lmpc_no_border_no_orientation_auto_tuning.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "colab = False\n",
    "if colab:\n",
    "  import os\n",
    "  if not os.path.isdir('../duckrace'):\n",
    "    %pip install casadi\n",
    "    !git clone https://github.com/giuliovv/duckrace.git\n",
    "    %cd duckrace\n",
    "    !apt-get install -y xvfb python-opengl\n",
    "    %pip install pyvirtualdisplay\n",
    "    from IPython import display as ipythondisplay\n",
    "    from pyvirtualdisplay import Display\n",
    "    display = Display(visible=0, size=(400, 300))\n",
    "    display.start()\n",
    "    %pip install duckietown-gym-daffy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Hyperparameters\n",
    "test_results = True\n",
    "N = 3\n",
    "n_from_index = 0 # How far the first point is\n",
    "# K nearest neighbors\n",
    "K = 3\n",
    "\n",
    "# N iterations to consider\n",
    "i_j = 2\n",
    "i_j_all = False\n",
    "\n",
    "# Number of points to consider for convex margin constraints\n",
    "CM = 5\n",
    "\n",
    "frame_rate = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gym_duckietown\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import optuna\n",
    "\n",
    "from gym_duckietown.simulator import Simulator\n",
    "from casadi import *\n",
    "\n",
    "import utils\n",
    "from utils import get_position, my_odometry\n",
    "\n",
    "np.random.seed(42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['figure.figsize'] = [7, 7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#gym_duckietown is very chatty\n",
    "import logging\n",
    "gym_duckietown.logger.setLevel(logging.WARNING)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:duckietown_world: data: /home/giulio/prog/.virtualenvs/RACE/lib/python3.8/site-packages/duckietown_world/data\n"
     ]
    }
   ],
   "source": [
    "env = Simulator(\"ETH_large_loop\",\n",
    "    full_transparency=True,\n",
    "    domain_rand=False,\n",
    "    user_tile_start=[3,1],\n",
    "    seed=42,\n",
    "    max_steps=float(\"inf\"),\n",
    "    robot_speed=1.0,\n",
    "    frame_rate=frame_rate,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "start_from_trajectory = True\n",
    "\n",
    "# Trick to let the trajectory extractor see the whole line\n",
    "env.unwrapped.start_pose = [[0.11699990272521976, 0, 0.41029359288296474], pi/2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = 1.0 / env.frame_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/giulio/prog/duckrace/utils.py:390: FutureWarning: arrays to stack must be passed as a \"sequence\" type such as list or tuple. Support for non-sequence iterables such as generators is deprecated as of NumPy 1.16 and will raise an error in the future.\n",
      "  points_fitted = np.vstack( spl(alpha) for spl in splines ).T\n"
     ]
    }
   ],
   "source": [
    "env.reset()\n",
    "traj = utils.get_trajectory(env, samples=500, method=\"distance\", last_value_distance=1.035)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "if start_from_trajectory:\n",
    "    env.reset()\n",
    "    env.unwrapped.start_pose = [[0.3, 0, 0.41029359288296474], pi/2]\n",
    "    # Why double? Good question\n",
    "    env.reset()\n",
    "    env.unwrapped.start_pose = [[0.3, 0, 0.41029359288296474], pi/2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Position(x=2.0549999999999997, y=1.9297064071170351, theta=1.5707963267948966)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pose = get_position(env)\n",
    "pose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(1.9486294618007634, 1.9308421914242628, '|---------|')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy import spatial\n",
    "distance,index = spatial.KDTree(traj).query([pose.x, pose.y])\n",
    "index += n_from_index\n",
    "startpoint = (traj[index,0], traj[index,1])\n",
    "plt.plot(*traj.T, \"r--\")\n",
    "plt.scatter(pose.x, pose.y, c=\"r\")\n",
    "plt.scatter(traj[index,0], traj[index,1], c=\"g\")\n",
    "plt.scatter(pose.x, pose.y, c=\"r\")\n",
    "plt.text(startpoint[0]-0.1, startpoint[1], '|'+'-'*9+'|')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Samples must be at least: 125.0'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f\"Samples must be at least: {np.round(np.sum( np.sqrt(np.sum( np.diff(traj, axis=0)**2, axis=1 )) ) / (0.6*dt))}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AiuQyyeIXAxg3va2ghs0NWtjEw4MY5RQCoNBOhTFm5EwxBt93SD1boRyxJF1Sat6uv1PNeEPwcDPK4M4TV4NaWRKUesc+v2xdEJpBlQEABPTRucgCU4EIMYpjMq33EFHbJhMDhmHEMA7Y2d7BkSNHMQyGcYpRNGybiDAOg7JEJDITHLUCGmZXiEFbjAPe+a53YjGMYC4tOgWBHXVqUQMBytyQ7y2WC8H/6Qh+/R//GnKpeOLxx/Hscydx6dIlfPnLX5KEbyRMcwZBNrk+r2GJrhCCw3KWsGaWZFxlBquxrpCkdy6aZ0kRP6okga4G9a5hGPh1D70GBw/sh9G6JPtefBeWhyfFcRmGa9n9D8OAucswMgu1ZBxHQHegUorgozrpUkoysEWZA0MS1kII/jnzYAMF5/cFxV1t9zOvz74m9VbsRVoCL5dJsNfc8BwJnYNgSdwYCTlnBJDQVHJ2r4dZ4I+pFOzu7QFq0LMa2jxnLJcLrNdrjItFYy3oM4/DgDlnxBCwWCxQcvENKQQCuGBra4lDhw5iSAMefsPDuPuuu7C1tY2dfdsdLCAG1fixAHw9XJ4Zn6aMs2fP4cy5s/j4Jz6B9WqFU6fOCH4aNWEXBPPuDact2loLuBjEAOd2GvWGKHg0Y8mMfm7knAWjbiiqhs/yHoNCK7I/kBspg2Pas2iYTS2CGoYBaRgQKaCWIp5Od+0++RgoNHQD5s0TmDYpXQYtFHUK5JnFg3aEotvPbLiFolQ16aOYsyZ7WD0WogDUigx2/F7uU85r0VeZZ2TNCzCzGHK9GEOpkSwhteCcEHpdaTxm+4wzODovt+pmD2blNzPe9c4fx+233Y4YCIcPH25R0mX47UslI93J6CCYWisuXbyE73//e/jCF7+Iky+cFoxW6W1pGBxGsHfV6HHtsISijbXlOXKRNRpiRC4VTz19DPM8vySic9UY2odf9xAOHtivzABWQ1l9J88W1nKVJFSHkZQiOzpDMuwANBPOToy2z3K18FR+1ocB0ElmIDoAN+i1Vg0fgmJIjJRiR6yW8+acHUuuzIghiDdKgCbrMc9Zk2sFpeYN6COlQbwYyPlZz2lGDQwMacRqnrG7t0JRLqyMjSycNAxYr9fYWi5185FZEkOUxaB0r/07O9jd3cU4CP718MMPY2drgZtuugn33X+feHlEYoyJUDdwwc1xk+9oVrcyQoz44TPH8N3vfhfPv3AKj3z5ER3LoJzkhqMa3Y4gDAoK5BxHYYIQVqsVtre2/P2I5ybvNelGxsya5CsImhy190JRcDpGRQypeYZqECzcdt5miMKJpiB85s6Q90kxiwSIyNkXhuf54gc8m2/RgyU83U1DY0jQRlLQIgc1tmq0bJORcWCHZBQU9ntosKpjOgIddfCQzL0WadUisNi0tweApTik29CdO04tWbq9ve1fi6dbNblbOy43IVeBfYhJubLFWTYGwR0+eBCve+3rMI4DHnroNTh48IDDCS/FuDDDKkOsm4lh2zov5jnjq1/7Or785S/jmWefwzTNKJp4NkyadB4aJa7f+EqW+45JNhVLPNsekgvj2HMnrn5D+7rXikdrxgcAamkTthbltQby5JiF/T2PNobgnpxl042pQIHkbzVq5rXaAg0hYFpPoEDO0QUJGC8vQNkKpTreaecVb0s+U5R+5N4iSQg/DvYZxpAWmpyaGzZpi7Na4i5CsvECP3BllHlGoIApV6ym2WlhZuD7xTMMgxZRtETi4J4xYxzE4Bw9fAi/+iv/CLfccrMbbZt0/cG181TRsECzFOcvXMB6tcI3v/lNPPLVr+L8xV3s7e7JQnNsTu5tniaEuElJK0VYJzbJgxYwxBhR9DlSjBpZRDUO7PYFoJYcVSjD8Nz1PAuVTplthq8xQ2GmiIpq8Kd8j4zGVt2Y29gamyRFwW0N3vL1dJn3ZkekFl57chdoxtLAo9CMh31PklPB8xjiLcqcAjTph87jI0ly1e49WpWUrQG7R1Z+OAClPGbsXbzoa8aiMuNqg9lzCyklpfkJTTLngmEcUOvsG5RQp8g9cygkUtXxMaCJmT1ZF0PAgQM7SDHiNa95EG984xsRQ8C+/fsxDEkiPv0dG6xGs9uEriwJee7CBXztq1/FX/3153Dy+dNgCLRDJMazKLSRNJdh0IvNfVvP9s6q8tVLZTx34vmr39C+9qHX4OD+HXnYPIOhE1QXRFEXP6RN+kXO2Y0tKzPBw2w1gvaZqL8btVgABEzrtWJTUY2cGjVm5DkjpiieGgvVKqaImovDEHnK4lUNw4axFI+2wjKoYkwIpcyCjQ5LDSvFs5bQH7Asp3k8xhlNahSDWoqLeyswgnq7ljnfpHGlYUDWexqHQQ1G8ux7ihEH9u/g1//xP8Ydt98qm40aONhk7eEA86q7EK6Wiq99/es4d+EivvzII3j22ec8uzuOC5SSHfOqlTEMyROJ5tUb19g2RcE+27syYycRQmzJEkg0ExRf7avYYhw0ephBIWA9zYiDYKENVhaDGfS9Gy/fzi3edHsHZiBlzo6otSDG5MbEjub1tmRiw2j13Yag0Y4Y3kY9c+vaXY99owoUUKokCgmEEFsewrP2Nv90/fTVj7W2JNTm2me/3nq9Rp4ncClYr9fuLVuJvH3O1px54iVLpDYMAygA45g2QnqL+GR+ReQ5dw5MBZHMv5RkrqcUNdFGmiyvOHjgIB544AFcc/Qo7rzjDlx//fWwakwbp5AiSM8rAQP52uZaUcqMS3sr/M7v/h6eePJplJIx5VnWVxqcn58V4jMmir3XnGf9WRu/UhnPHb+yob16kmFVPD2ujGIkYsVq5ZnUe+HgC35Ig+zwsImuu73y5his4XJC5nlj8pNWfsjihiaQIKEkglefmIdUSwWFijrLBI8pCqiOLItbMWFmyWoSS3keiKTCJBquU/Vl5YbfoYKZEKLs4qRYGnPFNBVNDIr3EqP8jEjDZTuHLqDeo7Nw1cp5S65IMWBICavVCtccOYq///d+EXfecVvzICGbk3mEVXf6QBLO1sy4eOkSSi347d/+HexdWuPYc88CgEQDurBqqTohLToxPLv6xpOzVLZ56EY2hkCpkhQy/mLJEmKWLCWTKUmm2ENOCFQT0EorF8uFlm2yh9wttASAzXJuMFAMJ1fjblgnAI+GfPOsDOZWwWj4ukzn6gtcPEuoDWX1mgUjDd2m0bjBCg10tQLBfgcKtdRNfy0oGd9CWrsno7bJjqHoNIuPa9ixe9wEcKlYjgvs6WZpjgaoRTGlZCf3W6J2HAYE5XRbRFlrRiliWOd59gTUbPmWygqrVQzjgEADiAjLhRh0KRgS+LASMM0ZJ06cxMmTktQ8cOAA9u/fj2uvvQbvf//7ESNhe2sLA8sGRCGBuyIDIWwEBBqwsxPxD/7B38Pvfuj38a1vfhuUAnIuiFWKFJjIS8NrEScoa6l6CAGLRdzAdItF3Fc4rhqP9qEH7se+fTuopUg1FAGMuhESWwhshQNpSO4xXA6GEySUGtLg2FOgIOB3rbDsscEONhl8UumiiilueFmliCFwj1NDijgI4dkTMeoZGwYcY2xfB8mwl1IcCiGSxFCMETWT41tiYEkqyZRpYWyMWSlZXKX0VeCJAetpwjiOvtBiSkhBOYkpSWKDgV/84Afwtre+GRTg3ix13pgbTQq4cOECHnnkqzh/4Tw+//nPYW9vF0QB81x845nnGSkNmKfJQzKj1lgEsl5PG+WLw5CQ54xhTGAUHU+hexGsaCNsJBpDkJAzRjHc1OHolpSUuSJ+RCkZe9OEEFOj6wGIGk6aMeSwqR0Qo3jAfRmrwRcgQmFhhtiG3pPZe+NpxTQSkcDnRz/OzSNWGpRCQpasi3quoB69JZmqZbEA/7x5rHrJDo5WAEI99DaXGuRBOrd3dy9hnlaiC6COTYoJjhlT8/CMfSBUKYEGhBXURF5sDRlcJGupuAMCapAZcwFYNDeYg8NfRnsLFLzMXpwATTbGgDe96Y249tprcejQAdx3330gdUbsuNzDnqcJ/8O/+R1849uPukMyz1k3LNuA1XEozWmw3I05TXOuOPn8qavfo60EUJDMaaQm0GFhhL/YLuFivE/zMiSxocYCAKt4BFcJ/0LUz4WgO7O4/4Fi85iDvMys2dZQgw9qiAGM6KyBUruMu06+pHhdgTAgcs1u/AExzMEI5Jp0K8iOdM5zATFhnttiaN4SgQKj1ILKcOqZEYkIwJyzJ06KUk+GFB1bC4FAqHjXO9+JN/7Ywxqaq2EIQehXLGIh0zTje9/7Lj7zV5/FPM94/PHH0ZJDUjRhybLeoyfzBj1kNm+ygqhABI4qYmSAKuIg4ViMSY1HAaiiKm1IeI+K3Znh0PnhpdYhqApUK+CoteDixUvYt09wPgSgclGcVz1Narxq9wzZCkyEjtSH9kEvzMxIITpu6iW+sPnXjLaE+QDM61ajrriErwHxWiWKIPUUAwRnhUIcEsWSG1lL/Mh17FzGKGjYpC4UjQrFcNYOSmAYfgxM0+SbucETEVH1LkijFeN5Q+CFQABkHgSKiJF0gxRnqNSCSGKop3lGilVhLoX8gpSx2nuLulkOQ0QISUvRDbKQcXRRIxLmEGXCX/3VZ1Frxb79+3DjjTdiZ2cbD7/+dbj33nsQeJPdQUQYxgG/+IsfwFwyvv/YY5inLInumCR5ykIHDCFgjBJ9FQi3W+yHMD1GFZ+60nH1eLQPvQb7922hsqgK9ZlTo1hxZ3CFl8fOIkgpqQfZBrJhR0VeptK5+t09q0ccg2BfzpOdsxQ06D1SkJC7eQdwmoifj6A4FmCQUU/4ZxYjOQ4jLME1xOQiLKyYIpfaGZCoPEx99ige2mpvwu7e2sttDSoQLzy5+tj29hKrvRUWywUsmfGmNzyMX/uVX5XEl+3M6tVXEJ4+9gz+9E8/gscee0zGl7tEnWGMaKyPPGdPLgKyOaxWawyaJMm64dWSUVg+O6g6U/MUGYGSGCw2ulwEOEjIZ55RbfQqCy/ts2a3xFMTGs9qtSeVb2BPETNDzuteZ8seA6YNoc/HzdAGhREaJAChZlE7b4xNqc3WVoBAQgyoOW7VXhZ5RbIihu73OtpdT2XrPWe5rm4sXFEBrwI0B4SrpsMIHVwB5TS3VFmidt6SZ5w/f86vJfzq6BuOVViGQLpubJNq1MlSqrBEVGDIPElbb43dUR0KknfcktN9BGmGjULaiDDsvho23ioBKwpiILz//e/H29/yNt200MZLE+rznPGnH/4wvvGNb2LOBbkWlNL49EYPtfxQiA3CZBYK4/GTL1z9Hq0cgpMZT9Vmh01gW1QSgimeOAh3tLKysAEXgmDDkYIUMxj8YBlfgJy/WuxnaCC/VeoY5jhDwigjYhueaUZN8OXiSbgUk4cXzopQKKJyRc3ykm2x2WEhkUAc0Mys8V0Fa2OQTmCZtMZJdMEY/yP3YXzKu++8Cx/4wC8Iv9g3HB3nyjjxwgv4rf/Xb+HEyRcQvRLOEpJFPbLqSRzzPABoSCfva9RiBxAjJlXqigMwS5i9WC4wrScfO9lMGptjzlZ3Lh7OOCZJthAjRChckpBnBiD3IGpogoOa151S8zSMBiQRElriiI37qbg6KkASbZj2hnBgdfdEl+3uZ29ohghoZbJuPIncyPYMXfNSdfr77zg2zL40ADPUtlw6jFcqz4x5AMesG5rbjJP8jq4napKhbgwtmaT5gqD3bCXhVv4ul5bzz3PW9ReRc1GPcZR7LnBIp0I2M1svMUSPTgwSEu6zJOC8qowk7L1c9MjWqNAWWQexGd7CjE9+8lOIlPCmN70RkYwzLY5ZIOGXv/9nfgYHDx7CZz7zWSBDIQyNXrqqPSlkygqPJMXHX/64agytTC6lfaDqwLNO6BfjIrJ7dhO343wSiRYsWDPHiQSsphb22E4YQgBV2jCqUvcM9WDFox7GQaAA07Nl3XlV9ahnG+SSvezXjGsM0SeLJUrM4Eo4J1hToADSyiyyxEptOFfOzduthk9qQYJ7HNRkELkyFoslCIy777oD//Sf/s818dAMrCWCjp88if/qN/8bnDtnnowkweY8O0+Sa0VIA+Z5xnKx9AUHyNhIZbQY4jxnzNkSZI3oXVk4ycyMaZ7kdzWLO6oak4RmKkmpSUFAKHMKHqFkVk/ZjEL1BKQskKIbVQUlSx4qZqqej5nOHrsNIeq8q81QViPny5KpUMNZG7c4EAAm9Y516QWBmCJJJrwP9ftDBIPImQg25y2acZdb35WsEvEge4OjEwVW90EQ2EHuSDw0sko1TST7eeH2HqUylsulGBXVbGWw630EIhQQ0kBIiVRkqJMZJLmeM0FYKqtAnVCR0rooyfpbLuR6UdkGJo3IVXQ4VnsrKfrxRJrccwyCpw/D4IawlDWGcZQ5AsLe7gp//Cf/Frky3vrWNyNYBaOtAQCLxRLvfuc7cdMNN+Jjn/gEnjt+AmkYsL21jdV6LffURdeRYxeBvLypvWoMrRm0Uqp4GNxwoFoLrMyPmcFWRaXKUGZkzds079YKEwDZsS08NmNkVBMPYahueJ99cqyvOPLKMK7g3AyseSkhavVYFQDdsF8LmUk9G6tEM8zZcS/XXxAO7yY1SvDcRIRxFDwthoD1pAatVlBKGFLCJIrvWK9XePDB+/GP/uEvYbEYFWbQxanz7dSpU/jtf/PbOHnyJBbLJVKUEkOQbFaWMRbPWO5rnmeHLqxKKpfZ+cU11I2xMNUyYWRICDzNomubYquMc9yTgVrNk2mhMHRcjH8r0aos9nle630YsZ5cUJxiUCDUvMCq55UN3iIL1vySeDxV2Q3GRGA3RuZNNuiAfQ74xqIeI7Pht2r+NOJwb9Txx5bQBSwRJ+8fxAgIWjjSsHXziGUJWHWYVpGx+bE9Eb8ZezcU6nGLka1Yr9eY86SbuTgqVOWd2RwWKMvWUpMhBcmGGDVZbcbXKjEtUWt8aEvEAsIwmfPsCTDT6Njd3fU1EUMAoswZyZMIrGe0QrEZ4uHmbHxjGcOPffSjWK/38Pa3vxWLpJxxiyRYbMndd9+FcfGz+L3f/0NcuHgRu7u7Dl3Mk6jvTdPs9yv3//IluFeNoS21+oIlhQ36SWiDZTgnYBnWTsmrf1jdUZuAt+CnIgunqkWaHTVBEwAeGll2FMDGZDHDHDqMz5JBfSZW6CWEWJVeNmf3iAFZeIGDe+QhbeJupWpFl3r21uojRPF41yspj5QafdWmBTAuBIsd06ATmfDqu+/Gb/yHv47t7W33+CgQKuTcFy/u4Xd+7w/xxNPPqAYCS/23GlMbTzNyOWeXfLRNjlEACkgpOO4lXmdBXIg3b3hcrRUpSFVeSkO3kMnfo9GHiGSzEhqelZc2GpNzJUNFqbPwnLlxcrdVmWw1ZU+AGQyFIFEDs5lZUz9okAqTCKYw2PWSDUKw8J00FBXPWMqmPSGrf8jCS+ZmZDXxalAEmMEksBDYIjy9Lyu0UGPJCpEQ4DCLmVTqjLhDFlUx5m7NWWIJVKGsMxm7YcC4WAhcRTK/XAeaNucnFV0DNYNI9EIqJNKTCkvT+4jdetZzyHBimiePKGE2wPBWbmp2ljMxOyGc+wyigkt5reNqCWSBnQiMNOq1WTj2n/7UX+D0C2fwkz/xbhw9fFCACR1qqgyKAbfcfBP+8a/9Cj70oQ/huZMvYJpFXzotI+Yswt/mLKzXa+/EcqXjqjG0Mim76hiSbKvtauLVQjfiZnStOqjkjGEYJXGAFgp6KMNtUdrLQAR4ZvdEpmlCicVLc92Dw6aiVdRiB9vJahW8FSyJITM+gYLveEDD9Eouwlzgxgfujbsl+GA7c8mwVkSlFsSUsLOzjXz+wsYGpI/peFcMETvbC7zvPe/B1nKp3npQL4d8Un/xi1/Ak08+iRgCMpqKVAgBW9vbWK9WIBKsd71eY7FciMr8YqH17UWq0NTDNM+8lIJxHB3j7KEf0wIlQDQODKLRJJm1EXIpzFw6T1Uws/V6kkRXbdlfg5Xm2ZgpWUU/unnmG1qQ5JoWAti49YkWu1/DLcmxVjOBFnJ3Xq0bOMW2bSPXOW2fb78rd1MZ2sonbITyMOxU75o1nFafVWlo1F1bIRQ3aW2O2Ppq34cY2+6+LIErXOcZi8Viw1vNcyszt+skFcYxHYpA2v7IzgfxRGcVfCIiTPMMQuuUklJE0GIjgo2dqcg1GEHmR/F3AgDLxULw0ig7EiEKYUQTdAYBrfZWyPOMr3/963jh5Al84AM/jxtvvHEjMgEzKCVce+01+JmfeR9+7w//LVarNXLJmFWLmQphnmYgbtqGKx1Xj6ElzcxWIa7XKqpRHnaGpppkXEER8bB+TZYd7LK2FEBRDReqL9q+bNcgBQDOe2UF5W0+Jq0Im+dZ6tnBqLmiUFGeLjeyus7HnHMXRjZjHmNEGFXVSKEHo66Y5xZDbB41M0CtxFOI/xW7l3YlCUbk9fa++AIpV3XGu97xdtx7z6vb+IEa9SckfPLjn8QnP/FJTNPs3mLOGTEJn1Hgg4JSgZQCYpLqtjToeGg23HQJDJNOMXVMkE3hGxMbMaNsehQANpKMAJxSgwjvRiFZ+gAezXM18ZLW502gH1Xdn/vikGYMLZRnZimbVkNUuSrDQHDq/vOaNZBw08bRFqjMZLB1MKCWfAOhEfQBdxgcS7WfayTmmJ9r4cpcYACFxPM2kfh+jlmTREla6q9qdsxoa+12bV5CgE6do8Y7DSGi8qYEYAhBesKhNTI0I8wwMZ/iOQJvdmhQg3FvU+qqGK3bgfBaZW00z9/KswEZv5hE0zl1bAZzGmwjAIwqplGf+OuylocEBMIPjx3D/+df/Q/41V/7Vdxyy80aIQSEKtS3EAJuv/12pAjsrS7BCqLmaS1CT8orBmNjDr/U8fLAwr/Dw+qgowpcN+oNu4QdAMdZZfFaeBIdq9Vf8owmIDxM12VVQy0JK02MceszJqTlpgdgXqcR1YdhbDXq3OAJ2xH9WgZzKOxgXqqxE0KU5nKXSz2WLMbNeh2ZMbAmj+bx2s+rUsGGQark+oTY9vY23vb2t0tNegwN42bJ437hi1/CX33ms7KpqVhG0mcXQ8Hu6QhwyVotUxTQYlQuCLFpCtRavRiDIVxnw9slClDvCx2BHa0E1wj4vVdoDJSsrX3ATcquL3G1go42doxpWktvKMc/Gy650bm1817NGFgW3r1aGRgYZiARAgNQoWw9J+u7rGB/BoMPyKMP9vDDjLhsnE2n1rwwUkC4rQi2qdH/y6/DG59jN7L+rFzh2gbcMGP7Z4XQDPf29iT6S7HNndq6exiPPGryUKrO2kZmWrAxRmnrpOvPC5A0uVq5YrVeoVap2DQGkN1TqU0lzUrEBT4qmKdJDau9l6ZdYJuWOfEpDZ3nLWXQZ86dw+/+7ofwzLFnwOigvyDvY0hJxJDVe7Y8wmJcOBMjqcPwsvbtZX/67/CwsK0PYXrDYNnPah08Fa8zIv9iXDiNyRJVVurJWtprYtAtISUvomqFVVZ6iNG3egNYq3TPNK84xOhhuP0854xpmrSyrRldMBTgr/4509S1kDwNaUNvoS9TNQ9cwPfBs6tGIM9zdhaBUW5qzfjxd7wdhw8fagT6KkR2JuBzn/88fvvf/Btc2r0EEdrOkpyrYkRLacUHwzBIyXFshRa1VGdSGAzQuoh21JvLxsdgAks22temoGVzQGCXAQCJcdZnMK+ZAqk300j7ci4lmXdGdbFYeCa7p+KQRkFc+9C68ZEbpYj8+4DuMZW9gwUbTcWwUTm5e7sEkkiDG2wh5970hjeSqpflKGzxB03KGbZr1qVhwY2K1UdUihep4TdFOcX8O8nDUgsqaalvtPZLGYaVWCRo//W6GD5uIQpzQ8vp85wxaTSYs3TctTJxaCQ7DANA5M8WQ3RZyUBB1lXOyEU0om2N2Do10SUbs6BRnhh4mTvzPGFWnQKrqKRAOH3mNP7b//a/w6nTZ3zOiMYCQDHgAx/8oBRf2IZbpX1OLsVZCCbWc6XjqjG0tcruBsNhStOitVlkXqqV4LK+xFnpWpbZNolDC7WZJTy3bg3mvbrnic7TYzmn0WasdNbOVUoRg8uledfUyj/7jcEqyIiawlHvKRkXz7QUQui96uheTS+GbloAUb1h84p6kvcwDLjmyGG89jUPONbXED7gc1/8Aj78kQ97eEYE5DyBOYOpIBfBofKsnoven3kzNral6ubH1d9J792bkTZ4xjYHa5lj42FeZAgdMwRA0my00ez6qGNcLDShZ7BNlA0hRgxDwjC06MTej9DOdCy0wsn4seZJ21wA8KLNlmSiOtRQWahl4IZ/BpJklFWQmT5WIK3ykgycbwQNVpK35BbN3FNY15F2kP1e9xvm1wb2YMMdDPO0hVyhfi6Re6+Va9uMWbDUFKMWnOgG23nlkoiSdz9rRGiOgeDMBC4AkRScWOTJuhZiSuputnLpkrPKM0oRka1lu6aVYcv7HZQy2UTR8zzD2DvmLVsxRkxRk8kVi8Xg8qZpGHQTFz3ZL33pyz5PbYMFgK0toTF6xKxjEWNEGgcRsekrXl7iuGowWtvt2bxQAMzFDZjjLRoimARh0+esbsQM/ySQTwgz2NYbXsKZpvJl4t+G84jXJNcwARkA7vUadSyFKN6SQQnd5mCetXs26uUGbhitELirc3MrCTY9pIRAQYnfEhKv15MaRfEI9vZ2YVqhXg2lk/b+++7DTTffpENrixd45tln8bGPfUzP1ehElgBzhgTwIu+UwZ6gQoC3/IlRlJgcQ63mrYdWJq1hfoypU/NS0e1ohkMWXi7ZGQ8hBn9/YpjEi5mnST1qnTwGRYSgCbBmxA0HNA1W2zgdjlIonMEdY4CF/UWEFEyMvbgkosEOXiACY4eYJy9BK/lc0BBe51lQ42EJPIcjQjNAhsuigxKaeW0Lm7m/rvzleqlBmTUMsBZrG5PADbyOkfWSM0dnmoTjTFpAYAp2RrmSXILqToTmJTt7iCy6qhvMnjzPIJ3blWcvuImhaRgYI8Mqsxq9UqiM1iXEoDhLeHKMGMZRNouUsJ4mGLY9jiOmefI5v7e312iJOePkyecxTzOGwYptZIyXyyVuvOFGPH/qDAJVMLHPV4s6HWK7wnH1GFrNCLAaI2njQaihbuqgqtE1wnLNjSDdN2usWj9tk9qSZFyEqGPUMMuIO5itC868RwtFxmFEoMYhrEqGn9XoGXPAhKrNA5ZTdjQzS7ClBhUYRmbXEl1WQLVL3PM2zipzxTgqw0InTYgBVITfu1wucffdd3feGBzDvrC7izNnzmG5WAIoamQCSgFiZA+jcxH2RCmivVC5SqJPW52AtIhEN5flshUvWMVNUuNvVWmS2FRZxKJeFndCLLox9h6xY4B6DtsE+8XObuhaYYcsIKG8xRRx/sIuYholTFa8XbW5bD3JppFa8Ym4qHBj4SFzAEiFb+oGdgqQ12aJdxmDVCZRaMneftJbKSog+GjWUBS1Oq/T7g3mbXklnJ1FPm9yj25tIQbeElNqseV8tUN32QoZBJbJc9YoTDb3UfupAW1TMh96QwZS78GcHmnfJEaYKaDWDEDmRwgRKcpYmnypASGlFOELc1MWm01HQ4thWCGH4PfV9HXzLM1OJXE1+xjm9dpZMI0+2NpTnThxAo8/+STuvvtV8CJzZhzYvx+33Xorjp943teyc+oVPnR62hWOq8bQWqJHcX/FktSTRfVEjxOooRoFqXEzqyVBSMJtC1mZreRPsb0qHnFWigBHI8grRoewEeZbNZl5XP0AA3Kv5qW50aOGsxEREHUycHVBnFKEMxoCgZTMTYHAkyRXDM80A2tGN2fxNmJMqKr3OmsVTQSwvb2Fe+65V36HJakVKIIJOHH8OAgy0SWrXBr2xDLppmlCghicGCQsotoWvFemqVdfa0VIrUTaNi/bXAwLNIUrAJiRPVrIOXtC0zzNmCKoyPj7RkiSrDOvtGqy03Dp7FDNZvcLMLBcLlCqLGXbVAmaoNI5KBxqlRGUOFfkO6lAFMWaAEsIEMOnYwYuoj7VFUSoc+oYohkT0y5wpwHsuPLGJtNtKtaeXKZcRyFzjFrmORO3eVTFKzMj0Mqz9RyKV1dm18mFwj3TtBZJS26ats1T1dPUVortEJqOqxh3QkLwnEbUMvGoHkSuEjUU1SemEITyRQTKKoBEwv4wnjgApGHQ0mhr2NnDjNzJZwokmYJAFYvlUhyAJPPfqtaIhMd95swZnDp1Cq961V0ozF6qG0LAvp0dj2rGYWxRta71aX75duNXDUYLai9MFmXYwO/M62jwVZuoAJrSvc9GcnxRigQsBBNjNY5Dq9vukmHWIJDRymsFHKeNjLpXmukkSINK8nVJLBfJ0EnsjITOEJuyUcllAx8KUSAJBjwR5+W/BMSUsNzaamOnXgmYsb295aWbDIC0RHieZnz8Yx9HLgW7e7sopSLPVTFfAnN2T7vU1l9NjIZMFUlaiCERrzr4GMUg42UYeezq2YuKSM+qUZu1lNOkJeecXZym5DZ+DRef/W+vuNOxEQ+jbQA+/qVK+EuEPW3y6ElQT+508ncKu5j3DV3Mou4mc8oSK+pcuxdJXSty10VQr9giMMdcawNSJe1UwdSJh7PhqnKTcq0u8dXBU25g1QjKOKiHGbouGe7EmLfrrqkK4TdHwyKoHo7boLn5AMITYpaDGIaENAxYjCNiTG7IZY1NYFTkMqOWGaSsFYO8apFxjEHKae3PYrnw+wGAkjPW0+QtcgyDNu65R4DjiGEcsVguW0GBblCWazGHxyq9vvzIVzDNs7OToJDPm9/8Rhw9fFA1POBdXmQu52afrnBcNR6t7dKlmoxbC4FsgUAxXLKSPWoUGFBrzAcS8e4eHDdhXq4ijVYh66DX5AwqsW+44uUYZYrJd3gLcUMMIG6YX2DyyenhVZVQyOgxjqfpwrRFVecmTs7iRojhVVWyorzhOWfM04xpnqUvWBYdB2IRonnfe38alQsiqaGbM0AsfZKKlZASUhxQi4kWNwxtIzGoDApLeK1WK8e/QwgeukeKyJxVkzY1zDUGQAVFLLiWcJscg7UKPRPuqFwROfp7JzS4wjYPtS6Ajp11mjXP38pz51l0b6Vb6UL3pGZshK5jPcfQFLq00o9JIiCgRUUAYG2/Q+fBEsHnI7MknNTSuAFmbglS2YAN24d4yPZs5jDoKVAtwgu+sbLtFuhKeRmg2ETRW6KtwW7USc34urILcnNgUopg9VGSVhramjJMmdlKXpWH7DoEWtJs7AJdb7lY91n5kwbB2RMIIQy+ViX5JEJCpTaIqqdRkW4Qi+XCIQxz0Kxcds6z/9uV+XJjURiuvlwuATBOnjiJeZqxSNHhFUB6or32dQ/hE5/8FEqR7/ac7fwj2o1fNR6teDWzswjMK5knoYXM04ysu9C0npxa0VdkWOY6aoIKEIPVyvtaFYd5BEadIbSd0AysqcIDDYOxxEWfdTe+Lim8YSGy6RTYhM/GL+0ms0njGSXHPBPrROA6DuANfuD29rY8i55HJrSca9/OTmfs4bvyZ/7qM1JhpRJ3lnSwjgNWNhyUz4ku7DVtAVDDl+3ZLMFQ1UBYFDGtJ3hg7jiWGBf3gBTzNjFtL76AEuK1ymkYRMVJDHvDx5itaMH4k3aOwT8zDEnCRlLvUP8G4J466XMGgw90oM3bA0x/tGG27lXqnLBkoHt+Dg/A3yG68TCjR5QQKCKasfborb0b/Ybiluwl36wOiev/QkJ62wDN8Bu9zHIIfh3fsBQjDRHTPCHnWbWN2aM0u3bbiIVeV2vz6Iw943M1CoSSotG1oq5DZedk8WZzUepfbWpxAsNZeyXl5SbxmNMweB83o2pVTaLbJpNSwqi9v2x9gU1lztT7giaaBSopteJLX/4SAPKNyDzg++69d8NeGFvFNo2XO64aj3aDlwdjGagXgwDkpsbePBJ41taMihGKqcigDmlQOTPrXtm0DeYyN11U+889jRZOSZjKXmhgL9EwSqteE7WoxgFkkp9FFYi2Gvt+c7D7th5StRRXVDLPMecZIRieSEiabR+8t1JLrL3h9Q/jphtvdANnC4pCxLFnnpWkAqqGS1NbqNAeabpATcTbyP8G1UzrCYvlYiNMt88T4FoJFh1YtGHhXcnFiyoYrSqu1KpFGarApjxGsE5oG4uSLYCWWROCbxrW+siOWiEwQAiILGpXMq5GxeoaFGqG3EtIQ+OWmn1slYs6tqHTfe0wezPMJqQtxqh4MU4/53UP9JCcUDuvta0Ps+fmLAT1fmMwqljXOgfmvQagitoZkXnfZpjloaKWrJMa/gLxxEkpWXZtK7WtutmGKDejonqAz+NGX5SITe7DmA82J6wFueQA4KwFoRDOEB1iKzKWyDGrsFFl1q4cpokb9NmbvgQAFcjXzSYEF6IKXfTDkL6BDT4peOqHT0kUWTc1V7aWW7jrzjvxvcd+oNBMi6J/VAnuVePRUlAxXepxWfmefU1ooi5uzHQ3d2HhjcoVZR+Y9xWkOMCJ96bCpQIoBguYcTTP1EIjF/9VfMYG2uhdtsBE37agg9Uan1S9XlswtqtblQyAy55ZwfpaEEKnC1CrK8yDW2Z537592Nre6hac/Dn+3HGcPnPGdRys9NTESFryoCrvUI2FbxIqtqOTGt2iAeBKX16xxqbvKkRvK9yQfmSdOA81j7E3QmCrLrJkSqNNUbh82naem0cQavBIQjyLLuQqjfblyUoYbALfGGz8rSlkcwTIQ+6eFWAeb3uEFrm43GF3zz1U0xYCNmADG2O5x837NK8QBiF0n5fP9M/X7qnvhGteud+rXiUqpBO6aztso+NlCeiiOLn8XTwp6Z0liLwku3HEofOEXfOXlRZYWbi0Uvyj69iogOqBLpaLy5g7soFYZ97KLeGcFYsFt7GzSCjF6Gpi0I311KlTeO74cYdtzBlaLpe47fbbxZ641oNET7ZxXOm4ajxaMBCB9nDMGwswxAQTwpawXHAowz6leSJpNaSW3+qCK7mikHVUhS8YX0xKXrefmddrGrTWbtyNCKpzLIkICGhFEmi4spXHMjN4ajs+6a5q5zDPyZI8ZpSg4bBgkgFcte98Kcgm5KLhFQHYt7WFm2+6UTy7zuiACM88+xyOHXt2IwFYWTYksnHX0l6qzQgZBp20vtza51g23LoMW/QgOgkyFpYomPOMUlUXYgOvbFikGFQZzwRJosQQOuwtolJrLcIM1VVlZU9UX7h21FKwtVhqbfoMRvTxLFykkSPJJks0yLwgCRmjemwgRgwJbO876DVMiMVU3KhCkltyRIKyHCypWxGChdwEQpQ/obX5ZmXXGLyhUx8ggrPCKMCcfQpqpB1C0OFkBpMpkgn+anBBbywF8QhukNk1keXabuBIKGq2Tiv0+RFQOSNAuzRD9RKCitUgSILLoRb1mnXOMaAyowBRQUyWsCPn68YIb/lUa2vQyfp+WZXtplnBZD2zYcNmmL2lfBVtaRMcYlaBomlChGxeJ0+8gCefeArXHb1GjG8HAV1z5DCWiwVW0+w6J9O09uKkKx1XjaFlwxs1vOGNPzJ8fYKM0WQOAwXlOxKQABMZEUPHvlOZQTHPygylLXjzSgz/MvnDQMYYkEaPLlxsibGpePGDeVFeTqvntBDU6GkWaojBh3twvZfR3xsp/1DsM4Fzwc6+Haz29rRtSMHW1hbe8PDDPilkkQh15+yZM7JZKEwiJbONkmZQw+UiLzaOocgE99JZNI0HVi9TMLWmgA9AcE4NQb2qj6GC2NaAr9HCquJk5h8YLszdOcUj1aRZkgRVjANm7TllRkeKL2YsxgXOXdxFGpcgCjh4oGAMUjor7yGgcMCFi2J0trczRt2QAKDwGrUmzFMAEJASENMaVIGSZRPIqGBeSqUaKiIXxCiGGCpFWHgA0QCggjgjBKWnRUg1FcnAOG6soTfACMRQV8TD4b4XmZVuBNvIzaDC4AJswhQwz65vbtnq/Ek3nBCj9/AT4ynQRkqDyAWGEX0DxqpQBavmg61l64Ihz9XW3jiKaFDSwpUGFwWPIMWoCuVxg99OKq9JaaPai5mR1EO2ztqTJuFiTJ47IJ1f69UKpiQXiICQ8PTTz+Dh173WNx077rv/PvzlX/01Lh0/7gm2GCOG8d8Tj9bpGWiVJBYNWbYa1MKtPqnE1OqeHWJICZlUGb4PjyqbPH2XaGqG0cJ000wopcgCIFOEb+08nCCvFCYiI4zLYXX5CHAtAHs24+BBNxHbfQcafAyksoxhFAkjo4/jABezVsxKSn5nXzge3hKwmmb89ec+py2vGWFIiDUi57XgXFplZ2yBYRzAU6P6TDxp4kEWjyWrLIowD8HwbPF4tXNwh10ZI8SggyEMmCfRkLUSzJikEZ8VnpA+f0EBqvJ+dWIwZRASwlAwDEAkBiFjCDOY9zDPN6EE7elGBHBFwIyff+8+HDm0C0oBxFtgznj0sYpP/kXFOAa85eEV7r13iYCFhtmMp44dwZ9/+iy4Vrz2oYQ3vG4fuBaAJFRdT8An/nzG8RcCbryO8O53HsbWzujgaqAFvvHNFR756mkc3CG858dvxtGdAExAyBl5dw+rSxO+8vlT4BJw5PCIm29cYpr2UApQMlDKCs89W7DHAWkrY9zewpqBCcA6EGZEXJwImSUaWI4EGJQCBnNAzhWraQaFgCEwAkQpqyIgUEFhwpAC9uqu47zMFVvLCXdcn5FSRRoCRIOIEVLFseMVx17YL5sFF4Ar4iKiZJWuhLYYAktkyrKqg3bCBWSYSmkUshB0I/fCu8ZkoBAk3AdQYkKMIr8IQOaTVl2WnGEKYZbME0w3iWesibtxscBqtZICFyJM04xvfvNbeN97fxrby4XPXwbAteDI4YN49rnnUHJR+CKh8r8nHq1heSbyIYaldUgoNXtGc86z47MuSELY8LCCGuRAJOLNLBUo0zQ1o5itMqglXADFJYOS7in7i7JkmE0OI+FzZMclzTtkFmlGq0Czum3LTPc14xZOm8KV4YkB1mOpyt5QO5YFA5d2dyUhpt7HBz748+K5u1QkaTFBxAXVri21dMUFcKzYNplpnpx9AYbzXK2owNTFbPOKxjFVY2bPbgkRS9JYu+qiTRNTkigmJiGOW3YZzE6ZGWIC5woKKwyRcGhfwU03HsSZs5fwxDGJZB5+4DQevHeJm2/awpAmBBQsBkaJA/6L/+oinj8/Yk8paWOMIGIcOVxAtMbWuIP9+wEKjGPPA+CC/ZjxwOEBN+5OwMUVDsaAtCq4+VnC+PxpLCrj3u8A910MSPOEuGbEiUF7jB/7QQbvVhx+gnH9o4Q0F8R1RZwKwlxR1xUxVyRm4JN/d2spE2EKBDqwjbI1Yt4aMS8HTMsFLjDj+yd2cYEYN736CHBgwKVlwsXtJU4h4S8fPYfTYeFZfqEDVuzfH/C+nyAcOVxB1PQuKgV87ksZz54qqAjYWgT8B++ccc89W3js+xfwzPE1Mnawt0544smCuVQURJgOj0EWOTf8v4IRSaARU+sighdciMHTPn/MSgdTpkGUziDR9BW4NXc1KC1ZvoEJJUs3iVorpmn2tZBLwRNPPYXX3Hvvi8b33e9+Jx797mPSyRcEosbhvtJx1RhaH4ggvYIEjG3ZZiICB4MNulAXlrUubnC5cqtHpiY6zbqI7bAOARtQgN0P5HoCfIuGbaXaKnWYpZxXDatpGJAETl5JBjTsU64TYb3BEODG27znqBNFxkRhCIreBNGglHWn2zmGgEyEAwcPShjnOJ9c/7Of/axQdbQM0p6hVNUtDU3LQBIJzTgaG8MEeSy6iFE6BVstvW1GQDPcwzDo2CRUrZs3D948F66t51WtFcMYVe9CSlD37b+En3/fiDHsYmdfwdEjBX/zrYt4+vg2Shnw6ldt495bMuLeBYxnMoYVI11iDFPF+06ssD4TsDXP2GHCPlzETi2477+sWOQJizUwThVpxfjJSxX/Yl0lOP/8S8/R99sXT8lfNRHKGPxP3Qu4WAN4DJj3j5iWWyjLiDIm8JDw9IkJjz83Iy0D7n/9fmwfHMEDoQ4jkJbYq4SPfOoY9nLE7bdt481vvhEI0vqnUgKHiD/9o+9ivVvxwKuWeO29N4PmGaEAMSdQLvibLz2GC6cnbFPBmx64CYv1hLS7xrg3YfvMRRw8v4ebzl3Cdi4Ynjn+omf83+jfl0LAqUA4EyPOxojdc4xrP8IINxH2DgF7BxP2DgXs7a/gYi12CDs7jAdevUQaTuGh+xNec39CxYycI54/scJeuQ4f+rNdaKs4tO6+xskVaULp2CC4qjF+rFM1mJG5SasaNm9JMKNszbmKtKJWOza4QO0LyBOrnnwmckGrz3/uc3jwvnvNIMDajC3GBbaWS2/Lni3P8TLHVWNoGZbHqp7VpBDAuTjmWaANF7XiSAoElDvL0elWADYgBphiE29iqIAYOkqkBoA8HHY6Vwrgopljatn4nsPr3jE1NoSVrhqtyR7SSn8t2SdgfELkCI5wg1pqQUqq+s+62MC+SwPwiZdiwB2vugP7trZdQpZsUAE88/QzzWgGgOss3inIJw9De9mrJF7RUMjgj1Iq0qj3yRWBBo8eUkyCj4YgDfigSUWjAtWKcTHqe6lN0CRYh4k17rz9WmwtzuPooYu4dv9hfOdPTuG6i3u4/ULGT39lwnDxAoZLGfFSxVsvAv+z4xewWGcc/lbFOL20N/G67usVEXZjwG4ImJ8OuDAGPD8ErFPE6mDA+QMJJ1bAKiUsrwkIBwdMY8C0HDGPAefKfvzNY+cxxQHX3rqNm+8eERZJChsCoRbG176xhxfOZlx3dIk3/tg+l+gTSU3gu49ewneGC9jZR3jLvQdw6AAQwsIlD/dWa/zF0SOY5oRjRwfUa5cIsUrnkLQfiFv462uew8VLAXuvOoCtt92OlAgUA1LcAiHiD1Z7eOzxNQ4e2MLwv34H9u1o6EsE5oDHvnscv/uhr6PyJfzv/uP34BCtMJ67gOHCLtbHzuDLf/YdbK8Y+9czlhcv4UipOFoK7jmfce3nK9JlQ10BvHdB+F9hxomUcOFcxU0f38J0I+HCkQkXrwlYbTGGmHHTjSO+9cQeypzAdQZFhRbiJE09SYTQOTcYr58vtmaaYyUa07VzvMQGGCOjIs/CvwckmpSOy9H74FWWf1srI3fymHHh4kWcPXcO21tblqEHAdi/bwfv/PG34s8++nEdVytFvvLxtzK0RPQkgAuQNj+Zmd9IREcA/DaAOwA8CeCXmfkMCej5fwfwswB2AfwTZv7Kj7qGSQGyagEI/mj6pHC9SfOswI1s7jSl7lnJso9dplNUfiR0N60EAB25u4MQNKTOyI67ulK77sC9kITdU1EurZ8XLcsOVamSrLXK8qkn6Dqjlwl0G6ZrEAmHRj0KUfoXhRBx+223Y2dnW+6jViAKtHJp9xL2VitYuxlhFDCGQfjKbfxZNjJLooXg3XyFcZHBPDg8YLgfoO9mZljeoJaKOEQvMgjRqrzgvMPlVsTddy3w2gdvxBgv4MGze7j5G+dw7WfPY+eppxBKu7fyfSDvBMxbAXk7YLVY4Ng28PxiCewvWG8NWC8SdscRpyrh5FRwas7YTftwcmZcJEZcbgNWLcgE6VarwkUMhERg6y1LDLpIPu8qAQEZdWuJQBGnXsj4zumplelW8egKZ4ATTr6wwkc+OoEspxCEd1qLzNfdXcanPn1KMEvFjgVOj5hrAKPgqR8WPPvcDxFT0Nr8EQgRu7vitT36vfM4cfLbiJERwwhAYJHjJ2aACXu7E/7kT76C5WjCNRKJXLpQRF+WIr7y7aewb2eJIRBCOoDdoxEfu/Y6rCuhzgXPnzqtxT+MyoRQK45W4Lo549pccEMtuC7PuG4uuHbOuCUXXHc64/BH1xtre7UV8MItCSdvS/j6mQGYD4CDRXCMn3vfLXjyyVP47uMFjK6IJ5C3vDc+gRdrBBGtAUyESjDYFKNLPlKQSDBqUhRqJwjk+tAGh5WilaAGWcaIM6dP4/Ef/AAPPfQQnK2h1sVsj+WGfgRy8D/Ko/1JZn6h+/e/APBJZv6/ENG/0H//c0iE9Wr98xYA/6X+/bKHGCNCUXpW5YrAbZcyLw8QAzvnWWT6alNGqloR09dpGwUpsHgXFRI6UCURjbBwWJkISTt32vdDCJjypJnRxixwI61CN/IQcJaAe8aaSaehaa6WUlAt8aaQgnmQYsdJs+l8mYFWz1YhhKohS4zA0aNHfCw921sZ33n0O3jm6acRggmLtGqnrW0xzEaRAyQsmmaRIAy1VbX16mQmgM4s7cJHGh3PlS6m8vPFYoFpPSGCQCEhqAdbSsU9d+/gl99/BHd8/Bnc/Kc/wPZzu6iJcO7+/XjiF2/Ep84u8OfHGCfGhLxdEGLBPAeUOkhef594kVYEEmNqlLslwAt5T+fPn0cpBcvCiCmoyhVQCdpbTqIQVMvuy2KrkCQmU0DNBYhC84LtkZzAihn6e68AW8a+MtBBViUHZVgUsG52RFYsoAvcOiRSRWZgnhLCHMFMCCR6uhURIMbZ84xzF4QnGsMMcIXkGg1rZ3z7W2d0bRlUo+ExM0JI+Mu/eFYTdRpN1gLwFmqesJomGEunZPUUI+NkAE6MBB4TAg0IYUuU8XTsS63YLhU3rifcVjJuLxWvmjNe+8M1Xvv9XbwBwH8WLuAj+7bx+0cOYLoHeNNrL+Ktr9+PP/rIC/jB0/uwuyuNNGsAisp5UpAeY+KUCONAOLBStBBTwthFe7a2rMqUiBBYq9xycVuyGEdpBjBIAjfF6AZ1vZ7xzHMncd8DBcFthUR/999/H770yCM4fuIFMODJuCsd/79ABx8E8BP69X8P4NMQQ/tBAL/F8sSfJ6JDRHQjMz/3cicjqJcYAqpRhkhK92Y22Tp03lzTC2DW8lZLFtn2BzWKtVGnYpLaewKagLLq0fZFAqBmUK0JoyRuqhtP9ziZvRDAMGEOcO+YmV16zuENUnoTCR0HgBdP9LQueUSZaFQMZZLDxC/27+zDG97wcDfJ5LcYYgjX67V6TlBB7zVqjZhVpGYcRsx5FuigNAw3c9aCj4RsBhXw+3OPHVoh01HfQrCWzMBUJBONmVAh5Zqv/dZzeOcffg3Ls2uceeAgHvulu/HYvYfx1986i/MXFzixu41nts7JeVcBMSzcmxH7ZhufYNaui6AbdtZqsa2tLSW7S5lugNbiR8H/er5qoOB8aiboxszatqsVNhCJBgKBnUcs2fBGWzLjZie3opZatSrKeMQy0Xyzl8ioYwtoxlKgSTXqsAy4CtEwAAi/1u7TqFsODGnmHnqfCNY0srZ5AwhjICabRI1KxaxZemrRVhCOtUVnYCn13YsBT+xs43FmFWcRPOsACG/bW+G9Fy/hAxcu4VfOX8QzvMR3HwXOP3QUv/Az1+CZk4fxu3/4OE5fYIwYxOsPySmHrSlkYxNQkA3U6ZiWz+jE8C2SJCKMi9HXcAhRMNZgmsNZIy9xzL76ta/hbW95I/bt7EBGUMZqe2sLO1si3pSLVf1d+fjbGloG8DGS+OO/ZubfBHB9ZzyPA7hev74ZwNPd7z6j39swtET0zwD8M8BKFo2OpDtuFFqJKWAZhmqhuFkhV9mx87Ds+zaIiraqMatgDp6McYNs9B89XBqOO9m62HodWXIN0HvSl5aGJBl/NIDfjaSev8dsiUjCSivMKPANxaALAI0GptlXkAh+zLPQsg4eOrhRLqnUS+zt7eGTn/yUJsagi2qz7DTnGUTC6KjB5Aerq4kZjANIDbmNgSWycqmIIel7EqObdHLPSiIfCHjXO4/g4vkJj375FP7zJ07gp85fwtM37uAzf/8u/PGZCc89AsxfvIg8SxKy1jMgIUXr3EggqlpXu4nHmSEQGK0CITYRIcWsL1y4gOVyG2Ma2ntQoZagz0L6eTBpPYJS5XRDnZX3C13oeFGFWruvSK0xYVL1NIvMZDjNezUuqIFdJoHYki/iaStMRj5lxfPu8gQ6kfUuZNxqtQ6wOh9t81BD3G/ctv5EC7pVbYWUVKe3qAxE+4yXU7M8vzku5ihZdAcA5wj4s60RH9leYPvIAfyjvRX+6XPn8Z5/+SyeecMlfPM37sCr79zDr//yzfjInz+P4yciQOJhBs1PWOcEa8waYwSrlxtiBEpLxgZdswGh08lV0RlVlLNiJa6WLDaeuwidz/OM06fPYGd750Wv+j3veQ/++//3vwJDFMVe7vjbGtofZ+ZjRHQdgI8T0Xf6HzIzk6W4/5aHGuvfBIBhGNg4bi76UkU+zh68N2xW7WFILKo8ZKTY2AcwTEe5rqQej9HdWMBxwyAt1NB7A0CuFOSSiKFJAgYOG8m3UovglGrazdtTM7ExOc0jMKPGsbEbxAtuhvpFZZ0kLUZKqcgyq/D2t75Vqt70sPGiQDh77oLq2WpvozK7UQ66KAlwj4s6rVRPchGpXGFGCG1cZBsRbqYlvzJn95BCCJhLwevvO4CfetcOwrMr/B9+72lcf37G//X6I/id6w9h+uLkibFS9kR6EVUKAWLTXHCcXS2n7kUgEhUw4ze3DU3GedbW2ObRFJ0Y3uPJDQ5EPcvFtRvrwuEANuUxKOQCFXAJXrVIWtYNoKvVl52PrDuuz055Fos2er1Yg65kc1WPt/OoLeoIgseAmFWjQBwUECGqRydZ8eacQOeYheBcWQVtJPlq4jw27tX0BIhQS1YOt3jlea6OwcM0OpQ6aMlaWwd2HjDjYoz47w7sx+8cPID/ZH0ev/GNs7jun38Tj/wvb8OFB/bj1/7hDXjkaxmf+PRx1CplsmYfYoiYy6xfaydo04/Wis48z+6V11IBg/Fq0TEMDdrjgmh6JbUiDoNGSLKmvvClR3Dbrbf6mrXtb/++bdkk0Tq9XOn4W2kdMPMx/fskgD8A8GYAJ4joRshkvxHASf34MQC3dr9+i37vR1yjheJFS0ytQKDk4hqleZa65Tyrpql5s9ToGRZaWI08gz30EF3MjKL1z1NHO7KMpiiAhcbFg7ws+7wB6X2DO8OGzchUFi3U0nW0NczL7y20XlpWrpqVuN82FCFEA5Kwqnb/anTuftWrcOstt/gi9j8gPPqd72CeZ6zXa7BiqKWKXOJ6Pfm66xNuQsAO3onXsegUwVVFfNDEtuX9t4iAYVJ5Isx9aN+Mn37XDhZnT+Bt/6dv4drdgv/9vTfht645iKlIJCPVe6QedvbE5TxNrkfr4jWloFhpr2oIgyUErpfRzAARDNnd3e0aQXZsEZl4DuWwYni2gXpI3WW9nZam3h4qA6XxkJtj0BZkgxCscquHFqj7vI0luvfYvjacVT7XQmcmQKSCWmgL/WwlAlIEuk3IXrxEOmpsua1BO/84jvozGzdrMWWFDPp8tRUbMctaTF3k4+pwl1Gpaq24xAX/cusw/uFdN+GZIeCt/48n8Jo/fw5bizVe99oFjh7awmJUhbeUsFwuXQtkoXrIPhEhDs+0ntwbNwlQG1xSJTgKTSnOVOWiaq3Ye4b+ffr0aUzaAgv+Lhnb29t46MEHkecZs9mRKxw/0tAS0Q4R7bevAbwPwDcB/DGA/0g/9h8B+CP9+o8B/Ickx1sBnPtR+CygvimzJ2rk77gRdvtiVu4ddAKYcIT9gU8guBg1df+ZZqXjoNxCtj7ct15hUQ1i38LFklG9ITLBGu/MafxQxS6tBNXVwgIhpcENOgBfwObZ23NGuw+f+ELqvufuO3Fg37Yacsv8y31++ZGvgkJArgUxShKJWe4nlwzPvehYtWs2ucY26YCcxdM0KEJ+uYDIDKXI/QmPuWDfdsIv/73bcOTALh76vz2O7ZNr/B8fvh2fGXYkPK+qLxGDJAMJLn9phs/gIIlMW6Dr/dh6zBLQZoNm4MSrN4HySK1tTFBtBX9HMH9MNJHnUgD1UqRiSUL5oPNUnVBkMArkfXhlExo0IZ9rBtc8bflZ8PuUSxtDReeo/ieZJm7ax1X1Boi0PJZAFJvBtLGyDZCpszXUoA9bA0Bj1MBgJsZqtcY8SR6gHztzAkihEeNiu7G1d0BtPlsS2K7XMHWpSPt+GPArN92Iz163D6/77edx5+/9EJ/5i1M4fW6WxCRJwc5sinMKCQXTMK7VxYuk+EnVv0JwbNbWrAvAd3McBNFtCC1iZggT4dy5c/j2o9+WueozTTz/W266AYEYg7bUudLxt4EOrgfwBzrICcC/ZuaPENGXAPwOEf0vIBTuX9bPfxhC7XoMQu/6jb/FNcTTU2FlnwTWGCM5SIBC2gGhE+UN3e4KdLxTPZfROKg2b7eUVgIrGENT0+qrq9zLg0ABQXvXm4aCG6lSvRTYw9jQNgiCCteoEEhFFfjBxC/0voRK1hl1017V0M/k6haLhDFF3HrrrXK/OhqWXFtNk7doZjRcWCaQYJ9chU2QjSEwSYbXcFhpaTKpWA/5Dk9aaWfY9MwZISQN7QAiRi0TfvLHr8ddt0y484+fwTV/cwH/9euvwYdXIyqXDZ2FhidaWbUaNjWCsslV92QEMghCOasd7abz6CURElBVzc2qgRx3R+9p9kilbrpoGqPU/QRoBlMkDcnhB/NO7Z0BbZ7YSRy7RKcQtuHNyvtlCFbNVAGuoNoiCNkcGMw6h827tbXjOQLF9h12a8+sxZcd/s5IIWhllSjJDWnAjAbDWJWiJAeLvrPaEl7mKftmLdcIVq2lkVlf9FMLg1ScZQ8J/9trrsf/eQZ+5veP47pbC+YD+5A4gQbDXdUzHySxKyX1ArFIcji409AgO1EVs/yISKvCNxyb7ykllNzBlZCICAScPXdOnkl2IZ81d911F26+6WYcf/4UXu74kYaWmR/HJvfbvn8KwHte4vuMVmDyP+oQxkDDoGznsRr53gttsnkAxSZjaBQf1xXglhkWXE2gBDE4alTRPDrzAFwKkdpObx4Ws3S/ba1RWldc66DgkotqLPoCBt9JO40EOHdQwyvSaqyiPFYAPYYGAPv27eDuV93lRs8ScxQI3370UTz73HFYA0tZ1GLEhhi9Ki7PzZP0ttGavRVCd1VtX0blDBSWmvBA4IIOF23mKISAe+4IeOi+s1icZNz1oWfx7bt28JtlB3NeIw0DcgnImrBkQI2iUO+8DU8popdaqyeeSjdHbCwFmmneIKh1TgXk58vltrAUbIERSWYfwFwzXNwGQKBWDuyeITbDfRtzgYIIqA1ekDGIkOSrZeR1IwxC0ncdVWpm3sTWWXt52fs09S2HM2wdWCSmSrvB4ArdP7Je21Traq3mtsvGXBkOLeq4VY2GxFEWXQ0RfJL2SZyzQAMqsGSLMKojwCxYcdAklZ3aqyk92jCvMGJvLVoaKQLrTPjn11+Lw1PBf/7MC/jePVt4cmup81pCfI9qTHCGGcitHZGN05CaCpxVXEb1dNvY2diTSimSbz4msMTM+Pa3HsUbXvc67N+3o1GG3MNisZBCiB/RYeGqqQwjyOSfNbwQQ9naDBttA4yWwPJQp3mvPf3DKsjMAJZaUImxiFH7DYmHaJxXk0Psebq11I3afjOW/YuKMYI17Jvm2T1c08JlZnBonTdTTKhBDHGEUMaqTSBjWaSksMegxQLiRbXwXrVCO68Mej9cKy5cuCRFCskEX6qGpnBPzWECSEhVS8XEkxh2MwSgrhswa6AsSRAwMM9F9TwNj2Mc2Bfwsz8dMYSM2z/0DCgz/tPFAeytRalKDDhgGWVoQk2ekTDPFtopNS5XxGAbXc8iaclO2SAyCuAkd1FWSpimqfVgq4zFcgFr7jfNE4YhoVhRSrepegUbqaKVGRJBSnQuVnAIamw7GqIaWaLUoiY059YlLHVOuWfcvU3ZKGQDqCoHWCX3pYwG4eGGapFda45o59Lb0YgLLkYkBti8M/YxZI0jbV2RbkgCAehmr1x3m3omPGPUKIO8zHECU8O+DQ5C54TEQZOxFUNKqBX4T2+9Ab//2FP4L86exh/8sxvx/R9ewqf/co3MjEgJoqLXyuZtYxQnp937MAxKmWwQjg0w6xotuUFVeRZmial21VqxXG7h7JmzPtcANEM7jghE4vm+zPG3Sob9uzhsYATflFp6z/DH4JO8di/MGvYZV9X+lk2Z/HddLHhcIAbpZMlKsZEESHEvzs4TgiQDFsuFl+z14Z8R9r1SDVDMNbqxtw3AJjAFclFjb0VerZuDGTLzeCUhmPOsC8bCYpn04zji5ptv1huycFY2lAsXL+LzX/iCGGY2QfOqQh7sZO2s8Il1kCD1ok3URrqLQmUPg2905vEzS2SwXk+esJqmGecuZnzkU3uopyNu++wFfPjIAk9iB5mr6JpSUExTmirO86T4XVcd6JFNg4ZkYcpCJwQN81TQw8abqy84sCRBt7e3HTNfLJc6dzJWk4iJWNcJewcAXDbPDx1bX6v6t3UtsOIS25zAXdsYS7KQvl/qzmyeKhhMSqnSOWy81e4WNMJyCwe7Y4GHdA5o40ciYSFAsUpLGEebb72hVIyBglUodspaOoctQc1gT5ZWTU6WIuPe88ttmOS+gyefbB7bOqm1uEj3ep6Ry4yzacC/vPsorj1xEe/41nm8+Q134pprFxhS6+7hSWgrc6bglC879zRN0pKqa49l0bK1M++58HZ/sRMpX61WEklR68ygLTVBwdomvbx9u2o82gZMm7g3ScWJexRBQ5qmH2CFCDZYhqP2BteNg+1o1MrnbHBKLb44XBVMQ39Afk+wwcZn7MN1uT5vDKYJe0eFGKSiSjKXbRKad6Zlh7HhSQ57UAAxdx6OEO1DILztrW/ThdoCdwaQS8Xp02ckmaj4NHSRViVn51owrWbdfFpCwRJMBAJFG//oC0MgGPFCLHS0iFWiD8Y8AY/8Tcbbv/ocUgZ+c+cwpnlCCBHTlDEMQXm2ReEM+LnsXVpLGVJPRTZOG3sRlJYkj/GjN9ug21g4VqrMj2lao1EJNUy2DbS2RJ9hyEE9QKFDhQ7NtbkEHYNNloCE6STdbTUhI/O8SSva2DF33hZBQu4Y9T6aPrJlwq1KSQS4WXMO2vFjA2pTjL+y07lqFVoadeNTFTIxLLx1dm3nknmvY05WXg7ZNOwZ1Hjb70A3Ic+VVGtXTspiaNaJiMCaoyEKmOcJnzp4AMfum/Dq33kMx37yduzbrjh1qrW0kmistbxndZDW67Wo2qknXmrBEAfFqOEOna2FlCyRyLDmAVXHQdhKjFyle4PNK5sGgZpw+ssdV41H2+/I1p0gl9w8h9gSMIB4HGlIiElq6j35ZN4dGlXMKsbMK7bfN4ZAinKejS4Jel373R4gt6yrZ15ZQnPzjI2KZokaad/SeJ5GOTNit9xjFUEXdI3sdBW2TK0aQrBQSowreNlL9hfPXQsabZZX1DOxqpmYZCOwa3PnIZYsXELzUjzwYhHHMbpXYyfADRNAeMfxC3h0MeLRGP1dAK3zgn0NNANrf3rM17Rtq0osllr8OYTuVVR1n31DsTEwGtg0KSRiWWZ9EAuzjQgv49dCzOpMghZRgRmJAqLPpxZFKQisc6UAVJyCJjBB3x6mY3bU9jWpx181atsIWe0F2JVsTlqCDFI511dHMRve287QJ+FsrlkSqxd+t43AnAl7H2tNtlovMPt55UaRs7lrOZM+29/mKvv99JFMoIDdvYo/fPAQxoszbv74D3DLzQRAYKHewWFuvGqL9ixyDDreNn9tqXj3j2nemMOWyzGjbfcm668JJvn80KIqa99zpeOqMbTgtrSa8UIzlrm0EItbdt9+17u2xhZmmgdiu7a8mCLddo3fqkfPwzX+rZ3bPGjnuXKXKLPJGjavBVgjSBP6zupBtTbdBmu0ZAm7V+lebncNIgZXIRSVUnDm7Dm0KsugHh5JTT60kSFVDENwr0UupV6FTjDfcFLyEIwADaMsRAse2luZrsnDideQQaHBEvvKhNetJvzFzpZuTA373EgIuifK/vPLF6ML7QDOutjcXxps0gvIyzkET65V6tFFfMQiBviiEknKoKindAlAZ0RrrY5zMjVs0Ixr7d+fbc6C4EsChoUaRkyOw3PnGjVvNfjzSN4iIMVBkoHab81XinnrDl11lDAK4m0G9aIhRSEwCIsEYmglxpcfpOuP3aGQddH44ryxBtXYucdaXSPWecvdWunL261ay8PyWgBizDPje0cP4NQ9+3H7x5/BQ/fvA9A48YSGb9tmYkadAOfyemQEcTSsP5+vtUAaJUFFaVgr4DZt0jwpl9Y3aHb8+0cdV42hNTypbx1h5G4/Oi/TdkjDdsyLdZxXKz8knGoq80DLzlo/K6DRqKwCjPpRdi8JDpqb1w3qiNgxuKHvs6sN08purAD1qkOUNhydYRcDqIIxjq0p3UhdsPV6jTNnzug1oN6DXC8QbYzjoOGPTVB/Pr2eeVPmXdquJ0kxzcB6dZGGX8H6awn3mRGwf2fGO960xLXXVLx2T3owfUnlES18tOtakrDnG9umYnhtXylY1SMxj9Q0IaCwjnGXW0NN+dPzRbNudlQqIgiJpOWLSUuKFxZAHDc9df3PYSjYhgCY92oGxZ2A7nvm2dl9+0mwaXxiiLBGhfZsQDNUfVRlXhwMrmBIlkyNYy5FIR27dssV2GbA7SbciNoONphqVjWqFPyeiHQNyTfdW5TorSscQuuE0qKeVgEqz9SPFzSXMvo6fuaZGd99yyHse24Ptzx9BoHOupqeFbbYO5q7fIY8q9EZG3xhfHVbezHEDW67FQwZ5GGQCzNjd2/Pn3PT6Ssb7/SljqvG0NoOaQMVU0QKUWgfKcG6pzYoK6gMWqNp2YD1ALedyxITHkrrIuw74TpwPs+SHKvN+CokBwCtCkyN9TRNEk4rDmhFEgasA3Y9ycpTZ6y5WzxeQUPKu1W+qWT6TWYwAhwBCtjZt8+56FIAaSMBwDA1QJN/WnJZmwiM4HgyruM4tnbutbVQNxEROQwjDpocJIdbKEQcWe7i/e/cxS//3EX80jVrFABfWY56R6QTsj17dI+jJbWc8qQLNdhVGcKwMI8itMhF1qx8shnzVsYMwEs0IwUI24EBWNmsnFscPjWqmoh1T7QLFy3BJTqn7MUP1D6gUZDcby5F2DRohTZg1qIEHdlgxQtdWC2TwbHOFEL7Sb/hK0TFjI1Iy+7hRfgxs5TQohkl70argusm3Qhs5kEkeZn9enmeJRnmIXfrBmzRqH3f6InteSXpPY5DWyO60UaNKn94bBffvHtEjYRbvnYKd9952JPgAFoEYzBZd34bAyuRtnE3SMm6ZEuUVB1PBwJiSAIpdoULp8+cRgshxQoBBum9vKG9apJhVRdbUTEHy8ZL5NY0BCyMNCwMFETmrQ/l9d9SsmqLWIWs1ds14rsY3eghtCe4wChz49GZ5+qTtlj4Jv8nvb24dWHQ7qimfylFE9I11KLSWnQXVWUvC42J23OYApO8zAwgalmueMIAVGlKbkd223Y9MCOliPU6O6ZrDAjOrBNRuoCm1LrbWlNKZmwIyUgonoU7qFxcAlDyhDvuGFB5jWuORNzzwoRHxwF7KYkmgHI6BYcThah5NjqQDiX1Zabkf1sIb+/GOMeAhfRKfapF5wQ5nmiHtc82LBAkUoiGJ5tBIVhJZ4t+2F6zzkNUoeNZVVIIwbsuA+Ih2735fFEPKcgvtOfpPV89xNiKAFCIQo1KFGAYpBu0jcKI6pVQIPJmlr3RbZAc6xiZkA7r3Av+jPZvyyv02sv9fDBZwcapJfe0uRbfHNqmKM9l8I+F9sKdLqjKzc5ZC1poG89NR/DULSdx8IuX8NjdaykgCtJdJFLjvYItmSUWw541KzYMpXjapmZOkYyNbIIidC861pUZpGNUasXJEyeAB+5rC02Pre2tds4rHFeNRysUjeaReE8thQhyye5litqOu7aADlAvKmL81qDYIgBVopIQY5om9ybNqzGc0niAvQh3X+ZrVVuATORB9QF6mTwPyUtLcplaUnB8NjpUARJ8S0LLHpc12lsDjZhFdd8mvzoe7mWQfQ8B0zxteCRgS8LpkiDV0uw8kXme3fBvQCCGheuYWIQhcEXBq1+tNKHKuPVUxteXCzCrxie3ZzH8z4723hrH0v5tRkHeI9wrJDSszyAiN0LGidUxHDy5w86fdQhAT2aens2H/vd7LxMwTLRR3IpW922wvyy0l19ABBB0rCyctzlSFE7Y7CYrNynvrKtaNONKrYzW7t9gJhvTEDqlOgunbc5f5qXbc/WhPNBCf6nCqx5G97/T7hetXF1D7jZ32I2q6yb491STgKEepcKI6hT9+V+ewcemBW48s8K+onokUaJddNc2z9rxco0YfV6g4cqeTI+tzN+gHRsDuz9jqVy8eFGfxwMrnV+Dj9eVjqvGo/XQBuRwAAjgYGpeAEIDsOFltooZGU5KYcPz9N70IWjNNDlcwMxSyx3DxuSy5JA1gzRYwD7nLIRAoqxfm7oROmMENO+xKhdVFlfVlwutVIN7WZJxLrLrk3p/IQEcEYKC75UxpOgeK9PmknFlM/XWt7a2MK0n4czmVpHE0XZz8a4DmvdRMlAzFJtU+loS6pgItUlGPagEIOWM7e2CiIJ0DNiaGd8+NMI5pdT+tqTNQnVw3euj3hiroeOGOyrULMYnbCakxMsqXpNf/TwF4xgxF22DTb5HSn4JqvVaZeylxWDwkmjD+uC/15I+jIoIo/1FqWLT8N1hLm5hvj2TeHdNYBrKWDG+sOgEMFBNy4BRyH1FcJVmlpEt70CuB2CQFmqrYmyhe/dMngRq88YMafG+clFFjETxrXATldHf6OAgoOTadelo2DArGyFK69yNoiIiYIjk2K4zfyyypBkXLhC+ujUgALjn7EV8+cB+5HVB4awOCPz5XJVMNxfp9ttYFQYdMKuGhT6nRRDMAp/ElNweGTd3bToLPhPk/44cOoSwsQJffFw1htYmGJtQSLfzUwxInWfqdCPuSgiB5kWqIbQXCzZ6k06sGEHchH6hxqAH7C1k7WGDGCMKSVLo8ux4LVqUoN64eQ1SYRVRYeW6eksW2hnGqUZWSjQVWqgVLndiIbU+b84FW8stv3eosAuUFG8sg2masLu75wT0cRy0E8IgiSWleVmninmexQhoOGlGXzY7NdA6PqRQQIwR4zAhyW6Incf3AADfWly+09viA1IKl2W0bVrLYd63hYP20z5DLsLfzSib1997yGTiIrUVolgfNF+PFkF0Rt7mgk5OmZ/Kxmi4u4qqqDEOqeH/bmzRzt97zXaIg99YNj2k4F6uesuGsZBCA0XDcdkf2zkDBdFI8Av4InOKla0XmZPNeFAgkOK3pgli0IGF6K4V4mG3jlkpfr1AVXmsBA5ANMMXTQgcqlMg0Migc7DAqkELprliHBK4VrxwbQAeB37p/oAn9i7h+dM7CJDfJUCkDWvdEF6yiGee5lbRqUNVNUJN5mQBUho+Z1lv1JhEQaM+o5X13iwAjIvFi6Key4+rx9AqcCnAvvH/5IVQbYsbAU4qtkXaSNAtHVS5Atm8HpJsURe+hmBZTstQd6EqQ8nM5HQlYyyYKTDPwXEvNNYDYIZCPUK0XdxaqVdNjrCKXLhQCAgxSolhwKATyTo1FFAQw59zRRqiePYOFsjvF5V0FO8goBTGPImXEkNSQ5dUItLoQE1RqdaCNIz+ZkjHPcQIVEIpDMGKSXC1ynjg/qPYWpwGQDj6bMUM4ImtLVQWfLHHCWXjMMiDJcllZaQxIlLXGbe0SMM8XAaaYI9+v6guAlTPQUJmAlHE7u4KUnAxAGj946jKRkcSEkEv6F54b/jlXzIH/TlIPSACIol3N6RBkpKq+CVhve0Z/fwoGnGx8moh8949MnmfmUXvVWAHeR8AoZohVe/VkoNV3+E8z9ja3kaxwgO2GQxVbbM5gzZPzaCH4OGyzWUL7bl7D9LI0J1230T6Tcq+3zBa+UyKCVyKVlUFECIQWmQYu5b3KQG3v54wfTPgzt2z2Le9HyeoevRoTomtLzbF9AB/fvPkg8INFFQKNQr+KuLvGSEAs8GTLBsBKiOAkCdrQFr92WxeOmvoCsdVY2jlZiNCLQBFmUgdVmI0ikDRPUrDNm3g/DzdroYC59WZkLNjm7rLkU8y9bBiaGWHOUuNPKvyT20tU2qpjetq3Qi4VSgB8HuVBaTGGfC2OOYBGFm7cQUA1zNwSMEKOBhbyx3BqPw67fdyLl3BA2kFXfDJRgT1XGW3h9bjS7EBI9fcJlp3BetCACh3UHUWuVYc3F9BVBB4gaPHIr6/GDBB77vH1PVclmyTZ2+L0p9Go5C+MaarYmlYKb2iBGaKWi0nsKVCNjooQxpgyZHmKet1dOPzbcq0I9WCiAaFGdjmgTqkoe+zdHkAwIRwlD1Su2KZzmu2Z3Yj0exeS/BotVYFvLKLIVVnank3hNx14mhHBPZ7bXOq0+pQb5k7A+k0LwDr9bqVn8PYN0p3IvIEjxlfqhaKbxodcujCYDUZ7aDYPVBBSDrH2CsSS5aNK+cJu3sFu9dEbL0wY9/9lxD4oEpryjNylfdAgdqzArJp5J5OJhEYOlqYr31iSDLUohaNSEkcEdE03nz/AGP//v2wnnxXOq4aQ2tQgT1EAIGDvMyNDLOH9hbWKlzA2RNo9vmGBenLL1r6Z9he1SSRekFg7TQAw3ekv5AZVZ+g3at0kQ71ug2usM+Urpy2UiNPx2AMB/PMLwtXFf/yDHxgRIrusc05YxhaWxYAnYRbo7aNixG1VmxtbWG1WiNGkZMDGnfSW/RYD7CilKtu02BmcGyGkWELX7zjz3xxxuOPD3j7G0e895kVvrTc8nMQkfZVirqvsPuKMSZ3iSzUyzkj14qo14q+IMmpZ0ArTjFNjKjVb0k5oCEEIAGr1QogwjAm9aChNlb6jonxKm3sCCCKG/BNMN6vb4UGLVXByMnegc4LhalsY30prFQiL9uEzYuW8Wmwg3KQQWpbdYFH86gbVQ6htWwJRE65svfYuLF6r1382xt/82QXi1GE12sW8SO7F8+B2LOqoQU6z1k3J4VVHGoDd1WesnFXMCZea+uZVlloUWZMAygE7B1N2Dk5421vvQOP/oDdIWKWAoOSGeMwuJNkABfrO5/nuRviNsZ2b8Y4MDopFSgnPWAuJqDfvFkLMHZ2djYQmpc6rhpDC5vUzG03hz1Mw00DQWr1TeAbBjtou5VaXWavqU75iaT6iYJPphjiBjxQK4NCWxQVQh3S2A7W6kVsWkW14jK7TGX/LADPilv2NqjwBXeLSSCLBmsAWrYJ6/DKqCrlZwFzikPnIfuMAYiUGiMLQDpSZPd+55y9p719rypv0RJ2Rr+xTL89jLf3YAlzgQhCRC2EioCnTmzjwh8V/Gfriu8fEFZEnkQdS6Qd2Xf+Df9Wk4o6KnCRHQaKGReo1oDS8mKMnoQ0sRfboy6nDBEFjIuFblptU2WYYahe324RRCUGTAMAQUJ4EAoXSeyZ10oNXrD7ZEA7zWprotpkHA16EEdOS4L13fWc5ZYn6D1V2WzNcDp8oc8cYlAZyTb3oPcSFVe1Nkk+9qRFIKXpeUhrIKmSKiRtm7op3kWN8M3EVfJgMIFuqnq/QddNrcLTNa8YxEhJdHBbUtRawzTvNtcBlw6NOProHsZB1N8MKhRLLufs2ywZ9iqbqnjQNm6WMA4giRqYFGoi1Dr7u7POzvJOlFdeuNkeImxtbXkS70rHVWNojeYkO6AMstFemkK6ZL9jRwMz+TiQZI+d7F+tDFbVoAK7MafYSgoFQw1O0DdPxylcst5gs5coIAYNtaj6xKJCPtEAMbjB8d8AoiZ2bLhinjM4WL8pmbhGwI8pqRG3sDpsqDmtVqu2wNXYGp9WOMhRxyq6YhFg3qhSYpL825o82lhaptXEbAQ37roJ9wUcunBNkew2lYt7fDGAUTGOg0/a5tEFfw7rXtA8u8Yt3SiqALwARDirPjSdYEqj6wktcLMaymQvqxkDSLbe4QAStoJl7Unv1eAKw1WzelteHWdeJgGVi2/I4hF3sAg1PNxuPsUI9nM0ellVXjypd1c1zC+wMmDyMNgMatZ2K0b7coy1KxENet8GpZmOaoXiu8yu+8A630NoiToiraxSB8L64BERiLv3bANCcAzaKj17brIzKdA2OjdmnRPxwqkd/KDsw9175/Cv/58XMZf9uknIMyZKKCUrPVMmp9HDKs/+DrnKpmPUUVIesOlLWtGRzdWoZem29sWnY3+FpIb28t5+lx9XjaE1PMmpR2yVJE0RvTcWrfLL1HOE6mQvLyqgT+otsrfxBjJL/6jIseFYBF/Y4klZ2K4whXpB1kBPDEHs7pW6ySiej9NbzINi1jLj5hXIYZtIO5dgyeSJsloDUAu4ykTeXi5U34EBk7lTz8PGcb1eYXt7R/uDSXgbXN80uwcoyQjpWCDjB/Xmui4VteHRIUD0epFQasG+rRH333sA+7Yi3vadk8AzwBOLBAqsDfmWMA8wGtXNHDbf0BRGidZ6JGzACWbLpIxZxrklKM3bMnUtYzHIYtm/fxvzbHoGmgTTMXe4CmI8qnqRCGJooxYKBCaQZtktOmJmFPfCNpNkdhrz3MWYt/x+w6y7Gn8QKFiJdvQ5I56deUyW7CM30D7/hFsGAKIaHIK3K7J1458lgb0Mnmm0dFk78zxhnrNwRFnmA3STM0NuFC6ZLsqOsJyK3yv7fVs1mHSC0I0xBJAWDMm6k9+NxhHWufDEDy/gU2eBnwGw7xLj5JYlOKNDL0MafZzF8Cs8Qa0FPViwX3vf7f4MQ9c5R0HUyIrCk2yjQ9p9xSrnpNPDvzeGlqA1/lqj3Rst82AB6EP3Ig4GaltNuRlkdipPEYVgGFYoFA2GB3qVUbpJ2BJrbU8lGNdPOYLdJBIKSBCxEcVViTTLWoqtS/lbscPIjQLG0XC8Hqc1b8XgBAXx1RstNSMNhBT15dsCR9MKIBIB82GQrqCGXdo9A/C25eKpBx/rKU9e9WNdDTKbx5DF61VvaIgzHrzzPF51W8RDT5/FKgDHVRC5oHXKMIgEaF5XCEaNUpvn4w3HHy3ktO6spL8v0YFukjE4D1iuZVoHlugpYNBGoUvbOPReyBKaRmMSHmsBAGO02OTUl2r8SZ+TRrFjxS5lZovXzZsaGp1TLuNC3CUc5RxVPx7dQyTn25pAdS1FNW5VyB4Nu4WF4joHQxAYBMxQyqvOhm7+E2EcRhV0J2GF6DUj4F6ntBPStUbabTfItSyBZBQ+W5Omp2zVgQY/mMEESYFJcwJawnq6FsDTwFuvXeHEPGBdRpmL3BKVRfML0DVhfPjCUiHJteVRjB8srBXdkWpTlJM9rsPYrSKFu3emFqKvnHup46oxtOZNSt+wzd5RAMDqIRqGA7RsLcyD7bFdZtScFRNk/x0z2N7SAl1WWI2vG3uvACMEigiR3BOT8LlBB95sDubZ6I2Q8SdbuSPMgHDrayS4FDris3k6zYuX01nIXbC9vcD29ih+nLiDAIB8QgSt7Y+Jh4cqYiLWgjrMhklJyM79dXRCWVRtLprxUluLFtscVggx4cCJjKeXCUKRbNVBNvEBbIyzwxjQeR6aN+gQAjXvDTDeZ1vMPu7iAmpkIKLUNfdSgWglw9V4zbaQq8AGFbDW4QgBhavAOxr+WiKNNWx0r5Mb80XGjQGyRBBACuVYqScgMAPBhFxslJqEJgARDYdEts21YuewNsxVRrUwgaxHgl68ylaBQE1q03FKtjGxai4AMA+zpcusIapr4TqlUimBFvmpt+odK+ydq8GqnB0egRYQwc7J1dt+23iyzTmecd9PLoCvAD/9KuAr54HHjwUQB1QyTjQrLk8bG3P0QiP2d1YVrrO5IhujshCClaBLBadUHjY2xsah77oXaH+p46opwQVz57XatmF4myi49wrpffbW1Jp6Wkmf5ZUyx+IvO2iobBnFRoUCxCh3v190ERH7i9ogPwPO6XRIQ8MgIjiBOpgoDmmpY6fFYLQwa6zoOgxoz1C1Ttvq+ZnhmBqUGgYdlzNnzrSNykI5y8TquSQ5Il4Ta1LGvJs2dp0Ob+dJmcfpyZ0KCbOZsP94xdNbCYS+/Tq3javztvw92jtDW5zmtVqZsm261kJaPFQ5n0UYRpcztTPZQBmH9+/DXXfcCmaVP4R2W45RNRAARnW8j7pnBQDNvEiZt71PfXbovZr1tAon8d9UQYuCGB7ahEFMypC7TUjKe03rQdYFmzeoHHLx/pogTvV5J89mm3q/tsCtIEigC2nhYpWT9qxeaEFALVk2S2XfWIQoYisimjQMA4Zh1DL0iHEcu5+lxotVMaeUJEpjVIRIbrwpWOeH6Mpa0pssIQRCSluYDkfUAGydmnDLLSNgfYt17Np8g3rbqgKnokrwtVQ9iUpQfrVGU6b2ZRGYNwzVd9DgKou9DFu+gl3T46oxtObhyKH4UYy+2MyY9i2aRUlohrUcl3CqQQ3RFpJlSKEi27pQs6kO1SahFiAZUKM+GX/TQhKbmHKb5CW/APyzjJZQ843BiNop6WSTnTKmJnSSs91b9XFoE7Vxapkr5nmC4b8OguhC+sEPHpPwhwTjNWEcZ2AQ9HvV78Wyvu0g98Zt0yjVDLcETL7xEIGFHY7t04znlhISmoykvB9pFyPeg9y3jbP0a5PFZaGZGWN2A2LOTzfmel/SO002Myt/lnsC9u1s4R/84s/hnrvvUI/FNkFN3EASYDGOCJRE9Iy04AVqmBiIULzTDHkI7u2ABGYwXLiAJZPt3reULbtEJhGkl1gEWPmoHQ5YuWo7GmHZeNsZlg3CymuhIXVAowgGAJJPNydZPV5lUdgAE0kAZJKhje0g93DTDdfhnW9/M4J6i9Ru0J0XwdrbnIpBClhCEO9ZjLo8v1Dk2nglFVvyCNUiAmoJRABNnYwIuQasDwZsny3YXhbkKSPn4qH+NE0wJTMT0yc11kk3ghCCd0oQvRHAZA6ZG35rrrwlcq2tjbyo6n9s416Mi8vWz+Zx1UAH/uIgAhaON9UWarWdXF6o/B0UYzFPT2M7tPDOdQgADXdagqcVRAA2ulxDS8IQwLW1KDeNBMMHZcKT4z7SaVXVo3RiOkbpSSDy5zEvukrFIkpp3rNVi9lhz+IhkPhxEm4yJCwF4cL587Asq3kTlqwzviAFwiAnlXLcUkRRKwuWa5l6hobSQcoiM/OGuLphaFwCFmfXCBU4OVrm16hCet9qKMTTl4Z8ddbKNr1fw4Nby25S9S8ZCvM2CIQ0DMKhZQsP1WMpAgXs7Gzj5/6D9+JVd70KTx07jq2tbT2PtC8hCsgWGdmmguoeYcOLdZERgSzfGJpGhRt7W3Zsr9neHfn92+bp0ANYMVByHQajaBHa3Deqn2kAQx1f61Drc4Tbe7PxKrWVA7ex1fvRPILxtY19c+tNN+Jdb3sTDh7cj8/+9Rewu7dCyQVB5waq8octogmAFNS0ikiBCqxyUSPLqknIDlKwuU1dlGrJa1lXFXMGzpwNWO+PWFwo4DoBvAAA9XoDlltbTvschqFjobQGo7VW8Dz7tbN1odZ/S/4kdjq23BwOMPbv2/ZiBzPOc6kYFM++0nHVGFrzPPsWErabiRFQ+TczvNSoNea9QA1mw3cZ87wJM8jcEraAJUEsLDAcJw2kJZRtp2/Sil3llwNYjFyqt3U2z4sgnprJtNXu3mwyRseODTawcEhO7WGOL0xoFZoscr28wx2BCLnjd/YJjnmesViMMGqTGddai/MW7YSuhqXnYGsLoqGdVMwEQEOzWoHtM/Isx0ejK9UmQxcCQrfBlVpEplHDfoLQ3LyDbVAFGd88ZVBqMexQGQ3UcMKcZxAFDENCigPe91M/gYdf9zqEEHDvPfdi+8BRNZZiZA37JU16eWPCEFQJS5glIKgXFJyGGLuEqc0ree8CS1kE5UlKTY4ZV7NP6JqhdPI9Gi1Rfm6qVx00BYjnXau2jtH5W6zJpZazezTRzm8hsIy9QWbVN7s5z7jlumuQYsI73/IW7N/ewsc+9Rmspq7dT+WuDJqUe24aGezrlBUDlnXZNG2hm0pldkNp0BkICInc0SB1v594+gWsDwQsL1QsU0GKQK6NmTNPk0ccuSs9No/XimGMF+t5FbUrFvmZYmCDGeS5pMUUg6i2LsgA8nqFRqh/6eOqMbRmIC1jDwApAAgQrwOKJSoPEgRU83g0tBIDKmF+jKnbxRrWAsAnP9cZISYRA1Fvg8hKNBVHNVpLMSWt6GFrC7fY+b9sFUIM5WgGx7ZcpLgaXYxRrWSUFYOj5v0BEoYJN9NUmQRbSjG6ILYnUkiwwRRFdUnGYEbOxjmWSqGcpUEgIJlXQGrC2YS4lX9YDAe0iq6i2Wa0sk8wYT0F/MXnIhZnVngXgO/kCMQZQIQ0dhRDCqogRBAXiRR842EwbSpDqa8noa2WoZqH7nAGy0Zk2e5AhJQCtpcjfuqdb8MbHn69fr7ixptuxNEbbmuRy0t6H9Rhz+1zMjVahLDxebJPyiYv49MXp8INrXzZ0xdb2G3zD4yNa7BlJeEXUmdWLBXzSz9L58C2+/Af2hjL+umxcYvCQl2DV+dRSsXrX/c6pDTgo5/8NC7u7knkwRUokpQTvdyIPnltHN9aJSFp+Klj8p2TgqpRbIywNEsGI9RGnQtgvPB8xXQo4sCza1CaUHJAYdFKcGlPBuY6+/PInEh+7XEcfexNEhUAQiSPVpsBNogoepRgW4uGHGBm7O2t8O+N8HfTvWyK7CYkZy49GO7ZFq4qBtF2es+WwsJkI8YTDI527h/bQKkEoy4aouDCE3I/5tUp5srWIqQlusRQNG/X+j5JiF9F2EK9vBiCVB11XE57XimbLEhJzUwgD8Hs3isJRBKjvjo2T0r+SQSRftSJbcRsBnxihUAeLuacsViMupEoXUoXu2WHHcZgfaYoMILwToG5Rjx9Zgd4YQawxjNxCa7WWbRq8QaUxWFYMoCgJbpo995ibPndou+xsshiguHehJX0xtTaeg8R+Ikffxve+pY3eweDHoaQTfxHpybM0DsS9VILifovyecFo5WB6wSGuXAOJ/S2sT/1ph1XMMI+RM3I6reMLXC5sW23azhG9wOb+83C67tqNxNCQA0B83qNQITXPvgabG1v4d/+2cdwcXcF4uIyoiZVSNy6KXtfLyIMQ4Ilp5oBlvk2dApsGxoltqF0RQ7r9TaeWO/ihnMV331sH0IMSGgtkWxeGVXM5r81XDSP1vDW9Xq9cU27FpGIxBAsUpHvpZh8jCq3QX322Wc339tLHFeNobUHTqqBWblV9ADY+DtQEF1Taj3GMlfBQKsIcMjiaxSwWqHyhVaZFDDNGUSto6aVQBpWBzJVHrmGtNuDTvDQcDBuIaQkZRT/RfPC2EKm0GlmArCSVE/8qBctL9/CuhZGAVoxpy+aNZQR71E8q75MOMTg0Mt6nrG1XGKaZiyXC8W1NcTkimDCHqyhn+ww4FKQlQInlXXNG3JLXwk3zhVnQ8DFouOHRgWSjxLmIqEYddQ2M/ClVIRBMENoNZJ4F2qYVX9VKrrYOxmgAkwFITDe/a53421veqPXzBvmKzbgSl5HDz/Zd+TYtIebUBUxd/oScK8X/ff0++75dpGQDyHUYKLhmf3VL78X9v/vfsI+xG2zslP1t9Vdz3ctsnnWjAfXijzNyq0Ww3Xfq+8BMfCJT30azz5/Shg5AU1Xwl6HIWueR5HNumTjibCX5fZ7RL/GiaAqdpKsynPGPCU88sKId5WLePLRCA6iSzJrLzjrygDAO2MDm33L7DNG7ypFWE2iZTJhXIz+vFacYTz8AOjn1AuW/ko4duwYdi+t8HLHVWNozbgQlH4Vmmfg1CxdlIX1xVYGh1Y91PAWa4tTPBRkBrg0/JeUnSBTLjjeJeWrkmQK3cyM2jbG5yezt6IBLJnW1KX6flDdU+okZBWNsgVolB14CGLGzo9o67djIMASfUEXjMAK6/VavNxAKFPRDQcAs0ojSgmvdTS1poVBNR4uXdrFvn07mOcZOWcMg0wT6zCRYnKooZSCYRDd2cNzxvOOgwekJNq3wyB8xHnKWK1WEr7V4lJ4Tqeq0wYD5HLVsfVqjXExCMeRzdvXCj1UvPenfgLveMubEWPCOC6QrVU3Mwrqyzqy3BkZOzZCeFZv3H7WfrABd9j3NsIMNYSKXoJecmZw9zfZ/za2Bv+MG9V2XT/nZZ7sS20eL7745qYASAJNuMbymxYZ3n/ffThy9Aj+9M8+hieefMZF8okI86SCTVY5FUyzgrC7WmG9WvtlQgT279/nY7ue1rDsvm3MO4MkmOa5uDE/qTmNI6VgN0WginDTsGgdR6ZpwjiOfq3ew91I4ALulZv+idkbsSky5xmACYRvwo/6Vpg3NpqXOq4aQxso4Jojh9pGrGFmZcbJk8+7+Ib1r6+24zB5Z1SvoVbPzgSYCW23dE+gkO/mFqoYUZkhCQpWkRXHeVm8KCnvhXdO8ASXVyOZJ9fKDvvS3b72vHTGlEDO1WRmXHfdNf5iUxIgxbmnFTjx/Clc2tvTDKucY84ZZBBKZQxpwDgOYLTWznnOmtSJoikaIA3yNPO8WCxgIiXLtNxgWiTP5rYGjTaGRxk4m6JvGjZhLaQOMUpJJyC4L1pYJmMuDQgrW8LHWB1aYjkMMJMi46BiOZpwvO7aG/D886cQY8RiMQJkteuMi6uKSptqZ+4bquWyDXkj1LdPmh22h/GgvoXmlxtQcqe/eY2sJ/OF6s5wu5idxxxju79mKW3MdKPXqEfupn827qCP/sa669iG1W0KRMD2mLClXc5jkhKykhnPP/88mCseeM0DOHN+F6fPntZnIkxzdoeo1gKqUHYHyXvfkrWRc0FKwUuaJRo0qCE65RAaNY7jUopuuOKsKtYdmjJ+OAyIIWKxWKLo5jZPM8ZxIbx73bSzld9XRqnSXNIqxtyIahKOO8+Y0aRTGYQpZ7xw9lxH5ZIxDmnEtddfj+8/9UNc6bgqDC0BWO1dwhNPP4mLu7s4sLMfq/UKRDIYKSUpnYsBk/a3CiFgPU0+h4aU3JjFJImwQJKJDCGgqqHJ6wnLraWorgOYZ9EBKKWoshchESFEMSh5ngEUH/CoClp7eysEJ1lLhUmpBcMQsLVcCuyg1BlmxmKxwJAG7NvZkYk2JCzGUQnfg4rItAoeoWUlpECYpzVW04TTp0/j3IVdAIRf+Ln34s47bkUI0QH+vd095JLxnvf8JL7z2A8Q4wAGcGm1EmyQJZs9zxnjMCAESULULHxa0ZQQD3crLjx55xVs2rYmJBkDr3bTkOxwrXgyRTUOaii1ICRruePMFSmNAv/EgN3dPSwWCxhlKVDAoJ5uKVkoZ/OkHm7B1vaWl8mmNIhmaggomfDtR7+FX/2H/0DVtaCQQ8GxYyfxr/71b2Nn/37l9GrSo8pckme0TbBoMrX1m/ONXOeXsyiIkMskmGQcESzh2XlGZrjEU2u86nEcPUQ2DYZaVW1O6V0yDqJSZptvLqY1DP8aCpGlKNQrrhVpGNxoANDfzV2kQJ7tr1XmvnQ+IISQ8Po3/Bh+8j3v2VinlWb87h//Fs6ceUHecZXNxvjqi8WIWXvqJcVlASDEhCEOSCw5mJAkw59ilM2TgcViGzlnrNdr1MqYcsV6XmMcBiy3lkhKOzszyo6xb3eNSyEhUMG4WIj3HQKYGLvr4m2PQmgdagNFUf5jIGeWDU899QIGYsQqZ3DQgpMq7X4yy99PPfccPvX5R/Dud/9EB4kT3vUzP4sbH3sMf/3FL13Rxl0dhjYEUIwomZFowDxXAGL0KEkSzPAVhJYZtjAjRe2IqYvAMukhGg4qdCini0B28znPiClhvZYXKkYkIaUB0zQJzgfJyMeU1MALTrm9vQXUggfuvw+vf/3rPbtZuWJ7exumamTJnnExIoUo14Hci20ONuE9DNWwZjFEbC0HcCmYS8bFCxeQZ1moO/sk7Kq1YrVeCZ4Fxunz5/CxT34cgAg3mwc1jEl2tCpjN80ziFSvtBYnrtcqybu9VfOIiAiLxYiIgL29PZSiO74aoMVCdvjDpeBry4UbEwKQhuTPZxKWJWdUCpim1n4cJE0up2lCTIqzafLOQtM0DMLl1ChhnmdPdAkmRxiGoGIiVpzQUfvYmmwaA4UdnrSkknGrqRsPAC7gk7OE0ym4+oCHopZ0scRbb6CtAwIFQgrJKUQGy9g4W9LX1MfmWboYkBpCc6oNEmCwPxfYFO8E+2d9PiISrw7C9525gBgopfFLAaGFgaQ33UsBDfaszuU2eqReN2jVGlkyt6skjCDxOq0YyLxcEo/ahIaWi6X8WyPHAIBzmycXlVJ2JAZsby0hgZuV1ooBjympkYS/D3F69F37Rhxljui5qxpWZV9KAtfzJewl38CmcL1Bni93XB2GFgCIMKmXOakHU2rTyMyGt6LhK/JrhHEcFZdsjdRMv2C5XKoBlc8O4yjeCItIcBpExm+5WAjtCWIEF+MIBmMZAuo4IhCwGAbcdPNNuO7oYTz4mgdx2223tiovNvaBPdXl1TaXPe8GLKY4L+kuy1aCqh5zJCQkbG8tYUkmCsA0z4hhdCz17Llz+KM/+TP84PGn9bmqqxbJRBEPbRyTV8BQCCjFuKQayqnYeYxBvVwrwMjYXi4w6/mayLm8l8Ol4uyQEMOAIUl6pyXDyCEDAGpUFc4wAW8tz0yp59CKRzloVMOhS5B2Jcai4ZAcBgJY2CRKppe+bexlthIeNoNlkaBUEhlcVLyVkOmT2xsUwRaAEL3YoVYpFTdB9pgaFDHPKzBLiGw8ZCjElbMkUhaLUZ45JMQhCbVvnpwrm3PWe4nK8bVxNcNBqNrCfZrWOv8k6y8Om7YO7/BEawpZVDM3DeQJxP6wuS0dM4SCWdiKZWTMK7RDiK5BvSkpRiKoWphUBxYEUK2IFDHEhJoquMDnipTltl5vgnLMuO72CnwXuP/6Fb5+7QpPPbcEMreXyFqVZmtKJrn+0S7UhtEywA6dyEQQ3ZAmWOTUN0h0JLkPCM3S7BFoo2jkpY6rwtACaMo4gRCJ3EvlWhXbS5imGYsxbRCNLcy0nat0mUdT0J+mCXFI0r5FX2IBNoBvwYBZvYKsHgywGAdsby/xznf8OI4cPoQbbrgBBw/sl3u2unBAcTDzcfQbGq6/qGKE/f/0PIJHu1CLL3ooHNIJ0sB0GWoLVblib28PH/3zT+PJHz7t1zC4kXQHNuEP+8s2MWuzXnLxyxteKfPPLBG88MCTPSQ43FadkQBcHCKWC5nEOcsJDGNs3p6mfLQ1Cis8MY4LTFOjYuU8Nxm8EAFkf+/GpKgkz+blkTp43BmKUgrW0xpxTI7DG8fTPMKARuWqpTrbxMa9FyyyxJB1kAixyWVatlrmcsusWwcO+wOI6LzNDYnYir/jcVgAYPf+mhi+fJ2ZAVJvH61UVEpMNWs+Z1AQiAGweWAJRnmGUIUbLboXAFdgKpMYW7S5a4bHFcN03GxqV1SQRY0GEageM1sSUc9hBtFK59PWUgX4lW+rc9QrE9WLHNIWbn/tJeBjwIO3BTx4xwJPPktgEp65weFSgUju3dv4ko2fQj/cYbesz2Z1JIaPm3OHfu3w5rgAbdVf6bhqDO1iMSKmiGmSl0zdi65VvISci3cD6B9smiYxoDFiubXlNfS1VgxpEF4sNR5pTEmwJSUjmzE3I3vgwEHcfustOHToEN7x9rdiaYIaVuYJM0abz0DKpe2+s/kGfPFTM1wQs6MgB+yFdiXk6m0RWjUPhGKlO/Pu7h7+7Yc/gm89+n3krCWhGtZBPVl49S/p5TUcigHznN0Agq0ggB3S8fdQJCHBqB7SgwVa2WKZSu94d8Qt717gC185j49/NiIX8e6qbqTegDDoc5pR9HC5uLGQKrTk9zYMCTkXN6opybmDGg5Xubc1oS+K9dwMY3UoV1KV9XPJIqgNKOtEN2Oyz7I+g1VWiUGb1TByKeBgmhwy1+ZpduyziQXJu5jzLHDOMMpcToOrcFlUNWMGIOW54ziiFtGuIIqtuwBXrTYU+CzGiJiiGlozOEFEVbgCIUpbmhAALTCIKWFISSlSEm7X2cSLfOLCikRSjLpWNKzWGUzo5pWMmieFfQ2wRSlwHQKjbklZt0x2YrR1RIIZlzwLkhoZ80AYdgmgCagJTqyWOmC4MfVkeOMaOwSgzo1tTm0jsAIaW5ceL/g6MPNr4+JB1MscV42hrbVishI6TTBZG4mijQSNYhVj6wkVYwRKAWnpJkE0UOdpbiLSkGz8oHQj82rnacJSMcUQhLpyz6vvxuFDB3Hbbbc0LQIdyNpNGga5yIh906qDbFI23+2lsAN9bvWKyUszO09XDTJb1trPxI4j5VLxpx/9OL76rUfFgxT/Ru65Vpc0NJFljVflNqzsl1o7aQqtzQ8AWM8nIgICi5fma0DgDgqE5SwbY9w6jzHsiWvEB9HYGPCOr7qexCMvBQhW1Rck7NaNYp4mpEESm0bXEe8rq/EUWlqMEmYuthY+5gyLEqAKWc2gN6+yk/mrxo81CcDgnqL/XrVuELUtP/0dG7OkmgjSWBIAE3LWTrbiN2uui1zgSOa2JK8CwQtVLHILFSDW3mgxYpqLsjZ04yfpljvP1lFB7isOCVE94FK7ggodA+smMKMgc9V+eUCMXaua7uDuD9QDNJ1nXxdEXlZuxsw8RjdRGpWYx55zxhCGhj27t2zYulZYEoMQkXcihj0GsNCEbpGgnxVYU6580SalJtoPH1sCV+koLRRKZQqV1qsw6+ZVq7mweh9mAkhghx9tYuW4KgytGQzzQq2qBGgvxZJhQmUqImidBoBaAYDxMYdxAHjAelpjOY6YpgkpSWPDFCPSMABccestt2D//gN4zf3344H7H3CFn43B851N/tGCU1ksPSC+Wq8xTRm5FOFwFtGCNQzVejYBMgfzPEvVjL5kM9reHiUCO8sFmmqH1PcPacA11xzGuBzxxx/+CL76N9/CYjEihIqcK2rJistKuFRy8WQhDGvTkBRsLXdaDVIvX9iXFrKGZKJs39qiExG2VPM0D2rk0JUsEjwTT4EQvCcZAES4OpV5E5VRgyjbT9OEUirW04QYIqZpVgxUQm0KhNVqhe2dbWwtt23SSBUZ9N2RVT3pzfSeF3VdAbo/RK1CUVqikGPZgJYuMxAH2Ywtu28htyXAbKud5+wJ06QRlVTtKftB524aEmKQ9kO2ic15FjwzsGhwQDH1mIQVox0KqhLs7V5SMkMBX1NWUFgVpsolAyULvqoApDE/2urUr2TnAZN1ayYgNh0Dw4u9LKGyKmRxozESO0PA1gECeSLRsNPmvmjoziyGjRnzNmHYnbSUXKu5YF1G5PdraLqyqSuhBUtJu0AuAqdVrtBaeJhX5clOWQSy+ZveSndv7tn+CPDgqjC0tVas9lY4cHA/VquVh6VSFFAw54xlRwcREvzgzQVTSuJ9mEcEqCckhixok74YE+bVGjfdcB1+7OGHce99r8bhQ4cANKxFDjOrOmkYPpDt3wBTAKWEL37hC3j22edw8dIuKszgTuDKWK32ME2zauoWF2MpJetLV8HjkPTfTR8BaIplYPl6vbeHmBI++PPvw9NP/xB/853vgQGspwmliE22TLxNWHsy1ht3j5va89mn+u4MAJz+Q0QIGECUkKJ1Sm1e3VIXUh0B8ACrCpIy6areAzZwcWEuzDD9VWZ5bxJ2s8+BGDsZSk9+sSciMzJqKbj+uut9yretMXRwiEUI1Q2deWYC+wBcs3Omq3Yo4CzQABSeMqtdagFl1X9QowoCrPVSa61tG44kJoNymGNStkzQhosli+cdG/PBsPOiXpWVscrYtXEQiIcgAV5TpculqGBKa4pp64VrFeHsUgRaygWTdgixDaNz34RDrp40MAukQlquXptDFGNyjy/n6m+DmVGVYgViabxYCsgyje6EKFsCBOhcDpHAHLGagfXWiLQXUWkJxiTKctohwVtYmccM8s3G3kEkkWjkGtBYBy3vQDAnQ9cKibi4aKy0Mt22si6DCF/iuCoMLSC7xXq9hvUeAuAeQNbOrUa9scPoM1FxMfdUWEnHBCyHhOtvuB7MBQ8++BAefM1rkFLCUilJG5gqW/ivL+ayUB4ApmnGs88ex4WLF/G5L3wex559FqUUzFN2kL2XeWznkeeZpkmqaUJUcrWEjJMlfgCg07x16guAuWQUiLrSH/zJn4G4IiTlUZYK8GZxAHNWg2YepEksSpZZtF6rP7uXysJC+2Avx5OTZijF2Mkv1lqx0CxCHuUEtRtDC8GN/QBI2E8qbEOW/lfjZDQoYtKiEOWjQhgmZqhMztE23OtuuF4+52GdnNPkFAVy0Q2Bm84tAzAaVg3BhXoM42MIE6QotBI1QVl0vpTaeb5BmBo5F2niqXgvYkRU+pqMW1XIJjhMUatCX0W8UxAhFG0gGlrjQ4M/5qxyf5l945IOA9nnrmGkNvbUGYqAhqP2HTaabq4OYGdPrNGiJcOSRmGE4nPJ7tE7N6BdVxzYAHABVcGQbc0bm6hFOPB7hr6LP//LjF98AdiXJ/zFZxngEcDsUEcpVibv+JYaa40uuC8iAlCD9Ae0ssHQCqIQTTxe5gKFFv31Lgw1ZO+Kx1VjaA3bZAA1Z29NYwLWWZkADLiKvRiHgnEYAV1wMQagFrzmNQ/gVXfdiRtuuAF33nGHCg4rgldbdt+wOluEDU2CvHwNOc6eO4cvfOnLOHvmDL7xjW8CRE5DE0hjRC0FuWSMg9DNQhJubskFaRiQdWFENSaL5Sj8XlUt2kgyKCYUxFWHGJBOQISAxXILuahSUQBQm0ENROKFdV6CcXsNFgCzY9hOmbNdvNt0JJSX+2FWsRpmJJAb1IGV6xitOEQlBSN50iSYFKbJ/bnH0N5Lpb5MGqh1xjCOmGcN94JU/wyDcJ23t7ek0k3lCec564SSRV+4KkZKWpjQ2iQV/YwYMFF9M6goUHCctZaK7Lhwax0eh6SQQlPhL7aQubW3lqlE/nuWsXb5vtiWrWk0QN/FnOdNviYR4mB9rhqWLv2vAqCJSiHnE1IiNUBt8xYusNC8mITf6t1nNdSW63dRnI6TdbsAC5RlFVnKi1E+tvUOk3kaEEUXwtZUp4FACsf5mtTzmRZUQ3bl+ec8YA9CJVwXoYeBI2rHbJCB1Hu189o7QNMBsXkg04+d6+zOlSU/1YGLQdhPL8qlNGf8isfVY2jRAPBqBkC9IAAeLtlED6rQHrVIgCDcwWFIuOnmm/DBD/wCDhzY3ziDruLFClQpjqRhOQNA1C+IcPbceVy4cAE/fPppfPazn8Xeao3zFy74OQIIy8VSPNQQkZU8by2xJXEnL9i0AFJMKFycElRMHNzwJ6puaEOQTcSI9ZWh5atiaDAEMFmiSgdRH29DiIeasA7AWjSgItbQdtf6n7MqJH/V4AXl9xoPN1rhRwiIkAy33cTxUxHH90WcvZhUC7Q1wLOxBjUuaIE+LwWfrBaRDKnVlhdlm8SYUEJ2eMkYE2K0EvZWZjwVYkDB3t7aoxfRsyj+tUwNctnKoFGFee8EuDavifDEIKXAYNZEW8O1Wc9nQ9JHYHaIg9sad9baKrygMzMoi8HYBUblA/rNtvFNi1LkyiQazsOgBSUoXgZrXl8toYnsk7Z50bJpmwu909YzCiSkLuCiTgppBMrsJrEVPGwWi6BqFt8cViINz+EerZP/dSwqMwYKMMz8HW+JuG6KOHx8xn13Vnz/Ce18wToWMblz1O69T9jZYlcvlWTdmVC/efX2eeneYZtccCdGkm7NaP8Ih/bqMbR9uxXrDWaGtedOUggYhlHoHkrpScolRCDcestN+MUPflAEK8iwM/jAUUgaNqvtRWhiI0T4wWOP43vf+z6+873v49ixZ7RSyjzS4iW38zxjHKVYIGgCrZTi3wOAUrW7QFogK3NCsuYFUbFmo//Mc/YyS+sawayRjAY2VUU+pFCAMU0Z0m23a0NDGnp1UIp5qPZvMHu2u+SivbPEgEtWtvNeqhG3m8EmsBcy+KFh+J99IuGR7SVyHUEhCakeAbUSNnFfDU31OSUUFSnEmLSAYYigojCGPo+F2l6UQgInSOaZRYKSPUYBWDiipTAomBi2JV10QwI5LJVsQ4BQqWxDIoqIsd27hcPGYGFNEppiWIwq6xka5a9WkxYcHGow78jx4G58JLegux5pUtPgC+oMFtdmAIhQuQiuW4oaGYNjoA5KcNy76HhkU6QCpAS1M7D9YRGJGUxLohUztBSaIQsilG0bMZNFT/qcMainSy3y0jkaFHJgmBMGDEPEHbcRto8A289X3HbzjB88NaCoXpBFahQCCutGqqI2ZgNszrisIjS5G+BaJtbssX947yQMBwz0+x1E8TLHVWNoayko3JJgxjCwQ16ihk5RyuSGru9VmWccPXwYv/T3/x6OHD0iYSp1+JYOlEAPESEK//PU6VPYW6/wmc/8FY4fP4G9vQlnz5zxhE2tFeNiVMM6qI7l5Ny7cTFKO+NasRgXrhw0zWuUPGNnZx/mOWvtuez+wzCgluphSAjB6Uvt2ZM+r1Cfitapgwi8XqNWQp4LlkvBLLkq94+VJI9mXI1TKM4xt8IFKJZairI2bbdvRPQQRYQGzBuesTRJlA9JdZeq1tOAQgkIJnOnZbBKiqeoXh5zJ8jTJ7wCwNp8kZPisQGL5aBe6yg6pFaAEoPCTEUVzQB0z8dAyyxDvdcQOuFsMaqefOVWxuoRtIfWYqAIhDlnx+JtbqYYUVU0Rca2le8GS9JAu/NWjYzUc7V5kOfZXpsqaHUdawu55ydsg802TfrGkFKTD5VqOBlrqY7UqCRGjyIoNiyXmTFpmbKPITfTklTrwzgq1lXEmDEiX6lGqVaEZIVH7I4EwVpEtc0KBIkOFN7yxeq6AwA4I+cAHgLCzGCOikkXT1x5c0l1FIL+fiBjJ4X2TObhoiWFg8N02kTTEstggFrPQrdL1DNarnxcNYZ2njOGobWMMLyFa0UaRwk3lTLjYDQJ+J3njOuvuw6/8U/+Ca679qjv4qbL2kuYMUQR/ZFHHsGZs+fxyJe/jPMXziEE8Sq3ljv/X+r+NNi27DgPxL5ca+9z7n1jzQNQmGeAJAhOTQqkJIJsiuKkoaWWrBYtS3TT4R8dHXa43VZHdKgdIUdYER0hdYQ6FMGw2k1S6qAkqkXIaMnWwEkkSIECSJAYCjVgLBRQhap69eq9d+89Z++10j8yv8x1bk1g2G4/bgl8r+47d5+915Ar88svv3Q8zhIgXAzzPAcWlwLBvnBh+GFX4zoas6AC1TFmuBdbJJI9rN4ZMaHFhXBE+HfbtJuNTXoaOoHC7j21goriTSOd9N5WANW4w67hQAnHIHA7ZYXQii1EceiCYbJ5GmtrqBhoN77wuCF6b1i74Y1bWQMnW9d8JuoI06iq18pLN20FPoeV0gqkG8eVLVnMkxaLRtTkHunh1aMjp1MNBmdY/b33qMIS38xwHHbtrkMMBTvM2q8TsrD34kGibgVZkSVCzVxyRxGHg3nJVn8vRYC1R8LT6EyJEROqCFzXjSnXX6+UKiyHkR5gLXwgaG6ENy4oU0JOE1gBQC2H0FdzbAhHUIymt5wj0GMejEgYfGTYTc+PwIGNddIFbd2z119BFwzOz0CXVNNDgOOqIwZKp4a/02ZBXY1Ta0nDnHKZkjHBZo9Rcjsk2o0Qxv0Nw5qhCSfARaia+dUFFMgZImR+J6GJV7huG0Nri656yERNSlt41TEoU/Fa0RY/YaVgs5lxz5134D/+ib+Mu+++23/uGX8pKJPgbL/g+gs38dWvfhX/5t/8Gzx37RpeuH7dvJ3WUSsrjCz5UEu1BakmmLLb7XF0dITFF/40TU4xm9B1BSgSXpj48Y2qBevaMc8Vy7oHMGGz3eLk1i3DscTCqFIN4yUGyqouGiMa5nVZsAxSdDSY3TEmJrzMMNnGpNZs7y30Aui5jFU7zPLbZIhr7R42rmutQ5xSpSsGL81wMAD4ke9TvPWBDf71r+/wxFddbAC+OYntSgFKhrv8ftaSA9QlMEy3tRXTNGNt1n2Cxr6LlVyTNufYiL9DBn57x8+Vav1KLyTF3i3Mt+eMsNLfzYxa0oBEah5Qha2Sehg6B148KdYjEUVxIr538+dYG/WAxXFxU7wqvTs9q4ena4c8s/8eUbhcJbsNL8O/bRySm0UgZXY4gQfYCkCxdA2DaeeFi61zc+aysDAbbpgBFLD83SlTqtDegOr6AkicOrBOjrnPE+clGyGmBjF6x9oXTFXQMaGUFX0uKEtHb36fzqIGM/hVClRy7R5wwemsCDI5HO/JKi/bP61xnxV3qhKC0IAj8HVdt5GhZTjaQuiF0oVMiGm37O/RpSOcnZ1Bu/WC+l/9L/8i7r7rLvewJDxOhfFLf/3Xfx2/9Mu/ips3bmKaTa2Lpbn7ZY95mqNpW/OQvmqNZNw8TzFB02we6zzNsJ5e1kV2v9tje3yEs7NdFD2s64oLx0fY78+CfrPfLzg+PoZRcCzr21vD7EwFlhqTksLv5WIZPS7zitLr4KKJ8li/8uBhLiopPqx8YQZ7TOoEzSogG6840wzFmGATX0pXL654w4PP48EH7sYTXz0NQ1Q85KSn1JoCaPHUxNfW1gwn7R3i3XpJxCeeWZ1bOk0TFpe7q3WK0mzlYLhHfnZ2htZWzLoZKEjZ/ZgJR36eoi+2uabAY3mARn8rkSgDXheNCExjzAumuXphgmf9V/vdcBwCK875tHnOeSpTtTJaWAjdyGvmQVcolF6Cu9udureKYF1sbddi0oXTLIFT02NXYprizsJogQZrEnuztwE/NdiKeh3VubLhqTtOqkCI+jC5JEPTOxYc8NDg34vkGrpxssGNZYuyKK7fNOGkteXBgnBCau6D0oOXPbZOogIXmUbcZ8UFaHSAolRzPvj8o+16NYN72xjaCCPcm5g8VGNpaCnVVIh2wFQmbOct7rn7LvyFP/fncN+994aHB8IKPrGPPPIY/uW/+NdQWBKJ2Ot+2WNbtpimCXtPSq2txYAt0S3TaD9ajDpjrZvVQy3TlaUXvuwXoygVirUIlmV3MCkipk4GpzGxIkzRoFix2y+YJ/Oe540lntbmambNjbN7oiIpBUeDxrBtqhV7z9SbZ3gOSxKEaE9XM2qdFC1CA14JM03lQKCDWGZVdTGehrIx9XzRhuevL/jUw9cgcow6VU+yGd+5rT0OVZVquQpfqKx/hxuPrt2r/1xWcp6wtr0JO0vH9mgL7HJtBHTA4bYF5foI1gK9ueZC9I4DXOKPUVW+owCOyzqhXhyKdCPO7sbGMnGerofghsMapBBVi4xUkLKf01QdsySO3gMPz24TEzCx3ZLJTJpD3g+SxQCC7UJHpXvWt2lHXxaQR0oPbS4m29nWBvZTs0TaAcM8Fm+pnveoXk7sh4RoeryAxDgJJJTtRKxVlUE3NGIJ+YiWZFlUgzUqDG5r2rHuG37t14A3fanjWxV4/FFvUeUQxwg3dP+OiMSI9YIl1Ihoyk+M9Io9kqnOOwc0fm7iRgkf2FeW+NnLXbeNoaVIdnXhF6222Pb7vdePZ8VL6x1Xr17Bn/kP/hRe99BromY/+K+wQX/08c/iH/zcP8B+v8e8MbFpqQXVxT26T8DspzTHvRQTMdaumLdb7HZnqNUSIeTMmgdYTB2smUZD88ZvFhZ2zBurctoeHbkAOLDZbHB2dgoKYncx+o2qiabwINhszGM2L9vuO82m2WunM3B84Tg8UOKBvNa2HugW0HBUx7vMk/JSSFINPRcWBqh3VCnYt9WTDnDJwRIiPgAAKXjbZWNa7C9W7NqMW7c6ZDr0GMk0CE/NscwJE0QseUZHigfEYTWdHYTWVpxtoVeTZZw3nujo4YlxNJbFyrWbqh84GmPC5F8WXzhcQKK6fzaTTsm2oIQjoQxrdWLrVKEH+B97b42ZHjJp1L0tM165fjvsMGSxAQ+kuI8iDBhLcI3y6JogntOg0W49C37EI6laapDwq9MHV6yBb9LomDXz96wGAVmhRp5r4mMZ4DWcD4vE9QFjaBA7pgFjdEEMnfkIwjlUW7t5a8Xpzt5htzePtIkezvngYXLMNHhksPxJgMPc816ObOGaHX7xPuKRGGGNdFoyOsQrXreVoV1XCxur47LqfxpOa1J002SdCf7wH/5uvO1tb0GpxFDck4Utzsceexx//+//fdw6OcG6LBDHQQEbnMWNIkUxxiIBGoOmDeuqB4s5qpFcScpoSBPWZY1OB4QhEo5YIzShF9O83JKVRMR9M5Q2Q21ygFOEz6iGEbe+xnOPxsy8kxVlrmDpbFbm+OcibEMagwO+sqTH555eJspciKWY8DaFN94629jfurJBa8cAFL15ImwwbMFW8o1bIty3Db2uxtDojk2qM0ZMZ7i4ULXTnxznZSFIJOgw4G4Abp2cmPcOFqvowWZmQgM5+gGfCA8yQid+iXtvqeiloYdLCho7ZvDwap4oqpP1Uws2iBisMFbT0ftNeT/ex/4sYvcZy62JUZOqVkqF+O+XyVgL45qJ91+t+8KmbCAF3v2AqmmHYTJFXrqOZH8OCGKdM+Tm3IUjFAc6O9dy7aaxqlMNtkXkEcSofRe2Cy4em6E92nbcXKsjUPSKNeExzpU7ceaD8z2sY4cly1xjpU5RxFJcZpGJOGLuNLbjCgve7Stct42hXf10JU632WzQvf1JIXY2Teh9xXd82zfje//IH44OBXzJ5kPyyKOfxc/+7N/D2W5nAjNi4seklwCIcNRI74slWzy0UrVwHVCc7VYvP01SlKgl0eLU7I5DCYL/aFVRHnooPMxy8fLi4sqcZKUgiOFpWlcs6wIFW42sgfuaR6k4O1sBdVqSA/e2srzVDA8egdWBI+lU0KwI4yKUYWy4+EX8ObnplV16UznfKvaANz/zAm5dFZxdUXz+YwvKfITegCITiljiotZiMh595Ec2RL25j28LyCO7kNr4m0GZvW8Zifj7fXY5reVwwXdYgvP09ATb42M7ZOAhdkOEiPyuLmMXYhqTITIg7ic1aEmWs8m2MWbYnManitLTMHUFpNtGnWdvXz0cRJRLFC/nJY7Le9OImmfqgt7+GQDhJRvUI+HBkko44sLioL3xyr37hMPmu/3Oo6vDThLTNKEzVkcyBKItuA6l2/AQ3telJVy5LK3vHivpLNhIzJRFLrG3dcXxhS3+1I9ewLd++DrwWeDd7wZ+4+MLulbDdDgGsINTtcRaK2KFDaUaNKXawvOmSbCDx59fhxL6ODxSgyQOAeBVjSzwasDC/4xXbw3b7RbHFy5AQDqQTSizwFOt+Nb3fhN+6Ad/MMoxz1+PPPIZ/IOf+zncvHnTwzjbhFTQ2i/7oDgR8wIAkr7JfaxeLnp0tHVPFbh44QK096BM0XDtl715CN4Vl55ZkeIqXkb/auuKeTMnSO9exRTUscSorZcSw8vUQVWv0VdVnJ15qxqwOsXDO6Jfwuw3vTYhHIUggw+LJSlrTJQdJtXOX/SitmXB257c4ek3zyhlwmceXqFKY6+WXBwMh/1JzdQMxUUYojpGG0wK98pcVMaEh5p7+xVTnXB6eprvMTyjwHUg4v2GENjDY/FEJWOi4gURYwKOBoWHTzQLhcSBHZ0WVIMNQXFxg6cyM28dhVskoOpUvUDBDubeOpZlSanEUlxnOd+vuxrc2EKn1uq96KYQkgEMPtnv9yZ25B4txAwPVevUI6ll2ePk5ASLG/dxMF80voMxDIgoAFqFiBVNjPgphrFnFEYoBeKQhySVM/dpRy0rSll8AFYUJWQh8T8a7kIjGlGcuJG1Z1A4x5rwgO+Nxp8hIwVbh+yq/VLv/rLbBMBt5NFut1tAjTs4eU/27WaD/W7vyRjFZp7wvvd9M46Pjw/0Dgx/Kfj8F5/Af//Tf89CcMdcidnYCWbDCAjqZNUvXRdMk2NvxbDPdTXmwNpXSBdggnNazVCunqmlYT7aHoHC0uKkc+tvZRq4xfHGeZ6xLiu2m60Zf+ePrq5G1qJ/E8Jjo7EjhQiAt1vPDVtrCnJY+NnRdfFmfFvnRyZXFCJwtlJkrRMe0TjVIxONLIHmf5uqlFWXfedZw+VTxT+9/xjPPXMJZ+00PGf7DkvGAR7eC1BkhnhrETiEwSorFneQDE8vrRDH9F5uZ2c7HB8LdsselzeXjD7kGY/Cr1fg7PTU9FynimXppsLvuCWxVDbfLLVEtMKogJxZXt3hB6OplYBkKD1Jz5QMB+ohiJCcLx6utoCrWFSTTSEV6lxb05l14wTBvJk96uiAH0ZLRGMGGbAQYrPxsRPBzo1s2E9VlNkMLIRz2rDxXl5AGhV+3oJLwi+5NqZpcqWsntEbMU0phnv62BQRrBG2ZzjPg0sVKAEneNSGBmlZWQZ4ZCA1DrcwfCJe7aaWZFSvLCwK6elQdOIw/t3wSjUg2/1wXs3hqyhlDthtxLvLSzh943XbGFpqRrJkFkB4jORIvv3tb8f73vc+nAekAeDLTz6J/+lDH8J+twfgteQkY1czPtNs3hR7XbVlDyuztAEtXh0EEfdyqlPODLdsnhFl7yZ+tnvmXod66dWNKJM5I3cwust2q51vvQHWjBdU17Lv0Qhba6WoC8tfs4ihlJTAizpv9xTo9QhMzAbuRY4hEBv00djSoHKz8bPjwmL2GgD+/HO38Hwp+K8fv4JL1yuu3ZzB1AeLDXozwRXbc9nCvVY/LJEhWHeKH7E9iHFQN+c8Xj5LHTB8u8Whh8XxJwZKT5lYLHcbuwooDbZ9Q8A91cNoMOsPFkOUMI58Hhq31hqaIDrzKlzKryRLRnt+d4l72QFLPQcaN/ti9/jExbeJdw6wAjHRmEcaLI8UqXzX2mrl6GUMhakCd+im8aDQnDB7Xx9xHuTpW9IASUgndhcChxu7UgSr/7dJJJBihlCt85EG5rFIwle4qhlbzaiFa9MYIJmbEAHYfDEMsjsEwXryn3ePoDkWPAhHWGS8/gB5tEc4Oz3x8HAMez1x0Fd8//d9wL0c4mc23zdu3sQHP/gLePIrX/XM6npQC2/Y0w7HcmzeqMApO54hZljolJtI0PiETd69YfJKkTJwBHnK11rR0T30yVY55t1Yea51eRh5mTRk1QgipcT3pxbrdLC4zDgZVen07BTz5hhAREe22Py7u2i2d4GHOkUwCftlnYcMzMsKDYARWgFiTGlQVBXv3u/xgVun+Ft3XsWuVOyuLYAaBpk0IjsUTLnfEyG+aSPqQBpwHkTaO8qUHGYaL3qa07wxUrkaZa73Ho0e7Ya2Rr7xG78BDz/2GPra4jD0DwzGtWMksNPzpOciLvrCIhKXoHBvuAfZgfQ6y867ypaP6erVfvxu9tTiRl6WFdoXVO+MS6+aGquAs0k6PWCJ/QLt2aPLD9u1JbziUbl1ZhDry6f+Xl1X9CZh2Kz0fTBEvqYUyThpLMwJ7m1CfABxTpjYy+QdeV24mwnX8F798ARoEAdD78NFb15kBs1WB2D8RtemGNYQbxnHGz10CCjHwDkeE28jHMC/V2dlGBd5TIjKwZ+vdN0+GC0J5N2oV201zJYT+03f+A245+470QPTAQDFyekJ/uUv/is88tnHQEzQsCdARFGq9afK9ssWzkRGWN2LHgaaXqiOVT1ONSPI2QfPgNioAm4EKRqX+OfeW+gsyxIGVqGeyDAD0ZVpIfuOEBdxr7mIYZvcOMfHRyiF9dn8vQEPc9fCvqe6GEkJHPIQ2OcNDhfN6NkCWTDB5Nx/+cw1XCsFP3P1EqDiXEhAJEuM61Cs0Hp3D6o4PSw9IHpdLGclNkqSPNSYCb1Z9NBWY0MoJA5QhsEcSYF5bZPTg4JV4jOUGys9Tnq7gLUXZ/v0dW2xmeOE8PWkMAzPqryG1tvuodZSnW5lc9lacw3hDF8pZE5Yab8sQzIp8wact7auWLz9vD2KY82OgScMZdoFKerOcLeiij9bZQjukpChOZBGlsuDySGuHfFxb4PRrS6mbspiFPPpqW/g/27GOLH40ass4mWyzcSGdrsdfv3Dt/DYI4bRfu5Lpq8AMaYH8X/xQ8Siyx4GV/vgtfN1iusLw6hoWV5PkfkObd2Vx1iCe2iID/Dnl7luG4/29OQkJPvoCdB7Ojo+wrd/+7eH8ApUrZ2wCD716U/jN3/j32J3tsNcTWClr+oJJKQ4zEDtMqUk8w50BTYba49DcjxgSv/ErCjmsjs7s2cYPK8AwzGEqSLpGQtP7gzoWbZK7jAgwXywcLOnHoAMGJaSO2pGZONtemp1HNDHTgeRZ3qWQdvSDP8By74vS3oho/ENnVX/n5WIUqug4S/vT/Ctpzv8nffeiSJb4NRKMQsVjUDs2DFNMMnV0fqK7t0MmLQxPV/jFU/eUYOaD72k8M7p6alphUZoDKfu5YK3DWDvevPmLdu4XnNPpS97whFK4e+X+DdWw0W236ONGMOeIibk0ao2P7jcWHjnWK5renV8jtY6jqYjkO1galKKtWeiK0R3hCG3t1xSuBBOi0pK8/pNkY0X1yVLbwUISU9GOrVU6EreLGIMAMdS5bB1E+DaGYo4HIEBenJdh9BrcL1niwjJBpCs1pJcMzKIf0sRrN26QTz8eMO1pxt2Injm+gZa2PL8YPpRyuTdPWCRzbn7k+0joU6X+gsSSUtKbSpASluusOEL/wB5tHDXnHxHKYJpM2PazLjz6lW87a1vi9PDP4EOwbPPXnMPqpgsofNHtJcop7NF5BUrmmWm5vrYYh0TP8z8riv1Qg1PZYdRLmh3noJQH+IZJVtgF+d+0kjyZA8PXo3MTvrJPFmTulpKKCgx215qxTTNg9KXJ8cavTdESB5FBcW8+1IVxUN3hkNF1Lo0+Cpg9llEQjmNrchrrZiKl4ZC8Z7dHv/Zk9fw1Xcd486fvAd/4o9fxsWLFVJcxo/el9imKlPCHxYVuk6qe+Olmoe73WxMKMi9yMpkSrdMvo1HCfybSmff+33fG7q/cmAkFL/0S7+E3W4fiUC+IzHQWqdgL5TBu4uEqySHUtWeY7/fG6NEzVuzsDZhA66LZV2jX9yYIOShJg5fLMveymEdDigi2LiHNrIUdFiv9nY4eBcA2bPOPbIYs2nCZp4x18nGlGtyELepTKS9RDhsxrVYZwk3jgy/GR1AzbGo0xzi/b7pOPGgGDehI9IhAYn1wH3ewWos2+Nz7TjWjn2xw8hJV6Zv4JKPIQDjalv0jLkeOD/TyDQp5MdmAQXfeXQVsoEA/LO8wysb29vG0EZrmU5B5yUM4mazPcB/uPDPzs7wG7/5G94DScAuryKCjbcvsVOzhFDNVLMOO4VBSpzu/JOLb8xMAyxVpPpRio8Y93YNInrwP7sl4VhpwzmioSZNjSEpiwzWxqqwHgkyVojRmNy4cTP5pMM7sNptcp6xhbFTeDE0nCb7WDBPc/wuxwKgYLk9c63Wr22z2eAu7fhvn34ay5WK3/lP3oLji0e48fwN7Hc0OIB5NmQ6lBxrN0ZmGKiIZEaOSSVu8vz+DFWnOuU8I/2K1z/0UODRYyQnYsUp4c0AMV8JHxFrH0AdZaFK8rR5gOVGsy8jW0RAb7TGYRPhu1pCbwkqFoJFMc8bgx+6DrCVVebxUKHHyMRraw3Lsga/l3NXSrYuYvQT+0adYTJAWuwcbfmKNeC18QqYgHNKjxNZHMB9x88S1qBSGg3u4Xtkpw1S6ghL8P8V83RQVHB8JPjxH78f3/LuDaZLFe95OzDBqwHBcdbwPMeQnge/uFc+PjOGdaTnFpB5wuKJxjzozl8vcS4dXLcNdMBFzvBZRLAue0yl4I/9se93rMW4lVMRsKPs2ekusKF1sfC/tT3WsodCsS4dOjl7wDfUftlju9mGp0FZxBF/bGvDfLxBc9y4RuWWJ4Xci4yEmL1EtC63jdIw143VpvtnDHjvaDvLhO+XvS0oEayrdWuA6uAJJ9WqlIKbN2/i4sWL4cH4cgEXPTt1QhBJm94RWXo29KOXbNVxHRMEpSZLAFBMU4nqLksWFVRR/NfPPof7dg0f/s/eDtx5EV/9iuDffWLBqrewnS7ZBleThVSYYaie7KmFCknGNJn8MKW4ztHx8YCj2dttNpsoKV6bU8X8/RSKq1eu4MrlS7GOuJY6BLvFSqBXZfISnhDj3HXTJvCNYmXZxZNk4oeOJ3oGPI66tIyv2ro4XiuOF7rmgHd9jcovNdpRV8VmQy1aX3uqnsBiMrKhdztYp4HXy1LkWFNtjcOL0A+1MSL8dUoa2iDrKGMZtUNUXbHoGgmi0eimlwdAjSZnfeocdvGckwIebgMglF3s/qH3CjUqlRRfI3BYIr+zlJIwWDGdhKPNBpsV6JuKyk4O1MeIg9IN5yA67kFHwH7+V3O2/UFfzS8lrBM4h2apr7zib95GhrbxhNOOquZ9zpP1hbrsm4gLoa0NWgW/+qu/ah6fZ/W7i1FYQsRC8qZGFtfO8GXI9teBmM4TsffYGPv9LnEiP9XgC5P6tMRS6U1Y0qtGSFWKeJsQP/0ZVg8TVkoxzFEFm81sYa6U4MeGl+3QxsnJiXv6s9fV2+gw9IGuAWuEx92TS0tRHAwLurU9eqMngGBaiACT81ZFBf/l00/jDz13gt/7iw/hubdfwo0bFX//Hz6J514ACqw0WBUeTbSD5IJ5RMQx7blYlgofn8Aa5zkq5vb7XRiLaTIBD3XPWTvwuodeiwcffCB4nfRORIB/829+DTdv3sLRhYsRKlMMhdQu9cVF/qt0piT9GVvntMd4MdkHTb1cS4gxoboGLktqUJTs9o6UT2yxxkqtmB2bbB5ekw0BHyceuKSAMZHJcRv7iJH6F/Q8N+Jm8BukGyOCEFfXEgne8RpslK9ZN25Rvp4Ho2G5/os0QoOxZl5DoojGer0xaZXrxccqIgIz37VOKIuizwVNiQELxI0q+dCWIhVPnqdHLlz2BHUdwxWrNUdXBJVSivNqByhhhFTyvoi99HLXbQMdLPu9ZcaRGGNXxTve/lYrUBBONpNDgq9+5anAx/pwck/kw8KM07qsFm45G0DcIybfcV1X6+HVmo+9RChGRgLl3QCbo3VdDyrMCDfkd9u1etgaTf3gJaYOC4gD7VZ2mH2zVm+2Z5VgZrCIDROLpLJQcUHxsZIOPlZlyFSfr4CiVySSLITZ9SWsB1P18SgoWvC/e+oZ/JlnbuDRH30AX/jBe7Csx/jlX7uJm7s68FoBiLfKkQrVQTREnEdbGX5atRNLSKOc0/meABezeDUefNG7jKRjZpcuXnSHip6LHTitA9dv3MTZ2S4xUhxWKdlmJ9UpD1uDFb0aSHgwZFIsvERJbLsyQQX4IULjxxLrcoB58yAkSyU5sFlt5k95UJnGi+F2RDeS2XK+A7m1gCU+53kK3ysxXEVrC8jICIgk4iUBwMy8rx4tUJQY0wO8hnvI3VntNIIeMcFLut0QJtaZv588bZtTC+HVdHqXjratKKjA+HveIjIOUrcT8Dm2tcMICmHEredYJgENJZSDuYZIsEYSzooA6lWvr9ujFZEK4N8B+LKq/oiIvAnAzwG4G8BHAfy4qu5FZAvgZwB8K4BnAfw5Vf38q91/WRZcvHghQgw4hvamN74RFy4cJ5bif167fh0nJ6fOtSygstd2swXAELjFYJnUWsu6bmmmOeuxzoifpReoXinknRPQ3CBOODs7iyKLGG2vMGIYY99rMMNIk1JV7M7OPPowb2WeUrlLAKN79cQQw5j3hlrn8LiJBfOUFmSyh+Ifda6G+fIw8Y1JTQFxQ91c/clBBmcyCBoa/jfPXMdffvY6Hv6e+/DZv/haFNng0w9P+J1P7dC1Yq4Fi+5B+hATHtWLPsxhMAPM7zMvVqNAge9fSsGy32PezJaALMXDfRNZv3B8ZOG1Sz9+z3e/PxwUtvSBAE89/TQ+8clPOaRC6lSFgEyMlMVcebDKUGTRs1Mvw3lqBKhvWpHJDxc5MHYiiGQmM/6qyQYZlcqWvkTrcN6bdLbiCToaS0JTZoAUQrK/H1qKjBZoJIrvGx4edTJq1fg5awyqXjxhT2JhPFdD+LXhOULhDBP3UDtLe4nHJ1wDWGlrgcSz8B9YuBPGebiMR24JuzoX1LrBtG9os0lLmtzolIdJYRcP055F9++EmMoXv9VwDxQIquRcmJlGRF22tUvMMcdgtEUHh8zLXL8fj/Y/BfDp4b//BoC/qapvBXANwE/4z38CwDX/+d/0z73qRc8T6ommWrE92uKee+4B4AZpmIOHH34YX37iCROaaT30a9c1ixV4MnLhHmSay4BNMWQEwpsIqgfpLIW6rrbZZtehNXCd+HLqlvLeZbhf/K9W7wLrnNZCFSOAEz1O6Ij99Wa1/qVUXLp0CdvtUXiw8OfvxAR9Exr7IiksxY1w9Hty+MKyxdW9KUEpHRe3DX/t+Wv4T55+Dh+64zL+xoN3Yr/cgce/0PFP/9kTaKvT12AcU5NznMKwQZnwK17vLwdefy012rr0bjquDEeXZUXzrD3XADPvqQEgODo6gnmqg9ZtV/zeJz6Bs7MzzJtNHIjE5Qhl2H0RdCsaSnqUuW5KVoB52qS57myG7smKYFKRSRjoofEb239PznwgH1fVkq405gYLmRGZp8mz8P7sAMgPDqeC3+9rPWiB64psDzQafddpKCb0YhWZjChe2oiIHHJOxUNO4p/wPRWhKMzwjgpovAitEO/m6ieubHMxYdkDH//tp3BybcELZ4Jnn2PxT+5bfzp/Dom19KL3kLEIQg4ggdHYM18x/NqLPvP1XF+XRysiDwH4YQD/FwD/e7Fv/wCAv+Af+WkA/xWAvwPgT/jfAeDnAfxtERHVVzb7V69cMZ1RN0S9ddx19Q68853viE1ph6NN3unp3hIH3f5nVUAruuaE995dkNnggpT2c7HvecKmzjg7PcNcitNMyoHEoUVJmWAYNwK/hwbM6vGLh7GKudbo0BDeM4YiAC7AYhgoiwo2m00sEG549l7a+MGydsryLYGn2r0E66qhcdu7qW/xO+1rpzAWEOs6otpxfCS4cmHCPJ/iHe+4jH/vnXfje/6738Frvvw8/uH9V/F/vf9ebD5b8eRPfRGnyx5SLqKoYcvKCqPeMZXJuccdKg2QCTM7ZajGGESGWyTI+5wzJgCr80KnWrHfC9Q76iqAaS5433u/OYznuKG0Kx5++BEUx3qXZW+Uta4gz9W8aeKREt5wGrikanWvCKtB5+F6oOhPB2D0PkV6O4a1Zy8JOATkkwXhvLkR0u7j4Vl6CuKoKsrM6IMeGvFRCeog70XMmBhtYOJ+mECBrt7mXAHVdC46NSjCACBgAJb/UtySvFp7nUMVMYYLNOhTJEJ7JDJtP3kFIfmwMQcOE7mtO90pfu03r+MvXVvw3Ax89WsdwByHgn2XR36NGKsBClIqpDdTogtTJFDxSkR/XnEYpArQHAIB1flcj+Ncys1/75Wvrxc6+FsA/o8ALvt/3w3geVWlPMUTAF7rf38tgC/5AK8ict0//8x4QxH5SQA/CSTHb7ffoQpLLU35aiRq06u9desW/u1v/maUNkYyoVh3VDNQrt8qTsmCROPEOlVUUq+cAmbDZplvLVbGuCwLqgu7GIXMII6jo0wwlFqwtjWSCvvFqseql45W9+r4fNGK3MtJFYnZjnQjbvSkGRmjoUpqDpycnJinUw9r7VlYQGxx8gy0KCt1XMSmI2g6f/j9r8H9dz2FN735Tly5eBF3fWbFN/7138D22R1+9y+/B//4hWPUz92EArh+eoR1nVDqhGnqXjTB1i6GIbMSLviuzTxe0tZsDFKhjV774nq09AijiKFmr60xjH7zm97kCTb3ntyAPn/9OlpPPi6TR+q1spa46geGgZi3HVCAeF1+MDY0DRlEAh7Jwl28aG5572ivtDqmXkokchnFRJt4uFaHVyP1MJLmsQYNLjw4hbc2DC+SVVZWtGDOQVR/0XNXHi6EppKCF8HUGCYHNkmjK0z421MM4trpSaZXyN5bBicIRNhtIaMK3p9OQiSqRaFoJs7UO3ZiCTDRYuQuGUtvU+sgnoUY9zBigiwIIlxZSFtzcSVozzL4GI/RuMrXBR28qqEVkR8B8LSqflRE/uir3vHrvFT1pwD8FADM86zW+LBj3h5Z4mCu+FN/8sf8syx5tTbFDcAzzzyDdVlxdHyEXbM2Kgpgv99juz2y4VA9t5FsoS7L6gOdWX3Vjs1mEzhhrdUwy+YJNQ9fazGRj8RGBfM0x6KYp9mLFQqab8E6Zfnvdtpg6atjVTOKdFTdQKDossPR5hLqZkHRBdoUFac43qx47evuxcd+p6AXD+38jekFWDJhRe8uclwbipcmNl2x2S64elxwPK1405uv4I1v2OATnz7FRz/RMVegr8/iPe+5iltfeg7v+R+ewUP/8ms4vf8CPvx/fj++9NAd0P/pGU/OMNvfgbJGyTAPQRNwSbxwu91GyxdidmMyqU5TJL/M2Lj2qwj2u711dKWQj4h13Jg3gAJXr141XD88O3jMCfzbf/sR3Lh1C7VUzNPsZcDGeuiwpGcZDaiq2/syVMT55ncAmJxa9sUiZicA1JORynXmmz70DcSpixWhINVA42bfbyXFPcqQmRgsamXLNBLdKWnc5OIHmlkx853HrU/ltzgoCOsM/cJErdQ1DON520FjqkxmdQAd6tq6ZgwziW12mFn+NJ48UEXdmMEpcoOxosNAr9zGXnFpu8GP/uiduPuxR9HedAVvfO0FfPaLt3wP+JqKHEEafAF58OoWlhCSHsAGo02wjx2KyIxJ5eFhHR55ZZ/26/Fo3w/gx0TkhwAcAbgC4L8BcIeITO7VPgTgy/75LwN4HYAnRGQCcBWWFHvFa1kW06IVy3b33nHl6hWMM06Q+uMf/10zeLoPXFVVoxIlvBsxw8gklo1LUp1ab2FktVvSZ11XN4wDVAGEoVQA4pgnT9LeqQvqOpk8jd0L5emnHSiyAv0a7n/gMh56cItNnfHkUwu+8KTgaAP86Ped4G1vVQA7iDZUMU98Laf45KcEN5cNllDbslLM19y7wWteU7A9OkLpN1F7Q507jq5s8bnPdnzqEeAb3naEP/HDe2zKiq6nkGnFtLmITz52Cm3A9Uf2eMezz+ONH/oK6q7hN7/lLvzL7347Hv/0ik/8/O9h3lyxhJDgoI9XKH8hixFKsb5WjOnJBIFkRnt2KczwDomtgsUgVkpNLJxXaw3HFyb0VvC2t70db3jDG2LDcKW03nHz1i3HL50ZUCZP2Ph2ElKCXFhl8KYy7HdnRTXm2bwjDW+ThqOUTAjlPRRAqlGZFixx0aGUF2xaKGAHYv6ejVuB1ORTh0i7erub8Pw8RJ9m9GKNRUknI2c6k7JjHEf+NQ4MMsXsmY2HH6bmzVuYzopLHgNhJP0bxvbpNJzEyO3zh0ni8e/jMxr3W/HahzbY9o7t1YqLF1zDRK3d0o2bt6KjsAC4euUyNs7QSfjRbIPCpTFpP3wiIncwJDbHBDmbldrHMorKY/Clr1c1tKr6VwH8VVtT8kcB/B9U9T8SkX8E4M/AmAd/CcAH/Vf+qf/3b/i//+Kr4bPxXV2NQbCu+IZveI8lORQeRlMJCvj0px+OgYJYZrtO1olgbat3lZ2i7YmqVahQmZ9QAAWKJ2/DrWAo7Yu/rYZd+UbczJuD05ahlMF8WZ9Nr6D3BRcvFqxLw9IE0hUPvOY6fugDR7h8YcHxpWdRRfBrHznFF758FSenp3hwM+OOJ57H5tqK7fWG+VRRGlDaKX78yYbT04KTWnFaCm6o4uToGG+9p+Gd31kgl1Z03UPVkngqHTdvbNAf3+Pm2RF2p6eoFwDBCl0rXn/PBn/0+lfxR546wQeuX8dGFR++/xL+7298LT7edqgfvmmLUuZoe01Km6qR6w1P995jjiUzbIXDFuvwM0Il62rzxOo1GtPeGubNxgocsBwwQbgAiLNTRGSsjgKAp556Co8+9hjY+YIeKhM/uaHVhZ9eYpP4poqwWNXobgAgSedjHT8c4y2VGgPOpS1J0aLhiHft1sFgmiajF4WXBb9fd/HtrKhix9uggg2edm9D5dIQwktlN+FU2GKyNJK5kSTVA6/tEH30/xrmg19lh6QkJ3oYUxmeJUIO4MV7SXNPBZsnjQOKVEifIbuGZ75wHevnT3HPjQ7ZLzhRxbPHx9iJhJNz+cIxME8YcJB8HxFMPLDoYcfzZMUoxyOjlDyEQdxa9CWX0Hj9f1Kw8J8D+DkR+esAfhvA3/Wf/10APysijwF4DsCf/3puRvxye7TFut/hLW98A7bzJkM6Dy9eeOEF3Lx5005f7bDExgqo04Aaw1ILS6iStMqaSSduNrCtsT1DcxyRiklkMlgLDhtJhm1MWLXeME8Vu70VOlTpeOC+ire+6W6gfxHf+r4H8KUvrfjQv7iFVYE63YcHHwQuPXcNV3/rBBe/dIZ3fE7xE4/ewGtPdjj++JMvO0Zvf7l/+ByAvw/srhSc3ltx64EJt+6bceu+Ge/92hFuXCs4euEmsC7Y7ve487mCe7+y4DVffQw/1hXXa8EH770TP3fXZTxx6SLavkF1izLDjGWxsmJ4Mqh44rA1k9cDTG9VSgGVcbPgwdxChbqOgxmQeWOtv1meS17zsq62af1+XOCm+DWhlmbJiUnwLe97XxgmEQCOre/2C67fPAm+KqGWRiaGSxuaIe3ozbC56DzA0BHUaUXgxd3Hwb63QL1zcI9WQgbjZBLK8FZjEQhSEDy9pGVZDB+s1T14x4mRcqFcm4l58tmqHwLyooOOBTU0HpNLSBLeEEmFuL4uqIPITBjsg8sNi7KXlosV1QKwGlI1Ir7ilYGMdhgijIYM/j4FkoLsSO8XQtKXQNc9Pv+LX4ScrPjKY9dwoxQ8ffkyTuYZS+/YrytWf/bLreHBp5/ByQP3Y7fd+NNL3JsOOiODtJQDvc6vpmpNXSdjhgTU4EaWcNorXb8vQ6uqvwzgl/3vnwXwHS/xmTMAf/b3c1+AE06RkBkXLlBn1YBz1nd85jOfwVNPfRWl1KAGiVhixRJXGspZo/e1LAs2200sUoCeRbYeoXFgCwxuNgpxqxo/j+IVDInXtuKeuzv++Pe/DZcv3cCVK1vceaVj2d+JIjvcceECvvbBZ/GOZ2/ifV86wzf861s4vsnW3sDzV2Y8Mm/xkbsv4PTeGTcvzXiuTviKAF/dd5yooKHg5s4yoUdNcaUWXBHB1WWPd29v4fveBlz8muD4qR0u/O4pHrxxigLgfQD+Il/4UfvjZhE8drzFL95zB37r4kX81pULKJvZvMx1DcHjdV1wdHyM3dmKOmUzSrhnYmwIbx7oB9N+tzND0deo+rLwUaN2n5nfs3VF6R0y1Vzs7inPZF6AGH3D0dEx+mrG+/j4GA88+CCkt4H3aZbhc5//nEMRGglRNpFkcGXKTba+zBMsQdcKLvSQYIwsvoiX4lrVVfeGh+wwa3bIFLKycSYP7IJy4O354e0eOcXiOaBjYQN/v7eGZVlAaUwr4XV8NKAPDqcEZQ7Sz1WqHYbTqgq4U1KHbrwAMdvgqRjsNsA1CUc4jAKfNLB9OsJT5WszCUaoiYfPIXTgXm+1f69ffhaf/OhT2ADYA3ji0iV85eJFrGLYPSGKC73jnTdu4Oq64sbuDM+98Q1YttsX3ReChGH8WWwoc3yI8YqI84/HuUsj+2q8g9unBNfLEXtb8fqHXoP3ftM3gdSV8NK14+Tk1LLQEG+8aB7DflnQFhNwITTAyZznOZo/8mfTPKd2QSnoQ5iw3++D89nWhmme0Ho29CvepK1q8a4MHW9+/YRveu8EtKu4cfMm6r7jvl9/Fvd/+Hnc83s38MO7jg7g80cb/KuLF/CJO2c8fOkSHj86ws7V8JmZr62i7RvYYtm6wnbo3NGXFbcmYD9NuF4LPjdVfLxcxD/8oqt4XSrQtwJbVbxmbTja7XAsBbvecVoLrl84xrNIsJ817ejqhsOoT1bObGPZuqIvqdeweNPMZb+PRNa6WrdeIInqxF9rLSFuon6o0ZD23rHsF3sO92p58NXweOxZl/3eRKS14xve8+6h3QnCiLa142Mf/Z04aKHAheMLzislhp+k/EJP2J9bS8EkMvThsvVpoXYDjUnwlAHXMa0W2hbrngxfuaRU2ZV6GiLc2ANW6WvA/v3Q4PCzxA7zmbJiLMJa0Ai7NgIGo+uOjHqkECI+QWEsIWaezwBLgGH0tO19AtKA49RAQHA2ptkqJ4xcFJUM2GxxcZievHeybzY3b+LKU0/j0rPPRXnwAuDKfo9n1hWnvIcI5t7x5pMTXPHk9cUbN4HPfh5fe8ub0Kl6B//+DEGSHaT54wJv+CpyMKb8QPpsI5780tdtY2i5EGqdUig6U51QFdy8eRMf//jvmNfh2WFoR/XQtpZi3EJPgBCjI2tANxuDHEJyz3qU2eAZ3BCKVxTi1jU2sYnQdHRR9HWBKnB2eoaj4y2kHAFtwsWHv4S3fegLeM1vPINp3/Hs8YR//eBd+MX5GL+53eLW7P2/nMYEmCcz1yloNyOOBlAxzOld02DMOhMLwNpsjKpHBksp+MK2os2WHacSvkkvUKuT2Kh62L6kcQPCY7WuEHmGk2K0jjigzxcLOwjT9G6aFUC2yyF1awxzibf23l33wRe4mIJT72a852nCsnS8613viuexaN5+9+TkxN6T3ijhI7XebmYY2KHADDgjH5Zbp7dHTDWLIHjg67CvbGiHSjilARZgzTbu9vNzOgLEBuFFEp7E4s9ZHUgDP2bKpWbFmLFA/CAp5pHy4BYhBVCiSnFMeiVMwjF7aaNBehTxYIsWxiTi+c9mmQAPnRGTHa/AbynG5fc4OjnBPV/4ErY3Lbk5++fPANx7doYO4MQxVgDYqOLu3S5uf+vyJRyfnuLStedx/f5705su+bwmh1lwaCw9huY69PxLwFT+Vl/vdfsYWpg6TxHBv//93384aQCgHW1t+MpXn7KNVQUG1+XkhV4BhjBFzWDU3oM2BD9hrWlhOXiK1sxr1D6ZYpQQ6Fcv+1QczSv+5I89gMcfP8W/+9jzWPYNx5+6hjf+4uN4y+eu4aQIPnTXFXzwriv4+NEGK6pTqMxbsj7XBaVOWJsVHCTXM9+Hm6iUQ3oO4PXY2rC2jrlmt1CGca2fa+4I5CahME/xjaCU5Ksh+ddV0XY7vwcb6hlMUF2o21S1RhETjQz3uARbhK/Jj8TZWTAyou6/Z4GJRQowitdmg+5dEiCCCxcv4vj4CBG2DQboNz/yEZyencV4SLED6uKli57x9tp/hyMU1JO1/3UfB9KVbB31WF/sQtx6EunZOBLwTg++YVVS/IVzAcihkRuMMp+ZNCKGwnxGGnhyvc0RNZ0AlWR9RFtz//uoBxDULgyQAfcZIZPRGEZYnBAJmRqW+OXKYuGBBGyRhlwjx2HrOVvzKBRSCRE5hgsXh+kddzz9DKazM7RSUHrH1u9BAv/9Z2d4uUsAXLpxEwAwOQ4OpLdtTi3pZof4t28LnweFCnF1v3eaFzfAf0CgA4puXNhu8eAD91m5NCtGXAPz0cceQ2sjkdgSMtYs0e6x2W6x3+0gUjBvZrTVq7WceZVGzDC8Vd3TijDQcdqaoWGTBu2CLhbO/tAPvgbf/J6CtzykuHgq+MC/fBI/8twLeK4W/K3778Y/uusKbtYaIS3Q0FAg0rDbpweyX/bg5h4pRq11RJcFYmFD2M4kCz2zoPcMIaUZtBKE9MOxzmojJlK4eeKTfpKbRoTxZSNx4guPWHhUxbnRBF560QoQhq7BPInEJSU80dWjh1om9zTMMLTWsJ1mvP1tb8UDDz5ghtMPI87prVsnlkiDsRM28wa7/S66ZXRnTnQ3GBGa8zn93WxsKOuHwOdby4ID9fcJv80Taxzj6AgCCQ44jSdzEow0SNOCe2dp7NzMUdDen/3APWAILgy7syqQNKzeX47CJsN6sX+vw7wdYI860JxAg+p4rjMG7FB2Iyz2TBHthA4s1xwT0llGi1KAphAMLZQUYFkIPdplmLPhYQ0TP7fm+J7UfVYFRhSaojJx3I77Sf0AU0JEcv4rz7u5L3ndNoaWXuv3fM9348KFC7a4igz/KPj1D3/YT1SfUKfOBB6oiI23DsLhXZ032xqmIpF8KKyzB0IzoU4FtRcPzSani3UIKnpb8Ifffy/e9eYF+90JHvi9m/hrH/wCLuwa/rt778RP3XUFp/NmCNX94RXxHI7Bh3dda8G6mHrYuiw2ubOrfkV/UQp+qGvnAsfHx8AQjtEITtOE3W4X0orb7dY3XAtPok4T+n6PMk1AM69uqlYiaxxXuwd7nBE3LSIo4X0nX1ZLFhmQyzxWIU2uzkUNC2OCZWno7B1vefHfDKMeS0oNT79y+TK284y+dlhpks3zE088gcc/+1l7JscTqTW8LEuwHrgTubnJDzZsWqGtD0UhdoDHnlejMYW3yJCflKvh9yheb3Nh31VL8ZpnWxPTVKLyy/Bww4Gr6oExzEgHIeZO0Zr4TE8PmeN4fpcRBguowMcUQFD4Gg49Xdt9HgW6MTZmpJs/htTm/voha8+JwOqz2swMdN5/8n28ancRmJgcLBeOsZyeYXNyAkDD0K44QBkgFbjyIPB8A9rTgGpB7ezdN4yRHsIk/DkTfrXWg/cfk4tAMiXoxXOOXjzWh9ftY2h7x91334kHH7gXomyXbDOoUKzNaDvES1pTLyywCemqdurUPK1LrViWPSZMkGr0saoEzgt6A1pTbAh0V3E9VUVb4SegeGKo4f47Fd/+LRNKuYW3fvBreMc/+Aoe3W7wX7z5tXjswsYxMU9q9BWibtRVjc6k6UFg2ORSxEJ2V2VSKFCADhZ3ZobXaENZL88WHB71oXc9MHbZu6x4wqoG7SpakQsijO+tYYEXerBcVpiQlNikfBfzFExgnHq9hB6KJtEf8FDVFz/J4gCwZz83AEdHR1F2K147X6cJk5qXvz3a4p3vemdIWob4iSquv3AD1649H54xDVQWscA7xVo9fzRwlEPP1jBjwlDs9qro6OG5F0/wRYskZtEdZw1IIPip6fQwIUdYoQyeXhzSGLzfmh1vVV2op1Q/h4cmgnD62FDKLcPcQZWOZx4K7ozNdY65JbSSA5JlO4DNW3fifmsNFUZ/VFGoY58WcHV7TocgxnjbDlYvDQbplvY9XYEXbt7EflnwtBRcuOcevPHpp3Dp5BSMERYMaLcAm4vAlbcDV+8Brj8GXP+0YL8zuGEvgi4CJvR8QBAP4/+XXrYCQJFBaYwwjxWDiOTv8RqLal7qum0MbdeO+++/D294/evcu2XoahP30Y/8O1x7/hqoAVKKYF3W2BDbzSZ6SokYVrbdbLFEHGEGhb3tVYE6u/qPhxStdQ/3jcdZIFgWk+a76+oGP/lX3o0rR8/ibT/zFbzln30Nv3jfVfwX996DXalQuIKSh440cIAvbBq3Tg0DysO58SolsGDGMKNHw2SJ9ZZSbLZbL8w4cq/JvXtvIw6oG+TDDSe+kcPb8Ac0PmS1Q0UHwrobeHomHYr9fgmCe1fF5KGvCeqYVzDPs5Ht3ROf5xm7IXRlxpvzMW82WJfFgxdje8yTbfzGThjeRuhNb3oTCHKkfKHiS088ESXUYBYZFvoty4LNZpORhVnpA2+HYzQm4mzT5UZi4lQ8jHdnOFgrTFQxDI0FAI9ifH6bRwU01iOVzJgV+btZFsx6fQkHRGBesjqVilqvrO3ngTxNqekx8ldZZbjqGpWSo1j4aE8S/tHDQ3f8mI9psBn885Fo9JtMnnxlaxwzcFZg9Ozz13Hj1kk4Cqet4YHWcQl4kUcrR8B93wLc+62ATGaA613AjYvAC7+9xZ03T9FLweLjR6t/HlMVN74BeUkyDfIzgyAQ8KJ7vNJ12xjaIoLjo62dgFxl7qZJmdCiF4Vn4tuCWq1zQl8beu1hxLqXSK7eY6tOFeuyQiDRVsbUuSyEyYytwRGmiuWYUgFEBd/5LTOOpy/hzf/gGbzln30NH3r9Mf7a1buwNIW2BaXOpo3gG7SUyV/BtkOB65/6axWpQBeo9JhAYqXBNmiOU2n+G71WKHD58hUXTeH3msfb++rfL065Us+yWjJjniavOMrEhCW4TBFMGFJ6ODzNs2GIvsmjZYq4U1Wsbl7gBrqb0EwpBWvPipo4UHxeWR46FibYONQYP9MeN53hUlbcd/995gXWbISJZtqvH/nIb1lCr7cIh9vacOHChQGX1ZiXNnh+IxaurjdAKzLq+3rgGWIwQOJ6xLsbD5Ogg5WYH1VxRkvmAGiogmcMdiqgQcjqJKUX72F+KdlxoaMA/t9dxm2kaeTdSLP6q7r3qg5u9jaUEB86bYGnAonph9EmRouO4gqwqgBEPblov58lrGqlwgeeoO2DmycnkXeAj/IiRlNjMuwUQC/Aa78buPebgbMFaA3Y74Fbp0A5arh7PQUALKXgZLfH2W6Po+3GI+DsTgHCHv5l2aOX85uVhOIHHwdndIZe6bptDO00zXjrW98Cfy0AeXo+//w1fPzjH4/2HgJFV5Pfa40FCytIh6nVyPatMVlki29tLdaOiMvSwbPkSnUk18Sl91AKXnPPDu99z4r7P3wTb/8nX8VvveMq/nO5CiwKuPIROg1885N4ATuqLss+PUkBBCYmrqooVSOsQ1BIJES47eAgSV5xdLTFuraQcmT7bCbIKAe4LPtoFEmx58VFoymQE96Jqnd0sEOOkIF1nihgixQmcAin1DIh2+0YN5MezepcWZZDTpEYMkxw8bkojlHXjVUBrqupjFGpit0aVM0jfP8f+q5gaRgbwDzW/c76rc3bDbBfLInHSj+W9XqVWKMWKxAeTGx4ZZJ0pFhR5/WQYmVdH2z86KGSe9tbi4INCstYu/FMdFU/5PTcAdC79bdjF95as68YYRcAcfgZI+dQiWxkMBBXJXOB819UB11mAGt6bdFRRLjjGNYzOiIG4VGPwCrC3JMNqMkjxjIYrYAmeLj5riwy4WR3EtjzeDBuVVGRBqsBkBm49AZgVTOuZ3tgWYCTM2B/E6Z7459tPROc8LcJbqzUAcKxdw4GhBRMxSJfSmr+fjxZXrePoa0mEhJxliYgvbaOL3/5KwiACcYHNOjAmiZGyOkUIS5YJsFmlzlsa3cRZ+d0SolMctJd2FtK0LXha89t8OFfOMF/8CtfxROv2eA/vXg39ETccyywdi0DIb95W/FQ1Hc8r1b0tqJGVKYQSRxVu6A3QCf4M8/hYUylOuMiwzFV9eKKxH+DQE7a2riQnV/J5BkvPnMk1XQIBh3SCllIGRJfFUHbAuyZN4EnluAqi2fByRFFKcYhdndipOhBFdNs1XbEJtduTR3LZsLFCxeMuEpXxL0ME/negUkwAJjdILfWsHWjJUVQidWVrBajxxlhpTCg6lB1OhSJ9kqcL3HZAguHo8xXEicGvVeBc7vt2Uu1JzHB8GQDECcUTSaAsQkk4DSOp93Jq9ZK8b5gHjmRxQBEUcJ4P+0dS7f7Zot1gfQAVXHQAIyMh2I+Hz1yQilpgDTkJaXyOxOuEG/ICPdwFY5xdzg8lLgo5w9+MDLltAKolwC5AOwXeNsi82jbGSCfgZWP8elFIlITsaKjKMclbKBkQ8QRnL+P7JA9wte89/HRoQD/+evl/+V/xksEmKcaOqXnY5YbN2+id8uMRyIJCBUlZpYpVhJJHJ6YvYdU325noivNS3WtmKH5SZfJCT6FasHpWccP/dqz6Gcd/9srd+H5U/M4uwLLalzWDDvHSiC7y+pdAvb7Bcvasa6+eMAsKD04zwr37nq8awxHhmm2gaPkEBLUOADevSANrQKokxlHtt4hWV/dA2lOj6NBZlUdNSGAwxYh8GiA/b42s3Uu7o6j9tZMs8AfgBuF2XV1yCDq/lUj2ujKPl2K3dkO2q0IYN7OeMc7344777gamw4wm3fr1gkeffRRAL5GmLByXJDKauyCECT/ATKgpkDxdyJOScbACGd1jxJoBMgb5n3ZiJGGkZ1TVdNjVY8irOtBMkdIkaNhgOTvjJ0U+DzTNKFOk/UC4+/4vGcSkInUEl5x4qLqPOcelXRjCa4jCg4v8M4Mlz0Yg6Jps9JideYGDZKm5wiO0aAhzfva7yCM98gKGBkQNFgrgL4C+1M/9wS4cgk42gK1Ae1EsHPDOquiwOGx6MILVDHBKOH/E7Ys4sGRCUmeqxJx0LDDVaPS8eWu28KjVUVUw9gPJJ1XIED1WitKdwUmT/4YGXxKio0PShmMyrIuqGDpowQmxYg9MrCh88nP2fN848kZ/vjNU/ytu67i4XWDWrIXGQ0sezktS4tFYhsvaR/hjToqp04bYnVUaCgMngw3mnlW1sbGkl8zujf/G9kF1IO15zOHhOLpNARsRkmYAPCuq+KtZZbFtQ3WCGsDN3ac2XM6FlHsDRqh2Lkpo2mUtGKYjxELzfAStELZ/hqIA0FKwdWrV/F9H/gAjo8vxFhyvXz2s5/FF77wBTdYht+Sqia9x+Hjs+AJw37Om7VoSIi1MlFHcj44V+ptsjOyoHoZja2g2Kb2lL7dx4RmRlyYfxqlKjdDJObo/cWYDck/ro/Wzn0+tQP6ACGQZcI5C67uYLQjURj7cPDpIqT2f4B70s70F+cJKwCpWWHHxB3XH9c0L0s8+8EPRGdqHmIH4zTspg6g3QTWPVCPgasXgTYbXLCeAidasa9Wknt5XXGjVGBOZgWTy2zKyGefpsn7CuY6iPlKGPf3fd0WHi3g6kcqIFRm7X8tpNjvXCoPDdpX9LY4TNCixJa6BVyAiydjgsrlhsS4gxq0E1b60CuGZF07BaL/42vXca0I/vs7LnvI4c8oebrZwnix/BsnK2EJhCvQgQhneJgUF9CgN8NDgfjS2dkevcE6+/Ye2HRsYA+dqzd3nEqFNxVIg+5GTYEopTRIIcO7NhQjwD0l0sSqU77UNwMPSXKSW+/RJ4x/UruAknx85vQEBIIJy25FKTNKmf0wUVy8cBF/+sf+JF57/4ODp2UbZtnt8Su/9mHAqWDsjRXP0hr2yxJhonWOzeQUvTseAjzUloGHzeaXKYloF40xxy8imr5iXb3VUmvO206aGz1lX+iDkLR59jxoc415dWMp0W8tmpg65jk+L73YUiumaRCRQcJEXANGxC8xNsZvtdZQRhFIo2prxH6ugHmwUgApce9o5dRtP1MZoHWjknUo1m5c3aYdWriHFEAPz3yckxnABV/fI3SgHXjmYeDGDeD554CvPQM8+zVg/2Wgrk4vBNBFcHR8BIHCggybePE9+CLdBeSBBSAjMQ0X6UX269Wu28KjBRAttIEXhyjrYnqydZpQFt8gUuw0h8RCUSDUv0yIhRgpB4uZ56GVShl4t8Xk7OpUsHbB3Veex/vfeAUfeOQU/7c7L+OsTs4DTQ+RXMjz2UdODL1NXpxAipZ0p5TRggRVyw0ra6wJM/RuvaM2G/No6SWUMlLHHAMs6ZF1VycjbseBptFTaCTQ4t3goby3qumqLrZjFXnVPceAE3iwIZMmEEFbFhSW60rqw3LTZwnyDEjBfr9E0u6ee+7Bn/qTfxJveP3r/QCSMBK9dXzik5/El554wvUUkApspKqRNhdqURYYcnw6WC6sgBvSdSWPtWUWftBzJTUuKq3ivVM0xtZX6uBi4D1TBtJXhEdWjllKEuRNSD69UsApTf6rZaCwMToROC+HhoE9xtyzHmETE4eRg7UrNERKk+Ien/8X5UdH0R7Os98ljJl4DiLodCBNceCrEtrwMu+jzQZH2w1utRVbV9u7Z11x5E4CR7f5r978beDWNQCX/JGfB/A0cKOYZKcCaPMMnFPeMqfDed4jXKisrkvoYti86aUjHaqv57ptDC1EjPtojqx5eR673Do9wbyZsZkmrJPRlkQVXYppxoqEFzqqyK+thXQifSYS99mfXrscCDzbRlFME/Ad3wD8h9evoQL45HuPIU9qhIq8mESiwRhD2kjIFdatA9AexRW9daAyaVcCP1Itgbt2tUaLPHRrMeO2LRsICi5cuODeZAsjwzFgg0lVG4fVvasMDcl8YKfUjqkqFvc+pRSoy0uqV+wQj4QCu/3eEkCEImBYbq0VaNa00ahaiiJTegsDxtcbME9bo9+Jk8a70cwuX72IP//n/0O8/qHXgXEsw/feGk5PT/HbH/84lv2Kqc5o2tGXPVrv2K8LLly4gFM9dRyzDh5fNvAjlUfDRFGQxp7FpoThenIxyULg5wCgdQWLGaVkd1lGGfb9AnbLtTGwl7JgyhJchu+aaSOThevJ+tm5d17zYKNqHVkgvftcddLc1jAe/A4pzrt27FFVUdQ6FkAqjCvgPqkAEGOL0GnJzL34Pd1LZMhNL9qdBFF/Nt7OO98WpyuiFEAUd955J65euWwJxrbijqefcSWtF/NosQB4zP5DBCGCcDdr7gGYZLKEg8SDk+PIdx9hLX6OgkMcApsHwVjZNhrfl7tuC+hAACzrkq55QET237dOTtC74vTszEMua3FCGIChW5GS9/GNQL3aHDwPk0uJ5LX6lwYu1E2y7xu/8X48+Kkdnn9gwnP3XvRihJyEse55TIbRaxg9CPuM/TliTyPiQ15pbx2t2WKmZ6v+fpvtBjQGTJBZ+Jpei0hmSGutkb2nvmmdqv+8DoUJGQbP/jk2W2RwwZ/Rqw1ckOPvG3nxhGRrHftlwbo2YwT0ISSGlZDO0+zvl0mQWgsuXryI/8Vf+At43etedzDmNl+W3Pzox34bjz72eFS7AdmdOBa+Uue1xhgTcoGOBpAcVQ2DH9gCn7h4N4/A4DUONB5i3eEn9qjSWHMDbDEk6YDE4BnOxqXwljfTQQKT0EK2D89uCV0DewsoiGuaVYoMjW3O2AJc3YNvB57f4RggPVAuSgQSZn8vxWG59PrGSFtyWmK+w1OUDNnnecK2VNz75Fdx91e+6sDCYTKMzGA42kEj23HwlYaAQA/2J6NN9QN89F4PciN9vBMjD482h7ka2S4vdd0eHq0YFefwYqgByz6ruqCKKdCTMQA1AD+62zrFRuCLvXAhC6rAg6CcUBrLSGyJoiuwKYDos7j38T0+821bPPtcO3xk8TLgWs4Z06T1jBn+wGm74cO2AR3XKuwdpShTLlISo6PnvABH223QewCDP+a5+D3YxdPDXBlKcd1DllJMGlLawWLhxluc80nPuPh4TlM16g0Mb2Oyae+JMFYeUc+2KSENp3ZVYtvM7Np30ntelhWbeTaK2GbGj/7Yj5on2zMJkfOt+PKTT+Jf/+Iv42xnLXGs7ZEZG2OEdJyenoZH0lrzQwpOk6uAe4s0sNRiiK4LdUxkuqH3cJNdkQ0KWW2sQZ6qbUQ7uA7pY2nMJZwGdPMNU0XMIQbfBkkT00zYtFRDC+jKW6qYLqy1ORcAMu6JwBp1ROdinpjPYGun85fdx3BVGbDNNJIZHebgWVBgnmMfoskOaIl5Y0GGHZQFKAZzNZgdPc+jPe8lnjfG5/8xcyT2LIwkmZuhw6VQlxfJMSB8cnDLwQN+JSML3C6GFrDIkOssIUSIANevP49SBPvFgge2Yt5sZjcIE7So40UeHlGWjj/rgIpVTQEmwcaJtVp3ky4UlyS8dHGHK187xbRXfPFuwZc+cwbIsVV4aYcoMDk/dnIcdirFaCc9q1r4HulRJ37p8+uYIo1ithPJGvlhMZeOabZwbtk3LOsOly5dQO/qhRoNItW9FjO+y2Jk/raYnoIZ0g6RGmFQqSXahlP6cDN45JSIVJhgD3jwuQEgjLDfr+gdgQdLSdWvIgYtRCNC3muezUvsHdvNBj/8x38Q7377Ww06ooIaPZKueOLJJ/GPfv4X8PwLNzHVirN1xeqlx9waPGBEzAslnmgHm4+r62IIKVPOxLA1qL5WfG0WHnoOK/iBZvMyVEj5xksPew2PLeZQ6EU6+6KqEUHD2KT4S3VKI406G4vKuXsSbIMCbXX2hetgQBF1+x09e52ZQIUf6AJoNYMrh05F7Ek14XDxw4bMIMufdejkFWGEFCzMBNQglawqg4XeHtJDHDen0ff3sql3aGWzgex2YbDWNBMHV3mJn9Pj1hCpciixWDTW3DlAPKM9H7+eBrXEOB/qEY9ww8tdt42h7Ur+ml/+4qpwmbs5aqOX5VAe0DoopLaAqm0IDmIVZtz1AC/rvfkmdKwSbtxLwdvfcRF3P2Nal8/edxF45BJ8u/tpz1APHuJNide5sAYNMJ9DYEpFSdCHr1TiXM5b1aSVWIbaVLw6E08ogckq/KDRNTzHdTWxbX4nPWYmMCS+ODdpEeu2KyKY5ikSFkHL6q4VSw/c78GDo68NixvfadpEHyyWqlplWcckVnY5zxtjTCDlAWud8J73vAff8r73DXNJ42lz9swzz+Jnfvpn8cLNW44jW0i/LEt4rmXgR46NDFmGG2Fkz/VWah0aJCKMJb0duyTxSff4mGxDofasBgQTRRtxz4QnIk/g409FrpGhMlartQFmGGEbW+s5n+phrT2/RXRh9MQNbikukLO6+FnCBcR8cxNq/hXJzeU+KRAr/vEkmRSBsAAIvoc9umK5ucBKdQNHGK6DpOCATcQ8+Z8BG2CYnuGp4+8ixj5wBgQ9crKVGCWRyeFuf0STIvaOhGzO+/nJVPkDYGjTZR/IwcPE73eLn0oFvVlJqoUhlv2eJw8pnUYT6lQ9eZsGT8zDaV5Q1DFe6+Xsi61BteHBezY4/poN3nNHl7H2PUoxuhGEvNAWIYU9rmdom3kLDK+t8ZzfX0zv0zZpde+ohBCJwO5tyQvzSNeV5a+KZW86AhCxhInamAimgarlmgHFyn8Noy1h6Ne22KYHAO0oFViWZi1rmsM4YrjlZrPBbrczPGtZPJIo6J0VNBb6TdXgkIsXt56EqzGvxsldDsLm2WECgO8PfOM3vRt/+k//KWzn2Y1ZRgJdzZP96Z/5e7h2/fqweCiZmYkLinLvl320L6KBYs0/mQghz+jiOygpOVlKCSU0rkXjaRc08TXXvQqQgum9B3WLlEJABjWwNOKIJKk6DMCgnNFZQkbjfzMHsdIQ+/qhQSLm2loP1bHeexzkxcuATddCIvKLYghRi/UD7RTQalrrI6us7L5nV3+2CkY+SHEfpe1K/jETciaCY8E+55kiUkGkUsX+6AjVx27yp2pImGA0tATxqEawXDjG8a0TmByffXgUWefaIowXtsgjYYg3Zxy887Sp+c2vxj64LQwtwA60w8MSoBLBftlD1bqorq1hqlNk+c/WfUy+ks7T/LTVHtlXwDeVungHALoa1BGIU21t2O+uY3rBMpcf/6L92Xs2e+TJa5xc4mseEvHRkZt3pM5kYz/XFFgWF6sGI6mocyd0UETQwO6iNQoH2pCRBrKeHZDoca/oKFx5Q8UY4LS3DkyT0eXIMe3uzVLoRPyzpKbN8xb7vXmpUGDvDIf9zirWyGSwRNUai5jvRM3co6MjXL16FR/43j+KN7zxddhuvfMxjazDFc8++yx+/ud/Hs9fvx4aAZnE6qh1g91uqLkcllHQsMAEpuv8Cj3HVFEDv3PwFM/zZ0XE2BaBk2blW3hJgUhneSwTbTUOdQRnejxQxu9K+l52XRixw6BKCdvL2O/WUqAeoolK0JcgQ+FAbDEP35uXa+vgyQ5YnqEH+Zz81+LQCRNbgAvJCA+s1NcIr6QD0Kx8GyMrrjUqfckQ6U5IfPY8FsuZHf97e+vEubK5l/IA81ADftYh92DXjipGgbKosIQDl3f3aGSIKF7uum0M7doyGMhwzQfdT8fT01PMm42RomFeIxsYMiFQXMCiFkFv5ikJyHukUUo90N7SKxERFFR0mfEvfrXi/adbvGfa4dNf6hCZ41npmVnYSFyH2dximC80qq+SOuLZ+UqyuvdJm1jF5lqxs4D2ekyu8f16b84dttr2gEV40PhpHFVz3nDPPFtA6mQcQzUFJEtQVEyTY4YFKGpdhk0JawrxdAvpC0i6792MTbAcpgm6LlFbD4y4rH3p3Xffhbe85S2488478IHv/d7wHGk06YF27UAHvvrU0/iZn/0ZXLt+HVOdcLbbxaa2LrwS5bVkINjh4BCOt4mO7Dw9lDj8pqD78DkLDkPL5lGQ0e7GvmDFqUXiz9NijQAeyveOvRvlUkxhi17s7H3jFIe6EVwzgVfysJCEF3I9Zmkuq1u11oC1AKRqFtkQnc0Z3cstYuwqP8RGxIDGx57Dn5HJY38GfhW7E9iB3HLP+aAwMqWZVp+jcHq4//1e2hWbk9P4noqEDV7ZtCXw0acJp5cvx3hGvsT3YGGkxcS4e7V2CLkD07rLgg73Hw4k6iK/3HXbGFrKIyY3D4DjTb13k/eb52imuK4Nk/+easPkmCTbYrTVRWE6IFViVkg3sZDKNpZ1MLXqtFIE0oE9CvqzDc+i4sZuC0TbGI0kgw7iIYZ3pedqcoVGsC+lAppJERYRBE4bYYrEZzLRwZHwELsmBCEiuHTpchjrdYBKzOhMbricV7yumOYJ68q+XsRhC9alQapgXa2zbZUZu90ebOTYW8P2aIt17SjSseg++kdhmK953kTIVYrpwF64cAG1Fbz7Xe/Ge7/pvbh8+Qoeet1rzSfwUFZ7c0+2xZz33nHjhZv45//P/xeev3EzvPHQMOgmODSG95adtz9bb9BmRRbVqYAMzemZxaZr6bVJSTK+eTc6RDLJJWZbcngEYAULmeQKuAKeIB0ip+A7DwYT4tLUQ4g9GlR6s5HkAj209O2smIJQB8DuuvZu3lIHa8ATthc62BeiovpnMqjEMHLLshi+6s+pkmNOqc8YG7y43DoWNKMFqOlG7/foZDxocrVPrl7GxevPoy6rPx+iXPm8keffx2t/4RjX770XuyuXTUHMP9iRhjF8VEYKDpMQ72a5Muj1Sh50jFJe7botDG2E2EpsJpzy2BhtwCkBfs7ecF0atkdjg0NT6RI33t0TJJE99I1qmqU15epUIR5Otq447opb4joACihcpxTmIWUhgkIdTxXhpiqxObngmPDoPSuIpmm2sGrAqBJgl3gmES9ZnTfR+QGAMQWmas0Wu2LpLe5NzNIwXnGMd4mODtY9AalL0D0RgXLo7bh3qqqONSYPcb9vTv1ag19qGFzFa1/7IK5evYr3v/+78NrXvtYSbqXGQcKxsUhbXY82N/HJ6Sn+6Yf+H3js8cdwtttjnicLkf2wW9clqtX6MpQ/u3dKGUMaopAZbEDXFhGyeYu2Fk1lzZYWN1eU2A5rlX83/QDN0FMGOpbflB7eiBHHfWhM/bklqH7IMRqMNlSxrh3iiSWK3oxrikF14L9wKEYGBTBipAx7lYY8BYp46fh3zXE2vLPGLhVkg1QZvOJxp4t7rvSGVRW7/Q60+3HcORxy8847AAB3PPEkzqYJu7MzrK3h6eNj+2Qx5bSlVpR1Ne2GYqXKa2u4ecdV9PvuQRngh/Bqh6jD9gv3qY+HepL23DwElst9/XVY2tvC0EIS1OZAK08VDw9p1Nhjq7eOve5dX7Sj7KnCbwLUVm8vziW1xAMHlJ7YtD2y7y/W+dY80BkPPrDBH/qOO/Dmf/wCppOOzVRN4Bu2EC2RUMNTrLWi7a0hZFs9IefYVBXzELpwM4vjoHDPez3YbDmJYo6JEAqwR1Xt2G4nLIslydZmB0odNpD4mM3VQh2rAhIU91tEBNVLnhmaLuuK7XYLIPFDel3kbVLf1oRbLNGx2dh9pmrlkkfHx/i+7/s+XLl0Ea9//UO4dOESlGILIGwjga9lmOjGRm3BL8uCj3zko/jMI4+h+6bsEeJ56MlN4AnKyMIPnGWFKXfti+Co23yXBKzDYAQuKI5Tdg3uqYhYQsQ/yGOuuzdpEEfq0ZIeN27ASFYRrhjgoFGD4oBtAISHPF5FUwnNorjmkV2KcdMzT4NiY9G8A4hJhQ6VjAJUYVNHRcgjCkLUm3kAP1XMw6MLOFKn4nvTEKlyPPQwskP4GIzZ02wXixpfuHIF+3dcxsX77kX9zGfQn3oa8of+kDkDnnQVZ65wDlcR3Lx5Aycnt7BRe756zrAGh0AkfpoQh8Q88wHHOVI6hXGY/AHBaJuuqBXWOpsmt5QwBmdnZ9hszPtjtVNvJkLRzhKkJv0JMHxybQ0F1bw4x0F7N0L6MnQnADwMA3DX5Yb3ve2ruKueot1VcOFIcOOshMFfVxOjNp3ZFdq9L7xqCK4EV5P3dc/BOp/mYizOWafHG6pK8S5JfE+FMseLRFO/gAkrXz5dU/6x946Kscuut9nWJOB37djtrDCEQtnGFEhhleZCLQLTDa2lYLvd4g1veD3uuHIZ3/Pd342Lly5G91f73B7AeOrbHQ7bwnto3u17bty8hcceexS/8iu/gmVZs9oIEh5VaJR6dGKed2qMAjjw/Od5ThYKMrQFBo+zd3RxPJlzpuEUBqwVGDCjFBRfv9UN/JA0ce+3OY4eegkDVgggtWX9sOzOrdaeVKki2UJ9nE9+F9XLgKGy7WD9IShuzXF+i+7s8AglrnNGwwxKHr5SCrC2WN+cVjPkWUgxhvT2YY8MuonKgMaUHrtkkYZFljaHVSb0Tce3fds9eP2tL2N+7hk8eOMr+PLNjtOrV2PcuLq6UoLThPJpOKHEgxFPxsRvYO6k6yHHqxKaiYMtebSMPA+lUV983R6GVs2zOzqaceFoTq/B+ZqJfaYgi4lddyiqG9SOwmZ+pWD1JosHJXS9QzIuzJ8HdCORiBGsmPYNu8sVKgt6Txk8br4yOc0MCM+Ek0rBGgWpXMQR3bAI1ZwmlHKY7GBiCHAva6AX6dqx7BqkVDOqbvzpfZkR86QPyIxAQC/Wl8w9MfTQqM2utKwsgofeiP+h2AaupeKhhx7Ct7zvfTg+2uCd73pHYouQ6N0Ww3sAFcSQQzVZE1/72tfwkX/7Eex2e1x/4SaeePLLWJbVynQ3ZkAXbxseAiv0nBxW2Ww2odPL72QTx4MkEkub45kR8pjkGdN7VWgaos4kmntDXT0plNlzYBBqGQxOhCW6xngTyrLDOLUCNNYpAKdR9W6yh1Cjl53v9sA1OBpUdaZWqeTY+B6SEjoJpDvy//G9aUHTWJJ/3MM5UTVst/j7sdiFOC0PBzrVFI6hIWcJPYenKXF2/2YBBAXSFYIJv/qrj+C7Pv8sHlw7vnzhCk5LD0zfDhaAVDHx+yjsjDBudXquohm5wA9HO6gzYS5+E+HYwQ6zNtAC+V1t/QNgaGutuOfuu8GJjEXuCy7VnjwcIs4Vnl/xXlhzeEDdNxIb4DEkze6bA4itbghXrySDEd6nM8W6LVGdRJUfC/1qbIxIvHDhanpVgM2/dbv1BR+C2r5Ye2J2EMTi7xiBdhYxKL75G9+JGzd3+PTDjwaeRg84QpvuFBv31NLBydYl3QV1DF6x8bV7JHwgfr8HHrgfly5fxJvf/GZ827d8C0SsHh1Q9HVlP9nBoBICOTQAgC3ixx//PG7duoVf/40P4/r168b53ZsugpSK/X5vzRTd6+F9eNCmF2fefAitONug9466oWax44f0Vh1OgTrW694xD1rbWeMacbPhHjK9xuGFYu75nOH6Iw9ZjkOIc/eRtO/WyCeKxhj+GXEjq/bScUhYMUwP7izHne8cB4Kk1xeKcINXZk/g78z35Pr1Kil7hGwQKWLNOosUr+pUp5pq0MmiDH3gytKgR9m7DzEjkhzXdEogijLNHrUBu4XjMmjKarIa4jDwCIBjHFWbItllYXhejum4HpqYu9KcqdFbtmRXtYNm/QPh0Qpwxx13gImo+LEogH4gEGPkdgvVVa0qau9g+uilzvMcCznDPJ6zcqBREOX0vsitd1bFtAPWraDf7BCZfNCdc9n9Z2iwMlYmu2q0Dk+j4J4pw8FhgVvFDENN+tXpqYi7fnSI3vn2t+CHf/AH8NnPfhHvffe7gCI4OT0JIZdlWfGVrz6F5pVjxFg32xnzZoPNPKNOMzabObzYaZ6Mo15rkNoTN+6oRfD6178ed911p3lWqiB9zN4DfkBpKK+NF3HCtTc8+thj+Ozjj+O3Pvpx+zdotC+hQZqqCcF0Nfx9alNU/hmE0UKtCjBvVHx9dD9wixsgY1ukLiyFegCyF4CqeJGXzMPCknPc8CXmNd4L7oU2Tuqgm+FJw8D8lIkyF4gZoI1gGrTsazcm3cJDJu/W/7179JCUNnifN1svxQ/NdV0tT0BvsrJYp4RnSa8dmtEJIQP6dY1VXn5YxaFREmuG7VqPoHRYy3STWUmGGGeDc1IYPIyuD3+tHd/9/ofwhpPncHR6C9/wznvwqU8/i86IEuQT+3OLgGp4B4dyjLU7s27ao2MPEBAGDTcP0MYxhzlOfVj/vZ9f9YfX7WFo1QxtGYyN/dz+zo6t6gUI1Hit3jhwnq3ks9aKVqzb7TRNURCwLCs6qB9KgY4U8TBIzqlgaOhd0JtgOlMsW4HeyJLLtpr3U2oF+oqkahVMVGaimodjDKrcCALRJHGXQgUnWxAUm2F4DjfQc60oonjHW9+CH/nBH8Bme4S3vuVNuOPKFfOya278porrL9zKd6KIR/WtUhJPFq90YYwVGWhBbA6Qm4ukFxGPOw8F8P/GZuvAM88+g+efv45PfOKT+NznP4/d7szxyvxN1ezvVUs9wBfBKGZRlMk27jRPmGdiyHanqU7e1cAPsGqdIo49O00qFTHoMeogt/GfNAABAABJREFUlYsJPjs0iIc6J3RZIZIFCUya0Xu1udMYnzCgXb0CrQcEAenWhQAShR2MBFpnI8WhGwUyKggYhgkzxxjhe0NVg7RfPFFnbAB7N/43IbBeksZGZ4QsClfEHjaqJ6n5HIPfy7zAIe0svWcdvH23c6CGsuTthzWZ+18VmKaKN77+Xly5PGPaFNx/32UztI26It4zjZ7mGFLw9s5G4Tyx9Q7H9/xFz5h7S3vygnvvWMm57sDa1hf9/njdHoYWwB13XEXyATX/9E1PY7XZWDmnLcjUGG29Yb/fOzbKVhjWjllEgN4x1Wm8c3hRlqmuUMd1zWMVTAuwbLMKqa0NqQGaOJwIW4MDUxC+09sxZkIJri9gm4CYFBcWSzZ7t0lfl9WNccXrHnoNfuSHfgBXrlzBbr/3MbFFWmgkfQPO04zOQiDaq7Rb8Q9hKFXHdR1XGgi6qfyAHHzY/Ya43ws3buATn/wkbt46wyOPPIKvPfOsKefDdBgYiQOwYo2W3qT9bELZmxBOV+utBUEk66x8d038fbAHkQDzg4TJH3YosDLXXE9A4mujJ8sDuTjkMHnDT145V+kl2jscelEmQ5glyGzH3SipiENGwvj7xY0oqXfZiQH+GcdqlX3WzLOKAxGAtm7iOTBBGRahRKVYwBGAVAnPdpQAdcyAqyIO5YREEHMxHhI0/Px9HoD00DMi4BZgpJgHSR4uHaIr0K03mSl/SeK8SpQ5I40DIx6Pfrhu++Bw8FnT8x084LhHHq6t9YAe1gPn4cXXbWNoL128gCpxvABgBlJjARIGGQ+8tS2YvZng7myHaaomaCLstmC9r2iwKadoZZvVF00S4bULvvjEiv/hZ2/gzwL4lY/vcOP4AoooSrHOrdF2Rqtl7lVjgbELKcO41ru3mbZE1EQhcpFccCIGzvtpiypODbOT/M1veAg/+P3fizuuXPEN0MG21XYy5zgyVB3/m6EVDkzCGC6xwseNzNBtuKJm4gC5cca1d3p2huevX8e1a9fwr/7VL2LtwM1bN93ImUe3LCZ2x024LAtKLZi6zR15uHZANlPjaobFcjxZO89DlDxQQiD2M0Bhxs8EbqxL8unpKerFi/7E5gFNpUKgEKqUqW+a1iCF79kBuGi5G/ERa+yNbAIWgNjY2RjawSxF/dBwgXe3Pa01w7ZLiQ4MfB+uD7R+YDh9oYJaFcX3wlQmtxw+n05hZHUd565MQxsd7XbYq41JJHoPzNG5tcIITHj+alSjMfoghmzOyBAdhSc8rEvixdDB4GI42AeHoFSncQFrlzC4BzQrevxqaejEWw3eQHdVvEEGcoQ0us8JDzobZ/E1pwEzcl323iFuV17kqQzXbWNoj46O0v0aLnpuCsRi3WxmnJ6eYZpM2o+YXO9GPWlOAQOG7CAQ7U2oYN89QSWjR6nAjVPgmRtWGvnU7hh9W0Ihi1csllh47vX6t6kvtuphjaoCJWkgHWwG2GJxlzJBQLV6gw/uvHoR3/+934PXPPhALCaFWpmsaLREicV2frJ5IuVOGX5+bqxhJtdyEA4GyHCi0yt2T/fLX/4KHnnscTz33HN45NFHzUv08J/wTBGBOoFxnmac7c5QigmYq5p+xW6/T5y4ZFXZSJnJYhQdOKOe4HLGwbrsQkCHFxNnQeNxb6X1bqpONAT+glKsBYqU4r3QnC7UuhnPcxeNbxHOc4bRRVjhZhQg/4Z4v1rz8KLHytB0vH/VTOrF533GugLsmjyWaoMHU0sYBIJszSMJ9lhITeiihUj64coYnimMJUCohg4DPVKyEkaIRoCgIjKiZIBvGDaxf77fGCkA6j38VAyDNo0R94RjXfeDxyV+T4dNwUo/vocfaAbGesLUD0/NiJp7lN4uNUEOWCWvcN0WhlYBHG2O4EX2hu3Aa8gL64wLOoyDunbzSiHJNRXHPzmg5Mwu+8VDagXE6FBdTc2y9w6XsUUV8zrXvmDChIvd7ntSKnoDmmR/rgxJihcE2GRP3r1gWQwnNugCnhDo6H2gjxUmxcxIe8F82MrW9rj7vjvxx7//+/H61742MbxmHGB4NVWA/8o6umFQ/bIF5VlgJeHMLS2dATeMxK0YHu3WBS+88AJ6NyWv09Mz/M7v/h4efvhhrK3j5PQscD+TsWSZcjbEPODMevgc4Z1qYO00mvNmjuozYPCIdDD66u9SrchhXdbYbKYRPGG72dqh5N6XGX33iiBQHDbUJE9V3bOdyiFMdCCoMmClMhjZsaqq9b0/u4+JU+rEv5vJXKPa+ZR2BcqQSMJhMklh9EVrD454vgO4AIcymzR043jmnyz9tmdOSAHDz4eDNv5b/fMZeULooWYhTBzofFaPSjjeivQBhHvggL1ha/30luJ//Mefwtsfv4Y3vbDHx377y96DzsAOGm7hvTkmvQNarH0ODSzSQBbkHPJn1Z+9Ed8WQAtpjx21KAomXD469u7RguOjY2Dcf+eu28LQAoqjo+NhUVQoGE4TM8mKH2sb4vXm3WQDjZDesHeu5TTN6G5FqUVQa0WvUyzceZpwenpmpZ3dMrN1mqBQXPJNdcvpT6UUzLPEhqdB2e+og6tOd0qlJdJBqLgFANM8Wyi9Lth7WSkBfYZb1LT94R/4Abz1TW9GKRXzxnQe2Ormd3730zg7PXNcroWxO754GZASXNbuofbiGXmWH5I90FuD1BKlrEwkkC51/fp1PProo2it4dKlS7j+wguAVBdxaTg6Pg5Vo2mesNvt/FnXYDTsdjtsPGFZKrV5bSzXdXEFsxVlkqhjn2f72WazwcnJiRecHFZcVadyVW+81+PfAZZumJZFYn5U5LJNXkJPr2tW0EfzRIa3jkcajgdANEJuOxjTi+LhEsUA9kR2Z2b0RYF26E2b9CDi74yuSEcjSyAMvjBasuePIhSPKOKzbqiTc4w47IE0ujykSfeL4NI9OXu3hmVZfAxKjLnlG4b7KWLc0G2/siS6D2PVWo/ngQDV60OJD6uSkQJAO1641bEuHWtX7PaHv2uJ7W688pp0OmOvKOo8xZqhmHrOjEurFsHubBeNYpmcpA40o9hSzCE5KnNUom3n6aUC8rhuE0MrqJstGmZ0NU9P1dz+p5/9ClAqOlhHbaW102SbZXUjVWrBLBvMmy0A8yKKAme7HY42G5DKYm1ZjP+pCmy2WwvTpwlSvL8WBJd3ZqiWzQab7caFx9dY9CLWpXSz2YBZXQsHXYh8XbHdHgFQx40thLWEnC2OzbwBxZ5NeMbuPc0zWjMj/rkvPoG3vOWtqGVG3ZqxlUnx+Be+jI/9zu+iFOD46MgWE4CmFlK1bqXItc5uWBt2yw4FvtC4YNQCif1+j812E8kNa9NDvq+N1emzzzk2tQTNqbU1GB82k8DinRoUQG9rYF2277JDAOBJwXXFRAaJs0W4oO2A9LGlsYAC6loWsEKVUgSlSRx6pQj6smKzmXD10mUIq901PUTzoQpUrAjAROBH/JmwDCJisDHrHgHB4ASlBKeGkQWQUpfd5kSmVASz7x/4uB4VlVpQpTjUwLGnR28WzPSH2CKeEI+H6h4p2b/ZLShcbeMtRisLSIi/Tx6uPcwLN27gU5/8BKZ5judYlj3OTk9xenoa77bs9tCuOD4+hgqwnixhpKDqeLN55/tlb8nN1qJteq3VDud5thJgjMbaNHenWlFFcUE2aMuCtXe8cON5QL0V0lTRmmHou5NTbLabmIPdbgeFYt5u7O26ojpNb7/bo4hY6blHXtTUsI9m9FndcfrMZx7Gfr8g2UvmSD3z7LOHOPq567YwtCKC7eW7IBfuBcBwxwb8uS8+CdQJ02Zrrv5sfbNE7YSd5wWbrZXZlVKCZmFloIL9uoQyUVHg6Piin1iI8JTZf1ZkbTdb3O8LcLrrKu67dBHLIpDiNf91iucrxXDiMmXIqKqRpW7ripkUM+3enK9G8L5f9ibyDYZ6grqZAb2AD/6LX8Jms8H/6a9+O1BnEzreCGo9xdW778FDr3sN1rZCuxdjtDWzwLoFG/fVUjGXCXOfzylRaeCF2+MtelsDcjmqM3CutJAGlUaVGqNTrdYTTIHNsWHtra0Gm/gBUAsw+SEIGF7OluukIfXWfdzMGE0uDl7kKMR3osfXdmPelBe01FJw8cqleFZjnjSIWGg+zxtM2y16X9Gaea3mAWvCFAJI65CpumGv8VycawAojhcbrLWg9YapbkARnrWtHh47Y8PlPBWKdVnR0AKjBszAmgD3EusUKt5I8yg5viJxYIdnOkR6lqyFwws1PLrWs1MzozHziFPHIsuCAYXg3rvuwlve/AZsNtsY03Vd8NsPPoDPfe4x9L5AdUItxda+tXV2XHr1fW2Y8zSZNi4jDIFRXKVY95DNfCnW6rLbo3UToQcssmF7p9Pd4tATsD/bmXPhz2/nb0GZJ+x9nSoUMjGp1QwaU2DRFbpangMVOF1O0+OviqWvEX3YQdmwAtjvd3j6a0/h277t23Hx0gXf7PBobmxn/uLrtjC0ALA2xdneVKxKrZiqeSvsI19LKm4xI2gdQmviK+JZ8gF8n6bJPFHiuUHdyEoqVq3Y71sIf8k3wbqx9i2iEvxEw/wOv4NNIBGg/lh6q4ERZrBi11SngL1GKottoOoe8yE2GZiXezvNywiBLGss4tVqYELGPi8Qo/uoCYOj208LeZ0uNGIYYLamZnUeOcA0PMQ/mycdVAHtZvhKpUG3R+/dOuPyu9SxXOKR1pXBwjXADDml94rziouHxay5L1LQkAbTxG9SHMUFyognODOkZ+hI71qGMfVwVFVfRD2LUJ7OgOcGLGw3mU7qFrS1x+/XqQKdSTCLXtZltY7ClbkF75LbEXSw/X4P+MHdh+coRbD2rJCL6klizLPEM07OylHvDUfssksWeXAsupqiHI1uXgqG9TZf3AM5rrzHVKfAsBmeTmK48lRMdyTbqvu4NoMH580Gk+YBUtWZBWLYfgUsbD+aPPpwmqR/1zxNaOKFPpDB8cg3KVKghaydFhg6/y3yLoUUSgmmEO0P1UFHFsUrXbeFoVVV3Dw5wQu3bpmbP8+4uD1GKXDhk+LhIQKTVKfJFJ9okpXrNB3gTeJJHLiRQCnJKaXUHEgaB9y/wFvuuwA8DHzXB+7HfXvgt37rOtaefb16zy4NtbCMUJzjbWWdAqTSFErghJz1THIMz2R3DMxQyqDNYMAX/GvDK6XnDBwmTZgN52ZcmyeMOhcIaV3mrYoIpsk0JNbewpOrrsUwbSTGf1n2JtGnNTFMmBe3tgVFBdvJvDapVoXW1wWlwhOa5mlVnR3zq4ArnFVQb9YNQinY7XbmnU81WRlD+FlrDaoVq3bs3yaDQVSj0kyhXpM/LEL/e5ECcQ0Lw7FtzibX0Uh8kXhwZvt761jbillcGW1ipZViXXeeJLTW4d3xSQvJd/beTuuCH1JSC2Td27P6HGsHap1hHQx6RCSEVqhJzGijd9NxJmbLeeq+BpqLHAUJUATap/Dwc4/6QS0T0FMClBn/KMLxfUATLB5yNzU+b2FCWRUC48JupglHRxVnuzME7Uv8MFYyOQDFgovbjosz8P7vaDg92+BjnwTafthTUFeqy/0FGt6e75S6FyzCIERj5cShX0GhcyikKOrknbMljIhXQ74CQAu8dGfe/39c+2WP/W6H/bJgt9sn6I5McnAhMHQlh1QFllX0CRyNEJAiHxbuZeWK9fpIjItuzTTNuOuChUxv/+Y34T3veQum2ShFnHxxrKvBegqN0nbEpyByYAzjlEeiYfF5vqHIsNDgmCJiLIgxsktqeveZECJJP7O39o32hn4PJm1KPlOPcPrQy2tjB4ua1CpVwi8InJzfBQB71y4Y36+WGjgncbQoj3UuK70+Ez+p0b3BXQfX78XgYZuRocEZ6TytdyyLecZUwjq/hpixH5NFB5d6VRyPzJJt6inmQ71j7dn4k5n1OlTujSFpDb0MBCdzXVcs62IYKJ+15L3hh+gyeKI2rqS12RyVYnAMjSCfn/mB6uXWNqc0nLa+17YGzHBwCRwvzyaiya9GGl5/VlXSKyXen+W7ZNCs3Odu5LhHiPP2YtvUvPkNtkeKCxcUf+j9Bd/+bVcCy+U4chcnnJLVfjhnDG0s+LOCIt7nThBjBhFIByZ3i6kpzb3EvfjiwTq8bguPFrCJnzYbV9ph4zf4SV+w8gAZxsYWk9N3DkJU907FPN4xdERMPsBpCcPp5aZtXbBdrf9U2xTILW6+pCzZAj5wMEFyMzRpL9Q7AHDoQQW84DhdTGQWLrAqS1/yvLT3jRprQhkiLkaNIeydEckXd4xpwHnak7ZmPcaMnjZPs3uoXsXU7bOlGLuCWqzLumCqk7E3IJjFkhERlqr9fvHxmOYKYO/vb90yFG603WstahjaVGZb2KVAuj18W1aorihqvzvPU7Q3mafZDtNCqk93zK9hBizkG9aECKzjhDcVjMPrHI/X1tWA5UpB18X0L7wg35gpxr9e1xXqur1WTq2exDIanKpis9mEdy6eXCNkA10hzZ7T8hNevedJPfP2DQ7YL860qYIyZYTRtIdeb2ThHW4g/a5Iseo8VfRlARwCidZD3Cm+oeygtMamUYrce65tkYM2TO4eOqSk/uwa1b29m15wcZF+8ox9idrYFLEsr5zZOGoB+jEgi42TJr2LxrO7UYzNOeYd/WHpdETUqYoqyW7hHk0DXjAXw/zpaIh7u6923TaGtpSCuVbzTIcTMMPhwVYCUfFh3MckRQPwo83dQK/c4kqIU84XCETCG8mOAsBmdSx3e4TedwdRO4sEqFSUOA3LMfM04OYcM/jElBPXyuQA9RgoyScQz2wDsYJBjz09CR7Fufg17m0aof49TPC4x8FCBxHHEeGao67dWWpFHTwVw0F7lNRqNw0AQA1PhNOtSoUIe1E5HQwmyFG0oIrpURy05FSTqVMRLG2NcSPUUafJssb07vz9VF3vtXdvk9rQYbhmcfESdsnleNHLPuBGM9oIKUC2SurxWQBh4LgIuirUk7DpsVes3d5pXSzBODk2q2LP39aGBgrJTx6wNBR/t4AnihMenZq0tI7gnPp6bNqxLnuvPrQDT9zI28GkoW/begt+Ot/BQnvDvDE4KucvlYJVMzGIng4DtYGDW+uHi0E6vi/08N6lWFJ0s3FvNhyIHkZWfK+JVndkmncUOYYF5Q0ig9YEPWK+RyesANdygO9DykT65lAroVd0dFGTIvVcAH2zjBzG65VhA+A2MrRzKZhKRXcuIcPuTBBlOEFqi4O4oOoXzxbtPcLYMFzKz0gaZwgQcoQjztpR14Y2V6BcRdOvZThEm+efBbwaSgrg32OyjY4HcRNF2JntYZqHsp2huv/Ze3MDyNYjiLCZC5gXT1QFGzcOnVLde69lCOfA2noAMRbm0VFQnbjb2porW6mVLcOMAzFA1trPpJBRrGXYJLXMUYjAiqN1WYAi0KWFJ8oEEd/ZjEwS8YmDNtd/oHoXW7ezGnBdFi9kKEYLdLnIGjrEOW62eQrY1oZ8WDPClpwhvYfwE0d+da2FUitQslOGRRQS4txcx8HQmCbLI4jdn54pBOktTjmHAEuO7b2brmZsBNENuhR6w67d4J1GSqloamupTAbDNDRId5GgQYu2ac8kmGQh0LDabf1W+90CdzRKdkgGEIbOnpvFHoNEolj7c3EqF+D60Q6d+E0OYAAmrYrU8JjrbAlua//jn1TSBxHwjMLmiLBRrKda/J4FzR0Fa/TK5LutD+ZkuM9Ia7O9ms7gq123jaE1j8WaJNrgFlc5M9wpPFj/k6eWYY8SFRqWoXa/kmGiz1p4fm4tk1DueJ5jj60LnvvKC9hJwT/8+Y/h5OQMvQWb3CcUdmKLLSQaTUs+VUjpgHiZbzTqYVdVRCgItUwpFJbIEJZLSniEdlKnGAtPbk64TbX6sKSAdCmK1owypN0ggFksK2tCK7Mt0jW9W4aT6kPTdIQNZNxz0N7RJDvgFiA6AyzLYga7qrECfFMU99ab2gG3LGt4Wpm4qKhF/UBhNj/Fg0QlqqhKcdwYHpGYCw90gxhaM8xduy2lwBA9bGVEw3BStbvgS/JdWV9PeICYonViSAMZ6mAhHs6DkPikHHhqpVTosnjoaveLggOfX3ZIbuqEGZYDi0BmCe0Ojqs4+4UY/Tp4h6BQ9+TJw96jrVJrCl1XNJMqCNwxn9/mfKqurqZWyyZSY/+GM8MSXhV/1ryBiZczT2J7b3SqAHWYSWJ/GGQBQCbTONCKfb8Tn3r4eSvFn48O59LtBzzZlp1/kwttu5HykIwONfYc4Yd4t8HLPXT6gDwSXv66bQxtrRVTLSHowKy4wGhVEyTKFGlse+8uAm4XJ051hBok9A3C6/VTaMR7KSpCj7rd2uEEgk9/6hkY8qDuBdjE2//N4grbPMX5vVTJRPSmTxxY490KjcmADUa4CLsvW5bDXs3/ZIItjS4r5XKx2wEgvcQ48EAi22BtKyYxLiSiNTri940KZNg1RV+sF1sNHL2Pngjg3lp5UXIIwoRSd8eSJcGmIdC0JY/WN4YVlvQYN1KYAGBZjVNZUSMisfY+WYVnveHsPdfWsJnmwP4TbuGQUvpSUwHMn7nDMuaBaRan97gzY5/xiKVW9HUN3LFGiFyicMXWewFgXiZ8zavjxDTyUIQEZjAbmNRS70irHaU7XakU46yeg0ZGeERVMc+C5lQzCqxw/dohk+vRYUxwBZEy1n3/VJdf1FGcn4nTYvQrUqy4b4rDStrZaQKxFviudiM+B6BiEM7zLwiu7Rr+m799DaoF03QJBh24AaBz65tbe7JDDiLkIijdvGuFhO0Q18FVKMAKM7V7syCJY2Drhs7eK1+3kaH1TLNvcgtrgfPVMzSwXAH0BkgLiUk6d8pkIsPxJDHZOFHHf4bQsAjwwJUj1OUIf+wH3otnvnYdH/3YZ0HBa17EaN0S27MNhsoccgkYgM/TqBFLrKMK+moGsIpgjfs7Zja8R+R5iS8N/xtGyryXCKWMbUGimarTm4oZUtCwOl5mxs9gmTFshx9UIx6e2XvztGg41AdIxF0kRdLFPGFjMMt0oKc7ZsntsDBcmNhn8W7D67rGvLfFCPorw30/ZM271xT28ciAYifds+zcZL2tCQ0xLIWEupgKIL2BxL5Sq0sx6oEojHm9deBQB+HwYOyWxQsUyCXV7t4WK6tMwlEG3jLgh5mPl3T7/rYuPuoUdSlu0BpKcSEdN4atUVDJllaHr19PIFZHvWLZcvuRQ6sd6CXuZfuGSSNFkQ4jlntkRahP1R0pd1aUUYXf36NFzR/Z+lH4wecwmxrTB1JQKtC7iUQpWJiA2ONcL+OeNAfAnocaKJybUYTKv9iiJR/TWiefB4lPjZDUy123kaGtUZbHdyiFhQp8JcmTawjfw1uM0KwcLBC7NDAVei9U2BqbtokYhnnnUcV85Qjf/l0P4ouf3+Kjv/0otB+WKbKJW4mFViLRkZ6zsyg8DC6lkMQYugOsTCK9BqCxzuxmzmR6t+oGiZQuC49TQs/eh+G4eZGEJQBEMQCTYOHtAUG14oIdnyvu7xaJZzo9RXowFLVWaOKz1JGtCF7sOCc0SlaquaKzlLhQE8LWR3pMtjGpK8ExrkP7d1XirT2SQQZJKBSp/0D4ISh2g2cFOA5bOzZ14wbAoAP1TszRWNPHlxEK53UuwyFdKlpL4fKQRiwl1LgIZ1CBivdmRj00W4ugrQ6zeOJrqhvnDPegorE1d3Rr7gpMHqWQpM4kshweqBBAQv81k6ld+pBMhkN3XCfi+zgVuYo7OkUEvVgEWwQptuTfeSBuU/iXhsuXFZcr8Ef+PcHpUvCx3zEj2bvGQdAbDycWCQ3rVGFj4uAd6YCmLWvfM5oORm7MC5WYB+5JwguvzJS9bQwtJ4qi10S0A4dknF/y1AN8w0Uon94IxuE6F3qHd8YNgbDdvtEV07Kib2cLFcLYabRHMcV++1mt1VgsfjdK5hG3O1+FRNYDf9ZdlIUeaLSJUW58Pnu+E70+Qg2qJoxS1Dyj7OSpEFXnmQrgVBhqv4pIhLOkGzkW4kkyy7rOs1GAoqpLrRPwPM3xTBTVGZNxqtYRQXBYPNG6kful8yCQKOPtPUtxixh5fr/fZwv3WiOU45xRJtM4ue6dqskw8rDqjcUMHlZ7EgxFAgeuwIuMX5FiZbSw0murYiJ30zoUd6Xi1iAkJOYo9KGDLFkBtmkzUhiTX7VWdLGwuq2HcAmr5sgJT8+P3qY4+6MFDLHZ5BxN8wyoQQ2s3OtRkmwLiWI9Sk8yV12sjzHG4oHGzad94II79KCEW9y7jG7A9Aa5CbmYue+5b/wQ3WyB7QK8+10LdvsL+PjvLWhdQxWs+AG/+piRLilg8sr522IRMxGgQ6EZg8skYEc/8AabYY+Y7ZwOrPNLXLeNoaVRlcGNp+ligkt9AOjFcJHGSagIEjZDehpe7QjWAE+3+GYascGg1mVBv7CFaou+UZ2E91gc6WWUIrGwDw6Hc6517z0I5SyvBOA9uwp07VGa2pVtOsZ55D0lJjsXeybCSBFTZMgo5xZycbgGsHZBVgigYcRKKehuPNTD4/i5KqA17m8HPL1ICW98zLaHBKE4bcc9HdEsu/Xd6ngwnFftr+3/urqho9dlWeJq8+JGLcRxuteul4o6beLzwFAdBMdWlXh3iw1OTyzxSTJDrJ07IxoWWXQZeMwHCdriWC5bj7tHX2t4/lBv6+7fjQH/LhQn9zFqbQ2opoTBFVBIaPJKud7Vxks1eL3ak2FiEqQZpTWfo3WguyH+1UtQ8wfRA8/soJombbTA8QQlnNlDIx3LUGN84GJLtr+5tm2PMS9SuQ9UcecdF/GVp6rBIrKCMIUqk8cOQYrGOlPuGy4mH8uIDjxytPcm3Sz3V7ZYyugy18grW9rbxtBmpvQwZOFGAOz1jDIDtKIZ1bkHW4YBjfCPoYhThkYs1r8gJokygl0V09LQtt5180AfE0kngS0+ZmgJ7Kt7BeHVgXaZST4LzadaY2HbhGUoyO8zzy6/zVHSfA/ybR2P5PiRI2k/bwFlNJd847+lN5khMw2AAF55Z58hs6OKYCoFKzwU1B5eMcNDqeaJM4HWWsO6rKlVMaWgiYiEBkXv5o0ytBcA82Zjyl5lMoUoN3Chaq8VUavuBi+wZh6eBwEOP1uNNiXZviQSrT53lJus3pWA88e1Rngg5lYQRPnm8Av7jkE1OiDTgz6AGorxi1klpg5PqSqmzezsimEt+/dQnKf6Wpu8DL1OEhGDtf7xDiCLry0140bWCDWBR/hxPGwAwkG2RkUtmoQYCtEFbvwd8oILoKNY7gVKFB2E2rhmzJO2Hd5Y9sp9TXqWlIOqH+3i+05gxYJqVWSN7ACHpIb9wC+kXocAKOo9OUpGtXC7G/vYHbFaysBeASSYR4eH0vnrtjG0ZSACS4T+Ni1SS3YSCO/V8Tf46YOORm+JuGmxdshQQBt1LTGQrG0RKqzwxO5vgzftV6xTxW53hpPTnX9vjSin0tApldhLenbm2kYmOjqX6pBYQhole6ROtxvRr0oK5tlkHM9DtCgCmaw0sDfTI2g9wyEZvK+AXZzy0xoPoDz5TfYvRTjIyVRkdro6M4GcR1Vu0hLhPHrH0homVWAi7cobHHpCCWKiKUxwQcekmjpmnKXX+2WJw2uqk4nieJJxWdbwBPm7/LtVlHWUqpBqrnEtAiwSmzt1WgeaWs1EIDgmPdkPlM1DeOc+915BlxgtqVIdy7KEShaFkMQ7PFt31R4/TyUtNeO1rliXxaGT4t51dkGITS7J56Vhp9G1rrIGITRZ4tDlYUSlMiGqNRbH+L1VkskCMcMK9yBLKShNnY1AlgH9mExEm+MCAN14sfkSWBvD/Xx/qBobAx3d2/Wwm7BBFALRCgzdT1Iq01k0MXc938XvHc4TsnzfHqKZWNBw4ES+I6xAjtAfGEOr4bZzgvmGw2dw6O2SNhRK7V2DeoQYWOPkqZzzBJHUImAk8QMqFe3mDl985hY+9KGH8dyzp1Dnwlq5ovV1J3ZrbaIc1/HnVzCZhKiYoUbruq5GXaIBVPq8h+OhykSGvCwGxIXjq+cc88CV0Lw7bBdBOQdnMJIw+tHkITEi0ULskc9vv0P1KxYuJHzSPIS0kk5WdxVATWid39la0pdUrSLH3oPyhElRiiQWAKwN67pgu93COg9XaPGeTYSHIpLIyKXUAgizzDBDOhyEGNbVVCesoL5DNgAtjmEElueUrXWFJyTzu6kxXOTwYOouWWilxhPIgEjNCI31KG4wknZlzkVHHqJ0OhAHaz+c11A0m6Kx6OQwBCMfqlnZOhiMCuCenI2LiHnLlKAEDIpTX3fdRYGotCaQwE7Fb0BtCJN8YCRn30QvGEBIO9IREjUPetWK3gqeeHKDp56bUWSPvRdt2H7O7h5sH8QEnx1u3J/wSDb3SiQ/fYswCqW4eWw1/9t4mLzaddsYWvOu2ot/2m2T1eC3ZRUKMLrwkllaYlm+CFRM84A6nMyue64dMgwa1Gk2+wVP39jhE594EtpKbLTu3ikcYqABD1J4IQSQnrclX73Sqg7kdsC8sd5QnaLN0FJ8tqd5spAmwjkJuEK7eCKD1CUT/Lbb2vMSd2XIyy4KTKaN9erLsoQ3Vbw7rXrYLwJvzVPi3aITgIMjTHBoycVuMIli1RZem3m/iAXdhmgjeMpK9oD37vIDbFkXFJEQVbHNP0M0+2a11lz31MdJ4eMEmBpfYpGA4bjmxA5sEX+OUgQb7wzAw49e57ouVgUmYh09eo9k2HiA0WsmNMYkZlEKYyNgo0iK1Yq+2LvO3vVjXe2dtFv0xrJuhsciEloLIoJlv8fq5bbLulgz0WCE2DzPMkNg9f3Gxa5o3b6rx/nuk+MiPyodMgkqxFpuqxpkXg5zK3DIhtGjRYIe0XmZ92Fi2ETg1f9usaqEn9FVce2a4ORWx//4wR1EGtbF9TsGeC/WtIf8ZBdZwtkoYGaQ67CfWjy/dQm2CI19BblWrEBjbA+Ew3d+mes2MrQDDeTA40KEhhBE3/v89wzHmXll0cBITVJxDqxrtJqxYGigB/qSRSqOeoduKi5caLh1a4W2XMBsEsvknGW/fdM2hRRSvBiijotwWAxu+KXBKV8I43N+TDiXY4NA9q6K7Dk0xgviHEUdZOkEoPau4ajJB2TBRmDaUlDm1IclAwFgNt4w5u5eyri4xcNjGj0T6lnDu2zrgMGpdQa26rrVeKNj2Kga82pz5vPeNRgRhmlqwHep2Vqi2orGW33zc+2o/4BC0+xUEXAL0qu3gyUPh947mvRYf9NUsQLQ1fBQwl2tNesgUIdQGYQWuo/pFOsijK17ijKOAw9iXyRj4i7gE/+eONR7xzocruaUZOdeUuzK7EUknfS9TCbT2hmeP2LQiEMyDA7X+bjmhzFVfzb4YZ1JMI1DH9zP/u9kD6yeBz3dAdDFyvDF96/tgHx2rn3uW3DZMa2WBjK8YEmPPsac7AkMeLu/z7inX+l6ZfLX/8zXGA4dJAloQHEIOtNLk/F3fUPxKqWE8EcHM/NjKK6DYbPf3W4ajgG8/Zsfwv/6r3wn3veNd2MzD7qrbsyi73sn3YV/DhnquDNFTXoIFTuYkTQwAvaDNTi/OfM5e3j7ZARQs4BeJjEpUszMs2uxkfjegbHCQuB1XYzvSs+/1ggHA9vrGl5hLdnCmh4bq8kOeIxCD1P9+eg1mpc7TXNUwvXuWrD+d2MvSHx+mu2z1qiwRQ8z/o+MjSLFuySzsCAFzO1/zqcdIAfq1pKjTDoSDXYkvdyjX5YF67oE9a/UEpxgrkV+H+eUSU6OQ7SulnMsBlp2jAeDjYTBAXWYuz6MvTUlJbujTpOH/SXWSnP93ObvCEm2SfB6hz0GwIsyDmU606vLUDzWPg83QXivCvhe5L/7OhAWguQejejVDXqdgKkoHrxvxdXLiKISzgnHRoe9Hi3ekc8Wpf3DrsqS/NEApw2K/M/ws6/3un082hEOOPBYMbjtQFGKp7hgCsVCAlPRTEiYlTk4nbQIpA+EaL8xvdwigu1mQmkdm8sXcPWOO1CrRq38upi8X/eTsgbP1TyQtXcUr8UvIl7SWYJ0HkZ58Ga6Aq6ujQOXtlTUaQ7PyJ4wHnrYhCTvq+Mhdq4Hdq1ZRBDhr7+3tRqZKHAELrCx3NWSJQXNa/p12PiEEWwxJ52M3WWjZJc6EIXyieM9cs65yXVZ3NvJ8ujW8vcIQRAy0lVNA6F3D/3Mm20OV3RVUNpHwCSYOURGJ+rBxY29rcn3HNka9m9DohHOlugm/EKxHfH3z9/Rg/dl77r1nBffVTGJxGfED5P4fU0oaEycpeFLzDfx5RKOQlIGG7RpHE5VK8S7Sx+uhvw7oxjR9Lpt4ixCcXco16ranvR/ROHh7uXrvdh/qTtCdP1ExRNzXvKr1ivw7vsEF3eCH/+P7sQjj674hX9+4j7sIX2rFK4trwpU++5Q79IO+BoQwaAGx6IePdBetlesBwcJx3t0Cl/uun0M7Us8qOqAs5wzxNwgeaIiDIl4LJMbYYQiyFbg4Aoj9rg21SkftQP91AngQzg5Gm5fxEH/cFpUhNIybFgAqJIVacDBe2XZqfi7MJEExl72O+45m7aCv5/azy3hMYR0fXguodejEEneYC4yN9jdwzlW/2CIHsRHrGaSSENgJBcdjdPoPcpUwjhk/b2XhQY2x/euybMVFkHk4WSFGuodX+2ZiNGz/5phteb5s/cVE5hlwPONgsZ5sLEPz88mKZ6XhR5MPiGeOddEN1pHdkwAgsrWe0db12gSKv5M5mWRumaRBQeEz4KSoT0EwJokeuLZFO4xKCWx6PF/rLbkGmIb9N47dIXr9x6kVQ/2XsAAw2VwFBkcmpEMKJGY/mNAAmJCSnR0gininiN08DLVEnVaFaV1iN6ENjP4LMKhkWVUa2swKwapOzvu3ciXEZKCwgQq6Bfn1stOyUNOZ3j/V7puH0M7XIl9eAKipxEd8RH7k79FXVoNbDYUrw5OHD//dMR6ZSifBLZc0JOi91Ocna3Q0tB6noiqiqJANUDYT0cNrw5g0s0JaMU7oSri98crsWd7b6sVNxxU1DFf4Wax92LnWPJBjTJTsFLdScyFsKZ+CwLS8HfmvUiMqY7ZinPEKKTSnbZGXLmUAmms6ac3gSH5k4Ii8IXfVEOYJjFPe1+GyMljpn5qPTAiUQyiGtxcrYfeMH0YYoZdbXxUjeq0rgoFsUpzxEae9ORdeEUEzU/gUgsqvc3u7XDW1ZWvBMxUZlA/JGSRbcFTkxjuobPQQ+IzpWisdfOinRbnSbjxPowexmRbRUWZJPBZccMukv3B1GlsjAilFEiT0JzoXQIDjt0lI6sm8XjuxVIKjLDmVCz1MJtQne9BJjuZpCt0erg7PYKdACil/NQPI8BkGTsAmb1mxSsoJXMn8P3dPOo17wvWLcnZC5wjGmVyxdFd8tTXE3oWDdmhNh1GyEO0/UrXqxpaETkC8KsAtv75n1fVvyYibwLwcwDuBvBRAD+uqnsR2QL4GQDfCuBZAH9OVT//at9z/honkV6OPU8q3+fkj3SXXOQjnnXetTfQ3f7OybZBb9jS25ktw7iuAoiiTuzKmuWfoRk8LEz+vcTC4s8BeOIpjDHx0p4eYcYnidGOBwW9dX6O1XK9dTuNhWFbj9B3bAeu7pXRs+R917Vh8n5Z4lJxoSfg38zMOgRI3rMZ1LamHio9KsN2xQyVfRi9rf7o2YImvCQZQm4P41OPwT0JkegJFYZ+FHcWCd2MoEiJRNQRa6tnOS695oh21DC+UoZKNiERH/6e3ifLMWZd1zx83Ig294rnwQPmYSMxf8lIoZdLjLg47GSHHCIygcqL1rWqBstkPMzISy2aSc+govkYhICOatx3iCFjXDmOjHbGZqmQhIcOICFfB6UW76LhIb66GJCmBxxOlkeBoFwjFOhAr4KyOs2tcy9KdLLm76pIGH4mUuOMQ9qE/D7boKNRrWJi89Gg1AWDMPxujj1e8fp6kmE7AB9Q1fcC+GYAPygi3wngbwD4m6r6VgDXAPyEf/4nAFzzn/9N/9yrXueTXPYXvoRGKMHsJMCQNT4Um1WBUIrKZEePKhvDc/P7SLWieEQ7NajgK8/cxCOPfA0vvLAHk1axcAsFsuGFElllVYSnuRHBWTsOx04hY6seWxixQIi7aob2/oIDvuFjMbwTDRCUyRXL4BN/YwKE48sCBHJDaUS68zUZOpqqWm4mJovWtZlMn+PKAvMG7bNmwPdO0u+a5bLgWKmR63d76w+XNfxDMYGUMErW2YGeXWKNKfLhz9baQXKsSLEkm78b4mCRMLpMRhFbTulHrimjkFViduM69XkYD/86rBMa3nVdbbyimKIEzsyDuzUb0+YemMFQEnRCVZNG3O9tXBWeEBsMRjgA/kz0munhntdI6N0TcS0ZCXWysuCECPKQHCUwgcSge+xJ+zi1NTj+GPIT7M5MyC1w3a6QbpFiuPW+DswmFPRaUZqilC26mCgN54R7VOE5mAHCCIxaUsQ9xksHj1QQP4/P+Dqc6gRq1QbQNKy9V7pe1aNVu8NN/8/Z/6cAPgDgL/jPfxrAfwXg7wD4E/53APh5AH9bRERf5UnOe5wMA8SNIl+IYR69m9ErADyJg/RuIiTxk7F4twPV/N2kJtnc3njuBADwsU8+g3/+3IR9sz5NDKfoCfiTIUJ+1RA/ghIrYiYZXjVDWo1/b/eQVP207GmMRw8qRs+7UTKkzw6m9lydGFVXU7MfssMiiOobIPE59mlr7ulUILBTVn5N1RZ5UoSSh0uc00JBGm/viNC7ZfoBTPT8/PvrNEHXBdFOunc4FmDZ9Cm7KJQi2O3ME24tE3t5+NlkN2nh3Y4dXkutmGiMydZgxRJss1LSsHsCz5zqFs8K+AauhwZGgOHAs006eZY/+8Wl2M7iPzNIqaTHWQqWZQ9t6a1v/ZBoyHLmEfcG0ojyHgf0sH7IECEMow4rFGS3XxpnHjx0HLi2ee6zKIBrLjxQdaH63lHnjXmkfuh2ZalrJqJrmcACjj6MH+jMNPfKi6A3oLUVX7nWgab4hQ9ex7XrK7puzUioFY9Q0CcKXtS9Z8AF4zPKJTxVvHS9DAp7kVcp7M/Gqjz+9oDrDtHJy11fF0YrxtL9KIC3AvhvATwO4HnVqHt7AsBr/e+vBfAlf4BVRK7D4IVnzt3zJwH8JOB958+F3mEE1RcBJ1dJr2AAYFf33+PJyftYOEqxFZN4gw6GawiQiKhu3dE/WwW7ZYfeJ0Amz2an91C9HQcTALUUaGfdewmvhJsYhBgMKwjFL7unh24yLt6RHUGvAoCkMdbh+ccxY8g8TRXsf5WfM2O1RrlmhvgsHqCxZqafuF4RAUpxWHrwCHsHumGM9JYZfSiQ+KAPfHWZSsoSGqTiIa1TlMx40MOoTsa38aOxas1a6tA7r6iuB+KsDG9vTs5xnL7+d37OyOtOV4uiEYSeQITcImFkgn7F6REcVMrx2RN/zeTeuq5Y4SXUQ2KMfNqmmUiE3yPoUZ40pbzm2ESScqPiUIsBzVmNtq5r4MIhdhPlvxJt55M7IP7/aVzE8UwQPs29CcT+bGvHtJlt7dDB0HSI/HRy/N6ih3E8eShAnNGhAFBw7cRSnZ9+pADlCChWGm+/Yw9kDouXIhVrWcODwg7nIQpynJbzw4s0QzovjKwOIBHNif//iqFVK9n6ZhG5A8A/AfDOr+f3XuWePwXgpwDg6OhIdXgJgBPrCujjiUEPhCfTcKrwt2l0yZQT0KtzrMY/Ga2PHcMz76TgtfceAQC+/Xsewp3f/jb8wj/5BE5PEr8aHjIhgd6tqovLL+7nz0l5R5j3VHyxWlWYGeZ8Fs+OYkgaicZ32XuPEIZdpcyRHBk9BDNaNTYlJfyISfamWDwBlZvLjByN3jpUjXEubEMiy37dSPZSIkQXp31N1UqO6Slxzngf/lnE29QoDt4hPSg3XgPVqq/W9rHzPr6RWIFGrJObju1hgCkNOoAWRiwx7JHmxvEZPT/7SvfCOEPe/mddE8sbGQjxPsqwvcVYjl5plCL7OIybdYzI6E3Cn21lBDMYeBsXa4AqcFlIIXfVnt9ocCwFJs8KYZjNMXBallqIz0PSDJkCyIiEEV02LUWsX+0KOL0tStmTYxjzHgckD39vWXHHtuJW79ipGdoCRM4lfRIJaIIHwmggq2T3BxHHZdmMUx3fZyEL3C8OLJtf5Pv/lZGD31/Bgqo+D+CXAHwXgDtEhHP/EIAv+9+/DOB1AOD/fhWWFHvFa/R2/Lug3u+HPLnxtDMvEmCJJQeXYbkt2jFJRuODKNVMzNIHQwqAjsvGBMI9r7mIN7/pXszV8OAS1SyEMVb0vkC1eShLVgD8vkNlGHKj2iJ21S8hFWXEejRCVssE63B6Hl70yNpYqMDs/+BVgWGjk+lpgOyuXoPPsQ28tFhhQKnx7oH5as4HvfLiyRz4v41GCkAQ52n8c7yStcDQj0r2HJPVZRxH40xjOhqnZV2SlqbszFAC5+P97H+EIAauaXhmmnKCg6cT0EM4Bik2b8ZNssvEgKEn1DMULcxzfOdYbKCqETmFqppHDWz9fgAf+DjQqyfGvkaZ8liIwPczQ7S21XHjHvoCwaZ48WLj0MS6UTeUUjgXqSlMtgT6sFb8HowaDvIGRQbHwvdLV5SuKB2Yq+DN77DN+Vd+/CK+49sKZhSEzGPY/MEg+M+zBc1QxIDxQEloctxl9rg68Jj9e85Fkq/m0b6qoRWRe92ThYgcA/j3AXwaZnD/jH/sLwH4oP/9n/p/w//9F18Nn6WnNYLK5GYCtiCoVM8h1DCyufEKHOy2vw34wGGmOTYL9Fw4YGM4EcesAu3Px1E5UnZIZ4GYij3fQwpApTmhB4RBbzUeSaLvEiBGHO8NGs9qk17cSNr9R8gDYK8nJoXcJQ44o8Xm9eqwZvKC9vx1MCKEHLIqimFTwCQ1P6/IjcQKsshye3jLBUyPLTwZtTBsnjcHhrS1NKIHeKJ/Lw3OmOTh/SC2HurE51M0tc+sXoLbI4kqERrH7+OwsIPR0TjfE0NykTAKXLeWbGzh/YuY5kD1yi3hAdXHirN8x2CFCCKBqZxwZCUZK7v6uIaHPwmxlGJiO/wsu+JyLSicZeCJHTqb/CxlPxErIzaqGR4xHrZUbhrbbwKHeqr43vK15+td2TfK9UAEltknnkO4bUxUcR2VaonlMtl/X5gnHG1LsGL4rCoDNxbUkPWWQkUCVqIXyy05Rqvhe/d+OAr+e/z7S4zQy15fD3TwIICfFqopAP9QVT8kIp8C8HMi8tcB/DaAv+uf/7sAflZEHgPwHIA///U8yIgznfd0mKgCbHBsE9gCm0oKa/BiiHAQ8oXnmE0D1e8XfYXcw5ycmKxTAXQPVa+n1izBVCdKc6GqYz/0CspUsC6ucOThT7SHEeTJqd61AbBF6OFIqQL0xkrBF118p9aa9VBaW9Svj+8fxgWZ5R1/n+9THK5orravIpCuVkBD/ieNbknBGMDwUhqfSOCpeqNFNy5rg/V18o03eHbpdR3Ovxkk58HyM5K6DWObGFHisMiGh+yVxQQeOD+I8l5l9HAOzojFxvH2/46NLzUOpA5ycdVx6hTbIQYdhSxunKEKmabQ+DXvdYr5CNrfMBakKQWveDgIxr/zeekR871eBIOEERsq/roxRMIx4L4BiDDYj1G81VZxHJbQj/1sFHlJb2+AiiTMa4biBSE0cwDbiMRe7dVMVu2KroQ6Ek9WhR0iQ2KTezQ6BTPk9WdSdJQyoa3NPd8K9n6D7/Vsa5RrQgbT/Cq+5NfFOvhdAO97iZ9/FsB3vMTPzwD82Ve773iJCLbb7TlowP7Nst+HvFh6pQWsBAmkJDLHOsTsxgxwh68bqb8J+YJwj9RPuSKYvJ1OqxUis3vH3ABWOFDEGQLFTszqHoK14rH2MLGA6GmqMwG8PNWACk3BG8BwMHOD881YAccP+Fis6wodWnGjHW4mjifx2FJcfclJ/JSGTOORGOW42RltkHoVPGJuIjHqlFU1sQ/ZFPeqYllzfo44LN9jxFvHAzLfZTAikptKxOxC0KvigLHPTx4CR7+ydXW6E73AhAC6J9XS08zD3R904OS65+7jS50HuCHnve0Z8yZ1mizT72O7Eh4SsRYzODRMB/CAH9jUoS2lJDd5GKso/HDoaExU0eCvFL0ZIhYRO3CipB1wTzWtqw7Pp2qtlwqySCgcD9XoHMu1H16zeq6hGMsFACaZQFlR8bFm8YrW6tVdHjnOvla6QRKixpa1HzWjiikLJ8RrSXr2CHSLzm1J2Au9Y3LdazPuxvllbgV4Mc5O2/P1XLdNZdhIF+FgACT0H5K7gcG9V1NeqsFj5R3t96y1u00IvTkGBOpxdgD6jred3TIe7Re/usNXPrPDflktpO8FIjU8IWKgZCu4JQx4IBJ2trU9JGVvKV/kCkg1vdgCZ1mwsygPCRpsPiY0OZrw51eDW0Z9g9HTN+djpK14ixO/Asv2TH90WKBHoRp6DVnRlFBGJpucNO8ltdXhEdvAhrsb48BI+pNvgNyNGlxcIMO3MAr+Sevl5p/h2nDvxboPkK/b433oEUIp45gtftZV4mfEXEdD1FWBwfDTEx83X/IzAREzaLwnkKW09vw1FbgchqFdokdHYyO14qVwcR4sYi8YUAxLxuk9x/MVVu2VqGQkVg2H0YoAVab01kRyHdjKc8guf17osUgs/Fz35mlAu0T23h89tGqTmzzuX363/awIUCaBukdbFnW+cQsNETscbYUwejM4wxyj7rDHeBnkETvEny0dPa658cARZAEH5+LVMNrbxtCOi8h/4j/vuZv9Go1ubE/Nmuo0MPw993fVMCKC+GkshoIBCK4/cwsA8C9++Ut4+GPPoesMhWFskbH38JVNrdq50439mDL0syflc9FjTEgDHh7bJg1mhEMj+Xz+88EwQp1frIIiU1CMYpGIieBwI8ONnwDxTuQnG8ZXfWwoiSdYlwXsLGrhssEK3DhjK2oeAHA4Rj28to1u92/OG+YmYUhnHnTHZmMZ6e4bIaAl94oBQItvUknWANeHdmMXrN7GHTxELKzxg6wfbBYbZztojD95eGDxs+O8hbHleHm4SfYHl7LSi+b6FRa2jOvfDgF6VXHw+b8HJMFnys1zsD/IaICvEUoppvea4zQaYu6R5tBZjAlyjMKouIMi/m7V54ARTz6SMrAEyf40bEyiiQ6G/GCcG8SFXEQsQnrmeWvR/oVHFU8/U5INcGihsxzXPWp269BY+37gMM8h6WHT8ToYs1jTOPie8XOvdN0WhraUguOjI39kP2HUTsjeFR3iXTQd99LBhPLkESaXfGCDUsIwBumZuNdpX6GWtVSJE3ZDe7+tmKeK3eIftiFF87LWyE92Cmr0+FlbVy8TzcnSTrNhuBBXbkAbgzG0BX2Y/Q3jpe6VCfFo9c12iGmbV2YbaeOcRgABA7QBkkhR72KizyXx0dmTOnwK5cOoRQ0M2+cNPYvEaQE/BEMXlt9PuKJAaybA1Ns+L96+huEuMURyqDmubW2ok8SYVC9IaVrNEsOTjK2hzP70YaCTMVDKFDgroZEcX3a+zWtMxnUPbUNNDAP2DIT6VhhnGjdJLmvei5xPe8exHxkLIUykuqD7gVpriSQas/nVDUPcu2d4nWtEQxC/E+pAFg/wEl+j5vMIoAJqHQXEIuYdRnm2J2dHYaAQ8XavHeKi90NLG5WsMrMkuPOS0bHbKx59agcA+PCvP4fHN8dQLYBmkhfDniTUYz5Owl7hJMX3dagfkIwSinKf+9ir2wq/lw9qOHpzfWVT+vuid/3/8mJ4TLedCw3jaXUOPgASh0zN1eQU8jQejdXB3+HJG1QoXNQZiruv2u9/53ffiR/4gdfgeHuImyVO5V4zQ8B2yPmlF5KPP3hcOmQ5xbxSaAF1cPzNwxDSkORXMgLIdw2PqA+GKELvHGu2x+EmtdLZwZByLPvwdxq9wtJXW5ixKcVCSuKgACk14Qf5szntiIksH8vIqtfDJRlz6gYIPmdZEUZutM3oWGZNj3yq1mtKx4hp8FTD29GcSyZL/aMRQTCjTwaCKlI3QAeBdM7vMGb0EEOwnQwKZwSM42pdjJNV0IirxsFQonyXc8uoZ9wPfOZkbqQQED/H8WLEQUybhtdv7ut+UC3ThDk4TrEvNPdtwhwHw2/eKmrM1Qh1EXYg3AZY5dbCG6yO2SrwUmaMjg2RvLQJ52yA5PPnszkN0z33LBrKnUnPnv87OjoaPvfi67YwtAaO+xHpC5ZGdgwpCsxjOgAYxDBXZtqZ+aTYxEFEAfeXO+vYdSiZ5Z+CO51H+7Z33Yt3vv1uFDZlVBm8TjdmZG355IjahuZ9Mxx179pHvHrNNTAkRmz2LHQUCUUxD05injNUEaxrQ4vQm4YcABtb+oJjq5rWVtMNWNnyBmHo6MWFV+CLf6WY9tAXyyhaM6Zptp5k4NwlW2C324enPE2T052yXXnvJo/IxoXptVkVGDdxGqfh2dy7nefZaD8+LywlFRrdzj5yJSheVpLqyaWDMdPYlGQqHIiJu+GCJGfY8OSMImhsyXdtbY2E1LyZsdlsstuCalY++gHEbL8Ah6LePrbNje66LDFHMb5DefNhois7PJc4KGsYsTBCPQ8aCQYMMoIRRgLOYSw8nPLfw+ginSdQaAZ54AsAdbZNHKTD9PIS7mFRbOYZ7/6mSwCAH/zee/DWN2wP8iQZ8jO68wNErAKPsBGdt0xaIsYYYJIaflBn8tG3Z6wBQg4CHGhGv9R1W0AH4wTk6WyGjHXGNiE96VkvcSqLG41xPzJMiPJHHSuszs0qDO/hoHRZsK5nAM91H8veh9AjDoJs4HaIhdmSG8MxgYR8G2vHBFmcEdSYOH01uIEcpEi6gHiZJ3d4gg9Z5TUy3Q3QEuGbuKEZ6/FLLSGQXUqJksxIhslhFRJJ4LW6kLWIl+3y+6ks1szQeudbzi18vugJ5nylPCKQlKk2RA3Ubp2mGlgmMUwAEdIDwOTGzjLutgZGI0O2wPmqumBulPQwuYlHpf2oLuv2nVTK4oEoItGSnb8zef82ADHO0ZdOkpLHz0sxfQK1HwSlLZJmXkpNr3WMLsaWQqMXSniD38nDJb4zwjGua98lDhux+hJCbDZpYzFubvCE4vSx18b9c7gXY48LPHlrMqN33me78/2/90V85B0PoXy+GI7PykZi/sN3CxkYDrWA0bM/Ax2K0NBVhKgOx8F+nHMZNsE9d3d+X/a6LQytHxAHBsz2YFYEEeBnRELMjCfZS2b93M6NCQ0u0jylNT5TXWKQQ7xiwX7Z2emn3Fy58NPgu7FAJldGQjqnQPJFEz4QIE1/PovIKIDBFzl8PVNGmjK06u79KvnCDLvZJ2qEZ7z8dgjzVoZampuMLbiDtykpc0guM98lIAPnjlonWbtX1wY0a0ejmtoELNENvqN7nOuaRQmcWXIrp6lCFViWvdOVWvy7DbF10m29A0HPtveZ53noaNBBnG2sABvx5TiSB0+Afl5rNnZkaihGqpfh9PCIgmptZVg37IQ7fl/CQd4lAbnROQ9cBqM4N7UmzDjnnqDBHsPy0agKACkFE50EKIq+dKA7wljjc3EvdV97AWGYJxB5FOYizt8TPv46rHEa2fi7AoKCfvECAOCBjz2Nk4fu8/XThvsVlNIjSo19ikMeOZCJ3IP3G+Y5DgwZvPMXjwo/jhdt0OG6LQwtMEwaQxR3S8U9L0TWvsfmHU/PyFrrACP4y+cgKJgiiwSZ/4t9fzH1Ka6MKjjdnxiJn6G7T9oYqgPJDySVR8H/Pqzu8rcFNL2n2ZMRNLZdFKpGJRNXFMI4kb6p2V03xo+COuJqYb1g/OrirbNNvs4PBO2UGQeAMEK+R+L/hCi0apS1WphsmWFineSYigDSGQkQIvE56t2pOYKpAijlwNBFiA64l5uMiPQQNRgMLIrgOlAB4DBHqaTSJU2M3lkpgtb490PeaSShirG1+Y6JlQ9FIT1J84IswTVNBQ3eLA+TsTS39B5hJw+2kWFh6y0TY4n7Dzj/8BxWAbj6O5iqGkrKSY4RYXRtGA4Bep6x2sKh5SEN62rg/NLmDgo9RAAoPRuPHnjByMjkRYeazytrPwMyE8OJqwhqVTz/rtfg2pvvwO7qkbV5wj6+l88dC16KRRYy5lRsWEnq4uEA5GEUrcX5DA5titsAJ535d2Q+5JWu28bQAocPe/6xzyd+xt8hMX78GU/f+Ew6biA2FV7osIhaa+xDjt3ScLp4ma4kKM5Qye5tm8xoPh5IJa5wsABtMec6OB9mcWHxJM4wh4cIYtPRg8xwluOUSk3UDaCoBw8UEbHySXoN3lJ51EpldtrCTDVDUmzh0i1J3Mow5ebQwgidjPNwMD7uxZKSZRFFipyXQnxM3WHJuW9tRa1TGOcORKdYirB0YcVfjn13gws1toIWCXwUyATSuFgk3tXoXjTG4clLQh/+8BmK8sBBeqOQhCMElPX08YlEmB10peT2/H9T96/Btl3XeSD2jTnX2vucg3uBi8fFi8SLAAHwAVKkSEoUKVKSKVp0iyYVue32K7Y7FVU6nao4yQ933pWulNOdH51yV1Jxq7rLcaddbbvjliWRMkWKepGSSJEECb7wIAiCJAjieQHcxzln77XmHPkxxjfmXPsCoPqP62hJl/finL3Xmms+xvjGN16M2iD/zRTmxZUSxFtlq++/nkrJuQk57daRAtxa0RN5NhDRArI6pR7zQ0tUYr81k9q+zfKJDP4PLnlHYXH6+kVrVp/99ziskSpaFJKKx6JTYLeb9A5NTriwSh7H5+/CNYqHSfuMOOgLp+ZikE0WvNp1cgStdiaJouu1RR2nYE3Z6gWE0W0YIlMAi5g3gcXUzWroOFMRdWZq6x9VoJLw3LPGpX3y0+fxhAqmMpvZQo2XlhoS6ALyRQD3GNN+WZiddbkqYc6BCyqWPgiFSkv59RnwqVoGUdthAiQ1rUy+s/pB6J9H9Aa48oh2MF66UAQqOQ5PLTNEU1QyCo+/SLQsT6CwTGH2hyAKgeDZZTvjAbBwOJkQI2WRIShhpdjvFaVYUH5QGx7WxDKOVESSujArxJK4UG77IGoBuCCanK7iaklnWtMc7ymr3jM9eWnJgajN9ySkRQDw3RsiNqejcAxRlD0GsLD6OFc9MrTQrxTCr/r4Z8/GYyLDarW6bP/G3JbWGqcJWEfq8LVL0tEBXSlLacDCxtXmqffI1+qImK+nVhe2sti9dtaidgSaVEheQwqgOWOKRUUcfpMbvSBNi7Y8Qcl1z4ZbvwmW2ZcYquXAplEIEspzCWAVLxdl218nRtBSlABt3lL8osH7aOksglmbF1j5UQpdmlVJkFSs+Z5qTFAYetKZL757jo8McXzru8d4IY9xb2CpcaVDTdwYRSsk6VKI80ABYSLFP2mchJnVkCxTdekMEBCd9mNhyT2AxcPVN27jgkskJfD9606h66jRmVihXpr5F+tCrz3iO8Cy3iq0Q7qp5bxHerUrmjwMSNqEVmR3+VzN8xTzFM63LmVVInKh47sRXwFbq9D82xXCrIqWUkLx/SRiqcKyg1xqrVBvEcNLYSZyi8tsaM3OcUswqKrx/TwsC8/von/bQxqKIt7Xx4jeCy7Ncca5CUea34tKiMqaSjDM5C6yI4lYPGmopf6stDNFfpt7i0ke8P1ZoVbzwTMA+V2oJfJE2JA0yoz72d4JbS/4QVEoDjcFv/ZrD+OnXjzGE0Xw3f0tINlqfMR4KHMZHdRlP3bvwd8TpCVH2xadQmTuzuowhXnfNjchd5aS97LrxAhaU2T9YG1jMOaQZiGkHbwIhoaFfhUuGtGqNgohxUQh8p6t7ivNF4TZe+rANvMdt+1hfxrxw2e2MIFmQqe5t7rxhwRvfGBkUvHzqq4I+G3nNcmbVUWNHLP2GZuHXgl3Jpz/LUks2D/4zd0DLOgCVxqqpBDrKjbZwQPE6RAeaFuKjurwikisDKYciwvClDNKabURqBRrrZbz78hafS13kSI94OTwUs4m3FwB2Ilsm57IPucm6AMJiiEoy4xX53sb8uY8cpyB6nqhRYcgnxUOWkVmixM/pKWDWT2VVZsUaXPRPZef7RtWKuB0SNixEUEQisrvTQXIDtEUJJEynBoH3SPiJsy9ngPXweeXdFmg8MUBKIbpaK2peN2PGt8NB29pnZ5VrXuGZM6jnduETnm104O5AN974hh1UlzcCI43Q+xf7vkQp2Imnjn3iMztbMaei/3W0ojCOu7XnpZPFJbCQqmbNbm0VHevEyRol+IFrs0UCI8t4yBFPKWUAtKlUFsgCiO7G7taelILilqGVhOOBJqCnCtuvj4BDwIf+Plr8NDTBZ/49BbT1oRUThnqnRYA8XTFTuB5ARrt6rtWbd0UfNVaaJQf1lAqaJ5dlxM+HdSd4p9pSQU8rFFYxZElP22eakFWHih3xrMgOJMBpHPaqFoNBijUay8MQwsd6oVCoLaOKxcxBwaFyICmIA3tW1wui5hwLbj+Rl+QA7TNHUgMrIp1eTiddpwrVKFJMOTB5bI91zouLGMo+f4ce/J+VCII52jfdJBcZJ+sAEhYXFBFSgMENSyfPjUawjY/NYrzGLKy/dDXoeW6lH6d+3Piio3cPC2lPqU91qtbn3aLJXJkWyL4+4dZjsZjJzhwkR5M8DxJnCdbqyasmiJ2oYsW6mjha/5vNBSpDoISBKdPKUYoZACGoWK7ET9YVBDcQc0Rq+1HsWeoQkKYVsobjfX3r4Bx35ZF57w/9wQnqZvPl7tOjKC1wxb/BOAaqBNMoW0Ac34IJaSZlZIbEiKKo9C13li0K4h2KeT8ripAFaySbeT1FQUp24YotUK4mOGpZUKAxoKaMPGCNt2tASzaIRMJEq210oYNsWr3f2GeiP8mHCOttilcY6O0e0bAf0RJ9FktLa9flTVW+8LT1dpzd6hLUaJbAgVKbEZ/N3LrRE78LHlsAIEqKJhUFdN22ymZxgOTIguvPyxWN8w/muwpBZKLmFytmIsiDWbFMLaWjrswu6VZQeSBATSzWyRMa1VFHkd7R/UqajbAprxVMXN+0lI5xY4X7yZB8x8AyJHWFr+bOgHf/72I8aVw7iyD3c82r7qJmWjsKC08T9So+J7XJ30nbooT/dmWY4sp7lg/kwQJyvXMvfFhZ9SR7eBo2bIYfX+6NRhRElCcOij4lV95F6766rdw173X4/Zbrsa3HnmJdgNo7HPIBF52+x0/TsAe+14oOlf6sxar3yANmbcz1s5S/z6vdp0gQatNkDTF2DYJhacLuX7aKmxhKyqSOpcV9pQtWiyi6lIoAOZJh8NdVjeyEaGWCXV2Tg0VZW5lBAEGboNA1RWbLhASx6OqLSTLzQ2pXjNBSygaZmcFxusELDcuUwfbogtELPaSz27dWXunn3RClzOAuMeQGZcrUWmKVZ0KPdb+soZUbDNnEWth48IqIiKqtVbJbvaHee0dGwBfKkcbxbsovFxLeevIm/19WAwesR/sHnbPnDIkoglaKxVJ0uJEO2W5QNv++VqNyKF1ZV77JZ2QkmXI9eiWNEEUlvGftVhw8vISKFQc4QINuVMwq6ql/AZV1sKk+rniWWGcMZUb7xEVwEpLm2ZrmMxMsVo7tN8UfrP6DF3CsyUDXReft2wSVh2AMNLEvtqQX28Rcewi8BR0o3faZzLAAkByCCkVSECWBk6IriWIPftDzpWbzHWG+yL8PHE/s5EkLufNTUFl5Dy2M4623/ruHy93nSBBaxfHSiHLtMAIZQkTkcLR0VNOXkii8UomgJvmsq+3AGZ4jKotJBenRp1PFbFMGvF2GTGPLog6hKUenJ9gMYuzqiHoMGZ8Uwla1ATRK4VyVaQsUJ3BZnRNizaAzHslT4OkUDRzry1pv0kA9hIrOxvChHYfchRCNFkjPKJPpo3aPStqady5eBNI1a4rq89UKEsgTFczF7tsudTy9xklYFEDLCZjHJ5lt9l8scFjWwtXtik1lOL7QSDhiCG3rF5YQj1sjWZ5xD535ra1MG/8LJFOKHXn+SLkzIWg+JzSAlG0ELHgR90B2RdBj/XgGvo94meuvKgEGJpn4+uQliN71joAzCFVnM+P4LI4Cx2fjh6zoe0l5bpyrIosRtFF+jgA8RhmWpqOYwxNjwPmeXKB7vOVqguxFP3SiMxNTlabZ68DTdmwq5RCaMd5wRLtEpjw3zulE6PeBHpZ0/byrpIQkSiC9ErXCRG0RIc9ou1QIBAHPKyPboLDww6xVOZoZNg5GwQezN6xOKxmlajlYIWEyd0JUHWyR7O9jWvdCqIIhAkaXF0gpoZwKQTChIlN4ZtLFRCNCkkaPenjqPKW/ndHK4i5uCxKoa/G3zaGmaACkQzKS5rIIq2wCsA00HgFkG9lKTnbgC2o35DzsnfWLmqLJAC/J4Uy1LlgtTG0XPxW37bnXckfs+tDzznWUqCOrIicoO6hz8385iBKLd3MxsaKMRPBGn3AOFwNJVCKNTg0AdkiPgDtlEC/ZnZVtRoP2heSpvlP4UskGnululXiiK12a9MJ90WyR62W7YeGgPmspGZFRNsiiHvurUVT7/RcTo/tocp960S2JAv/KqIRKkXkSCSfGAQliML4gSgBiGWauECmD4bo2KgeYB9SFDWQsx3cnq6y9+UctHNDRWZWWgnrzJxhDUhlVxC0eJKklmBIwOQ7h3udIXOvdJ0QQdtdYcG54AEuOwysbr/QYHCtRYTpk8SbOi6MzRpGKxGmcy4zKp57zuJo//T+F/G9pwXbYoW/mUdtmtCFFR1dndeRB4DxkcHndEKnmfWWnqpEt6QK0IRxu/FSs85zCVPXgrNrmPtsG16KRQ60eVlOdHJk3KxpnyOxwihEQozxBNCQUcejEg2qtkiBQKv2YfRcJzfoPE9WEZ9CN2ko06YksvG0RG9odRZ26wJE8Rh22qiKKi0Ti2ZzFJhRo1TmudWPre6gagixhhWSUgqn1DgMrdgLqRKuvc6BOntlh25v9Ao3gIRIvH/f4dgy09pxJ81A3rjna3u6gOi4OI8sfD8XEjn4VW69GskACuI+niCvWxwg3vYxlUNECnTyhs8UFubvHrZLwwTgwrK1lf3YQFIarrS42CyAd9dS9ZoLnC/eTxBJEj3FAkFQeDbtLV69UT0IVAu4QzlkisQjuGZ9AfiXu06EoG2oT9sLOPYnvBdf5KqKTAELz9gpvVHdnDTkoazFdstb5t9hkviPzCqa8ewL9qHf/b2CbbK40WjqlrrP9lEQVQM1wk1DRTs08A1IrpFIIyIp4KZYajVNyUMT6fcyUiCueStQG5KguUvaxTZYq0RFod93AhaRMJUBRPQA86p6pNRMqd1DAozjEIK8VxBVLZyLAkU6AT0Mo3++hTGRGuBE124fIPYD59+/k/PCAjSe1OmA2hVJcSHCKBCX7/HefF8i2OUeRShLoEUI8LsMG+wbjTJjje/Neen7dO1GEZQADu1d+sNstITzubUCO6FaUe+2H7s21M+1aKazLOa3dZ52VGp3cQrEdnXLLmsAgXwozXSez4WZTTCk7XkQ0jBWoCjFmmkAEIHg6Ejxsd/4Cn5+M+Px75/HM+Uqv1+rk7Go6cwX535sh7FREowBpqIXWtIWU6vduhGU+EIt9tplWXo714kQtIDLoe6kmJhSazcMhg6jabswj0pbPNdCRZsQqKqQxIIVNAeWyKzfvFkGpNHGcdX+jAuacLR1rphbzp8TAJRjroqabJtZeJDbdzB+ipq/lOIolpyUv5mSEzRKn72YzImHJhHQFBJNXCJzm6CO03aek5QCUUOpBeQH4v1hmVZ97j01fayNsleZbW7LRmroip9hXzA6K4JW8V1MR1FkqOUcSJGxoNYrqiGzXijQKqHjbZfTJGq2f7dDEIciKVAA7Qpr8xy2zCiahjUiS0Sa0ukLDWUWk+kRIna8/T1qla6oiyzjZuH7HI48U8ohqBklQNTavxOfQ/43QgjFu8VyDvz+1RUB0GrmNngQsM/3Q6MxYtMrTXSa7TnOKikCvkupxercdso6QIpikcEHLx1JXpchYJtJ8c0HnweK4pnnN3jxig3gfc1YD0P7c4QG0JKHrJXa6Dtx5zDrdjQl0AEkvgfDzpzWMxTtiqm3Ol/henUx/G/pCmdJN+DdTZRzNhTQoS6oxubsC3+TXyGZbotHU7YC0rjM9nx/XgJuudUOzYc/mPGmezyoujMX+k4FPTFOJC3wKAftsqVEkCGQUqGl+qaLt/VNm1oIUq3oZiPmY9fhwdqpfG/pDo29D51MVqIwp5bF0899bwJzHsn9GfrNLXwIy8ykQNC8X1gbLTrDrnbYmbM/l9aGG/B5Si1pgMi5D2XjHwrmKFrOPbAzH22dWsWxVnnM1nEcx5irlKwq2uA/o9nLcffz1rc+5yWugIhAYx473nx33/fcamTpxZibRULvdpS27OgIFgKPFHSuS7dH6NNYjEHbnBJphtHs1uaCQugUcX9Oi1aPVRejokLZscvyMva7UTiVd7b9HFJaOgWn2FtVvO62K5ChOLgyY71Hq8UxqsBRsYQQjROkFP4SfwTWOSGjdQ4LfltbuUiOId7bj+z/kOvEINpdQUI4P1czpRiaxMmKQsFh2LTvxwagqdgVVakKa1FOYdwLeAWyAqevsoN7y82Kx88B5IeYGglY+mUEqwtQxcegrSyhmv2BYSQJb5EIpdZIAtDiXXmdXwX8MIt0iVw9wdHQYUNA5kjqEWEc1Fq7fl3uENMEhDOvQ2gdouIm6+MDKTwWgfccT22hW/396EiywyYhjM10a+/CyAcebt47e7IBK7nu8vJ8Fp1PNHsbMmwlESPiQlv9WVo43G9E81aOcQhkSMS5QM/dmFgS0banYJ6Nu6RQC4eQLJUNP0+6oZ+z5EKxD99S3/t879Zt10QhC7ZQaTYTuSFoOO9uAkQ9gcMgKhElULzWRrPk4CjfpbHRdtrz/rCf+7eyeH0EWASQgCF4MB7Y54O3l84n40ZjgBdVxVWnMj7yS6/H8N99FnfdcxNuPjiD73znhVYHF0vBD+cepevaQUuRv8/OswPNcqGigWBxnlTVQzF7Eb7cl690nQhB25s+8TO4eVOtM4DFBmpslmhb3AtYcmbSefZ9M5kQ6kxobRp5l0OqpHPn2WokYIhJpwNA3duq7bTZ5ko8NH2wsy8CkVbPGwFh9gAajr7WosUpD3/Xnqck4mPjR9YqDWdL9hAZR3mmpZfppUkSkncTaS22ufGWtQSm7dZrBBB52UTlXhjsmPAAvfU1EFfEQrv5bXUNGipGVcwdr0qLhgKJFwVJmMhYIm2GLJHPDK+zZ/axu2xCQ5dMsyVqDMXqY6VzkNQHPeNLhW0nsRTrVdYXvOmrte06T8jlBgpVbZ0vuvPRr4lpJVOmVRpXSFTe1oA+gWYFQo3OkoHUUZsrAF3hGCz2LOkOPl+E569ZLuy3llMLvePe77lty7hq98+SMJe57WPV2JPDIBgGIFV1ByDPBxolEQrWTftunBb3vdyfpZLeAy4LAeOZ5zrJrnjdWbtXuU6EoH2lyzb/jLnMaOFHbXEF4jU3G1IC0CpQ+aehNr8KjzVVHsDLM3ZUFBjcHFNvWpcTRFud0aoWGwiYU4WCTgTeQnuAliZgi3aGFzNrtCE6IjhmK/V1AbjRqO1jbuyJzr+h22Ru+vjnOA+1M8d6oUARbmmGDqRTRtT99fvk5IHfiuDPGF0wDEM40JZOGOk2oB9w2PuwXbiIo9ZmmTXUKwAdjpa51qgEgaVhg4pIAYiZooaSOEOpU2T+DJrPtSINQ6MRdog0rpFIG9Oiuy2ayd5QKcCebbwYylZhFThbw0WuCRbr0f83owWGYQghF0VgGG3gwMIUjkcVaIt24JrklKzFTumTEUrocQpQs80CV7Z9J8BcW11fZQq3r2cvkGKc3VwSpXNj9QjUUCJRt0SxGdbkSJIgaY56CkUU8+RV9QRBFy3Wz7aE7UOQXliuXXxHaEnC6YgUQIBjhS4TaV72Pq9wnShBuzvYPgyloU7xghUUWoo4R9IjYbX42NpgPREcNXTUbg1zI0GlxKykUlC0ouoA28+Nnyth8UjkwnMQXNw44K7JQ2iCLcsrkCSETzQy5Hi9OEPc/WXmx5xq6uFC4ps5QTxWNuIxA2y1AH9ylBrPbMKVNESiGctMK0cgQBM+0UFgnltNVXQVwKCR3NCbWO1QsRZtQ9sm0Mxpp9UUBQUZPxdxxlQ0sPoQVGh2uDOSZE8rbciepibN09xVlTKlZZLBkF+fgtk4U7g5PFNIqrpA6NYsrIMlLRMOuA4k9Txuv+dJWewKTn4OnGsXElVLxLEugERqTSItHtbAB7q9ITA+3qw/CXOf269WAImV4ThWhDVJqy/uiVYMyvaFjYPzByAcaEji55WCzUFAztBSsRozUrWGfjOsSH2FW4Rxhtv80PznfsrjyvSyo2DKloV86VA8eK5ib6Uocs73/rNeJ1LQ7iIhKkFqHSmABEhpGy0Id6VjBnHoTcgiNmPDan4P33RV17hwbCFHzz51gPMvTdBIhW+CggvQzCjE2IM3tZfqft+Z050mj/5hjlzRBf3H55Yz1YSuHybW8hQg+tMTRhj6cQeIV1YKx5tqJ4Da+9HzT8TSO8hUrVoXnW59uFEfJcCTSSdTNL/r4kNNKTbOs3bUiCkx95pHVphvcDU6yJxnuWlY0LxtZiDvLeK1Bbo1VHDencsnWvUBNvRqSRsRDueCRcVbyzv6MT3gCDJblwzSBtWRVY/Mgy7w9eKIe6pgGdbVhHq8mywjCnIeADVrYZ5nDE4hUbFFSrgLj1oYxw3/eZvL/hJhlI8ukZ5/XlzJCAD2B2P4lO1PRg81CgxKp7W0s0JE2e9jmLJP1azKGQOm2aNvYv06nlTa/YDmMCVXDH/3viIbrTXH2ov5jXt2YqNfgz83iJabaIle/dAXL/3W1bZUP2xaqmtgn2gA/alrP+l4IrXljnJpoO5OQFF84SuX8GEAv/6vX8Tj632obxYtZlpEtSHVMEXI1fGGxh/J0jxCWycBWpZarWxdZkHZRDva+DhETYUmGIgSEgRIzRnE+QRoUtWdMXB3Ni8tYJshurBK83ijE0aAe8VTy/ix8aUIWGcrcRMiXldJW6iR3d9XhVynrx9rM9jzBlhLHxa/abGyTBSh4yvarziqVFiGH+e/IR0KAi+RWY2uKXSUkWvGDjpy5NtzwERxrGELT3elRWJ/5uB1U7e3+78pbOedko1AS3umgKbjsC8fGeF4tjjt3yIYug7A4oKkFbmx/WS/l4b09HIzHNx7LmhZL0S592uFZkFCW2PWnmCqM+kAobIEUNXor6qNi00d0Mi+nyQlPP/CFl/4/MP4RQDf/8HzONy/xtLWta1XWAEeW5tUMKTU+qv52mVJbf78/3huG7CjHGn7WGJ3NGuhX69Xuk6MoAWWiJYoifRBqdodGvi7SltU7RoSohUG4WeSb04KYfZxEjvBHIGZaZy0woWogTJpbnPBErVzr+m6VM3FFZur/T7QtSMErYo0EilqzEFTCcvniJv+Fkdg5uCQkhV4gadhzrZZeHaaBrfaCv3zmzBtDhjycQ2tpwW64ueF/JWjZTqfoHTYeSiOAKpuYRAB+fzSrGa3W0PXra0OdUSShJosYmOaZ6QqgDjVlJa8LBW2nSWNLLUoOi0JQ5ZA12x3s4tYaMHY+wrPX9AY4jxqP8dE/zzUvYXVX3TO7dIrfb1cAwbtYPexsuRqF6F5HdJlm3dRjfAqwIQUAo2LK98doNKVnbOoCxfu/uMcCpDOYpsrWhoCA0lUNFRGqVPWELgi0EZVoNXIqHXG8+eAP/nskwCAJ585xvGNDb0K0Bxh3fypW38CT+TIbHveBDL3ZrMnOkqHynaxLj0Vt1yvV7pOjKDd1aKqhjKsHJ4jM+oTtXCvWhFIpqhV7lLXUJwcosG5aqTRodusRKHq/XPyKLjq7Ar4DvC2N57B8THw5FNTRBKEl9NugI6PMK6V3t3atRlBWD98uzBNmjZ1BJOsFUxGjfv2R5KJC338ZWSocd+h8V59jGn/HPVDb21huswpNOEhvBks3RQikZrJd+S9qpvxvE92s6w3uyhsqiOX6u8bDTZ9vcxU7nlRR/QL09LQE8TajVtYl5HyVMqAGRy1VBgt5PG6yvRSGiAaqI+om9l0QRHE2ElL0Zz1sXdr1BfHCd4diPqzKSVD8l3CTAjwDgD0RVWqR5FQSEeUBa2fbl0XNINqBNiTeyaPSuepKUOjlCT5yggFDyWK73GCE8CI8ySLvV5rUyjgnuz3pmta1pI2odUUfWbtWm58ZXimOV1XtNgEjRziGTakYA0AaIUCYTUhdX4TCn1GLkgTmj19F+cutWzGy0VqW+NXuk6MoLWraQqaNYFynWBvmqgAyPHS2XmoPq5QF5PnThqaM1W7zWadXaEFeci4500J+FPgXW86j8d/oPjB0wcedtKb1YZyAx3SDCM3FYsqgRBUO/MGnusNi2tlami7GWxjF2aQNZTBcHIrs9iEOJVArV2JPgfriYVbiLQ79EiBysNJ62BxgEUi2wvoOUQvulFrxBnbHFsK7yKml4jO/zZlWt2x0jZqW7PlRjfUlrpKZW0uFKw53AROq+aP9lkxNaSefQS4g0dqmJtE16zX2qNKyyyyqwRFgoi66MfdrKylEyultGhXY3ONQO08zGGWEp1RyM9zrGFfd6LWuohOsPnVQOgtttjHSA6+mBytqkCpSJlz1osU0nh2lqoL6eJRNnDhT5NlGAbM04SUM7IMmJWtgFyQpgRwbEie7loD6ar6RpZWv+DtP34r7rtxD/jCA7j1jmuRjyqKr73CLFMN+w6+32v4B9hJQQQd2u/OIUU3JTT1SexhJoK0M9rONF71OkGCtmlPO2iMv2zB7cvLzcgFNtHlS4dQdnZAYRW0GGTtoUBEDMNgi786Zc6w1bRF0jUEM6zpXcfp9p0GfHFZDYkUh6pXq/f3Efei22jFEWLxJe77zNtTqpYW1tYjAtgg6NBqm0ZQ0SwDOj96s6dv4UMtnfwAD9nC03jVHSqgJgoKOtZIm8gitpS/Y6EVOKrrzV0K3uhlVpvhFk6gnXAxojj15eYhMgTmSJzcmyg8czX2Q8oJUq14uSF+Wiid+UfUSqEGrq8sHD219o6yNreX+RrQHJ8938vaEox91s5SaSq10SUZKcBEJFpoi4nlvWNu/UEEFgCajwOO2ngJrK4Wz86uKRyTDotyCWHUWYfctYFmu7hlzmvteXqOMYf1affpHISqUC+4JFDcfPOVuO3mfQDAwekV9GhGb2CGFPTB9MqK885oBlrMImJ8LedbcoxBImzT1313XmKvKlpA5ctfJ0bQUqj2FzU+IT43pnmbPcxZHZn2aLGbXKAvbEHziZNdoe6o6DdE2fOg780MldGq6NPcKsuQLTMteRgR3liavEQP1qvIOSkGrMIqJdVaIVUWZqA5LRBmF18puCfODWh6ipVWrN6GRNCiMIrFR/XB3KUWP4gdkkQTZpIS5mmKB1ffeFwLvuvQl/rz+2XnSKsLz1pa3dZam1VC9JbR5el3dMQcXRRabr+IhDCNoh9C5dLK90XgvWtp46pnwJ1CgAt95/RN2KQQRuEcCyu5NsuBFdx8nmz/Vt9ry3cpRPJYRjBw7qXriBsJGD2CdWXUm6xh+u98rl+DNr9e58ATbOwlWGReAC8dpKi+X+we5Mjt5RBnbZq2gUI5P5Rv1ZMzJOZjeab7ZA37nqHMnLJRhGKhjpHBprp455wzUHxBMmtW0HBvTjcbssa+zUhxRvqEl1DK2vwpBGaqRk/Y7yTAnllF1smjL47eZ1C+3HViBC1AGN4QqhWXLoHU1c1TmrkAg6Kpqe1/muyQuJeIYJ5n5MFiKpnjLK7dBNayRgeg7tkNhq1tOCtSg4YkuufNfjj40D6e0A4bUIUOmg5R8PD5AbKW6B5+4y9i5tzlCzjPE7abrSmLjrqgskjiNAvIx0mYzSHMOkRoc++WQ7USgdnfxfLu0yLFFmixpEWki7jQeBc74Br3E2HbGqb22rOGcYzF72s0tFjVhhpKKRGDmVnlTASlTv656tbLkmYB6RFIc8qhxWmr0gFEVNx1JoBGWm+riaMRjE+LwrbAMiaTvHVf+KYXjqHkHAX20RcLxcM91QktIuI+eaJPmw6qRulJb2FdpYrv5zYuSUy8AZAEh4eXsNlusLe/Z3pBJc6A+pgd7/keboJNVD3etDuXPI3iZ7s6nQfSXBlsMWTKVSMUj8BhyLnRKLGinZs4kDyNXQc73ZwjxgA0MY7234rY5wRvLWKJ+4Vm0lK5vdp1ogQt0F4OgFe1Lw2JsWqOV/oJIVWKp4Y2YduEgjbujMgXsI1CDe/zLUgoOuGiF2edXjrGpPtGDKgJnxD6gb4YiqVuIvuCKgs105Nc3W/GRbEwJkQrG2ncl5tw5EQrzDvMeZmmGdtpi2EYUApaVow23o/I7OU2VTicPPY2EIm62UyFUhUqVtSaZhfvx9hOCpQWwJ+MWvN5pwIygWCHjNaLwg+ZsNXQTvxo929+pxTvvuCUi3n8symlSsI6hYCxl7N4VotrHaClGGIFIkKkGSq64Hl5yCXciz6btUavser3CceXLLlWzpfRJqxbq0v6gaiKQhutulxPEdA5R1yWugMe/GyvUKMgCjDr7N9PXgnMNQcpAxdeZbY5lE6YAQxrDBgENqhsWYFNUfZcNk11UgbtnNN30sLrGn/vT5b2fLuXK2JJCL2AJkTBs+RzqV7oRhLb43RI3Gs8MKkm6Azfh+LJL4A7gUO+ajxb0b/bK18nRtD25g/5DlWrc8ANW704cymzx+u12FqLtROoui1Rm+Oq176ARwRoQyYCpv4pttuM/+63j/E3AHz9fuA7V7sALI0HI8IJlGgPAiBmbkMxDiaWBQJhlprSLDTz1ltu+QFEM+WpSaWlJHKO/B92kHSJ6k3ge7aVLLsS2Lt6ab+qFu7jnvYhZ6//aWZ8qdbldNY5CsgAzLpCm1e4QAiesUNifmj6vHbxObJ2Ya1dS+3Wvj3P57QzgwGEBcLD0vPCOWeoxStZjWJPW+65U1V7dz/vUK+m3yNIxuUGmqWASRLcLpM+uC7m7LEB9nVsGw/d/AdpR4D2CJkCtzjCh2qrXetKeJ4mS0IoBTMudzhSqKuqpYprU7QMreJ+lmRrzvH0tXQbbkSgREbfEAXnKNAESGr1J9S1N9O5xa0aE3A2nloM+QIKxhT10Qvk/+mwPjqccL5uAQDbLau+Sfg2SEUwU0x9z6XsrY0gDcg5H2ddQ5oFYKhbA3wwhDIc2pVJPv4BKEpYSq98nRBBy43e/lsgKJU8pBdxCSqA35GgnVThFbHUlTQ3HnlJ/q/4Rq4tpMfvA69t8OQFm5bDc8CLQ/YAfQpsbeaDNBOVKzO4MKusiKTFBKraVkopuwmaUKoGNWKkvAA5eUSFQJDbQecliG6+vRkPIAQCkguFSA6QyBzrEwkUO9/jOFz5sCiJoa/GTTehoRH7CfQZX57F1c8PliFvhgLgB7SNsymzGr2nSBeQ4ul5SJr/vCeRFs1d8rA93aTVeevuotDhe3C8LarElbpHk6SaYg9YUgEQjlFvo02UzSf168VU5WEYIiEHQISPhZLlBvcxCIDshWb6fRFCopvroCckWMZ4hvgc9UlA8e6u7NvVza9aqJy4NJ1r67BglqKl8YoYmI7aE3CntFqjT62kfv0c+b7iPJAGYORwQsZnP/sonqgzfhnAY4+/hHpwyhTbjiJPSstCm7DsooG4R7lvEtABKUL2dr7t+TYnVeGRHK2SF/rz8QrXq+Pdf+tXt3FgQnY7TSEkspvoST0bKhDbcrKpPSMttDbBVD1f3kzChoqM3zIz9vY7bSlee6bg9P4xVAugBWyL0aM5oMUyAmbZKNofG2aJ0DMKICoHfo862da2ev0EF9pKdH75jPVIjf8mdRCJE37QGCAeRWvArhXVygYuhHALSUrusAgHiz+bZmP/7B7J2Jgb7wi0A83nc8V751j7PUKpxbt1Hna2q26mrXPPtWXIhQJBq6PQzxkdg337nf7dJUm8e4xfEXPFtOB+C1vd3uV8o3v/fs6qUyHJzer0Movc6uvWxaM4TwsF5XuCESMO/NEPsrfMuL8W1BIQlEnb5XaP3eaeYXz455qDycfW7ujzZupdckZOOZBis24cNBEsJSuqnjLw0qVDPH/uRQDAhaNNswAdmcbTuvmAoGUx+lyy/m7MqfP2CEXuESqgtSgoaJxxrRVzqZhnq6c8l2JtpV7lOhGIVsMcBNqGkIXQEDAIvSEei3GsQSEYZrTgax5iQn9mipnZ0zR6KcWq46uFU+0NFX/pF05j/i3BG28Fbrsy4cFvCXhbceqCh5LFUABb4FJcM4sdopxSpAsPeXAT3cOUiOrIozkSTmIN8oq2SIHlZNkjWzB9Da1dfMFV6HCQQKQhlNLSO06kqDuHrlEjGoIKcFTi0R98DwBN8Pj3mI1EBdc7gHpaY+EU0tYdwuggT0HVvkSm8FxwqzTNlpY/D0UjtvY5adActtvUC8g0BKtQaCAlz2ACoB6LXLh2PmdWXY4DkBBUyav/i0h0YBAg+pGRn/bNg2Gw3mxGj/XtABEIazecKxIQXKiFtdEpBiJHhe/X6nu1OjK1iQrUh/YWbX7939NMasEm3ZyGCOtRXZhSeShYUa3VkIh2Qk5BGH1Gs757aV+/qhVZgPe973W4c56ArzyIO+64BnKhQqJbbgsLW+wJtHPF+ejTqG3qxc8s97uEEOZ3FMCQeWYMAVePbRDdaUf0MteJELS7l024e0S3E6RK2/hCjew50Y6+kNwhher50wxb4YrBTGqhrAppFZoM9hOs1glllbCeCtZrAXRGlQGDt1dhDKwJcKtmZb3L2CbDOUMRJKgVSkmCohPy4CFEHl6qaCZwmIOSwKTbqJcZ4/Y5KhV1LsFH2YavkFEC1RUW9+5MP8aswvUDkSQdjQobGzlQCh6hBeHmZpKETGoCiupde5m+rKDQbXxq3zqoR7YUENYipwu1Sa1oDT9LE84EpDuIcquq36N4VQU8M6yWikK+vxO+CpuL3rlWInZ5iX7N8ZaC8wMAFFdIXCQ4RYKEorPt5ZDB4gVf1BNaOsWjFdOsWCqGpVLiHET9Xw+fS7mVTYx56sO/uiiEvn9e5tyGntN4HiNT4ux0qBSQiGShU7pUDZSfPDlIhQLQQ71gnXBBAMCawwGQnf5wp7UpMzrMKm675RrcWTcAgKuuGpAuzOFP4F6uzZb0aBcqZfVwbiY4aNRqgNMFzCgDnXupJWZAOSeeEqxWM1nVIphKfXXq4IQJ2h7N2uSYc8T3qW9OSpwWgG0C1BDljJQH/rRpLloH8RSbPPtOcRPZuMVaJ0wHGeNRV8VeOq+8b0iWAUxixTu2dduQjXaL7CmNfQB+DSQlYe6F9zLuD1cevVknS4Hbm8Gq0ZuJB5bRGEWL6ZWaUL1yPiPHeodPSskdSjafszsetZs81Woxro5k2GJI0IRo6oQE425p6qUkEWkQP6fQcYdKH9vcx/Y2hyCagKBw1aYsKTApAv2F3GxsnRaARgPwsJIqCCQvKcxNCvOWrkvEyjRgtELWSqdODqSfWe1fW2QCFU2sZ0ef8F36ugVE06DfoNuTu0KZyNX+O0WCDt/XpwXolIx4eGC7Ah42GismH81CCGvLFRjTZ4VO2Arky9lKOigjGuVla77CrdXj+I7NA4sDNUUTzsWYi6aE3QSLvdisMZ9Xvs9CcHacNppyLO4YE1ho5qtdJ0jQNmcYs1aqFmzLBMsRtDCovjbmBJpQDY8mGeCJ0CBHy0mKg65tY4PCDRSiBVkER2vBeKlaUWGhl9EDykGHSTNVVIFxGDFvN6blsgCFkQCNeijkiz0cSGGaFEQBcIRYFavcipTszlXUEtAcSRSiFk2BWj1EiyjFvdEpI1rb2nQYpcIaEb4RiXqYs0+hVsrWD38zvUotGNAOCygwaTr4IVXOtQ0/HELq69O/pRAF2iZAqWydg3AiUUvExlfA2tY4J18H2xU+lJztXcpsgs9c3yaIoUAtilaf2GJXG89saxjCBUTsTfjyBZJzimYdzA4ANNAfS1ia0nBhzfhQn4eFMOTcoykvceds7zBj+3J7Fw99dBBKMMAQOgITs3BmZG1tu0nD9XSB39b3uakSfj/Mf99r2dOWo04D17ZTLOx4zNTYpC16iM9kZBWtT64/vOV6leS0kgR9EqGRjr7bEbdqXT4gbnzfn41eI4Kl8mePADtSCtGKWi3BN7m1N5di1MFclrpp5zpBgpZakxNE0nlGgfZrHgfNDrRNli20RLC679vYDNS6/d9LjenxrClB0hp6OmN16NJRrQ4Cqgs3Gx7FB1SMX1MAucyo4p7WbIvJNswUQm2jY2G2hWc4CnhYCi4dQm24jY8iQmQRDUNwLBXYso1mpwDCvKSHvTJsStoSqCFgIr2cchySlHKLZjAJAPBr1Qq6WFdeu3/Ej7JzsZuvEevLMCki4ZSBoeXuU9GUUgidWgIGHU6SUKQ0KgAIkzhVi+9sKM57WiU7eDTrwyqonpqpilpmQ7Rd94B4dmXefKMrFpy3FxtKSTpE3sxY7u/eXmGiRMTKluqKw3ljiCtX7tlWAL06t8QxGUXkyRsKVEfHpAuI1qk8jMutgQy5x9v5aJ9rDss2b6HR1GJMU26IMuZdEhbF9mUZDZFozVHRhIBVWJGhuVmxkpHEikXFGINjNmJgQZf4ehh9wbX0fQ/bE2LSH3PpQwzhESrisbN+b4aFluan6EXU7nWCBG3PV7k2JFfk1ZTMVLeFoTaEVuRMB5d5CBlOsnDSqDtSKhGuaXi2QFZVDJKwnQb84199Cjc8Bdx+NOHBbwIVBVlGr1pvgoSajGFf0zRBUsKQs8c2ligUnVw7mvDR/pVBr762uHX7hBii72sn9Nqm1Nals8wFKbUFJ1KqCgzJlriWAlCQlAKp0jZIR2mk3GgChQbpz0M1TVukNII1Q8OzLm2OSzFkLakhLsYrkx9beIH9zWqtkOyILJn5moeMeZqd93PlVgEGTZVSIENzBvm0Nr62E7yFc+DzoLWA6dn9+KRS+9WwPsKZ6IvTm/W8f5jvWoFZaaQAaPUdJPfN/opbXto5d0u8R/YYX7MU/N2VoKIvEgNXQAmDm8zamdS9UKVwD2HJ+rH+nrE1KczRlJcHMdsYYOPS0hXOcfohxhMCFaFgcso+Hu5VG0tUYCuW3ac+Nvh9py3wsd/8Eu6dDvFzAB599HlM46mwLNv5MF4XaoJ7rrVZjl4EXSALZzHQhGQoErXQtQBGgAMaW/NRBAd7exjHAVDgiiuuwKtdJ0LQijgfSb0dlqEV79DKlEMg0KuIa02bBlqrgGlUQR9poDFRtfjigvevFkBODkYFL5xf45yOeOO0xeEWSGk08wG2Kcy09rHDFmeeZ+sSm6wegqSMee66kDIAnuaMf7lteKJqcj2Wbiou5Gge82JH2jpbc0FUlvDzduVEvC4IR/eYA81kg4+NhZXt313wOxQyNtTRTMuK4rBKq5qDzzPfIOI1P21OwoFEtCmI+Far+tWcM4bAWzQCJ6pHsCHMSte919e5OSmdsqF57YonE1kzjlYUZW5plRS2fOYgeRGtEchVmjCnslykOVdHh1os7rJsoZ75x+QAAwsCZksVtdYs2s9zoMUm0H3WG5/ZWWkIOkabldBFKdTKimWdh1/deSut8hziLDGKQcPSOd4cN0BUK+apoUzGGA95iNhorQW1FCQxemIzb7BareKdSq2Y5hmleg3jxK7BxmsXT1KqqnjmnOLayeicly7NSNcIpnnr72V7b0gZQ86uHGxOaOJTAQzukDTna42EECrj9Xrt4X7AdrOJY7dajUgSNZKwtxoxFgMAB+vVwkLevU6EoK1V8dRTT+Huu+6Eg1GoAHvjgJtvuB6PXTq04s6SLOMHCkhBrRJaNjyoMD61lRa0zZwEmLZbAIL1eo3NxopjsDEgYM+cthPmMuNcLbiS6MIFFgBcuHghvNICYMgD9vf3XatXbLcTpmnCPNdAlnkYDCVp9Y6vaI4TsW6lDHkp84xTpw5wzdVXAhBcdfoUEiqCBlQgodoG7rzx81xg+eEeLiNu6mg7lPbZFgJkPGx2jzcLuDCzyJQczUz7WQZbM0NbRlfxZn9sk80SlDm7c42pjgJXdOrtVdwk60xMFu0m8mbXXUX1OUSYlaAKUEDBRoGNL6TAGrKtAdOGVVyx1AJkhHnJOhVxZ2kCrnX/VS8JyaQEE0wRvgRAspjFkFyIFut71hdVYUqydk5TltYc0uBolJYJLQrnLkWQBkNmdE41oawdH8mQLW+GyRTx4GAtS02SOMvVYq4tKaIHODa+1ThimrYYh9GFdcK4zk0Bdc5G0hgp2VhTTshi9UFIkbDUJEsVzrPVn2amYkXFuF5DZsVqWGP081OqxdhzX7PNeikFZZ690lkNx2pOth51LphnZpsqJCezHHyNN5tNOJQZVTCOY6D6ixcvYp4nDMMIESBn24N7e38OBO08z/gX/9//Bv/pf/y/xf7eCIXF5l1zwxn8h3/3b+M//r/9Z3j+/EsYJHnIUhfYLWKOJje9xnGANRSzhTw8PASqHTRkwTiOWK0GDEmx3W4BFMvmKgV76z3sjQnTnHF4YcSeKtL2CMewg7FarXCwP0J1COFQSsHh4XmI2L1FBNvNBvNcMeQR0zxhe3yM9d4aOQuGLJgmO3iqiirA8XSMvf0Rw5AhSLhib41/75c/guuuvgaAQNIEC1tTlKJYywZvvOt23HXrazAOAyrsXYheGSs8zROOjzfYbubI895OWxwfH2G72UIrsNlucOnwEOtq6c5aK86ePYuzZ69DrQXf+OaDuHDhAk6fPg1BxpgTjo6Osbe/D8Dar0zTDEliqEEV81ywWq2wWtnmO9oeBsWwnSaklLBe70V6dVUPvyoFwyDYTgUiJlzKXAIZl1JwcHBg3t5Ka8WUrapVJ56nOUxVKolTB3s42N9DHlbOe9vBrh4PXat1w+3jK8lz93Gr2Vvez3PBqIbkIerhU5lWtafKWnoqgEiIiGB+IAQBTXsLfTNlMTriqqViHEfMxQrg0/Rn1bRQAslSgimk+Lk4X7KsmzCuxqAiWDCI1pa9s3XpOD46xODpynbPghtvuB5PfP872G4OfZ+5jwBcB10ouaCk0gDdeP1htfcdUkYeBlS2AAKw2WwsQsN9DNa519Laj1Rx8dIRAOD8xQt4yZXquBqt3RSA7XYbhZ7GcbAi+oNz35Kw3c4dQAEg6NqyGwVouKFZEn3Uy5987o9x2+2349prrvXqeqaMjo4uvaqMOxGCVp3jJMpTbWURFRX7B3vIly4EtB+GAeNqxDRNmLaTCTg3Ey8dXsJqNWBcrTBNE/KQzZQRwfHxMcZxNI93ponSTLKLFy/iytOnkXPG0drMm/3tjM16jANHE2O73S7I9pxzFNcehgHbzRG2rqVTTm4SGSc4DBmqtvhDds9rYn+oGedfuoB/9s//Ff7Gv/tLuPaaazy8ig6KGdM849Zbb8Jtr725kWlARGQA3kBRFRcuHUOrRA1X8mJWBg+IrgNuZqIqxmHAuLIQuZ9933vtAIvgM3/0x/jBD36AlHIIdhGzEFJO7nk1Hs4O/tRxXmhrLIqLFy6gqj0ruWNqtVrZXKYlT0wBOOQB2+3k4WH2He4H8md5MNQ6TXMg822dcen4GGdOr1Eo3PydQTrDEQ7bHTEUr6+4xrTd5FxXCL5q5jKVQcWSR4YqxmFsiS4AhkCOrbHkdjqCSA7HXyZf7kI/5QQpYoW/Rbx2sCJj8OpaDbGSCoo97kpLVZFKy5Sy2GfbPDmZFcSz1IfSEdHRSiSLSgtSPI6aMb6Nl7dPJnheDuhcTEEFuoxGqQWrcUTVDIU7EknZgFl4No5xGLG/v2fJK2hRRKvVGoNbthBgRacn/TBDjvPhBKN937ncnAenwjz5CexW0Tj5PvpkOR+vfJ0IQWuHdWSeReMuBZjKjKkUN/F9IwEtY8x5JfVq+sOQW1GNZGQ9BSSrG7E0XHh4xbTfsLf2epgFl7I968bVjKNxH9XRE00dE5YIJKuqmLbbcAzs7e+BB1ahmMuEWmfXnibUNLVC26Wo10u1ez577hz+xb/61/jL/86HcPNNNwYVoDC6AjDHitXWZXhUowckJSS1DRmlpAXWzQH+eVImXIf4jxb3ur+/9t8JfvmXPoJaK7792HfxrW89iq9+7WuYneua5glMfaUjSx25jKMh27F7ErnDMpuSggimafJiN4LtduNI0jzVEWoG4+/mecY4jJDcaowOw4BhGFFrwWo1YppmQzSklRxhhYXXUSgUSuzKQJO+LwjDMn45JQx5aMpAGdtcWxZUsvKNjBbJKVHSQBSBPtNgayOp69Sqvr8hyGH+DkHsS8puBlunhSo1UGnyTLqUrVoZrQER8fjplsBhoEHDB5ByQp27FOcdU7gqfQWsdgWnNFx508pA8zsQOBU1nnZIdIdW1JogSTGOK0O1U3NqNdpPgFLdIlOcvUaAx4B77h1weNMaX3rgEGXu2iwpPCa3eEFvf3ZKhpK9JGMUzwGdocuOI4yK4B4xmsfD8RLnAd05emXaADghghZgfKSFoSR4LVMRlGmL7TRZW4zUMmDUkePeuGdIZ9qYEyQJ5mn2mgamjWjCRt45TIONqxWGnDE5Z0MO7cabMt7x42vg/wP8rQ8c4P/xxRGHWwoJhYJmW0MRkb6pXZ8uHtTwMo9WRETpnEsdT6Xxb4jd78lnnsW//O9/Hb/0l38Rr7nxBkiy3l2G2jIEGZI0sqkat9i0bEIC+tAtXvwIui3i1B1L19nVUicTjNO7++67cNddd+Bd7/pxzHPBpz79aVy4cBFHR4e4dHSMcbUO8yznHMJrs9mYgBxHbLYbW0NHx5R+0zQBEFeMo3Gu1Q7MNE1mbRwdh6NkGAeM4yoEWilzKFIOXFQwMibZqQZT5AwnctQlLcFDnRaJylPB2YqjK7bJMYFGhyjg9JUZ5naPqthuqzsAM9Jgha7V6Z08mDWw8tq8pShSHl2xT6FIDFhkjOParCPfsyKIkp8RjSCuAKpiGIfgvxNpFe1y/V0wx3yZ5AXDq/orpQFZ6GwiwGT2l81c02PazbnxrQOsjQ+FPErB6AAo5RTOUL6H5Gz1Q9RojuuusXvf/foZ4z0FX/2GYOuF7W3f2Gf7gkoiOZRlVB6jMrHcTWgFchqC34efg6izArOuE4WsWwHtPfGq14kRtBy71V3VkBWTm+g0A4l22QIFMHRgWl+ghRugeZ4Z3kJPfZibjnCMS2vI9/SpEVe+1jJQbspbSNoHy98RZfXxkqW0UCu7j4JtoS2OMqOW2SvJt6IcPYVBfs/Sd31DJ8FLFy7hNz7+b/AzP/1TeOM9d0MV2G6mMHGhIaNAkSmspSDiAePm5OqRa2/+xM+F6yB+aw8LIvKVhlZyTrjuumuhCvytv/HXAQCPPPwIHvvud3F0fIyvfe3rNk9z8YQMq8OQHHmsV2sTVNriYed5Bl1RVsnfEJpkxh57SJlUVE3NcmFcqDSOmjxpmYs3Z/TMvtK1zXEhS56NaCpKLzofCsBNToTFoWpB6jy8ANewQCuL0AhyGpzKmFDnGqUPRcRTwpN3wLA6sIzZDbNbs3HBUSCpoFRP7c2+n+sMyUCSIegbWn2gAuBez+zHZetqc2OhefNkKJD9u3oRq74/aH1YY2gP/vIU2whDbKyCnz8KZD8bIihzhaf+YJqM/ps3nE8LwwS8hmxKnvSziZiNi4dAHuz5CSkKvoQg4fP8b6NsWqy1CfoSe6zvXC0q0W+QZwEuvIc0RA0LdHvmR10nQ9CqIiczhxsct406MesptUwsRgZqNecHa6sCDU1SOANL5MiDEyjB+WEzTe0zF85PeE6s7uXwwiXUuodSzJxMniml6hpOrGMrtZzVQe280E43sBVK0qbxKVwMuWiEjDHkaXJh/uzzL+LffPLTKHPBPa+/C9N2CtpCXbMqNGI8GeYE2PZnhlC7Gkpt32jmHjfX4u/4vAQtEMvkv7/3Dffi3jfei1IKfuonfwLzVPCFL3wRTz79FKZ5xvHxsXW5SDkypLSawCriQsHXqJTZBdgyFbLFRJPKqdDUxblKi4tFbRwv44sthK6EMGAFrapMkTbrKmVDXszSa7n/LCUI6GRRHik7Gk4CkcFTXj2qxNN5c0YI/9nRLBX/PM+ARweUYigzDz6vpEzKjAqjE/q6AgoviJLdIsvGQ4oIymTzROchhTytrkVsswjKPKFogZQt5mm7s2koQE34tboK2JkXamWFZJjF5eNkDY2IraXCImjgrHUmuRUCSu4MTN7HC7jyzArnGgfk8btdCU8oEOVPg2EGxCimWltJxkVhHrXwrW2Zjec2NQE26s3Sep61/f+jrxMhaBXANdedxVQUx1Nph1cEz517wTyRpWBcDYE2csqo3sKEm4k8yzRNWK/X4TwLIVsrhpTCTKIAXq1GUA2KCI42E54Wu/f++YJBtgD2OtOM6boVkIIoZehOgwjSF/MEM1Bb4IkD/qxaqy+6ZaBZqq+Xzsu9N34GUPHxT30a5158AXff+Xo8+dRT2M5HAIzjEgjWe2vsrfdw6vSV2N/ft43h4Ws7Sa7Lf2psw46CQCRjUPEtjh3rCkj7hvjhGccRr3ntawBV3HbHrchpwHce/w6+/o0HcXx8jIcfeQTTZotxGCzmNnuGlMc0Wgxuq7Jm84ngUHP2JAy3LoZh6AqGizXZhFk6ZsHUoHZ6ikerz62b0ugOaRw+NWsAirB4aFVRUKjSm4524Gtf3tIVQAghm+BwQqJ1rGg98paCnWiSlQbKZOnDlwGHWiHDEBEoWcT3kJdE9KwnUbHIl+pFeRKz/mgPUVW0Q6oiphCSQDz0L0myEDmwnmzrZmJrxuxK7jeem+SI14AL6zIzRI171CyNbh5jUmZzcttOACQZstUuDdu/D4iVV/UwLu4rjfdcbOxA/87GBIgjXbmUrct451e6ToSgtbNecbyZ4gDTVDn3/AtRCrEPHqcAAxwhAIAatzgMQyCbPJjTInhTWNynHUJrbRKOCdfSmyPgwrZiuy9Yv1QxDn3TPIlDWj1n2/6blEXXFwouwzSZs4tkur+1CDyUxIPunWeyQ8gOtLZR5qrYXLiEz37+C/jSV76OaZo9RpdKg38L9vcP2vsqwrSVJOFUYbjSdrsBzWXmy6sqJBvVcu89r8db3/LWUEgW6A+r3F+rv0fjqvletn78ecUdt9+O22+7DdM04aln3oEyKR544AE89vh3cOhx0uRV57k4FZQweVB59BYT42FtjQ1ZsBZo42kbPy/wnlZVXbBQ4LBVuCuTChSx6I/qKJlURfZOraVWyxYqKeitIeWGeEWiOI4kgYH0lsGVkmcOznOY0tEVWbvY5sG4wdlDusxCMoEjbuamlB3pUUAJpjpDoB5Tzf1jCj5LU07Fs+JUSwhVqHVDtmB+QfKMQotTb9ZOdgGZvCCFOQkpn7pIBbiD0B1n7PXlM4HwAyQF0LrQClwQ+t5n5bEEAGnEtLHqXcez4uLhjLkWpLQySwAaay1gqJqnYruT0MZocy+esWd1IMyKZDbjkIyUkNTOMhJCiVEIA85W/AhoeyIErWkZIr1+wBJZHFXV+FdHj01weqZTaR5P47Bc0zuqUdHggtTTdoOzra3BHgDMZUApp7C58iWsLlTccKfghUetrqAdCOeptFV2Ep/5qkEwAeJRByqBXskLskpXtP5Gih5ZlaE35Id4r2HE4eGE4yML6yGKY3yniAnHF144H6XzGIu53W7D3GT0Bb3tOedImqieEQMxz/+3H3scv/WJT+Gaa67BT737J5Fzwt133YX9/f0oZ9dXrSeq7RsJcpVFLLrj1ltuARS4445bkUTwp3/6BTzy6LfwyKOP2fpLcqffgKHMgZwsacUVMQUa4IejOW5Y+SuxRgPQ7RevreDClV0Qgjd39JuQAHrpa42uBqU24VhqwZAH7zCgEUGyUPLaZSAlbxOULLICjoSZxac+95kWm5jwrrViKoZg8+AIT2GVsETCmcQOtYwVZrRB8Q4ORJrr0fa8zsUtLHUJKI7+L0dotFySC+4SdTBMCJYO1UknsJJY7YAw01Ws4BLXrm1w0FfB9RFamZDoFv3UMzbHH/+E4ktXXsJcDqC11SaIMTgAiGw3uPJ3Pj7WKLXavwYwEoBk74eWoceesXnIAX7skUoQ/KrXiRC0djY9tAU1Dq2ddzdrNIUDzEJrajhRyL+RG+vNQ6sOZBvaKrUnMDyF5trAVtaZFYyAi0crHJ0esXpJcf3Zs/j6N48wVeNyqyrKbCiavaLYXhsqEVerbvrD+eKth3/RFBYXHr25nlxIABoVtJq6F0we1gTVCCsjCiLfmXPGdrM1p9844Oj4KH4+DAMO9g+MYzTSzFFXwTyZI2WeZkNIHdJ/7vlz+Ne/8ZvIKeOuO+/E3t4e7rjjdrz1LfehbmcM44ChK75C03DBUpA/FSvFSKH5Ez/5Ltx335vxve8/gd/4jd/AxUuHONrMkQChtUIHb48CR2luStOBQcFbq2Kz2QJuKpZq85SHwQPMTagJY0ZBLp/Uj0CrO/DcJFEAiAgExte6d1wQra2bY7N5/5Mr2yotPJBz2iccAMB2O9mB9dAxhWI9rhZRB/M8uYxtRXdKqcge1khBNU0FUMG0nVC0WmKLvzvyaAInCySb72CerbV8nV3oRw3NtoAWJ+sKyNvaKyNaJIEdSpKVkIusMtJmfhPfForioWXtTEhQNybDWqcOlpucN2bZTHWFo2kf0BlABtOuWeSllTNt98ySAoWynCmFsBXfETQF3oVABhVicd+ZmQpLCYZXu06EoCUn4rQswtsH1xRqXBLYCaFW19wMIE9ezR8LioEa3WLfLK+eJn7xalIWz+lxdB5zWBPwpW+s8fXngTsOZ/z+Hx4BOWGQHIikOCIZWGFeBTkBdlsqhbZRuIBAa2YofgjJ9VEDLxw6aMHUcPRJPhGFUQ8luohCjUqhkB7ygLxyh4tv+sPDQzOzGCuvjV/LKWEcBzebWr1UtoROOePbjz2GJAkPPfwQfvu3P4EzV5/BW9/6Y7j6zBnccsstuOaaq60GgisJIv72js55gUpWcOrK03jDvffgrjv/l3jgga/i6w8+jAcfehjzbEIkZfNOWxEUNv0DN0xspZy71jG+eTabrXOxo69F52AThHnK2+VhCAur1LpYO2iF5AFJrWAJI0eiEFLHU2qtqOQsO3qF1AajAhhWSMuEQoI0iO2ZDBlsDrfTFEqXz7c1ZwwpFYKb+XRC+XjnuYT5bPVxDX2Lm911NpQrlwkPifMVqfAwcNDMaKOKOlOscf1xrvtmjSakOGc2x412onPMrLuCq6+yaKC776zYXjfg699QFHWBD29AWtzR1e05aNsmEd7lP8+D1z6GJ3AwMSVJq88LO9fWpijFz7hOfy6oA6AFcAMIHC5ijhWuWXBAfoCZcdXyuT2Mxp0q4fSAhmBm4eVWld+iBhQaMa4A8PyLM55Ja/z4vMVqNeDYx5e9HU2E+EQrHUe08Mye1EozxqUa4kWBMGtanK0Gsl+2xtDIlZ+nyTOhTJjPxaiRiBDoBDVTSQ+PjgIBQlv655AlHIXSjcGKm9hmm6Y5DgXL3tErD1i93hdfOo/f+/0/wDiOuPHGG3H11VfjxutvwDvf+eP22U5g2xx2ygJN2GqyNOcff/vbcNfdd2PabvH9J57EdvZssJSQvJlhS8Olx9/rNrjZTK7cfi6cxcV6cEQ2B7XRHnBlmVoYnzoaXDpSmxKi01W6vRtCyYUhf7ZUoCnmJPYA17+zlJhyO03Nymjv10LjbJiKnFc+DhOkEbcKWYStWbhXDSScEixULKIKmgBRtxIoXJKkoBAodEkIhJnGmRcT3TwD1XnmaP/dPyNZr2Gmktv+Vsx1xnXX2vy/9ceAG1+/j0cfnXG4YXSKCU7OTdUlWub9W3SKI1k0FAs/l2yS2cfjcp24n9rc6J8P6gAADo8PXSul4EMUimE1mtlTrZBKq/KFWEjLfjGnCENMRATi5QzRbW5he+laI++aiKt6wYpxNWBAwXCd4qrnK375L2b8t791jEmBMm+bQ0sRJRq5cXttqSxUAkTKJzcp4KArScRwUmCz80Cfry4wnih7aus4GOq01E5LcojOBGq0Sk4ZOQ84OBhR5hlzMRN/miYoKibPxIkqW478GbRvxcUVtKFScp5y3rgzccB2W+KgHx0d4+jwGN/P38eDqxGf+exnkVLCu9/9k7ju7HW46sor8ZrX3tw5BQWorXShIR8zM6+68jT+1t/+G/i1X/t1fO1r3wC5S9QKODeKweJGs1sPTC4gZ8lCMdO0xfHRBqvVGtXpFVPOddENNw55SuYY8n3H+YG0GgLjOEboVmQUSWtJRIEa66qNU6eitFobLcSMyr7fw9PG4olnAcpUm3PIvf1AE+qGwNX39xwREClb5lTK1bMJWwZcmYGZ/g23ACQNUOkqxMceNN8VE2tFPJBfqIh8q2hHFcAyGa1ASw0UaSGGjGk1yoclOrW0WHXJgmLFTJBFkIU8cA6HJqMvUkrBuYffgFGhVASdIuwBnP3dzlxOydORU1jBtnajFeKJ7wYb9arXyRC0qh4bqp0WtMsCpJv2p4nMzcvQqarmpQ6HDonsqhZn6Y6GCmbNwEI+6EgTcRPINPR6dQG3vC0DDwNnjn+AnE6jeLYOORmamykJsrcGJ6kPcb7Vc+ubg8YFPpaCuelGTglTWRvTLoIuRMg2ynbahreU0RYsH2lZclO0dJEkuHTpkqcBW5wjHYKc66mYQB5zC5nqa79ut1sILOGDKI5oy2o3WHnI6grj6PgYv/OpTwMQXH3N1bjttluwt7eP9//M+3DFFQfmpe/eW5J5+VUV++sVPvqXP4whZXzl619DHsfgTA0R04s/RRRKCB0/JM3R1VApzdGWgCKLtVhwrIldJqjcNYQ4HZzDMDit0W9pG0tfzKW/JwVur1wVrSi6UbVDODI5/7wvsxl5Lz7Hai20+WTsOOt95GwdSKyvKykFdW5+ckfzsJiXfl8GyHCAwMWrsKaV7XspTP+qBhIGWIhb0WXd2pbaa0K8klYAi20vf2/jEdRqzzGnZeuwEDyweEJDainhvFfsN+3OIn/vICA7jYnUwspYQKdFL8BlAV71+pGCVkRuAfBfA7jB5/tXVfUficg1AP4FgNsBPA7gr6rqC2Kz/I8A/CUAhwD+rqre/6OeM88z2MyvvbpgHFftQwlIaJ5kVcUwegyta60+j5tZMoBNYl/yje2EDanl+J0VewFq2cfRtSZgzm4HXH0m4+lnKRy9fbjnrpe5ekhNq65E7jSJxzHOc1AcNMUt0SHFptMweRtvavutcbbTZAIlSULOY9T2JOFZa4XOXRqmC1wRxSqPyAcrdwC14jgk/bd+eGut2NQtBO4orOr8nwnjcVjHkpRSLV9drDboNNnNRAS5lOC0tVacv3Ae3/jmgwCABx96CDlnvOnNb8B9992HG66/Hrk7VHZQEvb39/CRj34YSMD9X74fKbkjR0yZsGvser2HnrcnfVC4H3I28zUZt43O3F0cQHKZRKBACDOt1Rpt9p/tzPdYR/85E2EoVIPWcguAgppOLDrYalhaHqqYkmVOzZZaTlqM70pETfohxqsKFIuLtYyyilwl4FfUaxAz+UthM80ZVWcuRggguKLXKsgimIP/VEASUlX+E0KU61l6zVwnh03QYfGsDUQRmS/LXo45Q6UieYX8483sdWETsihqwgJ5mnlf47xVXVou0qYB7eUaj6xSIG4ykEpC7IW2x82KujxVeff6syDaGcD/RlXvF5HTAL4kIp8C8HcBfFpV/xMR+Y8A/EcA/gGADwF4vf/5CQD/b//7lS+ReJHda7UaIxxJIE52l1aCjjGT2sx3wDbOMA62yB3XNtCr70jR4h1tcecymRDSATNWuHQGAJ7F2c2Im244haeeuRQhPNZixp5jm4eL0lfIz83Uc3NjEUjdHdrGB7aMp35zLr7bIbV5OwfqL5OnjorltzPd2Da0HbTq6ceAxmFXoHu+PWM1jmZuSsKem9DTbFl4feUySQlSvFWOKgCLyhjHEeu9vYjPHfbGKMOoAF588UWM44jPfuaz+PKX78cHf/6D+LE3vwW5D1bw9x+HEb/4l/4SyjTjW99+LFpe25rN2G6tjB61aFg/pUZECZ1agW7R4n97imZB4bii5PwkpxR685MolUiOlkvrfjF3efYuDOHpwE5LMFg/wr7Im8PqI1etSIUOs6FLF25jbhEIrdZroGY0hySAKEgPIkkg6CJRc4FwX4dQ8t0dQpwzLmiWXGJTxIZSU2IMsyFDR0ghZP22C8FrdUpSnBNLr60QGSJP8Hi7j+NyAMWRWzcSckB8bap3ESFQoR+DcHbhKEOzHBunzaJGLQ6aPpBm2e5mL7789SMFrar+EMAP/d8XRORBAK8B8BEAP+Mf+6cAfh8maD8C4L9W2wmfE5EzInKT3+cVHtJltsjyF6zxKmKOsePjY98ERI7JY1mLCzuFpho9i1SdDXKKIPgw8kXAIqUTsDRIyQNePGXIbf9FheYtIMbNTR4KM9J8dlOdedxUlUpzk//WxgFJbh0PWBGMtEOwA53gs15WrQoZYwGphHLKSCsbB5MY7BDPKCKhdXvvLvlIanypRNompCzGuFi9CXK3PF0waoTOLtaWBczBWGvF0dGhHSDJzgs3dDiOg9eDBY4Oj/GpT/0OLp6/gPe+572RitwoGmB/bw9/5Zd/Gb/5sd/CVx54wDIA54LWw61RAjS/GVo3jq3ym6F55/x16VQiiuwFsHYoF52ziwIVaGvaO84ihtXpir7GBemfcNqgK/fosdaskTpXQ5as2Wq+hyHGkBxZavd+fVywReRkoCLitMlYWuahja8BBl/nzrzmGYUgrD9JggEsZ8oP2J+G7noLTkKYkiKkALeIAok5BJoCUBVrz+P1FJ74vv3+dz9T8NADz6GWBCZFUNXWqtBWsy7ADmjIiFu4iUIWcRY5FvVSedq1cWIx8gXPCw0U/mrX/yCOVkRuB/A2AJ8HcEMnPJ+CUQuACeHvd197wn+2ELQi8isAfgVA5Hsvh2ovztAeJMHx8SYEoohxKDm7c0etYLEJt4rsApVrTu1KxMAYSt7LNoILOq+a/umvTvjlIeHpBzb49nWTc2jekbU2J5IqC3k4qnatTadF9TJt6otrnGrqDqQJt14A8up5Q3QmGLUra4wyGYH1dlPKGIaMIoYg+xbkRD6lNp6uhSQpcmq1UJMIhq71SI+mBVbGMqk7HdUrRVWa0zl4NFVE1IJ1V5itO4FanYfz5y/ik7/zu1BJeN/73mv3V9oMdoxySvjQL/xFnD51Bb54//04OrZSihMtFWgrqsJsLd9fOVnlrCIkpgKTdVaDhALr9mnQQWCoVWb9Ag/e79ByQ4EdgqUC9+IubT+26AORZbYjBW1QEqqQzk/Rc739uOdOubO9kqghvQFwhdmKhouXdiSnnqrAWxU6VUDrws1nESDTEqyoauuewPhYKnM/X36UlTfpBC853OByWYELEgFiqUPAtm8NRBxtgMPDdJkla3Mm7Rz63knStYlScq/GxabuTLQkBWZbMiHB5jXnwSOVeEbtPfb29l+VPvgzC1oROQXgXwH4+6p6fkGUq6qwR/if8VLVXwXwqwCwWq10vVpFa+J+uEMmh6Ve/coSBBiWNLt3tdbSnDGsTzoOC7ThLwKFa3zXVCxME0i0KmYkPPCNiidzxvD0BufXiiQZSM25RSTIjQUUa53cmXJEC2Ha1YIklkTBxTWT0SgOKPPcm/MFC7O+RqPFocuOswiDbJkr/jzm+h8fH6M6J5scBbFQOcs4Jv9+eNBdIWhVc7ilhAHA0fFxWAA9J7jntSXG9codQ44n/C/Wlx2HEcdlBsswDsMq7qWq+MM//ENstxu8//3vwyCtcLRpI2C1HvC+978XV197DX77k5/ExQuXALXK/BZrO4fXOechuOgaiLcTsICjtLTYJ6kThr0VQIG43W4XQpwOQXTCcpdK6J1VRg2VRXYjow2IxqN2g6pZP7i8HsI8z5h8z1rHAovv5NHk/afttgvgRwhmhQne7BaIzhb3O5XZy1V2FA4Q37X3MwurM+CaSa3tGT1SZSUvwARvdiFVtDQaQ4n4Xej6meD3vB4/rr0q4exVA55+frbcmNoUcqMEKhjeZl0bTPQr3PdgI1kqR75najU2UmKhcHWF3XhaXizF+krXn0nQisgIE7L/TFX/e//x06QEROQmAM/4z38A4Jbu66/1n736lcUnuPE2AOP8POYUnuHFoOFaMY4eEyrJMl0EyMheo3bbuCBFl+5o9zZnVhMG4QkVQMRCYZ5ZjbhhmnCwVwDdx9Hm0GMpNcKwtjPNfol+RL355nNoCyHSXtEXtsUsulwVmwstJRQPzZcQ7kgLtFOr5caPdWz0hFiNhCQDkgDDysJ8SrUuAAJpSilJVJUSMQce04tt+tT6ZCXB3mgFdlgH1sLJ2DNtG9wvOyZYDLBizCz5p+bUEgFQvGpaDbriD37vD7Fa7eG9P/Vuw0mJ1gdQqwmv+978Jlx1+jQ++alP4ZnnXgjHE9OKq1qt1+DmHSH2qJMZeJGJ5+tAioaf3+0aUGsNdEqHFtcp7uECs3QomH/3ApWomN/bDQmLz3RWTv/Z4Nk7RDakHJYKAAzDiLm0z6kqlHG9CquRmwQplSjq05mC7Yy6ElIA6PY3OVt66/ufOVkLpOaQbgKJ0drSIgVYAoGqOjY/gKy44QYFHgLe/94Rd992Gv/kn72IMu9gPHEkLLSmDJVGSrvQ0cyY6Vbcvb0rMIw5rDB7pxTnt7dAe4T+StfLe6D6Mdu3/ysAD6rqf9b96jcA/B3/998B8Ovdz//HYtdPAnjpVflZvwzFYaG9AER5RFoCq9XKkFvOGFcrjxdNkRHD70+z1WxleBO9jsyYyilhGK0045AzxtUIZnQRXdQCnD8tuGOo+A/+Z9fhqiteRNWMaS4W1O8OIhZPNhSy5PEYHhTpvl2TwJSWlcTE+TThd/yzNp4coUREfzys1gxybh1Ec8J6bx38NoAwD7dbS80t84ztdmvNKKe5ayo5L0KlxnHE3noP6/XaWggNI8TfbbvdYDsZumNRb36X41yNK6zWI/b39rFar7ynGwWRteU5OjoydDZNODo6wna7xac++Sl8/OO/haNNTxc15TLkjNtuuw0f+oVfcOGnOD7eeFfVKYQsc/fpsKramgeSrweMA2VdYyLKBd/q+7G3jLhv+7Arrld079j5DK8IG4MJdiJYEQnem9QAIyC2223cI6fl3rLklRZWx/Azdh/m5yJOF7YGs+8F1ZbS3iO73auZ/AQKS8dcIz2dopGKnFqCB6/s/oHK+hBwakkRseVAmwtAIAkY13bzg/0Z++sZSYpVIvP/MznokfYUqguFingeBKgCD3TrriyoQu6dlpmjoA6ocT64L5bzsLz+LIj2PQD+NoCvichX/Gf/OwD/CYB/KSL/EwDfBfBX/Xe/BQvtehQW3vX3/gzPCM95I9btBV3nBBqkqV29cMxqWPnBmC5LZ2VkAs0PcW1Eze7LB1VE+q2qt1RJAugWcuuIg89fwsHmEt729jN4+tMbqLJknfGIeUiBtHioe54VoMloJgfbq/ScLM18oKGo4EIdORWPBSYqqKqt5xQa2qqzm8HOI7PAdqltDgDf0DAlNY6so8o5qe4gA7ZOVfQmVHBj6qmjtYaJy3vM0xycV4HF8m7L1p0tNXjblIyqWK/N+Vhdcd5///1QrXj/+96HM1dfZWumzvfC6qvecMP1SAKUOmNcjTHPY26RG4DlqPtOiipsBEp0pJCro3AtnRCgJdULyF3LhWsYfG/nPKPJD38Of9avNdEpBTafxbHwM+THV+t1KAERq77V77ee3+9DvpIrLSQvjF5rJDGkjsvvLwovceHFe/WJANGVXKp3JGj8K6MCuPksgIZlJzthBSJaRChdzJkG4ePWxACL6yrxc8Uy41K1INrC81FOPPeoH9CgGdRpjJyTp/OyvGKF1VVIl83PqwlZ4M8WdfDZmJ3Lr7/wMp9XAP/hj7rv7hWdNNFbK03I9gegz1W3JoOCcVjBqtv7RoKZ2LkzAXnHnpPhZsnR6sRK34kISt3DD68+C9EXcdWzwI1nC5IfLIZFkfuq1b2dSu25nHhDAgiU2McW2vvbIhO1sUmhZB54O7jb7dZqzbK5IlGZwHqkgWFCVrglOFs/ELUWSNLgg6mwj483gXzoLBjGIe7XoxftrANFS++sZYr3ySmHlUGFR0WaJEUaczgJxTjhybuYQgRTKfj8n34Rz587hw9+8AO48cabMAjTJgWodgCHLE4h2fv0iQp8/uyNOrkGfCa7A+8Klx6h1G6v1G7dejQDbSFkRr0UrNbrsGICCfJzHtFgIADmgCVIQAs5o1K197QKa7OHjPU8anLEGlSGatTUCCTngsyEmwktNrNUd6qWMvtaNpwXvKUraQp6AcKpK+gUiN/fzm4LWbN5uXxe46hwjlWDtjKdKEBVJCiC5WV1LQoMk45hott72nwwkzRq8cP3LSSKWNmpJXLl5wR58KYCDtD63oX9Xon5eYXrR1IH//YuX6TAHURW7QDEpksZFq9JVDFjO1mdSpqLEDYxtO+NI1PnJExw5shzg/My86ug6IRPv2Dtjc8+vsHeKuPKq2aq7Y5b5aFj/nbT3MsDiU7TLmMf7U8z7+nAqbV50FUVe+u1HbqxhXit1iuvTrWM6wSs+SPN+2maPIDfkiysO4ShR3MkOjUxZG99LhEoTyQ1zUYxtLKLNXp5DXnA3novOsLGBkwS36NZXt3EBxDIR8QcmKvVytvCr5CS4IknfoDf+M2PA9LC0awBYsJqvcb73ve+6DphcZw1uh+vVitYp18vM5iaCc2KV0SQQPPy82e9kq8uIAMB1q54UUpL/rFDuyyR2Nc74P3IqwLNIQb3ms+e8EHhQ9OeDmKi5MnXZ56mGCPH1L9DjXdohcVZXSwyCyFBhfE8EfWD69SdWnWhCOnMdaUwtggC1g62iMolfcAxOFBGUiAz6sEdVajV+FXCXQAZI1RdYXTnOAohCUskdjGwVA/SlEYDBs2RyPZXJjus88rgbeBZoW5Bb/YK9xWuk5GCC3YeaAMN8qDjvkRa73rAEOSctu4FbznO48jaoQUDeUqnEpiiW1WtxqeYidubfOKFJmop+FY9wIVr1zj75Rdw/V94He66c4XnXnzRG9RVtMIYFTmjc060t6gs4i2CUpoZBDR0YMirFQDpEQJ8I+acUWYzkbVUz6SpgQ4tdpQJHI3vkh2T1wSRzVEGoMqCJBqmpG1WxdHRUYyzCB07g9MNY4cOU9zDEFfF3t4eNscbTFuWl6yRLjx6IW8qPhPmW+uIWufgno1zzvjBD57EF77wRbz7Xe8AD4vbkrjqqtPY21tjrmYKr9drE+g6A3OL0RZHWabwzKPMd0Vn5fDg8uJBIqeZUsJcnROXhmaYTEDluKhz6lw+7z94iUsqWpFWEElysnvVCu344nY2GjXRl2bsHXb9u9ARSDpBoZF2nmPdKGxc8FAp9GJ1B7FFlAwjb7z0oMCrjZnUshq+qvDyuiHkrLZt7ZCtK5Tsv0cXhSMKScDR8R4A4Nlzp/DUcAUqXgTE2tz050U9jrrF7Tb+1j8UcsOQtM2rFf1q91L1rh6uSHNqFAgf18/1K10nRtDSvAqV6JeZ562wB4XtOI6GVAczWxkrxxg6arSoqgTzqq9WK4/5ZOEIM5dX61Vr9+3aXeuAogmP3Hsd3va5J7E6/xL29o4ALSjFiCSaWxZxMAc/S34wYgqltSOhrdTTBj06CseIH/aMlocNEXfgaAhVSAsXovDLXgMxEFHHG1dVqB9e8t3igoumoD8KAjrmWkYTx0lBuDCLi3FiWS1JQZJ1oG1I3zY0x6O14vDwcOeeTnF0Aq7WipdeetHNym5zANjb28e4GjEdGf97vDm28XgB68Bk2iIOABeyQJtHNFSye3iSLV67R62YVRcC2WJ5bWCW4k2Fp63aWId0yb+Go642bh3JrLKczXnIhJCet+fVI7po4+77gQ7iKG6kFmsN1QAtdNQR9doc0CMfDwE6YR/PdwHFdHSa3qoKSdkKdocSa11Kwonmx50hcBwDQ794PqwRRsLjT5gV9Du/+wK+evo4OjaQb+WegisJdg3ptkug8gTGy7bC8YxS5blVtficWmk9t3P4svPxCteJoQ6mecbTzzxrC+vVtXzFosUGX2bt3BeA2ECRaioSnkz44edmiLAY8RYwYumdy+DwLnZPFdM8459fMSAVxet+7xxuuvGsmbQ5WfvtRLRt32c8XROyzSETqYigpmyFrf2HkW/OwxJ1FaiV0UrnUcjyosd5LgXTPGHrpjqf0yca0FqAKnIekfOIYVgjpxEpDRCxP9nDfVhQpswWyUF6o69cNWSLShjygHE1muLzFMZpskiAzWYTkQ/zbFEHvVBjiuMwmNm/dodPSgnf/OaDeObZ58xOkIjUxc033YRbXvPamD9LUPDIDkdmq9U6lDaEwlvdIO659mWWV6xVx8P1f6hcLHPPaKsYX5KFlz/CwnhPOh+lOb8iJbdWlGkO07cv/mO8/DIyIuJ6vRBN386pdEKc82axy0PMLVwhsUXTy3plRJzflOCZSSeYmW+psE6UO/1kP4+EWyUFwdBN8uoStACRNNGmcb6tnKS9JzvaWqhjNreud2FxNBzrxMQHHhQNyiISIsQplA4Zs5OCUpaIROaqxP9yH7zMfHXXiUG0OWc89+wzuOPWW8zzKY5SfbNa8RL7bC0lCHcedEtUMAqAdEESy/vvNw0PD0vlFU8DHUcruVfVGjgy+ybnAd9MZ/DQ3Rdwx68/jsNTNyF7LVYR46DYqRdoZmqKgOeGVsfOW91Mbok0Ugo/RfKWGnA0ArD6e+sqYIJtM1mTQ+2Eu7SXjdzvPi50YVqmlkKLDqG52wQ5G0JJKUEG2/xEybE5hdlTdvBmTydt+fUSiogoi9/hGrGmrlkbLeECql6Iu+L8+fM43h63Yjv+jjlnXH311RYqJ63rMB03wzB41lNt1oA7LqXbQ73Q6rm7Xuhy/Xb/jhRvrdGFllfKORBNZQgWwYBNtheuT0GpBIcrzcETQrHby32cLte0Lyje7zWOibUOVDWcYcbLD9hsNmC79vbOEgK6V+yqjQpQkGtlXUINJQpFE1DSLM7eSUdhxcL3RIzSjbsCuOmmAjwCvOMtI4ZTI7745eqOLAHYFQO9QGzCMKEVuIejXVJavgxBI5j8sDAvgJmXCIdZhJCFLwavep0YRLu3XtsCi6Ki69dTK975zh+HakMCzQxCxAcqgPXKkO48TailYjttMc1T8FHNRLL7c1EARBhU4w5T9Ct79rkt/k+rK5Gngp/7V/fj+Kh4NgqQkDEOGUMWT10d/PuNG6PzpWm/PoLictREJF7rjLlYIZYyW9iSogtbkq5bg9+DlaeKZ8IADfUT0TJelOZqKKvRHWFjxjhmJGZiutIosyUM9Fq8lIp5miOlF/7etBSGPASqtRoTLSFCfZwMQ7PSfzb32YUOnWKsUvalL94PEatZrErFBPz4j78d45CsZTa5SGUHAR7etBA+PBx9AgDXLiwAzmtnEahLmD78irJBpAlAUkncrBTIIhICnJxp7Alp/HCSpsRKR/Vw1y5ibTvHaq2tjoeILBAu901RO2V0uHLwRLlIjIXyeQplQx5WAalhgZj1Yok85rfqrAOw/gACoZoAZnGnxu1yzISfTTDbfJw+ZZ+6867TuPcNZzBka2NDZK1CkOBCGo0S4bN5P2tAYT+no9DGq/G/vPjvnor6kdK1u04MoiVi4WJGXJwqbrnlFouxFAtvMuFiIVXzPEc2ELk53i+8qNAIjxlyhnoOMyCx0QGjHALdVAtWtmphFY8OK/y/bjqLv//ks/hfHJ/Dn7zzLL7+8BabOWGQwVKDMaCqeEo84xfZ+qPEOA1lZZSyPLQUGg2BAMOQAU0QWVaYKl4bopSCwTeK1oqChphLmULYC1r+vAm6VpSch8iQHDcRXGnV4FNFrHZBzgI2lRxX4wItLQ47ENlmtVYULRjQKKDksZysbWvmrNdHcIVJZHZ8fIxxHPHII99aKkt7Ks6cuQpveuMbcP/9DwRPTyekNS30cCexWuPDYJl8cNP65a7emdWb/5zDeZ79oLtwTIBUL/nnPeXs+a12LGO94Qee91wqB+Paa25lEKt/rudfteM1ewWu1VBez/9yzH3abyBrn2MW0uZ+pFBujG2TLbRUrD4IY5ARzk44hSncS9xqvIcYyhXvisE9allwfoZLs5ycNEMS7mdBtRvAKuGacLZ7O2UHeAidlYMUf7ZoQ+eq3fhY6wQIR5/5eRhWRmTfRR3YQ152//TXiUG0pVY89dRTEXbCg1+14oqDA9x9990A7FDO7lGslb3tW+59dvNxtVp5uE3zpjLwGGKccKkts2o7bUMo0KEQNRb8vv/N2avxu1cf4FceO4f/+d4RPvwLB1ivCrQWH3N1zzE1v12R8eXmiEVFLDN1FsWzmVmUG/rqs8FGb6HOcoXw+5IGWDmCsTCpAeMwBErm/Wpnds6FxWVqzAnr+gKOnHxc6/U6nGM55UBtDAHjf5dSrMSfm9MCwd56z9DpuMJqbX/YxYCojBlihR1+c144grabDb7zne/YxHbmfJKEu+6806kA4zaJKlNq5SqpPMNERVckpjPNG2fX0mJtLXv+3UOwqFi0/T4Prb23DVUjaoEOPyLS/v6ACRiOneOzjg4peHoAi89wnZiuG0ktHQrvU4J7XpjSc+o4cyLoPurAUCX/OwFgM0jp6LmGzmXnZz1EFLHOuRWKlAZHw1QWiLk0C9GFKNAK38OPmHbVu3SxJcJqqd61WIDgZxVUBIpIBHa6QoGFUzHGD09qkLbOf9brxCDao6NjPP3c8/ju957AHbffBq6KAthb7+HG62/Aww8/ssi+sZjIlaPSEoeEzikGokcigQBZsoUbEflqi3HkxjI0bJp1yKPfowBI+O2/djfe9EeP453/9Hs4+MWzuPZ/dBM+/9WE+7/2AoCEYUhIqQaaiAPk1lmtTOtrDrw+6qCUGcVKTIHZb4Ic3s7sMa8CWFlEoknfJAKgqBdRV6Cqb+C65HjNyeJtc7rDk8SiFWIuvb21ZV9NKNs50jrJLfIdiVABU4iDDvE79rSKFN08YC5zfJZlAq2AOsyMdQFEJA4Ac9niGw9+A7ffduuO6abY39/H6dOn8dL5ixHyxpoXVWszD6nE2UanW4tAhImxoaw2pmEdca0490ww0bQMEaO5Xl3A8juAtSrXovE5Il3rpqCY5xalQNOc6eaz+xdeDmUHteB7muiXdYGj7KO2wkimSIkgYc5oBVjFqw+JMqEmKC6kUmfmqypUPBGmClJu9Q5UAWRvUwXz4gPu/FT1RIxlBhvpMEiyAFshcrVHlLlAUJGS0x+qHm/rayUKVZ87F9w1qA23HKvJBDE4bvmL3uGjJw8i5p5ZZmj3WGiQV7hOjKAtteLCxYt48cUXoOqHSNoLnT17Fnv7+8DxcYR3tfxxpofWOPzW98k2dIRMqYX8pJw8Nq4hwf7wkE7I8KaHRvWj6IyvPDLhv/zFu/HXr/wO3vSxZ3HDw4e45W/diiSCr3xtwqWt0RI02Xoqo49TbKY6C6UQvabgXdVbmQOt/mnwhapQz6Bi+Tw6DpIAKl3mmWLxjibYEWOJ1FwbmW/iObgrESCNVuOA8xUCBWIms6Mnhu0EH16bedz4Rc+/T82MDVOVqAGIou1AK/lXq+KZp5/BxYsXcOrgisUeuunGm/C6170OX3nga2CX3J4rpIClIdqQlyMZDxNUAKLtmFFAp9SynDjm3skIAPQF9Eofqhh601518Z2IGOjqI/TIVdUaE2bNYZbTEugRM69aWp88OrH69G5f5m7PMx6cpR/Z86u9U3s/R3PBU7b5X1BCbj0I1By13X3s32lxf8ReZUgewtRP2Wg2Cz4YfT9kbMvayylqcBLs/EuqIPKC0UIkF+DENgJS1/4m+F4yShxI/NOdbZ187ZH0y10nhjrIg22yRx97HFPfERcAoLjzdbfjioODhYaeOwcBPdzc/BGXq43r6R1BEOvwSk62ulOHG4rmGk0x9bYYzzw34b/9jafxf7zpWnzuV+7DVU8c4xf/Lw/hHzz9Av7qOzY4e81oh6FYtSoLGLEi4RwfzcDVyhr8AYBqQdUZkhRzmVDrFCakSCt6ArhJNVjRGd4/wRbTkiEECRn03vsD/HeKUiZUbbSJ/ZpIrCtUkpLxw8gos5uftUJrQi2WTlmrFZQ5OjrqHGIWsD5kc66NK3NqCTkur7rPilK1WDYcC9NM0xwcMgWPZYklpDTge999As8881zsDkZB5CS4/rprAVhs8zxPDRUCVmi8WsjcXNp7m6NGIgyqeEZWcKe+f6r/PAq2JAtfG/LYKYol5zpNUxzwYRiwGleRmcjns8DPPLU47HEco6gQP6fQKPxDCoB0TlALPh+kYYon5/CKDspuiRhFxBRyQJADEOya4eRkayG1slu/t3njbSy9g08ArUHZsN4xC/y0CIDmFK5wumOeICgos+KhR6zd+Md+8zl87GM/xOzBG7TyLDW3gFFBcOSs7uBLKZsSNrFie1EEBYAmKhRP9/WwtARAqifllAYw4r3d+nq164QgWg3e6qGHHsIvfPADHiLTBp9zwm233YrnnnsuNnWmye9IijwZzaSZDijQVGLJxRRCuA9viXuIbZnjoyMMw2ihHX7vqlZ45svfvIR/9Maz+Lm//0b87GefwD1/8AL+QQJ+5rUb/BfbffzpwZ6ZVx1K5oGfttumIaVpw5ToePGCHF70RVXBzqxE26yhy2ycbMErqGUGuS7jtRJqqhYhkSwsLeVgrLypZAvE5lhtbOT4vH4pY2YHi0FNyczDcTCUEfHIuSVdhKKrjXNfNKscmpckZXZxyNb5WJsTilaMwNrmXLp0qfHOaM1E3nzfffiDz/wRqpqnO3u66jiuospV8drF/buq5lBq4emnue/QpapC6tKkL12njl3+tg8bI1pjvC7RcTgkfVwEA0FjOHVCnpr7veddga5QkoMM209pmYzQWRV0zFnbGXMclaqA1GjjQ9DHd+PfFkJIxN1oI40N3SvuzjcA3+sCr0li2ZW9gnol3tPOg6K442kqwHayPW5L2BXIj2GZNaYVXv7Tn00w7kg1CeuUdAkotb2ToK/Jgd4V1iboR0DaEyJoBfv7+6bRFfje97+PN957b7Qd5/We9/wUvvyVr9g3xPtURaHl2evRts2egaj23zapIYMhD9iWLaB2iCFojgUFClrrbvUIBmtVA4xlBHSNbzz8Ir792IzHf/oGvPPnz+DWj7+E+77wAv5pvYBncsLHr9jHH99yGo9fO+L8JeDC+RmlGlIpZUJOQ7wfHQoMrFYgUlOhLCzezGpaALPOQFVcfaXimmuMdzVOF+5tFTz9LHDp0ATGOCRIOsJ2KwBWYAsd6yAAegjQ90oif5jz4IkACSlZREStBWlIHRIsSIWFRiQ2Lw8AayewvkLyCJKsOcxhCLlQOuYM3fY1XH//D/4Qb7j3nsUuUliPudOnT+Po+DnUWiyCAYj3NPSRW6WyToDYmD2COC3Dpnpz3xw7bhL7PPXKm7z/7vfpgFyYrqApLki5CcaXq74VyiHM2MYZ90KqF1ZB76DRGsHlGkcSv28FhTzsyvnU5dWUBrlO1nm1kHXhNNtHaJ43IgRw68GJA7A7SNBP3fjV+Vs2Qbz6alu3O25JePpgjSef9K6/Ieh0+TjADlVH05jgdHFJyU8tQGmMutgHy7mVAGMBjX/EdUIELaKgSkqCr3/t63jTvW+wXzSKBYMI9tYrHB4dwzyerYma9TJqm5wFrcfVGJRAmd20BVoJP1BLZyAD7GuUUrIgdxEkbw9Dk2euFVPZQqvi4lbwsU+/hMdeN+LbU8LRba/Bzxwe48MXLuFvnr+Ev/eNSzg8lfDoHSO+fKvgm689jaPxSnzrW1s8+fQWmzlDsgmfVR4AzFA2eKxWkHuaZ1S1rr6Q5BWEEO8vKeFtb1T81Du2gM4ArIAHRCDDiH/+6wnf+p4drOuuqXjP2yuOjifMusaL5w/wta89g0vbhJT3MRfxkKWWhQTpox4UKZmzTTHEZlvw2yFIHKW6VdF3yBB0cc2wtRlHhopZEXMLw2rhY9lRWKkVx5sNLh0d42Bv3W1zE5Tvfve78K9//eOWYu19w1pTzISpTJ3wbxynUMmRj7RfhLcfOwKM8zPPTFJp9SSieLtqvBcdUH1khhUIGl04LYsc7XK45F75LAqNXhD0gjxicn3Yu3UR+N40uwlsqjIb65XQJXlKi1VNrvxrTJrPEauscYFEFjKJpr4p1o6TFwZT2T1McCbkJLj9thH4E+Cd77oGR7KPp586hJapJceQJmIfwCToc5Zqb/LHuDQUhI3LLMiMZcQJf8v5NgebOdxY8+KVrhMjaJsJBxwdb3Dx0iWcOnXFYuFOnT6F97znp/A7n/69QKi8RAwR6NyC9lkvdZ7nqNtqZk87JDmnFurkqlCB4IlLbFrjnKZ5WpgJIoK57OPLD88QvRI6VHzy9AF++/QezqZj/MO3T3jtQ8e4++Et3vI1RZVjvHjTC/jhazMee/0p/JNvJXxz2uKK/WP8T//mDciyMUHrp15V8K3H1/jYp84jDSOKUwsAsN1uwwmmKhCtgBZAJgvGVoGWBC0ZrIx/5tQhXncbACiSvIhpHvHO+6zjQa17+NQfVzz4aAHq7FSKu4fcQWECpB22/g8z81Jnkka5O1a7QhMm9OL2DSXpTU9IqGKKjrHBLJCdUsKlS4f4o89+Fh/8+Q80sxQmwM9ceRX29/ZwdHyMPGRsNtuFEjBBUwFlNht872l06YXTNX1vN/g96ODqGzn2e1hEsK2tXGEvOEOxi72fonVj6McBYOEsBBCx0kBL1OlToImomZxFrjYcc8nSqavXgWUpxKAVvJKbIEUsayA3/3cDfyGloiOFdKVOadFQgQCtslpP+UQ9DyFH3O4fVIQAWqzecU5Oi2DA8fHs9Ea/Dp2DEw1hG6iKvLV4nYUOcFqRtUh6NNsrPu63sEigP4o5OEmCtsQBferpZ/Hgww/jne94e2gowCZtb28P7GJa5hlgCE1VV44ZKdmLJ0dUUjsuz+M6DV0VTNM2ECJAFJBj0zKcA3AvcxVsvZgK2CbDw2Lmso2FKbXi+ArFH960h5vfcQ2knsfZ7x7hlkcKzn634PUPbPCmzQYfBnAsgu+tB4z/8hIunAWOrgKOrkw4PJ1wfCrj3HYP+1vBUTLkvyeCVVXsScLpWnHVvMVdj2WcvVCwf6li/5Ji/7Di4FCRpwn3vAS8NGdskuC6UyPkMxtcuHbAhWsHvHT1DKwyJBfsj8e4cGECygp5GF2oDEgDN6m6qWoTUuYStRAgiIIyTG8m551zhmQJ9Mr6njyM5BIDudUaBWGQi+8NcUdGizs9PDwyxNrzcqo4e921uOt1t+OBr38DKFY9LQ85uHqzkjz9WdFCtzoOlf/ukwiAdshUltldsT+IzrSFssV8uHIZKHi0ZaLxvXtOc9ds5Wc5Vy3qBgskDNi+Lds5kG+tFZp1cU/y/sY1uwiemxjqw5sChKinwHuPvapAFmklS6HhYRdoCNrmwff3MW4rKAfAC23v+AdIcVgNAoQ/wL8B1RmQft4SrKi89wurjGBoAjNigZOEomXse61WknEx76YRACjScHlVs1Y95JWvEyNo22ZSbKcJ58+fNz6ui6FUKN78pjfjC1+4H089/bTVYPUNz0Izm415JSfvF1ZrDeRHExYKzGrOmtV6HYd6b70HNnmcu6gGFg3hOKft1vLqnd/JOaHOzRGhtSLlEUebNf717yUMwwTZrnFwMOEnf/K1OP2OS8il4unPFay+ucGd2xn31Ak/9t0Zd3y54PLrPP73P2oCn2z/PBLghSHhXE7YpIS9UnGmVuyr4tqvHuGKr7QDtB2AH9yc8fTr9vH061eYD62eLCmWg4MZb379Hr760EuY64EpFT+A5LtFJNJlaT6zdU6EpbGmLtQomrIMos9DXnjy8zqjzCWoB2DJd6oqHnnkYXzv+/fhta95DUcEANjbW+OqM1d1cbieVp2SmXoiLQQqZ4ACrnSCxbm33myMZ3dCIBC8NiG2myQgImZpdZ8BWohW0BNo6LJHgcAyPIsUQD8uCx/MCwqCZ4dKBMACAfdXnxADbZXNepManVB3ndYSI2B+hv6cGHJtDESPDlv89U5WZPJoB3K2WjE6sBIA47iKMZcyA5KgTAvvuFgyFqK8Z5t/s3RbmBn3ZY/cF441iIXySmvH01ucr8CwLK4TI2hrqV7kpWCUhPu//BX8xLveidOnTy0+t16vcOqKg9gY7OK6OT4OFGJrbCZrVtNAozuzeocYETRR2XbaehUmEwybzWaRHWabXjDWtQuT5tUc0DrumrlZUOaCS4ceHgTBucNT+Je/cRGKGWNSpGGF+aoVAMF6BN52H7CqgiuPZ5w5LjhzXHDlRrG9pHjpmYqVKrIqNhAcC7ABcJgE59KAF0fgXMo4Nwi2UTHK2tdAm9lWK3BNmXHbXHHbNOHNm2O88+kN3vW9i0i/fxE/lwSf3N/Hx6+8An+yN+Bdb1njp39Scfutp/HH9494+tmN145gz7UW+M4NGlWloGFB9JRNzhmzWhbearVqMbJuaQzjgO1mCwW8oHUJzjiiD0RweLTBdmoOzHCHqOLeu+/GVx74Ki5eOkRiXzkeflRYSxIygbsHC4u1JG2y5OqwQOEM00vJssIyNBpd9vfuEXAktGjHRXbRBrsRCACCjmiO0lb7g8qRz2MSCIv28KIy6NEjqThDn4buQsI6px6xo2JuOPseTW6a0QhrhXdQlcU7APCyisLbB4XUhFYDXpZs5JEa3XtsomWTBKVhPLE42gVYU1M6Ye5OBbdwGpUj/nNGCVsIbgUkBSKO+YIhWSEt8SOE7YkRtEQ0TD09Ot7g0uFRCFoHGEgAPvgXP4h//F/8KmrVyAFnfVpxRDpNk3NOglS8PizNWbQq+YDn46sGmmIRGh5oIgQrv8jCGxlat34gWjgQnR29Z9cWEgAqhjEBcOdIbamgcy343JeL8Wg1wzJwLP1QVaCnPdHCNXHK1ka8lcMzr2xzHnDjElnZPJda8FxKeG6V8KXVgF87dQBVxem54J3bLX7+0hH+4uERfvnSIV4aE7773SvxnddfjTfefYBbb7sKv/9Hh3jgm+dMIJQESS0xIbg+NwEXlerd5OeGHYcROrCoMwAB6tyQL9OhGX63iyBLsaLun/vTL+DWW17buEHfTzfccIMLSKuZUIplEAEmGFQbf7lwDjmHSCgWSRbSYpIpAHuBZpnfPgaT52GCJhEkz34LoV1rpJNqNUchu8SG4gIizplItI8dF4kMfIjIIonhsqJBQMQl9+/S31v8vdlWaMlmipv4jDqoQXK2Zooa6BEOdoCGqMOBR+Uj7r50ZEtljRCIdllcbUWpCc8+b4r1se9MeHIi5WhnGlRoyjGjURl+bojEVVrLKwTd4fKBBerFlESbA3un3unGkS5Cvl7mOhmCVi1v37yzjZT+4he/iA//O38JABbH6NTBgW8Y10h+Gx6WMlsTQ1adsg1gQjQKUxOBZBOGNHUZTiJJLDUP5uRpxWvK4qAa92YHi9ldvRPEXo//tntFzOHCUvX0Wa/SZW+VXFsmSHb+qVrQfGKBnNqaIpZSLFJhGDFt56iVwCsQDNDsOUcZF8cBnx4Sfu+KA/yfa8VPHx7jr2wP8XOfeRFv/syL+N67rsY3Pgp85BdvwBX7R/jy12ZM7nHtuWz1wG5keBhV88jbuzmS8Aw9roOIVQ8jb0vnZkNbJiRYy1Zg6PYHP3gSwBKNUgLcc8/deOCr3+gs3xpOOuaw98VcuFYL87Iz4XvnSd8ihuMHvAwi0R7DsdCELkQsHtrvydTkfgx8g9zFw/bOmFZbwS24oeN1XajTJxHvha5OAZU/o2u6WFvubSLaBVLzs8mmna2GLKvhZbD+MruOsPgQ+fp4vw4dxgKJhCOKDxSHllULtrPg6994CQBw//3P4YkzV7qIrC4US6DRzr4JZQTAa150O0UoXk3JUOjzYvgh9wbHbPfw/1ag/AhIe2Iyw/o+6YBpsWefO7eId+Sfvf09vPWt91mGk0cYtM8gNJv4z5hhIyJRkBrS+K/NdhMZQDR/mfzADZyduB/HAcPgfYS8ZY59RwFZliAMT7MjD94bECRpBaHJ7SZvaMi2HaxGTxOH7wSgNc8TouIuIw4JOY+AJiQZrDBHxwPykAKu4QFs58m8+rXgUCs+dcUe/oNrz+JDd9+E3379Gbz2Sy/iF/4P38Qb/uU38XPvugp/+2/chquvtC6jhsINSVC4kveKyl3FemMxVpNCttXvdaFTu6BxPwThzOnmk57ueZ7xmc/+ccxrf27fet+bIxaXyRY9AuwFdK8U27PMSfJKqa7Ns42gJwKR1dZfjIkaPTdK4dnXG+j53b6/V/T4QrMMescdw8V4FmhhRDeMrtwiqZyenth1vBH1cX+0F0b80FCt/2f1PyGoEdYi3LTmc1gmUlWjdRMc3ZrgphlPIUwgY3TAamWKeb1e+17nmgjYxYQ1bngPhp8pNJJ1krer4f81WqkppFbT1pxqLloWE8Nn7HLeu9eJEbQ0SYgKU0o4d+4cvv3oty97iXEccfPNNy1Ibpo9Vke2VcUqcwnht5222Bwft03Zmfs5WUPCwYPyh2HAam2dFICW5snOAtM0WUNAFpBOYt93oc7n55T8vjkWHLDNwbHxj1XOsn5brKIVnmVyQUxhHFrXU8u8al0UFvcsxVJaKew8VnEuZVHtv/fo06klAjwhe/hf4Ur8zbe/Bg/ecwpv/thT+Iv/8AHcevgkPvD+q6BzwVy2LUxKzGmwGlch+Nv9pKttWxZdGkj1lFKiaSNg6ImONvKIQMt6mucZ5869gLBj/RIRnDp1Gmevuy64PXFnBhEXu2PwT1RNS2mhBCmkGF5WZnMYhZJg1Th0RWKcw+f89oi1F+pAS4s1hd7qHTABhFZB3xCSY+ZZocDdbrfRsy2eIS0cjMKSe2tXgYGWFeNxQ2TtnlYKdADeKJWF1OO8ivhernGLPmWXSs/SXCW4YOkEeVsHwd5qxtvfdjUA4L3vuRG33nrKrU8vfkNF4d/PIsgUiNKUa3J6LfUFzv1zPZfcIguolF6+nGa/lq90nRhBKzD+6ejoCPNsQuzixYt46pmnL3sJUcUdt92B66+7IQ4y0BZ4s92izBZU36r8Y+GJTakh0pSsBc0wjLaBYCnBR0dHOPYiNn2zPR8wch4h0rrH2h+xWqeeb121YLudsNlssd3OKLNVZjKKInUdeQcIMkTs30mawObBzSl7xSJg2s7eyZZe6SE4ZgrNQPGeN2/KY734GVEGc877UKtaFdO0BVTxtfMZ//76avyzv/J67L8040P/8BG89Ovfw7BaYVytMHTCKhRgbYiLwmq73bYaB7VG2ikPdtSY8HcYhgHTvMVctgBKfDcUyVzwgx8+iaeeeYpQCoCF95w6dYC77rwDAykkP1Aae6UJEHUoxv3AMolA+1kTICZoytyU4ez1Z2l1UMnuIlYK3RB0pWV1JVdEvVm/qB+7G/PbjbcVIOfcs9bs8vO0zoacIz+f766d45SmMS0E4XtrhcATC5KFc6laj6/cNQS3Ur9WTWvwcMlWlLtV2Mu5IUvjZp1oSKmzTK3eRsoZZ6/fBwCcvfYKHOwLamlcuSoliQTNAenmU1hkh9RGE8DaKQjGicdRFypxQ9U+o/G78Me8ynUyBK1vsDB9SaInwePf/S4O2Ym1+/wNN1yPK686Y0h1szGE6b2scgjUpeanhrJDkBcOg+20xdHxETabDTbHmzj4Vizc0K2ln2IhxMT51qijyuIvqih1jjzyhppGjB2CWZodnqHWoQgbn91zO20xjINrcOediZTd9OqtAqL8HsETwZSo/q+BhgFgu506tO/1Cnx4lw4z/u8Pzvhfv/sWPDkO+L9+/Rm87/wlpwXMMWG1ZO1+0zyZQkrNQUjBkbM1xLTl7GoJA9huTBiXUnB8fByOGZYaJOogj/vCC+fw4osvxXvzSinh5ptvxqlT5lCdHSFWpzZqh+pYfCWiAqQ58nYFXxwsadRS7dAusxwZvcKL927F2Nsz+L0wsTvh3DvHqLhCuDPe2Mdp3S2GoMvI/y6SIpziYe0HgGi5JTBMXTdnij+HnD4OBFiI5Aa03zXF1M4I9zjHKj5/fbyy8a0d8g8q0EKs2OKp6mxhlqm1xmkCttU1YDRExFCDY5KFczDWmffpftZerHHzuyB/itj6l79OhqBFbyIY/2mtSwTf/d738dJL56mnmgARwR133O7I1NqdRB/7ZES8IUV3uPgc2IGYgpeleaSqGIeGTEPoO+ET3nE/HEQz87yN2FtrINkqBOVkQroVYl6GCvUhPAtvcZfnblfnvZZGZZhJ01AhNEWDwF540HnEg26v0cwsCngLG8oxx+O4wlyq+yesj9o0A595csBfv/lmPLS3xn/y+JO47+KFcFwlP3iSxBNBLNuIbW20mvJiZ2O+oxXFNvqEwgG+3ny/zCD5WqO1jRUUSvjed79n2V6cLz90Z86caRWrdgUCej62oUAKMs5XL6h6xTh23H9cHScZDixdZo0BiOga7kl1IUZ0T7TbC91e8DJ0jHz4wqGFphx6RMx5tqzJ1uAzCTPgbFY4zpfjHYkSaUa72ArFZAKvrQLNbjbq5BPoouoe2X5j3AEAL7mopBgEwpjo6qVR/T7QJeLnOKIDL7r36YwZJfG6s4ZQvVxwiiW/XA6QcNk8714nRtCSk6HJuZ0mb7aX8clP/s5lTohaK975jreHgDY00cxKM3sndy7BEJ+I9RVLCXvsFMBA8Nqq5c+ejx8ooON5xtUY3RDGVbZuCSLdgawoXdm5eSZ36QhVGefb0PWuUyx3XCHQ4i1LZWC1O1/cE8+ICkCQ0xA8GA8mvegNiUlDMs49MYpinhttYGUGFUDC7OFxRoclHK4H/D8/8Aa8dGrEf/7DZ/FTd56yTQ2vSO+IkR14KbzIPRNVxXvnIQTvOBh1IJ3A5BrXjo6wTg8mtL/ylQfAjDWBe/khWHmdAfKxwzD63C4zzYBGKfQmfjin+O8d6wBo6NDGvUzb7AXv7r16Prc/tBS2RPXLeF2WsVzWwtWqUVaz/0NrKqUm6KpaZTs2HLR3MF9C7yiO6nk78lbQLE4qcBEJdJ2s6EigUVpapB8CpTpVEYLLiAZngKpbSTw/ZmUM66t9kgSSBkC85GEn+Ghp0ivGPe+TBcAdiWiOx/5KbhU2q9USW3JKaG6W1D2rFXl/pevECFrWGrDDk7FerXwBkzVYDLIewSOllHDttdd6Py4JHpICphUpaUJnmg3ibzbb1vq6czjE5PrBHMcRw9gcOtZI0Db+drPF8ebYior4YvXCjYvVDgfrvDY6oz94AJpAKq25X28aUpGIpAVdQWcd/03KoXeohXlblnVVmxDgfuwoFm8l0iPCWowf3nvtiK/+gx/DFccz/u4XHgLEapsSVZlyKIFm+P6sn9qbxVWrtx9KxsPqUpg1h4UpmrHb2GyIyXkiaoMqDg4OQknV2qMUCRooSWsLHuuVcvDECyHIv/0diaRo8dCy4fv2ji1+72UjGNBay/TolSi1X8N4P6BZYDkF/cbvWDzy0qE6dC3GVbW1Ni+lU1S0H0nw7rw897ltytiXfJ/eGntZVOw7rJ+fnmMN7jS+b2GEm0nxyKOWAvmth36A73//eVg/PQDaMrtYd5kz6w+I8fFXca7Y1mgXqfoeCsXZ3a8HS68mYGO+fuQn/i1ctinszzyZ5/R4s3HkMuGpp5/CA199oPFUsKpB++s13vvTP43Veo2h82zzgPacKdFu07pdl9VxhfV6jdVqFYeLHt7tdovtZovNceOBuWkpzIdxMIfQOCAPgpStApU5wyaUusU0HTeh2AlR/jcR5pAzhmR/1qsV1qtVFCDnxtw/2Lf2KrUzleBKiuhYxKmMJjQp2FjVKY8jVOg1HzqO01B3KY0fnr2f1FRmTFPBPM144gcv4sXXJjz80VvxtsfO4z3ThNU4Rppk9igOcnA9Hz7PM+Yyt0LWc8F2s40AfZp6q9UqNnoTymbxtIiFLWZVi1utADx2swrCOuCz7V0m1NoptJcNx9MQXLume08LsIxm9Jiq1aI8diwwKpZdQRt7oIsa4XcWaLt7pmApuElpkJ7pkdjCGcbas51AUUG0dwHfJw5mo5YoAJUcKNcI6i1rPOKCoWT8cDvk9l4KpO5XIuLZXMkda4BIsp+lZOnOYsh0s634/Bd/CAB46JsXcfFSRtUSxYiD3ovnS9CCzjBHyFYSQSYAkHZmwncCCVqB7wtVa+woO3Ug8KOF7YkQtIA31ONEqXkjQ/MAOOocYvSSCoD1yNYWc/CbABZoiGaQJDf9h8GE4m7SQmFRbTv8zSO8rEyfc8Lo4V8CiThS1kSgN73qToNDaSiZgmPwPwhBcnnFoF4oN6HXdQ/gxgLMOQEAIot+YNTe9I7bvyeQp104hXYQsSrRCuMPjbqodR/zdICHf/FWHF69wr//xDNg9MLoQfOlOufsnCzpoT6RQSBR9Ju8JTdzVCiDLDpM7Dr3uDlo/pPv5DtDGwoJs767AtV392wIaCk0ewuFSCjlVoKwt1IC3WkfL905YbQVOeEe4r7lOHYFfd8+vh8ruV7ytz1lQKuh54CpzMLUdlkR97U37pCsBMLjuPh5SYKaKCAFSPDMt9ZpelHtjEqGFpXj3ELyKfacBrBJSTEMNpgxw4Vo8++EgPA1wc46cx16HjnBQ84WmyGMp36DLD6z/NUrO8F4nRhB20N2BrXDtWQtigvnL3r8ooYZoADe8KY34B3veHtwpYtwqGxhUiyCn1MKVDtPs9c8rZi2UzQKtLTPYYEi6XQAvNScCz9rU+KmfLJnQ5o5l0MwOw9sCcOY5i0sBKklHdRSUaYZoFMEbVMyfCy7ky1JDl4wzB8gPOlA483qyxxcojgRwTxb7K6hWaI3cqfGaTaqwzdVsr+/9/0X8dBD30UdCh794I1424uHuOtoC60Vm+22KSFomNKcQzooKWSBpQlKRWLhXTNqBfIwmkJW6wQs6CNVepSx/Dt4NqdzFkKrM/+aeYiFoOzD+kqnyPm9fg8DCB6Pc11rjX0SoVyp8euIMSyf3QvQeAaWdRP49+6z+BwL0k/O65vC4hkIIBLmMGOL6axisJY/mb6OhHB6KiScpc5Gw1ooEfVqFPcBFMXbxM+1YI5oly6FN2Rktx5qvPDpg4xf+itWp/qDH7wTd7zutNf0bmtBp2ZQwalxxNYRxKgGa2vW6ixfhkiDTmtClKgYuIy2/pHXiRG0Q8rOFzUuEWgC48EHH8QLL7zggrYhW60FP/kT78K991i1/TIXz20v3oOpoZq+QEcenH8dhgj+56bkc/t40pQM9c5ltpCqbM4a9sUCEE6e4MRijG6SeWpjEqBUa4nNBWYcapKdMCKxGgtMLoDC+dWK7XYCBVQvWojqAm2lJXHPg07HhfgJcqCBFpjtyRhioVuBXLwvWC0rHG8HzMfH+M57T6EI8AsvXAx0zislN+U9sYPRBZCGpHNK4Wmnl9jetWAcRiTJqMWiIlIS5+2XYUsLZKvtWDSEuQyF6uei/zd2PtPvhx7xLgSg9Lx2CwPsOd5IEe8dXD2i9Xv1FcFiD/WoVS+P7ZVunfkd1kUgOiXSp5AM7zp8zR052nNrIEm3m/05JjyRmsBnTK29v5+jQOyuHACvS2LPY4ibURVtvwFeJ7jaeYm2PQCSKMa1fXaVvNsHyBZcXlYy2uT4e4N/+T6XZLTJLqfM9+rnt3bzB+AyQfujUO2JqHUgMG88+bTVamX/nVLEoV68dGjNFOcCyWrNB5PB/muvvRYf/chHcObM1fijz37WTNBiJRZrtUIu4ziE1xoApu1kWVjVuTinFgYXoFUr1nvrKKc35AF1aIiwlmpxolvT46txFfzXkA3ZMgwpp4RpniGDRGtt89gakrOssNZBlos2jEMIN9Ipwzhi2k7hrLNoAT8z0oqv9IcTwOXCocxASmAr9taVtN23R4u26awQ9+Dl+CqAZ54dkPKIzRWC779uH+//wXn85zdd63RBU1Bs/93zoALjLqujnNH7s5GyIdqYJtb5TR5ryjY/5mgbXNHN04w8dmU1TYJ0CpMhUB1K7c1Z+IHNOYqMqI+DVyDFbi4jbditJoKAQEuwuerv0ytj3q93DvU/70304JB3hK2IeHlOs0xUlwK6/3wI1+4ZWiuqqL8LnWHdZUDVq2451dbFCNNHIAKkHY+8AlE9S6CNv+X7+ZrYiUgo2vX/cqVrxfwnqAMheB86dKg39rp2FWKlgTVS0UCjX7h2XMveemnRKLp435dDwH8uBC3EHCdsL1OPa5iNySe85Iznnn8e119/PZJ6y5ratPiYE372fT8NrQV/8rnPe7iLmebTNGOet27SwNEGMK5WqKX1d2KuNQUcOSSodTMgSuiD7nuOcZD2vcxsmI6Hml1RAOQZPdVUWQy7eb+5mEMecLw5BkOEZg9Zk2r9sfqDt7sBej4ye4gXfw7YwbFz17JkctQJtWgDliWk9SApW+vrnCE54eFvXcD7f3YE5lP40/0Rf/X4CGfmgnPJBLLCK3CVhvhULZYWQKuCVXXBwQZ9AvFuEdXXbVgU7RERzMXKAR5vjrAaWVbThYW8nCMLQauEKc0DCVpLXvpQiMeWzilrK2TfoWke3XjpqFSN3H7+yTljnqZASP360akVc0BFRSHhZUR5kVNG3N/mKWV2qs1BifHzpRR3mPI71d/DD0YFak1OBwjC6KV8UyMU0O213kICEPPBK/hO7cR3EtTZQASbm1d1rlYEqgVSe6XioDmtwc1L0swEdw3lQA5W0dAu5xASn/ICMxKCdpcOolIlYCAatjEJ+sSKy6iHnetECFpVYHO8MSSKFKYFQ7ZWqxVqKfjEJz6BWgre8IZ7rc/SogivCYm/8HM/i9XeHj79O5/2zJxqji93NCXJXjmqKw+XLAWVnRjiwIO8UTuoe+t1CN/YNS74KUSNK61xCIl+xDkiOsiYBWcJEBWpq7lqZo6Egw0wwZhTCm6ZJh8FIVQ9p19iYi243RvN8VDX6v2s6uIl7N1pmjbzl/OxGluZO8sTLzjarPFf/pPnofMWbzm8En8V53HPZoPPX3Fgc+v5jKQDyA9O1R1xnXmfnD5oc2/XkId4114o9YKpFKudsNhXfvfVaoXtXAJdIykAN8/ZShzLsDRbM3H0V1t8aZ+FB5sHovWEnqawNFWtNSp1QdU7GdiVJEWvqV5Q9VEJAg9X8umIyAsHEVxPoAXnK9KiBKepCt8DLN6kFSB/6UrF5Sxcy73sVWtpysgPQb9WklKX2uvK0tHrzuLYWMuy2JGkVjNCsng8blPSEM+qqxm1zjRb/P81zg04bxwtf69ohW04f93YpZt/ouVwlrny20Wvf76cYTSZnA+iYFIoLl26hLkUXLh0iI/9m0/g9//gD0HBwLCwFvyc8NM//V789Pvei7Vni4lYrjSqZ3YkSyaoFZZcUNQRgAnBIZtwT95cjg4wO+DNsVTmgnk7oXgqJDeYSAv7MjTJhn120AO1woSHpYLOKHVC1RJINntkQ2++VxfyCma5zQuTqXeMhEe3O/zk60qZod4GRku1cnTaBB4XI4lzY4M7yjILKCtSHlABXLy0xqVj4LGVfe/242Jz6pxGi4hgDzIEQucuD8eNOxANzdq6TVNBKQogeTUr43QJPfnO0cUYtocAQLQVvQ7O0a+oLZAaWu35cXX+MLz5qpGJ1Z7SogIYXhfxuN1zzUmlsSZhQaEhQn4vxorGDV/GB0sTosljs61bAFALgo9uVg7DmRraC8ogEhfSQmj2c0lFDtY9JryzQVqTRheyoeiljZVCsBI5Q2FV6rw+gpuZBqTpmE2Av5eqoFTg8NjufXhxi+3WxmAlKLtl59yRTw5ZLUFXAC2RodbqhR5NEVbfJ+GQ5FyFQNWYk12K7pWuE4FoAeMfTWgA1GiGxryiPmz+qgJfuv/LOD46xgd+/uexv7cGy7dSQwGKn/2Zn8F6tcYf/OFnPH7VOcdsCGTIK/emu3lQKxQF4zh4tavC+TQuV43LrWoNHdmyBh2CZDIEBFGZiuaeoQptXJIvTov/dW+oJNTCAzYvFpGmjsJ6J5lZ2MJO+spIPZ3AavyBHEqBsD2ICJCt7kPKOVqJRC1RJedbYVk7GllIIqYUxgG49upjHGQADwHXiRVjDm6QcZGwMpOcjzywSE6rUatQa3sO+JoJ2MMtIQEZjiKr1eNV82CLWIuh/gq8rJYynYfB6jCglcAM0x2Nx4MgzH+R1ubbbrWMg+2dJ3GAZVlljMorvNhuAfXf6+Nle8cOP7Mb7RDvmDp6yKNRajgwPVxtR3wy1LAUC/WzJJPq0TmGftvVR4yqxwxbrzD1/ZY8tTzmEdL2Tm6F1aMxo++76KrAkD4/46QxqBcJFl44L/j//dpX8EsAvvC5b+OH11xn7+Fz2r9j8ciDJMmiKqo5oRknLC1bOwQphCFwFdBmuZiKl+73lwvVPzeC1oTeEtrTNCSPJwJMly4hp4QvfOl+bOeCX/roX/biwBIEOB0a733PT+HK01fi937/d3Hh4kUApulXo6X59ZlRhobMDK/VBJlVb0fnwDKHUXEEqn5YC1GlC0qt1v58t9iGmZo72TtqvGutJkiz0wmMgWUX2f7wA96C3OsazKkdwuzv3+flc6P3F3/P3zXzbVmxKUk2bo3oDwLN6CIkBNdfN+Df/fAVGMeXUH9XcIVUd0iY1CIKh1rxDQsGV+hMwcSW8WlRbU1g96fTS8QOeRErjl7UzHNRM6X7tjZtznvEKKhJAJWu0HtnJvph6YuRc92YbrooPLMjMLkGPSfbc8m9MF2g4u6ePd/HObHzkRbP0LoU0vG3d6XozV84NUKOlPxvIOKk4eipXlxW+XczrAF4ayT/Hs+koT+F1IosOTpMcM1Jsah3uCDizBCTZ27YSPufzlR3BKwzBBmHW1ubaesOTS9Yw7ywqCFLc9/332JNXKErYL3rHKwwFZ1XROvAOzXwfXcugv1Xu06IoFUcHx25kIFnbwHDYLGw9BInSZ4pZBP56Le/jY9//OP4wAc+gCuuOABXli3Wswjeet+bcdVVp/Gbv/VxPPXDHwJIoSkHTxzonSV0tJRSsLe/Rpm3LYPIs9UY3B0HiOjF/81DnNCCwGnyso05W0ev1ms/KMB6fw9sIBm0CDPbqnn8FRoCtngxG5aJBDpUxTC2ZJXM+upC/eEHLJ21ukaPymCwep79zlKF834I+kArME8Fm0sXsX/tFvNasJ42UC3mUHFhMZeC7FYB0SSjM0intPZDyT3Kjm5g6J4KyCBGjepL6nTPdrNBz8lx7pld1s9NHH6nBYKSEYuQMA++JZNYp10sHGZJEopY0fMe4YZS8z3IaIRdQUohR8XSm6DhrGQmV2rfYUEeyR5hIl2XWwowbbGhFiRgCj4EjFsZDKEzoemKzov6sPJcE2FkDhRJMopTXP4bCLMKad1NU/DL8X61ZZ05Q+g0Xu2AEvdXZ5FAIJqxvw9cf2Bn7cyVCasx4XjrRn/MIc+lPad085K4LZwSTADKTt1eoHHbbC3Ekah9uX8DG9vymLzsdUIErW+4WjG6x5/amd1sx9EErMKEzJgzNptjfPH+L6FC8Usf/ahvZF8aIYEuuO22W/Hv/bW/hkcffRSf+cwf4eLFi1it1q10H7lPpxDmaYICOLw0AVLD2ZCy1VtlTOu4Wvsha5uoVIvf5eEoU0uttPqkjW/NOWOapyhYUUpB0RKOtR4BsZj5drtFzt4DTVorEtIfvSMMjmzDNPKf9wiK96eiKWUOx83s8+e3Qs6OLrvQGMkJFy/NeP75La69RjCvBAd1i5yBUiSoh4HVHyHWx40KpdphnKfZBY9i3k4BEVj5yxyNje/OwxAJAOM4opSCw8OjhUDlqaYi6ksKhuPE33UYjJ+vTiFUpxFmmrxuNVG5LRStNMdKOLWkpYTS298j26YI80LA8g9rf5BqYHaXzaD9Ham2tfH3jb4gGPA/aJxwKcV6bLlQYvNMnpvgR7vz2e+dHq3z9yKIMwt/Hiu67Ua7xNiq772IXfdIDYYaakcnCfDaW07jI++/F/jEl3HfG16DT5xTbKZj31YJfSywcyexDZIfCb4KAXcoNRClu3IR0mU+gf7dy4t/687fL3+dEEFrfa64gCxiTZ6Uwk88gyglicwSEcHXvv5NzFPBh37hgzh16orFpiECOXvNtbj+J67FG+69F3MpeOThb+GLX/wiVIFz584ZV8hWGt1BKLUgj0PE3FrEQkaZZ2w3E9g4zhYH6JmiJIK0GpHCfGlee63AtsyAimXL6OyL6hlZ6yHST43OaLGlyTnVYYea4LWLWHc5xMVhceRWSkECmpMJDNi2cCFBH9Pp6zSYkDjeCC4cAioTNAtOrYfY75bYAX8vp0yqooonP5RiNQlS9s4K4oqkRInLaTtBxL3tqFE0RCsTIEwYbrebnYNgB2QcxlDS6ii7ovF6CoTQEdWGdv2g1TiMbX6pqNTjsLk28UG5PPGgpwR2LY+el+XPKagBD2fUFu/Jz/GZtdaGdl14osCdxE2QmnKxQbpL02i0StDB+ga94DA4b8h/tvoC6OYOatFC2j4/OH1BRNnakLuSUxNuSObMUpeCKkZPKCrELVt1wbe3WkOp5EtB7Xz5ycs+mkStfi/uebpWfcCqzTpxjiMijAhQao19G9xAbeUWVSXu3Rb9la8TI2hrLVitVr5YFUDn/XWtZlyitRGWToMfHh3hy195ANM840Mf+nmcufKqQHsMXwEAqOLMmTMQEVxz9dV497t/AnMp+PznPo+j42M89tjjePLJJy1W1bWuefY37QBkDyuBYL23NhO+TIBYWcYhtcM2zTP1JFSrJRtMk6WgDqNlw2lF9qrt0zyjloI8GAcrYkKE0QzAkqvrEW8ySHE5J6hmfvW8cE4pKnwxTrmPEe3RCmv7ojsgKXnFqskcgwBwtD3Agw8f4ue2wLTKAIhYFXnwbaxeQ1QZOZCNb0VLve2daFzzMLN9vBTawziCDReRMzbbTcxNmHKSsL+/H/NlCDFBKiMKtGcZHN2F7Qoyhuq2bi8YOfekQnrem8i7jcccZL1jNJywnSDuuVw65/i53iFG5Ws0BUtnpqhz0JRqhUqOWq1irvhm+cBKX6oLoEhC8PciC8PPspkkdhQvx6VoKN3GTYUiQU9xv6ojX5O3YkWM6KzqBFhQXKuxdQ4upZUgtaHZ3hEEjdAGzvWU7r1x+TxRUwjrhbQat1QGlLnLtb38Z7vXiRC0IoJTp05FxhUkhYOm70NUq6LqDMxA9f5cWovHehZ84xsP4vxL5/HhX/wQbr7xBkAGoLoGAmzinSIY0oAyT8gqeM9PvhuqFe9+x7twdHyEH/zwh/jc5/8Ulw4PcenSJUOhNlDf0BkpVWw22yi6Elk7g4WMjQMwZg/v6kolrsYRxhMLyjxj8o4GPhGG0qpxcaUWrPIYsbfsWbW/txc1ALLHairjK7vwIVXjePuGeAsT1Z8Jbc6yMFvRkJttUEd6qU9u8Ar9Cnzpawnzdg9/byM4yoBIQk7a6niiKUcRgXYxrLY0xq1XUhNVoVIxrlaYYTHGgwxRV8L2yLwY7/Z4g6Tk0xhGVLG/v2+JJh5PbZ5HBZJlFy5SpquiaAk+PCI9XGHxnAqa00zdzDXg1+qbLpCs26+M5aUw8hs0J6A2J21PFbCVeI+Ke8Er0ooI9cKa69OUlpnlkbTgfGWP7kyYSDiW4px276SUwjAun+g2OcfPcrREhKVqjIUpxwGiHIFTqTFHMebPnzgMCqUCq9oatxKNEsm7Yib1YtwxhXwcNVt3sb3Kwe6uMe/V88u2tv7fROK7k7VznQhBC7T+9ew3xZJ9Wo0ns5AqJ/ooeFWDbGefqSd+8CR+7w8+gze94R7ce8892N/fj5hVu+iUoMZrm/3gigPsH+zj2muvxX33vRlzKXjgKw/g2WefxbPPPYvHHnvMa9EyY4nIo6WBmqmfwExBmsGstWBCNcFiQu1gjKuxHTwXfGxTMukEmXtiSa2SWUpW8EUA8bAs0h4Lz3UX1L8rABaIuHMIRlJCSkgJHmfaedB5QDlcSbh4sSLpBkiK0wcJKc2oxbvcdllfOadAORQsyQu9FJilwI2+bOFSMRf1jMBktSKqIrzUAhwdHccBpeAGgP2DfdROmWAh4Mz0z9Jy9Inc51IW6M03qKMl/w0TF5x/V1VoabHN/KyZo2UxtyEEEjBIV1O3YrGGu5RPTzH0fGlkrbEylzvBFkADjLHtOVXjZWndMJGFglJciFSoC/PUIcCmYLh3VcRis0ltuXDtrSobO4KCIa8aOFsRfbzinAz7gDRBW5UCH22Nus8zFRedMNVqyBfQUDLUErQyaEGHtRdPkFZ7IXQrU4jxqteJEbQ9md9nCCWxOgWq3GgAbTrVismdN5ZKa4VZvvq1r+ORhx/G9WevxUc/+lFce8012NvfWwocz3unYIFSyMNjDw3F/thb7oOI4MLFC7hw4QIOj47x+7//B7h06RIOj46xnSbX2J7I4HzhHCmjra20qnqF/2EZ0F89mH2evaoWmqmcraPsPM/IwxCm8lxa8oECSC6/F55rVeyWSiQqYVph7ymn6Q4wXtONarUsqSZkE1BIOxiiueFsxW03XMLpZ4GrDiagFNRqwp/IwvhECbqBLcNZppKOKRPEDD1jpakS86GwIjzmEDQnXR8WRs7NDoFEIW7bYwpoa/0SQkhaiUHuR4vj9rnz0DOQwuKcovNQV4uEsDrAMOG6Yx30HCujBgCEUKyqgbL5PWCJcncFLhUWoyfCGefWIU3m+E7MMz/rWYLuoFyY2L2EBlyI+Zn1iAx+hIKTzmMtvYKmlUrOvo2Jc8J9YI7hGgLRtTm+/tXv4dx3nsCHATz+7WewPX3WqCg/R+JWjkvtjn5ACNMWNYPYI303RipPVM69osJbMgoi+YccLef6R0nakyNoYeagpOWClGrlA21RmhZRhVdy8kgAKRiG0ZxmkjBX4MmnnsM//tX/Cne+7nb82Fvfgrfc9xYgMWXREYnS6LHA7dDKvnsUAKpif28Pe3t7gCr+zt/+m0g544EHvoonnngCh8cbfPOb33TH0uAeYus3Ng4jtl4y0KpeJe/IwAQHLHjHVW4xxIO3aSnFPN1lZoB5CeTFlFtz5MDrAtBc6k3etrENNfnm9jhdQxzGv5ZaHGUiqBLEnmcYTmrl76Risz3Eu995CukPz2N/VSBakPPaN6B2xagBNgEU5/zgQp/vlXPGdrsBMEQKMcQiDcwBxupnHkepWEQUcLBCbk6rvYuYs4ewKYRYtVA5KjeImLOlizaBj9f2W6eAwrx1072nZ1jRShIs0q+Zl5FfrzXiSGdHcEBzclEQ9UKWAltgzsHgcnc6LFCJaCUvzDTXVjaR6B9gpmKr1EYZx7myMMvZhJkXBa+1og6KDNYCcJQIdNSDgFHVFMICBapHbPC9mDWozQnIuUoCvHSxYrpglu+F8wXzKaDWOagmCJDTEIACjvCrLiMZFsVw/B0D/apRVhAEkBBBOMKgYtmk2tK2BXAaDK94nQxB64hqYvaSML/dDim5WnIo9pWKabKfFU8lnWcrMh0JBmKFVx5+5FF85/Hv4fNf+BL213t4//vfjzNnTmMYB6xX68VQmE3DGgQu2ZuJYjYXtFa89b43421vfQvmUvHud70TFy5ewB/98Z/g+PgY1YPx2SMseWC1tcSRKE5jKb129ygNSc7WNe6Qc2RCsSPB7B1m53myNukuUCMchtraFUdwZ0Rsjp6YRQRxpCpLpNuSJLrDb6PsDnTC8eEIEeO8sigO9hTnjwrMrDdkTU4zyk6C9AC7PwwuiGt09w0vr6+F+kFhXVkXeQtqCNz8sVd8DTneMF07iqU2IRfCR9zM9h5yfhIbgvR1tUPtWU5+34j3VQW8SDWVKa8enWr33z2PzouCOUlCUQ8Z1GVhcL5jj3IhAGoXSSBNQTBrq5n4zTHI/cTV5liCfnHrJg+DC3k4ndAplO690CHIaHg6k9ZSgtBGHThCjZAvCF5z8z6uPTUAXwROX2FqJpI1hEqthZPFfLhzk8qY82XJGW2fNB9Ct298b9gYasx5ZelTLlBYgC9/nQxBC0CFi6ZhHpbihaxl2X2Uh9K+aIKMQqzm5BRCilClNFqkwvefeBIK4OFvPwaB4u7Xvx5veMO9OFivccfr7sAwMERFYhFIxvSHVuhoEROKGYpbbr4Jihtx7+vv8uQEPzjS5fp3BxmgVeZ3loSkwP5+ttYg2kJQynbCPE84PDrCPM947tkXIBCM6wG//vFP4KWXLvgByEiDFeUg+qyORLxWB+vwQMR+YK9XgWKYQ6TFuPbcX2SFAe1dxGkAEWhaodZLxjdmwS23XYkHH2lpv2wgaZYIkbB4hIchqsmtEQpblQoZDDEnsULqpFBs6uZA7RDBwcEeVqsMLXbUeRCGYTBEFRXdtKt6hYj9NKMqGQKGh1Kl6miVjqemrHwLWCEVleApWYtBYU4gLVYdjAoCsFji3vw3YZEwlSn+m5aMhRS2TgkhXBzR2ri6jCZJHZoWVEkUcQBamUIqeUa9QIwG0pA0NKkpAQ3NpZTbHPgz+hoOhrL9/Hl0R8e+tnPsPW2oemopltYbIWbVx23o8Z3vuhP33HoV8M9+D3fcciVWh4LNtglZe+HuXEk3ftARaWeZOW8RxSCsw4AovEPFwXOC+Cas27SHCSa9PDV69zoZgtbOrB0idwrRo8xYTZpqimU5PTMbbPHmebKc9lwxbZtJZ/8vWK1GmxytWK9WePjhh/HII4/giisOcPPNr8EgwDve+Q7cdPNNqLVgf70XKZdxhWC0v1hJvi2GCyHuHl0iFf5s5x9Qtbbeogkp4q7tfYdhwHocccX+AUSAQUacO/cCbjp7Az7yoV/Ax///7f1ptG3JcR6IfZG59znnvqnmeUAVUAWgMBEkiFFqNieQAMRBFCmxZVmUJa6WB9lqecmDtNrLbS//UXt5dVs9t2ypJbbEpiSKBAGSIATOAkAAJEgMhQIKqHl+r4Y333vP2Tsz/CPii8xzX70CJbNQD+TbtV7d6Zyz986dGfnFFxFffPRf44XTZzHPzY20RU90IuHmM89UYydv1AIDekQe5DUZJGLmR5Y++8CucZoVVRaGaCE4cnhE1cl3eq+rTy3n8yBas4Bi6+9l12OFBotFBjRFwLTM3rwxKBD7rOuuuxY7y0XbHH1xPHv8GYBBqJxRywwKV2ttWQc55zBCvN+E7b5d8dzUyIlSZ0hpBQM9lcOgGsV0BHSPWeopkYnQo9se/RJdRxEPcSapoOJ53aG1a1kTEcDyYoaG/E0oqML4+FrUK9CaKFJDs1yc7fvWZrxRef1BjQzGCOwWm0YvoOEx9gjckCeDbJ2X4mtfRDCkBEmWwifsztDNowjkopVKx9qEvd/sd6U5QVsF3EvaPcLRtv1orzjIsRet1nqnfDMYWiAmOnMNiUr7oAD5QQa96L5ykhdHK7VWZLZO1taaZp5nDOPQqrvctTl7fhdffeAB6Dzjvvu/CtWK66+/Dt/+trdhzAlvuOee7dxGiYt2g0Wr1RlbOIfV+yZbN3zBN8YX0SdV10hFxzX6JycRDOOIndUKd9x2K/7cD/0gPvTLH8WJ516IDcqu1a4xSQvCVG2LX7zmXz3daZ5m57Jsstv4My80WcGIz8haqU9AofCENB4DRJBUMI4TtFYUtKaKfE5smWKeiWm+MsLbZyRYi53sAbEmSJJSQk4DoAWSJQJYy3Ewb0M5bmYwzp09befzQWF/L8RnKio7CvQuobZNqHf5oeoVZAjub/Z81kYxAXlIVgXnKLl2aDT+KxrzO1KyMnUnaDQQRonXFM+Ez9qNEYO4fI2IbUw0tnGOaBmuVptaWyWb+rrqI/o2afxaKZbta5Zon5OORjaMq7vupFViHaVOt9YDwlHe3q0ZGsuUAA34Szu+TfcwOBmGHs0oKjNGpN0Tja0REZ5B4M8YkEZz1LZ5mx3yTjDVaCUGpi92XCKG1nbHacNmgIhMA9alM3puu42R8oT4hZUqbliRTJi5SMXopZost61asV6vA0WUUrFYjMYH5Ww7fsp45sRz+PAvfQRDEnzlqw9guVjgnntej1fdfjsWCw6bo1QaWfvif/HJ6RTA1qHA1oshzht6kIM9m4JiaG6aOsJYLEyGcb0puPH66/DDP/A+/PyHfwkvnDzNj7SFltM2gizq0oBMbvduBZ4tYQvSZ3PQBs6VkutStsBprixUcObMAhUJpSac32OmBdGXI2B3JwF7tuvNxtC2iG+wfbpS44ctEnwgGR/wyif7/Wq1EygEsO6qkbng7i38d+qBqyTwPFDnEVPC7Jx/cQ+g8FGioU+ud8sQso0xkqKEojV2P5EmHW2D2jxQaVx3r+4VNKcjUAMcnN9tU6pakVViDLI/15RamhL8/bHRxXVozDOBZ04QIByEqqQzXPzdPB5p9wGEKNLBoyHLdkRxB9RlDmU7jcqNn4bBdGQvTTgoNgLhu/g9KTHOFwSoUr5SWQUGeKTSMnd83cBBHcILtGdaqv3MMZzn4hKjFwFUflwShtZuTDEuxiCjraeQGdbiDQStUSB5PkM6ySkHW5D23jIZt7UYFh5RTw0pu4vKNI1hyC6L6O/t8k4BYJoVX/jSfRiHAV/6yv0Yc8Zb3/IW3HrbrbjzjtusvNPRTZubtvAAB6f9fAAOoN+wuuDU4cKjXF3s2jBXHR5cshYvxsfddMP1+PEf/RH8i5/9eTx/6nRbvGqShqEj67tvgkeMi1V32eR2vVhlGp2Phxvgpp7X7tfQwgzUip/+2V2899mCUycF9w4bQF2vIloGJZTZpCizB/h60RGjDTyp3hGtwFKyKBnJAgiFle+Oi4VdrwKHDh0y3VpfQBzv06fPxEKIoJqneU0dlUJUTYrBChsEXGQIxK2B3GgYJSWEnAOfqCDE59EjSPEsm8RNQ7ZQoWkm+/PyBzGMo53fJxMBCGqXmufXHcEtPw/7s8UGFXngdm82310dzVFziGZL3E281yYuC0L8VLYL+dinRo/64NrcdVRNI++lweKfm3L27ikNTROvQ4HHHzuJaT1CBTh3ZkYdpaMAtq4SgHYCTc1Qtj/z88mvYWsTD8cySrp9fP3ac7Lio8LgmW4NxwXHJWFoxTkj1BK6sev1BqP3f8pDjoTzlJoLSkUn4ECdeCe2wr5jbKpXVaN7rSFmBiUsJ9BcMBdITq1raq2KabbCg09+5neRf++zuOP2W3H0yGF827e+Fddec7W5syTXudI44bZ29d4v8kmogEhFqVbMYM+OE6N7p9pCnKcJUHgwChAkXHv11fgLP/pn8bMf/BCef+G0LbTBlbOyZWLMk7feVsFizCjJ8o/Pn9sNIZNaK1arRZe/XJtMpO/2YzKzUmvFNM1ISXB+P0FqwoyMqgNyEsyb/S2X2VDewrNLBHu7u9EjTt2gLpcrb7CpyMlTvLRgM01YwFXdUsb+XgGctx1SwnJcxgZjKMnGb38zYb2Zcfjwwp5BVVRHmo0FauLe1VN1jBrwOdVlYiiogUq+sS1Q9tsyF90XYRbUarRH1WobljTqga9PyVE3rVRVFJRAVtR4MLedwZ3Ge9OocF4Tv8XakG4TV3X3m8jfUsDgHkf26+HkNFSqvhEiNppai6enNR0A8VQ2AT0KliZXpCHDKqZzXGuFZ7/MJrNoT4XFFxXq1Zef+vQjGEbB31bgxDPnoLdd5Rt+dU4WMUbE69O0AdRVulLCmDOyp5GyW65y8wTtR8vLtv24dvMA8PgvluOIgSlkX8fSXhKGFhAMEGx0u4QweZTZ2m1nn6g2mQbnXTebjcF337l3Vjs2R4sF1tYuzCICLJcrFJccHFLGYrmK3W6aNsbd1uJ11wWoFdOmrcbVcgWRhCFnnDl7Bg889DAW4wIPPfIYzp07h3EYcc01Vzm6yHjhhResa+4wQJ13NtSRcOjQDsZxgdViiaqKzWaD1XLEjTdejyuOXYGrr7ka42D8ZS1zLHqtpolwaGeF3b09i0ZnM7SqgiOHD+NH/+wP4qf+6T/HmfO7SNVQ6t7uJnZxcnFLDJ70bwuJ9fNJzDizw4SqYprm6Fw6DBQ3keDKmWCeAcxekpzyYF0YSmvUKCIu2YjY9EppjTCXyxUAljknTJspDMNyaXKH81QgUqO0GGAubLWqOTQeDb7QV8tlSGCqC9Mkvw8aBBrTpt3ri/dAsIo5lH2Qk4ZWgOAvaeiNYmH9v+VrKzi+yXOZNSoNEzlFIm/SQI4yaQB7LpdfRTxAG9xt29Z77pSoX704xGxsi+CuViucPPmCUW7+QbUWnD59GtPU0XB7+1gtVwZioDHGyfOfaXpYVFRVI8Lf+uf5+LN6q6MtWNSiUNQyoVSgikBrwTRZCfw4Dpj8s7Rs9wFjGiWvdy4Au5gQjLG8GWJl8SLWqTml7Z5rKSWcPn0aTz/9NFIyj9vTi1Dn0qVlXnhcEoZWRHDtNTdgLhPK7BfO8seOr6qlhLvJHXUxjq72L6GiVGvFsDJZxXGRodrV5Y+mgWqcraVppGS9wAAgFQZ3bGhatH1GqTNQBRUFh1euI4uK/f1dQ3+14OTJF7aoGmt2yCoxosOKU6dORTSaE16geOzJJ5ooh6e51FKs2sg3np2dHdx4/fV4//d9F44eWcH4+Bat/ezv34thsYNydtdcYK3IWaK6yO7LhF8sIJWwc2iFlAS7u7tWzjyYchaNzzh6Rwe1gEXKGTqXSIa3CZ2Q1JJ51psN6qDuBgLTeuMtfIwyKOt1aOkKBPt7+xAklLIf454yMIzZNlI3PrWYERnGATsrQ8br/TXe9tY348iRHUxldmPHOaN47/d+J/LyCJaHj2GLC+X8c0eVKJABw+bySsxTQYv826HtU8jtBXI0usECfimMHt1zvlciSCNb813QjOhWHkDwNiCfFJuoAlsLvp2zbT4MCBlKbTm2Lf0QOHv2DDZnT+L8dB7jaM9tmie8+bV34u7bb8bvff4LOH78WVDRbjNtwtsUSaE8N3jKJjV+zXDmMH4MeEamhsINco0sGABYr9cYh4y5TKhQTPtrnDlz2gDKavb+C5MAAIRfSURBVOUgxESC5nnGgtknAHZ3JwzjiHkuKHPBzs4qPA/qhVTnlzebTXQkydnm+WazwXK5xGa9xvr8aeyffq6jXoyCeuKJp83LvMhxiRhaYLFYIteEMngKzMiulBpzeRZBcs6VCceqVo4pjkKTpwilJKaqBaseY8WIIVZTeycvuHC9Uioh5ZyjSonVNqVUMz6w3QvZhD643eduBzX0reF+WOQV4XaZHsLC7sm1a01cnBKAhgQyc0+HBHbJTclQ3VNPH8ehnUM4emQH1jGgJYc//PBjOPHsc5CUME0ljOng+rfzRM1Z6s/S6zHdhSQSxRHDOGLI2TUKSrhH02aDBMEiD5DBcn/39/eRVOENb02PVLXpPbgRNIOv2NlZRT60TpMvQg8yTBN2huxI3opRlIEIESxXg0XLxXItv/yV+/Cud3wbrr36KnsmYu1rtCre+pY3og47GHauDO3Ydmh81QN/6WxofBP5oEHlNXqHpu5iHuR2JL/7fD87uXueS8mF8rfavdtd5Z6L7l9DuUcc+FucK37evlhuQE8+8QSuPJRx5bEjEBGMiwVKKdjccB2Ov/A8fu23f9uAzDAGv6xasdlMfu32WWyhJM710ku1zY7FRYyRpHjPYjGilJbK2fRKkmXl1tYNYbPZbHkBItbWiGtvmjZYLhZGkfjcgiC8MZufs3mOMMBjwKmiltn0DUqBloqbb7wWr7vrVdGIE2J2an1+d2vzPnhcGobWZ0v1Hak6Vwigm9Dq5D7FhGu4SERdgHNtmjwWxTJSN2TVshAgZgSq2uCVOseVsBHirBWi4hHFVpOfJWHysrxaK2bfkVVdDUkSch4x1w0U8CCc90JTc7GrJ8EbjSvxvmHoAiwwtDvXDVRhyF2B5BzWer0fi01B0t55OL820ZYug+QRXt88tBZMdYJ6mxqIld6a+DgXSG6i1sAWrQM45wqbRFqNS7eE9xZ8jA0wAXDdgGEYPNhjJZSSEhbLBURbK5vBdR2qmiTgOHqOZMJWl9WqFWlIWM8VH/7Iv8b73/s9uO2Wm2D5ohkzbHPjovLHjEae9841Z2PjXCVep+3lcNpc23sO/r//zMaWOhUT16EHX9q9/yJHbxvlxV/N67hgn+hOZdd08XNJEuQhxZs3brieP3kSv/KxX8Pu3h6ABJW5Kb+lJky02UxbCLkFPBNE1DUJFOv1GuzLlrNN3llbQ8r+M7QKxLM7tCjW68n0c2s13edEbQm/Oze+wzh6ENF0ctXvfJ5nJBFsXOgf/vrJf8/cXvF7ywOROCkXN/bM/qCS1Iscl4ShBfrqKf/Z0SwDBdZCw/pEMXUFzo1VXzgKMyyWv2kHH36ZSwxiTsmiv1UxjNYgkM0HqS8AmCtZdca0saj9KIPpS0VeaI1W02wsKTIgza7L2blE5NXorpVq7bGHPGAYG01hY2ALEsps0BqbELxqbLVaIWWnUJCoHWJGK7r/0mhU1AqP2GfrsJsTqs4ROCmlYBxGK31WBmpcD9e9WvLmQBMAMT5OcMuxDW64YcYVT1mzxjx4a3d3oVMeI98V6NFXGyMEgLNWKuKvqVp9HrSx6QsvKhTjMOCpZ07gn/3zf4G/9B/8Bdx0/fV+HsViucLcC5R0BmbLXr6kwZMXf4lnJfjF+ue9CGaOgCaRZrOYkStNI95xvltnl66+S2T7CrX9PvhXImTSC90FBY7XRhlsnU8sEMwUvVoKTp06hQ9/5Ffw5PFnsVzuRBA0O9pkp4aDzSzRnYsINzO/GLYJRvNQtdZDEHRG1oNwQ0UaB1QBFoNgtRhD/wLJS/GFQTqv3HKaptSCuRQsRq+qywMGkcgaUAWWy2Xj6mnkpWkBJ+k8GpCbt5+qluDYX+y4+F++gYeicVE0rCyfJWosPT97cNIr3XKJYBMHiOgQQHyuubElztU/UOvW6SpbwxCtZwwVV9OPLS2AwtbhLSlfAhnWatoLgpa0n3OOYgrqOsyz35+LzVC8OflEZxBKoa0wI8oD7ZBuYvagahgHR4RGCTAAUTxgVWpx/QQ2nDzQnVWsYoxtfHivoTolwHJR8afeU/Bnvg9Y5ALkipSasWZkPcTY5cC4Vyu13mqMJwK2iidXDGl8IrlA8oIAMI4ZKhk/96FfwhNPPmkeRcpmrCM7AGgDt23QpFtIW+aYtpRjvGWXuqWnXlxw4H0xUCBefmnUSu9t65l2D7ZWffE3HjguuFReJLaNeZ8KeBAFM1Xs3Llz+Niv/RqefeE0tNSg56IVj6+10JSO02l4ifRUOBcYT+l1dWuxlkVMm+PmPqSEIY+47WZBGgS3Xp9x1RVrUABnmiZUz1rqj36e5aFrJKCsRNOYX5PzyuyvZz3sHNn65x1scgonG6i3crHjkkG0IkCpiF1CFd7qpKJJlhnyHXzwmLrFZogAIN6PigpRLICAeiVNEmgBarHXlgJIyo2SqBasGgDYmAqGYRF/Uy1RgWYG2SZcggWYqrD3lAXhplqM88lipZFJnO80l0ZgPC0HYZ5n+ultbLz6Jkmy5Hqp0YuMpZYtMRsxNgCgtfgYebqO2JiMaUAVF20WiaaRxpm5RJ27/VyIs/PWCDETO8f58xPOnj6LMh+GFKAuC0oViHq/MrTFTERPpFpLk8aMfMdakDwHV4DIBOGWaZKNCVqb2ExBQU5GReztb/AvP/hh/MgP/QBuvfFGTNOM4y+cwAvn97GzWjWDn5ha1bwOYWtzH0++jidnJgaRUywuJWfXTeotwyVbX42R0PZ+AQSsxdfub9vIiX+L7SCMpaFki60yz5mfYa8rPr4iTa1KQQbDsgFYhnb6zClceegaaAX29vfx67/9cTz8xHFMc0FVQZlmKztNKS4jujugxT/a+m5gg5KQRSkw1NC3ZKMOc87WtihxM7ZTver6U8ij4uZr93HlsI+TZ66DgjKbjTLIVJxDM445ZSg6zQPtpEopfembE7NkmoqeYszZQFxtzwMxw1968/y6hlZE/hGAHwBwQlXf5L+7GsA/B3AHgEcA/AVVPSm2dfx9AB8AsAvgf6Gqv//1zgEcFGVg6WArp4zUmm4HjIepiAVrWp4ulpEtbabU4jKMxvGOw4DJdSv782ZP/g/D4mksKRuqkq6pINGgFInKELM73D0dhfp12Y5bXXLPXN+csufPSrj687S5AIVVcnmcpClhFsU0V0tr8UUvkpC80AMiXraaOilIiQnJe+Bk0qqQIUWgCpI8f1FRvcyUCduSjD+lAIwJl+yYUHNVLBYWeINKTGbjwFrr9Ih4A9FBgobMEKo0ARxgy6hF+o6a4VIxKNnzbLv7a/zCL30E3/+93407b78dDz/8MH7n9z8X5xS0dChejxn8vLUIzSjn0CjwAjWAiB6u4auN0lAlGtVA4cKmki4qE66+AvAIeLsWBtgULYe1F81uil9N+Z9IzcWQKlFqBXt8Vd8Ikgx+XfZZiSXfCigqILaufuLHfxSr5Yjf+sTv4Etfvh9Hr7gC++tNo3p4/SKAqFNuFxocrl1y9i0nueEJ99JjnjELg+p3LJEW2JhInUFhpIPIn6mH4PP08eklKTmXerpO3QbwOZXZgEISwXRAH7jfY7fdnxc//jCI9h8D+K8A/FT3u78D4NdU9e+JyN/xn//PAN4P4G7/904A/61//UMcjlJQABe7kJQtfciVkUotYYDC7UGXbuSum3igLCUEEiq1IKch0n9aOgkLIZJX0LSdd55L1D9XrZHTmyRBxdplp5SsqaCIlxkY4g0lMsmQPDi1oS4qbgclGQsqBkkmu5czJGfMpfjOPiBV2zys+R5iQe3urTF6+3UbP0Hd3TfXp7beVywXZNXXXGaU2lqr2z33br3v6MyFFFhq2dQ6Bxgf5u2uRVGUnYyBxU6KTUqVHJvnKXq0OJ5ftfey+66qbbBU0arVczM9OGcGXpFzzwB4SpajkurFBy+cOouf/eCH8L7v/36cPHvO54stQnpMRtU02qp3e4nYWezSGleqQSzfv2ph/zV/PeACP4jc0DpZatwsjfIStD5aQgOrTRAFoNoa54y9jolivJSe+hJusqUA2sYCZIJFoNnT9GCFFAUA1IJIZpRt85jnCb/3uc/jiaefQVHF+d1da7EED1azlFcbYqWO7UFulmu2D1xnyjQK9ZctqEx3nhVt4s8i8oBFIEqdBPe6RMPzJYAwzwShqUCaI+VGD7DDcmKmkTBY2QUTfXyZqdPyOZK5A2oVgy9F6HxdQ6uqvy0idxz49Q8D+E7//p8A+E2Yof1hAD+lNpKfEpErReQmVX36650nHo42DiqCOSCPIs7hILpUJlhgqxTXME0JtUzOj0oY1Cat50iF0UR0E9VeAIWljOWhiUWE0LJWl0HU4E7Z3qQUVp/VQGki1p8MqpA8ICVpTRgZmU/JZNvcGJkkYcbgu/80GXdaQ75QA8H3LozGBLdJEo0dpR9LNN7XX5+SFWxEYrcHGkmRGN3Sa9q2iWyIXyDDESjOIlXFsErIxXmvefZMCbhWbQKz9iCAJvXraJ8XEpiSAtWSGy6F5acWvfY/Wt26Gw8aGwiw3sz40C/+MhbLHRw6fDgCNkTbKq3On/ODBtgnoVEIuSsqcA+G90DKlOmGpiUhcc904elWm22yiiyIxxeACPhyg7KvtkEnNBRYtEvKJ43j6wTuYagkL6pIEFZgkSJQAKhePde3KW8usFbgdz/7OTzw4EOYfaOxasR2HVB08pG1ccfCa99GjaQHei+ShpabrG2mpeNWFdbmfkbwyAmQKphmpvvZXGCZ+RZlkZJxknyk4l5ptfVW6Cm7XYlimo4y49xYLpe45dZbYnNBb3I9YH+x49+Vo72hM57PALjBv78FwOPd657w311gaEXkrwP46wCawXK3ADhA1MPdiu57uhelFjJaiF5HdG26nR5o9eFzrU13UyQW8WZj5XqUZuQOLO6GG+lvn0VKIrvARvQf8kkf0nuS22sdNSZJkNwZ+Fp9MlthQHEjmoOGyNDqkd1SvF5ewl3pPRjEjgzXJW1q+hwLcTczhI9dR2CeC3LWQL55MO2BmPQH0IICzpMr1pslgHOQApRBgOIC3Z6DzM2Neq503dkwkKI/IglaEHKD1GJl4IQeyDiMgSglNaUr0gBtYJKnASZsNhOGMXvRA4KSMvFuT7lLrd8UgyAcQyVDYLMs5iz1Jji+lYu3mzNRzSrEYf5/AWgXRLLNHWbWAEb7aGtzIzaRbQ4eKLywecn2NM0lTmJFIln7qjGJzcaG0f8vBl/movjqg48acE/J06LseRRH71UrBhlCvpLt2QUtDTDoLxZedMJADX1udwwm6uU6ZhaQwgGGP/ecWrWewjbDXL0Kzb0+Br3E1xmfTcQLxOieIQ9Yr9dYLpcB4kLxb2hSAEePHo3nhm6a2bx+GSvDVFUloMW/1fv+AYB/AACr1VJJ8ld3LasjM5PzM1dNueGKQDI5RG+ipwr1gI+k5AsVka1At6ZPu+oTnAHEa5JITB4KdZRaA+lw9zP0XZvb5A3psoxQWA8waEWZNm6oC2o1NCVi3QSMYaD4y+T8siFHGfwhavU0NbEc/SSYZxrbzkXjJgPE5kC0RoeHm5O4SwoxPrlurLLH0IDX5Is4Z+nurEPRQEQ5Yz1NSCnhoUcmADv48xNw4syAOkxIeWloXLwW3EtxpTOGSUxPQeBK/ZLAJHAuVJvXEgJBTbrOJvaAoS1mGh7n6QzF2GtHiOXyhrFrOcQAtXaTt0GvnbFV5+o8aqON4+bIN+7OKCQG8ohMze5RL5glugYzmdbElubZXWly7Jakr6C17kGAzWE0dO+GQ3ws+czDiUieDkjvyOkZiGs/iH2WDUmFioZguwnyC7Ibr0j16zdxacEwGh9uzKVYtRc3VaJYIsQLSp2d/spDwjxPBo488KVQqAe3SXeowkvKGVj16eDPONmOHOsVQAji50GQ5xz3wo2bqHocjDLMaYm99ezzwG2WWoAw9t4XOf5dDe1xUgIichOAE/77JwHc1r3uVv/d1z2IVKoL+nLAKGThM90QY0oh0aZdUjzQDB/gSKRSdclV3t2t6StU2oRtsoAg+Q0Eh9e3cgl+19WmrEld08IFWmpK7QyUlSYONpnFwEmi68sS1dkWeaA/sbxURrVtMjAxGxFk43Uxl5gerqHs3jXPkYYW4hqO7qklAXeniBZExA2BuHtrz210fYgnnxE8eXyBoSqOv1CBG8cI3IFGUAzR1FqtQWWdbXGjdd4l6giVe2iguVorkICkrJu35zKjSWYav2eGZHa0rP4saPm2nGQx1DhIBrLG9ZELFfvGxp7XKObicuzmUjx7g+uPMoVwqqAZH14P12TLvdRmQHwRMyiovqf26JVBTAGNOGJuwluF1+odC9QoEm8rG+MEILQUupVoyFr6n/2cIr5PtTc0z3P793FP3SGCLQ6c90GDxc/qkWGtFeJCS6gV9z0wIp3dxX3PAE8fWW6dIcZdWwsmiQ3Zg6Yd9UWPjM8sAsSeB0yFOXq59rwyppnByhasv1ALdfv4d82j/RCAv+Lf/xUAv9D9/ifEjncBOP2H5WdrIfcJEluGANVbR7gbUNWSnukCRCRctoNb4Ro4ut1CsY4ihmHAQF63c8MsPcTzRf2B9MZcckIeB7C9C6CYq/U8CxfXHyY/P+cBkgZUTa5pCUzTjLkApUoEn1JqOauCAaqCeQbKpPa1WlpMawmdYQIX8K4K6oUM1h02DwnjYnSdVaNZ5nm2AJ5THPQQwhj65sy8WbYW4qKvaqlec7Ec3DJV1JJwKJ8BAFx1rWDMa+d4EQgG4GLIYSQoGBJIgh4GaRFV56ibn8bqNume+1zmWKBzKZgr5w5Fc5xrJ9oq289bxNWxkv2r3fwx49ioJvJ9gYgVsallCIacXMQd8fztPLaRpmT6u4rWWNKkBROStzk09Oz32wYDLPk1Wio1mUnfEPmvehk31JWr3KCapirzvGu0WqpaUVECeddasNlMmKYSm9w8m96HomlPNHoAB8ZT4nt6flyTLDe3r/MFFB+/ZzfkMqsFumrC+XOHcKgCj+ytsDcdhWBAkgFZFshpDCnVPrsBMM92nm2NGtWnKGUT9kWS5YtXeMCdXD6Mm4V6f7uEoDe55hSMa1zcxP1h0rv+JwDfCeBaEXkCwH8C4O8B+Bci8pMAHgXwF/zlvwxL7XoAlt71V7/e57cT+f/c9SHX1nNaNKSxI9VGL6QD3EvP8RBZMnPBXG8XH4kMg7aY53k21y8hdA+CiO933SgsyNDSoWNtlMTs78vZylPh+qm8diK5UuYotLANpEVfxV38UnhdDIoBzFehi+igJbQXoqoluGZEIUStUyRrl9l4TwbNjJ+1TQnFOKgmF2e7f+SGJkHGBj/wHTPwWeDO1wC3Y4EHHzMDxjS74OLcOyFf2Hd8ZUCUtoVNOvm6fgFHgK9zo83D3m6/w9c3bwBgxDiFUWjpYQKWTtegDIYItBitUzzAUqvzl6oMQAcoGPJgRq559YFOc7acTvQUSdy2UUKWbujxAggiPQ6+YYlncVQiubgL3w/a/AJg2TNV4zXNrbcMj+w7CMWZ5rmg1gmL5dgtU/W52ITEewqhN7K8TkkCnVt2D6kOIkkJ2oKiUBYAIy0yjiPmaYOUM65x+H7Kr7tt4I1S2ZpL4OcqxlGg6htERqDd2o1hKa3TA2nEtQvN9G3mD1rVNqovfvxhsg7+4kX+9D0v8loF8De+3mde9BC6TIKURqi2AEh3jrYzesSTbTn6oM3cTQS6YkBz/xlkgyckh1Qa0PJK0VzfnK2FXXSqVTN00zxj4S6ydbhNYbTFFwI/d6psw5IgQ0KaUyABcS6OgaO+fNfUn+C5rvb6cVigu61AnK3Kaxt1sEY7J/HoLPMvXRbQUQfHsswFefBeVJWcnU2yPAygAHYC05EG3HjNIXsOi4prj2U8/AQs7csXjFEFHnSqiKwMTvbYZA/M2IMbbO+dxCbqfw/Doo7qfDGWWrF0b4GdB1QROsiJ9ycS7nxTj2qbtlFJbqiMlwnaJZnlRRYLkLKjA4tkQEytzqMSDRN9xtkUwLZkoAb9bJuXornKpIWCC+eMUMT8tUCwfUjRNqYBHGavovNCFdMGdo1atfxmE9svYdTYPLKBhdZEtfdiWPnY+Fc+V9MiCVEZuz1QfIkZBRZIHTAOBe9/bQYeBfTqEUkrit0MGIAGGn3IDZiPlkY/JaNshnG0hp+qsQlP04xxaBwvaQS2vHf+6eAEjbVxseOSKMF1uIo0eMDHEQYHjKiRi4y11P2/rY9zY8aj1hbY4OAHN+QTar1ebyVUc5IXb4PTqwgF+Q9bFHMp8XfAdmC63XFN0oot+Hoi15wHDMPC+2AhSgTLXLZEyiUJUkbrQxVX0b4z0fIU9eIGhCwnknxS9UwN3mNEyj3IBEdc8AXZI05mANjcaq5ZEsH+OW/dvpMhso4caBoTlhibQRW0BlBtDvQopf3aN5xOtpHUT59wzmfTUwv0Ggwl5eADGTSkNwAPHG2PZTO69LZIh7DAROFoX63yik9DVNrnOcq2+kGJ8TKFLQ0vhufIeeg6HDCfk+2DbDxzso7H1iLeqA2jHkhb8Dxe/gxxKs5zRdXT1vjXOA+LBbar4HifXE8ANwFBv/wOIkv7vhl2eiA0WA1xt2wZ8uTNExATqh8q3nP4PADg1j8N3HDdCIt1NA+yX3P9tdrfAKAE/UK7AI4BeXxOAHQbErjBajOsEu9kwvNFj0umBBcCaHF3Ag2pHcy56yOcQx4ws8VJh3DU/bM+TaSfHPbAicy2K82oeStOSdTq9ddqQReS5L06Fd/bq1WF/i2wZQAAN7rFIrpKF9izJWoSV5l3o6hsZzzHBLXJ1c3u7hkPwwAkwXrjfdFg6GJwF7Rqc9/MTXRvoKNeOF55sFQoeLaGbQKWaG6pYC7YUwtqrnjofuNoZwjKvIGISdNR31NGGl3vwFpbZNoS9w09EyVHgM4bafacm7Umly1kexCl2XNoWsThSnLI+qBqL3jT0U4iltBPgWky4+AcShakoZiLRfKlGU9tc8m4WA+IEXWhUR3cX2L+wte7AOob3jAMmOYNxCmKYNwggbDB5+hgIoybWMCUGsg5WfoeQC7aZh0pmTJ7zzPPgKjgpmLZEMkrBs0F3wY8NHqs0lTQAyBXW6GQAE0MYqWUgs5jRg2DoKITrnnmHOYBOHFlxWY2Hp6FPP1mS7ogSnhjID0elBv4SS7juUiLkH203PIJO4d2rGUUhkC9Ddw4ulXv6IGLH5eOoVWASehtsbQUD6BbAEAQ2KlLdI+a5k7dveXoIgh9aJddAObd+S6n7CW2jUh795Qcoohsff7WawBoanmEPTLk+YxvMy3MnDOS75zJDUOZrX4/rqtUWK6lQlLrdro1iP6PVV2qFWMe4i8pjYDYxCgq/pk23n27d9579mBY7YoMBOZGxkSVAagVp5+3lLjnd4/ikec3MLxWnOursRiTeNWdFiiS1+Dz+dudEJWZkcrBuXIe9Gr8Pfo++MwAGuiKMs9uLMmEOjpRREYFoGHoSq0eFB2QsjYkC1+4jkqpFVzhBfmKmH/xmYAHGYmA/F6d/lGYUX6xpxnzV6urTZkB7XtiEZeZ4QY0NSTWvA+7nJTNeFrwS9vJDpiKcdGZh9h4LOMCklBQLggiM6OkBaRtjpPDLI6WbS7a5pCxDZLE0TTbWqkCKjNuvmmBax6peOGGhOdPTTh1amNzz+dZ20YRn8NrIw0U68Kpqj6QznWbs4S2gWrBMLJTc4p4jHHmzp0D8fVix6VhaLUFWwxBGoLibkiXRWuFdlUfTHE5iEBoUBWNt93K+ROT/0v+EKKShGiuM9pcyFscVGoFCYtxDBUgolvu0j1XC21BMV4HX1enlohPEQv1axYGHFSRBv+5VBP0OPBse+4r54y5eidZ55hSSphKsfY3/rl2b54WlQcrMKjFgzUsxECMhU36EonnVvRQIEh47pkdAMBvf3YfJ644DEbyTSuh6XVGbq8CVY2bDjQk1g6nsFC5ozf6QKRKl3+K9vy5WPsAWa0pov1VmbSPpmvheaT2XHLwc3Yu29Ts0sxdZH8zGsrITAGrtdQQnxv/wvxhkKZAIHvQZa2dGps0N1WlUSeMSyQHGzY3LM2P92ABz/5+jFLgOlKncfgcEAXh4s+lxn0ulwuwfT1nAZXjJLHdS6cF3VELvSfKzBYGE6OrSGwyrUSXniLTzmKOIuOuOxa4/uMFD3zLCjMOQXXgFhZ0FtdQe3411pnRT8liJZnFM61zb5mLSzZOxj2r8e0kfPq1cAHK8Q3kYselYWjFHn6kgKBlDWxRB7iwGqafhMC220e3X2G8KV9vaTwNHQU3SxcTjbI4iEhjQngttm0Qc/BP5DCpscnrUWCLx80pxSKkJGC81lHxXBqyjqAP1CK0KW09Z7sXG6XINMj+ekaqjYoM6iFn4+1SzjahnKNNiQ0dLbOjepscaEN7RP3Zq45EBINT/pMwt97QbhIgjWOkFEG86V2IzrQAi2pF6Xi80GsIjg9bz8Wmj30NzYpCLhhuKBDubRb1tDwbL7ZF0hhDR4dxzgqo8/l8nQu/GwjUWHDZUWMWa3HkjrKlGEaVkplbajL4B9o9OlXVZQ91nGHz5kq1DSxLq7VHQuR705YjPrq6wTaPsZbmurME1TxK3fIizGAaVVVKKxjiuBE0RJ7qFufKy9atn7fXr3PbUCCyJhDjljznuNaKnEa84dQZLNbAo3cN2NuMSMnWmHkRglqsyq534m3js+Ba1QIBQVNbo4uUUHz9c9MexhHr/f3wloAWhL1g3QG+sV3c0l4ahtYPX8s+weny2NbBdK6WvtKMcO1QYO/G9AebtDE3NqluoWEGp6LcrkPOB417k2Dz8tBI/6qoc4169WgG6OcaxzHOVUpBcsOQ8xDIjYcAKH4/IYAxju76eTaA3Sj4hWNGns26AOfgsg3dK9iBle4VDV1KnoLjBQmmXqTOgdVw5eICuQH5zxsfs9uOAO9+2wq7+4LP3TtZ5UzRQI+Wh8mMkD6wQsRPvq4htJ7vFh+nuBZHRZH+1VE7/TwYPKUqeeVQpMQpQsNAtelgqF+XumcVm5tq9C5TtI0XQEsXk2yltJK8/DVHxgXneq/lap+lDSgl24iiE60bpaTMCxG/x2QUAHzzddoiko2UmM+HhUgcVurLIKCTDDHOIgm7u+cBBQ4fXsXz4UFgxDgA/DN7UNCyfois45Lc0LX0MFKEpRZvOukbYLj4u3jz185gHoBH7xxw30d2UcoRL3zpVboShrEFMK2lORkigiXtvKu+FNztSrFu0aUU7O/v2/yv1rePi000QncAALajv9hxyRja4H9yaosxeXTUuT0loeVHH+Cau8BU75b3FACrjni+Pi+Tr6HxHXJu2QvSUlbshTCDJy3yzPcDwFznMJwHeUP+HMn1XTliGwcJ1Sxukmy3Xl1ekX3OaCwBGhUGKRCG3trtONJDdS0HM058rVur+DnyI/VApY5Wd6+bcaxqAiWPJ0ER4HtuUdz87x3GM8/N+MK9E6xNj7t16lV5E42sxOdwAXITUGV3DZaiIjyH3us56M2oQ6Och5g7gCMWrVspUJx3pDIkp21dgS2k4ud07QFu+30bdvA9HVK0CjPEXBE0g0wPgfdFT6u6J0GJS/ENRt1FTWhJ8iFO3X/l/TG7pls3qna/udtwYGwHmPYmIiZk46PVPMe6BUxII8Qa0y5G4WOzveEZQmZGA70NBlgXi7EDS4hz33DlgLd8ecKjr1tgM2acOpWAnCyzpZsbDKqRppjnSjfO16tlNtHgpm59W466j520eI26aJVP+rYZ6oUMwsWOS8LQ2o6XoOoLmzJs8AciOfg0AaI6DEAsxH6xAQjk2rviDCiVUrYT4VOCLBaBeidvFJh9wtLN7z+vlALJVlIvIsjj2M7jO2SfzM3Jx9Sv/rUAtl4fgShXplfVKAfVuVoQK2+7ZHbYz6yS4mcvFgvMxdrmCDKgyTcSxf56jaXfO11ZnnOebMMw1FCDGlGFeweGZpg2lRcLPHTFCtc/cBZfyTMOHypYLTaY12xcWfzZFcyFgRJf+O5+DkNG3wtOxIonDEC3Bdtzb8z5jfmgfeaEjbX1KRNo9XxXaQZYkkBq7WijLpDSUxZKJtN/QNs4w++l0RZ69Y3uoGFS9785B+K+RADXKcghfNs2w8gqcJc/EZGjc5c7K0Cj6avMKIk4j2dlmI4gmKirgmjnLUmQkCN2YpfnY2I1dua+T8XFkFrJNg2kGXSJIJ7lmduzNpSbEULzMfZEv00P4V1Pzji8q/iZY0ewe+Y1wPgUUHl/GmuInYxTt2GlqoAbS1Z5TZsJw2hB4iFnTMKxpLE1gSfwGTowy5JQtGxZV1G1duO4+HFJGFoR+GR3dX3uyDSe0K0k8d7FT6nVvfdBkz4ntg+EFSmuceBIVxpq4usj37K2z+RA93X31EBthL1NeFIERMd91VlfTXOQnuDrezK/8cODG53BDX947wGk4GOW2CWgQ9KLxcLdJLSULKcTNtPGOFcZYnEILK+ZieTD0PHTubnBwSu6gfmt1RJ/7eHTWDy/wbBa4VV3LPGF+9ZW1UbjlAQZgnmmclMB4ALbNFKROtQQSj92/e8VGptkj6gAq7gDELoWvD+oUwG1XVOiAUsSvDPnIqPVpbp6VIceq6ekNW/EjBGDS+TWBZa6x3HssyjojvKZk1qgw6GlaXUAPgd5zs4AB7XhehXGx4u/p4RBTiJGTRGXB3A35Dd7e3AzmGxFYwhX/Bz82gfEiBAb4HFE68+CwCQMt2JrfcZu5XObY/vXnn8BD4wDfur4MdRfeMrmvG7zwQFKUkO3DOxlF2/3aRFUpAi9SvcivDiHGrVlmk2rtluX3AT47PSlLKwfl0bBAmAWQINc87ribkHVGgMVNACNE5oh3AomuYHjP8AGeHDxFgjbfJdo5RJuixtCAeukZ0O6VBZLEqi5R6cRQT0QROP3PF/UmmtDb6xQY/ltLTVEpVu6ELYmcrdC7PpxYAd2ozhPBfPMJnUbDxBIcE8sv80pYxyHmJzJ07vsTIaEarHiA9aP11J8khZ8+MrrkBS449dPYzyUcN01iiELhrxASoaCGeAj/252pnG2DJDZtGjeSgTTOAf65yrbUoqN801bDTejjNoNlACQCt/k4bwtQ0KmS2FNB6qPWYsTpEQVgpadQR0N0gXJS3aJjAo05BZVNeY4gNBSiL8LoFbkb5vTkCMzZEisKixORaSgKVjcY2NsxQxW8Z0Dzapa92BFjvFIyXvCJUObc5mg4V02mooFIeSIwwNz4JB5brT3bTvY7blz7ZDD5eep++8K4M+cP4/XTTP+qyuOWtNOydaKSlqxBNeO9bfzwiafvzlZBkHi9eWhXY57Z0yVo6fBTdHoeaNtKipUSDxVMGNDknO0L4FpLw1D69wcFxirp6Zp2kJ5FpApHWLh+7c5uh7FVjeS/aIE2oPpI6c0gPwc8fQqM7hGkrP+vd9Jg/h39NpXotEM9mi5pR1t0wyBAoYc1yeAI3Zvh1NaE0MiFf7bQhVASD2ykyknv4gh1CEPhhx9gQ+D0SmW6G8eA41rcOT2y27DYvoQkNOAx5aC37v1CF7/q09hcSrj2CFgGJzGUEufaoiupd30VIG5jHnr9/wXi7nbvMZhjM1gm4tsXF/PsWfSTdy4fYG18WzcIvN1jaNrRph8HY2UURBeWeS/n+Z5yzvhXIc0LQsNT6zGtXBTsHuga0/u2TU30MatAJg6KU26zuI3b8ZRIuZx0Jtq8QFEB5FxGHHkyBGMizEunAiU80Lc/d9eW+06OZ4tdpIPPE+Jr/17VRkgK7giKf4vZ87ii8sRv3LFEUtN7IwxKZ6eViKHzxJ90zVpgU+TTi2xOVZH7jnl6IzSj40VE+WwO5wm5HIFgmEcGn3zIsclYWhtv2t5foCGcQK4yNuLOTA0ikR4Gg+3GTdGYllGWxjQ8gdEw9ej4dIZeR4pp3gI1bvyks8MLrHLaqDRpsoVD06IKIhQRMAmiiH8X/+5LBBQIMqGP/6JT8CtYBtLNV1bOMdEN22xWPjfiR41hHWyL0oaZhFBmedABik1HQfAXVppSmg0DKbslPDf33oN8lzxjp9+EHffdQ2uvmrlC76tVC6wYRjdvWzzQZwQ1aqB6Gmce0Qbv9vKe+0QrbbfMR2JC046A8B79rOCCLTfJO2cZvT4XkEzJO3aOrlGnw8RqHWkmLpNl4uTG1ryiis7r7Vsl0BbaBRZPO+G7qfS6BEFgiKJ6aGNlrC1QrceUZiRc448a3EjYsFpxDMMSiEZV0v6yoJcaKhXBNmRKjvh9muEPefs52zXwAwBLVgMA/6f67O4dir45e+9EaudlprHTZCfY5uLxEZFydW+AGo7v7cBCABYjGNQg9kBBzdve185YEabWVUoNus1XsLOXhqGFmguL9AMKyf4VnaANGNFV7xHrf37+8BIkiZg3WsXANja4fudkZRB/7uUbCFoqZjmaYv7a4isXXtPPRC9xt/VHiYf6JA9SFZKICZSKCxeSC4Kk3PG8ePHwV7zAgtYD0PGznIZ5+U17+3tRQqLccrpgjbQkbMrKdSKii+qaTNhnto9RJNFcHPjRqd4aHkMv/v+V+O2z5zAq37pGZQyufaAG/XOwyohbyiB7ngYwsphJJNs8+3NXWxt0OmlJEnRXtrGoRN675AQrVAVlrQ2qooGzzxfT33ihq7tGqE0zy0QFGgagsViEbyuQEJCkaiPBQ/w9jKJr/ENoVSXEiSK8k8uVbdLT6WdH0KEzbnb5rBdWorsiZxNG4Pcv8lozgE4ALgcaRtjzh0rBLFqKvv4VgyRxOZkcuBEDrY3ssMwQtW43GE0D2m5GDEOI/78fA7f/9Q5fOG7rsQN37fCd75nYWOWfXwFMfckNQ2QhpyBcRyccsmhf0JKENKE7XNq+r7srD3PrSBDUfGWN785nh3fDwDzZoMvfPGLeClLe8kYWhHpdtILtQH6LAIAbSH4dtrvWIF0/Qi+tzOoRK692954rRb4grZqk96V5c7Mv4cBOnBu6V57AUfbobshD7Fb00kP3Vhf3EkMATI3cyun1b9RVXz3d393CHPwuhaLRYzVwpGuJMFqZwWFYpon413ngrk4Hz0XzPPkyEDiPJLE5RvdbU/kw+wez+8C//GpEb993VF8x0cewnc8cBrzPEHENHg7/8R5W3aboNHM8ZWLO7lb3gfCODf4r9/IuFD6IJohcQQaDaBHTwI0kMZzsmW9nwgstuA48qBLSgPNsWrj74FDN8rc7EhcVMYn3FvjSo4ouBslGvBW6SexYfC6eT39JfLv/ZxrgaOWbjjPM9brtfHtBAfaWs/H/O/z0aVt/Pz9MAwYRnuWY8fHDwOfdSvhZrPNPnilWvFObPCfPHESz9y5g3t/8CZMZQePPb7y/aYptvVxkiE3955paAQpKbcqy+VygWEYsBhHvw5csKbNk+gMpype97rXxobZH6VWPP/8C1vr/uBxSRhauijMcesNLI1poNvERWcPuF9ovTvJjAEr5zMXoh9QHi3QVi8wqNlTgvi63i0Nl34cItrdI/G+HBHYFpbpU75a4M7d9tz4qxBlhi2uUj27wselX6ydpcDOzgqHDq060XG7XyK/aZ5c+BrY39+3woTuvliualzxCGYXDHnAOBoCKZUauSUQ4zzP0KKY5wknz1T8H66/Dr9zZAf/t6eew//+7EmMybInhjQgScViMITDRdFzYJOjZ0ijfXoem0aUxR9W5lkBKVAtVjWlTL9rAtsU7CnOo1coqiNzQ66eJ1lNREVVMYgAokBweo4kE4MoCHSVnL81J3b24ElHZcQajRwM9EExESLeljZm7jsfcaNfrJBCXPpP4h7s+agF8rTLBxbfyDsKZq7Wsn6aZ6e5zE0usUHA111T1uOaARCVblWbfoiIlS1bw0RHk1kgqEhSkTO9r4ScBTkBSRQJ1oTynmnCf/PoCewfG/Dx/+WdKOMKv/pvzuErD53187Vmrep6DdyIoAJLYfQAWIfiuQnOvtlTAtSoRes2spknmESrIOcxDP/1111ngu5cbSJhb+dqKYYvdVwShpY0IzMJWuS5ehpSp4Gg28aO/xaLReycdMWINBmY4uTK3c4LINzjuJzOAGaiK0mBEvXA59HV5m4YRvlFar8PUgwgEu/ew26rPXdMAp9GmXTEPE+BgOnCDuOIt7zlWwK99KXDgDcjTJ5xMFhe7ziOWC6XvrkRkbUFFfygnweqoXur2gpGRCSuf5Mz/uat1+Nj1+/gf/X0WfzUyRO4NU0Amv4tDSfpF/t4dfSzPQZs706UyrEE0KHq7Zznadpgs944L5rjfFubNDlXB+2xSVfmhbZNDEBIMHJ+NeSjDe2IICObXGI1GgA+t7lB8jwpdxF6/8fnwI050JJ2cYju+h2qtOvvuUgYwoNv2Bzjfk4SqNhH23mXy2UEneKQA197d7kDG1tBFZEua6Yh6lqrdznxbIGU8Jb1Bv/kiRNIOwm/+jdfjb0rVnjq+WO4/2uK5N2kI0AlfdFRuw57/u1nlnGbpgFXiwkq5WypjgzExz1w/WfjyO9+7d3Y2dlB04lo///0pz9lcwUXPy4JQxsulBtc5rIF54o2weuBgehTpAYn8/sAF7oJ1RtJIqIcO24XDOsyAaJbQvLIojSh6qABasuEIMLNQ95CwzyMXmili6kz+FzcWxkQrjafs02enCzBGyI4eeoMvvyVr8ZCcECGIQ84duxo8GhE6eM4GleNBPUeR9HGuVTMpVW0AYjqJxFxqqKlew0eHGtqVpbyVWtBmeegIa66/jC+9n98Ez7952/AG57dxQcfegr/4foslslSjrjhbVNFXbdcadwq6QByh/21Gwpz7Yl43YxhyFiuliCXx/GnTez5ZY83IVAmtqvioledApQX7NGdOrfHz/Bkq1i8qO0cnFMMiIZbTu/tgBt60COK7sbowjLuAUF6HtGNrDLQ1kw6aYc+6MvNGACmeXKO9kBATTWoI9sMxdOqMqK1lK8/8tz0kFrQy+Y/OxqUUvGB0+fwPz55Anp0xK/87Ttw5voFTjy3wC98+AnMru9BIR1rdFoc/HQACNU8Gi/jpQBQqdXTEOtWYJeUUB5yVzrvKoK+iQqAQ6uV2RCCQh+OzTTjuedPYb2Ztiixg8elUbAAN4K1xIOeqWOpHhyiy3JgAm7xTx5dJqpIjnQlNZWvHl32aOpgQKxPuwJaoQF3UX6WdNfFzwv+qqMItv6xyyxa0IzGpt8ESPjbjusBLA+YbaYJosDJU6cRy4pIB8Ddr7kLn/v8F3Hy1ClQEal4vmspBVkVquYucTOJtjaleJDCqnpCClLMhVxv5rZIZzaxtPEYZTRU7Z7A3noPm3oNHn3/7Tj+xiN4+88cx9/6ykn8+Z2z+O+uugo/d+gQ9pk25yW5PNiOh4ic40XEuhgXhiSy/w4DqMqPnICZWhEb6OpQ9/6e/yS/61EOfqneoNFLNb3hQSy8xM9w2isUv/rWQj4yLKUlj7o1ZyKI2KXniQSq7ee4zQdSE+a+am3NBK1sV73hYLOMNjatNDdoks5At24Q241KV6tVQ/v0FEAxpORVbA1UAF7sIqQTyOu6ZKUYsi3OMatWHNaEv3viefz50+fw+WNLfPp/fTN2bjiMvb0BH/2NZ3F238fBkTq1eZNm1GpphXPZNISfbFxqKd7wtPH602RB3SiKErvnzTRFLu0wZMzTBrUWJAiuuvJKvOEN97RN2HdLEcEjjzyGp585cWEa34HjkjC0gAu1uOtSS3EeshcPbgR3b9Ro8Mgdlc4Qi08AreyMKhdMXv8hfhdcMIsVOgQLtMmWRJDcAPWopzfeNBK9q9tLttXqXQdk242Oxc+Hp4BW60A618lRqyHw+778Zbz1W97s/eY10M1VV1+FI0cO47nnnr9gs2D+qyFK3xBy00YogdbsHvbX5HABwWSG1NtGh5wiBMh9cMqGdXdvgX/2M0/gBz/wKrzmVTv41b+5wu33nscbP/Q0/h9PPIu/mRN+5uhh/PShHRxfdL2pBBEI44a2FZwQhCrTVrpRVa+AQqTNWTC0N150HhH0DvNB7fM05gQrgyx/Vn2M4YbTNwYiY21508HLwhA6P69qq/Ci3YTCXU/yrI3+inkHF4Ghe69eJWkEJ0QTMoCkXRNRaQn9KtJJazL/dXvO5v7ZjQlW1dx1iQbLia0BqN2+3UhfTJSydXpI1IYZOsRthcOWiTGfx48Miv/dg8/i6t0Z//DaK/FfXnMFrvntig984Cju/8oejp+whpcFgnExoq7XDohsHMz1N5RKDzalBPVqLnSbGIEMgdVcZozSSodZNAMVJOdnAcVyMeLI4SMtta4aCJymgkcffwzTPGG5WkHkHC52XDKGlkBUBFEOCSDcDvUABNDrjLYFGPt3GFCBiCL5gogMBTSDAzQDJx1CjQXt6IVIkephYVi1calbLm5tDRGbqEmXGiYNxVRtXG4bi8a62TX6SKjnCZYCiHFLp06fwWZqqWpEaVor3vjGN+Cxx5+wSTXNyGOOUbXUm4y5zD7BWmoLvUemXeWc/ZxWTMHUuFAzUqd1So1sCMZuainYTIpf+MiTuPMWxfveew2eeHPGI69b4rovnMStHz2Jv/HEWfxvTp3Fbxxa4V8eOYzfPrTCxjnhnvrg87Jb0DBwFZ5upe05mDFIWxxya0Viz04577rRM46d6lcWkIQCUptVJBIF550v6Nhd1EVf0PJ1W+jLzwNDXjZ2HcPqfKOICcIreWIaWMhWZgPRsz95JAApWwv42Z+FaRiX0O7g+VNCKN6xL5wUAy2z9+1K0qLynM/wTXCus/OfZriLA55Ii4PHB1CgVbDIA8ZxjZtuqvgzhyve+zuncNsTuzh9yyH8l++9Bf/oIQAY8ewLig9/+AzO7O4CyarsTNOlGfOcEiS3js/KPYRekIMgi0UYaMhpwDCOgeoZcAyeV9ojpBqYQHHXa14dKDZmigL76w0+//kvYo6A8CVOHQCIhykkz9woBUeaNQaiz6UEumBTx3WR41NtAxBotA9GYdtF427HHbDt/l6CV1utv0MOqGoLxvkCGgbv/4VtigEK9FVMfSCC90I0Q06QrF+SrmeVCNgR9/7778d73v0urh//7Iq777oLvyIfA7VpSYUYCrUc1hSehGVZJOdaU0oWs1IN/jNJwmazcbuiwTWnZF10xWkGorthHLDZTJBasV4X3PfVgvW8i+/8UyNuuGrCibdcgX9x9ige+uQ5/PiZc/jxc3v43t19vJAEv3j4ED549DC+sGBp53bwo9aZNgkS8pnN+KLa2EcuNYxXDbdamiQgfKMlauec4IZHjrJ5IoV7b+SxQtz2ExECMbZObLqd9s0eDDJpSG+TT02StwoTiJIBxFxgwLHNf2Y6uFubDOHax4qX7Q5WsOMbBikR8t+1VAwpgV1g52kNwHJRGXSrDlq4/mKdiIkgYZ696KBCUZHzCK2K5U7Fj7z/MN7+7C7e9LFnccODuzh/1Yjf/Z/fjUfeexeu3K84+lOPY/dcgUrFmfP72KyNwkIWjF5GnX3jgLQqw5QyZrZ66rxUC4ZOraTddVRqLUhpjFzxYRgwTRuMixXUs0hSsrm+HEd867d9q3kbnfYwAOzt7WIzbVAUYdgvdlwyhjayCogYVE3J3yejZRvUmPChU9mnxXQldW4FHQ22BTfPczMGaN0QmAzfu/CR8P8iXXYBxKLuI7hcEZHo3BnT3ogfNLI9Ytvi8FKTPeS12j5rhrbMBV+678t4z7vfZacOYysYh4w777gdDzz4cGjo8t6JfNlRAQA263WjAehCC1CKLco0OPJyRDMsaVQRC66UEkhts95EcYPAKIYHHz6DZ58F3vbGDY5dscTvfn7CejHiP7vqCvzX116B9+Ec/rKs8RcfOY+fOHseT48JHzu8g48dXeGzyxGbkmLhmBYriwdoiiyNyBYiwLqUcUiAFCQBbr39iKWp1YJSrFT26afPA5qwswTyADfk2Xu7JWw2DNAB4wAkjJ6Ct4HCBLLnak8mpQzRCojXxqtRDaWaNRYVVLUgE9G1yRmaO1+U4iy2satvquxya6Lflj7mLl/QCahujB0BC9QoAwUK1uYJKcCOuDqLu9sClcHG0zeF4nM9iaDoDKa45QEY04BJNhCxlDBV4LYbMl579xKHD+2j1jWACb/zGcXVp4Effuok/uz/62Ec2Ss4d8WA3/nx2/DYd70adUhY7y3wxfueQpm9aAWCnAakXIGkTq1sC8jQyA45e8v1CvGsgr5lkqIhevXNf3YPsFQvEEnCOgtbf12mx2K5sOBpd3B9fupTn/F1aLm5L3VcMoaWDFitHKCu3NLLPHvE2bv+ALaM1jiMW68HZOt1W3oGpAqkUQo5Z0No9oYtDpauBlXEeneG/w7yigej/3x9fy/kR5k5wTJC0gAQYJ40JgKNZVXFufPn8eSTT+HWW27eGtNxGPDGN7wBjz3+ZFxP8FPzhFpntJY0nvBNHs8pHMpJ8ikZGkjxfV8YYQhLgRnBi1pXVubLGhI5t5vw259ZoWJGqSNyUjNmJWP335/w6dev8Lm9gjvu3cWdX5rwlx44j584dR5ndxL+zXLAry+P4uM7S6xuBK48Rj1VCwQlCPbWFY+dSKhlwDhYTuk4ZOQBGNIG3/kdt+K666/0DXPA/lrxD/+Hj2N/L+Gd77wNb3v7awApYfimWfFPfuqTOHVyg2uvFfzYn/tWVF1js9kzsZ4N8MzxfXzyUyeQRPC2t9+AMRfMm3OYJgv0nTixxlPPVGgFXvPqFRbDylOtMqqaetljT53F+XOC1SLh9lctobpCnYyymeeK02dnnDy9AbTgxuuPIA/aDLEods9XnD41IQOQrLjiisGkBDFZReSUsLc/o04ZwyA4dDih1D1D+7CA6WYjmOfk1EVxQ7vEXXdUrJbncOUVihuuPYLrbzSN46efmfGp31/gyacn3HHrjG+9Z8LyzBo3PTzhhi9P+FtfOIVrz06YAHzuliM4+YHr8eljM3RxDE9++gy++KUTmMoO5skQ/jgOWG82FsTKrkUcgjPmDbJppAgweZwgcc3B6CqibHpC4u5PShmSLLA8TbOXRVtGhIZHoAEc3vHOd+LosaMGMLShWkmpCzRXK8QhAHuR45IwtAp4q2Zzs0hZ0ihIElPS4+vdyJEH7X/fo8ODVUT8zP61fF1PR+SUjMAXex3LEA++n65sGOcus6H/fL4uOFo0Gcc+VYyvhTiKNs4fs8vbCc/L4InYbry3t4/HnngCt9x6c2O2BRBJOHLkCBaLBc6fP+8Gdo62PpCEnEeUMsVzgCAmD1SBjGZ8sV0lF2MMwZBokJNHwpmlkZCEz9IQxzTbAq6KEMmx1J193HnrDgRrbA4t8NW3VzzwjiXGfcFt929wx30F7/nSGh849TwA4MmzA069PuHEHSOO3zFi90ozjCeerfjZj2Sc3RzGxNJnrVimbLyeKAQbQ5dpxjgcRkLGOGSsdnYwLpeAq2YBimFQDLkiJSt4uPrqa4weqHvQugaQkIbnkdMLSFLxjrffjuUCSHrWUCcEn/r0Mzj+7ClUzPiu73o1bhhm5POnMZ7fRT43Yzy/iy/e/zzm5xTX6BpvO3QUw1SR1xPyZsawP2PvhTXmcxU7peKKhwUZFVJMb1UqDArPahklAmAQqAiqgWVUEWwKsC6CukjIR4B5FEyjYDMAm5xw/NyAZ/cSzifBeQBnBVjv7+FPfcthLK9OmIaKKZ3D8CSw2AB37WbcfLJgeOoc3vrRijs/uIsjJ22NbFaCx159DP+f0yM+cvgYcN0SVzwhePbZc5jmNVRnQA4DkhzhCzYT6RttBhOMy+hWHCGMbxJMU5eHDbYwSk4dosU9hLnGugWsbK2aEHotBcPS1uuh1Q76PnKMCZx49jmc293zNdPRUBc5LglDK0BImJGI5SAeNJQHNQp6RNkCIe19PY9EeoAGZytDwFPIgJbqAm2Rb57jYMECNwOesy8wII9KygKqqNI44uAPO2pBwKCStaFRaMdLmsGr6PRMnSt97rnnMW02WCyXW2N755134rZbb8VX7r/f0L7nENaaMKQMwleqPtl1shTUGvCF8ry2AALHtx+bEKiGxKJQtECUdU7J0cIFVYx7h+ViVij++QdP49W3H8Gdd4wYxw0y1rjhmkN48FsG/MbVFb80XYNXn5nw7+2v8QPLPbz2Mxu88RMbAMC5KwUv3JzxxJUZJ88t8AfzBo8PC8zZU58KgDTg7NkZi8UeRAwZrTeTP3PBkIEyTc4zekUZMmqx7sM5L6EYAPXNN3nQJVcIKna04MjxZ3Dk9B4OnzyPnZP72HlhF69+8Fn8pafP49rNBtf/zXsxzAcU6AD8ac5xAcqpM5iXCWWZMS8yyiJhf0w4vhiwSQl3vnaFvJxRRaEZ0JRx6pziwUcr9otguZjxLfeMGLQAVbHenbEaBzz1ZMXpF4BrDgtuv2aDcVKs9hVH10Bez7jx3AZ5rThcCxY9QPsfn7vo+v0OAHsieGxnwAO37uDEG3fwicWIj+8q9ucB6/Eo5jpBzhWcOVOhOlpnWTeY45Bbhg3gPKpt29M0mcwlKZNhwOCpYda0lS2b2jrv0zBLYT+/ZjPoDVJgqgE3phfa2r7i6DHcfPPNEdgjTSYieOzxx3Hq9GmYyt0UwvMXOy4JQwvAjJrndEZUNoIV24EjHjREQGvMF/yqd8GNj68Kze03AkB6Q41t9x/kQnNz8ZMYQojP9PeS8wmD3hnegmLtSMTRG92T7v294eqLHMidBg9t/jxEWlDErhv40pe+hHe/8+247vrrIiDCG73mmmuwWCwukJ3kdXYxtKYL0d2LCrYi3UzrqlpRNsXcMWwHS3gfyVvrzKVES28+y5RS8xZEUKvgbDmGz3+14otfKxBdQlHwqtt3cPjwjOdP7GN3o7h3tcRXjq3wyHuO4s4b1rj26Rm3PjHjhidmXHt8wru+vMZ7dA3gLCYATw4Dnlgt8ezhw3huHLH/02fx5KEV9nZGrBcjzggwrAVrTLj3C8fxxBPnkXJFroJFVQzrNa48tYcb9ta4/tEzOPnf/TKObvZw1e4aV+5ucMX5Nd51dg9/7cwaR0sBPvkHW1N7WmSc3FniCcm49/AhXPst1wPXDZiPrrA5ssR0eIH5yIif/80T+MqzgrQq+Kv/4e3IaQpaR3TGr//6Sfz+vQUZwE/+z67H0cPnnBaoEAx45LE9fPRjit11wpGdXfzVP3cMQy4Wp5CCqgkf/VXgi1+uuO1m4M/+0D6W4w7Ontng8FFgc37Er398wpe/arKQC51xRUq4UgSvufI8bj6ygZyfkMuIaTHgfF7gFEY8dLLikWlESiuUsod8emXnQ0HSDDD/woN7AVT8K+eAGUz3DGFawtFPrVphQ/LPYDFLZhocKrS0DI0UKmqeAhaFETTo3TqGAz31ij8vfDl27BhuvOlG1HmznXEA5u0rUrLNguJTFzsuIUPbAl0ghXAgBYsHI/vRRYGDKwIlBZC9C62XtBawZt0juwfyWWnEo1igKhSGLDnIwzCEkn5vJOe63Tqm50J7aoNH37aG5+6NcyPyWcihkNF2YaLYnjtNS9sETp85i+uvuw6Qlk6UFHjnO96GT3/mM1tdCFiEMI4jas1+7xsPgHlJbS2Q2a4j8oq9JTNTrxaLBZhNkXOO7AS200mSsd6fPJjmHQ8USGmIjYn3PIQLl104B4AcxSOPO81SlrAcU2CzLvjob1fPv85I6ZAt0KsVqyuAO/cKXrOZccdccEcpeHUpeNPzz+PKuQBPfP3paIKHFznutS+zAM+PI55bjPjqYoET1x7G84sFTq5GPLcc8MJygecXI84PAzZFMU+2pS2ngvF4Qj4hEJlQyhqqZiDnJNCN4n/4xw8jq+kwSKrIUnF+N0MxQgX4Vx98EmOaY1PTVLCZlpimAaKK9XqFj3xsRtKKPLD/nOKp4wOQK06dBj7+8YzVwvJ2cx4wzwUnns9OqQAqA87ljPVygSf2RuS1BPKXjSNA8aBxElSsXZ9jbYHKUsMTmsuMcRhjg2dWUOo8Oa51W9Ne8+bB2qj4lAQM1mwUEOztb2Iub6YJO8MQWQmN2jNEW0pBTU3gW1LCNG2wwMIlQ83Dm0vBcrXEsWNHoe7hARaz0KI4e+YcfvM3/81W9hIlSS92XDKGtqHJFsTqO6T2wRwAkNqoAckZyUkbpoRZeWDrTBrBGyhKYQC1Senxs0IgJqmX7jWF+RCOZsmuc6F9FgPTvpj+xDLLg0I2fH0fHDtIpgdl0HG/liaUXOPWXPfNZsJiHPCZz3wGd7/m1e0DnH5ZjpZ69mKTgW2ADOmamEgUOLgouCibVbaSUeBgZkXCerOOSjEGI80QZCRRExGJRPnt9upb3gsURVkCXQLNR/ZCGHWgVCAhQ4pH9QGcl4R7Dwm+uGMLHAocPXYMy+UKh1LCVesNrp1nXFEKDpWCw6Xg8FwwaEVWM7BJFZMI1iJYp4RNSjiTM06PA04OGafzgNPj6EIzZqzsOcI5L5MHRAFQJECESMV6P2FfuUgrGBDTLmPkzLkFnIWFiPHF1ACfteK50yO0jn5CC+rB0yPNLc746kPwUl2xOe9B4aQZ585X/MGXAOgaogkqxarKLK6IzWaDNGbIYIaHbvo0l61Ckr5XG2MpjCXQiKaUsFwsUUrBcrHEerNBzlb5N5eC5WKB9WaDXhS+qmLhffhYZTbPBcPgG3+ygHRojIhYWXetUVFYvHAlqAW0mEkpc6QNzjM3AY2Ot6qK7/jO7/THYeMa1F1nuMdx6OjEC8xaHJeMoQXgBLcR2BZsUOdrm1GyhdnKGU0PoInCBDJMgrSVwE60iECG8zzHjnyx3Yj0BA34dpFEq8QKN5y8cG2IvA+SheSfTyYq+PO9L1aFFqloJOXV+1p5SxmbRIKTp8/g3O4ujhw+3Eh/AIvlAt//vvfiwx/+MLTIViCx71jApoTjOIaBsmaMPkVjMzBhcMolGuVhgS9JTa5OVcNwmJtl6Tb2t2Ieg/NiFwtkGq8+QJCALmDISR95q77RcrKrWspP9gwJfyPWKeH4aoVn/PUMkLSNDME1AxQc8ipF2NzZmm+0jsoUJH+/IgRcjNhTvszuF9WNs8ITlrtna63K7ffC1FtrqSOe2udehGXguadWunxtLihPb2SHAHoiqhUWJ0oWlFRzfQtzZPOAgorT587h8KFD4S6rKqo0frnMTSCIRUEm1pKj6MHG0UFOZRddL4hIKTIHjPNPgBtFeqsQeGVzpzpW5kjzK5Uo2TycWqt3fh5cTrI9z1Zs5J6xZIhkJBmgqTSwVgqWiwE+uWLeQYE/+PznrRnrtAnvcH9/P4Dhix2XjKFldLG1sTCJtd4ANvTnRhlelgiJSVp8wTBd6mBArE+r4oLdQlRoC0+k5eaKEaNxvGi1Ejq06plO/B0NaL8ISLBnyTGx+gBdn4kQBkg8bzDuw1ITkgjOnz+Pz/3B5/Gn//R7wCojvvfQoR0MQ4ZWQ/cHg4yAGdu5VEzT1DYTT60bxxz5hCklYGgq+TVaPludeAumwXNGfTGy/xkQFUTRQK8b0/Awcg7DSZQRRlEtkKVVUYUFCUDPvYEbFd1S5/jghung1rqVwdL9nwtMO7Vv00OWOJ89P15rl/PpRi2wplKblnPHECk3JUFLXYwgjF0dFK0E16qEnW6D02HSPAyHlW3MCuceM10MgVlcxBoR0msAWouZYWjGxoziZFKT/eDZLtzNKY17VRVI0tbtIVTfWQRSYg7b5i+MPHmxQaP2aqkQF1cqxddmRWziIm19m/SnOxdVPWhFmgIxv8SzQsyra2pdb/3Wt1rHXPhneJxFoXj00UdDq6RWm/MXJw3suGQMLSdICTEZ+z1hv6C596XU2A3h+qLZ8wCBJgtoKKNsqWNpbWWRfSfdPhDGc9VqYiDkevjaPpWrN+B2Emz9ntfTGzZLqd9GcLymXtJwC40TxYQBbLKHgBvmWrHeWNEBiPL8eNXtr8Idd9yJBx94CKqtbc0Q3XWt5UrQMW4YcsqmH5uZmoaI5NqzKta62bkx2hfyuABCO9cQOhepevDB09tcDrPPYrB25oZIFU2PAADGYQQXt72+zSUaxrnO1hVCFeNy2QxcuHnqojrO2YmEYST8pME1Q27cZZwDzRDGs0HTM6Dby4Xs7wzDyM1wS8OD96TaGWE0ZCXiwUqyyDXQbQRZAe+MK/48xMeK8Y52/USBRKycs5YpUmJg+X++Ngxft5nzsfZNEKt1UfSsgD4ukbxYhkp2QM6tjxxpxNk9wyEPLiVqVV3J9Wj76s2UvNJrHK0wyemu2lVzsssCqzOZypjZRNMWDm668UaMg+ch+8alVXH23Dms1+sAg5yr/LyLHZeEobXFW8JQ0oD0qVT8Zy5GE5nhcdDNNuS0baz6YJB1PW3IY1u8u6VvJUkwr9XRJRDuCBd9/7XWCp2bEQ0qwxc535fRDCqzCwQGVUTNkEShgLaCjWjHkTJqIsXQdFsfffxRnD59GtdcfTWYyC8iOLzawWqxQpuUaauwQ0QwZJNQZHYBOWqm2FAomUbcuOmEhVfFkAYhp5o0hRFVVcxT9WCK9ZayTUNdCDqhZhrCFJ8XGRRS47y1Vsxz5wJvzY32LJSujxr3lvzZGV+QAnUBVokEKGalkE9149Y8p0Rbh87QkkYgVaNWNNF7JmECBahOF6T22zCAPgNsAXMed4aX809EoqRaYFQb6Z3ETViI/DxH2YVy2vXGhyFak3eNFg1NltjcaERFkhvg7fTKqsZjRHA5EQxwzCXWFceJ/6oHu0ghpSQoswWszcvxkls37pr5XI26IvXA+wsw4huQ+HspxNRTeuM4Yp5LbPC1Fhy74iiOXXHU7IcSedvXL933ZTz//AtY7eyA6mOk0l7quCQMrYAPrblD6BYMvzICfzA96sX41YM5qlZB4w+340G3kGxnGPvP7SkGIBgBAE0Ske+n+9tLLKpacK2nLMxo5ph8qha4EQxb5+sFOkLvtKppQfiYNRpD8PQzx3H69Blcc821bvQ8eJWAd77znXjgwYe6yC/dTW5MFcGP6AFKxO96GJt3QMRCxDGX4oaihqHuuXCBG3MRi6SnhqLF/5lbbs/LREuaRgOfZeQuhye/3SCzD5wqGo2UuBj7mSe8VwajWgqSdPceU6zzKvzkW3A6kB0aIu0DfXy/oV5DUNy8AKYtbQccibTC6/NF3cbElLJ6WoyfS+8H3Zry/WNr/dh40fDZc9tZLbDZrMHW74bGnaLrCm5ELGDGwPLkaDLmv88FACjadHx52wFo4AUJrrfMKsRpmqzDg2e+CIhIneLovEvOTXG0LGpzbponpJSxmaaIRwyZ9GFBra144cYbb8SrXnWHZzHBtTTgpcw2NpvN5BywCYq/VJwHuEQMLeDohWpy3q4lazN6B9Of+n8Agl/q3fSgAdyVFqE4RVsYfQrZQde9P2/P6R4siujfHzmvnUEIEXHnjlg1lXOOCRhoVxApZT2XBDdsAqsUm2dOWIIfC80NwxIf/+SncOeddza/VgDJGTffcnMYDPKwpFiGcfDoLkzndcuNnGOM53kOpJmkiflsNlY0IJ7XOA7kxMoWHSBJrVvurChSHb0KSqFB0rjunuLpN61oHNlvGCmZAAnP4+O5mSZkTvPOyNJrYv6vEsFyyMgR+EITcXGfbjHZ8y9N3IXpTPx7eCSWnFDR5jeDWu2C0DwJ1xrQWl19TlG3NgXvNptYEGNtY2Id+FjlbM/CdGQSKgoH1m6DBoQcJzeFpFFpdfjQoQYcHBxMm020pue9k96DItZY0AQGR82t9/lBEFG0NJEaBoa1eQo52fNOriCn0oSV4BWFDFDa2kdQXLUULFcrG79i83Cmdzab4E3OCZtpDUkKnY26yFkwjt5VRWcUAVAF58/v4Qtf/BIqrMhimicoBGW9tjTDlzguDUPr840IzdInjPznYudi6nlNYNt9IR0AtMUGaVFkBm/80Vzwfr5vK5lfO9dNJGQOifj6wBmvM6ccJbK98Z2nOV4faSzMROi4rrimemBDUYVkU6i3zUICjbJ19GYz4fnnn8cLL7yA66+71nZ/MRcyJ8HrX/96fOELX2xi3mh5ypZfbHmLNK5AQy3FOTmrTAOqVNvVkyI5RcDCDkomiiACLERCis6Q+ZFzo1gURFUcq+bi09XsOXA+XwZT+g1Q1SijvguGJhY0o9EDXSYI3PBKkk6wu+m1qppHYeimUU70KsKA98E1bh6iIEXAe+Xsi2adkoLTJSVAN9iXS3CtsSG5AQ06gghYXDvWuyyw51aUVSsRJZP1WyDOxL2Nc03J5Aoh1ioJgM9znxtcH8ki9sOQ4/pSuP4WWLPChdaSRmOTMfSdhwzM9CR8TYgArnOgnUfRe1B8vzI4quq9+CTuh0a3VhYZDFFVZlQY8Pa3v93WeaeJAlGs12ucPHnK5541mpymCdklS7dc3QPHpWFotQ0CVbp6t7VRlb0bpiGuEoULnXEEmsvfc7ElUlO2g1i98e5dIh61KnJCuPo5Z0u34QR3ybkXQ8Oc4Nkj9Vv3Bi8B7l/fLgTB4XZuctXWvsNf5uNniHy93uCzn/0sPvD+99nOrma0AME999yDL3/5K1ivLUmeSJQpV+NiONCby3p3Gdpvxo1SirN3z23jopjVhH0GD4jl+DznIaVxXtNmjvtg6lHuAg3sANsMcws4BSev7m7Lhc9cxIoqaqkhF2kuZ0uTssqrNr4x7ep2JgGLNqjh2kFvWGDPUS7QBSsbsWuC4hbUk8i71TA20MZZcu/vW9O02IEC0tEOPiqM2DP7gHMPqg1Rd4HWxhG3aihSFdUwNDabCcPYvLbBC4FomDlHzLOpULUxqpFq5s8qZ5RqspwiLatGgZACrcWCh/NsQcyUEtJoMZlSTey+iIMg1QikWYcHD65BwZgFYAG5yGYhbecDYznaA4j05nlCSoKbbrrJeGgb2BjTk6dORdrjZrNBTgmbWpEWAzb7m5eys5eIoYUN9lxmMFeOaA9oHFKPNPtAFYAtnquPhAJc1C2dxF7T81nbPF9/nuIuh0KjYKFNsJaBkIYuEOcuZG9Aehk2gJVW25xOGHfyc9mMR/ao/Xaw0I5xHEIjNw9D8HB5GLcfvC+uK44dw7Fjx3DixIm4jlorFosFSp2jOostv+1+bAz21/vYbDZBITD1JwSsJXmlWTOCpoFqbidRri3KhuSikV4F8uAuqCiSDKHNavfQDGzTGK3eDbagaEfHiN3bOI5+/eZ+SnLk5CxAuPBh/IvPk2peVUdPhTusNMD9Rt2hSDQZv/gjjEqQjhrxiW9jUSuKgwe/AL9lDRoJjkpJr8SeIKQQ2jwyase4XkPDjfdXWIlqZEf4h0n271WxXCyQhwHz/h7mGdhZrbDebHwj9MpA+EaYLQuCmyScAsopQyhChNhvIJDIUsmpqYRZya1d9zCOaM0SgVpmsFO1dp6ebZ7eGl6Nr+ZnTVO16kb3qgbJkRc+jNkam6oh7ZQT8lBw9913Y0gS64VeVCkzPvmJT9B3AKp6aqkh4+qZUBc7Lh1DmzMGQRDgvRGMwFAf6a8VRXzC9AYq3CP/3I4zneeCXtOWgZo+YGZJ+CloAkbQGUgDzJDygdnF+IP0jp4MfIUQi7R8VB5Ba0RQq0sI7+gPKIBBmpCz87HuKbUJVyvm9T5SyhjHjAcfehCnTn4brr3uuua3Arj55pvwqlfdjmdPnAiDBUHkyEbEWxWb9TqudS4zSif0nVLCuBh9TJnGhHBFuajI7cGvl2k44s+GaUU24SXG24S7DelzXGxMfBDcOFkE3rV2ZTAE00XFmS6YckYV25dJAXCMiZjNDaWxNFeZHoS5r274HOWYbqu7/369HINSG+cLot+ObuK5t7y0MJwI2iF1wV922Ljg9WoGnM+OBrBGiXq6cP24IVZtAu4XUC6TbaZs9T44756HDJ2IZK0Jp4lnT3bdce9t3VKGk/MpPDvfWLh+xTduqa0XWaqADIPTFM1rjThHpMphi3ceh9Gr2txDUCt2MsSttolXVntVvPrVd+D7vvd7m4h35+X8/u9/Ds8cP25renYKyL3EnDLYAftixyVjaJur5T+rxuAFb1m7VKh0IPe1myQHqYaGPhO02oPk5GFgJ3Z6JVeI4PVoWIIWkPb5fVEBUWfkoOLCwByRU5+/2Lu5/f2znU+MjZC3FJRZOz2GitHdp2GwSpfTp87g/Pk9XHcth8QDLFrx9nd8O750771Yrzem7YBOhk6omL+tQyCSYPPPjZwgjKzWirnj02wBsEIvYeRGV7aV1ygeAkVLuyKCqAUpKaCltTYSRMEFqloDRh8rGrXqRpbPxsTk4RtnP74NXakbKnQ/Z0+it3uwc1fOLe2CaPydEIgaDUFkSsNoAirbRtYnToirADb+nI9m0w2B136z4RiGvW3Iy/JGFEkRyB38PDRvrEffAUzcGLXDxtC6QtuGZYa0zVFeR3UaYJ5nX6s1ULk9yxypfdnLqGMjrq5l7Ig91g3XsLdJWixG7O3twagfp7Pci2OVZU1q3CrsfQMyilNrKWdIbXbBKCbzBo8dO4bv+fe/C1ccORZrxS5esb+/j4cffRSbuQRVU2q1HmYu79pz7S92XBKGVgEXIVEANZR6Ljik0QIMGHDBAtsGrEePdO/pL2Zsd6nl+yw/80IVnr7D5cHmilupRJ2bmVw4Oa43N2RNbrRVl1wotdgWg3fOVQWV7y3vcVvVq9YS1S2LxYg6F6zX+0GDSG5CHtdfex1+8id/Ej//cx/E0888HfxmG8eKMpXgTKUfQ7rb1RYdgxeW6sUc2eYplFLgjqP97FkXzIEmEiDlwIBMTibmrLVimudAwKWYVQupRRpZblaeyO6gE/vz2lKDAKCawn649IHeFDU2ug7togOljiwZWW+sT/uMFrQEtN+AYzGiqaD171Yi0S4VURtahncJANPFujcLxHE/oEz0Bbpl7xw0WtyhBzSWadIHEM1V32zWmFAwMBCWxIGqxD1ZZZZ4y6WECushxtJ5ekYpZedhG7hnWyZWfzYaoq1vjn/xdK953pYeVZhKX0rJ1PoIhgBkdQU/rm0HBLT/ORMQZFx55VX44R/+IVx//XX+zPpnDnzta1/DAw88aHM1mdi4Vo3CKfOW5xj7FzteupzhG3jwYfJwDznQCdEi3VI3Z/ZaR7wUmCBBzs+NlCyfTL1IS28Yx3GMiQW0Hbt35Q9mNcT5unxaC7D46yo/o0CkBiplwImLK9BX1ch/NHQJSFKIMEhoqE7VksrXbrCLo/PFOLorlvGZz/weNtPkwTPm5RoOu/bqq/DDP/QDuOqKY5jnCZv1BpuN/TMuWr1MNmMYFgBMgGexWGLIA4aR/8ZIm9ls1pimCfv7+3EvySuAxnFEThnL1RKLxRLL5dJzhA0trjdrrNdr7O3vY5o2mKbJrqXM4VoSsS8WA7IvSD6z0TlF+Ljs7e+7EluNeSG2S0FgNICpx8DLOrkRos0pN7xJvOsx7J9wTkhj2ZMbyiRiEE9a1dJWvEACELbzJXsPqSD+LbCq86HJEX+jDmgRpLP9EmuHvC2VsA7GI4im0aNHSXHu5WKJnZ0dLMaFGUvfWK3zRg5Xn/RLv3jjXMn8spTt2W0FfH39xHXAvKQkKVIgk9j7cjYPYXCu3QLLGdZmCVB/mKoJWp0aSAPUlXi0WqcNW7utDHfIGT/4Q38GN954vd2DNOpEHXh9/OOfxDCOKPSOgJZh47GMYRy7zffC45JAtEBDcsmDSGz5XLRCSwPmZjB696uPfjZRbbrvYfxqQxu1c9cj8V2AVC29TJLzs/nCnF2iz97d7xF0n/MJGPrUYjvGNPsOCHOjog12bTmHhmRhAZ7k1w9fU0KBFBsPKx6wsaDSEdQaRVZVPH38OJ555jhuu/VWG7+UkEKXALj+uuvwE3/5L+NXf/03LBNhs4mChJTUJ7uN5ZAzNtM+AMVm2rScUUe2rDUfcg4JR61NjlFVQ9t3njeuGmb3N1DTQMTzb9mQEWYwshsy8n+AX1sJCggirbxSBMPCqtWq51YyO6GVx7qXLM1w9hkh1bUzINuGkqa10SSOBkAU3Upqqf/Q0xSkEunS27mcJnCw3Awo4toZTyVPzM+015t9sJxVzxpw+oNzVhwh0iBLeAEI76lXzwIQAd1SCzBxjAR1mlyou1kW661mWSQQxjEMySpcdlOsgoqtoFJqolBcp5TapHYsaTPKLNq8qhgWC9Q6YRwWTn2U4OSteg2AxxWHPLrhNK7eNumEq666Cj/2Yz+Km2644QLqSGvFZp7x2d/7LJ59/nmkNAYKF58nlnEz43wplr3zEtzBJYNoVRtfExfsi4BudxIiD87F5vL3UXmKl2wtkESNSzsiNQgInrS4+91nMNhlyLYB7xAiud2DhQx8fTP+hodqZcK5BwHsArburS02z2tUASQhIUVNdkP5M0op2EwTpmlynqw4slzjX/2rn8Ojjz9hkf9SwbQwXvuxY8fwfd//Xrzt29+21WBOVbDZzJinCaXM2F/vY5qLTWAkpDxgMS4wLhZYjKOjxpZuxY1ts9mE4Pi0mbzTquUujsOAxTgaUs2GDJjTSL6zuK9Xa/VrKVvPOmVDtavVylEaJRR7lTWbW+wewaICnsOBTridbfo1IxxUlht8IjVJCTkPFrgRCWqFnGlzx7X7G4I/DSLAjT7zkKXjViOQ2tMT4tfrdA0AR97t4/h6Vl3Z7+3ea8h/WqZFXGN7M8rMsmCJZ0vESw1b+N9MC4PX3wEeSbCW5b5F+fNIsR41UG1QcJGy1nsO4sbZysTL7ILbpamHkR9m3OFgrvEwDL7hAYcO7eCHf/AHcfONNzYPINax5ZE/+vjj+NRnfg/racZm2vjc8LFOppHQdB3SSyLaS8jQtsAVDR53YoBiLoNH+Iig7L092uj5Vi6u4FKTWAUUXdmOJthy7zreje4RU4XC6HfZAoGCOqNPyoN8U7iROBjd5QSni5q2npdWtmHRoADoxlFl3iZrwmJhu7uIIdxaFWd3d/Evf/Zf4emnngl+jNfmg4Yjhw/he9/73fj+7/8+LJcrpzIqFuPS3LZBsFwuMA4LzHMN12yebXLPpWCzmcy1Ug1jmJKl6YwLG7fVahlqTLVa+6CNG3IaZePqSwS1+FzGccTSKYdxMTrNVJybVsxOkWht6MlQXcL+3h4W42hGHS39iUYsWo3DgnxcUP1/YWwDYdYw3BYAI/pNB+aRB5z4NwSra+cKOgdhMMLQKKCoHeLtZoZvGAhUbVgWqtHVQsR/RyOqFjxlFJ7nEjRZT4VVmfGzp83sz7UVlZgXMgAqUd4chrTzLM2QJohkN2T2GVR7Y+8vc8sp/sTn0qV22jdO5bRiAepT9JkYpPGat9sKGqqX0O7s7OD73/tevOq2Ww3VqwKldutXcfzEs/j5n/8FnD17Lqg86oJY/AFbCoHlQKfcg8clQx0A2DY+NaZj+1vuDASae5n6yd0FEkic4wD3RZqBPx9Eq1vX1KFHGtR+IpFeOHhEdoSI8YCyXYcfFEHVmKC11qjC6SOf8fHu/pD66B/wPM+Y1MpqByZwO6919tw5fPAXPoT3ft/34XV3vya4YTuH7cRDHvC2b/92KAQf/ehHMQzeqqYWJBXUMmGeGz/dijHs4kanMQTW457PwFCGB8UkYZ7mlpHg/FupFSkLVnlpUWAXvamsZtpCOm0B0Yxlfx4RXEkS6KZWxbhYGMIl6gTCf1f11HzqAgi652OvDWZOW4tq44wleGhIaGkZxVO1BeiAeN4iEi1doM1AxObrdAGc4mp37JZK1SmPfpPeXhfK83FNqDrnQDUuE+WxeWYeSMppS0pxHEfTTVOg6tytH7+G/mQ4UKDAoGYpbljtTrJQe7bRayKC2bUM1uu1UUJ+HWwTPo4jpFocIoeesZ2chpFTkQEuXivX6jAM2Gw2WCxWePvb3467XvNqp02aZ0Nq6cTxZ/HBn/8Qzp09H2Xdtp7FxccH7248x3nMG7w4pL1kDC13LSLYCqtU4SSlO8rFx3Qv6QjsWPxDNwk7d62fjDSc5IXMn9mu5uIE4c+9ewEFaqpbCyV1C55H48haTi2/5/X111YZ2bcLR5LBkU+N8kKuNBG2MmfL8tb5QX3nhxh3ubu/j1/8pV/C9N7vwete+1osV0tf+M2gQCve/q1vxXIx4Bd/6RdNXDmZF1FLtQ4JLNBIVhU25B1Igrdbtjxl2zRcZ1QAIHkQgy6mF4bMxWvdxb0Pl8QU0yK1YIhxh8M4oFSb2NYpIkHr5Aje0p9qpwCXsnWeYFmlamt4KSKM08cGS7SC1KQeqWoF11QNWObuL2pnzLp5SvcUiXmrbR4nn+NV1ctWsWVwc7Z+bc4roJBoTK3smvOXBtmWgKV2EW2bZgbnpwJVnd42r8qmOf1q8YBS9fTB1oPP1L8yoCnaR+WcUIvnn+eEUsQaLNbq80Vaxkq3gQDAkBduGBMkecqYeN46aLCNahvyiCrGOw85uXdqGzQ3cPW5RsOd8wKb9SY8T665UiwA9vrX3413v/udGFIrDIm1p4pnnn0W//Sf/TT212tUWJeGlMUVvjpAx8C0e95Go1wIuHhcIoaWUfq2O4sk5IxATJbcLNaGWylC0ygCTvR+l6drz8E5mIrFg0a3bzdDxNKXM/YuCtFMxbYm54WJ3+0r071aoMephdz0dtVdUCab+8X4pM4QsRQuTjQGKIhEpmk28W3AeCV3+eY5oZQZv/yRj+DBBx/A+97/fuysVh7MgiEkmCF461vegr31Hn7zN38L8+yTyFENNw72VivYDiKllLBcjG4o7d6z86+zJ7fXpJhZ+ov2zKiOL6l1E07O5QKCvFh0noW5cFUrlotl+4zcypxHbzE014LiGwXgBigMV3PBBfRgEAYsnrvbJCsKsA2AGyXRb//cAdpkc+17vQci28TzirnTymvjnGGwUdr7mjxiM7o9ag7kGVwsMbG/XO2bmDtgwUUNQ0qwsdlM5iKnVsAzq5fqehWXakPjbC+TshV71KnzIsG1kTF5eW3VinkuWC0HbFzkSIGt4JhtfgAbJ1LakxH/zWbt867lPbOYiFw5ALznPe/GNddcjbvueo2tj0gRa/blqaeews/9wgdx7vy5AC8pca0NLuS0LcikPp7T9NLBMHkxt/cbfaxWS73ndXeDaRdVqyV9dwYSgAcQyOXWmESqzcUHLkSuvSEkncAk7YNybwcFPXrja5/HxH/dOk9PSfSuNa+35W7CFxd88fj7cnPnuUsmcT1OB9lm+C1ANk/GRebc+jcBDXGYAc8umFwxJInqnKoVb7jnHnzg+74PR48dvSBQqP4M9tZrPPnkU/jMZz6D/b01jh8/DgDRhkS1BSqLFy9Y6eOmMzIu9OLBjFIq8pCCg9s6pAnEhNfgyJjiLaUULJdLTFPTB+aYzx6l5rjbuBrKH4cRFcDOagfwMWSmBK+TXgSNbnNmaswJCS6985LiefLnftNvc4MGu88Rb0UM/uz7+evz2l9o87/SrW75pHEdB+g2UHrQNwj+fpuy8msV5uPaq9b7+1jkjOVy5UY0BUJW36h4XZzfecixtlKyTd+6HhjPPI5DbNRbj929EmYk0HixczM5VzN4lkWinhPdNgZSbYJhGHHNNVfj0KEdfPu3vx0333QTDh/asetTk5m0ddfSKZ9//gX803/209hd72F/vXGd2hmSsvVPk5bHG50ggDDItRQcf+4FbDbTi/IHlwii9UKAKlAtUb1R3HUM8YlAi2wHomBX1Kovwkuhpe20lixjLITICIBE9Y+IQOcuMNcVHfSf3/980LD35+XRB9sEEmWirBlnq+UIRnAzdrfXdiBAk9Ec1H7lvbJBJKXiWjCwYBgHyxjwST5NE774xXuxd+48/sKP/xh2dnaMNomT2iI8tFzitXfdhde97rXYTBPuu/dLOL+7i4ceehgPPvAgSilYb0qUVvJ+INlL+BXjuLTnVIslt7uLWapvqjG+xnOqOOfqG94wDG5kzX1MUjBtbEGuN5vYDGPj6zZHodF0iiWPluZTXVnNMCFFSHJE9tuGB6dxmlCLfWYbd+JK0lz24IKYQFXL1Ei8HmDbSJsrEUbQxF+YbNT42vYziwcaPVXUskiN0qAEo2UTEE36CX0j8HXk5dGBznqaDQLu8KN3nc2uKYDu+nNO7jWZxis3r+rcdQi/uBFMycYkpYSm22JeqsiAXg2NdgHovVMLQm3Wm6DprKtCwmq1wrvf9W4sxwXe9KY3Yrla+eNwcMTqOt90SBedOnUaH/vVX8Ppc+cifmCZC7ZWBb3kqeWYA+yDxzF4acB6ySDaN7/x9TbAXW08J9NWFD95VVGgB4lcPd5JX1lGt44ImInQvZsfr/Pflbl1vuXB3/UGk0dvgPtFcxAp8zNb4K7GQ+TnQBrqTGn00sYaxpMBHsD1MNW6gy4WC5+UGoa8jQEwOPJl186cM3IacPvtt+BHfugHcfTokZaGJm1hqwKSmxYDYC7ltJlw5uw5fOITn8Du7i7OnDmLvd1dKFx3wVFvKQXztPYyUzgllIxv1Zbmk5IVRNRarejCjd08TZ6uVhzNOJfJnNnsVJIvOmZmVM84kSQYxwWWyxVWOzuO7PgMtsuMiT7p7kPUe0Wxf5k2uqebIKQz4rNAPQ33tGrr5Mq8g0D8TgmUauI4NNPq7rKJ6zQKCdqlvkUsoKMMfC3UMkcbF+7Y7EaRU44S2UL32ceQVWzr/TUOrVY4tLNj89+FhYpz4UR8kCbrOUT1oHecrt2a9I1rubSgVB4GKyIID2UC+3WRGiJQoYDRer2ObKFaFVddeSWOHj2CxcKaj47jiMM7h3zTgeso2EwK5O7Pg6BjM0/41x/9GO699z5D9Q4CWB4uKaPMJbY+6qXQC5nnGeNoVNmzz5/CZrN5UUR7yRjae153tw9Iz3G1rZwIqP+eOZY8GLWPqUy02Q1y/z25POodHMwMoKFkbh6RMa/NULGLDaftXY3fsxUHOTCgRUJ5b407Lh2tYUUCfZsb7e4zDwOmzRR5fFyL0zSFMY6ChkY2QhlQGhq6+5Y3vxE/8IH349DOTlO4Qo+6NFAKx5v/FwiqCB5+9FE8/vjjOHnyJO677z7s7+87ojGXPHWVen0pb6C8lDBkQ+q1lDAmNIDjsIjnxcVZagugTdMUKESrey42cChzwbhcYbnaMZWmtB0o4c5COkREWuWPezv8XAWsVb3z4n1DxEZN1XDHA0VyRPuNuKOXim8OAFCD92VwVuIxsgtCt69HJR+ANj+dwnCLDoDpWx2nqmKte/yajDqxTWK9P2G1WBgN5ROMLnrvyRk/bBxzuOY+dvM0gZKF5N45ZtGO3tfNYrHAZmMyhYvFAvv7+9YC3Oc/RWsW44gbbrgBd7/2tbjh+utw16vvxHZFaZvvDHRu0SuqkQY4zTN+9/d+Hx//xCewmTaYZgMgU5mbJ+z2A9qCblz3zKYxKcYZz5x4Huv1JW5o3/j615rx4mRT9uxqBo8T04wXnMNrYiSM2AMN7dpfxBFF9d1225By0vTBst4YcqenEe5fx6PnaA/SDMB2GS9fD3U30q+fr2OpI40SjUH0XlLbaa3Bom5tBKRCqmogRGsD7gGTakUO4ziCeZCSBMcOH8Lbvu2teMtb3oKrrrqqezrNsPbapw0tOcJyznkzTTh/7hz212t87nOfw1NPPonze2vs7u6iVqvw6Sd+cKkiGIZm4Bvv7LmRyXItJ9aUC/lyCZSpaH2gVL3U2g3IsFgi5QHjgiXKHHPnVyVyL8BuqhCEmA2NccQPQNc5xwaI7pn37q+iGc7qmz3nb3trp97mL6CBY5iOryOakmTc+DRPB+gIGHoFaSovdpDu/QbYjZdVe71Zc3um06YYmlUraR7HMTzH6qi1vxZ7hiATEn+r83bK3ZCHEJcZx9E9RbE0v2K8eV8lmVPGsWNHsbOzgzfc8zrcfdddWK6WOHRoh5Nui84DAXy3Lvk78Tk8zzNOnjqNhx56CP/m45/E/noNiFhl5DBg4wL93KTFvWbzINpGk1IO6dScM558+vilb2jf/MZ7zOX3tBHCd5vj4v20ZEskObniOqt06Lb0SmB0zQAEorSMgtaaBmgTnW53FCQ4MuSi6l/f87H2S3ggYLsO5KBRbq/XQCyxUAAPPBgSPtj0jded0mARVzcYnGx9cABo3Ve5aZg7P2MYFhE5t9YeM4Yh4eqrrsI73/EOvPnNb8TOzirc26Bq0KiP/t6aUaEXon7ejCefehoPPfQg9tcbfO7zn8fe3h5ahRE6CT1t/GnnIkPRxEfcQuWUWyWhbIt6NHQmgQqHxRKlViyWKxCJEwmp2phnEU+R4v8A3k547+3Om0CM28EWAPUOFFtBH0dWqW3K4p/Rz4laKRETb/PP7KsJJcqe+4KcCMR58QGEz4ybNAKRqwdPSe8k36goWKQqGJKh/81mg9Vy6dSbhKRmIFu08tweREsYJ8usMQpg9GutGEfrSZbzgF5kiPd6z+tfj2uvuRqvfe3duOaaaxzRl0Cq/Rjx5z4zKDYysev72tcewKmTp7Ber/GFL1q8IXmmBIDQ2w1hKWl5ucWpsM1mMu3mQjnX4nRYxuNPPv1NYGjf8Hp7yHRvYCo5NAZsCQ0glHikQ36sPwYQ7hqNAI1tQ7mdy+hHbxyJWOETMqVkXVA7eoDRcUq4Mb+Wk6Q3yFElI9uGiS1fePCaOOk5ackJcXc1oW3bjDg2W4ZWWh5t9o4CxdXRFotFTFYmX4/DYO1HRiuBzTnjumuvxl133YU3vfFNWC4NQSjqAalBoqf4TYuod38jeiy14NTJkyhV8Tuf+hSOHz+OM2fPYX+9D8uVzG54rdljdp1ZuufFA3lEq32wK/lzKMX46sZnep38YonBxVF4iTQGfP8A2TJyNCJ2DgS3l1Nz+dVvUjoEyjnUDJFufx6/dxeW18lnXtQ9BdCLaFQDs3GSp1yVMpuBCC+jdeNQ8LPb5mPzxbMLqrYNoppwuvrml0SQHPUWaDwb0gOkOVQ5hj5PvciA1V5MxYo1hTbmNGLzZoOcM44ePYKd1Qrf/T3fjUOrHVxxxRVYLBawjmltQ+sA/tbRByprVZw5cxaPPfY4PvXpT2GxXOLM6TPY3d3DcrnEZjNhHBdbHtZ6s4Hlo5vhr5VZLgus17YhTNMGi8UyPCca2mEY8PAjj2N9qXO0b3z9a42j1BquW3/FnCAiNGwAYIEgAbZ6D9FtY5M4UhDkC6vWreck4ETRmMAtYKUdMkCTy/NdlVVcdCsB25VZnskoLQ158LzSnbc2F1rB7rh2f9yp477g7n91zkgRKV5mUFuWBMcnzks3PTXVsZjAHigkGk3e9wyquOWWW3DXa16DnUNL3HPPG3DsyOHuudRmcOwXbshohBDPB8qotNXJK4DHn3gCjz76qKGwYu8hT0sNV5Zf8/p7wZlhSIayag1uTau59/M8YZptgzl15jzOnN/zzRk+JhLUFMSVubj/Sitc2Ea0DW3Hqg9baKNQvP23wJ7LNE0w7lNdkrBRC8Ul9/p5DhpnubCNtUhCUgsKF6di+gqlGPvOyLfPd6BSq+V/K1pPNKpW2cgACnzLPa/DFUeOQHJCHpmgZBv86VNnTB7TA5TMdqEQDQOr2q21hsrbfIAIapmxs1ziW7/t24xOKDN6L+2C4yKGFgA204QHH3oIzxw/jj/4gy/EJhPItHi+fG1xmv39ffPqqgnFDMMYSJ+e13q9jqyDnZ0d7O+vbRNQBtYznnzqGZzf3XvRi75k0rvIS6q2xVsYQFJEs8OtogL4AwZzE1uKj2Ue1K1JzIdsddpddZi/jzl1eRjCaAKIqLjxZzVcMxGxidoZXh7ZJ9o8h8lpoje1hotE8ijeq20RBpIKksmrZ1LCkAXzbN0C+JnmSlMPQXzCsJ1ygwK1NMMONISRa/Y0uwp4ylPKCc+cOIGnnnkG4zDgvvvux2o54u6778ZrXvMaDDljtVoxZTPGnwdtUApnwyO+ZQNAcdP11+HG667z9/nmdmCq0rD1BgoiEE3YWWXndoHAi77pVZ8DZa44u1+wweAuvRks//CuI4cgu1YE6Sgb/cZrtoMc5YUNQzXmYnOf27XbfWzTTmZ0In8b/JUb9KBE7Hv3pbayc6LgR+HtgrybSO3GYTJdilJKBA/LNGMzTZjLhPVmHcUwu+d38Z53vR233Hg9gNZmvqrhy1Mnz3beFSI90i8xNvqDh62jdi98HT9HK9WLHVR03pJwx4upbGO7Xq9x6vRpfPKTv4O9/T2cPHXKuHzXna6+EbENTpVWEET9CnZiIK2hyudrVFuU6RPxB+2ksbb6hqcHj0vG0NLtIgfJEY5sA3Vjqi3AQeQpAmT0SNc+y4yPu0ldOw8aBBHxKhK6bJ6QfCDSL3KhYYq25GhGl38LlzBV41tj19umJ7TW0M1V6BYdYf2qmsqWJKrI23kszcQWGTefnAeMoydUSwpxFUo30jBYxSP1BtAlmXsbdIrWFEM+VauNbSl45JFHAAD3f+1BiALXXH0V3vTmN2IYEt70pjd5AOXFHrBvCETVblwCC3fSl4rmQaAzcKrt92aYvRmgwjMCGrIWWK+1IWVoAmQYIasjUMDEw9VoAmvMaLq/yVPPKMnYTMWBBHuDvN1vGGhyOiLuhc8vZnijgxxRNYNCkMB73Ua5EmdCUALcWLYCb/SMuqKb+Kz+NXGOtgEH+lTB2bNncMWRJcANrnjuOhR19t5yMSAxCo0r7Q2ktMBZv+EDrFyr1jio89r6sT14qCpeeOEFPProY3j+hVN44IEHcObcec+vXUPEMhfWmw2Wy4UXTjhd4XoYG6crGu1mBjN0d5X52e1ezLgOQRdw7GqdW9ffixyXjKGNVC2fa9aSx42pBy44EaoLq9DIsjzPUI4Gz5k8uT92fjVuKWtC1TlcWD7Lvkc9ORozpP5358H4fZSMohkDEuiqFaIMQJnegHapZAmCAmlBi6qQQaJKxg4uQ6aZOB+bEnIWTJu2sTC7gB0ImIuoqpin5iYZNzuFsbAUFXutFQf4RjSzZj/HhsQ8SUk5FvLpc+fwWx//JADFl+9/AAmK1732tXjjG9+AJOLyhR26iUwFLqiANwBaWWyLjvtG0y1cfrVE9xoTXFG7z5J4VYPIAq2GXqyEGDFXsiRAFEnVeovRavKhbp27PxqKlq2XtNcK/6B+PVC4NFd7Da9PaES3z0YECEG06270xYsdFxKaQSX0e9iW+0B+ROlAOTPS/mNGy5aBdrRJrTB012rIv/9q9x6rSPx93ETF34sGtgDFPM3YTDO+cv/9ePDBh3F+dw/PPnsC4sYwgI4XPMzuPbbKT9e5gD3vYRwt/SwxF5Y0QHZu1sRvZq9Ws0aOEvQB0x2b13GRx+DHy2JoReR9AP4+gAzg/6uqf+8P8z7yqQCQ4K48hT3sk5HFJqM9OxYitGqYrWiktiBFjybb4/MAVm0PipqaWgFN1aqxwlBXZGkIFMpWILr1uSLW514q1afQ9aLX2EDM8GGrMaIp/3ttkpokogkHMVLdzjSX2dGqBk1gn8PAXXNPiVq5a/MzcjbJOYnrabq/8zy7xq1NqP399dY5TK6S3HPGY489gZwznj7+LH7r33wcV1xxDG9/+9uxGAa84Z57IEJ4cBC1+ILvXWd0qK6HCp0hi2BPla2f28tYYdfyP6ep4Nz+rgnMeHluloykjdtnZRgXfHC1ve09cAfbbEdvZLs8zgvep/HetunQILcNZ2vz8PGLO+4RfveVLi5Qu+vn6y+8hnYXTH00Ty6ltmm16/Fx6d5t82p7LF7c9hBJdRtBB1J6JF9qxeOPP4HTZ87igQcfxCOPPOo2wkBDqYokXqodc721alftG54q4G2yyMnSm21eQMt6sNe3rtcpmUYDCzVYmsyg3uypXxc7/sgNrYhkAP81gPcCeALA74rIh1T1vq/33pySNZUD3IC6WAzzVn2mG0BgapQ1ZAPgqv2ejQDjdVswC75Ls8UxP199bvtnIAF1DqNGQ1KJwA5MerrCbCBIzq5vycyH3MpyW+PFCKhpS5Vh5kU9SFaCYwMUqViulkBtmgfWaM6kB2uxCcVUIFIH40gtV/sX7ZvRibp0liXlHBREtBIXiZLfwUW2LcBmgb79tfGvu8+cwId/8SNYLhb43c/+Ab71LW/C61/3WqSUsBjI1XXo3RdgB2T6v9pXoUEVAAUFCRnNkML/5syfVWUl6lP45uptdpDcc+Ji40k726Iu1X8wLnMhJ3vh0bvMDDj1c41jzCmlcWouggue/Iv98oKj54j76+sNyvbr2/cxL33sKelolWpdZduBh9QXVmjHF7dtJDHtNbxUfsQ8u/6wf87u3h4++TufwQsvvIDnX3gB53f3wlNswWQDK1TVKgdE7YFWzQZ42iDclmSrquRrW3qcBcOYn80Nh3OeynRcN6UUrFYrL/556efyciDadwB4QFUfAgAR+RkAPwzg6xpaoO2TIgnqUfBwVbQtRqiaGyru0gNIeUDRaopQ3tCN7gvLeCE1FPKzACLG4bG1isRiqOEm5Zyt1bcH5GzmscLEz+MLF04FpCTIGADpIsdEA9LhUrrI3QYSx4F1RSSccwKKerI0iy3sxVTbmkuJ/kq0CSmZ5mefiZBzCjF0rRpllsvl0nbqeTYvAk21KA02eXd39yAiWC6XWK/nQODGVwnSkAJpP/X0M3ju2Wfxq7/667jp5pvw6jvvxM7OCsvF0gtCFOfP7RrKgILiPQks0DBBmOAAq2lCXHHlUVx57AgOHz7sfaRSLA7hAq98ZN1G7YaAXr0ZFaIXcQ6ul/qLtX3B0QsIxaPrkOVWuqBH+7fWpVtabn+69bWlh3F6iPToFHGeFzv/tmF1I8o5foFx4PjYnLz/aw9jyJauxZTBUky/l6WosQx9YKxvm99P8nJ2m7yW6iUtS0d8bd735ftw4vhxqFpJ9Xq9hqQBa+dRs6db0RMrapKg0+RFD1Gk0oSCVCtyXth1SANAzC5YLJfY3d31knQzxLQT5s2VABaAzafB24qPQKPZAKhYWmrZypvePl4OQ3sLgMe7n58A8M6DLxKRvw7grwPwflSTGa1CLqi5RuQNqxs4Rd1OY+KDJgqhcXVUau6ET1thaIO7ExO3JVBFpfYrDF1UomIAkhoCoUvOhSDU+/TE7SDM/cFDkjeIMx6QxsTHAxEJt7tAVdsAzMA2lJNzwnJYYL3etXMlqlFZQrvpDCSo68RSKIPN5RStB9c0zf5z2lLg2tvbDwRsz6FGvX9xioMol+4WS+9LbdVDhehRrFRUIHjw4cfw8KNPGN9dq6WVAVjvW8I4+fdaCkQFKZvJXIyjj6W615Bw5MghHDp0GKudlXVQ4JyoTfqyzDNuuOU2XH39TdjdX+P87q5V0uVsSfnu5dCdpKHmLmdl1slV0baNKCmXqCQEAiXt+nmuuuoqy18uTPuC3Qe2Wyr1NWCKA2Wu8b2NcZ+zzWvhuWOi8LsDRvli39s1ABDF/u4efuXXfgvPPfscchIsF4vmKqvJCHANarUdSFFMxtQRK6k9KCCD6ReP7EoAtL5z2vX2841BZEKpikwgw2fuKVrr9cYAWKGYOTdnU4+zzy3d2BpyLilZZoMHoWcv9+a6tEwGDTpAgNAxRsqWLqgVUhgXsb9feewYnjlxEhc7XrFgmKr+AwD/AABE5Oy9991//yt1LZfgcS2A517pi7iEjsvjsX1cHo92XBJj8QROAMCrLvb3l8PQPgngtu7nW/13L3Xcr6rf/jJcyzflISK/d3k82nF5PLaPy+PRjm+WsUhf/yX/1sfvArhbRO4UkQWA/wDAh16G81w+Lh+Xj8vHN8XxR45oVXUWkf8tgI/C0rv+kap+6Y/6PJePy8fl4/LxzXK8LBytqv4ygF/+t3jLP3g5ruOb+Lg8HtvH5fHYPi6PRzu+KcbikhCVuXxcPi4fl48/zsfLwdFePi4fl4/Lx+WjOy4b2svH5ePycfl4mY9X3NCKyPtE5H4ReUBE/s4rfT3fiENE/pGInBCRe7vfXS0iHxORr/nXq/z3IiL/hY/PF0Tk2165K/+jP0TkNhH5DRG5T0S+JCL/kf/+T+p4rETkMyLyeR+P/7v//k4R+bTf9z/3jB6IyNJ/fsD/fscregMvwyEiWUT+QER+0X/+phuLV9TQdroI7wfwBgB/UUTe8Epe0zfo+McA3nfgd38HwK+p6t0Afs1/Bmxs7vZ/fx3Af/sNusZv1DED+Nuq+gYA7wLwN3wO/EkdjzWA71bVbwHwVgDvE5F3AfhPAfznqnoXgJMAftJf/5MATvrv/3N/3R+34z8C8OXu52++sWhlb9/4fwDeDeCj3c9/F8DffSWv6Rt473cAuLf7+X4AN/n3N8GKOADgvwfwF1/sdX8c/wH4BZgg0Z/48QBwCMDvw0rYnwMw+O9j3cDSKN/t3w/+Onmlr/2PcAxuhW203w3gF2HVtN90Y/FKUwcvpotwyyt0La/0cYOqPu3fPwPgBv/+T8wYuav3rQA+jT/B4+Gu8ucAnADwMQAPAjilquxr099zjIf//TSAa76hF/zyHv9vAP8nNPX1a/BNOBavtKG9fLzIobYl/4nKuxORIwD+FYC/papn+r/9SRsPVS2q+lYYmnsHgNe/slf0yhwi8gMATqjqZ1/pa/n/93ilDe2/iy7CH9fjuIjcBAD+9YT//o/9GInICDOy/0xVf85//Sd2PHio6ikAvwFzj68UERYY9fcc4+F/vwLA89/YK33Zjj8F4IdE5BEAPwOjD/4+vgnH4pU2tJd1EdrxIQB/xb//KzCukr//CY+2vwvA6c6l/qY/xHTs/iGAL6vqf9b96U/qeFwnIlf69zswvvrLMIP7Y/6yg+PBcfoxAL/uHsA3/aGqf1dVb1XVO2C24ddV9S/hm3EsXmmSGMAHAHwVxkP9x6/09XyD7vl/AvA0gAnGMf0kjEv6NQBfA/CrAK721wosM+NBAF8E8O2v9PX/EY/Fn4bRAl8A8Dn/94E/wePxFgB/4ONxL4D/q//+1QA+A+ABAP8SwNJ/v/KfH/C/v/qVvoeXaVy+E8AvfrOOxeUS3MvH5ePycfl4mY9Xmjq4fFw+Lh+Xjz/2x2VDe/m4fFw+Lh8v83HZ0F4+Lh+Xj8vHy3xcNrSXj8vH5ePy8TIflw3t5ePycfm4fLzMx2VDe/m4fFw+Lh8v83HZ0F4+Lh+Xj8vHy3z8/wBxopq5eWUJkgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "utils.show_on_map_array(env, traj[:,:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xlUOJU4nDpCXepLQjeJEzCMMeHkIK08cU0E5jGtOYxjTWJCytW6BqXL2yM6BgrmQFXfKwTynXamsfxDbLqsINZAQFUVZoYiyVFSClGCEAqd++lEKXIr5kXJIHfts2qx7epWSKkzR6UuApD1tHCI0O0RhLcUgQsGtpZimmcc5BSmQg54gLkmZNOWuFuKS2k4EIteIqIVRrrqZplX30OC9yjSY4zjz9NK644rHMDFoee/nlDGekAC6rHrFKXBVXZm9MpRYr5cK461haXuGz117LgYOH+PKXb6CLfeFO0esQKDWzHlVbHLT4TNjRTFZrMDtGQY6hhDdm9+WcMJ45y+Ikl6IA1lPtTp0tQORzTu8hO56Ao6zsrKv3mF48ki5cehst2SbnVDWqRXXVVVqgxVsZvS4GfRWYm57WwOykZ3KtzdIsgQHW6leME92td2JzoWMSCJrlvJ2Twqk8ommbek5Ft096D8TY0TQtIG4VTSOFVyH46kPrnCfnKNC/yLXoumWW9+xlz5693HDjTTQhcMnFlzA3P8vjrrqSjRs2MBwOH+C3a+B2Uk9MlWjs2Lmd7du3cfnll3PjjTfykY98jMNHj7K8YtkQuQll8Snz4c12rZRaABpCo1p0WcjFlEgP9OGdiCmgncY0pjGNaaxJ5CzgtORMKuqVmosWDynYbAIuKVNqXppq+wMwGAyUeYVMEQZInQdMbmA+mEFT/LWmXq2AMJ1mI4xqimrFpeDN0qGtHUuBnRSdCbBqGmFe23YIOIIyc6ZNFbshZ9VCArpC/xCvx1HQ6lQjOx6PK0C3NLCdl7HE6PEfc+EF/OjLXsr69etEPmEuAI76tLdCnBqGSZ3jlltvZd++fVz/heu5d88eUipatJdWsWelFEITSCkSfKgMmoAsaFTvORwOxYKsbRVDa7EbWjSk2lXRIyPp8CwaWnygaXxNzbsgaWsZqoMJb2CRTlABsN1bortUplnPoQJlbVbhcNUv2CHNDIRRNT9f5F4SrcGkkLhnFxW5ZqNW6bWeOed+UeN6llZAei8nMXbVLoq5D4j0hMpce+d1kScNOGQIhXYwqHIc5yDGjraVRY/MC+rBHGmaFudCLTK0zINJgK7/0pdoQuC66z6Pd56rn/AEdmzfzqm7drHr1F1iuFYMiPbaXLPDk+sD69bN8/irr+aySy/hwx/+CJ/93HUcOnyUpm3Ixazf6mxWHXHwoUoSigJ+0dX3zPpDxRTQTmMa05jGNNYkiupnDdgaAKyNCrRoxAAUzjSHPSgzPZ5TfWJNX8sBaNq2N4U3YOOdMokZVwzc9jIE76xTllqAKRuXzGvWi0emc44SbbuoFdqxssJSbDaRolVtsIGrpggziYPUCaCKlZ0KtUjGWL+UkrKPAhykuKYwaBvOPPMMfuSHX8K6dfM9WHQ9K20pXh9Ua+kdJ04scPTIMa6//nruvPtuDhw4xNLyUrVhct7hUl/8FbRpRGik4MdAYavyh2Sfw5o2pJoi977XP8q4tJtZMe9hr4sIGfNYHSocvUG/bNczobLPvsALB7kkHL4uCGxxkFKurKtJNIzpRcfsdHGFzdkEi6t0KQUTmfZFbNYIg5pGL6A8q7G0BWF7czYvAgOtEyl31y/k7Lht07LSScOPlBJRC6TsmpRCvZeLl/lKOdG2LV2M9JJr+y6pXpiioBhKSeAbXBHJCgjjnrIHl/jEJz6J8575uXk2b97Mueeew4UXXMDszAw7dmyHklUT7sV2TXXgpjuemZnhWc/6AR5z8cW86a//hiNHjogVXikE5xVIZ5Va6PfeiU9z/fehSo4e3gFlCminMY1pTGMaaxKllApqU06iU41RmMVCTb/XVC6qcwweV1wtbDEtqfOuNlowL9qsQKYJDc5JMZlVTANVD9tF2d5AmKSycwXLBjQNONs+THObkiMEYXdTSnh6SUXwIiEQiUQmJQFHKyudFvr4CqIMSFtMuh2AaCiFeBWQ6L1n546dvPxlL2XT5o1SEGaV+8YIgjBiFMajMXfceSc333Izd951J/fcfR8pibzCtLBiN2bnFyoYjTHhvVvVNUqq4Iu2VjUbMa+V6uCcGkolAbJF7Z0ETBU7SVLqFBgnKY5CQaGBUJVNYOemiwPvMs6FnvlWSQgFva+E2XMAymgLQ5qr9MLAtCymBKjmUnATfzd9sRG1BkC974vFvC4wLKVepSMlVzkBev9UQCzQspffJPOZFbBvhYrGBFcwq5KRUoo6W2hTkdJ3i/OhAZcpRdoJj5fHgp91QZg1lQ9ZQLiTuWkah3OBLhaRWDhPN+44Pj7G8ePHuevuu/jABz7I5s2bOP/8C9i8eSNXP/5qhoMBMzMziA9fL63w2nnujDNP5+Uv+2H+4i/+iiPHj8t8N46SRMftnad4uQ5dN6qMtcxz0IVJ7zH9wJgC2mlMYxrTmMaaRC6F4kp1LzClKZSqu8xZ2oLWgiPdyDsP6hcrJu7KsjlXQV215wrClvnQEKwYSB0VLO0fFFimmMT+S9nBAhUQZ2/6UZNHCEtaW/A2jQLu3nfTedXJ0rfHNW2upWdj6khJ9wvK+olNWEpJZBUKrtq2IafIzMwMKUY2bVjPC1/wfC3kEZasZ3EB7zlx/Dg33nQz+/fv56Mf+7hKKXIFRVa4pfy34bEaIgkoxNiJh24RPa4U2hV8CfV6xGTgu4hkQIvOzGPU+1CPXYuiirXdzZVx71P3AuZccTQqLUDZ155NpYJDkwig7J5hP/Rtk6uYs0EpBV8SbYG2FGZSpi0wyJlBKbSlMCyFpthZFS1UkrEFPb542DrGDsbO0znP2DtGTn7G3tF5R8Y0vSiJW+RXksIxHWZluicXD2ZZZx60MUVyygyHgypZsMJHVH4Tgkgh4sqotrPNOdOqtZk5IpjFmUlpSkm07YAuRtJ4rFIHW1B5XPAsLi7z+c9fR9MEPvaxTzKcGfDkJz+JTRs3csbpp7J58xaxzNPr5bLjzDNP55Wv/HH++M/+nIWTC1jnOR0yBS/WbCHIAstkGQU6Lap8uJgC2mlMYxrTmMaahPMCghzgIr1eLpn+sWhnr753fMmlgk8HtVgK1+taXetqqtpeNzCZUhKNp3eUFIkxymdwuEYY28ZpJ6OYJgp9qHpVAVOlMmIllZqCn2TRHGiqOBMnupeZubxIHJzqGDtGoxGt6k1jlIKy2to3RgZtS1ImOcbIzKDhh57/XC44/7yqWzRWNubCDTfexCc/+SmOHDnC4UOHBdAo0LMCI4Kr8yrOAICXxcagaQW0t40WHXlSFm2m6FKtmEcss3KJVWIRfEMuETGj8JRM9QY27acx4aafjFG8TIfDAYNBU9P3PjvWlcR8yqzLmXUlMVtgNhfmS2GYE7OpMFMyszkzm4v8LoXZ3L8+oz+zuTCcAKztV9FlfrMjOsdiCCwGz1JoWAyexRDkz03gpP59oW051jQcCYEDObEvRo76Hq9TpONWGKhdGahXsbC2425UvzcpSTOPxpkzgt4nVaqT1UKrq927nHOMxys4J/69ci1C7XxXJQA508VCzmNWRiu8+93vwTnYtHkjL3/Zj3LmaafXBYYx1Keddio/9Y9fxdvf/nb27TtI9oUSrfArSnGkap2t+YnJMvK0KGwa0/j2jJQTK3GFlbjCclxmJa5w1sazaEPL3cfu5itHvsI4jRmnMV3q6HLHSy9+KYMw4FP3forP7PmMvJe7us1/esZ/wjvPG7/8Rj5054dWHa/xDf/r+f8LgDdc9wY+de+nVr2/YbiB33r2bwHwl1/6S245dAttaBmEAYMwYMvsFl51+asA+PBdH+bo8lHmB/PMt/PMD+bZNLOJ3Zt2A8KETBqvT2MaDwynld7FqkqysqKq5ctJUs/mMeu8J5ZUH6aOPu3unCOVVItnJi27gg+SMk9JWFuk6AsHwUlRU2WBkdSxD57sc2WPJpmyoO83+gjNORMarepXezCPaWcFVDdtQ06S5u1b/loaXs7GdLPBC4iPKdUuX+In25jEEFfgB575TK688kotrjLmShi5z33u87zpzW8mF8d4NBLNr56L6BelirzYQqFYpzWZv7Y1D1ePVcunlGmbti42zEPVOWmI0bYNXTemaaxbFDQpsyFGNuXCxpxZnxJzMbEuF+ZiZAMwnzLzOTPbReazgNb6O2Xmvg7AGYFl71nRn2Xv6p+Pty2jEFj2nrH3jJ2wptF5Oi+M6liZ1c57OucYO0cMgex7ZtUWSiIXMHGEJzhhdptcaEtmkAtNzrQl06ZMmzPDnJlPibkU5bxjZPO44/S8wrqUmI+J4cOcbwaOBc/R0HC0CRwJgf1N4EDbsr/x7GsCB9vA/uDxw2Gvg/YqZ8mIFAAFxuq04XC4lFVS4u02YjAcYjZk0tyjVFu5nKPocUsB1eLagsg5z/Fjx/nrt7yVl730pZx5xun17jS5xGm7dvFjL38573jnu7j1K19ZVVQo7GxveZa73rd4WhQ2jWl8A7ESV9hzYg+L3SKL48X6+3tO/x52rtvJrYdv5S03voWlbonF8SJL3RLLcZn/8LT/wPlbz+fdt72b137stRWw2s97X/leHrP9MfzuNb/LL737lx503Dt/+U52b9rNX3zpL/i1D/7ag95/9rnPZuvcVv7u1r/jNz7+G6veCy7w60//dYbNkOv3Xc/f3vK3fVEDMAgD/hcCaL+4/4u867Z31fdKKWye3cxvIYD2b276G95601tX7f/sTWdXQPufP/qf+cCdH1j1/mU7LuOLP/dFAL73Dd/LdXuvY34wz1w7x7rBOp58+pP5oxf9EQCv/ehrOTk+yaaZTfXnnM3n8PjTHg/AkeUjbBhuoPHTf6a+Y8M5xJBeWsIa+1JU/wgmJFB9ogPn+8IjS08XhK1qm5ZIVwuouq6r/rROGdaEpTGFMWraRjSIrWplY6TkVDWWjTZHcFmAc+wiqSTIokVsB60AYySFTdKqev28U52v9wJ4QtHqdQXdlmYvqhkGh2sM5AqLHWMUD86cmRnOkFPkpT/8Ip785CeJxEB1GPZd//znr+ONb3xzr2FUKcXMzIzMiRraN40w1RSZX5FISBPXlItKOXrW16rNKSKX2DKOnL20wtnjMbu7xI6uY2PMbEyZDSmxKSZmvwYYjSCspPec1J8jIXDPoK1/XwqBk8pqnvSy7bJ3jNtWwWtg5Jy8ViCoXroAxZnWtpejmHIlaUbA5UJQL+BJL125F4sWjcn9Y61tbTFWZQLOEfQaVFs578hF3DesoYFzov+1wjCgWoNZq+JBKWyMiU3jjk3dmPnlZTaMRmwYjdicEltzYVOMnLeywvfGxPxDzPGR4DnYNuxvG/a0DXcNB9zWNtw+aDigVl65iEbWviNiQ1do2oZkmQuVC4xGI3UQ6aUAznua0GinuiiuF42w8eA4fOgIf/GXb+QnfuLHOf30U0V+UARcuwKbN2/mZT/yI3z6mk/z4Y9+jOJhOBzQqX9violIrLpnifSgc63/nHw1tPsPGVdffXW59tpr1+TY0/jOinEac2J0ov7smN/BqetP5djKMd745Teueu/E6ASvuvxVPOPsZ3DjwRt55d+8UgBpt1iB6Z+8+E94+aUv5wN3fIAf+LMfeNDx/u7H/o4fuuCHeMct7+BFb3wR3vnKUM40M7zppW/iCac9gffe/l5+8+O/yUwzw0wzw2w7y0yY4def/uucteksPrvns7z7tnfX9+3nxRe9mPXD9dx97G7uOX5PZUfb0NL6lnO3nEvjGxbHi4zTuL7ehvabzoiWUog50uWOLnWkktgyuwWAe47fw+Glw6sA/2wzy3PPfy4Ar7/29dxx9A55v1vk5Pgk520+j9/4AQHhV//B1Vy//3pijvV4L7rwRbz9FW8H4JT/egr7F/ezeWYz2+e3s31uOy++6MX8qyf/KwB+/9rfZ8NwA9vntrN9fjs75newbW4bgzD4ps7Boymcc58rpVy91uN4JNG2bbnqystpmkDJSVvXRgGz2WyEJszW6QHVKrskrXq3AhyUkR1341r8UpsOqMWU/T1qxX5Oubfs0of4ZPvdaofktdOTd1r8FaXQS18zy6embYgKBpOywla85pDKdTsOzhG7jlJgNO4Yd2OGg0G1M2vbAU0jIKJtGgaDluc/79k84/ufTts0mEuC1hDxxeu/yFvf9jaOHj9B27SEJrCystLrlJ1UwVthW7U2S0lZZtX9mpWWza33bBmNeMrxk1y5uMLlJ5c4fdzLKJa8Y1/bcrwJHPOeE03gWPAcD56FJnDcexbahhPOsdi0nMCx3ASWSQT11I0xUYrolcfZ2gVb0wfR7VJ8LS6zRY65UpifLK5vFKGNYOs1Ny9Zp1pcEws7K0DzZh81od+t26I+tAbyPUWL3qSNshZASX682qYVva+M7bQ72/xVfWV6ZTzGyJMltX9y4QQ5p1VZAqAuZtaXzCkxsjMnto3G7Og6dsbEjnFkZ0qcMe5YN5GqX/CeO4Yt183P8Ln5Ob64fp7FtqlMbC5ZGzCoI27u7wVvwDclnAuiLS995zHpOCaLCPs+bNiwnhe9+IWcf+55NGqpZ1KeXKQb36c+/Rk++alPs3DipCziUlRv5qRaaLl/Y0rcu2cfXdc9SEw7BbTTeFTE4niRGw7ewBf3f5GzN53NM895JgcWD/DY1z2W/Yv7V237G8/8Df7NU/4Ndx69k3N+5xxAmMsNww1sGG7gtc94LT/x2J/gjqN38Ev/95f6lLmC0ldc+gquOOUK9p/cz3tvfy9z7VzdZq6d4/yt57NhuIGYIyknBmGwakU/jUcepRSW4zLHVo5xbOUYrW85f+v5gADifSf3cWDxAAeXDnJw6SA/cPYP8GtP+zVijrT/qX3Q/n7xCb/I7zz3dxinMT/59p/kzI1nctbGs9i9aTfnbjmX87ac9x0tg3i0AdorrrhMdKEp4iaKrSSdPWHfBRUGBB9IFeyUVT8GT5rQVJBhRVzVEUE1uAZavfOVyTVHBfGxVQataDct1zOVrWpLTZNaLawQGVHTSJMFkyGkKNtZJ7GgBVBt29Q6ppwyi0vL5JwZaqo3p8TM7Cxe2eim8fzQ857Ds37gmTRaWOacAKZc4L779vInf/KnHD58GBBpwaAd0MVOAIYCIAO0OPWMdWLd5NXOTFrOypxuTZnnHF3gGUdP8NiTS3jgcBP4wro5vrhujpuGLXcNWw41DT4EYooTbgauXjvTblqXKuf6qn07D/EKFt3n0igSgrSdLaVoAaAw+rU4aoKVdq7vJldtwXQM9iPvOavFUsApPKlztdNDXUh57ysjmxXZGgtrPrF46r3nMbs0V5so2HY2lj4LUeq4TUNs3rpWFGhWcsvLi4xHK3KfmeuBc9VebXJhV0qsVnemkyVnTsFx9sqYs8cd56yMuWBlxCVLKwxKoQM+t36OD2xcz/vXzXJE9dXieND0EhPDi7rotJAhZ0Johb2n4IMuNBC9++xwhic96Xv43ic9kbZtMeBuC8eUMtdccw3v/8CHWV4Z1X2P1YcXLKsB9+7ZOwW003h0RcyRV7/j1Xzq3k9x25HbanrmFx7/C/zu836XmCM/986f4/QNp7NldksFrJftvIzztpxHzJFDS4fYMNzAbDM7BZ3fQVFK4cjyEQG6iwfr78t2XsaTz3gyexf28pT/8xTuPX4vXe5ZJFvsHF0+yjtvfSdP3/10ztx45hqeyTc3Hm2A9sorH0vbSNW+POyTMoPaAcn5Cia9Ew2s1xR827Q1nV4ZVZMpGNAr6l9LDybH43EFHcGH6qlqgNmKYgryMBe7KmVb1T/WADFYp6pcAVmMUcCFAmdj6iztX5R57Y3/BSi1bcvS0ooAAyuCS4mZmVmZo5zYfcZp/NRPvoqt27biQz+G4hxHjh7jTW96MzffdIuckzLDrYKTcTfW9HFT9a2lSGMKad7gSDlWVm334hKvPHyc5xw+zrAUbp+d4f2b1vGBTeu5a3YGr2A9xlivhy0AUrWDEimDo2/pG7tY2/Y6IOUsDQCS2LZZK9nF5a4Wz1kjBbAMvzL1mK7SsGivB3ATC1fbrmdZqfsV1l9VpcbE2zFRRtbJOAWQGwC3LncKiE34oRZtBrbFN1V/q3ShKNC1bIPdv04twDBYpouplZUlFhcXRS+unxNWPff2bHreMk19ZsKs13KRNsQChLXJyHjMZYsrPHV5hWedWOLMcUcHfHTTet6ybTPXrpuVRh/aRtfaMRsjC+JB3DSt1kwEPe9SF585Udne4B2XXXIxL3zhCxgOh8Kgq/d0Tpnl5WXe8jdv5/Y77qrFmpPHGmsm4+EA7VScNo1vi0g58dG7P8qbb3gzzjl+7/m/R+Mb7jl+D5fuuJRXPvaVPHbnY3nszsfWoqPGN/zhC//wYffZ+IZT1p3yLTqDaXwrwznH1rmtbJ3bykXbLnrQ+7vW7+L2X7qdlBP7Tu7jrmN3ccvhW3jiaU8E4LP3f5ZXvV20wGdvOpvv2/19PO/85/Hc857L/GD+W3ou383hnZN0urYj9c6JD6UWhlT7LU2BggIHlSOUJA+7JjSybWNdlMQHU1LYuYKb0ATa0tbXRDPq6ns11VwlBakCmBBCle/l1Oshs+sLVkIjxWIlF5VPKOscS8/ahkDxHqeAPcYIpTAejdSz1FUpQFTwa40HfuAHnsG2bdtqdbpgH8fi8gpve9s7uP32O/FNqCx1donQyrmEIBZkIfRFNyF4culoB57xaIz3njOWlvnlPQd46vGTrHjH32/bzFt2buWO2aGkomOCnCmxbytrdlHeedEXayhxWIFbrv62PZiv9mXe043HgDCz9fMqASj6WfGULbVJgoHZys76CSDrJtzHHKDQ0yy35GL2alanjHHOWZ2xeo9ZV2UKpe6r5wO1QM57vBZdWbqggOqxSx2G08I9GXvfTMG6yslxZb9VZx0TBE8m90WCwVefYDmvXAv1Mqlul2MnThr6vXB6jtF7rl03y3Ub1/H7Z7ScuzLieYeO8cIjJ3jmsQVuHw74g51bee/GeW3TnFUy0yhI1TbB6gstADwSdYEnC0xZoOSSybHw+S9czzgmXvLDL2J2dlbuef23YHZ2ltmZAePxClmvUzceVYkOuf8uP1RMGdpprGl87v7P8afX/ylvvvHN7Du5j7l2jpdd/DL++MV/vNZDm8Z3cOSS+dL+L/GRuz/CR+7+CB++68McWT7Cda+5jitOuYK9C3tZN1jH+uH6tR7q1xWPNob26sddIb6qxtLkRFadoLGhlkrtbbyUUdNUPwX1me1BsHXqGo/HE6BJQOVkoYsZ0ptXrR0vhEA37irTmkuuFkjeSTexnHIP8ByrgK+xbFIZLl6hBnCk8EbBgG+wFqZdNxY/ei22mZ2ZYTwa07YNTdNw9u6z+Kc/+2pmZ2Zw1WVAdLd/+ud/wc0331JbABuKi2lMaHp/0VzEpUAsmaT7lFWXz4xG/Oy+w7z80FFWvOfPT9nGW7dvYqEd9OC95CoL8VoQNCkTcd4TvK9NKBo912r4bxKBYnZmcu7WvKDrxpVRTBjbp8Cz/nKVQXVq3WYMa21coJv7ovrroJNSei9V2zY4a8EqDK1DrrltMylVsA5bJmmYjKzHd5pNsJH2Pe1sDPIOhQqsjem1xVrSBV5RQLtw/Dij5RXatpF73eQwehSvLgYpZXKx9tCxjl+usTD/YYKptnvUpDG2+BjkzA8cW+DVh49z3qjjtuGA3zl1Gx9dP1916rb4C01Tr699z2onN7V0M2s2oEpILrjgXF7xih9j2IrTRtHv0xe/+EXe9Ja/YdSJhhYF/bZIHXeRPfsOTBnaaXx7RMyiN/PO85Yb38LrP/d6nn/B83n5JS/n+ec/f8qQTeMfPLzzXH7K5Vx+yuX80hN/iZgjn77v01y+83IAfu2Dv8abb3gzL7/k5fzMVT/D95z+PVPJyj9A5JQoypDWblimBcyFTK6gQLbPZKeOB0y0/DTA5DyRqMUrXrSuCg5iF6skYBWwbUJldWsHJQSgNL6hOLENsm5m4tGaK/gIIVSwY8A1p1xBtnce3/o6fqmYkV5YjlR1oyE0eC+SiDJRtFUKzM4MeNITrmYwHFTWEGBxZZk3vfnN3HrrLZi1Vqf+o12ULmQ9WEO6qxVp9xuaIGC8wNXHTvD/uXsvW2Li7Vs38Qen7+Rw48WebELH7J2nGTZ0XaxMn1dSLE5oHZsQyM40qA4XRLbRtK2C1kxwDW3riTGpBIG+4YPcBFqwhhR8JWlo0Fdp9Q4ETbVMkyYFxoaaJVVJxsgqUNXfpRSyE+BpLVhxnuKMZRYW1deGBwJUDZxVnaqrDXgFJNr49EoFJyLngl3+rDpTayDRg8xkTK73ZLWuapoGNzOUe0zZapz4xxrg80ENnbPphBvAqe2b7N4Ap3nP2tx2Xa6ShVIKXQi8Z8dW3rt1E885scQ/2XeI37nzfj6wcR3/9fSd7G9CdW1Io5HYv+k9Wb2atZFGzonBYMh4LN/LRiUuX7ntTr74pS/z+Kuu0O+9zOtZu3erlrvB+yILL+9pQysyJPt34iFiCmin8S2LURzxumtfx3//9H/n9573ezz/gufzq0/5Vf7tU/8tG4Yb1np40/gujsY3POXMp9S/v+Zxr6levm/4whu4atdV/PrTfp0XXfSiNRzld16U0uvxhK17ALCccDTI5L6AqvQPcmNEXdZiJ31gx058Zdu2Va5sNTAGhI0tYaJ9rVh9FQW42Wvb3KaR1HdXKiA0z1uQ+yeEQHYCZLvcVQ9d08qaRZh3Yv1lPenlHBMpZUaa9jeQbGByy+bNXPbYy2TOTLHp4EMf/jA33XSTpnh7TaZpUU1HaTZn5qsbghTWtc7xmvv286r9h7ljOOCfn38mt8zNiDxC58/0w6LBbEjqVZpirMVIKSYBYCnjgrGSpdo8FZ2D2HV9B7Mi3eC8l5a65oEr5+YhlV5/Sq+Llvumlwjg+/NujL0svbQAtOALlRYUlazkQnG6D9AiLgckAbzqCWxgFh2D6bl1UBXEKzpcJTUwNtPGJNpiuS4mR8G5qgvWk5N73AoNi2ipR6OR6H2NDdf7wyuYtQxGaPqCLpsHK8BK2rrYUveiURXf49A0/T7VPSKVwt9vnOe9G+b5RweP8k/2H+YtN93Bb566g7dvmJPj6fevCUG/J1678OXK2nfdGBAN7smTJzU70rF3715yfqxqpAskAcQ7duzg/n0HpVjTgDGxFnc+XHznlvtO49smSim89ca3cvHvXcy/eM+/YPem3Wya2QTApplNUzA7jW+7eOLpT+R/v/B/s/df7uX1P/R6FkYLfPiuD9f3a2p3Gv9vYRZLE3rAJjSERn9P6GirZjQLE2p2WPaQ68GbpxRHUpDcdR0xxSolaJu2OhrklOnGnYDYXCobFpxUt0tP+U6Y2UIFm9KlTBm1lOhiV7czkG0go6Z8UyZ1UbugOZqmlfG0bT3uzMxQ2EqnMgovjOoll1zCYDgEKvkIoeGuu+4FrJrfrJUcKeaamq9yDQU1pu3d0EV+75a7+Mn9h3nHts28+pLzuHV+dpUu1hYNk44Romntu0T1cpC8CjwHb3ZnfcLdXANEdqGpcd1HzoXBoK1gPnYJh4cMjWb0DPAKCPR9YZxzleS0gisDuM478YGdHInzwv0XlRyAyA+Cr406QFhGkw8UBzGnutgRsKig0U24NWCMrUorSu9Bi44hGTtqilp5UUC2bmdz2qksxo4VQmAwaMV9wLkKcqVZRqkst+lxY+zEW7nI9yInRynSDi74lkE7pB0MjMKl2naplARgXDL/e9tGfvj8M7hhZsh/um8//9+9h9ngm3oNkn5XYozSLlfPuS6IsixQbNyhabj55ls4evy4yjVkzgdtywXnnU9KUccf+ytXegb4oWLK0E7jHzxe8dZX8OYb3sylOy7lPa98Dz947g+u9ZCmMY1HFOuH6/nZx/0sr77y1SzHZQA+eOcH+Zfv/Zf89rN/m6fvfvoaj/DRHVahTZHUrujuTMPoa8W96PWonbRS7pkaSc1LijKXjPdNZQRTpkoSRB7rqtbPeUdwQY4RxQMXzGrIqtWlCMda42YtZpKinlzN6K37UYoCoHPKFZi5IOn9TgtlYpRK7cGgrfsQ/Wgn2tHckXNm3HXVDeCC8y8QUGSdmHzgwMEDHDt6FNBxloxT3Sn0mkwDn7YgoMDG5WV+9yv3cObKmH97xk4+sGOrAGjVMZpfqoHVuqjAKvehaQQke3wvw5hkUek1rT5YARa1IEzeUm2vyitAWv12XWQwaPXvQccv/3MUdU4w7Sv1PsBpCZfpOembcDQhyFwUr4C4t+8K3lon98VmdtCssgMD9zgFoCaN8JPyA5PLVPdbPW1zHei13sZeUnoQq0oLZVDlug4GLaMVsXPr2Ve1zVImuNj23gq+VFagRY9eQbtXCYnpgw10mlTGfG4ndcO2IHPOsX828IsXns3P7DvIq/ce4qKlFX5+96kcHEihJSGQo32PXC+XcI7gHd4P6nspJ44eOcLCwkk2btxYsy/OObZt28agbVleGTEYDPrr20D6Kq1vpwztNP5Bwto/Arzkopfw+8//fa57zXVTMDuNR2UEH1g3WAdAlzqOLB/h+/7k+/iRN/8Ie07sWdvBPapD7Y+8r4wm+gDFqtKddVzKNSvbhGaVpVNWVwHr8mWMTtM0kubXVHSMUdwLYg+I7biWsjXG10CqdUJyWriUc98m17S+PvhqAWZsqBjDpx58OwE/XlO0SdvtRk375pLxagdmGkdXMls2b2R+3ayceAGc2Cjde8997Nu/X84nFyhBmV8RUg7aQT0/0xd77zkjJv7wlrs5ddTxL84/k/dv3yJz4HxtoWvAFagyDpFJlFopn0uur5mEI6fcp4QnNLG2KKmSj9wXEIkeulRf0+XlFQCWllewtsCG92oBWs7SxSwX8YXVQivvQtW5igLA45BCtZJ7qUZwXu24vGhmlfm3BYAsAkxNncD1955JAorJI6zxA9SFFxOv5WwMrXaedatdFnpZgNyj3rma8sf04k7nUre3znK1mLKIttaK5JqmoWkC7WBA07TV+SHnRMmJlDtS7nAuk4t0+Oq6SE5QsrDrg7ZlMBgwOzMjWQQFtV1O/K9tm/nFc89gV9fxZ7ffy1mLi3VslsUYzszo8SdY3BilgUaSJhopZz78kY9qoWeqc3vRRRdw+mm7GA56uZDdN18tpoB2Gt/02HNiD8/6s2fxu9f8LgCvuPQVvObq10xbmE7jOyKefd6zufmf3cx/+v7/xP/9yv/lstddxl/f8NdrPaxHZRSVBaQY5QGnRVtd16lUIKkfZf8gM3bVQGjTNNVrFtAuR6u7Ktm2IjvwFSDIsVNNkTehqTZR5oNp5u9S1R8mfEi1EEydDmJaXVVuTG/JhW7cVWBo/rbBhwo0BCDD0tISw5mZKhUAOPecc9iyeTNWoJS6jpQi99+/FyrjLIBtPO5lD5MPfwPpG7vI79xyF+ti5Bcu3M3nN21YVShUQaiBdQWgxnAbgBJwklZZb5m+VGQNyRSrExcbAcLZtMMC5CZt1VDm29rzgshabTy24MmlB6dQJtheHa8BSz2sNUkIPtSFEBhk1RR/bYBALdASYB9wTMhe5A1Mo2uLGnvDCrfqe5Pzo2Or2Dj3C43JotPJ8ccYV2UjJu9nH2QR1batMqE6V+rrWsF/ilKAmQtJF34xxer1HJqGQTtg0A6qBAbXXwsrROu6Thcj8Mn5GV597hkE4M/u3scl48hwMKj3k32P7Z4ZjUdVx5tiVCs6x8LCAouLizVDA8JgX/24q+Tc68IvVt/jh4spoJ3GNzU+evdHeezvP5ZP3/dpNs5sXOvhTGMa/yAx287y75/277n+n17PBVsv4ODSwbUe0qMyjGVa9YLpNnOf9jZNnz3cJ/V9BgRCCFW3aY0RTENrKVWvxS9NaGqKO2UF0VEevlbZb00RjGFNUYz/QxDgaz+TQCTGSDfuarGU86rJDdaZrFTWNqYO7wVgN6GRNrU+MB6NKuhq2pYzzzhDwTP1fHMufOaazwg4L5KW98HX9DxOmVUEbMUuElLkv9x2Dzu6yC+dtYsb188rsJE5qgU3Di2Mk/mvWl9tnFABsHf1M7VITwt/vDLMXguPigKRmpY3gFaETS9FGj3E2OGdYzBomZmdWXWv2PWiFGXoAy7ojxVH6Tb9goO6OMirgKVKKdA2uBSVQvQaYAHZrm7hSsG7slon601/S134SNFdr3m1u8MVAc09HyvOCuLcIL4a3vXj8TqGjDCvg8FAiwptjCZ7LTiXKUVaMedc6uIp5yQss8t18eVcwLmApyH4Fue8Sme8MNGIfV6KsTYAQVnhthWtbdO2NG3L7evnefWFZ7PoPf/rjvs4dXFZFjz0C6qo91aj909oGpURiNb8wIH93Hn3XfW+Ra/X5s1bmJ+bEyZe762eJn/omFJm0/imxdtuehs/9tYf4+zNZ/O3r/hbLth6wVoPaRrT+AeN87eez8d/+uMEMbrkPbe9h3M2n1Pb907jq4fTVqs5SRepRMGVjHcNsUgxTEDm1k9UhwPVBzY7LUwK2thA9aRBktG18YExtiYJMBbV2uFaKtfYX6eFRj1zVyrAnWTdpMjFk0shBLfapaFIpy5jCGXctVxLtskixxTj+0TbDhUMyGee8MQnKJPbs49HjxwlmV0ZGRdd34BAx+mDyDhSFLD47+7ay5WLy/zqmafwpfVzDHXOkqb6jWE22yepfg9kZfFMR2xznUvWZhR9N7AudqskHP1iRdsNg2A3b6CyYbLJQgiBMVIR71WrS2WPFRw6a/XqenhTmclei6sv69HLKpDVL0IcBnudK7WwzeZ5FXutnHM16HJSgOeUra2FcqYtwD6jYMyp7yz9uJ2zBZ3BXPQY9Pua2JPThVKpRZCoRKJghXXWarY4AZHeF5zTZh4qk0A/bx3jXO6/F9aKVorqQp8F0WIsn+V7Y5rzPW3g5885nT+6/V5+77Z7eOXZp3JoOOgzFSHQhJYYc+3ul3Lf1rqUzKHDhyeni0Jh29at7N69m5M33tQzt7kwGo95uJgytNP4psRdx+7iR9/yo1y560o+/lMfn4LZaXzXROOFpRunMa9552t44v9+Iu+/4/1rPaxHRXgE23gvwCJ4q1wXx4MKPCfcBaz6frI4yx7mOZX6oK0V95oK95qWX+WOUHL/4FVwa2n3h5IsiDuCMrsmhzA97gTIdd5powYB3l3s6sMaqN6gaOV5Sqk2gcD17N/Obdug5FVAzDnHJz71KVZGIwGWOVPIdN2IlHqZRNd1dWzPPbrA848c5w9P28FHdm6rxXbg+hRzoTpLtG1bXQ3MUQImJARWIFX0L/W8tBmCd73lGga2pNubpfhLMSmEpeYFwA2ahqzsoFcNaSZroZf8eFeq9MN76YobvPjfmjzA5AniMRtUM9vLKJxZv7qA8wHvA6EWqzm8a/AuaDvX3lPYroP8AQHY8qJee5OkqFxiklR0Vl0mn7X5UfVFDzgV3Yns2tXOXnbvmv8sBVyR5gUF0c5aI46mCTjfa5YlXZ/qdUhJ/t51iW4cGY/GtQV0CC1tM1C3jlDlB5Z5iCmK/KFIN747Bw2/eN4ZbEiJ37r3AEPnRQah39mUpStd0tbWUvjX6TkVPv7RT9CpHrsvAPVs27qlsuEUqgzpq/17Mo1p/D/H7k27efvL384HXvUBts5tXevhTGMa3/IYhAEf/Mcf5NT1p/KcP38Ob73xrWs9pG/7MHbKT+gv7eGLMnSW+jYAa7ZKBhprYwMtWIox9bZeyvpNbm9dswQYaMOFLN2+Wk2vQz+W2MXakQwEfAcv7gbGDKaUqsavjte0kVpoZVrLyvppwtt8P0uB+fn56tWaU+Lxj388M8Mh0NsxxRg5cXxBGMEJRgvKBMjsQcy2ruNX9xzgC/MzvOGUbbWyPSUpwslJ9JZuwrfWup8ZgAFqxy+bl/64PdNowN5Aqsyrq2yqYTu7hrVjl4KW4D1t09CEwPLyMt451s1HTtns2L6lsHl9YttmcYgoZIZtZP1cZMNcYt1sYm6uY9BmgnM0wTE7k5ib6RiEETNtRxOikMM+ERjT+BVaP6JlhHcjYUF90MVVxLtI8JHgkjCdqLTBebyDxkPwmeBFZuC8Mb4yP8Gusi7IgvM0tnjSYjdbABWoultrdWwLm8rQut53VloYO9pBg/eOtmn0mtm1kGKvqt0uloWIKguQY7dti/cNTTNQL9lWGooUYVLtuto9Y1IEY/ZDI5+5fcN6Xrv7NK5YXuGf7z0oC7muq5KBrouYB+9oNKrfM5PQ3L+nL641RvZxj3uctjuWbIzT++PhYio5mMb/U7zz1ncyCAN+8Nwf5PkXPH+thzONaaxpnLP5HD756k/y3L94Li9/y8t540vfyEsvfulaD+vbNqxPvQMt/Co1GY+mm0spJCe6UwOEueTeLsuLfjZpIRL6+ZJKzeRWzaMTWYLtw6ryU5ICJ0u7r2pfG3pwZqlj6Blis3yKUVv2ptR/Xlk3Sbe7WlxjmlPUtqlpgnYsE72kGe63ja+pWKf2UIePHuWGG26ojHDTtOTUVSeHyaYMUPj39+5nUAr/8cxd0AR8yjABXr33NG0js2Yd14InVmN/pABfgbqcuyNXXaN0fJMUssx3TpnGe7occTTicIUDL6C8nY2sW9cw8ODJNH6FnMfsO7CDpMcSBWvi6U8actEFY5xv8G5AzB1v/psR9x9suOTCMU9+UqDxM7I4yQ0f/eQcN9+6wNYN8LIf2QBlhKPBOc/9ezPv/WDHaNzwQ8+d49RT57CzinGGD3zoCHffu8jVj9vKVVdtpCTpIjcaLXPv/St84pNHKTie/KQdBD+m6yIpOpZWOm68YRF84bRdQ9pBq5IYKKXhwIFlRl1mw/yQDeuHtRlELo6VlY6jJ5ZpvGNuKGcds8zBaJzl+k60lcUlLj5rxOYNidA4QigUJ2zup65zLI3mgcKgHbNx05CTJyPLywVHK/eQ8710xHuRlKjko2QHSFFhyqZvVmkCIotpB9IKOejna+Fkyrxv8wYu3baZHz94lE/Pz/Dh+VmRF7hECGrtVRwD7RZm3tOLS0vcfOtXOP200wEDuZkQHNu3beW+PXt1cbq6eO6BMQW00/iG4zN7PsOP/rXIDJ51zrO+6o02jWl8t8SG4Qbe/RPv5rl/8Vw+dOeHpoD2q4SxpwbggFoMlkqsTI3oQCcq991qjWMIQRhYtNzGO7rcVV2l+NsKG9rFrn7WgObkg9nhxKnJ9YyuAeO+Qr/XS1p6u2176YK4LGgxTZH9SiGaAxfE+kqhVN/9yDHuumpxtHPnDi659BKq20ARBm8cI6PRqOoTS8nK3vVpfgPsTzq+yFOOn+S3TtvOvcMBrc6Vsa3Wwtc0vyKT0Hku0p3Nzr9pmrqdc+rhqnPSNC0pi6Y2xsggtLTNCrO+Y/PGJS67ZAd77l/gCzdnZkLmZc8bccr2WdbNgSPSeFhJLb/9+0ucWG5ZWVlWu7XA7GxmaWmZ9evm2LCho7hCOyh4Iju3tWxYB8ePL7Jzxyy5OGZnDKzDxvWe4VBAoMexstIvbHbuDOzY4bV4LDFeSQzaDshsWJ/ZuTMqi+mhrMf5wDXuKLkUrrryNDZvanEkEnByacxXbr6edqbwg889n9NO3aYLgSG4Ia9/3fvZt3/EOedt4znPvRhHIadEzI677jjE3/7djWzd4njec87GuTExwXjkeeff38bJJZMfOFIqtB4uuQAue4x01gNlPaPnSzcnFpYjbeN57lMDF18U2bt3hSMLhS477rmn5d49SyzFGVL0tYVuSrKw9N6TY8aH/vtlWRGnC7gqdXCusvvFFqKl8Nu7tvH4k4v82n0HuObc01lpNeuhzSeKc9om2akEQjISX7ntdp74+MczOzOs3/HhYMBjL7uU/fsPajOKUrXKDxVTQDuNbygOLx3mxW98MaesO4W/+dG/mYLZaUxjItYP1/Pef/ReZpqZr73xt2k45+4CFoAExFLK1c65LcCbgN3AXcCPllKOOvkH4H8AzwOWgJ8spXz+ERykdu0qWmFvfqQ++PqwNKBlWk5Ld1oaP5EquHTOEQjVkB0r5JrQzZoG18BZ0zS4pGlfq/SPHT57tddSHaYV1pQeQE5qTM1dwTxsnXNV81clEE2oHZ68D5quL3Sxq0b7oQmsm5ulCeK0YEVNAO973/vqOEVDqy2DJ6SFKSfImZ/fs589g5a37NhabZe8ebKqnEPY2V4yUM9vouLfivGytm5NORFCgyuJxg/JecTGdZnBcMihI56SIs96ZssVFyScL3h/P1/ZULj5zk04Os46fZahX4ZiTgEeR6ZtEqNRoW0H+GZIoXD4cGLTpsDxEx2Lix78gNhFKA0Li2NOLAwIzRxHjokoNiaHx1MyjMYNuczU691FcC6SS6S4lhjNozWQi6cg1zq5THEFnDSrcG4AblnmJGUoK1CWRX/r5nBuRorzXIMvQO7AeRlHiUAkl0QzgLYFH1qgBdcwGC7gcczODjjzrFNJ6QQA43EmNBEfGtGfqnsExbM0GtMviaBqDXC0bcPAR84/29P6Jc441XGGK6TSccWFmZjm+ct3Ntxz34poqVPBh0TwLZQs94Mr9X52Xvxjg5dCwKSdy6yTmX0PrfFDwvHa3afxhpvv5F8eOs5/OfOUel+a1t3ueRDdc0yJPXv2sLh4sgJapwmWU3edwuzsDCdOnhSnDKYM7TS+yfHP3vXPOLR0iGt+5hp2rtu51sOZxjS+7WKunQPgpoM38XN//3P81Y/8FbvW71rjUX3d8f2llEMTf/83wAdKKb/pnPs3+vdfBZ4LnK8/TwRep7+/auSStZgraQqdyg5W7aYCLQOJIFpXa9ySMSDcV/2X3GtnDQwaQKttPVWX6pwj+741qWkLJ7W5OWZolK1TKUHQ4jWn52FFYgZoDSw6J8VWQG07a40InM+rGhp4H0gp4p3j6U99ikguskoEciGRWVleVjmDVOYHL61Mg/dKnhWCCzzz6AkuWh7x78/aRVSNckpJQEoQds3hql9pzgJmzCnA5qOCeEc17vcOtm0JDAcjHnNByzlnDZkZjFleHvAH/+c42TWktJ125h5c9pQUOPP0eTbONiwswu13e2aHEELD0WOBu+47zuGDicXlUDW4Xq22PvW5xLVfnCNMtPYdjYd477n2i54bbg04YmW2l5dPUgocX2z40zctE7yCoxKJMbO0EsnZ89a3HWPYHpfLGQS0Hz1aSBk+//kFbr15QeZKu42tjCIrY3FfeOc7b2RutmE409K0s3Q5EHNh3MHNt+zn0KFjhDbQNkO8b1kZdZQMJ06M2bPnCE0w1wrPoQOHGceOcQdHj65I2+XgGY/HpE49kFXr6igU5/jEdfN88SaVCWCOC4VjCw3WqOFLtw44bZfDlZPMznjWr/fgEnfvWWDf3tl6nw+HcMr2OQ4cHlOKFnBpQZ3c+9IIwammXRqcOErKKoMptakIqv+9cd0cb9y2mVccOspbt2/i9rlZ0WXTa7Gl6M6rREfu3y9/+Qae/rSn9ucFnHH66axfP8/xhQW9Fx++9GsKaKfxdccH7vgAb7rhTbz2Ga/lyl1XrvVwpjGNb+sYpzHX3n8tL/vrl/GRn/yIVoI/auNFwPfpn/8E+DACaF8E/GmRp+mnnXObnHO7Sil7v+reahelIiyQFYBo+tMcC2qBEQiwCiILqNo/kxRUVlcKWqLqA+3hbWnUtm17QFf6wi+z/bK0atXbVousWMGqjEukAuZ/a7pcnKMbj6v+NZGqv62xnyUroJ6wDTO3We9g3fx8PQ4qO7jz9ts5dPiwVP5bUU5Qy6umURZPCsp+cv8RbpsZ8J7NGySVrLpj+YxILYTJpWpmrVlCF6Xtrvee4BQwB0/2UpT21O9dz1OfdCrzs5GYlgl+Ce8HnDiW2bTFc/Bwx0c+todD+8eMxg7ckJVxw7GTHaNx4Y1vH+PckFLAN4HCFsgR7wIxnSCUgBvIdevGgfG46DybREAATxc93YlMIeB9IZeROBMETxczh44k0RabUqUUUhYHgiOHtUjJgaT0hS13eI4vZI6fEH9XV7vYSto8lcIdd0Vhb12HY0XS9rlhaSXx0U8cUsAWdPGSKAhAvOnG+7n15j346rDgcQRKLhw80PFXb7xe3Amcp5BYGc0QY0fX9Z3tXCkcO9Fw9ETfVMNRwBUV3ASWxoV3fXhEyeD9kK2bG3Zsbxg0S5w42ZKKzBceztgVeeVL1/Opz2Y++fkxXQyUHHBNrvPsnasadfPADcGrt68WBU7IhnKMvH7nFl5w5Dg/d/8h/uW5p9N1HTikg51aQJQC7WAg917O3HnX3TztaU+t/zxIJiJx/nnnct/9e1cVJD5UTAHtNL7ueMbZz+DNL30zL3nMS9Z6KNOYxrd9XH7K5bz+h17PK9/2Sv7rJ/8rv/qUX13rIT3SKMB7nXMFeH0p5Q+AnRMgdR9g6ZnTgHsnPnufvvZVAa10bxLgUoKwqdbnfpWJP45UUh2VNVio+r1aBKUsorKeufQV3qYNNaYWqHpKAF96B4TK+Ha9jlA8V0vVyE4e3xfVF1rFuhaw2LZkYZInXQMqC1oUPQNdFHb24osfw65duyaJamHgjh1jYWFBXSF8lT2knEndmCYIqL3k5BIXLK3w2jN2SmpaPWRFKtA3jJgchw/WHlaYU2OSiwvkPCYlT0Hmb8O6AevXJ1Ic4dwyiwtwx13HOXaiZWZ2PbjjLK40fOb6IKll54Bx1SsXQgUnLruaii4+MxzO1Cp/tAWt877aYcm10hnLUHTOpQBLmXiElnU+qK+usNPS3MBJMV7utclg0heVcjgt6gNc6P2PrTGE8wGxXFPZS8ngHblY4R84l1VnPMkqelIupGx+ygXnxOWji44DB5frtZZRiX1YqusaHYeegqO/d8wpwuEJLlCcB+8oJXDkmOPIcShlphYL5lLYPBf4wacH2mbE9z91lvPO38H/ff9h7r5/mTYN8E700a51dF2ni5uietZedoMz3+C+M9pCE/jTHZv5Z/sOc9nyCtcPVN5RrIiwxTlq5y/vA3v27uPWr9zGuWfvrufrcJx7zjl87OOfoisTupqHiCmgncbXFV3qaEPLyy552VoPZRrTeNTEj1/247zt5rfx6x/+dZ53/vO4bOdlaz2kRxJPKaXscc7tAN7nnLt58s1SSlGw+4jDOfezwM9C3/nJipiC12IllRK4+oB2UsVdXH2AVoYUY2xEi2ngxFEUELmajrXtV6fUxRC/et02gRLLKsCr5yrHUHbQPFBxbhXgnDTJd8oY25GNrTWGaRVziLoYRAHCGzdskK5fhcogxi5yzTWfqWndUlB3BqcFQ4mEaIR/5NBRFr3j3Zs2yP796s5rdm45Zca5U5cIBY9ZNMVdjJQileYXXzTPoPF84cvHiOPCtdfu49SdjtvvOM5Ntyyy0g05dnRELJDzCrk4UJaS2rDA5h9l9VydD7muAlaaJhBjYmllkXWzcxNgteBKX3xU9FrjIKuWtBRpuxtcUU/hBzRacK7qNx2mo0YXUazyNEa7gnVZK/wxLbNXdlHAZG28gYJlHEURt0ld7D7JJSOms2ViPI7s+oXLqvewrAIiRTG7OAXCbuI+9nav2h6KTY/KTbQlcjQWv2SWxoXPfmHEurkBm7dv4OwzOl7xw9t52zv3cP8BTym9I0KYyArYgcxKqzZJyKUvpATetHM7rzx4lH+0/whf2n2qZAA0o2B6bAdaJAklZw4fPsI5u8/qvxjAtm1bOffcc7j1tttJhu4fIqY+tNN4xLF3YS9n/fZZvOOWd6z1UKYxjUdVOOd43fNfx8bhRv7rp/7rWg/nEUUpZY/+PgC8DXgCsN85twtAfx/QzfcAZ0x8/HR97YH7/INSytWllKstDR5Tqj/S571/aBog8D7gfUPwTXUSmLSnklar6qmaEylHcoq4bO1bpWGA9LvvQWq2trddp2li37e21ZS7Pbhj7Gpa3gBVBWY9rMV61yf1pXVOi2smdLwmN6hennpM7xzDtuVxV17Ze9i6nlHeu/+gWGOVDNrq1AAOChjncTzr6AL/d/MGTvreXqyCXm29m2LS83ak2DPY1i6YAsU7Ttk54MXP38wLn9dw+cUdULjz3sj//MP7+fv3neT2ewr33LfISufJKZJzqgVo0uJX0skpC+eZde67LlbfVRCQWVsV6zgSheyE9cxJ9pFSrqlu8QR2+CI2X169YLMykEV9cVEdqqE8b4sRBWMKQ/v7TsEkkpXH3A7steo3rK1sJ9DoxOehglPvKHqvtHrfKteMCE3MkovK8nsFwiFoUwhdfBnjnbUgkuIhO6T2UEBnKUXlL0nT9jL3MSW5FuqMsbLScd0NDX/73sCB/cuMl5eZHRzjlS8/hWc/cyslj6oHc9bP5Fw0QyJFapZhaZqmFjza92A5OP526yaefvQE21ZGai1Xql+xFGlaJkYyI9d94foKWvUqMDMcsn5+Thnrhy8KmwLaaTzi+I2P/wYHlw5yyfZL1noo05jGoy62z2/noz/1Uf7ohX+01kP5muGcm3fOrbc/Az8IfBl4B/CPdbN/DPyt/vkdwKucxPcAx7+mfhZq16OcM0kfkiA2XTFFYop0444YO31/ddremF1roWvFXCDsZRc7UhKbK/ts9Y8NQYpZvHwuKQjruk6tvQxQW6/73ls250zXjWsnLrHOKvX4IqUQ1i9G0eemFGu1vbXLNXDUqYY3p8hll13C9m1bBbApo+iAm266mZWVFcbduGqEx10nHcO8r02onnD8JDOl8P6tG3G4Ks8AVFYAKfYd0sSH1C5Iz+ACtD7yg9+3jrnhMVxZZtf2DepB6+hiJmeHZJx9bVAhHaniKr2jFPYJiM4KqqybmMxRqtdzaWmJ0WikUgzqosDVBgPyuqTuM8aJg3Lz2jCj3mMG/HKZSP2vbmtrBYYGkoXV1z06g7Rynt5ZSwxX9aN2bIPFItUQe5BV41PAWoKHCmzNSQJbIa2SMsjCSe4ZirCYyebX5kh/y/dECyzp7ehsEWWLI/sppZBK5ra7x/zZmxf52GdGuJAJbokLzg2smxvSNCJRkAYMsmAYtAORIti+vNf7V7IlOff627ds34wHfvSouDc4b5kLyUaYBtwWDAsLC5xYOGEXT68VXHnFFXiHaNMfJqaSg2k8olgcL/LHX/hjXnHpKzh3y7lrPZxpTONRGRdtuwiAE6MTzDaztKFd4xE9bOwE3qbMYAP8ZSnl3c65zwJvds69Grgb+FHd/l2IZddtiG3XTz2Sg9jDMFTWpU/Hmo42uVTfy0Xtt3Jv/t6o3tNa0xqrCprWZ6JlqfFmrpceoJIE73tWyArGZDTK3PpQ07gWMUZBLJZOLwqyg6+sbCmaFlYdrZ64drPqwbcAbMc5u8+ibaRblRxLQM6dd99NVMDYtgMKXpnPjIt2boWnHl9gwXuum5sV8JnNJ9TYRVTji7YlTXocr1IGkS0MWs8LnnMq553dUVJm3/6Wj33mBF1Xaicz3zq6rjfgL7GXaZheWS+mZtqzApkGV4oyqVbkI9vK4qEhJkGVPUPtVL7gZMqdALkUo4A9JuQczuEKyJpBjuMokFJl1UVq4pjA7xNShl52YguoOgT6okCpugLnGpWPqAyh6rkn2NdS+s5oxdhitD7KVWazZC30MhZXJRLLyysM2lat4cSlw3uxBsPbSXiKy5rWt+s8MRbT4BZqQ4WcC03TcPxk5qPXRE6eDFx2acenP7OfEyczITSEpiFrcwUrarVFYNF719nJ6KBLFuuz+wcDPr1+jmcfOcHrdm2vV1qkJBGKWYAVMrAyGnH9l77I9z/tqdTlS4Ft27awYd08E2uVB8UU0E7jEcWbb3gzC+MFfvaqn13roUxjGo/quPvY3Tz+Dx/Pbz/nt/nxy358rYfzkFFKuQO4/CFePww88yFeL8A/+0aO5ZQOs6KSWtyiVlYuyUPSQELxhUkdLVBdCDCwQultt3KvSTQ/WpBHpTGsJkmg9HpTnFNwIQyepcINOJt/LVBdCoRCk/HEFNWuSwCumf1nlTroY50QPE0j7Nf6dfNccP75WBGSaYOXlpfZc9+evgWpFnc1pREtqLYUjTHylOMn+cSGebpSKFFAZUoJgsks1Hu3bSgpUbJWqBO0wUUm4Dn7jI7LLlzCF8f9+5Z4498scuz4QFlfsaEqLk40pXjghYUJMr0yriUXsrPzX3UPAZ4YE6U4ZmfXrb5HdBeugqYJKYCj6qXdxLFSNhCpzGzJlKJAOcj8Z9W0uonxCBjMfXEaqF8tikANKGd8Fvu0ggFlI1q9aH/Vdk3uOV08CeUsoF6PL7evzVGmKMvfpQgOZmdm6flpOYe+QEzOwxhnOS9rRlKqjtzu36TuIVnBc1FddjeGz30pcsNtkfG4qadbFxZeXESapln1/YtRFkGrdPFWfFngvZvW8x/v3c+FJ5e4Zd08OFe/H0mlJhXU5syRI0fpukgTtEUwhUHbcumll3LNtQ9vbz2VHEzjEcX/vu5/c9G2i3jKmU9Z66FMYxqP6jhj4xlsmd3Cf//0f1/1UPhujaJ6ycnUe0z9b0tjW+q4amj9hM/sBJuWYuo9YfUBWZQJNHmC7UOi73hkaVMDn867uj1O08kTnrMowDK3hLZt62fAvHHNyktAUfCeVn1pbXw5y5jbENiwfl4Ak0kqgZOLS9xz354Jm7JEIdKGQLBiNgrnxMzWmPjshvnq1mDH6YF9ptA3pkipUEro0/TFcfpOx0ues57ACisrK3zi2sLBw41cj5IoNMQMKUGMhZwhpUJMEFOhi4kYEykWYhTda5zQS9q8mZ63mJ7SmPcUaQcDvPcM2pa2aZSdFBbZT+xDACxVo2o6WrQgqhQB7JNOGOqipfMo94DlBrzvC77sGvQFh0rIO0dwHl8aIOjrE24aCCB2JRO8cv1FFzuARxj6LKsRBFALIPNQdaJdjobQ5Zo59W4uUIpTWy6RRPiJ74BpVMEWA30R3GQ3OadgP2ZHKk4geimcXPI413HxRRu57JKGDevH2iCkVInA5PdOCsF6R5Kg96WN50Mb19M5+MHjJ+uY2qat31ED5wJsAzffdAvHjx+v/0aIdlZkF8vLKw/7b8mUoZ3GI4rfeOZv0KWu3sDTmMY0vrHwzvPLT/xlfv5dP8+n7vsUTz7jyWs9pDULA4tS9GMV0JLuT2o1JalIZWQLBIJIAhQ0mlZwEtR6vOpyBTAFhMlMpAryTO/aNH2rV7Nx6ot++ge/HEOOmK3jGFQ/3FzEgkr1B6t0ir0bQ89LCjgFK6Bpgmd+fr4XXCoIyqXwxS9+sX4GVKLQyLwVBWsAlywIYLhudigAXueqZNFK9qxZ0XOQg3Vd13sA545xHHL0xJim6fjop5a49voZRjHRNqvdAHpmVm23Sl+kJjZZXplLbbPrZK5DCGolJueC9swoBWZnZkjKJBpzPlks5nzfhc3mxBhIVV2oXGRCJ+sNbKGOFm7V9TUlSTEGlwnm1xYFyuLaS857/MR1rR3Y7Jrb+mAi6yBjkZbFpm01VlcwdK9pKQpC88S9YrrqZKDUvieuP7+s3siFutNeagB1W5h0AMlSGNiIptqFwLp18NIX7aAdwBeuP8nb33Vwle64ynrM4aCIF7Jc+1znHQcnm4YvzM/xxIVFfsfuDSdWeLGTYrMgAuaqoxfmWK6n0tfMzszw1SDIlKGdxiOKp531NJ55zoMyjdOYxjS+gXjV5a9ivp3nT6//07UeytqG6vycK4TQG+ebjZYPvhZvgTGKeZXkwABFTdM7q3YP8qPAxIrMrP2tdSyy6I8ZavOElFJ1JOiZLeq47DMWnRa2VWss3xeflYJW/SdSydXiy/bRtA1PfcpTJgBR7wBww403EXwj7JeXVLW3tLODcdcRU+LypRWOB8+dbS+FMA1mzkJjinaxaOpd2L2icyFFVYF77ov8yZuW+eDHMh/7bMvSigDXlVFXLbSAClwM1Apz3RETpCwpf9m/o2RHjoWcpJDM5tQcDQpUwOq9ajALjMdjVkajyvAKo5uNB5Wx00tXrPjJ4yv4EuZT/1xZXV28qIdsKpnsBPjjvabZTYtquCrXIkY5rrHgRZ0UbONSddUmkSgl47y8F3PqQXTO4o+r95DTz+EcxblVi6uqh7ZFSZUYlAr0XPW91dbMRZpB2BxNFurVr6GiZYG2kGMmxYaV5RM4Vzhn9xzeTWQ8jFXVwjwDuiZpKKz2kS4l85l1c1y0PGLjuFs1/16/R7YfG3No2rrILB71G57QLz9ETAHtNL5m/J/r/g+fvPeTaz2MaUzjOybmB/O84MIX8Nab3krMca2Hs2aR9aFswMZawwLVraAg3pZt29IOWtq2EcBaH9hifyXdhlLVs5aiLUPVfqtpxIrLiruqtVEuVfJQGThnbgWaTs5igRRVzpBTriysD5Lyd6aVnTgfs+bKJdMoUMb1mlvbBqiV6w+koKzgzRgwOWaoD/7YqTF98Fy+uMz1s8Nan2SaWSv+MaZQWo7mCSDaLxB8EP3l0RPw/k9mTi6Jt6v5/XZdrDIJA91iB2ZAj/q6LSDsvZTtWqV63c1SzMC92Kj1zhAp5wq26n2j1l0V9JukwlhRnd8GT6icuDGvE+l2MrhMil3dt/n6opKISRBXSeAiutHYxfr3GhMZAGF/5RimcMmGjlUPWx6wvdLPqxjl6uOrY6gAtBS6rqtOFpNZiqJNKZg435Qmtcu2KEmr7kWTWywuJW668ShdXqBpRmzd7Os9L5pfvV8UhHovll3jrusXF3Z9nOOauSEAV5w4KZ912oY6xlUTOAmOH/g9sMXPw8XXBLTOuTOccx9yzt3onLvBOffLD7HN9znnjjvnvqA/v/619juNR0eM4ohfevcvTZmkaUzjmxy/+r2/ytte/rYJLed3X/QZ3T5NawDT/F4p/UPXhI4GDIW5db3Pqz4kDYB2cdyD1VXSAde3oqUHl6bdNZN4AzZW5GIPbynMMrsxAWg4qo+tnwDD9lDvK/B9bcwgjFQiFwHjR48ek+ZYagxVipNWrs7slzJtG6RrmoEXhDkcjiPnjDq+PDdTmeZSygNYb1dB9qSdl6SqE8Vl8QAtULKCtawaUlYzxzmvBuSSru/Bn3OqO56QB/ShHrE6dgPTcv1Fl9upvjbnKEVrCtLMBUDGnWWAllpXCYB5phb6Jh31WtAvYGwJE5xXllSaXbgyWWBlUhRhxcsEkGuaFrynTJ7fxAIERJog96Z4zjoPRTvYVabSQXbCtucHzJcAPEdOPaCezA7YtTAdsEknhKHV1rurAKKOX6UCsnDs9cXCJEOMsDRucF1kdqbjnLNnq0SoKLCtUhoFoSklmiB6bGOEjXW9cWaGDrh4eaT3lSMnCMFRnLhPMDFn466r96Z98SezFg8Vj0RDG4F/WUr5vBNfws85595XSrnxAdt9rJTyQ49gf9N4FMWn7vsUJ8cned75z1vroUxjGt9RccUpV6z1EL4twnmHL5JeNR1nKb1mMZMrk5fUasie3GJbNKGlrFrJvpjLNKTVxUBTwKa3nNS7mrUViDzAO49TNtjhhAJKVM0nUKULzun7BWVqcwUNku4XMOUrI2nV81CyaEQXTooGVoq40FR1wfsg4Kz0lePOO1zpO6RdOO7wwM0zw+rckFNf/CXa39Wsl7hA2Hk4ztgeufyyOT792cMcOTanBvcG7gz895IDA15WXPQg94mcJyrwrcDKV1lIUWbPeac+sVSwn1MieU9whWDtDUqSRgs5V/eCyvTqvJjPcH8pbaxyTWrRn7xarw04StJiwMqWStiYSplgQWVicWrB5YOv81tlGKWIP7CxqxNzJiynySbE5cArs+l8rVrDIU0LJtP5QVlbW7DE1Mtcip6rMN5WoLYaBNp8WZtpvRsAqgWXc55bb13i6is983OJ+ZkTUBqgqYB5kvkNmjUoReYidbJosgV75+GOmQGPWRnrXGRtNZ16RleXHqUUFhcXKVs22VTJfNVMwUPH16QGSil7Symf1z8vADchPbqn8V0QH7nrIzgcTzvraWs9lGlM4zsuPn3fp/mda35nrYexZlE1saUvcml8U5sdmA7POdHENqHtNYnZunKVysp6NWc3j06HFJ405ipA6R0U1NHAgGst+vGu2nJZSjdVtjDXlP2kRZEwZlL8ZKn2MpEGt2IeYZaz+G8SyaVTQNHgXGBufo6iQCw5SUdnSgXmMmdZoIcyqcbSXbAk1d+3rZur7UWtGYRINAzaBRyqLQa1oxLUtX39Eo9/zDH+yY8VTts5rkDM2Nmqty0Tms4KKHsg6J3DFwjOV6DqZLJk2yJ6WmGgTehBZcLlujXCnLogDgLqvUrJOAQo5qxFVk4WNuZ+UBRI2gIHB03jqxPAqsWIsu1R/XiNNZUaJVd/9+z0xP2r+tngXC91QZpelFIoKpVI2u/X0WtXq0MDjqQksy0WLCNRsrHCWT1tS104QG8v12tji7LpKAOuDh55NQtux8/abMK6pTXeU1KuUpq9BwrL40LsAhvXraNtQi06q/rYnAm6cLPFoH1PTNZjhXc3zwy4YGWkGQwHThY0FC9dAHU77z2HDx+iMrNAKepE8f/I0NZwzu0GrgSueYi3n+Scux64H/hXpZQbvp59T+PbMz5y90e44pQr2DSzaa2HMo1pfMfFO299J7/58d/kp6/8adYN1n3tD3wnRumr5lEmrzJaCpxM14pzlfFKRX026R0KorabrUDP0qvBE1zoH66lT5HLBlIII0whuGD+o0XBdV99XVPq3inDlNW83hK+CrSwdqHyute0f5lMn2qnNK/FY00rjTaKs9Sx6l69q96fITTETgrcmraVcTvHhSsjjgXPHgclimNEjFEZbQduNeiQoqZe/1hcx2MuHoKPtAPPwkmZp+rgMAGkVlW706ev6yVV1jMrg1nUiUCJuAmmchJkOdXQpr7lr86Bd8I0ZmVWzWRLmGtl84sBPmNjpV2uMYRZGUBh2TNtzgxLZlCg1b8PKAxzYeCgyYVBKbS5MATakvEKaL0tqqBqdEspROcYe8fIOTrnGTlHbBpiI39fcp6TTWA5BGuxoSl7XYiVnuE1hGv3HXXO+t8mK7FFhC08KsPsVn8P+jA2tr9vTX4TgrDeLmcSLR/5RMOhvcc5sVQYddbRq5KmIpcw9wkb2wO+u6Z3vmcw4EXxJDMps1wXS+rcMSELyjlz5OjR+u+DxczMDMPhDA8XjxjQOufWAW8F/nkp5cQD3v48cFYp5aRz7nnA24HzH2IfPwv8LMCZZ575SA89jTWKXDI3H7qZl1/y8rUeyjQeIrrUsTBeYJzGdKmT37njrI1nMdvOsu/kPr5y+Cuit5uIx5/6eOYH89x7/F6+cuQr9XWHYxAGXH3q1QybIYeWDnF0+ShtaBmEAa2X3xuGGx5CEzeNbySuPvVqUknccOAGnnj6E9d6ON/yMDa0FK2M9iKitOIhoAJQl6ICIXotrKbbDWBZBzFjyibBgDVkCKHBe4gxi3/rRKOF6nqQlRXDPGudaCUn2odSqHKInllSGYQyyNB70RYfJqrUC86FVV3N2ral8SaLoIIFKxTKCvhnhkNpu6uFacEFIpELl0fcPDOsz3+RTzgoUgDmPVW6Ie8XUupqY4RAYts2YY7H3QZScTiXcPgqzQjOkTQNLhrZfrCTHqemL9iRM5+59wA/v30z75mfq9dqUrtctaQaITica4RnLwI053NmviTmYmQ+ZdbFzLoC60tmJmfmCsykxDBn5nJhJuf+JyVmS2FW/z5M8jt8c2/lrzuWvGexCSyGwFKQ3wtNw7Gm4VjbcLRpONa2HGsb9saOe1PmePDiXas63VSUkdUVUP2uIIs4WViVylpDr32t4BfJLORcCG0jYBZh7lPOXP/lE7gMITTIVfFkYv1OiHSiUJIszIydtnu71z077h/Igu3ULnPnzFAlCXq7ONSzOeG8Z3l5GViFZxm0bWXZHyoeEaB1zrUImP2LUsrfPPD9SYBbSnmXc+73nHPbSimHHrDdHwB/AHD11Vc/PG88jW+L8M5z77+4l6Vuaa2H8g1FzJErfv8KfuEJv8A/vfqfftP3n0vm2MoxFseLLHaLLHVLLI4XOXvz2Zy+4XSOLB/hb2/+W1biCitxheW4zEpc4Ycf88NcccoV3HLoFl77sdfW9+3nPz/jP/O0s57Gh+78EK96+6tYiSuM4qgC1ve+8r0885xn8tab3sqPvfXHHjSua37mGp5w2hN4563v5J/83T950Ps3/PwNXLz9Yt5601v5F+/5Fw96/55/fg9nbDyD1332dfz6hx9c33n0V4+yaWYT//HD/5HXXfs65tt55gfz9fd7XvkeGt/wl1/6Sz6z5zNsmtlUf7bMbuGFF74QgCPLRwgusH64/ru2MOqyHZcB8OUDX/6uBLTGztaKcGXRfBMIOdT0K5q67BEtq2QHPvT94asfKLqZtX/N1C5VfcW6Uz2sq53FBPQJyxqaIMVpwfK0Wojm+tR79ZNVPaqUGlGN5XEOVF8owFQM6sWaylUgmGJiMBjYtKwCeQb8uvGYrm0qk+nVt7P1jvNWxrxp68bKxsXafQm8D9WVwBjX4kqdV+cdjV+hdRmP45ZbjrG4PItzg8pU2/VZdfm8XzUHto33jo0x85E9BwB4xvKI+5uGzaWwKWc258KGUlifM+tLYV0pzKfE+gLzKTGfMvO5sC5n2q+SYp6MkXMse8+K/QTPivMsNIFDPrDsPaMQWGkCy86x7Bwj7xk7T+cdnXNE7xl7R/SBLnhhWb2jw9EFTywgrgW+Lmrof9EUGBrLC4SUGAJDB4Ocme0ScykyFw2cJ+b191xM7Bgvsanr2BgfupI/A0e8Z38T2Nc0HGgCe0NgfxPYGzwH25a93nFyosCrftEmvnSr3BD069RqdkC+PwIsm6bBOdi6Fc4/fwNHD+/nK7cPhTx2PUCu82BgWO8/0a276iV8n9rJnTbuuHNmhrYdkLrYT6DeQylG4nhcMxQ2/NmZmdqd76HiawJaJ2f+R8BNpZT/9jDbnALsL6UU59wTEA758Nfa9zS+/SN4ARyPtti7sJcX/NULuOHgDbzphjfxsotfxonRCU6MTrBhuIGzN59Nyok/uu6PWBwrGO0WWRwv8v1nfz8vvujFHF85zo+8+Ufq6/b7X3/vv+ZXnvQr3H3sbs75nXMedOzfec7v8ItP/EX2nNjDT7/jpx/0/jmbz+GKU65gsVvkY/d8jJlmpv7MNrN1u+3z23nWOc9ipplhGIYMwoBBGHDWprMAuGrXVfyP5/wPWt+uYlHP2Sxjeu55z+V9/+h9BBdWMapnbZTPv/Til3LVrqvq67lkutSxfV76bb/kMS/hnM3nVCA9TmPGacxcOwfA5Tsv5yUXvWTV/Cx3ywQn3Me191/LG657AwvjhXqMjcONHPs3xwD4ub//Od58w5vxzrNxuJFNM5u4aNtFvOsn3gXAn13/Z+xf3M/2ue1sn9/O9rnt7Fq/i9M3nP513g3fvnH25rOZbWb58oEvr/VQ1iTMXsjAVk6mD9UNjM1z4IvqWs1bVVOyBWn5KvuDEDRN7/pCMWOuUEbXqtZjSoqPnRbYhIokrWDGWuGafrE4k0aUOr5JVrIkqbBPSTSN9t2z/Xka1W4K4Mgl1/Np2yAa0WwpbRl316l3p/N0XVbmTZjXwWDIKSdOMFMKt88Mcc4RY1R2WSrYDRGYE4RIJXRtEISdO+esDcwOTgCFk0sNObUTGtoJv9+iaWcHvvTMtqS2BZBsS5lr7t1Xr/NLTy7x0pMPJkaWnWPRexaD56T3LIXA/W3L8baw0g5YahqW9L3F4FlqAid9o6ymZ8k7lp1nJTTqNGDXfkKT66hSE++8yjdabdQg18x8h53ec9ismaxCWU0rODQtsNcCqsp8+/64q9rAKoNfcqZt214jq/pj0/6iWl2fMxtiYnPXsSl2DE+cYN3SMptjZGfOnBITu2LkqpURmx+iSOqw92zV1688bSdHfT83tj5ogiz8Gt/oKXu131VdspfsxbBNPOPJkQsvPMKtt2Ruvm1MKY3e870DyOT3IedcXUTs/ga4r5E52TUaUcpcL1nQez6EANl0xFY0NrE4nZjXh4pHwtB+L/CPgC85576gr/074Ezkgv8+8FLg55xzEVgGXlG+mnJ3Go+K+OX/+8vsmN/Brz3t19Z6KF93vPodr+Zzez8HwIfv+jDb/n/b6ns/e9XP8voXvB7nHK9552vq641vmG/n2TSziRdf9GLa0LIcl1k/WM/O+Z2Vhbxo20WAAM7ffvZv19fn2jnmB/37F267kLt++a5VgHUQBvUf26t2XcWdv3znw57DpTsu5Q0vesPDvn/B1gu4YOsFD/v+aRtO47QND1+/efqG078qOLx0x6VcuuPSh33/JY95CS95zEse9v3/9uz/xn979n8j5cSJ0Qlhs7vF+v5PX/HTPPG0J3Js5RjHVo5xZPnIKkD/hi+8gQ/f9eFV+7zilCu47jXXAfBjb/0xDiwe4IN3fhCA7j90NP7R1fzQO88lOy7h1iO3rvVQ1iTEiUA6S5VccL7XqNrPKp2g96SShN1M8gANPvTFPSlWIGJsatVWqnwga3W1C06LwkSdCVRLKytQq+yxOgqI5VMPIByTxVZ928+UpctZShk3yWTpb4+A4ESS4h1XaNthZckmQ9ri5r6KPBekqMskFYHdIwH0dw7l8yFohzCEla5tUTG9o+mICyEIsN60qdH09JBY5sm5wwfXLzS8gSE5Y2Fuc9WUOp2NUmApNLx7bobnaKHav962iaPes9C0HPWOhbbhZNuQnKNtrQDPxq2APHiaJmC9CqoThQFnZG5L6VPbvXFV7xJQSq+9paSeqc/GTop1mqP3up0EtrXASUGZzRv0bH5/r/iq57Wx1usOOFvUqMzD7ocqezF/YuBI23B0IO1+j1I4nhODwTq9z6hAfJASO0tmZ0zs7ATontFFXrEg/9a+ZHmFP1k/r76xRbJhCrz7Vsr9PNiYkjK0o1EkhIQvywwGK8wM1rM80kI+XfD0XdJ00QTVfaKY5AE43DSMnOO0GEEL5czezu5vWxx0407PVAr8CoWZmRkG7eCh/zHhEQDaUsrHqfj6Ybf5n8D//Fr7msajK95y01t45tmPzu5gv/WDv8XvPvd3+Xcf/HdcvO1iNs9uZsNwAxuGGzh/i8i7vfPs+ZU9zLVzzLVzDMLqL8pcO8cnfvoTD3uMdYN1/PL3/PLDvj/Jpn43R/CBzbOb2Ty7edXrzz7v2Tz7vGc/7Oc++KoPsjBe4ODiQQ4uHeTg4kHa0D/wt85u5e5jd9e/f37v53nCaU/45p/AP3C8+yfe/aC5+W4JKx6imDygBwDQV4uDAJaUMjkVNHsv4XrJAPQFSuZH6oqrD3OXBTxYIwRxKPCVocv1WMLI9rpEeb0yuIXarjdX9k6GY+MwXSmg1kQoI0ct2BGr1kAp0qyhCY0W29ijvGexweybCoNBS4yO0XiJpgnsVs/Oe4fDqpB1/Q6koEoL1TB5AAL0SnY4F/js9ZG99w+4+HzPbXeNK2B2ztU2ulKc1cO+4AM5x8pSJ4SFHLWBXzxlO++5dy+3ty1/s25+FbvmvSeEBlcSUmVvxWlyHbqu03+PDTwrcApe2XzRfTpK3/nM3AOCh5y0cMtArYDXosxyF9OEzGnimmvxm3UKK2jr2VUISO9Z0wxjixUZgxVH5VIIynY6J4y9m7inzQO21Hu8F5rYPDhQ/2EYDgcKGhWMA3hY8Y57Xcu97QBmS5Xx/PX8HG/dd5B7QqjZDGOanUlkiljB5ZKJsaNptDMaWgwJ+DCD8xHPmNN2beTUU9Zz530jqG4XumjyQfbXKwQkCxKj2owV8I77Bw2njTtw6s2bS7UlA2HRY46MOznGZAyHQ9r2/0FyMI3vzth3ch/3L9y/KiX9aIrHbH8MAG966Zu+6nanrj/1WzGcaXwD4Zyri5Bzt5z7oPf/5/NkDX1s5RgxR7bObv1WD/GbElvnHp3j/maFVXT3KdiJNp76f8voG5Axdiyb12syr9deb2qa2JTEkzUllSVgvp+5AlezBwMwv1JjqSaBbbX4MoCrtliWcjfrJCtKs2IXAbkmrXDkLO1YSzGHBKf2UxOpYZ0fY6xDCIzHY7ouVmsm0y+eNeo4GjzHvLClKYsllhVumewYIKVY5QEy98KQp+y4e9+Ae/ZJJzLnUp17Y9GEFQw9awk0TV9e5b2xf4W5FDmni7xj/bwU3xUITegZ4glrp1KE5/RerpcPgaZpK9Nn6WyX+4YJRRcGxWQq+n9ZxEB21v7WvGNd/RwKzMVD1isYnmiIUEQnm1JS7t7a8drKS6QlwQCinnvKE564uVQnDmMpLSUvINVa2aJdxFw91xj7zEBS+UgIIneRLlvW7pkqgZB7RWenFO4MAqx367Fwq+297N4sJdM0jtD0i0kfzCNZxrQyWs+RYwc5emKZ8XhISVn0JhY1W6D7NylRQcGssvjOsb9t2Nkl5fMD+ELuOkIIdF2ni1vXezuXXi4zHA6/qob2u7MSYxpfM67bK2ndRyugvfPonfzU3/4Utxy6Za2HMo1/4Ng0s4ltc9tWMXuPprjhwA38zDt+hjuPPrz85Ds1xO8yUDs/TTx05cGeVnloWltSA2jW8gBUd5e1w5h51JoGUgFr8OJJW4tiJoplzI3A7LWq5tI0kLrPlMWTVpioUreR8fnKOtl4egmFw/tGXRYkQU9xxFgoWRk8G5cTJs7+Cz6QcqZtBxWcOU3X5gy7xx13DQe1aZYQZTozpfR+pb6fL5ym7El4D+3AMWgd7UAL8VzBuVw7Uk3qTIP69DosTQ5mmQXCZF+ohU23zgy1O1qv3zS/X+fMHk0ZziLX2GQIKReSMucl913JQBpxJIRllva4KFBGFjZZ/F+FmXX9tVYQZ6x3yrZoUXBqdKwuNppgkpiM88qkFnClSFuzInMgzQ1MP53qfZNiJHcRtNAqpQi59D8K4PwDah1KKeSY671EEW/eVls4N00jVm9NQ9MEQrCfhiYETg5ajnvHWV3U17VDnrZgDvq988H3rLK5fJReCuGd55rPOd7ydxv587fMcO/eVDWzYqmm7h8IO+9smr2X75qCcQOph5qG7QrSrejTihxlURP0/jYHEPku4AqDwaD+W/BQMQW003jI+PzezwOP3m5GH7rrQ/zxF/5YTaCn8Z0cuWR+/K0/zh9+7g/XeijfUCyMF/ij6/7ou7IwrPeapQK0EHx9OBuALZq6jDFq29L+oeYQ9sc+1xc95f4zUVL6tc2qEWb0Gj5jHK3zF6gEwnv1iG200EUeuKUUaXubYn2g24+k1ntAHFPSBhJUEOd9wLmAd6FqGL0ToOSLw2WHK14K5BzS8x7UX1YkBjnBeBw5Y2XE3YNWZRB9ertKJ2S2pTmDYibvTMYRaZvEC57h+YVXzfJjLyy03uzJhMVr2wYfPIN20IN2bWZhezeAFLTz14WdjPcrw4E0vjCkOXHdpTWrAKmiOlhAGXWVECjT7Op/cqzgg86vF1AXhHUOWkRYJkBwZdpRW6vagGPiXsSq5Cz9b1kDY/J7IFyKAO1k2o2q7ZU0guhBtb2u2beVUvXQ2dL/E9KSpA0LapEhuoCrzLP5Fuv+cq4LCNP11vECxcG9TcOZ9XsjYzcpxmSRH6VvGZy1SDMrQI8xct/9y9y3d4XiRoSwQsrjmg3JWdrdVmaavlubseMGyp1zHGgC22IkTXhGW4bDq4NIXbRNLFYp/ffq4WIqOZjGQ8ZsO8uzznkWG4Yb1noo31B89O6Psm1uWy3QmsZ3bnjn+dR9nwLgnzzuwTZl3+5hrhR3HL1jjUfyrQ8DXb1UICmLZylobYOqlc/Uh2QPgioTW7QTV0BZSV/Tvd6Jp2Zluyqo831K0zmCpv17oNZ3ZJpkz7w2VSgK/HIR0OS8p6hjg9N0vfO+z84qiFPhQz2upJsTc3MD5ucHUmomuX6WVsZaFU8FstZq1Dloxh3bY+KettXiMd+zjCDIRlP8BWHRTOfrvLbDLZlhOMqWjQFKArcO3Gp4YNZfqgOozg9S0W6ep9T09/mjjkXn2KOLjFqwZfNvLKBef2NosftBQY5T3aztV4C2JPonAXrR+6XKE+rlM9/gvmuV6WOtYC/r9TIdr5yiXnv6MRaVu5RcxFVBgbOdzwMBl7WITWXiXsf+YrITtBCxl5zIeagPchCgZ0DU6WeDlznCZyZlE1kzCQD7QuD0mGjbpl9ATDQUEemNOojoNXCrrNjEL3njumV+9EUtczPzfOa6Fa798jqgq005KEXdGwzUCrBOOU+0ehb98MGmoS2wMWYWho24GhgDLl8YW/YwqU1f1fr5YWIKaKfxkPErT/oVfuVJv7LWw/iG4xP3foKnnPmUR20aehpfX1y07SJuPnTzWg/jG4rtc9tZN1jH7UdvX+uhfMtDXA78xANWpQMpYt25anW76w35vTd9bFJQW3BFqUwFBF4LgAoma3DKvoKxb6kkKfRCgaUyxU7d3kvpGSJjO701GvAGYFTH6G07qnSh4GiDk0Ileusraf86obeswsxCcAqjvIxnNFompahz0pBirIx1CA2nJDGg39e2mtbNveUY4MgVkE9acHlrElW8pumTWqMVfBED+1xT81YB37c7LUzohu2fWdE4AJ4Lxh23DlpSZWMzrbUV1mtSVE/rXW+LRcps37aN/UeOVvZQsL3eB2SVRIgDgsInKXBTXWhjzhcTwN7WFFUqoQsocSZwovd0MhfZ9bpdWViZltMrEDdGv1T3A1ePUybYcT2y88K8TwD4UjLZADGqQbVmIZhdmLhJtE1gJEcnWAFV8ZUdtta8FNMci/vEgUHL40bj3ieYjA+y/5RTn9HQhZxY5Dntl+FUH10YDObYtX0ZV0acs3uGa2/sKGLKS4oiaRDrPKfuDfJeeICUKHjPYXUp2JEyJ5S1zanvYKe+XVVyoMuY+m9DEx7+mT6VHEzjOy6OrxzntiO38fhTH7/WQ5nGtygu2noRtxy+5VEpMXHOce7mc78rAa21fjUQKrIBv0puYA+znAXEWQoZBFCKfrD/DPSgWOQJmdgpm+Q8jYLdJjSVAS7KsIqNV6oV185JCttNSB+ypdpzqXpdnFXuC5NmQB1QuUGqYNa5Xmtr2sVSio7RdJilAscD+/dz/PhxOacsnc4kBGSepkDg4ECaIIQQanJerND6BYMx28LUGfRCQZTYcDmsperqBYaApFQZaDuOzKMWhhUqQ3j2uOOOtqmLBLP2Kia7KCYXWa1TPuuMU/mJl7+EtvVAkm3wCJ/pwQe8bwXweJTplsH6UvCFuqAx/a9cP0vhi+42OyGve22tKZbB4XGuheIrRq/zYZ/QYjt04RC813NyyuuanRkyLvptDan1jG1Rx4sJqQO9M8Vpp+7k7N2ngkt6j5dV3x+RZxj0QxczhQNNYHPODFRuYGOWrEWvg+0XbBNtqKHKe6RFshx380aIo0iMqWqFx+OO2m5YWdsqG5oAzQ44PJD7d2s3lu+QFVpOLES9an4nJ97aHYcJDfwDY8rQTuNBcfuR23n6Hz+dP3jBH/C885+31sP5umPvyb1cuPVCHrfrcWs9lGl8i+KibRex1C1x34n7OHPjo6+t9kXbLuLI8pG1Hsa3PEoWXadIDUxSUCroESbWGMUeDFVQVplH275PS+NctVFKMZFLItcCroILYvwefKgP08liMrMMck3PEMsLlv60wq9eGyquAgrSkNS4o+9TX7dBWceqZ1SAI5AC0LSvg+XlZWG/FBAaGM45Mxi07FJwf2Aw0I5MkbYd0HVdTdkKOLY5zxTV8YoTgpxqjk6vQw9MpP1wqVpG81b1CEiRbmM9gw2QU2KmZHamxN1Nw6TMwKlUwxjBnEp1JXAUdu7Yykte8ENs2byZubl52jZC9oSmwTlPqqDHnC90MeSkyM67oEVOqsH0eh+oTMUYQ1M24FYzgP31ob+vDDwqjhSP4f516Fv+9vZbhWTeshMa1aJ2W6mkKnswKUR/c/X3v3Mi87jy0ks45+wzefvfvZM77rqnbgPF7FzrXFgnOoADjZzd9jjmvkGj593LRZzeDw5HCb3vcu+sIXMxGmdOLng2bQDKGIosKLwPOO8ZDhvNGPSOF5ZBsTmwfR9QGnW7acL1O2MZEtPaOg/r18+K37SC/HGXaL9K+9spoJ3Gg+LWw7eyZ2HPo1Y/e9G2i7j5Fx6d6edpfGPxmO2P4cpTrmRhtPC1N/42jL/6kb/6rpTHeGVWUyo4J00Lck7EmOrDtM/8umr945RNc5NFOmnSDUELhDT13jSBUsyfVlinBsBRgYYxeb74yqauTrczcY1kHI16fJYKxFMdAxPAyE8wsQI6slpGGUDV5geaKpbPieTB2Nq+yMZ8TRM+zLBTi68ODlqKamtNC2rgKyvDVUqpTgdeu56VJGBj1DmWVwIrowldsp7rpH7VWDzpCNizhSF4tdzynDmWMd3TiJdpMqBX1NsWAcMmFWmahk0bNvDSl7yAXbtOoZTCD7/kpQL0vTkqiLOBpcat65d3PUjGiZRBpt9XVtBNACZc39jC9APOJB/12lIlBz1wVPCOAUJj0nvAZttSCkltq0rOymqb7lvcDsD8ZPXaUKD0xzOwHVPklM3r2TDT8tIXvZB3vfd93HrHPYzHUcZlwLyCfAWRFA4PhwCc4QMH9c/mHlLM8k6Ba9CMRaEQGj8h7/F0OXP/gZNs2TRg2GQGTabLgZwLwRVi6mUH1d0hrW7fa9+dgwPxEt+RMo1pe7XBSdXuZnH2CBRrR0cBRilSUveQ/5bAFNBO4yHiK0e+AlAbEExjGt/u8bSznsbnX/P5tR7GNxzfjWAWmGABtVOUkxS2y6WmzFMW66VsyWBt2RmCeZ6GChSKaRMVkCbVE0pzpKDpyoz3Ex6ouv++c5OvrJHkpIu6GCgjaaBOPyuslOlzTUIBxVsqF2VtNa1OEgCT5Q0rbgshEBRcOcOQ+ncDqAIY1Lw/JWLXsbPrOBI8i9q8IcYo7xtZqE2zvKXoVWuJAsGUoYuO9318yAc/ERmnzLgUPfdQFweS+tcmFa4vPEo5qZa2lzScqezbfYO2prd7LlQWCKJvzQzaho3r53n5D7+Q004VX/DQwNlnn1PT/ALuDDz33xWbI1v1lPri5Fb996vauDm36n3Zx2omvhgzXTH7hOUZaIHYxHjqNtTP84DvtRLaVIRWx57r/quU1Mn8OOcI3RKlW8I3gRc9/3m8673v44s33tx/f0qhb3NMnecD6tm6bTQmz7SVfW6CLPBkO11opFQlEiK76RdHdB1LSw2+DTAo5LRCyiLxMWZ2PB7r4rF5AGONLlpl4dLlzLJ3bJ4o0owxyq2q7XKTgnJbUBQnbPZoNGIc4+qLOxFTDe00HhRfOfwV1g/Ws2N+x1oP5RuKF73xRfzq+351rYcxjWk84vj0fZ/mOX/+nO86L1pLf+acSarJsz73IECk6mOVmaRIh64U5ccaMRgTGkJTQaZVoOecSDmLxZZWuve+naIFpagEItsYcm12ELTbUy69PVfvlRuVdaRqZy31agA7qfa312f20oGari+W/y6TM7TKRqw+/BVMdl3Hli5yKATG4w570hcFwCDAprEuampzVXFakba/KWcWRgOOLs9wcrS+b2Oqxvomr8gT1ytOWC9ZxyzT1p6mrPE9oZdxiG1VmTw1cI4N6+f5kRc9nzPOOKOC1lW2bG4SSBpTzOr9TEoGyuT89ZtM+pc+UDtqkoj+vQktfv2cqWfLxEjkdbsnHKzaZvUgVn9eBRp1r/2hdE8FXVTI+XYxQinMzAx5/nOfzROvuoJB29I0Tb2njCkGsW47oF21dqSMU3s4kfj0WufJeajXVXXkKcn3JiXPJz8X+MM/d/z5mxpSnid4kybAeNxVdhUmW+r2gNUaSqSUOe4D67so30ekc1/9nmHa+KbeW7KgLOzbt4+TJ08+eG41pgztNB4U9564l92bdj8qWaNSCh+56yOcvv70tR7KNL7F8UN/+UNcuuNSfvMHfnOth/J1x3K3zHtufw93HbuLszefvdbD+ZaFAUuXS+8zX3onAPsdfMAX+ta4LldAkXLfdalP7au1lpcOXTGZ2750iCopa3FMb5dk6dceXjhS1E5Pmp5tVHsqVJsVy5jXaA/CjXH1vlRAmEvBVzswGb3ogk2DCVa5LtlxoVaNheulBpGcffU53ZgSx4JXtqwjRmHCxuNOiqAKxE4WCYnUz22jqXJkfp3zdOORjJkeUIg/q9hCjUYdTdsAYnJvZ9JFbUerjPOOmBgDR5u2X3DY3DpzlYDZYcOLX/B8zj7zLNqmIaYJbWkvx3xArGZpLUQ+bV25iuiE60d6vWp9yd53UsLlChPX3gj6Hsz2e3cPJF77LYy9VnbXmUtG3So/+DMP3NcDAHnByfVTOYktmH7wmd/Pxg3r+egnP8MKY1yt/rd70nHSOyKwWRnc5aUVtX5zeA9z87MiD8i2OLQOZIWZ4QwhBFZWVnDOsf9ww+HjnrZtCS11UYnvm46EEJibm5uQYJTKiksBmSelwvHg2ZAS4/GYmZmZKmWJMYofb5bvaFb9rMlDxqMRS0srD558jSmgncaD4slnPJnLd16+1sP4huLg0kGOj45zwdYL1noo0/gWx/7F/cR9ca2H8Q2FtWC+f+H+NR7JtzaaENiwfr52TbL/jh8/scrJoChTSeqtstD0sDe6kZ6hKkjVecpZmhU4qZIvWiFuFk+5SDcsRK0nu2XCtks1tubdaXpXIRe9SBkqG5UnNJF9YQ04BYwCONavm9d9OUJoqlQix8jJk4scO7aADw0lC3xaOLHYp6dxzM7O4Zyj68aUApty5q62lX1RmGkacJ6cxzVlb52iTKNsdmRNE8jFV92pD6Gm79OEbtg7R8RS8rJJp+1KpRtWomlD7Ui2PSUONmKSn1OiaUL9XMpJmh8UeNL3PInNGzZxfGGBmdmZygo6HGM/Cf7LBI5VyrJMJvipwNAkCphGlr6BwYPkCM7AqcNY3glpbX9PrNJO94ec9KCd5GgxuQLmjTbB3CrY7g/WH696gE2O1TmatAwpEppECI5SHCvjjksuuZiYCx/9+DWM4ogQGpaXVjAKPufM8eDZqI0Vcsk0basLPhlzygIcTbfeSwbkvhZ/2VQZ2a7raEOr8oCEC4HsCimNGAyGminoCyENyFrL2lLgmPdsTOZhK/eSNCARUJxJeB9YGY9VguNwLjPqIvPz6x6SAIcpoJ3GQ8S//t5/vdZD+IbjK4dV/7t1qv/9boszN57JTQdvWuthfEOxa/0uQBw6vlvCAStLJ9nXLVXfy5LRB2xf4GWMai6l2gQZkKoMmxaWVFmA93RdrA9RS3lGZbkoRZnGRjqI5Vj3E7SYaDwa0zTCiHmcPvChbQb4IEyt7TeEwOxwprJU0rkqKHiQ8zDLqJmZWQKFLnaMx2MOHzlKSoXHXXU5p522i8FwQNsOiDEyWhlx3rnnsnHTBo4fP4nzntF4XIuWYkysj4mjwwGj8ZhcpMlBKaIJbtpGQbujS+ITmoHQNiKbUCSVU1LtrZtgIM22TPWPwZOjOAU48wFWnSVA4xt8K+BjZ8ocahqGbUNw0CqbSyk4NeIvpfDlG27g6U9+IjODgbC4HkpOvPu9H+XeA0cAK2ASKUihaEGVq685LQibTLf32lRUJ9wJmAuDvmCprAak5qkbU6zdzqxYEAdWbEUuNMqUTnbHShMFebb4MQsrY41FS2oab2v7GuoCp2maymgKoBRd6fc+5SlceNGFJJzYjVF41/vfz113305KhZUukrSJxGA4rNKdEDzHQmBzKjTtkPmmFVAaozCtITA7aOsCZTweE1MiF8/i8phB2zKcmcF58T52JRO7yGg0wntPO5zRhacjk1ha6fosiTHUviXlQo6qZ3dwvAnsHne44Fnuxij6lhbF6mt86113ce2Nt3HhhRfqAiSw69yLeM7sBr5400MXfU8B7TRWhfksmtn4oy3uPCYaROu+NI3vnjhjwxm89/b3rvUwvqFYP1jPfDv/XcXQOu9Z6SJlLDZVPoi9Vtuqdk5BrHnAOucoabW8QCQKiXYwIGrPegOlXYz4ECQ1mjNRi15yku1DaOrDeDzuaAetaE8b6T+/bt08Lke+//u/n/n5eQZtSwHm5+cnXBAKg0FL27TMDmeqhnag+2/bpi+O0WYEw7ZhZtCQUmRxaYmFEyfIKTM7N8vs7Gzdb9s0jN2YL990IydPLjLuOpEvgLJ0Is/YlBJHgC6K165TgJJzVn9QYykzg8FAUs/LS7StVJsbuHdKSTZNw3g0EmY29E4BAta9FiFRwbt8JhBjh8uig9wWI/cOh4AjNA0UcUEQPaQwhW0j7PT8uhmGjQD/QqIkWYwsLCyQciJ2sQJAKD3zN+GDWvcNVatZspyXd46YpGDJO1tgFF2QdOrtG3owqlZwMUUFrkFkME7vuXFUoCz64rZpVFYiixbrSOcmCqZSTDjvmBkOqxNASrmCzsmFUc4CfFEJStu2dDHifA/XnIOllRVOLCzK3BSRjJi9XWjEzxnnON62bEqZ4AAXSDjCbEvwnjY0tVucw4mMxIlsxHtHwFGiVPuVnAmNFC6KrEHt5pTZHgyGE24a/UBtPq0YDzInvGejfi+d8/333LqzFRjHjlE3piBuHM45hjOzrFu3/gEi6j6mgHYaq2JhvMDm/7KZ333u7/Lzj//5tR7O1x3b5rbxnPOeU1O40/juiZ3zOzk5Pslyt8xsO7vWw/m6wjnH9575vcy382s9lG9ZCMNnOrvIsBmuKpBJWVrJppQYDAY1LTkcDhmPxzVdXBREtW2rbKo8/MyvsnjPzHAIzgn40KYJ3nlCI/ufn58jeE8TPLt37+b0U0/hsksvZcuWTbSDtnYHy3V0Ew4Gk+ckb02cowgcDFSCIwRH2wTa1jOcGbB1y8a67ThFvGvpxmPGOfH566/n/R/6GF2SlL5H2EUh4wrz3jEETmhzCafz6r209DVT+1rdXwqUzNzMrNhK6RxbytwH0Vq27QzOFe2QhVhnlUyhb89qtmPFoUVnRa2fHJtS5novvsBJ+77WVsValBdTkmr7bHNpLhVFnCz0HiilEFPC2tSqWLWep/cCrERe4ia2EZ1nRvxcJ5lU5x3BFXzjIAvI6rqOUhxN0666hjGNKKUwHA5lbO1AsGaOFAWlMSbVa2uBlhegZlIT6QznWFlZIeWsiwlx6rDmD94HBcO5MtFtO5SmCQ+4zwrSkjZn8d/N9HNXRH0NCJt+PAROH4+tibPqtqWYMjpH66WwLOVMNJmJ+gW7Yq1yHevXdVx5aQAiR446brpjQB731wKnLgOmRXbexOC93KOIjv2YD2xM8r0Q0ZCr+upSQbF1CUQlMtaG+OH+RZkC2mk8IPad3Ecu+VHrQfuc857Dc857zloPYxprEJfuuJQXXPACVuLKow7QArznle9Z6yF8y8OaGmR1NmiUJTNAarIBAyNt20q6OmdcCKQYadqWlLM8lFPCK+MlLJerjJ01MTBFY86ZJgS2bNnMpo3ruOrKKznj9NNZv34dszMzPZOnY+39Zam/H2D+VMHWqr9O6D9NWoHKD4Tp1K5NTnW/CpK+fONNvO9DH62MnmatVZohjOVMFKZ4KUixXGgagtc5rJ3W9BwqEhCZgWiPBXTI3HXMzQd2bhEwuXffiHEXdM764h4DGF6ZvZwTg0ZYRBT/rsuZk0FBWsqrdMXCpmqXLWPu6hzL75WVlcq+Oq9+v1oEJ/7DxteWiStEZaZBQZnORUpZ5Sc9KI4pKes6CZLUds2J7jmEQNZWwylFYsw0zYDGBwpO/Y17l42UEgXZp1fAikpkQhNUH9w7ZHjTeWuXPJelWE1S+LLNeDxapWc2T+IQxF4uq/dx75ihXcNUEnKsCVy2FOv9KOsCyW5AJucRszMzAqr1njd9eQGKLnjWb2i58qoRM8OGe+4J3HKno9B31MtlorWvfkFKnvAyli0pwPEQmCmFmexYscWeHs/337i6n7pOKRNtlh8ipoB2GqvixOgEAJtmNq3tQKYxja8zXnDhC3jBhS9Y62FM4+sIK/gyq64qJVCAGix9G6xdrDB7TtPgw+FMLTrKmmLOWSrwk5m846R/vaaJh7OzeOc4/7xzueiiCzjt1FPZvnVr1VNaC9BqvG8PY7/6YV0RqgFWC7f6gSzQRqGtsz2aQZV8NmnRUlFpwI233Mrfv/cDLCytyPjrZ+3Tsp+hjmfkpMBMKtile5NLWoDEZDc1FISg6FqLcLKktM/etcCPv1iq4H/vTxa5/9AGTK86GQZs9X9ybsouDnxgthROemFtq751AoxY4VHbtnIupbe0Ms/h2sCgTB7TVSkK+jnpBkZtn1qy2JAFvV+ythKOKfZA0Hu6riOmrAVrDucDXju0pSpfgRAamkYlDWbB5uTPw8EAl6PqbIO6PTi6VIBOC/8CBC+d6ZwW3uVMF6X4zaQNdsc0oZHFjTMJQ5pYjPREp3RFC1JMWSZhvav3oHeehSawLolbhTOG01hjXZTEqN3FamGa3rvK9JccCT6RO0cKA6ATe7QCWnVZAWnPxPb7qPePl65wy9o0ZT7D2Duy+js7vS1Fz+4mwK1+O3Rh93AxBbTTWBVL3RIAc+3cGo/kG4sX/tULcc79/9n78wBbrqu+F/+svavO6e47696rebBky5osz5ZnW57xTIzBNsRhCPDLe4/kJSG8JOSR/JwAIQR+CbxAEsJkeGAChhiwAwGPgOXZ8iRZlm3Jmsc793RO1d7798daa1e1LNmWMGq11Mu+6nu7z6natWufru/+ru/6Lv7wjX+42UPZju24X/GW97+FK2+/kne88R2bPZQHLbzwxu2Ixg0EBpcDqQCziZG5GbR7a05nOp0BKxQCUtPtMQo59+zds4dLLrqYs88+mwsee35lxZx9rGyqFUQVS6tvsC8cywnu8S3vLAVUvSHFjmFvKF7hLp5iDe5VhncF+8KXruP33vFHln4djp1HhUZe57Bg5+6MnRNjXMXYVIe/zurpnCsGGdiwUvXLkQT5qLJ3RRnNjeywaybtXCN+NEYFqUvmIXtMHNOUCliDBPo+0bYKaKbTaU1X172Ds695uCe1QLAM2mVfOymlejMc1FIShaFZRrSObpX1FfUrdkDemz2bN79wy7D5fG7ZgkiQyKRVkNx1vek8eyJ5aN8ahCZO6K3VciFbEZ9UqYXLELzg0Bsc5Dx0y0pFvVkl6OuiuUQ4e1pQpUQqufq3UgyLim3+bD2tiLBQCpFCKvp5ysWLI7XoTDMaoYLQgY1XFlYkQBEWFiLThUDJjckq9KZV5pzhs+qd7XzzMayVwqp9ThZL5phYFqDe+2wbPq/jGUDtPTdW94xtQLsdG2KrA9q7V+9mx+SRo0PcjiFuOHoDz/yVZ/KzL/1Z3nTpmzZ7OPc7bj1xKx+++cObPYwHLbRoaV7BbDENZEqpAttiQDUnb1wQiE0zJDAtXd73vRarhECI+uALGfbs3sX555/H0y97GjuWlti7Z+89CJ6irJwUS8W6j6kdP0a6bs6dd97F8vIyJ1ZWWV1bZ211lXnXsbqywvLyMrPZrKaRs1WYg7G8xYFkqOTtZNJW0FB6LZC69HEXcvLJJ/H7f/guVtdnTKeTqj3MY7AMeMeniQG8WRC8BbB3P3N/XnUBiCrTQCglqktBKagaN1cw7l+lREujB7SdrxbPUUJ1TYBCExqcW1W9rLBoKf9VNEWsYG4AUK4pRWDvnr0gsfq1DiKCgPPYCvytEFAiSVJlfV064vesNqwIQ5FUnQeokog+pw2gDdswYMVHEnRDlDuzoCq5rk932GisqK3vCyFCtqI9B+FBohZylQ4JVDBdStHNQwwK0GNAfDOHtV0uBZIyvYMiFlsDeq1N1GYEoWRK0JVMySMZix531Qq8F1NhOXgWQLMLMSrQDnFiTUeGzYPPfiCQ6ck50mehtU9NQTcVXqSnu5BiMgjrFGYKWc0SuPtBZt3W8tSyInq3g2nUVROs3xzLDXz/cd+ag21Aux0b4szdZ/L3L/v7nLHrjM0eygOK1W6VgzsObvYwtmMTYvd0N7ct38bty7dv9lAeUOxd2MvR9aObPYwHLVxDWH1cQfWcpo11e61x16EKFM1Ka2G6QNd1NE2kCbC0cychChdccAGPPvc8Tj54kNNPP60ye+Nz61+ozKlHSpn12YzDh4/w8Ss/waFDh7j++q/QzVWv2/d9fdC65RIjIBAkkFJfNb0icXwq3D2gGNWmAD5x5Pgx5uur9BSrfPcmCAaRcqZY8ZXrYKcG7efGNIagsorEPVg2Aw612AcD/zYo3zwM8wN9GmywYgzkVIZj+QUx8GchRrquJyRriBGjAV0Da2avpal8LWI6cPCgSQbEirOMiW9UiuCNLooxk+ONjGbDVcNZNamoJlXPG4fOZmnQFA+62lRlLC5hqQVcKJ7SLnKO1az5R+7MBUDnTOxrb1ZgPb2PkiiREM1xwI+Rk67HPKyKxsYQTdbSd31tViBindM24Ljh3qZi4xUhFzFph9TzeXp/KSVWojp1hNhU6UkwJnVYJ9pkwrW+IQQkBo4cLfzPdwea2HJiOZOSgKg/LaLuIVWz7ZZnEijGIjugzQXWzdprKavFXvHRiLsiBIq5SgwZEss3bGtot+Mbjced/Dh+/uU/v9nDeMCx2q1uWXZ5O/56sXdhL4JwZP3IZg/lAcXehb3M0oz1fp2FZuHrv+FhEIoFC33XDaxbGRg5198pCFGv1Ol0qmDBGM8diwtccsnFnHLyAZ7ylCczmU5oYrPBJzQQRuezoiG8QEy/13U9V19zDXfccScf/vBH6fpeU85BSAkWlpaYzda1H33f0TQtOeXKbKaU1IqKQjRJhHpyymgs1Gt0oBRCoAgcPbHM4oJqMpVRDCQybkKgDNzIWaHA1ADnDCoQK8FZQuXYasq3FCOLFURk2xxUlrOUysQWEax7ME6+hWitepOylTTNRv/XYi1L7bjJ2VKEhYWFeo+9MMydA1Iyjrfk2vAiRGXrcsl4+9OcnSUulQEEzLEg1jat+Lz6psNS+y5HEQNFLi/Y6BMsJLtvfd9VOQwyWMdlG2/Xm+dq8a50bruVqz6161RH6+g/GHMcQjbduI7WJQ/YfIrpfEtvTSiqnoANTLT3JBv2GJbyLwUkIQRWTZ+7M8HdxeQuWZ0eyMOGQ9/rWlW797hGOjDr4ItfzhTWKRIIJRDQpgrFtO7YPIxbB0sI1rrZ5QyZNetqtmhAVnW9A7stosA5Ng2DHmVY9/cV24B2OzZEyol5mjNtpqoL2mKx2q2y2Gy9Cvft+OuHiLDULrEyX9nsoTyg8ELMo+tHOXXnqZs7mAcpcslELI0NIFr0BVQGrUv6UM9QO1qVko2tbXn2s57BC1/4AlrzHLUeqABE/PXg+sMq0hTh1ttvZ3l5hQ9/+MPcdvvtHD5ylL7rK1iKMVpKlerdqmBai9CU9dPxe2eyoZAmV51pyhlB7Y907J62NyYtZQUGNHjhl06HpmtzdgbY/0hlDQFt42pjHksCHJDWojCchUyD+4MxbCKF5bWG628uIIF50sKnYpuHlApB7D4ZSPP/hRFzJt7coNHzNLEhSCQHdWbQ5gLqRlGysLaeDeCbZKMks6rK5myQdM7suMHGLyGoEX/ReVamFXtPIWdR7Wlda4M1mM9hFKGvYF4qIxhDoO+V6a1th23uRLSJBGDzGDdoezG2VX2SVe+c5gpem2ZigN473uk4UlK1QE/Gmw+Ugvmvmv7Zb6kMOtWcEyUZ8yvZ7rcQCoSga2XN2NAdQm1qUVlOUQAvOnEjBly/lqLWX4WOk/bBM54c6VPhltszV3+hkDJI0YLEPNo8qZbbQLqgYNU2ChIic2t4slgt24p9bgZWNkjQJifia93HfC+/SCy2Ae12bIhf/9Sv8/1//P3c+A9v5Kw9Z232cO53fNtF38YTT33iZg9jOzYpdkx2sNJtTUB77r5zed45z6sWPY+EUB9SBQMOYJ3BDG7D1TTK6HXKijZRWbEY4FnPuIznX/68WmDjLJoW9mhxWYWNEpjPZ/Qp8fmrr+HaL36Rz131edbX12pnMhkBQ/crTWZ6n02D2icFvH2aMZ0sMDB8wVqE6tfGujI5ADGVAOoKNdBMuWRiE8gpM591xEbqQ1xCcVxabZEYAbJakpW1+l4L4SD1qQIAceGoHUOySR0kVSDnr7n+5kV+7XczSCBl0zCHaKS5A18ZMcXGTpuDQYgygAqXFpBrIZS6AQiRaEB6gMUVIheh762NcHYwTwV6OWt6P4youmguFoIYC6qT5tX7ggHM7Oxrb5KFUoFlKVRnDNeHNnaWnJL3isWr6hSn6d/7eVdlM+6Fq6BTAVnGGin0iZR61TEb0Isx0lQqvNC5ZMOLIgXjYWUAc7aBUlss30kYw1mKMb3Kjq/ZJnAhZTtYqXu6IINjxhgo1s0R5r1chL17hIsvghgTO5Z6rr1ugTQv6sBhzROCCKm49EAqu68Mv4NpqZKDRbyhgn8+Qv26oRizguzC10K024B2OzaEs7KpbM2H6s+9/Oc2ewjbsYnxxkveyKWnXLrZw3hA8Uj0UNa2prkCv5ySU4qAgkRnadqmgWJ+s13HZU+9jJe85MVMJi3BdILOmCoA1IeoINx6261ce+21fPFLX+KGG26klMDq6kot0GnaxtLDaoY/7+YVXDdtS9fNCSHSdZ25KXSa+jYWNlbdb6PHaxTMNY2mq1Pf63hCoGn8Ya9gsAlR58Hmo2knUKFqriyXamhHBTel0JsO8jRjq0vOJJVwGhvpxTvBukG5c6imgnMplOQuE5HcQDJWW0Iw8Cv1eJ6OFlwPOrQoRgQh04trM6FpAhjrGGKoQMfrnGqThhE4LQVj+obNib5P51SCEIuOMbvcgZF0QFQy4T65fcqIpArOXRYg4udRSUuMoWqPvd2uF3/pkgwGRguSg3atC0Fdq4yVzzlb0wsZtNUmO2na1jZv6q6gzG8GSZDUd1nZ8KZqeUspdL12zRvmx8Zl+l5BXSpcppOLOWKg35vb+ybYRtG653mLWgWPoNYOxeQB1Puk7gMqU8il0FqRWRAhiOqKTQli2YFgMhlvfDJq6qHLhFkYQHYMnqHx4kfd2PjvgToazzJ8DRHtNqDdjg3hLW/vWUSxHduxFWJ7Q7O1ous6ptNJZcrceF7Ba6ms66A/hb6b86xnPpPXvuY1tE0Y9IQjZmd1bY3b77yTm2++hQ9+8ArWZzOOHz9m6f5M20yG49Z2tdOa/mybtqbrc1K/1FIG54UQJhXcRNMDtpMJqU9Mp62Xr9TjleI+ugBDi1JtPOCaWWWFtZDMAEIFa/aQNypNq9jhwplW4f+bOw/zu+ecPtIEW0FOLpTojSscyjpIyVV6kHOhSOaFzzrILbfexrGVKXcdzuQ+E5pQQZTOQWPA0m2eBjumEAM0BohTrteNzUdvLWAFITRRNZKVxtPR5+KuCw4UU9XnVqmGsbHuNQtu0VUgNnWeo6W2QwjaQjcExDZPnlbPtfjKZCaWGXDXCL3P0LamazU7sVKMRRUD5l686NZzLp3ptXXvdDIBtPmFiGqM3WEip1SL/zQtb04d1tIXEUaYsDKeykgP82uTZgysbj6S3Z22oK1snZWWsYZYDx4Qa+zgbK/+CdFt8OxoJVRNczH5DqGYJldQtwgHubk2XAghWAtojYDLHXokCpJtjYl/roeMSRkw7n3GNqDdjhopJz52y8fq37diXPKLl/DU05/KW7/1rZs9lO3YjvsVV9x0Bd/zju/ht7/tt3nq6U/d7OE8KCFCZUYdmMYQqj60ESi5N8urQBMjz33Os3j1K15J04T6QBfRFrd33H03f/mXH+TW227nhq98hXk3t6p6BULJetZ3fWep9KGDlae1XVqgT+5kFdve8KG34xRK1gd3yh0UoWkmFNQmSt0PjIYs2m7U+96nnCobFaQwm80rWARltIqBpOq/apXfvQGtlDIHEP7NoaMAXDmdVBGCp4/1OgK5FhaNv+8scaigZtoIT7jwEM9/Ss+h4xPe+geRY56yd9Yb3Vhg3bW04CdBKOTSQ450zsQZSOz7jum0JRreysZsdl1njguVBEZKoJSe9dla1fWGLAPIZai8dx10MPAXjXl0gKZaVW0+EEIgxDIqMMvVfsuZ+L7r6PqeyWRia9P9YQe3B2dzBRDzbU1p6PoVRAheEGjHzsbUJitsiyHqHwmExlwz4tA8IaWenH1+TUPrqhExvTTGNkujc2Pfy5gXbymA2pz1pimPZQRSLYVR5110W5Kq7EZt9DCAngUKgZSgE2HeZ1tLelZfT00cNM3KVZfBks+KxcYgO5q1mn7GElhrZQevOjZbOANXe5+/T7YB7XYAWojyPe/4Hv7wC38IwM3Hb+b8/edv8qjuf6z36/S53+xhbMcmxat++1Usz5d5//e8f7OHcr+jSx1fPPzF2q3vkRBeoOMWVqDMk7cfFWPQmrYlCFx22dN41ateRRObjenoIszmc971rv/JF7/4JWbzeQU5wTSP/pCPUdvtjs32yeqT2nX+tWM6nTKbzVmYLNBl1Uj25mTgoj9tSNAznS4wn89VE4xW05eckFLY2Sf2pMS+XNg179hHobVWvALkrieGyKrAYQpr/YQTMXC8abhD1DNVMCbX0tenl8yv33oXALfFwD8+9YAxYqU+7x0wqw9sqYCi+sFWOzQzxZdMDMuUWDh8pLDeLWgau2RLq0cicUj9GjOrQL9TEB4CU0uPrwexCn/tYNbElpR62lbdIYIEbT5hjKADrZRy1TSnPHSQU2a0bGCVFZSqBlYlmqUC3JTcH7WYDjsyRKnA2jc8qahdmnetqxZjlVFUKUIIQ0MPL/xSpyyhM7s5Z5FD8Nc5KNMxzjvdxETUHaJpmnrNIcogX0gGcF2zLAOcU3Z7SMF7tzAtDitEGgpCdkALVafrLWkrU2tzlpNJDgLD58vA5NEjLe95/5S+71hehpzW1HPWP7jiGQlF32N5QLF5Ahj8ZiF4m2JEnRPwph32ShnumW8KtyUHWyD63HPH8h3ccuIW7li+o7bw/L2rfo8P3vRBjs2OcXx2nNVulV2TXfzut/8uAP/6A/+aD9zwAQRhx2QHuya7OHP3mfzUi38KgHde+05Wu1XO2HUGZ+4+k9N2ncYkTup5Sym89/r38v1//P3cfPxmfupFP8XZe87m8kdd/qDPwTcjjs+Os2e6Z7OHsR2bFLM0Y57mX/+FD8GYNlMAZv1sk0fy4IVX4zswcB1tLSBi8E190hMu5ZXf8jImTVNZGwdX877jj//4XVz1uauNzbUOZNYFyR/8TYwbLJ/UB1fQ4u9M26q+cmFhQs7JbKUUBM67uep5baxx0pBTYmFhgaU+8dSu5+zDxzi7m3PmvOOsWccZ844FzxM/gJgJ3Ny23NA23NS23NBE2lL4/qPHWcyFN512Mh9pY03vegGO+pY6C6xz7Mb+g4dqqQVLQYRTToEmRCQXbr51RjefEENTvVChVMN+TJcrfg8l1mPuMjZ4xVjFlLyJQG8tZLV4rRQZWt/CoMPMBff3tT1I1Wf69xx04qyjjSOGoUlBDAp++pSQXkmOxiy4UlI9KKmv7Ktbb4kMzT1clhKjthNutHlabb+rWmkqU+xtdPteGdeepG4Xts4cPLt7Rt/rebzzHaXUtsBR1E0jJZOdeGFYnS8x7XipzL2YFkKckS9Cb4Ll1rIRRaR2qxW8o5cBWXu/g9EoQ/vgY0fnHD22rnNNoIjbhjFkMEzm4FIUP6S/RwSk6JoDELununkdtch1ztcyMx76921A+5CIw2uH+cLdX+ALh77A33nC3yFI4Kc/+NP83Ed+jtuXbx/tYIT+X/YECbzn+vfwts+9jd3T3eyZ7mGpXdrAQM7TnHmak0vmrtW7ODE7wYGlA/Xn/+HD/4H3Xv/eDeN47tnP5S++9y8AePFvvpj3Xv9eztlzDn/5vX/JM858xoMwE38zUUrh6PrRan+0HY+8kK/xy+6hHl6QOTyiH/4RQqDr5prmtQfbWH7gD9XTTjuFV7ziW9izZydDBbQ+5Lsu8Sd/8qd86IorjM1tjNkzPSbQdz1tq4+72rLVHuraptSqxg2oeTFYSomAHqdpGmU2u44nr895/PIqF67NuHhtxtnzrl7Tmgg3T1tumk744K4d3Nk2HGsCx5sJR2JgZdKwhvYRyAWSVfEv5sQ+YGfXsbPrOCkXTpspOD573vOM1XWW7IH/memEf3HwJK5pG8jZtLiqNU2p17mpuldvmZtGaXRlJ1NNpQtnnrbEpF2nEMjSoJX4BoC9q5V3iLINgQQHJmLODg2Lph1dtTy5bzrGADGY60G1dRoBn5QSs7luSt2/tJjjAeJFUfYeZ6WLtRSmNphCNzzUTZLbmcUYTJvpXbm8uMxkLjFYG1+9DrUSK0jSwr3oThwmU6mbCUPl0Qx8c05VBqCMq+pkh7bNwxy41KWMXBjU/1bZ2/Frx58dZ9hhGIizqq4TTq4NLqUysc6mqpvG4FghAW1OMdr0+f1uW1haVJu3+VxYnQdyEfO8lWq9V9eGmFTHWFy3DDNBNACNrUftJsboGt2t4p5uB3zVv8exDWj/BmK9X6cJDU1o+KMv/BE//cGf5pq7r+HQ2qH6mssfdTmP2vsoztlzDi979Ms4Y9cZnLH7jPrV4z+/8j/zX171X+7zXD/+wh//mmN5+7e/nZuP38wtJ27Rr8dvYfd0d/35k099Mq+78HV835O+j8V2a/u3rnar9LnfBrSP8HgkAcKtHmpzpWndYP6kMaq+UIyd3btnJ9/+utdy4MD+WgiDCAkFIX/0znfxsY99zMzoVbIQjAnzwpXgaVdjbIsxlpmeUhL9PNEsLVJ6tPMRA+uUuo5Hrc957okVnnX0BJeurFXW9da24erFKX900m6uXpjwpcUFbg/KnEXrSBUqiNPuXwM4GQpdAO5YK9wUIs3CVGsYRO2pStY0bk6Z/SkTc+J2SxV7Ot4T2qlkyCMgZ+xfMgmHgytQjWsw0BEDLLTHyZLousJtd0VL9yqrlpMBKEORCuwgF0uxF1VhJJNWACzHqC1jRQH0wlSbhVTAgxZM3fPjmimsrK6MCrXUT5ZEnTdAK/ANkI+vqzebNaAyo5gSI48kDE3T0DTWgjhnaxecrSGEeqsGL3wTqhewoI0fmtjaGu4HiYB7uYoCMm2O4LprLS7ruo6SM03bIBIqyyuiUpVskgtBKohfnykz6rKDKlMYS0uLamIlWOPgKhkYolAqIFegCan4xsQ1DVKlJW45V0g85vwlXvrCBZoofOZza/z5B+aUMnSusz0Ebr2mfLBJLsTa8gIEIdWNkLXolcB4Ifi5gwwg/p62evcW24D2mxCHVg/x/q+8nytuuoIrbr6CT9z6Cd773e/lOWc/p1brve6i13HB/gu44MAFXLD/As7arR6vb3jcG3jD495wn8f+WjfvG4l9i/vYt7jvPq2M/v1L//1f6/gPpUgl8cPP/GGectpTNnso27FJMVTtbr3Yu7CXV57/Sg4uPXJaN4vAzh076C3F6wAiRLO0ivDtr/tWzjvv3CpBcETTdT3vfNe7+NCHP6Tgy1jAUpJ5mA7tTge2Tiu2U5/t4R6RRowhhqXFRdbX12nbllOPH+cVR5Z56aGjnGUM7LULE95+YC8fX5ry2V07uDNn2kmrDPCkVcsuc2soYs4NxrYVT1Fbu8+UerXKyoPR/Xw+J8QpGBwYWFZNiR8JDTlbkY0MNkd5RHF6dbjrDT1lPhQ2eVgSW4QQEosLcyiBbha48Uag/kwL9Vy24W1sc06qtdSXWtoYzpvNScD1cfAF7lNmfX2dyWSC2pm19F2iczlI8REpcEm962SdBR2AjMoRcl1AIQZI3hyh1HWkGlS1gXNw5POj1lwdMTZ1Lpq2rSyjdu7KlSVV1lW9fgswn3fqH9soKA2Nk4/FNLV2P0weE60wrZitVm/XmEtfpTClAAFiMF0DmupPfWJ1ZaXqg4EKXKXO2Ybbqr8DTXLRmrXb3N/LCBhWanmYmypHsc+bdxWLIdM2M5qmEOgZ/I1HbP0I/GOMsNg5fbB+/QCqZi+DDneUVfD16//+Rn63bwPaBxC5ZNa6NXZMdvDRWz7KM375GRQK0zjlaWc8jX/0jH9UO/286rGv4lWPfdUmj/iREbunu/mZl/7MZg9jOzYxXv3YV7PWrW32MB5QPHb/Y3nnd75zs4fxoMaknTCfzSHIIDsoXkQTOP/88znvvPNq+hE0Dd3nwnve+37+8i8/SM6ZtpHaJrXvzWOUTCiBGIVknp7SKHtFIxQSIbQGbnqVFHRzXn70BK+//W4uXVkjAR/ftYP/99QDfHDPTu6ctHRdR9NqdfrCZKItUKMC07ZVu69kICBbGl51uKGeR4uzGlLf05tEwFGJstRSASL2yFfJQKsaYJs/BQyhWp651ECx60ZA4EBl+LcVL+VMIfKZa/dy023HOffsA/Tl+KgwyFi3nBH/XghI0eIjPWZAREHoo9fn3NQ2zIIQDcy7PlXBXjaHg0gUQTLK+mb1oy191ja5TdSipmRMrMlH3MJtvB481S3mzeqAthudX0agTbuVFWNsdb25xjgYg56sS5lrjgUtxPLNCRS6Tjc62spXWVMtXDMP2a6rbPC4C5mPdz6fk1Oit+uKtRmF6n0lb7Qmq2HMfi55YNxtCbnGuZjPwMSZawfVtkFQ1p5aRIfeBpXflEHaocA32aZDgKhs60i64Lr1sRtF3XtKQbKzvQp0vdQrmebZ58XXEoJ2eZO4zdD+TUQumStuuoLfvep3+f3P/z5vfvyb+akX/xRPOOUJvOXyt/Ci817EU09/6oaCq+14cOO6I9dxxq4zanHNdjzy4ocu+6HNHsJ23I9omkZTvUUN1ufzTomcEphMGl74whewa9duvHjMJXgf/ehH+OhHPjpYcgUhissREpPJxPw7qelmREj90FZXgnX9Qpj0PW+68whvuvMQB7qeG6YT/uOZp/Bn+3ZzZ6tjjE2szGHf97RNU7WOOWUrOKIayac+4QVG0Rg4Z0rH7V9DseK3EOj79dqsQaSMdInYtRTTm5Zqz+QP+cb8U53dq7raUdSOZyO2K4ZITj033Zy5WXZy1ZfW6JMoexbyUDAkVhBWqKCLXChxOG7JhUfPOq5bmG44hzoWZCuqU3eJJg5+vA4ac9YmF0s7ljixvm5FX3oMb6Kgc6o9rPS2Dp6y4O4EQdPhdn5nbd0KbWiu4BuAZOPYWDAYQ6QnDXKD0c+aJtJ1WlSmRWrDOhNxRwmTPJjExaUQg3QhmoyGyjB3faeFUzLYi4En9isZztA6F5uH0b+dMRdhWgFtUwvOUsr150Ggz+pBazsh2ziMNys2z6jlmNBRN0x23T4ukaDdwkya4h69wx2CiTlhzEbMecE2DAZwm7at8zVc49fOWG8D2m8gfvaKn+UXPvYLXH/0eqZxysvPfznPPfu5gFYm/9jzf2yTR7gdpRRe/lsv58IDF/KHb/zDzR7OdmxSzPoZkzj5a0t1NiM+dsvHeO3vvJa3fdvbeP6jnr/Zw3lQom0a5vM5ggLA6WRiIDFwysH9POrss+rT0otzrv3yl/nTP/8zZrOevk+k3BGSskXKdpaaHhfrBy+Wno9WCOUArCmF1919mO+97W729z0f2b2Tn3jUfq7YtVQ9OT0Nmk0qoCBD2cYQQvXsLqivZpJkVmFU2UCfk6kJB2cG19RqZyUv8OkJQR/LCii8wh19bxBKHhrgNHYMjzHgGksZSr2GbIzc8PoSgBJJJdFIpGSpXqsY41dQGcigfxWby6GKX0TY3fecPZvzJ7t3qLbWxuXjDdLgaeyUsxU4l8r0IrCwMOHAgf0cv+FGK3QrGwrRYNBG+3VVUGy6EjEWF6+QL+aOkFOVnjhT6+BStZ/ZvFWpxwrmbNF3nYJq07mKuRb4uPquI2F2ae7TK3rtEqTaiHVdV4Gf29OFGGjQLETOqbosuEWZzjkDK2r3LkqgL+7qapsH+xqKula0pmme20ZATGbg7iE5Z2tfm22jpAx8cPmANUZYXc3ccmskNsLdRwtFtAvcuOV0SdoVzudbC8OqSqh+Bhfs351pnJVZHiQQIoE2ave2QS709X+nbwPa+4hr7r6GCw9cCMCVt1/JufvO5d+84N/wmgtew67prk0e3XbcM668/UquPXQt//Dp/3Czh7IdmxiXv/Vydk9387/+9v/a7KHc7zg2O8Zty7fVh/8jIVbX1miNpW1acxEQlR+8+EUvVs1l5aXg6LFjvP3tb+fQ4cPsWNppaXx/hTK13nFJ9XrJdI/6gM2j1OiTTqzwL265i3PXZ3xi1w7+2RlnceXiVDs5AZj+0hkkBypeDV+KanCDBOu8ZUBCAkNPBe+OxD3YwWJFQ8ru5aTj27lrV200UUpGcqiyAH+g1xS0UEGrF88MDSIwT9VhHDCAAk9tiwjnnyOUPnPj7ZHUDwDW+3+FEMiph2rY700gBtbStavPXV4nAh/au1Mr9mNQjWuB+WxOiBBCQwH6vlPA6rSdcZAbPImrjraM9JNSbb286MnMp/QIBgSb2AysNoWx/ZPqa3N1O1BvYqr8oO97emusVszvNprlW7F57ru+ArkYgzVwECSXajGWUiYH1QxXLbLNlb8G05SKCE0wmzrbPOSSLY0/6IjHmlKfI5+fMeTz93u+ch2swNBYV2N4a/HZvYaCzJQLX/7KKtffqOA05UIhmixGapYCs94S26SIb8ZGmYRSwMvPuzg4mvi6Uv2td07bCGI9Q3NfsQ1oR+GerD/5Vz/Je69/L5/8wU/ypNOexK9/66/ThO2peijHr175q0zjlDc+7o2bPZTt2MRYma9U/fpWi5X5CgBL7dImj+TBjaZpmPcdKWeVClA4+eBBLrroIhMGGsMYI0eOHuPw4WOqo00zBYUS6eaJxcWJpaP9IY/6YglIUUsiSmFHyfyjG2/ntYeOceuk5Z9ccC4f3L2DPicwlq+3yvRsafJsgLvve6JLDiaTWuRDKVYd7366CjYdwDRmAxVjHCyZcDukCUG0MYQWbg0Fbc5yZgEx8FoClNqdCdMZmiTAALdbQzVNqKlu10oGKYSgFUgH9sG3vrRlaanh459pef+HZsznVJcIxc2F2Ih1G7OuWVKITUPfaUrcW8w+98QKh2PkCzt30PbWxtd8tNQzlVqotX//SZx91ll2DUOR0p133smnP/MZdu3bpylrt1GLDdkkEBXUgdlxeYcshUB9yvSlr4ygMq1jf1ulDfs+IXj72uAzWkE9aFc5DDj7NZQYqqSj3rNSEIkUycaAClhDheqb680QjAEto+suVshY5REhVFDumyrA0vjBUvu6pgNCrgR2QYK2FG6aCQv23k5852AsqGULMhAipFQIbLQOLAISVZJCBc5aIFdEiEW7+uXevHxNG1MCCLlmAgDEshIlF6YGoLugFmeDlEK3JVlEN4kBHNSW4iPb1tB+3bjytiv5x3/2j3n/V97PaTtP42de8jM85qTHAGyD2Yd4rPfr/PZnf5vXXfQ69i3u2+zhbMcmxmq3umUB4Wq3CjyyAO3UtK6uaXQWbjqd1nSwGsErg3PFFVfQNA1d5wbrClJqXrOYhi+N7KqqrFC4cG2Nn7j+Vs6Yzfn1U/bzK6cfpG/Vfqmm5Ytrb0u13BIRunlHNJ2qGIvnjRa8m5Sztn3qaUwn20TtlAUYuIy1SEzBC2DPmNXVFdp2QmyDFnwV6yQVG7KYbrVoS9Pillwp0TRDh6XkRUwjJs+/xiCo1FeYNHNe/JzISSeptnLX0holu9xRGWLdSIjpIQcQVOdrVNATRXjO8hof2L1EbFu1wLKOrk2jc1HyoKvcs2cPZ555Bv1szpAuV/Z0fX3GbtHCM3c0qAVQfl/8HUVtosRS4C7nEAF6ZTgDrntu9XXi+t5ihyykoi4GIYYqAwlBaNsG10J7xzWXjoydGFSb6ppab60bRrrZbO1v88C2omx5MrbXNwxS5TNW5OUYzhlpcSssT+vbxk3fYCBZbdFip8eZw6gFrbkIuPVZ8K5oA/NbKIj5AAvCRRfu4DnPigiBz3z6BB/9ZCLZz7LNIUEoDG4a6l/snz/qeF0GMQsGZnV/VTckCuwHpt4u3e7zff8+2UZqwPJ8mRe89QW0seX/efn/ww88+Qe2C4u2UPzpl/6UI+tH+L4nfd9mD2U7NjlWuhV2tDs2exgPKB6JgJYQaGIwbaMooBC4/PnPpZApVv1O1IrxY8dOWDV6IPWF0ERSVkCUkrG52U3qc2Unc868/ugJ/unNd3C4afg/LjqPK3csknJiMm46YOnuOGbfxLqXjSrhtXbGxleGNq3uWxtCYDabGZDrN2g9XfPqDQbm8xlt6xKEOBTX4OnwMCoCM+wegrJ7OonUlraSq6doCMYSW/p6aFIATVt43jP28YRLMpPpTu48BH/5sRldmjNplirw0gnFXBQcHAshKogNtgFIKfEtK+vsyZl379tNyYWmUVArpuctpsMQ02We+6hzTENa1RoArKyts2PnThcg4EVpDmhTHhhwH19BWWlQdllKsUK+pmpwS8m6sTAgGmNAJNZj+n1KKVNyT9M2hNAOkgRj47N3EQMkiFl3SV07fi1DBzIHtfp1bk0jXB8M6jccG+1GJiEjMZB7LfDr+76uwxEJi2uPdRcCwqBZFvtPLoXWNgTzqIi3mH5XKNYUwbIKDJIGRBssFG8mIbBzsWXfnikxFHYsiWYFcHBfagcyE/hScEeFQVHi0+RjmjFcUwWv4rp1cMcD0/R8XS3tIxbQllL48+v+nJec9xJ2TnbyB2/4A5582pO3Tfm3YLz2gtfyge/5QC3U245HbmxlhvZRex/FGy55w0OmdbOIRODjwC2llFeJyLnA7wD7gU8Aby6lzEVkCvwG8BTgEPCGUspXvpFzJGvZiWhR2OLOBbr5nMWlxVoEU9DWnl/60pe57bbbKUXtsfwhX8gj26RI7py7MzatZP7RnUf47jsO8cHdO/hX553J8SYawEmIzKtjQCmZKOqO2XjBmiFMLwyjahWVtYwh0pdE07SIQNO2CrBs/OpAMDDQ4/anzkinlM3SK9qDfdDLmvq1Fv6MJYQ6NnMfENMydnNjOsV8brO1ATbtbREe+6jCs57eEprMkWXh7X98mDsPzRECfeqIoSGNWEE/p7Lhgnr9GtOIFtx92x13c/Ok4UO7dxJKIaV+JHdoEHL1GxURLn3c46yrmYEUS1e/973vU2eAosVXWgw46Gj1D4NuVKgaXmX7UfAUnNkf2rqGGOoxdWORBlsvaa1DmDK1OatXrbOWsYkEYxazrUvVPqeRrME02sbKJgOjY3DrQG1gfZVFJg0gWEyiIWBNNoayr7rhcQmBxCqtKbZSgqfsgUktCosDMy2Y17POeaTZwBxX5tnO6VpwCREJmUwkl94YU3MfsfO5Vny8bqWC2YJIZlq9ccOGe6gbr4HhrdjV2Vn/x31EuM+fPIzj9uXb+Vv//W/xsv/3ZbzjmncA8MJzX7gNZrdgrPfriAjPO+d5X3Pnth2PjPiHT/+HvOS8l2z2MB5QvOi8F/E7r/8d9iw8NAAt8H8Cnx/9+98B/6GU8hjgCPB37ft/Fzhi3/8P9rpvKObdXAurzEc15cTFFz6WUw6eXD/Pnj5dWVljbXW9FqB4mnfSTnCar3ZYMtquEfjxG+/gu+84xNv37+GHH3M2R/yBW4YWqtiD1J0UQKvRo3Umi8bCNeblGcyia5Az2AN71MzAMVo0vaVYirhpvPWuuxAMxvs5u02Vj031kYGhnanbPAUZtIfJGGmwAqYQdKwIURo7v/7Zt7vw8pfuZWlHRsIuPvbJxC13JmJoKotcUKcGdyXQiv9CISFhkDR4MdWjV9d48vIav3dgH53ZsAUvpMqZkhMhKNMXRDjl4EEWplNKEbtm7Sx1+Ohxji2vMBu1EnaA5V+dGa7V/67bzENr3ZS1IYH6EvcG4PQ+jN0XtAgpaftjY0wreB25Y6SUlCm1zVeMWgzor2G0pmw5VW2xbyQG0F2qptZ1sk3c6Lfapzk5dxSy3QdfBcr0uuRB2XkhI8rU6lZGN4lF4aTbds1FXblSLlCEXFQO4IC1zjcunVEAq1oGIbaNsrmScFff4ZE7KFuLs8CohFgt3kxrLnqfFwyz9sGlQ0N7ZL+nMcYqadG1T/1zX/GIA7QfvPGDPPG/PJE//dKf8u9f8u95zQWv2ewhbccDjJuP38w5//Ecfvuzv73ZQ9mOh0i85QVv4ZWPfeVmD2PLh4icCbwS+GX7twAvBN5uL3kr8K3299fav7Gfv0i+wd1l3mA5BRTYvXs3k2lrz1E9TJ8SV155pQIMZ+2yWRtZyrsCDuzBWDI/dsPtvOLoCX7h1P381Fmn0lnKWM34xYputErdwWu1cSqa7q0FPfbAHbS+OjZvolBMH5hSGop4ZGSRBTX9PlhoDWCnaRomk4k2mGC4dgXEwVhEA3IjkKfgagDFbaOa4JrnRYFaiDqQdhqZTFpiu4fPXDPnik8co1g6vMAGDTFYAVJNm5d6HhE1548x8P13HWVdhD/ev7feA2cLvbJ+Om0NbEfOO/dcdu3a5ZJYYwMLn7/mGo4fP74BwPq1RZMJBAM6es9GIHXUFc59b1NK6jRQK+bNs7hpaJpB4+quA4PUworARpZqKfnx+qqZ9oYRVXLAiEEeM54ysvgqQ0czl8cg1Gt1ba03aMiW9q9ron6yho5avtZ8zfg9AGjtPnYMGwDNXDBCh2PeX0+heuFYgXlKmdl6YbbW0PWNbm7EshoxbOjExgB5B4bfz1UGkD0L7rYw+nUxuo7Rpdbjfq14REkO3vqpt/IDf/wDnL3nbP78zX9+n+1gt+OhHykn3vw/3szKfIXLzrhss4ezHQ+BSDlxeO0wexb2bMkGJ//0z/8pb/30W7n9n9y+2UMB+I/A/wW4R+F+4Ggppbd/3wycYX8/A7gJoJTSi8gxe/3dX+8kTduwvr7O4uIiqe+ZTiZcdtnTDOQUJILnM2+88UZjCYtaUnU9KWklv6c5Xe8ZJfDPbrmLVx85zn8+dT+/dtpBBZ549Tr1Aev/dRmDMp+lOhKEOCr8GhVZjW24KFjquBCD6Wr99YEBhI4e+n6cqbXODbEhNK7nlQpW/fUwdFOKraaIp6Gl9w5XIaA4RWhLQ5TIjh09F154kJ1Ly6yvCx/52DKHjrT89n9f4cKLlvnYJ+ekLtJIJMlcmU8Dj1kCXdcr6BOhmGODa0nF5vDC4yt8y9ET/PIp+zkxaQnzwnw+Z3FxkcaaT5SiLmgFaCeRk08+ULXHDr7W19b58Ec+QowNbmflABFPYVcngIHdvud/QbtspdFcZ2sk4JuOYPSigtFAa8V12c6pahbXcooxwkOjCO2mVSxlr8BWmsbAWRoAckoUu4e1pax5q7p2t086x5DN6kxdBFRPHbQ4bAODOmyWBHOPKIXgoE/M+9VmxCUHXQz6Gk/z1wIuA6CON+2/Phe+KfncZ4/x5Ws7RAIra0KhqdKHOjxjYbWYUtf+0GHMxheGorC5SUt8AznMsYyyHzJ8Zr9OPKIA7ak7T+Wlj34pv/m3fnO7Gn6Lx89+6Gd5/1fez6+85leqG8V2PLLjtuXbOOs/nMUvveqX+IGn/MBmD+d+x/HZcVJJX/+Ff8MhIq8C7iylfEJELv8mH/sHgR8EfcAvLCywurqqD/UQmM9m7N2zRx9ybjMVAp/99GeUIbMmBprSlcrKxUbbyDqz83cOH+c7Dh3jN0/Zz387+SRNn2bt5pVHOkHX61VWVaDrOybthMxQVOTgTfvVDwA1pd50pQYArFgI6/RVQMcY1ClgNA8VHAcRpm1LbwAIhm5XXoSmEgQFuzFELUATMeN908saS3buWRPOOXPOY89fZOeOhj379hInuzhyWLj5jru59dZ17jqWOPThyDxHA8lp5I+rrFkToE+dggkbZxr54RZju//R7XdzOAZ+db/etxDU/Gk+mzGdTOi6TIytdaeCtok84fGPR2m3AbCszWZ0fSKVTDfvtXlCzgPwdWZ8VHTlIMibFFSwNmI6xXydszHBQaDHu7cNMoEYI4GiHd6CuRb05p7hqe+6EVHWNKe+guRSMqEMa8tBWl0b9jUG9eZN1hbZmVqKSVaCSWLDqEhr42dIv2JuDAbsvRhQSkWRiAiTnElACnoPXfOsIFa154oryxg3m3xGmWKRzOo8M+/tvhcQIrn+vnK1LQpqXcZzD7AMaJvrMUOrahblj4vqwb09cBivkYLKdL7G75eHPaDNJfOhmz7Es89+Ni97zMt46aNf+lULZDu2Vnz0lo/yf7/3/+b1F7+e733i9272cLbjIRLu47pjsjVdDh5CDg3PBl4jIq8AFoDdwM8Be0WkMZb2TOAWe/0twFnAzSLSAHvQ4rCvilLKLwG/BNC2bfF0aTRQ+PTLnspkOrGipkIImSIN133lK6yuqguEdy7KZG0ba7rMvmjx2DPX5/z9W+7k3bt38B9P3W9pfgWGDlyqMb1Y//mUiG2r7FdRUBujtrodvz4YcHK/2cYqkEKMNLmQAsayaRFUIy2FGU3cQTPpCcwhFaKss2tJaKYncdMtHVky5EJvDgnKUgagp5SsClPRlrip9EwnmUno2bdHeOz5J3F8ZYWPfjIRmsITHr/EJRe2zOeJpSUhTIRutkDTBhYWJzRRC5UkQMziZKFiIAOOArSTCZM8qUxlCIGu77Uy3uJbTqzy1JV1fvL0A6y1DQ0K9ruut0I9BeJ9rxsWKbB3777qDFCcSszw0Y9+lNl8XhuLFGP7/J4oe2fMXVbDqIx3VNOOY2JSANEDqIWVAeZgmlMH5t4WWB0sBl1uic7CK5gbwHQ2RjSOwG0ctNem6zblTF1rIoJ4Z7Ougw0aXpN1VA1trxrUpKAwmZb5qxHLaJNTMiKFUMbFe6GOoS2FThS8+mfAdenYfc8MzRv8nvkL9Drh0Y/eyQXnN8Qw5dovrHH1F5fr3OqmwMBmccBdrNmC3Y8wyHlcctCZPtgLQ6t8A2rHMny8xhbzNfDbwxrQ5pL5wT/+QX71yl/l4z/4cZ582pO3wezDID5y80c4a89Z/NdX/dft+7kdNVY6A7QPDVB4v2OlW3lIgPFSyj8H/jmAMbT/pJTyXSLye8DrUaeD7wb+0N7yR/bvD9nP31vGVSZfI/q+ZzKZaPV5Fg4cPGDtLqtqkBPLy9xyy601rSziAEVN2gkKPGIT2T/v+fEv38RN0wk/duYp9DkzidHM900KwNBsoGpjy8D+UiUFgRJGD2tjncRAsLdDbazTWQhC6o5w6qm7Oev0BSYx8amrEitz4UkXrXL5cxuasI7Q04gQmsyVV61ywy2ijQB6BRVNaDj3zJZTTm1oQyDkZZqYmexquPHGzNVfCLzwmQ2XPUlNj0KzzOETi1x7Xc/Kcub6L854wuN2IKXlC9cc4/DxxKGjC3zqM7eQy5IWzllKOMRQm0gMgEIBRN+ruiSlRNu2FRSKFWbt73r++c13cvXSAr9/0h4E6FNPjNpprYlNZfz61LM4WUKA5zzn2dpAIw8FfDlnDh8+Ut0DXG6hQNIYbrxDmRiIE6S6B1jzAl3Bei8L5DS0w/WxK1sO3jksWUo/FX1fzkUL6oyZVQmCwuSSSwXCDsrFNMUDi24a4jJO54dqK+ZzmlKq1yh1fKbdNc1yymkA9kFckjoUcRkwLSVBaGoWwEGrg8d5uJdyKTtGGX02dKpCPX5tsFAyp54y4ZJLlgjScOxoxxe+JGQi6/M1TqyukJMW4+3ascTS4qKef3QObCMRgKnbdsWBUR+3EXaHhRC8yYXh2JF84d7iYQ1of/Q9P8qvXPkr/NjzfownnfqkzR7OdnyT4u8//e/zvU/6XnZOdm72ULbjIRRbvdPWarf6UAfj/xT4HRH5ceBK4Ffs+78C/KaIfAk4DNyPdn0OFDL79u3lvHPPtUIh+36B1dVVbrnlFpI1EpAMsWnIucddCWIIZDL/9Kbb2ZEy//uF5+rD0kCZMLA9yk4OKX83sC+WbneGquCtdNX/VEZFY0ECbTPn1IML3HbHOkEmLC4s84Nv3sHupTkLi2tkOm64ueXY7VPaSWH3Qmcep6a5DA0iq/R9S9dTu1jFtuFpl65z6YVAWDGmUIFYN1/gs1/sOXRkkcIRYmwRMvv2LLJjxzLHj0W+eHPHL/7Sncz6RVbWOnJaBtboU0OhJ6DX7FIJTGrhOlmVFQzgFS+Ew/xo+54iwo/ccBuLOfOWR51Btnlrm0YZWtQ3WAvcFIx2846FxUUWFxYHks2Ywzvvup0vXXedtaMdvFpdQ+xrxbWtbtMmMlxCfVVdP4POuWTtbCUlA00FT/o6reQf2gZ7cViqQNTZcZdfpKQtlT0djjVR8PEqmFVm1YsYKUP73hgDjW+cvOjMQPi46K+UUtvg+jq2v2CL2T5DWuRlqmM9c1Fv2DZnBbT2Hi+C87kLYdBn+0RWKy1jx3U9TFi+fZVbr7idwx+9i5OO9dAlDofAnYuLJGOydzYRFhY23BTXgDeW7ZjkojIIl4wwlnO43MiuV8Ya6bLhXt8zHraA9tc/9ev8uw/+O/7eU/4eb7n8LdtM3haP5fkyb/r9N/Ejz/oRnnfO87bB7HZ8VVSG9iHAcj6QePljXs56v77Zw9gQpZT3A++3v18HfFUFZillHfj2B3YGLdgJE2FpOuHg/v1a+CP6EC2lcP311w+MUclAhqIPYDW5T4jAi46e4EXHV/i50w7wpbapBT1Vq+hMFOg5QqkAIqVcWUBlkhJhxB4JgYWJMGl7zjl7wuMu3Ecb7+b0Uxb4k3c3fO6aOcgO9uxdYml6CMmZrp9w6cU7uelWYXU1cWQtMFudcMftM26/a43jy3Dk6JJJCxT0NE1EAtx15wwujkiJdH1iNk/0KQKJkiJXX3ucvbtbDh/NZFr61HP8qCChY20tcmJ5AiREjD0sRbuLYcDd0tiavbeistYAmTF73kygRxnsGBuKAY7XHz7Gi44t8x9PP8iXFybEUph3nXnpanFUSomuz4TYEgx3Hdi/n3MedQ6uqxQRihTW53NW1mYECTRtAwV6ZzqTpvuD3Rdbc3WjoWx5rClz7cCWgFDZz5SSgsucofQwuk4K1mRB12Pf9/X7SFEAX7QrmjP01YXBjl0bH4gXN8UqTfG5yD5mY6T9GI5NkqoSKBhrbPxoLEPBY5WHVIBbQNydopiOVkhAKAroJyY5oG7qStWCG3ltQHJsZ2d/F4XlUuDYl+/iit/7IsduOs56jNy6Zw/Li4vMUmLedRRgMSXOue0OZrmwfNK+yhS71ECzIYxAtrshjH6fgDZcmTRVCqIf/1Ln/77iYQlor77ran7wj3+QF5/3Yn7+5T+/DWa3eCzPl3n5b72cD930Ib77Cd+92cPZjodoPOakx/ATL/wJzt177mYP5QHFP3j6P9jsIWxKiEDXzbno4otw/1jFrNrt6tOf/vRIMqBMl7NZpSjgWcrwIzfdwdULE35j/x5l8JIVdYE+yM3aK9QH7FDkpenpbI4GgmStzHFXgiCr/MD3Xswp+4V519HGGSlNiCI86pyWz35hxryHv/rwKm0zQ+ISs/kS11yzTpHIp66Cz1yjrF1mgZSnQEZKIBc18Z9MIpMmkvuOL98amFw5IfUncdsdy9x68wrrc2GW5oS4wLG1wLs/tJOSE1qpfgIyXt2DoEBrOp3SdR3T6ZR5pw0kEsm0w4OO2O2fmqaht9R9182tVSw4kmqbhotX1/knN9/JB3ft4P89uA93fMCYzcYAnzYVSEwmDTmpPOSkfftYWlwi9d2GAqQrr/wUQL3/04UpgaEJQE6FHDaynIOdWjEdbTG2kZELggKq2s3Lu7QBJTvILUNaXwZWWNzOy4BzMW1xsfnwtsd+Im9560wyUIvo1CJM6msqCMZB+MgKzbW9lVkeLLj0zApOfcw4m1oKJWnDBGenASalqJvA6AOnulm//y4zSF/NfpoOefHwcY589laatRkC3L2wwJ2Li/Q509l9aErh4uVl9nUd3Q03Ukph9cB+K0BzEZGC6WkpzMT9janrp4BJK8Z6WkG7kg087X3F1wW0InIW2gXmFBvTL5VSfu4erxG0aOAVwCrwPaWUT369Y/9NxUUHLuKt3/pWXn7+y2lju1nD2I5vQhxdP8qr3/ZqPnTTh/jtb/ttXn/x6zd7SNvxEI3HnPQYfvS5P7rZw3jAMU9z2tA+ojbgnvqkFM5/9KO/Kn987NjxUTGYSguc1UXULL/rOr7j8FEO9okfPvtU5qWwUNQf03WaXtQTTELgrW2btoUypDubqDZTWaDregUHIuzYucCB/UKImZaOEOC22zLHl1e55faGUjrmXcMHPjSHsqSMMJ116yr0WVuJjrsxeao7hMhkoo0QVNIg3HDrhJtug5SPAxDCDgU7OaGdwSI5FUSaOl2ZbAjfu4tB13W0k5bOrbNGxXHKwno3qlwdFUSwavtYvUhd2rF7bZ2f+tKNHG4i/+rc0ysTKDHWiv2UEpO2NWAdK1AGePozLtM0+agAKefCnXfetSHdLEmsW5io+X/Q6qUQ1eGh5FKBZ+8MqrGXDnTHThKg5ws2x5iTgINBB49+/RU8GdgcQHQP3u7YHR8MMEdjYwfmuNRjjKUFIkN639dlKYOjhbPjtWgx5UFDyiADKH4Ty1AspeyxgkC3oNOisFDfj7GdhhWHQrIY7boGaUPoOk6+5VZ2HDqywQ/31NVV1kLg7qZhwa7zjPV19nXWECMIJ918C93CArMdKgHTwi+V/UxLpgu1XYjhZmeIhVi1xBvvh29w7iu+EYa2B364lPJJEdkFfEJE/ryUcvXoNS8Hzrc/Twf+s3190OPw2mFOWjyJN136ps04/XZ8E+PQ6iFe8NYXcM3d1/C2b3sb337JA8xqbscjIo6sHeHY7Bhn7znbWl5urXj0zz+al5z3En71tb+62UN58KIoMDnttNPYvXu3f5NiDNR1132ZO+68U79X1Eapba1bUhBySuwBvufOw/zl7h18ducSoRTTw3oamiFlCwaSlMHydLJbNynISDQxcemlu7nqmhOsrWf6vuGO24XZ2jKf+swdLK9NuOXWdZZXraiKhhAzFC9kUsbL9ZgCeLuBaoTPoBXWAiXtTpaKFrhVXSsDKHJUMrYc84r1uhESt6tSANV1mr5W8BwqMyuW7nVN5VCU48VXGBeox5zmzM986Ub2psT3P/osjsRI7nskxqHACKqLgLKkRWG7jX/v7t06viAoUaz+widOLFfPWmCQFlBG160g0UGNF+k1TYMXYHnDg8pY1hQ6pr81W7IyXHsRZ0KpgKq6YoxAadM0VLI6D+MYWtsWgml8JQSCySFEgjXzyFXiUYC2bc25YcBovg7H93LobCb13hYD4/bF5CPJmFY/mjXsyJn5OG1v62f41xgkqkdvVo8z9t1xJ0t3H9JsRf10QlMKj1pe5pzRRzm6rABAAm1KLC4vV0A73iS0BXNeGCQELuvQe079g99P/aR8TYb26/7WL6Xc5mxrKeUE2grxjHu87LXAbxSND6P2Lqd9vWN/s+N917+Pc/7jOVxx0xUP9qm3428g9i7s5SmnP4V3fee7tsHsdnzd+NUrf5Vzf+5clufLmz2UBxQr85UtW9D2QEM7WzWcd87ZnLRv7wDYBFLKHDp0lG7eG2OTEfECJX3aNU3DGw4dY3fK/JczTtZq/DIU4YhQ25pW+yWAEun7TJ+Sgq+irVK7Tgu3Ln/eXl73mp18x2t2sGtn5sRy5j/9t6v5b795Bx/+ZOazV69z+CjMu0yfZqQ8p+sT874j5cSsm9NbWrk3H9BcijkZjMA11G5k825OX8YFa8E0kQOTXVLGTZxqAVL2ZrkOYrOxvaicIGeVDtj53IbLz+0Ad5wCx1PfzvrlzI9/5VYuXl3nR886lc9N28o6uotAYwVhmjIPxDgZsYGBiy66kD179mxoUCEi3HnXIVbX16uDQN/1tfrf3QBS6un7nr7vaucv929VcFmhd7U9CyHSWPvdahFGIaeenBKp64YWxcGr7DfaRGW7h9UrVhRUhejd0waNckq2nuyPF5l5mj2MpAzYWtQiwcGyKo7cCJKBYH0TDMVRfBWrXEGwratsnfAoWhTW1TU1gOUgtYmuSjBsY+WgMQDtbE5uVDuNrTHv6zUphan9mRTbuNj42q5DrPhSghKzMQhRhFAY6XqHTYuvddXsFoIM7Hqdgvqfe4/7paEVkUcBTwI+co8f1U4xFt5F5rZ7vL+aap999tn359RfN3LJ/Mif/wj7F/fz5NOe/E099nY8uPHOa9/JpSdfyjl7z+HXXvtrmz2c7dgi4UVhWxUUbgGXg2965JQIMuEZz3i6PmyNhQKh7zs+8tGPmDSgMfYpWxrcgEfOfNuhY3x4xyKfn04g9QSzTgrRbL2KMz5ZQUUuhCj2AMcKVcwOKmee/PhdPPXShtQd48D+QhMyRRLzGVXL5xAyGIjIVqgGCkQiClxSttalIUCMlg5XY32MqS0lM1ufs7C4qMcuVnle1Pmg7+cGXoduZkBNaVdGFsg50TbaPaxpGuZdhwDzrhu0w9ouSt9qLG4tWErJHCOG+xNF+L9vuJUXHD3Bvzv9IB/Yu0tlBmDsqAFivy+lEENDkMzMpA4xRg4ePMh0OqWkhBS13prN5lx19VV1k1KM1awDqOl1h+wbmVcsRV4YUvrBHA2KsaPY5iAGHYcDxVwKxRh6B74Ozgu6iYjNUCilsgxdX6rNHnSdmB7UWV1n5ZGh2CrGoVvYmJHN9sdtwmpTBhht3ob5GH5mLHJ2BtzgqWcl9PS0QC8KwgvD2qpH9EyAfQ6Cs/0i9AsLlJVVBJUSjK54kCo0sHQaHDkMrCoYHXtTDE4FDoWLyiDMecH9ntV32jME+s4w0v46uN3ofLExvuG8nIjsBH4f+IellOPf6PvGUUr5pVLKU0spTz148OADOcR9xtuvfjufuO0T/OsX/GsWmoVv6rG348GJlBNvef9bePXbXs1bPvCWzR7OdmyxWJmvMIkTmrD1al1TTszSbMs6NDzQEIFzzzmLfXt2V0ZV7TYLa+vrrK7PKCKklAmxIZcBNFAKzz62zGldz+8e2KsMXKGyhAPei6S+INpH16rgewWiPQo4ciHTs39v4fJnT2mbVVIf+MBfrXPkWIRkIMf+16eePiXm866ycZoKHlLvmh5X9hehfi3WvteS2YCym8o8emGOp2GpAAeo1fQKvkfAzn7mxWCAtcRVsOf6TmfBBkA1dP4KxuZiLF7OmVAK/+yGW3nVkRP8p1P287YDe21Opb6mt2I7L7xKWT19m9gYK1mYTidccMH5ZPNV9TF3fcd113+lsr1+HX4NwZjTJjbE2NA0LU0TiTFURlUdCgzmGThMKdH3xsp78ZhJClxL27YtcQOD6/eujLTOOv9+bTE2FWjq/droIevHa5rh2j0zoMVgg2NCGP/B1mBO1rVO2domxkEyU0dX6leVloitL/VKVsYa3wsYQxv01TI0Xyi2Pr1AknpcOLGyyl1Hj3FN2/LlgweYRf2dOkBSjdDAztPg4NPgrOfDrtOhb3WO5iFQJBjr6+/UtTbJmU6EaDrtYvOnQFrHISjTfk9CdpiLr45v6De/iLQomP2tUsof3MtLvFOMx7iLzN945JL5l+/7lzzu5MfxXZd+14N12u34JsYtx2/hb/+Pv837v/J+3vz4N/MLr/iFzR7SdmyxeAh12rrfsdWbQjzQKKVw8UUX0TTRv2Eay8DHPvpRul7Twtl0sTFqZ6S2aUh94jWHj3FXE/nL3TusQ1eooM99VTEfgBD0YZ6c4Uym1e0TpST27G75rjecwcknrdJ3wic/l/jE53pEWnUiSKmmXp0ljRuaM5RB15gzBPdK9QYQ7q5g7KgzxCiwa1s1ka8NBVCdbLZjxSCD/la+WktYLclKQQzISdjIWbneMlNqu99csgHqVFPebdvSAG+5/ha+5egJfvnU/fzKwX0bz2Nz7Pex/jEZgANTr6Q/48wz9dqssxUFvvzl68kmbUCcnRSSgVHQ53vtRlVcc+xzt1GaoY0wGGyxMKDnOuagMoAYRiCYARBWUJsz2fTOvhlw0D3WfQa7J31Sp4oSGYCwCBIHBtvnySUMld1GNGOQbaNTsh0v66YgxHutCagigCJ1E1JK0eYKBoJjjKP0vhb6CVhXNPUjrhZdJQOJ5ZUZh48eQ0QtzErXcWYpTO28PpK4C868HHY/BnKAZg6znYXb3x9p7kpkEWZV1jH2mRWaUugq+2qyhLpIhy8bZDDfQHwjLgeCGmd/vpTy/7uPl/0R8EMi8jtoMdixUspt9/Hab3p8/NaP84VDX+C3XvdbtW3edmyduPK2K3nJb76EtX6NX3vtr/HdT/jub3gBb8d2eKx2q1tWbhAl8s+e/c94+pmbUku7aTGZTNi5YxEY2DNB9YjLq2uAFn6lALHx4ppCVwqLufDM4yu846TddPZQbicts3W1FkopWWMEB0xmV5QVZIZATQ0XhCdfPOfg7kN0c/jS9av8zz9bpe8XgTmFQLK2q57eLSZl8A5WMXhnqEDKhVBS1bCWGPzEyj4W84YNQ1e0IIHFpUWzfsqVqXUWz9nIyjbGUAFXLsWq1L0zFhWkehvUGIYuVoKm2WuqG2pVvEhgOp/zk1++mWcvr/Jzpx/kN089QOlV2+rjztYuGHQeQ8rE0JKDAAr+J21DQXjs+Y8hmh2Td1UtBa699ovkUatUB9ULCwt1Tfgf72jmBVguEQnBWWapnsIhaCq+jOa4VPbS5CLBu3QBhHpNEgKZYql84y1dkmHhzK2CNG8bywDgixb2jTW5OjZstVFZaECbbJgPckNdEsM5HXv7chHf3IgxtUJ0VJhz1cJSoM2a3o8GZqt7QnFv4qrAhiIsr63WLmYOQjuzvRPUJQBRMLvrAjixph66azNYTbCnzKAoQ7s6m5NT0oYKMnSGc+cFXffYvfa5rfkIm2dvPX3Pn391fCMM7bOBNwOfFZFP2fd+FDhbB1H+C/A/UcuuL6G2Xd/7DRz3mxaXnXEZV//vV3PuvnMfzNNux18z/AF2wYELeMG5L+DHX/DjXHDggs0e1nZs0fjbj//bXP6oyzd7GA8odkx28G9f/G83exgPeuzbu5czzzxT/1HBi3D48GGuuuqq6g2bUk+MbU3t55S4bHmdhVJ4/+6d1rVJu1ENhUlAGYCdazH9GNhxoBBiZv+BCbPZjPVZ4S8/EjmxtkjJPU3bGKs2GOLP53OzonIwKgpiRU39lYEb7LFKLoQm0nfdxpa7uWgqPTbW/czP4SU2xf4+0pAaK0kZWGe1zEomn1Bmz8fqKe6KGMpQSR8q0EoV4J61ts7Pfvkmzl6f8/89/SB/eGAvjZ2jN1DrhUzuSiCiGw8leAewiOi1P/axj1VGMg0FYbPZjBMnlqsu2Av9Up9IMd3DLiuZdrJUTapfS86qJ8VBvemnPQY/U+q4VZ4y3M+cerJJEaq1Vhx8YWua3rIFOan+OJokIIyINJUV6HXn0ldA3DSDG4TLHrzYrEosxjpR8eOlEZgewFy29eZs7Fjh6g4WAgYeXWdtmxdj8Wt3PHtPSoXZrBt0w3bu6egzU4AwhekBmPewugYnVmA2h+4QlJUBf4/lJdjnANExLdv8ahFkrgePwW3nZHQ99RB/PUBbSvmrDbN4768pwP/x9Y71NxkXHbxoM0+/HfcjZv2Mn//Iz/Pfr/rv/MX3/gVL7RK/9+2/t9nD2o4tHi8894WbPYQHHH3uOT47zq7JrkeMd7YI7NixxK5duytgEHsAzvqO5ZU1YmxMIiDaKCFEuqTNEZ5zYoUTIfDJXUvEos0W8qjgZj5PTCcTsvnR5qw/SakAPYLUYrCSIr//rjnXXQfL6x3XXr+grGAupHmPyACSK6gbpZKTsWLI2HNUatFPCIKkVPWZnmpuGvP+REjzOU0T6bqe6XRC36sNk6d+vdtZoVBST/RWuTHWtL36pBa6UQMJB2TZAGzf9+rnaoVjqe9pW/WqvfzwUf7VTXdQgP/POafy8V07aEageOyhmgzMVhYaBeIihfm8r7ZUi4sTTtq3B9K4UCpz+PBhvnLDVxRYpkTbtrRNW8c+bmqg9laCqi9CLYTya4QRmwsbJCDuDeser86wK+NtQM7eO/Za1YIkYxGD+rgKokVtesKR1rdUNjaEiHvm1s5gI2eGGkUlNMXmt+RMqi4cunEJzqy6HZfhVi+e0yK87PWFFOw6vcBLBpeDXDLBWuQGY7RtQgyA58pgj0HjhiI2/5w2kICStLYxJejnUL4CrFKlLyEIxDh0HFO9A20p9H7dyRhlGYrgBF1nzuiOAejCdHqfhWFbz6zxHvH2q9/O63/39RxdP7rZQ9mOrxOlFH7/6t/n4l+8mP/r3f8Xp+w8hWPrxzZ7WNvxMIkvHf4SXzz0xc0exgOKz97xWfb/9H7e9cV3bfZQHtTIOW34tz8wu3m3kc2yNLoDghACT1hb59M7FuhDIFinpZwVkLj1VXFg4+capXKzFUR5Ycy8K3z405mrvqhMZTLbpWStV2Ew7XfmarBnGoDqGBjAkOY29eeoQ9cAwvq+H9k8QWWmGAqwvBBImcNBy1lLeZwNk4GlC84iMuhG3T6qsa8xRibzOT9yw6387Fdu46ZJy5sfew6f3LOrAkaXGjhD6efya64yhJxrFX3btkwmLU9/xtM57bTTN97nXHjfe99H6vuq8+1MUoDNvRe9KeOdrBI++9UauFemtGma+scBt8/5WLfq+mZfd8HWVtM0xCZq4wXxgrfhfdmKDF2i4a+jHn8o6EpmhVZtzUKsbO4913pl5F1jOmLSc11HCurF32RSlHq/2chaFoGsN5wSw9BYAd9g5Q3MaXWYEChh6NDla328UXBRTVqF+ar+ffcSHNgDO6aQusDdCwtkEXb3PdMQrJ2zbQhEiAiTrGPy+QHt1Lfhl8DwMdgYf03JwUM6fv/zv89f3fhX7J7u/vov3o5NiztX7uSlv/lSPn3Hp7n44MX86Xf9KS97zMs2e1jb8TCKH/qfP8TR9aN8+Ps/vNlDud8xT3MAJnGyySN58KIUZXg0W+qMkWofU+/FIIUQNK1cX1YKk9mcx6zPec/unbWKPZhNlj+oK8CKQk8h9ZkSh/SmNhMwg/kMUrKyYDlaRy7qsVLKG8buWs4BSBg4MGBAycRiKWbFHtbxaZANkAtFAn2fmc/mNG209H9PKRMdezOAxKqHTTYm9yBNSYvhyqCn1fkdAItYGreyxy5HAJ55fIUfuf5mTp93/MaBvfw/px0kxUATtH2tSxI0Da7AK+VM07bMZjMaYzz7PjOdTjUVHjN91/OkJzyZFzz3+TRus2b3/YYbb+LmW28jNi3zzgGgbzCKjU+Pq3rWVGcu5+HaoJBSsTS1gbsgQyq9DO4JOifKhuec6enq/dtY6KUOA/244xgOhLOBMkxgW+qGQQFqsuscwLBbmdWNwejeuCevw3RBCwN1ExcoWpqGenG5rCCg9nF1JQ0gr7jEdhCmagGWdSbztT9al76JUJxcaNtmw0ZtgjZSqHNon5fjt0DYDbHA2glYPwbxrsyO0hHs9YsLU3ongjE3CJyh/WpgWud6g1RhkFL4Nd1XbGlAm0vmz778Z7z6sa/ekp2BHu6xMl/hU7d/imef/WwOLh3kwgMX8o+f+Y/5zku/c0taK23HQztmabZlAeEszQCYxunXeeXDK5q2qcwRCN6yvZurji/EQHCLV1F/gCLCJbOOAHxmUedLDMgplswmMzBQaylajOUMok4JyuL2XHz+nK5f5Ms3AMnS00E2AMOxrZN/b0OL0TCkpvu+oxRtCRuCti61Opx6rZpKNUxk+eK2nRj7OxQ5aYGTFn+5bpYAuU/VDSEYm6hgoJiWFnOOsFa/InTzuY7TGMlz1uf8bzffzuVHjnP9woTvv+BcPrlgDRPsOj1t7v6tXjhVSlEJQxjS7Dln+j7VZ/HjH/94XvPqVxMNxCCq2ZzNZlxxxYc4sbxCSuqbm0wG4fep79VWbQCaUq9XxBspuF7V5CbZiwrt/tjxxlX23lHMC54ctAXR5gL+/jy63zLa2Phx+tomeGCCw0jS4PfZ2XwRCAXTKjd1zZaRRlc1sV605ecaWfJSKq5T0KfrNGAFYiNQPmb2J6WQRDd7VWUQ/PpKPR6l0ITA0uIis9msSkYOriQal3KM4uhH4fhhKDugzIA7Ya0EVmJkmhJ5MkGaRteDf5YMnLY5M7e143M71kzXiQcoJjtwRpz7ji2NKm44egOH1w7zrLOetdlD2Y5RfPaOz/Jrn/o1fu1Tv0aXOm774dvYNd3F77z+dzZ7aNvxMI55mm9Zl4NHIkML6EMrCMUYKK+DXllbYzKZaJq8baHrKKCG9kk4t1cm7CsLOl9DajSPGC6h75MCu+yslj0cg1BK4sBJ8OJnwuLijM99UXjne6IxhMMD/Ktth5z5NN/c4BXlZpVlhVkYs+w/K0WZUYnGBMZQQdu4EGnHjqUN7J6fr2p3k1o+dV23EWgyFBWp7EFL4rVgLNNOJpScOWve87dvuoPX3H2EWQj8lzNO5jdOPkmdIuxYmvoW+wNCNAaxDIA8gUijWl4z+c8p005anvLUJ/GqV71Kq9vdhzcXct9zy6238PlrriEZCJt1Halk8rxnYWGBXIzpLYP9l054Ub9WVCuqRXGx3tdga0iLscxjtRaBFQNMgK2ysR7Y7zMU1YTO53V9igztaV1H7KH2Xrb+RCpLLkEgl6qRHhGmtQMb7ohg902qG0OiNhAhQNFWz4OXq46rS9kyF667HQrZRIZGF03OzKLUeRivXTHLCf2vOlzs3LmThYUpoRSm6+vsP3GiMtC+0RGAOZTPAxFEjTlYIrNkv8uybeC8WYrYGkCU8e1kaH6RS64Fa6rXHtvSbWRy/7ouBw/Z+MwdnwHgCac8YZNHsh0A773+vfyff/p/8rk7P0cTGr7tom/jhy77IXZOdm720LbjERCzfsbehb2bPYwHFA5op80jh6EVUd3kxoSiwqa1tTVyLszncxYWJlXPpyBGOKvr6ARuda2sgZ6Uc33qlgokndEyQAaaYhVh/56WffuEkjumCwtVA1HZOhMuuma1MnojnaFX34NW6IMDbEs9+8M6aaq3MaJVCkgMNK2mt4PrZMu4Q9JXs4R+fO/8BCOdsL66vtMBm5TCk46d4PV3HeGFR0+QRPgfJ5/EL592kMONMb0Mvrqp7xFpVCqRM/N5Z76pg9wiBpdI5Fo0FQhccsklvPKVr2LStnX8vtlYWVvj3e95H/Nu6NaVzIqNwgb/2WG+rYjOmPbqSYuny41x9HUVdBzKunoBHiTrCga6mShe0GWa5NolzLSyQ4HhuFCq1BkWETBrruqE4Ndjtm4BN1jVY43lD2O3jepJLAYvbb4U80c7rctyhjUwBqmuUdU5CEQglkIDdF8FD13goK/FMwF2nLZpaHJm/513sevoMfq6wjeCWilAP7CmG35ehrnT6x3kH95YwUfjrH69Ft+4jK7tG4ktDWib0PDMM5/JJSdfstlDecTF0fWjXHHTFfzpl/6U1130Oi5/1OXsW9jH7ulufuEVv8C3X/ztHNzxze0Gtx3b8bVinuZbNmV//knn8+Mv+HHO2n3W13/xwyaEtmn04T3Cb0FgdXUVL5Zq2wbQNPRkEsh95oxZxy1tqxXUVuzjKd9i3cQcfigAvaf1lcoSmrBGoaNQuPbLGbeP9yrwsT2UF1mNgWUFKMZOKujLeAMECULpMYsvkKwpeWcI9ZiwY8ei6h8L9H3HwsK0es46aIwm06ptfyVUUCPGromgbLexxRetzbj8+DKvOnyc0+cdJ2LgN07Zz++dsp+720bHbZZnnqJXUGnyjKAOCiFKlTeo+4Km3UOtylcm9aILL+A1r34l06ZRxwqb/5IzqRTe874PcNXV11As7V9KoWkbZrMZuWTWZ+sm21AXisGqyyYnWwGWaUEVcKsF1QD+veOU0LRNlVxWj9k8ML8SzB8Y8zn1hSi6Nt1lQZlbZX/HaX29l9ZlDapW2cOty1TqMhRc2cTYGvOCtYLIwJxq8kLlJqUm6z0KOfUOcbXTlm3gtAuZAvPG1mEfh+/ZDRuyDZm61otdu7PSQLX8CqN1f1/4Uu7l7zXXIYMURBnaQddd58vbFdf3l+H+M97k3LvwYEsD2lc+9pW88rGv3Oxh/I1GKYVjs2OVebripiu4/sj1rPfrzNKMKJHd09286dI3AXDXyl0stovfNFa0lMIszVhoFljtVvkHf/IP+NDNH+Lqu64GYLFZ5IL9F3D5oy7nSac9iQ9+3we/Kefdju24v/GTL/rJLZsNOH//+fyL5/2LzR7Ggx4pJUtKGo2qz2ROnDihwC15B6NijKh2CdubMoebATwM3Jn/RWoqVkFutpRnqlpTJHPGaSAlgwRuv12ZsOANC6Kl3bOlQK1Ix8MZWlATfu0alWvhS01Vi7CQM+d1Pad1HafmxIFcWCwwLYUssB4CdzQNN8eGG6JwbDphtWDsX1aWTlQ/mtPgnerUVcqwIPCY9TUeN1vnkhOrPHN5lZP7RAY+unOJXzztAO/ds5OubXUTYYDOwV/fdUgI9MnTv1JT4Z6qD01LGIHJlFPtZHXyKQd59StfydLCdMSMW+erLvEnf/q/+OjHPkku0DTBdK/aFcslI7VLWhkcDvze66QHmiYMlfq5QMgb2E6/59laIfv1ARuaBYhJScaNGqofamVlAREiVlSV/dotVW6SAw8H6c7oesGVvrcgous9evcvgVJsU5RtzAZ+tQPYhpVdL1DEALpfra85x4523om9N9l9dmAcRp+Y4uzwPU5QnEGNESkFSRsdScZxbwBXTHJQRCU43thhaKzg1yv1HkuwNsBV48Hontjo7gPMwhYHtA/HePd17+Zd176LLx35EtcduY6vHP0KgrD8o8sA/OLHfpHf+uxvbXjPaTtPq4D2+/7o+3jnte9k12QXp+86ndN3nc6TTn0SP/uynwXg9676PY7NjhEl1g/VyTtO5qWPfikAP3PFz3DN3ddw64lbufXErdx47EZefv7L+a3X/RaLzSJX3HQF5+47lzc97k0888xn8qyznsViu/ggztB2bMe9x6se+6rNHsIDjhOzExxZP8Lpu05/hBVMFrSlkz1UjSVyfWjMDVo4HkxbCDFEdqXE3U2jfpvYQ868YFPKNFH1hjEOXrP6P9PXkikSOP9ROwjS0+cF+tIQ4gBSKfdig4XU1rk6Ki/yAlAGrimZx807nrK8ypNncy6czTmrT1/lkbkuwjwIsRSmuWx8GN8AdzQNt7YNh9uGIzFyIkZ6tBirBXakxM6UONgnzph3nNr1uDHU4Rj46NIiH9q3m7/ascDRhan6xpZCTMnAmEoRgkRrkDAAj5yUWXQnBZdCeHFaDApIS4mEIJy0by+vee2rOeWUgwPQLOr6MO863vPe9/GBv/wrJEZaa1QB3p1s6KaVenVs6Lqugq9qD+ZOEyP0pKn1gIg5JLhnsW2QcskqLXBcmU3eIFIdBxzaVecK1NUikxjeODSh0HFTx7yhUceIPaySFWPSHVeXXCqYVwcEK16UDCWYvtuuu5jDAYWhPEzBrtvKVcZXXEhgrPVoqoqzrBLqawqFIK6LljrG6hZhf0tti8znOi+opMC/+pr20fk5u8UFFmZzKJmgapv62c4p05Si7gfiMhKXHQzadb333ziYhS0OaF/9tlezb2Efv/G3fmOzh3K/47oj1/HcX3suLzr3RVxz9zW897vfy87JTt7/lffzXz/xXzl///mcf9L5vOzRL+PsPWebSXLg37343/Evn/8vWWgWmMYpqaSafgH43576v/Gcs57Dbcu3VVB63dHr6s//7V/9W668/coNY3nO2c+pgPatn34rh1YPcfqu0zl7z9k888xn8vxHPR/QD87V/8fVD8LsbMd23P+44qYrOGXHKTz6pEdv9lDud/zO536HH3znD3LTP7qJM3efudnDeXDCta8GZIEKHruuA0o12m+bFsEbJGR25cJ1MVSQWbBssRE7hhzM51MLdZKxhtGJJ+mIzToUuPtQZN5l3HA/pY5apJLz0EEKh8YMLJy97o9uuYNLup7DIXCSIZ4bmobPTSf84e4J102n3NwEDi9MONo25KCtbHPSh/ye9Rnn9InT5nPOQzhjPufU2ZxzZnOemBK7UiaYJrIHlmNgOQQONZFPLS1yU9ty3eKUq3ZMuSlEQlCAXsjVZmqs4RQR7ShWCjG2pNQTJI6AR6oFZQpoh1unndAaQghcfPFFPO1pT+H8xzymbgLGfz7wF3/Be973fpNlpApQwS3ABt1sLplI3CDvUA1posRgBV+5gtVgRWdB1IvYsGotOIsx4LxiKUmBqoH04BsRA57qJqEykWhbAy/gKnWMA1tcj1O1t8M1OzGrQDFXMKxHGLrYYSx2tsK5ja1odcyDVKYM7xPq5qJawY2At8sJ3G4rjdbyOHMwUgPUeRhcR+x0465r9vXe2hqMN2zt2ro2XrDPXAhSz+fShcwga6juH1XxYX7NFZIP8NwlCfcWWxrQfvHQF3n8KY/f7GE8oHj0z+tD9zc/85s8/5znc8fyHew8aSc/+twf5V+/4F/fpw3ZGbvP+JrHfcX5r+AV57/iPn/+/u95P8fWj1UgnEtmsRkY1s/8vc8M6Z3t2I4tFK9522t44+PeyH96xX/a7KHc76hFYVtUA/xAogB9nzb8G/Sx1SdlDLu+q2njtm3o+jmFwu6UOBEHZs+N8D2J6k0U/CE52E0paA0S6XLLH7wz8KQnCHfdMWd9vcXtpTSNq1X0yYqXogi1TKgUkyYouDqv67mk085ZH1xc4H/tWOCTi4scnrQmcwiDZjRCDCOdomgR0t1Nw9GFKR9ZD+zcuasWk+WczM3AAJQ1LlC9ZjLfVarWMsZA1EQyKScmbWs2U6G6N8Qo1cJLQah1awIIQUGHmewHEfrUV4bxwP4DnLT/JJ7ylCfzqHPOYdfOXbRt3ADocs6kPvHu976XD15xBTEE5l1fJQWgmuNkvq05mQWVaVzVOaGM7qEJU8JQaFXbG+NdxYztZ2ALkVHhE4zAnrW+1ZtJKTpeRVSDk0E07XMpYRh3HsCeM67j9roeap+WFUQby900zQDsbEPmzROqdZ2v6SBIiNyz+YgtzarPrbpeVyjIYA0X7brTqJlCZUOrNMc3aaUWcumOxnxoV1aHDefoM/q1/l2AHCPzxcXKcItuSQl2qKQ3yKRAI1Z7BKhLGY4+fO9hKjm4a/UuDi5tzcKjd7zhHfzFDX/Bv3jev+CkxZPq9/+mbYd2T3d/zSYU22B2O7ZqPBx8aLfq+B9I1BSo9jGt+j99lubaurNLvaZoU1YGKyV2psyJ6lupLFBO4MbsCoQMEHrqtng3K2tFm4Wb7m64+T0gRJIxSRsAykjXqQyatl/VNDK1/ezNC7oRef/SAj986gGcyYsiFAOKIn7VrtcslbmSIEhWgLm0tMNa3UYrwMJcEDQla05UxhpC6oZWsSFG+j4TI3SpQyQwn/cD4C+FtmmsGUFh1s2IMdJ3fZ27yaSt8oKUEouLU3a0Czz60Y/hkosv4dTTTuXkgwd1Pu1eqk2Yd0xL9CnxqU99hr+84kPGVDrrBn0eWplWazIUqLqLwWQ6uQfT69pVY+2Kg5+RT2sZ/q4AkcpUukbAu7SFEI3l9aK7Yb2MvWs3rNe6cVIpQk6JjN8T6+YVBtusEAZf1epX6zKWCl7dO9a70em6ysW9azdqXyuWk0LfzXEFb2VnMfcGs14Tv24HuZUCrRcFaIF9n3pSKSZX0DGu7t7FjqNHCffQz94bpBzP1nxhyrFTTma2axfV0q5o4VvVYKNGZLnISBsx0h9XMDvMnVT5xb3HlgW0fe45vHZ4y1bSv/bC1/LaC1+72cPYju142MQ8zbcsIHxE+tDKPVKbI462FPN0tQduSokYIin3TOaJCJzwTmBWnONV/1UnaEUtqqYVYhPMs1VBpQNbBDIJKQ2ItZY1BWGMURvVM7DBVjOjzReymfKLcCwINzkDZ+xYMWAgMRpYMo2ng3d7eKtfaYKibKgzsoVCTj5OBUG1Y1jRoje37ML1nEG7domEWkBGTa97hzRlnr2QTawbmEoMNJV94KTdXHzxRZxzzjlceOFjiSHW9rkVZBmzVnKujGnOhS9c+0X+7N3vZn19ps4PGBgruYK50UKwZhcKtr3gK0TTkyZIyYGgFqKJjPyB3QdYClFGBVaM5sXkLYUBmI5T8yrFCAMA9jU5AqBibHVNg8vAHKo9WwHLLGjxma7qgb11sGoWZDlTZCg4VOZ91CkrF1LJw/XZp2Ts1zpeQ37thcF+DcuA5BE4F2t04Kn7nDPzPNdPSikbznTipH2EnJnedTfHG3XF6Dq1cMMBvgip65jEaPKVyIm2JR48gFBMnuAeu6VKDpKYq0GI9TOfit7DOu8MX3WTOPLivZfYsoD22PoxgA3s5laKd177Tq646Qp+4oU/sc2Kbsd2fBMil0yUe1N3PfSjz5qubmO7ySN5cEOKWy5JfehThJysSr5kYgh08w5a6LqePWZ6f5xC3/Wm/yzEBmOCRjpHKyTT9HoBsqXuG57+5J087YkTUtfz4U91fPqqDgmatpYQCaaDbGJDVzq84AyojGJjLWdFhJ25sGxV9BTrEOWaVRuXYzpEta0Owh3A9p2ym3j6XxSAjTuGgZfrKDAPouA5Z5UJ9H3PdGIMpwM0k2xkM/tPSdv+llyIjY5hx9ICp516KvsPHOB5z3s+kyawe9cuqGcrVT4hxqTWPUhWkJZK4fbbbud//dm7ObGyYl2ytH0t5tda08/OztrXXAaP2a7r7L1i2l9dGxu6fqG2VSXnWqg3Bn7BNZeUofVv1g1PnxJ5Iy5VC657sWXLo+YMruFWa6xgdl1qseUZhmxsdSrmVlBT687cGnC0QqxkNmghBi3Iy5qJwMarkgQba/3PYGWlk1CqUkaXm6X5jQ1NdqEGhev1ZXtdBY1lNIdB18exA/vZceZpXPz4R5NT5tjNd7O81pMm0w2gXonYwvr6OmF1pW4qi6VM7kkO55pNGTyFxY9lG8Gx44Uz4Q9LyUGh8J2XfieXHNyaHrR//uU/562ffis/+aKf3OyhbMd2PCwi5XSf2vOHerzs0S9j93T3lh3/A41Mz8JCa1o/BS8S1Jqp6zratlGdrejv/NhEltb1gbYWgnbbQn1eq5uBaVKVXdWCppQTUfuK1ur2XYvrnLL3TgJwcN8eRp5HFUSEoODHntbm5RmqLlD1iMIOY6KOj1m74L6wXsxiBUIh6vtG7XLHNk9NjJU9ROxh7hpZA/lk3wBoClzq1zAaswMBA7wp06dESr2CUolMp1N27tzBZZddxoGT9nL2WWcxmUyqtrbrOrxaf8ARqconXP+4urzCvOu45dZbueKKK7j77kMIZmNF2QBKxEWggjGSloquzSQG315nR2u3MFSeAYPcw8e2kVlFGW87VxChxEhBwXN0mp2Bhc2WFXDGdszWDt6/GyGhs6ljCUm9r8U1txmRvOH9UrBuWANLXHLRRhAGLKvbwJgVZpAO1Dkx1tcZcwkqh0DE1r+NM+fBrxbXTUudh9EeqX4OahFhSMRyhGnTMJMT3H5knW462dCdLo/u87A+RtdIRopUGYQXaUo9Z6kyo7H0wz16i3UZG+vu7xlbFtAeWDrAb73ut77+Cx+icXR2dMt2NdqO7Xgoxv94w//gsfsfu9nDeEDxtDOextPOeNpmD+NBjSBahT5prLra2EhqGnxoWTqbz4jWHGG3PWRn7RTB05W5AiVBK/SJnp4cvFsVOIB2GRUaScq1xozo47kit2J5cgdtrkNV1s66TNkYl+whuxKkdjWLFchSze5B26+GsaYx6TlOOfkUbrrplspcujRA0+xuuq+FaV7ZX/JQ/BVirEBG7MRVZlCK2V7puR57/mM48/QzeNzjLmH3rh00TazgpXrrjoiwwR3B0/6Zm2++hVtvu5WVlRWu/OSnWF1bIxfdiIQQaNqWQk/qR8VgPp/JmdZC27b01sVr0k4qCKqerjlVFrGUTEkb2eHqKzuSEKhUgwqmnQXNxUCV/Q/bcIgYCESBlt5/A5SYb6uBcAnKUOvGJ1dgqfg8VmBbzDFhPC71XVYWNKBSAwXcLhdwPe4w9+N17WysA1JnzG3PQzQpRVZtgwJ3jKHFxzSwpKbupjfniIIC4nGDiVBg1sGnPn2IKOoakRcXKCP5iG7+tIDN13YRawvtmmADtg0OgDVDM1hz+S6nktCkVOhTrmCZglnM3XtsWUC71ePo+jag3Y7t+GbGVtak37F8B3ev3v2I6noYYmD/SSfdI4WoEgRvuJBSpmkiTdQOXG07YamsATCLkaZtyZY+77q+gla1cxqOqkwPjscQCcYCKuh1EDKwQcYQyUiriBeIqetAkKAOCDmxYIB2LQz6PwcunnpVKYIWbikQVgZvMo284iUv4sTyGguxIbYN67OZgRtt/7u6ulZtssQ2Am3bEGJUv15jneNIxxhDBDH9sehIHv/4x3P66aexsLDAdDqt43NvVGDE2A2aZk/1Hjp8iOuuu54PfuijrK+vs76+Ttf3xNBU9tkBR8rJw6DrpwABAABJREFUnAPGsgmpnboIOrbqasBQud+n3lhyvWFhhMIS+h7tiKaM9biLV6Goib8xoNUaDkHK0Eghe59X07lusDRzVwy98eoRq2mCEQNJZTE3FLDlTMqDtjZY9sGlKGIuFepK0Q/XNpI+ODvrFmX6z4Hp102WMayFmqnAdKmeta+OAgyZALCsQWFkn8YGdlZMb+MM6sJC5sKLDlKycPz4Ol+5YbUWxPnn1s/vQ60Mt91DCQq0q22XdQpzttrHljJkKfR4kWGm905qhSr7ubfYsoD2Hde8g+/6g+/iw3/3w1x6yqWbPZz7HUfWjrBvcd9mD2M7tuNhEblk/uSLf8IFBy7gMSc9ZrOHc7/j5z/y8/z0FT9N92PdZg/lwYsCe/furcBONX/GqNbCHyveikEbAwBLVoi01kTrduVtR+29FPrUawerIKQkxvCNi7FUS1tSpISsFlIJEKkV/y4pEHE22dLgpgvMNs5SYMHYvRVjpTaIHovrJo09LpmStOlDQHj+s57Jk5/4BI6fWOEllz+vWiwlcws4sbzG8WMn6vljE4ltNAuoYEB36OqlDOdQIOR6RAcpYIztSLPqQ/XiqmJ/n3cdq6urfOWGG7nmmmu4/c47OHFimUIwJhqa2JpkIGpBT4zMu45GWkqxTUZWEFjZWGMCXVpA0UKmPiUWFxfpurmyn8bQukbTC+tUE22gbgRalWlVsOs/c83uuJhNGeIBaI+93EHbL0sIZtXmWK9U6zRtRWyATAa7sUHn7GzrwEC6TVoFrIYHnTWu5x7Z0YUS/PYpazpiTtVqd2iDrDdQRkWCeh2+Zj2rUP1ni/nYlmwsaoFg9l22drxxyb59i3zLSy8F1rjt1lVuvulq5v3ICUJQxwUbg90uRh8CkrVjkBGolugFaoP8A5s3dzrJRTc+iULM0PX9BgZ7HFsW0B5dP8pqt7plW12udCucvefszR7GdmzHwyL63POqt72Kn3jhT/Cjz/3RzR7O/Q5vnPJIi/37R0W9Ba365qsBl6ZrjQ21FO/xlChtUzWW9QFaioI/B2oGOIK1cC3GqpYMuURKKtZ1SdPOXsjlRSpq/p8BTeuX7CZKljIms9sY0jXZaLPk/ynWDQ20G5am+Bue95xn8KxnPt3S6wpkIxCaBqE1drdhcWFk5yjU82+YPOzaABkxZqCeqJFYgUrxcd3jfriW9I47buemW27j5ptv5aqrrtY5KaWyryEOkgl3Ohin1kNUwJtLJnXW7rUZvHSdXXVwVQxE6wakr/dMSrGNgzXVINMbE+/nEgeJYaTDNfDrLGaylDeYDMDZWwPWccQsFwqSbQ3auqnaV/vqaXVsjyCjn7knbCRWiUGuOuBCSqUC7GIM7phd9uYRKrEZ5rXez3oDfQ5DBdT6fi1aK7kQ7N6kSrqXrzpm1bv6YWXj60B9k0tep8gaOXe6ln0dlkHa4eeQ4cDDnNrQvWF1shM6Mz9+v/2lgt2cM33RQrsup3tZuRpbFtC6y8GehT2bPJIHFh//gY/Xyubt2I7t+OuFMyxbFRQ+UgHtrh1LVY/oUaHaCCBhafuu61kaAVrB2JuczV/V08QqWwhY56uR/kBBVOTTV8/54pfmdF3H8XmE0iDSVDsv1RtamlbcTinXhgd6GmW5quQgWiFY8YIYAwlZTfxDDETJTCcNT3/KE3nW056qjgQM+tb6PKdUAD6M39PAYzA7zkjbuBhV/RchELWqngEIedoZYDabcdttt3HXXXfzkY99nPXZnPXZTN0ATMvrhXJ93yMjKYEDrCRCCoHe2rpmyXV+BGfb5+bP6vpgMc9VZV77XsHq+vo6u3fu8jumTLRn1eNgpZVT0uuo82YmURJcTaLvScYS5qysp48dlUGECLGYE4Izl7mneGezEVh1ZwZs7VEKOehmpcgwvyoNMdcLt88ygJnJdW03sSE0wdjavr7f5Qb1ntUFbH9sXbpcQO3AFDoGxDCngUcGt4vx56rKYYqvvcHnd2OI/T+QctD58LH53slb/DLyu61zItXVQbyWzcaSXVccjLK2tr4p2WfG7m3fdUguNVNzb7FlAe3R9aMAX7NJwEM5ROQRZ9GzHdvxNxWu/9uqoDCVrevQ8ECjAIuLA/NY669HALSyVyEQghn9G5hYCUMldLFOUc4wBdOSOvgQ17WaZ23OmbuPQWZKTlPVtWKygBHr5sVgCjASOWPV6GrJFKzYaYeNd9VkEl5YFcTlB97hqzCZTLjosefx/Oc8i+l0ihc7hQBBtJjGQczG1C0DkME7PY2lDcO8QjEG0n48Yt08Vb+yssry8gof+fgnOXb8GDfdfLPOTdJJaJqmSga81e18PlcgKtZFre81RW4V6NnkAO5V2vc9bduS7P3DWEbjGV9AgdSnwcbLgGtKmeBtE8rAcBL1WdpXXay2t43NqKkBzsiGmqKvjgBSqu9tzlbEhFlolWDp87HLwhABqa+vbK0f2zYxAuprPHJmwNa4HzNnK1SzdaYd03SOXMZQJ47Rhg/nVfETO+6sLKmbGJbxa+3nBYwVHj57ja/1eyDaQuHEiRmUzMryINeooFYAGYrZUsq6LsbzYmNqRjIIKWqvpkVs+as3dMawN01EOhla6N5HbFlAe2x2jJ2TnTRh611Clzp+4I9/gO+89Dt56aNfutnD2Y7t2PLhDO1W9aHdyh66DzyKptJF1P/VtY5RtEMWYgAlkftSq94XrShkDX3dWNcI9mwtkPukQAtIqSf17sVqLGuJiEwQUUBRnJiyh3QIgZSLsXHq39o0rVbxS9CmAcbCugximWDSiEKMVgQTolagFwHpefS55/AtL34xu3bu0g5o2TS8vVs3QZGkcLQEtKPrCLiKsq7OsOlUDjAW0SYBA94tzGYzrrnmGtbX11laWuLuQ4f47FWfZ2VlBSRUUOdz6M0q2qZlNp9Z62BryJASTVCbNAWrqRZRtROdH2cmK0C0tHhKer9M7qxV8XbMGBottgtC8m5uBMjaLnWwcBqu1yUi0dg+sMvPBoRdFmHl/WOJAtGAlm2G3TrLWcRCIkgkSERGrWMdTiXT9npRlzKdUAjKwAbV87rNlIRBPzt2cfANhm4c3HlA75trhe9VXuKMPiq3iSPWNZjDh6OjLFRWWXTntAEZewvgWqBmDHPu9RpvvmmVX/pvH9e1kvVPQW3A6mGSv7VQUqLrO8SkOG0ccFoszho7kFZHkGxyF7/aYHreJsDSZEJrGuRkPtT3FlsPDVo848xnbFlG49jsGG/99Ft56ulP3Qa027Ed34TY6pKDNz7ujTzp1Cdt9jAe3CgwXVhQEFb0YZ4KzGezquOLsaEU7IGngGoxaXnJLAhioEpE6FM2dkrBRIyBYB261NCfyvy1jXZkcwZIOU9Lq1r6WBla78qlYMa7l+WSadqmMp8OstebRoFDGZwN3HosSiCXxIuef7l6vYbAdNLSdx0F+NgnPs3HPvFpmhjQzlOZtpmwc88eUt8ZhtPCqfX1NZQBjpqdKNYeNwp9Skyn01oE5DKB2Wy9pv+7vqdLymxHc0/wRgHr6zNo1JqrsbkNIdD3/QAqjWFMwQq2PJU+G9rGeiq5663Q0YBSbBTkNjHS9cVcDgIhoJ2xYmRHM1VwKSDZU/hhAKtVMjB4uAKDTRZQRDveDlZnAysa4tC4QoGlDC5vxsLX4wZLw4dBUz3+eQn6d/fF1Xn0IsDReat8gAqs6xoxOwJfW0G8+5l+b219jcOHDxtm1+tfXl5mNlPGPEumm811AxED/dxcQjpNz/dZ9c8KujOpM8bZzt/3PZO2rcVp1WbM7mUsKtXo5nNCaCk5qeY46AbOC8scpPd9r24b/lG31s05Z7qZtvnuU6brOtbW1lhcXFSZQU7VpaPr5hw/cYwjR4/gyFuAtdWV+/yVsmUB7Xdc8h18xyXfsdnDeEBxZO0IwLZt13Zsxzcpltol3vN33rMlHQ4ALjvjMi4747LNHsaDGhICzdJe8vSkQUNb4LZbbqRL0C4s6IO9SUxaBX5937OnbVkPgX0n7VcmV6TaRYVGvWop0LYdTdMChYXFpY0tRnFD+EJsxFi6SC6xtpaFQurNagot0nHA4REs7bp/1gNHme4/iZOKfr9PCiZckziZTsh5gf/1vr/i9DPO4NWvfg1FAtIUQsq0O/aQQ2A95Wo7tr4+4+jKbYil84VQ3QrGXbdcKyG9ApFZN9MOXDEieLerMBQniTBp27pxKNadKhdYXJhW1lyAQCAGYaGdDsV3XpDFkD6PcdS21thYteMaAGdvBV/KUAqTdjoC/YG+j7TtlEk7oZlMKaiHrG8mYLAXEwSigtpQrbC8gYHev1C8C1myDlzD+SqbaUxqaHWsA8PcVrmLvsdkTQihEUTayhgHyxBE6xzna6OYbAGTWLhvcbJmHd5IAAOwvu7Abbb0SgOwvrZcr6uUzI7FBWazVXt9pJ93TBcWCFls85FYX1sHYG22znxxWuen63qaRuHmpJ1AKcxnM1JKzGfz6sUborAwXaAJQtcV1uczyCopkBBsnSoD3nWdfUaoBXxtaqv22jcCqzMd03o/Z2Vtma7r6XNfMy2uC57P1rnqqs+xsLBIjLpBCAhraw9DQLverzON06+pp3iohut/twHtdmzHNyfa2PLCc1+42cN4wHHdkes4vHaYp57+1M0eyoMbzZSuNFDEHrCFLiujlI0da5qGyWTCpJ3Q9z07yt2sGlATyUynUz1U27DezSml0MaGhRhVGyvaEMGLlRAhCEzaKUhBJEOJdHPtIy9B7aUQgYkCkVS8aEuIouxiSsnYWNjh2sHJlMWohWihm9P3vR5TAhK1je7tdx2mXdyBNBP1Qg2CkAmxZXFpkb7vVKsrCtRiq+4EfZ80vW8P/Thi+LJdm1uV9amjiIJGZR/1GCnlqmutzQ6AEob2urGJxrJq2pec0Qavdv2Nst69N0womeKdy6yQTot8hMlE60S0WE9lGFqkp2xlY6AtNo1uTNpA07RaLNW25NwbmB3pYq0IzNlyERuzWXEFkxY4E6/zoW9z67NcZSo9ORXrTqdyFBoqIHfvX7XgsuK4LoF57oq1q1UC1zZXBvCDaHFTCAZcbT5KziTLAvSpx90WqPMjlRXPRce8Y2mJfXv3Vj1tobB7927a1pppIMSFBcsYqHczJdAYQ9uGQBRv1VsI06l2pAvukKCMa9NEYlgwDa3o/cluI5eJTYvkQoy6aeiz62kD7WRimQld03Ek8QCUbY5CtOq+Ym4FodGNlARU02ye0Z7p2LN7NyE68y4QuE/ct2UB7XN/7bmcvONk3vWd79rsodzvOD47Dmzdgrbt2I6HWqz36/zhNX/IU05/ypZkaX/mip/h7Ve/nTt/5M7NHsqDFqUUTqys0kwXIAiL0wUmTSRnIUhkMlnAZHPGymmxzmIuzGIktA0LBpg8PbsYFkwXOaRUMyARprH1wnA9lgSe8qST2LVzztr6nM9+bpmV1WbQpZJNhiAmfShVZ+upWHFdbynaVEHUE7UATdMqo2aVLtE6KQG0TUs1IvXn/Yg5VF/cVItvzPFLGWvThNaCoaqxFEv3ZiREYmjIlv4Nom2CC4VmEpBQ6Pp1m4dB7wqqN1YXgqCOBLFR9jV1UDLJ0skUCEGbU4RorDc6vr7ryDkzm88sHT/YX1XnCLsZer5SwU8IDV7Q5nrk3ueiLh6Mbbc0fcq19bWz6LVgsKgW19n0lLzLWyA2gZIUoHb9TMF1bCrIzCWTjVX2ZhW58Xa+ma6bQ+PNDMS8gW0DEEJ1xFBPXejo7L6JaWqtsDAN7V190yLZ+HErJBvLaL3AkSQI0VjhPGwURr609jHQsZgcI0ghl1Rb5bZNS8G6cAlQrK10yrVILIaOx54nNLEw7wLX3RxI67UOTJ0VcFZftcSaBBla4erYh3uoUgWTZ9jnQyRAyUgoNG20t1kRpOgG7b5iywLao+tHOf+k8zd7GA8outyxd2HvNqDdju34JsWx9WO88fffyC+84he2JKD1h80jLdbW11lYX6cEtRqKsgCM+tQjNcXudVGLObEah8YBA2cltS1pGXVFGsDeRmanaSNPeOKZnHF6Qy4NN93ySZZXZ7jZPMjQKSyNqs0tRe9goZTCYk6sRbN98tfYz2qJT0FpqDJ41I6rz3MeQJ0DzJT7WgE/+L1a8ZcdH+9KFZyt1fawYt3M9HVWdFYysR105rm42T21gjxnZ4Kh6zrA2eBAaLTBRTE2eACHpY45iJCDsuMU9Yh2XaV/DwOOrmsWUX/eIOqcUIBpcmswd7tIG5oG+PXXW1rM3N+WzgD+dV69YUF10RBAcr1uTdMr2CPo+2MI2uCi76vEQGiITdTWsiapyEk3ETofyloi2ixCjKEPUQFfSj2FuKHP1riAzn8XOMvb933VSY9BrXaci9pVrRa/mU7XVCjjphmjT0lde7lkSt/TTBttzGGsqtrWZV3/6HqbTAovuDyza1fDbH0Pv/wba6ytD/6+BetUZ8y59UipZ6/3wkE2AsS6gVTWXM/vBW4x6noaf0aGWfvq2LKA9sTsBLsmu77+Cx+C8S2P+RaO/NMjmz2M7diOh01sdTDoadJHWsRG29cW13IagxrMz9UZHtcpagFW2tBiFmfq/KCjteCpc0bwwTtNlZQIoTMWbYJLY12W4KBWz03997ga3MewlDLrYdDvOjB0eYCnejUVnmux0AAF9Kuys6UW66g2U0FjMnlDCG0tTvIxjNlaEVEAZNfTGHBMvQJCMXlAiI16ABftjtY0jTZ8iNCa3ribz5EQ6OadnrOJmnaWgIRAnxQkK5OaaVoF0WJWVV5MRSlWoJSMoRtawHpaH3t9TqmC+w34VRdD7VBmM4ZIpHiXKoZ7Mi5mS7XCX6wgzAAsqpeOMSJEghV49V2v/rBVTqAsaeoToJ3OsKK5IJ4h0C5hybqi9akjBKFpA9KEWjQW7XqS6b/7bI0kbPPRNI3OedeptMKlMqMQMRlJCLrhyQ76cl0XuhQdPJa6VvTzZFpfWxd97Ia5Hv8u9QYUKSPSqwY5L1HogV7dIMTXon8e643YCML9dfYNB6oBSLZYneHVP0IT29EBNny07zW2LKBdni+zY7Jjs4exHduxHQ+B8IfBPVtYbpUIZp30SIs2RiZNQzIdnnuPBhk9FxEr4NIH4kLKnPCWqUbhFTHD9pEswIuT9BhuA4UCIGP2mhAIoaHkBjUqEMS8YN2z1M6i6VkGeUNlYEVYzJnVGCq766AY6/iUc6qpZ5cRGFav41NAS5VMlNHPXU4gBnDdsmlgScsGI36vNk8pQcDssAbGsjdXhqZplGk0e6X5fKYtbO1aooE6ZwFLr/i0sZ8HCrkIQRroOwrC3FwNfAxNo8C5KaZfNflINmCag+lZKVppDzSNtYc1ZYJv9pSh082GBKGkQhaTo1h74WKgV+c913uflS6u1900DV3Sue17ZQejgWy/h/P5nKobFgFnebNZnEmgkVLlJ4lEjK1JCBKpZPr5XNelLdkQA6EIycB0tup+CQqyG7OWI9g1iXVAG4M5S7+n0RrHPZNHmyjvfasfn4GtLQwZIYnB9LMDHHSnCvX7tQMUK5TM65SyB5hB6BHsd9cIbZZ6HtuMWktg/WwNfsIUZbFzykgM9bz+/sbs33zdbpyEr44t6XFTSmG1W2VHuzUB7R98/g94w9vfwKyfbfZQtmM7HhaxDWi3ZjQh0sTIJEYaq/B2naVXlzs75/9eKJmZFx6hnYkCg7k9oCwqUtOrUqRWWxcKBCGVnqPHG44e28HR44nU55FUwJ+3msZNVrVSTLvpz1Yxke9iyqwbKAyoH2lANOUMsKFRgBnISwHvLFUTr1b8YkatCqpNLoE++F1j26dUvVDFgKf62Q4MputJ+2QspTGUYB3W7Bixifp9033mYq4CVUYQaKIWbvUp0fWZedfTp1QlBBKi6T0Hz1m3+Zp3nbJwQSAELQRCJQI5a4W85ELuEympHZkXR6koU4a5t3nS+5mH67BWu2LSEyxt7yApiILajOpUkzkMhDAwvylnbZoRoxahCcN8GEsaLXvgIHfeJ/pc6PpkncNMQiCRJk4MFMponJkudYoPg4LO2DR2LnV1SH1PSRkSlDza3dVN3lDgJhSbVv/MWCtZ+3QANfvg6zu7LMGAbgiBru9HGQT7sePo4vekITbQd73ej7pOlYX3a9W1p5/XKIGSijGyAYztllIIUe9RlEgo0Nh71MpMZRWDZOEb+H3y9V/y0ItUEj/63B/l8kddvtlDeUDxmTs+w+9e9bv89ut+e7OHsh3b8bCIrQ5ov+9J38eLzn3RZg/jQY8YQ+085Q8/EdV0utm6VpmbBi9nJjkzMybNWaQy6uglQSqjV1mgqMxpTceLkAn87h98CslZXQwMOAw6WP+PWXXJUNzkek0Hmgs5sR689aenhK1AyUz+c8oVQFRT/crAlqGQDQU2gwBFWbKmaTD1wSAzMG9PoDKh5GTyCANW0bujJTX6tWiiSiRyKZXZiqO57jvtEtaVrroMBLs/xVL2Y21qMLCprC6EoNKBruuqFZqD+iiR0ESkqJa07wfwSwl00tPa7fMbonJMlUKI1Qr5fR53Csyi9mYhRHLulf1jKMISq9z3wr7gFXcMNmTushBH//b75XPftAqfijGlJfUV0A7ruzXnCQWZfUoUsxBTuYHKQJqoGtam1a953pFLos9m8WsZBcONivFjqFrXgoE/Kz7TTeCG5VX/oS1xI+6tINg5TNIhheFcWbXBEoXZPPKRKxsWl6bcevMax453hEblLFUCY+uVXEwGoutfwbaB6wpQZVg/BZVspNHvb9GNhQJc0HbSX5ul3ZKAtgkNP/7CH9/sYTzgWJ4vs9Qu1TZ427Ed2/HXi52TnXz0+z/KWXvO2uyhPKB44qlP5ImnPnGzh/Ggh+s2YQCngnl9WjWzPvyV8ZNSmOTMPGxkMt2zsxQFme6X6inYbN2+ShlawgqF008+QAyBPvXcdtth+j6Zo4Ayow4Yg/lrlkI1qHdmL5fCNBeON87ggoNg718/IDMFTzVNDAxSgwE4efMCB3IyvFJBZRC0532yYrFCSmpHFpumzpsyycN5Bxsl7WCmP3GApal0H1sYpddBi3ZSSfp9cZ9Unc++77XaP+mlTibqo6vHkqo57vu+wqhctBpflR5CE5vaqSybZVMuVv1PqWP0++j0oYgQiLWrXAh6TNfwiulX3MorFLXpKmnoEKYuBu7Q0GsaPKcBjIl1zbIbknOutmUUnatchva+uQxFc94OuOpeZQDJzmIHm4eAAs4Qo3Yas83QeH9mH5a6+ci24dFVYNrvoj9xWtMbPagOXQbdq322/Lps14AvPP98IZE+Fz72yUQpyxAiTTtFlQYjwG9vd3206mI2LHU2bNXqBtIyI9Y4wwvUVMfs9QW6br4WU7slAW2few6vHWbfwj7a2G72cO53LM+X2TnZudnD2I7teNhEExqedsbTNnsYDziuPXQtNx67kRef9+LNHsqDGk0TaaOn8MUz0hTTsQLUKmp72E5yYR6ipobte1Vb6frKDRpXqoG9HysgTFrhNd96Cbv2LNHNOn75v72PQ4dVE1issKdYm9YKKrUTq9U5qXQhlEKbM3OTTBQHUagPqT+gswNpA8vcw35I2cGsdkolGZhx0JyHeTCpgyffU06U3phhNQgFGDVRcCBgaXcHumDNF1zWoKl4Z2idZZ7nrgJq9WINdaPgrJun3/0Yfa9s5KSdqnQggG88RNSOqyQhh1KttxBBorJ7IRiMNWZZ0/5WFAfaCMNS7EPDAiFLqXrfENQ6LZh9VN/nCrpUxaBs7Ri4NlZV7+14fWMRY6y66mKOF4KYtZpUZhhnE3u93t70znnuhV+tsdhWZJYzUrQQMGdt8pGzXnsTmkFWI37jMUZULOuQdB5LgWBrxO5bkAKmVw1ADE3NUrieQOUXQ8MHHbXJZsTXqPokt03icRdF+l5YWQ/ccKPQ9SptCCGQzBEDXG5QqixBN2nFtPAOsn1NjSUL9gObU9XQbvyd8bUKgLekhvYLd3+BU37mFP7g83+w2UN5QLENaLdjO7650eeeX/7kL/Pp2z+92UN5QPHLn/xlXvO212z2MB70qFZPptN0iyN3AfDcp0EyRGBq4NEB1IbnW62qYkPqd8NDUDy7mmkbYTIJLC6Zz6wxsJ7+d4bQK9nF2UYUVFKcoc10MWrxVYxVw+nndpmDi3Md0ODkLfpgTykpS1zMg9XS033q6axaP5ullupVxbpaSWVAU+oJBmpiUHCe+r52FnNW04unvMmAiNA07UgOMTQTaNqmFlK53KDvu4FhjKHeq7ZpND2M0M175vM5XddrKlzU0zfasdTmSb1zu3lP1yXUtSBYK1QFxi6ZyPa9LiXVEKehWYaEoBIW0wO7VZizyKGuAXNKgLrunJXu+l7BlDOqNrfqrKCSk2j6WpeeIPq+3jqaOQMfbHMRTQc673r6XucjpWJzBO1kYjINXft9n/VPp2tBYdrQWMA3NjFEKNm3cTULUFyuUgbPVhHIUihBQb82w9BOcuP145IYZ7UN+QMwnSaedVnhsqfMefHzA4uLfst1XccQzc1jYFF9XeFsvd0noIJb79w3fq0Ygy9VOy3DRvBrSA62JKBd6bT12VZ1Odg93c15+87b7GFsx3Y8bKLPPT/wxz/An3zpTzZ7KA8oHqlFYTBoA/3hKJayHIPQQRMLbSl0wXS2YSgacWaWghUMla8+HaWCSAUBCUrSAiiTByhzx/Awr4B7YH/9Ie7MbVsyMwdVQb1aq9WSADVtKqNUvKdfS/0bDAyuF8RJGAAWYEVDG62c9LwKpFPKdNb8QKzgqGmaantWsmmBxfXLYsCwCnQNkGkq2hspqI7Y7pMDdkubu21X1URKIMS2blYUBBtAtfNEa/4QQkO0Bg0Q6FJiNp9XYONgxtldxvM/StsPtm/BwJVuOFKvxV4SrDlCbIbNiHeOC0Ety+y+OBCGwSHCPWFd9+pWYD5PCLXjVi1GswUgoaFpJtaKWEi5GFjPVWqiIHn4U4qQM3Qpf9XvBkH1zrieVrQr3HgXp73dDDzaRmzwCg51DkA9iHUzFqp8BzRL4l3DdO4zBw8sITRVRkJxhl2d4obP8uD7q59Lk08wsOS+3tWBJOgfl8T4gerrhvt+X7ElJQcrcwW0W5Xl/MVX/uJmD2E7tuNhFVu9KOyRCmj1GTekxPV79sATdzjA+xEQDdDOLd3tzgbVXgghBEjWztQ1eth5XI8XqibT7bMG71KM0QNG3aWyAggbs6dofayTbCDbjuVtZd0ovoxsjURK1Vq6BZiDAnHQjGsks+MAFPx717DBnzaI64lDZajcmB+sfa3rSdE0t3uxjlPf83mH1fgYyFPnhCQKFufzrsoNvFUsFGSke63AMmdi0yhAigP7qQxkQsgkBveB2DTQD+CnGPAZE+vunBCCAj2MdXXNcUpJgV7TWOpf8La1zrK664SvA58jsestuajTQ3aAP6zLEKMWkzmAzn6dceOGw3S8tWjOpBKxaTSVb8VkyXTdOWXT7cYKNkPUhg5+z5yltKWs12DMr89RJJBF2zRv7CKn71Kphr45ix9zxGkWdRlIDBuX4hkJyXVzoq91lljos8psXAut79PX596063w1rypFqs55+LluXvye1WIyl+dKqTKXe4utCWidod2itl3bsR3b8c2NbUC7NcPTrBoDWykh1GYL/sCDQmPs3nrQlLSnOdXH1HxYLYVOLgqEXYkoQjZFgphe7+jxGVkKKytz82Z1ezDtVoQDQ/9azEszS7U3KsUK1dy2q+o6g7VEzZYaBtACpqadbJwIA+hEoSFU/WzJqisuzmCFQN8PQK+UTPZeacVtpeIGBjOnZG4Rqg1tsraTTaWvkoIQAm3TIEFU31qvVTYAC8XVhZx6kzyUWoQGRXWaQCoFUk9CgVjbtDSW3s4l08072ygkiJE0mxu7a44OrTGIkol4cdQwt25Z5VEMwLkswZ0xQgiEYqlwWzODtlqqD6x6zs5IKVv7WteAlnrMaJ3XYuNtkDN9UaA+nkcZbg7F5q9PPaXrTSoS6mtB2xMH6TYA89hosZmokxpj3InhO702A+bun4s3adH1UHl//+L7pwLahCFsAMp9dsmEOXvY+glS8wfGMKNtns15YGNmQ8vbchq6l1Uq2TTvtuTrxlFBr9nUlYGddZkFMnIu+RqSg60JaOdbW3LwPe/4Hi7YfwH//Ln/fLOHsh3b8bCIbUC7NcNdCexf+JPXH5D+HUGLnFpjJbva+rZUltcZPQXIybR5+hT1pghVx4fQZfjd3/skIoWchZVVN+iPIIVkekL1XLJjBz/rKITqvJBHgKkawWuVVX1xLrmm+sfWXf73oUvW4HbgzGU0raJqMyHngdVWM39LP7ctNI21kfVjQbAmBjFGa2trzKq1mY00FaTnUsCuR0SqyX1lJ4v/SdaiVHWjOY+q/f1+dd1IgmGMbNFGDQNQUV1p36fKBNa5yGUAWDnXYrBoKfIMarHlxvxlIwMfYrT7kjf8zMGlz6GgsoFSqMVhxa5X2c++zkUxFn20mLW9rzGZYjKFak8lUqUKKkcQgjl8xCZuzBLgTg+WxcilbkqGOWxxLbQol6/zY+CxDc2QFYCqba1jsU2CblSEGAZJSnWUkKHDXp+mfPbqveTcs7wspG7VAG2onwjFycMGtbgetwz3ucLSulkdMjLDZ2Ej4PXsS/3A3UdsSUB76SmX8pMv/ElO23naZg/lAcX7vvK+zR7CdmzHwyr8F99WBYVvfvybefZZz97sYTzoUZzxHOninAktuQwtce1nEwNFc9NUBgObDto0DQ1t00DJdG607ziAXNOlBWF9raNQ6LuOlIZOX1gVe02Wmpawfs/SyIgoyATmpkF0T1y3TxJjFpNdVyBbhbqzVlL/KDiXEZAd968v9CMfWZGhWj5X4KnAv+s61cl6m9fiTRCs0MuOEQ3ge9cuL8TTwicHxNSiqMbspIJ1W9M5pepUG7+nUIt/PN0fYqiFXPU4QWpLWK1ZE3LWPwqubD5KxvGwtu/NbATC+t7YNDoHebSeSkasDXHTtNU5IaVBHuGMp4JuvXd5xBTGRoF+tuvrvUisNtNQz9Ri33fdsTO2FeSWYkV7KknIfalOE+7j205aW/u6jnLSsXgHPMvpayYhClGiNopImWCSgmi6ZZ+iIP4Z0PUdLCPgDSD88yO2Btylw7MUpRRm64W/uuKorp8Qa7Pa7I4gBsYruPUWz/ZZo2RbEwZSdYdRwaoWT+YBtBcIoakZHJfPfi2Xgy0JaC8+eDEXH7x4s4fxgGO1W2WpXdrsYWzHdjxsQkS46n+/ioNLBzd7KA8ozt9/PufvP3+zh/Ggh6e0ncXSb+p/HJiM+dCJbVj6OCrUslSmPwgVzGSvDR8BU6sst+fh0mLmsmecxdJiy1133cWVV64y74ZGDg6UnDYSS31LGB6quRQmBjJnNl7BNZmRvusMMA3NH0QGVrBeryho05R4GTqCFWVPvdqb0VxEs5aq1eEeBsbsHzRNq5pXm9ecesTANTaHGLPq7KVqhBXoxRjVZxZnnl1DTC2mSknHnk1fKkHB0ODxGivL7hKIon1nN7B0WrlP1Ue7rZWyhsnubx6tl41paD1f2KBxVpZ3mKcQ9N4I1gFsdMyvdjbIFURVX1sYNgFVYiA1VS4OjA3cjnW6OSXatlUwbGx4X7SNbhGztmqNdfUNW806YNkF/Rru4R+rhVlD+1uVWRjgrpkAY2ftOF6AVde4XeeGpIIdu+RCEwttoxsYCS2Sc92QOgPu95TRmhQBiQrUs210/BOQs7a99U1F/X1A2bC2x+z1fcWWBLR3r97NidkJHrX3UV/3Ah+Ksd6vs9gsbvYwtmM7HlaxlTe51x66ls/c8Rn+1oV/6xHXcGWw3zLQ5s0IjG2tmftSWDT8MhdrKWsP6Vr9LEIeG8rjekENg7UEEXbunPK0p53P0tKUL38x8rnPfMXal/Z4MVkxdk2Kp3+tHakDAgbWuBNnXX3Q9ndnYy0lXCQSm7ZqCsdPME9vKx4QJMuouKfY/8uGBgRBxFwUsjKQUNPa7jlbgWUI5NhYM4mkWllj4xoD2Q48xwymp98R7eqltlOmE84DaI1WDIVILZ4C6muDFZOpFrgjp1FzAdccy6CVxZnDIIh5ogY1H7YUvktW7HtWOFYLufyaS65zpjIBa29r14oztWW4LgdTFcznIWXehABNUyUYvgnIpdAwADMwnbAxszkXStfX++1jqOn4pFZotfOdu32Y9nVYK1Z4iFhnuILkmqfHV+f/n70/D7TsqurE8c/a+5z73qtXc1VSlXmeyAwBAgSCIDIjCKI0iqC2U9u2gv1rbdG21a9Dq40D0C3tAE0rioAMyowCMoVAgIQEkpC5MtQ8vnrv3XP2Xr8/1rD3fakAKYvcvMpdUKk33HvOPvvsW+ezP+uzPqvXN0TNdph1WdTsgHP/tmx1zZILdeU4jIS1a4EXPGcFVsw0uG9rj/d/dBH9Qva5h0oi1IkZxOTes7LplGKzTsfQVPeMM9xZxCCduTIsxXijTUlGY1nadv3JVX+CM/7kjHEP47BjoV/AdDM97mFMYhJHVbzx6jfi47d/fNzDOKx499ffje//++/HQr8w7qE8ZHFoWy0DteyAxoAYEWFK39LFUMpJRg7DnvK24+GQXwNTUwHgBSAvousXkJcMZ/Q48qAdKfqR06HthTlcVJYua1rdAFStjTTmyTpM+XWqnnDEVsm+jva1tQENleNC8RQVrWV2QFZ8aLOfw/lMKt3KsmomU1ZmV1lM18vCOnbBzx3CaEGVs6YQkGYes8VNQP101Uu3FGXVBWfmw9tX+lcDsdLKNlBV9Fax3QbUckpIfT+qA65eV+4dCeNrgEllBVZE57ZdNk4FimbVZdfgll5qdWUtdet7HkJA07bClJPKGRTEl05ho/de7ov8vjMvXRpdy+4C4pkN05vKTonBSAZgfStX7r+5KpT1bhiW3Ju3tKwltC1jzep5rF09jxXTHYiT7dH842XjzDb3UEmBS36AzoCsgXjAmykYbGe9/vLZK5mcOkuxNJYloJ3v5jHdTC9LdjZzxgXHXoATV5847qFMYhJHVfzXj/1XvPvr7x73MA4rBlGq3odpOOaRSBDRNBF9noi+QkTXE9F/15+fRkRXEdE3iOjviGigP5/S77+hvz/12zjHyPcCYHMBIigPMsUWGChIHCozWLqCaUcsQtUznuXn9gBVABBUzjA1mAJRRs5zGC52yBgisTCWrGwVcUawdOoIkNV0NhhTmmbtlE7m6k82xs9ZWwJyRhODvhZyzUgASZEToCwUS7GPgRYieBpaj6RAP3hXMGtCQAQHamZflhQgWdOIou0skg/TygZN21uxFzOQ+t7BpiEUkxLYcfu+F/2oFoO1bVO8XxUgyzGSSxYQKo2pgTTr3FV1ICO9twZ2BUxWDKayyAaokgPTbMSlg26CAka9Hm/3W40h6cbEfm4gr8gReBR8V5sEmwM7hoHWGKN0L1OpR0oJXdf5fYOm/CmQb2RGNj5y4wAwKMjnhcIojAvKrjIyOnUnaMF+r0GyqnpOYOtfZxkJFp1wYAOi+pkhQBx0pekFcQQhQrrABfdBBgVxEjH9OAEU1QfX5s4ZWlRdwQqIrj2VwxLQ/a1iWUoOFtMippqpcQ/jsCJQwJd+8kvjHsYkJnHUxSAOHjaA8MHGVJR/zx5G418E8DRmPkBELYBPEdEHALwawOuY+W+J6H8D+DEA/0v/3s3MZxLRDwL4PQA/8O2c6FBMLS35vbXsbFVH2dmDjrBEWxlM5SjHoaK1ZBTgA86Ymm7FVxWMvpPfxaYRzaqCEybprCTMMXs63gBMztklB4sUvDjLxl2nvz2XSqWYy/CK/bzWC0oq3EpvCpMaQyjgBOQG/pZ+Z0gzAQN3pnf1+QSkQMykGirtgBdFye/JQEaMiFyY7z5nRE1ry9uCAyDKymJqy9cmFk9YoAD1lGTMvaanQeocoEBWOlX55eucZHcxECmFAWvzF9Yp1m5tgGhvUyqSiajXGEIAFKzWrgeAbBqoYmeNKR3pqqUnY2OnK2cDAlyTXK8DW+f2OkAYRSuCTDqGXv10jaEOyjCPfkCM7Ye0AeZaplFAce/gsTg65CwabXgXsWKVJdIFWSU5MawSz9vv6lis+DYEQmK7hxDnghCQVH5QCHFyBY4DWl2T5mZCgN8jK6K833V/i1iegLZf9AfAJCYxiUkAyxvQPtwYWpYn4wH9ttU/DOBpAP6d/vwtAH4dAmi/V78GgHcAeD0RER9aV+AxwtIuSbgJMyn/yZkRAjDQww2DgCkpnoKmxTVZmdlTp3L4AhIBILHoHe+9by8++tHrQQC2b5/zKnsdmILEeqwBlDMCrCBKgJiJx4ZWlMal6rvkZJU1I2vaULO9whsjy/UIEFJ9aqWVBYqkgAAkriyhYkRgUgAdKpAGpFTa4OpEwOzOktpMWVMGe42xuVmHl6wyXoERGOhTaRPLnLWgi5XZbeT9zAVwVU0ZHOcYm50zsoJzY0OztuU1yE+k5v0qC0C1doJKKyiURg6iQZX7zzp3SYEbKYCGM9N9YWS5NOWw+ai1tKGJrkc1OzBAuovVTG0N4u0+1X9GHBDEg03WSB6VK4wURlUrhygggJB0vULXRe09S7pxaiGtklPKIC7rKepGICpwJ5M2mG4c2pqWM5gJc3MBnCMOzmckFFlOUF1yNvbYlQEkLK59yQDrnDZV0RcBvi6s9K6pWunKPNrnGA8YyxPQLmOGduuBrXj+256P1z7ltXjBOY+83u2TmMR3KiaA9sgGEUUAXwRwJoA3ALgFwB5mtqqWLQBO0K9PAHAXADBzT0R7AWwAsONBnFEexirmMwbK2CciYEqfZosg1XzmqliH/ShCJgUHDwVgEgzg7Nw1xK5di3I6AogiQNkZOAYQrb1nze4qqyi6yuBjWtBUt1XlB5C6ezEolg5g4gdqbJqEEIKsrKNV5mdlqYoOF4CzlAZxzKIqUEndp9SX42QGNVKCYwVZgBYrqeY4pySSiiqVH0PrTQO861kogM1AojkJAEmJy+IWEGPAcNjJfeqtwYMygqp9FRZV2NKkWlsGY6BWYqW4LTt7zj4PesdV/0s5gVmr6ENpzmGOCVa0RzmBAbQKSO2eZ/25Af1QXYtJDDhBmXLxBDaN7QhgzdYWN4KckTevYEavrYvJbj6KfMS6kQFwr2DLUPhdd0mAAFXZx5V1YYCyN2kIK3OeC/NsDHzWbnQOQG2564YJLNmBHTsT/vbtHXI+iMxAlwbaqEG9gNUaLWd5rxSYoYzXZDQxooMwtAaESTdDzLIGbIylSA02wG8qQViWgPYVF78CTz/t6eMexmHFgeEBXH3P1di7sHfcQ5nEJI6qmGqmHlaA8MHEM898Jj7zo5/B8auOH/dQPJg5AbiEiNYC+AcA5/5bj0lEPwHgJwABVzWo0wSoVKRXPqB1cVZjPrSBYH2QzB+W2KQBcNbQfWRhIEAekgEBmzbM4NhNDfo+Y/uug9ixIwO5So9TXfiU0DRRe9VLSly7r45441oDBzCQkRFIDMRYOyuBaIQJLfOirKmCbeltL0VQJnEwUOkuDAb89dq6St7ADPW6NbY1e9cyspQ0aRMJlTcYWOy52E81TXQG3FLnHszS0QomAZAf55zQa8OEEAZ6DDlPpyyneclmBWmNOgYoxajAUz1Tg3mXqk2baT4N4HMBPcUZIcMst6JLL4LLNnInc9h1XdGgEnkHMi9kI3IgHIjccovV9cIdDlyOIODP5slYW4GW5M0WbK5cisDyddPIHIQY0MTGG1I4q69TRAZ+WeYyomZxGeCAJkRlTIFocg2230tGw/XTyKWVNFC8lHVDkEEAB8x3AeAocxuMlSdl0o3Bl4YfhORrCyCEzArYGT0RWp3zQHVnPT2/daWrQLzdl6OOoX3aaU8b9xAOO6yKeeJyMIlJHNn451f887L9XB07eyyOnT123MM4ZDDzHiL6FwBPALCWiBplaU8EcLe+7G4AJwHYQkQNgDUAdh7iWG8C8CYAmJmZ4RFQYuyps6oV66WgNerrey7NBADog74AE+aqqxIMzJY0MAE465x1uPJpmxFoCp/+9F34l3++Awit6yOF4eztkBVYsnMJEGmUIe1CSZ+6PyhMFqBtcnMGk6bFBYF55lzS8YSQg6bguQAYinosgHPpyGVP967vFcBmtdSSY1qhTYwBXd85OEWfXXNpes0QR+3ick4CUBSsmYzB/86li1hJizO0LMkLsyy9bRpOIkKAtRQG+tyjiY2w8CCERoCnFcgZay1MXgBYiuq8K5sVUxFVbK7cf/s66nyFEJ0tTSmJBEGv1zYvhZFVP+KK4TWtrEkB7HyJFAR6dzrVhpJ1LdPxV2jMC9HaFrkXzbGNFwASpcppwDp2UQXyCjA2Bre+HzkzOr24IFS3280BqJwyin7YMiP+2cv6OWLGho0tnvj4AWIk3L1lEV+6LqNPpJ8H+NqyfIns33STpzIVS3Yk0s+yrUffRIaKia83fUV2srSYtI5l6XJw886bcfPOm8c9jMOKCaCdxCS+M3HcquOwbmbduIdxWHHP/nvw5i+/Gdvmto17KAAAIjpGmVkQ0QyAZwD4GoB/AfASfdmPAHiPfv1e/R76+3/+VvrZGiDJ9xnCt8qDL2lhkb8eQFBNaQpasAT5215WF1WlbLZCXKX0rRBK2FNKBORF5HQASkeVh6vpArkHqm5mpJpCGNC2QiqTJCiraiOXdLjJCuBsH/y660mBF0TZ96OtcJWVNqaUDHAWg39nSlNSuy3VFAfxgI0qF0jqOND3vUsHmqZB00RYPtsKojzlTaSvabz9rHTdSs7ShhAQ7TWeyi8WVZYqpxAQG7X2gtyvPvUuL9DZLil0nRBrA8t6nw0I1uMzAG7rwcZorW8BoG1bb+fLbN3iUjVO0dlacZ0U2/XOvtZzEYK11i2srVl8RbUx80YgCvR9ztR3OEap7Ldr87mvPgPVFs3nEZSVcRfWNmhhJAVh2wHZdJXNnzDFlg8wiCsKmrqAT2U1ek9XzkSccfoKnHvWLE48IaI1zSvB54c0PWFyHNHgKnDXDRtBitWaajMHLkDYPr9GSpcrf2Aga/EtAS0R/SURbSOirz7A759KRHuJ6Mv659e+5Vn/jfHT//TTeOV7XvmdPs13JCaAdhKT+M7EW778Frzly28Z9zAOK27YfgNe9Z5X4aadN417KBbHAfgXIroWwNUAPsLM/wjgvwB4NRF9A6KR/Qt9/V8A2KA/fzWAX/pWJzBAa1/790IzVeysWAn1KRWGFsrMKctjwLX2rgxeHGXaO2M4JfVKQVhK4l4AashufwUo4yYu/zASiTWdHdR2CygG8dIwjJHsWlL2Ah+DZwbeRkCrzwcK42jASFPFxoiao4NcX0mzG5ixQiYDGPaenPqKZYbqW6WinII2QTCQlUYZVQAiWVAD/7qoyeQAtW/tCAiG3MvgbCCrTVWvIFbZVAVzRKJDlja9cGBrwC9nHmkaUUsdUAE/8+E1IGmTbfIRb6Kgr7XCLL9etd3qK/AaY+Msdt2EoQb7o2w1RsapBxq5R2K11rttV9a1FaKwstbuNtcsqoYJDAjBUKVdvUtGEAgdidkWheBrTpMHst4UGdv/vPmFZTT0T4zqthAIjEY6rNnmie146phR3ZEQZOMphKt02ksk8gBzdrCNj2dQnJ2lkb++Faj9diQHbwbwegD/95u85l+Z+XnfxrGOSCym5etysKJdgSed9CRsXLFx3EOZxCSOqvirL/8VGIwfueRHvvWLH2bxcCsKY+ZrAVx6iJ/fCuBxh/j5AoDvfzDnMMBUGFr5uQAns+LiERBaAO2oNAEAGNlN6fXN+rCEMKz6Y6niJhA1yFncNQMGqp9lZdmSMr+iR/RCqCTH6bvkUoImmQ+tFt4wa/V5NmckhAp0lS+XPqyFAeSctYq/sHQGfoSZI6SU0aoGmczCi60SnBBVDxkbtWliBhKDqMyXV9cDCKFiHxWsQgvxmhBhVYAGqC09H53hDAUwV0DPGWlj6dSNIBlQV0ZcZAOsNmpBTB+0SYKtA2YF1CbHgADxpbZkco+hQFqLlFRGIOtMGV7Vr9aSD7uerMAaSbWvS8DqaBe0jBAKwLc1SaTOCLpJsvmyAVoxWdDWwqKF1YKzqN3MQqUhVdbT0vZFWkDi8EEKmjkDJJplYiBBZTHKBLtQh8RyC0RoKI5slrz9MYkzAkM3cRTAMD1ukHPqPS+SE9HkgkXHbfOU2TIIWRnajEa7IjIE0JpdHGAFd4bTrQPZN49vCWiZ+ZP0bZhkP5Sx2C9i5YqV4x7GYcWlx12KT/3op8Y9jElM4qiLqWYK+xb3jXsYhxUPN0D7UEWtk7W0Yl4KVFnSogxGVP/LhCIvcJDIUH9MTfsrCWq/qwmunBm33rYHXZcQKOOuO+eQkcUejKIzvpaCZUCZ15Je1cewg+wEeMEPW9o1kOsmzTifiRAsOaqDc5umqJZQgbTlrFbrg5Fz8Nea1jGzpI1TKsyyAR2RIQSEUI5vuluGFCxZBywAnlrPBjRTD6KATFWXM2Y0MXo63buQAUDdjYsZTMWLNauFV9NEt7oiIi9Eyyo3CRQUpEZQjKL9ZEYMASmxM/cjvrF2PpVymIxF/pgeN/o12GspEPpenBRs01DAVPAUuG0qdDEiOuur16A4svaatd+57AKFHU/qM2usdK3JNWSe2Rju4NpioNwDo1jZZNQEzTpQySbY5o9Er0osaxiBvPkCKXvtGlxmZ9XlOMGlCCESwA3ACZkjMs3r51KK2Fhb77KyxqQWdVZsVj7hQQGtfSCpSA7YZD3VxpTl4mqGeukGxuJIFYU9gYi+AuAeAL/IzNcf6kVUVbiefPLJh32y5czQTmISk/jOxMS2a3mFp2XtIWbsjtsrKUNbvafR13amU3UwbABTH/qZwZridPCnrJOeHVvu3o8tW/YBrCAa8r5MWlWuaNjxmoI/Sf8Gtwxr2DS0wYFBVjbMZAoAy0OfjWgrul9/iEPtnygAyMjqdODm/Yp3ltoWmdzQ2FuxTwogKuy3AVwD1XbOlEvxDSvgFBBXrtvYVmu9G2LwOSCCs9ZZW7S2g4GDF7EQExYVSRsqUNHajoCUzKAmaCGezkUI4mMLAYBg6f1mF+4erwawq81B0WgLiIwhAgGejl8KiuvvoSl6gmxKjB03SYgVmtXvdwkIis+rNcKgCrDWcgSzTrNjOLsL2y4BI84Suk7qqIsfy8bDNl5SgNXoIjFtq4FWVRvAJpX0KomVyXVwTNi+NeGfP7oLsQnYubtDnxS00pK5DNZwQo5R3y9QAIiRQGjBPl9EJEVrdk0FwutnyLemoOrrpXEkisKuAXAKM18M4E8BvPuBXsjMb2Lmy5j5smOOOeawT7jYL18f2vfe+F486g2Pwh177hj3UCYxiaMqjgZAu9gvjnkkD12EEKQ7FBhgSVuzMZYw2x546hQAojkKEIm1F7QoiFlT+FQBGvhxxG6rAB+AMbsi4fhNASceH7BmdStjgAISAy/Efv7cJ2EmFTQaUDY5QSb19VSALeCiFGsRCuComemMSovJOlq9bmcbjb3Ooku1oizTwpZzBcsAI2eg63r0faeFXyUt7i1jURoL5JTEH1U7a1lxFVDAV0oJfdc7mA2VD6tpMvuuQ6cFVgZqrYWp3RfXshozTQFAdHkHcxbJCEoq26QCwlSW9r+BCE3bSmtZdTEojCeUkS1FcEklHSZ5CQZGFUjmlPS1ovUFuGpZSw5YbT44Z5dvhCUgl1naETt7W0kNCKWxQa21ldbM0lo2qLuFs7LKwrqNl8pLAkHaKftKg89tTyTMJanrRaVggG7+imxH1w5bYZowxeCEfXMdbvjGIr769Xlsubfzz2vJpqjMRDXgbCoHImVsg8sH+kDCvgd5n9x9YY6jAm7tZC3ODBWZO2jbB/Si/TcztMy8r/r6/UT0RiLayMwPwlD7wcXvP+P3sXZ67Xfq8N/R2DW/C1/b8TVvHTeJSUziyMRyBrRnrj8T1/7UtTh5zeFnrpZnUEnve4tZwMRzgifV45IIQQHpkB3zyUMe1UNPI1hK3nR4bLpZRgyMR1+6Elc88SQwR3ziE7vw6c/dB9Ze9HXRjry/QAhFylLAEwLaKrVrUgPWlHXOArQtNQuqAQBgDLIdNnNGTsJ2pcwIyk4V6yoFHUmq6IOzhzSSus4KBjWbCyJtd8tagKVAKMaoTRiCuyn0qUfgku4PMSAE8V816YDJEUyRGV1GIEwuVPtqRVUFQFfa6SwaY2ONSddBDOIKkHJJ4edqI2IgyvS60jCgFBeaVjXGKADVX1uzp1xkD8r0RipjBJFoinNCSpVWOLN3PLPzpZQQFbTaugnqABCDdiPT8aUKSCfdnPgngUgLraT9rDD2ARRG0+26uPWeR5jeXKG+SHNCsXUzhnZpG1lmgPJolsTmu7TRhWca1qwJOPXEAQJFbN02FFBbXYHJOKzRiQyZRdKrP3DZBWRMJjVivSO1lMM3szoIvzVLmP06/s2Alog2A9jKzExEj4OwvvfzHzyS8fxznv+dPPx3NJKmT5qwLC2AJzGJh238+fP/fNxDOOyYbqZx4aYLxz2Mhzy4ArSW8LSKfqcaXTfI7ijQQYtS6mNV6XV2Vne0Dae/BkAbCIReQYkCRh2GtWA1jWtmTeNDU+MEBwixekiTg0/N4nJlZm9JVHvwg2HUs8kmHGChAhpcmC9m9hasOSfV1eqRNb1vRVjGSFMM6lJQpBxyTkv7B61gZ5cliJ+tyAqQCmgN6oxgbhDewUvxZu2MUJpSZFjnM3KNrKThrQiKFZRntamiRBgskQ0YmJU1knzeDCzW1l11mt61sWQbH2tjW97XNNXzWAEpmgjKpaua3XNjd0fBV6XtDcGlEVawx9VGI6l7gjRSaGStqQzCNKyuh4ZhhnINfvNMogMCKFcbOx2XjmPAGccNO+lg58ymcf62vopUw7MHsA57ArxP2DyDK69cibaJ+MqX92Hr1oQ+A4m15a9urrxRgt2LXKzasrLBf7X5WMzVbDZwP3bbMiCmCy73Bw8Y345t19sAfBbAOUS0hYh+jIh+ioh+Sl/yEgBfVQ3tnwD4Qa6V0d+B+NSdn8Ktu2/9Tp7iOxa9GnXHEL/FKycxiUk8mBimIc59w7l485ffPO6hTOLbjmI6bx6hKSUHbcXbUh6GkVkq7pUBdf2dHa1mmriA23IucwqQ4q/MCTkvoO8LQLIHsX3PbKxgyapZxylmLs4LI4Uso8wSoZIY2HAqkta+N8ukEIvlVGyEsYzqEWuWVMF63Xt6WFLpBQQaCxncC7WJUVPc2gkrJaTUSyW7jq/4psaRY5sVlzOaCm5rlj2l4jfrcoJgnaBMnyu60azpetPlmozC5solATEixsbPZ+MzFtYaR9TWYHUDiNo2y2Qfg7Yd7SCmANPsy2SzwOV+BJNzyHzInBW/2nLfypzZWFJfbMIMMNZjddeFakMWY/DGEvJDLoAcBdjW5/I1hsK4ggjXzc7isfv3Y7V2LaNqfVuUBg5l3dvSNOu5pmnRNHIvpEBPxuUCCBJXiWp4cmw7F+smkAi3zszgvIMHsdaL7So5TlgC3vWAkiXxPMkh49txOXjZt/j96yG2Xg9ZPO9vnodXXvJK/NGz/uihPO0RicQThnYSk/hOxDANsWXfFsx38+MeyiS+rTCOSNLyrCnK0oVAHtJ19X7DUuRSilUYvfmAOvAUqJsB8ZHVB6Kl3kl9OmNUhwDusTAcCqhwHYP8XQCxsGFZ2TKncpm9UK2vQAKFIECXpII/ECEjQ+ytorLGBWjL6WiEiBKGWNjRUvgTIH4KQKzZLAiIEXa3askaghaJqd4yRpBuGgJJOjz34lFr2t+goMPO6dpSL/xJPplBnQjEz7cAR2bxm7XjFZlFQAwRgQJ6FOcAQFoFQ9POBszKfLC+R9hCs/+yTlwCpnSGlBW0cQAYsQgLgGtn62IwY3V9c6AFiaa/NsbZ0+Q5A1VxmYHw2rrLAGvKWRpwULntNaA28A1m9YWFt/kd0YtWII8BEGeRH3DwtszJ5kPHdfXqVXjy3n1IYXS9GGgMKPIC03QHa4OrIDISYXrQIFALwDTMCcwGNstaBUhbPtfDtnPJuM8+eBA/de9WfGD9OuwJxYHCP2/RgLv1/9PPnMkYHoAzXZaoKrP1Nl5+cdLqk/CsM581aawwiUkc4ehyB2D5bhZ/7V9+DZ/b8jl8+Ic/PO6hPCRB1cNp9PHEMI1qrZkEJL3fk1U+Y+TBZjo8yUrTSDo/VMX9GYw+Mw7OZ+zes4hhnzC/0MvDswIMBnbMT9VlBg7w5AEbLeXt0gYsAcNmZVQxT2xAzApwZPRWZFQARm1BVVLANUvlLWudfQ6AFmQJa1oBvkrjaRGr96eUkamcK1QV8bEqJDMpBJwFFrAaQnVsZnVRIEALsqwblhVG2T3MOUtRXbAWrxix38p9Ql7Syla6aFVSEx0nBbNFKzIPVllAzRzX0gwArnu1c/v9V6BZM5u13MCbUuSsDHpJnQMAxaieyOanK3NR3wcHyyibkaZpHP0a3vGjKtqnusLL7oXNoF6zbbjykvGz3iPPgjAUHLMfn1UGI5KTBpFmAOqQOQFsncLIP3cmmakzJzWHrGeD5afZbMGqTIrJDUITR+5PiX8DQ/twDLZd5DKM55/z/GWtAZ7EJB6ucdzK47DlF7ZgzfSacQ/lsOL2Pbfj5l3Ls6X3YQfbM5v9ewN4VvkvxCEDQR7OqQYLVLGa+vOkzJozmKiM9wlgTuhTwNXXzOFrNy4iM2PP/t5fUNt7CU6wTlhARklRy3iLN25nllgo12StZ+0hLaxXZS9WXTdBC9nI/GILGOCcXYtoOsQ63V0AV/CUte4LYAx1YmEdkasiu6AAXUF60DH0KYEzIyEhxKjnigqWjJGUQ+dKn1uz6aPMoryz7zsIg1fYtwx4g42cMyJJgZp5+noJVwVE+773YrJaTgAF1r7R0TEWIKeuDQq2jcX0JUVhBETVvr222TDv2OpGy8/027o1Ltnv/JjVBiVn9Pp127ajIFiv0xwn7PoYJjuwtVR8jmWzZYDQoGNx4UiVwtQL8YJ5zxIoGn1c2uGyV3QF9D1j35x8Tg4u2totY7Z3MhgcyLXjVqhW+Fv2kbB+Lkwny/o5d3mFz5s6n7AWOz5ALEtAKymc5QloJzGJSXxnIoaIE1afMO5hHHZ0uUMb2nEP4yEPBjug8wekPtyY4UUzYCBqlyFjl+wdzsWRNCEQ3Z+B2aqlJoy5JRyYY8wvdApWoGAAI0wcIMymMZNgadlKAWA1+m9Ydb32HiKAc9HK1jpHKgb8nLm63MJOCSCN/hpGAUxS6NUX9ktZ0qVgF7DWuARQkPH6JsFcPRmddjyLniaXy7TGAnIpVVMGBc/CnimwovJ7AaUymSMOBiQV+4zSvrZm140dLSIMzcIGAuWMGBsYGPR5qlhSK3aTYjYDsxVDH8wjWNnhKIVtpkFOyYA4OyAsKLd45lqpmc2j2W8ZgDega6DWbNZM/mFzX/vS9roe7D3FWs061dkoDMqWkGs3E1kD53Jt4sXMsBYRmeCfBQoGC2XWfb0TAwj++bOpYGJc85WtuO76e+T+JQKoBYWsBZMk8gMuzUU0AWM31Nc/qDC0iYrMwDSyNvW+iYFBbAa+Be5blqhwOQPa13/+9Tjxf574iPKbnMQkHorYNrcNv/7xX8cN228Y91AOK7rUoY2PLEBrqevy8FNfVhLVQNbvE4SpC6ozjazPXi5m9yYPEJZR3o+gwMdTmvKQjk3GEx6/Gi950TF44XM2YtMxUyBqQCRFLwZSCrOqmcEQRS6gzevFYklY41qvSQpqOQtDm1NGyizsMQEUiv9sSe+W9DkYBURiFOTEpkEMjfqilo5WFnWhUc4JKXXCWIPkT5QCMzuHs4E5o+/Vi5ZND1qcDex1yT1Ye5GFOGA1trhoUFMWva1VzZv3cL1p8Hun4w9Rbb2cvpc/loo38GhFYVIwJvcOgN87tvUF7VSWzJFBmNZYgdAQCqi/fyFcKW6zYjTXvVbzUTPUzshS0dHWx/ZNFpV2u/d7HUtzh9hUGlPYpqzcC/uwMJd7b+sTUL9XAKnCwrKJET11pAAOJJIZCtpFTDvdQdwvZF0BfReQcgOKbdk0UpQsBgGBTKqim0xlW2VvIpuaCEKrNzvLYHxjRyRetMTlWMLWluNSqC5kSSxLhvbtL3k7Tl93+riHcVixZ2EP7t5/98TlYBKTOMJx34H78N8/8d9x0aaL8KhjHjXu4Tzo6HLnDRYeKaHZRAEvCh5z9dCv2dVSnKU2SsGkBGajZTXgVYOEnLUwzNgsACC0AThuU4/TT5vG4rDFF74sUgRmTdejvMeBgI3NJBBsLqyjKVAHpqRdz6pXOJPor4Sn7lmLqrJ6zBqII9PoKsNYs6zykA+ewi8FW3DW0bxqc1ZjsUAC3NUyCsqa1ilvYxZtjkMIaJQBtvvGmZFU4wsFdwQgNo0W6FUFXsxgllazpp01kGgtg5PKLMwArXYoEAsxLmNTZtKWRGaoM0Azch0257YWgn7fa1cz06mGYHKKwnpbeLGYXke0wi/VHjvjbr9XiUatj7W1VNh0LUKrmGDTMvuGxLS7jhWUoVT207S9NmYpuCJfWTYL0cAj1Q0kZCxUfS9TaetKvg8qFyDKuOBR63HeueuROOCGr+/GDTfsKtkR0gYNFYucVVrjmY+KP3WGtnJVKMVqdg/KZ3bJLX3AWJaAdjlrUN22iyaAdhKTOJLRpeVdFHbRsRfhxFUnjnsYD2kYcwe4EkB+rlXptUa2TklnYkDT0m7lI7YGSMp8BlYmqyAVwB/6AU0bgMDIPETf9aJXVH1s3Uu+gGb9GRXQGABhKKFEmaINUtRajOfZWSbR0HovNBlc3WinytUa0LMHuxWJWfOArEVcdVg620GKM7UKslKZaAEKphEubG3yBgqlotzBEAnLm5EcODlLDkhTBQcnyqaibDCMjSVIQZsBvqiSBNkomA+xjM8BjYJNa0pQQL6AXgGA9mJycGljsTVn155S7ysohFAK1Sopgf0RL1rxsI1N44C9bdtyXP1j96gGp03TiESlaZx9F2mAXAuzsNMA3A6NWTY31jxDpkNRPLH2Vwg6J4wGAKfsGQ4iILBkOKDd1RRjwrXdhSCFyXxsfpiBQA0IPdavb3HaaSsBmsa2bfOIgZByBYxRmn+IsseOTbK89Vyci+6cSdhnLySr1zFFAME3MrWu+ahyOfinm/4JZ204C2dvOHvcQ3nQkWyX/O1uOSYxiUl8W2GbxeWqQ/3Np/3muIcwnvCsOzvzZPpEY8QMGDiyUUYohAq4kf28Aof6oARJGtMLsSgVdjhnP5a/vgJK9pDO3CPAtJQOw/1BLCBFIWxA0Z6y2V1lSdFzkGIxkyjoUAk0krkzh4SlWlEDTqTAN+dis0RkNlI2TQZu4YC81qsaa2sV+jamtm1BgLeJdRCquk5jno0+M72nt0z1TmIMijQClEKMsmkA+cbFwKQjmqzuDSTtgIXd1GIrA8jMVceywornlDUlX5wKDJTWoNznUu9fLRmoY4RpZbGDM5/kpc9xlxHoz2tP3qUOC6aVFgu1gD73yEnmL6p0A9V47VNiofbNMG00lNkMFKRls25sGhStqm+2CGhj6cZWjqE64xBVrlGNmaS5CEgbZWT7bJVNgn1ErRBsVMNuRXLkrDFb69tqE3a/+Vwyz95G+BCxLIWoz3vb8/DX1/71uIdxWBFDLItnEpOYxBELs+16pOlQl3fUPq+A2Vl56td/X9LBRmAa82P/lJqmMBBACjyyvTFXQALCHuWUkHrRV/YpC3OpHrhS+JI8xW5p07q5goyhFHyVIhrRzCq0kxeyHhuWelZW2Q/F5W8u87K0MQCgTGIUe6gYG2X8gkshjI0dcR8wAGXpcsj15FxM/aWbWKrGVBhWYxVtxGZV5deeszdHEJ2ppv4ZOpel6QOgzGyUZgVgBldjJRBiE/W+kk2/gOvKxkx+XtwavCGEaXR1nNaow5wiammA6WFtB2Dz7Nfnmwc9j76nqZhl09rmXNhUO36rDRxq5wQbk7HtVuAWKslBTtkdMgyEL0UMAh5LMV9gZeejAOUAkQxEZmSC2pnZpoFkzWsh10iywBhRCGtuBZlELTgMhOBH1CVcCshsbRIRcjVamV85LuvfdVFYIGkUYmKJIp+x7yvJBop/76FiWTK0yzkuPPZC/MD5P4DMeSI7mMQkjmAYQ7tcJQc/8I4fQKCAt734beMeykMWdREUwP58lRS+5jzVC5XY0vkKMgAHBM4YQrSaRhrUD0NjjxjAQp9w1dUHcdPNQyQG9u5j9MjaHSubha2DH1LbLkvRWzrYgDWhAMaMLJXrYC8KUxrLWc0KP3hq3VL9NZBlRewGSM1SbKnm1a6xFImVsZsWMzYNetXkFhAoqW0DbHnJ+e04Qf1j7TyWgq+1o4HrdLloWtkYXSretXb8EAIiBVBs/GcEbUSBgLpznBU6MTFytTGwa7PvfbxEyDqOJsYiveh7lSSQz6v9XsZcwJK31GUWGwzmMgfGKNfjsHPkysNWxybgOaDvy5pPfXKgmkNVTJbZj8XMyFR3OisND4yVJZNkUGHx7WvAWnGoOMcoTNU42DpyDSxFgNQDukbQAQDNgNGCaUGArN4jl2bYcZfcC9ugwv2Ng1uNOXOschxCcIbb/22goHKGssaPKkAbKfrDa7nFix/1Yrz4US8e9zAmMYmjLp588pOx95f2YqaZGfdQDivu3nc3ppqpcQ/jIQ5jMQtzRA4S1eVAbbsyW/cvwPwugVLJzoCDHoJ1HoPhT+i7NdXOuO2ugFvvyCDKYE6AmvHbw7kwgZYup+Ku48StWYhZej+AuZfRVWCdyTSa9rDPzvYqsQoiVJpPZacz6TUry6upe2MFHUxYynYkRS1RAysBMJW0A1IQZcb+bdv6fNagxBhIA8EEoFEd6VK9aNHh1kVHcHmIMOxq76V0u4+ZjMzOPqYQTD9cbUrqYjsWNlrmQXcsJqtgFouuJXZmo8x08oI2a11LRNIQAYW1NRBZg9aaHV4K8us5kWGOMo3uvpFrdlpXVcWGlx1KKWqUDZBsAAKV7IAQZcV3mSGtmZNJMBCq+4oy50Swkq6AgITkTC0zgEy46nN34NovbUEMAfOL+l6dGpcDGWBFlXUwKYR9vgBEsksyMB5cblBLMsSGr/IZRpGAHCqWJaBtQrNsAe0kJjGJ70zEELF6avW4h3HYkTgtW3b58GMk1ylglFF0sxDmKHNhwAAoYwl/iFNQ1kc7Tbn/p6YsBXhET/UOYsTJxydMDST9f9udGYtDAR3Gmok2M0EJr+pBqwb25tdpgI1IiozIdLqF4mJlKe1g95edFY0pYCyogAGCgCsDPPZAt3FZYVF2ICVaR/OyFacBY7cMd7DrYtl9RHmkGM7BcgXygOKe4F61qNhhZmUiZZ6XSlLFxkkAuEghSto9GKAKxrDDGfCacbT7w9VcuHRBZnIEWALFB9bYYzleAJEyo1T76Ob7gabarcE3C8rwitwiamp+SUcxXaQuRdC1MNLQgkTb27suOavOWR0pbEe2JOr140PKGRlB5levMzAjK8hlYtWLlwI8W38g2TzlrApxgnv1goCu10WHDl2ye08FcFZAeql2OcsuFESyqWtZsXDltZu1iYMah/mfqunft4xlqaFtY+t6ueUWf/aFP8Oa312D3fO7xz2USUziqIrrtl6HX/zwL+Ke/feMeyiHFX3uH3EypDplbXpFhoBE0VlGB2DGygnzNqrJNIbIbC+hoDJESWGLx6p2l2JgakB4+lNn8JIXTeEZz2DMrlA9p+r/ci3OVdKPIQ/dlEVba+yfs2nqO5utNa3pJxSMWHGVDBiOQsr1Z9eaZtXv2nlqIGXgPISgzCwcHI0ypKlYP+mckTLF1oL2UB6oRR/LztYC8BS7XUBv4+Qia7BrszHWLK/LKBQwWiFYYWxNL9zLRiUnuXdcNKreFrhiR4nEOSA2zUhzg6VrzDWuipRtLsQ/l7xYrpYc1Brm+j7YufWGFHsxY86dcRbw3lSSDVvLS311vREGVNvsso+6O1bpMuc7GhS2l0JEBqn/svwyQjxo/bpQrPFMEFOIX3HNIMKIdjcGxsUXrsILvvdkPO8Fp+OM09fCXDtsPCZ1sA0bBcuS2EZMfGRDiF6oVsQ3yjKrpMKt+2BgdvR1DxTLkg5438vehxNXL097mz732Le4b9kC8klM4uEaN+68EX/42T/Ej1z8Izh+1fHjHs6DjpQfiQxteUCJlE4Ku7q+R6PdnGpAYjVarpPMdQcm1ViypusBJKvJggA6GJsKIFASeQCp2T6ZLVIFwiR36kxwoKr7lcoeMmkLVwVgXN5ggy0PfJBfk0UtDwhkvre1W4M5GQQHnNDrEUBXpBJlPkuXp8zszDEg4zemsgZ/KaWSVkcBEhSD24RFmyOWn/d9B1aAb5rVvtKbxiptX7PrqECfOTuY1ELY2Vxdj/0Hfm7We+AsaTWnftwY0ff9CPD1cbA0tjBWMcYoAE0dFEII6LoORjHXGln7PizZENS/9/a3up7s/CMFTfUmwrMChBgaZ68tcV/BOwGLbC4ClpWwdauvs9S/tovOKKy3actd28rsGlVzFsnZ1o+yrwHYuHEap5+2ESm3uO3WIZh3wa3s7Np1x0kmYdANpjtV2DpnEwAVFxAKtGQNw+eQbSdbn+sQsSz/9XzqqU8d9xAOO6wCeyKZmMQkjmws96Kw7zr1u3DM7DHjHsbYwtivnBP6boicBKgBpRAmA4gOSCRM/5ihKtgsoEj0rGoPpUCzfjjaQ5c5aMeiUCytsj3ghS2z56lZTBkYyZnRGZDSlq+idVRGT4EwZ+v2RYA6Eow+lJV9DeQFUYSo52ZI04cCmmpNrLF8wGjqv2ZscwWwxNu0nN9S5hb2fjtXVn8oZmmkIK+JynDa+wrgs82FaZ1ruzDALK8Y0NSy6GWlYIkoFBs1kgI7A4OhcmxIuRTL2RhNR2rjABc7KGNuraGCA/cKgIrOU+aoS8UijDAKyJ1h1StvmvLvTd1EIY+AYQPbS3S0RCNMum+GqDDi7Cx/kR4wieuDwXzb8ADSGGRkPUDYUP8cVZ8nUlAb7Gc8eg89a8IEoh4M0R8PF4cgBC/084m3D5ghWRTZhW1ymBnEebS7ns2dfSRcFpNG5svv7QPEsvyX/303vg/HzB6Dy0+8fNxDedBhD9sJoJ3EJI5sWGOF5Wrb9YfP/MNxD+EhjaVsjIGAzMkfaP6E0wdlR4SWTY8Hf7/p+VIqjgBiUp9hHaVqnShTQoiWyk0qM2AEZf7sGD7OQra6xCBDjjvU17V9Rh8bTxsjFPkBkQEDuC/+iH4Rhfnz9HaWFu8MAJWOlbkwbcbMmvcsM3kxlY+T2QGrFJ0lIzwFpGbzbVU7K0tfAyL9IJnXWqcbgnrfZvaCNDuvzBnLfcyyqbB5pGCbBnIphGoO9D4Jfx4ouEdqzgY2i94UTaPzY04HJM0YUDk7wNLYeu8dlLK6WdTMOdTurIDWpcV1dScvW3wmZalfX0sSxLVAGjennBCoHckq+GtskRODdV3JtRBCaHR1K6DVIeXMAKkrh8oLrDGDzTWYS3pfwazjS5SNGmwuQApe9TPGAIWIANZWy7Ng7rC4uOjSBb+PNkoy3YGsZWuzzABYi/cik4BslSzYx4AV1Lt+mEjXxJLNygPEsgS0P/fBn8OTT37ysgS0Zvo+TMMxj2QSkzi6IumD85GmQ12uMaKdHf0FPLVqKUkWQDIkwpQyaYFUkuA8FbuLgMIxAIA7ESgYYDD61OD2u1ps39Hi4HzCcGHOT28dnOBFLQV7BgVGlRkXhgomBgzMo+gCl+qC5QEt7KyAEbtWvWz7DwuLmtWFQGQM8OMA0I5mKECGzL2h6EzrP00TAZAzXo0a+ls63MAqUFhPS5fL2IP/TIBdYfNykna22TYM+r5AQYCmMtQAvMCviVFfA6SsQF8ZPyf7KpBtwNuLxXRH47IMZzSrvLQdQ5nMvu89pV6/rrCqrZ8r5+SvtQ1TvU6NpTcJwaiTRC4sfrUpirEBIYwyodn0qqH4v1KRONjKGHEA0GsX6UvNoMKlBn5NISBApDMhBs9e2LHKwlMHCaWo1bHWdCc6/gGAFpkJC4tl3k33Wm9Q5U6IxEL5fW9sEkJwb1zWtW7yHebS+MOKAVF9nuoNxqFiWQLaqTiFxbQ47mEcVpy78Vz8+KU/jhXtinEPZRKTOKrCKuHrbkvLKR79Z4/G5Sdejjc+943jHspDFnWhTdFYWuGQeb2yKSth/+o3zEiFZnTGzFwB2Bok6AO+hIDd4ULGBz64z22epDKcwYkLO8ws2j8FJ6NMrQsYYNUQrTGmqDjXrOAl1HIAeYgDfrgKCEKBXhQwn4qnqV2PMJnqYMC1K0PRapIDM2Mqcf/0Ldm0yReNssBQiYKwbxmsGt2i10U5p7OLVdqeVDZhbCUCgmLgrB6/fl0u/wwCynSbIHrl4DpXGTM7iEuZK8ZVwkEcCuBkAEHtxZK2NHbAr8x0SkkaTlSuEHY8d8vwAq0yf7X+OFSAP6OAX7NWKzpXaBMBApLqVDOLDy0D0qmLQBQrHWvZ9HFZgOCcFKyGAlIzAyE7Uw8AkU1yAAHNtjj1/mcm0Y9z8aUNeszAcu3DnvG5z9+Jm26ew7DrsX37vFy3Hq4Gs0yMBgEhqAUd2Wvg1xDAXhTm2RBbe5DPXfSBHmLT+wCxLAHt7GAWc8O5b/3Ch2E89oTH4rEnPHbcw5jEJI66+NFLfxSvuuRV4x7GYcfO+Z042B0c9zAe0ljK0BrwEBY1V+yP/L4zs/yUkJvi2WrghGodHgpbm5FHCmFyTohBLIcMqErNWBhhxxyYUimGYhRmDWAMFeS16m1qrymDgBKK+mQ3YJr96Hrt0J/BxwlSG6OmtJYtGlQIOKvAQJFpyIQZm2oMnwFOa1tqhWUmNXD5hxZH1fdI2vra5sFAnXJpCgwNBLJQkEip6FhhTCRk05BTdjY6mH8siVyB2cz9C0Noc2ruDktbyhqAZZijsNwfA4bWGczAE5u1FbTqv/LahW+0oKyhpL6LvnSURTWZBlAKq3xjoyw2ULx7QXYd5FZaKWdP9YtdltrDERWdirLLFKytLtx32bIJUJs625xEALmWz+jCtu5uUaUjvlQVlNocyJpIuO8+wvbt+1yuUG/yjEywi2ZdmzJPtkmUE3MWaU9C1TzBxmaSEs+qjDLjh8zoVLE8AW07i7lueQJawP6xKl1sJjGJSRyZ+FYpqYdzpJwecXIJYRutnEtT7XUBkz3WFOQM9fY2YCywpaDlwU2Ag0QBcuTHMAAi6UzGylUtLr2ww6mnrEXPA/z9O+/DsGtQt36FwF1/yFf0LDJEBgGUMbVeeKbsMCTlTCy2UCmp52oIUj1vQBeGV+S5kHMqRvusv+QaoMp7vCAHhRUcAeOcQe7BK0AhaArYmEdPqeeMzorLNAVs2ljR48YCGitQEUKBjlb172wmF2cGA6jWBrUuXhMdqMy34GX29Ln51NqasM1EUPP+GCNyCH5vc0oOCGsJQC1fMMa3aZoRqQBsPkxHreesO4LVOmED0DaX+qLyHqKROQYXHbIx6A2JvtSKAT3bkEsRI6i4PzjMY0LqcwVczY856iZDgT0RArO2mCV4K+dAIEQdh232bCFSdT7yz9MJJ65F0wC5B+67dx+GWT4fekBdj9I0wdZmED0FgNJwIXNWb9wy5yGWZhIuCRn5t/yBvh6NZYmoVg5WLluG9vpt1yP+RsQ/fO0fxj2USUziqIqP3/5x/OT7fhL7FveNeyiHFX3ul61Dw781ilZRQIxk3osvpz3khsrQTlcSBWdYAQXHavBOWcEA5OGo6dsQCDEwLr1wgBM378G6lVuBqrvX/cCrg54KgUKBMhGGxoZWleosmV9EBGVZAWEyxY82qbUVqlMJaxcRSL1RbcyAV8KnPmFUX4nRQiQqwCBrWl5cIzr0KRUvXmCkhagVa1kBXd1FawTAxqBFReRzk/S4fd+j6zplakcBCesN4szIKRctJ5kXrEoXHDCXMZmlU3Uw9xa2efGUNaQYMFTyi5H1pddkYxW2u7CAxpoWDhruXeteuAaA6/lWttc2ZNZIwTcmVDYI0Htj+vBaS2uNFOx+2u/v93kBRuQ0psv1tS6rDW3TILJueGwe/GUBzME3SyRoExGEwAAlAbtgxoqZFs95znl48YsvxbOefR5i6N1ZgsEi9dH7ZOcZkcJQcPkEYLZdxu4HZ4yrPVoFbqvrfmByFsAyZWhf98zXjaZ0llGsaFeAwTgwPDDuoUxiEkdVXLf1Orzpmjfh/3v6/zfuoRxWJE7LVv97uHE/AIkiOcipVNCzakXdUSBn2OOraHDNvsoYK4AzARAHgKiV7RkZ4IwQW7XrKmxl0Or5YubOiCGKEwBKo4HCIgGdgq0pT8FKGtnPA3JmmJlBkYUFrTCIXjpMW2sWRsZIOvVEYrGU1dpK3qYp4goIAWKoH4jELUDeKmltBa3Gpo500Cqn0WtWplcZM6k41/NUBVFAsbaypgFSSBSUmSNkpLJPQGk3TIiKHrOf3Yri5DvR4VIsDQzqOYIxuIpAU0IBdRWwNQa7gMpRKy4ALknQxmMja3Qp42tjiDEUthkES7LUx3c9a4zOUsOAOwBGr+x01HUlzgWUWeej3mTJf/p+qI4gKqEglCyFguOu042aXMgI2AVQWjIjIKUeHAI6sxnj7HMQAjA91aIdtGjCAjKLDMNqGzMXdxA7h2WhRb1gEhedD2izB2VxjTi2NUAKcOXeR81ciCRjNIsyGssS0J6z8ZxxD+GwY+VgJQBg/3D/mEcyiUkcXeFFYcs0bf8D5/8AHnfC48Y9jIc0lmo+mRmp7wuYMK9NgrscAECTtaMRl4dnLTfp+x5RLYwCULXOJKhfPUIoVlcpqXVVHtW2ZgCcex0fOXgQgAQkzlhQsDKlD25hl0UvmlJCD0bIWhykl2rA2EbMzBgOFwvo0p+L1dOor6gZ0SPK77n2oiVy7aLmsgXIw3x5jcEuRWOWDodtCoQ2LSCNC1uYTNesLHBomhGGmAAkvR6XAZhjQC42VYB42jIzUk5SXQ8D5XJPfHymxTS2korDhaJAafhg12Ss54jkgZ31plC0wrYZ8k5fJjMI909e1562QGmeAMBT+VSdo3Y/WKr9JC7V/IJCtTVtZgX7mpInYTD37durfss6R4B3c2MF9d7uNmcgSvFbE0VWkDVrYZkP2OYK6nwQxNpNNpO6zH0Nqd1ajI6JQwxAR7ank+MYoFa2mJmRAxdNMZkNlxSbOVAnczgonceMpbfPdpm7USu1pbEsAe1VW67Cdduuw48/+sfHPZQHHQZoJwztJCZxZMNsu5arNv31z3n9uIfwkIelIe0ZxZnRd70zlVYBTfrALxZZpeqfvNiLnbUzUGRpfS+cgvy8zx327c8YNIvYuy8IBdVbMRE56Kz9XA3TysM2KxEcMKdjn9HuVwrpgGwp14CknqkGht1ujOEP+bm5g4ixgeVda0aw1n+6tlEf/uLUoKBBMZ60jGUF41AQl10uUANkY89cu0wAKYg0O64Qo1yPjUvHT5byD5VVlJ7PrkMYVTmfAXQBthEyjYZcggJSwJtcUACjtCw2qYKBVpcUVHMSTM+p68k0sb3pem0uw+hGobbgsmLD2iFj6bzVvrQjOl2SZgZ2r81SbcTei8t9lXmr5Ais6tksqDJRAXe1BEcArmUkRCaA6rqkUC9XEuxDpO9Jzp+rNScvLaILd8AlZUvVgUFWf9nEMVtxmoLQkc93Kap0Rh8Agq3noLKSkm2pNwL2+fbd7QPEsgS07/rau/BHV/3RsgS00800AgXsX5wwtJOYxJGM5W7b9UgMAQMM0pQ5g6XlqD6oneVT79J5fd903+tDT4uSPN1fwI0Br6wP+hik0xhxwt79AX/9jh4zA3lw97081K3u3Wy/TE1pgCT1HZhZLK4gtkXzCnpWpKTsqQDjXLFJVjmPShtp118YqNGiJQd6Cgq85W1iZ2ntb2MsY4xSXCjqXTl+Eu2tAYYwwoYWZpVi9E2C/R1iqd5fCuiysueZGRHwNrM6ZAFZMSICnna2a+61FS+RyB1qQM3AiCVXiNGWQ2FcIVpct4WyjmoooMq0qF4kxYy+T/411CGiBsYG3AycG0NcM70WNdvrfyorMDtPbQPmc+g+xObmoMxnCIhEMJl04uSbOQ+9tqwbKHFEgG4QbD6yqTF08wEH8T7HDuyLpMH11zYnyvj3fcb2+w5gMN1hYX4eXZ+Rc8Vk247PgXZ1vQpCg24SzRuX7XsQTH9DkPdHtYobaTQCK+4cBeZ1LEtAu2Z6DYZpiPluHjPtzLiH86CCiPCaJ7wGTzr5SeMeyiQmcVRFExrMtrPLlqFd+dsr8QuX/wJ+82m/Oe6hPGRhDydLZebMGHYdGElT3eL0bi1oDyorNpOyamxLVyHBKNJ+1u24IJZdRKGASBByAvbsZexlIWeFFNRUbAWOQMUbFcyIMbhHqz1kD0QBQytSUmYroOfkWr8QBCAlVrYUrRdGlWAlNIsVlcxLBaC8AUDRrXKv4B2VhCAXZhBB5AGBg4MnASxyLgOeVlQVYoT1pUr6ezu22XKNgFYU3amBPme1DdixsXUFEBuIU7+IkkY2OQEqfWtWWYILKeSaR4q+SF9jEhQDa1yOG0MENYXZtgvoK9eCbH6yysDGGGX+KuBanAVI3SoKyDfP2+IOUXciy+55a6+3MdjmxZlIA/AmN2FjJ209sK6V5Oxn4qwet/o6Zf/NpVbaCtscQ8G8Y0lnte3fT3mP2LkdPNjhHe/8krfXTdyITpxLE4Ug+yBEHW8t+fDPkM6zyCAA4iLVsGsj+zmLttaK8iyTYJuSQ8WyBLTrZ9YDAHYv7F52gBYA/scz/se4hzCJSRx18fOX/zx+/vKfH/cwDjvm+/nCyj2iwh528tAadkNhZjkgqsaPFFjOkYHHAiRcBoCSRgWMHVOGlTNytsIcYHYm4xlPn8b0TMaddyzg81dbUVks5vNyEGW1FIhBHsSWTgcY+3UYK1JdMU+jfqT6ELdWtubVaulc0bjCwYlrVhXIebrVwBjk7xjiCBh0YGtWTDCLK6GNA0eZNgWe3jnLmDUWYO2mAgaMMaorPZTTAmdji0nvDesmQ4Cxa3ntqskAdlXNX2WTpYOZaEpdVwlhcmum1vyFCQTSDYfphW3e2FwF6oIu9Xn1fI6yldb+1sC4zZ3fG7/Ho9Zpdu8NxN5P1mEA3f7L5fV680eOV2tFrQ1sPUGmd7Vpo1D/utxXgmQLTAKQ9QYTiva4ZDmqJg3muABGbIDpFVk7uxGwwN6UpNiBGUBXT+jqXjpQ99HJf03SEQL53oBZ9NUB2lUvZSST0ADuTHGoWN6Adn43jl91/JhH8+BjmIY4MDzg1zGJSUzikR0GQh5ptl2l+KOA0DTsRGBngEfBXSTCnD4KV1oquJGiI6Kqbaql9iGFSBSE8ROvT0LOHWamGjzq7ADCARyzeoAvfGGILkVQA4BCVUldFbSAAfP6pyxdxIhwsBFINJszgASuCtUAw71adMbSCSmPgCA4uKn3MwZWsxZiGbj1oicalSjUAKoU1jASKkbLUvDK/gmQMDcBiZQTMpWirzqlXoOs+mc5VXrQmjl1prm8PoSgAF600RQInNjvs7WAdTBJIuCI2kiDc5Fj5JSRydheKTYSlwKCFVopvV+0sQq+c86ig7XrUlmIWUwlt2EDkDJiFODsAJ+osLtL13Rmty5bCmzLPecyD/At3f2PB/Y1JaCRAM7oU9JNC42sAVu7zNA1L4kDzkmK/Yic7bWsQLn/ld7VN0fAulUD/OiPXYFAGXv3zOEv/vJz6HPji4aqzyqjjFVkPLIRlAJB+CYv+3uptF3OMp7MjCZk/RroU/Yuc3Ux3tJYlrk5A4K75neNeSSHFy/9+5fiu97yXeMexiQmcVTFO294J/7dO/9d6VqzjMIK2parQ8ORC0Y3HI4ycpxdb2eSg1m3ilKWCpaKZ09PqigPmZNiAPV/hQBW0R5OIURtsauoInPRHwZlxhovAIK3dpVeWoREhAUizHJ22QJgOl4gJStqKql61iKnEuQFTKYNzfq1v0JT30v9VXMWJtdeAyqvpVCKnQRnmC4xVeMScOuWVVRQSk5JGz0k/R1GAFqw61Wg1vf9iGSijLmm66AaZeg9LK81HbTMgVg0pSzHTH0q/rWWTo+xsNR63JSSzFsFtmwcIiMIbp1VmkCoawAXiUjQyv7YiIY3qWTAgG7m4trgdly2SJh1/JV7QrX5cFZXx2yAv54Hv2dC6etbyKfbu3sZG55ZMxGsrh3VfEPArTtiQNvbVmDWm2SoRMBAtmm0G+oB7AV4ThFy2aSASH9UZUpGVrfpveWtpJ/tlJM0IDHNL0p2w7MgQT7XXUroU0Knn89DxbIEtE848Qm4+T/evGwtbjau2IgdB3eMexiTmMRRFddtuw5v++rbPCW7nMIAySOxoK0uiGIwFvshiDOQTSfI3mFpn97aWZUCMGvRiYJBz8qSafEsCyqaPAZDDp1ASNi7Tzp6ZZKXlIYHdnw5HxHQRGHPcy6aULCwjAdDwAoFYXXxU5bO9GBlq1LOaED3f+JDq9PdM1WBTkrglMEpi17TWUN2jae+3ZlBY/trxle8Zg10WQIapSlC6rXLVtHfeqrcAFc2Zwf7IynjQFahLvNs90PAMDtgLtemRV0s9xecwJxG0u/m72oISEhutfAy5wLRMwirGoP8MbBPMn/WgMH/qHY3GhAOohNlA/opoe/60sCCC4M6erd0PgyYc9H1hhBAUUG8riUD2iYBcFcIvd6inU7IXFob15sLqhEq+arRr0nvZ3F/CLp+TURg+/ygzgKZMxCCOID4VZGvG3PMkPOL9ANI+lGi8hbYpkRXhq9/1WCTjp/JNzKkn4nSwlhf75suZWsBd4xIqUfXd0ef5GB2MIsz15857mEcdmxcsRHb57bfL4UziUlM4vDDUrLL8TNFRPjZx/4sHnv8Y8c9lDFESakyZ3R9h2SpTy4MVAajC4QhAbMpKYC1Ih44awdL7ZKlU8sD23SlFBqEMIWVqxawb98A4AggA5m8ElyYrew6v3bQolMDfyKI6T0BQMBcFEALJiNC9XqMGC3I2FvbenKWyovZqsCNCYazbiDyh7mlug1EQbWHTlczBEznAm6jtkWlIIxbVJusnnvVl7IDyxCjs3Ze3KVgx7qNhQqUMXMpDlP/XTCQsjQMyMG6RSlzrPc76+XbpsXkAsa41q83MJyhDG5KAsJDQE72Wvs7gimLlAHkLGDmjIwydmHgo3rCKijMco9zn6RwSldPYXijODqwsvlZtKfeHU03BIGo0vdKJAX5knKXM0ZLxdt6IKv+z54RGAkyJwJrbazMaC7sKAVN9webZwHNwTdp8toYbGsi9yDAwKadytj4jKyNF8BTKh8Y7dYnn1D4ejAXBkAAtBWLEZk9HhAhRYuJRc8t1yXHrLukhUDIicE5jWQtlsayBLR97vFHn/sjXH7i5bji5CvGPZwHHcesOAZd7rB/uB+rp1aPeziTmMRREZnzsmU4B3GAP33On457GA95WDq4LuqyJgd9ys4meR/4nDAXAla4TjALeDGWF3DdphymVK2bPVGkgD17E/7X/9kh1kOckHKDQIzAURjFELyFK2dpKABIswYBD0l1iaKpPBAjVlXdqgCAEFCyuEZeMDIn6fAEFHDBqFLTIlOgEB34gsRflRoF/ikJC4oCBH2eqnR1hqSenXFUNrDnjECNgFuVJjSmYU2SfjdGNQAO+Nw+SQGTedDmlDU1nEGRXCcbWMF2xcCzFl3VhU5EpbGFmtOiN4cEY4lzKvrfKONJzhQqc51G9cm2brwTWi73I6WkOmjAGjmEKGIScTlQZljPXzsXRC1KM/cIe43uQGTjojeYiNCY+4GuQSv+ClTsz2QuzAargEVnTeVClUg13YGse/MLJgY4wIshAbGW622PlhmxKYl5+9zZGLM2NbHiPduI7dq5iLe+9VNoBwTmFeiGWhRG9qlDaV5CZb0bC9/EqEM3KQOPNGIgyCbF1jFgLhYCuqcGU8L0qvTkgbJwyxLQRor45Y/9Mv7zE//zsgS0G1dsBADsOLhjAmgnMYkjFFbZvRyDmTFMQzShWbag/HCCjE4k0+5BmBgmr7QnZZdIQdVcCFiZ7T1UQB8DIRqjBGXCjO1hRBIGkYnR98COnVLUQgqOyBwIlIUkqorKVM4QYxRmEAF96hEpIIOxJ0as6ZNqCoUVDqF4cEqRUgZTroqPzGxerjM2DZqmQer0uClrKry0riWS1HpTpe+d0cos7WUNFBAcWDZNY+hBX09uc8WZtRgxIRDc1SFZ+9mgzgjlpklBWQVcWIEZVCphrzPA7K4AKbuLBHFxdLDGAgaSAJlrzlmYUm10kFLWr8txAwU05sEKkta+mnpPCr6LJ23wr1NKnurv+6Jx9rGTeLsSByROpRiJa0aUy+eVMJI+l80Vq4RCwaUy2lT51LqFWSUrkLXOfh9riy8VGmBhccEHm1JG32kqngiUCU3TejcyZtmkNLFB3/UITXQQ23cdhn2PmNRRQyUZbIVnISD1GXdvy2jbFuAhEAhd36lEQsY3aFpndJNpwUn9j7OsQc7iM03ZNLQZfd9jamoKfUo4eHBerPGYMRgMECMhRiDGgBimAAD9cHF0PVaxLAEtEWHT7Cbcd+C+cQ/lsOKy4y/D7zz9dyZgdhKTOIKxcrASx608btzDOKzYP9yPNb+7Bn/wjD/Aa574mnEP5yGJlHp8+YtfwNOvfJIyYQEpAFc+4bH48Ec+jr3798vD1P08pYXqgRCwKmcFi1pdT1qVThFNjBgOh2jbBjEG9H1C13eI1OqDskXijMXhIkCEqWl5UOaU0bQtFucXNDUsrN9gMFCA0SL1Qwy7DsNhByJC2w6QUsLuGHDC4iK64dCLnEKIaBrRaeaUsHLFLJ5w+aNBIJxy/Ca01CnwBsAdIjK6xUXEEJGZ0fUdKAKoGT59PSviyqotHgzkGrq+R6dgPFJA27QAGIvDIfquR9u2IGoK8FKPV0tPN00DhjQgiI1IFIKCP6JSYT41mEJWMGLsZNM0yMQY9r0ya1EL1rLLECyLErSZgjHoWdsN5yxeqitWTGMwGAigjcn1raZ1FekoSUczcgSMnLPMubLN6HsBnGSpcTMdNmlCCwoi5eAML5wS1jpq0w+TQaBcV8oIDcnaBJzJjTEitLJhMQbS9KW+ySJC5loqUlL7MsbiUOFylyYip77aAAJrVq/GcDgvdmgqbQkx+iZouCifF+SErJuDHj0oEBYWhmhiI5kGLb4jCGtta1sGA8zMrAA0s9F3HRYWhroBAGLbIARpmTt/8CBsI5ezuFLEJgI54ODigkpIjK3PSAx0/RAHDsxhbv4gANsgDSRD03X4+te+hpNPOtUL1kgFJA8kK1uWgBYANq/cjHsP3DvuYRxWnH/s+Tj/2PPHPYxJTOKoil95yq/gV57yK+MexmFFrUV7pETX9bjhK1/BC572JHCQrHGOAU+67DH44tVfwr4DB5yFa9UaK+eMPSFgbZ9ADIRGmMKmaTBUMEkgNJEwaBvpnNUPMdVGhCByhpw6+V0zBRBhcXFYGMTco4ni79p1olHs+6GwSrOzAIDhcAF9l0EISAqY9sSAtSmDiD1LEAjo+w4zM1NAbDB/cA7cJzzlyU9CEyOIRIvKfUbIPS4+/yw886lPFEDAWtWujGKfMrquw759c1gc9g5mF4dDzM/PY7g4xMLiIg7OSy+1+fl5gBnnnXcecu5x77334Z577sHU1BS23HMP5ucXkAHMrJhBl3r0vaTzu6530DjVTIM5YzjsnKFOSQDj4uLQwR2FAlaHXSesJhHmFxYQSJjs6ekZ0eWysN1916NpRCqS+uQbF+YMtA261KFtGmGRSYGrdbSyn4EQqs+Nge4YYwG7QVwNZOOTQSSQJ/VJ1o41OWiDM64IylCCEYKJoYHMHdq2RWCp6G9iI17B2oUt9VbYWVhOua4E8yY2aUwy5hXS+GMwaP06bJ1LBJijwOLCfHGsAGPVylnk1KPvFgFEEEVw1yEEbU6RRVoCZYH71IOSWI1J9iGDk4BOTgld6qVVrjLDonENGC7Mg5FdGsHJ7ONkHjuINETuH4PUjyv3CV0vAoMR3SuJfCTlhPnFeWmKwRms9nvzC7KGQwj4xi3fwBP270PUTQoBWFwcPuC/KcsW0B636jhs2bdl3MM4rGBm3Ln3TrSxXZY+upOYxCSObLgO7QG0YUdjWGGLyAXIH/o5J+lY1TTyME4JHIVlW1xcxO4YcM5ih5QT0jBjamrg+lMDwMPhcCTVLcyitnJVjayxZSEwAkWgMnnv+9EuT23bul60bVqAtQBRi512EWF1zmgBdARlZiWVbqwmhYBPfOZzYGZc8cTLMTUYqObVvD8Za9evksp506sq6IFqTVetXoWsbg0K6VSyYHpG/VKJPNMzXHj+eRAGlHH3vfdh167duPqLX8K27du1a1lGbx3SlGnsOgEOg7ZFbLQQCgK2c0pIfUJKwsSllIQhDMLiWevUjIymadH3nd8PcWZg94FtplswZ8TMyvgC88MhjNUEdMNXSVAE5Ms9FVBN4uev68gAYYxW1CaAbNCWxgGAuYsI8900jXSpYwZScYYAyVwPu06ZYr1fUdrvknq7coQXniUFcL022yD10jW9NwW59r7r3QFB1lOxOIuxUfuxWm5wqM2v+c9mnVeAooBekxxk18MSosprTe4QOKBpG3TGzOpLA0njheL1m7F2TYS4ORP2HgBSL9KgpIWEpumVlcfeHMM8fGHyIRYf2mSFYy510feqoD6MyK+sFfUDx/IFtCuPw9V3Xz3uYRx2POqNj8JPPPon8LpnvW7cQ5nEJI6KeNMX34SP3/5x/M2L/2bcQ3nQ8UhkaEGEqbZF9vSvAJiFLmFhOPTCpMFggMwZbdNg5aqVOHDgINbNL2BqSoqactKWolqBToEwQzNo21bY3bYtHpta0JMBbD6GcOFZBKIOt9wxi1vu7J1tFC/SxlPiABwoEREGU42mr+Whva+VR+k6ALsHlScpSvoYAUiZ8fFPfw7zi4t46pOfhKl2AABo2hYxNlIVH6zwx82NBGyzFK0xSpU4gdQWyae0nl59L/QFIis45eQTccrJJ+Giiy7C7bffjvu2bsXXb7wR923brm19yZlFAyQ2xykl0V0qELHrNAlBYEI7MJZRPXJTL2xm5avbtq2PSVwfdOMCAeMNNWXcmus3pwOrm4o6RkCYQjBcL2u2VMSkDSQaEFjtybI7FvS5E9CZDYABQCMpcfXgjQ0h6TpiACnJPe978fKV4wCBImKr4J3Y9xOi7S+uBNbpzDZEMURnhwmMvpd2sxyEETUv5NojOLOwzwENmKzRAPvvQi5OEbZW1JysuCaE0lp2ajBAbsQmzth4ZkZWzTkDaBrGD7xogJUrF9F103jL385h194AuOWtbMCC3qDeatYouL7ZZBRy53VDJvJy1SOQyhsIjAR3NtONWwZbndohY9kC2t9/xu/jj5/1x+MexmEFEeGk1Sfhrn13jXsok5jEURPXbr0WH7rlQ+MexmHFI5GhlagN3AEpcOk1PWztY7VFa86gGLEnBKxOGRFKZqLoDvWQ/uCvO2nZY9eq/U8/dYDLH70fMU5hoQ+45S71iq2rrbWIqhQElSIetzQKhN3Kqq0aDrFDNYSjoNaquQW4f/HL12G4OMR3PeVJWL1qtQDGPgMsxUDCCpbZoQrYmQZUiW3FfQYpbD5sTsVOiew4PtEECowzzjgVp512Ki695CIMux5fve6ruO3OO7Fr9x7s3r2nMG7KXjdNgxACpqem9cpEt9n3vcsk+l40ktbEICW13FLQ4sVsWbpvBQqgWFwgLHWfVVtr5v920X6vFXSZVMGcCMybN6heVlhSG0PxorXGGIFkE9R3HQjCVgaKSNqQw4B50KLC2Kj2NzFIGVfOjESQlrKBEGKrG5mESI23qU16/pBJXkvit5tzHtk4pZyQOm2AUGUaSggQDhRUlmEZD9m0GcMpU8amWtBvZUskxZfC6vaqezZW1xjuDAbFqELvhNgm7N7VY826Hg0JV5s4++eLbF1agWetcdaNa84JpogFrHCSR9eubhRbmeyKqT9KGdo102vGPYR/U5y0ZgJoJzGJIxnSHnV5OgRMN9P45St+GY894RHkQ8uMpmlh1eWsD64+GTNlrCrU3F+A4q4oUGRln3BA5QaAgK2axXLroGztV0t1PIGxa9cQqR+CkYEkhTpAVG0nvOOYpbOB0lTBUDhBQMouBbRr++TgQ5jeqLpETbVSQKeA7Zprr8fCwgKeduWTMbtiVgqjgh5cU+cKmR2EsjOyloKvBlK+AwAE1R4YGLZjsb1PLayIGDMzKzAzA1xxxZNwBT0Je/fuxc4du3DPvffhq9dfj2HfY/++/XJNMcpGglktzcxeCw6QzOIL5oKgDR+CgjhpYStaUmvNWwMfk56UtSLXbF3U7PXCvgakpE0sVMPJbIVdom1lYMQnl0BIfa8tWWXdBFFCePGZgOOi482ppNObJoBDQAwNKCck8VNApz6zUQu+rFkGtBjOCuAoA10aqhRBGHlvkqH3s88J4Azqh0ipG50KCKhOKE4WBBYbMr1uo4it9S1I2tgGBqDd96CAvVcds7zDd4lwf11OIM4IDBx77BSGfZFuxBi9O6PDbiLvBsYsNmvygowY1feWZOyBxV4uwSzUnKhFExvfjJk05JvFsgW0N++8GW+8+o34j4//jzh93enjHs6DjpNWn7Rs2aRJTOLhGCmnZWvbtaJdgd9++m+PexgPeaxZvwHzw044SAUyO3ftwcG5g0hZ0tuckvuOghl79cG/JmXs0UYDZq0VtdLdvq7ZLXMKsKryXbsPYmHYYyZGtLQIwoyAWKi9FEa1m1Zdz9kM8E3HSdhtYxp26KcGsPapVuGetJlCDIWBy4lx/Y3fwIH5OXz3lVfivm1bMfzyPEDAoB0gxoCZmRVYvXo1Vq9ZK8bzITijVch8+8KKecQ7VjxqJY1ubG3NkFq3J1KEVLPA69avx7r163HmWWfgqU99Cnbt2o1rv/pVHJibwzXXfAkBOq+aEzZPV+bgmwgBrqINTZzcC1acCBowZZdEGLCzBg7ekhbwYiNWyUMx2w+uAzWgasxvGZrasen8w3XToZyDS3c0AXiFLU16rBgbEMHBcdd3cgsaUuAbwBSko5sBa6gUIsIBdmZxgwgM5GEGI7te2+hNAddRe8wJC1oIWrb/A5HAAaAMILN3Sqsbw7p/M6r3A2KdJl8o4FZ7ODa/YFkb3oIW5PIbxhAxzvoqA0UEBGFqdRWKrCEgIKNGoe4LLdtIH2kgcvu58m941g1vvc65etf9Y9kC2r2Le/FHV/0RnnrqU5cloD1x9Ym4d/+9Us0Z23EPZxKTWPYh/5AuT0CbOWPX/C6sHKzEdDM97uE8ZJFSwuJi8kw6iLB//5xqNEV7Z1ZKlrLcpQ/I1cOEMD0lEgV9XQ1qRZ9p1e3BgZGY2TMO7A8Y9oxpjmhiQgyM3OsjmdkZWhC86MkruYmAlACW4rJ7FQBs7DMyE3ICGiLRRJAdx9wL2NmwPmXcctsW3HnX34JVIyrAWx7mBv6sY1dOGcEKbBTEAcDU1EAcBgwYKAOawQiRsOnYY3DJxZdgzZrVOPGEE8A5AUHBLJPPbS1LcJaTgI0b1+OpVz4Zqe9x5RVXYGFhEVdddRW279iBO++6E6RsW9f1MqZQGNYQoqf+ZZNBIyyosMS6IFi0sQGkvRI0na/XA5DfF6m8TwhcmkkYy9v1CX3OiBAWWYqxVG6gjJ8xhFBJCQNomwaxabxYyZjHzFkaLmgBWN9LgRiSbATEj1Y2O01sBHblDEJE1/UgYgy7TrMSkkYPA3VcUL9hZmlzHEm7eeWM2AxEHkGhYuXly6iSCpJqONlAoDSB0FeqzICkC17hctWKzFhPa2hgx2dvKkIqLaDQ4ubbMtaszch5EYudNOdI2eRSAJh9Y2GNPhyAsklghJVVaC0bqyy2YHYk5gwOhNg2Ks0Y7Ur2QLFsAe0pa04BANy+5/bxDuQw48XnvRjnbDjHPzCTmMQk/m1x7Oyxy3JzC0iTlU1/sAmvf/br8R8e9x/GPZyHLCz7XXMuUduuAhh5iBnA2NPIY2u9SQKMdcxcpW01dclJbaRQ/VyAUdc3yHkGIQIbNwe0LUFqixQcAa6jlYYK2f+2AbL6p+4MAR2AY/oe0Ae5uSiYDlcvxBlC69IEJgy7rGA0Y3FxiNhEzC8sOmA1NwWbn5SSZyTaQYv9B/Zrxb02AzAdLwL6lLBnzz7cdPOtmJ2dxbHHbsQxGzbgsZddhrZtsWr1Kr9eZ3F1rKz6CmO1m6bBmjWrsWYt8KIXvgAHDszh1ltvxcc+/gns3LkTRh8SAU3TSsczkvFH1awC5N2qjBEMvmlRxrNpinNBCKqXFvATILIAsMx/pqLTlG5f0Zn0ZG1/Qe4wYB3OfGNhLKR6+sKBPPnrmNkdC0zaEmMDgmp0GeJ6YPdc73GIAdwV1jZ7QwVTkZRNjBXaZTBy34m0IPXWOE3z8CVdH2PUYrNynPpzQyTSA+k/Qv45EpBrAhRb5/B7rci0fLYAJJVcfOJTQGbxSeY8BXFuKPKSooM1Zrc6C418B3XnlXUWyibNNp0gKcRzaE5HsYZ244qNWNGuwB177xj3UA4rLt58MS7efPG4hzGJSRw18VtP+61xD+Gw45HqclBafRplYyyhAjlSYWOl19urnrRr+iGIVqgGsHegh2A6UUkVV89SAZLlG3z1pgjOBzF3cAVS34B5EUZaGpghiAQh5QTOAlQFkGpxmD6Mt8eIY/ukbG52UGOAzU366zlgcT4AEfqcELVTVuoTBoMB+r53p4GeezRNg67r0HWdeKVGYeTaQQRz8FaqAIMC0HVDdH12/XC3dy/27N2LW265Ddd86VpMTU/hkosvwuzMNC648AKsXr3a0+91EwLvCKapbUOtK1evxEUXX4jzz38UPv/5z+MLX7wG92zdLlrjzNLylOwwCrqU+TNwZ22GpSsbFSs3sCamhYE07W9QOzS5r0GPU9rSCkekHcK0GYAwq8Zql6I0ZlZPYEJQoNp1nbsg1BumLnXKdgp4E6cGoFEYlbKwzqkuUFMWmDQrwCSgNKWhd74TK7NW2PKoOnLVWfeafWCu9MT6KREJQwKr72vS60MI2q6YAVgBlngGu6ZZ5Q3WtETmtGJSUdaASzyI0MQOgQK6HLA4LFpmIkLuVTutn23JsJjUQlG5zkMAkExlgZIJkc5oDCAgUETbNMWVAcIoAw/8b+SyBbREhFPWnLJsGdrMGVdtuQrrZ9bjnI3njHs4k5jEJMYYj1SXg5RTATya9nbPSmbEVuUDXIz1dyigPabSVBqoNHYO0IITLZhh1UJKYYxoNxNlfOLzhJSnEHpCpg6AFM6I16qA2KjVQmaKz1oMBVJ7KO2WtTUGHNtbUVCpqjems2hLJeVO9jNmTSuTywmapkHf9wBBvFlVPmEAeWp6Sj1SAbAAbiJgseuQDASrFlKAmelGtXq8abR5xBBXXX0VYoz41Oc+h9nZlXj84x+HdWvX4YTjjsOa1atGKtUpBsQmuPbUGec24AlPuBwXXngBrrvha3jve98PDkCfe5WBNMVejM3jVcZonq3GztWMsMyZ/Vq/T4BB5OIkUdhecSQgB+a2nqz7m3mzFtmHFLUFBbYuW1BgG1Rm0DaNrLMkTG7KxTs2hoDcMayLlW2wuq4DgR0wxtgCyIhQTW4S2UTXdVoEJRuaoP65xJBGBoeQUtmmKmuHM18fWdsry25LGV1SpwP9FybLJiHGKPNuHcwM4Opn0bumgQHM4/tfPIW1K3vksAp/87dz2L03yKaDi6a53A+oFzNc9xtg12assUlFkt//2mquaVvdGJpTiNmYHfrfk2ULaAHg1LWnYt/ivnEP47CCQHjGW5+Bf//ofz/xop3EJI5A/MFn/gCf2/I5vOOl7xj3UB50PBIZWgIwvzBfiksgwL4ZtBgMGiwOxcJLtKsJEVLktUCMvTHgmE4q7s3iyyuyibyoq1cWMOek6dfiCxubgKlAOGbDAi68YAU++bkF7JsT4BFAQBNBSR6e2VQGyrqapk8YX/l6WxNxetdrqrl0dDKEXVwL9PoVaHl9DptRP2FxcbF0sSKRG7Rt6y1nU9J2vkFAU2zgoK3RdL35mwpoNn9dbTSQE/p+CNi1UUJKC9i/fw7/9I/vx2BqCsdt3ozZ2VmcddaZOOPM0zHVtpidnVVdrmw0iIteM8SI2ZUr8ZhLLwEz8OEPfxTDPngqmlJS/SZEKxojktp7AcHb8BIBCwvz3gwhKVg35tmkGjUoNTa1aF+liCy0rZvze7EXl4K4It/Qa6mKCW2zlHOW15NuDogQOEhjCc4ILPZXpgkOIbj3cdd1YEinN2kPrEwrBZFAoHOj2JR6ABGUrXCuVUY7CDCtwDZDNkCipUUF8IrkAQiVbtZ8e0vBW7FyI7U55qLP1k0FAiETA5zRUMCKGcbUNIGp1/NYlqLYsjEET3NylaxvLkxOELjIMpxZhxWEsbP5TdsUmYRh41qftCSWNaB938vep7vn5RUfv/3j+B+f/h+Y6+Zw484bxz2cSUziqIgbd9yIz2757LiHcVjxcGNoiegkAP8XwCbI8/NNzPzHRLQewN8BOBXA7QBeysy7SZ46fwzgOQAOAnglM1/zzc7BLB29XLunfxkrZoxTrsA+a9HJ9qbBscpEJgWvYEZn9kOsFkV2HEsfBwEjpn095/S9eO4zGoC24+ovEQ7Mr5SCKiKQeckShHnLwX1va2suA65bY8TlC4sOrAAoM1cALWu3MQFmqvNVkNYEAVJ9kuuKTYTDEVVdLC4u+ryIU0L2wq2mCe7kQIG0SCwoVWbnyUAWgN82kvIWTWhADDJPkQL6YYd7770XKWd87WtfBxFh8+ZNOPfcc7B+w3pccOEFaJW5tq5gRKJ1DSHg8sddhtnpabz9Xf8gc+n3D87mDYdDb95QypWKxRdnue5iu5a82YYVK1G1TtzmzaZLwagV1nlhkTGBFaj1+1OhJQPJpn21YwICDq27FkPWXRHGFplBE6P6GLNLN7I1UWgDAJKGDaliMjOrJ3GvcoQ4ynzqigpUtKluf6U6YHHkCM5GszHjDIACMrKzvpZFKDr1YqMmt0vujui4WWUettliZdAJHArDSgHFCaNWCRjTD3FHtvNY8Rh7x8AiMVq6yf9me/5lDWiXI5gFgHd97V34wDc+AAD4wDc+gJf+/Uvxk4/5STz99KePeWSTmMQkxhGrBqvw20/7bTzuhMeNeygWPYDXMPM1RLQKwBeJ6CMAXgngY8z8u0T0SwB+CcB/AfBsAGfpn8cD+F/69wMHkbT+hKRuLQVpVeDyGktlKnvbiBXU9ibimK5X3aIwfmZb5KlwPY1UXdfm7wSKjBAS+jSD2CQgt9h0LGH7HmWnrBgIDGSg77ICUAMLVKQLfY8Lhh1O6jqsyYxBn7BoFkqZQVQAGoMBa52qBUvGRKKBs3sGBJj0fKZlVbcHcEar7JUBOWEDdWukRGCfhElrgjB/REBoCECDtmkcLAJijZZyh94AikopjNHdtn07duzYgcFggH/9109hzZrVePzlj8epp5yCGe145kxbCLjgwvPR5YR//Md/xLDrHYRlZTTbwQCNNhrw61U9NAXrUJVFN2kFRzUoBaSQK2dtywtnY6kGp1wKnJyhVvlBcXIglwjIYUsr5agtXe14BpJbTYebPMSOZZsZa2cbm+hgWv4WuUn2MZBoWyGSk8wZLbVyL1MSgMpFmuPQlgI4C/NpdYoCN1WmE4RZDbZxYnMdgP8dTIag85mVnc3MWnDGAJPKWxKABnNzC5hZIecPADLJ/SRAdMGUVUKkhX5yEwqzSkpKu9xGf6EuDmTjc/2xfC/jh3+ODxXLGtBet/U6/Ponfh2//bTfXlY61D9+1h/jxx/943j+256PO/feiU/e8Uk8+8xnAwBu2H4DfvgffhiXbLoE5248F2esPwNnrDsD52w850HZ+aScsHdxL/Ys7MGehT248NgL0cYW1229Dtfcew0SSzqljS2m4hS+99zvxXQzja0HtuJgdxAbVmzAqsGqR1QKdBKTGFesmlqFX37yL497GB7MfC+Ae/Xr/UT0NQAnAPheAE/Vl70FwMchgPZ7Afxflqf+54hoLREdp8d5UNE0rbYZVXYKQO56xAqAbWsbPO7AQWfQKJDaJRXgGIIVJHH1AA/oe+lZz9SgRwtCAhrCmaetwHVf3y8Ak7OAWh2Ts4sFTsBsxUII+Kdtu/znv7F7L/5yzSrcPGjV3F8fxhHehczCWqg26tzg+ssQhYFVIB5jlPax5rka2LWfVjyWsxZTVeCJTPtJhKlB613PRL+pBWyqAe26oYL4oECscY/SOBj45mFxcRELCwvYtWsX7rjjdpx//vl4zjOfhdmZGQEhRMgUEALj0osvBjLjIx/9GA4uLMicARgOOwGMIqYsG44AxEaaUdgmxv5bNLW5sK0oUouaca3lGrVTAeeM0DSlgBBAUjDatK2foy4as3UQ1RGh1tjmnBFSca4gkLsuZAPrfSUFIQG4MJa2OlYIAVGvSVL/Cu5itf6qx3GIwQummFmKIbMWz6nmNKvMhU3LqusDDm6LywFB9MbSNcwkANrMQ/QH2L1vFsgtproVSLlDRh4ZFAGwqks5hqt27bSOyqUWsvwO/hmzJjnGulMFahMeCMwC3wagJaK/BPA8ANuY+YJD/P5Bp5qOVCROeNfX3oWXXfCyZQVoiQgXbboIr7781fj5D/08PvzDH8YFx8rULvaL2LhiI/7x5n/EX375L/09H/3hj+Lppz8d77vxfXjNh1+DdTPrRjw33/LCt+DsDWfjz6/5c7z6Q6/G/uH+kXPe/p9uxylrT8F7b3wvXvsvr73fmHb+/3ZiupnG6z73Ovzep38PALBysBInrDoBJ6w+Ae972fuwol2BG3fcCAbjrPVnLVuGfBKTeLhFn3vctfcubFyxEaumVo17OCNBRKcCuBTAVQA2VSD1PogkARCwW7c+3KI/+6aAtu/ECkmegfI0a1ppmSq2RAFd3yEE0vS0PGi3xoCNfQJlBkXt884ZMQRQq9ZagKav1Wg/Crvr6eg+Y9hN4+DiALEZYP/cHFLO6pMKAKWgyJKvKYv2VX4LEEk6+IWbNuDdW3cCAL5/bh7fPzePLU3EVdNT+ML0FK6fmcatgxa5AkwES3ObVRk5MLO/2xixngLWAKCuA7pFpBCwAMZCDNgfgredNWBqzHKMpqGVnw+HQwFeCpa6Xr6Hvj6zdLgKMaJtB8L49j2apsXicOigcDAQO67ci+byK1+5Fvv27sdLX/pSzK4opIsVFz3m0Y9GjA0+8MEPYe7gQXF1yMroKSPXa4OMlBJijJiaGug8BYTY+P0UYMPuNWx6UXs/APciBuAMK5Ew6YzKvcLuhf7ONLNW3OS6XGVkSS2kbINhLO/SorIQgoPXwoBXGwiSzZew7AMwGCmKDZnJSBpu/NrkOWuwE8rcC8CjELzgrO97ZVxNomP4gDVpIRQvgdzz1XXhytQaU27FXMwC5BkZKUW86137wCDEMERicocF2LVy6eZlcpicPb1gJ7S/pNGFn8vYWvk+5Sxd3VQ/LLpe+/rQ8e0wtG8G8HqInupQ8eBTTUcozlx/JgDpGrYc44cu+iFsnduKczee6+D00uMuxYd+SDqI7VnYg1t23YJbdt+CCzddCABYO70Wjz7u0dizsMcXLlC6a5y78Vz86KU/inXT67B2ei3WTq/Fupl12LBiAwDgZx77M3jZhS9D1L7UXeqwmBaxZmoNAOAHL/hBnLPhHOw4uAN3778bd++/G3sW9mCmmQEA/MYnfwN/c93fYKaZwYWbLsQlmy7Bk05+El5x8SsemkmbxCQeIE5ec7JvDJdb3L3vbpz+J6fjL17wF/jRS3903MPxIKKVAN4J4OeZeV/9MGFmJiJ+wDcf+ng/AeAnAAVxYenDiRFDBGkBSx4uIoZYqtNDRE4JO9oBWgDrM2MniXE+gbxQSdLS1plK7aAUTDiTFyK2bsv4P//vIEBTmFsYolEWWAqW+oIhNO1rBfkOpgQd40ttg99bPYv/sm8OV0+1+IfZFbhyYRFPPbiAFx84CADoANzVNri3idgaBIzOBULKjEGIWAXGBmas7XqsSwnrU8balL7pQzoB2BMjtrURW9oGd7UNbp0e4MaZadzUJHAUTa11tgKVgrmov4tNlDlHKXQbdoswbXBKvcsibH4YGVNTU4DqJO+8awve/va/x0u+//uwcnZ2hKljZlxwwflYtWolPvSRj+C++7ZhcTGhidElEoPBoAKixeJMfFe175myikSlsEnXlINWY6pLtX7FHoYAyibzSLoGBMBDAehwcXEE1JocwTYZQClEyzljMBiULMESYO16W5UsGPBmZiTSznGAjzO2DThlsWJjVpcLUh2xFLLpLQQUzHIQRpZTD3MbMPDn7CaokvBUtlrQQi1d5NIIQn5mvGtUhl461Al7D5KNnfnfKpWux5LPsGwUbF70Y8S2EVzK6JrUgEQDgaK/jU0pCrN7PTU1PeJuUce3BLTM/EndoT9QHLFU04ONlYOVOH7V8bhp103f6VN9R2LDig3ftN3l2um1eMzxj8Fjjn+M/+zJpzwZTz7lyQ/4nitOvgJXnHzFA/5+3cw6rJtZ94C/v2TzJbhk8yUP+Pv/esV/xTNOfwa+ct9X8JWtX8Hbb3g7Pn/P5x3Q/tYnfwvrZ9bju0//bpy1/qyJZGESD1n86pW/Ou4hHHY83IrCAICIWgiY/Wtmfpf+eKv9+05ExwHYpj+/G8BJ1dtP1J+NBDO/CcCbAGBqMOAQgzwkUR5uUfWnDiRy8qIuzglEjG3Kkh6beuxqBu5z6YwjywM6mLk8BNCkZKBJoNSwZww7sbVKHIoG0rSEBoAYOs5cX4uDBSLgL9asxHPnF/GH69bg6ukpvH3NKoAZZ/QJj+p7nL0wxKl9j81dj8d3Q6zMGbOqMUwA5gNhd2ywKwbc3ja4ZipiTxuxt22xP0R0YHAIoJQwg4zpnLE2MdanHsd2CacvdrjywEEMFOsNCfjq9BSumZ3BF1euwOdnBsihEbZbRZekjF3XS5exxBmcShtpCoWNbNuIEG0z0LhHrulAb7v9drztb/4OL3vZy7ByZloZRgU7AE499WQ8/7nPwT//y8dx2223o0usutosLWLJGGu1n5JZLsSNShBKlb5EUCZTQHp09jszY3E4VDu0wp4aUM05I7mtGmshXjOig7UwxtUAM3B/plfGUlr4OkBX/W8kKQAzz91aCkEkRYgAinRBHS9STmoRhup5agy/jQOqQy8AWTG0zJVvAKouYlSOZLpkkzY4hCRUlngZT7isxfT0ACEEfPKzC5ibX5RNBwnoduxs4+H7n49MQoBi9WXFbRnaaUxlQvLvQHEVqef6UHEkNLSHlWo6UnHW+rNw087lCWiXY5x/7Pk4/9jz/fvMGTsO7gAg/xj97Vf/Ftdvvx6A2Kq94OwX4Icu+iE89oTHjmW8k5jEcgh/SD9MNoAqJfsLAF9j5v9Z/eq9AH4EwO/q3++pfv6zRPS3kAzd3m+H1DBJnacgoUyaWXABop3VlG4IAhZ2TEsR0qY+4caZIJpETZkDVkNNhfnRB78V3QDCPuWcEGODs04mnHLaKlx//V7cvsUqvs27lhSAsIMEVsBbdJCERQKed9wxkn52L1Dg1kGL2wYtPrBytrTTBZyZKg0XCDPT087iWdo7qu+u2VqlvkeIyhTWWlIwIoDTM3D2/AIedXABj5lfxI/s2IMf37EH84Hw+ZUr8JFVK/CxVbNYGLTCYpMANqf/dHixEclHnzqEaEVsQE6ipwxR55ngoPaO2+/AX//13+ClL/k+rF+3FoQAI/Fzzjj++OPxfS98Id75D+/GN269Hd1wCFbmt1fHg5xZGmIYM6lSgLLRYK3SVxAZyoYoxKhFZQL8paBKZAOmUzZHBAOd7mXsek5yP1c7LzN7C2JjIke0u8ommn9sUIaViNApa2tyB9fbhnLvbCzWjU6yF+pva2tsyb8NpA4cSwG+AVPb4NnnyzyZoYA16LrNOu+swNucOVg/c7IWCU07xPnnN1i9cog+TeNzX0yYm68lDjZ/wuj2Xe8SBkRyllr4/fo6jHlWRp0Ba8esl/Nt/7v4kBaF1emmk08++Ygc89LNly5bhvZoiEABx84eC0AW3XU/fR1u3X0rPnLrR/D+m9+PP/vin2HdzDo89oTHYpiG+NK9X8LjTnjcw+bBPYmjJ37rk7+FT9/1aXzg5R8Y91AedDwMGdonAfhhANcR0Zf1Z/8VAmTfTkQ/BuAOAC/V370fUkfxDUgtxau+nZOU1GHRzlmZiheIKOzNOaFpWjCAe6MwaMcP9aGprJAAjcKcQYt6AH24q4UXjMGNAbODfXju96zH1EyPJrTYcl8WGyZlGMVcnmAZYGHoqGRbtQtXjNK1ymsb9AHOnBFio/rc0jSCFFQJ0yYX2/XSKtasq3LO4I4djDjrV3VMqrWaORBuHzS4tY344KpZAMB0Tnjc/BBPPnAQT9l/EFfum8Ov0Q58avUs3rV+DT4zOwMatN7alVm6Z5m+OcRRr9emiZJudmmHFPKZ+8OWLXfhHe98J571zGfi5JNPhFTDy1hzylixYgXOPvNM3PyNWyWlnBNSsqYADKbkulADsDVjWG8KvNjL0vv6ta+rqoCs1rN6wwRjat2vuGJJ9XrtntVOBiZzqN9vgHWgHrQmg6iL2ETnKlKBmqEMJF7DGSKXYJVNFAZT11MVZU6Kt7IBWfscRJgMQD5JhOC+t7ANX7UpsvUlxw3+iYxkzKp6+qYAygHE/mn1Z3ot6TAdtWBUcuZcXoiKzi2bTynopKK9rda5Hf+B4kgA2m8r1aQD8XTTZZdd9qC0Vw8Uk6YED68gInFmWH8Gfuqyn8LccA7DNAQAvP/m9+NFf/cinLPhHLzqklfh3z/m32P9zPoxj3gSR0vcsecOXLv12nEP47Di4cbQMvOnUJE+S+J+/oIqOfsPD/Y8MViRR8XVkvlSQtjOGJFypwVaAGfCzqkpzBPhxMVSrGTdofzrYGBCW49yHml44K1dmw3gMI3EQ5x04gCU5xykZH/Qj4673KYKPIGUWWR/kest1U0gqxUUDMwSoe/lb2OXl6aypZo9qJWSsroKKIX9LNUUxOTWU8a0LcSIz6xZhc+sXYXfB+FRB+fxrN378ey9+/G0vQdwd9vgncesx9tWz+JALIVSZjdVe8QmbVBh3cgyq6yjIbehCjHiri334O/f8S58z7O+G+eecy5at1RTwNwENJEw7Ku0vxYVSbdbBbKkKXFkmKVuoDACTg2syj3mEfDqBWHKsoJH2yS780Dld8rM3pY3qq+vhR3H7o/ZxHGlqx1aW2Jl2M0bOBAhV+OR+1U2NxTINw/I0tFO5AlZwZ2tMgN4CiRRGFhAZKgmsbFfilxBmjnYHBkAFys1uOwg5YyW5N4mO1dmBGYQelRaBUtXyCZO7yFRBIUMsv1IUG9aHX1AHhk/UNjkEKJKhEiLPEedJ+rNy6Hi0MraBxfvBfAKkrgc32aq6UjHN7vISYwvZgezrtl92mlPw58//89x7Oyx+KWP/RJOet1J+Nn3/ywODA+MeZSTmMR4Y+OKjfiTZ/3Jw8mH9jseRhIBBuTJ5QHygqLrIwQFlQzmhD71uHvQ4oTFDmI3FB1cNJquBaBp4sJEFVaR3OD+wMGDuOkbc5iaXoXpNmLdul7TssE9cG3E5eEKBzWHYgvtjxUoZQVSSb+uGbEQCINBC2vpSSQtPymKjtTS0WDWDl+9eq8mMAN9zyBEEMUR5jHonNRV+X1O+OqKafzepnV42hkn4DUnHIO7By1+7p5t+NDNd+Bnt+/BBiq+qTmrjjMlZyhrDanJHoikuKxtWzRNgxgD9u7fh3/6x/djx65dAlR0k0GBcMGFF2D1mlUCiF2jKWOOTcRQi9gEEAoobJpGirg07V+zoHVzBFRzVheI2bqoC8Xq7mGxmi8oOK61tAZ+BfSlcg5lbcVaTeQCWeer73u395J0fvBrsPObi4L71oaAEANiLE4JBkCNsWawa8PrsOyA251VG+WmaRQ+mu+sSnTYmjQI8R/9qJrd0GIxA7CEKTBHcJBj2ZzZvIZArhuuC9OIyufQuVcKonqhIjuIQeaxbRo0USVE3+aG/9ux7XobgKcC2EhEWwD8NwCtLp7/jcNMNR2pYGZ8z//7Hlyy6RL8/vf8/kN56kk8yFg9tRo/9ugfw489+sdw7dZr8brPvQ6fvOOTWNGuAAAs9AsPymt3EpM4WmLN9Br8x8f/x3EP4yENgviyAqgVB7DK6FClbE1VIN6skta/a9DgpK5DbMSmywCRMUamUUxqEWU2QKavJQJyz0AM2Dc3g8UhsHLtepx7TsR9O3ZJm1xktYgqbVKXkicO7CrZyIjkAVBQDtUHk7KrpD60PQwsM2unp1RAI6FIEBBKUYxV2LdNVPBKyFlkApkzOKlZfyAsLMwLIx1Q0uNNg3/ZuB7/uvlYnHtgDq/auhM/uW0XfmDnXvzpMevwD8esRSbCwsKCNqdgZ/yini+oNVjKwnr2PRemNgQcmDuIT378k/jBl36/b06YGVNTU1ixYgYx7kXfJ7RtK+9DrpwCjBVmlXUUJraedwehKIAn9T0QSlvVEILrNpu29TVnTR1YdgZ+jLr4qAa1piuN1AJL9LcGOqMx9tU4600PVcDZALdfDxFyrrIMCkRjLNZVh/wsGVMM6+sluoOm0hf3KZsWQYGpeeeysv/KZIcADuROA3LfGX0O+NoNqzE13aDrA4ZdAEIS2YEC/QDNRugYZG6Cfwbq7IXcAkYkAkJw6Y20qY4qwyAfq3++qnuzNL4dl4OXfYvfH1aq6UgFEaEJDd5z43smgHYZxUWbLsJffe9foc+iKdq3uA/nveE8vOS8l+C1T3ktjpk9ZtxDnMQkHrIYpiG+vuPrOHH1iY8oGY75iUZjdSwNyaN6xpyzsF8hACx2T1ump/DEA/PSGqFttFWqIOM+9WjQeCGRdUMK0dreAiBgajBAzj3u2jLE4y9bB27msGJ6QbokAaqdTRCiqoAPawRgaWUbp6sO9eFdN4MwUCNSAAEaKaVSyMYZfa/AR19vzF/0JhGjKXYDHFaAlHNCiGUTIIVvcq0xAE1snAU2FrvrO1w3NcBrTj0eZx2cxy9u2YZfvW8HXrp7L/7b8cfghhXToEBoY+ssG2dhVI0tFrBfOp9FLc4KIWDP3j04OD+PFTNTqpWUe3HiCSdiy91b9bUdAELqU5FWotJbVvO3VG5gUQOdYIytMqPeFYwCkhayWRtkO2ZK0lrXNlJevFUBz5wzkJMzklR1F7P7YlKSpcC4ZretBbLBsrZtwTnrBk/lF0Hm2bp3kc0LUeVaIAtZllvRNAOuBlBRgsyl8bfZZAJsMJHL51He5CBVPpeMrm/wyc/sLUCdkoBVOwaz+spGYXXZ1O8lzH1BRi3WeVY0WNaz3i8ieGuTgme/KUt7JCQHY4/nnfU83Lzr5onbwTKMJsieqksdnnvWc/GGq9+Ac15/Dt785TdPZCSTeFBx9oazcfmJl497GIcV9+y/Bxf/74vxnq+/Z9xDeUhj37592LV7l/elN6hHqs208Ha4mrYOIeD62RlMMePsg/PyIn2Ad33nGjx5bfROYjFGrUSXY2ZlRO++dx7DPiA063HiKadhakqAn2oLnIWTtHMoKXR9QEctfPKfqZaUVVJgj2AyqcNSljeJfKCJcp2Nai/NvirlhE5T2NbZyv42wCbAspF2qGgQEBFCixhaTA2mZexq2ZVSxsLCAhYWFrwxQ0oJN05N4cdPPwGvOXkz1mTG/7vtHvzUjj1oNUXd9R26rkOfeiwuLroMATpGc2yw5gIxRmzbth233Horkl2zArvzzj0XnLMCQgH0UJZaOsVBjy+srWmak6bprVHBUpZzRGdZAUqTB7iEA6U4zDcNgALLVPSymUeYYMqMftihr6y5lnYmM7lBqthqe53d05yyA3bO2YsPo+lpVcdqRY51CBgOYF3nrBscA4WEANEEqICW2UGwgU8hRq0oCw6EQzVnBMsuBMTIOOEE4PjNPdauHopWl0nWfQaQRUJgH0Yi+EZVzi+SBnMykIyFSo3IpCvGbkM3twrl2Qb4wCw1cJQA2uee/VwAwNuvf/uYRzKJw40NKzbgTc9/E6776etw/rHn41XveRWe8dZnYG44N+6hTWKZxH9+0n/GO1/6znEP47DCIA/jkbOJYwBTU1MYLkrRaM1mbT5uM1LqXfsIwLWTVoX95RmRJ1144CByyhguDpFzRtu0XnVtoMDAMQGqv4yS3ldWrOsi3vaOu/GHr7sBf/f2G7G4yGqb1KieT7qXQVP4lgKWP8Yqsx8Tmr7Nylgy179P6PtOQSy7XrNMDI8AL9NZuuuBvsy0lzWTW2s0TT9sgLjve3TDTiQNVRW9byaqFPfH16/FS885FR9auwo/s3UX/vzmO7FGNw510VSgct6maTAYDNBqSp/0nqWUsG3HdtRAhJmxevVqHHfcZrRN45rYpomYnp7Wpg8GkApQk+PSCHjLOSMpU5xScqBva8r+NjAJQEF9GnUuCNLu11lJZb6t3bAztqH4otaA1YuyQhi5TgO4RZqia7nyW04p6YYgu01XaCJCiFJoqGHSFa+f1E+SF4dRVeBGgFmt2Vikc1yZF9Nmy7Hhm0VnQRUIRwCDtsMzn7ESL3nRMfje52/GyqlofRBgOldb5zKFRRcrcwbHo1zJi+AgXKce8DXKarEnF/rN9bPAUQJoT117Kr7njO/BG65+Axb7xXEPZxL/hjjvmPPwiVd+Am98zhtx/KrjXV87iUkczeHFHI/ArIQ9xJmKzvDiiy9CO2gRFRCZ7KDre+QkAG/roMG9bYNLtBPXYDCQQhl9YAcS0NBUD3hhOZMCnySeqjrl27b3OLjQ4uACYeWKHhvXMADpQtY0UVL2TVyS8jeAZ6yhaD2BUS1miNGLtEIAmkbBubK9fpyKYRTtbHbQVAPXJloBlmpZK4AlhWcJiTtk7sHoRZ+atFqepePaoB1osVXr4ApUwMT+EPCrpxyPXzzhWJy9MMTbbr0b584v6jXE4pdKNKL5dQBn40kJV3/+CyIn8OsDVq1ehfPOOxvgIslIKWsh1dAL26z6ParkhAKNANRSmFZy7Q5GjYn115cNydLxjkg8lF22grWu60Y6hTVNg7ZtHYzauUwH6mwsFaeLmlG29SFj065fQNnI2BrQgka7xhK6PiAyAimqUrZThS/WWc/AI4gK6yn0qhzH9NGs745ljl12EGStTg2mMD3Top2KYmsG9s8W2X0AQMwqaaGiG6/vEeBzZQDYPzOyGMocUfWGRwJDCwC/+pRfxWuf/NpxD2MSRyACBfz0Y38a//dF/xdEhFt23YJf/ugvo0vduIc2iYdxvPafX4un/NVTxj2MwwpnTDh/i1ceXTE3N4cd27c7IyZG+Bmzs7PYvGkzALhfK1DYr7ZpESjgc6tn8aQD85gxdolKQQ1UV5hyBoMV0CmraQ9iKEMElv72mdHGIV7wrBV45cvX4ezTCVJvI+cX4FNSqwIoC2snAK9KT8PAdWHO7BoYAEiLjrRAydLvnuIOpZp/BEA6+JWDuL2Y+amy+ZkWYFAfpwnRswEiYxhN3zPYj/GhtSvxitOOBxPhzbduwVMOzEu73Bj9NcKSFuDdNMV1gJmxuLiIbdu2WvYZNgEXXXgR2sEAOSf/YTLgjZKWjmpdZnNcOxzU7Gg95/Z9SiLXqDcF9ftr7asxvLbW6mPXrhV2XVGr8U1mYvfFNM1UHcPWQc3YSoGerMXa/cDuS9d1uoZTWTMGXB0FRgDaIU3BaQGO5R1FzVoQYgIjEyFQU8kFKha8YqMFk6rrBwPg4AVs9Sas6LOVaYZofm0MBHaQXRfT1dkMB7q6ySr3E980jhpAe8XJV+A/PO4/YKqZGvdQJnGE4z03vge/++nfxXe/9buxZ2HPuIcziYdp3HfgPty6+9ZxD+Ow4pEoOQCA+YVF3HDjzVKBbXPAwMrZlTjxhBNG2FAwI+jDO2Vhrz6yfg1mc8aT9s0hhugPRjtWnVIVX0sBYsErr5XxbFpNLUdcdulqnHnGGqxYMcT3PXcVnn7FDNatbsFsr1XGNkaY/s+ZJRQdZc1KMVjT4oW17JPYeAGMdtCiCcK6GntYcrQZOXdIeYiUh8i5GylSEgDaI3NXsApL8RxRA2IB2cbKZe7R6zGM/S76yQLAmqZxK66bZ2fww2edjNumBviD2+7GE/ceKKBNZQqg0gnLAJeBz65bxHXXf9WlkKR58xgCNqxbpxIDuU/i21pYW2sTKw4XZf7kd3kEwDVNIy4E+qcGiMAoS1ocBIrlG3T95FR0u/XrjAW331nKPMaIpm19bdkaWMrIhiUbk5HjVTrYGAkU1Gc4MzhDmdciwTBgm1gKGOVn6gah2ltU/rVSNGmbDABMYLaMRpmjWp7jjGgI4ACAGgDSQhqcIUtVQKrPNJktFwkJDDMRs1cakyztgEUPrNkOFFcQlz7wqBzpm4HaowbQAnKj3vTFN+Evv/SX4x7KJI5gvPoJr8ZbX/RWfPauz+Jpb3kats9tH/eQJjGJIxrrZtbhr773r3DlKVeOeygPWRBE23nvffdiOBzKw656up500okK8ITti9qelSDV0cyML66axc62wbN271NNoTJuFdNtD0VjFC2slawVWGX9/oabhvjitUMMhzNoW+DyRwc8/5kNjl27AOu7ZDZalh51Zqpi/IoHqmAlS3mDKq6MDMRndzAQsFE8bx0wa+cmrt63tBp/qdyBVX8rMgvtcKb/DQokBIwLKDPbJxmUVtkra7azafCTp52Ab0wP8Ie334MnHZj3NDVQxmxhMhFjlO+8804cPHhQ2Hh9zdRggIsuvlhY2CCa0brAS9Lvph+uJBm5tKQd+ZNLAZWzohVDWttn2fudsdUivBhKS9kRdwNeArTqMeasBYDBG1LUzG5ZYwWAPxAD7FZgAKIWMo6k5EmAqELGkY1U/ekqTClG1idoVDNdH9eAOFf3KMYIcECMA+zdA+zaxdi7r0XPhOJQENzj17SwohAoFnZ1oR4YCDZ6A6y27utrqJloe+83iaMK0ALAO254B37+gz+Pe/bfM+6hTOIIxg9d9EN4zw++B1/b8TVc+eYrce/+h7x3xyQm8R2LFe0KvPKSV+KcjeeMeygPaVCI6PqEr97wNYwa/DBOP+0UAbEoHrDWVco6KCUAH123Blfs2Y+Ni52nbwXMFR9MK+wBMFp9bmAxBAfLe/dlvOf92/GRT8wjTm9GbKZw6okNXvy8Bhecq40a2CQKuXQ7q0BK2zYOYBkJITAYCUB2ezFLh4+AihgK6Mq54rOCyhJKUY8Uy2UAko5O6pRQ21pV0wnOhNRllQkwCMK2iW42Yzgcyjly8ltRSx4Axv4m4qdPPxG3TbX4/dvvxpkLi+LA0HUCONUmDShtVAEgUMQdd2zB/v3SRMfkJSDguE3HYmZ6Sp0WxJM3hAjOSSrzsxTSFSwjsyKNMYoO1vXDCi6NjRXAHhBCMwJsR/S+yuRH1e3W7G7OMjd96iVLsMSxwK6n/ybsLylrWTPEBvQEyAfZpGUD64ycK70oG3eJKgWvDhuBEEm0wbbxMXusYGwpqzcz4Jpb8062zVTZXJkbgnjCitwhYW6O8PZ33ou3/r/78N733YeFhdIsQvZSwgqLhlbvExEQigzH6GCz52Nl6snuqrkfsLmd1AAXupYeGLYeVYCWiPDG574RwzTEf/rgf3pEFlgczfHss56ND778gzhpzUlYNbVq3MOZxCSOWHSpw2fu+swjaqMmhIwUet19993uGWsxGAxw0UUXARBQMWhbNJr2lYeocDx/s3EtIjNetnWHOweEiq00kCtFO9rSVTtWGavXdz3MvD8lAdpf/Mo+/J+/ug033bIfOSds3LgCM41oRS1FXXvQxhiQlfE1vW7xTlWNKEFtw8ivw6KAHPtavZCQwZzAWebH0+E5KRiRc8RQ2re6WGEJuK0BoDRAYLkeCuJRq5X+FIo5vzPfeoydnPGzpxyPAyHgf95+N1YOOwVIMreNFktFZWhrd4q77rpLB1Lu8/HHH4+ZmRkHaU3TYHp6Gk1sXNphncKkGKvx7mGDtkXbtiPg0lwhar2rpeBLSj/6vTNQm6r31S4J9lrTY/dLmNb6NZYhqBng2vKtiY2unVEGWuQIochZDChr1kA2IHZvq8JHK7wCRsZsf1uaX6QvowSnuHFEiOHtaEGiFYmx3ysGQkJsCbGpWi6zaWAPgbXYMhlmPQbfNPqYAS2KrDISKOx2Wc/F2uubxVEFaAHgzPVn4teu/DW844Z34A1Xv2Hcw5nEEY4rT70SH3z5B7FysBKL/eKkUGwSHhdtughPP/3p4x7GYcXuhd140l8+Ce/62rvGPZSHLAhiKJ9zxu133Ik9u/doCl8edDEEnHzi8Qgkr7NUvTCbvVsd3TVo8KF1q/F923dhbTIQW0z5Yyi6xqZt1POz2GDVve2ZgRDNdD5gy70d3vPBg7juhoRrrp3HV25M2to0Y/Ua4AXPbPCc7w448+SD2LBmiA3rGky1HUJgAJpuTwHyqGUFwZKWlteQSyKk3WlQtjDjOd+V8O9eOIeXv3AeL39hjx9+EeOHvi9g00ZCCAJ8Tz4+44Rj92PdKsba1RFN7MDUI0M0p3W3NEBBD2sjB2SEoOdtCsCzAjGgAGJL+5vEYGsT8IunHo9NXcLv370NrQLMGAOYe+Sc0Cs76u4UOePar16PPrMDE5GgMs4752zR7yqY77pOGdwCYmqPU3d20IPUTKgX5I0wsWKVVoO1Ym0WvK1tXRx2KGBrrgf2+8IAwz2Ol0oIRv62TEEFSOvjZdXkWgFZ0VOXzw270tR3G+DAqjFXIFhJDexvIU0L65uZwdZ4xObFXle9z/aGq1cCz3vOWrz4RRvxXVduwPSgdSBNEH32iDogiOI3uIQGLr9hO7qiXAOutb5YXkHVfIlM4X6UbRXfslPYcoxfuuKXcNXdV+HVH3o1XnDOC3DympPHPaRJHMEgIgzTEN/91u/GozY+Cn/2/D8b95Am8TCIn3v8z417CIcdj8SiMAbQdVJYdPDgQQyHUuFvv2QAJ590ItatW4ftO3b6g846UDWNuh8Q8FfHrMdzdu/DK7btxBtO3OysooEjA3bm42rsKFNpOWrSA+tx32vl/oH5gHd9YB4hMPpemyVEwtqVPR51BiOnRVx05hAhZIAabNmSced9M/j0F3swMs45c4ATNhGYO4QYAM7IiLj+6xH3bO2QeyDLj9H30kI2gnHipozjNgCgHoxFAAQO0xjEFlLV3uHJjwVOOo4AOogDB1fgppv3o+dpzM1P4dqbMuYPZpgGV9wH5JEvuCaDkYGsbCzB9bIglIKxBGcYFUGiaVpcPxjg947biF+9Zzu+b8ce/P2GNX7fTAecUwIpYGRm7N69B/fccw+O27xJ7jPJdZ9++un41Kc/5xraWkebkzVcsDazcFZwxOLMtKlU2GQDjHY8K2QLdp9Nn60d60aAnWlyw2gLXWdKqRT/9dX57Jz2fR2iG88jAI5zsaxzOzj9DMj11J7HVKFTOaJJCwR4sutSrfDRbbuM5TQAaZpnQ6ysc1iNH2T/JhEGLeG4TQPMTE9hYeGASBwQACS4rpfKZkGuh+0geoqymSFw6ZaWeQTI2vzbPJvuFsSqHz50HHUMLSA38q0veive97L3TcDsURqDOMAVJ12BN13zpklDjUks+3gk+tD6A5hE2ffJT33GmRh7bq9ZswZr1qyWZ7ime41NAwKaRrxqb1+1Au9dvwYv37YLpx6YQ0oJw6F0sgLBmy4YwygV/KJxHLQDMa8na42bpSNW34OZ0HdASoxuqH6rBGRkTLULGC4kxGYAivpgxwGcdHxC1+0Ru7BMOPOkBTzhwj144sX7cfkFe3H5BfvxhAsO4Lh1HVJfAFQw3SUJwNx3kLD3IGHvgYi9B1rsPTDA7j0Rw07ec8zaBqtWLgrLyRmzUwdw8QUtHndpwOUX90AedT2IDanOMYlPbVWt36fyN7OASGMl26bFoB3oTQNa/Zoz453r1+CzK2fwc3dvxabFYZEpSNUPgtpaAQJyDhw4gJ07dzqrZ5rJdWtW46QTjxeZRYVfsjPnhWGuWc+6KCsnS+GrMwbkXtesX13QlVJyf1nz0a2ZWKAwnSOa29SPFHTZZoG5eN/WALi2Gas3bO5dW/nqGmg1KULKpm8No5tdm5+cACKkxEhZ5AWZCKwNNQqrDu3KhRH22r4PGLUNs98TBYDlPk21LQIG+rtGz538tS7zCUWLWwNxIsm6EOB+uGySmJHXqaY9kPoQV0zt0iKxJXFUMrQAsHpqNZ555jMBAO+/+f04c/2ZOHvD2WMe1SSOZPzm034TH7vtY/iZf/oZPOWUp2Dzys3jHtIkxhi/8rFfwbtvfDeu/5nrxz2UBx1eNf0I8qFlY2wY6FKPnbt2YTgcSoMEwEHCZZddhm/ccpsACC/KEZ1m10lREuWMP9y8AVfs3Y/X3nUfXnnmSTDwIMyk+aYyBu1AmSiqQJwU4xiDl1JSHaMweMbGRWOvKGDL1jX4uw8wphugIeC881Zj08aMgIztu4SJA2dhgZkRVHLA3ICoEeYyaoteyHA97RwYH/gE+VwIM51AaLFzzxDMEXMLAR/4WIN1q4e44MJVGMR5BOqwYpqw9+AAw0XV3HLGYMA4+7QBbrljDilPIWXRzXJmcGQEVIVOtMQRAKrjTKLX5SCpbRvrb5ywCe+8+Q780t3b8ZozTkJsomwklKnrus6hGDPjS1+6Buedc7aSdjInK1fOYtOxx+DOLXcjaTGZ6UTlPpkbQQFKLglgm7csBCEVmQUzg7h4ANcWXzUwTpRGfmcyBDk+V4xjkSHU7K5d2/0YXpMBkLLFZF29qHQGy2Xz4J3EKoswaHEW1el2J1Bdh4NAo3IBabqg6XqwE7HGIBtL7WCXyz3Sg4M5i2dxYgwGLWIcgJS9HwGYFeNrMpCloNnGHYyhrfc+NTOrf8cYq9a4h3BLOEQctYDWYqFfwE/9409hmIb4yA9/BBduunDcQ5rEEYomNHjLC9+CS//sUvzkP/4k3v0D7/6mu7dJHN2xb3Hfsi2qeiRKDgAo8BDgtWv3btz8jVtw/vmPkl/qQ3Ljhg2YnppCr7pOzhmdFdxAba4CsCcG/P7mDfidu7fj5Tv24G+OXV9SqFnYpkhwABtyUJayA2lXsUgCTppmIOAVxiJV7UBV+rewmHHPVvPJncXX70xgJLQhA2EKBCAEwg03ATt2lHawIKniv28HIYQMzqVFrOkZKRP27iUwCrvHYG2qNY0YCAcXGHfetwK33zuFL90EREyhbQNOP3UV5hcZXeqQWUDguacDz/sexjdum8WnvhCxc/cCciK0AxmXd1NTwGhSDs4CiJ25U8bTQNhgMMC2AePPN23Ez927HY9ZHOKLGIAZ4ljQy3pOKTmo3LZtJzKPYjNmxjnnnIOvXHc95hcXi59rZHA2UMMAiq2Xa1pzqbaHM7qsugeMeMGKBRWkMDBKcVbSTYy9xq6/lg54uh/mJsGuM3a3Ar0+09RSCA60zXHDXx9oBAiL1lrdHJZogbnyklUhrH8tgE9Au4WdHy7NKO8b3ajIz+TjI84DpnUFgKC6b2nFy1o0KF3thr12M8sGss2xIDjAtrHUmxnRHZC/JNJoMwkpVAMoVHM5ciwrSDt0HJWSgzqmm2l8+Ic/jCY0uPLNV+LTd3563EOaxBGM8445D7/xXb+BG7bfgB0Hd4x7OJMYY8QQly3DOTuYxTu+/x147lnPHfdQHuJQf9UQkHLGjp27BUBWgOTYYzbiggvOBwBP+Yo8QOyAYmhAEGbx/etW42OrZvHz9+7A4w7M+wPcUtPDbigFR0mOQ6GY3Tdu7k9oQiM2TySPdKAwbtIyVxtBcAAhgiAtdttmCkzTAMvxQoy4bQvw+WuBz38F+NyXGZ+9hvGZLybcuy25TZNZXBlQtFao9hA3cCKkmHZUy7YZEO1rnwkHF1p89esLuOW2RajDGWangSc9foC2CbjwvGn8yA8ei7PPWIHQ6PxXm6mcxPGhZkCt8tzspQIJe9m0jdt6/e3GtdjRRPzEnfcia7etoHpNczqoC8S+eM01MEhl8OTYY49Rey5ho8V+S6rkxYkglW5eqWqjq++3VrmNuiKEGCWVrcBUOqJJe2Kz2DKm0q6pliQsdSuw62jVWcHAlq2tvu+9ha4BOnN3ME/euhubAWg7v3wcStvewg6Tg0z/zFQ6XuLiOiC6VmNEDWySv8uuy96rugxkg7fKijtbC2FpMzL27Mu46vN78KlP78VNN3foU1Zf5bI+WYFzxijodPZaJsVOK8ysXqf9zEZq67+WLNiQHyiOekALAOduPBf/+qp/xfqZ9XjqW56K//nZ/znuIU3iCMYvXP4LuOFnbsAxs8eMeyiTGGME9RtdjjGIA7z4US/GWRvOGvdQHsIwkCCPshgjbrjhBvR9ck2dpFIJq1evgj1lY2yKbk/BSgxqxUUB/+2UzbhzaoDfuf1ubF4YOkgEitm+FTm5hrYpRUFi+9Sj78V7VECVesjyaOvU8ic4E8bagYkB1dFmJPe+laIW0TuiXKemzoWJ1dlhVm1rRtclCM6XIqAaHNUOBkV3Ksx05oyFPuADH1vEjl0ZKTNWDPbiRc9biydetgIzUwJIzEM2L7EBM/eDpm385yONBvR/CzHgLzZvxGMOHMRj5g4K+6igqm2VnVZw1/U9tm3fgT7linAkDNoWl15ysQMbVl9aAbDqnKCgse/7Ed/XlOxPcncLu992nyWFLTfJ2v3mJH+stay9pwa2Nrc+55puX2ondr/X2b1huXZrEhIr5rfct8La1pZiwnTbMcqf+lzGtAKyTs0mC6qBdds6k0OQyRAqbSqRaF+JKmDpoh0wMrbvnMNVn9+Jq76wDXfcKU012KUMxUsWqKQHS35GDlZpFJjq66me90oCQrqpo3oCDhGPCEALAKetOw1f+Ikv4PlnP3/ZpiUncehoY4s2tpgbzuGmnTeNeziTGFMsZ0Db5x4f+saHcNvu28Y9lIc8jAVMKWH/gTns238Alh41tumyxz4GU9Mt5KFtoFIfdsru9n2PzBn7ifCfTtmMCOBP7rgHGzOLu4CxnCC1zSoFPwaarCiKAkBBUvG1P2gxr68YMktXK2tKTMVgH1A5gwLuWBhJeYCTA3p7WJd0OavvLiBVNAZBSkraoh6TgVqTCvQ9Y8t9AW9/X4/rvz6P3AMR+/BdV8zgxS/ciDYuKkYQFrZtxNeVggEQEh1sZpdG1AVZpj9+19pV2BMjXrpzr1yXgjgDbzln9J203L322q9i9+698IIlCJg/bvOmUfZR9bx1pb9186pBJ5EBOgV5lZ9srXm16wq6UQLD2+nWnr2uZa0AsRdTASNMsTHJS+VuNpY+9SPNPIx5XFpQtnQMph8mKsVxDjWrUxFMlhCQczmeabJNI2P/NgadVyvkovqYJAVi5dug+JexdlWLM09fhbPPXI+NG2er6y0MKiBaXmdfq/kk0qIwtvFXllz+mVDHiszSVKOKGmg/UDxiAC0ArJ1ei3e+9J34ne/+HQDAx2//ON55wzu/qch4EssnnvHWZ+An3vcT4x7GJMYUl26+FC951EvGPYzDioV+Ac/662fhHTe8Y9xDeYiD3dg+hIDhcIirrroKVusirwBmZ1Zg/br1rsNzhi0X1tQ7LsWIu6an8OpTjscJww5v+sZd2DjstagrOniuje0BaJFWUxg6ADkDYKrABcGKdMqfrFnTYv7eOMumvJWlYhPjfuwcF4DElYG+sZwxjD7Gl1bEG6Cu/5h0Iqv+ss8Zu/Yw3v/PPT78iQPo0xSYFzGgOUwPpgWoW6MJlIp+QAoVZSxF45j65MxfyqKP7ZsG/7RhDZ66Zz/WLg6RcsZwuCgpa9WRkgLilHrs2bunkpbIvJx5xhlYt3aN26hJFzZrqzqqLQ1UOrMtnRdzOjiU8wBVxzbWr55PAEvmEX6+QwFRmyPTFzvwpmLhtdSNYek5R5pCqJaaBMkC0I5y9SZPPxnkOwJCSjIG2/ioj8Ro8t+YUFTZCgBNiAis7KkWjhkTal3WTj11JZ797BPwvOedjkedtwEAV6DV+V4EJgQbViC35rL750Mx1pZKwZfYipGyv0UmsXTtP1A8ogAtIBPSiHgIb7j6DXjJ378Ez/7rZ+PmnTePeWST+LfG885+Hj5xxydw6+5bxz2USYwhXn7Ry/HmF7553MM4rHhkFoXVqjkFSZmxb/8+LC4ulpexMJWXPeax8oAWYZ+zmd56E1p9n4Qt/eKqFfjZU0/AcV2HN33jThyzONRnJas0gEeBDsRxoE+9FOgoSBVAqsVagREiECNBnvmmSyQQFVumWv9XpAIEe+TWOk0ALllgTU8761YVAY0ywYXJu3/hklWDZ2H3sswriDHsCF+4jvG+D8zjxpt7fPBj+7B/XgAn+P4dnwzEj7gDpOwpdiuwS1k2Bu9cvxotgOfv2guAESMBEJ/fEINXx6eccc2XrnEGUtWamJ6ewnGbNzkT3KvUwEAxUJwganbWMH8NJJd2D2NmdF1XOn2hALt6LmsXBQe2mR3oOSCu29oqA2pMrBV+OaNctcq1DYO91qBgE6WTmB+vFxlE0A1Y0aGyuyWYFsEkCwRpg6sfG7fQIgg7yhXNKWy1FC5m23QgO0AuGtsABqEdAIO2QRMZnIeolLdwtwUoyxqDyheMAS5/SI9XPgfkNl6mGTY4G2IDWkLN1huNpfGIA7R1vO3Fb8MfP+uP8dktn8UF/+sC/MIHfwF377t73MOaxGHGKy5+BQIFvPnLbx73UCYxiQcVj1QfWuksBYCK/dHN37gF27ZthxUzW5HUhg3rsWJ21ot/nNVktWiqHpKmM/3Sqln8zGknYGOf8He33o3H7D9YtKkKoC1lbhZLBr4KI1ckCvbgZrZOZGK+byAEBjqqPzUraEVCZZylLaqDoEpKAQoIdUtbZR/tGMD9NZ91db5V4icrqsqMvk+44aZ5vOufDuLebY2CrIzYNOJ2ABoBsl6wxMX4f9gNXRsKlLa7tw0GuGFmCk/dNzfCgKecCphNUsi2f98BHDw4b6vB/3faaac5u80MB5MGAl3uUH1ff2rMCqyej6Wsan0MayZR22wtZWIN8NUyhkMx5cCojnaE4VWphLTIrYrOsrU5LusdINdCP/C/CVTJCmxDY/+GWBGVgMXCtRaJQXYWP9t+Qv5D1dxR0B+pR3MgHWvZuMl0ZxuRbzTrTZAOUEBuBbL9x6jcF9iRsX+2lsp8Hige0YC2CQ1+7vE/hxt/9ka8/MKX408//6f46K0fHfewJnGYceLqE/H0056Ov7v+78Y9lEmMIX7rk7+FNb+7ZtzDOKxw9muZaoAPJ5yNpALUKAaE2OLTn/6sv47kKY1TTjkZGzduAFAVJgHeytaq20kB6aAdgMG4bvVK/MjZJ2NvjPhft9yFV2zb7WwkObVX2Mh2MFAPWkBwVdXqtGeIyxgBHMBsbgsFhC7VttYPdqpBklfqi2RB2EJ9cAdjoqsEcwVsUt9jaWQ9lhVJ1SAtZwZICs6kMj0A1GL9+imce9YAT7xsGhdduAF9TmDUrGT1B+xFY1aEF0ikHsNOiu9iE/Gvq2dx4cEFrB72FdAvWum2bUEhYPv2Hbjzjjth+QkDW+L2kEo7XdUu16zrSLpfGyPYBsfa5hqwtPtgRVw1s6orUddRkQ/YWOumDHYtKSX0XT+yoVrKxNavtVbCfd97AV+oPH9rrW3O2ZscNE3jHra2YajEprpmdHMUyLMW8llS+UFl+WUbKtiyCpoFqMEiR1WBlM+W/CKjaVeD4ipkCqDQOnNrFCqhbD5BJlsY+cTL2uLRDQhBsh1NLBsP2bQGLeKrMjnVJuJQ8YgGtBabV27GX/7/2fvzeNuuqswb/845196nvX2Xvu9DEgIBAkTpe0IriICgFopiaSmWpZa/17JKy9LyfdWyKVBRQUTECCggCNKFLiG0IaTvc5Pb9/d0e6815/z9McaYa+2TG5ooOVyyRz4n95zdrDXXWnPv9cxnPOMZL/xLbv2ZW3nlBa8E4A8//4e89O9fyodu/dBIBeQ4vrvjWac/i1v23sK2w9tWeijjeIijjjWHBodWehgPKh6ekoPWoF2Kb0JhQOfm56RlbWFlhN067rjjpPWsa10KMO2dyQn0Xlc3NTlnhsMhN3vHK087no+vnuEXdu7lL+7ewSnDRm+mrXbWeaeWXlL5PhgOaOoWPPrgilVVCL4A0C4L2LWoMkYzHamQilYmYAC1ALJletguq2iMZPfvUnCUpd1oC8Bk3CIRME2lVMPHmHCu4TnP2MBTn3oMm9cdJnjz1ZX3dXWnplHu9/oCNpCFQ0qpnL8YE59eNUMALptfVCmDVcPfn53uMsgGQmdnZ8WxYFlq2XSvxnLbj9fCvQdiSo05t9+NJS02ZDqmmOLIee6CZgPa5Tp3Wil3bb26Vlzt+FoAZq83ltoyE96bq4E+39mWw5XrMfr1kMu+TKNq43A5q+SkZUO7nw2TW5jf7ygJ7Eq2g3IuHffdt58vfekevvKlbVz/9XvI2Xegpi48y0DbHdlcNzbXJAZet2/uJCY5EJVD63tsm/1WGNrv+cYK306cuu7U8vtivcin7/4077nxPZyw+gR+5KIf4RWPeAXnbz5/BUc4jm8Wr7zglTz11KeOu4Y9DKObtv9GX3rfjdELPT786g9zxvozVnooD11Yqt+3YKDX65FTYvuOHdx86y1c/MhHys03C4h93GMfy5e/9OVyg2wBj7CQ1sHKbvzdpgAD7/mlU47j8/sO8nPb9vD3t9zNX2xZz19vXMeQOAJiCrOqoC1o56bkEtLiyJYeAhxyRE3nR31LR+QG6O/BjYzdAVXVo4mNgHjaOew74KybMrcw9trYNufEDr84QDjXGYudKUk+kyN79s6ztLjA9Eyf887ZxGevGbKwILZpjRZ7FaZT399E6QKWXSbXytxq69hQBa6fnGDOex65OOCD61bpOOS9tkiJsSF7D+riYEAbBavGKlvhXZdt7c6f7nmw99miwsCyzIOM13+dptmT1j0VqUk1KvsZPXeueMl2i9CAtoNaZ+HhXNsQwcY1ArB1brqkCw/XWmthEtIsfsMiCbHaOWFpFaPr2GUWubKg03njxA9We4zp+ylseE7ZGuEhtY+uIyPJCtp1MYLjzrv2c9dd+1U7rp7fWRdIdBqY2MJJGWPr+SCgW4vUnMNliqyn2MWVz529p2v/1ZnzDxBjhvYB4pcu+yXufeO9/MPL/oFHbH4E//PT/5Nf+divlOe/vP3L1LFewRGO40hx7KpjufjYi1vd1zgeNmHXPOajL6PineeZpz+T09adttJDecgiQ2GijKltmkij4Kge6vdrbnnryclJNm0Wv+kukybepFF9P8Ub0wdPr5NiFka34h83rucHzjuNT6ya5g079vK+m+7kZTv3UMVGUqWa+uz3+sVEvwpVa3GUzZWgKWyqAA5rYerb/WmqeDlbZzf8Yshf18W1ocvyWmramM37W1VRGgcYEIFlXqgdj1ZjcM0/NOfA7t0e7/pMTi4xPTUoAK+qKtHNago+prYRhP1uLVNN+5tzJjvHTVN9zl1cErCm19AAqDUNaKUMmJByREcpMoMwwnxbtIz0Mua6A/y7fsFWte+9Vz3sMp1rISQ70gbXanAd1slrVMphuucj6XTtHC1vzGDjMVlL9zVdezJL3UtR3yiYl6F1zr/TBUEGgieJfqW4vYXczgt5p4DlRtlgaAGj1SJmQ8BZdLXHbJ7i/HPWce45G1i/bnJkDpYVpgLp9py2GuxWl+tIzhXwWa65dVP7JmTEN6ozGN/1v0GY2fmHXvUh7nvjffzuM34XgK0Ht/LoP3s0635nHc99x3P5/z73//GV7V95WOnfvpvjfTe/jz/94p+u9DDG8RBH0LTd0fo5fPcN7+bru76+0sN4SCMokxW8yA2qEOj3RZ+3deu9NOp/it7sVq9exZOf/P3MzkwXg3sJRxV6BF9pI4Ae/X5fGEsFCfWwZlgPGdZDtuXEfznpGP7DKcdxz0SfX9mxl3++dSv/Yc8BNiMtYa0YKDZSbd/ESN3UxBSFtVWrMDHsz8pcJSDhXG51gCXtmgsgzKpRDd7j8FTaeQpaA3wD6iZXAIrLAbSgzgqjmkbAMbTkZTZw751IOpwWuakvLji+dt12BgsHyGmOU0+aBnxpXmDbMB2sFUd1U9/SNcsXQJZy4qbJSc5aGkKdycmJfjQ3RZtp8oF2sFnH3AJakYO02tQu2y3j9/cDl93ztJwRtTC5iDhV+A7wj22HLhmkzqz2fcv31d12XqZX7coMDKx1WWNQK6uOfCHnZI23AAX1wel3mgBLm+9Oh+jMY9l5soFJY2ATRAWPHmFsrXWG81Z4BlIIpmysRxeFvrDADs/ZZ63m2c89jec892zOOns9XruTdfXFZdzBl6JG59R/VnXqsqgAT3uel0PU3Pn328m1jQHttxjHrjqWszeeDcD6qfX8w8v+gdde9Fru2H8H//lf/zOP+rNH8Tdf+xsAth/ezsfv/PhRq+c72uOKG67gtz7zWys9jHE8xHHxMRfz44/68aJHPdri5f/wcv7u63+30sN4yEJucC2LakUvdS3a1xtuuIHBYChpZ2PVYsM5Z5/Ny1/+cjZv3qzp+qqwiZaerYc1S0tLDIYDlgZLDAaDkioPPjA9NUUVKr66djU/edbJ/OQZJ3LPRJ+f3b6Hf77uFv7Hrfdw6b4DpKWltpI+Z3pVr3R88j6UdqnGyJqOt7B02uzB2ttawVrQFq1k6Pf7wppmaJo4ApacE4urri40w6iNU5FJUF5ThAWd7lOjbgjiIZpzZjCYJedJUoJ1awak1EjqO7cuCaaDNVBnXa3KvvWaWgOGm3qBqZw5TgFir9cr4LSAPedaGUEG68RWmOsYSwvcIzkGGItq18IezzmXxgpkyvUr27B5ouf1SC1vDdwWvbIVwy0r+uq+3jS4QGHgDcC1HsYtI2vygm7zBgN3y4vyeADIZ4VYSTzmFES2Cxb5PIgvrCFgYbONDW1t3Uy+4Kw4zuQe2MKoFs14Uc66kTGU+WmLN5uTblQukMnC0CpYJrd631I0WbasBHH3yL8BQzvW0D6ImOnP8NLzXspLz3spAPcduo+P3/lxnnH6MwB4/y3v5/UfeD0Oxzkbz+Gxxz+WRx37KF570WtZM7lmJYf+sIjT1p7GO772DupY0wu9lR7OOB6ieM6Zz+E5Zz5npYfxoCO48LArQE05M2xEWhB8IGQp1iE7YvYsLi4xOTUFKeNJxaT9pOOP45Wv+EH+7l1/z959+wpbW9c1MTWYO0DwPXAtILT0bNNEnHcFsF01NcFnTz6GM4aRH9h7gMsPHObZBw9zMHg+vnqWj65dzTWrpqhzWyhljCuO0hTBUt3OQ04NVRVIUWUMzrfv66Skm6ZWQA9TUxMFyHoFs91CKgNsVVW16eOcScgCoVvVL5rP1vLK2FlJXzuSywQX2LZ7kV17YcumNSzM7yd4T6InncGC6iJDK4QMau1l+2q0PS0o65cSuyb7AGyuB9w7EUgJPFVhGE0nPBgMkLbCHYBkTCy0rLaCVLDmDh1AqeMUH2AD2IKiTNtr200pkUj4rMBcZQBdmYcB1K6Gti3QakFY9/WiC44jlmnodYFMCFYo6CiFUh3G1uQson1ORPWEFUI70HoYt8VaMWcyvjDDRavtfVm4AW16X3Wr+qtNmI4dnahli3wmZ9HaZvAuCtvqe5CCNIfAk1y+HzMN4MwrTHW5OMq2ckpk5/CdxVhrDScMsl193P0VCOOisO9wHL/6eH74oh8uf7/8/Jdz8pqTuea+a7hm2zV88NYP8rZr38arL3w1AL/72d/l3Te+m3M3ncsZ687gxDUncuLqE3nyKU/+hhfr3zNM//u9CPjWTa0jk5kbzrFuat1KD2ccD2F0WZyjLSpfHZX6339L5Cwm/SkKWNUcJ71+n5QSH/nXf+VpT3ua2nW5UlgCjs2bNvKqV72Sd/7du9ixYwcZaVUrZTDtzT9r+tWApKV5U2MWVPLaEAJ3TVf8fzPH8AfHb+bSw/M888BhnnFwjhfvP8Qh77lmZorPzk7yuZlptk30So7TtLJtkwZAWWNJ4WoRkBZvGfBNdIGRdRwTJtCY2aSuDkUri8kVdX8gJVWmpczyeyySDAUrCqCqINsJXrp/LS3Bv3xsiYqKnXsqmuhwTq5HMvBbfEYVkLk21QzGeLafvR0Kwo81Zlqrj8xOLOVM5b0CWgMtLXPc7/eFYcx6jrIVRil7WJhL9VON6uXqFNh1G0IUpi+XRYIB1S4gLQV2Bso6x1fOK2ITZqMtzG4Ggl4TfT7ljE8yx5rGismUrU0d7WlHOyxAuW2HjO2pYMaW7ky6mLJt2LyzU2kNR7IDX0Bn+72YdYwuZ4JKRnK5Dp3zYdtzFY5Jsu+TdEGQTWPLsu9czQLkbC1snUgjUhIPaafw3LcAnzJ+Y/ChlaJ8U2ktMAa035FYO7mWZ53xLJ51xrMAuVi75nexfmo9ABumNzDTn+HDt32Yt869FYCZ3gyHf+UwAD/7oZ/lE3d9grWTa1k7uZZ1k+s4ac1J/OZTfxOAK66/gq2HtlL5iuCE0dg0vakwxn98zR9z+77bWagXmKvnOLh0kDPXn8nvP/v3ATjvT87jxj03AqIT3jS9iZec+xL+8Dl/CMBt+27jj6/5Y45fdTy/+MRffGhO2r9jzPRmAJiv58eA9mEUv3/V7/PGj7yRA7904KjMhAQfaNL9/UW/V8PAW9KbfkpRLJS8Y2lpiaqquOmWW9m7bz8vfMHzOf744/E5kZSldc6xft06XvGKl/Oud/0923fs1NSrV8AnwLBpslpZeXJO+Eq6iRnzOZJWV+1r4x2fWjXNlTNTTByXuWx+ke87NM/j5xZ4+uF5YC939Xt8ZWqCr031+dpEn9sm+jShZbtQ4CbFQAHvAlWoyF6AgLSP7VbwW0veeD/2LymbaL+P6EUN3DnrDuYV3HUAmXc4UtEq4wRgV/TIZLbvcJCHOBcJPpDpEWPdLjZwxdLMgLQBYgsDISkm9vaEKFk3qHGrZoVpVMeJAvhipGlqWqWkIBevmkvdKgKuxLs1xUQ2l4mS8k9FY5pTLm4EI9rODvA2dteufxfcdo/FKvJt8dHVzi5nco3l7O67MNm5lTs4l/XciY7UfJBTVglJMj1xy7R2TK/KeMVFIeLJ2mVL5kWl11akEcowOyd6VQOZdJviZnBBtLedK2FWYDkjFmApMxxm5ucSdRyyMK8ANLUFm1aUJnNNgKh0IaOAY5MEJRCGli6YT/J4p5EHnWNvMf9YcrCi4Zxjy+yW8vePXfxj/NjFPwaIPdi9h+5lz8Ke8oE6de2p3Lv+Xg4sHeC+Q/dx/a7r2Ti9sQDaN3/pzXz8zo+P7OOCzRcUQPuu69/FtTuuZbo3zUx/hrWTazl5zcnlta971OuYH87jnefw8DA753dy/KrjAWhSw4VvupDFRjq4rJtax+se9brv0Jn5zsRMXwHtcH6FRzKOhzLsi/BoLQqrfPWwkxyEUImFU1bbLe9JTaRXVQIIE+zbf4B3vesfePGLX8Rpp54ijI9lMp1jw4b1/OArfpArrng3u3buLKlf50WbJ5XyaumUPSlFqirQNBFjBEEcF5yCSq++t5lM8p5Pr+vz8dlpUkqcWjc8fm6Bx80t8P1zC7z44BwAAwc3T0xw10SPu6vA1qlJ7qw891UVc77VRpqmFhhh57wPymO22kwHzMTIhphYHyOrc2bRe3Z5x9aqotb3VkADOLUtC1XAuFynyMRpS1HvQ9GXphQJwVNVcMqJkYkebNy4ns9cvb8UTBW9aEabHqTi4VrgTB4FNIu1PD6BFL05Y9vUWq2JESpPXY86BZl60nxaU4wF7BmIdR0HG3OVaEGRjMNAd6svbiUKXScJO8+2rRHnBDop9M6/y439Rwr2sDxC+57gwv2kCDGmMu8crTwgpqaw6ym1NlcjoNF+y8Z2Q3bq0UsHQNox4QioDVfszi11pkio72su7LnXK2ESi5jh81/YyVe/dhAyDIdxlNUuV69dVHhZNeEcRLX4Mu10dMWoTZ6jtfAytYJpvLudybrX60gxBrQrHFO9Kc7ccCZnbjizPPbzj/95fv7xP/+A7/nAD32AYRwSc6RJDTFFKt9eyk//6Ke/4T7f+Pg3PuBzKSfe9Lw38Vdf/SuuvPtK/viaPz7qAO1Lzn0JB37pAKsmVq30UMbxEMbRDmg//OoPs3lm80oP4yEN58yn0yR9mRAcMSmQSo5maYm6rnn3e/6Rl774hZx22qnqKKDMnXNsWr+OV/3QK/jIRz7CTbferM0QvDK0saSapXI/Fx1pYW29Vt0ri0UWbWZ2qhFVeYL3ntsrz53r1/A361ZByhwfIxcuDnjE4oBzBzWPWVjiBXUDHCzH2QAHQ2Bf8OwLgYF3NDiigwZHdo5+jEzFxHSKzAKrUmJ9TPQf4NwNgGsn+nxuosfPHZrnL2an+e9rZhU8CfjxztqdAtlDFheCUebWMzXpeNb3zzAze4iFxSU+fbWeF2WEUZAUk7iaxhRLWrtNPcvfMUeierr2c8S7XLS85m1a9SpySgwHQ0ZT6gJdqlDJ2LLKDlLbojbRui84PwpuoQWBywEqcD+QKxuiXNsuyE26wDHbMvt7RKZAy84WjW5KuNwWzXnnVdoi3q1ZQaCc1xbUynyWZh0qE9Z9W2tcdTpAdAQxip6l+NACEZWImF+ucyQHPsv3YyK1XrBAwJGlOkt9Yem0yqVIMFxOpFyxuFSbEgDxoBV2mLJNh3e5LN7MD9eVzWkbYdCisKhbWNYUgyzn6X7hxoD2ey2melNM9aa+I9vuhz6vfeRrWT+1np+79Od45unP/I7s5zsZk9Ukk9XkSg9jHA9xHO2A9rHHP3alh/AQhxQFhVAhTKKXVrNI1bYjk9WLNOfM3MIc737ve3jxi17IWWedVVg72VRmzewsz3/ec1n12VV84ZovMFiqGQ5ruYErs2iAxYqqcs5MTEwQte3oSGcuBWpegbMxWt6FkoZ23rGjqtgx0ecja1bpUDJVXXNqzJy0NGBzndiYM+tiZF2MrG8SM00ikPE5E/RnwTnmEOC7I3jmvGef9+zzjr0KhudCYNo5tgxrzhwMedzSgJ87JJmo/zC3wF+snmW7gghoU8cCwgyfdMCDgczkmJ9bYM3qhqY5gM8J/DRN05TkdIxRrZ6MUTPdrFa+q2zZitFqYEJZYGj1uN6LLVjlA4PBsJWt6qX03tPrVeX6FquuqiqsZBek2rXwzgvQzmDNVQtLGkILIjWK96vOCbv+9reB9a6nuaXr7fVdxtbn9nXeeWXApQjt/npckVV0XQyyAnthZtXOKwlEFbeB1k0CkI55PhBjI1rZnAmhavflHPVwWNjQIoOx8+KUnVWAnbFL2HoHGzscQuD8R6zl2C1raBq47tqd7Nm7JMCzU2jogxx3LG2Ec6tjwDTYMoaQRVoBqD4clQgbqO3qctt/uwz98hgD2nEcMf7XZ/4Xs/1ZXnTOi1Z6KN923LL3Ft7y5bfwhse8gVPWnrLSwxnHQxRHO6C94vorOHbVsVx20mUrPZSHKBRQAcEAZkoMY1MaG/gqdNgrx8JgwPv++YO8qKo4/ZRThH3qWP1MTPR52pOfwhMvfTz/+rFPMBwOuOfurczNz2sXMqk4t5tlTomlwVBsnZS9DVUoQLnfm8TSu8YI13WtNmG5bRJQ2s16ueFOzXBr03Db1HS5QccUSUmsvNB9W9q+qiqWloYKCLvAJ4/8a4+76SlNy2eOqWs+fe9OAI6PkR29SlkxBWtZa9fFk4mcfXEGIIt+c34hce99ixx3rKPnA/1ezfxQ5S8j+kexLjNWVgr5UkGkxqLmnKm9I2jqHGNAq0BsGvq9PuTM0tLSiA5XdifMep2SAqJc9JSjBUOKgpUZjVibXQrDXxi/DpA15tQeN/Y+NlGzBKloYUc6pUF5vPv+7usM4BYwrIx4zqKZNs/Zbict58yNQdweTEfrdbHh1bGjy2JDLrph19HadudLTtp5DwjZFiQep7KNAmEzhOClWK6IGqSYK6lGtpqoOOv0YzjjzBNZWlzitpv3gxvYUoZUGNpRbTPOt4wuwv5650nK2gYfCuuPk25uohPXa2koF/tImgThyDEGtOM4YphB9tEY9xy8h9/93O/ygrNfMAa0D6O46JiLeOOlb/yOZS++0/ELH/kFnnba0x5GgLbtygXCmjrnlRnK4hurhWJV8MRGwMNgacA73/n3vOiFz+fcc8+hp++zFHXlA7PTM7z4RS8gxsjOnTsZDmu+/OWvsPXee5k7PMf8wgJJdYw+CDsUqp6wg1UgZ/FAraoew+GAnBNNbKRJAtDEQauVRBoxiHWYJ6hzTBV66qfa0G0da5XdvX5fQY1qKF235S6lGn+koAlGQEtKiftCIAF/vGqGL/R75BiLK0KpyPfgshWetUVOYAtAxzBOcGiuYWF+mtlVkYV9IjswJhHnCL61C/PO0TQ1DrFL8+osYGBkiGNCkvIqbZD/Qqho6hrvPXU9FHbPt9ZklXr9NvWwZfQUoBVgaoyuMnql7TXy2i6Q7S44TG5RGHZnRv+5zEfzrAVKcwkb2/0kCcpyt0VfrfRAroGjomolNB122SlrbF3WnMtSPOekuE805SVZX/ZrJ0A8jiPk9vrYSwuTbHpVBYajYBrwxoLKtYnqtAHS4MHQqPeOqhfICvjrcl46UgUZYEcXrp+PjqYXux44YWhjLJcSnFp2pdKMZNTz1izpeMAYA9pxHDGOZkB7tDN143hw8YQTn8ATTnzCSg/jQcfDrSjMOZiYmNBWqkm1rGBIxRlzFhNJO3NVlQCfhcVF3vuP72fv3n084dLHMTHRB0J7T1cAVPnAscccQ4qJk044gZQzO7bvZNv27dx1993cfscdDIdDQoyFAJP3ip53cWFBDfMliV2p/KFXhVJIU2maNwXxz81JvnsGg6ESieoPWrxI2yKXlJKAnZ6jChXRgBACQksxVGdsssn2rh5CkPS+a31qu4CutXPS1L030/2g4xfLsZvvnOS6G5c4NOdIrsK7XFrvFtZN2TQZNwUcVVq97nDFBq32jj4q71Cg5O34nchKBoNBYemNHQzaeMI1Ttjy5MhNUwBgKRjTpgeiCVXQqlZVHjsP4Hwo7GVOwiKnnAog7TaxEHcD7bzFqLSBLG21RyzMoDDXzrmOVZrwrfZ8Ac4pqaZWthFjBCW4S9MJHEnHL2StAl3dq3w2KPPItmVetgbqg8vaEMIcBSz9n4uuVTcvfrL6vC3TTAoh5yVTVWI7hmttP80xo0xQR8lutGoBV2QlpqGNrrWfy4yC1Fw207LFXeVCh2y/X4wB7TiOGGNAO46jLZrUsFgvMtOfGdG9HS3xcLPtsuIVq1QXfaUAHbM2En2tpt/daIOAum648lOfod/rcfZZZ7J+/XqVE+itMmfRL+LRXpu4nDn2mC0ce8xmLnzE+dSxYfeevVx99VUsLQ245567GQ5qvWnKzdpkBMZ6Vt4RfCsJ6HbtQpuMppRKq1nR3grzbF3QUk5tj3scw7rW4w+iDNDdj+oIKb6zBkgKI+icvK+rj9XnvSC80qnL5BMGVgzn7NzV4IjMroGqmuDgoVg6nElKvLXEyp19h+CJOm1tERIKwGUEMMYozQIMfC4tLklbY5/JaDFVFej1+sQF0Qa7DkBPoAsDj0ttG+DGuoB1WW0DRJq6t2OtQqBumhHA6qAUIZnkoADcZZ3BRsAbFDsza9FrrzGpgb0vNlJI57wubmi3aSAf17Ko5Zityt+VXRZA34LSLPl8TMagEoCUsbYVqNTAKQNs11COV90Fuiyvst/G9obQBzw5CcvfZYWdM0/bDovcmYdgnga6T2Vo7YCsQYlNxoRZk1lBXoG2dM7C/WIMaMdxxPDOH7U31yLaHwPah1X87XV/y2v/8bXc9jO3cfr601d6ON92BBcedo0V7IYqdlBZHQm8NkgQ4OeUkcoJGksZW0FMqnjv+97Plk0beexjLuH8889n/bp1olUELVZRkJOcAin1IfUO5yuOP3YLP/DiFzEYDtm9ezcLC0tcdfXVzM/Ps+/AQZq6lrEkS3u7EdslS0M75+hVPWJUZpDWxL+p66L9y1lZXQW5Va8iZ2l72y1aWh7LtZsGrAxggu0zlvR/zpnsBNBnTenK+ynp4eQEXG9clznn1HnOOWeGL3x5gesO9pXpa1P0oABWAaTpje1YLN1v2kuy6Iy9Aj3vHVGvgesCL5aDp5YZzlkYfAOoglWjsHY6ruA9yQCYLhhSR2pgfqnG+pXua51uccWuy+y3DKzh2jay5fjaaykWWx3nCLn4BFqtbnm9NZ/IjIDmAl5Vx2r71V+KX61Eu00D7uL3mmkVCh1nB7QAS99rCyHBvh7nEk1svY+9k8+JN/40ZwaDho995DqmpqfIuWF+rilSDXHCaOfTCGXbYmwFsgpYjSHOHQCe22M3OsIWt+oyJ4uxMaAdx7cbf/XCv1rpITzoGDO0D88w67qjdSFW+eqoHfuDDe98aavqEC/WJjZ6g3VavJKom6zWWkE7bInRfoyREHrs23+Ij378Sq754pd41CMv4tJLH0+ogqaPFaAYAIwdUGfgIEvHsGO2bCHnzKmnnERKmeu+/nUWFhe57uvXs2f3bop9rAtUVSU2VU0ko4VBmgKOjbK2doN2Hq+a2tAPquUUQBFTlFQ1DnLE+dB2TUvKN7uWES4AUHWpBYBlV0CzHGwHVNgv98vbOn04MWyWePRF00zP1qyarvGur7oHCqNowEMJXpph3abS1Wmgbmq8U2iR2wYGsiiRlq4GZox5KyPMsnJx5gyAU4FmmxIXCYhtPotXrZ0D9aQVptussaxYShi+2DQFGGtT2CIzAIgulkWKFd4ZY1jkI1r41WWfi1bXjwKurvbWrrO5FuQOa+rsmub2OrcMZWqvnabgY2pKm+ekB5QdpbBKD1jBYy6XPWUDtfKAl7Nd9mnP2/mQLniJ7bsanD8I2dMkh9ndlSyLN/cPyVQkPTZ0gWGfP8sIeNPIZsiu/TzYYstgcRO1QYld9JTa6bssxoB2HEeMk9eevNJDeNBx2UmXEX8tfsOV3Di+98IA7dHKcr7nB9/z8LKbU+YyKfvZ70vXKvP1lBv+aLo6xkSVgxJHdZuNUVZsz559fOwTn+Izn/s8a1av5pJLLmFqqs8550jxmAEb665VWKJMAUymhwzBc/FFFxK853GXXMLSYImvXnstBw8eJDXy2jrFwsL54EUHG2NpQICjWJChx5P02K3yPcaGwdKAwWCID7D1vh3SilSZQQFRAm5MR+qDGuGnrJ29BHtWvUrBJW1KXLdjekdb8PsRcOZohpNklnDA5k2e4DNFPpoSzhoyoMfUSce3xVJJ2PUsXGAxy88Cwrz3kGIL2DosoNO/raAoGStraXvncB48rQtFAZSa9pdCqSQd2eguBrTa3rd3hZgSKYqsIodRDa2DwjZ79c5FNbJdpna59jY6AcCx44ogJ4bC8gpo1X7INhdKMl1dKUwS4n1pxNGOXN4bzVLNZCXK8krntFYLKwytzQUMycvcVIDd3im7MgIFmzkzNVHxqMccQ7/qMTc3z1e+spM6juq12+sHMNrKWsC6zVmIzhUW1lj2bgaiyRmnoDilLA4hBdB2FmvLYgxox3HEeO+N72WxWeSVF7xypYfybUdZ2Y/jYRVHO0N71oazVnoID204J7ZcKWPSwxijWD+RO0DJgAOFkcw5i0QjxsLECuYJOOdpmsjuffv55w/9C71exee/8GUmJ3o88QlPYHZ6mtlVs/T7/WX2QPav5UilwCjGSC84qqkpLrv00gLOBEy0wKfdBkAHhOGZqGBiQr1VXS7aVGFnG5YWa+6++162bNnIRz7+SW657XaamABfAFWxSCJDWbRZelpduVyWV2TT7raaSHyHiTTFggL4lDJDMik5vIscc+wsExOBulmWfle7JzPtl1PlRFZQ/Fwz3lMM+rtV/1mLoqJLeBzr1q1ldnaKqmh5pQVyOb9ZFwF6nVB20yzSbCxd3StRgVXKBeyScwv87HRoU4mYrcgsFuDp9Dw51+qfuxIEK940MNb1riVD5csSpkgavEE421Zuz2txY1CmssBRZ4VeOq9y+3iyDl+KXu2Ol3R+Flbf2xbsgufCvNvZEAZXXA5KZ7dsytdMf6LHoy46hYmJhsOHD3L913cyrLustXoQdIvXyiLEnEtSWRiU1rddKtggsY2fRE5Rr3mm1utTVllHiDGgHccR48+//OfsWdhzVALauw7cxe985nd4w2PewAVbLljp4YzjIYqjHdBecf0V9ELvqPR+fnDRFlRZowMrrCk2S+ZF2mHuxN4rl1S4ASHxkZU7exPNiN4xHAy4+667wDluve0OXEqcddaZrFq9ijPPOJ2TTjpJ7LtKAYuGa4GGsU8tLnAkvUGbtm8EM+gvI4VEKYN5hwLBiYWVqyp6rkcInrWrVvPC5z6bf/nXj3PjrXcwrMU03zsBLzllfHb4YDd/23gLeM0KzZ4zk35odZt6eJ2/MxkvDDBzrJ7p430LZpP698aYDMcKOA1BwaGndF3Ta2LvzXQ9b3Nh7VLOzE5P0fOoS4Ky3kuL7NuzG9frgff4lEHN+zO0+mUncoMcOp2mvNf2waINNnCUFBgZmDTvVjz4IM0yYjTGWI6tFEW5drHTLRQrx9eVHOSWSRVda8e7Ni13EmilAcacWumUaUWzzvOuQqR8eoqUQs9dma9yHMHJmbCuXM45lRO0muiRrmA6h2xeOd2enNuMd5GcxcJOGHo/cq6yHkM2wKm/V6EqIBvU2QPlmfWzJYoKaxwhyzZbaFp3uaif6RzbbS2PMaAdxwNGq9Y6umLX/C7e/KU38/yznj8GtA+jOHvD2fy3J/03tsxsWemhPKj4/at/n5n+zMMG0FpafzhslMVq2SrIpWUtmOtBAAd1PSygTPO0uEYKg7z3uKS3RS9pYO/bdq/9fp/hcMgtt99JzokvfuVaet5x7jlnc8YZZ7Bu7Rq2bNmiDFUqKfAucMyAy76kiUe+JU1/2E3xFhY4KthdzjA5ZcH6TE5P4Qee5z7r6fT6n+Sr191Q9lqq0dUyy3rdQyHupPgqRnI0s389F4arU9I0tqEkObYQAh5Hk2ZxrqbOmZxj8ay16yHjELBjqffgvapiKVZgLUrquBso+5c7AK3X6xc2VNLjqlf1BmDagwsGxDuNEeSYMjGLPCEYwO6ATtUaQKY0D3BJ2dXCNrdg1YChyR26Otkyr/A4BegpWjq8reTPWRojkJHWwz4UGQO0DQvkPIZi1SaAVxoSGHAX/WgaBbOgTHXrlOH0/LUFfBJRzrp9VExRoKAUYs7lc1aAdS4nrlwbvCe7RM4VcdkUlsVMu+DL7btb6zDMBxhhy7vnLI/OmZzluGOiuFzEJorFXeezuDzGgHYcR4w61fR8b6WH8aDCGLpeODrHP44HF2dvPJtff/Kvr/QwHnQ83Hxoi/bUmf1TKH3voxaFmW2XWU11AYbxSeDoVRU+BGUzPVmtprJHvWylC9RgaYCloy2lvJQyX/jytVz79RtYvXoVG9au46ILL+C4445l3drVugcDKvaXJZRHb97GFo8yp5By6+vZBWMSqSDOpq7BiT/vM576ZJzzfPW667Fq9MLFlh12+TVj0wSAGrvtnRNGrNPitR2LeuMq6/aPH9yHp8aFwPy86UezygjarlgG7oL35dwa4AZ1bEDAZlM3hdU0gB2qipwyszMzun09Gudo6obBYEiYmCzA0gBxKaSio3f1XhsCdABoh20vs8RJ+1x7RnSuNp8SZFdS/N55xdHKeNrCge7807lbtXO0XI+cpf2r2pPJedHCL5ywx+Yjm5IUbjlhZIv7g2v36zr/t2tdCgCLrKJM0MLcOod008uU/QHtdc1yDLIGscKudL/WwU3TsGvnIXr9mvk5zfo7V4CoSWnojDeb33A5dxS7tqQaWnHQgOxaZrmV6ui7nHgl27wz0H2kGAPacRwxmtQctYDQTJ8tBT2Oh0cM45A9C3vYMLWBiWpipYfzbcfDz4dW9aAYYMnF9D+EipSGqs2UG66BFituKpZHuGK3ZDe8ZJXQrr1JBr0pFisnAxrBUVXC+h04eIiDBw9x2513MTszzVlnnMbxxx7LWWecTr/fR3dcGMbc3tPlJp5ze691xopJg4IqeWXhuq4LAmJSitSNWHuZK8D01DTPfebT8Q6+et0NBBdwwYn+1AdibIhNyxGbb+9gsNgCsJyYmpoYWQyUYh206UHKDIfCem/dDt5P0OtVwozlRD2sccHTNA1N0zCjINS6aBVrrZjoT/SJTcNwGJXJzgy1i9jk5CRkx+LSEt4HHJnJiUlhK1VW4RUwHjq8wLrJKYKTVq0+qxWYXn9JncvCx+lix4BZ2wjCic1bbu3fjBUNyoqikgixgtNjUVkALuHxeKeuE65Tj6Qp8K7zQancUI1IylkZzRYUG5AUcB10v7kF6rnV3gqx7ME8jXVa2fwpnsTajETeTzsepWOz065cCmidd6Ssut/Ujk0Y9JbddUihXUqJA/uH/N27rsV5SMmTqQQs59ZJwua9y5SW0FHBtjTvaDXEwmDnIk9w9rjraqQd3kPw4F1g9dQ0ZuzlxoB2HN9O1LE+KkEBCLsMHLUM8zgeXFy19Sqe/LYn8/HXfJynnPqUlR7Otx2VrxjG4UoP4yELh6PCMUDAmABZse2qgqdXVcXHNVSBSpnRwWCA+W/2+315TUo45wvImJjoK+AS4BBjpFf1FFyJFpWciY3cIpu6LiDD+0C/59m/fz9fvfY6brr5Vj768SvBwdo1a0rzh0OHDhfZgadNHU9OTdCr+kxMTlIPh5AT6zesZd3atWzYsKF0O0uxKVZHWY9lbm4eXynQ1pam33/ZE1lYWOK6G28mVIEUE02shdlTFkxS0CoLyIzoG5smqvwgU9cNQRsThBBomoYQKqqqEqs0Bet1XVMV71hPtMWGi9S1FIDFmFhaWmJmZpoYI/1+rwDKEBT051w6f9V102FWxaO3iZH5+YXymHOJhflFer2Kfn8CsnT2ci6pr2ub63beiwVXh/HueroCxMKfd9wSsiww5H2SyvcuYMx3NjbTJWU5g2o5vabs2wWUnGR0nSOMaGFYjV1ObXZBh2L/lLG2jHn7+WitxDL9/gT3bL2ntNN1Dnbv3s1wWJcmIylGeqFHkxqqXk9AYwgMm1jAP1k6mGUHVdUrGnYbkDg82OhkTol+uSHVWSUrFSALnKrq0eh2c6dZiBUJZoc0YYhJWvDqeWhyJiCLAlsYicQgluvgnGPXzp3cfffdhWXPoM4URy4MGwPacRwx3vuD7y16oKMtcs5MVVP0Q3+lhzKOhzCC9oM/WlnO4B5eDK3zns2bj6Fpaq2XSqQcR27qsZFWo8Gq6slMTUwU0BA1zS0p70hKtK1o+30BRPp+5xzTU5OFXayqSunVtoNWTI0wfkjBUhUCKTUFIB44uL+AvqKrzLkwcillDh8egGr+xE4qsmPXjsK8WsFWWwwnB7xh/Xouf84zOGbLesgiUwC487Y7uXf7bmJy+CR2Xt5FUEDa69v3nGiSp6aFiBgOh/T7E+qXKxxyv99nWA/xzpVCPJeTWr2mjs+uY6lp6FU9snPEuiZ5KdobDKVdbVVVTE5Osri4RE6OurYubp5eTzqeNeqjOxwMcc4L2O+L7drM5DQXnHcWVb9SUjMDgc1bNvK6H30VE2u2CPAsvqOdidFtnWrazY7kswD68gbTdxojaw8pu+h9BzRlfc7YQ9/eCzv7KTrbb3af7KTSXW430JWqFPGKjVFBprD+sHPHDqZYIoRAr9cj5cwl55/FeaedyIc/eSWHDx4EPI1vqOsBQWUQdd0wqGt8yhw8eBAQ6zto7dose2FFlLHTFc7kKFEXQnVTy0IDR9PUkrXQwx8MBkxMTGDouB4O6U9MMBwKwTQ1OQlOQOygkccW5w/TaDEoGUIVZDHV69E0NVMhsaqShalTb+Xd+/cyHAyOeKrHgHYcR4xNM5tWeggPOp5x+jNY+NWFlR7GOB7iONp9aN/6oreu9BAe0nAIKMpkpPrD4/EdbaCALJd9WazknPE9Sb826vcqwFT6wwcv7WOltazYMmVNyxtTmGLCVVVh+KoQ8NqpzPtA5QPNsMYFp0Cr49WqN/YUxU/WqZYxWZGR9/SMHdPjbEp3o9zWvji1e3LgVBt44MAhqhCY7PfJ+AJ0h8Mhe/bsxYUgYMOZHjQUmYLLaBcqLaAp3cKEbQ1VEMbVycIhhyAyh7qmFyYJ3jPR7zEcDmliKgV2uFbjPBgMpEhJu7SFIPIQc18o10wtyaqciV4Bkss4L4xojHI+9h9c5DNXfY4Xv+Byer2qjG12NjA7u4o0tUEA9cisaSUWBsAE6+YOOGwBrQo8BZxmLJGv4Oj+kbsANY8+PvqgNbHIZf9FhtIBo/qUjLXoS1tAWzSvZZ9dmNvud2HuMOvXrZbUvZdOequmJrjuphvZs3t3WSDFpIuoFLXLVqTOIk2o65qq8lqkJ3ZxWRn0pqnp9Xo00RwMxMKtWI5ZVzDvqTWbIYx/XbIMDtOAa+FilCJCk+IMh0PMBSMpM+1tUZBFJ2td11Cbt00b13Lslg167YSZrVUHf6QYA9pxHDHe9IU3sXF6Iy87/2UrPZRxjONbiqPdtuuY2WNWeggPbZQ6lqSV+0mBhis3QS9O+gAlZWpMZ0mLFouuStKjWVLvVSUgyVUQEuQcNe0tWlMDL5kkkgPvRavoAq7Sgqim1s5UWWydkqMiAC0baRpM89BtaIgpqiuDK7pg03/mnGlixBGhqqQRgAL7rDrCosV1Dhe8nJus8kwv3dUcjomJSciZikwTrFYmKzOt9mDBj1T9T01NyzkHpnu9UkhH3bB+jWPt2g3s2LlAHSXlnlKi16sKUIcWpHmVd9AHK4oyV4QqQ64Ck1N9fKd1bM66zYkJbrv7Xt79T+/nBc99trJ7olPtT/QYGnh1nckyCls7j48+N8LMdp5roaLTIqb22eIIoSwu5VzSYUtHtZsjsKrDEC9/3LStZOiUjt1vhJnR7f+PijYAAITESURBVFv44Kl6QbyXU6Kua2665VY+duVncb4SdjvL4qNuGtGtVrI4zA4CmWAd+Rwie9HjKhZeOes8MUu6tstbzioJCRVNo3rn0OonnBNPaQOmdU6EXkUu+5MFZEoiK7LGE5UP4qihhXHZ5BlQOs+JGkO1yAlSjlThyNDVH/HRcTzs44+u+SOuuOGKlR7Gg4qrtl7Fq9/zau47dN9KD2UcD2Ec7YD2PTe+hz/94p+u9DAeusgoiPVaoCVMn7X77IKnbpo2qdG+VaOXwprOjRm0cYG2LrUKaWFT2+0XeYKyWzGmUiDl1PLLUq/CNDqaGHXcchiiLVWLsNC2OBXngE5bVi3I8aG1GLNuWEn9Os0lwPYd1Jc3hEDVq+j1+woyjCn1+BDoZUh2jAiAmOhPMDkxSa/XK1rN1C3e0f9lIITE0y6DV7+44VlPOoDLg/Y9mvJPVpWvMg4bt7Bqck5iEk2kMbR1lusVo+hlRXsaMceCejjklttu558//K8sLCyQYqSqQmGHyyD16o9A1i7eHYGqy0ChbqO0g+3Mv+W/tr4ZrSNB+3irAe26D5iu1hZhVpRl+5Ldd1hZXXCMaGvKQ+22U26BuXUsMz/h2++4g09+5nPMz82PXF9botl2vDkKZDoNIJQd7Vh7tecil8VHtwtccAlfZTau7bN5g2N6Ki3rApfLNq3lvADQXNhdbDwKXgGRu+jzXbsx08jenxmnfL6PFN8SQ+ucezbwf4AAvCXn/NvLnv8R4HcBQxB/nHN+y7ey7XF8d0ad6qPWJeCO/Xfwjuvewa896ddWeijjeAjj+FXH87vP+F3O33T+Sg/lQcXbv/Z2bt93O6+/5PUrPRScc38JPB/YlXN+hD62HngXcApwF/DynPN+J3fT/wM8F1gAfiTn/OVvvhMALfrRP733NLERX/XcuhNIIVYRPradozpAjZxBU6QiQ4C6aQrqcF66kjndR05SiOW8FMiApm1jImcpanFkqt4EmAzCBQG/erNOcUivX2FWWV5tj6os351S0ORomihsKaGwWSCyCW+yhShpYrGPOgLTp0yWyQDsFHqVN9S0ICIirG+Mjaa2W/yUOmAhxoh3nrqOxHoPG9at5tB8pJqA4ZJsXyy2UgvW1INVxpyK8b33nhRj0RMHMo1ZwaoY1Pmgi4+kVKXD+4rrb7qNejjk+c99NlM4hsMFds8fYnJyEu+r4iksDDCyANLFTLeLWcvuWc7ft0shw8AmT9AxFYfWLnZyHdDc5VBzCxgNURepAbnddtmUvae7JGvJ4dSRo6R2Q/KIsqcum1WYHNv2nTv5+Kc+y4HDC8SYcV5lAdq8YnlhnDSRbcGhyb7lWrry3mxpfbXfyoj0JCOfmemJhpc9f5F1qyo+/rk5Pn/tLCASHnl/C2qLq0YW/+ioRWLWLQ4F5iFnQlXJ5xQKgJbCN9fO+44KpLsOWB7fFLE45wLwJ8AzgHuBLzjn3pdzvmHZS9+Vc/6P32x74zg6oo710WvbNXY5eFjGpplN/Ocn/OeVHsaDjpjid9Mi8q3AHwN/3Xnsl4GP5Zx/2zn3y/r3LwHPAc7Un8cBb9J/v2lkY6H03xHPSr35W3qS3LJKuSnohKSsEkja34E4JvhAFSqx+0oKHnwoldxNbiusJUUrINhVnoxcD7H4SjiSVm07iBmv343ZRWUeRTvY0xu5gcCkDQ7qRjt+ZS86R+chCOMWFKgloIm5MMFeX5PtJq8V7ma/ZWxYX89Z02HLnNOOWsEsuvRHwYAVwRkT7YDkpsgkXErMTFcMhiYRKKe/XCcp4FOmWy3XRH4BpERwjipDk7Wblx5DUpsostOOrZnY1GTgtrvu5p8+8CGe9YynMlH1ed8/fYBhrdkWZdetqxkdQFbsyFzL8pdOEtZ4wBYBHVBrj5e6vlDpoipQTpTtp4DEVo9rLYyxDAFiJWZ/W1euNiMgID4lbR+RU5nv3lcjYNsWDFldGKYmJjj9h1/Brn27ef+HPsLh+QXRuloxm7oR4Chzw9j06NpUvPdenS1CC2w75yOrlIYsx5JzUk1uJjgI+SApZhwNMFM+O91FUmGGUyqgtLsAy9AytKq9Li2J9fjtc9PVcWQ957i2ke/y+Fa+PR8L3JZzvkMmgPs74IXAckA7ju+hWGqWmAyTKz2MBxVmfTR2OXh4xUK9wD0H7+HkNScz1Zta6eF829GkphQ/rXTknD/lnDtl2cMvBJ6sv78N+CQCaF8I/HWWu+LVzrm1zrljc87bv/FOoKRxAZStkqryBHh1GHBEZXs8XiUKoUgWTPvnvPBNUbuKNVGqo02GIM0a2lS26VZjjKVzVIpJmVkEDFVObcGiAB0nWl9xP0hUwYqWatB9ZAAvrgvZQ3ZOC8w8TbYuXpBrBVMhKNBKLA4GzC8N9bwIE7kwv4Q5KhhYNQmAc45cywK+ceIEEYJrgarTRUJhMSnFQqCg12e8hyZLg4Jez7F2VcXuvdH4RAVhlAYMBjyyMuymxYyN6olzIuTMIGu3Jz3PPqhPsKWpc6srHuK58dbbWRgMeOwll7A4GFDXwzJPbNKYbCKnIkst+NO2ZdX79lYDiMZgQrtQKoB+WSrb/G5buryVqhjjKr25lBV2uv9lAobihoEsxEQnrdvS+V/0qLltWYx2Ncsu4fIqDs0d5srPXs3hhQUalWaUBYZDAWhXSmAg1alVbdaCrxY8jnwcs74yiyxGsgtZdduOnKJehoAjFgY25ajnvWWHuwyxLZ68ynW6GtomRWKUhUhMklVwKCh3HUlE4bFNU8sR41vR0B4PbO38fa8+tjxe6pz7mnPuH5xzJ34L2x3Hd3EM4oDJ6ugEtPPDeQBm+jMrPJJxPJTxhfu+wLl/ci6f2/q5lR7Kg4qYv6sY2iPFlg5I3QFYj+Fv9R5x/+gwRAI+XGHezMGg2xQgJXMVSK3uNouO03R3ZlhvHcLMgL6wu2gKl6yeqUHN5nPZT9R2pqG0T5Ubbt3UNE1Tto2T1LfYKfVF9dAI89vESMbRJEn7i342EIJIFGTMUsBWN1p1nnJxTEgJ8ckt7LV2y1JAacB8WgtkamdFNB1Q5pwCWO2KZZrFNCrnkEK4VWQcIcDs6kqbH7gRkGJpY/MNlk5dBmCcSi/k8R4Q0TGJ5sMG1W7L0svK7jofuPuee7nive+jUXa2q+dsdaya4tc51M4dZQyhpLXJmr5X4BlTkla5Rs86bfBRgGfWwihkYZIj2dh6mUmYRKFlVFXqoYWLZIpPcMuaa/cvb6x4CyyzAlg5C6q9LsfnGNYN7/vAv3DHnXcxNzcnc7BpRjIZxvYWf1yMFdVliffqQdwy+SN64LIICpCdfi4ky+E62wdPE2XcHsRZJLRZBDtWvVqALh514dk0DWXZ7p3KgsTerhyHc8zOzrJx0yYo56qdh6bTXR7/Xt+e7wfemXMeOOdej6zen7r8Rc65nwB+AuCkk076d9r1OL4TsfXnt5bJeLRF5Ss2Tm9kpjcGtA+nuGG3JI3OWH/GCo/kwUUda4L77mBov1nknLN7IO+jbxDde0BVVRgsKbrErkgu51IY47zDZbMjso5Pak2lHpYoG+k6TNFohyhXUq7krF2J5MbotXuWdaCyVHtpRex0m0lu3m0b1kRUmyOnYKqiAteCyLqJyjYJoAsKRH1Qb10thHOhKkxqy63JiwUkWPq8ZZ2lOYWyXU7S+wLMIyFA0yjwlQMQIArkrODFW3tbWFgKpFwRC0uYSktVu9AFfGUKaxsbYzozOWsRkb6+8cLKda5/dw7pqRWP0ZZpFVA1HA6peqFlTkv22RY9ApASLSjDJAkdYIXOMmsfDL4AOfMOJueCfw0w21Arcwcw/i+JTZtToauzcSuj3so0zFas3ZfzXppwOE90Dp9baYLzxj62bLwtEgaDIdt37cM5r4s8XwBz61AgrKp9joSwd3iVs7RAtj22ck0756r7nDfw6AzYy+uDt/Mshy5a21Gg7Mpcyx0Jho5Jr1cdE/1JdepQX+QQPHXd0Ov1mJiYLN3ZlNAnptzaxC2LbwXQ3gd0GdcTaIu/7ITs7fz5FuB/H2lDOec/A/4M4JJLLvm2vwzH8dDFbH92pYfwoOKuA3fxYxf/GD/zuJ9Z6aGM4yGOD9z6AU5YfQInrTk6F8sfetWHODw8vNLD+Eax06QEzrljgV36+De9R1h07wFTk5M5ZWNcYzF8LxAktz3qnXPCgqlFl3lchtCXG7GC2dg0nS5QLYBqmmaEFUypTYFCawVWiluSpbVN42gm85mg/4ozQtLCKpUuOF80mEE9Q61Qzdr7UmkxjjK2uZGxxJiUyTQ9pgBebwVROeO9LAJsTCklXBQmc4CeL7XbgrarFFm6YRkIN7BfuYqmEWnBTTdX3HdfH+8r9u2rUYMIMmIzVphhAKcp++yJ0cZjC45E0PNWJ2liYUxuiknBpQHlrmNAC+JIWcq5ItqGzXVweQvMvPN430pPDGSGrJ3KOoA6Z2NAW4TuTTTgpdgs51gYSnShEJy6b5AKkHZmvuW06YJvO4OJ64Y6cYwgR8AllRnINTagqWVb9hnR824A016vx5EyLggq9Z3ti/dwq7W2906nzEKHZTe3j+7nw2QXxra3gFq9Z5uGGDN7DwYWhzC3JHMzEUekAV25gVxKV0BsNu04iWDHGgSYBwWzhqb7/Z4C9x4Li41ciwyZSF2nVoGyLL4VycEXgDOdc6c65/rAK4D3dV+gX24WLwBu/Ba2O47v0qhjzS98+Bf45F2fXOmhfNvx+g+8nvX/ez0v/fuX8tavvpVd87u++ZvGcdTHO697Jx+89YO87uLXjd5EjqKYqCbYOL1xpYfxjeJ9wGv199cC/9R5/DVO4lLg4DfVzyK375QSTS3V/VJE1ZBSpImN3kRjSUUGbYBQUtA46rouWlJJX5vtT6uHNdmCc65IEKyZgtPtmsYWhDkOvYpeTzT4KeeR8eCsG1avpOCdDzQxUdcNTd1Q142m2B29Xo9KXys3dsdwGMVZoMk0URoVuE5aXUSRwu4JyLYCLoq1lwG1nmZfox57qITpdVoklFU3mZXmSim3GkZrOxojhxci2/dmtu9JDIfKaqqFU/BBGWVl2Jw+ps+Z9ttkIhP6Eaw7AMuuQ9F46muWF7w5L8cYepVKBeRatvZnUFmXKycLBZfF09QkF05pU+c8/V5PGMSkmlVMqS0wsuc8lfqdOoKwn7qkAJFsoOl4a5msV6kjG0gls2CvCSEUWYPXBZm5cTQ6r7PqcmMySzPtimaMKIkW6HZ0vsYAa1bAzn1J93dA6TFNw+4qFPlDUl/lESmEZhzsNdJ4QazYmlqamywO+vz9+/u87R8qrrt5GlwlDhQuIN7OYWTfkNXOLYrEQy+eD57gysUv89I69/WqXjsfgIR0sEsqw7HP1ZHimwLanHMD/EfgwwhQ/fuc8/XOuf/hnHuBvuxnnXPXO+euBX4W+JFvtt1xfPfGYrPI7139e3xp25dWeijfdjzu+McxjEPec+N7+NF/+lGO+X+P4fXvb22QHkh7M46jL7pawbd/7e1cdtJl/OITf3EFR/TgY7Fe5A3//Aauue+alR4KAM65dwJXAWc75+51zv0H4LeBZzjnbgWern8DfBC4A7gN+HPgDd/qfnI3/6lMq6WMjaNKKRVvU7o3bGWTit8sFE2sD75N9Wpa1m646DblPR19qOr4bF924xfA6jsNFtrXAAqyRWsYVDYgzK3oYxtlUL3z6jVrwEvAWEyZYUylc5NpGbtyDK8pXgMdKaXiUds3gAtqXi/jsgIu0ROLL25UyySv3rnGTDvnqfA85pxFXvPSzAuemZiaDC3T50c1r8V5AijoTuM5h+d4wpIU5i52WEdLh9vntuhLU/c6tbpSK1xbNmPKf04XML4KZO/ACzseqkp+18YaKYmcoQBnXDmfeEf2qqHVOeiUFS8stx1gduXaeQXxcg3kuvtg51S8gUtmwVSsygKX06ZzzjThBiBlISMhLZvF13hhYbFox+VzkzuyZFfOa1ebS85cNBhyU68aPeddOUZu/Ztzzp35n3QxpH60oSKFSZKbJjOBVyY7Zys0PIJmuHxHm4+uAPLpGFlyDt+vgFSOWz/9cu5z1wItl/+nzhxaHt+Shjbn/EHkS6v72K91fv8V4Fe+lW2N47s/lpolgKOyKOyZpz+T3/jUbwDw5Z/4Mu+/5f2cvOZkAOaGc5z0+yfxuBMex5NOfhJPOvlJPPq4Rz8s3RBSTizWi0BbPHfvoXsZNAPqVNOkhjrWrJlcw2nrTgOk6KqbRnM4Ns1s4pS1pwDwtZ1fo+d79EOfXpB/V/VXMdOfKdq70crVbz/2Le7jc1s/x0fv+Cjvv+X9fPCVH+TsjWfzly/8S9ZOrj0q5yzAzXtv5k1ffBNPPuXJPPb4x670cMg5/9ADPPW0I7w2Az/94PakwALpaGUFUeS2SEzIqPaG2TV8XzYQ2aLOT3vebrKyj1ajHKMC1qzMqLKt9nhWUJ2zNGBIJjvo3LSt1adTJi4Er5pQAZfmAytMcy5dw0IIBFQa4VSXGKyj2Oi5sfG0qWKRKqAMqn171a4trEGBVNFRJl/S7N0WuamcM0nnPvrRPVbN7GXV1Hp6PVgcKKsblxndZytSc6PgJSX+cPf+co4vW1zi76YniR0waUDPthW7wFXZSWPb7fsid540GYQoCmxx086F4neq1yh5sUszcORs7Dq3TJObk0kTlutMrctby5K2BVDyYM52XO05Ko0HyCSb546WtVU9bVbZg2hQVQ4SE73Od6UVnOVkrgMi9eiyu3ZOk3n8Ak9aWOS4GPn9qVXtQkcdBLq2WrYgtOO3eW6sb0qZE46bxKdDzA+mODhnxZa2mhn97I3IDuzaFXbfsbZJHOgsOn2RlLjOsRj73AGvrl1iHCm+q0tqx7EyMWgGgKRAj7a47KTLyu8XH3sxFx97cfl7oV7ghx7xQ3zy7k/yKx+T9Vc/9Hnbi97GKx7xCvYv7ufWfbdyweYLvittn+aH8+xe2M3BpYMcWDrAwcFB+qHPs894NgC/f9Xvc/Pemzk4OMjccI6FeoFzN57LHz/3jwG47C8v44bdN7BQLzCIco2ff9bzef8PvR+Ax/z5Y9gxt2Nkn694xCt450vfCcBT//qpzA3nRp7/8Uf9OH92+Z+Rc+aiN190vzH//KU/z+896/eYr+dZ9b9W0fM9JqvJ8vPGx7+Rn7v059i7sJcXv+vFTFaTTPWmyvOvfMQredYZz+LG3TfyzL95JvceuheQxdaTT3kyC/UCcPS3jbWCtqO1KcSDDechoIb8nZuhsYfGrBqDl1MW43d7v76uy/p1b6qmM80pEWnBhlVdGzNmt81eVY0AYQN8BiptTOY7am1MlzNT3gfVvvY1ZS7dtByOrJrTUFmaXpg7T4UrI2kBgXlyZrI6Lzhi01D1eoQAlWorGy+6XANWpi3unith+DSVnqEKXmUU4H2PpWFg7aqGyZmED47ggrCXLhNjo2DdE3OkC2RyB6j99IY1/MnegwA8e3HAVdt28+6ZKd69apq7JifvB3qK+4QuYsrCxZneudUzm2hA9LEtw18KkDrHqUcNaFGSsoAui3Y2u7agzKE6ZYdKD1DbLAkDyDLfqo7OVRlOXJmX5tigKzKx88rIbLEFDAGPJ1OLLZdTD2SEkRWwrQwuneuZPWgBnVP2uQDuFoHjUualcwv82r793NKreN/URMv+I/ppyxK089bsy9L92HSP49Tjl3j8ozzz85EPf8Zz570mf2ilBu3nUEGqnEiVFThSFkeN9SlyoCz+5PPfU0mKxXImGb32pXrvCDEGtOO4XxzNDC3AO1/6znIM3dg8s5k/ed6fALB7fjefuvtTXHPfNTxi8yMA+OgdH+Xl//ByHI4TVp/AmRvO5Mz1Z/LLl/0yp6w9hb0Lezk8PMyWmS3/ZsCbc+bw8DD7F/dz8lphkD9824f5yo6vsHt+N7sX5GeqmuI9P/geAC5/5+V84q5PjGzn/E3nF0D7/lvez/W7r2fNxBpm+7PM9GdGquafdurTuPiYi5nuTTPdm2aqN8WZ688sz//Bs/6AYRxS+Ype6NHzPU5YfUJ5/t0vf3dpK2tfXCeukVqgTObdL383dawZxmH5uXDLhYA4T/z6k36dpWaJQRyw1Cyx2CwWdjfmSPCBw8PD7F7YzWK9yFKzxGUnygJl7eRannTyk7hoy0U8+rhH84QTn3DUzs8jxRfu+wKT1SRnbjjzm7/4eyxKi08hA8kdWZCByBQjLgQiLVvZGsi3oKgLZlpwKTfq2GFqk2pp7X1dTWmGAlwNIMeSghWQG0Io7GFX9lAYXDI5CdCyQjNjhwsDWFK6GWnCOcpE2bb7/b50FNPisKgFbTkn6joTFCA3yn4WJpOMy6pF1CIkuqBH2WipZIfkIrfdtsgxGyqGgyGOHjGpfVNUH97cYXdTJBpQzDIej+MDU5P8N3+YzSnxzpkpNqTE6w7P85OH57mlV/Hh6Uk+Mj3F9b2qFPAVtlZ1z90UeFGkmMY4t98/Bv2NDW2aqNphY1WFWTUdsklZUgF3UqRkLK0BTrds2y1byP1AFq7VB6ck9nE5JXo5UWVX5nfuvF6OLdJ4T3KSmbACPpMVFEbZyQLECiFTing8MSaV0AWsoG59jDzj4Bw/OrfA6U3DNf0eP7NpPQM7b6RWXqHj6WY6MiY/aKULKWVZ3HAQ8FQV1HEVOaU2U2BMeWFYbRLbycxk1zZQOK6O3NerRE+bQpHmVFUgxqjSHftc5/ZidMZ1pBgD2nHcLwy0HK2A4RWPeMU3fc2mmU289LyX8tLzXloee8qpT+E9L38P1+26jlv33cqte2/lihuuKN2n3nbt2/iFj/wCAGsm1rB5ZjOz/Vk+8sMfYeP0Rq64/gr+6eZ/UiYllZ93vOQd9EOf3/r0b/FXX/2rwrDWqWaqmmLhV4VlfMd17+DtX3s7071pNk1vYtPMppLuB/hPj/tPvPrCV7N2ci1rJtawZnING6Y2lOc//tqPf8Nj/u9P+e/f8PkffMQPfsPnn3n6Mx/wOe88Lzn3JQ/4/GQ1yX978n97wOc3z2zmE6/9xAM+f+yqY/mbl/zNNxzf0RyfuudTXHrCpQ87+UtWVkq0oS27Y4yUsWeSQh8FrgYgAXJKVL3eSFq1q6t1dNOguejwuhIEYV7b4iMUuEgLWWvKIBXsXfBaKatr4NmAWMyZVDdUuSrg2XuP76TvpWuYgk/fes7qAPT/ueO+IAVt4jAg3a16eoMfWgoc6xYVWjBYxtbpBOUs1a6sZ4RtOyM7Dx3P9dcdYn5+iPeOJqqmUguYhOFrSLQLAenC1QKNT0xO8IMLi9zcq/jrNavYGCPPmV/kOYtLvOHgHD9zcI77QuCqqQmunpzk6qk+O5Q1t7HGpiH0e+RlACZ3U/dFtqCaYmW9y0nMgoS8nCwBls602Qp41QJrJkfW1g1rmsTa2MhP3bCqiUynxHRsmImJ6RiZSpmZFJmOiX5O9HKWn5Spcv62gFUN1N4xcJ7awdB7Bs4xdI4l71n0jnlg0cHS3AKLDgYh6GOOgOP4pQGPHAw5d1gTgOt7FT+9aT0f7PdAnQQU01Js1/S6JbI2VmtlCyJpsM9MpjeR2LxpAnLNYOjYsWMJ5ycEgKsMxq5/V98agi4YvNfPnFy2E5qGz09PlmYbPkGoXJF1eNdqtnOKKv/BDuABYwxox3G/OGvDWSz96tJRKTn4t8TG6Y28+NwX8+JzXzzyuH1An3PGc1g7uZYdczvYMbeDXfO7mK/nmQhynrYe2spV914lqbLOjxWiHTN7DI857jEFjG6c3sim6U0l/fOHz/lD3vz8NzPdmz7i+F54zgu/g0c/jpWKJjUs1os878znrfRQHvIo7gZJ0pzJmiZ0AG32uQDHbpTnFTxa+rctdJKbYGN95JcZv3dZ1ZIy7fweUxKP2ND16Gy1uyZDMOcEkz6YTCKq71XXQcEAWPBSdR6qoABRWt66Uew28rdDNLqtnlOq5StdCESzxkqZ0LFh6p4rp2Mw7S6pC0A8d2+d5q1/fUAryyVdbgCim1Y2LaScCnlRKaxLiT9eM8OlgyEfmZ7Ce89e53j76ln+Zs0q1sfI0xcHPGVhiactLPEDc7Kgv6cKfL3f44Zen5smJ9g5u4o9MZE7i5hi8+UcwRn/2gGoRja6NmU9kRKbh0M2DWo2DQdsqms2DWt5bDhk87BmXdPQyw+MlOa9Z8F7FoJn3gcWvGdnr8fCpGfJeRrnqL2j0d+HHoaI65gBvUJaIhIFB/iUmEiJKkkL4wltZdxPmYmcmUqJ2ZjYmBJTKTGV5LGpnEcq+g87x9cnevzJ2lV8YKLH7ZNTZMTGznUyFubPYO4JZueas9rRWUbCmhwk6bo3VfXYslkWRI2bxJpUGFtuMoblchI7cOfabmXr65qZlLm3F0gxUfUqzWgkfFXhkitNO9oPQLvQS0UTcv8YA9px3C+6NizjaD+c5246l3M3nfuAr3vj49/IGx//xgd8/scu/jF+7OIfe8Dn106ufdBjHMfRG5WvuP4N15eWzQ+n6FoFQQuaujSMaSpHQGEHeIIWzTRNYV67rgYGXk2na+C2KwGwG3mRKDhJtdu+7XmTGvjQSdNmBeX6t3OOZEyXjqHocnMmNhEqZV6dxwUPKeGyAOruzXpEguEgZikvijlpk4SET9r6VkuPelrRXlrfpjalnmk7jeVk6WZLtTdEpPmCzzWr1/Y5PCdWSaFqK9mtKQCaNh85B14Y37tD4LJjNkinNfUABtED7/GOd81M8Q+rZ8kxcm7d8LjFAY9eGnDesOa5C0twENi5mwbYOdFnR3+CXf0ecyEwHwLzoWLghXkNgM8wkSJrmsiapmFt07C+rtk0GLIm3t8tYS4Edvd77Or1uWbNFHurHgcqz8FQcahXcaCqOBACB6uKwyEULXXRQUNJobdzR7SzIg1xxd3CGjdAR1IAJEW4rswf1Wx70fmKsZjMpyZG6uGAqgp6zjNVTEykiPcVe5pYPjHSyjmOSgnUesx8iLssqnWfMzmG2bzZNIwpUgUI1TzZwc6dDbgJiMg8T46IZlXo+tBGXWBJ05AcZbF5zqLUb9w00S/Pd3XwpvOVNridjEXRgOiH4QgxBrTjOGL87md/l8VmkV970q998xePYxzjeNBhDP3DLSMCqKRQWSNn+rjcFs8oq9hN5eeUpPmo3jhNUmCdiEaKWRS81nVdmKeo/eRzbrsTWdFQ930mNwDUMzRTK3ipXOupWoptnLT1FEDR8cYFKgXPKefSfSnFRCTikgCPnhYb2c26ZbnMtF9AsOxLWbUqMD8hMpV1CCNrQNWOsyu9kI5NVp2Ovla1vsrmnnNm4KLzVjO7uuJD/1pz97YlcpFJJDJSqGXM9IiFkskddYxdxk6cJCgLDgAXAjeFwI0Tfd7GanAw3TScPax59MQ0xwyH8jMYcOHcHDMxMRsbqgcgUw+GwEEFpNv6E3x1dpZdvb6C14o9/T57JyZY7PWUoM5l0eCyto01RlGdAEzHm7NYhSWdY96kIna9Rqa1FWvJwsNaDY9eV31M9aXakEsKyBRfWlGY957B0hJhZrrMt4GDJZ1/qTMHLbqLtCwIuTiJyHhAurvJ4NvMiG+3pRmPmel5PUbPnXcOadIU1iiwNCqxpgypm81wOFfJwq0SPey5QwH6N/V7MkfNIze1cz+npm0aYRIZ2iwM+cgTYAxox3HEuHnvzbz7xnfzq9/3q2O2dhzj+A7F/sX9POJNj+C3n/bb/PBFP7zSw3mIIxOCI+LwBFJqcE6q/nP2IzdoA0+m++y6GVgBlxnXd1lVY3+KB6mCTmiZXxDHAQO+9pzZdeHQJgwqU0hxRGZgafi2MEi22zTNCAgO2sjBV+17ckYlF62hfFsI1akct3t9EhCbcixM1l7fA2DtYAh5RvxmG2ESkxXSKIOIkxSysYzeXBE6lePHHtvjlJMcoRdYNX2YFGtypvVJzbkANOdMl2uyBlpgo6AQRvXL3UWARWETMyxUPa7tTXDfps2YPZfJJOy9vZiYykkYQudocqbxXppLZH1XVvYziwWb98J5joBR7QjmtHjJudYDtltln8vCSxjhJkXMH9gFVxwx2qI1PS5zEkDAqTHsSrOX+Syg0kywzJhK5zOuaMTLJ8c6fXlxCPAd1rK4RijcFmTsy3UTf92mXBcvCYLOAtEAKfpZyCQ2cvWXd/PoCzczTAtlfKMSgyxuHb4qnflyNqkD5aRctLDIPf0eB4N6zeqcrod10fdm1fM6HN0G2zlTLMmOFP82U8hxfM/G0059GgeWDvDl7V9e6aGMYxzfs/G2a9/GtsPbihvEwys0/a/dnbxvW3ICI8UfIQR6vR69Xq8AVGjlAlacFEIoP63UoJUrGGta7Lcs3WsAtqrKPszT04Bpzm3nse7+jZU1Q3rbvv1A2xyiUaYXrNGCShg64L0rPxQg5UsXLZNamNcqOPZoIdSmJkoHKmPmtDmAD6HQh2bZhWsrzo2Js9+v+/pemhQZDJc46cRQmO2sBVQU5q37o00InI3bUvTtwmI0zd0a+Hd1yI2exyY2pWDOYJ44IgiIa6rA4V6P+api3nsGIZBswaCLD+fQhguu+PsKy9pqr1XSej+231oe2zHYX3Je5brJHBtt+yqFfknXH7pYcJ3t5NwWR3mn8oGEV7/gpGytacLL2NU5wXxoMdlDOae5ANF2ni/r3NVh9uUapGL7ZRZb8pmx1ZMVGWa2bjvMF766mr/4u3nu2paQfluj+5fPblvQKZ9Hk03oJlPi0QsDvjAt9m3ls5cMHHcWetn6uqELIzmfrSXb/WMMaMdxxHjqqU8F4F/v+NcVHsk4xvG9GSkn3vzFN/P4Ex7PRcdctNLDWZHIKRUQ29W8ClAdbdHZ1bJ20/0FVHaKX0wu0AW2MUaauin7LpIAS9umJK10swASH/xIAZixs3YTD2YjBWUfTdMUAFyAp4FgTWGnmEhNLMWizrliX2XJ6y57acfYWollUpSbfsqRgYedVeC0YU3w0o0MWnDWLdgSv1VjFFNhFg2X5JwY1GuJeS0xz3LyKZNUPuNdC9662mMbf3ecBmqWj38EXHXe132d945erypg2xYVkHF6fpwJWE1Q6TzOBQFFWaGeK9zuCPvsvDSYMJBkwN9WTzmLhjW70QUEII/pdkXrLC0RHJRFTgiBUBZmLWNr3eZKGt6LVZq1cRUNKwW048B5OeeVVxeQ3IDTTmJ6nktntc6ctmvvndMWswYyW+a4BeKtprbL0LZZAjvVkhUYDBKxEekBnX2W1s3ahc7GYL7HOUMIFecMhqxJiS/PSrFgERnkVhID+nkkycV25vjctjTueoF0Ywxox3HE2DK7hcef8Hj++tq/HtVIjWMc4/h3iXff8G5u3nszP/u4n13poaxQjPaOb5pYNK5d1s7+hVF9LNiN25ebZ1PXZZuWoq56VZEDmFygdAmzAjG9CYsllxbndMCBNDZoga3sozOGZayv7cOYYdO79ioZS0ZSuU2MytqqjtfQDB1G0ck+LI1rvqhtitlxw9Qk5y0NSjvYEBTgeZM6GPBpNbTimtBae5Glk9ncwiK33n6YpSWY6k+wakbZbRyV6h1bfWRXL6uv6mgw7cdAcNferJzzZcwtCAgVtjkTOgsXuUZZQWmrYTUmN4M2BVCwa/l+PV3CFhYaWZhgZZ/l/NBKMfQ1xs6X5wvDqfugBZitBlvG0qRUOtA5JwV3dn3LYgqniydjdNvzJ62SPRP9PjOzMwUgu4LBXZkTlvZfvlAYYeJR1tTZdWrdP2zcpodNKdOf8Jxy/BQh+I50x4/sY7StdJtliY0135DHYow8dW6RCHxmRpx8KmW5jY0Fh/OtB3QbuQiMq6qdz8tjDGjH8YDx04/5ac7eeDYHlg6s9FDGMY7vqcg58xuf+g3O3XguLzvvZSs9nBWLLkAwsNGCr86LaOUF3X9F89gyhQIUE03dtC1ss4CiEEIBtgY6h8NhMayXG7OwmznF0i3Jtt2VMoiedBQcg8oIzJeWVk9rx5GzMLveOaoQ5IaO6QwzV111lcCywmiqxjY2bYGasrWGqDNww1SfUwY1q/WRGKO03m20gUQwICkSBysuI9N24FLA38TAocM91q5bw8yqac49Z2NBUFkr9AG8D6OAGAO1bSrfrlF3QVKuVR5thW2gxq5t0EK1NvWsFKPTdH1nbngnel0DRcUqy7XQR44vKdenxZgG/lXD6oPHK4vdAr9W1eoxcEqxlSpg2EC3pu1NPtDEhqgVX9aZTIauwNx7hNB12sJXjt0WP0X/XT4OIv3wJZ1vLhpZZSZZJQztAiJ4sWCT+e/p9XqiKfa24JDHheGXbU32Ky4+z/EDlycue6xjctJY3m4BmsMkE7JAjXpekUK0AvRlnE+fW+ArUxMcqCr6vV65xi54UxQI+E1Rwb99N5TcBfv27bsfaLcYF4WN4wHjVRe+ildd+KqVHsY4xvE9F845/uYlf8OhwaGHddGlVVsboANouxVZfrT9xwBwaXSA3ORK44FOuj7nRGxaiYGZtS9Pf4vuMVN5uakG74lRb84KXpcXlhmolmNIxVVA0sttar4LHFOMBXCXtLs5DChImpubk3SwATfnWLd2DTNT08wtLhaAMxwOhX1W/eN101N49vPIw/N8Zs0qFB8QqqoUylVVj6R6X4vSpABpTmCA5c57hpxwwkHmDsNddx8El0sau87StazdTpuyl/NOhw31I7pVYbODMNLGFo8gYttGCxJNJpFzZ6zlfVl9d11JRBt4MgmHgEEFV1qkNTJkJ9fKrLmUJ2R5xzp0/LII0GYBKRYglgyQ59zCsKInNSDvcUEBnjLMZplV+F5deMnciiKDSYmlpQGhI4NxyvIKKx2Rzr3K7BemttU1J92P91a8FwrolWsTIEfA413ghGMSl16cmewHHntRn3u3DblnWxI3BucIPtBEKeT0wRe3DueyWtGpxEOP44xBzdmDmt/esl4WLB2f2VZahDpzNFz6uMeVz61dG3Lm5ltueQDBwRjQjuNbiJv33Eyd6tIidhzjGMeDD2EfwsO0EGw0fPBS+BJdAaRdv1homdluO1B7HLRTkT4RvMcFAxDhftZSBkK7hVXmXZs6TGvR8+JIrmWFl7fbdcvGmXMuzQq8F7YvIcA1aaOFJjYFQPgsYDz40PGFFd2gpZRPOeUU1m9Yz+L2HSPODd1j+tLsFHPe85SDc1w5M1XGZy17nUPAvXOl+QLQ8R9FtZ/gXebebUv87d8vAYl6KEMK3lHXCnq1Za4tQbraWGhT4F0tcfu8gi0PPku7WO8DKepl67Ci3nXaFtOVD4je0itAs2voEHLWwG/OooVw2Tx8jT2289AADpcllZ4xi65Umg50O8eZBEGOLSkQFRs2csv6gisdyXIWbW92Zs9l7SBa/+OcBATa9agbWSzE2OBw1HXdkTP4oqN13uOR8RZPYdq5m4sQA6JeL2vO0WrQU9lGr6qIdc3aNZnnPn0169aKDOGarw25b7tazjnTBEPlTDfraTvFOZVstHMgeM9L9h2gdvDB1bMFZHsftLmJeiarpUHlPWvXrpZzi84JVdIeOHDwAWWQY8nBOL5hNKnhGW9/Bq973+tKEcM4xjGOBx//8YP/kde89zUP+KX88AlLI7epavt/l6EzcFRax5Y0cVdXmUp1fNbCLZMYdGUC3SYNOUvjA3sNri0eK2nvKhRW1Ng5oKTybTvLXQ1KkZkWiYGyWlUlVfha6NPEhqZuqLWQbDgYdhg+2V0TIyeffBKxafDO0++L72y/35fxh4pY9fj06hmefHCOvoLHmKICqqTnWECYc46etZn1XtPnrgA6gBgFQC4NhpAHPOoRkWM2is0aSVLa4mmaiq6y241tFOBKdM9tey0imUSMtSSvU2JpaUn2nzJONaqoPresXFodSnG58JpaL3pLw79d+YG5M+g2VJZpkw46+uuuDrvrrNGdh35E/4mC6FZWUYBlFiY5dfS/+iLNTqCd8tq2zDF1m1bkkaLJalnGwPt2fN0iraAFaGV+OiBHZY7lwKsq4IMjeBlDfyJw6cUV69c6Qm+Ce3et4vNfGhbZRMmAoO2QVXdumtz2HAWVMAQmgeftP8SVq1exv2fss1ynpG4L9t6cM2eceQazMzOaQWiv/959+1lcXHwABe0Y0I7jm0TlK37jKb/B5+/7PG+/9u0rPZxxjOOojn++5Z9585fezKbpTQ+oA3v4hN24pfIfOt6wuQUGcZluNqdU7LUKYO2ypDCinx0p/irFKxT9a9M0Izd903yaa0E3RW9+taZJtTF3x7ecwbV9NR1ALQVZXvSOwRf7ooXFRbZt316Ow8DMWWeeSa/Xw2mqv23jK+CzaWr+dfUM62Lk0sPz4Nyo20HRYWoVunNUvUqugTZJGAyHsiioBYSnmKi859LHruHJT5zhRc/t8YTHrGFy0uFdoNuO2LSuwvy2fsDlGup5LgV+piZxtqBpC7+CD6LvDEFkH9qdS9Lj7WemJPI7TP2R5CQpx2XXKAnGzeBcENCcEDNWlb6YKmGUWbbxtmD6fsVvapXl9ccGWpZqykBnUlmsmdxAPxGFPS9vdDLvAHXQaOcctg2MCTe2NJdtita31aiLjtoVP+L2bDpCgEsumOXCC2chZA4v9PnYlQeoa1TTKqNMSDOYdl2RCkAunwld0MUYufzgYTbExLvWr9YCx6htnylyG8jFym79unXqt2zXQq7lPVvvZf+Bg7RLvtEYA9pxfNP44Yt+mMef8Hj+07/8J27fd/tKD2cc4zgqY/vh7fzIP/0IF225iN962m+t9HC+KyLGKGAuj3aeamJTmLwus5piKjrUqCl84+16vd5IkVV3e930d1A2y7podcFWKTLquBV0fWrLNswXV5shdMcqKdRRy67lQFlAUyKTpDisqqibhoOH59m2bQeFjVSd4epVqzj2mGPKvtFzkGImRhn0latm2NWreNXu/cIoBq8dwFqtZFsJD3UtoDWmWBYNJnuoQkUVekxM9Dj2uBlWrV7N2rU9nnyp5/sfF1k1mwi+ElYxjXrKmtTVOVeK8Oz3dgHiykLExuor+TdUxnrSMoIdNh5N2xugE5mHsNFmuWZALZS2W3ZGFbDmZPyszCdtO2uabltQLffQzZgml7JIKIxshyHNKWlDAJF3ZIQNb+ngwj0TNJ0uRKQugGyfzhVmN2MsLaOgObdFc4UtNxG1McAm/bDiwI4UIKeMD5X46/YcJ57Y0OtDHSf554/sYcfempRVx5ozuKQuBLIgsGYboQo4r/piHUsVAgH40T0H+frkBF+YnZbr52Co3fvkswKpSHE8Z595pq4bTBMMdRO54aabqY/QythiDGjH8U3DO8/fvvRv8c7zA1f8AIv14koPaRzjOKpi0Ax42RUvY344z9++9G8fnm1u7xeusHEhtHpUSfGH+9lhgTJYHWeBAoQNtCLAoutm0C3gsm10QZYxT+Jl21qEBQOj3UYKqWWgYpSCoCOxv8budgFR0ZKCpMpjAryAdNXFhl7FjTfdJBIE2qKtmZkZjjv+uBHXBNNfGtOWqsC7Nq7j0rkFzh7UhakzlF7XNTFG6mFNUzcFAIrtmVX2C1g2b9Y6wgc+uIcvXdcjpnVkV3PJxWv5oRdNc8zGJazlQPBBf3wpXDKJRldDa80zTAphiw8DqAVU2wIkt6DT0epPldgsGlByJip7afIBVXHSIQ512ikj2GGRjUyVxVLL0hqBWdjdYtfWNlFwiHtCTlbolqVDW/AK3EUjvXwOjoLN1rGg6EudUxcAsZ6bmpxiYmICc/ZwehLEAk3Pb4dz9d5T+UAIVZHfSHZBQLFkORpOP2WSC8/1TFY1KXr+9ROL3HHPJNfd6Lh3WyaoJnZEVpOtZbJTyYJ8Vqoip7GLBM8/NMfJdcNbNqwZZcqTyUoc4Km0HXG/12Pzls1ljmeVlOzctZvde/YUT+cjxRjQjuNbilPWnsLbX/x2nnbq06j8uJZwHOP4duLmvTdzw+4beOuL3sp5m85b6eF8l4S2yiypUkvd+sI0ASOsJDAiL7DGAMZiWbrWgOXywjL7tysjMARRtIFJX1ue7hQ1OWNGR2UGQPHDBYoedDn4tOOTFKpQVbkDymOM7Nt/gLrTAMLGf87ZZ9Hv97EiIgEQlaakRRP77o3rWPCOH922sxxDAW3q4uBUMmHHJsV26hShgCwn0XDGpmFYw4c+tp13vXc7B+en8d6xbk3kBc/2HLtBCrqCdjvzTjS2BaTSsuOApv8bElHT7q2dV3F/cFI4mWglAoWmgxa05bYpgGBWbVagOlVj/iVzP6qLXd5tyjlfejUUQGnzUYGbMd7Oe1JWn1Udn9dxW4OE0XDFpo2sBXk+SLGgdVjDFkYy172ytsTUtuvVQqvi4eta5w7X+d0WJ/a4cxTN7VS/xzHrHOeeDi989jSv/cH1vOyF63nB847j5JOmwMFiPckH/+UQn736EBm11bLFg30eK08IjhB0Phd5hSv7zCkxESM/u3Mf1032+cjMpBSlqd0bCswlGyItc513nHnGqUXOUE5lhmu/9jUGw2FbIHiEGCOTcXzL8byznsfzznoeALvnd7NxeuNYBziOcXwLceGWC7n9Z29n3dS6lR7Kd1lY8VDLYAr4CVi3JXtsedp+1EKrCy7z/RwIirsBLYPqnadJzcjrSgEXo96pxhKbRtI0jQaQ7H2lKMy1HblszCNH7T3eWLacixVSipFhXfP166/nsY+5pGgocXDMMccwMdFnYWGRqlcVtwOxDKtxDg64zF9vWsdP7tzHu+cW+cLMJFZ4l3JU4OCkiIdOetw5YhMVYChLq8eZonSHunNr5B8/NM/3Py5x4jGe/QenOHBoUdP4iSp4gq+JqdKiMicMq2utyeSctdfOlg3OOYTWzG3BX0qgQJmgiwCy2EGpZMDS77ph0McF6KYCrsp5pE3Xu0wpziMnnEvti7KoAyTtb0JR1b7a9mmLwXKWCvxu04siizAFbW710o5W/pJiLJ3JzMYsaxe34FqbucFwKAxmvy+fidixf7ODVGDdqzzBJZyLOJ+omykymfPOW8WTnpDoVTWHDjlWb1hDL0yS6fGIC0/grnvvEylOdgyHSYrKdEE5HNb0+/2Rz0XZr4iZCysu897zI7sPsqWJ/PJJx5A7C9MqBOqmZmJiUhnx1v7u1FNPUxu19jMzrGsOHz5MTole74Fh6xjQjuPbju2Ht/PoP3s0P/rIH+U3n/qbY1A7jnE8QPzGlb9B8IH/+n3/dQxmjxDSQUiqp6XYpa3sLrpZszYqN1AJAz7yXCxsHdmX93Qrvy1V6bMWIJFH9lOAjsoCsut62ras3vIKfmNM7XXdwqRuUZEVtth+oe0oFbx0jGoQreCOHTvJeoM3MqoKnosufARXXXUNMSbRLDqxdBIzfelm9rYtG7h8/2F+4Z5tvPLsU6RNa+d8q9uU6lR96+HrpAi46zAhlfZinpRSYuu9h/mHnZkLzk7csTUwrL2AQe855YRFnvXkQMyZu+9u2LUn06Qeh+c9920fElOflMC7ipy10Cu5dpHhjdmW69DvQUoNjzh/A8cet16lJrBt+wFuvPkgq6Y9p5+xAVzCEUgpM78Yue3WfaSUOfGEWaYnK1JOxDQgNpkDhxOHD0UmJism+pCTFuvFRNN46uTxJDyRqFZYWYvWYm7IyUFw+BBHzhPOSVGZF12qSGCytNFNo9Zfzgkg9ynTkMpbnRP2OakGGwJJn7fFhwDtBseQ6SlYv26KNasqYvQcOLDErn0VG1c1PP/ZM6yaaciupknwd+8ZMjff5/Zbd/F9l6xn2DT0+33mDjRs27GXw/MzfOVru0Q+EcVW0GmtnFd2vNLPWwheFkS+dXhIOeMUwIt1WeC0pQE/vmc//7J6hq/MTOPqmqZpSqcvh6NuGmHHVZoyMzPD6tWrVV+CTVT27NnD7XfcBSrteaAYA9pxfNtxzOwxXH7W5fzWZ36LpWaJ//2M//2wNocfxziWR86Z/3Hl/+DXr/x1XnvRa+8HxsYhYR2VlNYqBVUjrgZ5NG3dBZlWFe+q0ceEkRxtgQvgwqgFmAENKyBzzuHSqNesMZjGItl+LLz34CljbNSCy6KwuwoIrMo/JSlqE3JLwI8cH9x+553s27efjRs3tPtxni1btuBDgI43rlcpgY1tPif+32M38vt3b+c12/fwls3rhSXVbTjvSQpafPBqJdV26cKJfZMrjgJWjCXbGNSOL37dFf/QECpyhkc9corpyRpy5IJzlnAEIDEcwAc/MeSWrYGZGXjK4wZsWJcLO5yBgwczH/lMYGkwISyrprV9Spx04gznnr8esse5HjfcOMWttx9iw4ZVPPXpj6TX82Qx/2XXzsPcfvvVOBqeeNmpnHjCOmJcIsWa2MAXv7ydL3xxJ+efv5lHPvIYcjxIigNydnzuql3cdvuAE46b4fu/71hgKAuuXBNj4p8/tIOFecf5Z09yzrkbqeuhAOKm5trrDnL3vYmN6yoedfEMOdWlQn/HjpqbbsmkmDn+xMxxWyBFaYvbNIm778kcONjnmE2RDesGZdHTRNi1q8e+gwL4UpSmBxdfsIZHnL2TXnBM9OaZnhat7s59M/zd+xpc37Np4wCX5/C+z7Duc+GFa7nqqkWWhlPcvnWC+7bvZ//+yMJSZt+BeVI+XOa1U29ZospmEHmL01Wngc+UkjQh0c9YbBotlPP4nPjv2/aw4D2/faxkcittXiGFh65oovGSocgus3HjRo477jhh13HgMtk5lgZDlaN4Yhz9fHVjDGjH8W2Hc443Pf9N9EOf37v697hl3y284yXvYPXE6pUe2jjGseLRpIaf+sBP8ZavvIXXXvRa/uIFfzEGsw8QznsCncKYzmmywq+u3nW51AC4nz92a2klKVCzyzri/pfJEkYq2k1zScsGLx8HtLrJnKz1qCtg2fS6BgDKwsaBdwpwY6LtvCWp9sWFJRaWlorcwBi6U04+hU2bNrF9+/ZynAZqvXM0cQjO8YlVM/zzmlnesGsfX56Z4to1sxiRWCQGel5CFSSR7pRpkxODVapH7YZVhZ6y6GY9psVNZJxvuOWmRXwzxeYtwjxXZEJIpDRgoZ7GO+hXni3rh2zeOMAam+YM0xX0e47FJU1c50zTyGIlZ0dqGjKNguAGlz2TE30MbPushVJeCpaC61FV0/R6M/SCJ2UBrRMTct5npmHt2oBnFpdnwDmmpvbj3JDp6Yrjjp1W2e4imR45RyZ7sOQza1cnTj5pSVy+kAK2O+4YkvGsWlVxwfmQ88BmI7fPJm69PdOkxHFbEk98bCC7xOFDQyb6FR+rHfsPJM4+Z4JHXzSAFEg5EJvMZz7fY99XI00zFCcI54hxkWM3TQKNSBNyImfP7KpEzhXziwPu3ZrYsHmabdsS27cP2LnvEM5V1Cnx/g/vIYQJndNDHD2qIJ3uMvJ561XiYGE2XxaZjhRDPyPWnMSFULIKP7lzL49cXOJXjt/Mvl5F5T0uZ3LTaMGdA+8BT85iX+eAjRtVxph10uss+8IXvwLek3Mq7amPFGNAO44HFd55/ui5f8S5m87lZz/0s/zaJ36NP3j2H6z0sMYxjhWNnDMvu+Jl/ONN/8ivft+v8htP+Y0xmP0G4aQahhxH9bLdtP0IG6qemubF2vWbLeA0CxPrFSDb7bgLWJf/GECtqmpkmwam7V/TExoINhBgPrrBhfu9row/MwKsjbVti19arW6KiU996lO8+tWvlGdUpjg1NcW6devYtm3biJ2Z6VGdDwT1Iv2fJ2zh/MUBv7N1B6+YPJl9vapYk1lquAqV+PA6KXzq6fgzaHGRh0aPM5p+dHnjAUfKnq/dtoob7sz0AgT6bNwEZ562moMHDrJzd8K5AN7R5IrFYcLlDLkiRU/deIIXP90QeoSqAjwpe75y7QHuvHuRfiUs364980Rg/8ElvnbtNvo9T/DianHg4DzBi5XUXXfu5NDhfVS+US9e2Ld/ATIMBg0H9g3woaEKHh961NHmVmJYz+N9g3eTArZUAoDqu6U7ncdl8wIOWF8u5wI5V8oae5xrdEFibH8AArOzIjOJSbqYLSwMgcDhw57+BHgCTVNDEr2vOYBs215zyx01w8Eiderjqx7DZpo9+2uaxtEM+rzng4nQ6xNjQ5MjOToB+6pzTTEWTfJIBiKK9mFY14QQ1KPZl/1b+9ycxG5O5DM6n2LEB88TDi/w+t37+ad1q/jntasAJ01BQiiLL0lISIvpqnLEJpGz46KLLtL519Enk1kcLGKJnJTiA36nugeibr/Tcckll+QvfvGLK7Lvcfz7xqfu/hSPPOaRrJ5YzZ6FPayfWv+AthrjGMf3evzpF/8U5xw/8eifeMj37Zz7Us75kod8xw8iJicn8oWPOHcEUKYU7wcyrYDLmFhjF72mznFyw7QKbBBgitcUe86lF7zdUOu6Ln939bm9Xq88ZvswCYOQSiodUDbWwlLnI5rflIpXKWgrWh2njSMoq2U6wpYhhU0b1vPDr34lkxN9Se1XYsF0z9atvP0d7xyRsbSWYeZZGomx4azFAX9z5zbumOjxYycfx1K/KsfmlIWteppOdgoytJFBExuCDwwGQ2LM+OBUJiGV7d3rM1Ic5BwZWQCkHFVfbE4KmbWrMl5b+zrnFZg7Ds05YhTmrt/vs2bN2rJA8V6aLIi2GZWpUNwAHC1r6JA0uHNR7KzIMhe0RW7TOKYmPRN9j/eqafWBQ4eHLC1lJiYc69c7Kip5T5I0+fbdA+rGsXo2sXa1aItxieAiO/fAoYWK2Sk4bkskIJKN7BMLiz22bRfwtmVz5tgtEHzGBylCu/mOwK69kZOObTjztEpT8pmcPDfdntm2PZNSpF+pw0FwVCEzrBsy4hYQkzC1js6C0LsiI/FF19suBoX9biUv0p5ZGz4Ur2O5jmJvF8qCsEh0dH43TUMIgVObyF/fdg97qopXnXECi6rJ9Wr3JS18E71en6ZulJ2Vz+309DQ/+sM/zNq1a0g5lgXg1772dT70rx+l1oYfzjnu3baDpaXB/VDtmKEdx785vv/k7wegjjXPfPszWT+1nj99/p9y+vrTV3hk4xjHdz5STrzpC29iy+wWfuC8H+D1l7x+pYd01ETrSZmJORbQYu0/QVuCenMpAK9+mmY5ZTfglpxpfUFBoNRIcZaTLlpdSyl7r1X6d7uGLZcaFICbOiyrFZJ19LrZjep+rXiodFyyY48JH1wx0w8+UNcN+/Yf4I477uC8c89tj93B7MzMiB6365GbyXrTF2B9Y7/iF07cwv+5Zwd/tHUHP3P6iTSlqMaM+ZURc57hcFgYahw0NGTMJN+TvcBHc2UY1Ya3jF9Gz39H+oEuNg4czoJKy2ltC6+8T9SxoakFJPV6Pbk+USURoAyznD+cIxVXA1SeITKInD1No8x9QvXKwqjOLWTmFmJJdYO+PycGA9i2zQMNskevFmii6Tw4B4cOV2S0ii1HsfzymcNLmVvursiN0e5Z5oZOmW07Pdt2gfOZnMS6LaeMy5577gts3dbI384Tc1SrrsxgOGSimhCNdoKYHXUE73O5htaGNwRfdOkiw5C5VVWhZC+6i8NyDZWFretavW97NI0eoklNbH4rSxq8NP6oqoq1w5o/uWsbEfiZk45hPrfe0DrhsQK4GCNVVYmsRC3kzjvvPNatW6szyWmTjMzi4qL4JruOfdkD8LBjGm0c/25R+YqfuuSn+Px9n+e8/3sev/zRX+bQ4NBKD2sc4/iOxZ377+Tpf/10/uOH/iN/f/3fr/RwjsowYAptcbPv3Gid1xt/hpgyjTYIiE1baW5FXsXLU9kpbWMgLV27rVddW1w20rzBjUoTljdFMKBrzK01UIhN7GgO/cjrwVKy7baC96Vhg/PtsaaUaGKD91IBfu9920sDBxQcbNq0kYsfdZGwWJ1js+5q1uo2hEC/1+dza1bxaydu4ZKFJf7PnfcxYzpkxO9VPHATsWnU9skVRk7Av8cHlSCoKb8UpY1KM7q+u4B0/fIV3vUwr9LiFCHySdEey8UQMOzUM1XnhDDWbZEgCo6dAbbcFrQJw43Yeuk5t9fk1KbGzQ7OYVX55jssLXHL60jELK1zJbWuID07eVybcKTsyBGxHUvyu+JnUka7saVSABlToqklxS6PJT2fiRRFvlE3sshLMRNTpur1WBwOWRwM1LUhloVgip1CPtWzep0rInNQINnxTia31x40M6AWZtbOWD4b7YKkm+Wwz44twlbXDW++ezsb64afPukY7gkea2cMVnQpQJ3scAQc8jkyx4NeFVSDjko3HHXdcMNNN+vCNRWZ0XLdfBnvt/vlM45xPFA45/jxR/84N//Hm3nFI17B73z2dzjrj87ipj03rfTQxjGOf9cYNAP+92f/Nxe86QK+uO2L/Pnlf867fuBdKz2soy7MWB6sNad2I9I2qS3YbE3jUTapgLFO8VW7XVe6J3UBaNchwf7tAtZuxy/bdrelbYpSfe18C1xNj9rEprTRNacDa7ZgwLxsT8GIME4mFzBgKzf5ECpuuOGGtkUobRHb+vXrCX7U59Y0xyEEbQFsjJbnQ2tX82snbOGSuQX+9Ja7Wbs0xMzphZhsgXa/32uvhXnS0nZHE1CqFWY6JhuXXTPr9tZlxY3ZNhAm22ut2dpuYS1Dn3PuNDxoNdXdhUMu11OBLUUhMsoOd3SXucu0K7Ns57/l+enMEWM0O215l4dV/+tYUud9Xc0xHWBoI83m9mEsZLBjsyyCLhCCL3Ow9bmlbQZi2865tGyWfbWPt+fBPgujshthdb0w/XakStO20o6WjV9dN7zl7u2cPhzycyds5rqJvhZJavc733bHa8GysMb6UWZqaorHPPaxdE++U+3tvv37ivQBMr2qd6SzD4wB7Ti+A3HcquN424vexudf93medMqTOH2dSA++tO1LzA3nVnh04xjHvz0+fc+n+aWP/hJPPfWpfP0NX+d1j3rdAxYqjOOBQwzk4wgj2mVSW5us1IJaJ12bDIAW2UBqmUJjTAuD67SNbSdV391n2ZcxqJ1WoSM2YQh4tSIwKyTrAix7vLxHQWXwgSpUo/NE2UA5BrUqUtARo7TinZubs5cWwPfICy9icnJqFIgUgCaFTTammITRe//aVfzcqcdzymDIO+64l0csLCnolPcIU2iFbrLHmISdbGJD00TxS8Xp+ZSFhhRNyU8LsFA9JwVw29iz5OeFqessOgw71XVdipZKWVAG5VAxpWxW8JgxrwV5bbFrO8J16D7mXMvimtbUJAmtV7BKBxxlOzhjg5dby9GZk50OdQpqDeja+Mv1V914AcOuPWfGPFvbYrMCi0m8Xg34F8YyUxYylvXAtNXGbndkNgaWu4WLRf/tOkWPqT3zlX42qlBxfBN56533cepgyM+csIXPzE5j2mw9wSVbYO2UpUuddT6TM9HrVUxPTeo5k3GknLn5ltuITSwL33aKH/m7dgxox/Edi8ce/1je9QPvohd6DOOQy995OSf+/on83L/83Ji1HcdRFTlnPnbHx3jTF94EwNNPezrXvO4a3vdD7+OkNSet8OiO3hCGrtPpK+URJrCA0w7oTMsY1cIIBl+KUQ2IlW10QLMBqBFXBL3Jxw7ba6+tOmyxpdeNjTVGFlrpgr3WxpFSkm5QyTpXaWOGLJXhkmqORX6Qsuzfa8HUl778pQLuJBUL/V7F5s1bRqQNOecyrg5eUoZami58bs0s/+G0E8jAX922lVft3EOOqYDAuq6V+RMwVYUK9N/ggxbntQxgJuK8SghGQnS2dl4M9IdQdYBue+67/r5VCPT6/XK8BiLteUV8OhcS1mlKnkdlDDqKbuEeLQwSLacyqbode39Cf0RHwEh73ayeqVk34t3oc+W1lg0wwGj71nmWu/OiZW9dBzh7Y/St2UgSfbR3XtroOi2Kc64slFqdqTgSeJ1nMs9lEHY+nbLW1tq2bbvrC2jPqPOBAWU9Xw64YDDkHXfex6am4adPO4GrVs8KG+u1pa3OTevsJQtMlnnWy2svvPBC0dK6duEIme07tuvnrMGyOA9kwQdjQDuOhyj6oc97fvA9PPuMZ/N/v/B/OfdPzuUpb3sKn7r7Uys9tHGM4wEj5cQHbvkAT37bk3n625/O7139e9RRKuQfc/xjVnZw3wMhmlRP8F5N/10BpcVhwBjEDtDtpvWLLhDup40t4BHK60yaUNjbDttbAPEyhthS+pLOrwpAsxusaXrtPd0OZbavqOArxVRskESTKgCiq8ENqmfEBe7dtoODhw4B7bH0en0uuOARHfCSyvnsSjV6vUrT6/ITm8jXJ/q87NTj+NSqGf7zjr38+V33ccpAgKx3xnhb+lzQm4H4TCKlRk3+RQtJ8gTfU8uwVmNs59XOn53XYT0kxlQWAt3CuVBsztrrXqQARiLmRIxNAX9dVlwK54QJzKI1EKbSmeqgBci+gN0sbXAxwKraW0QDK393dLlefhy5BVBOXts0DdYqN+UkYN9l5ZZRoCeHl5VlzjoMr3pXHXUB+06PeXp6msmJCQXjSVsrG3SXBYL93fU+Lnl9aLdv50GZaGGo1emgIy0w+Y9JNozJfvGuffzFrfew5Bw/fOrxfGl2uujFvZNsRKiCstKyr1BVBF/JYqUoQGQfm7dsKppyuy5zhxfYs2ef+tXKmGPTaBaFI8YY0I7jIYtLT7iUd770nWz9+a38r6f9L7Ye3MpCvQDALXtv4S+/8pfsW9y3wqMcxzgkrrzrSs79k3O5/J2Xc8f+O/ij5/wR1/3UdfTCA2u4xvHthFMWJyjoEDArWkG9OfpRaYEVKhmI6UoUZIud4i0FWAb6uqlWY4JtW11QFHyrP03LGFs66ejlmlt7vFuw5lynna6+hpEUccs2C/uVS2FYVoC0Y8dOduzc1QF+8totWzazatXsiOyhaRqGw2EpEhsOhyM6SpWMcriq+IVTjuM3jt/MuYtDrrhtKz+5ez/VcKiMYFbgafZMBgClKt1snZx2HsvqWmAMnjHXXe1oV35h6Xk758tdK3KmZe0NydIyi75zLa0aXl4iADx4j4cR9nEE+DrR2hqLaM/Lj81OhzMBL4ym8XU8SedFSrmMoTtmYdR9YeSNJbXiJ9Or2uKhK89wpltVPWlKaiMHpSOXAOlUxtMm5Ftm1nfQn7V1Nk1rd+7ZvktBph5zV1Kzqon8ztYd/Op9O7lmdppXnHoct/erIt2wz0yGsjBIKmFpmkiMmdhEUJDvvWf16lVs3rRRFpM6Jofj4MGD3LdtG+C0G13n2B4gxrZd43jIY8vsFn75sl/ml574S+VL4N03vJv/+vH/yus/8HqeftrTecFZL+C5Zz6Xk9eevMKjHcfDJXLOfOaez7B2ci0XbLmAzTObWTu5lne+9J289NyXjoHsv3tkBW6Wqk2lktrwyfKiIq8djUzH6Rzkzg27iQ0uyS07+dRJ/UoYiOqyvs61/puF4nGSGrV9dcGtbJ9S4OJw5feiIaVttgAU5rEwtkmOHdtlAWitNlcATI8q9Lj66qs575yzyz6ccxx37LFs3LiJrVu30jSNenwq45YyvX6lvrICUoIVioG2Cs68Z8NaPjE7xX/Zvoc37NrHy/Ye5M2b1vKe9avJCiKEVWzHn2kBZ10PO2MSv9gu49qy5UGuccql/XC34MgWAuJVKw0MYtPgqgoyhOApTR2MlTQ2PmehR117bjyO1GHHnbG2Ni5Lnxs7aZkAY+3VvziTO9dGFzRO2eIO6ASRIqQUlXpMmrJ3xWbKhxasO0v7QylQKwVZpufNXTeBSIytO4ex+TklojqA2IICLTbrbq+d8539ZlvUCTg22YsVOIrEhKItf+rBw/zy1h2saSJ/uGUDb928niYlvJP5HZNYcaEMdMpip+d0/jdNJPsoi9Wk8p3UsHr1ajZt2iRaYvv4Ocfhw4flM+R9adrg1Ce5rHGWxRjQjmPFovul9suX/TLPOP0Z/P31f8+7b3w3b/jgG5jpzbDvl/bRD33uOnAXx606jn7or/Cox/G9FDlnPn/f57ni+iu44oYr2HpoK6+96LW89UVv5dxN5/L5131+pYf4PR3OOWU/O5XudhN2rQl8YYA6IEUrXO7HsMrzCclO5vuxc0Xf2shNslvw0i32AtWfBo/Po+4Hy7V8XdbI2GU6N10r8AFh54KCiKgsZpfAq6pKmTGRY2QdX0yRylVYitw7x2mnncrdd98taV7txCTerSIJyGR6vR4OARjBewbDgbJkcn52hcAvnngMfzM3z8/vOsD/s2MvP773IO/auJb3rl/LoapqtcAqm7CUvK0PUm7ZUMm4i+epASQ5Vx5fqS1aTMpU5xGZiLHNMSV8pf6+em6KZEBT0slsw1LG02FsUyIrk4nOo9ROlwK2ZI6NSkMcuViCoSyuMY8x6/GqNjXqPBScmMqc1F3ouLUQThc4Zkdlaf2kIF+mS5sBADm5Wbc9OTWB847hYMDk5KR2hXP4HIosRNhtO09tJsN7B7HVsEqjCWnUgWY0bI45lSdIe1kZx4lLA9543y6ePLfATZN9Xn/iFm6ZmsTlhA+BGBv1pw2dxalIDVJKqo11HflFxhHwlWOi8px77tlkk7CoOmIwGPL5a66Ra6KyjyRmaOpJe//vEhgD2nF8l4RzjkuOu4RLjruE33n673DL3lu4cc+NBcC+6O9exK37buWJJz6Rp576VJ566lN51LGPovLjKTyOby+WmiUmK6moveyvLuNzWz9HP/R51unP4ree9lu8+JwXr/AIHz4RQlU0gV0tbNJCpa4+1PSAbScuZdO0sMs0m5J6N4/aVnsZYyygT6QCfsRaypo7lH1Z5JZ5LfKC1KZoDeSCAWiVR1QtAC6p8ZwLs2y+rt5J1XrQwh2vAsOorHEIFXv27OWeu+/hzDPPVDApQOW8887l05/+NPWwkUKhqiqsm4FcAaNSZLak1fKiNRXNsjCQia+vXsXr1qziiYcXePWuffyn7Xv4iR17ef/aWd6+dpbb+vJd7J3DaQGeHbeHkc5UBstiaooUA5zadWmFu/NUDmVk23OXkprta3FR6FwjUtsS2WfdlxkkLNPU6gVRgNcuGLIuCLokn0lBpBmHK49lbfUqG1aG10sGwNs2QSQXnXc6J+oHn5WB9SI9QLMQIzpxOoAWmQuyB4PGsq3S7jklYUIzAkobYbBTMiZdNdNloWcFYK3EAgdZWVLrImZtm3tVjyZGNtUNP7pjFy/be4CB8/zelg28fcMahkn8eHu+QtxHQumKl5K0xBXNddQPj1i4xaxtf7MrWvlHX3wxF2u7W+Gz5SzeeONN7Ni5E5CsiyxKTCLhRi9eJ8ZoYBzfdeGc4+yNZ3P2xjbF9t+f/N/52J0f4+N3fpxf+divAPCqC17F37zkb8g5c+XdV/KoYx/F6onVKzn0cXyXRc6ZbYe38fn7Ps+n7v4UV959JdsOb2PbG7cRfODHH/Xj/OSjf5LLz76ctZNrV3q4D69QjWhWEGlduixVapX7y9nXLmAxhi6TSzepctPD4VwojGoVqtbSSQFqtyNZl+ntbr9JUrxkmlCgSB6MPQ4+tIAkxpGxFs1mEt2gZX6TGsS74PA+0zRS9d5kSTGHShwGoGE4SBw6dFgRlNCgKSY2rF/Hs5/9LD76kY+xuLSkwMJpZXjC+U51eG6k8EbPry0WBOt4BXDwqelJPnnyMZyxMOBV+w/xwgNzvHz/Yb40NcF7187y0TWrWdSFQbFBy+2xN7FRsJ9LFb4UBqFFYxSAa+DENK2ih9bmEHQKA/WcOdqCKEFlToG0MapSflUY8yy+vlY1X2QLhaE1+lcBLKY8aBFvKwkw6UtH1+u82m7ZjHHYZvEZl9qir6TpeaC0Fy7z3aQqCjpRplseFgu3bEDXJZrcUPWqEX10V1bRZZZlvmgLX2LZt+Hl3G0D7T0nDGtevXsfL9l7kCpn3rdhDX+yeQP7+pVaaOmc1msUU9taV2QE8rdXLa1ce7leTaOyBBznnnMO3/eEy1TKpdcgZQaDAV/7+vXFFq2qKob1ECuetEXJkWIMaMfxXR/OOV54zgt54TkvBGDX/C4+edcn2TKzBYB7D93LU972FByO8zefz6XHX8qjjn0Uzz7j2Zy67tSVHPo4HsJYrBe5Ze8t3LD7Bp5/1vNZNbGK//np/8n/84n/B4DJapLHn/B4XnT2i1hsFpntz/Ijj/yRlR30wz06aWJJnVJ0rKMFQW1xTdes3gqWSg/6LgBCnQ46DFXopGgzLRNbgLMyvV0HA+86LFoBMtAFxj44HG03rNHino4swlnvMoo9VkpWhe+lJaqCecjKYItv5549exgMh/T7/c4xeR518SMJLvAv//IvAmpzC/qroIwdqJ5RAJZVtVtBE2S15GrB/R2zU/zm7DR/XDe85MBhXrD/EL+5fS//dcc+/nX1DB9YNc01M1M0qsm0ojNjVL03KyqvLgLmJar+qqhfLi0ACyEQo8gmPCLN6BY9GeC0MTonoFlS+C04TEk9V8vsMf6vnU8Z1bLatZBdKCBeFk6LxXQBVdwHsG52lPOesk2QRDSgbaBZd1K2nw1IZwX2FGbVNLQpS+HjzFS/FIaBgP8Rhtc6gnXYUuecHE9u+d5ihabXrKoCxMRj5xb5oQOHeMqheTLwgXWr+ctjNnJvvyfgMiZZZJk7RdIGEDaXaO3Boi1yMuQgZ9sWUDlnzjr7TJ7xzGfQ7/cpYFYZ8q9+5ats27aNFGWMog2HnIX9rX2z/OqUGAPacRx1sXlmMy8//+Xl743TG/nwqz/MVVuv4ur7rubdN76bt3zlLbzjJe/g1HWnct3O6/jNT/8m5286n7M3CPN71oazmO5Nr+BR/PtHTJEDSwfYu7iX4AKnr5eGFn/+pT/nwNIBFptFFuoFFutFHn3co3nNRa8B4PJ3Xs7ccI6lZknSkznxsvNexi9d9ksM45CL3nyRFCXkWNouvuExb+CXL/tlDi4d5Il/+UQxjfdV+Xn9o1/Pay56DXsW9vAT7/8JZvozTFfTTPfk5/KzL+fSEy7lwNIB3n/z+5nuTTPVm2KqmmKqN8UZ689g4/RG5oZz3LD7BuaH8yzUC8zX8+xf3M+zz3g2J689mSvvupL/8tH/wt0H7mbn/M5yLj77Y5/lCSc+gWef8WzWTKzhkuMu4VHHPoqJamJFrs04jhAOMV2n1dObBq8LNAUUWVX9/Rlb87U08GitQKFtY2vp1FxAUxwBRiYLyFmY3i4wLkVRy27KIxpar8C2jNOV15pvZ0nxo8U+PuFSxhwCYmqKzEKAoUgpUor4quIr136NxzzmErHlQhgyr8D8kRdeQL8KfOSjH+PgwUM0BvRTBieaRXLr82lFZ+i4fKjKOJ2DFHMBYQd6FX+xaR1/sWENFyws8cIDh3nOoTleeHCOA8Hz8VUzfHB6gi/MTtN4L/vunjtvYFDavbZuEa1euMhIciJ4bberkobgxc5qpGMYtrDJCpCRxYiThQV+dMFRFh5oMwY9D3a9cBlSIjnTvHbsv3Sylt+Kp6tA9GzP6cJj2RSX862sesvIoosSWps3R+s5mzsssx2bH22lbMfsEImO+NZSWinLuZGhmhWW6WVx8p5z6prn7F3kefsPcWzdcCB43rZ5A/+weR3bnBQS5mQtf3MBy1Gt5ySCziVHE1Np1uEVjMcmEvpaHOY8Z5x+Os977rOZmuy30o8s5+HQoUN85dprcT6UzwEp6sKX4hP9QDEGtOM46mOqN8UzT38mzzz9mYB82Lce2lpSyDvmdvDFbV/kiuuvGElVXPUfruLSEy7lqq1X8ZHbP8JJa07i5LUnc9Kakzh29lhm+jMrcTjknBnGYQFfV997NfccvIe9C3vZu7iXvQt7OW7VcfziE38RgKe87Slcu+NaDiwdKMf3grNfwD+94p8A+P994v/HrvldAPR8j6neFHWqC6A9sHQAh2NVf5WkBF1gzeQaAIILXLjlQtHjuVDM1c9YfwYgN5dzNp5DkxpijjSpoUlN0TYv1ovcuu9WFuqF8jM/nOf41cdz6QmXcveBu3nNP77mfufgbS96G6+56DV8dcdX+b6/+r77PX/Fy67g5LUnM9WbYvXEai4/63JOXnsyZ204i/M2ncdZG84CKLrscXz3Rjfl751DC5s7wKvV0Gb1yoTWZ9ZAgIFQY61MimDvteg2TbD3dVlVh8gDYopt21xyeU+3sKwtRNJ/o7WulfAilm0ZwJSVzVOu0YnnrL0fxN6otOqtHL2qhxUXve99H+BFL3ohs7PTklrusLHnnHMOq9eu5YMf+hfuvfdeOade0vJyXsCY7ipUZMtNOzHsF3DVcWLQcxgqbagAXL9qhq/PTvPb9XqeuLDEsw7N88xDc7zkwGHmvOOq6UmunJ7kyplJdvd6ihNFv2sWbd6bu4QAQEulW6rarkNd122BHQZ8OmPLxqq2Y47K8gtrKrZboiOmAEA5b6mw9uU80JWz5AJahT1NmmIXkJvs5NvA5OLqtrNmADqMcjm3+r6MbluYeQOgooBQHa/KVIxZ1eGUKBKD3Lp3+GDXWj5HXamE856JuubR84s8YX6RJx1e4KS6IQJXr5rm94/ZyCdmp2j6fZm3aoln4zSXgaJdV7/ZmKJRv8r2m/bbl7GZPOWUU07hRS96If1er2WnlfUeDms+e9XVbNuxC+u0FtXdoGliOda2De79w3XTMw9lXHLJJfmLX/ziiux7HA/PMHB1856buXnvzbzhMW9g/dR6/uDqP+DnP/zz93v9fW+8j+NWHcdffuUvec+N72HD9AZW9VfJz8QqfvEJv0gv9Pjiti9y5/47CzvZCz16vsfTTnsaAJ+/9/PceeBO6lgzN5zj8PAwla944+PfCMCvf/LXufLuK0cA61kbzuJrP/U1AJ7wF0/gqnuvKuOa7c/y5FOezPt/6P0A/MpHf4VDg0NsmN7AhqkNbJjewBnrz+DSEy4FYO/CXiaqCaaqqWVdWlYmulZAg2bA1kNbC3O8UC+w2Cxy4ZYLOWH1Cexd2MvV914tDG9vmpneDOum1rFpetPYRusI4Zz7Us75qEDwkxMT+fzzzhphZe1+nRQUCGDtANrcppW9paNzm/q16ALO5ayqvb+rmS3p02VsbZcNtqIcYISxteiCZt8BKd4ArQF3b+yuL8wbwLBpqOtGCqKAXq8n1ebKKnsnN/hTTz2FF73gclatWlU0qqW4y8Ghw4f50Ic+wq233lpAj0gmhUVs6qj63XY8Xtlcr8U6WfWPVtwm1k3aOCC3dk+JzJRzPO7gYZ6yOOD75hY5thHAcVu/xxenJ/nSzDRfnp1id/A02hlL9lUVBtP2VYCtc6xbv0HY9o7dFU5Y1gLyVAragaF6vaToT7qgdbS8nXR4t9WwAc9EK8GQ+YPRrK3WVdFlxooToZczkzFS5UzI4pQQciJk6GXw+ntymQZH4xxDBxGo9adxjiUHtR6M4VoQXelUv0/OmV7P2hWLBlnq8kR+YcLbnGE6JU4ZDDh90HDB0pALlpY4e3FADxg4uGZ6io+unuHKNbMcnJgoQDEn8Z41MIuCTpmL4H2PWnW3VRXUL3g5yJSx2efIO89pp57C8577HFavWtXR+2ZQC7vPfO5qPnfV55mbm6fX75G0M5oAfa/NNByLi4vs3X+I4bB2LN/rGNCOYxwwaAbcd/g+7j5wN/ccvIed8zv5uUt/jn7o83+/8H95y5ffwt7FvRweHObw8LAwkr8mzMNPfuAn+dMv/enI9qZ708z/13kAXv2eV/OO694x8vzmmc3s/M+SIn/jh9/IF7d9kfVT6wsgPXXtqfzUY34KgK/v+joAG6Y2sH5q/ThtPo4HjKMK0E5O5PPPPUuBprSRNXAKFLDXaiglfEdXWYz/u4U1uXUaAErhUvc561IFjOheu685Ehg+okZ3GWMLbRo459aM34qxnMsKmtVIXhnnJiaGwxpo2/MakPDOidZRt33qySdx+eWXs37d2rZAxzvQYriFpQH/+N5/5I477pCx51hAUGw6xv/OAeKdKkDaKSYSIGhQz1hWa8mbszC3saPpTEnS9mcMa75vbpFLF5a4eGGJGd3XPb2KGyb7fH2iz/UTfW6amuZwJZXyZC2msyIx71mzZp3KHgSoF0s3TbNn1R2D2nZhHKm1hPXFVrjMCSDqcaUsYMp1XhNSYl09ZN2wZmNds7Fp2Fg3bGxq1tcNszEykxJTMTGVItMpMZ0SvX9HGDVwjnnvmPeeeeeYC55551nwnnnvWAyeRe9JOm9cdkzHyGzOrGkatjQNm5vIpqYFmfPecf3kJF+bmuCq6Qm+Oj3JkvPFacPp+ZWsRNW6FkQpTjQvWjnzIjHIubWok0JIkZDYws8hn4vBYMDmzZt58YteyLFbNrXEti4KUkx8/pov8LGPfxKcZ2lpiVBpK2fVCRfpjvOkFNm+cy/D4XAMaMcxjn9r5JwZxEGxftp+eDv7FvfRpIY61aUq2hjSew/dy9xwjp7vMdOfYVV/FdO96RFGaRzj+PeIowrQTkzk8887G9NBmj9p0bIq2EsxaWclYdOsotp7XwAtcD9Q2mVXU0olO2Hes/a67j3Q0p9F1rCsIKwLcEulOMaytqyUpZWXaziL40EBignnZHtNFAZUCsGcespWpSmBPR6Cp/KezZs38YynPoWTTj4Z59uuapZHHwxr3vNP7+XGm24khB7eB1ITSxo40zLWci4b9Zi17ldx5LhcMHsmh8fTRNX8Ok9d160EJLba3J53nLOwxKMXBzxqaci5SwOOr9vFxO4QuKNXcUev4s5+n3uDZ9fEBDurQL1uA9m0yFgqHjmvauHmlc12mbbBhjNQK7pNUmI2JTY2DeuHQzYMh6wf1myo9WdYs76p2TisWRuPnM7eXwX2VBWHQ8Wi9ywo4Fz0noXgWXDy+5ITz9voHJH8/2/vzGMsua7z/jtV9bp7ZjgbOSRFakSRDCmJjLmIpCkyEh1agRM5EUQBEWIlQSIHCgQECeIAARI7fySOECD2P3GcBQkE2ZBsBLENObYpS4ajiNpFWRIpUhxSGm4QxUUkZ+uevV9V3ZM/zjm36jV7yNYy09Mz9wNm3lav3r333er33XO/8x16hF7scadGnhtggtIkI9C1QuOP51XZkhJbNLGl77kgJbYkZbP3YUtSNqs9jr22BEZ+K+FwXfNSU/NyM+GF+QlP+tg+s7CAVoJqb1rfFIUPwj/Yvrv4HiupqVZo09u2zddUXD9VrsQ3u+thZNckB5Om4r3vvYdrr7nGilWoZgmOauIrX/sa9933+SyrSNmhI3YNKqbT5WzpJiL84KV9JUJbUFBQcC5joxHa695yjT9yAjuO3nh0rk9DVDAiRYnRFjCeuc0sMR1LC8Ya2YgeBRmNRLEgqisJLgz63HG0d/x6kLi6qj3KONhCyYrjgtBGcpO4G8CJk61/VpjiB4mus5UTaoTcdLc9Wy/YzN13380tb30rTVMPkWlv4tHjx/nMfZ/lxRdf4sjho0yXp7jIlL4zi63oX9u2CILZ2TYsT5ftcVMzPzdH1/dM25ZKhK5ts01TLDxCFxqlU62gwxC9Bks223JymeuXp1y3POWq6ZSrpi1Xtx07ViT7tCIcahqO1DVHmprDdc3RuqarKqY4SawqalUmqjR+u6Xv2dr3bO06tvY9O7qehVUSiaYiHJhMODCZsH/SsL9p/P6EA03NvsmE/U3Dwbk5Wk3D7JpZpIT4wb6vvu8JxwIIBYDraXVI2BonHDKmYKNzqyiaeqSqmE5bKo/Wz8/NDf7MAtn71+8jQu0RexFb2AQ5lUo9oS6uHavONY60gi0GotxszP0goRHpDzmAfb/eP5+3W7ZsZevWC7jrrrvYuXM7F+/aZTH0KGecbJfiq/ffzxe/8hWmbZcdF5aXp9R1PaObDV2xqtL3Hfv2LzJtX0loS1JYQUFBQcGZh28Zp5zFnGa2I/0Qak8QCZ2lZZfrTJQVwRObZOYf/p7azfsj+z2yvHNTRseOMY4Wq2qusLXyM4aysh71VLd/8j6aflWdUFRepcyaVHuufFM3WaNaVZVbL1lRhGSNy7ZIJNOiLh05xqf+7M/ppi1vu+P2TJK99WzZvIn3vvvdnFhe5smnnmZp6TDf/MY3OHHiJG3fk7oecY3qxCPAUpukY26y4NKCipPLy/S9kZDQlEamfVVbZYNmFFmOAhSpV1KCru2oKsuC75qGrzYN91+wxcbHCdmOlLhsecplKXF5Ui7vlQv7jq0psbXreN20ZUs6ySTpDIntRGb+HasrjtQNL8zPc7RuWGoa9s8ZWT0wN5DUw55F34cNVyaZs9+9qLpcxJAYdgoscc7elTyyLzrMAzOZGBwaVi6Qsn5XgKQzZX2tqENNUphOp+zcus0WSEEw8ff4fFQ023UlVeit3ZVUXqUMREwmYvrfCk1GQLs2uSeweJKa93WU5BXXm+mTJWu9EdPcTpoJf+nqa3jjlVewe/duLtm1KyexpZEuPbygH9nzGF/40pezljvKG1du3YYO/saqRnatOEoziKZXoBDagoKCgoJ1Qe36vdT3CEakTN84ZKuPI6n5OQZSGVGlsdyg7/tsCTWOEFpENLZFh+htRI3GZHV2C3WFLGGFpMFPnslkJisKSEJl5D0qFmVFzA6p7yPpxcvRorRda16sHp2N+vV9ctJfjaqWqXLf57+AAnfe+Ta00qwhtYOVhfl5brjhp+j7nltvuZlp2/LII3tYXFzi6aeeZnFpyaLjPp6K0nWt9bPFZAhUQ2U37SyRLoh9LjBRWeJZ1yEIy8stTd1kHebc3MTIVfQpQZcsErcvKfsnDXtEaCYTNm/Zmj1m43sZuyBYrDGSi3DtbUwXX2hkCYjncoUOGjfbUhAZJYgxcCVxEqv5+0w5Cy3OFRFJ3GvXiGyfdxeMROaZQ8qV6IZ5EklTxmktMkuyNw4Jc1UuXZznXq48JznxLfpn87+25C3/Tuu6ovWFRWi5VY201lVN3yuTSZN1q3FdTaddPpddU+7+IRVz83O85bo38Ybdu3nzm95EU9U0XlEuFj0mEQk3ELu+n3rqab7wxS8YgfWFRdu21M2Q6FvVNX3bupzBfY5HMp7VUAhtQUFBQcG6wPxgZy201KlKTvaKbcfY8tRBfydVRRXbrCEHUEWq2rLpR0UYxtHLbL+Vy79iteKdwYSdUGwlj/0/x1vEpumb1ceObb4iAmfetoJi28HqsVkZ6RQXNi3QtraN6zzUfKEzw7K+qqpZMpGIuGHqEv/3/92HiHD7bbfQNBOMW3qVJlW066lFmGsmzNUT7rz9dkBYXFzkxMmTPP7EUzzxxOMcO36cpaUljzoHgaiJHXYj3r7N7B4D4cCanHBPJhNS3/v2eG3kLC8azLkiSI5tL7c0LvvAz2OLGzt/ELkxoQmyGCVRRWYXNXYreRGkY99g3AtW1Yo3MPZ1dYIskqUUvbtCGMF0mUGQWayUccgH6rrOx0bylJ/aI6CxAApNq/UxYU4bfRp8lCXe6SHe1BshjB2HTLZxZxDEXBbEqnKJE1OLCDNaqFVYBZOB4De+6GgarwhWx+6DLYwmk4ambrjwoou4/LLLuPnGG1jYtMDFu3aNrmjbPchWZCtIbUrKgYOH+MKXvszS4SMWwa6EPpkVmoyKqQw7MMz8fRhr5VeiENqCgoKCgvWBqhHJNPoRE5yo4pG/5EkiYzspD5iFRjHpDElNrnmUJDPRJsUqHuUqZJ5ZU3mVr0gGG5wTWLHdOqsJtQ1omf0RdgJTiWXnVwi9WvhQCFLkGtu8v23+s6EVHIga4OS+bnC5ReU/7IP/bhCez3/xy7zwwgu846/cycWXXELjcgAjUylHMu0zjZht37aV7du2cemll/COt9/Jvn0v8/zzz/PiSy+x97vf5fiJk0QlKPNFHQiZ3VRUtZNaL+TQdz3h0GB5Zv1gn4UVjUjeFIsIhsbTSFvfdbRty2QyZ761oaH0pLRM9Bii4qEfjZdMwhKeqLU5QQQZNoFyPj4IeYx7Pmt8lyEREDwRblgY5Tk4XgCJuGMFWWpgVdpGUd8UulAj7zlC659D3GKeruMkyKZurKKYb8uLhKaBEfEekv6iXPCw0ALES9a6Sa+IfSPxXfceSZ+bm7B58yZuuvEGLrxwJ1dfdbXtHviORN93ozkRN2PNss2btm05euw4n/r0p3h5336quqadttRSu1xjKJ9rdmThZeveziL0fZrxJl6JQmgLCgoKCs44LAGpJiUhiW/FqieGSbLo7ShaZUUKnJ3JQEqCHKiYEX3KkTrJmf8RmRq7DgRRFQStUtbaztpzWVQwkrmEIbMeBqKTCYsqvZommKq2OGwlM5pYa69bYuVtaWFSN7TtYJVl3rBGMqpKcqlcI0gWNUsp0UuPiEUFU0o89PAjPP74E9x0443cdNMNXH755TP91zEBIpLnhgpMF124k4t27uSnrr+en/2Zn2Hp8GEefvjbHDt+nL2PP25EbUQcUbIVmKoRvsZJR9f1NJMJVBU1Lq3oujz25j5hC5AgLXVT0zRGTaxohrtTeGEITeasEJKAKuaEj2tME1tADCWIs2whyxhkiCD6aCTwqLlmTkkmWZV75Gb6OxCwkF74/IgEp7F3cvYpjlXFqE2iYwmDtUuorP9iEe8+9a5p9ZLBQh5zk7RY5LvSWbIehTx6hsWIVLEDUtGllqapmU6XmZ+fZzpdZjKZsPv1r+eSi3dx8803sW3bNuYmjcs6BE094QeRkxCd4EakWsS8lZ995vscP36CZ597jr17n2B5eepWdi4ZypZgOlxTPhZ93zOZTGb08bGYWA2F0BYUFBQUnHEEdYMh6Sa8Qi1zPipJeULW6Pko/QpQpQSVFSBIVcrbm4iVHO20m9myHHxTwxhfs8wgiirEsfFDHRHe1crervSijffkRLI4H8QLQ1nPiLBhkgBNFrFWHbZXcyRSJEcyu7bzx+K+uuGyYIk1y23HAw89zONPPMHll1/GHW+7g82bN7Nj+7ZMfiTO7NrE/J1kjaJtge/cuYOfvfuv0vUdt992C0ePHefBBx9k8fBh9h84aAQTiwT3JOabefuOZCB8XZDYfpo1t1VdUdU1XddZQpknvPUp0bYdm+YWPEKPj70n2VVBHok991kdswjaD5XAgvji7082uLYI8veGkKB2vSa4GLcfIvOKbb8nDXnBkBiHk1KzvKpQSUT1NxFxwi4D4csfYQuNRAKJueAReiezqr6Oa03bHAsjk3JU5oSA0HvkOAh2H/KB1M9Y1eHXUVi1NY1pVS/YspkdO3bwlre8mSt2v4Ht27ezadNC3k3ISZQD98zIY42w/8BBXnzxJb7+ja9T1RWLi4dppy2qUDcNvWqWFkTEeW5uQtt2hD2dLSDD2UTzvDcbu+oVnx9YE6EVkXcBv4ktlT6qqr+24vV54HeAW4EDwC+o6vfWcu6CgoKCgvMTKfVo3+ffpyAqkfQCtm0fVcS63o8PAuxkoRKvc5/IUTkYKo6lNGzjjhPFQmagGmVHNUdPg4yEHAGMsIR+MRJcVhKFHKkbSR1CSjEoNEPzWbkmOEhfysS+qgQYkRfIBSEiMtz3NkZRojeIU2hZDy0e5sChRR79zl62bdvGFbt3s+PCHfz0rbcyN2mYTCbe7pQ1snlLWocFh4h5377u0ksQEd587TVMp1Oeevpp2rYldXZsn/pRxM0T8JBhzMXkHZM5W6z0Ggl59q+dTpm2LcvLLd9/cb+Twhj7QaMMghdHy5Fda+lsxbjsGuBtCBstBLq+Q3zeWOUrj1LnaDYWTR67aUDWNOfIr49bhbgqVaDvmczZuFp7Yg4OOwTosJAKzbDEYgx1qzpre13V/PW73mGErnFrOIQu9Rw6sEgzmXiilkW4EY9Wj3Ynxgsj9UjrID/puXjXxVx2+WV57oyjynoqBunj0LYd+w7sZ8+je3jqqWc4ceIE6q9lTW5Voa0tbLLfrXvNWruw6nFO4iG8bo14xzXQ9z3NZHXq+pqEVkRq4L8DPwc8B3xDRO5V1cdGh30QOKSq14jI+4FfB37htc5dUFBQUHB+QvyHuusTeEJWkESIUrMybPEGaXUZAGnQhPa9/QhHlndEjCa+Fa8pzURXI9Ib9yNym1Iya69RqdrEcAxEdEuoqsa3xMkuCUmtgEPyhLUxEV4hYLV73k5UqL3cqIz6H2VFxzpCq6o2RA77vvOI7qDlrbOXrY9fJSwdPsy3H32UWoSHvvUwmxbmuemmm9h6wRauvPJKFhbmPVo9kJeBxA3V2DSpu1Io11x9le+eO6GU4T32/rh10i9CpcKWzRPEy7RGRF495KoKXacsV5uRuib1OMkkRwuN/FRUMpQOzmMro7tB3lbZplaNz9OZNke/jXMOiUlZ5xqfpbN9XTluqpGUaP3s+0TSfmYu9l1H13UelW7tvj837aZ0XU/X9Rw/eoTbbrmRprbItvh86lU5cvTkbMcq8jUUOumsEMnzWPIOgX8t5MQ5jWXMMEY2rCOdrMKxY8d57vnn+f6zz7F37176lJhOp1R1kyPvIRsQEVscxCJPhM6js6pkUgt2LQ8LTvK8EyE7LdQzOvYBa4nQ3g48qapP2wfI7wH3AGNCew/wq37/E8B/ExHRV/NXKCgoKCg4r5GTfLRy4eNQRrNybV7vhC5+w2zLGZRqyHCP8+ko2iViFkhigj4jmBFFrTIhGUdZc1R2JrI1jtyCySAGr9UxWcoepL3raEP/68UcjCQEyZEhIuuRZj+LR66EyaSm60JW0HmEuCGIn3jUN9MstWz1qqpp6qHQguk/+7xtvLR0mIOLiR+89BmaqmLHzh1Mmpq77noHWy+4gB3bdxjBje38HJUcbbOv+HlPqiufmt0a1tk4X1SNipIFUVTDCDikyTxV3dBVlsjXe4RdsK3/uqpGBQSCxc58wgoiqzlVqfIOGfEM/+NRZFcjsSpkGKOoKgPRy2ORj7N3yOgccb6xfGR4bTjfSmKdyTSwdOjQrKTFS/b2XnxgYPESPZ8ho8NpZy3oGA55ZRR2dJz4AuvgwUMcOXqU+++/nxMnpxw5epQ2bL663klnR9M05rLgEfS6Cns8pU+hhx1ZkDHoe22szHZPpB6KkYwWEKcilmshtK8Hnh09fg5426mOUdVORJaAi4D9azh/QUFBQcEGx2tJ01YiiEJKOkRWVTGzKPdRdRLS6WCyThd2XobYfhcR1DW4RhYtupr61kigRhnXiOCOIo46VAmzH9KBGBBb1WiWJ2Q/WIxcZb2f84qIzkY0KnKw7LRuEqURBbM+VpWwfLLNzg5hQxZyghi10MsOiV523wj2UFEtVULfur4yhaxjsMpS49QkqTi4eJiqEv7wjz5JJXD1VVeyc8d2rrvuOnZddBFzcxN8v54g0wO1GPVlFVKUta4AmlDXfabR+caHRBwWoO+VE8vLVqGskkzURa24hubScmNyb0+IzJ4VQsc806AZMjxwuKFdMnocCU/j9xvJClI2ENZhCAb5ypiURXuzdMGfG94rWAEES+wK/XCOZGOkd0yokyakr2YXeSuC08N2vswsVmaJrfWk6zqWp1MeeWQPL+/bz9NPP03XmTymaqpcJtqkMMNtjEvfW5W/NNI4WwS+Y25ugmpi0syRUpop+1xVViks3Dzi+fDTfWW83XBGk8JE5EPAhwCuuOKKM/nRBQUFBQWnCWuUpq3+Xv9fU0J7r3I0itiImA1SkMzQxQ4WXqPniaQx+9ETr1+fo19pSBaqcvTU2GYmlx6trcYVyqpIo/LosAyJZZ2TnCBGVVXb1q0TkPgVt211IzXViFDjZKfXxNz8XCaHlWfb4+3qo0ztKHJcVXWWJEQhhMoj0W07RA+rukJ704eG32gQKnM4UHOb8PF5bO/joMo3v/UwdVXx07fexrXXXMXll10a31ZupzeQCHIGHxsfE7FOG0+TlcQiYXAZcCIUY6jQa2J5OqXtOyaTBqexw/uGD/PkoSGJbBWVwSvnXt7OHkXjx7Tc2zj0I2/Wr4hQz0aHx5HZ2eeCOA+3426MhjOPic8gRBIVQsISCis/3YwswPXbZA36TLOGOQd5x2MYr5C/wPeeeYZ9+w/wne/uZXHxMNO2pes7mmaCotSNyWqquvJESohCDeOFQV4YepJaJbH7MESle5fQWMnnSP5z+YN/n13XeTWyxm3FVsdaCO3zwBtGj3f7c6sd85yINMB2LDlsBqr6EeAjALfddtup2lRQUFBQsLGwFmnaKyFOHMUiap2a7VAk4qSo4OQ/lCJV1tRWdW2RUgYTdsTN59WJrQy2XWCem0mVShltAVs6T0RBM5ENEjoiwREErKNilSe1hN9pZOoH6sqLPThRsPNBqowYGel2u6pKaLsONCqCDd66gUEKYePRta2RQ6lyglOVyTc5Gtu1XdYnh7axymSf7Pdpn1Gbf2xKrm8WvvTVr/Loo3u4YMtmrrzqSq7YvZvJZI7JxKJsyyfNiik0tJK7nJhMJkMfkpX/7XZuY9P8PE1TDclJI52tihpjE7NpEj9npSAJqHzscpJYREmFKHTh8/CUU2+Iio5J7SAL8KOGiKwOwcyIx46/a9WVEdbh3Cs/M44fjhsI3vizg8xqUp5/YZ8vhOw1TUrbK1NPtBriyYPjhuKVxNxrVleMh4jQti179uxhaXGJufl5jh8/xpGjxzly7JgXiUhZ42pR1Dq7EAQRDTlMLA5D+9q7/jn1ya3CBt1sJEwOziLRW3IVuiiokb1nq4rUtzNFMsZYC6H9BnCtiFyFEdf3A39vxTH3Ah8A7gfeB9xX9LMFBQUF5w3WIk17Bdq2tcihR6oQzduY4PUWdEjkijKYsaWawHe8/fggs1ikJ+mwTSzDvrRLHcZbvWr2VRjhimMiY38o3BAkSTDu6qVxhZzsk/yzg6hJJRYvdm4UFZEGsmXn3Tw3z8kTy0ZOc1JMZHhXloSW71eeZBSuDR7FmkzQXum8xKmNcUczaUxXmTST4shiF4GmMa9PIxfmVJD6PpNhUA4sLnFw6TDPvvCi0UdV5hfm0ZQ4evR4Jj/xPdjnKHNz81RRxS1BXQsX7bqQrVu3srCwkD1ncaITPqNXX3cD0y5x5Ogxpm1LXdc0rpudNA11U+dEuHATEKl9fPDvcFRwwx0qckQ/JZaXl5lOp2zfvj1XNwtmqi57iXGM0sChzw6Mk5aAXJkrXot2eIvy45V62VcSWpcZAAcP7OfeP/4Tlk8uszA/l713k89DK7JRkXrF12Pu1TtIX6QSklcGi8VVXjD6AjFF6NRLMfcrqnLlaL6muPoyGe37ZNcLSpVGtnSpBbUKaurXqkI+VtRlRyQmoatFwH1/U0pWrQylSx2bNi3QdYdYDa9JaF0T+8+AP8e0Ub+tqo+KyIeBb6rqvcBvAb8rIk8CBzHS+6p44IEH9ovIM6913HmMXRQN8lpQxmltKOO0dmzksXrjejfg1TCWnQHLjzy2d896tucMYyPPqx8Fp+7v40+99rv/6JM/2dacfpTv98xh1b9zUgKpZydE5Juqett6t+NsRxmntaGM09pRxuqHh4jcCfyqqv4Nf/wrAKr6H1/lPefVOJf+ntso/V1/rG7mVVBQUFBQsHZkaZqIzGG7dPeuc5sKCgrOI5TStwUFBQUFPxZOJU1b52YVFBScRyiE9uzFR9a7ARsEZZzWhjJOa0cZqx8Bqvpp4NM/xFvOt3Eu/T23Ufq7ziga2oKCgoKCgoKCgg2NoqEtKCgoKCgoKCjY0CiEdp0hIu8Skb0i8qSI/PIqr/+iiOwTkYf83z9ej3auJ0Tkt0XkZRFZ1eJHDP/Fx/DbInLLmW7j2YA1jNPdIrI0mkv/9ky38WyAiLxBRD4nIo+JyKMi8kurHFPm1GnEa/3d24hY7foTkQtF5DMi8oTf7vTnN/T8OtU1dA73d0FEvi4iD3t//70/f5WI/IX36/c9IRIRmffHT/rrV65rB35EiEgtIt8SkT/1x2d1fwuhXUfIUC7y54Hrgb8rItevcujvq+rN/u+jZ7SRZwc+BrzrVV7/eeBa//ch4H+cgTadjfgYrz5OAF8azaUPn4E2nY3ogH+pqtcDdwD/dJXrrsyp04Qf4u/eRsPHeOX198vAZ1X1WuCz/hg2/vw61TV0rvZ3GXinqt4E3Ay8S0TuAH4d+A1VvQY4BHzQj/8gcMif/w0/biPil4DvjB6f1f0thHZ9kctFquoUiHKRBSOo6hexgh2nwj3A76jha8AOEbnszLTu7MEaxqkAUNUfqOqDfv8I9gf79SsOK3Pq9OGc/Lt3iuvvHuDjfv/jwHtHz2/Y+fUq19C52l9V1aP+cOL/FHgn8Al/fmV/Yxw+Afw1kVepw3sWQkR2A38L+Kg/Fs7y/hZCu75YrVzkyh9WgL/t2zSfEJE3nJmmbSisdRwL4E7fNvszEfnL692Y9YZvjb0V+IsVL5U5dfpwPo3tpar6A7//InCp3z9nxmDFNXTO9te33x8CXgY+AzwFLKpq54eM+5T7668vARed0Qb/+PjPwL8iatxa+8/q/hZCe/bjk8CVqnojdhF9/DWOLyg4FR4E3ujbZv8V+OP1bc76QkQuAP4Q+Beqeni921NwbkPNUuicshV6tWvoXOuvqvaqejOwG9tleMv6tuj0QUTeDbysqg+sd1t+GBRCu754HhhHXHf7cxmqekBVl/3hR4Fbz1DbNhJecxwLQFUPx7aZe4ZORGTXOjdrXSAiE+yH+H+p6v9Z5ZAyp04fzqexfSm21v32ZX9+w4/BKa6hc7a/AVVdBD4H3IlJJ8LPf9yn3F9/fTtw4My29MfC24H3iMj3MEnQO4Hf5CzvbyG064vXLBe5Qmf0HmYF2gWGe4F/6Jm0dwBLo22vAoeIvC50TSJyO3b9b6Q/sj8R+Bj8FvAdVf1PpziszKnTh/OpTO69wAf8/geAPxk9v2Hn16tcQ+dqfy8WkR1+fxPwc9hv8eeA9/lhK/sb4/A+4D7dQKb/qvorqrpbVa/Ers/7VPXvc5b3t1QKW0ecqlykiHwY+Kaq3gv8cxF5D5ZVehD4xXVr8DpBRP43cDewS0SeA/4dJspHVf8nVp3obwJPAseBf7Q+LV1frGGc3gf8ExHpgBPA+zfSH9mfIN4O/APgEdfEAfwb4Aooc+p041wtk3uK6+/XgD8QkQ8CzwB/xw/f6PPrVNfQudrfy4CPu0NHBfyBqv6piDwG/J6I/AfgWxjJx29/V0SexH63378ejT4N+Necxf0tlcIKCgoKCgoKCgo2NIrkoKCgoKCgoKCgYEOjENqCgoKCgoKCgoINjUJoCwoKCgoKCgoKNjQKoS0oKCgoKCgoKNjQKIS2oKCgoKCgoKBgQ6MQ2oKCgoKCgoKCgg2NQmgLCgoKCgoKCgo2NAqhLSgoKCgoKCgo2ND4/7YOAhF5No0LAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "inside, outside = utils.get_border(traj, distance=0.16)\n",
    "fig = plt.figure(constrained_layout=True, figsize=(10, 5))\n",
    "ax_dict = fig.subplot_mosaic(\"\"\"AB\"\"\")\n",
    "ax_dict[\"A\"].plot(*inside.T, \"g--\")\n",
    "ax_dict[\"A\"].plot(*outside.T, \"g--\")\n",
    "utils.show_on_map_array(env, inside, fig=ax_dict[\"B\"])\n",
    "utils.show_on_map_array(env, outside, fig=ax_dict[\"B\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Position(x=2.0549999999999997, y=1.9297064071170351, theta=1.5707963267948966)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_position(env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model_F(dt=0.033):\n",
    "    \"\"\"\n",
    "    Return the model casadi function tuned according to the parameter found in the thesis.\n",
    "\n",
    "    :param dt: the time step\n",
    "    \"\"\"\n",
    "    # IDEAL PARAMS\n",
    "    # u1 = 5\n",
    "    # u2 = 0\n",
    "    # u3 = 0\n",
    "    # w1 = 4\n",
    "    # w2 = 0\n",
    "    # w3 = 0\n",
    "    # # parameters for forced dynamics\n",
    "    # u_alpha_r = 1.5\n",
    "    # u_alpha_l = 1.5\n",
    "    # w_alpha_r = 15  # modify this for trim\n",
    "    # w_alpha_l = 15\n",
    "\n",
    "    # THESIS BY GUY\n",
    "    # u1 = 7.662\n",
    "    # u2 = 0.325\n",
    "    # u3 = -0.050\n",
    "    # w1 = 6.826\n",
    "    # w2 = -4.929\n",
    "    # w3 = -6.515\n",
    "    # u_alpha_r = 2.755\n",
    "    # u_alpha_l = 2.741\n",
    "    # w_alpha_r = 10.8  # modify this for trim\n",
    "    # w_alpha_l = 14.662\n",
    "\n",
    "    # MANUAL\n",
    "    # [7.662, 0.325, -0.050, 6.826, 0, 0, 2.755, 2.741, 14, 14.662]\n",
    "    # u1 = 7.662\n",
    "    # u2 = 0.325\n",
    "    # u3 = -0.050\n",
    "    # w1 = 6.826\n",
    "    # w2 = 0\n",
    "    # w3 = 0\n",
    "    # u_alpha_r = 2.755\n",
    "    # u_alpha_l = 2.741\n",
    "    # w_alpha_r = 14\n",
    "    # w_alpha_l = 14.662\n",
    "\n",
    "    # FITTED wrt speed\n",
    "    # [2.14148837,  0.12200042, -0.28237442,  1.3380637 ,  0.40072379, 1.30781483,  1.03762896,  0.62189597,  2.9650673 ,  2.89169198] \n",
    "    u1 = 2.14148837\n",
    "    u2 = 0.12200042\n",
    "    u3 = -0.28237442\n",
    "    w1 = 1.3380637\n",
    "    w2 = 0.40072379\n",
    "    w3 = 1.30781483\n",
    "    u_alpha_r = 1.30781483\n",
    "    u_alpha_l = 1.03762896\n",
    "    w_alpha_r = 2.9650673\n",
    "    w_alpha_l = 2.89169198\n",
    "\n",
    "    # Fitted wrt position\n",
    "    # u1 = 4.3123709\n",
    "    # u2 = 0.42117578\n",
    "    # u3 = 0. \n",
    "    # w1 = 1.34991163\n",
    "    # w2 = 0.66724572\n",
    "    # w3 = 0.74908594\n",
    "    # u_alpha_r = 2.27306332\n",
    "    # u_alpha_l = 0.73258966\n",
    "    # w_alpha_r = 3.12010274\n",
    "    # w_alpha_l = 2.86162447\n",
    "    # States\n",
    "    x0 = MX.sym('x')\n",
    "    y0 = MX.sym('y')\n",
    "    th0 = MX.sym('th')\n",
    "    w0 = MX.sym('w')\n",
    "    v0 = MX.sym('v')\n",
    "    x = vertcat(x0, y0, th0, v0, w0) # Always vertically concatenate the states --> [n_x,1]\n",
    "    # Inputs\n",
    "    wl = MX.sym('wl')\n",
    "    wr = MX.sym('wr')\n",
    "    u = vertcat(wl, wr) # Always vertically concatenate the inputs --> [n_u,1]\n",
    "    \n",
    "    # V =  [[wl], [wr]]\n",
    "    V = vertcat(wr, wl)\n",
    "\n",
    "    f_dynamic = vertcat(-u1 * v0 - u2 * w0 + u3 * w0 ** 2, -w1 * w0 - w2 * v0 - w3 * v0 * w0)\n",
    "    # input Matrix\n",
    "    B = DM([[u_alpha_r, u_alpha_l], [w_alpha_r, -w_alpha_l]])\n",
    "    # forced response\n",
    "    f_forced = B@V\n",
    "    # acceleration\n",
    "    X_dot_dot = f_dynamic + f_forced\n",
    "    \n",
    "    v1 = v0 + X_dot_dot[0] * dt\n",
    "    w1 = w0 + X_dot_dot[1] * dt\n",
    "    x1 = x0 + v0*dt*np.cos(th0 + w0*dt/2)\n",
    "    y1 = y0 + v0*dt*np.sin(th0 + w0*dt/2)\n",
    "    # Cannot use atan2 because x1 and y1 are approximated while th1 is not\n",
    "    theta1 = th0 + w0*dt\n",
    "    dae = vertcat(x1, y1, theta1, v1, w1)\n",
    "    F = Function('F',[x,u],[dae],['x','u'],['dae'])\n",
    "    return F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the angle between every consecutive points in traj\n",
    "angles = np.zeros(traj.shape[0])\n",
    "angles[:-1] = np.arctan2(traj[1:,1]-traj[:-1,1], traj[1:,0]-traj[:-1,0])\n",
    "angles[-1] = np.arctan2(traj[0,1]-traj[-1,1], traj[0,0]-traj[-1,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add angles to traj\n",
    "traj = np.concatenate((traj, angles.reshape(-1,1)), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.04862946, 1.93084219, 1.54813545])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "traj[index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = DM(index)\n",
    "traj = DM(traj)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initialize states, inputs, and system dynamic equation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "pose = get_position(env)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "N_MPC = 10\n",
    "\n",
    "delay = round(0.15/dt)\n",
    "u_delay0 = DM(np.zeros((2, delay)))\n",
    "# N += delay\n",
    "\n",
    "# Initial reference point\n",
    "r0 = repmat(traj[index, :2].T, 1, N_MPC+1)\n",
    "# Initial reference angles\n",
    "t0 = repmat(traj[index, 2].T, 1, N_MPC+1)\n",
    "\n",
    "# With preview\n",
    "# Initial reference point\n",
    "r0 = traj[index:index+N_MPC+1, :2].T\n",
    "t0 = traj[index:index+N_MPC+1, 2].T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "F = model_F(dt=dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import namedtuple\n",
    "Line = namedtuple('Line', 't x y theta')\n",
    "finish_line = Line(10*env.frame_rate, pose.x, pose.y, pose.theta) #2.2 same as start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "opti = Opti()\n",
    "\n",
    "x = opti.variable(5,N+1)    # States with dimension (n_x, prediction_horizon+1) (x(0),...,x(N+1))\n",
    "u = opti.variable(2,N)      # Inputs with dimension (n_u, prediction_horizon) (u(0),...,u(N))\n",
    "l = opti.variable(K*i_j)      # Lambda of convex hull\n",
    "#l_margin = opti.variable(CM, N)      # Lambda for convex combination of margin\n",
    "x0 = opti.parameter(5,1)    # Parameter to set the initial state conditions (x(0))\n",
    "D = opti.parameter(5,K*i_j)     # Nearest neighbors\n",
    "J = opti.parameter(1, K*i_j)    # A matrix time, iteration with the old states\n",
    "t_to_N = opti.parameter(1, N-1)  # Next t time steps\n",
    "margins = opti.parameter(2, CM)   # Margins for the track bound constraints\n",
    "Q1 = opti.parameter(1)\n",
    "\n",
    "def h(x):\n",
    "   # return 1 if it gets across the finish line\n",
    "   # finish line is defined as the area where t is enough and y > y_finish\n",
    "   return if_else(\n",
    "       logic_and(\n",
    "           t_to_N, \n",
    "           logic_and(x[1,:]>=finish_line.y, \n",
    "                     logic_and(mod(x[2,:], 2*pi)==finish_line.theta, x[0,:] == finish_line.x)\n",
    "                    )\n",
    "       ), 0, 1)\n",
    "\n",
    "def boundary(l_margin):\n",
    "    return if_else(vec(l_margin) >= 0, 0, 1e3)\n",
    "\n",
    "obj = J@l + Q1*fabs(D[2, :]@l - x[2,N]) #+ sum2(h(x[:3,:N-1])) + sum1(boundary(l_margin))\n",
    "\n",
    "opti.minimize(obj)\n",
    "\n",
    "# Constraints Definition\n",
    "\n",
    "# 1) System dynamics constraint over the prediction horizon\n",
    "for k_ in range(0,N):\n",
    "   opti.subject_to(x[:,k_+1] == F(x[:,k_],u[:,k_])) # No delay\n",
    "   #opti.subject_to(x[:2,k_+1] == margins@l_margin[:,k_]) # Convex combination of margins\n",
    "# opti.subject_to(sum1(l_margin) == 1) # Sum of convex coefficients of margins = 1\n",
    "# opti.subject_to(vec(l_margin) >= 0) # Convex coefficients of margins >= 0\n",
    "    \n",
    "# 2) Additional states/inputs constraints \n",
    "opti.subject_to(vec(u) <= 0.5)\n",
    "opti.subject_to(vec(u) >= -0.1)\n",
    "# 3) Force the state variable at instant 0 to be equal to the parameter value containing x0 value\n",
    "opti.subject_to(x[:,0] == x0)\n",
    "# 4) Set the convex hull constraints\n",
    "opti.subject_to(l >= 0)\n",
    "opti.subject_to(sum1(l) == 1)\n",
    "opti.subject_to(D[:2, :]@l == x[:2,N])\n",
    "# opti.subject_to(D[2, :]@l+0.2 >= x[2,N])\n",
    "# opti.subject_to(D[2, :]@l-0.2 <= x[2,N])\n",
    "opti.subject_to(D[3:, :]@l == x[3:,N])\n",
    "\n",
    "opti.set_value(x0,[pose.x, pose.y, pose.theta, 0, 0]) # Set the initial x0 value\n",
    "\n",
    "# Ipopt\n",
    "opts = dict()\n",
    "opts[\"ipopt.print_level\"] = 0 # 8 to see constraint violations, see https://stackoverflow.com/questions/44558507/how-to-find-which-constraint-is-violated-from-pyomos-ipopt-interface\n",
    "opts[\"ipopt.acceptable_constr_viol_tol\"] = 1e-5\n",
    "opts[\"print_time\"] = False\n",
    "opts[\"verbose\"] = False\n",
    "opti.solver('ipopt',opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LMPC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This instruction transfom all the Opti problem defined above into a callable function\n",
    "M = opti.to_function('M',[x0, D, J, t_to_N, margins, Q1],[u[:,0], l],['x0', 'D', 'J', 't_to_N', 'central_line', 'Q1'],['u_opt', \"lambda\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#M.save(f'controllers/LMPC_max03_noborder_noorientation_k{K}_ij{i_j}_N{N}.casadi')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loop 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "******************************************************************************\n",
      "This program contains Ipopt, a library for large-scale nonlinear optimization.\n",
      " Ipopt is released as open source code under the Eclipse Public License (EPL).\n",
      "         For more information visit http://projects.coin-or.org/Ipopt\n",
      "******************************************************************************\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# First loop\n",
    "Mpc = Function.load('controllers/N10_max03_fittedspeed.casadi')\n",
    "\n",
    "\n",
    "# MPC loop\n",
    "# F = utils.model_F_tuned(dt=dt, method=\"speed\")\n",
    "X_log = np.empty((5,0))\n",
    "U_log = np.empty((2,0))\n",
    "\n",
    "x = [pose.x, pose.y, pose.theta, 0, 0]\n",
    "r = r0\n",
    "tr = t0\n",
    "idx = index\n",
    "u_delay = u_delay0\n",
    "\n",
    "kdtree = spatial.KDTree(traj[:, :2])\n",
    "\n",
    "t = 0\n",
    "while True:\n",
    "    u = Mpc(x, r, tr, u_delay,  1e3, 5e-4, 1, 1e-3)\n",
    "\n",
    "    U_log = np.column_stack((U_log, u))\n",
    "    X_log = np.column_stack((X_log, x))\n",
    "\n",
    "    u_delay = np.column_stack((u_delay, u))[:, -delay:]\n",
    "\n",
    "    # simulate\n",
    "    x = F(x,u)\n",
    "\n",
    "    distance = (traj[idx, 0] - x[0])**2 + (traj[idx, 1] - x[1])**2\n",
    "\n",
    "    _,idx = kdtree.query(np.array([x[0], x[1]]).reshape(-1))\n",
    "    if idx+N_MPC+1 < traj.shape[0]:\n",
    "        r = traj[idx:idx+N_MPC+1, :2].T\n",
    "        tr = traj[idx:idx+N_MPC+1, 2].T\n",
    "    else:\n",
    "        r = vertcat(traj[idx:, :2], traj[:idx+N_MPC+1-traj.shape[0], :2]).T\n",
    "        tr = vertcat(traj[idx:, 2], traj[:idx+N_MPC+1-traj.shape[0], 2]).T\n",
    "\n",
    "    if traj[idx, 1] >= finish_line.y and t >= finish_line.t+300:\n",
    "        break\n",
    "    t += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(constrained_layout=True, figsize=(10, 5))\n",
    "ax_dict = fig.subplot_mosaic(\"\"\"AC\"\"\")\n",
    "ax_dict[\"A\"].text(X_log[0,0], X_log[1,0], 'START')\n",
    "ax_dict[\"A\"].plot(traj[:,0], traj[:,1], \"b\")\n",
    "ax_dict[\"A\"].plot(traj[index,0], traj[index,1], 'go')\n",
    "ax_dict[\"A\"].plot(X_log[0,:], X_log[1,:], \"r\")\n",
    "ax_dict[\"A\"].plot(traj[idx, 0], traj[idx,1], 'yo')\n",
    "utils.show_on_map_array(env, np.array([X_log[0,:], X_log[1,:]]).T, fig=ax_dict[\"C\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# all_points: [x, y, theta, v, w, steps to arrive]\n",
    "all_points = X_log\n",
    "X_log_orig = X_log\n",
    "first_loop_len = all_points.shape[1]\n",
    "all_points = np.vstack((all_points, np.arange(first_loop_len)[::-1]))\n",
    "all_points_orig = all_points\n",
    "x_orig = x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loop > 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import NearestNeighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython import display as ipythondisplay\n",
    "from timeit import default_timer as timer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.patches.Polygon at 0x7f8bf016ea30>]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(*inside.T, c=\"b\")\n",
    "plt.plot(*outside.T, c=\"b\")\n",
    "plt.plot(traj[:,0], traj[:,1], \"b--\")\n",
    "idx = 63\n",
    "more = 20\n",
    "plt.fill([inside[idx,0], outside[idx,0], outside[idx+N+5,0], outside[idx+N+more,0], inside[idx+N+more,0]], [inside[idx,1], outside[idx,1], outside[idx+N+5,1], outside[idx+N+more,1], inside[idx+N+more,1]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### TODO next: time for next N steps <= min time until now in the cost function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_lmpc(q1):\n",
    "    n_iterations = 1\n",
    "    error = 0\n",
    "    idx = 63\n",
    "\n",
    "    real_time_plot = False\n",
    "\n",
    "    # If it has to stop at the end of the lap, set this to False\n",
    "    # If false flying start will still be used in the last laps\n",
    "    flying_start = False\n",
    "    next_lap_start_times = -np.arange(N+K*i_j) if flying_start else 0\n",
    "\n",
    "    # For debugging\n",
    "    X_log = X_log_orig\n",
    "    # X_log[2,:] = (X_log_orig[2,:]+np.pi) % (2*np.pi) - np.pi\n",
    "    all_points = all_points_orig\n",
    "    # all_points[2,:] = (all_points_orig[2,:]+np.pi) % (2*np.pi) - np.pi\n",
    "    last_iterations = np.hstack([all_points]*i_j)\n",
    "    x = x_orig\n",
    "\n",
    "    if idx+N > all_points.shape[1]:\n",
    "        idx = all_points.shape[1] - idx\n",
    "\n",
    "    Js = []\n",
    "    idxs = []\n",
    "    plain_loops = []\n",
    "    loops_with_time = [all_points]\n",
    "\n",
    "    kdins = spatial.KDTree(inside)\n",
    "    ins_len = inside.shape[0]\n",
    "    # kdout = spatial.KDTree(outside)\n",
    "    # out_len = outside.shape[0]\n",
    "\n",
    "    step_times = [0]\n",
    "    casadi_times = [0]\n",
    "    iteration_times = [0]\n",
    "\n",
    "    # DEBUG\n",
    "    debug_flag = False\n",
    "\n",
    "    for iteration in range(n_iterations):\n",
    "        if debug_flag:\n",
    "            break\n",
    "        iteration_time_start = timer()\n",
    "        last_loop = X_log\n",
    "        X_log = np.empty((5,0))\n",
    "        U_log = np.empty((2,0))\n",
    "\n",
    "        # Normalize the angles\n",
    "        # Overfit the starting angle to avoid normalization problems ;)\n",
    "        x[2] = mod(x[2]+pi, 2*pi)-pi\n",
    "\n",
    "        # x = [pose.x, pose.y, pose.theta, 0, 0]\n",
    "        # idx = int(index)\n",
    "\n",
    "        kdtree = spatial.KDTree(last_loop[:2, :frame_rate*10].T)\n",
    "\n",
    "        # Method 0, cut, working poorly\n",
    "        #nbrs = NearestNeighbors(n_neighbors=K*i_j, algorithm='ball_tree').fit(last_iterations[:2, :100].T)\n",
    "\n",
    "        # Method 1, hide\n",
    "        last_iterations_filtered = last_iterations[np.vstack([last_iterations[-1] > K]*6)].reshape(6,-1)\n",
    "\n",
    "        # Method 2, enlarge, not working\n",
    "        # last_iterations_filtered = last_iterations\n",
    "        # last_iterations_filtered[-1, last_iterations_filtered[-1] < 2*K] += 1e3\n",
    "\n",
    "        nbrs = NearestNeighbors(n_neighbors=K*i_j, algorithm='ball_tree').fit(last_iterations_filtered[:2].T)\n",
    "        _,idx = kdtree.query(np.array([x[0], x[1]]).reshape(-1), workers=-1)\n",
    "        t = 0\n",
    "        print(f\"\"\"Iteration: {iteration}, \n",
    "              avg time per step: {sum(step_times)/len(step_times)}, \n",
    "              avg casadi time: {sum(casadi_times)/len(casadi_times)}.\n",
    "              avg iteration time: {sum(iteration_times)/len(iteration_times)}.\"\"\")\n",
    "        print(\"Last time: \", [t.shape[1]*dt for t in loops_with_time])\n",
    "\n",
    "\n",
    "        already_changed = False\n",
    "        while True:\n",
    "            start_step = timer()\n",
    "            distances, indices = nbrs.kneighbors([last_loop[:2, (idx+N)%last_loop.shape[1]].T])\n",
    "            error += sum([sum(d) for d in distances])\n",
    "            indices = indices.reshape(-1)\n",
    "\n",
    "            if t == 0:\n",
    "                D = last_iterations_filtered[:-1, indices]\n",
    "                J = last_iterations_filtered[-1, indices].reshape(-1)\n",
    "            else:\n",
    "                S = last_iterations_filtered[:, indices]@l\n",
    "                distances, indices = nbrs.kneighbors(np.array(S[:2].T))\n",
    "                indices = indices.reshape(-1)\n",
    "                D = last_iterations_filtered[:-1, indices]\n",
    "                J = last_iterations_filtered[-1, indices].reshape(-1)\n",
    "\n",
    "            Js.append(J)\n",
    "            idxs.append(idx)\n",
    "\n",
    "            # Closest point to the current pose in inside line\n",
    "            _, border_idx = kdins.query(np.array([x[0], x[1]]).reshape(-1), workers=-1)\n",
    "            # Margins in track for convex hull\n",
    "            margins = np.array([\n",
    "                inside[border_idx],\n",
    "                inside[(border_idx+N+more)%ins_len],\n",
    "                outside[border_idx],\n",
    "                outside[(border_idx+N+int(more/4))%ins_len],\n",
    "                outside[(border_idx+N+more)%ins_len]]).T\n",
    "\n",
    "            casadi_timer_start = timer()\n",
    "            u, l = M(x, DM(D[:, :]), DM(J)/600, (np.arange(t, t+N-1)>=finish_line.t).T, margins, q1)\n",
    "            casadi_timer_end = timer()\n",
    "\n",
    "            U_log = np.column_stack((U_log, u))\n",
    "            X_log = np.column_stack((X_log, x))\n",
    "\n",
    "            # simulate\n",
    "            x = F(x,u)\n",
    "            x[2] = x[2] + np.random.randint(-20, 20)*0.01\n",
    "\n",
    "            _,idx_new = kdtree.query(np.array([x[0], x[1]]).reshape(-1), workers=-1)\n",
    "            if idx_new >= idx:\n",
    "                idx = idx_new\n",
    "                if idx+N > traj.shape[0]:\n",
    "                    idx = traj.shape[0] - idx\n",
    "\n",
    "            if x[1] >= finish_line.y and t >= finish_line.t and x[0] >= finish_line.x-0.1:\n",
    "                break\n",
    "            t += 1\n",
    "\n",
    "            # DEBUG:\n",
    "            # if t == 100:\n",
    "            #     break\n",
    "            if t/frame_rate > 60 and not debug_flag:\n",
    "                debug_flag = True\n",
    "                break\n",
    "            if t == K+N:\n",
    "                # Now it can see all the points\n",
    "                kdtree = spatial.KDTree(last_loop[:2, :].T)\n",
    "                last_iterations_filtered = last_iterations\n",
    "                # Needed for method 1\n",
    "                nbrs = NearestNeighbors(n_neighbors=K*i_j, algorithm='ball_tree').fit(last_iterations[:2, :].T)\n",
    "            # Before the finish line\n",
    "            if x[1] > 1 and x[1] < 1.7 and x[0] > 1.5 and not already_changed:\n",
    "                # The first points in the next iteration have time 0\n",
    "                last_iterations_filtered[-1, :N+K*i_j] = next_lap_start_times\n",
    "                # The first points in the next iteration are as in the first loop\n",
    "                last_iterations_filtered[:-1, :N+1] = X_log_orig[:, :N+1]\n",
    "                # After one iteration the angle is +2*pi \n",
    "                last_iterations_filtered[2, :N+K*i_j] += 2*np.pi\n",
    "                already_changed = True\n",
    "            end_step = timer()\n",
    "            step_times.append(end_step-start_step)\n",
    "            casadi_times.append(casadi_timer_end-casadi_timer_start)\n",
    "        last_points = X_log\n",
    "        last_points = np.vstack((last_points, np.arange(last_points.shape[1])[::-1]))\n",
    "\n",
    "        plain_loops.append(X_log)\n",
    "        loops_with_time.append(last_points)\n",
    "\n",
    "        # I use the last i_j iterations\n",
    "        if i_j_all:\n",
    "            last_iterations = np.hstack(loops_with_time)\n",
    "        else:\n",
    "            last_iterations = np.hstack(loops_with_time[-i_j:])\n",
    "\n",
    "        # all_points_len = all_points.shape[1]\n",
    "        # if all_points_len > last_points.shape[1]:\n",
    "        #     last_points = np.pad(last_points, ((0,0), (0, all_points_len-last_points.shape[1])), 'constant', constant_values=(0,0))\n",
    "        # if all_points_len < last_points.shape[1]:\n",
    "        #     all_points = np.pad(all_points, ((0,0), (0, last_points.shape[1]-all_points_len)), 'constant', constant_values=(0,0))\n",
    "        # all_points = np.hstack((all_points, last_points))\n",
    "\n",
    "        iteration_time_end = timer()\n",
    "        iteration_times.append(iteration_time_end-iteration_time_start)\n",
    "\n",
    "        # If it gets lower than 11s it is cheating\n",
    "        if loops_with_time[-1].shape[1]*dt < 11:\n",
    "            break\n",
    "\n",
    "\n",
    "        if loops_with_time[-1].shape[1]*dt < 11.9:\n",
    "            # 11.8s is record time without flying start\n",
    "            next_lap_start_times = -np.arange(N+K*i_j)\n",
    "\n",
    "        # 11.7s is the record time\n",
    "        if loops_with_time[-1].shape[1]*dt < 11.8:\n",
    "            break\n",
    "    return error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "6.2314179948102115"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_lmpc(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 17:59:35,221]\u001b[0m A new study created in memory with name: no-name-79da8ed6-b2fe-4b30-aa20-bf764c2fedd4\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:00:06,566]\u001b[0m Trial 0 finished with value: 36.20646565338165 and parameters: {'x': 6.654636551226192}. Best is trial 0 with value: 36.20646565338165.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:00:12,229]\u001b[0m Trial 1 finished with value: 6.166648494769404 and parameters: {'x': 2.158726124004946}. Best is trial 1 with value: 6.166648494769404.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:00:18,067]\u001b[0m Trial 2 finished with value: 5.921582431860104 and parameters: {'x': 7.724560163518904}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:00:52,588]\u001b[0m Trial 3 finished with value: 36.1277355908983 and parameters: {'x': 0.0625723981993248}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:01:23,418]\u001b[0m Trial 4 finished with value: 35.30358396463139 and parameters: {'x': 7.386824868560244}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:01:56,268]\u001b[0m Trial 5 finished with value: 36.098571248462186 and parameters: {'x': 35.463732685492005}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:02:28,471]\u001b[0m Trial 6 finished with value: 35.09660861716041 and parameters: {'x': 4.66846994695292}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:03:02,935]\u001b[0m Trial 7 finished with value: 36.5384818661416 and parameters: {'x': 156.60649409841275}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:03:09,021]\u001b[0m Trial 8 finished with value: 6.295446060399809 and parameters: {'x': 0.11787248284113325}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:03:49,870]\u001b[0m Trial 9 finished with value: 36.09959882972121 and parameters: {'x': 6.0891854546775015}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:04:24,926]\u001b[0m Trial 10 finished with value: 36.40015180598386 and parameters: {'x': 920.2903728187059}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:04:58,311]\u001b[0m Trial 11 finished with value: 36.226883111731674 and parameters: {'x': 0.49070345562630324}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:05:04,171]\u001b[0m Trial 12 finished with value: 6.2126965884356515 and parameters: {'x': 0.6330180272357762}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:05:35,944]\u001b[0m Trial 13 finished with value: 35.30173665780116 and parameters: {'x': 0.728908226268465}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:06:10,708]\u001b[0m Trial 14 finished with value: 34.36731533888127 and parameters: {'x': 0.012051871670871173}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:06:45,794]\u001b[0m Trial 15 finished with value: 35.89092317112397 and parameters: {'x': 43.552506523706334}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:06:52,157]\u001b[0m Trial 16 finished with value: 6.301101604822229 and parameters: {'x': 45.92533779083152}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:07:25,351]\u001b[0m Trial 17 finished with value: 36.672779508641455 and parameters: {'x': 1.3602371417850387}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:07:30,450]\u001b[0m Trial 18 finished with value: 6.072131205878506 and parameters: {'x': 0.11401604517436394}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:07:36,464]\u001b[0m Trial 19 finished with value: 6.081051586624956 and parameters: {'x': 0.11585969272679024}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:08:07,230]\u001b[0m Trial 20 finished with value: 36.20302066117884 and parameters: {'x': 0.010982050362390113}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:08:38,975]\u001b[0m Trial 21 finished with value: 36.37255529346616 and parameters: {'x': 0.1467875758230688}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:09:11,486]\u001b[0m Trial 22 finished with value: 36.00936268740195 and parameters: {'x': 0.031952173720776474}. Best is trial 2 with value: 5.921582431860104.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:09:17,373]\u001b[0m Trial 23 finished with value: 5.919657882560674 and parameters: {'x': 0.19574248841140077}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:09:48,527]\u001b[0m Trial 24 finished with value: 36.25387253432875 and parameters: {'x': 0.32808375157128034}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:09:55,357]\u001b[0m Trial 25 finished with value: 8.126735937702723 and parameters: {'x': 14.933997273623067}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:10:25,920]\u001b[0m Trial 26 finished with value: 35.53861618930706 and parameters: {'x': 0.04007575788624462}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:10:58,715]\u001b[0m Trial 27 finished with value: 37.06202900007637 and parameters: {'x': 0.2723479296994778}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:11:34,506]\u001b[0m Trial 28 finished with value: 35.30571148560037 and parameters: {'x': 1.4297540601754364}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:12:05,632]\u001b[0m Trial 29 finished with value: 36.06885443243803 and parameters: {'x': 12.335414326824012}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:12:35,865]\u001b[0m Trial 30 finished with value: 39.352919383633626 and parameters: {'x': 0.025610445943808714}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:12:41,258]\u001b[0m Trial 31 finished with value: 6.030377898230981 and parameters: {'x': 0.1575693595109431}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:13:12,433]\u001b[0m Trial 32 finished with value: 36.274117897416396 and parameters: {'x': 0.21366968776569578}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:13:44,176]\u001b[0m Trial 33 finished with value: 36.9527812051193 and parameters: {'x': 2.3177557882818838}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:13:49,066]\u001b[0m Trial 34 finished with value: 6.2268591556089685 and parameters: {'x': 0.07059178038861152}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:14:20,842]\u001b[0m Trial 35 finished with value: 36.426171882838645 and parameters: {'x': 1.113267242451479}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:14:52,020]\u001b[0m Trial 36 finished with value: 36.703727691742074 and parameters: {'x': 3.2946966034868055}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:14:56,791]\u001b[0m Trial 37 finished with value: 6.454218290075921 and parameters: {'x': 0.06289565755781637}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:15:28,120]\u001b[0m Trial 38 finished with value: 35.79849065248163 and parameters: {'x': 12.292868629620667}. Best is trial 23 with value: 5.919657882560674.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:15:33,686]\u001b[0m Trial 39 finished with value: 5.517232467409396 and parameters: {'x': 0.17450154412852512}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:16:06,749]\u001b[0m Trial 40 finished with value: 36.018509412821146 and parameters: {'x': 100.09526441714989}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:16:35,538]\u001b[0m Trial 41 finished with value: 37.24280510625997 and parameters: {'x': 0.15539734620228174}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:17:07,999]\u001b[0m Trial 42 finished with value: 37.74252159921541 and parameters: {'x': 0.40046366900575253}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:17:14,464]\u001b[0m Trial 43 finished with value: 6.740515648653975 and parameters: {'x': 0.08581940396424168}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:17:44,250]\u001b[0m Trial 44 finished with value: 35.935710329948215 and parameters: {'x': 0.8046134405242988}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:18:12,678]\u001b[0m Trial 45 finished with value: 37.26824002541794 and parameters: {'x': 0.02385879285618563}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:18:44,686]\u001b[0m Trial 46 finished with value: 36.20490516606382 and parameters: {'x': 4.074166199574647}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:19:10,647]\u001b[0m Trial 47 finished with value: 35.26616910479306 and parameters: {'x': 0.04779624118062142}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:19:16,617]\u001b[0m Trial 48 finished with value: 6.1427865443257925 and parameters: {'x': 0.2056479104695289}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:19:47,309]\u001b[0m Trial 49 finished with value: 36.79481941958235 and parameters: {'x': 0.5340094408439707}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:20:15,757]\u001b[0m Trial 50 finished with value: 36.65194116438044 and parameters: {'x': 0.09517167986821025}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:20:21,151]\u001b[0m Trial 51 finished with value: 5.5784362186289185 and parameters: {'x': 0.1257616939434876}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:20:51,731]\u001b[0m Trial 52 finished with value: 35.235799003947946 and parameters: {'x': 0.16930143091194744}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:21:20,040]\u001b[0m Trial 53 finished with value: 35.43391510452438 and parameters: {'x': 0.01865163341539079}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:21:25,679]\u001b[0m Trial 54 finished with value: 6.438046057097667 and parameters: {'x': 0.34512670646379323}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:22:04,043]\u001b[0m Trial 55 finished with value: 36.1561685685047 and parameters: {'x': 0.09475013817688145}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:22:38,190]\u001b[0m Trial 56 finished with value: 36.187198644833174 and parameters: {'x': 1.98187433247425}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:23:13,969]\u001b[0m Trial 57 finished with value: 35.62993394245395 and parameters: {'x': 0.23750064341590396}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:23:50,258]\u001b[0m Trial 58 finished with value: 35.94109334419422 and parameters: {'x': 0.8793869283772203}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:24:21,914]\u001b[0m Trial 59 finished with value: 35.27595670069378 and parameters: {'x': 6.466944676950031}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:24:49,604]\u001b[0m Trial 60 finished with value: 35.970864279187886 and parameters: {'x': 0.045445015309909104}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:24:54,100]\u001b[0m Trial 61 finished with value: 6.210353214727161 and parameters: {'x': 0.13023906441051739}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:25:29,035]\u001b[0m Trial 62 finished with value: 34.685814187126695 and parameters: {'x': 21.729387547254355}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:25:35,861]\u001b[0m Trial 63 finished with value: 6.022522133194826 and parameters: {'x': 0.11486494925863801}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:26:18,400]\u001b[0m Trial 64 finished with value: 36.44391116702032 and parameters: {'x': 755.599382870591}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:26:52,320]\u001b[0m Trial 65 finished with value: 36.68106699814372 and parameters: {'x': 0.01640596752142014}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:27:28,088]\u001b[0m Trial 66 finished with value: 36.0529395997393 and parameters: {'x': 0.4845028150591879}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:27:34,178]\u001b[0m Trial 67 finished with value: 5.653211251378069 and parameters: {'x': 0.05586151460014075}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:27:42,114]\u001b[0m Trial 68 finished with value: 6.451944241636838 and parameters: {'x': 0.057572008547562455}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:28:17,393]\u001b[0m Trial 69 finished with value: 35.33557619331133 and parameters: {'x': 0.03699533408873039}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:28:52,587]\u001b[0m Trial 70 finished with value: 36.09179483636845 and parameters: {'x': 0.28993774916875675}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:29:02,305]\u001b[0m Trial 71 finished with value: 10.433930784371428 and parameters: {'x': 0.11879146207415979}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:29:38,717]\u001b[0m Trial 72 finished with value: 36.13932101640112 and parameters: {'x': 0.07509713339833576}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:29:43,950]\u001b[0m Trial 73 finished with value: 6.091493305890522 and parameters: {'x': 0.17077217845040238}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:30:17,950]\u001b[0m Trial 74 finished with value: 36.32372073868517 and parameters: {'x': 0.029189973128623852}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:30:51,350]\u001b[0m Trial 75 finished with value: 36.96850120043441 and parameters: {'x': 0.05602373895951006}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:31:20,034]\u001b[0m Trial 76 finished with value: 36.98529170553793 and parameters: {'x': 0.11697729138259017}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:31:51,325]\u001b[0m Trial 77 finished with value: 36.72450328384185 and parameters: {'x': 9.078563900743841}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:32:24,145]\u001b[0m Trial 78 finished with value: 37.49287515418963 and parameters: {'x': 0.2377868359317686}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:32:29,917]\u001b[0m Trial 79 finished with value: 6.791738929830636 and parameters: {'x': 24.73276995069228}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:33:09,574]\u001b[0m Trial 80 finished with value: 37.09872192124168 and parameters: {'x': 0.40850858488052}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:33:46,949]\u001b[0m Trial 81 finished with value: 35.85809333898422 and parameters: {'x': 0.10465293765272471}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:34:24,605]\u001b[0m Trial 82 finished with value: 35.70524175460607 and parameters: {'x': 0.07108975186057445}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:35:03,395]\u001b[0m Trial 83 finished with value: 36.30282758625192 and parameters: {'x': 0.1743227354088172}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:35:44,156]\u001b[0m Trial 84 finished with value: 35.683082321240626 and parameters: {'x': 0.1368005807571173}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:36:19,929]\u001b[0m Trial 85 finished with value: 35.71052781495205 and parameters: {'x': 0.0798085038163255}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2023-03-11 18:36:52,237]\u001b[0m Trial 86 finished with value: 35.70581364791881 and parameters: {'x': 4.9271120551136915}. Best is trial 39 with value: 5.517232467409396.\u001b[0m\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration: 0, \n",
      "              avg time per step: 0.0, \n",
      "              avg casadi time: 0.0.\n",
      "              avg iteration time: 0.0.\n",
      "Last time:  [50.800000000000004]\n"
     ]
    }
   ],
   "source": [
    "def objective(trial):\n",
    "    x = trial.suggest_loguniform('x', 1e-2, 1e3)\n",
    "    return run_lmpc(x)\n",
    "\n",
    "study = optuna.create_study()\n",
    "study.optimize(objective, n_trials=100)\n",
    "\n",
    "study.best_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "study.best_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f\"Average iteration computation time: {sum(iteration_times)/len(iteration_times)}s\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(traj[:,0], traj[:,1], \"b--\")\n",
    "plt.plot(*inside.T, \"b\")\n",
    "plt.plot(*outside.T, \"b\")\n",
    "plt.plot(*plain_loops[0][:2,:], \"g\", label=\"First iteration\")\n",
    "plt.plot(*plain_loops[int(len(plain_loops)/2)][:2,:], \"y\", label=\"Mid iteration\")\n",
    "plt.plot(*X_log[:2,:], \"r\", label=\"Last iteration\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(traj[:,0], traj[:,1], \"b--\")\n",
    "plt.plot(*inside.T, \"b\")\n",
    "plt.plot(*outside.T, \"b\")\n",
    "plt.plot(*X_log[:2,:], \"r\", label=\"Last iteration\")\n",
    "plt.fill(D[0], D[1], c=\"g\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "f\"Max speed: {X_log[3,:].max()}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(X_log[3,:], \"b\", label=\"Last iteration speed\")\n",
    "plt.title(\"Last iteration speed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(traj[:,0], traj[:,1], \"b--\")\n",
    "plt.plot(*inside.T, \"b\")\n",
    "plt.plot(*outside.T, \"b\")\n",
    "cm = plt.cm.get_cmap('seismic')\n",
    "sc = plt.scatter(X_log[0,:], X_log[1,:], c=X_log[3,:], cmap=cm, label=\"Last iteration\")\n",
    "plt.colorbar(sc)\n",
    "plt.title(\"Speed profile\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "[loop.shape[1]*dt for loop in plain_loops]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.bar(list(range(len(plain_loops)))[:-1], [loop.shape[1]*dt for loop in plain_loops][:-1], label=\"Time to finish\")\n",
    "plt.title(\"Time per lap for each iteration\")\n",
    "plt.xlabel(\"Lap\")\n",
    "plt.ylabel(\"Time to finish [s]\")\n",
    "plt.ylim(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(idxs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = plt.figure(constrained_layout=True, figsize=(10, 5))\n",
    "ax_dict = fig.subplot_mosaic(\"\"\"AC\n",
    "        AC\"\"\")\n",
    "ax_dict[\"A\"].text(X_log[0,0], X_log[1,0], 'START')\n",
    "ax_dict[\"A\"].plot(traj[:,0], traj[:,1], \"b\")\n",
    "ax_dict[\"A\"].plot(traj[index,0], traj[index,1], 'go')\n",
    "ax_dict[\"A\"].plot(X_log[0,:], X_log[1,:], \"r\")\n",
    "ax_dict[\"A\"].plot(traj[idx, 0], traj[idx,1], 'yo')\n",
    "# ax_dict[\"B\"].plot(np.arange(len(errors))*dt, np.sqrt(errors))\n",
    "utils.show_on_map_array(env, np.array([X_log[0,:], X_log[1,:]]).T, fig=ax_dict[\"C\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xs = np.concatenate([loop[0,:] for loop in plain_loops])\n",
    "ys = np.concatenate([loop[1,:] for loop in plain_loops])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_video = False\n",
    "\n",
    "if save_video:\n",
    "    from matplotlib.animation import FuncAnimation\n",
    "\n",
    "    ratio = 15\n",
    "    fig,ax = plt.subplots()\n",
    "\n",
    "    def init():\n",
    "        ax.plot(traj[:,0], traj[:,1], \"b--\", zorder=0)\n",
    "        ax.plot(*outside.T, \"b\", zorder=0)\n",
    "        background = ax.plot(*inside.T, \"b\", zorder=0)\n",
    "        return background\n",
    "\n",
    "    def animate(i):\n",
    "        line, = ax.plot(xs[:int(i*ratio)], ys[:int(i*ratio)], color='red', lw=1)\n",
    "        return line\n",
    "\n",
    "    ani = FuncAnimation(fig, animate, init_func=init, blit=False, repeat=True, frames=int(xs.shape[0]/ratio))#, interval=(1/env.frame_rate)*ratio*1e3\n",
    "    ani.save(\"assets/lmpc.mp4\", writer='ffmpeg', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Video\n",
    "\n",
    "Video(\"assets/lmpc.mp4\", width=600)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gym simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The MPC does not consider the delay yet!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "record = False\n",
    "\n",
    "if record:\n",
    "    import imageio\n",
    "    import cv2\n",
    "\n",
    "    env.reset()\n",
    "    env.unwrapped.start_pose = [[0.3, 0, 0.41029359288296474], X_log[2,0]%(2*np.pi)]\n",
    "    env.reset()\n",
    "    env.unwrapped.start_pose = [[0.3, 0, 0.41029359288296474], X_log[2,0]%(2*np.pi)]\n",
    "    pose = get_position(env)\n",
    "    images = []\n",
    "    positions = []\n",
    "    odoms = [pose]\n",
    "    actions = [[0,0]]*10\n",
    "    v0 = 0\n",
    "    w0 = 0\n",
    "    for action in U_log.T:\n",
    "        env.step(action)\n",
    "        positions.append(get_position(env))\n",
    "        img = env.render(mode='rgb_array')\n",
    "        img = cv2.resize(img, dsize=(400, 300), interpolation=cv2.INTER_CUBIC)\n",
    "        images.append(img)\n",
    "\n",
    "        p, v0, w0 = my_odometry(action, odoms[-1].x, odoms[-1].y, odoms[-1].theta, v0, w0, dt=dt)\n",
    "        odoms.append(p)\n",
    "        actions.append(action)\n",
    "\n",
    "    imageio.mimsave(\"assets/lmpc_run.gif\", images, format='GIF', fps=env.frame_rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if record:\n",
    "    plt.plot(*np.array([[p.x, p.y] for p in positions]).T, c='g', label='true', linewidth=5)\n",
    "    plt.plot(*np.array([[p.x, p.y] for p in odoms]).T, c='r', label='odom')\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "if record:\n",
    "    utils.show_on_map(env, positions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import HTML, display\n",
    "# Trick to prevent cache use\n",
    "display(HTML('<img src=\"assets/lmpc_run.gif?%d\" width=\"750\" align=\"center\">' % np.random.randint(10)))"
   ]
  }
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