2step_clustering_kmeans_dbscan_log_rho.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cbbd1eb7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script>jQuery(function() {if (jQuery(\"body.notebook_app\").length == 0) { jQuery(\".input_area\").toggle(); jQuery(\".prompt\").toggle();}});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<button onclick=\"jQuery('.input_area').toggle(); jQuery('.prompt').toggle();\">Toggle code</button>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display\n",
    "from IPython.display import HTML\n",
    "import IPython.core.display as di # Example: di.display_html('<h3>%s:</h3>' % str, raw=True)\n",
    "\n",
    "# This line will hide code by default when the notebook is exported as HTML\n",
    "di.display_html('<script>jQuery(function() {if (jQuery(\"body.notebook_app\").length == 0) { jQuery(\".input_area\").toggle(); jQuery(\".prompt\").toggle();}});</script>', raw=True)\n",
    "\n",
    "# This line will add a button to toggle visibility of code blocks, for use with the HTML export version\n",
    "di.display_html('''<button onclick=\"jQuery('.input_area').toggle(); jQuery('.prompt').toggle();\">Toggle code</button>''', raw=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3359748e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
       "    return false;\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
    "    return false;\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2462b9e6",
   "metadata": {},
   "source": [
    "# Step 1: Using K-means clustering to identify low-resistivity regions\n",
    "# Step 2: Using DBSCAN to identify spatially separated low-resistivity regions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e060bd58",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from resistivity_functions import *\n",
    "\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "90658374",
   "metadata": {},
   "outputs": [],
   "source": [
    "datafile = '../Data/rho.txt'\n",
    "\n",
    "dataframe_original = pd.read_csv(datafile,skiprows=1,usecols=[1,2,3,4],names=['x','y','z','rho'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4ce44c96",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe = dataframe_original['rho']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3fa55c1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe_array = dataframe.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9ea215d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Try DBSCAN instead of SOM\n",
    "import numpy.ma as ma\n",
    "masked_data = ma.masked_values(dataframe_array,-9999.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "493429a3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-8-7939f8e8710d>:1: RuntimeWarning: invalid value encountered in log10\n",
      "  log_rho = np.log10(masked_data)\n"
     ]
    }
   ],
   "source": [
    "log_rho = np.log10(masked_data)\n",
    "log_rho = log_rho.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1d0c1d7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "clustering = KMeans(n_clusters=2,random_state=1).fit(log_rho)\n",
    "labels = clustering.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "63f5f189",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_clusters=np.max(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b53812a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe_original['cluster_id'] = labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "36cd8bd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe_original.loc[dataframe_original.rho==-9999, 'cluster_id'] = -1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "97df7007",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "37.3"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Minimum resistivity in high-resistivity region\n",
    "min(dataframe_original['rho'][dataframe_original['cluster_id']==0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e49bba21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0xd24dbe0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 416.375x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.displot(dataframe_original[dataframe_original['rho']!=-9999], x='rho', hue='cluster_id')\n",
    "ax.set_xlabels(r'$\\rho$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3e0ecdba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x140df670>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(dataframe_original[dataframe_original['rho']!=-9999], x='rho', col='cluster_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "bfee19c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x13bff2e0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.displot(dataframe_original[dataframe_original['rho']!=-9999], x='rho', col='cluster_id',log_scale=True)\n",
    "ax.set_xlabels(r'$\\rho$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7bdb7fff",
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_rho = dataframe_original['cluster_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "ad8c13db",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = Data(dataframe=dataframe_original)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9144695a",
   "metadata": {},
   "source": [
    "## K-Means clustering: Identifying low-resistivity and high-resistivity regions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c2d814f",
   "metadata": {},
   "source": [
    "### Value: z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e06d0e20",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3c52b8f61b354b8799f0d3e8ef2b62f2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=-12.0, description='value', max=28.0, min=-50.0, step=2.0), Output()),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.display_cross_section(variable='z',quantity='cluster_id',logscale=False, vmin=-1, vmax=num_clusters, cmap=\"cubehelix\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2329d386",
   "metadata": {},
   "source": [
    "### Value: x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5ee0917c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ff41757849444f01bd2fc6ada88d6e94",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=243050.0, description='value', max=245400.0, min=240700.0, step=50.0),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.display_cross_section(variable='x',quantity='cluster_id',logscale=False, vmin=-1, vmax=num_clusters, cmap=\"cubehelix\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87ddacf0",
   "metadata": {},
   "source": [
    "### Value: y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "72ad2e82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2a7144f1c41a444d819be895a3c2b38e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=561250.0, description='value', max=565000.0, min=557500.0, step=50.0),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.display_cross_section(variable='y',quantity='cluster_id',logscale=False, vmin=-1, vmax=num_clusters, cmap=\"cubehelix\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a092cb06",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_cluster = labels_rho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d82d0230",
   "metadata": {},
   "outputs": [],
   "source": [
    "low_resistivity_indices = np.where(data_cluster==1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d40dfeb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "low_resistivity_indices = np.reshape(low_resistivity_indices,-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "57be119e",
   "metadata": {},
   "outputs": [],
   "source": [
    "low_resistivity_indices = np.asarray(low_resistivity_indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2c01477c",
   "metadata": {},
   "outputs": [],
   "source": [
    "list_low_resistivity_indices = low_resistivity_indices.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9dac093d",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_size = len(list_low_resistivity_indices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d17b1dd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe_coordinates = dataframe_original[['x','y','z']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9e9a6cb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe = dataframe_coordinates.iloc[list_low_resistivity_indices]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "066cbd87",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = Data(dataframe=dataframe)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0a0551a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_array = data.dataframe_to_numpy_array()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e6fb2de8",
   "metadata": {},
   "outputs": [],
   "source": [
    "normalized_data = data.normalize_data(data_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "10f22419",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import DBSCAN\n",
    "clustering = DBSCAN(min_samples=20,eps=0.14).fit(normalized_data)\n",
    "labels = clustering.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e13d29d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_cluster = labels + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "845a7988",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_cluster_resistivity_position = labels_rho.to_numpy()\n",
    "data_cluster_resistivity_position[list_low_resistivity_indices] = data_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "546dc5f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_clusters=np.max(data_cluster_resistivity_position)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "121c91c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframe_original['cluster_id_resistivity_position'] = data_cluster_resistivity_position\n",
    "data = Data(dataframe=dataframe_original)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a488506",
   "metadata": {},
   "source": [
    "## DBSCAN: Identifying spatially separated low-resistivity regions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab2561ea",
   "metadata": {},
   "source": [
    "### Value: z"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "419c68ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2b5602d6d6ef4b2c8b17b1aa8efb0fdf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=-12.0, description='value', max=28.0, min=-50.0, step=2.0), Output()),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.display_cross_section(variable='z',quantity='cluster_id_resistivity_position',logscale=False, vmin=-1, vmax=num_clusters, cmap=\"cubehelix\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6086d8d6",
   "metadata": {},
   "source": [
    "### Value: x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "8905c1ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67335e71f9f04798ac4b859081c66071",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=243050.0, description='value', max=245400.0, min=240700.0, step=50.0),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.display_cross_section(variable='x',quantity='cluster_id_resistivity_position',logscale=False, vmin=-1, vmax=num_clusters, cmap=\"cubehelix\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "760d60b4",
   "metadata": {},
   "source": [
    "### Value: y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e8a99d84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f944c71315dc4232a3d8a26fcd11166b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=561250.0, description='value', max=565000.0, min=557500.0, step=50.0),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.display_cross_section(variable='y',quantity='cluster_id_resistivity_position',logscale=False, vmin=-1, vmax=num_clusters, cmap=\"cubehelix\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "68c0676c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = dataframe_original[dataframe_original['rho']>0]\n",
    "df = pd.DataFrame(df1,columns=['x','y','z','cluster_id_resistivity_position'])\n",
    "df.rename(columns={'cluster_id_resistivity_position':'cluster'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7f990417",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(dataframe_original, columns=['x','y','z','cluster_id_resistivity_position'])\n",
    "df.rename(columns={'cluster_id_resistivity_position':'cluster'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "66939aa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "vmin = df['cluster'].min()\n",
    "vmax = df['cluster'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "73b1c054",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_min = data.find_min('x')\n",
    "y_min = data.find_min('y')\n",
    "z_min = data.find_min('z')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "359038cd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "x_step = data.find_step('x')\n",
    "y_step = data.find_step('y')\n",
    "z_step = data.find_step('z')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "61f5d62b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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3ZQmO0/7p4lz7YWSJoWTrOFliR0JmYtEmKEPHDrA8hQwAlmARTwAAAKB6yuYL2T9i0fc66MBlZGm7HC0uy6xCdmQLgDnpbWZ2rIMfOxA0cIRbyRLnHH7XdrqOU6BgKIWM42SJoWTpOFliZ5JkCN4wgkiXrrYhW8fJEkPpr46TJcaSqVvJEmPJ0q1kiZ1J18C4+56Hq2xsT733s+Kp937W0psBo9WaLWiVTAEAEVdFI4WjelnEEwAAAKjeLKWl2s45/sX7Pr7o6x86d06XKWTQjyxBGX2zBJzmvH0oY84sdY0X5bgOi8zAMFUXypAlAABgKxyGrMiUVT4VRLZElqCMKdp71wwoWaI1Q2b1TZklR4tpXe1ZOvba8rWcRQsYpnNfZsxUKmFbJ1m6jCyxI0vTO/yMZWmd1pil2t7TYXZq2z7K2P+e1/Ld1tZW+2ZJf1UHi3gCAAAA1auj7MVRfauSx+7XVUmELZIluN2YI2CXHC2TJdam77TzU48dom9mzHKiVWNmm0yZJeqkgNGQS6ZbmQK1DbVNyVsjWdqGNU7ZPbT0+5KlbVhTlvqcFz/H63dl5fB2mVqftY7z5n4/Y4t7fQ50Mb2zrSWl9LyI+PGc88em2oi1hrG0uY6SATfJEpQhS1DG0J2vYwsPmp3BktbUH8jS/Pq0ns+JiLellN4RET8SEW/KOedpN4tTFHygDFkCoFUlT+mCLeqaCTgkW7I0v7OLeOacvysiHh8RPxwR3xwR700p/U8ppf9s4m0DAAAAiIiea2DknHNK6cMR8eGIeDgi7oqI16eU3pxzfmGpjVnTeZJTcLks+pKlYWSJU7SP/vz2cIosQRmyNI2uz/PY523mxXL6rIHxbRHxnIj4SES8KiK+Pef8yZTSp0XEeyOiWAFjn2BCGbJ0O50OY8hSN5liCFk6r2QxUD7XS5am5epZderT2j87Ir4u5/zb+3/MOX8qpfS102zWTYcNRUBvNyRMPr/tkqXzTmXJ58WOLN10KjPnrpQAsnS7Y7mRJc5ZS5ammMXXZz+p1c9rq85+Wznn7zlx23vKbs55Ko2XUTlkR5aGWcvggPK0jWF8XnTZctsYMz7b8ufFadrGMD6vtpxdxBMAAABgacpLDThXFTSrAuYnd1CGLEEZskSXVmbdlti+EjmQpbrV3YoH2NLUn0t+hEoWP/4/f/ev9Lrff/Xifzj6NZjflrJ0id3nUqKTO8zSLjPHMiZP9erz+ypP0+rKEm2TpfnsMiQ763JqzCJL05Cl6TTfYrt2Hlq+lFvfGRclFu88VYQQuG1ZY5Z2zi2AZiFcShqysOVhG2ylfTk6xZT6/DavJUu1ONzZsvO1Lpdk6fDvsLRmW+KQwVNNndklO0qXDBg7d05PdEw6r20okaVaMjY0IyUWTetjaJb6zm6iLpf8Rrey87V04UK/tA1byNLO0pna6cqUzG1PLW1yqNq2WzFwOhbxBAAAAKpXd1l6BaaYNTE3R4M5Z44jXLXk4RKyxKHDo8S1Hj2uJX+n1oc5xpoY23HuNMghWTrX3mvJZUn6J86RpcuYiVHOdlpNzBuiWgZ7SxLQ9ZKlYYbudHU9nvWasth9bj2B/byuIW9wTJ+dr77tv0+WLn2NuZ3rpywqzc4cWTr3/ENeo1b7mZKlYTZVwKjJmOrllFc92BEgSpj76HHf12m9s2N7+mTp0r7h1EK9tWbm3Pn6MEbJLLXq0oI7RJTZZ1lDniJkagoKGHtK7HRNcWS6lulVhwNGK1YzpTVOO+y7SJosMUbXgHGNWepyrp+CPkoeMGqVLFGCLN10mB1ZGs8ingAAAED1Us65+JPe99CD5Z90RrXNwBj6Gvu6KuZ9pjGpDE7j3jtvpL733VKWhp4q1fK5xpQhS8cNbfclzmOmfX3zJEtwmizdTpYYoytL65k3WtCQBWVqWym+i6l/LGHM4kzOl4TbXbLQ2SXPDWszZZZg61rZL6JtWtdA5y7TVfI5Yc1KtvsaMuRyjSylhvYPrTg1y0+W4DLWvGAOChgzWzrQ504dsdN1uXvvvHHLv+976MFFtmPtls7SjlWlmdIWB4OKgUzh8IjwFk6dculTptBndsXa+i5ZqotFPAEAAIDqmYEBhZlxsU6OCsO0zGYCAM5RwADoYcyVfOBSa5l+C0vb0uKCCu5MaUtZOiRLddhey9uYvjtdAgllyBKUIUtMQVEQyiiRpdrXynAVxzqlnMtfgrj16xpvger8cvpeHzxCllogS8uRJSinb55kCU6Tpf5qL2CwrK4smYGxUXayoAxZAli3w6nydrZgnC2edkJ5rkICAAAAVE8ZDAAAOphxAZcx84KStCYAAACKUrhgCloVAAAARR3OXrJoJyUoYAAAADAphQtKsIgnAAAAUD0FDAAAAJrzwP13WGtjY3zbAAAANMc6G9tjBgYAAABQPTMwAAAAaJ6ZF+tnBgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieAgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieAgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwGAz7r3zRtx7542lNwOaJ0tQhiwBwDB3LL0BMJWuQeHu7/c99OBs2wItkyUo41yWIuQJhjjMlPzAZVoY2ylgsDqOZkEZsgRlyBKUpRgIZbSYJQUMNqvmYAIAcCvFQCij5SxZAwMAAAConhkYbJZZFwAAwNbs9oNanImhgMHqtBxIqIksQRmHWTosoMsY9HPu4JMswTBdmao5SwoYrJYZFlCGLEEZXVmSMShDlqCMmrNkDQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1Us556W3AQAAAOAkMzAAAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieAgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4CxMSmlF6SUckrps/f+9uKU0vtSSr+ZUvqqjsc9JqX05pTSe6///675thrqkVL6/pTSu1JK70wp/bOU0mOv//6IlNJrUkq/kVJ6T0rpxR2PlyW41pWn69uemFL65ZTSu69z9agjj5cniNNZur7981NKH08pvaDj8bIEcXKc9/SU0tuv+6O3p5S+ouPxsjQxBYwNSSl9XkQ8PSL+3d7fvjAinh0RT4iIr46IH0opffqRh78oIt6Sc358RLzl+t+wRS/LOT8x5/xFEfFPI+J7rv/+DRHxyJzzn42IJ0XEX00p/Ykjj5cluOlonlJKd0TEj0XEc3POT4iIp0XEJ488Xp7gSlfftPPyiPjZE4+XJbjSlaWPRMRfvB7nPScifrTj8bI0MQWMSqSUnntd6XtnSukDKaW3TvAyL4+IF0ZE3vvbMyPitTnnT+ScPxAR74uIpxx57DMj4jXX//2aiHjWBNsHF5s6Sznn39/756PjZp5yRDz6esfrMyLiDyPi9+N2skQzFszTMyLiXTnnX7++30dzzn905CnkiSYsmKVIKT0rIt4fEe8+8RSyRBOWylLO+ddyzh+6/vu7I+JRKaVHHnkKWZrYHUtvAFdyzq+MiFemlB4RET8XET94eJ+U0ssj4suPPPy1OeeXnHr+lNJfiojfyTn/ekpp/6bPjYhf2fv3B6//duiP55zvv97W+1NKd596PVjK1Fm6fvzfiYhvioj/sPc8r4+rTuv+iPjMiHh+zvn3jjxclmjGgnm6NyJySulNEfHHrp/rpUceLk80YakspZQeHRHfEVczcI+ePnJNlmjCgv3Svr8cEb+Wc/7EkdtkaWIp53z+XswmpfRDEfHvc85/q+BzfmZEvDUinpFz/g8ppX8bEU/OOX8kpfQPIuKXc84/dn3fH46IN+Scf/LgOR7MOd/Y+/fHcs7O6aJaU2TpyGu8OCIelXP+WymlvxAR/+eI+OaIuCsi/kVE/Dc55/cfPEaWaM4CeXpBRPz1iPjiiPiDuJqG+10557ccPEaeaMoCWfqBiPiXOefXpZS+NyI+nnP+gSOPkSWaMneW9v72hIj4J3G1X/VbRx4jSxNzCklFUkrfHBFfEBHf13H7y/emTO3/77Zzq1JKr76+7Q0R8Z9FxJ+MiF+/Ll48LiLekVL6nLiacfF5ew99XER86PD5IuJ3U0r3XD/3PRHxwOg3ChObMEuHfiKuqvAREd8YEW/MOX8y5/xARPxSRDz5yGNkiaYslKcPRsQv5Jw/knP+g4h4Q0T8+SOPkSeasVCWviQiXno9/vubEfF/TSk978hjZIlmLJSlSCk9LiJ+KiK+6Vjx4posTcwMjEqklJ4UV+dJfWnO+WMTv9a/jZszMJ4QV+F8SkQ8Nq6Ocj3+8FzjlNLLIuKjOeeXXIf/MTnnF065nTDG1FlKKT0+5/ze6//+GxHxZTnnr08pfUdE/OmI+Na4OoXkbRHx7Jzzuw4eL0s0Y8E83RVX/dFT42o9mTdGxMtzzj9z8Hh5oglLZengPt8b3TMwZIkmLNgv3YiIX4iIv304U/3g8bI0MQWMSqSUXh0RXxU3q3S/mnP+Hyd6rX8b1wWM639/Z1ztdD0cEX8z5/yz139/VUS8Muf8qyml/yQiXhcRnx9XVzH5ho7z+2FRU2cppfSTEfGfR8SnIuK34+oqCb+TUvqsiHh1RHxhRKSIeHXO+WXXj5ElmrRUnq5v++8i4sVxtYDaG3YDQHmiRUtmae8+3xt7BQxZokULjvO+K676pPfu3f0ZOecHZGleChgAAABA9ayBAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6d0zxpPc99KCVQTnp3jtvzPZa9z304Gyv1ce9d95Ife8rS5wjS/3IEudsOUsR/fMkS5wjS7JEGbJ0PEtmYAAAAADVU8BgEfc99OBslb5777wxawUT5iRLUIYsQRmyBGXI0nEKGAAAAED1FDAAAACA6ilgsChTo6AMWYIyZAnKkCUoQ5ZuNclVSKBmu1DWuNoutESWoIz9waI8wXiyBGXUnCUFDKqwC8acFb+agwljyRKUsUSW9l9PllgLWYIyZOmKAgabVUsIoXWyBOXIE5QhS1BGbVmyBgYAAABQPTMwqMqUU6Nqqx7ClGQJypAlKEOWoIytZ0kBg9VqIYDQAlmCMmQJypAlKKPFLClgUKUxlcUWAwhTkyUoQ5agDFmCMraaJQUMmreGIEINZKltD9x/1aXffc/DC28JW8rSrt0darkdylI9ZKntdihL9VhTliziCQAAAFTPDAyqdmpq1JoqiTA1WdoOR7ymJUu32rWzrqPHLZOlacnSrbaQpUOyVcZ+Xg7ztMYsrS8hrNoaQwhLkScoQ5bWTSFjPrIEZaw5SwoYNGHNIYQ5ydJ62bmalyydduyIqzbKMbJ0miwxxBbypIABANccaYVx+kx/Pzc1vpbc1bIdbFOJLB0+19zWeBoM9dC6JnIYXJ0hjOO8SShDlqAMWaIVS+2P9H2dU4UOeaKLq5AAAAAA1TMDo4ch556ZMgXdZIk1qOE0E1lijZaa2dD3KLUs0bqp+y9ZYg5az0iCB2WMzdL+40wzpJQ+banvpe7mbpeyRE2O5eSwffVts312ukrumMkStRubpSH3XzJL+4+VJQ41uxc+JBA1NnydHEsb06nU2lZ1ctRoyLm9tZxTL0tc6rDtnGpLfYuBO33uV0thUZa41JC2MzRLfdSyUKgscajZAsYQQxewmWJ2RZ+VhAWTOY3p7GrIUp/XkyVqV3KHbQqyxFrpl+BWlxY/5sqULLFjEU8AAACgepuYgXFIBQ/KkCUAgLYcG7dNcRoKTGHTLXSpayPD2sgSW1RysFfb6VjQiqH9jSyxZUMWqj5HllhKsy1vycVqpuJoNkuQJZhfKwNEWWIOY/qh1tqkLDGHLcyikCXW27qB4hwlhtsNGTAacMF48gOXsfPPGljEEwAAAKiew6UAAKyaGYIA69D8r/kWzvWCOYzJktzBTYdTci/Jh2wBANzOCKkQhRQoQ5bYoinOS5YlWndJYV2W4HZDctGVpUtyIEuUoPVMrCuox35AhJnaLdlGT3V6JTtXmIMswe2mmAk4ZRuWJVpzqsCnX6IVFvEEAAAAqtd8Cau2KlzX1Kw+U7Zc0oglyRKUcSpLXbdNOa1WlmjVYR6WvlSxLNGKIX3KuX5pCrLEJeraYxnBuVRQhixBGbIElzFlHIAueoQLqQJCGbLElpXcQZMltqzkIp6yROu6ioFDZmbIErVZzRoYd9/zsHBAAbIEZcgSlHFJluQQbiqRB5liaaspYAAAAADrtbpTSI6de+x8ZBhOlqCM/SNVh1NyZQn6O5YlYLgSWeozC0NOmcJqW9WxUHUFTbim9dRv/u8HP+YX/5cfnWBLGEOWoJzD7MgSjDN2oc9TO11yxxYtcRUsuMQmfqmn7JBKLnCzNmMKF9RNlpZ3LleKf22QJSijK0tjMiYzcDt9CrVZbQFDFb1Ndr7qI0tt2RU4ZKlOl+bp1JEyg0u2RN8EZfTNkkIGtbCIJwAAAFC91ZWv567Iq0KyVrJUD6djseMIGFxGhuAyMsTSVlPAMJVwHUx/X57CRX2O5eFcUUOWlqdfgrJkCsqQJVq2mtZbcgVdO1Rl7HacHD1uiyxBGbIE9ZElgLatpoBBvRwBhvLkCgAYY7+QZzYGrbGIJwAAAFA9BQwAAACgeuYMAQBQvWPrV5j+DpcpuV4TzGG1LdW5XVCGLMFl7HQBAJSx2hHUJYND1zeGMhV5WYJbjc2TLEEZsgTHDR33yRJLsQYGAAAAUL3VzsDYN/ZI8rH7qzKyZbIEZcgSlCFLsKz9LMkQc1hdAeNUR2ZKPJQhSzDOYXuXJSjDQoRQxiVZ0h8xB6eQAACweQ/cf4cCCFy7+56HRxciZIkpra5l9QmLKj2UIUswTNfRKVmCMmQJ6nHY55mhQQlmYAAAAADVW115WkUPypIpKEeeANgqfSAlrK6AAQAAwLIULJiCAsZAh0F0LheMI0tQhixBGUOzJGtwnCwxpU0XMEos9CRoIEtQiixBGbIEZcgStbGIJwAAAFC9Tc/AGKPvFKhDp6qXqpJskSxBGbIEZYzN0qnbZYktujRLcMomW88UoRnTqR3eppOjVSUzJUtsmSxBGbIEZcyZpT6PlSU2VcBYonAB9CNLUIYsQRmyBGX0zZLM0YdWAgymg4GyZArKkCUoo2+W9mdElMxf15VMwCKeAAAAQPU2Ucpy6gjUS5bYsrHt/9gRL1mCcQ4XtJUl6G8/LyWzJId0WW3L0OihvClyVeL64rA1p652IEts0RRT12WJLaotSxbt5NDqfpl1NlDGsdWepxjUySxrd+zo1NSvA2s0VZYO+ztZgssoXDClKn6hTzVunQn0N0WWZI8tGpKlroXGjg2+5An6mztLChlsWYn2fpihoVlStKAPi3gCAAAA1au+tDy0YqdaDsfJEpTRlQ2ZgWEOM3Pu6OtUl2s8JMuszanZTDW93qn1nWBnkV9oVwWBMmQJyiixUnpX8W+unS6owZCiRNcVCw6nn7fIwQCW0JW/pbLktCymMGsr0miPa7mDZhmydJwsMdSUC9K2nFNZYqg+M5O61ovpesyQ4kcNjm1vbVma+0g887gkSztTZqrrOVtuh0NnkFFOPb/6AFCxGneY1sSOFZRxasdKvtatb5HwGH3b7fpkyec2P4t4AgAAANVTMtoIR7agjDVOg2ScS450dT3Xlo7kbOm9ctq5LPVpKyXz2Jox79W4sB19Frbs+z3K0mlbeq8tm/Vb2uIArY85OxEd1jrI0nHaN0NdkqWu9jbmOWvJ8uG2L5ElOW7T0js954rLtWSsFvLVjj7f1ZS/m1Nmu7Xf+2Nr+rSy7WuyyK+5zuRWczR8n/k6+V5vtWSWWuuEudWQHfeuKyfsrCGP+iUuNWbRwCl2lLZwFYQ1vzf6OZe3EgX1wx32Nba3Nb+3NfHtbJSdLYDbHftNNJCBMs6t2i9r0zh1JRja1JUlM5HmY19qORbxBAAAAKqnDFeBOSt4XVOfVQ9ZgyWztMQ2MJ01HaWq/cibLK3bqXY3Z5ss8VqtZmmfXLVtbNsrsch0iec6fM5a90dqz/rW+VYm0lrDr+2HA3aGZKmm9mvKLrVofQ0AWWKMKdt7q1liveZoi7JELbSWiQ0J5rlzQ8cYOnA1UGzTFjqA1rIEY8zRvi65SoosMdR+m1nbd710G5al7Vnyu56jKLgUWWrLot/OGhtJDZeg21fi8n4wpxKZmaKdyxJzmLLN1vpcU1zKFmrNUkn6JeZQ8ndWlihh09/KnI3zkiNeY15nCgaKdJGlYWSJLnNelWENWYIuS2RpjCHbJUvszDlbb4nXLunYdspS21yFBAAAAKheFaWzpSp5ta1+XeJzmPI8ZdXK+i2dpSna8CXPXcvUdFlqz1Ln7c85O+fY+zr3+rWtnyFLbZnzHPqls9T3dces7zRFlmCnliyVer1j/bkste3sr2VK6XkR8eM554/NsD1Aw5aeTqgTYS1KZGnKPLQ2hZj162qLtWdpR6aoTdelrUs855zjNJlanz7f6OdExNtSSu+IiB+JiDflnPO0m9WuKcJeUm3bA11qb6u1bx/ltL5jMcVVeUpaeoYU9DWk3bWyoyZLHJrzkqy1tjtZqtvZbyfn/F0ppe+OiGdExLdExCtSSq+LiB/OOf9WyY1Z86W2+ij5nrf4+XHTsR9PbWIcnxs7rRcyauHzY84FNtfM58aas7T0aWDUq9cintczLj58/b+HI+KuiHh9SumlE24bAAAAQET0WwPj2yLiORHxkYh4VUR8e875kymlT4uI90bEC6fYMEe6lmHa03ptKVNbeI8sZ81HvHbOHfm6ZHotHNpCps6Z+nLGbEMrWaplVkWtnw+n9fnWPjsivi7n/Nv7f8w5fyql9LXTbNZNrQTxnC3tPFK31tvikO2v5b0qDK5bLe1sqFPb3Uqbdc4xNTiWpdbapCxRg5JXBVmKLE2vzxoY33PitveU3ZzzSh4NWqNzYREqdraQpSXfy6l1SORvndZScD+ltvckS+tUe5b6/JZPMYtpSrK0TrVmacji0rLEobq+8RUrGa5LgiFUtGruDqpvVhQl6FLrzIzatgfOqXVh6hq2AYaQJdag1yKeAAAAAEtqvtzVdfTzVCWv1qNirXDEed22mKWp23LX5yNL29DiJcJb2c4dWdqeWqfGH6p1u7rI0va0cmpGbdtzjixNp62WcERXo+jTWNay8zXVolGtfy6UseYf3lMD4Evf96n8yNZ29V2nqFV9ijV9+94+92v986KctYzpptBiERVqJEt18Mk34NyAd6odzDXvuFJWK0fCzinZ5o91cjLFOWvJUsT49n74uFMDRpniUCtHk+dw7LM4V+iRKXYO20qLV4ErRZbqso5WdaExIVv7UTSYy5xZmqIzGTLbC6bUar80JB+yxBxaLYLIElMaUrjo+nftGdqRpbpZxBMAAACoXhtlsJn0mYnRt8p2SfVeJY/WTZGlMVV7WaI1XadIlMjSlPpcmu/ckTko6VyWxrS/OabFj8kSTKFvO79ktoIsMYYCxkCXnssuKKzRmA5haJZkB47vQPXNUomdL9Nqqd25qz6VULKQ4TREtkyWGEMBYySL8sFNl+RAluCmc4O5U3kZWsiANeq7Q1TiqlOyBLLE/BQwgNm4/BT0c8n0dmB9V0GAuckQtbKIJwAAAFA9JTVgNseq+I4aw3CyBP30WTTQwn5QhiwxBwWMkQQSAAAA5qOAscc5XlCGLEEZsgSXkSGAdfGrDgCc1LUTaDYitattIUJZojW1ZWhHlrbLIp4AAABA9eoqpS2s1gojtKaWLFlMitbVkiVonSzBZfosiAtz0PKOKLGTswu1HSa2bO4snetM5ZJW1ZYlaJUsQRmyxFK0hIn1CaajxHBeyeKDQgZbJktQhixBGbLEEAoYhZSsCnYFTyDZAhV2KEOWoAxZgjJkiRIs4gkAAABUTxnsQn0riSVmT5h5wZrJEpQhS1CGLEEZQ7MUMT4TsrR+ChgjDZ0C1SdMAscWjZ1OeOpxssQWyRKUIUtQxiWnjHQ9VpZQwJiYkAEAAMDlFDBGOnct5CGFi8Nrkyt6QLdj+TjMnyxBGbIEZcgSlCFLWMQTAAAAqJ4ZGIWUrAKeO19MxZE1OHe54CEOZzH1fS5ZYg3GnmPcZzZT39eQJdZgjks8yhJbIEtMSQGjIl07YbBGXR3LJQUNGWLLpiwGAgDUwAgFqJodKjjtXDFQIQOGGVsM3H+c7ABMw69rhQwc4XaXLIwLWyYP0E/JYqDcAUzDIp4AAABA9ZSFK6Z6D0ApFjSDy3SNy05ly1gOximxrhPrpCU0QOcH48gOXEaG4HaKgTCO7FCCEUlDhB7GOdwJkyUYZsyRZ+Cmc8VAWYLT+hbUZWn9FDCAzdCpwWVkCC6joM4WTNmuFdSxiCcAAABQPTMwAABgRo4WQxmytD0KGAAAMCHT3eEyFpNmR0sAAIAZKFxAGbK0XQoYAAAwITtbcBkZYscingAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieAgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4DBZtx75424984bS28GAAAAI9yx9AbAVLqKFbu/3/fQg7NtC7TsXOFPlmCYw0zJEFzG2A62QwGD1THLAoAanSusR9gBgz5kCcros99UW5acQgIAAABUzwwMVmdXJTQTAwAA4LjaZlf0oYDBarUYSKiRLEEZsgRlyBJsl1NIAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACoXso5L70NAAAAACeZgQEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BYyNSCl9f0rpXSmld6aU/llK6bF7t704pfS+lNJvppS+quPxj0kpvTml9N7r/79rvq2HeqSUXpZS+jfXefqplNKN678/IqX0mpTSb6SU3pNSenHH42UJrnXl6fq2J6aUfjml9O7rXD3qyOPlCeJ0lq5v//yU0sdTSi/oeLwsQZwc5z09pfT26/7o7Smlr+h4vCxNTAFjO16Wc35izvmLIuKfRsT3RESklL4wIp4dEU+IiK+OiB9KKX36kce/KCLeknN+fES85frfsEVvjog/k3N+YkTcFxG7QsU3RMQjc85/NiKeFBF/NaX0J448XpbgpqN5SindERE/FhHPzTk/ISKeFhGfPPJ4eYIrXX3Tzssj4mdPPF6W4EpXlj4SEX/xepz3nIj40Y7Hy9LEFDAqkVJ67vXsiHemlD6QUnpryefPOf/+3j8fHRH5+r+fGRGvzTl/Iuf8gYh4X0Q85chTPDMiXnP936+JiGeV3D4oZYYs/bOc88PX//yViHjc7qaIePT1jtdnRMQfRsTvH3kKWaIZC+bpGRHxrpzzr1/f76M55z868hTyRBMWzFKklJ4VEe+PiHefeApZoglLZSnn/Gs55w9d//3dEfGolNIjjzyFLE3sjqU3gCs551dGxCtTSo+IiJ+LiB88vE9K6eUR8eVHHv7anPNLzr1GSunvRMQ3RcR/2Huez42rcO588Ppvh/54zvn+6229P6V097nXgyXMkaU93xoR/+j6v18fV53W/RHxmRHx/Jzz7x15jCzRjAXzdG9E5JTSmyLij10/10uPPEaeaMJSWUopPToiviMinh4RR08fuSZLNGHBfmnfX46IX8s5f+LIbbI0MQWM+vz9iPi5nPNPH96Qc37+JU+cc/7OiPjO63PznxcRfysi0rG7XvI6UInJshQRkVL6zoh4OCJ+/PpPT4mIP4qIx0bEXRHxL1JK/zzn/P5LXwsqMHee7oiIp0bEF0fEH0TEW1JKb885v+XS14KFzZ2l74uIl+ecP57SsSEfNGvuLO3+/oSI+HtxNVOQBShgVCSl9M0R8QVxVVw4dnvvamJK6dUR8eci4kM55685uP9PRMTPxFUB44MR8Xl7tz0uIj4Ut/vdlNI915XEeyLigfPvCJYxdZZSSs+JiK+NiK/MOe8Kft8YEW/MOX8yIh5IKf1SRDw5rqbt7pMlmrJQnj4YEb+Qc/7I9X3eEBF/Pq7OJ94nTzRjoSx9SUR8fUrppRFxIyI+lVL6jznnVxy8hizRjIWyFCmlx0XET0XEN+Wcf6tj82RpYmnvO2FBKaUnxdV5Ul+ac/7YBM//+Jzze6//+29ExJflnL/+uor4E3F19PixcTU4fPzhucYppZdFxEdzzi9JKb0oIh6Tc35h6e2ES82Qpa+Oq+mKX5Zz/vd7f/+OiPjTcTXd8DMj4m0R8eyc87sOHi9LNGPBPN0VV/3RU+NqPZk3xtVR5J85eLw80YSlsnRwn++NiI/nnH/gyG2yRBMW7JduRMQvRMTfzjn/5InHy9LEFDAqcV39+6q4WaX71Zzz/1jw+X8yIv7ziPhURPx2XK3s/jvXt31nXO10PRwRfzPn/LPXf39VRLwy5/yrKaX/JCJeFxGfHxH/LiK+oeP8fljUDFl6X0Q8MiI+ev2nX8k5Pzel9FkR8eqI+MK4OjXr1Tnnl10/RpZo0lJ5ur7tv4ur1d9zRLxhNwCUJ1q0ZJb27vO9sVfAkCVatOA477viqk96797dn5FzfkCW5qWAAQAAAFTPZVQBAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVO+OKZ70vocetDIoJ917543ZXuu+hx6c7bX6uPfOG6nvfWWJc2SpH1ninC1nKaJ/nmSJc2RJlihDlo5nyQwMAAAAoHoKGCzivocenK3Sd++dN2atYMKcZAnKkCUoQ5agDFk6TgEDAAAAqJ4CBotSWYQyZAnKkCUoQ5agDFm6lQIGAAAAUL1JrkICNdtVFWtcbRdaIktQxv7RLnmC8WQJyqg5SwoYVGEXjDmnLNUcTBhLlqCMJbK0/3qyxFrIEpQhS1cUMNisWkIIrZMlKEeeoAxZgjJqy5ICBlWZsrJYW/hgSrIEZcgSlCFLUMbWs2QRTwAAAKB6ZmCwWi1UEKEFsgRlyBKUsaYsPXD/1e7Y3fc8vPCWsEUtZkkBgyqNmRrVYgBharIEZcgSlCFLt1K4YKytZmmWAsausnio5cAeVktVT5ezhiD2JUtMSZbabneyVA9ZarvdyVI9ZKntdidL9VhTlmYpYBw22jU5fE9r/PFZ0qnK4pqC2JcsHSdf58nSrWTpOFk6T5ZuJUvHydJ5snQrWTpOls7bz8thntaYJYt4AgAAANVbX4mvEqqF01hjFZFhZKsceYIyZIlDpsqPI0sckqVx1pylRQsYh9OHNEy6rDmEJWwhS2t8T0uQpdOOTWtde9tb+/ubiiydtsUsMY4snSZLDLGFPM1awDh3blcL50Ot8bw02jNHlo5VvEtWwWWJGvQ557hvWz2XpSGPGeLSLBkcU4IsnX5OmaIvWTr9nLJEs3sQcy6WOSaEFvOkFXMWDi/p0KbubOFScxblFABZs7nbtzyxVrLEGlnEEwAAAKje6spkphdBWSWnlx973NhqvYyzZSWzBFt3mCdZgnFkiTlU1apKDshqnW6uwMIcpt65GdqOpzjHfv855YkpTTkgqyFLp15Htihpi1k6fD2ZogRZkqUtq6KAcaoB9lnIZqhLF74pvQ0CSCm1Zqn0Y7ueS5YopfYsHdu+KQa0ssWlas/S/nZ0/dtRZGrRlSdZYksWaUVzDISOXTlhqLlCZoDIWK1kaYqO9RhZYqy52sylWdC2qZ0sQRmyBMdZxBMAAACo3urm8ZyaVmvaEvTXcpbMxKAmLWdpR6aowVJZ6mr3Y15TlqiBLNGyNkZOPfRpvEMbeCsDSyhpiiwde9wSHSTMacosnaLvYm2WytIlr3m4cyWX1ECWWINmWsAWGq1KInNYMkvWlWFN1twvyQ5zWmOWzi1mCFOQJbZgNa3bDguUIUtQRotZamlb2Y4WswQ1kiXWwCKeAAAAQPVWMwMDAOjmiBsA0DoFjCPWdN4YANuiUAEArNVq9tSHDNimOP9rjYvmsE1TZqnPVUgOszRme6AGS/dLsBayBGXIEmuwmtH+qZAtuVNzuD21bifszNVGzxX9xnSYConUxO89lCFLUIYssQYW8QQAAACqt9pS26kq4pRToc4996nbTdGiRlNnaYpZE7JErUrOOIItkyUoQ5ZoTXMFDFPEoYzasqSjpFW1ZQlaJUtQhiyxZinnXPxJ73vowfJP2uGSYI7ZYTp8PTtdDHXvnTdS3/uuOUtwKVman0Xd1qtvnmSpDEe910uW5iVL69WVpebLcnNXGIWBtVKthzLWmKU1vRfaIUtQhiyxJhbxBAAAAKq3mtLVGiuLwDimuUMZsgRlmOYOZdjXY3UtQCEDLnM4mGopSy1tK+t3bMeklTZ6uJ3Wf2JJa8pS1+0yxRzWnKUdWVq/NlrsCPuNt6vB6zSgjFqzVOt2QRdtFspoJUu1bx/IErVZbQGjlWoiUI7OC8qQJShDlqAMWWLHIp4AAABA9RQwAAAAgOqt7jyLMaeOtHJuF8zJaVhQhixBGbIEgBkYex64/w6dI1xAhqAMWYIyZAnKkCVqsbpW6DKqUMYlWTKrCW7qc1WsLrIEN8kSLE+WWJoZGAAAAED1FDCOMEUKypAlKEOWoAxZgjJkiaWsttVdMs0QuEmWoBynOUIZsgRlyBKt0VKPcE4XAAAA1GUTp5Dcfc/Dg4oSpkTBcUOzBBwnS1CGLEEZskQrNlHAAAAAANpmmsEJS18m6Pd+/lO3/PsxT1Nvok2yBGXIEpSxP9N2iTzJEmshS8xtUwWMsYvULB1MqI0sQRmyBGVcshDh0oVBqIksUbuUcy7+pPc99GD5J53AJetczBlMlcV1uffOG6nvfWWprMMs7chUm2TpVnNkqStDO7LUrr55kqUyZGm91pKlEusBTpmlcxnakaV2dWVpUzMwSuoK9RRBFTzWbMks9e38oAVzZEmG2IIpsiQrbJEsMQUFDGCzFAfhMjIE/fQt/skUnLbLiFlM2+WbBQAAAKpnBgYAAMzI0WFqd8linnOQoe2qs0U2qOtcLqvxwjCyBGXIEpQhS1CGLFHCpgsYfSuL+2ESMLjdJVkCbpIlKGPI0ePajzTDkmSJ2mhdPQghlHEsS4qBMJx+CcqRJyhDlpiDk4cAAACA6imTFaLiCNOQLejn3GwmWYIyZAnKkCXG2HSrKREawYMyDteXkS0YR5ZgGrIEZcgSl9hk6+kbmpKDP4t/skayBPM61u4Pc9U3G7LElskSlDFFloY8hu3ZZAFjqGOrvascwnB9siRbbFGJHSDZgXG6siNTMIwsMQeLeAIAAADV21Q5bGj179QRsaFT4k2DYk1KVtK7snTu77AGJWcgDV3EU5ZYozEZOuxvZAluKjHm68qILDHGpgoYJShcQBl9syRDrFnXjtOQAWPfYp8ssQWH7fySLHVlRpbYkiH9kv0k5qCAMdK5gAokazZ0gFhyNhOsUYnFAmUJ+ju1WKAxHPR3LEsyxJSMcgozRYotWaLCfuw15Ym1meMUKlliCy7J0thTSvo+P7REv0QtLOIJAAAAVK+ZGRhLzmA4NjXqkvOVYe1Knsd/7v6wZpdkaar7Q4tkCcqYa99HnuhS/V53V6Gg77S+Ifqc1z92xfhWQmjqFn30XfvlVCc3dqG1VtqjLDFE30UDh2TpXHvTHtkiWYIyZImlVF/AKLmw0hwVwykKK1PoswNqVgldurI0pP1fsvBnTeSEEoZexnFfVxtsbe2lISvcwxRkCcqQJaa0upH3qYZ2uDLulnY8tvReKavPSu1bal+XvNdWijJMRxu4aUyWWhv8wpyGZEqW4Lw+41xZmp9FPAEAAIDqNXvYtMQimmPPwV+zU0fboUvfcxq3njGZ4hxZ6keWuJRTZq/IEpeSpSuyNJ/VtLISg7o1DwzX/N6Yz9jp72tqd7JECU4lkSXKkKWbZAqmIVt1qepbuORKBX0alE4Obuo6Z+/UuXxTXgVozXxO69Y3S8dum/KKWmscaMnSNvSZZdu1rpks9dtuWdq2uWdct5qlPmRpflW0oqkLF12PKXkKydjLBc1tzT8gXNbu+mSs785XySzVSpbocmrna+ilwS85XVKWaFVXUeJUli4pZJxrg61k6ZBs0Uff/qePvllqtU06XaYOFvEEAAAAqld96ejcpWlqqX51HQmAWvRto0MuFQVcNuOp79GoLWSv9SNzlNcnW32PEtc6M3YOjhrTh32ZYXw+y6niV+zU1MAufoD7KXG1Ftpx7Hvu+wOrrZzm86GvLe8oAXXzuwS0bjUj8DE7FefOnxzz+rU53C47X9s1ZsbFpa+1pnYmS0zhXPsp0be1ptaZlsxvSFsemiWzEtiyPu1/TF8iS8yhqlY2JEx9/37uddZg7pWEqd+pdlBy50Z7g5u2sHjtEnw2DHGuvZQoPrdeJGR7hswiHdq+ZYm5WcQTAAAAqF5VMzDGGFJJX2t179jMlRLvVVV0HfrOWurzPWsL/U2VS+onS1CGLEEZtWXJabhc4myrSSk9LyJ+POf8sRm2Z1YlQ7PkDorwU4sp2+LcGVN0oMvQ4l9t59pr29Suq42WyNJaxn5wCVmiZX1a3udExNtSSu+IiB+JiDflnPO0m9XfmIXNllBLMMd8BrVsO9MqcQ7jlE4twFajY59JK9vOMEPWZup7qcc5tNweW952ypgjS1u4RGvL204ZNWapz33ZrrMtMuf8XSml746IZ0TEt0TEK1JKr4uIH845/9ZUGzbnFRPmsFQIW/28KOdcloZM46vhUqJTZulUxznmlBvWqattDLlSwpJX2li67dphosu5ttFn52bOgjqsmSxRq16LeF7PuPjw9f8ejoi7IuL1KaWXTrhtAAAAABHRbw2Mb4uI50TERyLiVRHx7TnnT6aUPi0i3hsRL5x2E2/V6vXhlzp/H7pc0hbXejrWkHNCZYwdWRr2eqXux/oMmVVRw4zArm2B2g2ZcTonp5DQR58W+tkR8XU559/e/2PO+VMppa+dZrPWp2QIl/ph0UEzhznb2anXmnJQLEvM8Ts+5+kqfdr0FFP+ZYklsrSGBasP34MsIUttv+6W9FkD43tO3PaespszXA2V9319z5Ov5TzOIQRx3VrN0v59x2Zp7vcsS8xpzGLXJbM0ZQFFlrbhWP+0RJ9VW5b6bsMpMrRNS3/vrWVpiKU/2y2oY0+lgJqmP+2rZTugr1ayVMt2QZdjg5ga2+1U21RbUZT21b5jMHWWzr3OmM/H0WJqNUWepmjnFnmfX69FPAEAAACWtNrDIn2mm9eitu2BfbIE5bRyyuDQ7Tk226K298Q61TprcGdsli55LUeAGUOWyr020/JtEBHDpvrqIKGbafNs0ZRTfWWJLTk1xhp7JZ8hV9iCtbhkf0VO6rbJb+dwUDRkkLS2AdVhqPt0cgoX7FySB1mCMmQJyqgpSyW24dQVtmBKW8gSy1m+VVXgXMPu0wHUENA+hgRQWClNlqAMWYJyThXNItaZJZjCWrJE3SziCQAAAFRvk2WwvtW/S44KTVlh7PNaqvDMQZbgMlMuSrZklo69niwxhbHtWpbgSsn2fG7didpmZMhSmzZVwJgzJCXP/ToXLuFjbrIEl1li0DZnlvreB5ayn4Ml26osQVnysn6bKmAMVeJqG0IEsgSllLwKlEzB9OQMypIpFDAAYEMM/uBWpQqDsgVXnPbElCziCQAAAFRvUzMwxi4cY2E/KEOWoAxZgvLGzsSQPRhm6cU7aZvWAwxWcjFA2CIZgnr1LWQoXEA/c17phPUzcgKAFTCog7IOMzUkY/JIK2oqqO/n5dz2yNh2Ld9SuU1XYAWUNZqyA5IltuiSna5zz3lIlljaHDtfh889ppBxjizBOCUWDO37HE7frINFPAEAAIDqmYEBVMnUQLjMJUeNgfOWzpRLVbI2U8yk2n/Ovhd06JNteVvOpgsY5xreJSGaYnoh1Kbk1N1LOpFzzwG1WuLc4z6Zqm17gPMUNBhjbWOnwz5lyLoaXc9FXXwrJ5waWPYdcJUcmBnksWWyBPW5JEsGhpRQQzsquc5MLYVFaF0teTHmLK+Ob7ZyjvzCaX2n5AHH1ToTY+hznWLwxhRquoLClLMRl2JWBxw3tA+VpXIs4gkAAABUr64yb4P6VspLHOlSqYNps+TyWGzRqQXOzrnk6LdsQb3OrUsVIcNsz5A2f65flKXxFDBGGjvF79TjNF7WYo4pvbIE5XXl6lym+mTeecBMqaZTSfoYUkgv9dylmRK/Dms5DXjK34Cp27YsDdNmCwWYgA6Dpa1lIHmMfDGH1goZJUyZLbndni1mqMtSC1Qr+J+mZVZEY2VtluoEZYm1qGUgeS5TTr+iNrVkp8thpoZs55TZqvXzYn61Z+hQye3s09dd+vnoI8eziCcAAABQvTZKahWZowp57jVU7KCfvnmVKein9iNxZl9xqPajyGO2a+xaNTBG7RmawpTvVU4vt52WCCym9s7PTg+1qz1Dx3QtSjbFYmUtfS4so8UMDdXnva15nR2Yk+wsxycPzGZ/4FTjD79LWsF0+lyW8ZxzO19yyzlbKGScstX3zeUUv6iFlgdwRN8pumZvMKdj7cwgEgDYCqMeYLNOFR2snwHTGnJFk8Pb5I5L1T4jEGq39dlMY+nHLucqJAAAAED1lMwAjjg8sqBSDvM4dVTvMIeOAFLCWtpRyfehzwNq1fYvdYXO/eBf0qnoTNiiKRaNGpIluWMtWl2ArU8G5ZQ51Z6lIYWMtRRvWI7TsfrRT5Wjlc1sTEehwcNNlyxiKEtwU4kFQcesI9M3h/JKK5YuApzLiiIgsCYKGAN1TSufotPSmbBmsgRlzJmlw9e89D5Qk0uzNPeR6BKFC5jD0kW+sS45ndgpyNOxiCcAAABQvbbKYBXpWkgMGEaWoAxZgjLGZqnEOmennkOmaUXt68ScU6I/ldfptNWaVuTUNEMNHobpGvjJEgxzbidKpuB2JRdolzFa1mr7bXW7t0oBowJCA2XIEpTR+tEzaEXXefL7mdO30bpa18CQrTbV1YoAgOoY5MEwlxYBZQ7aYtHO+VjEEwAAAKieGRgAADDSmMsK1zaVHriMmRfz8esJAADApA7Xwuiz9sulxT6FhfVRwAAAgBm4Whb0K070KXKwTVoAAADMQMECug05HUshY7ss4gkAAABUT+kKAACAWV0yI6nvqSXH1tWgbQoYAAAANMtaGdvhmwUAAGA1zLZYL2tgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieRTxZrXvvvHHy9vseenCW7YC12mVMluAy+/2VPAFANwUMVssgEKYlY1CGLAFAP04hAQAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqpZzz0tsAAAAAcJIZGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieAgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwNiIlNLLUkr/JqX0rpTST6WUbuzd9uKU0vtSSr+ZUvqqjsc/JqX05pTSe6///67ZNh4qklL6hpTSu1NKn0opPXnv749IKb0mpfQbKaX3pJRe3PF4WYJrXXm6vu2JKaVfvr79N1JKjzryeHmCOJ2l69s/P6X08ZTSCzoeL0sQJ8d5T08pvf26P3p7SukrOh4vSxNTwNiON0fEn8k5PzEi7ouIF0dEpJS+MCKeHRFPiIivjogfSil9+pHHvygi3pJzfnxEvOX637BF/yoivi4i/teDv39DRDwy5/xnI+JJEfFXU0p/4sjjZQluOpqnlNIdEfFjEfHcnPMTIuJpEfHJI4+XJ7jS1TftvDwifvbE42UJrnRl6SMR8Revx3nPiYgf7Xi8LE1MAaMSKaXnppTeef2/D6SU3lry+XPO/yzn/PD1P38lIh53/d/PjIjX5pw/kXP+QES8LyKecuQpnhkRr7n+79dExLNKbh+UMkOW3pNz/s1jN0XEo693vD4jIv4wIn7/yP1kiWYsmKdnRMS7cs6/fn2/j+ac/+jI/eSJJiyYpUgpPSsi3h8R7z7xFLJEE5bKUs7513LOH7r+57sj4lEppUceeQpZmtgdS28AV3LOr4yIV6aUHhERPxcRP3h4n5TSyyPiy488/LU555cMeLlvjYh/dP3fnxtXBY2dD17/7dAfzznff72t96eU7h7wejCbmbO07/Vx1WndHxGfGRHPzzn/3pH7yRLNWDBP90ZETim9KSL+2PVzvfTI/eSJJiyVpZTSoyPiOyLi6RFx9PSRa7JEExbsl/b95Yj4tZzzJ47cJksTU8Coz9+PiJ/LOf/04Q055+df+uQppe+MiIcj4sd3fzpyt3zp60AFJs3SEU+JiD+KiMdGxF0R8S9SSv885/z+CV4L5jZ3nu6IiKdGxBdHxB9ExFtSSm/POb9lgteCOc2dpe+LiJfnnD+e0rEhHzRr7ixFRERK6QkR8ffiaqYgC1DAqEhK6Zsj4gsi4nkdt/euJqaUXh0Rfy4iPpRz/prrvz0nIr42Ir4y57wrUnwwIj5v76GPi4gPxe1+N6V0z3Ul8Z6IeKD3G4OZTZ2lDt8YEW/MOX8yIh5IKf1SRDw5rqbt7pMlmrJQnj4YEb+Qc/7I9ePeEBF/Pq7OJ94nTzRjoSx9SUR8fUrppRFxIyI+lVL6jznnVxzcT5ZoxkJZipTS4yLipyLim3LOv9VxN1mamAJGJVJKT4qrqX1fmnP+1LH7DKkm5py/5eD5vzquphB+Wc75D/Zu+icR8RMppR+MqyPHj4+If3nkKf9JXC1Y85Lr//9/990WmNPUWTrh30XEV6SUfiyuTiH5LyLi/3bkfrJEMxbM05si4oUppc+Mq/VkviyuFiE8JE80Yaks5Zy/dG8bvjciPn6keBEhSzRiqSylqys4/kxEvDjn/Esn7ipLE7OIZz2eFxGPiYi3Xi9K86rCz/+KiLgzIt58/fyvjIjIOb87Il4XEf86It4YEX99t1BaSulVe5cPeklEPD2l9N64Oo+yxPljMIVJs5RS+m9TSh+MiP8yIn7m+hz9iIh/EBGfFVerV78tIl6dc37X9WNkiVYtkqec88fi6rzmt0XEOyPiHTnnn7l+jDzRoqX6plOPkSVatFSWnhcRfyoivntvEdG7rx8jSzNKN88kAAAAAKiTGRgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqjfJZVTve+hBK4Ny0r133pjtte576MHZXquPe++8kfreV5Y4R5b6kSXO2XKWIvrnSZY4R5ZkiTJk6XiWzMAAAAAAqqeAwSLue+jB2Sp99955Y9YKJsxJlqAMWYIyZAnKkKXjFDAAAACA6ilgsCiVRShDlqAMWYIyZAnKkKVbKWAAAAAA1ZvkKiRQs11VscbVdqElsgRl7B/tkicYT5agjJqzpIBBFXbBmHPKUs3BhLFkCcpYIkv7rydLrIUsQRmydGXSAsYD99/69Hff8/CULweD1BLCPmSJmskSlNNKnmSJ2skSlFFbliYpYBwG8dzfBZWdKSuLtYWvD1liLFm6lSwxlizdSpYYS5ZuNTRLEfLEla1nySKeAAAAQPWsgcFqtVBBhBbIEpQhS1CGLEEZLWZpkgLGbnrTuXO6drfv/t+0KHbGTI1qMYClyRKHZGmc/f5LnoiQpbFkiUOyNJ5xHvu2mqVZZ2B0FTROnetVa1APt6vW7dyCNQSxtFOZ2qmlrcpSPWTpuHN5qqWtylI9ZOk4WWIoWTqu9Szt1LKdW7CmLE1awOiacXHufn1vq8Hhe+qz4xhR//uqxanK4pqCWFqL7WtsliLafL9zk6XtkKVpydJ0aisUyNK0ZGk6tWfp3N+PqeW91Gg/L4d5WmOWLOIJAAAAVM8ingtxTug4a6winlJiFtMW1HakoRVby9OltjCdfM3vbUqyVNYa2uEa3sMSZKks7XC71pylRQsYzoOirzWHsARZoi9ZGq7r3N1WzkFmGrI0vVMZ20JBcStkaXpryFLt21eLLeRp1gLGuUU7S5wH1SeglxiyjUOfUyApRZZkiXLGttWSi+meatuyxBada/dj+kFZYosuWetlCTJF3S30hDnDVXuQ2Y4pBlmyxBb0PR2rVq1vP+sx5c7+nPYz1fp7oU1ryRLMzSKeAAAAQPWU/HqYa8ourJ0sQRmyBLe6pP2b4QRlzJElp45Q1S/01AOyoedMHXvtKUPjnC5KkSVZog2yBPM6NW1fluAyc7RzWaKKAsapBljDOf/Htk+1nhrJEpRx6vx4WYJ2z9/vU7iQJebUapaOkSXmsGgrmrJyVmJxJpU9WiFLMMwlV8UqMVVdlliLpXa+ZIm1kaVhzMTYLot4AgAAANVb3TyeU9Nqp6xodlX/xrymiiI1kCUoQ5agDFmCMtaQJbZrkdYyxY92n+dcorPoE9Q1nfvGPKZsM61lKeL2AaEsUQNZgjJkCcro02ZLPNdQssQQzbSAtTXaPguwwTl92swcCxAu7dyiUTDUVi9TKktQhizRitr7NlniUN0tdgBT8qAMWWJLxhQB+5IlKONUlvrmUw6h/mIF9KEVA8AJU85a6npOO1u0Zu7ZfXbEALbJVUgAAACA6ilfw8qtcc0LaJ3TS1irkosEwhbJEJy2mhQMGQQaOEI3WYIyZAluNbagLhdw5dKDUg5qsQarab0lFniCNevbackSHDd04NenKCFTcN4lBT7FD7hJn8MarLYVnwqozgz6kyUox6KdACxtv89ZsqhhjMkYFvEEAAAAqtfcDAznbsFlDivasgTDyBBcRobgMlvIkLWh6JJyzsWf9L6HHiz/pB0uCWztgTDVeJ3uvfNG6ntfWSpDltZJluYnS+vVN09TZmmKnbBa26YsrdeSWVpjIWOnKxuytF5dWWq+la9xRsaa3gvtkCUoQ5ZgnCmOKh8+R8mdmjFHiGWJKW1hZsbOmt8bp/nmKyKIUIYs0arapszKEvS/ete+Le1IUq81FNRliUMW8QQAAACqt5oSVsvVub7bWssRuaGe9hf+Su/7/vwv/cMJt4Q+ZKluffMkS8s71s5ayZMs3SRLyznVvsZmacgsp6GvcUnmZQmOK5HDVshSP80v4tllSGNfuqGf29alt4+yal14sIssLW9IEfDQmju51rIUsczOzJgFzmTpdmvOUkQdi3gOMeWCnyWeu+9ztZqliPF5kqUrS2aplWL6ELK0PqtdxHMNWg4c1ESWblp7p8Z5a74aypxkaR36FBS2dBWUJchSPfbbZWvFDJmSpbZaLLAZU64c35r9juqwSr/1Tozb9R2M1rZg6BxkCcrZZUaWmMOa+ypZGsYingAAAED1zMAAmrDFo8XHqMZzTssL8c5Jlrahq88Y05fI0nGytG2yVI4s9aP1hB0jKKVkluSRLZsjSwaQbMFhli7JlCzBTbLEUrSSPQoZUIYsQRlTZkk+2ZI5smTniy2Ysu9oeXFR5qNlHGHnC8qQJShDlqAMRUG4rDgwV390WBg8fF394nZZxBMAAACo3mpnYJiCBGXIEpRz6VTzU49zFIotkSUY71gbH5qlPvefIkvGomgBANAI59pDG0xvpxWt9Sf6QTbxzWvoUIYsQRmXZunYzCg7TGzRFP1SiSzJIa2pPUv6OnbshZywdEB+7+c/dcu/H/M0S5bQpqWztLPLlCzRqlNZWjpfsDa19F0wpTnat6IgJRnFAwAAANUzA6OH/alUqn8w3tJZMvOCtXAaF0zPmI8t0a/QCi11oDmmEx6eOtL1dztjtGzJLB2SJTjN6VdsicIFlHW4joWMcYlNFTBKLk7T9RyXBLLvzhYsTZagjDmy1PWafRxmSSGdWtWeJTtutGLKxTy7/i0XDLGpAkbtdgPBcztfBoxwmizBTZes4H4uS2ZmsGWHWTq2w7e7zRFoardkmzyWiykOcLEORhwAAABA9TY5A2OKqVElOZJFK2QJylgiS6eOFh+SJVpRS5a6OHpMK2rNkllM1LnX0aCuEAkZDCNLUMZhVmovOEKtZAfqY1y4XX6Je+hzPhZwnixBGbIE5ShQQLsUMrZn07/UfTssHRqcJktQxhJZMuhjjYYUJfRN0E2Bj9o4qRUAAAConlLaRFQp2ZIp27sssSVzZsnMC9ZsiiyNORJtejutMw6jNlpkYULOFk0xvVCW2CJZgjJkCcpo5RQSxcLtqLslVuLUYml9QyJUIEtQiixBOV07aLIBw5zLUu1FENqgFZ3QJ2yCCP3JEpQhS1BOV2ZkCYapIUsKketnEU8AAACgepsuLZeoBnZV9VT/2BJZgjJkCerRN0vAaU4hoaRNt6Ipw2RgyJbIEpQhS1C/wywdy+thlq05A+MofnBISzjhVGcjRAAA22UsCPVQ6NgO33CMW316aAXd1F227FR7H9rRnDrSBfQnS3CZPjtMMgVlnDula8gConLZNot4AgAAANUzA2PPHFOPVPxYszEZkgm43ZAsyRB0M60cyqg9S/rC7aizBS7sVEC7Fm46FxqhYku6Fi87dp8dWYLbDRkwDj1VUZbYkjE7X+f6pVp35GBKl2SpJPnbLt/8QH3Pr2ptYOj8MOa21izt7L+PVt8DbVh7lmBpfXeUZAzKkSe6KGDQyeAXypAlKMOlKAGI0A9smUU8AQAAgOqZgXFC7YvVzEWFk7G61rnYKlliLP0RlCFLUIYssRQtDgBogiIgNbDjBrAcv7wXWksndux9GCgyp7VkaUd+mMLacgJrYgwF5VjziC6rHQGV7ET2H981aFzLoNKPBFPqkyXgPFmCehwbA9r5gjJkiUMW8QQAAACqt7rDNseqdCp3MJwsAbBWU8xiMjOKLdLumdtqW5kAAQAwlT5X2lL4h25DTsGXJXZWt5c/xVoUiiFskSxBvabO0uHzGzDCZex8QRm1Z6n27VuD1e5NHGs0QxvUJQNEjZe1KNGGZQkuU6JgMSRLa1mYGg7NnaVWXPKe1vh5cF7JLHFFlvqxiCcAAABQvdWVvU5VrlSzYF5LVdZVsFmLWo5OyRStk6XyavlMmVct33vfLO1vb625q+UzbcXZTyul9LyI+PGc88dm2J6LHZv2OrSxTnHOf62BgRIO2/kUP8RjsiR/tGaOQUyfXBhM0bo5s7QGJU6v1ueuU6vtfKn2KEvT69MiPyci3pZSekdE/EhEvCnnnKfdrMv1+cLnPA9SQ2SNDjNUYq2LvveTJdZkiQHimouCrWwn5V2SpTnXful6jaXbbK3bxfxaz9Kx2+dsx7I0nbOtKuf8XSml746IZ0TEt0TEK1JKr4uIH845/9bUGziFOcKkcUIZJRcRlUu2rGT7rzVTXUXV2raTugzd2epqT60eqe7j2HvrcxlZtmVslrbUdrb0XqfSaxHP6xkXH77+38MRcVdEvD6l9NIJtw0AAAAgIvqtgfFtEfGciPhIRLwqIr495/zJlNKnRcR7I+KF025iOUtWvBwFYk2mzNK5arwssSZjs7Tf/s9NU5UltqCGfmnr/Jasw5JZ4oosndan9Xx2RHxdzvm39/+Yc/5USulrp9msspY4/2rK11xq0GmwiyxBGZe26z6PH5OlsdtVa5Zq2x7KK7meWd/bt9wv1bpdXG5tWTr1+rW1Y4WdYfqsgfE9J257T9nN2Y4+C8oM/RE49Vwl1BZ22Bm6AGifv0/Z3mvtQJne2o5s9RmMzpklmdqOtWXp0FJZ6iJb67X2LM3tkizJWT/baU2VmCLAUzV2q+cSUW+n02e7Si3MdqlaP0PW5dLZE6VNkSdZ2ra5vv/a2tkSWTLWWzdZKqfke3SAq5+6WtVGDW34U6wkP/frwhzmHKDV1knDnGQJylg6S8Z6rE3Jq9mVcKpIIX/99LoKCQAAAMCSHOZo0CXTixzZYqg+VztolSxBGbIEZcgSLK9klg6zfOy5nToyzCZ+6fo0nBZN/T6EiK2QJaa0lj6nj7mztKXPlm2RJSijliw5daQcv1YbJzB0MZgZR6agLJmCcuRp24ztyhmaJdkrZ7WtWECPEx762uKlr8a4ZJqvPMLt5AKmc67/0T+tm7FdOX2zIlPlWcQTAAAAqJ7yWyFzVjQPX0tFD8qYK0syyxb0PSrV9/5jXgPWQJagjKFZOnxcnwU4ZWl6ChgXmqKRdoVEIABYC30aADU77KfWfGW+lvjkLzRl4zW4g2lYfR2AtRgyXjx3hJl1M945rWt82GemvZnx89GKgc1YqlMxYITx+gy4ZWnd7HQNM+bzsvMF3YZkSpamZxFPAAAAoHpK2hWqpXJnDY5tW+MRrzmztcbPD+YgOwBAF6OEis1ZQDg1YFS4YG0umV67c8k6GjLFlimOQxmKfVCGLLXFt9WQMUePDRQZa85LA7doTB7lD253ycwomYIyZAnKkKXp2TNpUJ8dyq77DFlNl23TNq6c+xx8TnTRNm5VMksGiGxZyd8WWWJLptwPkqX5WMQTAAAAqN7qDg9t8YhXifP5j1FJ3KYtZmhny+8dSpMnKEOW4KZz+yeXzFSnDb49Op07L7mWq6VAK7oyI0swjCxBGbK0DWvaYa+1bZ7LUh+1vadarac1M5mh5y0LX9usjzK9c2vU7MhS22RperK0brIzH1lapzVnqPZCBtPxCVNcrT8o0BpZgjJkqU2KgPXZ/y7kqX5byNAa3pssDWMRTwAAAKB67ZesDmyh0jilYxXAsZ/lscepMLZDluohS23b/67kaVmy1KaSYxPKcXpJOy5Zl4HpydIwq229BozjTP1ZmcYLZcgSlCFLUIYstcN+Ut1k6bRNtFhVRwAAAGjbJvfkTY2f1qlqoc+8Par0UI7+B8qQJShDlmiNRTwBAACA6im1UYzztNbP6VgAAMBSNr33YcpUWRac2R4ZmofTeNZHMRAAYDgjprATNifFDRjOpR9hOrIEZcgSWzLl/qMsnWaPneLMxIDpyBWUIUts0RQ7XbLElpXMlCz1YxFPAAAAoHpmYOxxKklZZmJsh+wAsAT9zzCHYzOfGzvaxDCHWfL5zccMDKCYu+95WMEKRpAdAIDzlIgoziAcypKp7XAEZ1qyBFecrw9lyNL8jJAAKqVD2w6n3E3L57p+in/zkKX1k6V5yNJ4TiEBAAAAqqe0RkScrgIeVmBVDOG8/Zx0HcWQJShDlqAMWYIyZGk6ChgbNSZUggjjHE7HlCUOmbI7jixxSJbGkSUOydI4sjQ9LfIIgb2VIDKUDN1K4QLKkiUoQ5aA1ti7OKHPj3orO2hd7+XUjpVTR7jUlgsZx96zQgbnnPut5or+CcqQJSjLWG96FvEEAAAAqueQzsr1rf4dqxZu+eg5ZW29LW39/XM5beiK9WToS2ZOkyX6kqXTZGl+WiIRcTpsgghlyBJjGTjCOHa++rHzxTmy1I8sTU8LXIFLAiJcALRG3wVlyBKUIUvzUcBYgf1KqPBAfVTjoQxZYixHj28lS4wlS7eSpflZxBMAAAContLZSLVWHVUBYRp9jzjIHlNwxAvKkCUoQ5ZYihY3s2M7N11Fh1p+EFwjnFL2204t7buvru0dkgdZ4lIGjFdK5JFta7k/KklRnkvJ0hVZms92W9nMxlzlo+vvc/84GDDD7XRELGlLA8ZThX8owTgHypAl5qB1FdI1e2KKnZylZmrYYaM159rsmOy46g/Mq09OZQsAtsEingAAAED1zMAY6dzRnjmPBm1pKjHrcek0wyHryUy1DVCDOdpx12vM+dr7ul7PQtZcYskswZrIElPyja+MQRutKdkBjW3/c3eCFiBkCiXacd/i/NwFi51zhQsoYS1ZgqXJElPwTTOYI1wsacp2d2o2k/bOWo1p29aCgdtdkqW512Sys0fthrZvWdoOnziDGXwyhXMdzxraneIfc1jiaNRcr3n4OrLElObM0twLtMsSc5IlSrKIJwAAAFA9MzCAqix1meCu7Sj5+qryzOlcllpujy1vO+2RJShDlihBAQOo2tIdwtKvD6XM0ZblhS2QJShDlhjDKSQAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqqeAAQAAAFRPAQMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9RQwAAAAgOopYAAAAADVU8AAAAAAqpdyzktvAwAAAMBJZmAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwFjI1JK35BSendK6VMppScf3PbilNL7Ukq/mVL6qo7HPyal9OaU0nuv//+uebYc6pZS+qKU0q+klN6ZUvrVlNJTOu731dcZe19K6UVzbye0IKX0N65z8u6U0ks77iNL0ENK6QUppZxS+uyO22UJTkgpvSyl9G9SSu9KKf1USulGx/1kaUYKGNvxryLi6yLif93/Y0rpCyPi2RHxhIj46oj4oZTSpx95/Isi4i0558dHxFuu/w1EvDQivi/n/EUR8T3X/77Fdab+QUT8NxHxhRHxV66zB1xLKX15RDwzIp6Yc35CRPzAkfvIEvSQUvq8iHh6RPy7jttlCc57c0T8mZzzEyPivoh48eEdZGl+ChiVSCk99/oI7jtTSh9IKb215PPnnN+Tc/7NIzc9MyJem3P+RM75AxHxvog4dgT5mRHxmuv/fk1EPKvk9sFUps5WROSI+N9d//f/PiI+dOQ+T4mI9+Wc359z/sOIeG1cZQqaMUOW/lpEvCTn/ImIiJzzA0fuI0s0b4YsRUS8PCJeGFd91DGyRPNm2H/6Zznnh6//+SsR8bgjd5Olmd2x9AZwJef8yoh4ZUrpERHxcxHxg4f3SSm9PCK+/MjDX5tzfsnIl/7cuArkzgev/3boj+ec77/e1vtTSnePfD2Y1QzZ+psR8aaU0g/EVVH4vzpyn8+NiP9t798fjIgvOb/1UI8ZsnRvRHxpSunvRMR/jIgX5JzfdnAfWaJ5U2cppfSXIuJ3cs6/nlLqupss0byZ95++NSL+0ZG/y9LMFDDq8/cj4udyzj99eEPO+fkTvN6xnq2rWg8tmypbfy0inp9z/smU0v8hIn44Iv7rg/vIGWsyVZbuiIi7IuK/iIgvjojXpZT+05zzflZkiTUpnqWU0mdGxHdGxDPO3fXI32SJVk26/5RS+s6IeDgifvzYzUf+JksTUsCoSErpmyPiCyLieR23964gppReHRF/LiI+lHP+mhMv+8GI+Ly9fz8ujk+B/92U0j3Xsy/uiYhjU3uhShNn6zkR8X+5vvn/FRGvOvI8fXMGVZs4Sx+MiH98XbD4lymlT0XEZ0fEv997mCyxClNlKSK+IyL+ZETsZl88LiLekVJ6Ss75w3sPkyVWYer9p5TScyLiayPiKw8K6juyNLN0/HtgbimlJ8XV2hJfmnP+2ISv8/NxNS33V6///YSI+Im4On/rsXG1QOfjc85/dPC4l0XER3POL7leXfcxOecXTrWdUMrU2UopvSci/lrO+edTSl8ZES/NOT/p4D53xNXiT18ZEb8TEW+LiG/MOb+79PbAVGbI0nMj4rE55+9JKd0bV/3R5+8PGGWJNZhrzHf9Wv82Ip6cc/7Iwd9liebN0C99dVydlvJlOed/33EfWZqZRTzr8byIeExEvPV6IZpjR3FHSyn9tymlD0bEfxkRP5NSelNExHW4XhcR/zoi3hgRf31XvEgpvSrdvOTqSyLi6Sml98bVqtZj19yAuU2arYj4P0bE/5xS+vWI+J8i4v8UEZFSemxK6Q0REdcLQD0vIt4UEe+JiNfp2GjQ1Fn6kYj4T1NK/yquFkF7Ts45yxIrNHWWjpIlVmjqLL0iIu6MiDdfP/8rI2RpaWZgAAAAANUzAwMAAACongIGAAAAUD0FDAAAAKB6ChgAAABA9e6Y4knve+hBK4Ny0r133pjtte576MHZXquPe++8kfreV5Y4R5b6kSXO2XKWIvrnSZY4R5ZkiTJk6XiWzMAAAAAAqqeAwSLue+jB2Sp99955Y9YKJsxJlqAMWYIyZAnKkKXjFDAAAACA6ilgsCiVRShDlqAMWYIyZAnKkKVbTbKIJ9RsF8oaF6uBlsgSlLE/WJQnGE+WoIyas2QGBgAAAFA9MzCowq6yN+eUpZorizCWLEEZS2Rp//VkibWQJShDlq5MWsB44P5bn/7uex6e8uVgkFpC2IcsUTNZgnJayhPUTJagjNqyNEkB43CAeO7vBpDsTFlZrC18fcgSY8nSrWSJsWQJypAlKGPrWXIKCavVQgChBbIEZawhS7uinyIfS1pDlqAGLWbJIp4AAABA9aqYgaGaz6ExU6NarCCWJksckqVx9k8tkSciZGksWeKQLEEZW81SFQWMna5zkffV0vkd7ihaGG45awhiabLEGLJ03Lk81dJGZakeW8jSuYL5sdx0tcnaiu+yVI8tZGlLZGk5a8pSyjkXf9JfvO/j5Z/0wNINvs8O4lBLv6eaHassthrEe++8kfreV5bGWfo91UyWplNLuyuZqVreU43WlKWI/nmSpXFqeU812mqW7nvowcFZGtoma2l3sjSfwzytMUtVzcAYorZqfQlrfE+ltRzCWq2x3a3xPU1Bnspaut1NUQxc+j21QpbKWrrdydJyZOmmEu1w6XYnS8tZc5Ys4gkAAABUr9kZGDtdlb39qlzJSt0UlcSu11BZvGnNVcRayNI2yNL0TrXtKc75l6VlyNL0ZGkbZOnKlO1PlrZjC3lqvoDRpc/iUcB5sgTlHGZHlmAcWWItlm67skRrJjmF5O57HlYNgwJkCcqQJShDlqAsmYJhrIFRsQfuv0MVFAqQJShDlqAMWeKQQsY4srQ9ChgAAABA9ZSrBjpc6AYAAGAM+xQwzKSJWcvO/rHpXId/m+I9mkbGzlqyBEuTJShDlqAMWYJhZklKq8FUQKA2rWYJaiNLUIYsQRmyBP1ISCFdxQ4/QgAAAHA5i3gCAAAA1TM9YGJ9ZmaYMgYAAACn2WNeiPU1AAAAoD+nkFTk7nseVtgAAACAI8zAOOHUKR1zFBoOX19xAy6zy5QswWVkCcqQJShDlrbDDAwAAACgegoYIz1w/x0W3QQAAICZLLIHfji1Z02FgL7v5dT0pnNXLjE1Ci4jS1CGLEEZsgRlyNL6rady0JhjhY5zQRNEAAAAtmrWAkbXDvju7y3OxGhxm2nfmmcxwZxa7n+gJrIEZcgSnGYNDAAAAKB6VZX29o8qqzpCf6r1t3K6FZQhS1CGLEEZskS1eztbmiJ/btHOvveHU21jzRnakSUupRh45Vw2LJIG/cgIlCFL7FQ/QtviIHKL75nLaDPHnftc7ISxo3DRz+Hnc/hvWUKWhjnsh/RL7MjSZWRpvapPxNAjqq049r5af08sZ8yP85ra29jOSafGIVka1+fKEodkSb9EGbIkS9zKIp4AAABA9dZTnmvMfmW0b4Ww1Uri0/7CX+l935//pX844Zawb01TE4dOE2w1SxH98yRL89lClrreoyxR0haydKjlDO3IUn22mKU1OZeprWcp5ZyLP+l9Dz1Y/knPaDmg535kWg3skMLFoTUH8947b6S+95WlYc4t/itL6yJL02k1K+fIUre+eZKlYdaapYjxeZKlK7I0zJqztDM0U1vNUruteEW2WFnssvYgMq3DLG05U7LEJfRLN8kSl5Clm2SJS8jSTVvP0mpmYOyoLNbnWDVxy8Gr/ajxjizV6TBPstSPLI0jS9tR81HjHVmqkyzdSpamteYs7ewyJUvHs2QRTwAAAKB6ZmCcsNRli7ZQWdyyLR41liWmIEvzvb4srd/WjhrLElORpXleX5bWzxoYA1wSiK7HtjxVC8aSJShDlqAMWYIyZImlaCV7pqzkDbmckUVqaJ0sQRmyBGXIEpQxR5YizudJlrZLAWNma7ouMyxpSCcHdJMlKEOWWJNzl6af6/Vbz9LXfffXRETEP/7+Nyy8JethEU8AAACgem2XtI4oUa3r81jTlVg7WYIyShyVlSWQJShlTJbGzMjYYpZ2My66/m4mxuVWV8C4ROtTlKAWsgRlyBKUIUtwGRk6ratwsStYdN3OcFriSJcuHHOq8rnFaiXbVWIRpq7ZIrLElsgSlLHlLJ3bCWN7SszE3WKWDjMjQ+WstoAx10JKJYMJNZIlKGeORclkiS2QJSijK0sls7WFLHUVKA6LggoZl7OIJwAAAFC91c7AAAAAxnO0mEvUPmtiTrJUjgJGISWmRgGyBKXIEpSxpSzZyWJKW8iSU0amp4BxocPzxlpbYAZqIUtQhixBGbIElzksWLS6IOcQChbTSznn4k9630MPln/SApa8/E+fxabWFF663XvnjdT3vrJ0O1liR5YuI0vs65snWbqdLLFPlrqdy0qfheNlaTu6smQRTwAAAKB6TiGZSZ9q5hbOC4NLyRKUIUtQhixBP+eyIkv0sakCxmFDX3K64SmCSe36TJetgSxRO1mCMmQJypgiS1M8pyxtl1NIKvbA/XdU3xFDC2QJypAlKEOWoAxZ2p5Nf9utVOuhVa3MeoLayRKUcexorTzBcH2yZHYEUzADAwAAAKjepkvOKu4wrVOVePmD87qOXh3LklmF0O3UkeDD7MgSdOuTJZjSpn+ZW+mgLFJDrYZOa186a7JEa7qKgLIE5SyZJ1liTZbss2RpO+rec6+Eo8YA1E7/BGXIEpQhS0xBq+qhlvBZGAfKkCVaVUt/tCNLtKL2o7OyRCtkiaVZxBMAAACoXl2HcgCAs5zaCOMcO3pcy9oy0BJZYila10IMPlmDWtquDpOtmHoqrCxBGbIEZcgShzbdEgQBLqNTgXnJGpQnV1CGLDGHTbeyWna+uo6ojbkkpYVqmNPS2TkkS1CGLLF2c/VfssTayRJzq2vvYyG1FDLOETYoQ5agDFlijZYYF8oSayRLTMFVSAAAAIDq1T3lYGa1zMRw/WIoQ5agDFmCMmQJypCl7VLAmJlwsSZLFv1kiTWRJShjTJZKZUCWWJMls1T6uVgXBYwKCSytGbuw0tRkidYcttkxA8cpcidLtGZIlna3zdHOZYnWyBK1UcA4opZTSQDYpjH9jz4LbjckFzIE3WSJWljEEwAAAKieAgYwmbvvedgUPxhBdgAAbmd+z8zmPDcM1mx/eqI8sVZznNIoS6zRElPYZYk1WmotJvtMdFHAWIhODsrRybF2c63NtGSW/u5LnhYRES9+0c/P/tqsT4kFcQ+NWQNgySztyBRz6XtpU1niEk4hOcEUXihDlqCMMVlqLX9/9yVPu23QCEM9cP8dtx0sujQHrWUJaiVLXEIBAwAAAKieU0gqYPo73G7MlPk5s2S6O7W7JAdLZAmmsPTlHGUJypAldhQwKlJ7IaP27YOdKdtqiU5NlhhqqZ2w2rMEU5ii3csSWzLl+EaWUMA4Yulq/dpYsHS71pSlWjo1xQ9aVzJLl+RBlmhdLf0SHGrt91WW2rKevYsCatnZ6hv6Y9tb0w9FLZ8n86vluy+Zpd2pIoed3BwrVNfyeTK/S777kgPIObI0t5r6S8ab6xLDEbLEusmSLLXCIp4AAABA9VLO+fQdUnpeRPx4zvljfZ/0vocePP2klaj9qOaYayfXcESpz+daw3Yu5d47b6S+95WlMqbM0pSLecrSaWvKUu0Z2mk9S8e2pbWpzlPpm6dastRKZrq0miXOk6WbxizIPvY1DslS+7qy1Kc1fU5EvC2l9I6I+JGIeFM+V/Wo3CUhmiOIO31fY+5BV9d2bX3wt0WydBlZokT7rzFLEcPb8f/wnF+8/q9517OQN5ZQa5agpC33S0zn7Deec/6ulNJ3R8QzIuJbIuIVKaXXRcQP55x/a+oNrMF+Y2+94j8ln812jP2ua8/SmAVnrXnBEmrPUsTwosIUhYTDz6b2GYycVmtbn1oNWWJdZEmWWtar9eacc0rpwxHx4bgqQd0VEa9PKb055/zCKTewpNanSHVp6SoftW8fp83RvpfM0r7ap5XXul3c7thv9NLte05LZGnKI3LMb0t5OaW2fqm27eE8Wbqi7bbtbCtOKX1bRDwnIj4SEa+KiG/POX8ypfRpEfHeiGimgAEAAAC0qU8Z7rMj4utyzr+9/8ec86dSSl87zWaVdWm1sc/ja6loqihSs5ayBFMo1b7l5Dify7r4Putx6rsw9qyfLLEmfdbA+J4Tt72n7OaUM3VQtzwNmG3ZepbObdeYAVut75W2yRJsw5xZUpRgzabMkuxMZ3U9/1yDmS0MmrbwHukmS8eN2Uls7T3Spi20sy28R5hD3yzJHPTTtWi0QkZ5q/lV8gN7ZWhI5lyUkbrJUD/nPqe5ZqxQL1kqa6rPU5bYoinyJEv10h9Nz2c8v09begMAAAAAzlEyWoEhlW/TmTh02CZUkvvpypDPcbt85+Poj9iRocvIEjuydBlZqpvWvQJTXe/+8L5TLHTD8nxvZR3LiSxBGUOzdPg4g/q6+Z6m19W/+MxhGkMOFBr/9ePXamOm2HESNrZIltgxi+kyU2Zp99zHXsOMxPrIzmWW+vxkibW5JEuXFAllqR89BbfYD5fwwHiytH52tuZRMkuyWCdZWs7YWU3HHsvyZGk5l+RBloaxiCcAAABQPWW6lTmcNnvJlObD51AdhHFkaZ2cMjK/sVmSOejn3O+aLMEwslSeUddKDR3UGYBvj/P2oSwZWo7zhqEMv2NQhixNp/lPVuPop+scRwvKbJfCxfxkaZ1kaX5dWfIdtMn3uDyfOZQhS9PzCdObna91svM1v3NZkrU2ydJ8fNbr0PVb5/udn8+8bb63esjS9CziCQAAAFSv+dKQKtetHLllLFmCMmRpOo7Ur4uxyvx85jCe/NRBj79SNQzmFFPgMsdyLE/L8Zu2vHN9W1dBQ5bqIkvLGztOlKW61DDe35L9z/vSArosjafV01vfUPkxhdMu6aAM/KHbkP5HluplHDGdKT5bWaqHWWnzkaXlaN0Vqu3H59IQHatWUo9a2tkUasvSTm3bw2l9BxRr/l5rzRJtOdd+ttC+ZIkSutrPltrVElnaHwds6bOujUU8AQAAgOo1WzpaY9Wra3GynVrfc63btWVbn/XSapaGMM2wHmtoT11kiSmtof30JUtQhizR/je8IrU21sPtWsMPw9rV1obmVmuWSlrze6vN4W/flj77LbznNb+32mx5HLFkluaa9i5L85Gldbe3Nb+3ErbX6hvQFcylf6y2+CO5Blv4oe9Sa5Zo2xYztUSW5JQ10i9BGbK0Xb7Zih0Gb0uDZcrRbmSJMgyK5s3Slj/ntZMlWaIMWZKlLbKIJwAAAFC9ZstIa1yw5ZwtvEfmt8Xq/ZbeK9PbYoZ2tvieYQpLZWnLv1+skyyt32o+4S0WNFq0xXPHWyFD63Due5O96cjQusgSWzLlzpcssSVLZmn/9dfM6Ao4SiX5Msc6kJKfpe9lOX0HBzJUxpAsDfnMfT/LG3qFH9/V5c59xmMKsbK0PN/B/GRpOav9dOa6ZBSsnSwNM3flu29nt4WK/FLO7XzJ0Dh92uy5z3zKq6NQzrnvy2d+mUs+P1lqix3gaclSHSziCQAAAFRPeY6ImH66O8BaDZ0Gz+VKnGqgj6tP1xFK39XyTh099v3Ux0yMesnS5XxKRMTxgbcfPxju1E7slIs82mlenu+grEsKQlP0X77f+VkYt4z9z+3SdlzilDhZolWyVAc9AWeVHAhuNWhQmizBtA77PjNs5uMzrs8Ui1D7nqenCFgfWbqcVszkthaqtdHZ1UWe4LxLfrcOMyZzy9nq4LwmFhxcB2O55clSORbxBAAAAKq3iXKctRz6K3luF+vgEpDjnMrSJZ+jI5JsTZ9+ySmO0M+5PkQ/D/3I0nJ8skBvioFwGRkqy+e4bqdO5/HdlzXl52k9meXpe+Yz52e81SxpxXS6NIBbCxN0MWDgkMHkOD4vdmToMnN8bsaB9VIMLMfnN79NfeI6u3nosNZPluYlUzAd+WrHsdOJ9Ef1OZcpmVuOvKzLVrNkEU8AAACgespvDLbVah9MRaZgHrIGy5E/KGPrWdpkAcP0qXG2HhYoTaagLJmC+cgbsAR78PS21ZVuAaibfmkbfM/z6br8t+9gHU59jw7wTqPPAfS+B9m3nkctFBjNbCa4jAyVsfXBHExNttZPPzSNU5eD3um6xHDXd7L1PFrEEwAAAKjepkttjnyddvj5bL3aB6XIEof0R+PIEjsydBlZQobKGJOlrlO2umx930wLDYHta+thoZsMnXb4+cgSlCFLHNIfjSNL7MjQZS7Jks+8H58SUIxODy4jQ+PY+YIyZGl7fOfTOPe56ufH88ntMXC8lc8BypAlgHkZ013m8HOzc7te5644I0OX8fmV5xM9QmDhMkPP5QNupR8ap+SRxCGfvZ07tmjK3yeZWk7XVTP0R/UZ852sIVuuQgIAAABUTyntBBXH40wrhDJkiXP0Q+PMfU63c8jrJUNlaONALfya97D/Y60DhOEMIPsxQISyhmTqkt8nmWUr9OPbYUyyTmv4Xv0KcbE1BIF5KAb2I1NQ1tS/NzILrI2DT+u0hn5KixxojjD7wYAyWs9SyWuJr6HD2rKl2/LSrw9DKSoBrJNFPAEAAIDqOZQy0qVHo/ocEXDEizUr2b7P5an1LO1v99ijiY5GrsPSbXnp14extN226LOALn7FZzbmh/iSTveSH/6+r6dzYQlrzBL0NdV6MocZmeL3vdYsHW7XkNfSD7ZjC4WMU+9xC+8fWDe/XheasyO4ZHB1yeupgjOlJQZTtWXJQJJa1P5735WlEhmSw3XpOzMvot3vfsh77Lqt1ffOfKb83YUxtLxCzu2Q1DoY7KPlbacdW9ip78rSFIMBud2OKdrPuUJG19/nyu3h69dQCN1/ffmrh+/ktNp3Rn1/9aq97Qwxpk9rddy6hkxZxBMAAACoXhulogbNUdVquXIG53RVtqc8J//U+cJz6NoOWaePkkeDxra5lqfl9z0C12daPm2p6UjqkKPaJfvFWmYx7bT2+7FlLf/u73T9zg/J1ppmpNTOJww0Ye6i4K4DWmKqnU6QEvq2o7l3ulubvtrKdnLcJQs+70xxtawhp2mtrS8YciU+6mEtjHptLS9aHMARNXTMW+uQmMZSCzIveUTXFUQo6Vy7GrMeyhba3Rbe4xZ1rUEUcb7dT1kM7Lq99OvXZKsZW9e3CFDYVjsH1meptrxEAcVVtJjCmOnkJV93iSve7fR5bTnj3G/vmGJg39ccs30lXn9nbcWRmlnEEwAAAKieUhEAMLkljs6eOhrYdR63o8jUasm22WcWyBRHtWnTue98jW2ihplSW6GAAdAQVyiB8Y4NLBUu4DzT45lCn9/fKX6jp/y9n7KQoZ+64tcIoEE6MShDlqAMWWIKrbWrKRYq5VYKGAAN0akBAGtybKe/1fFODVexWzuLeAIAAADVUxoCqNx+Fb/VIxKwpGNHxGQJhju1EC7Qf+aFLI2ngAFQOR0alCFLMMypnTF54lKttaFTRfBLThlp7XNYmgIGAADw/+eIMIy7bHAXWSpHAQMAADbkXIHCzhaUWZBTlsqziCcAAABQPTMwAABgAw6PJDtVBM5zadS6+BYAAGBDFCxgOFcOqYMCBgAAbICdLShDlpZjDQwAAACgegoYAAAAQPUUMAAAAIDqKWAAAAAA1VPAAAAAAKqngAEAAABUTwEDAAAAqJ4CBgAAAFA9BQwAAACgegoYAAAAQPUUMAAAAIDqpZzz0tsAAAAAcJIZGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqp4ABAAAAVE8BAwAAAKieAgYAAABQPQUMAAAAoHoKGAAAAED1FDAAAACA6ilgAAAAANVTwNiYlNKLU0rvSyn9Zkrpqzru85iU0ptTSu+9/v+75t5OqFlK6ekppbenlH7j+v+/ouN+sgQ9pZQ+P6X08ZTSCzpulyc4I6X0xJTSL6eU3n3dRz3qyH1kCU5IKT0ipfSa6wy9J6X04o77ydICFDA2JKX0hRHx7Ih4QkR8dUT8UErp04/c9UUR8Zac8+Mj4i3X/wZu+khE/MWc85+NiOdExI923E+WoL+XR8TPnrhdnuCElNIdEfFjEfHcnPMTIuJpEfHJI3eVJTjtGyLikdfjvCdFxF9NKf2JI/eTpQUoYFQspfTclNI7r//3gZTSWy98ymdGxGtzzp/IOX8gIt4XEU/puN9rrv/7NRHxrAtfFxZVOks551/LOX/o+p/vjohHpZQeeeSussTqTNA3RUrpWRHx/rjKUxd5YlUmyNIzIuJdOedfj4jIOX805/xHR+4nS6zKBFnKEfHo66LgZ0TEH0bE7x+5nywtIOWcl94GzkgpPSIifi4iXppz/umD214eEV9+5GGvzTm/5OC+r4iIX8k5/9j1v384In425/z6g/s9mHO+sffvj+WcTYmieaWydPC4r4+ro13/9ZHbZInVKtg3PToi/nlEPD0iXhARH885/8CR15MnVqlglv5mXB0tvjsi/tj1fV565PVkiVUqmKVHxNXs2q+MiM+MiOfnnP8fR15PlhZwx9IbQC9/PyJ+7jCIERE55+cPeJ505G8qWGxJqSxFRERK6QkR8ffi6qgXbE2pPH1fRLw85/zxlI51U7B6pbJ0R0Q8NSK+OCL+ICLeklJ6e875LWU2E6pXKktPiYg/iojHRsRdEfEvUkr/POf8/jKbySUUMCqXUvrmiPiCiHhex+1Djhp/MCI+b+/fj4uID8XtfjeldE/O+f6U0j0R8cDgDYfKFM5SpJQeFxE/FRHflHP+rY6XlSVWqXCeviQivj6l9NKIuBERn0op/cec8ysO7idPrM4E47xfyDl/5Pqxb4iIPx9X5+bvkyVWp3CWvjEi3phz/mREPJBS+qWIeHJcneq4T5YW4BSSiqWUnhRX51N9ac75YwWe7wkR8RNxVVV8bFx1aI8/PD8ypfSyiPhozvklKaUXRcRjcs4vvPT1YSkTZOlGRPxCRPztnPNPnrifLLE6pfN08NzfG92nkMgTqzJB33RXXI3tnhpX5+y/Ma5mN/3Mwf1kiVWZIEvfERF/OiK+Na5OIXlbRDw75/yug/vJ0gIs4lm350XEYyLirdeL0rzqkifLOb87Il4XEf86rjq1v74rXqSUXpVSevL1XV8SEU9PKb03rs5J7jz/HxpRNEvXz/enIuK79xaNujtCltiE0nnqJE+sXOlx3sci4gfjamfrnRHxjl3xQpZYudL90j+IiM+KiH8VV3l69a54IUvLMwMDAAAAqJ4ZGAAAAED1FDAAAACA6ilgAAAAANVTwAAAAACqd8cUT3rfQw9aGZST7r3zxmyvdd9DD872Wn3ce+eN1Pe+ssQ5rWWp8PaOztKY7ajtt4Sy5sxSpfrmqVi/JFPrJEvzZ2lHpuYztp0P+Y5k6XiWzMAAAAAAqjfJZVQdNaav1o4el2AGBlNoLUuFtrdYlvpsTy2/IUxrw0e8zMCgKFk6a/YZGLvvRPbGWWr2pizdapJTSADglF2HvuFOGQCKOuxTu/ra/X8rZpTl85yeGRhUobWjx5cwA4MptZqlkdttBgaT2WBxrdqjxrRNljpVOcaTx9udasNzfF4bzNCOGRgQYfoclFIiS4fPMXcnrXABAPq6oeb8vMxavZVFPAEAAIDqmYFBFZaoLDr/jzVqJUtjZl4cPveU79FvAo54QRmyxFoYG9RBAYPN8iMEZZQ4hWSq5x/6un4XYDryBbTIb1ddLOJJlaao0tfy42MRT+bUWpaGzOYYkqXoWCytlt8F6jdXlhY8Sj35woPyRsQmZmJYxJNJbSBDOxbxZFv8AEMZSyxU1erzwyl92t+cp0oB63bJaZpQK4t4AgAAANUzA4MqjVnwSeUYbidLUIYsDbPl985pFvVcjlyyBgoYhTxw/60f5d33PLzQlmyPH+N1kaXlrDlLa35vXWRpOSXbW2s7e1vMGtNprf3XSi7XZeu5aG4Rz92ArJaB2OEA8RK1vKcaHQtoqz/GFvE8TpbmIUvrJ0vzmDtLMwxUL1p4sNXfEZY3JktjLsU9o8UW8ZTDbams3U+hzUU8uwZiSxcySg4QD5/TgLGbH+bylm53srQceVoXWVrOHFnqeo2lBrBr/v04bPfnsiUf5fRtV4f3q7SQMZs155FuW233FvEEAAAAqrfoKSRTHC3a2a+GlzyCNOU2H1LRX6fapr0PObIkS9SktiwtRZaIKHIEbtC09zUe8b00S/KxvEqORM92Cskac0gZlWThUkeztEgBY87BVst0hOu01E5Xidz1nU5bG1lapyFZisZ2umrNmCzV74JB66idrlYydWjqjMnK8hbcgZu8gNFq7rqcyqMsldVYYaPNNTCAaXV1DKdmW7RayGC7WhvsncsldDnV1qcYuB4uptiKY7MLS3IVoOUdtsnGdtyOai1n5/TJnrWYOGQkVDGBZQ5d7axPu2ulkCFLUIYstW2rC75BRLsFjbUVLSLGjRv1P9NqqX+wiCcAAABQvUUOm7Zy1Ba2yLRXqI/+kpKOHdEde9RtjUeH2YbaZ2S0mC1jyPrVdknuMWYZEWnMsLxzhcM+fz/Mrp0qmJaMUasWd672zZ0t09/rV8sU+pazdTjW7MqZdZ7qU0v772OWVtK142QmBrRFVuG8S3ZUZIzazblzNcVO/9IZU8io39wL4a7R2H28Y7lYOrNb00IhY9YW4ccagLU6HGTZUYFxpszSqefoO2O4xA6V34c2tbBzV4OSs+9lZBklTzUszSKeAAAAQPXMyQGACYw5auTUSrhdbUdg5ZTWZ2KcWt8Mupxb+HauhXH98gLABC6ZIm4HCW6q9XSLw5zub59137ahtSv6HGt/teaL+p1rs6fycUkRcNZf0cOA+BGH+ckfAJRzbMfPziA1OTXm01aZ02FRY8yiuYvswdhxGkZlFMqQJVpz7ipep26bsq+VJRin6zKTssRS5miD2jklWcQTAAAAqJ6pELBRTiWBdhweteqT2ykvAQlrIhOs1ZC2bZYErfCL3RA/LOyUaAslBmytFkFkiZJaa/8lyRIlyZIsUUZtWdKuKamu1g0Mcuq8+CnpiGAZFmKDMmSJNXvqvZ91y79/8b6PR8Txtj1l8UyWmMKsBYxWj9ZCbbqyNKQTkkcoY84sLT3rCuYwR6aW3rEac1oY63Z4eclLnuPQrqBx7LkVLmiNRTwBAACA6in3VkS1ktp1tdHajgrLEktYY7tb43uiXoftbUvtb0vvlXK6ZlwcGjOro+9zX/o6MJQCRgV0WpS2XxQ4177OTdWtrThxiixBtyHT8mUJYBklTiXZmaNwoWjB3BYpYDj3/jJWqmanK0t92sZhO9piLmUJypCl7Si5cwV0GzMDYmdIPse+jt8AlrLonsqYgc5adq4uGeQZIHKotjbRysyL2j43WJos0dfhTo+dGVjeHDmUdZZmEU8AAACges1NZ1jLNPchaxTAFA6zdHgqSUtMX4fz+vSbssRYc8zIMHaCy1xyWgrUotkqgOtnQxldg0A7MlCGnS626NSOUoniRu19VO3bxzrNsUbN1NmGc+z1V0AnR42OzXaqvY3KEjXab49LtNExBX5ZYqzDHZhjOzslZ2vU3lZr3z7WacqZFooULG01BYw+p5aYtQHzkDWox1pOvaQufQoVx+53iWPFwFrJHcA0Nv2req5zmfsqKar01G5sG5UluNUSbXTMDpUscairILH0Udna2uphzmrbPoBWuQoJAAAAUL1Nz8DY6boawyXPdcgUQhhGlmAaprbD9OSMtZrjikNwil/VPVNO6xvSkZlmSE1qa4eyRMtqaouyRMtaLRDIEkvaFRtcTpWWtfWrP1JNnUSrHe6+r/vur4mIiH/8/W9YeEvYspYWc4OayRItq31cVfv2sQ2HsyT2/z20mGHGBUtb3a/pFB3FseeqqSgyF4ULAKBGWxyXQV+7IsWx4sPQWRmnngvmYBFPAAAAoHqrm4ExBVX9K2ZeAABAm0rOnjATg6UoYJww5UJLp845VjCBYbpOHZMlGEaWYFqyxJIUG1iD1RYwhnQQ59bL2L996mJGi6yNQS1azxLUQpagLJliDksUKPbXzlAgYQ6rLWD0YUXoyyhcAADAeLVc2vSw+HB4ikif7XNaCXOwiCcAAABQvU1MQZhyLYstM/OCQ86bBwA4r/ZZCofb1zVD4xgzMZjSpmZgPHD/HbOdNjLnawEAAO2676EHL97hv/fOG7cUFg7/XVKf7Z3y9dmuTexhH66qfklhYehsjsP7n3ptR6tp3ZxtWJYAgLUZMtPhXAFhjhkQx17jcJu73oMZGoyxiQLGOV07O5cUOsYUTZzqQitqOFXk1KWIZQnKkCWAeR2eftHiTn6fmRn7/z/mOdiuTZ1CAgAAALRpUzMw+pzGce7+cxyFcsSL2g3N0tS6tkeW4DKyAzCvLcw82MJ7ZDp17H0srGsnbDdwW2oAZ+cLypAlAABonwLGESV2cmo5Mg1zUCAAAACmZi97j8IFXGbOQsaxU7tqO7UFAAAoxyKeAAAAQPUcpuyhzyKeUx7xNT0fbncqD4e3HV7OWJYAAKA9ChgDmZoO7VGwoHaHfYs2CwBwO3vje2o/OmuASyu6slTyksQlnqv2zLMdh+u3aJsAALdTwDjicOC4P4A0AwP665OlsTtoQ55LbmlN14K0ChoAwJZZxBMAAAConsOSCzGrA8Y5lpfDo9Uup0qrDmdYaMsA1MCpjdTCiKgHA0co45IsDXmszNI6A0UoQ5YA1sUo/4S5doLGnrd/6kg01ESWoJ/Dttj1b+0TTlPIhjJkidpokSMtMa3XgBXKkCVaV/KKPrAFin9QhiyxNIt4AgAAANUzA6NCLpvHFnVV9EusmyFD1E47BwA4b5MFjKGnf5QcFBpgsiZTZGmKXNrBo3Yls6S9gyv4QCmyRG023RL7Humd+1xjg05aI0tQxpxZUugAAFqz6QLGjsszQhmyBGWcO5Vw//bDQoSCBNwkD1CGLFELi3gCAAAA1XMIFABWwALQAMDabbqAMWaxtEunvTvnmDXqysXhwk9TZOnweaFlfYsQsgQAbNGmCxh9HRscdg3y+g4klx4w/t2XPO2Wf7/4RT8/+zawfod5GJOlPqtfL1kYlCWmNOTywkPb/7FsyRJrseUZSbIErJkCRmEuNQRlbGmwCedMWVgoOZsDaqMvAVgXi3gCAAAA1XOopQJzTtk9nFYItRtzaVZZgsvIEq0z8wJgnRQwBpqyQ5xywGiASG1kCc7r04bHtvNTOTm1AG9pu/PzZQvKsOYFsGYKGAO1dhURA0Jq1WqW7GwxhyG5GJulU/dfYi0M2WJprfVLAFu0iQLGlAOxKVa57tuB9lmF3oCQkmRJlijjXJYuyVrtWeoiWwDAORbxBAAAAKp39hBPSul5EfHjOeePzbA9xSx1Kbg5XnfMaxyeD3k4HR66yNKtZIlL9G1ztVySu+/siZLbKUsAQJc+I47PiYi3pZTeERE/EhFvyjnnaTerfjXtXI2ZHvw/POcXr//LeZ4sS5bYssM2t2urY3JRMkslChdD86RwwVKsfQHQjrOjnZzzd6WUvjsinhER3xIRr0gpvS4ifjjn/FtTb+BQSx+tWsL+e+7b+eqkOWcNWepq513vTZaYwiXrQszt0oVA99+rnUJaoY0CtKPXHkrOOaeUPhwRH46rw4x3RcTrU0pvzjm/cMoN7GsNO1slGDByqVaytN/G+27zkPcmS1xqTHubcjvmuHTxUq8PAGxDnzUwvi0inhMRH4mIV0XEt+ecP5lS+rSIeG9EVFHAAAAAANarzyGfz46Ir8s5//b+H3POn0opfe00m9VfK0eLoXZrzNIa3xP1K7kuBGyZ2TsAHOqzBsb3nLjtPWU3h1LO7bgZDEA/ssQc5rjqyCU7g12P7bO9fR8jSxyaok0MyZg2Cd1kiaU4PAk0yewKWvH/a+/+Y+7b7rrAf1bntiJwO7cMc+OFqkzEr2Mhk5qq0cmYqRoRM6IEYqJ/iIDG2HDHhDqjEsSgbQaHIPIrgTTVzDgJNlWDAQXMSK8aHHEYqwGLcEtBJncolhoabiFiS9f88Tyn97nne/Y5e5+z9t6ftffrldy03+c5zz6/1nvvvT57rbXPnbgdt+Mst08dclzIuOb1Zn+P9GkoS8B1jIAiq27PHpz4LM+ObJtkCdoYc3ebsduYs5M/x758yuu1z2GsW9rKElmCXlxT4DvOjiyRxSvWfgEAAAAAl3RXQlP1u43RExzI0m1kiYM5R0nM6dRzXGrXt6yf0XKbbFOvWVqbEbIMaTG1Srsim+3v1bna1J2ehdngtFuzJENMWUfjFkMdoSxtUDa27ZYh6mP/dkybOd5G1vObPRRnyGdKu9dGmYNWtTNrXN14+Pu1D/bQSi9rE0B2TnA5mFJ8WHKUUpZ98rXv+ZrRVvQt2341W5boW67WfUa2IO7JtTsbO6mcZGk9YzPhKnMflsxSLyd/S3Uwx45iGlqEjj6da1Nj21vPbWHoNZumxZKco7A2i3gCAAAA6bkUy9WyzgmFqda+NZgsMadLV22nrAkwpU1eu27SLYbWLpAlplj7mDDVlNcrC/t2yz5xzrVpYAqticnshNiqteZXw1gt20zLYsTahqaMwLFTbWSofWdv90tSDGzv0ZNPnf398y9+qPlztvz+ZIm1OMIzmhNCspvaeTl3QJ2zI5Q9S7/h1a85+/sf+/mfW+iVwHnZO1WyNI0C1PyuzczaGdtjlg4FjmsKGbLEkC1kKX2rFrw87Az7tofvrZf3KEssKXsn/xbH70mm+mbkG7QhS2yZRTwBAACA9JTOiIhtXpmDS+aYN7/FLPUwnHANvY2kmaN9zzm6Q5b2Z8lMbbF9DX1+W3yvsnTekreQ3mL72pMes5T2rKuXE8KtOLWDu/Y72MOBsyeydJ1rT6TnzNLxdufS48GMdcy5kv0tWRoztUSW9mnK997L+cylXJxaZLG3qWVbzNJhbYtLi3lm0aLt9NbutmgLWdKz4WXmXrDQDovMWrbPuQpHDv6saY0OXcuRIw+3JUv7cs33PFTInnLr6+xFkBY5kKV5nSpwXCp+tLiDiVu8k1WqAoYrxXfWGJbc21BozhtztXEP33WvWZLHvuzh++o1S0PbbL1dtm1sW8x2wWbMnbbmfh4uGypGnCtSjB21ccuIozloK7Tg6J3Icai32OFUpc9ji+3rQJZYwxYLGWOzNKUd3nK74zmuCMpSPlmydMvzLznyItvnJUvXuVTIeOjWaSdLtxWjOWjJXUgAAACA9FJdJtr70M49VK63/N4yOZWlPVW/W2ZpiStbt8zNZj23XGHtZVRQ9uNSy4yznmxZmmva0tzWbstrP/+eXLsA6Lm2nT1LcKBVJTR0wphliCDbMsetRLPoJUvZO4lMk619tXApS9cY+tsxJ9gt7+xDXktnSfsgk0NxosWCnEuTJeaUtnVt8QRwqiXnT+75c966qfeF32L2rsnSGh2kLX3me3CpHZ3LUq/f9RrHpVPPodi3LS2ydGkb5x7Xax7h2KViR7YsTRkRAgf22B1Z6wC7xQ7tnl1z1XNrht7rXJ9BL9MFYKpbRg9dmtZ2TU6y37KS+WTdr+5p+iZtjRl5cTyVpMWojaxZggOLeAIAAADpKbEx2pwjMS5t05WKdlTWHzf3Z3J8lVqWtu3cKICt5m/OIcWn/n7sqKYWI0Ra3DqWNlpkKcv3Z7RQnu8iq2tGU4x97NJZOj7vGbMP1z4Ykv5MyvSFZU3ZCR1M6TD5HtcjS8uaI0sP/8b3mM+YqUlb//6mvK+x7b9Fls4VQca+5q1+Z5lNWQel5dz7JUzplPVS7Jja4cz6Pnp0y5SRJbN0yx2GWuglS5zXzdF46yd9a2uxkvwc340dS3uyNC9Z4hy5e8mco4VaZskJ73q2+FmPfU/n2m6LxRbJb+27j8yxH13jHLRFlsiluzMpna+8hr4b31VOspTXFu9eAWuQpe3r7Xu81GGa8n6yFdfWfn5us0SWsuY1W5Y4zyKeAAAAQHo5y2AsruUQqhZX9lU+6ZUsQRuyxDlZr+SOtcTQdW2WMZa+tTzcqtuWafh7Pi2/C3PSliNL+chSn4ayZCHj9chS3675zHs7pl3zOi9NP9FGaWHtLN2ysPNYstSnPvbupGbBQWhDlrbp3Pe69gniVsnSNtxyx4LesnXrnSBObYM+ZVm8c+jfeyjSy1Ju22hlNHPqdn/nHgOcJkuc4+RovDFZOvVYtk2G8hm7QKnvLpfevg/tCIt4AgAAAOl1f6mityGCPVvjns2qq8uRpeXI0raNydLx9yJ/bbQYhj9ElljSuWH5t4x0uLUdj8nUpcfIUt+Oj1dzHbda7c9vyRI5OVNikBNpaEOWGOLkaZpzc69hq4Y6csf7jzHHGpnhWksfr5ZYy2goS73o9XXfajNn1a5ebcvegpiJLG2LLK3nmizJ3zhrrIUhS9xiiTsnLNFGWyzYKEt9a7F/vWVtsCWylN1eCxcHzpBIZa9BZF+W6KTKEnukcLE/WU/ks72eDHwm+zX2uz9VINNuHrf3z8QingAAAEB6RmAANzPsfRqfE5esnampUzTOPd4wc+Yw9ursklnaYps99zmvvZ9iWWO+76kLy45pX3Bsc3scO9PltfzMDRfLY8r3mjVvc96R4JrXcen5ZWmbxswZz/Z9XXo9c7zOOeY1yxLH5jhP3HLbaFmclKVtmfI9HudOG7jN3j/HnL0OunAcmhadxb0GkW0bW7gY+rcssbSsxYSDobsvyNL+rHEiv6U2seTnt6XPjetc2kf3TJaWo4DBaFPDcu7+40P2XlGkreP2lGWEliwxZI22uYU2cs0CcQeytA2Xhqgf832+3DXtfGqBUJb6tva5Uy+08/lZxBMAAABIbxeltCxXXXt3bUXR587cpmZ87X3CLdV5edqnMfOHs7eNJaaSXPO3wG1kiTlNWTSafbDHWcmYRd2yunTC2Nv7oU8tVqxeu1MoS0x1ro33clK3RiFDlvbD8O3byBJZaGsM2WzLyH7g2kIot/AeuKzHK71DblnAb4lCBts3dc549mNZS0NX2abkQ5b241KWXLUdZ+hzlCUO1spSb3cuyf76tmRXe6e1h40znpXic2uZpWu39fDxl777sduess1eyFJujkvDTn0ma94aWZZyk6U25shYi9EcsrSeFtm6ZTFd3z3HLOIJAAAApLfrMrVqPeRxSx4vDS9ceyj6pSta9kUM6WXo7JxuWfdDpuA2c456ajFF1T4yN7fW7UdP38Wuj+xObLbFfNe+tCw2TH3OLNk//gyyvD5ZymPLn/0S7X3tTMnS8tacZrQHc7fhocz21Lnas6l3gyOfHqZL7nKvvvYJDWzFtbcv3ZvjE6+hhansk/Zrz20g2+1V2RZt4DZrZenSAo4KHMtrce7i+8mnxbF36WL9/s6UgNWMWSRzjkWiWppjMas9dlrZlhYnsJeuvJ7720vPcc1QddNTYP0O59QRNaf2F7csIMnjrvncfNb5LHl3vdbfv0U8AQAAgPRcPgBW0evVy+wjRNiWLMOir1ko95Yrp9e+jimGrs5eM8rDwoNktsVbhI9hAcllnNsX+myZg7NpNsfOEtiatU4Kp3bMx7yubPNtlzxmmLfP2rS5x/lM2vEZ8tBc7WHXBYw9L5q2ZQ5Ey5MlaGNslk79fuw+79y2Lz3/lFsAL7lfWHu/P/a9Oi4tb0z729r3MmU008FWPoM51rvh5cYcQ/bA2irDLOIJwKrW7hwyztjV+sdso8Xj1yhortVWx75XJ7w59baPmyNbWQsaLd5rlveyB71laao9Xai7ZprkUt+7RTwBAACA9PZTRmKUa4beZbPVqi+sRab60ts+e4/OjZKRt227NNJhzPSwPUzbvPa9ydK6tvaZX9MOs49CuWbEYLb3st093wR7OBBckq1hHhvzHWV/D3sgS/uU+SDXK1m6zTUnkGtOeTn1M1lqY0qWrp1Gce47a3n3nSVsqd3J0jJ6/HynrOc0VdbPo8Vd9LK8N2dGDwx9KVs6gczS8MYauupwi2wh3KI9ZKlXY+Y0tjhppw1Zml+WwsWBPM3j3Oc6ddHaod/3nMs178YzF1maxy2F4Ut/2/KCyNIL+GZtb1ssyvS7p13QLfd6v+Z5bgl7S2seiKectLdYeZ9lLJWlJS1128hWbrnaZ1RAHlvM0hx8Noxxy91/uMzntj8tv/Ml72TVm15f960s4gkAAACkt8+yzQ2Oq/Rjb1d3rro/xzSJXl167y2udu/5881k61fz135f17TzqVcfZSmHrWdpbXNkqcVz0N6es7TEbRJlaT+GsnTcf1r7Vty9Z33OdZ4yZ6nvb21FLQ9y1xZDTv275T3mlzyQ3xKSbPcmZpo52tnYLLV4jqFO/VpD/Jdo57KUU69ZykqW9kuWbrNGsVuWcrpUyLhlmy221dJW1gXr4fWXWmvzjT7/4ofab7Qzc44CWDogcx7A9+jRk0+VsY+VpXkXYcpy0LuGLMnSVLJ0mizdGZsnWZKlA9k5TZbG23KW5ON2Q1nqZy+5ES0a85x34lg77DBWyyydyoMssBdzZAn2aK9Z2sqVZ3K5tT2tnSW5mI9FPAEAAID0+invMosl1gZQeSS7tav0Q069Lnkis6yjmGSJ3mTPUoTzPPqwdpbkpL08e8SNydpIt7aYINu3ZDsac2K2xsFPlmhh6XaUsTAoS7QgS3fkiVvtKUsKGe3k2hMymzmDKohsmaIf9EeWoA1ZgjZkqR0FjJ0YCk3L2xjBlkxt37IEp8kStCFL0IYs9c0ingAAAEB6Chg79/QzH1UZhAZkCdqQJWhDlqANWcrFFBIiwgrt0IosQRuyBG24cwi0IUs5KGDwMkIIbcgStCFL0I48QRuytB5TSAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9Eqtde3XAAAAAHCWERgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGBtXSvkvSinPlVI+XEr5lqPfvaGU8sOllB8vpXxTKaUMbOMr7h/zY6WU37vMK4dchrJUSvnEUso/KKX8aCnlPaWUv3JmG7LE7p07Lj14zHeWUv7NmW3IErt34RzvVaWUt5VSnr8/Pn3hwDZkid27kKU/ct9f+qFSyveWUj51YBuytJAn1n4BzO4/RsRXRcRn3//30LdGxJ+MiB+IiO+OiM+NiO95+IBSyusi4g9HxGdFxKdFxD8qpTyqtf7yzK8bsjmXpa+rtT5XSnlVRHxfKeX31VplCU47l6UopXxBRHx46I9lCT7uXJa+MiI+UGt9VEp5RUR8yvEfyxJ83MkslVKeiIhvjIjX1Vo/WEr52oh4NiK++uEfy9KyjMBIppTyp0op//r+v58spTx3y/Zqrb9Qa/3+uAvmw+d5JiJeXWv957XWGhF/MyI+/8Qm/mBEvKPW+ku11p+MiB+PiN96y2uCJSyVpVrrL9Zan7v///8pIt4dEa89sQlZoktLZen+uT45It4cEW89swlZoktLZikivjQivub+cR+rtX7wxGNkiS4tmKVy/98n3Y9Uf3VE/PSJTcjSgozASKbW+m0R8W2llFdGxLsi4uuPH1NK+WsR8TtP/Pk7aq2Dw9ePfHpEvPDg3y/c/+zU435gxOMglQWz9HB7T0XE58Vdtf6YLNGlhbP0loj4qxHxi2ceI0t0aaks3R+LIiLeUkp5Y0S8LyKerbX++6OHyhJdWipLtdaPlFLeFBE/HBG/EBHvjYgvO/FQWVqQAkZe3xgR76q1ftfxL2qtX95g+6fWu6g3PA6ymjtLEfHxYYZ/KyK+qdb6E6cecuJnskRPZs1SKeX1EfGZtdYvL6V8xrmHnviZLNGTuY9LT8TdSMB/Vmt9cynlzRHxdRHxR48eJ0v0bu7j0isj4k0R8Zsi4ici4psj4ivi8VGCsrQgBYyESilfHBG/Nu7mWJ36fYsrXS/Ey4e5vzZOD4l6ISJ+9YjHQToLZengbRHx3lrrNwz8Xpbo1kJZ+u0R8YZSyr+Lu/OTp0sp/7jW+sajx8kS3VooS/8h7kYxfcf9v/92RPzxE4+TJbq1UJZeHxFRa33f/TbfGRF//sTjZGlBChjJlFLeEBH/U0T8jlrrx049pkVFsdb6/lLKi6WU3xYR/yIivijuqorHvjMivr2U8vVxtyjNr4+I//vW54e5LZWl++d6a0T85xHxJ848TJbo0oLHpW+Nu8Wl434Ext8/UbyIkCU6tWCWainluyLijXE3vP53R8SPnHioLNGlBc/x/r+IeF0p5b+stf5sRPyeiPi3Jx4nSwtSwMjn2bhbKfq5u7Vi4v+ptZ7rFF10fzXr1RHxqlLK50fE59RafyTuhkT9bxHxK+Pu7iPfc//4PxARv7nW+hdrre+5rzb+SER8NCK+zIq6dGKRLEXEz8fdau8/GhHvvn+ub6m1vl2W2Iglj0tDj5cltmDJLP25iPg/SinfEBE/GxFfcv94WWILFstSKeUvRcQ/LaV8JCJ+KiK++P7xsrSScncDCgAAAIC83EYVAAAASE8BAwAAAEhPAQMAAABITwEDAAAASG+uu5CkXhn0+Rc/tPZLWNyjJ59a+yXwkjLhsamztKZzOdbed0OWoJ2xeZIlOE+WoI2TWTICAwAAAEhvrhEYJOFKNEs6jIqY0u4ujYg63tYeR1ABAAA7LWAcOkS9d4SyvY+h16GIwi1tNEv7BgAA1rXLAsZWZOnYXXodD3+vmLFN14y8AAAAmEIBg9FaFEx0dLfJ9wkAAMzNIp4AAABAekZgALNZepqTkSAAALBdChgbM0cHLstaG3DJ8RQlU5bYs6l3+AEAyE4BYwN6PAnVsdyHte6Uo+jGnilcAABbpYABABsyVDhUuAAAemcRTwAAACA9IzAYZBg+vev1irMpVrSkHQEAW6GAAZCUQga30G4AgK3ZZQFjKyML3HEETuu14yZ/AAAwrNRa59juLBudYssdgS0WLnrtcF6pTHjs6llqaal21nt7Ovc59f7eGtttlmAGY/MkS3CeLEEbJ7O02REYD0/y1+6cw97J4Hk+H1ow5QgA2Dp3IQEAAADS2+wIjCw+8P7TH/HTz3x04VeSmyuH22RkASzH/hMA2LrNroFxypKdqaHCxSlTixmHk9RT7+faE9hsHc2Nn4jvZt7+nO3qVMaOs5S9Hd3y+WR/bwvZTZZgAebtQxuyBG3saw2Mh7IWLo7/ZmwhI1uxYQ5GZGzf1Ha/1jazGtoPyAwAAFu12QJGy07+mCu9vTs3qmNNChnbcipLcxYdjtvzHtrRHt8zAAD7YBFPAAAAIL3NjcCYYwTBwyvDh6vFUxfnvGZqyZKyjbxgf44zMkeWjOgBAIB+5e5VJ3ToVE3tRB13xuYqaFzbQTv1eEUNbtVyalL2IiAAADCvzfUI5ljLYUzHaer8/a2toTE3V877dvjeHj35+O++//kPv+zfLbKxp8U8AQBgLzZ7G9W5Rg9MnTqSzVABoMfRFrcWq1Yshrj14xmXvs8xi+qOLWCsXRBbIndrv8eZyVJjxwXFg0OWNt6e9s6tH6ENWYI2TmbJIp4AAABAepsdgfHwKlLL0RFGYGzTwlcVXTUeYU+jE+Z8r1ne40xkqYFr2t/G29VeuWoMbcgStHEyS5stYDzUsnNwfNJ2KJT0UsBgnJlPznW6JthD577XYk2CtWlkqbGxbTFLdm5x/F638J5upNMFbcgStLHfAsbB8cl2yxO1vY9g2Jtb2sSjJ5/S6Zqg1879FNn2H5c+j3Ov12imvilgpCjMrUWnC9qQJWhDAWPImY5ms22xTdfcflYBY5olM7VWhyXrfqPllLNbPlvFwHmZQnLaDgsZOl3QhixBGxbxBAAAAPp0ekXKndnR1RUa2+EVuk1LNDUihZYjQy5N4dvj50suQ+3dfh4A8jCFpJGsQ8BbOj5528N7noNh79fJ1t7mXBRzj859nqaQLGdPa2ActMhdb5/Hqfc8IU+yBOfJErRxMktGYDCaq1DwEnmY354LOmsZu8j1Ftp/1vZldBIADFPAYLKsJ32whpaLAO/ZFjrEe9RLZ3vu9jXn9u1jAOAlFvEEAAAA0jMCA2AGD6+aulI6nhFe67r188/e7uduX9eOSNHuAWAcBYwbOekALrk0vNx+hC3qZXrJnC5N/7gl+9dMLbGvAaB3ChgAC7lUyGjRqYGsFDReMmfGrScDwJa5jWojOhyM5daP19lixi51MLb4nluSpfks2faW6GjvPUtjiqNuo8q1FM0eI0vQxsksWcQTAAAASM8UEqALW5xeYUg9LJODU9vc0r7kkj29V5Z3fHx2LAPmpIABkIROBlyc5jDbtiGT7Hf0OaWX1wn0TQHjRk6GAGAZt17hffh3jt/04po7zqwp+0iM7K8POM8ino04EWIsCw+2IXPI0vyy5uzajkfW95OBRTxzuaatZuuQr1EouCXjDV+nLEEbFvEEAAAA+mQKyY1czYF1GAoO+2UIOFvT4jiWNRdTXtelz2HOBb0trA19UMAAuqRoAehwwOO2UMi4tA1gvxQwAIBNUNCAl5zq7C+RiaEc9lZ86PFOMLAHChgAwEm9djwOen3d7M9xB3mLbfd4f5J1/6JYAblZxBMAAABIzwiMG2WtHgNAK4512+RK8/6sMc1qaL9hfwJcQwED6IoTHliPQsY2KFzkd+o7mvPOG9oE0AsFDIAN0LFkSVtsb3tYg+BAp7VPvdxCdOhvt5wpYDkKGI1s8WQOerXHPO7pvZLHFjv9W3gPbNulY1yLY2CLgkZvWVLQgz5YxBMAAABIr9Ra59juLBvtSW9VZ5bz6MmnyoSH7z5LYwwNh85+qzZuI0t9kLu8jvaZY/MkS8mslbGtjMCaYeSFLEEbJ7NkCslMdJhgOZdOPuQQ4CWGym/LWuecY6eZOAYDLSlgzGwr1WnokfzBsmQsD0WK/VnrmKdwASxJAWNhY04o7PAB6NG5Y5xjG5CJIh/0ySKeAAAAQHpGYCRk/QyYh2wBW+eqMmuvhZGdjEDfFDCA3bE2Rh+cZMJlcsIxxfrTZAW2YdYCxtCtDS89fsrfbJkDECxD1vKw798uOQNgL4aOdc5zbrfICIxLhYwtncxorADT2UcCMAfHFzKZeoGfx1nEEwAAAEhvlhEYQ6MQLo206LkSdem93VJtM+wW2DpXJABoyfGENYztr516nDY7Tqm1Nt/o8y9+qP1G7y35xc5ZMLjmfShg9Om4APXoyafKhD+fLUucJ2/rG7GflKWOyVhbDc6PxuZJljqx94yt2BmUpR1rmTsFjdNZSnEXkikjDMauMTGl8WS9I0GW18F1jtuVnVBfjHwCoGeOY9A3o1NPW7WA0fLLaLFztoNnTnZCcJl87IfOFQBbM8exTR/i5SziCQAAAKS36giMta+6fOD9T9z/74cjIuLpZ+Z7rikVs7U/F26TdUoS0/jeluWqAowjKzBMPtgyIzHupFgDI4tDQePpZz7abJsKF9t27vv1ffbHd7acFgsZ7/0AvhWmkoyjvcPw/kI+2JO9FzJmKWBkvwJ9KFTMSeFiH3x32+B7XI47MAEw1dCxY68dONizRUZg9HZ15ZaRGGN3pL18FrAlcrcehQu4zhwdtFPZ0hHcroff7Vb2q9or7JdFPAEAAID0Zh2BkbXKexhZcWkqyZSRGEZesBXn2mivVzzkbn3H8zV9J7AceaN3Q2241/MS4HqzFDB6OVCOLWRcw8k6vcq+hg190544pk205fNkD7IULkzHYsicfcC9t7Fu70IyZydrytoXlxqQEwl6d2rubC87TvmDvOSzLZ8ne7D2+Udv50Fs097bYbcFjJZuuW2qkRZsXQ9tuofXCNyR18edW2Rx7yeqkInzfVifRTwBAACA9LodgZGt8mkkBhnMsQDnFm+/BizP/mOcqftqnysAe9JtASMrhQyWcE27Ov6bawoaWYcwW3gU8rNmVFs+L/Yk6/kHsDwFjJkpZDCHJTvsD7c99LzZTizkDtbXomi6ddd8JvZrAPu29+OpAsZMsnbs4GCojZ47Ob504pyt3StkQF5yOY3Pi2ttoe0oiNKbJXJ36rw727n4HBQwZmZKCUs4t5O6tc2dWwNj7M5xrZ2pvEEe8vi4U5/Jlk86WdaWMzfHecWYz0s+uWTJwsUpe2ij7kICAAAApGcExkK2XAUnt6mV2DFTSoa2ecsaGYaHAgBLm3KO7nyeIUu0jeMR/Xs9V1bAgA2Yo/N/y9BmJwOwT/I8H1NRGWtPbWTvHTm2bewFw71RwIANyHpie83r2vtOGdg3o9EA+jO0r852br6kuQqMChiwAcc7xzG3Ph3rmp3OUOHCiTjANHs++YWx9no3BrZJmz3v4iKepZRnSymvWeLFAAAAAJwyZgTGr4qIHyylvDsi/kZE/MNaa533ZQGtLDHiYolt3fL8rmACwPadOt4bicGa9nwuOlfmLhYwaq1/oZTyVRHxORHxJRHxLaWUd0bEX6+1vm+WV7WyD7z/5R/L0898dKVXAqfNuRN0oAeAfp07fu+xE3Xg/Aa2YdQaGLXWWkr5mYj4mYj4aES8JiL+Tinl/6y1/tk5X+CSjgsXwDbsufoNALzkuJBx61ph0Iri2jgXe+yllD8dEX8sIj4YEW+PiP+51vqRUsorIuK9EbGZAsaQh4UNozFY0xwH1T3tLBUyAGAd2QoFaz8/++IctJ0xQw4+NSK+oNb6Uw9/WGv9WCnl98/zsgAAAABeMmYNjL945nf/tu3Lyc/6GKyhZbW2lxEXbsEKANu19hXptZ+ffXI+ezuLPsBO9L7DtPgW5DcmnzoLsJ41pnFkPW7bF8HjzuUiS5Z3VcBQaWUvsuxg5nAqv1Pfb7Z5uLAn8gd5LHFuLOOQX0853VUB42Cos/Poybv//f7nPzx6W4cpJaaSsKYtFSwO+Xv6meWeU3ET1nNp/yWXML8W5xGyCvltIaevWPsFAAAAAFyyuREYW7oSDQd7bNdTRje1WvDT/H3I51Qu5RDyGTqGyitsQ5b16DZTwJjyQV7ekW7mY4HuXXPnn+Md7DUFDidckNfUkyd5hvVY9wbW1zJ3txQyWlx0nKWnfm1VZk87tONOWcT162h85G+8dDfbV37pb7z6NUEPTmXn2CFLQ/uUMTte62LAdpzLuozDMmQN1jPHeW2LERnXFDRSDTV4+IJ728kdD3e/NPz94c8Pj526IOjDwsXxzxQy2LOxWVLIAIB5OX7CtrWcWvJwfzG0PYt4AgAAAOmlGoFxTYV26UVEjq/oDg1nnzIdxC1YoS2ZAgCAl5tzZPHQSIzWz5WqgHFuCkkv96eeOg3kFodpIqemkuzRb3j1a87+/sd+/ucWeiXc4r979MkREfH9z394sec0leTlZAmAViziCfsyd8ZTFTCA/Rk7b+5cUXDMwp4Ap+ypOAkZyBxwi7Rn/XNMDbl2h5l9OsjDBTuNxniJq8S5HefwMOLiMALj2LnRTceL50619FS03k7eZIk96C2XAHCtno95FvEEAAAA0ks7AmOsoarRmLnsx9s4vno7ZjTFrVd+WzDq4o6rxNtwae2LMevMjF2LZqmRF73N/5Ul9qznq1LQE1mD9fWYw24LGJc+5J6+hGspXLBH54oSWQoWQ/awXwKAKc4t4g9wrNsCxtrVouMrvG7bCNMcFxM+8P7zIy9uydhQ4eKaux1d2tba+yYAABijx/PVbgsYQ8ZM5bilI3S8/aHnU9CAaea8feoSxYXjwoYrStAneQWAvCziCQAAAKTX/QiMw1XOKVdtxy7WuebCnGM8vH3qgXUx6N0SIzGW4Cou9Mk0MFiP/MEyes5Y7h76QrIXKqY4VdSALTiX00xTtno+IAAyDACZbabnPudV22tYGwP60eLuJDo9AAAwr+4LGI93Gtq9pUOxYUsjNGANpwqL2YqOAACwB8cX73q6EGcRTwAAACC9bocWDFWJzo2auDR945qRFsfPd/wcQ7ddnWsqydzbh1Z6H3nRU6UauEymAdibbMe+MdO6uy1gTDFU1GhZ0BhbMJijsHDqdSpkMKfjnV2LNSSGXJtf4LxDEfFhlubMMsAl2TpTsBc93QFoswWMc52bS6MmplizUDCmwKLTx63G7MgOjznu/FwzymKNNnp4nYd1OcboaUfPvpwqTJzy9DOP/2zJ4mQWMgzrkkFYz/Fx/txx//h8f63sbraA8dCljv6ci3RmWwjUyAzGumandPibMXfhmZqJbFk6WHsnDgdjCxcHezweyCnkIY/Ql6kXNc6dI99ygcQingAAAEB6uS5ljtCiWpvtCu4a9njljfVtOXs9346K/jxsX1vOFWRwaX++h6lWAAdT94mt95G7POuZYyj60FoTQ3chOfe6bnHpLigw1jVTI1q0tzWyNGXti7Ee7qwVM7jV1OkhEbdlaY5MQG8u7bsP2Xn05AIvBmBBrad9tNRd73Zsp2rMbVQvdfZPnSiO7aAtUTgweoIlXHNL4jGPz5SlWwwtYPqQdTK41pjCRcvC9VYLF7LHGFPbyVbzMjd5hD4NZXfpwkbunsENWnbul+pAzTGtQ5GDW/WYpanGFCGOH3tpGw8fd/iZQgZzMjUQbjN2KmCWq5C9cMyD/mTez1nEEwAAAEgv5+XQlRzPD57javEtQ+lhDVPWchgayt6yjc9xdblllXnKaA645DBE/TCV5OCWWxIfb0NbhdNkow2jD4GW0vecj3d2LQ4mx8NsWw67vbRAqGIFPVvyJGRKlm7N7hxFh1NTSOBa5+baf+D9Hx783Sl7LFyceq86U7Asd+sCWkjbm740z7yFKXc1GDLUcbpmUTXzlunF2I7PlI7V2Cydfp6+5v67GkVLh+KG9nSZzwjyaFFYPHc+Iu+wTWkLGFszx2gPWMvhpODQno+vDh8Pd+/FqVETToDohePLZW5vDLkNHXuvGTE29DeyD3mNGcFsEU8AAAAgvV2OwLg0t37o8acMXfEa+vm553bVjN4MtdmhhQfPmZqlU8937NIVnHNXYVpeoZljLR8Y0vIKJsDWGJkBfUtVwMiy45hSSDA1hK06lcehg37LKSNjCxnnFjU8uNRhG9Ohm3O/ZJoKLR1nQsHiPAsKQl5L7r9kH/qSqoCxtGsW2hy7rS0VMhRnOBg6yA+NLBozeumS420s3Smb+nxTCj9Dv3cyBctbsqC4dvEUeIljMPQlVQFjrcW1lry16ZTnyjbETSGDW92StV6uJrd4nUZmwLZM2S/IPaxD9qAPFvEEAAAA0ks1AmPLzl15HjOX/yFD3ejFmBEXQyN6ehlxMadTn4G8Qz/G7sfkGgDGSVvAWLOTfjxV4pY7hhz/7dRixdKWnE4DEY9Pl9hT4WJov7anzwCyuZS/Mecj2aaAAsPkEtY3JYfd9FbnmBN+qbM+R2f+1N0aMhQ1zr1Xa14w1lBbHtPue+m0X9oHnXsfY/df54o5Okawrmv2VfIJAI+75vjYTQHjoGUh49wIi0uG/ubxTtnLf3/qdR//rJeOHNs2JWtj22yGYt21WhQfrn3OMduy8CfkI48A0JZFPAEAAID0Sq11ju3OstFzbrnKMXR70DEjM8YOme9lGsYWp5Jku/3royefKhMevniWztnzaKGp+5iHWTrsJ+bYLyy5SKAswTg9jryYkCdZYhPmyqkswXjncjiUpe6mkAy5Zfj0NSfjx4WLU3P8e/Tws9jagp7XvJ8sHbUsshYsMi6G+bDtzLl/GJpmMmcHSpbgtB4LFwCwtFuOl9vqoca02w5e6twcr19xytiOydpXLl/82m+NiIgn/+ybRv/N8Roha7+HqVoUYI630ct737JD5lp+F1N2oocsHUzJ1JyOCxkt18SQJQC2xtpRsLwWeUs/heTaNzn3lddbr6gudfJ+3Nk6yNLpmsOSI0eu+R4Ne7/OucwtkaehLB2MydSSRcChE7P//tf8to///3/y//7A2W3IEoyzhQ6QYe/sVev8yhIMm5K3oSxZxBMAAABIL9UIjLWvYByuNp671ePx8PVrr1AuPXz6mikkGRyuFl+6UvyQq8bbtPQIjKHREr2Oano48uJYhpEYskTPnnnNfx0R045V2bhqzN616ofIElw2Jm+pF/Fcu3Bx7PB6elnE8uHrHOoEZO9cHTvX2cpgD/P3hxaHXNqSC+SeyvxxIeOQpUtTSrJo8f3dWrAds20AWJM1MWA5tyw+30cPfSFTTtKnnsjPeZLecttbvI1qS3v4DI53ILccyNcufixhqDh4qrCYdSHcoZFOcxZxs30GcIv3/9yPnvz5EncDkiUA9kQB44E9X13sZbTJWnr5Hq8x5wl2i1EchyldS4zEOHcb4bGdhXOjONZ06GAdhro/tOSw9y1nac9O7UduLWCe2n9kGRmWgSxBW0ZewPKuyZ1FPAEAAID01r8smMjQFJJzV2WZx+GK8GFo+5TFPOecr891TlVXxyyam8nx1c4W68osOQT81MiLS4Zel2ztxxIjtK553PGIrLH7kYfbmmMUxxyf11DejMCA6xjJBX1b9Sw061CtcycF2U8YzhVfetTziu6cd2ibh47IUAfkpf3E/LurLXbMD5+fLDFFi+Pz0LSvOY5LlzokS51vtFwEcIv7I1jSpRxm7YfAlrXInaPjlaYWCua80nrqJGfs84w5Qeq9CDLk1Pva06JoxzuQtVbfPnzWl553rYUwpz7PuRFAx9vaQzvbw3ts6VIOXDG8M9Su1u6QXPv8ez4Wwy3Wzjww7Fw+b7ngoIBxpTWnKdzynFu8otPyPe3hBNHBfhlbnnq2h5ys5VIhce6hzy33D9nvvjP0WY79jOf4rKAFUySAJQ0dD+faB616Vr3H+y2fO5EbGtWxVudnqydUW31fYw2drPeSw1O5yP6dZn995DO2kPHwsVllb/+97PuAl8yZ2z32T2CKoVHcS3EXEgAAACC9bY1rXsG18+On/O745+dGZLS8a0DWYb/X2sr72Lul2qX2QgZLXAl0lfE6D684+QzJ4LgdbnEqiazB+tbep8xSwJi6w9zDUK2lOkNbm2s/ho7mbXrL35zft7ZEVmufLAD5HR/Pt7jfUNQF9tfb3YCl18bY2kgMxjl14uOgDmxFywVTeysEs21bLFwcyBgwaw94yxXgDNZe5JNtcZIObN2p/VyLQoZ9Irdae1E8gAzG7Pss4gkAAACkV2qtzTf6/IsfetlGb6kiu6oxzRKjMUwluc2jJ58qEx7ePqArkmda2nOWWtprLi+dm+ztc5mQJ1mawbn2ZjTG4zLnU5agmZNZMveAyayJwSWZTyxg7+TzPJ8Pazq3/pRCxktMaYX9Sl/AsIOaZmpR4ZoRGwoXXCK3kIccnnbcKbz0OVkDgzkpTgCMM2sBw844v+NihAVBaUkhA9Z3fCyWx5fzebCGa+5yw+OmfDayDttgEU8AAAAgvfS3UVUtXZbpIQDbZmTUdc6d0/hMmcqoirzGfDfWJYH1pJov4MAPfRo6kMs0sDVjChnHjwXW17LYcK5oqagB87IGBtCMk3XIT07n47OFfk1d2BdYR4oRGHYQAEArt3RAxo6iePhzF2ygH5f2C/olkJtFPAEAAID0Sq21+Uaff/FDL9vo2CsTKp7swaMnnyoTHt4+oCuQbeawxyzdQg7Pu3SusvXPb0Kedp8l8sqQU1mCZk5maZYpJNcOpTz1dxl2RMBtZBvIauw5iwU6IR85hP2xBgawCotkwbLWztxQAaDFehX2I7Ava2feujewnlkKGEM7FWGHfVr7RAPIW7g4ftzx63TuAGRhfwTrs4gnAAAAkF6KKSTAthnmDfs1dUTFlCuc9ikAsC8pChg6N7APDzsm8g7LWvtY22Lo9RyvfWhKy5KvAcjN1BHII0UB40DnBvZj7c4U7NU1J+K35PTWE/+l9hGXChn2VQCwvlKrWxADAAAAuVnEEwAAAEhPAQMAAABITwEDAAAASE8BAwAAAEhPAQMAAABITwEDAAAASE8BAwAAAEhPAQMAAABITwEDAAAASE8BAwAAAEhPAQMAAABITwFj40opv6eU8i9LKT98/7+/68Hv3nD/8x8vpXxTKaUMbOMr7h/zY6WU37vcq4c8hrJUSvnEUso/KKX8aCnlPaWUv3JmG7LE7p07Lj14zHeWUv7NmW3IErt34RzvVaWUt5VSnr8/Pn3hwDZkid27kKU/cv/zHyqlfG8p5VMHtiFLC3li7RfA7D4YEZ9Xa/3pUspnR8Q/jIhPv//dt0bEn4yIH4iI746Iz42I73n4x6WU10XEH46Iz4qIT4uIf1RKeVRr/eWFXj9kcS5LX1drfa6U8qqI+L5Syu+rtcoSnHYuS1FK+YKI+PDQH8sSfNy5LH1lRHyg1vqolPKKiPiU4z+WJfi4k1kqpTwREd8YEa+rtX6wlPK1EfFsRHz1wz+WpWUZgZFMKeVPlVL+9f1/P1lKee6W7dVa/1Wt9afv//meiPiEUsqvKKU8ExGvrrX+81prjYi/GRGff2ITfzAi3lFr/aVa609GxI9HxG+95TXBEpbKUq31F2utz90/5j9FxLsj4rUnNiFLdGmpLN0/1ydHxJsj4q1nNiFLdGnJLEXEl0bE19w/7mO11g+e2IQs0aUFs1Tu//uk+5Hqr46Inz6xCVlakBEYydRavy0ivq2U8sqIeFdEfP3xY0opfy0ifueJP39HrXVw+HpEfGFE/Kta6y+VUj49Il548LsX4sEVsAc+Pe5GaFx6HKSyVJaOtvdURHxe3FXrj8kSXVo4S2+JiL8aEb945m9kiS4teI731P3P3lJKeWNEvC8inq21/vujv5ElurTkcamU8qaI+OGI+IWIeG9EfNmJv5GlBSlg5PWNEfGuWut3Hf+i1vrlUzdWSvmsiPhfI+JzDj868bB66k9HPg6ymjtLh58/ERF/KyK+qdb6E6f+9MTPZImezJqlUsrrI+Iza61fXkr5jHN/euJnskRP5j4uPRF3IwH/Wa31zaWUN0fE10XEHz3+0xObkyV6Mvdx6ZUR8aaI+E0R8RMR8c0R8RXx+ChBWVqQAkZCpZQvjohfG3dzrE79flJFsZTy2oj4joj4olrr++5//EK8fJj7a+P0kKgXIuJXj3gcpLNQlg7eFhHvrbV+w8DLkSW6tVCWfntEvKGU8u/i7vzk6VLKP661vvHoz2WJbi2Upf8Qd6OYvuP+3387Iv74iW3KEt1aKEuvj4g4/LuU8s6I+PMntilLCyp3yx+QRSnlDRHxv0fE76i1/lyD7T0VEf8kIv5yrfXvHv3uByPif4yIfxF3i3h+c631u48e81kR8e1xN4/r0yLi+yLi11uUhuwWztJbI+I3RsQfqrV+bODvZYkuLZmlB4/5jIj4+7XWzz7xO1miSwsfl94REW+rtb7rvqP3P9Ra/9DRY2SJLi2VpVLKp0XEv4yI/6bW+rOllLdExCfWWv/M0d/L0oIs4pnPs3G3UvRz9wvTvL3B9j4zIr7qwWI3T9//7k0R8fa4W2jmfXF/B5JSyh8opfzliIha63si4p0R8SMR8b0R8WXCSCcWydJ9xf4rI+J1EfHu+5//iQhZYjOWPC6dJEtsxJJZ+nMR8dWllB+Ku6kjfyZCltiMRbJ0v7DnX4qIf3qfpddHxP8SIUtrMgIDAAAASM8IDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACC9J2barpVBYViZ8FhZgmGyBO2MzZMswXmyBG2czJIRGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6FwsYpZRnSymvWeLFAAAAAJwyZgTGr4qIHyylvLOU8rmllDL3iwIAAAB4qNRaLz/ormjxORHxJRHxmyPinRHx12ut7xv4k8sbhf2aUgSUJRgmS9DO2DzJEpwnS9DGySyNWgOj3lU5fub+v49GxGsi4u+UUr622csDAAAAGHBxBEYp5U9HxB+LiA9GxNsj4u/VWj9SSnlFRLy31vrrTvyZiiIMc9UY2pAlaMdVY2hDlqCNk1l6YsQffmpEfEGt9ace/rDW+rFSyu9v8coAAAAAzhm1BsYVVBRhmKvG0IYsQTuuGkMbsgRtXL8GBgAAAMCaFDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwYCHPv/iheP7FD639MgAAALqkgAEAAACkV2qtc2x3lo1CDw6jLB49+dTQQ8qEzckSDJMlaGdsnmQJzpMlaONklhQw4AYjihWn6HRBG7IE7eh0QRuyBG0oYMC1rixUDNHpgjZkCdrR6YI2ZAnaUMCAJHS6oA1ZgnZ0uqANWYI2TmbJIp4AAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6ChgAAABAegoYAAAAQHoKGAAAAEB6pda69msAAAAAOMsIDAAAACA9BQwAAAAgPQUMAAAAID0FDAAAACA9BQwAAAAgPQUMAAAAID0FjA0rpfyWUsoPlVI+oZTySaWU95RSPnvt1wW9kSVoQ5agDVmCNmSpP6XWuvZrYEallLdGxCdExK+MiBdqrV+z8kuCLskStCFL0IYsQRuy1BcFjI0rpbwqIn4wIv5jRPy3tdZfXvklQZdkCdqQJWhDlqANWeqLKSTb9ykR8ckR8WTcVRaB68gStCFL0IYsQRuy1BEjMDaulPKdEfGOiPivIuKZWuuzK78k6JIsQRuyBG3IErQhS315Yu0XwHxKKV8UER+ttX57KeU/i4j/q5Tyu2qt71r7tUFPZAnakCVoQ5agDVnqjxEYAAAAQHrWwAAAAADSU8AAAAAA0lPAAAAAANJTwAAAAADSU8AAAAAA0lPAAAAAANJTwAAAAADS+/8B116NHlNgew4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x1728 with 40 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_z(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df, col='z',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_z, 'x', 'y', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r', cbar=False)\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3937e6cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Want to display data in 7x5 grid, in accordance with A4 paper size\n",
    "N = 35"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "fa49ead9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df[df['x'].between(x_min, x_min + (N-1)*x_step)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "4a4fd695",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5mniyNZp5wqM2afQ0a1254hRts2Ha5PbkiVMjS1CXhp6rcQUGAAAAUJ4CBgAAAFCeAgYAAABQXuu9H3ofAAAAABZyBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CxsC01n6otfY7rbWPtNbuaq09Y+rxL2mtfba19qaJZc9srf1ma+2TrbX/o7V2w2j5U1prbx9t6wOttedMrPPp1tpHW2v3ttZ+a2L5za21d4229a7W2lPm7OfLWmu/21q7v7V2x/aPBGxmzSz94Oic7q21p04sb621fzp67COttb828djMLMgSx2KPWTIucdS2nKWvbK3929baF1prPzy1HeMSR22PWTIuHYACxvB8KMltvfevTvJLSd4w9fjrkrxnatmPJ/lfe+/PSvIfknz/aPk/SHLvaFvfneQnp9b7pt77c3vvt00suyPJXaNt3TX6+Tqttccl+akkL0/y7CSvaq09e7VfE3ZunSz9RpKXJvmDqeUvT/Ks0e1/SPLPkguzIEsci51naYJxiWO2zSz9UZJXJ/lfJhcalzgRO8/SBOPSnilg7FBr7Xmjyt8TWmtPaq19vE1c5bCO3vuv997/dPTj+5M8feL1vi7JLUneObGsJXlxzsObJG9N8i2j+8/OeajSe/9Ekr/cWrvlgl145Wgb09ua9Pwk9/feP9V7//MkbxutB2upkKXROh/qvX96xuZemeTn+7n3J7mptXY5i7MgS+zdgLO0iCyxd9Wz1Hu/2nv/YJL/e+oh4xKlDDhLi8jSDp0degeOWe/9g621O5P8WJInJvmF3vvHpp/XWntvkhtnbOKHe+/vXvAS35/k10bb+KIkP5Hku5K8ZOI5X5bkod77tdHPDyR52uj+h5P8rST3tNaen+QZOQ/455L0JO9srfUkb+69v2W0zi299yuj3+9Ka+3SjP16WpLPTPz8QJKvX/B7wEJFsrTIrHP+aXOWj7MgS+zdgLN0JcYlChlAluYxLlHKgLOUGJcOQgFj9340yQeT/FnOLz96jN77C1fdaGvtO5PcluRFo0W3J3lH7/0z5xddPPrUWS85+u/rk/xka+3eJB/N+eVW40LHN/TeHxwF7l2ttU/03u9edvcWvCas69BZWriZWbuzYPmm24VNDDFLiXGJeipnae7mZywzLnFoQ8xSYlw6CAWM3bs5yZOTPD7JE5L8yfQTVq0ottZemuS1SV7Ue//CaPELkrywtXb76PVuaK19Psnfz/kluGejqzCenuTBJOm9/3GS7x1tsyX5/dEtvffxc6621t6e88uc7k7yudba5VE18XKSqzP2+4EkXzHx8yOvCRs4aJZ674uaK80752+YszyRJQ5niFkyLlFR5SzNsygLssShDDFLxqVD6b277fCW5M4k35HzAL1pC9v72iS/l+RZC57zPZOvleQXk3z76P7PJLl9dP+mJDeM7v+dnM87TpInJblx4v77krxs9PMbk9wxun9HkjfMeP2zJJ9K8syc/wH34SRfdej3wm3YtwpZmlj+6SRPnfj5b+b88sSW5L9I8oHR8rlZkCW3Q90GmiXjklu5W+UsTSz/Rzn/A2/8s3HJrdxtoFkyLh3qfDn0DhzzLef/ssevjO4/LslvJnnxhtt8d857VNw7ut054znXBTLJX0nygST357yY8R+Nlr8gySeTfCLJryR5ysTzPzy6fTzJaye29WU5b/z5ydF/bx4t//KcX5I1ft4rktw3+vB47Sa/s5tboSy9OucV82s5r5L/7Gh5y3kn6d/L+XSs2ybWmZkFWXI7xG2oWTIuuVW7DSBLf2m0/I+TPDS6/yWjx4xLbmVuQ82ScelwtzY6eAAAAABl+WdUAQAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPLOdrRdnUFhvrbCc2UJ5pMl2J5l8yRLsJgswXbMzJIrMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyzg69A2zmvocfWvq5t954U+57+KHceuNNc9effAxOySpZmjTOzKz15YlTtkymZmVEluB6F2Vp2Rwtej6cilWzYUyqxxUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHmt976L7e5ko9NOsQHluo0Gd2XcGHR6GQu1FZ7bk8Xn+nRj1lWsej4d03tbMUtjMrW0lbK0qBHXqk26tnH+rPq+jl/z0OfD5H5Uy9Es0/t56ONX2FJ5uu/hh2Z+x6uepWVfZx/nxxByM4vsLG2jLF1k0feFbbjofV71HxDYJVk6ejOz5AoMAAAAoDwFDAAAAKA8BQwAAACgvJ30wFh3Ttcp2vU8tmqGNhduR/u79Lx9WVqeLG3XIebVrkGWtuzUcpQMM0vJ4fIkS7Nts2/AkO1rbn/xMUqWVrTKsZel7So+RumBAQAAAAyTAgYAAABQngIGAAAAUJ4CBgAAAFCeJp4M1q033lSikc8aTWo0HqSEag0bZYmhqpalaUtmS+NBDm58rlbMUSJLDMfQsjRrP2+98SZNPAEAAIBhUsAAAAAAylPAAAAAAMpTwAAAAADK08QTtmyJBk8aD8KSLsiTLMGKFmRK40HYgnmNB6fJEiymiScAAAAwWAoYAAAAQHkKGAAAAEB5Z4feAdiWq1dmn86XLl/b637c9/BDCx9fokcGHNSsLO07R2OL8iRL2zf53h/qPT82V6+clTqW8zIlT5ub9z1krNJ5AJUsys5kbip9Pzl1h/y7yxUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHmaeHL0Vmn4owEXzHZRNlYlS5yCcW62nZ9JssQp2GWGxmSppn2896dk18dzvP1d5skVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5uqJwktZtYHP1ypkmT7AF+2jyBKdAlmA7ZAm2Z5d5cgUGAAAAUJ4CBgAAAFCeAgYAAABQnh4YsKLJ/hnmScJm5Am2w/x92A5Zqmfee7FuTzuGzRUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHk6n3BULl2+tteGPtOvpeETADD5fUCjQVjPRd+rfe+u7+qVs62/T67AAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMrTVYijs+9GnnCM5Oh0aYq2XbJ0eqYzJFPbIUvHS0ZYhSswAAAAgPIUMAAAAIDyFDAAAACA8kwk42hMzp+bnktnziQsb5yfyRzJ0GkwD3m7prMkR8dNfnbHsYXtGXo/GVdgAAAAAOUpYAAAAADlKWAAAAAA5S1VwGit3dVae8XUsrfsZpcAAAAArrfsFRjPTPKa1tqPTCy7bQf7Aztx6fI1DaBgA+MMyREAh2Icgs0cQ36WLWA8lOQlSW5prf1qa+1Ld7dLAAAAANdbtoDReu/Xeu+3J/nlJPckubS73QIAAAB41LL/AOzPjO/03n+utfbRJD+wm10CAAAAuN5SBYze+5unfv7tJN+3kz0CAAAAmLLsFRgAkOS8AdTVK4YPWNV08zQ5AuAQxuPREMehZXtgAAAAAByMAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYn5dLla49pogasbpyleZmSM7jYdH5WyY3xjFO2i/NfnmA5h86KAgYAAABQngIGAAAAUJ4CBgAAAFDe2aF3AA5h3tytq1cWR+LS5WsXPgdO0arzIWUJHrVMH4x5eRk/X544RZN5mc7AonFp8rnT+ZMlTskyY8iq/Zkm7SJPrsAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAytOlBla0qGEUsDzN0mB7Vm2kC8dmWxmQJU7RkM57V2AAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5emeBhsYUsMbqEiGAACO0y6+57kCAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAo7+zQOwAAAACHcPXKo38SX7p87YB7wjJcgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4knwBZoAAWbGWdIfmA5k+NOIjuwDVevnF2XJd/v6nEFBgAAAFCeAgYAAABQngIGAAAAUJ4eGABAGeb1w3oWZWd6Xj8w33SWVllPznbPFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYzLVuA5sh03iHXTjFLAFwWFevnD1yA7ZvnC052y8FDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA83UZ4jMkmNNMNaU6hyeWly9c04mEr5mXpFHIEy/J5C8AQXL1y9pjvcLPGsPEy3/d2wxUYAAAAQHkKGAAAAEB5ChgAAABAeSaech1zkWczh41pm2TlVHrLHOvvxXaskqFln3vM59wx/24c1qx8Hfv5duy/H8tb9fvcrD4Ym2xvqMbH4KLjsQuuwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKO40uI8x1Ko1mVqW5E5uQK5hvnYZpwOZkCbZDlh51iL+ZXIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAccI0oAEAGB7f4WBzcjRMChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHlnh94BhuXqlbNcunzt0LsBR+nqlUc/kuUM1jOZozF5gvVM50mWYHnjv5vkaLtcgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4knW6XJJ2yHLMHqZjXwnF4uV3CxZbI0Sa5gtlmZMSZtxhUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHmaeLJ148Y0mtLAZjR5gu2bbqgmW7A53/1gPRrjrs4VGAAAAEB5ChgAAABAeQoYAAAAQHl6YLAz0/MhzY/kWMybr7jv15Ql2NzVK2eyBFuidxNsh7+b5nMFBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFBe670feh8AAAAAFnIFBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAsbAtNZ+qLX2O621j7TW7mqtPWPq8S9prX22tfamiWU/2Fq7v7XWW2tPnVj+342285HW2vtaa18z8djLWmu/O1rvjonlN7fW3tVa++Tov0+Zs58z14cq9pilT7fWPtpau7e19lsTy2WJo7DlLL1ytJ17W2u/1Vr7xonHjEsctT1mybjEUdtmliYef15r7S9aa982scy4dAAKGMPzoSS39d6/OskvJXnD1OOvS/KeqWW/keSlSf5gavnvJ3nRaFuvS/KWJGmtPS7JTyV5eZJnJ3lVa+3Zo3XuSHJX7/1ZSe4a/XydC9aHKnaepQnf1Ht/bu/9tollssSx2GaW7kryNb335yb5viQ/mxiXOBk7z9IE4xLHbJtZGp/3P57k30wtMy4dgALGDo0qdR9prT2htfak1trHW2vP2WSbvfdf773/6ejH9yd5+sTrfV2SW5K8c2qdD/XePz1jW+/rvf+HGdt6fpL7e++f6r3/eZK3JXnl6LFXJnnr6P5bk3zLjN1ctD6sbMBZWkSW2LsBZOnzvfc++vFJScb3jUuUMuAsLSJL7F31LI383SS/nOTqxDLj0oGcHXoHjlnv/YOttTuT/FiSJyb5hd77x6af11p7b5IbZ2zih3vv717wEt+f5NdG2/iiJD+R5LuSvGSN3X1kW0meluQzE489kOTrR/dv6b1fSZLe+5XW2qUZ21q0PqxswFlKzr80vrO11pO8ufc+vjpDlti7IWSptfatSf7nJJeS/M3RYuMSpQw4S4lxiUKqZ6m19rQk35rkxUmeN/GQcelAFDB270eTfDDJnyV59awn9N5fuOpGW2vfmeS2JC8aLbo9yTt6759pra26rW/KebjH8yNnbWCZyv0jm9xwfZhliFlKkm/ovT84Grze1Vr7RO/97mU3OWOZLLGp0lnqvb89ydtba/9lzi/zfWmMS9Q0xCwlxiXqqZylf5LkNb33v5hax7h0IAoYu3dzkicneXySJyT5k+knrFpRbK29NMlrcz7n/gujxS9I8sLW2u2j17uhtfb53vvChjCtta/O+bzIl/fe/6/R4geSfMXE056e5MHR/c+11i6PqomXc/2lVGOL1od1DTFL6b0/OPrv1dba23N+yeDdkSUOp3SWxnrvd7fW/mo7b6ZmXKKiwWWp9/6HxiUKqpyl25K8bVS8eGqSV7TWrsW4dDi9d7cd3pLcmeQ7ch6gN21he1+b5PeSPGvBc75n1msl+XSSp078/J8kuT/JX5963lmSTyV5ZpIbknw4yVeNHntjkjtG9+9I8oYZrzN3fTe3dW8DzdKTktw4cf99SV42+lmW3A5yK56l/zRJG93/a0k+m/P/S2Vccit3G2iWjEtu5W6VszT12M8l+bbRfePSgW6aeO5Qa+27k1zrvf+LJK9P8rzW2os33Owbc14x/MV2/s9f3bnEfry6tfZAzit7H2mtjTtR/8MkX5bkp9vEP6XVe7+W5Adz3mn33yX5l733j4/WeX2Sb26tfTLJN49+Tmvty1tr71hifVjZULOU8yZR97TWPpzkA0n+Ve/9X48ekyX2bgBZ+m+TfKy1dm/Ou7P/7X7OuEQpQ81SjEsUM4AszWRcOpxxZRYAAACgLFdgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOWd7Wi7OoPCfG2F58oSzCdLsD3L5kmWYDFZgu2YmSVXYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlnR16BzZx38MPJUluvfGmg+5HJeNjMsv0cZr1XMfyNE2eC86Bc+tkybE7XYvOl7FTPz+MOcxz0bkx/fipnzeyxDzLjEXTTvncmf7+dt/DDy38e+miYzVrfbbPFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAea33vvWN3vfwQ9vf6BYsaqqyatObfTVoWacZzyFpXLOUtuwTh5alVc7Xi7ax7XNpSFmSo6UdXZb2eZ6u24zsEFla1NBx2fW40FJ5kqX1X38bY+c2TDYsXHUdlnI0WTrU5/09933+kZ8vXb428znLqPbdT45WNjNLrsAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAyjupJp6HdOuNN81tiDZWrdHMrsxrHrVOY5vJbeyz2dyq+zq1n4NvPDgkV6+c5dLla7l65Wzm47OaQw3dJufnom2Mm2pt85jJUl3zMnORIWZqW+PSvDFnejsXNajbhlW/byybJ1na3KrZGmKmps1qcrrJd+LpRo/TtnHM1m0UKUubm8zIKu/l+DvfvO0dQ5aSR/+unF62yEWZWvS5tM88Jdc19NfEEwAAABgmBQwAAACgPAUMAAAAoDw9MPZs3TldHA/z9rdj2Swt0wNj3pxJzk0fuyrHSpZ2Y93eF2NVzo+qVjm++zyW5u3PN2uMWDRubJqhaePXObZ5/JtY5xjv67jJ0ua2naEx2XmsZY715PfoCuOSKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8nbTIYWNLWo4CMw3KzuLGhTtqlHUMVnUBJXaZr1vux5HNBqcT46GY/q9WjS27CtTMCQVG60eYkxk+1yBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSnK9AOTTaKuagJngZN+7Xq8dbg53Cm36t574UMbW76M2vZ565Clg5vuvGgppvbdfXK2WOO5bp5mddwbtnPRfZj1nvO9m06zl+UTe/h4cnS7mySn8l1540/+8ySKzAAAACA8hQwAAAAgPIUMAAAAIDyTBrfk1nzjszZ365dHk9zJOuQpf3YVc8ec/frmH4v5Gh79jUeUYf3Zft2cUy9T/V5j7ZjX8fxEO+XKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwitDIbjg0FwKA0+E7GkAdChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeboRHthkY6hZTaI0jKxp/L5o7LUfly5fWzoL896Teeuvsm0YulXP9+k8LbOuz0WO0XR2jB2w2EVjwdUrZ488R5ZYhSswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPJ0TNmhbTQym9yGBjecsouysEneNB3kWE02Ghyf58s2TbsoF+s0+IShmHX+Ty9bN0urZsUYxTE6xHktS8fBFRgAAABAeQoYAAAAQHkKGAAAAEB5JqwOiHlbnKJl5iFvuj04ZvPO+cn+GIfcHpy6eZmSJ07Fsv1kIHEFBgAAADAAChgAAABAeQoYAAAAQHkKGAAAAEB5OqUAJ0HzzotpokWyOCsX5UjOOEXzGthumhd5AngsV2AAAAAA5SlgAAAAAOUpYAAAAADlLVXAaK3d1Vp7xdSyt+xmlwAAAACut2yntmcmeU1r7Xm99388WnbbjvYJ1jKviRawGlk6HZPvtYaB2zF5HOXodG3SDBdO1brfP6YzZVxbfSya18i9YoP3ZaeQPJTkJUluaa39amvtS3e3SwAAAADXW7aA0Xrv13rvtyf55ST3JLm0u90CAAAAeNSy14L8zPhO7/3nWmsfTfIDu9klAAAAgOstdQVG7/3NUz//du/9+3azS7C+U57rBrCOS5ev+ezcEcf1dEy+19737XAcWcas88S4dr1jOxb+GVUAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvGX/FRIYjEuXr+Xqld2c2rvcNlSy63P92BpKwTyydDq8F9s3eUx9/zoNi95zGatvH++RKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8nTD4egtaiazbEOoyW1o5MmpGJ/32zzfNeCCzckRbIcsDYP3qb59vkeuwAAAAADKU8AAAAAAylPAAAAAAMozkZ+jtOt5WObiAQDA7vi+zSyuwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKU8AAAICBu3rlLFev6M8PHDcFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQyAC2iKBtszbjS4TK5kD1Y3nRs5guutMg7NWpfDUsAAAAAAylPAAAAAAMpTwAAAAADKM4nnyE3O07p0+doB9wSGbZylRTmSN1jNosyYZwzru3rlzDgEMyzqESMzw+AKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8HbJOyDJNCIHF5Ah2Q9NBWGxeY1u5gd3SVLoWV2AAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5elIcoLWbQKlwRo8ap1mnpPZkyVO0UWN0GaNM7Nyo5kuXEzjQVjNdGYuXb62MEdD+ttoevwcMldgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUNv4sHc63apGVeI5pjaPYCu3IK+bioiRUsss5YtK1twSlYNhcXNb+t3pDQWMS+zTvfJpdXz820XeRo37+/KzAAAACA8hQwAAAAgPIUMAAAAIDyTCTjOtPzuKbnSA1tnhdUMfR5u5vOmfS5wSkbn//b+ByQJdaxrT4ZhzaZpUXfV1fZFrBcv49ZDpEjV2AAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5Q27qxw7cVEDp+oNnlYxrzHhMfxubMe6TfeOseHtrN+nYnMnTsuQsrZOhhatC+saemPpaas2mpYntmny3Dv0ubWvMfGQv6crMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyjquDD4/YRnOmY2vwNM+hm+1Q064zVKnh0yYWNfsd8u/FMIxzNOTm0tP7rLE0u3Yq3+9mkaXTto9zf/L7j+9Cu+EKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAC2zpxPgM1cvXJ20v0qAGZRwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADK0xkIAAAK08wThkNed8sVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5Chhs7OqVs0duAJwu4wBs3yFyJcuwPbv8O+kU/wZTwAAAAADKU8AAAAAAylPAAAAAAMo7rQkzbNWs+VZXr5zl0uVrB9gbGLZZeZIlhmh8Lh/q/F00F1imYHmyBJubzNG2vuvN+xvsVLgCAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjvdLp9sDeHbuAGQzOv8ZIsMWSHaCh20Wuus0/yB48lS7Ad87I0nZdTatJ5EVdgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOXpBsLOzGo2o4ETrG7Txk1yB+ubzp88wXoWjWVyBdfb5Lvf1StnCzN16fK1QTcFdQUGAAAAUJ4CBgAAAFCeAgYAAABQXuu9H3ofAAAAABZyBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CxsC01n6otfY7rbWPtNbuaq09Y+rxL2mtfba19qaJZT/YWru/tdZba0+dsc3ntdb+orX2bRPLPt1a+2hr7d7W2m9NLL+5tfau1tonR/99ypz9fFlr7XdHr3vHdn572J5tZqm19jdaa/+/UV7uba39w4nHZmZBljgWe8yScYmjtu3veKM83dta+3hr7T0Ty41LHLU9Zsm4dAAKGMPzoSS39d6/OskvJXnD1OOvS/KeqWW/keSlSf5gemOttccl+fEk/2bGa31T7/25vffbJpbdkeSu3vuzktw1+nnWNn8qycuTPDvJq1prz17id4N92mqWkrx3lJfn9t5/NLkwC7LEsdh5liYYlzhmW8tSa+2mJD+d5L/pvX9Vkv/XaLlxiVOw8yxNMC7tmQLGDrXzKxs+0lp7QmvtSaOq3XM22Wbv/dd77386+vH9SZ4+8Xpfl+SWJO+cWudDvfdPz9nk303yy0muLrkLr0zy1tH9tyb5lhnPeX6S+3vvn+q9/3mSt43Wg7UMJEuzLMqCLLF3A87SIrLE3g0gS9+R5Fd67/9+9Lzx9zzjEqUMOEuLyNIOnR16B45Z7/2DrbU7k/xYkicm+YXe+8emn9dae2+SG2ds4od77+9e8BLfn+TXRtv4oiQ/keS7krxkmf1rrT0tybcmeXGS503vfpJ3ttZ6kjf33t8yWn5L7/3K6Pe70lq7NGPTT0vymYmfH0jy9cvsE8xSPUsjL2itfTjJg6PX+3gWZ0GW2LsBZykxLlHIALJ0a5LHt9b+P6PX/8ne+8/HuEQxA85SYlw6CAWM3fvRJB9M8mdJXj3rCb33F6660dbadya5LcmLRotuT/KO3vtnWmvLbuafJHlN7/0vZqzzDb33B0eBe1dr7RO997uX3b0Zy/qyOwVzVM7S/zfJM3rvn2+tvSLJ/5nkWdk8C7LELgwxS4lxiXoqZ+ksydfl/I+0Jyb5t62198e4RE2Dy1Lv/b4Ylw5CAWP3bk7y5CSPT/KEJH8y/YRVK4qttZcmeW2SF/XevzBa/IIkL2yt3T56vRtaa5/vvS9qCHNbkreNAvzUJK9orV3rvf+fvfcHk/PLpFprb8/5ZU53J/lca+3yqJp4ObOnnjyQ5Csmfn56zv9PGmyibJZ67388cf8drbWfbucNoBZlQZY4lMFlqff+h8YlCiqbpZyf83/Ye/+TJH/SWrs7ydfEuERNQ8zSfcalA+m9u+3wluTOnM+dem2SN21he1+b5PeSPGvBc75n1msl+XSSp85Z5+eSfNvo/pOS3Dhx/31JXjb6+Y1J7hjdvyPJG2Zs6yzJp5I8M8kNST6c5KsO/V64DftWOUtJ/lKSNrr//CT/PueV9blZkCW3Q90GmiXjklu5W/Es/Wc5bx54luSLk3wsyXOMS24VbwPNknHpQDdNPHeotfbdSa713v9FktcneV5r7cUbbvaNOa8Y/mI7/yd77lxiP17dWnsg55W9j7TWfvaCVW5Jcs9oDvIHkvyr3vu/Hj32+iTf3Fr7ZJJvHv2c1tqXt9bekSS992tJfjDn/7LJv0vyL/ujc5hhZQPI0rcl+dgoM/80ybf3c4uyIEvs3VCzFOMSxVTPUu/93yX510k+kvPM/Gzv/WPGJaoZapZiXDqY8f/lAAAAACjLFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeWc72q7OoDBfW+G5sgTzyRJsz7J5kiVYTJZgO2ZmyRUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHlnh96BVdz38ENrrXfrjTetvc1F6y7a1irr7dr07zjet/Hyi/Z12ecxHKtmadlzZN1t3PfwQ7l65fzj6NLlayu//r7NytSs/E9mp+rnA+tbZ0zaZDxadv0hZWnSRWPV9HKOwyG+2y3a3irrVj4XjTmnZxdZWnW7V6+c5RtvffLK61U/R+WpFldgAAAAAOUpYAAAAADlKWAAAAAA5bXe+9Y3et/DD21/o1swPQ99n8ZzkqdNz1Fet+fGIR3DXLA9z21ryz6xYpYmj882z8FF8/bn5WfS5HqrvodVsjQ2pEzdc9/nk8x+35L5v8t9Dz+0jd9z8Fnaxbl30XhzUZ5kaf9WnSu+o74gS+XplLI0tm6m5mVp1d5iFXI1hCxt4zjJ0mZZms7Cou90k/lZlKVZfystu4/r9LbZ1OTvMLReVJO2dcw2+dv21htvmpklV2AAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5Z1UE89DWraJJ9dbpvHLRU1mVmlYt45V93FeQ5o5651Mli5q/LTr9/GYrdMwajpX8xprLWq+uqqL9nPZ5k5z1j3ZLI3Na5I2+d5d1HzsVGyzydqsMWofx3le87p5DfCWzdMpZWls1UbS0+vI0vZUaGh6EVlabFYTz1VskqfJhqFDssvGn5UzpYknAAAAMFgKGAAAAEB5ChgAAABAeQoYAAAAQHmrdU1h69ZtXHNRw8NjcVHzsyS5dHnxNnZ9bCo3vzmEQzXbXDVL8xxjlsbn6KJjdNHvPe/xbR4vWbrevMapk4/v8nzdNFNDztKic3GTHK36vE3M+x1OLWcX5ehQ+zDLvIa6048NybzzrcL7wsV2+T6tO8Zs6/vekJza5/ZFXIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlHd6XVBWtErjpX00JFq0P6fSEGmykekx/n7HbtlMTT7vkO/zKeTq2H6fYzZ9Pq7S6K9K47OhNyecHu+Htv/sptn0Nr6TbNrUcEjn4pD29VTNOx/nLZ/3nlYZeybN+wzfNEvLfA74+2VzrsAAAAAAylPAAAAAAMpTwAAAAADKqzcpaaBWnSe2r9c/Bbv43Sf7bMxazn7t8/w+5SxN2/RYTOfFvM/dW+c929U5L0uPtc4xuWheuUxt36a9KHahep4O9fm+ynGZtX/Gpe2pfo6OXdRLatvbX+c51Xq/zTKrd8j08l1xBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQ3jC6rXCSttEEZ5evDVWtev7KUU3zGmSxfas0INt1A7iLXg+q2kYjv1NuhApj22gue8xjkyswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPJ0s1nRuKGKRkAw36zGQzID67t0+dojTb1kabcc3+OjIe7+Oc7HYfr7nPd1f+Yda9+xXYEBAAAADIACBgAAAFCeAgYAAABQ3mlNmNki85Bhtllz8xYtlyNYzjhD5iTD8qbz4vsbLGfW9zb9ZA7PcXcFBgAAADAAChgAAABAeQoYAAAAQHkKGAAAAEB5uoBcYF7jwYseSw7fZOWi/YMKqjdUkyOqG5+jlXM0Jk9UUH3cWZVccQjHlqMxearPFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAecfXeaWQfTe30XSGoZrMyqzz+BBNouSJoTnWhmqwC/M+44eUIeMUh3Zs4862MzU+PlW+2x4LV2AAAAAA5SlgAAAAAOUpYAAAAADlmXyzY+M5T+Y5wWLm8sLmKs9HlnHYHnmiislzser4sy+zcjkvq8fQh+dQXIEBAAAAlKeAAQAAAJSngAEAAACUt1QBo7V2V2vtFVPL3rKbXQIAAAC43rJdQp6Z5DWttef13v/xaNltO9oneMSiJlXzmtws00xoersa5nCM9tlEWKY4JoduSqcBOENjDIDtqNyMu4plp5A8lOQlSW5prf1qa+1Ld7dLAAAAANdbtoDReu/Xeu+3J/nlJPckubS73QIAAAB41LLXp/zM+E7v/edaax9N8gO72SUAAACA6y1VwOi9v3nq599O8n072SMAAACAKTqE7ImGLKtb1MBz8vFFx/WibcAx2td5L18ciyrncpX9gKHzHRG2o2KWlu2BAQAAAHAwChgAAABAeQoYAAAAQHmaMgyYuXv741hz6mRgOKbfK/2Xals3WzK5G4uOqyzVM/l+Xb1ytnQu5Gf3lumdwOFMZ2dy+TJZOmSGXIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKerShHjhimTP88yfs42Gqdsc1swVLOaTK2SiVWahsEhDKWR2vT+HXOujvl3O2ZDydKpkqvDm/UeXPQ3DfVUz5IrMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDydE85sMkmKcs0TNmkqYpmgwzV5Hm7raZP01lYNhuzcjRepjEule2qAeEu8gmVVc2SMYghqdQUV2aGxRUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHmH75pyQvbRIGayEc6s15vXgHDROlDJZLPM6eWTdtkUata2KzShgmXssunmOtuWHYZql00Ih94ct1KDRmqb972ugum/m/yDCDW4AgMAAAAoTwEDAAAAKE8BAwAAACiv5oQj1jI9f2zePK2q88zm0aODacucB5ueK847TsFFc3srjBfmHFNdtTn887IsR1RVuWfKNvZpvI1lM1hxLK7EFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeTqCHDlNm2A1sxolrZOj6e3IIdXNOkenm3wus842aVzGUFRumr7ufvgOyb4NvXnlRc2wZWo7XIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlDesziisZWgNcKAiOdqMplXDt+l7OM6Qc2Ezly5f83k0EPPO9X00xF3lHLmo8SAcyvi8XPV8vKgB9bZNN+qctR+TjxsHN+MKDAAAAKA8BQwAAACgPAUMAAAAoDwT3LjO9DyxU5+jdeq/P+sZ2tzhXc6plyGmLXuurTKn+BRM/t6negyOxTY+c7ediaGNW5yWRef4Ns7dXfVokqvdcAUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ7OIgzeuOHONhvlaJDGqdllI0/YpqtXzuZ+7vvsZigOca5ONyr0mc8x2Ob3l8nxZdFzJl+b/XMFBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCe7j2sbF/Na9ZtyLPM/i3atoY87NoxNh6clalj+L2oaV/NB9d5nW00lDvGzwhWt+x5tEzjwU2eD9VNNqbdxrm9q+ztcl9OiSswAAAAgPIUMAAAAIDyFDAAAACA8kyqORK7mh813U9iH/Owtvka5o2xrF2fK7vY/nibk3M/x4aYV46Dc2J2Jpel/wXrWPVcW2WOf3KY83DTcUyWTs+s93jV8+gYx7B9fSfcF1dgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUdTzcPdq5CQ8CrV840YYIpFbIJVQx5nJAzqhparmSJSZs0Vr7IUM+1efs9nfWKzXBdgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUN8yuIwzauBnMLhvqwJBMZwJYzzhL1TNl3GOIKjbylCWGaPK8rZappH6uXIEBAAAAlKeAAQAAAJSngAEAAACUV3uCC+VtMh+y+vwq2Lfq8/ZhaJbNlOxRTdXvSNP7JTMMQdU8JTK1DldgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOXV7WjCYGh+Btu1SXPcyW0A5ybzcOnytbn5kBsqGNJ5OK8B4ZB+B47XNr5P7Zu/qy7mCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPB122JohNsqBqqabDi56fBuvJbucCs0FYXfkiwqO4Tw8ht9hV1yBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSnOwhbNd1w5tLla5rQwIZkiKFwrsL65Ae2T66OjyswAAAAgPIUMAAAAIDyFDAAAACA8hQw2Kl9zju7dPna3l4LjtGly9fkCABgjm+89cmH3oWTp4ABAAAAlKeAAQAAAJSngAEAAACU13rvh94HAAAAgIVcgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAMTCttR9qrf1Oa+0jrbW7WmvPmHr8S1prn22tvWli2Q+21u5vrfXW2lMnlv9PrbV7R7ePtdb+orV28+ixl7XWfne03h0T69zcWntXa+2To/8+Zc5+zlwfqthjlj7dWvvo6LHfmlhHljgKW87Sl7bWfrW19uHW2sdba9878ZhxiaO2xywZlzhqW87SU1prbx9t6wOttedMPGZcOgAFjOH5UJLbeu9fneSXkrxh6vHXJXnP1LLfSPLSJH8wubD3/sbe+3N7789N8veTvKf3/kettccl+akkL0/y7CSvaq09e7TaHUnu6r0/K8ldo5+vc8H6UMXOszTxlG8aPX7bxDJZ4lhsLUtJfiDJ7/TevybJ30jyE621G4xLnIidZ2niceMSx2ybWfoHSe4dbeu7k/xkcmEWZGmHFDB2qLX2vFG17gmttSeNKuDPuXjN+Xrvv957/9PRj+9P8vSJ1/u6JLckeefUOh/qvX/6gk2/Ksn/Prr//CT3994/1Xv/8yRvS/LK0WOvTPLW0f23JvmWGdtatD6sbMBZWkSW2LsBZKknubG11pI8OckfJbkW4xLFDDhLi8gSezeALD0750WI9N4/keQvt9ZuiXHpYM4OvQPHrPf+wdbanUl+LMkTk/xC7/1j089rrb03yY0zNvHDvfd3L3iJ70/ya6NtfFGSn0jyXUlessp+tta+OMnLkvzgaNHTknxm4ikPJPn60f1beu9XkqT3fqW1dmnGJhetDysbcJaS8y+R72yt9SRv7r2/ZbRclti7AWTpTUnuTPLg6PX/du/9/2mtGZcoZahZGu9+jEsUMYAsfTjJ30pyT2vt+UmekfOCiHHpQBQwdu9Hk3wwyZ8lefWsJ/TeX7jqRltr35nktiQvGi26Pck7eu+fOS+2r+S/TvIbE5e8z9pAX2X3NlwfZhlilpLkG3rvD44Gr3e11j7Re7972d2bsUyW2FTlLP1XSe5N8uIkfzXnmXlvjEvUNLgs9d7/OMYl6qmcpdcn+cnW2r1JPprz6SnXYlw6GAWM3bs555fuPT7JE5L8yfQTVq0ottZemuS1SV7Ue//CaPELkrywtXb76PVuaK19vve+TEOYb8/1l7w/kOQrJn5+es4r+Enyudba5VE18XKSqzO2t2h9WNcQs5Te+4Oj/15trb0955cM3h1Z4nAqZ+l7k7y+996T3N9a+/0kXxnjEjUNMUsfMC5RUNksjYp+3zvaZkvy+6PbF8e4dBi9d7cd3nJ++d535DxAb9rC9r42ye8ledaC53zPrNdK8ukkT51a9qU5nxf5pIllZ0k+leSZSW7I+aVTXzV67I1J7hjdvyPJG2a8ztz13dzWvQ00S09KcuPE/fclednoZ1lyO8itcpaS/LMk/2h0/5Ykn03yVOOSW8XbQLNkXHIrdyuepZuS3DC6/3eS/PzovnHpQDdNPHeotfbdSa713v9Fzi8/el5r7cUbbvaNOa8Y/mI7/+ev7lxiP17dWnsg55W9j7TWfnbi4W9N8s7e+yOVzt77tZzP4f83Sf5dkn/Ze//46OHXJ/nm1tonk3zz6Oe01r68tfaOJdaHlQ01Szn/0nhPa+3DST6Q5F/13v/16DFZYu8GkKXXJfnrrbWP5rxp2mt6739oXKKaoWYpxiWKGUCW/rMkH2+tfSLn/2LI30v8vXRIbVQBAgAAACjLFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeWc72q7OoDBfW+G5sgTzyRJsz7J5kiVYTJZgO2ZmyRUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeWeH3oFtuO/hh3LrjTcdejdgsO57+KFH7ssSrGcyR8lhsnTPfZ9/5P433vrkvb8+bGo6R8n+s3TPfZ/PpcvXHvn56pUzeWJwqoxJk1k61H5wXFyBAQAAAJSngAEAAACUp4ABAAAAlNd677vY7oUbXWVe1qz5kMtYZo7Vom3PmvO4yr6Y48Wc/ixthU2slKWLzrldZmlscg7+pEVZunrl+nY8k/Mlh5Cj8e8yhH0dshnn+l6zNJnnClm6577P5xtvffLCLM1arxL9d0pZNk8bfceb/rxcJ0urniuTWRqPL4uysoxKeRp/NsnTYvPOtWWP1Qpj/VpZmv7OuGw21s3Ssr/3vLFo2SxN95O5yCGzNes91mvxesucZ9OfR8ta9m8mV2AAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5e2kied9Dz+0k86gm5jX4GbcTGaywcz0Y5NmPW+Z5y6zrVUanmzaSG4VixruDLXZ4iHdeuNNSzcerJyl5Px4LtO8adlzKFnc0HOZx1e1jyxVb1q1qgo5SoaVpatXzh6Thcn3fHxM12ksuGqDtE22v8g4S/Mavq2yrXmWbRY3hPEoqZOlZPk8HSpL8z77p9/reVla5fvbUGw7T4u2Vz1TsrS8eef89PeQWZ/li86RedtdZoxa9Jxl/0bbxDaztMy25Gk587LkCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvOF2LlrROs1Idt1s7LGPP7T0tqebVG26r6uY91rrNnzZRSObKs1njtHksV22idImTQZXz9FqjUOrnCub7scuG0JVOUZDM30Ojht5jk02wb10OaP/7rYh5ywXNWVbtnHmdFPffY1Ls15nk3N2UZbue/ihxzQynl53ctm8BpOsZtE5OO+YVvheNG1ePmZ9l1ulkfy6VtnequfuvBzNy8dFWbro+azv0J/h8/Znmees2/DzkFlKljt/l8nQMub9IxH7/Achts0VGAAAAEB5ChgAAABAeQoYAAAAQHkn0wNj2r7mFq/iEPtUYa7bEOdeHbtl5hTu6rX2sc1dzYdctyfNNl5bjoZpm+fdoRz69bftoiwtenz6MbnkVC1z7q+SpWW3Oc90D6JTtWxPo21tb9nn8FjbGj/mbWe6p92qvXymn7/PvoyuwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKO+quKqs0jVm2aWHlRjSb7tusBi6rNkMcYoOkCo1Mq6t83m/bMg2uJrMy6/mzcrFKo6shnofLfBZoorb48+ZQx2dX+V52u5O/8zrZmT5uQzzPVm2sN8TfcdvW/bw8ROPofa0zL0vzPo+XMaTzbJXvrJNj+JB+x11YNUtVMrTL11vlnFi0raGeW9Wbs7oCAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjvdDrzrWi6oU31Job73L9Fr1Wlqee6x2PeekNtwlNB9eyMLbuf4+dt8/ea3tY6TYV3eY7uq0HdqVmmAewpWGVMWfZ5mzSlWydLy44d2x6bOK5js41m7POWL9tM+tCWba64q2N1yo7hmGzrdxj6sVhm/6ezNKTf2RUYAAAAQHkKGAAAAEB5ChgAAABAecOZ7LJly84FHNJ8oIpWmYO1re3BsZk1n39R34yLMiVHnKptZWnd3hxwKLs4F8e9NZZ5jW2NSzLFsdv2306bvE5VrsAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAyhtu9441TTY9WbaRJ7u1qGGa9wcetWqTs3Ge5OhwfKbVtG6WOAw5qmvd5psydTi+G9Sz6nuxSuP2Y+QKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKC8k+reMqvJiUY2tY5BhX3gess0B/K+XX+cqhyPKvtxqhaNOYn3Z55KYxI1yRGsZ/ofM0hkiOFxBQYAAABQngIGAAAAUJ4CBgAAAFDeUU96Wmbu/uRzj30O2EXHY5XjxXFb9Vw4tXmUy2bpVI4H65l1Hp3iOTMvT9vI0Xhd49vx8nk72/Q5v+7xmV5Plo6PnjKLbXJ8rl45e8zfmDK0OVdgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOXp1DLhFBp5bpsmdEzSTO16GjWxKhl6rG00I3Q8j9+8z9tTfO9nHYttNWrUGPe4bav567HYxnk+fQw1xt2cKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8k67M8sMGqhdb1GTzouazmiKerq894+lMRarkKH5ttWMEE7VNj5fZO80GIt2r+rxXfR33qH32RUYAAAAQHkKGAAAAEB5SxUwWmt3tdZeMbXsLbvZJQAAAIDrLXsFxjOTvKa19iMTy27bwf4AAAAAPMayHTgeSvKSJP+0tfarSb5zZ3tEeRc17wSAYzLZsMwYCIezav4O3WwQqhryWLbsFRit936t9357kl9Ock+SS7vbLQAAAIBHLVuW/Jnxnd77z7XWPprkB3azSwAAAADXW6qA0Xt/89TPv53k+3ayRwAAAABTTAzjJE3O+zI/klNz6fK1C8/7WXMjZ60jS5yaq1fO5s4dvigjq7wGHLNFOZq07Xn64+3JGKdkl/0uDpGpZXtgAAAAAByMAgYAAABQngIGAAAAUJ4CBgAAAFCeDjZzTDe5m25+ovnPuWWbMO3DMvuxzP5W+X2GTnPH2tY5z1ddR5Y2s2wjVerY1TkvS9uzTBNj9m/f57hmnqyjwnmzzD4cYszY52u6AgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoT+eaBRY1I6nQxAVNBYfiouM+pBw5hzikY2tAKE/s2qxz7NhyNCZPq3PMLrboGB1jjpaxqFH9vprYn/K56woMAAAAoDwFDAAAAKA8BQwAAACgvNOcuLRF0/OPKs4F2/ccqVOek8V6hpCjbTvWOdjs3rH0lNnGWCFHrOvYeplt2hPsWI4D++Uz+GKytn2uwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADK00VkyyYbtWjSorkP63HewPo0DIPlLdP8UoZgvmNpLL0vvuNuzhUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGDu0TGMoYLZLl689cgPWN6QcXb1y9sgNqhhShhJNE6ll39/nhpRV1qOAAQAAAJSngAEAAACUp4ABAAAAlGeS3I6N52ENcT7ieJ/NJePQJs/BIWYJKhjaeHT1ypnxh1IqZ2h6nyZ/liOquHT52k7zs+1zfda+ytPhuQIDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKK9eF6IjNd3wpWIDqHku2leNotinQ2dpncaC0w1xh5R/jk+VpriadDJUQ/sslzUqqTIGrcvfPYfnCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvOF1TjkS+2wANa+B4C4az2gUxb5tmqVLl6/trYlUlWZVcsrYrPOgynk6ad64dah93eU4ynBc9P5XytL0vhzi3N3GeLtofXkcnmXes0o5mjZr36aXVW36uclxPfTv4QoMAAAAoDwFDAAAAKA8BQwAAACgvLqTik7E5ByiXc/xumje+7bm9JobzCHss6/MLEPrK1F1TiaHd6gsLfN61eZCLzPembNPRYfK0rrn/BA/H9iOffYq27UK3xWP4Vi6AgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAob/hdPI7IrKYu041WdtH0c3o7x9DchdM1bvZ0UVa21URpctuL8lrZrKZSuzxmDMuiLG3aXO1Yxpt1fw9Nr+HcvCxs8zNCzqjgkM3mj4UrMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyjqebx5EaNxzaVeOVY2josuh30LDpNE2/75s2GlzXkPK1zL5OPke2TtO+3/chZWgTi7Ila5ySU8k8u3Pq59B0Q9xjPB6uwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKO76uHkds2428jrGpy7Tp33FWQxsN0k7D5Hu/jff8FPKzyKzfX5ZgO2QJYHWn/t1s0jEfC1dgAAAAAOUpYAAAAADlKWAAAAAA5SlgDMSs+bDmyK7u6pWzo54TxsWmc7PO+eAcAgCA/VPAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMpTwDgx+2w+qNEhAAAA26KAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSny+KADaFJ5hD2EQBgXy5dvub70ZouXb523c+O42maPA+cA5uZzlRS/5i6AgMAAAAoTwEDAAAAKE8BAwAAACiv9gQXHmM8J2nWfCUA2Kfq82SrMG//NPmudr2rV842Oiaz1tUL4TTI0nZddDyr58oVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB59bpyAOxBxaZEUImmadvhOMKj1m1Gv8zzL12+ZmyHC6ybvUrZcgUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUF6dbhyspFIjFeD4zGry5HOHSc6Hc4saB85rllaxKRrs07rNPC8yuT354hjtKjsXqdSQ2hUYAAAAQHkKGAAAAEB5ChgAAABAea33fuh9AAAAAFjIFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYA9Na+6HW2u+01j7SWrurtfaMqce/pLX22dbamyaW/WBr7f7WWm+tPXVi+VNaa28fbesDrbXnTDz26dbaR1tr97bWfmti+c2ttXe11j45+u9T5uzny1prvzt63Tu2exRgc2tm6Z+PzuuPtdb+t9ba40fLW2vtn47O94+01v7axDozsyBLHIs9Zsm4xFHbcpa+srX2b1trX2it/fDUdoxLHLU9Zsm4dAAKGMPzoSS39d6/OskvJXnD1OOvS/KeqWW/keSlSf5gavk/SHLvaFvfneQnpx7/pt77c3vvt00suyPJXb33ZyW5a/TzdVprj0vyU0lenuTZSV7VWnv2kr8f7Ms6WfrnSb4yyX+e5IlJ/vvR8pcnedbo9j8k+WfJhVmQJY7FzrM0wbjEMdtmlv4oyauT/C+TTzYucSJ2nqUJxqU9U8DYodba80aVvye01p7UWvt4m7jKYR2991/vvf/p6Mf3J3n6xOt9XZJbkrxzap0P9d4/PWNzz855qNJ7/0SSv9xau+WCXXhlkreO7r81ybfMeM7zk9zfe/9U7/3Pk7xttB6spVCW3tFHknxgYp1XJvn50UPvT3JTa+1yFmdBlti7AWdpEVli76pnqfd+tff+wST/99TLGJcoZcBZWkSWdujs0DtwzHrvH2yt3Znkx3JeyfuF3vvHpp/XWntvkhtnbOKHe+/vXvAS35/k10bb+KIkP5Hku5K8ZMld/HCSv5Xkntba85M8I+dh/VySnuSdrbWe5M2997eM1rml935l9Ptdaa1dmrHdpyX5zMTPDyT5+iX3CR6jWpZGlxV+V5K/N1o065x/2pzl4yzIEns34CxdiXGJQgaQpXmMS5Qy4CwlxqWDUMDYvR9N8sEkf5bzy48eo/f+wlU32lr7ziS3JXnRaNHtSd7Re/9Ma23Zzbw+yU+21u5N8tGcX251bfTYN/TeHxwF7l2ttU/03u9edvdmLOvL7hTMUSlLP53k7t77e8ebmbU7C5YvvXsbrg+zDDFLiXGJeipnae7mZ+3mKru34fowyxCzlBiXDkIBY/duTvLkJI9P8oQkfzL9hFUriq21lyZ5bZIX9d6/MFr8giQvbK3dPnq9G1prn++9z20I03v/4yTfO9pmS/L7o1t67w+O/nu1tfb2nF/mdHeSz7XWLo+qiZeTXJ2x6QeSfMXEz09P8uC8/YAllchSa+1HkvzHSf7HiU3NO+dvmLM8kSUOZ4hZMi5RUeUszbMoC7LEoQwxS8alQ+m9u+3wluTOJN+R8wC9aQvb+9okv5fkWQue8z2zXivJp5M8deLnm5LcMLr/d3I+7zhJnpTkxon770vystHPb0xyx+j+HUneMON1zpJ8Kskzc/4H3IeTfNWh3wu3Yd8qZCnnDZ3el+SJU8/7mzm/PLEl+S+SfGC0fG4WZMntULeBZsm45FbuVjlLE4//o5z/gTf+2bjkVu420CwZlw51vhx6B475lvN/2eNXRvcfl+Q3k7x4w22+O+c9Ku4d3e6c8ZzpQL4651W+azmv7P3saPkLknwyySeS/EqSp4yW/5VRiD6c5ONJXjuxrS/LeePPT47+e/No+Zfn/JKs8fNekeS+0YfHazf5nd3cCmXp2uicHq/zD0fLW847Sf9ezqdj3TaxzswsyJLbIW5DzZJxya3abQBZ+ks5/+73x0keGt3/ktFjxiW3MrehZsm4dLhbGx08AAAAgLL8M6oAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHlnO9quf9oE5msrPFeWYD5Zgu1ZNk+yBIvJEmzHzCy5AgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjv7NA7AJAk9z38UJLk1htvOuh+wNDJEmxunKMxeYL1TGdpTKZYlyswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPJa730X293JRscqNCjTkIYNtBWeu9MsHdI9933+kfuXLl975P7VK+e9hb/x1ifvfZ8YnJPM0nR2xpmZXJbkMctl6rjs4LvQsnk6miyNzftON87Q5Bg1Xi5Pp2ONrJ1klublaGxenvztdPxmnRtLvu8zs+QKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKC8nTbxnGzYMdmo46ImL5tapRnMZDO0SbMao817XvLYxjSz1j10w6f7Hn5Io5w5ps+D6QZDm5o67is1HpzOy6033rTzDG3SSHNeprblon2adby2TZbmW/SZug3rZum+hx/ae7O0bTT6G5/Py4xH61i0fxs03VravO8Jp25WjrY9Lo1NHPel8nSILG16bkyeZ7OyNKuR9KpmZWne5+Euvg/uY+wbol1/v5t0CllK5o9Ls5rdznLR86bzMStHyzxn0fMvYmy63qzP0ENmyRUYAAAAQHkKGAAAAEB5ChgAAABAeTvpgXGIOV2TFs2lWjRHatFcnovmca0zZ3Kd19vGtndpCPPEpueJXr1y9pj5rzue11V63n6y+PxbJk+7PLfnWfY9W/b1D5WhsSFkKZk/v3hPcyTLZmn8ObJojvB0j4zJY7nMcdtVlpbdB1navl33kFlk2TztI0uzcrPs+TbO1PhYLnMer9MDY5l1lu0JsMxrbNs6/bS22T9h3v5Mv8aqvQgu6oVwalmaZZXz8BtvffKFWZo33i+bi2X2aZW/t/Y55sw6J5fN1ap52mcPyUWvtY/vd2PzsuQKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKC83XYAO6DJxiKzGvpsq/HIrhoyrdvA7dDN0pZpMLOoQdMhHPqYVTDdkGdRo6Z5TRsPZdXXX6d51CFclIt956jiMapmnc/kIedplcaKh7RKlvY1Hg3huB3KKo3/Zq13URPHVV93my5qgnjR87ZpnXN9mSytm6HxeovW36Sx4Clmbt4xWaXp+Tp5uuhYTz6+7rl+6LFybJMxY9G6m2RpXYf+e2wVrsAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAyjuKjjYXNYtZp9HLsTT7uXrlrEyjm7F9NolZtjHW9PMO0VCrgouaYJ1ylsaqnBtVmy1dlKWxU8jURZ+/qx6DY8tSFVWzNGkX33OOzSrHYNnPqVW2sczzj/19OmSWVmlMuek2hmbdppmr/oMC+8jROtsf4vtqXFrMFRgAAABAeQoYAAAAQHkKGAAAAEB5Rzuhdt05T/uYi7WOTeb2Lfualy5fmzm/f925c1WZR36xbfR52Ndx3tXrrLLdZecBXtRjhOOz6efnvj+vdvF6m/RBkRmSzXM0vY19WbfXxi6+K04fw2P7bje2yft8Cp83p5alVZ87dsznwDK28R7v8jPGFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeUfdzfCihpRDUmW/ZzVk2WfTo2WOw6L3ucpxHJpFjXgc09Vt0tRw1/swaTrjbGaV5riO+fUqN9fzXu3XrOM967zwvsw3qyFihWx5z/Zrme8i3pPHWnRMKuQoOf73zRUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHnH3eFjyrE3NDm0eU3Wlj3u22oK6n3eLcd3dxY1S531vIsyIku1Ob7bcdFxrNJUjeWt2nRdlja3SmNnhmOdf8BAnta3yrGTp/W5AgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoT5cWdkbToOFZp9kTu3H1ytljGtvOeg51rNvAmP1a9L7MypxGa/s1Pt6Tx12Wapgcl2Y9lsz/HJSj/ZvOkhzVssxYNH6e/FzPFRgAAABAeQoYAAAAQHkKGAAAAEB5RzEZyrzj7XDcTtdkhsw7Xs0uj5HjP2x6yiw269jsep7vRe/HkN+vY+41IEt1LPs+eL/qkaPh8D4t5goMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoLyj7BCiqeejx2DT3/0Ujx2P0vDpUZtkyjE8Xdv6LB6qVT9DlnnuqR7LU3fqWVqGY8NFfK9bj2NWiyswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPJOoiPJZFNPTVi2x7E8DZriwuY0INwOTXRnO4XfcUwTQtiMv4seNe/z5NSPS3WuwAAAAADKU8AAAAAAylPAAAAAAMo7uQk+5iHvzngeWfVjO93TYVr1/T80848ZuyhLiTxNM/eYaXK0OuMQyXLZmea8gcdaJUsVMuQKDAAAAKA8BQwAAACgPAUMAAAAoLylChittbtaa6+YWvaW3ewSAAAAwPWW7cLxzCSvaa09r/f+j0fLbtvRPsFG1mnqNG8bFRrVwKHsIkvb2CYMjfOe6uado5Of3ct8J1r1+auSJdiOIWdp2SkkDyV5SZJbWmu/2lr70t3tEgAAAMD1li1gtN77td777Ul+Ock9SS7tbrcAAAAAHrXstV0/M77Te/+51tpHk/zAbnYJAAAA4HpLFTB672+e+vm3k3zfTvYIAAAAYIoOhezUrpo4TW5/14bc5AaW4RyHc9sYs+QJzskTp+ai8/XqlbOlnrPKNld1DJlatgcGAAAAwMEoYAAAAADlKWAAAAAA5emBccQumnc4PQdql70qlt2PVfcZ9mUb+VjlXN81WeIY7KLP0qo5lSWYb9V8yBNs1zFmyhUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkn28RzF42/KtnF7zZuArPL43aMjWZglm1/BskOFe1qvNjX+S5XDMGy52n1773yBttx7FlyBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQXu1uPjt2UYOT6s2ODmUfzTypbdXmQM6V2WTptC1q5DovY86Vxzr2ptzMNp2RIZ4DxgAObdH3uSGdl5O/x6r77Tvt8LgCAwAAAChPAQMAAAAoTwEDAAAAKM8kngU2mU+1K5XmS5p3zLIqzFU+lnmeHJdV595WztIhc1RpbOQwVs3S2Pic2ec5NL2vFXIN04bQK3DWPvr75Pi5AgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoT4eTJR2qadm6Tan2RaMc1rHv80aOYHPVczQmT6xin+d19QxdvXJWfh+pw99GHIorMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDydLna0GQjmW03rdl1k5pt7a9mOgDHa8if8dP7rrknh7LLHM06r9d9vcltzdrGeFnFLG3zOFCT93M/KuZ7kiswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPJqd+gYmEuXr5VverJLlX/3eft26u8ZrGLVrGi2NXzH9h5W+Mw/9OuzP4fMzzbOs8ltTG/v0Fla9rXl7TgMZSw6hvNtCL+DKzAAAACA8hQwAAAAgPIUMAAAAIDy6k9yGZhl52gNYX7RtKtXzgYxB22VYzvvuUN8f47ZovNuSO/VeF+PLUe73Aa7NXkuDuUzPrn+3Fp1n/c9d18OTsdQ8rMth+iDIU+nZdeZmnU+Tb/mJuPNMq95ap8b2+AKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8nXAOZNywZWjNiFZtZDP0Rmka6+zOtjIwxCyt08xzutniLu0qS0N6j4Zim+fFKX3e7TpPux6PZGl3fFatZ2ifH0P87jAU886FYzjW+/gdhnZuXrS/u/hscAUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUN4wuoPwiEoNXa5eOdtKY5Z1GhrOWp9hmvW+7+M9rXDebHrub9M+G1OxG8fcOG2RTceibZ+X+8rSsb+vh3SKWTrm320RWdqffTanHFojzFmG9p1p+pjvcv9dgQEAAACUp4ABAAAAlKeAAQAAAJQ33IlBJ6bqHK5t9cFY9TU5bruck3qIc/Yi2/hd1/m9ZOk0bHsucKXeLWNVzuV97scxzPEeGsd8f/Y5Vntf98vxPm77yK0rMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDydE8pbggNbva1j0M4FmzPNps8OXeu53icpm00x3XuPNahj0mlZqqnYpeNpk/dIY+rLO1X1RxVbPbO9VyBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngFFYxcY2sG8aKcH2bJKnoYxJ+9zPoRwTts/YBJurmqOrV84euVGPAgYAAABQngIGAAAAUJ4CBgAAAFCeiT1FXbp8zbwr2MB4XqUcwfVkox7vyTB53w7voh4K3pv6/M1Ty7xMVXqPXIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlFenGwdJLm5GxGqG0IgGqlv0uSRLw3UK4834/Kzyu160H5pCDlOV82sfDp2pUzrWp2T6ffUZWFeFccoVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5OqQcmGZE27Xs8azQgIbtkqXtWjVLiTydqiG875P7uO/Pim28ns+30zCELI1dvXI2yPNyiPt8ijZ9n4aUpaE6ZJZcgQEAAACUp4ABAAAAlKeAAQAAAJRnghBHY525WPPWMXfuuA3x/d3nfON1X2fWekM81ixnqO/tELLEaRhqhqCSoedoqP1kDskVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5w+56AtlNkzTNdKho3Kjq0uVrO2laJUucisn8OO85hKE3HkyO43dg2I7lHNTIczWuwAAAAADKU8AAAAAAylPAAAAAAMprvfdD7wMAAADAQq7AAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKU8AYmNbaD7XWfqe19pHW2l2ttWdMPf4lrbXPttbeNLHsn7fWfre19rHW2v/WWnv8aPl/N9rOR1pr72utfc3EOi8brXN/a+2OieU3t9be1Vr75Oi/T5mznzPXhyr2mKVPt9Y+2lq7t7X2WxPLZYmjsOUsvXK0nXtba7/VWvvGiXWMSxy1PWbJuMRR22aWJh5/XmvtL1pr3zaxzLh0AAoYw/OhJLf13r86yS8lecPU469L8p6pZf88yVcm+c+TPDHJfz9a/vtJXjTa1uuSvCVJWmuPS/JTSV6e5NlJXtVae/ZonTuS3NV7f1aSu0Y/X+eC9aGKnWdpwjf13p/be79tYpkscSy2maW7knxN7/25Sb4vyc8mxiVOxs6zNMG4xDHbZpbG5/2PJ/k3U8uMSweggLFDo0rdR1prT2itPam19vHW2nM22Wbv/dd77386+vH9SZ4+8Xpfl+SWJO+cWucdfSTJB8br9N7f13v/DzO29fwk9/feP9V7//Mkb0vyytFjr0zy1tH9tyb5lhm7uWh9WNmAs7SILLF3A8jS50fLkuRJScb3jUuUMuAsLSJL7F31LI383SS/nOTqxDLj0oGcHXoHjlnv/YOttTuT/FjOK3m/0Hv/2PTzWmvvTXLjjE38cO/93Qte4vuT/NpoG1+U5CeSfFeSl8x68uhSqO9K8vcWbSvJ05J8ZuKxB5J8/ej+Lb33K6Pf70pr7dKMbS1aH1Y24Cwl518a39la60ne3HsfX50hS+zdELLUWvvWJP9zkktJ/uZosXGJUgacpcS4RCHVs9Rae1qSb03y4iTPm3iqcelAFDB270eTfDDJnyV59awn9N5fuOpGW2vfmeS2JC8aLbo9yTt6759prc1b7aeT3N17f+/Utr4p5+Eez4+ctYFlKvePbHLD9WGWIWYpSb6h9/7gaPB6V2vtE733u5fdvRnLZIlNlc5S7/3tSd7eWvsvc36Z70tjXKKmIWYpMS5RT+Us/ZMkr+m9/8XUOsalA1HA2L2bkzw5yeOTPCHJn0w/YdWKYmvtpUlem/M5918YLX5Bkhe21m4fvd4NrbXP997vGK3zI0n+4yT/49S2vjrn8yJf3nv/v0aLH0jyFRNPe3qSB0f3P9dauzyqJl7O9ZdSjS1aH9Y1xCyl9/7g6L9XW2tvz/klg3dHljic0lka673f3Vr7q621p8a4RE2Dy1Lv/Q+NSxRUOUu3JXnbqHjx1CSvaK1di3HpcHrvbju8JbkzyXfkPEBv2sL2vjbJ7yV51oLnfM/ka+W8Cc37kjxx6nn/SZL7k/z1qeVnST6V5JlJbkjy4SRfNXrsjUnuGN2/I8kbZrz+3PXd3Na9DTRLT0py48T99yV52ehnWXI7yK14lv7TJG10/68l+WzO/y+Vccmt3G2gWTIuuZW7Vc7S1Do/l+TbRveNSwe6uQJjh1pr353kWu/9X7TzTrPva629uPf+/95gs2/MecXwF0eVwH/fe/9vLljnZ5L8QZJ/O1rnV3rvP5rkHyb5siQ/PVp+rfd+W+/9/9/e/bta8t51AH8evVplcasbr5UWbmGXoGKRzi6tBLsg2mnQ0lokkD8hkRCsLAS1sLEJNt82WASbTQqxuXAhsLBfEPSGsdid7Nz5zpwzP56Z+TxzXi8IZO/ec+78eN53zn6YeX+fc87fSh+adn85pfSDpmn+8+N7fSel9I855z9LKf13SukbH/f1N1JK32+a5utXXg+z1Zql9KEk6l8+fu0upfQPTdP828f3kiV2V0GW/iil9M2c8/+llP4npfTHzYdPeq5LhFJrlnLOrkuEUkGWBvn30nHaySwAAABAWP4zqgAAAEB4BhgAAABAeAYYAAAAQHgGGAAAAEB4W/1XSDSDwrg843tlCcbJEpQzNU+yBJfJEpQxmCV3YAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADh3R29ATV7+/7dF7725tXr3bcDzqCfJ1mCdT57+3m6f3iWJQDgNNyBAQAAAIRngAEAAACEZ4ABAAAAhJebptnifVe96dv378I8szvUc9H19PipRuT+4fnF30XZB7a1oLshz3j7pv8z3rx6/YU/X9q2aOvwWqaGRNsHtjN1bX80K0tz1l77syN3s/S3rXs9arkuMeM6MDVPs7I0JvJafPv+3WCeWvcPz+np8S597c2XdtwqKrJrli6JkLPP3n7+4s/961JKMbbz1o19/jr43xKDWXIHBgAAABCeAQYAAAAQngEGAAAAEJ4BBgAAABDeJiWeb9+/26QZ9JJS5SJTy3SmlKVdKoAqQQnOcluXJo35eH4mFw8ekaWUXq6jbvnSnMKy7jEeKrsdy8fQur70/WuN/TxZ+qKjctPVOy+hszRlzc7N1NPj3axrTfd7r23Ptfdtiwunvj6l28xRiZxcKggvZeDcTMrT1llq1/jS3/lTMzWnpH2uoXPWz+6Uz5GtWnM0twS59DVmzjEuobN/IbKU0rR119d+/9x11y/rbN9r6FoytJ2XtuWSW8zSkLHy8RLmrJuS3rx6rcQTAAAAqJMBBgAAABCeAQYAAAAQngEGAAAAEN5pSjxTmle41JY8LS06mVsMtLSwcMuyoSFvXr3+xTEZKrqZc7ymFOVEKAXs27o8bayQZkgNWUrpep5KlHj232vpuRkqQSylu+aHjkU/E1PX/97FZ6VMKe5ao4Ysdc0p9WzL0JYWmLWmlLftfZ25Zm6Ouq5lYey1UTPU2qOMcGqe9ijx7FtS+tee636x4JZF0ZGy1P08N+V7h8zN39hrotjrd2CULKU07TPP1Gv10+Nd+tqbL73I1JLy50t5jpShpab8+6nmHKU0/XPHWko8AQAAgGoZYAAAAADhGWAAAAAA4RlgAAAAAOGtbyw6wFghzZzSkE8FafN/9tS/W1NiclSJTbc0Zm2BzFhhTfRimjObWmA1Z/09Pd4VPadbl9Vtma1rx2HpcRrKkhwda0kZ3JS1157XudemMSWKCfe2VY6GXitLx1u6Rq/lqXSWajNnXZf4XlmKY26mpn4uun94Tp+9/fwURZtbmpIDWVnHHRgAAABAeAYYAAAAQHgGGAAAAEB4uWma4m/69v278m/aUbJrYurP2NrcfRjrAWGZOed77XF/8+p1nvq9pbN0bT+3WlOR8yRL5Wz13O2YyFlK6TavTay35ByXOE9T83REllKq//okS/s6KkcpHZel1qV933odbp0nOTrGnv9O6hrLkjswAAAAgPAMMAAAAIDwDDAAAACA8AwwAAAAgPD2bQPbyFCxyJICkb3L0a797P4+9L/nqELGo7X7fdQ57r7H2Y7xGbLU//lD2z8lS2c7t31zf+dc+320dBvOfJxLrKvastR15nPbOvr8tM6epZTWF7gffa6W/D5dek6H1kPU69zR56VrzefLWpReB3ufvym/B7Zc61HXSMQctbY4Vu7AAAAAAMIzwAAAAADCM8AAAAAAwjPAAAAAAMKL0/hRWKQyk6XW7sPUEpVaykDnlphSRu3Heen2z31dNyfRMzW2fZe2u/Z1EEXNx3Huth+xr0dni/3cQpbW7OOU10a/VrGPqeusXQ+RsrckS1uUkl97r+6x6x/HsSJS+RvnDgwAAAAgPAMMAAAAIDwDDAAAACC8OA8xEdbSZ8M8u8UtmZOTJZm69MymrMEHrlf1i/ic/a1a0wXF+Zwlk0fsR/dn6vRbzx0YAAAAQHgGGAAAAEB4BhgAAABAeAYYAAAAQHhVtoYoeKrDtfOj7CmG+4dnWaqAcxTTpXJVYLp+lnzWg2XGPl/LEmfhDgwAAAAgPAMMAAAAIDwDDAAAACA8AwwAAAAgvKrbXBQ8wTxjxU6yBPPIEpRxrdBb0TSUIUuchTswAAAAgPAMMAAAAIDwDDAAAACA8E4xwLj2/CQA7Ml1CYBoXJs4g1MMMAAAAIBzM8AAAAAAwjPAAAAAAMIzwAAAAADCuzt6A0rpltI8PZ5mtzbnWNHVL3eyPmC5+4dnGYICfMaDcsaKPGWLWrgDAwAAAAjPAAMAAAAIzwADAAAACM8AAwAAAAjvlG0titOG3fIxGSssat3ysYG5LuVJll5qj5XjwhBlevP5jMcQWYIyasiSOzAAAACA8AwwAAAAgPAmDTByzj/MOX+997W/22aTAAAAAF6a+jDLb6WU/jrn/HtN0/zNx6/97kbbBKtc67uAOa51GNxKx4FcQRmyBGXIEqxXY46mPkLyLqX0hymlL+ec/zXn/GvbbRIAAADAS1MHGLlpmuemaf48pfRPKaXPUkr3220WAAAAwCdT73n+bvt/mqb5+5zzj1NKf7HNJgEAAAC8NGmA0TTN93p//lFK6U832SIAAACAnnO3zlHEtXKXfnnhUaWGe5bQ1Fh4w7aG1sRYNoZEKgG1vtnC0LVhSm7mvOf9w3OoLKUkT2yjv9bnflarjRxxpNoL27u/L86QpakdGAAAAACHMcAAAAAAwjPAAAAAAMIzwAAAAADCq7OJhCqMlcSULMA5QxEN51VqffbfZ4sSKVkiiiVrMdL6jbQt3IYpa25qyeel603377YqM5QftrZmjV177dxy3dac0vcl27XkPSNzBwYAAAAQngEGAAAAEJ4BBgAAABCeAQYAAAAQnhJPdre2ROZMJTSwxFbloGynPdZbFd+xTIkMyNH+9iiT5DLXofNxnTqOHMzjDgwAAAAgPAMMAAAAIDwDDAAAACC80z7kNPYskee66uX5sP3J0TnJ0nFk6lxk6XhD50CeYLl+puRpnvuHZ8dsY+7AAAAAAMIzwAAAAADCM8AAAAAAwjPAAAAAAMK7uYaRS4Vb0QpXlhRTXSsUi7aP1OlaEaECI5hnrDSt/bo8wXTRSgjlmJp18/T0eGc9czh3YAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhaV/piFCAeW0btnx/ZTys1V1fc9Zy6bWnRJTa9fMzNU8l1320IkRY6tpa3mKtD2W2X4YItel/zhtaxyVLPo+49hGfOzAAAACA8AwwAAAAgPAMMAAAAIDwPDAUyNb9F3hG7ha0OVrb97K0g+CWyNM5ja31ks8185Jjuq8j+8aGvsf5L8ex3Neltb6mj2xuRl2fyltz7rY+D+7AAAAAAMIzwAAAAADCM8AAAAAAwjPAAAAAAMLTdBKEgsDtKPS5DTK0H5k6rznlg0vKcOe+/uxKFNw5jnG4Dh2nVFmkPB1Pjo41NwNtaWf3vG1d5OkODAAAACA8AwwAAAAgPAMMAAAAIDwDDAAAACA8TTUzlCz6qbmg5tp+t38fYR+VMbGnpWu/hnVaYhuVpdEV4RpxlJJrf+uytFsU8Zgqbh1W+ljc8u8lyqgxn2u3+VJh9xbcgQEAAACEZ4ABAAAAhGeAAQAAAIRX30M6gUR8RrKrVBfF0n18eryr/lnC6Of4LM52nPv7srb74QxZGnLGfTraGbLU3f5ra6T2fS1FlsqLnqXutm3RPTa079GuRZHPDx9E777aq7evf12LlqXauAMDAAAACM8AAwAAAAjPAAMAAAAIzwADAAAACC9Wk0qF2gKWKKU0UbbjTJTssJZcwjKyw5Gifcabas32XnvtXqWHnFN33RyVq7GC2q5S6/vSz5pTWM1L7sAAAAAAwjPAAAAAAMIzwAAAAADCM8AAAAAAwqurlSiw+4fnXcpoShZKKWIikmhlaWPbIS9EFy1L0cgwcw2tGfmCdSJfqyJuE5+4AwMAAAAIzwADAAAACM8AAwAAAAjPAKOg+4fnX/yvJk+Pd571Iow9MrTm/eWFWkTOEdSu5PqXJW6ZLDGXAQYAAAAQngEGAAAAEJ4BBgAAABCeAQYAAAAQnia6jdw/PCv6gxX6RUzR8tTdHqVRRHVpbZbI1LVr3aW/kxtq113Da/Pkc+P2/M6Jy7mpy9Hnyx0YAAAAQHgGGAAAAEB4BhgAAABAeAYYAAAAQHjagjZUstxpjfZnH124EsFYMWT7dQVacUU+RxG3aWtTfp/c4nGpydHXBNemT/qfFxyT+jhnMfQ/KzgvsE7EDLkDAwAAAAjPAAMAAAAIzwADAAAACM8AAwAAAAhPw9pOIhQQ3mIx2Nz9vbXjUyPn6DjyxBZuuWzvFveZZZQiXyZLUE70PLkDAwAAAAjPAAMAAAAIzwADAAAACM8DdTtb+kxRqWcfPUMJLBH9eUjqd0vXp0t5kjWYbiwvcnQ7utcO5329Go6hOzAAAACA8AwwAAAAgPAMMAAAAIDwDDAAAACA8G6nMQsAKK4t/LqlEk7YwtosLX3dUGlfDXmuoWyQbVxan911ccQ6rjFPtWXJHRgAAABAeAYYAAAAQHgGGAAAAEB4BhgAAABAeLEbRaje0+Nd6GKYyNsGAAAsc//wvHmBpn9L7M8dGAAAAEB4BhgAAABAeAYYAAAAQHi5aZqjtwEAAADgIndgAAAAAOEZYAAAAADhGWAAAAAA4RlgAAAAAOEZYAAAAADhGWAAAAAA4RlgnFjO+W9zzn/V+fO3c85/eeQ2QY1kCcqQJShDlqAMWapPbprm6G1gIznn30wp/XPTNF/NOf9SSuknKaXfb5rmZ8duGdRFlqAMWYIyZAnKkKX63B29AWynaZr/yjn/LOf8lZTSl1NK/yGMMJ8sQRmyBGXIEpQhS/UxwDi/76eU/iSl9OsppR8cuylQNVmCMmQJypAlKEOWKuIRkpPLOf9qSunHKaVfSSn9dtM0Pz94k6BKsgRlyBKUIUtQhizVxR0YJ9c0zf/mnP89pfROGGE5WYIyZAnKkCUoQ5bqYoBxch/LaP4gpfSNo7cFaiZLUIYsQRmyBGXIUl38Z1RPLOf8Oymln6aUftg0zU+O3h6olSxBGbIEZcgSlCFL9dGBAQAAAITnDgwAAAAgPAMMAAAAIDwDDAAAACA8AwwAAAAgPAMMAAAAILz/B5OOdjTbRST6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_x(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df1, col='x',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_x, 'y', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r', cbar=False)\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "e3f298ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df[df['x'].between(x_min + N*x_step, x_min + (2*N-1)*x_step)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "5a1f4b1a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_x(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df1, col='x',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_x, 'y', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r', cbar=False)\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3c8767c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df[df['x']>=x_min + 2*N*x_step]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c99ed331",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_x(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df1, col='x',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_x, 'y', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r', cbar=False)\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8559632c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df['y'].between(y_min, y_min + (N-1)*y_step)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "e6955dce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_y(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, cbar=False, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df2, col='y',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_y, 'x', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r')\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "07b30764",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df['y'].between(y_min + N*y_step, y_min + (2*N-1)*y_step)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "36875844",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_y(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, cbar=False, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df2, col='y',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_y, 'x', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r')\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "1a9ef425",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df['y'].between(y_min + 2*N*y_step, y_min + (3*N-1)*y_step)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "a75b42eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5ChgAAABAeQoYAAAAQHkKGAAAAEB5B9fdRMMWAPhi6zRCW7dZmrmWbZjKeTVmM8+pvGdqm+p5dN4Gnesck8NlBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQ3sF0OZlyw5Yxx75uE5zzNKCC6iqdq8uyVWl8jOcQ/1wX39PJ+bzv9zpmozfq2Pd5tQtV36NMMRWr/u5ykWzt4+9gXJwVGAAAAEB5ChgAAABAeQoYAAAAQHk1L8jjVGNcY7XJMVzTRQWb9G0Zw1mvc57xyBIVnOfc3ef1+3JzuKr2hVjXFMcvT4dliufgMpu8j0N5z5yfFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAebqgTIjGS2zTMTdFki0YxzpZWvWzRg5hHLIE4zrJ1Pz8JWf7YwUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUN7ku/Ydc+NBOEZjZF7jJRh3/pQpGNd8pvyuC/thbqvJCgwAAACgPAUMAAAAoDwFDAAAAKA8F9UBAOfi+mAYl0zBuMbsJyOfNViBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJQ32SaeF23CAszIEgDsl+aAMC6ZOlxWYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADl6d43AYtNaBabLmpSA7snd3A+Z81pAHBefj87fFZgAAAAAOUpYAAAAADlKWAAAAAA5bXe+77HAAAAAHAqKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMCamtfaC1tqnWmvvH7YXzt335NbaO1prH2mt/XFr7SnD/p9srd3dWuuttcfPPf7vt9Y+OGzvbq193dx997bW7hxe471z+x/XWru1tfbx4etjV4zzOa21jw2ve8tWPgy4gJGz9NwhR+9vrb23tfYtc/ctzYIscSh2mCXzEgdtzCzNPe8bWmtfaK19/9w+8xIHbYdZMi/tQ+/dNqEtyQuS/PKK+96Z5NnD7UcneeRw++lJnpLk3iSPn3v8NyV57HD7O5P827n7rnns3P6XJ7lluH1Lkpctecx1Sf4kyVcmeUSSDyR52r4/O5ttfhs5S49O0obbX5vko8PtlVmQJduhbLvI0vC9ecl20NuYWRruuy7J7yR5e5Lvn9tnXrId9LaLLA37zUt72KzA2KLW2i+01n5q7vtfbK29eEuv9bQkl3rvtyZJ7/2zvfe/Gm7f0Xu/d/E5vfd3997/Yvj2PUmeuMZLPTfJ64bbr0vyPUse88wkd/fe7+m9fz7JG4fnwblMIEuf7cNslORRSU5un5YFWWLnJpyl08gSO1c9S4P/Lsmbkjwwt8+8RCkTztJpZGmLFDC269VJfihJWmsPS/L8JK9ffFBr7V1zS5zmt+9YcdzvG5bY/mZr7UnDvpuSPNhae3Nr7Y7W2itaa9dtMNYfTfJbc9/3JO9orb2vtfZjc/tv7L3fnyTD18tLjvUVSf507vtPDvvgvMpnqbX2va21jyb5X5P8yLD7tCzIEvsw1Swl5iVqKZ2l1tpXJPneJK9cuMu8RDVTzVJiXtqLS/sewCHrvd/bWvt0a+3pSW5Mckfv/dNLHvesDQ77tiRv6L1/rrX245lV9b4tsz/LZ2W2/OkTSX4js+VTrz7rgK21v5NZAeNb5nZ/c+/9vtba5SS3ttY+2nu/fc0xtiX71vlXNFhqClnqvb8lyVtaa/9Vkl9I8h25eBZkiVFNOEuJeYlCJpCl/yHJT/fev9DaNae/eYlSJpylxLy0FwoY2/eqzILxZUles+wBrbV3Jbl+yV0v6b3/6/kdC4H+9SQvG25/MrPA3zMc861JvjFn/KLYWvvaYYzfOX/s3vt9w9cHWmtvyWyZ0+1J/qy1dqX3fn9r7UqWL6X6ZJInzX3/xCT3nTYOWEPpLM0d9/bW2l9vswZQp2VBltiXyWWp9/7vzUsUVDlLz0jyxuEvXI9PcnNr7WrMS9Q0uSz13t9qXtoPBYzte0uSn0/y8CQ/sOwBm1QUT8IwfPvdST4y3P7DJI9trT2h9/6pzKqM7112jLljPTnJm5P8YO/9rrn9j0rysN77Z4bbf3d4D0nyLzJb5vXS4es/X3LoP0zyVa21pyb5d5ktBVv63mEDlbP0Xyb5k957b619fWbNmD6d5MGszoIssS+Ty5J5iaLKZqn3/tS54742yb/svb+1tXYp5iXqmWKWzEt7ooCxZb33z7fWfjfJg733L4xwyBe31r47ydUkf55ZtTLDsqaXJLmtzUqE78us4pg2a4Tz/8msqvnB1trbe+8vTPKzSb40ya8MVcWrvfdnZLZ86y3DvktJ/mnv/beH139pkn/WWvvRzJZePW94jS9P8qre+82996uttZ9M8q8y67D7mt77h0d47xyx4ln6viT/oLX2n5P8pyT/de+9JzktC7LEXkwxS6018xLlFM/SqjGblyhnilmKvy/tzcl/VcaWtFkzmj9K8rze+8f3PR6YKlmCccgSjEOWYByyxCb8LyRb1Gb/Vc/dSW4TRjg/WYJxyBKMQ5ZgHLLEpqzAAAAAAMqzAgMAAAAoTwEDAAAAKG9b/wuJ61JgtbbBY2UJVpMlGM+6eZIlOJ0swTiWZskKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvEv7HgDTd9dnHlz7sTddf8PWxgFTtUmGThxKlk7e+6G8H/brPFk6MfVzUJY4j4tkZhXnIMdoG1ladJKtY/95bwUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUF7rvW/juFs5KOPZRaOZKVrVDGfMz+um629oGzxcloo75iwtNpOa37eKLLHKMWbpIg3Yxv68NsiTLBUnS5uRJc5yDJkaoyHorrJkBQYAAABQngIGAAAAUJ4CBgAAAFCeHhgTdgzXYx0i1+3XI0vTJEv1yNL4Fq9L3tZn7Lr9WmTp4nbZk2nhdWWpKLk6n130CFzxunpgAAAAANOkgAEAAACUp4ABAAAAlKeAAQAAAJR3aZ8vPmbjj7Ma9UyRRjOs67Rz5aIN4C6SrcXX2nVOZYjzmj93LnreLjsP1z3myXNPHr/JOT1m3mRpf6b62V/kvN/GMTeZj1Z95mNkaqp/nlPks17PeX9XW5yftvEamxyT7an2WVuBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJTXeu+jH/Suzzw4/kHhQNx0/Q1t3cfKEqwmSzCedfMkS3A6WYJxrMqSFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHmX9j2AKXjg/oc+pstXru5xJHA4TnIlU3AxsgTjkCWA+qzAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMo72Cae8403Tyw2ZVr2mPMc97TXWOc453nOeV4TzmOTnJyci2Nka5Pz+rzPPW2c6x7jl176rUmSf3zLO9d6PCTny8h5j32RLC0661jrzL2rnGTphExxEZs05NxGHiv8zmZ+YgybzCkXbYS77O9Hi8fcZbNd81JNVmAAAAAA5SlgAAAAAOUpYAAAAADlHWwPjGW2ec3xRV5jF+Na9Zr6ZzCmMc/lixzrIj0A4FDtY645zeK1xbANu+xvsWuLPS5kil3Y1e96i/ftIncyNA1WYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADl1ehCBAAAbEzjQeCYWIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJR3ad8DAI7bA/f7MQRjkCUYx0mWLl+5uueRwDQtzkeyxJiswAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKO9iOX8uaxYzR4OzkuMfcLO2s5laaXx2W0/4cjzkHu3BaluRs2tb9c5Ox08kBq5z1O8o6jun8ush7PabP6RjJEtVYgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUd1TdwTTgfMirX/ctSZJ/fMs7z32Mxc9xsTHPaZ+zJj6HQaZ2w+cL41iWJfMRZ5laA8KL/G4H6zrPf5hwDFma2nucIiswAAAAgPIUMAAAAIDyFDAAAACA8lxYfaRcHwnjkCWqq9pDRXaYmmpZkiGmqlqWTsjUNFiBAQAAAJSngAEAAACUp4ABAAAAlLdWAaO1dltr7eaFfb+2nSEBAAAAXGvdDipPTfLTrbVv6L3/98O+Z2xpTAA7dfnK1X0PAQ6OXAFwmpN5ompTT2pa9xKSB5N8e5IbW2tva609ZntDAgAAALjWugWM1nu/2nv/iSRvSvJ7SS5vb1gAAAAAD1l3vc4rT2703l/bWrszyYu2MyQAAACAa61VwOi9/+rC9+9L8iNbGREAAADAAh1TJkhjNBiHLHGMFs/7MZunyRTHZJtZgmOybO6Yap7Mg9u3bg8MAAAAgL1RwAAAAADKU8AAAAAAylPAAAAAAMqbZneUPbpoQ5nzNKmp1gzmrKZV1cbLYTnt/Jpqw6dVZIldmHKmNs2ITLFNx5SlsZ4Lq2iSyypWYAAAAADlKWAAAAAA5SlgAAAAAOW5mKiAk2u8ptpLYirjZPtWncvbfu6Yx4BKznNObyMHfs5zKDbJx5hZkiGq2sXfP8b8HQ+swAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKO8pOd9tscKY5DYdm/pxedY4u7q/SzBMqWCdDZ9lXM09ZYipOzvOqDQgBWWIcVmAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5emgMjLNaWAcssQh2majwVVkialazItzGHZnH/MVrMMKDAAAAKA8BQwAAACgPAUMAAAAoLzJXkzouqzd8VkfNn++AHA2vTiYqk36yax7fl/k90e/c3IRVmAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5ZXvQrRpI5kT+24Oo9ET1VTLyKJVzaBkianYZkPcTc7/s7IE1W3z570swbjWydQhNow/xPc0FVZgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOWV7Yp33uady/bvs7nKrhsQrttQRkPE47FORs5z/1jPqeqiWZp/nkZPh+GQzu+KZOl4+XMd1zo/q3zW0+b3/d3w+dVkBQYAAABQngIGAAAAUJ4CBgAAAFDeUVzYs4vrl/Z5/eYm78+1XJzltHNk1Xk+5nm16jV2ka1tvA+O13mydIgu+l5l6fBs2pvp2M+BY/p5wWbW6R001ms4/6jCCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvOPuirQFu2x0c+xNrRjXec6nfZyD28iYLDGmi5xP+5hDtvVacgXnJz9cxDYb4jo32TcrMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDydGHZsWWNbzZtoKZ5DvtW4RycH8N5mxBWeB9wml2coxfJkgyxiV2ez4vnctVzteq4YFH1+YjjYQUGAAAAUJ4CBgAAAFCeAgYAAABQngvvtmTVNZhjHBPOcmznyqZ5O7bPh4vZ5vlS7VxcN0vVxk1dx3SubHL9frXPZRu/tzK+aufNNk31nJzquKfECgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvFKdYI6pMc28Vc1eqnwemtCwT5s0Q6qeJdilxTyM0VhMlpiafZ2z5iMYx1lZqvb3lGrjOURWYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADl6SS0Zedp1qTBE4xDlpiqfZ+7qxqAwjG6SENc2YGHyBJjsAIDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE83lELGbE6zeKx1muMsOs9zYCyL5/Am+dDoCVabcpbMS6yr2rm7T+vkRrbgbHJSgxUYAAAAQHkKGAAAAEB5ChgAAABAeS4QPBJn9cQ4ud+1XXCtVdnYZL9rsdmn6uef+YepqnrunoynevZhKqpl/NhZgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp7sPSTSngbOs2wxtWZbkC76YBoNMzb7P2U2bhpp7qGoxS/vO1onFjMlQTVZgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOXV6JjCRk4aylRpeAMAcKz8PgZ1nJZHTTkPgxUYAAAAQHkKGAAAAEB5ChgAAABAeS7aA4AFrmlfj55MAMAuWYEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlNd67/seAwAAAMCprMAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAylPAmJjW2gtaa59qrb1/2F44d9+TW2vvaK19pLX2x621pwz7f7K1dndrrbfWHj/3+G9trf2HuWP97Nx9z2mtfWx43i1z+x/XWru1tfbx4etjV4xz6fOhih1m6d7W2p3D/vfO7ZclDsKYWRru+9bhOB9urf1vc/vNSxy0HWbJvMRBG/l3vH80d5wPtda+0Fp73HCfeWkfeu+2CW1JXpDkl1fc984kzx5uPzrJI4fbT0/ylCT3Jnn83OO/Ncm/XHKc65L8SZKvTPKIJB9I8rThvpcnuWW4fUuSl23yfJutyraLLA33XfPYuf2yZDuIbeQs3ZDkj5M8efj+8vDVvGQ7+G0XWRpum5dsB72NmaWF535Xkt8ZbpuX9rRZgbFFrbVfaK391Nz3v9hae/GWXutpSS713m9Nkt77Z3vvfzXcvqP3fu8Gh3tmkrt77/f03j+f5I1Jnjvc99wkrxtuvy7J92z4fNjYhLN0Glli5yaQpR9I8ube+yeGxz0w7DcvUcqEs3QaWWLnJpCleX8vyRuG2+alPVHA2K5XJ/mhJGmtPSzJ85O8fvFBrbV3zS1Nmt++Y8Vxv6+19sHW2m+21p407LspyYOttTe31u5orb2itXbdGmP82621D7TWfqu19jXDvq9I8qdzj/nksC9Jbuy9358kw9fLS4552vPhPKaapSTpSd7RWntfa+3H5vbLEvtQPUs3JXlsa+2dQ2b+wbDfvEQ1U81SYl6ilupZOnn9RyZ5TpI3DbvMS3tyad8DOGS993tba59urT09yY1J7ui9f3rJ4561wWHfluQNvffPtdZ+PLOq3rdl9mf5rMyWP30iyW9ktnzq1acc64+S/LXe+2dbazcneWuSr0rSlr2dDcZ40efDNSacpST55t77fa21y0luba19tPd++5pjlCVGNYEsXUryt5J8e5IvSfL7rbX3xLxEMVPNUu/9rpiXKGQCWTrxXUn+Te/9z4fvzUt7YgXG9r0qs2D8cJLXLHvAJhXF3vune++fG7799cwmp2RWtbtjWIZ0NbO/QH39aQPrvf9l7/2zw+23J3l4mzWt+WSSJ8099IlJ7htu/1lr7cow7itJli1JPO35cF5TzFJ67/cNXx9I8pbMlgwmssT+lM3S8Jzf7r3/x977v09ye5Kvi3mJmqaYJfMSFVXO0onn56HLR06OZV7ah16gEcchb5k1ZflYknuSXDfC8a7M3f7eJO8Zbl+XWfOXJwzf/5MkL1p47r25tsHTlyVpw+1nZlaJbJlVJ+9J8tQ81FTma4bHvSLXNqV5+ZIxrny+zXbebaJZelSS64f9j0ry7iTPGb6XJdtetuJZ+htJbhvO/Ucm+VCSv2leslXcJpol85Kt3FY5S8O+xyT58ySPmttnXtrX+bLvARzDluSVSV460rF+KcmHh5P8d5N89dx9z07ywSR3JnltkkcM+1+cWZXvamaVvVcN+39y7ljvSfJNc8e6OcldmXXH/Zm5/V86TIgfH74+btj/5UneftbzbbaLbFPLUmadpT8wbB+WJVuVrWqWhvv+UWb/e8KHkvy/5vabl2zltqllybxkq7oVz9ILkrxxyeuYl/awnfyLIVsyNKP5oyTP671/fN/jgamSJRiHLME4ZAnGIUtsQg+MLWqz/6rn7iS3CSOcnyzBOGQJxiFLMA5ZYlNWYAAAAADlWYEBAAAAlKeAAQAAAJR3aUvHdV0KrNY2eKwswWqyBONZN0+yBKeTJRjH0ixZgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlHdp3wNgOu76zIM7f82brr9h568Ju7LNTJ1k5+Q1Fr+f3weHYhuZkhOO0S7mJzgGsjQ+KzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8lrvfRvH3cpBGd8+GnPu2pgNbtb5vJY1S1y4v23wkrI0MYeYqX03iZKl4zblTO07O4tO+yw3yJMsTdhU8yRLVDPVLJ2okqnzZMkKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8TTwPwNSbyOzLac1rtvmZajxY17I/98XzRN42a/wkS8dr8c/+rPPmGLN1niZq2/qcNB48HMeYpRMVMiVL03HMWTnLRZp8jvW5auIJAAAATJYCBgAAAFCeAgYAAABQXtkeGGddO3PWdenz9591He7J/evu3zbXYx22bVy3f5FzZoweDyfH2FdmziJTh6lKls7TE6TKfLMuGTp8F71uf4xzpOr5PwYZOh7b7IGx6jwaIztV5yHZOV56YAAAAACTpYABAAAAlKeAAQAAAJSngAEAAACUt5Umnnd95sGtdAadssUmhxyvTRoPytJDZIhFsrSZMRr2crjWzZMsmY84nSydTYZYhyaeAAAAwGQpYAAAAADlKWAAAAAA5SlgAAAAAOVd2vcAjoUmNXAxMgQXI0MwDlmCi5EhLsIKDAAAAKA8BQwAAACgPAUMAAAAoDw9MI7UL730W6/5/h/f8s69jIPD8MD9sx8ll69c3fNIdk+WGNNJlk4cU6ZkCQA4ixUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHlH3cRzsVnaopPmacsed9HGats45joWm6TBmFZlaptZmj/uMTU85DisOrfHzNK+5iPYpvM0xD1rDtvkeTLEoVknU+v+3Wqd15AhVrECAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjvqJt4nuWsRjTbei4cmjHyIFMcszHmo9Oa6cKhOy0H52nSCcfuPLmQJcZgBQYAAABQngIGAAAAUJ4CBgAAAFCeC5GA0lwvCeOQJZADgKmzAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjv0r4HAByOy1euXvP9A/f7EQObkCHYPTkDmA4rMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyjrpr0WKztFWWNXda3LfuseAQrTr/12lIuKp5mkzBZk09D6UR4T++5Z37HgIHYNUccig5gV07yZQMsW9WYAAAAADlKWAAAAAA5SlgAAAAAOW5iGkkJ9eDTeW6fdcYU91UrrGUJRiHLLELruOHi9mkNxNsgxUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHm6royseiMbTdIAAACYIiswAAAAgPIUMAAAAIDyFDAAAACA8tYqYLTWbmut3byw79e2MyQAAACAa627AuOpSX66tfZzc/uesYXxHIzLV67m8pWr+x4GAAAAHIR1CxgPJvn2JDe21t7WWnvM9oYEAAAAcK11Cxit93619/4TSd6U5PeSXN7esAAAAAAecmnNx73y5Ebv/bWttTuTvGg7QwIAAAC41loFjN77ry58/74kP7KVER2YxT4YD9y/bs0ISB7K0El2lvWWkSs426osyQ9sRnZgHLLEefhvVAEAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDydExZw3zTwIs2mVnWgBCOxUWydFp25IpjMUYT28VjyA/HaIzf7WQHxiFLbMIKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKC8g2viedKIaVlzpm00iDk55kWbe0I1sgTTJEswDlmCs435nx1MyeJ71Yh0d6zAAAAAAMpTwAAAAADKU8AAAAAAyjvYC5V2fQ2W6yRhHLLEIdtmH5lFsgQs2uXPIDg05tMarMAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAytOJBDiVhkVwMetkSGO91eY/P5/PcXMunI95HDgkVmAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5R1lV59VzdLGaKKmqRTHRJZW02zueFVryFllHJvSePB4LWZII9zzkSE2IUNfTIZqsgIDAAAAKE8BAwAAAChPAQMAAAAob/IX9mzjeq1jut7ptPfqGjguSpY4Bhf5sz/ruefpBTBVh/zeWM95zgHnzUN8FpyH8+aL+UxqswIDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKK9Uh5L5himLDcvGaCi5jYYs22giOqZjagDH6efjuufqOufIMWZpFZk6TMvmo4sc46I2OdZUswS7tK+5Dg6NnLBrVmAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5ZXturLYEOasZpT7biCjaRqVnNaAcNW5uu8MnZAlqtlGZvaRN9li3xbP+4uci+fNUJW5DnZhm7/zydKMOXX3rMAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAyptc9xUNY2AzqzKzjSxtM58aELJvUzsHz2reNpX3weEbc+4Ys1HoWa8hQ0zFJhlb9VhZutYUx3worMAAAAAAylPAAAAAAMpTwAAAAADK01Aiu+mrMeVrvKASWWLfdtHrZRdkierGyMM2z/Nd9NsY2xTGyPnt4nzfRZa29ToXVXFMx8gKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKC8Ek08d9m0bNvOanCzTgMcjdWYmm1keN0snfYY4GzVs1RxTIxjH01rd/Ualc7bSmNhc+c5rw6h2bS/D7GKFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeYfTPfMc9tk8dFlDnkNqZspuHfu5o9ETYznELG3ynhYfK1Oc1yFmaRPmJbbhGHMlSyyyAgMAAAAoTwEDAAAAKE8BAwAAAChvrxdSHeN1XMv4HGAcla6TrDAGmDIZgouRIbgYGarJCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPN0jt6RSM8FNTG28HL6pNbmVIQD2yTwEFyNDtVmBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJQ3re54jE6TGrgYGYJxyBJcjAwBx8AKDAAAAKA8BQwAAACgPAUMAAAAoDw9MLbsgftrfMSL43CdJADAfp38fub3MhZV+TvEVMjS8bACAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPd5gJOU8jzpPHaAQED9HUlkV+Rp6PLLFIls5HljghQxcjS4fPCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPF1iAAA4l2oNB7/lpkcnSX7vrs/ueSSwnmoZguqswAAAAADKU8AAAAAAylPAAAAAAMprvfd9jwEAAADgVFZgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOUpYAAAAADlKWBMTGvtBa21T7XW3j9sL5y778mttXe01j7SWvvj1tpThv0/2Vq7u7XWW2uPn3v8P5o7zodaa19orT1uuO/e1tqdw33vnXvO41prt7bWPj58feyKcT6ntfax4XVv2doHAuc0cpYe01p7W2vtA621D7fWfnjuvqVZkCUOxQ6zZF7ioI2cpce21t7SWvtga+0PWmt/c+4+8xIHbYdZMi/tQ+/dNqEtyQuS/PKK+96Z5NnD7UcneeRw++lJnpLk3iSPX/Hc70ryO3PfL31skpcnuWW4fUuSly15zHVJ/iTJVyZ5RJIPJHnavj87m21+GzNLSf6/J1lI8oQkfz6c+yuzIEu2Q9l2kaXhe/OS7aC3kbP0iiQ/N9z+6iS3DbfNS7aD33aRpeF789IeNiswtqi19guttZ+a+/4XW2sv3tJrPS3Jpd77rUnSe/9s7/2vhtt39N7vPeMQfy/JG9Z4qecmed1w+3VJvmfJY56Z5O7e+z29988neePwPDiXCWSpJ7m+tdYymwz/PMnVnJ4FWWLnJpyl08gSOzeBLD0tyW3DYz6a5CmttRtjXqKYCWfpNLK0RQoY2/XqJD+UJK21hyV5fpLXLz6otfauuSVO89t3rDju9w3LmH6ztfakYd9NSR5srb25tXZHa+0VrbXr1hlka+2RSZ6T5E1zu3uSd7TW3tda+7G5/Tf23u9PkuHr5SWH/Iokfzr3/SeHfXBe1bP0y0n+RpL7ktyZ5Kd67/9nTs+CLLEPU81SYl6ilupZ+kCS/+cwhmcm+WtJnhjzEvVMNUuJeWkvLu17AIes935va+3TrbWnJ7kxyR29908vedyzNjjs25K8off+udbaj2dW1fu2zP4sn5XZ8qdPJPmNzJZPvXqNY35Xkn/Te//zuX3f3Hu/r7V2OcmtrbWP9t5vX3OMbcm+vuZz4YtMIEv/9yTvH57/1zPLzLty8SzIEqOaapZ6738Z8xKFTCBLL03yP7bW3p9ZMfCOzFYzmZcoZcJZSsxLe6GAsX2vyiwYX5bkNcseMPxF5/old72k9/6v53csBPrXk7xsuP3JzAJ/z3DMtyb5xqxXwHh+Fi4f6b3fN3x9oLX2lsyWOd2e5M9aa1d67/e31q4keWDJ8T6Z5Elz3z8xs39Ng4uonKUfTvLS3ntPcndr7X/P7DrJ07IgS+zLFLP0B+YlCiqbpaHo98PD41uS/33YHhnzEvVMMUv+vrQnChjb95YkP5/k4Ul+YNkDNqkonoRh+Pa7k3xkuP2HSR7bWntC7/1TmVUZ37vsGAvHe0yS/1uS/2Zu36OSPKz3/pnh9t8d3kOS/IvMlnm9dPj6z5cc9g+TfFVr7alJ/l1mBZKl7x02UDlLn0jy7Une1WbXRf5fktyT5MGszoIssS+Ty5J5iaLKZqm1dkOSvxqurX9hktt773/ZWjstC7LEvkwxS+alfekFOoke+pbklZn9i9IYx/qlJB/O7Hqs303y1XP3PTvJBzNb3vTaPNS5/cWZVfmuZlbZe9Xcc16Q5I0Lr/GVw/E/MLzWz8zd96WZNbL5+PD1ccP+L0/y9rnH3Zzkrsy66/7MGO/dZquapeH8f8fw+A8l+W/mjrU0C7Jk2+c2tSyZl2xVt8JZ+ttDJj6a5M1JHjt3LPOSrdw2tSyZl/a3teHDY0uGZjR/lOR5vfeP73s8MFWyBOOQJRiHLME4ZIlN+F9ItqjN/queuzP7/4KFEc5JlmAcsgTjkCUYhyyxKSswAAAAgPKswAAAAADKU8AAAAAAytvWf6PquhRYrW3wWFmC1WQJxrNunmQJTidLMI6lWbICAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAo79K+B8B03fWZB7d27Juuv2Frx4ZqZAnGsY0syRDHZJvz0QmZ4hjI0vZYgQEAAACUp4ABAAAAlKeAAQAAAJTXeu/bOO5WDsr27eJ6rW2rcj3Yqs/yputvaBscRpYmSpYu7uQzPBnH4mcqS8fhELJ0Yt+ZOrHsM90gT7I0YYeUp6ROphbI0hGYapaKZmaVpVmyAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTxPPAzfVBjPbtKoh4LLHrHKRz1XjwWmTqfWs2yRKlpCp023acO28n6cmnodDppYbo3nhOp+tLB0OWVpuG41AN2kubQUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUN7BNvFc0Qhk5+NYRVOY4zXlxoMn522lLJ1Gzg7bFLM0tQwtkqnDVbnx4EWablclS3Ws09x9w+OVzdIhk6n9Oc/P4Ys0xLUCAwAAAChPAQMAAAAoTwEDAAAAKG8rPTDu+syDW7+ma/Fam31f9zT29XMcrk2u259alh64/9I131++cvXc4xhjPBy2alka02KWFq2TrVXZNl+xzKbX7Vc/f87K0Lyz8rTu9d3VPxN246I9MKqcR+tmaJPf9U5s0jOhyufB7umBAQAAAEyWAgYAAABQngIGAAAAUJ4CBgAAAFDe+h2OiqnW0KXaeGBdVc7dKuOAis7TJG1VpmSNi5j6+TNmluAiqp9XJ1lZ1czzPFk6Uf29U5sVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHmX9j2ACh64/9qP4fKVq6fev+wx677Gps+DKTk5v0/O92XZWXzsiXUzIkscslWZOWueWvZYGeEYnTbvrHN/Ijuwjk1+x4MxWYEBAAAAlKeAAQAAAJSngAEAAACUpwfGEutcH7nOY4DNyRaMY90srXOt8iY9OOBQrOonc5E+GnrUMBUX+X1s0/P8Iv00zE/HxwoMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDzd8gAAYIVtNJfWzJNjokE7Y7ICAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjv0r4HABynB+6f/fi5fOXqnkcC03OSH2B88gXjkCW2wQoMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDydVfLFTQQ1nIGLOcnUOlmSNwAAYB1WYAAAAADlKWAAAAAA5SlgAAAAAOW5+HyJTa7fB4CxLPZkOmE+gvWsytAJWYL1mI+oygoMAAAAoDwFDAAAAKA8BQwAAACgvLUKGK2121prNy/s+7XtDAkAAADgWuuuwHhqkp9urf3c3L5nbGE8AAAAHIjLV66e2WB3Cq9BDesWMB5M8u1Jbmytva219pjtDQkAAADgWusWMFrv/Wrv/SeSvCnJ7yW5vL1hAQAAADxk3f/I95UnN3rvr22t3ZnkRdsZEgAAAMC11ipg9N5/deH79yX5ka2MCAAAAGDBuiswAIAjpTEax2zV+f/A/Zv/Gi1LHLOzzn+ZYh3r9sAAAAAA2BsFDAAAAKA8BQwAAACgPD0wtuQQrsc6uQ7tEN4L03UI558sUYHzD053kpF1r8OXKVhONtgmKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8jTxPMWmzZwOwTG9V9imZVnSzBM2N58l2WEXjvH3PzgvP5fZNSswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPJ0JyKJRlVsxzE2Qjum98ruyBKM4xizBGPaVYY0B2UVKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8nQwOnKaWME4ZAkuRoYAgLNYgQEAAACUp4ABAAAAlKeAAQAAAJTngtMj4xpjGIcsAQDAblmBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJR3sF3o5hvsXb5ydY8jqUHDQc5rnSydPOYYsiZLbNMxZQm2QYYADpsVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5utEBo9E8Dc5nsTmsLC3nc2GVbWbokM67xc/pEN4T27GqaflFzplDyhL7YwUGAAAAUJ4CBgAAAFCeAgYAAABQ3mR7YCxeQ7XqOq1ljz3rccy4Pu24LcuDaxfXN/8Z+dzg/JZlicNw1u9yu+5f4fxi6sbI0Fk5WNVvZtnrXuT3H787sYoVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB55bsVTbWBy1THPbXxMnORpk2bNMQ973iOiQwdvlU/37fRLFCWOAa7OM/HnNucmxyiMXO4aSNQ2IQVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5e+2gcpHGg2O83i5ed9fv8byqjovlztP8aKrNx/aRW47HOllada5NrQnZIWRpSmM9NhfJ0rZfd1evOaXzc0pjPVbLzrOpZkgTXcZkBQYAAABQngIGAAAAUJ4CBgAAAFDeXi7gXXUd1Pz+xeubtnnd0y6vn1z2PlzTxdhOy9I6z1n3sfs8Z3d1bei6Tntt2Z62Tc/3Q+iNUTVLTNum2ZCl8VUbD5s5byYq/N52XlP7OcD2WYEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlFe2K8o6jT5Pe1x1VcY9xWY+bGabmalyHsMuON+3y3wEMK5D+XsTzLMCAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPJ5cjpVkaXIwMAQDAblmBAQAAAJSngAEAAACUp4ABAAAAlKcHxpFwvT6MQ5YAAGA/rMAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAytPEE4Cj88D9pj+4CBmCi5EhOB8rMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDydto9RrOa8zn53C5fubrnkbAvsjMOWTpeMgTjkCUA9skKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKC8rXRi0uBpOxY/V40ID58sbcc6n6t8wfpOy5QscehOzvEx5mxZ4pg5x1mHFRgAAABAeQoYAAAAQHkKGAAAAEB5LrAHJmn+Okm9QuD8XHMM45AlgO2zAgMAAAAoTwEDAAAAKE8BAwAAACiv9d73PQYAAACAU1mBAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4AxMa21F7TWPtVae/+wvXDuvie31t7RWvtIa+2PW2tPGfa/vrX2sdbah1prr2mtPXzY31pr/1Nr7e7W2gdba18/d6znDM+5u7V2y9z+x7XWbm2tfXz4+tgV41z6fKhih1m6t7V25/Aa753bL0schJGz9NWttd9vrX2utfaShdcxL3HQdpgl8xIHbeQs/f3hd7sPttbe3Vr7urljmZf2ofdum9CW5AVJfnnFfe9M8uzh9qOTPHK4fXOSNmxvSPIP5/b/1rD/G5P822H/dUn+JMlXJnlEkg8kedpw38uT3DLcviXJy5aMY+XzbbYq2y6yNNx3b5LHL3kNWbIdxDZyli4n+YYkv5jkJXPHMS/ZDn7bRZaG+8xLtoPeRs7SNyV57HD7O+PvS3vfrMDYotbaL7TWfmru+19srb14S6/1tCSXeu+3Jknv/bO9978abr+9D5L8QZInDk97bpL/ZbjrPUluaK1dSfLMJHf33u/pvX8+yRuHx54853XD7dcl+Z4lwznt+bCxCWfpNLLEzlXPUu/9gd77Hyb5zwuHMy9RyoSzdBpZYucmkKV3997/YjjEe/LQ737mpT1RwNiuVyf5oSRprT0syfOTvH7xQa21d80tcZrfvmPFcb9vWMb0m621Jw37bkryYGvtza21O1prr2itXbfwOg9P8oNJfnvY9RVJ/nTuIZ8c9q3anyQ39t7vT5Lh6+Ul4zvt+XAeU81SkvQk72itva+19mNzj5El9qF6llYxL1HNVLOUmJeoZUpZ+tHMVtwm5qW9ubTvARyy3vu9rbVPt9aenuTGJHf03j+95HHP2uCwb0vyht7751prP55ZVe/bMvuzfFaSpyf5RJLfyGz51KvnnvsrSW7vvb9r+L4tG/Yp+9d10efDNSacpST55t77fa21y0luba19tPd++5pjlCVGNYEsrWJeopQJZykxL1HIVLLUWvs7mRUwvuVk17K3s8EYZemcFDC271WZBePLkrxm2QNaa+9Kcv2Su17Se//X8zsWAv3rSV423P5kZoG/ZzjmWzO7Fv/Vw/c/l+QJSf7bued/MsmT5r5/YpL7MrsOa9n+JPmz1tqV3vv9wxL5B5aMe9Vx4SKmmKX03k++PtBae0tmSwZvjyyxP5WztMppWZAl9mWKWTIvUVHpLLXWvnYY43fOHdu8tC+9QCOOQ94yKwZ8LMk9Sa4b4XhX5m5/b5L3DLevy6z5yxOG7/9JkhcNt1+Y5N1JvmThWP+PXNt48A+G/ZeG8T41DzWV+Zrhvlfk2qY0L18yxpXPt9nOu000S49Kcv3c7Xcnec7wvSzZ9rJVztLccf5/ubaJp3nJVm6baJbMS7ZyW+UsJXlykruTfNPCfvPSvs6XfQ/gGLYkr0zy0pGO9UtJPjyc5L+b5Kvn7nt2kg8muTPJa5M8Yth/NbMut+8ftp8d9rck//Nw351JnjF3rJuT3DXc9zNz+780yW1JPj58fdyw/8uTvP2s59tsF9mmlqXMOkt/YNg+LEu2KlvhLH1ZZv8q9ZdJHhxu/xfDfeYlW7ltalkyL9mqboWz9KokfzG3/71zxzIv7WFrw4fHlgzNaP4oyfN67x/f93hgqmQJxiFLMA5ZgnHIEpvwv5BsUZv9Vz13J7lNGOH8ZAnGIUswDlmCccgSm7ICAwAAACjPCgwAAACgPAUMAAAAoLxLWzqu61JgtbbBY2UJVpMlGM+6eZIlOJ0swTiWZskKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvEv7HgDTc9dnHtz6a9x0/Q1bfw3YN1mCcWwzSzLEMdlGlmSIYyJD22cFBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFBe671v47hbOSjbs4tmgtu22ODm5D0VbHzTNnisLE3MIWTpxEl2Ft9ToUzJ0gE7pCydpUim1s2TLE3MMWVp3h5zJUsHSpZ2bmmWrMAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAytPE80gdaxOadW25WY3GgwdElk4nS5xFhjazxUxpPDhxsjSOETImSxMlQ+PaVpaswAAAAADKU8AAAAAAylPAAAAAAMrTA2PCXKe1O+e5hmvVn89N19/guv2iZGp3xsiULE2DXO3WBa45dt3+RMjU7m2YK1maCFnanzUzpQcGAAAAME0KGAAAAEB5ChgAAABAeQoYAAAAQHk7aeJZrUHKA/dfOvX+y1euXvg1Nmn2U+3zYbs2aTx412cenESDp1WZGiNLJ2TqsJ325ztGQ9ypZmnMDC2SqeOx+Ge97M9z3Tytm6Vl59c+zqOTcez6tc/Kl0xN22mZGjtLy173vOfPRXK5zs+RbZClw3bGn68mngAAAMA0KWAAAAAA5SlgAAAAAOUpYAAAAADlbaWJp2ZpsNohNh48cZIpWWIXZAnGs83Gg3BMZAnGsSpLVmAAAAAA5SlgAAAAAOUpYAAAAADlXTr7IQDALul9AQDwxazAAAAAAMpTwAAAAADKU8AAAAAAylPAAAAAAMrTxHPOA/cv/zg0U4PzOcmUDMHFyBJsZjEzi7/jyRKsR3aoxgoMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoLyjbOK5qlnnJo9ft4HNRRqDbjrOdY8LY1l1jm6y/6JZmj/GeTKzyRhgW8577s4/d9Pz+LQ8ntUAcRVZYt8Wz9VNsjVms9yzjnXWuGSJfTvrd7ll5+guM7Tt51OXFRgAAABAeQoYAAAAQHkKGAAAAEB5R9kDYwwXuV4ZeIgswTi2kSX55BiNed7LEMdIhtgmKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8i7tewDA4Xvgfj9qAKhjfl66fOXqHkcC0+R3O/bFCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPN1XgHM7aXymkRPshqzB6RYbcq6TGbmCL3aeLMEuWIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlHeU3Vg0pQGgEvMSAMDZrMAAAAAAylPAAAAAAMpbq4DRWruttXbzwr5f286QAAAAAK617gqMpyb56dbaz83te8YWxgMAAADwRdYtYDyY5NuT3Nhae1tr7THbG9K0XL5y9Yuar8GxGSMHu8iSvHIMnOcwDlkCqGfdAkbrvV/tvf9Ekjcl+b0kl7c3LAAAAICHrPv/tL3y5Ebv/bWttTuTvGg7QwIAAAC41loFjN77ry58/74kP7KVEQEAAAAsWHcFBmc46xrJB+7f/KN23SXHaNV5P2aGZItjMOa8JDMcs8Xz3+90sD+yxLo9MAAAAAD2RgEDAAAAKE8BAwAAAChPAQMAAAAoTxNPYBLWadqksROs77S8yBJTd55Gm+clLzA+uWIVKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8jTxPMVpzWN22RwKAAAAjp0VGAAAAEB5ChgAAABAeQoYAAAAQHkaOeShXheb9LU4rT8GsNyy3OgnA+s7z3wFfLH5+Uie4PxkiV2zAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoT6cVYK80xIXNaZoGABwjKzAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8nT+uqCT5mkaEQKwDyfzj2aecL4cLGbI73QAdVmBAQAAAJSngAEAAACUp4ABAAAAlOeCWaAE1x5zzMY8/2WJY6QHDIzrPHOJnkzsghUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHlH2WFlG41lNE3jmI2ZKVnimCxmR5agjsU8yhLHSENOqrECAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAACjvqLqybNqERgM0WG4XDZ3kD77YeXKhESF8sflcrJsJzQwB9s8KDAAAAKA8BQwAAACgPAUMAAAAoLzJX8y3zvXAF71mcdnzV72e6yM5ZGNm6bzXHLt+Hy5GpmBcm/yeCIfmPL/bbXrcebKFFRgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeeU7Tp632di2m2nusjEo7MJiQ9xdZWjT836dcckSlWyjwdmYxzwtU7IE56NZLsB2WIEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlFeiied5mgWues62Gw9CZes04ztv88xtkVm4GBmCi5EheIg8UJ0VGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5k+vSorEMjEMjXACmzpwFdcgju2AFBgAAAFCeAgYAAABQngIGAAAAUJ4LlQBgR1wfDOPYZpbklGPkvGcqrMAAAAAAylPAAAAAAMpTwAAAAADKU8AAAAAAyjuYbi0azwAAHC6/68H45IqpsQIDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKG8rXVs0g4F6jjGXJ+/58pWrex4J+7bLc8F5B8stZmPdrBzj/AXLrJuFQ86UORYrMAAAAIDyFDAAAACA8hQwAAAAgPKmewHUAXJNF6usulbRubLclK/tZLvOk6WzzqdVzz2E89C8xKJV58Qm58piNg4hK6ts2u8DxjhXDjlTYAUGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4OLztynqZW4Jz4YhdptnjW8zRX4zymntNl5/1Fs3TW8Zm+qZ/32+a85ywyBOdjBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUF7rve97DAAAAACnsgIDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BY2Jaay9orX2qtfb+YXvh3H1Pbq29o7X2kdbaH7fWnjLsf31r7WOttQ+11l7TWnv4sP/vt9Y+OGzvbq193dyx7m2t3Tm8xnvn9j+utXZra+3jw9fHrhjnc4bXvLu1dsvWPhA4p5Gz9NwhR+9vrb23tfYtc8damgVZ4lDsMEvmJQ7amFmae943tNa+0Fr7/rl95iUO2g6zZF7ah967bUJbkhck+eUV970zybOH249O8sjh9s1J2rC9Ick/HPZ/U5LHDre/M8m/nTvWvUkev+Q1Xp7kluH2LUletuQx1yX5kyRfmeQRST6Q5Gn7/uxstvlt5Cw9Okkbbn9tko8Ot1dmQZZsh7LtIkvD9+Yl20FvY2ZpuO+6JL+T5O1Jvn9un3nJdtDbLrI07Dcv7WGzAmOLWmu/0Fr7qbnvf7G19uItvdbTklzqvd+aJL33z/be/2q4/fY+SPIHSZ447H937/0vhkO852T/GZ6b5HXD7dcl+Z4lj3lmkrt77/f03j+f5I3D8+BcJpClzw77kuRRSU5un5YFWWLnJpyl08gSO1c9S4P/Lsmbkjwwt8+8RCkTztJpZGmLFDC269VJfihJWmsPS/L8JK9ffFBr7V1zS5zmt+9YcdzvG5bY/mZr7UnDvpuSPNhae3Nr7Y7W2itaa9ctvM7Dk/xgkt9ecswfTfJbc9/3JO9orb2vtfZjc/tv7L3fnyTD18tLjvUVSf507vtPDvvgvMpnqbX2va21jyb5X5P8yLD7tCzIEvsw1Swl5iVqKZ2l1tpXJPneJK9cOL55iWqmmqXEvLQXl/Y9gEPWe7+3tfbp1trTk9yY5I7e+6eXPO5ZGxz2bUne0Hv/XGvtxzOr6n1bZn+Wz0ry9CSfSPIbmS2fevXcc38lye2993fNH7C19ncyK2B8y9zub+6939dau5zk1tbaR3vvt685xrZk3zr/igZLTSFLvfe3JHlLa+2/SvILSb4jF8+CLDGqCWcpMS9RyASy9D8k+ene+xdau+b0Ny9RyoSzlJiX9kIBY/telVkwvizJa5Y9oLX2riTXL7nrJb33fz2/YyHQv57kZcPtT2YW+HuGY741yTdmCGRr7eeSPCHJf7vw2l87jPE754/de79v+PpAa+0tmS1zuj3Jn7XWrvTe72+tXcnypVSfTPKkue+fmOS+Ze8dNlA6S3PHvb219tdba4/P6VmQJfZlclnqvf978xIFVc7SM5K8cfgL1+OT3NxauxrzEjVNLku997eal/akF2jEcchbZk1ZPpbkniTXjXC8K3O3vzfJe4bb12XW/OUJw/f/JMmLhtsvTPLuJF+ycKwnJ7k7yTct7H9Ukuvnbr87yXOG71+Ra5vSvHzJGC8N7/epeagpzdfs+8/CNu2teJb+yzzUePDrk/y7zCrrK7MgS7Z9bRPNknnJVm6rnKWF4742DzXxNC/Zym0TzZJ5aU+bFRhb1nv/fGvtd5M82Hv/wgiHfHFr7buTXE3y55lVK9Nny5pekuS2NisRvi+zimMyu2br/0jy+0P18M29959P8rNJvjTJrwz7r/ben5HZ8q23DPsuJfmnvfeT65NfmuSftdZ+NLOlV89Lktbalyd5Ve/95t771dbaTyb5V5n9oHhN7/3DI7x3jljxLH1fkn/QWvvPSf5Tkv+6z2an07IgS+zFFLPUWjMvUU7xLK0as3mJcqaYpfj70t6c/CsHW9JmzWj+KMnzeu8f3/d4YKpkCcYhSzAOWYJxyBKb8L+QbFGb/Vc9dye5TRjh/GQJxiFLMA5ZgnHIEpuyAgMAAAAozwoMAAAAoDwFDAAAAKA8BQwAAACgvG39N6oaa8BqbYPHyhKsJkswnnXzJEtwOlmCcSzNkhUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5l/Y9AKbjrs88ONqxbrr+htGOBVNzkSzJDnyxszIlN7CeVVmSIaAKKzAAAACA8hQwAAAAgPIUMAAAAIDyWu99G8fdykEZ35h9LaZmj9dztg0eK0sTIUt7IUsH6JizNG8PuVo3T7I0EbJ0rR1mSpYOjCxda99ZsgIDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8TzyOh+cy4Lti8RuPBCZKhcY3UAEqWJkiWxjViMzWNBydGlsYlS8dHhrZj21myAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTxPPA6MZzf6t0bhG48Gi5Gf/Nmz8JEuFydN+XKB5msaDRcnS/m1pbpKlHZCfmtbMlCaeAAAAwDQpYAAAAADlKWAAAAAA5W2lB8Zdn3lwa9d0XeDazo1t85qp87wP13BN08mf9cmf303X37D2dfvnzdIuczK2dc/zi7xHWToMm2Qpw7XGi3/2q86jZefIVHO16nyXIeZtkKdrsrTJeXSe5xw6WTo8m2aJi5Ghw7UqS1ZgAAAAAOUpYAAAAADlKWAAAAAA5SlgAAAAAOVNroknTN0umnjCMZAlGM+6eZIlOJ0swTg08QQAAAAmSwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTwEDAAAAKO/SvgewDw/cf+3bvnzl6p5GAgAAAKzDCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgvKNs4rnopKmnZp6wmcWGuCeqZUnjXqrbZ5bmX3vx9aaScThR7ef9qgyd2Pf4YJVqfz+SJU5YgQEAAACUp4ABAAAAlKeAAQAAAJSngAEAAACUp4nnGs5qGrMrmtMwdac1C1z2GODiNsmU/HFottHUU044JrtonilTbMIKDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8HVOAvThp2HTS/EkDJxiXTMF6zmr0KUuw2jr58LseY7ICAwAAAChPAQMAAAAoTwEDAAAAKM+FSAAwYfrJwLhkCMYlU4zJCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPB1V5iw2mDlpiAZsRpYAAICxWYEBAAAAlKeAAQAAAJSngAEAAACUp4ABAAAAlHeUTTwXGwouNhw8az8wM0aW5AxWW5WPZY1xZQkAOHRWYAAAAADlKWAAAAAA5SlgAAAAAOW5YHYN89cau8YYgLGdzDPrzjHmIljurN5MsgPr2XRegl2xAgMAAAAoTwEDAAAAKE8BAwAAAChvrQJGa+221trNC/t+bTtDAgAAALjWuiswnprkp1trPze37xlbGM/kXL5y9YsaRgEAAADjWreA8WCSb09yY2vtba21x2xvSAAAAADXWreA0XrvV3vvP5HkTUl+L8nl7Q0LAAAA4CHr/se+rzy50Xt/bWvtziQv2s6QAAAAAK61VgGj9/6rC9+/L8mPbGVEAAAAAAvWXYHBGU4aeT5w//k/Us1AQZZgLIs5OE+mZAkuNi/JEMfkrKzIEmNYtwcGAAAAwN4oYAAAAADlKWAAAAAA5emBsWOu34KLkSEYhyzBZs7qKyNTsJ5NejTJFYuswAAAAADKU8AAAAAAylPAAAAAAMpTwAAAAADK08QTAADOSZNBGIcssQ4rMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAoIjLV65qYgYAsIICBgAAAFCeAgYAAABQngIGAAAAUN6lfQ+gMtchAwAAx+rk70MP3O+vjdRgBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQngIGAAAAUJ4CBgAAAFDepX0PYKouX7m67yHAQTjJ0gP3+3EEF2FeAgAOnRUYAAAAQHkKGAAAAEB5ChgAAABAeQoYAAAAQHlH2TVv02aBpz3+5D7N0wAAps/vdAB1WYEBAAAAlKeAAQAAAJSngAEAAACUd5Q9MLZh074acEjGPP9lCcYhSwDsk34ybIMVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5OnwVcNJoTaMbONs6jQlliamq0njTvARfrEo+oSpzB7tgBQYAAABQngIGAAAAUJ4CBgAAAFCeAgYAAABQnm5Ep9hGsyYNoACowHwE41qWKc0MAcZlBQYAAABQngIGAAAAUJ4CBgAAAFCeC2ABAADYC71i2IQVGAAAAEB5ChgAAABAeQoYAAAAQHkKGAAAAEB5R9XE84H7j+rtAgAAwMGwAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoT1dLYGMa4sK4ZAoA4GxWYAAAAADlKWAAAAAA5SlgAAAAAOUdxUW3ri2GccgSjEumYByyBONYzNLlK1f3NBJYzgoMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoLwSHY82aby0biOZbTdz0iyKypadn1WbMMkSx2ib571McUyc77BdMkY1VmAAAAAA5SlgAAAAAOUpYAAAAADlKWAAAAAA5e20K8tiE5jzNBXUSAYeskkeNs3OST5ljmO3KgOLc9g6j9O8k2M2xu+BuzCVccLJuTrGOWoOYSqswAAAAADKU8AAAAAAylPAAAAAAMrbycVOrqmCcewyS3LLIRvj/F73GLLEMVm8Jv+083/V9fvVMlNtPLB4Tm6apW33ZtJHhm2yAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAobytdiTQ7Otu2m+dwGJwbm9EkirPIFIzjrCxtkjW5hMNuLr1OM1FYlxUYAAAAQHkKGAAAAEB5ChgAAABAea33vu8xAAAAAJzKCgwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFDAAAAKA8BQwAAACgPAUMAAAAoDwFjIlprb2gtfap1tr7h+2Fc/c9ubX2jtbaR1prf9xae8qw//WttY+11j7UWntNa+3hw/5vba39h7lj/ezcsZ4zPOfu1totc/sf11q7tbX28eHrY1eMc+nzoYodZune1tqdw/73zu2XJQ7CmFka7vvW4Tgfbq39b3P7zUsctB1mybzEQRv5d7x/NHecD7XWvtBae9xwn3lpH3rvtgltSV6Q5JdX3PfOJM8ebj86ySOH2zcnacP2hiT/cNj/rUn+5ZLjXJfkT5J8ZZJHJPlAkqcN9708yS3D7VuSvGyT59tsVbZdZGm4794kj1+yX5ZsB7GNnKUbkvxxkicP318evpqXbAe/7SJLw23zku2gtzGztPDc70ryO8Nt89KeNiswtqi19guttZ+a+/4XW2sv3tJrPS3Jpd77rUnSe/9s7/2vhttv74Mkf5DkiWcc7plJ7u6939N7/3ySNyZ57nDfc5O8brj9uiTfs+HzYWMTztJpZImdm0CWfiDJm3vvnxge98Cw37xEKRPO0mlkiZ2bQJbm/b3MihuJeWlvFDC269VJfihJWmsPS/L8JK9ffFBr7V1zS5Pmt+9Ycdzva619sLX2m621Jw37bkryYGvtza21O1prr2itXbfwOg9P8oNJfntu999urX2gtfZbrbWvGfZ9RZI/nXvMJ4d9SXJj7/3+JBm+Xl4yvtOeD+cx1SwlSU/yjtba+1prPza3X5bYh+pZuinJY1tr7xwy8w+G/eYlqplqlhLzErVUz9LJ/kcmeU6SNw27zEt7cmnfAzhkvfd7W2ufbq09PcmNSe7ovX96yeOetcFh35bkDb33z7XWfjyzqt63ZfZn+awkT0/yiSS/kdnyqVfPPfdXktzee3/X8P0fJflrvffPttZuTvLWJF+V2dKpLxrmBmO86PPhGhPOUpJ8c+/9vtba5SS3ttY+2nu/fc0xyhKjmkCWLiX5W0m+PcmXJPn91tp7Yl6imKlmqfd+V8xLFDKBLJ34riT/pvf+58P35qU9sQJj+16VWTB+OMlrlj1gk4pi7/3TvffPDd/+emaTUzKr2t0xLEO6mtlfoL5+7jV+LskTkvy/5471l733zw63357k4a21xw/HOqlUJrMlVPcNt/+stXZlOOaVJMuWJJ72fDivKWYpvff7hq8PJHlLZksGE1lif8pmaXjOb/fe/2Pv/d8nuT3J18W8RE1TzJJ5iYoqZ+nE8/PQ5SMnxzIv7UMv0IjjkLfMmrJ8LMk9Sa4b4XhX5m5/b5L3DLevy6z5yxOG7/9JkhcNt1+Y5N1JvmThWF+WpA23n5lZJbJlVp28J8lT81BTma8ZHveKXNuU5uVLxrjy+TbbebeJZulRSa4f9j9qeO5zhu9lybaXrXiW/kaS24Zz/5FJPpTkb5qXbBW3iWbJvGQrt1XO0nDfY5L8eZJHze0zL+1pcwnJlvXeP99a+90kD/bevzDCIV/cWvvuJFczC9ILhtf5QmvtJUlua621JO/LrOKYJK9M8n9ktnwwmTV1+vkk35/kH7bWrib5T0me32eJutpa+8kk/yqzoL+m9/7h4VgvTfLPWms/mtlf0p6XJK21L0/yqt77zb33054P5zLFLLXWbkzyluGxl5L80977yTWVssReVM5S7/0jrbXfTvLBJP9nZln4UJKYl6hmillqrX1lzEsUUzlLw33fm+Qdvff/ODdmf1/ak5N/MWRL2qwZzR8leV7v/eP7Hg9MlSzBOGQJxiFLMA5ZYhN6YGxRm/1XPXcnuU0Y4fxkCcYhSzAOWYJxyBKbsgIDAAAAKM8KDAAAAKA8BQwAAACgvG39LySuS4HV2gaPlSVYTZZgPOvmSZbgdLIE41iaJSswAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyFDAAAACA8hQwAAAAgPIu7XsA7Mddn3lw30Mo7abrb9j3EJiYXWVq1blZPdMyxbpkaT0yxaJ9n7tTzZQscWJf5+riOVg9M6vsKktWYAAAAADlKWAAAAAA5SlgAAAAAOW13vs2jruVg7K+qV47NTXnvNarbfBYWdozWdqtDTMlS8XISx3nmJ/WzZMs7Yl81bMiZ7JUnCzVtZCppVmyAgMAAAAoTwEDAAAAKE8BAwAAAChPAQMAAAAoTxPPCdFw5jDcdP0NGg/uiQwdFlnaH1k6PBvkSZYuQHYOnyyN6yQziw1TF/fL1uFZlSUrMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAAIDyLu17AKymGQ1cjAzB2eQEzkd24GI2ydCqx8rh8bECAwAAAChPAQMAAAAoTwEDAAAAKE8BAwAAAChvK008NVOBcazK0k3X33Dq/Yfg5D2ucsjvnfGte76cdt5VPefOysqJquNnWs6al8Y49i7muHXGKzNs0+L5NWaGdkGG2BcrMAAAAIDyFDAAAACA8hQwAAAAgPK20gMD2K5juKbwGN4j9UzxvJvimDk8Y56Huzin5YZqpnZOTm28HA4rMAAAAIDyFDAAAACA8hQwAAAAgPIUMAAAgP9/e3fsI1d1RwH4d80qMiIIaYuJpqSnxA2VRTrK/AEpUibpU1FERMq/AFRUiCYUINEFUSCaKE2iFPSRVtrCShlFAzeFM8E78nhnZ+/wzpv3fZXX3uLK845nfPzeMUA8BQZwdq6vLur6ykYxAACcEwUGAAAAEE+BAQAAAMRTYAAAAADxFBgAAABAvEWu3G3H/VbrzcQneWrf2GDK+WDX7jU79bVqsBOO96L8TJ1tuK+09yuYK1kihTswAAAAgHgKDAAAACCeAgMAAACIt+gHxw/dwnj2ma+7Pu/l2XyW4LYsjXjGXpY4RyOv67u8lx3y/TAH+67rfdka+X4kQ5yTfdf1KbMEx3AHBgAAABBPgQEAAADEU2AAAAAA8RQYAAAAQDyreHW3EbW7jkXBkhyTA9mBMbw/wf2u99uGbmWJJRhxnd82CHrOI5+/ePedG19/+t4XE53kfLkDAwAAAIinwAAAAADiKTAAAACAeAoMAAAAIJ41onsy6ARAIu9PMIYswXGWmB2jnafnDgwAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAg3iILjNV6U6v1ZupjAAAAAAdaZIEBAAAAzIsCAwAAAIh3UIHRWvtza+2dnZ/78DRHAgAAALjp4sDve72qftdae9R7//3/fu7NE50JCLe7IXN9degfJcCztlmSIbifU2RJLmEM73WMdOgjJP+qqp9X1c9aa5+31l473ZEAAAAAbjq0wGi9903v/ddV9aeq+rqqVqc7FgAAAMAPDr2P5/3tD3rvH7XW/l5VvznNkQAAAABuOqjA6L1/sPP1X6vqVyc5EQAAAMAOSyqD3GecZncQETiOLMEY+4Z6ZYw0c7kmZYh0pxja3L3eXf+McOgGBgAAAMBkFBgAAABAPAUGAAAAEE+BAQAAAMQz4jnYvuGz274PuOkuY1LyBPvdlqVD8nPx7X+qqurJt8//9cvH/j0EXkSGYKwnX31fVbKzRF5xAAAAIJ4CAwAAAIinwAAAAADiKTAAAACAeEY8fyRGBuE4sgNjyBLczykztB0k3DJMCIfZzc4uWTo/XlEAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAABqtd7Uar2Z+hiwlwIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAgngIDACaWPpp2+fhBXT72kYF86VmCuUjPkvel5fKqAwAAAPEUGAAAAEA8BQYAAAAQ72LqAwAA8+B5YzjObdl58tX3P9JJAObNJxEAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAJjQ5eMHRnLhCLKzPF5tAAAAIJ4CAwAAAIinwAAAAADiKTAAAACAeBdTHwAAAChjhDCILJ0vrywAAAAQT4EBAAAAxFNgAAAAAPFsYNzRar258fX1ld9CuI/dTAH3I1MwxjZLPutBPpsXy+GVBgAAAOIpMAAAAIB4CgwAAAAgngIDAAAAiGeVCADOgPFOGGM3S7LFEhmvJZU7MAAAAIB4CgwAAAAgngIDAAAAiKfAAAAAAOJZZzkxw08AAGNtBwZ9zgJYFndgAAAAAPEUGAAAAEA8BQYAAAAQT4EBAACwQNdXF//flIE5UGAAAAAA8RQYAAAAQDwFBgAAABBPgQEAAADEs9gCAEA8Q4MAuAMDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAg3iLXkIxAAQDM3/Yz3Wq9mfgkMB/+LsScuQMDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAg3iIWXAzVwBiyBGPIEgBJvC8xF+7AAAAAAOIpMAAAAIB4CgwAAAAgXuzDTtvnsFbrzcQnAYAxPGMMpyFbAMvgDgwAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4UYtHzxtg2jfmaawJ9ntRPmQJjrObFVmC07gta8BhZIlz5A4MAAAAIJ4CAwAAAIinwAAAAADiKTAAAACAeJMsju0Ocx4yfJYyjpZyDnjWXa7LlGt4N/+GpUhwTD5SMgVzsW9YcF+WZAye767/2YEscQ7cgQEAAADEU2AAAAAA8RQYAAAAQLzWe5/6DAAAAAAv5A4MAAAAIJ4CAwAAAIinwAAAAADiKTAAAACAeAoMAAAAIJ4CAwAAAIinwDhjrbVHrbW/tdYettZeaa39o7X2xtTngrmRJRhDlmAMWYIxZGl+Wu996jNwQq21P1TVw6p6uar+2Xv/48RHglmSJRhDlmAMWYIxZGleFBhnrrX2k6r6S1X9u6re6r1/N/GRYJZkCcaQJRhDlmAMWZoXj5Ccv8uq+mlVvVpPm0XgOLIEY8gSjCFLMIYszYg7MM5ca+2zqvqkql6vqnXv/bcTHwlmSZZgDFmCMWQJxpClebmY+gCcTmvtl1W16b1/3Fp7qaq+aa293Xv/cuqzwZzIEowhSzCGLMEYsjQ/7sAAAAAA4tnAAAAAAOIpMAAAAIB4CgwAAAAgngIDAAAAiKfAAAAAAOIpMAAAAIB4CgwAAAAg3n8BAam5RufSPQcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_y(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, cbar=False, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df2, col='y',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_y, 'x', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r')\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "bcf4df1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df['y'].between(y_min + 3*N*y_step, y_min + (4*N-1)*y_step)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "17e9beea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1512 with 35 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_y(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, cbar=False, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df2, col='y',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_y, 'x', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r')\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "bb2dec5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df[df['y']>=y_min + 4*N*y_step]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "3b22267e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 11 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def draw_heatmap_y(*args, **kwargs):\n",
    "    data = kwargs.pop('data')\n",
    "    d = data.pivot(index=args[1], columns=args[0], values=args[2])\n",
    "    ax = sns.heatmap(d, cbar=False, **kwargs)\n",
    "    ax.invert_yaxis()\n",
    "\n",
    "fg = sns.FacetGrid(df2, col='y',col_wrap=5)\n",
    "fg.map_dataframe(draw_heatmap_y, 'x', 'z', 'cluster', vmin=vmin, vmax=vmax, xticklabels=False, yticklabels=False, cmap='cubehelix_r')\n",
    "fg.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f54e2206",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}