{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys \n",
    "\n",
    "%cd ../../\n",
    "%pwd\n",
    "\n",
    "from util import utils\n",
    "from util import evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "models = ['gpt-j-6b', 'llama-3-8b', 'mamba-1.4b']\n",
    "datasets = ['mcf']\n",
    "\n",
    "path = '/mnt/scratch/stealth_edits/results/jetpack/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_jetpack_results(num_sample):\n",
    "\n",
    "    template = 'jetpack_results_n{}_{}_{}_layer{}.pickle'\n",
    "\n",
    "    values_to_save = ['edit_success_rate', 'fpr_wiki', 'fpr_other', 'probs_wiki', 'probs_other', 'ppl_op_other', 'crosstalk_count', 'mean_fpr_other', 'std_fpr_other', 'mean_fpr_wiki', 'std_fpr_wiki']\n",
    "\n",
    "    jet_metrics = {}\n",
    "\n",
    "    for dataset_name in datasets:\n",
    "\n",
    "        model_metrics = {}\n",
    "\n",
    "        for model_name in models:\n",
    "\n",
    "            layers = evaluation.model_layer_indices[model_name]\n",
    "            layer_metrics = {key:[] for key in values_to_save}\n",
    "\n",
    "            for l in layers:\n",
    "                try:\n",
    "                    contents = utils.loadpickle(\n",
    "                        os.path.join(path, template.format(\n",
    "                            num_sample,\n",
    "                            dataset_name,\n",
    "                            model_name,\n",
    "                            l\n",
    "                        ))\n",
    "                    )\n",
    "                    layer_metrics['edit_success_rate'].append(contents['edit_success_rate'])\n",
    "                    layer_metrics['crosstalk_count'].append(contents['crosstalk_count']/num_sample)\n",
    "                    layer_metrics['fpr_wiki'].append(contents['fpr_wiki'])\n",
    "                    # layer_metrics['fpr_other'].append(contents['fpr_other'])\n",
    "                    layer_metrics['fpr_other'].append(contents['fpr_all_other'])\n",
    "\n",
    "                    layer_metrics['probs_wiki'].append(contents['probs_wiki'][0])\n",
    "                    # layer_metrics['probs_other'].append(contents['probs_other'][0])\n",
    "                    layer_metrics['probs_other'].append(contents['probs_other_all'][0])\n",
    "\n",
    "                    layer_metrics['ppl_op_other'].append(utils.smart_mean(contents['am_perplexity']/contents['om_perplexity']))\n",
    "\n",
    "                    # mean_fpr_other, std_fpr_other = utils.smart_mean_std(contents['editwise_fpr_other'])\n",
    "                    mean_fpr_other, std_fpr_other = utils.smart_mean_std(contents['editwise_fpr_all_other'])\n",
    "                    layer_metrics['mean_fpr_other'].append(mean_fpr_other)\n",
    "                    layer_metrics['std_fpr_other'].append(std_fpr_other)\n",
    "\n",
    "                    mean_fpr_wiki, std_fpr_wiki = utils.smart_mean_std(contents['editwise_fpr_wiki'])\n",
    "                    layer_metrics['mean_fpr_wiki'].append(mean_fpr_wiki)\n",
    "                    layer_metrics['std_fpr_wiki'].append(std_fpr_wiki)\n",
    "\n",
    "                except Exception as e:\n",
    "                    print('P:', e)\n",
    "                    for k in layer_metrics:\n",
    "                        layer_metrics[k].append(np.nan)\n",
    "\n",
    "            model_metrics[model_name] = copy.deepcopy(layer_metrics)\n",
    "\n",
    "        jet_metrics[dataset_name] = copy.deepcopy(model_metrics)\n",
    "    return copy.deepcopy(jet_metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P: [Errno 2] No such file or directory: '/mnt/scratch/stealth_edits/results/jetpack/jetpack_results_n1000_mcf_llama-3-8b_layer1.pickle'\n",
      "P: [Errno 2] No such file or directory: '/mnt/scratch/stealth_edits/results/jetpack/jetpack_results_n1000_mcf_llama-3-8b_layer5.pickle'\n",
      "P: [Errno 2] No such file or directory: '/mnt/scratch/stealth_edits/results/jetpack/jetpack_results_n4000_mcf_llama-3-8b_layer1.pickle'\n",
      "P: [Errno 2] No such file or directory: '/mnt/scratch/stealth_edits/results/jetpack/jetpack_results_n4000_mcf_llama-3-8b_layer5.pickle'\n",
      "P: [Errno 2] No such file or directory: '/mnt/scratch/stealth_edits/results/jetpack/jetpack_results_n4000_mcf_mamba-1.4b_layer21.pickle'\n"
     ]
    }
   ],
   "source": [
    "jet_metrics1000 = extract_jetpack_results(num_sample=1000)\n",
    "jet_metrics4000 = extract_jetpack_results(num_sample=4000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "image/png": 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BYHjg2AqjmjVr0rBhQwDat2/P8ePHWbFiRZ6TGvdL0zTzk4fWrVtz9epVnnzySXx9fZk1a9ZDiUEUDKUU7733XoaEFRi/cGT3Ob5y5Qoff/wxH3zwAUOHDgWgUaNGlC1blmXLljFx4kQAli5dSmxsLJs2bcLX1xeAtLQ0XnzxRaZOnUqpUqUKoGQFSylFSkoKTk5ONr1NW1G9enVrh1DoDB06lNdff53ffvuNOnXqWDucApGXe47ExERcXFwKOCLbfa+ePn2aF198kdatW+e4bEBAQL7cy1WsWPGBt/Gw+fn54efn99D29+yzz5KWlsavv/5K6dKlzdOfeOIJRo0aRUxMTJbrPqz3dHr3Hp/Tp08D0KBBA4oXL/5QYxGiqJPmJzYuNjaWgQMH4uHhgZ+fHxMnTiQtLc1imXubn5iqsk2YMMFctW337t2Zbj8qKgqdToe/v3+GeTrd3bdHVlXdvL29mTFjhsW0rVu30rx5c1xdXfHx8SE0NJTjx4+b50dHRzN69GjKlCmDk5MT5cuXZ8qUKRm2ERISgouLC35+frzwwgsWTzBSU1OZMGECZcuWxcnJiZIlS9K1a1fzBS2n+bml0+moXbs2ly5dspg+efJkatWqhbu7O6VLl6Zv376Eh4eb54eGhrJnzx62bt1q/h+kP07Zlc/e3p5Ro0bx7bff8tVXX7Fjxw769OnDypUrKVOmTJ7iF7Zlz549XLhwgWeeeSbP627fvh2DwUDPnj3N03x9fXn88cctqvR///33tGvXzpzQAOjVqxcGg4Ht27dnu4/IyEiGDh1K8eLFcXFxoVmzZuzdu9c8P6f3NRgTpcHBwbi7u9OmTRv++ecfi/nJyclMnTqVoKAgnJycqFatWoZq6abqyd999x116tTBycmJb775JtOYTdV7f/nlF9q0aYOrqyvlypVj+fLlud7mxo0bqVu3Ls7OzpQqVYqwsDCSkpLM65rOsT/88AO9evXC3d2dsmXLmuN+7733KFu2LL6+vgwbNozk5OQ8xTd48GA+/fRT/vzzT/NxNVVL//PPP+nUqRPFihXD1dWV4OBg/u///i+7f2OWVZVPnjxJixYtcHV1pWbNmvzwww/Zbgdydw2Kj49n1KhRBAcHm8s3YsQIi/NtuXLluHjxIosXLzaXceXKlQCsWrWKFi1a4Ovra75mHD582GIfV65coVevXgQEBODs7Ez58uUZN26cxTKnTp2iW7dueHl54ebmRufOnS3ef9ldG4OCgmjcuLE5pkeNqenrpEmTKFGihPme4ODBgzz55JOUKlUKNzc36taty2effZZh/eyu69mdNzJrfrJ3716aNWuGi4sLxYsXZ+jQoURGRprnX7hwAU3T+Pzzzxk1ahQ+Pj6ULFmSl19+OcN7MzPZfd5Nn/Vbt27xxhtvoGkaoaGh93NILRw4cIAGDRrg7OxMzZo1+f777zMsk75ZxsqVKxkyZAhg/GKsaRrlypUDjMd6+PDhlC5dGmdnZwIDA+nTp0+W+758+TKaprFjxw7ztNGjR6NpmkUzyClTplCjRg2LdQ0GAzNmzCAgIIDixYszZMgQi3uxzJqfJCcn8+qrr1KhQgWcnJwoU6ZMps1od+/eTb169XBzc6Nx48YcPXo0myMI+/bt4/Dhw0ydOtUioWFStmxZatWqBdw95x0+fJimTZvi7OzM4sWLgZzfXwBz586lUqVKODs74+fnR7t27Th//nyu5+dFTveTufX666/j6upq9SZ+QliL1NSwsswuwPb2d/8tQ4cO5YcffmDu3LmUL1+eDz74IMd+Gg4ePEjTpk0ZPXq0uapnVk9DGjRogMFg4Nlnn+Xll1+mUaNGFvvPq7Vr19K3b1+6devG6tWrcXR05Oeff+bq1avUq1eP5ORk2rRpw4ULF5g+fTq1atXi8uXL7N+/37yNDRs20Lt3b4YMGcLMmTMJDw9n8uTJREVFsWbNGgDmzJnD0qVLeeutt6hRowY3b95k+/bt5i8TOc3Pi4sXL1K+fHmLaTdu3DA/9Y6IiGDevHm0atWKv/76C3t7ez744AP69++Pq6uruU2qKSGRU/n0ej0fffQRH3/8MU899RS///47a9asYceOHbzxxhuF8km7MPrpp58IDAwkMDAww7xz587h5eVFYmIitWrVYtq0aXTv3t08//Tp0/j7++Pj42OxXrVq1fjkk08sljPV5DDx9vamZMmS5qdEmdHr9XTs2JF///2Xt956i4CAAN577z3at29vviHP7n0NxurSb7/9NnPnzjVXD+7fv79F9dtevXqxf/9+pk+fTrVq1fjuu+/o378/Pj4+dOzY0bzcf//9x5gxY3j11VcpW7Zsjs3y+vTpw//+9z8mTZrEmjVreO655yhVqhRPPPFEttv8+uuveeaZZ+jTpw9z587l9OnTTJ06lUuXLrFhwwaLfbzwwgsMHjyY4cOH89FHHzFgwAB+++03/vjjD5YuXcq///5LWFgYFSpUYOrUqbmOb9q0aURERHD69GlzEyTT072uXbsSEBDAJ598gpeXF+fOnePKlSvZHovMpKam8uyzzzJmzBimTZvGW2+9xdNPP83FixezrSafm2tQQkICer2eN998Ez8/Py5fvsybb75J9+7d2bVrF2BsPtepUydatGhhrqpvejJ94cIFBg4cSMWKFUlJSeHLL7+kZcuW/P7771SpUgWAgQMH8t9///Hee+8REBDApUuXLPqR+vfff2nWrBk1a9Zk5cqV6HQ6c/OsM2fO4OTklOO1sVmzZvz44495PraFyb33HHZ2duZkz8KFC2nSpAmffPKJebmLFy/SvHlzRowYgbOzMz///DPPPfccBoOBQYMGAeR4Xc/pvJHe0aNHad++PaGhoaxfv57r168zefJk/vzzTw4cOGDRVOWVV16hW7durFu3jgMHDjBjxgwqVarEiBEjsix/Tp93U3Pe9u3b07t3b4YNG4anp2e2x1QpleG4appmjvXatWt06NCBWrVqsW7dOqKioswPMurWrZvpNjt37syrr75q0VTBVKssLCyM77//nrlz51KuXDnCw8MzTZKYBAYGUq5cOfbu3Uvbtm0BY4Ld2dmZvXv3mptC7tmzh5YtW1qsu2jRIh577DE+/fRTzp49y4QJEwgICMi277enn36anTt3MnXqVJo0aUJERAQbN260WObatWuMGTOGyZMn4+XlxZQpU+jRowf//PMPDg4OmW7X1DQs/Tk9OykpKfTr149x48Yxe/ZsihUrlqv316pVq5g2bRqvv/46TZs2JSYmhn379hEbGwuQ4/y8yul+MjcmTJjA0qVL+e677/IlCSdEoaSEVUyfPl0Bmf7s27dPKaXUn3/+qTRNU5988ol5vbS0NFW+fHmV/l+3a9cuBagjR46YpwHq7bffzlUsEyZMUDqdTgHKxcVFtW/fXn366afKYDBYxOvm5pZhXS8vLzV9+nSllFIGg0GVKVNGdejQIct9ffjhhwpQBw4cyHS+wWBQQUFBqm/fvhbTv//+e6Vpmvrjjz+UUkp17txZPfXUU1nuJ6f5mTEdx19++UWlpqaqmzdvqrfffltpmqbWrFmT5XppaWnqypUrClA//PCDeXqrVq1U586d81y+5ORk9eabb6rbt2+rXbt2qUGDBimllPrqq6/Uzz//nKcyCdvy+OOPZ3hPKKXUggUL1KJFi9SuXbvUpk2b1OOPP64AtX79evMyw4YNU8HBwRnWffvtt5WDg4P5tb29vZozZ06G5WrUqKGGDx+eZWxbtmxRgNq2bZt5WkpKiipbtqzFZymz97Vpupubm7px44Z52ooVKxSgLl++rJRSaufOnRk+J0op1bt3b9WoUSPz60GDBpk/izkx7WPatGkW01u2bKmaNGmS4zbr1aunmjZtajFt2bJlClC///67UuruuWHixInmZaKjo5WdnZ0KDAxUKSkp5ulPP/20qlu37n3FV6NGDYtlIiIiFKC+/vrrHI9Devf+j0zXm61bt5qnnT9/XgHqs88+y3I7ub0G3Ss1NVXt379fAerMmTPm6UFBQWrkyJHZxq7X61VqaqoKDg5WU6ZMMU93c3NT7733XpbrDRw4UFWoUEElJiaap924cUO5u7urxYsXm6dld21csWKF0jRNxcbGZhtjYZTVPYfp/w+o6tWrW1z372UwGFRqaqp6/vnnLT4zOV3Xlcr+vJF+eo8ePVTZsmUtPlM//PCDxefA9N7t2bNnhm21bds22+OQm8+7Upb3NtkJCgrK9LhWrFjRvMykSZOUh4eHio6ONk/bsWOHAszXd6UyngNM546IiAiLfdaoUUOFhYXlGFt6AwcOVKGhoUoppSIjI5WmaWrUqFEqJCREKaVUQkKCcnBwUKtXrzavA6jGjRtbbGfQoEEWZbs3xu3btyvAYjv3GjRokMX9nFJ3z7Gm+9/MjBgxQgEqKSkpx/Ka3u/33rvl5v01cuRIVb9+/Sy3ndP87GT1PzXJ7f2k6Z7cYDCoESNGKB8fn1xdL4UoyqT5iRW5uLhw5MiRDD+mzP2RI0dQStGjRw/zOnZ2dhZPb/PD//3f/3Hu3DneffddOnbsyOHDhxk0aBADBw7M03bOnDnDlStXMjwlTm/Hjh1Uq1aNpk2bZjr/7NmzXLx4kV69epGWlmb+adWqFTqdzvxkrn79+nz33XfMmDGDI0eOZOj/I6f52WnSpAkODg4UL16cCRMmMGnSJHr37m2xzPfff0+zZs3w8vLC3t7e/NTp7Nmz2W47N+VzdHRk6tSpGZr7PPXUU9JJaCEXHh6eafvjsWPHMnLkSEJDQ+nevTvff/89ISEhvPbaaw8ttn379uHp6UmHDh3M0xwcHHjqqacsalJlp27duhblMz0FN9Us2L59O76+vrRp08bi/W/quyZ9z/XFihUjJCQk1/GnP0+C8Wnh0aNHs91mXFwcJ06cyNAcyPR5v7fc7du3N//t5eWFv78/LVu2tHiyWKVKFS5fvnxf8d2rWLFiBAUFMWXKFD799NP7qqFhotPpaNeunfl1uXLlcHFxyXabebkGffbZZ9SrVw93d3ccHBxo0aIFkPM5EYzNRnr06EFAQAB2dnY4ODhw5swZi3Xr16/PO++8w5IlSzh37lyGbWzfvp0nn3wSe3t78/vKx8eHevXqceTIkRxjAChevDhKKa5fv56r5QubzO450nfa2rFjxwwjMURFRTFmzBiCgoJwcHDAwcGBDz/80OJ/k9N1PS/27dtHt27dLD5Tjz/+ON7e3hk+j48//rjF6+rVq2f7fs7r5z23evXqleG4bt682Tz/0KFDtG7d2qJjyDZt2lg0EcyL+vXrs3LlSt555x3++OOPXK3TsmVLDh06REpKCvv27aNEiRIMGzaMo0ePEh8fz8GDB0lNTc1QUyP9OQ9yPsY7duzA1dU12+YwAKVKlbJo6nLvtSI7eRl56d4OuXPz/qpfvz7Hjx8nLCyM/fv3k5qaarGNnObr9XqL65tSKtsY7/d+UinFwIED2bhxI7t27crT9VKIokiSGlak0+lo2LBhhh/Tl9nw8HAcHBwyVDcPCAjI91jKly/PSy+9xFdffcWVK1d44okn+Pzzz/n9999zvY1bt24BZNs84tatW9nON7XL7NGjh/kGysHBAVdXV/R6vfnLwiuvvMKkSZP49NNPady4MSVKlGDmzJnmi0dO87OzatUqjhw5wtatW2nRogVvvfWWxdCaR44cMbcx/uyzzzh48CC//PILgEU7/Acpn0loaOgj28a7KEpKSspVx5Q6nY6nn36aU6dOkZiYCICPj0+mfcJERUVZ3BzndrnM5mfWt05AQECG9sZZubcHfEdHR+Du5+LmzZtERkZavPcdHBwYNmwYaWlpFu2I83qeuzf2gIAAUlNTLdp637vN6OholFIZppuqet9b7szKl9m0zM4DuYnvXpqmsX37dqpVq8bIkSMJDAykYcOGFv2c5JaLi4v5/5FTrCa5vQZt2rSJgQMH0rhxY9atW8cvv/zCpk2bgJzPibdv3+bxxx/n4sWLzJ8/n3379nHkyBHq1Kljse7atWtp27Ytr7zyCpUrV6Zq1aoWVdpv3rzJggULMry39u3bl2mSKTOmz6bpM1fUZHbPkf6ckNlnbvDgwXz55Ze8/PLLbN++nSNHjjB06FCL/01O1/W8iIqKyjSOzM5Duf3smeT1855bfn5+GY5r+iFLw8PDMz23ZjYtN95//30GDBjAvHnzqFWrFmXLlmXJkiXZrtOqVSsSExM5cuQIe/fupWXLluZ+HA4cOMDevXupUKFChr4qMjvG2TXjvXXrFiVLlswx8ZDTtSIzptju7eMsK66urhkeDuXm/TV48GDeffddfvjhBx577DH8/PwYO3as+byQ0/y2bdtanIOyG1HpQe4nU1JS+Prrr2nRooW5LxEhHmXSp4YNK1myJKmpqURFRVncVBb0UyR3d3defPFFtm3bxqlTp6hduzbOzs4ZstGpqanExcWZX5vaZf/3339ZbrtYsWLZJkpMN1iLFi3KNOtsunFycnJixowZzJgxg3PnzrF8+XJmzJhBhQoVGDBgQI7zs1OtWjXz6CctW7YkODiY8ePH06FDBzRNY9OmTXh5ebFu3TpzZ6oXL17Mdpt5LZ8omnx9fYmOjr6vdatWrcr169cznA9Onz5N1apVLZa7t++MmJgYwsPDLZbLLLYbN25kmH79+vX7fqKY2T78/Pyy7Mgs/U1+Xp7GgbFdcvob8uvXr5trXGW1TW9vbzRNy1DumJgYkpOT863cuY0vM1WqVGH9+vWkpqZy4MABpk6dSteuXbl69WqmnTfnp9xeg9avX0/dunVZtmyZeVpuh0Y9ePAgV65c4dtvv7UYdSQmJsai34WSJUuyfPlyPv74Y44ePcqsWbPo3bs3Z86coUKFCvj6+tK5c+dMh8TNbjjO9EyfzbwOxVlU3Pv5SEpK4ttvv2X+/PmMHj3aPP3emo85XdfzoiDPQw/z855eyZIlMy1TZtNyw8vLiwULFrBgwQJOnjzJwoULefHFF6lZsyaPPfZYputUqlSJUqVKsXfvXvbu3cvgwYPR6XS0aNGCPXv2cODAgSzXzYtixYoRHh6OUirP5/CcmPqK+OGHH6hUqVKOy2e2/9y8v3Q6HWPHjmXs2LFcvXqVNWvWMHnyZIoXL860adNynL9s2TJu375t3nZwcHCWMT7I/aSTkxNbt27liSee4IUXXrA4/wrxKJKaGjasUaNGAOYnXmCs1pa+WmNWHBwccszyAkRERGRae8FU7a1EiRKAsVOvlJQUi57kd+7caVF1Ojg4mDJlyrBixYos99euXTtOnTrFoUOHMp1ftWpVypQpw7///ptpLZbMvvRXqlSJ2bNn4+vry6lTp/I8Pzvu7u7MnDmTv/76y3zcExMTcXBwsLhgmjr3Sy+zp0b3Uz5RdAQHB+eqh3SDwcD69eupUaOGeQi6xx9/HJ1Ox1dffWVeLioqiu3bt2eoQv7TTz9ZJE/Wr1+PTqfLUF07vRYtWhAbG2sxQkpaWhqbNm0yNyWAnJ+GZqddu3ZERETg6OiY6fv/3poEeZH+PAnw1Vdf0aBBA4uOBe/l7u5O3bp1M3QIum7dOgCLcj+onOLL6bg6ODjQqlUrJk+eTGxsbLbJ4/yS22tQYmJihv9dbs+Jpqeb6dc/cOAAFy5cyDQmnU5Ho0aNmDVrFmlpaeamKO3ateOPP/6gXr16Gd5X6b9UZHdtvHDhAl5eXubr3qMuOTkZg8Fg8b+5ffs2X3/9tcVyOV3XIffnjRYtWrB582aLjjd//PFHoqOjH/jz+DA/7+k1btyYXbt2WdSg27lzZ441Q3JTe6FWrVq8++67ADne3zz22GNs3bqV48eP06pVK8BYg+PHH3/kl19+ydD05H60a9eOhIQE8zHNTy1atKBx48bMnj0709FBLl++zMmTJ3PcRl7eX6VLl2b8+PHUrl070+Ob2fzg4GCL8092SdXc3k9mV56vv/6aVatW8dJLL+V6PSGKIqmpYUUGg8FczSw9f39/KlSoQPXq1enRowcvvfQSSUlJlCtXjg8++ICUlJQct12tWjW2bNnCY489hpubG8HBwZmeWD/99FM+++wzBgwYQL169TAYDBw4cIC33nqLBg0amE/yHTt2xM3NjeHDhzNp0iSuXLnCwoULcXZ2Nm9L0zTeeecd+vbty9NPP83AgQPNPc43atSILl26MGDAAD744AM6d+7M9OnTqVmzJlevXmXv3r18+OGHaJrG/Pnz6devH/Hx8XTu3Bk3NzcuXrzI1q1bmT17NlWqVKF79+40aNDAPBzYN998Q1RUFG3atAHIcX5eDBo0iNmzZ/PWW2/Ro0cP2rdvz4IFCxg9ejQ9evTg4MGDmQ5xV61aNT799FO++eYbSpYsSalSpShVqlSuyieKpubNm7Nu3TpSU1PNbXovXrzIoEGD6Nu3L5UqVSIqKoolS5bw66+/WiQwypQpw7Bhw5gwYQJ2dnaULl2a2bNn4+Xlxf/+9z/zciNGjOD999+ne/fuTJ06latXrzJhwgRGjBiRbdKsc+fONG7cmP79+zN37lwCAgJ4//33CQ8PtxjJI6v3dW60b9+erl278sQTTzBx4kRq165NfHw8f/75J+fOnePjjz/O6yE1W7VqFS4uLtSvX581a9awd+9ei+EKszJjxgy6d+9O//796d+/P2fOnGHq1Kk8/fTT+VqlN6f4qlWrxvLly/nyyy+pXLkyxYsXJzY2lvHjx9O7d28qVqxITEwMc+bMoVy5cuaRQwpSbq9B7du3Z+TIkbzxxhs0bdqU7777zmL4yPRl3LlzJz/++CM+Pj6UL1+eJk2a4O7uzsiRI5k8eTJXr15l+vTpFrVaYmJi6NChAwMGDCA4OJiUlBTef/99vL29qV+/PgAzZ86kUaNGdOjQgeeff56AgACuXbvGnj17eOyxx+jbt685hqyujb/++ivNmjWzGM78Uebl5UWjRo2YO3cufn5+2NvbM3fuXLy8vCyedud0XYfcnzdeeeUVmjVrRpcuXRg9erR5dIrGjRtbJG/vV0F83q9fv57pvVyNGjXw8PDgpZdeYvHixXTs2NE80tn06dNzrBFUrVo1ABYvXkz37t1xdXWlVq1aNG/enB49elCzZk3zaB2Ojo451rRo2bIlI0eOpHjx4uY+LFq2bMmECRPMfz+odu3a0alTJ4YOHco///xDSEgIkZGRbNiwgbVr1z7w9r/44gtCQ0Np2LAhYWFhNGjQgOTkZPbs2cPixYtZtWpVtv/H3Ly//ve//+Hj40OTJk3w8fHh559/5rfffjPXAstpfl7k9n4yO23atGHjxo3m98js2bPzHIcQRYKVOih95GU3+slzzz1nXi4qKko9++yzys3NTRUrVkyFhYWpt99+O8fRT/bt26fq16+vXFxcFKB27dqVaRx//vmnGjVqlKpZs6by9PRU7u7uqnr16mratGkqKirKYtlt27apGjVqKGdnZ9WkSRN1/PjxTHsI//rrr1VISIhydnZW3t7eqk2bNur48ePm+ZGRkeqFF15QJUqUUI6OjqpChQrqlVdesdjG9u3bzaMpuLm5qRo1aqjx48ebew//v//7P9WwYUPl5eWl3NzcVP369S16285pfmYyO44mH330kcVxfOutt1SZMmWUq6urat++vTp79myGXvWvXLmiOnXqpLy9vRVgcZxyKp8omq5du6bs7e3V9u3bzdNu3bqlnnzySVWmTBnl6Oio3N3dVWhoqMUoJCZJSUlq/Pjxyt/fX7m4uKh27dqpU6dOZVjur7/+Um3btlUuLi7K399fvfzyyyo5OTnH+G7evKkGDx6sfH19lZOTk2ratKnavXu3xTJZva8zG93g+PHjGc4/ycnJaubMmapy5crK0dFR+fn5qdatW6tVq1aZl8lsJJCsmHqTP3DggGrVqpVydnZWZcuWVR9++KHFctltc8OGDap27drK0dFRlShRQr300ksWo2hkdW7IbDSPe0eKym18MTExqk+fPqpYsWLmURGuX7+u+vfvrypUqKCcnJyUv7+/evrpp9XZs2ezPSZZ9ZR/r9yM8JCba1BaWpoaP3688vPzUx4eHuqZZ55Rv/zyS4YRfP744w/12GOPKQ8PDwWoFStWKKWMoz+Zri21a9dW3333nUUZkpKSzKP/uLi4KF9fX/X444+rw4cPW8R69uxZ1atXL1WsWDHl5OSkypUrpwYOHGgxykJW18aUlBTl6+trMdJLUZLVe8Dk3uuXyd9//63atGmjXF1dVWBgoHr77bcz3VZO1/W8nDd2796tmjZtqpycnJSvr68aPHiwunXrlnm+afST9O8tpZQaO3asCgoKyvFY5PR5V+rBRz/hnpE89u7dq+rWrascHR1VtWrV1Lfffqvq1KmT7egnSik1Y8YMVaZMGaXT6cxlmzBhgqpVq5Zyd3dXnp6eqnnz5hlGlMrMH3/8oQDVvXt387TU1FTl7u6uSpYsmWH5zN4T7777rsVnP7PRPBITE9XkyZNV2bJllYODgypTpowaOnRotuWMioqyOCdk5/r16yosLExVrFhROTo6Kg8PD9WyZUu1fPlylZaWppTK/v2e0/tr5cqVqnnz5srX11c5Ozur6tWrW4y8lNP87GR2vHJzP5mbc/qmTZuUvb29ev3113MVixBFjaZULnpOFEIIkS+efvppvLy8WL58ubVDKRJWrlzJkCFDiIiIyLF/Cmuw9fiE0datW+nXr99D6atECCGEEPlL6lgKIcRDNG3aNNauXVtkh40UojCaN28e48ePl4SGEEIIUQhJUkMIIR6iunXrsmDBglwPMymEKFhxcXG0atWKcePGWTsUIYQQQtwHaX4ihBBCCCGEEEKIQklqagghhBBCCCGEEKJQkqSGEEIIIYQQQgghCiVJagghHll79+6la9eulCpVCk3T2Lx5c7bL79+/n+bNm1OsWDFcXFyoWrUq7777boblFi9eTLly5XB2diYkJITDhw8XUAmEEEIIIYR4tElSQwjxyIqPj6dOnTosXrw4V8u7ubkxatQo9u7dy6lTp3j11Vd59dVX+fDDD83LrF27lrCwMKZPn86xY8eoU6cOHTp04MaNGwVVDCGEEEIIIR5Zj1xHoQaDgf/++w8PDw80TbN2OEIUKkopbt++TalSpdDpilZOVNM0Nm3aRPfu3fO03lNPPYWbmxufffYZACEhITRq1IhFixYBxnNOYGAgo0ePZvLkybnappynhLh/Rfk8ZUvkPCXE/SuK5ym9Xk9qaqq1wxBFhIODA3Z2drle3r4AY7FJ//33H4GBgdYOQ4hC7fLly5QpU8baYVjd8ePHOXDgALNmzQIgJSWFo0ePMmXKFPMyOp2Odu3acfDgwVxvV85TQjw4OU8VLDlPCfHgisJ5SinFtWvXiI6OtnYooojx9vamRIkSuUqcP3JJDQ8PDwAuXryIt7e3dYPJBwaDgYiICPz8/IpEplfKY9uio6MJCgoyf44eVWXKlCEiIoK0tDRmzJjBsGHDALh58yZ6vZ6AgACL5QMCAjh9+nSW20tOTiY5Odn82lSB7vz580XmPHXz5k2KFy9eJD4HUh7bFh0dTfny5R/581RBk/sp2yblsW1F6X7KlNDw9/fH1dVVam6JB6aUIiEhwdx0u2TJkjmu88glNUwfNE9PTzw9Pa0czYMzGAwkJSXh6elZJE7yUh7bZjAYAB75C9a+ffuIi4vjl19+YfLkyVSqVIm+ffve9/bmzJnDzJkzM0xPTk4mKSnpQUK1CQaDAb1eT1JSUpH5HEh5bJcpQfion6cKmtxP2TYpj20rKvdTer3enNAoVqyYtcMRRYiLiwsAN27cwN/fP8emKI9cUkMIIR5U+fLlAahVqxbXr19nxowZ9O3bl+LFi2NnZ8f169ctlr9+/TolSpTIcntTpkwhLCzM/Do2NpbAwED8/PyKzBNQTdOKzBM2KY9tc3R0tHYIQgjxSDD1oeHq6mrlSERRZHpfpaam5pjUsOrdS16HUwTYvXs39evXx8nJiUqVKrFy5coCj1MIIbJiMBjMT4YdHR1p0KABO3bssJi/Y8cOmjZtmuU2nJyczE870z/11Ol0ReZH0zSrxyDleXTK86iR+ykhhDUV9honwjbl5X1l1St/XodTPH/+PJ07d6Z169acOHGCl156iWHDhvHDDz8UcKRCiKIoLi6OEydOcOLECcB4jjlx4gSXLl0CjDUoBg4caF5+8eLFfPPNN/z999/8/ffffPLJJ7zzzjv079/fvExYWBgfffQRn376KadOneKFF14gPj6eIUOGPNSyCSEeHXI/JYQQ4lFm1eYnHTt2pGPHjrlefunSpZQvX5558+YBUK1aNfbv38+7775Lhw4dCirMAmcwGFBKmZ+UPeDGQCnQNAzoTH+S2Waz3W+67WS6cm4X1evhnupCeSrvnY0blIbSdLkJJ/PNpKWhDAY0nQ6dffZv+0xCtoglL0EYDAbzj06ny5/y5BBH+uNLdu+B+yhPUfPrr7/SunVr82tTE5BBgwaxcuVKwsPDzQkOMB7bKVOmcP78eezt7alYsSJvvfUW//vf/8zL9O7dm4iICF577TWuXbtG3bp12bZtW4bOQ/PMYDD+n0y/hRDiDrmfEkKIwmHlypXmB13nz5+nXLlyuVrvwoUL5ubPu3btIjQ0tIAiLJwKVZ8aBw8epF27dhbTOnTowEsvvZRv+8jXBEMufPnllwwdOpSkpCScnZ1Zvnx5njocVEqRmppKcnIyLps3w7DnoLgrcb7FWFtsCGdVVW4l+tB3mAfNmuqJjYlGF32Df//9h7c/+ZyUlFS8vLwY1LMH9atXxcnLB3X8d/QffUyUmxvY2ePdqxdaixYoNOLi40lMSsbZ1Q1XNzf27td4fxG4e9xCZ6+jb79itGylw3D1P+LnzSMhOhpnX1/cxo6BkiU4+PN+NqzfgEGfRnJiAkMGDaJxo0YkJsSTmJiAk4MDhrQ09B7uaMeOEb3texxddLimpPL17fb8ktaIZ55OokJQHJ7J0Ti7upLiUwow9iTtGB+Np4MO5eGD3sWD5KRkzm//gQr//oV7QgIJUUlcbdYMr9ahOMRF4+moAw9v9C6e/Hc1ha3fxOKVFImTkyvNniqNX4BGTHQMdqd+x+vgXoiOR58Gqc88w+2yQXgkRePq7kaqpz9oOqJjY9GS4nF30Pj7cjibtu+gRImSpKSm0bFKeUpcuowhMpY0nSP73FuS5OFLnepQqqwrOLmh16cRHx+PS2I0Ls5OpHkUR7OzIyE+ARJi8Lh6AbtfjpAWl4LewYHbrVvj7uuCu6sLyZ4B/Hn2LDt/2oGzSsE1tQwRMT05d6skBr2OsHEabWpeAn0a/HkO5r8LtxMgMgmWL4cH6OiysAoNDTWPNJKZe6tjjx49mtGjR+e43VGjRjFq1KgHDe+un3+GUaNg8WIYORIWLYLmzfNv+0KIR0qB3U9J8lUIUQiFhoayZ88eAGrXrs1vv/1mnnfr1i3KlClj7rh90qRJzJ071ypxiqwVqqTGtWvXMh0qMTY2lsTERHMvqendO1RibGwscPcJenqffvopX331FTqdDjs7O0JDQ6lSpQpKKeLi4khLS8PV1RU7OzuUUiQnJxMbG4udnR1eXl4opVBKcevWLVJSUvDy8sLJyQmApKQkIiIisLOzIyAgwLzssWPHCAsL49atWyQlJfHTTz8RExNDREQEOp0OPz8/c6wxMTGkpKTg6uqKo6MjBoOB1NRUEhMTAXBOSqJDWC/q2sXgDjzHIeCQsXCXjD+mI+QHbOha427ho07Azyfuvu5SDS/zgd8PG/YD4H3P8e0B9Hgq3YRwYM2dvxu7AW7Gv3/+CIBAoFeLdL0jX98L3+69999mVqrB3T2O4BgjOAaRGH/uXTaLbZR3AWr4AD4AlOU6HFmb6foNK6ab8Ps9261VHChu/PvWEeNPNjEEAm3qegBxxgmJp4wH3k8HpFGFncbpd/43uVbJEbjTEd6NA3Dj7qyyQMfqpvnRwEd3Z16582PSpzHqahRq+T4YNgx69sxFrRxDtvNFATAYYOxoiLgIPTvDf9HGBMfRo/KlQQhxXwrkfurAARg7Ft57D8aMgYULoVmzgi1IPjI91Coq1zkpj20rKuUoin7//Xf27t1Ly5YtAfj444+LxEh0RV2hSmrcj6yGSoyIiCAlJcX82mAwsHXrVho1amSeFh0dzeHDh+9737du3cp0ekxMjPlvU4eA6cffNY2cYDAYCA8Pz7B+QkICCQkJGaaXd0qkLjEoINLRCzdNj2NKIslObqQ4uRsXUgY8bhu/Bd/2CDA2PQCckm7jmBJPiqMryc6modkUmjKgKXXnx2D+DQrNYDBOS7cc6ZbRlEJDYdB0KE0HmrHJhdI0FKa/00+/M8/82/i3c2Is9mnJJDl7kOZgvNHS6dNwTYhEaTri3Yubj4FTUiwOqUkkO7mT6mjsMVcz6HGLv4XSNOLd/dItexuHVOPxSXV0u7OsAbf4mwDEufuZj49j8m0cUxJJcXS1OJbucRF3lvXP9FgmOXuAApTC67bx/xrr5ocyLZuagFNKPCkOLiQ53R2r3CP+JppS3HYrhtIZ28I4pCbgnBxPqr0TSeb/EbjH30JTBuJdfTHY2QEaDqmJOCfdJs3eiSQXL2JuQnKiRsViN9EMetJiEsEAaTgR06CBcUM3buT4JTn9e1c8JDodDOoMt/6Aq1Hw8R6YOFESGkKIhyrb+6mkJHj/fWPbzXHjjL/ffx8qVCg05yrTwyOlVJHobFbKY9vkfso2OTg4kJqayvvvv0/Lli3R6/V88MEH5unpRUZGMm3aNL7++muuXbuGr68v7du3Z/bs2ZQtW9a83Pvvv8/cuXOJjo6me/fuNG7cONN9f//998ydO5djx46RlpZGw4YNef311y2aSd/r2rVrjB8/np07dxIZGYmPjw/Vq1fn5ZdfplOnTvlzUAqJQpXUKFGiRKZDJXp6emb6VAFyP1SiXq/n4MGD2NvbExwczO3btzl58iQTJ05Ep9Nx+vRpEhMTqVixIj4+PmiaRlxcHBcuXMDFxYUqVaqgaRqapnH58mWSkpIoVaqUOWmRkpLCjRs3cHR0pFSpu8/zJ0+eDBhPbklJSdjb27NixQoSEhKwt7c3j8et0+nMT0icnJxwdHRE0zSUUkRGRlLcxYGSKyeDox1pV6LRfbWbWy4+tPI6QlKSPclxdvx7XofOTiMy1cBjLVty7cpe0tLS0DQNbx9fjv5+Ejs0nGtURaWkgqaRGBCA3s0Dpx+2obMzXkTSDIpkvQGloPVjOkyfcU8fAy6uii0bdTj07Q0XLqC305Hq5YuuVEnsP/mYFs2bk5ySjIu7h7HGS1oau3fvRqfTMChFqt5ATHQMxb290D32GKQkc9vRCaXTkZKq0dKwFydnjd27FbHKmLV3trcz5g2AqBQ9KQYDzvZ2ONppGNL0JPXsxaVadVEa+O4+SopOh/269cSk6UlMNeDuYIeboz3jxili4xWN2ySTmqJx5rATSxbr0FDceCmMJJ9APP79G8+/jxsvqAcPciXVgJ2m4eNsj51Oh06DNL0i3mAgKLAMt2OiqV+/PsePHSPaYMAZMKUuEnHGgxicnHXExIBnJtdoj3R/G/R69CVLoUtMwNOUMXZ2JuFmJEqn4azT8PH2No7j7luc4iX/JuG2M9cu2d1ZVCMmBnQYsPPygqQk7AD/O9vB3z/Hm08ZKtEKDAbYtQ1qlwHnO6fsoUOhd+9C82VBCGFbCuR+qm0jtEPX4GoU6sc/jcmNbIaytjVFbWhjKY9tk/sp21S3bl1u3brF5s2buXLlCkeOHOHSpUv07duXL7/80rxcUlISrVq14o8//sDe3p4qVarw77//8sUXX7Br1y5OnDiBn58f33zzDWPGjAHAz8+Pffv2sWXLlgz7Xbt2LX379kUpRVBQEDqdjv3799O+fXt+/PHHLBMbL774Ips2bcLd3Z2aNWsSERHB7t27admy5SOX1EDZCEBt2rQp22UmTpyoatasaTGtb9++qkOHDrneT0xMjAJUVFSUxXS9Xq+cnZ1N340VoJydnZVer8/1tu/H6tWrzft1dnZWq1evztP6er1ehf/3nzKsfUup6d2NP43KqzQHZzXAfrUCpZydlbp3s9nud/Vq40pZraxysejp00pVr26cUb268XUuyqvX61V4eLjxuKfbeCLOqg+rcwonU/tHjlSJxi4xVSKo/SNHZnIclapWzRiu6adaNeP0vB6Tu8dmtXJ1dVWNGjVSrq6uxv0+aHlyiCP98bW3H6AcHNIyX/Q+yqOUUlFRUQpQMTExeQha5JXFeSotTal6QcbPdr8md9+gaWnWDjPXLD7XRYCUx7Y96ucpq9xP6fVKda5rPE+NbHv32lKI3lNF7XMg5bFtReU8lZiYqP766y+VmJho7VAeSKtWrRSgQkJC1Lx58xSgpk6dqlq3bq0AdeDAAfP3w0mTJqnly5ebX5vOt0ePHlU6nU4B6rXXXlNKKdWiRQsFqIoVK6rbt2+rtLQ0FRoaal73/PnzSimlypUrpwA1dOhQZTAYlMFgUD169FCAatGihVJKqfPnz5vX27Vrl1JKqZo1aypAff755+ay/Pfff+rUqVMP7dgVpLy8v6ya1Lh9+7Y6fvy4On78uALU/Pnz1fHjx9XFixeVUkpNnjxZDRgwwLz8v//+q1xdXdWECRPUqVOn1OLFi5WdnZ3atm1brveZVVJDqQdPMNwvvV6v0tLS7utErdfrVdTer403EjOeUurgN0olxiul1yu93vi9J6vNZrvfnFbO7aKZfPHKbr8ZLlp3Nq5P1ec2nMxjTE1VacnJSp+amuUy+/crVbeuUnv3Gn/v358huFwfE5PU1FR19epVlWrab36UJ4c40h/fbBe9j/IUlYuwrctwngptYPyMv9hWKZ3OmCgsRIrazaiUx7Y9iucpq99PpaUp1bGW8TzVo4EkX22AlMe2FZXzVFFMakRFRSk3Nzfl4eGhANWgQQOllLJIarzwwgsKUK6urhbbqVatmgJUp06dlFJK+fj4KEC9+OKL5mXee+89i6TGjRs3LB6q3/vj4OCglMo8qTFlyhQFKDs7O1WxYkXVuXNn9X//93+F/n1lkpf3l1Wbn+R1OMXy5cuzdetWxo0bx8KFCylTpgwff/xxvg0/1rdvX3r37v1QRz8BHmw/tyPx3H+nZ85WvaBJl7vbfZD95iGmbBfNZGzUPJX3zrIP+p/IaRhXMA4mYep7MdM+GO/j/2RqOmQuc36UJ4c4cn18i0D1zUfG2+/Bt2+DtytUrQobN1o7IiGEDbH6/ZSdHeju9Dfl7GC8vlStmsX46EIIYbu8vb3p378/y5YtA8jVqHf5pUKFCvj5+WWYnr4fyPTefPNNmjdvzg8//MAff/zB3r172bp1K7t372br1q0FHa5NsWpSI6/DKZrWOX78eIHFVKja6SmF9s0HaMkJqBIV0B572toRFXr35B6EsA11G8G3GjjYwfwJEBxs7YiEEDbEJu6nXp4Kuz8BH0m+CiEKt1GjRrFs2TL8/Pzo06dPhvmNGjViyZIlJCQksHnzZrp3786xY8c4c+YMAA0bNgSgRo0a7N+/n+3btxMfH4+zszObNm2y2Jafnx9BQUFcvHiR+vXr8+WXX2J/52Hs2bNnuXjxYpZ9sPz888+0atWKzp07A7BmzRr69u3L3r1ZjyxZVMlXt8Ls2I9o546j0CDxNlw6Ze2IhBAFwd4BnI2j+XDljHVjEUKIzNS6M5JWgA9s3yLJVyFEoVWzZk1u3brFuXPncHJyyjC/b9++1KxZE4CePXtSo0YNmjdvjsFgoFSpUowaNQqAl19+GYBz585RoUIFKlSowIEDBzJsb/bs2QBs2LCBUqVKUa9ePUqUKEFwcDBffPFFlnFOnjyZYsWKUalSJRo0aMDQoUMBqF279oMdgEJIkhqFVdR1+GEFAMreAS0mAlw9c1hJCFFo+d4Z9rlaU+vGIYQQmfG6M7y6QQ/HfrRuLEII8YB8fX3No1jey9nZmT179vDiiy9SokQJzp49i4eHB88++ywHDx40NyHp1q0b7777LiVKlOD27ds0bNiQWbNmZdhev379+Pbbb2nVqhWJiYmcOXMGDw8PBg4cyLBhw7KMsXfv3jRs2JDY2FhOnjyJt7c3ffr0sRip5VFRqIZ0FXcYDLD5PUhJQpWtRkSbYfjFX0MXEGTtyIQQBcWvDPx3DvSpOS8rhBAPm70DuHgYa446yHCVQojCY/fu3Tkuc28TP19fXxYvXszixYuzXe+ll17ipZdesphmqsGRXufOnc3NSDJTrly5DDGMHj36ofb5YcukpkZhdOhbuPgXODijuo1CObtCtSbWjkoIUZC8/Y2/o29YNw4hhMiKf1nj71KVrRuHEEKIR4okNQqbiMvw0+fGv9s+Cz4lrBuPEOLh8A4w/r50Gq6dt24sQgiRGZ8756no69aNQwghxCNFkhqFiT4NNr1nrH5esS4c3IL25Wx08dHWjkwIUdBMNTUiLsGfGTuZEkIIqzOdp6JuQDajsQghhBD5SZIahcn+jcY29c5uUL89xNyC/85hcHKzdmRCiILm43/3b89i1otDCCGyYqqp8dsu+EuSr0IIIR4O6Si0sPjvH9izzvh3p+ehRjMIeB91K9zYOZcQomjzKAaaDpQBghtZOxohhMjIVFPDoIebV60bixBCiEeG1NQoDFJTYNNC401C9aZQ6zHj9OKloXJ968YmhHg47OzAyzhEGFHSXl0IYYNMNTXQoHEnq4YihBDi0SFJjcJg15fGDkLdvKDz/yBNhnQU4pHknS6pYTBYNxYhhLiXuw/YOQAKkuKtHY0QQohHhCQ1bN2lU3Bgi/Hvri8abxLmDYXtK+VLjRCPGlPV7q1L4fQh68YihBD30uksk69CCCHEQyBJDVuWnGgc7QQFddtA1cbw+15jYiPiivHmQQjx6DBV7U5NMdbeEkIIW2MafvrwdxAXbdVQhBBCPBrkW7Et+3EVRF0Dz+LwxFDjtFa94NlXoXVf68YmhHj4TDU1SlWCZt2sG4sQQmTGNFLT6UNw/YJVQxFCiIctOjqaGTNm8Ndff+Vq+cGDB1OzZs1cLZuUlMRrr71G+fLlcXJyomzZskyYMME8/8KFC2iaxoYNG+4r9sJMkhq26twJ+HWb8e/uo43DuIKxdkblBlCqotVCE6Ko2Lt3L127dqVUqVJomsbmzZuzXX7jxo20b98ePz8/PD09adq0KT/88IPFMjNmzEDTNIufqlWr5k/ApqRGwm1wcMqfbQohRH4y1dTw9gdnd+vGIoQQD1l0dDQzZ87MdVJj2rRprF69OsflDAYD3bp148svv2T69Ols376dWbNm4ejo+KAhFwkypKstSoyHLYuMfzfuBBVqG0c+QZMmJ0Lko/j4eOrUqcPQoUN56qmnclx+7969tG/fntmzZ+Pt7c2KFSvo2rUrhw4dol69eublatSowU8//WR+bW+fT6daU1Ij9ibo9cYRUYQQwpaYamq4+0DpStaNRQghbFzFirl7UL1ixQoOHTrEqVOnKFmyZAFHVfjIN2Rb9P3HcPsW+JaEdgON007ugw/Gwh/7rRubEEVIx44dmTVrFj169MjV8gsWLGDixIk0atSIypUrM3v2bCpXrsw333xjsZy9vT0lSpQw/xQvXjx/AvbwBZ29Mcn546cQG5k/2xVCiPxiqqkRfcO6cQghRB4tW7aMoKAgXF1dad++PcePH0fTNFauXAlAuXLlGDVqFG+//TalS5fG1dWVbt26ER4eDhibf5QvXx6Anj17mmvsXrhwIct95rb5yUcffUTPnj1zldCIj4/nueeew8vLC19fX8LCwkhLS8v5ABRiktSwNX8egN93g6aDHmPA8U4V86M/ws0r0pu4EDbEYDBw+/ZtfH19Lab//ffflCpVigoVKvDss89y6dKl/Nlh+pEFfvkGwv/Jn+0KIUR+MdXUiIuC+BjrxiKEELn09ddfM2LECB5//HE2bdpEu3bt6NWrV4blNm3axKZNm1iyZAlLlizh0KFD5tq+JUuWZOPGjQDMnj2bgwcPcvDgwQeuWZGamsqxY8cICgpi4MCBuLm54eHhQa9evbh27VqG5adOnYrBYGDdunVMmDCB999/n1dfffWBYrB10vzEVpw5A317Qtsy4OYEVVtCYLp2+P1egeM/QZ3W1otRCGHhnXfeIS4uzuKiFxISwsqVKwkODiY8PJyZM2fy2GOP8ccff+Dh4ZHpdpKTk0lOTja/jo2NBYxJE8M9Qzdr3v5okeGowKooF49CMbSzwWBAKZWhLIWVlMe2FZVyFFouHuDgDKlJ8PZgmPwFOLtaOyohxEOilCI1NdWqMTg4OKBpWp7WmTVrFm3atOGjjz4CoEOHDqSmpjJt2jSL5W7fvs3333+Pl5cXAIGBgbRt25YffviBDh06mJsjV65cmSZNmuRDaeDWrVukpqby1ltv0bJlSzZt2kRERAQTJ07kqaee4sCBAxbLV6xYkRUrVpjLkZiYyLx585g0aRI+Pj75EpOtkaSGLYi6DpOfgyZ+xoTG9Rj46iPoPfbuMs6u0PRJ68UohLCwevVqZs6cyZYtW/D39zdP79ixo/nv2rVrExISQlBQEOvWreO5557LdFtz5sxh5syZGaZHRESQkpJiMc3TyQNXIN6/InGO3nDD9qt4GwwGYmJiUEqhKwL9Akl5bFtMjNQOsCpNA98Sd0c+iQyXzs2FeISkpqYyZ84cq8YwZcqUPHWgqdfrOX78OO+8847F9G7dumVIarRu3dqc0ABo06YNvr6+HDp0iA4dOmS7D6WU+bWdnV2miZd7m4nY29ubk/UeHh5s3LgRJydjTf6AgADat2/Pzp07adOmjXmde5tVP/PMM7zxxhucPHmSli1bZhljYSZJDWuJuAKnDsJfv8C1f6HOnSrlyamw6ZgxsaHXG28OisBNphBFyZo1axg2bBjr16+nXbt22S7r7e1NlSpVOHfuXJbLTJkyhbCwMPPr2NhYAgMD8fPzw9vb23LhEmXhFLilxuOaLpliywwGA5qm4efnVyS+NEt5bJv0BG8DfAKMSY32AyWhIYSweREREaSlpeHn52cx3T+T+6ysppn61chK27Zt2bNnj/n1rl27CA0NzbCcg4ODxWulFN7e3miaRrNmzcwJDYDQ0FDs7Oz4888/LZIa98YYEGDs6yinGAszSWo8LEoZL/B/HYRTv0DE5bvzNB1ci4Nj5+DPq5CUBtWrG0c2+HYp3I6C1n2hRDlrRS+EuOPLL79k6NChrFmzhs6dO+e4fFxcHP/88w8DBgzIchknJyeLi5SJTqfL+CXTtwQAWswNtOREYy2uPFaxtAZN0zIvTyEl5bFdRaEMhZ5ppKY4qTUjxKPGwcGBKVOmWD2GvPDz88Pe3p6IiAiL6TcyqQ2b1bSc+s1YtmwZt2/fNr8ODg7OdLkjR45kmObq6kq5cuWy3HZSUlK2MV6/buyTsSiPmiJJjYKkFPx37m4iIzJddkxnbxyqtXpTCG4MV8LhqacgPtmY0Ni4EZIS4MQuSEuBZt2sVw4hiqi4uDiLGhTnz5/nxIkT+Pr6UrZsWaZMmcLVq1dZtWoVYGxyMmjQIBYuXEhISIi5cyYXFxdzVcSXX36Zrl27EhQUxH///cf06dOxs7Ojb9+++RO0qaPQS6fhrf4w7iPwyqfRVYQQIj/4mEZAkc7NhXjUaJpW6GrM2dnZUa9ePbZs2cLYsXeb/2/evDnDsrt27SImJsZ837dz504iIyMJCQkB7tYWvDfRkFUS414NGzbMdHqXLl1Yv349SUlJODs7m/et1+tp0KCBxbKbNm1i3Lhx5tcbNmzA1dWVWrVq5SqGwkiSGvnJ1Fzk8mljEuPULxCTLuNn7wgV6xoTGVUagYvb3XnBnvDnn8Zt2Nndnf6/d4xNVMpWe2jFEOJR8euvv9K69d3Od01NQAYNGsTKlSsJDw+3GLnkww8/JC0tjZEjRzJy5EjzdNPyAFeuXKFv377cunULPz8/WrRowS+//JKhSuN9Mw2XqO50hnjrP0lqCCFsi6mmxuWz8NPn0K6/deMRQogcvPrqq3Tr1o3hw4fTs2dPjh8/zqeffgpY1gD08PCgY8eOTJ48mejoaCZNmkTjxo3N/WmUKFECb29vvvzyS8qXL4+TkxO1a9d+4ETPhAkT+Oyzz+jWrRtjx44lIiKCyZMn06JFC4t7WYB//vmHIUOG0KdPH44dO8acOXMYN25cke0kFCSpkT/OnIHn+oFXGtQsCy7pDquDM1RpANWaQuX64OSS/bbSJzQA/AKhVWD+xyyEIDQ01KLTpnuZEhUmu3fvznGba9asecCocuDubUyQpqXA/+ZDyfIFuz8hhMgrU02NuEg4sMXYhPbe+xshhLAhTz75JEuWLGH27Nl8/vnnhISEsGTJEh5//HGLjkF79OhBmTJlGDFiBFFRUbRv356lS5ea5+t0OlasWMHUqVNp27YtycnJnD9/PtvmI7kZqSUwMJBdu3bx0ksv8fTTT+Pq6kr37t2ZN29ehvXffPNNdu/eTc+ePbGzs2PkyJG8+eabeT8ohYgkNfJDv17QuTzo7ryhUvTQsC1Ub2KsmeGQsa18jpQqFO3khRAPmaYZm6DcvAqJt3NeXgghHjbvdJ3UNXsS9KmS1BBC2LwRI0YwYsQI8+tPPvkEgDp16lgsN3nyZCZPnpzldrp370737t1ztc/bt2/j6+ubq2Xr1q2b7QO2cuXKmR/WDR48OMPDuaLM6r1pLV68mHLlyuHs7ExISAiHDx/OdvkFCxYQHByMi4sLgYGBjBs3LkObpYdKr4eYa8aERmwifH4A3voWuo2CqiH3n9BY8Qr8uAoS5EuLEOIepi8M0bY/nKsQ4uGwqfspR2dwu/Nks3oz42shhLBhkZGRjB07li1btrBz507eeustxo0bR7du3bKtZXG/oqKi2LJlC7t376ZRo0b5vv1HjVVraqxdu5awsDCWLl1KSEgICxYsoEOHDpw5cybT4XJWr17N5MmTWb58Oc2aNePs2bMMHjwYTdOYP3++FUqA8clD9TvDlf0XDRduQdVqD/ZE4vxJuHQKrp2HFk/nS5hCiCLE1K/G73vg6t/QZYTU7BLiEWaT91PeARAfY0y+yrCuQggb5+DgwD///MPq1auJjo7Gz8+PAQMG8NZbbxXI/vbs2cOAAQMIDQ3NttaHyB2rJjXmz5/P8OHDGTJkCABLly5l69atLF++PNN/7oEDB2jevDn9+vUDjFVs+vbty6FDhx5q3Bn0fRrO7IeoeAgONo5c8iDK1YS+UyH2lmVnokIIAXdralz4w/jTuq+xrw0hxCPJJu+nfPzh6lljU7mYm9KhsRDCpnl4ePDtt99mu8yFCxfybX/du3e3GOJVPBirNT9JSUnh6NGjtGvX7m4wOh3t2rXj4MGDma7TrFkzjh49aq5S+e+///Ldd9/RqVOnhxJz1pKNv16faxzBJJdD9mRJp4PgRtDoiQcPTQhR9JiSGu4+0KYfaFZvSSiEsBKbvZ8y1Sjb+QWsfyf/tiuEEELcw2o1NW7evIlerycgIMBiekBAAKdPn850nX79+nHz5k1atGiBUoq0tDRGjBjB1KlTs9xPcnIyycnJ5texsbEAGAwGDAZDPpQEtMhwNMDgUwLyaZu5ZTAYUErlW1msTcpj24pKOQo9nztJDU2Dlj2tG4sQwqps9n7K28/85EzFx6Bs/PpRFK/XUh7bVVTKIYStKFSjn+zevZvZs2fzwQcfEBISwrlz5xg7dixvvPEG06ZNy3SdOXPmMHPmzAzTIyIiSElJefCglIGAyOsA3FIO6G/cf8d9urgofH5YSkL1liRWbZqrp68Gg4GYmBiUUhZjKBdWUh7bFhMTY+0QBNytqXE7ElJTwOHBxj4XQjxaHsb9lCOO+AJpnv7c7PUaPMD90cNQ1K7XUh7bJvdTQuQvqyU1ihcvjp2dHdevX7eYfv36dUqUKJHpOtOmTWPAgAEMGzYMgFq1ahEfH8/zzz/PK6+8kulJbsqUKYSFhZlfx8bGEhgYiJ+fH97e3g9ekNhbaPpUlKajWIWqYHefh/TAAbTFr6EFe+G56RM8egVAs2Y5rmYwGNA0DT8/vyJxkpfy2DZHR/nybBNcPcHBGVKT4OYV48gCxUpZOyohhBXY7P2UvfFJtF1CtLGzUhvvzLioXa+lPLZN7qeEyF9WS2o4OjrSoEEDduzYYR7H12AwsGPHDkaNGpXpOgkJCRlOZHZ3Rhkxjcl7LycnJ5ycMg6rqtPp8uekeGdIRc3bD+1+n5YaDDB6NJz6ExoEod2IRds3Go4eNfavkQNN0/KvPDZAymO7ikIZigRNA28/iLgMy8Yb+9Z4ebm1oxJCWIHN3k/5+IOmQ0tLQUuIAQ/fPJTKOorS9RqkPLasKJRBCFti1eYnYWFhDBo0iIYNG9K4cWMWLFhAfHy8uffugQMHUrp0aebMmQNA165dmT9/PvXq1TNXl5w2bRpdu3Y1X4wfushw42+fzJ+G5EifZvy9eDE0bw4Hzhlf/7wpVwkNIcQjyifAmNQAMOghJRkcM37hEEIUfTZ5P2VnD57FICYCvl0GFetC4475s20hhBAiHasmNXr37k1ERASvvfYa165do27dumzbts3c2dWlS5csMpmvvvoqmqbx6quvcvXqVfz8/OjatStvvvmmtYoAUdeMv33vI6mRGAfr3jY+zZj+seW8kSNzXVNDCPEIMvWrEdIFOj5n3ViEEFZls/dTPgHGpMaZw8aHOJLUEEIIUQCs/o151KhRXLx4keTkZA4dOkRISIh53u7du1m5cqX5tb29PdOnT+fcuXMkJiZy6dIlFi9enD99Y9yvO52E4lsy7+v+9w9c+ANO7of/mwV168LPPxt/L1okCQ0hRNZMSY24aKuGIYSwDTZ5P2U6TwXVgIYd8nfbQgiRjwYPHkzNmjUBWLlyJZqmcfPmTStHlTsvv/wyNWrUwMPDA09PTxo1asSaNWtyvf4nn3xC7dq1cXNzIzAwkOHDh3MjXefOFy5cQNM0NmzYUBDh54tCNfqJTTLV1Lif5icV60DXF6BUJShRDo52NCYypIaGECInpi8L0bY9ooAQ4hHmc2eYWd8SULWxdWMRQogiKi4ujuHDh1O1alVz8qFv374YDAb69euX7bqrVq1i2LBhTJgwgSeeeIKLFy8ydepU/vrrL37++eeHVIIHJ0mNB2XqUyO3zU9+2w1VGoKLu/F1/XZ355kSGZLQEELkxJTUiPwPvl4Mzm7w+GCrhiSEEBZM56mo69kvJ4QQ4r4tXbrU4nWHDh3466+/WLlyZY5JjdWrV9OqVSv+7//+z2L60KFDuXz5MoGBgfkeb0GQb88PIuE2JMUb/zY9jcjO3vWwaaGxHw29vmBjE0IUbaZzTmIcHPsJ/jpo3XiEEOJepvNU1HW4cQliCkdVbiGEuNfkyZOpVasW7u7ulC5dmr59+xIeHm6xTGhoKF26dOHLL7+kcuXKuLq60rVrV6Kiorh48SIdOnTA3d2dGjVqsHv3bot1V61aRYsWLfD19cXHx4fQ0FAOHz583/EWK1aMlJSUHJdLTU3Fy8vLYprp9b2jYcXHx/Pcc8/h5eWFr68vYWFhpKWl3XeM+em+kxopKSmcOXPGZgpiFaamJ+4+4Oic8/JVGoGjC5SvJbUxhBAPxtkNnFyNfzfsAO0GWDceIYS4l/edpEZMBHwwFo7vsG48Qghxn27cuMHUqVPZunUrCxcu5MKFC7Rq1SrDd+Hjx4+zcOFC3nnnHZYuXcq+ffsYPnw4zzzzDF26dGHjxo34+/vz1FNPERcXZ17vwoULDBw4kPXr17N69WrKli1Ly5YtOXv2bK7iU0qRlpZGdHQ0n332Gdu3b89yWO/0nnvuObZt28aGDRu4ffs2f/75J2+++SZdu3albNmyFstOnToVg8HAunXrmDBhAu+//z6vvvpqruIraHlufpKQkMDo0aP59NNPATh79iwVKlRg9OjRlC5dmsmTJ+d7kDYrMhcjnxj0oLszPFqJcjDmA3D3LujIhBBFnaYZq3Zfv2BMmFZpYO2IhBDCkrs32DmAPhUcnO8OYy+EKLKUUujvecL/sNlpGpqm5es2ly9fbv5br9fTtGlTypQpw86dO3n88cfN82JiYvjtt98oXrw4AL///jvz5s1jyZIljBgxAoBSpUpRq1YtduzYQbdu3QB47bXXzNswGAy0b9+ew4cPs3LlSmbPnp1jfDt27KB9+/aAsTPoRYsW8cwzz+S4Xr9+/YiPj6dfv36kpqYC0K5du0w7Gq1YsSIrVqwAjE1cEhMTmTdvHpMmTcLHxyfHfRWkPCc1pkyZwm+//cbu3bt54oknzNPbtWvHjBkzHs2kRladhF74E775AJ599e7oKJLQEELkF1NSQzoLFULYIp3OeJ66dRX6TDZ2kC6EKNL0SvH139btR+fJygHY53NS4/vvv+eNN97gzz//JDY21jz97NmzFkmNunXrmhMaAFWqVAGM35XvnXb58mXztFOnTjF16lQOHDhgMfJI+poa6WuFaJqGnZ2d+XVISAhHjhwhJiaGbdu2MXr0aOzt7XnuuecAYyImfXMSe3tjGmDjxo2MHz+eadOm0bJlSy5dusS0adPo1asX33zzjUVyqEePHhbH5JlnnuGNN97g5MmTtGzZMvsDWMDynNTYvHkza9eupUmTJhaFrFGjBv/880++BmfzorKpqaEU7PwCbv0Hu9bA0+MebmxCiKLP1F498j+4ftH4d0CQ9eIRQoh7+dxJakjyVQhRSB05coQnn3ySbt26MXnyZPz9/dE0jSZNmpCUlGSx7L1DYzs6OmaYbppmWvf27ds8/vjj+Pn5MX/+fIKCgnB2dmbYsGHmZS5cuED58uXN2wgKCuLChQvm1x4eHjRs2BCAtm3bkpaWRlhYGIMHD8bOzo6KFSty8eJF8/Lnz58nKCiIESNGMHz4cKZNm2aeV6FCBVq0aMGPP/5okbDx9/e3KFtAgPE+9N6+Rawhz0mNiIiIDAUCY8ch+V3Nx+aZm5+UzDhP06Dny7DvK2g38OHGJYR4NHj7GX+f/wN++RaqhhifhgohhK0w9asRLSOgCPEosNM0nqyciwEUCjiG/LRp0ya8vLxYt24dujv9IqZPEDyogwcPcuXKFb799lvq1Llboy0mJoYyZcoAxiYrR44cMc9zcnLKdpsNGjRgwYIFREREUKJECb755huSk5PN80uVKkVERAQRERHUrVvXYt169eoBZKiwkL4GCcD168bzesmSmXwXfsjynNRo2LAhW7duZfTo0QDmRMbHH39M06ZN8zc6W2eqqeETAAYDpCbDpdNQ2fhGwMMXOg23XnxCiKLN9GUhNdnYaai9o3XjEUKIe/nceRB29ihc+Rta9YJyNawbkxCiwGialu9NP6wtMTERBwcHiwf4X3zxRb5uH+7W4AA4cOAAFy5coEaNGuZ5ppoYubF//348PT3NTWFq1aqVYRk/Pz9cXV05duwYAwbc7XD+6NGjAJQrV85i+U2bNjFu3N3WBxs2bMDV1TXTbT9seR6CY/bs2UydOpUXXniBtLQ0Fi5cyOOPP86KFSt48803CyJG25SSDLcjjX//fQmaNIL3x8BnM+HbtdaNTQiRK3v37qVr166UKlUKTdPYvHlztstv3LiR9u3b4+fnh6enJ02bNuWHH37IsNzixYspV64czs7OhISEPNCQXNnyvvNlIeE2TP4cngkrmP0IIcT9Mo+AchPO/w7Xzls3HiGEyKP27dtz7do1Ro8ezY4dO5g1a5Z50Iz80KRJE9zd3Rk5ciTbt29nxYoV9OnTh9KlS+e47u+//07Hjh1Zvnw5O3fu5Ouvv+b555/nww8/ZOrUqea+MzKjaRrPP/88ixcvZvr06ezcuZMVK1bQv39/atSoQZs2bSyW/+effxgyZAg//PADc+bMYc6cOYwcOdLqnYTCfSQ1WrRowYkTJ0hLS6NWrVps374df39/Dh48SIMGj1Dv+6ZaGk6uEDYBjhyDQ79BfDLMm2+suSGEsGnx8fHUqVOHxYsX52r5vXv30r59e7777juOHj1K69at6dq1K8ePHzcvs3btWsLCwpg+fTrHjh2jTp06dOjQIUOVvXxhSmokxUFKUvbLCiGENZj6/lEKuo2WkZqEEIVOp06deOutt9iyZQtPPvkke/fu5dtvv8237QcEBLB+/Xpu3LhBt27dWLBgAcuWLaNSpUq5Wtfb25vXX3+dTp06MXz4cM6cOcOmTZuYNGlSjuvPnTuXGTNmsG7dOrp06cL06dMJDQ1l27ZtGZq4vPnmmyil6NmzJ//3f//HyJEjbaZSg6aUlcfcechiY2Px8vIiKioqQ0cueXL6EKyZCyUrQq2noHlzsLcDFwfYtgOaNcu3mLNjMBi4ceMG/v7+5jZehZmUx7ZFR0fj4+NDTEwMnp6e1g4nX2maxqZNm+jevXue1qtRowa9e/c2D8UVEhJCo0aNWLRoEWB8DwQGBjJ69Ohcjw6Vp/PUWwMgMQ5eWGCznYQWtc+BlMe2FeXzlC3J9Xkq4Tb8352+xaauAcfs24FbS1H7HEh5bFtROU8lJSVx/vx5ypcvj7Ozs7XDEUVMXt5fee5Tw87OjvDw8Aydhd66dQt/f3/0en1eN1k4RabrT2PkSOPfaXq4rTe+PnrUOJSZEKLIMhgM3L59G19fXwBSUlI4evQoU6ZMMS+j0+lo164dBw8ezHI7ycnJFp03mYYKMxgMGHKo9aV5+6MlxmE49hPatfOo4MbQpMuDFCvfGQwGlFI5lqWwkPLYtqJSjiLDxd1YqzU5wTgCin+gtSMSQghRxOQ5qZFVxY7k5GSLzk2KvPQjn8yaCgvmw6uz4KWXYdEiSWgI8Qh45513iIuLo1evXgDcvHkTvV5vHuLKJCAggNOnT2e5nTlz5jBz5swM0yMiIkhJSck2Bm8XL5yBlGuXcL74J0n2zsRUaJz3whQgg8FATEwMSqki8YRNymPbYmJirB2CSE/TjE3lrl+AS6cgMhwq1AZHeaorhBAif+Q6qfHee+8BxiraH3/8Me7u7uZ5er2evXv3UrVq1fyP0FaZ+tTwLWFsitK8BLimSg0NIR4Rq1evZubMmWzZsiXTYa7zYsqUKYSF3e3kMzY2lsDAQPz8/HJsfqL5B8K/x3Hy8sHQbTROJSs8cDz5zWAwoGkafn5+ReJLs5THtj1SD1gKC58AY1Ljx0+NNTaGvQVlqlg7KiGEEEVErpMa7777LmCsqbF06VLs7OzM8xwdHSlXrhxLly7N/whtVWS6pIZnMWONjeJlJKEhxCNgzZo1DBs2jPXr19OuXTvz9OLFi2NnZ2cet9vk+vXrlChRIsvtOTk5ZTreuE6ny/lLpq+xVoiWkoRWr032y1qRpmm5K08hIeWxXUWhDEWOqbNQVw/wKQFp2ddAE0IIIfIi10mN8+eNQ3C1bt2ajRs32sTQLVaj10NMhPFvnxLQZYR14xFCPDRffvklQ4cOZc2aNXTu3NlinqOjIw0aNGDHjh3mDkcNBgM7duxg1KhRBROQaQSU6AIYXUUIIfKDaVjXgHLQJ3cdJgshhBC5lec+NXbt2lUQcRQuMRFg0IOdA3j4WjsaIcR9iouL49y5c+bX58+f58SJE/j6+lK2bFmmTJnC1atXWbVqFWBscjJo0CAWLlxISEgI164Za2y5uLjg5eUFQFhYGIMGDaJhw4Y0btyYBQsWEB8fz5AhQwqmEKYvC1HXjT/XzoNfIBTPeWxzIYR4KHwk+SqEEKLg5DmpAXDlyhW+/vprLl26lKETu/nz5+dLYDYt/cgnUs1ViELr119/pXXr1ubXpn4tBg0axMqVKwkPD+fSpUvm+R9++CFpaWmMHDmSkaZRj9ItD9C7d28iIiJ47bXXuHbtGnXr1mXbtm0ZOg/NN95+xt/JCfDjKvjrALTtD489XTD7E0KIvEqffBVCCCHyWZ6TGjt27ODJJ5+kQoUKnD59mpo1a3LhwgWUUtSvX78gYrQ9UelGPvnlWzj2E9RrC027WjcuIUSehIaGZjmiE2BOVJjs3r07V9sdNWpUwTU3uZejM7h6QkIseBWHkhWNQygKIYStMDWTS06AT6cba7yOfA/s7uvZmhBCCGEhz9UMpkyZwssvv8zJkydxdnbmq6++4vLly7Rq1YqePXsWRIy2J30nodcvwo2LkBRv3ZiEEI8uUyd8ZavB/96Bhh2sG48QQqTn6ARu3sa/L582DusqtTaEEELkkzynyE+dOsWXX35pXNnensTERNzd3Xn99dfp1q0bL7zwQr4HaXNMNTV8SkDVxlAtxPi3EEJYg7c/XP1bviQIIWyXjz/ER0OjJ6BqiLFmmRBCCJEP8lxTw83NzdyPRsmSJfnnn3/M827evJl/kdmyyHDjb98A40W5SkPwK2PdmIQQjy7zCCgR1o1DCCGyYupXw90bgqqDQ8ZhrIUQQliaMWMG7u4F26z4xx9/pF+/flSsWBFN0+67CXX37t3RNI133nnHYnpoaChdunTJj1CzlOeaGk2aNGH//v1Uq1aNTp06MX78eE6ePMnGjRtp0qRJQcRoW5S6+zTUt6R1YxFCCEiX1LgO3yyBv4/Bky9CpXrWjUsIIUxMI6BEyQgoQghhS7Zt28Zvv/1Gq1atiIyMvK9tfP/99/zyyy/5HFnu5TmpMX/+fOLi4gCYOXMmcXFxrF27lsqVKz8aI5/ERUFqMmg6Y4Lj2E8QEASlK1s7MiHEo8rUp0b0DeNQ07E3IeKyJDWEKAT+/vtvdu3axY0bNzAYDBbzXnvtNStFVQBMNTUi/4O/j0JSAtR6zLoxCSGE4O2332bevHkA7Ny5M8/rJycnM2bMGObMmcPQoUPzO7xcyXPzkwoVKlC7dm3A2BRl6dKl/P7773z11VcEBQXle4A2x9RJqFdxuHIWvl5sHEZRCCGsxVxT4wa0eAqGzjaOyCSEsGkfffQR1apV47XXXmPDhg1s2rTJ/LN582Zrh5e/TMnXW9fgi1mwdZnx4ZAQQtiAwYMHU7NmTX766Sdq166Ni4sLrVq14sKFC0RGRtKrVy88PT2pWLEia9euNa+3detW2rdvj7+/P56enoSEhLBt2zaLba9cuRJN0/j11195/PHHcXV1JTg4mJ9++gmDwcCrr75KQEAAAQEBTJkyJUOCG+DIkSM0btwYZ2dnqlWrxrfffmsxPzdxZEWny3NKwMI777yDj48PgwcPzna5VatWUbFiRVxcXAgNDeXMmTMPtN/0HqwE6WzcuNGc7MiLxYsXU65cOZydnQkJCeHw4cPZLh8dHc3IkSMpWbIkTk5OVKlShe++++5+w867yHSdhLq4Q8W6xrahQghhLV5+xt8pScYER9lq4Oxm3ZiEEDmaNWsWb775JteuXePEiRMcP37c/HPs2LE8bcvm76dMydfbkeBfFsrXhrSUgtufEMI6lDLej1jz5z4TpteuXWP8+PG88sorfPHFF/zzzz88++yz9O7dm1q1avHVV1/RoEED+vfvz8WLFwE4f/48Xbt25bPPPuOrr76iefPmdOrUid27d2fY/sCBA+nSpQubNm2iVKlSPPXUU4wdO5bLly+zatUqRo4cydy5c1mzZo3FeqmpqfTu3ZtBgwaxceNGKlWqRI8ePTh58qR5mbzEkZ8uXbrEnDlzeO+999A0Lcvljh07xpw5c5g7dy6rVq0iPDycDh06kJycnC9x5Kn5ybJly/jxxx9xdHRk7NixhISEsHPnTsaPH8/Zs2cZOHBgnna+du1awsLCWLp0KSEhISxYsIAOHTpw5swZ/P39MyyfkpJizkBt2LCB0qVLc/HiRby9vfO03wdiGvnEtwQENzL+CCGENTk4gruPsXlc9A1w87R2REKIXIiKiqJnz54PvJ1CcT/lVdzYdNeQBv2ng6dvwe1LCGE9qckwu691Y5j6JTg653m1yMhI9uzZQ40aNQD477//GD16NJMmTWLatGkANGrUiI0bN7J582bGjh1r0ammwWCgdevW/Pnnn3z44YeEhoZabH/06NHmkUJLly5NrVq1+PXXXzl48CAAHTp04Ouvv2b9+vX069fPvF5KSgqvvvqquWlHhw4dqFy5MrNnzzaPSpqXOPLTuHHjeOqpp3LsW/P69evs2bOHypWNXTbUq1eP4OBgVq5cyf/+978HjiPXNTXmzp3L6NGjuXDhAl9//TVt2rRh9uzZ5uzVlStXWLJkSZ52Pn/+fIYPH86QIUOoXr06S5cuxdXVleXLl2e6/PLly4mMjGTz5s00b96ccuXK0apVK+rUqZOn/T6QyHRJDSGEsBXpOwv9+xj8vBkSbls1JCFE9nr27Mn27dsfeDuF4n7Kzh48ixn/jpbhp4UQtqdUqVLmhAZAlSpVAGjXrp15mre3N/7+/ly+fBmAK1euMGjQIEqXLo29vT0ODg5s376ds2fPZth++/btM2y7bVvL5sJVqlQxbzu9Hj16mP+2s7Oje/fuHDp0yDwtN3GkpaVZ/Dyo7du3s337dubOnZvjsjVr1jQnNAAqVapEnTp1LMrwIHJdU2PFihV89NFHDBo0iH379tGqVSsOHDjAuXPncHPLezXnlJQUjh49ypQpU8zTdDod7dq1M2er7vX111/TtGlTRo4cyZYtW/Dz86Nfv35MmjQJOzu7TNdJTk62qNYSGxsLGDNYmbVXyokWeQ0NMHj5g14P2VSzeRgMBgNKqfsqiy2S8ti2olKOIsknAK6cMdbU+HW7sVZZqUpQvqa1IxNCZKFSpUpMmzaNX375hVq1auHg4GAxf8yYMTluozDdT2ne/mgxERgir0GZYGMVcSvfR5kUxeu1lMd2FZVyZMrByVhTwtox3Id7a6s5OjpmOT0pKQmDwcCTTz5JTEwMr7/+OpUqVcLNzY3XXnuNS5cuZbv9nLZtURwHB3x8fCymBQQEEB4eDpDrOO69xqgH7NdozJgxjBkzBldXV6Kjo83Tk5KSiI6OtihbZrUG05fhQeU6qXHp0iXatGkDwGOPPYaDgwMzZ868r4QGwM2bN9Hr9QQEBFhMDwgI4PTp05mu8++//7Jz506effZZvvvuO86dO8eLL75Iamoq06dPz3SdOXPmMHPmzAzTIyIiSEnJe1tO/1v/oQHR8Yl4z3mWtGKliez+stUuygaDgZiYGJRSD9zJiy2Q8ti2mJgYa4cgsuJ9p1+NqBtQpQHERYPj/V3UhRAPx4cffoi7uzt79uxhz549FvM0TctVUqMw3U95OnviCiT9dQjHXWtI8w4guuOLuVq3oBW167WUx7YV6fspTbuvph+F0blz5zh+/DibN2+mW7du5umJiYn5up/U1FSioqIsEhvXr1+nZMmSeYrjyJEj+RrXmTNnmD17NrNnz7aYPm3aNKZNm0ZiYiLOzsb3wo0bGYfzvn79OnXr1s2XWHKd1EhOTjYHBcYskq/vw20PaTAY8Pf358MPP8TOzo4GDRpw9epV3n777SwvwlOmTCEsLMz8OjY2lsDAQPz8/PLedjQpHl1yPADeHq7o0pJxMKTif8+NxMNkMBjQNA0/P78icZKX8tg2U1ZZ2CDvdMO69p9m3ViEELly/vx5q+zXavdTJcvBmYO4GFLRYm5gp2X+9M4aitr1Wspj2+R+qmgwJQ3S/z8vXrzIzz//bG5ekl82bdpk7lNDr9ezefNmQkJC8hRHw4YN8zWmXbt2ZZjWunVrRowYQe/evS3i+eOPPzh37hyVKlUCjImY3377LV/604A8dhQ6bdo0XF1dAWN1x1mzZuHl5WWxzPz583O1reLFi2NnZ8f165btKq9fv06JEpn3V1GyZEkcHBwsqkZWq1aNa9eukZKSkukJwsnJCSenjE8rdTpd3k+K0XcyTG7e6IIbw6hFaMkJaFY+uWqadn/lsVFSHttVFMpQZKXvU0MIUeiYqgFn13t8ZgrV/ZSvMfmqpSTCwJloxctY/R4qvaJ0vQYpjy0rCmUQULVqVcqUKcPkyZPR6/XExcUxffp0Spcuna/7cXR0ZNasWSQlJVG+fHk++OADLl++bB76+0HjuHjxorkWR0JCAv/88w8bNmwA4JlnnjEvZ29vz6BBg/jkk08AsuyAtGLFihnmBQQE0LVrV15//XXAmFcoXbp0jsPA5lauP1EtW7bkzJkz5qHGmjVrxr///msx/NiJEydyvWNHR0caNGjAjh07zNMMBgM7duygadOmma7TvHlzzp07Z9EO7ezZs5QsWfLhZDzTdxJqZw/FS0PpytmvI4QoUEqpB24TWCT4mJIaEXeHMkuV4RKFsHWrVq2iVq1auLi44OLiQu3atfnss89yvX6hup8y1SiLuQkVassIKEKIQs3JyYmNGzfi5OREz549ee2113jllVdo1apVvu7HwcGBL7/8kuXLl9O9e3f+/vtvvvrqK2rXrp0vcezatYuePXvSs2dPIiIi2LZtm/l1enq9Hr1ef19lqF+/PhMnTmTixIkMGDCAgIAAfvjhh0yT5fdFWdGaNWuUk5OTWrlypfrrr7/U888/r7y9vdW1a9eUUkoNGDBATZ482bz8pUuXlIeHhxo1apQ6c+aM+vbbb5W/v7+aNWtWrvcZExOjABUVFZX3gPesV2p6d6W+WpD3dQuIXq9X4eHhSq/XWzuUfCHlsW1RUVEKUDExMdYORX366aeqZs2aysnJSTk5OalatWqpVatWWTusfHFf56nUFKWm9zCeo6JuKLVghFIznlIq4XaBxZlbRe1zIOWxbbZ0nsrJvHnzlKurq5o4caLasmWL2rJli5owYYJydXVV8+fPz/V2Cs39VOwt4zlqxlNKpaXmfr2HoKh9DqQ8tq0wnaeyk5iYqP766y+VmJho7VBEEZSX91eemp/kt969exMREcFrr73GtWvXqFu3Ltu2bTN3dnXp0iWL6lmBgYH88MMPjBs3jtq1a1O6dGnGjh3LpEmTHk7AUelqauzdAB6+UL0pOLk8nP0LIQBjM7dp06YxatQomjdvDsD+/fsZMWIEN2/eZNy4cVaO0ArsHYzDJcbehNuRoE8FZYCbVyCwqrWjE0Jk4v3332fJkiUMHDjQPO3JJ5+kRo0azJgxI9fnskJzP+XuA/aOkJYC/56EqHDjyE2VGxTsfoUQQhRpVk1qAIwaNYpRo0ZlOm/37t0ZpjVt2pRffvmlgKPKgqn5iWcx+Hqx8e/gRtaJRYhHWH59EShyvP2NSY3oG9DvFeMXCDevnNcTQlhFeHg4zZo1yzC9WbNmeR7mrlDcT2macaSmm1fh1EE49iPUbCFJDSGEEA9EeqnJC1NNDQ9faPgEBDcGVw/rxiTEIyg/vwgUKebOQm9AifLg7m214aaFEDmrVKkS69atyzB97dq1VK5cRPvsMvWr4eRivI+SmmRCCCEekNVrahQaqckQe8v4d6mKULm+deMR4hFm+iIwdepUi+lF+otAbvikS2oIIWzezJkz6d27N3v37jU3pfv555/ZsWNHpsmOIsF0nrJzgL5TrBuLEEKIIkGSGrkVdedLgpMruHpaNxYhHnGP5BeB3DDV1Ii6Donx8NsuiIuGdv2tGpYQInNPP/00hw4d4t133zUPzVetWjUOHz5MvXr1rBtcQTHV1JDhp4UQQuSTPDc/2bZtG/v37ze/Xrx4MXXr1qVfv35ERUXla3A2xdT0xKcEpCTdHTJRCPHQmb4IFC9enM2bN7N582aKFy/O4cOH6dGjR663s3fvXrp27UqpUqXQNM38pSIr4eHh9OvXjypVqqDT6XjppZcyLLNy5Uo0TbP4cXZ2zmMJ75P5y8INUHrY9gns/8p4zhJC2KQGDRrw+eefc/ToUY4ePcrnn39edBMaYOwYFO4+LNLrjbVhhRCFlpLvRaIA5OV9leekxoQJE4iNjQXg5MmTjB8/nk6dOnH+/HnCwsLyurnCw9RJqG8ArJwGc/vD+T+sG5MQj7D8+CIQHx9PnTp1WLx4ca6WT05Oxs/Pj1dffZU6depkuZynpyfh4eHmn4sXL+YprvtmqqkREwHO7lA7FB57GvRpD2f/Qogcme6hTH9n91Mkmfv+uQ7ffwxv9oFft1s3JiHEfXFwcAAgISHBypGIosj0vjK9z7KT5+Yn58+fp3r16gB89dVXdOnShdmzZ3Ps2DE6deqU180VHpF3Oh/0DoB/foPkBHCXUQWEeFhiY2Px9PQ0/50d03I56dixIx07dsx1DOXKlWPhwoUALF++PMvlNE2jRIkSud5uvvEsBprOmMSIi4Knxj78GIQQ2fLx8SE8PBx/f3+8vb3RMunMVymFpmno9XorRFjATDU14mOM/WoY0uDWf9aNSQhxX+zs7PD29ubGDWPNK1dX10zPaULkhVKKhIQEbty4gbe3N3Z2djmuk+ekhqOjozlr8tNPP5mHVPT19S26TxXgbvOTYqXg5RXGJIdvSevGJMQjpDB9EYiLiyMoKAiDwUD9+vWZPXs2NWrUKPgd29mBV3Fj85Oo68YkhxDCpuzcuRNfX18Adu3aZeVorMDF3dg/WXKCsdP1xh3Bs7i1oxJC3CfTQxxTYkOI/OLt7Z3rh4R5Tmq0aNGCsLAwmjdvzuHDh1m7di0AZ8+epUyZMnndXOFhbn5SAhwcISDIuvEI8YgpLF8EgoODWb58ObVr1yYmJoZ33nmHZs2a8eeff2Z5jkxOTiY5+W6bclOC2GAwYDAY8rR/zdsfLfoGhqjrxqES9WnGJ6JWTHAYDAaUUnkui62S8tg2Wy9Hq1atzH+XL1+ewMDADElapRSXL19+2KE9PD4BcO28sb8fU3MUIUShpGkaJUuWxN/fn9TUVGuHI4oIBweHXNXQMMlzUmPRokW8+OKLbNiwgSVLllC6dGkAvv/+e5544om8bq5w0OshOsL4t48VqpQLIQrNF4GmTZvStGlT8+tmzZpRrVo1li1bxhtvvJHpOnPmzGHmzJkZpkdERJCSkpKn/Xs6eeAKxF89TwqO+H49H71HcW72zbj9h8VgMBATE4NSCp0uz1052Rwpj22LiYmxdgi5Vr58eXMNtPQiIyMpX7681WudFRhvf2NSQ4afFqLIsLOzy9OXUCHyU56TGmXLluXbb7/NMP3dd9/Nl4BsUuxNY5tPO3u4cNJYa6NqCJSqaO3IhHgkFaYvAg4ODtSrV49z585lucyUKVMsOlqOjY0lMDAQPz8/vL2987bDkkFw5iDuqfGo8sFoBgN2yfH4Fy8GOuvcbBgMBjRNw8/Pr0h8aZby2DZHR0drh5BrpiZz94qLi3t4oyZZg3kElOtwch9c/Rvqtwf/QOvGJYQQolDKc1Lj2LFjODg4UKtWLQC2bNnCihUrqF69OjNmzChUNxO5Zmp64hMAfx6Av48aq3JLUkMIqyhMXwT0ej0nT57MtiNlJycnnJycMkzX6XR5/5J558uCFhOB5lkMXvoQzau41Tvu0jTt/spjo6Q8tqswlMGUxNQ0jWnTpuHq6mqep9frOXToEHXr1rVSdA+BT7rhp69fhPO/Q0A5SWoIIYS4L3lOavzvf/9j8uTJ1KpVi3///Zc+ffrQo0cP1q9fT0JCAgsWLCiAMK3M1EmoTwmo3hQ8fKF0ZevGJMQjKL+/CMTFxVnUoDh//jwnTpzA19eXsmXLMmXKFK5evcqqVavMy5w4ccK8bkREBCdOnMDR0dE8KtTrr79OkyZNqFSpEtHR0bz99ttcvHiRYcOGPUDJ88DUPj3qBmgaePs9nP0KIXLt+PHjgDFBe/LkSYsHQo6OjtSpU4eXX37ZWuEVPO90NTUadjD2U+ZXhPtlE0IIUaDynNQ4e/as+UvD+vXradmyJatXr+bnn3+mT58+RTOpkb6T0HptjT9CiIcuv78I/Prrr7Ru3dr82pQ0GTRoECtXriQ8PJxLly5ZrFOvXj3z30ePHmX16tUEBQVx4cIFAKKiohg+fDjXrl3Dx8eHBg0acODAAXPSo8CZkhqxN439AUn7ViFsjqmz4yFDhrBw4cJcD0NdZPjcOU9F3zAmNWQISCGEEA8gz0mN9D2k//TTT3Tp0gWAwMBAbt68mb/R2YrIcONv6SRUCKvK7y8CoaGhKKWynL9y5coM07JbHoz9C1m1jyEPH9DZG/sBun0LkuLh+A5w84KWPa0XlxAigwULFpCWlpZhemRkJPb29kU32WFKviYnQGIcuHpYNx4hhBCFWp4bnjZs2JBZs2bx2WefsWfPHjp37gwYq20HBATke4A2Ieq68be7NyTEWjUUIQSsWLGi6N7sPyid3d0mJ9E3IDYSDm2FP/ZbNy4hRAZ9+vRhzZo1GaavW7eOPn36WCGih8TBCdx9jH9H3wCDwdhkzoY6eRZCCFF45LmmxoIFC3j22WfZvHkzr7zyCpUqVQJgw4YNNGvWLN8DtDql7jY/uXoONswz9tD95IvWjUuIR9yvv/7KunXruHTpUoZhTzdu3GilqGyEt7+xhlnUDahYF5p1M3bCJ4SwKYcOHWL+/PkZpoeGhvLKK69YIaKHyNsf4qKM91hfvAHxMTDyfelbQwghRJ7lOalRu3ZtTp48mWH622+/XTTHJo6PgdQkQDNW5wbjyCdCCKtZs2YNAwcOpEOHDmzfvp3HH3+cs2fPcv36dXr06GHt8KzPO117dU9feHywVcMRQmQuOTk50+YnqampJCYmWiGih8gnAK6cgZgb4Fnc2FQu9qYkNYQQQuTZfY17Fh0dzccff8yUKVOIjIwE4K+//uLGjRv5GpxNMPWn4VUcOg6DqV9Cky7WjUmIR9zs2bN59913+eabb3B0dGThwoWcPn2aXr16UbZsWWuHZ33pkxpCCJvVuHFjPvzwwwzTly5dSoMGDawQ0UNkHqnpOjz7KkxdY6xZJoQQQuRRnmtq/P7777Rt2xZvb28uXLjA8OHD8fX1ZePGjVy6dMli6MMiIf3IJwCOztaLRQgBwD///GPuz8fR0ZH4+Hg0TWPcuHG0adOGmTNnWjlCK/O5079R9J3+gAx6Y4JDAcVKWi0sIYSlWbNm0a5dO3777TfatjWOrLZjxw6OHDnC9u3brRxdATOdp6JuGPssE0IIIe5TnmtqhIWFMWTIEP7++2+cne9+we/UqRN79+7N1+BsQtSdpIaMfCKEzfDx8eH27dsAlC5dmj/++AMw1iJLSEiwZmi2wdxRaITx98+b4b0XYc9aq4UkhMioefPmHDx4kMDAQNatW8c333xDpUqV+P3333nsscesHV7BMtcou27dOIQQQhR6ea6pceTIEZYtW5ZheunSpbl27Vq+BGVTTDU1HJzgq3ehTDCEdLJuTEI84lq2bMmPP/5IrVq16NmzJ2PHjmXnzp38+OOPtGnTxtrhWZ/py0LsLdCnQfEyYOdgHGFACGFT6tatyxdffGHtMB4+c42yG5BwG/ZvhJgIeGY8aJp1YxNCCFGo5Dmp4eTkRGxsxmFNz549i5+fX74EZVNMNTUMeji5F+KiJakhhJUtWrSIpKQkAF555RUcHBw4cOAATz/9NC+//LKVo7MB7j5g7whpKRBzE6o0gFe+NA73KoSwSUlJSRlGcirSQ1d7FgdNZ0y8JsXDwa9BGeCJ58DDx9rRCSGEKETy3PzkySef5PXXXyc1NRUATdO4dOkSkyZN4umnn873AK3OVFOjXC1o2x/qtrZuPEIIfH19KVWqFAA6nY7Jkyezbt06SpUqRb169awcnQ3QNPAyNUG5AXb2ktAQwgYlJCQwatQo/P39cXNzw8fHx+KnSLOzM3bCDnA7Elr2hE7Pg72DdeMSQghR6OQ5qTFv3jzi4uLw9/cnMTGRVq1aUalSJTw8PHjzzTcLIkbrSUqAhDu1UirVhceehjqh1oxIiEdacnIyU6ZMoWHDhjRr1ozNmzcDsGLFCipWrMjChQsZN26cdYO0FT4yAooQtm7ChAns3LmTJUuW4OTkxMcff8zMmTMpVapU0et4PTPpR2pq3QcadwQXd+vGJIQQotDJc/MTLy8vfvzxR37++Wd+++034uLiqF+/Pu3atSuI+KzL1PTE1ROcXKwbixCC1157jWXLltGuXTsOHDhAz549GTJkCL/88gvz5s2jZ8+e2NlJjQTAcrhEgN92w8l9UKMZ1GkNuvsa0VsIkY+++eYbVq1aRWhoKEOGDOGxxx6jUqVKBAUF8cUXX/Dss89aO8SC5RMAF/64e54SQggh7sN939U2b96cF198kYkTJz5wQmPx4sWUK1cOZ2dnQkJCOHz4cK7WW7NmDZqm0b179wfaf5ZMTU98AuDKWWObTyGE1axfv55Vq1axYcMGtm/fjl6vJy0tjd9++40+ffpIQiM973Sd8AH8dhjOHYNf90CDBvDzz9aLTQgBQGRkJBUqVACM/WdERkYC0KJFizyPKGez91LZSX+eUsrYuXH4vw8/DiGEEIVanpMaY8aM4b333sswfdGiRbz00kt5DmDt2rWEhYUxffp0jh07Rp06dejQoQM3bmRfZfrChQu8/PLLBTvkWWS48be7D3w8Cd4ZKqMHCGFFV65coUGDBgDUrFkTJycnxo0bhyY95WeUvlq3wQDLv4JvT8Br78GJEzBqlJzPhLCyChUqcP78eQCqVq3KunXrAGMNDm9v71xvx6bvpbJjGgEl6jpcPg3zh8GaudaJRQghRKGV56TGV199RfPmzTNMb9asGRs2bMhzAPPnz2f48OEMGTKE6tWrs3TpUlxdXVm+fHmW6+j1ep599llmzpxpfsJRINI3P3H3Ad8SUmVbCCvS6/U4OjqaX9vb2+PuLu2vM5W+Tw2dDma/C0cvwLUY4/TFi+V8JoSVDRkyhN9++w2AyZMns3jxYpydnRk3bhwTJkzI9XZs+l4qO+nPU8VKG0dDcXA0jogihBBC5FKe+9S4desWXl5eGaZ7enpy8+bNPG0rJSWFo0ePMmXKFPM0nU5Hu3btOHjwYJbrvf766/j7+/Pcc8+xb9++bPeRnJxMcnKy+bVpOFqDwYAhh6eUWuQ1NMAQVA26vgBpqTb3ZNNgMKCUyrEshYWUx7ZZuxxKKQYPHoyTkxNgHAJxxIgRuLm5WSy3ceNGa4RnW0w1NW5HQkoyjBx5d54GjBoJvx6VxIYQVpS+Y+N27dpx+vRpjh49SqVKlahdu3autvEw7qXgwe6nsuTlhw5QsbdQjs4wdTXY3Rn95CFfb4ri9VrKY7uKSjlyotfrzSNmCmHi4OCQ703G85zUqFSpEtu2bWPUqFEW07///vs8Z/pv3ryJXq8nICDAYnpAQACnT5/OdJ39+/fzySefcOLEiVztY86cOcycOTPD9IiIiAzjwd/L7+Z/2AFROJGaQxVOazEYDMTExKCUQlcEvpxIeWxbTEyMVfc/aNAgi9f9+/e3UiSFgKsnODhBajLE3oRFi4xNTt6aCd8uhQatJKEhhBWlpqbyxBNPsHTpUipXrgxAUFAQQUFBedrOw7iXgge7n8qSUgTYO6ClpXLz3zPoTUNRW0FRu15LeWybte+nCppSimvXrhEdHW3tUISN8vb2pkSJEvnWhDzPSY2wsDBGjRpFREQEbdq0AWDHjh3MmzePBQsW5EtQWbl9+zYDBgzgo48+onjx4rlaZ8qUKYSFhZlfx8bGEhgYiJ+fX/btVdNS0eKiAPCpWB3cMtZOsQUGgwFN0/Dz8ysSJ3kpj21L3/TDGlasWGHV/RcqmmasrRFxGaIjoHlzOHoUzhwGXye49qdx2GpnV2tHKsQjycHBgd9///2h7/d+7qXgAe6ncuIdADevUMwuDfz9jTU0dLq7vx+Sona9lvLYNmvfTxU0U0LD398fV1dX6ftMmCmlSEhIMPf5VLJkyXzZbp6TGkOHDiU5OZk333yTN954A4By5cqxZMkSBg4cmKdtFS9eHDs7O65ftxzK6/r165QoUSLD8v/88w8XLlyga9eu5mmm6lv29vacOXOGihUrWqzj5ORkrqqenk6ny/6kGBMBKHB0RvfNB+DiAe36g4dvHkr4cGialnN5ChEpj+0qCmV4pJiTGnfOsTodVGsCjw+Gmi0koSGElfXv359PPvmEuXPvv3PMh3EvBQ9wP5UTH2NSQxcTAd+th68/gWahsHC9sYZZJv24FZSidL0GKY8tKwplyIperzcnNIoVK2btcIQNcnFxAeDGjRv4+/vnS1OUPCc1AF544QVeeOEFIiIicHFxue+O+hwdHWnQoAE7duwwDyVmMBjYsWNHhuYtYOwZ/P/Zu+/4KIr3D+CfvcuV9F4IpFESEggk9NA7AvKlSFcMSBEFpUhHSQAhICAiUtQfEFDpUkS6SARC6L1LbwFCSCE9uXt+f5y35NL7XcLzfr3uldze7OzM7t2ze3OzM5cvX9ZZ9uWXX+L169dYsmQJXFxcilSOHGkHCbV0AG6d0fz/zkcllz9jjJU26yzTumo17V72ZWGMZZORkYHVq1fjr7/+Qv369bOND/Ttt9/mm4dBX0sVhHb8n1fPgR9WAE0cgaP738zSdJbH/mGsPNGOoWFiwj+csNxp3x/p6en6adS4d+8eMjIyUKNGDdjbv7n38d9//4VMJoO7u3uh8hs/fjwCAwPRoEEDNGrUCN999x0SExMxZMgQAMCHH36IypUrIyQkBEqlErVr19ZZX9vlMevyYnv1X6OGjRPQuq/mS4Exz7LAGCtHtF8WYvIYE+jZfUCuAGxKpvsfYyx/d+/ehbu7O65cuYJ69eoBAG7duqWTpjDdtQ32WqogMje+Tp8HLJ+smX4a4FmaGCvH+JYTlpeSfn8U+kwxePBgHD9+PNvykydPYvDgwYUuQL9+/bBw4ULMmDEDfn5+uHDhAvbt2ycOePXw4UNERkYWOt9i0zZq2FUGajUDmvUs+zIwxkrVkSNH0K1bNzg7O0MQBOzYsSPP9JGRkRg4cCA8PT0hkUgwduzYHNNt2bIFNWvWhFKphK+vL/bs2VPyhS8Iq0zTJebkYhjw0wRg5zKDm9mJsYqsRo0aePnyJQ4fPozDhw/DwcEBGzduFJ8fPnwYf//9d4HzM9hrqYIQG1+fA5+PATaeABJSNMtGjQJePASI9Fc+xhhjBq/QjRrnz59Hsxzub2zSpEmhRtHObPTo0Xjw4AFSU1Nx8uRJNG7cWHwtLCwMoaGhua4bGhqa7xeRItHefmKd/X5UxljFkJiYiLp162LZsmUFSp+amgp7e3t8+eWXqFu3bo5pjh8/jgEDBmDo0KE4f/48evTogR49euDKlSslWfSCERs1nuf8uquPZvpEYzPNLCmMsTJBWb6k7927F4mJicXK0yCvpQpC7KnxXDOGhp8fEB6u+Tt7CvDjF8DuHwGVSj/lY4xVaIIgQBCEPGOkvt2+fRvt27eHhYUFBEFA69atS3wbrVu3zpZ3edg3WoVu1BAEAa9fv862PC4uDqqKdMLR9tTISAOe3uELfsYqoM6dO+Prr79Gz54F64nl7u6OJUuW4MMPP4SlZc4zIi1ZsgTvvPMOJk6cCG9vb8yePRv16tXDDz/8UJJFLxjtl4XEOCAthxhm7QB8shjoNxlQGJdt2RhjoqyNHG8Vq//iVFI80KCeZgyNpk01fx0tNY0ZCbGaGZ0YY+We9suzIAiYM2eOuPzGjRvl6kt0Wfriiy9w6NAhpKeno2HDhvDx8ckxXVhYmLgPsz78/PwKvd3GjRujcePG4pAT9+/fF/MLCwsrRo1KXqHH1GjZsiVCQkKwYcMGcVAPlUqFkJAQNG/evMQLqBdq1ZtfNs8eAPatAvpPAWo2zns9xthbLyIiQmfaQwDo1KmTfn4FVZoCChMgNQmIewHY5zAAoA33RmOsrGkvCrMueysZm2piVUqi5lY5RzfNcokEaPiOJka5ePPYGoxVQAsWLMAnn3wCGxvDm12ypKSlpRV7Ct+rV68CAMaOHYuQkJACrVO1alWd8S89PT0Lvd0TJ04Ueh19KfQZYv78+fj777/h5eWFIUOGYMiQIfDy8sKRI0ewYMGC0ihj2YuPBlQZgMQIsLAFTCwAW2d9l4oxVg48e/ZMvI9dy9HREc+ePct1ndTUVMTHx+s8AM0MBsV6EIGsNCc09atneadNSwEd/AXqS0eKv90cHkRUKvnq68H1MeyHoSMiDB48GL169UKvXr2QkpKCkSNHis+1j7eGVS4zNQFANT/NYMZaEX9oetAyxsq9uLg4zJ8/P9fXM/c8uH//vrg8a4+O0NBQcdmWLVvg7+8PY2NjdO7cGVFRUfj555/h4uICW1tbfPrpp+IMLZnFx8cjMDAQ5ubmsLe3x4wZM3R60cXFxWHMmDFwc3ODXC5HlSpVMH78eCQlJYlpBg8eLN7C8c0336BKlSpQKpW51k+lUmHRokXw8fGBQqGApaUlOnTogKNHjwJ40zPizh1NzJs3bx4EQSjQOJZfffUVTpw4IT7WrVsnvhYTE4O+ffvCxMQErq6uWLlyZY55ZN7PoaGh8PDwEF9r06aNzu0qJ06cQLt27WBrawulUgl3d3f06NFDLHtpK3RPDR8fH1y6dAk//PADLl68CGNjY3z44YcYPXp0xWll0956Yu0ADArS/P82dw1ljJWqkJAQzJw5M9vyqKgopKWlFStvK2MrKPEArx/dRbJl7lM1mlz+Gxbh20BKM0RZuYDkJXc7ilqtRlxcHIgIkgrwayvXx7DFxcXpuwj5CgwM1Hn+wQcf6KkkBsLaAXh2VzNYaF6unwT2rwFkCmDUUsDKPu/0jDGDVb16dTx//hxLly7FmDFjSizfwMBAuLm5ITU1Ffv27UOrVq1w+/ZteHh44PHjx1ixYgXq1q2Ljz/+WGe9adOmwdLSEpaWlnjy5Almz54NOzs7fP7550hLS0Pr1q1x4cIFKJVKeHt749atW1i8eDEuXryIv/76S6e3XUREBI4ePQovLy+kpKTkWtaPP/4Yq1atEvfHq1ev8NdffyEsLAx//fUXPD090bhxY5w/fx5paWmoXLkyqlSpgmrVqhVrHw0bNgzbtm0DoJladcKECfmuY29vLw5EDQDe3t6wsLCAj48P1Go13n33XURHR8PR0RHe3t548uQJdu7cibFjxxa7vAVR6EYNAHB2dsbcuXNLuiyGI6dBQt/WbqGMsUJxcnLC8+e6F+bPnz+Hk1Put3lMnTpV55aV+Ph4uLi4wN7eXpxqsagExyrA/YuwUCXB3MEh94St3wM9+xeo3xH2VdyKtc2s1Go1BEGAvb19hfjSzPUxbMXt5lsW1qxZo+8iGJa8empk5uGr6bnh5MENGoyVc7a2tnj//fcxc+ZMzJo1K9cZ5Qpr+vTpmD59Oj744AP89ttvuH79On799Ve8//77aNGiBY4dO4bDhw9na9SoV68eDh06BABo164djh49irlz5+Lzzz/Hhg0bcOHCBcjlcly6dAk1atTAxYsX4efnh7///ht///032rVrJ+aVlpaGPXv2oHPnzrmOOXnnzh2sXr0aADBmzBh89913iIuLQ926dfHgwQPMmDED//zzD06cOAF3d3c8ePAAw4YNQ3BwcIH2g/aOCq2goCAEBwfjzp07YoPG5MmTMW/ePNy8eTPfKb27du2KWrVqib01li9fLvbSiI6ORnR0NADg7NmzqFy5MgDNbTOZb4EpTYVu1Dhy5Eier7ds2bLIhTEY2p4afK85Y6yQAgICcOjQIZ2T88GDBxEQEJDrOgqFAgqFIttyiURS/C+Z/w0WKsRFQcgrL4kCGBSE0mq+FQShZOpjILg+hqsi1OGtY51pWte8KE2AgV/q/tCUkQ4IEuC/cd4YY+XHF198gWXLlmHVqlV49913SyTPbt26AdAM7p51WdWqVXHs2LFsPz4BQO/evSGTycT/jx49iufPnyMqKgqnTp0CoGmsyGlsCu2tF1peXl7o3LkzAIhjUGZ19uxZ8faWgQMHAgAsLS3RpUsXrFixAmfOnClUvbPKOqZGlSpVALwZnwMA3nvvPbG8derUwblz54q0LVtbWwQEBCAiIgLVq1dH9erVUbt2bXTt2lWsW2krdKNGTlPIZO5uUyFmQNE2akQ/BVZPAxp1BWpnn8aWMVa+JSQk4Pbt2+Lze/fu4cKFC7CxsYGrqyumTp2KJ0+e6NyHqO12l5CQgKioKLHlXjsS9ZgxY9CqVSssWrQIXbt2xcaNG3HmzBn89NNPZVo3kXZa15h8fgHNKj0VUKt5VhTGWOmzLmBPDUC38UKtBrZ/rxkMuc8EjleMlTPm5uaYOnUqvvjiCwQFBWV7PafvmPndYmhhYQEAMDIyyrZMm19RZ5ySy+Xw9/fPttza2lrnedax1fThq6++KtDYGyXl0KFDWL9+PcLDw3Ht2jVs3boVGzduRGRkJCZOnFjq2y/0zxkxMTE6jxcvXmDfvn1o2LAhDhw4UBplLHva20+S4oGH1zUjcjPGKpwzZ87A399fPEGNHz8e/v7+mDFjBgAgMjISDx8+1FlHm/7s2bNYv349/P390aVLF/H1pk2bYv369fjpp59Qt25dbN26FTt27Mi3W1+pKWi37swe3gBWjAMOrss/LWOMFZc2TsU8L9wYZlGPgJungLsXgef3S6VojLHSNWrUKLi4uOTYS8Ah022zt27dAgBs2bKlVMqxbds2ZGRkICMjQ7w9w9HREfb29mjYsCEATcPK8uXLxcE3w8LCMHHixGy9EQoym1X9+vXFdOvXrwegabDZs2cPAKBBgwYlVrfMMk8Hu337dgCafXvp0qV81zUxMRH/T0x88/2YiHD8+HEMHjwYq1evxokTJzB06FAA+d/lUVIK3VPD0tIy27IOHTpALpdj/PjxOHv2bIkUTG+I3vTUaNUXSEsFqhR+ChzGmOFr3bp1nq31Oc2TXpDW/T59+qBPnz7FKVrJ0fbUSH4NpCYX7JdMVTrwKhLISANSBmm6fDPGWGnRxqm0ZE2sMrEo2HqObsCQrzXXba7epVc+xlipUSgUCAoKwrBhw7K9VqNGDbi6uuLhw4cYOHAg/Pz8cPz48VIpx5kzZ8RbVp48eQIAmDJlCgBgwIABWLx4MS5duoSGDRvC29sb6enpePDgAVJTU3Hv3r1Cj4FWrVo1fPTRR1i1ahWWLFmC3bt349WrV3j16hWMjIxyHEC+MGbPnq0zq4m5uTkOHjyI6tWro0ePHtixYwdCQkKwfft2PHr0CFKpFBkZGXnmaW9vD1tbW0RHR2PQoEGoUaMGPvjgA3zyySdo3749zM3N4eLiAolEgmvXrgEA6tSpU6x6FFSJ3Xjq6OiImzdvllR2+pMUrzmpQgCq+QN1WvLYGoyx8ktpAhibaf4vaG8ND1+g11jg0yXcoMEYK30yOWD2X/ftwt4qV7kG4NvizfOEWODWfz+wlYPpfRljmqlQvby8si03MjLCpk2b4O/vj5SUFLx69UrsXVDS5s6di3bt2iEuLg62traYPn06Pv/8cwCahpd//vkHn3/+OVxcXHDr1i3ExMSgQYMGmDNnTpFvN/nxxx+xYMECeHt74+HDh0hPT0f79u3x999/5zjkQ2HcvXsXJ0+eFB+nT58WX1u1ahXee+89KJVKxMXFYdasWWjSpEm+eQqCgJ9//hnVq1dHfHw8Tp06hQcPHkAqlWLkyJHw8PDAkydPcPv2bbi7u2PChAli7+fSJlAhbyrK2jWFiBAZGYl58+YhIyMDx44dK9EClrT4+HhYWloiJiYm5xa1RzeAVVMBCztg/M9lXr7CUqvVePHiBRwcHCrE4GhcH8MWGxsLa2trxMXFifcnspKXb5wqrB+/ACLvAv2nAjUbFT+/QqponwOuj2HjOFU2SjxOrZqquQbrMwGoVcRxzNJTgR/GAbFPgdpdgLkrgB9+AJrln19F+xxwfQxbRY5TKSkpuHfvHjw8PKBUKvVdHGagSvp9UujbT/z8/CAIQrYu2E2aNBGnpSnXtLeemFkDV48DTu6ArbNei8QYY8Vi5aBp1CjMuBqZ3b0EmJhrplFkjLHSYOWgadQobE8NHQJw8RbgqABGjgdeJQKjRwNnzwIV4IswY4yxnBW6UePevXs6zyUSCezt7StOS5x2OjFSA1sWAL4tgffG6bdMjDFWHEUZLFTr7AFg1wpNg8bwbwBpoU8bjDGWP3EGlHymdc2LTA4Mnwl06QDEJ2uWLVvGDRqMMVbBFfrq1M3NrTTKYTi0PTUs7QCJFHCupt/yMMZYcWkH4StKo4ZXI+CvXwEXL0Cl4kYNxljpKOr005mp1ZqeGdoGDQAYNYp7ajDGWAVX4AgfERGBP//8U2fZunXr4OHhAQcHB4wYMQKpqaklXsAy9ypS89e3BTB8PhDwP/2WhzHGisu6GI0aZlbAZ8uArh8DckWJFosxxkTanhoxz4qeh0SiGUPDzw/45zDQuSmwaB43aDDGWAVX4Cg/a9YsXL16VXx++fJlDB06FO3bt8eUKVOwa9cuhISElEohy5T2ZGrNM54wxioI8RfQInbrNjF/8792NgGeVYAxVpK0t8nFRRUvvjRrpumZce8w0MgBMEkvmfIxxhgzWAVu1Lhw4QLatWsnPt+4cSMaN26Mn3/+GePHj8f333+PzZs3l0ohy0xqMpAYp/mfp3FljFUU2kaN1CQgObHo+YT9BQzrCGxaBtSvD4SHl0z5GGPMwhYQJIAqA3j9qnh5SSSAZwNN7w8jecmUjzHGmMEqcKNGTEyMzhy8//zzDzp37iw+b9iwIR49elSypStr2l4achPgh8+Ard/qtzyMMVYS5ErA5L8p44o6CJ9aDSyZBbiaAxf2Areuae5d5x4bjLGSIJUClvaa/4s6U1NmjToDn68AGnQsfl6MMcYMWoEbNRwdHcWZT9LS0nDu3Dk0adJEfP3169eQyWQlX8KypB0k1MQcSIgBkuL1Wx7GGCsp1sWYAQXQ/PI5IQQ4dgvYfApITuNZBRhjJcu6mLfKZSY1AgSh+PkwxhgzeAW+Gu3SpQumTJmCo0ePYurUqTAxMUGLFi3E1y9duoRq1cr5TCHaRg3nasCw+UDbgfotD2OMlZTijquhnVXg0DXgbhRA0MwqwD01GGMlRTuuxqtiDBaaFVHJ9PxgjDFmsArcqDF79mwYGRmhVatW+Pnnn/Hzzz9DLn9zn+Lq1avRsWM57+Knvf3ErjJQxVPzYIyxiqC4jRqZZxUID9f8/eEH7qnBGCs5qv/iyfcLgVq1gJs3i5dfcgKwdBTw/SggpRjjCTHGWAm7ffs2Ro4cCT8/PxgZGaF27do5plu1ahU8PT2hVCpRt27dbLORAkBcXByGDh0KGxsbmJubo3fv3oiMjMyW7vjx4wgICICxsTHc3Nwwf/58EFGJ100fCnw1amdnhyNHjiAmJgYxMTHo2bOnzutbtmxBUFBQiRewTGl/GeBBQhljFU3qfyetX1cX/cuCdlaBOj7AspmAgr8kMMZK0E9rNX9dbIDEF0CvXsXLz9gMkEg1t6FE3i1++RhjrIRcvXoVu3fvRvXq1eHj45Njmo0bN2L48OHo168f9u7di4CAAPTs2RMnTpzQSdevXz8cOHAAK1euxG+//YabN2+ic+fOyMjIENPcvn0bnTp1QqVKlfDnn39i7NixmDFjBhYtWlSq9SwrRoVdwdLSMsflNjY2xS6M3r36r0Xr8S1AYaoZOVsq1W+ZGGOsJHz7A9CyClDFBjhzX/NlIdM03QUmkQD3LgMH1mgG9avXnntrMMaKT6UCzl0DmlQCbM2Awc2BVwnA3xsAvzZF/8GpzwRNTzWFccmWlzHGiqFbt27o3r07AGDw4ME4c+ZMtjRBQUHo378/Zs+eDQBo06YNLl26hFmzZmHPnj0AgIiICOzfvx/79+8X75rw8vKCt7c3tm3bhr59+wIAFixYAFtbW2zcuBFyuRzt2rVDVFQU5syZg88++wwKhaIsql1q+EpUKyMdiI/W/H9mP/D7tzzAFGOsYlCpgJOXNIN7miqA9wOABtbA/SI0agBAzUaAhy/QrAegVpVoURljbympFLB3AUKPARceAqkZgI0ZcGQz8P0nwOppwJkDhZ+W2tGNGzQYYwZHks8PQnfv3sWtW7fERgmt/v3749ChQ0hNTQUA7N27F1ZWVujQoYOYxsvLC35+fmLDhzZdjx49dIaP6N+/P2JjYxEREVESVdIrbtTQin0BkFozn3ntFoBXI/71kTFWMUilgHt1YMVh4MRtIEMFeNgDoV8C6+cAz+4VLj+ZAgicBTTqAhiV81mvGGOGY9s2wNQB2HkO2H0PCOgHVPMDBAnw8Drw5wpg4RBg8wLg5mlAlZFvljoqyL3jjLGK78aNGwCAmjVr6iz39vZGWlqaOCvpjRs34OXlBSHLj/He3t5iHomJiXj06FG2vGrWrAlBEMR05ZlBfGtftmwZ3N3doVQq0bhxY5w6dSrXtD///DNatGgBa2trWFtbo3379nmmLzDtIKE2lYDe44E+XxQ/T8YYMxTbtgEuHsD+K8C+B0C1hpovCrfOACvHA1sWAS+f6LuUjLEiMohrqeLy8tLcFpeRAVy6AnTqDwwKAsb9BHT4EHBwBVTpwLXjwIa5wKKhwN7/A57eybvB4vEtYP1cYNeKsqsLY6zUERHS0tL0/iiNwTZjYmIAAFZWVjrLra2tAQCvXr0S02VNo02nTRMbG5tjXnK5HCYmJmK68qzQY2qUtE2bNmH8+PFYuXIlGjdujO+++w6dOnXCzZs34eDgkC19WFgYBgwYgKZNm0KpVGL+/Pno2LEjrl69isqVKxe9IK/+mxGABwlljFVE2i8LKtWbsYJePgHCNgJXjgFXj2m+KPi1BVr1Bazs889TlQHcuQiYmPNsUYzpkcFcS5WUrOOZWdgCzXoCTXsAz+4DFw8Dl48AiXHAyd2ah70LUKeV5mFppxvrVBnArdOAwgToMpx7mDFWQaSnpyMkJETfxcDUqVN1butgZU/vPTW+/fZbDB8+HEOGDIGPjw9WrlwJExMTrF69Osf0v/32Gz799FP4+fmhZs2a+L//+z+o1WocOnSoeAXRDhJqlf3kzxhjFUbmLwt2lYHeXwAjvwU8G2puwTv/F7D0U2DvKiAhNu+8jmwB1n8NHP29VIvMGMubwVxLlTZBACp5AO98BIxfBQz8EqjdXHPrcNQj4NCvwOIRwCcdAe/Kb2Z6cvEC2n0AfDQXkOr99zzGGMuXtkdGXFycznJtDw7tJB3W1tbZ0mjTadNoe2hkTZeWloakpKQKMeGHXiN7Wloazp49i6lTp4rLJBIJ2rdvX+ABS5KSkpCenp7rwUhNTRUHUgGA+Ph4AIBarYZarRaXC68iIQCgC38D1yNA738F2FUpQq3KllqtBhHp1KU84/oYtopSD5aFkwcwcBrw6AZw6Dfg/hXg5J/AuYNAk3c1v44am2Vfr1Yz4PQ+wLaSpus3D67MWJkri2spoODXU2VGEIDq/ppHSiJwPQLCxX8gPLwGOJqCBjQBrT4G9O4NXLyo6ekBaGJVDl3FK+L5mutjuCpKPfRNJpPpxD59lqOkace/0I6ZoXXjxg3I5XJUrVpVTPfXX3+BiHTG1bhx4wZ8fX0BAKampnBxcck2dsbNmzdBRNnG2iiP9Nqo8fLlS6hUKjg6Ouosd3R0LPCAJZMnT4azszPat2+f4+shISGYOXNmtuVRUVFIS0sTn9u9fAIjAEJKIpCSiBfJGaAXLwpeGT1Rq9WIi4sDEeU7im55wPUxbDm1BLMKxKWmZgDQu5eAv38Dnvyr6YVxep/mC0HjroBc+aZbt4Mr8MVqnvqaMT0qi2spoODXU3pTuQ5QqTakA96DRW0rKOyVSOlcH3EXYoBnz/Id/L2ina+5PoaNr6dKhiAIFfa2j6pVq8LT0xNbtmwRp34FNLcbtmvXTqx3586dMXv2bBw6dEiM4bdu3cL58+cxefJkcb3OnTtj586d+Oabb8RGmE2bNsHKygpNmzYtw5qVjnLdB2/evHnYuHEjwsLCoFQqc0wzdepUjB8/XnweHx8PFxcX2NvbvxkshdQQ/pvOVT3sG0Ctgn0V91IufclQq9UQBAH29vYVIshzfQxbRTtxHDlyBAsWLMDZs2cRGRmJ7du3o0ePHnmuExYWhvHjx+Pq1atwcXHBl19+icGDB4uvBwcHZ7vw9/LyKj8jSwsCUK0uULUOcPOUpueGtlt3+A4g4i6w+wTgVVMz+GimXw8YY+VPQa6lgAJeTxmCVwnAjlvA8JZQOhlDIXkBOP03XtrT2xCuHgfVago4V9dZraKdr7k+hq2iXU+xwktKShKnXH3w4AHi4+OxdetWAECrVq1gb2+P4OBgvP/++6hWrRratGmDTZs24eTJkzhy5IiYT0BAADp16oSPPvoIixYtglKpxPTp01GnTh306tVLTDdx4kT89ttvGDBgAD799FNcvnwZCxYswJw5cyrE+1GvjRp2dnaQSqV4/vy5zvLnz5/DySnvATsXLlyIefPm4a+//kKdOnVyTadQKKBQKLItl0gkb4Ji3CvNaNoSKSSVqpa7Xx0FQdCtTznH9TFcFaEOmSUmJqJu3br46KOPdAJ/bu7du4euXbti5MiR+O2333Do0CEMGzYMlSpVQqdOncR0tWrVwl9//SU+NzIqh+3HggDUbAx4NtAMJHp4AxDzHPB3AFzaAKHhQK9emsFHASD6KSA3Bsyt9Vtuxt4yZXEtBRTwesoQbN2qiU3/PoNQwwnC6H5vemmc2gNc+gcCqXMc3Lgina8Bro8hqwh1YMXz4sUL9OnTR2eZ9vnhw4fRunVrDBgwAElJSZg3bx7mzZsHLy8vbN++HQEBATrraQeLHjFiBDIyMtCxY0csXbpU5/qzevXqOHDgAMaPH48uXbrA3t4eM2fOxBdfVIwZP/V6pS2Xy1G/fn0cOnRI/HVUO1DV6NGjc13vm2++wZw5c7B//340aNCg+AV59d90rlYO5a5BgzFWdJ07d0bnzp0LnH7lypXw8PDAokWLAGjmAD927BgWL16s06hhZGSU75eJckMi1cwmULMJEOAFtPEG7MyBRh7A4WuaW1EOrgVO7AJa9QPa9Nd3iRl7qxjMtZSh0M70dPcSsC4IuHcOeB2jaXD1bQGoVUA1P32XkjH2lnN3dy/QVLBDhw7F0KFD80xjaWmJVatWYdWqVXmma9q0KU6cOFGocpYXev/5cPz48QgMDESDBg3QqFEjfPfdd0hMTMSQIUMAAB9++CEqV64sTtczf/58zJgxA+vXr4e7uzuePdM0SJiZmcHMLIeB7Aoi5r9GDakRcHwn4NVIM/AdY4xlEhERke2e806dOmHs2LE6y/799184OztDqVQiICAAISEhcHV1zTVfgxuALydGMiDNHNh3BZLeDUBNqoHiZJoeHU4eEAQJkBADyqG8FXGAN66P4aoo9SgMg7iWMjQevpreGI9vaaZ8bf8BUKO+5sEYY6xC0XujRr9+/RAVFYUZM2bg2bNn8PPzw759+8QBrx4+fKjTRWvFihVIS0tD7969dfIJCgpCcHBw0Qqh7amRGAccCAVsKnGjBmMsm2fPnuU4GF98fDySk5NhbGyMxo0bIzQ0FF5eXoiMjMTMmTPRokULXLlyBebm5jnma/AD8GmtWQOEzIVtXCpklnIkjRmI1y9eAHbVIBk0F2oTSyCHAZYr2gBvXB/D9jYOwGcQ11KGRhCAZr2ATfOA03uB5r0ApYm+S8UYY6wU6L1RAwBGjx6daxfJsLAwnef3798v+QK8itT8rVxDM7K/o1vJb4Mx9lbIfDtLnTp10LhxY7i5uWHz5s25dh8sNwPwOTgAW7YCt84CG+fC5OE5GBsPA8wd8lytog3wxvUxbBVhwLOi0Pu1lCHyagjYVQZePgHO7n8zrWtiPHDvElC7uX7LxxhjrEQYRKOG3mlvP6nfEajZSL9lYYwZLCcnpxwH47OwsICxsXGO61hZWcHT0xO3b9/ONd9yMwCfllcDwKUmhEc3IIRvA7oMf/NaWormVj6p7umlIg3wBnB9DFlFqAMrIRKJpiFj5w9AxC6g8buAWg0sHg5kpGl+xLJ30XcpGWOMFROf+Yne3H5iU0EG9mOMlYqAgAAcOnRIZ9nBgwezjUKdWUJCAu7cuYNKlSrQLW2CALQdqPn/7AEgNkrz/4FQYMEQ4N+zeisaY4zp8G0JmNsCCTHApX8AuQJwrwU4eQBJr/VdOsYYYyWAGzWSXwOpSZr/eSpCxt4qCQkJuHDhAi5cuABAM2XrhQsX8PDhQwCa20I+/PBDMf3IkSNx9+5dTJo0CTdu3MDy5cuxefNmjBs3TkwzYcIE/PPPP7h//z6OHz+Onj17QiqVYsCAAWVat1Ln4at5qDKAI1veLE9PAW5f0FuxGGNMh5EMCOim+T98u2b2k35TgJHfAm4++i0bY4yxEsGNGudPav6mZgDzBgHbVui3PIyxMnPmzBn4+/vD398fgGYGAX9/f8yYMQMAEBkZKTZwAICHhwd2796NgwcPom7duli0aBH+7//+T2c618ePH2PAgAHw8vJC3759YWtrixMnTsDe3r5sK1cW2vzXW+P8ISA6EmjYBRgaAnQdod9yMcZYZvU7AkpTIPopcOMUIHs7x11hjLGKisfUmP0V0KQSkKECFEbA6l+AXp/ou1SMsTLQunXrPOcIDw0NzXGd8+fP57rOxo0bS6Jo5YNrTaB6PeD2OeCfzUCvMYB13oOGMsZYmVMYAw07A0e3anpreDfR3EanVgNJ8YCZlb5LyBhjrBje7p4aKhWQHKv5/9YzYOFe4K/TmuWMMcbypx1b4/IRIOrRm+V5NBYxxliZa9wVMJIDT/4F7l8B7l0Gvh0GbF6g75Ixxhgrpre7UUMqBRIUwMaTwJl7QEoGUM1Ts5wxxlj+nKsBNRsDpAbCNmkaM47+Diz7DIh5nv/6jDFWFsysAP+2mv+PbQesnTSDh754AKQm67VojDHGiuftbtQAgPWbAak18DQW8PICtm3Td4kYY6x8aTMAgABcDQee39f8AvryCXDpiL5LxhhjbwR0BwQJcOc8kJwADJkDTFijuT2FMcb0JCEhAVWqVIEgCDhz5ozOa6tWrYKnpyeUSiXq1q2LP//8M9v6cXFxGDp0KGxsbGBubo7evXsjMjIyW7rjx48jICAAxsbGcHNzw/z58/O8Dbs84UYNLy9gzxZg1wpg80+a54wxxgrO0Q2o3Uzz/+GNQLMeQI/PgCbv6rVYjDGmw8YJqPVfrArfppn9xEim3zIxxt56s2fPRkZGRrblGzduxPDhw9GvXz/s3bsXAQEB6NmzJ06cOKGTrl+/fjhw4ABWrlyJ3377DTdv3kTnzp118rx9+zY6deqESpUq4c8//8TYsWMxY8YMLFq0qNTrVxa4UQMAHlwDzuwHbp7JPy1jjLHsWvfX/AJ685RmlgG/tvzrJ2PM8DTrqfl79Tjw6pl+y8IYe+vduHEDy5Ytw8yZM7O9FhQUhP79+2P27Nlo06YNVq5ciYYNG2LWrFlimoiICOzfvx+rVq1C37598b///Q9bt27FpUuXsC3THQgLFiyAra0tNm7ciHbt2mHcuHH44osvMGfOHKSmppZJXUsTN2oAmpb65r0Ar4b6LgljjJVPdpWBOq00//+9Qb9lYYyx3FTyAKr5a8YBitgJXD4KhH4FXDmq75Ixxt5Cn332GUaOHAmvLHcL3L17F7du3ULfvn11lvfv3x+HDh0SGyL27t0LKysrdOjQQUzj5eUFPz8/7NmzR1y2d+9e9OjRA3K5XCev2NhYRERElEbVyhQ3agCaRo32g4BaTfVdEsYYK79a9QUkUs396vcuA1fCga3fAqrsXSoZY0xvmvfS/D3/tzgbinCt/F/UM8bKl61bt+Ly5cuYMWNGttdu3LgBAKhZs6bOcm9vb6SlpeHevXtiOi8vLwiCkC2dNo/ExEQ8evQoW141a9aEIAhiuvLMSN8FYIwxVkHYOAH+7YCzBzRja0Q/BRJjgdrNAStXfZeOMcY03GsBlWtoGjTSU4FOQ0BejYA0fReMMVYUaWmaD69MJhO/3KtUKqhUKkgkEhgZGZV62sJKSkrC+PHjMXfuXFhYWGR7PSYmBgBgZWWls9za2hoA8OrVKzFd1jTadNo0sbGxOeYll8thYmIipivPuKdGeirw4pHml0S1Wt+lYYyx8q1lH0BqBDy8Bng1AFq8BzhwgwZjzIAIQqaxNcKBeh0AKwf9lokxVmQhISEICQlBUlKSuCw8PBwhISE6t2AAwMKFCxESEoK4uDhx2enTpxESEoI//vhDJ+2SJUsQEhKCqKgocdmFCxcQEhKCrVu3FqvMX3/9NRwdHTFkyJBi5cM0uFFj/w5g+efAwuFA/fpAeLi+S8QYY+WXpR3QoJPm/xcPgbbv85cFxpjhqdkYsK0MpCRqepcxxlgZefDgARYtWoSZM2ciLi4OsbGxSEhIAKCZ3jUhIUHskZG58QV404PDxsYGgKZHRtY02nTaNNoeGlnTpaWlISkpSUxXnr3dt5+o1cDy7wE/G+D2TeDCBWD0aODsWUDC7T2MMVYkzd8Dzh4EHt8C/j0HVPfXd4kYY0yXRKKZfvqPZcDxPwBbZ5hfPg50HwlIFPouHWOsEKZOnQpAc5uIVrNmzdCkSRNIsnynmzBhQra0DRs2RL169bKlHTNmTLa0fn5+8PX1zZa2MO7du4e0tDR07do122tt2rRB48aNsX79egBvxszQunHjBuRyOapWrQpAMy7GX3/9BSLSGVfjxo0b8PX1BQCYmprCxcUl29gZN2/eBBFlG2ujPHq7v7lLJMCXC4CQP4EtpzXLli3jBg3GGCsOc2ugURfN/4d+A57egcmVML0WiTHGsqnTCjC3ARJeQdj2HUyvhAH3rui7VIyxQpLL5ZDL5Tpf6qVSKeRyebZxL0orbWH4+fnh8OHDOo/FixcDAFauXInly5ejatWq8PT0xJYtW3TW3bRpE9q1ayfOYtK5c2fExMTg0KFDYppbt27h/Pnz6NKli7isc+fO2LlzJ9LT03XysrKyQtOm5X+yDO6pMWqU5v+0/0bnHzWKe2owxlhxNesJnNkHPL8Hyf9NggUAdf02gLWjvkvGGGMaRjKgSTfg4FpAIkGSdzMozct/N2zGmGGzsrJC69atc3ytfv36qFevHgAgODgY77//PqpVq4Y2bdpg06ZNOHnyJI4cOSKmDwgIQKdOnfDRRx9h0aJFUCqVmD59OurUqYNevXqJ6SZOnIjffvsNAwYMwKefforLly9jwYIFmDNnjs40r+XV2/3NXSIBfvgB8PPTjKXh56d5zg0ajDFWPKYWmi8LAEimRIqHP5DOUwswxgxM/Y6AwgRCcgJSXWsDjm76LhFjjAEABgwYgJ9//hnr169Hp06dEB4eju3btyMgIEAn3aZNm9ChQweMGDECAwcORI0aNbBnzx6d3iTVq1fHgQMH8PjxY3Tp0gULFy7EzJkz8cUXX5R1tUrF291TAwCaNXvTM4N7aDDGWMkJ6A6c2gMhJREpVf0ht6us7xIxxpgupQnQsDNw7HeYnt8PNOqg7xIxxt5CrVu3BhFlWz506FAMHTo0z3UtLS2xatUqrFq1Ks90TZs2xYkTJ4pVTkPF3+CBNw0Z3KDBGGMlx9gUaNodAGB25k9ArdJzgRhjLAdN3gVJZZC/uA9cPQ7c53E1GGOsPOFv8YwxxkpP43dBJhYwinsBnNkPPLyR/zqMMVaWzKwAvzYAAMm2b4Ht3wM5/GLKGGPMMHGjBmOMsdKjMAY16wkAEPatAjbNA1TcY4MxZlgooDvEZgwTCyD5tT6LwxhjrBC4UYMxxljpatAJKmNzCAAgNQJeR+u7RIwxpsvGCSnV6mv+t6usadhgjDFWLnCjBmOMsdIlUyCx/n9zpRMBppb6LQ9jjOUg0b+T5p8rx4CYF/otDGOMsQIziEaNZcuWwd3dHUqlEo0bN8apU6fyTL9lyxbUrFkTSqUSvr6+2LNnTxmVlDFWkRw5cgTdunWDs7MzBEHAjh078l0nLCwM9erVg0KhQPXq1REaGpotTWFjWmGp1Wqdv+VBknczkIUd8PoVcOaAvovDWIVjaNdS5TFOZdi5gKrWBUgNhG8HUpP1XSTGyq2cZvJgTKuk3x96b9TYtGkTxo8fj6CgIJw7dw5169ZFp06d8OJFzi3kx48fx4ABAzB06FCcP38ePXr0QI8ePXDlCo9UzRgrnMTERNStWxfLli0rUPp79+6ha9euaNOmDS5cuICxY8di2LBh2L9/v5imsDGtsMLDw1G/fn0cP34c9evXR3h4eInkW+qkMlDL3pr/j24FYp7rtzylQPvdrRx9h8tXkYc/KcTOyDNpRdyppcDQrqXCw8PRsmVLbNq0CR07dtSJUyoDH1NHOwYQzuwDjv1e/AwN8D1c7ENgCMewJPZrSR0bAzzG+iSTyQAASUlJei4JM2Ta94f2/VJcem/U+PbbbzF8+HAMGTIEPj4+WLlyJUxMTLB69eoc0y9ZsgTvvPMOJk6cCG9vb8yePRv16tXDDz/8UMYlZ4yVd507d8bXX3+Nnj17Fij9ypUr4eHhgUWLFsHb2xujR49G7969sXjxYjFNYWNaYajVaowePRqvXr3C999/DwsLC4wePVr8JfTcuXOIiIhAXFycuE5iYiLu37+f7ctNenp6oX5BVavVUKlUxfvVtW4bwMwaSIoH1gUDajXUas31cW7Z5rnd/FYuaNIcLtBz2y4RIUNNyMj8C4NajbDjqeg9KAX/HFOhfn0gPBxQqQkJaRlIzijYFwB1RgZUaWlQZ2QUvS6F2CdvVlGLD20eN6+pUMtbDSMjwMcHuHmzwNlpKl+/PnD0KMSdkcM2VSoVjh5V5560APkwDUO6llKr1Rg+fDiSk5Nx48YNODg4YPjw4eL7a9myZZgzZw6ePHkirvPo0SPs3LkTp0+f1snryZMniIyMRFpaWoG3Xew45V4bsLTX/H/5WPHiVCHew/l+dAsRp3LbQLE+1wBw8ybI2xswMtL8zSODUo1TmfYr1a8P1ZHwwrcnFCJOqfN6D3CcykYqlcLKygovXrxAdHQ0kpOTkZKSwg9+ICUlBcnJyYiOjsaLFy9gZWUFqVRaIu87oxLJpYjS0tJw9uxZTJ06VVwmkUjQvn17RERE5LhOREQExo8fr7OsU6dOBeo2zhhjxREREYH27dvrLOvUqRPGjh0LoGgxrTAkEgkmTpwoNqrI5XJ06tQJGf99CT5+/Diio6Nhb28PY2NjAJreJb///jsqV66MDz/8UMwrNDQUkZGR6NOnD6pXrw4AePz4MQ4cOAB7e3t069ZNTPvTTz/h4MGDOHPmDF6/fo0VK1agffv2uHTpEkxNTdGgQQMx7dWrVxEbGwtPT0/Y22u+GMTHx+PcuXOwtbVFfaULjBJiQK8i8WBwT1yp1gGmUgKS1bCsVhlO1ZWIi42FoMqALOohLl2/gRtxabCwtEQdP3+4GwswpnQgIQPpp88h1swMKgcnmLh7wNjZCVJBQEJiAlLS0iBVGEMplyPygRTHwlUwN4+FXWUjVHE1hYuDBEav45F47BiSlMZQuVeD0t4OVhZmuHPnDq5cuQL32nWhMDWDPD0FVV2qICkpEQmp6Ug2UsJIIMhMFcDde3h15Qoqe7lj4TtGuH9Ahr7+nrjxZzJsXsRBkRANSGUwc/MEALyKeQVpQgyMMlJgZOMEhaUtUlKS8eLqFdjJVTBKTYP04i289PGBvKY3pAnRMFanQWLtCKmFLf69nYI7N+Lgaf4c6ekKyKp5ws2dEBcfD6PIBzCNioQqKQOUDqT51kGKmSnM457CyMgIqU7VQYKApORkyF5HwzQ9CTGQ4+bLeJiamkICoAYSYJSWBpXUCpsmyPBKZgPj9HhI/o7B3cu2SLV2AqkJaWmpcIi8BqkgwWtXXwhGMqSkpEAR8wRWz+8hrX8bpO//HaqurZAUcRAOl/+EkQCkVG+Ih89faPaviRTV5Qr80KMSwlb5oLGpDH98LUHTgUcgZKQB2/8G1NHA4PeAu1HA8OHAlSuARO+/xxgUQ7uWkkgksLe3h7e3NxITE2Fra4uAgABs2bIFEokE8fHxUKlUOHLkCExMTCAIAqKjo/Hw4UPcv38f0dHRkEgkEAQB586dQ0pKCvz8/GBtbQ1BEPDq1Sv8+++/sLGxQa1atcS0R44cQUREBB49eoSMjAwMHz4cvr6+iI6OhlKphIODg1jGyMhIpKenw8HBAUqlEoDmV8NHjx7B0tIS3uQIV0Qh48VTXB0zGOTkAiOJFPdUVWDpbA472wxkxL+CXcJzpJCAvx/FIiMtDSampmhkbwxrIyDR1hXpV25C1b4Rkv/aBgztB/nF45DFPIQAIDklGSoiSJWmSHwtwdXzKgAqmJknw7WGMSwsFTAiFYTkZKTevYsMmRxSKxtIra1hJJfi1atXiIp6CRNLK5AgwMLEGBbm5khPT0cGESQyBQQivJAIQEIC0l7Hw0KdiL2fp+C54IA4tTlehKUBpxJgmfgSkEqRbGYHiToDqtRUmCa/glyVinSFGUgqA2WkQxIbDZMPG0NNTZCaJkC9cQHSHJ2gTEuEjDKQamqDdKU5YuLUiI1Jh6vsFdJIjlgbD9jaSfE6JQXmsc9hmhCDpCQgLTEN6V5eyDBRolLsQwhSKWIq1wagaZC3SngGi5Q4PDOywPHbj2FhYQmJWoW2ygRI+9THix3rgLYNEPPXH5BH/AU36UskO1RBoo0rMjIykJqUgOpPL0AiAE9rtABJpEhKToLtqwewe3kP8T0bIm7HOmR0bIKUf3bB83goBIkEkdUCEPkqFg/u34eHXAUPIRX3UjzxzyNfPL0nwwcDJAgwCdPcprT1oCZOfdgLuP+S49R/nJycAKDEeqmyisfKykp8n5QEgfR4w9PTp09RuXJlHD9+HAEBAeLySZMm4Z9//sHJkyezrSOXy7F27VoMGDBAXLZ8+XLMnDkTz59n786cmpqK1NRU8Xl8fDxcXFwQHR0NKyurkq2QHqjVakRFRcHe3h6SChBAuT6GLTY2Fra2toiLi4OFRcUaGV4QBGzfvh09evTINY2npyeGDBmi8+Vhz5496Nq1K5KSkhATE1PomAYUPE6p1WrY2dlh3LhxRa+onglE+BzXYIV0fReFlRN0Lwr0awTg7g78+2++6StynMpJWVxLAQWPU+np6Wjbti06duxYArXTD4EIo3ADtkjNPzFjAOjWM9CmUxynslCpVEhP5/M90yWTyUqsh4aWXntqlIWQkBDMnDkz2/KoqKgCd2c0ZGq1GnFxcSCiCvGlmetj2DLf1sBKTkHjlFqthre3d1kWrcSRIOB3ckdzPIdCqYTc1AKWSS8hzUhDvNIK6UYKAIAcKpgnvkSGYIQ4E1sAgCCRwiI5GkbpqXitsECaTNMbRSKTARCgVmWIfYMFiQSC1AgggjrjzQWVxMgIEASoM/cjFgQIEikAAmXu4q39zBJpHlqCoPscgEXyK8gy0vBaaSmWy0iVBsukV1BLpIgxtRfTmqfEQp6RggSFJVL/SytVZ8AqKRokSPAqc9rUeMjTk5GoMEeKzERTLFLBOuklAAEvTbRpCeZpiVBkJCFJZopEqTEAgkAEu5RXAIAXcivgv6JbqFNhnJGMJCMlXkMOAkEgwFH1GgDwXDCFWvivbhIVTFSpSJIo8BoyQAAECLBTJwIQEC0xAf23r0yQAaUqDWkSGZKkCvyXGJbpiRBAiJOZAoIUEATI1WlQpKUhVaJEosQCryKBtBSgQfVoCKSG6u4jgIB0tRIJ9f+bavPpU8Ao70sXjlOlozDXU5UqVcL58+chCAIEQYCFhQU+/PBDqNVqEJHOI/OyrK/n9Dw9PR2pqakQBAFyuVxcfu3aNUilUiQkJIi3Y/j4+OD169eQy+WwtHwz61JMTAwyMjJgaWkJuVwOQNNoExcXB7lMBqt793BCZgZfY0CwsISlVAUjdQYS5BZIlShgJCUIGWkwT3sNtSBBrMISIIIgCDBNS4BcnYEUpRnSSHPRrhYESIxkEAAQacpGagIEARKpFCoVQa1SAyAIUEMik0EiCCBVBpCeBjUEQCKBxEgGqFQgaHpLSQQJpHIFIAAZqSmQGRn9V3dBs5zUoPQ0UEoKVBIJrCkZMnUGYiUmeElWEIwIxkYqOKTHIl2qQKS5M1SCBGkZalRKj4FxRgqeW1TGa4Ul0gkwSk2Ge9ITqCRGeKSsBIBAcjmcEyNhmpaAWFN7pMhNkZ6qgjElwyEhEgQJoowdoTBSAxnpME+JhSI9GSkyE6RJFdBGUou0OAACXpvYaPaZWg3j9GTI1GlIkSiQIpVr3k+khnl6IgAg0cgUEASQIECuSodMnY50IznSjRSa94xaDRNViqZnjMxEk1athlSdAZlaBZUgQYbw3zECYEypEEhAiswYGSqV5j2mSodMlY40KJEkmCL6KZCeCjSoFgWBCKp7jzVxSjDhOJUDqVRa4l9eGcuJXhs17OzsIJVKs/0q8Pz581y7ozg5ORUq/dSpU3W6WGp/WbC3t68wPTUEQagwPQG4PoZNe/H3tsot/lhYWMDY2Fg8eRcmRgGFi1MJCQmYP38+1Go1JBIJPD09ceLEieJXLhdqtRrOzs5ISUkRlymVSjx9+rTA72m1Wo2XL1/CzsYGkipVgEx5JUMJOzwFQQKlUnMtKJFo1nHKZbsAYO7srJOPzso62wZyTdq0ieYXNZUKkEqBGjWgPn483/rmVR8jKOGKp3B1k+DiRc0yCQDbHPaL2X8PdUYG0uzsAADCf2lTAMhfvtQ0wgAwBWCcV13w5kUTACY57JM3ne/fHJeqzs5IS0uDn58fLl64gCdqNZQAHDMdH2c8haeXBBERgGkOhzxrvqhbF7IHD2Cqfe7mBu3OsMnyfkpPvwLA47+a6/7IKalRA7h/HzJtfdzdNXXMx9sWp8riWgooXJz6+uuv0bt3b1y/fh3e3t7YunUrPD09C1mzglOr1bC0tMz2uY2LiytUnIqKioK9rS0k1tbZ4pQF4sQ4FRf3Jk7ltl1jiQT47z0syuFXfLUasLTM/rnWbgN162rGrtDGKS8vqM+fz7e+2vo45FAfcyhRBXGo6S3BhQtvwmZOk21rl6kzMnDLxAR2/zXoOgK4IQjwTEoS45RVfvXBmxeNc6zsf5/1LMfFydISaWlpqFevHs6dO4dbajVcoYmfBOA+3OGCf7NmpSNbX4g8jo25znEVAMQBb0qssx2OU4wZCNKzRo0a0ejRo8XnKpWKKleuTCEhITmm79u3L7377rs6ywICAujjjz8u0Pbi4uIIAMXExBS5zIZEpVJRZGQkqVQqfRelRHB9DFtMTAwBoLi4OH0XpcQBoO3bt+eZZtKkSVS7dm2dZQMGDKBOnTqJzwsb03KSV5y6ceMG+fj4EADy8fGhGzduFDjfolq/fj0plUoCQEqlktavX1+o9XU+B+vXEymVRABlyJQ0yGg9AZpFWbPNc7uZ8slxZSpA0hs3iHx8NC/4+GieF6C+udUnRVBSf6wnb28xqwI7NmoUJf/XJyQZoGOjRhWuLoXcJ29WWU8mJibUsGFDMjEx0Ww3U32uz1hPfn5Ex44VojI3bhB5e2vKkcPOyLx/5XJfcnaOzTlpPvnkpiLHqdyU9bUUUcGupzIyMgqcX3EZZJwq4Hs4z49uKcSpIn2uiehAUBCdFwRqBtB5QaADQUGFr08JxKldCxeK+/UavMkTNwqa1RuFiFNGRoNIJsvI/fhwnGJM7/TeqLFx40ZSKBQUGhpK165doxEjRpCVlRU9e/aMiIgGDRpEU6ZMEdOHh4eTkZERLVy4kK5fv05BQUEkk8no8uXLBdoeN2oYNq6PYatoJ+HXr1/T+fPn6fz58wSAvv32Wzp//jw9ePCAiIimTJlCgwYNEtPfvXuXTExMaOLEiXT9+nVatmwZSaVS2rdvn5gmv5hWEIb2ZYFI817OyMgo0ns52+dApSLKyCBSqTL/W/jt5rdyQZPmsC/z2m5e9SnOYVGlp1NGaiqp0tPzTpdXXQqxT7TS09PpyZMnlK7d7n95qNJV4tMiyWNnZN2/ee63Qu7UihanCqKsr6WIDPN6yiDjFFGB3sP5fnRLKE4V93OtSk/XbFPfcYpIU5/CZ6WrgHGqKMcnL29jnGKsNOl9TI1+/fohKioKM2bMwLNnz+Dn54d9+/bB0VHT+fXhw4c6XQebNm2K9evX48svv8S0adNQo0YN7NixA7Vr19ZXFRhj5dSZM2fQpk0b8bm2a3VgYKA4O8jDhw/F1z08PLB7926MGzcOS5YsQZUqVfB///d/6NSpk5gmv5hWUsr6HtUSvX0qU1755ZrndgtRpjyT5rAvC1XfTGmLc1Qk+dyDncPmCvlibqtIxEfmPCTQeVp4ebxHs+7fPN/OfD92vvhaSsMg4xRQoPdwvkUvoThV3M+1wcQpAJBK8z02+SpEnCpqPoyx0qfX2U/0IT4+HpaWloiJiakwY2q8ePECDg4OFWLMBq6PYYuNjYW1tXWFH61b3zhOGTauj2HjOFU2OE4ZNq6PYeM4xVjJKv9RgTHGGGOMMcYYY28lbtRgjDHGGGOMMcZYuaT3MTXKmvZum/j4+ArRfU2tVuP169dQKpVcHwNU0eoTHx8P4M3niJUOjlOGjetj2DhOlQ2OU4aN62PYOE4xVrLeukaN6OhoAICbm5ueS8JY+RUdHQ1Ly5xmtGclgeMUY8XHcap0cZxirPg4TjFWMt66Rg0bGxsAmpHAK0IQiY+Ph4uLCx49elQhBhri+hi2uLg4uLq6ip8jVjo4Thk2ro9h4zhVNjhOGTauj2HjOMVYyXrrGjW0XdYsLS0rRFDUsrCw4PoYsIpWn4rQ9dOQcZwqH7g+ho3jVOniOFU+cH0MG8cpxkoGf5IYY4wxxhhjjDFWLnGjBmOMMcYYY4wxxsqlt65RQ6FQICgoCAqFQt9FKRFcH8PG9WFFUdH2M9fHsHF9WFFUtP3M9TFsXB/GWF4E4rmEGGOMMcYYY4wxVg69dT01GGOMMcYYY4wxVjFwowZjjDHGGGOMMcbKJW7UYIwxxhhjjDHGWLlUIRo1li1bBnd3dyiVSjRu3BinTp3KM/2WLVtQs2ZNKJVK+Pr6Ys+ePTqvExFmzJiBSpUqwdjYGO3bt8e///5bmlXQUZj6/Pzzz2jRogWsra1hbW2N9u3bZ0s/ePBgCIKg83jnnXdKuxqiwtQnNDQ0W1mVSqVOGn0en8LUpXXr1tnqIggCunbtKqbR57E5cuQIunXrBmdnZwiCgB07duS7TlhYGOrVqweFQoHq1asjNDQ0W5rCfh7fFhynOE5xnCo8jlNli+OU4capihSjAI5THKcYK2FUzm3cuJHkcjmtXr2arl69SsOHDycrKyt6/vx5junDw8NJKpXSN998Q9euXaMvv/ySZDIZXb58WUwzb948srS0pB07dtDFixfpf//7H3l4eFBycrLB1WfgwIG0bNkyOn/+PF2/fp0GDx5MlpaW9PjxYzFNYGAgvfPOOxQZGSk+Xr16Vep1KUp91qxZQxYWFjplffbsmU4afR2fwtYlOjpapx5XrlwhqVRKa9asEdPo89js2bOHpk+fTtu2bSMAtH379jzT3717l0xMTGj8+PF07do1Wrp0KUmlUtq3b5+YprD76G3BcYrjFMepouE4VXY4ThlunKpIMaoo9eE4xXGKsfyU+0aNRo0a0ahRo8TnKpWKnJ2dKSQkJMf0ffv2pa5du+osa9y4MX388cdERKRWq8nJyYkWLFggvh4bG0sKhYI2bNhQCjXQVdj6ZJWRkUHm5ua0du1acVlgYCB17969pItaIIWtz5o1a8jS0jLX/PR5fIp7bBYvXkzm5uaUkJAgLtPnscmsICfhSZMmUa1atXSW9evXjzp16iQ+L+4+qqg4TuniOFV6OE5xnCoqjlO6DClOVaQYRcRxiuMUYyWvXN9+kpaWhrNnz6J9+/biMolEgvbt2yMiIiLHdSIiInTSA0CnTp3E9Pfu3cOzZ8900lhaWqJx48a55llSilKfrJKSkpCeng4bGxud5WFhYXBwcICXlxc++eQTREdHl2jZc1LU+iQkJMDNzQ0uLi7o3r07rl69Kr6mr+NTEsdm1apV6N+/P0xNTXWW6+PYFEV+n52S2EcVEcep7DhOlQ6OUxyniorjVHaGEqcqUowCOE4BHKcYKw3lulHj5cuXUKlUcHR01Fnu6OiIZ8+e5bjOs2fP8kyv/VuYPEtKUeqT1eTJk+Hs7KwTCN955x2sW7cOhw4dwvz58/HPP/+gc+fOUKlUJVr+rIpSHy8vL6xevRo7d+7Er7/+CrVajaZNm+Lx48cA9Hd8intsTp06hStXrmDYsGE6y/V1bIoit89OfHw8kpOTS+T9WxFxnMqO41Tp4DjFcaqoOE5lZyhxqiLFKIDjFMBxirHSYKTvArCSM2/ePGzcuBFhYWE6A0L1799f/N/X1xd16tRBtWrVEBYWhnbt2umjqLkKCAhAQECA+Lxp06bw9vbGjz/+iNmzZ+uxZMWzatUq+Pr6olGjRjrLy9OxYawkcJwyXBynGNMo73GqosYogOMUYyxn5bqnhp2dHaRSKZ4/f66z/Pnz53BycspxHScnpzzTa/8WJs+SUpT6aC1cuBDz5s3DgQMHUKdOnTzTVq1aFXZ2drh9+3axy5yX4tRHSyaTwd/fXyyrvo5PceqSmJiIjRs3YujQoflup6yOTVHk9tmxsLCAsbFxiRzviojj1BscpzhOlTaOU0XDceoNQ4tTFSlGARynAI5TjJWGct2oIZfLUb9+fRw6dEhcplarcejQIZ0W6swCAgJ00gPAwYMHxfQeHh5wcnLSSRMfH4+TJ0/mmmdJKUp9AOCbb77B7NmzsW/fPjRo0CDf7Tx+/BjR0dGoVKlSiZQ7N0WtT2YqlQqXL18Wy6qv41OcumzZsgWpqan44IMP8t1OWR2bosjvs1MSx7si4jilwXGK41RZ4DhVNBynNAwxTlWkGAVwnAI4TjFWKvQ9Umlxbdy4kRQKBYWGhtK1a9doxIgRZGVlJU5dNWjQIJoyZYqYPjw8nIyMjGjhwoV0/fp1CgoKynEKMisrK9q5cyddunSJunfvXqbTXBWmPvPmzSO5XE5bt27Vmcbq9evXRET0+vVrmjBhAkVERNC9e/for7/+onr16lGNGjUoJSXF4Oozc+ZM2r9/P925c4fOnj1L/fv3J6VSSVevXtWpsz6OT2HrotW8eXPq169ftuX6PjavX7+m8+fP0/nz5wkAffvtt3T+/Hl68OABERFNmTKFBg0aJKbXTkE2ceJEun79Oi1btizHKcjy2kdvK45THKc4ThUNx6myw3HKcONURYpRRamPFscpjlOM5abcN2oQES1dupRcXV1JLpdTo0aN6MSJE+JrrVq1osDAQJ30mzdvJk9PT5LL5VSrVi3avXu3zutqtZq++uorcnR0JIVCQe3ataObN2+WRVWIqHD1cXNzIwDZHkFBQURElJSURB07diR7e3uSyWTk5uZGw4cPL9OgWJj6jB07Vkzr6OhIXbp0oXPnzunkp8/jU9j32o0bNwgAHThwIFte+j42hw8fzvG9o61DYGAgtWrVKts6fn5+JJfLqWrVqjpzxGvltY/eZhynOE5xnCo8jlNli+OU4capihSjiDhOcZxirGQJRESl2xeEMcYYY4wxxhhjrOSV6zE1GGOMMcYYY4wx9vbiRg3GGGOMMcYYY4yVS9yowRhjjDHGGGOMsXKJGzUYY4wxxhhjjDFWLnGjBmOMMcYYY4wxxsolbtRgjDHGGGOMMcZYucSNGowxxhhjjDHGGCuXuFGDMcYYY4wxxhhj5RI3ahSCIAjYsWMHAOD+/fsQBAEXLlzQa5neBsHBwfDz8yvSuoMGDcLcuXNLtkBlrKzfd4MHD0aPHj3E5/3798eiRYtKbXusZHGc0g+OUxynWMFxnNIPjlMcpxirqN7KRo3BgwdDEIRsj3feeafAebi4uCAyMhK1a9cGAISFhUEQBMTGxua5XkHTGYrM+8fU1BQ1atTA4MGDcfbs2VLbnvaEU1wXL17Enj178Pnnn5dIfoYg6/uuLHz55ZeYM2cO4uLiymybjONUYXCcMiwcp94eHKcKjuOUYeE4xVjF8lY2agDAO++8g8jISJ3Hhg0bCry+VCqFk5MTjIyMSrGUZYOIkJGRkevra9asQWRkJK5evYply5YhISEBjRs3xrp168qwlIW3dOlS9OnTB2ZmZqW6nbS0tFLNPzN9vO9q166NatWq4ddffy2zbTINjlNvcJwqHo5TrLRwnHqD41TxcJxijBXVW9uooVAo4OTkpPOwtrYWX//333/RsmVLKJVK+Pj44ODBgzrrZ+62dv/+fbRp0wYAYG1tDUEQMHjw4CKV6/Tp0+jQoQPs7OxgaWmJVq1a4dy5c+LrH330Ed59912dddLT0+Hg4IBVq1YBANRqNUJCQuDh4QFjY2PUrVsXW7duFdNrf93Yu3cv6tevD4VCgWPHjuVaJisrKzg5OcHd3R0dO3bE1q1b8f7772P06NGIiYkR0x07dgwtWrSAsbExXFxc8PnnnyMxMVF83d3dHbNnz8aAAQNgamqKypUrY9myZTqvA0DPnj0hCIL4XOuXX36Bu7s7LC0t0b9/f7x+/TrXMqtUKmzduhXdunXTWe7u7o65c+fio48+grm5OVxdXfHTTz/ppLl8+TLatm0LY2Nj2NraYsSIEUhISBBf13YnnDNnDpydneHl5SW+HzZv3izug4YNG+LWrVs4ffo0GjRoADMzM3Tu3BlRUVFiXvkd76yydpeMiYnB+++/D3t7exgbG6NGjRpYs2aNmP7Ro0fo27cvrKysYGNjg+7du+P+/fs6+2n8+PGwsrKCra0tJk2aBCLKtt1u3bph48aNuZaLlQ6OUxynOE5xnDJ0HKc4TnGc4jjFmN7RWygwMJC6d++e6+sqlYpq165N7dq1owsXLtA///xD/v7+BIC2b99ORET37t0jAHT+/HnKyMig33//nQDQzZs3KTIykmJjY3PM+/DhwwSAYmJicnz90KFD9Msvv9D169fp2rVrNHToUHJ0dKT4+HgiIgoPDyepVEpPnz4V19m2bRuZmprS69eviYjo66+/ppo1a9K+ffvozp07tGbNGlIoFBQWFqZThjp16tCBAwfo9u3bFB0dnWN5Mtc5s/PnzxMA2rRpExER3b59m0xNTWnx4sV069YtCg8PJ39/fxo8eLC4jpubG5mbm1NISAjdvHmTvv/+e5JKpXTgwAEiInrx4gUBoDVr1lBkZCS9ePGCiIiCgoLIzMyMevXqRZcvX6YjR46Qk5MTTZs2LccyExGdO3eOANCzZ890lru5uZGNjQ0tW7aM/v33XwoJCSGJREI3btwgIqKEhASqVKmSuK1Dhw6Rh4cHBQYGinkEBgaSmZkZDRo0iK5cuUJXrlwR3w/a/X7t2jVq0qQJ1a9fn1q3bk3Hjh2jc+fOUfXq1WnkyJEFPt5Zj0Hm9x0R0ahRo8jPz49Onz5N9+7do4MHD9Iff/xBRERpaWnk7e1NH330EV26dImuXbtGAwcOJC8vL0pNTSUiovnz55O1tTX9/vvv4vbNzc2zfT727t1LcrmcUlJSct3nrGRxnOI4xXGK45Sh4zjFcYrjFMcpxgzBW9uoIZVKydTUVOcxZ84cIiLav38/GRkZ0ZMnT8R19u7dm2cwzO/kqlXQdFoqlYrMzc1p165d4jIfHx+aP3+++Lxbt27iyS4lJYVMTEzo+PHjOvkMHTqUBgwYoFOGHTt25Lv93E7CycnJBEAsx9ChQ2nEiBE6aY4ePUoSiYSSk5OJSHMCfOedd3TS9OvXjzp37pzn9oKCgsjExETnxDRx4kRq3LhxruXevn07SaVSUqvVOsvd3Nzogw8+EJ+r1WpycHCgFStWEBHRTz/9RNbW1pSQkCCm2b17N0kkEvGEHhgYSI6OjuKJjOjN++H//u//xGUbNmwgAHTo0CFxWUhICHl5eeVa7pyOd17vu27dutGQIUNyzOuXX34hLy8vnX2QmppKxsbGtH//fiIiqlSpEn3zzTfi6+np6VSlSpVsJ+GLFy8SALp//36uZWcli+MUxyktjlMcpwwVxymOU1ocpzhOMaZP5f8GxiJq06YNVqxYobPMxsYGAHD9+nW4uLjA2dlZfC0gIKBMyvX8+XN8+eWXCAsLw4sXL6BSqZCUlISHDx+KaYYNG4affvoJkyZNwvPnz7F37178/fffAIDbt28jKSkJHTp00Mk3LS0N/v7+OssaNGhQ5HLSf13qBEEAoBlE6tKlS/jtt9900qjVaty7dw/e3t4Asu/HgIAAfPfdd/luz93dHebm5uLzSpUq4cWLF7mmT05OhkKhEMuXWZ06dcT/BUGAk5OTmNf169dRt25dmJqaimmaNWsGtVqNmzdvwtHREQDg6+sLuVyeZ96Z02ZelrncBTneefnkk0/w3nvv4dy5c+jYsSN69OiBpk2bAtAck9u3b+vsNwBISUnBnTt3EBcXh8jISDRu3Fh8zcjICA0aNMjWZdLY2BgAkJSUVKBysZLBcYrjlLb8HKc4ThkqjlMcp7Tl5zjFcYoxfXlrGzVMTU1RvXp1fRcjm8DAQERHR2PJkiVwc3ODQqFAQECAzuBJH374IaZMmYKIiAgcP34cHh4eaNGiBQCI9yru3r0blStX1slboVDoPM98oims69evAwA8PDzE7X788cc5jozt6upa5O1oyWQyneeCIECtVuea3s7ODklJSUhLS8t2sixsXjnJbd9lzlt7AZB1WeZtFeR456Vz58548OAB9uzZg4MHD6Jdu3YYNWoUFi5ciISEBNSvX1/nwkjL3t6+QPlrvXr1qkjrseLhOMVxqqB55YTjFCsLHKc4ThU0r5xwnGKMlYS3tlEjL97e3nj06BEiIyNRqVIlAMCJEyfyXEcb6FUqVbG2HR4ejuXLl6NLly4ANAMTvXz5UieNra0tevTogTVr1iAiIgJDhgwRX/Px8YFCocDDhw/RqlWrYpUlL9999x0sLCzQvn17AEC9evVw7dq1fC9ssu7HEydOiL86AJoTVnH3IQBxHvZr164Vak52b29vhIaGIjExUTzRhoeHQyKRwMvLq9jlyqogxzs/9vb2CAwMRGBgIFq0aIGJEydi4cKFqFevHjZt2gQHBwdYWFjkuG6lSpVw8uRJtGzZEgCQkZGBs2fPol69ejrprly5gipVqsDOzq4ItWSlgeNU/jhOlQyOU6yoOE7lj+NUyeA4xdjb7a2d/SQ1NRXPnj3TeWiDX/v27eHp6YnAwEBcvHgRR48exfTp0/PMz83NDYIg4M8//0RUVJTO6M45uXz5Mi5cuCA+Ll68CACoUaMGfvnlF1y/fh0nT57E+++/L3ZVy2zYsGFYu3Ytrl+/jsDAQHG5ubk5JkyYgHHjxmHt2rW4c+cOzp07h6VLl2Lt2rWF3U0AgNjYWDx79gwPHjzAwYMH0bt3b6xfvx4rVqyAlZUVAGDy5Mk4fvw4Ro8ejQsXLuDff//Fzp07MXr0aJ28wsPD8c033+DWrVtYtmwZtmzZgjFjxoivu7u749ChQ3j27JnOSOCFZW9vj3r16uU5CnlO3n//fSiVSgQGBuLKlSs4fPgwPvvsMwwaNEjs/liSCnq8czNjxgzs3LkTt2/fxtWrV/Hnn3+KFzXvv/8+7Ozs0L17dxw9ehT37t1DWFgYPv/8czx+/BgAMGbMGMybNw87duzAjRs38OmnnyI2Njbbdo4ePYqOHTuWSJ1ZwXGcKjiOUxynOE7pB8epguM4xXGK4xRjpURvo3noUWBgIAHI9sg84NDNmzepefPmJJfLydPTk/bt25fnAENERLNmzSInJycSBEFndOfMtINKZX1IpVIi0owy3aBBA1IqlVSjRg3asmULubm50eLFi3XyUavV5ObmRl26dMm2DbVaTd999x15eXmRTCYje3t76tSpE/3zzz86ZSjI4FqZy6hUKqlatWoUGBhIZ8+ezZb21KlT1KFDBzIzMyNTU1OqU6eOOFgYkWZQqZkzZ1KfPn3IxMSEnJycaMmSJTp5/PHHH1S9enUyMjIiNzc3ItIMbFW3bl2ddIsXLxZfz83y5cupSZMmOsty2pd169aloKAg8fmlS5eoTZs2pFQqycbGhoYPHy6OhE6U82jvOb0fctrPa9asIUtLS/F5QY53Xu+72bNnk7e3NxkbG5ONjQ11796d7t69K64bGRlJH374IdnZ2ZFCoaCqVavS8OHDKS4ujog0A1mNGTOGLCwsyMrKisaPH08ffvihTv2Sk5PJ0tKSIiIict7RrFRwnOI4lRnHKY5ThojjFMepzDhOcZxiTF8EohwmUWYGLyEhAZUrV8aaNWvQq1cvfRenQNzd3TF27FiMHTu2TLaXnJwMLy8vbNq0qcwGJquIVqxYge3bt+PAgQP6LgorZzhO5Y/jVMngOMWKiuNU/jhOlQyOU4yVHh5To5xRq9V4+fIlFi1aBCsrK/zvf//Td5EMlrGxMdatW1foeyqZLplMhqVLl+q7GKwc4ThVcBynSgbHKVZYHKcKjuNUyeA4xVjp4UaNcubhw4fw8PBAlSpVEBoaCiMjPoR5ad26tb6LUO4NGzZM30Vg5QzHqcLhOFV8HKdYYXGcKhyOU8XHcYqx0sO3nzDGGGOMMcYYY6xcemtnP2GMMcYYY4wxxlj5xo0ajDHGGGOMMcYYK5e4UYMxxhhjjDHGGGPlEjdqMMYYY4wxxhhjrFziRg3GGGOMMcYYY4yVS9yowRhjjDHGGGOMsXKJGzUYY4wxxhhjjDFWLnGjBmOMMcYYY4wxxsolbtRgjDHGGGOMMcZYucSNGowxxhhjjDHGGCuXuFGDMcYYY4wxxhhj5RI3ajDGGGOMMcYYY6xc4kYNxhhjjDHGGGOMlUvcqMEYY4wxxhhjjLFy6a1q1AgODoYgCBAEARKJBJaWlvD19cXo0aNx/fr1IuV54cIFBAcHIykpqYRLWzb5ZzZ48GBx/2R+vPvuuwXOQxAELFy4sBRLqREWFqZTRnNzc/j7+2P16tUgohLfzpkzZ8RlwcHBOH78eLa0ZVX3zOXSPkxNTeHr64slS5ZApVIVOr/Q0FCsX7++FEpa/mSOE4IgwN7eHm3btsXRo0dLdbs5ffYEQYBSqcx3XSsrKwQHB4vPW7durfO5DQsLw9y5cwtUDo6TeeM4mft2OE6WvdziRuZHaGhojsfobfLXX3+hf//+cHd3h4mJCXx8fLBgwQKkp6fnuV7Lli3RrFmzbMvr168PQRBw7949neWLFy+GIAh48eJFiZY/J7l9xnITFRWFL774Ap6enlAqlbCwsECrVq2watWqIn0eSkPW+FqpUiV069YNly9fLrVt3r9/P9fPTs2aNfNcNzY2VvyMabm7u2P06NHi8x07dmD58uUFKktBzi/u7u7iciMjI1StWhWffPIJXr58mWs+jo6O6NixIyIiIgq4Vxgrf4z0XYCyZmxsjL///hsA8Pr1a1y+fBk//fQTfv75Z6xatQoffPBBofK7cOECZs6cidGjR8PExKTEy1va+WdVtWpV/PbbbzrLrK2tS327RbVmzRrUrFkTsbGxWLVqFYYOHYr09HR8/PHHJZJ/vXr1EBERAW9vb3HZzJkzYWZmhqZNm+qkjYiIgJubW4lst6C09Y+Li8PatWsxduxYJCcnY8qUKYXKJzQ0FGZmZhg4cGAplbR8yRwnHj9+jNmzZ6Ndu3Y4d+4cateuXWrb/eyzz7IdA4mk8G3Py5cvh1QqFZ+HhYVh4cKFmDZtWoHW5ziZN46TujhO6k/WLykBAQHZ4ki1atVw9erVsi6aQfnxxx+RlJSEWbNmwdXVFSdOnEBQUBCuXbuGNWvW5Lpes2bNsHjxYqSmpkKhUAAAEhIScPHiRZiYmOD48ePw8PAQ04eHh6NGjRpwcHAo9Trl9hnLye3bt9GmTRuoVCqMHz8e9evXR2pqKv7++2+MGzcOdnZ26N69e6mXuSC08ZWIcPv2bcyYMQOtWrXCtWvX4OTkVGrbnTt3Ltq0aaOzzNjYuND5bN++Xed8sGPHDpw5cwaffvppgdYvyPmld+/e+OKLL5Ceno4TJ04gODgYly9fxpEjR8Rrhsz78e7duwgKCkL79u1x+fJlVK1atdD1YszQvXWNGhKJBE2aNBGfd+jQAZ9++im6du2KoUOHomnTphX6w56cnJxnkDY2NtbZP4audu3aaNCgAQDNsfT29sbSpUtL7GLdwsKiwPtDH/sta/3Pnz+PNWvWFPpinenKGicaNWoEd3d3rFy5Ej/88EOR883v8+fq6loi7yMfH59irc9xkuNkYXCc1J+c9mdJxZGSplKpoFarIZPJynzbK1asgJ2dnfi8devWUKvV+PLLL7FgwQKd1zJr3rw55s2bh7Nnz4qNBydPnoSJiQl69OiB8PBwvP/++2L68PBwdO7cuVhlzS/+FMX777+PjIwMnDlzBpUrVxaXv/POOxg9ejTi4uJKdHvFkTm+BgQEwN3dHS1btsSvv/6KCRMmFDnf/PZrjRo1SuRz4+/vX6z1C3J+cXR0FNO0aNECKSkpmDFjBs6dOyfGuqz70cPDA82aNcOmTZswderUYpWRMUP0Vt1+khulUomlS5ciLS0N//d//6fzWmhoKOrUqQOlUonKlStj+vTpYje90NBQDBkyBABgb28PQRDg7u4urvv48WN88MEHsLOzg7GxMVq2bImzZ89m2/66devg7+8PpVIJOzs7dOnSBQ8ePMg3/8uXL6NTp04wNTWFpaUlevfujYcPH+rkLQgC5s2bh8mTJ8PJyanIvx5ERkbio48+QtWqVWFsbIwaNWpg2rRpSE1NzXO98PBwtGzZEpaWljA3N4evry/Wrl2rk2b37t1o3LgxjI2NYW9vj08++QSJiYmFLqNUKoW/v79Od9Bt27bBz88PSqUSzs7OGD9+PFJSUsTX09PTMXHiRLi6ukKhUIhdHbUn+KxddgVBAABMnDhR7NYXFhYmvqbtVh0cHAwbG5tsXVuvXLkCQRCwf//+Eq+/RCJBnTp1sr0HpkyZAl9fX5iZmaFy5coYMGAAIiMjxddbt26Nf/75B7t37xbrlPlWhpIqX3nm6uoKe3t7nfdWXrFB+7ogCIiIiECHDh1gamqKiRMnFrssO3fuRM2aNaFUKtGoUSOcPn06W5rMt58EBwdj5syZSExMFI9v69atC71djpP54zjJcdLQ42RMTAwGDhwIc3NzuLm54ZtvvsmWJiIiAm3bthU/MwMHDsx2O8WrV6/w0UcfiZ/bpk2b4siRIzpptHFo7dq18PLygkKhwMWLFwHkv7+076n9+/ejb9++MDMzg6urq3j7z/fffw9XV1fY2Nhg2LBh+X7Gcmq08Pf3BxHpHOesmjZtCkEQEB4eLi4LDw9Ho0aN0Lx5c53ld+/exbNnz3RuV/nxxx/Furu7u+Prr7+GWq0WX8/rPLF69WrUqlULxsbGsLW1RfPmzcV4n9dnLKujR4/i1KlTmDZtmk6Dhparqyt8fX0BADdu3ED//v3h4uIi3qazaNEinTIDwLx581C9enUolUrY29ujffv2OjElNTUV06ZNg5ubGxQKBby9vYt865b2S7o2fyLCwoUL4enpCYVCgapVq2Lx4sU66wQHB8PMzAynTp1CQEAAlEolli1bVqTtZ/bzzz+LtzC1a9cOt2/fzpYm8+0ngwcPxtq1a3H16lXxOA0ePLjY5cgq6z7KibaxJWvsY6yi4EaN//j4+KBy5co6XTm//fZbDBs2DJ06dcKuXbswefJkfP/995g+fToAoGvXrvjyyy8BAPv27UNERAS2b98OQHPh0Lx5c1y4cAFLly7F77//DlNTU7Rt21bn4mDBggUIDAxE/fr1sW3bNqxatQo1atRAVFRUnvk/evQILVu2RHR0NH799VesXLkS586dQ6tWrfD69Wudui1ZsgS3bt3CqlWr8Ouvv+a7LzIyMnQeAPDy5UvY2Njg22+/xb59+zBp0iSsXbsWI0eOzDWf+Ph4dO3aFRYWFtiwYQN27NiBESNGIDY2VkyzdetW/O9//4Ovry+2b9+Ob775Btu2bcPQoUPzLWdO7t27B2dnZwDAH3/8gd69e8PHxwc7duzApEmTsHLlSp2u8yEhIVi5ciWmTJmCAwcO4IcffoCzs3OuF0ja98dnn32GiIgIREREoF69etnSDRgwADExMToX5QCwYcMGODg4oH379qVS/wcPHuh0hQWAFy9eYNq0adi9ezeWLFmC+/fvo1WrVuKxXb58Ofz9/dGsWTOxTsOGDSuV8pVX8fHxiI6OFt9b+cWGzAYOHIi2bdvizz//xKBBg/Lcjlqtzvb5y3wxeeHCBbz33nuoUaMGtm3bhsDAQPTt2zfPC/phw4Zh6NChMDY2Fo9vQe/vzYrj5BscJzlOlsc4OXLkSHh6emL79u3o1q0bJk+ejH379omvR0REoHXr1rC0tMSmTZvw008/4fTp0zq3JqhUKnTu3Bm7du3C/PnzsWXLFpiZmaFDhw7ZGiTPnDmDBQsWYNasWdizZw9cXFwKtb8++eQT1K5dG9u3b0eTJk0waNAgTJ48Gfv378fKlSsxa9YsrFu3DosWLSr0vjh27BgUCkW290Jm1tbW8PHxydao0bRpUzRt2hRXrlxBfHy8uBzQ9O4AgKVLl2LkyJFibBw8eDCCg4MxadKkbNvJep44cuQIhg4dii5dumDPnj1Yt24d2rVrJ8aFgn7GAOCff/4BoOmVkZ8nT57Ay8sLy5cvx549ezBixAjMmjULs2fPFtOsW7cOX331FYYOHYp9+/bh//7v/+Dn5yfuBwDo27cvfvzxR3zxxRf4888/8c477+CDDz7A3r178y1DVtov6tqYNWbMGMyYMQOBgYHYvXs3Bg8ejMmTJ2PlypU666WlpWHgwIHidjt27JjndvI7//75558YMWIE2rRpg+3bt6Ndu3bo06dPnnl+9dVX6NKlC6pWrSoep6+++irfOud0fslL1n2UkwcPHgBAnu93xso1eosEBQWRqalprq83adKEatasSURE8fHxZGZmRlOnTtVJs2LFCjI2NqaXL18SEdGaNWsIAEVFRemkmzFjBllaWtLz58/FZSkpKeTq6koTJ04kIqLY2FgyMTGhESNG5Fqm3PIfN24cmZqaUnR0tLjs+vXrJAgCff/99+IyAOTj40NqtTrXbWgFBgYSgGyPo0ePZkubnp5Ov/32GxkZGVFiYqLO9hYsWEBERKdPnyYAdOnSpRy3p1aryc3NjQYMGKCzfO/evSQIAl25ciXXsh4+fJgA0IkTJyg9PZ1evnxJc+bMIQDiMfP396eAgACd9X788UedMnXt2pV69eqV73ZOnz6dYx0zy7rc39+fBg4cqJOmatWqNGrUqFKp/4IFC0gQBNq4cWOu62VkZNDjx48JAO3fv19c3qpVK+ratatO2uKUrzzTxon09HRKT0+ne/fuUa9evQgA7du3r9CxYd68eQXabk6fPQDUrl07MU2/fv3Iw8ODMjIyxGWrVq0iABQUFCQuy3o884t9OdU/NxwnOU7mth2Ok4UrX2nIbb9r94X2c0WkKbu7uzsNHTpUXNayZUtq2rSpzmfh6tWrJAgC7d69m4iIdu7cKcZDrbS0NHJ1ddV5n7Rq1YpkMhk9fPhQZ5sF2V/a8k6aNElMExsbS1KplFxcXCgtLU1c/t5775Gfn1/BdxIR3bp1i0xNTWnMmDH5pv3444/JwcGBiIhUKhVZWlrS3r17Sa1Wk6WlpfgeGTlyJNnb2xOR5j1kZ2dH/fv318lr6tSpJJfL8z1PLFiwgGxsbPIsV27HOquRI0cSAEpJSck3bWZqtZrS09Npzpw5VKlSJXH5qFGjqF69ermu9/fff2f77BBpzl8NGzbMc5uBgYFUq1YtSk9Pp7S0NLp+/Tq1aNGCZDIZXb58mW7fvk2CINCPP/6os97kyZPJycmJVCoVEWnOYwDy/Jxr3bt3L9fzb+bPRuPGjalFixY663711VcEgNasWSMuc3NzE+NX5joVREHOL25ubvTpp59Seno6JSUl0eHDh8nZ2ZmqVq1KSUlJOe7HmzdvUps2bcjNzY1evHhRoLIwVt5wT41MiEjs0nf8+HEkJCSgT58+Oq2l7du3R3JyMq5cuZJnXgcOHECbNm1gY2MjriuVStGqVSux+2BERASSkpKK9GvO0aNH0bZtW9jY2IjLatasibp16+LYsWM6aTt37izWKz/VqlXD6dOndR5+fn4gInz33Xfw8fGBsbExZDKZeI/m3bt3c83LwsICn3zyCTZv3oyoqCid12/duoUHDx6gb9++Ovu4VatWkEgkBRqlvUmTJpDJZLCzs0NQUBBGjhyJGTNmICEhARcuXEDv3r110vfr1w8AxH1Ur1497NmzB8HBwTh9+nS2LpbFMWDAAPzxxx9ITk4GAJw6dQp3797FgAEDSqX+EydOxOTJk8U6au3duxdNmzaFpaUljIyMUKVKFXH7eSmJ8pVXiYmJkMlkkMlk8PDwwOHDh/HDDz+gU6dOhY4NXbt2LfB2x4wZk+3zl7lXxcmTJ9GtWzedQUCzvsdLG8dJjpMcJ98ob3Ey86/VgiDA29sbjx8/BgAkJSUhPDwcffr0gUqlEuvi6ekJFxcX8TN59OhRWFhYoFOnTmJeMpkMvXr1yva5qlOnDlxcXMTnhd1fHTp0EP+3tLSEg4MDWrZsqTMuh6enJx49elTgfRAfH49evXrBw8MDc+bMyTd98+bN8eLFC/z7779iz4yAgAAIgoDGjRuLPTS0PTgAzW0cL1++zPZLfr9+/ZCWloZTp07pLM96nqhXrx5evXqFwYMH4+DBgyUys1NB4ltKSgqCgoJQvXp1KBQKyGQyTJ8+HZGRkUhISBDLdv78eYwfPx7Hjh3LdvvYgQMHYGNjg7Zt2+ocY+14NvnNtHL16lXIZDLI5XJ4e3vjzp07+O2331C7dm389ddfAID33nsv2znn2bNn2d4HhTn/zp8/P1tc1/aqUKlUOHv2LHr27KmzTmmcf3M7v2S2fPlyyGQymJiYoE2bNqhcuTJ+//13nTFDMu9HLy8vnDx5Etu2bYO9vX2Jl5kxQ/DWDRSal8ePH8PT0xMAxKmRcuvOl98J9OXLlzhx4kSOA2JVq1YNABAdHQ0g7+5iuYmJickW5ADN4EGvXr3KtqyglEqleG9eZosXL8aECRMwadIktGnTBtbW1jh9+jRGjRqlc+91ZtbW1jh48CCCgoIwaNAgZGRkoEWLFli6dCl8fX3FfZz1JKFVkIuUdevWwdvbGxYWFnB3d4dcLgegOZZElK3ulpaWUCgU4j6aPn06JBIJ1q5di5kzZ8Le3h6jRo3CjBkzCvwFJzf9+/fH5MmTsWvXLvTt2xcbNmyAm5ubeNFTkvV/8eIFQkJCMH/+fLRq1UrsZnr69Gn873//Q/fu3TFlyhQ4ODhAEAQ0adIk1+OmVRLlK6+MjY1x5MgRCIIAOzs7uLi4iCOKFzY2FObzV6VKlRw/f1qRkZHZxnuwsLAo0LSvJYXjJMdJjpNvlLc4aWVlpfNcLpeLtzTExMRApVJh3LhxGDduXLZ1tXWJiYnJcdyZgnyuCru/cipvTsvyO05aaWlp6NmzJ2JiYhAREQFTU9N819GOkREeHo7k5GT4+PjA0tISgGbMjaNHjyIuLg5Xr17Fhx9+CECzj4Ds9dc+z28/tW3bFr/88guWLFmCTp06QalUonfv3vjuu+90GmkLQjuOxsOHD1G9evU8006ePBk///wzgoKCUL9+fVhZWWHnzp34+uuvkZKSAjMzMwwePBivX7/GTz/9hMWLF8PS0hKBgYGYN28ejI2N8fLlS7x69SrXAWEjIyPFRsOcVKtWDRs3bhSndK1UqZIYZ16+fAkiynVg10ePHomzK5mYmMDMzCzf/aNVtWrVXM+/UVFRyMjIyPa+L8x5o6ByO79k1rdvX0ycOBEymQwuLi45vie0+1GlUuHixYuYNGkS+vbti0uXLpXJLGGMlTVu1PjP1atX8eTJE3EAH22A2LZtm86vDFr53ZNmY2ODd955R+c+RC3ttGC2trYAgKdPn+YZ4HPLP6d50J8/fy5+4dAq7kUnAGzZsgX/+9//EBISIi67du1avus1atQIe/fuRXJyMg4fPowJEyagR48euHPnjriPf/jhBzRu3DjbugX5EuPt7Z1j8Leysspxrvi4uDikpqaK21YoFAgODkZwcDBu376N1atXIzg4GFWrVs13/IP8uLi4oFmzZti4cSN69+6NzZs3Y9CgQeLxKOn6t2zZEl5eXvjiiy/QqVMnCIKA7du3w9LSEps3bxa/lGvvq8xPSZSvvJJIJLleVBQ2NpTE50+rUqVK2d7T8fHxBb6gLy6Ok3njOFl4HCcNh/b9MG3aNPTo0SPb69ovknl9rrJ+ucr6udLn/lKr1Xj//fdx9uxZHD16NMeYlRMPDw9UrlxZbNTIPIVqQEAAFi5ciGPHjkGtVovjaWjrmXU/PX/+XOd1rZzizwcffIAPPvgAL1++xM6dOzFu3DjIZDKsWrWq4JUGxIGh9+/fn2+jxpYtW/Dxxx9j8uTJ4rLdu3frpJFIJBgzZgzGjBmDJ0+eYOPGjZgyZQrs7Ozw1VdfwcbGBvb29tizZ0+O28hvIOa8vtTb2NhAEAQcO3ZMbJzNzMvLS/y/JM+99vb2MDIyyvV4ljV7e/t8Gz4y78fGjRvDzs4O7733HpYuXapzfBmrKLhRA5rudp999hkUCoU48FdAQABMTEzw+PHjXH9RACAG1axfKtq3b49ff/0V3t7euf4SoN3GmjVr0KhRo0Ll37x5c/z000+IiYkR56++efMmLl26hI8++qgAtS6c5OTkbCeQrPNo58XY2BhdunTBnTt3MGbMGKSkpKBmzZqoUqUK7t69i1GjRpVoec3MzODn54etW7fq/OK0efNmAG8G8sqsevXqmDt3Ln788Udcv34917xlMlmBv0QOGDAA48ePx59//omnT5+KXaoBlHj9zczMMHPmTAwfPhw7duxAz549kZycDJlMpnNyz+m45fRLV2ken/KsoLGhNDRq1Ai7du3Ct99+K96CsnXr1nzXk8vl+c4OkB+Ok/njOPkGx8nyx9TUFAEBAbh+/Tq+/vrrXNM1b94cCxYswIEDB8TbWTIyMrB9+/Yc3zOZ6XN/jRo1Crt27cL+/fvF2T4KqlmzZjh+/DiSk5MxY8YMcXmTJk2QlJSEFStWwNjYWOy15uXlBXt7e2zZskUnNm7evBlyuTzXWJYTOzs7DB06FHv27NH5zBX0M9a8eXM0atQIc+fORa9evVCpUiWd1x89eoTY2Fj4+vpmi2EqlQobN27MNe/KlSvjiy++wPr168WytW/fHt988w3kcjnq1KlT4HoWRLt27QBoevB169atRPPOi1QqRb169bB9+3adWFnQ829Z/fCQl169eqFZs2ZYvHgxxowZU6Y9PBkrC29do4ZarcaJEycAAAkJCbh8+TJ++ukn3L17F6GhoeJUgFZWVpg1axYmTZqEx48fo3Xr1pBKpbh79y527tyJ33//HSYmJvD29gYALFu2DD169ICJiQl8fX0xfvx4/Pbbb2jVqhXGjBkDV1dXREVF4eTJk3B2dsa4ceNgaWmJoKAgTJ48GWq1Gt27d4darcbhw4cxYMAANGjQINf8x40bhzVr1qBjx46YPn06UlJS8OWXX8LV1bVUpovq0KEDlixZgh9++AGenp749ddfc5zKKrPdu3dj1apV6NmzJ1xdXfHs2TMsXboUzZo1E4Ppt99+i4EDByIxMRFdu3aFqakpHjx4gN27d2Pu3LnZfk0tjODgYPTo0UP8tePmzZuYNm0a3nvvPfGCpkePHqhfvz78/f1hamqKXbt2ISYmBm3bts01X29vb+zcuRMtWrSAqakpvLy8YG5unmPaPn36YMyYMfjkk0/g4+ODunXriq8JglDi9Q8MDMTcuXMxf/589OzZEx06dMB3332Hzz77DD179kRERAR++eWXHOu0du1a7Nq1C5UqVYKzszOcnZ1L9fiUVwWNDUXx8OFDMT5lVq9ePcjlckyZMgUNGzZEjx498Omnn+Lu3btYuHBhvhcn3t7eyMjIwJIlS9C0aVNYWFjo/KKVFcfJouE4+QbHyfIZJxcsWIC2bduiX79+6N+/P6ytrfH48WMcPHgQQ4YMQevWrdG1a1c0atQIH3zwAebNmwdHR0csXboUkZGRmDZtWp75l8bxLIi5c+di5cqVmDhxIhQKhU6c9fHxgYWFRZ7rN2vWDFu2bAER6fTUsLCwgI+PD/bs2YMWLVqIDQJSqRRfffUVPv/8czg4OKBLly44ceIE5s+fj7Fjx4o90HITFBSE6OhotG7dGg4ODrh8+TL27duH8ePHi2kK8xn77bff0Lp1azRo0ADjx49H/fr1kZqain/++QfLli3DunXr4Ovriw4dOuDnn3+Gj48P7OzssHz58mwN4h9//DGsra3RpEkTWFtbIzw8HBcvXsSnn34KQBMHu3XrhnfeeQeTJk1CnTp1kJiYiKtXr+L27dvZpgQvDE9PT4waNQqDBg3CxIkT0bhxY6Snp+PWrVs4fPgwduzYUeS8//3332znX+24KYDmNrzu3btjyJAh6N+/P86ebTzESQABAABJREFUPZtjnMjK29sbq1evxoYNG1CjRg3Y2dnpTDteloKDg9GhQweEhobmOSsXY+WS/sYoLXva0ZC1DzMzM6pduzaNGjWKrl+/nuM6GzZsoIYNG5KxsTFZWFiQv78/ffXVV5Seni6mCQ4OpipVqpBEIiE3NzdxeWRkJA0dOpQqVapEcrmcqlSpQr1796bw8HCdbaxevZp8fX1JLpeTra0tvfvuu/TgwYN887948SJ16NCBTExMyNzcnHr16kX379/XyRsFHB2bKO8Rml+/fk2DBw8ma2trsra2puHDh9OuXbvyHPH+xo0b9N5775GLiwspFApydnamwYMHU2RkpE7eBw4coFatWpGpqSmZmppSrVq16IsvvqDY2Nhcy5rTaPs52bp1K9WpU4fkcjk5OTnR2LFjKTk5WXz9m2++oQYNGpClpSWZmppSvXr1aP369Xlu5+jRo1SvXj0yNjYmAHT48OFsdc+sU6dOBIBmz56dYxlLuv4///yzTrnmz59PVapUIRMTE+rQoQPdunUrW1kfP35MXbp0ISsrq2wzaRSlfOVZQWcKyS825DYjR26Qw4jn2sejR4/EdNu2bSNPT09SKBRUv359OnHiBFlaWuY5+0l6ejp9+umn5OjoSIIgUKtWrfKsP8fJ3HGc5DhpyHEyt/2b277o3r17tnhw+vRp6tKlC1laWpKxsTHVqFGDRo4cqROHXr58SYMHDyYbGxtSKBQUEBBAYWFhOvnkNFuMVn77K7fyZp1ZgqhgMbtVq1a5xlfteyAvZ8+eJQBkZ2eX7bURI0YQAJo2bVq211asWEE1atQgmUxGrq6uNHv2bHGGDqLczxO7du2idu3akb29PSkUCqpWrRoFBQXpxNTcPmO5ef78OY0fP56qVatGcrmczM3NqWXLlrR69WpxRq1nz55Rjx49yNzcnBwdHWny5MniZ0VbxtDQUGrWrBnZ2NiQUqkkHx8fndmkiIhSU1Np5syZVKNGDZLL5WRvb09t2rShdevW5VnGgswUolaraenSpVS7dm2Sy+VkY2NDAQEB9O2334ppCjPjV16zn0ilUp20K1euJBcXF1IqldSqVSs6efJkvrOfxMXFUf/+/cnW1pYAUGBgYLHqn9NnoDD5NG/enKpVq6YzixpjFYFARFQyzSOMMcYYY4wxxhhjZYendGWMMcYYY4wxxli5xI0ajDHGGGOMMcYYK5e4UYMxxhhjjDHGGGPlEjdqMMYYY4wxxhhjrFziRo0sUlJS4OLigt27dxdqvbCwMMydOzfb8uDgYJiZmZVU8d46Fy5cQHBwMJKSkoqdV2kfiwsXLkAQBISFhRVqvR07dmD58uWlU6gCCg0Nxfr167Mt79ChA+bMmaOHErG8cJwyLBynygbHqfKF45Rh4ThVNjhOMaYf3KiRxYoVK2BtbY2uXbsWar3cTsKseC5cuICZM2eWyEl42LBhOHz4cAmUqmQZ8kl42rRpWLhwIWJiYvRQKpYbjlOGheNU2eA4Vb5wnDIsHKfKBscpxvSDGzUyISJ8//33GDJkiL6LUmDJycnlIk9DUKVKFTRs2FDfxShX2rRpA2tra6xdu1bfRWH/4ThVenkaAo5ThcdxyvBwnCq9PA0Bx6nC4zjFWCkjJjp8+DABoIcPH+osV6lUNHv2bHJzcyO5XE5eXl60cuVK8fWgoCACoPNo1aqV+JqpqSldunSJmjVrRsbGxlSrVi3at29ftu2vWbOGfH19SaFQkLOzM02bNo0yMjJ0XgdAx48fp/bt25OJiQmNGjUqx7rcu3ePAFBoaCh99NFHZGFhQdbW1jRu3DhKT08vUJ6XLl2ijh07komJCVlYWNB7771HDx480NkOAJo3bx5NmzaN7O3tydLSkiZOnEhqtZr++usvqlu3LpmamlLbtm119mtByqctW+aHm5sbERHFxMTQsGHDyNnZmRQKBVWpUoX69euX5/HVHgst7fE+cOAADRgwgMzMzMjV1ZXmz5+fZz5as2fPJkdHRzI1NaWePXvS/v37CQAdPnxYTLNw4UJq0KABWVhYkL29PXXt2pVu3rwpvh4YGJitjoGBgUREdPz4cerWrRtVqlSJTExMqG7durRu3TqdMqSlpdGECRPIxcWF5HI5OTk50bvvvkuxsbFimpiYGPrkk0/IycmJ5HI51atXj/bv3y++3qpVq2xlCAoKEl+fNGkS+fn5FWifsNLHcYrjFMcpjlOGjuMUxymOUxynGCtL3KiRyfTp08nFxSXb8vHjx5NUKqWgoCDav38/ffbZZwSAli5dSkREjx49oqFDh5KxsTFFRERQREQEXb16lYg0gV8ul5Ovry/9/PPPtG/fPmrTpg2ZmprSy5cvxW0sWrSIpFIpTZgwgQ4cOEBLliwhMzMzmjx5sphGe1Jyd3enuXPn0t9//00nTpzIsS7ak5yzszMNHjyY9u3bR3PnziUjI6MC5fnw4UOysrKi+vXr07Zt22j9+vXk4eFB7u7uFB8fL64PgKpUqUIffPAB7du3j2bOnEkAaPz48eTr60sbN26kbdu2UZUqVahDhw6FKt+LFy/oyy+/JAC0b98+ioiIoHPnzhER0ZAhQ8jJyYlCQ0MpLCyMNmzYQB9++GGexze3k3DVqlUpKCiIDh48SKNGjSIAtHfv3jzzWrp0KQGgCRMm0L59++iLL76gKlWqZDsJjx07lkJDQ+nw4cO0c+dO6ty5M9na2lJ0dDQREd2+fZu6dOlCVatWFd87t2/fJiKiDRs20Lx582j37t106NAhmjVrFslkMgoNDRXznzlzJpmZmdGyZcsoLCyMtm7dSiNGjKDnz58TEVFqaio1aNCAXFxcaNWqVbRv3z764IMPyMjIiC5dukRERFevXiV/f39q1qyZWIZHjx6J29ixYwcBoBcvXuS5T1jZ4DjFcYrjFMcpQ8dxiuMUxymOU4yVJW7UyKRjx47UtWtXnWVRUVEkk8loypQpOssHDBhA9vb2Yst/1gCvpf3VYffu3eIy7Qnol19+ISKi+Ph4MjMzo6lTp+qsu2LFCjI2NhZP1toT5rx58/Kti3YbLVq00Fn+1VdfkYmJCb169SrPPMeNG0empqbiyYKI6Pr16yQIAn3//ffiMgDUqFEjnXXr169PgiDQtWvXxGXak1ZMTEyRyhcVFaWTrlatWjR+/Ph890NmuZ2EJ06cKC5Tq9Xk7u5OQ4cOzTWfjIwMcnZ2pkGDBuksHzRoULaTcNb1kpKSyMzMjH788UdxeWBgINWqVSvPsqvVakpPT6cRI0ZQQECAuLxr167Uq1evXNdbvXo1GRkZiReFWo0bN6Y+ffqIz1u1apXtva+lPVZ//vlnnmVkZYPj1BscpzhOaXGcMiwcp97gOMVxSovjFGOlh8fUyCQyMhL29vY6y06ePIn09HT06dNHZ3m/fv0QFRWFW7du5ZuvRCJB+/btxefu7u4wNjbG48ePAQDHjx9HQkIC+vTpg4yMDPHRvn17JCcn48qVKzr5FWbQrZ49e+o87927N5KSknD58uU88zx69Cjatm0LGxsbcVnNmjVRt25dHDt2TCdthw4ddJ57enrC2dkZ3t7eOssAiHUubPmyqlevHkJDQ7Fw4cJs+6ewOnbsKP4vCAK8vb2zlTOzx48f4+nTpzmWPasTJ06gQ4cOsLW1hZGREUxMTJCQkFCg901MTAw+//xzuLm5QSaTQSaT4aefftJZt169etizZw+Cg4Nx+vRpqNVqnTwOHDgAX19feHp66ry3OnTogNOnT+dbBgCws7MDoPl8MP3jOPUGxymOU1ocpwwLx6k3OE5xnNLiOMVY6eFGjUxSUlKgUCh0lmlHKXZ0dNRZrn3+6tWrfPM1NjaGXC7XWSaXy5GSkgIAePnyJQBNQNUGW5lMhho1agAAHj16lOO2C8LBwSHHdbMG1Kx5xsTE5LgdR0fHbHW2srLSeS6Xy3NcBkCsc2HLl9XSpUsxaNAgLFq0CL6+vnB1dcWKFSvyXCc3OZU1azkz05Ytt7JrPXz4EB07doRKpcKPP/6I8PBwnD59Gg4ODnnmrzV48GBs2LABEyZMwIEDB3D69Gl89NFHOutOnz4dkydPxtq1a9GoUSM4OTlh5syZICIAmvfW+fPndd5XMpkMX3/9dbb3VW60n4mKOuBZecNx6g2OUxyntDhOGRaOU29wnOI4pcVxirHSY6TvAhgSGxsbxMbGZlsGAC9evEDlypXF5c+fP9d5vbjbBYBt27bBxcUl2+seHh46zwVBKHDeL1680HmuLXelSpXyzNPGxibbutr1tb8SlISCli8rS0tLfPfdd/juu+9w+fJlLFmyBJ9++ilq166NFi1alFj5cqItW25l19q3bx8SEhKwbds28USfkZFRoAu3lJQU/Pnnn/j222/x2Weficuz/nKgUCgQHByM4OBg3L59G6tXr0ZwcDCqVq2KQYMGwcbGBnXq1MGqVauKUlUAED8Ttra2Rc6DlRyOU7pl4jiVM45TTJ84TumWieNUzjhOMcZKCvfUyMTLywv37t3TWdaoUSPIZDJs2bJFZ/nmzZvh4OAgnpDkcjlSU1OLtN2AgACYmJjg8ePHaNCgQbZHcYLf9u3bdZ5v3boVJiYm8PX1zXO95s2b49ChQzrzad+8eROXLl1C8+bNi1yewpYvt18kMvP19cXixYsBANevXy+xsuWmSpUqqFSpUo5lzyw5ORmCIEAmk4nLNm/ejIyMDJ10Of2SkZqaCrVarfOL1OvXr/HHH3/kWq7q1atj7ty5sLGxEfdD+/btcffuXTg7O+f43sqrDFr3798HoPl8MP3jOPUGx6nccZxi+sRx6g2OU7njOMUYKyncUyOTZs2aYfPmzUhPTxcDp52dHT777DMsWLAASqUSTZo0wZ49e7B+/XosXboUUqkUAODt7Y2MjAwsWbIETZs2hYWFRYGDlpWVFWbNmoVJkybh8ePHaN26NaRSKe7evYudO3fi999/h4mJSZHqdOfOHQwZMgT9+/fHuXPnEBISgnHjxsHa2jrP9caNG4c1a9agY8eOmD59OlJSUvDll1/C1dUVgwcPLlJZilI+7X2ky5YtQ48ePcQTdLNmzdCzZ0/Url0bUqkU69atg1wuL/VfFQBAKpViypQpGDNmDBwdHdGhQwccOHAAhw8f1knXtm1bAMCQIUPw8ccf4+rVq1i0aFG27pne3t5YvXo1NmzYgBo1asDOzg7u7u5o2LAh5s2bB3t7exgZGWHevHmwtLTU+UWjR48eqF+/Pvz9/WFqaopdu3YhJiZG3PaHH36IH3/8Ea1bt8aECRPg6emJ2NhYnD9/HmlpaQgJCRHLsHbtWuzatQuVKlWCs7MznJ2dAQBnzpyBmZkZ/Pz8SmmPssLgOPUGx6nccZxi+sRx6g2OU7njOMUYKzF6HqjUoDx79oyMjIzowIEDOstVKhXNmjWLXF1dSSaTUY0aNXTmVSciSk9Pp08//ZQcHR1JEIRs86pnZWlpqTN3NZFmyqmGDRuSsbExWVhYkL+/P3311VfZ5hnPOnJ1TrQjLK9Zs4YCAwPJ3NycrKysaMyYMZSWliamyyvPixcvUocOHcjExITMzc2pV69edP/+fZ00AGjBggU6y3IafVo7Mvbp06cLVT4iouDgYKpSpQpJJBJxXvWJEyeSr68vmZmZkYWFBTVr1kxnrvCc5DZat7ZMWt27dxePX27UajXNnDmTHBwcyMTEhP73v//Rvn37so3WvW7dOqpatSoplUpq0qQJnTp1itzc3MS564mI4uLiqH///mRra6szr/q///5Lbdu2JRMTE3JxcaEFCxZkq8M333xDDRo0IEtLSzI1NaV69erR+vXrdcoaFxdH48aNE9+/lSpVoi5duuiMvv348WPq0qULWVlZZZtXvVu3btlGJmf6w3FKF8ep3HGcYvrCcUoXx6nccZxijJUEgei/EXAYAOC9996DpaUlVq9ere+iFMv9+/fh4eGBLVu25DiKtL4ZevmYRkxMDJycnHDw4EG0bNlS38Vh/+E4VTYMvXxMg+OUYeI4VTYMvXxMg+MUY6WLx9TI4quvvsKmTZuyDVLE2Nto6dKlaNasGZ+ADQzHKcbe4DhlmDhOMfYGxynGShc3amTh5+eH7777rsDTMzFWkdnY2OD777/XdzFYFhynGHuD45Rh4jjF2BscpxgrXXz7CWOMMcYYY4wxxsol7qnBGGOMMcYYY4yxcokbNRhjjDHGGGOMMVYucaMGY4wxxhhjjDHGyiVu1GCMMcYYY4wxxli5ZKTvApQ1tVqNp0+fwtzcHIIg6Ls4jJUrRITXr1/D2dkZEgm3iZYWjlOMFR3HqbLBcYqxouM4xVjJeusaNZ4+fQoXFxd9F4Oxcu3Ro0eoUqWKvotRYXGcYqz4OE6VLo5TjBUfxynGSsZb16hhbm4OAHjw4AGsrKz0W5gSoFarERUVBXt7+wrR0sv1MWyxsbFwc3MTP0esdHCcMmxcH8PGcapscJwybFwfw8ZxirGS9dY1ami7SFpYWMDCwkLPpSk+tVqNlJQUWFhYVIggz/UxbGq1GgC4q3Ep4zhl2Lg+ho3jVNngOGXYuD6GjeMUYyWr/EcFxhhjjDHGGGOMvZX02qhx5MgRdOvWDc7OzhAEATt27Mh3nbCwMNSrVw8KhQLVq1dHaGhoqZeTMfb24jjFGDN0HKcYY4y9zfTaqJGYmIi6deti2bJlBUp/7949dO3aFW3atMGFCxcwduxYDBs2DPv37y/lkjLG3lYcpxhjho7jFGOMsbeZXsfU6Ny5Mzp37lzg9CtXroSHhwcWLVoEAPD29saxY8ewePFidOrUqbSKyRh7i3GcqtiICBkZGVCpVAVeR61WIz09HSkpKRXm3u7yVB+pVAojIyO+Fz0TjlPs/9m77/im6v2P46+TNE26B20pYGlZMmQKgoCKIorj4uCqgIiAuEERfiq4GHqv4EYRxQluUS9uRRFFEVCUJVvZqxO6V8b5/v4IjcTOtGmTtJ/n49FHm5MzPt8k5530m3O+RwghmrKAGih07dq1DBkyxG3a0KFDueuuu+q2Yl0Hg+Hv30IIUUv1llPC66xWK6mpqRQVFXm0nFIKXdfJz89vFP9YB2J7QkNDadGiBcHBwb4uJSBJTgkhhGhMAqpTIy0tjebNm7tNa968OXl5eRQXFxMSElJumdLSUkpLS1238/LyAOc3U7quw5o1MHkyPPcc3HknPPssDBhQvw3xIl3XXR9IGwNpj39rLO2oT/WSUwHOH/cDXdfZu3cvQUFBtGzZEpPJ5NE/9DabDZPJVI8VNqxAaY9SCpvNRmZmJnv37qV9+/blji7xp9eZv5KcKs8fc6oupD3+rbG0Qwh/EVCdGrUxZ84cZs+eXW56ZmYm1pISmD8fjEaYMsX5e/58aNs2YI7Y0HWd3NxclFIBcdhwdaQ9/i03N9fXJTRKVeaU1eqDirzLH/cDu92O3W6nZcuWFf4DVxWlFOA8DSJQjmyoSqC1x2QykZCQwMGDB0lLSyMoyP2jjORU/ZCcCizSHv8mOSWEdwVUp0ZiYiLp6elu09LT04mMjKz0Q+l9993H1KlTXbfz8vJISkoiPj6e6OhouKA/2vpMyClCffCbs3MjMbE+m+FVuq6jaRrx8fGNIuSlPf5NDvWuXr3kVIDzx/2gpKSEvLw8TCZTuX+KayoQjmzwRCC1x2QyYTAYiI2NxWKxuN0nOVU9yany/DGn6kLa498kp4TwroDq1Ojfvz9fffWV27Tly5fTv3//Spcxm82YzeZy0w0Gg/PSL5+/Bb1aQ1Qomq7DDTfAiBEBc6QGgKZpzvYEUM1Vkfb4r8bQhvrm9ZxqJI+5v+0HBoMBTdNcP55QSrmWCYQjG6oTiO0pe94qek35y2vMn0lOVczfcqqupD3+qzG0QQh/4tM9qqCggE2bNrFp0ybAeYmxTZs2cfDgQcD5rcD111/vmv/WW29l79693HvvvezcuZMXXniBDz74gClTptSuAKUgNdv5d1qO83dJiXO6EELgBzklhBDVkJwSQgjRlPm0U+P333+nV69e9OrVC4CpU6fSq1cvZsyYAUBqaqrrDRmgTZs2fPnllyxfvpwePXrw1FNP8eqrr9b+8mNGI4TFOv8OtziPzujSxTldCCHwg5wSDc9uA2tp5T+2k36qmq+mP3abR+WNGzcOTdO49dZby903ceJENE1j3LhxXnowKuZwOJg7dy6dOnUiJCSE2NhY+vXrx6uvvgrgdhRMRT+zZs1i//79btMiIiI47bTTmDhxIn/99Ve91t/YSE4JIYRoynx6+sm5557rGqCsIosXL65wmY0bN3qviCfnw+ePQ3QodOoES5d6b91CiIDnFzklGo7dBkd2g7W4ipkUOBwnOsC9cLpGcAi0ag9BNR/TIikpiffff59nnnnGNQZCSUkJ7777Lq1bt657TdWYPXs2L730Es8//zx9+vQhLy+P33//nexs59GPqamprnmXLFnCjBkz2LVrl2taeHg4WVlZAHz33XecdtppFBUVsWXLFp599ll69OjB559/zvnnn1/vbWkMJKeEEEI0ZXJCV8++gAZBRnjvBejY0dcVCSGE8BVdd3ZoGE1gDqn4J/ikn8rmqemP0eTcnoeX9zv99NNJSkpi6Ukd8UuXLqV169aub+vLLFu2jLPOOovo6GiaNWvGv/71L/bs2eO6/8033yQmJsbt6Ijbb7+dTp06UVRUVOH2P/vsM26//Xauvvpq2rRpQ48ePZgwYQJ333034ByIsuwnKioKTdPcpoWHh7vW1axZMxITE2nbti2XX3453333Hf369WPChAk4HA6PHhchhBBCND3SqWE0QkiY8+8N3/m2FiGEEP4hKAiCghvgp/YHTN5www0sWrTIdfv1119n/Pjx5eYrLCxk6tSp/P7776xYsQKDwcCVV16JfqIj5frrr+eiiy7iuuuuw2638+WXX/Lqq6/yzjvvEBoaWuG2ExMT+f7778nMzKx1/ZUxGAxMnjyZAwcOsH79eq+vXwghhBCNi3RqAEQ3d/4OjfRtHUIIIUQNXXfddfz8888cOHCAAwcOsHr1aq677rpy8/373/9m+PDhtG/fnp49e/L666+zZcsWtm/f7prnhRdeIDU1lTvvvJMJEyYwa9YsevfuXem2n376aTIzM0lMTKR79+7ceuutfP31115rW6dOnQDYv3+/19YphBBCiMZJOjUAWrZz/o4/xbd1CCGEEDUUHx/PpZdeyuLFi1m0aBGXXnopcXFx5eb766+/GDVqFG3btiUyMpKUlBQAt4EjY2JiePXVV3nxxRdp164d06dPr3LbXbp0YevWrfzyyy/ccMMNZGRkMGzYMG688UavtK1sfIhAucSsEEIIIXzHpwOF+o2YE0dqZKf7tg4hhBDCAzfccAOTJk0CYMGCBRXOM2zYMJKTk3nllVdo2bIluq7TtWtXrFar23w//fQTRqOR1NRUCgsLiYiIqHLbBoOBM844gzPOOIO77rqLt99+mzFjxvDAAw/Qpk2bOrVrx44dAHVejxBCCCEaPzlSA/7u1Die5vGl9YQQQghfueiii7Bardhstgovx3ns2DF27drFgw8+yPnnn0/nzp1dVyg52dq1a3n88cf5/PPPCQ8Pd3WUeKJLly6AcwyPutB1neeee442bdqUG/RUCCGEEOKf5EgNgJhE5+/Du+DXL2Dglb6tRwghhKgBo9HoOqrBaDSWuz8mJoZmzZrx8ssv06JFCw4ePFju1JL8/HzGjx/PHXfcwcUXX8wpp5zCGWecwbBhw7jqqqsq3O5VV13FwIEDGTBgAImJiezbt4/77ruPU0891TUeRk0dO3aMtLQ0ioqK2Lp1K/PmzWPdunV8+eWXFbZJCCGEEOJk0qkBfx+pAZBxsPL5hBBCNA12e+X3KQUOBygj1HXMh6q2U0ORkZUPcm0wGHj//fe588476dq1Kx07duS5557j3HPPdc0zefJkQkNDefTRRwHo1q0bjz76KLfccgv9+/enVatW5dY7dOhQ3nvvPebMmUNubi6JiYkMHjyYWbNmEeThFV2GDBkCQGhoKMnJyZx33nm8/PLLtG/f3qP1CCGEEKJp0lTZaFxNRF5eHlFRUWRnZxMdHf33HXOuhdJiuOVpaBE45/Dquk5GRgYJCQkYDIF/NpG0x7/l5OQQExNDbm5ulf9IibqpNKcClD/uByUlJezbt482bdpgsVj+vsNugyO7wVpc6bIKhd3hIMhoRMMLA1kGh0Cr9hBkqvu6akEphd1uJygoKGAG5qz0+UNyqqFITvk3aY9/k5wSwrvkSI0ysS0gdS/kZQVUp4YQQggvCjI5Oxh0vYqZlPMIi6Ag8EanhsHgsw4NIYQQQohAJ50aZWKaOzs1stN8XYkQQghfqq6DQSnQjM5OjQA5skEIIYQQorEK/OO3vCX6xLgaf/wIaft9WooQQgghhBBCCCGqJ50aZcoGCz26Bw7t9G0tQgghhBBCCCGEqJZ0apQpu6yrJQziT/FtLUIIIYQQQgghhKiWdGqUKTtSw26D5NN8W4sQQogG0cQuANZoyPMmhBBCiDLSqVEmKg40A9itUJDj62qEEELUI5PJORhoUVGRjysRtVH2vJU9j0IIIYRouuTqJ2WCTBDZDHIz4ehuaNdTLrEnhBCNlNFoJDo6moyMDABCQ0PRanglE6UUdrudoKCgGi/jzwKpPUopioqKyMjIIDo6GqPR6OuShBBCCOFj0qlxspjmzk6N9x6FGx+DU071dUVCCCHqSWKicyylso6NmlJKoes6BoPB7zsBaiIQ2xMdHe16/oQQQgjRtEmnxsliEmH/VuffuZnSqSGEEI2Ypmm0aNGChIQEbDZbjZfTdZ1jx47RrFkzDIbAP4sz0NpjMpnkCA0hhBBCuEinxsnKBgvtdg6cNtC3tQghhGgQRqPRo3+SdV3HZDJhsVgCohOgOo2tPUIIIYRoWuTTy8nKOjVys3xbhxBCCCGEEEIIIapVq04Nu93Od999x0svvUR+fj4AR48epaCgwKvFNbiyTo3sdN/WIYSos0abU0KIRkNySgghhKg7j08/OXDgABdddBEHDx6ktLSUCy64gIiICB577DFKS0tZuHBhfdTZMGJODDqWfww+eByGT5EroAgRgBp1TgkhGgXJKSGEEMI7PD5SY/LkyfTp04fs7GxCQkJc06+88kpWrFjh1eIaXGgEmCzOv7evheNpvq1HCFErjTqnhBCNguSUEEII4R0eH6mxatUq1qxZQ3BwsNv0lJQUjhw54rXCfELTIDYR0vdDr/MhJMzXFQkhaqFR55QQolGQnBJCCCG8w+MjNXRdx+FwlJt++PBhIiIiPC5gwYIFpKSkYLFY6NevH+vWraty/nnz5tGxY0dCQkJISkpiypQplJSUeLzdSpWNq5HYFiJivbdeIUSDafQ5JYQIeJJTQgghhHd43Klx4YUXMm/ePNdtTdMoKChg5syZXHLJJR6ta8mSJUydOpWZM2eyYcMGevTowdChQ8nIyKhw/nfffZfp06czc+ZMduzYwWuvvcaSJUu4//77PW1G5VyDhcqpJ0IEqkafU0KIgCc5JYQQQniHx50aTz31FKtXr6ZLly6UlJRw7bXXug6VfOyxxzxa19NPP81NN93E+PHj6dKlCwsXLiQ0NJTXX3+9wvnXrFnDwIEDXdu88MILGTVqVLXfRnikrFMj6wik7vPeeoUQDabR55QQIuBJTgkhhBDe4XGnximnnMLmzZt54IEHmDJlCr169WLu3Lls3LiRhISEGq/HarWyfv16hgwZ8ncxBgNDhgxh7dq1FS4zYMAA1q9f73rT3bt3L1999ZXH32hUqaxTY/cGeP0+0HXvrVsI0SAafU4JIQKe5JQQQgjhHR4PFPrTTz8xYMAARo8ezejRo13T7XY7P/30E+ecc06N1pOVlYXD4aB58+Zu05s3b87OnTsrXObaa68lKyuLs846C6UUdrudW2+9tcrDJUtLSyktLXXdzsvLA5znsuoVdVhEJWAAFEBIBKowF8KiatQmX9B1HaVUxW0JQNIe/xYo7Wj0ORVgGuN+IO3xX4HSDskp/9IY9wNpj/9qLO0Qwl943Klx3nnnkZqaWu5bhNzcXM4777wKB73ylpUrV/Loo4/ywgsv0K9fP3bv3s3kyZN55JFHeOihhypcZs6cOcyePbvc9MzMTKxWa/kF7NAcDQ1F+pX3ogpLobDic1L9ga7r5ObmopTCYPD4wBu/I+3xb7m5ub4uoUYafU4FmMa2H0h7/JvkVPUkp8prbPuBtMe/BUpOCREoPO7UUEqhaVq56ceOHSMsrOaXQI2Li8NoNJKenu42PT09ncTExAqXeeihhxgzZgw33ngjAN26daOwsJCbb76ZBx54oMKQu++++5g6darrdl5eHklJScTHxxMdHV1xcZGxkHeMeKMDPDgE1Bd0XUfTNOLj4xtFyEt7/Ns/Lz3or5pETgWQxrYfSHv8m+SUk+SUZxrbfiDt8W+BklNCBIoad2oMHz4ccI7OPW7cOMxms+s+h8PBH3/8wYABA2q84eDgYHr37s2KFSu44oorAGdgrVixgkmTJlW4TFFRUbkgMxqNgPPDQUXMZrNbrWUMBkPloRjTHPKOYcjNhNadatgi39E0rer2BBhpj//y9zY0qZwKMI1pPwBpjz/z9zZITvmvxrQfgLTHnzWGNgjhT2rcqREV5RxXQilFREQEISEhrvuCg4M588wzuemmmzza+NSpUxk7dix9+vShb9++zJs3j8LCQsaPHw/A9ddfT6tWrZgzZw4Aw4YN4+mnn6ZXr16uwyUfeughhg0b5noz9oqYRDiwHX5eCvu2wGW3e2/dQoh606RySggRkCSnhBBCCO+qcafGokWLAEhJSeHuu+/26NDIyowYMYLMzExmzJhBWloaPXv2ZNmyZa7Brg4ePOjWk/nggw+iaRoPPvggR44cIT4+nmHDhvHf//63zrW4KbsCSvp+yD8unRpCBIgmlVNCiIAkOSWEEEJ4l6YqO86wkcrLyyMqKors7OzKzwH940dYOg+iE2DoeOjUDyo479Uf6LpORkYGCQkJjeJQNmmPf8vJySEmJobc3FwiIyN9XU6jVaOcCiCNbT+Q9vg3yamGITnl36Q9/k1ySgjv8nigUICPPvqIDz74gIMHD5Yb8XrDhg1eKcynok8cqaEUdD7Tt7UIIWql0eeUECLgSU4JIYQQdedxV+dzzz3H+PHjad68ORs3bqRv3740a9aMvXv3cvHFF9dHjQ2v7PST3Cyw23xbixDCY00ip4QQAU1ySgghhPAOjzs1XnjhBV5++WXmz59PcHAw9957L8uXL+fOO+9sPNdcDo+GoGBAwZ+/w5Hdvq5ICOGBJpFTQoiAJjklhBBCeIfHnRoHDx50XWosJCSE/Px8AMaMGcN7773n3ep8RdP+Plrjg8fhh3d9W48QwiNNIqeEEAFNckoIIYTwDo87NRITEzl+/DgArVu35pdffgFg3759lV7bPCDFJDp/m0MgJMK3tQghPNJkckoIEbAkp4QQQgjv8LhTY/DgwXz22WcAjB8/nilTpnDBBRcwYsQIrrzySq8X6DNlR2r0Hgr/nuLbWoQQHmkyOSWECFiSU0IIIYR3eHz1k5dffhld1wGYOHEizZo1Y82aNVx22WXccsstXi/QZ8o6NbLTfVuHEMJjTSanhBABS3JKCCGE8A6POzUMBoPb9aFHjhzJyJEjAThy5AitWrXyXnW+JJ0aQgSsJpNTQoiAJTklhBBCeIfHp59UJC0tjTvuuIMOHTp4Y3X+oWxMjazD8Op0+Plj39YjhKiTRplTQohGRXJKCCGE8FyNOzWys7MZNWoUcXFxtGzZkueeew5d15kxYwZt27blt99+Y9GiRfVZa8OKTnD+tlvh8C44+pdv6xFCVKvJ5ZQQIuBITgkhhBDeVePTT6ZPn86aNWsYN24c33zzDVOmTGHZsmUYDAa+//57zjzzzPqss+EFmyE8BgqyYfB10KWRtU+IRqjJ5ZQQIuBITgkhhBDeVeMjNb7++msWLVrEk08+yeeff45Sip49e/LFF1803jfgsnE1YhMhTs5tFcLfNcmcEkIEFMkpIYQQwrtq3Klx9OhROnfuDEBKSgoWi4Xrrruu3grzC2XjamSn+bYOIUSNNMmcEkIEFMkpIYQQwrtq3KmhlCIo6O+zVYxGIyEhIfVSlN+IOTGuRupe2LIKMg/7th4hRJWaZE4JIQKK5JQQQgjhXTUeU0Mpxfnnn+96Iy4uLmbYsGEEBwe7zbdhwwbvVuhLZaefHNgO29fAkDEQf4pvaxJCVKpJ5pQQIqBITgkhhBDeVeNOjZkzZ7rdvvzyy71ejN8pO/3EYYekThAW5dt6hBBVapI5JYQIKJJTQgghhHfVulOjSSg7UqO0CMb9B4xG39YjhKhSk8wpIURAkZwSQgghvKvGY2o0SeExYDSB0iEvy9fVCCGEEEIIIYQQ4iTSqVEVg+HvwUKz052/lfJdPUIIIYQQQgghhHCRTo3qlI2r8f078PhY2LfFt/UIIYQQQgghhBACkE6N6pWNq1GUD0V5cllXIYQQQgghhBDCT9R4oNCKlJSUYLFYvFWLfyrr1IhOgKv+D+Ja+bYeIYRHmkROCSECmuSUEEIIUXseH6mh6zqPPPIIrVq1Ijw8nL179wLw0EMP8dprr3m9QJ8r69QoKYSW7SBYPnQI4e+aXE4JIQKO5JQQQgjhHR53avznP/9h8eLFPP744wQHB7umd+3alVdffdWrxfmFsjE1stN8W4cQosaaXE4JIQKO5JQQQgjhHR53arz55pu8/PLLjB49GqPR6Jreo0cPdu7c6dXi/EL0iaufFBfAph/gxw+hpMi3NQkhqtTkckoIEXAkp4QQQgjv8HhMjSNHjtC+ffty03Vdx2azeaUov2IOgdBI5yCh3y52/m7XA0451deVCSEq0eRySggRcCSnhBBCCO/w+EiNLl26sGrVqnLTP/roI3r16uVxAQsWLCAlJQWLxUK/fv1Yt25dlfPn5OQwceJEWrRogdls5tRTT+Wrr77yeLseKTsFpWU76H4umMz1uz0hRJ00yZwSQgQUySkhhBDCOzw+UmPGjBmMHTuWI0eOoOs6S5cuZdeuXbz55pt88cUXHq1ryZIlTJ06lYULF9KvXz/mzZvH0KFD2bVrFwkJCeXmt1qtXHDBBSQkJPDRRx/RqlUrDhw4QHR0tKfN8ExMczjyJ7TpBgOvrN9tCSHqrEnmlBAioEhOCSGEEF6iauGnn35SQ4YMUfHx8SokJEQNHDhQffPNNx6vp2/fvmrixImu2w6HQ7Vs2VLNmTOnwvlffPFF1bZtW2W1WmtTtlJKqdzcXAWo7Ozsmi/03dtKzbxCqc9frPV264vD4VCpqanK4XD4uhSvkPb4t+zsbAWo3NxcX5dSrSaXU36sse0H0h7/JjklOVUbjW0/kPb4t0DKKSECgcdHagCcffbZLF++vE6dKVarlfXr13Pfffe5phkMBoYMGcLatWsrXOazzz6jf//+TJw4kU8//ZT4+HiuvfZapk2b5jbI1slKS0spLS113c7LywOc56zqul6zYqMTMAAqOx2l62At8ZtLu+q6jlKq5m3xc9Ie/xZI7WhyOeXHGuN+IO3xX4HUDskp/9EY9wNpj/9qLO0Qwl943Klx4403ct1113HuuefWacNZWVk4HA6aN2/uNr158+aVjvq9d+9evv/+e0aPHs1XX33F7t27uf3227HZbMycObPCZebMmcPs2bPLTc/MzMRqtdao1mDMxAKOzMNoT03AUJRH+o3zwGiq0fL1Sdd1cnNzUUphMHg8RIrfkfb4t9zcXF+XUCNNMaf8WWPbD6Q9/k1yyklyyjONbT+Q9vi3QMkpIQKFx50amZmZXHTRRcTHxzNy5EhGjx5Nz54966G08nRdJyEhgZdffhmj0Ujv3r05cuQITzzxRKVvwvfddx9Tp0513c7LyyMpKYn4+Pianztq1gAw5mdDcDCa0kkI0iG+/HmqDU3XdTRNIz4+vlGEvLTHvwUHB/u6hBppkjnlxxrbfiDt8W+SU9WTnCqvse0H0h7/Fig5JUSg8LhT49NPPyU7O5sPP/yQd999l6effppOnToxevRorr32WlJSUmq0nri4OIxGI+np6W7T09PTSUxMrHCZFi1aYDKZ3A6N7Ny5M2lpaVit1goDwmw2YzaXv1qJwWCoeShGxYEhCE23w9X3QKsOGELCa7ZsA9A0zbP2+Dlpj/8KlDY0yZzyc41pPwBpjz8LlDZITvmfxrQfgLTHnzWGNgjhT2q1R8XExHDzzTezcuVKDhw4wLhx43jrrbcqvN56ZYKDg+nduzcrVqxwTdN1nRUrVtC/f/8Klxk4cCC7d+92Ow/tzz//pEWLFvXb42kwQnS882+jCfyoQ0MIUbEml1NCiIAjOSWEEELUXZ26CW02G7///ju//vor+/fvL3c+Z3WmTp3KK6+8whtvvMGOHTu47bbbKCwsZPz48QBcf/31bgNf3XbbbRw/fpzJkyfz559/8uWXX/Loo48yceLEujSjZmJOfNuRnVb/2xJCeE2TyikhRECSnBJCCCFqr1ZXP/nhhx949913+d///oeu6wwfPpwvvviCwYMHe7SeESNGkJmZyYwZM0hLS6Nnz54sW7bM9WZ+8OBBt8OzkpKS+Oabb5gyZQrdu3enVatWTJ48mWnTptWmGZ6JOfEBI/0A/PwxWIth8LX1v10hRK00yZwSQgQUySkhhBCi7jSllPJkgVatWnH8+HEuuugiRo8ezbBhwyo8x9Jf5eXlERUVRXZ2tmcDW63+BJa/AR36wF+/Q1Aw3P8e+PicOF3XycjIICEhoVGcnyft8W85OTnExMSQm5tLZGSkr8upVJPNKT/V2PYDaY9/k5xqGJJT/k3a498CJaeECBQeH6kxa9Ysrr766kbxBuaRsiM1CnOh2znQrCU4bGAInA8gQjQVTTanhBABQ3JKCCGE8A6POzVuuumm+qjD/5V1auSkw82P+7YWIUSVmmxOCSEChuSUEEII4R016tQYPnw4ixcvJjIykuHDh1c579KlS71SmN8p69QoyoPSYjCH+LYeIYQbySkhhL+TnBJCCCG8r0adGlFRUWiaBkBkZKTr7ybFEua8lGtxAWSnQ2wLKM6HqDhfVyaEQHJKCOH/JKeEEEII76tRp8aiRYtcfy9evLi+avF/MYlQvBu2rILVH0NSR5gwx9dVCSGQnBJC+D/JKSGEEML7PB4+ePDgweTk5JSbnpeX5/ElyAJO2Skouh1QzkFDhRB+p0nnlBAiIEhOCSGEEN7h8UChK1euxGq1lpteUlLCqlWrvFKU3yrr1LBZ4Z7FEBbl03KEEBVr0jklhAgIklNCCCGEd9S4U+OPP/5w/b19+3bS0tJctx0OB8uWLaNVq1berc7flHVq5GZKh4YQfkhySgjh7ySnhBBCCO+qcadGz5490TQNTdMqPCwyJCSE+fPne7U4vxOT6PydnVb1fEIIn5CcEkL4O8kpIYQQwrtq3Kmxb98+lFK0bduWdevWER8f77ovODiYhIQEjEZjvRTpN8qO1MjOgH1bYOvP0DwZ+l7i27qEEIDklBDC/0lOCSGEEN5V406N5ORkAHRdr7di/F5kHGgGcNjgyG5Y/y206yWdGkL4CckpIYS/k5wSQgghvKtGnRqfffYZF198MSaTic8++6zKeS+77DKvFOaXjEaIjofsdIiIgbOvglYdfF2VEALJKSGE/5OcEkIIIbyvRp0aV1xxBWlpaSQkJHDFFVdUOp+maTgcDm/V5p9iEp2dGkqH80f7uhohxAmSU0IIfyc5JYQQQnhfjTo1Tj5EsskfLhmd4Pydne7bOoQQbiSnhBD+TnJKCCGE8D6DN1aSk5PjjdUEBtdgoelgt0HGQcjJ9G1NQohqNamcEkIEJMkpIYQQwnMed2o89thjLFmyxHX76quvJjY2llatWrF582avFueXXJd1TYevX4UXJjsHDBVC+I0mn1NCCL8nOSWEEEJ4h8edGgsXLiQpKQmA5cuX891337Fs2TIuvvhi7rnnHq8X6HdOPlIj7hQIDgFdznsVwp80+ZwSQvg9ySkhhBDCO2p8SdcyaWlprjfhL774gmuuuYYLL7yQlJQU+vXr5/UC/U5Zp0ZBNvQcDGf+CzTNtzUJIdw0+ZwSQvg9ySkhhBDCOzw+UiMmJoZDhw4BsGzZMoYMGQKAUqppjNQdEg7mUOff+celQ0MIP9Tkc0oI4fckp4QQQgjv8PhIjeHDh3PttdfSoUMHjh07xsUXXwzAxo0bad++vdcL9Dua5hxXI20vZKdBQpKvKxJC/EOTzykhhN+TnBJCCCG8w+NOjWeeeYaUlBQOHTrE448/Tnh4OACpqancfvvtXi/QL8U0P9GpkQ6rP4HdG2HgldC+p68rE0IgOSWE8H+SU0IIIYR3eNypYTKZuPvuu8tNnzJlilcKCggnDxZalAf7/oC23aVTQwg/ITklhPB3klNCCCGEd3jcqQGwZ88e5s2bx44dOwDo0qULd911F23btvVqcX7r5E6NM/8FbXtA606+rUkI4abJ55QQwu9JTgkhhBB15/FAod988w1dunRh3bp1dO/ene7du/Prr7/SpUsXli9fXh81+p+YROfv7DTnERq9BkOzlr6tSQjhIjklhPB3klNCCCGEd3h8pMb06dOZMmUKc+fOLTd92rRpXHDBBV4rzm+dfKSGUnIFFCH8jOSUEMLfSU4JIYQQ3uHxkRo7duxgwoQJ5abfcMMNbN++vVZFLFiwgJSUFCwWC/369WPdunU1Wu79999H0zSuuOKKWm231qLiQDOA3QoFOXAsFXaug+LChq1DCFEhySkhhL/zdk5JRgkhhGiqPO7UiI+PZ9OmTeWmb9q0iYSEBI8LWLJkCVOnTmXmzJls2LCBHj16MHToUDIyMqpcbv/+/dx9992cffbZHm+zzoJMENnM+Xd2Orz7X3h/Dhz9q+FrEUKUIzklhPB33swpySghhBBNmcedGjfddBM333wzjz32GKtWrWLVqlXMnTuXW265hZtuusnjAp5++mluuukmxo8fT5cuXVi4cCGhoaG8/vrrlS7jcDgYPXo0s2fP9t1gWq5TUNKgRVtIbAO67ptahBBuJKeEEP7OmzklGSWEEKIp83hMjYceeoiIiAieeuop7rvvPgBatmzJrFmzuPPOOz1al9VqZf369a71ABgMBoYMGcLatWsrXe7hhx8mISGBCRMmsGrVqiq3UVpaSmlpqet2Xl4eALquo9ehE0KLTkAD9ONpMPwuZ4eGwQB2u/N3A9F1HaVUndriT6Q9/i1Q2iE55V8a434g7fFfgdIOb+VUQ2QUSE4FGmmPf2ss7RDCX3jcqWG1Wrn55puZMmUK+fn5AERERNRq41lZWTgcDpo3b+42vXnz5uzcubPCZX7++Wdee+21Cg/ZrMicOXOYPXt2uemZmZlYrVaPay4TZgonAihNPUDuypXw0ktw662wcCHccgt06VLrdXtC13Vyc3NRSmFowM6U+iLt8W+5ubm+LqFGJKf8S2PbD6Q9/q2p5VRDZBRITgUaaY9/C5ScEiJQ1LhTIzMzk+uvv57vvvsOXdc544wzeOedd2jXrl191ucmPz+fMWPG8MorrxAXF1ejZe677z6mTp3qup2Xl0dSUhLx8fFER0fXvpiktvAbWEpyMd9zD2zaBGtXgNUOu3fDr782yBEbuq6jaRrx8fGNIuSlPf4tODjY1yVUSXLKPzW2/UDa498kp6pWm4wCyalAI+3xb/6eU0IEmhp3akybNo1Nmzbx8MMPY7FYeOmll7jxxhv54Ycfar3xuLg4jEYj6enpbtPT09NJTEwsN/+ePXvYv38/w4YNc00rO3wrKCiIXbt2lftQYDabMZvN5dZlMBjqFoqxLQDQcjLQ5s+HEcPguv5QaoNLJkOQxwfB1JqmaXVvjx+R9vgvf2+D5JT/akz7AUh7/Jm/t8HbOdUQGQWSU4FI2uO/GkMbhPAnNf7Pe/ny5SxevJihQ4cC8K9//YvOnTtTWlpa4ZtcTQQHB9O7d29WrFjhupSYruusWLGCSZMmlZu/U6dObNmyxW3agw8+SH5+Ps8++yxJSUm1qqNWygYKzTsOd0yCrHzILoT8Epj2AKwb2qBjawghJKeEEP7P2zklGSWEEKKpq3GnxtGjR+nRo4frdocOHTCbzaSmppKSklLrAqZOncrYsWPp06cPffv2Zd68eRQWFjJ+/HgArr/+elq1asWcOXOwWCx07drVbfmyQx7/Ob3ehUZCsAWsJTBnNkybASPuh6n3wPznpUNDCB+QnBJC+Lv6yCnJKCGEEE2ZR+dIGI3GcreVUnUqYMSIEWRmZjJjxgzS0tLo2bMny5Ytcw14dfDgQf88REvTICYR0vdDm5awfr2zI+P39X93aPy5HlK6QnDtviEWQnhOckoI4e+8nVOSUUIIIZoyTdXwXdRgMBAVFYWmaa5pOTk5REZGur1RHj9+3PtVelFeXh5RUVFkZ2fXfWCr9+fCzl/hkpug7yXu9/3+DXyxENqfDqPuA2P9jLGh6zoZGRkkJCQ0ig8s0h7/lpOTQ0xMDLm5uURGRvq6nHIkp/xTY9sPpD3+TXKqYUhO+Tdpj3/z95wSItDU+D/tRYsW1WcdgalsXI3s9PL3JbSGoGBo1gK0wA9fIQKB5JQQwt9JTgkhhBDeVeNOjbFjx9ZnHYGpqk6N1p3htnkQm+g8VUUIUe8kp4QQ/k5ySgghhPAuOYSgLqKr6NSAE0dpnOjQUAr2bGqQsoQQQgghhBBCiKZAOjXqwnWkRpqz06IySjnH13hrNvzyecPUJoQQQgghhBBCNHLSqVEX0QnO39YSKMqrfD5Ng6g459gaJkvD1CaEEEIIIYQQQjRy9XNJjqbCFAwRzSD/mPMUlLCoyuc9+yo4tQ8ktmm4+oQQQgghGoquO49O1bS/L28vhBBC1LNav+NYrVZ27dqF3W73Zj2Bp6rBQk+mae4dGrZSSN1bf3UJISSnhBB+r9Hk1DtvQd8OEBcJYWHw3nu+rkgIIUQT4XGnRlFRERMmTCA0NJTTTjuNgwcPAnDHHXcwd+5crxfo92raqXGykiJ4+xFY9CAc3VM/dQnRhElOCSH8XaPKKV2Hz1+Af3WHAe2hpARuuME5XQghhKhnHndq3HfffWzevJmVK1disfw9PsSQIUNYsmSJV4sLCLXp1DAG/X1VFGuJ92sSoomTnBJC+LtGlVNKwaFjzr9PTwGD5uzYqGoQdSGEEMJLPB5T45NPPmHJkiWceeaZaGX/mAOnnXYae/Y0waMOTr4CSk2ZgmHkfZCbCc2T66cuIZowySkhhL9rVDmlabAzHYZ0AaMBeiXDtrS/v8ARQggh6pHHR2pkZmaSkJBQbnphYaHbm3KTEZPo/O3JkRoAllD3Do3845Cf7fxbDtcUok4kp4QQ/q5R5ZTBAM8vhC1HnLe7JcHrr8tgoUIIIRqEx+82ffr04csvv3TdLnvjffXVV+nfv7/3KgsUZUdq5B0Du6126zieCi9MhQdHw08roXdvWL3aayUK0dRITgkh/F2jy6lRo+C1L5yXr09uBhec4+uKhBBCNBEen37y6KOPcvHFF7N9+3bsdjvPPvss27dvZ82aNfz444/1UaN/C4+GoGCwWyE3C5q18HwddhvkHAdlg8sugdximDQJ1q+XbzmEqAXJKSGEv2uUORXTHNr3gr/Ww7qv4ZIbfV2REEKIJsDj/5jPOussNm3ahN1up1u3bnz77bckJCSwdu1aevfuXR81+jdNq91goSdLaA2DxsOiVc4ODYAFC6RDQ4hakpwSQvi7RptTHc9w/v7ta7CW+rYWIYQQTYLHR2oAtGvXjldeecXbtQSumETIPOTZYKEn03W472EoOOnNf+JEOVJDiDqQnBJC+LtGmVOd+8MXC0HpsO5LOGu4rysSQgjRyHn8H/OGDRvYsmWL6/ann37KFVdcwf3334/VavVqcQEj5sRAX8dr2alhMMDzz0PPnvDzKjj/THhunnRoCFFLklNCCH/XaHMqLBK6nuX8+68Nvq1FCCFEk+Dxf8233HILf/75JwB79+5lxIgRhIaG8uGHH3Lvvfd6vcCAYDsxSvlrL8Bpp8GuXZ6vY+BA55EZWz+GsxIhIdS7NQrRhEhOCSH8XaPOqQvGOgcMPbANMg/7uhohhBCNnMedGn/++Sc9e/YE4MMPP2TQoEG8++67LF68mP/973/eri8wPPeS83ezcGeHxvBaHmppMEDrzmAJh8Jc79UnRBMjOSWE8HeNOqei4qDDiXFBfv/Gt7UIIYRo9Dzu1FBKoes6AN999x2XXHIJAElJSWRlZXm3ukDgcMCGbc6/m0fBmP6Qddg5vTbOHQn3LILTh3ivRiGaGMkpIYS/a/Q51XWg8/e6r8Ba4ttahBBCNGoed2r06dOH//znP7z11lv8+OOPXHrppQDs27eP5s2be71Av2c0QosUWLYFrHZIjoNbzoPlb0BJoefrCwkHY63GbxVCnCA5JYTwd40+p07tA2jOAUN/+sjX1QghhGjEPO7UmDdvHhs2bGDSpEk88MADtG/fHoCPPvqIAQMGeL3AgLB0KeSbYcEKOJwPBg1++RyevwM2rwSlarfe0mKvlilEUyE5JYTwd40+pyxh0Lmf8+8D23xbixBCiEbN40MCunfv7jZad5knnngCo9HolaICTseOsG2b85QToxF2b4KvX4FjR+HjZ2H9crj0ZmieXLP15WfDB487T2P5v9chyFSv5QvR2EhOCSH8XZPIqYtvgp3r4NBOyDgICa19XZEQQohGyGvXDLVYLJhMTfyf77IPIe17wm3z4PzrwGSGg9th4VRY9jqUFFW/nrBIyE6H4gI48ld9VixEkyI5JYTwd40qpyJjoeMZzr/Xf+vbWoQQQjRaNTpSIyYmBk3TarTC48eP16mgRiPIBGf/G7qdA98sgh1rnaekbP0ZLhzrnF7ZY2owwr+nQrMWENmsYesWIkBJTgkh/F2TzKke58HOX2Hd1zD4WjDLJeuFEEJ4V406NebNm1fPZTRi0fEw4l73U1KWznN+Y3FJFaektOnakFUKEfAkp4QQ/q5J5lS7ns4vcZQO378LF9/o64qEEEI0MjXq1Bg7dmy9FrFgwQKeeOIJ0tLS6NGjB/Pnz6dv374VzvvKK6/w5ptvsnXrVgB69+7No48+Wun8fqPslJS1n8GPH8CBE6ek9LvUeRlXi3xzIURdSE4JIfxdfeaU32ZUsBk69IE/f4NDf3p//UIIIZq8Oo2pUVJSQl5entuPp5YsWcLUqVOZOXMmGzZsoEePHgwdOpSMjIwK51+5ciWjRo3ihx9+YO3atSQlJXHhhRdy5MiRujSlYZSdkjLpeeh8pvNbi18+h+cnwR8/Oq+S4nD8PX/6Afj0efhmsc9KFiLQSU4JIfxdXXPK7zNq2G3OU2uP/uX8bCOEEEJ4kaaUZ9cbLSwsZNq0aXzwwQccO3as3P2Ok/8pr4F+/fpxxhln8PzzzwOg6zpJSUnccccdTJ8+vdrlHQ4HMTExPP/881x//fXVzp+Xl0dUVBTZ2dlER0d7VKvX7d4IX70Cx1OdtzOL4MO1EJ/kvExssBXemAEh4XD3IjCWP7BG13UyMjJISEjAYPDauK8+I+3xbzk5OcTExJCbm0tkZKSvy6mU5JR/aWz7gbTHvzXFnGrojIJa5NSSx53ji51xsfOKcH6mse0H0h7/Fig5JUSg8PiSrvfeey8//PADL774ImPGjGHBggUcOXKEl156iblz53q0LqvVyvr167nvvvtc0wwGA0OGDGHt2rU1WkdRURE2m43Y2NgK7y8tLaW0tNR1u+zbD13X0XXdo3q9rm0PuPUZWPsZ2vK30eJDUTcNQr32M1x1FWzcgHbmMFSH3s6jOCqoV9d1lFK+b4uXSHv8W6C0Q3LKvzTG/UDa478CpR3eyqmGyCjwQk71PB/DjrWo9d+izh3p/MLGjzTG/UDa478aSzuE8Bced2p8/vnnvPnmm5x77rmMHz+es88+m/bt25OcnMw777zD6NGja7yurKwsHA4HzZs3d5vevHlzdu7cWaN1TJs2jZYtWzJkyJAK758zZw6zZ88uNz0zMxOr1VrjWutVh4EYHnqa6F6xBMcEU3zpGeRtyYGMTOh5iXOerPLf4oAzFHNzc1FKNYqea2mPf8vNzfV1CTUiOeVfGtt+IO3xb00tpxoio8ALORWeQHPNgKY7KP7yVfLOubZGtTWUxrYfSHv8W6DklBCBwuNOjePHj9O2bVsAIiMjXZccO+uss7jtttu8W1015s6dy/vvv8/KlSuxWCwVznPfffcxdepU1+28vDySkpKIj4/3r8O6swvg0z0wbiAhLUOwbMmExMRqF9N1HU3TiI+PbxQhL+3xb8HBwb4uoUYkp/xLY9sPpD3+TXLKMzXJKPBOTqn2vdD+Wk9I1iEsCQl1Ld2rGtt+IO3xb4GSU0IECo87Ndq2bcu+ffto3bo1nTp14oMPPqBv3758/vnnHn/4jouLw2g0kp6e7jY9PT2dxGr+oX/yySeZO3cu3333Hd27d690PrPZjNlsLjfdYDD4Vyh+9BEMHw77MtHaxKNNGQ1l9WWnw7Y1kHIanHJquUU1TfO/9tSBtMd/BUobJKf8T2PaD0Da488CpQ3eyqmGyCjwUk5dPgmevgktYz9a+gFo0aZmyzWQxrQfgLTHnzWGNgjhTzzeo8aPH8/mzZsBmD59OgsWLMBisTBlyhTuuecej9YVHBxM7969WbFihWuaruusWLGC/v37V7rc448/ziOPPMKyZcvo06ePp03wTx07wrZt8MCzztt7f4eiE6Ofr/offPcmbFxR+fJCCBfJKSGEv/NWTgVURoVHQ+d+zr/Xf9sw2xRCCNHo1fhIjb1799KmTRumTJnimjZkyBB27tzJ+vXrad++fbW9/BWZOnUqY8eOpU+fPvTt25d58+ZRWFjI+PHjAbj++utp1aoVc+bMAeCxxx5jxowZvPvuu6SkpJCWlgZAeHg44eH+NehUrXQ4HRLbQtpeWPc1nDsCup4F2WmQ3MXX1Qnh1ySnhBD+rj5yKqAyqveFsG01bPgOzh0J4VH1uz0hhBCNXo07NTp06EBqaioJJ86BHDFiBM899xzJyckkJyfXuoARI0aQmZnJjBkzSEtLo2fPnixbtsw14NXBgwfdDtF68cUXsVqtXHXVVW7rmTlzJrNmzap1HX5D0+Cs4fDRk/DrF9D/Mmjb3fkjhKiS5JQQwt/VR04FVEYlnwYGI+h251GoV9xRv9sTQgjR6GlKKVWTGQ0GA2lpaa434YiICDZv3uwa5CpQeHxddV/QHfD8HXA8FYbeAP2HVT5rI7tut7THv/n7ddUlp/xTY9sPpD3+TXKqYdQpp975D/y1HuJawaTn66U+TzW2/UDa49/8PaeECDSBnwqNkcEIA69w/r32U7DbnH/brLDrN3A4fFaaEEIIIUSdXHEHGIMg6wgc3ePraoQQQgS4GndqaJqGpmnlpol60uM8CI+BvGOwZRUoBQvuhPcehQPbfF2dEH5JckoI4e8kp4CwKOh8pvNvGTBUCCFEHdV4TA2lFOPGjXNdzqukpIRbb72VsLAwt/mWLl3q3QqbqiCTczyN5W/A6qXQ41xo0xX22KG4wNfVCeGXJKeEEP5OcuqE3kNh68+w6XsYdA1ENvN1RUIIIQJUjTs1xo4d63b7uuuu83ox4h96XwirPnIenrlrnXN8jWALNIJzCYWoD5JTQgh/Jzl1QsppYDSBwwbfvgFXTfV1RUIIIQJUjTs1Fi1aVJ91iIpYQuGMi50dGz8vhU79nFdHEUJUSHJKCOHvJKdO0DRo38v5pc2hXc7TbOUzjhBCiFqQr/z9Xb9LISgYjvwF+7f+Pb0oz3c1CSGEEELU1bBbwRAEuRlwdLevqxFCCBGgpFPD34VHw+lDnH+v+h8cT4MXJsMLdzkv/SqEEEIIEYjCY+C0Ac6/f5cBQ4UQQtSOdGoEgv6Xg2aAvZuhMNd5RZSiPMg87OvKhBBCCCFqr89Q5+8/foTsdN/WIoQQIiBJp0YgiEmAbmc7/177GYy6H+5eBM2TfVuXEEIIIURdtO7sHATdYYNvF/u6GiGEEAFIOjUCxcArnb+3r3Ve3z00wrf1CCGEEELUlaZB+9Odf5cNGCqEEEJ4QDo1AkXzZDj1DEDBmk98XY0QQgghhHdcNMF5edeCbDj8p6+rEUIIEWCkUyOQnDXc+XvTStj1G3zwONp3b/m0JCGEEEKIOomMha4DnX+vlwFDhRBCeEY6NQJJ607Qugvodti4wnkqypafQOm+rkwIIYQQovZ6nxgwdMsqyDoKuny2EUIIUTPSqRFozj5xtMaeTdD/MtSI6YDmy4qEEEIIIeomqSMYgp0Dhk69GqIi4L33fF2VEEKIABDk6wKEh9qfDs1TIH0/WMKhZTvIyPB1VUIIIYQQtacU/LEPuraCtgkw9QJYuwiK/gBbKaScBj3Ph7hWEGTydbVCCCH8iHRqBBpNc46t8b+n4dcv4Mx/+boiIYQQQoi6UQq+2AgtoiDEBKFmiA2DQzud96ftg1++AM0AzVqA3QZR8dDzXDilI8S2AOOJj7W67lyfpoFBDkoWQojGTjo1AlGXAfD9O5CdDj99SHhxMfQ+H1q193VlQgghhBCe0zTQguD575y3w8zQqhk8MwsO7gC7FfKzobQIso4458nJgAPbnH8bgiA8CopLYf0O2LAf0gvh9ddh1ChftEgIIUQDkU6NQGQ0woAr4MuX0NZ9RbitFGUKkk4NIRoz3QEGo6+rEEKI+mEwODsgbrgBSkrAocGsJ+GSkzoklIL843BoF/yxEo6nQbAFMg+BtQTyjjnn657k/NmTAdMmw4gRcsSGEEI0YtKpEah6DoaVS9AKc7DGtSYopasMFypEY+VwwNHdEBrhPNxazicXQjRGo0Y5OyAqO3VE0yCyGZw2wPlTRtchLws2fAdvvgB2HVLioF0CtI2HF++Cq++BhKQGbY4QQoiGId3WgcoU7BpPQ3PY4NTePi5ICFFvlA6lxZC6Dw7/5TwEWylfVyWEEN5nMDiPSPXkyAqDAaIT4NyRsGQ9vLMWFqyArYedHSGZh5wdGz+858xSIYQQjYp0agSyMy5CmUMxZafCn+t9XY0Qor6FRYG12HnURvp++XAuhBAnKzuFxWKBnCL4civE9wCT2dk5/OMHMH8i/P6N89KxQgghGgU5/SSQWcKgz1BY/THaqo+cg2h1Pcv5rYQQonFRJ0bzD40E3Q7H06Ewz3kVgIhmzm82hRDCT+i6jlIKTdMwNOR4FhWdwqLrsOMX+O5N5yDrXyyEZa/D+ddB/2ENV5sQQoh6IUdqBDjV71KUwYh2dLfzMq9H/vJ1SUIIb3vnDbjpOhh8Hpx1Fqz4HqLjnfcd3QtH90BRnm9rFEKIE9577z3CwsIICgoiLCyM9957r2EL+OcpLAaDcwyOifPhgusBzflF0Devw9sPQ8bBhq1PCCGEV8mRGoEuPIbiTgMI3b4KTBYoKfJ1RUIIb9J1ePVJOL8zODpAWi68+hwMHgwh4WAOgYIcKM53dnTEJDrH3BFCCB/QdZ1HHnmE0aNHExYWRkZGBo899hhnn302MTExmM1mgoJ89PEzyAQDr4RTz4DPFjjHKNq9EfZsRuvYl6Bu50NCgm9qE0IIUWvSqdEIFPa8gJDtP6PZSpzXaBdCNB5KOa9+YndAkBFaxTh/3nkEUk6Dlu2hXU9w2CHryN+npITHyCUMhRANTilFs2bNSEpyXmkkNjaWTp068dprr7nm0TSNU045hebNmxMVFYXJZEIpRVJSEi1btkSr79No40+BCXPgWCp89xbsWIu28xea7fwF1f1c+Netzg6Qyq7C4gld9856hBBCVMov0nXBggWkpKRgsVjo168f69atq3L+Dz/8kE6dOmGxWOjWrRtfffWV12rRdd3tdyBwRMZD14HOGz8v9W0xQjRSPsspTYM/jsDXm+GvNNiXAUVW54Chf/4OK9+H1+6DVR85zxW3FsOR3ZC2D0oKa7dNIUTA8ZfPUpqmsX//flauXMmePXvYv38/hw8fJiIiwjWPUopDhw7x+++/s2LFCpYtW8Y333zDq6++yqOPPsrzzz/P22+/zYsvvsjixYv57bffOHToEPn5+agqrvyk6zoOh6Pmn+GatYAR98KI6SiTGQ0w/LESHh8P/TpAUBCEhUFtT5957z3n8nVdDzg7t+tC153rqOvnW2+tRwghvMjnR2osWbKEqVOnsnDhQvr168e8efMYOnQou3btIqGCQwDXrFnDqFGjmDNnDv/617949913ueKKK9iwYQNdu3atUy2rV69m0qRJPPvss0yePJnnn3+egQMH1mmdDUUNuBJt68+wdTX0vQRad/Z1ScLf6frfA6jJt0dV8mlOGQzw0svwyHT4+U/QgmDGQ9CjI2z+Hg7uBBTs2eT8MZkhpjkkJEOXAZCYDJFxzm8dhRCNkj99ljIYDDz++OPccMMNrFy5EovFwuuvv86oUaOw2+1kZGRw9OhRNE0jNzeXnJwcjhw5Qk5ODrquY7fbOXbsGMeOHXOt88CBA66/y47iiIqKom3btkRFRREdHc3q1at56qmn2LdvH8HBwa5t1kjnfqhpb5G/YgkR239Cy82ES7vDeZ1AA7XsBbDvBqMRLf845GU5j4Zr1hI0A0oDDv0JKLRTOkKwGdDgy3dhZB/naYN2B7z+KLQ0OnPaaHJ2dgQFg9GEbgxCGYPRgkwYTH9P5+AhuOU22LET2neAJR9A5y6AB4Oxvvce3HADlJSgzBb0V19Hu3aU52/9772HGj8erbQUZTajLVrkHJi1AlUeoFKLo1d0XXf9GMo+uyiFrjSUZqjdgTDV1HHy4wsGr7ZHCOFdmqqqy7sB9OvXjzPOOIPnn38ecAZIUlISd9xxB9OnTy83/4gRIygsLOSLL75wTTvzzDPp2bMnCxcurHZ7eXl5REVFkZ2dTXR0tGu6rut07doVu93OyJEjOXDgAL/99htbt27FYDCwfPlycnNzGTBgAC1btnSta/fu3URERNChQwfXugoLCzEYDJjN5hqN+F2XEcJ1XScjI4OEhAQMix6EQzsgOASmvYWuGavM2Cq360FAVzmrw1HuqgxVbdetPd560wJ0ux2l62gGA4YqzuX19ptw2Qe4hIQE5znE/vImvHo1TJoEzz0Hd94Jzz8PNejAy8nJISYmhtzcXCIjIz0sPHD5PKfsNti3xfkBN9iCDigUGhqG0kLnh+msw7DvDyjM/XtFxiBo2Q7anQ7dB0FUnHN6LV54rteVUhg0zeMPoxXt12gaelUfFJGc8rgtjSmnatmepphTDZ1RUPnnqTK1+WzjcDjIy8sjJyeHY8eOsX37dvLy8ggLCyM3N5e8vLwqj9QoY7fbsdvtREREYLfbMZvNREZGYjQaCQoKIjMzE4PBQMuWLbFYLAQFBVFYWMixY8eIj4nmjG/fIbm1maAgP/0HVTNgRyO3qJhSu4NShyI2oTlRsSc6sI0mVJCJUofCHBqKtuQjsFohPhIsJuxZRbxlvY5B5+i0bVHgvER4UDAkpjj3N6VD+gHn0X4xic7xm3QdtXIFWlw42BxwJBtdgWHkKDieBqVFEJ8EMc3ZujOILz7X6Ra3j2KHheRzu3HGmSbne9JPK+DTjyEzD6w6TP0/OHeQ81QgY5CzBoMRNINzAGxrCd+uXcf/PTSbtu07sOvPXSwZcRU9ln4Cx3Ip0SxM0Z7hl6ghPDa7iAsvtYAl9MSpm3bIzgB0iIp35ohSznGoli+DZ56D3AIIDoaZM6FvD+fjG9uCr7/5lodmzCDUoIgPv4Dckumk5scQHKzxn//ApQMzQAFr1sEDD0F+IdhwXlK4Bp1pTTGnhKhPPu3UsFqthIaG8tFHH3HFFVe4po8dO5acnBw+/fTTcsu0bt2aqVOnctddd7mmzZw5k08++YTNmzdXu82q3oQHDx7M2WefjcFgQNd1bDYbsbGxGI1GCgoK0HWdqKgoQkJCMBqNlJaWkpWVRXBwMMnJyRiNRoxGI/v376ewsJA2bdoQFxeHwWCguLiYPXv2EBYWRteuXTEYDBiNRtasWcP69es5ePAgpaWl3HDDDfTo0YOjR49iMplo3bq1q760tDSKioqIj493HcZZUlLCvn37CAsLo8u+P2ifvR6lFH8es7A/qR+xQVZCiguwx8ZjaRVNUVERRoOB2My/yErPZH2xCUtICK3btCHJaCO8OIcSh4migxkUhVhQzeIJjo8nKCwUA4rSUis2hwOjJQST0cjxDJ0/dylCQguJiA2mWXwIMeEODEXFlP75J9YgI4bYeEzxcZhMRjIzszhy5Ahh0bEozUBsZDhxMTFYbaVYbQ40SwgaEGIAso5RePQo4aFGLMrG/qLm7C1pSbu2NiIsRcSUHEcLMlEcewoAhYUFhJXkEaqsWMNisYdEYrNZyT98iJa2XIwOBwWZRRS0aElQy0RCinMJ061Yw6NxhESRnm4n42ghp4ZmoXQD+c1SiI+HosJCQnIzCM8/jq3Yga3Qhr19O0pCQ4gvSHe+PuKSAY3i4mIsxblE2ArJViY2HkglPCwMXen0idQwlVgpyLGi6xoHLMlEhipahhagRYRjDW+GbrdTWlJCbGEGQQaNwqhENGMQpcUlBJUWEFGcg6OgGGu+Fd1opLhFS2IoJsioURjdgqy8Qo4eTSU6SJFg0Mgqbs3G9HZkHDZx2TAjfWI2g60UPv4ODh6BwlLYlQadO8PWrdX+09AU34T9IqfsNti/DYDPvvueD79YRnB4BMpuZ/Cgs+nWtRsAqVnHico7So+srYSU5KKdFO86GvZSO3npRdhtGgVdukBEKPG2fLQgE4WxrbDb7RQWFRNlzSPcoFMaFovNEsGBgwc5cuAAXYNKae7QKTpWgj04mPwupxERbiLKqCgNi8YWGkNBYRE2aymJ9lyMpmAKmrXGbtfJOn6MGKzE5GRh3bwdW76V3Mgotof0INQUjO4IIqJLEskpity8XEJLC9BzMlmzdScH80qIjIykW9eudI0OJtgURGGODX3NGnIiIsBoJKZbd2iTgoZzny0pLSXEEool1MK+vfDzKkVkZDZGI3TpGkPbthpabi7Fq1ZRbLNhsVgIGTAQLSqSPXv2sm3rVnR0CguK6D+gP23btKG4qJjikmKCzWaMmhFLiBlt3z6yt2whzKwTYbWytqAHW20d6d+/hISYPJpZczGFhFEc4+wMz87OIbQ4m2iTAWtEMxyWcEpLSsncsonWx49gKSklP7uUY506EdypM5bibKKDNOzhMdhDItn9l5W/duaRHJyN1WohsmsSbdtATm4eliN7id6/G3t+CfZSndIBAymKiaZZyXFCLGYKY5NA08jLy8NUlEO0QedQbhHL1v5Os7g4lN3OkJZRNEtNo/BYCQ5d45fIMzGEW+ie7CC6dTS2sBhsNjv5Bfk0K8wgNCSEophWKIOR/Px8DEU5xB7PQO34C2tOEXazmbw+fYgN0wgLsVAU3ZI9Bw6xceMGwpWNKBXLkZwL2ZaahAbceCP0T/rL2dF0+Bi8vhiy8+FovvyzUAlfZBRU36lRHxwOB5mZmRw6dIjS0lLsdju5ublkZWVx4MABDAaD18bjiFal9CGLsIgoilufhtFsQbdZseRlEFaSS0lQKNbYlmgo7EUFxOccxKAUx6NbYTCHotutWHIzCNat5JujMAcHY9TtqJJCDHYbRuUgSFOYNA3NbgVbKUG6/cR0MCqHc74T0wxKTvfwa7vS4P1fwGKBwkL5PCVEA/Npp8bRo0dp1aoVa9asoX///q7p9957Lz/++CO//vpruWWCg4N544033A4pfOGFF5g9ezbp6enl5i8tLaW0tNR1Oy8vj6SkJI4dO+b2Jmyz2TjzzDPdPhAEHKW4hV0kUuLrSkSAUEeyUa+vgpQU+Kv6ywHn5OTQrFmzJvUm7Bc55XDA0d3o1mJumjqNlD5nVV+40mlJCV3IoQs5xGD1rOFC+Al1IAv15hrnPwu5uTX6Z6Ep5VRDZBTU/POUL5R96VRaWkpISIjrUrIrV66ksLAQk8mE2WzGbrdjs9k4ePAgNpuN5s2bo5TCbreTmZlJRkYGERERRGdmYl+1CjuQ8+/RxPTuX20N9U7XMep2DA7b378dNgy6HYPD7vrb6LCdNI/79Ohj+zHZS8mNaklpSCQKDaOtlOjcI9iDLByPS0FpGmgGInJTCbKVkhfZHGtIFErTMNitROamojSNgqgWaLodo8NO9PGDWEryKAxrhi04FINux1RaROyxfaAZyItu6aozPD+D4NJCSiwR2E0haErH4LASVpiN0qAkJApN6WhKYbIWYXTYcBhMKIPBOV3XMSgHZV1XCg00nEdgAEozoJ840kMpRZDD+d5nM4WgNANK0zA6bATZrdiDgrGbQgAFSmEpyQeg1BzuOqrDaC8lyGHFYTThMAZTlK+hOyA2tNC5XIkV0GBPBmrpemdRJSXljv77p6aWU0LUN5+PqVHf5syZw+zZs8tNz8zMxGp1/5B/yimn8N1337kOlYyLi2P27Nlu5/GVDUBV3Y/dbncdeqnrOlarlcJC56B9ISEhrvVs3LiRoKAgSkpKsNvtAHTv3p28vDwMBgMxMTGu+vLy8rBarYSHh2OxWADnIZbHjx/HaDTSbP9+fjFG0CMMDOHhGKNiCSvNx2QrpjAoDHtIGOrEuYiRBRkoXXE8tBkaGprRQLitCJO1iBKjmVJTKErT0IJMaJqGUicOAT7xpqEFBYECW6mzZoOmOw+X1gxoygE2q/ONxqBhCDKBrlBKx263oWnOQ6s1TcNht2E0GEApFDjnRaEcDrDZ0DWNSGsewfZSioLDKTCEg6YIxkZ08XGUwUhOeDwAuq6IKM3DbC+h0BxBaXCY89BXu52YEue5ucdDnIffK6ORMGs+FmsxRZYISoLDsTtAU3biijNBaWSEJhJk0lBKEVqST4itkCJTGMWmUBQayqARV5gBaByLaA6aAV0pwqwFhFoLKAwKJT8oDO3EB/CEogxnDZZYdM2IrhkIcZQQXppPiSWc/JAY59GSSpGYfxRQZEa2wmE0oStFeGkBkcXHKTaFkW1xvi6UppFYcBSD0jke3oJiXccAhDqKiSrJo0QLJcuQQNZhRUmB4rzTjqI57Nh3HwJd4SgNIr93b+cL7OhR5/m9VcjNza3yflE7NcopUxS6IYxjmInNzSUkNBSHw0FpSQmnnuo8/S0vLx+H7iAiPByTMQgd2GBrwU8FhXQvPMzp2nFKdAMlykhpUBBGk5GWWglKM5BhinIeoWa3E6dKCDc4yDOGUGQwO/8p0BStVRFKQZYjGKVpWIOCaGa0E645yDdYKDY6/2kw6HZaUIymaWQGRZ7Y9+1EYyXCUUqRbqRYGbAbgwhNTCIq5xAAOTGtnR8kgZCibMwleZRaIikOPZGDShGdfRCA3OgklB+duxyen06QrYTCsDhs5jAAjPZSIvLS0A1B5EW3cs0bVpCJyVpEUVgsVrPzqDuD48Q/CwYjudGnuOYNLcgi2FpIcWgMpZbIE/Paicw9gtI0cmP+PpovpPAY5tICSkKiKQlxXglL0x1E5RwGKn58SyxRlIRGO1egdKKzy56LJOfh34ClKAdLSS6llgiKQ2Nd24s+7hznIDf6FJTB+QHeXJxLSHEOVnM4RWHNXPNGZR9EU4q8qFboRmfOmEvyCCnKxhocRlF4HKm7rOgOjR4tU9F0HVtGDjgUNruZgrKcysiotlNDcqp+ePJ5yhcWLVrEs88+i81mw2QyMXnyZMLDwwkPDy83b1xcXLlp7dq1Izc3l6ioKOfpMtdcg67D7f8HSbudV8wuynMOpzFxknNXyrMpVv70E0f37MJhd6BpEBWXwCVXDCdI0wgxKPQTn/cKlPMf6lAUBk1htdqwKQ2bIYjNGyDriANjkAOjwUZckpnOnY2YlR1jfh5FG9ZjR8PQohVBp7TEZDLy5ddfYwoyEpnQAodSZKcdYdjFF5FbWIhdh+CISLDbCTOCY+9eCjdsQIuOweyAX/9qy67iFMJCC7j0Mh1Lh7MIMhoJVs7TdgoLCznarD2h4RHOo0dQFBQUsv6rL+kV3QyLtRTDkVWsMgbRe8Q1HG3ZDXNoOCblwAC8sbgYo8lORHwEdnsQ2VscTJigU1xUiOOn1QSHBhF8PJOg/DxKzRZs11yDCgkjyGgkVNPRdeX8XGwMwhBs4bP/fUD+8WM0T0wkP7+Af52SjEkpQvfsQtcM5FtC+anZFZjDQjmnv8KkObBarVhtdnRzKEFBQZiVDU1BYVEhdi2IoD//wpR9nKBjGVhNwZSag1EXX+Sc11HKV19+RXBwMJZmUZgjB5GXFczxdNjxO1iLND78EAzocPXVYLM5X0S9e4PJBJmZklNCNDCfdmrExcVhNBrLfSuQnp5OYmJihcskJiZ6NP99993H1KlTXbfLvlmIj48v983CE088wVVXXcWOHTvo3LkzCxcu5NRTT61Fy2pG13VuueUWSkr+PrLCYrGQm5tb4/NPdV0nMzOT+GbNMMTEOHuHTyjGQhS5KAxuX3CVfaNR4XaB0Kgot/VU9u2YrkOls/bqAbt2/X2ueseO6Bs3Vr7dE+sua09CBe1xYCGBXMwWg1s5zSt4XKLLarTbsYaEEHzidiJQAgQXF7vOWQ+uri38facZiKngMfn735W/n5f4qCisViunn346GzdsIEfXsZw0b9nzU9ae2Aqe8rAKHvCwkhJcH8dOqiPU7XnVgFwgpHx7DBDcoQPs3w9lc6SkwImxYqoSHBxc7TyNjT/llK7rrPj+B7786mvXtBplRpUvcOdysRUsFsVJ34CWlLheUdEVrKP8vw1Oyfy9X8ee2K/NJSXE4DwduSAkhhaWoygMaAqOpmoYDGB3OEhu246iokLsNuc/TBazhYNHjmIAok5phVZS7GxeUBB6WATanj0Yg/7+dsyuK3Qdkk+B4hLnP/PGIEVYGOzZA6az+sNff4LDgSM0DNWhA9r339OqZUtKSkswGI2YTMEEm4I5cGC/6zG22R1kHTtGQmwMxlNOgdISdKMRhykYVDBtS/djNhs4mgo6zg7bKA3nWCQ4r/zgUGABwgyaM6fimqGbzSjNQJTNitXhIDjrGJrRiEOBGbCg0bIFlJSCKVhhMECQAQ4d1jCgo1q1wqEUwShCSkrAbIHUVBxoFdZgc+h0bNeOgvxcevboyebNmzhkDCLYaCTKbsdgt1GMhVbaUcIjDezeAzFBfx/a71AKpSDy5PU6HDjatsNYWkJ0SbHz21SzBf3oURyagTClc8qJxxc0zJajQAilJRqlxWCxaOTmgoaO6cRr1gSElr3eEhKq/WehqeVUQ2QUePZ5yheuuuoqhg8fXqcxyjRNIz4+3m3ZEVc4T4sqKXG+BF99Fbon/b3c4XWKuc88TklJCRaLhVdffZVz2lT+OFYkexM8PNt9Gxd2OmmGvj3Kjf2TtuMPbrzxRvft9vx7kFfX58P4eAy9usGVw/hgiWLETRrFpQbXdi45p+Z1Zh3cy78nTKC0tBSz2cwrr73GBQP6lZtvf5/yj9mZZaXt+6v8nb27V7ndtHatufmx/9ClSxe2b9/ONePGMeD116GkhBIs3MirfGrpzKuvwtk1HSd/91aYNtm9jm7t/97mtk2uxzco6Do07VVsNqNrVteuMmlS+fZUsR+VaWo5JUS9Uz7Wt29fNWnSJNdth8OhWrVqpebMmVPh/Ndcc43617/+5Tatf//+6pZbbqnR9nJzcxWgsrOzK53HbrfXaF3e8O677yqLxaIAZbFY1LvvvuvR8g6HQ6WmpiqHw6HUu+8qZbEoBcpusqgxQe8qcE7652qr3O5J66lwYVWDWXfuVKpLF+cdXbo4b9egvZW1pxiLGsm71ZVToZ8nTlTFJ44zKQb188SJnrXFw8fk70XeVaGhoeqMM85QoaGhzu3WtT3V1HHy4xsUNEaZTPaKZ925U6nOnZ3r6dzZ9fxUJzs7WwEqNzfXg6IDnz/lVK0zoxav4X9uc+SJfcjTdUhOVU9yyjvtUapp5lRDZ5RSNfs8FUjc9uty9ylltzt/V7as3W6vcNmab7/qbXi63craU5vt1HSbNd5OLYqw2WzqyJEjymazua3DYXPUvj3V1HFyW73dnqaYU0LUJ593arz//vvKbDarxYsXq+3bt6ubb75ZRUdHq7S0NKWUUmPGjFHTp093zb969WoVFBSknnzySbVjxw41c+ZMZTKZ1JYtW2q0PX98E67Lm2G5N62TgrVOb8IeBHSVs1bQQeTRm7A33rSUUg6bTdlLS5Wj7M2wsvma0puwUhU+P1Vpqm/C/pZTtc6MOnyadW3TZvN4HZJTNSM55Z32NMWcauiMUso/P0/VRVWdGoFI2uPfmmJOCVGffD6mxogRI8jMzGTGjBmkpaXRs2dPli1bRvPmzpMKDh486HYY4IABA3j33Xd58MEHuf/+++nQoQOffPJJna+r7kueHiJZzcr+/rMu2/WgpipnrWCgJI/ae2Leuj5CVV0esYLN1eLOyhYxuH5OXked2lNNHR49vtUMZCWc/C2nap0ZdcgayanqVy45VfM6avz4+tG4Kf7M3zJKCCGEaEg+vfqJL/jiEmT1Sdd1MjIySEhI8O4/HT4i7fFvcgmyhiE55d+kPf5NcqphSE75N2mPf5OcEsK7Aj8VhBBCCCGEEEII0SRJp4YQQgghhBBCCCECks/H1GhoZWfb5OXlNYrD13RdJz8/H4vFIu3xQ42tPXl5ecDf+5GoH5JT/k3a498kpxqG5JR/k/b4N8kpIbyryXVqHDt2DIDk5GQfVyJE4Dp27BhRUVG+LqPRkpwSou4kp+qX5JQQdSc5JYR3NLlOjdjYWMA5EnhjCJG8vDySkpI4dOhQoxhoSNrj33Jzc2ndurVrPxL1Q3LKv0l7/JvkVMOQnPJv0h7/JjklhHc1uU6NskPWoqKiGkUolomMjJT2+LHG1p7GcOinP5OcCgzSHv8mOVW/JKcCg7THv0lOCeEdsicJIYQQQgghhBAiIEmnhhBCCCGEEEIIIQJSk+vUMJvNzJw5E7PZ7OtSvELa49+kPaI2GtvjLO3xb9IeURuN7XGW9vg3aY8QoiqakmsJCSGEEEIIIYQQIgA1uSM1hBBCCCGEEEII0ThIp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiA1ik6NBQsWkJKSgsVioV+/fqxbt67K+T/88EM6deqExWKhW7dufPXVV273K6WYMWMGLVq0ICQkhCFDhvDXX3/VZxPceNKeV155hbPPPpuYmBhiYmIYMmRIufnHjRuHpmluPxdddFF9N8PFk/YsXry4XK0Wi8VtHl8+P5605dxzzy3XFk3TuPTSS13z+PK5+emnnxg2bBgtW7ZE0zQ++eSTapdZuXIlp59+Omazmfbt27N48eJy83i6PzYVklOSU5JTnpOcaliSU/6bU40po0BySnJKCC9TAe79999XwcHB6vXXX1fbtm1TN910k4qOjlbp6ekVzr969WplNBrV448/rrZv364efPBBZTKZ1JYtW1zzzJ07V0VFRalPPvlEbd68WV122WWqTZs2qri42O/ac+2116oFCxaojRs3qh07dqhx48apqKgodfjwYdc8Y8eOVRdddJFKTU11/Rw/frze21Kb9ixatEhFRka61ZqWluY2j6+eH0/bcuzYMbd2bN26VRmNRrVo0SLXPL58br766iv1wAMPqKVLlypAffzxx1XOv3fvXhUaGqqmTp2qtm/frubPn6+MRqNatmyZax5PH6OmQnJKckpyqnYkpxqO5JT/5lRjyqjatEdySnJKiOoEfKdG37591cSJE123HQ6HatmypZozZ06F819zzTXq0ksvdZvWr18/dcsttyillNJ1XSUmJqonnnjCdX9OTo4ym83qvffeq4cWuPO0Pf9kt9tVRESEeuONN1zTxo4dqy6//HJvl1ojnrZn0aJFKioqqtL1+fL5qetz88wzz6iIiAhVUFDgmubL5+ZkNXkTvvfee9Vpp53mNm3EiBFq6NChrtt1fYwaK8kpd5JT9UdySnKqtiSn3PlTTjWmjFJKckpySgjvC+jTT6xWK+vXr2fIkCGuaQaDgSFDhrB27doKl1m7dq3b/ABDhw51zb9v3z7S0tLc5omKiqJfv36VrtNbatOefyoqKsJmsxEbG+s2feXKlSQkJNCxY0duu+02jh075tXaK1Lb9hQUFJCcnExSUhKXX34527Ztc93nq+fHG8/Na6+9xsiRIwkLC3Ob7ovnpjaq23e88Rg1RpJT5UlO1Q/JKcmp2pKcKs9fcqoxZRRIToHklBD1IaA7NbKysnA4HDRv3txtevPmzUlLS6twmbS0tCrnL/vtyTq9pTbt+adp06bRsmVLtyC86KKLePPNN1mxYgWPPfYYP/74IxdffDEOh8Or9f9TbdrTsWNHXn/9dT799FPefvttdF1nwIABHD58GPDd81PX52bdunVs3bqVG2+80W26r56b2qhs38nLy6O4uNgrr9/GSHKqPMmp+iE5JTlVW5JT5flLTjWmjALJKZCcEqI+BPm6AOE9c+fO5f3332flypVuA0KNHDnS9Xe3bt3o3r077dq1Y+XKlZx//vm+KLVS/fv3p3///q7bAwYMoHPnzrz00ks88sgjPqysbl577TW6detG37593aYH0nMjhDdITvkvySkhnAI9pxprRoHklBCiYgF9pEZcXBxGo5H09HS36enp6SQmJla4TGJiYpXzl/32ZJ3eUpv2lHnyySeZO3cu3377Ld27d69y3rZt2xIXF8fu3bvrXHNV6tKeMiaTiV69erlq9dXzU5e2FBYW8v777zNhwoRqt9NQz01tVLbvREZGEhIS4pXnuzGSnPqb5JTkVH2TnKodyam/+VtONaaMAskpkJwSoj4EdKdGcHAwvXv3ZsWKFa5puq6zYsUKtx7qk/Xv399tfoDly5e75m/Tpg2JiYlu8+Tl5fHrr79Wuk5vqU17AB5//HEeeeQRli1bRp8+fardzuHDhzl27BgtWrTwSt2VqW17TuZwONiyZYurVl89P3Vpy4cffkhpaSnXXXddtdtpqOemNqrbd7zxfDdGklNOklOSUw1Bcqp2JKec/DGnGlNGgeQUSE4JUS98PVJpXb3//vvKbDarxYsXq+3bt6ubb75ZRUdHuy5dNWbMGDV9+nTX/KtXr1ZBQUHqySefVDt27FAzZ86s8BJk0dHR6tNPP1V//PGHuvzyyxv0MleetGfu3LkqODhYffTRR26XscrPz1dKKZWfn6/uvvtutXbtWrVv3z713XffqdNPP1116NBBlZSU+F17Zs+erb755hu1Z88etX79ejVy5EhlsVjUtm3b3Nrsi+fH07aUOeuss9SIESPKTff1c5Ofn682btyoNm7cqAD19NNPq40bN6oDBw4opZSaPn26GjNmjGv+skuQ3XPPPWrHjh1qwYIFFV6CrKrHqKmSnJKckpyqHcmphiM55b851ZgyqjbtKSM5JTklRGUCvlNDKaXmz5+vWrdurYKDg1Xfvn3VL7/84rpv0KBBauzYsW7zf/DBB+rUU09VwcHB6rTTTlNffvml2/26rquHHnpINW/eXJnNZnX++eerXbt2NURTlFKetSc5OVkB5X5mzpyplFKqqKhIXXjhhSo+Pl6ZTCaVnJysbrrppgYNRU/ac9ddd7nmbd68ubrkkkvUhg0b3Nbny+fH09fazp07FaC+/fbbcuvy9XPzww8/VPjaKWvD2LFj1aBBg8ot07NnTxUcHKzatm3rdo34MlU9Rk2Z5JTklOSU5ySnGpbklP/mVGPKKKUkpySnhPAuTSml6vdYECGEEEIIIYQQQgjvC+gxNYQQQgghhBBCCNF0SaeGEEIIIYQQQgghApJ0agghhBBCCCGEECIgSaeGEEIIIYQQQgghApJ0agghhBBCCCGEECIgSaeGEEIIIYQQQgghApJ0agghhBBCCCGEECIgSaeGEEIIIYQQQgghApJ0anhA0zQ++eQTAPbv34+maWzatMmnNTUFs2bNomfPnrVadsyYMTz66KPeLaiBNfTrbty4cVxxxRWu2yNHjuSpp56qt+0J75Kc8g3JKckpUXOSU74hOSU5JURj1SQ7NcaNG4emaeV+LrroohqvIykpidTUVLp27QrAypUr0TSNnJycKper6Xz+4uTHJywsjA4dOjBu3DjWr19fb9sre8Opq82bN/PVV19x5513emV9/uCfr7uG8OCDD/Lf//6X3NzcBtumkJzyhOSUf5Gcajokp2pOcsq/SE4J0bg0yU4NgIsuuojU1FS3n/fee6/GyxuNRhITEwkKCqrHKhuGUgq73V7p/YsWLSI1NZVt27axYMECCgoK6NevH2+++WYDVum5+fPnc/XVVxMeHl6v27FarfW6/pP54nXXtWtX2rVrx9tvv91g2xROklN/k5yqG8kpUV8kp/4mOVU3klNCiNpqsp0aZrOZxMREt5+YmBjX/X/99RfnnHMOFouFLl26sHz5crflTz5sbf/+/Zx33nkAxMTEoGka48aNq1Vdv/32GxdccAFxcXFERUUxaNAgNmzY4Lr/hhtu4F//+pfbMjabjYSEBF577TUAdF1nzpw5tGnThpCQEHr06MFHH33kmr/s242vv/6a3r17Yzab+fnnnyutKTo6msTERFJSUrjwwgv56KOPGD16NJMmTSI7O9s1388//8zZZ59NSEgISUlJ3HnnnRQWFrruT0lJ4ZFHHmHUqFGEhYXRqlUrFixY4HY/wJVXXommaa7bZd566y1SUlKIiopi5MiR5OfnV1qzw+Hgo48+YtiwYW7TU1JSePTRR7nhhhuIiIigdevWvPzyy27zbNmyhcGDBxMSEkKzZs24+eabKSgocN1fdjjhf//7X1q2bEnHjh1dr4cPPvjA9RicccYZ/Pnnn/z222/06dOH8PBwLr74YjIzM13rqu75/qd/Hi6ZnZ3N6NGjiY+PJyQkhA4dOrBo0SLX/IcOHeKaa64hOjqa2NhYLr/8cvbv3+/2OE2dOpXo6GiaNWvGvffei1Kq3HaHDRvG+++/X2ldon5ITklOSU5JTvk7ySnJKckpySkhfE41QWPHjlWXX355pfc7HA7VtWtXdf7556tNmzapH3/8UfXq1UsB6uOPP1ZKKbVv3z4FqI0bNyq73a7+97//KUDt2rVLpaamqpycnArX/cMPPyhAZWdnV3j/ihUr1FtvvaV27Nihtm/friZMmKCaN2+u8vLylFJKrV69WhmNRnX06FHXMkuXLlVhYWEqPz9fKaXUf/7zH9WpUye1bNkytWfPHrVo0SJlNpvVypUr3Wro3r27+vbbb9Xu3bvVsWPHKqzn5DafbOPGjQpQS5YsUUoptXv3bhUWFqaeeeYZ9eeff6rVq1erXr16qXHjxrmWSU5OVhEREWrOnDlq165d6rnnnlNGo1F9++23SimlMjIyFKAWLVqkUlNTVUZGhlJKqZkzZ6rw8HA1fPhwtWXLFvXTTz+pxMREdf/991dYs1JKbdiwQQEqLS3NbXpycrKKjY1VCxYsUH/99ZeaM2eOMhgMaufOnUoppQoKClSLFi1c21qxYoVq06aNGjt2rGsdY8eOVeHh4WrMmDFq69atauvWra7XQ9njvn37dnXmmWeq3r17q3PPPVf9/PPPasOGDap9+/bq1ltvrfHz/c/n4OTXnVJKTZw4UfXs2VP99ttvat++fWr58uXqs88+U0opZbVaVefOndUNN9yg/vjjD7V9+3Z17bXXqo4dO6rS0lKllFKPPfaYiomJUf/73/9c24+IiCi3f3z99dcqODhYlZSUVPqYC++SnJKckpySnPJ3klOSU5JTklNC+IMm26lhNBpVWFiY289///tfpZRS33zzjQoKClJHjhxxLfP1119XGYbVvbmWqel8ZRwOh4qIiFCff/65a1qXLl3UY4895ro9bNgw15tdSUmJCg0NVWvWrHFbz4QJE9SoUaPcavjkk0+q3X5lb8LFxcUKcNUxYcIEdfPNN7vNs2rVKmUwGFRxcbFSyvkGeNFFF7nNM2LECHXxxRdXub2ZM2eq0NBQtzeme+65R/Xr16/Suj/++GNlNBqVrutu05OTk9V1113nuq3rukpISFAvvviiUkqpl19+WcXExKiCggLXPF9++aUyGAyuN/SxY8eq5s2bu97IlPr79fDqq6+6pr333nsKUCtWrHBNmzNnjurYsWOldVf0fFf1uhs2bJgaP358het66623VMeOHd0eg9LSUhUSEqK++eYbpZRSLVq0UI8//rjrfpvNpk455ZRyb8KbN29WgNq/f3+ltQvvkpySnCojOSU55a8kpySnykhOSU4J4UuBfwJjLZ133nm8+OKLbtNiY2MB2LFjB0lJSbRs2dJ1X//+/RukrvT0dB588EFWrlxJRkYGDoeDoqIiDh486Jrnxhtv5OWXX+bee+8lPT2dr7/+mu+//x6A3bt3U1RUxAUXXOC2XqvVSq9evdym9enTp9Z1qhOH1GmaBjgHkfrjjz9455133ObRdZ19+/bRuXNnoPzj2L9/f+bNm1ft9lJSUoiIiHDdbtGiBRkZGZXOX1xcjNlsdtV3su7du7v+1jSNxMRE17p27NhBjx49CAsLc80zcOBAdF1n165dNG/eHIBu3boRHBxc5bpPnvfkaSfXXZPnuyq33XYb//73v9mwYQMXXnghV1xxBQMGDACcz8nu3bvdHjeAkpIS9uzZQ25uLqmpqfTr1891X1BQEH369Cl3yGRISAgARUVFNapLeIfklORUWf2SU5JT/kpySnKqrH7JKckpIXylyXZqhIWF0b59e1+XUc7YsWM5duwYzz77LMnJyZjNZvr37+82eNL111/P9OnTWbt2LWvWrKFNmzacffbZAK5zFb/88ktatWrltm6z2ex2++Q3Gk/t2LEDgDZt2ri2e8stt1Q4Mnbr1q1rvZ0yJpPJ7bamaei6Xun8cXFxFBUVYbVay71ZerquilT22J287rIPAP+cdvK2avJ8V+Xiiy/mwIEDfPXVVyxfvpzzzz+fiRMn8uSTT1JQUEDv3r3dPhiViY+Pr9H6yxw/frxWy4m6kZySnKrpuioiOSUaguSU5FRN11URySkhhDc02U6NqnTu3JlDhw6RmppKixYtAPjll1+qXKYs6B0OR522vXr1al544QUuueQSwDkwUVZWlts8zZo144orrmDRokWsXbuW8ePHu+7r0qULZrOZgwcPMmjQoDrVUpV58+YRGRnJkCFDADj99NPZvn17tR9s/vk4/vLLL65vHcD5hlXXxxBwXYd9+/btHl2TvXPnzixevJjCwkLXG+3q1asxGAx07NixznX9U02e7+rEx8czduxYxo4dy9lnn80999zDk08+yemnn86SJUtISEggMjKywmVbtGjBr7/+yjnnnAOA3W5n/fr1nH766W7zbd26lVNOOYW4uLhatFLUB8mp6klOeYfklKgtyanqSU55h+SUEE1bk736SWlpKWlpaW4/ZeE3ZMgQTj31VMaOHcvmzZtZtWoVDzzwQJXrS05ORtM0vvjiCzIzM91Gd67Ili1b2LRpk+tn8+bNAHTo0IG33nqLHTt28OuvvzJ69GjXoWonu/HGG3njjTfYsWMHY8eOdU2PiIjg7rvvZsqUKbzxxhvs2bOHDRs2MH/+fN544w1PHyYAcnJySEtL48CBAyxfvpyrrrqKd999lxdffJHo6GgApk2bxpo1a5g0aRKbNm3ir7/+4tNPP2XSpElu61q9ejWPP/44f/75JwsWLODDDz9k8uTJrvtTUlJYsWIFaWlpbiOBeyo+Pp7TTz+9ylHIKzJ69GgsFgtjx45l69at/PDDD9xxxx2MGTPGdfijN9X0+a7MjBkz+PTTT9m9ezfbtm3jiy++cH2oGT16NHFxcVx++eWsWrWKffv2sXLlSu68804OHz4MwOTJk5k7dy6ffPIJO3fu5PbbbycnJ6fcdlatWsWFF17olTaLmpOcqjnJKckpySnfkJyqOckpySnJKSHqic9G8/ChsWPHKqDcz8kDDu3atUudddZZKjg4WJ166qlq2bJlVQ4wpJRSDz/8sEpMTFSaprmN7nyyskGl/vljNBqVUs5Rpvv06aMsFovq0KGD+vDDD1VycrJ65pln3Naj67pKTk5Wl1xySblt6Lqu5s2bpzp27KhMJpOKj49XQ4cOVT/++KNbDTUZXOvkGi0Wi2rXrp0aO3asWr9+fbl5161bpy644AIVHh6uwsLCVPfu3V2DhSnlHFRq9uzZ6uqrr1ahoaEqMTFRPfvss27r+Oyzz1T79u1VUFCQSk5OVko5B7bq0aOH23zPPPOM6/7KvPDCC+rMM890m1bRY9mjRw81c+ZM1+0//vhDnXfeecpisajY2Fh10003uUZCV6ri0d4rej1U9DgvWrRIRUVFuW7X5Pmu6nX3yCOPqM6dO6uQkBAVGxurLr/8crV3717Xsqmpqer6669XcXFxymw2q7Zt26qbbrpJ5ebmKqWcA1lNnjxZRUZGqujoaDV16lR1/fXXu7WvuLhYRUVFqbVr11b8QIt6ITklOXUyySnJKX8kOSU5dTLJKckpIXxFU6qCiygLv1dQUECrVq1YtGgRw4cP93U5NZKSksJdd93FXXfd1SDbKy4upmPHjixZsqTBBiZrjF588UU+/vhjvv32W1+XIgKM5FT1JKe8Q3JK1JbkVPUkp7xDckqI+iNjagQYXdfJysriqaeeIjo6mssuu8zXJfmtkJAQ3nzzTY/PqRTuTCYT8+fP93UZIoBITtWc5JR3SE4JT0lO1ZzklHdITglRf6RTI8AcPHiQNm3acMopp7B48WKCguQprMq5557r6xIC3o033ujrEkSAkZzyjORU3UlOCU9JTnlGcqruJKeEqD9y+okQQgghhBBCCCECUpO9+okQQgghhBBCCCECm3RqCCGEEEIIIYQQIiBJp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiBJp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiBJp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiBJp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiBJp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiBJp4YQQgghhBBCCCECknRqCCGEEEIIIYQQIiA1qU6NWbNmoWkamqZhMBiIioqiW7duTJo0iR07dtRqnZs2bWLWrFkUFRV5udqGWf/Jxo0b53p8Tv7517/+VeN1aJrGk08+WY9VOq1cudKtxoiICHr16sXrr7+OUsrr2/n9999d02bNmsWaNWvKzdtQbT+5rrKfsLAwunXrxrPPPovD4fB4fYsXL+bdd9+th0oDz8k5oWka8fHxDB48mFWrVtXrdiva9zRNw2KxVLtsdHQ0s2bNct0+99xz3fbblStX8uijj9aoDsnJqklOVr4dycmGV1lunPyzePHiCp+jpuS7775j5MiRpKSkEBoaSpcuXXjiiSew2WxVLnfOOecwcODActN79+6Npmns27fPbfozzzyDpmlkZGR4tf6KVLaPVSYzM5P/+7//49RTT8VisRAZGcmgQYN47bXXarU/1Id/5muLFi0YNmwYW7Zsqbdt7t+/v9J9p1OnTlUum5OT49rHyqSkpDBp0iTX7U8++YQXXnihRrXU5P0lJSXFNT0oKIi2bdty2223kZWVVel6mjdvzoUXXsjatWtr+KgIEXiCfF1AQwsJCeH7778HID8/ny1btvDyyy/zyiuv8Nprr3Hdddd5tL5NmzYxe/ZsJk2aRGhoqNfrre/1/1Pbtm1555133KbFxMTU+3Zra9GiRXTq1ImcnBxee+01JkyYgM1m45ZbbvHK+k8//XTWrl1L586dXdNmz55NeHg4AwYMcJt37dq1JCcne2W7NVXW/tzcXN544w3uuusuiouLmT59ukfrWbx4MeHh4Vx77bX1VGlgOTknDh8+zCOPPML555/Phg0b6Nq1a71t94477ij3HBgMnvc9v/DCCxiNRtftlStX8uSTT3L//ffXaHnJyapJTrqTnPSdf/6T0r9//3I50q5dO7Zt29bQpfmVl156iaKiIh5++GFat27NL7/8wsyZM9m+fTuLFi2qdLmBAwfyzDPPUFpaitlsBqCgoIDNmzcTGhrKmjVraNOmjWv+1atX06FDBxISEuq9TZXtYxXZvXs35513Hg6Hg6lTp9K7d29KS0v5/vvvmTJlCnFxcVx++eX1XnNNlOWrUordu3czY8YMBg0axPbt20lMTKy37T766KOcd955btNCQkI8Xs/HH3/s9n7wySef8Pvvv3P77bfXaPmavL9cddVV/N///R82m41ffvmFWbNmsWXLFn766SfXZ4aTH8e9e/cyc+ZMhgwZwpYtW2jbtq3H7RLC3zW5Tg2DwcCZZ57pun3BBRdw++23c+mllzJhwgQGDBjQqHf24uLiKkM6JCTE7fHxd127dqVPnz6A87ns3Lkz8+fP99qH9cjIyBo/Hr543P7Z/o0bN7Jo0SKPP6wLd//Mib59+5KSksLChQt5/vnna73e6va/1q1be+V11KVLlzotLzkpOekJyUnfqejx9FaOeJvD4UDXdUwmU4Nv+8UXXyQuLs51+9xzz0XXdR588EGeeOIJt/tOdtZZZzF37lzWr1/v6jz49ddfCQ0N5YorrmD16tWMHj3aNf/q1au5+OKL61RrdflTG6NHj8Zut/P777/TqlUr1/SLLrqISZMmkZub69Xt1cXJ+dq/f39SUlI455xzePvtt7n77rtrvd7qHtcOHTp4Zb/p1atXnZavyftL8+bNXfOcffbZlJSUMGPGDDZs2ODKun8+jm3atGHgwIEsWbKE++67r041CuGPmtTpJ5WxWCzMnz8fq9XKq6++6nbf4sWL6d69OxaLhVatWvHAAw+4DtNbvHgx48ePByA+Ph5N00hJSXEte/jwYa677jri4uIICQnhnHPOYf369eW2/+abb9KrVy8sFgtxcXFccsklHDhwoNr1b9myhaFDhxIWFkZUVBRXXXUVBw8edFu3pmnMnTuXadOmkZiYWOtvD1JTU7nhhhto27YtISEhdOjQgfvvv5/S0tIql1u9ejXnnHMOUVFRRERE0K1bN9544w23eb788kv69etHSEgI8fHx3HbbbRQWFnpco9FopFevXm6Hgy5dupSePXtisVho2bIlU6dOpaSkxHW/zWbjnnvuoXXr1pjNZtehjmVv8P88ZFfTNADuuece12F9K1eudN1Xdlj1rFmziI2NLXdo69atW9E0jW+++cbr7TcYDHTv3r3ca2D69Ol069aN8PBwWrVqxahRo0hNTXXdf+655/Ljjz/y5Zdfutp08qkM3qovkLVu3Zr4+Hi311ZV2VB2v6ZprF27lgsuuICwsDDuueeeOtfy6aef0qlTJywWC3379uW3334rN8/Jp5/MmjWL2bNnU1hY6Hp+zz33XI+3KzlZPclJyUl/z8ns7GyuvfZaIiIiSE5O5vHHHy83z9q1axk8eLBrn7n22mvLnU5x/PhxbrjhBtd+O2DAAH766Se3ecpy6I033qBjx46YzWY2b94MVP94lb2mvvnmG6655hrCw8Np3bq16/Sf5557jtatWxMbG8uNN95Y7T5WUadFr169UEq5Pc//NGDAADRNY/Xq1a5pq1evpm/fvpx11llu0/fu3UtaWprb6SovvfSSq+0pKSn85z//Qdd11/1VvU+8/vrrnHbaaYSEhNCsWTPOOussV95XtY/906pVq1i3bh3333+/W4dGmdatW9OtWzcAdu7cyciRI0lKSnKdpvPUU0+51Qwwd+5c2rdvj8ViIT4+niFDhrhlSmlpKffffz/JycmYzWY6d+5c61O3yv5JL1u/Uoonn3ySU089FbPZTNu2bXnmmWfclpk1axbh4eGsW7eO/v37Y7FYWLBgQa22f7JXXnnFdQrT+eefz+7du8vNc/LpJ+PGjeONN95g27Ztrudp3Lhxda7jn/75GFWkrLPln9knRGMhnRondOnShVatWrkdyvn0009z4403MnToUD7//HOmTZvGc889xwMPPADApZdeyoMPPgjAsmXLWLt2LR9//DHg/OBw1llnsWnTJubPn8///vc/wsLCGDx4sNuHgyeeeIKxY8fSu3dvli5dymuvvUaHDh3IzMyscv2HDh3inHPO4dixY7z99tssXLiQDRs2MGjQIPLz893a9uyzz/Lnn3/y2muv8fbbb1f7WNjtdrcfgKysLGJjY3n66adZtmwZ9957L2+88Qa33nprpevJy8vj0ksvJTIykvfee49PPvmEm2++mZycHNc8H330EZdddhndunXj448/5vHHH2fp0qVMmDCh2jorsm/fPlq2bAnAZ599xlVXXUWXLl345JNPuPfee1m4cKHbofNz5sxh4cKFTJ8+nW+//Zbnn3+eli1bVvoBqez1cccdd7B27VrWrl3L6aefXm6+UaNGkZ2d7fahHOC9994jISGBIUOG1Ev7Dxw44HYoLEBGRgb3338/X375Jc8++yz79+9n0KBBruf2hRdeoFevXgwcONDVphtvvLFe6gtUeXl5HDt2zPXaqi4bTnbttdcyePBgvvjiC8aMGVPldnRdL7f/nfxhctOmTfz73/+mQ4cOLF26lLFjx3LNNddU+YH+xhtvZMKECYSEhLie35qe3/tPkpN/k5yUnAzEnLz11ls59dRT+fjjjxk2bBjTpk1j2bJlrvvXrl3LueeeS1RUFEuWLOHll1/mt99+czs1weFwcPHFF/P555/z2GOP8eGHHxIeHs4FF1xQrkPy999/54knnuDhhx/mq6++IikpyaPH67bbbqNr1658/PHHnHnmmYwZM4Zp06bxzTffsHDhQh5++GHefPNNnnrqKY8fi59//hmz2VzutXCymJgYunTpUq5TY8CAAQwYMICtW7eSl5fnmg7OozsA5s+fz6233urKxnHjxjFr1izuvffectv55/vETz/9xIQJE7jkkkv46quvePPNNzn//PNduVDTfQzgxx9/BJxHZVTnyJEjdOzYkRdeeIGvvvqKm2++mYcffphHHnnENc+bb77JQw89xIQJE1i2bBmvvvoqPXv2dD0OANdccw0vvfQS//d//8cXX3zBRRddxHXXXcfXX39dbQ3/VPaPellmTZ48mRkzZjB27Fi+/PJLxo0bx7Rp01i4cKHbclarlWuvvda13QsvvLDK7VT3/vvFF19w8803c9555/Hxxx9z/vnnc/XVV1e5zoceeohLLrmEtm3bup6nhx56qNo2V/T+UpV/PkYVOXDgAECVr3chAppqQmbOnKnCwsIqvf/MM89UnTp1UkoplZeXp8LDw9V9993nNs+LL76oQkJCVFZWllJKqUWLFilAZWZmus03Y8YMFRUVpdLT013TSkpKVOvWrdU999yjlFIqJydHhYaGqptvvrnSmipb/5QpU1RYWJg6duyYa9qOHTuUpmnqueeec00DVJcuXZSu65Vuo8zYsWMVUO5n1apV5ea12WzqnXfeUUFBQaqwsNBte0888YRSSqnffvtNAeqPP/6ocHu6rqvk5GQ1atQot+lff/210jRNbd26tdJaf/jhBwWoX375RdlsNpWVlaX++9//KsD1nPXq1Uv179/fbbmXXnrJraZLL71UDR8+vNrt/PbbbxW28WT/nN6rVy917bXXus3Ttm1bNXHixHpp/xNPPKE0TVPvv/9+pcvZ7XZ1+PBhBahvvvnGNX3QoEHq0ksvdZu3LvUFsrKcsNlsymazqX379qnhw4crQC1btszjbJg7d26NtlvRvgeo888/3zXPiBEjVJs2bZTdbndNe+211xSgZs6c6Zr2z+ezuuyrqP2VkZyUnKxsO5KTntVXHyp73Msei7L9Siln7SkpKWrChAmuaeecc44aMGCA276wbds2pWma+vLLL5VSSn366aeuPCxjtVpV69at3V4ngwYNUiaTSR08eNBtmzV5vMrqvffee13z5OTkKKPRqJKSkpTVanVN//e//6169uxZ8wdJKfXnn3+qsLAwNXny5GrnveWWW1RCQoJSSimHw6GioqLU119/rXRdV1FRUa7XyK233qri4+OVUs7XUFxcnBo5cqTbuu677z4VHBxc7fvEE088oWJjY6usq7Ln+p9uvfVWBaiSkpJq5z2ZruvKZrOp//73v6pFixau6RMnTlSnn356pct9//335fYdpZzvX2eccUaV2xw7dqw67bTTlM1mU1arVe3YsUOdffbZymQyqS1btqjdu3crTdPUSy+95LbctGnTVGJionI4HEop5/sYUOV+Xmbfvn2Vvv+evG/069dPnX322W7LPvTQQwpQixYtck1LTk525dfJbaqJmry/JCcnq9tvv13ZbDZVVFSkfvjhB9WyZUvVtm1bVVRUVOHjuGvXLnXeeeep5ORklZGRUaNahAg0cqTGSZRSrkP61qxZQ0FBAVdffbVbb+mQIUMoLi5m69atVa7r22+/5bzzziM2Nta1rNFoZNCgQa7DB9euXUtRUVGtvs1ZtWoVgwcPJjY21jWtU6dO9OjRg59//tlt3osvvtjVruq0a9eO3377ze2nZ8+eKKWYN28eXbp0ISQkBJPJ5DpHc+/evZWuKzIykttuu40PPviAzMxMt/v//PNPDhw4wDXXXOP2GA8aNAiDwVCjUdrPPPNMTCYTcXFxzJw5k1tvvZUZM2ZQUFDApk2buOqqq9zmHzFiBIDrMTr99NP56quvmDVrFr/99lu5QyzrYtSoUXz22WcUFxcDsG7dOvbu3cuoUaPqpf333HMP06ZNc7WxzNdff82AAQOIiooiKCiIU045xbX9qnijvkBVWFiIyWTCZDLRpk0bfvjhB55//nmGDh3qcTZceumlNd7u5MmTy+1/Jx9V8euvvzJs2DC3QUD/+Rqvb5KTkpOSk38LtJw8+dtqTdPo3Lkzhw8fBqCoqIjVq1dz9dVX43A4XG059dRTSUpKcu2Tq1atIjIykqFDh7rWZTKZGD58eLn9qnv37iQlJblue/p4XXDBBa6/o6KiSEhI4JxzznEbl+PUU0/l0KFDNX4M8vLyGD58OG3atOG///1vtfOfddZZZGRk8Ndff7mOzOjfvz+aptGvXz/XERplR3CA8zSOrKysct/kjxgxAqvVyrp169ym//N94vTTT+f48eOMGzeO5cuXe+XKTjXJt5KSEmbOnEn79u0xm82YTCYeeOABUlNTKSgocNW2ceNGpk6dys8//1zu9LFvv/2W2NhYBg8e7PYcl41nU92VVrZt24bJZCI4OJjOnTuzZ88e3nnnHbp27cp3330HwL///e9y7zlpaWnlXgeevP8+9thj5XK97KgKh8PB+vXrufLKK92WqY/338reX072wgsvYDKZCA0N5bzzzqNVq1b873//cxsz5OTHsWPHjvz6668sXbqU+Ph4r9cshD9ocgOFVuXw4cOceuqpAK5LI1V2OF91b6BZWVn88ssvFQ6I1a5dOwCOHTsGVH24WGWys7PLhRw4Bw86fvx4uWk1ZbFYXOfmneyZZ57h7rvv5t577+W8884jJiaG3377jYkTJ7qde32ymJgYli9fzsyZMxkzZgx2u52zzz6b+fPn061bN9dj/M83iTI1+ZDy5ptv0rlzZyIjI0lJSSE4OBhwPpdKqXJtj4qKwmw2ux6jBx54AIPBwBtvvMHs2bOJj49n4sSJzJgxo8b/4FRm5MiRTJs2jc8//5xrrrmG9957j+TkZNeHHm+2PyMjgzlz5vDYY48xaNAg12Gmv/32G5dddhmXX34506dPJyEhAU3TOPPMMyt93sp4o75AFRISwk8//YSmacTFxZGUlOQaUdzTbPBk/zvllFMq3P/KpKamlhvvITIyskaXffUWyUnJScnJvwVaTkZHR7vdDg4Odp3SkJ2djcPhYMqUKUyZMqXcsmVtyc7OrnDcmZrsV54+XhXVW9G06p6nMlarlSuvvJLs7GzWrl1LWFhYtcuUjZGxevVqiouL6dKlC1FRUYBzzI1Vq1aRm5vLtm3buP766wHnYwTl2192u7rHafDgwbz11ls8++yzDB06FIvFwlVXXcW8efPcOmlromwcjYMHD9K+ffsq5502bRqvvPIKM2fOpHfv3kRHR/Ppp5/yn//8h5KSEsLDwxk3bhz5+fm8/PLLPPPMM0RFRTF27Fjmzp1LSEgIWVlZHD9+vNIBYVNTU12dhhVp164d77//vuuSri1atHDlTFZWFkqpSgd2PXTokOvqSqGhoYSHh1f7+JRp27Ztpe+/mZmZ2O32cq97T943aqqy95eTXXPNNdxzzz2YTCaSkpIqfE2UPY4Oh4PNmzdz7733cs011/DHH380yFXChGho0qlxwrZt2zhy5IhrAJ+ygFi6dKnbtwxlqjsnLTY2losuusjtPMQyZZcFa9asGQBHjx6tMuArW39F10FPT093/cNRpq4fOgE+/PBDLrvsMubMmeOatn379mqX69u3L19//TXFxcX88MMP3H333VxxxRXs2bPH9Rg///zz9OvXr9yyNfknpnPnzhWGf3R0dIXXis/NzaW0tNS1bbPZzKxZs5g1axa7d+/m9ddfZ9asWbRt27ba8Q+qk5SUxMCBA3n//fe56qqr+OCDDxgzZozr+fB2+8855xw6duzI//3f/zF06FA0TePjjz8mKiqKDz74wPVPedl5ldXxRn2BymAwVPqhwtNs8Mb+V6ZFixblXtN5eXk1/kBfV5KTVZOc9JzkpP8oez3cf//9XHHFFeXuL/tHsqr96p//XP1zv/Ll46XrOqNHj2b9+vWsWrWqwsyqSJs2bWjVqpWrU+PkS6j279+fJ598kp9//hld113jaZS185+PU3p6utv9ZSrKn+uuu+7/27vv8Ciqtg3g92xPL6SH0Guk96KCErpIUV9AhICADRXJZwELxQJYXkV5ERvNQhFUkCKCCIoIojRRmvSWkADpydY53x8hK0sKu8kmmd3cv+vKBTt7ZuY5u5l7kpPZM3jggQdw+fJlrFmzBpMmTYJWq8WCBQuc7zRgnxj6+++/v+mgxsqVK/Hwww/jueeesy9bv369QxuVSoWJEydi4sSJuHDhApYvX47JkycjLCwML730EkJDQxEeHo4NGzYUu4+bTcRc2i/1oaGhkCQJv/zyi31w9nqNGze2/9+d597w8HBoNJoS38/KFh4eftOBj+tfx44dOyIsLAz33HMP5s6d6/D+EnkLDmqg4HK7J554Anq93j7xV+fOneHr64vz58+X+BcFAPZQvfGXioSEBHz++edo2rRpiX8JKNzHokWL0KFDB5e2f+utt+Kjjz5Cenq6/f7VR48exZ9//okHH3zQiV67Jj8/v8gJ5Mb7aJfGx8cH/fr1w4kTJzBx4kQYjUY0adIENWvWxMmTJzFhwgS31uvv749WrVph1apVDn9x+vLLLwH8O5HX9Ro0aICZM2fiww8/xOHDh0vctlardfqXyOHDhyMpKQnr1q3DxYsX7ZdUA3B7//39/TFjxgyMHz8eq1evxuDBg5Gfnw+tVutwci/ufSvuL10V+f54MmezoSJ06NABa9euxdtvv23/CMqqVatuup5Op7vp3QFuhjl5c8zJfzEnPY+fnx86d+6Mw4cP49VXXy2x3a233oo333wTmzZtsn+cxWq14ptvvin2e+Z6Vfl6TZgwAWvXrsX3339vv9uHs7p27Ypff/0V+fn5mDp1qn15p06dkJeXh/nz58PHx8d+1Vrjxo0RHh6OlStXOmTjl19+CZ1OV2KWFScsLAxjx47Fhg0bHI45Z4+xW2+9FR06dMDMmTMxZMgQREdHOzx/7tw5ZGRkoHnz5kUyzGazYfny5SVuOzY2Fv/3f/+HpUuX2mtLSEjAG2+8AZ1OhxYtWjjdT2f06NEDQMEVfAMGDHDrtkujVqvRpk0bfPPNNw5Z6ez5t7L+8FCaIUOGoGvXrnjnnXcwceLESr3Ck6gyVLtBDVmWsWvXLgBATk4ODh48iI8++ggnT57E4sWL7bcCDA4Oxssvv4xnn30W58+fR/fu3aFWq3Hy5EmsWbMGX331FXx9fdG0aVMAwLx58zBo0CD4+vqiefPmSEpKwhdffIFu3bph4sSJqFWrFtLS0vDbb78hJiYGkyZNQlBQEKZNm4bnnnsOsixj4MCBkGUZW7duxfDhw9GuXbsStz9p0iQsWrQIvXr1wgsvvACj0YgXX3wRtWrVqpDbRfXs2RPvvvsu/ve//6FRo0b4/PPPi72V1fXWr1+PBQsWYPDgwahVqxZSUlIwd+5cdO3a1R6mb7/9Nu6//37k5uaif//+8PPzw5kzZ7B+/XrMnDmzyF9TXTF9+nQMGjTI/teOo0eP4vnnn8c999xj/4Fm0KBBaNu2LVq3bg0/Pz+sXbsW6enpuPPOO0vcbtOmTbFmzRrcdttt8PPzQ+PGjREQEFBs2/vuuw8TJ07Eo48+ivj4eLRs2dL+nCRJbu9/YmIiZs6ciddffx2DBw9Gz549MWfOHDzxxBMYPHgwdu7cic8++6zYPi1ZsgRr165FdHQ0YmJiEBMTU6Hvj6dyNhvK4uzZs/Z8ul6bNm2g0+kwefJktG/fHoMGDcJjjz2GkydP4q233rrpDydNmzaF1WrFu+++iy5duiAwMNDhL1o3Yk6WDXPyX8xJz8zJN998E3feeSeGDh2KYcOGISQkBOfPn8fmzZsxZswYdO/eHf3790eHDh3wwAMPYPbs2YiMjMTcuXORnJyM559/vtTtV8T76YyZM2figw8+wDPPPAO9Xu+Qs/Hx8QgMDCx1/a5du2LlypUQQjhcqREYGIj4+Hhs2LABt912m31AQK1W46WXXsKTTz6JiIgI9OvXD7t27cLrr7+Op556yn4FWkmmTZuGK1euoHv37oiIiMDBgwexceNGJCUl2du4cox98cUX6N69O9q1a4ekpCS0bdsWJpMJP/30E+bNm4dPP/0UzZs3R8+ePfHxxx8jPj4eYWFheP/994sMiD/88MMICQlBp06dEBISgh07duDAgQN47LHHABTk4IABA9CnTx88++yzaNGiBXJzc/H333/j+PHjRW4J7opGjRphwoQJGDlyJJ555hl07NgRFosFx44dw9atW7F69eoyb/uff/4pcv4tnDcFKPgY3sCBAzFmzBgMGzYMe/bsKTYnbtS0aVMsXLgQy5YtQ8OGDREWFuZw2/HKNH36dPTs2ROLFy8u9a5cRB6p6uYorXyFsyEXfvn7+4tmzZqJCRMmiMOHDxe7zrJly0T79u2Fj4+PCAwMFK1btxYvvfSSsFgs9jbTp08XNWvWFCqVStSuXdu+PDk5WYwdO1ZER0cLnU4natasKe69916xY8cOh30sXLhQNG/eXOh0OlGjRg1x1113iTNnztx0+wcOHBA9e/YUvr6+IiAgQAwZMkScPn3aYdtwcnZsIUqfoTk7O1uMHj1ahISEiJCQEDF+/Hixdu3aUme8P3LkiLjnnntEXFyc0Ov1IiYmRowePVokJyc7bHvTpk2iW7duws/PT/j5+YlbbrlF/N///Z/IyMgosdbiZtsvzqpVq0SLFi2ETqcTUVFR4qmnnhL5+fn259944w3Rrl07ERQUJPz8/ESbNm3E0qVLS93P9u3bRZs2bYSPj48AILZu3Vqk79fr3bu3ACBeeeWVYmt0d/8//vhjh7pef/11UbNmTeHr6yt69uwpjh07VqTW8+fPi379+ong4OAid9IoS32ezNk7hdwsG0q6I0dJUMyM54Vf586ds7f7+uuvRaNGjYRerxdt27YVu3btEkFBQaXe/cRisYjHHntMREZGCkmSRLdu3UrtP3OyZMxJ5qSSc7Kk17ek12LgwIFF8uD3338X/fr1E0FBQcLHx0c0bNhQPPLIIw45dPnyZTF69GgRGhoq9Hq96Ny5s9i2bZvDdoq7W0yhm71eJdV7450lhHAus7t161ZivhZ+D5Rmz549AoAICwsr8txDDz0kAIjnn3++yHPz588XDRs2FFqtVtSqVUu88sor9jt0CFHyeWLt2rWiR48eIjw8XOj1elG/fn0xbdo0h0wt6RgryaVLl0RSUpKoX7++0Ol0IiAgQNx+++1i4cKF9jtqpaSkiEGDBomAgAARGRkpnnvuOfuxUljj4sWLRdeuXUVoaKgwGAwiPj7e4W5SQghhMpnEjBkzRMOGDYVOpxPh4eHijjvuEJ9++mmpNTpzpxBZlsXcuXNFs2bNhE6nE6GhoaJz587i7bfftrdx5Y5fpd39RK1WO7T94IMPRFxcnDAYDKJbt27it99+u+ndTzIzM8WwYcNEjRo1BACRmJhYrv4Xdwy4sp1bb71V1K9f3+EuakTeQBJCCPcMjxARERERERERVR7e0pWIiIiIiIiIPBIHNYiIiIiIiIjII3FQg4iIiIiIiIg8Egc1iIiIiIiIiMgjcVCjChiNRsTFxWH9+vVl3sbixYshSRIuX74MADh9+jQkSSr1ntnbtm2DJEn4448/yrxfV+3fvx+SJGHbtm32ZZIk4a233qq0GpRu8eLFWLp0qcvr9ezZE6+99loFVETEnGJOOWJOkRIxp5hT12NOEVVfHNSoAvPnz0dISAj69+9f5m30798fO3fuRHBwsNPrtGnTBjt37kTTpk3LvF932LlzJ0aMGFGlNShJWU/Czz//PN566y2kp6dXQFVU3TGnmFPXY06REjGnmFPXY04RVV8c1KhkQgi89957GDNmTLm2Ex4ejk6dOkGj0Ti9TmBgIDp16gQ/P79y7bu8OnXqhOjo6Crbv81mg8ViqbL9u8sdd9yBkJAQLFmypKpLIS/DnGJOuQtziioKc4o55S7MKSLPx0GNSvbTTz/h9OnTuPfee+3LXnnlFdSqVcv+WJZlBAcHIyIiwmHd6OhovPnmmwCKXi5ZnL179yI8PBwPPvggZFku9nJJSZIwe/ZsPPvsswgPD0dAQABGjx6N7Oxsh21lZGTgscceQ3R0NPR6Pdq2bYtNmzYV2eerr76KqKgo+Pv7Y8iQIUhNTS3S5sbLJdevX4+ePXsiIiICgYGB6NixIzZu3FhivwpNnz4d/v7++P3339GhQwcYDAY0bdoU69atc2jXvXt33HXXXViyZAkaN24MvV6PAwcOAAA+/PBD+7I6derg1VdfhSzL9nULX+c//vgDvXr1gq+vLxo3bowffvgBsizjxRdfRGRkJCIjIzFlyhSHdZ2pr3v37vjpp5+wfv16SJIESZIwffp0AMCOHTtw++23IygoCAEBAWjevHmRE+59993HkzC5HXOKOcWcIqVjTjGnmFNEVIiDGpXshx9+QFxcHOLi4uzLbr/9dpw7dw6nTp0CUPC5yby8PFy5cgWHDx8GABw7dgwpKSm4/fbbndrPjh07cOedd2L48OFYsGABVKqS3+q5c+fi8OHDWLJkCWbPno2vvvoK48ePtz9vNpvRs2dPrFu3Dq+99hq+/fZbxMfHo3///jh48KC93f/+9z+89NJLGDlyJL766ivUq1cPY8eOvWmtp06dwoABA/DZZ5/hq6++QteuXdGvXz+Hz42WxGKxYOjQoUhMTMTXX3+NBg0aYPDgwQ51AcAff/yBN998Ey+//DI2bNiAuLg4zJ07F4888gh69+6NtWvXYvTo0Zg+fTqeffbZIvsZNWoU7rrrLnzzzTeIiYnBkCFDMHHiRJw7dw6ffvopJkyYgNmzZ2P58uUu1ff++++jdevW6Nq1K3bu3ImdO3di3LhxyMrKQv/+/REYGIhly5Zh9erVeOihh5CRkeGw/S5dumD//v1IS0u76WtF5CzmVFHMKeYUKQtzqijmFHOKqNoSVKl69eol+vfv77AsPz9f6PV6sXjxYiGEEO+8847o0qWLaN26tZg/f74QQoiPP/5Y+Pn5CYvFIoQQYtGiRQKASEtLE0IIcerUKQFArFy5UmzevFn4+fmJKVOmOOxn69atAoD4/fff7csAiLp16wqr1WpftmDBAiFJkjh8+LAQQoiFCxcKjUYj/v77b4ftdezYUdx3331CCCGsVquIiYkRI0eOdGgzcuRIAUBs3brVYZ9vvvlmsa+PzWYTFotF9OrVSwwfPryUV1KIadOmCQBiwYIF9mVWq1XUrVtXDBs2zL6sW7duQqvVirNnzzq0CwsLc2gnhBBTpkwROp1OXL58WQjx7+v8/vvv29scPHhQABCdOnVyWLdt27Zi0KBBZarvxu+J33//XQAQf/75Z6mvQeH7vm7dulLbEbmCOcWcYk6R0jGnmFPMKSIqxCs1KllycjLCw8MdlhkMBrRv3x4///wzAODnn39Gt27d0K1bN/z000/2ZZ07d77pZz7XrVuHu+66Cy+88AJmzpzpVE0DBgyAWq22P7733nshhMDu3bsBAJs2bULz5s3RqFEjWK1W+1fPnj3x+++/AwDOnz+PixcvYvDgwQ7bvv6y0JKcP38eiYmJiI2NhUajgVarxaZNm3Ds2DGn6r9+n2q1GoMGDcJvv/3m0KZFixYOf805cuQILl++jPvuu8+h3dChQ2E2m+19L9SzZ0/7/xs1agQA6NGjh0ObRo0a4dy5c2Wq70b169dHYGAgHn30UXz55Zcl/uUgLCwMQMH3FZG7MKeKYk4VxZyiqsScKoo5VRRziqh64KBGJTMajdDr9UWWd+vWzX4S/uWXX3D77bfj9ttvdzgxO3Op5Nq1a+Hr64thw4Y5XdONnzUNDAyEwWCwB/vly5exb98+aLVah69XX33VftIpbHvjtiIjI0vdtyzLuPvuu/HLL7/g5ZdfxtatW/H777+jb9++MBqNN61dq9UiJCSkyD5vPCndWEfhDNc3Li98fPXqVYfl18+KrtPpiiwrXH5jzc7Wd6OQkBBs3rwZAQEBGDlyJKKiotC9e/cil4EWfi/l5+eXuj0iVzCnHDGnisecoqrEnHLEnCoec4qoenB+qmdyi9DQ0CKf4wMKPgf62muvYcuWLbh69Sq6du0Kk8mE5ORk/Pjjjzhz5gxuu+22m27/7bffxscff4wePXrg559/Rs2aNW+6zo2TT2VlZcFoNNpn1A4NDUWLFi2wYMGCErdR2PbGbV26dKnUfR8/fhz79u3D6tWrMXDgQPtyZ08qFosF6enpDie6S5cuFZkNXJIkh8ehoaGl1lv4fHk5W19xOnTogO+++w75+fnYunUrnn76aQwaNAgnTpywtyn8XqpRo4Zb6iUCmFM3Yk6VjDlFVYU55Yg5VTLmFJH345Ualaxx48b2Cayu16VLF2g0Grzyyito3bo1AgICEBYWhvj4eLz88svQ6XTo1KnTTbfv5+eHDRs2oEaNGujRo8dNT4JAwV8jbDab/fGqVasgSRLat28PAEhISMDJkycRExODdu3aFfkCgJo1ayI6OhrffPONw7ZXrVpV6r4LT7aFo/UAcObMGezYseOmdRe6fp82mw2rV69Gx44dS12ncePGCA8Px8qVKx2Wf/nll9DpdOjQoYPT+y9vfcX9ReJ6Pj4+6NevHx599FGcOnXKoe3p06cBFPSHyF2YU46YU8wpUh7mlCPmFHOKqDrjlRqVrGvXrvjyyy9hsVig1Wrty/39/dG6dWv89NNPSEpKsi+//fbbMX/+fHTt2hUGg8GpfQQGBmLTpk244447kJCQgG3btpU68mwymTBo0CA89thjOHXqFJ577jnce++9aNq0KYCCmao//PBDdO/eHU8//TQaNWqEjIwM7Nu3D2azGbNmzYJarcbkyZMxceJEREZGomfPnti0aRO2bt1aaq1NmjRBzZo1MXnyZNhsNuTk5GDatGmIjY11qq86nQ6vvvoqjEYj6tati/fffx/nzp3D6tWrS11PrVbjpZdewpNPPomIiAj069cPu3btwuuvv46nnnrKbSP1ztTXtGlTLFmyBGvXrkV0dDRiYmKwb98+LFiwAIMHD0atWrWQkpKCuXPnFvk++OOPP+Dv749WrVq5pV4igDl1I+YUc4qUhznliDnFnCKq1qp4otJqJyUlRWg0GrFp06Yizz399NMCgFi9erV92fLlywWAIjNvlzZbd6HU1FTRtGlT0aZNG5GRkVHibN2zZs0SSUlJIjQ0VPj7+4uRI0eKzMxMh/1lZmaKSZMmiVq1agmtViuio6NFv379HGaJlmVZzJgxQ0RERAhfX19x9913i40bN950tu7du3eL9u3bC4PBIBo2bCiWLFkiEhMTxS233FLqazlt2jTh5+cndu3aJdq2bSt0Op1o3LixWLNmjUO74mbDLjR//nzRsGFDodVqRa1atcQrr7wibDZbia9zSX0QQhSp2dn6zp8/L/r16yeCg4MFADFt2jRx5MgRcc8994i4uDih1+tFTEyMGD16tEhOTnZYd8CAAUVmSCcqL+YUc4o5RUrHnGJOMaeIqJAkhBAVPnJCDu655x4EBQVh4cKFVV0KJEnCm2++iaeffrqqS3HZ9OnT8dZbbyEnJ6eqSylWRdeXnp6OqKgobN682alJz4hcwZxyD+YUc4oqDnPKPZhTzCkiT8c5NarASy+9hBUrVjj1+UyikhRePskTMFUE5hS5A3OKKhJzityBOUXk+TioUQVatWqFOXPmFHsPbiJnhYaG4r333qvqMshLMafIHZhTVJGYU+QOzCkiz8ePnxARERERERGRR+KVGkRERERERETkkTioQUREREREREQeiYMaREREREREROSROKhBRERERERERB5JU9UFVDZZlnHx4kUEBARAkqSqLofIowghkJ2djZiYGKhUHBOtKMwporJjTlUO5hRR2TGniNyr2g1qXLx4EXFxcVVdBpFHO3fuHGrWrFnVZXgt5hRR+TGnKhZziqj8mFNE7lHtBjUCAgIAAGfOnEFwcHDVFuMGsiwjLS0N4eHhXjHSy/4oW0ZGBmrXrm0/jqhiMKeUjf1RNuZU5WBOKRv7o2zMKSL3qnaDGoWXSAYGBiIwMLCKqyk/WZZhNBoRGBjoFSHP/iibLMsAwEuNKxhzStnYH2VjTlUO5pSysT/Kxpwici/PTwUiIiIiIiIiqpaqdFDj559/xoABAxATEwNJkrB69eqbrrNt2za0adMGer0eDRo0wOLFiyu8TiKqvphTRKR0zCkiIqrOqnRQIzc3Fy1btsS8efOcan/q1Cn0798fd9xxB/bv34+nnnoK48aNw/fff1/BlRJRdcWcIiKlY04REVF1VqVzavTt2xd9+/Z1uv0HH3yAunXr4r///S8AoGnTpvjll1/wzjvvoHfv3hVVJhFVY8wp7yaEgNVqhc1mc3odWZZhsVhgNBq95rPdntQftVoNjUbDz6JfhzlFRETVmUdNFLpz504kJCQ4LOvduzeeeuqpqimIiOgGzCnPYTabkZycjLy8PJfWE0JAlmVkZ2d7xS/WntgfX19fREdHQ6fTVXUpHok5RURE3sSjBjVSUlIQGRnpsCwyMhJZWVnIz8+Hj49PkXVMJhNMJpP9cVZWFoCCv0wVzjzsyWRZtv9A6g3YH2Xzln5UJOZUUUo8DmRZxsmTJ6HRaBATEwOtVuvSL/QWiwVarbYCK6xcntIfIQQsFgvS0tJw8uRJNGjQoMjVJUr6PlMq5lRRSsyp8mB/lM1b+kGkFB41qFEWs2bNwowZM4osT0tLg9lsroKK3EuWZWRmZkII4RGXDd8M+6NsmZmZVV2CV2JOVT6r1Qqr1YqYmJhif4ErjRACQMHHIDzlyobSeFp/tFotIiIicPbsWaSkpECjcfxRhjlVMZhTnoX9UTbmFJF7edSgRlRUFC5duuSw7NKlSwgMDCzxh9IpU6YgKSnJ/jgrKwtxcXEIDw9HcHBwRZZbKWRZhiRJCA8P94qQZ3+UjZd63xxzqiglHgdGoxFZWVnQarVFfil2lidc2eAKT+qPVquFSqVCaGgoDAaDw3PMqZtjThWlxJwqD/ZH2ZhTRO7lUYManTt3xoYNGxyWbd68GZ07dy5xHb1eD71eX2S5SqXyilAEAEmS2B8F86b+eEMfKhpzqnhKOw5UKhUkSbJ/uUIIYV/HE65suBlP7E/h+1bc95RSvseUjDlVPKXlVHmxP8rlDX0gUpIqPaJycnKwf/9+7N+/H0DBLcb279+Ps2fPAij4q8CoUaPs7R955BGcPHkSzz77LI4cOYL3338fX375JSZNmlQV5RNRNcCcIiKlY04REVF1VqWDGn/88Qdat26N1q1bAwCSkpLQunVrTJ06FQCQnJxsPyEDQN26dbF+/Xps3rwZLVu2xH//+1988sknvP0YEVUY5lQ1ZLUAZlPJX5brvkpr5+yX1eJSeaNHj4YkSXjkkUeKPDdhwgRIkoTRo0e76cUons1mw+zZs9GkSRP4+PggNDQUHTt2xCeffAIADlfBFPc1ffp0nD592mFZQEAAbrnlFkyYMAH//PNPhdbvbZhTRERUnVXpx0+6d+9un6CsOIsXLy52nX379lVgVURE/2JOVTNWC3DhOGDOL6WRAGw2QK0G4IaPa+h8gNgGgMb5OS3i4uKwfPlyvPPOO/Y5EIxGI5YuXYpatWqVv6abmDFjBj788EP873//Q7t27ZCVlYU//vgD6enpAAp+iS60YsUKTJ06FUePHrUv8/f3x+XLlwEAP/zwA2655Rbk5eXh4MGDePfdd9GyZUusXbsWPXr0qPC+eAPmFBERVWceNacGERFRhZLlggENtRYoaQJRcd2gRnnnoLBaC/bn4u392rRpgxMnTuDrr7/GiBEjAABff/01atWqhbp16zq03bhxI1599VX89ddfUKvV6Ny5M959913Ur18fAPDpp59iwoQJ2Lt3Lxo1agQAeOyxx/Djjz9i79698PX1LbL/b7/9Fo899hjuu+8++7KWLVva/x8VFWX/f1BQECRJclgGwD6oUaNGDftz9erVw4ABA9CjRw+MHTsWJ06cgFqtdum1ISIiouqFs9QQERHdSKMBNLpK+Cr73xYefPBBLFq0yP544cKFGDNmTJF2ubm5SEpKwh9//IEtW7ZApVJh8ODBkK8NpIwaNQp9+vTBAw88AKvVivXr1+OTTz7BF198UeyABlAwaPHjjz8iLS2tzPWXRKVSYeLEiThz5gz27Nnj9u0TERGRd+GgBhERkQd64IEH8Msvv+DMmTM4c+YMduzYgQceeKBIu3vuuQdDhgxBgwYN0KpVKyxcuBAHDx7EoUOH7G3ef/99JCcn48knn8TYsWMxffp0tG3btsR9v/3220hLS0NUVBRatGiBRx55BN99953b+takSRMAwOnTp922TSIiIvJOHNQgIiLyQOHh4ejfvz8WL16MRYsWoX///ggLCyvS7p9//sHw4cNRr149BAYGok6dOgDgMHFkSEgIPvnkE8yfPx/169fH5MmTS913fHw8/vrrL+zatQsPPvggUlNTMWDAAIwbN84tfSucH8JTbjFLREREVYdzahAREXmoBx98EI8//jgAYN68ecW2GTBgAGrXro2PP/4YMTExkGUZzZo1g9lsdmj3888/Q61WIzk5Gbm5uQgICCh13yqVCu3bt0f79u3x1FNP4fPPP8fIkSPxwgsvFJnXw1WHDx8GgHJvh4iIiLwfr9QgIiLyUH369IHZbIbFYin2dpxXrlzB0aNH8eKLL6JHjx5o2rSp/Q4l19u5cyfeeOMNrF27Fv7+/vaBElfEx8cDKJjDozxkWcZ7772HunXr2m9RSkRERFQSXqlBRETkodRqtf2qhuLuEhISEoIaNWrgo48+QnR0NM6ePVvkoyXZ2dkYM2YMnnjiCfTt2xc1a9ZE+/btMWDAANx7773F7vfee+9F165d0aVLF0RFReHUqVOYMmUKGjVqZJ8Pw1lXrlxBSkoK8vLy8Ndff2HOnDnYvXs31q9fzzufEBER0U1xUIOIiOhGVmvJzxXe0lW46Zau5RQYGFjicyqVCsuXL8eTTz6JZs2aoXHjxnjvvffQvXt3e5uJEyfC19cXM2fOBAA0b94cM2fOxMMPP4zOnTsjNja2yHZ79+6NZcuWYdasWcjMzERUVBTuvPNOTJ8+HRoX7+iSkJAAAPD19UXt2rVxxx134KOPPkKDBg1c2g4RERFVT5IonI2rmsjKykJQUBDS09MRHBxc1eWUmyzLSE1NRUREBFQqz/80EfujbBkZGQgJCUFmZmapv0hR+TCnKp7RaMSpU6dQt25dGAyGf5+wWoALxwFzfonrCghYbTZo1GpIcMNEljofILYBoNGWf1tlIISA1WqFRqPxmIk5S3z/wJyqLMwpZWN/lI05ReRevFKDiIiokEZbMMAgy6U0EgVXWGg0gDsGNVSqKhvQICIiIvJ0HNQgIiK63s0GGIQAJHXBoIaHXNlARERE5K08//otIiIiIiIiIqqWOKhBRERERERERB6JgxpERERERERE5JE4qEFERNVWNbsBmNfg+0ZERESFOKhBRETVjlZbMBloXl5eFVdCZVH4vhW+j0RERFR98e4nRERU7ajVagQHByM1NRUA4OvrC8nJO5kIIWC1WqHRaJxeR8k8qT9CCOTl5SE1NRXBwcFQq9VVXRIRERFVMQ5qEBFRtRQVFQUA9oENZwkhIMsyVCqV4gcBnOGJ/QkODra/f0RERFS9cVCDiIiqJUmSEB0djYiICFgsFqfXk2UZV65cQY0aNaBSef6nOD2tP1qtlldoEBERkR0HNYiIqFpTq9Uu/ZIsyzK0Wi0MBoNHDALcjLf1h4iIiKoX/vRCRERERERERB6pTIMaVqsVP/zwAz788ENkZ2cDAC5evIicnBy3FkdEVFbMKSJSOuYUERFR+bn88ZMzZ86gT58+OHv2LEwmE3r27ImAgAC8/vrrMJlM+OCDDyqiTiIipzGniEjpmFNERETu4fKVGhMnTkS7du2Qnp4OHx8f+/LBgwdjy5Ytbi2OiKgsmFNEpHTMKSIiIvdw+UqN7du349dff4VOp3NYXqdOHVy4cMFthRERlRVzioiUjjlFRETkHi5fqSHLMmw2W5Hl58+fR0BAgMsFzJs3D3Xq1IHBYEDHjh2xe/fuUtvPmTMHjRs3ho+PD+Li4jBp0iQYjUaX90tE3os5RURKx5wiIiJyD5cHNXr16oU5c+bYH0uShJycHEybNg39+vVzaVsrVqxAUlISpk2bhr1796Jly5bo3bs3UlNTi22/dOlSTJ48GdOmTcPhw4exYMECrFixAs8//7yr3SAiL8acIiKlY04RERG5h8uDGv/973+xY8cOxMfHw2g04v7777dfKvn666+7tK23334b48ePx5gxYxAfH48PPvgAvr6+WLhwYbHtf/31V3Tt2tW+z169emH48OE3/WsEEVUvzCkiUjrmFBERkXu4PKhRs2ZNHDhwAC+88AImTZqE1q1bY/bs2di3bx8iIiKc3o7ZbMaePXuQkJDwbzEqFRISErBz585i1+nSpQv27NljP+mePHkSGzZscPkvGkTk3ZhTRKR0zCkiIiL3cHmi0J9//hldunTBiBEjMGLECPtyq9WKn3/+GbfffrtT27l8+TJsNhsiIyMdlkdGRuLIkSPFrnP//ffj8uXLuPXWWyGEgNVqxSOPPFLq5ZImkwkmk8n+OCsrC0DBZ1llWXaqViWTZRlCCK/oC8D+KJ2n9IM5pSzeeBywP8rlKf1gTimLNx4H7I9yeUs/iJTC5UGNO+64A8nJyUX+ipCZmYk77rij2Emv3GXbtm2YOXMm3n//fXTs2BHHjx/HxIkT8corr+Cll14qdp1Zs2ZhxowZRZanpaXBbDZXWK2VRZZlZGZmQggBlcrlC28Uh/1RtszMzKouwSnMKWXxtuOA/VE25tTNMaeK8rbjgP1RNk/JKSJP4fKghhACkiQVWX7lyhX4+fk5vZ2wsDCo1WpcunTJYfmlS5cQFRVV7DovvfQSRo4ciXHjxgEAmjdvjtzcXDz00EN44YUXig25KVOmICkpyf44KysLcXFxCA8PR3BwsNP1KpUsy5AkCeHh4V4R8uyPst1460GlYk4pi7cdB+yPsjGnCjCnXONtxwH7o2yeklNEnsLpQY0hQ4YAKJide/To0dDr9fbnbDYb/vzzT3Tp0sXpHet0OrRt2xZbtmzBoEGDABQE1pYtW/D4448Xu05eXl6RIFOr1QAKfjgojl6vd6i1kEql8opQBAreE/ZHubypP0rvA3NKubzpOADYHyVTeh+YU8rlTccBwP4omTf0gUhJnB7UCAoKAlBwsgsICICPj4/9OZ1Oh06dOmH8+PEu7TwpKQmJiYlo164dOnTogDlz5iA3NxdjxowBAIwaNQqxsbGYNWsWAGDAgAF4++230bp1a/vlki+99BIGDBhgPxkTUfXFnCIipWNOERERuZfTgxqLFi0CANSpUwdPP/20S5dGlmTo0KFIS0vD1KlTkZKSglatWmHjxo32ya7Onj3rMJL54osvQpIkvPjii7hw4QLCw8MxYMAAvPbaa+WuhYg8H3OKiJSOOUVERORekijpOkMvlZWVhaCgIKSnp3vNZ0BTU1MRERHhFZeysT/KlpGRgZCQEGRmZiIwMLCqy/FazCllY3+UjTlVOZhTysb+KBtzisi9XJ4oFABWrVqFL7/8EmfPni0y4/XevXvdUhgRUXkwp4hI6ZhTRERE5efyUOd7772HMWPGIDIyEvv27UOHDh1Qo0YNnDx5En379q2IGomIXMKcIiKlY04RERG5h8uDGu+//z4++ugjzJ07FzqdDs8++yw2b96MJ598kvdcJiJFYE4RkdIxp4iIiNzD5UGNs2fP2m815uPjg+zsbADAyJEjsWzZMvdWR0RUBswpIlI65hQREZF7uDyoERUVhatXrwIAatWqhV27dgEATp06VeK9zYmIKhNzioiUjjlFRETkHi4Patx555349ttvAQBjxozBpEmT0LNnTwwdOhSDBw92e4FERK5iThGR0jGniIiI3MPlu5989NFHkGUZADBhwgTUqFEDv/76K+6++248/PDDbi+QiMhVzCkiUjrmFBERkXu4PKihUqkc7g89bNgwDBs2DABw4cIFxMbGuq86IqIyYE4RkdIxp4iIiNzD5Y+fFCclJQVPPPEEGjZs6I7NERG5HXOKiJSOOUVEROQ6pwc10tPTMXz4cISFhSEmJgbvvfceZFnG1KlTUa9ePfz+++9YtGhRRdZKRFQq5hQRKR1zioiIyL2c/vjJ5MmT8euvv2L06NH4/vvvMWnSJGzcuBEqlQo//vgjOnXqVJF1EhHdFHOKiJSOOUVEROReTl+p8d1332HRokV46623sHbtWggh0KpVK6xbt44nYCJSBOYUESkdc4qIiMi9nB7UuHjxIpo2bQoAqFOnDgwGAx544IEKK4yIyFXMKSJSOuYUERGRezk9qCGEgEbz76dV1Go1fHx8KqQoIqKyYE4RkdIxp4iIiNzL6Tk1hBDo0aOH/UScn5+PAQMGQKfTObTbu3eveyskInISc4qIlI45RURE5F5OD2pMmzbN4fHAgQPdXgwRUXkwp4hI6ZhTRERE7lXmQQ0iIqVhThGR0jGniIiI3MvpOTWIiIiIiIiIiJSEgxpERERERERE5JE4qEFEREREREREHomDGkRERERERETkkco1qGE0Gt1VBxFRhWBOEZHSMaeIiIjKzuVBDVmW8corryA2Nhb+/v44efIkAOCll17CggUL3F4gEZGrmFNEpHTMKSIiIvdweVDj1VdfxeLFi/HGG29Ap9PZlzdr1gyffPKJW4sjIioL5hQRKR1zioiIyD1cHtT49NNP8dFHH2HEiBFQq9X25S1btsSRI0fcWhwRUVkwp4hI6ZhTRERE7uHyoMaFCxfQoEGDIstlWYbFYnFLUURE5cGcIiKlY04RERG5h8uDGvHx8di+fXuR5atWrULr1q1dLmDevHmoU6cODAYDOnbsiN27d5faPiMjAxMmTEB0dDT0ej0aNWqEDRs2uLxfIvJezCkiUjrmFBERkXtoXF1h6tSpSExMxIULFyDLMr7++mscPXoUn376KdatW+fStlasWIGkpCR88MEH6NixI+bMmYPevXvj6NGjiIiIKNLebDajZ8+eiIiIwKpVqxAbG4szZ84gODjY1W4QkRdjThGR0jGniIiI3ESUwc8//ywSEhJEeHi48PHxEV27dhXff/+9y9vp0KGDmDBhgv2xzWYTMTExYtasWcW2nz9/vqhXr54wm81lKVsIIURmZqYAINLT08u8DSWx2WwiOTlZ2Gy2qi7FLdgfZUtPTxcARGZmZlWXclPMKeXwtuOA/VE25hRzqiy87Thgf5TNk3KKyBO4fKUGANx2223YvHlzuQZTzGYz9uzZgylTptiXqVQqJCQkYOfOncWu8+2336Jz586YMGEC1qxZg/DwcNx///147rnnHCbZup7JZILJZLI/zsrKAlDwmVVZlsvVByWQZRlCCK/oC8D+KJ0n9YM5pRzeeBywP8rlSf1gTimHNx4H7I9yeUs/iJTC5UGNcePG4YEHHkD37t3LtePLly/DZrMhMjLSYXlkZGSJs36fPHkSP/74I0aMGIENGzbg+PHjeOyxx2CxWDBt2rRi15k1axZmzJhRZHlaWhrMZnO5+qAEsiwjMzMTQgioVC5PkaI47I+yZWZmVnUJTmFOKYu3HQfsj7Ixpwowp1zjbccB+6NsnpJTRJ7C5UGNtLQ09OnTB+Hh4Rg2bBhGjBiBVq1aVUBpRcmyjIiICHz00UdQq9Vo27YtLly4gDfffLPEk/CUKVOQlJRkf5yVlYW4uDiEh4d7xWdHZVmGJEkIDw/3ipBnf5RNp9NVdQlOYU4pi7cdB+yPsjGnbo45VZS3HQfsj7J5Sk4ReQqXBzXWrFmD9PR0rFy5EkuXLsXbb7+NJk2aYMSIEbj//vtRp04dp7YTFhYGtVqNS5cuOSy/dOkSoqKiil0nOjoaWq3W4dLIpk2bIiUlBWazudiA0Ov10Ov1RZarVCqvCEUAkCSJ/VEwb+qPp/SBOaU83nQcAOyPknlKH5hTyuNNxwHA/iiZN/SBSEnKdESFhITgoYcewrZt23DmzBmMHj0an332WbH3Wy+JTqdD27ZtsWXLFvsyWZaxZcsWdO7cudh1unbtiuPHjzt8Du3YsWOIjo7miCcROWBOEZHSMaeIiIjKr1zDhBaLBX/88Qd+++03nD59usjnOW8mKSkJH3/8MZYsWYLDhw/j0UcfRW5uLsaMGQMAGDVqlMPEV48++iiuXr2KiRMn4tixY1i/fj1mzpyJCRMmlKcbROTFmFNEpHTMKSIiorIr091Ptm7diqVLl+Krr76CLMsYMmQI1q1bhzvvvNOl7QwdOhRpaWmYOnUqUlJS0KpVK2zcuNF+Mj979qzD5VlxcXH4/vvvMWnSJLRo0QKxsbGYOHEinnvuubJ0g4i8GHOKiJSOOUVERFR+khBCuLJCbGwsrl69ij59+mDEiBEYMGBAsZ+xVKqsrCwEBQUhPT3daya2Sk1NRUREhFd8Po/9UbaMjAyEhIQgMzMTgYGBVV1OiZhTyuJtxwH7o2zMqcrBnFI29kfZPCWniDyFy1dqTJ8+Hffdd59XnMCIyDsxp4hI6ZhTRERE7uHyoMb48eMrog4iIrdhThGR0jGniIiI3MOpQY0hQ4Zg8eLFCAwMxJAhQ0pt+/XXX7ulMCIiVzCniEjpmFNERETu59SgRlBQECRJAgAEBgba/09EpBTMKSJSOuYUERGR+zk1qLFo0SL7/xcvXlxRtRARlRlzioiUjjlFRETkfi5PH3znnXciIyOjyPKsrCyXb0FGRFQRmFNEpHTMKSIiIvdweVBj27ZtMJvNRZYbjUZs377dLUUREZUHc4qIlI45RURE5B5O3/3kzz//tP//0KFDSElJsT+22WzYuHEjYmNj3VsdEZELmFNEpHTMKSIiIvdyelCjVatWkCQJkiQVe1mkj48P5s6d69biiIhcwZwiIqVjThEREbmX04Map06dghAC9erVw+7duxEeHm5/TqfTISIiAmq1ukKKJCJyBnOKiJSOOUVEROReTg9q1K5dGwAgy3KFFUNEVB7MKSJSOuYUERGRezk1qPHtt9+ib9++0Gq1+Pbbb0tte/fdd7ulMCIiVzCniEjpmFNERETu59SgxqBBg5CSkoKIiAgMGjSoxHaSJMFms7mrNiIipzGniEjpmFNERETu59SgxvWXSPJySSJSIuYUESkdc4qIiMj9VO7YSEZGhjs2Q0RUYZhTRKR0zCkiIiLXuTyo8frrr2PFihX2x/fddx9CQ0MRGxuLAwcOuLU4IqKyYE4RkdIxp4iIiNzD5UGNDz74AHFxcQCAzZs344cffsDGjRvRt29fPPPMM24vkIjIVcwpIlI65hQREZF7OH1L10IpKSn2k/C6devwn//8B7169UKdOnXQsWNHtxdIROQq5hQRKR1zioiIyD1cvlIjJCQE586dAwBs3LgRCQkJAAAhBGfqJiJFYE4RkdIxp4iIiNzD5Ss1hgwZgvvvvx8NGzbElStX0LdvXwDAvn370KBBA7cXSETkKuYUESkdc4qIiMg9XB7UeOedd1CnTh2cO3cOb7zxBvz9/QEAycnJeOyxx9xeIBGRq5hTRKR0zCkiIiL3cHlQQ6vV4umnny6yfNKkSW4piIiovJhTRKR0zCkiIiL3cHlQAwBOnDiBOXPm4PDhwwCA+Ph4PPXUU6hXr55biyMiKivmFBEpHXOKiIio/FyeKPT7779HfHw8du/ejRYtWqBFixb47bffEB8fj82bN1dEjURELmFOEZHSMaeIiIjcw+UrNSZPnoxJkyZh9uzZRZY/99xz6Nmzp9uKIyIqC+YUESkdc4qIiMg9XL5S4/Dhwxg7dmyR5Q8++CAOHTpUpiLmzZuHOnXqwGAwoGPHjti9e7dT6y1fvhySJGHQoEFl2i8ReSfmFBEpnbtzihlFRETVlcuDGuHh4di/f3+R5fv370dERITLBaxYsQJJSUmYNm0a9u7di5YtW6J3795ITU0tdb3Tp0/j6aefxm233ebyPonIuzGniEjp3JlTzCgiIqrOXB7UGD9+PB566CG8/vrr2L59O7Zv347Zs2fj4Ycfxvjx410u4O2338b48eMxZswYxMfH44MPPoCvry8WLlxY4jo2mw0jRozAjBkzOJkWERXBnCIipXNnTjGjiIioOnN5To2XXnoJAQEB+O9//4spU6YAAGJiYjB9+nQ8+eSTLm3LbDZjz5499u0AgEqlQkJCAnbu3Fniei+//DIiIiIwduxYbN++vdR9mEwmmEwm++OsrCwAgCzLkGXZpXqVSJZlCCG8oi8A+6N0ntIP5pSyeONxwP4ol6f0w105VRkZBTCnPA37o2ze0g8ipXB5UMNsNuOhhx7CpEmTkJ2dDQAICAgo084vX74Mm82GyMhIh+WRkZE4cuRIsev88ssvWLBgQbGXbBZn1qxZmDFjRpHlaWlpMJvNLtesNLIsIzMzE0IIqFQuX3ijOOyPsmVmZlZ1CU5hTimLtx0H7I+yVbecqoyMAphTnob9UTZPySkiT+H0oEZaWhpGjRqFH374AbIso3379vjiiy9Qv379iqzPQXZ2NkaOHImPP/4YYWFhTq0zZcoUJCUl2R9nZWUhLi4O4eHhCA4OrqBKK48sy5AkCeHh4V4R8uyPsul0uqouoVTMKWXytuOA/VE25lTpypJRAHPK07A/yqb0nCLyNE4Pajz33HPYv38/Xn75ZRgMBnz44YcYN24ctm7dWuadh4WFQa1W49KlSw7LL126hKioqCLtT5w4gdOnT2PAgAH2ZYWXb2k0Ghw9erTIDwV6vR56vb7ItlQqlVeEIgBIksT+KJg39UfpfWBOKZc3HQcA+6NkSu+Du3OqMjIKYE55IvZHubyhD0RK4vSgxubNm7F48WL07t0bAHDXXXehadOmMJlMxZ7knKHT6dC2bVts2bLFfisxWZaxZcsWPP7440XaN2nSBAcPHnRY9uKLLyI7Oxvvvvsu4uLiylQHEXkH5hQRKZ27c4oZRURE1Z3TgxoXL15Ey5Yt7Y8bNmwIvV6P5ORk1KlTp8wFJCUlITExEe3atUOHDh0wZ84c5ObmYsyYMQCAUaNGITY2FrNmzYLBYECzZs0c1i+85PHG5URU/TCniEjpKiKnmFFERFSduTRRqFqtLvJYCFGuAoYOHYq0tDRMnToVKSkpaNWqFTZu3Gif8Ors2bO8RIuInMacIiKlc3dOMaOIiKg6k4STZ1GVSoWgoCBIkmRflpGRgcDAQIcT5dWrV91fpRtlZWUhKCgI6enpXjOxVWpqKiIiIrziBxb2R9kyMjIQEhKCzMxMBAYGVnU5RTCnlMnbjgP2R9mYU5WDOaVs7I+yKT2niDyN01dqLFq0qCLrICIqN+YUESkdc4qIiMi9nB7USExMrMg6iIjKjTlFRErHnCIiInIvz79+i4iIiIiIiIiqJQ5qEBEREREREZFH4qAGEREREREREXkkDmoQERERERERkUcq86CG2WzG0aNHYbVa3VkPEZHbMKeISOmYU0REROXj8qBGXl4exo4dC19fX9xyyy04e/YsAOCJJ57A7Nmz3V4gEZGrmFNEpHTMKSIiIvdweVBjypQpOHDgALZt2waDwWBfnpCQgBUrVri1OCKismBOEZHSMaeIiIjcQ+PqCqtXr8aKFSvQqVMnSJJkX37LLbfgxIkTbi2OiKgsmFNEpHTMKSIiIvdw+UqNtLQ0REREFFmem5vrcFImIqoqzCkiUjrmFBERkXu4PKjRrl07rF+/3v648MT7ySefoHPnzu6rjIiojJhTRKR0zCkiIiL3cPnjJzNnzkTfvn1x6NAhWK1WvPvuuzh06BB+/fVX/PTTTxVRIxGRS5hTRKR0zCkiIiL3cPlKjVtvvRX79++H1WpF8+bNsWnTJkRERGDnzp1o27ZtRdRIROQS5hQRKR1zioiIyD1cvlIDAOrXr4+PP/7Y3bUQEbkNc4qIlI45RUREVH4uX6mxd+9eHDx40P54zZo1GDRoEJ5//nmYzWa3FkdEVBbMKSJSOuYUERGRe7g8qPHwww/j2LFjAICTJ09i6NCh8PX1xcqVK/Hss8+6vUAiIlcxp4hI6ZhTRERE7uHyoMaxY8fQqlUrAMDKlSvRrVs3LF26FIsXL8ZXX33l7vqIiFzGnCIipWNOERERuYfLgxpCCMiyDAD44Ycf0K9fPwBAXFwcLl++7N7qiIjKgDlFRErHnCIiInIPlwc12rVrh1dffRWfffYZfvrpJ/Tv3x8AcOrUKURGRrq9QCIiVzGniEjpmFNERETu4fKgxpw5c7B37148/vjjeOGFF9CgQQMAwKpVq9ClSxe3F0hE5CrmFBEpHXOKiIjIPVy+pWuLFi0cZusu9Oabb0KtVrulKCKi8mBOEZHSMaeIiIjcw+VBjZIYDAZ3bYqIqEIwp4hI6ZhTRERErnFqUCMkJASSJDm1watXr5arICKismBOEZHSMaeIiIjcz6lBjTlz5lRwGURE5cOcIiKlY04RERG5n1ODGomJiRVaxLx58/Dmm28iJSUFLVu2xNy5c9GhQ4di23788cf49NNP8ddffwEA2rZti5kzZ5bYnoiqB+YUESldReYUM4qIiKorl+9+cj2j0YisrCyHL1etWLECSUlJmDZtGvbu3YuWLVuid+/eSE1NLbb9tm3bMHz4cGzduhU7d+5EXFwcevXqhQsXLpSnK0TkpZhTRKR05c0pZhQREVVrwkU5OTliwoQJIjw8XKhUqiJfrurQoYOYMGGC/bHNZhMxMTFi1qxZTq1vtVpFQECAWLJkiVPtMzMzBQCRnp7ucq1KZLPZRHJysrDZbFVdiluwP8qWnp4uAIjMzMyqLqVUzCll8bbjgP1RtuqYU5WdUUIwp5SO/VE2T8kpIk/h8t1Pnn32WWzduhXz58/HyJEjMW/ePFy4cAEffvghZs+e7dK2zGYz9uzZgylTptiXqVQqJCQkYOfOnU5tIy8vDxaLBaGhocU+bzKZYDKZ7I8L//ohyzJkWXapXiWSZRlCCK/oC8D+KJ2n9IM5pSzeeBywP8rlKf1wV05VRkYBzClPw/4om7f0g0gpXB7UWLt2LT799FN0794dY8aMwW233YYGDRqgdu3a+OKLLzBixAint3X58mXYbDZERkY6LI+MjMSRI0ec2sZzzz2HmJgYJCQkFPv8rFmzMGPGjCLL09LSYDabna5VqWRZRmZmJoQQUKnK9WkiRWB/lC0zM7OqS3AKc0pZvO04YH+UrbrlVGVkFMCc8jTsj7J5Sk4ReQqXBzWuXr2KevXqAQACAwPttxy79dZb8eijj7q3upuYPXs2li9fjm3btpV4X/cpU6YgKSnJ/jgrKwtxcXEIDw9HcHBwJVVacWRZhiRJCA8P94qQZ3+UTafTVXUJTmFOKYu3HQfsj7Ixp1zjTEYBzClPw/4om6fkFJGncHlQo169ejh16hRq1aqFJk2a4Msvv0SHDh2wdu1al09qYWFhUKvVuHTpksPyS5cuISoqqtR133rrLcyePRs//PADWrRoUWI7vV4PvV5fZLlKpfKKUAQASZLYHwXzpv54Sh+YU8rjTccBwP4omaf0wV05VRkZBTCnPBH7o1ze0AciJXH5iBozZgwOHDgAAJg8eTLmzZsHg8GASZMm4ZlnnnFpWzqdDm3btsWWLVvsy2RZxpYtW9C5c+cS13vjjTfwyiuvYOPGjWjXrp2rXSAiL8ecIiKlc1dOMaOIiKi6c/pKjZMnT6Ju3bqYNGmSfVlCQgKOHDmCPXv2oEGDBjcd5S9OUlISEhMT0a5dO3To0AFz5sxBbm4uxowZAwAYNWoUYmNjMWvWLADA66+/jqlTp2Lp0qWoU6cOUlJSAAD+/v7w9/d3ef9E5D2YU0SkdBWRU8woIiKqzpwe1GjYsCGSk5MREREBABg6dCjee+891K5dG7Vr1y5zAUOHDkVaWhqmTp2KlJQUtGrVChs3brRPeHX27FmHS7Tmz58Ps9mMe++912E706ZNw/Tp08tcBxF5PuYUESldReQUM4qIiKozSQghnGmoUqmQkpJiPwkHBATgwIED9kmuPEVWVhaCgoKQnp7uNRNbpaamIiIiwis+n8f+KFtGRgZCQkKQmZmJwMDAqi6nCOaUMnnbccD+KBtzqnIwp5SN/VE2pecUkafx/FQgIiIiIiIiomrJ6UENSZIgSVKRZURESsGcIiKlY04RERG5l9NzagghMHr0aPvtvIxGIx555BH4+fk5tPv666/dWyERkZOYU0SkdMwpIiIi93J6UCMxMdHh8QMPPOD2YoiIyoM5RURKx5wiIiJyL6cHNRYtWlSRdRARlRtzioiUjjlFRETkXpwolIiIiIiIiIg8Egc1iIiIiIiIiMgjcVCDiIiIiIiIiDwSBzWIiIiIiIiIyCNxUIOIiIiIiIiIPBIHNYiIiIiIiIjII3FQg4iIiIiIiIg8Egc1iIiIiIiIiMgjcVCDiIiIiIiIiDwSBzWIiIiIiIiIyCNxUIOIiIiIiIiIPBIHNYiIiIiIiIjII3FQg4iIiIiIiIg8kqaqCyAiIiIiLyDLgBCAJAEq/t2MiIgqB884RERERFQ+ny8BGsUCGg3g5wcsW1bVFRERUTXBKzWIiIiIqOxkGfhoNvBAJ8BiAw6eAx4eDwwdyis2iIiowvFMQ0RERERlJ0TBT5SyDGjVQJs6wITuwHefAKnnqrg4IiLydrxSAyg4CatU//5LRERERM6RJOC308D+M0Dv5kBUEBDiB/z+XcGXwQ9o3QNIGAmo+aMnERG5F3+D37EDaNsW2L694N8dO6q6IiIiIiLPoVIBCxcCJgF8uRv4aDtQsxvQpGPB88ZcYOe3wDsPAVuXAVlXqrZeIiLyKtV7uFyWgccfAUQmMHMCkJUCjB8P/PUXr9ggIiIictbw4QVzaNx495Pzx4BNiws+hpKTDvz0JfDTSiAwFOh4F9D5bv7MRURE5aKIs8i8efNQp04dGAwGdOzYEbt37y61/cqVK9GkSRMYDAY0b94cGzZsKNuOVSogXAcMagt0rA/c1wFoEQoc/Bm4kgycPQyY8su2bSLyKlWWU0RETlBERqlUgFrtOEhRsxHw4Ezg6YXAvf8H1I4HIAqu1ti8BJj3BLBrHZCfW9BelgGbreDfsnLHNoiIyGNU+aDGihUrkJSUhGnTpmHv3r1o2bIlevfujdTU1GLb//rrrxg+fDjGjh2Lffv2YdCgQRg0aBD++usv13dusQDp6UCuqeCxQQs0CQe+eReY+xiw8Hlg1v3Apk+BUwcLBjiEKEdvicgTVWlOERHdhBIzSpZl2Gw2yIUDCxot0OxWYMxrwLDJQEQtQK0FrlwENi4A/vsgMHM00LZ+mW8LK8sybJ9/DuHrW/5by143MHKzMZIifS1hO+Vis7m23wqqw6V9upEsy/YvIqIbSUJU7W/pHTt2RPv27fG///0PQEFoxcXF4YknnsDkyZOLtB86dChyc3Oxbt06+7JOnTqhVatW+OCDD266v6ysLAQFBSE9PR3BwcFA3brA6dNAgAGIC4WIrwP0vhW4eAKSfMMJRFIBPv4F/za7FWjfB6gRU3CZpSwXveTSSbIsQwgBSQioJMmlbciyjNTUVEREREBVONnptTpkqEotyb5fSSpY1/FJp/tTalObreCvNk7ut6T+yEKCkFRleXkLtmu1QsgyJJUKKk3Jn7oqtS9leI+tVqu9PxqNxj39uUkd17++KO17oAz9ycjIQEhICDIzMxEYGOhi4Z6rynOqYKfXHdso+dgtDXOKOVUM5pTnq+yMAkrIqWs+++wzvPzyy9BoNLDZbHjhhRcwcOBAqFQqGI1GqNVq+Pj4QGOzQH3oF6j+2AQp7ey/G7Be+/lLANBpCr4HNLp/JxmVZcBiBFTqgklIJQn5RhMkUy70KhWkfDNgsgD5loJtxDcE/IKABq0Lfo7z8QdyswoGWqLrASGRkPW+SL2agYjISKhWrAAefBAwGmHTGjBGLMRn1uEwGAqmDhk+/N9Sly1bhgcffBBGoxEGgwELFy7E8MIGy5bZt1Psytcp8Vv96FFgyBDg0CEgPh74+mugcePS94sbcuq6/gi9AfInCyHdP9zl43rZsmUYO2YMTCYT9Ho9Fixa5LBPp/pz0yeL3++4ceNwyy234O+//8Ynn3yC4dc+6sScIiKgigc1zGYzfH19sWrVKgwaNMi+PDExERkZGVizZk2RdWrVqoWkpCQ89dRT9mXTpk3D6tWrceDAgZvus8hJ+OhRYPBg4PBhpMfEoGdeHk6r1fA36DHvpaeRUD8SqrSzUF38B+rsq0W2J+v9YIEB6hPHIV/IgJxlgnX4cMgtWkCbdgYaIWALjwP0PjCbzZDys6HPvgzofSGHx+GPP/7AqlWr0DdIj24qAJdzABkwDxsGqXED6DJTIel9IEfUhk22wWa1QXPlPDSyFXJoDISPH65eTYe/RoLhz92Qtu+AnJwOi0aHLw33wxRaA4FaMxp3jUJ8uyBYLGYIUz5S/9yNX3buwu8X0qHVaXHfvfehVVwYtFYTxMUrEKtWwwIJsl4HzeAhkFq1gkqSIMs22KxWyAC0Wh0O7AeWL5cghBl6g8DgwSq0aqWB6nIa5EWLYLt6FXJ0NLT33w9VWDj27d+HVStXQghArdViyJDBaN2qNSBkWCwWWGUBi9mMAH9/SAf2w7pyJVSBBsCgw4b0bthu7IKhQ2W0aJwD9eXzUOt0sEXVhyRJsFrNkK6mQG3KBYIjgYBQQMg49fXXqHX+GLRWK8zJWbjQuTNqDhoIXE2G2pgDBEUAgTWwd6+Mb7/JR8uwMwDUqHN7Q7RurYLNZgV274D6j1+BjDwgxwQMGwZL06bQXDoFtVoNW3QDSGp1QduMVKhzM/DPpStY8NU6REVF48qVy3iqfTzCT52C7WIGZIuEpeqhyA6JxYBuVxEXHwqERAEALGYTNCknoZZQ0DetDjabFSLrCjSHDkDasQsiJQPQamC57z/QRPpDDQFbZF3s//sQVqxYgRANUDc4HhnmPjh4MQ6AhPHjJHSudRywWYBzacDCJUBmLnA+s9QftK5XHU/CisipRfOAZR8AAXrY8q34PCMfewGoNRo8NjABdWvVgoiqB1mjhSwLqPIzoc68DPgEQITFwmqTgb17oPl+NSQIiKv5kO9/AHKbNpDys6HJTAX0vhDhcbBarQAATdpZSDYLRHgcfjvwFz7//DN0UQFDQ32hNlkhMoywjRoF0bYt1JfPQWU1Q9SIhWzwhWyTIZnyoElPBrR62CJqITMjE/7+/tDs2gbVz1shUjNhtUj4XD8Kx/VNcEuNi2jXWYt6XevBZrVBFgKnf/8Ze3dsx9G0TGRYgeHDh6PVLU2hu3IB0tmzkFd9B5tsg6zXQxo2DKo2baGSCgZ8bDa5IGc0auzbA3z2OSDbZOgMMoYNU6FNGxVUaZcgPvoYttQ0iJoxUI8eDVV4JPbs+QNfLF0GWZah0+kwdOh/0LZtW0AA1mt/oczLz0dggD9Ue/dCXroMCNZDGAxYnd4D2/O74oEHgFbxOQXnD60eIrp+wfi3TQYun4fKlAcREgUpIBgQwKkvlyPuzGFobDLMyRk43/U21LnvXuDyRaiMORDBEZACQ/HHH8BXXxrRMuwkhKRGozsao227gh++sfMnqHZth7iaCynXDDwwAtbmzaFKOQGVSgUR2xiSSipoe/USVLkZOJKSho+Wr0Z0dDTS0i7hmc4tEX7iJMT5q7DZVPhMGoHM0JoYlJCO2s1CIYVEAgBsNhtU549CklQQMQ0gaTQFvwBkXIb6773Ath3ApXRAo4VtxP1QRQRAkgARXR97DxzA5198gRo6CfVCmuGqqR/+To6FPafijgGyDTh3GVi4GEjPBi5mM6dKUBUZBZQ8qCHLMrp164aEhATnOyEEWuIquiMFgcICleT8qu5kRcElzDYZuGrRwCxLsAUEIVRjgdZmRYY+BHlCB70OkCxGhJozYZPUuKQNBGQBSaVCiDUHBtmCHEMQjLaCjthUKqj0BkgAhCjIJtu1O+6ptXrIsoAxzwpIAmq1DLXeAJVaDdlqgTAaIUsSoNFBrdNB2GyQIWAymaBSq6HR+0CWJFiM+dBpC84BQlJBYzBACEBYzBD5+bBqNAi3ZkMvm3FV5Y90BEKnk6ETZoRbMmFTa5HmEwYAsFisCLNmw0c2I8MQDKPGAJtNhmQxIsqSBRkSUuGPfAAaHx/UsObAR5iRpQ9GvtYXJrMMyWpGtDUdVqFBqm8U9AYJZrMJIeYs+JrzkQsd8q0q2AIDISSBSHM6JEmNq0HRAACTyYQgczb8ZBMuGmWkmSUYDHqoAdRBDrSyjKsmHQQkpOtDEKw2IVidD4tfIPINwZBlGWaTEZHGy1Cr1LgaFAOo1DCZTPAzZcPfnANzvg35Rhk2jQbm0FBEWjOhUquQGRyLrJxcXL1yBSGSFcFCRpopDv9cjcW5fzQY0FeFVqGHCgYzrpqAr74G0jKBU1eZU0RVpEoHNS5evIjY2Fj8+uuv6Ny5s335s88+i59++gm//fZbkXV0Oh2WLFniMDL8/vvvY8aMGbh06VKR9iaTCSaTyf44KysLcXFxuHLliuNJ2GJBVGwsnnjiiRLr9RcWNEYGmiALetgQhXxowY+jkOcSF9IhFm4v+AtSZuZN/8KQkZGBGjVqVKuTcJXnVGAg0Kc1VLc2cHPPiDyDOHMZ4tNfmVMlqIyMApz/ecpms6FLly7o0aMHDAYDbDYbbDYb/Pz8nPr4gE5YYUBBGwlAAMxQQSAPGshQARDQwYYAWGGFhBxoUTgGEgwztLAhG1oISDDAhhowoRZyIUEgEzr4wAYDbIhFLvSQYYEKOtigLqkgIieIYykQK3Yzp4iqiNff/WTWrFmYMWNGkeVpaWkwm832x7Iso0mTJqVuK0fSYg/CsQfhAACVkBEFI1rgKhohCzKAq9Db20fACA1kpEEPy7XTpQFWhMIME9S4cl3bcBihhYzL0MN8ra3+2snYDBUuw2BvGwYjdJBxFXoYr7XVwYYwmGCFCmkwAJKEgMia8M++BI3FiFy/MFj0fgAAtdWEgKwUyCoNsoJj7dv1y06F1pKPPL8aMOv9nXp9K4NfThq05jzk+YXCrA8AAKhsZgRmJkOo1MgMrmlv65tzGTpzLvJ9Q2AyBF5ra0Vg5gUISUJmSC17W5/cK9CbcmD0CYbRJwgAIMk2BGWcBwBkhNQquJQQgE9eOvTGLBgNQTD6BhdsQMgITj93rW1cwceSABjyMmAwZsJkCEC+b6h9f8FXzwAAMoNrQqiuvcf5mfDJz4BZ7488vxr2tkHpZyEJgaygWMjXLrfVG7Pgk5cOs84Pef5h/7bNOA9JtiErKBqyWgcA0Jmy4Zt7FRatD3IDInDqb0DIQIfaFyDZrLAmX4WwCVjNWmS3bVuwodTUm56EMzMzS32eyqbUnDIaofcNgV+GGWofNWwWgZP+/35fxSAfEgRSYYAVKkgAfGFBMCwwQo106OxtI5EPNQQuwwDLtSmVfGBF8LVMunpDJmkg48p1mWSAFSEwwwwVrtyQSdprmWS6Lr9CYYLlhvyqcS2/0qGDUdIiILIm1BYjArIvQVZrkRUUY29bXCaprWYEZCUXya+q5lLWMtMK2t6QaZeOmSBkoFlkCiQhw5KWBQjAovFHTvt2gCyYU1XIlZ+ndDodfvzxR/syrVaLlStX2j/KVXhFmBACsizDarXCaDQCe/ZAt2QJZJsNslaLrKFDYWnSBH5+flCpVJBlGfn5+cjMzIRarUZgYOC1K7Ns+OSTT6BSqRCRm4sEiwVaIWDS65HRqRMO16qFsLAwSJIEM4BTV6/iT4sFwcHBMBgMgBCw5uUgJ/kMIkU+Qn75GVaLDRqVhNyacfCNDIFNZUCaKhzp+b6oW1eGyM9BYP5V5JqtOGlWQ9hkqNUqRKvMCPPTI98/HNaLlwAhYNFoIEJqQA1A7e8LFUTBFWkAoNEg44pAfpYMSRJQqyzwC9IiIFAFjWyDlHyh4PXQ6QE/f6hsVqj9/XDh/HmoJAk+gUFQSRKMOVmIioiALBdc6QaVBoCAVshA8kXYVBICRR60sgU5ki/Oi1ioJBlRQXkIykmFrNYi+1pOWa1WBOakQmc1Itc/HFZ9wYCUdDUNwbYsCKiQJRVksjU4GIG5l6GzGpHnFwqL3h9Xr8rQS0ZEWy5Bhhrn1DUREiJgs1oRkJ0GgzUfuRp/mKAtuArFR48aOamAJCE9OA7i2uvjb8qEjzkXGWofZEh6qNVqqISMWNNVAAJXNCGAJMGmUsHXZoKfJRcm3wDkGYIgCxmy1YqInEuQJOBKYAwgqQoG2ExZ8DNlw6jxQa7KB+LaNiKNlwEAVwKikWcyQaVSwd9qRIAlFzmqQKTKEUg7B5iMEvrccrLgKuMjZwAZsFgNyOPPU0RVpkoHNcLCwqBWq4v8VeDSpUuIiooqdp2oqCiX2k+ZMgVJSUn2x4V/WQgPDy9yueS+fftw4MAB+Pj42JcdP34cKpUKZrMZVqsVarUaev2/P/jn5eQAHTpAysyEFkAkALOfH6x798Ks1ULS61H4I2BeXh4AwGIwQKNSIfzaQIosy/jDZkOw2YyQa23zg4Igdu+GyWCARqNBJApOMmazGRaVCmqDAUEAAmQZFy5cgF9wMEytW0OTn48IABaVChlB4eik2w6jyQeSAA4elGA2G2G02NDhzjuQm5MDq8UClUqFgAB/bPt5O3wNeqhatoLOaIRRr4dVq4VWq4Vm106oVWpYbQU1yAD0eh+0bgkYjRJ0OhO0Oht0OjV27tRBc1c/WE+fgVmjgWzQwycmFvj6K7Ro0RJCCGi1OggJUEkq7N3zOwDAaDTCYhMw5ucjLDQY6patYBICGVodVBIgm1VoZf4dOj3w229GGCUUfCYXgEqSYDKbkGm1QaVRQ6fVQSdJsFotyG7TFkadHnqTCRqLGRabDTj4J7JkYW+rgYTmzWWoVEZotIDJrIdapcKB/RKsFhOybr0Vkk2G3mSGzmQE9Hrk/fYbUiUJeoMeGkkFlSTBbDEj22JFtkrCrbfehtzsbDRr1gwnjv+DHzVaBJotUFstUFmtyNb4op3uV/j4qvHLDj101663zTfmI00W0Oq00Ko10Fzbbo7JgtyeCdDn5EJrzIcEID8oEGnbfobWoINapULrFi1hsVggywKyOAbADyajBFM+YDBIyMwEJMjQBAUBRiO0AHyAgr8sRETc9CSs0+lKfd4bVXlOBQYCW/YA640AADWASK0WDXx9odZooFKp8PfffyNUpbJP3iZJEiwaDdQAwgBYTCbob7kF2txcSCjIKauPD/IOH4akVsOs0UACUAOAxWIBANg0GsiSBD9ZRqfmzWG1WHAoLw9qmw0+AGqiIOuMf/8Nm1YLoVLBH4DvtUnkJEmC+dq8ECHXPtsdEhQEXXw81EYjwgDYJAlZ/mHoGLwfUOkhCYFftpsgy1ZYrDJ63TME+Xn5sFktkCQJPgYD1qxdB6NGhcBWreBnMsKq1sCm0UIy6JG/a1fBJdvXarAJQK3WoHs3A4xGFdRqK9QaGwwGFTZvsiBwQD/g1GnIkgSbjy9UtWoib9VX6NmrN2w2K9RqDaBSQ6NRY+P6ddc+5maFzSaQk5eN0MAgBLZqBZvVCqOPDyS9BlarCj30v0CrB1Z/k4scABqtFioUjCfYbDZcsV277FythloCZKsF6m7dkK3TQyPb4GOxwGKzIW/7dhihsrdVAeh/lw42mwyNFpCFCmoVsHaNGbLNAk3vnrAICRqrDX4mI4ROi/QtPyIPqoLvFUmC6loNRpsMIQGjRo1Efm4+6jVsgLMnTuKrjKvwFQI+VitUVivyVHrcHrQDPv4qrPzSCs21iLBYrUiWBVRqNdQqVcF2ZRlGiwW2uwdAbTTC12iEBMDia0DKxs1QabRQScB9994Di9UGi8UKWWwGoEd+roSsKxIMBgknTwISBLT16gJGE7Q2Gb5mK3OqBJWRUYDzP08BwOOPP45x48bZ53v45JNPSt22XdOmwP33l2nun3Pnztn3+T+9Hp98/DH+M3SoS3P/pKWlITw8HCpDFDBunH1OjXHiE3xuHQqDAfjkE+CWgf+ut2LFiiJ9bTV0aOGT9u3YV7576A37Ba6dku0c/th/7Bhw333/zqmxciXQqBH+KGa/ne8bet12r+vPypUQY8dBMhmRDwMexydYgaFFLioIQVGB/24QNn9/qK+dI4IA2LRaqHNy7BsIuNafpiX1B/921rfYzgJ+xdSwbsUKPPTQQ4iPj8fhv//GFasVaovF3jYfBgQhE3qDCpmZQI1i3nLf6x9ce9F9jUb7z+jX12GQZQQFBRUMtEECkIlrPy0V6Y/+Wn/0APwLn2ROEVU+UcU6dOggHn/8cftjm80mYmNjxaxZs4pt/5///EfcddddDss6d+4sHn74Yaf2l5mZKQCI9PT0Is8tXbpUGAwGAUAYDAaxdOlS5zqxdKkQBoMQQMG/zq533T6HAeLavVVc2obNZhPJycnCZrM51GHVGsRIzdISN1dqX13oT4lNjxwRIj6+4In4+ILHN9tvKf3Jh0EMw1JXX14hhBC/TJhgf23zAfHLhAmu9cXF1+TfVZYKX19f0b59e+Hr61uw3/L25yZ1XP/6ajQjhVZrdVt/hBAiPT1dABCZmZkuFO35qjynHI5trRip0TCnmFPMqRJUx5yq7IwSovSfpwprsFqtBcdJJSnPPh2O64IFQlitQths1//X9f3ebGXh5Le61erSfovrz7LPrcJHbyvLacBeqKzXCwEU/FvCBtydU0IIYbFYxIULF4TFYnFP7jKniLxKlQ9qLF++XOj1erF48WJx6NAh8dBDD4ng4GCRkpIihBBi5MiRYvLkyfb2O3bsEBqNRrz11lvi8OHDYtq0aUKr1YqDBw86tb8KOwk7cdIqedVr+7RYXN5GVZ6EnWrqhpOwsFqFzWIr68tbsBmLRVhNpoLXuLR2pfWlDO+xw0n4um2Uqz83qeP619fd/amuJ2FF5JTDsc2ccrU/zKmSMac8X2VnlBA3/3nK0xQ5rit9/2WO5xK2V3x/yr0fJzfg7uO6QnKXOUXkNap8To2hQ4ciLS0NU6dORUpKClq1aoWNGzciMrJghvWzZ8863E6vS5cuWLp0KV588UU8//zzaNiwIVavXo1mzZq5pR6Xbo/ouGLl7/Mmddxsq6Xu14WaSm2qLjr1lkv9vda2vK9QabdHLGZ3ZXiypFVU9q/rt1Gu/tykDqdfX3d+33k5ReSUC8e2M9twfVXm1M02zpxyvg7mlHspIqOoXCrrW73c+3FyA+7OqZK2wZwiIqCK735SFUq7r7oncrgPuReEKvujbLwFWeVgTikb+6NszKnKwZxSNvZH2ZhTRO7l+alARERERERERNUSBzWIiIiIiIiIyCNV+Zwala3w0zZZWVlecfmaLMvIzs6GwWBgfxTI2/qTlZUF4N/jiCoGc0rZ2B9lY05VDuaUsrE/ysacInKvajeoceXKFQBA7dq1q7gSIs915coVBAUFVXUZXos5RVR+zKmKxZwiKj/mFJF7VLtBjdDQUAAFM4F7Q4hkZWUhLi4O586d84qJhtgfZcvMzEStWrXsxxFVDOaUsrE/ysacqhzMKWVjf5SNOUXkXtVuUKPwkrWgoCCvCMVCgYGB7I+CeVt/vOHSTyVjTnkG9kfZmFMViznlGdgfZWNOEbkHjyQiIiIiIiIi8kgc1CAiIiIiIiIij1TtBjX0ej2mTZsGvV5f1aW4BfujbOwPlYW3vc7sj7KxP1QW3vY6sz/Kxv4QUWkkwXsJEREREREREZEHqnZXahARERERERGRd+CgBhERERERERF5JA5qEBEREREREZFH8opBjXnz5qFOnTowGAzo2LEjdu/eXWr7lStXokmTJjAYDGjevDk2bNjg8LwQAlOnTkV0dDR8fHyQkJCAf/75pyK74MCV/nz88ce47bbbEBISgpCQECQkJBRpP3r0aEiS5PDVp0+fiu6GnSv9Wbx4cZFaDQaDQ5uqfH9c6Uv37t2L9EWSJPTv39/epirfm59//hkDBgxATEwMJEnC6tWrb7rOtm3b0KZNG+j1ejRo0ACLFy8u0sbV47G6YE4xp5hTrmNOVS7mlHJzypsyCmBOMaeI3Ex4uOXLlwudTicWLlwo/v77bzF+/HgRHBwsLl26VGz7HTt2CLVaLd544w1x6NAh8eKLLwqtVisOHjxobzN79mwRFBQkVq9eLQ4cOCDuvvtuUbduXZGfn6+4/tx///1i3rx5Yt++feLw4cNi9OjRIigoSJw/f97eJjExUfTp00ckJyfbv65evVrhfSlLfxYtWiQCAwMdak1JSXFoU1Xvj6t9uXLlikM//vrrL6FWq8WiRYvsbaryvdmwYYN44YUXxNdffy0AiG+++abU9idPnhS+vr4iKSlJHDp0SMydO1eo1WqxceNGextXX6PqgjnFnGJOlQ1zqvIwp5SbU96UUWXpD3OKOUV0Mx4/qNGhQwcxYcIE+2ObzSZiYmLErFmzim3/n//8R/Tv399hWceOHcXDDz8shBBClmURFRUl3nzzTfvzGRkZQq/Xi2XLllVADxy52p8bWa1WERAQIJYsWWJflpiYKAYOHOjuUp3ian8WLVokgoKCStxeVb4/5X1v3nnnHREQECBycnLsy6ryvbmeMyfhZ599Vtxyyy0Oy4YOHSp69+5tf1ze18hbMaccMacqDnOKOVVWzClHSsopb8ooIZhTzCki9/Poj5+YzWbs2bMHCQkJ9mUqlQoJCQnYuXNnsevs3LnToT0A9O7d297+1KlTSElJcWgTFBSEjh07lrhNdylLf26Ul5cHi8WC0NBQh+Xbtm1DREQEGjdujEcffRRXrlxxa+3FKWt/cnJyULt2bcTFxWHgwIH4+++/7c9V1fvjjvdmwYIFGDZsGPz8/ByWV8V7UxY3O3bc8Rp5I+ZUUcypisGcYk6VFXOqKKXklDdlFMCcAphTRBXBowc1Ll++DJvNhsjISIflkZGRSElJKXadlJSUUtsX/uvKNt2lLP250XPPPYeYmBiHIOzTpw8+/fRTbNmyBa+//jp++ukn9O3bFzabza3136gs/WncuDEWLlyINWvW4PPPP4csy+jSpQvOnz8PoOren/K+N7t378Zff/2FcePGOSyvqvemLEo6drKyspCfn++W719vxJwqijlVMZhTzKmyYk4VpZSc8qaMAphTAHOKqCJoqroAcp/Zs2dj+fLl2LZtm8OEUMOGDbP/v3nz5mjRogXq16+Pbdu2oUePHlVRaok6d+6Mzp072x936dIFTZs2xYcffohXXnmlCisrnwULFqB58+bo0KGDw3JPem+I3IE5pVzMKaICnp5T3ppRAHOKiIrn0VdqhIWFQa1W49KlSw7LL126hKioqGLXiYqKKrV94b+ubNNdytKfQm+99RZmz56NTZs2oUWLFqW2rVevHsLCwnD8+PFy11ya8vSnkFarRevWre21VtX7U56+5ObmYvny5Rg7duxN91NZ701ZlHTsBAYGwsfHxy3vtzdiTv2LOcWcqmjMqbJhTv1LaTnlTRkFMKcA5hRRRfDoQQ2dToe2bdtiy5Yt9mWyLGPLli0OI9TX69y5s0N7ANi8ebO9fd26dREVFeXQJisrC7/99luJ23SXsvQHAN544w288sor2LhxI9q1a3fT/Zw/fx5XrlxBdHS0W+ouSVn7cz2bzYaDBw/aa62q96c8fVm5ciVMJhMeeOCBm+6nst6bsrjZseOO99sbMacKMKeYU5WBOVU2zKkCSswpb8oogDkFMKeIKkRVz1RaXsuXLxd6vV4sXrxYHDp0SDz00EMiODjYfuuqkSNHismTJ9vb79ixQ2g0GvHWW2+Jw4cPi2nTphV7C7Lg4GCxZs0a8eeff4qBAwdW6m2uXOnP7NmzhU6nE6tWrXK4jVV2drYQQojs7Gzx9NNPi507d4pTp06JH374QbRp00Y0bNhQGI1GxfVnxowZ4vvvvxcnTpwQe/bsEcOGDRMGg0H8/fffDn2uivfH1b4UuvXWW8XQoUOLLK/q9yY7O1vs27dP7Nu3TwAQb7/9tti3b584c+aMEEKIyZMni5EjR9rbF96C7JlnnhGHDx8W8+bNK/YWZKW9RtUVc4o5xZwqG+ZU5WFOKTenvCmjytKfQswp5hRRSTx+UEMIIebOnStq1aoldDqd6NChg9i1a5f9uW7duonExESH9l9++aVo1KiR0Ol04pZbbhHr1693eF6WZfHSSy+JyMhIodfrRY8ePcTRo0croytCCNf6U7t2bQGgyNe0adOEEELk5eWJXr16ifDwcKHVakXt2rXF+PHjKzUUXenPU089ZW8bGRkp+vXrJ/bu3euwvTCux5oAAA+bSURBVKp8f1z9Xjty5IgAIDZt2lRkW1X93mzdurXY753CPiQmJopu3boVWadVq1ZCp9OJevXqOdwjvlBpr1F1xpxiTjGnXMecqlzMKeXmlDdllBDMKeYUkXtJQghRsdeCEBERERERERG5n0fPqUFERERERERE1RcHNYiIiIiIiIjII3FQg4iIiIiIiIg8Egc1iIiIiIiIiMgjcVCDiIiIiIiIiDwSBzWIiIiIiIiIyCNxUIOIiIiIiIiIPBIHNYiIiIiIiIjII3FQwwWSJGH16tUAgNOnT0OSJOzfv79Ka6oOpk+fjlatWpVp3ZEjR2LmzJnuLaiSVfb33ejRozFo0CD742HDhuG///1vhe2P3Is5VTWYU8wpch5zqmowp5hTRN6qWg5qjB49GpIkFfnq06eP09uIi4tDcnIymjVrBgDYtm0bJElCRkZGqes5204prn99/Pz80LBhQ4wePRp79uypsP0VnnDK68CBA9iwYQOefPJJt2xPCW78vqsML774Il577TVkZmZW2j6JOeUK5pSyMKeqD+aU85hTysKcIvIu1XJQAwD69OmD5ORkh69ly5Y5vb5arUZUVBQ0Gk0FVlk5hBCwWq0lPr9o0SIkJyfj77//xrx585CTk4OOHTvi008/rcQqXTd37lzcd9998Pf3r9D9mM3mCt3+9ari+65Zs2aoX78+Pv/880rbJxVgTv2LOVU+zCmqKMypfzGnyoc5RURlVW0HNfR6PaKiohy+QkJC7M//888/uP3222EwGBAfH4/Nmzc7rH/9ZWunT5/GHXfcAQAICQmBJEkYPXp0mer6/fff0bNnT4SFhSEoKAjdunXD3r177c8/+OCDuOuuuxzWsVgsiIiIwIIFCwAAsixj1qxZqFu3Lnx8fNCyZUusWrXK3r7wrxvfffcd2rZtC71ej19++aXEmoKDgxEVFYU6deqgV69eWLVqFUaMGIHHH38c6enp9na//PILbrvtNvj4+CAuLg5PPvkkcnNz7c/XqVMHr7zyCoYPHw4/Pz/ExsZi3rx5Ds8DwODBgyFJkv1xoc8++wx16tRBUFAQhg0bhuzs7BJrttlsWLVqFQYMGOCwvE6dOpg5cyYefPBBBAQEoFatWvjoo48c2hw8eBB33nknfHx8UKNGDTz00EPIycmxP194OeFrr72GmJgYNG7c2P798OWXX9pfg/bt2+PYsWP4/fff0a5dO/j7+6Nv375IS0uzb+tm7/eNbrxcMj09HSNGjEB4eDh8fHzQsGFDLFq0yN7+3Llz+M9//oPg4GCEhoZi4MCBOH36tMPrlJSUhODgYNSoUQPPPvsshBBF9jtgwAAsX768xLqoYjCnmFPMKeaU0jGnmFPMKeYUUZUT1VBiYqIYOHBgic/bbDbRrFkz0aNHD7F//37x008/idatWwsA4ptvvhFCCHHq1CkBQOzbt09YrVbx1VdfCQDi6NGjIjk5WWRkZBS77a1btwoAIj09vdjnt2zZIj777DNx+PBhcejQITF27FgRGRkpsrKyhBBC7NixQ6jVanHx4kX7Ol9//bXw8/MT2dnZQgghXn31VdGkSROxceNGceLECbFo0SKh1+vFtm3bHGpo0aKF2LRpkzh+/Li4cuVKsfVc3+fr7du3TwAQK1asEEIIcfz4ceHn5yfeeecdcezYMbFjxw7RunVrMXr0aPs6tWvXFgEBAWLWrFni6NGj4r333hNqtVps2rRJCCFEamqqACAWLVokkpOTRWpqqhBCiGnTpgl/f38xZMgQcfDgQfHzzz+LqKgo8fzzzxdbsxBC7N27VwAQKSkpDstr164tQkNDxbx588Q///wjZs2aJVQqlThy5IgQQoicnBwRHR1t39eWLVtE3bp1RWJion0biYmJwt/fX4wcOVL89ddf4q+//rJ/PxS+7ocOHRKdOnUSbdu2Fd27dxe//PKL2Lt3r2jQoIF45JFHnH6/b3wPrv++E0KICRMmiFatWonff/9dnDp1SmzevFl8++23QgghzGazaNq0qXjwwQfFn3/+KQ4dOiTuv/9+0bhxY2EymYQQQrz++usiJCREfPXVV/b9BwQEFDk+vvvuO6HT6YTRaCzxNSf3Yk4xp5hTzCmlY04xp5hTzCkiJai2gxpqtVr4+fk5fL322mtCCCG+//57odFoxIULF+zrfPfdd6WG4c1OroWcbVfIZrOJgIAAsXbtWvuy+Ph48frrr9sfDxgwwH6yMxqNwtfXV/z6668O2xk7dqwYPny4Qw2rV6++6f5LOgnn5+cLAPY6xo4dKx566CGHNtu3bxcqlUrk5+cLIQpOgH369HFoM3ToUNG3b99S9zdt2jTh6+vrcGJ65plnRMeOHUus+5tvvhFqtVrIsuywvHbt2uKBBx6wP5ZlWURERIj58+cLIYT46KOPREhIiMjJybG3Wb9+vVCpVPYTemJiooiMjLSfyIT49/vhk08+sS9btmyZACC2bNliXzZr1izRuHHjEusu7v0u7ftuwIABYsyYMcVu67PPPhONGzd2eA1MJpPw8fER33//vRBCiOjoaPHGG2/Yn7dYLKJmzZpFTsIHDhwQAMTp06dLrJ3ciznFnCrEnGJOKRVzijlViDnFnCKqSp7/AcYyuuOOOzB//nyHZaGhoQCAw4cPIy4uDjExMfbnOnfuXCl1Xbp0CS+++CK2bduG1NRU2Gw25OXl4ezZs/Y248aNw0cffYRnn30Wly5dwnfffYcff/wRAHD8+HHk5eWhZ8+eDts1m81o3bq1w7J27dqVuU5x7ZI6SZIAFEwi9eeff+KLL75waCPLMk6dOoWmTZsCKPo6du7cGXPmzLnp/urUqYOAgAD74+joaKSmppbYPj8/H3q93l7f9Vq0aGH/vyRJiIqKsm/r8OHDaNmyJfz8/OxtunbtClmWcfToUURGRgIAmjdvDp1OV+q2r297/bLr63bm/S7No48+invuuQd79+5Fr169MGjQIHTp0gVAwXty/Phxh9cNAIxGI06cOIHMzEwkJyejY8eO9uc0Gg3atWtX5JJJHx8fAEBeXp5TdZF7MKeYU4X1M6eYU0rFnGJOFdbPnGJOEVWVajuo4efnhwYNGlR1GUUkJibiypUrePfdd1G7dm3o9Xp07tzZYfKkUaNGYfLkydi5cyd+/fVX1K1bF7fddhsA2D+ruH79esTGxjpsW6/XOzy+/kTjqsOHDwMA6tata9/vww8/XOzM2LVq1SrzfgpptVqHx5IkQZblEtuHhYUhLy8PZrO5yMnS1W0Vp6TX7vptF/4AcOOy6/flzPtdmr59++LMmTPYsGEDNm/ejB49emDChAl46623kJOTg7Zt2zr8YFQoPDzcqe0Xunr1apnWo/JhTjGnnN1WcZhTVBmYU8wpZ7dVHOYUEblDtR3UKE3Tpk1x7tw5JCcnIzo6GgCwa9euUtcpDHqbzVaufe/YsQPvv/8++vXrB6BgYqLLly87tKlRowYGDRqERYsWYefOnRgzZoz9ufj4eOj1epw9exbdunUrVy2lmTNnDgIDA5GQkAAAaNOmDQ4dOnTTH2xufB137dpl/6sDUHDCKu9rCMB+H/ZDhw65dE/2pk2bYvHixcjNzbWfaHfs2AGVSoXGjRuXu64bOfN+30x4eDgSExORmJiI2267Dc888wzeeusttGnTBitWrEBERAQCAwOLXTc6Ohq//fYbbr/9dgCA1WrFnj170KZNG4d2f/31F2rWrImwsLAy9JIqAnPq5phT7sGcorJiTt0cc8o9mFNE1Vu1vfuJyWRCSkqKw1dh+CUkJKBRo0ZITEzEgQMHsH37drzwwgulbq927dqQJAnr1q1DWlqaw+zOxTl48CD2799v/zpw4AAAoGHDhvjss89w+PBh/PbbbxgxYoT9UrXrjRs3DkuWLMHhw4eRmJhoXx4QEICnn34akyZNwpIlS3DixAns3bsXc+fOxZIlS1x9mQAAGRkZSElJwZkzZ7B582bce++9WLp0KebPn4/g4GAAwHPPPYdff/0Vjz/+OPbv349//vkHa9asweOPP+6wrR07duCNN97AsWPHMG/ePKxcuRITJ060P1+nTh1s2bIFKSkpDjOBuyo8PBxt2rQpdRby4owYMQIGgwGJiYn466+/sHXrVjzxxBMYOXKk/fJHd3L2/S7J1KlTsWbNGhw/fhx///031q1bZ/+hZsSIEQgLC8PAgQOxfft2nDp1Ctu2bcOTTz6J8+fPAwAmTpyI2bNnY/Xq1Thy5Agee+wxZGRkFNnP9u3b0atXL7f0mZzHnHIec4o5xZyqGswp5zGnmFPMKaIKUmWzeVShxMREAaDI1/UTDh09elTceuutQqfTiUaNGomNGzeWOsGQEEK8/PLLIioqSkiS5DC78/UKJ5W68UutVgshCmaZbteunTAYDKJhw4Zi5cqVonbt2uKdd95x2I4sy6J27dqiX79+RfYhy7KYM2eOaNy4sdBqtSI8PFz07t1b/PTTTw41ODO51vU1GgwGUb9+fZGYmCj27NlTpO3u3btFz549hb+/v/Dz8xMtWrSwTxYmRMGkUjNmzBD33Xef8PX1FVFRUeLdd9912Ma3334rGjRoIDQajahdu7YQomBiq5YtWzq0e+edd+zPl+T9998XnTp1clhW3GvZsmVLMW3aNPvjP//8U9xxxx3CYDCI0NBQMX78ePtM6EIUP9t7cd8Pxb3OixYtEkFBQfbHzrzfpX3fvfLKK6Jp06bCx8dHhIaGioEDB4qTJ0/a101OThajRo0SYWFhQq/Xi3r16onx48eLzMxMIUTBRFYTJ04UgYGBIjg4WCQlJYlRo0Y59C8/P18EBQWJnTt3Fv9CU4VgTjGnrsecYk4pEXOKOXU95hRziqiqSEIUcxNlUrycnBzExsZi0aJFGDJkSFWX45Q6dergqaeewlNPPVUp+8vPz0fjxo2xYsWKSpuYzBvNnz8f33zzDTZt2lTVpZCHYU7dHHPKPZhTVFbMqZtjTrkHc4qo4nBODQ8jyzIuX76M//73vwgODsbdd99d1SUplo+PDz799FOXP1NJjrRaLebOnVvVZZAHYU45jznlHswpchVzynnMKfdgThFVHA5qeJizZ8+ibt26qFmzJhYvXgyNhm9habp3717VJXi8cePGVXUJ5GGYU65hTpUfc4pcxZxyDXOq/JhTRBWHHz8hIiIiIiIiIo9Ube9+QkRERERERESejYMaREREREREROSROKhBRERERERERB6JgxpERERERERE5JE4qEFEREREREREHomDGkRERERERETkkTioQUREREREREQeiYMaREREREREROSROKhBRERERERERB7p/wFYmnMi8tmwNwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x900 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(3, 3, figsize=(9, 9))\n",
    "\n",
    "main_colors = ['black', 'b', 'red']\n",
    "sub_colors = ['gray', 'lightblue', 'coral']\n",
    "\n",
    "\n",
    "model_handles = []\n",
    "samplesize_handles = []\n",
    "\n",
    "for i, model_name in enumerate(models):\n",
    "\n",
    "    relative_depth = evaluation.model_layer_indices[model_name] \\\n",
    "        / evaluation.model_depth[model_name]\n",
    "\n",
    "    axs[0,0].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['edit_success_rate'], color=main_colors[i], s=7)\n",
    "    axs[0,0].plot(relative_depth, jet_metrics1000['mcf'][model_name]['edit_success_rate'], color=sub_colors[i])\n",
    "\n",
    "    axs[0,0].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['edit_success_rate'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[0,0].plot(relative_depth, jet_metrics4000['mcf'][model_name]['edit_success_rate'], color=sub_colors[i], linestyle='dotted')\n",
    "\n",
    "    axs[0,0].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[0,0].set_ylabel('Success Rate')\n",
    "    axs[0,0].set_title('Edit Success Rate*', fontsize=11)\n",
    "    axs[0,0].set_xlim([0,1])\n",
    "    axs[0,0].set_ylim([-0.05,1.05])\n",
    "\n",
    "    axs[0,1].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['ppl_op_other'], color=main_colors[i], s=7)\n",
    "    axs[0,1].plot(relative_depth, jet_metrics1000['mcf'][model_name]['ppl_op_other'], color=sub_colors[i])\n",
    "\n",
    "    axs[0,1].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['ppl_op_other'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[0,1].plot(relative_depth, jet_metrics4000['mcf'][model_name]['ppl_op_other'], color=sub_colors[i], linestyle='dotted')\n",
    "\n",
    "\n",
    "    axs[0,1].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[0,1].set_ylabel('Ratio')\n",
    "    axs[0,1].set_title('Perplexity Ratio\\n (500 other prompts in dataset)', fontsize=11)\n",
    "    axs[0,1].set_xlim([0,1])\n",
    "\n",
    "    axs[0,2].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['crosstalk_count'], color=main_colors[i], s=7)\n",
    "    axs[0,2].plot(relative_depth, jet_metrics1000['mcf'][model_name]['crosstalk_count'], color=sub_colors[i])\n",
    "\n",
    "    axs[0,2].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['crosstalk_count'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[0,2].plot(relative_depth, jet_metrics4000['mcf'][model_name]['crosstalk_count'], color=sub_colors[i], linestyle='dotted')\n",
    "\n",
    "    axs[0,2].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[0,2].set_ylabel('Fraction')\n",
    "    axs[0,2].set_title('Fraction of Edits which Cross-Talk', fontsize=11)\n",
    "    axs[0,2].set_xlim([0,1])\n",
    "    axs[0,2].set_ylim([-0.05,1.05])\n",
    "\n",
    "\n",
    "    axs[1,0].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['fpr_other'], color=main_colors[i], s=7)\n",
    "    axs[1,0].plot(relative_depth, jet_metrics1000['mcf'][model_name]['fpr_other'], color=sub_colors[i])\n",
    "\n",
    "    axs[1,0].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['fpr_other'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[1,0].plot(relative_depth, jet_metrics4000['mcf'][model_name]['fpr_other'], color=sub_colors[i], linestyle='dotted')\n",
    "\n",
    "    axs[1,0].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[1,0].set_ylabel('False Positive Rate')\n",
    "    axs[1,0].set_title('Detector False Positive Rate\\n (other prompts in dataset)', fontsize=11)\n",
    "    axs[1,0].set_xlim([0,1])\n",
    "    axs[1,0].set_ylim([-0.05,1.05])\n",
    "\n",
    "    if i == 2:\n",
    "        label_to_insert = 'Max STD'\n",
    "    else:\n",
    "        label_to_insert = None\n",
    "    \n",
    "    mean_fpr_other1000 = jet_metrics1000['mcf'][model_name]['mean_fpr_other']\n",
    "    std_fpr_other1000 = jet_metrics1000['mcf'][model_name]['std_fpr_other']\n",
    "    mean_fpr_other4000 = jet_metrics4000['mcf'][model_name]['mean_fpr_other']\n",
    "    std_fpr_other4000 = jet_metrics4000['mcf'][model_name]['std_fpr_other']\n",
    "\n",
    "    max_mean = np.maximum(mean_fpr_other1000, mean_fpr_other4000)\n",
    "    min_mean = np.minimum(mean_fpr_other1000, mean_fpr_other4000)\n",
    "    max_std = np.maximum(std_fpr_other1000, std_fpr_other4000)\n",
    "\n",
    "    axs[1,1].scatter(relative_depth, mean_fpr_other1000, color=main_colors[i], s=7)\n",
    "    axs[1,1].plot(relative_depth, mean_fpr_other1000, color=sub_colors[i])\n",
    "\n",
    "    axs[1,1].scatter(relative_depth, mean_fpr_other4000, color=main_colors[i], s=7, marker='x')\n",
    "    axs[1,1].plot(relative_depth, mean_fpr_other4000, color=sub_colors[i], linestyle='dotted')\n",
    "    axs[1,1].fill_between(relative_depth, (min_mean-max_std), (max_mean+max_std), color=sub_colors[i], alpha=0.2, label=label_to_insert)\n",
    "    axs[1,1].set_xlim([0,1])\n",
    "    axs[1,1].set_ylim([-0.05,1.05])\n",
    "    axs[1,1].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[1,1].set_ylabel('False Positive Rate')\n",
    "    axs[1,1].set_title('Per Edit Detector False Positive Rate\\n (other prompts in dataset)', fontsize=11)\n",
    "    axs[1,1].legend()\n",
    "\n",
    "    axs[1,2].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['probs_other'], color=main_colors[i], s=7)\n",
    "    axs[1,2].plot(relative_depth, jet_metrics1000['mcf'][model_name]['probs_other'], color=sub_colors[i])\n",
    "\n",
    "    axs[1,2].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['probs_other'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[1,2].plot(relative_depth, jet_metrics4000['mcf'][model_name]['probs_other'], color=sub_colors[i], linestyle='dotted')\n",
    "\n",
    "    axs[1,2].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[1,2].set_ylabel('False Positive Rate')\n",
    "    axs[1,2].set_title('Theorem 2 Worst Case Per Edit FPR\\n (other prompts in dataset)', fontsize=11)\n",
    "    axs[1,2].set_xlim([0,1])\n",
    "    axs[1,2].set_ylim([-0.05,1.05])\n",
    "\n",
    "\n",
    "    axs[2,0].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['fpr_wiki'], color=main_colors[i], s=7)\n",
    "    axs[2,0].plot(relative_depth, jet_metrics1000['mcf'][model_name]['fpr_wiki'], color=sub_colors[i])\n",
    "\n",
    "    axs[2,0].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['fpr_wiki'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[2,0].plot(relative_depth, jet_metrics4000['mcf'][model_name]['fpr_wiki'], color=sub_colors[i], linestyle='dotted')\n",
    "\n",
    "    axs[2,0].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[2,0].set_ylabel('False Positive Rate')\n",
    "    axs[2,0].set_title('Detector False Positive Rate\\n (wikipedia prompts)', fontsize=11)\n",
    "    axs[2,0].set_xlim([0,1])\n",
    "    axs[2,0].set_ylim([-0.05,1.05])\n",
    "\n",
    "\n",
    "    mean_fpr_wiki1000 = jet_metrics1000['mcf'][model_name]['mean_fpr_wiki']\n",
    "    std_fpr_wiki1000 = jet_metrics1000['mcf'][model_name]['std_fpr_wiki']\n",
    "    mean_fpr_wiki4000 = jet_metrics4000['mcf'][model_name]['mean_fpr_wiki']\n",
    "    std_fpr_wiki4000 = jet_metrics4000['mcf'][model_name]['std_fpr_wiki']\n",
    "\n",
    "    max_mean = np.maximum(mean_fpr_wiki1000, mean_fpr_wiki4000)\n",
    "    min_mean = np.minimum(mean_fpr_wiki1000, mean_fpr_wiki4000)\n",
    "    max_std = np.maximum(std_fpr_wiki1000, std_fpr_wiki4000)\n",
    "\n",
    "    axs[2,1].scatter(relative_depth, mean_fpr_wiki1000, color=main_colors[i], s=7)\n",
    "    axs[2,1].plot(relative_depth, mean_fpr_wiki1000, color=sub_colors[i])\n",
    "\n",
    "    axs[2,1].scatter(relative_depth, mean_fpr_wiki4000, color=main_colors[i], s=7, marker='x')\n",
    "    axs[2,1].plot(relative_depth, mean_fpr_wiki4000, color=sub_colors[i], linestyle='dotted')\n",
    "    axs[2,1].fill_between(relative_depth, (min_mean-max_std), (max_mean+max_std), color=sub_colors[i], alpha=0.2, label=label_to_insert)\n",
    "    axs[2,1].set_xlim([0,1])\n",
    "    axs[2,1].set_ylim([-0.05,1.05])\n",
    "    axs[2,1].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[2,1].set_ylabel('False Positive Rate')\n",
    "    axs[2,1].set_title('Per Edit Detector False Positive Rate\\n (wikipedia prompts)', fontsize=11)\n",
    "    axs[2,1].legend()\n",
    "\n",
    "\n",
    "    axs[2,2].scatter(relative_depth, jet_metrics1000['mcf'][model_name]['probs_wiki'], color=main_colors[i], s=7)\n",
    "    mh = axs[2,2].plot(relative_depth, jet_metrics1000['mcf'][model_name]['probs_wiki'], color=sub_colors[i], label=model_name)\n",
    "    model_handles.append(mh[0])\n",
    "\n",
    "    axs[2,2].scatter(relative_depth, jet_metrics4000['mcf'][model_name]['probs_wiki'], color=main_colors[i], s=7, marker='x')\n",
    "    axs[2,2].plot(relative_depth, jet_metrics4000['mcf'][model_name]['probs_wiki'], color=sub_colors[i], label=model_name, linestyle='dotted')\n",
    "\n",
    "    axs[2,2].set_xlabel('Edit Layer Depth (normalised)')\n",
    "    axs[2,2].set_ylabel('False Positive Rate')\n",
    "    axs[2,2].set_title('Theorem 2 Worst Case Per Edit FPR\\n (wikipedia prompts)', fontsize=11)\n",
    "    axs[2,2].set_xlim([0,1])\n",
    "    axs[2,2].set_ylim([-0.05,1.05])\n",
    "\n",
    "    if i == 0:\n",
    "        dh0 = axs[2,0].plot(relative_depth, jet_metrics1000['mcf'][model_name]['fpr_wiki'], color=sub_colors[i], label='1000')\n",
    "        dh1 = axs[2,0].plot(relative_depth, jet_metrics4000['mcf'][model_name]['fpr_wiki'], color=sub_colors[i], linestyle='dotted', label='4000')\n",
    "        samplesize_handles.append(dh0[0])\n",
    "        samplesize_handles.append(dh1[0])\n",
    "\n",
    "\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        axs[i,j].grid(True, alpha=0.3)\n",
    "\n",
    "\n",
    "model_legend = fig.legend(model_handles, ['gpt-j-6b', 'llama-3-8b', 'mamba-1.4b'], bbox_to_anchor=(1.2, 0.95), loc = 'upper right', title='Models', title_fontproperties={'weight':'bold'}, fontsize=11)\n",
    "samplesize_legend = fig.legend(samplesize_handles, ['1000', '4000'], bbox_to_anchor=(1.19, 0.82), loc = 'upper right', title='Number of Edits', title_fontproperties={'weight':'bold'}, fontsize=11)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('jetpacks9.png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  }
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