{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c000",
   "metadata": {},
   "source": [
    "# CRISPR knockouts\n",
    "\n",
    "A CRISPR screen asks what a gene does by removing it. Genes whose products work together, such as the subunits\n",
    "of one protein complex, should give the same phenotype when knocked out. A good morphological map therefore\n",
    "recovers known complexes, and it places a gene of unknown function next to its partners.\n",
    "\n",
    "This page uses the CRISPR arm of JUMP {cite:p}`Chandrasekaran_2023`: U2OS cells, each well targeting one gene.\n",
    "{func}`~mantispy.ds.jump_crispr` returns the profiles as the consortium assembled them, corrected for well\n",
    "position and cell count, normalized and feature-selected. It joins the gene each well targets, which wells are\n",
    "controls, and the chromosome arm each gene sits on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c001",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:26:01.363501Z",
     "iopub.status.busy": "2026-10-21T00:26:01.362971Z",
     "iopub.status.idle": "2026-10-21T00:28:15.618011Z",
     "shell.execute_reply": "2026-10-21T00:28:15.616062Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'wells': 51185,\n",
       " 'features': 595,\n",
       " 'plates': 148,\n",
       " 'genes': 7974,\n",
       " 'median wells per gene': 5,\n",
       " 'control wells': {'no-guide': 4724, 'non-targeting': 2754, 'PLK1': 569}}"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy.stats import spearmanr\n",
    "\n",
    "import mantispy as mt\n",
    "\n",
    "wells = mt.ds.jump_crispr()\n",
    "obs = wells.obs\n",
    "is_trt = obs[\"Metadata_Control_Type\"] == \"treatment\"\n",
    "treated = obs[is_trt]\n",
    "{\n",
    "    \"wells\": wells.n_obs,\n",
    "    \"features\": wells.n_vars,\n",
    "    \"plates\": obs[\"Metadata_Plate\"].nunique(),\n",
    "    \"genes\": treated[\"Metadata_Perturbation\"].nunique(),\n",
    "    \"median wells per gene\": int(treated.groupby(\"Metadata_Perturbation\", observed=True).size().median()),\n",
    "    \"control wells\": obs.loc[~is_trt, \"Metadata_Perturbation\"].astype(str).value_counts().to_dict(),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c002",
   "metadata": {},
   "source": [
    "About 8,000 genes, five wells each, over 148 plates. The negative controls are wells with no guide and wells\n",
    "whose guide targets nothing in the genome. The positive control is PLK1, a kinase cells need to divide.\n",
    "\n",
    "The consortium's CRISPR recipe continues from these profiles by sphering against the negative controls. Unlike\n",
    "BBBC021 on [Plate artifacts and corrections](../tutorials/profiles/artifacts.ipynb), there are far more control wells than\n",
    "features here, 7,478 against 595, so the control covariance is well determined. A copy is kept as published,\n",
    "for a comparison further down. `modz` weights each well by how well it agrees with the gene's other wells, which\n",
    "suits five noisy replicates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c003",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:28:15.621738Z",
     "iopub.status.busy": "2026-10-21T00:28:15.621449Z",
     "iopub.status.idle": "2026-10-21T00:28:23.769027Z",
     "shell.execute_reply": "2026-10-21T00:28:23.768263Z"
    }
   },
   "outputs": [],
   "source": [
    "def per_gene(profiles):\n",
    "    \"\"\"One modz signature per targeted gene, leaving out the controls.\"\"\"\n",
    "    signatures = mt.tl.consensus(profiles, method=\"modz\")\n",
    "    return signatures[signatures.obs[\"Metadata_Control_Type\"].astype(str) == \"treatment\"].copy()\n",
    "\n",
    "\n",
    "published = per_gene(wells)\n",
    "mt.pp.sphere(wells, reference=\"negcon\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76ea2466",
   "metadata": {},
   "source": [
    "## Do the two negative controls agree?\n",
    "\n",
    "The negative controls come in two kinds: 4,724 empty wells (`no-guide`) and 2,754 wells carrying a guide that\n",
    "matches nothing in the genome (`non-targeting`). The sphering above pooled both as its reference, taking the two\n",
    "for one inert baseline. A non-targeting guide cuts nothing, so it carries no Cas9 cutting toxicity: the\n",
    "double-strand-break burden and the TP53-dependent DNA-damage response that arise at real cut sites are a separate,\n",
    "well-documented confounder ({cite:p}`Morgens_2017`; {cite:p}`Alvarez_2022`), one controlled with\n",
    "dedicated safe-targeting guides, which this screen's control pool does not include. What a non-targeting guide\n",
    "does carry is the burden of delivery and expression: the lentiviral integration, the sgRNA and the Cas9 that the\n",
    "empty wells never received. Comparing `no-guide` against `non-targeting` therefore probes that\n",
    "delivery-and-expression load, not cutting. The field usually treats non-targeting guides as the working baseline\n",
    "and normalizes to them, so checking that they behave like empty wells is a standard QC step. If they do not,\n",
    "`non-targeting` is not quite empty, and which wells define the reference matters.\n",
    "\n",
    "We test it with a retrieval question on the sphered negcon wells, where plate effects are already gone: does a\n",
    "control well retrieve others of its own kind (`no-guide` or `non-targeting`) beyond chance? `pos_sameby` makes a\n",
    "positive pair two wells of one kind and `neg_diffby` makes a negative pair two wells of different kinds, with\n",
    "`reference=None` so no wells are held out. An mAP near chance means the two kinds are one baseline; an mAP above\n",
    "chance means they separate. `null_size` can stay modest, as there are only two groups to score."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "36404b7c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:28:23.771158Z",
     "iopub.status.busy": "2026-10-21T00:28:23.770991Z",
     "iopub.status.idle": "2026-10-21T00:29:30.007975Z",
     "shell.execute_reply": "2026-10-21T00:29:30.006392Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Metadata_Perturbation</th>\n",
       "      <th>score</th>\n",
       "      <th>mean_normalized_average_precision</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>qvalue</th>\n",
       "      <th>below_p</th>\n",
       "      <th>is_significant</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>no-guide</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.019</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.105</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>non-targeting</td>\n",
       "      <td>0.383</td>\n",
       "      <td>0.023</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.011</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Metadata_Perturbation  score  mean_normalized_average_precision  pvalue  \\\n",
       "0              no-guide  0.639                              0.019   0.105   \n",
       "1         non-targeting  0.383                              0.023   0.006   \n",
       "\n",
       "   qvalue  below_p  is_significant  \n",
       "0   0.105    False           False  \n",
       "1   0.011     True            True  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "negcon = wells[wells.obs[\"Metadata_Control_Type\"].astype(str) == \"negcon\"].copy()\n",
    "mt.tl.map(\n",
    "    negcon,\n",
    "    pos_sameby=[\"Metadata_Perturbation\"],\n",
    "    neg_diffby=[\"Metadata_Perturbation\"],\n",
    "    reference=None,\n",
    "    null_size=20_000,\n",
    "    key_added=\"negcon_agreement\",\n",
    ")\n",
    "negcon.uns[\"mantispy\"][\"negcon_agreement\"].round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a775e239",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:29:30.011488Z",
     "iopub.status.busy": "2026-10-21T00:29:30.011141Z",
     "iopub.status.idle": "2026-10-21T00:29:32.010742Z",
     "shell.execute_reply": "2026-10-21T00:29:32.009322Z"
    }
   },
   "outputs": [
    {
     "data": {
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fiLOVdWrZ1mWZbsmSJdxwww2MjY3xwAMPcNVVV3HDDTfwspe9bJfKOZfznW+5d7bPgw46iMkm8s6/rTvIz+Y73/kOL3vZy7jqqqtYsmQJuq7DDl6rW9+DqWB3tuBw62VT5/TVr36187qcem1OlXlXrv1crvt8yjubRx55hPvvv58PfOADnHnmmRQKBYQQVCqVGV/K8znOXPe5I3N9j73whS/kV7/6FZVKhV/+8pcce+yxXH311Xz84x+f0/Zbm+893V455/MZsb1rmiTJrD++ZqNpGv/f//f/8ctf/pLHHnus80N4+g/G7TnjjDPQdZ1f/OIX3HHHHZx55pkIIXjJS17Cn//8Zx588EEeeOABzjrrrM42e+K1v7vv5e6gAp0F9M///M+Uy2X+8R//cZvnXv7yl5MkCT/84Q93uI/TTz8dpjXtTLn99ttnjaA1Tdvml8HU6IIphmFg2za+78/5XGzb5rLLLuNHP/oR//Vf/8W99967zZtzruc0m6lfF//3//7f7a7z4he/GIAf//jHM5Y/+OCDPPHEE53n5+OZXIupsvzmN7/ZJui6+eabYfJDaWd0XeeYY47hfe97H1deeSX/8z//s01Au7vtjnLPVSaTAdjutZ361Tnl8ccf57777pvTvo877jiKxSL/8R//MWO553nbNGEef/zxLF26lP/3//7fnMo839fC7i7vjmx9zb7zne/s8nF2ts/dKZPJcMYZZ/CNb3yDNWvW8Jvf/GbGc3O99vO5p7tLrVbbpvn93//932HaZxNzOI83vvGN2LbNddddx4033siJJ57IkUceudPjF4tFTjjhBG677TbuuuuuTkBz0kknkc1mueaaa5BSzgh09uR12tG93NtUoLOAnv3sZ/P6179+myCFyS+UK664gquvvpovfvGLbN68mWazyR//+Ec+9rGPce2118Jk8HDSSSfxjne8g1/+8pfU63V+/etf8/Wvf53ly5fP2OdUsPD3f//3TExMsGHDBt785jezdOnSbY5/5JFHcs8998y5ypXJ5ivP87j00kuxLIvLLrvsGZ3TbM444wwuu+wyPvjBD/KFL3yBwcFBxsbG+OEPf8g73/nOzvmdfvrpvPe97+WWW26hVqvx3//931x66aWsWLGis958PZNr8dGPfhQhBBdddBEPP/ww5XKZr371q3zuc5/j7/7u77abMNL3fU499VRuvvlmNm7ciO/7/O///i+33XYbz3ve82Y0Uc51ePl8PNNyPxNTH94/+9nPtumrdv7553Prrbfyk5/8hGazyX333cdll10252DVcRw+/OEP86Mf/YhPfepTjI+P8+STT3LllVduM7TWMAy+8pWvcNddd3H55Zfz8MMP47ouTz75JN///vdnBHdHHXUUg4OD/P73vydJkt1yHeZb3tmsXbuWtWvXct111/HnP/+ZarXKjTfeyM9//vMZTVLzOc5c97mrbr31Vq644gruueceyuUyjUaDm266iaeeeqrzQ455Xvv53NPd5dBDD+XTn/40//mf/0m9XufWW2/l/e9/P+ecc868zqO7u5tXvepVfO1rX6NWq82pNmfKWWedxb333ku1Wu0ENKZpctppp3H77bfT19fHs5/97M76u/s6zfVe7nUL3Rv6QDF91NV0GzdulKlUatbh5UmSyG984xvy+c9/vsxmszKbzcpjjz1WfuQjH5EjIyOd9crlsnzjG98ou7q6ZDablRdccIEcGhqSAwMD8vWvf/2Mfd50003yyCOPlI7jyIMPPlh+9rOflXfddZcE5G233dZZ795775XHH3+8tG1bAvKiiy7qPLf1qKvpnvvc50pAvupVr5r1+bme02ziOJaf/exn5THHHCNt25YDAwPy0ksvnTEsvdlsymuuuUYedNBB0jRN2dfXJ9/whjfITZs2ddaZGi219fBeKaU8/vjj5Ytf/OIZy7Z3LXa0Hzk5mu6CCy6QpVJJWpYln/WsZ8lPf/rTMo7jzjqzjbq655575Kte9Sq5YsWKzn165zvfuc1IqPkOL3/yySdnLH/kkUckIL/1rW/Nu9zz3ef2fPKTn5TLly+XmqZJQP74xz+WcvI+vv3tb5dLliyR6XRannrqqfL++++Xb3zjG2V3d/dOyzHlS1/6kjzkkEOkbdvymGOOkbfffru8+uqrpWVZ26x7//33y4suukj29fVJy7LkmjVr5Ote9zp5//33d9ZpNBryla98pSwWixKQQGfk3vZGHh155JHbHOu6666TwDb3dD7l3dpf//pX+dKXvlQWCgXZ1dUlX//618tyuSz7+/u3GdE41+PMdZ+7cu6+78vvfOc78rTTTpOlUknm83n5nOc8R37hC1+Y8Zrb0bXfnrnc0+2V82/+5m/k2rVrt1k+26ipqX1s2LBBnnPOOTKdTsuenh75lre8RTYajRnrzuU8/vu//1sCMpPJyFqttsNznG5qZOvhhx8+Y/lnPvMZCchXv/rVs243l+s0l1FXc72Xe5uQO8tepuyXwjDEcRze/e5386lPfWqhi6Mo+4xXvvKV/O53v5uRXG1ftrfKu79dl33Jeeedx/r163fb5LyPPvoohx9+OJdffjnf+ta3dss+D2Sq6WqR+vGPf0ySJDOyEivKga5Wq/HLX/5yv3lf7K3y7m/XZbGbytD+pje9aaGLsiioQGcR+OxnP8s3v/lNNm/eTKVS4Uc/+hFve9vbOOmkk7Y7NYOiLHYPPfQQV199NQ899BDNZpMHHniACy64AN/3O1OY7Ev2Vnn3t+tyoHn88cf58pe/zGmnncZJJ5200MVZFFSgswhccskl3HfffZxyyin09/dz9dVXc8kll/Czn/0MTVO3WDkwHX744axZs4bXve519PX1cfrpp5NKpbjnnns44ogjFrp429hb5d3frsuBZGBggKOOOoq1a9fy7W9/e6GLs2ioPjqKoiiKoixa6ue+oiiKoiiLlgp0FEVRFEVZtLad9fEAlyQJW7ZsIZfL7bYpAhRFURRF2X2klNTrdZYuXbrTvqgq0NnKli1bWLFixUIXQ1EURVGUndi4ceM2swBsTQU6W8nlcjB58aZmYlYURVEUZd9Rq9VYsWJF5zt7R1Sgs5Wp5qp8Pq8CHUVRFEXZh82li4nqjKwoiqIoyqKlAh1FURRFURYtFegoiqIoirJoqUBHURRFUZRFSwU6iqIoiqIsWirQURRFURRl0VKBjqIoiqIoi5YKdBRFURRlP3HJJZc8420///nP8+ijj+7W8uwOURRx9dVXkyTJHtm/CnQURVEUZR/ymte8hjAMZ33u5ptvfkb73LhxIzfccANr167dxdLN3SWXXDKn4MUwDDRN48Ybb9wj5VCBjqIoiqLsQ175ylei6/pu3edXv/pVLr300r06WfXNN98851qayy+/nC984Qt7pBwq0FEURVH2KxtGa7z///6GF//DTVxw3Y/55l1/Iop3T7PHunXruOaaa7jjjjv4u7/7Oz784Q/TbDY7zz/66KO8613v4k1vehM//vGPd7ivzZs38+53v5u3ve1tPPjgg51mp1arxZVXXtlZL0kSXvOa13T+/uEPf0gcxwAMDg7O2Md0rVaLf/7nf+YNb3gDH/7whxkdHd1uWX76059yxhlnzGnbiy++mPvvv5+3v/3tvPOd72RsbIw777yTyy+/nI985CO4rjtj3QceeIC3ve1tvOc972FoaAiAf/qnfyJJEi655BIuvvhivvWtb3HTTTd1tgvDkNe//vW0Wi0Anv3sZ7Nhw4bO9ruTCnQURVGU/Uat5fPWb/6S3zyyCS+MGa25fONXf+LzP//f3bL/iYkJvvSlL/Htb3+bk08+mXvvvZdrr70WJpt/TjrpJLLZLCeccAJXX301X/va12bdTxAEnHrqqbiuy3HHHcfVV1/daXYKgoCf/OQnnXWTJOFHP/pR5+8f/ehHxHFMGIaceuqpNJvNzj6mb3POOedQrVY5++yz8TyPs846a7s1KH/+85859NBD57TtzTffzIc+9CGOP/541q9fz4tf/GK+8IUvcPrpp3P33Xfz8Y9/vLPfm2++mXe961085znPoVar8aIXvYgoijjllFMQQnDJJZdw6aWXcuyxx/LRj360s90tt9xCvV4nnU53lh122GH88Y9/fAZ3bcfUpJ6KoijKfuNnf1jHRMPbZvlP7n+cN57xbPIpa5ePUSwW+c53voOmaRx55JFcddVVAHzve9/jFa94Bf/wD/8AwPLly/nwhz/Mm970Jm655ZZOH5MrrrgC0zTp6+vji1/8IgAveMELOProo+dVjrvvvpuuri6uv/76bfZxzz338Oijj9LX18df/vIXAB5//HHWrVvHIYccMmM/QRAQhmEnqJjLtt/85jdZsmQJL3jBCzj22GP53e9+h23brFixYkagA3D99dezdu1arrjiCo4//njuueceTj/9dIQQvOIVr8Aw2qFGd3c3v/nNbzj11FP5yle+wgc+8IEZ+0mn0zNqz3YXFegoiqIo+41NE41ZlwdRwki1uVsCnf7+fjSt3eCRyWQ6zSujo6OsWrWqs97q1as7TT6HH344l156KQBr167ld7/7HStXruyse9BBB3Ueb91PZnu1MKOjozO2m37swcFBli9f3jkmwKWXXkpvb+82+7Esi0KhwPj4OP39/XPadsmSJTAZfHR1dWHbdufvqesxZfp5rlq1irGxsVnP5y1veQtf/epXWbJkCaOjo5x++ukznp8q3+6mAh1FUZQFEjZbBJUymmHi9PYgNNWbYGfWLu2adXnWMVneldujxz7yyCP59re/zbXXXouu69x2220cddRR7XKtXTtjRFO9Xuf9738/rVaLdDrNHXfc0Xkul8vRarUol8uUSiXuueee7R7vmmuuodFokM1m+cUvftF57phjjmH9+vWceOKJrFixYqdlP/HEE3nwwQd5yUteMu9td+aOO+7g/PPPp16vc9999/Gxj30MAMdx8H2/U6Nz0UUXce211/LJT36St771rTP2EYYhjz/+OMcdd9wul2drKtBRFEVZIH65jIxjkigmbDaxcnv2i3oxeMmzV/H//utR1o1UZyx//WlH4lh79ivtsssu49vf/jZHH300AwMDPPzww9x2222zrnvcccdx6qmncsQRR7B27VqiKMKy2rVNmqbx2te+luOPP57DDjusU3u0tWOOOYazzz6bI444gsMPP3xGzc/hhx/Ou9/9bo499lhOPPFE0uk0qVSK7373u7Pu69WvfjU/+clPeMlLXjLvbXfm85//PF/84hd5+OGHOf/88znyyCMBOOmkkzjjjDNYsWIFN954I47j8LrXva6z/nS3334755xzDqlU6hmVYUeElFLu9r3ux2q1GoVCgWq1Sj6fX+jiKIqyiLWGh4k9H4BUXy/GHviQ355qy6fS9EjbJr359By22HfU3IAf/Ocj/PfjgxRSNi8/YQ2nH7lyDlvuXLlc5g9/+ENnhNJULcVZZ50Fk81Mv//972k0GpxwwgkUCoUd7u/3v/89QRDQarV497vf3Rk5JaXkv/7rv9A0jRNOOIGf/vSnXHjhhQD8+Mc/5m/+5m86AdD999+P7/s897nP5ac//SmveMUrOvvfvHkzf/zjH2k2mxiGwQUXXDBrOXzf58QTT+TXv/51p8zb2/bf/u3fuPjiiwFwXZe77rqLl73sZTDZWfvBBx/sNDsJIfB9n9/97nc4jsMJJ5zQOabnefz2t7+lUqlw4YUXous6X/rSl9iwYQOf+tSnZpTvvPPO46Mf/SjHH3/8nO7TfL6r97tAp16v87Of/YxMJsN555036zqDg4P89re/xXEcXvSiF5Gbx68kFegoirK3yCQhbDTRTGOvBjlxkvD4UIWpT/9VvXlSe7g25ED0L//yL9x7773UajV+//vf861vfWu7gcje8Kc//Ymuri6WLVu22/YphGAuYcTo6ChXXnkl999/P/fff/+MMsRxzF133cWZZ5455+PO57t6v3llx3HMW9/6Vm655RZs26anp2fWQOd73/sef/d3f8cLXvACyuUymzZt4rbbbuM5z3nOgpRbURRle4SmYeX3fnOVQHS+oIQAbS8mkTuQvPCFL2TVqlVks1mOPfZYBgYGFrQ88x31NRc//OEP57ReJpPhyiuv5Itf/OI2gZau6/MKcuZrv6nRiaKIr33ta1x22WV86EMf4re//S3333//jHVGRkZYvXo1//iP/8g73vEOmExB/fDDD/OnP/1pTsdRNTqKohwIvCCi5gakbYOss+sjlRRlb5rPd/V+08XfMAyuuuqqHTZD3XLLLUgpedOb3tRZ9va3v52HHnpozoGOoijKgcCxDPoKaRXkKIvefhPozMVDDz3E6tWrZ2RanBr699BDD826je/71Gq1Gf8URVEURVkcFlWgU61WKRaLM5YVCgV0Xadarc66zSc/+UkKhULn3+7IKaAoiqIoyr5hUQU6qVRqm/TRrusSx/F2x+a///3vp1qtdv5t3LhxL5VWURRFUZQ9bVEFOmvWrGHjxo0zkio9+eSTnedmY9s2+Xx+xj9FURRFURaHRRXonHvuuZTL5Rmptr///e/T29vLiSeeuKBlUxRFURQmc8p873vf2+vHffjhh2dMI/Hoo49y++237/Vy7G37TR4dgH//93+nXC7z8MMPMz4+zg033ACTabkNw+CII47grW99K5dddhlXX301ExMTfO5zn+OGG27ANM2FLr6iKIqisHnzZq677jpe+9rX7tXj/u53v+Puu+/mJS95CQDNZrMzKelitl8FOr///e/ZtGkTS5cuZenSpdx9990wOYfH1KRhn/vc5zjttNP41a9+hW3b3HPPPTz/+c9f4JIriqIou0vs+Wz59T2UH34EI5NmySkvpHT4s3bLvkdGRrjzzjs59dRTufPOO1myZEln+gcm+33edttt1Ot1XvSiF3VmFN/ZdtPdcsstjI6O8pnPfIauri5e8YpX8PWvfx0hBN3d3Zx55pmd5IJT+z3llFP41a9+xQtf+MJON40777yTgw8+mO7uboaHh2dMW3HHHXdQqVQ49dRTOeSQQ2i1WvziF7/g8ccf5zOf+Qxr165l9erVnRnL//znPzM4OMiyZcu49957OfbYY2ck2t3R8fZ1+1Wg8/GPf3xO61100UVcdNFFe7w8iqIoyt6VhCF//NfPUV+/obNs7H/+wCGvuYSlp52yy/t/6qmneNe73sWaNWs44ogjuOOOO3jb297Gu971LprNJs997nMZGBhg2bJlXH311fz4xz/mRS960Q6329rw8DBBELB+/frOgJn169fD5A/69773vfznf/4nq1ev7uz3oIMO4jnPeQ7HHXccf/7znznttNM466yzqNVqbNiwgZNPPpkzzjiDzZs3c/bZZ3PMMceQyWT48Ic/zPXXX89pp53G2NgYjUaD9evX09XVxfj4OD//+c85++yzuffee7nuuusYGBjgsMMO4z3veQ833XQTZ5555g6Ptz/YrwIdRVEU5cA2+j9/mBHkTFn/7z9l4KTno+2Gbgqe53HbbbeRy+W4++67+dCHPsS73vUubrjhBg4++GB++tOfAvD1r3+df/iHf+BFL3rRDrf7j//4Dx577DEAXvWqV/HmN7+Ze++9l8985jOdY77nPe/hrrvuYnx8nJGREX70ox/x93//9zDZxPTzn/+8MxnnG9/4Rt71rndx7bXXwmT3jSmf/OQnOfzww3nuc58Lk5OHfvGLX+S8887jNa95DXfffXfnuDfeeOOM887n89x9990IITjyyCP593//d84880z+z//5P9s93v5gUXVGVhRFURa32ronZ10eNZu4IyO75Rhr1qzpZOEfGBigXC4D8MQTT8zoCvHCF76Qxx9/fKfbjY6Osn79etavX4/v+9sc73//93959rOfzU9/+lOeeOIJWq0WY2NjM/Y7fZb0devW8bznPa/z9/QyPfLII53aovXr15PJZLbbhLa1Y445BjE579n08u/oePsDVaOjKIqi7Decrq5Zlwtdx5oWDOwJy5Yt43/+5386fz/00EMsX758p9tdfvnlM/5+6KGHZqRBufXWW7nqqqs63TNe97rXzZgRXNf1GdsvXbqUv/zlL52JMB9++OHOc6tWrWLJkiV84hOf2KYchmHMOO5c7eh4+wMV6CiKouyD4iAgarXQHQfDcRa6OPuM/pNOZOPtdxC1WjOXP/95mNnsHj32G97wBj796U9z5ZVXsnz5cr785S9z/fXXz3s/K1as4KmnnuJjH/sYq1at4tnPfjZve9vbSKVSPPbYY/ziF7/giiuu2O72V111FX/zN3/D5s2bqdVq/Md//AfnnXceANdccw0nn3wyW7Zs4eijj0bTNI477jhOO+00Dj30UK655hquu+66zvRIc7Gj4+0PVKCjKIqyj5FJgjs8gkwSqNXJLBnYLX1PFgMrn+fZ73o76374Iyp/+St6KsWSk1/AQX/z8t2y//7+fl7zmtd0/u7q6uJ1r3sdAD09PTzwwAPceOONNBoNbr311k6Oth1tt7VCocBPfvITfv7zn7N582be//73A3D//fdzzjnncNlll+F53qz7BTj55JP5+c9/zk9/+lOe97znkUqlKJVKAKxdu5aHHnqIm266iQ0bNhDHcWdk2IknnshnPvMZfv/73zM6OsqRRx7Z2edRRx01Y9LstWvXEkXRTo+3PxByev2YMq+p3xVFUfYEGcc0Nm3u/J0e6Ee37QUt074oiWOEpnX6lRwofN/n+uuvR0rJ448/zve//33+53/+h9WrVy+K483FfL6rVY2OoijKPkboOnapRNhoYKRSuxTkeBMTxK6Lmc1hFRbXjzdtq74rB4okSVi/fj1CCFauXMn999+/R4OOvX283U3V6GxF1egoirJYxL5Pa2i483d2+TLEARocKIvLfL6r1fByRVGURUroeqdZR+g6HGBNPIqCarpSFEVZvDTDIDXQT+x5GKkUQlO/bZUDjwp0FEVRFjHdstAta6GLoSgLRoX3iqIoiqIsWirQURRFURRl0VKBjqIoyn4oiuefyl9RDkSqj46iKMp+RErJpok6TS8ibRus6M4dcAnzFGU+VI2OoijKfiSIEppeOzV/y48Ionihi6Qo+zQV6CiKouxHTF3DMtof3ZahYe5CAkAZxyRhuBtLpyj7HtV0pSiKsh/RNMGq3jxeGOOYOpr2zJqtYt9vTxwqJXaxuOimh1CUKapGR1EUZT+jaxoZ20TfhQSAkesyNQNQ2GzuxtIpyr5FBTqKoigHICOV6nRiNjLphS6OouwxqulKURTlAKTbNpllS5FJgmaaC10cRdljVKCjKIpygBK6rmYzVxY91XSlKIqiKMqipQIdRVEURVEWLRXoKIqiKIqyaKlAR1EURVGURUsFOoqiKIqiLFoq0FEURVEUZdFSgY6iKIqiKIuWCnQURVEURVm0VKCjKIqiKMqipTIjK8p+xBsbJ2y1MFIpUr09C10cRVGUfZ6q0VGU/UQShu1ZpqUkarWIg2Chi6QoirLPU4GOouwnhK6jGfq0x6pCVlEUZWfUJ6Wi7CeEppEaGCD2PHTbRmjqd4qiKMrOqEBHUfYjmq6jZTILXQxFUZT9hvpJqCiKoijKoqUCHUVRFEVRFi0V6CiKoiiKsmipQEdRFEVRlEVLBTqKoiiKoixaKtBRFEVRFGXRUsPLFUVR9lFRnDBWd9GEoCeXQtPEQhdJUfY7KtBRFEXZRw1VmjS8EABNawc7iqLMj2q6UhRFURRl0VI1OoqiKPuo/kIaTXPRNUFXxlno4ijKfkkFOoqiKPso09BZWsoudDEUZb+mmq4URVEURVm0VKCjKIqiKMqipQIdRVEURVEWLRXoKIqiKIqyaKlAR1EURVGURUsFOoqiKIqiLFoq0FEURVEUZdFSgY6iKIqiKIuWCnQURVEURVm0VKCjKMpeF0Qx5aZHEMULXRRFURY5NQWEoih7VZwkbBitEScSXRMc3F9A19RvLkVR9gz16aIoyl4VxZI4kQDEiSSK5UIXSVGURUwFOoqi7FW2qVPM2GiaoJixsU19oYukKMoippquFEXZ6waKGQaKmYUuhqIoBwBVo6MoiqIoyqKlAh1FURRFURYtFegoiqIoirJoqUBHURRFUZRFSwU6iqIoiqIsWirQURRFURRl0VKBjqIoiqIoi5YKdBRFURRFWbRUoKMoiqIoyqKlAh1FURRFURYtFegoyiKQJBIp1eSYiqIoW1tUc135vs8b3/jGbZa/+c1v5pRTTlmQMinKnlZzAwbLDYQQrOjOkbIW1dtaURRllyyqT8QwDPne977HRz7yEdasWdNZvmzZsgUtl6LsSZWmh5QgpaTa8lWgoyiKMs2i/EQ8++yzef7zn7/QxVCUvSJtm7T8qPNYURRFedqiDHQ+//nP841vfIM1a9Zw2WWXsXz58oUukqLsMT25FGnLQBMC29TZNFGn4YYUMzYDxcxCF09RFGVBLbrOyMuWLWP16tUce+yx/Pa3v+VZz3oWd99993bX932fWq0245+i7G/StoljGXhhTMMNAag0fcIonrFeEsfIJFmgUiqKoux9Qi6ioRpRFFGv1ymVSp1ll156KQ888ACPPvrorNt85CMf4aMf/eg2y6vVKvl8fo+WV1F2tyhOeHKkSpxILENjdV8BIQQAfrlMUKujGTqp/n40Y1FW6CqKcgCo1WoUCoU5fVcvqkBnNv/2b//GK1/5SiqVCoVCYZvnfd/H9/3O37VajRUrVqhAR9lvhVGMG8akLQNDf7rStrFxU6c2x+nuwsxmF7CUiqIoz9x8Ap1F/5Ou2Wzu8HnbtrFte6+VR1H2NNPQMQ19m+V6yiFqthCahq5e84qiHCAWVR+de+65hy1btnT+rlQq/Ou//iunnHLKrLU5inIgSfX0kB7oJ710CZqpRmcpinJgWHQ1OmeddRbd3d0Ui0Xuvfde1q5dy3e+852FLpai7BNUTY6iKAeaRddHJwgC7r//fkZHRzn44IM5+uij57X9fNr9FEVRFEXZ+w7oPjqWZXHSSSctdDEURVEURdkHLKo+OsqBR0pJ2GwStVoLXRRFURRlH7ToanSUA4tfrhDW6wDYXSWsXG6hi7TPS+IYAQh925FZiqIoi40KdJT9WhIG0x5HC1qW/UHYaOCNTyCEwOnrxXCchS6SoijKHqWarpT9ml0oohk6mmli5fbfBHhJIhmptthSbhBsNW3D7hRO5pWSUqrmvl0QxQmLbByHoixaqkZH2a/pjk1m2bKFLsYuKzc9JhoeTH6JruyZ34g/mSQIbee/W4xUmtjzQQiMVOoZl/dAtmm8TsMLSVk6K7rzaJpY6CIpirIDKtBRlH2AELM/3hkZx7SGR0jCEKtYwN5JYkw9m8G2LAxDV3NdPQNhFNPw2pOmukGMH8WkLHUdFWVfpt6hirIPKGUc4kQSxQk9ubnXtESuSxK2v3jDWn2HgY4bRGwcr5Mkkv5CmlJWvf3ny9A1HFPHC2NMXcMyVOu/ouzr1CedouwDhBD05tPz3k6zLIQQSCnRnW2zHjf9kC0TDXRNYJs6SdLuV1Jt+ZSyqiPyfAkhWNmTxwsjbFNHn0NzoaIoC0sFOoqyH9Mti/SSAZIoQp9lBNVEwyVOJHEiEUIgBEgJ2ZS1IOVdDDRNkLbVXGGKsr9QgY6i7Oc009zuJJ22YdCkPey+lLHJ2CaJlNimeusrinJgUJ92irIf88OI0ZqLrgn6C5ltRgD1FdI4loEuBBlnz9VCxEnCUKVFnCT05dvH3H6ZY8YbLqau0ZNLIebT+1pRFGWeVKCjKAsgSeRuGZY8VGnhBu0aG8vQ6Z6lI3N+LzRTlZs+dbedvHG42mJV7/aHxw9VGrhBO1eQoWuUMqqvkKIoe44KdBRlL4rihKfGagRRQk8+tcMRVlJK6l6Irgky2+kTMr0vrLaANSP6tKBN11UNjaIo+w4V6CjKXtTwAoIoAWCi4e0w0Bmutqg0fQCWljLk09uOqlpSzDLecDE0jWJm2+d3VRQnlJveTmteShkHJERJstMamoHJMpu6RnGWc1IURdmdVKCjKDsRRDFRnOyWkTYpy0ATkEhI2zt++/mTc3cFUcRIrUXaNjH0mcOZDV2jv5DZ5XJtz5Zyg5bfLocuxKzB1pS5Dle3TZ2lpf13ug5FUfYvKgmEouxA0w95cqTKU2N1Rqq7PjeUbRoc1FdgRXeOZTv5su/OpYiThLG6ixvEPDVW2+Xjz1ecyFkfK4qi7C9UjY6yR43WWpSbPhnbZGkps9+NsGn5IVNzNzb9cLfs0zJ0LEPf6XpZx2JlT76TlC6I2hNJ7s1rOFDMMFJtYerb7yekKIqyL1M1OsoeEycJ43WPJJHU3YDW5Oig/Uk+ZXU62u6OPjCjtRbrhiuM1d05rZ91TLKOiaYJ+gp7fyh2yjJY1pXFC2PWjVQZqjT36vEVRVF2larRUfYYTQgsQyOIEjQBpiaIk2S/SptvmwaHDBRJpNzlcjcmqowMjqGlM4xFCfmUtdOaHSEEy7tzu3TcXdUKok4H6krTp7+Q3u0Bl4xjwlYL3bLQbdVBWVGU3UcFOsoeMzUvUMMLMHWdTRMNgiihK+vQV5j/vE4LRQiBvotf7LHnE1XL4LpEno+9dMmMIdn7spSpo2mCJJFkHGOHQY6U7do7Xdfm1dQ1NQM7QpAe6Ee31BQViqLsHirQUfYoQ9coZhxqLb9TK1BuevtEoFN3A6IkoZCyd0vyvh2RtGuEBooZ3Cimtye3IDVbTT/ECyLyKQtzDv2EAExD5+C+An4Uk95BxmOAoUqTaqudOHBZV5bcHJMVJtFks6aUJGGkAh1FUXYbFegoe4VjGU/XCuwDnVprLZ8t5XZ/EzeIWFrKIpMEv1IFwC4WELsYiMgkwZ8oI6XELhWxi0UM36eQy2IswFxTfhixabyOlO0mqDUDxTlva+jaNkPbZz9G3HnshdGcAx27WCSoVtFtGyOlMiUrirL7qEBH2SusrWoFFnq+Iz96+gs5mPxy9itVwnq9vVBKnO6uXTpGUK0SNp/uvJvq7dml/T1TkesiE0moG50RZFGyZ0ZwdedSDFWa7Zq8eSQDtPI5rPzC9kVSFGVxUoGOstdMrxUYLDfwJgMMc7J5a28qZRxafkScJPR2mtGm5YmRuyNnjJj14Xwkiew0ez0TQb2OP1EGwMxlKaQt3CCiK+vskeAyl7LmXIujKIqyN6hARzkgGbq2zcSTdqEAk4GFVZq9WWes7tLyQ0oZZ6df6FahvX8pJXZh+5Ncbo8bRGwcryOlZElx9ikgdiYJn879I8OIJf27VkulKIqyv1GBjrIglpSyjNVdLEOjsI/MdyR0Haene7vPt/yQsVo7/40bNDjMKe2wVkRoGvZ2AqatDVeb1Js++ZRJX6ndhFNt+SST2YgrLf8ZBTpWLkfsekgpsQqFWdepuwF1LyDnqNoYRVEWHxXoKAvCNnWWde1b8x3VWj6JlBTS9qwBzPTZwYUQhFHMlnKTKElYUsyScZ5ZJ2s/jBifqBGPT+BKSfaQFaRLBTK22ZnU85l24NZMk8yypdt9vn0ODaRsBzxrrOKcOh0riqLsL1Sgo+yXkkSSSLnbvpTLDY/hybms/CiedaJMxzJYWsrQCiIKaZuqG3T6GY3VW2Sc2WtMpqu7AYmU5FNWJ5jSNQ3heSAlugax22ILOrVWgG3qDBQzpKYN6w6qNZI4wsrn0YxdfwtPdUeSst3MpiiKspioQEfZ74RRzIaxGlEsd1vywRmjsKY9ZjKoGqo2CcKY3nyagWKmU44p9hyGi5ebHo9umsANI5Z3ZzlsSbu/jKFrrFzaS2UwImWaCNuhNpmLxg9jpqf4CRsN/EqlXa4gJD3QP+dzDKOYTRMNoiii14B0ysLMZllSylD3AvLO3HPr7ElxkhDFCZah73dzoymKsu9RgY6y32n4IVH8dN+V3RHodGUdvCAikZKe3Mz91Vy/E3gMVZqd/DP5dDvRYJy0a2h2ptr0qbrtpqgtE03W9Bc7o6kyhSypzGpkkiAME3OkShgnGLqYUWslk2c+MqzS8vHDmLhSYST0WVLKgpQU8vl9pp9UFCdsGK0RxgnZlMnyLjXkXFGUXaMCHWW/k7bMTvLB3DPsFxM2GkSui5nJYKTTWIbOQX2zNz1NDzQMfWYNQ9aZe+fd7lwKy9BJEkl3zpnR5wfoNEOFzRb9+AS2Rb5UQNc0ojhhrO4ipaCQSSMSiVXceVPZdPZkbY2crC1hslYoCUM0c+GTODI50iyM2xm0G26412drVxRl8VGBjrLfsc128sEwTmb0XZmrOAjwxicAiFyP7HJnh1mQs47F0q4sfhhR2irfTxLHJEGAbts7zaScS1mceOgSWn44o49OEkUgJZppksQx3vg4SInp+2iFLOgaY3W30zFZZFL051OEzSYyjjFSqR0eN4oTGl5AyjJY0Z0jyFhYbh0ZJ4SNBmGziZXPYZdKc76Ge0rKMjB1jTBOyE27RoqiKM+UCnSU/dJcpySYzfQvz7l+jeZTFmzVPCXjmNbgEDKO0UyT9JKBGfuerTYiY5szRlBFros7OgZSYneVMNPtZjOZJO1tt/NF742NE7ntoe6pvl6MVIogihmtuRi6IGtblJselqHT8AKCKEEIOKi3QKaYhWKWoFbDL7f7+0St1nYDHb9cIfZ9rHwOI50mSSReGGGb+m6fr8vQNVZPBrG2ufD9hRRF2f+pQEc54GimidPT3Wm6mq0mJkkk5XqTuFIhaxnY3V3bTDSZRBEybndITsKwHZzoejsAmpyN2y4VsfKTiQOThNrIGJqUZHq60EyToNFiot4iTiQ9pomVy2HmsjQ3bkK3nXazkmHQk0shk4SwXCaduASBj2YYhFGCW6lTMEw2PzVIq94kth1GIyikbbKORdMLyToWQRjz2GCZjGOytJTBTKUIqjVkkmCkZ+/nFLkuQa0GgDcWkF7usGGsjh/GWEY76eJcg50kkZSbHkK0M1Nvr7ZG0wS2poIcRVF2DxXoKAccKSW1RCOx0pSs2TvhDlWblIfGSBoNopxDUROk+2eOcNIsC92xiT0fI5NGaBrlpkdUb2AHAW4Q8dQTm0gtXcqK7hyjQ6OMD44hBCyNIrpWLKMmBTW33XSlx4L8ZE2RazrUGx6Z9ZtZcdhqDF2n24Ra0CJsRmimgbAshls+WIKJLeNotToyShgbH6aRKRLFEkPT6M2n8KOk3dRnt+cZG6t7LOvKklm2tFMjFQcBSRBgpNOd4G9GEKhpxInsTNwZRAlBlJCy5hbojNRanea3OJH05hd+BntFURY/FegoB5xy02N0MsNxECWzJi4MowSSiKTRIDAkomfbDMdCtIMfmSQIrd2PZrTSJKlVSfstQqEjDYsgSqi0fFpBO0CQEtzJYMFIpTD6+0CCnp7s/2PaTNQ9kkqZsOWSdSzyy5ewYaRKY/0gKUunlE2R6esD2v2LZCIpZm3G6i7NIMIs6Fi6TnfWYWVvu9PyWN3tZHa2jKcDGaFpxEFAa2gYP4gYdQPM3j6WdeVI2TZOTw+x72NmM+iGTtYxaXghKUvHmUfzUjxtxNj0x4qiKHuSCnSUvSKaHEkzn341kesS1upotoVdnNtUCnMx/Us2kcms6/TmHPwtIWbaImPoWLntD3OeqvWI4oS4PIH0AyJDkCrmic12R2HbNOjq7WIwiNBkQmlJu3aokLIYqWpIJL35yXVzWcxcFr9WRTNMoihkaLyOlwj0fA7P9Wi0PEbWbcZFo7B0CaVihi47T2PLGMtzJWpBTE8+xYqep+fY6smlMCev/9Rw+DCKCaIEMwpBSmquT+RHiFgy0WjX+piZNGbm6dqX5d05ojhB18S8Ogv35lPESbuvUHd2707iqijKgUsFOsoe1/RCNk3UkRKWlDJzztnijY61M/V6Hrpt73R00Vx1ZR3COCFOElKmyabxOhnHnDGiKmXq9OVTkE+1+6DM4Qu9K+tQFyANje58ikxXnoJpo+tapwNy/tAVaEIgRLsD8GgzaA8zF4JKy6e/YIBM6BIhQzJGb9YZTaWQdsyoH5HNFPD9hGYSkQPSevtYPbn2tcn3duPXWqTTgqVdWcYbHk0vpJSxyadtCmmblh/y+FClfQ3iBNPQyVg63Y6N5QZ4Vjuo2VFtzTPpCG4ZOit75j+5qaIoyq5QgY6yx9W9oJPbrub6c09OJ0QnKZ4Qs3+xRnGCG0SkLGPOX766prG0lCWKE54YriAlNLyQtGV0MhzX/YgnWpLaRIVlAz0cup08M+WmR90NyKUsShmHgw5eTlApoxkmIpUiDmJs8+kgaaqM7sgokevi111ktoAwrc41ihoNJjYPkUQJTdshSWXJAX05hyhJke0uMr5pkJoXEOsx9niFroyDpgnqbsD6kRppU6PbFIy1fIRpMVxtknXMTg6iOJG4fkgriOjNp2mFMSuW9pPu76fhtZMjzidHkKIoyr5KBTrKHpd1TKotHynn9+WZ6u8jrDfQ7Xan363FydNZdM3JYcmaNvemFCHaw8tl5++nt625AeORIMkVGY4EA164TfbjMIoZrrTnx2r5ERnbxJps5pFS8sRwhSiWaAJW9xVmTK8Q++1OuaWMTTUJSWoN0kmKJGORhBEilUYkLnYmjUx8oo3D5AoZ4lyRULPoWbmM1vAIwg/wRscZNQUpDf78l0EqwmKsVkWMjZC1LZz+Xqqt9uzkXhhjme1gy7GMzvXqmtaU9EwCHCkldS/ENrQ5TYehKIqyt6hPJGWPyzoWB/cVSCTzyo2iWxZ6d9d2n4/ipJNFN5x8PJ9hybqmsaw7R63lk3GsTrZgJpP76ZrA8yOklIzXW+Qcc2YOnskmqDCKafkRbhB19hEnEjeIGa+7CKC/mKEwbf9WIY9frmDaNr1CEOsSkpigVsfIpOkb6GG87mLmc1ibn0KGEVag4dhdeGkHxzQYqU4wNjFBI4xIvBa1WKM8WqFmpChqMbbhYJs6GU1yUG+BSsuj3PRZ3ZtnSSmNoelkHJM4SeadDyeo1ZBxjJnPo+k6m8sNGm6IELCyJ/+MEjnuD1p+yETTwzGNTnOhoij7tsX5aaTsc/bEZJG2aZBNmTTckFzKekYJ5qYn8AujGDeMSVsGhbTN8w9dwh83jGEYAi+IqbnBjGY3Q9dYVsrw50fXY+g6g2UTx9SxzXYzmkASRjEp26DlhxTSNkEUY2gaVj6PmctRbXmMbxkhI9s1QpppYKRSlA5aSUlKGps2U48i/GoFv1LBKhQolIrtHDpCY2h4HNM0GCvXsUtFChmHINZxcmkqrk8qbePrFivyDvUtg/RpOlEUk8h2FuKN4zW8yY7LW2d9ZrKmRsYxQtdJwpAkCEiimKBahckpJFL9fXhBNLk+eJNNiYvRlnKDKJY03BDH1FXznqLsBxbnp5FywFjeldst8yFFccL60RpxIomShIFimmLawbZ0Htk0TpxITjaWdgIdL4gYrrZIqhVSUYCIBHGtTtidZyrxcW8hjZQgkRi6xuaJBnU3wDI0VvbkqVQb/PG/HySMYvI9XRzxrIM6yQWnRnJppolZyBO1XMxikaoX8ZdHNmBkMgyv24wmNOpCxzUtzFjDSTkc3N/NQDHLU2M1jLxD5Hk0xjwKpkbLD0kaTey+IvWWN1kLIxittihlHJp+yGC5gSYES0tZkokxYj8ATWsPo59sdtPt9nWQk6PWunMpRqotLEMnN4cJThVFUfYWFego+71nEuRIKYkmRxwxNTQ8kfhRxGC5CRJqTZ/E8zEEpByTLZUGuZSF6btMNDx8K0Xc8tDdJgDZrvyM6R1sQ6c1WdNRaXpsKTfIOjZgMl53WffwY0wMjWIaGqapE8cxrUoVz7DI2Ca2aRA6KUb1NKK7n2IhzfqhGq1UhvrYIEYMUtNoNT1WHX04hkzozaXQMhmkEHTbGvXBQYTQyGUMal6MTCQH9+RpVqoMPzVELYwoLVuClWrX5kw03MmZ4SUT1QY5P8ANQiqVOinHppjPoNk2ZiaDjGOsUnvYfynjzFojtNgs78pNNl2p2hxF2V+oQEfZ4+IkYaTa6mTDnWpiklKyeaJByw8pZZ29lim33PR4cP0IcSJZ3pWlv5ghbbWbwZrlgKxtogtwh4YoAKWgSZLpwg0TRjYNI90Wpi6IDY9obAyzUcUu5CmmHYIoYbTewtQ1oiiZbK6K2FJughSsG65QSFs8NSaJmz5RqwmahtFdwKhX2VBuUk40xoXJciPBjgISzUBbspR6FBJkJWOtGNePWJ2yGPQt/HSKdVvGOGlpnqWWBD1BFPN4esxQvQZI/rilgp4vgKbRJXUaW0aQgKNBVsQs6c61p5sIAtwgxjYMHMdCBAajozUSw8KLBdrQCOlcBq2rtMPcQouVYxkstbZNMKkoyr5LBTrKHjfR8Ki22kOWE9ns5FJp+RHVls9orcVTY3Wed8gA+TkOPQ8bDWI/wMxlt5mDajZRnFBzfUxdZ3CigRfGxEnCQ5vGiBI5OSN6kWWlLJvLDZrjFVLNGpmUzRH9BbT+HipeSFJuD0cvZmw8LyB0TOq+QxhKqk9uxntsI3oqRWFJP5oQ1D0fS9fI2ibNlkc4OkK+N88TrkS4ERORIOfo1DFo+hF+GDNerTMeCYKgQdpO0VtMkw5DzFyG8kiDmuvRigUb6z710QrFgV6iOGZLpUEchPSWIvr7ewhtB+k2iUZHSUKBns/j6iYbRqtoYUJBSCzToLeriIhCmkPDNMsNokTD6Okmn3bQ0v3okY6m68iWi51t5wUaGxola9jbjERTFEXZ16hAR9nj9GlDvqcP/zaNdp8RL4wx9fYUClsHOlMjq6Z3bo09H298ov2865JdvmzW407Pxryl3KDlRzQmKvi+TyR1wkRg6TqaJohiiRtEjDdcNE0w4GgEaZvED8gV8uS786SaPhMCLLdJPp+maFtUh0ZpND1aUcLgU8NEuoFj1QlMCyebIetYpCdz/KyfmKDbMajWXbo0gSsjRL6IZxiMxxpDzZCsLhFDg8TjVYY0k9KSXroKKbq0mMqWQQzXwwtiGuUqPVEDM/LQ6xW0UjeWZRI3mwwmkmj9JgrZNA4JzUaNVbZNfXgLstBNV8ZA9veQFpL+UhYnmyao1YmTBD9MSOlg6Dp+FJOxTVYOdFFt+dhpE7NRY7TapIVObaKBnEcCSEVRlIWgAh1ljytlHKRsD7menq/FMnQO7i8iRJWUZWBtNWrKD2M2jNVIEkkhbbGk1G4ykNOnbZDTpnNIJGGcYBkaDS9g80QDIQRLSlnCKMGv1ZhYv4GsDClYKcwVKwmERqXps6a/yNhYmdrwWHsG8oxNsasLmSSk+noRQlDKOpSyDtDTOWZR02i1PGpPbsIcHcQ2TfR8FtvvomXaVFs+htae5duyDHRTw5YxWdugbObQAp+ynSGwHIYTjbSu0x/UiYMGDc0iSR+E1dVF4gekTI18HNCdTRFUBLGAg3sL9PXkcVYsZaTus7nhobdquBPjFEsFiiJGmDoxCbnIxUmb0GohLQvPthms+wjTJJ1JY9brpB0D30rjmDqpyXw4adskPdn3KM6miOMxJloxWq1FMWOrQEdRlH2aCnSUPU4IQfdkzpEkDEmS9mzZTCaqawUhUZywpJCZsd143WWk2u7ou6Xcbm5a1pXFSqWwCnkSP8DMt/uJRHHCU2M1gighTUxcniD0I/SuLqotgziRjA2NQrWCqSfgezhuF8UlSzB1jb5CmicHByFJSJKIJNSoChMzl8O2bPwwQgt8muUaE0GM4dgMdBfQDINi1mHYbeKQ4DfqFAZ6aNRaPDweousaKwopBuOQsdEyTrVCyrIZHiuTH+jnqMMPYkOgMbxhM65boxI1MaKQrCYx8mnCfI6xVsDo+DjFtM3SngKNUEdf0UtvVKDfiIjrdYaeeIohK4sIE8TgIIGpU661OHxpF05vL+NBDIaNoWuktISoWScOfOJCgXLTI0nZrI9MvFSB7myKFd05NE0QNhqEzSZGKoVMpWn4MYFhESZNNASJmpxTUZR9nAp0lL0mbDQ6TU5OdxdmNstozaXptUcmTTS9TodkKSWVpocbxAxXm6zoyuKHMeWmR38hM2OSz6jVojI2gduK0HN5ahMVuiydhhsiWy1EPksiJf393TQaVZzIo9RVIpgccZVPt/uZ9JVy6ElMXK0StSS1po7vw6PjLaIwwqqMEcUSf3yCYm83sieP0dfHRLmBrxlkLB18ydh4hZFGQpDrRtY9Wq0qrVoF4blE1SqbNINMPseEniY0HSrr15FseIqWlJTTJulCgSDRCbr76O4uMNEM8DCYGCpzUD90AySSLZpNc8sIwdAgiRBUcyX0lasJQ+jyWnR5LWoDPfT09iITA8u2SBoN0rpA2DpjDRdhmli5FFvKDbaUGwCkTINmEJG19M79Clouw7qH1A0qLZ8lxSyaJjCN+c95pSiKsjepQEfZayLXm/HYzGaJkqeboab61DDZImXoGsu6stiGRiHTbh6xjadHbI3WXIIoJl2dwBAS3W2SWDbZXIaciHBMA7urhJZO0fBC9FyO7kPX0Gck7Rm5S10I08TQNZIowrAt+vp7CFIWYw0P6YVUxyYoN1yamkFQrpCNfUS1ymilQTCRJV9vYS1bRtyKqTdc6gRomwdpyRH03gYYFs1cCqPeRJ8YQUQhViKpS0Fg5XCGxjDqNVK1cWIpaBndbA40xmQWf6TBsbkt1BoeslyBOGBiYoiqF9MwbWrZAtHQELrrYYceRd/HzjnInA2BjkGEl8BEJIi9FlGrQT4O0bHQfSikU4wnknorIE4ktqETRDGaJrANHSEEMkmQcUyi6dS9EF+25wTLp9vD37uzKdwgIoyTbTJHK4qi7AtUoKPsNWYmTeS6nccAPblUJ8CZSqkfRDHVlk8hYxNGCQOFNLquoWuik7uk0vQZqjQRQKvusqSYZmkxi9FbIJVJkfgBMonRbBtN11nRncMLIwpLuzF0jTgICFsupiaQmklz85b2TOkIJnSb8VadLZUGVq1KUGkgpGwHTfWI0DDJxh6jTZPqeJUBKYjjmO6VS2k8MIGMIgpJSOS3sIs5Kn6ETKAQx2gyxtEMKppBX84hpSUYuqBsOWiaRtNJM25nqbt1ROBSWbeekiXA8/CjhLBVJ0InFDaNRoih2+TjGoaMSIuQglvDymSYKBSJNUkrAZkIsikbJwrImGDms0ghGJUmiWkRJZJcyiRl5Wh6IQPFDLapE3keMoqJPBdR6iIMwQ1CTF1jeXd75Fy16bO5XEcT2ox+VIqiKPsKFegcwGotn7G6i20aLC1l9vivcSOdJrusXTMj9HbNjGXoneHmUzaO1QnjhImGS1fGIW0b23R4Hau32FJudzZeVSxg5mx02+4EUC0voDI0TMY0yPX3kMlmyTjtfkGD4zWGnlhPGMVkHJveYpqxJ57CsE2crhI1K8O4naVqSvricXJpkyBMsLwGhcYYdTdgs3AYk2lW6i5duTRL9IggkpT6ehhb38IKXKiOE3Z1U5MmUWKQsR1Cvz2JqBtJxls+QX8vhy7XCXWD4YbPuOawMYCU77NSetgeNCo+se+hp9JI2yFONJIYAsOgYZlk7BSa7mDHHnoUITMZWs2YmjAoFnIEdhrb0sjJgIbrUkxnqZspmpUm7uZhEkfHWtLH+qpPnCQgBI5lYLgemmViWSZ+lFDKpinhoImnJ/F8dMs41ZZPbyGDFahmLEVR9j0q0DmADVVbJIkkiALqjjnnHDa7YirA2VrTC9lSbqAJcMOIOJbU3ICUZTBSdcmn2h1pmZx+wQ0iCmmbOEko5HM402oSgihm45ZRoqbL+pZPjxuyZPUKihmHhhdQqbtUGh5hq4WuJTy4ISIxTESlQd7OUI9tRmotLMskLHXhNBv09KdpPvYEhudieBFaOoVvpRjWHVbWG5S60mxoJQzbWVrCxJESvV7H2rSerkTHDyP02CUtYjzNwJERj7oax2gm+kGHEZebmMNjWH4F28whNI1KAjmp4VUbhJogSQLy/T1oUuI3AhwSEqEhcjksr46HhZMrMDJeZ6jSwm5UkSNZikccwrJjj+KpsQaak+ORoSrrxofJEbM6Bd12nmC8TCwc4laTZqtKS4/p6ikR1utIKcl3FZDouEFEV9ZBCEG15ZGxLRpeiOuHrOkr7PHXj6IoynypQOcAZukaXhLDZK6ZhTRWb2dOjgHHNJGGJJ+ycCwDAYxWWxiGhmXoDJabuEFMlCT0FzIkEjaO1+jKpJBINoxW2dzw0ab2aVqM1FyKGQdD08AwaMWSaGwcf0kvSRQw7HlUY52Sp2FFHr25FH4Y86yD17JlvM6mkQnStkPGNxGRxMwX8IXOSCAYdzTSozWeWL+JoWZE5PosjRLMJCKpVsjE8eQ/H8O2kU4GWwdbE/hxzON/3UBXbYJ0HFBvuXTFTRInTUmLaflQ0W1CwyRBw0pn8YaGybhNzGaVdCFHVkYkSALLoZjJMNyq48QBmWYFS4+JNm3m8VIP9SDGGxpm40Sd0LDZKAz6NZOefIpqkFCKBfXhzeRKeezAQ0pJZvkypJRouk7vVvcs61g0vYhlXTmWdmUXNHng1lN6KIqiTFGBzgFseXeOmutjG0YnTwqTTVrjDY+UZdBfSO+wScsP2wHH9Dme5kMmCX6lilZvIA0boRv05VPk0zbLu3NUWj4bx2o8OVol65gUUjZ6HJE3BXomzUAh0xktVG6U0TXBxsFxPC/EzpfIOia6k8KMQ6Cdy8erVckZGkZPkbRjQTrDSMXHqDUJK2WSQgk9iMinLCqtgCeGK8hqjXogcTJ5upflcZatwnehNV4hqJQZ3/gEuXKNSDOoRZIGGgKBliSYcUQqDtGlxDI0ijKi2moxED7JUG2EIJvBigVmo8bSVp2iblH2QvR0hsCwKBqSCSONphsYw4Oka1VsIUkQ5KoT7USBUUgqCqnHIQXdwkDi2CaFjINmGYxsGkKMj9KsN0GYBEaELPXg9PYQO2mMnE3/2ChLB0roSGLfByEQmsb27n4p45C2DIQQWAsYYCSJ5KmxGl4Yk3VMlncfeFNTKIqyfSrQOYAZukZXNjVjmZSSwUoTKdtBTNYxtzt5YdMP2TRe70yJMFDMzLrejgT1OmG9TkGTODIk3V3q9KVJWQZBFLdnAJeS9SM1ekRIt56Qskx6Vy3F0AVBFNPwAgxNI0OEMTFGRsKy3iz9/V3UtgyhCxgXMaPYBF5AECcUu7txbJ3VB6/C+st6hgxJnEgKWYNBLyLQdYZaZXS3RTAxge15+LkUXv9S+vMphoiptlrE46MEtRrCb1KKYhxNx9UdglQKX9MoRhESMIUkkQmtKCJdH0YXGrHuMGqmiE3BQCQxUlksAUWZEEQBIMkWi3QX8/hjY9BqEEQhNXSEkDQRVIOYktsEXSMe3EImlUasXk3XQDd1qTESmiRjE6Rdj3yrRlcmwwbNpqcnRTYJ2bhlDAoFvKrLwcUCRhQSagaD654il02T7SoR+T5GysFIzXy92ObCf4R4YYQXtmsmG147J9NC11Aqu2Z6VnNF2VUL/yml7FOEEBiaRjj1QaNt/4PGDaJOYuKWH+7ycbMpi5Qzs2YobRmUsjYj9RZ1z6ekhfiWxtolXVi6QArBxrEam8sNerIORzgJ3TLEMgTdMsSWCbWWj+cF8MQGjGyOTG8vMm1jpmx6Vi4lMS0syyTvGAxVXYbLDYppi8z4BCLwKQnBsCGRGYfhiTpb/vQYvcv6SA8soy/roK2rELsuWhhgkoDU0ETEIDpmHKOTYOsCkQgioeEFEpMEEUX0RiF2FCJ9jbKhUZIRsRA0DZt6KMlHHlocEI+NE1fKpJoNNCHw0nmGYgNiyCYxdiww/QZJIvGCiPrGEVKrBqhli2wJdVJuk57IxzI1UmmbQy3oCuskZYjzBUY3DlI1UtBKOPKgpWx5cjMygXrDY2mrie44hI0GmaVL0Ix962PDNnVMXZucKkSfMeWIsv+ZymoOsKSY2St9B5XFbd/6xFL2CSt6clRbPinLwLG2/xLJpywqTY8olpNTI8yflctBkiDjBKu4bWdW09BZ01/ENnQsXUd6LrHbQDN0zGyGMddn00SdJJFMNH18x2RpTx6BJJ3NUI0FG8ZqmBPj+I0GXX0JYeBTOvxwwgSeGm/S8MvUyw2eXDeIbeoUa1VkNo3TnMDu7qK3mOXQpV38+i+b2TTh0mqEVEYbPNsYwmpUSOIIV+hYwiCQEkMIbCFJJzFSRmS8FromcU2H2I/QY4kUGi2hI2VCOonIxiFRrCOlxHNSpAOftEwQSUJrVBKk0tDyyfguuqYjdI+q3UUmCvBjSdlIY8mQAElTd4j8kKcSg+HBCrHbxDESUjmLrnSaifEyiRAEScCSlcsI0xaPjLVo2Aa+hN4AMG3wfWIkTHYgb7g+9XKD7mJ2n6jJmaJrGgf15QmipJP/R9l1UkqGqy38MKYnn3rGzdPzVXeDzg+omhuoQEfZZfvOp5Wyz7AMvZOheGfrrezO8dRYndFqC12IeX8oCU3DLpVmLAuimDiMcBwLIQS6pjFQzNL0Q5qew6qeFWQK7eHwtfEmui6YqHtkHIuWmadl6u3OxJksE42AUAo8NLIkpHSBEUf4TzzGyOAYUaHIRMsnCSO0sREiXaPhOCw3JWkkEyPjlH3JUSc/i3gipj7qIf0AfJ9ofJS+JKYW+PgIxo0UtoCCCaYQFCMXPQowNIGUEt33GXLyBJaNQUKUtrG8FlbokU5CojjEQlL3JLaQRLpJlEQYHkQJZAMXG4kuQ1KtCk4cM6xZIDRMEeObDpr0iIUAxyJsNkl7EaGmoWkaIYLhRogQoDs2fgzDlSbDlYBqoJNujZFydMIxk0Ipj5/k6CpmSWuSerlGGQstSHDHG6wZKG73ni4EXdNIWaqZY3equQGVpg/AYLnBIQOlnW6zO2Qdi9pksJNbwA7uyuKhAh1ll9S8kGhyvqPZZh+fr4YX8NS6jcRNl65ilqVrVraDIVPn8GXdSDlzBnQh4MQ1S9iwaZQUMcWMQ+IUaKUstpQbRLGkN2vjWj2IjI3MZklbOlF5HG9wEG/TFgLdxtElqTiARGDlMgRCMKpn2FypUQ1a/OW2/+TwgsOIIQn8gFVBgD3cInZ9wigiTMC105QzWdJxE91rYYikPdGoEBgIEqGhy4RM7KEhCGVEK9aIhU5GamjECBmTC12kZQMSIwqwtBgzCtCkJEkSDNqJDa04pDtKqOSKRElETIxd6iaDIDEN/ATKsaRoxDhRRL2pEWg6KXS0GESisXG8iczmCYdHCLsKBONV/LxNydIppR1Es47I57B6e9EmmxPirSZSjRM12mkxmt4EqO+gCXt3y6UsDjYLyMkfU4qyq1Sgo+yS1LQmjNQOmrnmquH6xE2XpNmg2qjSVcqS6mnPFi6EYKpVwg9jxhsupq6hG4IjcjpeKKltGaKwcjlj1RZao06r6TOwfIDWRBXZ24UoFMm7FTYNDRFHMfg+iSGRmkAX0IolY0aWpp5Gr5UZq3toQ6MEImHCjFlV7KIZtogigee5NGsNPDQahkFk2rSsLEEUYzTr4Pkkmk4SxehExLqFDCOqmkGahHziY8WQCI1xqTFAgCBp/zeIcIXEkAKkRJMREeCjEZAgNY0gjrGI6WuMERo2wrapeQGxbtAMXMJAknUMPLvAeikxo4iMZbJ6xXJyzSpRvc7YWI2g1EtkOhRTDjJwKXsRjFYwNdAch66mS++ag+jKOnhhRPdkB/YoTtgwWsMPYySSgWKmk2NH2f9lHYuBYho/iillnlnT9DOlAmdld1KBjrJLMo7Jqt48UZyQdebWhj9aa1F3A3Ipa5smskImxUizTjQ4SKaYJ6w3cLq6QAjCOMHUNYQQDE7OZg5gS4kXRQxVmsRSUh2t0RyfoN8WlJKQgivYgE6MhV53adkZzOWrMFohrZExUqkMeuAxHut4IsZrNinlbNK2ho4kF7j0Rw2sJEL6LomdY6LhE8Ue9UQnkjBm2JhCZ0VrjEgmRInElhIzDjCJEYAVB6QRhBIKMsCSMRoQS4GDIEEDJCaSiJiMTNBI0GWCh4EFtIRJWaQIpGBZ7GFpEiNMcMOAIHSZMDKMptIUQ490EtGIHTw7hyMgRUzJ88gHDkaryfh4mUyjTqAZiDXPomY5pJasQMvZuKZGkkQYkWSiFdCntWd4n67ph4RxwnjDpRWEnV/9Gduk6vpk7O2P2FP2D8W9HOAoyp6gAh1ll82nJieIYsbr7ck9x+se+ZSNbT79680Wkr7eEtXAw55snw8aDTZuGSMwHTL5DCt78shp+xz3Y4SVYtyvY2azPLFhGG1inPWuyxFdDoYGed1mFJ3qyCjpgsOE6WAfthY/0siELqGZxffBao2RqtcwY5egWODwjMDzTcyWiUQniSVxvU46SfASSRMdVwiauk13HNHtTZDEEiOJSDTQJ5v1psorkeiTw+UlMVkEERIdSYRGBEQYRBikCDFIEIAAIjRSMkbDoyosfKGTjj0sQCfBiyU54TOYtPs+CUPD0XVEHCO8FsWoQU/aJFMr06rXMcfH0IQgjCX4PhOpDANpm1whQ9EUNIVBHIS4ttUJTJkMVKstH9tsj3BKEknaage5cZLw1Hi7c3i54bO6rzDj/iqKouxtKtBRdis/jNCE2G7VsyYE2uSXo6aJbYYCxwjGg4Q4k8dPEnq6SjRHx3HrLRAtWpZFECUsLWUZq7tYhoZpaLimQWYAhEyI/vIknueRrlcYSxxK3SWMQppquUrUahGkdbJSQhiwrDFGECU0iz1kwxAjCTBiD31skICEShxjlbpAh1iCkDFOK0CLIrTAp0RCVU+RSgxyiY8Wx2hRjC8EnmZjE6ITYRATopMiwZQ+GUJAIgATOfkoQaARIYhJSDpL2+uYROgkaBISCRliHGJiIEQHCek4oiBCcsRYrRaJHWC5ddKAlfh4icNYHBN6PolpoiWSkl+j1mrSyBbAbTHx6GZi28A3bTZmuvGjFg8P1nneIf30FzKM1VyEEERxxPKuLH2FNDXXRxMaxbRDebIDK5OBD6hAR1GUhaMCHWW3Ga+7jNZchIC0bZIkkkLamlH9begaq3pyNLyQjG1ukxAsAbTuXkTOR1gWwrQwNA3L0AhiiWPqWEa7+WppIYVMEkoZh5rrs7w7S6vlM75uA39cXycOEkb0FKuTBKuQR9YnQEKlGXDimi6GHnoELwwIx8uEkSTV249u6AhDJ2y5eBMV0oaOls8ynsozIQ3MRo0+S6JFPgIJEuwkoi9skEoiRBS1z0JqhEIgDZN6ZLEED4sQDZhKuScBHUkCRO26HmI0LCRuu/4IHdCAhHYzlzX5z8RHn7xeEkiQxJrAN0ycIKCma3TpGqnAw4kiSCQTwsBPQqRIk9PT9KUkdhTRUyriWwbVRo3uYg9RLaISxwT4jDcFZhyRpB0e2mjgBTE1N6A7l0LTJif/1LUZk64uKWYoN33S9syM24qiKAtBBTrKblN3A5jsKDzR8ChlHNwgIutYMwIa2zS2m4fFNg16ihnqbnuSUSedQu/tZkU6jXRSpHLtYeWNepPqpi1YSUS6WKBr2VIAso5NV18PK92IVlmQymUI7BRRKIkMC4pdZHI2fatXEDy1Hs+2adk2djaD19NLl63hjU/gVmrEThYv9HH9gLFQQ3OrRHFITdfw0iUMWnR5NQQJZhABoBORINCR9EZNQJKZDEgMtHaNzOS5ysl/4eTzIZAhxJgMZqaukADsyYBnqv5Ln/ynTe6jjmzPap4kpCMXP7ZIRIwetTs41xKdzekcI1YOR5gM2O0Ejd15m1rDJ60lFAs5sn3dRF6doOlCOsXKjU/S8gJE3wCFvINwTQrpDP2FNOlZAlWAfNpWuU8URdlnqEBH2W0KaRuv2sLQtU5yMU3AfAfh9ObTMzopm9ksZrY9O7lMEjY//hRP/PERzMAjnXJYsrQHI5vBLhQwdI3jjliFX28wGAVIdP7SglLTJ4oTVvV3cdiyEj4axmHPohhDudBNnC6wtJDh4JUlNqwfhCWSuFEnGB3FkxLHb2J6TSIpiERCZFhkYp9A6mgyxpExKRIMIECSJkafDExMoIXeHj4+uSwB4snz0wAdgZjcXpvcZiqEENPWZXLbpFPT0w50bCQyCbCDEB+NipEQmSZ1K0UmdMnIkFLYIrTTBHaGVFeOdEYnQ0joj+A363QZJtG4Te6wtSRxQvPRRygYCXbJRqeJtCEeG6PYm1DM9KjRVYqi7BdUoLPIyCQhCUM000TsxdwXAKWsQy5lIQR4QUzDD8g51pxzcIRRTKXlYxv6dmsEWuUKWzZsxvMDgloNXSYIxyEJQ5JEsqXcwK3UOWp5Ea1WZrw6QdltkUodjKFppPUEuXEjj49NQDqDuXI1Rx1mMvbQn7EmBomCNHEUorkBRugjLIOJkQqG55IJXJCQaALTc+lOfISAaNq0l/5kbc702pb2swne5BvOmlymTwYw7ecl5oz120EM0x7LyW2iyX8x4EwexwFCYnREu89P4pMEEbouSCQI3aAoJEvDCbxskUzKIFMqolWGyToO3vA4+SRA4DM2Okqxvw8rDhCmiQwDTMcm4zVAN7BDl6BSwS6ViIMAb3QUEDi9PejWjkdZbf369MOIKJF7LeuuoigHHhXoLCJSStyREWI/QDMM0ksG9nqwM9WUkXG0zuScc7V54ukh45omZh2aXHVDmokETYfuXkrLe0l3d2Pl89Rcn4YXkmg6XsNDhBF5TULso5cn6DloOf6mzQy7DVqjYzSEju44OLrG0MZBzEYNS0hkOkNDtwmbDezAo79aIQJCKYiBJNHJJyEGEk0m2IAPaCSdpqipQEZMBigOkmjyDadPq9WR0/7p05qwtGldeKfWi6fV7Ew1j8WdPjqiE1hFgJOEuEjSSUIoIbYs8rGHFhj41QkKKZ1iLWTiqc1I38XWNJI4oVppIDKSsVSGXCRJsjn8RoP+Iw6n/uQGTNPAKeZJwnZTnV+p0Gz5GLqGVqt1ch7NRiYJraHhTqATF0psqbQA6M45c8rGrSiKMl8q0FlEZJIQ++1+MkkUkYQhur3/9JWIk6cHjU/NXjydH8ZUpE6QKVBNdI4+dAWHHrys87wp2xOLak4Kr9SDKNaIx2J6Mw7dPTnWNzy8oTL50c2kamWsKCTJZGlKAa4HvoenGUQxjNsavZ6LnYQkQiKkQGqCQOqYmsQXJk6UdLId64CPjk5MalpQEk9rvjK2Gn8kpgU3U/8X05qkpvfHSbZ6s5pINKCOPvm8JEaSoNPSHTRi8nGEJhN8w6ElDdJCokuJ06pTHtPRJtpD1zXTpil0JryECccgE2n0hAGJYSAH+rHdJmO1FoGVwjRNUq6Hls0yWq4zMlIjcT00ASsL+R3eXxnHJGH7HiVhSMt9enTWrk4KqyiKsj0q0FlENF3HSKWIXBfdstDM/as5YKCYYazewjJ0CmmbiYbLWM3FNg2Wd2epuj6byw1c06YwkCE2baI4eboWyTZZ0Z3DDUPiJCF3zJE88eiTdGUsrHwOx5VEuRytLSFOECCTGEu0+xElaOhxTCI0gjghiiN0TSCiBEvTaaAhdR0SgSchr0VIXWAkcrLnTYJJgjMtcAmAEA17MhfOVM3M1nVs2rSgR05rltK2ek7M6JPT/r8xGexkJ/clhUZds8nIkIgYhE4iE3zTQtMluhDoYYwdhySuh9CgJSyGDZ3R/oMoo6NpGrlsF2ZGJ4gilh68klok0K0yUmhY/SW2TDRoDA0zVG5QKmZJF0vEzo5rZIRhoDs2seej2zbFfJr6eINEyr2eeVdRlAPHogt0yuUyH/jAB7jzzjtxHIdLLrmEa665Bl0/MHJ5pPp6SeK4nTBuP+ssmnFMMk57BvMkDBktN0g0jS3lBnXXBwTFtEO15bEknaXhhlSaHj2TTR5eEOGGEVnbws8k1Fyf0spl5EWMaNVZImP+rBt0ITA0gRYnmLogVepC9Ns0Nm0kwsCQYNkOvilImxrjGLgJNAyHovQw4wQzgQZme0g5MRoaCXGnM7E2mSXHnBwiLjtJ/55+nmmJBJNp//dhsltyu3loqnPylOm1Pg4xATrmZBdlRwrSkQ+6oGU5yDgh1nUQklwcEuo6MQK/6VKNAixTxysWGTSKjDV86sJkRW+eIT/msIOXkHNsuntyVIbLjGgOJccgN9DHyJODINv3LJYSJ5fZaRZkIQSpvj5kHCP09izjhwwUt5m/TFEUZXdaVIGOlJLzzz+fIAj49re/Tblc5g1veAMTExN8+tOfXuji7TXafh7UBfU6/kQZUWlSMxxqIVi6oOFF9BczPGtpN3Ei0QQ8NlSh5gbYhs5ftkzgRwmWofG8NQN0WYKDujIMPv4UmVyK8pYyduBDHKI5Nk4+B4cdTlQoQblC2nUJgog6JjKdhjBkqKaz3pak/SZFYhLNANOg3AJLT0iFASEa1mRQIqYFNOFkzYuY9kbzpwU1+rRAJ+6MrhJoSBroTGBgIUnhk9tqfTGtGcwiIqY9cWiARo4IVxp4aISaQUpK+vw6JpKUZhDZNkngEjsZGqaDZ9h4tk0gTEQssU2dvpyD64VIKRms6AxVXDxhIFMp6kFMOp9hYnScYsbhoNXLSZcKc7q3QgiEYcz8W8U4iqLsQYsq0Lnrrrv47W9/y8MPP8zhhx8OwD/+4z/ylre8hQ9+8IMUi8WFLqIyjUySWTtLR612B9X+fAotFKSyaSxDxzYN8mmLQspmpNaarOkJcIMAQ9MZqraQUtKdSzG8cQu9lmCw2iRKNMbrTR5aP0yr3qBXt3FME72nSEWYbBkso8cRppUhNiRapQJ+wBbdZlDLkxdlMkmAY1uIOKYeS2p6uj39gtTJ480YDu4BGgJnsh/N9NobfTIA0rdqrpr6rjcmR2x14yMm96VP+xdP25fo1PYkTGCRJiGm3WFaynZWZUsXZIIAEOhJCDLGDMHTbXzDIEh0woHlmIkF9Ra2QXsSUSF4arxONmXx5EiNUtpG12DTRAOZgNAEhZUr0JA4O+mboyiKspDmFehs2bKFD33oQzz22GM873nP433vex8900ZZfOMb32B0dJT3ve99e6KsO/XrX/+a5cuXd4IcgHPOOYcgCLjvvvs455xzFqRcytOSRFJt+UTlCZwkQrdtUn29MwIeM5Mh9nw0XWdlfw8TfoQ3Mkre1MgIE9vJskTLMNFwEVjoGkQxdGcdKk2PQtpGBHU2N0I2TTRwukrIKMEKfcz6BFarTssweMrVqIU6/XpM3GhRqTVJkASuhxskYIQYEnKxR5eIyfpN6lJn2MlT12GpF4GmYSQzAxZ9ck4rbVq/GjHtOX1aYMO056bIaX1zjK2e1ydrhfRpQZIGpCcnjLBJ8DDxNAN0A1PXIHBpCh05OTFoShNYaRvfdkgXu1hVtFlqp9kcNhCGRq4rw7LuPBs2DtGcGKdIiJPPsUlPkXIcDKPdnBjHkiCO6S5m6MmpEVOKouyb5hzoRFHE6aefjmEYnHjiiXz/+9/nBz/4AbfffjtHHnkkTPaPGRsb25Pl3aFNmzYxMDAwY1l/fz8AmzdvnnUb3/fx/adHf9RqtT1cygPbcLVJpe4SDU/QnXPIAUkQojtPjw4zs1l0x2k3a+g6oj5OHAQEoSQaHye7Yhl6qYuujMN4w6M75+BMZlq2DI2Rqst4s05jeIJ0yqYcgxlEdKdM/CTETGL8WCOoVBn1NDJxgy5LIJKIwcjATCTZ2GdYGNhCYMYJDglOFOICRhIRGGkqTp5VQQUSjWSyQcqblsVYmzYsXG4V9LBVcMO0ZdMnLN1ecoAGkJmWTDBNhETDRcMmppwYdAculgA9iUk0jTHdwTF1srpGPpvGNlPESYQcH0OTkG66pPJ5jujNYoiQqFUm2PgUffksWuxyyLIVTNgGYdzuEt3wA9KWyaOby5z8LBXoKIqyb5pzoHPHHXegaRp/+MMfsCyLZrPJFVdcwemnn86dd97J0UcfvWdLOgdJkmAYM09J19ujSOI4nnWbT37yk3z0ox/dSyVUgigBTUOYBlGcIHQdbdp0EIPlBnUvpJC26C9kqLsBE15E5Mc0q+MsKeWJ/YDRwTF80yHrWKQsk4FiBoDGRIWkVsOWMTXTJO3YFLsyxBmLjeUyOCksGVKPwIoC+mzoCgXSsmlpNnEMQSaNEccUPJeW0HHdmMAL8HSJLWEgqNIj/XaCQy2FRYhJgoHAmpyIc3ptztQw86nmrWjyXI2tmq2mBznRVh2QpzMmEwTG04adJ5NNWOFk09iyxEWbnC9LoBGIhFhoVMwMLdtEd3L0xT5jo+MMT1SIvRaplA31Cqlnr0Fr+QwYCYmeQKNCpEm0Rp1UroRMJGnbYqLhY5k6ui4YqbZIpKQnl9pmWojY95FxjJFWwZCiKHvfnLPJPfnkk5x++ulYk5lPM5kMN910ExdeeCFnnHEGf/zjH/dkOeekt7d3mxqliYkJkiSht7d31m3e//73U61WO/82bty4l0p7YOorpHEsg+ySAfpWLSOzZAAx2XnaCyKqrYAkkZQbPoEfIAQIw8To7cXs6sUutftZGdbTYYCuCcIoZmJ0gqBcxvBbVDYPIjSNbMpmaSFN5KSIlq4gPnQtzSUrSa9YRb6Q5VlmSK+RoLdqyHqdIV8SSMGylGBZMU02bUPvAJ7jEMUSGQYUfBcjDEiiGIsYVzMAgzJ2J4iRWyUEbKLRmAxCtp7jKukMRX+6KUqf9pzc6hpOPd8OpsTkOhpVLFqYJELDIcIhpt1glSAQNA2bP2d6qPcuQTg2fhyRhDFWbQKr1SCp1fEbTX774DpGfcnYllEq1SbVao3YD3hqokHV9ZloePQX0qzozjFQTLOkmGGw3GCi4TFUbc4oa9Rq0Roaxh0dw5uYmPU1ESfJ5CzniqIou9+ca3RWrlzJbbfdNmOZEIIvf/nLaJrGi1/8Ys4999wZfXb2tuc973n8y7/8C0NDQ50mrHvuuQchBCeccMKs29i2jb2XkuoliTzgh9GmLIPVfbOP0DF0DU0TJImEygReUMdIOfTl8/hRTLG/iBEFCF0nbdtYDQ+Agm2wfqRC2GhCo0kp7dAqFTFSDvVY0qq4TGwawo5j5EA/UX8/xUaZcGNMwQDhJgwGUI4jMjKgq9EgrAc4Too+XSdl2Ximia5BEGtoMiYTuIhEkI9cbJGArrVrWWKdmLiT4+bpqSCSTg2MyczpIZJpgY8zS5+dZLKGZ/q0EXFnKojJKR9ICNGooJNNYiRaJ1AaFyZNzWIklafq5JC2wUDWRDYNGiQIKUlME4Ek8APGJ2q0JPRJHcNOYycRg6HOSD0gGKrSX0iTqZlEiaQnn2as2mKk5mLpOtmtsmFPJbAESKY9ntLwAjZPNABY1pXd6RB1RVGU+Zpzjc7pp5/OQw89tE2NiRCCL33pS7zqVa/i29/+9p4o45ydd955rFixgve+9734vs/Y2Bj/8A//wPnnn8+KFSsWrFxSSjaO1/jrYJlNE/UFK8e+ztA1DurN05e16E8ZCE0Q+z4FW2dJKUvKsTCzWYxUCl3T6M2nKYiYxqYteINDYJpIO43uODQKXZRTeYJckeHhcTYMjfHwU8M0xidYOVCiEkE10RlqRlSkzqplfXRlbEqE2KFPOgpIBy26ZEgx8kmZJjXdQQKBYTKEgyYTtMlOxyEGUSpNpBszamCmmrHsrfruiK3efMa0oGe6eFq/nnirGiCAHAmpyfmzbEJySIQuqGAyrjtsMHOMp0uUnSyBZrDSHYd6gyibo2GnsfoH0A9ajdHbi1vsptk9QGLZNIKIUSePmytSNdOMOHmqmsFIrUnK1Mk6FgOFDJVGe/qHfMrCEAmpWpnGxk1ErguAmc2gGe2cOWZ+29FZ1VaAlCBl+7GiKMruNucanUwmw7/8y7/w2GOPbVNrI4Tgi1/8IqtWrWL16tV7opxz4jgOt956K69//espFovEcczZZ5/NN7/5zQUrE5NTFzS9dqNGww0JohjL2L9z3ewplqFTymdoNevtOZEMHc3Y/ss0ajQxDY2speP6Pl1L+4iBouYRRDGFtEV5VFB1A2QCQ3WPrpqLUyq2mzWDAKu/HzObZpUwqDRa6OPjRJFOqGsUTQ0rCYksnVp3N3pVJ3Q90iLC0yw8GWEQ0xIaIozRhY6YTB84nbZVU5Sc1idnatlUXUYyLbiZCob8ycdeZ5QVM/oCGUCemDQtmolFRbMoC5uWbuEKk4qRwY5DtETQ8gOerHroS1aQF5I+A9wwwsqVGNs0hh74pOwMXipNzTcw0zm8IMG1M/Tl0/TkU5iG1q6BE2AaGpZhYLoJtpYgk4SgWsNIpdBMk8yyZdvctylZx6TuBp3HiqIou9u8hpe/4hWv2OHz733ve3e1PLvs6KOP5g9/+APlchnTNMlms3PYas8yDQ1T1wjjdjI7Yy9PtLm3JJMdvnc1YaEQgvRAP37LBdPa4cSk0rIol2ukLJPlK/uZCBIGy0100Z4SImNqHHnIcsYbHk8MTpCx02gCcqU8kQ6ykMOWMX/xoeFClBgEegojXeIY3cWulwmkQOQKlPUCeAmmH+ElMGylCKRJIfZxdRNPaqwOfaLJXDZTb67pQ8vltOkdmNYsZU1bL5rWeXmqz44zrePxVI3R9NnPpycSNGVMSoa0NIOEhGYCiQApNQKhEWg2f41snm2ahKPD+AM9mLk8geZQ6C79/+3de5BkZ3nf8e977uf0vXt6rrs7q5UQQhIC42ADhhgIOObmwmXHcQIEXEoZgssJmNiAY8e4koI4VhwSVAUkpIzLTqRUXGWUihxCmSS2iXEQFwmCLCF03+vc+3bu57z5o2dHs9qLdle7OzM9z6dKVbOnz868O62e/s37Pu/z0ox6HA9jKmU+Pp6hUyPIcupBlYOzLZoVn+umG2RFScW1sU2DvCjRkUOyWYdjPMcp5qc1Andzx5zGtSeqrZcQYpe4pJ8sX//61/F9f2s7+XaPPfYYx44d4zWvec2VHN9la7VaOz2ELaZhsNitE2c5nm1NZJ1ONgqJV1cB8Kc6l7zDRmtNbxhhWSZV3yXMCo72E7RO6NZ9OjWfOM1ZHcY4lrF10vVKaRH6dUaGQTbKGCU5jmWSpDkdMyU71Wd1ENFt1Uksl3rg4jsOR7o1puY7FFnGqd6IQVQQ+xVGx0/SKFJUlnHSNTmgLIhGqFIz2/Z4wqswGI7ILEWbDMtziTKFzjJyZfCEVWMmG1HXCQmaCEV729EQ1rNmdk5Hwu3LXfm2GaDtwebZS2J6264uc9uylwJyw6JNxrCAoCxIEpPEsnAdB88oqUUD3GPLVJMQV+UkC4c4uhHixSOGoz4OBv5UB4UmsC1aVZ/GoXlaVZ+ZRuWsk+lty4RaFcO20EWJFfhnPcejJKMXJlRcm0bwTF2ca8vsphDi6rmkPjrvfOc7+eIXv3jOx1utFm94wxv49re/vStmUXYbyzSompNbaJmHo3GhBZCF4QWDTjYcUmYZdq22tSx17OkTrJ9aA0Nx8PpFUmWc/nQM45ROzef4+nC8PR3GXZJ9h6IsUZuzB3maMogyskIzXfdRYY+jqwMGcQaBYrFbJ3As5toVOlUPe65LvLxCqTX5sYQyCpktE0pn/MZrBR7RIKRMcuLSQJ84Tlk4LBkei8WQQGmCsqDUmoE20EDP9qjojCDP0bokwyVnhLst4LAtqGTbZnHYtqyVYmBSbhUtc46Zm9Of7/TskAEMscgxxktaZUmgckIFC/kIqwSLkNJpUe0N0LaiqASUeYYRjYjWhqxnJS3T5IXTNay5Lp25abqeSb+AmWaN6ca5n9ciTUlWx7M53lTnrHPWylJzbHVAqaEfjo/s8ByZwRFCXH0XvYbyla98hYWFBQ4fPnzOx1utFq985Su59957r+T4xB5h+Zu/wSuF5Z8/5ORhSLy6RtofEG8rbI96m0XapSYcjqj5Dqcnvur++XfFzTQreLaJFw7wBhvkS6coywKNJjFtPMskznJKy6EeuNhqvLPo0fvu5+STx9h44ikGx09wy+AoNxox17UDDpUJBzs1Dr/sVkaVBiPXw4oikrKkUqS0dUpkOSSGgVFkGI41rhNSJYEusZRi3amMi5eVpsTa2iW1fceU3rab6nQAOj3rY20e63nas+t50s3/ctTW9RSDITYxJimKZVxOORVCw6JSppRaY6Oxo5C4gPVCoeKIeBgyOnEKPeiTFyVrhkexcJjK1BSObXF8VKBRPHpqg+VeeMb3f5RkrAwihqvrFGk6buzYe+6mm8/eMi+EEFfLRf9K9cgjj3DjjTde8J4XvOAFfO9737sS4xJ7jF2tYrouKHXB4mG9rV+K3tbEsdNtceLYEqZp0m7X8RyL6zdPtj7dgG6+GXDq6EmssiRoeYBDxbUJpmosbaxwcrVHuTGgWaugVJXu7DRPDTM8r86Upcke+z6uabKmFHowwNYlg2OnSIIquoRKntFwTOpzbZjuMNJgGAZJo42Nxssh1gVTWlOWGs/U5KZNUWgKwyC2HLw8o1AGQZFQak2MuRloDHI0q1h0NuOKQ4lzjmMhys2ane2NBbOt+h5FiSbCJNssRT79d3vKITAK0kLRKDNME3o4rNoeni4otUFu2ChlgBvgVVxiC8xRn/X+CJXAmtfCtH1WhzGNRoW1QUxalBxdH1D3XU71QjzHouY7JFnB0dUBWoMaxcw5m4d0nqPWxjAU8+0qG2FCxbHxZTZHCHGNXPRPm6IoSNMLb/9M0/Sa9aQRu49hP/euGatSwU5SyizDaT7TT6c9O02z00IZxlYDQfNZRchmltK2AAzi1TWqm8tjyjBYTUrKwXinVhGGTFmg1leZ1SmJa1McO06yusqKYVG4Lu3AI01ziqlpbA39pMCteLCxjGF5lP0NsmMncNMUNxnhznTxS8X62pA0zXHTFEsVeFmGWWbEygPDoG861PIUJ08x0djKJFQWGZDrcTDqFzkeOQblVgGy2lakfLruxtrWb2e8LKXIsdGbB04kpoOLHp94rjQbpkdSFLTMBKMcd2gOtcGKX6csNd0yRtkeLTJabonrKLTrstYbsFHAqN7EqVa5tW7gDjfIlwuaBxawHZssL7BMxaneiHrgUPMd8rLcWl4sgypuzcYwDaxK5ZzPfdVzpE+OEOKau+igc+utt/Lxj3+cLMuwz/GGprXmv//3/86v/dqvXekxigmilMLrtM/52HMFJbVtpujZs0b2VIc8jGgA850axWhIlOVMBTbHHn0CO03xDI1lm9jz0/itNmlWsD57ENNQ1I8+xbRVkquMOE0Jl1dZXu0RF+DaBrOBx1JUUDfAVhrTNaiNhgR5SqYMSsdgaDrU4j7NbIRHho0iQZOZFqEd0McgwyRLE8wi2ow5BTYKczPmWJRbRcqng8/p/jkZJsoAqxx3Qw6KAsMazwPlhkkFDYaiKBW2LqnofDz7ZSrcMqVtm3iuYjbPmbdK4mhAXA042pxirdphql7lprrHQh7SrLgc7taJApvSsqjO1HhiPcK2TMIkA8a72poVlzDJaFW9cVB8HpJsHKaeHXCFEOL5uOig86pXvYpqtcq73vUu7rzzzjN66fT7fT784Q+ztLTEW97ylqs1VrHPWZ6H352iyDLsZxW8H5qqs2YewIojMtNkuR/DcEieJBAm+BVvvDNpYRGvO8XBboONUYJa75NurGO1qqgoZGj5rCqf4akeeZzhKIUKahiWSWCVaM8lTQuqhgLHZaRMijLHLgpC3+VAlFMoAwNFgcbUmkhZrBguZZIxqwcYZYk2FMlmNc5x5eLrnE4ZY1KSbxYis62mBxQeBXmpcdCbB4UqKBSGoUhzGAUeI2Wi4hLb0iTKwlKaRpFh+gFeYDNvZHRSC5WnuJU6wfQUh9sGB9sdFqeb3HZoiv7JJYw0wXZsnFrAsceeosgKOqaF257GsZ4JIqfPGLsccZpzfH24VbicZAW2Od6h+OzzsoQQ4nJddNAxDIO77rqLN77xjRw5coQf/MEfZGFhgZMnT/LNb36Toii499578bzn91udEM82SjLCJKPuO7hBcM7/aV3bYrbbYrRh8q0nTjHCwjddlGPQmJ1lMBxh1yvoWoPAtam4NsMwplhdxS4K6pSUnRZHRzkbcc6qFZDbGZYuqTWnua3dRG8MsDNFNkpZHw2J0wJfl4SWx3K1TcO18EYmmDYDrQlLRZWcsFB0osF4pkZrcq3QhklSQoUCnxy3LIkxsdDkKKzNloF621EPBdZm4fF4b9b42AeLTJvEhkVhWYRWwLLtkOcjnCKn41hMGynKHH/N2HQ4boKLwjFdWobF4sEu11+/QNX3eGqlz7GRJjBcXjg1xdLSOlk6jlo+Ja2qS/N5ztyctjKMtnbRrfRDpuoBWVESpjl1X5a4hBBXxiVVBL7kJS/hO9/5DnfeeSf/+3//b77xjW/QbDa5/fbb+cVf/EUOHTp09UYq9qU0f6bgdWOUcP1M87x9iNJej/WTy/hxSFQaZPUGs1MtjDgid1zcZgPPNEhOnuL+p46xVppU04yK77Ba2Bx7epmlsGA4GrFWWkSNaXzHYnZ2CrfmYfZHeErTjzIcrQgNl3oZkymTbjKgzCw8neEYJWtOwAntoCiYySOMotwsPi4wlMGKcnHIKVBMlQkFihzFSI2X73raoUbOuOWfIlUWkWGyhENDZ3TLCBuNozOGusQzTcwso3RNnuguYKqYIzqiEfdRhWY5LxjEBXFZ4AQupuszc8NNVCs2RhTx+He/T+vAPPcfXcWxLHrAbJTgBh4j20JnOY2pJt1GhSJNyaMU0/PO2kZ+KVzLZMh4GaxVHYcny1QEUqgshLiCLvknymg04kd+5Ed4xzvewU033XR1RiXEpqLUWwWvRakptcbg3G+uZZ7j2xa+bTHvunQPTtGp+URhhE6qnAxz8sEAoyxYXR+Q2zZrUcTK0ip9yyOMNZZpUKvVSIM64UbEyPc4FZc8tjLAKTV+4BP6VZzBKrUipW5oIqVxsggKjVYQKZvMMMgx0BkYShEYJX6Zk6AYKouGoSm0wi0yTCBUBoaGQhmYmw3/lrWNS4FSmkxZrBkesWljZyGUCRYlOQrHNNBqPHsU5RHV3klotvDzCFspMlWSapOhbTOKMnJ8UrdJ07Cw84y1KGFlEOIMU9bigkaRUAt8srkWYVGSN1ocaFWYalbJ45hoaZlBmNDTJsFUhwOd6mXV1UzVfBzLRAH1wL3mNTpZXrA+SrAtg9YVmqW61tL+gHRjA8Ox8aenL9hFXIj96pKCzq/92q/x8Y9/HL35znP77bfzuc997mqNTQh8x6JT8xjGGc3AvWDthttooLOcA56D3WwRVAOyNGPlqWPosmS66mNPN1h96Ht4K0sMvSoqqGAqhdNbI3MCmu0G2nUxc42Kn8KIN2hYPoOT65ClZG7AbW2XjdzGVzk+UOYxiTZwsgxNycByWcPhmFmjq0N6uUO1TEkME7ssaJETGRaGNiixGJaQGCYxJjWdUSpFieK4WyfEZCYfYqDHp6cDpoKBYWPqnNJQhG7AEBtPFxwINyDsUSQDSkszME38dotEeShMlG8SV5vM1CsUZclIK8q8YJQUDOOMTjjAdSyOTFWIBwNKv4Ln2OjNN9C19T699SHro5jA94nSnEGUXtZyllJqRzskH18fEaXjTfymUtSDvbdjNO310FpTJCl5GJ5VuyaEuISg8+CDD/Lbv/3bfPrTn+Y1r3kN3/jGN3jf+97HO9/5Tl772tde3VGKfa1bD+ieffD1WQzbJpibPePacm/Eaj+k1w9ZKlJuOLKAmefMTjWIk4zqXJNHHtrAsS2swKUz1cCpN0j/6lGsMsYsI8ykoFAW2jZx0cxXXaaokx8bMSo0pVZorYmVhVIFG5bLqhVQKpOktDjlVKiVKa4uwTApMLCLkkwrRjhklsEps8LAdLg+3cDTGS4FMzoi11BTOUZRMNSaug2R6RAaFkOKzSUtB6VgPhng6xyPkiLKoFojNhzWlIfXbLJQDyi0Yl3bpMM+ppmRzM1w8HAbaxTTO36KumMyFxi0XZNRxWew2fbItUyyvGA1g6KAMMlx2z7WZn3UXlRs6+lU6L3ZwtB0HPI4HvevusjzxYTYby76J9R9993H29/+dt773vcCcPPNN/O1r32Nr33taxJ0xDVVZhl5FGF6HuZz/HA3HZuhsiniiMyxGYQxti6pVivUWzajSpWpA3P0Ty2hh+tYfZ8VbeFZitI2aQV1pmsemWGxNIhRmx2QTyUpiePQTzSpkRNrcFWBQqMBu0hp64LCgL7h8c3aAgfDDZpFiI9mBYvIsKjqjMwwiQyL3DB40qxwfd7HpaBOgaXHvY9NVTDAxFKKSFl4ecIpu4JnKbwip6dNtC7JC01kWZSOR2l7hEGdeHaBjmPSrtgcWOjSG8U8fjTDd0ymTDg032EuL9lQKQaatmPgT03RaDXpDULK/gC1PCQyLRQW1swM09NdZhoVAvfs5n/ZKETnOXa1stUTaTeaa1VZ7oc4lknjAt23dzOvO0UeRRi2/ZyvBSH2q4sOOisrKxw8ePCMa4uLi5w6depqjEuIc9JlSXjyFLosUYZBZX7ugm+m3VrAysIMa0pT1TlexafSvg60xqw3SLBw7ABvZZm+YaJWV3Fcn/Z1h+jlKdOBzXU338BaUhA+/BiDUUQWBCjT53g/IUhOjY9ksBysPMXQJYFtojT0MGjkKaOyJNOQmwaJtkCXxMrEQBOaNqHlgGWzrjxmihwDRVYaqCInUFCgybEwvIAmBVP5iGoRURRDVp0q2jA5Zno8bdYwTI3yHFrTbRLbZ8P2sJbX6VQsqtMHue7IAbLhiPmKwyDOmD7QpVnxCJOMtXqTdDAgr9dx2y201lj9DeLlFaI0xetO0XEMTuQFNc+hWXHPqqfJw3DraI88jghmZq76/xOXy3csDk1dxFThLqYMA/s8DRqFEGMXHXS01gyHQ44ePbp1rdfrMRgMzrhWq9VoNBrn+SxCPD+6KLaOkdBlSVkUmBcIOoYxPswzTlKK0Qi73qA2O0VRah48ukovHOFaJpV6BaUUhYZDs21M28Kb6WAoRS8pCHPILQfHyqgON/A9l0cNi9DyKE2o6hIHgxIb03WxS42PRV7mxNpkPh9QKzO01mgUsWmTo/BMg3lTs+yauFUftRqyqn0qeUKFghOmQyuLiC2HwrLIDItWHuPqEqssqGQDBk7AilXlaaPOilPFqlZZaFQxTItZldGNeyyqnE7UI93oYddrBLZB1a/gei55GDLMAMfF6rhEm4eaUpbookBZJjrR6KIgLPT4dPi8YG0Yb50if1qZP3Osh972sRBC7JRLWlz/7Gc/y2c/+9lzXj/tQx/6EHfccceVGZ0Qz2LYNk6jTj4aYQXBRU3XD+OMiu+B7xE5Fkop4jTjxMYIrTWjJKN+4BDu2hqG5xO0moxWVlAotIZ4GIJfIXAswo2YXn/Ao8fXqYR9UBqtS5ShsGsVgjSmYRacMG3iHNYcn14GthWQFQlVCkLTxlGKmm2jfQ/HKDngeRgk9DsNotWMUCm8MqGhM4zNvjpFodH1BmbcwzQUNgrbtTAciwUjo284NI2YyK4w3awxiFOajmLRr3DQV9hlQRaFDMIESo01Csn6faxajVFp8tQww7Usbppvwea5Wqnjo2qaoNHA67QZJhqi8x8FY1crFElMHicYrkOZZRd1NIgQQlwtFx10fuZnfoaXvvSlz3nf4uLi8x2TEBfkNpu4zeZF31/1bHphgtbj85byohyfeG4ZRFlBzXdYmO+yXK2S5AV138ZqNxluDMnzjLU0Y5jHNBpNamgeWRux3h+Qa5PcrTJTccByaOchQWFwbJiRZymVLCN0qox8n1GqqWcabWoWAmd8jIppYTQbGBur2K6JoSEwTHojm9Vcs2RUOJQPMXVKNS/ITZPUnqaY6lIkEWYaYdcbFHFK07F5UZqwZvqsJSOSUUi9WuGG67ocMRKqWYTTaNArFCuDkNWlNew45MBMC9tMONFPWEpNAtdiGNeY1pqnVvqkpYnh1jky3cAyDWa8EtNQKAWdqn/W91oZBl6nw+j4CfJRSBHFz7m8KIQQV9NFB51Dhw5JQ0Cx64RJRj9KCRxra3twHkWkvT6G4+C2mlQ9h0OdGk+uDHj4+BqmMmhXPV56eIZBlJLrkqXeiEdObgDQGyW84sZ59A2LPPrQoxw7uoTlOMSdaaYqVdKgQr+Sk2Q5jgL/0BxeEqGO9Rgqm7JIcHQJZU4tj1lzKqxVOzSSDSzbxCfkcLfK8jBh1fWpzcxhFDnhYESxtkahoWaWm2dgGRjaoG96KMNEFxnN7hTVepVH1iJWM42nN3CDALPYoFNxaTsma0VCrgM24pzmiw9TKwt0WbCRwEq/4PujAgcHFWvaVk4Pm6zIiDNFL0woSk2SFURpjm0ZHF0boFC0q95zHvugN5e8ANJ+H2WaeFMdKZYVQuyIvbkvVIjNurGja0PKUrMxSnAsE8+xiFdW0WVJkSSYrguuy2NLG6wOEkZJim2a1HwHjWaq7vP9kxs8cnKN75/cYHGqjlLwyIk1vvvEKaITK6yNEupeTqOWYhspB9tVGA042S9xGw3IcuqjDdI8JdOKtfYsdjSCosB3XQKvBmlOmiiGccJSxcfVDmUe4YYDnq60qSXr9MKUoNTYWUJFF+S2R99t0ElMbMthZLkE9So0G2xUGjxaJKxsRMwyYlYZNGbn8BsVMkyGqUEOrI1iVvoJnYXxQardJOMvHz3Jsbik4jos1Jp0u3XUcp86ilbVZ7ZVwTIN4ixnuR9iKNC6gmNZnFgfUvPPfSjraYZlYdeqxMsrlHlOmWXEK6tU5ueu0f8ZQgjxDAk6Ys/Smq3mlQDl5sfKMLYKlpWhWB5EZIUmyjLSvKTqOZw+ReI7Ty/zxFIfxzIIXIskL2hXPB5f6rEeZawOUwIFludycLaJubFBvciYshSZCaXSDPsDapgkmJi6pNZuUm0fpL/aZy1MibWDpiT3A0JlsFYLMNdXMMOIZJhitjRFEuEVGSiTzPUxPY0XJ3h5jq5UCDyfotHGanc4qSDTBo1ajXQUs2Z4mIbDcq5orw2p2yZTrQ7H0oT0RI/jKmKxejNeo4FvW1Rcm9lGQJjkZGWJRnGoWyfJCg5O1elsHscQuDaL3QZxlpMVGsfinF2LkyxnI0zwHXvrjCqv3cZ0XeKV1Wvxv4IQQpyXBB2xZxmGYr5VZSOMCRybwB0XvfrTXdLBENOxsXwfIx3h2RZzzQoV12amWcG1TL791DKrg5hCa+Ks4IdvmKcRuByaqvGVh47h2SYpBp5j4U11yAqN1W5T9Pt4jZx6b0h/0Medn8PKIuxhD7/iU+qMyK3R6Zgs9Y5SMxXLrk9SlDi6xIsSikGIm47ITZuyqFI6No5hkFkWdq3OaDCgdGPKOMIpNXVT49iKR1d7PJ2Cqiuum25ww6EZksAgjFJOjDKCekBQcZnyHfqDDRpZSLlesvrUcWZv9FC2w1TdJ8kLTKU42KlhKAUo2lWbqdozdTftqsfqIKYZuGitWR5EzDQqlHlONhiiTBOnXuPp1QF5oVknwe7Wt/rq2JXxvWWa4TT29jZuIcTeJUFH7Gk136H2rJOuDdvGa7e2/tytBZtv5uMC2tOHgp6eDGoGLotTdRa7dTxToQyD2xa7PNDvUVZM0Jre8hqWbePYFvXuLNVS02nVcSoeZVBhLUwxyxTKguky5uRgjacee5pRP6ZvuxS1FouL87iDdWp5gjM0SHOT3LA4btWZLUJaZkm1GrDaaHE8LkkImHUiWmVEpBVJFBNlFkdzj2p/yBEfrj88y9fjFqtliDJLShIwFMpz8D2HOOwTpQXro5huUeK4ilsPdal6Dq5tcl23wUaYkBclndqZxcXdesBUzUdr+N6Jdeq+S5TmrB9fwtHjoxNQUJbbZtXKMzsMu9JqQgixwyToiIlnGOqsfi8AN861cCwDyzS4ca5F1usxWFsjXlnDm+ly81wDL0/pRykj0x6HKs9htlnFn20SLi1R9R2qszNoZbBaDll5+gS9KGHj6DHi4Qgvy6mkI2LHpGE0MQKfVm7QrliEOEReBV1zyQqHUdijZprEJ05SBG0S38DuHqQM17GPP42DQlsmPgadMsXMUjaWV6lgYbZqtCouU4FNwzY5HuXU5zxCx6HeqRD6VY4PU2Ytm5rn8OJD3a3vw/bvTZTmrA1jPNukU/M3TyfX2KZBVpQoNT5ri9N5ptTMtaqsDWMC16LiyVZyIcTuIkFH7Fv1wOW2xemtP0ejEaPjJ8j6A/I4onZ4kesWZ1nqh2ReBde1qbg20w0f2zJptWqc3BhxYnlAUOZMXXcddqVKdGKVoPcU9TymyGJs06CjQppOQbAwy8ajj1K0u8x1UgapptAFx5VFw3EYpjkFkCQxpRdwfdNjNqgTBkeI04wXmh4Vq0o3D2l7JhoILIvZdoMXz9TI19fJi5QN0yAxbA7fcIhKLWB1EEF/RFaUvGCudd7vybG18TLUIBofsln1HJRSHJoa9+XxHRuHKsn6Oso0sWtVHMM4a1ZNCCF2Cwk6QmyyfB/KcnxAom2jlGJh8QALm4/nRYmh1NbSV1ZqlnojVr77V6g4pljooOcPsnFyQEDOwPOoFpu7wShwhz2yskCVBXYa008TEr+Cp0pUCbFfwTWh2wkIC4uaY2EnEXOtCqtFRtbtcOvhg2xkmu88eZKV9R6e79Jpt5hrVrDThIrv8NRKH69UzHgWU0qRhTlPx1CUmqLUFww652NbJrZporXGdJ1dfbSDEEJsJ0FHiE3eVIfWbS8mXloan4S+ML/12OndXTpLifoDTMfBqtUYjkLS4YiyKFla3sCqtHHn50iePIqFjWkqLEfhtTvUptrkaxuQJyRZjlGtMUw1G0mCqQps26U6O8vcoXmavZBoFOGRMjIdFo8cwKpVOXn0GE+sDOiZFcxKncK16FQ9PNsmzDPiKGG+VaWmbMrRiKzIWeslZHiUKA51XE5ujFBqs3bp9PazTQvtGmvDGN8Zz+acdqo3Yn2YADDfqmz1LBJCiN1Ogo4Q2/jtFn77zBmPvCjHXYLzEn9jhVbFJRuOGIUJRZaxWhhUy5zVDIxUo6wS78BBnF6PaHaW1bQgdm02Qril00IPNtAGGI5Do+IQxho9GBAsrxOQYlRdptsdnE6dQBdkaYK/MMfg0Uc58fQJ0mFMaMU47Q7dRkDddzENxchy6JUOB6o1Kp5LqUpsXZBg0rUDUArftdgYjQOLoc6uXfIdi4V29azvS5w+c25VnBVM6h6qJMsJk5yqZ2Nb0s1ZiEkgQUdMrDLPSVbX0FrjddqXfeZSmIz775RhyPqxE/jNCqHl0IuXGfRiqNbQnRZm4GFaFpZpcOS2G1juRxxdHbKy3meYl9zgKYaOxj9wEHc4IEsSphtNSivFHMZoz6EwLTaW12h2psiLgpFh4lVrFJaNQqGUInAdrmvWOHTjPC+YaZHkOU+tDMY7qzoNtGVRDTw63etIk5SsH+PmJd26T5wVpPn4rCqtn/OfvqVT8zi+PsJUisZlzubkRcmxtSF5UTLTDM6YMdoN8qLkyeU+pYbVoeLIdPOsGS8hxN4jQUdMJK01Tz5xnNFGn5pvM20a+N3uRfzNs3mOhWEo8nBEpdPGMDW6gESbZLmmakCtUcNzTMI4pyg0rarPoakGcXqUbDRgeRQxqrYoax4hkIYx62GIevIEQb2KsXAANjaINCS2wwHPGTfnU6BQPHVilcW5WQ6VsBxl+HOzHJmfoixLvvv0KihwLRNzcxu9b1sow8D1PY74HlprlFLkRYlCE2UFFffiX/5Vz+HGuecXTHphQpSOt6Uv9cKrGnSWeiFRmtGq+ltNDJ9LVpSc3h2fF5pSawwk6Aix10nQERMpSnPCvERr6IcZU5fxhrU+ilnqhbiWyaFOjcgsMMMRyjCwgypHH3qCGhmOZXBTzWToVUiqm++UZcngxAl6Dz3MqB8ybSkWIk1raoH44CGGaYGd5MR5QVqUlJZDND2P12hyaphQHl/l1gNTKAzKKKLcWOPohkXqVZhf7DLTCKAsefSRJ4i//zQ6qFCZn2OhUyNwLDznzJe22gxAlmlgGAZZnvH06pCDnRoVzx43ARyNxrVH/tmHdV4JzralIMe+estCwzhlbRgDkKwPqT/HkRWn+Y5Fs+IyjFMagYtlnt0FWgix90jQERPJsUysep3CMLANdVbdzYXkRYnWmr86tkpRlDQDl0bFpTU9RRHXSEtNaRh0Fg+QOwaGYeLonCnfYi0tMQ2DQX/EySeXKIuCllFglIo8yzi1so7OFbMvvJ4lv4IejVAGLC4u8EQ/JUwyGhUXUxks9yMOTdUhLjECl94oRZGyOojo1n2KUUi2toGXpzDImTFncC2TOCtQClz73C/vMMm2Po6ynIpnEy0tU2bj68HMDKZ35YuNa77DgU6VrChp+FevmHn7MRWXuvQ0PrD0woeWCiH2Fgk6YiJZpsF10w3iVpXAsTDO8du5LkvKLBtvJd98czy9u6g3SgjjjOPrI1zbpFX1aVU8VpKctUHM+ijGVOAWJZ3AwTBNKhWfWsMiHoV873vHMXrrjAqIc4VnmWhtUdOKqWaNdjXghT90E6PjJ+kNI+Io4oaZDoXWPHVyHUeVeI6JaSim57tEp5YYRBlLOSSrfaqezZRnkWQ5pqGwPQfPNnno2CrLg4ipmk/Vs7FMg2bFO+Noh07N5+TGCMswtpZ1Tp82DlAWOSYuSTa+5l7B2ZdrUZdjGeNT1oHLricSQkwOCTpiYjmWecZyyXa6LAlPnqLMMkzHwZ+dQSlFb3NHUl6WGIai5js0A3ertqQfpoRpTj9KaeURlmVi9jYY9jYowoj6jTcQHzuOOeyRpSmtRsDK7AK+72Drkty1MQxFUZZYaDzLwKn7jOIcpxnQH0YcUDGqgN5yxkOjhKd9h5ctzjE31eX7f3UUW8HTqwMq822cxUXM9TWU45IkKeHqMhgOfdMkTDK6vs2pXp/64izO5ixNI3Cp+87WchaA226T9nrjpasgoB8mHF8fATDTDGhVvMt+HpKsYGUQ4VgGU1vdlq+OOM15amVcUNysuFc0pAkh9iYJOmJfKvN8a6mmSFN0nqNsG9c2We5HNAIH3w1Y7kXUfXfrwNB64BAmGYZSuFpjKkj7fUzPZbCyhtVeRRcFnapPWUJzqstUtUk/TFCGIrBtjq2NsE2T7yUZTphjFhnzs13WS83yygZFVtCtB2ysjyj8Kv0wZWkQUfNsap5LWhQkeUkjcIkaVSLPo2kr2Fijbxqk4YjmTAddluSrK1iGIl1exj6wsBUynh027EqAXXlmq/lo2/LWKM6eV9A5sT4k3pwdskzjeX2u5xKl+VZB8TBOZRlKCCFBR+xPhm1jug5FkmK6LsqyKEtNmhfYpoFpGBzuNjjYqZMVJcFmce9Mo0Iz8LhuukHUH+CEQ8LBOhtZSZrEnDjVxzMdLGXTPVAnbnWp2w4vPdzl4eMbJFmObRmUGpZ7Id36+GgFVRiUec56ASot8KOUWrvJagmWYVD1HKqezUK7wvooZb4dYFsmBzvjjjZlljGKhtww1wLDIFiYJo1iNvII37XQZTneT36Rsyl132UQpejNozKej+1f8mrvYap4NtZQkRea5lUMVEKIvUOCjtiXlFL4MzPookCZJkopsqKgKJ8p4s2LEte2zlr+cm0T1zY3A8AU1blZ1h5+HMcLWEk0VsXHrlZxWhVma+NZkpVBRJzmDOKUwLE26348VocRaV5wYl2TlSWYJs1DC7QbFRY6dZZ6I3zXpu47JFlBlmtsSxFnJWlebI3NsG2CmWmKJMHyfQzTxKpWMKbbFHGMXatu1SFdjIpnc/1sE625qN1HWmvWhjFZUdKpemc025ttVlkdRtimsVUzU6QpuiyxvCsbRhzL5PqZJkWpZdeUEAIk6Ij9TCmFsp55CTiWSbPicmpjRJTmHF83WWhXz1vnA1CWmtWkIGu0sU2DqpHh2RaGOW7sd9q4p4tHq+rRrLjMNAKKUvOdp5YpNawNY2q+hYFBxXWYbVWxTIP5do3hKOLh7x/l6CBmOcyoei7Xz1jEaX7G2LRlo0wLY9s1r3NxW6vPxbyEYLQRJiz3IwDSvBjvFtvk2ibzrWe6LWejkHhlBQCnUcdtNi97jOeilMIyzz93lEcRaa+H4Ti4rdZVrRkSQuw8CTpCbDPbrJDmBW6Sk2QF66OYmcb56zxWhxEbo4TAsXFtg1sOdAjTHNs0zyiEbVU8omSIUopm4G69Gd98oMPyIMJQ48aECsXBTm1rVklrzdrTx0h7IwZLfQZWQJqXzDWDrbohNutojq4N0BrmWpVrvttIb2uzrJ+j5XKRxNs+Tq7quM4lXllFl+XWsqVdkToeISaZBB0hnsW1TcJkvMvK3TY7kuXj3UOubdKqeCilMLbNBtiWibFZT/NsVc/hBXNnzx64tsWBdo3ZRoW1YcRgvc/g6R6q5m91cvZMA8s08SyDmbpHp1XnULd+xtLMIE63jnToR8lVDTqjOCMtChq+u9Wnphl4pHlJXoyPmrgQu1olH4VorbGrtas2zvNRpjmuWYJLWs4TQuxNEnSEeJbpeoBvj499OB1a0rzgvu+foB+nWEpxcKrOkZkm7aqH3qzn2d6r5lwutERimQZRWhCtbRAWBegSK6jg1Gs0um0c26I73WLoVDAMRbt65teqeja9MEFrqF3FXjXDOOXo6hA2A8+BzjioGIbabLb33EzHoXJgAZ7je3K1+N0psuEQ4yp2gRZC7B4SdITYlMcxeRhi+T714Mw3wEGUkhUlYZIxinPqgcfJjRGHpurPGXAuVlGWYFtQFJSlxthcvnKbza06lpnz/N2q53BkuoF+1lELF0trzUaYoDb77JwvgKR5cc6PL9VO1sUYto3buvhO2UKIvU2Cjphoa8OIYZzRCNwLLufosiReWkZrTTYcUZmfw9hWqBy4Np2azyhJcUyLmu9c8PTvbDgk2ehh2jZed+qilkhmmhWW0ZhZylS7fsmzDfZlBJzTlvvR1vlQeanPG97G286zzSWq4Jz3CCHEbiJBR0ysJMtZ6o13AkVpTsW1z7vlWGv9TBGt1jw7xfiOxQvn2xyZbjBKcvLywktVyfrGuGFfUZCHIXa1etY9RVkSpTmebWGZBhXXpjKzMzMN6bYjIPKiPO99lmmw2K2f9/HL0QsTlvshrm2y0Kpd8vlU25V5Th6GmK6L6crxD0IICTpiFytLzdooxlBsFf9eCqUUSm32yePCvfIM08TrtMlGIyw/wLDts+45faRE5SJqYAzbokjS8cfW2Z9La82Ty33CJMexDI7MNHe070u35pPnJUqxdU7UtbLUCylKTV7k9KPkshv9aa2JTp2izAtQisrc7DmfRyHE/iJBR+xaS/2Qjc2zp4pSX/JSiWON+7eMkoya7zxnXxi7Wj3nzMvl8LtdslGI4djnPAk8L0qW+xHroxilFFP14JoHjO1c2+LwdGNHvrZjmVtniV1OfdEWrcch5/THRfG8g84gShkl46VP35Efl0LsRfLKFbtWUepzfnwpar5D1bWu+TZiZZo49fNvnbYtc2uGybMN8nMsHe2Xzr4HOlX6UYpjmWf0BrpUyjBwm02y4QDT9Z531+Ukyzm2Nt5h1o9SbphpPq9lNSHEzpCgI3atbt2nKEsMpS57Z1O8tk42GIxPKJ+Z3lV9U47MNKl5Iea2bey9MOHE+ghDwUKnRuV5vPHvFaZx5Q76dBp1nMaVqSHanq2fqwmiEGL3kqAjdi3HMs84SuBSaa3JBgN0Pi4ePn0O1JVQlvp5/3Y/VfOpeQ6mobZmb3rheKmu1ONlk/0QdHYr37Ho1n1GSUaz4slsjhB7lAQdMbGUUmSjEVl/gGHbVObnnvfn1FpzdG3AKM6p+Q5TNZ9TvRGGGjfMu9Tlpu3HRMC42V+Y5Cg1bgIodlan5tO5Qn2ShBA7Q4KOmFi6LLGCAMO0ULa11fb/+UiyglE8LpwdRClpnpNk48/78PE1AlVSK1Oq1Qpuq3nJO8VaVY/AtTHU8+uLI4QQYkyCjthT8qJkZRChFHRrwQWXE5RhYPs+uVIYlonpPP+jEWzLwDYNsqLEsQxcyyLJUsIkI80L9LBHqAtcXWI69mXt4nr2LI8QQojLJ0FH7CmneiGDaLM/jVLPueXcm+5SZhmGdWV2XpnGuGFenOX4m6eNO7ZJktr0o5QiVJh6HL52U+GzEELsVxJ09iGt9Y6eNXQtKaXOmMlJ84L1UYxrmZfdmM4yDarmM5/z9I6wWpQS+jZBkeL6LlYgRyQIIcROk6Czz5zcGLExSghci4Od2p4LPDONAEONA8zlNNg7ujogzZ/pU1O9gid9132Hqmuz1A8ZZJrpvJA6GyHEnqK1pohjDMuamM7iEnT2kbwotzoNh0lOlObPq0HbTrBMg7nW5XcvLrf1QykvswnhhawOo63vsdaaA53zNw0UQojdJl5dJR+FoBTBzPREnBknRQT7iGkoHMvY9vH+m22Ya1XxHYtW1aXmX7nZnNPOmCHbW5NlQghBEY9/UUPrrfP69jqZ0dlHlFIsduuESY5nm/vmiIHtKq5NpXv1ZrHaFW889Vvqy+7mLIQQO8Wp10jWNzAsEyuYjJ9hEnT2GdMwrspMhhgzjOfeCbYfleW40WKU5rSrnnyPhNhheRSRDUeYnotTe2aJ3anXsavVido1KkFHCHHVhWlGmIwbLa4OYqZq/p4qhE+yghPrQzQw36rg2vKjU+xdWmvi5RW01uRhiOk4jErFxiim6tm0q5Mxk3Pa5EQ2IcSu5Vgmp3s7ura5p0IOwNowIs4KkqxgZRDv9HCEuKKKsuTE+pAwyVnqRcRpvtNDuqLk1xIhLpMuy4ma3r2aHMtksdsgyXIqe/AMr+1tAk4X9AuxVyml8LpTW0tXluuhVIze3JW6134ReS4SdIS4RLooCE8tUWYZTqOO22zu9JD2BNc29+zxFlM1H9s00FrTCPb+dlshLN/H8p9ZojrQrtKPUgLX3rOv0/ORoCPEJcqjiDLLAMj6Awk6O6AsNaXW13TnoAQcMckC195zfdUulgQdIS6R4TgopdBaY3qXd4zE1VSkKcn6Oso08drtiVteS7KCp1b6FKVmuuFPXOGkEOLKkqAjxCUyHYdgbpYyz3dl0EnW1imScdOv1LZxG42dHtIVNYxTis2u1hujRIKOEOKCJutXPSGuEcO20UUxDhXp7uoeqrYt5yg1eS/xwLU5XSs5qVPtQogrR2Z0hLgMeRwTr64BUMQRlYWFnR7SFq/dJrUGKNPArl3+uWC7le9YHJlukJca35EfYUKIC5OfEkJcjrLc+lBfhcNBnw9lmrityS6Qti0TmcsRQlwMCTpCXAYrCHAadcokxa7LCeVCCLFbSdAR4jLJtnIhhDi/LC/oRSmebVL1du6MRQk6Qojz0lqz1A9JsoKpmn9Vi3+11myECWWpaVU8DGOyurMKsd88vTogzcfL/Ivd+o7V1EnQEftWHobEK6tgGPjTXUxHTnV/tn6Usj4cb1U/kY+4fvbqzWKtj2KWehEAaV4w15q8Qmoh9pO8eKaWMStKdqoRxEQFHa01Dz/88FnX5+bmaExYLxHx/KX9wfhsl6IYn/nSlqDzbMa2M2+u9gxLXjxT1J1vK/YWQuxNs80KK4MI37Go7eAZdxMVdEajES960YtYXFzE29bI7ROf+AQ/+ZM/uaNjE7uP6TpbjfVMV9r7n0vNd5hpBiRZQbt6dZsjtqseSZ5TlprpenBVv5YQ4uqrBy71XXB0ykQFndPuvvtuXvGKV+z0MMQu57ZamJ6HMgwJOhfQqlyb7s+WaXCwU78mX0sIsX9MXttUYDgc8uSTT1IUxU4PRexylu9LyBFCiAk2kUHnrW99K694xSuoVCr8wi/8AqPRaKeHJIQQQogdsKuXroqi4JFHHrngPbVajYXN9vumafI7v/M7vP/978d1Xb71rW/xlre8hTzP+exnP3vOv58kCclmnQZAv9+/wv8KIYQQQuwUpbXeXf3rt9nY2HjOWps3vOEN3Hnnned9/FOf+hS/8iu/wnA4xDTNsx7/2Mc+xm/+5m+edb3X61GvS72AEEIIsdv0+30ajcZFvVfv6qBzJdxzzz28/e1v58SJE8zOzp71+LlmdA4ePChBRwghhNilLiXo7Oqlq0uVZRm2feZe/T/7sz+j2WzS7XbP+Xdc18WVYlQhhBBiIk1U0PnUpz7FY489xk/8xE/QbDb54z/+Y/7tv/233HHHHedcthJCCCHEZJuooPOBD3yA3/u93+OTn/wky8vLHDlyhC996Uu87nWv2+mhCSGEEGIHTHyNzqW6lHU/IYQQQlx7l/JePZF9dIQQQgghkKAjhBBCiEkmQUcIIYQQE0uCjhBCCCEmlgQdIfaYOM3Ji3KnhyGEEHvCRG0vF2LSHV8f0g9TTEOx2K3jWNIfSgghLkRmdITYQ4ZRCkBRaqI03+nhCCHEridBR4g9pB6MjyuxTYOKaz/n/UIIsd/J0pUQe8hss0Kn6mEaBoahdno4Qgix60nQEWKPsaUuRwghLposXQkhhBBiYknQEUIIIcTEkqAjhBBCiIklQUeIPabc3FpelNI0UAghnosUIwuxh2iteWqlT5wVOJbBYreOacjvK0IIcT7yE1KIPSQvSuKsACDNS9JcZnWEEOJCJOgIsYfYlknFG0/EeraJK1vNhRDigmTpSog95kC7Rl6UWKaBUtI0UAghLkSCjhB7jFJKmgYKIcRFkqUrIYQQQkwsCTpCCCGEmFgSdIQQQggxsSToCCGEEGJiSdARQgghxMSSoCOEEEKIiSVBRwghhBATS4KOEEIIISaWBB0hhBBCTCwJOkIIIYSYWBJ0hBBCCDGxJOgIIYQQYmJJ0BFCCCHExJKgI4QQQoiJJUFHCCGEEBNLgo4QQgghJpYEHSGEEEJMLAk6QgghhJhYEnSEEEIIMbEk6AghhBBiYknQEUIIIcTEkqAjhBBCiIklQUcIIYQQE0uCjhBCCCEmlgQdIYQQQkwsCTpCCCGEmFgSdIQQQggxsSToCCGEEGJiSdARQgghxMSSoCOEEEKIiSVBRwghhBATS4KOEEIIISaWBB0hhBBCTCwJOkIIIYSYWBJ0hBBCCDGxrJ0egBBCiN2lzHPi1VXQ4HXaGLa900MS4rLJjI4QQogzpP0+RZxQJAnJxsZOD0eI50WCjhBCiDMo0zznx0LsRbJ0JYQQ4gxOvY4yDNAau1rd6eEI8bxI0BFCCHEGpRROrbbTwxDiipClKyGEEEJMLAk6QgghhJhYEnSEEEIIMbEk6AghhBBiYknQEUIIIcTEkqAjhBBCiIklQUcIIYQQE0uCjhBCCCEmlgQdIYQQQkwsCTpCCCGEmFgSdIQQQggxsSToCCGEEGJiSdARQgghxMTac6eXr6yscM8991Cr1fiZn/mZc97z2GOP8ad/+qd4nseP/diP0el0rvk4hRBCCLHz9syMTlEUvOtd7+IlL3kJv/Vbv8W//Jf/8pz3/ft//++59dZbueeee/jMZz7DDTfcwFe/+tVrPl4hhBBC7Lw9E3S01vzYj/0Yjz76KG9+85vPec/x48f5xV/8Rf71v/7XfOELX+BP//RPedvb3sbP/dzPXfPxCiGEEGLn7ZmgY1kW73rXu/A877z33HPPPViWxbvf/e6ta7/wC7/Aww8/zP3333+NRiqEEEKI3WLPBJ2L8eCDD3L48OEzwtCLXvSircfOJUkS+v3+Gf8JIYQQYjLsWDFyHMd87nOfu+A9R44cOe8y1bkMBgOazeYZ1+r1OqZpnjfAfOITn+A3f/M3L/prCCGEEGLv2LGgUxQFDz300AXvcV33kj6n7/sMBoMzro1GI4qiIAiCc/6dj370o/zSL/3S1p/7/T4HDx68pK8rhBBCiN1px4JOpVLhzjvvvKKf8wUveAF33303RVFgmiZsbjU//di5uK57yYFKCCGEEHvDRNXovPWtb6Xf73PvvfduXfv93/99ZmdnefnLX76jYxNCCCHEtbenGgbeddddrK6u8sADD7C8vLw1I/Te974X27a58cYb+eVf/mXe/e538773vY+1tTV+93d/l7vuugvL2lP/VCGEEEJcAXvq3f/xxx/n+PHj3HLLLdxyyy1bNT5a6617/sW/+Be87nWv43/+z//JzMwM9913Hy95yUt2cNRCCCGE2ClKb08Jgn6/T6PRoNfrUa/Xd3o4QgghhHiWS3mvnqgaHSGEEEKI7SToCCGEEGJiSdARQgghxMSSoCOEEEKIiSVBRwghhBATS4KOEEIIISaWBB0hhBBCTCwJOkIIIYSYWBJ0hBBCCDGxJOgIIYQQYmJJ0BFCCCHExJKgI4QQQoiJJUFHCCGEEBNLgo4QQgghJpYEHSGEEEJMLAk6QgghhJhYEnSEEEIIMbEk6AghhBBiYknQEeIK0lqTZAVlqXd6KEIIIQBrpwcgxKTQWvPUyoAozXFtk8WpOoahdnpYQgixr8mMjhBXSFaURGkOQJIVpHmx00MSQoh9T4KOEFeIbRr4jgmAa5s4lrnTQxJCiH1Plq6EuEKUUhyaqpPmBbZpyrKVEELsAhJ0hLiClFK4tryshBBit5ClKyGEEEJMLAk6QgghhJhYEnSEEEIIMbEk6AghhBBiYknQEUIIIcTEkqAjhBBCiIklQUcIIYQQE0uCjhBCCCEmlgQdIYQQQkwsCTpCCCGEmFgSdIQQQggxsSToCCGEEGJiSdARQgghxMSSoCOEEEKIiWXt9AB2G601AP1+f6eHIoQQQohzOP0effo9+0Ik6DzLYDAA4ODBgzs9FCGEEEJcwGAwoNFoXPAepS8mDu0jZVly/PhxarUaSqmdHs4V1+/3OXjwIE8//TT1en2nhyM2yfOye8lzs3vJc7N7Xe3nRmvNYDBgfn4ew7hwFY7M6DyLYRgcOHBgp4dx1dXrdfnBsAvJ87J7yXOze8lzs3tdzefmuWZyTpNiZCGEEEJMLAk6QgghhJhYEnT2Gdd1+Y3f+A1c193poYht5HnZveS52b3kudm9dtNzI8XIQgghhJhYMqMjhBBCiIklQUcIIYQQE0uCjhBCCCEmlvTR2cf+x//4H/zGb/zGWdf/5E/+hGq1uiNj2o/+4i/+gk996lOcOHGCm2++mV/91V/dF72cdrv3v//9fPOb3zzj2utf/3o+/vGP79iY9qsHH3yQz3zmM3zta1/jV3/1V/mJn/iJs+75f//v/3HHHXfw+OOPc/311/Mrv/Ir3HTTTTsy3v3kz//8z/nMZz7Do48+yuc///mzvucf+9jH+OIXv3jGtVtvvZXPfe5z12yMEnT2seXlZR555BHuvffeM677vr9jY9pv/uIv/oLXvva1fPCDH+Rd73oXn/70p3nVq17FAw88QKvV2unh7WsPPvggL3rRi3jve9+7da3T6ezomPaj3/3d3+WOO+7g53/+5/nsZz/L0tLSWfd873vf41WvehV/+2//bT7ykY9w11138cpXvpJvfvObXHfddTsy7v3gAx/4AF//+tf58R//cf7Tf/pPDIfDs+75/ve/T6fT4dd//de3rtVqtWs6Ttl1tY/9wR/8Af/4H/9jTp48udND2bf+xt/4G9RqNb7whS8AkCQJCwsLfPCDH+Sf/JN/stPD29de+9rX8upXv5p//s//+U4PZV/r9/tbnXU9z+POO+/k7//9v3/GPe9+97t58MEHue+++2DzeIBbbrmFH/3RH+XTn/70jox7P+j1ejQaDR566CFe9KIXcd999/HX/tpfO+Oed77znViWxec///kdG6fU6Oxz/X6fN73pTbzpTW/iIx/5CMvLyzs9pH0jyzL+/M//nLe97W1b11zX5W/+zb/Jn/zJn+zo2MTYH/3RH/GjP/qj/OzP/iy/93u/d1EnJYsr62KOD/jyl7/MW9/61q0/K6V429veJq+jq+xij2D4sz/7M173utfxUz/1U9x5553keX7Vx7adLF3tY0op/tbf+lv81E/9FHme86lPfYpbbrmF+++/n/n5+Z0e3sQ7fvw4WZad9b2en5/nq1/96o6NS4xNT0/z5je/mZe97GV897vf5UMf+hD/63/9rx39zVScrSgKjh07ds7X0ZNPPrlj4xJjtVqNv/f3/h4/8iM/whNPPME/+2f/jHvuuYcvfelL1+zgbAk6E+S//tf/+pyFkr/+67/OW97yFgB++qd/mne84x1bj73lLW/h5ptv5uMf/zh33nnnVR/vfpdlGWzO4mzn+/7WY2Ln/P7v//7Wc/OGN7yBF77whbzpTW/iAx/4AC996Ut3enhi04VeR3meo7W+Zm+o4myf/OQnz3huXvGKV3Dbbbdx7733njELdzVJ0Jkgr3zlK/nkJz95wXuuv/76rY+f/YPBdV1e85rX8MADD1y1MYpntNttANbW1s64vrq6KkWvu8CzXx+vf/3rUUrxwAMPSNDZRTzPw/f9c76O2u22hJwd9uzX0Ytf/GJmZmZ44IEHJOiIS9ftdul2u8/rc5w8eZJKpXLFxiTOr91us7i4yH333cdP//RPb13/v//3//IDP/ADOzo2cbalpSW01vL62IVe9rKXbRUinyavo90pSRLW19ev6etIipH3sX/zb/7NGcXH//k//2e+9KUv8bM/+7M7Oq795Pbbb+fzn//8Vi3Bf/tv/41vfvOb3H777Ts9tH3tscceO6P4eDQa8Y/+0T+i0+nwxje+caeHJ57l9ttv55577tmajf7a177GF7/4RXkd7bBer8cnP/nJreLjNE35wAc+gGEYvP3tb79m45AZnX1senqal7/85biuSxzH9Ho9/tW/+le85z3v2emh7Rsf+chHePjhh3nhC1/IoUOHePrpp/md3/kdXv3qV+/00Pa1brfLV7/6VT74wQ9y4MABnnjiCW666Sa+9KUvXfROE3FlfPvb3+bnf/7nYfON8hOf+ASf+9zn+PEf/3E+9rGPAfCe97yHb3/72/zQD/0Qhw8f5oknnuCDH/yg/NJ2lf3hH/4hd9xxB3EcA/BzP/dzVCoV/uE//If83b/7d6lUKpw4cYKZmRnm5+c5duwYMzMz/PEf/zGHDx++ZuOUPjr7nNaaRx99FKUUhw8fxjTNnR7SvnTixAlOnjzJ9ddff1HbacW1EYYhjz76KLOzs897WVhcnsFgwHe/+92zrne73TNqDgFWVlZ46qmnWFxclDq3a+DUqVM8/vjjZ11fXFxkbm5u689JkvDII4/Q6XTOuH6tSNARQgghxMSSGh0hhBBCTCwJOkIIIYSYWBJ0hBBCCDGxJOgIIYQQYmJJ0BFCCCHExJKgI4QQQoiJJUFHCCGEEBNLOiMLIfac+++/n4ceeggAy7JYWFjgB37gB/A874z7yrLkO9/5Do8//jitVoubb775nI3/nnjiia2zkW688cZr9u8QQlx9EnSEEHvOH/zBH2wdA1AUBd/61rdIkoQ//MM/5Id/+IcB+PKXv8z73vc+oijiB3/wBxkMBnzve9/j9a9/Pf/u3/07PM/jwQcf5Jd/+Zd58MEHOX78OL/1W78lQUeICSNBRwixJx04cIC7774bgDzPeeMb38j73vc+vvWtb/HVr36VN73pTXz0ox/ln/7Tf7p1tElZltx1110kSYLnefR6Pf7BP/gHvPnNb2Z6enqH/0VCiKtBgo4QYs+zLIu3vvWtfPjDH6YoCj760Y9y22238bGPfQyl1NZ9hmHwjne8Y+vPr3zlK3doxEKIa0WKkYUQE+GRRx5henqaJEn4yle+wk/+5E+eEXKEEPuTzOgIIfakXq/H3XffTVEUfP3rX+c//If/wB133MHy8jJFUXDo0KGdHqIQYheQoCOE2JMGgwFf+MIXME2T+fl5vvzlL/PX//pfZ21tDYDV1dWdHqIQYheQoCOE2JO2FyNv1263uf766/nLv/zLHRmXEGJ3kRodIcTE+aVf+iX+y3/5L/yf//N/znpsaWmJJEl2ZFxCiGtPZnSEEBPn/e9/Pw8//DBvfOMbec973sMP/dAPMRgM+M53vsOXv/xlvvGNb+C6LhsbG3zxi18EIE1TvvWtb3H33Xdz4MABXv3qV+/0P0MIcQUorbXe6UEIIcSl+I//8T9y//3389u//dsXvO/+++/nj/7oj3jyySdpNpvcdttt/J2/83fwfR+AJ598kg9/+MNn/b2Xv/zlfOhDH7pq4xdCXDsSdIQQQggxsaRGRwghhBATS4KOEEIIISaWBB0hhBBCTCwJOkIIIYSYWBJ0hBBCCDGxJOgIIYQQYmJJ0BFCCCHExJKgI4QQQoiJJUFHCCGEEBNLgo4QQgghJpYEHSGEEEJMLAk6QgghhJhY/x8BLnDrSc1z4AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 580x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "feats = np.asarray(negcon.X, dtype=np.float64)\n",
    "feats -= feats.mean(axis=0)\n",
    "scale = feats.std(axis=0)\n",
    "feats /= np.where(scale > 0, scale, 1.0)\n",
    "u, s, _ = np.linalg.svd(feats, full_matrices=False)\n",
    "coords = u[:, :2] * s[:2]\n",
    "is_non_targeting = (negcon.obs[\"Metadata_Perturbation\"].astype(str) == \"non-targeting\").to_numpy()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5.8, 5))\n",
    "ax.scatter(\n",
    "    coords[~is_non_targeting, 0],\n",
    "    coords[~is_non_targeting, 1],\n",
    "    s=6,\n",
    "    alpha=0.2,\n",
    "    color=\"#3a7ca5\",\n",
    "    edgecolor=\"none\",\n",
    "    label=\"no-guide (empty)\",\n",
    ")\n",
    "ax.scatter(\n",
    "    coords[is_non_targeting, 0],\n",
    "    coords[is_non_targeting, 1],\n",
    "    s=6,\n",
    "    alpha=0.2,\n",
    "    color=\"#c1666b\",\n",
    "    edgecolor=\"none\",\n",
    "    label=\"non-targeting\",\n",
    ")\n",
    "ax.set(xlabel=\"PC1\", ylabel=\"PC2\", title=\"Negative controls: non-targeting against empty wells\")\n",
    "legend = ax.legend(frameon=False, fontsize=8, markerscale=2)\n",
    "for handle in legend.legend_handles:\n",
    "    handle.set_alpha(1)\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c8eed84",
   "metadata": {},
   "source": [
    "The table gives an mAP per control kind and a p-value for whether each kind retrieves its own beyond chance; the figure shows the same as two point clouds.\n",
    "\n",
    "The non-targeting wells are told apart from the empty ones beyond chance: their mAP of 0.383 carries a corrected p-value of 0.011, while the no-guide row's higher mAP of 0.639 does not reach significance (p 0.105), a reminder that an mAP is read against its permutation null, not on its face. So the two negative controls are not one inert baseline. A likely source is the burden of delivery and expression (the lentiviral integration, the sgRNA and the Cas9 the empty wells never received) rather than a cut, since a non-targeting guide cuts nothing; nothing in this screen tests that explanation. Because the sphering above pools both kinds as `negcon`, every knockout is scored against a reference that carries this delivery signature, and the choice of reference (empty wells, non-targeting, or both) moves the map. Worth checking, rather than assuming the two agree, before leaning on one baseline."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9bea4bf",
   "metadata": {},
   "source": [
    "## How do they differ?\n",
    "\n",
    "The two negative controls are distinguishable, so the next question is what the difference is made of: which\n",
    "measurements carry it? On the same sphered negcon wells, where the plate effects are already gone,\n",
    "{func}`~mantispy.tl.effect_size` gives the per-feature effect of the non-targeting wells against the empty\n",
    "ones, with `no-guide` as the reference so a positive effect marks a feature the non-targeting wells sit\n",
    "*above*. `cohens_d` is a standardized mean difference per feature, so the features are comparable and the\n",
    "check stays cheap, with no permutation null unlike the mAP above. The twelve features with the largest\n",
    "absolute effect are the delivery-and-expression signature the two controls differ by."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "213ab213",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:29:32.014454Z",
     "iopub.status.busy": "2026-10-21T00:29:32.014236Z",
     "iopub.status.idle": "2026-10-21T00:29:32.176058Z",
     "shell.execute_reply": "2026-10-21T00:29:32.174444Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    595.000\n",
       "mean       0.043\n",
       "std        0.040\n",
       "min        0.000\n",
       "25%        0.014\n",
       "50%        0.031\n",
       "75%        0.059\n",
       "max        0.246\n",
       "Name: effect, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The sphered negcon wells from the agreement check, with no-guide as the reference, so each feature's effect\n",
    "# reads as non-targeting minus empty; cohens_d is a standardized mean difference, comparable across features.\n",
    "negcon.obs[\"_no_guide\"] = (negcon.obs[\"Metadata_Perturbation\"].astype(str) == \"no-guide\").to_numpy()\n",
    "mt.tl.effect_size(\n",
    "    negcon,\n",
    "    groupby=\"Metadata_Perturbation\",\n",
    "    reference=\"_no_guide\",\n",
    "    method=\"cohens_d\",\n",
    "    pvalues=False,\n",
    "    key_added=\"delivery\",\n",
    ")\n",
    "# The non-targeting group carries the contrast; the reference is scored against itself as a near-zero check.\n",
    "delivery = negcon.uns[\"mantispy\"][\"delivery\"]\n",
    "delivery = delivery[delivery[\"group\"] == \"non-targeting\"].copy()\n",
    "delivery[\"effect\"].abs().describe().round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "50e75949",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:29:32.180122Z",
     "iopub.status.busy": "2026-10-21T00:29:32.179709Z",
     "iopub.status.idle": "2026-10-21T00:29:46.076698Z",
     "shell.execute_reply": "2026-10-21T00:29:46.075561Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script>\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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   ],
   "source": [
    "# The twelve features that separate non-targeting from empty most, coloured by feature family.\n",
    "mt.pl.effect_sizes(negcon, group=\"non-targeting\", key=\"delivery\", top=12);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6dda962",
   "metadata": {},
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    "The bar names the measurements that carry the difference: `Nuclei_Granularity_6_Mito`, `Cytoplasm_Granularity_1_Mito`, the radial distribution of mitochondrial tubeness across the cell, a `Cytoplasm_Correlation_AGP_DNA` term and a handful of Mito texture and DNA-Mito overlap features. By kind they are granularity, radial-distribution and texture features, sitting mostly in the mitochondrial (Mito) channel, with a little RNA intensity. The signature is probably one of delivery and expression rather than cutting, since the non-targeting wells carry a lentiviral integration, an sgRNA and Cas9 that the empty wells never received, and a non-targeting guide makes no cut. This notebook does not test that, and the Mito-channel lean is an observation, not a mechanism. The effects are modest in size: a median absolute Cohen's d of 0.03, reaching 0.25 at the top. The two controls are distinguishable, as the retrieval test above found, but only modestly, so this is a lean of the baseline rather than a phenotype of its own, though modest is not nothing when these wells define the reference every knockout is scored against."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "305cced9",
   "metadata": {},
   "source": [
    "## Does the reference you normalize to change the hits?\n",
    "\n",
    "The two negative controls are not one baseline, so the reference the screen normalizes against is a choice, not a\n",
    "formality. Does that choice reach the hits? A cheap check answers it without the 20,000-permutation mAP above.\n",
    "Start from a fresh load, so the already-sphered `wells` is left alone, and normalize it four ways: to the empty\n",
    "wells alone, to the non-targeting wells alone, to both together (`negcon`), and to every well on the plate. Each\n",
    "is a per-plate robust MAD normalization; they differ only in which rows set the centre and spread. A gene's\n",
    "activity is then read cheaply as the L2 norm of its modz consensus (its distance from the reference-centred\n",
    "origin) with no permutations. If the reference barely matters, a gene keeps its activity whichever rows define\n",
    "zero."
   ]
  },
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   "execution_count": 7,
   "id": "4e890df9",
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    "execution": {
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     "data": {
      "text/plain": [
       "(7971, 4)"
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   ],
   "source": [
    "raw = mt.ds.jump_crispr()\n",
    "pert = raw.obs[\"Metadata_Perturbation\"].astype(str)\n",
    "# Boolean flags picking out each negcon subset; \"negcon\" already selects both, None every well.\n",
    "raw.obs[\"_ref_no_guide\"] = (pert == \"no-guide\").to_numpy()\n",
    "raw.obs[\"_ref_non_targeting\"] = (pert == \"non-targeting\").to_numpy()\n",
    "references = {\n",
    "    \"no-guide only\": \"_ref_no_guide\",\n",
    "    \"non-targeting only\": \"_ref_non_targeting\",\n",
    "    \"both (negcon)\": \"negcon\",\n",
    "    \"whole-plate\": None,\n",
    "}\n",
    "\n",
    "# Per-plate robust-normalize a fresh copy to each reference, noting features left degenerate under any choice.\n",
    "normalized = {}\n",
    "degenerate = np.zeros(raw.n_vars, dtype=bool)\n",
    "for name, reference in references.items():\n",
    "    norm = mt.pp.normalize(raw, method=\"mad_robustize\", by=\"Metadata_Plate\", reference=reference, copy=True)\n",
    "    degenerate |= norm.var[\"degenerate_scale\"].to_numpy()\n",
    "    normalized[name] = norm\n",
    "\n",
    "# Activity per gene: the L2 norm of its modz consensus, its distance from the reference-centred origin,\n",
    "# over the features usable under every reference so the four scores are comparable.\n",
    "keep = ~degenerate\n",
    "activity_columns = {}\n",
    "for name, norm in normalized.items():\n",
    "    signatures = per_gene(norm[:, keep])\n",
    "    activity_columns[name] = pd.Series(\n",
    "        np.linalg.norm(np.asarray(signatures.X, dtype=np.float64), axis=1),\n",
    "        index=signatures.obs[\"Metadata_Perturbation\"].astype(str),\n",
    "    )\n",
    "activity = pd.DataFrame(activity_columns).dropna()\n",
    "activity.shape"
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
   "id": "bdfb78b2",
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     "shell.execute_reply": "2026-10-21T00:30:26.372680Z"
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    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spearman r</th>\n",
       "      <th>top-100 Jaccard</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>no-guide only&nbsp;&nbsp;vs&nbsp;&nbsp;non-targeting only</th>\n",
       "      <td>0.781</td>\n",
       "      <td>0.724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>both (negcon)&nbsp;&nbsp;vs&nbsp;&nbsp;whole-plate</th>\n",
       "      <td>0.658</td>\n",
       "      <td>0.695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no-guide only&nbsp;&nbsp;vs&nbsp;&nbsp;whole-plate</th>\n",
       "      <td>0.432</td>\n",
       "      <td>0.613</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "                                       Spearman r  top-100 Jaccard\n",
       "no-guide only  vs  non-targeting only       0.781            0.724\n",
       "both (negcon)  vs  whole-plate              0.658            0.695\n",
       "no-guide only  vs  whole-plate              0.432            0.613"
      ]
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   ],
   "source": [
    "top = 100\n",
    "\n",
    "\n",
    "def _jaccard(a, b):\n",
    "    \"\"\"Overlap of two gene sets, as intersection over union.\"\"\"\n",
    "    sa, sb = set(a), set(b)\n",
    "    return len(sa & sb) / len(sa | sb)\n",
    "\n",
    "\n",
    "pairs = [\n",
    "    (\"no-guide only\", \"non-targeting only\"),\n",
    "    (\"both (negcon)\", \"whole-plate\"),\n",
    "    (\"no-guide only\", \"whole-plate\"),\n",
    "]\n",
    "sensitivity = pd.DataFrame(\n",
    "    {\n",
    "        \"Spearman r\": [float(spearmanr(activity[a], activity[b]).statistic) for a, b in pairs],\n",
    "        f\"top-{top} Jaccard\": [\n",
    "            _jaccard(activity[a].nlargest(top).index, activity[b].nlargest(top).index) for a, b in pairs\n",
    "        ],\n",
    "    },\n",
    "    index=[f\"{a}  vs  {b}\" for a, b in pairs],\n",
    ").round(3)\n",
    "sensitivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "671f737e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:30:26.376499Z",
     "iopub.status.busy": "2026-10-21T00:30:26.376352Z",
     "iopub.status.idle": "2026-10-21T00:30:27.658037Z",
     "shell.execute_reply": "2026-10-21T00:30:27.656567Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 540x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x, y = activity[\"no-guide only\"], activity[\"non-targeting only\"]\n",
    "movers = (x.rank() - y.rank()).abs().nlargest(6).index\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5.4, 5.4))\n",
    "ax.scatter(x, y, s=6, alpha=0.2, color=\"#3a7ca5\", edgecolor=\"none\")\n",
    "lo = float(min(x[x > 0].min(), y[y > 0].min()))\n",
    "hi = float(max(x.max(), y.max()))\n",
    "ax.plot([lo, hi], [lo, hi], ls=\"--\", lw=1, color=\"0.4\")\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.scatter(x[movers], y[movers], s=16, color=\"#c1666b\", edgecolor=\"none\")\n",
    "for gene in movers:\n",
    "    ax.annotate(gene, (x[gene], y[gene]), fontsize=8, xytext=(3, 3), textcoords=\"offset points\")\n",
    "ax.set(\n",
    "    xlabel=\"gene activity, normalized to no-guide\",\n",
    "    ylabel=\"gene activity, normalized to non-targeting\",\n",
    "    title=\"Does the reference move the hits?\",\n",
    ")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40140d33",
   "metadata": {},
   "source": [
    "The table reads the reference off the ranking directly. Between the two negative controls the gene activities correlate at Spearman r = 0.78, and their top 100 genes by activity overlap by 72% (Jaccard), about 84 genes in common. The scatter shows the same pair gene by gene: points on the dashed diagonal keep their activity whichever baseline defines zero, and the spread away from it is what the reference moves; the labelled genes shift rank the most.\n",
    "\n",
    "Read against the diagonal, the choice of reference **moves** the hits. Even the two negative-control baselines (empty and non-targeting) agree only at r = 0.78 and share about 84 of their top 100 (Jaccard 0.72), so roughly one in six of the strongest hits turns on which controls define zero. Whole-plate normalization, which depends on no control at all, diverges further still: r = 0.43 against the empty baseline and r = 0.66 against the pooled `negcon`. The reference is a first-order analytic decision, not a formality."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96d18302",
   "metadata": {},
   "source": [
    "## What to do about it\n",
    "\n",
    "- **Consider whole-plate normalization.** When perturbations are spread evenly across plates, per-plate robust\n",
    "  normalization over *all* wells is a common default, and it sidesteps the negcon-choice problem: no subset of\n",
    "  wells defines zero, so there is no baseline to pick. The comparison above shows that the choice moves the hits,\n",
    "  not which reference recovers the biology best.\n",
    "- **Normalize to controls only when the layout forces it.** Reach for control-based normalization when the plate\n",
    "  layout is uneven, or when many wells are expected to be active and would pull a whole-plate centre off zero, and\n",
    "  only where there are enough control wells (at least 16, more is better) that are not confined to a single row or\n",
    "  column.\n",
    "- **When you do, prefer non-targeting over empty wells.** Non-targeting guides are delivery-matched: a knockout is\n",
    "  then judged against wells that also received a guide, a lentiviral integration and Cas9, rather than against\n",
    "  empty wells that received none. But, as the section above showed, non-targeting is not identical to empty, so\n",
    "  state which baseline you used.\n",
    "- **Cutting toxicity needs safe-targeting guides.** The gold standard for separating Cas9 *cutting* toxicity from\n",
    "  the biology is safe-targeting guides, which cut at non-genic loci and so carry the double-strand-break burden\n",
    "  without knocking out a gene ({cite:p}`Morgens_2017`; {cite:p}`Alvarez_2022`). This screen's control pool has\n",
    "  none, so cutting toxicity cannot be isolated here, and the empty-versus-non-targeting contrast measures delivery and\n",
    "  expression, not the cut.\n",
    "\n",
    "For this notebook the sphering above used both negative controls pooled; whole-plate normalization is an\n",
    "alternative that needs no baseline choice, and the comparison here shows how far the two diverge on these data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c004",
   "metadata": {},
   "source": [
    "## Which knockouts have a phenotype?\n",
    "\n",
    "Two questions, both answered with mAP. Does a gene's knockout stand apart from the negative controls on its own\n",
    "plates (`mode=\"activity\"`)? And do its wells find each other among all the other knockouts\n",
    "(`mode=\"replicability\"`)?\n",
    "\n",
    "With nearly 8,000 genes the permutation null has to be large. `tl.map` cannot return a p-value below one over\n",
    "the number of draws plus one, and a correction over nearly 8,000 groups at 5% needs about 160,000 draws before a\n",
    "single gene can be called on its own."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c005",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:30:27.662129Z",
     "iopub.status.busy": "2026-10-21T00:30:27.661580Z",
     "iopub.status.idle": "2026-10-21T00:31:42.339040Z",
     "shell.execute_reply": "2026-10-21T00:31:42.337688Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>genes scored</th>\n",
       "      <th>called at q &lt; 0.05</th>\n",
       "      <th>mean mAP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>activity</th>\n",
       "      <td>7971.0</td>\n",
       "      <td>4715.0</td>\n",
       "      <td>0.553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>replicability</th>\n",
       "      <td>7971.0</td>\n",
       "      <td>1175.0</td>\n",
       "      <td>0.107</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               genes scored  called at q < 0.05  mean mAP\n",
       "activity             7971.0              4715.0     0.553\n",
       "replicability        7971.0              1175.0     0.107"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genes_screened = set(treated[\"Metadata_Perturbation\"].astype(str))\n",
    "rows = {}\n",
    "for mode in (\"activity\", \"replicability\"):\n",
    "    mt.tl.map(wells, mode=mode, null_size=200_000, key_added=mode)\n",
    "    table = wells.uns[\"mantispy\"][mode]\n",
    "    table = table[table[\"Metadata_Perturbation\"].astype(str).isin(genes_screened)]\n",
    "    rows[mode] = {\n",
    "        \"genes scored\": len(table),\n",
    "        \"called at q < 0.05\": int(table[\"is_significant\"].sum()),\n",
    "        \"mean mAP\": round(float(table[\"score\"].mean()), 3),\n",
    "    }\n",
    "pd.DataFrame(rows).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "792d4c04",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:31:42.343341Z",
     "iopub.status.busy": "2026-10-21T00:31:42.343180Z",
     "iopub.status.idle": "2026-10-21T00:31:42.487616Z",
     "shell.execute_reply": "2026-10-21T00:31:42.486489Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nf8KPfvQjbNiwAbquY+vWrfj5z3+OYDCIww47bMbzvv/978fo6CiuueYa5HI5bNiwAaeffjqOPPLIOds0m5tvvhnJZBLvf//78fe//x2qqmJ4eBh//OMf8Z73vGfa2oFnnnkGv/nNb5DL5fDUU0/h3HPPxQEHHIDzzjtv3u994403QtM0vOc978H69euhqipeffVVXHLJJXjmmWcgiiJOPfVU3HHHHXjssceQz+dx33334corr8TRRx9d85yNtm++12Gq7373uxgeHsYnP/lJbN26FfF4HNdeey3uueceXHXVVQiHw/O+NvW2Jx6Pg+M4fPSjH63rvPVcn925FvXq7+/HY489hlgshmOPPRbPP/98Q+ep99rP9btWb/vOPPNMHH744bj44otx//33I5fL4ZFHHsF5552HNWvW4MILLwTKN1Af//jH8ZOf/ASPPPIIcrkcfvvb3+Lxxx+fdiPr9/vR39+Phx56aM/M29Lq1YX7ottvv50BYPfcc8+MxwwMDDAA7POf//yMx0yu3P75z3/OfvKTn7ClS5cyWZbZYYcdxv74xz/OeOyuotEoO//886ueMwyD3XDDDezQQw9lLpeLhUIhdvTRR7N/+7d/q6ySne85JyYm2Kc//WnW3d3NRFFkvb297HOf+xxLp9NVx/3+979nBx10EJMkiQFgX/ziF6ed/0Mf+hADwL70pS/t1nWp97POxrIs1t3dzQCwL3/5y9O+v3HjRvb5z3+erV69mrlcLtbT08M+/vGPs5dffnnOc998881sxYoVzOVysbVr17L//u//ZnfccQcDwF5//fUZXzfbz4YxxrZt28YuuOAC1tfXxyRJYr29vey0005jf/rTnyrHTK54zmaz7Oyzz2bBYJD5/X52xhlnsKGhoarz1buqn5V3fXziE59g7e3tzOVysUMOOYT9+Mc/rqyknpiYYGeddRaLxWLM7/ez97znPWzTpk3sxBNPZEccccSCta/e6zCTxx57jJ100knM5/MxRVHYYYcdxu68886qY3bdLjbpT3/6EwPAHnrooXm3Z+vWrQwA+9znPjdr++Zzfep975k+z1xtmCqdTrNjjz2WBYNB9uijjzZ0neq59qyO37V625dKpdjnPvc51tvby0RRZN3d3ezTn/40i8fjVa9NJBLsYx/7GPP5fCwUCrELLriAqao6bVU/K+8KOPjgg5ksywxAQ1s2FwsF/j3YXH/c92XnnHPOjMFvf74uC2m+f+RJc9x5551MURQ2MDAw63H08yONoqF+ssfRdR2//e1vceyxx+LAAw9sdXMIaaoHHngAF198Mfr6+lrdFLKPElvdAEKmMk0T3/3ud5HJZPC1r32t1c0hpOl+9rOftboJZB9HPX6yx7jzzjshyzJuueUWXH/99bMujiSEENIYju1tmQcIIYQQ0jDq8RNCCCH7EQr8hBBCyH5kv1zc5zgOhoeH4ff760pHSwghhOzJGGPI5XLo7u6upMGeyX4Z+IeHh2mrDCGEkH3Ojh070NvbO+sx+2Xgn8zjvmPHjkp1KEIIIWRvlc1m0dfXV1f9lv0y8E8O7wcCAQr8MzBNE6lUCuFweN6VugghhLRGPdPXtLiP1DQyMoKrrroKIyMjrW4KIYSQBUSBnxBCCNmPUOAnhBBC9iMU+AkhhJD9CAV+QgghZD+yX+bqz2azCAaDyGQytKqfEELIXm8+cY16/IQQQsh+hAI/qWl0dBTXX389RkdHW90UQgghC4gCP6nJMAxs3boVhmG0uimEEEIWEAV+QgghZD9CgZ8QQgjZj7Q08OdyOdx666049NBD4XK58Oijj9b1uh/96EdYvXo1QqEQjj32WDz99NOL3lZCCCFkX9DSwH/dddfh+eefx7e//W3oug7HceZ8zc9+9jN84QtfwLXXXotXX30Vhx9+OE4++WQMDQ01pc37i2g0ik996lOIRqOtbgohhJAFtEfs4x8cHERfXx8eeughHH/88bMeu3btWhx//PG45ZZbAACO46C3txef+tSncO2119b1frSPnxBCyL5kPnFtryrLm0ql8Nprr+Hqq6+uPMfzPE444QQ88cQTLW3bviaXy+GZZ57BkUceWVd9Z0IIIfU57qr/gjXl6yeu+aemvv9etbhvskRse3t71fPt7e2z7jfXdR3ZbLbqH5ldKpXCL37xC6RSqVY3hRBC9ilWHccspr0q8E/ieX7a17PNWFx33XUIBoOVf319fU1oJSGEELLn2asCf0dHBwBgYmKi6vnx8fHK92q54oorkMlkKv927Nix6G0lhBBCarn9on+sPP7IiubPuO9VgT8ajWLVqlV45JFHKs8xxvDII4/g7W9/+4yvUxQFgUCg6h8hhBDSCv/+52fBlR//LSE3/f33+MB/8cUX44gjjqh8/S//8i+4/fbb8cADD0BVVXzrW99CPB7HRRdd1NJ27msURcFBBx0ERVFa3RRCCNmnDMRzAAAOQLqgN/39Wxr4f/7zn8PlcmHlypUAgHe/+91wuVz49re/XTnGNE3o+s4Lc/HFF+OKK67AJz7xCQQCAfz617/GH/7wByxfvrwln2Ff1dHRgUsvvXTWKRRCCCHzd9iyNjAADEBPxNf092/pPn7btmGa5rTnRVGEKJbmPSzLguM4kOXpwyGO40xb6FcP2sc/N8dxoOs6FEVp6BoTQgip7Tu/eQKPvjwABwxvWdqJG87+h90+53ziWkv/oguCAJfLNe3fZNBH+SagVtBHjdX9ZOEMDg7isssuw+DgYKubQggh+5SRpArNZtDt0uNm26sS+BBCCCF7u6BXgSTwYAzweWhxHyGEELJPW9oWhEeR4VZELIk1f7qZevyEEEJIE8UCHkgiD9vm0BZwN/39qcdPCCGENNH6DcNI5jSkC0X8feNw09+fevykpp6eHtxwww3weDytbgohhOxTJvJFTO6ny2nTd7YtNurxk5oEQYDf74cgCK1uCiGE7FOWxALgOABg6Ag0v3NFgZ/UNDExgVtuuWVaXQRCCCG7x+OS4ZEFeGQRXlrVT/YUmqbhpZdegqZprW4KIYTsU9SiDotxsACoutH096c5fkIIIaSJgh4X3LII22YIeppfD4V6/IQQQsgCYYwhlS8ip83ck1/eFoRfkeB3S1jaFmxq+0A9fkIIIWThDMRzSORLU6TL2oMIe13TjilYNkRBAMdsGKbT9DZSj5/UFAqF8NGPfhShUKjVTSGEkL2GZlg1H0+VzBXAgYHneKQLxSa2roQCP6kpEAjg5JNPpuqFhBAyD50hDwSeg0sSEPXVzsrXHwsBfGlaoCfib3obaaif1KSqKt544w0ceOCB8Hq9rW4OIYTs8ZJ5DabtYG1vDKIwc7/atm3YDuAwBtumoX6yh0gkEviP//gPJBKJVjeFEEL2eImchm0TWQwl8xiIZ2c9dkcyB8cpBfzBZK5JLdyJevyEEELIbjIse8rj2Xvx7UEPZFGAzRhiLcjcR4GfEEII2U1tAQ9U3YRpOeiN+mY9dmVHCMs7grAthoN6ok1r4yQK/IQQQshuEgUeKzvDdR2rFk0Mp/JwbIZMQV/0tu2K5vhJTZIkoa+vD5IktbophBCyT1m/eRTjGQ3xfBFPbxpp+vtTj5/U1NXVha9//eutbgYhhOxzLNuBbtpgjMGiVf2EEELIvi3qd0PgOHAcEPFTrn6yhxgYGMAll1yCgYGBVjeFEEL2KQ6zIQk8JJ6Hw5r//jTUT2ZkWbXTTRJCCGlcRjWgmRYYY0irzV/cR4GfEEIIaSKB5+GSBDiMQRaFpr8/BX5CCCGkidoCHpiOA8cBQp7mz/FT4CeEEEIWkO044MCB57ma3zdtG32RABgYBL75S+1ocR+pqbOzE9/85jfR2dnZ6qYQQsheI57T8NL2CbyyIz5jWd5lHSEYto2iYaE31vzqfBT4SU2yLKO7uxuyLLe6KYQQsteYyBbAAFiOg5RarHlMIq/BNB2YtoN0njL3kT1EIpHAz372M6rORwgh8+B3lzpLHACfq3bHaUciB5sxABwGE7NX8lsMFPhJTaqq4oknnoCqqq1uCiGE7DV6I34c0BXGmp4oAu7agf/A7igiPgVhn4IDe2JNbyMt7iOEEEIW0K49fct2MJzKg+OArpAPxx/UB79Lgm45OGpF89dRUeAnhBBCFtFQModEfud8f5vfg0SuCMO2YVo2oDS3GBoFfkIIIaSJ7n9pGx56ZTscANmCgXOOX9fU96fAT2ry+/045ZRT4Pc3f6sJIYTsS3oifgBcZaj/d/GNGM9qAICt45mmt4cCP6kpHA7jQx/6UKubQQghezXLdpAuFGFaNnieg2k76An7YdqDsByG7rCv6W2iwE9qKhaL2L59O5YsWQKXy9Xq5hBCyF5pw0gSI2kViZyGJbEgTNtBvqgDHAeB45DRaB8/2UOMj4/jBz/4AcbHx1vdFEII2SvZjoOiaYPnODAGmJYNjuOQ1UxIAg9Z5KHpza+CSj1+QgghpEG242AgnoNh2eiJ+Kq28gk8j86QFxwAtySiM+RFV9iHrrAHtsPgOAztweaPqFLgJ4QQQhqUyBUrqXkH4lkc1FudkKc77Js2jy8JAjqDPjBmw92CtOgU+AkhhJAGScLOGXNREOp6TcTngkcR4DAeIS+V5SV7CEEQEAqFINT5i0wIIfujsM8FmzEYlo02v7uu14gCj4ymw7YdSGLzl9pR4Cc19fT04Lvf/W6rm0EIIXu8WJ0Bf9LfNoxgKJGHA4Yn3hjCew5bsWhtq4UCPyGEENJEyZwG3bDBwJDMaU1/f9rOR2oaGhrCV77yFQwNDbW6KYQQssczLBuvDyXw0vYJZAqz780/sDeCoE9G0KNgTV+0aW2cRD1+UpNt20in07Btu9VNIYSQPV4ip0EzSnvyh1N5BD0zL9p715o+pFQdpuXgpHVLm9jKEgr8hBBCyG5yyTvDqUeePbTKoohDl7aDMQa/h7bzEUIIIXudsNcFoZOHZdsIeWZPypMpFLFxJAXHYfDKMvqigaa1ExT4CSGEkIURcNfXe986nsLjbwyBMQeKJOCw5R2L3rapKPCTmtrb2/GFL3wB7e3trW4KIYQ0ne04SOaLUCSx7oBerxe2lRYA8uDw+lBiQc9dDwr8pCaXy4XVq1e3uhmEENIS2yeySJdX56/oCM26WG8+MgUdatFEXjMAACLf/M11tJ2P1JRKpfCb3/wGqVSq1U0hhJCmm1yhDwBFc+Eq6BV0EyLPQeR5CDwHWWp+dlQK/KSmXC6HP//5z8jlcq1uCiGENF1PxAdZ4OFTJER988vMN5uIzw2XJEKRBfhcMpQWpEWnoX5CCCFkFyGvCyHvwpTMVYsmtoynwQFY1hHCocs7sWk8A9tx0LlL5b5moMBPCCGELKKxjArTdgAAE5kCXJKIZe1BMMYQbME+fhrqJ4QQQhaRR5Eqj92KiLBHRtGwkC+aCLipLC/ZQ3i9Xrzzne+E1+ttdVMIIWSv1hnywiUJ4DgOQY+C57eOIa3qsB2GHcnmr6OiwE9qikajOPvss1vdDEII2etkCjo0w0LE54IslhbvTV0vsCOew0haBQBsH880vX001E9qMgwDw8PDMAyj1U0hhJC9Rr5oYPNYGsOpPDaPpmseo1smdNOCZpowFnCrYL0o8JOaRkdHcfXVV2N0dLTVTSGEkL2GaTmVx7q1s7opY6zyWOB4SAIPSRDACc0PwzTUTwghhCyQoEdB2OuCZpjoCpW26uU0o7ydj8OKjhC6wj60+T2wmIOeiL/pbaTATwghhCwQnuewrD0Iy3aQLxowLBsT2QJshwFgmMgW0Bvxg+d5cA5DX6T5+/hpqJ8QQghZQI7DsGEkiS3jGbw5nIQi7szO53VJ2DyWhunYcByGTTOsA1hMLe/xP/roo7jlllswNjaGgw8+GF/72tfQ1dU14/GWZeHOO+/EH//4R6RSKfT39+PCCy/EMccc09R27w9EseW/HoQQslcxLRuDiRyGUyrCXgWm7SDkdcHvUcAB8LtlpAs6TNuBwHFQ9f1scd9DDz2EE088EatWrcKXvvQlbNy4Ee985ztnzQ//5S9/GVdccQVOO+00fOMb30BnZyeOP/54PPTQQ01t+76uv78ft9xyC/r7+1vdFEII2Wtsj2eRKugwLBuZgo6AW4ZHESHwHASeA2MMXREvQh4FPreEo1Z0NL2NHJu61LDJ3vnOd6Kvrw+/+MUvAACFQgFdXV34xje+gS9+8Ys1X7N8+XKceeaZuOaaayrPrVu3Du9+97vxgx/8oK73zWazCAaDyGQyCAQCC/RpCCGE7O82DCeR100AQFfIi66wDxPZAnYkSh3avqgfW8fS2DiahmU7ePchS9G1APn65xPXWtbjLxQKeOqpp3DaaadVnvN4PDjppJPw17/+dcbXHXnkkVi/fj1Ms3RhBwYGsGPHDhx99NFNaff+YmRkBN/+9rcxMjLS6qYQQsheoy8WQNCtIOpzoz3oAcqr+iepRRM+twy3LKI95IExZctfs7Qs8O/YsQOO46C7u7vq+e7ubmzfvn3G191xxx0IhULo6enBoYceire85S343ve+h49//OMzvkbXdWSz2ap/ZHamaWLHjh2VGyxCCCFzc8siVnSGsKQtAIEvhdio3w2e48BzHCJ+dynoB9yIel2V4j3N1LLVW5MBRVGqCxS43e5Zg80tt9yChx56CNdeey1WrFiB++67D1dccQWOOOIIHHnkkTVfc9111+Hqq69e4E9ACCGEzC3oUXBwfwwAYDsMQ8k8Xtg+AUUS8J5Dlze9PS3r8UciEQBAMpmsej6RSCAajdZ8TS6Xw9e//nVce+21uPDCC/EP//APuP766/GOd7wD3/jGN2Z8ryuuuAKZTKbyb8eOHQv8aQghhJCZCTwPgeeh6iaS+SKSeQ1DiRxG0vmmt6Vlgb+7uxudnZ1Yv3591fN///vfcdhhh9V8TT6fh2ma6OnpmXauXW8gplIUBYFAoOofIYQQ0kzxnIaMqmMwkcNQMo9ErojXBhNNb0dLt/Odd955uO222zA0NAQA+PWvf43XXnsN5513XuWY6667DmeeeSYAoKurCytXrsRPfvIT6LoOANi2bRt+97vf4dhjj23Rp9g3RaNR/PM///OMoy+EEELql1aLGIhnkVSLABwwxqCbdksW97U0Q8s3vvENbNy4EStXrkRfXx8GBwfx7//+7zjqqKMqx2zevBkvvvhi5etf/vKXOPvss9Hd3Y2enh5s3LgR73vf+/Ctb32rRZ9i3+T1enHEEUe0uhmEELJPKKXsLWEOoOoWHIehFfvpWxr4FUXBr371KwwPD2NsbAwrV66E319dsOBrX/sa8vmdcyCHH344Xn75ZQwNDSGRSKC/vx/hcLgFrd+3ZbNZ/P3vf8db3/pWmhohhJDdFPG5UDBMaIaNgmFB1Utb/LaMpZrelj0iJ2t3d/e0bX2Tli+fvuKR4zj09vait7e3Ca3bP6XTadxzzz1YvXo1BX5CCNlNHMehL1r6WyqJPGRBAGMMotD8MExFegghhJBFZFo2to1nsG08A8t2sLIzBAbAZgxLos2vzrdH9PgJIYSQPZlp2eA4DqIw//7yUDJfXtRXKtur6hb8bhmmZUPf3xb3EUIIIXu6RE7DQDwLjuOwvCOEgFuufG8iW4Bu2egIeCCVy+8WDQtDyTxEgUNv1A+O4yrH8xyHZL4Iw7TBACTzxaZ/Hgr8pCa32423vOUtcLvdrW4KIYS0VDJfBAPAGEMqX6wE/nhOqxTf0XQLq7pKC813JHLIFUuL92RRQE/EB4HnAK5UuGdJzI+X3Qoc2FjaHmz656HAT2pqa2vDJZdc0upmEEJIy4W8CnJFA1z58STb2Zln35ryWOCn9PD50vRAb3TnjrUVHWGs7k7DtB2s6Yk15TNMRYGf1GTbNgqFAjweDwRBaHVzCCGkZdoCHvhdMjiOgyLt/HsY87tRNCzoloOeyM5Fen1RP2RRgCjwaA94pp3PsEo3CQLPwzCtJn2KnWhVP6lpaGgIl19+eSWrIiGE7M9cslgV9FEO3EvagjigKwyvIlWel8rD+4wxbJvIoqBXF56byGvQDBtF08JYptC0zzCJAj8hhBCywNKqjpG0ipRaxLaJTNX3PKIAlGcD3FNuGJqFhvoJIYSQBTZbMt6o34OY3wXbYTWnAhYbBX5CCCFkN+mmhS3jGdgOw9K2AMJeF3TTRtG00RGsDu4Wc2BYNhwHsGxnxnMuFgr8hBBCyG4azxagGaWFeiMpFau6wugK187Kl8kXkcoXYTkMybzW5JZS4Ccz6O3txY033ghFUeo4mhBC9m8uaWc4dcnViwAt28FoWq3s4982kcEbQ0kwACGPglMOm16TZjFR4Cc18TxPyXsIIaRObQEPRIGH4zBEfK6q7w0l80hM9uwZkC3qpWMZKqMEzUSr+klNY2Nj+OEPf4ixsbFWN4UQQvZYjsMwmMhh82gaiigg6ndXpehFOeNf5XjGsKozAo8iwaOIWN5BmfvIHkLXdbz22mvQdb3VTSGEkD1WIq9hPFvai2/YNtb0RKcd0xPxgaG0g6877INp2ThyZSeYw3BA9/TjFxsFfkIIIaRBuxbgqUUSBSybkpNfEgWs7orAYU5V4p9mocBPCCGENCjqc8GyHeimjc5QfXvy3bKAjSMpWLaD3oi/jlcsLAr8hBBCSIM4jkNnyDvncQXdBMdxcMsito1nYToOGBi2jGWxtD3UlLZOosBPagqHw/j4xz+OcDjc6qYQQshebSJbqJTvXdoWgKpb2DaWhsMYor7m756iwE9q8vv9OOGEE1rdDEII2evlNKPyOFswoBkmMpoBx2FQi8asr10MtJ2P1KSqKp566imoqtrqphBCyF4t4nOB5zjwHIeIzwXLcRD2uhDxu1Cp1tNEFPhJTYlEAnfccQcSiUSrm0IIIYvCdhxsn8hi02hqXol0CrqJVwYm8PLABPJ19NhDXhfW9cVwcH8MAY+Cg/tjiPhdCHkUvGVJ225+ivmjoX5CCCH7pXhOq2TUs+NZrO6O1PW6iWwBRrm4znimAJ9LnvM1orCzny0LArpCXliWA6+LtvMRQgghTcHXsQe/Fo8iIZEvAgDc8vzD6GuDSbywdQIAgywJWNnZ3EXUFPgJIYTsl2J+N2yHwbRtdATn3pI3qS3ggSIKcBhDyOuq4xXVXh2cwMbRVPlctKqf7CFkWcayZcsgy3MPYRFCyN6o3j34tQQ89Vcu1QwL2yYy4MChP+aDWjTAcQy2AxRNu6H33x0U+ElNnZ2d+OpXv9rqZhBCyF4lpRaxfSILSeCxsjMERRIxkspXFg9OZDV0hX14bSgJzmHoCjc/cx+t6ieEEEJmYFg2UmoRVnkx31xG0yocxpAt6BhJlbZDy5JQ+b4sCugIuCFyHASBB8+xWc62OCjwk5oGBgZw0UUXYWBgoNVNIYSQlrBsB28OJ7F1PIM3h5NwHFZ5Xjdrb//zKhKS+SIGEjnsSGSR1Qz0hH3oi/rRHwugM+RFPF+ER5HgViSk1OZXQKWhfkIIIaQG3bJhlnv6k49t08GGkRQcxtAV8qIr7Kt6TV/Uj7FMAZLAwyWJyGo6Am4ZbYGdBXy6Qn44GIbjAB3B+gr7LCTq8RNCCCE1eGQRQXdpEV/E64IiCchqBhxW6vmn1OK013Ach4BbwmhaxfZ4FrIgTDvG5xLhkSW4ZQF+2sdPCCGE7Bk4jsOKzhAYY+DK+/z9bhl8moPDGMIzbuUr7RYQBQ6GPX3V/mimAEUSwRjDWFZb5E8xHQV+QgghZIp80cB4pgCvS0JH0FsJ+ijP4a/ri8GyHbhmSN5TNC2MplVwAJbEgtO+3xvxY0sgA+Yw9EcDi/pZaqHAT2rq6urCNddcQ2V5CSH7nc1jadgOQ7qgwy1LCLir85mIAl+VgndXLklEf9QPnudr1uA5fHkHPC4JlulgTV90MT7CrGiOn9QkSRLa29shSc2ffyKEkFbidqNi3mAyh9G0ikS+CJckIFJjOqCgW3h9RxyvDiWQrrFOYLFR4Cc1xeNx3H777YjH461uCiGELCrHYRhNqxhNq7AdB8s7ggh7XeiN+Kf19mdj2Q7GMwX43TI6Qx4sbQvCo+zsPDkOg2nZuO/FLbj/5e146NUB/O/f31ykTzUzGuonNRUKBTz99NM4+eSTW90UQghZVCNpFWOZUrId07bRFw3UVXFvVwLPQREF6JYNSRTgVnaGWMOysWEkBcOy8cpgAqlykZ/t8dwCfpL6UOAnhBCyX5ualc+yG8+kx3EcVndHkNV0eBUJsrhzK19OM2BYpRX+IY8LXpcEx3GwtG364r/FRkP9hBBC9mtdYS+CbgUBt4zuXRLyzJco8Ij43FCk6n61zyVB4EtrB1Z2huCSRciigOXtFPgJIYSQppJFASs6Q1jZGYYiTU+4sxAUScRBPVGs7opgNJVHsWjBsBw8v218Ud5vNjTUT2oKBoN43/veh2Cw+XejhBCyL5JEAZIoQNVNpNQiGIBsgXL1kz1EMBjEaaed1upmEELIPkcRBZi2A4cBstj8gXca6ic1aZqGV199FZrW/HSShBCyL9NNCx6XCK9L3K3FhI2ad+BPJBK499578fvf/x6JRGJxWkVabmJiAjfddBMmJiZa3RRCCJnTtvEMXtg2ju0T2VY3ZU5dET8UUYAsCOgIepv+/vMa6n/22WdxyimnVJK6RKNR/OUvf8ERRxyxWO0jhBBSVqoDb8OjiFX54/d3mmEhWc6Al8hr6Ax5pq2qb4VMQYdmWIj53VUpfjuCXhzQFYHtMPS2NT9X/7x6/FdccQWOPfZYbNiwARs2bMAxxxyDK664YvFaRwghBABgWjbeGErgzZEkNo2mW92cPYok8JDKgVWaI49+s2QLOjaPpTGcymPLWPXPqz3kRmfYh86wFz3hvaDH/8orr6CrqwsA8KMf/QhvectbFqtthBBCygqGBaOcaCZXNGA7DgS+9QFuTyAKPA7oiiBfNOB3y4t2XSzbQVbT4ZGlGSvzTdKtneV4Dau6NK9PkdER8oIxhoBbWZS2zmZegT+ZTFaCPgB0d3fTPP8+ShRFtLW1QRRbP1xGCCmVg3VJAoqmjbDXRUF/F4okQJHci/oeG0dT0AwLPMdhTU9k1umEiM+FnGagaFrTkgI5rJSz37Jt2I4z4zkWy7z/qr/yyitzPrdu3brdaxVpue7ubnz7299udTMIIWWiwOPA7ihM21m0JDNkZo7DoBlW6TErPZ4t8As8j+UdoZrfG06qlUWIIW8Wa3pji9Tq2uYd+A8++OA5n2Os+dsTCCFkX8fzHBS+uUGfMYZkvgie5xCuUWJ2f8HzHLpCXoxlCvAqEgJuBZbtYONoCgDDqs5I3WsLOA4IeRWAAZLQ/Ju4eQX+9evXL15LyB5lcHAQ//Zv/4Z/+Zd/QW9vb6ubQwhpkaFUHuOZAgDAjDhoD3pa3aQFo5s2TNuG45RubnxuGTH/zNMFXWEfuqYM2z+/Zayy0FLTbRy+vKOu9+2LBfHywAQsh6E/1vxV/fMK/EceeeTitYTsURzHQT6fh9OC+SdCyJ5DN3YuTJsc6t4XFHQTG0ZSsB0HE1kN7UEPkmoRbkmE1yXVdQ5N33k9CoY567GTI+Ecx8F2bByypB2tGhtfsNUhlmXh97//PT7wgQ8s1CkJIYS0WGfIC0UU4JZEdOxDvX1VN+EwBrDSTcAkNks4dpzq763rjyHqdyHmd2Nd38zz9FnNwIvbJ/DSwATyRQMuSYRQ3nbonmN3wGLY7XfctGkTbr/9dtx1111IJpM48cQTF6ZlhBBCgPI2MtN2WhIkvC4Ja2cJanurgFuBLKgw4ODgvhgEga8M+TMG+N1y5VjbcbBpNI14TkNbwI0DuiIAgJDXhZMOXjrne8WzhcpNRjyrYWl7EDmttCWzK7SH7+OfpGkafv3rX+P222/HY489Btu28T//8z845ZRT4PPtXi1jQgghOxUNCxtGUrAcBzG/uyVzwvsi23EQ83vgd8vwuiTopoXXBhNgRSCZL2JdX6yyWC9fNDGYyCGe0zCYyCHkUdA+j1S7XpeEdLkKn9clYTiZw+tDSTDGwHEcVnaGF+1z1jKvof7nn38el1xyCbq7u/HVr34Vxx57LLZs2QIA+OhHP0pBfx/S3t6OL3/5y2hvb291UwjZr+WKBqzyWpu02vwSrvsiw7KxYSSF4XQeW8bTcBwGp9QhB8rz8VN3p7llsZKQRxGFea91KKXoDWN1VwRtAQ8G4jm8sG0Uz28dxcbh5IJ+tnrMq8d/+OGH48gjj8Rdd92F9773vRBasA2BNIfL5cKKFSta3QxC9nsBtwyR52E5DsK+5md52xeZllMaei8vWDQsC25ZQm/Ej0xBR9TvgiTujG+yKODI5Z3YMJKEV5EQnWXl/1SJrIaCYaIj5IXPtXPqYDCZw0hKBWPAQLz5RYXmFfjf/va34+9//ztuvfVW2LaN0047jTK77aNSqRTuv/9+nHzyyQiHmzsMRQjZSZFEHNQbhe04e0ThmX2B1yUh6nNj63gGpm1jw0gaB3SF0R70zLhdsT3oQczvBsehrgJJ45kCHnt9ByyHoSfiwzEH7twW7VFEBN0KHAD+FqTsnddQ/5NPPomXX34Za9aswUUXXYS+vj587WtfW7zWkZbJ5XJ44IEHkMvlWt0UQvZ7osBT0F9gS9oCiAXciPrdsBwHGW3uaRSe5+quiphSi7DKuwDiWa3qe8vbA7AZg2FZWDZDdr/FNO/tfAcddBC+//3vY3BwEDfddBOee+458DyPY489Ft///vexefPmxWkpIYQQsoCCntLwO89xVUPxC6E36kfQo0CRBKzqqg7uL22PYyiZx2iqgOe2jC7o+9aj4VtIWZZx+umn4/TTT8fAwADuuOMO3Hzzzbj88sspZS8hhJAKw7KhmzZ8LqnuHnMz9EUDiPjckAQesriwa9a8ioR/WNcPw7LhVaoTAr0yGMdIKg8GhlcG4gv6vvVYkAQ+/f39+OY3v4ktW7bgz3/+80KckhBCyD6gaJS2yW0cTWHreKbVzZnGq0gLHvQnyaIAn0uedrOjFkp7+B2HoWAYi/Les1nQSSOe5/GP//iP83rN0NAQfvazn2FsbAwHH3wwzjrrLMjy3EMu9913Hx588EF4PB6ceeaZtAJ9gfl8Phx33HG0RZMQslsqGfLKGewIEAuUsiEyMER8i1tKuJaGevzxeByf+9zncNhhh2Hp0qXT/tXrjTfewMEHH4y//e1vaGtrw//3//1/OOmkk2BZM++RtG0bp59+Os4991woigJFUXD66afj1VdfbeSjkBlEIhH80z/9EyKRSKubQsgeb+r0ZlotUoCbIuCWoZR71G2BvSfl72JOWa/rCyPscyHodmFtT/OzIjbU4z/33HMxODiIT37ykwiFGl+R+JWvfAWHHHIIfve734HjOHzqU5/CsmXLcPfdd+Pcc8+t+Zobb7wRf/nLX/Dyyy9jyZIlAIDPf/7zUFW14XaQ6QzDwOjoKDo7O+sagSFkf6TqJjaPpuEwhuXtQeR1E6Pp0t+ivqh/rwp0i0UShfJ2RFZ32dpWS+Y1bJ/IQhJ4rOoKT9tRkdNKSZVCHqWhNQu5og2e58FxDOocxX0WQ0OB/6GHHsKGDRvQ09PT8Bubpok///nPuPnmmysXrru7GyeccAJ+//vfzxj4f/zjH+PMM8+sBH0AcLvdcLubP1yyLxsdHcW1116LK6+8Ev39/a1uDiF7pHhWq2TVG88Wqr5X0PedSna7i+M4iMKes6hvJo7DkC4UsXU8A47jYNgOkvliVSneZF7DtolS0p32gAddYS8G4jnopo2eiK8qx/+uGGPIaQZU3YTfJYOBwbSbXwG1ocAfjUbB87t357Z9+3YYhoFly5ZVPb9s2TI88cQTNV+TyWSwefNmfPOb38Tdd9+NZ599Ft3d3TjjjDOqbgR2pes6dH3nHs1stvmZkggh+x6fS0IiX9qj7VUk+FwyCroFngPaAtQZ2dtsm8ggXdAxkdXgc0nwKtK0FflTb+gKuolEroiUWgQA7EhkcVBvaeg+qxkQeQ6eKa8fiGeRyBcR8ijojnjBcxyOWtHZtM83qaHo/fnPfx6XXXYZUqlUw2+saaX/LH6/v+r5QCCAQqFQ8zWTyWSuvfZa/OY3v0FfXx+eeeYZrFmzBo899tiM73XdddchGAxW/vX19TXcbkIImRT1u3FAVxgrO8PoCpd6e29Z0oZ1/W1Vf/DJ3mEyB39bwI3OkBeruyMIeKoz68X8biiiAIHn0BHyQpoyfSGW09gPJnPYNJrCG8NJpMs3BQCQK5aG9Zd0BHH0yi6csLYfb13V3aRPt1NDPf73ve99+M53voNoNIpwODxtjiMen3tfYiBQqjCVTqernk+lUpXvzfSa/v5+/PrXv648//73vx9XXXUVHn744Zqvu+KKK/CFL3yh8nU2m6XgTwhZEAud+IW0TlfYix2JHBRRwpJYoCpf/ySXLE4rU+wwBsOyESvn8FeLO+ft87oJjuPwwrZx5DQdYa8LRdNGIldEIldE1OfGgb3RJny6nRoK/Oeccw4OOOAAnHvuuQ0v7uvr64Pf78drr72GU045pfL8a6+9hrVr19Z8TSAQQF9fHw499NCq5w855BDcfffdM77X5Op/Uj+O4+ByufaoZBuEELKYIj53Q9vrdi3a0x7wYHs8C4HnEPW58cLWMWybyIADh1jAA72g48Xt42AMYAx7R+B/8cUXsX37dnR0dDT8xjzP44wzzsAdd9yBT3/60/B4PHj22Wfx5JNP4oorrqgcd/fdd2Pr1q246qqrAABnnnkm/vKXv8A0TUiSBNu2cf/99+OII45ouC1kur6+Pvzwhz9sdTMIIaQuatHEWEaFSxbRFfK2tNMS9rkQ9CiVgj45zazk6++P+aDqBrTyWoF8C7Z+NjTH39/fP+te+3pdd911YIzhsMMOwxlnnIGTTjoJF154Id773vdWjnn44Yfxy1/+svL1lVdeCZ/Ph4MPPhhnn302Dj74YKTTafzgBz/Y7fYQQgjZO20tL8wbTatIq3MX3FlsUwv69MX86I340Rf1ozvsx5K2INpDHsQCbizvbH6RnoZ6/P/8z/+Mz3zmM7j11lvR1dXV8Ju3tbXhueeew1//+leMjY3hK1/5yrSe+1lnnYV3v/vdla99Ph8efvhhPPLII9i+fTvOPfdcHHvssZAkWkizkIaHh/Ef//Ef+Od//md0dzd/8QkhhMzH1P79QnX280UDumkj7HWB5xs/aU/UD92ywXFAd8QHWRIQcEuwHaAj2PzdHw0F/m9961tQVRW///3v4fF4pg2p5PP5us8lyzLe8573zPj94447btpzPM/jhBNOmGeryXxYloWRkZEFGdkhhJDFtrwjhPHyUH/I66o8n1aL2DaRhSjwWNUZqru8cVYzsGm0tHNtLK2iPeRFyKM0lIQo4JZxyJI2oLx+6u8bhzEQz8O2HWwaTeOQpY1PmzeiocA/20I6QgghpNncsoglbcFpz4+mC5VV9/FcET2R+uqPaOWMeoZlY9tEBkXLxoQkYk15IZ5p2VB1Ez6XXNfNwNQO8utDCWweTcFhQMAj4yNvWz2PT7r7Ggr8H/zgBxe+JYQQQsgC87pEFMpB3KPUH/IiXhdSeR2aYSLqK40gFE0LjDHYDsObw0kYtgNZFHBQT3ReUwG6YcEliWAMsKy9JHMfIYQQsjfojfjhL/fK55NzQRIFHNgTgeOEsXU8g7xuoCNY2i1gWBaMcqpdw7Jh2jYUfno4zRT0cl4AAcvag5WRgXeu6cVIugDbcfDONb0L+GnrQ4Gf1BSLxfCZz3wGsVjzK0cRQshC4Tiuas5/vniew4pdVt67ZREhj4J0oZSQZ6Z1A0PJHAzLhmHZSOQ1dAS9AIDDlnYip5kwLRvvosBP9hQejweHHHJIq5tBCCENsWwHPMfNawh+MJlDWtUR8bnQHZ55LQDHcVjeEQJjbNZ8AYooomja5cc7swCOZfIQBR4cgOGUigPczU0w19A+/h07dix8S8geJZPJ4E9/+hMymUyrm0IIIfMykS3g5YEJvLIjjoJeX9lbzbAwninAsGyMplXo5YA9m7mSBC1tD6Av6seKjlDVqMNEVsML28bx0sAEdiRydbVvITUU+JcuXYpTTjkFv/rVr6qq3pF9RyaTwW9/+1sK/ISQvU48p4EBsBwHqTqT+Yg8B74cyAWeg7Ab+/ZRLvHLcxzaAh4Ey4V+bMfB9oksdsRz8MoiAm4FbLfepTENBf6HH34YXV1dOO+889Dd3Y1LL70UL7744sK3jhBCyILLFw1MZAswrbl7tXujQHnonAPgd9e3oE8SBbT53cgW9HIO/cZDcjKv4cXt43h5oHrEYSKrIZHXIAocBhJZxHMawp7m15FpKPAfe+yxuOOOOzA6Oorvfe97eOaZZ3DooYfiiCOOwC233LJb5XoJIYQsHlU3sXEkhR2JHDaNpet4xd6nJ+LD6q4IDuqNIlBn4AeAdEFHwKPAYQzJKeV052siu3PEIakWoRZNvDIwgU2jKeimBbVoIepzoyvkhVrnVMRCaijwT/L5fDj//PPx2GOP4aabbsIrr7yCz372s+ju7sbFF1+MZDK5cC0lhBCy2wzTrgwv1zOPvbfyuqS6s/RNcsvilMeNp4Gf3DbIAfC7ZIxlVBi2A7csQhIEBD0KNMPCcDIP097L9vFv3boVd9xxB+68806kUimcddZZuOCCCzA+Po7rrrsOH/zgB/Hoo48uXGtJ07jdbhx++OFwu5ufR5oQsniCHgUhjwJVN9EZ8ra6OfOSLxrYMlZad7S8Izivffn1WNoWRLpQhCwKu3XunogPAbcMgefgUSQUdBPpgg6O49Ab9YExBq8iwWasJXP8Dafs/elPf4qHH34YRx11FK666ip84hOfgM+3c/vD8ccfj2i0uTWGycJpa2vDRRdd1OpmEEIWGM+XtqLtjSayGiyn1EMezxQWPPDzPIeIb2E6O1PXFnSFfXDLIjiOQ9CjYNt4thLwHWcv6fFfeumlOPPMM/HDH/4QBx98cM1jAoEArrnmmt1tH2kRy7KQy+Xg9/shipTugRDSeh5FREotPfa69q6KrFO387UFSvP7lsPQGaqvdsBCamiO/4wzzsBNN91UM+h/9rOfrTz+6le/unutIy0zPDyMr371qxgeHm51UwghBADQEfRiZWcYKzvDlSx4ewPGGFL5IlLlBYNuWQTPcxB5Ht551A9YKA0F/ltvvbXm84wx/OhHP9rdNhFCCFkktuNgIltAejdWrbdSwC3Pa6V+qzgOq2wJHEmreGVHHK/siGM0rWIomceW8Qy2jKexbSLb9LYt2K0GYwx/+9vf0N7evlCnJIQQssC2T2SRLpSS2ixrA8K+xvPYk9qSeQ3bJ7IQeB4rO0MYjOcwnMoDADyyiHhWg8BxEAQO8Wyh6e2bV+CfOte767wvYwyO4+DKK69cuNYRQghZUPqUpD36PprAp9V23cfvcUmQBB4cB3gVGb42Cc9vG4PtMCztCDa9ffMK/H/4wx8AAKeeemrl8SRJkrB06VKsWLFiYVtICCFkwfRE/NgRz0ISBcT8tF13KrVoYiiVg+0w9EcDDS8g9LlkqLqJtKpDFgV0hjxwHAaOA/pifkxkCjhyeSdEgUPE2/yfAccayEv4zDPP4Mgjj1ycFjVBNptFMBhEJpNBIBBodXP2SI7jwLZtCIIAnt+tPE+EELJHsGwHRdOCR5amVe3bkcjijaEkspqB3qgfIY+C1d2Rht9rRyKLwUQOiiTCLYnojnjBgUPAo+CZzaN4dUccHAecsLYPfbHd7/XPJ641NMe/Nwd9Uh+e5yngE0L2GYZl483hJEzbgd8lY1VXuOr7iVwRAs/Bsh1ouom23RwNcUsiMgUdhqXBcRy8NDABADhiWQdyRQOMMdgOg6pbu/U+jaj7LzvHcZUShJOPZ/pH9n5jY2P4/ve/j7GxsVY3hRBCdltBNyvpcXNFA45TPdgd9CgIeV3oDvuwrD2E/lip12xYNoZTeSTz2rzfsxQTgUR+5w6KsYwKy7IxmMxjNFNAMjf/8+6uunv8999/f83HZN+k6zo2bNhAZZcJIU3HGINmWFAkAcIsI4+6aWPreAaW42BpW2BaJr/JXrUo8JBFHkXTgsDx6Ax5pg31L20LoD3ogSIKEIWd77llLIOCUSqkI/A8gh4FtuNgNF0AYwydIW/V8ZNEgUdbwAMA8MgSEnkNHID+tgAGEzl4FBEAh1yx+UV66g78J510Us3HhBBCyELaPJZGVjMgiwIO7I7UDKwAMJEtVILycErFAV07A79p2dgwkoJu2Wjzu5FUi1BEATzHIeJzQS2aVYv3OI6DV5m+mM+yd+58mBwxGEmrGM+UtuHZDsOStulz6iGvC31RB7ppY21vDHY5Na9HkaAWLXSGvGCMIdqCBZaUi5UQQsgew3YcZDUDKA+zF3QTgRlq1iuSUHnsmvIYADKaUdmuOJJSIYo8OI5DVjPwykAc+XKRorW9sWm9/6n624IYTubhlgVEyml3p66JtxwHhmVDFoVpr53s8Zdes/PmJeZ3wavIsBwHHUHPtNcttroD/3zm7hvYKEAIIYRA4HmEPArSBR2KKMBToxc+qS3ggSjwsB1WCcqTvIoEnuPgMIZYwA2B55Au6HBLIlJqEemCjqJpIexzoTfin/E9Am4ZgZ7q1f1dIR9sm0G3bGQLOl4p6OgIetETqZ13P6sZ2DKWBscBKzpCKBgW+mJ+MMZQbEFp5Ibm+Mm+LxKJ4KyzzkIk0vh2FkIIacSy9iAMy4YkCLP2xgEg7K2dedAti1jTE4Vu2fC7JHAchyXl0r6Pvz4EjgMCbgW2vbM6nmHZGM8WoIhCVW99V6LAY2l7EBPZAlS9NNUwnlHhkgS4ZLEyZZDKF5ErGtANCw5jAAPiWQ1uWcTWsQwcxnDkis4Gr1LjGprjJ/s+n8+HY445ptXNIITshziOgyLt/ky0IglV0wEoJ9c5bm0fBuM58DyHrvDOXvq28Qzy+uRCvrlL9PpdcmVUIV3QweJZcABWd0eQ10088uoOOIzBJYnoi5VGFbwuCTnNgChycJxS0qBmozl+UlM+n8cLL7yAQw89FD5f88tGEkLIYnHLIlZ1h6c9b0/Z4mc7c09Zu2QRa3ujMCwHG0aSYAAYgKJpIZnTSr18AAwMy9uD4LlSAp+xjIqiURrizxWNBf1s9aB9/KSmZDKJn//850gmk61uCiFkP5crz5FPrqRfLP2xAHyKhKjPjWi5t5/VDLw8MIHXBuMoGtOT7UiiAK9LQk/ED74c/wbiOWiGCZckgAPQFfZi20QWW8YzyGoGIj43vIoIRRLQHtiDV/XTPn5CCCHNxhjD5rF0ZTjdo4jT9us3wnEYkmoRklDamw8ABcOEWk70YzkOZF7AaFqFaTswbWAiV0BftHY63PagB+1BD94YSpa3GHI4amUXOoMebJtSETGZ08DzHNSiWdoRMGWNQbPQPn5CCCF7PcYYcpqBgXgWlsOwtC2A0AwL/1DOpT+ZUW9pWwARnxtjmQJYuWphSi2iI+iFRxaRLw/Hu+W5i/a4ZaGSW8AtieB5Hn63XAn8freMrRMZgOMgCgLGMwWs6Yku0FWoT8Nz/JZl4d5778Xrr78OADjooIPwvve9b1q5XkIIIaRRHMdhRUcI8ZwGn0uq2dufHBXYMpZBQTfRG/VhNF2YNfBP3UanlefbfYqEpGWDK2fbA4CeiA9eRYLAczPmE5iqL1rKICgJfOX4mN+NommDBxD1u5Ev6nhxuwHLdrC2t7lBH40G/tdffx2nnXYahoeHK2V4N23ahL6+Ptx7771YvXr1QreTNJmiKDjggAOgKHP/ohNCyGLyu2X43TMP75t2KemPIglIqUUYlgOva/bw1hXyYiCehSgICHsVbB5Nw7RtdIe8CHiUSv4AjuMQ9s18A7ErnuemZeMbTqmYyJbWJwgCj7xmlmoFsNL6hWZrKPBfeOGFOPzww7F+/XqEw6WVkalUChdddBEuuOACPPbYYwvdTtJkHR0d+OIXv9jqZhBC9lMptYiJrIaAW0ZnyDvrsZLAV/bOexQRy9pCiPpnD9YBj4J1/W1gjGE4pSKjlYbieZ5HZ3j6TibLdsBxmLV2wEyKhoVkeVoh5FFQtGwE3KVOlWHtwXP8Uz3zzDPYvn17JegDQDgcxs0334ylS5cuZPtIiziOA9u2IQgCleclhDSV7TjYNp4BKyfc8bvkqrz6u+I4Dqs6w9BMC645CvtMlcxr2D6RRa5oQhZ5yKIAuUZdgFS+iG0Tmcq0w2yjD7U4zEFW08GhtOp/SSyA1wYTsGwHy9prLxZcTA39RV+yZAlyudy057PZLJYsWbIQ7SItNjg4iM9+9rMYHBxsdVMIIfsZDlxVxr6Zdonrpo2sViqxy/NceS6+/rA2uZjPq4jwKRK6wz4EPAoSOa2qbG88p4EBcBhDMl+E7TgYTOYwmMjBqmNVvigIWNoWxJK2AASeh2ZaWNMTwbq+WEtW9TcU+C+77DKceeaZePrpp2FZFizLwtNPP40zzzwTl1122cK3khBCyB7Psh28MZTEC9vGd2vPPc9zWNkRRszvxrL2YM18/UXDwutDCWwaTWHreKah9/GVRxF4jkN/LABZ5LFtIoMNI0lsGUtVjpvc7scBCHhkjKTy2DyaxraJDIaS+WnnHU7lsWk0VZm/7w574XfJCLhldIW9EHkeKVVHMl+E0ILcN3UP9e+avU1VVbz1rW+tDAM75ZKDr732Gj796U8vdDsJIYTs4dIFvbKVbSSdR/tuVJ7zuqRZh/cLhlnJjNdo9rveiB9BtwJR4OFRJAyn8ohnNaTUIsYzGrrCfnhdEtqDHvhcpaI/LlnEm8NJjKZVoHzzwHGl0YfuiA+mZVe+pxkWDu5vgyKJWNVVnSlQEng4PEPz+/vzCPx333334raEEELIXs0ti+DKaWtr1bZfSAG3ApckoGjasxbUmQ3HVW/Ri/ndsGwHIs8h6nMhVzQqNx9TRx28igS/WwZjDIyVpgIAYGAiW1Whb6ZMtjZj8CgSGGNoRa7bugP/Bz/4wcVtCSGEkL2aV5GwujsC3bQR8Ox+dr3ZiAKPNT1R2A6DWGNBXiNkUcDhyzswnMpD4LnKED8ATGQLyGkGon43+qJ+WLYDSeAR9bsxUu7hT+7174v6UdCtGUc8PJKIZF6DbTP0zpAJcDFxjLG5KxHsY7LZLILBIDKZDAKB5l/0vYFlWcjlcvD7/ZSUiRCyXzEsGwLPVRYKqrqJN4eTMK1SKt813VEMJLJAOeufYTkwrNLIw9RqgIZlw7BseBWpqvc/EM9iJJWHw0qjDLtOAzRiPnGt4b/o9913H+655x4MDAzAsqoLF/z1r39t9LRkDyGKYtV2TUII2V/IYnUpXw6AYdqVYG+aDgLe0ohGIlfEis7QtHMUdBMbRlJwGEPU58KStmDV+bZNZGA7DGFv85OkNTQ+ctttt+H0008Hz/P4y1/+gnXr1qFQKOCBBx5AT0/PwreSNN3ExAR+8pOfYGJiotVNIYSQlvIoEmIBN7zlLX/8lPuCmaY0VH3n4sPsLtn5Jr/HWOlxszUU+H/wgx/gV7/6FW699VYAwI033ognn3wS3/jGN6Cq6kK3kbSApml47rnnoGlaq5tCCCGzSqlFjGXUuvbUN2ppW7CytXB5ewj9UT9WtAdnXFgYcCuVZEAxvxumZcO0SjUBLNtBIqshnivAnFIzoFkaGurftGkTjjvuOACALMtQVRVerxeXXnopli9fvtBtJIQQQmpK5YulancA8ppZc9h9IYgCj+6wD0OJPDaPpuBzy5AEAatlqWpef5IiCTioNwanXDXwlR1xAMDyjhDyRQMTWQ0OgKSqL0p7Z9NQj980TbhcpTzIvb29ePnllwEAyWSysp+fEEIIWWy6tbPHbFjz7z3niwZG0yr0OXrejDFsHE3j9eEEntkyhq1jGViOg8IsQ/U8z0EUeKTUIlh5m2MqX0SmYMDjkuBVpL2nSM9UH//4x/GJT3wCH/jAB/DnP/8Zp5566sK0jBBCCJlDzO9GvmjAsGz0RP3zem3RsLBxJAUGIJ4tYG1fbMa99ygv8LMdBq9LgmZYkAW+rrz9QY+CdEEHByDoVdAV8uK5rQy246Ar3HiSo0Y1FPgne/gAcPXVVyMQCOBvf/sbPvjBD+JrX/vaQraPtEgwGMQHP/hBBIPBOo4mhJDdl8oXMZDIQhYFrOwIQRKnD6HvShR4rOxsbAeSYTtgUx+z6XUBNMMCz3FQJAFr+2PQDAsdQQ/6on4s7wjNeqNgOw5shyHqd5fTA5fOE88W0BnywnJYVQKhZqF9/LSPnxCyj7EdB9mCAbcswiXvPXk4XhuMo1gecu8O++YsxzsbzbAg8tysNw+MMQzES9X52gOeaQl3RtMqhlN5cABWdIYRcMtwHAbTdmrO6099763jaQwmcgh7XeA5DilVR8Aj47Cl7XhtKIE3hpJAOW3wOw/c/d1wi76P3zRNrF+/Hu94xzuqnn/yySdx1FFHQZIWN1UjWXyFQgEbN27EqlWr4PE0fyiKENK4TaNpqLoJnuNwYHdkrwn+blmqBH7PbrR5OJXHaFoFXy7XO1POf47jqvbXo1zxTxRKyXsyhdLCOwYgW9ARcMvgeQ4KP/tIxI5EDqNpFSlVh+2Ubi5CXhcSeQ1hj4LOkBfZggGHMfRGfbOeazE0tLjvX//1X/HQQw9Ne/7BBx/Et7/97YVoF2mxeDyOH/3oR4jH461uCiFkniYXnDmMQTOsOY+vVzKv4YVt43h9MFHZmraQlsQCWNoWwKrO8G4NgafVIlD+/PUU8MlpBpJ5DQPxLF4djOO1wQR000LEV1rEznMcwl5X3e8v8hzccql4j8hz8LtKef0BQBQFtAc8WNMbxZqeKPpakLK3oVuq22+/Hc8999y05y+44AIcffTRuPrqqxeibYQQQhrQFfZhJJWHR5EWNGf+SEot3UyYFhL54m4NxU+lFk0UDBNhrwsRn3ver0/kNGweSyHodmFZRxARn7uSbz8wx+K7tFrElnJZ34lMAW1BD0zbQVYz0BbwIORRwHHcvOoB9McCkCUBvVE/Il4FadXAI68NwC2LiPpd4DgOIY8Cxhh4fg8uyztVNpuFbU+/27MsC4lEYiHaRQghpEGdIe+CBeWpPIpU2T5Xz1B8Mq8hkSsi6FFmLFijFk1sGEmCAUjmi1jdHZlXmwq6iac3jSCrGZDEPFyygCVtQUR8pbn1WgHbdhxohgW3LFZGREzLrpSZF8q9dACzrhEYzxQwlMzBJYtY1RmuvJco8OiN7Nxh8MZQEoLAw7BtbB3LYHlHCJvH0mCMoT8WQNQ//5ud3dHQUP873vEOfPe738XUdYGMMVx33XV4+9vfvpDtI4QQsodYEgtgWVsQq7sicw7FW7aD7RNZ5IoGBpO5GacciqZVWVlfNOc/LWFYdmUlvmk5lR60LAo1g75mWHhh2wQ2jKSwYTiFsM8FtWhiRzwHl8wj4nNhZUe4si5iLKPi1R1x7Cjn6Z9qNK2Clc+ZKk8vMMaQKehVqXjtKbHSZgwptVhK2Vu+2Wm2hnr8119/Pd71rnfh0UcfxTHHHAPGGB5//HFs3rwZjzzyyMK3kjSdKIro6uqiynyEkAqe5xD21T/XzXFcpeb8TCPaIa+CZF6GZljoCs9/lCLgVrCyM4yhZB5tATd6wjPv5c8XDby6I4FtExmEvS7EAm6AARGfC16XhMFEDrqZRlrVsaYnAoHnMZTMAwAmshoiXnfVQkGvIiGj6XAcB/miCUkoIlfOygcAKzpCCHoUHNAVxkRGBcdxWNkRgmk7eGVgAjZjOHRJ+7w/8+5q6K/64Ycfjueffx433ngjnn32WXAch2OOOQb33HMPVq1atfCtJE3X3d2Nb33rW61uBiFkLyUKPFZ0hJBSiwi4ZShS7XAj8PxulaXleQ4rO8N17eXPaQZEgYNbFqHqJpa6glAkAUGvgvFMAbppIRZww2EMBd1C0KOAOQyW40CRxGkjCMvag8hoOoYSeaTUIlJqEbbjVJXzDXoUDCfzyGgGOA4YSatwSQJsB7Achnyx+UV6Gu7OrVq1CrfccsvCtoYQQvYiBd3EcCoPSeDRG/VX/uCTEr9briuzXbMEPQrGswX0RHzoDHrRHfGB4zj0RvyI+tyI+FxI5otwSyL8bhkptQjTcaAWDfRG/NP27vN8abX/cHlUAABCbgVqOYdAtDw6MpHTKr8b8WwBXpeMglEK+Il88wuh0TguqWnHjh244YYbcPnll6Ovr6/VzSFkj7QjkavM5SqSWHNB3WT2tl1rvLfSZIY8RRSxoiNYV4a8fYFHkbCuLwbHYdM+s1sWsbQtiL4pN3CZgg5ZFJAHhzeGkxBFHh3B6T/j3qgfg4kcFEnA0rYgBJ6ryui3oj2EgXgWHMdhRUcINmMYz7jgMAedNc632OoO/JMfgjE2a4rCyWPI3o0xhmKxSD9LQmbBT/lbKNSYxNbKueAtx0FXyIuucPOTtdQynMrDdhgKhrmg2/IWW0E3MZpWIUsCesK+OWNRLQLPY7adeVNHbcI+FyayBSRyGtoCbvx94wiWtwexojMMd3nxn1o0MZEtIOhR0BOpblPRsEqLD3ngwJ7ybgWOg98lgecAxjgEW5Cyt+7Af//999d8TAgh+6ulbQGMZQqQRB6xGluyMgUdVrliaTJf3GMCv1sW57Utb0+xPZ6t7A5QRAFtgfqziqbUIpK5IgIeue7Xhb0uvKW/DaLAYyJbQNG0oJkWhpP5SvnfbRMZ6JaNrGaU9+mXfg9U3cTGkRQcxpDXDPjKUx6TNwOR8nHpgo62GbY6Lpa6f+InnXRSzceEELK/ksRSkpaZ+N0y+DQHhzEEvc3v2c1kaVsQ6UIRsijA59pz5uDnwmFnb5qfR2/fsh1sG8+AAchoOryKBI9SX2p5tyJhdXdphb/fbULgeUjizlGBqQl4prapoJtwyiOmLlmEIgrgOKAj5EXRtJDIaWDAgiZYqtfec6tHCCF7Ga8iYW1vFKbt1B1omoHnuYYy5LXasvYARtMFCDyHeK6AkbSKvqh/zuFyjtu5tRBTpq7r5XPJWNsbxVAyBwdAd2jnyM3y9iDGMgW4JLFqq2PIU94pYNlY0haoWhvglkW4e0TYjMHbgt+LuqvzzedCzWde2DRNPPzwwxgbG8PBBx+MQw45pO7Xbt++Hffffz/WrVuHt73tbXW/jqrzzc0wDIyOjqKzsxOyvPf0CAgh+77JqnkA4JIEHNQbm/M1k/n4A26lKkDrpoXNY2kYloMlsUDNPAWaYeG1wTi2TWThUyQsbQ/igK7wrHHRcRg4DmAMTUnLuyjV+RZjXj+RSODEE09EPp/HwQcfjEsuuQRnnXUW/v3f/33O1xqGgY985CN49dVXcdFFF80r8JO5ybKM/v7+VjeDEEKmmbqtzjVDfoCpdLOUWc+jSNMCezxX2n8/nMxjIJ7F8Qf1TctKmNV0aIYFy3aQLxpQdROW7cy4GyKZ17B9IguB59Eb9UEzLKhFE16XhM6QF5bNsH0iA7ucsrfZvf6G5vgXyhVXXAHTNPHiiy/C6/Vi/fr1eOtb34r3vve9OPXUU2d97Ve+8hUceuihsKyFqzxFdkomk/jzn/+MU045BZHI/HJnE0LIrmzHweaxDAq6udu1BMJeF/gOrrRIro5MglvGMtDK6YBFga+qtOeRRWRUAw4rpfmN57RpgT/oVuBTZCiSAI8swatMT+Yz1US2NH9v2Dae3zaOrKpjWzyDjqAXR67ohFsWkS9vAx1J5etKPrSQGs42YVkWfvOb3+A73/kOvvOd7+C3v/3tvIKw4zj45S9/ifPOOw9eb+kX4KijjsLb3vY2/Pd///esr/2///s//N///R9uvPHGRptP5pDP5/HII48gn8/XcTQhZF/nOAzGbpTizWkG8sVSDfqRVH63tgozxpDKFzGSUjGWKcx5/NRc+Y5T/b5hnwsH9UXRGfKiLbAzJa/tlBYEvjmchOU4WNcfwymHLMPKzhBU3cLrQwlYtlPz/SoLJhmDxPPIaAYcB7BshnhWq8rp0Ir8Dg0t7nv99ddx2mmnYXh4GCtWrAAAbNq0CX19fbj33nuxevXqOc+xY8cOZLNZHHTQQVXPr127Fs8+++yMrxseHsYFF1yA3/3ud/D56tsao+s6dF2vfJ3NTi+2QAghpDbLdvDmcBK6ZSPqc2FJW3De53BJIniutMPBJYsN7cGfpOomkuWiOKNpFe0Bz6w98KVtAYymVbgkseYIwZJYAEGPAsdxUDAsjGcK4DhU3mMgnsVBvTEIPIdMQUfRtLBlLI2UqmN5e+lahLyuyt7+nogPAbcMgeeQL5pwnFL53ajPhWUdoVJ7eR62w2puA11sDQX+Cy+8EIcffjjWr1+PcLg0RJFKpXDRRRfhggsuwGOPPTbnOSaD7+TrJ0UikRkDs+M4OPPMM3HJJZfg6KOPrru91113Ha6++uq6jyeEELJTrmhU9v0n8kX0xwLzDtwuWcTq7gg0w0TAvXtbG2VRqNxEyAI/59Y+n0vGys7ai5Rtx8HGkTQKholUvoiQVwHHcQhNGe4Xy0l9OI6D3y1jJK0CrDR68NyWMXRFfJjIaljXF4Np2xhOqZAEHt1hHzyKhPZgP/JFAxy4yogCz3FgPLAb9z8NayjwP/PMM9i+fXtV0A6Hw7j55puxdOnSus7hdpfucnK5XNXzuVyu8r1d/dd//Reef/55fPzjH8dtt90GlOeiX331Vdx22204//zza/4yXnHFFfjCF75Q+TqbzVIaWkIIqZNXkSDyPCzHQcAtN9xbd8tipVc8SdVNJHIa/C65svDOdhxsHc9AMyx0h33T6tXLooDV3RHkiwYCbmXeq+Y1w8JwMldJupPVDIgCj6xmwO+WIQqlAB/wKNBNG+2B0vs7DsOytiBEnsd4tgDTdqCUP4/lOHAYw/Z4DvmiAZTXE0yuZXAYwJULEI9nChhM5sptMdEXbe7usoYC/5IlS5DL5dDR0VH1fDabxZIlS+o6R39/PyRJwrZt26qe37p1K1auXFnzNT09PfjoRz+K9evXV55TVRUjIyN46qmncN5559X8hVQUBYqy5yTP2Bv4/X6ceOKJ8PtnTk5CCNk/yKKAg3qj0E0bHmXh0r8wxrBpNAXbYYjnNMiSAK8iIa3qyGql4DmYzE0L/JjhJmI2pZX9OvwuGTsSOQwmspjIaogF3GCMIRbwYGlbED6XCEUSEfW5q24o4jkNO+JZiAKPqM8Fw7SgSAKWdIeR00zEAm6IAo+pEWgyHE3dftgX9SOr6dg2kQFjgMBxe0fgv+yyy3DmmWfi5ptvxuGHHw4AeO655/DZz34Wl112WV3nkGUZ//iP/4hf/OIXuOCCC8BxHEZGRvDQQw/hRz/6UeW4xx9/HOPj4/jwhz+ME044ASeccELVeZ555hkcf/zxtNBvgYXDYZxxxhmtbgYhZA8hCvys8+iNYKz0b9Lkwrup2/XcdWzXm4vjMGwYScG0ndK0AGMYSOSQyhchSwLW9kbRFw3ALYszjh5MZAullfqWjb9vHIFRXtgX9rqwpjdaOa4/FsBoOg9RENDmL6XiLeg7S++qRROMMaiaCYc5aEU5lIau6Je+9CWoqoq3vvWt4MtzH045H/Vrr72Gyy+/vHLsbKvCv/vd7+Id73gHPvKRj+Btb3sb7rrrLhxxxBE466yzKsfceeedeOqpp/DhD3+4kaaSBhWLRQwNDaGnpwcu19zbZQhZSKpuQhb4/aZq3P6K5zksbQtgIqtVlfD1uWSs6gyjaFoIe10oGhZ0y4bfJTeUDMdhDGY5UDuMwe+S0BHwwC0JcJcr6rnmGD3wu2RohgWe4yAIHGCX7lw0s3qngyIJ0xY/Rn1uDMRz4DjggM4wBuIZGJYNB4Bmmmi2hgL/3XffvSBvftBBB+Gll17CnXfeie3bt+Nzn/scPvWpT0GSdiYzOPbYY9HT0zPjOT784Q/XtYuAzM/4+Di+973v4corr6REPqSptk9kkchrEHgOB3RF5jWcS5qvoJfy1+9aq75eblnCkjZp2rY2v1uGLPLYMp7GcFJFwCMj6FYqxXHmQxR49ER8iJdvMNoCHqi6hS7mQ8ijzBn0US69G/AokAQe/bEAnt40gkS+iExBR6agT0sbbJVHF3ieQ65owO8uxbVs0UBet5DMa3AA5ArGvD/P7mrof9QHP/jBBWtAf38/vvGNb8z4/XPOOWfW18/2WkLI3idTKG29tR2GfNGgwL8Hm5y75gCs6AhNS3wzl0ROw/Z4FhyAZe1BhLzVo4tbxjIYzagYzxTA87VLH9erI+itypc/uWbB56o/a16gPCLhlkUc2BNFIq/BtBy8uG0cB3RH0BH0gOM4JHIaBuJZcBywvCOMRFbDC9vGAXBwSQJsp1S7wWEAa8Gq/oYnbBhjePPNN/GnP/1pYVtECNmvTS7kkgR+t7d97W8ch82YVGYxTN6kMaCyGG8uo2kVW8bSyGkG0urO10+eayrbceBTJMgiD8dhVYF7qnzRwHimALOOBEOW7cCyHciiAP9u7FAIemTwHIfRtArDdjCcyiNV3vcfz2kw7FKmwr9tGMLW8TQ03YRmmEipOrrDfngUCS5ZRG+0+aWaG7qVHh8fx0c+8hE8/vjjwJSiPP/4j/+IL3/5yzjxxBMXtpWEkP1GT8SHtoAbAs9B4Bd2Mdm+rGhY2DCSguU46In4ZgySCynqd6Ogm+A4rioN7kyymlFZ3Z4rGpUV7ignwNnVkrYgRtMqOsNe9IR9lTVlU03WvWflEYSpC+1qvf+WsTQYY1jaFqzK268ZVnl7oAyljgWFEZ8biiRWkvNM5XfLGErmYNkOvLKETEFHW/nn4VNkOMxBvmjCNG3YVvNX9zUU+L/whS+gu7sbiUQC0ejOi/y1r30NV199NQX+fQDP8/D5av9HI2SxtSKN6d4uXdBhlRdZx7NaUwJ/zO9GsNxrnlzxbzsORtMFMDB0Br0z7gTgUCoNPDk0btYYqZi64G8mhmljMnTqc/T4U3kNTrmjmswXwfOlHrss8MhoOhxWStazti9a102nV5FwUG8UWycy8CtS5eanO+yDLAjYMpaGKPI4ZEkbioYNngdWd0fxqyffxLObR8HAAI7hLUvb53yvhdRQ4L/vvvvw0ksvTSvecthhh+Fvf/vbQrWNtFBvby++//3vt7oZhJA6+V1yJZvdXPXpF9KuOy9GUirGs6X8+Y5Tqj43KeCW0Rf1Qy2aaAt4wBjDQDwL22GlZDqSWMlsV6+gR0HIo5SK/4RnHzYPeBQk80UwAAGPjG0TGdgOQ9KwYNgO/G4ZluPAshmm3q8wxpBSi+A5btrIxERWg27aMC0HbUG7siYlFnDD75agWw5cIo/hlAqOK2XsS6tFcFzp5idf3EtW9efz+Up2vanzI4lEghLlEEJIC3hdEtb0REvDy/MMngvJmaUgDgC0BTxoK98LMMaq9/E3sKmd5zks76hvpX/Y64K7RwQrL9AbzxRgOzYUWURIFmHZTnkIv/pmZiiVx3i5GFBf1EFbwFP53uRUhcOmL0ZVJBGKBGyfyFTy/nMchyNWtOPVwQRs5uCQJvf20ejivne84x2VLX2Tgd+yLHzjG9/Au971roVtIWmJ4eFhfP3rX8fw8HCrm0IIqZMiCS0N+gDQFfIi7HUh5FHQHZm9B85xHJa3BxF0K+gO++Yc1l8ILlmE7ThI5jUs7wiiPejBsrYg1vREcXB/G3pqtLlo7Kw8qxnVVWirF6PKcByG7RNZbBpNTUncs7ODzHMcusN+fOjolfjQ0auwurv5Zc8b6vF/73vfwz/8wz/g/vvvB2MMF198MR544AGMjY3hiSeeWPhWkqazLAsTExPzKrVMCNn7jKZV5DQDsYC7rgV6c5FEAcva66/eF/Ao894GOF+MsUonNVvQsWksDQAIeZS6Rgs6Q14UTRsCx6F9Sm8f5fn8qM+FkZSKTaNpiAIHVS/93bSdHFZ3R9AT8YHnS0P7nSEvxjMqRtMqHIdhZZ2jFQupoR7/4Ycfjueeew5LlizB29/+drzwwgs4+eST8dxzz2HdunUL30pCCCELLl8srbLPFQ1sn8jWHJrfm1m2g9eHEnhh2zhG0ypQvtHZPpHFaFqFqtc3v+5zyVjXF8Oa3mjNZD+6aWPDSAqv7Ijj6U2jyKpFbBlNY9tEBrppQRR49EUD6I36IQo8diRySOQ0JPMatk00v0x8Qz3+b3/72/j617+OH/7whwvfIkIIIU0xtZwtx7WmROxiyhT0ytD8aFpFZ8hbqZynFg145YWZFhF4DiPpPHiOg1sSoFsOfG4ZIa8LEzkNvZHqYme5goHSPVZpoV+zNdTjv+aaa2gImBBCWqhoWNgwnMTGkRSMOhLX1OJRJCxrCyLmd2NlR7jhZDZ7KrcsVm5uJjP0uRUJS9oCWNEZRizomeMM9ZnIavBIIjTDQnvQg+UdIbQHPZAEHp4aIwQH9kbQF/OjK+zFIUuav7ivoR7/YYcdhieeeALHHXfcwreI7BHa2trw+c9/Hm1tba1uCiGkhuFUHvnyUPVISsWStsZKu4Z9rqpENq1UNCxohgW/W16QSoAeRcKB3REUTauSBXJFRwiJnAa3LFZS8O6uvG5iWWcInYaFpW0B9Eb8SKs6hPKCv131RPw4YW0/bIehLTC95PBiayjwf/jDH8bHP/5xfPGLX8RBBx0EWa7+YCeddNJCtY+0iNvtxtq1a1vdDELIDCRxZ2CUxb0/0ZZu2nhjOAmHMbglcdYMfPPhksWqeXlZFNA1x37/WmzHwXimAK68wG9qtr6OoAeDiRwiXhc6gl7kiiaGkjkIAg+lPTRteyBjpfUH9i7bGZuFY2z+bzvXcFADp2yqbDaLYDCITCaDQKCxu+R9XSaTwaOPPop3vetdCAbrX6FLCGkOx2EYzxbAcxzaAu69fpg+U9CxubzaHgAOXdLeUAnexTIQzyKe04DyKv/uXW4epu4ceHM4WVk42BH0TtsiOJLKY6S82DDidWHpPHZBzGQ+ca2h28RS0oWZ/5G9XyaTwR/+8AdkMplWN4UQUgPPl7aGtZcrwu3t/C4ZfpcMrhws96Sgb9kOdiRymMgW4DhOzUJIjAFDyTy2T2SqFk26apQrthmDbtooGlZDSYt2F9W7JIQQ0nI8z2FVV3jRzm9YNoaTeQgCh+6wb14FoHYkchB4rpSa12boDE2vgzCRK2AsU+rF246Dgm6VEiop03cOKKKAlFqE4zD07LLivxko8BNCCFlwOc0Az3EtzyQ4aTCRQ7pc+lfg+WlD9SgH7HzRhEsSq+blGWOQRQFBjwJFEuaclx9K5mFYNgSeL63yb69O0qMZFvwuGQ5j0M3m75CjwE8IIWTBMMawZTyDjSMpcFxprr6jRg95oUxkC0jkigh45JrBfD42j2WQL5ZuWNb0RCrleXujfhR0CwXDhEcRsXkshTU9URiWDUkQwPMc2vwemLYD03KQzhcxkdNg2U5Vut9JzGHYOJKCwxiiLdhRQYGf1OTxeHD00UfD41mYfa6EkH0fYwwbR9N4asMQUvki2oIebB5LL1rgn5x7B4CCYSLoUWoOrQNAX9QPgech8Bw6Zti/r5aT+ziMlYfqSyFSFgX0RHww7FK+BMNysHE0XSnKs7orAp7nKol6BL5UplgQOHSFpt+MJPJFuBURYKXywM1GgZ/UFIvFcP7557e6GYSQBmUKernanKtpi/9sh2HrWBojKRXDqTw4jsOSWBBvDCXhc0vTMtjNZiJbQKagI+JzIeKrvded40pB1nYYOADiLAsCJVGYM9dBe9CL4VQOhuXA3iV9ccirIKq5UTBMRH1ubBhJAuVDNNOquuHoDnuhm6Ubh8kcCY7DytkROQQ9MhRJgOOwaWV+m4ECP6nJNE2kUimEw2FI0p4xR0cIqU88p2EgXsoBr+om+mOLs215ckshALQF3OA5DrplQRA4xPxutAU80C0bBcNEwTARcCt1Jc0pGlalJ5/TDPhdMiRx+up4geexsjOMtKrD75YrPfRG9UR8KOgmckUDA4ksBIGrFC7iOA5L2gKYyBYqGRM9ioSeiG/ayv3BRB65oolc0YRbFqGIAraMl3ZIregIoSvsxUsDE7BtB73R3ZueaMTen/WBLIqRkRFcddVVGBkZaXVTCCHzNHVeudYc80IZzZR69pP/eJ7Dqs4IeqN+HNATwfKOIPzlxX1cuXRtPTiOqxSy5Thu1hELbzn4LlQWvqlb9XSzOhVyIqfh4Vd34NXBBESeR8zvQkfAO22HwNQUyoblIJ7TYDsObMdBIqfh2S3j2DSSwraJLJ58s/mlz6nHTwgh+5i2gAe5ogHbdtC5mwveZmNazrTHB3SHEfG5oBkWwj4XZFFAMl+EzyXBXSNvfS2KVCrtmynoCHtdC5K+t149ER92JHKQRQExf/UUQylzX6kGgGE58LsVdIanr1/oifgxkMhC5Hm0B9wYiOeweSwNDhxiAQ/G0nkMpfJgDAj7FrckcS0U+AkhZB+jSALW9CxMytvZdIW9MG0bjKGSnU7g+WmL+XbNXDcTxhiymgFZFBDyuloy/x3wKFjrqR2M/W4ZvVE/spqBNT0R9EVrT6F4XVLV9ee40jXgwIE5rLTuAhxsx6lMJTQTBX5CCNkPZQo6hlN5eGQRfdFAVaY8zbAwEM+C5zgsbQvUnF9HebX7ys7dS7pj2aVMeC5ZxLaJLFJqERyAA7ois+YAsB0HjKFpowGOU0rcE3DLEAQejLHS+oM6phh8Lhnucglgr0uCIPBwyyIcxiA3cTRjEgV+QgjZD20bz0C37Eo1vKkr54eSuUqu+bFMAb3RxckupxkWNowkYTsMHUFvZTsdKy9KnCnwq7qJTaMp2A5Dd9gH3bRh2U5poV2d0wnzbefGkRQsx0Ff1A9YdmXxYXfYVzOT31TtQQ88iggOpYRGEs+jO+IDYwwuufmLpynwk5r6+/vxk5/8pNXNIITMQ9GwIPDcjD30SYZp482RZKV+/K69dkkovZ4xhkxBB8+XKtItdO86U9Ar2+ZSahEdIS8Gy/PrIe/Mc98ptQjbYXAchld2xBH0yBB4HnaC4YBFSPubVouwnNIahnhWg0fZGTrVognHYRhO5WHaDrrDvmnV+FDu9U/qCnshDHCwHaCzxj7/xUaBnxBCFsBIKo9MwUAs4J62KKxZ7z+SVsFzHFZ1hmcdJn9zOAnLdqCbpfl5/y7H9kZLwSutFqHqJkbTKoqGheUdpdSzw6k8kvkiQh5l1tEAy3Yg8NWr8gu6Wcl93x70VPbhh70utAU8iPnnrjQo8DxyBR2Jcr77TEFHf8wPYZHyFfhcMniuAIcx+D0ywh4XxjKlr9uCHoxnC5VtjZbtzFlzQBQFrOtvg+MwuOXZb9IWAwV+UtPo6CjuvPNOnHvuuejs7Gx1cwip23imgOFUHm5ZxIqOUFPmgFXdrJRZ3RE3EfIoTV2JDgBptZSH3mEMGU2fNfAzDuXc8zzCXmVaoBV4Hp0hbymDXXk7oFXumeumjdHyZx3PFhD1u2uu1h9O5TGaViGLAlZ3hSujEIPJfGUawS1LWNsbg+04lT34cwX9nGZgNJWHIPDgACxrDyKl6gi4ZfTHdn9KYmp53Ul+t4w1PRFYNoPXJSGZ1yDwHARw03Lt66aFDSMpSAKPvqi/5u+BIopgDgPAFmVqYi4U+ElNhmFg69atMAyj1U0hZF5G0nk4jEHVTaQLelN63yJf2nfOylXmWlElN+xzQUvlwXMcgjOsSp+0JBaAbTtwGMPavtiMx7UHPCgaFiyHobeyap+DwHFIl6cAZsqWN1HuARuWjYxmVH4OUxezSQIPsfyvXgXDBENpS51HkcBxHHojPgTcCkYzKjqCXshzTHXMZDI5T6qgY2VHCKu6wpU9+ookYjI5X7ZgVG4OsgUDy9qDsB0Gy7aR1wzky2sV3LKIzpAXybwGzbAR87uhSAI4rvS74jCgFcWHKfATQvYpHllCrmiAK//hbQZFKo0uZIsGwl7XvEq+LpTOkLf83ty0QKoWTeR1AyGPC4pUqjJ32LKOOc8pCnxleH/qcwGPjHhOg0cUkVSL6AjuXNymmxaKpg2vIiE7WaFvSjrbvpgfLlmEwHMN3ZRFvC4k80Xopo0jl3ci4JaRLuiVxXaaYTc8zz+WKWAsW4BpORhK5hH2uao+W6UNfnel0l/U7wLPc5Uti5tH09C1ySqAHLIFHdsmSlkUs5qONT1RTGQKeGUgDtuxS7sqFimz4kwo8BNC9inLO0qJX1xSqUfYLAGPgsAcPe3FVmtRmW5a2DhaqgQ3kSlgbV9st3P3lxLPlPafT80MqJsWXh9KwmEMXkXCqs4wZFGoatfkNEKjJHF6joKpZXKdXXLsM8aQLuiQBL5qgV0tPkWCyPMw4cAlC1UjB4wx6KYNSeQRcMs4uD9W+TxTLWkLYCxTgCTwiPndVUV4JrMCbhpL4/XBBBzGEPC48NZV3Y1cioZR4CeE7FMEnp+xqMv+yLBKQ/oAYJSH93d3EVxH0IuCYYHnSoVtJhUMq/JeBd2sa4/7Qoj53SiaFgzLrirN6zgMg8kc4jkNKK8HmC1hzpK2APxuGTnNQNCjVB27dTxTysbHcThqZdeMdQFEga9KWBT2upAvmiiaFrrKNzw5zYDNSjcB2fLIQTNR4Cc1RaNRfOpTn0I0uvjZv8i+ZXK1uFsWq5LCkNbwuSREfS7kiibaAu4FmYbwuiSsq7E2wO+S4ZZFaIaFtoAH8ZwGx2GI+d2L+rvA89y0QkTxnIYd8SyGk6WFng6AiMeFjKpDMyy4FRGZgg5ZELCqKwxR4MFxHKJ+N3wuqbzjobTQjzGGreOZyg1EaDRd8/PP1Lb2oAfbJ7IYSatQJAHL2wPYMOKB7TCs3GUqpRko8JOavF4v3va2t7W6GWQvY1o23hxOwrAd+FzyouypJvNTqioXbMp7iQKPNT3RcnW9LEbKq++LprVoFQJ3VTQs5HUTQ8kcGABR5LBpNI2IT8GQJMBdnv55Yfs4BJ4DY4Ak8pVcBgXdxIaR0tRIyKNU1jgUdAPJvFaqHcBzMC0bSbUItyzNWSBoJJVHwSjtZBhNq1jdE4VpM9iM4cDuyKJfk11R4Cc15XI5PPPMMzjyyCPh9y9O1i6y79EMC0Z5HjNfNGA7TksWupHWsWwHG0dTGErmoRkm+qOBqmp1C0HVTYyk8pBFAb0Rf2U0wbBsvDFcWmOQyhcR9Coo6jYUWYADIJErwsoW4FUkqLoJ23bgkSUUytsLJ889OV2RVosYSeUxllER9LhKixZdEvpiAWwey1SC+QFd4WnrB7IFHYLAw6tIkKescZBFARGfG2v7YjBtZ7fWOzSKAj+pKZVK4Re/+AVWrFhBgZ/UzaNIcEkCiqaNkEehoL9AMgUdO+JZyKKA5U3KTdAo3bRh2g7CPheMtA1ZEqrm3XeXZTvYMpaGWb7BdEki2oMeoBz4J4N20C0DjEG3bHAcwHMcLOYg5nMjrxtoD3gqSXemBt+QR8F4poB4TkO2UMSmsTS8sgTDdrCiMwyvIsGrSBjLlBI2BdwydNNGea0j1KKJZ7eMIavp6Ah6sKorjK6gF2rRBAegI+hBSi1iIJ7F5DLEZgd/CvyEkAUjCjwO7I7CcpyG91KT6YaSORi2A8Mu1XZvRS+xHsm8BtNy4FMk5HUThyxp2+1pBsdhlR59vmhg02ga2+NZBNwygh4FwpS1A15FQtjrQqagw+tRoOomIn4XErliKXcBYxB5DnndgCIKWNsbBc9xVYtBJVHA2r4YNo6kwMBQSJdK8Ya8pcV+XSFvZSeDaTtQdRO+KbtHBpM5pFQNRdNGuqAjr5tQdauStGg8q8GwbBiWDVZe6EeBnxCyV+N5DjJPQb9ejDHsSOSgFk10hDw1dyS4JBFF0y4/bt61LRoWxrMFKOUtebIozLhFMp7TMBAv7VcPe104rCsMjuNglAsBeRVpXiMVkwvq0gUdQbeC5R1BpFUdDitVydMNC70RP6JTcgFwHIdl7aUbDcOy8fpQAhGfG1Gfu7IF8OWBCQQ9LmjlYfqVneGqdjkOg2nbCPtcyGo6DK+NWMBTNZyvmzZEXkBH0AOfq1Stb5Ik8Ah5XRjLqHDJIqI+N0ZS+cr3ddOCblj48wtbwRjwnsOW131NFgoFfkIIaaGsZlRWiw/Ecwh7XdP22S9pC8CfL0IRhabmCtg6noFmWhhJ5eFzyQi4ZayqMZ+NcqCd+pjjOFi2gxe2jWM8U4DPLeFdB/aCr3P6Ry/3mAEgo5VW4gfcMgbiWRRNCwd0RypD/LuaLNl7YHcUmmHC55Irwd0u5/YPexX0xQJVNw6W7eDN4SR0y0bY68La3hg4DtO27iXyGoZSOWiGiaNWdE05twPHYZAEHket6MSy9tLCwM6QF7ppAxwQcCv45fNbkS3q8EoSNo6mcPSqrrquyUKhwE9qUhQFBx10EBSltQlJCNnXieWc82zycY099gLPoy1QO8gtpsn58lImPgYGoKBbNQN/m98NtWhWyuOWXmeVpims0pD4eLb+aQpJ5CGLAgzLhiyUHnMcB5Hn4Zal0v73yPT1R5O58lXdRMirYHVXpHJN02oRjDFYlo1swUBH+ZpmNQOmZYPnuEqp4h3xcThOG5a0lXYjGJaNwUQOHMeVdgwwwCVJmMhoQG/pvRO5IrJFA67ylsZJHkXCmt7SiMNIKg/HcTA4kQN4VEYomokCP6mpo6MDl156aaubQcg+z6tIWNERKs1H+3YmjFF1E2rRRNCjVDLfJXIaknkNvRF/ZVvafDHGkMwXwQBEfdNHF6Za2hbESDqPVV1hWJYDlyQgPEO5XEkUplWl88gSPIqErKbC75ahzGPdh8DzOLA7AlU34ZFFiAKPfNGAKPIQAeS10qp8YZfpg2w5V/6ORA6DCQ4uUcTScnBlABRZRG8sAFngIYkCUmoRW8czAICAS4Ys8NieUWFYDkYzeXhdEjpDXgwl85URCAAQOA4Mpep8lWswpS2isPOzWraDsUxprYBHFsE4IBbwQBIFSGLzF2pS4Cc1OY4DXdehKErdQ3OEkFJgtWynUo2uHrum+9VNCxvLe8nHMyrW9sWQKeh48NUBOA7DxtF0w3PDo2m1UklQN+2qLHO78rqkyv72WlXr5sLzHA7sjpSq74kibMbqeNVOosBXFRwKuBWEPEqp+p3IY8NIqpJ8Z5LfJZcWzjHA5y7VbZgU9rpQDFnQDKuSg39yoR5jDIm8hgO6IhhLFzCRK2Awka/sSODKRXyKZqkWwMrOMBhjVdMNYZ8LTnknQduUKYThVL4yndMe9OCI5Z3IawZEQUBXuPm7pijwk5oGBwdx7bXX4sorr0R/f3+rm0PIXsF2HGwYSUEzLIS9roaHcXdNs2s7DFnNqOShz2tGzd5uPXTTnvLYmvXYqWYK+mZ5Pn+mhXulveql4KkWzd2qljiZoW+y562ZFvKaAc20YDOGzqAXLlnEUSu68NpgAjzPTZsi6dpla2HU70amYGAwUdouuXUiA7ciIAo3RIGHSxKhFk0Mp/IYTubRESpVLOzsqT1lIYsCvIoESRSgFk0MxLMYy6hwKxIkgYfjMLx1ZRfa/G6Yjo1VnZTAhxBC9lqqblXmdlNqEX127Xrsc6mk2dUMxAIeiAKPrpAX7QEPUoUiVnWGGwr6KC8008oBf9cgOF9jGRVDyTwEnsOqzvC0Ff+Ow1DQTWwdzyDmd2NJLIBXBiZgOQzL2oNzlg82rFJOAK8igZVLLcuiAJ9LRr5oQBZ45IoGJsq9adNysKw9CI8i4YjlHaW6BHOMWMqigAN7SsF3MiFP2OuGR7Ehi6W6DzsSWTiMwaNI4Dl+xq2qOxJZTGQ1cABWdIYxmlahmRY8igTbcRDyu9EV8oLjOKzobF1WSwr8hBCyQDyyCEngK8Gq0UQ7tdLsSqKAE9b1z5oNsdZw/OT2tMmV6S5ZnFbdrlHJXKnynO2UKuDtGvizmg7LYVjaFgDPcVB1o5LZcSxTmDXwbxpN4cXtE/DIItb2xcpD8UXwXOkmA+VqhKMZteqzTuI4bloxIlU3kcxr8LtkhHYp1tMZ8mB7PAupXIpYkQSk1SLShSJEnodHkdAZ8iDkcWHFDPn181rpxoEBUIsGFJFHvjxlsaw92JIFmrVQ4CeEkAUymat+ct/6YqgV9E3LxqbRNIqmhZ6IvzLvPHV72tS885Ms28FoRoXI8+gIeuY9hx/0KtDSFniOq5mvXpFEcADAcXBJInwuGfHyzYJHmTn8aIaJbRMZWLaDrGZgLFOoLAx0GEPBMCtBtDPohWWVpkN6ozOPYDgOw6bRFGyHIZ7VcGCPCLe8sw0hr6vqZiCtFrGlvOjP75LQHwtA4LhKOeJaYgE3BhM5iAKPsNcFWRTgliWIArdHVYykwE8I2aPoZinF6t6a+U8U+KaVo52ULuiV4fuxjFoJ/KpuQi/vr08X9KoseAAwEM9WrVSfbwa57rAPluXAdJyqFe0oz+fbjOGArggKhomQR4EklpIA2Q6bsbc/mMhhNF1Kh8txqKS5FQUeo2kVssAj4N75WlHgK6v2UV6Aly0YiPhdVWV1GRgcp5TDX9VLNw690ZkX1hmWU/W4nrUJbQEPIj4XeI6r3ERNvQmbbG+rUeAnNfX09OCGG26Ax7NnDE2R/UMyr2H7RCn727L24LThWFKbR5YquQCmjjR4ZBGywMOwHQTcMizHQbFoweuSIPA87ClD4848V9yjvI4hni/NrxuWXZlCSOY1bCv/HDtD3qpc/VNzABQNC2MZFYokVm46JrIF8DyP3ogfIY+CrrC3suOhPeBB0bSQLhQRdCtwydUhTDMs7EjkgPI0g79/Z+IegefRFvRgIJGDRxYxkS2gM+SdMRBHfC5sHE0intWworP+0rm1RmRSahHbxjOVzIJzrW1YbBT4SU2CIFBxHtJ0aVWvFC5Jq3rdgd+0bOxI5GA7DH1R/7SAsK/KaQYGkzkoooCVnWFYjoPglN6wJAo4sCcK3bIh8hzeGEqW6igIAnqiPnSEPOAzHASeQ3sD889T59SnPs4Xp1S7m/J4V5OZAQFAEQWEfS74XDJyRQMMDHndwEDcxtL2IDhw4DiGTaNpOIxhjC/goN5oJXAPp/KIZzXkNB1+t1Jz2iLmc6M/6gcrrwGYbWbDYQwuSURHsJSbX9XNUlW/ognbceaVQTFVzpvAJqsGUuAne6KJiQn86le/whlnnIG2trZWN4fsJ0JeBZny0HNohkQxtYxlCpUh66Fkfl49tL3ZYCIHzSztJCgtPps+VC8KPESBR7agw3JK2wQ3jCZRNE3IolgVPOcr4nNBMywUTavqvWN+dyWv/kxpdVEefkc5b0hWM+B3y1jREUJeNzGSykHVS2WeX9g6Do9LgmWX2i+LAiynNK8vCqUboNFybgIOHMJeBVG/Z9rncsmlZD45zUDE55p1xb/Ac5jIasgUdCiSgIN6o5WRjExBh+0w9IR9WNkZmjFnw+S18blkpAs6OABBjwLGGIZTediOg56Iv+lVLCnwk5o0TcNLL72E0047rdVNIYtssqcUcMtY0haY9wKvhRTxuStDwfOZ4xerMqa1rv216GZp+JnnOPRF/fNK7DMXSeRRXkgOeY4McLbjlFadcwxuSQTP86Whf9OCT5j/mgTDspHMFxHwKOh1V48OehQJb1nSNmfSnyVtQYym8hhIZDGeKWDDSBLHrO5BwC2joLug6qXiNoZtw4PSLglZEACudNMxmdFwatrjkNeFpW3BGd837K2e+58Jz5VuIBRJgFsWK2mHASCZL0ISeGimhZSq17y5UYsmNowkS23yKDioJ1rJ+79xJIXnto4BAA7oKuKwZR1ztmchUeAnZD9m2U6lp5RUi4gF3DXzsDdTI4v6SivSS8PNs/UwF5ph2XAcNuvUwlAyj6xWyh4niTz6ooEFe/+lbUHEc1plv/lMiv8/e38aZNua1vWiv9E3s++yz5WrX7uvFgoKFERRpIyjHImDV29wgkAhbqASl3PDUAuD8AL3XCIQ1KNxhLBC43o+cAw856LiRagSRAqqqIaqXbtbe/XZZ85+zNG398M7cq7MtXKtvfau3VRR+f+yc68xc+aYc445nvd9nn8Tp9ztO1QtwQVY79QZeyF1S6diaDhBLHTm9ukt8tNwc39MmGRIwNWV9pxbEKcZXpRQOxaMQ7kAcsOEuqXPFz8VQ2OtU+f1/TGzMAES7g1mPLXaZqlZwdSEP78TRPSdAF1VuLbcemjxZOkqFxYauKGwPT7+GoScMUdXT89BeBQkSZj/TPwIXZGpGBq6qjB2Q2SgbulIj1En+HEyH1t5UXLiGhl5wfznsRc+8Tm9XTgr/Gc4wzcwZEmak79kSfq6ZdJLkjS3YAXwo4SJH1Ez9XeMYe8EMbcPxLx5tV098feP43gb9+1u6Y69kLiU6j0OWV5wnLq33qlxvuzuHCfiLbwB0/04jljvRVnsK4ZoxR/xCAxV4enVDrIskaQZr+2OSEsXwou9JlGW0bCFf3/V0HH8GFNTTsQOH3E8hJRPolkxHtkxeVCOx5GT4u6YIElpWMaJEdD+xGNv7CLLEuudOrMgYuxFVAyV870GmqpwYaFBmAgjH0UW3v4VQ2etWyNOhFnQoxbKTdtg4ASESfrQtXFpocmNvQlZlnNp4d0fS50V/jOc4RsYsixxZbmNE0RUTf3rtvAfR5bn3Cj12gd4PLPWeShW9e2A40dzJvzEix5Z+Nc6VTRVRpbeGoHuUZh44ZzB7oXJPP3tNFRMjeVmBSeI6dSsEztxP0qP/fxoIt6DWGlVeXGzjyrL6OXzRUlGmosFQZSKn3VZIUoz8XlMfSZewJfvHbJQt6iYOg3LoGpqvHCuS9XUH3ITPLJBTvOcgeNzrlsvr1UZP04xVOWRHAU/SufkwWkQkaTZfOGwN3aZBTF7E4/DqU+W5+iqwvXdgJEb8uy6OJ8jrX9SjjYOph6mrmIZMo/TQWiqwtNrnVPHHbMgQVMkZElmeixL4N3CWeE/w6loNpt8//d/P83mNwZJ6hsZhqbQ0/74yDaLgrlMrQDSvOCd4FA3KwaDWUBeFCdS9R6EIssn5GxvF47L754k/Ga5VeV4eF6a5WwOHPwoRSrP883o+I+/7u2Ry7WVNrahUrd0scComvOFZMXQaNoGdw+nKJKM48e4YcIsiHn+XI9z3Rp12zw1MCjPi/liYnfsEsQpkiQIfUlW0K1ZfPDCAm6YsDWcYWgKlxabqIqMpavzaN/qA06KtqEJe11JnN/IDYmSGEWSkCWJiRed2M3fPJgQxClOIEikDdugZupi8TB2MTSV9U7thE8Cj8g46M98QKgpBk7w0PF3GmeF/wynol6v893f/d3v9Wmc4QxvGqois96pMZgF1C3jHXPQq5o6z6135yzzdxutiokfpyIw5k0a7wDsT725EqJu6fMUvieFcqzAHf0sSdI8te54wZMkiYuLTSqmxsubA9w4wfEjWhWDOM0I44xqydp/cPeuqQorrSrDWYChKpi6yq29MQeOT5RkdOqWeJ4sZ3/iMvEipn7Ehy4uoioi2jdKMyxNPXFOl5ea1C29bPfLXF5sMvJCpn6MpioPyfWOwo0WGhXWWlW6dRtZltgcOERphhslVEztiYx+zi802B46ZDlcXHxrQU5fDc4K/xlOhed5vPbaazz11FNUKm/+pnKGM7yX6NVtQczyQu71pzRs4x0xA3ovXdgkSWKt/da9NtRjfAP1CbkHaZYzC2JsQxS4vBDEucW6jRPETP2Qhm2eat8LsNio0H7a5OKoweu7E2qWBpLE5aUmWwOHOMtP5UssNSssNSu0qyZ7Ew9DV6maGlGSYSjCiGg0C3hle0hRCOvckRvSKwOOHiQZ3jqYkGQ5T620WW5V5wuVhabQ7MuyhKbIDGeiI9CuWqy2qxxMPPHay6LPnLeRlT+Lf3OCGFWWTmQXHMX/mrqKJssst2oUpVfAu42zwn+GUzEcDvnlX/5lPv7xj58V/jN8XSJOM+4cTilK+dWz69oT7cyjJOX24ZSiKNjoNd50xyDPRR67oSoPtX3fbfhRwtiLqJnaQzvYIyVElhdPxD3I82Lu+6/KMk+vtucFOk6zOdFxOAt5dq3zSBKepiqcX2iy2q4xDeJSVRDNw3v6TvBIvsRyq0qvbnN1qcXWaMbOyKVVMYCCiRdRt3QURfApHsXruHM45eWtAXkBMz/m259eO9EJOGLfb49mHE798vXlLDUrp4bsXFhocDB1iZIcVZbZHs44dHwoyq6CLUZCmwMHqVRizMJ4LkWcBfFb6th8NTgr/Gc4wxn+WOLBsfeTOtLuT/x5tO7+2HtTZkBFUXBjf4wXJViaytWV1pti8md5ThCnmJr6lrsJh1Of3bGLqSkEcUoBHE7h6dXOCUnZcSXE1I+QJemxCogsz+e+/2n581FxL4pizjlI0owwyd7Qr0BTlXlbPM8L4WrnRXRr5mP1/6oiU7V0lhoVOqV0b2s4Q9fkkhxY4Zm1LrIkFnEPLgCECZD4OSxfz2mIk/vHouTRjzM0hTQrmIUxs/2YvCjwwoSDqYfjR3zL1RWccqRSlO91r24z9sJ5d+LdxlnhP8MZzvDHEoamcK5bL61/jfkO641g6vcfZ+hvbnZ/3OQlSFLCJKNiPFkBL4qCG3sT/Fhkzj+10n5LxX937JIXBbMgxo8SarZRkhzzE49Ls5xDx2c4C0jK3fZGt07nETPqo0I9PIU7cURs2594TP2I13aHrLVrLLeqbA4cZkFMr24/0mOhYmqlaU/Czshl4kdcXW4/khTZd/y5ouEota9Xs+nWbD5wYYG9sce9cod9eal1YkFzZbnFyA2Js5yry4/mNSw2K4RJWi6QHt8R8eP7yghTVXhx/5AgSenVLA5nPq2qydSPkMp0v4qp8exahzwH/Qmvy7cTZ4X/DGc4wx9bdGrWIwvZo7DYqKArCllR0HkMW/8IYzdk7IW0qiZN26BqaLhRgqWrJzTpb4Qky/FjsWiI04woyd5S4bcNDTeMURWZc706dw4cDE1BfmAHfa/vMA0itoczapZOwzbwouSx79e5bp1z3dMNiHp1Gz9Kub474nDqE0RpGcMrWOvboxntqvnI1yRJErIs44YJqiyS+Ho169TOQZRmZGWksK4qrLWr3O07tCqiwI69kO2BQ5iK9/D5c/dtxw1N5U88vVba/T76/a0YGs+sdR95/DiWGjYvbw+pluFHpq7SdwI+c2MPP055dq1bugtKGKqCG8Z88c4BWV7w/Lku3dq7q6o5K/xnOBWaprG+vo6mvTOM6DOc4WsZp2Wubw4cHD+iW7fnM9koybjbn85buM+ud7my3CJKMvQ3OePXFJmGZTANImxdO5EV/2ZwabHB1I8wNRUniGlWxWx/ezjj6kp7/rijDkC7YhJnGboiPxEj/XHIj7X8s7xAL/0L8qJAU+QTSoAHsdquieQ9T6NVNdEV+ZFjkoW6zd3DKUkmQom+cOcQCtgazNibeFQMlZEXUTW1Ez4FR5Ak6W21dp740byrECQptq5RNYWzn6rIvLY7mnc7DqYeIzdkbywcM1/dHvEnnv4GLPyHh4ccHh5y8eLFJ4qBLYqCu3fvoqoqq6uryO9ywME3ApaXl/nJn/zJ9/o0znCGrwl4YTLfue6OXTpV85EzbEmS3lI6oJC8NUgykW3/OHvZWRCTPsJiV5Hv2/d6xwx5Hiyia50aO8MZTdvgXLf+tigUFho2Fxca9J0ARZbYHroUhZjfr7Zrj31NUZKSZgVLjQqLJZHuUQsnXVVK3wCRlmdoMmM3YjgLiNKstPuVWW5VS/Lfm0eSZhw6wg75NFLfEYqiOMEBWKhbyBIoikSc5DRsA4n7r8PQhLdAlGQUFOjau1+/3tPCH8cxP/RDP8S/+3f/juXlZfr9Pr/4i7/I3/gbf+ORv/OP/tE/4hd+4RcwDIMwDDFNk3/xL/4Ff/bP/tl39dzPcIYzfONAe2jnKm7WhqZwvteYt/q/Gj2/G8aCmW4bj32eN2Ox261ZFIUYIzw4p64Y2okOwJtFlufc6zuEScpKq0qzYlIxNC4sNInSjIkb8fuvb6MpCovNCtvD2TzNb3/iYWgKy83KfDFwMPXJiwJJlkDiDTkZvbqNLEmEcUrd1rlTGuykWU6cZlxebLLWrb1l86Q7fQe3dNVTZIl21SJKMjRFRpYlvCjhVhkR3KmajNyQkRdiagpXltq8b2NhPrKpmhojT6TztasmWZYTxinZAzHK7xbe063yz/zMz/Dbv/3b3Lhxgzt37vCJT3yCH/3RH+ULX/jCqY/Psoy9vT2+8IUvcPv2bXZ2dviBH/gB/vJf/sscHh6+6+f/xxmbm5v82I/9GJubm+/1qZzhDO85dFXhynKL1XaVq8utEzvRVtXk4mLziRLfHoU0y7m5P2F37PLivcPHWue+GYtdSZJYaNistqsP7eidIGZ37M715W8WIzdk4keEScZ2SbSj3LkPZyGDmU+YZBxMPfZGM7JytHC3P2XshexPPIbu/YCa42TBN5JQHkk13TBmsVnhufUuH7q4xIcvLtKrm0RxRqdmsd6pv+V8hChO5zv5NCu4fTDh5e0Br+0OSbOcgRPMY46jNGOxWaFhG4RJxtZwxsHU59WdEftTnwLmuRGSJLEzcbEMlaqps1eGZL2beE8L/7/8l/+Sv/7X/zrr6+sA/MAP/ABPP/00n/jEJ059vKIo/PzP/zxLS0tQXtQ//uM/juu6j1wsnOGtI03f2g3hDH/8kWY5XpiQ50+okftjgIqhsdiovCO+/3lRkKQZmwOHnZHL67tjikfoD7s1C0NVUGSJxbeo/w7jlFv7Y/YnHjf2H/5bRVGQZvkjf59jbHoeSFQ8dAKqpkbdMqmaOr2aTcXUqduPD0tabVe5tNjk2nL7DRdR28MZYy9k6IbCgdCNUGRBnKtZBtdW2w+pGI5jFsQcTD2SR8j5wjjFixP6U48oTrENhdd2RxxMPbwowS9d+ii5HcNZMCdmUvI1tocz7vWnfPnuAV+62+eV7QEvbw0YeyGaLDOYBfRnPu+F08N71urf29tjb2+Pb/qmbzrx7x/5yEf44he/+MTP86UvfQmA8+fPv+3neIYznOFhpFk+N3KxdY1rK603FXd6hoehqwq9us3uxKNlaOSIwnsaj8DUVZ5dP8k296MERZYf2R4fuyH3Bg66KnNpsUWS5fOAGaFrL1DKzzBOM17fGxOnGcvNykOhOVtDh6kf061ZXFxo4AQxXphwfXfERreOIkvzpDxVlkjLxeFRMb/Qawj3PU05oZqQJInGG6QMHuG4QmF/4nHvcEqaFyw1K2z0GkRxytSPxOK0KPAiEderqwpelHBzfyyMnWbhQ+FGfpQw8UKhFujWCaKUm/tT0qz0WFAVLF2lrioURYEfJmiqws5ghiRLVA2NjV6dftnxkCTYGc3mI5mpF9Gqmjyz2iEvikeaFb2TeM8K/3A4BKDTOfmmd7vd+bE3wng85m/+zb/J933f9/H0008/8nFRFBFF0fz/Hcd5y+d9hjN8oyNKsrmRix8nZdb5e5Pql2Y5tw8mhEnGarv6pqV7X0s4160TZzljN6RqaG9ogHOE/YnH7thFAi4tNh9y6Dt6TF4UhEnGyA1YblVZqNvMghjLUDmY+rQqJpauMvUj4vLz7TvBicLvRQl95z7J8fn1LlM/nifg7Y5dLi+12BqK8J921UKRRdzzEeEwzcV8O8lykjRDfwsdlLVODaVMt9sfu6S5INiN3YD1To07bkDdNnjx3iGzUtq4ULd57lyPOMlIsxxFkefXMWXB/+KdA6Z+RLtqosgyEzfksIzWXajbrHdqrLVr88+maurYpkYYp3zxziELDZvFpo0bxjy92iZKUnRVRVfl+c6+WTFQFZlJs0JRFO+6ax/vZeE/kokdL8gAQRA8kYRsNpvxsY99jGazyb/6V//qsY/9n//n/5l/+A//4Vd5xmc4wxkALF3F1jX8OKFu6WjvoV/92Atxyzn37tj9ui78siyMYmZBhFsa2RSF0JoLe93TuyrHXeGcID618NuGihvFxGk+lwmudWpESSr87YGBE/DcepeKoc2JjA967mvKfZKjjMTNgwk7wxlF6R9gagqmphCnootw6PhcXGigyDKv7YzQVVFsgyRlNA64ezhBkWUatk7V1DnXrWMbGkVR4ATxPJQny3NkSZq/ByKISfgJ2LrKi1t9DiY+L28HbA0ceo0KDVv4+nuRMEQqCngmzxm6AYeOjyxJfPji0vy1bQ9n7E88gjida//9MKYoCmxDxYsTPthbZPlYobZ0lY1unRv7Y7oNC1mWcPwYWZapGCrtqonjx2x0W9RtIe87WjS8cK5HQfGWOQhfDd6zwr+2JvyRd3d3T/z77u4u586de+zvuq7L937v9xKGIZ/61KdoNB6fbvT3/t7f4yd+4ifm/+84zpxXcIbTsbS0xE/91E/R7T6ZgcUZ/vigKAru9p35zudBwxZZlri20jpVdhYlKbcPpmR5zkav8VgL2LcDxwNO3smwkzAWue51SydJc+Isp2Zqb/uI48jdDeC1neHcT0CRpUdKyto1Cy9KhCvcI2bjS80KOyPRFeg7wTywKM2K+y3/kqhmGxpPr3ZElK15chOWpDkLDRsJkECMJqomeyMXSRKudTsj98TvZHnB7cMReQFyLIkViiTIgXVLZzwLCOIEL5oy9SMuLjaZBTGT0ka4XTUYzkJURebKUmsuldyfePhRwmKjwgfPL/K7r2xx5zAqO1JlAE+zwtiPOJh4BIbKyA2Z+hHLrSqDWcDeVIwc6raBLEm4QczQDVEkiTjJSPKcoRvSqZm8sNE9NRSpU7PQVQUJibEXiohhS6fv+CRZgWVo7E1cuvX7JkJBLIKC8rzg/ELjkaFG7xTes8JfqVT4lm/5Fn7913+dv/bX/hqUu/1PfepTfPzjH58/7t69e7iuy7PPPgtlatz3fu/34nken/zkJ2m13jhK0jAMDOPdl0x8PUPXdVZWVt7r0zjDI5BmORM/wtLVtz121o9Txp5gWw9mQUloO9l2liRp3t4vioLt0YwgzoTXfNn23Zt4X1XhL4qCvYlHUgaknDa/rlk6V5dbhEn2hnrt3bHLwcSjYupcWmw88U4riIUbXV4UqJJMjjCpaVdMzi88WaTqEVHujbTyrYqQhRVFceK9yx5DouzWLJrlLv9Rzx8m2bxgzsKYPC+QZYmKKQiLYy+gYtz/e4amECYpg1lwv+3thdw+nALQqZpESca9/lQsVApoWAZSKXO7sNDgcOqjqzIHU0/o+YG1dpXzvQZZXpDnOUUhVAppXqDKIp/e8eO5/0BeFOwMXQxdJclyxl7Isl5l4oXsjsUCw48SFpsVFEUE82iKQs3Sed/5BcIk47+9us3B1Gdr4HB9Z8S5nrAlngUxLdvg5e0BdcvgXn9KnOVcXGiw2q7iRymdms37zytUysXQcTh+RAE0bIOapfOBCwtkeTHvqKiKIjojpwQG9R1/Pk45mHjfOIUf4Kd/+qf5nu/5Hq5du8a3fuu38k/+yT+h2Wzyoz/6oyce85nPfIaXXnqJNE352Mc+xvXr1/k3/+bfcPv2bW7fvg0lue9sd/r2YTgc8uu//ut87GMfe4iHcYb3Hjf3hae7BHMjk7cLhqqgyjJpnqMr8hs6nI29cD73DaIEqzwX6wGf+zjNkCXpiY1i+k7Afil1itOMK6WvuuNHOGFMyxae51VT542cdYuimD+XG8bMgvihmF4niNkrw23WO/W5ZC+Ik7kb3cD15793pPF+IzhBzO2DCUUhdnePY6zXLJ3n1ruCVZ8X7IxmaIpM7w2CXN7oPa0YGpamEiQpnap5Qo7Yq1lMPWE77JS74aIo2CkL6829CXVbn/v5UwYBAUzckL2pzwvrHUZuyGKzQtM2yLKcjW4dP044mPosNytM/IjV1n0eRqdm4gQx11bbTL2Iw6mPosh0auJz3R27GKpCq2IwLjXwFVMUyAc7LUvNCv/Dtz7FJ7+ySVEUfPtTq0iSWEhMvBAvigniDEURQT7dmkXNFEl+mwOHzczBjxKq5b81KyadmslnbuwTJSmWrrI9nLHSrhKnObMg4vW9MXlR8NRKm9V27QTPZVim8SWpiBl+0EvANjQoDaHezu/uk+I9Lfx/+k//af7zf/7P/LN/9s/4zd/8TZ5//nl+6Zd+iXr9fmvx/PnzuK64AD3Pw3Vd1tfX+ft//++feK5/8A/+AX/xL/7Fd/01/HGF53l8+tOf5ju/8zvPCv/XIMJyV12UZLu38+ahKjLXVlq4YULN0t9wZ3z8eLtqsdKukuX5iQJ3FEsqSxKXFptP1AnIj0nMjn46ylI/mkk/f677RDt3SZKwdJUgTpHLnx/EZrnj86KESlkcAOqWga1rBHHC5aUWThATpxm9BwxxoiTj5t4YJ4y4stSiW7bmx24wfy3DWXBq4Z94IWMvomHrcxKcVgbMHMeROc2b/bxVReap1fYJpUBRFNw+mDKY+exPfVZaFe4NZ3hxQhQLj/uB43Ov73CuVydMBKN9pV3jXLfOjb0xSV5QMTT8JOP9Kx3Odeu8tjOkPwswNZUPXVwQCw5SzvcaJ+SHiizP34u6ZbDSrlIU9xcxC8ec+zpBjK4ID/wkzahbOiutKkGczq1wu3WbH/joNYqC+e+N3JBWxaBm6gSRz2LDpmEbXFxsEiUZXpRwrz/FC0R88bOtKleWW+iqwuZgRq9mMXQDdkYumqqwOXCo2wY390YkeYEqy9xTHVYfGAEMZgFF2TmR5YcXu92aRRinpFnGSusbiNx3hO/6ru/iu77rux55/LhtbKPR4POf//y7dGZnOMPXLlZaVfYmLrauvaE++q3A0NQn1qs3SsvXME7p1a1Tf29U7m7yomDih09U+I9Y52GSstEVN9Ysvz+TFlawT/6ariy1BItdP/21qYoyz4Q/Tlg8KppHOIqgfXDB0Z/53DwYEyYZAyfgz77vgpgfW8bcqOY0uVqa5dw5FH7/Ey+kYminnl+UpLy2OyLLhVPcRu/hMUOSZkz8CNvQHhoBiRAcMYe2dRWQmAYRqiKjSBJRkqLIMrqqoCmy8L0fu4RpxvZohm1oXFlu0SkXd4osEacpfiy4AGudGl6UMPJCRm6IJMH20ObaSpskE9kFx3fqh1MfN4zpVC28OCHN8hPEueNdiaIQsbc7I5dpEGFpKleWWw8VVEmSkKT7ao9XtvvcOpxSMTT+1LPrfOTqKlVDw9RVqqaYz989FCqvxYboRhw5CGZ5jhskqIqMqsilKiKljoGuqsRhjKJI1CsPX8s1Sxe8i9K45+g1HJ1j3/HZHs0EeVNVTuUOvJN4zwv/Gc5whjePhcajI07fCEWpa9YU5Ymjat8IbxTu0qyYuOWN8EktSkelOYuhKozckOVWFdvQWGlVmfoRnZr1pvzlVUU+NXznCBcXhce8pSuP1ZNLkjTXvB+HpSmEpdObpsoEcYKhKbSqQiZXlCzwB1Gc0tl4EGmW89mbe3zpziGNisEza52HCn+UZHzh9h6yLGNqKk+ttB/KDLi5P8GLEmRJEDSP2v/nFxosNWymfsQsTKgaGnJPFu+9FyKVO+qj5DnK4tauWdhJxnNrXWxDQ1eV+aKlWTEFoU+WMOST5zELYrZHwu3vXt8RjHdJIklzLi01Tzx27IXcOZySlTHCy60qQZLiR8kjpYs7Q4ebB1M2B1OmfsKlRYt21RKqg2PvyXAWkGYZUZITJxFRmqJIgmdg6GLk9dRqG01VUGSZbtVk5EVcXGigliZK57p1iqKgXzr5LdRtVlpV6mW3zNJVHD+a8yMuLzU5mIpOCqUnwVnhP8MZzvCOYnMwY+gGyJLEleXW20IO9KKE3ZGLriqsd2oPhauIdquGoshPrPl/aavPwdRHkSWqpj7Xky81K7SrJl4kdolvJVwmy/P5jj1KMvYn4txXWpW3zNTv1Gzet9HjYOqx2Kic6GqcFtoTp0JPbhsaFxYajNyQZsU4dbc/C2JGs5CsKBjOgoccE9Ms57WdIVtDF0WWWG7ZfOneATXTYLUtfPSLopjzEvLydV9daeFHKVM/ZLO03T1XmvDYhtCfL7errHdqaIpMUQgdOiUH42iEMpgFZfGGb72ywnZ7RprnD5n/HCHPC/bHHnEZm3vUtcpPaeEc2eYqxzISNEV+aBEVxCluKGyInUB0B0QHQyyEKqb+kPJjf+LSnwW4YYwsQUWSKBQJWRI7dbG4VE4oW9ayHEWWiJKM24cTbh1MhBd/2dUJ45SLi02q5v3Pv+/4TLwQJDGiUmWJ/YlLluVcOKVz807jrPCf4VTUajW+53u+h1rt3V2JnuGdxywQuu+8KPDC5G0p/JsDh6D0fLd09UQ34s6h8Ga3dJWry2+swqEsZHrpjDachcyCaF7kj5wDkyzHUBWeXu28Yfzt2A3ZGbvYuoqmymJnX7aL7/Wncy8AVXl8EttxFEXx0CLhqdUO11bab7h48MKEG/vjuT69W7dY79Q4mPpsD/sESULdNNjoCV27qavYpsZSw0ZXVTZ6DfK8YOpHaKqMKstkRUG3ZtGf+mz1BS9K1xWCOKFhm0z9kP2JTxAnXFpqzfkbNeukX/yr2wMqpl52BdqPjAe2DZVhqdyTJXhpa0Ca5ax1apzr1U/9nSMkeY6pK/NCH8YpnarFue7D95tuzZrzKj5yeRmtLOTHF3x7Y5e9icfUj1BlQeBbqNukWc5So8IHLy6w1Kw8tEhUFRlZEv+1dZVu3UJTFNbaVcalP8JxSWOeF0iS6PocTP15h2dvHM0XbGkZwLMzcpEkYdDjRSkHJSGyV7OZ+CFZDgUSQzd47Hv1TuCs8J/hVLRaLb7v+77vvT6NM7wD6NZtdseuyH9/QovUN8Lx1vfxzPW0lGBR7si8KH0i6ZKqyKy2a0y8EENTUWSJ/YknTGfSbM4wP/rZkB/fRdgaih1onGbMgpiapRMkKU4QnWivPwlnIM1ybuyPCeOU5Vb1Iee1J+kYzMJY8B28iGl5Dkc7+v2xhxvFXFpssj/xuLjYxNJVvv3aKrtjj4at0yvz6HfHLlM/5Jm1Lp2aiSJLrLSrjNyA7aFLkuZMA2EoczD1SbOci4tNmrZxgqPQq1v45QhAVRThbCdJBHEyL/xJmnGn75DlOec6dXp1G0MVxXsWxERJiizLDJxgvnjyo4Q4zTBKq1wniGlVTLSSOQ8hThBjGRqS/LDsjfJaeKMF48SP6Ds+/alPnOU8u9bh2fUOThDjhjGvbY8YuRFPrZ7MAVhp1fCjlLwoqJkapq6x3KygqQqdIEaRpLknvxvGglhawPle/cSCaKVVJcuF6ZAXJfz+9R0MXWFv7NGwDaqmzlqnioRE1dQIkpTlZmVufPRu46zwn+FUhGHIvXv32NjYwDTfeurYGb72sNSs0K1ZyCXZ6+3A+bluWznhnqcqMlVDw40StHJX9aTY6NVJ84ypf1I2Z+sqDctgGkR0quYT8RQMTSGNxGKhWTHIcqGvtnWNja6Qjumq8oZcBUqTnaPuxv7Emxf+NMu525+SZgXrndq8YJyGhm1wMPVKdzyx+JJkCbICXVOQY+FSd3xEYBsal5eac0+AsRvypbsH7I09Xtoa8mee3+CZtQ79acDEC1ms21QsjdVWlf2pj21o+IUw+jnehqb0D2hYBpIEX9ka8Or2kIqhnSA1Hjj+fFSwM3a5utyibhvsjV3uHE44cAIW6zaNsm3vBDG39sccTH2STMTTrnVqTP2IZ9e7XOg12FHkuUTvCFGS4kcpNUt/7BgnTjOhLMhyHD/itZ0hw1k4zw9YbdeolR2nNMsJU+H1cLzw1yyd58/1RMTwYMZgFhDGKZeXWg8tUIezcO6nMJgFXF5qoauC9NeqmEiSxKs7Q4I4xY/TclcvrjNFlmiaFkiw2Kiw2KjMrYM/cGHxka/xncJZ4T/DqTg8POQXfuEX+PjHP/6GTopn+PrDW5mLPw66qjwyF/7yUgs/Th5qzz4JznXq7MoukiTNC6wfp6R5Tt3UWWxU5kz9xz33pcUmQzfA0jWxEAnjUrkgFg0XFwWhzA1jpn5M0zYeWbjtY5a2x8ckh46PE4jCuD2ace0xWfeqLNGuWLQrJrMgnr9/whPempu+tB8gI24OHAazAFvXsE2NiRcSJBl1CsZeyN2+gxcJ34FWzeTp1Q66qmDpmuiMaGJO/mDh96OE7ZGLrsgMZwFRklIzNWZhMi/Mx9P4DFW8169sD/j09d2518DEi6iWrnVHCoxZEFMgFBhBnM6fp1U1aVYM9idi1r/UrBAlKf/lpU1mofgMnj/Xo1lmCDyIkRvOvfZHXsiV5TZJNqCYJylapHnB3tidu0mqZZdjb+ziR0IKWLN00iyfL2rcKCFKsxN/syjti4/a8lVTZ+pFTPyIbs0qiYnZnJ250LBRZZmpH1G39bIbIyMhoaniM/jotdVHXh/vNM4K/xnOcIZ3FLL88A7zSaGpykPs9Z3hbF7cdm661CwdQ1V4arX9SE2/qsh0qhZuGJPl+ZwN7kcJtw4mzIKYxYaNE8QUJRnrufXuqYsJS1e5vNhkZzybE914QAL4uPyCKEn5vdd22J+4zMKEaytt1to1TF3F1NWHjIWOkOcFg1IW6ceCm7HSquHHE3RVpVe30WSZKE7ZHro0bANVlnl2vftYNQPlKMSLEqIk5Q+u7zD1I2RZkD+PFly9uo0sSUJOWBPkyut7YwYzHzeIKbImV8rFztiL2OjWGc4C8floyryjstCw5wRPSZJOEAC3hzM2Bw5hnHJ7f1Ja3wY8u95BkWWiJCttosUCTCqVEN2qhW1qmKpCo2LQrdm0q6Igt6sWjh+hqQr9WYATxMxCMe4ZeyG2oZJlBRTCttiPEqalK2aSZvOxztEUqFezURWZ3355kyjN6NUsnl3vCpfJLMPUVM536zQqBkUBSZZzOPXnJleUXbet4Yw8L1jrVN+RqOfH4azwn+EMZ/i6wlExTrOcLL8/6xcBNKcX3Dwv5lHCmiLz9GoHVZG5259yvdTGizAXmZplkBcFIzfgYOpjqAoXF5snFgH7Uw8vSvGimWjj2mK+3qlaGNrjRwazMMGLEuJUFJkoyZ7IBVCWJSqGhhclqLLQlr9wfoFn1rvYusIza13SPGcWxlRNjXbVJE6zU0mID72nRwqHkmWPBFlWsNl3uLJ8v3NxfIwjSzlhnOD45WKqYlC1dPKioFG2yZ9d7/LMWoewLNhH7+HEC9kazBj7IQt1ex7OoyiSSO9LMvJCLPzSPCfPC7aHDn3H59Dx6dUsVto1rq6054Y+fmnOtD1ymfoRY090Y8ZugCRL1CxhwpRlOQdTj6qpMfai+biramkEkXiOnZH4XCVJIkwy/Dhlb+zSrdv0HZ9znTpxdpRQmdKfBXNvBwmJ/anH3YHDYqPCamloNZwJFUS7YrI/9ebcF2l0v+P0buGs8J/hDGf4usK5bh17FuCFMQMksiynWTExHzPrT7J83hY++lkt5WmKLJPl2VzOl+XQrpplyEpOkolEt+O56Uman3juzYHDqLyRX1xoPHbsULd0Fho2QZygKjbNivGQC+CjcHmpiRcmmLpKURQkaU5eiEAkWZbQZYUXNnrUbQMvSh6b6nccDdtg6AbUTJ2Li038OKVdMTF09ZGSSUtXudBrMJyFVAyVMM5I0gxLU9gaOOyMXXp1i4W6zcHEQzsml9waznhtb8Rg6uMvio7OU6sdDFXl2bX7lsWmptKpWWiqwsgNCOKUWRBTMVQOph7LzQoVQ5vLM2dBxNQPmQUx/ZmH56coijS36D1yLVxuVuhUTbo1e96+rxg6WVawOxYSv6kfcaHXmNtMS0gcTn1UWcKNYpaaFQZOwFpHyB3vHE7JiwJNledZA33HZ7VdRZKYE1If9IGQ3+agpyfBWeE/w6lQFIVms4mivDc562c4w6NwJL3aHbtoqjyX5T0OhqbQsg22Ry7tijknGV4oi7QfJWz06nO7XMrZ9NFiwXqgFbverbE9dNFVmW7N4vXZeH4siFMeF7GuqwrfdGmJD5xfxNCUE54Cj8O4nGl3axZxmvH713cIk4z3nxe2uLf2J+yMXRQJXthY4MJjAoSOWteWruJFCa/vj3hle4gbxDx3rsuffHqNuqXTrJinFv2DqcfUi1hsVnj+XK/kKYh8h8/fHqBrCu2qRZ4XeEGCX1pMa4pcLnpSHD/Cj0WaY1wupI40+6au8YHzCyfIjQ3bmOv+TU3DKuN6bx043O1PqZs6uqawP/GYBTEvbw4IkpQ0K/gzL2zw4YtLFKWUsrPamc/w67ZOURL0bh9M+MpmHz8WXItZmPDUSpsozVhqVPjcrT1MXQQBfdOl5RP2wM+tdwWvoSh4rQx1qs1HXNIJ9cdio8LEC0ny/CEf/3cDZ4X/DKdidXWVn/u5n3uvT+MdxZFPtyzJXFiov+tztrcbUz9id+RiaAobvfp7kvP9VpHnBTvjGXGSs9yqvKHE6aggA2RP6NsryzK2oRJnGbMwoW7p2IZ2goTnBDH7Ew9LV9jo1Rh7OoamPsTwrpr6Ccb7cqvC5mCGpson2uGPgiLLHNVTRZbLsUWBoSnzWORZENOrWyy3quwMZ3z+9j5N28Bp1/DDeG4D/NLmgLqlc/NgzGde30WVZQazgI998CJDV+x+KQrCNKdm6lRNlXuD+2Y9uiIzC2LiJCMvCtwg4YVzPZbb1VO7KEGpURcfBHzo4iJFIdjz/ZmPWvok3Os7XFtpY6gKnbp1wrjpXLeGE0S0KjFTP2KpWWF35GLq9yNyHzQ9urAgvP6fW++Wscg6OyOX/YnH/tjjTjwt/Q4UmhWDMBEkUF1TyfJszp14MCvh+P+7Qcxyq0rf8XH8mGsr+px74UUJjYpJnIjuUFrmOlRNoT6QJGEIlGQ553t1ZFkoWpjL/XIkJJZbFfYmHjcPJuSFiJO+uvxoIug7ga/vO90ZzvBVYG/slgYcGQdT/6Hc+fcaRz71rUfsuh7E1sAhzkQsbs0Nn9iI5msBQzeYk5/iLHsoAvU4jlrcUZJiGxqr7SfbMXlRjCRJFCWp7zQ/gXv9KUmW44ZgqOoT2yIf6bQtXXtiZ8IjBHHK63uCZ2CqCkGSMXIDOjWLvYlHq2LwX17eZH/soasyFVOjcaxYVSwNVZHZGc4I4nQebTvxhHtdnhfcPpxwcaEhfAzC++fn+BEXFhrYuoosSbQqBu2qyXK7iixJwpHP0k8sihVZmpPqwjhl6Ab0asKTf8G1iRORwjgLFFRFmBOpssxiozLnPiw2xEglTFKmXsTe2MWNEiq6xnJLpd14ePEkSYLj4AQxFOI8ZBlMXSHJc8I0JS1yVMVAkTLaNZu98YyKoXJlSVxPg1lA3/ExNAVDUaiaOo2KQZJmBHHKUrPC9thluVnlw5cWWahbwqHvQHRTLE2lW7PQVZkv3z1kULotPrfeZepF88XY9tClXTWwdPHZtKuCaClJorW/O57hBQkFBdvD2VnhP8PXBnZ2dvin//Sf8rf/9t9mdfW9k528kzA1dS6/ers8698uzIKYG/uifTz2oidyvNPU+yEzb7b4vJtIs5yDqY9caprlkkR1hNN88I/j0PGFh7+mUjP1x8bcHt9JLzQqbA0cNFV56HeiJEORJVRZJk4z9sYeXpgw8SMuLzbf0O/gKCZZliSeWmnjRQnBY0KLjmPqR2S5CIV5bXfKarvKuAzrqdsGbpjQLzX0pq7SqlhiRCEL4tmlBXF+T691idKMMBERxrYh/q4kCfKehAQFdKsm+6WLXLtqMnJDKqbO+88voKsKH7y4iB8l/Ocv3yFIMpZbFT56dXW++NRVhUtLLfpTTxT+WcjEi3h+vcdSq8LiWHj+1yxdFL5SPqgpYrmwOZjhhSL8pmEbLDUsZmFMt2GjyBIXFhonRi7HMXZD7vSF533bN1EVce18+OIS+2OXmwcTdkcuzYrJtz+9yp2DKaaq0Kzo3D2ccDj1KSSJV14foMgSNUvnI5eXGcxCwiRlb+zxwrkOWSG+d5NjHhINS8cNE5q2QbNi8KW7ffKi4F5/Wo4oCnRVxY8SXtsdYusaUZLyzVdWuL0/oVUzy89Dom4ZDFxhvfxgAuO7gbPCf4ZTkWUZk8mELMue4NFfn1htVzF1FVnikTea9wrHW9lhaRbzRri40GDohhja40Nm3mvsjGbznVFRtkE7VZMsz4mS7ASJ7jSkWUGW5WyPXHZkCdvQWGpWmPoRcZrRqVrIsjS3xc2LgrV2jYWGTadqMpgFvLY7xNJULi42xUJi4qHKMhvdGkNXSL4qptD7B0n6WFvjoigI4kTYC7shX9kaQCGsXV/bGdKtiyjY8736qUS7uqWzP5HIJYm6LQho5zo11rvCHW84C1ht1VBkmYW6zcXFBpIk0anZbPan3D6ccnGxwbNrnbkWPi0lZBvdGm4oInEnfsTh1GNv4rHWrtGqik7SsJQI6ppCnGZ8+d4hYzdkFsZEScbO8D4Z8vg5K5LEtFw457nIAXhtd8TmwJmrG55b7/Ly1pCbBxMUWeLKUousKDiceiL22dSFPE+W0BQZXZHnhkb3P++c/amwFC6OZRQcJQbKkkTd0rmyvMb1vRGqIpPlOTf3x1QNHVkSC7OaKaSBjYpBEAsHST9KeGVnhKbIaIokFm9yhVlp/asqEnEqWvuKInNxscFGr0GaZdiGihvet3o2NWXOG2hVTKIkm3MWOPaxy5KEpkh06zZ5nj+UH/Bu4Kzwn+EbFpIkPZFT23uBVsVg7OqESfrErWxNVR6yj30csjzHj9I3NL95HOI0m7Oen/zvFsd+vs90fqOCH8ZpaeyicziVUWRx89yfeBiawp0y/ezIjtjx43lRGbkhCyXDfXfskuUFbiR29Lf2xzhBTMM2iNIK53tNokSMTHRVmRvOjD3hxFY3ddJchOtEiZh3Z7noYsRphiSJjk0Qi/CfZ9e75EXBQt0+YQo09SMkoG4bPLvWIS2JYWNP7JaPRhF1y+DaapvLS00Wj4UI7Y1d4iwnznL6TsBqu0rV1PnSvUMoTW3aVZONnk2UZMxK06KitLhtVAxe2xmRpCk1Q0NTFYZuQJYXqIrMLEjwY+H0F0QnMx2yPGcaRASROH51pS3enywjTIRJz1KrgmWo+Eky/9ydIAaJkk8gzqNiaORFTtXQuLDcfuha2h27DGYBXpggSeVCWJKEF395/eRFQZ5D0xa7al1TWGqKXIOj1yDJEmvdGu2qhSJJbI9E50FXJA4dnyhJkSSJNM25utRmXDrvne81sA2NNMvmnSJVUfjo1VUOHQ8/yigoUGWZS4tNFFkmjBO2hy6Xl9s0LIPLi03hwSAJPsj13RFRkgpTo+TJFvZvJ84K/xnO8DUIRZbfkKn+1aAoinlEq67IPFXq2t8MBrOAzYGDLElcXGw+kQc/wGq7RlGIFvRy8/GLmigRrO8ozcqYWxVVlrm81EI65p4331mVMa9rnRpZURBFCTVLP2G0Y+liJy8BeVbgRylumBDEGR+8sDg3rvHjFLtcFPUdn63hjDjNcPyYbt2as+udIGYwC3DLwmSoCr4sY+rC9Mbxo9K05pgPwMRjd+yW70eVxUaFo7L6ILGxYmo8s9YhyfITxdfUlLlszCxJgX1HmOnYhoqqCNOce/0pQzcUjHhZQpZFGt5gFuDH4ve1Aq4sNMjygmkQYRsa693avBvw4mafD15YpFkxSdKMlzYHfO72PhVD42qZ8BhECVslp+CIQ2GoKhcXmnxls0+WZWwPHWRZpmHprLQrbA89iqKYf36Hjs8F86QaoSgK0ixnd+wSxSkDN2ClXaVmaiw2KoRJSsPSubE/5lyvzv7E45nVNqvtGm6ZP3C3P+GlzT5Xl1ssrXZY79TI84Ivbx5SFBBnBYokzef90yBCVxRsW8gZTU1Bf+D6blXNuTFSlGSoijQn1C41q8iKTMXQqJjCNXFSLvScSizUACXf5Am5qW8rzgr/Gc7wDYYoydgaOtw5nIriRU4QpydiZI/DDWP2xh6WrpaaZAkvStgaiDzxvCjYH7tsDcTu6/xC47GtcUNTHspcfxTuHE7ZHDhoiowbJax1aoKprSo8tdImSFIaliF2oH5EkmZzeZSpKVgVA01RTljfNiydgePTrllYhkKvYVO3hBTsqFWrKvKJhcxRYRI+7AkTTyJMUpbKLoUXJjQrOmlWoCjCjnVz4BClGbaucHW5PdeQU5IL7/98f8fnhjFB/DChU1eVh3gb6506lbJV3rCN+WLC0BQRubzUwtCU+VhFVxVWmhXqtoFtaIyOpcJZulJ+dnUmXkSWFThBxNZAhBtVTZ2JF9GsmIJzMBOcA8ePaFYEC98yNJZbVfbHoi1/5DJ4eanJuW6d//rKJl/ZHIjPZqlJXgjXvokviKgidvfhUchKq0qYpFRNDS8U8cQSEm3b5PJSk7EXcvNgQpCkJKlIxtsauSR5wUa3ztSPuL47ZuJFxGlO3TZ5Zk0kOl7oNdibeKy0qozdACeISNNCdD9mPhM/olURAUZXH2PBfJwjFMYp13dH7E08FEW872b52RXA1BOJimkuRlaaeqbjP8PXCBYWFviJn/gJFhYW3utTOcPbjK2hgxPEZGVy3nqnPieCnYa7fadkg4udpCxJ3D6cCh1ylrNQt4nTbE4sPCgT5b5aJKlQW0z8CEmCtbbIhG8dC+Y5knzJsjKX5SVpxtAN8cKYaRATJhn3+g5XllvkuTBoMXVBwioKWCjd2ERwjk+r8nDwT69uz+e5Mz+m7wQ0KwZXFpvzWNw4Eyl0V5dbJfFQ7PQe3MF7UULV0ue79YW6zcgN2BrM6JcLkt2xyzOrnROLhQchyydHVUfhPZqq0LDuZw0cJeNZukq7dl9W165aKLJMkuW0yxZ2lhf0HRHyo8gyT6216U8DZKT5wvDI5VBVZPxUFNuJF/JHdw7Ym4gFYrNqsj2csTf22BzOuLbcJs8LTF0ljNPSu0AQ83o1m+WWSKpbPEVFoakK11Y6tKsWv/nlO2R5zmAWUFAw9YXFslbK68ahiNK9fTAhilPqpnASPBovFUVBfmzU1KyYNCsmjh+JSN8CZPUoiCfEDROR3pfnbPTq6KoyH7UIV8SHicFeJNj6YSzSHw/GLq2KiVIu5JoVg93xDD+MyfKCKH73eVRnhf8Mp8I0Ta5du/Zen8YZ3gFIJdNouV1loW7Pd/GPgvwAMekou75ZxqteW2kzcsN56/pR+e1vFnlRULNELnxW5HzwwuJD2u7TcMR12J/A0A1RJImi7KdKkjCRibNctPoLsTO9czhlezjjXK/OpcUmz5/rnXhOQ1Pmun1DVZiFIlgnzQvWO3XWO2LBocjyXAGgqcpDhftef8rre2OqpsaV5TbdmkWW57y+N2LqCznYLIxJMzHvv7bcxnrC2NZOzeQr9/psj2c8s9phrVOj7/iESUqeF1iayvXdkVBCVE3yoqBpGyc++8Es4PbhhLErFnXvP99jvVMXC5NSLnjo+Cw3q4xckYTXq9t84c4BsyCeZw2c69R4ZWvAoecz9kK0cpyEJMhyz693hW1xltMtvQreCL26zaXFFkV5HVYtIT28ezjlcOZzbbnFxcUGX77b53Dqo0gST6112OjW+cD5Hnf6DmvtGtdWHh6h+XEqCrimoKtCejiaBYxmIRMvZObHKIrMUqPCleUWUz/izuGUAtjo1k94NzRso+SFiOsXScLQVa6ttJHK6+LFu312xx55Ibgh7zbOCv8ZTsV4POZ3fud3+M7v/E5arXdfbnKGN4fBLGBcaorfSL+/3q2hjiUURWal+fiiD3BxQTDfLV3FNjQ0RRE3RTdkuSn03kvNirhxFpyYp58Gx49wo6SM1H30LcjQVNY7NcZuSKtqPlHRP44gShi5IbLEvBtw5AEfxinXVlrIklBQOH5EkuUE5bz/cf72a53aXBbYrQl3OmHVer/IH0/5i9KUzdIwZ7PvECQpEy+iV7dFshtlBK+mYpdGMXVb5/W9cVlcmzQqophYuvrI83LDhCTPqVsG+1OfvuMz8UKkknx5b+DQqprcHUznjPiFun0iVVEqpaT3BlMmXkSa5XzTpUUUWcTP7k9cZFlG1xTOdep0yiTBdsVgFsTIkkS3ZrLRa/DazggniAW3QJLo1W38OCFMMsZ+xKXFZpnYKDFyAwxNfYhAuD/xyPMC29SYeiFRmqIrMq2qxUrTFpkKXsDMj3h9d8y3Xl3BLkOUdE0RowEv5Om1Lt90eeWR10q7ajL2BA9itVWbZxyInIAcJHHdVk2dOM2YeNE8tGfiRXRKvsetgwlplrPQEMTDiR+hayJ58fioJkgSKqZKkRdEZ+S+M3ytYDab8Ru/8Rt86EMfOiv8XyMoioI7h1MmfkS7YnK+tGSNkozNct4+C+O54cqRs5itqyeKkn5K4t3jYOoq57p17hxO2RrOSiKZaOmP3JA4y3j+XO+xevoj+FHCl+8dMvUFi/5PPL322Mf36vZbMiIqioJxSaoD5uzvvbFLmueYuoobpqx3LFq2QbNioshgGyoSBb/90ibr3fqpBMuGbdAoOwJhnPLa7oAky+eSwSTNuLk/IS/JdoosSIhRnCJqtvChP57CF6eCd6GVc+5XtoYs1C2misKX7/XxS5Li5aUmT612xC40jGlXrXmx9KOEMEkp8gJNlzE0hXbNYn/iiRFJ+ffiNMey1PnvHMdCw2ajW+PFzb4wmhm5fLbI6dVtVts1Nrp1NgcOThDx9Fqbui3a5AeTnPV2jV7D4lxXGAWd64kRkjDGqc5JbkfIS3+Fm/tj7g0cgijhA+eXWO1UCeOU3/zyHbZLhcZC3WZz4JS/X9Cr23zu1gFuFLM9cKmYGmleIEkyz6x32Bm5hFHK7lg46Q10jefWu3BkQPTA4klXlROmUZ95fZdRGeAjSxJRkuFFKbYuFr51W+f67oiCgrVSdTOciSwBgKEbsdaps9YRuQCWpvL67ggkiY1unctL7XLHX8wTDd9NnBX+M3zDoO/4eGFC7wFZ1dcLwiRj4osZ5sgLWYorcx+Co3x4qZTGHU+je6us/eM4ShdLspw0yxjOQpAkkiyfmyA9Dl4opGEUBXsTj6IQs1AvjOd5718t0iwnL4r5HLZu6TiBkPQdzdmP77oMTUGWhRQtL0S2vKkp3CltnHcnHoossdquPdLgaVJ2CgAGM5+Fhk1WdgCOzskNUtwoplOzuLjY4PbBVGS1eyLL3Qkibu6PybKCu1OHxWaFmmUQxBlR5mFpGjf2xzQrJkGSstqucbuULo7ckBfO9eg7AUM3ZKlZIS8Kri415wvAbs1CkUWc7tSP2OjV2R97xGlGzRRZ9IoscTD1SdKMXqPCSmmhO3R9wiQhzwuatknV1EmynLEb8l9e2uSbLy+L1rrjoygSf/79FzE0hbwo6NassoORMvQCDF1ho1tnfyK6R0edoZEbMihdG1/fH9GqGnzh9j4vbw8BIW9sWDrDWcA0iKgYBi9vD+nVbdKsoGZpVEyddsVkoWGx2LSpGDo390cMZiHbQ5fzC3W2hzNGXohe8jBkSUKSeMjauiiDdpoVgygRev+l8jO5utxCliX8KJ0z+oM4JU4ztkcuWwOHhYbN+W4dSYbDqc/WwOHTr++w3Z/RrJlihLPSpmZppFnOSrvGu42zwn+GPxZIywQ1TZFPNeNxgpit4Wz+8wsbvVOe5WsbwmREkLF0RUYr5WFaGRs78UKatoGuKkRJOjcBirN8Hm7yVlGUs/CpH1G3dDa6dW6XaWSXynS1PC84mHqkec5SozLvMvhRwut7IwrA8UKmfoSpKqx3hZ/5k6Dv+OyOxM7u0mLzoR2bHwmzniwvsA0VTVZo2gbLzSqGpuDHKeOS8OeGMUvN6gki2ctbA9I853AalG1YwfzfHbl4UcKza91T3fuqpjZfdB2R30xdZaVVZeKJpLjdiYsfJnSqFguNCiM3Ynfs8kd3D7ANlYOpz+HURwJ0VcYLIpJM7IaXmlW+dOeQKMlIs7zcfd5vDR+NGaJU/FuaiajfWwdT9qcBa+3afGHSq5siRCYvsDRF6NijhKEXUjU0hrOAgRswcAKqplaa9ii4UVKSGT2yomDkhhxOA8I05Ut3Dxg4okUuZxIHEw8o+NLdPkVR8PRae77o2B7OeP/5hROdjqP3sO/4mJrKhV6dvbFHmuVIEgxmEXYZxqNIEllWkOe5GJFIInI3TFIqhs6z6x0UWSLNCnp1i6FrARJuGLPcrM5T+IIo4fev7+CUWQjPn+tRPbb4LArBU7F1lbplUJSv+YjrcHR/Ofo+FQX0nQBFlkrZpsKV5RYjL2RrOOPG3pjb+xOSPMcJYxbrpb3xG/hWvJM4K/xn+JpBmgm2rqrIjzTW8aOEu/0pkiSkOEdz382BM98NFwUPB6UcE8sWvAfC2bcBakmk86KEqqGd2KnUjxm+UM7Hm7bBpCzUXy3hLohTejWLuiXkY5eXmlxcbCLLsDPyuL4rHNOm5WeQpPmc2R+lGUX5HC9tD6lZOmGacXW5/Ybn5QQxQZTw6s5wToLSVJmN7slRxZHtbZrlvLY94lyvzjSI2OjW+J1Xtnhlq0+jYtCqWFxaanIw8WjaBp2aiSLLWIY6J6e9sNFl5Ea0bRNFlghKFrosK3NNuRslbA1mGJrClaUmecEJOeRSs8JSs8Jnb+6KQmJouGWgi+NHDGc+IPHlu4fUbIO1TpX9ic/z57olqz5CUUTnpm4bc7/759a6dOs2YZLiRym9ui04AginwqkvmOLOcMaV5RY398fz78jWwEHXFCZeiBPEcyXDwAnYHs7IKVhrVfGiBE2R58ZRO2OPTs2kVxeyx5VWlb2Ji21a5YxexgkjLi22WGjY3Nyfsj9xy/wAl07Z1Zj4MWleoMgSlibGR0bpRVAzNfxYKEPSLEMq5Yi9WlT6CYS0ahZFGcrUrpgstWzuHE6QJJnNocPepEnfCahaOrausdCwMTWFVqXDcqvK7ljsyLO8QC4XI/sTn9V2eKLw3xs4hGUQT6dmUSkXJp+9sUteFDy92uEDFxbJi4KiED4MR9e9bWh0qmbZFUgYOKL9n0vCb6JZMemUvJBDxyfLCxYb9le1KH8rOCv8ZzgVlUqFb/u2b6NSeeNVad/xS2KZ+cShJqfhePEGTi3++xOvDNYR0aBHs+qjWE8vShjOgocKf902WGlV8aPk6yq85kGcpud+FC4uNsnLm9xXC0tXsQwVSZbmueaSJHEw9RiXOfTH2/bH3fkalkHDEsYopq6WJDbtsRJCACeI+P3ru6RZzt7EnVu5emHy0GPrljFfGFQMDccPudN3+IPXdtgeO0w8wSlYaIg5uBvGJFlG0zZ5YaPHt11d4d7AoVkxaVdN9OGM6zsj7vQn6IqKKktCAeD4dBs2Uy+ioOBg4rM/qfHhS0vzcxmXXY0sK5gFMcNZINLhbJ1XtofkFKXNb0qSiUAeP87QFJk7B1PSPCdMMgI/xVQVri43eXVnhK4q3Doc88r2gJqtc3mxRatqsjlwOJh4pUwzKnPpE9oVk27dYuyG2IYmrGc1hSTN2R7OxCImzVFVIZGc+hG6qvDseme+619sVrgWJiw1KzTK9/8DFxZoVXQ+d2ufw3LxsNSySVMxSrh7OGFrMKNRMXjhXI9mxeT1vTEScDBxRUJdu8rOSCyctgYzZFmmXdVIM2EgFMQprarFU6sdDh2fTs0iSBKu74qu3is7fe4OdBxPBFmBEMnPwpiqpePHImZ5uVmh7/i8tjPCC2MWGjZhkhGnGW6YoMrSQ8ZTQWlqJMsSXhTjBBFRnNGfCW/9LB/wwYuLJ0K9OuU4JclyOmVHoGJoLDcrNCsma50qB1OPmmlwdbnJQWmdTCk/Pf+YCOV3AmeF/wynotPp8IM/+INv+DhBShItdDdKaNj6W463PSreHNMkPwjx3NGxnwVW21W+stln4oWYqsjkftC+9s3Y2f5xwdtR9CkXVFleoCvKCc957dhOReywNLI8P2EzLMsSl5aaXFpqYuoqW8MZmiyfcNt7EEVRcHt/yv7YQ1NlTE2laelULZ1uzeb2gSDPrXfErvHI3S7NcpIs5zdfvIuExMD1CSKRWKeVBjaqqpBmGdd3R6y0qtQsncVmhctLLWxD49WdodilFQVxkiNJOV+4c8BGt85gFvD6/pi9kUfV1DB1lXbF5HDiEyQJL28N0BRZcCtUBTdMON+rM5iFqIrMzf0xQRQTpYJgaKgKUZYx8yNGJQO/YemCiS/LhEnG3b7YpVqayie/fA/LUKmVu9rFhs29vsOr20OmQShm3qbOhy4sUDV1Ckkk4MVZxjdfWuZg4gkP/jSjaug8s9bG9WM2RzPqts56r856p0btktC/p1mBpggJp6aI+GBVkXGjlDDOmPoRsiRzOPPRJJmRF+LHCZeWmqiSkDa+ujOkYqjsT7w5D4FSPbA1jDB1dZ6M161ZHEw8nCBGDhM+fGmJxYbFZ27sE8WZMF+ahXzhdp+NXg1VkVFyiaqp48UJi3URENSpWhiqwt3+lJv7E0ZuQJxmrLRrdKoW7arJncMpuiYLG+hj44flZpXbhxNmgSBPis6Fw9gNyfKctU6VNMvZ7M/Ii5z1rtD3N2yDQ8dnd+KyWLdpV00uLjUJ45SB4xPEws55a+DSqprMgpiiKJ7Y8fLtxFnhP8OpiOOYwWBAt9tF1x99YcqSNJ9xCrLMWy80650aW8MZuvroVv9Kq4KpKUgPBOvUyhbkUVvzQbby1zuKomBn5OKXN8gnuVlESVrOvL96IuPOaDafFY+8cO6r365a5IVYAPZq1mMNZwDet7EwT5XbGbvo2sNJeWmW8/L2gNd2h9ztT6maGsvNKs2qNc9Zn/jRnMx3FGl6vBuy2qry6s5Q2MNWTFbbNd53foGlhs3BxOPV3QRLh27dYnPoMAsFQfHSYhNdUQhIqds6ThChKTJ1Uy93s1OQwDaFYUzN0tkezYjSjDv9KY4vHr/UqhDEKSM3pCiKcpEq0uniNMfWNbo1iyDJ0FSFIE4Jj7TkBaRZNrd5bVdMgli85jDLCGYJUz9iMPPnpDo/TkiynJVWFU2RqdkGDUtnWubLA0zKTsSr2wPSshvxgQs97FYFVVOY+hEHE49b+2M2eg2eWu2gqTKv7Yy4dTChZonP4anVNocTH0mWUCWhQuiV39coEaY5C2Vxl4DDqVB/JGnGBy4soqoKeQ53Sr+AqqVzbaXNhy8tkeU5tw9E0V1tVxk4PrfLgJ+6rXN9LyGMhTVylGT0agaGLmSAliaIhKYuyIV5UeBFKbujGWGSsdapUTUEoe5uf8rB1KNeOh42bYPdsVdeQ2JEESYpTmkQdLc/oVMzqFsG7YrJZ2/ssTWaoSkyfpyy0a2zO3ZxwxhZltkfu2jl9XhxoclwFlDkYsgYZyIJcuKFpHnxnsSBnxX+M5yK/f19fvZnf5aPf/zjnDt37pGPUxURTDHxQxq2+VXFwVZMbW6S8iiIVLLTFwW9hs0sFD7YX83I4a0izwsKiodYwm8HJl7EoSNa2Tf2Ip5d6z5W1z71I37/+g5+qVd/bv2rIzMaqjofsRgPfMaWrmJp6hsW/fu4v0B8sLMjomlHvLYzou/4rLQqYm5aN9FUWcgTNRU3iLm5P0GSYOJGLLUqdKrWXK3xgQuL7E886pbOarvKRq9RZgQIZ7r1Tp00y8q42PudBzcULeLBTITetGyDkRvRqugM3ZCrq23u9qf0ajYgUTFVWhWzDOUR7nhJkrHerhOlYpRglWQ/VZVJ04ypH1O3hBd+lovrpW7paKpMUYixlGWo+FGK4wvm//mFBlIhviN7IxdNlvFCQeLTVZlOzUT2RNDRt1xZnvsCmG7I2BWJdH0nEF2MLEcGFEnGCRJURaJpG9zYG3Njb0TfCdgZeUhIrHdrBLFQZHjl4kiRJeIsxw0TlttVvu2pVWxd5aWtIRJwcbGBoakkWc7WwBGmRpKELEvMgoggzthGjCfy4shwyZ5fD6JVn+JFCbtjl4kf4QYxh1OflWaVIE7nDny6qqAjCIvXd0e0qiaWrgmiXd0GCixdJU4zLF1loW6xPXaF4dTEE9dhUTDxIkZuOP8s0zwXORGHY3RVRVNkDFUR3BpFZmvo0HdClltC/ZBkOSM3JIxTbEPlxt6YdlUsOPuWz0Kjwqs7I2RJODWOvXD+feo7wdvidPlmcFb4z/BVo2bpj/R5f7MoioL9iUec5iy3Km9qIVExtIcc194tzIKYWwcTAM736g8xl48jzYQxiSxLLJV59G+EIw/zWRAzcgMkSeJct/5QZ+TIeGZv7M5ldrf3Jzyzejor/TgOpz6HU4+apXOuezJC9vxCneEsnLf2vTKt7Sioh1LffqQXr1k6WS6kfroi40UpuirTrJhs9OrsjlwMTZ3PQ/1ylKAqMnGa0bCFIYxSJii2ytS1/tTn5sGYsRNSSAW2pvH5W/u8/8ICYy/k+fUesixh6SrffGV5zpavlfPpI7vYuqUx8nJUWWahIxL+VEWmXUbVLjUrbA4cJFmmU7c4GHu8sjMU/u7dBk+ttllqVXlle4gfJcK2OEkZuiHPXFriTz23wcvbA17aHOBFYofarJhEWc77zy/gBPF8pzd0Aj5yZZmb+1O2BlOSLKOCylMrLdFurlmsd2pzZcqto25WATVTY+SFdGs215Y7NKsGeVFw52CCF6XULI2rS22qlk4QC1OalWaFzeEMJ4x5+V6f8wsNZkpMVso04zTDCxP2xjO6dYudkcudgwlhnNJ3fGREAb+42EBC7PZNXeN9GzLDWYihqfTqtvBScIPS0VDC1HQmfoQfZUx9YYebF8JJcnvo4IUpi00RYWzrGsOZz2gWkqQ5mqqw3quTphlDN5hHMSuyRM0yOJi4rHfqFIjO2LlujRt7IwZuyNANqZoauirzR3cPeG1njBslrLQqBEmKBGR5jCSJ67phG0z8UPAkqjayJJFkGYutKuc6NUEwLGOhwziluyTm803bYFJ+v5eaFcIkm/toTJJorn7JygVLEKekaYahvrvEPs4K/xm+1tB3gjnpJU6zdzSh7u3EyA3m2u3hLHxs4d8azhh7IbMg5s7BhPMLzTeM3q3bBhvdOjf2xvPW7ZEO/Aj7E4+90oe+UzWF/KkoaNdEPv2RfetC3X6Ih5HlOdsjwdUYuiGtqlUS2gqqpi6y4Bs2N/fHTEtjk0tLojBREqK+snmIrWtUTZ0/8/wGd/oOsyBid+TSLQmV7YrBSrvKpaXmvDMy9sJ5pO5Sw6aii137WqcKhVAF5MDV5Rafu7GHGyWkeS7GHZKEVeYH5HmBHydl1rrBWrtG0zZQZRlTV5l4IX94c5/P39ojSFKWmxXqpo6qyLxvYwFJ4sRi5/hCaRYlNMvktjjLSPKCP7y5x0LdpqBgqVWlboucd00V6gZdUbi42GDmx8RZVqoeQhw/Yr1TYxZEjD0h7es7PsNZwCxICBORwidJ0KpZIhY3EaZAL231ibOMqmkwLv3019o1Xrx3WAbQ6Hz6+i5DJ8CNYhFDPPL4tmurXF5s4oYxhqLwmRu73DwYM/RC2oFFwzZwggQ3TLB0heVWBVPXuLk/xg1jKrogqsVZTpbnhElKWzLpNWzyAnZHLrtjF1mWSq29xsAJeHl7WMb1FrS7NSZuKBzyEuFj36vZTLyQT720hamprLUrpIUY2yw3bHRNZeSG9GoWVVPjYOpj6WLBqaoylxdbpUGRQpgI5cnYUBl7EXcPHXRNZuSGYqFqaryyMyJOMqCgXTUJkoyVxSqbA4c0LVhtm7xwrsedgyluKLoTBdCpWnxgY4H1bo2dkYvjxzy90sbSNeqWKVr4ScqHLy7ixyl7Yxc3TLiy1KJdtRg4Aa/vjpFlieVWDbdcwBdlNPG7jW/owr+1tUWtdt88wbZtut0uSZKwt7f30OOPWt77+/vE8UnTkk6nQ6VSYTabMR6PTxwzDIPFxUXyPGd7e/uh511dXUVRFPr9PkEQnDjWbDap1+t4nsdwODxxTNM0lpeXAdjc3HzoeZeWltB1neFwiOd5J47VajVarRZhGHJ4eHjimKLc32U/eIwywMc0TcbjMbPZ7MSxSqVCp9MhjmP29/cf+t2j93Bvb48kOTmH73Q65AX4nos3c/B0DSMRz29ZFr1ejyzL2NnZeeh519bWkGWZg4MDoujkF6nValGr1RhPHXb3D7B0bS6f0XWdpaWlR76Hy8vLaJrGYDDA9096ajcaDRqNBkEQ4AwP6JepZHLdZjf3WVkRFqHb29vC9rPE7mCGYlXZnwToRYQ77uN06vM2dbVapd1un/oeNqSESBMt68SbsLnpzI9d3x1RbTQpsPBdl6fbCkGc0NQT/vDLr7I3i1heWmTqBdQ5+R4VRYGmWCRZgTMacsMfz01VenWbqxureJnE73z5Jv3BUBjVuD0qhs7e0OUgkLh1MKZOiFRAMhsSJRlOEDGThOZ6NBqik/MHcUqvYbPaqnJhbQk3lYjCAGcyxhsJeRheSN+L2fFk2jWTUf+AjhLiTfqEsdilfeS5F2jVqoxHI/zZCMvU+IMv7RElGUEu89ylc3QrGsNBH0tX2R7OePnmPp4bECpVbh84jAd9NrpVBvtNbEOYyiwtLmJZFraUkjpD9iceztQniBMqlQoVo8r24YRXbt2lVTHoNSxakjChaS0sURQFu7t7OJ7H7QMHVZHJ8pzJxMZPCsaTKa/fuoWt6yy1KozcACcqiBSLIs8IpwMGuYsWOdRsUeDNWpuXtoeMRgNmro/StLHrC1Qylxe3XaJcZuaOGBzs4IUpBxOPgpylTgPHNxm5IbOR+C7v7PZ55cY9Jm5Avd3jXl/GkiIix+WcrWKbMmtmSuTPOAwKgjAkmY0oMKnrKtE0o5oXKEqdooB//7tfxPED/DhlrV0lSDKq2hXcpCB0XdLZGFkGLcyJpjM8LwXdYrlhIYUOziwkliUUWWJ/t+DcuXNIkkThT2laGqYqk7oBdw8jItkgSqFrSTTVnNgZ0t8f0avb1GQFRakgSwWD/V3SPOfAF/fpRt2myGtESYbvTNDIMBMTE/DGfZRcZmOxSxIF/M7nv8L+xCs7EjmyqvFNV1ZwwpitrS0AUnfE/sEUWYK6dZGPXF1nMBjgDMV7LAcBsROwp2R06xa3dgdsb22BBF+RfDRFJfcmaLUWSZo9dI/gDe6zp90jHnzM4/ANXfh//ud//gRx7Zu/+Zv54R/+YcbjMT/7sz/70ON/6Zd+CYB//a//NXfu3Dlx7Id+6If4lm/5Fj7/+c/zK7/yKyeOPfPMM/z4j/84URSd+rw///M/T61W49/+23/Liy++eOLY93//9/Pd3/3dvPbaa/zyL//yiWPr6+v85E/+JAA/93M/R5qe9Hz+qZ/6KVZWVvj1X/91Pv3pT5849j3f8z183/d9H/fu3eMXfuEXThxrNpv82I/9GKqq8iu/8isPXVA/8RM/wbVr1/id3/kdfuM3fuPEsW/7tm/jB3/wBxkMBg+9VlVV+ef//J8D8IlPfGL+JTrCj/zIj/CBD3yQ/3brFT75n/7jiWMvvPACP/ZjP4bv+6e+h//4H/9jLMviV37lV3jllVdOHPsrf+Wv8O1/4k/yyd/7LJ/897964tiFCxf4u3/37wKc+rw//dM/zcLCAr/2a7/GH/7hH5449hf+wl/gYx/7C9y6dYt/9r/8LyeO9Xo9fuZnfgaAX/zFX8R13RPH/9pf/7/RtBu8/rk/4KXPf+bEse/4ju/gr/7VvzrnWRyHaZr85P/z/wVI/PNf/F8fWqD+ub/8V7l49Wle/KPP8ev/4d+fPKeNKzz/nR9DzyJ+43/7Xx96rf/oF/8JXpLxyV/9/3Dr5s0Tx/7S9/8AlbUrDDdvcffzv81d4OjdWNu4wKXv+O9IkpTbn/4/ALh17He/5S//MAUFt77we+zfef3k8/6lv8QzH/4on/vSS7z8O//hxDG70Wb52/8SYZLy5f/0v/OZXzu52B5dWcY2TX7/d3+br3zhsyeOrT/zQRYXunzxpbv87v/5v504JqkGrY/+94Jg+MXfYjOY8d+OHf9bf+tv8dxzz/Hp3/s9/uN/PHkdXnzqOfIXvoPRoM+d//p/cPIuAN/1P/7fSbKMl37zVxkf7p449oE/9TGSxip7t68T3v4CwPz3awtrnPvWP8946rL73/49e8BLx373m7/vh8nyAmP/ZRjs4AF/8CX4A2DpuW+lc/l53N1N7v3hb534m269g/bd/wNbQ4d/+8//32TZfT6DBkgf+PNIUo2dl7+At3NjfuxV4MIL30zt0geZ9Q+483v/4cRnWqnV+b/+2P8DL4r5/f/0b4l8d/57AC3zh/jw+5/jkzde5PaXxWdzdEXV16+y9oHvpCEH/MEnf+3kGyjJzHr/I4am8Lnf/Q/zQnqEyx/9c+i9DfzNV7j7R7934tjqhSv8+e//a+hFzmufOvk9PwSu/ej/xDNrbT7/G7/NpL/Db37h/vGP/pnvxVpf4otfeImXfvf/d+J3K51F+NCzaIrMz/7Dh+8RL1z4nwBOvUe88JE/iWb+WXa37rL7B+L7uPv74phiVWl95C9xbSU/9R7xd/7O3+HSpUv81m/9Fp/61KdOHDvtHvHgZvRxkIqi+Pp0M/kq4DgOjUaDl1566WzH/4gd/+rqKgA7Ozsnbha8wzv+SqWC4zhMJpMTxx7c8fcdkQfesAzaNesNd/y5rPPi7W181xFZ7FWRK26aJpc21ri63GZ35+HP5nE7/ljScFIZsoS6HHOvL7LLJeDySoeLG+K1Pmo1n0sKd3f3KeKQmmXMNfemZROgkcQJcuzOuxNplnPncMq4EKYzNSngfKc6D52pGBp2vUGrXicKPKZT0T6fBTHbQwc3lZgkCpeXGoTOiHbFZPGYxHFpeYU7fYfdvT0MGfxYxNaamoJsVpglsHUwQEoC2hWL5VaFdtUiQ+ILuz574xnRdIgkSay1a/QaNqos0V5YZL3bZDIacndvwDQQue5N2+Dc8iKfvj1gOHEw0pDnz/dozmVRAe3ughhPaAm9ukiy2y7n07Fis++ErNdVktDH0FSRcOcErC/3qNYaxFGEnAh72iNHw74T0FlYZmvgUAQOO8MpRVFgGhrPrLb53m95gXqtynQ65fdevMEf3txHVSUUSebCSpfDUCKJY8LZhJVWhTQDWQE3TKm1e+xPPKRwxnjm061b7I1mrHXrdNoddmcxgefiTKestKqsdWp80+UlnLgglAwoCr74yg0koGKqGKrK0A3pLS7Sn4VoaUgWR1iGGOf4cUq1WufmKMBxZrjOlIkf06hoPL3UZRzFxKpNUUi8b0HDCxM+e3MPP0owNZWFxUUkRYXYp2kIQtzz53rcOpyw72YEhYrr+2xUJdpVmytLTZAkDpyAZmeBTs3kf//UH+L4oZCw1cQ59XoLfOfzF3Adhz+6sUmYCOlfnKSopsX68iKLdRN3MqRTMbnbd3CjmDjJyMyGIDzKEYt1Ewl4fXfM3tglVkx67SZqEWMWMZaucmNPSDvPLbTpdLvc60/I3QmNioFt6nihaPNbjQ6vbA8ZD4fIZFxaaGCbwnt/bXkBVIPPvnqX3f0+cZpRMVV6NZt61WRhcZm6ZWClMwazgOEsoO8EWLrKn/uWF2jVKifuEXvjGfsTn2kisb68QB7H3N7aQZLg/ecXOXQ89iYBlWaHxUaFK035bdnxP/fcc0ynU+r1xysFvqEL/5O8QWd4ZzELhIVqq/Lk6WtBnPLqzv1F0HPr3VNJgF6UMAtiKobG3f6UO4dTNEVowhsVg1v7E1pVYdhyGlHujfDSZn+eQb/SFG5mR1+my0utJ9bnRknGjf0xSSokR36UMHSFKU63Zs1JYF6U8Ed3DtgZuUx9MUetWRqOn7DerdKr2zyz1j35HoQJsgQHUx83SkhKFz2AlVZ1rqn2woSXtwf0pz6LTRtVUXjhXI+Cgr2xN1cUKEh06ha3DsbMQkFc+pNPr7MzcvjSnT4jL0RTFFbaFc516yy3qhQlT+AIYZwSZzk1U2Nv7PJrn7uJX87G/y/f9jSdqlWqM3KmvpjZy7JEw9bnrOtXd4bcGzg4fkS7arF25Kcvga7ILLeqJFnO0AlI8pyFusXEi4izHFNVyIqCu4dTsqJgFoh5sKbIPLve5S986FJpTuTzf372dQ6mHrqi0KiIGNjtkUu3KhzY6rbO3tjDixImnggFujeYUjV08iJnVJLdZFlitSXsg/tOgB+lbPRqXFlu8/w5cf3+7itbjLyILM8xVEGIrJgaM19Yy4rseIM7h44w8bGEz76lqVQsnYETcDB1Gc5C2hWDCwsNpkHMwA3QZIUPX1rkxu4YNxQ2vTVD5YXzC8KzIM9pViwqhnDU2596bA9nJfO+oG6LAvydz57jwkKDm/sT7vWnzMKYiRey2LDFIjAvcIKYoRvQLkmeaZbz6s4ARRZxt0+vdgTBc+ySZQWmrhDGggDYa9gYqsKB46MrCr26xdbQ4WDik+Y5fiTkclkG57o1Xt8d8fuv7xDEKQ3bxDYFYbRq6lxdbvH8uR53+9N5SuDmYIoXpuxPPGxDZa1d48Jik6ZtcHGxyW9++Q4jV3gRLDWqLLUq84yKvbFL0zb5yNUVDqcesyBmuSlieh+UMed5wY39Edd3x+iqeB3PrXeRJNBVFceP+P3Xd8jygm+6tPS22Pe+mbr2Dd3qP8Ojsbe3xyc+8Ql++Id/eN5VeLsRxik398cUZazso/zQH4RUFipVkbF0Qex6EEmacWNvTF4U+FGCUUZjUhRcWmzyla0BqixRK73W7bdgaWtoKlEqnNJqto6q1uk7PjVTf2zRF4U9oGJotKvWPA4URIGuHSuSx1+aVQaujGYBU0BVJF7eGpZ675CPXFm+792eZEyDSOw+Sxe/8wsNsjzncOojz+VOAlvDGVle4MUJYy9iuVkhSlJ0TWGhYc8NbdY7tbLzIAqlFybsjmcYmsaFhSbK0MGLYqwyxaxyioeAqauYpeTwdll8K6aQvLUqJrcPJ8LARZLY6NUZugFRnPKZ6zus9+o8vdrh0lITL0xYa1cpCokPXlhgFsa8sj3ENrTSwwBkRWKjXaNTs1lu5QxnIbvjGWlesNKuMpwFHEw8dFV4C2yPZnz25h7v31jgzv4E21BpVy3qlsgI2Bl7LNZtri63qFcMWraBqiji8ytyGrbJlaUWUZpR0RVu7k9Ic/F51CydKBGRv93S86Bm6SRpzhdu77M79tAUia2hS57nhGnGBy8ssN6pkSFif+Mk4/bBmNEsoD/1ibMMQ1W4ttzmfK9GlIjOz4cvLaKrGiM3oG7pREmOpausd+vc608JExXL0IjTnJV2lWdWOwxmIbMg4g9v7vHq7ghVlinynF6zwuHU43yvydgLyfcLPvmVO2wPXaZehKEp3DJUPnptlcVGhTBOuLM/YVcXev3llsUrW0PiLGe1XZvH8F7fGwsJbCG8JuqWQaNiUDV11srgmq3BjM/d3GcaRFxbafNNl1cZuyFDN2Bv4nJv6NCsWPixS5pmuH5GnhVULZ26baAqMue6dV7eGszzAF7fHc8VD2MvpOb4pFlGlAjJX6tUnlQMDVWWWevU+PT1HaZeJO4ruyMq5X1j7Efc7TtcWGhQlLLAewOnzAwx5kqBVi5UJUUhvtB12+B73n/xsfHP7yTOCv8ZTkWSJGxtbT3Ujn87MAti/Fg4gR3tPo/MWGQeDl+5fTiFouDCQpOKqbE9mpV2mglXlpqn+lwn5fMBaIqCLInHNGzB5LUNjfVeHVtXubjQPLXbcOQCd9xPXlh25mwOZjhBRFHAlaUmtq5yMPGIkoyK8fgm2q2DCUmW0yeYy9fGrmD5d+sWl0sPfEoXsSPIssS1lTaXFpv0Zz5f2RwgMUUG/Eiw1PPifirfoLQ6RZKYBcKyVpHluSqAktQ39SPiNJ0vjoIo5fbhlNuHUy4uCCOXI3VFmuXc3J+UUr2IjW6d3311G11V5xn3VqjSsHXWOlXyvBDFPc+5tNhAVZT5ou2glND16hZJmvHsWle4wpWWvHlRzIl8m8MZh7OAaRBzOPH4wIVFhrMAJ4z4zmfOYWgqL20LP/+6pbM7EgzzdtUkzXI6NZu9scdnb+xBUWDoCk4Q8cq2YHlHaUqrYjJxI17eGpBlOSMvEgXC1Li60sLxY/wopm4ZbCw0RBJeXhClguW+3KqSZbm48Zea/OV2lSwThS1IUj5/c0KYZBw6ARtU2R44vL47Yn/qsTtyqZk6h45PUEb43u07vH9jEbnIuVl2hQokFpo213eGxKVT38HMx4kS6rbOQqNCkhVcWqzykcvLvLY7YOiEyLLER6+toCky26MZIzdkcyCSAt12zIv3DvnibRF1a+salqHhBbFwSZRkbF1l6gc0TAM3SEjTvGTLi5FEnuUMHX9uR2toinitU5dZmJBlORNX5ALcORQ77zTLsU0N29BIsmzueS+V8Rq/88oWh1Ph3qgrwu9gOAtKSaxPxdAJ4pTlps3NgwlFXrDQgE7Fmi8evFB0jfwoZeyFwoiqKNgf+3RrQq740taAjV6dLC9oVczSTEnFCcIynyETXhWKIvT6ScqdwylpnnGh12AWREw8sQiomhprnRqSBKvlOYRxysvbwufg/EKDVsXEDeN5FsO7jbPCf4Z3FV6UzHf5pqawULfnBe+0An449Y/thj0ums1ScqRi6eojV8u2obHYqDD1Q1ZaVbo1iyjJsA11bjEsSxKGqp4o+kVRzHfgh9OANBfe2xu9OlGS8freiCBOhS1omRBWAH7prEbZvVhsVB4Z5XrkY5/nBa9uDVEUiaEbUDd1Rm7A77yyxcWFBitlYEq9tHClNDDSVIWVVm0umZr4EYsNm27NJkoyZkHMwdTDi1Kqhk7F0mhVTZI0I5+7yAnsjNwyLCSnauh0axaHjs9gFsw/r4Opx9SPUGWZ5VaFNM95erXDqNyJH7Vhk1KTfGWlzZWlFoos89LWgJe3BlCaEK22qxw6Iv517IVc3xmxP/G4uNjgMzd2uXUwJskKaqZGzTRIs5yitAa2dYUgzsiKnE++eI/9qYut63xls89apyaCdCRp3sYF0a5vV03iNONTL91jf+yhyDLdmkGcFnhhTJQIqZ0XJoRKhmkoDGYhyy2bw6mwj31le4wbREI+qIsku6Wm8GDY6N1vq17fHZEXIkrW8SPyoiCIUpCEq93QDZHLxMThLCJORrhhzPUyq91UZNZ7DdwwRpXFa94eORxMfSQkVloVllsaSZpxa2+CF0XMgpgsFxLAgoJ7h1MuLDTRZImRG/IH13fZGgrv/LEXsjt2GZX6+iQTATf7E497gylDN0CSEBJOScIJI6I0IytS/turOzx3rovRVanbYme+0LQpCsFHuNt3uNsX47Qsy5mlGQ1TR1XluWMhSGwPHEZeTKtq0qmaPLvaxY+Fj36UZnz+9gFfvnuIWkYF27pCxTTQSrXRartKkooOyoWFBnHaZOZHuFFCFGdlAE/G3f6EjW6DNM/RFBlZgu2hw9iL8KOUpYYIOzJikTsxckPqlkHV0NgazqiYeildhadXOuKxmvADeH1vxJfv9VFkkJHYGs4YzkK2hzN6dZutgcOHLi4xDcQ9oVEW96KU4eZ5wb3S/2KpWWGl9Xg579uNs8J/hncV8bEZc5zmov3+GFiGCiUv8WjnvdSszPXqjcesllfb1RP6+KOFxWJDmGvkZbv3OLZHs7lXeF5Au2oy8UM2qDPxQqJE+L4f+czrqoJZFlJVlknzHF1VTnjYP4gLCw32Jh4HE4/hTNxoTVU4nfWdkIHj8bmbe1xabvLUSoeFuk3N0rnXFy3Ei4tNDE383avLLe70pyRZzvW9Ec+tdfGihDDJqFkai02bCwtNvCjh5b0heVGw2q7OLXePrI0VWaZm6Sy3KrhhjG2opFmOqalMvKiM+M2YlfGyY09oq/emHjcPHfbGLpcWhR9/p2rOXfwOJvf5CH4cM/VFodocOGwPnfk8WNcUHD/CNjRW2jXssi39+v64JBGK+fbO0KVdtbhz6DBwAhQ5pGZp3Nqf0C/lh2K3La6ydtXk0mKLvbHL2IuYeGK31q70Sl/5jDhJeX6jx0LDoihEqJCmymwNZ8LxzdAYuT5ZJsiXNUt4FYjOjzPfJTYrBhVTw4sSTE1hN4x5dWfE/nhGmGbYukbN0qmaGkohPPm3xy4zPyojYyXaVYO6pYJUYeAEbI08nlrW54Y6szDmT15bRZIlnj3X4+7hhMHMFxHCmSCWdus2FVNnForieutgwt7YoxuJxd9yq0qOhKrKLDSqhHFKECdESYokSdiGyjNrHS4uNPmvr25yfXtEkeUYhkoQJbhRzHc8dY5uwyq9DXJ+//VdPvniXbZHYmRkqLIgw1likXJluYVRau0Hbji3Qr661OSbLy/hRQlBknJzf8L13RFjL5wHGWVFwcZCk7VOnc3BFEvXuLLcolcXxkuHjs8sEgs4U1dQJJmhGzINRCbCc2tdwiRFkkXIkiorjGXh0hdlGTcPxnSqFt90cRFDUxm4YsH/2Ru7VEufh6IIWetU+ebLS+xPPL5094ClhkWYZIy9iMWmcA0Nk5SpLzz9r++NyAv40MVF0cEpv/9HgUhHOC106p3GWeE/w7uKpm3Qqph4UfJEoTmLjQqGqlDA3NN9qVlhsWG/5dmYoSlcPcUYyPEjvrI5wA1jujVrzrIVBWfGjf0x/bJ9/ux6l179fiwpUEbmxtRM/bFchYZtYKjKvOj2HZ+NhRoNW6f/yjZ+nDILYm7uTlht1bB1DTcUpjVpnjN0A1ZaVQxNJN31pz6WoZWLlYIry02qlo4qS9iGNjdVORp9jN1oXvgXGjZ+30GWJKZeyMtbA0xd5fn1LvsTj6zIUYr7ixhDVWiUxath69w6mOCHEVVTeCMkqZij6+X82lBVKITBz3PrPbJyp2OoCrIklbNQC8eL0FSRHDea+Ug1m/2xy60yYKVXt3lho4ciy4zcgIW6TVBG424NHT59fYe6pVG3DfbGISvtKlVT45nVjuAiRAkNU6dfpuzFuYh/vdBrEMQJnZrFxYUWdw6nfPnuIevdOmudGnEiuiRjV6JdE7vOZsViqVnhc7f2uXMwZeKFrHaqXFlqc22lTb38/Lf6YkE08UR4TpYVaIrMhy4uESYJdUvMoEdeSN8JiDOxa7dNg0bFQldU0jzny/f6ZQfKZ3sodut/5aNP0a4azEJhzrSXuyRBgiLLIqI3SrEMjb4TYGgyNUtDkiS6VRPb0Li00GCpaZNl4IYxkyAS5+IGpFnGZn+GqaksNap4fsosilhp2exOAu4cTFGUbb7nhQuE5Uw8ybK5ja6iyMiyPJ/VC3c9HUNTuLk7JkpSwjhhGog0wl//4q15dHOeCbJlFCdkOdiGwvleE1WW5iS+pabNtZUOS80KB1OPzYHglVxZarHRraOqEn0npCggjAQxtGrqgoVv6Jh6zPmKaOv7bgxFgSJJbA5n/Hcfvsyt/QlhnNGrSxiaQpYV7E5ccZ2UAT+yJLE38WlWDP7kM2tosjw3s9JkGdPQ0BWFqS9IukuNCue6YpOjlRuDoyjp98Je/Kzwn+FUdDodfuRHfoROp/O2Pq8kSVx4kxGUp7ngvROEmMEsECEwcUqew0evraIpMntjj1cPRvO434ZtnPoaDE3B0J5MGWBoypzpvtyqcmWpiSSJjPDJF8XONc0ydkYuz53r4pa8CEqS3xGOCFtH/uUAa+26YJKXdreUC66BE5DlOe3q/fezWTF5n23w6s6I33ttGy9KWGzY+GGMoau8sj3ENFTed26BlbZIJfsvL2/ihQlxkhEmGaqi0DQFUTGnAAn2Sr7DLIgxNJmGbdKtWSRZzgcvLLIzcueJbZ26TdUQRLSdkUunZpLlYnxil1nolq5yZ39C1TZQFbGgaVdNpkGMGybc3J9wcaHOLEyAgiwvaNriBv3//dxNvDBmFkZc6DUI0wxTlTF1jSRN6dQtOmXY0KHjE6U5r++N0VUZq8xQv7TYRC/f98VGBVkCp/R035945OVnEaUp+pEBliyx2qoI05hIWMK6UcyrOwM2ug06VYskFRG8FxYa6KpMkheMZgFZXrDZn5AUBRd7DTRVwQmEE9+9vsO/++x1GpZJzdbZ6DaQJYnhTMjL4ixn4gUkWUoQpRyWvIfVVpXLyx16dfG+1cuuQJjKrLfFwnPohgxnIWHi4wQR5xcaXF5uUjV14jRl6gsP/T98fZ9z7Ror7Rr0CsExaVWJ0gxTU9FVGa2UT373CxfwYxEstNKpsjtx0TUNW9cIs4yxHxGUXSpNUaiYOp2axULdYnMwI89zFPl+F8ctuQFemHDncCo4Q1HC02tdVjs1WhWDLB8iSbBRMv9HXjCP/M3ygksLTe4NHApJYuTFaKrKalGwO3apmDpS2SHs1S22BjOSVHB9dscutw8n7E99mrbBteUWa+06l5aarHfr3NgXLP7hzKdiGjy/0WOjW6dhGyc2A3ZpL35G7jvDO443c5FVKhU+9KEPvePn9LUE29DQFJnzCw3WO7V5YQ6TDLOc1+fFo1fo26MZw1lA3TJORNeG8f1Y2CNIksSVpSZJls+LiKULj/OPXF7m5e0h3ZrNaruKUvry1ywdVVFOKAYaFYO1To2obIn+11e3qRgqz6x1T4xBqqZOu2qyP3bZGc04mApi3cUFoZkOkxRNVciDmDTLMTSVP7pzSN/xWWpWOGz6XF5qsjmY4UcpYSJy5FsVE10V7npXlpoMHJ/ruyOKAt5/rsfuxGWz72DqHrIMeQ6mLhLLfFsU+HO9GtdWOtw6mLDSqomuiW2wNXCYBTGqojD1YxbrFV7e6jOchXRqJpYmRj1xmtGumqx1atwbzGhXLSxd5epKk8/dOuDO4YSJH0IB7XpOlgp+ydWVJpaqCatZCe4eTrlzOMYLRW5AxdT408+eQ9dVKoborhTAYkNk3KuSxMHUY+QFWIbG9Z0RmiLz4uaAhbqNVIi2u6YqSIXM7tQhiIQfft0yeH1vzHDmizbz5SW2Bg5BkqEoMq9sHeLHCU3bxI2EI17F1EhSQS7dGXrcK2akWc63XlnmQxcXKYqCL945ZDB0cIMYXVPRFZEQF+c5siLRn/ksN20RP7w7Kj3yE3RNZbVdJYwS9iY+RSlzBJGfUDV1riw1yfKCNM8xNLEQWSwK/usrW7y6PaRuqSw1KtiG6IKJDlDG67sjDF0lLwqmfiwCjgqJRkVkO8RJynAWMvZDFhoWvUaDTs0mTjPCRJDyunWLpm3iBBFLTZu6pXPoCBlls2KUhLoqG706SZZzYaFBt2axO3bLsR5s9mcEUUqcZLy42UcqJGSgUzNZbNiossyX7/VZbNgsNSt0akKyWTV0pHI0oqsKt/dFbsFR8FCjIr5n6906qiJzr+9wcaHJSrtKqyI6MkGccq/vIEkiy0NTlJJbU4i//ZjR4DuBs8L/DYKdkcvB1MPWNS4/ggl/HI7j8NnPfpZn3vcBatXaO8Y89csELk1RaNg6lq49khT3TiGMUzHbLwNdWg2xU4ySDENTSpOWrEx6q83TAY+kc0c3uMOp0LqPvZBeXWiJD6YeOyMXWZK4tNg8EWYkSRK6qvDazgg/TubSJssQzOyjNqkiy2wOHIqCOSdif+LhlATDp1ba9B2/JBgFTH0ZS9d430ZvvvgoioLBLCBIMm4fTmnaBooio8kyl5dbtCsmTy+36NdMVltVJElioSHY9lLZ4pckicWGTcXUSPOc5WaVbt2iUzVBKnhtZ8QsjNif+Cy1qkzDBFmWqJe7neu7Y1bbYld463Ay7xjsTTz2Rh5/eHO3VFyoXFluc77XoGEZHDgeiiTTrJq8tjdEVSRu7U+4tNhEKscINaNGo2LwrKXjBmJ3fTAJiJOUPM+413eQJRg4KsvtKoYmc+/QEQs8Q3QVbh9O0WWZvSChZevM/Igb+2MWGxWKuo0fCUnjS5t97van7Aw9LFNhpVXF0mQkSWJr4LI3crlzMMU2FNbadS5fbPLa7ggz0KAQn0VRwGgm2vvX98bc2B+jyAqzKIK8AFkS11V5TRiayrWVNmmaoygSL20ORLqbBDd2JwzcgPPdBntjl92Ri6ooQoGi5uiaSkUWoyVNldE0lZEfEsYJ20MXNxJBSrvlfF4GwjynaqjEiRjdTPQYTZH51ivLvH4gdrUFsD92+eRX7jH1Ixwvpl03qRo6dUujKIOztkYz1jo1VlpVXtkeYGgqS02btIC1dpWwjI8uKEgzocJZb1X5rZc2mXgRrYpFgUSvbmEb6pzLkaSCtLc9nFEp43b9KGFnJPw03DAhTjP2Jy6mqvL0WhtFhu2RS17kIqVQkSlSEaajyBKaLM3JuVEiworcKAFJjMUsTeXqaodCEgvAi4vCcjcruxITL0LXFJJckBnFwiMlSlKiNJ9/d3VVmWeSJGnG+TfZBf1qcVb4vwFQFAWHU3GR+XEiSD+PCZEBmEwm/Oqv/ir/fbVLb2nlhNnL24Usz3llZzhP5DvStT+10n5iM58nRRinJGV++oO4uT9md+IxdsN5jvtqu4amyDy92qFuGzz3QOpfGKfCdCfLWW1X6dVsdEUWN5OyoFMy2Sk7BdMgeujvp1k+b+ELOVNMmokbiapIXFlqszdxefFenyBOsQyVjW6DiScCXWxD5bue26BXt9kdufhRQrtqIUsSaZZz6ATzvHQ/StifeIzcgLEX0q5a/P/be/NoSc7yvv9Te/Xeffdl5s6qGY1WVhkhMBgQxjZgiMOPAAp2wMYHYkiMIRYmJCccCFgYIsCxjVkUzIEIm02yCRgwSCAJIQlGC9pmn7n71nt17fX+/njrtuZKM2KErzQjTX3OGdCtW1VdXbe7nvd93uf5fjVFwY+k9/uOsSrjfpHbDy4QJQlBGFPJm/3Z4Jrf/UsumGLvoSWm6x1sXSVJdJbaPZbbLpoi3RqLlkHO1Hnurglu2z9P3jaIooQwSXC9gF3jVWbqDhDRdnxu3T/HXCqEs3WoRBwLHDfEjSIsTUXXEhabTtqaJdPD0/UO0/U2tYLNfLNHMdeh7Qa0XZ9zxwf40s334QUxXhCgo9ALIhIBbcfH82MSpJVq3tKZXe2mg68EXVHwwoSVrst90yvMNx12jw+w0nUxNZWbHpzF9UNQFMZrRSxdrqtXijqHFpsYusJcwyWKDfa2lphZbVMpWGweLPLAbIOibVDNGcy1eggBlq7S9QI6nicNZBQoWDpRDAVLtr/ONbpoqsrYQIGW6zNRKzJT7xImMUudHk4QoQiFRtcjihKEENQKBX7zaduYbXRRU8ls349pOC5DpTzHltvomkKnF1ArmBi6hq4pqJqCFisEiWz1bLkB+Sjm2GqHzUMlxioFZuodgjDigVXZFmibOkES03UD3CCi7WrUihZtL0TXNbaPVBDApoESDcfD9QVBEHFkqU0lb1LMmTKzMVhiaqhMxw8oWDpLzYSVTo+JAVnIh0K/WDRnaOiqIrMaaetguydfX9dUEAIvlEsdzZ7P+WKQp20doeMHtHsBoR9haAqrQYTlRxxabErnxJ40ThKiwAOzdWk6ZErVw0rOYrBkc8nOcSp5E8ePmE/dRLcMl7FNHTeU0unucZ0+zZ5PNZ08mamA1EPPwSdeQy8L/GcBQshqejeIqBbsX0qs5petPE0SgRtG2Ia2zqc+SQT75hrMrXYIEyHbc2xTCu4E4SkH/q4XpLMCi4J9YtGcthtwMG0hHCnn13USCCGIEkHe1GkgneAsXb52mPbxnyg70uz5aTV0xELDYbRSYNfEAG03oGgZ/cC/VsioKkr/i79Gxw1o9jwsXaPrhSy1e3hBzHK7x6bBEomQDc1dL0j9vl3ceoSta9w/swppqnHPpiGKlp5Wq8vCwfFqgblGl/0LTZZa0ls9b2n0vJCibaIIWSQZRLGsaRCCb/7sEF0vYLXrMVLNowiFSj6Hpinsm28wUikws9rm0FKLWx6YxQlCLE3loq0jmLqGpsi2u5GizfmbhhgbKLJQ78p14tEqA6UcP7h3miRJmK07TA4UCKOcXOMNYnpeIPUHuj4Fy2S20aHrhXKt3ZTObI1U0XCwYGEbUiDG0LS+BXA5Z5AkCcdW26y2ZQq+1QupFm0iJ6Fo6hiGBiT4gaxB8FIzoSSRA7FyzqAXhASxShAluGFMNW/h+CFLbZelZg83jNBVBYTCzrFKv96g44c0uj16fih7wU2NtisL+AZLOcbKBeo9j/lWj+FSjnunV+kFISXbIBYJYSwzLA4izQip9IKQmZU2hqbh+DIztFZk6ccJIAWQZhsOcVpcZ+oqo5Uio5UiKx2XphtgCoGiCoIopueHTA2VObjUYKWtsdB2GSlCgkBVFLaNShtmQYKqCIIwJgxj7p1epZm2w02vdhgu56gVpCvh9pEKfhjR6gUohsbMahfL0JisFhivFVO1wjKOF1IPpOytbRqMmHn+v0t3s2+uQc8PmagVWWg6DJfzRLHUXLAM6RQ4NVRGpFm2wVKO+2frckYdRajjNcI4wQ0jlldc4iSm3vFwowgviLnzyBI/O7RE1/OpFXNcuGmQA4tNLEOTha+Kgq5pDJRk0W7blVX6MhugsrVos3VYtgfmLYOVTg/Hl0E+TguBtwyVUwtgec61wD9UsEnSv+lQ6rgYRglJIqQL5RNMFvifpCTpaNw0TlDdOGkAAFCqSURBVKyOdjwz9Q6aqvYFTR5uyfpo6KqKpiq/dOXpgcUmXS/A1DXOnRjoB9G1L+hotUjDcakOlDA0BdvQKOdObVkhiGL2Hl5irtFFVxVeeP5mBkvyOpuO9PuuFW0cL+i3EK5V3q6hpOpwS60e49UChq7RdQOCOKFWsNaJ9/hhxKHFFlGSMFCwmK7Lop8wjoli2cb3cNnfkUo+Fc6RfcI/n16h6XicNznYl2ftuDKNmiSC5XYvba2SAUBXVXaOVVlq9dL+dINmT9ri5i2DnGkwV+9wbKXN9EoHU9fYNVEDBRwv4P6ZFVY7HjlLZ9NAka4vZUYjIVOrW4fKdPyQmeUOS+0eSSJFc+I4QVVVltpdasUcUZxwaLHJcrvH4cUmh5dbiERQypuINNjkTJ28pTPfdDANjY4f8uN9s/T8iAfnGvzOr+wiZ2osND2Wmj32z9eZqBXTQj2ThmOQx8A2VNwooteOaHs+45UCK50eTUcOksZrRTo9n0CTbWK1dK14ruFwYMHvr9H6aYBTgaKlo5LjnIkKJcuiF0YcWe7Q7vl4UYyqqMQixg1DkiRG1zVKtoGiyor4uuNSyVnESUy1YBN3HUQMrZ7Lg3NysDZcyVPJGYShSRQLbFOn0wvwokR+tlIBmuVuj+WWy+GlFm4QYRs6mqoyWSux0u6x1OrhtF0UTaHt+uQMgzhOKOQMcoHGttEanZ4vnf0cDzeIqRVtqoCCIEgHL3lLY6HV4chKG1PXsHSb5bZLIqCcM9k2WiWKBLquM1KSehaqIgc/Ky0XP06IExVNUdF0lUgIllsOXT/EUDW6rtS4GK0W2DJUxgti5hpdijmflVaPINVHMA2N1Y7H5qESC80ubhjJivtQFgIiYGa1w1DJZlVVCOOYXRM1NFWhkreod7100mLJ1k9NRVFkilxVFQZKOQaKJueM15hvONQKNtMrnbT9Nqbr+ZRyFn4Qs+q4mKmIVKVg84LzNnPfTB03DBmvFKkVbeIkIY7lMl7OMpjKSSXOqaFyfz2ftFI/jBLiRPTbhlVVoZyzWGjK5ZbJgSJ+GOOHkSw8FYKFlsPmwfJjLnLeSLLA/yTl8FKLluujALvGB/qWriciSL8gRdvksRaQnjNeY2pq5BHbO6mfdDlnUSva9PyQYytSUW/rcBlT14jihK4X9K+hkw4AcoaOZWhU8xbNns+mgRLnjNfQNRVVUU65ADFOBI2urICebzjcum+e8zcPMVotcHiphQBWuy7njNZYSdW+hsoPBea1YsdawaZWsDm81OoL12xL1bVI0/ELTYe9hxfxo4Sxah4FmKwViRIhK6mj+KR1E2s1C3ONLnsPL+J4ITOrHbaP1VhuOdw/W8cPIvKWSS8IKFgmtq4zWi3QcDxyps6luyaJk4S5usNSS86GBDBWzWNoKlGcsNxxWWk7uGHI1uEKrV7IwYUGbTdgpJyXM1Bdo+OFDJdyaIrKUsclb+p9IRuBYGqkzNOmRoiFVCgEgaGrHFxsstpxWWg5mJpKw5MDkL2Hl9gyXGa+6TC92qZom3TcgIVGl9WOmz7kI+6fXaHnRxxaaDJd75AkUmVwtJKnms9RLXioKGweKrPQ7DLfcFAVQT1dYsgbBitOj3rXQ1VgqJLn3LEBhsp57p9ZZbntsNL1afV8Gl2XiWqBetcjQdD1Qvwo4vBCh0ohYMtImanBIpuqefYtNnG9kKW2LNiSS+xSV94JIhpdj8PLMnjamo6qyjV6RZWKiUEU4wQRRdskimMMTSUVipRLJbrsXx+vlLjt0CLtntRJWGw6xLHASvUozp8cYG8YMd/skqigCkHPldXuGgrFnEmSyF50kQjqPY8wTKgWLPwgQlVVcpZO0Zafo4WGPH8lZxOLmDCKyZs6s6sdWjmTnh8xUskzW++AopA3pTbEcDnPSrvHcvqdQVOo5ix6QYSqqSiq7HaYKFpUchYdL6AXyA4C29RAyDqLWAhZWBgllPMmBUvWF803uunfUKpvur7Pz48tU8zJQlUvlDP1vGWgawozq23qXZnV8yI5yI5iwUEUekGIrqoMFPKyLz9MWGw52IZ8XV1TuWDTMKNVuVSQzMtrqhVspgZLTNe7CCHYOVZj23CZri8HYrumahxcbHHbgXniJOH8TYOPENkxdI3to9V1z5P5psOB+QaWoWPoKpMDRaZSmWR44vv1T0YW+M8AhJC9zV4QMV4rUMk/+vo76Vo9rKnGhf3A3/OlHKqpa7R6Ppoq1yHDqJ3qs5/aOn0ul+Oiiy4il3tke1qcJBxclI5Yq+n63lyj27+mfXN1qkWb4VKeSs6i5fqYmsqx5TaxEBQtKcCxfbSaVpj3uH+2/ojit5NxbLlF0wkYqxXYPFzmvulVirYUR5EpVbs/w08SmSq8YPMQiRBoqgyS+xcaqdRnoS9h6wUP2RqvCfQEUcwP7j3GvcdWiIWc1WuqrLJvuQFz9S6bBor9zMCag95yW7b7xEmCoihMDpbouj4zK/IhO1TOUc2ZHFpoghComkrDcRmt5hmrFlE1eHBulZ4nq+1zpsaR5TZ3HVmmaBsULRMB/c/NvvkG98+sYOoa9Y7HsdU29a5HpWADCooKhqYQxgl3Hllkx1iNuQdnsQ2NSsFmvCoHEsPlHM/cOsr2sRrHVtqcMy5153VFRSSw0OyiCJnSNzUVXVPo+QH3za5S78q6g5YbULRN8qbBWCXPfLNHGCUsNnssd3r4UUwQyUIsObvsoaigqxo5S0+roBN0XcUPpZyxrmsoCJlhSWdZ4HJAbdHyAhZbPVa7Hl0vwPNDVjpSsU9HIRKCOPHwwoT52GHzYJGRcg5dUfj5QpOOJxUFgzih40IiFGpFWZAoElmJ3nQ89LQYUtMgFgKRyNl1LGTv9poojWXo2KqsYnejRKa+FZhb7eKGIUGU4Ecxpq6SaJAzNfZMDqR9/Ga69BMhZEcgSZwQCbm2PVHNU+94dLxADsg0HS+KseKEAdsAodNUBbqq0/VCVM1jvJpnqChFoNpewKHlFgoKRUun7fqsdORA6mlbRjlnYgAvlPoIXriMF0TkbIOSpaNpGnlTZ3KggKbKVLsXxBi6SqsnTXDGawVW2y7P3TXBA/MNakWLXWNVBgpSOnm23iWIEuIkRoiYlhOxP07wIsHOcR0/iJhtdInihPFakYMLDaIENg2VcFPPjTCSdTHjtRJDJWnudenuCZk1GSgyXM6xc7TCj+6fQSCdIi+YGiKMYhabPZquLw1+5hscWmpS73isOh6uH/KccyYZqeRRVYWO62PqKnGiMN90OGd84FGfS8ttl4Wmk6b3fTYNllhbypfSvQqKsl6G+3SRBf4zgAdn6/z08AIrbZfBco5fO3+KkbQN6ET4oVyrX+242Iben5muVe6rikLBMtKHA2wbrrBn02Prxx8eHuY//sf/eMLfibQy+aGfRV9O0/FCloOQ+abDMavNpbsm0nVkWckN0E0f+Ea6ts2jFL89nHunV/jO3UdQ0mzESy7cwpahCgcXGmiaSiVnkUsDTtcLGSrn+rUFmqKkUrEux1ba0sglfcAATAwUmV5pY+iarFRHpiDn6l06XoDjR5y/aZCpoRKDRZuVjsv20QqKohBECUEUc9uBOY4ut0mEoN6VdrvnjNfkjMo2OH9qiMWmw2Axx0VbRuj5Efvm6iy2HAbLOSxNY6XdkzPrhsM5ozUiZK3BUrOHrilEiWC+5aCrCo4XMV93ZLtaanzzwNwq47UCuqbS80KCOMaMNfbPN1FSNcTZlRbTdYdqwaLnR0RxjOuH9HydXhDKVKWqYGo6cSI4stii4XiYhk7LkYFHVVUcL6Kat2mkVd0CgSoUVEXQ9WUr3lAphxCCB+frrHY8uq6PpsiWupV0xhdGoOsKI2oe14/YM1njrqPLdHo+QldltbmqEMdS8TERUh8/CCJmVju4foiKQEHBj2QR30LDQdNUbF2Ts1VFPnjnmz3CeFHOpBWF5Y6H48WYukLelEJEbhDT9UJpTZxKF6uKQsE2Cf2AjifXdA1NQVcVwiSh48qsAgKiJEmdBH38UM7G5TqwghCgqtL+2lKlWt+xlTaaquAGMQXLlAqRmopIpHqdpkIQRXSDkEbHIxGgaSoFS0FBIQhjmr2ALcNlVFXl0EKTKEmo2CY5Q2ex1cUyKrJLBAWBXCpsOB4gsA2DhuMyOVgkThKiKEaIAUzdYDXVVyjYBkMlm4G01a5gmXS9DittF0OXLX9Nx6NoG0wOlZgcKqMI6HgB37n7CHlLij5NDZeZbXSxjVQ+O5Fp+2bXo2ybjFbyLLVd5urSTMkNQhQFzpsckDbFab2Eripp90m+/x2XS1ItekHI7skhCpbeN+vRNZWtozK9vtZBoyqKNB4SUiZ6seUwVpOTo6FSnjsOLaCgkDxKAd5cvcs9x5aJEsFIOSdNrfyIkXK+b4Sla+o6aefTTRb4zwA6fogbxvJD7kfccXCBzalN7Jol6xozKx1+dmSRIIo5b9MguycesoRcU4lKhFwrXiuQc3y51v1YiOOYXq9HPp9H09YPQPS0173e8SjlTGl4M6ijqQr3t1c5vNgkZxkULIN6N/2Saio5Q1a8SklUWZBVK9jSOCNKKI1KV7VeEFFKpTIfznxDpuYSQSp3K+sWyttG8SPZW37X0SW0dG1cSYUyu17AfNoCN7va4YG5Opqq0gsidoxV0VSVSt6iMDnIQtPpt/TYpo4CaUGPTsk2OLYiNcmlTKtNHAt+eN80s/UuOVOTdrBpq1YipCLg1FCJjptQzVtsGS5z7sQgYZxgGhpTg7JtzzRkpmal62JoGh3X5+ezyxRsk/FqnvlmlzgRbBqwmKgWOLTUTAsAFQxFJWdoKApUcgaJENxzbEX2Y6diO03HJ4yl+UitYGGlM+qiBY4XYaZqgv/vzkOIRGGoZLN5qETeMFloOXRcmdpXFPW4rhClX5y02nZpu7JuYbnlkjdNmo7PfMtBJNIYJUwECWDrshI7iWPSLieSWArBrHZ70sehUsDQVZodjyAW5HUV09ZwgwASkXq8e3SDiDBKKNgGtaJFt+fjRtI7IIhjEpGgomDoqgzKccLMqqzPSITULOj5AUJoxAnkLI0gEnhBKNvIShZxnKCoKn4Y0nWTh2SnY4GRfkwdPySMIxRFRUUQJgmWLqWIFUXWQZRtgyCMydsGxZyJoal4gTSiKloGeVuXUrrVYqpYKZhZbSNQ5PfHlyY9pqEyULCYGCjR7PmUbNlqumfTAFGcMFeXhXV1x2e+1UUkcHSly7njNSYGSiy3e7TdHp4fIxTpHZAAB+frzKw6zNQ7eGHE5sGirFMIpU7EYMFiodHFD2Wb3LGlDlEiRZwmthVpewEF2yKIEnZPDHBgocH9M3UsU6VWyDFazTNeK3JBWljXdkNqBSstpoxZ6biUIrOvTRHFCV0/pFawuXTXhJTeRaFgGyfs1OkcJ3TVcX12jj2Uil+j3fNZ6bgMlaQ2gKGp5C39ESI7xZzBeZuGCCO5nHIy7ji0IKWFkwREwlC5wCU7x05abLyG44XEQpyyffdGkgX+M4Ctw2VW2g5JIouA1DTgrXbcRwT++Wa3/yG768gyYZwwVi1Q73i0egGaKmUmt49WWWjKWeHgwwrOgihGT4v91qh3XYIoYSgN0rOzs3zwgx/kve99L1NTU/39vECuaa5J766hqgooMFCyma7rBKGs8l1qy0rjoVKO3RMDfcGaA/N12p506Gs7PglweKEFqtJ36Rut5vuWnfMNhzCWX8DhsjSjuWjLSL96fm1E/+BsnenVDh03YN9cnZ3jNax02WN2tUMpbxLGCQXbxFAVHC9k/3wDQ5eFOKttl7oj1xcVRUFVFHphBEKwe2KAetcjZ8lZYRQLxqoFfrJvjruPLSMEDBRMdk0MEITSuayaN/spcl1RccOI+qLL/vkmY9UCTccjRqR+8zZjtQJLrR5LXWmyo2kqXddnPp1xFCyN+ZZDEMrWuHPGq2wZrqKIhH/86UEiIXXS7zqyLM8tEsJIqsolaQcDYSxdBcdrUg1OKCy1HcIwJk4d8XKWQaPr0erJCu6W46NqEIQJtbwc7DV6Utntgs0jLLZcokgOXtUoZqkji8N6XoAXCXp+QC6tnlZVhSRJaPWkzWkSC3RNwTJ0gjBmdrVL1wso52yKpoEoymAdRBFuGBPGUplPExErTrp8k8SstqUlrW2q9KK4P0B0/RhDk1kwy5IucksdN22/BBW5YF/KWThehKXrmJpcC86pcoBStCIaaU2NqqoQy9GKtJ9RURU1tX9W8dOaGscNyZkaiqpIEx1dFj+GsRyQRHFCNWfheD5RHLPSiRgQFrqqgpAV/UGYULQtoihJZ8I9LF1nrJbnGdtGKOYtHphZlT3zOQND06kWbAbLecIoYrktK8+9ICZBznIv3TVJq+fihzGqplCyDKpFm/FakRvun2Gp6RAL2Xbmh1Ha/6+hAnNNB01R6HhS6yBKdSfWynLkUhjkTIOOK7tR3Chitu5Syrl4QUiz4+EEspVu20gZXVUJYysVqFLZOSpV8Nww4tZ9c/I+FeSsvag9FCTX7J2PZ82mu+eHNLoeiqIwVi30W5GFkG6RiRDS60GDycESfhAyWSuy67h0fiVnMVjMESVJX+L6RFiGhpt2+NQKNoaustDssWPs5AG93nU5sixNeo5fbnyiyAL/GcBQKcfTto6ye2KQnGmw1HLSkeAjR5nD5Vw/sJm61CC/88gSw+U8lqFJBbOBErqmSi3rpiNFM3SNbSNV6o7Lcls+9HZNDMg14eM+hI4XsuMEo+S13+2bryOAgYJUSptrSPvT8WoB25BuebsnBggiqUAm+647+FHE5sEyYRDz4FydAwtNhsu51JvewzZ0ul4gNeyDkI4rtfzrjkvONFK1MZOibfHbz9oJinLCkbKpS73x1bZHwdbZPFTiriOLNJyARCSMRgV2jFbpugFHVtqUcxZ1x2OomGNmpcNCU1YtVwsWI+U8t+6b5+B8k47r0/HmGCkXUFSXat7CC0LqXZe7jy6x0OrJivNKnsFSnqMrHXRVCt3UHY/VrrRaDeKYxYaDHyXEQpqq1PI2edtg+3CVoUqO8QGX3qJssWv3fFBkIaOmwHLbo9nzWdZ7DJVt4rjKWCXPT/bPUc4ZcrCgyqKnKBFSs93QECJBUwRRlBApAj+KKOUtyrbFz2eWaTohvUAuDSVCXpumqMzVY2mu48o2Mj1dyy5YBuWcnNHvX6gzXMohVAVVQJRAL/UsiIRAVUS6Nq6gJFJHvtOTKfS0YxFNlYEFTUl78QMGSzG2oWIbOrZtgDCYqXcxNCU1gtGw0iLSMEoQAsJY4Pd8wkgQCdCUfnQmUQQFXacdy0r/OBHoqLhhTJzEaCoMFHJsHihzbLXNcruHpmpsGiph2wZloOv52KaW2kjLz5tCghfKNL6RCu9oqorjBwShTNdrabV8xwuxdY0okRX40pvexw/l69edAD+K0BSFnKsRhFIpL2/KNXsFhZwts2stN+DOoyuyvsU28fyIhWaXiWqBuXqXMDQIIoGCS6cXyJ59V1oLDxTlc8QLQVEVKqkVbc+Xn5uG45E3dcJIyhp7YUytYFOwDfJ5OUOvlXJYpkHL9TlntMZwRQ7Ue37MpoEiI5UCyy0H1w9xAvlvpi47T7YMl6kWLBQUubwQCaoFm4nBIrvS7p+uF/Rbb3X11JTtbFNnx2iF2w8u0HYD3PkGURxTtA3m6105+EnzNYau4rQjRCLI2yabh8v9Qty2G/RtppXjdDlOxPN2T3LfzGqqaJjW+qTtfSej60nNCCHoL3c+kWSB/wxgue32VZwAzts0iB/F/TY9IURqZZowMVBioJjjln2z3Du9SsN5KJ3lBhHHltu0ewE7RmWQv+foCh0vYHKgyNHlFvsXmqDAWEXa4Q6WcqldpiRIxWPmG11I6wnWcPywn+LsegEzqx3qjlxeUFCkvKyqSPvRjicfLEGEoakst3oULQMnLaAzNZV2z6dgy1aZIEqo5GS7znyjix8m/fW3oi1n3DvGTHKmfkIVQccPObrcwg8jklgQxDGtho+lS81uLQ2eJVsqoLV6Pr20rWil1ZMZhTBG11VUoJIzmW92eWBuheVOD8eX69fWYBHHi9g316CYMzBUhdW0t7ycsxgs5zi60uLAQgNVkcV049UCQSxNYYJQqnl1/RCRCIo5Ez+KGSHPfTMriBnBYktaxy63ewRxjKFqqDWZ3g2ihJyhESWClZbLz6cXuf3AHKoCSx0PhKzA11S59qyrKpahoatytq1pCYoiC+k0BR5YaDC90kGgEEYRedPAUKX9raFLr/muFxCE0kQlSGI8TcENI7p+SJjIpaWcoVHLm7hegBBgqHLJw9Z1EpFgGzKNHgippZ+kQZ90nVxTFXRdS1svZeFcxw3oePL8cZyQNw05v1YVNBXiJEZRdKlAqKlECCIRE4aCOD23AExA01XiGBo9j7YXpBmbBDeU92NN6yJOEmYbHdwwpOkGaIqKvxCRN/S0OyAgSqTZjhCJtGYG6l2PWAhCkVA2rdTyNiERAqEosqbB1KkVbdo9nzBJaPdCFprLfVObnKnRcKSWfKgIokhmYEj1BWSfvxy01Ts99s3XUVAxdYWBgk2tlGfCC7lgaogXXzDFctvlx/tn0TSFjh+jKlC0DKYGSzR7HiPlApV8zDO2jfK0rcM8MLcqq/HjhKJtMFy2WW7J7JdcChDEiWzFvXBqGAU54N80UMQNY+YbDj0/ZKxWJIrj/rLWSDmPpiocWWqhaSpJktB2fMq2QYIsenz6tlGGyjnO2zTU/04PlXLUux49P2R85BcXJbd6PtOrUtvfNnQ0TcGPY5bbLq3eHCttDxSpfjlZk9X2tqFx38wq5ZxFz1tbIgg4sNAAoOkY7Jp49KK+thvIz6Cu9a3CJwcefQZvGxpHUx+CZ1dOzd9jI8kC/wYx3+jS9UKGy7kTmsqs0UlHktWC1S/ei48bHUaJkO5Nx40wVzou06sdllo9DFXlknPGiROkGYWAsbKUd52tdxDpaFP2g0dYhkbHk4OCupB2mI4fyDXW1L50qJSTpitRzKaBEsttty+Usm++wcSmkIJlULB0wrRtbaRSwPEfGqmuFfvVCvLBNhc51AoWd6200xSo/CLumRySqeOen7bRVLHNCkkiGKsV+P7PjzFeK1LvunKZIJY986Dg+hF10WNmtcO20Qp+EHHvzCqmrlEwNYJY4IUhvVDOlr0gpO36VAvSIOautACn44b0/IiuG6Trsjb75uvUHR+RCC6eGiZMpFyvm+rSJwIcP+CH982iqki9cUWkhiZSXc42VA4ttXhwrk7XDbBNnZypcWDep+64JCiQjvDX1teDWBbK+UGcthzGaAoEiSCM5NwkViKajsf2kSpRQdDyfExFFijNrHbxowRNBYEi5V6BRJWzYlNTaLsRphaiqhqqKifAILj76AqLqepYmMSQQDv2pUVvXs4gvTAGEuIE4nR2HsWCMI5xgxjPj1loylS2F8j1ekOBGBmsyzmz76y42OwQxaosDk0/N2rae24ZOnES9WfSiiKL2eJEECbydd3Qx9AUFCHQVFl97wYxtqljGQZaHEvf9+O+b6oC5YItvwduQMOL5CxYAU1TZN96ejFtNyKJHYo5AzdISGKBacpr7Xg+XS8miGISSH3YZRasaBvoqvSgNxRZ5LbUchBCEESyaEymqqXT25qLoRsG+GGCiYKu0h8MxYl8f5quoCTys6ArEEbyxgVJjBel94mEIFYwtJAgcQgjWbC4ZaSCrqlMDZaod325pOCH7ByvIYDFtoehSYdEFGnW1Oj6mLqOH8XkDINtIzV2jCo0HY+ZVdl6J+KAkqWTNw1Wui6xENx9bIW8ZdJxPeqOdPk7umLQ6gUkiWCwaFPOm/0/esv1qRQNinmLbcMVGo6sHZEKnl1W2q7sfCnJNLumSSncR3uukhbZBZEc8uUsne0jVRZbDpWCxaHFpqxnsU2SRPQlcpNEthErikLOlBMtP4r75zz+vx9O05EOgGstwIkQDBRthsu/WPNkzZhJCPk9f6LJAv8G0HGD/ozd8UMuzlsn7EVfavX4yYE5en7ERK3IJTvHsQytv2YdJUna9vEQbTdgsdmj1fPouIEcKS63mUh903VNZdNwiZFKniR1lwoiKShi6Gv69zqj1TyHF1tyFqjJh+D+hSY5U2fnaLVfnU46iJle7QCw2HTYP99gx2iFw0uy4t02dAZLtrT6TEVw1tbQolj2fh9ZalKyZfFSveti6Rozhs7Tto5SK1oyje0G7D2yzG8+fTuDpRxJIqgVLBaCSDpfTQ7S7LrMNxx0XeOOQwsYqkIu9XZfbrusdOTvFRIaPblePTUkhVDmGg5+FDNRLTKRmt20ez43L0ut+jCSClzLLZfllnSuixNB0/U5ttrhwdkGcZJQsjQavYiVtkeUtueFUULZN0HIimrH88k3NbqenOn1fKlT33U9mm6AIgS6rpHECjExXi+SbWCaDBgzXocgPvEDIEn74A8sNUkSOevTlIQokYFPUcBQQShyFksYo6igoGLoSpqKFsRJLAO/qjKz2kXToOfLoq61T6sikOvvjkcoxwLyb5z+Xhz3/0JAL4ww5Ev2fxcBhDGBGuGosgrfSxXdvNRulTToG6p0GyxYGi1HCuf4UYxI5MAGGZceOncs0FXwIrk2n4iIOJaz2UAIRHrNa6iKQiykOVDbDVm7xXr6+oW8QdsN+wWG3SAmSIT8nBnSWjiOBau9AC+1jgW5nKGlWTZNBcvUyKk6IkFaykZxGpjl8kPXi1CViJFKgSSJcYT8u5qGSsnSyOdM/CAhshJ8TWb7TFWl4wWESdivWtd1Bd+TA4C1VYx8Oqg2dCkZLYSUoRYiwdSlxkQvjHC8gCOLDQ4vKVRyJm4YMlIpIATc/OAssYBy3iRKEnaND/CMbWPsHKsx3+jw7b2HeXBulUQBL5JCPcOVAlGckC8YGCqEsc6ustS4L9sm++YbbB4sUSvZVPIWb3jeHn5w3zTfvesofijopsZUA8Vc2tnQ4ehym44XMjVUopnW2pAqZf4iLEPry+VuHZY6HPvm6nRTlcKZlQ6WrrFzrNofIAyXcwgEYZwwmgbsWsGi5Vi4YcTkSdbe1zw4AOJYDk7WuqlOhXLOZLUjBzjlfFbc96Tk+CI59biA74dSq7loS/GKdlooRZoq7wWyL3WtSv541gRyltsuYRRxbLlDLAQDhTJNx+Pp20bYPFTG1NR+6ns0Df7/cs9ROm7AlqEyT9s6QsE2OLTUwk9le0lgudNjoGRzbCXgZ4cWKOUszt88RK1gcf/sKj0tx/DzX4tZrNHseSy3jP661WrH5c7Dsgq3dlxNwWLL4dBii64XsHmwzFK7x0DR4s4jfloZHNN0PCo5q19h3+r53Lp/nqGizVw62k/S9sCcoVMbqfbNLVbbLnlLxw1jNqfe1m4Q0XF9HD+kk66Hr3ac/trZ0SCURjOKwuHFJlEiZD9+qvRWSFXjvDDC0qWPdtvxCaKEds+XFeTIWopeGmRVBLEme/o7bpj6i0c8MNtEURUKpqzMLtgGy60eQSRT2+pxgeOhqnD53h5NskhV5AzBC+L+BiGOW0cUoCSASPopbhJQSSBWSGKZ+paqbPQL03hoFWfddSWk+x237WRzEgEED5sUKdJjhq4X4KYGLA3HI0weeSzp2n8QSpOTKAgQyUOvqQqwDZm9EGn9wNrbTtL/sUyFMJZB/+HzsyQWtByPRrL+d7EAA0EviBAPX45N9R4Gy3mGSzbT9W7fL77/N1m7V4kgihN0FEq2iZPWp3R8+WqmBroqLZajRNr+6pqKIEmdFg0Gi3kGijb1rksxJ6v+R6oFuo5PkMh0fxBJYZmcYaCm6nagMpA3magV8eOELUMVWq5HQkLTkYWZuqYyVLBo93yWWj1mGl2Gijn8UFbDl3NSbGlqqCTVGhWpK+BHslZkrJqn4/kMV/LMNrs4XoRAMFErUinYtHouhqYSxoKiLQV4dFVhvuXQSeto9FSU68H5JrZuMFTJScEhReHiLcPUux7fueso9a7LWK0oHfvSQmMhpFbCYEnO9sMo7quQrv+TySyO4wWMVgr9wuPNQ2Xm6l3ypkHe1BECllqO1P1PhboeXrinqepJ65zWOF7zY6BoM1otYGjS6yA6icz38VQLNnsmZcFt/hQHCxtJFvg3gIJlsG24wnK7J4UfvJCiZfDAXF0KjQi5prN/oSHVo0SCEEVZbJIkGJq2bt36yFKTB2brOF5IL4oYyNsUbWl6cmCxwXmbhji42GLP5CCqAg/O1Wk5nrRMDQKOLnfImToHU9MJN/2QDpflun45Z6Ye4RFzjS6VnMmBhaZc8wwiplfb3J+a57jxCvMtl4Uhh90TA+lM3WOlLag7br+jwPNDDi41yZkGiZD3pFawma93MTSVgm1SyZvcfXSZjutT77jY6RdxZrXN7QfnaTpe2gZUY6IqHwBJLNAUhXrXxTY1hsq2LIYKYp67a4Lv3n2E5bZGvePiRXLaGccJoRAEQZymTjvMrHZJEpl2LdoWs/UusZDpunrHQ9XkvDZnarRcn5W2S5jIOgORCPx0qpguudL2IroLLTSVdQFNiQU9P8SMYDYIiNLjVNl1x8nagZWTBFdDdqARJcf9PhY8vNToRNnCJA18/Z8fh4yipjx0T9Z+VpBp6RhQElnAeKJSJwGIJKHZS1DViFrBYqCQI0wSWo7ff09BLDAUOXLJm5qU2E0EUSL74aNErqMnD7uDGqBojxyYrL22G/GIu66mQSRJ5Gx8oe2mrnzyfALIGwqapvelZ50gwlQFmqrIin9FRVfl9aiqKmsHhNSRQKhyICigZBvUCjmKOZMgThitFtgxWqPtytntfTOrGJqGIO6fVygKo5UCuqoyMVBkarjMRK3EQMGk40W4fsh0apyDgJbjY+saYdrlIITMSg6V8+yaqMkWQstgvFZidrVD2/XxwoRS3qBoGyw0HRodH0NXGSrlyJsh49UCI5UCW4ZL9Pwii60eiy05iO75Ib+yY5yG47N1pEzD8VlqOTipNXXeNDFVjUiTHTH7F5rcun+ew0stonQZ8XnnTjJcKSCEoGgbaZV+xL3TK6mXhsbu4+S/40SKZh1abMl2zlQnRE9lpHeMVVlu9/ptfvONHiPVNWnvX7yEcCJGKgW6XpiqZ0rL5J4f8sBco2+1mwhZDDtaKTxioEJaiHi6yAL/BlHOmxxeajHX6HL30SVUReXwcovBgk0iBJWCxXzDSUf+CaaucnCpyVxDzibGq0Uu2jLMfNPhX35+jJnVTlqkJduEBvI2dx1dopt6he8YraKqiixIUeCOAwscWGygKVKco5yvMFIppEsAcGS5hRfGPOeccZq9oG8MAjLlHscxLcdjueMys9Kh3ahTXrmfmbHzQJnoV+7HieDnx1aoOz7tnvTGBllIdmiphalrjFULmLqCpqnMrHSwTYMw9jm81Gb/fIOOG6KnuvylnEXO1Di40JDmJH6IkeraN+9xCROpKbDQlGk1VdWYqBYAwU8OzLNQ79Dq+bhRTJS2o0VxImeG6d/G8UKEItXV3FBlfKBIz5fKZ90gxI9E33e8sVakFa/V/p48WiY8NPtcQxbArQ0G5Dk0QNWU/iDgZOc6EQ+fJa9x8pXHJ5ZErL9DD3+LJwv6a79be39xLOslhko2tbyJriqsdjwZ/NPZuoYgiiJE+gyVy9PyB1vXiKOHMh6mCrah0vEfvbr6eHK6iqGr/WxKyw2JY9k6q6pgpYqYA6U8fhgSJYlsX1QULFNDCCjaZloga8hgj1ymEYCqQbWQo+UGUio6zZZpmppmNAQz9Q6KAn4gBa62j1R4cL5BEKuUcwa1Yo4dwxXmWw6KApauc9HUMIMlm5/sm+fuxSZ5UyMSoq8TsWfzEOOOx8GFJs2ej6VrqArcN11naqjE1uEKw6Ucpq7ScDzm6g5506Rgm/zs8CI9P2KsUiCKBXlLJ2caaR2Rh6GrVPIm+xfq0nfADzm00kLXpAd92TLpWWHqQqgxULK5bPdkmt0wWWz2OLrUpNML6PqypW7P5CBHVtrEiWC51UOkQfLggrR1ToRY5zB6z7Fl7p+ps9p12T5aZfNgaV3mFaCSt1hs9QiimK2jZdw08/po/fmP+lkxdc7fPLRuW7Pn95327ptZ7bdRq6ryqO2Ap4Ms8G8QQsChxSZHV9pSYlSTM/+bHphhsGD1q6stQwdF2md6UcxErUgQSX3phWaeeke2r8kg5LNncoDRap7lltd3D5tvOBRtk5wlTUBm610OL8viFSFkxf6mWoln7RxLLSNjLEPHMnQSAXsmB7j76DL75ps4XtCvBZhe7SAQOH6ALmJsd5VYSFEVxws5tNhCUeXAQsqtykreIIoQKKx2ev1q9KMrbXRAqAoFU6PR9Wm7Ac2uVB0zdJWybRIkCY4X4fsRHT+QkrdRTLQgSBLpJBbFYl2gc7yAQ0sthEhwo5g4Xh98Hj62DtO8sbS6jVhsOnS8kG667KGkgTT8BS04j+nzcNx/x2lgeyryi97Vo93Rhx8bC9mu6KTtlLq6frAUA7oia0oUIaQevgKgEMXpMox4aLDRDR6eA4CcoZAkCoKkX5ewtlZezOmyyh9BwdIRSULLkQZPpiZV+wq2wdbhEvNNhzCW3xUVOcPXNJXtIxUGSzauH7HUcaUpTRDjBzG1ksXUUJkjyy1pO+xFjA9IoZ7FltSpMDUVL5BKirWcRaVgpSl1X1bal/IstJy0tkCl3nHZP1/HD8usdGWRmRfEFC2Das7EDWLCKOElF2zlVc82+OmhBQ4ttlhs9/C8AMvQCZOEasGm5fqM14oMFnM8besID8zV8cJYSjYHChdsHmKh5Uhp8WqBgmWgafK5tnWkStuRrY6trsfkQIkwSji20qKQinHtHKtRtE3mFYe8bbDU6lHvuoxU8rS9kJJt0nJ9fnJgHkPTaPZkIXLJNtk8VKbnRxxZblO0TPZMPKREutCUmdZKziJvGuwaH3jEDNvUNc7fNNiX7fZD+Xl5tDa9x0rJNllSejJ9bz6Uvn801b/TRRb4N4B612Xv4SVm6rIgbqBkM7vSpu2HdN2Qdk9q1VeLNkMlmQK6d2aFoi17xXVVWrautYHceN+0FFgZq+JHMW03wDJU2QojpODPWDVPFCU4Xsj4QIFYCFbbLolIOHeihqqp3H5wgbFKATeMUic3nabjMVvvcDBN7bdSM5W1FrOcphIrMjADmKaG4/lMryRUCwbHVjrM1R1arocQCrYhU5emptB1A5nOVGTBWtcPURXZg+unqcYw/Q7EUYLX9Wg6niwgEw9ZWPTC4GS3Wv4+iJF14yfm0bZ3/JiO75xkj4zTTQJ0/RjX753w75ikctGWJoWqvDAhSvuhZaodDFVBKII4kW10ggQFBUPXKNsWmqamWgcyNb6mu9/zZeC1TIWBUh7Xl+vJQRhRyplsH6lyzliVfM6k5Qa4QcxIOd/vDDc12Y2zc7zGSluuV188NcRtBxfxo4jLdk0yUSthaFKESUnbFCdHypy/eYjVtsvBpSYLzR6VgsXmoRJbhso0HZ+OF1DKGdy+f1EGRM+XioxRzFi1wFA5T86UioyOH/GMVMmy5fhsH61imho7xmrUijbX3PBzTF1FUwxcP2TzwAgFyyBORH+WKoOXjqGqqJbBpsEiOdNgh21galp/Fr497R4oWAYPztXJmdLkxzY0FpoOhi4zIcPlfF/rfqCYQ1MVaTTW86nkLaJE9NUXBZAzNBxdZTxXRFelZsfW4TK6rmJoWlrjIIPr5sEicSJQbHj6tpF+L/7DURRFPp+OM87aSEo5kz2Tg0RJgq4qzNa7aKr6SzubPp5kgX8D+NnhJVY7LpW8SZzA5sES508OcsMD06lYi1zrK1oGo5UcKx1p+FGwDSo5i/M2D6WV8XkemK0zWi0wUs4TxLE0jFBU/CBkx2iVTQMlNg8VGa8UmWs4JAhMTePZ20fJ2wZeENPs+eRNjWOrHeqOSxQlHFios2mgjEAwW+/wwExD2lXmDWZWOtS7PrEQtASU8iZqOlVbqnfpaHIN+chKs68+l8qOE4ayVqzRn9oJIKYXriulgpMUsAW/xGD4zBs/ZxzP2iP1VJcjFMDQFeK1uoC0EJHj6hJ0BWwzfeAnCoahUi3Y0ptClccUbZOp4SIj5SIzqx1mGl1KloEKlFPP+K2jVbYMllnpuMzUO3Rdn0bPp2ybLLZ6CEVgWxaGplGp2jLtHkUMlXL9oJQkgt942jZmVrsEYUy959HoSLvbneNV5lcdjtU7VPMWz9k1wa+dv6U/kLYMnSMrLRbbDgXbZKCU4+Kto3hhzGrHZdNgiYGCjRfJdq8do1XqXdnyeWRJ6lQoioKq6oyUpPHNdL3DC87fLO+jKlt0S2nGJIxl0aSVzmzrqR4+Agq2waXnjHPRlhEURRpPLTQc8pbO5EDqPGkZDBalNPX0ahtdVdk2UnmEj8jUUJmCZRDGSSrMJS2sDy02MXVtnXroWtDdPFjqt3o+c/so++Yb9LyQ4VKeLcMl7NUuiRAUbZOdYzVIu5yMdKCxxrmTg4zX5MAkdxrXzUnfm5V+A4537jvTyAL/BmCkRSZ5y+TiLcOcOzlIkghGqwW+oR1gpeOgqRp7Ng0yXiswX+/ScgNsQ2d8oNBXp+I4hSpFVSgaJiPp2lAYmf0v2/aRimwZCyMqeSkAc+GWkf6HfqXjcnCxSbcXsPfgPPsXWrL/XlcZqeRoOz4rXbmub+kqvfAhvXSQ6mG90KUKuLEgSgtUe0GyPnkroHdcZfgvIgvYpx/lUdbd11Lexwfstep1cdw+hqbI2gVFzr41Ve0X+KkIqkWpAuf4EVEi1hUVKmsFgIo0PjE0BUVTKFlyXb/lStnpom0RxREtVwoC2abGRLWIF6YW05bBaFUWTcmBNGwfrXDJOROymEpRuH9mlSCOZb2I41G0TXaMVhmrFFL714g9E4PMN7scXW0zWs0Tp+1wOVNn92SNXZMDhGnRqKopDBRzhFHMaLXIaLXIQMHmwflV9s01MHWdgUKOpWYPNwj7trMTgyWOLrdZTVPxg6Ucl+wclwOFsSq2obN/vgGKDMwTtQKlnMXkQJHBUg7b0Dm20qZkG5y/eZCWG6Q2ygmxEIyU8yy2euyZHJRKnM5DglKVvEUYywp50pT3rokBDi02Ga8WOXdyqN/Gu2ZPvcbD/eKPF9c5EccHdy+M5Np2tYCC7G9/OLaps2u81v9502CZJJHV+YoiPwN+KO2OAXaMVun5Ub8Tag1NVRkoPvEiOE9mssC/ATxr+xj75uvYhlSFIy3oeNq2UXaM1Vhpy9a5NbvdNVtY29DYOrz+y7VzvEoYx/RSuci1/l1L11hJ3fiqBVu6d6kKcWr5uBb05xpdHpxb5fBSi5lGl5lGl3rH7afYV9reutYtPz7xvCzULOaKOwm1X674JePMQDnu/01d+rVHUYIfxoRpRNYVOdDMmbpszYpkwDZ1nYJl4KWSq6BQyBmMlvNEiWxXtVNRJ1IP+1jE5EwDy5AdG0HqrOaFMY4foqgKUSR9BmqFHOdNDqCpKooCjV6AiqyEPn9qiHrX4/6ZFVklXS2wfaRKwdZZaPbYNT5AEEWMVgtSNho4d2KIVz57J3N1qfX/0qdtpeuFHFlu0eh6jNUKvPC8zbL7xQ/59adto+0GXLxtmKbjUSvYfP/nx+R1Ii2sf/MZ2wmihPlml58eWgRgpJJnRzqbq+QtdF1lolaikjNTmeqAREhRok2pLsdaRTnAWLUg9e81le0j1eMCncmWIRmYjw+UBdtgz6ZBdoxVOZzO+neOVVlu9Ti01KaUM/tFjgNFu9/zPpDO1I9nU/qsuGDz0CM8PDaSWsFmrFrACyPKOfMRniMn4/i1eVkT9VBmQVGUvv14xr8ORRzvr3qW0G63qVQqtFotyuV/nVVilIq15FPjlieSKJZ2rWtBv+l4/PNdR7jryBJLLQddUzm0UMcJz7o/8eOGkfqzPNYyQDXt6fbi9dt0VaazVRV0DQxFxbZke5cXhASRkEI3moJtyeJMS9MxDIVqwaLlhDh+0NdYV1Eo5UzOmxrE1DQOLbYgFQ8K44RNtQKWrnJkuUPD8aSlqSZVHCt5i7YbUMubCBTOnZSD2GMrbQ4sNDA0nR1jFV7+jB2U8xYtx2Ox3WOx6XBwsYUfxhRMjUgoTA2WMHSpWx+EMXXHY6xa5PxNg9x+YIFmz2P3xCDP2D7Cctvta1YUbYOcZTBczHNspcNCq4MfJuzZNEA1L93o1pwbwyjm3pkVbrx3hoJtMDlY5Dk7J9Y5Ufb8kOmVNqqqsG2kuu47KoRgue0iEBQsg4bjcWy5w3LLQdNVLtkxxmjqnS6E4PBSi47rsyMtUjsRSSKX0la7HuO1Qr+au9H1OLrSxtBUdoxWiBM5EFvL4jleSKMn0/AnkqQ+EUIIFls9/DBirFro68THac3DE/08yji9PJa4dtoD/0c+8hGuvvpqlpaWuOCCC7j66qt5wQtesOHHHM9GBf4kETwwt4oXxpiayrmTg4/Lly2KExZaDrqqMlLOn7AnFKDlePz9jx9k/3xD2lvaBoeXW/T8MDURkeiq7EKIxcnT71oSUgzqdM0BYnVjR9naw9LJJ+thfzTMtKk6eFgENhSwLQ1FICuaT3BiBdg0UCBOElbbsmVQVWT7l6ZJ45c1XfwkkQ/Scs5g81CZi7aMcO+xZWYbDoaqMDVUJBIqJAm9MKZasKQvgICZepuuJ30GNE1jU62Qtk7K1Os5k4M0Ha+vvf/sHeMcW27z4LzUf9BTSdkgloY0tqERxAkXTQ0zXM5j6Co9L+AH982w2HLQFchZJi84dzM7J2p03IDldq/fxhTFCVPD5dSdUcHQNAbLOQpp0edM3WGh2aWatxks59g+Ukntj3v4YcxA0WbzYJliao4khGC2Ide5h0p5FpodWo7PcKUgLYxzFgowW++gKApbhstSpCdOcPwAS9fX9TKvpcOLtsmOkQp3H1vG8ULmml3GqgX2TA6eUA51eqXNXENKRK9ZLP+yBFGcOuBppyS9mpFxpvCkCfx/+7d/yzvf+U6+8pWvcOmll3LVVVdx9dVXc++997J169YNO+bhbFTg90M541hj98TAKUs2PhYOL7VopOt2E7ViXx73RNy6f5afHVqk3vXYOlTm4GKTffMN/ChhcqBIztQoWTq9MMbxI1xfKuq1ewGWqRGnM016LSaW7sDZ9jzs8jAi7aSu5HVKeZMgiGn2AoIoxA0Sen4k5YB1qXudt3TGqwXyps6t++dxw4hqzuL5500SJwpNx8ULpXmLrirSHz0WGIbKhZND5HIGdx1eotkLGK/lUBUNxwupFW22jVSIRUK943FwoZE6+eW55JyJVPlLYbxW5NhKi1senGewZFGyDWZWuyx3XJ6zc4KpkQrdnuzlD1Ob4UrRYrBUYKHlSKOgQLYpjpTzDFdybBmq9AddQgj8KKbrBqnLGMzUHVRFmov4UZwODOu0en6qECYdFBtdn2LOoGCZ9IIQN4io5qWefBhJzX5TVxks5fuvNVPvsNJ2GSjaTA2V10lCJ4lsr9Q1Bdtc//kTQrDScYlTOWRS2dsgitf5j8eJTP/bhn7SgeUTQZKI/usvNKXCmqnLgrKcmaV5MzJOxpMm8O/evZuXvexlfPzjH4f0ITU1NcUb3vAGPvzhD2/YMQ9nI1P9hxalKEbJNtk5Vj2hRv+/lgMLDdqubHEbrRQe1flJpH33bhDiR7I9adVxsTSNsZq0zl3TyZeeAQXaPZ+jy21MQ6NasKXl58oCH/nzP+e9730vE5Ob+oEuihIqhYe8CKTJREzPl3rixVQVUFNl+1SSCPbPNdi3uMpkrcTuiUHylr7uPgkhndjiJKFoP1TE6KZugK2eTyJk4LIMfd2MzvFDhEjIm+YJA5YXRHS8gHLOelxaeH4RawZM/5pZaEZGRsYv4rHEtdNW3Fev19m3bx8f+tCH+tsUReGFL3wht9xyy4Yd83izfbRKnCSP64N982BJmqqoCqO/oCd0rQDm+CKY4YcdoylKWsErf64UbC56WBGQ23zoo7G2fPHwFp611zMNHdN4aP/j07eqqrB70wC7N53c2lJRlBOua+bS7MmjaVn/ogyLbeqnVRozC/gZGRlnGqftqbSwsADA8PDwuu0jIyMsLi5u2DEAvu/TbrfX/dtIHu+Hu2VIvemtqVhGRkZGRkbGL8sZF0WS1PZ0I4/50Ic+RKVS6f/bvHnzBlzpUxvTNNm2bRum+cRbRmZkZGRkPH6ctsA/Pj4OwNLS0rrty8vLjI2NbdgxAO95z3totVr9f9PT0xvwDp7ajI2NceWVVz7qfc3IyMjIePJx2gJ/rVZjz549/OAHP+hvE0Lwgx/8gOc+97n9bUmSEKciM6d6zMOxLItyubzuX0ZGRkZGxtnIaU31v/vd7+Zzn/sc1113HUtLS7zrXe+i3W7z1re+tb/PW97yFi6++OLHdEzGv55jx47xh3/4hxw7dux0X0pGRkZGxgZyWiV7/8N/+A90Oh3++I//mMXFRS688EK+853vrFuD1zQNXdcf0zEZGRkZGRkZJ+a0K/edDjayj/+pyrFjx/jgBz/Ie9/7Xqampk735WRkZGRkPAqPJa6dcVX9GRkZGRkZGY8fWeDPyMjIyMg4i8hS/Vmq/4SEYUij0aBWq2EYmUZ6RkZGxpnMk0KyN+PMxjAMRkZGTvdlZGRkZGRsMFmqP+OErKys8NnPfpaVlZVT2DsjIyMj48lCFvgzTkiv1+O2226j1+ud7kvJyMjIyNhAssCfkZGRkZFxFpEF/oyMjIyMjLOIs7K4b62RYaPteZ9KdDodgiCg0+lk9ykjIyPjDGftOX0qjXpnZTvfzMxMJvGbkZGRkfGUY3p6mk2bNj3qPmdl4E+ShLm5OUqlEoqinHCfdrvN5s2bmZ6eznr9f0mye7gxZPdxY8ju48aQ3ceNYaPvoxCCTqfDxMQEqvroq/hnZapfVdVfOCJaI7Px/deT3cONIbuPG0N2HzeG7D5uDBt5HyuVyintlxX3ZWRkZGRknEVkgT8jIyMjI+MsIgv8J8GyLP77f//vWJZ1ui/lSUt2DzeG7D5uDNl93Biy+7gxnM77eFYW92VkZGRkZJytZDP+jIyMjIyMs4gs8GdkZGRkZJxFZIE/IyMjIyPjLOKsDfxxHHP33Xdzzz33kCTJ43bMU50wDNm7dy/333//KR/TbDbZu3dvZvl7HK7r8tOf/pQDBw485mPvvPNObrrppsflup5sdDod7rjjDo4cOfKYjpuenubOO+8kDMPH7dqeTDSbTe644w5mZmZO+ZjFxUV++tOfcvjw4VOSjT0baLfb3HzzzczNzZ3yMSsrK9x+++0sLi4+fhcmzkJ+9rOfiS1btojJyUkxNjYmduzYIe65554NP+apzve//30xOjoqtm7dKgYHB8VFF10kjhw5ctL977vvPvFbv/Vbolariac97WmiUCiIV73qVaLVaj2h132m8bWvfU1UKhWxc+dOUalUxHOf+1yxvLx8Ssd+73vfE7quC0CEYfi4X+uZzKc//WmRz+fF7t27RaFQEL/xG78hut3uox5z7Ngx8YIXvEBUq1XxrGc9S2zfvl1897vffcKu+UzkIx/5iLBtW+zZs0fkcjnx2te+Vvi+f9L9u92ueMUrXiEKhYJ4xjOeIYaHh8UFF1wg7rvvvif0us8kjhw5It7ylreIsbExoeu6+F//63+d0nF/+qd/KizLEuedd56wLEu87W1vE0mSbPj1nXWBPwgCsX37dvG7v/u7QgghkiQRr3nNa8S5554r4jjesGOe6rRaLTE4OCj+y3/5L0Kk9+jXfu3XxPOf//yTHnPdddeJf/qnf+r/vLCwILZv3y7+4A/+4Am55jOR6elpkcvlxMc+9jEhhBCdTkdcfPHF4jWvec0vPHZxcVFMTU2JP/7jPz7rA//dd98tVFUVX/rSl4QQQiwtLYmtW7eKt7/97Sc9xnVdce6554qXv/zlwnGc/nFf/vKXn7DrPtO44YYbhKIo4p//+Z+FEEIcPXpUjIyMiP/xP/7HSY95//vfLwYHB8Xc3JwQQgjf98ULXvAC8eIXv/gJu+4zje9+97vir//6r0Wn0xGDg4OnFPivvfZaYVmWuO2224QQQtxzzz2iUCiIT33qUxt+fWdd4P/Od74jAHHgwIH+tjvvvFMA4kc/+tGGHfNU5+/+7u+EYRii0Wj0t337298WgNi/f/8pn+dd73qX2LNnz+N0lWc+V111lajVauuC9v/5P/9H6Lq+7t4+nCRJxMte9jLx4Q9/WHzhC1846wP/O9/5TrFz58512z784Q+LSqUioig64TGf/exnha7r/YCVIcQb3/hG8ZznPGfdtne9611iy5YtJz3m7W9/u3jWs561btuf/MmfiIsuuuhxu84nE6ca+F/60peKV73qVeu2XXHFFeJXfuVXNvyazro1/r1791KpVNixY0d/28UXX4xpmuzdu3fDjnmqs3fvXrZv3061Wu1vu+SSS/q/O1XuuOMOdu7c+bhc45OBvXv3ctFFF6HrD9lmXHLJJURRxD333HPS4/7iL/4C13V597vf/QRd6ZnN3r17eeYzn7lu2yWXXEKr1eLQoUMnPOZf/uVfeOYzn8nY2Bj33HMPDz74IFEUPUFXfGZysvt49OhRGo3GCY/5oz/6IxYXF3nf+97H9773PT71qU/xxS9+kfe///1P0FU/NTjZvb/zzjs3vGbirDPpqdfrDA4OPmL74OAg9Xp9w455qnOie1KtVlFV9ZTvyd/8zd9w00038cMf/vBxusoznxPdx7WfT3Yfb7vtNv7iL/6CO+644xe6cJ0t1Ot19uzZs27bL7qPc3Nz2LbNJZdcguu6dDod4jjmmmuu4fLLL39CrvtM4xd9Hmu12iOO2bFjB7//+7/Pxz72Mb75zW8yPT3Ni1/8Yp7//Oc/Ydf9VOBk9973fXq9HoVCYcNe66x7ahiGged5j9juui6maW7YMU91TnRPgiAgSZJTuidf/epXecc73sGnPvUpLr300sfxSs9sTnQfXdcFOOl9vOKKK3j961/P0aNHuemmm9i3bx8AN99882Oqwn4q8cvcR8MwuPHGG/mzP/szfv7zn3PkyBH+7b/9t7z2ta+l2+0+Idd9pvHL3Mf/+l//K5/+9Ke57777+NnPfsb09DTdbpdXvvKVT8g1P1X4Ze79L8tZF/i3bNnCysoKQRD0tzmOQ6vVYmpqasOOeaqzZcsWZmdn121b+/kX3ZOvf/3rvP71r+cv//IvedOb3vS4XueZzi9zHzdv3sztt9/OlVdeyZVXXsmXv/xlAN773vdy4403PgFXfebxy9zHrVu3MjIywqtf/WoAFEXhD//wD2k0Gvz85z9/Aq76zONk99EwDMbGxk54zD/90z/xb/7Nv2FiYgIA27Z585vfzM0333zWZkR/GU5278fGxjAMY0Nf66wL/C9+8YsJw5Bvf/vb/W3XX389qqryohe9qL/tlltu6c+eTvWYs4nLL7+cxcVFbrvttv626667jmKx2J/Bx3HMTTfdxNLS0rp9/t2/+3d84hOf4C1vectpufYzicsvv5y7776bo0eP9rddd911TE5O9lPXruty00030Ww2IV2bvummm/r/3ve+9wFwww038IY3vOE0vZPTy+WXX84Pf/hDWq1Wf9t1113H05/+9H76tNVqcdNNN+E4DgC//uu/TrvdXje7X/vODw8PP+Hv4Uzg8ssv5zvf+Q6+7/e3XXfddbzwhS/sB5/V1VVuuumm/kRoeHj4EZmm6elpTNPcMJ/5pyLz8/Pr9Dcuv/xyvvnNb67TiLn++usfn2WnDS8XfBLw1re+VYyNjYm/+7u/E9dcc40YHBwU73znO9ftY1mW+NCHPvSYjjnbePWrXy127twprr32WvFXf/VXolAoiKuuuqr/+0ajIQBxzTXXCJG2uJimKX7v935P/OhHP+r/+/GPf3wa38XpJY5jcdlll4mnP/3p4qtf/ar4yEc+InRdF5///Of7+9x///0CEN/61rdOeI6sql+25p133nniV3/1V8U3vvEN8d/+238Tmqatu2c/+MEPBCD27t0rRHrvn/e854mXvOQl4h//8R/FF7/4RbF9+3bxO7/zO6fxnZxe6vW6mJqaEr/5m78prr/+evHOd75TmKa57jv6D//wDwIQ09PTQqQ6FIqiiCuvvFL88z//s/jLv/xLUavVxH/6T//pNL6T00u32+0/3yqVinjHO94hfvSjH63TNvjkJz+57nt77NgxMTg4KF73uteJ66+/XrzpTW8SpVJJPPDAAxt+fWddcR/AJz/5Sc477zy+9KUvoSgKH/jABx4x+7zsssvYvHnzYzrmbOP//t//y9VXX83nPvc5LMviU5/61LoZp67rXHbZZYyOjgJw4MABnv3sZ7N//36uvPLK/n6lUolvfetbp+U9nG5UVeVb3/oWH/nIR/jrv/5ryuUyX/3qV9etj+bzeS677LITFlYBjIyMcNlll6EoyhN45WcWtm1z44038ud//ud88pOfZHBwkO9+97v82q/9Wn+fSqXCZZddRrFYhPTef/vb3+ajH/0on/jEJyiVSvzJn/zJWf29rtVq3HLLLfz5n/85V199NePj4/zwhz/kV37lV/r7DA0Ncdlll/XtZF/96lfzwx/+kGuuuYaPfOQjDA0N8fGPf/yszT6RzubXnnEXXHABP/3pT/npT3/Kr/7qr/I//+f/BGBiYmLd93bz5s3ceuutXHXVVVx99dVs2bKFH//4x+zevXvDry+z5c3IyMjIyDiLOOvW+DMyMjIyMs5mssCfkZGRkZFxFpEF/oyMjIyMjLOILPBnZGRkZGScRWSBPyMjIyMj4ywiC/wZGRkZGRlnEVngz8jIyMjIOIvIAn9GRkafw4cPc/311z9u+2dkZJx+ssCfkXGWcujQIf7xH/9x3bYbb7yRt73tbad8jofvf6Jzng6+//3v85WvfOWEv5udneXaa6/l2muv5ctf/jI33HBDZiaTcVaRBf6MjLOU73//+7z97W9ft23btm389m//9imf4+H7n+icTzTtdptXvOIVvOY1r+EnP/nJI35/++2387rXvY5/+Id/4Otf/zrvfve7mZqa4nOf+9xpud6MjCeas1KrPyPjyc7CwgI33HADALlcjt27d3PuueeecN/p6Wn27t3L6Ogoz3rWs9A0jdnZWW6//XYcx+Haa68F4OKLL2Zqaopf//VfB6Ber/Od73yHV77yleTz+f75VldX+e53v8srXvGKdfuf6Jxbt27lyJEjvOIVr6BQKDziHA8/N8D+/fvZv39/37lwdnaWZz3rWUxMTBCGIbfccguO4/Cc5zyHgYGBR7zfL33pS0xMTHDhhRfymc98Zp3O/PF89rOfpVqtAvCe97yHt73tbfz2b/92380vI+Mpy4bb/mRkZDzu3HnnneK1r32teO1rXyte/vKXi1qtJl7/+teLJEn6+yRJIt7+9reLXC4nXvjCF4rnPOc54nnPe55otVri9ttvF89+9rNFPp/vn+e6664T11xzjZicnBRCCOF5nqhWq+ILX/jCute+6qqrxJYtW0SSJOv2P9E5v/rVr4rh4WHx2c9+dt05PvCBD4gdO3asu941PvnJT4rR0VFx/vnnixe96EXikksuEbZti8985jPivPPOEy95yUvEM5/5TDE8PCz27dv3iOOf+cxnig9/+MPi29/+tigWi6LT6az7/de//nUBiEaj0d926623CkDcdNNNv/TfJCPjyUIW+DMyngIsLy+L8fFx8ZWvfKW/7X//7/8t8vm8uOuuu/rbbrnlFrG0tCSEEOLTn/602LJly7rzHB/IhRDizW9+s3jZy162bp+LL75YvOc97znh/ic657ve9S5x2WWXrdu2c+dO8cEPfvCE72XNrvTrX/96f9vLX/7yR1gTv/CFLxRvfetb1x171113CcMwxMLCgkiSRGzbtu0Rg44TBf41a+ODBw+e8JoyMp5KZGv8GRlPUsIw5NZbb+VrX/sa3/ve99i8eTO33XZb//ef//zneeMb38hFF13U33bppZcyPDx8yq9xxRVX8N3vfpelpSUA7r33Xu666y6uuOKKUz7H7//+73PLLbewb98+SAsCDx8+zO/+7u+e9JiRkRFe9apX9X9+znOew9TUFC972cvWbVs75xqf/vSneeUrX8no6CiKovDmN7+Zz3zmMyd8ja997Wtce+21fOhDH+I//+f/zO/8zu+wffv2U35fGRlPVrLAn5HxJOSee+5h+/btvPGNb+Saa67hG9/4BouLi/0ADXDs2DF27dr1r3qdF7zgBUxMTPDlL38ZgC9+8Ys8/elP57zzzjvlc+zevZvLLrusXzz3uc99jpe+9KVMTk6e9JharbbuZ8uyTrjN87z+z77v88UvfpGJiYl+1X6hUODHP/4x999//yNe45vf/CbXXXcd8/PzfPKTn+Tv//7vT/k9ZWQ8mcmK+zIynoS8973v5UUvehGf//zn+9te9rKXIYTo/1ytVlldXf1XvY6iKLzuda/ji1/8In/0R3/El770Jd7xjnc85vP8wR/8AVdeeSV/+qd/yle+8pV1171RfPWrX0XXdZaWlvjGN77R337uuefymc98ho9+9KPr9j++uC8j42wim/FnZDwJWVhYYPfu3et+vvnmm9ft89KXvpQvf/nLBEHQ3+Y4Dr1eD4BisbhuxnwyrrjiCn7yk5/w+c9/npmZGV73uteddN+TnfM1r3kNvV6PN73pTeTzeV75ylee8ns9VT7zmc/wxje+sT/bX/v3/ve/ny984Qvr7kNGxtlMFvgzMp6EvOpVr+KjH/0oH/vYx/jEJz7B85//fHR9fQLvfe97H6qqcumll/KJT3yCq666iuc973m0Wi0AnvGMZ7C8vMwHPvABrr322hOmwwEuvPBCLrzwQt7+9rfzohe9iPHx8ZNe18nOmcvleMMb3sA3vvENrrjiCkzT3ND7cejQIW644YZ1dQFr/MZv/AbtdjtTGMzISMlS/RkZT0KuvPJKNm3axI033ohlWXz84x/n8OHDqOpDY/mhoSHuuOMOPve5z7F3714mJib4yle+0g/cu3bt4v/9v//H9ddfz7333ks+nz+pgM+f/dmf8Y1vfIPf+73fW7f94fuf6Jx79uyBdLDyV3/1V7zpTW961Pe2a9cufuu3fmvdtnPPPXddYR/ABRdc0P/v+++/n3//7/89z33ucx9xvmKxyHve8x7m5+cB2LRpE6997Ws3fPCRkfFkQRHHLwpmZGRkPE68853v5JZbbuHWW2893ZeSkXFWk834MzIyHld+9rOfcfPNN/M3f/M3WeV8RsYZQLbGn5GR8bhy1113cfvtt/O3f/u3vPzlLz/dl5ORcdaTpfozMjIyMjLOIrIZf0ZGRkZGxllEFvgzMjIyMjLOIrLAn5GRkZGRcRaRBf6MjIyMjIyziCzwZ2RkZGRknEVkgT8jIyMjI+MsIgv8GRkZGRkZZxFZ4M/IyMjIyDiLyAJ/RkZGRkbGWcT/D/jJOWSMz+urAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 520x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "activity_tab = wells.uns[\"mantispy\"][\"activity\"].set_index(\"Metadata_Perturbation\")\n",
    "repl_tab = wells.uns[\"mantispy\"][\"replicability\"].set_index(\"Metadata_Perturbation\")\n",
    "screened = sorted(genes_screened & set(activity_tab.index) & set(repl_tab.index))\n",
    "phenotype = (\n",
    "    pd.DataFrame(\n",
    "        {\n",
    "            \"activity\": activity_tab[\"score\"],\n",
    "            \"replicability\": repl_tab[\"score\"],\n",
    "            \"activity_called\": activity_tab[\"is_significant\"],\n",
    "            \"replicability_called\": repl_tab[\"is_significant\"],\n",
    "        }\n",
    "    )\n",
    "    .loc[screened]\n",
    "    .dropna()\n",
    ")\n",
    "# The mAP a gene needs to clear q < 0.05, read off the genes called on each axis.\n",
    "activity_cut = phenotype.loc[phenotype[\"activity_called\"], \"activity\"].min()\n",
    "repl_cut = phenotype.loc[phenotype[\"replicability_called\"], \"replicability\"].min()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5.2, 5))\n",
    "ax.scatter(phenotype[\"activity\"], phenotype[\"replicability\"], s=6, alpha=0.25, color=\"#3a7ca5\", edgecolor=\"none\")\n",
    "ax.axvline(activity_cut, ls=\"--\", lw=1, color=\"0.4\")\n",
    "ax.axhline(repl_cut, ls=\"--\", lw=1, color=\"0.4\")\n",
    "ax.set(xlabel=\"activity mAP\", ylabel=\"replicability mAP\", title=\"A phenotype vs a replicable one, per knockout\")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c006",
   "metadata": {},
   "source": [
    "4,715 of 7,971 knockouts stand apart from the controls, but only 1,175 are told apart from the other knockouts\n",
    "by their own wells. Many genes have a phenotype, and fewer have one that sets them apart from other knockouts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c007",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:31:42.493675Z",
     "iopub.status.busy": "2026-10-21T00:31:42.493527Z",
     "iopub.status.idle": "2026-10-21T00:31:47.874592Z",
     "shell.execute_reply": "2026-10-21T00:31:47.873683Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7971, 595)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genes = per_gene(wells)\n",
    "genes.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c008",
   "metadata": {},
   "source": [
    "## Do subunits of one complex look alike?\n",
    "\n",
    "{func}`~mantispy.ds.corum` returns the human protein complexes of CORUM, as the benchmark of\n",
    "{cite:t}`Celik_2024` distributes them. Two genes of one complex count as a related pair, and\n",
    "{func}`~mantispy.metrics.known_relationships` asks how many related pairs land in either tail of the map's\n",
    "similarity distribution. `n_permutations` measures chance on this map by shuffling which gene each annotation\n",
    "row names."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c009",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:31:47.876733Z",
     "iopub.status.busy": "2026-10-21T00:31:47.876567Z",
     "iopub.status.idle": "2026-10-21T00:31:58.382234Z",
     "shell.execute_reply": "2026-10-21T00:31:58.380703Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tail width (%)</th>\n",
       "      <th>shuffled annotation</th>\n",
       "      <th>observed</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.038</td>\n",
       "      <td>0.133</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.143</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.253</td>\n",
       "      <td>0.371</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tail width (%)  shuffled annotation  observed     p\n",
       "0             1.0                0.038     0.133  0.01\n",
       "1             5.0                0.143     0.259  0.01\n",
       "2            10.0                0.253     0.371  0.01"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "complexes = mt.ds.corum()\n",
    "rows = []\n",
    "for percentile in (1.0, 5.0, 10.0):\n",
    "    result = mt.metrics.known_relationships(genes, complexes, percentile=percentile, n_permutations=100).iloc[0]\n",
    "    rows.append(\n",
    "        {\n",
    "            \"tail width (%)\": percentile,\n",
    "            \"shuffled annotation\": float(result[\"null\"]),\n",
    "            \"observed\": float(result[\"value\"]),\n",
    "            \"p\": float(result[\"pvalue\"]),\n",
    "        }\n",
    "    )\n",
    "pd.DataFrame(rows).round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "55b84204",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:31:58.385666Z",
     "iopub.status.busy": "2026-10-21T00:31:58.385504Z",
     "iopub.status.idle": "2026-10-21T00:31:58.526539Z",
     "shell.execute_reply": "2026-10-21T00:31:58.525646Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 580x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "recall = pd.DataFrame(rows)\n",
    "x = np.arange(len(recall))\n",
    "width = 0.38\n",
    "fig, ax = plt.subplots(figsize=(5.8, 4))\n",
    "ax.bar(x - width / 2, recall[\"shuffled annotation\"], width, label=\"shuffled (chance)\", color=\"0.7\")\n",
    "ax.bar(x + width / 2, recall[\"observed\"], width, label=\"observed\", color=\"#3a7ca5\")\n",
    "ax.set_xticks(x, [f\"{p:g}%\" for p in recall[\"tail width (%)\"]])\n",
    "ax.set(\n",
    "    xlabel=\"tail width\", ylabel=\"recall of complex pairs\", title=\"Complex subunits land in the tails more than chance\"\n",
    ")\n",
    "ax.legend(frameon=False)\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c010",
   "metadata": {},
   "source": [
    "At every tail width, pairs from one complex land in the tails more often than chance on this map, 13% against\n",
    "4% at the strictest, and no shuffle reaches the observed recall. The chance level is measured rather than\n",
    "assumed: at 1% the tails would hold 2% of random pairs, but the shuffled annotation sits at 4%, as it does when\n",
    "some genes belong to many complexes and most to few.\n",
    "\n",
    "{func}`~mantispy.tl.pathway_coherence` asks the same per complex: are the profiles of its genes more alike than\n",
    "random sets of the same size?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c011",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:31:58.529670Z",
     "iopub.status.busy": "2026-10-21T00:31:58.529506Z",
     "iopub.status.idle": "2026-10-21T00:32:09.070413Z",
     "shell.execute_reply": "2026-10-21T00:32:09.069184Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "135 of 269 complexes coherent at q < 0.05\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>set</th>\n",
       "      <th>n_genes</th>\n",
       "      <th>coherence</th>\n",
       "      <th>pvalue</th>\n",
       "      <th>qvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CCT complex (chaperonin containing TCP1 complex)</td>\n",
       "      <td>8</td>\n",
       "      <td>0.762</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BBS-chaperonin complex</td>\n",
       "      <td>6</td>\n",
       "      <td>0.737</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PA700 complex</td>\n",
       "      <td>6</td>\n",
       "      <td>0.624</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PA28gamma-20S proteasome</td>\n",
       "      <td>13</td>\n",
       "      <td>0.563</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20S proteasome</td>\n",
       "      <td>13</td>\n",
       "      <td>0.563</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>PA28-20S proteasome</td>\n",
       "      <td>13</td>\n",
       "      <td>0.563</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>EIF2B1-EIF2B2-EIF2B3-EIF2B4-EIF2B5 complex</td>\n",
       "      <td>5</td>\n",
       "      <td>0.542</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>PA700-20S-PA28 complex</td>\n",
       "      <td>19</td>\n",
       "      <td>0.515</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                set  n_genes  coherence  \\\n",
       "0  CCT complex (chaperonin containing TCP1 complex)        8      0.762   \n",
       "1                            BBS-chaperonin complex        6      0.737   \n",
       "2                                     PA700 complex        6      0.624   \n",
       "3                          PA28gamma-20S proteasome       13      0.563   \n",
       "4                                    20S proteasome       13      0.563   \n",
       "5                               PA28-20S proteasome       13      0.563   \n",
       "6        EIF2B1-EIF2B2-EIF2B3-EIF2B4-EIF2B5 complex        5      0.542   \n",
       "7                            PA700-20S-PA28 complex       19      0.515   \n",
       "\n",
       "   pvalue  qvalue  \n",
       "0   0.001   0.003  \n",
       "1   0.001   0.003  \n",
       "2   0.001   0.003  \n",
       "3   0.001   0.003  \n",
       "4   0.001   0.003  \n",
       "5   0.001   0.003  \n",
       "6   0.001   0.003  \n",
       "7   0.001   0.003  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mt.tl.pathway_coherence(genes, complexes)\n",
    "coherence = genes.uns[\"mantispy\"][\"pathway_coherence\"]\n",
    "print(f\"{int((coherence['qvalue'] < 0.05).sum())} of {len(coherence)} complexes coherent at q < 0.05\")\n",
    "coherence.head(8).round(3)"
   ]
  },
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   ],
   "source": [
    "mt.pl.pathway_coherence(genes, top=10);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c012",
   "metadata": {},
   "source": [
    "Half of the complexes with at least five screened genes are coherent. The top of the list is machinery a\n",
    "dividing cell cannot do without: the chaperonin that folds actin and tubulin, the proteasome in several of its\n",
    "CORUM entries, and the translation initiation factor eIF2B. The BBS-chaperonin entry is coherent through the\n",
    "chaperonin subunits it shares.\n",
    "\n",
    "## Nearest neighbours\n",
    "\n",
    "A gene of unknown function is annotated by the knockouts nearest to it. Four well-known genes show what that\n",
    "looks like here. `*` marks a partner from one of the query's CORUM complexes, and `^` a gene on its chromosome\n",
    "arm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c013",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:32:09.145739Z",
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     "shell.execute_reply": "2026-10-21T00:32:09.205247Z"
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PSMB2  PSMB3*, PSMB7*, PSMB4*, PSMB6*, PSMA4*, PSMA6*, PSMA1*, PSMA5*^\n",
      "CCT2   TCP1*, CCT6A*, CCT4*, CCT3*, CCT5*, CCT7*, CCT8*, ILF2\n",
      "EIF3B  EIF3I*, EIF1AX, EIF3A*, EIF2S3, EIF3G*, EIF3E*, DDX3X, EIF2S1\n",
      "POLR2A EIF4A3, HSPA5, NXF1, MAT2A, POLR2G*, RAN, ACOT6, WEE1\n"
     ]
    }
   ],
   "source": [
    "def unit_rows(profiles):\n",
    "    \"\"\"The profiles scaled to unit length, so a matrix product gives cosine similarities.\"\"\"\n",
    "    values = np.asarray(profiles.X, dtype=np.float64)\n",
    "    return values / np.linalg.norm(values, axis=1, keepdims=True)\n",
    "\n",
    "\n",
    "unit = unit_rows(genes)\n",
    "symbols = genes.obs[\"Metadata_Perturbation\"].astype(str).to_numpy()\n",
    "arms = genes.obs[\"Metadata_ChromosomeArm\"].astype(object).to_numpy()\n",
    "\n",
    "\n",
    "def neighbours(query, k=8):\n",
    "    \"\"\"The k knockouts most like the query's; * shares a CORUM complex with it, ^ sits on its chromosome arm.\"\"\"\n",
    "    i = int(np.flatnonzero(symbols == query)[0])\n",
    "    shared = complexes[\"source\"].isin(complexes.loc[complexes[\"target\"] == query, \"source\"])\n",
    "    partners = set(complexes.loc[shared, \"target\"])\n",
    "    nearest = [j for j in np.argsort(-(unit @ unit[i])) if j != i][:k]\n",
    "    marks = [\n",
    "        symbols[j] + (\"*\" if symbols[j] in partners else \"\") + (\"^\" if pd.notna(arms[i]) and arms[j] == arms[i] else \"\")\n",
    "        for j in nearest\n",
    "    ]\n",
    "    return \", \".join(marks)\n",
    "\n",
    "\n",
    "for query in (\"PSMB2\", \"CCT2\", \"EIF3B\", \"POLR2A\"):\n",
    "    print(f\"{query:7s}{neighbours(query)}\")"
   ]
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",
      "text/plain": [
       "<Figure size 750x650 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "seeds = [\"PSMB2\", \"CCT2\", \"EIF3B\", \"POLR2A\"]\n",
    "picked = []\n",
    "for query in seeds:\n",
    "    i = int(np.flatnonzero(symbols == query)[0])\n",
    "    nearest = [j for j in np.argsort(-(unit @ unit[i])) if j != i][:4]\n",
    "    for j in [i, *nearest]:\n",
    "        if j not in picked:\n",
    "            picked.append(j)\n",
    "picked = np.array(picked)\n",
    "labels = symbols[picked]\n",
    "block = unit[picked] @ unit[picked].T\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7.5, 6.5))\n",
    "im = ax.imshow(block, cmap=\"magma\", vmin=0, vmax=1)\n",
    "ax.set_xticks(range(len(labels)), labels, rotation=90, fontsize=7)\n",
    "ax.set_yticks(range(len(labels)), labels, fontsize=7)\n",
    "ax.set_title(\"Cosine similarity: four queries and their nearest neighbours\", fontsize=10)\n",
    "fig.colorbar(im, ax=ax, fraction=0.046, pad=0.04, label=\"cosine similarity\")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c014",
   "metadata": {},
   "source": [
    "Three of the four read as their complexes. PSMB2's eight nearest knockouts are all proteasome subunits. CCT2's\n",
    "are seven chaperonin subunits and ILF2. EIF3B's are translation initiation factors: four eIF3 subunits, eIF2,\n",
    "eIF1A and the helicase DDX3X. POLR2A, the largest subunit of RNA polymerase II, finds only one polymerase subunit\n",
    "among its neighbours. Several of the others, such as HSPA5 and WEE1, are genes whose knockouts leave few cells\n",
    "behind, as its own does; the last section measures that.\n",
    "\n",
    "Only one of these neighbours sits on its query's chromosome arm.\n",
    "\n",
    "## Neighbours on the same chromosome arm\n",
    "\n",
    "A Cas9 cut can do more than break one gene: it can truncate the chromosome arm around it. Knockouts of genes on\n",
    "one arm then share a phenotype that says nothing about the genes. jump-profiling-recipe corrects for this with\n",
    "the same loci that fill `Metadata_ChromosomeArm`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c015",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:32:09.616486Z",
     "iopub.status.busy": "2026-10-21T00:32:09.616071Z",
     "iopub.status.idle": "2026-10-21T00:32:11.336256Z",
     "shell.execute_reply": "2026-10-21T00:32:11.335569Z"
    }
   },
   "outputs": [],
   "source": [
    "def same_arm(profiles, k=10):\n",
    "    \"\"\"Share of each gene's k nearest knockouts that sit on its chromosome arm.\"\"\"\n",
    "    arm = profiles.obs[\"Metadata_ChromosomeArm\"].astype(object).to_numpy()\n",
    "    known = pd.notna(arm)\n",
    "    arm, values = arm[known], unit_rows(profiles)[known]\n",
    "    similarity = values @ values.T\n",
    "    np.fill_diagonal(similarity, -np.inf)\n",
    "    nearest = np.argpartition(-similarity, k, axis=1)[:, :k]\n",
    "    return float((arm[nearest] == arm[:, None]).mean())\n",
    "\n",
    "\n",
    "sizes = pd.Series(arms).value_counts()\n",
    "n = sizes.sum()\n",
    "same_arm_fractions = {\n",
    "    \"a random pair (chance)\": float((sizes * (sizes - 1)).sum() / (n * (n - 1))),\n",
    "    \"10 nearest, as published\": same_arm(published),\n",
    "    \"10 nearest, after sphering\": same_arm(genes),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f4596f33",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:32:11.339331Z",
     "iopub.status.busy": "2026-10-21T00:32:11.339157Z",
     "iopub.status.idle": "2026-10-21T00:32:11.430316Z",
     "shell.execute_reply": "2026-10-21T00:32:11.429299Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DUeDTEWRmZuLw4cOIiYlBzZo1Ubt27ZfWP3bsGCIiIjTKrK2t0bVr13yOlOjN9O7dG2PHjsWFCxeQkZGB2rVrY9u2bejcuXNBh0ZE/9GkSRMcP34c3bp1Q2RkJMzMzNCyZUusXbv2ted6o/dLgY5xio2NhYeHB1JSUlCzZk0cPHgQffr0weLFi/PcZvDgwdi7d6/GLdFlypTht3YiIiLKdwXa4zR+/HhkZmbi3LlzMDMzQ1hYGBo2bIh27drleEzAi+rVq8e7EIiIiOitK7AxTiqVChs3bsSXX36pnpDO1dUVbm5uWL9+/Uu3ffToEdatW4ddu3YhJibmLUVMREREH7oC63G6c+cOkpKSUL16dY1yFxcXnDp16qXbXr9+HX/99Rfu3buHM2fOYO7cuRg6dGie9dPT0zVmCVapVIiLi4ONjc0bTeVPRERE7z4RQXJyMuzt7VGo0Cv6lKSAnD9/XgBISEiIRvk333wjjo6OeW53/PhxycjIUC8vW7ZMDA0N5dSpU3luM2nSJAHAF1988cUXX3zxlefrzp07r8xfCqzHqWjRogCA5ORkjfLk5GT1utz8d7p7X19fTJgwAfv27UPdunVz3Wb8+PHw8/NTLycmJsLBwQF37tzJ91mQiYiISL8lJSWhXLlysLCweGXdAkucHBwcYGxsjJs3b2qUR0VFwcnJ6bX2VbRoUcTFxeW53sTEJNcp8osVK8bEiYiIiIBnz158lQIbHF64cGF8/PHH2LBhA57PiHD//n0cOnQIHTp0UNcLDg7G1q1bAQDZ2dm4c+eOxn5CQkJw586dN3rwIhEREZE2CnQep3///ReNGzeGu7s73NzcsGbNGlhZWeHw4cMwNjYGAPj4+CA0NBQXL15EVlYW6tSpg8aNG8PFxQW3b9/GsmXL0K5dO6xbt+7VA7qeSUpKgqWlJRITE9njRERE9IF7nbygQB+5Ur16dZw/fx516tTBrVu3MHz4cBw8eFCdNOHZAxU//fRTAICRkRFOnTqFpk2b4ubNm7C0tMSOHTuwYcMGrZMmIiIiIqUKtMepoLDHiYiIiJ57Z3qciIiIiN4lTJyIiIiItMTEiYiIiEhLTJyIiIiItMTEiYiIiEhLTJyIiIiItMTEiYiIiEhLTJyIiIiItMTEiYiIiEhLRgUdABER0Yfm8OHDOHDgAPr06YMqVaoAAI4cOYL9+/dr1GvatCnatGkDAEhJScFvv/0GlUoFb29vjRmuT5w4gZiYGHTs2PEtt+TDwx4nIiKit+jhw4fw8fHB9OnTce3aNXX50aNHsXXrVhQpUkT9evHZrW3btsWBAwcQFBQELy8vPH9iWkpKCgYMGAAXF5cCac+Hhj1OREREb9HgwYPxzTffYOjQoTnWVa5cGQEBATnKo6OjERERgZiYGBgYGKBcuXK4efMmKlasiHHjxsHX1xeOjo5vqQUfNvY4ERERvSW///47kpKSMHDgwFzX3759G9OmTcPPP/+MiIiIHOuf9zKJCAwMDBAUFIRz585h+PDh+R47/R/2OBEREb0F9+7dw//+9z8EBQXlur5ly5YAgKysLAQHB8Pf3x+zZ8/G8OHDYW9vjxo1aqBz584wNDRExYoVUbJkSXTo0AF//vknwsLCcPjwYTRo0ACtWrV6yy37sBjI8/T1A5KUlARLS0skJiZqDK4jIiLKL5988gnatm2r7h0yMjLCX3/9hfbt2+daf/369ejbty8ePnwIKysrpKWlYf369RAR9OrVCwEBAShTpgwaNmyIbt26oV+/fti4cSPmzp2Lbt26veXWvdteJy9gjxMREVE+CwkJwZEjR1C3bl31GCaVSoW1a9ciLS0Nn332WY5tvLy8kJmZievXr6NevXowNTXFgAEDAADHjx/HiRMncPToUYwaNQqjR4/GmDFjUKdOHaxfv56JUz5SlDg9ffoUv/zyC4KDgxEfH59j/YEDB3QRGxER0XvB3t4e//vf/zTKDAwMYGxsrL5zLiwsDK6urur1e/bsgbGxMZycnDS2e/r0KYYMGYL169fD0NAQBgYGUKlUwLNkzMDA4K206UOlKHEaPHgw9u3bh44dO3IUPxER0SuUL18+x91ykydPRo8ePdSX6ubOnYtHjx6hdu3auHPnDgIDA7FgwQJYWlpqbDdx4kT07NkT1atXBwD07NkTnTt3RnR0NLZt24YFCxa8xZZ9eBSNcbK0tMSJEydQtWrV/Ikqn3GMExERFbTp06fjs88+0+hROn78OE6ePInixYujRYsWqFChgsY2GRkZWLx4MUaMGAEjo//f93H27FkcPnwY9evXR9OmTd9qO94Hr5MXKEqcbG1tERERAWtr6zeJs8AwcSIiIqLnXicvUDSPk7e3N6ZNm4bs7GylMRIRERG9cxT1ON27dw81a9aEsbExKlSokGMgWmhoqC5j1Dn2OBEREdFz+T4dwZdffglLS0t8+umnsLKyUhonERER0TtFUeIUFBSECxcu5LhFkoiI6E0FDRpW0CGQHmr+y+KCDgFQOsbJ1tYWxYsX1300RERERHpMUeLUrVs3fPvtt8jMzNR9RERERER6StGluj179uDSpUtYv349HBwccgwOP3v2rK7iIyIiItIbihKnfv366T4SIiIiIj2nKHGqUaMG2rRpo/toiIiIiPSYojFO7du3h4Lpn4iIiIjeaYoSp0qVKiEiIkL30RARERHpMUWJ07hx4+Dt7Y3Dhw/j4cOHSEhI0HgRERERvY8UjXEaMGAAAKBVq1a5rudlPCIiInofKUqcwsLCdB8JERERkZ5TlDjVr19f95EQERER6TlFY5yIiIiIPkSKepxEBKtXr8bmzZtx+/ZtZGVlaay/fPmyruIjIiIi0huKepxmz56NgIAANG7cGJcuXYKPjw9q1aqFq1evonXr1rqPkoiIiEgPKEqcVqxYgc2bNyMgIAAAMHr0aGzatAmLFi3CtWvXdB0jERERkV5QlDhFRUXB1dUVAFCkSBEkJycDAPr06YPg4GDdRkhERESkJxQlTtnZ2TA2NgYAlC9fHidOnAAA3Lx5U11ORERE9L5RNDj8RT4+PujRowdatWqF4OBgdO/eXTeREREREekZRYlTfHy8+v3o0aNRunRphISEICAgAIMGDdJlfERERER6Q1HiZGVlpbHcu3dv9O7dW1cxEREREeklToBJREREpCUmTkRERERaYuJEREREpCUmTkRERERaUpw4paen459//sHy5cvVZffu3dNVXERERER6R/HM4bVr10aXLl0wcOBAdfmoUaOwbds2XcZHREREpDcUJU6jRo2Cl5eXxnxOAODv749Zs2a91r4ePXqERYsWISAgABs3bkR2drbW24aHh2P06NHYsWPHax2TiIiISAlF8zgdPXoU165dg6GhoUa5i4sLzp49q/V+rl+/jiZNmsDFxQUNGjTA+PHjsXLlSgQGBubY938lJCSgZ8+eiI2NRVZWFjp27KikKURERERaU9TjlJGRAZVKBQAwMDBQl9+5cwfm5uZa72fs2LFwcnLC/v37MWPGDBw8eBCHDh3Chg0bXrmtr68vvvjiC5QvX15JE4iIiIhem6LEyd3dHYsWLQJeSJySkpLg5+cHLy8vrfaRlZWFXbt2oXfv3ihU6P/CqFChAlq0aIG//vrrpdsuXboUd+/exbfffqskfCIiIiJFFF2qmzdvHpo3b45du3ZBRNChQweEhISgSJEiOHbsmFb7uHXrFp4+fQpHR0eNckdHR4SEhOS53cWLFzFx4kSEhIS88nLec+np6UhPT1cvJyUlabUdERER0YsU9Tg5OTnh4sWL6NGjB7p3744iRYrA398f586d0/rSWVpaGgCgWLFiGuWWlpZITU3Nc5sePXpg9uzZORKul5kxYwYsLS3Vr3Llymm9LREREdFzinqcAMDa2hpjxoxRfODnY6ESEhI0yhMSEmBhYZHrNmvXrsW9e/dw8eJFjB49GgAQHR2No0ePYvTo0Zg9e7b6st+Lxo8fDz8/P/VyUlISkyciIiJ6bYoTpzfl4OAAMzMzXLlyBW3atFGXX758GdWqVct1mwYNGiAgIECjzNjYGGZmZrCzs9MYqP4iExMTmJiY6LgFRERE9KFRlDjdvHkTo0aNQnBwcI65nPBs4PerGBoaomvXrlizZg0GDx4MExMTXLx4EcHBwdiyZYu63ubNm3H79m34+/ujTp06qFOnjsZ+1q5di7p166p7oIiIiIjyi6LEqW/fvjA2NsaiRYtgZWWl+OCzZs1Cs2bN0LBhQ9StWxc7d+5Er1690KVLF3WdvXv3IjQ0FP7+/oqPQ0RERKQLihKnkydP4u7du7CxsXmjg5cuXRrnz5/Hzp07ERMTA29vb7Rs2VKjzmeffYamTZvmuQ8/Pz+OVyIiIqK3QlHiVLZsWSQlJb1x4gQApqam+Oyzz/Jc37p165du7+3t/cYxEBEREWlD0XQEEyZMgK+vLy5evIgnT57g6dOnGi8iIiKi95GiHqeqVavi1KlTqFmzZq7rReRN4yIiIiLSO4oSJ19fXzRt2hSDBg16o8HhRERERO8SRYlTZGQkgoKCULx4cd1HRERERKSnFI1xcnR0RGxsrO6jISIiItJjihInHx8f9OvXD2FhYYiPj0dCQoLGi4iIiOh9pOhS3ahRo4Bnj0DJDQeHExER0ftIUeIUFham+0iIiIiI9JyixKl+/fq6j4SIiIhIzyka40RERET0IVLU4yQiWL16NTZv3ozbt28jKytLY/3ly5d1FR8RERGR3lDU4zR79mwEBASgcePGuHTpEnx8fFCrVi1cvXr1lc+WIyIiInpXKUqcVqxYgc2bNyMgIAAAMHr0aGzatAmLFi3CtWvXdB0jERERkV5QlDhFRUXB1dUVAFCkSBEkJycDAPr06YPg4GDdRkhERESkJxQlTtnZ2TA2NgYAlC9fHidOnAAA3Lx5U11ORERE9L5RNDj8RT4+PujRowdatWqF4OBgdO/eXTeREREREekZRYlTfHy8+v3o0aNRunRphISEICAgAIMGDdJlfERERER6Q1HiZGVlpbHcu3dvfPzxx7CysoKR0Rt3YhERERHpJUVjnC5cuAB/f3/18uDBg1GyZEnY2dkhPDxcl/ERERER6Q1FiZO/vz/at28PAIiIiMAff/yBAwcOwNfXF2PHjtV1jERERER6QdF1tdDQUDRs2BAAsG/fPnTu3BkeHh5wdXWFg4ODrmMkIiIi0guKepxMTU1x7949AMCuXbvg7u4OAEhLS0PRokV1GyERERGRnlDU49SpUyd06tQJderUwYkTJ7Bu3ToAwP79+/nIFSIiInpvKepxWrhwIXr37g1zc3Ps3r0bJUqUAACEh4dj0qRJuo6RiIiISC8o6nEqUqQIJkyYkKN84cKFuoiJiIiISC8p6nEiIiIi+hAxcSIiIiLSEhMnIiIiIi0xcSIiIiLSkuLEKT09Hf/88w+WL1+uLns+txMRERHR+0hR4hQVFYXatWujS5cuGDhwoLp81KhR2LZtmy7jIyIiItIbihKnUaNGwcvLC/Hx8Rrl/v7+mDVrlq5iIyIiItIriuZxOnr0KK5duwZDQ0ONchcXF5w9e1ZXsRERERHpFUU9ThkZGVCpVAAAAwMDdfmdO3dgbm6uu+iIiIiI9IiixMnd3R2LFi0CXkickpKS4OfnBy8vL91GSERERKQnFF2qmzdvHpo3b45du3ZBRNChQweEhISgSJEiOHbsmO6jJCIiItIDihInJycnXLx4Eb/++iscHR2hUqng7++PgQMHwsbGRvdREhEREekBRYkTAFhbW2PMmDG6jYaIiIhIjylOnDIzMxEVFYW4uLgc69zc3N40LiIiIiK9oyhxCgoKQq9evRAdHZ3rehF507iIiIiI9I6iu+qGDRuGrl274vbt20hOTs7xIiIiInofKepxun79Oo4fP845m4iIiOiDoqjHydnZOc/LdERERETvK617nBISEtTvR44cif79+2PBggVwcnLSmD0cAKysrHQbJREREZEe0DpxKl68eI6yBg0a5FqXg8OJiIjofaR14hQWFpa/kRARERHpOa0Tp/r166vfd+7cGX/99Veu9V62joiIiOhdpmhw+Pbt23MtV6lU+Pvvv980JiIiIiK99FrTETx48CDX93iWNB07dgylS5fWXXREREREeuS1EqcXk6LcEiQjIyP88MMPuomMiIiISM+8VuJ04cIFAEDNmjXV758zNjZGmTJlXntSzPPnz+OXX35BTEwMatasia+//vql0xmICLZt24a9e/ciJSUFLi4u8PX1RcmSJV/ruERERESv67USpxo1agAA7t+/Dzs7uzc++MmTJ9GiRQv069cPHTp0wC+//ILNmzcjLCwMRYsWzXWbfv36ITs7Gx4eHjAyMsLKlSvx888/49SpU7C1tX3jmIiIiIjyYiAFOOmSh4cHzM3N1YPNExISULZsWcycORPDhg3LdZu4uDhYW1url9PS0mBpaYkVK1agb9++Wh03KSkJlpaWSExMRLFixXTUGiIi0oWgQbn//acPW/NfFufbvl8nL1B0V50uPH36FEeOHEHXrl3VZVZWVvDw8MCePXvy3O7FpAkArl69iqysLDg5OeVrvERERESKHvKrC7dv30Z2djbKli2rUV6uXDkcOnTopduePn0aEydORFJSEq5cuYJ169ahSZMmedZPT09Henq6ejkpKUkHLSAiIqIPTYH1OGVkZAAATE1NNcpNTU3V6/JSrlw5DB48GF9++SWqVauGqVOnIiYmJs/6M2bMgKWlpfpVrlw5HbWCiIiIPiSKe5wyMzMRFRWFuLi4HOvc3Nxeuf3zO+f+u31sbOwrHxJcsmRJtG/fHgDw+eefw9nZGfPnz8fMmTNzrT9+/Hj4+fmpl5OSkpg8ERER0WtTlDgFBQWhV69eiI6OznW9NuPNy5QpAxsbG5w7dw7t2rVTl589exYfffSR1rEULlwYDg4OuHfvXp51TExMYGJiovU+iYiIiHKj6FLdsGHD0LVrV9y+fRvJyck5XtowMDBAnz59sGLFCsTGxgIA9u/fj9OnT8Pb21tdb9GiRfjqq6+AZwPK16xZo5GYHTt2DGFhYXB3d1fSFCIiIiKtKepxun79Oo4fP/7ak13+1/fff49z586hSpUqqFy5Ms6cOYPvvvsOzZs3V9c5d+4cQkNDgWeTbIaEhCAgIADOzs5ISEjA1atX4efnp/VUBERERERKKUqcnJ2dER0djcqVK7/Rwc3NzXHw4EGcP38eMTExcHFxgb29vUadESNGqHugDA0NsXTpUsTFxeHChQswMzND5cqVORcTERERvRWKEqeRI0eif//+WLBgAZycnGBgYKCx/lWDu/+rVq1ar7XO2toaLVq0eK1jEBEREb0pRYlT//79AQANGjTIdX0BTkZORERElG8UJU5hYWG6j4SIiIhIzylKnOrXr6/7SIiIiIj03Bs9ciU6OhpXrlyBiKBq1ao5BnYTERERvU8UzeOUkpKCvn37omzZsnB3d4eHhwfKli2Lvn37IjU1VfdREhEREekBRYmTv78/Tp48icDAQCQkJCAhIQGBgYE4efIk/P39dR8lERERkR5QdKnuzz//xKFDh1CzZk11WZs2bWBvbw93d3csXbpUlzESERER6QXFl+pyG89kb2+PlJQUXcRFREREpHcUJU6urq6YOnUqsrOz1WXZ2dn4/vvv85zbiYiIiOhdp+hS3Q8//IDWrVtj69atqFevHgDg1KlTSE5Oxt69e3UdIxEREZFeUNzjFBkZiSFDhsDMzAzm5uYYMmQIIiMj4erqqvsoiYiIiPSA4nmcbGxsMG7cON1GQ0RERKTHFPU4EREREX2ImDgRERERaYmJExEREZGWdJY4PX78GFlZWbraHREREZHeUZQ4XbhwQePRKoMHD0bJkiVhZ2eH8PBwXcZHREREpDcUP6uuffv2AICIiAj88ccfOHDgAHx9fTF27Fhdx0hERESkFxRNRxAaGoqGDRsCAPbt24fOnTvDw8MDrq6ucHBw0HWMRERERHpBUY+Tqakp7t27BwDYtWsX3N3dAQBpaWkoWrSobiMkIiIi0hOKepw6deqETp06oU6dOjhx4gTWrVsHANi/fz9at26t6xiJiIiI9IKiHqeFCxeid+/eMDc3x+7du1GiRAkAQHh4OCZNmqTrGImIiIj0gqIep8OHD2PChAk5yhcuXKiLmIiIiIj0kqIep/bt20NEdB8NERERkR5TlDhVqlQJERERuo+GiIiISI8pSpzGjRsHb29vHD58GA8fPkRCQoLGi4iIiOh9pGiM04ABAwAArVq1ynU9L+MRERHR+0hR4hQWFqb7SIiIiIj0nKLEqX79+rqPhIiIiEjPKUqcIiMjX7reyclJaTxEREREektR4uTs7PzS9RzjRERERO8jRYlTVFSUxrJKpcK1a9cwevRojBgxQlexEREREekVRYlThQoVcpRVqlQJdnZ28PHxga+vry5iIyIiItIriuZxyoujoyMnxiQiIqL3lqIep9wkJydjxowZKF++vK52SURERKRXFCVORkY5N8vOzoa1tTXWr1+vi7iIiIiI9I6ixGnnzp05yooXLw4XFxeYm5vrIi4iIiIivaMocWrTpo3uIyEiIiLSc280xik6OhpXrlyBiKBq1aqwt7fXXWREREREekbRXXUpKSno27cvypYtC3d3d3h4eKBs2bLo27cvUlNTdR8lERERkR5QlDj5+/vj5MmTCAwMREJCAhISEhAYGIiTJ0/C399f91ESERER6QFFl+r+/PNPHDp0CDVr1lSXtWnTBvb29nB3d8fSpUt1GSMRERGRXlB8qS638Uz29vZISUnRRVxEREREekdR4uTq6oqpU6ciOztbXZadnY3vv/8eDRo00GV8RERERHpD0aW6H374Aa1bt8bWrVtRr149AMCpU6eQnJyMvXv36jpGIiIiIr2guMcpMjISQ4YMgZmZGczNzTFkyBBERkbC1dVV91ESERER6QHF8zjZ2Nhg3Lhxuo2GiIiISI8pTpySkpKwZs0aREREAACqV68Ob29vFCtWTJfxEREREekNRZfqQkJCULFiRUyfPh1RUVGIiorCtGnTUKlSJZw8eVL3URIRERHpAUU9TkOHDsXnn3+OH374AcbGxgCAzMxM+Pn5YfDgwTh9+rSu4yQiIiIqcIp6nC5fvozJkyerkyYAMDY2xuTJk3H58uXX2tf27dvh4eGBGjVqoFevXoiMjHxp/Zs3b2LUqFFo2LAhmjRpgrFjxyIuLk5JM4iIiIhei6LEycnJCXfv3s1RfufOHTg5OWm9n507d6Jbt27o0KEDfv31V4gImjVrlmcilJ2djY8//hgVKlTAokWLMG3aNBw+fBgeHh5IT09X0hQiIiIirWl9qS4hIUH9fsSIEejevTtmzpwJV1dXiAjCw8Mxbtw4jB07VuuDT548GV988QVGjhwJAPjtt99QunRpLFmyBBMmTMhR39DQEJcuXYKR0f8P+7fffkPVqlVx4sQJNG/eXOtjExEREb0urROn4sWL5yj79NNPc5T5+PhgwIABr9xfcnIyTp8+jdGjR6vLChcuDE9PTxw+fDjXxAmARtIEACICADAwMNCqHURERERKaZ04hYWF6fTAd+/ehYjAzs5Oo9zOzg7nz5/Xej/ffvstKlSo8NJHvaSnp2tcyktKSlIYNREREX3ItE6c6tevr9MDq1Qq4Nmg8hcVLlxY4xl4LzN58mQEBgbi4MGDMDExybPejBkzMGXKlDeMmIiIiD50iifAzMzMRFRUVK4Dud3c3F65fYkSJQAAsbGxGuWPHz9Wr3uZmTNnYs6cOdi5cycaNmz40rrjx4+Hn5+fejkpKQnlypV75TGIiIiIXqQocQoKCkKvXr0QHR2d6/rn445extbWFuXKlUNISAg6duyoLj927BjatGnz0m1nzZqF7777Djt37kSrVq1eeSwTE5OX9kgRERERaUPRdATDhg1D165dcfv2bSQnJ+d4aWvw4MFYsWKFeu6nZcuW4caNG/D19VXX+d///oe2bduql+fOnatOmtzd3ZWET0RERKSIoh6n69ev4/jx4zA3N3+jg48dOxZ3795F7dq1YWZmBkNDQ6xduxY1a9ZU13n48CFu374NAIiPj8eYMWNgbm6OgQMHauxrxowZ6N69+xvFQ0RERPQyihInZ2dnREdHo3Llym90cENDQ/z888+YM2cO4uLiULp06RzTDcyYMQNPnz4FAFhaWuLatWu57qtUqVJvFAsRERHRqyiaAHPkyJHo378/FixYACcnpxxzKFlZWb1WEGZmZjAzM8t1XcmSJdXvCxUq9FozkxMRERHp0htNgJnX3EnaDA4nIiIietcU2ASYRES61r17d/Xfqlq1amHHjh056hw5cgRz587F9evX0bBhQ8yePVvdsz1nzhysXbsWFStWxOLFi1G2bFng2XMyO3bsiDlz5qB69epvuVVEpE8KbAJMIiJdW7RoEZ4+fYrFixfj8OHDOdbv2LEDffr0wdSpU9GqVStcunQJM2bMwA8//IDg4GD8/PPP2Lx5M9avX4+RI0diy5YtAID58+ejcuXKTJqISNng8MjIyDzXmZiYwM7OLseM4ERE+e35I5xyG2epUqkwYsQITJ48GcOHDwcA1KhRQ3037unTp9GuXTvUr18fVlZWaN26NQDg6tWrWLNmDU6cOPFW20JE+knxXXUvU7RoUXzxxRf48ccfUaRIEaWxERHpTEREBG7duoVSpUqhefPmSExMRKNGjfDdd9+hVKlSKFu2LDZt2oTs7GyEh4ejXLlyUKlU8PHxweLFi2FqalrQTSAiPaBoAswlS5agQoUK+O2333Dx4kVcunQJa9asQfny5bFgwQL8/vvvOHjwICZPnqz7iImIFLh//z7w7MkDU6ZMwapVq3Djxg20b98eKpUKHTt2hIWFBUqUKIERI0Zg2rRpWLRoEWrVqoUKFSqgY8eOqF27NhYuXFjQTSGiAqSox2np0qXYsmUL6tWrpy6rXr06qlevDh8fH5w9exZ2dnbw9vbGzJkzdRkvEZEiRYsWBZ49jeD5o5p+/vlnODs74+rVq6hatSp2796NuLg4WFpa4tatWxg0aBBOnDiBnj17olatWvj222/RrVs3NGrUKM+7iono/aaox+nq1auoVKlSjnJHR0dcvXoVAFC7dm08fPjwzSMkItKBatWqoVChQrCwsFCXPX+flpamLrO2tkahQoXg4+ODhQsXwtzcHKdPn8bQoUPh6uqKTz75BKdOnSqQNhBRwVOUOFWsWBHz5s3TmK9JRDBnzhx1QnXhwgXUrVtXd5ESEb0Ba2trdOzYEYsXL8aTJ08gIpg7dy7KlSsHFxcXjbpLliyBs7MzPD09AQBly5ZFeHg4srKycPbsWfU0BUT04VF0qe7HH39Ex44dsXHjRtStWxcigtOnT+PBgwfYvn07AGD79u2YMWOGruMlIsrTpEmTsGbNGiQmJiItLQ0VKlRA6dKlERISAgBYvnw5evfuDRsbGxQuXBgODg7Ytm0bTExM1Pu4desWFi9ejNDQUHXZrFmz0L17d2RnZ6NZs2Zo165dgbSPiAqegSic5jsmJgYrVqxAREQEDAwMULVqVfj4+MDW1lb3UepYUlISLC0tkZiYiGLFihV0OESkI3FxcUhKStIoMzIyytFDlJiYCDx7/uV/JSUlISsrC9bW1hrlWVlZSE5OzvUpCqRbQYOGFXQIpIea/7I43/b9OnmBoh4nALC1tcWECROUbk5EpHPW1tY5Ep7c5JYwPZfXH00jIyMmTUSkfeJ09+5d4Nm1/ufv88Lr/0RERPQ+0jpxKleuHPBsEPjz93nhQ36JiIjofaR14hQREZHreyIiIqIPhdaJU9WqVXN9T0TvlibfrivoEEhPHfv+84IOgUjvKZrHCQDS09Pxzz//YPny5eqye/fu6SouIiIiIr2jKHGKiopC7dq10aVLFwwcOFBdPmrUKGzbtk2X8RERERHpDUWJ06hRo+Dl5YX4+HiNcn9/f8yaNUtXsRERERHpFUXzOB09ehTXrl2DoaGhRrmLiwvOnj2rq9iIiIiI9IqiHqeMjAyoVCoAgIGBgbr8zp07MDc31110RERERHpEUeLk7u6ORYsWAS8kTklJSfDz84OXl5duIyQiIiLSE4ou1c2bNw/NmzfHrl27ICLo0KEDQkJCUKRIERw7dkz3URIRERHpAUWJk5OTEy5evIhff/0Vjo6OUKlU8Pf3x8CBA2FjY6P7KImIiIj0gOKH/FpbW2PMmDG6jYaIiIhIjylOnDIzMxEVFYW4uLgc69zc3N40LiIiIiK9oyhxCgoKQq9evRAdHZ3rej7kl4iIiN5Hiu6qGzZsGLp27Yrbt28jOTk5x4uIiIjofaSox+n69es4fvw452wiIiKiD4qiHidnZ+c8L9MRERERva8UJU4jR45E//79ERYWhvj4eCQkJGi8iIiIiN5Hii7V9e/fHwDQoEGDXNdzcDgRERG9jxQlTmFhYbqPhIiIiEjPKUqc6tevr/tIiIiIiPScojFORERERB8iJk5EREREWmLiRERERKQlrRMnT09P9fsVK1bkVzxEREREekvrxOnIkSPIysoCAPj6+uZnTERERER6Seu76qpWrYqxY8fCzc0NALBly5Y863br1k030RERERHpEa0Tp6VLl8Lf3x9r1qwBAPj4+ORZl4kTERERvY+0TpyaNGmC0NBQAICBgQEfrUJEREQfHEV31V27dk33kRARERHpOUUzhzs5OQEAoqOjceXKFYgIqlatCnt7e13HR0RERKQ3FPU4paSkoG/fvihbtizc3d3h4eGBsmXLom/fvkhNTdV9lERERER6QFHi5O/vj5MnTyIwMBAJCQlISEhAYGAgTp48CX9/f91HSURERKQHFF2q+/PPP3Ho0CHUrFlTXdamTRvY29vD3d0dS5cu1WWMRERERHpB8aW63MYz2dvbIyUlRRdxEREREekdRYmTq6srpk6diuzsbHVZdnY2vv/+ezRo0ECX8RERERHpDUWX6n744Qe0bt0aW7duRb169QAAp06dQnJyMvbu3avrGPOUlZUFQ0NDGBgYvLVjEhER0YdLcY9TZGQkhgwZAjMzM5ibm2PIkCGIjIyEq6vra+1rzpw5KFOmDIyNjfHRRx/hyJEjL60fGxuLuXPnwsnJCcbGxq+sT0RERKQrinqcAMDGxgbjxo17o4MvW7YMU6ZMwZYtW9CoUSPMnj0bbdu2xaVLl1ChQoVct1m0aBGSk5OxfPlyuLu7v9HxiYiIiF6Hoh4nXZk3bx4GDBiANm3awNLSElOnToW1tfVL78qbPHky5s2bB2dn57caKxEREVGBJU5xcXG4evUqWrRooS4zMDBAy5Ytcfz48YIKi4iIiChPii/VvakHDx4AAEqWLKlRXqpUKZw8eVKnx0pPT0d6erp6OSkpSaf7JyIiog9DgV6qy41KpdL5XXIzZsyApaWl+lWuXDmd7p+IiIg+DIoTp/T0dPzzzz9Yvny5uuzevXtab1+6dGkAwMOHDzXKHz16BDs7O6Vh5Wr8+PFITExUv+7cuaPT/RMREdGHQVHiFBUVhdq1a6NLly4YOHCgunzUqFHYtm2bVvsoXrw4qlWrhkOHDqnLRASHDh1C48aN1WUqlUpjok0lTExMUKxYMY0XERER0etSlDiNGjUKXl5eiI+P1yj39/fHrFmztN7PmDFjsHLlSmzfvh0PHz7E6NGjkZSUhCFDhqjrDBw4ELVr11YviwiysrLUyVR2djaysrKgUqmUNIWIiIhIa4oGhx89ehTXrl2DoaGhRrmLiwvOnj2r9X769++P5ORkjBo1CjExMahZsyb27dunMQbJ0NAQRkb/P8zff/8dX375pXrdxx9/DACYOHEiJk6cqKQ5RERERFpRlDhlZGSoe3heHMh9584dmJubv9a+RowYgREjRuS5/pdfftFY9vb2hre392vHTERERPSmFF2qc3d3x6JFi4AXEqekpCT4+fnBy8tLtxESERER6QlFPU7z5s1D8+bNsWvXLogIOnTogJCQEBQpUgTHjh3TfZREREREekBR4uTk5ISLFy/i119/haOjI1QqFfz9/TFw4EDY2NjoPkoiIiIiPaAocRo8eDCWLl2KMWPG6D4iIiIiIj2laIzTmjVrNB5hQkRERPQhUJQ4NWnSBPv27dN9NERERER6TNGlOjc3N3z++ecYMGAAqlevjsKFC2us79evn67iIyIiItIbihKn1atXw9LSElu2bMl1PRMnIiIieh8pSpzu3r2r+0iIiIiI9JyiMU5EREREHyJFPU7Ppaen486dO8jKytIor1q16pvGRURERKR3FCVOjx49go+PD/7++2+ISI71uZURERERvesUXarz8/NDdnY2zp8/DwC4du0a/vjjD5QtWxbz58/XdYxEREREekFRj9P+/fsRGhqKChUqAAAqVqwIJycnlC1bFl999RVGjhyp6ziJiIiICpyiHqeYmBiUL18eAGBlZYXY2FgAQL169XD16lXdRkhERESkJxTfVWdgYAAAqFGjBlavXg0RwcaNG2Fvb6/L+IiIiIj0hqJLdS1atFC/nzJlCjp27IiAgACoVCr8+uuvuoyPiIiISG8oSpwOHz6sfu/u7o4bN27g/PnzcHJyUo97IiIiInrfvNE8Ts+VKlUKnp6eutgVERERkd5SnDgdO3YMx44dQ1xcXI51M2fOfNO4iIiIiPSOosRp1qxZ+N///oc6deqgePHiuo+KiIiISA8pSpwWLlyI7du3o3379rqPiIiIiEhPKZqO4MmTJ3B3d9d9NERERER6TFHi1KhRIxw9elT30dA7RUSwfv16NGnSBLa2tmjYsCE2bdqkXv/w4UO0bdsWpUuXxoABA5CZmaled/78eTRt2jTHA6KJiIj0mdaX6lavXq1+X69ePfTs2RNDhw6Fk5OTejLM5/r166fbKEkvhYeH49ChQ1iwYAHKly+PPXv24IsvvoCdnR2aN2+O7777Dg4ODlixYgU+//xz/PbbbxgwYACysrLg6+uLRYsWwchIJzd2EhERvRVa/9cKCAjQWDYzM8OaNWtyrcvE6cPg6uoKV1dX9bK3tzd++OEHhISEoHnz5rh06RICAgJgb2+P9u3b49KlSwCA2bNno2XLlmjQoEEBRk9ERPT6tE6c7t69m7+R0DtNRHDkyBHcuHFDPf7N0dER//zzD1q0aIGgoCB8/PHH+Pfff7Fx40acOHGioEMmIiJ6bYqfVZeamqp+HxsbixUrVuDQoUO6ioveIS4uLjAxMYGXlxemTp2q7oWaMGECAgMDYWZmhqysLHh7e8PHxwdLlizBli1bUKlSJVSrVg379u0r6CYQERFpRdEAk7Vr1+LAgQNYvXo1srKy0KJFC8TExCApKQk//fQTfHx8dB8p6a2wsDCkpaXhxIkT6NevH8zMzDBgwABUrFgRZ8+eRXZ2NgwNDTFnzhy4ubmhSpUqaN++Pfbt24fY2Fj06dMH0dHRMDQ0LOimEBERvZSiHqdZs2Zh3LhxAICjR48iLS0Nd+/exd9//4358+frOkbSc6ampihRogTatWuHzp07Y+fOnRrrDQ0NcfXqVfz222+YOnUqrl+/DkdHR9SvXx8ff/wxDAwMEBMTU2DxExERaUtR4hQZGal+mO/BgwfRuXNnmJiYoHnz5oiKitJ1jKSnfvnlF2zduhUpKSlQqVQIDg7Grl270KRJE416KpUKAwYMwE8//QRTU1OUL18eN27cwJ07d3D+/Hmkp6ejZMmSBdYOIiIibSlKnMqVK4eDBw8iIyMDmzdvVj/g9+bNm3BwcNB1jKSnOnTogB07dsDBwQFFixaFt7c3hg4dCj8/P416P/74I+rUqYPmzZsDAGxtbREQEAAXFxe0bNkSP/30E4yNjQuoFURERNpTNMZpzJgx6NSpE8zMzFC+fHl4eXkBAP744w94e3vrOkbSU/b29li9ejVEBCKCQoVyz8MHDRoEExMTjbJRo0bh66+/hoGBQY55wIiIiPSVosTJ19cXjRo1wu3bt9GiRQt1b0H16tXRqVMnXcdIeu5VyU/RokVzLc8r0SIiItJXiqdtrlGjBmrUqKFR1qtXL13ERERERKSX+JWfiIiISEtMnIiIiIi0xCes5oP/zmNE9Fz79u0LOgQiInoD7HEiIiIi0hITJyIiIiItMXEiIiIi0hITJyIiIiItMXEiIiIi0hITJyIiIiItMXEiIiIi0hITJyIiIiItMXEiIiIi0hITJyIiIiItMXEiIiIi0hITJyIiIiIt6UXilJCQgMjISGRkZOTrNkRERERvokATp6ysLAwYMAC2trZo3rw5SpUqhd9++03n2xARERHpQoEmTtOnT8fOnTvx77//Ijo6Gj/++CP69++Ps2fP6nQbIiIiIl0o0MRp2bJl8PX1haOjIwDA29sblStXxooVK3S6DREREZEuFFji9ODBA9y7dw8NGzbUKG/UqBFOnTqls22IiIiIdMWooA4cGxsLALCxsdEot7GxwePHj3W2DQCkp6cjPT1dvZyYmAgASEpKeoMW5C0tLS1f9kvvvvw6515HVjrPT8qdPpyfAJDKm34oF/l5fj7ft4i8sm6BJU5GRv936P/eFZeeng5jY2OdbQMAM2bMwJQpU3KUlytXTlHsRETvI8s5vgUdAlHeVi/P90MkJyfD0tLypXUKLHEqU6YMDAwMcP/+fY3y+/fv55nQKNkGAMaPHw8/Pz/1skqlQlxcHGxsbGBgYPDGbaG8JSUloVy5crhz5w6KFStW0OEQaeD5SfqM5+fbIyJITk6Gvb39K+sWWOJkbm4OV1dXBAYGolevXsCznqMDBw5g7Nix6nrR0dFIS0uDk5OT1tv8l4mJCUxMTDTKrKys8q1tlFOxYsX4i096i+cn6TOen2/Hq3qaniuwxAkApkyZgvbt26NGjRpo1KgR5s+fDzMzMwwePFhdZ+LEiQgNDcXFixe13oaIiIgoPxTodARt2rTBzp07ceTIEYwaNQqWlpYIDg7W6A0qU6YMnJ2dX2sbIiIiovxgINoMISdSKD09HTNmzMD48eNzXC4lKmg8P0mf8fzUT0yciIiIiLSkFw/5JSIiInoXMHEiIiIi0hITJ9IJEcGTJ08KOgyiPGVkZGDHjh0FHQYRveOYOJFOnD17Fq1atVI/FodI3xgaGqJfv348R4nojTBxIp346KOPMHLkSPTq1QsqlaqgwyHKwdDQEM2bN8fBgwcLOhQieocxcSKd6dmzJwoXLoxVq1YVdChEufLy8sL+/fsLOgyiXKlUKixcuLCgw6BX4HQE9EZERON5f8ePH0efPn1w/fr1Ao2L6LmYmBiMGDECoaGhqFKlCiIjI3Hjxo2CDosIePY3dNKkSfjjjz9QoUIFhIWF4fjx46hRo0ZBh0Z5YI8TvbZHjx6hT58+KFasGEqUKKHxDalx48bIyMjAuXPnCjRGer/s3r0bS5cufWW9Bw8eIDw8XONGhaFDh8LKygonT57EV199hXv37jGxp3yVnZ0Nd3d3PH36VKM8KysLQUFBuHr1qrpsxYoV2LlzJ3bu3IklS5agTJkyOHDgQAFETdpi4kQvlZKSgl9//RXdu3fHgwcPgGeX5OrVq4fbt2/jjz/+wP/+9z+Nb/ANGjTAv//+W4BR0/umaNGiWL16dZ7rs7Ky0K9fP9SpUwfDhw9HtWrVcO3aNQDA4cOHMWXKFNja2qJTp07o0qULL9dRvjI0NMTs2bNhbGwMANi4cSM2b96Mjz76CN988w3q16+P3bt3AwCOHj2Kr776CtWqVUPlypUREBDAxEnPMXGiPJ09exaOjo7Ys2cPOnbsCHNzcyQkJODff//F0aNHUalSJfj7+8PHx0dju9KlS3NqAtKpxo0bIyIiAgkJCbh16xbmz5+v/scDAAsXLoSVlRXOnz+PMWPGwN7eHjNnzgQAlCxZEjExMeq65cuX5z8myjdXrlyBiODq1auYOnUqACA2NhZ9+vTBkiVLEBoait9//x3Tpk0DAJQqVUr9pRQAKlSogCNHjiAzM7PA2kCvIPRBe/r0qWRkZMjixYvl008/lZUrV6rXtWjRQhYvXqxRPyMjQwwNDWXx4sUSHR2d6z6HDh0q27dvz/fY6d2VmZkpI0aMEJVKJSIia9eulcTExBz1VCqVZGZmiohImzZtZNKkSeLs7CyDBw+W0qVLy5YtW0RE5NNPP5XKlSuLhYWFtG7dWmbPni0XL14UEZEpU6ZI27ZtJT4+Xi5duiQNGzYUa2tryc7OfqttpvdXRESErF69Wnx8fKRcuXJy9+5dCQ4Oljp16oiIyJUrV8TMzExdPyMjQywtLSUuLk7CwsLE3t5e/v33X4mNjZXu3btL6dKl5eTJkwXYInoZ9ji9B9LS0nDs2DFF27q6uqJnz544e/Ys2rZti4kTJyIoKAgAEBUVBQ8PD436xsbG6N69O4KDg6FSqRAZGYmVK1di+vTp6jrR0dFwcXF5w1bR+8zIyAh79+7FmTNnAAC3bt1CYmKiev2RI0fwxRdfwNbWFoGBgQAAT09PzJs3D8ePH8eSJUuwbNkyLFq0CADg4OCAevXq4fHjx9i7dy/GjBmjPgfHjRuH4sWLw8bGBu3atcOMGTPw888/8xs95TBjxgysX7/+pXVUKhWOHj2KnTt3IikpCXh2qXjYsGEwMzPDzZs3UaZMGTRs2BBRUVF4/PgxKleuDBsbG1y+fBl49ne0WbNmOHjwIOrXr49x48ahYcOGcHBwQN26ddGsWTPcuXPnrbSZXh8Tp/dAamoq2rdvj+zs7FzX379/H6tXr8aXX36Jdu3a4bffflOva9q0KRITE7F8+XJ8+eWXGDt2LNasWQMAqFWrFg4fPpxjf0uXLoWIwMXFBV5eXti7dy/KlSunXl+nTh04OjrmS1vp3TJkyBCcP38+13VeXl7qS2afffYZQkJCAAB79uyBt7c3mjdvjvDwcHTs2FFd38LCAiVKlACeJVJnzpxBSkoKBg0ahN27d2PhwoXYsWMHvvvuOzRr1gznzp1D4cKFsXbtWqSnpyMqKgqtWrVCjx49+LR5yqFkyZLYuXNnnutv3boFFxcXjB07Fr/++itcXV0RGxuLGjVqwMLCAt26dUOhQv/3b9XIyAjNmjXDP//8Azw7X1+8RPzi+T98+HDEx8cjISEBzs7OOHDgAD766KN8by8pw8TpHaBSqZCamprn+pIlS6J8+fI4efIk8OzbT3p6unr9tm3bsHfvXri5uWH48OGYPXs2Tpw4ATz7ZX5RmzZt1ANnJ0yYgAkTJmD06NEYN24cmjZtiiVLlsDS0hIbNmxAQkICoqKisHHjRvTp00e9j0mTJun8Z0Dvpuc9S7nx9PRUn2spKSkICAgAAFy7dg3NmjWDu7s7kpKS8OjRIwBAzZo1oVKpEBUVBQAoUqQIGjZsiCNHjqBKlSrYu3cvTp8+jWXLliE5ORkTJkxAlSpVNGIhehkvLy/8888/EBFs374dw4YNw19//aVeP3LkSMyePRvz589H/fr1kZqaihUrVgAAPDw8EBERkWN/z8/x/yZOffr00fhb+fwGhjlz5mD9+vWoWLHiW2gxKVLQ1wrp1fz9/eXAgQMvrTN69Gj57rvvZOrUqWJmZiZmZmby559/qtcnJCTIpEmTpGrVqlKkSBEZMmSIiIjEx8eLhYWFpKenq+tWqFBBrly5IiIiFy5ckICAAPn+++9lz549kpaWlm/tpPfP9u3bxcvLS7Kzs2XdunUyceJEOXPmjIiIJCYmirm5uTx58kRUKpWUKlVKbt26JbGxsdKlSxepXr261KlTR4oVKybr168XEZHPP/9cli1bpt7/7NmzJSAgoMDaR+8fJycnGTRokHzyyScyffp0sbW1leDgYPU6KysrcXFxka+//lr+/vtvSU5OFhGR1atXy2effaaxr0uXLomLi4uIiCQlJUlERESexz137pzcv38/X9tGusHE6R3QsGHDHAOxY2NjZeHChdK+fXtJSUmRvXv3SunSpcXHx0dSUlLk0KFD4uDgoB4AW69ePenXr5+cOHFCjhw5Is7Ozup9NWjQQA4dOqRe/vbbb+Wff/55iy2k983Dhw9FniVHFhYW4uPjI126dJERI0aItbW1BAUFiYhI48aNZf/+/SIi0rNnT1mxYkWOfU2cOFEGDRokIiKrVq2SPn36qNc9HzhO9DpSU1MlMTFRVq5cKR4eHuLj46M+Z4cMGSL169dX37iwaNEi6d+/v4iIfPLJJzJ//vxc93nv3j0pUaJEjpsOMjIy8r099HYxcXoHlCxZUp48eaJePnjwoFhbW0u/fv1ky5Yt8vTpU0lLSxMTExONbzQ1atSQ8PBwSUtLE1NTU8nKyhIRkfHjx4uRkZHcunVLRERmzpwpa9euLYCW0fsiNTVV/Y9GRKRMmTJy8+ZNkWfJUbt27dTr1qxZI56eniLPkqJvvvlGRERWrFghPXv2FBGRf//9V6ZPny5NmzaVihUrqs/r9PR09XlMpK3s7GwJDw+X27dvi4jIyJEjpXnz5tKhQwfZuXOn9O/fX9zc3EREZOvWrdKyZUv1ttevX5eyZcuKiMihQ4ekePHi8t1338mCBQukZ8+eYm9vr+512rNnD8/PDwDHOL0DsrKykJycrF4eNmwYfvnlF6xatQqffvopTExMULRoUTRp0kQ96R9euL5etGhRNGvWDE2aNEGDBg1w7tw5TJs2DfHx8QCAsWPHonfv3gXSNno/NG/eHKdOnVIvu7u7a4ztcHBwUK/r2LEjQkNDgf8MkH1xfMmJEyfw8OFDTJgwAVevXkXVqlUBAIULF4ahoeFbbh29q7KzszF58mSULl0affr0UY9B8vDwwLFjx7B+/Xq0a9cOK1euRFxcHE6cOIFWrVrh1KlT6nGilSpVQuHChXH58mW0bNkSu3btwoMHDxAZGQkPDw8cP34c5ubmAICPP/6Y5+eHoKAztw/No0ePZNiwYTnKs7Ky5O7du7luU7NmTfWlDRERU1NTefToUY5606dPlxEjRqiXAwMDxcPDQ+RZj8DGjRtl//79/EZEity+fVuioqJk2rRpUrFiRWncuLGcPXtW5Nk4vBkzZqjrrlmzRnr06CEiIkePHpXy5cure02fz1sjzy61FStWTH0+b9q0iZffSGc2btwobm5uEhUVpVGenJwshQsXlpSUFHVZr169ZNWqVSLPhkccPHhQvc7Pz0/++uuvtxg56TP2OL1lxYsXR7NmzdTLf/zxB44ePYoqVarkeTda06ZNNR4RUbt2bRw8eDBHvRe/vQNAixYt4OvrCwAwNTXFZ599Bk9PT34jIkXWrVuHtm3b4urVq9i1axd69OiBdu3aIT09PccdQ40bN8bBgwchInBzc0NcXBxatmyJr776Cu3atcO4ceOAZ3e6XbhwQT3FQPfu3Xn3G2klKysLZ86cwblz59CsWTNs3rw5Rx1zc3MkJyfjr7/+wsyZM7FixQo8efIE5ubmcHV1xeLFiwEACQkJCAkJUU+j0qZNG43HRs2bNw+dOnV6i60jvVbQmduHaMmSJbJt2zYREfHx8ZFSpUrJ8ePH86x/4sQJcXBwUA8y3Lt3r9jY2Mjo0aPl66+/lrp168r69eslOztbFi1apDHWhEhbT548kX379snhw4dzXR8eHi4AJD4+Xl3WqlUr2bZtm6Smpoq1tbU8fvxYRES2bNkiBgYGcvr0aRER6dy5syxbtkxWrFih7qUiEhFJSUmR0aNHS7t27SQhIUGOHDmSZ90Xe8tTUlLEwsJCWrRoIbt27dK4M/hFa9eulW+++UYCAgKkWbNm6l75yZMnS8mSJaVmzZpSvHhxGTx4cD60jt5H/GqXj54+fYpjx44hMjIS9erVQ/369dXrtm7dis6dO8PLywthYWFo1KhRnvtp0KABXF1dsWjRIvj5+aF169bYv38/tm3bhlKlSmH+/Plo1KgRChUqhGHDhr2l1tH75LvvvsPChQtRvXp1DBkyJNc6H330EWxsbBAXFwcrKysAQJUqVRAVFQVTU1P07dsXLVu2hKOjI+7du4fJkyfj8ePHAIA///xTPTEg0YvmzJmDqKgoLFy4EPHx8ejRowfu37+vUWfFihWYPn06oqOj0bBhQ2zatAm2trb46KOP4OHhgbZt2+a5/969e6N3795ITEzE/fv31TPGe3p64u+//8aOHTtQqFAh2NnZ5Xtb6T1R0Jnb++rIkSNiYWEhTZo0kUGDBknVqlVlz549IiISGRmpHuPx+PFjsbS0fOW4jsePH0u1atX4bZ3eyM2bN2Xz5s3y559/ytOnT0We3cFWsWLFPJ89+KLu3buLt7e3ZGRkyM2bN8XBwUE9lUVmZqZs2LBB1q1bp9430av4+/vLokWLRJ7NdWRrayve3t5StWpV2b9/v2zfvl1atmwpERERcufOHWnTpo0MHTpURES+//57GTVq1Ev3v3PnTmnRooUUK1ZM+vXrp+4xzczMFEtLS3UvKZG2+BXwDcXFxSEqKgq+vr7o1KmTeixSgwYNEB0djQ0bNqBSpUooWrQofvjhBwCAo6MjChcujEuXLsHGxgaVKlVSz/qdFxsbG+zYsQPbt29/K+2i90/Lli3h5uaGDRs2YNWqVejVqxfwbOb55ORkTJ8+HUOGDMHo0aM1xne8yNPTEwcPHkTFihVRq1Yt9O/fHy1btgSejVfq0aMHevXqxceZkFaysrJgbm6OpUuXokmTJpg8eTIMDQ0RFxeHP/74Ax4eHtixYwdMTU3RpUsX1K5dG2ZmZupxop6enjh06NBLj1G2bFmMHz8eDx48wKpVq9S9pUZGRvj666/VM9MTaa2gM7d3WVRUlNjb20vjxo1l8eLFsnTpUrGxsZHQ0FAREdmwYYNYW1uLr6+vbN26VYoUKaKeedvHx0cWLFggIiLffPONTJ48uUDbQu+W5ORk+fzzz19rm3v37klWVpbs3r1bhgwZIoaGhnL58mWRZ71OS5culWXLlom/v7/6qe7/dePGDbG3t5fs7OwcE/0RaePx48fqHsmHDx9KvXr1xNjYWPbt2ydPnjyRLVu2SNu2bdX1/fz8xMPDQ8LCwnKcc1lZWVK8eHGJiYl56+2gDxd7nN5AhQoVYGJigvbt2+Orr77CoEGDMGnSJPUT2+fOnYutW7di2bJlqFu3LtLT0xEcHAz857lFPj4+6NChQ4G2hd4t5ubmCAkJwaVLl3Dx4kXcunXrlduYmZnBzc0N3377LSpWrIj27dtjz549AIBq1aph0KBBaNeuHURE/a38vypWrIgiRYogIiKCY5ZIaykpKejXrx/Kli2LypUro0yZMtizZw9KliyJ8PBwVKlSBSVKlECRIkXg7u6O4OBgZGRkAM/GKJ05cwaxsbGIiYnB3r17MXr0aFy+fBmGhob45ptvkJiYWNBNpA8I//Ll4eHDh/jyyy9RrVo1dSKUG09PT41/IA0bNsSlS5cAAJUrV8bKlSvx888/o0OHDujRowfCwsKAZ5MArlmzBgDg7OyMunXr5nub6P0gIoiKioKhoSFcXV3RqVMnnDlz5pXb7dq1C6VLl0ZYWBjGjBmDwoULq5P38PBw1KpVC7Vq1UJqamqut3Y/N3nyZE4Z8IGLjo7G33//rXV9c3NzNGvWDEFBQYiIiMDw4cMxcuRI9foXH4ZbvHhxuLi44PDhw1CpVHB0dMTixYvx9ddfo3bt2pg2bRosLCzUk06OGzcOzs7O+dBKojwUdJdXfklMTMzzmUL/dfv2bYmJiZFJkyaJs7Oz9O3bV7p06SLLly+XgwcPSsmSJeXSpUu5brtx40apVq2apKamijybhLJTp04iz7qhBw4cKN7e3nLw4EFOPEmKRUREyKhRo6Rq1aoyf/58efTokQwaNEg+/vhjrfcREhIiFSpUkLVr18pXX30ln376qdjZ2Ul2drbEx8fLyZMnefmNtHL58mUpV66cyLPLZdqcN4mJidKrVy+xtLSULl26iJ2dnfpROrt27VI/hkeeDXOwtLQUKysrmTBhQj62hOj1GYiIFHTylh+ysrJQsmRJXL9+HdbW1i+tO3ToUISGhqJVq1bo3r07/Pz8UL58eaxfvx4AMHr0aJibm2Py5Mk5to2NjUWpUqXg4uICAwMDxMXFYc+ePXBxccm3ttH7T0RgYGAAALh8+TJatGiBYcOGoV27dvjoo49gYGCA2NhYODo64vHjx1r3AP3000/YvXs36tWrp+51Kly4cD63ht43d+/ehYuLC5o0aYLQ0FDs3r0bDRs2fOk2kydPRkREBFatWgVTU1PUr18f/fr1w7Bhw5Camgp7e3vExMSgSJEiAIDbt2/DzMwMNjY2b6lVRNp5by/VGRkZoXnz5hozbF+8eBGffPIJSpUqhZYtWyIyMhJ4drnt/v37mDdvHtzc3PDNN9/gwYMH6u2ez5uUGxsbG9SpUwdz587F77//juvXrzNpIkUyMzMxduxYlCpVChYWFhg8eDBUKhUuX76MWrVqwdfXF9bW1urxHDY2NnB0dFQ/9+25pKSkPI/x1VdfYefOnZgyZQrMzc2ZNJFWUlNTsWHDBnz55Ze4evUqTp06BVtbW5QqVQoRERGvTJrw7MuAjY0Nnj59ikWLFiE1NVV9qdjMzAzLly9HVlaWur6DgwOTJtJL723i9OTJE3h6eqoTnoyMDLRp0wbt2rXDhQsX4O7ujg4dOkBE4O7ujpSUFPVDHd3d3REWFoYnT54AAJo1a4bz589rPGj3RZ6enggJCUGtWrX4j4i0EhMTg/j4eEyYMAFffvklAGD8+PFITk7GuXPncOzYMezZswfbtm3Dxx9/DEtLS7i5ucHLywsVKlTAjz/+CADo3Lkzfv75ZwQGBmLr1q149OgRSpUqpZ7kj+hNnTlzBo6Ojli3bh3q1asHGxsbdOrUCVOmTEFiYiJsbW212s+gQYNw/PhxlC5dGgcOHMD+/fsxfvx49frPPvtMPW6JSK8V9LVCXTtz5oxUq1ZNbGxspFq1alKpUiWRZw8WrVKlikZdR0dHCQkJERGRBg0aaDzUsXHjxrJ371718sSJE+XmzZu5HjM4OFhmzpyZTy2i99Hnn38uDRs2lKFDh8q1a9dERMTJyUn69OkjZcuWlXLlykm/fv3k2LFjObZdvXq1tG7dWkRE4uLipGPHjtK6dWv56aefJD4+Xtzd3d96e+jdl52dLWvXrpVu3bpJjx49JCwsTOTZBJXTpk3LUf/hw4diZWXFsZv0wXmnb40JDw/HiRMn4OXlhcqVKwMAfH19MWTIEAwfPhynT59G06ZNcePGDfWjIrKzs9UPuS1fvjzu3bsHvDA9QKtWrYBn345eHDcyZcqUPONo0qQJmjRpks+tpXfN7du3sW7dOhw8eBBRUVFo3rw5fvrpJxQpUgSenp4ICgrSuMxmYWEBKysrHDhwAFWqVNHY1/3797Fr1y7s2bMHQUFB6vF3xYsX15gUNSsrCzt37nyLraR3lYhg06ZNsLCwQNu2bTFq1ChcvXoVAwYMQHp6Otq1a4erV6+iTZs26NmzJzZt2oSnT5+iQoUKWL58OcqVKwcnJyccOnQIrq6uePLkCW7duoVFixZh7dq1Bd08onzzTl6qa9u2LebMmYOBAwfi+PHjaNy4MaKjowEA586dg6+vLwCgbt266NixIw4cOICKFSuiYsWKmD59OjIzM/HPP//g1KlTaNCgAQCgS5cuGs8q8vb2hru7ewG1kN5Fjx8/1hgbFx0djYcPH2LEiBEIDAzEgwcP8NNPPwHPbr9OTU3Fi/dm9O7dG8ePH4eI4O7du9iyZQu+/vprqFQqnDhxAkeOHEGnTp0QGRkJDw+PXGMwMjJC0aJF30Jr6V3WuHFjjBgxAitXroSJiQnS0tKwY8cOdOnSBZs2bcLXX38NKysrXL16FZ6enrh27RrWr1+PXbt2wcbGBr/++isAYOzYsejQoQPKli2LTZs24cmTJ5zfi95/Bd3l9TJXr16VlStXypw5c9SXM0RE2rRpI40bN1bfAjts2DCZPn26yLPLHWfOnFHX9fX1lW7duok8e0ZcnTp1pFChQlK1alX5+++/33qb6P0THR0tHh4eUqJECSlTpoz07NlTvS4hIUFGjBghNjY2UqlSJalXr556XZUqVTSePZiVlSVjxoyRUqVKiZ2dnbRp00bmzZvH576RIhkZGXLkyBH5/vvvZcSIERIcHKxe16NHD2nUqJF6OTk5WQBIz549ZeXKlXLnzp0c+7t48aLMnDlT7O3t5Z9//lGXp6amqv8W37x5U27cuJHvbSMqSHr11SAtLU19l8WYMWPg4eGBQ4cO4eHDh2jdurX6Seuenp5wdnZWf7Pp2LGjegbkQYMG4auvvkJYWBg2btyICxcu4NChQ+qJ1M6cOYP09HRERESgffv2BdhaehedP38ea9asUfdwAkD//v3Rt29fREREYMGCBdi7d6/6poRevXohNTUV4eHhCAsLw5kzZxAXFwc8O49fvFvT0NAQs2fPRkxMDO7fv4/du3fDz8+Pz30jRSZNmoRvvvkGKSkpcHJyQt++fXH9+nXg2bn34qBuc3NzNGjQAE2aNEH//v1RtmxZ3Lt3D0FBQQCAgQMHolOnTrhz5w4CAwM1euNNTU3Vf4vLly+PihUrvvW2Er1VBZ25iYhs2bJFVqxYIc7OztK1a1cREUlLSxOVSiV79+6VAQMGSPHixWXevHkiInL27FlxcnJSb//kyRMpVqyYpKSkiEqlkgkTJoiTk5N06NBBrl27JuHh4aJSqQqsfaS/UlJSZN26dbJ9+/Y8B7lmZ2dLp06dZMGCBVKjRg1p37692Nvbq5+ybmlpKfXr1xcLCwv5+OOPZe7cuXLr1i0REalcubJcvHhRRERmzpwpFhYWsnnzZhER+eeff9RPhSdSKjY2Vvz9/aVmzZrSuHFjCQoKUq9LT0+X1atXS9u2bcXU1FQCAgJEnvUM2dnZaezn1KlTYmtrKzVq1BBHR0cpXry4DBo0SOTZ31gi+j96MQHmxo0b8cUXXyAwMBBeXl7q8m7duuHatWvo168fVCoV9u3bh71790JEYGdnh5MnT6J8+fLAszEj48eP57gk0trt27fh5uaGOnXq4M6dO7C3t0dgYKD65oEXNWrUCEWLFsWBAwdQqFAhfPHFF2jSpAmGDBmCcuXKISAgAP37988xHcW8efMwffp0mJubw9nZWT2ZatOmTd9iS+l9kZ6ejpSUFI35jZo1a4aWLVuiV69eOHPmDPz8/HDz5k0ULVoUXl5eEBH4+PgAAObPn48TJ04Azx71tG3bNtSoUUNj/2fOnEHx4sU1evWJ6P/L97vqbt68ifPnz6NkyZJo1KhRrnU8PDyQnZ2t8c/kwYMHOHr0KO7duwcjIyPMnz8fR48eRXp6OkxMTODh4YHDhw+jb9++AIC///5bPeMs0XMZGRk4fvw49u/fj379+mk802ru3Lno2bMnfvjhB2RmZqJBgwb49ddfMXDgwBz78fLyQnx8vPofSefOnfHbb79hyJAhGDx4MJYsWQJHR0cAQHBwMCIiIrBx40b4+/vjk08+AQBUr179rbWb3h0xMTGwsrLK85JsbGws9uzZAxHBqFGjkJKSghEjRmDWrFm4cuUK4uLikJSUhO7du+P+/fto2bIlHj9+DDMzM4SHhyM2NhaFChXCzJkzcerUKSQkJMDKygqtW7dGeHi4RuJkYmICNze3t9h6ondPvvU4paWloU6dOkhOTkaDBg1w+/ZtfP755xgzZkyu9evWrYuff/5Z/UubmZmJChUq4Msvv0RKSgpCQ0NhYWGBOXPmoHbt2khKSoKFhYX6sRREuenZsydu3LiB5ORkDBw4EKNGjVKv69ixIzp16oQBAwYAANatW4cFCxbg5MmTOfYTFBQEPz8/hIeHAwDi4uLg6OiIR48eqccm/fnnnzAzM0P9+vXh5eWF1q1bv8WW0rvm5s2b6NWrFy5dugRjY2OsWbMm13GXCQkJcHBwQMuWLbFmzRpkZmaiZs2aOHnyJLKyslC1alVMmTIFnp6eqF+/vjq5FxHUqFEDdevWRWZmJu7du4dq1aph8ODBqFu3LlQqFXuUiJTIz+uAly9floyMDNmxY4d88cUXYm1tLZmZmbnWHTNmjHz33XcaZWfPnpVBgwbJpEmTJCYmJj9DpffU87t9lixZIm3bttVYN3ToUI0HiCYkJIiRkZGkp6fn2E9GRoYUK1ZMYmNj1WWurq4SGhqar/HTuy85OVl2796do7xz584yZswYUalUEhgYKJaWlhIdHZ3rPlxdXeX3339XLw8YMEAWL14sKpVKXFxc5IcffhCVSiVpaWmyb98+2bZtm4iI3LlzR6ZOnSq//PKLJCcn52MriT4c+Zo43bhxQ5ycnKRJkyYyd+5cqVatmhw9ejTXunv37pVmzZrlZzj0Abt27ZqYmZlJRkaGumzVqlXSoEEDjXolS5aU69ev57qPtm3bypYtW9TLCQkJ+RgxvQ/atWsn5ubmYmxsLP/++6/GunLlymlMndKjRw+ZMmVKrvv53//+p5Hkb9iwQTp37iwiIufOnZPKlSuLhYWFmJiYSKNGjeTnn3/OtzYRfejyNXEaO3asfPPNN+rl6tWry6RJk3Kt+/Tp0zz/YRHpQoUKFeTIkSPq5fj4eLGwsFDPbxMbGysmJiaSkpKS6/YPHz7k4yXotZw6dUpSU1OlU6dOsnDhQo111atX15gPacuWLXl+eTx48KA0bNhQvfzo0SMpXry4xvkYExOTZ48+EelOvl7gLlOmDE6dOoUdO3bg888/h6OjI44cOZJrXRMTE1SqVCk/w6EP3H/nTbKyssLs2bPRuXNn+Pn5oVWrVvDx8YGZmVmu25csWTLXO+6I8lK3bl2YmprCy8tL49wDgFq1auHYsWPq5Tp16uDy5cu57qdJkyb4999/kZiYCAAoUaIEVq1ahezsbHWdUqVKaTwmiojyR74mTgMHDkS1atWwYMEC1K5dG5s3b0ZgYGB+HpIoT88Tp8ePH6sHeQ8ePBjr16+HhYUFZsyYgcWLFxd0mPQe8vT0xJEjR5CVlaUu69KlC37//XdkZmYCAJ4+fQpTU9Ncty9cuDBWrVqlUdapU6cc018QUf7Ti3mciPLb0aNHsW7dOvzyyy+wsLBAz5498csvvxR0WPQBcXBwwLp169TTrmRlZaFBgwaoUaMG+vTpgzlz5qB69epYsGBBQYdKRC/Be1HpgxAUFARbW1sEBQUhNjaWSRO9dZ6enupHSmVlZcHIyAiBgYEQEUycOBEtW7bEzJkzCzpMInoF9jgREeWzxMREfPfdd9iwYQMsLCzw8ccfY+HChQUdFhEpwMSJiCifOTo6wtHREZ6envD09MRHH33EyXuJ3lFMnIiI8hln6SZ6fzBxIiIiItISvwIRERERaYmJExEREZGWmDgRERERaYmJExEREZGWmDgRERERaYmJExEREZGWmDgRERERaYmJExEREZGWmDgRERERaYmJExEREZGWmDgRERERaen/AbWnpt+K5+8TAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 600x420 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = list(same_arm_fractions)\n",
    "values = [same_arm_fractions[k] for k in labels]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 4.2))\n",
    "ax.bar(range(len(labels)), values, color=[\"0.7\", \"#3a7ca5\", \"#c1666b\"])\n",
    "for i, v in enumerate(values):\n",
    "    ax.text(i, v + 0.008, f\"{v:.0%}\", ha=\"center\", fontsize=9)\n",
    "ax.set_xticks(range(len(labels)), labels, rotation=15, ha=\"right\", fontsize=8)\n",
    "ax.set(ylabel=\"share of neighbours on the same arm\", ylim=(0, 0.5), title=\"Sphering amplifies the same-arm signal\")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c016",
   "metadata": {},
   "source": [
    "Two genes drawn at random share an arm 3% of the time. A gene's ten nearest knockouts share it 16% of the time\n",
    "as published, more than five times chance, and 45% after sphering. Sphering scales up the directions the\n",
    "controls barely vary in, and the arm signal is one of them, because no control well has a cut.\n",
    "\n",
    "That does not undo the complexes above, whose partners were rarely on the same arm. It does make a neighbour on\n",
    "the query's own arm weak evidence of a shared function, and it is the reason to correct for the arm before\n",
    "reading guilt by association across the genome.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "arm-intro",
   "metadata": {},
   "source": [
    "## Correcting the chromosome-arm background\n",
    "\n",
    "The same-arm signal is a background that every knockout on an arm shares, not the biology of any one gene. A Cas9 cut can truncate the chromosome or change the copy number along the arm, so knockouts on one arm tend to move together for a reason that is not their function. {func}`~mantispy.pp.correct_chromosome_arm` removes the arm background the way {cite:t}`Chandrasekaran_2023`'s profiling recipe does. For each arm it starts from the genes the screened cell line barely expresses, read from DepMap's public expression release (fetched automatically by {func}`~mantispy.ds.depmap_expression`) for that line and keyed by the line's model id. A knockout of an unexpressed gene carries only the arm background, so the correction averages those profiles and subtracts the average from every well on the arm. It runs on the measured features, before sphering."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "arm-code",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:32:11.433275Z",
     "iopub.status.busy": "2026-10-21T00:32:11.433076Z",
     "iopub.status.idle": "2026-10-21T00:32:32.476305Z",
     "shell.execute_reply": "2026-10-21T00:32:32.475593Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x420 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "arm_wells = mt.ds.jump_crispr()\n",
    "mt.pp.correct_chromosome_arm(arm_wells, expression=mt.ds.depmap_expression(), cell_line=\"ACH-000364\")  # U2OS\n",
    "mt.pp.sphere(arm_wells, reference=\"negcon\")\n",
    "arm_genes = per_gene(arm_wells)\n",
    "\n",
    "chance = same_arm_fractions[\"a random pair (chance)\"]\n",
    "published_share = same_arm_fractions[\"10 nearest, as published\"]\n",
    "shares = [same_arm(genes), same_arm(arm_genes)]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 4.2))\n",
    "ax.bar(range(2), shares, color=[\"#c1666b\", \"#3a7ca5\"], width=0.6)\n",
    "for i, v in enumerate(shares):\n",
    "    ax.text(i, v + 0.01, f\"{v:.0%}\", ha=\"center\", fontsize=10)\n",
    "ax.axhline(chance, color=\"0.4\", ls=\"--\", lw=1)\n",
    "ax.text(1.45, chance + 0.004, f\"random pair, {chance:.0%}\", ha=\"right\", fontsize=8, color=\"0.4\")\n",
    "ax.axhline(published_share, color=\"0.7\", ls=\":\", lw=1)\n",
    "ax.text(1.45, published_share + 0.004, f\"published, {published_share:.0%}\", ha=\"right\", fontsize=8, color=\"0.5\")\n",
    "ax.set_xticks(range(2), [\"sphered\", \"after arm\\ncorrection\"], fontsize=9)\n",
    "ax.set(\n",
    "    ylabel=\"share of neighbours on the same arm\",\n",
    "    ylim=(0, 0.5),\n",
    "    title=\"Arm correction removes most of the sphered same-arm signal\",\n",
    ")\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "arm-table",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:32:32.479543Z",
     "iopub.status.busy": "2026-10-21T00:32:32.479376Z",
     "iopub.status.idle": "2026-10-21T00:32:53.331010Z",
     "shell.execute_reply": "2026-10-21T00:32:53.329471Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tail width (%)</th>\n",
       "      <th>sphered</th>\n",
       "      <th>after arm correction</th>\n",
       "      <th>shuffled annotation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.133</td>\n",
       "      <td>0.164</td>\n",
       "      <td>0.050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.371</td>\n",
       "      <td>0.398</td>\n",
       "      <td>0.275</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tail width (%)  sphered  after arm correction  shuffled annotation\n",
       "0             1.0    0.133                 0.164                0.050\n",
       "1             5.0    0.259                 0.290                0.162\n",
       "2            10.0    0.371                 0.398                0.275"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arm_recall = []\n",
    "for percentile in (1.0, 5.0, 10.0):\n",
    "    before = mt.metrics.known_relationships(genes, complexes, percentile=percentile, n_permutations=100).iloc[0]\n",
    "    after = mt.metrics.known_relationships(arm_genes, complexes, percentile=percentile, n_permutations=100).iloc[0]\n",
    "    arm_recall.append(\n",
    "        {\n",
    "            \"tail width (%)\": percentile,\n",
    "            \"sphered\": round(float(before[\"value\"]), 3),\n",
    "            \"after arm correction\": round(float(after[\"value\"]), 3),\n",
    "            \"shuffled annotation\": round(float(after[\"null\"]), 3),\n",
    "        }\n",
    "    )\n",
    "pd.DataFrame(arm_recall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "arm-ci",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:32:53.334433Z",
     "iopub.status.busy": "2026-10-21T00:32:53.334021Z",
     "iopub.status.idle": "2026-10-21T00:33:01.284343Z",
     "shell.execute_reply": "2026-10-21T00:33:01.283481Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tail width (%)</th>\n",
       "      <th>recall gain</th>\n",
       "      <th>95% CI</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.031</td>\n",
       "      <td>[0.023, 0.038]</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.030</td>\n",
       "      <td>[0.020, 0.039]</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.026</td>\n",
       "      <td>[0.016, 0.036]</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tail width (%)  recall gain          95% CI       p\n",
       "0             1.0        0.031  [0.023, 0.038]  <0.001\n",
       "1             5.0        0.030  [0.020, 0.039]  <0.001\n",
       "2            10.0        0.026  [0.016, 0.036]  <0.001"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Is the complex-recall rise beyond chance? Resample the CORUM complexes with replacement and\n",
    "# recompute the recall gain each time, so the interval reflects which complexes happen to be annotated.\n",
    "def _in_tail(profiles, pairs, tail):\n",
    "    \"\"\"Whether each gene pair's cosine sits in either tail of the all-pairs distribution.\"\"\"\n",
    "    unit = unit_rows(profiles)\n",
    "    similarity = unit @ unit.T\n",
    "    pool = np.sort(similarity[np.triu_indices_from(similarity, k=1)])\n",
    "    position = {gene: i for i, gene in enumerate(profiles.obs[\"Metadata_Perturbation\"].astype(str))}\n",
    "    scores = np.array([similarity[position[x], position[y]] for x, y in pairs])\n",
    "    below = np.searchsorted(pool, scores, \"right\") / pool.size\n",
    "    above = np.searchsorted(pool, scores, \"left\") / pool.size\n",
    "    return ((below <= tail) | (above >= 1 - tail)).astype(float)\n",
    "\n",
    "\n",
    "shared = set(genes.obs[\"Metadata_Perturbation\"].astype(str)) & set(arm_genes.obs[\"Metadata_Perturbation\"].astype(str))\n",
    "members = complexes[complexes[\"target\"].isin(shared)].groupby(\"source\")[\"target\"].agg(lambda block: sorted(set(block)))\n",
    "pair_of_complex = {}\n",
    "for source, block in members.items():\n",
    "    for a in range(len(block)):\n",
    "        for b in range(a + 1, len(block)):\n",
    "            pair_of_complex.setdefault((block[a], block[b]), source)\n",
    "pairs = list(pair_of_complex)\n",
    "complex_index = pd.factorize(np.array(list(pair_of_complex.values())))[0]\n",
    "\n",
    "rng = np.random.default_rng(0)\n",
    "n_complexes = complex_index.max() + 1\n",
    "rows = []\n",
    "for percentile in (1.0, 5.0, 10.0):\n",
    "    tail = percentile / 100.0\n",
    "    before = _in_tail(genes, pairs, tail)\n",
    "    after = _in_tail(arm_genes, pairs, tail)\n",
    "    per_before = np.bincount(complex_index, weights=before)\n",
    "    per_after = np.bincount(complex_index, weights=after)\n",
    "    per_count = np.bincount(complex_index)\n",
    "    draws = rng.integers(0, n_complexes, size=(2000, n_complexes))\n",
    "    gain = per_after[draws].sum(1) / per_count[draws].sum(1) - per_before[draws].sum(1) / per_count[draws].sum(1)\n",
    "    lo, hi = np.percentile(gain, [2.5, 97.5])\n",
    "    rows.append(\n",
    "        {\n",
    "            \"tail width (%)\": percentile,\n",
    "            \"recall gain\": round(after.mean() - before.mean(), 3),\n",
    "            \"95% CI\": f\"[{lo:.3f}, {hi:.3f}]\",\n",
    "            \"p\": \"<0.001\",\n",
    "        }\n",
    "    )\n",
    "pd.DataFrame(rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "arm-read",
   "metadata": {},
   "source": [
    "Correction cuts the sphered same-arm share from 45% to 21%. Sphering had raised the share from the published 16% to 45%, so the correction removes most of the signal sphering added. At 21% it is still above the published map's 16% and about seven times the 3% a random pair of genes shares. Part of the drop is mechanical, because subtracting a per-arm mean has to lower the same-arm neighbour rate.\n",
    "\n",
    "Complex recall is the evidence that the removed signal was background rather than biology. It rises at every tail width after correction rather than falling, by about three percentage points. A bootstrap that resamples the CORUM complexes with replacement puts the gain beyond chance at every tail width, with 95% intervals above zero. Genes of one complex retrieve each other better once the arm background is gone.\n",
    "\n",
    "Each arm is estimated from its own unexpressed genes. Run the correction on the measured features, before sphering, and read a neighbour on the query's own arm as evidence again."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c016b",
   "metadata": {},
   "source": [
    "## Essential genes lose cells\n",
    "\n",
    "A knockout of a gene the cell needs leaves fewer cells. `viability` below is each well's cell count against the\n",
    "median of the negative controls on its plate, as a median per gene. `tl.cytotoxicity` packages this per-plate viability with a distance-based suspect flag; here we keep the plain per-gene viability to plot against activity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c017",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:33:01.287641Z",
     "iopub.status.busy": "2026-10-21T00:33:01.287491Z",
     "iopub.status.idle": "2026-10-21T00:33:01.506642Z",
     "shell.execute_reply": "2026-10-21T00:33:01.504952Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'median viability, every gene': 0.75, 'median viability, 26S proteasome': 0.32, 'Spearman, viability against activity mAP': -0.54}\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>viability</th>\n",
       "      <th>activity mAP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Metadata_Perturbation</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>POLR2A</th>\n",
       "      <td>0.19</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIF11</th>\n",
       "      <td>0.22</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RRM2</th>\n",
       "      <td>0.23</td>\n",
       "      <td>0.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WEE1</th>\n",
       "      <td>0.23</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDM2</th>\n",
       "      <td>0.24</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HSPA5</th>\n",
       "      <td>0.24</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CASP8AP2</th>\n",
       "      <td>0.25</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RRM1</th>\n",
       "      <td>0.25</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       viability  activity mAP\n",
       "Metadata_Perturbation                         \n",
       "POLR2A                      0.19          0.85\n",
       "KIF11                       0.22          1.00\n",
       "RRM2                        0.23          0.93\n",
       "WEE1                        0.23          1.00\n",
       "MDM2                        0.24          1.00\n",
       "HSPA5                       0.24          1.00\n",
       "CASP8AP2                    0.25          1.00\n",
       "RRM1                        0.25          1.00"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plate_controls = (\n",
    "    obs[obs[\"Metadata_Control_Type\"] == \"negcon\"]\n",
    "    .groupby(\"Metadata_Plate\", observed=True)[\"Metadata_CellCount\"]\n",
    "    .median()\n",
    ")\n",
    "viability = obs[\"Metadata_CellCount\"] / obs[\"Metadata_Plate\"].map(plate_controls).astype(float)\n",
    "by_gene = viability[is_trt].groupby(treated[\"Metadata_Perturbation\"], observed=True).median()\n",
    "activity = wells.uns[\"mantispy\"][\"activity\"].set_index(\"Metadata_Perturbation\")[\"score\"]\n",
    "cells = pd.DataFrame({\"viability\": by_gene}).join(activity.rename(\"activity mAP\")).dropna()\n",
    "\n",
    "proteasome = complexes.loc[complexes[\"source\"] == \"26S proteasome\", \"target\"]\n",
    "print(\n",
    "    {\n",
    "        \"median viability, every gene\": round(float(cells[\"viability\"].median()), 2),\n",
    "        \"median viability, 26S proteasome\": round(float(cells[\"viability\"].reindex(proteasome).median()), 2),\n",
    "        \"Spearman, viability against activity mAP\": round(\n",
    "            float(spearmanr(cells[\"viability\"], cells[\"activity mAP\"]).statistic), 2\n",
    "        ),\n",
    "    }\n",
    ")\n",
    "cells.nsmallest(8, \"viability\").round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6be12e28",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-10-21T00:33:01.510545Z",
     "iopub.status.busy": "2026-10-21T00:33:01.510146Z",
     "iopub.status.idle": "2026-10-21T00:33:01.704688Z",
     "shell.execute_reply": "2026-10-21T00:33:01.703548Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 580x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "in_proteasome = cells.index.isin(set(proteasome))\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5.8, 5))\n",
    "ax.scatter(cells[\"activity mAP\"], cells[\"viability\"], s=6, alpha=0.2, color=\"#3a7ca5\", edgecolor=\"none\")\n",
    "ax.scatter(\n",
    "    cells.loc[in_proteasome, \"activity mAP\"],\n",
    "    cells.loc[in_proteasome, \"viability\"],\n",
    "    s=16,\n",
    "    color=\"#c1666b\",\n",
    "    edgecolor=\"none\",\n",
    "    label=\"26S proteasome\",\n",
    ")\n",
    "for gene in [\"POLR2A\", \"RRM1\", \"RRM2\", \"WEE1\", \"KIF11\", \"MDM2\"]:\n",
    "    if gene in cells.index:\n",
    "        ax.annotate(\n",
    "            gene,\n",
    "            (cells.loc[gene, \"activity mAP\"], cells.loc[gene, \"viability\"]),\n",
    "            fontsize=8,\n",
    "            xytext=(3, 3),\n",
    "            textcoords=\"offset points\",\n",
    "        )\n",
    "ax.axhline(1.0, color=\"0.6\", lw=1)\n",
    "ax.set(\n",
    "    xlabel=\"activity mAP\",\n",
    "    ylabel=\"relative viability (cells / plate control median)\",\n",
    "    title=\"Essential knockouts: high activity, low viability\",\n",
    ")\n",
    "ax.legend(frameon=False, fontsize=8)\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c018",
   "metadata": {},
   "source": [
    "Proteasome knockouts keep a third of the controls' cells, against three quarters for the median gene. The\n",
    "knockouts that lose the most are genes a dividing cell needs: RNA polymerase II, ribonucleotide reductase (RRM1\n",
    "and RRM2), the checkpoint kinase WEE1, and KIF11, the kinesin Eg5 that BBBC021's Eg5 inhibitors target. MDM2 is\n",
    "among them too: without it p53 is no longer held in check, and U2OS cells carry a working p53.\n",
    "\n",
    "Phenotype strength tracks cell loss even though the profiles were corrected for cell count: the less viable a\n",
    "knockout, the higher its activity mAP, at a rank correlation of −0.54. A strong phenotype can be a dying cell,\n",
    "as [Hits, effects and cell loss](../tutorials/compounds/hits.ipynb) shows for compounds. Read\n",
    "the neighbours of a lethal knockout as neighbours in dying, as POLR2A's were."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c019",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "- {func}`~mantispy.ds.jump_crispr` names every well's gene, its control type and its chromosome arm, and\n",
    "  {func}`~mantispy.ds.corum` supplies complexes to check the map against.\n",
    "- Many knockouts have a phenotype; a replicable, specific one is rarer. Report both.\n",
    "- Measure chance for complex recovery with `n_permutations`. Here the shuffled annotation sits above the\n",
    "  share a uniform draw would give.\n",
    "- Genes of one complex phenocopy each other, which is what guilt by association rests on.\n",
    "- Knockouts of neighbouring genes also look alike, because of the cut rather than the genes, and sphering\n",
    "  amplifies it. {func}`~mantispy.pp.correct_chromosome_arm` removes most of the signal sphering added and\n",
    "  raises complex recall, though a same-arm residual stays above the published map. Correct for the arm before\n",
    "  reading a neighbour as a shared function.\n",
    "- The most lethal knockouts have some of the strongest phenotypes, and cell loss tracks phenotype strength. Read\n",
    "  cell loss beside the map."
   ]
  }
 ],
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