optimalk.ipynb

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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6-final"
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    "interpreter": {
     "hash": "55dc2ef33d481be31a5c00b42f248808e4edd8b163c72100e3df152a03ba29f1"
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 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import kmeans, library\n",
    "from matplotlib import pyplot\n",
    "import time\n",
    "import numpy\n",
    "import random\n",
    "from sklearn.decomposition import PCA\n",
    "import seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_silhouette(cluster_results):\n",
    "    # Using equations from\n",
    "    # https://en.wikipedia.org/wiki/Silhouette_%28clustering%29\n",
    "    cohesion = {}\n",
    "    separation = {}\n",
    "    # Calculate cohesions\n",
    "    for cluster in cluster_results.clusters:\n",
    "        cluster_size = len(cluster)\n",
    "        cluster_cohesion = 0\n",
    "        cluster_doc_names = []\n",
    "        if cluster_size == 1:\n",
    "            # If cluster only contains one document, want silhouette to be 0\n",
    "            cohesion[cluster[0][0]] = 1\n",
    "            separation[cluster[0][0]] = 1\n",
    "        else:\n",
    "            for i in range(len(cluster)):\n",
    "                doc_i = cluster[i]\n",
    "                cluster_doc_names.append(doc_i[0])\n",
    "                # Calculate separation for doc_i\n",
    "                dist_to_centroids = []\n",
    "                for centroid in cluster_results.centroids:\n",
    "                    dist_to_centroids.append(kmeans.item_distance_dot_product(doc_i, centroid))\n",
    "                # min dist is assigned cluster's centroid, want 2nd min\n",
    "                doc_2nd_min_dist = sorted(set(dist_to_centroids))[1]\n",
    "                separation[doc_i[0]] = doc_2nd_min_dist / cluster_size\n",
    "                # Continue to copute cohesion\n",
    "                for j in range(i, len(cluster)):\n",
    "                    doc_j = cluster[j]\n",
    "                    cluster_cohesion += kmeans.item_distance_dot_product(doc_i, doc_j)\n",
    "            for doc_name in cluster_doc_names:\n",
    "                cohesion[doc_name] = cluster_cohesion / (cluster_size - 1)\n",
    "    \n",
    "    # Compute average of silhouettes\n",
    "    silhouette = 0\n",
    "    for doc_name in cohesion.keys():\n",
    "        silhouette += (separation[doc_name] - cohesion[doc_name]) / max(separation[doc_name], cohesion[doc_name])\n",
    "    return silhouette / len(cohesion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def optimal_k_WCSS(K, WCSS,threshold):\n",
    "    for i in range(1,len(WCSS)):\n",
    "        if WCSS[i-1]-WCSS[i] < threshold:\n",
    "            return K[i-1]\n",
    "    return len(WCSS)\n",
    "\n",
    "def optimal_k_silhouette(K,silhouettes):\n",
    "    max_idx = 0\n",
    "    for i in range(1,len(silhouettes)):\n",
    "        if silhouettes[max_idx] < silhouettes[i]:\n",
    "            max_idx = i\n",
    "    return K[max_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "loaded 200 docs 4.53\nrecalc frequencies 0.03\n"
     ]
    }
   ],
   "source": [
    "t0 = time.time()\n",
    "pickle_dir = 'C:\\\\Users\\\\Colin\\\\Documents\\\\SCHOOL_STUFF\\\\EWU\\\\W21\\\\CSCD_530\\\\Project\\\\Code\\\\data_after_removing_words'\n",
    "\n",
    "t = time.time()\n",
    "num_docs = 200\n",
    "vocab, docs = library.load_project(pickle_dir, num_docs, random_files=True)\n",
    "print(f\"loaded {num_docs:,} docs {time.time()-t:.2f}\")\n",
    "\n",
    "t = time.time()\n",
    "sub_corpus_freqs = kmeans.sub_corpus_frequencies(docs)\n",
    "print(f\"recalc frequencies {time.time()-t:.2f}\")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "k=2, iteration 1 (0.06s) [78, 122] skipped 0\n",
      "centroid length: 182 (0.01s)\n",
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      "wcsse (0.01s)\n",
      "wcsse total: 153.47\n",
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      "k=3, iteration 6 (0.03s) [26, 113, 61] skipped 0\n",
      "wcsse (0.01s)\n",
      "wcsse total: 147.51\n",
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      "wcsse (0.01s)\n",
      "wcsse total: 140.88\n",
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      "wcsse (0.01s)\n",
      "wcsse total: 144.73\n",
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      "wcsse (0.01s)\n",
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      "wcsse (0.01s)\n",
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      "wcsse (0.01s)\n",
      "wcsse total: 127.05\n",
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      "wcsse (0.01s)\n",
      "wcsse total: 124.16\n",
      "WCSSE distance calculations:\n",
      "[(2, 153.46846124819146, 0.0),\n",
      " (3, 147.50741718100662, 0.41213044794932696),\n",
      " (4, 140.87807660449593, 0.979508772348803),\n",
      " (5, 144.72937200075904, 0.8878053727089416),\n",
      " (6, 133.2138512353822, 0.814651599698857),\n",
      " (7, 131.4269833333343, 0.25710470155512544),\n",
      " (8, 127.05210512451488, 0.3007626559740473),\n",
      " (9, 124.15985648157816, 0.0)]\n",
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      "k=4, iteration 4 (0.04s) [53, 19, 80, 48] skipped 0\n",
      "wcsse (0.01s)\n",
      "wcsse total: 141.76\n",
      "dim 4 -> 2 info preserved: 0.602149699875856\n"
     ]
    }
   ],
   "source": [
    "kmax = 10\n",
    "K = []\n",
    "WCSSE = []\n",
    "\n",
    "for k in range(2,kmax):\n",
    "    K.append(k)\n",
    "    results = kmeans.find_clusters(docs, k)\n",
    "    WCSSE.append(results.wcsse)\n",
    "# Calculate optimal k\n",
    "scaled_WCSSE = [x/WCSSE[0] for x in WCSSE]\n",
    "optimal_k = kmeans.optimal_k_WCSSE(K, scaled_WCSSE, 0.025)\n",
    "optimal_k_v2 = kmeans.optimal_k_WCSSEv2(K, WCSSE)\n",
    "\n",
    "results = kmeans.find_clusters(docs, optimal_k_v2)\n",
    "\n",
    "# X, labels = library.reduce_to_2d(results, docs, vocab, optimal_k_v2)\n",
    "X, labels = library.reduce_to_kd_2d(results, vocab, optimal_k_v2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_compare_k(K,WCSSE,optimal_k,optimal_k_v2):\n",
    "\n",
    "    pyplot.rcParams[\"figure.figsize\"] = (20,7)\n",
    "\n",
    "    figure, axis = pyplot.subplots(1,2)\n",
    "    figure.suptitle(f'Using {num_docs} Documents')\n",
    "\n",
    "    axis[0].plot(K, WCSSE, color='b');\n",
    "    axis[0].axvline(x=optimal_k_v2, color='r');\n",
    "    axis[0].plot([K[0],K[-1]], [WCSSE[0],WCSSE[-1]], '--g');\n",
    "    axis[0].set_title('Chosen Furthest Point From Line');\n",
    "    axis[0].set_xlabel('k');\n",
    "    axis[0].set_ylabel('WCSSE');\n",
    "\n",
    "    axis[1].plot(K, scaled_WCSSE);\n",
    "    axis[1].axvline(x=optimal_k, color='r');\n",
    "    axis[1].set_title('Chosen by Change Threshold');\n",
    "    axis[1].set_xlabel('k');\n",
    "    axis[1].set_ylabel('Scaled WCSSE');\n",
    "\n",
    "    pyplot.show()\n",
    "    return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "plot_compare_k(K,WCSSE,optimal_k,optimal_k_v2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1080x1080 with 1 Axes>",
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AAQAAAKCNvqh8VQt3XK+KQL4kWxWBfC3ccb2+qHw1LNdfsuTv+vnPf6lu3TLDcr3dCIAAAAAA0EZvlt4jv13frM1v1+vN0nvCcv0bb7xNhxxyaFiu9X0EQAAAAABoo4pAQZvaOwoCIAAAAAC0UZo7t03tHQUBEAAAAADaaGrmTfIYcc3aPEacpmbeFKWK9g+rgLYDl2wZQb+C7hjZth3tcgAAAAAcpN2rfUZqFdBIIQBGkGFI5pa1Kn7mCdWvW61uZ52vxEnTFEzpFu3SAAAAABykw1NmRzzwvfLKkrBejwAYQWbRNq095zQFq6skSbXzb1ROUYHSfnaTLGbfAgAAAGhnpJAIatywNhT+dtvxpz/ILC+OUkUAAAAAnIwAGEGGx9OizYyJlUxXFKoBAAAA4HQEwAiKGTxcMX36NmvrdcMtstKzo1MQAAAAAEfjHsAICqR316A/L1T1fz5Q46YNSj7+ZHlGHqagxUqgAAAAANofATDCAtm9FT97jhIMQ5ZlKxjtggAAAAA4FgGwHdi22P8PAAAAQJv86U9P6b333pUkjR9/jK688v8d9DW5BxAAAAAAOpjPP/9Un3/+if785xf17LMvad26tfrww/cP+rqMAAIAAADAAVhcVq77C4tU6POrh9ejG3rkaGZGeliunZHRTVddda083+4s0KdPXxUX7zjo6xIAAQAAAKCNFpeV66Ztear/9lavAp9fN23Lk6SwhMD+/QeE/p2Xt13vvfeOnnjiTwd9XaaAAgAAAEAb3V9YFAp/u9Xbtu4vLArr62zevEnXXnuVrrrqGvXq1fugr0cABAAAAIA2KvT529R+IFas+K+uueZKXX751ZoyZVpYrskUUAAAAABoox5ejwr2EPZ6eD1huX5x8Q7dfPP1uuOOe3TYYUeE5ZoSARAAAAAA2uyGHjnN7gGUpDjD0A09csJy/b/+9QU1Nvr06KMLQm0zZ87SzJlnHNR1CYAAAAAA0Ea7F3qJ1Cqg11xzva655vqwXOv7CIAAAAAAcABmZqSHLfC1FxaBAQAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BNtAAAAAAEAH9Mc/PqkPPviXJEPTpp2mc8654KCvSQAEAAAAgAOwanG5Pri/SFWFfiX38Oj4G3I0YmZ49gX8+usv9eWXn+vZZ/+qYDCgCy44S+PHT1Dv3n0P6roEwCgxbUvavFp1K/4rV1KSYkePVTCrV7TLAgAAALAfVi0u15s35SlQb0uSqgr8evOmPEkKSwg89NDD9Oijf5Db7dbOnaUKBoOKjY076OsSAKPEWvm51p5/umRZkiRvTg8NfnGxAtm9o1wZAAAAgNZ8cH9RKPztFqi39cH9RWEbBXS73XrmmT/or399XieccLIyM7MO+poRXQRmyZIlmjp1qiZNmqQXX3yxxePvvvuuZsyYodNOO01XXnmlKisrJUmFhYU6//zzdeqpp+qKK65QbW1tJMtsd25/g/Lv+3Uo/EmSr6hQdV9/HsWqAAAAAOyvqkJ/m9oP1E9+cpneeONdlZQU6/XX/37Q14tYACwuLtaCBQv00ksv6bXXXtPLL7+sjRs3hh6vqanR7bffrqeeekqvv/66hgwZokcffVSSdMcdd+i8887T0qVLNXLkSD3++OORKjM6Aj75S4tbNu+qkGFEoR4AAAAAbZLcw9Om9rbatm2rNmxYJ0mKjY3VxIknaNOmDQd93YgFwGXLlmncuHFKTU1VfHy8Jk+erKVLl4Ye9/v9uv3225WdnS1JGjJkiIqKiuT3+/X5559r8uTJkqRZs2Y1O68rsBJSlH3RT5s3GoYSxh4h297zOQAAAAA6juNvyJE7rvnojTvO0PE35ITl+oWF+frtb++Sz+eT3+/Xxx9/qNGjxxz0dSN2D2BJSYkyMzNDx1lZWVqxYkXoOC0tTSeffLIkqaGhQU899ZQuvPBCVVRUKDExUW53U2mZmZkqLm45WrYvGRmJLdoyM5MO5G1ETOJZ58qUrcKnH5c7I0N9b7lTaUccKdPrjXZpXUZH63NEFv3tLPS389DnzkJ/O09H6POSElNu9/6Pjx1yRjeZLkPv31uoykK/Unp4dMKNPTTq9Iyw1HPssRO1du0qXXLJ+XK5XDr++BN16qlTWjzPNM02/fwiFgDtPQxlGXuY31hdXa0rr7xSQ4cO1emnn77HsLen8/alrKxGlvXd62dmJqm0tLpN14g4V6Liz79Mg087S3J7FYiJV1llo6TGaFfWJXTIPkfE0N/OQn87D33uLPS383SUPrcsS4GA1foTv2fY9DQNm57WrK2t19iXiy++TBdffNk+r21ZVrOfn2kaexwQCz0etup+IDs7Wzt37gwdl5SUKCur+ao1JSUlOu+88zR06FDdddddkqT09HTV1NQoGAxKkkpLS1uc11VYlq1AQqoCMfHRLgUAAACAA0QsAI4fP17Lly9XeXm56uvr9fbbb2vixImhx4PBoC6//HJNmTJFt9xyS2iUz+Px6PDDD9ebb74pSVq8eHGz8wAAAAAAByZiU0Czs7N17bXXas6cOfL7/TrjjDM0evRoXXrppZo3b5527Nih1atXKxgM6q233pIkjRw5UnfddZfmz5+vG2+8UU888YRycnL04IMPRqpMAAAAAJDUdBtbW28/i6Y93XbXGsM+kLM6uE5xDyAiij53FvrbWehv56HPnYX+dp6O0uclJflKT8+W2x2ebRzaQyDgV3l5sbKyeobaonYPIAAAAAB0FnFxiaqu3iXbDt8iLpFk25aqqysUF7f3sLcnEZsCCgAAAACdRWJiiioqSlVcnC+pM0ySNOT1xioxMaVNZxEAAQAAADieYRhKT++auw98H1NAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHCKiAXDJkiWaOnWqJk2apBdffHGvz/vlL3+pRYsWhY4XL16sCRMmaMaMGZoxY4YWLFgQyTIBAAAAwBHckbpwcXGxFixYoEWLFsnr9eqcc87RUUcdpYEDBzZ7zvz587V8+XIdddRRofaVK1fqxhtv1LRp0yJVHgAAAAA4TsRGAJctW6Zx48YpNTVV8fHxmjx5spYuXdrsOUuWLNFJJ52kKVOmNGtfuXKlFi9erNNOO03XX3+9KisrI1UmAAAAADhGxEYAS0pKlJmZGTrOysrSihUrmj1n7ty5kqQvv/yyWXtmZqZ++tOfavTo0XrwwQd155136ne/+91+v3ZGRmKLtszMpLaUjy6APncW+ttZ6G/noc+dhf52Hvq8/UQsANq23aLNMIz9Ovexxx4L/Xvu3Lk6+eST2/TaZWU1sqzvXj8zM0mlpdVtugY6N/rcWehvZ6G/nYc+dxb623no8/AyTWOPA2KhxyP1wtnZ2dq5c2fouKSkRFlZWa2eV11drWeffTZ0bNu23O6I5VQAAAAAcIyIBcDx48dr+fLlKi8vV319vd5++21NnDix1fPi4+P1xz/+Uf/73/8kSS+88IImTZoUqTIBAAAAwDEiNrSWnZ2ta6+9VnPmzJHf79cZZ5yh0aNH69JLL9W8efM0atSoPZ7ncrn00EMP6fbbb1dDQ4P69u2r++67L1JlAgAAAIBjGPaebtbr5LgHEPS5s9DfzkJ/Ow997iz0t/PQ5+EVtXsAAQAAAAAdCwEQAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BAEQAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEC05JfqCiw17rRlmka0qwEAAAAQJu5oF4COpaHY1pu3bte6dyoUk+TSj+7so0FTk2XGRLsyAAAAAAeLEUCEGLahjx4t0rp3KiRJjdVBLbp2syo2+KNcGQAAAIBwIAAixFdpaeVrZS3aS9fXR6EaAAAAAOFGAESIO95U9tC4Fu1J2Z4oVAMAAAAg3AiACDG8tqbe2VeeuO8+FoNPSlHWyNgoVgUAAAAgXFgEBs2kD/foyn+NVNmmRsUkmkofFCN3YrSrAgAAABAOBEA0Y9u24nuYiu/RciooAAAAgM6NANjFGYZk5m1U3f++lGwp/pCxsnoPlm3b0S4NAAAAQDsjAHZx5tZ1WnPmVFm1tU3H8fEa+vIbsvsPj3JlAAAAANobi8B0YaZpqHzx/4XCnyRZdXUq+78X5XLR9QAAAIDTkAK6MNM01FiQ16K9MW+bDCMKBQEAAACIKgJgFxYIWOo2+5wW7ZnnzlEgYEWhIgAAAADRRADs4jxjjtKAh/+g2L79FNO7j/r/7jF5Dxsf7bIAAAAARAGLwHRxwZh4eSfN0MBjTmw6jk9SkAVAAQAAAEciADqAbUuBuKRvD6JbCwAAAIDoYQooAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIdgERjsF58pbQ76ld/oU88Yr/q7PPKylSAAAADQqRAA0SrLlP5aUaH5G7eF2u4Y2EcXpqXJJAQCAAAAnQZTQNGqAtvSHd8Lf5J056ZtKrBJfwAAAEBnQgBEq3YFAvph1AvaTe0AAAAAOg8CIFqV6/Wom8fTrK2bx6Ncr2cvZwAAAADoiAiAaFWGZejF0UM0NCFOkjQ0IU4vjh6iDMuIcmUAAAAA2oJFYNAq25aGyK1XRwxRlWUp2TSVEGxqBwAAANB5EACx3xKCUoJMKRjtSgAAAAAcCKaAAgAAAIBDEAABAAAAwCEIgAAAAADgEARAAAAAAHAIAiAAAAAAOAQBEAAAAAAcggAIAAAAAA7BPoBdhN0oVW7zq64soNTeMUrINcU+7QAAAAC+jwDYBViN0idPlOjDhwolSe4YQ3NeHKruR8TIJgUCAAAA+BZTQLuAXZv8ofAnSYFGW6/+bJP8lVEsCgAAAECHQwDsAmpK/C3aKot8aqyyolANAAAAgI6KANgFpPaOkWE0b+sxKl7x3eheAAAAAN8hIXQByX1cOuvJgYpJckmSug2I1ayHB8iIjXJhAAAAADoUFoHpClzSwClJumrsSDVWBZXQ3S1XQrSLAgAAANDREAC7CMuyFZNpKCaTLgUAAACwZ0wBBQAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BAEQAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BAEQAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAXVSDy9Aul2SbRrRLAQAAANBBEAC7GMOQVlp+nb16nY7+YoVuzS9QicuOdlkAAAAAOgB3tAtAeG1XULP/u1o+uyn0vVhUoqpAQA/16yNXkCAIAAAAOBkjgF3MxvrGUPjb7Y3Scu20rShVBAAAAKCjIAB2MUnull2a5nHLa3AvIAAAAOB0BMAuZrA3RselpTRru3tQX6VbBEAAAADA6bgHsItJtgw9PLCvVjc2aKcvoIHxsRpsemTb3P8HAAAAOB0BsAtKtQyN98RJnm8byH4AAAAAxBRQAAAAAHAMAiAAAAAAOAQBEAAAAAAcggAIAAAAAA5BAAQAAAAAhyAAAgAAAIBDEAABAAAAwCEIgAAAAADgEARAAAAAAHAIAiAAAAAAOAQBEAAAAAAcggAIAAAAAA5BAAQAAAAAhyAAAgAAAIBDEAABAAAAwCEIgAAAAADgEARAAAAAAHAIAiAAAAAAOAQBEAAAAAAcggAIAAAAAA5BAAQAAAAAhyAAAgAAAIBDEAABAAAAwCEIgAAAAADgEARAAAAAAHAIAiAAAAAAOAQBEAAAAADawDCkWpdU4ZJkGtEup00IgAAAAACwn4Km9JGvXqeuWKNxX/xP9+zYoZ2mHe2y9ps72gUAAAAAQGexIejXBSvWhY7/kFekWNPUz7OyZFsdPwgyAggAAAAA+2l1bX2Ltr8UFqvS6PjhTyIAAgAAAMB+S/O0nETZK8YrbxRqORAEQAAAAADYT6Pi4jQiMT507DKkOwb1VWwwikW1AfcAAgAAAMB+6mYZ+suwQVrd0KCaYFCD42I1wHBLnWMGKAEQAAAAANoiwzJ0rDfuu4ZOEv4kpoACAAAAgGMQANFhWKaUb1haa/tV7Yp2NQAAAEDXwxRQdAgNpvRCebnu3ZyngG2rf1ysnh0xWL1t/kYBAAAAhAvfrtEhrPf79JtN2xWwmyZQb65v0PzN2+VnJBAAAAAIGwIgOoS8xsYWbR+W71J1Z7qjFgAAAOjgCIDoEHK8LbfOPDwlSQl8RAEAAICw4ds1OoQhXq8u69k9dJzhcevuQX0UE2QEEAAAAAgXFoFBh5BgGboup7vOyuqmqmBQvb1edbMNJoACAAAAYUQARIfhtaQBhltyuyWrU+2nCQAAAHQKTAEFAAAAAIcgAAIAAACAQxAAAQAAAMAhCIAAAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIfYZwBctGiRfv/732vt2rXN2v/whz9EtCgAAAAAQPjtNQDef//9WrRokcrKyjRnzhwtWbIk9NjSpUvbpTgAAAAAQPi49/bAhx9+qEWLFsnr9erMM8/UT37yE2VmZmrcuHGybbs9awQAAAAAhMFeRwBN05TX65UkDR8+XPfdd5+uu+465efnyzCMdisQAAAAABAeew2Affr00cMPP6yysjJJ0rHHHqu5c+fq4osvVnl5ebsVCAAAAAAIj70GwDvuuEP5+fn66quvQm0XX3yxzjvvPFVVVbVLcQAAAACA8DHsA7ihz+/3y+PxRKKesCgrq5Flffe2MjOTVFpaHcWK0N7oc2ehv52F/nYe+txZ6G/noc/DyzQNZWQk7v3xA7no/oa/JUuWaOrUqZo0aZJefPHFvT7vl7/8pRYtWhQ6Liws1Pnnn69TTz1VV1xxhWpraw+kTAAAAADA90RsI/ji4mItWLBAL730kl577TW9/PLL2rhxY4vnXH755S22lbjjjjt03nnnaenSpRo5cqQef/zxSJUJAAAAAI4RsQC4bNkyjRs3TqmpqYqPj9fkyZNbBL0lS5bopJNO0pQpU0Jtfr9fn3/+uSZPnixJmjVrFvsOAgAAAEAY7HUfwN3mzp2rP/7xj83azjrrLC1cuHCf55WUlCgzMzN0nJWVpRUrVrS4tiR9+eWXobaKigolJibK7W4qLTMzU8XFxa2V2cye5rxmZia16Rro/OhzZ6G/nYX+dh763Fnob+ehz9vPXgPgvHnztGXLFuXl5Wn69Omh9kAgINNsfeBwT2vL7M/+gQd63vexCAzoc2ehv52F/nYe+txZ6G/noc/Dq7VFYPYaAH/xi1+ooKBAt912m2677bZQu8vl0qBBg1p94ezsbH3xxReh45KSEmVlZbV6Xnp6umpqahQMBuVyuVRaWrpf5wEAAAAA9m2vAbBnz57q2bOnli5dul8jfj80fvx4PfrooyovL1dcXJzefvtt/frXv271PI/Ho8MPP1xvvvmmpk+frsWLF2vixIltfn0AAAAAQHOtJru33npLJ554og477DCNHTtWhx56qMaOHdvqhbOzs3Xttddqzpw5mjlzpqZNm6bRo0fr0ksv1cqVK/d57vz587Vw4UJNnTpVX3zxha655pr9fkMAAAAAgD1rdSP4yZMn67rrrtPw4cOb3YuXm5sb8eIOFPcAgj53FvrbWehv56HPnYX+dh76PLwO+B7A3ZKTk3XKKaeEtSgAAAAAQPtrdQroIYccog8//LA9agEAAAAARFCrI4AffvihXnjhBXk8Hnk8Htm2LcMw9NVXX7VHfQAAAACAMGk1AD777LPtUAYAAAAAINJanQKam5urlStXauHChUpPT9fXX3/doReAAQAAAADsWasB8KmnntJf//pXLV26VA0NDfr973+vxx57rD1qAwAAAACEUasB8B//+IeefvppxcXFKS0tTQsXLtQbb7zRHrUBAAAAAMKo1QDodrvl9XpDx8nJyXK7W711EAAAAADQwbSa5HJycvTBBx/IMAz5fD4988wz3APYRRiGZJqmLMuSbUe7GgAAAACR1moAvO222/SLX/xC69at05gxY3TIIYfogQceaI/aEEGu8mLVLftA1cs/UtIxExV/9HEKpmVHuywAAAAAEdRqAMzOztZzzz2n+vp6BYNBJSYmtkddiCB3Q63yf3Wddr3/riRp5+JXlDb5R+px76MKeuOjXB0AAACASGk1AJaWlurll1/Wrl27mrXfeuutkaoJERbM2xwKf7tVvPUP5Vx9ndR/eJSqAgAAABBprQbAa6+9VklJSRo+fLgMw2iPmhBhthXcS7vVzpUAAAAAaE+tBsCysjK98MIL7VEL2omrVz8lHnq4ar7+ItSWdNR4uXr2VSCKdQEAAACIrFYDYI8ePVRXV6f4eO4N6yqC8Snq++AT2vXGIlW+/45STj5VqVNnKhDL/Z0AAABAV9ZqAMzKytLMmTN15JFHKjY2NtTOPYCdWyCrl5LnXqPUn/xMluFSwGIfCAAAAKCrazUA5ubmsu9fF2VZtiyZYhNAAAAAwBlaDYBXX321amtrtWrVKgUCAY0ePZqtIAAAAACgE2o1AK5YsUJXXnmlunXrpmAwqOLiYj355JMaO3Zse9QHAAAAAAiTVgPgb3/7Wz3wwAMaN26cJGn58uW69957tXDhwogXBwAAAAAIH7O1J9TU1ITCnyQdffTRqq+vj2hRAAAAAIDwazUAmqapgoKC0HF+fr5cLldEiwIAAAAAhF+rU0CvuuoqnX322Tr66KNl27aWLVum+fPnt0dtAAAAAIAwajUAnnzyyerfv78++eQT2batK664QgMGDGiP2gAAAAAAYdTqFFBJysvL0+bNm7V9+3bt3Lkz0jUBAAAAACKg1QD46KOP6t5771VSUpJiY2P1q1/9Sn/5y1/aozYAAAAAQBi1OgX09ddf16JFi5SUlCRJuuSSS3TOOedozpw5ES8OAAAAABA+rY4ApqamKiEhIXScnJys+Pj4iBYFAAAAAAi/VkcAR44cqSuvvFJnn322XC6XXn/9dfXo0UNvv/22JOmUU06JeJGIHMOQfOW2aooDiktzKa67KduOdlUAAAAAIqHVALhx40ZJ0p/+9Kdm7c8//7wMwyAAdmKGIZWvDujFi9aputgvb7yp0x/sr/6nJO7n8kAAAAAAOpNWA+Dzzz/fHnUgCvxV0t/mrld1sV+S5KuztPDKjbr6/VFK7OOKcnUAAAAAwq3VALhhwwY9//zzqqysbNb+8MMPR6wotI+60qB2FfiatdmWVJnvU2KfuChVBQAAACBSWg2A11xzjSZMmKAhQ4a0Rz1oR7FpphIzPaop9TdrT+ruiVJFAAAAACKp1QAYGxurm266qT1qQTuLSTd05uMD9cKF6+RvsGQY0tQ7+yqpT6sfCwAAAACdUKvf9I888kh9+OGHmjBhglwu7gvrSmxbyjkyRld9MFKV+T4ldPMosZdLBt0MAAAAdEmtBsCMjAxddtllMgxDkmTbtgzD0Jo1ayJeHCLPtqW47qbiusdGuxQAAAAAEbZfq4AuXLhQvXr1ao96AAAAAAAR0moATE9P1+jRo9ujFgAAAABABLUaAMeNG6d58+bplFNOkdfrDbWzATwAAAAAdC6tBsBvvvlGkvTyyy+H2gzDIAACAAAAQCezX/cASlIgEJBt2/J42CMOAAAAADojs7UnlJWVae7cuRozZoxGjx6tOXPmqLi4uD1qAwAAAACEUasB8M4779SYMWO0bNkyLVu2TIcffrhuv/32digNAAAAABBOrQbArVu36uqrr1ZycrLS0tI0b948bd++vT1qAwAAAACEUasBMBAIqLGxMXRcX18f2hQeAAAAANB5tLoIzNSpU3XRRRdp1qxZkqRFixZp8uTJES8MAAAAABBerQbAq666St27d9dHH30ky7I0a9YsnXHGGe1RGwAAAAAgjPYZAP1+v3w+n2bPnq3Zs2dr3bp16t+/P1NAAQAAAKAT2us9gDt27NC0adP0wQcfhNqeeOIJTZ8+nW0gAAAAAKAT2msAvO+++zR79mz96Ec/CrU99NBDOu2003T//fe3S3EAAAAAgPDZawDcsGGDfvrTn7Zov/zyy7V69eqIFgUAAAAACL+9BkCPx7PnE0xTMTExESsIAAAAABAZew2ACQkJysvLa9G+fft2uVyuiBYFAAAAAAi/vQbASy65RFdccYWWL1+uxsZG1dfXa/ny5brqqqt00UUXtWOJAAAAAIBw2Os2ECeccIJqamp06623qrCwUJLUt29fXXXVVZo2bVq7FQgAAAAACI997gM4ffp0TZ8+Xbt27ZJpmkpOTm6vugAAAAAAYbbPALhbampqhMsAAAAAAETaXu8BBAAAAAB0LQcUAD/88MNw14EOyjCkhmJbFev88lc2HQMAAADonPZrCqgkNTQ06O9//7uee+45lZWV6fPPP49kXegILGnTuzX6+zWb5auzlNTdo/P/PERpw/b7YwMAAACgA2l1BLC4uFi/+93vdNxxx+muu+7S1KlT9a9//as9akOU1WwPauHlG+WrsyRJ1Tv8+tulGxSsinJhAAAAAA7IXgPgihUr9POf/1ynnHKKNmzYoPnz5ysrK0vz5s1jNVCHqCzwybaat+3Kb1RtWSA6BQEAAAA4KHsNgGeddZbcbrfeffddPfnkk5o6daoMbgBzlMRsT8u2TI/iUl1RqAYAAADAwdprALzlllu0evVqzZo1S/fff782bNjQnnWhA0ju49bUO/uEFn7xxJo687GB8qbzhwAAAACgM9rrah4XXnihLrzwQn366af629/+ptNPP12maWrx4sWaNm2a3G4WAunqDI90yHlp6n9ssmp3+pXS06v4HFO2He3KAAAAAByIVlPcUUcdpaOOOko7d+7UwoUL9fDDD+uhhx7SBx980A7lIercUlI/l5L6NU37JPsBAAAAndd+D+N169ZNV155pS6//HK9//77kawJAAAAABAB+9wG4pFHHtHy5ctDx7/4xS/0+OOP66STTop4YQAAAACA8NprAHz66af1n//8R7m5uaG2Cy64QB999JH+/Oc/t0txAAAAAIDw2WsAXLJkiZ566in17t071DZ69Gg99thjWrRoUbsUBwAAAAAIn70GQJfLpZSUlBbt3bp1k8vFPnAAAAAA0Nns8x5An8+3x7ZAIBCxggAAAAAAkbHXAHj88cfr/vvvl/29Td9s29YDDzygcePGtUtxAAAAAIDw2es2EFdccYWuuOIKnXTSSTrkkENkWZZWrlyp/v3769FHH23PGgEAAAAAYbDXAOj1evXMM8/o888/1zfffCPDMHTxxRdrzJgx7VgeAAAAACBc9rkR/Pr161VRUaGpU6cqOzu7vWpCB9PgMrQjGFC8aSrbNvS9WcEAAAAAOpG93gP46quv6oILLtDTTz+t0047TR9//HF71oUOosC0dO6a9Tr+y5U6/quVWlRTJf8+lw4CAAAA0FHtdQTw+eef15IlS5Sdna2vv/5aCxYs0IQJE9qzNkRZwGXo9k15+rq6VpJUF7R07drNGnLoCA03PVGuDgAAAEBb7XMsZ/e0z0MPPVQVFRXtUhA6jkrZeqesZb9vbWyMQjUAAAAADtZeA6BhGM2O2fzdeeIljUiMb9Ge5WH0DwAAAOiM9vturh8GQnR9cUHpvsH9FO/67mNybk6mhnpjolgVAAAAgAO113sA161bp7Fjx4aOGxoaNHbsWNm2LcMw9NVXX7VLgYiukaZX740dqS0NPqW4Xern9ijOinZVAAAAAA7EXgPgO++80551oIOybVvdbVPdvbFNDYQ/AAAAoNPaawDMzc1tzzoAAAAAABHGjm4AAAAA4BAEQAAAAABwCAIgAAAAADgEARAAAAAAHIIACAAAAAAOQQAEAAAAAIcgACIq/C5DZS6pwWVEuxQAAADAMQiAaHf5pqUrNm3RYZ/9V7NXr9Nq2y/DIAgCAAAAkUYARLuqd0lXrtmod8t2SZJW1dTpzP+tUZFhRbcwAAAAwAEIgGhXO4JBraipa9ZWG7S0taExShUBAAAAzkEARLuKN03FmS0/dsluVxSqAQAAAJyFAIh21d029JtBfZu1XZCTpf5uT3QKAgAAABzEHe0C4Cy2LU1PTtawQ0doa2Ojsj0eDfHGKJZbAAEAAICIIwCi3Xktabjp0fC4b0f9CH8AAABAu2AKKAAAAAA4BAEQAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BAEQAAAAAByCAIiuI2DIV2bLqo92IQAAAEDH5I52AUA41BVYWnp7nta9U6HuI+I1+8GBShnqkm3b0S4NAAAA6DAYAcQBc/sb5CrcIndZoQwjenVYDYZeuWqT1r1TIUnasapOT5/+jeqKgtErCgAAAOiACIA4IO6SPOX9v0u0atLRWj3lWNX//UWZvujMvazdEVDBf2ubtfnqLFVs8UWlHgAAAKCjIgCizUw7qOInH1Llh+9JkqzaWm295TrZG1ZFpR5PvClvfMuPckwyH28AAADg+/iGjDYzqypU/o/XW7Q3bFofhWqkuGxDP/pN32Zth5+fpdR+3qjUAwAAAHRULAKDtotPUPywEar+/JNmzZ7snKiUY9vSkOnJumzYCJVvaVRSlkd9Dk9WgxqjUg8AAADQUTECiDYLeOLU65Y7ZSYkhNpST5gkz7BRUavJ8EjpwzwaODVR2YfHKCmT0T8AAADghxgBxAGxBx+iYa+/L9+WDXIlJsnVf7CCCanRLgsAAADAPhAAcUBs21awe2+5uveWJLHhAgAAANDxMQUUAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BAEQAAAAAByCAAgAAAAADkEABAAAAACHIAACAAAAgEMQAAEAAADAIQiAAAAAAOAQBEAAAAAAcAgCIAAAAAA4BAEQAAAAAByCAAgAAAAADkEABAAAAACHIAACEeB2u2SaRrTLAAAAAJpxR7sAoCupMaXldbX6W1GphiTE6azsbuonl2w72pUBAAAABEAgbEzT0N93leu2DdskSf8q36WXikr15qHD1cNmsB0AAADRx7dSIEzKDVv3b8lv1rYrENCa+oYoVQQAAAA0RwAEwsT49r89tQMAAAAdAQEQCJM029Av+/Vq1pbucWtYXGyUKgIAAACa4x5AIEwsy9bM1BTljBys/ysu1ZCEeM3slq4ci7+zAAAAoGOI6DfTJUuWaOrUqZo0aZJefPHFFo+vWbNGs2fP1uTJk3XLLbcoEAhIkhYvXqwJEyZoxowZmjFjhhYsWBDJMoGwibcMnRATr6f699O1mVnqY7uiXRIAAAAQErERwOLiYi1YsECLFi2S1+vVOeeco6OOOkoDBw4MPeeGG27Qb37zG40ZM0Y333yzFi5cqPPOO08rV67UjTfeqGnTpkWqPCCiAgEr2iUAAAAALURsBHDZsmUaN26cUlNTFR8fr8mTJ2vp0qWhxwsKCtTQ0KAxY8ZIkmbNmhV6fOXKlVq8eLFOO+00XX/99aqsrIxUmQAAAADgGBEbASwpKVFmZmboOCsrSytWrNjr45mZmSouLg79+6c//alGjx6tBx98UHfeead+97vf7fdrZ2QktmjLzEw6kLeBKLBsWxtr61XU6FP3GK8GJsTJZbR9LU363Fnob2ehv52HPncW+tt56PP2E7EAaNt2izbje1/i9/X4Y489FmqbO3euTj755Da9dllZjSzru+tnZiaptLS6TddAdBiG9O/Gel26aoMaLEsxpqEnhg/UibEJUsuPzF7R585CfzsL/e089Lmz0N/OQ5+Hl2kaexwQCz0eqRfOzs7Wzp07Q8clJSXKysra6+OlpaXKyspSdXW1nn322VC7bdtyu1ms1Cl2GJYuW90U/iSp0bJ1xeqNKjK4pw4AAAA4WBELgOPHj9fy5ctVXl6u+vp6vf3225o4cWLo8dzcXMXExOjLL7+U1LTy58SJExUfH68//vGP+t///idJeuGFFzRp0qRIlYkOpsQfUF2wedhrtGwV+/xRqggAAADoOiI2tJadna1rr71Wc+bMkd/v1xlnnKHRo0fr0ksv1bx58zRq1Cg98MADuvXWW1VbW6vhw4drzpw5crlceuihh3T77beroaFBffv21X333RepMnEQDMOQYajZdNuDle3xKMFlqvZ7ITDWNJXt9UgMAgIAAAAHxbD3dDNeJ8c9gJFXtSmoje9XKuCzNPikVKUNdstu+zotLRiG9LGvXj9dtUG1QUtxpqknRwzUcTHx3AOIvaK/nYX+dh763Fnob+ehz8OrtXsAubkObVa1MaCnpq2Wv6FpSO793+Xr0tdHKH2E56CvbdvSBG+c3hs7SiV+vzI9bnW3zTaFPwAAAAB7FrF7ANE1maahVW9UhMKfJFlBadkfdsg0W/84GUbTNfbFtqVsy9Aol1fdLcIfAAAAEC6MAKJNDEOqrwy0aK/f5ZfRSlCry7e08f1KVeQ3augpacocGSMzJkKFAgAAAGiBAIg2CQZtjZqRoU//XNys/eif5iho732VlvoiS8+cvkY1pU2reS77ww6d/dQgDZicoK53FyoAAADQMTEFFG3WbZRXF//fUPU7Jlm9DkvUBc8NVo8j4vZ5zo5v6kPhb7e37tyuQE0kKwUAAADwfYwAos0Ml9T9iFid+/wAyZJsd+tDeEFfy9FBf4MlOxiJCgEAAADsCSOAOGC2ae9X+JOk7iPj5Ylt/nE7/v/1kDc1DHtHAAAAANgvjACiXST1dWnu68P1n8eLVLa1QeMuzlb/E5PCuok8AAAAgH0jAKJd2LaUOtit6Q/1kR20JbfN4i8AAABAOyMAol1ZsiSX2NsPAAAAiALuAYQjGIZk1Un+cluGxX2HAAAAcCZGANH1WYYKP6/X67/col15jTr07ExNvKaHYrMIggAAAHAWAiC6vKotfj137lrt3qf+y5dKJVuafFdP2SZzUQEAAOAcTAFFl7dzY0Mo/O329cJSNVa03JsQAAAA6MoIgOjyYlNaDnSn9IiRO5YpoAAAAHAWAiC6vMyhMeo3Pjl0bBjSaff1kysxikUBAAAAUcA9gOjyPKmGZj/eTyWrG9RQGVS3gbFKGeBmH0IAAAA4DgEQjuBJNZQ7Pi7aZQAAAABRxRRQAAAAAHAIAiAAAAAAOAQBEAAAAAAcggAIAAAAAA5BAAQAAAAAhyAAAgAAAIBDEAABAAAAwCEIgAAAAADgEARAAAAAAHAId7QLQNdhGFKpYWu7z6ckl0t9XG55rWhXBQAAAGA3AiDCZr0d0Nn/W6tyf0CSNLdnd12bk60Ey4hyZQAAAAAkpoAiTBpdhm7ZuC0U/iTpj/k7tNbni2JVAAAAAL6PAIiwqJOtL6uqW7QXEQABAACADoMAiLBIlKET0lNbtPeOiZEkmaYh02QqKAAAABBN3AOIsPAEbf2qf29trW/QxroGuQ1DN/fvpUHeGK0J+PTPkgrFGKYmZ6RpkOGSbbe8hs9lKC/oV00wqN7eGKUF2/99AAAAAF0ZARBh09sytXjkUBUE/EowXco1XFrpb9TMr1dr92KgD28r0D/GjtCgH3z0akzp4cIiPZ2/Q5LUPcajv40aqr62q53fBQAAANB1MQUUYZUYlIYYHvW0TbkMQ0/l79D3d4Lw2baW7CxvMR10ra8xFP4kaUejX3dszpPfxbRRAAAAIFwIgIgY25CqAy3ncdYGgjJ+kOvyGxtbPO+TXVWq0R7migIAAAA4IARARIwdsPTTXt1btM/MylAw2DzY9fp2sZjvOy49RUliBBAAAAAIFwIgIuqImDi9OHqIxqcm6YT0VP19zHANd3tbPG+YN0bX9c0NfSD7x8Xq5n695A4yAggAAACEC4vAIKK8lnSMJ07jhwySYdtS0FazmwK/FW9JV2VmaUa3dNUGLfXyeJTIKqAAAABAWBEA0S6MwB5S3w+Ylq3eckmmSyL8AQAAAGHHFFAAAAAAcAgCIMLGdjWq1p0vn7uixSqfe+NzG6pzGTL29wQAAAAAB4wpoAiLavc2/V/+LVq5612le3vown4L1Nd1rGTt+W8MQVP6wteg36zbrspgUFf16qEfpSQr0dq/IFhh2lrX2KigbWtQbKyy9vM8AAAAwMkIgDhotqtRC/Nu0jeV70mSyn2FenTdebp1xAdK06A9nrMm4NfZ/1sbOv7l+i3yDOmv2UnJsltZ+HOHaeuCb9ZpY32DJCnD49aiQ4apj+0KzxsCAAAAuiimgOKg1RolofC3m6WgSho37vH5hmHo48rKFu1P5hepwdz3SJ5hSO9XVobCnySV+QN6rqhERivnAgAAAE5HAMRB8yheKZ7sFu0J7vS9nGErw+1p0Zrt9bQ6JG2aplbX1LVo/6q6VkHyHwAAALBPBEActNhghi7s96AMfZfADk+fqWzX0D0+37al8clJ6ub5LgS6DOn6vj3lamXj92DQ0knpqS3az87uJlfrO00AAAAAjsY9gDhoti31dx+nW4a/p9LGLUpwpynbPUyeYMpez8m1Tb0+Zpi+qK5VTTCow5MSNcjl3uMm8T90eFy8burXSw9uy1fAtnVxbnedmpoi22rl5kEAAADA4QiACAvDcqubMVTe2ATVBHcqYNQpxkiTvY8VXXpYpk5LSJJhNIXI/Ql/kpRoSZd166ZZ3dIVlK0suWQS/gAAAIBWEQCxXwxD2q6gvqipVdC2NTYxUQMM13crdppBrWp8Q89unie/3ah4V4quGPScehnjWl3Vs7XH98iylSlDkiGJ8AcAAADsDwIg9ssWBTX969WqDgYlSV7D0JKxIzTk249QpbFVz2y6UpaaHq8LVuqpTXN185D3FBvIilrdAAAAAL7DIjBolWka+sfOilD4kySfbeuZgmKZrqaFXyr8BaHwt1u1f6eqg6XtWisAAACAvSMAolWGYajI52vRXtDQKNtoCoCpnhwZP/g4JbrTlejq1i41AgAAAGgdARCtCgYtzczMaNH+k57ZsgNNK7ekWv10Uf+H5TKapoTGmPGaO+ApxQe7t2utAAAAAPaOewCxX0Z7Y/TnkYN1z5Y8+SxbP++bq3FxCd+t3Gm7NTp2ln41/DBVBXYqzdNDicGe+1wFFAAAAED7IgBiv3gt6cTYeB09Yqgs2UqwJPuH2zZYLiWrv5KN/lJg/9fmNAxDZv5GNaxdJcPjVeywUQpk5ob7LQAAAACORwDEfrNtKTbYFOvCOa5nbFypNWdPl1VfL0nyds/RoBf+rmBO3zC+CgAAAADuAURUuWSp+OnHQuFPknw7ilTz8fv6dn0ZAAAAAGFCAERUGcGAGrZsatHeuH2bDBIgAAAAEFYEQERV0O1V1nkXtWhPOeFkWRYLyAAAAADhRABExNmGlG9YWuar1zrbL9/3PnW2LcWfeKp6/eJWuRKT5MnKVv8HH5N7xNjoFQwAAAB0USwCg4gyDOlTf6MuWLFW/m+3hPh/fXroyqwsxXy7imgwKV2JF12tYTPPkVymgkkZCrJ9BAAAABB2jAAioipMad6ajaHwJ0kPbyvU5qC/2fNsWwqkdFMgMZ29AwEAAIAIIQAioqqDQRX7/C3a99Qml6Gg22D1TwAAACBCCICIqAyXS8MT4pu1mZL6xsaEjg3D0HoF9PNt2zV7zXotqqlSFZ9MAAAAIOz4mo2Iig9Kjw0boEHxsZKkFLdLT48cpN5yhZ6zTQHN+Hq1FhWX6b9Vtbp27Wa9Ul7OSCAAAAAQZiwCg4jrZ7u0eORQFQeDSjFNZcpstsXD6rp61VtWs3Me3lag2RnpSgm2d7UAosUwJJfLVDBoiVuBAQCIDAIg2kVCUOovl2RJlpp/s/OaLQei41wuhqcBB3GX71Dtx++r6uMPlDzxBMWPP17B9O7RLgsAgC6HAIioGx4Xq2yvp9nCMLf1761ky5AthgGArs7VUKO8W36uyn+/J0kq+8drSjtlinrc+5iCMfGtnA0AANqCAIiwcNdWytpVJjM1Q4GElDad290y9eroYfqgslLb6ht1SkaaRntjZFuEP8AJrO2bQ+Fvt4q3/6mcq7dIA0ZEqSoAALomAiAOimFIxpqvteHnV6hx21bF9OmrAQuekD300Dbdw9PTNnVhSpqMVKPp/kCr9XMAdA22vedfePYEBQAg/LjNCgfFVbZD6+eer8ZtWyVJjdu2av1Pzpe7cqcCVVKwummbh/1h22q2OAwAZ3D37q/EQw9v1pZ89ASZPftGpyAAALowRgBxUPxF+QpUlDdrizvmNH25yNL7j3wjl8fQKbf01sBJSTLjolQkgA4tEJesvgv+oF1v/l2V772t1JOnKGXKDAViE6NdGgAAXQ4BEAfFnZouuVxSsGm/BjMhQVX9ztc/bi8MPefVeZv045eGqMf4tiVAwxBLwQMOEcjMVfLFP1PqxVfLkqEAswEAAIgIpoDioNg5fdTnV3eFjhPHjtN/P2i5at/K18vlcu3fx63BtVMbgm/po5rHtNX6SH5XVdjqBdBxWZatgMVUcAAAIokRQBwUy3QpYcZ5Gj7mcPl2FCq23wBlPhGnrZ9UN3tet/6x+7WgQ8BVrYWFv9DXFW+G2qbn3qATU6+Rgq5wlw8AAAA4CiOAOGiWxytr4Ei5J5yiQO4AHXlRlrwJ3320EjLcGnJq2n79VX9ncGOz8CdJ/yh4UFXKC3vd+9LgMlTukizX/i1gAyC8TNNQsFoK1jZNBwcAAOHBCCDCLiO3Xlcs7q/ijZYMj0vZI+IUl7N/f2vw2fUt2iwFFbAbwl3mHhmGtNLy6+bVW7Smtl7TszL0i9656m7xDRRoL8FaadUbFXr/wQK53E0LSfU7MVFmbLQrAwCg82MEEGFjGIaMNV9pwxmnaPvMgXI9M1MD+m/b7/AnSVmeAUr2ZDVrG5w0Xqlm73CXu0f5hqUz/rtGK2rq5LdtLSreqZs2bZWf2adAu9n2cY1e/+VWVRf7tavAp4VXblTx/9rnj0AAAHR1BECEjau0QOsvOlsNW7dIkurWrNaGn14gd1XZfl8jNpCtawe/osPSZyjV210nZs/VhX0elhloubBMJGyqb1SD1XxT6vfLK1VssTM90B5chqFP/1zcov2b18v2eyEpAACwd0wBRdj487cpWNN88RdfUaECOwqk5Iz9vk5qcLAuyHlMfqNWXitJdqD9vvQlu1u+VrLbpTjDkFiYEIg8Q0rvG9tiIam03vu3kBQAANg3/pyKsHGlprdYrcHweuVKTmn7xYJueQIpsq32/YgO9MTo1G5pzdruHtRXmfyqAO0iaNkaN7e7PHHf/c7Fp7k1dEoq20MAABAGjAAifHr2U8+f36j8390Tauoz/x7Z3dvn/r1wSLSk3/brrYt6ZGun36/+sbEa5PbwxRNoR6mD3Lp86QjtWFUn02Wo+6h4JeSaYgAQAICDRwBE2Fhur1LOv1RJxxwnf3GRPD16yegzSJY61wqaKZahcZ5YyfPtkoPc/ge0K9u2ldjHpYF9kr7XFsWCAADoQgiACKtgTLw0ZIzcQ8bI1vdumzMNlciSLVtZMmUQqgAAAIB2RwBExFWbtp4rLdUj2wplSbq0Z3dd1j1LqR1wb71Kl7TF16gYw1Rft0dxBFUAAAB0IQRARNwndXV6YGtB6PiJvCINio/T7KTkDjWtq8C0dMHKddpS3yhJmpyRqnv691F6BwyqAAAAwIFgaUNElNtt6h+l5S3aFxbvlNmB9vQyTEN/KioOhT9Jeqtsl76orY1iVQAAAEB4dZxv4OiSgkFbo5MSWrQfnpwguwOtrNlg2Pp3RVWL9v/V1Mo0GQEEAABA10AARETZtq1T01PVNy4m1Jbt9ejs7MwOtbVCrG1o6g/2/5OkI5KTOlSdAAAAwMHgHkBEXA/L1KJRQ7WuoVG2bA2OiVW3DnZfnW3ZOi8rU59WVuuTXdUyJF2Um61D4+LYBgIAAABdBgEQ7SI9aOjoDr6vXrZl6NnBA5UX8MtrGMo1XXJ30FoB0zRkGIYsy5bdkVZTAgAAHRoBEBFnuesVVKO8wdQOternnsQGbQ0yvv21IPyhg6ovtLRycbk2/btKI09L1+DJKYrJ6Fij6gAAoGMiACJyDFtF+kKvbr1DOxvzNDFrjo5OvVBxwaxoVwZ0Wv5K6cWL1qt0fYMkaesnVRr9WYam3t9bhqeD/4UFAABEHYvAIGLKjfX63drTtanmC1X6i7Wk4H59WP6UDJMvqcCBqtjcGAp/u61YXKbawkCUKgIAAJ0JARARU9S4VkG7+ZfS94r/qHqzNEoVAZ2fsYdtSQxDEjNAAQDAfiAAImJizPgWbcmebnIpZg/PBrA/0vp7lTum+d6ah12QpcRcV5QqAgAAnQn3ACJicmNGqUfcEBXWrwu1nd37bnmDKWISKHBg3EnSWU8N1MZ/VWrrJ9UaOilVvY9JlMh/AABgPxAAETFxge66asBfta3+K1UHStUnfoyyjBGyWV0TOCixWYZGnZeqMRemKxDgFwoAAOw/AiAiKj7QQ8M8PSSPJPvb/wAcNNsW4Q8AALQZARCdkiFb5o7tCuwolDsjU1ZuX9kmH2cAAABgX/jGjE7HMAwFP/1A6664SFZDg2Sa6vub+xU//SxZpifa5QEAAAAdFquAotMxy4q0+ZrLm8KfJFmWtt56g5S/JbqFAQAAAB0cARCdjlVRpkDlrh80WgqUFEelHgAAAKCzIACi03F1y5InM6tZm+F2y5OTG6WKAAAAgM6BAIhOJ5iaqYGPPSN3eoYkyYyP14CH/yC7R9/oFgYAAAB0cCwCg07HtiVj5BEa+vp7CpTskDstQ8HsnrIOcIsJy2XIJynelqwDvQiATsFVvF0N3/xXtt+vuOGjZfUZJJtfewCAgxAA0aEYhqSAIZmSbez9W5ltS4G0bCktWwHpgPYXNAxpgx3Qw1sKtaa2XufnZGpGeprSLeNAywfQgbkKNmvdOdMVKC+TJJmxsRr68hLZA0dFuTIAANoPU0DRYQRrbW36Z43+cuYGLb5iq8pX+eX2N8jdUCPDCH8oKzAszfjvai0pLdfGunrdsWm7nigqlu0iAAJdjWEYqv7gnVD4kySroUHFzzwh1z7+2AQAQFdDAESHYBjSpndr9PLlG5X/VY1WL63Q0zNWq/DN1do4e5LqF78oV+2usL7m2voG1QatZm1/LijWTll7OQNAZ2WaUmNBXov2xm1bZAQDUagIAIDoIACiQwjWG/rwkYJmbVbAVv7GWPl37tTWm3+uuvffUjgHAmP3cLF4lym3GAEEuppg0FbqpCkt2rPmzFXQ5YlCRQAARAcBEO3C1VgnY8MKWV98JFdJfospnYYpeeNbfhzdHlu2FZSkpqlajXVhq2loXJwGx8c2a/vVgN7KsAmAQFfkGjFWAx59WjE9e8mTmaU+8+9R3LEnsQgMAMBRWAQGYWUY0k7DVoHfpzS3Wz3kkremUqUP36OSF5+VJLkSEjXk+VdkDxnz3XleW5Nu6q3nzlsbaotNcSkrZat21TWFPk9mlhTGv9SnB6UXRgzRJ9U12lLfoGNSkzXKG8NKoEAXZXnj5D1pugaNmyhZlqzkdAX5fQcAOAwBEGG1yvLr/JXrVOEPyGVIvx7YV2fuLAyFP0kK1tZo6y3Xqf8LrykQmxhq73FkrC59fbjWvlWhxHRTPRJXqXLBtU0PmqZ6zLtegTBP1cqyDJ2WkCQzKbkp+HH7H9Cl2bYUiE9pOiD8AQAciACIsKlxSVet3KQKf9OCCkFbunnDVh3eN7vFc+vWrJLqaqTvBUC5pW6jvZo4prtsWzILa5SScKeCtbVKPOwoacDwA9ntYb8w6gcAAAAnIAAibCosS1vqG1q0F3m8OvzaX8hwu1X66kLVb96olIknyE7KULBW8iQYsr4X7XaHsWBOP8VM6yfD6Fp/qDcNQ/5qW644Q3J1oTcGAACADo8AiLBJM031i4ttEQJTVq9Q3oL7ZLjd6nXNDape9Y2SLlugN24u1pb/VGnYlHSNm5uluJw9r0nUlRZoaNxp66sXSvXV30qVNTROk27qpbShHtld6U0CAACgwyIAImwSg9JjwwbogpXrVO4PyG0Ymp8So6S7HpVfkh0IKO+h+zXwjZX6w1nbVVnkkyR98swOFf6vRuc+P1BmXHTfQ0RZhj78XYG+/GupJKlqh0/bP6vWFe+MVHwuC/ICAAAg8giACKsRpkfvjBmhQr9fqfU18l90lnxrvgk9bgcC2rk1GAp/u23/okbVBQGlDOy6H8mGUktfvVzarM1XZ6l0fYP65MZHqSoAAAA4CcMOCCvbljIsQ6NcXvVr9ClYkNfscSMmRt7kmBbnGabkjuna+++ZHikmydWi3bOH/Q8BAACASOCbJyIm2C1HAx//k1zJTUuumwkJGvjo00odnKiR09ObPXfClTlKyG0a/TNsQ3aDIdPsWoEwtpupKbf3adbW89AEZQ5pGYgBAACASOi68+0QdbZtyxw7QcPe+ECB0mK5MzIVzMqVbUun/rqXDpndTaXr65UzKkFZo2JluGxVbgzq348UqOibOo09O1OjZqfLm9E1gqBl2RoyNVlz+w1Twde1SukZox6HxsuT2jXeHwAAADo+AiAiyrZtBTJypIwcWaYULK1XfWmj4rNi1fv4ePU5IT60ymddkaVnTl+thqqgJOntu/NUkdeoSXfkyja7xiqZRoyUOSZGWYfGdKnVTQEAANA5EADRLkxTKv2sUv93baEq8hqV3sersxbkKrtPrRoL8+XOyNTODdmh8LfbFy+WaMLVOYrN7lqjZIQ/AAAARAP3AKJdNG6v0V9+sl0VeY2SpPJtPj1/aZ4qVhZq3TmnafWPjpPLV9XiPE+cKZM/UwAAAABhQQBEu6jY1qCGyuaje7VlAdU0NC0QY/t8cq9/Q92HN98O4eRf9FJMt641+gcAAABEC2MraBeJ3bwyXZL1vQzo8hiKSwiq4ttj2/BqxLQMjZiaoeoSnzL6xapoZa1G7EqTOyUqZQMAAABdCgEQ7SJxQIKm3pypN3793UboU2/OUO3/3RY6rvP01r/uypMnzlR8qltVO3yybenIS7KUnuKNRtkAAABAl0IARLuw3C4dMitBPUcYqir0KTnLUEpcgTY9+bEkyYyPV8ahQ2QYxfLXW6qs90mSXF5DsSl8TAEAAIBw4Js12k3Dp/9S8XVXSZLqJZVnZWvQ75+WEpPlyshUMCNHJ9/o1Tv35IXO+dGv+yqhh0u2wrtspmkasqzOtRSny2UoGOxcNQMAAKBjIQCiXbjdpkre/WezNn9JsQqfeFi9n1uswLfBZuzFGeo/MVnVRT6l9IxRcl+3bCN8ocdXZmv7J7Uq+qZWfY9OUs6hcXIndexFZipNW5/W1uo/u6p1eHKixiclKsPq2DUDAACgYyIAol0Eg7aSjjha5f98QzJNuVPTFKjcpaSjj9X3B+JMr5Q+zKP0YZ7w11AjvXrVZm39pFqS9PETRTpuXg+Nvyarw66HG3AZuj+vUC8UlUiSniss1nFpKXpiUD/FB1s5GQAAAPgBAiDahW3bSjpxshIaG7V+7FFa643TEMNWz+zsdpuKWb7JFwp/u330WKHGnN1N8bkdMwHmW4FQ+Nvtw4pKbfH7NcIMf0gGAABA10YARLtp7NZdz54wTc+UlEuNTYu8nGnu0t2JyfKYrazyaRqqM2zF2YaMAwyMQZ/Vos0KSlag495XF9zLew3YLd8LAAAA0JqOOeyBLimvobYp/H3P/+2q0SorqLWWX/WuPZ9XZFq6q6hIp65co5vz85VnHlj4SR8Qo+Sc5kFz2JQ0JfbYywt3AD3dbh2bltysbXB8rPp5Y6JUEQAAADozRgDRbhqCe75p7ZOaet27abuOSU3SgkH9lfW9BU7qXdLP1m7WF1U1kqTt9aX6uKJKS0YPVWqwbQuheNMNXbRwqD79Y7G2fFKlUTMydMiZGVIHnkkZE5R+N7CfFpWV6c3SCh2XlqJzs7spmfv/AAAAcAAIgGg3feLjdUh8rI7NTFeyp+mjF7RsVfj8kqT/7KrWm+UVujgtQ7bdNPUxPxBQkc+nMcmJWl1dK59tK6+hUVsbfRrjbvsoWEIvUyff0UOWr4eMGFt2x539GZJlGboyI1OXZmbKY6nTbV8BAACAjoMAiHYTZ8bqwWH9dfGqTdre0ChJGhAXq7N7ZIWe81bZLs3t1k2Bb+/Ls01Dp3RLV2FDo6YN6K2vq6r1j5JyxZoHNnvZMIymHQW9nSP87WZZtlyWxJ1/AAAAOBgEQLQb0zT0z9LKUPiTpE31DSrz+5Xt9ajY59cpGamhzc53mLbO++9a7fQ3jRC+tbNC8/rm6qIeWerj8UhtmAZpGIY22wF9UFGpRtvSCWmpGmy6ZZCoAAAA4CAEQLQb0zT0SWV1i/ZNdfXKjY3RgPhY/Sg9Tfa3UxzX1NeHwt9uz+bv0DuHjVRcoG2vvdH2a9rXq1VvNSW++418vTZmhEaylQIAAAAchACIdhMMWpqV1U0fV1Q1a/9RZoZGxMaql8ejuO+N6ll7mKNp2VKM3bbFX5pGHneFwp8kBW3pifwiPd6vr+wgw4AAAABwBraBQLuxbemE5CRdkpstU5LLkC7rlaMTExM12Gwe/iRpWHycUt3N/0ZxXd+eSmtjXjMMKWjb+nvPoVqWMVJ/6zVYiS6XKvwB2UYnuhEQAAAAOEiMAKJdpVmGbs3tobk9smVIypZL5l5Wtcy1TS0eM0wvF+/U6to6ndc9S+MT4tX2PdBtnZufoiW/3KKSdfXqeWii3r97mDb29EkdeBN4AAAAINwIgGh3ZtBWj9Dg894DmG1LfeXSzTndZRiGAoEDWwZz11ZbL/54nRoqm4YY87+u0as/3aA5fx8msZ86AAAAHCSiU0CXLFmiqVOnatKkSXrxxRdbPL5mzRrNnj1bkydP1i233KJAoGllj8LCQp1//vk69dRTdcUVV6i2tjaSZaKDCwbtpvB3gMo31YfC324VeY2q3Nq4lzMAAACAriliAbC4uFgLFizQSy+9pNdee00vv/yyNm7c2Ow5N9xwg2677Ta99dZbsm1bCxculCTdcccdOu+887R06VKNHDlSjz/+eKTKRBfgDjTK3VgnYy9rw8SntBzodnkMxaUyAA4AAABniVgAXLZsmcaNG6fU1FTFx8dr8uTJWrp0aejxgoICNTQ0aMyYMZKkWbNmaenSpfL7/fr88881efLkZu3ADxlWQPp6mbZecqY2nTlZDW8slKu2stlzTNNQdZlf4y/NadZ+0vW9lNaHLSAAAADgLBEbAikpKVFmZmboOCsrSytWrNjr45mZmSouLlZFRYUSExPl/nb1x93twG5uX53ka5RVukNrLpzddLOgpC2/mKf+9z+imB+dFXpuwJDydzbIm2DqvKcHq7bcr8RMr3btaJDhtvdxByLQsRiGVOsqVLFvg7xmnLLcg+UJpEa7LAAA0MlELADae9jDzfjeHL29Pd7aefsjIyOxRVtmZlKbroGOx/L7teujD7T517fJX7xDmWeco5wf/0RFz/4x9JwdTz+u0TPPkNTU5zWBgOoOdWvTJQX64KECSZIn1tRprw5WRlbLzwk6r67+O76l+mv99pvTVBMolyQNTT5Wlw95Wt1ie0W5sujo6v2NluhzZ6G/nYc+bz8RC4DZ2dn64osvQsclJSXKyspq9vjOnTtDx6WlpcrKylJ6erpqamoUDAblcrlC7W1RVlYj63tbC2RmJqm0tPog3g06AnPzKq0+b5b07YbuhU8+qu5zLlFsv/5q2LJZkuROz1B1Q1DpKVJpabUMQ/L0cSvh6SwN3WbK8EvVfQ25Rnr4THQhXf533BXQ4qLfhsKfJK2t+khrK5ZpiHtqFAuLji7f32iBPncW+tt56PPwMk1jjwNioccj9cLjx4/X8uXLVV5ervr6er399tuaOHFi6PHc3FzFxMToyy+/lCQtXrxYEydOlMfj0eGHH64333yzWTu6FsMwtNO0tdryqcS0ZZqtj/I2rFkVCn+77VyyWGknTGo6ME31+H+/UND87t4+25bGxyeo74A4PTWoXH8dXaV+IxPUz2ABGHQefqNWW2q+atG+o2Fjm2dIAAAAZ4voCOC1116rOXPmyO/364wzztDo0aN16aWXat68eRo1apQeeOAB3XrrraqtrdXw4cM1Z84cSdL8+fN144036oknnlBOTo4efPDBSJWJKDAMQ5/5GzR31XpVBoJKdLn05IiBmuCN29e2gDKTWk4N8GRmKXnC8XJndVfiUcfIGDii2VaBhiFVbQgodWVAv0rorh6HxCvNNKW9bD4PdEReK0VHpM/UWzsea9beN2HsHqfNAwAA7I1hd8FvD0wB7dhKTVsnff2NqgLf7c0XZ5p6/7CR6m7tfVDaXVaojT8+Uw1bNjU1GIaGPPuyjMMnyjBCa8FI+q7P81f69OLpa2QFmh5MzvXqvFeHKq17RLfARDtzwu94rbtArxTcov9WLJXHiNFpPX+hcck/ljvovHtZndDfaI4+dxb623no8/BqbQoo8+DQ7kr8/mbhT5LqLUtFPr+6u2P2el4go4cGPLtQjSu/VmDXLsWNGC0NHC5bzcPfbpZt6t+/zQ+FP0mqKvBp6/IqpZ2eGqZ3A7SPhECu5vT4g2b2yJdbMUq0c2UHmf4JAADahgCIdpfhcSveZaou+N1kTY9hKMvj2ecUUEkKdsuV+4RcudXqUxXwWaop8LVorynxyzSNZqPEQGdgBGOUogGSWv/8AwAA7Anz4NDucmxTjw0bKO+3i1e4DUOPDBugHkZ4P47BRFMjL85s0d5nfDLhDwAAAI7ECCDanW1LJ8TG6/3DRmmH36dsj0c9DLeMMIey1fX1qjzRowkNPfX1H3YoNtWtCb/qpfgRe59mCgAAAHRlBEBEhy3lylSuO1am0cp0TFMqkqWd/oC6ezzKss39XPnQ1hXFm3XUiUm68rR+qjSCuqRkq15xDZNsBr8BAADgPARARE1jqa28T2tUurFefcclK2t0rFzxzZ9jGdLS2hpds2aTfLatZLdLz44crMPcMXtc+OX7BsbEanB8rD6trNanlU0rS83pkaUepksKOnsKqN+UCqygGm1LPd0eJQRbPwcAAACdHwEQURGotPXypRtU8N+6b1sKNeVXPTX2J5myvpfs8hTU1as3hvb2qwoE9dNVG/XOmOFKs/e9AmJKUHpuxGC9UVah5buqdFpmho5LTpLp8PBXbdp6qKhYz+TvkCSNSozXH4YNVI99bMEBAACAroFvfIiKsrV13wt/Td69v1D1RX5JTZvFN7gM1VpWi3N3+v3aGdy/Iascy9RlGd30l0EDdHpSstIsls1f0dAQCn+StLKmTk8XFst28bMBAADo6giAiAp/dUOLNitgSz6/yrYEtCqvXlds2KzfbsnXvUP7q2fsdwu3ZHjcynC79vu1LMtWIGC1OmXUCQzD0Iqa2hbt75TtUh0bCwAAAHR5BEBERbdeluJSv5uBbBjS2Y/311+vzNNTJ3yjN09erwuWJylQb+mWdVt0aa/ukqREl0tPDh+kDEbyDoht2xqeEN+ifWJaiuJbmVIbTYYhmWbHrQ8AAKCz4B5AREVirxhdcHdQn7wepx0bpWN/kqgvXixV0TdN00L9DZY+uyVfFy7so/REt8ZtjtXSXQPVrV+sMg03o3kHYUxcnGZnd9OrxTslSX3jYnRFz+5h34YjXGrc27W25gMVN2zWiOQT1ct9mFxWQrTLAgAA6JQIgIiKQHyyuh/ZTafErVB9fqliRh2vRTdVtXheTr1bJ73l1qJn1oXazn5qkAaemshm7gcoxTJ0d5+euiy3uxosS328XqV00FVA69xFenjDmdrZuE2S9O6OJ3VB39/piPgL6H8AAIADwBRQRE2gW65iTpyqjIsvUszAPuoxquXUxIQYt9Y8U9qs7bXrN6u+pOXiMD9k2H7VNlbJNAJhq7mriAlKgw23Rrs6bviTpKLG1aHwt9uivDtVb5bu5QwAAADsCwEQUWXbTQu0GLG2Truvn2ISv1vcZfQF3RRsbBn0GqqC8lXvPQCapvR5Xr4u3bhFx63L082bt6u4oTIi9SOyAravRZvfapAlQj0AAMCBYAooOoz04V5d8e4I7drqU0yKS6n9PWrYacnlNRT0fTfdr/vweCVk730V0J21lZq9IU9l/qaQ8EK5XxsafXpxoEdud8tRRnRcPWKGKdaVqIZgTahtUs4VireyWbMUAADgADACiA7Dtm3FdTeVMy5W6cM8MmOkhFxTP/7rUKXmeiVJPQ9L1JlPDJS5jxy3sa4+FP52+7S2Qfn19ZEsHxGQbPXV9UOX6KiMM9QrfqTO63OvJqbNlc0qsAAAAAeEEUB0aLak7ofH6Kf/HC5fjaXYdFNG7L7PiXe1/LuGxzAUu4d2dGy2LWUEh+nc7o/IMnwyg3Gyg4z9AQAAHCi+EaPDs23JlSzF9Wg9/EnSoPh4/Sg5rlnbddlpyk1MiVCFiDQ7aMoIxMpm/w8AAICDwgggOoWgx1SVLHWzpGArq1bGeBN1f+/uOre2QVsafRoWF6PRcXEKWvy9AwAAAM5GAESHZprSCsuvBRsKtL62Xj/KStd53bPUO7jve8D69Oyp+NJqTWinOgEAAIDOgACIDsHvMmRLirFsfX+W3ybD0rn/Xavqb4f9ntxepIIGnx7s10sedgIAAAAA2oQ5cYiqgCF9EWjUK5vK9I8NFVre0KD6730q19bVh8Lfbm+UlGm71fpG8NHichlyu/nVAgAAQMfDCCCiakuDX7Xv1Kns10Wq3xWQ+6JMFcztpoGZTds+xJktg1S8y1SM0fG2ATAMab0d0P8VlanM59c53TN1iDdG3n1kVZ/bUNC2FW8ZLHACAACAiCMAImpcLkN13/i07OptobZv/lCiuBS3Bl+TI8sX1NC4OI1OStCK6trQc67p21M99xIADUNylRercvM3csUnycrpLdtun7C4WUFN/3q1Gr4dnXy1eKdeGDVEE7xxLZ4bNKUvfY26e/127QoEdWXvHE1JTlYS+9sBAAAgggiAiAr3rhJZO4tV/d+cFo9teKlM4y7JVmKsVOn36+q+PbTLH1RefYNGJiVqdU2NtgaC6itXs/MMQ9Lqr7XusgvlL9spMzZWfe9+UDGTTpNtRvajbhjSx7uqQuFvt99ty9e4oYPl/sHedWsDfp31vzWh41+s2yLPkP6alZQsBgIBAAAQKdyohHbn2r5e62edojVnTFV6dstgltYvRoXySZIaLVs/XblBt6/fqn+Wluuyb9br4a2F8tkt51W6qsq1ad5c+ct2SpKshgZtvv5qmflbIvuGvhVUy+QWtNWi1TAMfVxZ1eK5T+YXqcFkBBAAAACRQwBEu3IFfSq4/9fyFe+Q7fcrs3uZug3+bnd3l9dQv2sz1ehpik39vF4NiItVnWVpY12DJOnw5ET1cntaXNsq3ylfYcEPGi35CvMj94a+ZdvShJRkeX8wNfXnfXLlCf4wAtpKc7cMvlleD0PyAAAAiCi+b6JdGbXVqv7sE0lSt9NmKTF/mcb9caZK1wZkNNqq6m3oH5lV+qUnV7KkpKD0l5GD9cfCYv27olKTu6VpTnaW4vawGbyZmiZPVrb8JcXN2j3Z3dUea4YOMtxaMnaEni8sUYnfr4t7ZGtsTKx++OK2LY1PTlKGx60yf9NeFqak6/v2lKtFWAQAAADCx7C74NKDZWU1sqzv3lZmZpJKS6ujWBF2c1l+Fd14teL7D1Dl8o9V/cVn8hx3oip/fovysnsoOzZOw2NilPzDxVBMQw2GFGdLtrXnj6xhSPbXy7T+0gtk1dVJpqm+8+9W/MxzZblj2uHdNXG5TBmGFAjsO3YWmJY+r65RTdDSkcmJGmS6ZXTc3S06NH7HnYX+dh763Fnob+ehz8PLNA1lZCTu9XFGANGugqZHudfforK//UXVX3wmSfJ/+J7iP3xPp/72IcVOP0d7uL1PsmzFquX9dN9n25J56NEa8fq/ZJeXyk5Ol53bR5bZcrpoJAWD+5fici1TuQnJTcHVVouRQgAAACDcuAcQ7c7u3lvVX33eor3q3+/L5Trwj6S7eLvKH7hD6y85RyWvviyZRruHvwPR9cbgAQAA0FExAoh2Z8lQygmTVP35p6G2hFlT5f9/p2uT/9/K9AxQQjCnTcHI3VCjrddfpZpvg2XJ9m2qXPaRBi38pwLJGeF+C52Gv8JWyZoGNVYH1W1QnJL7u1o/CQAAAF0WARDtzrJspU49XbveWaqar79Q+i+uVtFZ/ZXvW6ZPNy+SZQf18yGvKj04fL+vGSzcHgp/uzXmbZd/2yYZo5wZAH3lthZeukl5X9ZIkkyXdMkrw5V5qDfKlQEAACBamAKKqAhk5qrv0y+p30fvauUsr/6ad5u216zVmX0f0SFpU/VK3h2yXY37fT3TG/PtTvA/aI+N3cOznaF4VUMo/EmSFZSW3LxFVgN7DQIAADgVARBRE4xP1sr4r/XPwkd0Qs9HlWfcqWvW99D6wDz1TZ0jn9GG1aByeqv7JZc1a0o7dZrMXgPCXHXnUV8RaNFWsa1RViM3HQIAADgVU0ARNZarUf8ueU5HZf0/3b+tb2ij9011Dfo8aaAmjEjb72sFXR5l/PT/KenoY1W38r9KHD5C7lGHKxibEKny98gwDPld1XIrRgpEdwGazMFxLdoOOy9L3hRD1j7XUwUAAEBXxQggosa0PcqOHSCX+zBtrPM1e+y/1fXKa2zbvgjBxDS5jj5JyZddr6zTz1QwpVs4y21Vo2unltf+UQ9sPEVP512oHcbXkhG9oJU2yK0L/jJEKTlemS7piAuzdPRl2YQ/AAAAB2MEEFFjB01NzvmZllcW7/Fxr3lgf5+wo7CvgmFIn1b9VX/Pu0uSVNywWeuq/qObh72rdHtIu9cjSXJJvY+L02XvDFfQZysmzZQdxUAKAACA6GMEEFGVaY3SMamjNC0ruVn7GdnxyvTsik5RB6DRVaa3ih5r1ha0/SpsWBWliprYtuRKlLzpBuEPAAAAjAAiumzbVpqdohnp7+nolKHaWOfVoPhG2f6Xta1utEZ4ZkS7xP1iyq0EV4rqAruatXvNlvfhAQAAANHCCCCiLmg06LPiB5Vk/1eHJ0m2vEqPHaeGYO2ednbokDzBFJ3R+85mbeneXOXGjo5SRQAAAEBLjAAi6rxWqqb1eUY/X+/Spm8Xg/EYWXr50CMVhdv5DohtSwM9x+sXw97Q+uplSvV014CEcUoI5Ea7NAAAACCEAIiosyxbhb7e2lS3JdTmt23dt3mnnh+cKk+wc6RA04pRjg5Xj6QjmhaiabkNX5dge2pUHFivCl+BMmP6K0ODZVjR3fICAAAA+4cpoIg6w5DKfC1D3rb6RjV2wi0LorEKaXuwfVLxV3Va+ssSfbMgTnXrE/XQ+jO03ve2jM4yVxcAAMDhGAFE1Nm2NDYhpkX7hYkxSmtokN8TG4Wq8EP5y+v0wo/Xh45j/thN019+UC9svU63DD1CsYGsKFYHAACA/cEIIDqEwfnb9VSSRz1jYxTvMnVVcpxOef9NBfI2t3quYRtqLLXlK7dlmoxERYLdKL3z2/xmbY01QQVW9JbfapDPro1SZQAAAGgLRgDRIXga69XvorP1wvkXycroJmPhS0ocNEgae5jsFZ/K06e/AimZLc7zldta/mSxPvnTDnniTE2+tbeGzUiJwjtozjAk184i2X6flJmjoMsb7ZIOim0bsvYwTdcOGBqSfIwSje5RqAoAAABtxQggOgSz9wAlHjJW7q2r5cmuU+J9/0/mgF5ac94srTt3htafOUXugk3NzzENrX69QsueKpIVsNVYHdTrv9yi4hUNUXoXTVyNdap/5TmtPvUYrTrpKBXdeLXcOwuiWtPBcsXZOv7a5iuauryGuh3m0xk9fy0zwH6HAAAAnQEjgOgQgnFJSv/93foykKftviRZMtR/To56xwRVdf+T8hXkq/ip3yvr9gcUNFySJKtB+vKvpS2utfnfVRr9o5ajhe0luHaFtv7ql6Hj8jdflze3l9KvvU1WJ10fxral/icm6rw/D9Ynz+xQco5XR81NV/oIjxRgBVAAAIDOggCIDsEwDK1zSdesyVCJzy9JSnHH6/mzf6zYx5+XVVurqk//o+z6Wik+uekkb0BZw70qWVff7FrdBkZv0RjDkGq/+V+L9rLXXlW3S38mKyG1/YsKEzNO6nNCvPqfOFAybAWtrrvVBQAAQFfFFFB0CC639H55IBT+JKkyENTCCktpJ0ySJGXMOENmcop27zhQYW5S70uKFJPkCp2TMcijHuOj97G2bcnbs3eL9vjhI2THxkehovAL2lZT+AMAAECnwwggOgRDprbXN30cM70e9Y2L1fraOm2ql4KWrdjf/0lvHnqk3t+0VZPSU3V8SrLqAztV0He9fvSPKfJvNGV4alWY85bqsy1JOVF7LzGjxyrpyKNV/dlySZIrIVE9r7u50y8EAwAAgM6PAIgOwe8P6rTsDA1JTFbAlr6qrNYN/XvpODtRCVcv0Gtmre7bnK+gLb21s0KnZqTptoGH6a41KSpoKJJSpJGJHl3VPV3JruiuSBlMy1bvR55RYNM6WfV18vYfJKt7b3XCPe0BAADQxRAA0WGMiUvRQ1s36OuqGvX0xujHeWla8sv1qiz0KefwRD1xRz9d1bhVftvW0rIKzczppoKG76aMflPjV6WOV7wVmQVgXC5DhmEoELBafW4wKV3GmKPlkhSUCH8AAADoELgHEB3GJl+jvq6qkSRda2Rr+SVbVVnokyQVfVGjvBuLdXZit9DzK/wtVyBZUeWTYYT3Y20Y0k5zlV4vu03PF12mbfbHCprR3WoCAAAAOBCMAKLDaLS+G1mLK7D/f3t3HldVve9//L32ZgMCMqiAiIFjOIVmZVaWmXnUDDGH22B6Go6SZmadLLvV1TRv96bnZGVW9vDRT8u0MrVjmZVZVtqc1eWY1jErZRKUQdgMe/j+/rDoEBagyN6wX8/Hg8fDvfYaPpvPAn37/a615HHVHDY79H9OpZa3lSRd0iZKcd7aAfCSNlHyeOoeoWuIw7Y9emj3ZXKZSknSJ4c36Obuz6mb/dJGPQ4AAABwqjECCL/RKTREfSKO3SnTRNc+NVtFBymsdZAe6J6sh2IjlfTqeo1pfeyRDzZJUyJDda6rslFrsizp26MfVIe/X7yWvVgmiFFAAAAANC+MAMJvJHgs3X96J71VUKTvy13qe32cvnrmkKRjQWzM3zrr9B6Rcrm88n79sQoW3qdZl47QlFFXyOb1qNVjKxX5nwtkWrdt1LrMcS7gM/KIC/sAAADQ3BAA4T+MdKaxKaFVkIqqihRzpVfnDEuU0xmqmM5hiuxkV1WVR5LkSOqs4Pj2qti6RfatWyRJVrfTZU9MbtRnkxsjpUQMUpAVLLepql5+WYe/ynK3asQjAQAAAKceARB+xb7nK5VMGCWbpOKfl3V7fIVCk4dK7kp5gsJkjOSOilX3//eishYt0NFPPlLURUPU4bY5codHHXe/lrFUedgrK8hSSBtL3gY8yLyt6ak7e76m9wtWqcSVr8Gx1yspaIDUuJcaAgAAAKccARB+w2azVPTOm7WW5z79uFp/+bmKtr2l9hm3KOzi4TLhkSrzJih48hJ1ucuh0MQwuazjn85VR4w+eipPH67IVUiEXSPmJun0yyJlC6lfXcZIseYMTYj9myxLxx4DQfgDAABAM8RNYOA3jJHsrSMlSY52sWp9wUUKjm8ve1i4nLszVb7vO+2/c6Zc32Tqu40FWjpyv56acECPjzmg3M/LZDvO2WyzWfrnxkLteCpHXrdReZFbG277XvmZDb9ZjMfjrdczABuLzSYFBfEjCgAAgMbDCCD8hjFGkRcPU1BEpN7r3V9vBrXSxZ4KpbVyqGTUxdXrlboT9dLtWTI/Z7GyApfWzsjSTf9wyB4XVmOfHqf0+fP5tY61f2eJEs6Ja9BU0KZUmOvVd+8U6fC/KtRtaLQ69g9Tq1BfVwUAAIDmjuEF+BVn59P1t7MGqUjtNCE/StFV7bW4KkjB12dUr1OSb1WHv+pluVUqy609qmcLkWJPr52c2iSH+m34Kz5stPaqvXr77p/05YpDWnfNt8pcX8hoIAAAAE4a/6KEXznodmtCcVt1X1qp076Qkt/yaOyuKFVdPPrYCjabopLCZVk1twtvG6Sw2OBa+zOW0cWzEhUc9uup3q57qJLOjTiVH+Ok5O52quiHmmH2/QcPqrDA46OKAAAA0FIwBRR+JaLSpthMr/Z7pLcXHVBIa7sGZXRQ2zNSFH73PEWce4HKf/xEl9+XqlcfKJDxSo5WNv3H4vYK6Rghj6f2qF50ikPT3uyjQ3vLFRRqU1yPUAW3tY5zdP/gcdX+DO5Krwz5DwAAACeJAAi/Ellu6etMp/65+YgkqaLEo62LDujaPimKm3STbB6X8v9rttoldta0VbeprMimyOhKmT3PSZferuM9nN0Yo7CONnXqGN7En+bEtO/ZSqGRdlWU/Jr4+k9pr+hYu7xebj8KAACAE8cUUPiVCkl7thbWWp6/r1yS5LEHK/aa62Ql9FLF7s/kefFOHcwYqrCeveTxtIxw1C7Rrokbe6r3le3U4YxwDf3vJJ07NY7wBwAAgJPGCCD8irO1UVxKK5UectVY3jopRMZIxm2U7bhMm9YckPOIS/3S/leDnqpQcL8ktZQZkl6vFNclSGMWJ8ntloLsxm9vWAMAAIDmhRFA+BV7qKWed7avcdOWxLPCFdbHLs/OrSra7dTam75XWYFLxivteqVMX7zXTt7waN8VfYp4PV7ZLC/hDwAAAI2GEUD4lThj02dd3frT5tPl/FelQsPtKuwkub7brsOvrtfh1D61tvnixcM6f0aCgiKbvl4AAACgOSEAwi94bZayjFsuj9G5rgptcmfpw+6tlOCq0lU/Zcs7/x61nfs/ch6q/ay/dp0ccrSyZI5zA5imZFmSveSwvCXFsrWJlbtVa5/WAwAAAPwWARA+V2ozWpabpycP5Mgr6cLo1pr747809N23pH99K0ePi1T4H2u1domlAZOidFr/Sh34wilJsgdb+tPMMNlCJY8PLwK0ZGR2fahv/3qzqnJzFNazlzovXiZPpx6+KwoAAAD4DQIgfG5XRYWWHcipfv1+0VG9kpKqsY8uks2ya781Qe8tLJUk/fTZUV04vYMuuqG1KrJzFRVeoA49o+Q+zvP/mpIt50ftvuFqmcpjI5TOb3Zr383Xq9uLW+QOj/JpbQAAAMAvuAkMfMpms/RZydFayzcfLVeHZ9cr4X+f187Vzhrvvb8sW7LZ1bV3gToM6yF3Qqcmqvb3uQ7+VB3+flHxw3558rJ9VBEAAABQGwEQPuX1GvUOD6u1/ILoSAXHxEqx7WV31D5NncFBKurSVSaq7Qkf27IslWd7lbWjXEf+WSVv+QnvSvY2teuwh0fIFsmdaQAAAOA/CIDwubPDwzW0TXT1646hwZqS2F6WxyikraVL7+xYY/3IxGDt6ODRVQXlyi4rOuHjFnxdpceHZmrVxL16atRuvTUvS+7SE9uXldRVHW75678tsNTpv/8mb2ziCdcHAAAANDauAYTPtfFaeqxbJ+13VanSa9QlJETRP9/QxRip9/gYte0aqi82HZaje7BKBwbpPysOqMoYvVNarsnxNrlc3gYd01suvTL7e7nKf93uixfy1W9CO8WfHdLgz+B1hCrm+psVNeRPcuXnKbhjksxpXWV4hB8AAAD8CAEQfiHMI/W2BR8bk/7N3TztYVKHIeF6KKlAOwrzVVDhqn5vr1eSrAYfz11mlLen9pzP0nyX4tXwAChJnpAwKaWvglKkhsVRAAAAoGkwBRTNgs1ldFZkuApcrhrLL20XI5er4c9/CI62KeXS6FrL23Q6sfAHAAAANAcEQDQLBZZXRR6vJiTEym5JrWw2ze7cUf2jok9sh0FGI+5PUsezIiRJIRF2jXukq6K7ORqvaAAAAMDPMAUUzcI3FRX6+/6DOjMyQrd3Pk1eY7Ql/4iujm2r2vcQrZ+wRJuuXd1dpXluBYfZFBpncc0eAAAAWjQCIJoF98/JbFdJqXaVHLtVZ7BlnfS1dlaoUetkuyQR/gAAANDiMQUUzUJKq1BFBdlrLMtISlA7wykMAAAA1BcjgPBbLrulchlFGUsdjE0b+/XSiuw8ZZY6NbF9rIZFRUpehu0AAACA+iIAwu9YlvRPr0sLvv1J+5wVuiohVpPjYtXZa9fCjonyWJLdY2R41gIAAADQIARA+J0f5dEVX+5W5c+je4/+mK0jLrfmJybK5jGySWLcDwAAAGg4LqCC3/muorI6/P1iTc4hZVsNf94fAAAAgF8RAOF3gm1WrWXRQUEq8RIAAQAAgJNBAITf6dIqVL0jaj7dLyO5g0pdBEAAAADgZHANIPxOB2PTzORE/VRZqRK3R7HBDm0vKNKYmBid9IP/AAAAgADGCCD8juUxOjcsTG3tQdpVXKqDzgr9V5fTFOetPTUUAAAAQP0xAgi/FO21NK51pK6Ijpbda+TleX8AAADASSMAwm8ZIwUZr/J3uZT1f2WyOywl9o1QTC+7vEwFBQAAABqMAAi/lvupS89ctVueqmMjgGExQfrz6h6K7sWpCwAAADQU1wDCb4UEO7Tz6ezq8CdJzkK39r5dpLAwTl0AAACgofhXNPyW2+nV0TxXreVH86rkcDh8UBEAAADQvBEA4bdMsEdnXRVba3mPYW1UXFzpg4oAAACA5o0ACL/l9UrJ57XWyLnJiuoQrHZdQjX+0W6K6x3i69IAAACAZok7acCvhZ1m0/k3t1Wvy2Jks0sh8ZLH4+uqAAAAgOaJAAi/53R6FRx/7M+EPwAAAODEMQUUAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAJEkK8LOBVsNqtey9Cy0fPAQr8DC/0OPPQ8sNDvwEPPG09d30vLGGOaqBYAAAAAgA8xBRQAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAJEiwyA2dnZmjhxokaMGKFp06aprKzsd9fdsWOH/vznPzdhdWgsmzZt0mWXXaZhw4Zp9erVtd7/5ptvNG7cOA0fPlz33HOP3G63D6pEY6qr57+46667tH79+iasDKdCXf3eunWr0tPTNXr0aE2fPl3FxcU+qBKNqa6ev/XWW0pLS9OoUaM0Z84cVVVV+aBKNJb6/k5/9913dckllzRhZTgV6ur30qVLNWTIEKWnpys9Pf0PzwmcJNMCTZ061bz66qvGGGOWLl1qHnrooVrreDwes2LFCjNgwABz7bXXNnWJOEm5ublmyJAhprCw0JSVlZm0tDTz3Xff1Vhn1KhRZteuXcYYY+6++26zevVqH1SKxlKfnufm5pqMjAyTmppqXn75ZR9VisZQV7+PHj1qLrjgApObm2uMMWbJkiVmwYIFvioXjaCunpeVlZlBgwaZ/Px8Y4wxs2bNMmvXrvVVuThJ9fmdbowx+fn5ZsSIEWbIkCE+qBKNpT79zsjIMF988YWPKgwsLW4E0OVy6dNPP9Xw4cMlSWPHjtWWLVtqrbdv3z7t27dPCxYsaOoS0Qh27typgQMHKjo6WmFhYRo+fHiNPmdlZamiokL9+vWT9PvnAZqPunouHfvfxaFDh2rkyJE+qhKNpa5+u1wuzZs3T/Hx8ZKklJQU5eTk+KpcNIK6eh4WFqZt27apXbt2cjqdOnz4sCIjI31YMU5GfX6nS9K9996rGTNm+KBCNKb69DszM1NPP/200tLSNH/+fFVWVvqo2pavxQXAwsJCRUREKCgoSJIUGxurvLy8Wut1795dCxcuVFRUVFOXiEZw6NAhxcbGVr+Oi4ur0effvv975wGaj7p6Lkl/+ctfNGHChKYuDadAXf2OiYnRpZdeKkmqqKjQ8uXLq1+jearPz7jD4dD27ds1ZMgQFRYWatCgQU1dJhpJffq9atUq9erVS3379m3q8tDI6up3WVmZevbsqbvuuksbNmxQSUmJli1b5otSA0KzDoCvv/66Lrroohpfd9xxR631LMvyQXU4lYwxtZb9e5/reh/NDz0NLPXt99GjRzVlyhT16NFDV1xxRVOUhlOkvj0fPHiwPv74Yw0ZMkTz5s1rgspwKtTV72+//VZvvvmmpk+f3pRl4RSpq9/h4eF6+umnlZycrKCgIN1www3avn17U5YYUJp1ABw5cqTee++9Gl8rVqxQaWmpPB6PJCk/P19xcXE+rhSNLT4+XgUFBdWvDx06VKPPv32f86D5q6vnaFnq0+9Dhw7pmmuuUY8ePbRw4cKmLhGNrK6eFxUV6YMPPqh+nZaWpr179zZpjWg8dfV7y5Ytys/P17hx4zR16tTqn3c0T3X1Ozs7W+vWrat+bYypns2HxtesA+DxOBwOnX322dq8ebMkaePGjbrooot8XBUa2/nnn68PP/xQR44cUXl5ud58880afU5MTFRISIg+//xzSZwHLUFdPUfLUle/PR6PbrrpJo0cOVL33HMPo8EtQF09N8Zo9uzZys7OlnRsFlD//v19VS5OUl39njlzpt544w298sorWr58ueLi4vT888/7sGKcjLr6HRoaqkWLFunAgQMyxmj16tUaNmyYDytu2VpktJ47d67mzJmjJ554QgkJCfr73/8uSVqzZo0OHTqkW2+91ccV4mTFx8frtttu0+TJk+VyuTR+/HilpqZqypQpmjlzps444wwtXrxY9957r8rKytSrVy9NnjzZ12XjJNSn52g56up3bm6udu/eLY/HozfeeEOS1KdPH0YCm7H6/IwvWLBAGRkZsixL3bp10/333+/rsnGC+J0eWOrT7/nz52vatGlyuVzq37+/rr/+el+X3WJZ5niTcgEAAAAALU6LmwIKAAAAADg+AiAAAAAABAgCIAAAAAAECAIgAAAAAAQIAiAAAAAABAgCIADAbxw8eFA9e/ZUenp69dfo0aNrPCC4srJSS5Ys0ZgxY5Senq60tDQtX75cv72p9bPPPquUlBR9+eWXf3jMd955R5MmTdKYMWM0atQozZo1Szk5Oafi4/nMgQMHdMstt/zhOnv27NGgQYOaqCIAgK+0yOcAAgCar9DQUL3yyivVr/Py8nT55ZerT58+SklJ0fTp09W5c2e98MILCgkJUWFhoTIyMuR0OjVr1qzq7dauXau0tDStXLlS/fr1O+6xNm3apCeeeEJPPPGEkpOTZYzR8uXLNXnyZL322msKDg4+xZ+2aWRnZ2v//v3Hfc/tduu5557T8uXLVV5e3sSVAQCaGgEQAODX4uPjlZycrB9++EElJSX6/vvvtXz5ctntdklSTEyMHnroIWVlZVVv8/HHH6u4uFizZ8/WsGHDlJOTo4SEhFr7fvjhh7VgwQIlJydLkizL0tSpU9WhQwdVVVUpODhYjz/+uF577TXZ7XZ17txZ9913n2JjYzVp0iT17t1bH330kQ4fPqzJkyfr8OHD+uSTT1ReXq4lS5YoJSVFkyZNUteuXZWZmanCwkKlp6dr5syZkqStW7dq6dKl8ng8ioiI0N13363U1FQ99thjysrKUn5+vrKystSmTRs9/PDDio+PV15enubPn6+cnBy5XC6NGjVKN910kw4ePKjrrrtOgwcP1ldffaXi4mLddtttGj58uO69917l5eXpxhtv1IoVK2p8D3bv3q29e/fq0Ucf1ZQpU05VGwEAfoIpoAAAv7Zr1y799NNP6tu3rzIzM5Wamlod/n7RqVMnXXDBBdWv16xZo7S0NMXHx2vgwIF67rnnau23sLBQWVlZ6t+/f43llmUpLS1NERERevnll/X+++9r3bp12rRpk7p37645c+ZUr5uVlaWNGzdq6dKlWrx4sQYMGKD169frwgsvrHHM7OxsrVmzRhs2bNDmzZv1zjvvaN++fZo7d64ee+wxbdq0STNnztT06dNVWloqSfrss8/0yCOPaMuWLYqMjNQLL7wgSZo9e7bGjRun9evXa926ddq5c6c2b94s6dhUz0GDBmndunW64447tGjRItntdj3wwANKSkqqFf4kKTU1VQ8++KDat2/f0NYAAJohRgABAH6loqJC6enpkiSPx6OYmBgtWrRICQkJstlsta71+638/Hxt3bpVL7/8siRpzJgxmjdvnm6++WaFhYVVr2ezHfs/UK/X+7v7eu+99zR27Njq7SZPnqwnn3xSVVVVkqRhw4ZJkk477TRJ0oUXXihJSkpK0ieffFK9nyuvvFIOh0MOh0MjRozQBx98oC5dumjgwIHV25533nlq06aNMjMzJUkDBgxQRESEJKlXr14qLi6W0+nUp59+quLiYj3yyCOSJKfTqT179ig1NVUOh0ODBw+u3qaoqOgPv1cAgMBDAAQA+JXfXgP47/r27auVK1fK4/HUGAX8+uuv9eyzz2rRokV66aWXJEnTpk2TdCzglZaWasOGDZo4cWL1NlFRUerUqZO++uornX/++TWOc+utt2ratGm1wqbX65Xb7a5+/dtrBB0Ox3HrDgr69a9bY8zvBlljTPX+Q0NDq5dbliVjjLxer4wxWrt2rVq1aiVJOnLkSPW1kA6HozrYWpZ13FoAAIGNKaAAgGbjzDPPVJcuXfTggw+qsrJSklRQUKAHHnhAHTt2lMfj0Ysvvqj7779f27Zt07Zt2/Tuu+8qIyNDq1atqhW6ZsyYoYULF+rHH3+UdGzEcdmyZdqzZ4+6dOmiQYMGaf369XI6nZKO3Vn0nHPOafDNYf7xj3/I6/WquLhYr7/+ui655BINHDhQO3bs0IEDByRJH374oXJyctS3b9/f3U9ERIT69eunZ555RpJUUlKiq6++Wm+//fYfHt9ut8vlcjWoZgBAy8QIIACgWXn00Uf18MMPa+zYsbLb7fJ6vRozZoxuvPFGvf322/J6vUpLS6uxzXXXXadVq1Zp+/btuvjii6uXp6WlyRij22+/XW63W5WVlerdu7dWrlyp4OBgjR8/Xjk5OZowYYK8Xq+Sk5O1ePHiBtdcUVGh8ePHq6ysTNdcc43OO+88SdLcuXM1Y8YMeTwehYaG6sknn1Tr1q3/cF+LFy/WggULlJaWpqqqKl1++eUaPXq0Dh48+LvbdO/eXXa7XePHj9dLL73E6CAABDDL1HUxBQAAOGGTJk3SxIkTNWLECF+XAgAAU0ABAAAAIFAwAggAAAAAAYIRQAAAAAAIEARAAAAAAAgQBEAAAAAACBAEQAAAAAAIEARAAAAAAAgQBEAAAAAACBD/H0E+XZwInQqKAAAAAElFTkSuQmCC\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "library.plot_clusters(X,labels,num_docs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}