5drV64SGfkAFFUqXKUXTZk0YOXoordu0UnSJOS46OoZ1qzdw+OBRnj19TkxMDCVKlKBqtSq0+qMlk6aMo0jRIl/NF3ThEmtWruPyxauEhYVRuHBh6tSrzdDhg+k3oLcCvonssrIvXjgXxKmTZ7l54xYvnr8kPDyCuNg4ihYtQs1aNejW429GjBqKZgHNDGt4/uwFixcs49TJM7x/H0IhLS3qN6zHiFHD6Nm7m1y/b3YKDw/n8MFjnD19ntu37hD86jWpqSmUKFGCho0bMGhIf7r37PrNeW/dvM2RQ8e5dfM2T588I+xDGDExsRQqpMXvNarTuUtHRo8dQbHixXL2S+UAeR6bFsxfgqf73PR/P3l1NztKlrus7IffY2Vuz4a1mwCoULE8p84f+eZ0vt7z8fcJ+OHyjp7aT9VqVX66DkWQx/60d/cBtm/dwa2btwkPi0BVVZWy5crQqnULxk4YRb36dXPuC+WArPyuHT54lI3rt3Dj+i0iIyIpVrwojZs0YtSY4XTu0jGHvoF8yGtfDHkfwppV6zl+9CQvXwSTkJDAbyVLUKPG77Ru04op0yegpqb27XlDQlm8YBlHDx/ndfAbNDU1qVm7BoOH9GfYyCGoqKjI7ftmp6xc9zx7+pzDB49y/lwQ9+7eJzQklPz5VSlTtjQtWzVnzPhRNGxUP7tKzxbKcO2TV863BPkRjUt5QL58+SjxW4nvvq+urv7Va5ERkUwcO41rV2+kv1aokBYJCYk8uP+QB/cfsn7dJub6edCrT49sqVuerl+9yaRx02Wa9+CBI5n6sfqR5UtXMcdtLkmJSQAUKFCAfPlUePniFS9fvOL8uaA80bgklUqxtnBIv8gA0NRMu9j/+F137djNpKnjsbYzV1SZOe7cmQsY6JkQGpL246yuroZmgQK8ffuOt2/fcf5cEN16/EW9LxqXPFy9WRS4NP3fRYoWISoqmjOnznHm1Dn27t7P/IU+qKrmjsN1VvbFxQuXc+zIifR/FyxYEHV1dT58COPDuSDOnwtixbLVrFi7mOrVq31zGceOnEBvhhHx8fEAFCpciIiISE6dOMOpE2cYMnwQHl7OueJkunXTjqSkpKT/W0NDA1VVtfRt6tCBI3T6swOBi/0oUKDAZ/Nu2bidNavWfzavpqYGERGRXL50lcuXrrJi6WoWrwigWfOmOfadspO8j01PHj/NVCOJMsrKfvgt585cYOO6zT81j5qaGkWLFf3u+7nlmAZZ258SE5PQm2HIkUPH0l/T0ipIcnIyT5884+mTZ2zZtB0LG1MmT52QU18pW8n6u5aamoqJoQU7//kXABUVFYoUKULYh3AOHzzK4YNHGT9xDHZOVjn6fbJCHvvi7l17sTSzIyY6Bkjb/tTU1Xgd/IbXwW84eeI0o8cOR63o141LN2/cZsLoKYSHRwBp215sbCyXgi5zKegy+/YcZPGKgG9eKyirn73uuXTxCsMGjv7stUKFtEhKSuLZ0+c8e/qcbVt2oDtzOkam+tlSc3ZQ9LVPXjrfEuQn9/yyC99VrnzZ795B/B4ne7f0hiWDWXqMmziK4sWLk5qayqWgy9hZO/Hg/iNMDC1o1rwpZcuVyY7S5apo0aLUb1iXBg3qUb9hPZwd3NNb4X+kVOmS1KtflwYN69GgYX20p/7cj8vSxStxdfRAVVUVbb1pjBg1lEqVKwJpDXnXr93k9KmzP/2dlNHWzf+kX7z17N0dEzNDqlWvCqRdjHm4enPowBGWL1lFy1bNv9uzIi+5dPEKk8fPICEhge49u6KtN42GjeqjoqJCfHw8D+4/4vDBIxQuXPiz+dav3ZR+At6nfy8srEwpV74siYlJ7N61FzsrJw7uP4y7i1euaqiTdV9s16ENHTu1p0WrZlSpWoVChbSAtB48u/7Zg4erNy9fvEJ7ykz2Hd5FvnyfP9n98sUrZmrPIj4+nuYtm+Hh7Uz16tWIjY1l8YLlzPMNZOum7fz+ezWm60zJlu8uTykpKTRu0ojBwwbQsVN7KlepBMCrl8HM91vA5o3bOHHsFFZmdsz1n/PZvI2bNqRiJVNatGzG7zWqp/eYi42N5cC+Q7g5efLhQxjTJ8/kyMl9FClS+KvPz23keWySSCSYGVuRmJhIs+ZNuHL5Wg58A/nKym/ip+Lj47GcbYuqqip16tXm5vVbmZqvWfMmbNi6+qc/TxllZX8KnLcovWFpzPiR6OhNp2y5MkgkEm7fuouTvRuXgi7j6jiHVq1b5rreE1/Kyu+a9xy/9IalCZPHMtNQm+LFixMXF8f6NZuY4zaXVSvWUqVqZSZMHpvj301WWdkX9+7ej6GeKRKJhJGjhzFh8lhq1qoBQExMLHdu3+Xg/sOoqn19SRcVFc2UCTMID4/g9xrV8fbzoFHjBiQlJbFx/RZcHDw4eeI0TvZuOLnayfU7Z6efve5JSU4hf/78/PV3Z/oN7Eubdq3Sr3lu3byDi6MHl4IuM89vAeUrlmf4yCHZWL18KeraJ6+dbwnyIxqXfkGJiUns/ncfAIOHDsBglm76e/nz56d1m1YsWhbAn+27k5CQwNEjxxk1Zriiys2Ulq2bc/X2+c9em+M29ztTf27g4H4/9ejbl+7dfYDnf5/lF+D9VTfQosWK0rFzezp2bi/zZyiTf7buBKBK1cr4BXh9duex+u/VmL/Qh66de/Pi+Uv27N6f5xuX4uPjMTE0JyEh4Zt3VAsUKEDjJg1p3KThZ6+npKTg6z0fgAYN6+E7zzO9sURDQ53BQweQkJCAjYUDq1esY9yE0emNC8osK/vipCnjv/l68eLFGT9pDOrq6liZ2/HwwWOuXL5Gi5bNPpvOx8ufuLg4SpUuybKVC9IvALW0tDAymUloSCgb1m0mYN4iRowammGvCmWwbtNK2rRr/dXrFStVwN3LmfyqqmxYu4kd2//FxNyI8uXLpU8zaMiAby5TS0uLQUMGUKpUKcaPnsKH0A8cPXycAYP6ZtfXyDHyPDatWr6Wy5eu0n9gX6pUrZzrGpeysh9+ycvDl+fPX6CrP523b95lunEpL8nK/vTPtrTtsvUfLXF0sU1/PV++fDRsVJ+lKxfQrmVnYmPj2LfnQK5uXMrK71pYWDjLl64CoFv3v7B1+H+vioIFCzJl+kQ+fAhjUeBSfOfOZ/CwgRQuXCiHv+HPy8q++P7de6zM7JFIJFjamjFl2oTP3i9USItWrVvQqnWLb86/dNFyQt6HoqmpyfLVi9JveqqrqzNuwmhiYmLxcvdh47otTJwy7rs9gnO7KlUrc/DY7vSbDR/lz5+fxk0asnbjcgb0Hsa9u/dZOH9JrmlcUuS1T1473xLkRwR6/4KiIiPTH91q2KjBN6epUrUyxf47EMTFxuVYbbLKnz+/QuYFCJy/iOTkZLp1/+uXeL74/fsQAOrWq/PNxxrU1NSoW68OkDu2naz6Z9suXjx/SanSJTG3Msn0fLdu3E5/hG7ytIlf9cIBGDFqKEWKFiElJYUd23fJrebslNX9KSNNmjVO//vtm7efvRcXF8f+vYcAGD12xDezrbT1pgEQEx3DwQM/19tTEb7VsPSpYSMGp//9sxf8Ga3L3Epex6aXL17hPceP4sWLYW2fe3oMfkpe++HVy9dYtXwt1apXRU9fWy7LzIsy2p8+bpcNG3/7fKtIkcLpF725/TczK79rZ0+fSz83nao9+ZvLn/7f61GRURw6cFje5WeLrOyLK5evJTIykvoN6jJ56rdvvmRk+38N7n3690pvWPrU+Imj0dIqSGpqKju375a5TmVXrnzZrxqWPqWurp7eIPz8+QsiIyJzqLKsUdS1T1483xLkRzQu/YJKlipJwYIFAbh549sXJM+fvSDiv4Nrbr6Llt3i4uI48N8BdsDgfgquJmd8PEG5e+feZ3kwHyUnJ3P3zj3g+42XecnH3hK9evdAQ1Mj0/MFB79O/7tmrd+/OU3+/PmpVq0qAKdO5o3HKrPiYtCl9L8rV/l8sIFLQVdISEgAoNOf3w58rVipAjVqpq3rUyfPZFOVOUdD4//bW2qq5KfmzWhd5lbyOjZZzLYhLi4OKzszfssg1yOvS0xMwszEGqlUiquHw08d3341Ge1PlSun9cy5deP2N+eNiorm6ZNnwPcboHKLrPyuBb/6ZN6a3563WPFi/Fbyt7R5T+T938SP5xf9B/X76dyaJ4+fpoc7d/6zwzen0dLSokWr5gCczgO/iVnx2e+p5Od+T381v+L5lpB5onEpDwj7EE6/noNpUKs5dX9vQqe2XTGaOZvzZ4O+Ob2KigojxwwDYNuWHfjNDSA8PBxIC1O8cC6I6ZPTHpXr1afHLznqV2Zdv3qT5ORkIK0R7mLQZaZN0qVFo7bU+b0xHdv8jeksS+7fe6DgSuVnzLiRQFoDpIGuCc+ePk9/78njp8ycYcSL5y+pUqUyk2S405abJCYmpTfQNmhUn+Dg11jOtqVdyz+pXa0RLZu0Z8oEbY4eOZ7hcjJqGEiVpALw4P5DudWdmyTEJ/D0yTMC5i3C1SktV6hV6xY0+uIi7NP1U7t2ze8ur9Z/7z28/ygbqs1ZF879/xhfp26tH06fmJjEq5fBrF6xDmP9tB45VapW5q+uf2ZbjTlJHsemjes2c/b0edp1aPPdR6F+FfN8A3n08DHDRgyW6Tzg4YNH9PirL/VqNKVBreb81bEnFqY23L51JxuqzXmZ3Z9Gjx0BwPlzQdhaOfL2zTsgLYD+1s3bTJmgTWxsHM2aN8kTj6d+lJXftY/vf8v/2LvrqKi2PozjX0BJBfXace3u7n7t7u4GJUQEpLtTwu7Oa8e1Wwzs7lZUpHvm/QOcCwbiEDOD57OWawFzzsxvxhN79tnn2aKU1MfyU7vqR16+eMX79x8AqF+/DvfuPsBAbx4tm7SnVpUGtGnWiTmzjLh86eoP179/77/PtkYm58Sv58uHDx/nYPW563e/92TFhbTzaclSJSiaD2dRzUl/YntLkHVC5lI+EBcXx62bd9DR0SE5OUkyK86unXsYOmIwzm52390iMG++IeGfw9mxbRd+3gH4eQdQqHAh4uPiSU5O5u+KFTBdYMzUGZNk9K4Uw9OnzyQ/79tzEDdnL8RiMVpamhQsUIBXL1/z6uVOdu/ci6OrLcNGDJZdsTmka7fOWNqa4e7sxYF9hziw75BkRqb4+Hi0dbQZM34kxiYGCpGHkB2vX70mMTG1c/HF85fYWTkSHR2DqmpBNDQ1JPkbx46cYMSooTi720uuPpYvX07yPA/uP/zhCMGvM5kAREVGERsbKxl1mJ+FfQijZZMfXw3r2q0zHt7O3/39ayNcR0cHdQ31nz53qdIlgdQsC0UWGRFJcOASIDV3oUrVn2dl1KraUHK7SXpNmzfBN8ADNTXFmSUoM9k9Nr17+x4XJ0/U1dVxcrXL6/Llyu1bd1gSvJziJYpjbmki1XN8/hzOly8RaGsXJjo6RjIz2pZN29GdMx3j+YY5W3Qe+d39adzE0bx9+45li1eybvVG1q3eKJktLjExiRIlizNTbxr6hrq5eltxXsjOea18hXTr3nv4ww7NsA9hklnPFP0Y/itfR7MBXL4cykKfQBITk1BXV0dVTY13796zb89B9u89hKHxbOYY6mZYP/3nU6r0zyfl+fpYdFQ0MTExaGlp5ewbyQXSfO/JzNUrofybduvWiJFDhdnNfuFPa28Jfo8wckmBlSpVEn0jPfYd/oe7j68TevsCtx+GsvWfDbRt3xqAbZt34Gjr+t26aupquHg4YG5pQsGCqVOXRkdFS24liIuL48uXCBITv29ACf4T8SVS8rO7ize169Ri557N3Lx/hZv3r7Bj9yZq1a5JUlISFqY2XE+boU/RTZ46gaCl/pLh6fHx8ZIhskmJScTGxBKVNmVufpb+vvxA/0UUKFCAgEW+3Lx/hWu3L3L64lF69+0JwOaN21i+dLVk+br161C8RHEAFgct++FtPGtWrpdMPQxk+Dk/U1ZRoXiJ4hQvUTzDUPXefXtiZjGPIj+4qhgTHQOARiYNndTHNVKXj4nJuYLzmEgkYq6BKR/eh6Gmpoatg1Wmy5dI+yzTd0y2btMSK1tzypUrm9vl5qnsHJsszGyIiozCYK6eQoTn55bk5GRMjS1JTk7Gxn7BD/M0MlOpckXMLOZx5NR+7j6+xtVbF7j14Aqr1y+jXoO6iMViAv0Xs2zxylx6B7nrd/cnZWVl5pvPxc3LCS2t1HViYmIlFyYSEhKJiooiNm06b0WWnfNa67atUE3rmAtcuPiHzx/o/9/fo6Pz9/kwIuK/9oWPhz8lS5Vkzcbl3HpwhRt3L3Ho2B5atW6BWCzGx3MhB/cfzrB+dLpzXGbnxfSPfT2PyqvsfO/5mU+fPmOgNw+RSESlyhWZrvvjvC/Bf/6k9pbg9wmdSwqsfce2GBrPpnadmpIrZSoqKjRt1pjV65fRrUdXANat2ZjhCgikDrft32soLo4e9OjdjV37t3Hz/mXOhBzDw8cFJSUlFgctY8SQccJBIRMi8X/DvtXU1Fi+ehENGzeQ/K1Rk4YsWx2Muro6ycnJP20wKZK4uDjmzDJi6oRZlC1XhtUblnH5xjku3zjH6g3LqFajKju372ZQ3+HcvXNf1uXmKpFY/N/PIhGuno707ttD0mFbrlxZ/IO8JCHCwQsXSxrbBQoUYI5hakDuo4ePmTphFrdu3iYxMZGwD2EsCV6Oh6uP5LkAlH4Qjpof/fVXMUJCTxMSepo7j0I5G3IcPf0ZHP33OL27DWTjui2yLlGm7K2dOXbkBAB2TlbUrlMz0+VPXzhKSOhpbj24Qsi1Myywms+d2/cY1Hc4Ph7+eVBx3sjOsemf7bs5fvQkderWZso3MzL9aRYFLuXO7bt0+V8n+vTr9dvrDxzcj+mzplClSmXJ8UtVVZX2Hduydcd6GjRMnTnTzzuAyMioHK09L/zu/vT5czhjR0zCxMicxk0bsWXneq7dCeHi1VMEL/WnWLGirF+zicH9RkhumVNU2TmvFStWlImTxgJw5tQ5jObM5/GjJyQlJfH69RvcnL1Yu3qDZF0lpfx9PhSJ/mtfiMVigpb40a59G0lIevUa1Vi6KogSJVM78/x9gmRSZ17KzveeH4mJiWH6JF1ev3pDoUJaBC72VYiRWwKBPMvfR+Y/mLKysmQou0gk4mjaFxFIzVWaPlmP+/ceMHjoAPwDvajfoC5aWlqULVuGIcMGsnbjClTVVLl14zaLg5bJ6F3Iv0LpTkL9B/aRDAFNr2zZMvQf2AeAc2cukJLy8ywBReDi6MG+PQepUrUyW7avo32HthQrVpRixYrSvkNbNm9bS+Uqlfj8ORwbSwdZl5ur0jdCKlWuSPee//tuGWVlZaal3V4aHv4lQ6jruAmjmTZjMgCnTp6hf6+h1KrSkJZNOuDq5Em58mWZPmuyZHmd3xxBkB8oKSlRpmxpjOcb4rPQnaSkJKwW2EmCmb/SKpT6fxEXF5/p88WljQ5Q1Aaks4M7a1atB8DS1izDjHFZUbz4X0ydMYlV65agpKTEQr9gjh45nhul5jlpj01hYR9xsHVBRUUFZ3f737qdIr95+OARAX7BaGlpYu9snePPr6auxjwzQyB19M65M+dz/DXyUlb2p3mGZlw4H0LLVs1ZvX4ZzZo3QVu7MCVKlqBHr25s2bmeYsWK8uL5S9xdvGT0TnJOds5r88yM6DugNwC7du6hW6c+1KzcgPYtu7I4aBmNGjdg2MjUeAGdIvn7fFio0H/nqDbtWlGv/ve3GGppaTFuwmgA7t29T1jaTH2QsX2a2Xkx/WNahRTzvAiZf+/5kdjYWKaMn0no1etoaWmyfM1iyYVAQeb+lPaWQDpC51I+VqlyRYoVKwrAy+cvJX8/ffKsJAhx6ozJP1y3eo1qdO7SEUAy3aTge+k7k6r+ZHYTgGo1qgGpJ7OveQGKKDo6hk3rtwKpDcgfzR6krqHO+IljALgccoWPHz/laY15qXT6//9qVX66XLV0s+akn00HwNzKhC071zNk+CBq1KxGmbJlaNioAcbzDdh7aAfKyqkZHOXKl0VVNX9k40irZ+/ulC1XBpFIxJaN2zM8VqpU6v9FREQE8Zk0eN6/S733v2Sp7zuC5Z2ro4fkVqIFVvOZPFX6wPyGjRvQrHkTAMk+rciyc2xyd/EmPPwLI8cMo2q1ysTExGT493XSBkDyt/x6y7iNhQOJiUnozpmJjo72d59FcnLqxRGxWPzDzycrmjRtJPn55YtXOVm+zPxsf3r08DEnjp0CYOqMST/Mcile/C8GDR0AwKEDRxCnGxGrqKQ9rxUoUAD/QC+Wr15E3/69qFqtCuXKl6V5y6bY2FuwaftayfH964xz+VX69mW1apm0L9O1Pd+km3Ev/Tnu/bufj4j7+lihwoUUvhPgZ997vvW1Yynk4mU0NTVZvnoRzdNmzRP82p/Q3hJI78+9PPcHe5RuRoiKlX6eK1GpckUg/zT+ckOt2pnfjiKRrrGoyEGBT588k9zWlVkmyddtB+DVi1cUT8s/yW+KFC1C6dKleJdJww0y/Pf/8P+/WfMmki8m3/o6G12Tpo2lLzQfKV26FG9ev+XZs+cZ/p5+Npz79x/SsFH9H67/dZaT6jWr5V6RucDFwYOli1cAYGYxL0cmW/ga5Pr82YtsP5esZefY9CrtHLd+zSbWr9mU6evUr9kMgIlTxmFttyC7Zcudly9TPwsPV288XL1/utyb128ln4WlrVm2Ojrzix/tTw8f/Nfeysp2GRcXx8ePnyiRllukyLJzXuvctSOdu3bMfN1m+fucWL16NVRUVH452j1DX2S69kXNWv+dEx/cf5ihEyq9+1/PiZlcIM1PvnYsXbxwCQ0NDZavDqZFq+ayLkuh5Pf2liB7hJFL+djzZy/4/DkcgAp/l5f8XUn5v5PP61dvvlvvq69XdQsp8DDZ3FapckVJg/FxJtO4PnyQOg1nocKFFHqKU+X0287rX287oNjDrLOiXce2QMZO2289evDfNKzlK5T/6XLfCgv7KLltZHDale0/mVgslnz5/fa41KxFE8nMYKdOnP7h+q9fvZb8P7Xv0DYXK81Zzg7uGTqWps/KmcDRly9Sr+wq+tVqEI5NiiT06nXJz79zPJR3P9qflLPa3gpLt11q5e8ZQbNzXrt9646kwy6/nxPV1NVo0TK1A/fRo0zaFw9T2xdKSkoZZtyrXKUSZcuVAeDk8R+fE2NjY7kccgWAdgp0TvyZn33v+So2NpbJ42Zw8cIlNDU1WbFm0Q9nJRRkLj+3twTZJ3QuKahfDZsWi8W4OHoAqfchd/lfJ8lj9erVkfz8s6u0YR/COHzwCACN0w1hF3xvyLCBAOz+Z59kCGh6b968Zc+u/QB06tJBEsaoiKpWrSI5oWzZuO2HM8GkpKSwaX1q4LKOjk6mU6TnB0OHDwJSGzVf95n0RCIRS9NuZSpduhT16tf5bpkfSUlJwcrMlsTEJBo2akCHTu1yrmg59KNt6VtbN+8g7ENqpsS3DUJNTU169u4GwPq1m34YFLwoLT+uUCEtuqcFf8o7Zwf3DLfCZaVjKSUl5ZfniLNnznP92k0AWrZW/Ku22Tk2bdy2hiev7v70n76RnuQ5vv4tP45agtSw6sw+i6/nu3Lly0r+ln7U0q+2u4SERLzcfIHUfbZtu1a59VZyTHb2p/TH+/Vrf9zeio2NZef2XUDqaOj0s9DlN9k5r8XFxWFlbgdArz49Mr0VPb/42r44d+YCt27e/u7xmJgY1q3ZCECjxg34669ikseUlJQkHXB7dx/g1cvX362/dtUGYmJiUVFRYcDgvrnxFnJMdr73wH8dS19vhRM6lqSXX9tbgpyhuN9y/3CvX71hYJ/hbFi3mRfPX0oOuiKRiNAr15g0drrki+6oscMzfMFv3rKZJLRuzar1ONq5SjpFEuITOHn8NCOGjCMqMgolJSWmTFOM4e4RXyL4/Dlc8u/rTBvxcXEZ/v6j2e/SP/71qgdAbExshr/H/WCq4CnTJ1KufFni4uKYMmEm10NvSB67HnqDqRNmER8fj7q6OvqGurnwzvOOuoY6I0YNBeDWzTtMm6jLvbsPEIlEiEQi7t65z+TxM7hyORSASVPHoaKiIsuSc12Lls3o1acHAOYmVhzYd1jyxfb16zcY6Blz727qzFTGpoYZOhdfPH+Jp5svt27eJiE+AUjdhy9fusr40VM5fOgo2jraePg4K9TtlNLsi5dDrjJiyFh2btvF2zfvMjzf0yfPcHP2wtLMFoCKFf9m6LBB372u0Tx9NDU1+fA+jGmTZklmi4mNjcXfJ5ANazcDoKc/E50iOrnwznNW+owlCxvTLN8K9/bNO/r2GPzd+QFSO7uDA5YyY/JsxGIxRYroKMwxPjPCsel72TknSivkwiXGjpz03X6clJTE2TPnGTF4LNfSzpFzDGehrQCTFGRnfypXvhxdu3UG4Oi/x5mrP5/nz14gFotJSkriyuVQRg2bwIu0fJipMybm6XvLDdk5r127ep3AhYt5+OCRJNcsMTGRk8dPM3zQGK6F3qBM2TLYOVnl+fvKDmn3xQGD+9GwUQPEYjG60w04e+Y8IlHqLMWPHj5m+iQ9wj58RFlZGWNTw+9ed+qMyZQoWTytfTqDm2kTiiQmJrJuzUZ8PFNnNxw5ZhhVqsj3hcDsfO+Ji4tj6oRZhFy8jJaWJivWLs43t8LJ6rtPfmtvCXKOkLmkwG5cv8mN66lXylTVVCmkpUV0TAyJCf8FjQ4dMRgbe4sM6ykrKxO0xI8JY6by4vlLVixdzYqlq9HS0iQuLl5y4lJRUcHC2lRhevb79hz8w2HnSxatYMmiFZLfhwwbiIePS4ZlmjVo88PntLVyxNbKUfK7vpEehsazMyyjqanJqnVLGTdyMndu32VQvxGSYe0xMbFA6jB330DPn97zrkhMFxjz7OlzTp44LfmnmjYlbPptr9+APujpz5RVmXnKw8eZTx8/EXLxMnozDFBVU0VDXYOIiAjJMvpGepKr/l9FR0cTtHAxQQsXA6mjKWJjYyUBuWXLlWHRsoUKt91Iuy9euniFSxdTh+irqamhpaVJbGwc8fH/BUbWrlOLxcsDUNdQ/+75K/xdnoXB3syeacSli1fo2qEXhbULExsTK8mtGDpicI7dVpabXr9+I/mslJWVWRy0nMVBy3+6/LQZk5g2878JGu7euSfpjFNVLUihQoWIj08gNjZWskyFv8sTtMSPEiVL5M6byGPCsSmj7JwTpSUWp46yOHfmAgDq6upoamoQFRUtOa4pKyszU28aM3Sn5shr5oXs7E9uXk5MHDuNWzdu88+OPfyzYw8aGhokJSVlGGE3feZkBg8dmBdvJ1dl57z24UMYXm6+eLn5oqSkhI6ONlFR0ZLjd42a1Vm2Kljhchyl3ReVlZVZsiKAsSMn8fDBY8aNnIyGhgYFChYgKm20SMGCBbFztKRN2+9HAWprF2bZqkVMHDOVhw8eM6D3UAoV0iIhIVHy/9G+Y1ssbcxz+i3nCmm/9xzYd4gL50MASE5OYfZMo0xfJ3ipP00VJNNLVt998lN7S5CzhM4lBVW8+F/YOlhy9co17t65y+dP4URERKKmpkqFCuVp0rQRw0YO+WmYYsVKf7P/33/YtGErRw4d48H9h0RGRqGmpkbZcmVo0ao5Y8ePonadLAZW/+GqVqvCwWN7WL5kFf8eOsrLFy9JSRFRpWplOnRsx5TpEyhXvtyvn0gBqGuos2LtYg7sO8yunXu4deM2nz59AiWltBlh6jN0xCC6dO0k61LzjKamJhu2rmbrpu3s3L6bB/cfEhMTS+nSpWjWsikTJo39YUOlfPlyzDHU5eL5EJ4/e0F4eDiFCmlRpVoVevTqxphxI9DQ0JDBO8p79RrUxdvPjQvnQ7h54zZhYR/5Ev4FVVVVKlb8m7r169Czdzd69emR6YiTzl07sv/ff1gctIwzp8/x4UMYOjra1KlXm1FjRtCrT/c8fFfSE4v+Gx0hEon4mG6K6R/52pENULJUCQIW+XLxfAjXrt3gw7sPhIeHo6ysQtlyZahdpxb/696FAQP7/rCTTlEJxybZq1m7Ogus5nP1yjXu33tA+OdwIiOjUNdQp1r1qjRv0ZSRY4ZTq3YNWZeaZdndn4oVK8qO3ZvYvvUfDuw9xJ0794j4EoGKSur6TZo2YtTYEflmtqrsnNfqNajL9JmTCbl4mVev3hDxJYIiRYtQq3YN+vTtydARgylQ4M/66lKiZAl2H9jB2lXr2bv7AE+fPiMhPp7yFcrRuk1LJk+bQM1aP9+f6jeoy8Fje1gctIxjR07w9s07NDQ1aFizAUOGDmDYyCEKEdeQne89onTn04SEBBLCEjJ9raTE35sB80+VX9pbgpylJM7CnKeRkZHo6OgQERGBtrb8D2GWtfYd2lOiZDG8/NxkXYrcC7l4mZFDxrFy7RI6dm4v63Lk3oTRU3n44BHnLp+QdSly7+aN2wzoPRT/IC/69u8t63Lk3sypc7h86SqXr5+VdSly7+GDR/To0g9HV1tGjx0h63LknuFsE06dOM3VWxdkXYrce/XyNR1a/y9Hg9vzs/917I2Wlia79m+TdSly7969B/T+3wCWrgyS3Kon+Lne3QaSlJTEvyf2yboUuff+3QdaN+sotLeyaHC/EYSFfeT0haOyLkXupaSkUL1iPVauXMnEiRNlXc4f63f6guS/q1ogEAgEAoFAIBAIBAKBQCC3hM4lgUAgEAgEAoFAIBAIBAKB1ITOJYFAIBAIBAKBQCAQCAQCgdSEziWBQCAQCAQCgUAgEAgEAoHUhM4lgUAgEAgEAoFAIBAIBAKB1ITOJYFAIBAIBAKBQCAQCAQCgdSEziWBQCAQCAQCgUAgEAgEAoHUhM4lgUAgEAgEAoFAIBAIBAKB1ITOJYFAIBAIBAKBQCAQCAQCgdSEziWBQCAQCAQCgUAgEAgEAoHUhM4lgUAgEAgEAoFAIBAIBAKB1ITOJYFAIBAIBAKBQCAQCAQCgdSEzqUcJhKJCAsLIy4uXtalKIT4tM8pPl74vH5FLBYTFxdHSkoKYrFY1uXIvbi4OADi4xNkXIn8E4vFxMfFIxKJhG0rC74e3xMShG3rV1K3rThShG0rS74etxITE2VciWJITk4mPj4BkUgk61LkXkLaufDrNibIXHJyMomJiaSkpMi6FLkXl9aGF777ZE1ycgpJiUkkJyfLuhS593WbevPmjYwrEWSV0LmUgy5evEjrNq25f+8+B/cfZuKYaTx+9ETWZcml+Lh4AvyCmTFFD2UVZebqm7Jy2RqSkpJkXZpcunXzNsMGjubypauEhX1k7MhJ3L/3QNZlyaWEhEQWBy1j4phpKCsrY2Vux9JFK4Qvaz9x7+4DRg+fyKmTZ/gS/oURg8dy5/ZdWZcllxITE1m+dBWjh09AWVkZVydPAhculnxpE2T06OFjJoyeyuFDR4mKjGJw/5Fcv3ZT1mXJpeTkZNasWs/QAaNQVlbG3ycIP+9AoSPgJ54+ecaU8TN48fwlDx88YkDvoVy9EirrsuRSSkoKG9dtYcLoKantLQNTPN18iYmJkXVpcunF85fMnDqHRw8f8/LFK/p0H8TF8yGyLksuiUQitm3ZyZB+I1BWUWbBfGtcHDyIjIySdWly6fXrN8yZZcStm7f58CGMnl37c/bMeVmXJZfEYjH/7NhDl/Y9UVJSwsrKCkNDQ8LDw2VdmuAXhM6lHPDmzRvGjx9Pq1atiIqKZMOWVcyYNYULF0Lo0aUfDrYuREZEyrpMuSAWi9m/9yBdOvTEx3MhNWvWYPW6ZZQrXxYHWxd6dOnHyeOnZV2m3AgL+4jpPEsG9B7G3Tv3MDE3Qt9Il6tXrtGn+yBsLByEA20asVjMv4eO8r+OvXB38aZy1Uqs3bicylUq4erkSbdOfTj673Fh9ESaz5/DsTK3o0/3gVwPvYHBXD3mmRpy+9Yd+vUcwgJTaz5+/CTrMuXG8aMn6d65L052bpQrV5Y1G5ZTs2YNvN396NK+Jwf2HRa2rTQRXyKwt3amZ9f+XAq5wqzZ0zG3nM+D+w8Z1Hc4JkbmfHj/QdZlyo0zp8/Rs2t/bC0dKV6iOKs3LKN+g7r4+wTSuV0P9uzaJ2xbaSIjo3Bx8KB7576cPXOBKdMmYuNgwbOnzxk6YDSGs014++adrMuUGxfOhdCn+yAszGwoUrQIK9cuoXHjhiwKXEqnNt3Zse0fYdRXmujoGDxcffhfp94cP3aSsRNG4+xuz5s3bxk1bAJ6Mwx49fK1rMuUG1cuhzKg91Dmz12AppYmK1YvpmXr5ixfuopObbuzeeM2YdRXmri4OHy9AujavheHDx5lxKihePi48DHsE+NGTmb6ZD2eP3sh6zLlxvVrNxncfyRz9edToIAKqzcsY56pIcuWLaN69eoEBwcLo77kmJI4Cy2WyMhIdHR0iIiIQFtbOy/qUgjx8fF4e3vj7OyMmpoaxvMNGD5qCCoqKgBERkQyR3cuZ0+fp1DhQsw3n8uIUUMlj/9p7ty+i62lI5cvXaVEyeJ4+rjSvmNbyeN7d+/HytyOiIhIOnbugJWdGVWqVJZhxbKTmJjI6hXr8PUKICkpke49u+Hp64K6ujqQ2ggymj2PE8dPo6GhwTxTQ0aPG0GBAgVkXLls3L/3AHsbZ86fvUixv4ri5ulE126dJY8fPngE8/nWhH8Op2371ljbLaB6jWoyrFh2kpKSWL9mE17ufsTHx9Plfx3x9ndHS0sLgNjYWOYZmPHv4WOoqaliOE+f8RNHo6qqKuPKZePxoyc42Lhw6uQZihTRwcnNjl59ekgeP3n8NCZzzfkY9okWLZth42BJ7To1ZVix7CQnJ7Npw1Y8XX2IiYmhfYe2+AV6U1i7EJB6zjSdZ8mBvYcoUKAAcwx1mTx1PGrqajKuXDaePX2Ok70bR/89jra2NnZOlgwY1E/y+LmzFzDWN+X9+w80btIQW0cr6jeoK8OKZSclJYVtW3bi5uxFZEQkrdu0ZGGwN0WKFgFSj2sL5luza+deVFSU0Z0zg2kzJqOuoS7bwmXk1cvXODu4cXD/vxQqVAgrWzOGjRwiefxyyFUMZs/j7Zu31GtQF3tHKxo1aSjDimVHJBLxz47duDh4EB7+habNmxC42Jfixf8CUo9rNhYObNuyE4AZulOYqTcNTU1NWZYtM2/fvMPVyZM9u/ahpaXJ/AXGjJswWvL49dCbzNE14tXL19SuUwtbR0uat2gqw4plRywWs3f3fhzt3PgY9pFGjRsStMSPUqVLAqnbnqOtCxvWbUYkEjNl+kT09GdSqJCWjCuXjQ/vP+Dh6sP2rf+goamBsYkBk6dNyPi4my/bt+ykfv16+Pn507lz50yeUZBTfqcvSOhckoJYLGbHjh3Mm2fMq1evmTB5LHMMZqGt8+PP5tbNO8yZZcTzZy+oUbM6tg6WtGrTIo+rlp2PHz/h7eHH5g3bUFNTQ09/Bnr6M3+4rEgkwtXJkzUr15OSksKkqeOZbTALbe3CeVy1bIjFYo4dOYG9jTOvXr6mZq0aBC31o1Klij9c/sGDR+hO0+fJ46dUqVoZGwcL2ndo+8Nl86Pw8HB8PQNYv3YTBVULMmPWFPSN9FBW/n5QpkgkwtvDn+VLVpGUlMT4iWPQN9KVfDn5E5w6cQY7ayeePnlGtepVCVriR7XqVX+47JMnz9Cdps+D+w/5u2IFbOwt6Ny1Yx5XLDuREZH4+QSyesU6ChQswKTJ4zAxn/vDbQvA3yeIRYFLSUhIYNSY4RiZ6PPXX8XyuGrZOXf2AraWjjx6+JhKlSsStNiXWnVq/XDZl89fMmuGAXdv36NM2TJY25nTrUdXlJSU8rhq2YiKiibQfxErlq5GWVmZ0eNGYGlj9tNta3HwMvy9g4iPj2foiMHMMzWkRInieVy17IRcvIytpSP37t6nwt/lCQj2oX7Dej9c9u3bd8yaqs/NG7coVaoklrZm9OrT44/ZtmJiYlgUuJTFwctRQolhIwZj62j50wtPq1esxcPVl9jYWAYO7s9887mULlMqj6uWndAr17CxcuTWjduULVsGv0BPmjZv8sNlwz6EoTvDgNAr1yn2VzEWWM1nwKC+f8y2FRcXx9JFKwgOWIJIJKL/oH64uNv/dNvasG4zLo4exETH0KdfT8wsTShXrmweVy07N2/cxtbSgdCr1ylVqiTe/u60btvyh8t+/vwZvRlGXLp4mSJFdDCzNGHw0AE/PSfkNwnxCaxYtoaFvkEkJyfTu19P3L2cfnpR8/q1mzjYuHD1SiiDBw/Gw8ODKlWq5HHVfxahcykX3bhxAwMDA06cOEHnLh2xsDGlStWsja7ZunkHjrYuREVF06NXNxZYzafC3+VzuWLZSUxMZM2qDfh6+pOQkEi37l3w9HPN0tWeL+FfmKM7l/NnL1JYuzCm5nMZNnJIvh719fDBI+xtnDl7+jxFixXFxd2e7j3/l6V1d/+zF2sLByIjIunyv05Y2phRqfKPO6Tyg+TkZDas3Yynmy9xcXF06twenwDPLF3tiYqMxmC2MadPnkVTU4N5ZkaMGjM8X4/6evLkKU62rhw/dgqdIjo4OFvTt3/vLK17YP9hLExt+BL+hfYd22Jtt4Cq1fLvSTwlJYXNG7fh7uJNdFQ0bdu3ZmGQ908vHqQXGxuL0Zz5HDtyAnV1deaa6DN2wigKFiyYB5XLxovnL3Gyd+PfQ0cprF0YG3sLBg8dkKV1jx05wXzjBXz+FE6rNi2xsV9AzVo1crli2RGJRGzf+g+ujp5ERETQomUzAhb7UKzYrzsh4+PjMTFawKEDhylYUBWDuXpMmDwONbX8O6Lw9es3uDp6sG/PQQoV0mKB9XxGjh6epXVPnzzLPCNzwj6E0bRZY2wdLalbr04uVyw7IpGI3Tv34uzgzufP4TRp2ojAxb6UKFnil+smJiZiPs+SPbsPoFJAhdkGs5g6bWK+HlH47u173Jy92LVzD5pampiYGjFh8tgsrRty4RKGc0x49/Y9DRs3wNbBkoaN6udyxbLzNc7C0c6VD+/DaNCwHkFL/SlTpvQv101OTsbK3I4d23YBMGv2dGboTkFDQyO3y5aZsA9hktE16urqGBjPZvrMyVlaNzT0Ovqz5vL61Rvq1quNraMVTZs1zuWKZedrnIW9jQtv37ylTt1aBC/xp3wWvhuLxWJ2/7MPN2cvwj+HY2xsjLm5OYUKFcqDyv88QudSLggLC8PKyoqlS5dSuXIlLGxM6dSlw28/T3JyMnZWTmzZtB0xYmbMSh1e+/WWlPzi+NGT2Fk78eL5S2rUrE7QEr8sd8Kld/P6LebMMuLFi1fUrFUDO0dLWrRqngsVy86X8C/4+wSxZtV6ChYsyJTpE5lrov/bVyxEIhFO9m6sX7OJlJQUyfDawoXz14H29Kmz2Fk5SUZrBS31p4YUt7jdu3MPvRlGPH36jKrVqmDraEnbdq1zoWLZiYyMIsAvmJXL1qCiosL4SWMws5gn1bbl6eaTFrqfzITJY9E31EWniE4uVS4bF86FYGvlyIP7D6lY6W8WBvtQr/7vfyF99PAxutMNJKN4bOwt6Ni5fS5ULDvR0TEEByxh6aIVKCkrMXL0cGzsF0i1bfn7BLIkeDkJCYmMHT8Kw3mzKVq0aC5VLhuXL13F1tKBO7fvUa58WfyDvWnc+PdvQ3r+7Dmzphlw/94DypUvi429BV3+1ylfjZ6IjY1lcdByFgUuBWDIsIHYO1tLdQEgOGAJC/2CSYhPYPiooRjPN5Dc7pRfXA+9gY2lIzeu36R0mdL4LnSXqp30+tUbZk3X5/bNO5QuXQpLW3N69u6Wr7at+Lh4li9dRYBfMCkpIvoP6IOzh71Ut30vX7IKb09/4mLjGDJsICZmRpQsVTIXqpad27fuYGvpyJXLoZQoWQJPH5cMcRZZ9f7dB3Sn63Mt9AbFSxTH0saUvv1756ttKyEhkVXL1+DvE0RSUhI9enfDw9tZEmfxO9au3oC7szcxMTH0G9AHM4t5lCn76848RXLv7gPsrJ24eD6Ev/4qhru3s1Sj42NjY1kcuIyli1dQtGgxXF1dGTt27B8z6iuvCJ1LOSgpKYmgoCBsbW0RiVLQn6vHuAmjs30lOuxDGHozDbl6+RpFixXFwmo+/Qf1VfidIUM+SdEiqfkkvbtn+3k3b9iKk70b0dEx9O7bA3NLE8qVL5cDFctOcnIyG9dvwdPVh9jYONp3bItfgJckn0Ra4eHhzJ5hxMULl9DR0cbUYh5Dhw9S+G3r2dPnONq5cuzICbR1tLF3sqL/wL7Zft4d23Zhb+1EZGQU3Xp0xcLalL8rVsiBimUnJSWFbZt34OrsRVRkFK3btmRhkHe2bwGMiohijt5czp4+h1ah/JMjlz6fpHDhQljamjNsxOBsP+++PQewNLcj4ktEvsmRE4lE7Ny+GxcHd758iaBZ8yYEpMsnkVZ0dAxGc0w4cewUGhoaGM83YPS4EQo/6uvNm7e4Onqyd/d+tLS00vJJRmX7ef89dBQzE6t8lSMnFovZs2s/TvZp+SRNGhK0+L98EmnFxcUxz9CMw4eOoqaaf3Lk3r/7gIerNzu27UJTUwPj+YZMmjo+28/7fY6cBbV/courohCLxRzYdxgnO1fevXtPvfp1CVrqT7lyZbL1vImJicw3tmD/noP5Kkfu48dPeLr6snXzdtTV1ZhtOItZetOz/bznz15krv78fJUjJxaLOfrvceysnXnz+g210uIsKv4kziKrkpOT03Lk9qCsnH9y5MLDw/HxWMj6tZtQU1Nlhu5UDObOzvbzvn71GlcnT/btOUjzFs3x9/OnVatWOVCxAITOpRxz8OBBjIwMefDgISNGD2NuLmRoXAq5gqHePN6+fUf9hvWwc7BUyFDFb/NJJk8dzzxToxzt0EhOTsZ6gT3bt/4DwEy9aczQnaKQoYpnz5zH1tKRx4+eULlyJQIX+/w0n0RaoaHXMZiVmgtWp24tbB2taPaTLAF59jWfZPmSVaioqDBm/EgsrE1zdNsSiUTYWzuzccMWxCIxU2dMQnfODIUMVfydfBJp3b51l9kzDXn+7AXVa1TD1sHyp1kC8uzbfJLhI4dg42CRo7dIps+RS05JZvLUCQqbI3f1Sii2lo7cunmHsuXK4Bfw83wSaWXIkatSGRtHxcyR+5pPErRwCWKxiAGD++PsZpfj25aP50KWLV5JUlIS4yaMxmCunkLmyN24fgs7K8fUfJLSJfHx98jxbMpvc+Ss7RfQuUtHhRs9kRCfwPJlq1noG0RKcgp9+vXELZN8Emkt9A0iOCA1R27kmGHMNTFQyBy5u3fuYWvpyKWQKxQvURxPX2c6dMzZkaT5JUcuMTGRNSvX4+u1kITERLr3+B9efq5Sjb7JzJLg5fh5BxIfH8+Q4YMwMTXM0i2c8ubB/YfY2zhz7swFihYripunI//r3iVHX+Pt23foTtPnxvVblCxVAksbM3r37alw29bXyWS8PfyJi4ujc9fUyWRyup0dcuES9jYu3Ll9l3HjxuHi4kK5coo9GEEeCJ1L2fTgwQOM5hqxf99+WrZujrXdgly/arNy2Rq83H2JjY1j0JD+zDc3zvbVurzwbT5Ju/Zt8A/yylI+ibTCPoQxa7oB166mhipaWJvSf2AfhTjQps8n0dYujPVv5JNIa/3aTbg6ehITE0Pf/r0xs5xH2bLZu1qXF0QiUersQE6eRERE0rJVcwIW++Tq7TKfPn1Cb4YRl0OuUKSIDuZW8xk0pL9CjPp6/eo1Lo4e7N97iEKFtLCwNmXE6GG5+prbNu/AQQFz5L7mkzg5uBP+OZwmzRoRuChr+STSUuQcue/ySczmMmHSmFx9zfQ5cp27dsTSxozKVSrl6mvmBLFYzL49B3C0cyUs7CMNGtYnaIlflvJJpBUVGY3hbGNOKWCOXNiHMMnsQOoa6hgaz2bajKzlk0grQ45ch7ZY2Zn/dGIDeSIWizl88AgONi68ffuOOnVrE7zUn/IVcu+LU2xsLHP153P03xOoqasx10Q/R0bv54VPnz7j7eHHpvVbUVNTQ3fOdGYbzMrV1zx+9CTz5y7g06fPtGzdAht7C2rVlv8cObFYzLGjJ7C3Tp1MpkbN6gQt9aNy5Uq59prf5sjpG+kyccp4hciR+xL+BV+vANat2UjBggWZNnMyhsazc7WtqMg5cqdPnsXWypGnT1JjKAKX+EkVZ5FVKSkpbN20HS/31I6sBQsWMHfu3Hyd9ZXbhM4lKUVERODg4ICfX2pD0MzSJE/vN09MTMTU2JJ9e1JDFecY6jJl6gS5HV574VwINpYOPHzwKFv5JNl5fSN9E96/+0Cjxg2xdbSkQQ6P0Mgp0dExBC1czLLFK1FSVmLU6OFYS5FPIq3k5GQsTG35Z8culJSUmTV7OtNnTZbbA236fJLy5cvhF+wlVT6JtK5eCcVAdx6vX7+hXv062Dpa0qSpfIYq5mQ+iTREIhE2lo5s2bhNIXLkvs0n8Qv0zNNpkhUpRy4+Lp5lS1YS6L+IFFFaPom7dPkk0hCJRDjbu7Hua47ctAnoGcyS2xy5WzdvY2vpyNUr1yhZqgRevm60bZ93OW737t5Hb4ahpAEvzzly/+WTBJKUlEzP3t1x93bK8RESP5OaI+fLymWrFSJHLkM+SfG/cPdyytPZOx89fIzuDAMePZD/HLnExETWrt6Aj+dCEuIT+F/3LnhlcTKZnOLnHcDioGUkJCQyZtxIjEzmyG2O3KOHj7G3dubM6XMULVoEZ3d7evTqlmev//zZc3SnGXDv3gPKliuLjf0CunbrLJcXjJOTk9mwbjNebqmDATp2aodPgBeFC+ddeyc4cAkBvsHExycwfORQjE3lN0fu6ZNnONq5cvzoSbR1tHFwtqbfgD559vpfc0dXLV9L+fLl8PT0YvDgwXK5bck7oXPpN6WkpLBixQosLCyIjolGd/Z0pkybKLP7Wl+9fM2s6frcuXWXMmVKY2lrRo9e8hOq+PLFK5wd3Dl0IGfzSaS1bPFKfLwWEhcbx9DhgzAxM5Kb4bXf5ZO0aErgYh/++ks2J4K3b9+hN92A69duUqJkcSxtzOjTr5fcbFvf5pOYWc5jzLiRMqtn9cr1eLp6ExMTS/+BfTFdYCw3oYr/5ZO48unjZxo1bkDQEn9KlpLNth8W9pHZMwy5cjmUosWKssDShAGD+8nNqK/37z7g7uLFzu27czSfRFrpc+R69enBAiv5yZH7mk/iaOfC+3cfqF+/LoE5kE8irS/hX9CbacjF85fQ1tHGTM5y5MLCPuLl5ifJJ5ljqMtMvWkyq2fn9t3YWTkSGRnF/7p3wcLalIqV/pZZPemJxWKOHD6GvY1Laj5J7ZoEL/HjbxnVlyFHTksLE/O5jBw9TG5GFH7+HI6Phz8b1m1GTU2NGbpTciSfRFr79x7Ewsw2NUeuU3us7Mylmqwlt5w4dgo7ayfJLdvBS/1lVp+858hFfInAzyeQNSvXU7BgASZPm4jxfAOZHVePHD6G6TxLwj+H06ZdK6ztFlCjZnWZ1PIjZ06fw87SkcePn1K5SiUCl/hRS0azm8bHx2NsYMbhQ0dSc+SM5zB+0hi5yZGLioom0C+Y5UtXo6KiwrgJozG3MpHZtvXk8VOc7d04dvQknTp1wtfXl4YNFS+CRpaEzqXfcOrUKQwM9Ll27TqDhvTHxGwupcuUknVZQOpJcv7cBXz8+ImWrZpjbW9B7To1ZVbPj/JJbB0t5aIRFh8fj6mxBQf2HaZAgQLoG+kyaeoEmQ6vTZ9PUq5cWfwCPWjSTD4yj86eOY+xgRkf3n+gSdNG2DpaUq++7EIV4+LiWBK8guCA1HySgYMH4ORmKxe3dSQmJmJhasOunXtRUVFGT38mU6dPkmmo4o3rt7C1dORaaO7lk0jrcshVDGbP4+2bt3KRI/d9Pkkv3Lwc5aIRlpycjI2FPdu2/APATN2pzNCbKtMcuTu372Jn5cSlkCuUKFEcD18XOnRsJ7N60rsWegN93bm8evma2nVqYetomaejzr6VmJjI6hXr8PMOICExkR49u+Hp65Jno28yIxKJcLB1YeO6zYjkJEfuwf2H2Fk7cf7sRYoVK4prLuSTSOvOrbvMnmXEs6fP5SJH7ms+iZeHH/Fx8bmWTyINkUiEm5MXq1euIzk5mUlTxzPHYFauxiH8ypPHT3GwceHkidMUKaKDo6sdvfv2kFk96T148Ai96QapGZtVKmHrYCnVjGs5JTk5mU0btuLp6kNMTAztOrTFP9A725PJ5ASRSISvVwBLF60gKSkpdfZQ49kyzZF7/uwFjnauHP33ONrahbF1tGLg4H4yqye9p0+foTvNgAf3H1K+QjlsHCxkmiOXkpKSGmfh7EVkRCSt2rQgINhHbnIATx4/jaOdK0+fPGPq1Kk4OjpSooR8DEaQd0LnUhY8f/6c+fPns2XLFho2boC1rTmNmzaSdVk/5O8dyKKgZSQkJDBqzHDmzjegWLG8G14ri3wSab18/pKZ0/W5d+c+ZcuVxdrOnP9175KnB9q3b97h5uzF7n/2oqWlybw8yCeR1qKgZSz0CSI+Pp6hIwYzz9SQEiWK59nrZ8gn+fCRho3qE5jL+STSevPmLbrTDLh54xalSpfE0saMXn165Om29W0+iZHxHKbOmJRnr/87Vi1fg6ebH7GxsQwc3B/TBXmbIyeLfBJpyUOO3KdPn/Fy92Xzhm1p+SQzmG0wM89e/3dsWLcZF0cPYqJj6NO/F2YW8yhXrmyevb4s8kmk9fnzZ/SmG3IpLUfOzNKEwUMH5OkV5O/ySWZNxnBu7uaTSGvblp042DgTFRVN957/w8LaNM9z5E6dOIOdtRNPnzyjWlo+iTzOBBgZEcnsWUacO3OBwtqFmW82l+Gj8jZHLjIiEn/fIFYtX0vBggUYP2kspguM5XLbkoccuXNnL2Br6cijh6m3NwYu8qF23dp5WkNWREVGYzhnHqdOnEkdaWxqyOixI/L0gmN0dIxkMhllZSVGjx2Bpa25XG5bB/f/i4WpNeEyzJG7FHIFW0tH7t65R/kK5VkY5E3DxvXztIasSEpKYt3qjfh5B6CkpIytrS16enpyM6JQXgmdS5mIiYnB3d0dd3d3tHW0mW9uxMDB8h/YGxMTw1z9+Rw7chJ1DXXmztNn7IRRub4zXLt6HRsrR25ev0WZsqXxDcjbfBJpHf33OKbzLPn86TOt2rTExn4BNXN5+GqGfJIUEQMG9cXJzU4uRkhkJj4+nnlG5hw+8C8FC6piaDybCZPH5nrdGfNJSuLl5yq3+SDppYYqmhH24SPNmjfB1tGSOrncOPuaT+LnHUhycjK9+nTHzSvv8kmklZiYiNk8S/buTs2Rm20wi6nTJuZ6jtzdO/ext3bi4oVLFC/+F+7eznTq0iFXXzMnXDwfguGc+bx/955GjRti42BBw0a52ziTh3wSaSQnJ2NpbsfObbtQUlKSzB6a2zly3+aTuHg40L3n/3L1NXPC1SuhGOjN4/WrN9StVxs7J6tcz5H7Lp+kc3t8AzzlYvRNZr7NkZs+cwqzZud+jtyTJ09xsnXl+LFT6Oho4+BiQ9/+vXP1NXPCzRu3U3Pknr+kRs3q2Dla0rJ17o6kTUlJYcvG7bi7eBEVFU3b9q1ZGOQt09FTWSESiXBxcGft6o15miP34vlLnB3cOXzwCIULF8bafgFDhg3M1dfMCffuPUBvukFqjlzVytg4WtKufZtcfU2RSMSObbtwdfTgy5cIWrRsRsBiH4oVk++ZEkUiEV7ufqxYuoqkpGTGTxqDgZFerufIvX79BldHD/btOYhWIS3MLU0YPXZErr5mTvj06TM+nv5sWr+VGjWq4+PjS8+ePWVdltwSOpd+QCwWs3HjRubPn8/Hjx+ZMn1injQWctqjh4/RnW4gueqQW6GK8pZPIg2RSIS/TyCLg5eTmJCYOrx23uwcD1VMzSc5hKOda2o+SYN6BC31U4gZ2dJ7lhaqeP/eA8pXKIe13QK6/K9Tjo+eCAv7iKebL9s270BdXZ05RrrM1J2ao6+RF4IWLibQfxHx8QmMGD2UuSY5H6r4XT5JnZosWuJPhYoVcvR1ctvrV2+YNV2f2zfvULp0KSxtzXNlsgR5yyeR1rLFq/Dx8icuNo4hwwZiYmZEyVI5P+rr+NGT2Fk78eL5S6rXrEbwEtnlk0jr3bv36E4z4Pq1G5QoWRwLa1P69u+d49tWxJcI/LwDWbNqPQULFmTK9AnMNZFdPom01qxaj4dL7ufInTl9DltLR548fkqVqpUJWOwrs3wSaX38+Am96QapOXJFi2BuZZIrFyMjI6MI9FvEimXykU8irS0bt+Fo70Z0VDS9+nTH3HJ+rowUvXg+BBtLRx7cf8jfFSsQsMg3TyeTyQlfwr8we5YRF86FoK2jjekCY4YOH5Tjo76io2MIDljC0sUrUFJSYuSoYdg4WCjctvXPjj3YWjoQGRlF126dsbQxy5UcuSuXQ7G1dOD2rbuUK18WvyAvmjRplOOvk5uiIqPR15vLmVNnJTlyI0YNzfFRX3FxcZLJZMRiMYOHDsDBxUYu4ix+x90793GwcebC+RB69e6Fj7cPNWvKLoJGXgmdS9+4fPkyBgb6nDt3nh69umFuacLfCvbl7Ft7d+/HaoE9EV8i6NSlA5a2ZlSpkv0vBd/mk/Tt3wtXT/nIJ5FWdHQMRrPnceL4aTQ0NJhnasjocTkzvPbO7bvYWjpy+dJVSpQsjqePq0zvpc8Jhw8dxdzEivDP4bRt3xpruwU5MiT/az6Jr1cASUmJdO/VDU8f+cgnkVZsbCzzDMz49/Ax1NRUMZynz/iJo3Nkf7l/7wH2Ns6p+SR/FcXN04mu3TrnQNWyc/L4aUzmmvMx7BMtWjbDxsEyR3Lkvs0n6fK/1HwSRbt4kF58fDym8yw5sPdQjufIPX70BAcbF06dPEORIjo4udnRq4985JNI69zZCxjrm/L+/QcaN2mIraMV9RtkP0cuYz5JLO07tsUvwEsu8kmklZSUxAJTG3bt2IOKijK6c2YwbcbkHMmRe/b0OU72bmn5JNrYOVkyYJB85JNIK32OXL0GdbF3tMqRHLlv80lat2nJwmBvucknkUZqjpwD27bsBGCGbursoTkxEvLVy9e4OLpzYN9hChUuhJWNGcNGDsn288rS9dCbzNE1yvEcOZFIxD87duPi4EF4+BeaNm9C4GJfuZ1VLCtEIhGOti5sSMuRmzJ9Inr6M3NkJOTbN+9wdfJkz659aGlpMX+BMeMmjMqBqmXn7u276M1MzZGrVr0qdo5WOZIjJxaL2bt7P452bnwM+0ijxg0JWuKXp7EHOU0sFnPowL+4OHjw9u079PX1sbKyokiRIrIuTW4InUtp3r59y4IFC1i1ahW1atfE0taMNm1bybqsHCMSiXB18mTNyvWkpKQwaep4ZhvMQlu78G8/19cdy9HWlbdv31G3Xh2ClvjJZT6JtB48eITuNH3JlVQbBwvad5CuI+jjx094e/hJ8klmG8xEd86MHK5YdkQiEd4e/ixfsoqkpCTGTxyDvpGuVI1esVjMsSMnsLdJzSepWasGQUv9qFSpYs4XLiNPHj9Fd7qB5Eqqjb2F1NNEh4eH4+sZwPq1myhYsCDTZ03GQE7zSaTl7xPEosClkhw5IxN9/vpLuiHnGfJJqlclaIlfnmcN5KaXz18ya4YBd2/fo2y5MljZmtOtR1epRuZERkTi5xPI6hXrKFiwABOnjMfEzChfbVs5mSOXMZ+kEkGLfahVp1YOVyw7b9++Y9ZU/dQcuVIlsbSVPkcuKiqaQP9FrFi6OjWfZNxILG3M8tW2tXrFWjxcfSU5cvPNpZ8AJuTiZWwtHbl39z7lK5QnINibBrl8C2xeCvsQhu4MA0KvpObILbCaz4BBfaXatmJjY1kUuJRFQctQQolhIwZj62ipcCMkMpOTOXKhV65hY+XIrRu3KVuuDH4BnjRtLh+TyeSEz58/ozfDiEsXL2c7Ry4uLo6li1InkxGJRAwY1A9nd/t8tW2l5si5EBUVRfee/2OB1XypB1jcvHEbW0sHQq9ep1Spknj7u8t04oOc9nWARZD/YrS0tHB0dGTKlClyMXGVrP3xnUsJCQn4+vri6OhIQdWCGM2bw8jRw/LVwSK9L+FfmKM7l/PnLlK4cGFMzecybGTWQxW/zSfx8HHJlVvt5EX6UMUu/+uEpY0ZlSpnraMjMTGRNas24OvpT0JCIt26d8FTAfJJpBUVGY3BbGNOnzyLpqYG88yMGDVmeJb3pYcPHmFv48zZ0+cpWqwoLu72CpFPIq0D+w9jYWrDl/AvtO/YFmu7BVStViVL6yYnJ7Nh7WY83XyJi1OcfBJpxcbGYjRnPseOnEBdXZ25Jr+XI5chn6SIDg7O1gqRTyKtY0dOMN/YQqocuZSUFDZv3Ia7izfRCpRPIq3/cuSOULBgQQzm6jFh8rgsj/p68fwlTvZu/HvoKIW1C2Njb8HgoQNyuWrZSc2RMyfsQxhNmzXG1tGSuvWydpuRSCRi+9Z/cHX0JCJCcfJJpJWYmIj5PEv2SJkjlz6fpFAhLcytTBg1Rv7zSaQVcuEShnNMePf2PQ0bN8DWwTLLOXJisZhdO/fi7ODO50+fady0IUGL/eRyMpmckJycjJW5HTukzJF79/Y9bs5e7Nq5B00tTUxMjZgweWwuVy07V69ew0DXWJIjZ+toRdNmWcuRE4vF7N97EEc7Vz68D6NBw3oELfWXy8lkcoJIJMLWyonNG7ciFv9+jlzYhzA83HzZvmUn6urqGMzVY/qsKblctey8f/cBD1dvdmzbRcOGDfDz86djR+kuGOcXf2znklgsZvfu3RgbG/Ps2TPGTRydJ2Fm8uLm9VupoYovXlGzVg3sHC1p0ar5T5f//Dkcb3c/Nq7fgpqaGjP1pqFvpJuHFcuOSCTCyd6N9Ws2pYYqpg2vzSxUMX0+SY2a1Qla4qdw+STSunfnHnozjHj69BlVq1XBzskq01GA3+eTTGSuiX6+uor9MyKRCE83H1YuW0NSUjITJo/FwEgv0y/y3+aTBC7xo2bN6nlYtez8bo5cZGQUAX7BrFy2BhUVFcZPGoOZxbw/Ztv63Ry5C+dCsLVKzSepWOlvFgb7KFw+ibSeP3vOrLQcuXLly2Jjb5Fpjpwkn2TRCpSUlRg5ejg29gv+iG0LIGjhEgL8g0mIT2D4qKEYz888R+7K5VBsLOy5c/se5cqXxT/Ym8aNs3+7mCL43Ry52NhYST4JwOBhA3Fwts63Fz2/tXzJKrw9s54jdz30BjZWjty4dpPSZUrju9A90/ZsfvL+3Qd0p+tzLTRrOXLxcfEsX7qKAL9gUlJE9B/QB2cPe4WOs/gda1dvwN3Zi5iYWPoN6IOZxbxMc+Ru37qDraUjVy6HUrJkCTx9XWnXIXdDwuXF7+bIJSQksnrFWvy8A0lKSqRH7+54eDsrdJzF77h29Tr2Ni5cC73OsGHD8PDwoGLF/HPXxe/4IzuXbt26haGhIUePHqVDp3ZYWJvK5dSteWHzhq042bsRHR1D7749MLc0oVz5/25v+zoNo7enf1o+SSd8Frrn29E3mQkPD2f2DCMuXriEjo4OphapoYrpD7Tf5ZO429Ord3cZVi07O7btwt7aicjIKLr16IqFtWmG4bXJyclsXL8FLzfffJNPIq3IiEj0dY05e+YcWoUKMT8tVDH9iMJnT5/jaOfKsSMn8k0+ibT27TmApbktEV8i6di5A1Z2GXPkUlJS2LZ5B67OXkRFRtG6bUsWBil2Pom0oqNjMJpjwoljp9DQ0MB4vgGjx43IMOrr1cvXODu4cXD/v6n5JLbmDBsxWIZVy86vcuREIhE7t+/G1TE1n6RZ8yYEKHg+ibRiY2OZZ2jOv4ePoqb64xy5N2/e4uroyd7d+/NNPom0vs+Rs6B2ulsnxWIxe3btx8k+/+STSCshIQFTYwv2p+XIzTHUZfLU8RlGfX14/wF3l9QRAxqaGhibGDB52gQZVi07v8qRS51M5jBOdq68e/eeevXrErTUn3LlFGsymZzwNUdu9849KCv/OEfu48dPeLr6snXzdtTV1ZhtMItZs6fLsGrZuXLpKgZ683iTliNn52BJ46aNJI+LxWKO/nscO2vn1Mlk0uIsKuajOIusEolE7NqxBzcXbyIjIjExMcHU1FShMz2l8Ud1Ln369AkbGxuCg4OpWOlvLGxM6dylY47PFKNoUkMV7dm25R8AyfDayyFXsbVylAS85bd8EmmFhl7HYJYxr169pk7dWtg6WlGjRrV8n08iDZFIhL21Mxs3bEEsEjN1xiR058zgxvWb2Fg48PjREypXrkRgPssnkdbtW3eZPdOQ589eUL1GNewcrahbvw6B/otYvmQVKioqjBk/EgtrU2HbEolwc/Ji9cp1JKckM3nqBGYbzOLe3fuSfJIKf5cnINiH+g3rybpcmcuQI1elMjaOFjRp2ohFgUtZHLwcJZQYPnIIto6Wf3xmgEgkwsdzIcsWryQpKYlxE0ZjMFePp0+eYWPpwK2bdyhbrgz+gZ40aZZ/8kmk9eTJM3Sn6WfIkWvVpgVLF60gaOESxGIRAwb3x9nN7o8ZfZOZhb5BBAdkzJF78/rtf/kkpUvh4+9OqzYtZF2qzL168YpZ0/W5c/seZcqWwdrOnI6d2rNi2RoW+gaRnJxMn349cfNy+mNG32RmSfBy/LwDiY+PZ8jwQZiYGvLx4ydsLR25FHKF4iWK4+njTIdO+TfOIqvevn2H7jR9bly/RclSJbCyNadrty6sXbUeX6+FJCQm0r1HVzx9XbN8u2F+tnrFOjzcfIiN+S9HLjIyEnsbZ86duUDRYkVx83Tkf927yLpUmYuJiWFR4FKWLV5F8eLFcXNzY/To0X9Mf8Mf07m0f/9+xo4dS3JyMnMMZzF+0hjhRPSND+/DJMNr1dXViY2NRaeIDo4uNvTp10vW5cmd9Ws34eroSUxMDBoaGiQmJtC2XRv8g7zybT6JtD59+oTeDCMuh1yRbFva2oWxzuf5JNLatnkHDrYuREVFo6mpSXx8PC1bNSdgsU+mtzX9iSK+RDBnlhHnzl5ETU2NuLg4ChUqhIX1fEaMHibr8uRO+hy5r9tWk2aNCFzkm2/zSaQVFRmN4WxjTp08i6qqKnFxcan5JGZzmTBpjKzLkzsH9h/G0tSG8PAvaGppEhcXR4OG9Qla4pdv80mkFRsby1z9+Rz99wQFCxYkISEBdQ11DObOZvrMybIuT+4cO3oC07kWfPr0OXXbio2jTt3aBC/1z1eTyeSE+Ph4TIwWcOjAYVQKFCAxIRE1NTV058xgtsFMWZcnd9LnyH3dtmrUrE7QUj8qV64k6/LkSmJiIuYmVuzZtR8VFWWSkpIpWLAg02ZOxtA4f00mkxNevniFi6MHB/cfpnXrVuzff+CPmFXuj+lcsrS0JCg4iINHd0s9G8yf4uL5EEYNm0CdurXZfWCbcLDIRHJyMmNHTuZyyGV27d9O3Xq1ZV2SXLt6+SrDBo2latXKHDy2R9i2MpGSksLkcTM4c/os23Zv+mPySaR188ZtBvcbTtly5Th6ar8wQiITIpGImVPncOTwMTZtX0uLls1kXZJcu3f3Pv17D6V48b84cfawcGEqEyKRiCEDRnE99Aar1i2lQ6d2si5Jrj1+9IQeXftRu3Yttv6z/o/JJ5GGWCxmzPCJXDgfQtBSP3r2+jMjB7Lq+bPn/K9jH6pWq8KOPZv+yDiL3zF5/AxOHDuFp6+rcNHzF16/fkvndt0pX74cu/Zvp3DhP+u2r9+1eeM2zE2sePz4MVWqZG3iHkX2O31BCv8tUEtTU+hYyoKWrVOHYteqVUP48v8LBQoUoH3HtqioFBA6lrKgSbMmFCxYkKrVqwrb1i+oqKjQoXM7lJVVhI6lLKjfoC6aWlpUqVJR6Fj6BWVlZTp16YCSEkLHUhbUql2TIkWKUOHvCkLH0i8oKytTu3ZNAOG2riyoWq0KaqpqtGnbSuhY+gUlJSXJzIRt2raWcTXyr2KlimhoqNOyVXOhYykLGqTdPt+uvbBt/Uq5cmXQ1NCkWYumQsdSFvz9d4VfL/SHEr4JCgQCgUAgEAgEAoFAIBAIpCZ0LgkEAoFAIBAIBAKBQCAQCKQmdC4JBAKBQCAQCAQCgUAgEAikJnQuCQQCgUAgEAgEAoFAIBAIpCZ0LgkEAoFAIBAIBAKBQCAQCKQmdC4JBAKBQCAQCAQCgUAgEAikJnQuCQQCgUAgEAgEAoFAIBAIpCZ0LgkEAoFAIBAIBAKBQCAQCKQmdC4JBAKBQCAQCAQCgUAgEAikVkDWBciDuLg4Lp6/xK2bt7l18w63bt7mzeu3AOgb6WFoPPun60ZGRHLxwiVu3bjNrVup64Z9+AiAu7czQ4cPyvS1j/57XLL+mzdv+fzpMwkJiRQtVoTatWvRu19PBg3pT4EC+eO/6tbN2xz99wS3bt7m6ZNnfP70mejoGAoV0qJqtSp06tKBMeNGUqRoEVmXmueioqJZv2YjRw4f49nT50RHR1OsWDEqVa5Ii1bNmTx1PNo62pLl89tnmZ398N3b9/x7+CgXzoVw59Zd3r17D0CJksVp1KQhI0cPo03bVj9d/+L5EE6fOsfNG7d48fwl4eFfiI2JRUdHm+o1qtG95/8YOXoY6hrqOfumc1F2Ps/0wj6EsXb1Bk4cO8XLF6+Jj4/nr+LFqFatKi1bt2DqjIkULFgwN99KrqtSvnaWl23VugUbtq6W/P7q5Ws6tP5fltcfMnwQHt7Ov1VfXsvOtpMT+1JycjLbt/7D3t37uXfnPhERkaipqVKufDnatG3FhMljqVjp7xx/37klO8fq7LYxFFXIxcusXbWeK5dC+fz5M4ULF6ZWnZoMGzGE/gP7/HCd7J4H5FF29kVfrwD8fQJ/+RrHTh+kUuWK3/39nx17uB56g1u37vDu7Ts+fwonRZTCX3/9Rf36dRgwuD+9+nSX/s3JgeCApXi4ekt+f/LqbqbL/247TZ7lRBshLOwjS4KXc+zICd68fou6ujrVa1ZjyNABDB81FCUlpV8+x7Onz1m/dhOnT57hzZt3pCSnULzEX9SqXZN2HdowbsLobL/X7JKX9lR+aY9t27KT+XMX/HK5NRuX0659m58+rgjbzp8of/RYZNP10JtMHj9DqnUPHzqapR3kZzxcvXlw/5Hk90KFtFBWVubD+zA+vA/j5InTrF21nuVrFlOiRHGpX0debN20g7WrN0h+V1NTQ11djS9fIrhyOZQrl0NZuWwNS1YG0qRpYxlWmrfOn72Iwex5fAxL/dKgqloQdQ0N3r17z7t377lwPoTuPbtSJ12jJb99ltLuh2/evKV9y66IxWLJ3zQ0NBCLxbx6+ZpXL1+zd9d+ho0YjLO7PSoqKt89x5JFKzh+9KTkd01NTVRVVfn06TOfzodw4XwIK5evYeW6JVSpUlm6N5jHsnNc+2rv7v0sMLUhOioaSN3GCqoW5M3rt7x5/ZZTJ88wZtwICurIf2MmM8V/cWxNTkriy5cIABo0rJfhMWUV5V+un5CQQFRk1A/Xl0fZ2Xayuy9FfIlg0rjpXAu9IflboUJaxMcn8OD+Qx7cf8iG9Zvx9nOjd9+eUtWY17JzrM5uG0MRuTl7sThomeR3bR1tIiOjOHv6PGdPn2f/3oMELPLJcNEtJ84D8ignjuMFCxZEp4jOTx//2cVLSzNbYmNjJb8X1i5MSnwyb9+85e2btxw+dJT2HdsSvNQfTU3NbNUoC08eP81S59tX0rTT5Fl2t62bN24zccxUwsO/AKClpUlMTAyXQ65wOeQKB/YdZsnKQFRVVX/6HCuWrcbdxZvEhEQgdZ9VVlbi5YtXvHzxigvnQ+Sig0Ae2lP5sT2mrKxMsb+K/fTx/LDt/ImEzqU0Ojo61K1fm3r16lC3fh0c7VwlVwd/pUTJ4tSpW5t69etQr35dZk3Tz/Lr9uzdg4mTx9G0eRMqVCgvuZr7/t0HNm/cir9PELdu3sHE0JxV65dK9d7kScPG9SlfwYRmzZtQtVoVyRWemJgYDh34FxcHDz59+syMKXM4euoA2tqFZVxx7rt86SpTJswkPj6eHr26MWv2dOo3qIuSkhJxcXE8uP+II4ePUrhwxs8iP36W0uyHohQRYrGYNu1aMXjoANq2a0Op0iURiUQ8fvQETzdf/j10lK2bd1CqdEnmmhh89xxt27emQ8d2NGvRhIqVKlKokBYA4eHh7N65DzdnL16+eMWsqXM4cGQ3ysqKcUdxdo5r+/cexHC2CSKRiFFjhjNxyjiq16gGQHR0DHdu3+XwwSMUKKj4p5GQ0NOZPr5s8UqcHdwBGD5qaIbHypYt88v1bS0dWbNqPerq6gwY2Dd7xeYRabed7O5LDrYuko4lg7mzGT9pNEWLFiUlJYXLIVewsXTgwf1HzDM0p0nTxpQuUyrn33wOy+6xOjttDEWzYd1mScdS3wG9MbcwoUzZ0iQkJLJ3935sLBw4fPAIrk6eWNqYSdbLifOAvMrOcRygSdNGbNy25rdfd/ioIdSrX4cmTRtTpmwZ1NRUEYvFvHzxipXL1rB65TpOnzyLk707Tq62v/38siQSiTA1tiAhIYEmTRtx9cq1TJeXtp0m76TdtiIjo5g6cSbh4V+oWq0KXn5uNGhYj8TERDZt2IqTnRunTp7BwdYFB2ebHz7HsiWrcLZ3o0CBAsyaPZ2Ro4dR4e/yQOpFhuvXbnLm9Lkcfb/ZIcv2VH5tj5UpW5rTF47+9nqKtu38aRRrK8wlzVs2JfT2hQx/c3fx/snSGQ0a0j9bw9J/NpSyVOmS6BvpkZCQSHDAEk6dPMPbN+8oU7a01K8lDwYPHfjDv2tpaTF46EBKlCjBhDFT+fTxE8eOnGDg4H55W2Aei4uLY56hGfHx8UyYNBYbB4sMj2toaNCwUX0aNqr/3br57bOUdj/U1tFm94Ft1KtfN8PflZWVqV6jGouWLWTyuBmcPHGalcvWoDdnJmrqahmWnTx1wg+fu2jRokyYPBZVVVUszGx4+OAxV69co1nzJr/57vJedo5rH95/wMLUFpFIxAJrU6ZOn5jh8UKFtGjRshktWjbLqXLl2pZN2wFo1qIpVar+3si1hPgEdu3cC0DP3t0U4paJ7Gw72dmXEhIS2bvnAABDhg3EYK6e5DEVFRVatm7B4uWBdG7Xg/j4eI4dPcHosSN+9+3luewcq7PbxlAkycnJ+HoFAFCvfh18F3pIOh/V1FQZMmwg8fHxWJnbsWblesZPHMPfFSsAOXMekEfZ2Rezy9ru+xFzSkpK/F2xAjYOFnz+HM6eXfvYuW0Xtg4WCnE7zlerV6zjyuVQBgzqR8VKf2fauZSddpo8y862tWzxCsI+fERdXZ0VaxZLvtirqqoyfuIYoqNj8HT1YdP6rUyaOv67Uar37j7AI+21/AK9vru9UqeIDh06taNDp3bSvr0cJcv2lNAey0jRtp0/kWJcfs9l2RkendtDqxs3aSj5+X1afkB+1ijd+3339p0MK8kbO7fv5sXzl5QoWRwzi3k5+tyK9llKuy9paxf+7gtFekpKSgwbORiAmJhYHj16/NuvoWifJWTv2LRqxToiIiKoW682U6b9uLPgT3HlciiPHqZuMyO+GbWUFQcP/EtERITU68tCbp7XMtuXIiMiJEPc6zf48e2DFSv9TZG0W3xiY2J/uIyiyewzUZTbt3LCrRu3JbccTZk+6YcjREeOHoa2jjbJycn8s2O35O95cR6QBXn+///aPo2Pj5fcNqwIXr54hZe7H0WLFsHS1uyXy+dmO02WsrNt7di2C0gdXfi1Yym9CZPGoKWlSUpKCrt27P3u8aCAxSQlJdG9R1eFyO2SZXtKaI9lpGjbzp9I6FySc5cuXgFSG0YV0q7Q5WeXQi5Lfv67ouIEtkprZ9oJunefnjl+FfVP+ywzo6b232ebkiL67fX/tM/y63Y5YHD/LAVy5mdbNm4DUvNGevft8fvrp416qlS5Ii1bt8jR2hRRZvtS8RLFJdktN2/c+uH6z5+9kHyRrd/g550JiuRPO778zOvXbyQ/V69R9YfLqKioULlyJQBOn/q92x6yex4QZHQpJLV9qqWlSfHif8m4mqwzn29FbGwsFjam/JVJ3stXudlOU0RPHj+VhFl36tz+h8toaWnRrEVTAM6cOpvhsdjYWA7t/xeAgUP652Kl8iG77SmhPfafP23bUVTCbXFyKCYmhlcvX7Nz2y6WLVkJpA6Nz8pJUBElJCQS9iGMY0dO4OO5EEi9Ot21W2cZV5a7EhISJV+g6jWoy+vXbwj0W8TJ46f5+PET2jraNGxUn9HjRtCla6csP+ef+Fn+yoXzIUBqAGflKpWytE58XDxv375j/75DLPQNAqBFy2YKEcicHS9fvOL9+w8A1K9fh3t3HxAcsIQL5y8S8SWCYsWK0bR5YyZMHqcQtwdmR0xMDPv3HgSg34DeaGho/Nb6L56/5MK5iwAMHzkkx+tTFFndl5SUlBg1djjLl6xi+9Z/KF+h/A8zlwB69+2p0J11wrE6c5l1/qSIUgB4cP/hbz2nNOeB/ODhg0f07NqPF89foaysTKnSJWnRshljJ4yibr06v/VckZFRPHv6nHVrNnJg3yEAJk+bqDBfejet38K5Mxdo2771T29XTS832mmK7v69//a7GjWr/3S5mjWrc/L4aR4+zDhK8HroTZKSkoDUCwSXQq6wdNEKrl4OJTomhpIlS6TOfDZ9IjVr1cidN5FHstueyu/tsc+fwunfawhPHj8jJSWFkqVK0KRpY0aMGkqrNt+f3/+kbUeRCZ1LciL0yjWGDBj13d9VVFQYPHQAdo5WMqgqd9Wq2lByC0R6TZs3wTfAAzW1n88SkB+8fvWaxMTUg+SL5y+xs3IkOjoGVdWCaGhqSPI3jh05wYhRQ3F2t/9pA+5P/ywz8/LFKzas3QxAn369KFy40E+XDfsQRssmHX74WNduneV+Cvmc8PTJM8nPly+HstAnkMTEJNTV1VFVU+Pdu/fs23OQ/XsPYWg8mzmGurIrNpft3bWfmLRbr0aMGvbb62/dvB2xWEyBAgUYMmxgDlcn36Tdl+bNNyT8czg7tu3CzzsAP+8AChUuRHxcPMnJyfxdsQKmC4yZOmNSbpafa4Rj9c+VL19O8vOD+w9/ODItMTGRZ0+fAxAVGUVsbGyWZir7nfNAfvP5czhfvkSgrV2Y6OgYnj55xtMnz9iyaTu6c6ZjPN8w0/X37NqHgd73t4OpqqkyeeoE9I0U4xzw7u17XJw8UVdXx8nVLkvr5GQ7Lb/4kNbZAVCq9M8nVPj6WHRUNDExMWhppU7u8PTpM8ky+/YcxM3ZC7FYjJaWJgULFEib3XEnu3fuxdHVlmEjBufOG8kD2W1P5ff2WFxcHLdu3kFHR4fk5CTJTG+7du5h6IjBOLvZZZjN8k/adhSZcFucnCioWpDiJYpTvERxVFX/C0UcNXY4+nP1JLPI5Scl0t5v+oZh6zYtsbI1p1y5sjKsLG9EpMsoCPRfRIECBQhY5MvN+1e4dvsipy8elUy1vXnjNpYvXf3T5/rTP8ufiY+LR2+mIXFxcRQrVpT55saZLq+soiLZD9PfQtG7b0/MLOZRpGiRXK5Y9r7mAwH4ePhTslRJ1mxczq0HV7hx9xKHju2hVesWiMVifDwXcnD/YRlWm7s2p90SV7tOrd++BSslJYXtW/4BoHPXjpQoWSKny5Nr0u5LaupquHg4YG5pIgkIjo6KJjk5GUhtjH75EkFi4vcdNIpAOFb/XN36dSheojgAi4OWSf7P01uzcr1kKm4gw88/87vngfyiUuWKmFnM48ip/dx9fI2rty5w68EVVq9fRr0GdRGLxQT6L2bZ4pWZPo+6urpkX/6aPaOiosKMmVOYOmOSXOdCpWdhZkNUZBQGc/UkQfC/kpPttPwiOiZG8rNGJt9N0j8WE/3fOhFfIiU/u7t4U7tOLXbu2czN+1e4ef8KO3ZvolbtmiQlJWFhasP1tNlDFVF221P5tT1WqlTqpFX7Dv/D3cfXCb19gdsPQ9n6zwbatm8NwLbNO3C0dc2w3p+07SgyoXNJTtSrX5eQ0NOEhJ7mzqNrHDt9kHETRrNh7WZ6dunHkcPHZF1ijjt94Sghoae59eAKIdfOsMBqPndu32NQ3+H4ePjLurxcJxKL//tZJMLV05HefXtIvlCVK1cW/yAvatepBUDwwsU/bGyD8Fn+SHJyMoaz53Hrxm0KFiyIz0IPSpUumek6f/1VLN1+GMrZkOPo6c/g6L/H6d1tIBvXbcmj6mVHJPpvuxSLxQQt8aNd+zaScN3qNaqxdFUQJUqmfgn09wmSSZ257cH9h1xLa5hIE8R98sRp3qVNwjB81J93S5y0+9LLF6/o32soLo4e9OjdjV37t3Hz/mXOhBzDw8cFJSUlFgctY8SQccSk+5KjKIRj9c8VKFCAOYazAHj08DFTJ8zi1s3bJCam3kK4JHg5Hq4+GWYlU/pB6Hd60pwH8ouBg/sxfdYUqlSpLPnMVFVVad+xLVt3rKdBw9TZzfy8A4iMjPrp83Tr0VWyL999fI39/+6id9+eLPQLpmfX/ly9Epon7yc7/tm+m+NHT1Knbm2mfDPbVmZysp0mSCUS/3fLq5qaGstXL6Jh4waSvzVq0pBlq4NRV1cnOTmZwIWLZVFmjshueyq/tsfad2yLofFsatepKRmtq6KiQtNmjVm9fhndenQFYN2ajRlGb/1J244iEzqX5JCysjKVKlfEzskKM0sTYmJiMZpjkmEoan5TvPhfTJ0xiVXrlqCkpMRCv2COHjku67Jy1dchwpB6hbF7z/99t4yysjLT0m7/CA//wq0bt3/5vH/iZ/mtlJQUjOaYcPjQUQoUKIDPQg/ad2z7W8+hpKREmbKlMZ5viM9Cd5KSkrBaYMfdO/dyqWr5UKjQf9tlm3atfjgDk5aWFuMmjAbg3t37hKXN8JSffB21pKamlmFq+KzasiF1/dKlS9Gp849vD/tTZHVfSklJYfpkPe7fe8DgoQPwD/SifoO6aGlpUbZsGYYMG8jajStQVVPl1o3bLA5aJqN3lDOEY/X3xk0YzbQZkwE4dfIM/XsNpVaVhrRs0gFXJ0/KlS/L9FmTJcvr6Gj/9Lly4jyQX6mpqzHPzBBInT3v3JnzWVqvQIEC1KpdA79ATyZMGsvHsI/MmWVMfFx8LlabPWFhH3GwdUFFRQVnd/sMt9n8Sm610xRZoXSfSVwm/+/pH9NK165Iv37/gX1+2NlbtmwZ+g/sA8C5MxdISUnJVs2ykt321J/YHlNWVsbc0gRI7dA9euSE5LE/adtRZELnkpwbN34UqmqqxMTEsnvXflmXk+saNm4gCaXbtH6rjKvJXaXTHRSrVqvy0+WqpZs1J/1sOr/yJ32W6aWkpGCkP599ew6ioqKCt7+bVLN8pdezd3fKliuDSCRiy8btOVSpfEp/sq5W7cczNgFUq/7fY29eZX27VASJiYns2rEHSP2/187kC+yPhIV95NjRkwAMGT5QYW4byQuZ7UunT57l/r0HAEydMflHq1O9RjU6d+kIwMG0WWMU3Z96rP4ZcysTtuxcz5Dhg6hRsxplypahYaMGGM83YO+hHSgrp+5P5cqXRVX1xxlVuXEeyG+aNG0k+fnli1e/vf7ktGnR3755y4njp3KqrBzn7uJNePgXRo4ZRtVqlYmJicnw72tAMCD529fbbnO7naaISpb67zN5nzY690e+PlaocKEMnXTp2xhVq2fSxqhRDUidISw8/Iu05cpUdttTf2p7rFLlihQrVhSAl89fSv7+J207ikwI9JZzaupqFCmiw4f3YTx/9lzW5eSJryGAz5+9kHEluatI0SKULl1KcuvMz6Qblf3bQZF/ymf51dcr1Xt3H5B8oejbv3eOPHfp0qV48/otz/L5fli9ejVUVFR+ebUn/XZJPgswPXL4GJ8/hwPS3RK3c9sukpOTUVJSYtiIP++WuF/52b70KN2sQhUr/TwTpVLlioB0X4jl1Z92rP6VZs2b/HT2o6+zdzVp2viHj+fmeUDwn/Rf9OR5u32VdpxYv2YT69dsynTZ+jWbATBxyjis7RbkSTtN0dSs9d8McQ/uP8zQsZHe/bTZHKt/83it2jWz9kLpPlRF/Uyz254S2mMZ/UnbjiITRi7JuejoGD5/Sv2Sk77nPz97+SK1l/pPeL/t0oboP/pmqtb0Hj14JPm5fIXyv/X8f9JnmZKSguHseRm+UPQb0CdHnlssFvPyZWoDNf0w5fxITV2NFi1TG9iPHmWyXT5M3S6VlJQoX6HcT5dTRF9viatY6W9atm7+2+tv2ZQ6IqdVm5ZZDo79U2S2Lykp/9cIfJ3J1dePHz/9cH1F9icdq7MjLOyj5BauwUMHfPd4bp4H8pvQq9clP/9u2wIydu5q5aN98Vu53U5TNJWrVKJsuTIAnDx++ofLxMbGcjnkCgDtOmS8FbVS5YqS8+LjTD7Th2mfaaHChSiqoJOpZLc99ae2x54/eyG5wFfh7//2pz9p21FkQueSDGUl9G9p8HLJcq1at8jtknJVSkoK4gzd6987e+Y816/dBJDqS52iGTp8EJB6ID188Mh3j4tEIpamzeRSunQp6tWvAwif5be+Xqnet+dgWraGe5a/UGRlP9y6eQdhH1LvY2+p4PthVnzdLs+ducCtm9/nR8TExLBuzUYAGjVuwF9/FcvT+nLT69dvOHs69cvrsJFDfvuq16WQKzx5/BSQbtSTIsvuvlSvXh3Jzz8bYRD2IUxyrGyc7rYeeSUcq3NOSkoKVma2JCYm0bBRAzp0avfd49KeB/KbX21zCQmJeLn5AqCpqUnbdq0yPJ6VfTk4YInk55at5He73bhtDU9e3f3pP30jPcmyX/9mbbdA8jdp22n5lZKSkqRjd+/uA7x6+fq7Zdau2kBMTCwqKioMGNz3u8eHDBsIwO5/9vH+3fd5sm/evGVPWhRIpy4dJAHWiii77an81h771bFJLBbj4ugBpOYvdflfpwyP/0nbjqISPvE0EV8i+Pw5XPLva0J/fFxchr//aHaa9I9/7WkFiI2JzfD3uLi4DOvt2rmXaZN0Obj/sORKLKSeqO7euc+C+dYs9AsGoGnzJnTs3D433nqeefvmHX17DGbDus28eP4ywwHmzZu3BAcsZcbk2YjFYooU0WFK2v38+VmLls3o1Sc1B8LcxIoD+w5LGnWvX7/BQM+Ye3fvA2Bsaig5SObXz1Ka/fBrtsbe3QcoUKAAvgEev3ULxOWQq4wYMpad23bx9s27DI89ffIMN2cvLM1sAahY8W+GDhuU/TeaR6Q9rg0Y3I+GjRogFovRnW7A2TPnEYlSZ+l49PAx0yfpEfbhI8rKyhibGub128pVWzftQCQSUaBAAYamNWJ+x5a0UU9FiujQo1e3HK4u70iz7WR3X2resplk1qU1q9bjaOcqaTwmxCdw8vhpRgwZR1RkFEpKSgpxXMuJY7W0bQxF9OL5SzzdfLl18zYJ8QlAapvo8qWrjB89lcOHjqKto42Hj3OGjt/sngfkmTT7YsiFS4wdOem7fTEpKYmzZ84zYvBYyWyYcwxnfZcrtyhwKUZz5nPi2CkiI/6b/js5OZlrV68zc+ocdmzbBUD/gX2pnpZxkh9J205TBNK2EabOmEyJksWJi4tjyoQZ3EwLMU9MTGTdmo34eKbOfDlyzDCqVKn83etOmT6RcuXLpq0/M8OU8ddDbzB1wizi4+NRV1dH31A3t97+b5FVeyq/tcdev3rDwD7DvzsnikQiQq9cY9LY6ZJO3FFjh1OlasbtRxG3nT+NkLmUpm/PwT8chr9k0QqWLFoh+X3IsIF4+LhkWKZZgzY/fE5bK0dsrRwlv+sb6WFoPFvyu1gs5ui/xzn6b+rsMJqamqirqxEdHU1i4n8Bg63btiJwkU++uG/07p17ki8XqqoFKVSoEPHxCcTGxkqWqfB3eYKW+FGiZAkZVZm3PHyc+fTxEyEXL6M3wwBVNVU01DWIiIiQLKNvpCfprf8qP36W0uyHVy5dZW/aVQolJSVsrZywtXL66WtY25l/96Xj0sUrXLqYOoRbTU0NLS1NYmPjiI//b7aT2nVqsXh5AOoa6tK/wTwm7XFNWVmZJSsCGDtyEg8fPGbcyMloaGhQoGABotKmrC5YsCB2jpa0advqu+dXVCKRiG1bdgCpV7zSB5dmRVRUNPv3HgJg4OD+kil2FZG020529iVlZWWClvgxYcxUXjx/yYqlq1mxdDVaWprExcVLGtQqKipYWJsqzCjC7B6rpW1jKKLo6GiCFi4mKG0KaR0dHWJjYyWhy2XLlWHRsoXf5bzkxHlAXkmzL4rFqSMdzp25AIC6ujqamhpERUVLPktlZWVm6k1jhu7U7547OTmFXTv3sGtn6sQGWlqaqKqqEhUVnWFUU9/+vXDzdPxu/fxG2naavJP2OK+tXZhlqxYxccxUHj54zIDeQylUSIuEhETJ9tW+Y1ssbcx/+LqampqsWreUcSMnc+f2XQb1G4GWliaQOnshpG5zvoGeP810ymuyak/lx/bYjes3uXE9dbSuqpoqhbS0iI6JITEhUbLM0BGDsbG3+G5dRdx2/jRC55IMde7aERd3ey6cv8TdO3f5GPaJiIhI1NXVqPB3BRo0rEff/r3p3LWjrEvNESVLlSBgkS8Xz4dw7doNPrz7QHh4OMrKKpQtV4badWrxv+5dGDCwr5oD2NoAAQAASURBVEJ9gc8uTU1NNmxdzdZN29m5fTcP7j8kJiaW0qVL0axlUyZMGkvTZhmDS4XP8j9frx5B6lXZj7+YhjU+7Wr4V/Ua1MXbz40L50O4eeM2YWEf+RL+BVVVVSpW/Ju69evQs3c3evXp8UfN+lWiZAl2H9jB2lXr2bv7AE+fPiMhPp7yFcrRuk1LJk+bQM1aNWRdZo46e/o8b16/BaS7pW3vrv2S0SPD/7Bb4iBn9qWKlf5m/7//sGnDVo4cOsaD+w+JjIxCTU2NsuXK0KJVc8aOH0XtOlkM9pQx4Vj9e8qXL8ccQ10ung/h+bMXhIeHU6iQFlWqVaFHr26MGTcCDQ2N79bL7nkgv6lZuzoLrOZz9co17t97QPjncCIjo1DXUKda9ao0b9GUkWOGU6v2j4/hw0YOplixolw4H8LDB4/49PETkZFRaGppUrZsGZo0bcTAIf1p3qJpHr8z2ZCmnZbf1W9Ql4PH9rA4aBnHjpzg7Zt3aGhq0LBmA4YMHcCwkUMyHcVVtVoVDh7bw/Ilq/j30FFevnhJSoqIKlUr06FjO6ZMn0C58oqfHwTZb0/lp/ZY8eJ/YetgydUr17h75y6fP4UTERGJmpoqFSqUp0nTRgwbOeSnEzrAn7XtKCIl8a9ufgQiIyPR0dEhIiICbe3fm5I5N1laWrJ69SpOXfj+HmjB96qUr83gIQPw9HOVdSlyL3DhYvy9A7n/9MavFxZQq0pDOnftSPBSf1mXIveWL12Fq6MnD5/fknUpCqFhnRY0adKQleuWyroUubdh3WaszG15/PKurEtRCC0at6dylUps3r5W1qXIvQXzrdm0YSv3nlxHVVVxR+TllbrVmzB2/CjMrUxkXYrcc7JzY/nSVVy7E4K2dmFZlyP3GtRqxqAhA7BzspJ1KXLP12sh/j5BXLhy8rdHIv+JGtVpSfde/8Pd6+ejPgWpzp+9yJgRE3n8+DFVqlSRdTm57nf6ghTnxmCBQCAQCAQCgUAgEAgEAoHcETqXBAKBQCAQCAQCgUAgEAgEUhM6lwQCgUAgEAgEAoFAIBAIBFITOpcEAoFAIBAIBAKBQCAQCARSEzqXBAKBQCAQCAQCgUAgEAgEUhM6lwQCgUAgEAgEAoFAIBAIBFITOpcEAoFAIBAIBAKBQCAQCARSEzqXBAKBQCAQCAQCgUAgEAgEUhM6lwQCgUAgEAgEAoFAIBAIBFITOpcEAoFAIBAIBAKBQCAQCARSEzqXBAKBQCAQCAQCgUAgEAgEUhM6lwQCgUAgEAgEAoFAIBAIBFJT6M4lkUiEWNZFCAQCgUAgEAgEAoFAIBD8wRS2c+nkyZMsX76c9+/es3TRChITE2VdktyKjo7Bw9UHgIsXL3Pn9l0ZVyTfLl+6yq4de0hJSSEoYAkJ8QmyLkluxcbG4uO5kMTERK6FXufG9VuyLkmuXQ+9wfYtOxGJRPh5BxIXFyfrkuRWfFw8gf6LiImO4datu1y9EirrkuTa7Vt32LR+K2IxeLn7EhMTI+uS5FZCQiKLg5YR/jmch/cfEnLhkqxLkmv37j7g3NkLAHi5+REVFS3jiuRXYmIiy5euIjExkYP7D3P2zHlZlyTXHj18zMkTpwDw8fAn4kuEjCuSX8nJyaxZtZ74+HiO/HuMk8dPy7okufb0yTP+PXQMAD/vQMLDw2VckfxKSUlh47otxMbGcur4aY4cPoZYLAzf+JmXL16xdPEKAMzNzfnw4YOMK5IvSuIsbD2RkZHo6OgQERGBtrZ2XtT1U8+ePcPExIRt27ZRv0E94uPjefjgERX+Lo+1/QK6dO2EkpKSTGuUFyKRiJ3bd+Pi4M6XLxFUqlyR16/ekJiYyIjRQzGeb8hffxWTdZly482bt7g6erJ39340tTQpXuIvXj5/RZkypbGyM6d7z/8J21YasVjM7n/24ezgzsewj1SqVJG3b98RHx/P0OGDMDEzokTJErIuU268f/cBdxcvdm7fjYaGBqVKleT58xeUKFkCSxtT+vTrJWxbacRiMQf2HcbRzoX37z7wd8UKfPgQRlxsHAMG9cN0gTGly5SSdZly4+PHT3i6+rJ183bU1NUoU6Y0z5+9oFixoiywmk//QX1RVlbY60g5SiwWc+TwMRxsXHj9+g3lK5Tj86fPxMTE0rtvD8wtTShXvpysy5Qbnz+H4+Phz4Z1mymoWpDy5cvx7OlztHW0MbOYx9Dhg4RtK50Tx05hZ+3E82cvKFe+HBEREURHRfO/7l2wsDalYqW/ZV2i3Ij4EoGfTyBrVq6nQAEV/q5YgSePn1GocCHmm89lxKihqKioyLpMuXH2zHlsLRx4/PgpZcuWITo6msjIKDp16YClrRlVqlSWdYlyIzIyikC/RaxYthplZWUqVvqbp0+eoaGhgfF8A0aPG0HBggVlXabcuHg+BBtLRx7cf0jp0qWIi48n4ksEbdq1wtpuATVqVpd1iXIjJiaG4IClLFm0HCWUaNe+DVeuhIIYbGxsmD17NqqqqrIuM1f8Tl+QwrQKYmJisLKyolatWpw+cxpvf3d27t3MoWN7CFriR3RUNNMm6jJh9FQePXws63JlLvTKNQb2GYaJkTnqGups3r6WIyf3c+XmObr36MrWTTvo2Kab5ArbnywuLg5/n0C6tOvJoQOHGTp8ENduX+TEmcMsWxVMQmIis6bpM3r4RO7dfSDrcmXuxvVbDBkwCqM5JigrK7Nu00qOnj7A1Vvn6du/F//s2EPHNt1ZHLSMhIQ/e9tKiE8gKGAJndp1Z8+u/QwY1JfQ2xc4duYgq9cvA7EYfV1jhg0cza2bt2VdrszdvXOPkUPGMXumIcnJKaxYu5jjZw4ReusCg4cOYN+eA3Ru150Av2Di4+JlXa5MJSYmsmzxSjq16cb2bTvp2bs7V26c4+ipA2zYupoCBQsy18CUwf1Hcj30hqzLlbkH9x8yduQkZkyZTUxsLIuWLeTkuX8JvX2REaOH8u+hY3Rp3wsfz4XExsbKulyZSkpKYtXytXRs041NG7bStVsnLl8/x5GT+9m6awNaWlqYzbOkf68hXL50VdblytyTx0+ZNHY6k8fP4MuXCBYG+3D6whGu3b7I+EljOHniNN069cHdxZvo6D97RGFKSgrr126iY5turF21gXYd2hBy7SyHj+9j1/6tFC1aBEszW3p3G8iFcyGyLlfmnj97wfTJeowbOZmwsE94+7txJuQYV29dYOqMSZw7c4Hunfvi7OBOZGSUrMuVqZSUFDZv3Eantt1ZvnQVLVs15+LVUxw+vpe9h3dSslQJ7Kyd6NV1AKdPnZV1uTL3+tVr9GYYMmrYBN68foOLuwPnLp/gyo1z6OnP5MqlUHp3G4idlRNfwr/IulyZEolE7Ny2i05turMocCmNGzfkbMgxlq9ZxPEzBxkwqC8mJibUr1+P/fv3y7pcmZP7kUsikYgNGzZgZmbGx48fmTZzEjN0p6KlpfXdcl7ufqxYuoqkpGTGTxyDwVw9dIro5Gm9svbu7XvcnL3YtXMPWlqazDOby4RJY75b7snjp8yaps/DB4+oWOlvbOwt6NSlgwwqlh2xWMy+PQdwsnfjw/swGjSqT9ASP8qUKf3dsn7eAZLOktFjR2Bkok+xYkVlULXshH0Iw8PVh+1b/0FdXR0D49lMnzn5u+WeP3uO7nRD7t29T9lyZbG2M+d/3bv8USNzxGIxhw8ewcHGhbdv31Gnbi2Cl/hT/u/y3y0bHLiEAN9g4uMTGDZiMMamhpQoUVwGVcvOp0+f8fbwY9P6raipqaE7ZzqzDWZ9t9zr12/Rm6bPzZu3KVW6JJY25vTq0/2P27aOHT2BvbUzL1+8omatGgQt9aNy5UrfLbty2Rq83P2IjY1l0JD+zDc3plTpknlftAx9Cf+Cr1cA69ZspGDBgkybOQlD4znfjbh5/+4DujMMuHb1OsWL/8UCa1P6D+zzR21bAKdOnMHO2omnT55RtVoVApf4UaNGte+WW7dmI25OXsTExNCnfy/MLOZRrlxZGVQsO5ERkSz0C2blsjUUKFCACZPGYGox77tt69Onz+jNMORyyBWKFNHBzNKEwUMH/HGjvs6fvYitlaOk3Rm4yJc69Wp/t9zWzTtxtHUmKiqaHr26scBqPhV+cO7Mz6KjYwj0X8TyJatQUlZi9NgRWNmaf7fNfAn/whzduZw/e5HC2oUxNZ/LsJFD/rhRX5dCrmBr6cjdO/coX6Ec/kHeNGrc4Lvldv+zF2sLByIjIunctSOWNmZUrlIp7wuWodjYWBYHLmNR0DIAhg4biJ2zNQUKFMiwXFRkNIazjTl18iyamhoYmxoyeuyI75bL765dvY6NlSM3r9+iTNnS+AZ40rxF0++Wu3f3AY62Lpw7e4EePXvg4+1D7drfH98U1e/0Bcl151JISAgGBvpcuHCRXn16YGYx75cnmKjIaPT15nLm1Fm0tLSYZ2bEyNHD8v3OEB8Xz7IlKwn0X0RKioj+A/rg7GH/y+F5+/cewtLMhi9fIujYqT1WduZUqZr/h9feunkbW0tHrl65RsmSJfD0daVdhzaZrhMdHcNc/fkcP3oSdQ11jE0MGDN+ZL4fXpuQkMiq5Wvw8w4kOTmZnr274e7tjLq6eqbrHTl8DLN5lnz+HE7rti2xtltAzVo18qhq2bl39wF21k5cPB/CX38Vw93bmc5dO2a6Tnx8PMYGZhw+dATVgqoYGs9mwuSx+XZ47VeJiYmsXb0BH8+FJMQn0LVbZ7z93dDU1Mx0vVMnz2BiaE5Y2Eeat2iKjYMFdermn5P4zzx6+Bh7a2fOnD5H0aJFcHKzo2fv7pmuk5iYiKmxJfv2HEClgApzDHWZMnUCaupqeVS1bCQnJ7Nh3Wa83HyJjY2jQ6d2+C70pLB2oUzXu3AuBCN9E96/+0CjJg2xdbCkQcN6eVS17Dx98gxHWxeOHzuFjo42dk5W9B/YN9N1kpOTWWBqw64du1FSUmbW7OlMnzUZDQ2NPKpaNlJSUtiycTvuLl5ERUXTum0rAoK9f3kx88rlUAz05vHm9Rvq1quNnZMVTZo2zqOqZefli1c42btx+OARChcujJWdOUOHD8p0nZSUFGwtHdmyaTtixMyYNYWZetO+u7Cc34hEInZs24WrowdfvkTQvEVTApf4UqxY5hEWN6/fYs4sI16kXXCwc7SkRavmeVS17Lx+/QZXRw/27TmIViEtzC1NGD12RKbriEQinOzdWL9mEykpKUyZNgE9g1kULpz5uUHRicVidu3ci7ODO58/faZRk4YEL/H7ZYTFvTv30JthxNOnz6hatTK2Tla0bdc6j6qWnffvPuDm7MU/O3andq7NN2TS1PGZriMWi/n30FGcHdx58/ots2fPxtramqJFFX8wgsJ3Lr19+xZzc3NWr15N7Tq1sLYzp2XrFr/1HHdv30VvphHPnj6nWvWq2Dpa0qZtq1yqWHa+zSepX78ugUv9KVeuTJafQyQS4e7izarla0lOTmbilHHoG+qirSPbfK3cEBb2ES83P7Zu3o66uhqzDWcxS2/6bz3HgweP0JtuwONHT6hcpRI29hZ06NQulyqWna/5JPY2Lrx5/YZatWsStMSXipUqZvk5RCIRvt4BLA1eQVJSEmPHj8LQeDZFihbJvcJlJH0+iZqaKjN0p2Iwd/ZvPcfTp8/QnWbAg/sPKV+hXL7OkUufT1K9RjWCl/r/dsd2gN8ighYuJiEhIV/nyKXPJylYsACTp03EeL7Bb418ePXyNbOm6XPn9l3KlCmNpa0ZPXp1y5fb1pnT57CzdOTx46dUrlKJwCV+1PrNju2li1fg6xlAXFwcQ4YNxMTMiJKl8t+or/T5JCoqKoydMJoFVia/tW29ffsOvekGXL9+kxIlimNpY5Zvc+TS55P8XbECC4N9qN+g7m89x+qV6/Fw9SY2Jpb+A/tiusCYMmW/HzGt6L7NJxkxehi2Dha/tW19DPuI3gxDrlwOpWixoiywNGHA4H75ctTXlcuh2Fo6cPvWXcqVL4tfoOdvdz5u3rAVJ3t3oqOj6dWnBwus8meOXFxcHIuDlrMocClisYhBQwfi6GLzWwMJwj+HM3umERcvXEJbRxvTBcYMHT4oX476un7tJrZWjlwPvUGp0qXwXehBy9a/1/m4Y9su7K2diIyMytc5cgnxCSxbuooAv2BSklPo178XLp6Ov3WxNyEhkZXLVhPovxh1dXUcHR2ZNm2aQm9bCtu5FB8fj4+PD87OzqiqqWJsYsDwUdkb3rlty04cbFyIioqiW4+uWFib8nfFCjlYtezcuX0XOysnLoVcoXiJ4nj6OtOhY3upny8yIpI5unM5e/o8hQsXYr65cbY/f3mRmJjI6hXr8PMOICExke49/oeXn+svR99kZu/u/ViZ2xEREUnnLh2wyEehivfvPcDexpnzZy9SrFhRXD0d+V/3LlI/X3RUNIaz53HyxBk0NDSYZ2rI6HH5Y3htUlIS69dswsvDj/i4eDp37YC3vweFCkl/hfXQgX9ZMN+a8PAvtG3fGmu7BVT/wa0piujJ46c42Lhw8sRpihTRwdHVjt59e0j9fLGxsRgbmHHk8DHU1NUwmjeHcRNG54tRX8nJyWzasBVPVx9iYmJo174N/kE+vxx9k5njR08y39iCTx8/0bJVc6ztLahdp2YOVi07z54+x8nejaP/HkdbWxtbRwsGDu4v9fPFx8czf64FB/cfpkCBAugb6TJp6gTU1BR/20pJSWHblp24OXsRGRFJq9YtCFjkk62O/7Onz2NsaMqH92E0adoIGwfL3+54kVevXr7GxdGdA/sOU6iQFhbWZowYPVTq50tMTGSBqQ27/9mLirIyunNmMG3GZNQ1pG+TyAuRSMQ/O3bj4uBBePgXmjZrTOASP4oX/0vq57wUcgXD2fN4++Yd9RvWw87BkkZNGuZg1bLz9s07XJ082bNrH1pampiYz2X8xO/jLLIqOTkZ6wX2bN/6DwAzdacyQ2/qL0cEKwKxWMze3ftxsncj7MNHGjZuQNASP0qXln6Sj9DQ6xjMMubVq9fUrlMLW0fLH972pIg+vP8gibPQ0NTAyFifqTMmSv18IpEIBxtnNqzfglgkZsr0iejpz8xWe1deiMViDu7/F0dbF969e0/denUIWuJH+QrSd85+eP8BDzdftm/ZSYMG9fH19aNz5845WHXeUbjOJbFYzD///IOx8VxevnzF+EljcnTkjEgkwtbKic0btyIWiZk2czKzZk9X2J3h06fPeLn7snnDtkzzSaR16+YdZs805MXzl9SoWR07R8vfHjkmL9Lnk7x6+ZoaNav/NJ9EGiKRCBcHD9au3kBKSgqTp05Az2Am2tqFc+T589p3+SSzJmM4d3aOXSW8d+8BetMNUvM8qlbGxtGSdu0zvx1RnmU1n0Qa+S1HLjIiEn/fIFYtX5uaTzJ5LKYLjHNs28pvOXLnz17ExtKBRw8fU6lyRQKCfX6YTyKt1By55SQkJCh8jlz6fBLltHwSyx/kk0jrxfMXzJpmkG9y5L7NJ1kY5EPDxvVz7PkXBS5loW9QvsiRi42NZVHgUhYHLQdg6PBB2DlZ5diFke9z5Mzo1aeHwm5b165ex9rSgVs3blOmbBn8Ajxp1qJJjj1/ao5c6q2uip4jFx8Xz9LFKwhauJiUFBEDBvfDydU2xy6MhH0IY9b01By5v/4qpvA5cjdv3MbW0oHQq9cpVaokXv5uOXpHyvq1m3B19MwXOXIJ8QmsWLaGhb5BJCcn06tvD9w8HbN1QT29z58/ozs9/+TI3b1zHzsrR0IuXqZ4ib/w8HahY2fpB2t86/q1mzjYuHD1SiiDBw/G09OTypUVazCCQnUu3bx5E0NDQ44dO0anzh2wsDGlarUqOfoaX338+Cl1eO2lqxQtWgRzKxMGDu6vMDvDt/kk/+veBS8/11y7GrF103Yc7FyJjoqmZ+9uLLAyzVYPbl77Np/E2d2eHr265cprfQn/wuxZRlw4F5I6vNZ8LkNHDFaYUV/f5pN07NQO3wBPCuXSPei7du7BxsKRyMhIunbrjIW1KZUqZ/12O1l78uQpTrauHD92Cm0dbRycrek3oE+uvJai58h9m0/Stn1rFgZ559pttwf2HcbC1JovXyLo0LEdVnbmuXZOyQ0vnr/E2cH9t/JJpPVtjtzcefqMnTBKYXLkvssnadmMwMU+v8wnkVb6HLlWbVpiY69YOXLS5JNIKz4+HmNDMw4fVMwcuW/zSRo3aUhQFvJJpJU+R65Z8ybYOloqVI7cu7fvcXfxTssn0cTEzJAJk8flymslJiZiNs+SvbtTc+RmG8xi6rSJCpMjlxpncQhHO9fUOIsG9Qhe5v/DyWRyQoYcucYNsXGwoGGjnOtMzm1hH8Ikoz/U1dWZY6TLTN2pufJaycnJWJjZ8s/2XSgpKTNTbxozdKcoTI7c18wfBxsX3rx5S+06tQhe4keFXLpj5+qVUPR1FTdH7tOnz/h4+LNx/RbU1NSYqTcNfSPdXHktsVjM7n/24ebsRfjncIyNjTE3N6dQIcXI+lKIzqWPHz9iZWXFkiVLqFy5Egus5/8y9DanXLl0NTVU8c1b6jWoi52DJY2bNsqT15ZWTuSTSCM5ORlbS0e2bt6BGDEzdacyU2+aXA+vzYl8EmldD72Jvt5cXr54Ra3aNbF1tKRFy2a5/rrZkT6fpErVygQs9v3tfBJpiEQiHG1d2LBuMyKRmMnTJqCnP1OuQxW/zScZN2E05r+ZTyItRcyR+zafJGCRL/Xq18n11/2aI7d6xVqSkhQjRy4n8kmk9ejhY3SnG0hGSdk6WMp9jlxO5JNII32OXGJiYmqO3LzZch3YmTGfRMygoQN+O59EWt/lyNktoMv/5DtHLn0+SekyqfkkeRWOHOi/iED//3Lk5poYZOt2styWE/kk0nr18jWzputz59ZdSpcuhZWdudznyN2+dQdbS0euXA6lRMniePq40r5j2zx57WWLV+Hj5U9crGLkyCUkJLJ6xVr8vANJSkqie6//4enjkmOjbzIjyZG7dpMSJYtjYW1K3/695Xrbun/vAXbWzlw4d5FifxXDzdORrt3y5has1SvX4+nqTYyC5MglJSWxbvVGvD39iY+Lp8v/OuGz0D1Pvtt+na1v6eIVFC1aDDc3N8aMGSP3A13kunMpKSmJ4OBgbGxsEIlSmGOkK7N8jNUr1uLh6ktsbCwDBvXDdIExpctIf99ubsjpfBJphX0IQ3eGAaFXrlPsr2IssJrPgEF95epAmxv5JNLauH4zLg4eREfH0KdfT8wsTeRueO23+SR2TpYMGNQvz+v4/Pkzs2cYEXLxMjo6OphZzmPIsIFydaD9Lp+kTQsCgrOXTyKt7Vv/wd7aWa5z5DLkkxQuhKW1KcNHSZ9PIi1FyJHLjXwSae3dvR+rBfZEfImQ2xy5b/NJ5i8wZtyE0XleR3R0TGqO3PHTcpsj9zWfxNHOjY9hH2nUuAFBS/xlchvR4YNHMDexkuscuZzOJ5FWhhw5NVUM5+kzfqJ85cjlRj6JtE4eP42JkTkf5ThH7uPHT3i5+7FlY2qcxWyDWejO+b3JZHJCfHw8pvMsObD3kNzmyInFYo4dOYGdtROvX72hZq0aBC/1+63JZHLKuTPnmWtgxof3H2jcpBG2jvKXIxceHo6vZ2qchaqaKjNmTUHfSC/P29CJiYlYmNqwa+deVFTkN0fu5PHT2Fk7SS7UBi3xo1r1qnlex6uXr3F18mT/3oO0aNkCfz9/WrZsmed1ZJXcdi4dOnQIIyMj7t27x8jRwzAy0Zf5FZnExETM51myZ/cBVFSUmW0wiynTJsp8Z0ifT1KwYAHGT8rZfBJphVy4hOEcE969fU+DRvWxc7CkYeMGMq0J4NzZC9haOuZaPok0kpOTsTK3Y8e2XQCS4bWyHvWV2/kk0goNvY7+LGNev3pNnbq1sHOypmkz2Q+vDbl4GVtLR+7dvZ8r+STSEIlE2KXlyInkKEfuv3ySZYBSjueTSOvbHDlbB0tatZF9jlzolWvYWDly68ZtypYtg1+gJ02b51w+iTS+zZGbNHU8sw1myTxHLrfzSaR1794DZs8w5EnayE8bBwvad8ibkQiZye18EmmIRCK8PfxYvmQ1SUlJcpMjl9v5JNJKnyP3d8UK2Nhb5NkI/8zcvXMPOyunXMsnkVb6HLlRY4Yzd76BzHPkEhMTWbNqA76e/iQkJNKtR1c8fV1k3g58+fwlM6frc+9Oao6cla0Z3Xp0lfkF44cPHmFv48zZ0+cpWqwoLh4OdO/RVaY1ASwKWsZCnyDi4+MZOmIw8+QgRy4pKYkNazfj5e5HXFwcnTq3xyfAU+btwDdv3qE7bQ43b8hXjtyTJ09xtHXlxLFT6BTRwdHFhj79esm0Jkgd4W9v48LdO/cYN24crq6ulC0rX4MRQA47lx4+fMjcuUbs3buPlq1bYGVrJnf3kr9+/RbdaXO4dfMOpUuXwtLWnJ698354bV7nk0hrxdLVeHn4ERcbx+ChA5hvPlcmw2vzMp9EWu/ffUB3ugHXQq9TvETq8Np+A/J+eG1e55NIa+3qDbg7exETE0u/AX0ws5gnk+G16fNJChXSwtzKhFFjciefRFrykiP3XT5J04YELc69fBJpbd28AwcbF6KjZZsjl5f5JNL6Ev6FObPmcv7cRQprF8ZsgbFMcuS+5pM42Lrw4X1YrueTSCtDjtz/OmFhYyaTHLlv80n05+oyY1bu5JNIKyoyGgO9uZyWcY7c13wSexsX3r55S+26tQhenHv5JNI6sP8wFvNlnyOXl/kk0oqNjcVoznyOHTkh8xy540dPYmftJLmoEbTEL0/iLH7H0X+PYzrPks+fPss0R+5L+Bf8vANZu3oDBQsWZMr0icw10Zf5Rc/04uPjmWdozuGDRyhYsCAGc/WYMHmcTEZ9nT51FjtLJ548Sb2oEbTUP8cmk8kpp0+eZZ6RGWEfZJsjFxkZRYBfMCuWraaASgHGTxqDmcU8udq2UlJS2LppO55ufiQkJLBgwQLmzp0r8wsc6clN51JERASOjo74+flRqlRJzCxN6NWnu8x7LzNz8vhpTOaa8zHsE81bNMXW0ZLadWrlyWvLKp9EWomJicw3tmD/noMUKFCAOYa6TJ46Pk9CFTPkkygpMWJU3uWTSOvCuRCM5szn/fv3NG7SEFtHqzwbXpsxn6Qc/sFeNG4sv9P4Jicns2C+Nbt27kFZWZlZs6czbebkPAlV/JpPEhywBIDBQwfgkEf5JNK6cukqBrPn8eZ13ufIyTKfRBqyzJGT5JP4BpOSkrf5JNK6ef0Ws2cZySRHLmM+SQk8fVzyLJ9EGiKRCCd7N9av2UhKikgyTXNe5Mh9m0/So1c3PHyc5apx+q17d+6hO8NQJjlyGfNJiuLu5UyX/3XKk9eWhkgkwsPFm1VpOXITJo/FwEgvTy48SvJJPPyJj8/bfBJpyTJH7vGjJ9jbOHP65FmKFC2Ck5sdvXp3z5PXloZIJMLfJ5DFwctJTMjbHLnk5GQ2rt+Cp6sPsbFxdOjYFt8AL5nEWWTV82fPmTXNgPv3HlCufFls7C3yLEfu2dPnONq5cuzICbR1tLF3sqL/wL65/rrZEbRwMQF+i/I8R+5rh42bizdRUVG0btOShUHeMomzyKrIiEgW+gWzesU6ypcvh6enF4MHD5aLfhOZdy6lpKSwatUqFixYQFR0FLP0pjF1+iSZ32r2OwL+z95dh0WV/XEcfwMqKAh27666rt25tq7r2t3diRImSEuJiISK3d1rrN0tdneLASrSPfP7Y2R+oIAwxATn9Tw+DzB37nxnPDfm3HM/x3sxvguWER0dTf9BfZgy3ZTChbNmhMfbN/64OLpx6MBRDPIbYGNnQZ/+vbLktbLC29dvZaGK9x5SslRJbOwt+Kf931myMfyQT9KgLouWein99sr0WLZkFd4eC4mKipKHKmbVCA9VySdR1Pv3H5g4xoTbt+5SrHhRrO0s6Ni5fZa0LalUyr49B3Cerfx8EkUlDlXM6hy5gI8BzHWdz64de8ibLy9TppkwauzwLHmtrBAYEIjxODOuX7spy5Gznk7XHp2zpIP6+3yS6jWq4rt8AaVLl8z018oqWzZtw2X23GzJkfv06TMebt5s27IDPT1djE2Uk0+iqC9fvjBpvDl+l2Q5cjOtptK7b48sa1uqkk+iqF079uBg60xoSNbnyAUFBeE5bwEb121BVzcPY5WUT6Ko73PkpltOod+A3lk2olBV8kkUlZ05csFfg/Hx8mXtqg3kzp2LEaOHMm2mudq0rbCwcMwnTePUtxy5qTNMGTikX5aN+jp/7iL21k48e/qccuXKsmipJ5Wz6WJ+Zjhy+LgsR+5LUJbnyIWGhsnjLHR0dBg0tD9WtjPVpm1FREQwzcySo4ePZ0uOnN+lK9hZO/Ho4WN+/bUMCxZ7UqNW9Sx5razw/NkLnB3cOHniNK1atcLLy4tatZQ7IECpnUtnz57F1NSUGzdu0L1nF6ZbTFHpxPjUREREMMVkJsePnkRXT5cp000YMmxgpu1oE/JJlviuQAst+vTrib2TtUqPkEjNyeOnmTFlFp8/f6FR44bYzbaicpXMG16rivkkioqKimL6lFkcPnCU3LlzY2I+keGjhmba8NrE+SQSiYSuPbrgOne22rYt2fBaSwIDAqlXvw72TtZUq555o/qS5pMUZ76PG42bqm6wXmpiYmKYNd2WvXv+y5Icue/zSTp2ac9cD2eVHn2TGlmO3Aw+vP+QJTlyD+4/xN7GmSsqlk+iiLi4OGxmzWbX9n+BzM+RS5JPEhND239UI59EUbIcuSn4v31H1WqVsXeyoX4mHrNUNZ9EERKJBAdbF7Zs2oY0C3Lkfsgn+asFngvclZ5Poqi7d+4zeYI5r16+zpIcuefPX+BoN4fTJ1Urn0QREomEOc7zWLd6Y5bkyMXHx7N18w7mus4nPCyMps2a4OProXJxFmn16NETjMeaynLkypfDzilzc+Rev3qD82w3jh4+jqFhfmxnW9Gzd7dMW392kuXI+bBy2RpiY2MZMmwgplOMM210jEQikU0m4zyP4OAQGjVuwKIlXio9+iY1z5+9YOJYU/kdOpmdI+f/1h9XJ3cO7D+MgYE+VrYz6TewT6atP7udOnEGZwc3Xrx4yZgxY3B0dKRoUeXETSilc+n169fMmDGDrVu3Uqt2DWwcLLNlWuDs8OzpcyaONeHJY9nwWluHWbT6q4XC65NIJOzdvR8XJ3e+fP5C3Xq1WbTUS+XySRQlC1VcQXR0DIOG9Mds2uQMhSp+eP8RNxcP9uzeRz79fEyfac6wkYMzsWLlefXyFRPHmvHwgSxU0dbBkr//+UvhkTlSqZQD+w/h5DCHgI+B1KxVHd/lqpdPoqjFi5ax0GsxUVHR9OnXi2kWZhkatRYYECifHUhPTw/TKcaMnTAqEytWHn//9xiPMeHOnXuUKFEcKzuLDN2WLJVKOXLoGI72c3j/7j1Vq1Vm8TIfyvxaJpMrV47VK9bhMdeLiG85ctMtpmRo1Nrnz1+Y7+7Nlo3b0dXVZcKkMUw2U618EkV9/BDAxHGm3LyeOTlyUqmUkydOM9vW5f/5JMt9KF++bOYWriQb1m3GzdmD8PBwOnftiIX1NEqVUnzU2vf5JGPGj8Bs6mS1uYqdmk+fPjNpvDlX/a5RsGABLKyn06NXxnLkzp4+j4ONaueTKGr71l042rsSFpo5OXIJt2WsXrmOXDq5GDZiMDOtlD+ZTGb4GvSVyROncPF85uXIXTx/GXsbJ548fspvZX9l4RIvqil5MpnMsvff/dhaORISHMJff7fCOoM5cmFh4fguWMqKpavR0tZiwMC+2M6epRFtKzQkDLNJUzlz+jz58uVlmoU5Awb1zdAF3atXrmNv7cj9ew8pU6Y03ioeZ5EeBw8cwWqmHV+DvmZKjlxERARLF61gie8KAHr37Y6Ds63aXlBPLDY2lvVrN+EzfxFaWtrY29tjbGyc7Tly2dq5FBERwdy5c3Fzc8PQMD/TLadk+ERAVR3YfwgrC3uCvwbTslVzbBws0x3Od+vGbexsnLh9845a5JMoKiwsnCkmMzh5/DR6efWYOt2UQUP7p2tjiIqMYuXyNSz0Xkx8vIQu3Tri6u6otiMkUnPsyAlmTrMm6EsQjZs2wm62FRUr/ZGudSTOJylWrCjuKp5PoqioqCimmlpw5PAxdPPkwWzqZIaOGJSudhEdHcOalevw8fQlNjaGdh3/wX2+aueTKOrM6bNMM5vFp8BPCufIPXzwGAdbZy5f9KNw4UK4zXfmrzatsqZgJYqJiWHmVCv+23cInVw6TDabyKjRw9KVI5dwIjDf3YfoqGjatG3FfB/VzidR1KULfpibzODjh4/UrlsLe0draqZz6PnTJ89wtHPl7Bn1yCdRVFxcHLNm2rFn1160tGQ5cmMnpC9HTh3zSRSVJEeuRlUcnGzSnSP34vlLnBzmcPL4abXJJ1FEXFwcDjbObNuyEylSxk0YxXjjMejrp31UVpJ8kpBQmjRtxILFnkqfyS8rJM6Rq1S5Ig5O1uk+D3/z+i0ujnM5fPAo+fMbYGNvSe9+PbOoYuX5f47cFuLj4xXKkZNIJOzeuRdXx7l8/RpM/Yb1WLTUk8KF1SfOIq0e3n+I8ThzXrx4ye8VymPvZE3TZo3TtY53794zx2ke+/ceQF9fn5lWUxk8dEAWVaw8EomEeW6erF6xTuEcOalUyt5//8N5thtfPn+Rx1kUK64ZgzUSk12w9GHrpu1UrPgHnp5etG/fPtteP1s6l6RSKVu2bGHGjBkEBAQwcswwJk4ep7ZDjNNKIpHg5uLB2lUbiIuLY8TooUw2nfDTjeH7fJKp000ZOWZYNlWtPI8fP8V4rKnsnuryZbF3tP5ph4cm5JMoQiKR4OWxkOVLVhEbGysLVZw66afDX7/PJ5lkNoEJxuqTT6KoFy9eMnG0CY8fP6XML6Wxc7Si9V8tUx09IZVKOX70JA62Lrzzf0flyhXxVbN8EkUpkiMXFBSEp/sCNq7/lk8ycTSm5sYqES6Yld6+8WfCGBPu33tAyZIlsHGwTFOOXJJ8koq/47tUvfJJFLVsySq85y8kKjLtOXLqnk+iqPfvPzBxrCm3b92haNEiWNtZ0KlLh5+2LXXPJ1HU2tUbcZ8zn4h05MiFhoaxyHsxK5evRUdHh8FD+zNLjfJJFBUYEIjxeDOuX71JoUIFmWUzI005cuqeT6KorZu24zx7LmFhYXTs3A5L6+mULpP6qK/w8HCWLFrO0sUr0UKLvv174eBso/FtKygoiEnjzLl86QpGRobMtJqWphy569duYG/txN079ylduhTevvM05q6W1OzasYfZts6EpCNHLjIykmWLV7F44TKkUgndenbFxc1BI0bfpCYkOASTiVM5d/YCBvkNmJHGHLnbt+5ib+3EzRu3KF6iGJ4+7pl6a7CqenD/IbPtXLl80Y9OnToyf74nFStm/QyPWd65dO3aNUxNTTh//gL/tG/LLJvpWRa+qKpCgkOYNMGcC+cukd8wPzMsptB3QK8fNoboqGhWrljLQq/FxMXF0alLe9zUOJ9EUfv2/IfNrNmEBIfQuk1LrO0sKJfMLQ8P7j/E3tqJK37XKFK0CPM8XWjRSj3zSRQVGhqO+aSpnD51jnz58jJ1phkDB/f74QATExPDutUb8fJYQHRMDP+0+xsP7zkaOfomNYcPHmXWDFuCgr7SvEVTbBwsk/1C//jRE2bbuXDh3CUKFiqI2zwn/v7nLyVUrDwRERFMNbXg2JET6OrpYj5tMkOG/RiqGBsby8Z1W5jv7kNkZCSt27Rkvs9cjb948L205sg9f/YCRztXTp86i1EBI5zn2NOxc/ZdUVIFUVFRzJhixaEDR8idOxcm5sbJ5sjFx8ezZdN23F3nEx4eTtPmTViwaD75jTIn/0RdnD97kalmMwn4GEjderWxd7Kmeo0fZw999fI1zrPdOHbkBIaG+bFztKZHr65KqFh55Dlye/9DR1sbY5PxyU4SEx8fL8sncfEgJDiEPxs3ZOEST7XNJ1GU3+WrmE2aLsuRq1UDB6fkc+T83/rj4ujOwf8S8kks6DewtxIqVp64uDhsZ81m509y5CQSCXt27cPFyZ2gL0HUq1+HhUu9KFq0iBKqVp4bN25hOmEqb9/6p5oj9/7dB9xcPNj7735ZnIXFFIaNGKSEipVHIpEw29aFzd9y5EaPG5HsIAypVMp/+w7i5DCHwIBP1Kpdg0XLvDUmziKt0pojF/AxQB5nkTdfXsynTmb0uBFKqFh5EgZhuDrO5cOHj5iYmGBjY0OBAgWy7DWzrHPp8ePHuLi4sHbtWipW+gNre4t0D/fTNHdu32PyBHN5ToSDkzWNGjf8fz6JnSvv33/QuHwSRUgkElwd57J+7Wbi4+MZOXoYxqbjMTTM/0M+ycTJY5lkOkHZJSvVw4ePmTTOjOfPXvD77+Wwc7KmWfMm8nwSBxtn3r7xp2LFCviu8KFcubLKLllpJBIJHnO9WbV8DbGxcQwdMQhTc2OMChjxNegrXh4L2bBu87d8kpGYTZ2k8VcaU/P82QsmjDGR50TYzbaS58idPX0eexsnXjyXDetetMxbY/JJFCXLkVtJdHQ0Awf3w3y6CYUKFfx/PsmKdeTKpVn5JIp6/fI1E8aaJpsj930+yaIlXlTVkHwSRS1ZtJwFXr7yHLmpM00pWrTID/kkAwf1xcZBM/JJFJU4R654iWJY21nKc+Su+F3D3tqJB/cfUuaX0vj4zqd2Jgbzq6PEOXI9enVlhuVUipcoptH5JIoK+BjIxLEm3Lxxm8JFCstGfXXvhJaWFjev38LOxok7t+5SslQJvBbOo0HDesouWak2rt/CHKd5P+TIRUVGsWLZahb5LCE+XkLXHp1xcXPIcRfUE/v8+TPG42Q5cgUKGGFpM0MeH3P3zj3srZ24fu0mxYoXxcPLjabNc/b36u1bd+Fk70poaBjtOrRlls0Mfvm1DNHRMaxesRYfT9lkMh06/YObh3OOu6CeWEJ8jO/CZRjoG+Ds7MzIkSOzZPbQLOtcMjAwIFfuXEyZbkL/gX1y9IHoe9s278Bptps8VDEoKFieTzJ3vkumpuGru69BX5k0wZxLF/wwNDKkR6+ubN28g+ioaP5u2xoPHzeNzCdR1J7d+7CzciIkJIQ2bVsTEx3D2TPnKViwAC5zZ9OuQ1tll6gyQkPCMJlozrmzF9DX16dX3x7s2LqLiIhIWrZqhudCD/Lnz1mjb1JzYP9hrC3s+PotR05bR1ueT+LoYkuXbp2UXaLK+D5Hrm//XuzasUeWT9LsTxYu9lTb2YGywrEjJ7CYZs2Xbzly+fPn58ihY7J8EodZ9O7bQ9klqoyoqCimmVly+NBR8uTOQ/9Bfdizax9fvwbToFF9Fi31pFCh1G9hzUm+z5ErVqwo/+0/hL6BPpbW0xk4uJ+yS1QZshw5a/7bdxCdXDoMGNSX/XsP8uXzF+rUrYXvMm+NmUwmM8hy5Kbz8UMAtevU4teyv7B3937y5cvHtJmmDB81VNklqoy4uDisZtrz7649aGlpM2BQXw4fOsrHDwHUqFkd3+XeGZq4QNNcv3YD04nT8Pd/R7UaValcuSK7duxBT0+PyeYTGT9xtLJLVBkSiQQ7K0d5jtyAgX05cfw07/zfUaVqJRYv8+GXHHbHVGo+vP+I+5z57N65l9q1a+Ht7UOLFopPPJacLOtc6tOvJ5bW03PcEOO0iouLw87Kke1bdwFgbDIO0ymTlFyV6rp14w7G40x59+49v/xahlXrlmZotgBNJpFIcLJ3ZeP6LUilMGb8SKbOMM3RV7FTc//uAyaMNeXN6zeULFmCleuXUrly1t+TrI4ScuTWrFyPVCph2IjBWNrMEG0rBU8eP2X86Mm8eP6SokWLsGLtEmrU/PF2JuFbjtz8hSzzXYlEEk+/gX1xcLIWbSsFL168ZNTQ8bx6+ZrixYuxcKlnjsgnUdQinyX4eC5CKoWefbrj5GonLnqm4O0bf0YNG8/TJ08pUqQIPr4eNGqs+fkkilqxdDXuczyRSGSTycyZ55SjR9+k5v37D4wbOYl7d+9TsGAB5i+YS4uWzZRdlspau3ojro5uxMdLaNehLfO8XHP06JvUBAYEMnGsKdev3cTQyJB5nq60adta2WWprBvXbjJrph2hIWH4+/tn6rqzrHPp8Il9/JHDb49Iix5d+vH502fOXDym7FJUnt/lq/TvNYTV65fRsnXOylZSxOB+I3j29DkXr51Wdikq787te3Tr2BsfXw86d+2o7HJU3pgRE7l+7SbXbl9Qdikq78njp7T7qwtOc+zFKIk0MJk4lbOnz3Hj3mVll6Lyrvhdo1/PwazfsirHxw6kRZsWHcibV4/9h3cruxSV9/DhYzr+3Y3lq33FF7Q06PB3N2JiYjh+5qCyS1F5Hz8E0Lh+S3G+lUY9OvclICCQ834nlV2KyouJiaFy+Vq4eTjTRwNnZMxs3vMXsX3LTvz932XqetPTuSQuH2YBHR0djZ9NSVAO0baErCLalpBVtLW1RdsSsoSWllaW5EsIgpaWlhhlKWQJ0bbST5xDqA/RsgVBEARBEARBEARBEASFic4lQRAEQRAEQRAEQRAEQWGic0kQBEEQBEEQBEEQBEFQmOhcEgRBEARBEARBEARBEBQmOpcEQRAEQRAEQRAEQRAEhYnOJUEQBEEQBEEQBEEQBEFhonNJEARBEARBEARBEARBUJjoXBIEQRAEQRAEQRAEQRAUJjqXBEEQBEEQBEEQBEEQBIXlUnYB6REZGcnli1e4e+ced+/c5+6de7zzfw+AibkxZlMnKbnC7LVj225mTJn10+XWbV5Js+ZNfvh7fHw8e3fvZ9fOPdy/+4Dw8HAKFSpE/Ub1GD5yMHXr1cmKsrNERtpGSHAIly9d4e7te9y9K3tuYMAnAObOd6F33x4pPvfSBT8G9h2W5jpNp0zCdIpxmpdXZX6Xr7J+zUauXbnBly9fyJ8/P5WrVqJPv1507d5J2eVli/JlqqR52T8bN2TT9rXJPhYY+Illi1dy4tgp3vm/R09Pjz8qVaBX7270HdAbLS2tzCo5y2VkW7x80Y+zZy5w5/ZdXr96Q1DQVyLCIzAyMuSPihX4p/3f9B/YB728esk+PzAgEL/LV+Wve+/Ofb5+DQZg07a1/NmkYea/4SwUFBTEsSMnuXDuEvfu3sf/7Tvi4+MoVKgQNWpVp2fvbrTr0DZd61y8cDnuc+bLf3/+9kFml610Z8+cZ+umHdy8cYtPnz6jhRbFihelTt3aDBjUh0aNf2wHGT2eqpqsOF+ysrBn84atAJQuU4qzl47/9DmBAYGsX7uJUyfO8Oa1P1FRURQuUogKFX6nUeOGjB43nNy5c6e7lux29849jh89xd0793jx/CVfPn8hLCwcAwN9fq9QnlZ/tWDQkP4UKFggxXUcO3KCLZu2c/vWXYK/BlOgoBG1atdk4OB+tPqrRfa9mQzKjLaV0WPeq5evWbZ4JWfPnCcgIBADfX2q1ahK/4F96dDpn0x5n5kls7ZFRbaljJzfqqKM7KePHz0p/yzevXvPl89fiI6OoWChAlSpUpmOXdrTo1dXcuVSn6/GyvruA+p3vqXM7TCBphwDfkZ9tiDg1o07jBw6TtllqBxtbW0KFS6U4uN58uT54W/h4eGMHz2Z82cvAqCjo4OBgQEBAYHs33OAA/sOMcNyCmMnjMqyujNTRtrGkcPH03SwSk7uPLkpUrRIqstERkQQHh4BQM1a1RV6HVXj5uLBUt8V8t8NjQwJCQnl/NmLnD97kQP7D7FwiadaHaQV8bP/+7jYWPnBNqX/+zu37zF80GiCgr4CoK+fj/DwcK76XeOq3zUO/neEZasXJbsdq6KMbIvLlqzi5PHT8t/z5ctHnjx5+Pz5C58v+nHpoh+rV65j9YZllC9f7ofnb1y/FR/PRQrXrmoa1WlBXFyc/HddXV1y5crNhw8f+fDhI0cPH6dl6+b4LvMmb968P13f82cvNOrz+Z5UKsXa0kHeAQKgpyfriHzz+i1vXr9l77/7GTlmGNZ2FsmuQ5HjqSrK7POli+cvs2XjtnQ9Z//eA8yaaUdYaBgga7+58+Tmnf973vm/58zpcwwa0o/cRqrfubR9yy7Wr90k/11XVxc9PV2+fg3m2tUbXLt6g9Ur1rFs9aIfLszFx8czzcySPbv3AaClpYWhoSFfPgdx7MgJjh05wbARg7FztMrW96SojLatjB7zTh4/zaTx5kRGRgJgkN+Ar1+DOXv6PGdPn6d3v564zXNSmYsymbEtKrotZeT8VpUpsp92nzOfx4+eyn83MNBHW1ubgI+BBHwM5PSps6xfs5GV65ZS9CfndqpCWd99QP3Ot5S5HWraMeBn1O6bn5GREdVqVKF69apUq1EVJ4c58p7WnKpkqRJpuoKYmOUMW86fvYi2tjZTZpgydPggDAz0Cf4azOJFy1m2eCVznOdR/vdy/P3PX1lUeebKSNsoWqwIVatVoXqNqlSvUY0JY0zS9Lx69evgd+NsqsuMHj6BE8dOUbJkCVq0apam9aqyTRu2yjuWOnfriKXVdEqWKkF0dAz79x7AzsqRI4eOMcd5Xopf4DTFz/7vVyxdjYvjXAD6Duj9w+MhIaGMHj6eoKCv/F6hPB7ebtSsVZ2YmBi2bNqOs4MbZ06fw9HeFUcXuyx5D1lB0W2xafPGtGjZjPoN6/Jb2d8wMNAHZCN49u7+DzcXD968fsuE0ZM5eGwv2tpJ7+zW0tKiZKmS37bjqhQrVhTLGbZZ8h6zQ1xcHLVq16RX3+60aNmMX3/7BYC3b/xZ6L2YbVt2cvrkWaxm2jHfZ26q65JIJMycakV0dDR169Xm+rWb2fAOsteObbvlHUsdOrVj2kwzypUvC8g61txcPDh6+Dirlq+lQcN6yY76UuR4qqoy63wpMjKSWTNsyZUrF5WrVuLOrbs/fc6B/YcwmzQdiUTCgEF9GT5qCH9UrABAWFg49+894MihY+TKrR6nobXq1KDML9Op36Auv1coj6GRISC7UHf44FFcHd35/PkL40ZN5viZgxga5pc/12Out/xLxfBRQ5hsNoGCBQsSERHBpvVbmes6n7WrN/Bb2V8ZPmqIUt5feinatjJ6zHvz+i2TJ0whMjKSeg3q4ubhRPny5QgPD2fZ4lUs8PJlx9Zd/P57OcZNHJ0Vb10hGdkWM7otKXp+q8oU2U+379iO4SOHUK9BXX75pYx8BPTHDwFs3bwdH09f7t65z3QzS9ZsXJ4VZWcJZXz3AfU831LWdqiJx4DUqMdR/ZsGjepx496lJH+b6zo/haWFlDx88Jj9ew4AMGzkYCZOGit/zKiAERZW03jn/479ew/iPNuNv/5u9cOXOFWTkbbRo1fXLBsa/PFDAKdPyjogevXtjo6OTpa8TnaJi4vDy2MhANVrVMVrgbu8bejq5qFXn+5ERUVhY+nAutUbGTp8kPwLcU60bctOAOo3rEf5338cabNi6SoCAz6hp6fHqnVL+eXXMoDsqtvQ4YMICwtn3hxPtmzczojRQ5MdraNqMrItjhyd/C2mBQsWZNjIweTJkwcrCzuePH7G9Ws3qd+gbpLlJpmOT3Lb6ds3/umsXrVs3LqGxk0b/fD3Mr+UZs48J3Ry5WLzhq38u2sf0yzMKVWqZIrrWrtqA9eu3qBbjy78VvZXjexc2r1jDwC/lf0V70XzkoycLP97ORYu8aRtq068fvWG//YfSvctheokM8+X5rl58erVa4xNxvHh/cefdi4FfAzAaqY9EomEWbYzGT12eJLHDQz0adioPg0b1VeoHmXo2bt7sn/X19enZ+/uFC1alGGDRvP502dOHDtF955dAPjyJYhVK2S3Q//Trg22Dv8fKZAvXz5GjxvB589fWOq7Aq/5C+nVtwf58xtk+fvJiIy0rYwe8zzn+RAREUHRYkVYuWaxvJNPX18f82mT+RT4ic0bt7FowVL6D+yDUQGjTHjHGZORzyuj21JWnt+qm5Rueypeohgm5sZER8eweOEyzpw+x/t3HyhZqkQ2V5h+yvzuo27nW8raDjXxGPAzqt1j8B11/2KuKk6d+P9tJ2PHJ3/bW8LtcK9evuaq37VsqSsjMtI2srJd7di+m/j4eLS0tOjb/8eRK+rm7u17fAqU9fKPGjsi2U7H/gP7YGhkSFxcHP/u2pvdJaqMa1dv8PTJMwD6JTNqCWDXty/Dnbt1lJ9kJzZsxCD09fMRHx/Pnl37s67YTJSV21PturXkP394/yFbX1sZkutYSqxv/17yn1P7wv/m9Vs85npTsGABrO01dzRhQEAgAFWqVk72ltzcuXNTpWplACK+3aqsqTJrW7hx7SZrV22gXPmyTDKZkKbnrFm1geDgYKpVr8KoMWnPJFRnKe2bLpy7SEx0DABjUogZGPft7yHBIRw9fCwLq8wcGWlbGTnmRUREcOjAUQAGDekv71hKbMK3i6VhoWEcOawaIxAz8nlldFvStGNiVqqTaBv++OGjEitJO2V+91G3tqWs7VATjwE/o1adS0Lm8Pd/B0B+w/wUL1Es2WV+r1Befr/62TPns602TSKVStmxZRcATZr9SZlfSiu5ooxLaDsAf1T8PdlldHR0KFeuLABnz1zIjrJU0rbNOwDZdtaxc7sfHn/+7IU8TLBV6+bJrkNfX5/6DesBcE5sh1zxuyr/+dffflViJapBV1dX/nN8vCTF5Sxn2BAREYGV3UwKp5JToe4Svqw+uP8wSVZVgtjYWB7cfwhAjZqakX+XlaKjY5g5zRqpVIqLmwO6ero/fxL/H0HWrWdXlcm9yWop7Zv83yY6Zv6R/DGzQMECFC5SGICzpzX3mJnRY95Vv+tERUUB0LJ18uG3ZX4pTYVvn7MmnLvmxG1JWa5cll1I19LS4pccPOJe+FFGtsOceAxQq9vihOR9+RxE1w69eP7sJfHx8RQrXpS69erQb0DvVNP6pZKUv4xIJBKkUikAjx4+yfSac4JLF/x49eo1kPLIFXWW2pfZeEk8AI8f5cy2Ex4ezoH9hwDo0q1jsmHLiberipX+SHFdlSr9wemTZ3nybRRUThMVGcX79x848N9hFnj5AtCwUX2NCcfPiMsX/eQ/V65SMdlltmzcxoVzl2javHGKt/ZoisFDB3D65FlevXyNqfE0pluYU7bcb4Dsi+1cFw9ev3rDb7/9ysgUrj4qejzVRAu8fHn65Bn9BvROdoa95Lx5/ZaPHwMAqFGjKg8fPGbxwmVcuniZ4K/BFCpUiHoN6jBs5JAfbmtVN9HRMQQGBHLi2Ck85y0AZLdktmnbOtnlE46LyZHEyx579PBx5heqIjJ6zEt8PlEpledXrPQHT58840mi8GZ1lJO2pfTKrP10eHg4b9/4s3vHHlYsWw3IbhfT5IswQvpk5naYU44BonNJA0RGRnL3zn2MjIyIi4uVz4qzZ/c+evfriYubQ5JbBMqUkY2gCQsLx/+tP6XL/Dii5nGik4CEjUpIn4S8nYIFC/BP+7+VXE3mKJOorTx+9IQaNav9sExMTAwvX7wCIDQklIiICPLly5dtNaqC/XsOyGcI7DegT7LLBCTaroqXKJ7iuhIeCwsNIzw8HH19/UysVDUFBgTSqG7yV6bbtG2N+3yXbK5I9YQEh7B40TJAliWQXKbXh/cfcXWeh56eHs5zHLK7xGzXpm1rrO0tmOviwcH/DnPwv8Py2eKioqIwNDJk0ND+TJ1ummKmQXqPp5rq3t37LFu8kiJFi2BpPT3Nz3vx/KX856tXb7DAcxExMbHo6emRR1eXDx8+8t++QxzYfxizqZOYbDYxC6rPWpV/ryW/zSGxeg3q4rXQHV3d/89UlXjE8uOHT5LtpAsMCJTPnBagwedbGT3mJZyLGhkZycOYk39+sR9eTx3lhG1JURnZT9+4dpNe3Qb88HcdHR169u6Gg5NNVpcvqJGMboc58RggbotTY8WLy0Lo/jvyLw+e3eLGvUvce3KD7f9uomnzxgDs2LoLJ/s5SZ6XeDjxQu8lya570YKl8p8TplwU0i4kOIRDB44A0K1nF7WZvvpnqtWoSpFvU7Qu9V2R7K0n61ZvTNJmcmL72frtlrgqVSsn2wEHEBYeLv85byonyokfCw8LT3E5TaKto0ORokUoUrRIklu/OnZuj4XVNAoULKC84lSARCJhiulMAj4Goquri71j8ifDVhZ2hIaEYjrFOMcE648cPQzf5T7yIeZRUVHyW2liY2KJCI8gNJl9kqLHU00UFxfHzKnWxMXFYTd7VrLZNikJDg6W/+zp7kOx4sVYt3kldx9f4/aDKxw+sY8/GzdEKpXiOW+B/DipTop+2zclvmjSuEkjbOwtKV26VJJlGzf9kzzfOpsSn1cltsgn0flWmOYeLzN6zEv4ObXnyh6XjRQOD1fv42VO2JbSKzP207nz5JafX+TJ8/8p4wcM7ovJFONUOy6FnCej22FOPAaIziU11rxlU8ymTqJK1UryK2U6OjrUq1+HtRtX0LZdGwA2rNucpOe1cpWKdOzcHpB9CXZymMPbN/7Exsby/PkLZky14sSxU+TOLdvpqvpMcaro3937iI6OBjTrlrhcuXIx2UwW6vr0yTNGD5vA3Tv3iImR3R6wbPFK3Od4ytsOgFYOaz+PHz3h5o3bgGb932enwoUL4XfjLH43znL/6Q3O+53E2GQcx4+epGPb7mzesE3ZJSrVbFsXThw7BYCDsw1Vqlb6YZl/d+7l5PHTVK1WhVHfzWyiqSIjI5k8wZzRwyZQqnRJ1m5awdXbF7h6+wJrN62gQsXf2b1zLz069+XB/UdJnqvo8VQTLVm0nPv3HvDX363o1KVDup4rkUjlP0ulUnyXedOseRP5ecQfFSuwfI0vRYvJLlL4ePpmXuHZ5Oyl4/jdOMvdx9fwu3mOWTYzuH/vIT0698XT3SfJsoUKFWT4iMEAnDtzAfPJM3j29DmxsbH4+7/DzcWD9Ws3yY+ZWlo563gppCwnbEvplRn76eo1qiU6v7jJibOHGDJsIJvWb6X9X104duREdr0dQQ1kdDvMiccA9X8HQrK0tbXlQ9klEgnHv30RSTBnnhONm/4JwKrla2nR+G8qlavJ3y06smPrLtq2a0Prv2QjnIzScdVSkNn+7Za42nVqUqly8lko6mrIsIGMGTcSgDOnz9G1Q28ql69Fo7otmOM8j9JlSjF2wkj58jmt/SSMWtLV1ZVPR50cg0S3t0VGRqW4XOLH9A00/5a472lpaVGyVAmmzjDDc8FcYmNjsZnlIA9mzmlcHOeybs1GAKztLZLMGJcgMPATjvau6Ojo4DJ3do64jQvA1cmd//Ydovzv5di2cwPNWzSlUKGCFCpUkOYtmrJ1x3rKlS/Lly9B2Fk7pnm9PzueapInj5+y0Hsx+vr5mO1im+7nGyTaRzVp9ifVa/w4clNfX58hwwYC8PDBIwK/zUCqjooUKczocSNYs2EZWlpaLPBezPFjJ5MsM83CnM7dOgKwZ/c+2rbqRKVyNWneqA1LfVdQu05N+vTvCYBRAc09Xmb0mJfwc2rPlT0eKVtezW8hz2nbUkYpsp/W1tambLnfcHC2wcJ6OuHhEZhPnq4RtyYJmSMztsOcdgwQnUsarGy53yhUqCAAb169SfKYgYE+6zevxGvhPNq2a0PZcr9R5pfSNG3emHlerixZsYCvX2VDAcuVL5vdpau1u3fuce/uA0BzR65Y2kxn2+6N9Orbg4qVKlCyVElq1a7J1Bmm7D+8C21t2ZSfpcuU0phbAtMiJiaGPbv2AdC+4z+p3k5SrPj/Z2pMbdrbhMcM8huo/clyRrXv+A+lSpdEIpGwbfNOZZeT7eY4ubNiqSx0dJbNDEaOTj6Ueq7rfIKCvtJ/UB9+r1CO8PDwJP9iY2Plyyb8LSbmxwwZdRIWFs6WjdsBWQd4cjOb6eXVY+jwQQBc9bvGp0+f07z+1I6nmsTOypGYmFgmTh6PkZHhD20nLk4WOiqVSpNtT4lnoK1QIfmZcQD5jF4A7xLNpqOuatWpKQ9zTWiHCXLlyoXPIg9Wrl1C564d+L1CeUqXKUWDRvWwm23Flp3rifrWYZIw06omyugxr/i35wcHB8s/r+SfH/DD66mjnLotZURG9tNDhg4gj24ewsMj2LvnQFaUJ6ihzNgOc9oxIGdczhSSpa2tTdfunejavdMPj8XFxfHggey2gbr16mR3aWotIchbXz+fvKdaE9VvUDfFmRHu3L4L5Ly2c+zICb58CQJ+3rFYqfL/Z7t5/OhJkgNTYo++zZCT0hSmOU2JEsV55/+ely9fKbuUbOXq6M7ypasAsLCaxuhxI1Jc9u3rtwBsXLeFjeu2pLreGpXqAzB81BBsHWZlUrXZ78Xzl/IMuNTypRJmjwPZ51TkWzaTIPPmjaztuM+Zj/uc+Sku987/vbztWNtbyDs6//ijAjo6OsTHpzwrDoBUmugXDZliPSGI+tXL18k+3rpNS1q3aZnsY/JjZn3NPWZm9JiXeIa5R4+eUKt2jWSfnzCr3B+VKmSoXmXLyduSMujq6VKggBEBHwN5lcPOL4SUZeZ2mFOOAWLkkgZ79fK1/IvuL7+WSddzjx89SWhIKHp6enTs3C4rytNIUZFR7P33P0AWPpwTR5oEBn7iwrmLAPTs3U3J1WSvhFvifiv7K40aN0h12XLly1KqdEkATp88m+wyERERXPW7BkCzFk0zsVL1JJVK5V9+DXLQLYIujnOTdCyNnTBKyRWpHm3t/5/M+funfPU+8Wil9NxmmpHjaU6iq6dLw0ayTqenT5+luNzTJ7Jp4rW0tJLMpqPO3ryWjZRI73H/3t37PHks+6w0+ZiZ0WNe/YZ15bM/njmV/PP93/rz9Inss2yu5sfMnLwtKSoj++mwsHC+fJY9NyeeuwvJy47tUNOOAaJzSU1Jk3SRJv+4q5M7IBuh9NffrdK87s+fv8ifO2TYQIwKGClcZ05z6MARQoJDAOg3UDNviUtNfHw8Nhb2xMTEUqt2TVq0aqbskrKNv/87zp+Vdar16d8LrZ9cQdTS0pIfRPbvPcjbN/4/LLN+zSbCwyPQ0dGhW8/OmV+0Cklu5sHvbd+6i8AA2b3syU3nqolcHOcmuRUuLR1Lm3es4/nbByn+MzE3li+b8Dd1HrUE8Pvv5eVfPLdt3pFse4qPj2fLRlkYvJGREeV/Lwdk7fFU3Zy9dDzVttOrT3dAdstzwt++vz2zd98eAFw4d4m7d+798Brh4eFsWLcZkOUSFi5cKGvfVAbFx8f/tI2cP3eRWzfvAPz0wkJikZGR2Fg6ANChUzt+r1Be8UJVXEaPefny5aN9x7YAbFy/hZCQ0B+ev8R3BSC7+PDPt3BndaZp21JGZGQ/nZbzi+WLV8qX+zOHnF8IaZOV26EmHgPUrnMp+GswX74Eyf8lpLhHRUYm+bu6T0H6M/5v39G9U182bdjK61dv5DtdiUTCjWs3GTF4LEcOHQNk02smnEQnOHH8FKtXrOPVy9fyoX6RkZEc2H+I3l0H8PrVG6pUrYz5tMnZ+8YyICNtI/HjCVc9ACLCI5L8PSEoMiUJI1cqVqqgsbeEvX71hnluXty9c4/oKNmMeBKJhKtXrjN04GiOHD6OoZEh7p4uP+1g0STbt+xCIpGQK1cuen/7AvYzo8eNpGixIkRGRjJq2Dju3JYdtGJiYtiwbjOe82QzD/Uf1Ify5cultiqVosi2eNXvOv16DWb3jj28f/chyfpePH+Jm4sH1hb2APz226/07tPjh9eVSCRJ1p94CtnQ0NAkj0VHq37GUOKMJSu7maneCpfT6eXVk9+KevfOfcYMn8jDB4+RSCRIJBIe3H/EyKHjuHb1BgAjRg9BR0eWDZfR46mqUtb5UreeXahVuyZSqZSJY005f+4iEokEkM0yOnaEMYEBn9DW1mbqTLNMfe2s8P7dBzq36/lD+wB49+49ixcuZ9zISUilUgoUMGLUmKSdbTev32LRgqU8efxUnm0WExPD6ZNn6dtjEDdv3KZkqZI4ONtk6/vKCEXbVkaPeebTTMiXLx8BHwMZM2KCfEawiIgIfDwXsWn9VgCMTcar1IVRRT+vzNiWMuv8Vtkysp/es3s/Y0ZM5NCBI0lGryYcG2bNsGWB92IA6jWoS8vWzbPxnWWMsr77qOP5lrK2Q008BqRG7TKXOrfviX8ygXXLlqxi2ZJV8t979emOu6drdpaW7W7fusPtW7IrZXl082Cgr09YeDgxiTbi3v16Yjfb6ofnvnzxCif7OfIZhQwMDAgNDZVvLA0b1WfJigXo5dXLnjeTCTLSNurXbJLsOu1tnLC3cZL/bmJujNnUScku+/LFK/wuXwVkI1c0VVhYGL4LluK7YCkgGwEQEREhD3UtVbokS1YsSDFPQRNJJBJ2bNsFQKu/WqQ5SNTQMD8r1ixh+KDRPHn8jG4de2NgoE90dIz882zesinWdpZZVntWUHRbvHL5Glcuy26J0NXVRV8/HxERkURF/T+8tUrVyixduTDZfdM7//e0aPx3sjWNG5V0u50730V+NUoV+fu/k39W2traLPVdyVLflSkuP2bcCMaMH5ni4znBzFlTefniFadPnZX/y/NtuurEx8Uu3TphbDI+yXMzcjxVVco6X9LW1mbZqoUM7j+CJ4+fMaT/SPLmzUuu3LkI/TbaJHfu3Dg4WdPk26y1qu7B/Yfyzu08eXJjYGBAVFQ0ERER8mV++bUMvsu8KVqsaJLnBgQE4uHmhYebF1paWhgZGRIaGia/sFex0h+sWLNYrfK/FG1bGT3m/fJrGRYsns+k8eZcuXyNNi06kN8wPxHhEfLPs3e/nip367Cin1dmbEuZcX6rKhTdT0ulUo4fPcnxo7KZHPPly4eeni5hYWHExPx/QoLGTf9k0RJPtbowqqzvPup4vqWs7VATjwGpUbvOJUGmSJHC2Dtac/3aTR7cf8CXz0EEB4egq5uHX34pQ916tenTv1eKgcvNmjdh2IjBXL1yjffvPhAWFkaRooWpWasG3Xp0pmPn9mq1c1UF27fuQiqVkidPbnr0Uv97ZlNSpkxpJptN5PJFP169fE1QUBAGBvqUr1Cedh3aMmhIP/LmzavsMrPV+bMXeef/Hkj/DIE1albj0Il9LPVdwYljp3j/7gN58+WlVqWa9OrdjT79e6GtrXaDTNOtes1qzPd249JFP+7cvkdg4Ce+Bn0lT548/Pbbr1SrUZX2HdvSoVM7+YgTTSaV/H90hEQi4dNPppgOD49I9fGcQC+vHqvWL+Xgf0fYs3sfd2/f4/Pnz6Cl9W1Gyxr07teDv9q0SvK8jB5PhR8VLVaUvQd3sX7NRvbvPciLFy+JjoqizC+ladykESPHDKNS5YrKLjNNihUvysIlXly+6MfNm7cJ+BBAUFAQ2to6lCpdkipVK/P3P3/RrXvnZDu9q9esxtjxI/G7fJW3b98R/DWYAgULULlKRTp1bk/vfj3JlSvnnI5n9JjXuk1LDhz9l6W+Kzh39gIBAYEYGRlStXoVBgzqR4dO/2Tju8l6mrQtZURG9tOt27TEde5sLl28woP7D/gU+Jng4BD09HT55ddfqFmrOp27dkwxbFkQMrId5rRjgJb0ZzexAiEhIRgZGXH4xD7+qKjesy9kh97dBxIYEMjpC0eVXYrK87t8lf69hrB6/TK1GoaqLMMGjubJ46dcuHpK2aWovDu379GtY298fD3o3FVzZ+3LLONHT+bqletcvXVe2aWovCePn9Lury44zbFn4OB+yi5H5ZlNms6ZU2e5fveSsktReVf8rtGv52DWb1lF02aNlV2Oyvu7ZUf09fOx58AOZZei8h4+fEzHv7uxfLUvbdq2VnY5Kq9j2+7ExsZy9NR/yi5F5X38EEDj+i3F+VYa9ezSj8DAT5y9dFzZpai8mJgYKpevpTKjn1Sd9/xFbN+yM9WJTRSR0BcUHByMoaFhqstq/uVwQRAEQRAEQRAEQRAEIcuIziVBEARBEARBEARBEARBYaJzSRAEQRAEQRAEQRAEQVCY6FwSBEEQBEEQBEEQBEEQFCY6lwRBEARBEARBEARBEASFic4lQRAEQRAEQRAEQRAEQWGic0kQBEEQBEEQBEEQBEFQmOhcEgRBEARBEARBEARBEBQmOpcEQRAEQRAEQRAEQRAEhYnOJUEQBEEQBEEQBEEQBEFhonNJEARBEARBEARBEARBUJjoXBIEQRAEQRAEQRAEQRAUlq7OpVcvX2dVHRrjzas3PHn8lM+fPvM16Kuyy1F5Rw8dB+Di+ctKrkT1vX//gXt37xMU9JVPnz4ruxyVd/SwrG1dvuin5EpUX2BAIDdv3CY0NJSPHwKUXY7KO3bkBAB+l64quRLV9+XLF65euUZYWDhv3/gruxyVd/7cRQCOHDqm5EpUX0hwCAEfA3nx/BWvXr5Sdjkq7/zZ/7ctiUSi5GpUW1hoGO/fveed/zuePnmm7HJU3tkz5wHZeZdoW6mLiIjgzeu3BAZ84sG9B8ouR+WdOXUOEG0rLeLi4nj9Svl9NenqXBo70hiLadYEBn7KqnrUVlRUFKbGU2nTsiMxMTFER8fwZ72WODnMERtDMi6cv8Sf9Vqycvka8ufPz7IlK2nVpC13bt1VdmkqJyYmhmnmlrRs3JawsHDiJfE0bdAaG0sH0baScdXvGk0btmah92Ly58/PxvVbadaoDdev3VB2aSonLi4Oqxm2NGvUhqAvQWihRYvGf2MxzZq4uDhll6dybt24Q4vGf+M+x5P8+fOz99/9NK7fkksXRAfm9yQSCQ42TjSp34qAj4Ho6GjzV/P2mE+eQUxMjLLLUzn37z6gdbN2+MxfRP78+Vm/ZhON6jTnzOlzyi5N5UgkElwd59KwTnMiIiKIi4ujbatOTBpvTlRUlLLLUzmPHz+lbatOODvMIX9+A7Zv3UXDOs05ceyUsktTORKJhPnu3jSo3YzQ0DBAiw5/d2PsSGPCwsKVXZ7KefHiJR3adGXGlFnkz2/Avj0HqF+zCQf2H1Z2aSppkc8S6tdsypcvQeTOnYuuHfswYshYQkPClF2aynn7xp8u7XsybtQk8uc34Ojh49St3pg9u/cpuzSVdOH8Jbp26M2/u/bRrVt3pdaSrs6lefPmcezISdo078CyxSuJjhYniAArlq6hXs0m7NtzgG49OnP6/BGOnNxP0+aNWbV8LXVrNGbvv/uVXaZK+PghgJ5d+jGk/0ikUinei+Zx7c4FXNwcCA4JpUeXfgwdOIqQ4BBll6oS1q/dRL0ajdm1/V86dGrHiXOHOH76IH/93YqN67dQp9qf7Ni2W9llqoRPnz7Tr+dg+vceSkx0DB5ec7h+9yJz57sQFRlJ3x6yx758+aLsUlXCts07qFu9MZs3befvf1pz/MxBjp89yD8d/mbblp3Uqf4nmzZsVXaZKuFr0FcG9RtOr279CQsLx9XdkWt3LuC5wJ34eAmD+4+gd/eBBAYEKrtUlbB7517qVv+Ttas30rxlM46c3M+p80fp0q0je3bvo271P1m9Yp2yy1QJoSFhjBg8hm6dehP0JYjZLrZcu3OBhUu80Mmlw4jBY+nesQ/+/u+VXapKOLD/MPVrNmH50tU0btKIIyf3c/riUXr07s7B/w5Tr0YTlviuUHaZKiEsLJwxIybSqW13Pnz4iK3DLK7evsDSlQvR09OTPdauB29evVF2qSrh2JETNKzdjIXeS6hbvzb/HdnN2cvH6T+wD8ePnqRh7Wb4ePoqu0yVEBUVhfE4M/5p3Zk3b95iaT2dK7fOs3LtEowKGDFpvBnt/urC82cvlF2qSjhz+iwN6zTHY643NWpWY9+hnZy7fIIhwwdy9vR5GtZphvscT3HBGNkFdfPJ0/mreXuePn3O1Jlm+N04x9pNKyhSpDDmk2fwd8uOPHz4WNmlqoTXr94wfvRkBvcbQaGChfDz88PXV7n7KS2pVCr92UIhISEYGRkRHBxMXFwc9vb2+Pr68suvZbCynclff7dCS0srO+pVKZcu+GFuMp2PHwKoVacm9o7W1KpdI8kyZ0+fx97GiRfPX1L+93L4LvehYsUKSqpYeeLi4rC2sGf3zr1oaWkxYdJYxk4YSd68eeXLhASHsMB7MatXriOXTi6GjhiEhdU0tLVzXjTY9Ws3MDWehv/bd1SrXgV7Jxvq1a+TZJmL5y9jb+PEk8dP+a3sryxa4kXV6lWUVLHySCQS7Kwc2bZlJ1KkjJswivHGY9DX15cvExYWju+CpaxYuhotbS0GDuqLjcOsHNm27ty+x+TxZrx+/ZZKlSvi4GRNwz8bJFnmit817K2deHD/IWXKlGbBYk9q1amRwho1l0QiwcVxLhvWbiY+Pp5RY4ZhbDqB/PkN5MtERESwdNEK+RfaXn26M9vFlly5cimrbKV5+PAxxmNNefH8Jb//Xg47J2uaNW+SZJmb129hZ+PEnVt3KVGyBN6L5tGgYT0lVaw8EomEeW6erF6xjtjYOIaOGISpuTFGBYzky0RFRrFi2WoW+SwhPl5C1+6dcJk7mzx58iixcuV49vQ5E8aa8PTxM34r+yt2s61o9VeLJMvcvXMPe2snrl+7SbHiRfHwcqNp88ZKqli5vOcvZKnvCqKjYxg0pD9m0yZTqFBB+ePR0TGsXrEWH09f4uLiaN/xH+bOd0ZPT0+JVSvHq5evmDjWjIcPHlGqdCnsZs+iTdvWSb7XPLj/iNm2zly+dIXCRQoz18OZ1m1aKrFq5Vm8aBkLvZYQFRVFn369mDrTlKJFi8gfj4mJYf3aTXjOW0B0VDRt2rZmvo8b+fLlU2LVyuHv/56JYyZz9859ipcohrWdJR06/ZOkbT15/JTZdi6cP3uRggUL4DJ3Nu06tFVi1cqzavla5rt7ExERSc/e3ZhuMYXiJYrJH4+Li2PT+q3Mc/MiMjKSlq2a4bXIAwMD/VTWqpnCwsJZvHAZK5etoVixYsydO5f+/ftnWX9M4r4gQ0PDVJdNd+dSwgrv3buHmZkZx44do3nLpljbWfBHDuk0CQwIZMJYU25ev0WhwoWwsp1J1+6dUvwPjY2NlW0Mc72Iioyi1V8t8FzgnmM2hk0btuLq5E54WDidunbAwmoapUuXSnH5589e4Gg/h9Mnz2BUwAgnVzs6demQjRUrz5cvX5g41oyrftcoUMAIC+vp9OzdLcVOkLi4OLZu3oG763zCwyNo2qwxPr4eGBqlvuFrih3bduNo50poaCjtOrRlls0Mfvm1TIrLv3r5GufZbhw7cgJDw/zYOVrTo1fXbKxYeUKCQ5g0wZwL5y6RP78BM2dNpU//Xujo6CS7fHx8PDu3/8sc53mEBIfQqHEDFi3xokDBAtlbuJLs/Xc/tlaOhASH0LpNS6ztLChXvmyKy/u/9cfVyZ0D+w9jYKCPle1M+g3sk30FK1FoSBhmk6Zy5vR58uXLy9SZZgwc3C/FDjaJRMKeXftwcZxLUNBX6tavje8yH4oUKZzNlSvH4YNHmTXDlqCgrzRr3gQbB8tUz5/ev/uAm4sHe//dj75+PqZbTmHo8EHZWLHyREREMMVkJsePnkRXT5cp000YMmwguXPnTnZ5qVTKf/sO4uQwh8CAT9SqXYPFyxck+YKiyU4eP82MKbP4/PkLjf5sgJ2jNZWrVExx+YCPAcxz82LHtt3kzZcXs6mTGDNuZDZWrDxRUVFMN5/F4YNHyJUrN6ZTjBk+aii6usl33kqlUg4fPIqT/Rzev/9A1WpVWLzchzK/lM7mypXj/NmLTDGdSWBAIHXr1cbeyZrqNaqluPynT5+Z7+7N1k070NXVxdhkHMYm47OxYuWJiYlh1nRb9u75Dx0dbYxNxjN67Aj08ibfeSuVSjlx/BQONs68feNPpcoVWbzch7LlfsvmypXD7/JVzCZN48P7j9SoVZ3ZTjbUqlMzxeWDgoLw9ljEhnWbyZ0nN2PGj8RsyqQcccFYIpGwe+de3F3nExISyowZM5gxY0aSC+pZIVs6l0C2Mezbt48pU6bw8uVLBg8dgOkUY4398hEXF4ftrNns3P4vAOMnjmac8eg098Z/+RKE17wFbFy/BV3dPIydMAoTc2ON3Rhu3bjD5AnmvH3rT5WqlbF3sk7XFepTJ87gYOvMq5evqfDH7/gu86bCH79nYcXKI5FIcLRzYfPGbUgkUkaPG8HEyePS3AEZ/DUYHy9f1q7aQO7cuRg+aijTLcw1tm3dv/sA4/FmvHr5mj8qVsDe0ZrGTRul+fnnzl7AwdqJZ89eUK5cWRYt9aRy1cpZWLHySCQS5jjPY93qjcTFxTFi9FAmm05IcwdkaGgYi7wXs3L5WnR0dBg0tD9WtjM1tm09fvyUiWNMeP7sBeXKl8Xe0ZrmLZum+fl+l65gZ+3Eo4eP+eXXMixc7EmNWtWzsGLlkUgkeHksYPmS1cTGxjJk2MB0nQOEh4ezZNFyli5eiRZa9OnfCwcn6xQ7PNXdixcvmTjahEePnvDLr2Wwc7Si9V8t03yl8fq1G9hbO3H3zn1KlS6Jj68HdevV+fkT1dRC78X4LlhGdHQ0/Qf1Ycp0UwoXLpSm50ZGRrJs8SoWL1yGVCqhW8+uuLg5aOyIwrev3zJ+rAkP7j2kZMkS2DhY8k/7v9Pctm7dvIO9jRO3btymePFieC5w588mDbO4auVZtmQV3h4LiYqKolffHkyfaUbRYkXT9NzoqGhWrljLAi9f4uPi6dSlPW4ezho7ovD9+w9MHGPC7Vt3KVqsCDb2lnTs3D7Nbev+vQc42Dhzxe8aRYoWYZ6XCy1aNs/iqpVn7eqNuM+ZT0R4BN16dGHmrKmUKFk8Tc+NiYlh7aoNeM9fSHRMDP+0+5t5Xq5J7vLQJIEBgUwcZ8qNa7coVKggs2xm0LVH5zSfXz56+BgHWxcuXbhMoUIFmTPPib//+SuLq1aeG9duMtvOhVs379CvXz/c3Nz47bfs6YDMts6lBNHR0fj4+ODo6IhOLh3Mp01mwKC+GnUQ37ppO86z3QgLC6dj53ZYWk+ndBnFrlY8fPAYB1tnLl/0o3DhQrh5OPPX360yt2Al+hr0FePxZly+eAVDI0MsrKbRq093hb4wxMbGsn7tJua7+xAdFc1ff7fCc8FcjRpeu3vnXhxsnAgJCeXvf/7CynYmv5X9VaF1PX3yjNm2Lpw7e4ECBQvg4uZA+47/ZHLFyhMSHILJxKmcP3dRfgW/34DeCu1r4uLi2LxxG/PmeBIREUmLlk3xWuhBfkODnz9ZTfy37xDWlvYEfw2mZesW2NhbUP73cgqt68XzlzjPduPEsVMYGhky29mGrt07Z3LFyhMWFo755OmcOnEGvbx6TJthxsAh/VIcIZGa+Ph4tm/ZiZvrfEJDQmnctBELfOdr1IWXY0dOYDHNmi9fgmjS7E9sHWZRsdIfCq3rzeu3uDjO5fDBo+TPb4C1vSV9+vXM5IqVJyIigmlmlhw9chzdPHkwmzqZoSMGKfRlNOGqpavjXL5+DaZ+g7osWuad5k4XdXDm9FmmmVnyKfAzDRrWw97JmioKdv6/e/eeOU7z2L/3APr6+bC0mcHAwf0yuWLliYmJYcZUKw7sO4ROLh1MzIwZOXoounq66V6XVCpl77//4eLoxqfAz9SuWwvfpd4aNerr0gU/zCdP5+PHAGrXrYW9ozU1Fez8//ghgLmuHuzeuZd8+fIyZbopI8cMy+SKlScuLg7LGbbs3b0PLS1tJk4ey5jxIxXq6JBKpRz87whODq58/BBA9RpV8V2+gNKlS2ZB5cpx7cp1TI2n8e7de6rXqIq9k7XCnf+BgZ/wcPNm+9ad6OnpMtlsIuONx2RyxcoTFxeHvbUT27fuQopUNlhj4miFRt9IpVKOHTnBbDtX3vm/o3KVSixZ7sMvv/2SBZUrx4f3H5nr6sG/u/ZRp05tvL19aN48eztos71zKcGHDx+YNWsWa9asoWKlP7C2t6BpM/W+3/3OrbtMnmCeaj6JIqRSKUcPH2e2nSvv372nSrXKLF7qrdYbQ1rySRT1+fMXPN192LxxG7q6ukycPJZJphMyoWrleXj/IcbjzHnxIuV8EkVIpVJOnjjNbFsXXr96Q8VKf7B4hQ/lypXNeNFK8n0+ybCRgzExm5gkn0RRX4O+4j1/EevXbiJ37tyMHjcC82mT1XpkTlrySRSliTlyP8snUVRISCgLvRezasVajcmRe/XyFRPGmPLo4eMU80kUdemCH3bWjhqVIyfLJ1lMVFQ0fQf0ZuoM00y5/e/7HLkBg/piq+Y5conzSUqUKI61vSXtO7bNlLaVOEeudJnSLFg8n9qp3HahDlYtX4uHuzeRKeSTKCoiIoKlvitZsmg5oBk5ch8/BDBxrAk3b9ymSNHCWNla0KVbx0xpW7du3MbW2lGjcuQ2rNuMm7MH4eHhdOnWiZlWUylVKuMdQT/kyHXrhIu7eufIffr0GeNxZly7cp0CBYyYZTuD7j27Zsq+OEmOXLGieHirf47c9q27cLJ3JTQ0jPYd22JpnXqcRVpFR8ewZuU6vOcv0pgcuYTtZfGi5RjoG+Di4sKIESOUMrpbaZ1LCa5du4apqQnnz1/gn3Z/Y2kzXeGRGMryNegrkydO4eL5y+Q3zM9Myymp5pMoKjoqmlUr1uHjtYj4uHg6dG6H+3wXtdvRpjefRFEP7j/EwcYZv8tXKVKkMO6errRsrV7Da7/PJ5lmYZ4lI/1iYmJYt2YTXvN8iI6Joe0/bZjn5ap2o74OHTjCrJl2fP2WT2I7e1aW3B75+NETZtu5cOHcJQoWKoiruyP/tGuT6a+TlSIiIpgyeQbHj51KUz6Jon7IkWvdHM+F89QuR+7EsVPMnGolyydp3BC72Vap5pMoKkmOnJEhTnPs1S5HLnE+Se7ceTCdYsywkUNSzCdRVHx8PFs372Cuiwfh4RE0afYnC3znq12OXOJ8knr162DvZE216lUz/XVev3qD82w3jh4+jqFhfmxnW9Gzd7dMf52sFBMTg+V0G/btOYCOjjaTTCcwaszwFPNJFCWRSNixbbc8R67hn/VZuMSTQoXUa9SX36UrmE2ezof3H6lZuwYOjtap5pMoShNy5OLi4rCxdGDXjj0A8slkMvs8SCKRsHf3fpwd5xL0JYg69WSjvtJ6q52quHHjFiYTpuD/9h1Vq1XG3smG+g3qZvrrfHj/ETcXD/bs3kc+/XxMt5jCsBHqlSMnkUhwsHFmy+btSCVSxowfyYRJYzP9PEgqlXJg/yEc7V0JDPhEzVrV8V3uQ8mSJTL1dbLa3Tv3mTzejFffLno7OFnTqHHm33obGBCI+xxPtc6RSxjpN8fJnY8fAzA1NcXa2hojo4xfUFeU0juXQPbBbN26lenTpxMQEMDIMcPSlSGjLEnySeLjGDEqffkkigr4GID7HE92bv+XvPnyYj7VhNHjhmfpa2aGjOaTKEIqlXLowFGc7F358OEj1apXxXeZt8qHKmY0n0RRnz59xmOuN9s2y0IVJ5lNYOKksVn6mpnhxYuXTBhtwmMF80kUIZVKOX70JLPtXPB/++5bqKI3v5VV/VDFjOSTKCooKAiveQvZsG4zefLkYdxE9ciRe/PqDRPGmcrySUqVxNbBkrbt2mT5rKenT57FwdaZly9eqVWO3LLFK/Gev0ihfBJFJc6Ry5U7FyNGDmG65RSVb1uJ80mKFS+KtZ1FuvJJFHX+3EXsrZ149vQ5Zcv9hu9SL7XIkVu7aj3uc7yIiIige8+uzLCckuZ8EkWpa47cD/kk3yaTyeq6/S5dwd7GmYcPHqlVjtzmjVtxcfw2mUyX9rLJZBSMs0irH3Lk+vXE3sla5Ud9ffnyBeNx5ly5fBUjI0MsrKfTq0/3LG9bSXLkSpXEe9E86mVBZ1Zm27VjDw62zoSGhNK2XRusbGfyaxbfeRIZGcnyJavwXfAtR65HF1zmzlb5thUSHMLkiVM4f/YiBvkNmGk5lb4DMn+wxvdu37qLvY0TN6/fUqscufv3HuBoP4fLF/3o3LkTHh7zqVgx8y96ppdKdC4liIiIYO7cubi5uWFomJ9pFuapzn6lTP/tO4i1pUOm5JMo6tbNO9hZO3L75h2KlyiO90L3TLkNL7NlZj6JoqKjolmxfA0LvRcTHxdPl64dcJ3npJKjvo4ePo7FdBuCMiGfRFH37t7HwcaZq1euU7RYEeZ5zsnyjkBF/JBPMs2EocMHZuv/a3R0DGtXrcd7/iJiY2P4p31b5nm5quTw2sT5JA0b1cfO0UrhfBJFqUuOXGbmkygqNjaWDWs34+HurfI5chfPX2aKyYxMySdR1LOnz5lt58LZ0+cpUKAAznMd6KCCOXKZmU+SkRoS58g1b9EE70XzVTJHLkk+Sc1qODhaU6de7WytQV1y5DIzn0RR8fHx7Ni6izkuHrIcuSaNWLBYNXPk7ty6y6QJ5rx5/ZbKVSph72RNw0b1s7WGN6/f4uo0l0MHVDtHTiKR4GTvyqYNW5FIpIwaO5yJk8dlSpxFempInCNXr0FdFi31UsnZQx/ef8jEcWayC0QVymPvbEOTpn9maw1Jc+T0mWk1lcFDB2RrDWkhkUhwd53P6lXriYuNY/ioIZiYTczWUchSqZR9ew7gPHuOyufIff78hflzvdm6eQcVK/6Bp6cX7du3V3ZZcirVuZTg9evXzJw5ky1btlCzVnVsZ89SmVlOnj55xsSxpjx9kvn5JIqQSqXs2b0fF8e5fPn8hdp1a7F4mWoMr5VIJPh4LmLZ4pVER8cweOgAzKZNomDBjOeTKEoWdDaff3ftJV++fEy3MGPYyCFKqyexxPkkpcuUwtYh8/JJFCEbankYR3tXAj4GUqNmdRavUJ3htb4Ll7HIO/PzSRQVGBCIu5sXO7ftRk9PD9MpxoydMEpp9ST29u07Jo414V4W5JMo4vscucpVK7FkmeqEKq5YugZPDx8iIyLp1ac70y3MKVZceScY3+fIjTceg4n5RKXVk1jSfJIiWNvNpHPXzMknUdTJ46dxsHWW58j5LvPO9os/KcmqfBJFfQ36io+nL+vWbCR37tyMGjuMKdNNVeKiXuJ8koIFC2BpMz3T8kkUdfbMeRysnXn+/IXK5cht27wDJwc3wsJk+SSzbGYqdZR2Qo7c6hXr0NHRYciwgVjaTFeJtvU16CuTJphz6YIfhkaGzJw1ld59eyh19snvc+QWLPakeo3Mvz1WEXt278POyomQkBDatG2Nle1MypZT3ijtsLBwFi9cxvIlq9DS1qL/wL7YzVaNHLnQkDBMjadw9sx59PX1mWZhTv+BfZQ6aujqlevYWzty/95DSpcphc/i+dSpU0tp9SR28L8jWM205evXYFq0bIaNgyW/VyivtHq+z5Hr2bsbjq52KjHqKyYmhvVrN7HA0xdtbR0cHByYMGFCtg7WSAuV7FxKcPbsWUxNTblx4wbdenRhhuUUSpZSzhfbiIgIzCfP4EQW55MoKiIigqWLVrDEdwUAvft2x8FZeaGK2ZVPoqib129ha+3I3dv3KFmqBD6LPJQ2vDYqKopp5pYcOXg0S/NJFBUVGcXypavwXbBUFqrYozMubg5KG/V19vR5pplbEBjwifoN6mLnaJUl+SSKunP7HvbWjtz4NrzWw8ct269WJYiJicFymjX79h5EJ5cOk0zGZ0k+iaKio2NYvWItPp6+xMXF0aFzO+Z6OKOrm32jgxL7IZ/EyYZatWsopZbkPLj/CAcbJ5XIkYuLi8Pa0oHdifJJxk0cpTLTICfJkYuO4e9//sLDe47SRn1dv3YDU+NpWZ5Poqgnj58y286F82cvKj1HTiKRYG/jzNZN25EiZez4UUyYNCZbR9+kJi4uTpYj5+ZFZGSk0nPk7t65z6TxZvLO1KzKJ1HU8+cvcLafw8kTZzAqYISjiy2du3ZUSi0SiQRXR3fWr91EfHw8I0cPw9h0PIaG+ZVSz/fi4+PZtnknbq4ehIWG0bR5Y6XmyD18+BjjsaaySTnKl8POyYrmLVRnFHviHLn8hvmxU2KOnEQiwWOuN6uWryU2NpahwwdhYj5RZUbsSSQSdm7/lzlO7gQHh9CwUX0WLlVejtzzZy+YMMZE3plq6zCL1m1aKqWW5Pi/9WeO8zz+23cIfQN9rGxn0H9gX6XVc+rEGZwd3Hjx4iVjx47F0dGRIkWKKK2e1Kh05xLIdrRr1qxh1qxZhIaFMn7iaMaMG5mtX44WePmyeOFyoqOjGTCoL+bTTVR2Kt+3b/xxdZrLwf+OYJDfAGvbmfQd0DvbXv/NqzdMGGvCg/uPsjWfRBESiYQ9u/bh4jiXoKCv1Ktfh0XLvLN19Isy8kkU9f7dB9xcPNj773709fMxY9ZUhgwbmH2v//4DE0abcOe2LJ/Ext6SDp3aqWTbkkql7N97ACcHNz4FfqJW7RosXr4gW4fXKiOfRFHKzpELDAhk4lhTbly/RaHChZhlM4NuPTqrbNs6fPAojnbKy5FLkk/StYMsn6R0qWx7/fT49Okz89292brpW46c6XgmTh6Xba+fNJ/ECAvradmST6IIqVTKieOncLBxxv/tOypW+oMlK3yyNUcucT7JP+3/ZpbNjCzPJ1FUQo7cxvVbyJ07N2MmjMRsyqRs+78NCQ5h0gRzLpy7RP78BszIpnwSRSXJkatQHt/lPtmaI7d/7wFsLB0IzuLJZDJDSHAIPl6+rFm5Xik5cmFh4ZgZT+X0qXPkzZuXaTNlcRaqMHojORfOX8LeypGnSsqRO3zwKLNm2hH0JYimzRtj6zCLP1RkROP3QkPD8F2wlJXL1qCtrcXAwf2wtrfMtrYVERHBVFMLjh05ga6eLubTJjNkWPbGWaSH3+Wr2Fs7KS1H7tnT5zg7uHHq5Blat26Nl5cXNWuq9uylKt+5lHi9Tk5OeHl5Ubx4MSysp2X5F8vTJ88y3dyST5+Ul0+iKL9LV7CzduLRw8f8+msZFizxokbNaln2ejExMUyfMouD+w+TK1cuTMwnMmL0MJUZfZOa70MV+/bvhYOzTZbuaC+cv8RUk5l8/BhAnbq1sHeyydL/n8x07eoN7K0duXf3AaXLlMJ70bwsvW01JiaGWTPt2Lt7P9ra2hibjMv2DmZFRUZGsmzxKhYvXIZUKqVHr644zbHP0hO0a1euY2I8lffvPigtn0RRt27ewd7GiVs3blO8RDG8Frhn6RX4uLg47Kwc2bFtN4Asn8R4tEpmGn0vOiqalSvWssDLl/i4eDp16YCbR9bmyN26cYfJE815+8ZfafkkikqSI1e0CPO8sjZHTiKR4GjvymYl5pMoKjo6hnWrN+DlsTDbcuTu332A8XgzXr18TYU/fsfeyVppIz7T69HDxzjYunDpwmUKFS7E3CzOkZNIJLi5eLBu9QZilZRPoqjY2Fg2rtuCx1xvoqKiaN2mJfN95mbpqK+nT54xYYwJz54+p1z5stjNtqJFq2ZZ9nqZ6dnT5zjauXLm9LlsyZGTTSazkOVLVxEbE8vgoQMwnWqs1DiLtIqLi2PLpu24u87Pthy5ly9fySeTKV2mFHaOVvzVppVKXpj63ssXr3Ce7cbxoycxNDTEwdmabj26ZOlrLvJZwiKfpURHR9NvYG+mTFdunEVaJeTIubnOJyQ4hD+bNGThYs8sHZWW0MG8bvVGypQpjYfHfHr06KEWbUttOpcSPHnyhKlTp7Bv334aNKqPrYNlpt8S8/aNPxPHmnLvrmrkkygqPj6e7Vt24uY6n9CQUJo0+5OFiz0z/QRE1fJJFPXm9VtcHOdy+OBR8ufPj42DJb379sjU1/j4IYAJY0y4dVN18kkUIZFI2LVjD3Oc3Pn6NZj6Devhu8wr04fXrl+7ST7NuCrkkyjK3/+dbHjt3oPoG+hjaT2dgYP7ZeprfPr0GeOxply7ekNl8kkUIZVK2fvvfzjPdsvSHLltm3fgNNuNsNAwOnT6B0vrGSo/i2RyPn4IYK6rB7t37iVfvrxMnWHGiNFDM/U1vgZ9ZdJ4cy5dVJ18EkX8kCNXoxqLlvtQunTm7lN279yLg40TISGhKpFPoqjAwE/Mc/Nix9Zd6OnpMdl8IuMnjs7U1wgNCcNkojnnzl5QmXwSRUilUo4dOYGDrUuW5sgd2H8Yaws7vn4NpmWr5ljbWyg1n0RRX74E4enuw6YNW7MsRy4sLJwpJjM4efw0enn1mDrdlEFD+6tMnEV6nDx+mtl2Lrx6+Zo/KlZg8XKfTM+RO370JDOnWfHlcxCNmzbC1mEWlSqrTpxFWn2fIzdyzDCmzsjcHLmoqCimmlpw5PAxdPPkwXTKJIaNHKyyo29S832O3MKlXlTO5P932WQys/gU+IkGDeth52hF1WpVMvU1skNISCiLvJewasXaLMuRS7g1NmEiFysrK8zNzVVykqCUqF3nUoLDhw9jbm7Ow4cP6TegN1MyIcw3JiaGmVOt+W/ft3wS0wmMHjM8W2cHygohwSEs+BaqmCtXLoaOGISF1bQMbwx+l65gOmkaHz8EUKtOTewdrVUqn0RRF89fxt7GSX4f8KIlXlStnrGdYFxcHNYW9uzeuRctLS0mTBrL2AnZOztQVggLC8d3wVJWLF2NtrYWAwb1xcYh46GKifNJqlWvgr2TDfXqq0aof0Zc8buGvbUTD+4/pEyZ0ixY7EmtOhnbZiQSCfbWTmzdvEMl80kU9X2OXK8+3ZntkvEcubt37jNpnCmvX7+lUuWKODhZq+Qsm+l18/ot7GycuHPrLiVLlcBr4TwaNKyXoXVKJBJcHOeyYe1m4uPjGTVmGMamE9Ri9E1qoiKjWLFsNYt8lmRqjlySfJLfy2HvZE2z5k0yqWrluXvnHvbWTly/dpNixYsy39uNJs0aZ2idEokEDzcvVq1YJ8snGTEIU3NjjAoYZVLVyvF9jlz7jv8wd75zhr8YPH/2gvFjJvP08TOVzCdR1IP7j5ht68zlS1cyNUfOe/5ClvquIDo6hkFD+mM2bTKFCqn+6JvUJIT5es5bQHRUdKblyL159YbxY0x4+OARpUqXwm62cieTySzf58i5uDnQrkPbDK93ie8KFnj6EhUVRZ9+PZk604yiRVUz+yatvs+Ra9mqGV6LPDI8otDf/z0Tx5hw9849ipcohrWdJR06/aP2bSurcuQuXfDD0d6VB/cfMnToUFxdXSlVSjUjB1Kjtp1LIBteu2TJEmxtbYmPj2ey+USFpyFfvWIdHnO9iIiIVPl8EkU9f/YCR/s5nD4p2xic59jTsXP6py4MDAhkwlhTbn7LJ7GynUnX7p3UfmeRWFxcHFs378DddT7h4eE0bdYEH18PhUZ9bdqwFVcn9cgnUdSrl69xnu3GsSMnMDTMj52jNT16dU33er58+cLEsWZc9btGgQJGWFhPp2fvbmo3+iY18fHxslBF53mEBIfQqHEDFi3xUmh47Y5tu3G0cyU0VPXzSRTl/9YfVyd3Duw/jIGBPla2FvQbmP4cue/zSWbOmkqf/qqbT6KI73Pk6tavje8yH4UuvOzfewBrSwdC1CCfRFGZlSMXGhKG2aSpnDl9XpZPYmHGwMGqm0+iCKlUyn/7DuLkMIfAgIzlyB0+eJRZM2wJCvpKs+ZNsHGwVNl8EkUFfAyQjfratpu8+fJiNnUSY8aNTPd6IiIimGIyk+NHT6pFPokivs+Rq1qtCouX+yg0kvTk8dPMmGrF50+fafRnA+wcrVVqMpnM8H2OnLHJOIxNxqd7PVFRUUyfMovDB46SK1cuTKcYM3zUULWIs0irzMyRO3/2IlNMZxIYEEjderWxd7Kmeg31iLNIq6CgILw9FrFh3WZy58nNmPGK5cjFxMQwa7ote/f8h46ONsYm4xk9doRaxFmkR+Icud8rlGexgjlysrxkdw7+d5iGjRri4+1Do0aNsqDi7KHWnUsJPn36hK2tLUuXLqVs2d+wspuZ5is6V/2uYzrp//kks51sqF1XNaZnzCqnTpzBwdZZlm1Q8XcWL/NJ07BqWT7JbHZs+xdQr3wSRQV/DcbHy5e1qzaQO3cuRoweyrSZ5mna0SbOJ6lStTJ2jlZqk0+iqHNnL+Bg7cSzZy8oV64si5Z6pilUUSKR4GjnwuaN25BIpIweN4KJk8cpbfad7BAaGsYi78WsXC4bXjt42ABm2cxIU9v6Pp/EwcmGxk3V90CUFormyEkkEtycPVi7egNxcXGMGD2UyaYT1CKfRFEZyZF78vgpE8eaqmU+iaIS58iVKl0SH1+PNOXIyfJJFrB8yWpiY9Urn0RRGcmRe/HiJRNHm/Do0RN++bUMdo5WtP6rpUZdmPre9zlynj7u/NkkbTlyC72X4LtAlk/Sf1Afpkw3VdnJZDJDRnLk3r7xZ8KYydy/95CSJUtg42DJP+3/1ui2df/eAxxsnLnid40iRYswz8uVFi3Ttq9evnQVXh4LiYqMksdZqOpkMpkhJiaGtasUy5F7//4DE8eYcPvWXYoWK4K1nQWdunTQ6LaVkRy5tas34j5nPhHhEXTr0YWZs6Zq3GCNxOQ5cu7eREWmL0cu4VxtxdI1FC5cmDlz5jBo0CC1v6CuEZ1LCe7cuYOZmRknTpygZavmWNnNTLEH8ft8klk2M+jWs4va/4emVWxsLOvXbmK+uw/RUdG0aduK+T5zU+woSppP0o5ZNtMpXUb98kkU9fTJM2bbunDu7AUKFiyAy9zZKQ6v/Rr0FePxZly+eAVDI0MsrGSzA2nSCInUxMXFsXnjNubN8SQiIpIWLZvitdAjxVDFxPkkf//zF1a2M/mt7K/ZXLXyvHj+EieHOZw8fhpDI0NmO9vQtXvnZJf9Pp9kuuUU+g3orVEjJFLzQ45c00YsWOyZ4q00SfJJWrfAxt4i03MqVFl6cuTCwsIxnzydUyfOoJdXj2kzZLMDqWM+iSIkEgm7d+7F1XFumnLkjh05gcU0a758keWT2M22omKlP7K5auVJT45cREQE08wsOXrkOLp58mA2dTJDRwzSqNE3qfkhR65OTXyX+VCsePJf5jUln0RR6cmRi4mJYcZUKw7sO4ROLh1MzIwZOXqo2sdZpJUsR+4ITg6ufPwQ8NMcuUsX/DCfPJ2PHwOoXbcW9o7W1MzGma+ULT05cnFxccyaYcue3fvQ0tJm4uSxjBmv/nEWaZWQIzfb1oV3795TuUollixPOUfu+rUbmEycyjv/91SvURV7J+ssnexH1STNkcvD+IljMJlinOyyEomEvbv34+Y6n69BX5k2bRoWFhYYGKh35EACjepcAtnGsGfPHqZMMefNm7cMGT4QE7OJ8i8fEokEOytHtm3ZqVH5JIr6/PkLnu4+bN64DV1dXSZOHssk0wnyxzU1n0QRUqmUkydOM9vWhdev3lCp0h/4rvChXLmygObmkyjqa9BXvOcvYv3aTbJpmsePwGzqZHkH7sP7DzEeZ86LFy/5/fdy2GlIPomizp4+j72NkzyvxXe5DxW/3SoikUiY5+bJ6hXriI2N05h8EkWFhISy0Hsxq1asJZfOjzly3+eT2M22otVfLZRctfJcuuCHnbVjijlymphPoqjEOXJa2loM/C5H7tXLV0wcY8rDh481Kp9EUT/LkVu8aBkLvRYTFRVNn369mDrTVO3zSRQVERHBUt+VLFm0HPgxR06WTzKZu3fua1Q+iaKS5MiVLIHXoqQ5cquWr2W+uzcREZH07N2N6RZTFLpNUxP8LEfu44cAJo415eaNWxQpWhgrWwu6dFO/yWQyy/c5ch5ebjRt/v8cuQ3rNuPmPI/w8Ag6d+2IhfU0tZxMJjNER8ewZuU6vOcvSjZH7tOnzxiPM+PalesUKGCEpc0MevRSv8lkMkviHLnCRQrjPt8lyfnnrRu3mW3nyo3rN+nVqxfu7u6UK6dZFz01rnMpQVRUFF5eXjg5OZFHNw9TppuQJ3dunBzcCA0NpV2HtsyymcEvv5ZRWo2q5MH9hzjYOON3+SpFihTG3tmaLRu3y/JJDPMz03KKxuWTKComJoZ1azbhNc+H6JgY2v7ThjZtW+No76rR+SSKevzoCbPtXLhw7hIFCxXEfrYV/+7ay5nT58mXLy/TLMwZMKhvjhl9k5rY2FhZqOJcL6Iio2j1Vws6d+3AbFsXeT6J7exZCt3TrYmS5sgZYuMwiyMHj8nzSaZMN2HIsIE5ZvRNauLj49m6eYd89sWmzRrTp39P7K2d+Pz5C40aN8RutpXG5ZMo6vscuVk2Mzh75gKHDx4hd+48mE4xZtjIIRqVT6IoiUTCjm27/58j92cDhgwfhJ21I4EBgdSrXwd7J+tMn9lXXX2fIzdj1lRuXrslzyeZZDqBUWOGa1w+iSISrvA7O84l6EsQdevVZsz4kdhZO/Hh/Qdq1qqBg5M1terUVHapKuHD+4+4uXiwZ/c+9PXzMXWGGY8ePWHX9n8B5JPJaHKcRVp9nyNXs3YNJpmMw/5bPlPVapWxd7KhfoO6yi5VJQQGBOI+x1OeI2dibsw7//ds2bQNqUTKmPEjmTBprEbHWaSVVCrlyKFjONq58v79B6pWq4yjqx0b121h5/Z/qVmzBt7ePrRq1UrZpWYJje1cSvDu3TtmzZrF2rVrAfijYgXsHa01Pp9EEVKplEMHjuJkLwtVBBg1djiTTCdgaJhfydWpnk+fPuMx15ttm3egpaXFb2V/xd7RmuYtmyq7NJUjlUo5fvQks+1c8H/7DoChwwdhOsVYoSBrTRcUFITXvIVsWLcZLS0tSpcplSPySRSVOFQRYODgfphPN9HofBJFJc6RAyhRsgS2Dpa0bddGtK1knD93EXtr2YhCqVRKr749mD7TTKPzSRSVkCO3YtkapFIpxYoXxdrOgo6d24u2lQy/S1ewt3Hm0aPHSCXSHJFPoqiEbJIli1YgkUiSTCaTU0dIpOb6tRvYWztx7+4DpFIpnbq0l00mk4PiLNIqIUdukc8S4iXxFDCSTSbTq0930baScfvWXXmOnFQqpW27NljZztS4yWQyQ+IcudiYWIyMjHB1dWX06NEaPVhD4zuXEowcOZL9/+3nvN8JMULiJ6KjoqlSoTZdunXEe5GHsstRefPdvVnqu5K7j6+JERI/ER0dQ83K9WjRshnL1yxWdjkqb9GCpXjN8+Hekxs5Jp9EUbGxsdSp/ie169Riw5ZVyi5H5a1asRZnhzncf3Izx+STKCouLo7qFesxfORgLKynK7sclTfd3JKd2//l5n0/cWHqJ+Lj46lRqT59+vXEwdlG2eWoPHtrJ9at2cjl62dEB+9PSCQSalZuQKcu7XHzcFZ2OSpvrut8lixazqnzR0RHyU9IpVJqVWlIqzYt8BHfE3/q5PHTjBo2nuvXr1OnjubnUKWnL0itu29LlSqFbp48omMpDRK+aOTOJTpK0kL3233HomPp53R186ClpU0u8VmliZ6eLqAlOpbSIHfu3Ojo6JA7l+ZeDcpMCXkJomPp53LlygVa/9/XC6lLOBbqibb1Uzo6OmhpaaVp1irh/21LbIs/p62tjba2aFtplSeP2G+llZaWFtra2qJtpVHC52RklDNzUlOj1p1LgiAIgiAIgiAIgiAIgnKJziVBEARBEARBEARBEARBYaJzSRAEQRAEQRAEQRAEQVCY6FwSBEEQBEEQBEEQBEEQFCY6lwRBEARBEARBEARBEASFic4lQRAEQRAEQRAEQRAEQWGic0kQBEEQBEEQBEEQBEFQmOhcEgRBEARBEARBEARBEBQmOpcEQRAEQRAEQRAEQRAEheVSdgGqIDIykssXr3D3zj3u3rnP3Tv3eOf/HgATc2PMpk5K8bkhwSFcvnSFu7fvcfeu7LmBAZ8AmDvfhd59eyhU04jBYzl96iwAjf5swOYd6xRaj7pYvHA57nPmy39//vaBEqtRjtDQMDau28yxIyd4+eIVYWFhFCpUiLLlfqPhnw0YOXoohkaGP12Pun6WGdkOP7z/yNEjx7l0wY/7dx/w4cNHAIoWK0LturXoP7APTZr+me6arCzs2bxhKwCly5Ti7KXjCrwz5VD083z7xp8Wjf9O8+v06tsD9/kumVKzspQvUyXNy/7ZuCGbtq9N9rED+w+za8e/3L1zj6AvX8mVKxclShanYaP6DBk+kKrV0v46ypSRbfHyRT/OnrnAndt3ef3qDUFBX4kIj8DIyJA/Klbgn/Z/039gH/Ty6qW4jvj4ePbu3s+unXu4f/cB4eHhFCpUiPqN6jF85GDq1quT6e85K929c4/jR09x9849Xjx/yZfPXwgLC8fAQJ/fK5Sn1V8tGDSkPwUKFvjhuVm1b1N1fpevsn7NRq5ducGXL1/Inz8/latWok+/XnTt3inZ52RG21M1GdkWvTwW4uO56KevceLsIcqW+y1N9cTGxtK1Q28ePXwMQK8+3XH3dE3Tc1VRWs6XMuv4oGoy0rYSBAZ+YtnilZw4dop3/u/R09Pjj0oV6NW7G30H9EZLS+uH51y64MfAvsPSXKfplEmYTjFO+xvLApnxWQEEBgSyfu0mTp04w5vX/kRFRVG4SCEqVPidRo0bMnrccHLnzi1fXlPPx3Zs282MKbN+uty6zStp1ryJ/Hd1bDs5kehcAm7duMPIoeMUeu6Rw8fTtIGkx45tu+UdSznB82cv0nQCpMkunr+M6aRpfAqUdUzmyZMbvbx5+fDhIx8+fOTSRT/+ad+Gqj/pXFLnz1LR7fDdu/c0b9QGqVQq/1vevHmRSqW8fePP2zf+7N9zgD79euIydzY6OjppWu/F85fZsnFbuutRFYp+nto62hQpWiTVZaKjowkNCQWgZq3qCtWnSn72fuNiY/n6NRhI/v1GR8cwabwZx4+elP9NXz8fsbGxvHj+khfPX7J96y4sbaYzaszwTK09K2TkmLhsySpOHj8t/z1fvnzkyZOHz5+/8PmiH5cu+rF65TpWb1hG+fLlfnh+eHg440dP5vzZiwDo6OhgYGBAQEAg+/cc4MC+Q8ywnMLYCaMUe3NKsH3LLtav3ST/XVdXFz09Xb5+Deba1Rtcu3qD1SvWsWz1oiQdZ1m1b1N1bi4eLPVdIf/d0MiQkJBQzp+9yPmzFzmw/xALl3iSK1fSU9iMtj1VlJFtMUHu3LkxKmCU4uPff46pWeSzVN6xpO7Ser6U0eODqspo27pz+x7DB40mKOgrIDvmhYeHc9XvGlf9rnHwvyMsW72IPHnyJHle7jy5f/qZRkZEEB4eAajGZ5oZ2+H+vQeYNdOOsNAwQHYcyJ0nN+/83/PO/z1nTp9j0JB+5Db6f+eSpp+PaWtrU6hwoRQf14S2kxOJzqVvjIyMqFajCtWrV6Vajao4OcyRj0D6maLFilC1WhWq16hK9RrVmDDGROE6AgMCcXZww9DIkGLFivL0yTOF16UOJBIJM6daER0dTd16tbl+7aayS8p2V69cZ9Sw8URFRdGuQ1smTBpLjZrV0NLSIjIyksePnnLsyHHy58+f6no04bNUZDuUxEuQSqU0afYnPXt3o2mzJhQvUQyJRMKzp8+Z5+bF0cPH2b51F8VLFGPKdNOf1hEZGcmsGbbkypWLylUrcefW3cx6i9lKkc+zVKmS+N1IvXPb3tqJdWs2oqenR7funTOzZKX42ftdsXQ1Lo5zAeg7oPcPj/suWCrvWBo8bAATJ42jRMniSCQS7t19gKO9K1f9ruEyey4NGzWgRs1qmf8mMpmix8SmzRvTomUz6jesy29lf8PAQB+AoKAg9u7+DzcXD968fsuE0ZM5eGwv2tpJ7863nGHL+bMX0dbWZsoMU4YOH4SBgT7BX4NZvGg5yxavZI7zPMr/Xo6///krS957ZqtVpwZlfplO/QZ1+b1CefkI1PDwcA4fPIqrozufP39h3KjJHD9zEEND2b4+K/Ztqm7Thq3yjqXO3TpiaTWdkqVKEB0dw/69B7CzcuTIoWPMcZ6HtZ1FkudmtO2pqoycnwLUrVc7U0a/P3zwmMULl/Hrb78QEREpvximjtJzvpTR44MqU7RthYSEMnr4eIKCvvJ7hfJ4eLtRs1Z1YmJi2LJpO84Obpw5fQ5He1ccXeySPLde/To//UxHD5/AiWOnKFmyBC1aNcvQe8wsGdkOD+w/hNmk6UgkEgYM6svwUUP4o2IFAMLCwrl/7wFHDh0jV+6kX8s1/XysZKkS6bojQF3bTk4jOpeABo3qcePepSR/m+s6P4Wlk+rRq6vCt74lx2bWbIKDg3GdO5t/d+3T+M6ltas2cO3qDbr16MJvZX9Vyw6RjIiMjGSamQVRUVEMGzEYO0erJI/nzZuXWrVrUKt2jZ+uS90/S0W3Q0MjQ/Ye3EH1Gkm/sGtra/NHxQosWbGAkUPGcfrUWVavWIfx5PHo6ummus55bl68evUaY5NxfHj/US07lzKyX0tNdFQ0e3bvB6B9x7ZpulVT3W3bshOA+g3rUf73H0c87N65B5Ddwjzb2Vb+d21tbWrUrMaKNYtp2qAV4eERHPzvsMp3LmWk7YwcnfyQ9YIFCzJs5GDy5MmDlYUdTx4/4/q1m9RvUFe+zMMHj9m/5wAAw0YOZuKksfLHjAoYYWE1jXf+79i/9yDOs9346+9WatFB0LN392T/rq+vT8/e3SlatCjDBo3m86fPnDh2iu49uwBZs29TZXFxcXh5LASgeo2qeC1wl///6urmoVef7kRFRWFj6cC61RsZOnwQv/72i/z5GWl7qiqr9uPpFR8fz8xpVsTGxuLoasesGbY/f5IKy8zzpZ8dH1RVRtrWiqWrCAz4hJ6eHqvWLeWXX8sAspEmQ4cPIiwsnHlzPNmycTsjRg9N10jBjx8COH1S1oHQq293lRiRmZHPKuBjAFYz7ZFIJMyyncnoscOTPG5goE/DRvVp2Kh+uuvKiedjqVHFtpMTqf5ZWTbISOPLzIb7376DHDl0jEZ/NlC7qx+KePP6LR5zvSlYsADW9hY/f4IG2r1zL69fvaFosSJYWE1TeD2a8Fkqui0ZGub/4ctXYlpaWvTp3xOA8PAInj5NvcP2xrWbrF21gXLlyzLJZIJCNamCrDqoHjp4lOBg2S0A/XLAfura1RvyTv6U3m9AQCAANVIYgm1omJ9y5csCEPFtuLYqy8oTstp1a8l//vD+Q5LHTp34/y1NY8cnf9tbwu1wr16+5qrftSyoMPul9Jlk9r5N1d29fU8+GmbU2BHJdhz2H9gHQyND4uLi+HfX3nStP7W2p6pU5cvRiqWruXPrLj17d6N5i6bKLidDMvN8KS3HB1WVkba1a4fsgkrnbh3lHUuJDRsxCH39fMTHx7Nn1/50rXvH9t3Ex8ejpaVF3/6q8Zlm5LNas2oDwcHBVKtehVFj0p4XlBY57XzsZ1Sx7eREonNJRQQFBWFv40we3Tw4z3VINgRP01jOsCEiIgIru5kUTuWeW022+9sBumOn9hm64iw+y9Tp6v7/s42Pl6S4XHR0DDOnWSOVSnFxc1DrUQBZJeEqbdlyv9GocUMlV5P1tm3eAUB+w/x07Nwu2WV+/VU2euLu7XvJPh4SEsqL5y+BlDugcoorflflP//6269JHvP3fwfIPuviJYol+/zfK5SXHx/PnjmfRVVmr9Q+k59J675NHST8/wP8UfH3ZJfR0dGhXLmyAJw9cyFd68/I55yTPX/+Ai+PhRQuXAgru5nKLifDMvN8KS3HB03z/NkLeZh1q9bNk11GX1+f+g3rAXAuHftpqVTKji27AGjS7E/K/FI6g9UqX8J5freeXTP9u11OOx9LjSa2HXUlbotTEQ42Lnz+9JmpM0zVJmgyI7Zs3MaFc5do2rxxircMaLro6Bju3JbdblW9ZjX8/d+xyHsJp0+e5dOnzxgaGVKrdg0GDunHX21apbge8Vn+3KWLfoAsKD1hBElyFnj58vTJM/oN6J3jD9TJef3qDZcuXAagb/9eSq4m64WHh3Ng/yEAunTrSN68eZNdbtCQ/jjYOnPpoh+2VrPlmUtSqZR7d+8z286V8PAI6tarLb/lKSeJiozi/fsPHPjvMAu8fAFo2Kh+imGbUknKnSQSiUQecP3o4ZPMLzabREfHEBgQyIljp/CctwCA38r+Spu2rdO1nrTu29RNah1l8ZJ4AB4/+vn/f3rbniZ68vgp7dt04fWrt2hra1O8RDEaNqrP4GEDqFa9aqrPlUqlWEyzITo6Gld3RwoWLJhNVWeNzDxfSuvxQdMk3u9WrPRHistVqvQHp0+e5Uk64j0uXfDj1avXgGaMxHnz+i0fPwYAUKNGVXlu2aWLlwn+GkyhQoWo16AOw0YOSfdtuppwPvblcxBdO/Ti+bOXxMfHU6x4UerWq0O/Ab35s0n6zsE1re2oM9G5pAKOHz3J3n/3U7HSH2o1A46iPrz/iKvzPPT09HCe46DscpTG/60/MTGxgOwg4WDjRFhYOHny5CZvvrzy/I0Tx07Rb0BvXObO/uGqh/gsf+7N67dsWr8VgE5dOpA/v0Gyy927e59li1dSpGgRLK2nZ2eJamP71p1IpVJy5cpFrz7dlV1Oltu/54B81pF+A/qkuNyQ4QN5//4DK5auZsPazWxYu1k+W1xMTCxFixVhvPEYTMwmqsxtLlktMCCQRnVbJPtYm7atk50uuUwZ2ZXGsLBw/N/6U7rMj1ceHyf6YpNw0q5OKv9ei5jomB/+Xq9BXbwWuqOrmyeZZyUvrfs2dVEm0f/340dPks0mi4mJ4eWLVwCEhoQSERFBvnz5kiyjSNvTZF++BPH1azCGhvkJCwuXz2C5bctOJk4ey9QZZik+d93qjVz1u0aLls3UvmM8s8+X0np80DQBifa7xUsUT3G5hMfCQsMIDw9HX1//p+tOGIlTsGAB/mn/dwYrVb6EEcsAV6/eYIHnImJiYtHT0yOPri4fPnzkv32HOLD/MGZTJzHZbGKa160J52ORkZHcvXMfIyMj4uJiefP6LW9ev2XP7n307tcTFzeHNM9mqWltR52J2+KULCQkFGsLe7S1tXGdO5vcuXP//ElqzsrCjtCQUEynGCcJ48xpgr9NXQuwyGcJuXLlYuESL+48usbNe5c5e/k4HTu3B2Dr5h2sXL72h3WIzzJ1UZFRGI83IzIykkKFCjLDcmqyy8XFxTFzqjVxcXHYzZ6V40MRkxMfH8/Obf8C0LpNS4oWK6rcgrLB1m+3PFSpWjnVEG5tbW1mWE7BzcMZfX3ZF93w8Ah553F0dAyhoaFEREZmfdEqQltHhyJFi1CkaJEkt2517NweC6tpFChY4IfntGz9/w6Bhd5Lkl3vogVL5T8nTOmsTop++0wSd4g0btIIG3tLSpculeb1pHXfpk6q1agqn2Z6qe8K4uLiflhm3eqNSf7fk2sDirQ9TVS23G9YWE3j2JkDPHh2k+t3L3H38TXWblxB9ZrVkEqlLPJZyoqlq5N9/ts3/rjP8SRv3rw4utolu4w6yezzpbQeHzRNWHi4/Oe8efVSXC7xY+Fh4SkulyAkOIRDB44A0K1nlx+moVdHCXlIAJ7uPhQrXox1m1dy9/E1bj+4wuET+/izcUOkUime8xbI3//PqPv5WPHixTAxN+a/I//y4Nktbty7xL0nN9j+7yaaNm8MwI6tu3Cyn5Om9Wli21FnonNJyVxmu/HxYwCDhw6gTr3ayi4ny/27cy8nj5+marUqjPpuxoScRvLt1g6Q3eoxZ54THTu3k3cwli5dCh9fD6pUrQzA4gVLk5xsi88ydXFxcZhNmsbd2/fInTs3ngvcU8xxWbJoOffvPeCvv1vRqUuHbK5UPZw+dZYPHz4C0HeAeg7BTo/Hj55w88Zt4OdDrL98CWJwvxFMN7ekTr3abNu9kZv3/bh8/QyLl/tQqFBBNq7bQs8u/fjw/mN2lK90hQsXwu/GWfxunOX+0xuc9zuJsck4jh89Sce23dm8YdsPz6lcpWKSDnUnhzm8feNPbGwsz5+/YMZUK04cOyXfR6rDTHHfO3vpOH43znL38TX8bp5jls0M7t97SI/OffF090nTOtKzb1MnuXLlYrKZbBKFp0+eMXrYBO7euUdMjOwWwmWLV+I+xzPJRTitZNqAIm1PE3Xv2YWxE0ZRvnw5+WeWJ08emrdsyvZdG6lZSzYLrff8hYSEhP7w/IRsIvNpk5MNbVYnmX2+lJ7jg5A2/+7eR3R0NKA5n6lE8v/zfKlUiu8yb5o1byI/dv1RsQLL1/hStJisU93H0zdN61X387HmLZtiNnUSVapWko/W1dHRoV79OqzduIK27doAsGHd5iSjv1KiiW1HnanfmZkGOXf2Atu27KRkyRJMszBXdjlZLjDwE472rujo6OAyd3aahzpqqsRDhMuW+y3ZYZza2tqMGTcCgKCgr/LAYPFZpi4+Ph7zydM5cvg4uXLlwnOBO81bJj/DzZPHT1novRh9/XzMdlHv6ZWz0rZNsqu0JUoUp1Xr5G850SQJV6V1dXV/ejvINDMLLl30o9GfDVi7cQX1G9TF0DA/RYsVpV2HtmzbvZFChQry+tUb5rp6ZEf5KkVLS4uSpUowdYYZngvmEhsbi80sBx7cf/jDsnPmOdG46Z8ArFq+lhaN/6ZSuZr83aIjO7buom27NrT+S9b+jNR8hGGRIoUZPW4EazYsQ0tLiwXeizl+7GSqz0nPvk0dDRk2kDHjRgJw5vQ5unboTeXytWhUtwVznOdRukwpxk4YKV/+Z20gPW0vJ9HV02WahRkgG2V54dzFJI9v3bSd82cvUr1GVUaMHqqECjNPVpwvpef4oGkMEp27RkZGpbhc4sf0DX5+S9z2b7c11a5Tk0qVK2agQtVhkOh9N2n2Z7Kzf+rr6zNk2EAAHj54ROC3GTNTo8nnY9ra2vJoColEwvFjp376HE1sO+pMdC4p0awZsi+yM62moaUlCwdM/C/+W6hpvETy/7/Fxyuz5AyZ6zqfoKCv9B/Uh98rlPvh/cbGxsqXTfhbTMyP2RSaokSiK82/Vyif4nIVEs2akzCbjvgsUxYfH4+5yQz+23cIHR0d5vu4pTqLi52VIzExsUycPB4jI8MfPsu4ONk2J5VKk/18c4LAwE+cOC6bJr5X3+4anxsUExPDnl37AGjf8Z9Ub5N8+uQZp06cAWD0uBHJzgZTpEhhevTuBsDhg8fkgdQ5UfuO/1CqdEkkEgnbNu/84XEDA33Wb16J18J5tG3XhrLlfqPML6Vp2rwx87xcWbJiAV+/3VKsKQHWterUlIe5btm4PcXl0rtvU1eWNtPZtnsjvfr2oGKlCpQsVZJatWsydYYp+w/vQltbtv8pXaZUum5/+Fnby2nqJhot/+b1W/nPISGhuDi5o62tjbW9JVFRUT8cFxP2YXFx8fK/SVIJ4lemzD5fSs/xQRMVK/7/c9ePH1IeiZvwmEF+g5/mLd29c497dx8AmjXyJPGI0goVkp8BE6DCH/9/7N3bdykuBznjfKxsud8oVEg2ecCbV29SXVZT2446E8MdlOjtG38AzCZNS3W5q37XqFGpPgBLVixQ26Cyt99OXjau28LGdVtSXTbh/Q4fNQRbh1lZXpsyFChYgBIlisuHtqYk8ffQhC+u4rNMXsJV/f17D8q/fHXu2jHV57x5I/ss3efMx33O/BSXe+f/Xv5ZWttbMHL0sMwrXMXt3rGHuLg4tLS06NNP/YZgp9exIyf48iUI+PnJypPH/58JJ7Ucj7LlfgNkAZafPn2m6LdsmZyoRInivPN/z8uXr5J9XFtbm67dO9G1e6cfHouLi+PBg0cA1K1XJ0vrzE4J4bevXr5O9nFF9m3qrH6DuinOnpQwy6oi//8/a3uCLL8k9Nttcv17DUl12T2797Fnt6yjZf/hXVStViXL60uvzD5fSs/xQRNVqvz/GeIeP3qSpGMksUffZnP8I4XHE0sIY9bXz0fnbpqzX/vjjwro6Oj8dGBAkutNyVygSiynnY/9jKa2HXUmRi4JghI1+3Y7w9NUpmp9+vip/Ocyv6h37kFWio+Px2zStCRfvrp0+/HLqZB+CQfvP5s0yhHB8Qm3PPxW9lcaNW6Q6rLa2v8/EfRP5Yrjp8DP8p8TQr9zIqlUKu/QNUjDrRLfO370JKEhoejp6WnUqJ03r2VXZ5O7wi/2bf8XGPhJfgtXz2+jAdMqo21P09y4fkv+szi3SLv0HB80UbnyZSlVuiQAp0+eTXaZiIgIrvpdA6BZi9Rv242KjGLvv/8BstD9tMwqpy509XRp2EjWYfn0aSrn+U9k5/laWlqU+eXHWVITywnnY69evpZ34KaW96bJbUediZFLSvT87YNUHx/QeyiXL12h0Z8N2LxjXTZVlXV+9h68PBbi47kI+Plnoyl69+3Bjq27ePXyNUcOHfthVJpEImH5t5lcSpQoTvUaVQHxWX4v4ar+f/sOkStXrnRd1T976Xiqj083t2Tn9n8pXabUT5fVRFf8rvH82QsgZ1yl9fd/x/mzsi+vffr3SvY2t8QStkmAjeu30OqvH/MPIiIi2L1zDwCVq1T6Yep0TREXF/fTPJPtW3cRGCDLlGjUuGG61v/58xdcndwBWTaPUQEjxQrNRvHx8Whra6fajs6fu8itm3cAfviympF9m6aJj4/HxsKemJhYatWuSYtWzeSPZXXbUzdSqTTVNhcdHYOHmxcA+fLlo2mzP+WPlfml9E/PG5r/2Qb/t+/o1ac77p6umVJzVsnM86X0Hh80kZaWFj17d2Oh9xL27z3IZLOJP3SIrF+zifDwCHR0dOjWs3Oq6zt04AghwSEA9BuoeecYvfv24OKFy1w4d4m7d+79kLsUHh7OhnWbAVlmUOHChVJclyacj/1s3ySVSuXHeW1tbf76u1WKy2p621FXYuTSN8Ffg/nyJUj+LyHhPyoyMsnfw8N/nE4z8eMJPa0AEeERSf4emYOmoRbSpmGj+nToJLv6bjndhoP/HZHPCOfv/w5T46k8/HYLyNSZZmo5O1J6KLIdJuSQ7N97kFy5cuG10D3Hfvn6Xkb2awm2fbtKW6CAEe06tM2WupVp+5ZdSCQScuXKRe8+3X+6fOkypWnTtjUgG1UzxWQGr16+RiqVEhsby7WrNxjQZxivv+UGjB43PAurzzyKtJ2rftfp12swu3fs4f27D0nW9+L5S9xcPLC2sAfgt99+pXefHj+87onjp1i9Yh2vXr6W30oQGRnJgf2H6N11AK9fvaFK1cqYT5ucRe88c71/94HO7XqyacNWXr96kyRv69279yxeuJxxIychlUopUMCIUWP+f7ttTty3vX71hnluXty9c4/oKNnsPxKJhKtXrjN04GiOHD6OoZEh7p4uSb6gZEbbU1WKbIt+l64wuP+IHz6P2NhYzp+7SL+eg+WznU02m5DjcoMUld7jg6pT9Bxh9LiRFC1WhMjISEYNG8edb5PNxMTEsGHdZjznyWa+7D+oD+XLl0u1hoSRYBUrVVDpW50V/ay69exCrdo1kUqlTBxryvlzF+X5ZE+fPGPsCGMCAz6hra3N1JlmqdagCedj/m/f0b1T3x+OiRKJhBvXbjJi8FiOHDoGwIDBfSn/e8rtR13aTk4jRi5907l9z2RvaVi2ZBXLlqyS/57cVZr6NZsku057GyfsbZzkv5uYG2M2dVImVSxoCndPFz5/+ozf5asYjzMlj24e8urlJTg4WL6MibkxvTTgROZnFNkOr125zv49BwDZFTV7G2fsbZxTfA1bB0uN/4KWICP7NYDQ0DAO7D8MQPeeXeVTxmoqiUTCjm27AGj1V4skwaWpcfNwZvjgMdy9fY9/d+3j3137yJs3L7GxsfLOYoCx40fSs3f3rCg90ynadq5cvsaVy7LbIXR1ddHXz0dERCRRUf+fOahK1cosXbkQvbx6P6z/5YtXONnPkc/uZGBgQGhoqPxkvGGj+ixZsSDZ56qqB/cfyjs28uTJjYGBAVFR0URERMiX+eXXMvgu86ZosaLyv+XEfVtYWBi+C5biu2ApAEZGRkRERMhDl0uVLsmSFQuSzXnJaNtTVYpsi1IpXDh3iQvnLgGgp6dHvnx5CQ0Nk3+W2trajDcew7iJo7PhXag/RY8PqkzR/byhYX5WrFnC8EGjefL4Gd069sbAQJ/o6Bh5+2resinWdpapvv7LF6/wu3wVkI0EU2WKflba2tosW7WQwf1H8OTxM4b0H0nevHnJlTuXPNssd+7cODhZ06Tpnz+sP4EmnY/dvnWH27dko3Xz6ObBQF+fsPBwYqL/H6Tfu19P7GZbpbgOdWo7OY3oXBIEJcuXLx+btq9l+5ad7N65l8ePnhAeHkGJEsWp36gew0YMpl590SOfkoSrRyC7KvvpJ9O4Rn27Gi783P49B+QjLvuq6RDs9Dh/9iLv/N8D6RtyXqhQQXbt3cLO7f9ycP9h7t9/SPDXYHR0dChVuiR169VmwOB+NGhYL6tKVwnVa1Zjvrcbly76cef2PQIDP/E16Ct58uTht99+pVqNqrTv2JYOndqlOMNNs+ZNGDZiMFevXOP9uw+EhYVRpGhhataqQbcenenYub1a3YpSrHhRFi7x4vJFP27evE3AhwCCgoLQ1pa1jSpVK/P3P3/RrXvnHzo8cuK+rUyZ0kw2m8jli368evmaoKAgDAz0KV+hPO06tGXQkH7kzZv3h+dlRtvTJJWq/MEsmxlcv3aTRw8fE/QliJCQUPTy6lHhj99p0LAe/Qf1pXIVMW13Wil6fNBUNWpW49CJfSz1XcGJY6d4/+4DefPlpValmvTq3Y0+/Xv9dLT99q27kEql5MmTmx690pehpk6KFivK3oO7WL9mI/v3HuTFi5dER0VR5pfSNG7SiJFjhlGpcurboqacjxUpUhh7R2uuX7vJg/sP+PI5iODgEHR18/DLL2WoW682ffr3SnFChwQ5pe2oIy1pGuZEDgkJwcjIiODgYAwNVWforLW1NWvXruHMpWPKLkUtlC9ThZ69ujHPe46yS1F5ixYsxWf+Ih69uK3sUtRC5fK1aN2mJYuX+yi7FJW3cvka5jjN48mru8ouRS3UqtqQunVrsXrDcmWXovI2bdiKjaU9z95ofs5aZqj8ey3GTRitNrfYKdOsGbZs2bSdh89vkSeP+l4xzy7V/qjL4KEDsLSZruxSVJ6zgxsrl6/h5n0/DA3zK7sclVezcn169OqGg7ONsktReV4eC/Dx9OXStdMaMdIsq9Wu2oh/OvzNXI+UR8gKMhfPX2ZQv+E8e/aM8uXLK7ucLJeeviDNDnARBEEQBEEQBEEQBEEQspToXBIEQRAEQRAEQRAEQRAUJjqXBEEQBEEQBEEQBEEQBIWJziVBEARBEARBEARBEARBYaJzSRAEQRAEQRAEQRAEQVCY6FwSBEEQBEEQBEEQBEEQFCY6lwRBEARBEARBEARBEASFic4lQRAEQRAEQRAEQRAEQWGic0kQBEEQBEEQBEEQBEFQmOhcEgRBEARBEARBEARBEBQmOpcEQRAEQRAEQRAEQRAEhYnOJUEQBEEQBEEQBEEQBEFhat+5JJVKlV2CWpBIJADExMYquRL1EBkRIf/MhJ+Lj48nNka0rbSIjIwS+610iI+LE/utNJK1LWVXoT4kEgmRERHKLkMtxMbFASCRiAaWFhJJPOER4couQy3Excn271JxzpUm8fGibaVV7LdzB7HfSpv4+DjCw0TbSgspok2lRK07l/LmzYu//ztMjafx7t17ZZejso4fPUnDOs0AOHTgCJYzbIj7dqIoJBUZGYnxODOWLl5JfHw8TRq05orfNWWXpbLOnD5LwzrNiY+P58zpc0wztSAmJkbZZamkmJgYzCdPx2f+IiQSCX/WbcH5sxeVXZbKunTBj8b1WxEREYnfpauYTJxCVFSUsstSSXFxccycasVcl3kANKjdjJPHTyu5KtV1/doNmjX6i7jYOFavXM/40ZOJEJ1MyYqPj8fa0oG9u/cD0LRBKw4fPKrkqlTXnVt3admkLdHRMWzdtINRQ8cRGhKm7LJUkkQiwcnelU0btgHQsuk/7Nvzn5KrUl0P7z/kr+btiYyM4t+d+xg6cBQhwSHKLkslSSQS3Fw8/sfeXYdFsf1xHH8DIgiK3V67u7u9Xrvr2h2AEtLdIB0KiN0d1+5u7O4WCwXp3v39gfITRYQldhfn9Tz3eXB3Zva7e2dnzp458zksX7IKgD49B7Jty07pFiXDnjx+yj89BhITE8uhA0f4d+QkwsLCpF2WzDpx7BTW5vYoKiqirKws7XJkjlx3LpmZmbFixQqCL17h72798fP2Jy4uTtplyYzXL18z4J9hzJqmTRHVInj6LKBPv7/ZvGEbLRu3Z9P6LdIuUaYs9l9K66YdObj/MCNGDsPF3YHkpCTGjpzEqGHjCP0YKu0SZUZIyDuG9B/J1AmzKVRICXdvFwYM6seO7bto2aQDq1esk3aJMmXF0tW0bNyBXTv3MmhIf9y8nEFBgUnjpjNs4GjevXsv7RJlxof3HxkxZCzjx0xBlJLCAg9Hho0cwr49B2nVpCNLFq+QdokyZf3aTbRo1J6tm3fQp98/ePi4oFK4MDOmaDKw73DevA6Rdoky49Onz4wZMZHRwyYQHxePs6sdo8eO4MihY7Ru2olFvoHSLlGmbN28g5aN27Nh7SZ6/t0dL19XihYriuZMHfr1Gszz5y+kXaLM+BL+hYljpzFs0BgiI6Owd7ZmwqSxnDp5lrYtOuPl7iuMhv7O7v/20rJJB1YsW0OXrp3wXuhO6dKl0NU2pHf3ATx69ETaJcqMqMhopk2azaB+I/n8KQwbewumzpjE+XMXaduiC84ObsK+9Z0D+w/TulknggKW0bZ9G3wWeVC+QnmM55vTo3Mf7t25L+0SZUZsbCyzp8+l399DePf2HebWJszSnM61K9fp2Lo7dlaOwr71nSePnzJ14iymT55Djeo1uXHjBn/99Ze0y5I5CuIs3J8RGRlJ8eLFiYiIQENDIz/qypbIyEicnZ3x9vamTJnSmFoaMmBQPxQUFKRdmlTEx8djPN+cg/uPUKhQIXTnazNl+iRUVAoDEHzpCraWjjy4/5C/qlZhUaA3TZo1lnLV0nPuzAUM9Ez4+CGUlq2aY+toSeMmjQCIiYlhsf9SggKXo4ACo8YMx9bRkkKFCkm5aulITEzE3Mia3bv2oaSkiLbOHGbMmopqEVUgdUSAraUjd27fo1Klivj6e9CqTUspVy09l4OvoqttyPt372narDG2DpY0b9kMSB0lt3TxCgIWLkEsFjF42CBc3Oz/2H0rOTkZa3N7tm/9D4A52jOZrTUdNTU1AG7dvIOtlSM3rt2kfPnyeC90o33HtlKsWLpuXL+FjuZ83rwJoWGj+tg4WNKmbSsAEuITWL5sNQt9AkhJTqH/oL64eTpRuHBhKVctHSKRCDtrZzZt2IJYJGbG7KlozZtN0aLqANy7ex87KycuB1+lTNnSePi40LVbFylXLT337txHe44eL1+8ok7d2tg5WqV91xITE1mzcj0+ngtJSEyk9z+98PBxSfue/mlEIhELnDxYs3I9ySnJTJsxmbm6mmhoFAPg0cPH2Ns4c/7sRUqVKskCD0f+/qenlKuWnkePnqA1U4dnT59Ts2YNbBws6NKtE5B6C9OGtZvxcPMhPi6e7j274r3QPe17+qcRiUR4eyxkWdBKkpKSmDh5HLrztSlRsgQAz54+x8HGhVMnz1C8RHEcXWwZMKivdIuWoufPX6A5Q4dHDx9TtdpfWNub06NnNxQUFEhOTmbzxm24u3gRExNLp84d8AvwRKO47P2mzS+LfAMJWLiEhIQExo4fjb6RDqVLlwLg5YtXONm7cvTwcTQ0imHjYMmwEYOlXLH0RHyJwM8ngLWrNlC1alW8vLwYPHjwH9XPkJ2+oALRufTNkydPMDQ0ZNeuXbRu2wprO7O0ToI/xdKgFfh4LCIuLo6Ro4dhZKpP2XJlf1ouJSWFbZt34OriRWREJO07tmVRoHfaSetP8O7de7Rm6nDr5h3KliuDla0Z/Qf2zfBg8frVG1wc3Ti4/wjFihXF0taMUWOGS6Fq6Vm9cj0eC1JPzEOGDcLE3IAKFcv/tJxIJOK/Hbtxtnfjy5cIWrVpiX+QD2XKlJZC1dIR+jEUrdm6XL96k1KlSmJuZczgYQNRVPx5sOjbt+9wdfJkz659qKurY2JhwIRJY6VQtfRs3rAVJ3s3oqOj6T+wD2aWRlSuUvmn5cRiMXt27cfJ3pVPoZ9o3qIZAUt8KV+hnBSqlo6wsDDmztEn+OIVihcvjqmlISNGDc1w3/rw/iPuC7zYsW0XampFmG+ky7SZk6VQtfTs2LYLe2snIiOj6N2nFxbWJlSt9vOVRrFYzMH9R3CwdebD+480btKQgKULqVy5ohSqlo7IiEjmac3n/NmLqKurYWxuwJixI1FSUvpp2U+fPuPp5suWjdtQVVVhrp4mmtqzpFC19OzbcwBLMzsivkTQvWdXLG1MqVmrxk/LicVijh05gb21MyEhb6lXvy6BS32pVr2aFKqWjujoGPTnGnLyxBlUi6hiaKzHuIljMrylJCwsHB/PhaxfswkVlcLM0pyB7nztP+qH3OFDxzAzsiI8LJyOndtjY29Bnbq1M1z25PHT2Fk78fLFK2rXrUVAkC+169TK54qlJzY2FgNdU44eOY5K4cLoGeowacq4DC+mfOskWL1iHcrKhZg6YxKGJvoZnj8LqlMnzmCkb8anT59p2641Ng4WNGhYP8Nlz545j52lI0+fPqdGjer4B3lT/xfLFkQpKSls2rAVL3c/khKTsLS0RE9PDxUVFWmXlu/+2M6lb44cOYKenh73799n9L8jmG+sS9myZaRdVp66eD4Y/XnGfPjwgeYtm2HrYEnTLIxGioyMwt93MSuWrUZJSYmJk8dhZmVUoA+0ycnJmBtbs2vnHhQUFNGaN4uZc6ZRpEiR36578XwwNpYOPH70hKrV/mLRYh8aN2mYD1VLz9XL19JyzRo3aYitoyUtW7X47XrR0TEELlrC0sUrUFBUYMzYUdg6WBT4fcvW0pGtm3cgRsxszenM0Z6Juvrvr7xeuXwNW0sH7t19QOUqlfEL9KRFi2b5ULX03L55h7ma+rx+9Yb6Deph62BB2/ZtfrtebGwsSwJXELhoCQDDRw7BwcWmQI/6EolEONotYMPaTaSkiJg+awraOnMoVqzob9e9ef0WNlaO3LpxmwoVy+Oz0D1Ln7M8e3DvAVqz9Xjx/CW1a9fExtGSTp07/Ha9+Lh4li9dxSLfQFJSRAwa3A8XD8cCPepLJBLh7uLFqhVrSUpKZvK0CejoaVG8RPHfrnv3zj1sLR25euU65cqVxdPXlU5dfv85y7Mnj5+iNUuXJ0+eUr16NWzsLejW4/cj3RISElm9Yi2+Xv4kJSXSp98/uHs7o6qqmg9VS4dIJMLP25+gwOUkJiQyYdJY9AznUrJkyd+u++D+I+ytnbh4IZjSpUvh6uVEz17d875oKXr54iWaM3V5+OARlatUwsbegp5/d/9tx1pSUhJrV2/Ay92PhPgEevXugZefa4EfURiwcAmLfANJSEhg9NiRGBjrZulC5pPHT7G3cebs6fOULFkCZzd7+vTrnQ8VS8+b1yFozdLl7p17VKhQHktbM/r27/3bfSs5OZmN67fgscCb2Ng4unbrhM8iT4pp/L7tIc8unLuEg50LD+49ZMqUKTg7O1Ox4p9zselHf3znEqR+GRYvXoy1tTXJycnM1Z3D5GkTClwD8cP7j2jN1uXGtZuUKVsGC2sTBg3pn+0rPM+ePcfJdgEnjp+meHENHFxsGDi4fx5VLT3r1mzE1cmTmJgYBg7uj6mlIZUqZe9gkZKSwpaN23Fz8SQqKppOXTqwMMCrwA2v/fTpM9qz9bh6+RolShTH3NqYocMHZ7tz6NXL1zg7uHH44FE0NIphbW/B8JFD8qhq6dm6eQeOti5ERUXTt39vzCyN+atqlWxtQyQSsX3rfyxw9CAiIoI27VrjH+RNqVKl8qhq6fgS/oW5mvpcPB9MMY1imJobMHLM8AxHSGQm5E0IC5w82LfnIEWLqmNmZcTY8WPyqGrp2bVzLzYWDkRGRtLr7+6YW5tQo2b1bG1DJBKx+799ONu7EhYWTotWzQgI8s1wZKs8i4qMRld7PmdOn0dNTQ1DUz3Gjh+d7Y7H9+8+4ObixX87dqOmpoaRqR6Tp03Mo6ql58D+w1iY2PAl/AtdunXC2s6cWrVrZmsbYrGY/XsP4mi3gI8fQmnSrDGBS/2oWLFCHlUtHdHRMczXMebEsVOoqqow30iXCZPHZjvQNfRjKO6uPmzfshNVVVV052szS3N6HlUtPcePnsTEwILPn8No36Et1vYW1G9QN1vbEIvFHDl0DHsbF969fUeDhvUJXOLLXxmMPpRn8fHxGOqZcfjgUZSVldGdr83kaRPT4iyy6vPnMLzcfdm0fisqKipozZvFXF3NPKpaes6cOoehvimhHz/Ruk1LbBwsaNQ4exd6xWIxJ46fws7Kidev3lC3Xh0Cl/lRo0b1vClaShITEzE1tGTv7gMoFVJirq4mM2ZOQUU1e6NvvoR/wdfLn7WrN6CsrMyM2VPRN5xX4C4Yv371BmcHNw4dOEKHDu3x9fWjTZuCfTEuK4TOpe98/vwZW1tbAgMDqVrtL8ytjenZ6/dXAWRdcnIyVmZ27Ni2C/g5n0RSp06cwc7aiRfPX1Krdk0Cl/oViOG116/fREfTgJCv+SS2jla0zmEWUGREJH4+AaxavhZl5UJMmTYRI7P5cn+gFYlE2Fk5sWnjVsQiMTPnTENz7qwc5x6cP3cRW0tHnjx+SvUa1QgI8ikQw2vv3L7H3Dl6vHr5+qd8EklFRUUTsDCI5UtWoaiowLgJY7C0NSsQ+5aLgztrV28gJSWFqTMmpcsnkVS6HLm/KrMw0JumzZvkUtXS8/DhY7Rn6abmk9T6mk/StVOOthkTE0NQwDIWBywrUDlyIpEITzdfVixdTVJSEpOmjEdHXyvHt3pfv3oDGytH7ty6W6By5J49fY7WLB0ePUwdhWtjb0GPXt1ytM34uHiWBq3A3y8IkVjEkAKUI+fnHcBi/6UZ5pNIKn2OXDk8/Vzp2Kl9LlUsPa9fvmbOLB0e3HtIpUoVsbIzo3efXjlqdyfEJ7Bi2Rr8fPxTc+QG9sHNy7lAXDAOClyGn1cA8fHxjBozHAMTvRzfbXH/3gPsrJwIvnSlQOXIvX37Hq2Z87h96y7lypfFytaMfgP65GjfSkxMZM2qDfh4+BW4HLlVy9fi4epDbGwsQ4cPxthsfoZxFtnxfY5cyVIlcXF34J8+vXKpYumJiYkhcNFSli9ZRZkyZXBzc2Ps2LFy31+QW4TOpQzcuXMHPT09jh07RtfunbG0MZXbTpON6zfj4uBOdHQMAwb1xdTCMMN8EkklJSWxfs0mPN19iY+Lp0evbnj5ucllqGJYWBhzZ+sTfOn3+SSSevrkGQ42Lpw+dZYSJYrj5GpHvwF9cm37+WnHtl3YWTsRFRnFP33/xtzKOMN8EkklJyezacNWPBZ4ExMTQ5eunfD195LL4bXf8knOnblAsWJFMTYzYPTYEdkefZOZF89f4mTvyrEjJ9DQ0MDOyZIhwwbl2vbz097d+7EytyfiSwQ9enbFwtaUmjV/zieRVEpKCtu27MTV2VPuc+Sio2PQm2vIqRNnKFKkCIYmqfkkufkj/c3rEJwdXDm4/whFixXF0tqE0WNH5tr289P3+SSdunTA2s78l/kkkviWI+fi4E54+BdatW6B/xJfucyRS8snOXwcFZXC6BvpMHFyxvkkkipIOXI/55NY0qBhvVzbvlgsZu/u/TjafcuRa0rAEj+5zJGLj4/HxNCSA3sPUahQIXT0tZg6Y3K2R99k5uOHj7gv8Gb71v8oolYEfQMdZsyekmvbz0/nz11kvo4JHz98pEXL1MlkmjTNvZzYbzlyjrYuvH//gUaNGxKwxJcqf+Xe74X8kpiYiLmJDbt37kVJSRGtebOZOXta2mQyueGnHDldTTTnymeO3NXL19DRNuDd2/c0btoIe0ertMlkcoNYLOb40ZPYWTsR8ka+c+S+nd/dXLyJjIjEyMgIExOTLMVZ/EmEzqVfEIvF7N69m/nz5/Py5cu0mReykisgC37KJ3G0pG271nn2emFh4Xi7+7Fh3WZUVFSYoz0DHX3tPHu93CQSiXC0dWHDus2IRGKmz5qC1rzZWconkdSJY6ews3ZKG8ESuNQvw3BPWfRjPomtk1WeXkH9Ev4FP+8A1qxaj7KyMtNmTsbAWFcuRub8mE8yZfpEdPS08vS2yDOnz2Fn5cSzp8+pUbM6/kt8qV8/e7cXSMuTx0/RmqnDk6fPspVPIqkfc+QmTB6HuZzkyIlEIny8FrF08QqSEpOYMGksugbaWconkdSlC8HYWDqmzbAjTzlyL1+8ZM7X2YEqV6mEjYNFno5MTpcjp6DAmHHylSPn77cYf78gEhISGDNuJPONspZPIqn0OXKV8PX3yFJenyx48zoEzVk63LtznwoVymNlZ0affr/PJ5FUXFwcQQHL03Lkho0YjOMCW7kZ9bUsaBXenn7ExcYxYtRQjEz1KVc+7zrIbt64jY2lA7du3KZ8hfL4LpKfHLkP7z+iOXMeN2/epmzZMljamObpDNfyniO3dvUG3Jw9iYmJZfDQgZiYG1CxUt7dcvt9jlzZcmXw8F6QNqOhrPv06TPas3S5euU6JUuWwNzKmCHDB+XZOSp9jlwS//T9Gw8fF7nJkbtx7SZ2Ns7cvH6L0aNH4+bmRrVq8tdBlh+EzqXfSEhIwNfXFwcHB5QLK6NvOI9/x42S2ZN4buWTSOr+vYfYWztx6eJlSpcpjbuXM917ds2X15bErp17sLFwTM0n6d0DC2sTqtfIn4NFYmIia1dvwNtjIQnxCfz9T088fRfI7PDa/+eTnENdXR1DU/18/S48fvQEextnzp25QMlSJXF2tZPpUMXv80m6duuMlZ1ZtvNJJJWcnJw6TbOrD3FxcXTr3hkff0+ZHVGYLp+kiCrzDXUkyieRlLzlyB0/ehJjAwvCPofRvmM7bOzNqZdPHYjyliP3Yz6JnsFcJk2dkKsjJDIjbzlyZ06dw0DPlE+hkueTSCotR87Jg4gvsp8jl5iYiImBJfv25CyfRFIhIW9Z4OjOvj0HUS+qjrmM58gFX7yM7lxDPrz/SLMWTbF1sKRZPt2SLBaL2bVz7/9z5Fqmzh4qqzlyycnJWJrasnP7bhQUFNCcO4tZmlmbTCY3yFuO3LWr19HRMuBtyDsaNW6AraMVrVrnT+f0TzlyTRsTuEx2c+REIhE2Fg5s2bQdMWJmzZmO5tysTSaTG+QtR+7D+4+4uXiyc/tumjdvhq+vH127yu7vWlkgdC5l0fv37zEzM2PVqlXUb1APS1tTmbrf/cd8kmkzJqOtOyfH+SSSEIvFHDpwBEfbBbx7956GjRoQuNRPpobXPnjwiLmz9XI1n0RSnz59xsvdl80btqGiooK2zmy0deZIpZaM5FU+iSTEYjHHj53Ezip1eG3denVYvMxPpobXPnv6HM2ZOmmzBOZGPomkwsPD8fX0Z92ajSgXVmbmnGnozZ8rU6Mnvs8nGTdhDPpGOpQqlXejbzJz+uRZ7KydeP7shUzmyP2YT2Jtb87f//SUyn3+aTlyK9aiXKgQk6ZOwMTcQKb2rcUBy1jonbv5JJL6MUfOf7E3DRo1kEotGQkJeYf2TB1u375L+QrlsLQxo9+Af6Syb8lDjtzKZWvwdPMhNjaOYSMGY2xmILXb077PkavyV2UWBnjTrIXs5MiFfgxFc1bqZDKlSpfCwtqEwUMHSGXf+pYjFxSwHICRo4dh52QlUxeMN6zbjIujOzHRMQwY3C81zqJyJanU8n2OXMVKFfDz95SpHLmwsDC0ZulxJfgqJUoUx9TSiOEjh0jlWJEuR04kYsiwgTi72efbRbKs2LZlJw42LkRFRdGnX2/MrbI/mUxuuX3rLraWjly/dkMmc+QS4hNYtnQVgQuXoK6ujpOTE9OmTcu3wRryTOhcyqbLly+jq6vDhQsX+advb8ytjHI1Z0YSeZ1PIqmE+ASWL1vNQp8AUpJTGDCoL66eTlIdXhsdHYOetgGnTp7Ns3wSSd27ex87KycuB1+lTNkyePg4Sz1U8dCBI5ib2ORZPomkEhMTWb1iHb5ei0hITOSfPn/j6btAqsNr0+WTqKqgbzgv1/NJJPXwwSPsbZy5cO4SpUqVZIGHI3//01OqNX2fT9KufRus7S1yNZ9EUj/nyHXFy89dqqO+4uPjMZ5vwcH9h/Msn0RST588w9F2AadOnqFEieI4LrCj/0Dp5sidO3MBAz0TPn4IpWWr1HySxk1yL59EUulz5GLp3KUDfgHeUs2RS8sn+W8vSoqKaOvMYcasqbmaTyKpH3PkbBwsGDZisFRruhx8Fb25hrx7+54mzRpj52CZq/kkkvoxR65dhzb4L/aRao5ccnIy1ub2bN/6HwBztGYwW3uGTIzOfvM6BBdHdw7sOyQzOXI3r99mnqY+b96E0KBhfWwdLWnTtpVUawLZzJETiUQ42Dizcf1WRCIRM2ZPRWvebJkYnZ0+R04NY3MDJk4eJ9Wa7t25j/YcPV6+eEWdurWxdbCkQ6d2Uq0Jfs6Ra9a8CYFLF0o1R+5b/tgCR3fevXuPjo4OVlZWlChRQmo1yRuhc0kCYrGYjRs3YmJiwsePH5k+a0quzJCVXU8eP0Vzpg5Pnzyjeo28zyeR1PdDCtXU1JhvpMO0mZPztQZp5JNIQiwWc2DfYRztXPjw/iONmzQiYKkflStXzNc68jufRFKhoZ/wdPVl6+btqKqqMk9fizlaM/K9jvzOJ5GEWCzm2JET2Fk78zbkLfUb1GPxUr98n6b5zesQNGfqcO9u/uSTSCp9jlxhZmvNQHf+3HyvY2nQCnw8FxEXG8fI0cMwNNHL03wSSZ04dgp7G2devnhF7bq1WLx0Yb7nyOV3PomkIr5E4Ovtz5qVqTlyU2dMwtBEL9+vtud3Pomkzp45j52lI0+lmCP36dNntGbpcO3KjXzJJ5HUzzlyYzG3Ms73Ojdv2IqTvSvR0TH0H9gHM0ujXJ1MJreky5GrWoVFQb75niP3JfwL2nP0uHThMhrFNTC1SJ1MRtZGSHybIWvJ4uUooMDof0dg52SV7/vWzu27sbNyJDIyir//6YmFtQnVqlfN1xqy4uqV69haOnD3zn2p5chFRkSio2XAubMXUFdXw8hsPmPGjpSJC+rfi4uLY0ngCgIXLUEsFkstR+7+vQc42Lhw8UIw/Qf0x8vTi3r1pH/RU94InUs5EBMTg5ubG25ubmgU18DIVJ9hIwbn+YH2x3wSAyNdxk/6V6aGXmbk5vVbqaGKN+9QoWIFfP098uWqjDTzSSQVHxfPsiUr8fdbTEqKiMFDB+DsZp/no2C+zycpXFgZ3flzmTxtgkyMvsnMndupw2uvXb1BuXJl8fR1pVOXDnn+uqdPncVQz4xPoZ9o07YVNg4WNJShW10ykpCQyKrla/D18ic5OZk+/Xvj7uWc56O+fswnmaenxfQZk/Mtn0RSD+4/ws7KMS1Hzs3TKV9uc7x4Phh9HWM+vP+Q7/kkkvoxR65X7x54+bnm+UiF5ORkLExs+W+HdPJJJPX40RMcbFw4e+Y8JUuWwNnNPl9y5L7PJ2ncpCG2jpYyH56dnJzMhnWb8XRNvRWta/fO+CzypFixvL2ol5ZPsnk7YrGY2ZrTmaOdf/kkknr+7AWOdgs4cewUGsU1cMynHLnbN+8wT1OfV6/eUK9+XewcLWU+PDslJYWtm7bj6uxJVHQ0HTu1Z1Ggd57nyIlEIpwd3Fi3eiMpKSlMnzkZbV3NPJ1MJjd8nyNXrFgxrOzMGDl6WJ6/7oN7D9Cerc/z5y+oVasGNo6WdO7SMc9fNydEIhE7tu1igaM7X75E0KZtK/yX+OR5jpxIJMLD1ZuVy9aQlJTM5GkT0NHTkvlJqUJC3rLAyYN9uw+gXlQdM0sjxk3I+xy5z5/D8PbwY9P6rdSpUxtvbx/69euX569bUAmdS7ng5cuXGBsbs2XLFpo1b4K1nTktWjXPk9fy8/JnccAymcgnkYRIJGL3zr04O7ilhiq2akZAUN6EKr5++Zo5M3V4cF/6+SSSev/uA67OnuzauQd1dTUMTeczeer4PHmt9PkkIzAw0ZVaPokkvoUqOti6EBr6iaZNGxOwNG9CFUNC3qE1U4c7MpBPIql0oYpFVNEzmMvM2dPy5LVS80l8iY2NlXo+iSTEYjGHDx7FwcaFd+/e06BRfRYvXZgnOXIf3n9Ea7YuN6/fonTpUphLMZ9EUp8/h+Hl7sum9VtRUVFBa95s5urmTY7chnWbcXFwJyZG+vkkkhCLxZw4fgo7KyfevA6hbt3aBCzzo0aN6rn+Wj/mk5hZGefLBbHc9CX8C75e/qxdvSE1R272VPQM5uXJe9i2eQcOti5ERUVLPZ9EUj/myPkv8aVuHtzaHvElgnma+pw/f4lixYphYjafUf+OkLnRN5mJjIhkoW8gK5evoZBSISZNHY+phWGe7Fu7/9uLtYUDkRGR9OzVHQsbE2rUrJ7rr5OXLpy7hI2lA08eP6Va9ar4L/ahYePcv7gWFRmN3lwDTp86h5paEQxN9Rk7frTMjb7JTHR0DAELg1gWtBJFRUXGjh+FlZ15nuxbhw4cwdzYmvDwL3Tu2hFrO3OZyo7MisvBV7G1dOT+vQd5miOXlJTE2tUb8PPyR0FBEVtbW7S1tWV+sIasEzqXctHp06fR09Pj+vXrDB0+CGMzAypULJ8r2z5x7BTGBhZ8lrF8EknFxMSw2H8pQYGpw2tHjRmOraNlrpwsfswn0Z2vzZTpk2Qin0RS165ex9bSkTu371GpckX8/D1o2Tp3QhVlNZ9EUnFxcSxdvIKAhUsQi0UMGT4YZ1e7XNm3EhMTMTe2Zvd/+1BSkq18EkndunkHWytHbly7Sfny5fFe6Eb7jm1zZduXg6+ip23Iu3fvadqsMbYykk8iqR9z5PoP6otbLuXI/ZRPoj2T2VrTZSKfRFJ5mSMnq/kkkkpMTGTNyvX4eC78miPXCw+fBbky+upbPsmG9VsQi8QylU8iqUcPH2Nv48z5sxdzPUfux3wSO0erXDsmSsOPOXLde3bFe2Hu5MiJRCIWOHmwZuV6klOSmTZjMnN1NaUymUxuefb0OQ42Lpw6eYbiJYrjlIs5co8ePUFrpk7qZDI1v04mIydT12ckOTmZzRu34e7iRUxMbOrsof5eFCue8///IpEIH8+FLF28kqSkJCZOHofufG2p5ojl1MsXr3Cyd+Xo4eNoaBTDxsEy13Lknj9/gdYMHR4+fEzVan9hbW9Oj57d5OrC1PdSUlLSZg/Nixy5UyfO4Gi3gOfPXjBz5kwcHBwoW1Y2Z4+UN0LnUi5LSUlh5cqVmJubEx0Tjab2zBz9+EzNJ5nHvbsPqFixAlZ2ZvzT92+5PVj86PWrN7g4unFw/xGKFSuKpa0Zo8YMl3h7P+aTGJnqy+xUs9n1LVTR2d6NL18iaN2mJf5LfChdWrJsn/fvP6A5U4dbX/NJrGzN6D+wb4HZt9KHKqpjamnI+In/Sry9NavWpzWghgwbhIl57nUeS5tYLGbPrv042aeGKjZvmTqiUNLRRaGhn9Cepcu1qzcoVaok5lbGDB42UK5GSGTmw/uPuC/wYse2XbmSI5eaT+JGdHS0TOeTSOJbOKaDrfPXHLmGBCxdKHGOXHh4OHNn63Pp4v/zSUaOHlZg9q1Pnz7j6erLlk3bUFVVYZ6eFnO0Z0q8ve/zSXr36YWFtYnUJyHJLRnlyAUu8aWqhPkrkRGRzNOaz/mzF9OCeMeMHSlXo28yExYWjo/HQtav3ZQrOXL79hzA0syOiC8RdO/ZFUsb03zPWctLJ4+fxs7aKS1HLnCJH7Vq15RoW9HRMejPM+Lk8dOoFlHF0Dh1MpmCMkIi4ksEfj4BrF6xDmXlQl9z5PQlPi4fOXQMMyMrwsLC6di5PdZ25tStVyeXq5aen3Lkgnyo30CyAQOxsbEY6plx5PAxVAoXRs9Qh0lTZGMymdwQFRWNv28gy5fmTo7cs6fPcbJz5cTxU3Tv3h0fHx+aNZPfi56ySOhcyiMRERE4ODjg6+tLhQrlMbU0ytZtM4mJiRgbWLB/z0G5yieR1MXzwdhYOvD40ROqVfuLhYt9shWqePF8MPrzjPnw4QPNWzbD1sGSps0a52HF0hMdHUPgoiUsXbwCBUUF/h07ChsHiywfaJOTkzE3sWHXjt0oKCiiNW8WM+fIfj6JpK5cvoatpQP37j6gcpXK+AV60qJF1k8k165cQ0fbUK7ySSQVGxubFqoIMHzkEBxcbLI86islJQVbS0e2bNqOGPnJJ5HUzeu3sLFy5NaN21SoWB6fRR60bdc6y+vfvnmHuZr6vH71hvoN6mHrYCHz+SSSio+LZ/nSVSzyDSQlRcSgIf1xcXfIcgNYJBLhZO/K+jWb5CqfRFJ379zD1tKRq1euS5Qjly6fpHZNbB0t6dQ573PopCEhIZHVK9bi6+VPUlISffr1xt076zlyIpEI9wXerFq+lqSkJLnJJ5HUg/uPsLN24tKFYEqXLoWbl3O2cuSePH6K1ixdnjx5SrVqVbGxt6B7z655WLH0fLttxsvdT6IcOZFIhJ+3P0sCl5OQkMiESWPRM5wrc5PJ5JYnj59ib+PM2dOS5ci9fPESzZm6PHzwiMpVKmFtZ06v3j0KzEXP7yUnJ7Nx/RY8Fnin5sh165SaI5eN2UMD/ZewyCeQ+PgERo8diYGx7E0mk1t+zJFzcLZm0JABWV7/222vq1eso0qVynh4eDJ8+PACuW9Jm9C5lMcePnyIgcF89u3bT7sObbGyNf1t4O+KpavxcveT23wSSaWkpLBl43bcXDyJiopOHV4b4JVpqOK3fJIb125SpmwZLKxNGDSk/x9xsHj18jVO9q4cOXQMDY1iWNtbMHzkkEzXWb92EwscPYiJiWHg4P6YWhpSqVL+zkQnDSKRKHV4raMHERERtG3fmkWLvTMNVfz8+TPas/S4cvma3OaTSCrkTUhqqOKegxQtqo65tTH/jhud6ToFIZ9EEiKRiN3/7cPZ3jXLOXJfwr8wT2s+F85dophGMUzNDRg5ZniBGSGRme9z5NTU1DAy1WPytImZrvN9Pkmvv7tjbi1/+SSS+JYj52i3gI8fQmna7Pc5clGR0ejONeCMHOeTSCpdjpyqKroGc5k1J/McuYP7j2BhkppP0qVbJ6ztzCUenSJPxGIxRw4dw97a+f85ckv8qJLJMTs2Nhb9ecYcP3oSVVUV9I10mDh5XIEZfZOZn3PkZjFXVzPTdY4fPYmJgQWfP4fRvkNbrO0tqN9AtieTyQ3f58i9fvWGevXq/DZHLj4+HkN9Mw4fOIKycmF052szedpEuY6zyKp0OXLKysyc8/scubOnz2OgZ0rox1Bat2mJjYMFjRrn7yyH0nLm1DlsrRx5/uwFNWvVIGCpX6Y5ct8C+z3d/IiPj8fMzIz58+cX2AvqskDoXMonBw8eRF9fn0ePHjFm7EjmG+tSunT6H7aXg6+iq23I+6/5JHaOVjRr0VRKFUtPZEQkfj4BrFq+FmXlQkyZNhEjs/npDrTJyclYmdmxY9suoGDkk0jq/LmL2Fo48OTJM6rXqEZAkA/1G9ZPt8z16zfR0TQg5E0IDRvVx9bRitZtciezSZ5ERUUTsDCI5UtWoaioyLgJo7G0NUu3b4lEIuysndm0ITWfZOacaWjOnSXX+SSSCr50BVtLRx7cf8hfVauwKNCbJj+MCLx75z5zC1A+iaRiYmIICljG4oBlv8yRE4lEuDi4s3b1hgKTTyKp61dvYGPlyJ1bd6lUqSK+/h60+uGYVNDySST1Y47c4GGDcHGz/2nf8nL3Y/mSVSQlJTFpynh09LXkOp9EUlnJkXv27AVaM3VSp6Cv9hc29hb5MgukrEmIT2DFsjX4+fhnmiO30CeAwEVLSUhIYOz40egb6fzUhv0T3L/3AFtLx685cqXx8HH5KUfu9cvXzJmlw4N7D6lYqSLWdmb07tPrj7jo+b0fc+R6/9MLDx+Xn9rpSwKX4+vlT3x8PCNGD8PIRK/AxFlkx485ci7uDvTu0yvdMu/evUdzhg63b92hXPmyWNma0W9Anz9u30pKSmLD2s14uPlkmiMXfPEy9jYu3Lt7n4kTJ+Li4kLlygUjckCWCZ1L+SgpKYmAgABsbW0RiVKYp6/FxMnjiPgSgdZsXa5fvVkg80kk9fTJMxxsXDh96iwlSpbAydWOfv3/+ZpP4kp0dEyByyeRVHJyMps2bMVjgTcxMbF06doRX38vkpITmTtHn+CLVyhevDimloaMGDX0j9+3Xjx/iZO9K8eOnEBDQwM7J0uGDBvEjm27sLd2KpD5JJJKSUlh25aduDp7EhkRSfuObVkU6I2iomJaPknRouoYmc0vUPkkkvpVjlxBzyeRxLccORcHd8LDv9CqTUv8g3xQVVVFf64hJ0+coUiRIhgY6xaofBJJ/ZgjZ2JhwIRJYzn8NZ8kPCycTl06YG1nTp08mBFMnojFYvbu3o+j3dccuRZNCVjiRzGNohjqmnLkyPECmU8iqe9z5IqoFcHASJdpMydz6sQZjPTN+PTpM23btcbGwYIGP1y8+tN8y5FztHXh/fsPaTlyZcuWxmi+OQf2HqJQoULM09Ni2oxJBTbOIqs+ffqMp5svWzam5sjN1dNEU3sW589dxEDHhA8fPtKiZepkMk2ayu9kMrnhW46cvY0zIW/eUq9+XQKX+lK5SmXMjK3ZtWMPSkqKaM2bzczZ0+R6MpncEB4ejo/HItat2ZguRy7kTQgujh7s33uQNm3b4OfrR/v27aVd7h9D6FySgk+fPmFlZcWSJUsoU6YM4eHhiBEzR2sGs7VmFNh8EkmdOHYKO2snXr18jYqqCgnxCan5JI6W2co3+RN8Cf+Cn3cAa1atp1AhJUSi1K/s9FlT0Jo3u8Dmk0jqzOlz2Fk68ezZ87R9q3btmtg6WdGxk3Ai+l5kZBT+votZsWw1ioqKiMViRCIRU6ZPREdPK9PbV/9Ely4EY2PpyKOHj1FVVSE+PoHqNaphY29Btx65M2NaQfF9jpxYLEZJSYmkpKQCn08iqe9z5FRVVUhISKRylUrYOFjQs1f3P+4qdmbi4uIIClhO4KIliEQiChVSIjExiTHjRjLfqODmk0jq+xw5FVUVEhMSqVChPFZ2ZvTp11vYt77zfY5ccnIKhQoVIiEhgRGjhmJkqk+58gU/ziI7vs+R+7ZvlSlbBksbEwYO/jPiLLLq+xy5xMRECikXIiE+gcFDB2JibkDFSr++NfpP9H2OXPESxYmPi6NUqdK4uroyfvz4P/6Cen4TOpek6NatW3Tv3p3yFcoRtHzRH5FPIqnExER8vfwJXLSE2ZrTMTTV/+NHSGTm8aMnTJ88h/CwL+w5uJ3qNapJuySZlZycTMDCIHw8FzFx8jis7Mz+iHwSST1/9oKZU7V4+/Ydew5s/yPySSSVkpLCsqCVuDp7MnzUEFzcHP740TeZefXyNYP6jUBdXY0Va5b8EfkkkhKJRCz0DsDX25+Zs6cx31j3j8gnkVRIyFsG9x2BopISq9Yt+WPySSQhEolYsXQ1zg5uTJoyHjNLoz9+9E1m3r/7wJD+I0lMTGTV+mU0a95E2iXJLLFYzOaN2zA3tmbM2JFY25sL2TeZCP0YytCBo4mMiGTV+mW0al0wJ5PJDWKxmEMHjqA1S5eBAweyceNGihYVLqhLQ3b6goRuv1zWtGlTGjVuRIOG9YSOpd8oXLhw2tX+9h3bCR1Lv1Gnbm1q1KhOsWJFhY6l3yhUqBA9enUHoE27VkLH0m/UqFmd2nVqoaamJnQs/YaSkhI9/+4OQMtWLYSOpd+oWu0vNDSKUbXqX0LH0m8oKirS8evscV17dBY6ln6jcuVKlCxVkkqVKggdS7+hqKhI56/ZZl26dRI6ln6jQsXylC5TmjJlywgdS7+hoKBAj56p2WadunQQOpZ+o2y5spQvX44SJUsIHUu/oaCgkJZRNWLECKFjSU4InUsCgUAgEAgEAoFAIBAIBAKJCZ1LAoFAIBAIBAKBQCAQCAQCiQmdSwKBQCAQCAQCgUAgEAgEAokJnUsCgUAgEAgEAoFAIBAIBAKJCZ1LAoFAIBAIBAKBQCAQCAQCiQmdSwKBQCAQCAQCgUAgEAgEAokJnUsCgUAgEAgEAoFAIBAIBAKJCZ1LAoFAIBAIBAKBQCAQCAQCiQmdSwKBQCAQCAQCgUAgEAgEAokVknYBgtwRFRXN+jUbOXr4OC+evyQ6OppSpUpRvUY12rZvw7QZk9AorvHTetHRMSwLWsnB/Yd58zoERSVFatSszqDB/Zk0dTyFCxeWwrvJvri4OC5duMyd23e5c/sed27f5W3IOwB09LXRM5j7y3UjIyK5dPEyd27d5c6d1HVDP34CwM3LmZGjh/329ZOTk9m+9T/27t7Pg3sPiYiIREWlMJWrVKZjp/ZMnjaBatWr5s6bzQc5+Ty/CQ39xJLA5Rw/epK3Ie9QVVWlTr3ajBg5hNFjR6KgoJDXbyPP1azSIMvLtu/Qlg1bV6d7LDf2PVmTk33n0oVgzpw+z+1bd3j18jXh4V+IjYmleHEN6tStzT99/+bfcaNQLaKa4fovnr/k6OHjXLwQzIP7D/kU+gklpUKUr1CONm1bMWHyOJo0bZQn7zsvhIeHc/TwCc6fvcjdO/cIefOWlJRkSpUqRZNmjRk+cgh9+vXOcN1tW3ZiPN/8t6+xZuNyOnfpmNulS9WZ0+fYvGEbN67f5NOnzyigQLnyZWnRsjljx4+iXYe2ma4v6flUluTGMfxHFqa2bFy3GYDKVSpx5uKxn5Z58zqErh3+zvI2R4wehruXc7ZrkQWBi5bivsAr7d/P3tz/5bIFpa0F0m0fhH4MJfjSlbTXvXv7Hl++RACwYctq2nfM/LstDbn1XQz9GMra1Rs4efw0r1+FEB8fT+kypahduxbtOrRlxuwpKCsrp1vn/bsPHDl8jIvng7l35z7v338AoGy5MjRv2Yx/x42iY6f2ufuG81BenNemTpjFqZNnAGjXvg0bt63JUY35SZq/fQpae0uQe4TOpQLgwrlL6M415FNo6kGhcGFlVIsU4f37D7x//4GLF4L5p28vGv7QGA55E8LYUZN58zoEgCJFipCYmMjtm3e4ffMOu3buYd2mlRQvUTzf31N23bx+m2mTZku07uFDx7J0svqViC8RTJ04ixvXb6U9VrSoOvHxCTx6+JhHDx+zYf1mvHxd6T+wr8Svk59y8nkC3L51lynjZxAe/gUAdXU1YmJiuBJ8lSvBVzmw7zBLVvrLVYM6I2XKlsn0+eSkpLSGb9NmjX96Pqf7nizKyb6zZPEKThw7lfZvNTU1ChcuzOfPYXy+EMzFC8GsXL6GleuWULNmjXTrXrl8jdHDxqd7rGhRdRITE3nx/CUvnr9k+9b/0J43G30jHYnqy2/tWnQlOTk57d8qKioUKqScdmw/cugY3Xp0IWCJL0WKFMlwG4qKipQqXeqXryHv38HvicViLM3s0jpAAFRVUzsiX796w+tXb9j9316mzZyMpY1phtuQ9Hwqa3J6DP/RhXOX2LR+y2+XU1RS/O1xMSEhgajIKCDj46I8ePb0OX7e/llatiC1tUC67YP1azdn+XOXFbnxXdy7ez/mJjZER0UDqecC5cLKvA15x9uQd5w+dZbxE8egXPz/nUtv376jS7teiMXitMeKFCmCWCzmzesQ3rwOYe+u/YwaMxxnN3uUlJRyVGN+yq3z2rYtO9M6luSRtH77FMT2liD3CJ1Lcu7K5WtMnzyH+Ph4+vTrjebcWTRp2ggFBQXi4uJ49PAJRw8fo1ixYunWS05OZsYULd68DqFc+bJ4+Cygc5eOiEQi9u89iLmxNXfv3Edfx5gVa4Kk9O6yp3jx4jRq0oDGjRvSqElDHO0WpPXC/07ZcmVo2KgBjZs0pHGTRmjOzPrB0MHWJa1jSXf+XCZNHUfJkiVJSUnhSvBVbCwdePTwCYZ6ZrRs1YIKFctL9P7ym6SfZ2RkFDOmzCE8/Au1atfE09eVps0ak5iYyKYNW3Gyc+X0qbM42Lrg4GyTD+8k7wRfz7xRsixoJc4ObgCMHjsyw2Vysu/JKkn3nU5dOtC1W2dat21JterVKFpUHUgdwbN75z5cnT15/eoNmjPmceDobhQV/39nd3JSMkpKSvT6uzuDhw2iQ6e2ad/DO7fv4WTvypXgqyz0DaRSlUqM+cX/D1mSnJxMs+ZNGTF6KF27daZqtb+A1NEhi3wD2bJpO6dOnMHCxAYvP7cMt1GxUoUMR5gURNu27EzrWOo3oA+GJnrUqFkdSO0McHX25MihY6xYupo2bVv9NOpL0vOprMrJOfF7cXFxmBtbU6hQIeo3rMftm3d+uWylShV/e1y0tXRkzar1qKqqMmTowGzXI20ikQgTAwsSEhJo2ao5167e+OWyBbGtBdJrHygoKFCxUsWv58uGlCtXFjNj67x4i7kqJ9/F/XsPojfXCJFIxNjxo5kyfSJ16tYGUkfE3bt7n8MHj1JIOf1POlGKCLFYTMfO7Rk+cgidOnekfIVyiEQinj55hoerD0cOHWPr5h2Ur1CO+Ua6uf6+80punNdCP4biZOeKRnENypUry5PHT3Opuvwljd8+BbG9Jcg9QueSHIuLi8NQz5T4+HgmT52AjYNFuueLFClCs+ZNaNa8yU/rbt/6Hw8fPAIgYIkvLVu1AFKvBgwc3B+RSIzeXENOHj/NubMX6NS5Q96/oRxo064V1+9eTPeYm4vXL5ZOb9iIwRLffpSQkMjePQcAGDFqKLrztdOeU1JSol2HtgQt96dH5z7Ex8dz/NhJxk0YI9Fr5aecfJ7LglYQ+vETqqqqrFgTxF9VqwCpV5ImTRlPdHQMHgu82bR+K1NnTPppBEpBsmXTdgBat21FzVo/v8+c7HuyKif7zrQZkzN8vGTJkkyeNoHChQtjYWrD40dPuXb1Bq3btExbplr1qhw+sTetM+EbJSUlmjVvwrpNKxg6YDQP7j9k8aKlctHYWb95FR06tfvp8Sp/VWaBhyNKhQqxcd1m/tuxB0NTfSpVqiiFKmXHzm27gNR9wdffg0KF/t/EqVmrBosWe9O7+wBevXzNvr0H03Uu5eR8Koty8j38kYerDy9fvkJbZzbv333ItHPpdxLiE9i1cy8Affv3lvnbCzOyesU6rl65zpBhg6hWvWqmnUsFra0F0m0fzNWdk66d9W00mCzLyef18cNHLExsEYlEmFubMGPWlHTPFy2qTtt2rWnbrvVP62oU12D3gW00bpL+1iRFRUXq1K3N4mULmTZxNqdOnmHlsjVoz5uDiqpK9t6cHLMytyciIgIXN3v+27FHLjuXpPXbpyC2twS5Rwj0lmM7t+/m1cvXlC1XBlMLw2ytu2PbfwB06NgurbHzvUFD+qed9L812GVZTobz5mTdyIgIEhMSAWjSNOPh/dWqV6XE1+HusTGxEr9WfsrJZ7Lj6/4y8Lt96HuTp45HXV2NlJQUdu3YK/HryLqrV66nNVZ+dWKVp2HoWZWX76l5y2Zpf79/9z7dcxUrVfipofO9woULM3T4IABevnxFxNfbFWVZRh1L3xv974i0v3Pyg7+g+PgxFIAGDeun61j6RllZmQYN6wM/H4tzcj6VRbn1Pbx+9QarV6yjRs3qzNXRzPH2Dh44QkRE6ndPHn9wvH71Bk83X0qWLIGlbca3Vn6voLW1QLrtA3k8Z+ak5lUr1hEREUGjxg2YPjPjiy+/oqFR7KeOpe8pKCgw6t/hAMTExPLkifx1rkhq354DHD54lHbt2/xyVLk8kNZvn4LY3hLkHqFzSY59a4j0H9A3W1cb4uLiuHr5OgDdenTJcBkFBQW6du8MpIajCjJWpmwZ1NTUALh9K+Mfdy9fvErL3Sno4XbPnj5PCxPs/ot9S11dndZtWwFwtgDvW1s2bgOgmEYx+g/sI+VqCobLwVfS/q5aLfsB+Soq/z9OpohEuVKTNKV7Pyny/35y6tuP1fv3HqTLqvomKSmJ+/ceAD9fDJD0fFqQJSQkYmJoiVgsxtnVLlc+l2+jOavXqPbbYHVZZGZsRWxsLBY2JpTOJPMFhLbWj4T2QfZ9Oy4NGT44TyZB+RPPIeHh4dhaOVFYpTBObnYFYnIZWVTQ2luCrBM6l+RUQkJiWmdG46aNCAl5i7mxNZ3a9KBejaa0ad6ZGVM0OX7s5E/rPnn8DNHXL3rdenV++Rrfngv9+IkvX4MXBekpKCgwdsJoIHX4u6+XP+Hh4QCkpKRw6UIws6enDuHuP7CvXDams+Phg8dpf2e2b9X7+txjORyGnBUxMTHs33sQSL0y/auwZcHvxcfF8/zZC/wXBqXlV7Vt11qiIOCLF4IBKFe+LCVLlsjNMqXi0tf3A1C/Qd0Mlwn7HM7gfiNoXLcVDWo1p1vH3ujPM+bi+eAMl5dnEyaNBVI79HW1DXnx/GXac8+ePmfeHH1evXxNtWpVmfbdKICcnE8LsoU+ATx5/JTR/47IlXPXq5evuXj+EpB+1J282LR+C+fPXqRTlw4MHzn0t8sLba30hPZB9rx+9YYPHz4C0KRJQx7cf4SutiHtWnahfs2mdGzdnXma+ly5fE3i1/h2TixcWDnTkSiyJifnNTsrZz5/+sw8Xc0CHcsgbQWtvSXIOiFzSU6FvAkhMTEJSG2w2Vk5Eh0dQ+HCyhRRK8LnT585fvQkx4+eZMzYkTi72af1zn/8erICKF/h1+HSFb577sOHj5QQDg4ZMjTWIzwsnB3bduHrtQhfr0UULVaU+Lh4kpOTqVrtL0zMDZgxe6q0S81zWd23vj0XHRVNTEwM6urqeV5bftq7az8xX2+7GTN2lJSrkT+hH0Np17Jrhs/16t1DoqnLr129zpFDqQGgY/799VTX8iIyIpJA/yVAau5CRplekDp64s7texQvXpzk5KS0WdN27dzDyDHDcXa1y/AWMnnUq3cPLG1NcXP25MC+QxzYdyhttrj4+Hg0imswftK/GBjpUqxY0bT1cnI+Laju3rnHksDllClbBjNLo1zZ5tbN2xGLxRQqVIgRo4bmyjbzy/t3H3Bx8kBVVRWnBXZZWkdoa6UntA+y5/mzF2l/X7lynYXe/iQmJqGqqkphFRXev//Avj0H2b/3EHoGc5mnp5Wt7b9+9YYNa1MnQBgwqF+6Y6Ksk/S8duzICXb/t5e69eowS3O6FCr/MxS09pYge4SRS3Lq+/tX/f0WU6hQIRYt9uH2w6vcuHuJM5eOpU17v3njNpYvXZ22fHR0TNrfRYqo/vI1VL97LiYm5pfL/elUVFVwcXfAzNIIZeXUaWCjo6LTbsuIi4vjy5cIEhMTpVlmvoiOydq+9f1zMdEFb9/a/PWWuAYN6xf4WyHzgqKSEmXKlqFM2TLphlb3H9gXUwvDbP/4+vw5DF1tQ0QiEdVrVGOWlnw3KkUiEfN1Tfj4IRQVFRVsHax+WqZ8+XLo6Guz7/B/3H96k+t3L3L38XW2/reBTl1SQ4O3bd6Bo+2C/C4/T02bMZmApX6ULlMaSO1Uio+PByApMYnYmFiivk7n/U1OzqcFUXJyMiYGliQnJ2Njb54rodspKSls3/IfAD16daNsubI53mZ+sjC1ISoyCt352mmzNv6O0NZKT2gfZM+3bDIAb3c/ypUvx5qNy7nz6Cq37l/m0PE9tO/QFrFYjLfHQg7uP5zlbcfHxaM9R4+4uDhKlSqJsZlBXryFXJeT81pkZBSWprYoKiri4maf1l4X5K6C1t4SZJ/QuSSnRGLx//8WiVjg4Uj/gX3SDpaVK1fCL8AzLbw0cGFQhhkUgpx7/eoNg/uNxMXRnT79e7Nr/zZuP7zC2eDjuHu7oKCgQFDAMsaMmFigG46CVI8ePubG9VuAfAbWyoLSpUsRfP0MwdfPcO/Jdc4Fn0BbZzbHjpygf++hbFy3JcvbiomJYdZULULevKVoUXX8g3zk/kq4vbUzx4+eBMDOyYoGDev9tEyXbp3QM5hLg4b1UFEpDKQGeLZq3YLV65fRu08vANat2ZjuCrk8i4uLY56mPjMma1KpckVWb1jGlVvnuXLrPKs3LKN23Vrs3L6bYQNHc//ew7T1hPNpeov9l3Lv7n16/t2dAYP65co2T508w/v3HwAYPVa+bon7b/tuThw7RcNGDZj+w2xdAkFeEYn+f1wSi8UELPGlc5eOKCqm/nSrU7c2S1cFULZcGQD8vAOytN3k5GT05hpy59ZdlJWV8V7oTvkK5XL/DeSBnJzXnO1d+fDhIxMmjaVFq+b5XPmfoSC2twTZJ3Quyanvv6zVa1Tjn75//7SMoqIiM7/eihUe/oU7t+4CqVOXfhMXF//L14j/7jnh4JCxlJQUZk3T5uGDRwwfOQQ/f0+aNG2Euro6lSpVZMSooazduILCKoW5c+suQQHLpF1yniqqnrV96/vn1IsWrH3r26glFRWVtNkyBJJTUFCgYqUKGBjr4b3QjaSkJKzM7dKCmTMTGxvL9ElzuH7tJurqaixfE5TWQSCvnB3cWLNqPQCWtqYSZdcoKiqm3eokEok49rWjSt65OLqzb89BataqwZbt6+jStROlSpWkVKmSdOnaic3b1lKjZnXCwsKxsXRIWy8n59OC5vGjJyzyDURdXQ17Z+tc2+6WDanHxQoVytO9R8a3vMqi0NBPONi6oKSkhLObfbZuIRXaWukJ7YPs+X7/6di5fYYzv6mrqzNx8jgAHtx/SGjop0y3mZKSgv48Iw4fOkahQoXwXuhOl26dcrdwKcnsvHb2zHm2bNpOxYoVMDTVl1KFBVtBbG8JJCN0LsmpCt9dZahVu+Yvl6tdt1ba3yEhbwEoV/7/6374eiUxI++/e658efm4qpHfzpw6x8MHjwCYMXtahsvUqVubHj27AXBw/5F8q00asrpvfXuuaLGiBaoxnZiYyK4dewDo2/+fXLmdRPB/ffv/Q6XKFRGJRGzZuD3TZb81dIIvXUFNTY3lqxfT5ussRPJqgaM7y4JWAmBuZcy0Gdmbmvp71WtUo1SpkgC8fvk6V+qTpujoGDat3wrAxMnjMpzZTLWIKpOmjAfgSvBVPn36DOTsfFrQ2Fg4kJiYhNa8ORQvrkFMTEy6/5KTU4DUkRTfHktKSsp0m6Ghnzh+7BQAI0YPlavp5N1cvAgP/8K/40dRq3aNnz6P79/7t8e+3QIvtLXS+9PbB9n1/Wii2rVr/XK52nX+/9zbN78+LqWkpKCvY8y+PQdRUlLCy8+1wM1k+6vzmrlxake5iYUhCgr89D3+NptZikj0/8dSUvL/DcipgtjeEkiuYKR4/oFKlCxBhQrl0zVKMvLdaP+0QLXadWqiqKiISCTi0cPHdO+Z8VXERw9TZ/YoW65MgQ2YzKkn381mUq36r3MYqteoBqTeQleQ1av//xlgHj18nK7R872HX/etOr94Xl4dPXycsLDU2QKFW+LyRoUK5Xkb8o4XL17+cplvDZ1LFy9TpEgRlq8OpG37NvlYZe5zcXBnadAKAEwtDP+ICQKy4/mzF2m3qmWWifPtWAzw5tUbypQpnaPzaUHz+nXqOcp9gRfuC7x+udzbkHc0qdcaSB1Bl1lH585tu0hOTkZBQYFRY+Trlrg3X8/Z69dsYv2aTZku++3zmDJ9ItZ25kJb6wd/evsgu+rUqY2SktJvOzm+Py7xi+PStxFLe3cfSOtYGji4fy5WK9vevA4BQG+uYabLXQm+mvY9XrxsYYajWAXpFcT2liBnhJFLcqzz16GsTzKZrvXJoydpf1f5qwoARYoUoVWbFgCcOnk2w/XEYjFnTp0DoEvXgjFkNi8oKP7/RB6SyRWjb1fIixbwId41alanUuWKAJw6cSbDZWJjY7kSfBWAzgVs3/p2S1y16lVp10E4ueY2sVic9uP3V9+l2NhYpk2czaWLl1FTU2PFmsW5Mo26NDk7uKXrWMqNWW5evniV1hH6V9UqOd6etCl+fyzOZFTRt2MxpL/lRtLzqeD3tmxKHWXYvmO7LIdhFwRCWyu9P719kF0qqiq0bZfa0fHkSSbHpcepxyUFBQWq/FX5p+dTUlLQm2uYrmNp0JABeVO0lBW085qsK4jtLUHOCZ1Lcmzk6GFA6sH08MGjPz0vEolY+vUWigoVytO4ScO054aPHArAxfOXuHHt5k/r7t97kFdfh5QOGzkkt0svMBo3/v9n+qurmqEfQ9P+/xT0EEEFBQWGf91f9u4+kHa16HtrV20gJiYWJSUlhgwfmN8l5pmQkLecO3MBgFH/jiiwIxvySlYCkrdu3kHox9RMiYwaMN8aOt+GZheEho6zg1u6W+Gy0rEkTncpO+PnXRzdgdScip5/d89xndJWq1ZNVFVTZ5nasnFbhvtTSkoKm9anhsEXL16cmrVqpD2Xk/NpQXLm4jGevbn/y/9GjBoKQOUqldIey2zU0uXgqzx7+hyQz9GcG7etyfTz0NHXTlv222PWduZpjwltrf/7k9sHkvp2XDp/9iJ3bv+c8xYTE8O6NRsBaN6iKaVLl0r3/LcRS/v2HPyaseQmtx1LOTmvZfYdfvbmPu2+jrRp175N2mPCqKXMFcT2liB3CJ1Lcqxtu9b0G5B6v7SZkRUH9h1Oa1CHhLxFV9uAB/dTZ8QxMNFLm2ECYMSoodSrXxexWIzWLF3OnU39USwSidi/9yBmX+9P7tajC506d8jPtyWxiC8RhIWFp/33baaN+Li4dI9nNGPb989/u+oBEBsTm+7xuLi4dOu1adc6LbBuzar1ONot4MP7jwAkxCdw6sQZxoyYSFRkFAoKCkyfKXlGSn6T9POcMXsaZcuVIS4ujumTZ3P7a/BtYmIi69ZsxNvDD4B/x4+iZs0aFBRbN+1AJBJRqFAhRn79AZYVku57skySfedK8DXGjJjAzm27ePf2fbrtPX/2AldnTyxNbQGoVq0qI0cNS7dMXFwcMyZrEnzpCurqaqxYGyT3Q7O/z1iysDHJ8q1wIW/eMnTAaDas28yrl6/TGuUikYjrV28wdcKstA6UsRNGp+tkkVeqRVTTOi/u3L7HzClaPLj/CJFIhEgk4v69h0ybNJurV64DMHXGxHTZPzk5n8qqnJwTc8uWr6M5S5QoTp9+vfPsdWRVQWxrgfTaByKRKN32IyIi0p6LiopK91xCQmJevf1sk/TzGjJ8EM2aN023/4i+5gM9efyUWVO1Cf34CUVFRQxM9NKt+y1jae/uAxQqVAifRe5yfSvcn3heywpp/PYpiO0tQe4RMpfknLu3M58/fSb40hW0Z+tSWKUwRVSLpDvh6uhrp11t/KZQoUIsXRnAuNGTefM6hIn/TqNIkSKIRCISEhIAaNS4AT4L3fPz7eTIwL7DM7w1bcniFSxZvCLt3yNGDcXd2yXdMq2bdsxwm7ZWjthaOab9W0dfGz2DuWn/VlRUJGCJL5PHz+DVy9esWLqaFUtXo66uRlxcfFojQElJCQtrE7nq1Zf089TQKMayVYuZMn4Gjx89ZUj/kRQtqk5CQmJa+GmXbp2wtDHL+zeRT0QiEdu27ACge8+u6YJLf0fSfU+WSbrvXL50lcuXUm+JUFFRQV1djdjYOOLj/z97UIOG9QlavgjVIqrptn1g3yEuXggGIDk5hblzMp8RJnCpH61at8j+m8snISFv0z4rRUVFggKWExSw/JfLz5w9lZlz/j+pwK2bt7l18zYAhVUKU1RdneiYGBK/+8E1csxwbOwt8ugd5D8TcwNePH/JqZNn0v4r/HW66u/f96AhA9DWmfPT+pKeT2VVTs6JuSEqKpr9ew8BMHT44LSpw/8kBbGtBdJrH7wNeUfXDhmPKJk9Pf350c3LOW3kj7RJ+nkpKiqyZMUiJvw7lcePnqbtP4WUCxEVGQWAsrIydo6WdOzUPt22r16+xt5d+4HUUWO2Vk7YWjn9skZrOzOZ73z6E89rvyON3z4Frb0lyF1C55KcU1NTY8PW1WzdtJ2d23fz6OFjYmJiqVChPK3btWLy1Am//EJX+asy+4/sYuniFRw6cIQ3r0NQVi5EnXq1GTxkAJOmjqdw4T+vMZhd1apXZf+R/9i0YStHDx3n0cPHREZGoaKiQqXKFWnbvg0TJo2lQcN60i413zRp2oiDx/cQFLCM40dP8u7te4qoFaFZvaaMGDmEUf+OkIsr/1l17swF3oa8A+Tz1g9Z0LhpI7x8Xbl4IZjbt+4SGvqJL+FfKFy4MNWqVaVRk4b07d+bfgP6ZDjb1LerdQAJCQkkhCZk+npJiZnPcCVt4u/ej0gk4tNvppiOiYlN+7tMmdLYOlhy7eoN7t+7T9jncCIiIlFRKcxff1WhZavmjPp3BK3btMyz+qVBtYgqK9YGcWDfYXbt3MOdW3f5/PkzKChQsVJFmjVvwsgxw+jZq3uG6+fkfCr42d5d+9OueI/+g4+LQlsrvT+tfZBTZcuVZfeBHaxdtZ69uw/w/PkLEuLjqfJXZTp0bMe0mZOpV7/uT+t9f05MSkr67TkkPj7zc6a0/annNVlU0NpbgtylIP7dTaxAZGQkxYsXJyIiAg0NYWrt3+nStQtly5XC09dV2qXIvOBLV/h3xERWrl1Ctx5dpF2OzJs8bgaPHz3h/JWT0i5F5t2+dZch/UfiF+Ap81fjZMGcGfO4cvkaV26ek3YpMu/xoyf06TkIxwW2jJswRtrlyLwu7XtRuXIlNm1fK+1SZN7l4KuMGT6BtZtWyNVtUtLyd7f+qKursWv/NmmXIvMePHhE/7+HsHRlAL1695B2OTKvf++hJCUlceTkPmmXIvM+vP9Ih9bdhPZWFg0fNIbQ0E+cuXhM2qXIvJSUFOpUa8zKlSuZMmWKtMv5Y2WnL0i4NCAQCAQCgUAgEAgEAoFAIJCY0LkkEAgEAoFAIBAIBAKBQCCQmNC5JBAIBAKBQCAQCAQCgUAgkJjQuSQQCAQCgUAgEAgEAoFAIJCY0LkkEAgEAoFAIBAIBAKBQCCQmNC5JBAIBAKBQCAQCAQCgUAgkJjQuSQQCAQCgUAgEAgEAoFAIJCY0LkkEAgEAoFAIBAIBAKBQCCQmNC5JBAIBAKBQCAQCAQCgUAgkJjQuSQQCAQCgUAgEAgEAoFAIJCY0LkkEAgEAoFAIBAIBAKBQCCQmNC5JBAIBAKBQCAQCAQCgUAgkJjQuSQQyBGxWCztEgQFlFgsFvYvQZ4R9i1BXhH2LUFeEfYtQV4R9i1BQSV0LuUBBRS4d/cBL56/lHYpMi0qMhpvdz8UFRVZGrSChIQEaZck0w7uP8LVK9f49Okzp06ckXY5Mi02NhaPBd4oKCqweuU6YmNjpV2STDt+9CTnzl4gKjKKwwePSrscmRYfH4/b131r4/otREfHSLskmXb29Hk+fgjl1s077N29X9rlyLTExEQC/ZegqKiIj+ciIiMipV3XaJD8AAEAAElEQVSSTAu+eJk3r0N49OgJO7btknY5Mi05OZlF3gEoKiri5xNAWFiYtEuSadeu3eDF8xe8fvWGTRu2SLscmSYSifB080VRUZGARUsI/Rgq7ZJk2p3b93j44DEfP4SyesVaaZcj08RiMQf3H5Z2GYJsEjqX8oC+vj4x0bH07TUYV2dP4cfHD0QiER6u3rRt0ZnLwVdp2641589epFWTDiwLWint8mTOs2cv6NNrEFqzdChbrixly5Vl2qTZDOo3gjevQ6Rdnszx8w6gddNOnD1znvbt23Ltyg3aNOtEwMIgaZcmc16/fM2APsOYOVWLEiVKUKFieTRn6tDv7yG8fCF0jv8oKHAZrZp05PiRE7Rv35b7dx/QpnknvDz8EIlE0i5Pprx9+46hA0YzefwMSpUuScVKFdDRMuCf7gN48viptMuTOauWr6Fl4w6cPHaatu1ac/3qDdq17IKrk4ewb/0g9GMoI4eOY9zoKWgU16BKlcoY6pnSs0tfHtx7IO3yZM6GdZtp0bg9+/cdok3bVty/+4COrXtgb+0k7Fs/CAsLY+zISYweOh41NTVq1KyOubENXTv05taN29IuT+Zs3/ofLRq3Z9uWHbRu05Knj5/RuV0vLE1tSU5OlnZ5MiUyIpJJ46YzdMAolAsrU6dubeysnenctidXL1+Tdnky597d+4wdNZl5mvMZOHAAPXv2lHZJgiwSOpfywLBhw3j48CFmZmasWbmev7v2Y9uWncJJHDh86BhtmncmYOESWrdtyYGju9iwdTU7926hTr06ODu40aF1Ny5dCJZ2qVIXGxuL1kwd+vQcSMjrECxsTDh8Yi/HTx/AwESPJ4+f0rNLX/TnGZOYmCjtcqXu1IkztG3eGR/PhTRr3oS9h3ayfssq9hzcTqPGDfFw9aFdiy6cOXVO2qVKXWJiIrpzDenVrT/Pn77AyFSfY6cPcPTUfkwtDHn18jW9uw9k7hx94uPjpV2u1J0/d5H2rbrh6uRJg4b12LV/K+u3rGLf4Z20aNmcRT6BtG3RheNHT0q7VKlLSkrCSN+M7h3/4eGDh+gbzuPEmUMcOr4Haztz3r3/QL+/hzBrmrZw4QW4evkandr2xN7GhZq1a7Bj9yY2bF3N4RN7ad+hHUGBy2ndrBMHhKu3JCcnY2FiQ+d2vbh98w7a82Zz8twhDh7bjb2zNWGfwxjUbyTTJs4iKjJa2uVK3c3rt+na4W8sTW2pWvUvNu9Yx8Ztazh8Yi9dunVi1Yp1tGzcgV0790i7VKkTiUTYWTvRsXV3rl65zizN6Zw8f4R9h3fi4u5AdHQ0wwf/y4R/p/Il/Iu0y5W6+3fv07NLX4z0zShfvhzrN69i0/a1HDt9gL//6cGGdZtp2aQDWzdtl3apUicSiVjg5E67ll04f/YiU2dM4vT5I+w5uB1PnwUkJCQwZsRExoyYyKdPn6VdrtR9/hyGhYkNg/qOICoimoMHD7Jnz16qVq0q7dIEWaQgzsJNn5GRkRQvXpyIiAg0NDTyo64C49WrV5iYmLBp0yaaNmuMlZ05rVq3kHZZ+e7li5fMmaHDo4ePqVylEjYOFvTs1R0FBYW0ZcRiMbv/24eTvSthn8No3qIpAUv8KFe+rBQrl46AhUH4+y0mPj6BMeNGMt9IlzJlSqdb5sP7j7i5eLJz+27U1IpgYKzH1BmTpFSx9Lx5HYLWLF3u3rlHhQrlsbIzo0+/3j/tWwf2HcbRzoUP7z/SpGljApb6UqlSRSlWLh3Lglbh7elHXGwcI0cPw9BEj3Lly6VbJjT0Ex6uPmzbvANVVVXm6WsxR2uGlCqWng/vP6I5cx43b9ymbLkyWNqYMmBQv5/2raOHj2Nv7czbt++o36Aei5f68Ve1v6RYuXSsXb0BN2dPYmJiGTx0ICbmBlSsVCHdMmFh4Xi7+7Fh3WZUVAozR2smOvO1pVSx9Hz69BntWbpcvXKdkiVLYG5lzJDhg1BUTH/N78SxU9jbOPPyxSvq1K1N4FI/ataqIaWqpWfLxm042rsSHRVN/4F9MLM0onKVyumW+RL+BT/vANasWo+ysjLTZk7GwFj3p8+0oPsS/gXtOXpcunAZjeIamFoYMmLUUJSUlNItd+b0OewsnXj27Dk1albHf4kv9evXlVLV0rNz+27srByJjIzi7396YmFtQrXq6X/IRkZG4e+7mBXLVqOkpMTEyWMxszL+4/atqMhodLT0OXvmPOrq6hiZzWfM2JEUKlQo3XKXLgRjY+nIo4ePqVrtLxYt9qFxk4ZSqlp69u89hKWpDV++RNCtexes7Mx+On7HxMQQuGgpSxYvRwEFxowbha2DxR+3byUmJrJm1QYW+QSgqKiEnZ0dmpqaKCsrS7s0AdnrCxI6l/LJmTNn0NPT49q1a79sdBdE8fHxGOqZcfjgUZSVldEzmMukqRNQUSn8y3ViY2MJCljOYv+lAIwYNRR7Z+ufTl4F0ZlT5zDUMyU09BOt27TExsGCRo0zPyHfuHYTGytHbt+8Q8VKFfBZ5EGbtq3yqWLpSUxMxMTAkn17DqBUSIl5elpMnzEZFVWVX64THxfPsiUr8fdbTEqKiMHDBuLsakfhwr/eHwuK4IuX0Z1ryIf3H2nWoim2DpY0a94k03Xu3L6LraUj167eoFz5snj6utKpc4d8qlh6kpOTsTS1Zef23SgoKKA5dxazNKdRpEiRX66TkJDIquVr8PXyJzk5mb79/8HNywlVVdV8rFw6rl29jq6WISEhb2nUuAG2jla/vYhy/95D7K2duHTxMqXLlMbdy5nuPbvmU8XSIxKJsLF0ZMvGbYgRM2vOdDTnzkRdXf2X6yQmJrJ29Qa8PRaSEJ/A3//0xNN3AWpqavlYuXTcuX2PubN1efXqDfXq18XO0ZK27dtkus7jR0+wt3Hm3JkLlCxVEhc3e/7p+3c+VSw9IpEIZwc31q3eSEpKCtNnTkZbV5NixYr+cp3k5GQ2rN2Mh6sPcXFxdOveGR9/T4oW/fX+WFA8uP8Q7dl6PH/2glq1amDjaEnnLh0zXef5sxc42i3gxLFTFC+ugYOLDQMH98+niqUnNc7Ch5XL1pCUlMSkqePR1demeIniv1wnJSWFLRu34+biSVRUNB07t2dRoDcaxQv+78hnT5+jOXMejx89pVr1qljbmdOjV7dM13n18jXODm4cPngUDY1iWNtbMHzkkHyqWLpOHDuFk50rL168ZNasWTg4OFCmTBlplyX4jtC5JKNSUlJYvXo1ZmZmREVHMUdrBjNnT0O1SMH88bE4YBkLvQOIj49n5JjhGJroUbZs1g8WIW9CcHF0Z//eQxQtqo6FtQljxo3Kw4ql5+3bd2jN1OX2rTuUr1AOSxsz+g34J90IicyIRCJ279yLk4Mb4WHhtGzdnIAlfj+NdiooVi5bg6ebD7GxcQwbMRhjMwPKVyj3+xW/evf2Pa7Onuz+by/q6moYmxswcfK4PKxYekI/hqI5S5cb125SqnQpLKxNGDx0QJb3LbFYzL49B3C0W0Dox080a96EwKULs/V5y5MN6zbj4uhOTHQMAwb3w9TCkMqVK2V5/dCPobgv8Gbblp0UUSuCnsFcZs6elocVS09YWBhas/S4EnyVEiWKY2ZlzLARg7N8xVUsFnP44FEcbFx49+49DRs1IHCpH1X+qvz7leXQti07cbB1ISoyij79emNuZcxfVatkef3Pn8Pwcvdl0/qtqKiooK0zG22dOXlYsfRERkQyV1Of82cvUkyjGCZm8xn174ifRt/8ilgs5vixk9hZORHy5i1169Vh8TI/qlWvlseVS8eeXfuwMrcnMiKSHr26YWljSo2a1bO8fnh4OL6e/qxbsxHlwsrMnDMNvflzC+ToiajIaPTmGnD61DnU1IpgaKrP2PGjs3UB8/TJs9hZO6V2TNWuSeBSP2rXqZWHVUvPoQNHMDe2Jjz8C527dMTa3jxb7zUyIpKFvoGsXLYGZeVCTJo6ARNzgwK5b8XGxjJfx4RjR06goqrCfCMdJk4el63RNxfOXcLG0oEnj59SvUY1/Bd706BRgzysWnqePnmGk50rJ0+cpkePHvj6+tKkSeYXPQXSIXQuybjIyEgcHR3x8fGhXLmymFoa0n9g3yz/2JN1585ewEDXhI8fQmnZqjm2jpY0btJI4u0FX7yMjaUjDx884q+qVVgU6E2TZo1zsWLpSUxMxNzEht0796KkpIi2zhxmzJoqcYdjTEwMi/2XEhS4HAUFBUaPGYGdk1WBOYlfDr6K3lxD3r19T5NmjbFzsKR5y2YSb+/qlevYWjpw9859KlWuiF+AJy1bFYzbVpOTk7E2t2f71v8AmKM1g9naMyQe7RAXF8eSwBUELlqCWCxm6PDBOLnaFpgRhTev32aepj5v3oTQoGF9bB0tczQC8OaN29haOXLz+i3KVyiHt5877Tu2zcWKpUckEuFg48zG9VsQicTMmD0VrXmzJR7tkBCfwPJlq1noE0BKcgoDBvXF1dOpwIwovHfnPtpz9Hj54hW169TCztGKDp3aSb69u/exs3LicvBVypQtg4ePM127dcnFiqUnNZ/EgzUr15OckszU6ZOYp6sp8WiHxMREVq9Yh4/nIpKSEvmnb288fFwKzIjCR4+eoDVTh2dPU29ts3WwpEu3ThJv7+GDR9hZO3Px/CVKlS6Jq4cTvXr3yMWKpUckEuHjuZCli1eSlJTExMnj0J2vTYmSJSTaXlJSEuvXbMLT3Zf4uHh69OqGl59bgRn19fz5C7Rm6PDw4WP+qloFGwcLevTsJvFvlWdPn+Ng48Kpk2coUaI4jgvs6D+wTy5XLT2LfBcTsDCIhIQE/h0/ivlGupQuXUqibSUnJ7N54zbcXbyIiYmhc5eO+AV4U0zj16MQ5UlkRCS+3v6sXbWBv/6qgqenF0OHDi0wv4MLIqFzSU48fvwYA4P57NmzlzbtWmNtZ/bbW6BkWVbySSSVkpLC1k3bcXXxIioqio4d27Ew0DvTIbmyLiv5JJJ6/eoNzg5uHDpwhGLFimFlZ8bI0cNyZdvS8OnTZ7Rm6XDtyo1M80kkIRKJ2Ll9Ny4Obnz5EkHrtq0IWOJDqVKSNQpkwZaN23C0W0B0dMwv80kk9fbtOxY4erB3937U1dUxszJi3IQxubJtachqPokkvuXIOTu48vlTwciRy0o+iaQKWo5cVEQU87Tnc+7MBdTV1X6ZTyKJn3LkmjTCf6kflSvLb47c/r2HsDC1IeJLBN16dMXK1jTX8qVCQz/h6erL1s3bC0SOXHR0DPrzjDh5/DSqRVQxNNZj3MQxuZJPkpYjZ+PC25C3BSJH7ujh45gaWhIWFk7Hzu2xtjOnbr06ubLt9DlyKszRmiHXOXJxcXEY6ply+NAxVAoXRs9gHpOmjs+1zv70OXK1CFy6UK5z5E6fOoOhnjmfQj/Rpm0rbBwsaJhLI40ivkTg6+3PmpUFI0cuJSWFzRu34eXuR0J8ApaWlujp6RWYzv6CTOhckjOHDx9GX1+f+/fvM/rfERiY6MnV7UyS5JNIKjIyikW+gaxYtppCSoWYNHU8phaGcnWglSSfRFIXzwdjY+nA40dPqFa9Kv6LfWjYWH6G14pEImwsHNiyaTtixMzWnM4c7czzSSQVHR1DwMIglgWtREFRgbHjRmNtby5X+9btm3eYp6mfrXwSSV0OvoqtpSP37z2gcpVKLAz0pnmLpnnyWnlBknwSSRWEHDlJ8kkk9X2OXIWKFfD1l68cudR8Eu+v+STJTJ42AR09rTy5GJIuR04kYvDgATi728vVqK8nj5+iNVuXJ1/zSWzsLfIsfytdjly5rzlyXeQrR87XaxFBActISEhk/MR/0TOcR6lSJXP9dX7MkevTvzfuXs5y9UPw5YuXaM3U5cGDR1SqXAkbe3N69e6RJyMkHtx/hJ2VY1qOnJun029zdmRNoP8SFvkEEh+fwOh/R2Jg8vNkMrnhxxy5Xr174OXnKlc5ciEh79CaOY87t+9RvkI5rGzN6du/d57sW48fPcHBxoWzZ85TsmQJnN3s6dOvd66/Tl66eD4YB1sX7t97wOTJk3F2dqZSpaxHDgikS+hckkNJSUksXrwYa2trUlJSmKenmatXCvLK9/kkAwf3x9TSMF9m4Hr29DkOtgs4deI0xUsUx9HFhgGD+uX56+ZETvNJJPXtSsG3UVKdOnfAL8BT5kMVt23ZiYONC1FRkuWTSOrli1c4O7hx5NAxNDSKYeNgybARg/P8dXMiLZ/k3EWKFct+PomkRCIR27bsxNXJg4iISNq1b8OiIG9Klsz9Hzq5afd/e7G2cCAyIpKef3fHwtokW/kkkpLHHLncyCeRxLccOWcHN8LkKEcup/kkknr/7gOuzp7s2rkHNXU1jEznM3nq+Dx/3ZzIjXwSSaTLkQv9RNOmjQlY6kfFirI9ycqJY6cwnm/O589htOvQFht7C+o3yPvZ3b7lyG3f+h+qRVTlIkcuPj4eI31zDh04jLJyYXTnazN52sRMJ5PJDfKaI3fuzNc4i4+htGrdAltHy3y5k0Iec+QSExMxM7Jiz679KCkpMldXk+kzp+R5fq5YLObE8VPYWTnx+tUb6tWrQ8AyP2rUqJ6nr5tTr1+9wcXRnYP7D9O+fTt8ff1o27ZgRAT8SYTOJTn2+fNnbGxsCAwMpFr1qljYmOToHue8ktv5JJI6deIMdtZOvHj+ktp1ahGwxFfmQhVzO59EUhFfIvDzCWD1inUoKxdiyvRJGJnqy9zInO/zSerUrY2tg2WO8kkkde7sBWwtHXn65Bk1alTHP8ib+g3r53sdmcntfBJJRUVF4++3mOVLVqGkpMT4Sf9iYW0ic/tWbueTSCr40hVsLR15cP+hzObI5XY+iaR+zJEbNXo4to6WMjfqK7fzSSR17ep1bC0duXP7nkznyC3yDSRg4ZJcySeRVFxcHEsXryBg4RLEYhFDhg/G2dVO5vat1y9fozlbl/t3H1CxYgWs7c3p3adXvu9bt27ewdbKkRvXblK+fHm8F7rJZI7cksDl+Hr5Ex8fz4jRwzAy0aNsufy9FTkhPoEVy9bg5+NPSnIK/Qf1xU0Gc+TevXuP1kwdbt28Q7nyZbG0MZVKBqy85MitXrEW9wU+xMbGMnT4YIzN5lOhYvl8rSExMZE1K9fj47mQhMRE/unzNx4+Lnlyt0hOfDt3LwtaRenSpXFzc2Ps2LEy1y4UZI3QuVQA3L59Gz09PY4fP063Hl2wsDaRiU6TjPJJRo4eJtWDRVJSEutWb8TT3ZeE+AR6/t0d74VuMjG8Ni/zSST19Mkz7G2cOXPqHCVKlMDJzY5+/f+Rak2QOvpGR8uAc2cvpM3gNmbsyDwffZOZ5ORkNq7fgscCb2Jj4+jStSO+/l4yEaq4b88BLM3s8iSfRFLPn73A2d6VY0dPolFcA3snKwYPHSjVmiBv80kklZKSwrbNO1jg7ElUZBQdOrVjYYBXvnfeZOTIoWOYGlkRngf5JJJKnyNXFEtbM0aNGS7VmiB19I2hnhlHDudNPokkfsyRa9WmJf5BPjIx6is1n8SMT6GfaduuNTYOFjSQcqf9jzlyJhYGTJg0Vqo1QeqPSGMDC/bvOYhSISV09LSZNmMSKqoqUqtJLBazZ9d+nOxd+RT6ieYtmxEQ5CsTs4dePB+M/jxjPnz4QPOWzbB1sKSplDvtP7z/iPsCL3Zs24WaWhHmG+kybeZkqdYEqW0bM2Nrdu/cg4KCIlrzZjFzTt7EWWTVjzlyjZs0JGDpQpnIkbt6+Rq62oa8ffuOxk0bYedgSYtWzaVaU/ocORXm6mmiqT1LqjXB/0cdu7p48SX8C0ZGRpiYmFC0qPTbzQLJCZ1LBYRYLGbXrl0YGBjw8uVLJk4Zh66+tlRCrEUiEc72rqxbsynP80kk9flzGN7ufmxcvwUVFRU0585knp6WVGp5cO8B2rP1ef48dZpaW0dLOnWWrVyHE8dOYWftxKuXr6lbrw4BS32pWTP/OydEIhHuC7xZtTzv80kk9SX8C75e/qxdvQFlZWWmz5rCfCMdqXSqPnn8FK1Zujx5nPf5JJI6c/ocdpZOPHv2nJq1ahCw1I+6dWvnex1isRhfL3+WBKbmk0yYNBY9w7kyddvetxy5lcvWoKSkxMQp4zGzlE6O3MsXL9GcqcvDB4+oXKUS1nZ5l08iqR9z5BYt9pbaRBjp8knGjsTAOG/ySSQVHR1D4KIlLF28AgVFBf4dNxobKeXIvXnzFq1ZOty9fY8KFcpjaWuWZ/kkkrocfBU7K0fu3U3NkfML9KJFC8lnI82J5UtW4+XhS1xsHMNHDsHIdL5MdOB882OO3PCRQ3BwsZHKqK8P7z+iNUuHG9dvUaZsGSxtTBg4uL9M7Vs3r9/CxtKRWzdvSz1Hbt2ajbg6eRITE8OgIQMwsTDIlziLrIqPi2f50lUs8g0kJUXE4CHSy5H79Okz2rP1uHr5GiVLlsDMyoihw/M+ziI77t65h62lI1evXKdsubJ4STFH7ub1W9jbuHD92g1GjhyJu7s71atXl0otgtwldC4VMAkJCfj4+ODo6IhyYWXmG+nw77hR+TaiQ1r5JJK6f+8hdlaOBF+6QpkypXH3dqFbj/wZXiutfBJJJSYmsmbVBnw8/EhISKR3n154+Ljk26ivg/sPY25iw5fwL3Tu2hFru/zJJ5HU40dPsLN24vzZi5QsVRIXdwf+6dMrX147NjaW+fOMOXb0ZL7mk0gqOTmZDWs34+HqQ1xcHN17dMF7kUe+3Q56/OhJTAws8j2fRFLPnj3HyXYBJ47nf46ctPJJJPV9jlx0dAydunRgYYBXvt0Oevb0eQz0TAnN53wSSb16+Rone9e0HDlrewuGjxySL6+dmJiImaEle3YfyNd8EkmJRCK2b/2PBY7uRERE0rZ9axYt9s632UODL15Gb54R7999oGnzJtg5WNJMhidKCHkTwgInD/btOZjvOXLJyclYmdmxY9suADTnzmK21nSZuz3oG5FIlDp7qL0rYWHhtGiVOuorv27Zu379JjqaBoS8CaFho/rYOlrRuk3LfHltSaTLkVNTw8hUn8nTJuTLa4tEImytnNi8YStisZiZc6ahOXdWvsdZZJVYLGb/3oM42C4g9GMoTZvlb47c9yP0mjVriq+vH926yVeYvSBzQudSAfXu3TvMzc1ZtWoV9RvWw8rGLE+zaL7PJ6lZswY2DhZSySeRhFgs5tCBIzjYuPD+/QcaNW5IwBLfPAtVFIlEeLn7sXzJKqnmk0jq06fPeLr5smXjNlRUVZirMwetebPz7PWePXuO1kxdHj18TNVqf2Ftby6T2WIZEYvFHD96EjtrJ0LevKVuvTosXuZHterV8uw1F/oEELhoKQkJCYwdPxp9I518zyeRVHh4OD4ei1i3ZiOFVQozc8409ObPzbMrf69fvkZzli737z2gYqWKWNuZSSWfRFL5nSMnC/kkkvo+R66QciGmTpuIkdn8PNu33r17j+YMHW7fkm4+iaTOnb2AnaUjT548o3qNagQE+eRpjpws5JNIKn2OnCLjJozB0tYsz/at0I+haM3S5fq1m5QqVRJzaxMGDx0gUyMkMpPfOXIb12/GxcGd6OgYBgzqi6mlEZUry8fMUzExMQQFLGNxwDIUUGDUmLzNkQsLC0N7tj6XL12hePHimFoaMmLUULnZt9LlyFWqiK+/B63ysFNsx7Zd2Fk7ERUZxT99/8bcypiq1f7Ks9fLTT/myA0eNggXN/s827cS4hNYvmw1AX5BqKmp4eTkxPTp06UaZyHIG0LnUgF3+fJldHV1uHDhYp7MovV9PkmRIkUwMNaVej6JpBLiE1j2bXhtcgoDB/djgYdjrg6vPXzoGGYylk8iqbt37mFn5cSVy9coW7YMHj4LcrVDMS2f5NAxVFQKo2eow6Qp42Qu5DIrEhISWb1iLb5e/iQlJfFP39RQxdycpvnUyTMY6ctWPomkHtx/hL2NMxfPX6JU6VK4eTrR8+/uubb9xMREjOebs3/vIQoVKsQ8PS2p55NI6luOnJeHH/Fx8fT8uxtefu6oq+feiMLz5y5ioGPChw8fadGyGbaOVjRp2ijXtp+f0uXIlSyBk2vu5sglJSVhbmzNrp17UVRURFtnNjNnT5PZ0TeZSU5OZtOGrbi7eBMbG5snOXJXL19DR9uAd2/fy0w+iaTS5chpaGDnZMmQYYNybfvJycnYWjqydfMOxIiZozWD2VozUFeXzRESmfkxR659x7YsCvTO1Ytst26kTibz+nUI9RvUw9bRkrbtWufa9vNT6ixabhzcnzc5ciKRCEdbFzas24xIJGb6rClozZstU3EWWSUSifhvx26c7fMuR+7+3ftoz9FPu7Bj62hJx07tc237+ent23e4OnmyZ9e+PMmR+zYrorODO+/evmPevHlYW1tTokSJXHsNgWwROpf+AGKxmI0bN2JsbMynT5+YPmsKmnNn5qhBIhKJ8PP2JyhgOYmJsplPIqkP7z/i5uLJzu27UVNTw9BEjynTJ+Zomz/mk9jYW9Dz7+5ycxX7V1JDFQ/hYOvCxw+hNGnaiIClC6lUKWfDawMWpeaTJCTIZj6JpEJDP+Hh6sO2zTtQVVVFZ74WszVn5Gib8pBPIgmxWMzRw8ext3bm7dt31G9Yj8VL/Pgrh1cFlwWtwtvTj7jYOEaMGoqRqT7lystOPomkwsLC8Xb3Y8O6zaioqDBHeyY6+jnLkZOHfBJJpc+Rq03AEr8ch9yvW70RV2cPYmJiZTKfRFJfwr/g5x3AmlXrv+bITWa+kW6ORjPIQz6JpH7MkfNf4ku9HF5E2rJxG472rkRHRdO3f2/MrUxkfsr6rIiMjMLfdzErlq1OzZGbPA4zK6Mc7Qdfwr8wV1Ofi+eD0SiugYm5ASNHDysQIyQuXQjGxtKRRw8fU63aXyxc7EPjJjm7zXbXzj3YWDgSGRlJr949sLA2oXqNvBtdnV9+ypEbOwobB4sc7VtRkdHoaM/n7OlzqKurY2iqz7/jRslsnEV2XLl8DVtLh685cpXxC/TMcY7cg/uPcLR14fy5i/Tr3w8vTy/q15fPi56CrBM6l/4gMTExuLq64u7ujkZxDYzN9CVqzMlbPomkbly7ibWlA3du3aVipQr4LvKgdTZDFePj4zHUM+PwwaMoKyvLfD6JpOLj4lkatIKAhUGpoYrDBuLsapftUUZnTp3DUN+U0I+faN2mJTYOFjKdTyKp27fuYmvpyPVrNyhXvhxevgvomM0Q98TEREwNLdm7+wBKhZSYqzNHpvNJJJWQkMjKZavx8w4gOTmZfgP74OrhmO1RX8EXL6M714gP77/mkzha0ax5kzyqWnpyI0cuOTkZS1Nbdm7fDch+PomkfsyR+/ufnnj6Lsh2jty1q9fR1TYk5M1bucgnkdTjR0+wt3Hm3JkLqTlybvb80/fvbG1DJBJha+nI5o3bECNm1pzpOb7YJYt+zJHr1qMLPhLkyN25fY+5c/TSJtOwc7SkXYe2eVS19PyYI+fgbM3Awf2ztQ2RSISzgzvrVm8gJSWFaTMmo607Bw2NYnlUtXSkpKSwZeN2XF08iY6KljhH7sGDR2jP0uX5sxfUrPU1zqKrfMRZZMf3OXLFNIphI0GOnEgkwtPVhxXL1pCUlMSkKePR0deSmziLrPp/jpwHERERtG3XmkVB2c+RCwsLx9vDj43rtlCnTm28vLzp3z9732eB/BI6l/5AL1++xNjYmC1bttCsRVNs7Mxp3vL3vdPynk8iCZFIxK4de3B2cCM8/AutWrfAf4lvlkbRyHM+iaTevX2Pq7Mnu//bi7q6GsbmBkycPO636719+x6tmfO4fesu5cqXxcrWjH4D+hTofUssFrN3934c7VKnaW7WvAmBSxdmaZafVcvX4uEqn/kkkvr44SPuC7zZvvU/iqgVQd9Ahxmzp/x2vXT5JKVLYW5lzJBhAwv8vvV9jlzDxg0IXOKXpZEOG9dvxtnBnZjoGAYM7oephaHc5JNI6tOnz3i5+7J5wzZUVFSYq5u1HLmwsDC0Z+lxOfgqxUsUx9RCvvJJJCEWizl+7CR2VtnPkdu+9T/sbZzlMp9EUt9y5Nav3YRyYeUs58hFRkQyV3M+589eoFixohibGTB67IgCMfomM2k5ci9eUqtWTQKX+mUpR27v7v1YmdkRERFJj17dsLQxlenJZHJDZEQkfj4BrFq+FmXlQkzJYo5cdHQMetoGnDp5liJFimBoose4iWMKxOibzJw/dxFbC4ds58gdOnAEc2NrwsO/0KlLB6ztzKkjhRlt81NUVDQBC4NYvmQViooKWc6RS0pKYv2aTfh6LQIUsLGxQVtbWy7jLASSEzqX/mCnT59GV1eHGzduMmzEYIxMM/6BmpCQgLGBBQe+5pPo6GsxdcbkAjf6JjMxMTEs9l9KUOByFFBg9L8jsHOyyvBAmz6fpDm2jpZym08iqatXrmNr6cDdO/epVLkSfgEetGzV4qflEhMTMTexYXcByCeRVFxcHEsCVxC4KDVUceiIITgtsM2woXcl+Cq6cw0LRD6JpG7euI2tlSM3r9+ifIVyePu5077jz1fyk5OTsTG3Z9vW/wBS80m0Z+Tb7Iay4FuA5kKfAFKSUxgwqB+unhnnyN28fpt5Wvq8KQD5JJL6MUfO3ceFrt06/7ScSCTCwcaZjeu3yH0+iaQSEhJZs3IdPp6LSExK5J++f+PpsyDDEYX37txHe44eL1+8kvt8Ekk9fPAIO+tvOXIlcfVwolfvHj8tJxKJcHXyYPXK9SQnJzNl+kR09LTybXZDWfDtB6qnuy/xcfH06NUNLz+3DEd9PX70FK1ZOjx98owaNatjY29B1+4/f2cLsqdPnuFg48LpU2cpUaI4Tq729Bvwc46cSCTCx3MhS4NWkpSYxIRJY9E10C4QcRZZ9WOOXOeuHfH7RY7c8+cv0Jqhw8OHj6nyV2VsHCzo2Uv+4yyy48XzlzjZu3LsyAk0NDSwdbRg6PDBGS57+uRZHO0W8PTJM2bOnImjoyNlyxbsC+qCjAmdS3+4lJQUVqxYgYWFBTExMWjOm8WMmVPSgm0Laj6JpF6/eoOzgxuHDhyhWLFiWNmZMXL0MCA1n0Rz5jxu3rhd4PJJJCESidixbRcLHN358iWC1m1bEbDEJ2147drVG3Bz9ixw+SSSCgl5mzpN8+4DqKurY2ZlxLgJY4Cv+SSzdLl65XqByyeRhFgsZvd/+3CydyXscxjNWzYjcMn/p2nesnEbjnauREdH02/AP5hZGheIfBJJpc+RK4KBsR5TZ0wCUvNJtOfocenC5QKXTyKJn3LkmjTCf6kflSunHpt2bt+NnZUjkZFRBSqfRFI/5sjN09dijlZqjlxkZBQ6WvM5d+Z8gcsnkcRPOXIN6rF46f9z5PbvPYSlqQ1fvkTQrXsXLG1NqVW7ppSrlp7McuSio2OYr2PEiWOnUS2iioGRLuMn/SuXk8nklhPHTmFv48zLF6+oU7c2gUv/nyN39PBxTA0tCQsLp0OndljbmVOvfsGLs8iqH3Pkps2cjIFxao5cXFxcapzFoaOoFC6M7vy5TJ424Y8effN9jlyNmtXxX+JL/a/7z7Nnz3G2d+P40ZN069YNHx8fmjdvLt2CBVIldC4JAIiIiMDBwQFfX18qVqzA2IljWL1iHR/ef6BZi6bYOlgWyHwSSV04dwlbK0ceP3pCtepVadioAUcPH0dBQQHNubOYpTmtwOWTSCo6OoaAhUEsC1qJgqICffv15srl67x7+45GjRtg62hFq9Y/j2r6U10OvoqtpSP37z2gcpVKtGjRjEMHjxbofBJJxcbGEuSfOk0zQO8+vbh96w6vX72hXv262Dla0rZ9GylXKTtuXLuJjZUjt2/eoUKF8rTr2JYDew+RkpLC9JmT0dbV/KNG32QmPi6eZUtW4u+3mJQUEb16d+fhgye8eP6CWrVqYONoSecuHaVdpsy4czs1R+7a1RuULVuGzl07sn/vQZKSkpk0dTy6+toUL1Fc2mXKhB9z5Lr16MLLF6948vgp1apXxdrOnB69ukm7TJlx/95D7K2duHTxMqXLlKZ7jy7s23OQhIQExk/8Fz3DeZQq9eeMvslMYmIia1dvwNtjIQnxCXTt1ol37z7w8MEjKlWuhI29Ob169/hjL3r+KF2OXMkS/N27J3v37Cc+PoFR/47AwFiXsmXLSLtMmfBjjlzXbp2oUbMGa1dvoFKlSnh6ejJ8+HBh3xIInUuC9B4+fIiBwXz27z9A6TKlsbA2YfDQAcLBIgPJycls3rgNdxcvoqNj6Dewzx+RTyKply9e4WTvytHDx1FTU8PW0ZLhI4f8saNvMpOSkpIaqujkQWREJH//0/OPyCeRVMibEFwc3dm/9xCqqipY25kz6t+Cn08iiW85ctaWDsREx/wx+SSS+pYjt3f3/tTZQ031GDeh4OeTSEIsFrNvzwEszWyJjIj6Y/JJJPXxw0c8XH3YsW0Xqqoq6BvpMHHyuD96hMSvfMuRszS1JSwsnHbt22DjYFkgJ5PJDd9y5LZs3E7hwoXRna/NlOmT/qg4i6z6liNnZmTFp9DPtGyVGmfRuMmfFWeRVeHh4fh6+rNuzUYUFRWxtbVl/vz5wgV1QRqhc0mQIQUFBVzc7BkzbpS0S5F5/guD8PPy5+HzW9IuRS7Ur9mMHr26EbjUT9qlyLzlS1exwNGDxy/vSLsUudCsYVtatmzGynVLpV2KzNObZ8TeXft58uqutEuRC/VrNWO25gz0DedJuxSZZ25szaYNW3nw7KbQUZIFjeq0YMKkcZhZGUm7FJnnZOfK8qWruHEvuMDNApcXmtRvzfARQ7BzspJ2KTLPx3Mhft4BXLx66o+O/8iqEUPGUrd2PTZt2iTtUgQyJjt9QcLwAoFAIBAIBAKBINcII8MFeUPYswR5RQGFP2qCFEHeEDqXBAKBQCAQCAQCgUAgEAgEEhM6lwQCgUAgEAgEAoFAIBAIBBITOpcEAoFAIBAIBAKBQCAQCAQSEzqXBAKBQCAQCAQCgUAgEAgEEhM6lwQCgUAgEAgEAoFAIBAIBBITOpcEAoFAIBAIBAKBQCAQCAQSEzqXBAKBQCAQCAQCgUAgEAgEEhM6lwQCgUAgEAgEAoFAIBAIBBITOpcEAoFAIBAIBAKBQCAQCAQSKyTtAgR/lm1bdmI83/y3y63ZuJzOXTrmQ0WyIyoqmvVrNnL08HFePH9JdHQ0pUqVonqNarRt34ZpMyahUVwjbfmC9lnGxcVx6cJl7ty+y53b97hz+y5vQ94BoKOvjZ7B3F+u+/7dB44cPsbF88Hcu3Of9+8/AFC2XBmat2zGv+NG0bFT+1+u7+O5CD9v/9/WePzMQarXqJbNdyYdOfk8v9m/9xA7tv3Hndt3CQ/7QqFChahQsTxt27Vm4pRxNGzUIK/fRr6oWSXr76N9h7Zs2Lo6w+eOHj7Opg1buXXzDhFfIihRsjjNmjdl3IQxdO/ZNbfKzXO5se/8yMLUlo3rNgNQuUolzlw8lunyoaGfWBK4nONHT/I25B2qqqrUqVebESOHMHrsSBQUFLL/xqTkzu27HDtykju37/L82QvCPocRHR1D0aLq1Kpdk+49uzJ+4r+UKFnip3UvXQjmzOnz3L51h1cvXxMe/oXYmFiKF9egTt3a/NP3b/4dNwrVIqr5/8byUPClK6xdtZ6rl68TFhZGsWLFqN+wHqPGjGDw0AHZ2lZ29z1ZkpPvYk7Pa2NHTuLSxcuZrluhQnnOXzn529eQVYGLluK+wCvt38/e3P/lsmdOn2Pzhm3cuH6TT58+o4AC5cqXpUXL5owdP4p2HdrmR8m5JjeO8zk5TicnJ7N963/s3b2fB/ceEhERiYpKYSpXqUzHTu2ZPG0C1apXzbX3mxO5dU4M/RjK2tUbOHn8NK9fhRAfH0/pMqWoXbsW7Tq0ZcbsKSgrK2e47p/SHhPIP6FzSSAVioqKlCpd6pfPFy5cOB+rkb4L5y6hO9eQT6GfAChcWBnVIkV4//4D799/4OKFYP7p24uG33UufVNQPsub128zbdLsbK/39u07urTrhVgsTnusSJEiiMVi3rwO4c3rEPbu2s+oMcNxdrNHSUnpl9tSVlameIniv3y+UCH5OWRK+nkCJCQkMneOHseOnEh7TF1djaSkJJ4/e8HzZy/YunkHZlZGTJ85JZcqlp4yZctk+nxyUhJfvkQA0LRZ45+eT0lJwVDPjF079wCgoKCAhoYGYZ/DOXr4OEcPH2fy1AnYOFjkfvF5ICf7TkYunLvEpvVbsrz87Vt3mTJ+BuHhX4DUfS8mJoYrwVe5EnyVA/sOs2Slv9wc27Zu2sHa1RvS/q2iooKqqgpfvkRw9cp1rl65zspla1iy0p+WrVqkW3fJ4hWcOHYq7d9qamoULlyYz5/D+HwhmIsXglm5fA0r1y2hZs0a+fae8pKrsydBAcvS/q1RXIPIyCjOnbnAuTMX2L/3IIsWe2fpeJzdfU/W5MZ3MafnNTU1NdTU1TJ8rnSZX7c9ZN2zp8+z1PkmFouxNLNL66AEUFVN7cx9/eoNr1+9Yfd/e5k2czKWNqZ5Vm9uy+m+lZPjdMSXCKZOnMWN67fSHitaVJ34+AQePXzMo4eP2bB+M16+rvQf2FfiGnNLbnwP9+7ej7mJDdFR0UDqeUC5sDJvQ97xNuQdp0+dZfzEMSgXT9+59Ke1xwTyT35+KQkKlIqVKsjV1cO8dOXyNaZPnkN8fDx9+vVGc+4smjRthIKCAnFxcTx6+ISjh49RrFixDNcvSJ9l8eLFadSkAY0bN6RRk4Y42i0g9OOnTNcRpYgQi8V07Nye4SOH0KlzR8pXKIdIJOLpk2d4uPpw5NAxtm7eQfkK5ZhvpPvLbbVs1ZyN29bk9tuSGkk+T4CAhUFpDZkJk8eiNXc2FSqWRyQScffOfRxsXbgSfBVnezfatmtDk6aN8vqt5Kng62cyfX5Z0EqcHdwAGD125E/Pe7r5pnUsTZk+kXl6mpQsWZLY2Fg2rN2Mm4sXq1euo1r1qkyZPjH330AekHTf+VFcXBzmxtYUKlSI+g3rcfvmnUyXj4yMYsaUOYSHf6FW7Zp4+rrStFljEhMT2bRhK052rpw+dRYHWxccnG0kfXv5qlmLJlT5y4jWbVpSq3bNtBGoMTExHDpwBBcHdz5/DmP29HkcO30ADY3/H+s7delA126dad22JdWqV6NoUXUAwsPD2b1zH67Onrx+9QbNGfM4cHQ3iorynXawYd3mtI6lgUP6Y2ZhRMVKFUhISGTv7v3YWDhw+OBRFjh5/PaHfHb3PVmV0+9iTs9rM2ZPlWi0oiwTiUSYGFiQkJBAy1bNuXb1xi+X3bZlZ1rHUr8BfTA00aNGzepAageVq7MnRw4dY8XS1bRp24o+/XrnwzvIHZLuWzk9TjvYuqR1LOnOn8ukqeMoWbIkKSkpXAm+io2lA48ePsFQz4yWrVpQoWL5XH/v2ZWT7+H+vQfRm2uESCRi7PjRTJk+kTp1awMQHR3Dvbv3OXzwKIWUf/5Z/qe1xwTyT+hcEgikKC4uDkM9U+Lj4zMc2VCkSBGaNW9Cs+ZNpFRh/mnTrhXX715M95ibi9cvlv4/jeIa7D6wjcZN0p9QFRUVqVO3NouXLWTaxNmcOnmGlcvWoD1vDiqqKrlauyyS9PME2Ll9FwDt2rfB3sk67XFFRUWaNG3EslWBdGrTnZiYWA7sO1TgGzNbNm0HoHXbVtSslX50SFhYOCuWpd4m90+fXljb/f9WVTU1NWbMnsrnz2EEBSzDx2sRI0YPo1ixovlXvARysu/8yMPVh5cvX6GtM5v37z789gf+sqAVhH78hKqqKivWBPFX1SpA6gjMSVPGEx0dg8cCbzat38rUGZPkYrTO8JFDM3xcXV2d4SOHUrZsWSaPn8HnT585fvQkQ4cPSltm2ozJGa5bsmRJJk+bQOHChbEwteHxo6dcu3qD1m1a5sVbyBfJycn4eC4CoHGThvgsdE/rLFNRKcyIUUOJj4/HysyONSvXM2nKeKpW++uX28vuvieLcvO7KPi/1SvWcfXKdYYMG0S16lUz7VzauS31fFitelV8/T3SjfSqWasGixZ707v7AF69fM2+vQflpnMpJ/tWTo7TCQmJ7N1zAIARo4aiO1877TklJSXadWhL0HJ/enTuQ3x8PMePnWTchDE5fbs5kpPP6uOHj1iY2CISiTC3NmHGrCnpni9aVJ227VrTtl3rDNcX2mMCeSPfl7gEAjm3c/tuXr18TdlyZTC1MJR2OVKV2e1qmdHQKPZTx9L3FBQUGPXvcABiYmJ58uSpRK8jbyT9PAE+fgwFoEkGt4BB6mf+7cptbEysxK8jD65euc6Tx6n7zJgMRi2dP3uBxIREAGZqTs9wG7O/Ph4ZEcmRQ0fzqNLck5N953vXr95g9Yp11KhZnbk6mllaZ8fXH3IDh/RP+8HyvclTx6OurkZKSgq7duzNlTqlrXnLZml/v3/3Pt/WlTV3bt1NuzV8+qypGY7C+nfcKDSKa5CcnMx/O3b/cluS7HuyKLe+i4L/e/3qDZ5uvpQsWQJL29/fxvbtfNigYf0MbyFUVlamQcP6gHydD3Oyb+XkOB0ZEZF2zmzSNOM2RrXqVSnx9VZOWfhMc/JZrVqxjoiICBo1bsD0mRlfLMiM0B4TyBuhc0kgkKJvV8T6D+j7R4ymkRYVlf9/tikpIilWIh+qVk0dDXDn1t0Mn4+MjOL5sxfArxs8BcWWjdsAKKZRjP4D+/z0fMibt2l/16lTK8NtlChZgtJlSgNw5tT5PKhS9iQkJGJiaIlYLMbZ1S5Lx7dnT5+nhaR279Elw2XU1dVp3bYVAGdPn8u9gqXocvCVtL+rVstegG1O1pU1ISHffZfqZvxdUlJSokaN6gCcOZ3xd0mSfU/w5zAztiI2NhYLGxNKZ5JX+c23zpP79x6QnJz80/NJSUncv/cA+HVnSUGS0+N0mbJlUFNLzfC6fSvj0YQvX7xKyzmU95E439r5Q4YPlmgiCqE9JpA3QueSQCrCPoczuN8IGtdtRYNazenWsTf684y5eD5Y2qXlm4SExLQTa+OmjQgJeYu5sTWd2vSgXo2mtGnemRlTNDl+7GSm2xE+y9+7eCH1syhcWDntCk9GHj96Qt9eg2hYuwWN67aiV9d+mBlZcffOvXyqVDaMn/gvkPq5WVvY8/5d6ux7YrGYO7fvMmOKJjExsbRs1TzdLTwFTUxMDPv3HgRg0JD+FClSJNPlU0Qpv3xOlJL63MMHj3KvQBm20CeAJ4+fMvrfEVmeRenhg8dpf9etV+eXy9X7+tzjx/I7CjEhIZE3r0NYs3I9BjqpoyeqVa9Kr949frtufFw8z5+9wH9hUFoWWNt2rTMMm5dXmV0E+PY9e/TwcYbPS7LvFWQ5Pa/t2rmHLu17Ub9mU5o1bMvg/iPxcPXhw/uPeVx57tu0fgvnz16kU5cOv7xd9UcTJo0FUjs8dLUNefH8Zdpzz54+Z94cfV69fE21alWZJsHIFHmT0+O0goICYyeMBmD71v/w9fInPDwcSJ0c49KFYGZPT71Vrv/AvnL9HX796g0fPqR+T5o0aciD+4/Q1TakXcsu1K/ZlI6tuzNPU58rl6/9chtCe0wgb4TMJYFUxMXFcef2PYoXL05yclLajBu7du5h5JjhOLvaydXMXJIIeRNCYmISAK9evsbOypHo6BgKF1amiFqRtPyN40dPMmbsSJzd7DO86iF8lpl7/eoNG9amhnEOGNQv07ybsLBwvvyPvbuOimpr4zj+pUEUu7u7u6967br2tbtASeluAUkF7Gt3d3vVa3d3Byoq0j3z/oHygoE6xAy4P2u5FjLnnHlmODNz5jn7/PbHcHR0ChAVFZ06E8eGdZvRnTkFEzPDHKpavkaPG0FIyGsWL/iHVcvXsmr52tTZSRISEileohjT9Cajb6ibpy/b2LV9D9GfhpkPGz7km8uUK1829ed7d+5/80A49G1o6ow6b9/kvi9kv+rmjVssDF5CseLFsLQx/en10j43JUt9P8D1821RkVFER0ejra0te7E5rFbVhqmXhKTVtHkT/OZ5oaHx7RnwQt+G0rJJh2/e1qVrJ7x83LK0TnkoVy7Na+nu/W+OWEhISEj9ch8ZEUlMTEzqKAiQfd/LyzL7ufb0yTPU1NTIly8fERER3Lh2kxvXbrJi2Wq8fNxyTcbQ65A3uLvOQVNTE9fZjj+9XpeunbBxsMDTzZu9u/ezd/f+1Nni4uLi0Cmow8gxf2NiaqDweXpZISvep2eZGRL2IYwtm7bj7zMPf5955C+Qn7jYOJKSkqhQsTzmViZMmjo++x5IDvg8ogjgwoXLzPUNJCEhEU1NTdQ1NHj9+g27d+5jz679GJrMYKah7lfbEMdjQm4jRi4JOapkyRLoG+mx+8A2bj+8yuWbZ7h5/zIbt62hbfvWAGxavwUXh9lyrjT7hX8a8gsQGDAfVVVV5s334/rdi1y5eZYTZw+nTsG6fu0mlixanm598Vz+WFxsHHrTDImNjaVIkcKYWZp8c7lKlStiYT2LQ8f3cPvhFS7dOMONexdZvnox9RrURSqVEhiwgMUL/snhRyAfysrKmFka4+HtivanKaijo2NSm6Hx8QlERkYSExsrzzKz3fpPl8TVrlPru0PzW7dthfqnhkDg3AXfXCYw4P+/j4qKyuIqFUtSUhLmJjYkJSVh72SVOjPaz4iKjk79WUtL87vLpb0tOir6u8spouLFi6W7LASgdZuW2DpYUrZsme+up6yiQrFP66a9zLdXnx5YWM+iUOFC2Vl2jqhbvw7FihcDYEHQ4m9egrTin9WpU3kD6X7OzL6XF2X2c61l6xZ4+rhx+sIx7jxKOca4fPMsnj5uFC1WlKjIKPR1TbicQRi2IrG2sCcyIhIDY70Mg+C/ZcKksQQtCki9vDkuLo64uDgAEhMSiYmOITIyb7+3f5YV79Mamhq4ezljaWOKmppaynYjo1Jf87GxsXz8GE5CwteN+NwkPPz/x/m+XgGUKFmCFWuXcOPeRa7dPs/+Iztp1boFUqkU3zlz2bfnwFfbEMdjQm4jmktCjmrfsS2GJjOoXadm6hlaFRUVmjZrzPLVi+navQsAq1asTdfxz4skUun/f5ZImD3HhV59uqd+0JYtW4aAIO/UoMjguQvSHWyL5zJjSUlJGM6YxY1rN1FTU8N3rhclS5X45rJ/DezLlOkTqVKlcurzr66uTvuObdm4ZTUNGqbM1ufvM4+IiMgcewzy8uFDGKOGjcfUyJLGTRuxYetqrtw6x9lLxwleFECRIoVZvWIdA/sOSx2indfcu3s/darkbwV5f1akSGHGjR8FwH/HT2E004yHDx6RmJjIy5ev8HDzZuXyNan7lZJS3v7YnR+4iFs3b9P5zz/o3benvMtROCfOHObc5RPcuHeRc1f+w8rWjFs37zCgz1B8vQK+u17RokU4d/kE5y6f4NaDy5w8dxQ9/akcPniUXl3/Yu2qDTn4KLKHqqoqMw1Twrcf3H/IpLHTuXH9JgkJCYS+DWVh8BK8ZvumvpYAlNKEfot9L73Mfq4Zmsxg8NABlCxVInXUtI5OAQYPHcCmbWvQKahDYmIis93m5NyDktG2zTs4evgYderWZuIXs3X9SGxsLDOnGzFp7HTKlC3N8jWLuXDtFBeunWL5msVUq1GVrZt3MKDPUG7fups9DyCPef7sBf16DsbdxYvuvbqyfc8mrt+9wH/njuDl646SkhILghYzbNBooqNz1wmEtCSS/x/nS6VSghb60659m9TJCqrXqMaiZUEUL5HSVA/wDfpqG+J4TMht8vZRrpCrKCsrpw5jl0gkHD70r3wLymZphwhXqlyRbj3+/GoZZWVlJn8aFhwW9vG7gX7fWu93ei6/lJycjNFMUw7sP4yqqiq+c71o37GtTNvS0NRgloUhkHK26NR/p7OwUsU0y9CCM6fP0bJVc5avXkyz5k3Q0SlA8RLF6d6zKxu2rqZIkcI8e/ocT3dveZebLT6PWtLQ0PhhjsEsCyP69O8FpOSTdP2jNzUrN6B9yy4sCFpMo8YNUmcsLFgo746muH/vAfP8g9HWzoeTm92PV/hC/jTvibGxcd9dLu1t2vlzzyVxXypWrCiTpo5n2aqFKCkpMdc/mMOHjv5wPSUlJUqXKYWJmSG+cz1JTEzE1soxNVQ4Nxs9dgSTp04A4Pix/+jXczC1qjSkZZMOzHadQ9lyZZgyfULq8gU/jU7K7L73u8ns51rFShUYPTYli+jCuUupmTmKKDT0Hc4O7qioqODm6fTLMQHuLl7s3rmPKlUrs2HzKtp3aEuRIoUpUqQw7Tu0Zf2mlVSuUokPH8Kwt3HOpkehODL7Pp2cnMyUCXrcvXOPgYP7ExDoTf0GddHW1qZMmdIMGvIXK9cuRV1DnRvXbrIgaHH2PJAckD/N427TrtU3ZzbW1tZm9NgRANy5fZfQTzNmfiaOx4TcRjSXBIVSqXJFihQpDMDzp8/lXE32KpVmFE3ValW+u1y1NLPmpJ1N50d+p+cyreTkZIz0zdi9cx8qKir4BHh8c5avX9GkaaPUn58/e5HJChXbg/sP+ffIcQAmTR3/zZyvYsWKMmBwfwD27z2ENM0ovLwgISGB7Vt2AtCjV7cfXl6jqqpKQKA3S5bPp0+/nlStVoWy5crQvGVT7J2sWbd5JXGfDrQ/z3SVF9lbO5OQkIjuzGkULKhDdHR0un9JSSlBzFKpNPV3iYmJqeuXKPn/98Q3r79/BvbzbfkL5M9VeUvf07BxA5o1bwLAutUbf2ndHr26UaZsaSQSCRvWbs6O8nKcpa0pG7auZtDQAdSoWY3SZUrTsFEDTMwM2LV/C8rKKbkiZcuVQV09ZdRuZve931FmP9caf1pfKpXy/NnLLKoq63m6+xAW9pG/Rw6harXKX+0bafeDz7/7fDlWVFR06mty9NgR35x5UFNLkzHjRgJw4dxF3r17nwOPSn4y+z594tjJ1IktJk2d8M11q9eoRqfOHQHYt+dgpmuWl7Sj5atV+/YMmADV0sw0+yrNDLTieEzIjX7flF9BkLNChQtRqlRJXmfw4QyQ9nNClmlMfyefRyzt2rE3tbHUp18veZeVq9y/9/+ZXTLKpahUuSKQcsnAu3fvKf4pKyUvOHTgCB8+pJyJz+iSuC916tKRTl06fvO2zzNDNmnWOPMFKqjnz1O+oHrN9sFrts93l3v1MoT6NZsBYONgwYRJKTMs1az1/5mH7t29n+6AO627n2YJq/6d23Ojz+G3T588++V1S5UqyauXITx58vTHC+cSzZo3SW24fSn1tdT0/6+lzO57Qt714lPjbPWKdaxesS7DZT/vG+MmjsbO0YrHj56kxhH8zOfh5/sr9imbKS/K7Pv0gzSzx1Ws9OPnNDef0KtevRoqKiokJ39/JllIf5xPmuN8cTwm5EZi5JKgUJ4+eZb6pa58hXJyrib7tft0qdaDDKbUfnDvQerP5cr//HPyuz2XycnJGM6Yla6x1Ld/7yzZ9uVLV1N//pW/QW6krPz/A5uXL74/Uu5d6P/Pzn4OmcwrPl8SV7FSBVq2bp7p7d28cSv1IHHgpzOMwtcqV6lEmbKlATh29MQ3l4mJieHCuYsAtOsg26Wuiuj5s5TRpb86EksqlaY2VvLn4ksEf1Zo6LvUS7jEaylzMvu5duXT+kpKSulmzcxL0n0eZjByPO1opdx8qe7PyOz7tNLPHmN8ek5z8/uahqYGLVqmNCwfPMjgOP9+ynH+l68lcTwm5EaiuSTkmB8N1ZRKpbi7eAEpmUGd//wjB6qSr8FDBwApjaAD+w59dbtEImHRp5lcSpUqSb36dQDxXH7p84il3Tv3fcpY8vzpxtKPnsv4+AS8PfwAyJcvH23btcpsuQrt8z4GsHrlt8/yxsTEsHXzdgBq1a6Zbuar3O7ly1ecPJHy5XXI34MyPVowNjYWW8uUaa979u6e4SWwud2JM4d59OL2d/8NGvIXkHI50+ffpR05oqSklNow2LVjLy+ef32pzcpla4iOjkFFRYX+A/vkyOPKjOTk5B++x5z87zRXr1wHSNfM/NZsaV/auH4LoW/ffVq3RSYqVXzJycnYWjiQkJBIw0YN6PBHu9TbMrvv5TWZ/Vz70frPn71g5bK1QMpozM+X4CuitZtWZLhv6BvppS77+Xd2jlYAVK1aBU3NlFnPNqzd9M3XZHJyMutWpwTqFyxYkCpVK+fAo5KfzL5P16uX5hjjOyPJQt+Gph4TN05z+WZu9Pk4/9R/Z7hx/evc1OjoaFatSHktNWrcgKJFi6Te9rsfjwm5k2guCTnm5YtX/NV7KGtWrefZ0+epBy8SiYTLF68wftSU1A+T4aOG5vkPaIAWLZvRs3dKHpClqS17dx9IPXh5+fIVBnom3LmdMvuIiblh6gwTefW5DP8YzocPYan/Ps+0ERcbm+73aWcP+ZyxtGvHXlRVVfGb5/VLl8KdO3OeUX+PZ+um7YS8ep36+8TERE7+d5phA0elzho203B6rpreWpbns2y5snTp2gmAwwePYqxvxtMnz5BKpSQmJnLxwmWGDxnLs085XpOmjsvxx5WdNq7bgkQiQVVVlcGfvpD+yJVLVwmcu4D79x6kZnUkJCRw7OgJhg4YyZXL1yhdpjSOrrbZWHnWkmXfyQqTpk6geIlixMbGMnHsVK5/msQgISGBVSvW4jsnZUa1v0cOoUoVxX9fC3n1mj7dB371Xg3w6lUIwfMWMXXCDKRSKYUKFWTi5P83PC6cu8SwQaO+em8CePzoCR5u3thYOABQsWIFBg8ZkCOPKTs9e/qcOR5+3Lh+k/i4eCDlc+3C+UuMGTGJA/sPo1NQBy9ft9/mMnFZXouZ/VwLDlzELEML/j1ynIjwiNTfR0ZGsWXTNgb/NZzw8HDU1NQwtzLJzocvV5pamqmXRt+4fovJ43S5c/seEokEiUTC7Vt3mTBmKhcvXAZg/KTRqKioyLPkXyLr+3xm3qebt2yWOgvyimWrcXGczZvXbwGIj4vn2NETDBs0msiISJSUlNK9J8qTrM9V/4F9adioAVKpFN0pBpz87zQSiQRIuWphyng9Qt++Q1lZGRNzw3Tr/u7HY0LuJDKXhBx17ep1rl1NOUOrrqFOfm1toqKjSYhPSF1m8LCB2DtZy6vEHOfl68b7d+85d/YCelMNUNdQR0tTi/Dw8NRl9I30Us+8fpYXn8s+PQZ+c+jvwvlLWTh/aer/Bw35Cy9fdwAunr/Eru17gJQzag62rjjYun73PuwcLdM1n6TSlDNKp/47A4Cmpib58mkRGRmVGvSprKzMNL3JTNWdlPkHmYNkeT4BPLxdGTdqMjeu3WTblp1s27ITLS0tEhMT0525nTJtAgMH/5WtjyEnSSQSNm3YAsAfnTukCy7NyNu3oXh7+OHt4YeSkhIFC+oQGRmVmrNQo2Z1Fi8LzlU5HLLuO5mlo1OAxcvmM27kJO7fe0j/XoPJn1+b+PiE1Ndj+45tsbG3zLL7zG63b91JbQKpq6uRP39+4uLiiYmJSV2mfIVyBC30p3iJ4unWPX/2IufPplxeoqGhgbZ2PmJiYomL+/9MTLXr1GLBknloamlm/4PJZlFRUQTNXUDQ3AVAykiQmJiY1L99mbKlmb947ndzXvIiWV6Lmf1cS4hPYMum7WzZlDIiIn9+bVRVVYmIiEz9YlxApwAec1y+m42VV5hbmfDk8VOO/Xsi9Z+6RkqQfNrjrb79e6OnP01eZcpE1vf5zLxPKysrE7TQn7EjJ/Hs6XOWLlrO0kXL0dbOR2xsXOr+paKigrWducKMyJT1uVJWVmbh0nmM+ns89+89ZPTfE9DS0kJVTZXIiEgA1NTUcHSxoU3br0fG/67HY0LuJZpLQo4pVqwoDs42XLp4hdu3bvPhfRjh4RFoaKhTvnw5mjRtxJC/B+X5A5Uv5cuXjzUbl7Nx3Wa2bt7Bvbv3iY6OoVSpkjRr2ZSx40fR9IsQYPFc/t/ns0eQclb23RfTuH4p7tPZ8M9q1q6Ola0Zly5e4e6de4R9CCMiIhJNLU2qVa9K8xZN+XvkUGrVrpEt9SuiIkUKs2XHOjZv3MbeXfu5desO4R/DUVFRoUzZ0jRp2ojho4bRvEVTeZeapU6eOM2rlyHArwV512tQlynTJnDu7AVevHhF+MdwChUuRK3aNejdpweDhw385emvf2f1G9Rl35GdLAhazJFD/xLy6jVa+bRoWLMBgwb3Z8jfg1JHcSq6EiWLM2++H2dPn+PKlWu8ff2WsLAwlJVTXku169Tiz26d6f9Xn6+aQ/Ua1MXH34Mzp89x/dpNQkPf8THsI+rq6lSsWIG69evQo1dXevbunqtGS2SkXLmyzDTU5ezpczx98oywsDDy59emSrUqdO/ZlZGjh6GlpSXvMhVeZj/XevXpjlQq5fKlK5/+Dh+JioqmYEEdqlavSvsObfh75NDfIjhYU0uTpSsXsHf3AbZv3cmNazd5//49KCl9msmwPoOHDaBzlz/kXWqOysz7dMVKFdhzcBvr1mzk0P4j3Lt7n4iISDQ0NChTtjQtWjVn1Jjh1K5TM4cfVfYoXqI4O/ZuYeWy1ezasZfHj58QHxdHufJlad2mJRMmj6VmrW+/Fn/X4zEh91KS/sSchRERERQsWJDw8HB0dHLPJSFCekpKSrh7OjFsxBB5l6LwAucuIMAnkLuPr8m7lFyhVpWGdOrSkeBFAfIuReEtWbSM2S5zuP/0hrxLyRUa1mlBkyYN+WfVInmXovAMZ5qya/seHjz7OtdB+Fqtqg2ZOn0SRrNmyrsUhWdlZse6NRu58+gq6urq8i5H4dWt3oRRY4ZjaWsq71IUnqujB0sWLePKrXPo6BSQdzkKr0GtZgwY1D9XXWYtL37ecwnwDeLMxWM/PRL5dza4/wgaNmjE0qVLf7yw8Fv5lV5Q7jj1JwiCIAiCIAiCIAiCICgk0VwSBEEQBEEQBEEQBEEQZCaaS4IgCIIgCIIgCIIgCILMRHNJEARBEARBEARBEARBkJloLgmCIAiCIAiCIAiCIAgyE80lQRAEQRAEQRAEQRAEQWaiuSQIgiAIgiAIgiAIgiDITDSXBEEQBEEQBEEQBEEQBJmJ5pIgCIIgCIIgCIIgCIIgM9FcEgRBEARBEARBEARBEGQmmkuCIAiCIAiCIAiCIAiCzERzSRAEQRAEQRAEQRAEQZCZaC79ZmJj4+RdQq7w9MlTkpOTiYqKlncpCi8iPIKkpCQ+fAiTdym5wrMnz5FIJESER8i7FIUXFRlFXFwcYWEf5V1KrvDh/QckEgkfxfP1QzExMSQnJfP0yTN5l5IrvH//AYCw9+J9/kfi4uJITEzk6dOn8i4lV3j3/j0A70PfybkSxZeQkEBCQiJPn4r3rZ/x7l3KvhX6VuxbPyKRSIiLE98RhcwTzaXfSLVq1XB18sDJzk18+fiOWzdu06lddzat34pEIqFFo7b4+8yTd1kKSSKR4ObsSYvG7ZFIJJw/e4Funfvw4P5DeZemkO7de0DXP3qzcvkapFIpLZu0x9PdG4lEIu/SFI5EIsHHy5/mjdqRmJDItas36NKhJ3du35V3aQrp8eMn9OzSj/+OnwKgVdOOuDjOFvvWd8zzD6ZZg7YkJyezY9su/mjTletXb8i7LIX04vlL+vQYyKEDRwDo0KYrtpaOYt/6jkULltK0fhuSkpI4sO8w7Vp25tLFy/IuSyGFhLxmQJ+h7Ni6C4Aef/bDfJYNSUlJcq5MMS1fuoom9VqTkJDA8X//o3Wzjpw5dU7eZSmk0LehDBkwgnWrNwAwoO8wjGaakZCQIOfKFNPli1cY1H84t27eplq1avIuR8jlRHPpN3Ljxg3c3d3ZvHEbnTv0ZOXyNeJD/JOIiEjGjZpM/96DCfsQhrO7PTv3baZh44b4+wTSvGFbjh4+Ju8yFcaeXftp2qANixf8Q+s2Ldl7aDs2Dha8ehlCzz/7M23STGJiYuRdpkKIiopm8nhdenf9i9ev32DnaMWeg9tp3qIZ8wMX07xhW/bvPSjvMhXGoQNHaNGoHfP859OkWSN2H9iKo6st70Lf0bfHICaOmUpkRJS8y1QIsbGx6E01pFunPjx//gIrWzP2Hd5B2/atWbpoOU3qt2bHtl3yLlNhHD92ghaN2+HjFUD9BnXZsXcTbh6OhEdEMqDvMMaMmChGFH6SkJCA4UxTOrfvwcMHjzAxN+TA0V10/vMPVq9cR+O6rdi0Yau8y1QYZ06do3XTjrg7e1Gzdg227lyPl687cbFxDB0wir8Hj+HDhw/yLlMhJCUlYWZsxR9tunL71l30jfQ4dGwP3Xt2Y+O6zTSu24o1q9bLu0yFcfHCZdq17IyjnStVqlZi47Y1+M71IjlZwqi/xzO4/3Devnkr7zIVQlJSEjYWDrRr2YWrV64zfcYUDh3fQ9/+vdi+dSdN6rXin8Ur5F2mwngd8gZjfTMG9R+OMsocP34cKysreZcl5HJKUqlU+qOFIiIiKFiwIOHh4ejo6OREXUI2ev36NVZWVixbtowaNatj42BB23at5V2WXEgkEuZ4+PLP4hUkJiYxdsIo9A11KVioIABSqZSD+w/jZOdGSMhratetRfACf8pXLC/nyuXj4YNHTJ+iz4N7D6lYqQL2Ttb80blD6u3v33/Ax8ufdas3oqGhge7MKcwwmC7HiuXL32ceC4IWEx+fwMjRf2M4ayZFihQGUvato0eO4WjryvNnL6hRszrBiwOoXLmSfIuWk6dPnqI7xZA7t+9SpmwZ7J2s6NK1E0pKSgB8DPuIv08gK5evQU1NjUlTx2M0aybKyr/nOZLgwIXM8wsmLi6eocMHY2JmQLFiRVNvP3HsJA62Ljx+9IQqVSsTtCiAGjV+zzOSL1+GoDt5Jjeu36JkqRLYOljRo1fX1H0rIjyCuf7B/LNkBaoqqowZPxIL61m/7b61dNFyfLz8iYmJZeDg/phaGFOyVInU20+fPIuDrQv37z2gYqUKBM73o0692nKsWH7evH6L7lQDrly6SrHiRbG2s6Bv/16p+1ZUVDRBcxeweME/KCkrMXzkUOwcrX7bfWvVirV4uM4hOjqGPv16YWEzizJlSqfefv7cRRxsXLh96w5ly5VlbrAPjRo3kGPF8vPu3Xv0phpy8fwlChUqiJWdGX8N7Je678TExLAgcDHzgxYDMGjIXzi52aGqqirPsuVm4/otuDi4ExkZRY9eXbG0MaN8hXKpt1+5dBV7WxeuX71BqdKl8A+cQ/MWTeVYsfzExcaxZNEyguYtJL92ftzc3Bg/fjwqKiryLk1QUL/SCxLNpd/YxYsXMTDQ5+TJU3Tr0RUrW1Mq/EZNk/17D2JlZkdY2EfatW+DnZMV1apX/eay8XHxLF28ggC/QJKTkunVtwee3q6oq6vncNXyERMTg7G+OYcPHkVDUwNjU31Gjx2BmpraN5e/fesOjraunDt7gWLFizLHz50OHdvncNXyc/TwMcyMrXj//gMtW7fA3smaWrVrfHPZhIQEVixbg9+cAOITEujarQtz/NzJly9fDlctH3FxcZgaWbF/7wFUVdUwMNZj3MQxaGh8+7V17+59nOzdOPXfGQoXKcxsL2e6du+Sw1XLz8kTpzE2MCf0bShNmzXGwcWGuvXqfHPZxMRE1qxczxxPP+Ji4/ijcwd853qRP792DlctHwkJCVia2rJz+x5UVJSZYTCdiZPHoaml+c3lHz18jLPDbI4dPU7BQgVxcbend9+eOVy1/Jw7ewHDGbN4HfKGBg3r4+hiQ8PvfLFPTk5m/dpNeLp5Ex0dQ9t2rQkI8kan4O9xjJiUlIStpSNbNm0HYJreZKbqTvzu+/bTJ89wdfLg0IEj6OgUwN7ZhgGD+uVkyXJ1+fJV9Kcb8/LFK+rUrYW9s813v9hLJBI2bdjKbNc5RIRH0LJVc+bN96XwpxMzeZ1EIsHR1pV1azcilUiZPG0C02dM+e779ssXL3F38WLPrv3kz6+NtZ05w0YMyeGq5efG9VvMnGbI06fPqV6jGo4utrRq0+Kby0okErZv2YmbixdhH8Jo0qwRQQsD0p2YycukUil7dx/Aw3UOr1+/QV9fH1tbWwoWLCjv0gQFJ5pLwk+TSqWsX78eU1NT3r59y4TJY9GdOTVPf/l4/PgJupP0uXv3PuUrlMPe2ZpOnTumnmnMyJvXb/Ga7cOWTdvRyqeF8Sx9Jk4Zl/1Fy9E8/2CC5i4kPj6ev0cOwdjUgKJFi/xwPalUyr49B3FxcOf16zfUq1+HoEVzKVu29A/Xza1ePHvBtCn63L55h9KlS2HnZEXX7l1+at969+493p7+bFi7CU1NDWYYTme63pQcqFp+Fs5fir/3POLi4hg0dACm5oYUL1H8h+tJpVIOHzyKk70bL1+8omatGgQv8qdipYo5ULV8hIS8RneyPteu3qBEyeLY2FvQq0+Pn9q3PnwIw2/OXFavXIeGhjpTpk9E30gvT4+eWL50JV6z/YiJiaH/gL6YW5lQqnTJn1r33yPHcbRz5emTZ1SrXpWghf7fPfGQF4S+DUV3qgGXL16lSJHCWNmZ0++v3j+1f4R/DCfAL4jlS1ehpqbK+EljmGVulKf3rXVrNuDq5El0VDS9+/bAwnoWZcuV/al1T/53GgcbFx4+eETlypUIXOBLrTq1srli+fnw4QMzphlx7swFChbUwcLGlEFD/vqp/SMyMopA/2CWLFqOiooKI8f8jbWdeZ7et7Zs2o6TnSsREZF07d4Fazvznz7pe+7MeextXLh75x7lK5RjXrAv9RvWy+aK5SciPIKZusacPHGa/AXyY2ZpzLDhg39q9E10dDTzAxexIHgJSigx9O9BOLjY5OmRO7dv3cHJ3p2zp8/Ru09vfLx9qFHj2yc9BeFLorkk/LKYmBg8PT3x8PBAR6cAppbGDBjUL099iMfExDDL0JKDBw6joa6OoclMxowfKdPoo6uXr2Fv68K1K9cpVbokfnO9aNGqeTZULT/Hj51glqEl70Lf07xFUxxcbKgtw0Hw5+G38/yDSU6W0LdfT9znuOSpUV8JCQmYmVizZ+c+VFRV0DfUY8KkMWhoavzytm7euIWDjQsXL1ymeIlizPGdTfuObbOhavk5c+ocRjNNefPmLY2aNMTB2YYGMhwEx8cnsHzpSvx9AklMTKBbz67M8XVHU/PbI1Nyo6SkJCzN7NixdSdKSsrozpzC5GkT0NLS+uVt3bl9D0c7V86ePkfRokXw8Hal859/ZH3RcnTx/CUM9Gbx6lUI9RrUxdHZhsZNG/3ydhITE1m5fA0+XgHEx8XT+c8/8J3rmadGFCYlJeFg48LG9VuQImWa7iSm6k5CW/vXTy49uP8QJzs3/jtxikKFCuHq6UjPXt2yoWr5uX71BjOmG/H82Qtq1a6Jg4sNLVo2++XtJCUlsXb1BubM9iUmJpb2HdrgH+hDAZ382VC1fEgkElwc3Fmzaj3JyRImThmHnv40ChT49cf4+NETXJ08OHLoX3QK6uDkaku/v/pkQ9Xyc+fWHXSnGvLk8VOqVauCg6stbdq2+uXtJCcns3HdZjzcfYiMiKR125bMDfKhUOFCWV+0nEgkErzcffhn6UqSEpMYN3E0+oa6Mo2afP7sBW7Onuzfe5ACBfJj42DJkGEDs6Fq+UmJqwhg/ZqN1KhRHV9fP3r06CHvsoRcRjSXBJk9e/YMc3Nz1q1bR8NG9bF1tKRJ08byLivTfpRPIguJRMKObbtxc/Lgw4cwGjdtSNAC/58aeaHI0uaTlCpVEhsHy3T5JLJ6HfIGT3cftm3ZQb58+TC1MGTshNFZVLX8LF20HG8vf2K/k08iC6lUyp5d+3BxnM3bN6HUb1CP4MUBlC5dKouqlo83r9+iO0WfK5evfTOfRFahb0Px8vBj84ataGpqYmCsx5TpE7OoavlJySfxJjo6mr79e2NubZIun0QWqTly9u6EvAqhdp1aBC/M/TlyafNJChcuhKWtabp8Elm9f/8BX68A1q7ekKdy5H6UTyKLzzlyTnZuPHv6PM/kyH0M+8iM6UacOXWOAjoFsLAyYfCwgZke5fBljtzEKeMwNtXP9Sf1tm/dib21CxEREXT+8w+s7cypXKVSprd74vhJHG1cefTocZ7JkYuMiMJAz5gTx0+ira3NLAsj/h4xJNO5SRERkczzD2bp4uWoqqgyetxILG1yf47c3j0HsDa352PYRzp0bIetoyVVq1XJ9HbPnDqHvY1znsqRS0hIYOXyNcz1DUJZWQUHBwd0dXW/G2chCBkRzSUh006cOIGBgQGXL1+m/4C+mFkaU7pM7vti+9/xU5gYWvxUPomsoqOjWRCUEqqohBKDhw7A0dU214UqJiQkYDnLhp079v5UPomsLl+8gr2tCzeu3aR0mVIEBHrTtHmTLL2PnHDuzHkMZ5qm5JM0qo+j8/fzSWQVFxvHogVLCQxYgEQiof+APrh5OuW6g4Mv80mmz5jClOkTsnwUyPVrN3GwcebypauULFkC7wAPmc7+ytulS1cw0DVJzSdxcLGlWRa/Rr7MkevZpztePm65bkShRCLBwdaV9Ws2IpX+OJ9EVuly5IoVxcvXnY6dcl+O3I3rt5gxzTC1+ePoYkPL1t/OJ5FVXsmRk0gkuDt7sXL5GpKTk5kwaSx6BtPQ0SmQpfdz/94DHO1cU3Pk3L2c6ZYLc+Tu3LnHjKmGPHr4mCpVKmPvYk37Dlk76jYpKSklR87Dj9jYWP7o1B7feXNyXZSDRCLB29OfpYuWk5iYyJhxI9E30s3yEUbpcuQK6uAy2yFX5sg9eviY6ZP1uX/vARUqlsfeyZpOXTpm6X18mSPXpl0r5gb55MocuX+PHMfV0YPHj58wZcoUnJ2dKVasmLzLEnIx0VwSskRycjLLli3DysqKyKhIputNZtKU8VnebMgOISGvmT5Zn+sy5JPI6sXzl7i7eLJ39wHyF8iPjZ05Q4cPzrb7y0pp80n+GtgPM0vjn84nkYVEImHblh24O3sRFvaRps0aE7jQP1eEKmYmn0RWr16F4OHqzc7tu9HWzoeZlQmjx47ItvvLSmtXr8fd2YsoGfJJZCGVStm1Yw8ujh68C31Hw8YNCF4YkOnRZDnhw4cP6E014vzZCxQsWBALm1k/nU8iq7dv3uI125fNG7ehlU8LIxN9Jk0dl233l5W2bNqOo50rkRGRdOvxJ1a2Ztk6KcWXOXJ169UhaKE/5cpn3/6cVb7MJzG3NGHo8EHZmjGSNkdOQ0ODGQbT0Z2ZO3Lkdu3Yg62VE+Efw+nUuQPWDhZUqVI52+5PKpVy5NC/ONq58vLFK2rUrM78xQG5IkcuKioaQz0Tjv37H1paWswyN2TE6GHZeoItLCwMvznzWLViLerq6kzRnYhBLsmRO7DvEJZmdoR9CKNt+9bYOVpRPZtHYB07egJHO9eUy+5yUY5cTEwMJgYWHDpwBA0NdYw+TSaTnSdB0ubIqaqpMn7CaEwtjXPFvvXo4WNcHT04euQYnTp1ws/PjwYNfs/ZFoWsJZpLQpaKiIjAxcUFPz8/SpYsgYXNLHr27p6tjRpZfc4n2b5lJ8rKyujpT2Xy1Ak52hA7e/oc9jYu3Lt7nwoVyzNvvh/16mftaKmsklX5JLKKjo4meN4iFs5PCVUcNmIIDs7WCvkhnpX5JLK6eOEyDjbO3Lxxm7LlyuAfOEdhL1u9duU6M6Yb8+J55vJJZBUbG8uCoCXMD1yEVCplwKB+uMx2UMgRhWnzSSQSKROnjEN35lSZ8klkdfXKdextnLl25TolS5XAf94chc2RS5dPUr0qDi42OTpCLT4unsWfc+SSkunTryezFTRHLivzSWR188YtHG1duXD+ksLnyD24/5Dpk/V5+OARlSpXxN7JOkdHqH2VI9ejK3P8FDNHTiKR4Oczj0Xzl5KYkMioMcMxMNGjcOGcm9Xtzu17ONm7cebUWYXPkXv65CnTJulz7+59ypYrg72zNZ27/JFjx9KJiYmsWr4WHy9/4uLi6dSlIz4Bngo76iswYD6BAQuIj49n2IjBGJtmPs7iVzx88AgnezdOHDup8DlyEeERBPgFseKf1ZQrVxZvbx8GDBigkN/ThNxJNJeEbHH//n1MTIzZuXMXLVo1x87Rkjp1Feea5FXL1+LhNofo6JgsyyeRVXJyMhvWbsbT3ZvIyCjatGvFvGBfhRle++7de/SmGHDxwuUszSeR1bOnz3Fz9uTAvkMU0CmArYMlg4cOkEst37Jh7SZcnDyIioyiZ+9uWNqYyW20gkQiYcum7cx28eLjx3CatWhK0EI/ihT58Qx+OSFtPolOQR3MrUwYPHSA3GZhefnyFbNd57B7x16082tjaWPKiFHD5FLLt2zbsgMHG1ciIiLo0rUT1nbmVKosn9EKUqmU7Vt34ebsyYf3H2jUpCHBCxUnRy4yIgp9XSP+O3EqS/NJZPVljtwscwPGTRwjl1q+Zc+u/dhY2PPxYzgd/2iPjYNFluSTyCJlCuz9ODu4K2SOXFRUNMb6Zhw9fAxNLU1MTA0YOeZvuV2CHBr6jjkefmxavwVNTU1mGukyTXeSXGr5liOH/sXMxJoP7z/Qqk1L7J2sqFlLPjNPSaVSDh04gqOdGyGvQqhVpybzFwYoTI5cXFwcJoYWHNh3CHU1dQxNZjB2wii5NaO/zJGbpjcZfSNdudTyLSmTyVjxLvQdzZo3wcHFRq7fNY4ePoajnSvPnj6nes1qBC8MoErV7BvF+Cs+f9fw9vQnPj4ea2trjIyMFLIZLeRuorkkZKv9+/djZGTEnTt3+HvEEIxM9eV6OdOli5cx0JvFyxevqFuvNg4utjRtphijOSLCI5jrH8w/i1egqqrK2PGjMLc2kVsTJ10+CVKmTJvI9BmTc3T0TUZOnzyLvY0zD+4/VIhQxZzIJ5FVVFQ0QXMXsHjBPygrKzF85FBsHa3kum+5O3uycvnabM0nkdW5sxdwtHXl9q07lCtflrlBvjRsXF9u9dy5cw+9KQY8fvSEKlUr4+BiQ7v2beRWT1oxMTEsCEzJkQMYNOQvnNzs5NbE+SqfZPxIDIz0KFiooFzq+dKVS1exs3FOzZHzn+dNsxbyy5FLm09SsVIF7BytsjyfRFZxsXEsXvgPgQHzSU6W0G9AH9w8HOU66ivAJ5D5QYuIj09gxKhhGJnqU6RIzo2+yUjaHLkSJYvjE+Ap1xy550+fM22yPndu36VMmdLYOVnxZ7fOCjFCIj4+gX8WLyfAN4ikpCR69u6Gh7erXL9ozw9azFzfIOLi4hgybCAm5oYUL64Y2Te3b93F0dZFYXLkXr4MQW+yPtev36RkqRLY2FvSs3c3hdi3Podj+3oFEB+fwJ/dOuPtP1uuOXJnT5/Dyd6d27fuMGbMGNzd3SlTpozc6hHyNtFcErJdYmIi8+fPx87OjuTkZGYa6TJmXPZeB/2lL/NJLG1NGTi4v0JeUvXo4WOc7d059u8JChUqiMtsR3r16Z6jNeR0PomskpKSWL92E17uPkRHR9OufRsCgnxzdJrmiPAIZkw34tR/ZyhQID9mOZBPIqunT57h6uTBoQNH0NEpgL2zDQMG9cvRGnbt2IOtpSPh4RF06tIRG3uLLJkdKKslJyezeeM2ZrvOISI8gpatmxM43y9Hp2n+Kp/EwpARo7I3n0RW6XLk8mtjY2+R4zly+/cexMrcPkfzSWQhkUjYvmUnbs6ecsuRS5dPoqmB0ayZ2Z5PIquQV6/xcPNmx7ZdcsuR+/fIcUyNrXj/7j0tWzXHzsma2nVq5mgNP0MqlbJ7515cHGcT+vYdDRvVJ3jR3BzNkYuLi8PM2Jp9ew6gqqqKgbEe4yaOQUND8fatt2/epoz62rBVbjlyJ0+cxsTQnLdvQmnStBEOLjbUq183R2v4GVKplP17D+Jsn5IjV6dubYIXBeToyOyEhASszO3ZsXUXKirK6OlPU9h813fv3uPj5c/6NZ9z5KahO3Nqjtbw4vlLZrvOYc+ufbRo2YIA/wBatmyZozUIvx/RXBJyzLt377Czs2PBggVUqlQRa3vzbD9DKpFIcLZ3Y+3qDXLLJ5HVv0eO42jnytMnz6hWoyrBCwOy/TKFWzduozfNMOU+q1fF0cWW1m0V/4Mobaiimpoa4yeNZpa5UbY2DyUSCR6u3qxYtorExCTGTxrDTIPpCnM5Y0b+O3EKRxsXHj58TOUqlQhc6E+tbL5M4f69B+hOMeDhg0dUrlIJeydrOvzRLlvvMytERkYR6B/MkkXLUVFRYdTY4VjZmmX7vuXnPZdFC/6RWz6JrM6dOY+9jQt379yjQoVyzJ3vR/0G2ftF6fHjJ+hO0ufevQdyySeRVXR0NPMDF7EgOCVHbujfg3B0tc32kx5p80n+HjkEY1MDihZVjEtlMyKPHLkXz18yffJMbt28Q+nSpbB1tKRbjz8Vft+KjY1lYfBSguctzNEcuUULluLnPY/YmFgGDx2AqYWRwlwqm5GrV67jYOvC1cvXKFmqBL4BXrRqk70jj0NCXqM7WZ9rV29QvEQxbOwt6N23p8LvW/Fx8SxZvJy5fkEkJyXTu29PPLyzP0du+T+r8ZrtQ0x0DP3+6oO5lUmumJn61s3bONi4pOTIFS+Gl587HTpm77FPTEwM8wMXsWj+PxQpUgQPDw9GjhypkCfUhbxHNJeEHHf9+nUMDQ05cuRItmY7bN28A0dbFyIiIuWeTyKrxMREVi5fg49XAPFx8XTp2gmfAI8sH177ZT6JqaUxw4YPVsgREhl5cP8hTnZu/HfiFIULF8LN04nuPbtm+f18mU9i62ipMNfV/6ykpCTWrt7AnNm+xMTE0qFjW/zmeWf5qC9FyyeR1eNHT3BxnM3Rw8fQKaiDk6st/f7qk+X3c+jAESxm2fDhQxit27bEzlF++SSySk5OZuO6zXi4ZW+OXFxcHCYGFhzYfwgNdXUMjOWbTyKr589e4Obsyf69BylQoAC2jtmTI5c2n6R5i6bYO1srVBbiz5BIJGzdvAN3Z89szZFLSEjA3MSa3Tv3oaKqwkxDXSZOGouGpkaW3k92y6kcuTOnzmE005Q3b97SsHEDHJxtaNhIfpcSy0IqlbJj225cnTyyNUcuKSkJK3N7tm/ZgZKSMtNnTGHK9AloaWll6f1ktzev3+Lp7s3WzTvIl08LEzNDxk/K+hy5Sxcvo69rwquXIdSrXwcHFxuFnZzke1Jy5A7g4ujOm9dvqV+/LoGLAihbNmuzXj9nIXq6+xD2IYxZs2ZhYWFB/vyKf0JdyDtEc0mQC6lUyvbt2zE2NuL58xeMHjcCAyO9LPnykTafpGrVytgrUD6JrN6//4CPlz/rVm9EQ0MD3ZlTmWEwLdPblUgkzPHw45/FKxQyn0QWUqmUo0eO4WjryvNnL6hZszpBiwOoXLlSpredkk8yk/v3HipcPomsPoZ9xN8nkJXL16CmpsbkaeMxNJmZJWe4UvJJFhMfH69w+SSyOnHsJA62Lqn5R0GLAqiRBZdepcsnKVsGeycrunTtpPBnsTPyZY7cmPEjsbCelSX71vzARcz1C/6UTzIIE3MDhcknkdXpk2dxsHVJzT/Kqhy5ly9D0J2szw0FzCeRVXbmyP2zeAXenn7ExMQyYFA/zCxNcvSysuxw/txFHGxcUnLkypVlbnDW5Mi9ef0W3akGXLl0lWLFi2Jla06/v3rn6n0rO3Pk1qxaj7uzJ9HRMfTp1wsLm1lym0wmq1y5dBV7WxeuX71B6TKl8Js3h+YtmmZ6u+/fv0dviiEXzl+iUKGCWNqaMWCQ/CaTyQrZmSN39fI1nOzduXzpCoMGDcLLy4vKlXPXSU8hbxDNJUGu4uLi8PPzw8XFBQ1NDYxN9Rk2fLBMeTWREVEYzjDh+LGTKWdRzBU3n0RWt2/dwcHGhfPnLlKseDHm+LnRoaNsoYr79x7EysyOsLCPtGvfBjsnK6pVr5rFFctPQkICK/5ZjZ/3XOITEujarQtz/NxlGvUVExODsb45hw8eTd1PR48dketG32Tk3t37ONm7ceq/MxQpUpjZc1z4s1tnmbZ19PAxzEysU/NJ7J1tqFU7d42+yUhiYiJrVq5njqcfcbFx/NG5A75zvWSapjkuLg5TIyv27z2o8Pkksnr08DHODrM5dvQ4BQsVxMXdnt59e8q0rZMnTmNsYE7oW8XOJ5FV+hy5GNq2b83cQB8KFPz1sPuEhASsTO3YsX03KirKzDCYzsTJ4xQyn0RWWZkjd/7cRQz0ZvE65DX1G9bDycWWho0bZHHF8pOVOXJJSUnYWjqyZdN2AKbpTWaq7kS5hhZntZcvXuLu4sWeXfvJn18baztzho0YItO2Ll++iv50Y16+eEWdurWwd7bJkgaMovgyR65Js0YELQyQKUdOIpHgaOfGujUbkEqkTJo6Ht2ZU2X6fFVUX+bImVoaM2bcSJm29fbNW7xm+7J54zYaNKiPn58/nTp1yuKKBeHnieaSoBBevXqFlZUVy5cvp1admtg5WP309e6p+STz/yExMZHRY0dgYKyXo8G7OUkqlbJvz0FcHFJCFevVr0PQork/Pbz2cz7J3bv3KV+hHPbO1nTq3DFXn2nMyLt37/H28GfDuk1oamoww3A60/Wm/PT68/znEzQ39+WTyEIqlXL44FGc7N14+eIVNWvVIHiRPxUr/dzlpLk1n0RWHz6E4TdnLqtXrkNDQ52pupMwMJ7x0+svWrAUvznziIuLY9DQAZiaG+aKfBJZfZkjF7TA/6cb2l/mk9g6WNKrT488u2+lz5FTZfykMb+UI5c2n6T/gL6YW5lQqnTJbK5afk7+dxoHG5eUTLfKlQhc4EutOrV+at3Q0HfoTTHg0sUrFClSGCtbM/oN6JOrR0hkJLM5cuvXbMTFyYPoqGh69emOpY0pZcvlXKhzTvsqRy7Yl/oN6/3Uuh8+fGDGNCPOnblAwYI6WNiYMmjIX3l238psjlzaOIuu3btgbWeukJPJZJVLFy/jYOPCjeu3KFO2NAFB3j99yV98XDxLF68gaO4CNDU1cXV1ZdKkSQo5mYzwexHNJUGhnDt3DgMDfc6cOUuPXt2wtDGlfIVy313+y3wSeydratSsnoMVy09cbBxLFi1jnn8wyckS+vbvhbuX83eH18bExDDL0JKDBw6joa6OoclMxowfmevySWR188YtHGxcuHjhMsVLFMfH34O27Vt/d/kv80kcXGyo/ZNfVnK7+PgEli9dib9PIImJCXTv2Q0vX7fvTtOckJCAmYk1ez7lk+gb6jFh0phcl08iqzu37+Fo58rZ0+coWrQIHt6udP7zj+8unzafpFGThjg429DgJ7+s5HZf58j9gU+A53dHPCQlJWFpZseOrTtRUlJGd+YUJk/LffkkskqbI1eocCHcPJzo0ev7OXLp8kka1MXR2YbGTRvlXMFy9Ks5cklJSTjYuLBx/RakSJmmO4mpupPQ1s47IyQy8qs5ctev3mDGdCOeP3tBrdo1cXCxoUXLZjlYsfyk5si5+xAZEUnrti2ZG+Tz3ZOYEokEFwd31qzaQHJyMhOnjENPf1qumEwmK6TPkcuPrYMlg4cN/O7yd27dQXeqIU8eP6VqtSo4uNjQtt33j8/ykq9y5Jo3IXChH0WLfnvUl1Qq5cC+Q7i7ePHqZQgzZszAzs4uV0z4IfweRHNJUDgSiYS1a9diZmbG+/fvmTR1HNP0Jqc74Hv65CnTJxtw9869PJNPIqvXIW/wdPdh25Yd5MuXD1MLQ8ZOGJ1umeDAhcz1CyY+Lp6hfw/GxNwgR6e9VhRSqZQ9u/bh4jibt29CadCwHkGLAihd+v8zjqTkk8zkxvVblCpVEhsHS3r06vpb7luhb0Px8vBj84ataGpqYmCsx5TpE9Mts3TRcny8/ImJiWXg4P6YWhjn+nwSWUilUg7uP4yTvTshr0KoXbcWwQv8KZ/mrOub12/RnaLPlcvXKFa8KNZ2FvTt3+u33Lfev/+Ar1cAa1dv+JQjN4UZBtPTLbNqxVo8XOfkqXwSWXzOkXOyc+PZ0+fUqFmd4C9y5N69e4/eVEMunr9E4cKFsLQ15a+BuTufRFY/kyO3cf0WXBzciYyMokevrljamGV4Iisv+1GO3Mewj8yYbsSZU+cooFMACysTBg8b+FuOkIiIiGSefzBLFy9HVeXbOXLbt+7E3tqZiIhIOv/5B9Z25lSuUkl+RcvRmVPnsLdx/m6OXGREFAZ6xpw4fop8+bSYZWHE8JFD81Scxc9KmyOnpKzE8BFDsXNKnyN35/Y9XBzcOXXyDN26d8PP14/atXPXpAxC3ieaS4LCioqKwsPDAy8vLwoVLoSZhRE9enfDzNia/XsPoKam9ml2oNF5Kp9EVpcvXsHe1oUb125SukxpAgLnEBcXn5pP0rRZYxxcbKhbr468S5W7uNg4Fi1YSmDAAqRSCf0G9MXRxQZbS0d2bt+TZ/NJZHX92k0cbJy5fOkqJUuWwCfAExVVFQxnzOJ1yBsaNKyPo4tNnsonkdXnoeoBfoEkJyXTq0933DydcLZ3T80n+Tw7UF7KJ5HV7Vt3cLR15dzZCxQrVpQ5fu4UKKiTLp/EwcWWZs2byLtUuUtISGDFsjX4zQlIyZHr2hlPXze8Zvul5pNMnjaB6TOm5Kl8Elndv/cARztXTv13hsJFCjPby5kyZcswY6oBTz816RxdbGjZOnunnM8NvpUj5xPgScCnJl1ycjITJo1Fz2AaOjq/nv+V16TPkdPBxd2BajWqoTfFgEcPH1OlSmXsXaxp36GtvEuVu+TkZNav3YSnmzfR0TG0adeKgEBvFi1YypKFy1Mmkxk3En0j3TwbZ/Ernj19jquTBwf3H0ZHpwB2Ttb80bkDft5zWbNyPdWqVcXHx5devX7PE1OC4hPNJUHhPXnyBFNTUzZt2oSamhpJSUm/RT6JLCQSCdu27MDd2YuwsI9IJJJPswNZ5Ol8Elm9ehWCh6s3O7fvRlVVhaSkZP4a2A8zS+M8nU8iC6lUyq4de3Bx9OBd6DsAihYtgpVdyuxAv+MIiYykDdlUUVEhOTmZ3n17YGE9K0/nk8gibY5cSMhrlJWVf4t8Elm9e/ceb09/1q/ZmLpvdevxJ1a2Znk6n0QWUqmUI4f+xdHOlRfPX6Ksokz+/PkxtzRh6PBBv+Xom4yEhYXhN2ceK5evSd23OnXugLWDBVWqiJmnvnTs6Akc7Vx58vgpKirKaGnlY5a5ISNG563JZLLC5xy5ZUtWoqysRHKyhLbtW2PnaEX1LJhxNa9JmyOnpqaGlpYW9vb2zJgx47eJsxByJ9FcEnKNuXPnoq+vz5Ll83P99O/ZLTo6mqEDRhES8ppT546K0Tc/sHvnXmZON8bCxpQp0ybIuxyFFhsby6hh43lw/yGnLvz72+STyGrlsjXY2zjj7TebAYP7y7schRYfF0+7lp0pXKQwm3es+23ySWS1bctOjPXNcJ3tyPBRQ+VdjkKLj0+gU9tuqKmrsXPvZnQKiuPTjBw+9C+Tx03HxsGCCZPGyrschZaYmMifHXuREJ/AnkPbRPbND1w4f4mhA0Yyy8KI6XqTxUnPDCQlJWFsYM7J46e5c+cOJUr8fpEDQu7zK70gcepQkKtGjRoBULFSBfkWkgtoa2tTrFhRNDU0RGPpJ1SomLJPlSlT6gdLClpaWhQvURw1dXXRWPoJpT/tUxXE+9YPaWimvF8VKVJYNJZ+QtlyZQCoUEmMVvoRDQ118mnno1ChgqKx9BM+71sVK4r3rR9RU1NDW1ub/AXyi8bSTyhfPiXbrEKFcqKx9AOqqqqULVuGIkWLiMaSkCeJ5pIgCIIgCIIgCIIgCIIgM9FcEgRBEARBEARBEARBEGQmmkuCIAiCIAiCIAiCIAiCzERzSRAEQRAEQRAEQRAEQZCZaC4JgiAIgiAIgiAIgiAIMhPNJUEQBEEQBEEQBEEQBEFmorkkCIIgCIIgCIIgCIIgyEw0lwRBEARBEARBEARBEASZieaSIAiCIAiCIAiCIAiCIDNVeRcgCFkhNjaWs6fPc+P6TW5cv8WN6zd59TIEAH0jPQxNZnx33YjwCM6eOc+Naze5cSNl3dC37wDw9HFj8NABP7z/5ORkdmzdxZbN27l14zbR0dEUKVKEZi2bMm7CKJo0bZw1DzSHyPv5zC2qlKv908u2at2CNRuXp/vd65A3HDxwmDOnznHrxm1ev34DQPESxWjUpCF/jxhCm7atsrTm7JaZfefs6XOcOH6K69du8Ozpc8LCPhITHUPBgjpUr1GNbj3+5O8RQ9DU0vzm+ocPHk3d9169CuHD+w/ExydQuEghateuRa++PRgwqB+qqrnjoy8sLIxDB45y6r8z3Lxxi5cvXpGcnESRIkWo37AeAwf3p3vPrj/cTmRkFKtXrOXQgSM8efyUqKgoihQpQqXKFWnRqjkTJo1Bp6BODjyinHHi+EnWr9nElctXeffuPUooUaJkcRo3acTwkUNo2brFV+tk9rWsaDLzOvweawsH1q5aD0DZcmU4ceZwhsvv2bWfLZu2ceP6TcI+fERVVZVSpUvSomUzRo8bQZ26P/+cK6LgeYvwmu2T+v9HL25/tUx2/B3kLSseU2joOxYGL+HIoX959TIETU1NqtesxqDB/Rk6fDBKSkrfXO/J46ccOnCEM6fPcef2Xd6FvkNFRZWSpUrQvEVTRo0dQf0GdbP08WZWVu0DoW9DWbl8Df8eOc7zZy+Ji4ujaLEiVKtWlZatWzBp6jjU1NTSrZPZz1RFtGnDVsyMrX643Iq1S2jXvk2635kaWbJ547YfrnvvyfVcc5wgCIpGvHKEPOHq5etMGDNVpnUP7D/8Ux9U3xMdHc20STM5eeI0ACoqKuTPn5+3b0PZtX0Pe3buw8zSmCnTJ8p8HzlNns9nblKseLEMb09KTOTjx3AAGjSsl+62V69CaN+yC1KpNPV3WlpaSKVSXjx/yYvnL9m1fQ9Dhg3EzdMJFRWVrH8A2SAz+87C+Us5evhY6v/z5cuHuro6799/4P3pc5w5fY5/lqzgn1ULqVKl8lfre8324d7dB6n/z59fG2VlZd6+CeXtm1CO/XuClctWs2TFAor/4G+nCFo27kBSUlLq/zU0NFBVVeP16ze8fv2Gg/sP07FTe4IW+qOlpfXNbZw+eRaDGbN4F5rS4FVXV0NTSyt1G2dOn6Nbjy7UyQPNJalUio2lY2oDBEBTM+VL0/NnL3j+7AU7tu1iwuSx2NhbpFs3M69lRZSZ1+G3nD55lnWrN/zUsvHxCcyYZsjhg0dTf6etnY/ExEQeP3rC40dP2Lh+C5a2pkycPC7LasxJjx4+JsA38IfLZfXfQRFk9jFdv3aTcSMnERb2EUjZN6Kjo7lw7iIXzl1k7+4DLPwnEHV19XTrXTh/iaEDRqb7Xf782iQkJPDk8VOePH7K5o3b0Js5FSNTfZnry2pZsQ/s2rEHK3N7oiKjgJTPAjV1NV69DOHVyxCOH/uPkaOHoVYwfXMps5+pikxZWZkiRYt89/Yv95+0NDQ0KKBT4Lu3f6+5KQjCj4nmkpBnFCxYkLr1a1OvXh3q1q+Di+Ps1BEzP1K8RDHq1K1Nvfp1qFe/LtMn//yBiaWZHSdPnEZZWRljMwPGjBtJ/vzahH8MJzhwEQuDlzDbdQ5Vqlbmz26dZX14OU5ez2ducu7yiQxvX7zgH9ycPQEYOnxwutskyRKkUilt2rVi4OD+tG3XhpKlSiCRSHj44BFzPPw4uP8wG9dvoWSpEhibGmTb48hqsu47bdu3pkPHdjRr0YSKlSqSP782kDKCZ8fW3Xi4efP82QumT5rJ3kM7UFZOf2V3j17dGTdhNE2bN6F8+XKpZ2PfvH7L+rUbCfAN4sb1W5gaWrJs9aKsf+BZLCkpiYaNGjBo6F906NiOChXLA/Di+Uvm+QezYd1mjh09gbW5PT4Bnl+tf+H8JSaOnUZcXBzde3Zl+owp1G9QFyUlJWJjY7l39wGHDhymQIHvH2TnJps2bE1tLPXs3Z1Z5oZUrlIJSGkGeLh5c3D/YZYuWk7zFk3TjfrKzGtZUWXmPTyt2NhYrMzsUFVVpVadmly/eiPD5YPmLkhtLI0aOxzdGVMpVbokEomEmzdu4+zgzoVzF3Fz8qRFy+YKN9LkRyQSCeYm1sTHx9OkaSMuXbyS4fJZ9XdQJLI+poiISCaNm0ZY2EeqVquCt78HDRrWIyEhgXVrNuLq6MHxY//h7OCOs5t9unWTEpNQUVGhy59/0G9AX1q3bUHhwoVJTk7mxvVbuDp5cOHcReb6B1OmXBmGKdDrNDP7wJ5d+zCcYYpEImH4yKGMmzia6jWqARAVFc2tm7c5sO8Qqmpff6XL7GeqIitdptQPR09+T59+PfHydc/iigRBANFcEvKI5i2bcvnmmXS/83T3+c7S6Q0Y1E/mS7Xu3L7Hru17ABg7YRS6M6ak3lawUEEsrGfx6uUrdu3Yi6uTB53//CNXfHjL6/nMazas2wxAsxZNqVI1/VlBnYI67Ni7iXr103+xUlZWpnqNasxfPJcJo6dy7N8T/LN4BXozp6GhqZFjtcsqM/vOhEljv/n7woULM3bCKNTV1bG2sOf+vYdcuniFZs2bpFvue5cXlCxVAn0jPeLjEwiet5Djx/4j5NVrSpcp9VN1ycvq9cto3bblV78vV74ss+e4oKKqytpV69m2ZSezLIwoU6Z06jKxsbHMMrQgLi6OseNHYe9snW4bWlpaNGxUn4aN6mf748gpWzdtB6BipQr4B85Jd1lDlaqVmTffl65/9ObZ0+fs3rXvpy4p/Cyj17Iiyszr8EtzPPx4+vQZevpTeR3y5ofNpa2bU/4OLVs1x8nVLvX3ysrK1G9Ql8XLgmnb/A+io2PYu3t/rmsuLV+6iosXLtN/QF8qVqqQYXMpK/8OiiIzj2nxgqWEvn2HpqYmS1csoHyFckDKKJMx40YSFRXNnNm+rFu9kfGTxqQbTVOxUgUOHN2V2jD+TEVFhYaN6rNq3VL+6j2UO7fvMn/eIoVpLmXm+Xr75i3W5g5IJBKs7MyZNGVcutvz59emRctmtGjZ7JvrZ/YzVRAE4Vcp/rdcQfgJmblkKDPr/nvk/8ONp0z79mVvny+He/rkGRfOXZT5vnKSvJ7PvOTihcs8uP8Q4JsHuTo6Bb5qLKWlpKTEkL8HAhAdHcODBw+zp9Aslp1//0ZNGqb+/Drk9S+v3zjN+m8+5Vspsm81ltIa+veg1J+//MK/dfMOnj19TvESxbCwnpUt9Smat29DAahdp9Y38zLU1NSoXacWADHRMT+93R+9lhVRVr0OL1+8wvKlq6hcpRIz9Kf/1Dqf/w71v3P5oI5OgdQGwa/8HRTB82cv8Pb0p3DhQtg4WPxw+bz4eZiZx7TlUwO4T/9eqY2ltMaOH4m2dj6Sk5PZvmVXuttKlyn1VWMpLXV1df4a2BeAp0+fEf7pMlZ5y8zztWzpKsLDw6lbrzYTJ3+7UZQZmf1MFQRB+JJoLglCJrx8+QqAAjoFKFmqxDeXqVqtSur12yeOn8yx2gT52rB2E5Cyb/Tq012mbWho/H+kUnKyJEvqys3On7uQ+nOFihV+ff2zKc1dJSUlyn+6xCw3y2j/+DyKp1fvHrlixFtW+Pxl9fatO+myqj5LTEzk9q07ANRv8PO5SVnxWs6N4uMTMJ9lg1Qqxc3D8af3owoVUl5bN67d/ObtERGRPH70BPh+A0pRWZrZEhMTg7W9OUUzyHsRvvbo4ePUIOs/OrX/5jLa2to0a9EUgP9kOF5K954oyf2fmZ/fx/sP7JctOUCZ/UwVBEH4kmguCUIWkGZwECORSFJDm+/euZ9TJQlyFB0dzZ5d+wDo27/Xd8OWf+TM6XNASghzRmds87K42DgeP3pC4NwFqZk3LVo2++lQ5ejoaO7eucdsFy8WL/wHSLl0My98MTz7af8AqFW7RurP8fEJXL+WMpKpXoO6vHz5CiszO9o270TNyg1o3qgdk8ZN58jhf3O65Gw1asxwIGWUqIHeLJ48fpp626OHj5k5zYhnT59TsWIFJvzkKICsei3nRnP9gnhw/yFD/x70zRn2vmfk6L+BlPcvO2snXoekjBKUSqXcuH6TSeOmEx0dQ5OmjVJHmuQG61Zv4NR/Z2jbvjUDB/8l73JynbTHPzVqVv/ucjU/3Xb//q+P1v38mVmiZHEKFy70y+srkufPXvDmzVsA6tevw53b9zDQm0XLJu2pVaUBbZr9wczpRlw4f+mXtpvZz1RF8eF9GP16DqJejabUrtqIjm26YjTTjDOnzv1w3VP/naFz+x7UqtqQBrWa0aNLP5zs3VKb3oIgyE5kLglCJpQrVxZICVV8+eIlZT/9P617aQ6oPh8oCHnbru17iP50ucew4UNk2sbzZy9YszIlnLh3354UKJA/y+pTdKFvQ2nZpMM3b+vStRNePm4Zrn/54hUG9R/+1e9VVFQYOLg/ji62WVKnPEWERxAcuBBIyfRImwP08sVLEhISAXj29DmOti5ERUWjrq6GVj4t3r97z5FD/3Lk0L8MGz4YN0+nPDE7TpeunbBxsMDTzZu9u/ezd/f+1Nni4uLi0Cmow8gxf2NiavDTr6eseC3nRjdv3GJh8BKKFS+GpY3pL607etwIQkJes3jBP6xavpZVy9emzhaXkJBI8RLFmKY3GX1D3Vxz2djrkDe4u85BU1MT19mO8i4nV3qb5vinZKmS313u821RkVFER0ejra39U9u/dPEyB/enBDwP+3twrn9PS9vouHDhMnN9A0lISERTUxN1DQ1ev37D7p372LNrP4YmM5hpqPvdbWX2M1URxcbGcuP6LQoWLEhSUmLqjKDbt+5k8LCBuHk4fvPyaICQkNepMztHRUVx7+597t29z5qV67BxsEw9USEIwq8TI5cEIRM6dvr/h/U8//nfXCZw7oLUnz9PIyvkbes/XUZTu04tmcJq42Lj0JtmSGxsLEWKFMbM0iSrS1RoyioqFCtejGLFi6W7zKFXnx5YWM+i0A/OSKupq6Wur67+/6mZh48air6xXuoscrmVRCLB2MCct29C0dDQwME5fbMsbdZIYMB8VFVVmTffj+t3L3Ll5llOnD1Mrz49gJR9dcmi5Tlaf3aaMGksQYsCKFqsKJDSVIqLiwMgMSGRmOgYIn/hfTizr+XcKCkpCXMTG5KSkrB3skKnoM4vra+srIyZpTEe3q5oa+cDUnLjPjc84+MTiIyMJCY2Nstrzy7WFvZERkRiYKyXOmuj8GuioqNTf9bK4D047W3RUdHfXS6t9+8/YKA3C4lEQqXKFZmi++0MzNwkPPz/7+O+XgGUKFmCFWuXcOPeRa7dPs/+Iztp1boFUqkU3zlz2bfnwHe3ldnPVEVSsmTKBB27D2zj9sOrXL55hpv3L7Nx2xratm8NwKb1W3BxmP3VunXr1cHBxYYTZw5x51HKutfunCdooT8VK1YgISEROysn9u7+/nMpCELGRHNJEDKhVu0a6b6kuTjO5sXzlyQmJvLo0WPMTKw5cuhf1NRSvuDmhpnihMy5d/c+Vy5fA2QL/01KSsJwxixuXLuJmpoavnO9vpvnlVcVLVqEc5dPcO7yCW49uMzJc0fR05/K4YNH6dX1L9au2pDh+vXq102z/hWOnNjH6LEjWLNyPT069+XQgSM59Eiyh5OdG0cO/QuAo6sttevUTHe75NNluJDSiJo9x4Vefbqnvg+VLVuGgCDv1HDr4LkLvplRlNvExsYyc7oRk8ZOp0zZ0ixfs5gL105x4doplq9ZTLUaVdm6eQcD+gzl9q27P9xeZl/LudX8wEXcunmbzn/+Qe++PX95/Q8fwhg1bDymRpY0btqIDVtXc+XWOc5eOk7wogCKFCnM6hXrGNh3WOolc4ps2+YdHD18jDp1azPxi9m6BPmLjo5mynhdXr54Rf782gQu8Pvp0U6KTCL5//u4VColaKE/7dq3ST2OrF6jGouWBVG8RDEAAnyDvrutzH6mKpL2HdtiaDKD2nVqoqGhDqSMSm7arDHLVy+ma/cuAKxasfary9zGTRzNmHEjKVuubOqoSS0tLXr06saWXetSc/vcnD1S4ywEQfg14puuIGTS7DkutG7bCoCli5bTofWf1KzcgD879GLT+i107d6FTp1TRjgV/MUzwELu83mkg4aGxi/niSQnJ2M005QD+w+jqqqK71wv2ndsmx1l5hpKSkqULlMKEzNDfOd6kpiYiK2VY2ow848oKytTqXJFHF1tsbAxJTo6BqOZpuku0chN3Jw9WbFsNQA2DhbpZoz7LO0Xq0qVK9Ktx59fLaOsrMzkqeMBCAv7+N3w5dzE3cWL3Tv3UaVqZTZsXkX7Dm0pUqQwRYoUpn2HtqzftJLKVSrx4UMY9jbOP9xeZl7LudX9ew+Y5x+MtnY+nNzsZNrGLEMLzpw+R8tWzVm+ejHNmjdBR6cAxUsUp3vPrmzYupoiRQrz7OlzPN29s/gRZK3Q0Hc4O7ijoqKCm6fTdy+zEX4sf5r3pdjYuO8ul/Y27fwZN4liYmKYOGYaly9dRVs7H0tWLEhtmud2+dM89jbtWn1zdlltbW1Gjx0BwJ3bdwkNfffD7Wb2M1WRKSsrp17GK5FIOPzpJMzPKFy4MLozpgDw8sUrbt64lR0lCkKeJ5pLgpBJ+fNrs3LtEvzmzaFr9y5UqlyRcuXL0rZ9a+b4uTN/8Vw+frpM5XcNZf5dJCQksH3LTgB69Or2S5eTJCcnY6Rvxu6d+1BRUcEnwOO3mpnqZ/To1Y0yZUsjkUjYsHbzL68/esxw1DXUiY6OYcf2PdlQYfaa7eLF4gUpoeRWtmZMmPTtUOpSaUa6Va1W5bvbq1ajaurPn2e+zK2ioqJZt3ojAKPHjvjmzGaaWpqMGTcSgAvnLvLu3fvvbi8zr+XczN7amYSERHRnTqNgQR2io6PT/UtKSgZSRlJ8/l1iYmLq+g/uP+TfI8cBmDR1/Ddzb4oVK8qAwf0B2L/3kEKPEPB09yEs7CN/jxxC1WqVv3o+0j72z79LSEiQY8WKq0TJ/78vvXn9/RFrn2/LXyB/hiOQPjeWzp29QL58+ViyfD7NP800lxekHbFcrVrV7y5Xrfr/b3v14tfexzP7maqIKlWuSJEihQF4/vT5L63buGmj1J+fPX2RlWUJwm9DnIIRhCygrKxMv7960++v3l/dlpSUxO3bKZdgNGnaOKdLE3LQoQNH+PAhDPi1y2g+j1jatWNvamOpT79e2VVmrlaqVElevQzhyZOnP174CxqaGhQqVJC3b0J5KsP68uTu7MWiBUsBsLCexaRPo46+pVDhQpQqVZLXGXyBA0j7nT4vhN9+vrQvo0ycSpUrpv784tkLin3KZvqSrK/l3O7585QvVF6zffCa7fPd5V69DKF+zWZAygi6z43O+/f+P8PXz/wdYmNjeffuPcWLF8t07dnhxbOU52P1inWsXrEuw2U/Px/jJo7GztEq22vLbWrW+v8Mcffu3k/XFEnr7t2USVCqf+d2+H9j6eyZ82hpabFkeTAtWjXP2oLlrHr1aqioqJCcnJzhcul6szK8j2fmM1UQBOFLYuSSIGSzwwePEhkRiaamphiJksd9voymYqUKtGz9cwe6ycnJGM6Yla6x1Lf/101KIWW0xOcvv/l/cLnEt0RFRfPhfUrDIDdlcrg5e6ZrLE2Z/uOw2nafLqd8kMF03g/uPUj9uVz5cpmsUr6Ulf//pSqjUVhpRytldMmNLK9l4Yu/QwajKN6Fpvk7fAr9FvK2ylUqUaZsaQCOHT3xzWViYmK4cO4iAO06fPuS8JiYGCaMnsrZM+fJly8fS1fMp2XrFtlTtBxpaGrQomVKw/LBgwzex++nvI8rKSlRrvzXMxZnJLOfqYro6ZNnqScGPmco/azLl66m/vyr6wqCkEI0lwQhG71//wF3Fy8g5VKNgoUKyrkiIbu8fPmKkydOAzDk70E/NRLk84il3Tv3fcpY8vxtG0s/Eyi9cf0WQt+mZEp8+WXiZ9ZfFLwkdblWueTLiJuzZ7pL4X6msQQweOgAIOVA+8C+Q1/dLpFIWPRpu6VKlaRe/TpZVLF8VK1aBU3NlFmmNqzd9M39ITk5mXWrU4JrCxYsSJWqlb+5LVley3nFiTOHefTi9nf/DRryFwBly5VJ/V3ayzPT7kerV357pE9MTAxbN28HoFbtmuTLp7jNpbWbVmT4fOgb6aUu+/l3YtTStykpKTHw0+WQu3bs5cXzl18ts3LZGqKjY1BRUaH/wD5f3f65sfT5Uri82lj67PP7+Kn/znDj+te5eNHR0axasRaARo0bULRokdTbMvuZqoh+dAmtVCpNPeZWVlam859//PS6H8M+EjxvIQCly5Smbr3amStWEH5Torkk5BnhH8P58CEs9d/nmTbiYmPT/T46+uupbdPe/vmMB0BMdEy638d+Y+rkI4f/5Z/FK3j65Fnq8OXY2Fj27NrH4H7Defb0ObXr1MJo1sxseuTZQ17PZ261cd0WJBIJqqqqDP70BSwjnzOWdu3Yi6qqKn7zvPLMpXCy7DsXzl1i2KBRbN20nZBXr9Nt7/GjJ3i4eWNj4QBAxYoVGDxkQLpltm/dxeTxuuzbcyDd6BSJRMLtW3exMrNjrn8wAE2bN6Fjp/bZ8dCzVNqMJWt78wwvhftSi5bN6Nk7ZaSkpakte3cfSP2y8fLlKwz0TLjz6XJdE3PDXD+TpaaWZurlazeu32LyOF3u3L6HRCJJ3QcmjJnKxQuXARg/aXTqbEFf+tXXsqLKzHu4rMqWK0uXrp2AlFG7xvpmPH3yDKlUSmJiIhcvXGb4kLE8+5SFMmnquCy7b0Ulj79DdpP1MU2aOoHiJYoRGxvLxLFTuf5pIoGEhARWrViL75wAAP4eOYQqVdI3f2NjY5k0djrnzl5AWzsfS1cuyDWXwsn6fPUf2JeGjRoglUrRnWLAyf9OI5FIgJRRqVPG6xH69h3KysqYmBumWzezn6mK6OWLV/zVeyhrVq3n2dPnqQ0jiUTC5YtXGD9qSurJlOGjhqY7gbBt8w6mTZrJ3t3pjxHiYuM4sO8Qg/oPT31fsrSZles/EwVBXkTmkpBn9Okx8JvD8BfOX8rC+UtT/z9oyF94+bqnW6ZZgzbf3KaDrQsOti6p/9c30sPQZEa6ZZ48foqLw+zUGWXy589PZGRk6gFAi5bNmL94LppamjI/NnmQ1/OZG0kkEjZt2ALAH507pAsu/Z6L5y+x61OotJKSEg62rjjYun53eTtHy1zTfJJ13zl/9iLnz6ZcEqGhoYG2dj5iYmKJi/v/7EG169RiwZJ5X72epFIphw8e5fDBowDky5cPTU0NoqKiSEj4f+hu67atCJzvq/CjUV6+fJX6XCkrK7MgaAkLgpZ8d/nJU8czedqEdL/z8nXj/bv3nDt7Ab2pBqhrqKOlqUV4eHjqMvpGeqmjUXI7cysTnjx+yrF/T6T+U/80VXVC/P9Dlvv2742e/rRvbkOW17Kiysx7eGZ4eLsybtRkbly7ybYtO9m2ZSdaWlokJiamG00xZdoEBg7+K8vuV1HJ6++QnWR9TDo6BVi8bD7jRk7i/r2H9O81mPz5tYmPT0gNR2/fsS029pZfbXvv7v2cOX0OgKSkZGZMM8qwxuBFATRtphg5l7I+X8rKyixcOo9Rf4/n/r2HjP57AlpaWqiqqRIZEQmAmpoaji42tPk0a3FamflMVVTXrl7n2tXrAKhrqJNfW5uo6Oh07/GDhw3E3sk63XrJEgkH9h1KbT7ly5cPDQ11IiIiU08Mq2uoY21nnmuOtQRBEYnmkiBkUrv2bRg7fhQXzl8k5NVroqKiKFa8KA0a1qf/gD706tND4b/ICplz8sRpXr0MAX4+/PfzmUuAxMRE3v1gCuG4uHjZC8wF6jWoi4+/B2dOn+P6tZuEhr7jY9hH1NXVqVixAnXr16FHr6707N39myNOOnXpiLunE2dOn+f2rdu8C31PeHgEmpoalK9QngYN69GnXy86dekoh0f366Rp9g+JRPLD/SM6Ouar3+XLl481G5ezcd1mtm7ewb2794mOjqFUqZI0a9mUseNHKcyXr6ygqaXJ0pUL2Lv7ANu37uTGtZu8f/8elJQoXaY0DRvVZ/CwAXTu8sd3tyHLa1lIr0iRwmzZsY7NG7exd9d+bt26Q/jHcFRUVChTtjRNmjZi+KhheWpmL+Hn1W9Ql31HdrIgaDFHDv1LyKvXaOXTomHNBgwa3J8hfw/65qiRtJ+Z8fHxxIdm/JmYmOakQm5WvERxduzdwsplq9m1Yy+PHz8hPi6OcuXL0rpNSyZMHkvNWjW+Wi+zn6mKqFixojg423Dp4hVu37rNh/dhhIdHoKGhTvny5WjStBFD/h5Es+ZNvlq3dZsWmJgbcvniFR7ef0TYx49ERkaRP39+KlaqQOu2LRkxapjIWhKETFKS/sQcsBERERQsWJDw8HB0dH6P6XiFnHHixAk6dOjAoWN7vpt/Ifzf2BGTuH/vAacu/CvvUhTe9Ws36d9rMAFB3uIs1E+YNmkmF85f4sLVk/IuReEdOnCEKRP02LhtTZ5qzmSX9q26ULZsGdZtXinvUhTe+XMXGTZwFCvXLaVtu9byLkfh/dmxF9ra+di+Z5O8S1F4d+7co9ef/Vn0T1DqpYvC9/Xq+heJiYkc/He3vEtReG9ev6V1s47ieOsnebh5c+jA0dQwdkFQdL/SCxIXlAqCIAiCIAiCIAiCIAgyE80lQRAEQRAEQRAEQRAEQWaiuSQIgiAIgiAIgiAIgiDITDSXBEEQBEEQBEEQBEEQBJmJ5pIgCIIgCIIgCIIgCIIgM9FcEgRBEARBEARBEARBEGQmmkuCIAiCIAiCIAiCIAiCzERzSRAEQRAEQRAEQRAEQZCZaC4JgiAIgiAIgiAIgiAIMhPNJUEQBEEQBEEQBEEQBEFmorkkCIIgCIIgCIIgCIIgyEw0lwRBEARBEARBEARBEASZieaSIOQiycnJSKVSeZch5EFi3xKyi1QqJTk5Wd5lCHmQ2LeE7JKyb0nkXYYgCEKuIppLgkIImruAd+/ey7sMhZWcnIyNpSPnzl3g/fsPuDp5IpGIg57vuX71BrqT9QFwdfLg5o1bcq5IcUkkEpwd3Dn+739ERERgb+Mi9q0M3Ll1B3sbZwD0pxtz+fJVOVekuCQSCR5u3rx9E8rVK9exNLUlKSlJ3mUprAf3H2JqaAmAiYE5585ekHNFiksqleLnPZfnz15w9+59ZhlYkJCQIO+yFNbTJ0+ZMc0QAAtTW06eOC3fghRc0LyFPHr4mOfPnjNzujFxcXHyLklhvXjxigljpqCkpIS9tTNHDv8r75IU2plT5zi47zBKKMm7FEHIFqK5JMhV69atmTt3LkcPH6dL+54sXvCPOED8wsb1W2hSrxVrVq6jc5c/aN+hDUsW/kPTBm3YtXOvvMtTKB/DPjL67wkM6DuMqOhoJk+dQGxMLP17DWHsyElEhEfIu0SFsn3rLprUa80/i1fQvmNbOnXuyMplq2lSrxVbNm2Xd3kKJTIiigmjp9C352CiIlP2rbi4OIb0H8GIIWP58OGDvEtUKHv3HKBZw7YsCFpMqzYt6Na9C+vXbqJJvVasXb1e3uUplJiYGKZOnEHPP/vz/v17Jk0djyRZwoghYxkyYAShb0PlXaJCOXLoX1o0akeAbxDNmjehV+8ebNm8nSb1W7N86Sp5l6dQ4uLimDHNiK5/9CHk5WsmThmHiooyY0ZMZECfoYSEvJZ3iQrlxLGTtGzSnjmzfWnQsB79B/Rhz659NK3fhoXBS+RdnkJJSEjARN+Mzu268+jhY8ZPGoOWlhaTx+nSp8dAnj99Lu8SFcrzZy/QnWLAiKFjKVmyJGvWrJF3SYKQLZSkP3EdREREBAULFiQ8PBwdHZ2cqEv4zbx//x4HBweCg4OpULE8VnZmdO7yB0pKv29n/9aN2+hNM+Tpk2dUr1ENRxdbWrVpAcCxoydwtHPlyZOnVK1aheBFAVSrXlXOFcuPRCLB3WUOK5etJjk5mfGTxjDDYDo6OgUI/xhOgF8Qy5euQk1NlXETRmNqaYyy8u/bW7937wG6k/V59PAxVapUxt7FmvYd2gJw8r/TONq48ODBIypVrkjQAj9q1akl54rlRyKR4OMVwJKFy0hMTGT02BEYGOtRqHAhIiOjCAyYz5KFy1BRUWbEqGHYOFj+1vvW48dPmD5Jn3t371OhYnnsnKzo1LkjSkpKnDt7AQcbF+7cvkv5CuWYF+xL/Yb15F2yXM31CyJ43iLi4+MZPnIoRqb6FC1ahOjoaBYELWZ+0GKUUGLIsIE4uNigqqoq75Ll5vnT50yfYsDtW3coU6Y0to6WdO3eBSUlJS5dvIyDjQs3rt+iTJnS+AfOoWnzJvIuWa4WBi/B3yeQuLg4Bg0dgKm5IcVLFCc2NpZF85cSNHchUqmEfgP64u7p9FvvWyEhr5k+SZ/r125QomRxbOwt6NWnB0pKSly7egMHWxeuXLpKyZIl8Z3rmXos9rtavnQlXrP9iImJ4a+B/TCzNKZU6ZLEx8WzdPEKAvwCSU5KplffHnh6u6Kuri7vkuUmOjqa+YGLWLxgGcWKFcPT05Phw4f/1t9vhNznV3pBorkkKJQbN25gaGjI4cOH6fBHO2zsLX67pklEeAQzdY059d8ZtLXzYWZlwrDhg1FRUUm3XGJiIqtXrMPby5+42Dg6demIT4An+fNry6ly+di1cy+2lo6EfwynU+cOWDtYUKVK5a+We/jgEU72bpw4dpJChQvh6uFIz17d5FCx/ERFRWM0Yxb/Hj2BlpYWs8wNGTF62FdfKpKSkli3ZiNe7r7ExMTQvkMb/AN9KKCTX06Vy8eB/YexNLUl7EMYbdq1wt7Jmuo1qn213JPHT3F18uDwwaPo6Ojg6GpD/wF95VCx/MTExGBiYMGhg0fQUFfHcJY+Y8aN+OpLRXJyMpvWb8HD3YeI8AhatWnBvGBfChUuJJ/C5eTY0ROYGlny7t17WrRshr2zNbW/0cR98fwlbs4e7NtzkPwF8mNrb8GQvwfJoWL5iY+Px8zEmr279qOqqoq+kS7jJ41FQyP9viWRSNi2ZQduTp58/BhO0+ZNCFzgR7FiReVUuXycOnkGE31z3rx5S+MmjXBwsaF+g7pfLffqVQgert7s3L4bbW1tzK1NGDVmuBwqlp/ExESszOzYvnUXysrK6OlPZfLUCWhqaaZbTiqVsnP7HlydPHgX+o5GjRsQtDCAkqVKyKly+bh4/hL6eiaEvHpNvQZ1cXS2oXHTRl8t9+b1W7xm+7Bl03a08mlhPMuAiVPG5nzBciSRSNi+ZSees30J/xiOqakp5ubmaGv/XsfoQt4gmktCriaVStmxYwfGxsY8ffqU0eNGYGCkR8FCBeVdWraSSCR4ufuwbOlKEhOTGDthFPqGuj983B8+hOHrFcCaVevR0NBgmt5k9I10c6hq+Xlw/yHTJ+vz8OEjKlWqiL2TNR07tf/hekcPH8PRzpVnT59TvUY1ghcFUKXq182ovEQikeDvG8jC4CUkxCcwasxwDGfNoHDhwhmu9zHsIwG+QaxYtho1NTUmTB6LiZlBnh+Z8/TJU6Z9Gn1TtlwZ7J2s6fznj0dSnjh+Ekdb15QRYVUrM2+BH7Vq1cihquUnaO5C5vkHEx8fz9DhgzExM/jhF/qIiEgC/eezdPFyVFRUGD12BJa2pnl+33rx/CW6Uwy4eeMWpUqVxMbBkh69uv5w3zp7+hz2Ni6pI8LmzfejXv06OVS1/CxesAxf7wBiY2IZNOQvTC2MKFEy4y/0UVHRBM9byKL5S1FSVmLY8CE4OFvn+X3rzeu3TJ88k6tXrlOseDFs7M3p06/XD/etC+cv4WDjzK2bdyhbriwBwd40btwwh6qWn5XL1+Dp5k10dAx9+/fG3NqEMmVKZ7hOTEwMC4OXEjxvIQADB/fH2d0+z4/6evfuPXpTDLh44TKFCxfC0taUvwb2++Fr6urla9jbunDtynVKlS6J31wvWrRqnkNVy8+VS1dxsnfnyuWrDBkyBE9PTypVqiTvsgRBZqK5JOQJ8fHx+Pn54eLigpq6GkazZvL3iCF58kN8754DWJvb8zHsI+07tsXO0Yqq1ar80jZu37qLk50rZ8+cp1ixonj5uv9UsyW3iYqKxljfjKOHj6GppYnxLH1GjR2OmpraT28jISGBlcvX4OsVQHx8An9264y3/2zy5cuXjZXLx5FD/2JuYs379x9o1aYldo5W1Kr9aw2P+/ce4GTvxskTpylcpDDunk506/FnNlUsP3FxccwytOTAvkOoqalhaDKDMeNHfTVCIiNJSUmsWbmeOR5+xMbG0vGPdvgFeufJEYUnjp1klpEFoW/f0ax5E+ydralb79caHo8ePcbVYTZHjxynYKGCOLvZ0adfr2yqWH4SEhIwN7Fh9869qKiqMMNgOpMmj0NDU+Ont5GcnMyGtZvxdPcmMjKKtu1bMzfIB52Cee+47NyZ8xjMmMWb129p2LgBDs42NGxU/5e28ezpc9ycPTmw7xA6OgWwc7Jm4OD+2VSx/CQlJWFj4cDWzTtQUlJimt5kpupOREtL66e3IZFI2LxxG7Nd5hAeHk7zls0IXOBLkSJFsrFy+bh08TIGerN4+eIVdevVxsHFlqbNGv/SNl6+fMVsFy9279xH/vzaWNqaMnzksGyqWH4kEgn2Ni5sWLsJKVKmTJvI9BmTf2n0jUQiYce23bg5efDhQxiNmzYkaIE/xUsUz8bK5ePN67d4unuzdfMOGjVqiL9/AB06dJB3WYKQaaK5JOQpISEhWFlZsWzZMmrVromNgwVt2raSd1lZ4tHDx0yfos/9uw+oULE89k7WdOrSUebtSaVS9u89iLO9O69fv6FO3doELwqgXPmyWVi1/AT4BjE/MCWfZMSoYRiZ6lOkSMajbzLy7t17fLz8Wb9mExoaGujpT0VPf1oWViw/z58+Z9oUfe7cukuZMqWxc7Liz26dZb7OXyqVcuTwvzjauvLyxStq1KzO/MUBVKxUMYsrl4/5QYuZ6xuUEtI9bCAm5oYUL15M5u2FhYXh7x3IqhVrUVNXY/K0CRgaz8gToydevQpBd7JBaj6JrYMlPXt3z1SGRGqO3OOnVK2Wt3Lk/lm8Am9PP2JiYtPlk8gqIjyCAL8gli1diZqqKmMnjMYsj+TIhb4NZfoUA65cukqRokWwtjOn31+9M7VvnTp5Bgdr5zyZI7dm1XrcXbyIjoqmd7+eWFjPomzZMjJvLzIyiqC5C1iycBnKykp5Kkfuw4cP6E4x5MK5ixQsVBBLG1MGDu6fqceWNkeuXPmyzA3ypWHjX2uCKqpNG7bi7OBOZEQk3Xr8iZWtGRUqlpd5e1/myA0eOgBHV9s8ccI4Pi6exYuWETx3Ifny5cPNzY0JEyZ8FWchCLmVaC4JedL58+cxMNDn9OkzdO/ZFUsb00x90MlTaj7JgSNoaHw/n0RW8XHxLFm8nLl+QSQnJdO7b088vF1ybahi2nySlq2aY+dkTe06NbNs+zdv3MLR1pUL5y9RrHgx5vi506Fjuyzbfk6Kj4/HzNiKvbsPZJhPIvv2E1jxzyr8vOeRmJhItx5/MsfPHU1NzR+vrIBOnTyDsb4Zb9+EZphPIqu7d+7haOfGmVNnKVK0CJ7ernT+848s235OSkhIwMrcnh3bdqGirIzuzG/nk8gqr+XIXTh3EYMZs36YTyKrhw8e4eIwm2P/nqBQoYK4ejjRs3fuzJFLSkrC3sqJTRu3ATBNdxJT9SZl2WjSzzlyc2b7Eh0dTbsObQnIxTlyVy9fZ+Z0I168eEntOrWwd7amRctmWbb9vJQjJ5FIcLZ3Y+3qDUgkUiZOGYfuzKkUKJA1f/vk5GQ2bdiKh5t3nsiRSzuZTLXqVXF0saV125ZZtv0Xz1/i7uLF3t37yV8gPzZ25gwdPjjLtp+TPp/QdXf2IiTkNfr6+tja2lKoUCF5lyYIWUo0l4Q8SyqVsnbtWszMzHj37h0Tp4z75SG68hYYMJ/AgAXEx8czbMRgjE1/nE8iq7RDdPPly4eJmT7jJ+WeUMUXz18yfYo+t27cplSpktg6WtK954/zSWQhlUrZu/sALo7uvHn9lvr16xK4KICyZTPOYFAkixf8g6/3XGJjYhk8dACzzA1/mE8iq9DQd3h7+LFx/RY0NTWZaaTLNN1J2XJf2SE1n+TqdYoXL4aNvQW9+/bMtn3r0IEjONm58epVCLVq12T+ogDK56LmeNp8kn5/9cHcyoTSZUply319nSM3CX0jvWy5r+zwZT6Jla0Z/Qf2zbbRH0cPH8PJ3i11ZtHcliO3fs0mXJ08iIqKolef7ljamFK2XPaMts3tOXIfwz6iN82Qs6fPo1NQBwvrWQwa8le2jZBImyNXuUolAhf656ocua2bd+Bo60JERCR/duuMtZ05FStVyJb7+jJHbtTYEVjlohy5yIgo9HWN+O/EabS182Fqacyw4YOzbWRRbs+Ru33rLi4O7pw+dZZevXvh4+1DzZpZd9JTEBSJaC4JeV50dDQeHh54eXmhU1AHM0ujnwoXlKcTx05iYmjBu1DZ80lkdeXSVRxsXbh29QalS5fCL3AOzVs0zZH7lsWX+SQzDXWZOGnsL+WTyCouNo7FC/8hMGA+yRIJ/f7qg5uHo0KP+jp7+jyGMzOXTyKrG9dv4mDjwqWLVyhRsjjefh60bd86R+5bFl/mk0yfMYUp0yf8Uj6JrOLjE1i2ZAX+PoEkJSXRo1c3PH1cFXrU16WLl9HXNeHVyxCZ80lklTZHrmixonh6u2bqsuHsJpFIsLd2ZsO6zTLnk8gqNUduzlzi4+L5s2snvAM8FDpH7vq1m8ycZsizZy+oWasGji42ORb2+2WOnJuHI917ds2R+5aFRCLBzdmTVcvXkpyczMTJY9EzmJ5lo28ykhtz5O7cvoveVEMeP3pC1aqVsXexoV37Njly348fPcHFcTZHDx9Dp6AOLu72Cp0jJ5FImOPhyz+LV5CYmMSY8SNzbBKdL3Pk2rRrxbxgX4XOkfvwIQwfL3/Wrd5I9erV8PX1o2fPnvIuSxCylWguCb+Np0+fYmZmxoYNG2jYuAF2DpZZetlBVnj5MgS9yfpcv36TkqVKYGNvSc/e3bJlhERGPk+L6u7ixYcPYTRp1oighQEKN01z2nySAYP6YWZpIpfpfkNevcbDzZsd23aRTzsfphbGjB0/MsfryEh25JPIQiqVsnvnXlwcZxMa+o4GDesTvCiAUqVkz5XJDlmdTyKr0LeheM32ZdOGrWjl08LQZAaTp07I8ToykjafpFChgljamjFgUM438D9fduDiMJuQkNcKmyO3acNWnO3diYyMpHvPrljZmlG+Qrkcr+P9+w+pX3wUNUcuIjyCGdONOHXyDAUKFMDc0pghfw/K8XySr3LkalQjaHEAlStXytE6fmTHtl3YWTsTER5Bpy4dsbG3oHKVSjlex1c5clMnYGiiWDlykRFRGM4w4fixk+TLp8UsCyOGjxwql1yf4//+h6Oda0qDS0Fz5PbvPYiVmR1hYR9p16ENdo5WcqkxbY6cqooqYyeMwtzKRKH2rcTERFYtX0uAbyCghIODA3p6er80mYwg5FaiuST8do4fP46BgT5Xrlzlr4F9MbM0yVRgalb4Mp9ET38ak6aMz7J8EllFR0czP3ARC4KXoKSkxJBhg3B0sZF78OD5cxcx1JtFSMhr6jesh6OzDY2ayH865EsXL+Ng48KN67coU7Y0AUHeNGmaMyM3vicpKQk7Kyc2Z1M+iaxiY2NTp2mWSiX0H9gPNw9HuQd2fplP4uBioxAj965dvYGDrQtXLl2lZMmS+M71pFWbFnKt6ct8kklTx6M7c6rcRyl8mSPXq28PPL1d5T6iMG0+SfUa1XBwtsnSfBKZ67p5G0dbV86fu/gpR86NDh3lO3uoRCJhtuscVvyzmqTkJMZPHMNMg+lyH6WQkJDA8qWr8PeZR3xCAt26/4m3/2y5jyi8d+8BupP1Uy9Jc3C2oX3HtnKtCVJy5Jzs3Th98ixFihRm9hwX/uzWWa41SSQS/Lznsmj+PyQmJjJ67AgMjPXknnv0ZY7cH5074DvXS+7vp48fP0F3kj53796nfIVy2Dtb06lzxxw/MfWlRw8f42zvnpoj5zLbkV59usu1JkjJ/XRxnM3jR0+YNGkSLi4uFC+e92a7E4TvEc0l4beUnJzM0qVLsba2Jio6Ct0ZU5g4eZxcmjkrlq3Gy90nR/JJZPX82QvcnD3Zv/cgBQrkx8bBkiHDBuZ4He/evUd3ij6XLlyhSJHCWNqYZms+iSwkEglbN+/A3dmTjx/Dadq8CYEL/OQy6mv9mo2f8kmisz2fRFavXoUw22UOu3bsQVtbGwubWYwc/XeO1/GtfJLBQwco1L4llUrZuX0Prk4evAt9R6MmKdM0y2O0Xk7mk8jqyxw5Y1N9JkzO+Ry5iPAI9HVNOPlfzuSTyOLLHLl69esQtGiuXHLkdu/ci42lI+Efw/mjcwds7C0ULhcqJUfOn43rN6OpqckMw2lM15uS43VERUVjNNOUf48cR1NLk1lmhowYPUyhRkhIpVIOHzyKo50br16+olbtmgQv9KeCHN4vDh04gsUsGz58CKNNu1bYOVpRo2b1HK8jIx8+hOE3Zy6rV65DQ0OdqbqTMDCekeN1xMTEMMvQkoMHDqOhro6hyUzGjB8p9yb9l9LmyFWrUZX5i+bK5f3i0aPHuDl6cOTwMf744w/8/Pxo2FD+Jz0FIaeJ5pLwWwsPD8fZ2Rl/f39Kly6FhY0pPXplTwj0l9Lmk9SrXwcHFxu5j3L5kTOnzmFv48z9ew+oWKkCgfP9qFOvdrbfb2o+yfrNSKVSpk6fyDQ9xQ5nj4qKJmjuAhYv+AclZSX+HjEUeyerHGlWXL96g5nTjeSSTyKr8+cu4mjrwq2bdyhXriwBwT40atwg2+9XnvkksoqJiWFB0BLmBy4CYNCQv3Bys8uRZsWdW3fQm2rE48dPqFatCvYuNrRtp7i5WQBXL1/D3saZa1dvUKp0KfxzKEfuy3ySsRNGoW+omyP5JLKKi41jyaJlzPMPJjlZQr/+vXHzcsqRL5QP7j9Ed6oBD+49pGKlCtg7WfNH5w7Zfr+ZkS5HrkRxvP1zLkfO32ceC4IWEx+fwMgxf2NoMpMiRQrnyH3L4sscue69uuLl45Yjo76ePnnK9MkG3L1zj7LlymDnaEWXrp3kPvomI3du38PRzpWzp8/leI5ccOBC5vkFExcXz9DhgzExy77JZLJCYmIiK5evwccrgPi4eLp07YRPDuXIRUREMs8/mGVLVlKuXFnmzPFm4MCBCr1vCUJ2Es0lQQDu3r2LiYkxu3fvoWXrFtg5WlK7Tq1sua/379+jN8WQC+cvyTWfRFbJycmsX7spdTaoNu1aMTfIJ9suV9i4fgsuDu5ERkbJNZ9EVs+ePsfVyYOD+w+jo1MAOydrBg7uny339THsIzN1jTl98iwFdOSXTyIriUTC5o3bmO0yh/DwcFq0asa8+b4UKVIkW+4vbT5Jlz//wMrOXC75JLJ6+eIls13nsHvnPvLnz4+1nRnDRgzJlvuKjIjCYIYJJxQgn0QWEomEHVt34ebsyYcPYTRumjLqq3iJ7LlcYd+eg1ibyz+fRFavQ97g4ebN9q070dbOx6xszJGLiYnBaKYZRw79i6amBkam+oweO0KhRt9kRCqVsmfXPpwd3Al9+44GDesRtCiA0qWzZwTykUP/Ym5izfv3H2jVugV2TtbUqp17ZmULfRuKl4cfmzdsRVNLEwPjGUyZlj05cnFxcZgaWbF/7wHU1NQxMNZj7ITRaGgo1uib75FKpRzcfxgnOzdCQl5Tu24t5i+am205cv8dP4WJoQWhb0Np2qwxDi42OTaZTFb4MkdOd+YUZhhMz5b7Sk5OZuO6zXh7BhAbG4uVlRXGxsY5MuGHICgy0VwShDT27duHkZER9+7dY9iIIRib6lO0aNZ8sZVIJDjZubF2zQakCpRPIqvwj+EE+AWxfOkq1NRUGTdhNKaWxlnWJPsyn8TRxVbuGTOZcfK/0zjauPDgwSMqVa5I0AI/amVRA/PLfJIJk8Yyw2A6OjoFsmT7OS0yMorAgPksWbgMFRUVRoweho29RZbtW2nzSapUqYy9s7VC5JPI6tzZCzjYuHDn9l3KVyjHvGBf6jeslyXblkgk+M6Zy+IFipVPIqt0OXIoMWTYQBxcbLKsSfb48ROmT9LnnoLlk8gqXY5cmdL4B86hafMmWbb9ef7BBM1dSHx8PMNHDsUoCz9zc1psbCyL5i8laG5Kjly/AX1x93TKsn3r+dPnTJ9qwO2bdyhdpjR2jpZ07d4l1+5b2Z0jtzB4Cf4+gcTFxTFo6ABMzQ2zrZmc3eLj4lm6eAUBfoHZkiMXEvIa3cn6XLt6gxIli2Njb0GvPj1y7b6VPkeuKHP83LM0R+7cmfM42btz6+ZtRo8ejbu7O2XLKlbkgCDIi2guCcIXEhMTCQoKwt7eHqlUwkwjXUaPHZGpD/G0+SRdu3fBytZM4fJJZPXwwSOc7N04cewkhQoXwtXDkZ69usm8vS/zScysTBg2fHCuGX2TkaSkJNau3sCc2X7ExMTQvkMb/AN9KKAj+yVYuSGfRFaPHz3BzcmDw4f+RUdHB0dXG/oP6Cvz9tLmk2hpaWFiZqBw+SSySk5OZtP6Lcx28yYyIpLWbVoyN9gnU02gg/sPY2lqq9D5JLJ6/uwF7i6e7NuTNTlyX+WTzNJnzLjMfW4oColEwrYtO3BzyrocuePHTjDL0JJ3oe9p0bIZ9s7W2TZaOKd9mSNnbm3CqDHDZd5eQkICZsZW7Nm1HxVVFfQN9ZgwaQwamhpZWLV8fJUj17ghQQszlyN3+uRZjPXNePPmLY2bNMTBxZb6DepmYdXy8+b1W7xm+7Bl0/YsyZFLSkrC0syOHVt3oqSkjJ7+VCZPnSD3yWSyglQqZd+egzg7uGVZjlza0cLNWzQnwD+AVq1aZWHVgpD7ieaSIHxHaGgotra2LFq0iMqVK2Ftb/7L+Q93bt1Bd6oRT3JRPomsjh4+hqOdK8+ePqdGzeoELfT/pSaHRCLBy92HZUtXkZiYmCvySWT1MewjAb5BrFi2GjU1NSZMHouJmcEvjcx5cP8hulMMePDgIZUqVcTeyZqOneQ7w1N2OXH8JI42rjx69JgqVSsTuNCfmr/Q5JBIJAT4BrIweAnx8QmMGjMcw1kzKFxYcfNJZBUREUmg/3yWLl6OiooKo8eOwNLW9Jf2rS/zSeydrOn85x+59ix2RtLlyFUsz9z5ftSr/2uXgQTNXUhgQO7JJ5FVVFQ0wfMWsmj+Uplz5F48f4nuFANu3rhFqVIlsXGwzLGcw5x24fwlHGycuXXzDmXLlSUg2JvGjX8t4HfxgmX4egcQGxPLoCF/YWphRImSOR/gn91iYmJSZw8FGDi4P87u9r806uvN67foTtHnyuVrFCteDBt7c/r065Un962rl69hb+vCtSvXKVW6JH7z5tCiZbNf2sbK5Ws/xRtE07d/b8ytTShTJucD/LPblzlyffv3wt3L+Zca/zExMSwIXMyiBUspXLgIs2fPZtSoUbkmzkIQcpJoLgnCD1y9ehVDQ0P+/fdfOnXuiLW9+Q+bJunzSfIxy8IwV+WTyCohIYGVy9fg6xVAfHwCf3brjLf/7B+GKu7dcwBrc3s+hn2kfce22DlaUbValRyqWn7u33uAk70bJ0+cpnCRwrh7OdOte5cM1/kyn8TY1IBRY4fnidE3GUlKSmLNyvXM8fAjNjaWjp3a4zdvzg8vK02XT9KmJXaOVrkqn0RWjx49xtVhNkePHKdgoYK4uNvTu2/PDNeJi4tjlpElB/YeQk1NLdflk8gqOTmZDWs34+nuTWRkFG3bt/6pHLkTx04yy8iC0LfvaNa8CfbO1rkqn0RWz54+x83ZkwP7DlFApwD2P5Ejl5CQgOUsG3bu2IuKqgozDKYzafK4PDH6JiNf5sg1b9mMwAU/zpE7d+Y8hjNNeR3yhgaN6uPoYkvDRvVzqGr5SZ8jp42VnRl/jxia4TpJSUnYWjqyZdN2lJSUmKY3mam6E/N89o1EImHHtt24OXn8Uo7cpUtXMNA14eWLV9StVxsHF1uaNlPsyWSywuuQN3i6+7BtS8rsoaYWhoydMDrDdaRSKTu27cbDzZuwD2GYmJhgaWlJ/vyKO+GHIMibaC4Jwk+QSqVs3boVExNjXrx4ydgJo5hpMP2rLx8SiQQfL3+WLFxOYmIiY8aNRN9IN9fmk8jq3bv3+Hj5s37NJjQ0NNDTn4qe/rSvlnv08DG6Uwy4d/c+FSqWx97JOsdmQ1EUUqmUI4f/xdHWlZcvXlGjZnXmLw6gYqWKXy0b4BvE/MBFeSKfRFZhYWH4eweyasVa1NTVmDxtAobGM746g/j86XOmTdHnzq27lC5TGnsnK/7s1jlPnsXOyLGjJ3C0c+XJk6dUq1aVoIX+3wyWXhC8mACfIOLi4hg8bCCzzA0pXryYHCqWn4jwCAL8gli2ZGWGOXIhIa+ZPkmf69dS8klsHSzp2bv7b7dvnTp5Bgdr5x/myC1fuhKvT5cC/zWwH2aWxpQqXVIOFctPZGQUQXMXsGThMpSVlRgxahg2DpZf7Vuhb0OZPsWAK5euUqRIYazszOk/oM9vt2+lzZErV74c84J9aPCN5tra1etxd/YiKiqa3v16YmE9i7Jly8ihYvmJjo5mQdBi5gctzjBH7sOHD+hNMeT8uYsULFQQSxtTBg7u/9uNvrl88Qr2ti7cuHYzwxy5q1eu4+LgzsULlxk4cCBeXl5UqZL3T3oKQmaJ5pIg/IK4uDh8fHxwc3NDQ1MDE1MDhg5PmY3rwKd8krAPYbRt3xo7Ryuq16gm75Ll6uaNWzjaunLh/CWKFS+Gt99s2ndsS0xMDCYGFhw6cAQNjbyVTyKr+PgEVvyzCj/veSQmJtKtx5/M8XNHU1OTY0dPYGpkybt3eS+fRFZ379zD0c6NM6fOUqRoETy9Xen85x8kJCRgamzF3l37UVVVRd9Il/GTxub50TcZSUxMZPWKdXh7+RMXG0enLh3xCfAkf35tTp08g7G+OW/fvKVxk0Y4uNjkmXwSWT188Ahne3eOH/svXY5cQkICVub27Ni6CxUVZXRn5p18ElklJSWxbs1G5sz2JTo6mvYd2qbmyF08fwl9PRNCXr2mXoO6ODrb0LhpI3mXLFdPHj/F1cmDwwePpsuRS0pKwt7amU0btgIwVXciU3Unoa2dOyf8yArJycls2rAVDzdvIsIjaNWmBfOCfSlUuBBXL19npq4RL56/pHadWtg7W//yZWF5zYvnL3F38WTv7gPpcuQkEgnODu6sXbUeiUTKxCnj0J05lQIFft/RN59z5NydvQgL+5guR+7tm7epsxnWr18PPz9/OnfuLO+SBSHXEM0lQZDBy5cvsbS0ZOXKldSoWR2pVMqD+w9T8kmcrencJW/mk8hCKpWyd/cBXBzdefP6LeUrlOXN61ASEhIYNmIwxqZ5M59EVqGh7/D28GPj+i1oaGpQvHhRXjx/RalSJbF1tKR7z7yZTyILqVTKoQNHcLJz49WrEMqWK8P79x+IjYll8NABzDI3zJP5JLL68CEMX68A1qxaj7q6OqVKleTZ8+cUL14MG3sLevftKfatNNLmyJUpW4aPYR+JiYmh3199MLcyoXSZ7JlqPjdKmyOnqqpK6TKleP7sBYULF8LK1oz+A/v+diMkMnLi+EkcbV159PAxpUuXIiIikujoaHr27o6ljWm2TTWfG6XNkVNWVqZsuTI8e/ocnYI6WFjPYtCQv/LEhB9Z5ezpc9jbuHDv7n1KlipBTHQMkZFR/NmtM9Z25nlmMpmskC5HTkmJ1m1bcuHcJbS0tHB2dmby5Ml5Ps5CELKaaC4JQiacPXuWQYMHEfIqBHMrE8aMH/Vbj5DISFxsHIsX/oPvnLmULFWCRf8E/Rb5JLK6cf0mFrNsuX37DsamBr9FPoms4uMTWLZkBV6zfalesxqzvVx+i3wSWd2+dZepE3R58eIVBsYzmDJ9Qp7PJ5HV5xy52S5zqFS5IrPnuPwW+SSyun/vAVMnzuDJ46dM05uMnv7U33r0TUY+58g5O7hTrnxZZns507J1C3mXpbAeP3rC9MkzuXf3ARMmj8XAeMZvPfomI59z5OxtnClZqgTuXs60a99G3mUprGdPn2Nr5ciJYyeZNGkSnp6eeXLCD0HICb/SCxKnnAThCy1btmT6tOkUKVKYydMmiMZSBjS1NJlhMB01NTUaNmogGks/UK9+XQYM7oeykjJ6M6eKxlIGNDTUmao7CWVlZfr/1Uc0ln6gdp2aNGneBGVlZQyM9URjKQPq6upMnDwOFVUVevXpIRpLP1C9RjVafWqQGJrMEI2lDKiqqjJm/EjU1dXp1v1P0Vj6gcpVKtG+QzsA9I30RGMpAyoqKgwfNRRNTQ06d/lDNJZ+oELF8oydMAoAJycn0VgShBwimkuC8A3iMhJBUBDipSgIgiAIgiAICk80lwRBEARBEARBEARBEASZieaSIAiCIAiCIAiCIAiCIDPRXBIEQRAEQRAEQRAEQRBkJppLgiAIgiAIgiAIgiAIgsxEc+l/7N11VFRbH8bxLw2iYLfX7u7u67W7uwuUEES6Q6RRsLv72t3d3R1YKEj3zPsHyqtXUBxiBtyfte5aOCfmN+fuMzNnzz7PFgRBEARBEARBEARBEGQmOpcEQRAEQRAEQRAEQRAEmYnOJUEQBEEQBEEQBEEQBEFmonNJEARBEARBEARBEARBkJnoXBIEQRAEQRAEQRAEQRBkpirvAgRBSBYREcnaVes5fPAoz5+9IDIykoIFC1KufFmaNGvMuAmj0NHVyfRtFUVMTAwXzl3i9q073L51l9u37vAm6C0ABsb6GJlMS3Pbd2/fc+jgEc6fvcjd2/d49+49AEWKFqZeg7oMGTaQFi2bpauO4A/BrF65juNHT/LqZRCxsbEUKlyQSpUq0rR5EyZMHoOamlrGX3AWy8jx/OrwwaNsWLeZmzduE/Y5jPwFdKlbrw7DRgymXYc2Wf0Sst2pk2fYuG4L16/d4OPHTyihRNFiRajfoB5Dhw+kafMmaW4bGRnFkoXL2b/3IK9fBaGsokz5CuXo2asbo8YOR11dPRtfScZkRtv5Lytze9av2QhAqdIlOXX+SKrrhYeFc+H8JW7fvMPt28nPHfzhIwBzvF0ZMKivjK9Kfm7fusORQ8e5fesOz54+J+RTCJGRUeTNq03FShVo16ENw0cOIX+B/OneZ3qPZ0518cJlVq9Yy5VL1wgJCSFfvnxUq1GVgYP706tP91S38fWah79PwC/3ffTUfsqVL5vZJWeJjJyLmXk87ty+y/q1mzh35gLv331AWVmJwkUKU6t2Df7+p2Oa/08U3fx5i/GY7Z3y76ev76W5rixtUpFlxvt8cPBHFs1fytHDx3kT9BZNTU0qV61E/wG9GTR0AEpKSmlum5SUxM7tu9m2dQd3b98jKiqKggUL0qhpQ8aMG0GDhvUz7bUKgpB9ROeSICiAc2cuYDjNlI/ByRdR6upqaGpp8e7de969e8/5cxf5p0tHaqTSQZSRbRXJjWu3GDdq8m9v9+bNW1o37YhUKk15TEtLC6lUyutXQbx+FcTuHXsZOLgfrnMcUVFRSXNfu3fuxXKWHZERkQBoaGigpq7Gm6C3vAl6y8kTpxk+cjBquorfuSTr8YTkL32mRhbs2L4LACUlJXR0dAj5FMrhg0c5fPAoo8eOwM7JKjNLlhupVIq1hUPKxTqApqYmAK9evubVy9fs/Hc34yaOxtrO/Iftg14HMXTgaF6/CgKS2198fDy3btzm1o3b7Ni+izUblqObXzd7XlAGZaTtpObcmQtsWLspXesePHAEsxmWmfbcimDzhm2sXrku5d8aGhpoamrw+XMYVy5f48rlayxfsopFywPSdUH1O8czJ3J39WJh4JKUf+vo6hAeHsGZU+c4c+oce3fvZ94CH1RVU/8Kq6am9tNzLa3tFFFmnIsZOR5SqRR3F0+WLFqBRCIBIG9ebRITk3j+7AXPn73gyeNnObJz5emTZ+nqfIOMt0lFlNG2devmHcYMn0Bo6GcAtLXzEBUVxeWLV7h88Qr79hxk0fKAVH9YiYqKYsqE6Zw5dQ4AFRUV8ubNy4cPwezesZe9u/ZjZjGDSVPHy1yfIAjykXPeBQUhl7p86SrjR08hNjaWzl07MXXaJGrXqYmSkhIxMTE8fPCYwwePkC9fvkzdVhHp6upSs3Z1atWqQc3aNXB2mJ0yaiEtkiQJUqmUFq2a0W9Ab1q2akGx4kWRSCQ8efwUT3dfDh04wuaN2yhWvCgzZhqmup+9u/djNG0mEomEocMHMWb8SCpXqQQkj0q5e+ceB/cfRlUt57xtynI8Abzm+KV0LI0ZP5LpRlMpUKAA0dHRrFu9kTlu3qxcvoay5f5izPiRWf0ystyWTdtTOpa6du+M6SwjylcoByRfgLi7enHowBGWLV5J4yYN6dy1U8q2iYmJTBijx+tXQRQtVgRP39m0at0CiUTC3t37sTSz5c7texgbmLFs1UJ5vDyZyNp2/ismJgZLM1tUVVWpVqMqt27c/uU2RYoWpkbN6tSqXYNatWsydaKBLC9BYdStX5vSZWbSqHEDKlaqkDKKNCoqigP7DuHm5MGnTyFMHj+dIyf3oaOT9vu1LMczJ1m3ZmPKRXyP3t2wsJpJiZLFiYuLZ/fOvdhZOXFw/2Fmu3im2tEL0KBhPdZvWZWdZWepjJ6LGTkejraurFy+Bm3tPEw30qNv/14UKVoEgJCQUC6ev8TDB49k2rc8SSQSZplYERcXR4OG9bh65Xqa62ZGm1RUsrat8PAIJoyZQmjoZypWqoCXnzt16tYiPj6eDes24+LgzskTp3Gyd8PJ1e6H7S3MbDlz6hzKysrMMDNk1Jjh5M2rTdjnMOYHLGbR/KXMdvGkQsXy/P1Ph6x46YIgZJGcc5UkCLlQTEwMpkbmxMbGpjoSREtLi7r1alO3Xu1M3VYRNW7akGt3zn/32Bw37zTW/j8dXR127ttCrdo1v3tcWVmZylUqsWDJXMaNnMyJ46dYvmQV+tOnoKGp8d26H95/wGqWPRKJBEvbWUyYNOa75XnzatOkaSOaNG0k24uTA1mPZ0hIKMuWrATgn84dsXX4/yiSPHnyMGHyWD59CmFh4BJ8vefRf1Bf8uXLm7nFZ7PtW3YAULbcX/gFeH7363OFiuWZt8CHTu268/LFK/bs3v9d59LWzf/y4P5DAAIX+aWMPFFWVqZHr25IJFKMpply/OhJzpw+R8tWzbPxlclG1raTGk93X168eIm+wWTevX3/y86Qvv175chb336m34A+qT6ura1NvwF9KFKkCKOHT+DTx08cPXycPv16prmv3z2eOUliYiK+XvMAqFW7Br5zPVBWTo4G1dBQp//APsTGxmJj4cCq5WsZNWY4f5UtI8+Ss1xmnou/68SxU6xcvgY1NTVWrVtK/Yb1vltesGABunT7hy7d/smWejLTymVruHL5Gr379qRsub/S7FzKzW0yI21rycJlBH/4iKamJstWLaTMX6UBUFdXZ9SY4URGRuE524cNazczdsIoKlQon7Lt/XsP2b1jLwCjx41Ab9qklGW6+XUxtzLlTdAbdu/ch4ujOx3+bpdyzAVBUHzibBUEOdq+dScvX7yiSNHCmFuZZtu2iuhnt6v9jI5Ovh86lr6lpKTEwCH9AIiKiubx4yc/rLNi2RrCwsKoWas64yeOlqkORSPr8Tx7+hzxcfEATExjSPrkL4+Hh4Vz6MBh2QpUIB8+BANQvUa1VG9rUFNTo3qNagBER0V/t2zbln8BaN6iaaq3NPXs3S3li/fXTixFJ2vb+a9rV66zctkaylcoxzSDqdn63DlJvQZ1U/5+9/ZdmuvJcjxzkts376Tc3j1+0thULyiHDBuIjq4OiYmJ/LttZ3aXmO3keT58vWVsxOihP3Qs5WSvXr7Ga44fBQrkx9r+5yONcnObzEjb2vbls6zHN59v3xo9djja2nlISkpix7bd3y07fvREyt+TpqT+HePr7XAvnr/k8sUrMtcpCEL2E51LgiBHXy82u3Xv8sNomqzc9k+jofH/45OUJPlh+ddj2btfr58GUP4Jgl6/Sfm7cuWKqa6Tv0B+ChUuBMCpE2ezpa6s9PXL8b2790lMTPxheUJCAvfu3gegdp1aKY/HxMRw5dI1ANq2b53qvpWUlGjTrhWQHBj+p4iLi2eWqTVSqRRXdwfxHvUTly5eTvn7r7J/pbrOn3A8g4K+ee+pkvp7j4qKCuXLlwPg1Mmc/96jqJ49fc61qzeA5NGEuYmFmQ3R0dFY2c2iUKGCP11XtMkfPX3yLCX4u10an3va2to0atIQgNP/+dz7ekzz6eSjWPGiqW5fsVKFlO9if9LnpiDkBuK2OEGQk7i4eG7dTL6loVadmgQFvSHAbwEnjp3i48dP6OjqULdebYaNHEyHju0ybds/0flzF4HksPOvWTpfvXr5mvfvPwBQu3YN7t97yPx5izh/7gJhn8MoWLAgDRvXZ/S4kTRq3CC7S5erJElSmsskScnLvt4SlpONGDWUE8dO8eL5Swz1TZlpbpwye9LTJ8+Y4+rFyxevKFv2L8Z9M7Lt8aOnKSG3VapWTnP/X5cFf/jI59DPvzUrWE411zeQx4+eMHjogJ/OsveniouLJ/hDMEcPH8fHcy6QfFtmx07tU13/Tzueqf0IkLLsy/tSWlk/jx4+pkvHnrx88RplZWWKFS9Kk6aNGDF6KDVr1ciSehWZLMfj8qWrQPKozWrVq3Lk0DGWL13F7Vt3iYuNo0TJ4rRp24oJk8dSukyp7Hw5GbJh7SbOnj5Py9bN07xdNS0ZaZO5yYP7/3+NP/vcq1q1MieOneLRox9HiwNIJWkfT4lEkjJJy7fPJwiC4hMjlwRBToJeBxEfnwDAyxev6NqxFxvWbebTp09o5dFKyd+YMHoqFjNtvpsNLSPb/mlevXzNutXJYc3de3b9IR/o2dPnKX9fvnyNPt0HsGvHHiLCI1HX0ODdu/fs2bWfwf1GMNc3MDtLl4tvLxQepvGlLvhDcMoMMR++dMzlZB07tcfa3hx1dTX27TlAh9ZdqFGpPjUq1efvtt04f/4Sw0cNYfvujd+1n29fe7HixdLcf/Fvlr3PBcfrV+7cvsui+UspXKQwFtYz5V2OQqlWsS4VSlenesW6tGn+N/Y2zoSFhdGwcQPWbFyOhsaPMyv9KcezdOlv3nvSuEiPj4/n+bMXAESERxAdHf3DOiEhoTx+9BRNTQ3i4+N59vQ5G9dvoVfXAXjN8c2S2hWZLMfj6+eijq4OnrN9mDhWj7OnzyORSFBSUuL5sxesWrGWrn/34sSxU9n3YjLg3dv3uLl4oqmpictsh3Rtk1ltMjdJ7+fe12WREZFERUWlPP71mEZGRhH0OijVbb/97vEnfGYKQm4iOpcEQU7CPoel/B3gvwBVVVXmLfDl1oMrXL9zgVMXjtCtRxcANq7fwtLFKzNl2z9JbEws+lOMiImJoWDBAphZmPywTljY/4+lj4c/RYsVZdX6pdx+eIWb9y5x4OgumjVvglQqxcdzLvv3HszOl5DtmrdshvqXC9yAuanPbhbg///HIyMjs6WurDZuwmgCF/un3O4XGxtLbGwsAAnxCURHRRMR8f1rjYz8/xdmLS3NNPet+c2yb79k50aJiYnMMrEmMTERO0fLlJnRhGRFihSmcJHC5MmTJ+Wx5i2aYmNvQalSJX9Y/086njVr16BwkcIALAxckuotqquWryXym/Pw27/LlS+LuZUph0/u5d6T61y9fZ7bD6+wcu0SatWpiVQqJcB/IUsWLs/6F6MAMnI8wsLCAQgNCWXRgmU0b9mMg8d2c/PepeR9rFtCyVIliIqKZvpU4zQ7CRSJlbkdEeERGM7QT3fodkbbZG4UGZW+z71vl0V981nZtn2blL/n+S1Iddtvv3vk9uMpCLmN6FwSBDmRfDOaSCKRMNvTmW49OqOmpgZAqVIl8Q/0SgkSnj93YcoXm4xs+6dITEzEaJopt2/eQU1NDZ+5Hqne3y+R/P9YSqVSAhf50ap1i5TgzspVKrF4RSBFiiZ/wfT3yd2jlwoWLMCYsSMAOH3yLMbTzXjy+CkJCQkEBb3B3dWL1SvXpbQ1JaWc/zESExPD9KnGTBg9lZKlSrBy3RIu3zzL5ZtnWbluCZWqVGT71p307TGIe3cfyLtchbYgYDF379yjw9/t6N6zq7zLUTinzh/h4rVT3H54hYvXT2NpY8bdO/fp22MQPh7+P6z/Jx1PVVVVphslB5U/fvSECaOncvvWHeLjk28hXDR/KR6zfVLeewCUvglY7tOvJ5OmjqdChfIp66irq9O6bUs2b1tLnbrJM6f6ec8jPDwiG1+ZfGTkeHy9ZUkikVCsWFGWrAik0pcMPmVlZVq3aUnAQj+UlJSIjIxi6SLF/gHr3607OXbkBDVqVmf8f2aD/ZmMtknhR9WqV/nux09nh9m8fhVEQkICT58+w8zEiqOHj6ccUzFTnCDkLOKMFQQ50dbWTvm7XPmy/NPl7x/WUVZWZuLksQCEhn7m9s07Gd72T5CUlITx9JkcPHAEVVVVfOZ60Lpty1TXzZv3/8eyRatmqc48p62tzcjRwwC4f+8BwV9mj8mtTM2N6dG7GwA7tu+iU7vuVC1fh9ZNO7IwcAn16tdJmYFPN3/OH0nh5uzBnl37qVCxPJu2rqF1m5YULFiAggUL0LpNSzZuWU35CuUICQnFztopZbtv205MTGya+4/9Ztm3525u8+jhY+b5zUdbOw+OrrbyLkfhFS5ciAmTx7JizSKUlJSY6zefI4ePpSz/E4/nyNHDmDh5HAAnT5ymV9cBVKtQl6YN2jDbxZNSpUsyaeq4lPV10zmSS0NTA1NzIyB51tCzp89leu05ya+Oh/Y3720jRg9FS0vrh33UrVeb5i2bAooduhwc/BEnezdUVFRwneOY6oygP5NVbTKnyqudvs+9b5d9254AZns607xlMwCWLV5Jm+Z/U7V8Hf5u040tG7fRqXNH2ndIHuGU24+nIOQ2onNJEOSk+DejaCpWqpDmepW+maHk6ywbGdk2t0tKSsLYwIw9u/ajoqKCt7873Xp0TnP9b0czVaqU+mwwQMqvtgBvXufuY6mqqop/gBdLVy6gR6+uVKxUgVKlS9K4aUPsHK3YsHV1SofJ11lycqrIyCg2rN0MJF9EpDYLl6aWJqPGDAfg8sUrfPz4CYCixf7fdt6/e5/mc7z7ZlmxYqnPjpMb2Fk5ER+fgN70Kejq6hAVFfXdf4mJyaG3Uqk05bGEhAQ5Vy1/devXSZks4GtbhD/3eFrYzGTT9rX0H9SXKlUrUaJkCerWq4OJmSG7D2xDWTl5CvVSpUuirv5jRlVaGjSsl/L3q5evM7vsHOdnx+PbLJ2ffceoXLkS8P0so4pmjps3oaGfGTJ8IBUrlf/hPPr2nPn6WHx8/Hf7yKo2mROl93Pv67K8+fL+8KNK3rzarF6/FN95nnTq3JFy5ctSukwpWrZujqevGwuWzOXzl/iH/07CIgiCYhOzxQmCnOQvkJ/ixYt9d+GZmm+zuL9OzZqRbXOzryOWdu/cl9Kx1KNXt59uU7lyJVRUVEhKSntmNPj+WPIHHEuA9h3b0r5j21SXfZ2tsEGj+tlZUqZ79vR5yi2jP8vh+Dp7HMDrl68pXLgQlSpXQFlZGYlEwsMHj2jXoU2q234Ngi1StHCuninu1avkC1SP2d54zPZOc703QW+pXbURANb25oybMDrNdf8UXy/mXzx/mfLYn3w8GzVukObsnCnvPQ1z9nuPIqtWvUq61vs6WYgif794/aXjbO2qDaxdteGn6349j8aMH4mtg+V3y0SbTFa12v9niHv44NF3P7x968GXz73KaSxXVlamV5/u9OrT/YdliYmJ3LuXfAv6n3BMBSE3ESOXBEGOWn25VetxGlO1Ajx++Djl79JlSmfKtrlRUlISRtNMv+tY6tn7xy8t/6WhqUGTpslfKB8//smxfJR8LJWUlHLU1MtZ4c7tuzx6mHys+g3oLedqMkZZ+f8XRT8b3fd1tBL8f4i/lpYWDRsnf/E9cfx0qttJpVJOnUi+ZaR1m9RvzRSEVy9fAbn7tsnMEBz8MeUWrt9977l29UbK37n98zA9fnY8GjVqkBI6/+Tx0zT38XWa+TJ//bmfiRlpkzlR+QrlKFmqBECaMwVGR0dz+eIVAFrJ8Ll35NAxIsIj0NTU/OnIc0EQFI/oXBIEORowqC+Q/Gv1wf2Hf1gukUhY/GUml+LFi1Grdo1M2Ta3+Tpiac+u/V8yluakq2Ppq6/H8uzp89y+9WM2VVRUFGtWrQegXv06FCpUMHMKz4FiYmKwsUiexrlr984/vWUiJ6hYsQKamsmz2mxavyXV4PukpCQ2rN0EgK6uLhUqlk9Z1m9AHwDOn73A9W8u1r7au3s/L18kdxz0zeUXHqfOH+Hp63tp/td/YB8g+daRr4/lhlE2P5OUlJQyuiMtZ06f48b1WwA0bd445XFxPL+XlJSEjbk98fEJ1K1XhzbtWqUs+9UxjouLx8vdF4A8efLQslWzrCxV7jJ6PDS1NOneMzl0ec3K9cTExPywjxvXb3H+7AUAOvzdPhOqzhrrt6z66XlkYKyfsu7Xx/47aiktP2uTuZWSklJKJ9runft4/erHmQJXr1hHVFQ0Kioq9O7X47f2/+lTCG7OHkDyreq6+XUzXrQgCNlGdC4Jghw1adqIrt2Tf5WxmGnDvj0HUy5ug4LeYKhvwv0vQ4NNZhl9N2tGRrZVVGGfwwgJCU357+tMbrExMd89/u107l8zlnbv3Ieqqiq+8zx+eSvcf/Xu15O69eoglUrRm2TImdPnkHyZLefxoydMGqtP8IePKCsrYzLLKNNeb1aT5XgCXL96g4C5C3n08HFK9kR8fDwnjp1iUN/hXL92kxIlS+DgYpPtrymzaWppMnjoAABu37rLxDF63L/3EIlEgkQi4d7dB4wbNZkrl68BMHbCSFRUVFK27z+wD1WrVfmu7UBy5+7e3fuxMEsOYm7bvjUtWzXP5lcnO1nbTmb4dv8hIaEpj0dHRX/3eGoXvIrm7Zt39Ojcj3VrNvLyxavvLvrfvHnL/HmLmTxuGlKplPz5dRk/Mfd2DqXHyxev8HT35fatO8TFxgHJ59LlS1cZNWwCBw8cQUdXBw8f1+9uxbp4/hIjhoxl+5YdvH3zLuXxhIQEzpw+x+B+I7h+7SYA042mopODQoJlORcz43gYmxqQTycf799/YOJYvZRR0hKJhNOnzqI/2RCpVEqhwoV+awa2nEbWNpkTyPo+P2HyOIoULUxMTAzjR0/m1pcJY+Lj41mzaj0+nskzXw4ZPpAKFcrzX0ePHGf5klW8eP4yJZIgJiaGvbv3M6DXUF6+eEX1GtUwNp2elS9fEIQsIDKXBEHOPHxc+fTxExcvXEZ/siHqGupoaWoRFhaWso6BsX7Kr9SZta0i6tGlX6rBoIsWLGPRgmUp/+4/sA8ePm4AXLl0ld079gLJv6jZ27hgb+OS5nPYOlj80PmkrKzMomXzGDFkLI8ePmHkkHFoaWmhqqZKxJcpmtXU1HBwtqZFy5zzi7csxxPgw4dgvNx98XL3RUlJCV1dHSIiIlO+BFapWpklK+ZTuHChrH8R2WCWpQnPn73gxPFTKf+paySHssbH/T/YtWfv7ugbTPluW1VVVRYvD2TYoNG8fhWU0nYkEglxcckXIjVrVcd3rkf2vaBMIGvbyQyN6rRI9XF7G2fsbZxT/m1grI+RybRMfe6scO/ufazN7QFQV1cjb968xMbGER0dnbJOmb9KE7jIjyJFi8ipSsUQGRlJ4NyFBM5dCCSPFIyOjk4JXS5ZqgQLlsz9IedFKk0eeXr29HkANDU1yZNHi4iIyJRtlZWVmaI/kcl6E7LxFWWcLOdiZhyP4iWKsXh5IJPG6XP29Hn+ad+DfDr5SIhPIDY2eUKHQoULsWR5YK4ezStrm8wJZH2f19HJx5IVCxgzfAKPHj6hd7cB5M2rTVxcfMpxad22JdZ2Fqk+7/NnL3C2n50yi1/evHmJiIhI+VGvSdNGLFgyF00tzcx8uYIgZAPRuSQIcpYnTx7WbV7J5g1b2b51Jw8fPCIqKprixYvRqGlDRo8dQcM0QpMzsm1u8fWXNkj+VfZj8Mefrh/75ZfH/ypStAg7921j9Yq17N65j2fPnhMXG0vpMqVo3qIp4yaOpmq19IWc5nS16tRk0pRxXLxwmdev3xD2OYz8BfJTrXoVuvfowoDB/X57OmdFpqmlybLVC9m35yA7tu/i9s07fPr0CZSUvswKVJsBg/vSoWO7VLcvXaYUew/tYPGCZRzYd4jXr4JQU1OlctVK9OrdnVFjh+f6GYSE1BUtVoR5C3y5cO4i16/f5MO7D4SGhqKsrELJUiWoXqMaf//Tgd59eogLKaB06VJMN9LjwrmLvHj+ktDQUPLm1aZCpQp07tqJ4SMHo6Wl9cN2VatXxtLGjKtXrvPg/kNCQ0IJD49AU0uTSpUr0rhJQ4YMH5TuoOqcLrOOR5OmjTh4dBeLFy7n2JETvH3zDiUlJapWq0LHTu0ZO2FUru5YAtnbZG5Xu05N9h/dxcLAJRw9fJy3b96hlUeLulXr0H9AbwYO6Z/miPlWrVsweuwILl+6wts374iMjKRwkULUqVub3n170K1Hlxw3CkwQhGRK0l/dmA2Eh4ejq6tLWFgYOjo5ZyixIMjK1dUVHx9vLl5PPaRX+F61CnVp37Et8xf7y7sUhbd08QpmO3vy6MVteZeSI1QpX5sZpgZM0Z8o71IUntH0mezesZfHL3/MDRN+VK1iXSZPnSBuvUgHSzNbNqzbzP2nN0RHaTrUrNyAEaOGYmEzU96lKDwXB3eWLl7B9bsX0dHJJ+9yFF6dao3o2793rrgtPasdPXKcCaOn8ubNG0qUKCHvcgQhx/qdviDFD2ERBEEQBEEQBEEQBEEQFJboXBIEQRAEQRAEQRAEQRBkJjqXBEEQBEEQBEEQBEEQBJmJziVBEARBEARBEARBEARBZqJzSRAEQRAEQRAEQRAEQZCZ6FwSBEEQBEEQBEEQBEEQZCY6lwRBEARBEARBEARBEASZic4lQRAEQRAEQRAEQRAEQWaic0kQBEEQBEEQBEEQBEGQmehcEgRBEARBEARBEARBEGQmOpcEQRAEQRAEQRAEQRAEmYnOJUEQBEEQBEEQBEEQBEFmonNJENIQGxvH2zfv5F2Gwrtw7iIJCQk8evCYxMREeZej0BITEzl6+DgSSRKXL16VdzkK7+rV6yQlJnHs6Eni4+PlXY5Ck0gk3L97H4lEwpnT5+RdjsK7dfMOCQkJnDx+iri4OHmXo9AkEgl3bt8F4NTJM3KuRvHdv/+QuLg4Tp06Q3R0tLzLUWgSiYSbN28BcPL4aTlXo/iePnlGTEws585eIDIySt7lKLznz17IuwRB+OOIziVBSEWzZs3IkycPf7frxlzfQGJjYuVdksIJ/hDMgD7DGD54LNraeXj69BkNajdn47ot8i5NIa1bs5H6tZpx7swFtLW1GTJgJIP7jeDjx0/yLk3hhISEMHTAKAb1GY62dh4uXbhMw9rNWb1ynbxLU0hbNm2nfq1mPHzwmHz58jJq6Hj69RzM+3cf5F2awgkPC2fUsPH07TGIPFpa3Lh+i4a1m7Nk4XJ5l6aQdu3YQ4Pazbl18w758uVl0lh9enbtz+tXQfIuTeFEREQxfvQUenbuh6amBg/uPaRRnZYE+C+Qd2kK6cC+QzSu25JLF66QL19eDPVN6Pp3b148Fx0C/xUdHc2UCdPp3KEn6urqPH3yjMb1WuLt6Y9EIpF3eQrnyeOnjB0xCWf72bRv3x4dHR15lyQIfwzRuSQIqejQoQOPHj1imv405vktoFO77uzdvR+pVCrv0uQuMTERq1m2tGrakVs3bqM/fTLnr55kw5ZVlCpVEgszG9q16MStm3fkXapCuHHtFm2a/421uT1//VWGjdvWcO7KCaZOm8i1azdo2bg9NhYO4gsiyb9iO9i60KJRO65cvsakqeM5e/kEW3aso3yFcthZOdGqaQeuXrkm71IVwt3b92jfqjNmMywpXrwYazeu4PzVkxgY63P3zn3aNP8bc1NrMaKQ5Lbl5uRBk/qtOXvmPGMnjOLMxWNs372JylUr4+o0h+aN2nLh3EV5l6oQHj18TKd23THUN6VQoYKsXLuEi9dOYzLLiMePntChdReMp5uJEYUkty1vD3+a1G/JiWOnGDFqKKcvHGXX/q3UrlMTrzl+NKnfmpMnxMgcgOfPX9D1797oTTIkb768LFk5n0s3zmBhPZNXL1/RqV0Ppk0xJjZW/KgHEOC/gEZ1WnLowBEGDe3PyfOH2XNwO/Ub1GOe73ya1G/N0cPH5V2mQggPC8fJ3o2uf/fm5YtXbN26lSNHjqCtrS3v0gThj6EkTcfVcnh4OLq6uoSFhYneX+GP8+jRI0xMZrBr124aN22ErYMFNWvVkHdZcrFx3RZcnNyJjIikW4/OWFjPpFTpUinLk5KS2LxhK+5u3kSER9CiZVPmzvdBN7+uHKuWj8+hn9GfYsSFc5fQ0dXB3MqU/gP7oKKikrLOq5evcXWaw4F9h8iXLy829hYMGNxPjlXLz/atO3GwcSY8PIK//+mAle0sypb7K2W5RCJh+9aduDnN4fPnMBo1aUjgIl8KFiwox6rlIyI8EgM9Y06fOoe2dh5mWsxg8NABqKqqpqwTFPSG2S6e7Nm5D+282lhYz2TYiMFyrFp+9u7ej7W5PZ8/h9G2fRts7M2pULF8ynKpVMrOf/fg4uhOyKcQ6tWvQ+Aif4oWKyLHquUjMjIK4+kzOX70JJpampiaGTFs5GDU1NRS1nn/7gNz3LzYvnUnefJoYWJmxNgJo+RYtfwcPngUc1NrQkJCad6yKXaOVlSpWjlluVQqZd+egzg7uPH+3Qdq1a5J4GJ/SpUqIceq5SMmJgZTI3MOHjiChro6RibTGTV2OOrq6inrBAd/xMvdj80bt6Kpqcl0Yz2m6E2QY9Xyc/LEKUyNLPkY/JHGTRpi72xN9RrVUpZLpVIOHzyKo60rb968pVr1qixY7E+ZsmXkWLV8JCUlsXH9Frw9/ImLjcPKygpjY2M0NTXlXZog5Aq/0xckOpcEIZ0OHjyIsbEx9+7dY/DQAcwwM6Rw4ULyLitb3Lp5h+lTjHj58jVVq1XBwdmaJs0ap7l+eHgE8/zms2zJSlRVVBk1djjmVqYoK+f+wZISiQRXpzmsWbmepKQkxk8cjb7hVPLly5vmNufPXsTO2olHDx9TttxfBCzwpUat6tlYtfzcv/cA/clGPHv6nIoVy2PnbE2r1i3SXD8yMorAuQtZsnA5SspKDBs+CBsHyz+mbXm6+7B8ySoSEhIZPW4EBkZ6P+28vXTxCvbWzty7e5/SpUsxd74PdevXzsaq5efJ46dMnWTA44dPKFvuL+wcrWjXoU2a60dHR7MwcCkLAhYD0H9gHxxdbb/rtMvN/LznsTBwCXFx8QwfOQQj0+kULFggzfWvX72BnY0zt27cpkSJ4vgGeNK4ScNsrFh+Xj5/ydSJBty//5CSpUpi52hJx07tUVJSSnX92JhYlixaToD/ApKSJPTq0x3XOY7fdazkZgsCFidHDMTGMXBwf0xmGVKkSOE017996w721s5cvXKdosWK4OXrTsvWzbOxYvkJCnqL3sTp3L51l2LFi2Jjb0mXbp3SbFtxcfGsWLoKP+8AEhMT6dLtH+Z4u/wxHSvnz17E0d6V+3cfMGrUKNzc3ChZsqS8yxKEXEV0LglCFklISGDBggXY2tqSlJTEdGM9Ro0Zlmu/IIaHhTNtqjFnT58nn04+ZlnMYOCQ/t+NvvmZp0+e4WQ/mxPHTqKbXxdnNzu69+yaxVXLz64de7CxdCQ8LJz2HdtibWdO+Qrl0rXt11/e5rh6ERUVTctWzfEP9EJHN3e+50aER2I0zYSTJ86QJ48WpubGDB0+KN0X8i+ev8TVaQ6HDhxBRycfdk7W9O3fK4urlp8D+w5haWZLaOhnWrVuga2jJZUqV0zXthKJhC2btjPbxZPwsHCaNm9MwAJf8hfIn7VFy0l0dDQzDGZx5NAxNDQ1mDHTgJGjh303+uZngl4H4ebswd7dB8ibVxsr21kMHjYwi6uWn2NHTmA2w5JPn0Jo2rwJdo5WVKteJV3bSiQSdm7fjYvTHEJDQmnQqB6Bi/xz7Q8vsbGxzDS25MC+Q6ipqWE4Q5/R40aioZG+7wBv37xjjps3O7bvIo92Hmaaz2D02OFZXLX8nDl1jhmGswj+EEzDRvWxd7ZO98hvqVTKnl37cHaYTXDwR+rUrc38xf4UL14si6uWj/j4eCxn2rJzxx5UVJSZZjiV8RPHoKmVvk6i4A/BeMz2Ycum7Wjl0cLIZBoTJ4/L4qrl59XL17g5e7B/70GaNm2Cv/9cmjRpIu+yBCFXEp1LgpDFPn78iK2tLQsXLqRcubJY2pnRvkPbNH9ZymkkEgmzXTxZtXwtiUmJjB0/iumGU2Xu6Dh+9CQOti68eP6SSlUqErjQL90XxjnBw4eP0ZtowNMnzyhfoRz2Tta0bttSpn2FfQ7D3zeQlcvWoKamytgJozCdZZxrRuZIJBJ8veayeMFyEhISGDl6GIYz9GXu6Dhz+hz21s48efyU8uXLEbDQh2rf3DqQ0z179hy9CQY8ePCIMn+Vxs7JSub3moiISAL85rN08UpUVFQYMWoIlrazck3bApjnN5/AuYuIi4tjyPCBzJhpSKFCst06efH8JeysnXlw/yFl/irNvPk+1K5bK5Mrlp/Xr4KYMnE69+7cp0SJ4tg6WtKpc0eZ2lZUVBQLAhazcP5SlJSUGDS4Pw4uNrmqbS1asAw/r3nExsbSf1BfZs4yokhR2W6dvHrlGvbWzty+dZeSpUrgH+hFg4b1M7li+Xn79h16Ew24eeM2RYoWxsbegm49usjUtmJiYli8YBmBcxchlUro3a8Xru4OuWpE4cpla/Bw9yE6Kpo+/XphZjGD4iVk60S7cf0W9jbO3Lh2k2LFi+Lj70GzFrmn0+Xre82ShSsoVKgQ7u7uDBs2LFe91wiCohGdS4KQTW7duoWRkRFHjx6lbbvWWNnNyvGdJnt378fK3J6wNPJJZJWQkMDqletS7onv2Kkd3v5zyJMnTyZULR/pySeR1ZPHT3G0c+XUiTPkL5AfV3dHunTrlAlVy8+3+SQtWjXD1sHyu3wSWSUmJrJ+7SY8Z/sQHR1Dm7Yt8Z3nRT6dtG9FVHTR0dGYGllw6GDa+SSyevb0OS6O7hw9fBwdXR0cXWzo1adHJlQtP8n5JBZ8DP6Uaj6JrL7LkYuIoEWLnJ8jFx8fj5mJFXt37UdFVQUDI33GTRiFhqZGhvedG3Pkzp+9iPF0M96/f0+9BnWxd7KmTiZ0Mv6QI9e4AQGLfClUKOeO+kpMTMTCzJad23ehpKSM3vRJTJwyDi0trQzv+82bt8x29mT3zr1oa2tjYZPzc+SuXLqKob4pb968pVadmjg4WVO/Yb0M7/drjpyrkzufPoZQt34dAhf6Uax40YwXLSdfR0m6u3nzOfQzpqammJubkzdvzv2cF4ScQnQuCUI2kkql7NixAxMTE16+fMmI0UMxNNbPcRcfjx89QW+yYbrzSWT16VMIPh7+rF+7CQ0NDfSmT2Ka4dRMf56sJJVK8fMJYNFv5JPI6tiREzjYuvDyxSuqVK3M/CX+lC9fLtOfJyu9eP4CvYmG6c4nkdXn0M/4eQeweuU61NTUGD9pDDNmGuS4XzTnByxinu98YmPjGDR0ACZZlO926sQZHGxcePr0GRUqlidwsT9VqlTK9OfJSt/mkxQvXgxre4uf5pPI6r85ciPHDMfCOuflyC1bvBJvDz+io2PoN6A3M81nZMkFZ27IkXv/7gN6kwy5fu0GhYsUxsp2Fj17d8v0tvXfHLkhwwZh55jzcuTWrFqPu4sXUVFR9OzdnVlWJpQsmfnB5ZcuXsHBxpm7d+5TqnRJ/Od7U79+3Ux/nqz08eMn9CcbceXSVQoUyI+FzUz69OuV6f/P/5sj129gH5xyYI7cjWs3cbRz49rV6wwYMIA5c+ZQvnzGf/QUBCF9ROeSIMhBbGwsvr6+uLi4oKauxoyZBgwZNjDd+UTyktF8Elndu3sfBxsXLl64TOEihfD0daNN29ZZ+pyZ4eiR48yaYSVTPoms4uPjWbViHb6e/sTFx9Ppn454+rop/Kiv/+eTHERNTf2380lk9ejhYxxsXTh7+jwFChbAzcOJfzp3zNLnzAxnTp3DxHAWH2TIJ5FVQkIC61ZvxHOOL7ExsbRr3xqfeZ7kzavYUzfHx8djYWrNrp37ZMonkdXTJ89wdpjN8aM5K0fu4vlLGE2fybu376lTrzYOTtbUrV8nS58zp+bIJSYmYmPhwLYtOwCYOm0Sk6aOy/L325cvXuHi6J7jcuSuXbuBwVQTgl4HUaNmNeydbWjUuEGWPqdEImHr5n+Z7exBWFg4TZo1Yt4CH4WfPVQikWBv48LG9ZuRSqRMnDKOqdMmZfn7bU7NkXv/7gMes73ZtmUHderUxs/Pn3bt2sm7LEH444jOJUGQo7dv32JpacmKFSuoVqMqNnYWNG/ZVN5lperbfJKhwwdhPNNA5nwSWUilUvbvPYSzvRvv3r2nZq0aBC7yo3SZUtlWQ3q9evGKqZMNk/NJSpbA1sFC5nwSWX38+AmvOX5sWr8FTU0N9A2mojd9UrY9/+9YNH8pft4BmZJPIgupVMrRw8dxsHUh6PUbqlarwvzFfpQtVzbbakivt2/fMXWiAbdu3KZosSJY25nLnE8iq9DQUHw957Fm1XrU1dWZrDceA2N9hRw9sXLZajxm+xIdnfF8ElmdOHYKB1sXnj97QaXKFQlcpJg5csEfgtGbbMi1KzcoWLAAlraz6NWne7b+f/1vjtyYcSOZaTFDIdvW+rUbcXPyIDIyiu49u2BuZUqp0tn7eXTm9DkcrJ15/Pgp5cqXJXChr0LmyIWEhKA/2ZhLFy6jq6uLubUp/Qf2ydb/rxERkQT4L2DpohWoqKgwbORgrO3MFbJtbduyAwdbFyLCI/iny99Y2pjxV9ky2VrDxfOXsLdx4f69BwqdIxcXG8fSJSsJ9F9Injx5cHFxYfz48Qr/Y60g5Faic0kQFMClS5cwNDTg3LnzdO7aCUsbM8r8VVreZQHf55M0adoIOyerTMknkVVcbBxLFq9gnt98khKT6NmrK26ezgoxC198fDxmMyzZu/tApueTyOrO7bs42Lhw+dJVihQtjKfPbJkDxDPbuTMXmGFgxvv3HzI1n0RWcXHxrFy2Gj/vABIS4vmnSyc8fd0UYprmr/kkO7btQllZGX2DyUycPC7LR9/8zP17D3GwdeHCuYsUKlQQdy8XOvzdTm71fCur8klklZCQwJqV6/Hy8CMuNo4Of7fF238O2tryH/WVmJiIvbUzmzduQ4qUKXoTmKw3Qa61fZcjlz8/LnMc6NrtH7nV862b128xbeoMXr96TbXqVbF3tqZJ00Zyq+e/OXKt27TAL8BbIXLkJBIJzvZurFuzEYlEyvhJY9CbPpl8+eRX27Onz3F1dOfI4ePo6Ojg4GJD776KkSN3/+599CYbpXRE2ztb06JlM7nVk5SUxJaN25jt6kVEeATNWjRh3nwfhZg9VCqVcnD/YVydPHj75i3Tp0/H1taW/PnlX5sg/MlE55IgKAipVMr69esxMzPj48ePjJ80hqnTJsrtC/7r12/Qm2TAnSzOJ5HVu7fvmePmzb/bdpInTx5mmhsxetxIudWzZOEKfLz8iYmOof/APsw0N6ZoMcUIxJRKpezbcwAnezc+vA+mdp1azF/iT4kSxeVST3I+iQHXr92kcJHCWNvNokevzM8nkVVw8Ec83X3ZsnEbmpqaGMzQY/LUCXKrZ83K9bi7ehIVFZ2l+SSykEqlHDpwBEc7N96+eUu1GlVZsMifMtn8K/tX2ZVPIqv/5shN0Z+IgbGe3OrZvGErTg6ziYyIpGv3f7CwNlOo0aD/zZELXOxHhQryyU/5HPqZaVONOX/2Ijq6OsyyNGHAoL4KM0Lic+hn/H0CWbVi7ZccudHMmGkot7a/Y/su7KycCQ8Pp2On9ljZzqJcecUZDXrq5BkcrP+fIxewyI+qmTBphCwiwiMx0J/B6ZNn0NbWxtTcmCHDBipM3tHXHLnlS1ahoqLCyNHDsLCZKbe2df/eQ5zt3Th75jxdunbBx9uHatUUb8SeIPyJROeSICiYqKgo3N3d8fDwSP4CazGD3v16ZtuH+Hf5JKoqTDOcyoSJY+Q6+uZnrl+9ga21E7dv3qFEyeL4B3jRMIszHL71Qz6Jsw1169XOtuf/HbExsSxZtJwA/wUkJUno1bcHru4O2TbqK7V8ksl64zNldqCscOvmHeytnbl29TpFixXF2989W39Fvnr1OoZ6JgS9fpNt+SSyiouLZ/mSlfj7BJKYmEjXHp2Z4+WChkb2vG+k5JOs24xUmn35JLK6d/cBDjbOyTlyhQvh4eNG2/bZlyN3+9Zdpk0xSum0cXC2pmlzxZyCPD4+ntUr1+Hj4U9cXDx//9MBL7/Z2ZYjJ5FIcHPyYPXKdSQlJTFuwmj0Daego5MvW57/d8k7R+7+/YfoTzLk2dPnVKhQHjtnK1q3UYzRsv+VmJiYnCPn7ktMTAxt27fGNxtz5CQSCV5z/Fi2eCUJCQmMGjMcA2M9hRgZlJqnT5/hYj+bY19y5Jzc7OiRjTlyISGh+Hj6s37NJipXroS3tw/dunXLtucXBOHXROeSICioFy9eYGZmxqZNm6hXvy62DhbUa5C1s5woQj6JLCQSCTu27cLVaQ6hoZ9p2Kg+AYv8smTWrK+CPwSjN8mQa1f/n0/Su28PhRl98zNv37zD3dWLnf/uRls7D2aWJowcPSxLn/OHfBLrmZQqVTJLnzMzSKVSdu/ci7ODOx+DP1K3Xm3mL56bpdM0K0I+iaw+vP+Ax2wftm7+F608WhibGDBh8pgsfc5tW3bgaOtCuBzzSWQhlUo5sO8QTnbZlyMXHhbOdL0ZnDl1jnz58mJmYcKgof0VZvTNz3z8+AlvDz82rtuChoYG0wyzPkdu98692Fg4EBYWTvsObbCyN5fbyKnf8d8cuSpVK7NgiX+W5shFRkZhpG/CieOn0dLSwnSWEcNGDlaY0Tc/8zVHbu3qDaipqzFxyjiMZkzL0vfcA/sOYTnLjtCQUFq2bo6tgyWVc8gMnCk5cs9fULFiBeYv9s/SHLmEhATWrtqAn/c8QAk7Ozv09fUVIg5BEITvic4lQVBwJ0+exNDQgOvXb9C3fy/MLEwy/cL2yqWrGOib8PbNO4XIJ5FVVFQU8+ctZtGCpSihxOChA7B3ts7UL4iJiYnYWTmxZdN2ACbrjZd7Pomsrly+hr21E3du36NU6ZL4BXjSoGH9TH2OG9duMV3PmNevghQin0RWMTExLJq/jPnzFiGVSunbvxfOs+0z9cJJIpHgZO/GegXKJ5HVjeu3sLdx5sa1mxQrXhTfuZ40bd44U5/j3p176E8xVph8Eln9N0eue8+uuHtlbo6cRCJhjps3K5etJiEhkTHjR2JgpKfws7GlJjty5B4/esLUiQY8efyU8hXKYedoRZt2rTL1ObJDXFw8q5avwddrHgkJCfzT5e9Mz5GTSCT4es1l8cLlJMQnMGLUUAxN9ClQoECmPUd2eXD/IQ62rpw/e4GChQoyJwty5J4/e8HUiQY8fPCIUqVLYudkRYeO7XLED1Pf+poj5+3pT2xMLO07JufIZfaor5PHT+PsMJsnj58yYcIEnJ2dKVpUMSIHBEH4kehcEoQcICkpiWXLlmFlZUVUVBRTp0/KlFvVPn78hP4kQ65cvkaBAvmxtDHL1lvwssqrl69xdZrDgX2HyKeTDxt7CwYM6pvh/W5avwVnR/cv+SSdsbCeqVD5JLKQSCRs37oTN6c5fP4cRqMmDQlc5JvhaZoVPZ9EVkFBb5jt4smenfvQzquNhfVMho0YnOH9/rttJ/bWzoSHRyhkPokspFIpO//dg4ujOyGfQqjXoC7zF/lleCbAiPBIDPSMOX3qrELmk8jq/bsPzHHzYvvWneTJo4WJmRFjJ4zK8H737j6Atbkdnz+H0bZda2wcLKhQUfFH3/xMco7cQZwd3Hj/7gO169QkcPFcSpbMWI5cZGQUMwzMOHbkBJpampjMNGT4qCGoqallUuXy8d8cuenGekzRy3iO3JFDx5hlakXIp1CatWiKnaMlVatVyYSK5UcqlXL44FEcbV15k4k5crGxsZgYmXNw/2HU1dQxMpnG6HEjcvzom5CQUHw8/Fm3ZmOm5sg9ffoMV8c5HD18nLZt2+Lr60u9evUyXrAgCFlKdC4JQg7y+fNnnJyc8PdPDmM2t54pU8i2RCLB3tqZjeu3IEXKpCnj5RoenlXOnbmAnbUTjx89oWy5vwhY4EuNWtV/ez+3b91l2mRDXr58rfD5JLKKjIwicO5ClixcjrKyEkOHD8LGwfK3OxolEgmuTnNYs3J9jsgnkdXFC5dxsHHh3t37lC5TirmBPtSt//tZW9/mk1SsWB47Z2tatW6RBRXLT3R0NAsDlrAgcAkA/Qf2wdHV9rc7gyQSCV7uvixbsio5n2TscAyN9dHNr5sVZcvNf3PkfOd50rhJw9/ez9Mnz5g60YBHDx9Tttxf2DpY0r5j2yyoWH4yM0fOz3seCwOXEBcXz7ARgzGeaUDBgjlv9M3PfJ8jVwRvP3datGr+2/t5+eIlUycacv/eA0qWLIGtoyV//9Mhx42++ZkfcuS6/4O7l4tMo74WBCxmru98YmNjGTi4PyazDClSpHAWVC0/3+bIFSpcCA9vV9p1aPPb+wkPjyDAbwErlq2mZMmSeHp60r9//1zVtgQhNxOdS4KQAz148IAZJjPYu2cvzZo3wcbBkuo1qqZr262b/8XRzpWIHJZPIqvExEQ2rt+Ch5s3UVHRtGzdHP9A73R1doSHhTNtqjFnT5/Pcfkksnrx/CUuju4cPngUHZ182DlZ07d/r3Rtu3vnXqwtHAgPC6d9x7ZY25lTvkK5rC1YjpKSkti6+V9mu3gSHhZO0+aNCVjgm64w1siISAynmXLyaz6JuRHDRuSMfBJZvX4VhJuzB/v2HCBvXm2sbM0ZPGxAurY9sO8Qlma2hIZ+znH5JLL4b45cg0b1CFzkn64cuejoN5KCIgAAgLFJREFUaEwMZnH40DE0NDUwNp3OyNHDcvwIiZ/JSI7csSMnMDOx4tPHTzRt1hhbR6t0f57mRFKplD279uHsMJvgD7+XIxcbG4vZDEv27z2EqqoqhjP0GTN+FBoaubdtfXj/IXnU16btX3LkpjNh8th0bXvm1DlMDGfx4UMwDRrWw97Zmlq1a2ZxxfLz3xy5GjWrM3+xf7pGeCclJbFl03a83H2Jjo7BwsICExMThZ3wQxCE1InOJUHIwfbt24exsRGPHj1myPCBGJsaUKhQ6rcz3b19D/0pRrx4/pJKlSvi4GxD85ZNs7li+Qn7HIa/byArl61BTU2VsRNGYTrLONWRORKJhNkunqxavpbEpETGjh/FdMOpOTKfRFanT53FwdqZJ0+eUb5COQIW+lKteuoXXA8fPkZ/kmGOzyeRVUREJAF+81m6eCUqKiqMGDUES9tZabat3JJPIquL5y9hZ+3Mg/sPKfNXaebN96F23Vqprvvs2XP0Jhjw4MEjSpcplWPzSWQVFRXFgoDFLJyfnCM3aEh/HFxs0hxROM9vAYFzFxIXF8eQ4QOZMdMwzc+E3OjbHLmSpUriH5h2jtzrV0FMmTide3fuU6JEcWwcLPiny99/TNv6PkdOQp/+vXH5SY7cogXL8POaR0xMDAMG9WWmuXGGb3HNSf6bI+fj70GzFqmPYH779h16Ew24eeM2RYoWxtrOnO49u/4xbSsuNo6lS1Yy1zfwS45cF9y9XNLs4L544TJOdm7cuX2XESNGMHv2bEqVytmRA4LwpxKdS4KQwyUkJBAQEIC9vT0gxcBYnxGjh6ZkRISHR2CgN4MzX/JJZlrMYPDQAbl6hMTPPH70BEdbV06fOkuBAvlxneNI566dUpbv3X0AK3M7wnJRPomsEhMTWb92E56zfYiOjqFN25b4zvMin05ywHRkZBTG02dy/OjJXJVPIqtnT5/j7DCbY0dOoKOrg6OLDb369EhZfvjgUcxNrQkJCaV5y6bYOuT8fBJZJSUlsXnDVtxdvYiIiKR5y2bMm++dcotbTEwMpkYWHDxwGA11dQxn5I58Ell9lyOXLx82Dt/nyJ08cQpTI0s+Bn+kcZOG2DlZUaPm798CnBv8KkcuPj4eMxMr9u7aj4qqCtON9Bg/YXSGMwxzqu9y5LS1sbD5Pkfu/NmLGE834/3799StXwd7J2vq1vv9W4Bzg29z5D59/ET9BnUJXORH0WLJo74SExOxNLNlx/ZdKCkpM3XaJCZNHffHjr75MUfOkLETRqcsDwp6g7uLJ7t37qNR40b4+/nTvPnv36YpCILiEJ1LgpBLBAcHY2Njw+LFiylfoRxWtrO4dOEyy5asJCEhMdfmk8hCKpVy7OgJHGxcePUlR8nCeiYuTu48fvgk1+aTyOpz6Gf8vANYvXIdampqTJg8FhUVFRbNz935JLI6deIM9jbOPHv6nAoVy2Ntb4GHmxf37z2kZKmS2Dla0rFT+z/mV+yfCQ8LZ67ffJYvXYWqiiojxwynQMH8BPjNJzY2joFD+mNilvvySWR17swF7G2cU3KU7J2s8fbw5/atOxQrXhRrOwu6dv9HtC2+z5FT+pIjV6ZMaXw85xIdHZ1ls6/mVJcuXsHe2pl7d+9TqnQpHFysCfBbyPVrNyhcpDCWNmb06tNdtC1+zJHrN7A31WtUw8PNh6ioKHr06oa5tSklS5aQc6WK4frVG9jZOHPrxm2KlyiOu5czVy5dY9H8JeTPXwB3d3dGjBiR4yeTEQRBdC4JQq5z48YNjIyMOH78OACtWrfA1tGSSpUryrcwBRQfH8+q5Wvx9ZpLbGwc6hrqmM4yYuToYX/s6JufefjgEY52rpw9fR6Aps0aY+dkTbXqf+bom59JSEhg3eqNzJntTVxsHOrq6n9EPomsnj55hrPDbI4fPQnwR+STyOprjpy7iyfR0TGoqakyzXAq4yeOQVMr86aYzy2+zZEDqFO3Fg7ONtStX0fOlSmerzlybs4eRIRHoKKiwhT9iUzWG0+ePHnkXZ7CCXqdnCO3d/cBAKrXqIa9s7VMAfy53bc5ciEhoaioqDBz5kwsLCzIly93TfghCH8y0bkkCLmQVCqlQYMGFCiky5IV88Uvjb9w6eIVBvcbgYePK/0H9v31Bn8wqVRK0/qtqVS5Ims3rRBt6xf27N7P9CnGrN6wjJYyzMr0p2nRuD1FixZm++5Nom39wulTZxk1dDyLVwTS8e/28i5H4bVv2RkNTQ32HvpXjJD4hZs3btOn+0Dmzveme8+u8i5H4XXu0JPY2DiOnd4v2tYvfPz4iSb1WuHn54eBgYG8yxEEIZP9Tl/QnxnQIgg5kJKSEsWKFUNZFXGBlg5fpxbW0PgzMzd+h5KSEsoqymhqaYq2lQ4aXzKCZJm++k+koqKMpqZoW+nx9f1KtK30UVFVQUNDXVz8p4O6hnjf+h0qKiqoq6uJtpUOX9tUsWLF5FyJIAjyJt4xBUEQBEEQBEEQBEEQBJmJziVBEARBEARBEARBEARBZqJzSRAEQRAEQRAEQRAEQZCZ6FwSBEEQBEEQBEEQBEEQZCY6lwRBEARBEARBEARBEASZic4lQRAEQRAEQRAEQRAEQWaic0kQBEEQBEEQBEEQBEGQmehcEgRBEARBEARBEARBEGQmOpcEQRAEQRAEQRAEQRAEmanKuwBBEBRPTEwMF85d4vatO9y+dZfbt+7wJugtAAbG+hiZTEtz23dv33Po4BHOn73I3dv3ePfuPQBFihamXoO6DBk2kBYtm2XL68hqFUpXT/e6zZo3Yd3mld89duHcRU6dPMutm7d5+eIVoaGfiY6KRldXh8pVKvFPl78ZMmwgmlqamV16lslI28mq4zF2xCROHD8FQNNmjVm/ZZXsLzAbhYaGcvjgMc6ePs+d23cJev2GpKREChYsSO26teg3oDedu3ZKdduMts2c7NTJM2xct4Xr127w8eMnlFCiaLEi1G9Qj6HDB9K0eZMs2VaRZOQ8TIuVuT3r12wEoFTpkpw6f+Sn6x8+eJQN6zZz88Ztwj6Hkb+ALnXr1WHYiMG069Dm91+Ugpk/bzEes71T/v309b0f1snIOayoMqNtBQd/ZNH8pRw9fJw3QW/R1NSkctVK9B/Qm0FDB6CkpJTqdkcOHePC+UvcvnmHN2/eEvIphLi4eAoUzE/16tXo1rMLffv3QlVVcS5vMutcDP4QzOqV6zh+9CSvXgYRGxtLocIFqVSpIk2bN2HC5DGoqamla1+/ey4LgiCkl+K8+wqCoDBuXLvFuFGTf3u7N2/e0rppR6RSacpjWlpaSKVSXr8K4vWrIHbv2MvAwf1wneOIiopKZpad7QoXKfzT5YkJCXz+HAZAnbq1fli+aMEyjh05kfLvPHnyoK6uzqdPIXw6d5Hz5y6yfOkqlq9ZRIUK5TO3+Cwia9uBrDkeWzZtT+lYymma1m9DYmJiyr81NDRQVVXj3bv3vHv3nkMHjtC2fWsCF/mhpaX13bYZbZs5kVQqxdrCIeWiCUBTM7kj8tXL17x6+Zqd/+5m3MTRWNuZZ9q2iigj52Fqzp25wIa1m9K1blJSEqZGFuzYvgsAJSUldHR0CPkUyuGDRzl88Cijx47Azskq0+rLbk+fPMPfJ+CX62XkHFZUGW1bt27eYczwCYSGfgZAWzsPUVFRXL54hcsXr7Bvz0EWLQ9AXV39h209Znvz8MHjlH/nzauNsrIyH94H8+F9MCeOn2L1irUsXbWQIr94D8wumXEu7t65F8tZdkRGRALJ7UhNXY03QW95E/SWkydOM3zkYNR0f9259DvnsiAIwu8SnUuCIKRKV1eXmrWrU6tWDWrWroGzw2yCP3z86TaSJAlSqZQWrZrRb0BvWrZqQbHiRZFIJDx5/BRPd18OHTjC5o3bKFa8KDNmGmbTq8kaF6/9vNNiycLluDrNAWDQ0AE/LG/Zujlt2raiUZMGlC1Xlrx5tYHkX7t3bt+Du6sXr16+ZuqE6ew7vBNl5ZxxJ7MsbQcy/3gEfwjGxcEdHV0dihYtwuNHTzLl9WWXxMRE6tarQ/9BfWjTthV/lS0DwOtXQczzm8+mDVs5cewUVrPs8Paf8922GW2bOdGWTdtTOoe6du+M6SwjylcoByR3Bri7enHowBGWLV5J4yYNvxsxkpFtFZWs5+F/xcTEYGlmi6qqKtVqVOXWjds/Xd9rjl9Kx9KY8SOZbjSVAgUKEB0dzbrVG5nj5s3K5WsoW+4vxowfKdNrkyeJRMIsEyvi4uJo0LAeV69cT3PdjJzDikzWthUeHsGEMVMIDf1MxUoV8PJzp07dWsTHx7Nh3WZcHNw5eeI0TvZuOLna/bB9l26dGTNuJA0bN6BMmdIpo1jfv/vAxvWb8fcJ5Patu8w0smDF2sWZ/rpllZFzce/u/RhNm4lEImHo8EGMGT+SylUqARAZGcXdO/c4uP8wqmq/vqT73XNZEAThd4nOJUEQftC4aUOu3Tn/3WNz3LzTWPv/dHR12LlvC7Vq1/zucWVlZSpXqcSCJXMZN3IyJ46fYvmSVehPn4KGpkam1q5INm3YCkCjJg2pUPHHkTbjJoxOdbsCBQowetwI1NXVsTK349HDJ1y9cp1GjRtkab2ZQda2A5l/PGwsHQkLC8NtjiP/btuV4zqX1m5cQfOWTX94vHSZUsz2dEZFVZX1azby77ZdmJobU7JkiXTv+1dtMyfavmUHAGXL/YVfgOd3t8ZUqFieeQt86NSuOy9fvGLP7v3fdRBlZFtFlJHz8L883X158eIl+gaTeff2/U8vSENCQlm2JPkWy386d8TWwTJlWZ48eZgweSyfPoWwMHAJvt7z6D+oL/ny5ZWpLnlZuWwNVy5fo3ffnpQt99dPO5ey8hyWl4y0rSULlxH84SOamposW7WQMn+VBkBdXZ1RY4YTGRmF52wfNqzdzNgJo34YoZrWLWTFihfFwFifuLh45s9bxMkTp3n75h0lShaX4RVmrowcrw/vP2A1yx6JRIKl7SwmTBrz3fK8ebVp0rQRTZo2Stf+fudcFgRBkEXO+BlcEIRsJevtajo6+X7oWPqWkpISA4f0AyAqKprHj3PWxf7vuHL5WkpnxmAZR4bUa1A35e93b99lSl1ZLStvdfyd47Fn1z4O7j9M02aNc+zInNQuSr81aEj/lL9/5yIhM9qmIvrwIRiA6jWqpZq5oqamRvUa1QCIjorOtG0VUWadh9euXGflsjWUr1COaQZTf7n+2dPniI+LB2Di1PGprjP5y+PhYeEcOnA4U+rMLq9evsZrjh8FCuTH2v7Xt0dm1TksTxlpW9u+dOL26N0tpWPpW6PHDkdbOw9JSUns2Lb7t/df/5vPiPdf8h7lLSPHa8WyNYSFhVGzVnXGT0z9x5f0+t1zWRAEQRaic0kQhGylofH/kUpJSRI5VpK1Nq3fAkA+nXx069FZpn1cung55e+/yv6VKXXlZOk9HqGhodjbuKCuoY7LHIc0w2FzOlnPpcxom4ro68Xqvbv3v8u5+SohIYF7d+8DULtOrUzbNreKi4tnlqk1UqkUV3eHdI0yDXr9JuXvypUrprpO/gL5KVS4EACnTpzNnGKziYWZDdHR0VjZzaJQoYIZ3t+f8nkIybeXfg2ybte+darraGtr06hJQwBOnzzz289x6cIVIPmHrDJfbkHMyb6OqOzdr1eGPsdkOZcFQRBkITqXBEHIVufPXQRAXV0tJdMkt4mKimLv7v0A9Ozd7beCWmNjYnn29DkBcxemZOI0adoo14Qu/y5ZjoeDjSufPn5iuuHUHBOELosLX84lgGrVq6Rrm4y0TUU3YtRQAF48f4mhvinPn71IWfb0yTOmTzHm5YtXlC37F+P+MwogI9vmVnN9A3n86AmDhvSXaZa8JElSmsskScnLHtx/KHN92W3D2k2cPX2elq2b029An0zZpyzncE714P6jlL+rVK2c5npVvyx7lM7bmKOionhw/yGznT1Ysmg5AH3798qUzj95evXyNe/ffwCgdu0a3L/3EEN9U5o2aE21CnVo0agd06cac/nS1V/uK6PnsiAIQnqJzCVBELLNq5evWbc6OTS3e8+uOS5rI71279hL1JdbZwYPHfjL9YM/BNO0QepTc3fs1B4Pb9dMrU/RZeR4HDl0jJ3/7qZK1cpMSuO2nNwgPCyc+QGLgORMj/TmJv1u28xJOnZqj7W9OXNcvdi35wD79hxImfEtNjYWHV0dho8agslMwx/eezKybW505/ZdFs1fSuEihbGwnpnu7UqXKZXy98P7j1K9kA3+EJwyU9iHLxfPiu7d2/e4uXiiqamJy2yHTNmnrOdwTvXt/+tixYulud7XZZERkURFRaGtrf3DOteuXKd/76E/PK6iokK/Ab1xcLbJhIrl69nT5yl/X758jbk+AcTHJ6CpqYm6hgbv3r1nz6797N19ACOTaUw30kt1P7Key4IgCLIQI5cEQcgWsTGx6E8xIiYmhoIFC2BmYSLvkrLMxi+3HVWvUY3addLOoPpKWUWFwkUKU7hI4e9uk+jWowvmVqbkL5A/q0pVSLIej/DwCKzN7VFWVsZtjiNqar+eljknkkgkzDCcxYf3wWhoaGDvlP4Lqd9tmznNuAmjCVzsn3LbVWxsLLGxsQAkxCcQHRVNxJfpvDNz29wkMTGRWSbWJCYmYudoiY6uTrq3bd6yGeoayVPIB8xdmOo6Af7/fzwyMmccTytzOyLCIzCcoZ8y41tGZOQczqkio6JS/tb6Mstbar5dFhUZleo6aupqKZ8R6ur/f58fOmIQBjP0U2aRy8nCwsJS/vbx8KdosaKsWr+U2w+vcPPeJQ4c3UWz5k2QSqX4eM5l/96DP+wjI+eyIAiCLETnkiAIWS4xMRGjaabcvnkHNTU1fOZ6UKx4UXmXlSUePnjE9Ws3gfSHJRcqVJCL105x8dop7j6+xpmLx9A3mMyRQ8fo1qkP69dsysqSFY6sx8PV0Z337z8wYtRQ6jesl71FZyNHW1eOHj4OgIOLDdVrVE3XdrK0zZwkJiaG6VONmTB6KiVLlWDluiVcvnmWyzfPsnLdEipVqcj2rTvp22MQ9+4+yLRtc5sFAYu5e+ceHf5uR/eeXX9r24IFCzBm7AgATp88i/F0M548fkpCQgJBQW9wd/Vi9cp1KR2/SkqK/zX03607OXbkBDVqVmf8f2brkpWs57CQrFbtmt98Rlzn6Kn9jBw9jHWrN9KlQ08OHzwq7xIzTCKRpvwtlUoJXORHq9YtUFZOPmcqV6nE4hWBFClaGAB/n8Af9pGRc1kQBEEWiv+pLghCjpaUlITx9JkcPHAEVVVVfOZ60LptS3mXlWW+jgzR0NCgT7+ev729kpISJUoWx8TMCJ+5c0hISMDG0iElTPhPk97jcfrUWTZt2EqJEsUxNTeWU7VZz9VpDqtWrAXA2t78u9mmfiWjbVPRuTl7sGfXfipULM+mrWto3aYlBQsWoGDBArRu05KNW1ZTvkI5QkJCsbN2yrRtc5NHDx8zz28+2tp5cHS1lWkfpubG9OjdDYAd23fRqV13qpavQ+umHVkYuIR69eukzBqqm1+xR1IEB3/Eyd4NFRUVXOc4pjqT4O/KyDmck+X95va2mJjYNNf7dpl23h9vifsvZWVlypUvi4OLDebWM4mKisZ4+swcc8tlWvJ+89pbtGqW6ky82trajBw9DID79x4QHPwxZVlmnMuCIAi/S3QuCYKQZZKSkjA2MGPPrv2oqKjg7e+eq2an+q/4+Hh2bNsFQJdu/2R4CHqXbv9QslQJJBIJm9ZvzYwSc7SfHQ9Ls+Qvz7OsTFFSSg55/fa/JEnyTExJEsn/H0tKO3BYEc129mDJwuTAWksbM8ZNSH+wdGa3TUUTGRnFhrWbARg5eliqsyFpamkyasxwAC5fvMLHj58yvG1uY2flRHx8AnrTp6Crq/PDeZSYmHzOSKXSlMcSEhK+24eqqir+AV4sXbmAHr26UrFSBUqVLknjpg2xc7Riw9bVxH7pQChfvlx2v8TfMsfNm9DQzwwZPpCKlcr/cDy+fe1fH4uPj09zfxk5h3O6osX+P1r5/bv3aa73dVnefHlTzVv6mZGjhqKuoU5UVDQ7d+yVrVAF8e3o7kqVUp95EaDSN7MyvvlmtsbMOJcFQRB+lwj0FgQhS3wdsbR7576UjqUevbrJu6wsdfjgUUJCQoHMu+2oePFivAl6y/PnL3698h8grePx+lUQAEbTTH+6/eWLV6hdtREAC5bM5Z8uf2dNoZnMzcmDxQuXAWBuZcqEyWN/a/usaJuK5NnT5yQmJgL8NBOnXPmyKX+/fvmawoULZWjb3ObVq9cAeMz2xmO2d5rrvQl6m3IeWdubp9pJ0r5jW9p3bJvq9rdu3gagQaP6GS05S71+mXw81q7awNpVG3667tfjMWb8SGwdLH9YntFzOKerWu3/M8Q9fPDou06Rbz14kDyrXOU0lv+MhqYG+fPr8uF9MC9y+Gdm5cqVUFFR+eWPIFLpN/9QUkr5MzPPZUEQhPQSI5cEQch0SUlJGE0z/a5jqWfv7vIuK8t9ve2obLm/aNq8cYb3J5VKU74g5k3H7QG53Z96PFyd5nx3USrLLHiZ3TYVjbLy/y+qgoLepLnetyOOvt5yk5Fthd935/ZdHj1Mnma+34Decq4me2TGOZzTla9QjpKlSgBw4tipVNeJjo7m8sUrALRq8/u3z0dGRhHyKbkT/XdHPSkaDU0NmjRN7vR5/PhJmus9fvQYSL6F/NvZGgVBEORBjFwSBCFTfR2xtGfXflRVVf+IEUuQfFF65tQ5AAYO6Y/SN78gpiYxMfGX+R2bN24j+ENyhkJqU3rnJhk9Hk9f3/vptkMHjOLC+Us0bdaY9VtWZazYbOTqNOe722hkGe3wu20zJ6pYsQKamprExsayaf0Whgwb+EN7SkpKYsPa5DB4XV3dlKnfM7JtbnPq/JGfLp9pbMHWzf9SqnTJX66bmpiYGGwsHADo2r0zFStVkKnO7PKr9wpfr3n4+wQAab8HZcY5nBsoKSnRb0Bv5vktYPfOfUw30vuhM2T1inVERUWjoqJC7349vluWns+IxfOXpoxCbJYLPjMHDOrLubMXOHv6PLdv3fkhdykqKoo1q9YDUK9+HQoVKpiyLKvPZUEQhNSIkUuCIKQq7HMYISGhKf99nbkkNibmu8ejvple+GvG0u6d+1BVVcV3nscf0bEEsHnDNiQSCaqqqgwY2OeX61++eJXB/UewfcsO3r55992yZ0+f4+7qhbW5PQBly/7FgIF9s6DqrCFL28nNx0NW3+azWNnNkvmi9HfbZk6kqaWZcrvf7Vt3mThGj/v3HiKRSJBIJNy7+4BxoyZz5fI1AMZOGImKikqGt1VkspyHmeH61RsEzF3Io4ePU/KH4uPjOXHsFIP6Duf6tZuUKFkCBxebTH1eRZRZ57CikbVtTZg8jiJFCxMTE8P40ZO5dfMOkNw+1qxaj4+nPwBDhg+kQoXvO3B3bN/NxLF67N978LtRhF/PUUszW+b6zQegYeMGtG3fOste/++S9Xj17teTuvXqIJVK0ZtkyJnT55B8yQ98/OgJk8bqE/zhI8rKypjMMsrulyUIgvADMXJJEIRU9ejSj6DXP94ismjBMhYtWJby7/4D++Dh4wbAlUtX2f0lRFNJSQl7GxfsbVzSfA5bB4tc0fkkkUjYsmkbAO06tPkuuPRnLl24wqULybcAaGhooK2dh+joGGJj/z9bTvUa1Vi4dB6aWpqZX3gWkaXtQO49HrIICnqTcqyUlZVZGLiUhYFL01x/4uSxTJwy7ofHZW2bOdEsSxOeP3vBieOnUv5T11AHID7u/yHLPXt3R99gSqZtq6hkPQ8z6sOHYLzcffFy90VJSQldXR0iIiJTsmOqVK3MkhXzc2Vm1bcy6xxWRLK2LR2dfCxZsYAxwyfw6OETencbQN682sTFxaeESbdu2xJrO4sf9i2VSjly6BhHDh0DIE+ePGhqahAZGUl8/P+DqJu3bEbAAh+FGqEp6/FSVlZm0bJ5jBgylkcPnzByyDi0tLRQVVMlIjwCADU1NRycrWnRslnWvxBBEIRfEJ1LgiBkmq+/xgEkJCTw8ZtpcVMTGxuX1SVlizOnzvEm6C2Q/rDkWnVq4u3nzvlzF7l18w7BwR/5HPoZdXV1ypb9i5q1a9ClWye6du+cI0ZJZJQ4Ht+TfnMuSSSSX55LUVHRqT4uS9vMqTS1NFm2eiH79hxkx/Zd3L55h0+fPoGSEiVKlqBuvdoMGNyXDh3bZeq2wvdq1anJpCnjuHjhMq9fvyHscxj5C+SnWvUqdO/RhQGD+/3y9qbcILPO4dymdp2a7D+6i4WBSzh6+Dhv37xDK48WdavWof+A3gwc0h9l5R9vrGjfsS1ucxw5f+4S9+7e42PwJ8LCwtHU1KDMX2WoU7cWPXp1SzNEPqcqUrQIO/dtY/WKtezeuY9nz54TFxtL6TKlaN6iKeMmjqZqtSryLlMQBAEAJan0u3kGUhUeHo6uri5hYWHo6OSu6YsFISfp0qULyqoQsNBX3qUovFs379C72wD8A71yxeiorNasYRtq1KzOslUL5V2Kwjt88CiTxumz+d91NFTw2a4UQetmHSlVqiQbtq6WdykK79LFKwzuN4LVG5bRslVzeZej8P5u2w1t7Tzs2LtF3qUovPv3H9Lt794sXh5Ix07t5V2OwuvWqQ8JCQkcOr5H3qUovMjIKOpUa8SGDRsYPHiwvMsRBCGT/U5fkMhcEgRBEARBEARBEARBEGQmOpcEQRAEQRAEQRAEQRAEmYnOJUEQBEEQBEEQBEEQBEFmonNJEARBEARBEARBEARBkJnoXBIEQRAEQRAEQRAEQRBkJjqXBEEQBEEQBEEQBEEQBJmJziVBEARBEARBEARBEARBZqJzSRAEQRAEQRAEQRAEQZCZ6FwSBEEQBEEQBEEQBEEQZCY6lwRBEARBEARBEARBEASZic4lQRAEQRAEQRAEQRAEQWaic0kQBEEQBEEQBEEQBEGQmehcEoQcRiqVyruEHCExMRGApKQkOVeSMyQmJBEVFSXvMnKEr20qISFBzpXkDImJiURHR8u7jBxBtK3fk5CQQExMrLzLyBGkEgkA8fHxcq4kZ0hISCQ2VrSt9BDfSwVB+Ep0LglCDqKlpcXRw8fxmO1DZKToCEjLogXLGDF4LAAWZrYsW7xSzhUprrdv39G3xyBCQ0O5fPEqvbsNICjorbzLUlgrl61hhsEsAMaNmsz8gEVyrkhxBX8IZmDfYXz4EMyd2/fo1qkPL56/kHdZCmvjus1MHDMVgKkTDPD1micu2tIQEhLCsIGjCXr9hsePnvBPhx48fvRE3mUprG1bdjCk/0gAjA3MmOPmheRLZ5PwvfCwcEYPn8Czp88Iev2Gjq27cv/ufXmXpbDu3b3PpHF6QPJ3VEEQ/myic0kQcpC1a9diYWHB8iWr+LtNV7Zu/ld8QfzG+bMXad6wHbOdPahavQp+AZ5UqVIZZ4fZtGjcjovnL8m7RIWRmJiI2QxL2rXoxL27DzCcoY+x6XQePnhE+5b/YGJgJn7h/saVS1dp1aQDDrYuVKxUHr8AT2rWrI6Hmw9NG7ThzKlz8i5RYSQmJmJtbk+rph25cf0WetMmYWYxgxfPX9KpXXemT50hRgR849aN27Rt0QkLM1tKlymN7zxP6jWoi79PAE3qteLokePyLlFhSCQSHO1cadGoHZcuXmHC5LFY2s7iTdBbuv7dmykTpotRct+4f/c+HVp3wdTInKLFiuIz14MmTRqxIGAJjeu25MC+Q/IuUWFIJBLcXTxp0qA1Z06dY/S4Edg5WvHx40d6dh3A+FGTiQiPlHeZCuPTpxCszO3p2aU/YaHh7Nu3j169esm7LEEQ5ExJmo6fxcLDw9HV1SUsLAwdHZ3sqEsQhJ94+fIlZmZmbNy4kbr1amPjYEGDhvXlXZbcvH/3Ab1Jhly/doPCRQpjZTuLnr27oaSkhEQiYee/e3B1dCckJJT6DesSuNCPIkWLyLtsuVmzaj3uLl5ERUXRs3d3ZlmZULJkCQDevX3PHDdv/t22kzx58jDT3IjR40bKuWL5+fjxE/qTjbhy6Sr58+tiaWtGn369UFZWRiqVsnf3fpwdZvPhfTC169Zi/mJ/SpQoLu+y5Wbzxm0427sRERFJl26dsLA2o8xfpYHkkUwe7r5s3bQdTU1NDGfoM2nqeDlXLD+fQz8zbaox589eJJ9OPswtTRgwuB8qKipIpVIOHTiCo50bb9+8pXqNasxf5EeZsmXkXbbc7Ni+GzsrJ8LDw+nYqT1WtrMoV74skHyh6+3hx4a1m9HQ0EBv+iSmGU6Vc8XyExEeiaH+DE6dPEuePFrMtJjBkGEDUVVVRSqVcuzoCRxsXHj18jVVqlZm/hJ/ypcvJ++y5Wbf3oNYmdnx+fNnWrdtia2DJRUrVQCSz1M/7wBWr1yHmpoaEyaPxdh0OsrKf+bv8/Hx8axeuY65PoEoKSnj4OCAnp4eampq8i5NEIQs8jt9QaJzSRBysFOnTmFoaMi1a9fo068nZhYmFC9RTN5lZZvExERsLBzYtmUHAFOnTWLS1HHkyZPnh3WjoqJYGLiEBYFLUEKJgYP7Ye9sjaqqanaXLTfXrt3AYOoMgl6/oUbNatg729CocYPU171yHTsbZ27fvEPJkiXwC/CkYRrr5kYSiQQHGxc2rN+MVCJl4pRxTJ02ibx5tX9YNyYmhsULlhE4dxESiYTe/XriNsfxj2pbt2/dZdoUI16+eEXlKpVwcLahWYsmqa5788Zt7G2cuX71BsWKFcXL350WLZtlc8XyI5FIcHPyYPXKdSQmJTJuwmimGU5FRyffD+vGxcaxbMkq/H0DSEpMoluPzszxdkVdXV0OlcvHgweP0J9kyNMnz6hQoTx2zla0btMy1XXv3b2PvbUzly5eoXCRQnj6utGmbetsrlh+JBIJXnP8WLZ4JQkJCYwaMxwDYz3yF8j/w7rx8fGsWr4WX6+5xMXH0+mfjnj6uqX6+ZlbPX3yDL1JBjx88Ji/ypbBztGK9h3bprruwwePcLRz5ezp8xQoWAA3Dyf+6dwxmyuWr+NHT+Li4M6zZ8+ZOHEiTk5OFCny5/5QJwh/CtG5JAh/kKSkJFasWIGlpSURkRFM1Z/IhElj0dTSlHdpWWrD2k24Os0hMjKK7j27YG5lSqnSpX653auXr3FznsP+vYfImy8vNnbmDBzSPxsqlp+QkBCmTTbm4oXL6OrqYG49k/4D+/zyl1eJRMK/23bi5uRBaOhnGjZuQMBCXwoXLpRNlcvHti07cLB1ISI8gk6dO2JlO4u/0jFi5M2bt7i7eLFrxx60tbWZZWXCiFFDs6Fi+QkPC2e63gzOnDpH3nx5MbOYweChA1BRUfnpdlKplN079+Ls4M7H4I/Uq1+HwEX+FCteNJsql4/du/ZhY+FA2Ocw2nVog7WdORUqlv/ldh/ef8Bjtg9bN/+LVh4tZpgaMn7S6GyoWH4iI6MwmmbKiWOn0NLSwnSWEcNGDv5lp61UKmX/3kM427vx7t17atauQeAif0qXLplNlcvHwQNHsJhpQ2hIKC1bN8fWwZLKVSr9cruPHz/hNcePTeu3oKmpwTSjqUzVn5QNFctPdHQ0JobmHD54FA0NdYxMDRg1ZtgvO22lUilHDh3D0c6VoNdvqFqtCvMX+1G2XNlsqlw+nj55houDO8eOnqBdu3b4+flRp04deZclCEI2EZ1LgvAHCgsLw9nZGT8/P4oVK4q59Uy6dv8HJSUleZeWqW5ev8X0qca8ehVEtepVsXe2pknTRr+9nwvnLmJn7czDB4/4q2wZ5i3wpVbtGllQsfxIJBKc7d1Yt2YjEomU8ZPGoDd9Mvny5f2t/URGRjF/3iIWL1iGkpISg4cNxN7JKtfdFnD/7n30Jhvx/NkLKlWqgL2LjUwjai5fuoq9tRN379ynVOmS+AV45rrbViUSCR5u3ixftprEhETGjB+JgZEeOrq/9x0hJiaGhYFLmT8vORi9b/9eOM+2z3Wjvh4/esLUiQY8efyUcuXLYudoRdv2vz+i5sb1W9hZO3Hz+i2KFS+G3zwPmjRrnAUVy49EIsHXex6LFywjIT6BEaOGYmiiT4ECBX5rP7ExsSxdvIJ5fvNJSpLQs1dX3Dydc92orxfPXzBlggEPHzyiVOmS2DlZ0aFju9/+7L9z+y721s5cuXyNIkUL4+kzm9ZtUx8hlpMF+C8gwH8hcXFxDB42gBkzDX/7B5O4uHhWLluNn3cACQnx/NOlE56+bmhq5q4f9cLDwpnrN5+Vy9ZQunQpvLy86du3b677XikIws+JziVB+IM9evQIE5MZ7Nq1m6bNm2Bjb06NmtXlXVaGfZtPoqOrwyxLEwYM6vvLERI/k5SUxKb1W3F38yIyIpKWrZszN9D7ty+QFdGO7buws3JONZ9EVi9fvMLVaQ4H9x8mn04+7Byt6DegdyZVLD//zyc5g7a2Nqbmxin5JLKSSCRs3fwvs509CQsLo3HTRgQs9KFgwYKZWLl87Nt7EKtZdnwO/Uybtq2wcbBIySeRVVDQG2a7eLJn5z6082pjaTOTocMHZ1LF8hMZGcUMAzOOHTmBpqYmM2YaMGL00Azlk0ilUnZs342r0xxCPoVQv0FdAhfljhy5o4ePY2ZiRcinEJq1aIqdoyVVq1XJ0D5za45cbGwspkYWHNx/CDU1dYxMpjFq7Ag0NGTvPPshR65OLeYvyR05cqdOnMHEyJyPwR9p1LgBdk5W1KyVsR+UcmuO3NfvRl5z/IiLi8PKygpjY+Nc13kmCEL6iM4lQRA4cOAAxsbG3L9/nyHDBjLDzJBChXLeha1EIsHVyYM1K9eRlJTEuAmj0Teckmo+iazCw8Lx9w1kxdLVqKmpMmrsCGZZmuTIkTn37z9Ef5Ihz54+/2U+iazOnjmPvbUzjx89oWy5vwhY4EuNWjmvA/N38klkFRERSeDchSxdtAJlZSWGjhiMjb1FjmxbT588Y+pEAx49/HU+iawuXriMvbUz9+89oHSZUswN9KFu/dqZ+hzZxd8nkAUBi4mLi2PYiMEYzzSgYMHfG33zM9HR0SwMSM6RAxgwsA8OrrY5ctTXqxevmDLRgPv3HlCiZAnsHC35+58OmTpC4tscuRIli+Mf4JVjc+QWBC5hrk8gsbGxDBjcD9NZRhQpUjjT9h8bE8vihcsI8F+IRCKhV98euLo75MhRX0FBb9GfaMCtW3coVqwo1vYWmT6q+9bNO9hbO3EtF+TIXTh3EUc7N+7dvc+oUaNwc3OjZMncfUupIAg/JzqXBEEAICEhgfnz52NnZ4dEksR0Yz1Gjv51roCi2L1zb3I+SVg47Tu0wcrenAoVfp1PIqsnj5/ibD+bE8dPkT+/Ls6zHejWo3OWPV9mioyMwkjfhBPHT/9WPomsEhMT2bBuM56zfYiKiqJV6xb4B/qQT+f3brmTlwP7DmE5y+6380lk9fzZC1wc3Tly6Bg6Ovmwc7Kmb/+cMW3zd/kkmhoYm07P0veRpKQktmzajrurF+Fh4TRt3piABb6Z2umXlU4cO8VMYws+fvxE02aNsXW0onqNqln2fK9fBeHmPId9ew6SN29erO1mMWjogCx7vswUGxuL2Qwr9u89iKqqKgbGeoydMDpDo29+5occuUb1CVjkl2Ny5M6cOoeJ0Sw+vA+mQcN62DtbU6t2zSx7vu9z5PJgZmnCyNHDsuz5MlN8fDyWs+zYuX03KirK6BtMydI8yv/myNWtV5v5i+fmmBy516+CmO3iyd7d+2nStAn+fv40bdpU3mUJgqAAROeSIAjf+fjxIzY2NixatIhy5cpiZTcr00ccZKZv80nKVyiHnaMVbdq1yrbnP3bkBI52rrx4/pJKVSqyYPHcdIXuykNm5ZPIKuxzGH4+AaxavhY1NTXGThiF6SwjhR2Zk1n5JLI6feos9tbOPH3yjPIVyhGwyI9qGbztJytlRj6JrMLDIwjwW8CyJStRUVFhxOihWNqYKWzbev0qiKkTDbh75x7FixfDxsGCzl07ZVvb+i5H7q/SzFvop9A5cosXLsPXax4x0TEMGNQX01lGFC2WPRfiUVFRzJ+3mEULlqKEEoOG9MfBxUZh29b7dx+YOnE6N67fokjRwljbmdO9Z9dsa1tXLl/D3tqJO7fv5YgcudUr1zHH1YuoqGh69enBLEsTSpTMnlv7YmJiWDR/GfPnLUIqlSp8jlx0dDQLAhazeMFyChYsiLu7O8OHD1fYc0EQhOwnOpcEQUjVrVu3MDQ05NixY7Rr3wYru1kZzkrJTMn5JDM5duQkmlqamMw0ZPioIRnKJ5FVfHw8q1euw8dzLnGxcXTs1B5vf3eFmqb5yKFjzDK1IuRTaKblk8jq0cPHONm5cfrUWQoUyI/rHEc6d+0kl1pSExsbi4mhOQcPHEZDXR3DGdMYPW6EXEbxJSYmsm7NRrzcfYmOjqFN25b4zvNSqFFfJ0+cwtTIko/BH2ncpCF2TlZyy2579vQ5zg6zOXbkBDq6Oji72dGjVze51JKa+Ph4ZplYs2fXPlRUVZhupMf4CaPR0NTI9lqSkpLYvGEr7q5eRERE0qJVM+bN91GoHLnzZy9ibDCT9+8+ULd+HeydrKlbTz63Pn6XI5cvHzYOFgwY1FcutaQmMTERy1l27Ni2EyUlZaZOm8SkqePQ0tLK9lokEgnbtuxgtrMHnz+H0ahJQwIX+SpUjtzVK9cw0DPhTdBbatWugb2ztdw6wf6bI2dhPZNhIxQnR+5rdtscN29CQ0IxNTXF3NycvHkV53NIEATFIDqXBEFIk1Qq5d9//8XEZAavXr1m5JhhGBrry/3iw897HgsDlxAXF58l+SSy+vQpBG8PPzas3YyGhgZ60ycxzXCqXGv6Np+kZKmS2DpYZHo+iSykUinHjp7AwcaFVy9fU7VqZQKX+FO+fDm51vVtPsnAwf0wyeR8Ell9Dv2Mn3cAq1euQ01NjYlTxmJkMl2uvxgHBb1Fb6IBt2/doVjxoljbZX4+iaxOHj+Ng61Lcp5YxfIELvanShbeypgeyxavxNvDj+joGPr274WZhYlC3AbzdZan5UtWoaqqyqixwzG3MpVr23r/7gN6kw25fvUGhYsUwtJmFr36dFeItnXuzAXsrJ0UKkdu3ZqNuDnNISoqmh69umFubUrJkiXkWhMk/wgUOHchSxYuT86RGz4IGwdLubatkJAQ9CYZcfniFfLn18XCxoy+/XspxOibSxevYG/tzL279ylduhRz58s/R+7GtZs42rlx7ep1+vfvj4eHB+XLK+bobEEQ5E90LgmC8EuxsbH4+vri7OyMhqYGM2YaMHjogAzNviaLY0dOYGZixacv+SR2TtZUq654twndvXMPBxsXLl28QuEihfD0daNN29+fSjwj/ptPYjhDnzHjR2VZPoms4uPjWbV8Lb5ec4mLj+efzh3x9J2d7b+2Z3c+iawePniEg60L585coGDBAsz2dObvfzpkaw3x8fFYmtmy89892ZJPIquEhATWrd6I5xxfYmNiadehDT5zPcibVztb67h08QqG+qa8e/uO2nVr4eBkTb0GdbO1hvR4+uQZTvazOXHsJLr5dXGRQ45cYmIitpaObN38LwBT9CcyWW+8Qo0CheQ6N67fgoebN1FRUbRs1QL/QK9s/+HlxrVbTJ9qzOvXQVSvUQ17Z2saN2mYrTWkx4vnL3FxdOfwwaNyy5GTSCQ42bmybu0mpBIpEyaPRW/65Gx/P/iVpKSk5NlDXTzlmiP34f0HPGb7sHXzv9SpUxtfXz/at2+frTUIgpDziM4lQRDS7c2bN1haWrJy5Uqq16iGjb0FzVo0yfLnTc4nmc7dO/cpUaI4Ng4W/NPlb4X4FTstUqmUfXsO4uzgxvt3H6hVuwaBi+dSqlTW/5r833ySmebGCj/1eHDwR7zm+LF5w1Y0NTWYZjSVqfqTsvx53759h95EA27euC2XfBJZSKVSjhw6hoOtK2+C3lCtelUCF/lStlzZLH/ulcvX4jHbm+ioaHr37YmZxYxsyyeRVUhIKL6ec1m7egMaGupM1puA4YxpWf68Hz9+Qm+SAVcvX6dAwQJYWs+kd7+eCjFC4meOHz2Jg61LSo7c/EX+2XJL9MZ1m3FxdCcyMopuPTpjYT2TUqVLZfnzZsT3OXKqX3LkjLP8/3FISAjTphhz8fxldHR1MLcyZcCgvgrftk6fOouDtTNPvubILfSlWvWsC7D/avvWnTjYOBMeHkGnzh2xtDGjbLm/svx5MyIiIpIAv/ksXZy9OXJxsXEsW7KKwLkL0dTUxMXFhQkTJmT7j4mCIORMonNJEITfdvHiRQwMDbhw/gJduydfBJQuk/kXAfHx8ZiZWLF3136555PIKjYmlqWLVzDPbz5JSRJ69e6Oq4djluT3nD97EePpM3n//gP1GtTF3smaOnVrZfrzZKU7t+9ib+3MlcvXKFK0CN5+7rRs3TzTn+e/+SR60ycxcYp88klkFRcXz8plq/HznkdCQgKdu/6Dh48rmpqZP4JIkfJJZHX/3kMcbF24cO4ihQoVZI63a5ZMVpCYmIi9tTObN25DipTJU8czRX8i2tqKNULiZxISEli9ch3eHv5ZniN368Ztpk015tXL11SrXhV7JyuaNGuc6c+TlR4/eoKjrWuW58hJJBJcHN1Zu2oDSUlJjJ84Gn3DqeTLl3OybxITE1m/dhOes32yPEfu/t376E825tmz51SsVAF7Z2tatsr8z5Os9N8cOUcXG3r16ZHpzyOVSjm4/zBuzh68CXrLtGnTsLW1zbYJPwRByB1E55IgCDKRSCSsX78eMzMzPn36xITJYzL1AurbfJJ+A3oz03yGQuSTyOrd2/e4u3qxY/su8uTJw0xzI0aPG5kp+/5vPomVrTk9e3dT6NE3PyOVStm7ez/ODrP58D6YOnVrEbjYnxIlMmeEzNrVG5jt7KFw+SSyCv4QjIe7L1s3bUdTUxNDk2lMmjIuU/b96dMn9CcZcfnSVYXLJ5GFVCrl0IEjONq68vbtO6rXrMaCRf6U/qt0pux/88ZtONu7ERERSeeunbC0MaNMJu1bHrIyR+5z6Gem683g3JkL5NPJh7mlCQMG98uxIySyOkdu57+7sbVyIjwsnA5/t8PKdhblK2TOvuUhK3PkIsIjMZxmwqkTZ8iTRwtTc2OGDh+ksLOwpcepE2ewt3HOkhy5+/ce4mzvxtkz5+ncpTO+Pr5Uq1YtU/YtCMKfRXQuCYKQIZGRkbi7u+Ph4UH+AvmZZTGDXn17yPwF8dt8kjp1a+PgbE3d+nUyuWr5uXblOnY2zty+eYeSJUvgF+BJw8YNZNpXYmIiNhYObNuyA1DcfBJZxcTEsHjBMgLnLkIqldCrb0/c5jjKfIFw7doNDKbOIOj1G2rUrIa9sw2NZDz2iujmjdvY2zhz/eoNihUris9cD5lvW5VIJDjYurJhXXI+ycQp45g6bZLC5ZPI6uutH/6+ASQlJtGtZxfmeLnIPKLw9q27TJ9qzIvnL6lcpRIOzjbZcstwdrl39z72Ni5cunA5wzlyEokENycPVq9cR1JSEmMnjGKa4VR0dPJlctXy8d8cuU7/dMTT103m9+WHDx+jN9GAp19uJbN3tqZ1m5aZXLX8PHzwCEc7V86ePk+BggWY7eFEp84dZdqXRCLB28OfpYtWkJCQwKgxwzEw1sv2vKKsktk5ciEhofh6zWXd6o1UqlQRHx9funVTnNk1BUHIeUTnkiAImeLZs2eYmZmxZcsW6jeoh62DxW91CgV/CEZvsiHXrtygYMECWNomzw6UU0dI/IxEIuHfbTtxc/IgNPQzDRs3IGChL4ULF0r3Pjau24yzoztRkVF079kFcytThc8nkdWbN29xd/Fi1449aGtrM8vKhBGjhqZ7+2/zSXR1dTC3nkn/gX1yZduSSqXs3rkXZ4fZfAz+RL36dQhc5P9bo/62bdmBo61LSj6Jle0s/ipbJgurlp/37z7gMdubbVt2oJVHC5OZhoybODrd24eHhTNdbwZnTp0jb768mFnMkMtkB9lBKpWyf+8hnO3dePfuvUw5cnt27cPawoGwz2G069AGa3tzKlTInTNPffz4Ca85fmxav0WmHLnIyCiMp5ly/NgptLS0MJ1lxLCRg3P06Ju0fM2Rc7RzJej1G6pWq8L8xX6/lSN38MARLGbaEBoSSsvWzbF1sKSynGeIzCqhoaH4es5jzar1MuXIJSQksHbVBvy85yGVgp2dHdOmTcuS2/UFQfiziM4lQRAy1YkTJzA0NODGjZvpup3tv/kkU/QmMFlvQo7KJ5FVZGQU8+ctYvGCZSgpKzF46EDsnax+2unxQz6JszVNmjbKxqrl5/Klq9hbO3H3zn1KlS6JX6AXDRrUS3N9iUSCs8Ns1q3eiEQiYfykMehNn5yj8klkFRMTw8LApcyftwiAfgN64+Rm99ML0/t376M32ZjnX/JJHFxsaNGyWXaVLFc3rt3EzsaZm9dvUbxEMXznevw090cikeDh5s3yZatJTEhkzPiRGBjpZftsYfLw3xy5nr264ubp/NML08ePnqA3yZDHj55QrnxZ7BytaNs+e2fQlJfvc+QK4+XrTqs2LdJcXyKR4Oc9j0XzlxEfH8+IUUMxMp32R2Tf/D9HLoCEhHj+6doJTx+3n+bIvXj+gqkTDXlw/yGlSpfEzsmKDh3b5djbwn/Hf3Pk3L1d6NCx3U+3OXn8NM4Os3ny+Cnjx4/HxcWFokVzbuSAIAiKRXQuCYKQ6ZKSkli6dClWVlZER0ejZzA51SDub/NJunTrhIV1zs4nkdXLF69wdZrDwf2HyaeTDztHK/oN6P3dOp9DPzNtqjHnz17MFfkkspJIJMnTNDt7EhYWRpOmjZi30IeCBQt+t96O7buws3ImPDycjp3aY2U7i3Lls342NUUTFPSG2S6e7Nm5D+282ljazGTo8MHfrRMRHomh/gxOnTyLtnYeTM2NGTJsYK4cIfEzEomEnf/uwdXRnZCQUOo3rEvgQr8fZlrct/cgVmZ2fP78mTZtW2HjYJEts6kpmndv3zPHzZt/t+1MM0cuMjKKGQZmHDtyAk1NTWbMNGDE6KGoqanJqWr5+G+OXO06tZi/5MccuaOHjzPLxIpPn0Jo1qIptg6WVKteRU5Vy88POXIz9Jk0dfx368TGxmJqZMHB/YdQU1PHyGQao8aOQEPjzxp9k5IjZ+fG2zdvqV6zGvMX+lHmP6NNnz19joujO0cPH6dNm9b4+vpRv37OmpRBEATFJzqXBEHIMp8/f8bR0ZG5c+dSomRxLKxn0rlrJ+7cvse0KUa8fPGKKlUr4+BsTdPmuSefRFZnz5zH3to55df9gAU+VK1e9bt8knETRqNvOCXX5JPIKiIiksC5C1m6aAXKykoMHTEYG3sLHj16gv4kQ54+eUaFCuWxc7bKVfkksrp44TL21s7cv/eA0mVKM2++N7Xq1MTbw4+li1bmynwSWUVFRbEwcAkLApeghBIDB/fD3tmaly9eMXWiAY8ePuavsmWwc7TKktnmcppvc+RKlCyB/5ccOX+fQBYELCYuLo5hIwZjPNOAggVz/+ibn4mNiWXxwmUE+C9EIpHQu28PXOc48u7NO6ZMMuD+3QeUKFkCO0dL/v6nwx8x+uZnbt28g721E9e+5Mh5+8+hecumLJy/BH/vQGJjYxkwuB+ms4woUqSwvMuVq7i4eJYvWYm/TyCJiYl069GZOd6uxMbGEeC3gBXLVlOiRAk8PT0ZMGDAH9+2BEHIGqJzSRCELHf//n2MZxizf99+SpQswft378mbLy+zLEwYNLT/Hzf65mcSExPZsG4znrN9iIyMRF1dndjYONp3aINVLs4nkdXzZy9wcXTnyKFjqGuok5SYlOvzSWSVlJTElk3bcXf1IuxzGBoaGsTGxub6fBJZvX4VhJvzHPbtOYi6ujpJSUloaKhjPNOAkaOHiXySb3ybIxcSEoqmpgYxMbE0bdYYW0crqteoKu8SFcq3OXLq6upIJEmoqqphYKzH2Amj/7jRNz/z/xw5d4I/BKOpqUlsbCwNGtbD3tmaWrVryrtEhfLh/Qc8ZvuwdfO/aOXRQl1NjYSERCwsLDAxMUFLS0veJQqCkIuJziVBELLN3r176dWrFx07tWeOl8sfkU8iq7DPYQzuP5Inj5+wZMWCPyafRFanT51l7IhJtGnXCk9ftz8in0RW4eERjBwylls377B4ReAfk08iqwvnLjJy6HiaNmuMzzyP3wre/9NERUUxZvhErly+xrwFPnTt3lm0rZ+4cvkawwaOpm79Osyb703RYiL7Ji0xMTFMGqvPmdPn8PR1o2//3qJt/cSN67cYO3ISRYsU5ciRI5Qu/edFDgiCkP1+py8o902rIwhCturWrRvq6uo0a95EdCz9gm5+Xf4qWwY1NXXRsZQOrVq3QElZicZNGoqOpV/Q0clH+YrlUVZWpuPf7cUF2i80bd4EZRVlGjSqLzqWfkFbWztlBJy4revXGjaqj6qqKvXr1xUdS7+gpaVFterJI+D+/qejaFu/ULdebUqWKkGnTp1Ex5IgCApJdC4JgiAIgiAIgiAIgiAIMhOdS4IgCIIgCIIgCIIgCILMROeSIAiCIAiCIAiCIAiCIDPRuSQIgiAIgiAIgiAIgiDITHQuCYIgCIIgCIIgCIIgCDITnUuCIAiCIAiCIAiCIAiCzETnkiAIgiAIgiAIgiAIgiAz0bkkCIIgCIIgCIIgCIIgyEx0LgmCIAiCIAiCIAiCIAgyU5V3AYIgCAAxMTFcOHeJ27fucPvWXW7fusOboLcAGBjrY2QyLc1t3719z6GDRzh/9iJ3b9/j3bv3ABQpWph6DeoyZNhAWrRsluq2r18F0ab53+mus/+gvnh4u/7GK5OP0NBQDh88xtnT57lz+y5Br9+QlJRIwYIFqV23Fv0G9KZz104/3UdkZBRLFi5n/96DvH4VhLKKMuUrlKNnr26MGjscdXX1bHo12ePUyTNsXLeF69du8PHjJ5RQomixItRvUI+hwwfStHmTH7bJSLtVVFnxmqzM7Vm/ZiMApUqX5NT5I6mul5FzWVHdvnWHI4eOc/vWHZ49fU7IpxAiI6PIm1ebipUq0K5DG4aPHEL+Avl/2NbXax7+PgG/fI6jp/ZTrnzZLKhePi5euMzqFWu5cukaISEh5MuXj2o1qjJwcH969en+y+2DPwSzeuU6jh89yauXQcTGxlKocEEqVapI0+ZNmDB5DGpqatnwSjImI+diRtrOlk3bMZthme46PXzc6D+wT7rXl4f0vqZV65fSqnWLVJe9eP6SRfOXcurkGT58CCavtjY1a9dgyLBBdO3+T2aXLAiCkOOIziVBEBTCjWu3GDdq8m9v9+bNW1o37YhUKk15TEtLC6lUyutXQbx+FcTuHXsZOLgfrnMcUVFR+W57ZRVlChcp/NPniIuLIyI8AoA6dWv9do3y0LR+GxITE1P+raGhgaqqGu/evefdu/ccOnCEtu1bE7jIDy0trR+2D3odxNCBo3n9KghIPqbx8fHcunGbWzdus2P7LtZsWI5uft1se01ZRSqVYm3hkNL5AaCpqQnAq5evefXyNTv/3c24iaOxtjP/bltZ260iy+zXdO7MBTas3fTL9TJ6LiuqzRu2sXrlupR/a2hooKmpwefPYVy5fI0rl6+xfMkqFi0PoEHD+qnuQ01N7afnmqpq7vk65+7qxcLAJSn/1tHVITw8gjOnznHm1Dn27t7PvAU+ab7m3Tv3YjnLjsiISCD5eKupq/Em6C1vgt5y8sRpho8cjJqu4ncuZca5KEvb0dTU+OXnYmREJLGxsUDO+VwEUFZWpmChgmkuT+tHk2NHTjBtijExMTEA5M2Xl8+fwzh14gynTpxhwOB+uHs6o6SklCV1C4Ig5AS559uIIAg5nq6uLjVrV6dWrRrUrF0DZ4fZBH/4+NNtJEkSpFIpLVo1o9+A3rRs1YJixYsikUh48vgpnu6+HDpwhM0bt1GseFFmzDT8bvuSJUtw8dqpnz6HvbUzq1asRVNTk959emT4dWaHxMRE6tarQ/9BfWjTthV/lS0DJI/Umuc3n00btnLi2CmsZtnh7T/nh20njNHj9asgihYrgqfvbFq1boFEImHv7v1Ymtly5/Y9jA3MWLZqoTxeXqbasml7SsdS1+6dMZ1lRPkK5QB4+uQZ7q5eHDpwhGWLV9K4ScMfRnzJ0m4VXWa9ppiYGCzNbFFVVaVajarcunE7zXUzei4rqrr1a1O6zEwaNW5AxUoV0NHVASAqKooD+w7h5uTBp08hTB4/nSMn96Gjk++HfTRoWI/1W1Zld+nZbt2ajSkdSz16d8PCaiYlShYnLi6e3Tv3YmflxMH9h5nt4vlDRy/A3t37MZo2E4lEwtDhgxgzfiSVq1QCkkdi3r1zj4P7D6OqlnO+/mb0XJSl7fTo1Y0evbr9dJ0uHXvx8MEj6jeom3KMc4ISJYunOXIyLa9evmb61BnExMTQsHED3L2cqVChPFFRUSyav4y5voFs2biNihXLM1lvQhZVLgiCoPhyzqerIAi5WuOmDbl25/x3j81x8/7ldjq6Ouzct4VatWt+97iysjKVq1RiwZK5jBs5mRPHT7F8ySr0p09BQ1Mj3XXFxcaxY/tuALp065RyYajo1m5cQfOWTX94vHSZUsz2dEZFVZX1azby77ZdmJobU7JkiZR1tm7+lwf3HwIQuMgvZTSFsrIyPXp1QyKRYjTNlONHT3Lm9DlatmqePS8qi2zfsgOAsuX+wi/A87tf8itULM+8BT50atedly9esWf3/u86l2Rtt4osM1+Tp7svL168RN9gMu/evv9p51JWn8vy0m9An1Qf19bWpt+APhQpUoTRwyfw6eMnjh4+Tp9+PbO3QAWRmJiIr9c8AGrVroHvXA+UlZOjQTU01Ok/sA+xsbHYWDiwavlaRo0ZntJpDvDh/QesZtkjkUiwtJ3FhEljvtt/3rzaNGnaiCZNG2Xba8ooRX1/uX71Bg8fPAJg0NABcq4m6/l4+hMdHU2RooVZumJ+yvcAbW1tjE2n8zH4I+vXbiJg7kKGDBuYK0b0CoIgyEIEeguCoBBkvcVFRyffDxej31JSUmLgkH4AREVF8/jxk9/a//59hwgLCwNgcA76Ep1ax9K3Bg3pn/L3fy/4t235N3kfLZqmeptOz97dKPNXaeD/HTM52YcPwQBUr1Et1VtE1NTUqF6jGgDRUdHfLcspt2b9jsx6TdeuXGflsjWUr1COaQZTf7l+Vp/Liqpeg7opf797+06OlcjX7Zt3+BicPCJn/KSxKR1L3xoybCA6ujokJiby77ad3y1bsWwNYWFh1KxVnfETR2dLzVlNUd9fNm3YCoC2dh569Ooq52qyVnR0NPv3HgJg+Mghqf7ANHXapP+1d99RUVxtGMAfQAGxoEYxFozdmESNJZpYsJtgFwt2bNhQWASkCAKigIJS7BWjorHH3o299wJKUxRQbEivu/f7A+HTWKIrMAs+v3M8B5eZ2XeW2TLP3nkvgOxLBQ8d/LxRUURERQnDJSIq8rS0/j+6QS5XfNa6OR+ia9T87r0NnQurDz0mqampuHLpGgCgXYe2711XTU0NBu3bAMhugl3Y5QRlwUF33+pTlSMzMxPBQXcBAA0bFZ7eIlJKT8+ArbUjhBBwn+OaZyOMvuS5rKouXbyc+3P176pLWIm0oqNjcn+uW6/2e5fR0NBAzZo1AACnTp5963c5QXdvo17se5OPUlJSsGfXPgDZl8+VLFlS4ory1+WLV3N7S7XrYPDeZarpV0WdutnHbFF4TyQiUhYviyOiIu/8uYsAAE3N4rm9dD7Fw8hHOH/2AoC3R/oUBRdePyYA8H2Derk/h4VGQKHIPmmvV7/uB9fP+d2zp8/xKu7Ve2e6KiyGjRiME/+cQuSDh7Aws4aNnWXu7EkR4fcx130eHkY+wnffVcfoIjIiIr8t8F2MsNBwGA/un6ehrLLPZVWTnp6BZ0+f4diR4/DxXgAg+7LMTl06vHf50JAw/NGpJx5GRkFdXR2VvtVDi5bNMcxkMH786YeCLL1AfCw4lCvkAJB7WRaQ3RMnNvYpAKBhwx9wNzgESxYux/lzFxD/Kh7ly5dHs1+awGT0cDT/pWn+Fq9i8vrY2bv7AJKSkgEUrtG8OV6+iEMvw36ICH8AuVwOvUoV0bRZExgP7o9fW737WvXmcVb/P94Tw0LDEXovLF/qJiIqDBguEVGR9uhhFDasy27W3L2nIUqXLvXJ627ZtA1CCBQrVkzlp1n+HAnxCViyaDmA7J4etWrXzP3d09cnaABQ6dtKH9zGt2/8Ljb2aaEOlzp16QBHFzvMdZ+H/XsPYv/eg7mzxaWlpaGMbhkMHTEIVjYWn3X8fK3u3A7C8iWrUKFiBdg72uTZdr/kuawqvq/dGBnpGe/c3uyXpvBd6AUtrffPVPXyZRxevYpHmTKlkZSUjPsRD3A/4gE2/7UNk6aMg9U0WT5Xnv+qVaua+3PIvVA0bPTuJZIZGRl4cD8SAJCYkIiUlBTo6OjgfsSD3GUuX76GBT6LkJGRCW1tbWhqaeHJk1js3X0A+/YchMxqMqbIJuX7/qiKvD52ckbz1qtf961LOguL1NRU3L4VBF1dXWRlZebOCLpzx270NzaC+xzXty6PzgktdXV1oV1C+4PbrfStHoC330OJiL42vCyOiIqstNQ0mE2QITU1FeXLl8M0e6tPXlcul2Pb5r8BAB06tUNFvYr5VGXBUigUmGphi6exz6ClpQUXN6e3fp/zjTQAlPjIB+k3P2QnJyd/cLnCYvRYEyxe4Y9vKnwDIDtUyrkUIjMjEynJKUh8PbU5fVhWVhZsrRyRlZUF55kOedYA/0uey6qkYsUKqFCxAnR0dHJv+61VSzi52KNq1SrvLF+j5newm26NIyf3ITj8Oq7ePo/bIVfwZ+BK/NToRwghsMh/GVYuCyjI3cgXPzb8ARUqVgAALFu88r2XqK4NCETSG8/DnJ9z+uIBgI+XP/Qq6WHtxlW4HXIFN4Mv4eCx3fj1txYQQsDHewEO7DuUz3sjvfw4dsLDInDl0lUAwMDBhWs0b6VKejC3NMPeQ38jOPwGrt05jzuh17Dl7w1o3TZ7Uoqtm7ZjlovnW+slv35P/Nj7YfbvS2QvXwTeD4mIlMVwiYiKpKysLMgmW+P2zTsoXrw4fBZ45X6z+ClOHD+FJ09iARS+D9EfM3OGO44dOQ4AcJ3thAY/1Je2IBWQmpqKKRMtMdZkIqpUrYw/N6zE5ZtncfnmWfy5YSXq1KuNHdt2oW+PgQgOuid1uSpt6aIVCLoTjI6d26N7z7xp9Pulz2VVcur8UVy8dgq3Q67g4vXTcHCahqA7d9G3x0D4ePm/s3wfo54YN3EMatWqieLFiwMANDU10bZda2zZHohGjRsCAPzmL0RCQmKB7kteK1asGKbIshu/h4WGY6zJRNy+dQcZGdmXEC5fsgpenj65jwMAqL1u+q1QiNzbhBBYvNwPbdq2ym0KXrdeHaxYsxgV9bLDK3+fxQW1W5LJj2Nn88bsUUuaWpro269X/hSeT9q2aw2Z1WQ0+KF+7ghBDQ0NNGveBH8GrkSX3zsBANav3fjWSDgiIvp0DJeIqMiRy+WwnGKDQwePolixYvBZ4IW27Vp/1jY2b9gKIPvyr/YfaOJZ2Li7zcXaNYEAAEcXu/f2kSpV6v/NWVNT0z64rbQ3flfYG7p6zPLC3t0HUKt2TWzeth5tDVqjfPlyKF++HNoatMamretQs1YNvHwZB2dHN6nLVVmhIWFY6LcEJUvqYKb7jDzZZl48l1VVhQrfYOz4UVizfjnU1NSwwG8Jjh7555PX19LWgrWdDED27HlnT5/Lp0oLznCTITAdPxoAcPLEafQy7I/vazVGy6YG8JztjarVqmDcxNG5y+u+Hhn35utWqza/vnfWwZIlS2K4yRAAwN3ge3j2ema6r5Eyx05mZia2b8tumt71904oV65cfpZYoNTV1XMv4VUoFDj6+gsYACj5+tj62Pth9u9Ts5cv5O+HRERfguESERUpcrkclubTsHf3AWhoaGC+/xx06/H7Z23j2bPnOHb0BACg38A+Kjsd9OfwnOWVe/mDg9M0jB77/sbUepX+PyIk9vXIrfd58sbvKlUqnKNIgOzLAP8K3AIg+8T2fbOaaZfQxoiRQwEAly9ewfPnLwq0xsLCebobMjIyMWnKBOjqlkFycvJb/7KyshsxCyFyb8vMzPzg9vLiuVwYNG7SKLfJdM6x+KmaNvs59+dHD6PysizJ2DvZYPOOQPQb2Bf16tdB5SqV0fjnRrCaZoE9B7dDXT379bhqtSrQ1MwegfLmSLY6dd4/0xyA3Bm9ACAmKuaDy30NPvfYOXr4H7x4/do3sBA28v4vNWp+h/LlswOzR5GPcm/PeX+Lj49/60uVf4t9kt1rSa8Qvx8SEX0pNvQmoiIjZ5TDnl37c09Ge/Tq9tnb2bF1J7KysqCmpoYBxoX/kjgPNy+sWLYaAGA33Rpjx4/64LJ16taCuro6FAoFQu6Fon3H94/ayplBp6JehULdzPt+xIPc3i7Vv9P/4HI5s8cBQNTDKFR43ZuJ/u/Ro+wTVC/P+fDynP/B5WKiH6Nh/eYAskfQvS/ozKvncmGR0zw/8sFDiStRDc1/afrBWd1u3bwNAGjarEnubXXr1oGGhgbkcvlHtyvEG/9RU/viOr8mOY289atXQ+s2v0lcTcF5c9bUe/dC0fjnhu9dLuc9sW79OgVSFxGRKuLIJSIqEuRyOWSTrd86Ge3Zu7tS28r5EP1rq5YfDRwKA3e3uW8FS+Mmjvno8iVKlECzX7JP2k4cP/3eZYQQOHXiDACgrUHhvkRJXf3/J5jR0R8eyfDmaKWSpXjZQ37Ky+dyYfHoYfZIic+9pOba1Ru5P1fTr5anNamiZ8+e517CZdS/d+7tWtpaaNEyO7AMCwv/4PphodnTxKupqaGaftUPLvc1+Jxj53HMk9zX/P4D+0KtCAZzkQ8e4uXLOADZAVqO5i2a5s4eevL4qfeuGx0VjbDQ7OOusL8nEhF9CYZLRFTo5Yxy2Lv7wOu+LHOVPhm9dPEKIsLvAwCMC/nQf3e3uW9dCvdfwVIOo/59AADnz17A9TdOQHLs23MAD19fNtD3jRO8wqh27Vq5Jw6bN2597wxVcrkcfwVuBpA9HXWt2jULtMbC4tT5o4iICv7gv34D+gDIvpwp57Z/j1rKy+eyKpDL5RBvDZd515nT53Dj+i0AQMvffsm9/b/WS0/PwLw5vgAAHR0dtG7z65cVq+Lkcjmc7FyQkZGJxj83gkH7Nm/9vv/AvgCAs6fP4/atO++sn5ycjPVrNwIAfm7SCN98Uz7/i5ZIXh8727bsgFwuh4aGBvoPNMqrMgvMfz0eQgh4zPICkN1/qWPn9rm/09HRwR/dugAAAtf99d7m50sXrwSQ3fur6+vG4EREXyOGS0SkMuJfxePly7jcfzkzAKWlpr51+5tT/eb0Zdmzaz+KFSsG34VeX3T5zOaN2Y28y5bVxe+GXb5shyT0Zo+l6c62H70U7t/6DeiD+t/XgxACk8ZZ4MzrkQIKhQL79hyA/bTsZs3tOrQt9JdHaJfQzg0Rb98KgunISbgbHAKFQgGFQoHgoHsYPWI8rly+BgAYNXb4Oz24lDluVZ0U+5TXz2VV8DjmCXr8boQN6zfhYeSjt05yY2IeY8nCFRg/ejKEEChbVhdjTP8ftl08fwnDBo3Cjq078TjmSe7tmZmZOHP6HIyNhuH6tZsAgCmyiSjzurl1YfYw8hG85/ji9q07SE9LB5D9unP50lWMGDIWhw4eRRndMvDycX9n9Exvo55o/HOjt163FAoFgOzZ58aNMsOzp8+hrq4OK1tZQe+a0pR5LublsSOEwJZN2wFkz7hWucq3+bGb+So6KgZ9ug9853moUChw7cp1jBo2DocOHAEADB428J0vECytzaGjo4Onsc9gOmpi7mxyKSkp8PdZhA3rNgEAzMwnQLesbsHtGBGRimHPJSJSGT3+MEL0e5qsLl+6GsuXrs79f78BfeDl4wEAuHLpKvbs3Acg+1IHF6fZcHGa/cH7mOFq/8ET1sTEJOzbcxAA0MeoV+50xYVNdHRM7uOlrq6OZYtXYdniVR9c3nT8KJhO+P8MTMWKFcOKgMUYMtAEUY+iMXzQaJQoUQIKhQLp6dknfD/+1AC+C7zyd0cKiK2DFR7cj8SJ46dy/2m+/ttnpGfkLtezd3eYmU94Z31ljltVJ8U+5eVzWZUEB92Fo50LAEBTszhKlSqFtLR0pKSk5C6jX70aFi/3Q0W9irm3CZE9Cufs6fMAAG1tbejolEBiYlJuI3R1dXVMMDPF+EljC26H8lFSUhIWL1iGxQuWAcgeKZiSkpK7v1WqVsbSlQveasydQ11dHctXL8SwQaMQGhKe+7pVrHgxJL4ebVK8eHG4znJEq9aFZ5SXMs/FvDx2zp45n9vwuzCP5r154xZu3sgeIaippYlSJUsiKTn5rdf4/sZGcJ45/Z119atXw4Il8zF5giUuXbiCTgaGKF2mNFKSU3L7fPU3Nvrk0cFEREUVwyUiKtRyvsUFsr+Vff4f00unvf42/H327NyXO51wYZ4NR7zxmCgUiv98TJKTU965rZp+Vew7vBMrlq7Gwf2HEfUoGsWLF0Pd+nXQq3d3jBg1NHempsJOu4Q2Vq9bhv17D2Hnjt24ffMOXrx4AaipvZ6pqiH6G/dFx07tpS61SMvL57Kq0KtUEQuX+uLCuYu4fv0mnj55iri4OKira6BK1cpo8MP36Ny1I3r36QHtEtpvrVu/QV04OE3D1SvXce9uCOJexiEhIRHaJbRRp25t/NKiGQYNHYjvG9STaO/yXrVqVTFFNgkXzl1E5IOHiIuLQ6lSJVGrTi38btgFQ4cbo0SJEh9cv6JeRezavx3r1gRiz679uH//AdLT0lBNvyp+a9USo01NUP/7ovN4fUheHjubN2b3IKxQsQI6demQ36XniwoVvoGLmyOuXrmO4KBgvHwRh/j4BGhpaUJfvxqaNvsZAwb1+2ATeQDo0Kkd9h3+G8sWr8TpU2fx9Okz6OqWwQ8/NcDgocYw7N61APeIiEg1qYn/uhAZQEJCAnR1dREfH48yZQr/sGsiyls6OjqwsbPEyDHDpS5F5Y0bbYbTJ88iKOya1KUUCvVqNsRUa3NMMDOVuhSVJ5tigz079yHs4bv9Zuhd39dujPETx8LSeorUpag8h2kz8NeGLbgbcaPIhMr56ce6TTFsxGDYO9lIXYrKm+06B6tWrMH1oIsoU6a01OWovB5/GKFDu45YuHCh1KUQ0Vfic7Ig9lwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiIiIiIiIiIiKlMVwiojxx/txFxL+Kl7oMlfYq7hUiIx8iMzMTx4+dlLoclXfq5BkIhcDFC5cRFxcndTkqLSEhERFhEVAoFDhy6BiEEFKXpNLOnbkAhUKBK5ev4vnzF1KXo9KSkpIRci8UAHDowBEeW//h8qWrkMuzcO3qdcQ+eSp1OSotJSUFwUF3AQCHDx7lsfUfbly7idjHsVKXQUT0QQyXiOiLubi44Ozp8+hoYIjAdX8hKytL6pJUSlZWFtauCURHA0PERD1GzZo1MXrEeIwZMQER4felLk/l3I94ANNRk2AyZCxq1KiBK5euoVNbQ6xZtQ6ZmZlSl6dS5HI5/grcjE5tDREedh9169bFuNFmMBk6NjcQoP979DAKE03NMdR4JPSr6eP2zSB0amuIlcsCkJGRIXV5KkWhUGDr5h3obGCIO7eDUa9ePZhPssKQgSMRdCdY6vJUTnR0DMzNrDCw71BUrlwF4WER6GRgiMULlyM9LV3q8lSKEAI7d+xB53bdcfnSVdT/vj5sLO1hbDQMN2/clro8lRP75CmsZXbo29MY1apVw/Dhw6UuiYjovRguEdEXmzZtGkJCQtC7V2842buil2F/nDtzQeqyVMKZ0+fQ43cjuDrNhlFfI4SHhyMkJATbtm3D/YgH+KNTL8xy9URCfILUpUouMTEJnrO88EenXggLicCWLVsQGhqKsLAwDBgwEG4uHujetS9OnTgjdakq4eL5S+jdbQAcbJ3RvXt3hIWF4d69e9i9ezeexDxF96594eI4C6/iXkldquSSk5PhPccXXTv0wO2bQQgMDER4eDgiIiJgYmKCOe7zYNi5N44e+YejJwBcvXINRj2NMW2qAzp27ISQkBDcu3cP+/fvR3xcAnoZ9sd0W2e8ePFS6lIll5qaCr/5i9ClfXdcOn8FAQEBiIiIQETEfYwfPx6+3gvQtWNPHNx/mMcWgJs3bmNg36GwnGKD1q1a4+7du7gbfBdHjx5FeloG+vYYiGlW0/Hs6TOpS5Vcelo6Fi9cjk4Ghjh5/AyWL1+OK1euomXLllKXRkT0XmriE97pEhISoKuri/j4eJQpU6Yg6iKiQurSpUuwsDDHuXPn8bthFzg4TYN+9WpSl1XgIh88hIebFw4dPILWrVvBz88fzZo1e2uZtLQ0+Pj4YPbs2dDS1oKVjQUGDu4HDQ0NiaqWhlwux9bNOzBvji9SUlJhb28PKysrlChR4q3lrl+/DgsLC5w8eRKdunSAg9M01KxVQ5qiJRQdFQ2PWd7Yt+cAfmnxCxb4L3jnZCMjIwP+/v6YOXMmNIppQGY1GUOGGaNYsWISVS0NhUKBndt3Y47HfCTEJ8DGxga2trYoWbLkW8vdvn0bMpkMR48ehUH7NnB0tkOdurUlqlo6j2OeYK7HfOzcsRtNmjSBn58f2rZt+9YymZmZWLJkCZydnaFQyDHFchKGmwyBpqamRFVLQwiBPbv2Yc7seXj+/AUsLS3h4ODwzufku3fvwnKqJQ7sP4BWrX+Fo4s9vm9QT6KqpfM09im85vhi2+YdaNjwJ/j5+aNDhw5vLZOVlYUVK1bAyckJ6enpMDMfj5FjRkBL6+s7tg7uPwyPWd54HPMY5ubmcHJyQtmyZaUujYi+Qp+TBTFcIqI8J4TAxo0bMW3aNDx//hxjxo3ExMmm75zQFUVJSclY5L8UASvXQk9PD15eXjA2NoaamtoH14mJiYG9vT3Wrl2LBj98jxmu9mj5W4sCrFo6ly5egZuzB27fuoOhQ4fC09MT1ap9OIwUQmDbtm2wtrZGTEwMRo4eDjOLCShTpnQBVi2NlJQULFu0EiuWrUa5cuUxZ84cDB06FOrqHx6EHBsbi+nTp2P16tWoW68OHF3s0KZtqwKsWjrXr97ATGcPXL92AwMGDMDcuXNRo0aNDy4vhMCuXbswdepUREZGYvjIIbCwNINuWd2CK1oiaalpWLFsNZYuXonSpUrD3d0dI0eO/GjQ/fz5czg5OWH58uWoWbMGpjvbon1HgwKsWjq3bt6Bm7M7Ll+6it69e8Pb2xt16tT56Dr79u3D1KmWCA0Nw+BhA2FpbY7y5csVUMXSSU/PQMDKP7HIfxm0tbUxa9YsjB079qNBd1xcHFxdXbFw4UJU068KB6dp6Ny140ffR4uK4KB7mOXigXNnL8CwmyF85vugfv36UpdFRF8xhktEpBKSk5MxZ84ceHl5oYxuGUyzt0Qfo14fPRkurBQKBbZv3QlvTx8kJibB1tYWNjY20NHR+eRtXLhwAeYW5rh44SK69fgDdtOtUU2/aj5WLZ3o6BjMcZ+HPTv3oXnz5vDz80OrVp8eeqSmpmLevHnw8PCAjk4JWNnK0H9g3yI56ksIgV1/78Uc93mIexkHa2tr2NnZoVSpUp+8jatXr8LCwhynT59Bl987wcFpGr6rUT0fq5ZO7JOnmOsxDzu27cLPPzeGn58/DAw+PfRIT0+Hr68vZs2aheKaxWFpPQWDhgwokqO+hBDYv/cgPGd5Izb2KWQyGRwdHT/rs97Nmzchk8nwzz//oEPHdpjubItatWvmY9XSefbsOebN8cWWTdvxww8/wNfXF507d/7k9TMyMrBo0SK4uroCELCYOhlDRwxC8eLF869oiQghcOTQMbi7zUV0VAwmT56MGTNmoFy5Tw/UgoKCILOU4fChw2jdthWcXOxQr37dfKxaOi9fxsHH2x8b129G3bp14OPjC0NDQ6nLIiJiuEREqiUyMhLTpk3D5s2b0bhJI8xwsUeTZj9LXVaeuXL5Gtyc3XHzxm0MGjQIc+bMQfXqyp24KxQKBAYGwtbWFi9fvoTphFGYYGb6WSGVKktNTcWyxauwfOkqlNUtC09PTwwfPlzpwDEqKgp2dnYIDAzETw1/hJOrPX5p0ey/Vywkbly/hVkuHrhy+Rr69esHLy8v1Kyp3Im7EAKbN2+GjY0NYmNjMWrsCJiZT0CpUkVjRGF6WjpWrliDJQuWQ0dHB+7u7hg9erTSgePjx4/h4OCANWvW4PsG9eHoYodWrX/N46qlE3QnGDOdPXDx/CX07NkD8+bNR926yp24CyGwY8cOWFlNRVRUNEaMGgpz2SSU0S0anxnT0zPw5+p1WOi3FJqampg5cybGjx+vdOD49OlTODo6YuXKlahdpxYcne1g0L5NHlctnXt3QzDLxRNnTp9D19+7wtfHFw0aNFBqW0II7N27F5aWlrh//z6GDh8EmdVklC1XNm+LlkhmZibW/7kR/j6LAKjBxcUFZmZmRTJwJKLC6XOyoKI3fICIVM53332HTZs24cSJE1ATaujXezCsLGzxpJBPqfs45glkk20woM8QFNPQxKlTp7Bx40algyUAUFdXx/DhwxESEgJra2usWBqAzu264+/tuwt1M1ghBHbv3Isu7bpj6aIVkFnIEBISAhMTky8ayVatWjWsX78eZ8+ehbZ2CRgbDYP5pKmIjo7Jw+oL3tPYp7CZ6oC+PQYiMyMLx44dw9atW5UOlgBATU0NxsbGuHv3LhwcHLA2IBCdDQyxdfMOKBSKPKy+YGWPvjmErh16wG/eQkyYMAGhoaEwNTX9opFslStXRkBAAC5evIhyZcthmPEoTDQ1x8PIR3lYfcF7/vwFHKbNQM8/+iExPgkHDhzArl27lQ6WgOxjy8jICMHBdzFz5kxs2rAVHQ0MsXH9Zsjl8jysvmAJIXD08D8w7NwLXp4+GDVqFEJDQ2FmZvZFI9n09PSwfPlyXL16FVWrVMPIYaYYO3IiIiIK9+yhcXFxcJ7uhu5d++Jp7DPs2bMHB/YfUDpYArKPrR49euDOnTvw9PTE39t3o6OBIdauCSz0M9OePH4a3br0weyZc2BsPAihoaGQyWQMloio0OLIJSIqUHK5HKtXr8b06dORnJyMiVPGYazpSGhpa0ld2if7d38SDw8PmJiY5MslWffv34eNjQ22bduGps2awMnVHo1/bpjn95Of3uxP0qdPH3h7e6N27bxvlqxQKLBu3TrY2dnhVfwrjJswBuMnjXmnMbgqU6Y/ibIePXoEW1tbbNy4EY0a/wQnVwc0a94kz+8nPwUH3YObszvOn7uIbt27Yf68+fnSn+TffeRGm5pg4uRxhWrUV0ZGBtau2YAFPouhoaGBmTNnYsKECflyIlsU+siFhoRhlqsnTp04g06dO8HP1w8//vhjnt9PUegjl5mZiQ3rNsF3/kIIhcCMGTMwZcqUfGnyXhT6yEVE3If7zLk4duQ42rVrBz8/PzRu3FjqsoiI3osjl4hIZWloaMDU1BQhISGYMGEC/OYtRNcOPbB/7yGVH5kjhMC+PQfQpX13LPRbislmkxEaGvpFl978l5o1a2Lr1q04duwYsjKz0LfHQNhY2uNp7NN8ub+89OzpM9haTUef7gOQmpKOw4cPY8eOHfkSLAHZo75MTEwQEhICmYUMSxetQOd23bB7595CcWwdOnAEv3fsgfle/jA1NUVoaCgmTJiQb71+9PX1sWHDBpw6dQrFNDQxoM8QyCbb4HHMk3y5v7z04sVLONq7oOcfRoh7+Qr79u3D3j17863xrZqaGoYMGYJ79+7B1tYWASvXonO7bti+9e9CMerrn6Mn0K1zH3jO8sLw4cMRGhqKKVOm5NsIiSpVquDPP//E+fPnUaZ0GQweYAKz8TJEPYrOl/vLS6/iXsHVaTa6demDmKgn2LlzJw4fOpwvwRKQfWz1798fwcHBmDFjBgLX/YXOBobYtGFLoRj1derkGfT43Qgznd0xoP8AhIaGwsrKKt9mD6xUqRJWrlyJy5cvQ6+iHkYMHoPxYybjwf3IfLm/vJSQkAh3t7kw7NQb4aH3sXXrVvzzzz8MloioyODIJSKS1L1792BlNRV79+7Dr7+1gJOrPRr88L3UZb3jzu0gzHT2wKULl7+4P4my5HI5Vq5cienTpyMtLQ2TpozH6LEjVG7U17/7k7i5uWHcuHEF3hA5PDwcNjY22LFjB5r/0hROrg5o2Ch/ThC/RF72J1GWQqHAmjVr4ODggITEBIyfOAamE0ar3KgvVelPUlj6yIWHRWCWiydOHD+Fjh07wtfXFw0bFuzIx5w+cnZ2dnjx4oXK9pHLysrCxsDN8PFeAHmWHE5OTjA3N4eWVsG+vkZFRcHe3h7r16/Hjz/9ACdXe7Ro2bxAa/gUD+5Hwt1tLo4cOoa2bdvAz88fTZoU7MjHf/eRGzlmOMzMJ6B06U+f7KAgyOVybN20Hd5z/JCamgoHBwdMnTpV5V5fiYjehw29iajQ2b9/PywtZQgNDYPxkAGYamOOb74pL3VZeP78BebP9cOmjVvRoEED+Pj4oGvXrpLWFBcXh5kzZ2LhwoWoUrUy7B1t0PWPzpJP0yyEwLEjxzF75hw8ehiFSZMmwcXFBeXLS/t3PHr0KGQyC9y5E4T+A/vC2laGinoVJa0JyP47+novROC6v1C7di34+PiiW7dukv4dExISMHv2bPj4+EBPryLsHK3Rrccfkh9bAHDin1OY5eqJ+xEPMHbsWMyaNQsVK0r7dzx58iRkMhmuXbuGPkY9Mc3eCt9WriRpTQAQ/yoe/r6LsW7NBujr62P+/Pno3bu3pH/HpKQkeHp6wtvbG+XKl8M0O0v06ttDJWYPPXP6HGa5eCLkXihGjhwJd3d3fPvtt5LWdO7cOZhbmOPypcvo0csQttOtUbVqFUlrAoDExCQs8l+KgJVrUblyZXh5eWHAgAGSHlspKSnw9vaGp6cnSpUqCWs7S/Qb0Ecljq2L5y9hprMHgu4EY/jw4fDw8EDVqkVzFlgiKpoYLhFRoZSZmYlFixbBxcUFQihgPtUMw02GSNLcMiMjA2sDArHAd0m+9ydR1t27dyGzlOHggYNo1fpXOLrY4/sG9SSpJeReKGa5euL0ybPo3KUzfH188+0yEmVkZWVh+fLlcHJyQkZGBszMx2PkmBHQ0sqfSzc+5t/9SZydnTF58uR8u4xEGaGhobC2tsauXbvwS8vmmOFqjx9/+kGSWiIi7sPddQ6OHT2B9u3bw9fXV6UuI5HL5QgICICDgwOSkpMw0cwUY8eNgnYJbUlq2bRxK+Z7+SM9LR2Ojo6QyWTQ1i74Wj7kzT5yTZr+jBmu9mjcpJEktUQ+eAgPNy8cOngErVr9Bj8/fzRvrjqjhN7qI/cqDqav+8hJMepLoVBg6+YdmDfHF0lJybC3t4e1tbVKjb55s49cw0Y/wsnVAc1/aSpJLdFR0fCc7Y29uw/glxa/wN/PH7/+WnRmmySirwfDJSIq1J49ewYnJyesWLECNWvVgKOzHdp1aFsg9y2EwD/HTmC26xxEPniICRMmwNXVFRUqVCiQ+1fGvn37YGkpQ1hYOIYMN4al9RSUK1euQO77Vdwr+M1fhPVrN6JmzZqYP38+evTooRIjXd7n5cuXcHV1xaJFi1BNvyqmz7BFpy4dCqzeUyfPYJaLJ8JCwzFmzBjMnj0benp6BXLfyjh8+DBkMhmCg4MxcFA/WNnKUKHCNwVy3wkJiVjotwRrVq1DtWpV4e09D0ZGRip7bMXHx8PNzQ1+fn749ttKsHO0gWH3rgVW7/mzFzHTxR13g+7BxMQE7u7uqFJF+pEuH3L8+HFYWJjj5s1b6DegD2zsLKFXqWCeC0lJyVi8YBlWr/gTenp6mDt3LgYNGqSyx1ZiYiI8PDwwb948fFOhPGwdrNGzd8GNcrx86SrcnN1x6+YdDBkyBJ6entDX1y+Q+1bGmTNnYGFhgStXrqBn7+6wnW6FKlUqF8h9p6SkYNniVVixdBXKlSsPT09PDBs2TCVGURERKYPhEhEVCTdu3IBMJsPx48fRoWM7THe2Ra3ayk/F/l/CQsMxe+YcnPhHuv4kysrIyMDChQvh6uoKNXU1WFiaYeiIQfk20kpV+pMoKygoCBYyCxw5fARtDFrB0dkO9ernXw8tVehPoqysrCwsXboUM2bMQFZWFqbIJmLEqKH5NtJKLpdjy1/bMG+uf6HsT/JmH7mWv7XAjHzuI/foYRQ8ZnnhwL5D+PXXlvDz80eLFoVjZrZ/95GbOGUcxow1ybc+cgqFAju27YKXx3wkJCTC1tYWNjY2KFmycMz6FxERAWtr69w+co4u9mjU+Kd8u7+YmMeYM3sedu/ci2bNmsHPzw+tW7fOt/vLSwqFAn/++Sfs7e0RnxCPCZPG5msfOSEEdv29F3M95uHF85ewsrKCvb09SpcuPLP+ERG9D8MlIioyhBDYvn07rK2tEBUVDZPRwzDFYiLK6Obda1H8q3j4+SzC+j83onr16pg3b57k/UmU9fTpU0yfPh2rVq1C7Tq14ORij7bt8vZkQBX7kyhDCIE9e/Zg6tSpuH//PoYOHwSZ1WSULVc2z+4jMTEJi/yWIGDVOpXpT6KsFy9ewNnZGUuXLkX17/ThMGMaOnZqn6f7UpT6kxw4cACWlpYICQnJlz5yycnJWLpoBVYuW4NvvvkGc+fOxeDBgwvlCIk3+8hVrlIZDk5530fu6pVrcHP2wI3rt2BsbIy5c+eievXqebb9gvRmH7l+A/vCJo/7yKWmpmL5ktVYtmQldMvowsPDAyYmJoXy2Pp3Hznb6Vbo3tMwT4+tmzduw83ZHVcuX4ORkRG8vLxQq1atPNs+EZGUGC4RUZGTlpaG+fPnw93dHdra2phqY46Bg/tBQ0ND6W3K5XL8tWEL5nv5IzMjE9OnT1e5/iTKunbtGmQyGU6ePIlOXTrAwWkaataq8UXbfLM/SevWreDn549mzZrlTcESSk9Px4IFCzBz5kxoFNOAzGoyhgwz/qLZ7XL6k3h7+iA5OUUl+5Mo6/bt25DJZDh69CgM2reBo7Md6tSt/UXbjI6Khscsb+zbU7T6k2RmZmLx4sVwcXGBQiHHFMtJGG4y5ItGfSkUCuzcvhtzPX3wKu4VbGxsYGtri1KlVGuGLGXkRx+5xzFPMNdjPnbu2I0mTZrAz88PbdsWzGXW+SkrKwsrVqyAo6NjnvWRE0Jg7+798JzljefPX8DS0hIODg5F4rN/WFgYrK2tsXPnTjRv0QwzXO3xU8Mv6wv47OkzeM3xxdZN29Gw4U/w9fVDx44d86hiIiLVwHCJiIqs6Oho2NvbY926dWjww/eY4WqPlr99/iUg585cgJurB+4G3csdfVO5csH0ZCgoQghs3boV1tbWePz4MUaOHg4ziwkoU+bzhuknJSXnzg6kp6cHLy8vGBsbF8rRNx8TGxsLBwcHBAQEoG69OnB0sUObtq0+ezuXLl6Bm7MHbt8qHP1JlCGEwK5duzB16lRERkZi+MghsLA0g25Z3c/aTkpKCpYtWokVy1YX6f4kz58/h5OTE5YvX46aNWtgurMt2nc0+OztXL96AzOdPXD92g30798fXl5eqFGjRt4XLLE3+8gNHjYQltbmKF/+8/rIpaWmYcWy1Vi6eCVKlyoNd3d3jBw58ou+kFBF/+4j5+A0DZ27dvzs1+dbN+/AzcUDly9eQe/eveHt7Y06derkU9XS+XcfuanTLFCx4uf1VExPz0DAyj+xyH8ZtLW14ebmBlNT0y/6QoKISFV9ThZUtD69EVGRV7VqVaxduxbnzp1DqVKlMXiACSZPsER0VPQnrf/oYRQmmppjqPFIlC1TFhcvXkRAQECRC5YAQE1NDQMGDMDdu3fh5OSEwHV/obOBITZt3Aq5XP6f6+eMvulsYIi1AYGwt7fHvXv3VLrx7ZeoVKkSVq1ahUuXLqFihYoYMXgMxo+ZjMgHDz9p/ejoGJibWcHYaBi0tUrgzJkzCAwMLHLBEpB9bPXu3RtBQUGYPXs2tm7agY4Ghli/diOysrL+c30hBHbu2IPO7bpj+dLVmDrVCiEhIRgxYkSRC5YAoEKFCliyZAmuXbsGff3qGD1iPMaMmICI8PuftH7sk6ewltnBqNcgCIXA8ePHsWXLliIZLAFAt27dcOvWbXh5eWH33/vQqe0fWLNqHTIzM/9zXSEE9u05gK4demCh31KYTTJDSEgIxowZU+SCJQAoX748/Pz8cPPmTdSrVx/jx0zGiCFjEXIv9JPWf/bsOeysHdGn+wCkJqfh8OHD+Pvvv4tksAQAXbp0wY0bN+Dv749DB46is0E3rFi6GhkZGf+5rhAChw8exR+demLeXD+MHTsWoaGhmDhxIoMlIiIAEJ8gPj5eABDx8fGfsjgRUYGQy+Vi7dq1onLlykJbW0tMsZgobodcERFRwe/8u3Xvspg0ZbzQ0tISVatWFevXrxcKhULqXShQjx49EkOHDhUAxE8NfxSbtq9/72MVERUstvy9QTRq/JMAIAYNGiQiIyOlLr9AKRQK8ddffwl9fX2hqakpxk8aK27evfzex+pO6FVhbmkmtEtoi0qVKomAgAAhl8ul3oUCFRMTI0aOHCkAiO8b1BfrNwV88NjasWezaNa8iQAgjIyMRHh4uNTlFyiFQiG2bdsmatT4ThQrVkyMNjUR1+9ceO9jFRx2XVjZyoSOjo6oUKGCWLZsmcjKypJ6FwpUbGysMDU1FWpqaqJO3dpizfoVHzy29hzcLlr8+osAIHr27CFCQkKkLr9AKRQKsXv3blGnTh2hoaEhRowcKq7eOvf+Yyv8hrCbbi1KlSolypUrJxYuXCgyMzOl3oUC9fz5czF58mShoaEhataqIVasWSzCHwW99/Haf2SnaN3mNwFAdOnaRdy5c0fq8omICsTnZEEMl4io0EtMTBQODg5CS0tLfFv5WzHff27uB8Swh3eEt6+H0KukJ7S1tYWTk5NISkqSumRJnTlzRjRv3lwAED16GYpTF47mfoA+c/Ef0atPDwFANGnSRJw8eVLqciWVnJwsXFxcRIkSJYSeXkUxd767CHt4R0REBYvwR0HCb5G3qFKlstDU1BS2trZf/fvkxYsXxW+//SoAiN8Nu4jjZw7lHlvnr5wQ/Qb2FQBEw4Y/iaNHj0pdrqRSU1OFu7u7KFmypCj/TXkx29NVhEbezj22Fi/3E/r61USxYsWEpaWliIuLk7pkSV29elUYGBgIAKJj5/bi6Mn9ucfWxeunxaAhA4Samppo0KCBOHDggNTlSiotLU14eXmJ0qVLi7LlygqXWY4i5MGt3GNrRcBiUaPmd0JDQ0NMnjxZPH/+XOqSJXXr1i3RqVMnAUAYtG8jDv2zJ/fYunLrrBhuMkSoq6uLOnXqiN27d391X0wR0deN4RIRfZXCw8OFkZGRACCaNmsifBZ4icZNGgkAYsCAAeL+/ftSl6gy5HK5CAgIEN9++63QLqEtzC3NhKX1FFFCp4TQ09MTK1eu/OpGSHxMZGSkGDRokAAgGjX+Sfgs8BLNf2kqAIjevXuL0NBQqUtUGQqFQgQGBoqqVasKTU1NMXHyOGFjN1WULFlSfPPNN2Lx4sVf3QiJj4mOjhYjRowQAESDH74XPgu8xG+tWgoAwrCboQgODpa6RJWhUCjE5s2bRfXq1UXx4sWF6fjRwsFpWnaIUras8PPzExkZGVKXqTKePHkiRo8eLdTU1ES9+nXFfP+5om271gKA6NSpk7h165bUJaoMhUIh/v77b1GrVi2hoaEhRo4eLpxc7IVuWV1RpkwZ4eXlJdLT06Uuk4iowDFcIqKv2rFjx0TDhtmXdP38c2Nx4sQJqUtSWQkJCcLOzk5oamqK4sWLCxsbG77Wf8SpU6dE06bZodKPP/4oDh8+LHVJKispKUk4OTkJbW1toaGhISwsLMTLly+lLktlnT9/XrRo2UIAEPXr1xN79+6VuiSVlZKSItzc3ISOjo5QV1cXEydOFM+ePZO6LJV15coV0aZNdqhUu3ZtsXPnTo6++YC0tDTh6ekpSpUqJdTU1MSYMWPEkydPpC6LiEgyn5MFcbY4IiqSsrKycPLkSbRr165INnHNa+Hh4ZDL5ahX78um/f4ayOVynDhxAgYGBmzi+gkiIyORkpKCBg0aSF2KylMoFDh+/DjatGkDTU3lp5T/WkRFRSEuLg4NGzaUuhSVJ0R2I/hWrVpBS0tL6nJU3uPHjxEbG4uff/5Z6lKIiCT1OVkQwyUiIiIiIiIiInrL52RBRW++XyIiIiIiIiIiKjAMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGkMl4iIiIiIiIiISGnFPmUhIQQAICEhIV+LISIiIiIiIiIi6eVkQDmZ0Md8UriUmJgIANDX1/+CsoiIiIiIiIiIqDBJTEyErq7uR5dRE58QQSkUCsTExKB06dJQU1PLswKJiIiIiIiIiEj1CCGQmJiIKlWqQF39412VPilcIiIiIiIiIiIieh829CYiIiIiIiIiIqUxXCIiIiIiIiIiIqUxXCIiIiIiIiIiIqUxXCIiIiIiIiIiIqUxXCIiIiIiIiIiIqUxXCIiIiIiIiIiIqUxXCIiIiIiIiIiIqX9D6SAtxUXG3H3AAAAAElFTkSuQmCC",
            "text/plain": [
              "<Figure size 1500x1500 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# 刻画每一圈的hex的圆心坐标 \n",
        "\n",
        "def all_locs_with_coords(order, radius):\n",
        "    if order == 1:\n",
        "        coords = dict()\n",
        "        coords[0,0,0] = [0,0]\n",
        "        return [[0, 0, 0]], coords\n",
        "    result = [[0,0,0]]\n",
        "    last_iter = [[0,0,0]]\n",
        "    coords = dict()\n",
        "    coords[0,0,0] = [0,0]\n",
        "    for order_ in range(1, order):\n",
        "        new_iter = []\n",
        "        for (q, r, s) in last_iter:\n",
        "            six_neighbour = [\n",
        "                [q + 1, r, s - 1],\n",
        "                [q - 1, r, s + 1],\n",
        "                [q, r + 1, s - 1],\n",
        "                [q, r - 1, s + 1],\n",
        "                [q - 1, r + 1, s],\n",
        "                [q + 1, r - 1, s]\n",
        "            ]\n",
        "            for neighbor in six_neighbour:\n",
        "                if neighbor not in result and neighbor not in new_iter:\n",
        "                    new_iter.append(neighbor)\n",
        "                    q1, r1, s1 = neighbor[0], neighbor[1], neighbor[2]\n",
        "                    coords[q1, r1, s1] = [math.sqrt(3) * radius * (q1 - s1) / 2, radius * 3 * r1 / 2]\n",
        "        last_iter = new_iter\n",
        "        result = result + new_iter \n",
        "    return result, coords\n",
        "        \n",
        "def split_numbers(lengths):\n",
        "    # 计算总和\n",
        "    total = sum(lengths)\n",
        "    # 生成从1到total的连续数字\n",
        "    numbers = list(range(1, total + 1))\n",
        "\n",
        "    # 计算所有长度的排列\n",
        "    permutations = list(itertools.permutations(lengths))\n",
        "\n",
        "    # 存储所有分法的结果\n",
        "    results = []\n",
        "\n",
        "    # 对每个排列进行分段\n",
        "    for perm in permutations:\n",
        "        split = []\n",
        "        start = 0\n",
        "        for length in perm:\n",
        "            split.append(numbers[start:start + length])\n",
        "            start += length\n",
        "        results.append(split)\n",
        "    return results\n",
        "\n",
        "def all_locs(order):\n",
        "    if order == 1:\n",
        "        return [[0,0,0]]\n",
        "    result = [[0,0,0]]\n",
        "    last_iter = [[0,0,0]]\n",
        "    for order_ in range(1, order):\n",
        "        new_iter = []\n",
        "        for (q, r, s) in last_iter:\n",
        "            six_neighbour = [\n",
        "                [q + 1, r, s - 1],\n",
        "                [q - 1, r, s + 1],\n",
        "                [q, r + 1, s - 1],\n",
        "                [q, r - 1, s + 1],\n",
        "                [q - 1, r + 1, s],\n",
        "                [q + 1, r - 1, s]\n",
        "            ]\n",
        "            for neighbor in six_neighbour:\n",
        "                if neighbor not in result and neighbor not in new_iter:\n",
        "                    new_iter.append(neighbor)\n",
        "        last_iter = new_iter\n",
        "        result = result + new_iter \n",
        "    return result\n",
        "\n",
        "def get_obj(result, order):\n",
        "    obj = 9999\n",
        "    locations = all_locs(order)\n",
        "    N = len(locations)\n",
        "    for (q, r, s) in locations:\n",
        "        cur_min = 99999\n",
        "        six_neighbour = [\n",
        "                [q + 1, r, s - 1],\n",
        "                [q - 1, r, s + 1],\n",
        "                [q, r + 1, s - 1],\n",
        "                [q, r - 1, s + 1],\n",
        "                [q - 1, r + 1, s],\n",
        "                [q + 1, r - 1, s],\n",
        "            ]\n",
        "        cur_neighbour = []\n",
        "        cnt = 0\n",
        "        for neighbour in six_neighbour:\n",
        "            if neighbour in locations:\n",
        "                cur_min = min(abs(result[neighbour[0], neighbour[1], neighbour[2]] - result[q, r, s]), cur_min)\n",
        "        obj = min(cur_min, obj)\n",
        "    return obj\n",
        "\n",
        "def solver(order):\n",
        "    result = all_locs(order)\n",
        "    print(len(result))\n",
        "    _, coords = all_locs_with_coords(order, 2)\n",
        "    # print(f\"HERE: {len(coords.keys())}\")\n",
        "    total_grids = []\n",
        "    # print(coords)\n",
        "    for k, v in coords.items():\n",
        "        total_grids.append(v + [k[0], k[1], k[2]])\n",
        "    sorted_array = sorted(total_grids, key=lambda x: (x[0], -x[1]))\n",
        "    single_x = []\n",
        "    for total_grid in sorted_array:\n",
        "        if total_grid[0] not in single_x:\n",
        "            single_x.append(total_grid[0])\n",
        "\n",
        "    print(f\"\\t Totally {len(single_x)} Lines\")\n",
        "\n",
        "    firsts = []\n",
        "    seconds = []\n",
        "    thirds = []\n",
        "\n",
        "    for total_grid in sorted_array:\n",
        "        if single_x.index(total_grid[0]) % 3 == 0:\n",
        "            firsts.append(total_grid)\n",
        "        elif single_x.index(total_grid[0]) % 3 == 1:\n",
        "            seconds.append(total_grid)\n",
        "        elif single_x.index(total_grid[0]) % 3 == 2:\n",
        "            thirds.append(total_grid)\n",
        "        # print(total_grid)\n",
        "\n",
        "    print(f\"Red: {len(firsts)} Nodes\")\n",
        "    print(f\"Blue: {len(seconds)} Nodes\")\n",
        "    print(f\"Green: {len(thirds)} Nodes\")\n",
        "\n",
        "    lengths = [len(firsts), len(seconds), len(thirds)]\n",
        "    combinations = []\n",
        "    all_splits = split_numbers(lengths)\n",
        "    idx_cores = list(itertools.permutations([0,1,2]))\n",
        "\n",
        "    for idx, p in enumerate(all_splits):\n",
        "        tmp = [[0], [0], [0]]\n",
        "        tmp[idx_cores[idx][0]] = p[0]\n",
        "        tmp[idx_cores[idx][1]] = p[1]\n",
        "        tmp[idx_cores[idx][2]] = p[2]\n",
        "        combinations.append(tmp)\n",
        "\n",
        "\n",
        "    fin_result = dict()\n",
        "    fin_obj = 0\n",
        "    for comb in combinations:\n",
        "        result = dict()\n",
        "\n",
        "        first_nums = comb[0]\n",
        "        second_nums = comb[1]\n",
        "        third_nums = comb[2]\n",
        "        for idx, line in enumerate(firsts):\n",
        "            result[line[2], line[3], line[4]] = comb[0][idx]\n",
        "        \n",
        "        for idx, line in enumerate(seconds):\n",
        "            result[line[2], line[3], line[4]] = comb[1][idx]\n",
        "        \n",
        "        for idx, line in enumerate(thirds):\n",
        "            result[line[2], line[3], line[4]] = comb[2][idx]\n",
        "        \n",
        "        obj = get_obj(result, order)\n",
        "        if obj > fin_obj:\n",
        "            fin_obj = obj\n",
        "            fin_result = result\n",
        "        # for k, v in result.items():\n",
        "        #     print(k, v)\n",
        "\n",
        "    print(fin_result)\n",
        "    return fin_result\n",
        "\n",
        "\n",
        "\n",
        "# 创建一个函数来计算六边形的中心坐标\n",
        "def get_hex_coordinates(order, radius):\n",
        "    nodes, coords = all_locs_with_coords(order, radius)\n",
        "    hex_coords = []  # 中心六边形坐标\n",
        "    directions = [(1, 0), (0.5, np.sqrt(3)/2), (-0.5, np.sqrt(3)/2), \n",
        "                  (-1, 0), (-0.5, -np.sqrt(3)/2), (0.5, -np.sqrt(3)/2)]  # 六个方向\n",
        "    \n",
        "    for (q, r, s) in nodes:\n",
        "        hex_coords.append(coords[q, r, s])\n",
        "        \n",
        "    # 每层添加六边形\n",
        "    return nodes, hex_coords\n",
        "\n",
        "def visual(result, order):\n",
        "    # 设置图形参数\n",
        "    fig, ax = plt.subplots(1, figsize = (15,15))\n",
        "    radius = 2  # 六边形的半径\n",
        "\n",
        "    # 获取所有六边形的中心坐标\n",
        "    nodes, hex_centers = get_hex_coordinates(order, radius)\n",
        "\n",
        "    # 绘制每个六边形\n",
        "    for idx, (x, y) in enumerate(hex_centers):\n",
        "        hexagon = RegularPolygon((x, y), numVertices=6, radius=radius, orientation=np.radians(120), edgecolor='k', facecolor='#DEE4D7')\n",
        "        ax.add_patch(hexagon)\n",
        "        q1, r1, s1 = nodes[idx][0], nodes[idx][1], nodes[idx][2]\n",
        "        ax.text(x, y, f\"{result[q1, r1, s1]}\", ha='center', va='center', fontsize = 18)\n",
        "\n",
        "    # 调整显示范围\n",
        "    ax.set_aspect('equal')\n",
        "    limit = radius * math.sqrt(3) * (order - 1/2)\n",
        "    plt.xlim(- int(limit) - 1, limit + 1)\n",
        "    plt.ylim(- int(limit) - 1, limit + 1)\n",
        "    # 隐藏x轴和y轴刻度\n",
        "    ax.set_xticks([])\n",
        "    ax.set_yticks([])\n",
        "    result_d = get_obj(result, order)\n",
        "    plt.title(f\"Order = {order}, D = {result_d}\")\n",
        "    plt.show()\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    order = 8\n",
        "    fin_result = solver(order = order)\n",
        "    fin_obj = get_obj(fin_result, order = order)\n",
        "    print(fin_obj)\n",
        "    visual(fin_result, order = order)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Honeycomb Game 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "SUM CNT:84\n",
            "Gurobi Optimizer version 11.0.2 build v11.0.2rc0 (mac64[arm] - Darwin 23.5.0 23F79)\n",
            "\n",
            "CPU model: Apple M3 Pro\n",
            "Thread count: 11 physical cores, 11 logical processors, using up to 11 threads\n",
            "\n",
            "Optimize a model with 80 rows, 530 columns and 2360 nonzeros\n",
            "Model fingerprint: 0x7b3156f1\n",
            "Model has 43 general constraints\n",
            "Variable types: 169 continuous, 361 integer (361 binary)\n",
            "Coefficient statistics:\n",
            "  Matrix range     [1e+00, 2e+01]\n",
            "  Objective range  [1e+00, 1e+00]\n",
            "  Bounds range     [1e+00, 2e+01]\n",
            "  RHS range        [1e+00, 1e+00]\n",
            "Presolve added 210 rows and 42 columns\n",
            "Presolve time: 0.01s\n",
            "Presolved: 290 rows, 572 columns, 2780 nonzeros\n",
            "Variable types: 127 continuous, 445 integer (403 binary)\n",
            "Found heuristic solution: objective 2.0000000\n",
            "\n",
            "Root relaxation: objective 1.800000e+01, 264 iterations, 0.00 seconds (0.00 work units)\n",
            "\n",
            "    Nodes    |    Current Node    |     Objective Bounds      |     Work\n",
            " Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time\n",
            "\n",
            "     0     0   18.00000    0   42    2.00000   18.00000   800%     -    0s\n",
            "     0     0   16.66667    0  133    2.00000   16.66667   733%     -    0s\n",
            "     0     0   15.00000    0  136    2.00000   15.00000   650%     -    0s\n",
            "     0     0   15.00000    0  130    2.00000   15.00000   650%     -    0s\n",
            "     0     0   15.00000    0  129    2.00000   15.00000   650%     -    0s\n",
            "     0     0   15.00000    0   85    2.00000   15.00000   650%     -    0s\n",
            "     0     2   15.00000    0   63    2.00000   15.00000   650%     -    0s\n",
            "H  248   199                       3.0000000   15.00000   400%  37.3    0s\n",
            "* 3255  1720              84       4.0000000   15.00000   275%  17.9    0s\n",
            "*28086  5507              76       5.0000000    7.25000  45.0%  15.9    2s\n",
            " 58647 10952     cutoff   65         5.00000    6.11111  22.2%  17.4    5s\n",
            " 112555 10639    5.75000   47   73    5.00000    6.00000  20.0%  18.4   10s\n",
            " 190516 11296    5.28571   64   69    5.00000    6.00000  20.0%  17.2   15s\n",
            "\n",
            "Cutting planes:\n",
            "  MIR: 11\n",
            "  Flow cover: 10\n",
            "  GUB cover: 2\n",
            "\n",
            "Explored 243951 nodes (4161648 simplex iterations) in 18.76 seconds (32.45 work units)\n",
            "Thread count was 11 (of 11 available processors)\n",
            "\n",
            "Solution count 4: 5 4 3 2 \n",
            "\n",
            "Optimal solution found (tolerance 1.00e-04)\n",
            "Best objective 5.000000000000e+00, best bound 5.000000000000e+00, gap 0.0000%\n",
            "\n",
            "User-callback calls 495929, time in user-callback 0.33 sec\n",
            "0, 0, 0 == 17\n",
            "1, 0, -1 == 2\n",
            "-1, 0, 1 == 11\n",
            "0, 1, -1 == 12\n",
            "0, -1, 1 == 3\n",
            "-1, 1, 0 == 6\n",
            "1, -1, 0 == 9\n",
            "2, 0, -2 == 8\n",
            "1, 1, -2 == 19\n",
            "2, -1, -1 == 14\n",
            "-2, 0, 2 == 5\n",
            "-1, -1, 2 == 16\n",
            "-2, 1, 1 == 18\n",
            "0, 2, -2 == 7\n",
            "-1, 2, -1 == 1\n",
            "0, -2, 2 == 10\n",
            "1, -2, 1 == 15\n",
            "-2, 2, 0 == 13\n",
            "2, -2, 0 == 4\n"
          ]
        }
      ],
      "source": [
        "def honeycomb_solver(order):\n",
        "    Honeycomb = gp.Model(\"Honeycomb\")\n",
        "    x = dict()\n",
        "\n",
        "    # 决策变量: x 与 最后的 D\n",
        "    locations = all_locs(order)\n",
        "    N = len(locations)\n",
        "    for (q, r, s) in locations:\n",
        "        for num in range(1, N + 1):\n",
        "            x[q, r, s, num] = Honeycomb.addVar(\n",
        "                vtype=gp.GRB.BINARY,\n",
        "                name=f\"x_{q}_{r}_{s}_{num}\")\n",
        "        # x[q, r, s, 'D'] = Honeycomb.addVar(\n",
        "        #     vtype = gp.GRB.CONTINUOUS,\n",
        "        #     name = f\"{q}_{r}_{s}_D\"\n",
        "        # )\n",
        "    \n",
        "    x_neighbours = dict()\n",
        "    sum_cnt = 0\n",
        "    for (q, r, s) in locations:\n",
        "        x_neighbours[q, r, s] = []\n",
        "        six_neighbour = [\n",
        "                [q + 1, r, s - 1],\n",
        "                [q - 1, r, s + 1],\n",
        "                [q, r + 1, s - 1],\n",
        "                [q, r - 1, s + 1],\n",
        "                [q - 1, r + 1, s],\n",
        "                [q + 1, r - 1, s],\n",
        "            ]\n",
        "        cur_neighbour = []\n",
        "        cnt = 0\n",
        "        for neighbour in six_neighbour:\n",
        "            if neighbour in locations:\n",
        "                x_neighbours[q, r, s].append(neighbour)\n",
        "                x[q, r, s, f\"A{cnt}\"] = Honeycomb.addVar(\n",
        "                    vtype = gp.GRB.CONTINUOUS,\n",
        "                    lb = -N + 1,\n",
        "                    ub = N - 1,\n",
        "                    name = f\"{q}_{r}_{s}_A{cnt}\"\n",
        "                )\n",
        "                x[q, r, s, f\"ABS{cnt}\"] = Honeycomb.addVar(\n",
        "                    vtype = gp.GRB.CONTINUOUS,\n",
        "                    lb = - N + 1,\n",
        "                    ub = N - 1,\n",
        "                    name = f\"{q}_{r}_{s}_ABS{cnt}\"\n",
        "                )\n",
        "                cnt += 1\n",
        "        sum_cnt += cnt\n",
        "    print(f\"SUM CNT:{sum_cnt}\")\n",
        "    x['D'] = Honeycomb.addVar(vtype = gp.GRB.CONTINUOUS, name = 'D')\n",
        "    Honeycomb.update()\n",
        "\n",
        "    for i in range(1, N + 1):\n",
        "        Honeycomb.addConstr(gp.quicksum(x[q, r, s, i] for (q, r, s) in locations) == 1, name = f\"{i}_num1\")\n",
        "    for (q, r, s) in locations:\n",
        "        Honeycomb.addConstr(gp.quicksum(x[q, r, s, i] for i in range(1, N + 1)) == 1, name = f\"{q}_{r}_{s}_num2\")\n",
        "    \n",
        "    visited_pair = set()\n",
        "    for (q, r, s) in locations:\n",
        "        \n",
        "        cur_neighbour = x_neighbours[q, r, s]\n",
        "        # print(f\"({q},{r},{s}), {cur_neighbour}\")\n",
        "        for idx, (q1, r1, s1) in enumerate(cur_neighbour):\n",
        "            # pass\n",
        "            # if (q, r, s, f\"ABS{idx}\") in x:\n",
        "            #     print(f\"{q},{r},{s},ABS{idx}\")\n",
        "            if f\"{q1}_{r1}_{s1},{q}_{r}_{s}\" not in visited_pair :\n",
        "                visited_pair.add(f\"{q}_{r}_{s},{q1}_{r1}_{s1}\")\n",
        "                visited_pair.add(f\"{q1}_{r1}_{s1},{q}_{r}_{s}\")\n",
        "                Honeycomb.addConstr(\n",
        "                    gp.quicksum(i * x[q, r, s, i] for i in range(1, N + 1)) - gp.quicksum(i * x[q1, r1, s1, i] for i in range(1, N + 1)) == x[q, r, s, f'ABS{idx}'], \n",
        "                    name = f\"Abs_{q}_{r}_{s}_A{idx}\"\n",
        "                )\n",
        "                Honeycomb.addConstr(\n",
        "                    x[q, r, s, f'A{idx}'] == gp.abs_(x[q, r, s, f'ABS{idx}']), \n",
        "                    name = f\"Cnst_{q}_{r}_{s}_A{idx}\"\n",
        "                )\n",
        "                \n",
        "\n",
        "    tmp_list = []\n",
        "    for (q, r, s) in locations:\n",
        "        for t in range(len(x_neighbours[q, r, s])):\n",
        "            \n",
        "            tmp_list.append(x[q, r, s,f'A{t}'])\n",
        "            \n",
        "    Honeycomb.addConstr(x['D'] == gp.min_(tmp_list), name = \"CONSTR_D\")\n",
        "    # Honeycomb.addConstr(x['D'] == gp.max_(tmp_list), name = \"CONSTR_D\")\n",
        "    Honeycomb.setObjective(x['D'], gp.GRB.MAXIMIZE)\n",
        "    # Honeycomb.setObjective(x['D'], gp.GRB.MINIMIZE)\n",
        "\n",
        "    Honeycomb.update()\n",
        "    \n",
        "    hardlimit = 180\n",
        "    def softtime(model, where):\n",
        "        if where == gp.GRB.Callback.MIP:\n",
        "            runtime = model.cbGet(gp.GRB.Callback.RUNTIME)\n",
        "            objbst = model.cbGet(gp.GRB.Callback.MIP_OBJBST)\n",
        "            objbnd = model.cbGet(gp.GRB.Callback.MIP_OBJBND)\n",
        "            gap = abs(objbst - objbnd) / abs(objbst)\n",
        "\n",
        "            if runtime > hardlimit and gap < 0.5:\n",
        "                model.terminate()\n",
        "\n",
        "    Honeycomb.optimize(softtime)\n",
        "    # Honeycomb.write(\"honeycomb.lp\")\n",
        "    Honeycomb._x = x\n",
        "    \n",
        "    # for (q, r, s) in locations:\n",
        "    #     for idx, (q1, r1, s1) in enumerate(cur_neighbour):\n",
        "    #         print(sum(i * x[q, r, s, i].x for i in range(1, N + 1)) - sum(i * x[q1, r1, s1, i].x for i in range(1, N + 1)))\n",
        "    #         print(x[q, r, s, f'ABS{idx}'].x)\n",
        "    # for (q1, r1, s1) in x_neighbours[0,0,0]:\n",
        "    #     for g in range(6):\n",
        "    #         print(f\"CHECK: {q1}, {r1}, {s1},A{g} == {x[0, 0, 0, f'A{g}'].x}\")\n",
        "\n",
        "    ofv = None\n",
        "    seq = []\n",
        "    fill_in_nums = dict()\n",
        "    solType = None\n",
        "    gap = None\n",
        "    lb = None\n",
        "    ub = None\n",
        "    runtime = None\n",
        "    # if (Honeycomb.status == gp.GRB.status.OPTIMAL):\n",
        "    \n",
        "    solType = 'IP_Optimal'\n",
        "    ofv = Honeycomb.getObjective().getValue()\n",
        "    for (q, r, s) in locations:\n",
        "        for j in range(1, N + 1):\n",
        "            if x[q, r, s, j].x > 0.5:\n",
        "                fill_in_nums[q, r, s] = j\n",
        "                print(f\"{q}, {r}, {s} == {j}\")\n",
        "    gap = 0\n",
        "    lb = ofv\n",
        "    ub = ofv\n",
        "    runtime = Honeycomb.Runtime\n",
        "    \n",
        "    # elif (Honeycomb.status == gp.GRB.status.TIME_LIMIT):\n",
        "    #     solType = 'IP_TimeLimit'\n",
        "    #     ofv = None\n",
        "    #     seq = []\n",
        "    #     gap = Honeycomb.MIPGap\n",
        "    #     lb = Honeycomb.ObjBoundC\n",
        "    #     ub = Honeycomb.ObjVal\n",
        "    #     runtime = Honeycomb.Runtime\n",
        "    \n",
        "    \n",
        "    return {\n",
        "        'FILL_IN_NUMS': fill_in_nums,\n",
        "        'RUNTIME': runtime,\n",
        "    }\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    \n",
        "    result_dict = honeycomb_solver(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[[0, 0, 0], [1, 0, -1], [-1, 0, 1], [0, 1, -1], [0, -1, 1], [-1, 1, 0], [1, -1, 0], [2, 0, -2], [1, 1, -2], [2, -1, -1], [-2, 0, 2], [-1, -1, 2], [-2, 1, 1], [0, 2, -2], [-1, 2, -1], [0, -2, 2], [1, -2, 1], [-2, 2, 0], [2, -2, 0], [3, 0, -3], [2, 1, -3], [3, -1, -2], [1, 2, -3], [3, -2, -1], [-3, 0, 3], [-2, -1, 3], [-3, 1, 2], [-1, -2, 3], [-3, 2, 1], [0, 3, -3], [-1, 3, -2], [-2, 3, -1], [0, -3, 3], [1, -3, 2], [2, -3, 1], [-3, 3, 0], [3, -3, 0]]\n",
            "37\n",
            "378 37\n",
            "90 37\n"
          ]
        },
        {
          "ename": "KeyboardInterrupt",
          "evalue": "",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[30], line 55\u001b[0m\n\u001b[1;32m     53\u001b[0m \u001b[38;5;66;03m# 使用 GraphMatcher 检测无向图的同构子图\u001b[39;00m\n\u001b[1;32m     54\u001b[0m result \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m---> 55\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m isomorphism\u001b[38;5;241m.\u001b[39mGraphMatcher(G, H)\u001b[38;5;241m.\u001b[39msubgraph_monomorphisms_iter():\n\u001b[1;32m     56\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(result) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m     57\u001b[0m         \u001b[38;5;28;01mbreak\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/py310_arm/lib/python3.10/site-packages/networkx/algorithms/isomorphism/isomorphvf2.py:396\u001b[0m, in \u001b[0;36mGraphMatcher.subgraph_monomorphisms_iter\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    394\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtest \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmono\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    395\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minitialize()\n\u001b[0;32m--> 396\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch()\n",
            "File \u001b[0;32m~/anaconda3/envs/py310_arm/lib/python3.10/site-packages/networkx/algorithms/isomorphism/isomorphvf2.py:321\u001b[0m, in \u001b[0;36mGraphMatcher.match\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    318\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msemantic_feasibility(G1_node, G2_node):\n\u001b[1;32m    319\u001b[0m     \u001b[38;5;66;03m# Recursive call, adding the feasible state.\u001b[39;00m\n\u001b[1;32m    320\u001b[0m     newstate \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m(\u001b[38;5;28mself\u001b[39m, G1_node, G2_node)\n\u001b[0;32m--> 321\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch()\n\u001b[1;32m    323\u001b[0m     \u001b[38;5;66;03m# restore data structures\u001b[39;00m\n\u001b[1;32m    324\u001b[0m     newstate\u001b[38;5;241m.\u001b[39mrestore()\n",
            "File \u001b[0;32m~/anaconda3/envs/py310_arm/lib/python3.10/site-packages/networkx/algorithms/isomorphism/isomorphvf2.py:321\u001b[0m, in \u001b[0;36mGraphMatcher.match\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    318\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msemantic_feasibility(G1_node, G2_node):\n\u001b[1;32m    319\u001b[0m     \u001b[38;5;66;03m# Recursive call, adding the feasible state.\u001b[39;00m\n\u001b[1;32m    320\u001b[0m     newstate \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m(\u001b[38;5;28mself\u001b[39m, G1_node, G2_node)\n\u001b[0;32m--> 321\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch()\n\u001b[1;32m    323\u001b[0m     \u001b[38;5;66;03m# restore data structures\u001b[39;00m\n\u001b[1;32m    324\u001b[0m     newstate\u001b[38;5;241m.\u001b[39mrestore()\n",
            "    \u001b[0;31m[... skipping similar frames: GraphMatcher.match at line 321 (24 times)]\u001b[0m\n",
            "File \u001b[0;32m~/anaconda3/envs/py310_arm/lib/python3.10/site-packages/networkx/algorithms/isomorphism/isomorphvf2.py:321\u001b[0m, in \u001b[0;36mGraphMatcher.match\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    318\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msemantic_feasibility(G1_node, G2_node):\n\u001b[1;32m    319\u001b[0m     \u001b[38;5;66;03m# Recursive call, adding the feasible state.\u001b[39;00m\n\u001b[1;32m    320\u001b[0m     newstate \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstate\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m(\u001b[38;5;28mself\u001b[39m, G1_node, G2_node)\n\u001b[0;32m--> 321\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch()\n\u001b[1;32m    323\u001b[0m     \u001b[38;5;66;03m# restore data structures\u001b[39;00m\n\u001b[1;32m    324\u001b[0m     newstate\u001b[38;5;241m.\u001b[39mrestore()\n",
            "File \u001b[0;32m~/anaconda3/envs/py310_arm/lib/python3.10/site-packages/networkx/algorithms/isomorphism/isomorphvf2.py:320\u001b[0m, in \u001b[0;36mGraphMatcher.match\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    317\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msyntactic_feasibility(G1_node, G2_node):\n\u001b[1;32m    318\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msemantic_feasibility(G1_node, G2_node):\n\u001b[1;32m    319\u001b[0m         \u001b[38;5;66;03m# Recursive call, adding the feasible state.\u001b[39;00m\n\u001b[0;32m--> 320\u001b[0m         newstate \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstate\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;18;43m__class__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mG1_node\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mG2_node\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    321\u001b[0m         \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmatch()\n\u001b[1;32m    323\u001b[0m         \u001b[38;5;66;03m# restore data structures\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/py310_arm/lib/python3.10/site-packages/networkx/algorithms/isomorphism/isomorphvf2.py:909\u001b[0m, in \u001b[0;36mGMState.__init__\u001b[0;34m(self, GM, G1_node, G2_node)\u001b[0m\n\u001b[1;32m    905\u001b[0m     new_nodes\u001b[38;5;241m.\u001b[39mupdate(\n\u001b[1;32m    906\u001b[0m         [neighbor \u001b[38;5;28;01mfor\u001b[39;00m neighbor \u001b[38;5;129;01min\u001b[39;00m GM\u001b[38;5;241m.\u001b[39mG1[node] \u001b[38;5;28;01mif\u001b[39;00m neighbor \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m GM\u001b[38;5;241m.\u001b[39mcore_1]\n\u001b[1;32m    907\u001b[0m     )\n\u001b[1;32m    908\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m node \u001b[38;5;129;01min\u001b[39;00m new_nodes:\n\u001b[0;32m--> 909\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m node \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m GM\u001b[38;5;241m.\u001b[39minout_1:\n\u001b[1;32m    910\u001b[0m         GM\u001b[38;5;241m.\u001b[39minout_1[node] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdepth\n\u001b[1;32m    912\u001b[0m \u001b[38;5;66;03m# Updates for T_2^{inout}\u001b[39;00m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ],
      "source": [
        "import networkx as nx\n",
        "from networkx.algorithms import isomorphism\n",
        "\n",
        "# 创建无向宿主图 G 和模式图 H\n",
        "# 宿主图: 多个数字之间的连接\n",
        "# 测试 order = 5的情况\n",
        "G = nx.Graph()\n",
        "order = 4 # o\n",
        "locations = all_locs(order)\n",
        "# print(locations)\n",
        "num = len(locations)\n",
        "target = 10 # d\n",
        "print(num)\n",
        "G_edges = []\n",
        "for i in range(1, num + 1):\n",
        "    for j in range(1, num + 1):\n",
        "        if abs(i - j) >= target:\n",
        "            # if abs(i - j) <= num / 1.5:\n",
        "            G_edges.append([f\"{i}\", f\"{j}\"])\n",
        "\n",
        "# 创建模式图 H\n",
        "\n",
        "H = nx.Graph()\n",
        "H_edges = []\n",
        "\n",
        "x_neighbours = dict()\n",
        "for (q, r, s) in locations:\n",
        "    six_neighbour = [\n",
        "            [q + 1, r, s - 1],\n",
        "            [q - 1, r, s + 1],\n",
        "            [q, r + 1, s - 1],\n",
        "            [q, r - 1, s + 1],\n",
        "            [q - 1, r + 1, s],\n",
        "            [q + 1, r - 1, s],\n",
        "        ]\n",
        "    cur_neighbour = []\n",
        "    cnt = 0\n",
        "    for neighbour in six_neighbour:\n",
        "        if neighbour in locations:\n",
        "            # x_neighbours[q, r, s].append(neighbour)\n",
        "            n_q, n_r, n_s = neighbour[0], neighbour[1], neighbour[2]\n",
        "            H_edges.append((f\"{q},{r},{s}\", f\"{n_q},{n_r},{n_s}\"))\n",
        "\n",
        "G.add_edges_from(G_edges)\n",
        "H.add_edges_from(H_edges)\n",
        "all_edges1 = list(G.edges())\n",
        "all_edges2 = list(H.edges())\n",
        "\n",
        "\n",
        "print(G.number_of_edges(), G.number_of_nodes())\n",
        "print(H.number_of_edges(), H.number_of_nodes())\n",
        "\n",
        "# 使用 GraphMatcher 检测无向图的同构子图\n",
        "result = []\n",
        "for i in isomorphism.GraphMatcher(G, H).subgraph_monomorphisms_iter():\n",
        "    # 不知道为什么 只能这么构建!\n",
        "    if len(result) > 0:\n",
        "        break\n",
        "    result.append(i)\n",
        "    print(i)\n",
        "    print(\"FOUND!\")\n",
        "\n",
        "# matcher = isomorphism.GraphMatcher(G, H)\n",
        "# if matcher.subgraph_is_isomorphic():\n",
        "#     # 如果存在同构子图，获取节点的映射\n",
        "#     node_mapping = matcher.mapping\n",
        "#     print(\"节点映射:\", node_mapping)\n",
        "\n",
        "#     # 获取边的映射\n",
        "#     # edge_mapping = [(node_mapping[u], node_mapping[v]) for u, v in H.edges()]\n",
        "#     # print(\"边映射:\", edge_mapping)\n",
        "# else:\n",
        "#     print(\"H 不是 G 的同构子图\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[]\n"
          ]
        }
      ],
      "source": [
        "print(result)\n",
        "# for k, v in result[0].items():\n",
        "#     print(v, k)\n",
        "# order3 = dict()\n",
        "# order3[1,0,-1] = 18\n",
        "# order3[-1,0,1] = 7\n",
        "# order3[0,1,-1] = 11\n",
        "# order3[0,-1,1] = 14\n",
        "# order3[-1,1,0] = 17\n",
        "# order3[1,-1,0] = 9\n",
        "# order3[2,0,-2] = 13\n",
        "# order3[1,1,-2] = 6\n",
        "# order3[2,-1,-1] = 4\n",
        "# order3[-2,0,2] = 12\n",
        "# order3[-1,-1,2] = 19\n",
        "# order3[-2,1,1] = 2\n",
        "# order3[0,2,-2] = 16\n",
        "# order3[-1,2,-1] = 5\n",
        "# order3[0,-2,2] = 8\n",
        "# order3[1,-2,1] = 3\n",
        "# order3[-2,2,0] = 10\n",
        "# order3[2,-2,0] = 15"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Honeycomb Game 2\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 110,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Gurobi Optimizer version 11.0.2 build v11.0.2rc0 (mac64[arm] - Darwin 23.5.0 23F79)\n",
            "\n",
            "CPU model: Apple M3 Pro\n",
            "Thread count: 11 physical cores, 11 logical processors, using up to 11 threads\n",
            "\n",
            "Optimize a model with 53 rows, 361 columns and 1805 nonzeros\n",
            "Model fingerprint: 0x89cb1bc9\n",
            "Variable types: 0 continuous, 361 integer (361 binary)\n",
            "Coefficient statistics:\n",
            "  Matrix range     [1e+00, 2e+01]\n",
            "  Objective range  [0e+00, 0e+00]\n",
            "  Bounds range     [1e+00, 1e+00]\n",
            "  RHS range        [1e+00, 4e+01]\n",
            "Presolve time: 0.00s\n",
            "Presolved: 53 rows, 361 columns, 1748 nonzeros\n",
            "Variable types: 0 continuous, 361 integer (361 binary)\n",
            "\n",
            "Root relaxation: objective 0.000000e+00, 110 iterations, 0.00 seconds (0.00 work units)\n",
            "\n",
            "    Nodes    |    Current Node    |     Objective Bounds      |     Work\n",
            " Expl Unexpl |  Obj  Depth IntInf | Incumbent    BestBd   Gap | It/Node Time\n",
            "\n",
            "     0     0    0.00000    0   28          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   44          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   47          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   25          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   38          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   28          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   39          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   29          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   48          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   31          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   47          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   32          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   32          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   25          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   48          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   33          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   30          -    0.00000      -     -    0s\n",
            "     0     0    0.00000    0   43          -    0.00000      -     -    0s\n",
            "H    0     0                       0.0000000    0.00000  0.00%     -    0s\n",
            "     0     0    0.00000    0   28    0.00000    0.00000  0.00%     -    0s\n",
            "\n",
            "Cutting planes:\n",
            "  Cover: 16\n",
            "  Clique: 2\n",
            "  GUB cover: 21\n",
            "  Zero half: 22\n",
            "  RLT: 19\n",
            "\n",
            "Explored 1 nodes (5721 simplex iterations) in 0.26 seconds (0.29 work units)\n",
            "Thread count was 11 (of 11 available processors)\n",
            "\n",
            "Solution count 1: 0 \n",
            "\n",
            "Optimal solution found (tolerance 1.00e-04)\n",
            "Best objective 0.000000000000e+00, best bound 0.000000000000e+00, gap 0.0000%\n",
            "0, 0, 0 == 5\n",
            "1, 0, -1 == 7\n",
            "-1, 0, 1 == 8\n",
            "0, 1, -1 == 2\n",
            "0, -1, 1 == 6\n",
            "-1, 1, 0 == 4\n",
            "1, -1, 0 == 1\n",
            "2, 0, -2 == 3\n",
            "1, 1, -2 == 19\n",
            "2, -1, -1 == 17\n",
            "-2, 0, 2 == 15\n",
            "-1, -1, 2 == 14\n",
            "-2, 1, 1 == 13\n",
            "0, 2, -2 == 16\n",
            "-1, 2, -1 == 12\n",
            "0, -2, 2 == 9\n",
            "1, -2, 1 == 11\n",
            "-2, 2, 0 == 10\n",
            "2, -2, 0 == 18\n"
          ]
        }
      ],
      "source": [
        "def honeycomb2_solver(order):\n",
        "    Honeycomb = gp.Model(\"Honeycomb2\")\n",
        "    x = dict()\n",
        "    \n",
        "    locations = all_locs(order)\n",
        "    N = len(locations)\n",
        "    for (q, r, s) in locations:\n",
        "        for num in range(1, N + 1):\n",
        "            x[q, r, s, num] = Honeycomb.addVar(\n",
        "                vtype=gp.GRB.BINARY, \n",
        "                name=f\"x_{q}_{r}_{s}_{num}\"\n",
        "            )\n",
        "            \n",
        "    for i in range(1, N + 1):\n",
        "        Honeycomb.addConstr(gp.quicksum(x[q, r, s, i] for (q, r, s) in locations) == 1, name = f\"{i}_num1\")\n",
        "    for (q, r, s) in locations:\n",
        "        Honeycomb.addConstr(gp.quicksum(x[q, r, s, i] for i in range(1, N + 1)) == 1, name = f\"{q}_{r}_{s}_num2\")\n",
        "    \n",
        "    for fixed_num in range(-order + 1, order):\n",
        "        lineq = []\n",
        "        liner = []\n",
        "        lines = []\n",
        "        for second_num in range( max(-order + 1, -order + 1 - fixed_num) , min(order, order - fixed_num) ):\n",
        "            lineq.append([fixed_num, second_num, -fixed_num - second_num])\n",
        "            liner.append([-fixed_num - second_num, fixed_num, second_num])\n",
        "            lines.append([second_num, - fixed_num - second_num, fixed_num])\n",
        "        Honeycomb.addConstr(gp.quicksum( i * x[q, r, s, i] for i in range(1, N + 1) for (q, r,s) in lineq) == 38 )\n",
        "        Honeycomb.addConstr(gp.quicksum( i * x[q, r, s, i] for i in range(1, N + 1) for (q, r,s) in liner) == 38 )\n",
        "        Honeycomb.addConstr(gp.quicksum( i * x[q, r, s, i] for i in range(1, N + 1) for (q, r,s) in lines) == 38 )\n",
        "\n",
        "    \n",
        "    Honeycomb.optimize()\n",
        "    Honeycomb.write(\"honeycomb2.lp\")\n",
        "    Honeycomb._x = x\n",
        "    result = dict()\n",
        "    for (q, r, s) in locations:\n",
        "        for j in range(1, N + 1):\n",
        "            if x[q, r, s, j].x > 0.5:\n",
        "                result[q, r, s] = j\n",
        "                # fill_in_nums[q, r, s] = j\n",
        "                print(f\"{q}, {r}, {s} == {j}\")\n",
        "    return result\n",
        "if __name__ == \"__main__\":\n",
        "    result = honeycomb2_solver(3)\n",
        "    "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "# show result\n",
        "order3 = dict()\n",
        "# order3[0, 0, 0] = 22\n",
        "# order3[1, 0, -1] = 37\n",
        "# order3[-1, 0, 1] = 10\n",
        "# order3[0, 1, -1] = 5\n",
        "# order3[0, -1, 1] = 36\n",
        "# order3[-1, 1, 0] = 32\n",
        "# order3[1, -1, 0] = 12\n",
        "# order3[2, 0, -2] = 4\n",
        "# order3[1, 1, -2] = 19\n",
        "# order3[2, -1, -1] = 23\n",
        "# order3[-2, 0, 2] = 31\n",
        "# order3[-1, -1, 2] = 21\n",
        "# order3[-2, 1, 1] = 20\n",
        "# order3[0, 2, -2] = 35\n",
        "# order3[-1, 2, -1] = 16\n",
        "# order3[0, -2, 2] = 11\n",
        "# order3[1, -2, 1] = 26\n",
        "# order3[-2, 2, 0] = 6\n",
        "# order3[2, -2, 0] = 2\n",
        "# order3[3, 0, -3] = 14\n",
        "# order3[2, 1, -3] = 29\n",
        "# order3[3, -1, -2] = 33\n",
        "# order3[1, 2, -3] = 9\n",
        "# order3[3, -2, -1] = 13\n",
        "# order3[-3, 0, 3] = 18\n",
        "# order3[-2, -1, 3] = 8\n",
        "# order3[-3, 1, 2] = 7\n",
        "# order3[-1, -2, 3] = 34\n",
        "# order3[-3, 2, 1] = 30\n",
        "# order3[0, 3, -3] = 25\n",
        "# order3[-1, 3, -2] = 3\n",
        "# order3[-2, 3, -1] = 27\n",
        "# order3[0, -3, 3] = 24\n",
        "# order3[1, -3, 2] = 1\n",
        "# order3[2, -3, 1] = 15\n",
        "# order3[-3, 3, 0] = 17\n",
        "# order3[3, -3, 0] = 28\n",
        "\n",
        "order3[0, 0, 0] = 19\n",
        "order3[1, 0, -1] = 20\n",
        "order3[-1, 0, 1] = 18\n",
        "order3[0, 1, -1] = 13\n",
        "order3[0, -1, 1] = 25\n",
        "order3[-1, 1, 0] = 12\n",
        "order3[1, -1, 0] = 26\n",
        "order3[2, 0, -2] = 21\n",
        "order3[1, 1, -2] = 14\n",
        "order3[2, -1, -1] = 27\n",
        "order3[-2, 0, 2] = 16\n",
        "order3[-1, -1, 2] = 23\n",
        "order3[-2, 1, 1] = 11\n",
        "order3[0, 2, -2] = 7\n",
        "order3[-1, 2, -1] = 8\n",
        "order3[0, -2, 2] = 30\n",
        "order3[1, -2, 1] = 32\n",
        "order3[-2, 2, 0] = 5\n",
        "order3[2, -2, 0] = 31\n",
        "order3[3, 0, -3] = 24\n",
        "order3[2, 1, -3] = 17\n",
        "order3[3, -1, -2] = 28\n",
        "order3[1, 2, -3] = 10\n",
        "order3[3, -2, -1] = 34\n",
        "order3[-3, 0, 3] = 15\n",
        "order3[-2, -1, 3] = 22\n",
        "order3[-3, 1, 2] = 9\n",
        "order3[-1, -2, 3] = 29\n",
        "order3[-3, 2, 1] = 6\n",
        "order3[0, 3, -3] = 3\n",
        "order3[-1, 3, -2] = 2\n",
        "order3[-2, 3, -1] = 4\n",
        "order3[0, -3, 3] = 35\n",
        "order3[1, -3, 2] = 36\n",
        "order3[2, -3, 1] = 33\n",
        "order3[-3, 3, 0] = 1\n",
        "order3[3, -3, 0] = 37"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 84,
      "metadata": {},
      "outputs": [],
      "source": [
        "order4 = dict()\n",
        "order4[0, 0, 0] = 42\n",
        "order4[1, 0, -1] = 21\n",
        "order4[-1, 0, 1] = 5\n",
        "order4[0, 1, -1] = 57\n",
        "order4[0, -1, 1] = 26\n",
        "order4[-1, 1, 0] = 29\n",
        "order4[1, -1, 0] = 8\n",
        "order4[2, 0, -2] = 36\n",
        "order4[1, 1, -2] = 7\n",
        "order4[2, -1, -1] = 49\n",
        "order4[-2, 0, 2] = 18\n",
        "order4[-1, -1, 2] = 46\n",
        "order4[-2, 1, 1] = 45\n",
        "order4[0, 2, -2] = 44\n",
        "order4[-1, 2, -1] = 15\n",
        "order4[0, -2, 2] = 6\n",
        "order4[1, -2, 1] = 41\n",
        "order4[-2, 2, 0] = 2\n",
        "order4[2, -2, 0] = 25\n",
        "order4[3, 0, -3] = 9\n",
        "order4[2, 1, -3] = 50\n",
        "order4[3, -1, -2] = 23\n",
        "order4[1, 2, -3] = 31\n",
        "order4[3, -2, -1] = 10\n",
        "order4[-3, 0, 3] = 47\n",
        "order4[-2, -1, 3] = 3\n",
        "order4[-3, 1, 2] = 32\n",
        "order4[-1, -2, 3] = 33\n",
        "order4[-3, 2, 1] = 59\n",
        "order4[0, 3, -3] = 61\n",
        "order4[-1, 3, -2] = 30\n",
        "order4[-2, 3, -1] = 54\n",
        "order4[0, -3, 3] = 51\n",
        "order4[1, -3, 2] = 28\n",
        "order4[2, -3, 1] = 12\n",
        "order4[-3, 3, 0] = 16\n",
        "order4[3, -3, 0] = 53\n",
        "order4[4, 0, -4] = 22\n",
        "order4[3, 1, -4] = 37\n",
        "order4[4, -1, -3] = 38\n",
        "order4[2, 2, -4] = 13\n",
        "order4[4, -2, -2] = 52\n",
        "order4[1, 3, -4] = 48\n",
        "order4[4, -3, -1] = 34\n",
        "order4[-4, 0, 4] = 14\n",
        "order4[-3, -1, 4] = 27\n",
        "order4[-4, 1, 3] = 60\n",
        "order4[-2, -2, 4] = 56\n",
        "order4[-4, 2, 2] = 17\n",
        "order4[-1, -3, 4] = 11\n",
        "order4[-4, 3, 1] = 39\n",
        "order4[0, 4, -4] = 19\n",
        "order4[-1, 4, -3] = 43\n",
        "order4[-2, 4, -2] = 4\n",
        "order4[-3, 4, -1] = 40\n",
        "order4[0, -4, 4] = 24\n",
        "order4[1, -4, 3] = 1\n",
        "order4[2, -4, 2] = 55\n",
        "order4[3, -4, 1] = 35\n",
        "order4[-4, 4, 0] = 58\n",
        "order4[4, -4, 0] = 20\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "py310_arm",
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    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.14"
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