Step 5 - Final model development.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c0163192-6dc4-4d87-bd8f-ef709a34c0fd",
   "metadata": {},
   "source": [
    "# Final Model Development phase"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fa9ebc3-c72f-4f99-b069-b0a1e357acbd",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "55db51a5-961e-4288-a52e-b006812d9205",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4ee48f76-552e-4cfd-8d00-257087aec7c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>LNG Flow</th>\n",
       "      <th>LNG Rundown Temperature</th>\n",
       "      <th>MR Operating Margin</th>\n",
       "      <th>PR Operating Margin</th>\n",
       "      <th>MR Compressor Suction Pressure</th>\n",
       "      <th>MCHE Warm bypass Temperature</th>\n",
       "      <th>MR return Temperature</th>\n",
       "      <th>MR Expander inlet Temperature</th>\n",
       "      <th>LNG Shell Temp Top Bundle</th>\n",
       "      <th>...</th>\n",
       "      <th>Natural Gas temp at MCHE warm bundle</th>\n",
       "      <th>Low Pressure Propane kettle level</th>\n",
       "      <th>Medium Pressure Propane/Natural Gas kettle level</th>\n",
       "      <th>High Pressure Propane/Natural Gas kettle level</th>\n",
       "      <th>High High Pressure Propane/Mixed Refrigerant kettle level</th>\n",
       "      <th>High Pressure Propane/Mixed Refrigerant kettle level</th>\n",
       "      <th>Medium Pressure Propane/Mixed Refrigerant kettle level</th>\n",
       "      <th>Low Pressure Propane/Mixed Refrigerant kettle level</th>\n",
       "      <th>MCHE Warm bypass temperature</th>\n",
       "      <th>Natural Gas Warm Bundle to scrub column</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36328</td>\n",
       "      <td>12470.894531</td>\n",
       "      <td>-145.712891</td>\n",
       "      <td>5.215329</td>\n",
       "      <td>5.215329</td>\n",
       "      <td>2.730273</td>\n",
       "      <td>-42.124023</td>\n",
       "      <td>-34.738281</td>\n",
       "      <td>-121.396484</td>\n",
       "      <td>0.727539</td>\n",
       "      <td>...</td>\n",
       "      <td>-32.703125</td>\n",
       "      <td>69.798828</td>\n",
       "      <td>70.355469</td>\n",
       "      <td>69.316406</td>\n",
       "      <td>71.503906</td>\n",
       "      <td>72.011719</td>\n",
       "      <td>71.683594</td>\n",
       "      <td>62.857422</td>\n",
       "      <td>-42.124023</td>\n",
       "      <td>-53.886719</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36329</td>\n",
       "      <td>12109.980469</td>\n",
       "      <td>-145.844727</td>\n",
       "      <td>4.203972</td>\n",
       "      <td>4.203972</td>\n",
       "      <td>2.740625</td>\n",
       "      <td>-44.075195</td>\n",
       "      <td>-34.828125</td>\n",
       "      <td>-120.605469</td>\n",
       "      <td>0.693359</td>\n",
       "      <td>...</td>\n",
       "      <td>-32.910156</td>\n",
       "      <td>70.337891</td>\n",
       "      <td>71.156250</td>\n",
       "      <td>72.058594</td>\n",
       "      <td>72.187500</td>\n",
       "      <td>71.443359</td>\n",
       "      <td>70.917969</td>\n",
       "      <td>62.437500</td>\n",
       "      <td>-44.075195</td>\n",
       "      <td>-53.781250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36330</td>\n",
       "      <td>12578.753906</td>\n",
       "      <td>-145.966797</td>\n",
       "      <td>4.852132</td>\n",
       "      <td>4.852132</td>\n",
       "      <td>2.710742</td>\n",
       "      <td>-41.948242</td>\n",
       "      <td>-36.542969</td>\n",
       "      <td>-121.542969</td>\n",
       "      <td>0.742188</td>\n",
       "      <td>...</td>\n",
       "      <td>-32.414062</td>\n",
       "      <td>69.833984</td>\n",
       "      <td>69.199219</td>\n",
       "      <td>68.835938</td>\n",
       "      <td>71.998047</td>\n",
       "      <td>71.568359</td>\n",
       "      <td>72.640625</td>\n",
       "      <td>63.259766</td>\n",
       "      <td>-41.948242</td>\n",
       "      <td>-55.460938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>36331</td>\n",
       "      <td>11478.726562</td>\n",
       "      <td>-145.561523</td>\n",
       "      <td>13.105408</td>\n",
       "      <td>13.523663</td>\n",
       "      <td>2.537109</td>\n",
       "      <td>-44.016602</td>\n",
       "      <td>-36.480469</td>\n",
       "      <td>-122.675781</td>\n",
       "      <td>0.561523</td>\n",
       "      <td>...</td>\n",
       "      <td>-33.824219</td>\n",
       "      <td>69.722656</td>\n",
       "      <td>68.837891</td>\n",
       "      <td>70.060547</td>\n",
       "      <td>72.734375</td>\n",
       "      <td>72.949219</td>\n",
       "      <td>74.408203</td>\n",
       "      <td>65.121094</td>\n",
       "      <td>-44.016602</td>\n",
       "      <td>-54.972656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>36332</td>\n",
       "      <td>11518.482422</td>\n",
       "      <td>-145.175781</td>\n",
       "      <td>18.634928</td>\n",
       "      <td>16.372524</td>\n",
       "      <td>2.546680</td>\n",
       "      <td>-44.965820</td>\n",
       "      <td>-37.191406</td>\n",
       "      <td>-123.364258</td>\n",
       "      <td>0.634766</td>\n",
       "      <td>...</td>\n",
       "      <td>-35.625000</td>\n",
       "      <td>69.921875</td>\n",
       "      <td>70.478516</td>\n",
       "      <td>71.187500</td>\n",
       "      <td>73.919922</td>\n",
       "      <td>72.933594</td>\n",
       "      <td>76.076172</td>\n",
       "      <td>62.156250</td>\n",
       "      <td>-44.965820</td>\n",
       "      <td>-53.632812</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0      LNG Flow  LNG Rundown Temperature  MR Operating Margin  \\\n",
       "0       36328  12470.894531              -145.712891             5.215329   \n",
       "1       36329  12109.980469              -145.844727             4.203972   \n",
       "2       36330  12578.753906              -145.966797             4.852132   \n",
       "3       36331  11478.726562              -145.561523            13.105408   \n",
       "4       36332  11518.482422              -145.175781            18.634928   \n",
       "\n",
       "   PR Operating Margin  MR Compressor Suction Pressure  \\\n",
       "0             5.215329                        2.730273   \n",
       "1             4.203972                        2.740625   \n",
       "2             4.852132                        2.710742   \n",
       "3            13.523663                        2.537109   \n",
       "4            16.372524                        2.546680   \n",
       "\n",
       "   MCHE Warm bypass Temperature  MR return Temperature  \\\n",
       "0                    -42.124023             -34.738281   \n",
       "1                    -44.075195             -34.828125   \n",
       "2                    -41.948242             -36.542969   \n",
       "3                    -44.016602             -36.480469   \n",
       "4                    -44.965820             -37.191406   \n",
       "\n",
       "   MR Expander inlet Temperature  LNG Shell Temp Top Bundle  ...  \\\n",
       "0                    -121.396484                   0.727539  ...   \n",
       "1                    -120.605469                   0.693359  ...   \n",
       "2                    -121.542969                   0.742188  ...   \n",
       "3                    -122.675781                   0.561523  ...   \n",
       "4                    -123.364258                   0.634766  ...   \n",
       "\n",
       "   Natural Gas temp at MCHE warm bundle  Low Pressure Propane kettle level  \\\n",
       "0                            -32.703125                          69.798828   \n",
       "1                            -32.910156                          70.337891   \n",
       "2                            -32.414062                          69.833984   \n",
       "3                            -33.824219                          69.722656   \n",
       "4                            -35.625000                          69.921875   \n",
       "\n",
       "   Medium Pressure Propane/Natural Gas kettle level  \\\n",
       "0                                         70.355469   \n",
       "1                                         71.156250   \n",
       "2                                         69.199219   \n",
       "3                                         68.837891   \n",
       "4                                         70.478516   \n",
       "\n",
       "   High Pressure Propane/Natural Gas kettle level  \\\n",
       "0                                       69.316406   \n",
       "1                                       72.058594   \n",
       "2                                       68.835938   \n",
       "3                                       70.060547   \n",
       "4                                       71.187500   \n",
       "\n",
       "   High High Pressure Propane/Mixed Refrigerant kettle level  \\\n",
       "0                                          71.503906           \n",
       "1                                          72.187500           \n",
       "2                                          71.998047           \n",
       "3                                          72.734375           \n",
       "4                                          73.919922           \n",
       "\n",
       "   High Pressure Propane/Mixed Refrigerant kettle level  \\\n",
       "0                                          72.011719      \n",
       "1                                          71.443359      \n",
       "2                                          71.568359      \n",
       "3                                          72.949219      \n",
       "4                                          72.933594      \n",
       "\n",
       "   Medium Pressure Propane/Mixed Refrigerant kettle level  \\\n",
       "0                                          71.683594        \n",
       "1                                          70.917969        \n",
       "2                                          72.640625        \n",
       "3                                          74.408203        \n",
       "4                                          76.076172        \n",
       "\n",
       "   Low Pressure Propane/Mixed Refrigerant kettle level  \\\n",
       "0                                          62.857422     \n",
       "1                                          62.437500     \n",
       "2                                          63.259766     \n",
       "3                                          65.121094     \n",
       "4                                          62.156250     \n",
       "\n",
       "   MCHE Warm bypass temperature  Natural Gas Warm Bundle to scrub column  \n",
       "0                    -42.124023                               -53.886719  \n",
       "1                    -44.075195                               -53.781250  \n",
       "2                    -41.948242                               -55.460938  \n",
       "3                    -44.016602                               -54.972656  \n",
       "4                    -44.965820                               -53.632812  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = './LNG-DATA.csv'\n",
    "df = pd.read_csv(path)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "77066574-8616-4167-b822-5b4e61e3a78b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('Unnamed: 0', axis= 1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e4228d87-1e33-40b6-bf96-ba9076ec64e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_use = ['LNG Flow', 'LNG Rundown Temperature','MR IGV Position','HMR Flow ', 'HMR/MR Ratio', \n",
    "                  'Percentage Nitrogen in MR', 'Percentage Methane in MR', 'Percentage Ethane in MR', \n",
    "                  'Percentage Propane in MR', 'Percentage Butane in MR', 'Ambient Condition', 'Low Pressure Propane/Mixed Refrigerant kettle level']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ce944dd9-525a-4577-a343-9ed5eee9353d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LNG Flow</th>\n",
       "      <th>LNG Rundown Temperature</th>\n",
       "      <th>MR IGV Position</th>\n",
       "      <th>HMR Flow</th>\n",
       "      <th>HMR/MR Ratio</th>\n",
       "      <th>Percentage Nitrogen in MR</th>\n",
       "      <th>Percentage Methane in MR</th>\n",
       "      <th>Percentage Ethane in MR</th>\n",
       "      <th>Percentage Propane in MR</th>\n",
       "      <th>Percentage Butane in MR</th>\n",
       "      <th>Ambient Condition</th>\n",
       "      <th>Low Pressure Propane/Mixed Refrigerant kettle level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12470.894531</td>\n",
       "      <td>-145.712891</td>\n",
       "      <td>77.762802</td>\n",
       "      <td>18679.066406</td>\n",
       "      <td>5.310718</td>\n",
       "      <td>3.646484</td>\n",
       "      <td>42.500000</td>\n",
       "      <td>43.532619</td>\n",
       "      <td>10.102832</td>\n",
       "      <td>0.125508</td>\n",
       "      <td>33.207268</td>\n",
       "      <td>62.857422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12109.980469</td>\n",
       "      <td>-145.844727</td>\n",
       "      <td>77.999893</td>\n",
       "      <td>18802.667969</td>\n",
       "      <td>5.283063</td>\n",
       "      <td>3.659180</td>\n",
       "      <td>42.519924</td>\n",
       "      <td>43.567482</td>\n",
       "      <td>10.041308</td>\n",
       "      <td>0.124922</td>\n",
       "      <td>33.207268</td>\n",
       "      <td>62.437500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12578.753906</td>\n",
       "      <td>-145.966797</td>\n",
       "      <td>77.957260</td>\n",
       "      <td>18743.687500</td>\n",
       "      <td>5.322514</td>\n",
       "      <td>3.625488</td>\n",
       "      <td>42.646095</td>\n",
       "      <td>43.582424</td>\n",
       "      <td>9.938086</td>\n",
       "      <td>0.124023</td>\n",
       "      <td>32.043064</td>\n",
       "      <td>63.259766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11478.726562</td>\n",
       "      <td>-145.561523</td>\n",
       "      <td>72.290688</td>\n",
       "      <td>17428.503906</td>\n",
       "      <td>6.037915</td>\n",
       "      <td>3.590332</td>\n",
       "      <td>42.380470</td>\n",
       "      <td>43.839748</td>\n",
       "      <td>9.975683</td>\n",
       "      <td>0.124102</td>\n",
       "      <td>31.496241</td>\n",
       "      <td>65.121094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11518.482422</td>\n",
       "      <td>-145.175781</td>\n",
       "      <td>72.255318</td>\n",
       "      <td>16420.748047</td>\n",
       "      <td>6.156987</td>\n",
       "      <td>3.558594</td>\n",
       "      <td>42.609573</td>\n",
       "      <td>43.771683</td>\n",
       "      <td>9.854004</td>\n",
       "      <td>0.124414</td>\n",
       "      <td>31.496241</td>\n",
       "      <td>62.156250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       LNG Flow  LNG Rundown Temperature  MR IGV Position     HMR Flow   \\\n",
       "0  12470.894531              -145.712891        77.762802  18679.066406   \n",
       "1  12109.980469              -145.844727        77.999893  18802.667969   \n",
       "2  12578.753906              -145.966797        77.957260  18743.687500   \n",
       "3  11478.726562              -145.561523        72.290688  17428.503906   \n",
       "4  11518.482422              -145.175781        72.255318  16420.748047   \n",
       "\n",
       "   HMR/MR Ratio  Percentage Nitrogen in MR  Percentage Methane in MR  \\\n",
       "0      5.310718                   3.646484                 42.500000   \n",
       "1      5.283063                   3.659180                 42.519924   \n",
       "2      5.322514                   3.625488                 42.646095   \n",
       "3      6.037915                   3.590332                 42.380470   \n",
       "4      6.156987                   3.558594                 42.609573   \n",
       "\n",
       "   Percentage Ethane in MR  Percentage Propane in MR  Percentage Butane in MR  \\\n",
       "0                43.532619                 10.102832                 0.125508   \n",
       "1                43.567482                 10.041308                 0.124922   \n",
       "2                43.582424                  9.938086                 0.124023   \n",
       "3                43.839748                  9.975683                 0.124102   \n",
       "4                43.771683                  9.854004                 0.124414   \n",
       "\n",
       "   Ambient Condition  Low Pressure Propane/Mixed Refrigerant kettle level  \n",
       "0          33.207268                                          62.857422    \n",
       "1          33.207268                                          62.437500    \n",
       "2          32.043064                                          63.259766    \n",
       "3          31.496241                                          65.121094    \n",
       "4          31.496241                                          62.156250    "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = df.loc[:, columns_to_use].copy()\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4b8c3bdc-e857-4400-b584-144caf13beba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exported df1 successfully\n"
     ]
    }
   ],
   "source": [
    "df1.to_csv(\"data3.csv\")\n",
    "print(\"Exported df1 successfully\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "009dc3df-af19-473e-9c43-d62944292bfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LNG Flow</th>\n",
       "      <th>LNG Rundown Temperature</th>\n",
       "      <th>MR IGV Position</th>\n",
       "      <th>HMR Flow</th>\n",
       "      <th>HMR/MR Ratio</th>\n",
       "      <th>Percentage Nitrogen in MR</th>\n",
       "      <th>Percentage Methane in MR</th>\n",
       "      <th>Percentage Ethane in MR</th>\n",
       "      <th>Percentage Propane in MR</th>\n",
       "      <th>Percentage Butane in MR</th>\n",
       "      <th>Ambient Condition</th>\n",
       "      <th>Low Pressure Propane/Mixed Refrigerant kettle level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12470.894531</td>\n",
       "      <td>-145.712891</td>\n",
       "      <td>77.762802</td>\n",
       "      <td>18679.066406</td>\n",
       "      <td>5.310718</td>\n",
       "      <td>3.646484</td>\n",
       "      <td>42.500000</td>\n",
       "      <td>43.532619</td>\n",
       "      <td>10.102832</td>\n",
       "      <td>0.125508</td>\n",
       "      <td>33.207268</td>\n",
       "      <td>62.857422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12109.980469</td>\n",
       "      <td>-145.844727</td>\n",
       "      <td>77.999893</td>\n",
       "      <td>18802.667969</td>\n",
       "      <td>5.283063</td>\n",
       "      <td>3.659180</td>\n",
       "      <td>42.519924</td>\n",
       "      <td>43.567482</td>\n",
       "      <td>10.041308</td>\n",
       "      <td>0.124922</td>\n",
       "      <td>33.207268</td>\n",
       "      <td>62.437500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12578.753906</td>\n",
       "      <td>-145.966797</td>\n",
       "      <td>77.957260</td>\n",
       "      <td>18743.687500</td>\n",
       "      <td>5.322514</td>\n",
       "      <td>3.625488</td>\n",
       "      <td>42.646095</td>\n",
       "      <td>43.582424</td>\n",
       "      <td>9.938086</td>\n",
       "      <td>0.124023</td>\n",
       "      <td>32.043064</td>\n",
       "      <td>63.259766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11478.726562</td>\n",
       "      <td>-145.561523</td>\n",
       "      <td>72.290688</td>\n",
       "      <td>17428.503906</td>\n",
       "      <td>6.037915</td>\n",
       "      <td>3.590332</td>\n",
       "      <td>42.380470</td>\n",
       "      <td>43.839748</td>\n",
       "      <td>9.975683</td>\n",
       "      <td>0.124102</td>\n",
       "      <td>31.496241</td>\n",
       "      <td>65.121094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11518.482422</td>\n",
       "      <td>-145.175781</td>\n",
       "      <td>72.255318</td>\n",
       "      <td>16420.748047</td>\n",
       "      <td>6.156987</td>\n",
       "      <td>3.558594</td>\n",
       "      <td>42.609573</td>\n",
       "      <td>43.771683</td>\n",
       "      <td>9.854004</td>\n",
       "      <td>0.124414</td>\n",
       "      <td>31.496241</td>\n",
       "      <td>62.156250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11785.019531</td>\n",
       "      <td>-146.176758</td>\n",
       "      <td>75.999893</td>\n",
       "      <td>18631.525391</td>\n",
       "      <td>5.313677</td>\n",
       "      <td>3.617188</td>\n",
       "      <td>42.730762</td>\n",
       "      <td>43.580765</td>\n",
       "      <td>9.858788</td>\n",
       "      <td>0.128008</td>\n",
       "      <td>31.496241</td>\n",
       "      <td>58.093750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11912.583984</td>\n",
       "      <td>-146.694336</td>\n",
       "      <td>77.086159</td>\n",
       "      <td>17979.867188</td>\n",
       "      <td>5.253815</td>\n",
       "      <td>3.439941</td>\n",
       "      <td>42.270901</td>\n",
       "      <td>44.206642</td>\n",
       "      <td>9.869726</td>\n",
       "      <td>0.122266</td>\n",
       "      <td>31.496241</td>\n",
       "      <td>61.101562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>12021.826172</td>\n",
       "      <td>-146.899414</td>\n",
       "      <td>73.999893</td>\n",
       "      <td>18722.001953</td>\n",
       "      <td>5.278831</td>\n",
       "      <td>3.479004</td>\n",
       "      <td>42.528225</td>\n",
       "      <td>43.768360</td>\n",
       "      <td>10.011230</td>\n",
       "      <td>0.123164</td>\n",
       "      <td>30.949419</td>\n",
       "      <td>61.095703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>12188.800781</td>\n",
       "      <td>-146.782227</td>\n",
       "      <td>72.028290</td>\n",
       "      <td>19286.933594</td>\n",
       "      <td>5.307084</td>\n",
       "      <td>3.486816</td>\n",
       "      <td>42.674316</td>\n",
       "      <td>43.703613</td>\n",
       "      <td>9.933984</td>\n",
       "      <td>0.118789</td>\n",
       "      <td>30.949419</td>\n",
       "      <td>60.988281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12176.355469</td>\n",
       "      <td>-146.918945</td>\n",
       "      <td>72.028290</td>\n",
       "      <td>19251.404297</td>\n",
       "      <td>5.310825</td>\n",
       "      <td>3.507812</td>\n",
       "      <td>42.878517</td>\n",
       "      <td>43.594044</td>\n",
       "      <td>9.823926</td>\n",
       "      <td>0.111406</td>\n",
       "      <td>30.949419</td>\n",
       "      <td>61.931641</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       LNG Flow  LNG Rundown Temperature  MR IGV Position     HMR Flow   \\\n",
       "0  12470.894531              -145.712891        77.762802  18679.066406   \n",
       "1  12109.980469              -145.844727        77.999893  18802.667969   \n",
       "2  12578.753906              -145.966797        77.957260  18743.687500   \n",
       "3  11478.726562              -145.561523        72.290688  17428.503906   \n",
       "4  11518.482422              -145.175781        72.255318  16420.748047   \n",
       "5  11785.019531              -146.176758        75.999893  18631.525391   \n",
       "6  11912.583984              -146.694336        77.086159  17979.867188   \n",
       "7  12021.826172              -146.899414        73.999893  18722.001953   \n",
       "8  12188.800781              -146.782227        72.028290  19286.933594   \n",
       "9  12176.355469              -146.918945        72.028290  19251.404297   \n",
       "\n",
       "   HMR/MR Ratio  Percentage Nitrogen in MR  Percentage Methane in MR  \\\n",
       "0      5.310718                   3.646484                 42.500000   \n",
       "1      5.283063                   3.659180                 42.519924   \n",
       "2      5.322514                   3.625488                 42.646095   \n",
       "3      6.037915                   3.590332                 42.380470   \n",
       "4      6.156987                   3.558594                 42.609573   \n",
       "5      5.313677                   3.617188                 42.730762   \n",
       "6      5.253815                   3.439941                 42.270901   \n",
       "7      5.278831                   3.479004                 42.528225   \n",
       "8      5.307084                   3.486816                 42.674316   \n",
       "9      5.310825                   3.507812                 42.878517   \n",
       "\n",
       "   Percentage Ethane in MR  Percentage Propane in MR  Percentage Butane in MR  \\\n",
       "0                43.532619                 10.102832                 0.125508   \n",
       "1                43.567482                 10.041308                 0.124922   \n",
       "2                43.582424                  9.938086                 0.124023   \n",
       "3                43.839748                  9.975683                 0.124102   \n",
       "4                43.771683                  9.854004                 0.124414   \n",
       "5                43.580765                  9.858788                 0.128008   \n",
       "6                44.206642                  9.869726                 0.122266   \n",
       "7                43.768360                 10.011230                 0.123164   \n",
       "8                43.703613                  9.933984                 0.118789   \n",
       "9                43.594044                  9.823926                 0.111406   \n",
       "\n",
       "   Ambient Condition  Low Pressure Propane/Mixed Refrigerant kettle level  \n",
       "0          33.207268                                          62.857422    \n",
       "1          33.207268                                          62.437500    \n",
       "2          32.043064                                          63.259766    \n",
       "3          31.496241                                          65.121094    \n",
       "4          31.496241                                          62.156250    \n",
       "5          31.496241                                          58.093750    \n",
       "6          31.496241                                          61.101562    \n",
       "7          30.949419                                          61.095703    \n",
       "8          30.949419                                          60.988281    \n",
       "9          30.949419                                          61.931641    "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_csv(\"data3.csv\")\n",
    "df1.drop('Unnamed: 0', axis= 1, inplace=True)\n",
    "df1.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dce3f645-6d5a-4814-bd91-05515b1eb302",
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import absolute, mean, std\n",
    "\n",
    "# import estimators\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "# for optimization\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import RepeatedKFold, KFold\n",
    "from sklearn.multioutput import RegressorChain\n",
    "\n",
    "# pipeline for preprocessing\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler, PowerTransformer, MaxAbsScaler\n",
    "\n",
    "# Metrics\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a167b4a5-4d34-4e6c-b56a-d93027c101f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_input = df1.iloc[:, 2:].copy()\n",
    "df1_target = df1.iloc[:, [0, 1]].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4c2698e2-063a-4731-ae83-a64690ab2a74",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(df1_input, df1_target, test_size = 0.25, random_state= 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "03d9e4a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.concat([y_test, X_test], axis=1).to_csv(\"inputs.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4530cb8b-1781-485b-9806-d45c86547a4f",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Develop Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3a7a1045-4ac9-4f54-92d1-8537f37da36f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# prepare a dictionary of estimators\n",
    "ESTIMATORS = {\n",
    "    \"Linear Regression\": LinearRegression(),\n",
    "    \"K-neighbors\": KNeighborsRegressor(),\n",
    "    \"Decision Tree\": DecisionTreeRegressor(),\n",
    "    \"Random Forest\": RandomForestRegressor(max_depth=2, random_state=0),\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2224e1ef-dcb7-469e-8883-ad5cb08915cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def pipe_reg_multi(estimators, X, y, X_test, y_test):\n",
    "    # Create an empty dictionary to collect prediction values\n",
    "    y_test_predict = dict()\n",
    "    y_error = dict()\n",
    "    \n",
    "    for name, estimator in estimators.items():\n",
    "        cv = RepeatedKFold(n_splits=10, n_repeats=3, random_state=1)\n",
    "        \n",
    "        wrapper = RegressorChain(estimator, order=[0, 1])\n",
    "        \n",
    "        pipe = Pipeline(\n",
    "            [('scalar', StandardScaler()),\n",
    "            ('regressor', wrapper)]\n",
    "        )\n",
    "        \n",
    "        # evaluate the model and collect the scores\n",
    "        n_scores = cross_val_score(pipe, X, y, scoring='neg_mean_absolute_error', cv=cv, n_jobs=-1)\n",
    "        \n",
    "        # force the scores to be positive\n",
    "        n_scores = absolute(n_scores)\n",
    "        # summarize performance\n",
    "        print(f'{name}-->MAE: {mean(n_scores):.4f}, {std(n_scores):.4f}', end = \" \")\n",
    "        \n",
    "        # fit model\n",
    "        pipe.fit(X, y)\n",
    "        \n",
    "        # predict\n",
    "        y_test_predict[name] = pipe.predict(X_test)\n",
    "        print(f\", R2-score = {r2_score(y_test, y_test_predict[name]):.4f}\")\n",
    "        \n",
    "        # calculate mse\n",
    "        y_error[name] = mean_squared_error(y_test, y_test_predict[name], squared= False)\n",
    "        print(f\", MSE = {y_error[name]:.4f}\")\n",
    "        \n",
    "    return y_test_predict, y_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "40f63be7-72df-4756-b594-f2b801e7aeb2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear Regression-->MAE: 224.5993, 4.3854 , R2-score = 0.8644\n",
      ", MSE = 315.4568\n",
      "K-neighbors-->MAE: 87.4067, 2.8391 , R2-score = 0.9783\n",
      ", MSE = 152.7402\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree-->MAE: 108.1261, 3.2295 , R2-score = 0.9737\n",
      ", MSE = 207.4046\n",
      "Random Forest-->MAE: 308.0645, 5.0757 , R2-score = 0.8588\n",
      ", MSE = 417.6720\n"
     ]
    }
   ],
   "source": [
    "y_test_predict, y_error = pipe_reg_multi(ESTIMATORS, X_train, y_train, X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0ac799b-43e0-4a31-bf59-ed9c99f94513",
   "metadata": {},
   "source": [
    "|Algorithm|R2-score|RMSE\n",
    "|------|------|------|\n",
    "|Linear Regressor|0.8644|315.4568|\n",
    "|K-neighbors|0.9783|152.7402|\n",
    "|Decision Tree|0.9725|203.3375|\n",
    "|Random Forest|0.8588|417.6720|"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "def64dc5-71fd-44f0-94a4-8079f79679b9",
   "metadata": {},
   "source": [
    "From the table above, Since K-Neighbours has the snallest Root mean square error; We wil be choosing K-neighbour regressor as our preferred algorithm for this problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b28a38ac-484e-40ad-9854-19b63ebc2137",
   "metadata": {},
   "outputs": [],
   "source": [
    "pipe = Pipeline(\n",
    "            [('scalar', StandardScaler()),\n",
    "            ('regressor', RegressorChain(KNeighborsRegressor(), order=[0, 1]))]\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e222a5b9-9b6a-4772-8f9b-b8b4813038e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;scalar&#x27;, StandardScaler()),\n",
       "                (&#x27;regressor&#x27;,\n",
       "                 RegressorChain(base_estimator=KNeighborsRegressor(),\n",
       "                                order=[0, 1]))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;scalar&#x27;, StandardScaler()),\n",
       "                (&#x27;regressor&#x27;,\n",
       "                 RegressorChain(base_estimator=KNeighborsRegressor(),\n",
       "                                order=[0, 1]))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">StandardScaler</label><div class=\"sk-toggleable__content\"><pre>StandardScaler()</pre></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">regressor: RegressorChain</label><div class=\"sk-toggleable__content\"><pre>RegressorChain(base_estimator=KNeighborsRegressor(), order=[0, 1])</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">base_estimator: KNeighborsRegressor</label><div class=\"sk-toggleable__content\"><pre>KNeighborsRegressor()</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsRegressor</label><div class=\"sk-toggleable__content\"><pre>KNeighborsRegressor()</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('scalar', StandardScaler()),\n",
       "                ('regressor',\n",
       "                 RegressorChain(base_estimator=KNeighborsRegressor(),\n",
       "                                order=[0, 1]))])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5c66e2c4-bb73-4f4c-9829-0c9af1bc141e",
   "metadata": {},
   "outputs": [],
   "source": [
    "yhat = pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "aa846f34-3818-46c0-a2d1-10648261ec04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((8006, 2), (8006, 2))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "64b312b2-b4a5-4fcd-913b-4025072ce658",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "152.7401679467612"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_squared_error(y_test, yhat, squared= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "20c4ce79-a627-4668-943f-6a6b2fc51db8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "302.01741745608524"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_squared_error(y_test.iloc[:, 0], yhat[:, 0], squared= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9b829f4f-13a4-4cb5-bb58-b310aea461e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.4629184374371413"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_squared_error(y_test.iloc[:, 1], yhat[:, 1], squared= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "6849fb38-2627-44a5-beb7-badc4895eaae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>predicted lng flow</th>\n",
       "      <th>predicted LNG Rundown Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13363.826953</td>\n",
       "      <td>-146.179688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12060.130078</td>\n",
       "      <td>-145.521484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13391.834180</td>\n",
       "      <td>-145.701172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12811.619531</td>\n",
       "      <td>-145.620117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11980.771289</td>\n",
       "      <td>-145.903320</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   predicted lng flow  predicted LNG Rundown Temperature\n",
       "0        13363.826953                        -146.179688\n",
       "1        12060.130078                        -145.521484\n",
       "2        13391.834180                        -145.701172\n",
       "3        12811.619531                        -145.620117\n",
       "4        11980.771289                        -145.903320"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(yhat, columns=['predicted lng flow', 'predicted LNG Rundown Temperature']).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ad11f128-5d95-4b3f-a62b-8b646735de3a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LNG Flow</th>\n",
       "      <th>LNG Rundown Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18778</th>\n",
       "      <td>13575.379883</td>\n",
       "      <td>-145.473633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10519</th>\n",
       "      <td>11672.666016</td>\n",
       "      <td>-145.039062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31757</th>\n",
       "      <td>13388.155273</td>\n",
       "      <td>-145.786133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6400</th>\n",
       "      <td>12687.996094</td>\n",
       "      <td>-145.610352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17354</th>\n",
       "      <td>11994.082031</td>\n",
       "      <td>-145.502930</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           LNG Flow  LNG Rundown Temperature\n",
       "18778  13575.379883              -145.473633\n",
       "10519  11672.666016              -145.039062\n",
       "31757  13388.155273              -145.786133\n",
       "6400   12687.996094              -145.610352\n",
       "17354  11994.082031              -145.502930"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09b6def7-6b93-4766-b2cf-1e90d7737838",
   "metadata": {},
   "source": [
    "#### visualize the performance of the pipe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "742b18a8-83f1-4533-b574-c3ee9ece20b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bf91b582-7320-438b-84bb-dbbce7d6574d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lvHLQEf0+f6yN8xsOEvwLIYQQQgghxDi0ZluKDY0dVCWjRfX7AEopKpMRNjR2sGZbivas16s0oLokwra2LH5gSERsbKUItBnzgf/J777KjU/eyZymd4uOby2byHcWXsgf5ywANfCYwdc2t/H/PjBtBK9y35PgXwghhBBCCCHGocGO7lu2vonfvri5qDSgJZNjzbZ2DGArSOd89Bjf8T+0eSs3PHUXZ65fWXQ8HYlx2wmf4I7jzyMbiffz7GLN6dxIXOKokuBfCCGEEEIIIcahwYzui1iKR9dsLyoN6HB9mlJuIdDXBiK2IvDHZuhfnu3gC8/9mn98+SEiOig697ujzuCWU5ewvWxCP8/u25aWNFqPzc+7pyT4F0IIIYQQQohxaHej+1rTHlOrEmxvyxRKA4wxNLVnCbpGsuefoVBEbMgFYycgdgKfxa/+mS8uu5+qbHvRuZVTj+Sbp1/G6imHDf11bUVTu8uabSmOmJwcrssddRL8CyGEEEIIIcQ4NNDovta0R2nMZtHcWn6+7J1CaUDW07i+xrYUJjDddv8N1sBl8vvUgo2ruPHJOzls5+ai41vKJ3HzaZ/h4dkn77auvz8HVcZJ53RX6r8E/0IIIYQQQgghxrj+RvfNmVLGlQtmUhaPcO/z7xZKA3ytMSaMm7vv8XvB2Aj+Z+3YxI1P3sXCd1YVHe+IJvjpSRfw8w/8La4T3aPXVtA19QAilqI6uWevM1ZJ8C+EEEIIIYQQ49j8WRM4cUYNa7alaE7nqE5GmVtXXhjv1700wFYKbQxa936d0SyBr8ykuGbZ/Xz6lYdxzK6L0yj+++gz+f6HltBUWrVX7xFzLLxAk8p4HD2tkrl15QSBv7eXPmZI8C+EEEIIIYQQ45xlKeZNrejzeL40YFNzBi8IRjXI7ykSeCx5+WG+8Nz9VLidRedemHYU3zzjMtZMnrnX76OAwIRlDiUxhysXzMSyFEGwu2fuPyT4F0IIIYQQQogD2PxZE/iH46fz/cffIuf3seU/Gozh9A0v8q9P3cXM5q1Fp96rrOXmhZ/h0cNP2uO6/l4UBNpQnojw3U8czfxZQ5sOsD+Q4F8IIYQQQgghDmDL3m7itqUb8MdI4D+76V1ufOJOPvTeq0XHU9Ekt87/JL847mPknMiwvmfCsahIRrnlE0dzymETh/W1xwoJ/oUQQgghhBBiP6e16bOmf3eWvd3ENb99lda0tw+ucmDV6Ta+9Ox9/MNfH8XuVtcfKIvfHHMWPzjl0+wsqRz297UteP/BVVy1cNa43PHPk+BfCCGEEEIIIcaYoQTzy9fvKHTz9wJDxFbMmFjKR46qZVp1ss/na2341Yr3+PdH3qDTHd3C9qjvceGqB/n88t9QnksXnXv24GP51hmX8ubEQ0bkvUtjNv9y9hwWHz99UIsl+zMJ/oUQQgghhBBiDOkrmJ85qZQrF8zstTO9fP0ObnhgNR2uT1UyStS2aM14rHhnJ89v3Elp1KEkZhc9f/n6HXz7z+tYsy01us39jGHR289z/VN3c0hrfdGpDdUHcdNpl/DkzA8OW11/IqLIegaloDweYW5dOZ89bXzv9ncnwb8QQgghhBBiv7Snqe5jWV/BfC7QrKtv54YHVnPzefMKwarWhp89vZ7WdI6KRBRjoDPn09Tuoruiel9rktFo4fmfOmE6963YxLbWDGYUA/8jt2/kq0/ewUmbVhcdb4uV8OOTF3Pv+/8Gzx6+un4FRG2byqTDP550MKfMmjgufi9DIcG/EEIIIYQQYr8zlN3xfWE4FiK0Nty2dAMdrk9teRzVteMdt2xqyy0aUi63Ld3AiTNqAPjeo2+yYmMz2kCHm0Gp8DUMEHUsjIFcoAFFbXmM+rYsP316AxgwxuDYCi/YtysAEztauPbZe7ngtcex2PXevrK4731/w49OWUxronzY39cApfEI/37ePD40e3w29NsdCf6FEEIIIYQQ+5Wh7I7vCys27uT2Ze/t9ULEmm0pNjR2UJWMFgL/PKUUlckIGxo7uH/lJn774qaitH1lwsZ1+Vhea7AUGBPu/itlk4habGvNUhp3MCjUPoz7Y36OS178PVe98D+U5jJF556acRw3nXYJ6ydMH9Fr2Nqa4fO/fYXPLpzJZafOHNH3Gosk+BdCCCGEEEKMWT131OfUlg16d3xfpXR/46G1NGeCvV6IaE7n8AJD1Lb6PB+zLZpyAf/xxFs0d+aK0vYN0H1Sn681jqVQChzLosP1aWrPoQ2kMj4A+6TNnzH8zZvPcf3TdzOtbXvRqbdrpnHTaZfw9MwP7IsrwVbQlvb4ziNvAhxwCwAS/AshhBBCCCHGpL5S+yeVx9nc3El1SWzA3fE121LMm1oxoteXr6sPFyISe70QUZ2MErEVuUATt+xe57N+QNr1yXjFgX6f12YgFxhijqItnaUl4+/2OcNtXv3bfPXJOzh+y9qi4y3xMn54ymLuP/ZsfHvfhaS2ZeEoQ843/PTpDVw8/1Acp++FlvFIgn8hhBBCCCHEmNNfav87TR20uz6lsQjxSO8AOWZbtGlDczo34tf4RkM7AJWJgdP0+1uI6CurYeakUtbVt1NbbqGUwhhD1tN4gWZ7exZPGxhCEO/6hibf36vPOVST23fwlWd+yfmvP1l03LNsfvn+c/iP+Z+kLVG2T68JwqEBlrJwbE17xuPB1+o57/0H7fPrGC0S/AshhBBCCCHGlIEa300ojdHuhh3ty+JOr6DbDTQRS1GdjI74dbZ0LTBEbavPFPqBFiL6a1h46mET2NycpiHlEnUUbWkP19f4ozqTb3DiXpbLVj7AlSt+R9Jzi879ZeYHufm0S9hYM3WUrm7XxEBLhSUPW1vTo3Yto0GCfyGEEEIIIcSYMlDju0TMJubYZP2ATC4gGdsV0hhjaE17zJlSxty64e8Y31NVMkobYUd9u4/08f4WIpa93cSXf/cana5PRSJCZSKCpw3r6tvZ3JzmUydM549/3cba+vZCacGYZgznrnuGf376Hg5qbyo69caEg/nW6Zey7ND3jdLF7RIE4YQDbcLRfwdVJkf7kvYpCf6FEEIIIYQQY8pAje8UiknlMbY0p2nqyDHJUsRsCzfQtKY9SmM2Vy6YuU+a/R1RW8a7QGvGo7rULlqo6G8hYtnbTXzu16+QynhYSpHxAloci4llcWrLYzSkXJa+1UR5PEJZzKE84bCtNbPP6/UH631b3+CrT97B+7e9WXR8Z6KcH3zo0/zmmEUEffQvGA2eNkCAr6EiGeFjR08Z7UvapyT4F0IIIYQQQowpu2t8F7EtKpNRplUnaUxladOGiKWYM6VsyOP19kZ+gaE0ZtOQcqlMRgZciFi+fgdf/t1rpDIetqWwlcIAGS9gS3Oa6tIoMUfx+pY2jFJEHUVDyh2Tgf+UVBP/vPQePr52adHxnOVw9wfO5acnXUAqXjpKV9c/T4dd/z+7cOYB1ewPJPgXQgghhBBCjDFz68p7Nb7Ly++oH1lXzt0XfpB1De2Fhnlz68r32Xi/7v7tnCO5fdl7bGjs6HchIt/HoNP1UYBtKRQKbQxaQ4Bhe8od+I3GgEQuyz+t+F8uX/l/JPzi633k8JP49sKLea+qbpSurpgiHIFYdEzBhfMPOeDG/IEE/0IIIYQQQogxxrIUVy6YyQ0PrB5wR91xrBEf5zcYJ8yoYf5hk4s69/dciMj3MahIRMjkAgJtMMbsF438AJTRnLfmKb6y9BfUdjQXnVs76VC+efplPH/w0aN0db05lsK2FL42KKAs7pCI2ni+YcHsSaN9eaNCgn8hhBBCCCHEmDN/1gRuPm9eoSP+vkjt7zl6byiZBJalBlyIyPcxiDgKTdh8bn9x3Ja1/NsTd3BMw9tFx5tKKrnlQ//I7+adgR4jdf3daWNIRGwmlsUojTlkvIC08ffJJIixSIJ/IYQQQgghxJg0f9YETpxRs8cB+VD0N3pvuBYaqpNRtDFsbcmC2T8C/6lt2/mXp+/hnDeeLTru2g53ffDj/OzEC+iIja2O+Y6CwMCE0iilsQjxqIVC7fNJEGORBP9CCCGEEEKIMWt3O+rDYfn6HdzwwGo6XJ+qZJSobZELNOvq27nhgdXcfN68QS8AdM8eqExEgHAaQHncIdCGQBuijkJpxmzKf4mb5soVv+OylQ8QC7yic3+afTLfXngxWyprR+nq+qcATVjn39ThYlsWMcciGwT7fBLEWCTBvxBCCCGEEOKAlW/E1+H61JbHC80F45ZNbblFQ8rltqUbOHFGzW6Dxu7ZA51uQMYLUAriEZuIreh0fSxL4fmGMdjAH0sHnP/6E3z5mXuZ1NlSdG715Jl844zLeHHaUaN0dbvn2AoFXXX+ioZUlg7XpyRq7/NJEGORBP9CCCGEEEKIA1a+EV9VMlo0VQBAKUVlMsKGxg7WbEsNmIHQPXsg5lhkPB+/q67fDzSlMQevq/ncWNzvP2HTar765J0ctX1D0fHtpdV899QL+b+jTsOosTsaTwGWgkBDMuowvTrOtlaXqVUJbjpvHvMOqjhgd/zzJPgXQgghhBBCHLDyjfiidt+Bbcy2aNOG5nSu39fonj0wuSzGe83pQkq/BjCQyvp0/ccxZXpLPdc/fTdnv7W86HjWifJfHzyP/zzxE6SjiVG6usFzLEWgwVKKiWUxbMtmQlmM5s4cllIHfOAPEvwLIYQQQgghDmDVySgRW5ELNPE+Ota7gSZiqQE7xL/R0F7IHnB9Q8YL6FnOP9aC/jK3k88u/y0Xr/ojscAvOveHOQv4zsIL2Va+/4zE0xgSEafQ2R8Gt3BzIJHgXwghhBBCCHHAmltXzsxJpayrb6e23Cqk/hsMGTdgR4fLoRNLmVNb1u9rtOTH+FmK5nSOYCwW9HexdMAnX3uMLz17HxPSbUXnXp1yON844zJePmjOKF3d4FSXRIg5NhaG+jYXFERtm4NrEljdShMGs3BzIJHgXwghhBBCCHHAsizFlQtmcsMDq2lIuVQmI3iBpjHl4voBAJubO7n4Fy/22zCuKhlFG827O9OF54xF8999la8+eSdzmt4tOr6tbALfWXAhfzxywZiu689LZTwmlds4tk0sYuN6Ab7WuJ4h0RXny2i/3iT4F0IIIYQQQhzQ5s+awM3nzeO2pRtYuy1FazqHAeKOzcSyGFHHGnDsX1smR2cuwPU0tsWYy/E/pHkr//rUzzlz/Yqi4+lIjP884RP81/HnkY3ER+nqds+xVNFYRF9DfWsW21IYwq/bCwydubDZohtoGe3XBwn+hRBCCCGEEAc0rQ1l8QgXzz+Ef3/kDXJ+wKSyOImoXSgDGGjs393L3yXmWASBIehZ7D+KyrMdXP3cr/nHl/9EVBfX9f/vUafz3VP/ke1lY3v0nW2FXfx7TkkwdB1XCs8YjIFO18fXYfmFjPbrTYJ/IYQQQgghxAFr+fod3LZ0AxsaO8h4AamMR8yx0VA0+m+gsX/vNHUysTRGOhbQlMqiR7nm39YB//DqI3xp2a+ozqSKzr100By+ccZlvDbl8FG6uqEJdNjMr+8lla77Y8LsgEMnlHDNmYczoSTG3Lpy2fHvQYJ/IYQQQgghxAFp+fod3PDAajpcn6pkFMdWpDIebhCwtSXDQVWJQud46L97fNoNaO/wyAXhDvRoOnXjKm588i4O37mp6PiW8kl8e+HF/OmIU0DtX0Fxz680nwXgBXrXOWN4o6GdrS0ZTpu9/0wp2Jck+BdCCCGEEEIccLQ23LZ0Ax2uT215HKUUxoQNABUQaE19W4aDKhKF9P/+use3uR5uMLoB9cydm/nXJ+/i9I0vFR3vjMT56UkXcNcH/hY3EhulqxuaiAXeANkTpts/FWBb4XKA62tufeJtDqlJUpGI0pzOUZ2MShZAFwn+hRBCCCGEEOOe1oY121KFgFAbw4bGDqqS0UJ6fzxq4ViKrBfuKAee5r3mTuIRmwmlMTrcoNA9XmvDr1duoqLbe+TDy325+V+ZSfGF537Nkpf/hGN2Rcwaxf/M+zDfO3UJTaXV+/CK9o4ibOg32McaKDQDVEBbxuNzv36FZMQOxy/aipmTSqX+Hwn+hRBCCCGEEONc97r+fEBYXRKlMxdQ1W0Xv9MN8ILi+nJtIJ0L2NScZkJplEVza7n9mY08uqae9Q1t3PSBXY/N70TvC07g8+lXHuaa5+6nMttRdG7FtKP4xumXsqZ21j66mr1nW2F9/1AWTno+1gBZX+P6mrIqh6pklFygB5zUcCCR4F8IIYQQQggxbvWs64/aFrlAs6UlQ4fr05rxqC6JYjA0tbtA8Wi57s37U1mfHzz2Bq0ZH2MgavcOVUd8198YTtv4Ejc+eRczm7cUnXqvspabF36GRw8/ab+r6w/2sElifve/+zSA/CQAy1LELXvASQ0HEgn+hRBCCCGEEONSX3X9AHHL5qDKOG81dtDYnqUy6eB6BtcPUCqcGQ9hQOl0zZL3tSHraXxfM1rT/A5vepcbn7yLU999peh4ezTBrfM/yT3HnUvOiYzOxe0jPUf+QRjo25bC75a10X0xYaBJDQcSCf6FEEIIIYQQ49Kabaledf15lmUxsSzG9pTL1tYsyYiN1qYosLcthWUpvG6RpN91fl/uHVen2/jisl+x+NVHsLvV9QfK4jfHnMUPTvk0O0sq9+EV7bmoo4hYis7crs/RV0Dfn/zjLMCxLZQKkxy0pjAQUAG2XXyH+pvUcCCR4F8IIYQQQggx7mhtePm9FjpzAfGIjcGgeoTsVYkonW5AXUWczc0Zgh4RqK9NIf2/l30Q/UcCjwtXPcjVy39LudtZdG7ZwcfwzTMu482Jh4z8hQyTkqhFMhrhhEOreGh1Q9E5pRjUmERLQSJi4/oabQx216JO904NlqWIWFbR8/qb1HAgkeBfCCGEEEIIMa7kG/ytq0/RnvXodD3iEYeJZTFKY7tCIDfQGGPY2NRB1h9aLv9gAtU9Zgxnvf0C1z/9cw5tqS86tbGqjptOv4QnZh6/39X1O7ZFxFZUlsRQKiypUKjC7r3bNWWhPwo4cko5lckIq7e24QeGXKAxOjxndS0gxB2LeGRX8G+MoTXtFSY1HKgk+BdCCCGEEEKMG90b/FUmImRyAVkvIJPz2dqiOagqQUnUJpML2NKaxh1i0D/S5jRu5KtP3Mn8Ta8VHW+LlfDjkxdz7/v/Bs/eP+v62zI+06oSvG9aJb9e8R4QllbkRRyLXLc5f05X/K41oGBiWYwb/mYOQOEeV0eihayBVNaj0w2wLYusr4nZFm6gaU17lMZsrlww84Bt9gcS/AshhBBCCCH2U1ob1mxL0ZzOUZ2MMqe2rFeDv0nlcba2ZAiMJtCa+tYMSkF2N7vM+9qEzhaufeZe/v61x7G6XZmvLH71vrP50cmLaUnu/43q3tnRyYSSKGWJCG1pD0tpLBVG+bYK+wF4PSYtRByLwyeXcv3Zcwqj+m4+b96u8Y3aELEUR0+t5NTDJvDM2zvY0NhBW9fxOVPKuHLBzAN6zB9I8C+EEEIIIYTYD+VT+zc0duAFhogdBvqbmzupLomhlMIQ1oRXlURIZXyyXkC2a2fZVvSq8R8NMT/HxS/9kc8+/1vKcpmic08fehzfOv0S1k+YPkpXN/zSOc2/PLCajx5Vy29f2kLONzi2xlJhsO9rg2MpPn3idA6ZUIoycOz0SuYdVFG0az9/1gROnFFTtPgzt64cy1JccsqMPo8f6CT4F0IIIYQQQuxXuqf2VyWjRG2LXKB5p6mDdtenNBbB14amdhfXDzAmzBLIx/qKMRD4G8PZbz7H9U/fzfS27UWn3q6Zxk2nXcLTMz8wShc3chSQdn02tWT48qLZ3LZ0A+0Zj6DrXEUywmcXzuSyU2fu9rUsS/U5tq+/4wc6Cf6FEEIIIYQQ+w2tTa/UfoC4ZTOhNEa769OQyhaCfdtSaAzdxr6Perr/UQ3r+eoTd3DCljVFx1viZfzwlMXcf+zZ+Pb+Fao5Fvi673PdR/lZFpQnImxo7OAri47gkpMP5cHX6tnamuagyiQfO3oKjmP1/UJir+xfvyghhBBCCCHEAW3NthQbGjuoSkYLgX9eImYTc2wyXoAFRCMWGAj6G9e3j01q38mXn7mX819/oqiu37Nsfvn+c/jxyf9AKl46ile458riEVIZr8+Miu6HYo5NWdyhqSNHczqH41ic9/6D9tl1Hsgk+BdCCCGEEELsN5rTObzAELV77w4rFBVJh0xbAIQd4I0x9BX7d9+NHmkxz+WyFx/gyhd+R4mXLTr3xMwPctNpl7CxZuo+uprhk196MUB71t/t9+lYYV+GXBA24qtORkf4CkV3EvwLIYQQQggxDHp2nj98YmK0L2m/1vP7zDdtq05GidiKXKCJW3av51koFBB1LAJjinb9uwf8+yTwN4aPrXuGf156D1NTTUWn3phwMN86/VKWHfq+fXElI2JyWZTOXEDG02hjUIRlFn0tuMQcxZSKBBbQmHKZMbGEObVlo3HZBywJ/oUQQgghhNhLfXWenz05ycdrRvvK9p3+gvU9sXz9Dn729HreaGjH8w0RGw6qTHD09CrijkU8YtPU7lJXGSPng681dld3/9ZMDktB3AHfWLheUAhE92Xy/7Hb3uSrT9zBcdveKDq+M1HODz70aX5zzCKCPhYv9ic7Oj3KEw5RxyYZtbEthWNZxCMWzZ05tre7aG2wFFQlo2xPhQ0YFbC5Oc3Fv3iRK06dQUUiKp3594FRDf6feeYZbrnlFlatWkV9fT0PPPAAH//4xwHwPI8bb7yRhx9+mI0bN1JRUcGHP/xh/v3f/526urrCa7iuy3XXXcevf/1rMpkMZ5xxBj/72c+YOnVX2kxLSwtXX301f/zjHwE499xzufXWW6msrCw8ZtOmTXz2s5/lySefJJFIsHjxYr73ve8RjUoqihBCCCGE6F9/neffbOiAGlixcSenzK4d7cvcrb0J3vta/Jg5qXTIs9W1Nty/chPfe+xNOrJemLZPOAJuR6fHX7emih7fmvHIJ//37DXXmu2n+9wIq03t4CvP/IK/W/NU0fGc5XD3B87lpyddsN/W9fekusbzGWMoj0eKfi81pTFiEZvGVJa0F7A95aJUWPM/qTxG1LZ4bUsrl/7yJUqiNpay9vh3IwZnVIP/zs5OjjnmGC6++GLOP//8onPpdJqXX36Zr371qxxzzDG0tLRwzTXXcO655/LSSy8VHnfNNdfw4IMP8pvf/IaamhquvfZazjnnHFatWoVthytpixcvZsuWLTzyyCMAXH755SxZsoQHH3wQgCAI+OhHP8rEiRNZtmwZO3fu5MILL8QYw6233rqPvg0hhBBCCLG/GajzfGkkBqS567l3mH/Y5DG9m7k3wXt/ix/r6tu54YHV3HzevEEFcuFu/wZWvLMTbwhz+EYnxO8tkctyxcr/5YoV/0fCd4vOPXrYidx82md4r6qun2fvX2wFkyviVCYcNjVncf2AtqxHZTLSVXQRKo052BVx3mtOE7UtasvjJGI2CkWH65N2A3xtsFAcUhPH06bf381wZpYcqEY1+D/77LM5++yz+zxXUVHB448/XnTs1ltv5fjjj2fTpk1Mnz6dtrY27rrrLu69914+/OEPA3Dfffcxbdo0/vKXv7Bo0SLWrVvHI488wgsvvMAJJ5wAwB133MFJJ53Em2++yezZs3nsscdYu3YtmzdvLmQVfP/73+eiiy7ipptuory8fAS/BSGEEEIIsb8aqPN8/o/vNHWyZltqzM4d35vgfaDFj9pyi4aUy21LN3DijJoBA7X8NbSmvSEF/mOC1vzt6qV88alfMqVjZ9GptZMO5ZunX8bzBx89Shc3MiZXxIk5NpuaM2RyAYGBrS0ZWjpzTCqPUxoLw0xjDDs6cygUUyriJKJdxzE0tbsYIOIoPK3JBYZEtO/fzXBllhzo9qua/7a2NpRShXT9VatW4XkeZ511VuExdXV1HHXUUSxfvpxFixbx/PPPU1FRUQj8AU488UQqKipYvnw5s2fP5vnnn+eoo44qKidYtGgRruuyatUqTjvttD6vx3VdXHfXql4qFaYheZ6H53nD+dGHVf7axvI1ir0j93j8k3s8/sk9Hv/kHo8PO9vTKKMpcRSWKt6DjqgwiFVodran8bzkPr8+rQ1vNLTTks5RlYxyRG1ZURCuteGOZ94m53lMq4h3LVgYYraiNBJle7vLHc+8zXHT+t5lXbstxeYd7UwqiRC1DEVV9Qomljhs3tHO6s3NHFnX94Za/hrcXI6EAxl7/wn+j9+6llP/507+9u23i47vSFbyw4Wf5v+O/jDasont024DI891c7R3GjSGZAT8wKAsRRD4NLZ14lQmcCyLtoxHWVQRxaI0YhX+jmRyGrRP0gnzBHxjsAiIKNXrd9Oe9fjGQ2vpcH0qE7sWpzZsT/G1P7zGv51zJCfMGLnmGvvDv6sHe237TfCfzWb5l3/5FxYvXlzYiW9oaCAajVJVVVX02MmTJ9PQ0FB4zKRJk3q93qRJk4oeM3ny5KLzVVVVRKPRwmP68u1vf5uvf/3rvY4/9thjJJP7/l/uQ9Uzs0KMP3KPxz+5x+Of3OPxT+7x/u8rcwHS/Z6/5ogMbW+t5OG39tkl9akNeLeP4x+vAWoAMv08M80jj/y539f94hG7f+93X13Gu6/2f37XNewfEo2NHPnLXzJ12bKi44HjsOFv/5a3zz+f45NJjg+PjsYljrDdfab2Po5l+zg28HPefTX8fj87K3+k92905xsrePiNXoeH3Vj+d3U63f+/f7rbL4J/z/P45Cc/idaan/3sZ7t9vDGmKO2qZwrWnj6mp+uvv54vfelLhT+nUimmTZvGWWedNaZLBTzP4/HHH+fMM88kEomM9uWIESD3ePyTezz+yT0e/+Qejw9aG/7pV6t4s6GDyWUxuv9PRwfDp6a18lDzBH6y+IP7tD55xcadfe6WtmY8SmN2Ybf0ufU7+NcHXmdiaQzL6v06WkNTp8tNHz+Kk/tIr167LcUXfvMKyahDPNL7BTKeJpPz+fEn39fvzv9dy97hx0+8hVLhmD6v54y4MSSZy3D58t/xmRUPEAuKd1sfOeJkbjn9IrZU1sLro3SB+5ACorYiMBB3bKbXJMFAW9Yj7fr880fm8DfzwkaXPf+OZHKazS2dKMJlhIRjMb26pPD3J/+7+cIZh/PjJ97aq9/X3tof/l2dz0DfnTEf/HuexwUXXMA777zDk08+WRRU19bWksvlaGlpKdr9b2xsZP78+YXHbN++vdfrNjU1FXb7a2trWbFiRdH5lpYWPM/rlRHQXSwWIxaL9ToeiUTG7A+ju/3lOsWek3s8/sk9Hv/kHo9/co/3f5edehg3PLCazW05KpMRYraFG2jS2RwAF86fSSy27yZIaW24fdl7NGcCassTKKUIANuxqC61aUi53L7sPeYfNpmasiRGWXT6hnik99i5jB9gsKgpS/b5O503rZppE8pYV99ObXmsaOPMGENTp8+cKWXMPaiKdQ3tvZq1aW14ZG0TbqBwLIVlKXJaY8ZY/K+M5hOrn+DLz/ySSZ0tRedaZ8zgs/Mv47mD5oUH9sON/qhjoQjvWa5HzwVF/yMSPQ22ZTGpJI5vwuA8EY3SnjNUlcZ5qylDczrHGUfWsXHnxsLfkahtEWCT9QIitqK8JIGPBab4d1NZFqfTg5K4jWd6L55ZlqLT92l19Yj/e3Qs/7t6sNc1poP/fOD/9ttv89RTT1FTU5wLdNxxxxGJRHj88ce54IILAKivr+f111/nu9/9LgAnnXQSbW1trFy5kuOPDxNvVqxYQVtbW2GB4KSTTuKmm26ivr6eKVOmAGHqfiwW47jjjttXH1cIIYQQQuyH5s+awM3nzSs0JGvThoilmF1bCqRHpB55oM7nAzchVFQmI2xo7GDNthRz68qZOam0K3i3egXvrWkvDN772VW1LMWVC2ZywwOraUi5RYsfrekwy+DUwyZw8S9e7LNZW1k8QmMqS8yx8QKNBdhK4Y+h6P/4za/z1SfuYN72DUXHG0uq+OHCf+TESxbw0kuR/TLoz9PG4CiFhkKvftPtn4pdJ7rfmohjMaUiUWjwB+AGGq0NP3ribRpT2cI9rymNUh532NmRo00bklEbgyFq29hdC0Hdfzf530fEVuQCTdzqvTjlBpqIpahOynj2wRjV4L+jo4P169cX/vzOO+/w6quvUl1dTV1dHZ/4xCd4+eWXeeihhwiCoFB/X11dTTQapaKigksuuYRrr72Wmpoaqqurue6665g3b16h+/+cOXP4yEc+wmWXXcbtt98OhKP+zjnnHGbPng3AWWedxZFHHsmSJUu45ZZbaG5u5rrrruOyyy4b0+n7QgghhBBibJg/awInzqgpCsgPn5gYsFZ+T+2u83lzOocXGKJ2H3n8QMy2aNOG5nRuUMH7lQtmFnbp+1pwOHFGDZ855VB+8dy7NKayWAoSEZs5U8o49bAJ/GrFpn4nCfz9B6fhBYZJ5THqW7N4vmasNPuf2trADU/9nL95a3nR8awT5b8+eB7/eeInCBJxTrTGdtQ/0M59xArLLILAgBUuAlQkItSURHlnZye2pVAolNo1vcLzNbprRaCuIk5JbFcH/4wb0NAV8G9u7qS6JFa45/VtLiVRi6tOm8W06iTVyShtmRy3P7OxaNFszpSywm9Za7NXi1Oi2KgG/y+99FJRJ/18/fyFF17I1772Nf74xz8CcOyxxxY976mnnmLhwoUA/PCHP8RxHC644AIymQxnnHEG99xzD7a9a2XoV7/6FVdffXVhKsC5557LT37yk8J527b505/+xFVXXcXJJ59MIpFg8eLFfO973xuJjy2EEEIIIcYhy1JF4/xGojv4YMbyVSejQ9ot7S9zoXsQ1t+Cw6mHTeCPf93Gmw0d+FpjAEspElGHM4+YzGPrGgYcA/jomu1EbEXUtjioKs6m5kxha3mgoHUklbppPvv8f/OZl35PLPCLzv1hzgK+s/BCtpWHDcXHUhf//r4v0+08PR6jLIgA2kAsYlEej3DLJ8KxhJf+8iVcTxOxw4wRYyDQBksp4hGLwBjaMj6WZeEFmsaUi+sFheyBrKfwtSEeUT3ueQO/uPj4QqbK/JkT+s1iGcrilNi9UQ3+Fy5ciBkgpWegc3nxeJxbb72VW2+9td/HVFdXc9999w34OtOnT+ehhx7a7fsJIYQQQggxGrQ23LZ0w4DB9M+e3sC1Zx1OdUmULS0ZDqqMY3Xr5NffbmlfmQv5IKy/BYe/bm7jufU7gDDYs5Qi0IbAGOrbsnztoTVYSjG5qxeAwZDNaXytcSyLyqTD9rYMkysSbGnJUBF3sABlKQxhoLkvWTrggtce59pn72NiurXo3KtTDucbp1/Gy1Pn7NNrGqyIDQqFF5iiYL/7N9j9PzsWOLZFoA2G8N4cUlPCv/7NHOZ3NXa89szD+f7jb5HzNUoblIKIbRN1FFXJKJ86YTrPvL2DtdtStKZzGMIyAD/QWJbC9TVbWzIcVBWWBfQsOckvlPVcNOtpMItTYnDGdM2/EEIIIYQQIrS7Wv6YY/Hiu81c9suX8AJDh+vzVmMHE8tiVCWiu90t7SsI62/BIaYs/CAgH59HbIXfFXjmg05twjTyhrYsvjZ0ugGuH2BMmEIetS0c22LR3Fp+++KmMF18lDr9n/TeX/m3J+5gTtO7RcfrS2v4zsKL+MORCzCq7zKK0WSpsFlfoA3agGOHCzC2UiSjNlHHot31yXq68Jx4JKzTL4naZD1NZ87HCzQ3nzePY6ZVFh532akzmTOlnO899habm9NoY0hE7KISk4vnH8onbn8eL9BMLI3ha83W1ix2OLoBPzA0tbuUxGwUqqjkZCgGWpwSgyfBvxBCCCGEEPuBgWr5O1yfxlQW34TnJ5dFac14NLZn2Z5y6XQDSqL2kHdL+1twyHqaXLAroPT1rsC/p8DA9pQbjoZzLJQVZvZnvQB8TVnc4VMnTOeWR98a4jey9w5p3soNT9/NWW+/UHQ848T4zxPO57+O/zsy0fg+v67+RB1FxFJkcpqYY1FbmSAZsWjLhAF8xLaIOoq2jMe06hIaU1lKow6B9tDGMKksTk3JrnsZj1i0ZgxzppQz76Deu++nHDZxwLT8dQ3tNKayTC6PE4/YZHIBSoWLPxYK2wLXD8jmNImovVcN+naXISB2T4J/IYQQQggh9gP91fIbwt1VbQyOpUhGHSxLUV0SpTLpsLU1y0GVCW4+bx7zDqoY0m5pfwsOvtZ036Q3pu+a8u5M1+MspbquGiwM9694l6jtUBJVKE/h+iO/+1+e7eBzy3/LRaseJKqL6/r/d+5p3HLqhTSUj7108ohtMaEkxo4Ol4Ork2R8zXvNaVxf98qo+MKHD2NCSYzmdI7NzWnueGYDnTlN1teFuvmWzhxRx2L+zJrC9IfBZITk9fx9xCMWMcci42kiVng9Roe/F2MsadA3yiT4F0IIIYQQYj/Q31i+bE6T9cIANuZYxCO7AnVLWUwojdHSmcNSashp0v0tODiWhaUoXgAYxOv5QdgOztcGY8LnrGvoQAFxxyYZdXD94W+UmGfrgH/466N88dn7qMmkis6tqjuCb5xxGX+tmz1i77+3qpJR2rIeWV/T2J4llQ0IuhZ98jvu+YyKrS0ZTps9qfDcGRNKiurmtQ4nK+R8zc+Xvcu9z79XlNI/GD1/H0opJpbF2dqSwdOG8OdmCLShIeVKg75RNvYKV4QQQgghhBC95Dufl8ZsGlIuGS9Aa0M65xNosK0w8OrZDyBmW3h7UGcNuxYcWtJeUTPueMTqd5Rgdz1DPE1YB55/KWV1RawG3CAglfUZKR9652UevvvzfOuxnxUF/lvKJ/K5c7/C+Z++ZUwH/vGIRWUyEjZxVLCz08PXYRq9pRRKqcI4PkvBI683oLutzsyfNYFfXHw8ty/5AJ85+VCijo3TlSEyqSxGScwpTI1Y3tXIcXf6+n2UxhwOqkoQ7+pFoLoaQc6ZUsbN582TBn2jSIJ/IYQQQggh9hP5zudzppSRdn0aO9yu0XsWE8tilMZ6J/bubZ11XwsOWV/j2HafNf7d5YNRBdhd/1lTiPfxg13BaaBHpsP/zJ2buet3X+fe//43Zu/YVDjeGYlzy4eWcMal/8lDc07ddbFjkKVgSkUChcJS4SKAATD579KgjcEPDLZlMakszsamsKt+0etYirl15SzfsAMv0NR21ern+zCURC1aMx4/e3pD0cJBv9fVz+/DthTxiM3k8jhfOvNwbl/yAX5x8fES+I8ySfsXQgghhBBiP9Kz83llIsItj77BGw0dGGOKdv77G+031Pfra9Ta0VPL2dqaYVNzmm69/4rk40dD2PivL/mFgOFWkWnnmufu59OvPExEB7uuCcXv5p3BLaf+I02l1SPwzsMv5lgkoxaZXICvddhNn3C0njYGo8O1i3jEZmJZjGTEprHD7TPbo2cTxw7Xp6ndLUxiAMOL7zZz/8pNfPrEg3d7bQON4vvIUVOYVp0c5m9D7CkJ/oUQQgghhNjP9GzCdtXCWdzwwGoaUi6VyUihodtAo/2Goq9Ra9oYrrxvFYdOKMEYaE17NKdzmJGI5IfACXw+/crDXPPc/VRmO4rOrZh2FN84/VLW1M4apasbGscKGyS6vubt7Z3ori83/x2XxW0qE+GIPceyiEctFIp0zscYw7tNnb069Hdv0tfh+mxtyaBNuFtvVDjeMedr/uMvbzFjQsmgdut7/j42N6d55PUGfvbU+q7MFDXkfgJi+EnwL4QQQgghxH5uoN3X4Qq4ei44LH2rCS8wxGwbq2vKQHnCYUtLpjB3HsJ0//52/YeVMZy28SVufPIuZjZvKTq1qWIyN5/2GR45fP6YTu/vydeQz4vIj1bMX70Cmjs9LKUoj0eJRRTZnCaV9WjuzGFbip88tb5X4J1v0ucGQWFKhKUUXqALTRghXCT49p/X8YfPnjKohaP872P5+h3c+exGOlyfqmSUqG2RC3Shn4DU/Y8eCf6FEEIIIYQYB/rane9rdNtw6WsSQGkswtQqRUNblowXptqPQBl/L4c1vcdXn7yTU999peh4ezTBT+b/Pfccdy6uM/SeB6PFUmFw33PRJBySGMovqjS259jRniuczFdg2BYkYzZR2yoKvE+cUcPMSaWs3tpG1vNR+cC/x/toDWvr2wed/g9h1sBtSzfQ4frUlu9qPhm3bGrLLRpSLrct3cCJM2qk4/8okIZ/QgghhBBCjBP53dcFh09k3tSKEQ2w+psEUBpzKIvvGgs4krF/dbqNbz72Mx65+/NFgX+gLO4/ZhGnXf5f3H7CJ/arwB+6gu9+vrj8HdUmLAuAMODX3QJ/xwobKNa3ZvG1obY8RocbcNvSDQBcuWAmMcci0F3TF3q8fsS2iDgKrQ2/XrlpUM3/oHc/gaLrVorKZIQNjb0bEYp9Q4J/IYQQQgghxJD11+m9uTPHjo6hjxUcikjgccnKB3j6vy5nySsPY5tdHQefO/hozrnoR9zwkc+zo6RqRK9jpASm96KJYymijlVUtZD/j5YCp9tkBce2cGyFNoamdhcURYH3/FkT+Pzph+HYqvA+qut1IraFbSlAYVvQmHIHHax37yfQl70ZOyn2nqT9CyGEEEIIIQZFa1NUVnDijBpuPm8eP3t6A282tJMLNOmcv9sRgHvMGM5cv4IbnrqLQ1vqi069UzWFm067lL/MOn6/qOvvnsI/GIE2KBU2+8s/t9BXwVIoFHSl7xsTNgq0LXD9gGxOE3Ms2roF3ouPn86vV7zHmvp2IhZYloUi3KE3GAJtiDlhBsdgg/W+SkG625uxk2LvSfAvhBBCCCGE2K3l63cUGgrmfI02mmTUYVJ5nPas1xUw6l5p5MPliMZ3+OqTd3Dye68VHU/FSvjxyf/AL9//UTw7MgLvPLxsSxHooX9HBvC7npdf2sgvBPSs7jBdD1IKjAZfawgoCrwtS/EPJxzM//fHNWHTP8LnaBMG/pZSVCajGGMGHaznS0HW1bdTW24N+9hJsXck+BdCCCGEEEIMaPn6HdzwwGo6XD/cQc54XenbPltas0AYhFYknGEP/Cd0tvClZ+/j7197vCi9P1AWvzr2bH54ymJakhUDvMLYkq+ft9hVoz+QQqDPrhF/+e/YssCE+/Vd/z9/Loz+jQkXAGyl+gy8Fx8/nd++uIk3GtoJtA5fR0E8YjOhNEqHGwwpWM+Xgozk2Emx5yT4F0IIIYQQQvSrewf30pjDpuZ0n83oDNCa8YftfaO+x8Wr/sDnlv+Wslym6Nwzh7yPb51+CW9NPGTY3m9vDKXKwOrq0p8P/COWKuzq98UQBvno4jKBeMSitjzOjg6XjKdxrK7rMBAYA0YTBIaoY9OW9SiNOb0Cb8tSXH/2HK5/YDVtGY9kxCYesbEsaE37exSs74uxk2LPSPAvhBBCCCGE6Fe+g3tlIsK21r4D/2FlDB95azk3PPVzprdtLzq1oXoq3zz9Ep6e8YFRr+t3LIVj7dqK71nDb6neHfsVMKk8jtaG7e1u11PNbr9To8OPqwxMrojh+hqFwrEtakpibGvLkPMNtqWoLovSnvFx/QAFJKM2c6aU9xt4z581gW93C9bbXX+vg/V9PXZSDI4E/0IIIYQQQoygtdtStLp6vwyAtDas2tRCpxugFGS9kY385zas59+evJMTNr9edLw1XsoPT/kUvzr2bHx79EOYuBPWs0csBQTYliJpO9RWxGjP+uzsdAn6yOm3FOzsyHFQVYIpFjS0ufh9PC6/kGApsK0w3T/m2Bw2uYzfXXESK99tLgTrnjaUxx0CE6b3GwOVCYfJFWUsmjuZU2ZN3O3vrr9gHWD1lrY9CuDzYyfF2DH6f3OEEEIIIYQYh1Zs3AnAF37zCp0eRGzFzEml+03qc77B3xv17bS7Hh2uN6ga9T0xsaOZLz/zSz6x+gmsbvvnnmVz3/v+hh+dvJi2RNkIvfvQKMDTBscKd+0hTLOviNt882+P4vWtrXznkTd7PS/MFFB42tDUnmV6VZJON0Ab6HR9bCvs0J8LdjX1cywLMPjGUBpz+Mqi2TiO1WewPqe2jHUN7Xu8094zWO/e4NELzH73+xW9SfAvhBBCCCHEMFu+fgffeGgtn50FyahDSdwmF2jW1bdzwwOrufm8eWM6gOre4K8yGSGd80nngmF/n5jncslLf+Czz/83JV626NwTMz/Izad9hg0104b9fbuzgGOmVvB6fQov6D+zQQGOrdAGoraFr3WhTj9qWXz+jMMAuHv5exjA7qrtzwu0wepaAHB9Tcr1KYnanDxrIn/461a0NmjCaQB52hjAELXD1+/+m+lrZ324dtq73/+qZJSobe1Xv1/RNwn+hRBCCCGEGEbdG+RB2JjNM4q4ZVNbbtGQcrlt6QZOnFEzoiUAvq958LV6tramOagyyceOnoLjWIVr7K8e2/c13330TZo7c0wojWIMRB2LzuEM/o3hnDee5V+evpupqaaiU2/VTOdbp1/CMzOOG77364elwpT6j73vIK5dNJv/7w9r2Lijs2vePdi2RWnUJuMF5AJdePzk8hiOZaGMD3Tw/oOr+OQHpnHxL16k0/WxlArT9YOwnj+fxu8HmogdpuY3d+SIRiyeW98Ehq5FBagpjVGdjJL1NF4Q0Jb1OaqugsXHTx/x7wOKf7+15fHCuL59/fsVw0+CfyGEEEIIIYbRrgZ5UaC4S71SispkhA2NHazZlhr0Tu1AwXpf7nhmAz99egPtmTBV3wK+/tAaPrtwJnPrKvpN5wb47qNvsnpLK8ZAe9Yf9tF9x2x7k68+eScf2Lqu6HhzopwffOjT/PqYRQSWPczv2rd8o737nn+Pb338KH7w98fyjz9fScbz0Tr83ttdH9tSKBR+YFAqTM9HQacbFkJcesqhrKlPsa4+RdSxSOd8jAkb8nm+LqTxaxNmAAQaXBMQcRSl8QhRxy407WtMuURsi4ht0ZnTVCYiXLVw343Hy/9+q5LRQuCft6e/XzE2SPAvhBBCCCHEMGpO5/CCMFW7LzHbok0bmtO5Qb1e99rrnK9BQW15nE8eP53Fx0/vFRTe8cwGvvPImwTa4NgKp6vrfFva49///AbliQi2pXqlc3/xv18FIJMLMAxuBv1QTG7fwVeW/oLz1zxVdDxnOfziuHO4df4nScVLh/ldB6ep3eWL//0qf3NULVnPx/PDRRHLCnfp/cBgTLiFb1sW7VmfiK2YXVsKpAG44YHVNHfmUOTT/Q0RyxBxLPxAY7oWGgIdpvYnoxbTqpIopbrG6ykaU1kyXsC21gwTS2OjMh5vuH+/YuyQ4F8IIYQQQohhVJ2MErEVua5274YwoPa1Dhu4qXDueXUyutvX6l57HXMsMl6A62t2dub4//64ht++uInrz55TaP7W2JHlP55YT6ANUUdhqTCAsxRYSuP6hta0x5wppdhdu+sxy6I8bvNecxoFTK2M0571h+37iHtZLl/5AP+04nckPbfo3GOHncjNCy/m3eqDhu39hspSkMn5tLs+dy9/D9V1zNeGiFLhny3wfIjaihs/OofpNSVUJ6McPjHBI4/8mW88tJatqVyvkX2eBtuEqf75Hf+KRATbguqSWNHOemnMoWRCCa0Zj7Tr8+VFR/C3x9btdsd/qFkhu9P99xvvIwPDDfSgf79ibJHgXwghhBBCiGE0t66cmZNK2bA9BcCmnWlSufzOr0EpxRG1ZYVRav3pXntdGnPY1polMAbHUtiEu9FvNIQ79pPKYuzsyJHK+oVeA4aeAWBYeW6AVCagqsSmw/VpanfJekFhNF19yh2WVH9lNOeuXco/L/0Fde07is6tm3gI3zz9UpYfcuwwvNPe0QZU2FQfuv4RmPwCgEahUAriEZtk1OLYaVWFdHfXDXe/W9M5cp4u1ParXS9HYED7YblARTLC5R+awd3PvdvnzrpSiop4BNfXVJdGdxvEj0RH/vzvd119O7XlVtEChTH5xaPd/37F2NN3LocQQgghhBBij1iW4soFM8nHdhnPL+wem66a78Z2lxe6RgH2Z1fvgAg7OlwCE2YMWCrc0Xdsi0Abmtpd3mhoJxGxiNi7AjXP1wTGYDBoYwqd6QG8QNPhemxpSZPOFe/y5/y9D/3fv3Ud/3fvl/nxQ98vCvybkpX8y6LP8dGLfjwmAv+8oI8ah7BRn6KmNMrB1SUcUp0gMLD0rUZWb2lD63DxBcLvzAAR2ypaAMhTCiaVxfjJP7yPDx02sSgzpKfB7qzns0LW1acoiTlMKotREnMKHfmXr98x4PP7k//9lsZsGlIuGS9Aa0PGC2hIuZTGbK5csO96EIjhIzv/QgghhBBCDLMTZ9QwsTQGpLGUQoel+kQdm7K4jetrfvb0wB3T87XX2oDraxxLFe3Cqq7O8xCOhNvW5pLzd3XkN0DO10W70Hk7O1yaOnY1vNNm1yOsHiPqhqIu1cg/P/0L/nbd0qLjru3w8w98nJ+edAEdseSevfg+kv+GDeFOd6frk4jYbG0Nv9+7lr3D/Ss2MXNSKSfPqGQK4OkA27LD77nrC+/+FSoFnzv9ME45bCJam73eWR/pjvzzZ03g5vPmFbIK2nS48DQaPQjE8JHgXwghhBBCiGG2ZluK5s4wJXxaVQnNWZ9UxscLApo7NWB48d1m7l+5iU+feHCfr5Gvvc56AcaEAWR3gQ53my1FoXu8bUHQYyJfX3F898397osIsGeBfzKX4Z9e+B2Xv/gAcb+4EdyfZp/Mvy+8mM2VtUN/4VHQfddeKUXG02xpSRPoMPV/SkUcLzCsq29n0452vnRE+P0ZE2ZUdH9+/qvUGtqzHrBrZ/2GB1bTkHKpTEaI2RZuoGlNe4PaWd8XHfnnz5pQ6CUxXP0ExOiS4F8IIYQQQohhlt+1B9AYWjo9tDHYloVSYTCYCzS3PvE2MyaU9LmTmq+9Xr2lLQzQ6R5UGnTXtn1+9z5s6mdhoYfUqd/s4S4/hHX957/+JF9+5pdM7mguOvf65Jl844zLWDntqD1/g1HQPVNCQaFcImIpaivi2JaFbUFtucXO9nCUo4FCGn8+Fs9/r/l79uia7VxxahjU7+3O+r7qyG9ZSsb5jSMS/AshhBBCCDHM8rv2ADvaXbQJx+6prlBQKXCsMJ2/v/Ts/A7x9f/3Gp05Hz/QOLYCws7xlqUIum3T+zpsULcnLBWOn/MDM+hmfx/c/DpfffJOjm5YX3S8saSK7y64kP896nSM2v9ajNlW+P0ChX/GHIu6ygSlsV3hU7jDHgUy2EWp+7teSxHe65hjs70tU7QTvzc769KRX+wJCf6FEEIIIYQYZnPryjl0YgnQSdb3sS27EPibruZ7iYhFTWl0wPTs+bMmcNN58/j//riGd3Z04voGWxniEZtExGJHp7fX1+oocGwrrHEfROg/tbWB65++m4+++VzR8awT5Y4PnsdtJ36CdDSx19c1WrQxRGyLmtIIbRmfnK+ZMSGJY/cOsmNdO+8nHFrNE28VZz7kA3/HsphUFiPtBb124vd0Z1068os9IcG/EEIIIYQQw8yyFJecfCg732gk0GCUCevCCdPIbaWYWBYn7tiksn6/6dnL1+/gO4+8webmdCG9PzCQ9QJyvsbu1pyvZ535YJmu//P66T6fV+qmueqF/+aSF39PLCieEPDHOafynQUXsbVi0hDffezRBsriDl4AlYkIrh/ga3B6x/64Xd/ZOUcfxCtbUqRzGk9r6OrREI/YTCyLY1uKSKCHbSd+OPoGiAOPBP9CCCGEEEKMgBNm1PDwGxCxLDJBWPuvFCQiFhPL4pTGHDJe0G969vL1O/jif79KU7sLJiwTMIT9AgIT7tLXlsdpSefIenrIQT9AzFY4jkXW0+h+XsDSAf9v9V+47pl7mZhuLTr36pTD+cbpl/Hy1Dl78O4jpzRm0eEOvQTC6uqt0OH6fPCQav5pwQxuf2ZjvzvsbZkw8+Ijcyfzf3+tZ+22FJWJCIExOJZFPBJmBjSk3GHfiZeO/GKoJPgXQgghhBBiBB13SCWvbumgIhEhYocBoVJqwPRsrQ0/e3pDODGgq9NfoIt39bWB1kyO2oo4W1uyeIEOmwkOZRVAKaoTDvWe2+fpk957ja8+eQdHNr5TdLy+tIbvLLyIPxy5YMzV9SejFolIhKyX69a4z+DvZi1gclmMsniEzpyPF2i+vGg2x0yrxFKq3x326kSYDuA4VmEnvi3rFx6X9Ud2J1468ouhkOBfCCGEEEKIEXTpKTO48Y/r6HADKpMWxkDWDwYMCtdsS/FmQzuBNmHn/n4C+nROk8r45Kv1++rc33OUH4QlAhEbcr5mc2vvwP/glm3c8NTPWfT2C0XHM06M20/4O24//nwy0fhgv4JhZSmoSkZJ5wJ8rQsjDw+pTvKZUw5lek0JlYkItzz6Bq9tSRFoTS7QWMr0uTAStS0OqopTGosAYXO/xg6X1q5d/YF22K845WB2vrFit48byZ146cgvBkuCfyGEEEIIIUbQCTNqhhwUNqdzuH4wqF38nZ0Dj3NTpnjtwFYwqTxOzLHY0pIpjLIDKM928Lnlv+WiVQ8S1cV1/f839zS+e+qFNJSPTjq5Y4GtFEFXTf6UyjjZnCad8/ECw48++T6OmVZZePxVC2dxwwOrac/6VJVEsZXC15q2tEdnLqA87jChNEYitqsZI/TdKb+/HfYg8Hn4DXb7ONmJF2OBBP9CCCGEEGJM0NqM26BpqEFhdTKKpYbps3cfXE+YBdCYyob/mXAxgCDgk399lC89ex81mVTR01fVHcE3zriMv9bNHp7rGYBjUUjPVyq89LrKBK1pj6wXYLqOOZbV9VkMna7PoRNLmTuluHSi5068q8Og/tjpVbRlctS3uSSixYH/cHTKl514MVZJ8C+EEEIIIUbd8vU7CkGaFxgitmLmpNJx1bisv6Cwr0WPuXXlHFSZKKSe74l8zN8ze6BnGcEp77zCV5+8g9k7NhU9bkv5RL6z4CIenHNqGImPMMdSOJZCm7D5oDFQEnOoTIa9ErY0p/H8cMxhLgjY2pjB9QMANjd3cvEvXuz1e+lv0eWFjTuH1Cm/v9/nFaccPOLfixDDRYJ/IYQQQggxqpav38END6ymw/WpSkaJ2ha5QLOuvp0bHljNzefNGzcLAD31G1SeOoNTZ09kbUOqzzr+wdjd02bs3MINT93Fhze8WHS8MxLnZyf+P+784MdxI7E9e/M9YEzvmvxE1MJosC1FMmbj+pqIrdjaksEAccdmYlmMqGP1+3vpa9FlKPX5A/0+v/HQWj47ayS/FSGGjwT/QgghhBBi1GhtuG3pBjpcn9ryeGGUWtyyqS23aEi53LZ0AyfOqBk3JQB5/QWVf93cxqW/fIlkxO6ZsT8sKjLtfOG5X7PklT8R0UHhuEbxv0edwS2nLqGxrGaY33X3AgNBUPxps56mscMlYimOnlrJ5afM4Pt/eYuNTR1MLI2Faftdv5mh/l56ZgVUJsKGf60Zj9Vb2gpp/wP9Pps7wvIJPaQRC0MznsthxL4lwb8QQgghhBg1a7al2NDYQVUyWjRDHUApRWUywobGDtZsS+1XddRaG9ZuC2vn125LMW9adVHA1t+ih+8Zsl7YwE6hiFjgBn2+xZA5gc+nXv0z1yy7n6pse9G5lVPn8s0zLmN17Z5vY9sq3GX3A7NHCxaWChv6heMKDYEOO+9/5uRDOGXWRObWlbNmW4rGVJbJ5XHiEbvo+X39XnYXOOezApav38H3HnuzVwbGorm1A/4+K7oWDN5oaOeYg4d/weRAKIcR+44E/0IIIYQQYtQ0p3N4gSFq9z0rPmZbtGlDc3rgjvZjST5g27yjnS8eAV/4zStMm1CcTr56axvr6lNEbYusp4lHws/f1J4lMBCxFa4XsJvR9IO2cMNL3Pjkncxq3lJ0fHPFZG467TM8cvj8va7rD0wYvEcchR/oficVKMC2INC7shoU4XPDwNyAUSSj4XeyfMNOrjg1rMEfyu9lsIHzQGn9b21vJ5vTVHXr/N/z/QBaRuD3eSCXw4iRIcG/EEIIIYQYNdXJKBFbkQs0ccvudb6vsWtjWfeAbVJJuCucjDpFARvATQ+vo7kzh6UUSrnEHIvyeATX1zhWOJJuOAL/w5re48an7mLBOy8XHW+PJvjpSX/P3R84F9cZvu/WDzRRxyLqWATaEGhDWcwm4ti8f3oVyzfuJJ310aZ4CIEBPG0K3QkdSzGpPI5tqaKd/MH+XjY3p7nz2Y27DZx3V3aypTVDxgtw/YBEtHfo5AbhXepvcWBPHcjlMGLkSPAvhBBCCCFGzdy6cmZOKmVdfTu15VZRavVwjF3bl3oGbFErDGTjEYva8hgNKZebH17Hjg6X9qyPAhQGS1lkPE3Wc9HGYDAEe1lCXpVu45rn7udTr/wZx+xaRtAofnPMWfzgQ59mR0nV3r1JH7QBLzDh5+j6DKlsQEXS4h9POpifLX4/D75Wz9bWNGk34P4XN9Ga7n+iQc/Mj8H8Xo6oLeWR1xsGFTjvruxkQmmUzbkMOzpyTK2ye71fW9c0hiNqy4bl+8sbr+UwYnT1nS8jhBBCCCHEPmBZiisXzKQ0ZtOQcsl4AVobMl5AQ8rtc+zaWLW7gC1qw+vbUuHnzAUEBjwNgdY4ale3e38vAv9I4HHJi7/n6f+6nAtf/lNR4L98+tGcc9GPueEjnx+RwD8v0KZoQoFjK7SGG3//Oivfbea89x/EVQtnsXpbGxhwrLDMIWpbxByLmKMwhCUQWT8oyvwYzO/lI0dNYWPT4ALn3ZcR2MQjNjHH6vf98tc1nAZT3uDtZ+UwYvTJzr8QQgghhBhVQxm7Nhblm8otfauRjBdQmYz0ekxje5btKXfXc7qd8zUEGGyLPW/tbwxnbFjJvz55FzNathWderdyCjedfgmPzzphr+v690R1SZSJpbE+d9wnlEXxtSHrBdg2qK58CMcyuL5mZ0eOeVMrijI/dvd78bQZdF+AwZQRlERtrjptFo+uaej1fleccjA731gx/N/ZOCuHEWODBP9CCCGEEGLU9Ry7tjcjzfblaLTuTeXSuYD2rEfW09RWxKmKdzXx63DZnhp4h9YQLgLsiSMa3+HGJ+/klPf+WnQ8FSvhP+b/Pb98/8fIOb0XJPaVppQLJix/WL+9vWjHPWbbTCyLsbUlgx+ECyCqKwvC14aYY/WZ+THQ72X1lrZBB86DLTtZfPx0Fh8/vdf7BYHPw28M/3c2nsphxNghwb8QQgghhBgT8mPX9sa+HI3Wsxt7ZSLCu74m4wVsaU4TnZAAoKndJWxvN7xqOlu59tn7+PvXHsPult4fKIv7j/0IPzzlUzQnR78eXAPb211sS2EpWLZ+B6fMmlAI0EtjDgdVJWhqd3H9gPCjhDv3nz/jsH7vW3+/l6EEzvkyghseWE1DyqUyGSFmW7iBpjXt9So76fl+wTCNYezrsw3luoQYDAn+hRBCCCHEuLAvR6P11419ckWcrS1pvMDQ0JoB9jyTvz9R3+OiVX/kc8t/S3kuXXTumUPex7dOv4S3Jh4yzO+69wJtMAp+sfwdSmM21SVRtrRkOKgyTmnMoSRmk81pvCCgLetzVF0Fi4+fPuT3GWrgPFbLTsbqdYn9lwT/QgghhBBiv7cvRqN1Lydo7sixfnt7r6Zy4S52koa2LLnAH5bPVmAMi95+nhue+jkHtzYUndpQPZVvnX4JT834wKjU9Q+WrRQ7O3N860/riEdsOlyftxo7mFgWoyoRBQWdOU1lIsJVCwe3s91XmcdQA+fhLDsZTmP1usT+SYJ/IYQQQgix3xvp0Wg9ywm0MaSyHlEn7AbfXWnM4dCaJFtaOoDhyQufu30DX33iDk7c/HrR8dZ4KT86eTH3ve9v8O2R+Z/23b9O0yONQTG0zAZtwhcxylBTkqA05hSaIXa6ASVRe0g72z3vi2PB5IoEi+ZO5pRZE7n7wg+yrqF9UIHzcJSdjISxel1i/yPBvxBCCCGE2O/03O3d2eEOusP77l6rZ4DYVzlBKuvRks6xrS2DUuBYFr7WOJZFPGLRmvXwgj3s4NfNxI4Wrn32Xi547XGsbmG2ryzuff9H+dHJi2lL9D1j3lYQDEPNgTH9JxMYhroAYHBsRaBBG0NVSYSYo9je7lJTGuX7/+8YjplaOaid7Z73Jedrmtpdtre3snpLK3c++w5H1pVz5YKZLDh84qCvUIjxSoJ/IYQQQgixX+mrqd+k8jjamCGPRttdg8D+ygkqkhGaO3N05gI2NaexLVUIkqO2RdYPiPe+jEGL+TkuefH3XPXC/1CayxSde3LGB7jptEvYMGFan88NFyPC6+m1VT+Y93Ys4o6iLbsra6G/l9ld4O9YCttSeIHGGLDtcJSfUuG9endHGtcP0Nrw3o5Ovv7gWr6yaPZud/173pfOXEB9W5bAdC0uBIZ0LmBdfWrY+z0Isb+S4F8IIYQQ4gCzL0fhDbf+mvptbk7TmfPxtWZaVXJQo9EG0yCwLB7ps5xAoSiLR+jMBWgDSpvCd5jOBRigLOkw5LR/Y/joG8u4/um7mZpqLDr1Vs10vnX6JTwz47g+nzq5LEZrxiPna7whbvkrwLJgUlmcWz5xNGu2pbjl0Tfx9cCvM9BZW4GlwkZ/llKFLIFAh4ssO9pdtCGcAmCHow43NnVy/QOruexDM5hWnez399m9zAOgqT0M/COWQimFsg2+1lTE47Rl/b3u9yDEeCDBvxBCCCHEAWRfjsIbbgM19ZtSEWdTcwbXD2hIZalMRgfs8D7YBoEXzz+EdC4gYluYrln1SqlwQSGzq4QgMBB0BdyOAt9Auzu0hn9H17/FV5+4kw9uXVt0vDlRzg9O+RS/PvYjBH1kNUAYVMcjFkGn2aPpApaCI6eUc/3ZcwD49cpNlERtOnM+gQ7PazO49H7HgmTUpsMN8LUh5thUJCPsaHfxA4NthaUZ2oBjKxQKbcBShpKYzbbWDN94cC3lcYeoY/X5+2xO5wplHllP4/oapyvwhzD7wWgIjNnrfg9CjBcS/AshhBBCHCD25Si8kbC7pn6TymO0dLpMrUrSmMoO2OF9MA0C125r498feZP2rEe762OpMCV+Ylkc1w/Iertq+iO2QhtDoMPAH8Kd7MGY3L6Dryz9BeevearouGfZ3HPcx7h1/idJxUsHfhEFW1szGAMRS+HrwS8CxByLGz86h0+dcDAAF969kg7XZ1p1ks5cQFO7S8YLMIMoIbAVHFFbzk3nzWP5hp08uqaBxlSWXKDD3X8FNaURdnTksK0w8DfG4BdlAxiUgvJEBNtSff4+q5NRIrYiF2h8rXv1Jcj/2bGsAfs9CHEgkeBfCCGEEOIAsC9G4Y205nSOnK+JRwztWa/QXC//WWK2hWVZfOHDhzGhJDZgWUP3neO+eL6mJe2Fj3Fscn4ASpHOBWxuThcFmkoBXYH/UMS9LJevfIB/WvE7kp5bdO7xWSdw82mf4Z3qgwb1WhFLEXQF55pwRx3oM/3fBpQFWgMK/vWjc1hy0iEArN7SVrQoUhpzAMPm5kyv1ym8ntpV+19bEae5M4elFFcunMkVp84olJhsbk5zx7Mbae3MobXBssPdf18bui4X03Xt+YaAJRGnz9/n3LpyZk4qZV19OxVxJ9zpJ38dhkAb4hGbeDTMDOir34MQBxoJ/oUQQgghDgD97XQbY8LgyFasq0+xemsbx0yrHL0LHcCmnZ20dXXZB4Vl7dqJL405haZ+E0piu03v7r5zHLdsDIZsLtxFtpWisT0LwMTSGJ25gO3tQSGtX/fYATcGvCHk2iujOXftUv556S+oa99RdG7dxEP45umXsvyQYwf/goR19IEBC1AqrLH3A9NnQ76AcAHAthVH1Jbx6RMOLvSBWPpWIxkvoDIZCT8bhqb2XK/P3J0hbOwXmHCnPe0FhV32nmPqZkwo4buPvsnqLa34Okz1T0QsyuMRmjpcbCuftm9wusoD+hrVaFmKKxfM5IYHVtOaCReCckGArfIlBIqJZTEw9NnvQYgDUd9LnfvIM888w8c+9jHq6upQSvH73/++6Lwxhq997WvU1dWRSCRYuHAha9asKXqM67p8/vOfZ8KECZSUlHDuueeyZcuWose0tLSwZMkSKioqqKioYMmSJbS2thY9ZtOmTXzsYx+jpKSECRMmcPXVV5PLSWqQEEIIIcaHvna6O1yfd3d28l5zJ03tLs2dOW54YDXL1+8Y4JVGxx3PbOCmh9fhBWGQGxiDHxgyuYCtLRnasx6taY+Zk0p3G+RpbbrGzEVp6nBpz+Z4p6mTd3d2sKk5zcYdnWS8ME094wU0d7oMVy7E+7a+wf/d+2V+/ND3iwL/HckKrl/0OT560Y+HHPhDuABhK3AcFQbCfvg9han1uzhWWL+vUEwpj3H92XN4YeNOLrx7JVfc+xJ3PvsOqYzHOzvS7Ox02dmRI+sFvV4HdqXZGxNmGyhFoelef7vs82dN4HdXnMS8qZWURB2mVyU5pKaEqGN1TRQwXX0CwqyOvJht4fVI3Z8/awI3nzePI+vKSUbD54flAxZTKuPYlqIh5fbq9yDEgWpUd/47Ozs55phjuPjiizn//PN7nf/ud7/LD37wA+655x4OP/xwvvWtb3HmmWfy5ptvUlYWzjO95pprePDBB/nNb35DTU0N1157Leeccw6rVq3CtsOGKIsXL2bLli088sgjAFx++eUsWbKEBx98EIAgCPjoRz/KxIkTWbZsGTt37uTCCy/EGMOtt966j74NIYQQQoiR03Onu8P12dqSCUejWYp8hfjW1syYq/9f9nYT33/8LVxP41gQ6HC32RA22jNas7U1Q11FfLdBXveGh51uQLsbLhr0xdeG+rbsHjXQ66ku1cg/P/0L/nbd0qLjru1w9wf+lp+edAHtsZI9fv1CJ/3A0L2SQXeNvvPyWQAmDP5tS3HZqTPZuKOTW598G9fTTCiLUpmIsMELyHgBmdag0OjPUv03+zOEmQeJiE0mF3BkXXmfCzDdp0x84rip3PHsRtqyPspSWGHtBH4AthVmc3TPUOlvVOP8WRM4cUYNa7alWLZ+R6HHQDoXELF0n/0e9rX9ebqGGF9GNfg/++yzOfvss/s8Z4zhRz/6Ef/6r//K3/3d3wHwi1/8gsmTJ3P//fdzxRVX0NbWxl133cW9997Lhz/8YQDuu+8+pk2bxl/+8hcWLVrEunXreOSRR3jhhRc44YQTALjjjjs46aSTePPNN5k9ezaPPfYYa9euZfPmzdTV1QHw/e9/n4suuoibbrqJ8nJJERJCCCHE/q17jfTkMlU0Gg0VBtTxiMNBlXG2p3Jjpv5fa8P3HnuLnK+JOApbWViWwe+aG28Ig9OICoPZgYK8ng0PK5MR3tru7zalfW/YmQxXL/09l6x4gLhfnFX68OHz+fZpn2FzZe1evkvYcNDXBm1AB7ua/eXHEEZtxYTSGFHHwlKKnZ05frNyE283duIFGtsKFztKYw5Bt/F++f/YfeKfRbjT3/1rCxcULMriTp8LMH1NmagpjVIed9jZEWal2JaFNoa6ynhXr4FQf6MaC+/dVVowb2pFUY+BsRBo78/TNcT4M2Zr/t955x0aGho466yzCsdisRgLFixg+fLlXHHFFaxatQrP84oeU1dXx1FHHcXy5ctZtGgRzz//PBUVFYXAH+DEE0+koqKC5cuXM3v2bJ5//nmOOuqoQuAPsGjRIlzXZdWqVZx22ml9XqPrurjuruYsqVQKAM/z8Ly+V5DHgvy1jeVrFHtH7vH4J/d4/JN7PP6Nxj2+4pSD+cZDa9mRymB0QNLp2i02YVBSVxElZsHEEofNO9pZvbmZI0e5TnrtthQNLR3EHYiosBYcwNgqTDc3YQp/edxiakW03+9Ta8Mdz7xNzvOYVhFHKcjkAhylsfuenrdXlNF8YvWTnPGf95Jobi46t2byDL794Ut58eB5AMSGIbcgYkHCVuR02HWwe7AedyxqKxKURMMP2pL28HyP+hYfR2kikbAMQAdhFkTEgrjd98SAiBWWFbhBUHgPBVQmHObUlXHJyYfywYMriu7Dio07+cZDa+lwfSoTu6ZM7GzPUhK1uGrBoUytSrClJcMvlr9DZ87Hd1RhVGNbxqM6YXPFKQcTBD5BMPB3ccTkJJAEGNTj98ZAf4/7+9wbtqf42h9e49/OOZITZtSM3MWJYbE//PfxYK9tzAb/DQ0NAEyePLno+OTJk3nvvfcKj4lGo1RVVfV6TP75DQ0NTJo0qdfrT5o0qegxPd+nqqqKaDRaeExfvv3tb/P1r3+91/HHHnuMZDK5u4846h5//PHRvgQxwuQej39yj8c/ucfj376+x5+dNdDZ4v8B+e6ry3j31ZG8msG5ft5gHhXQ9tZKHn6r/0d8vAaoAejWuX7mXl1an6rXrmXeXXdRuWFD0fFsVRXrPvUpNp12Gv/Ptvl/jGBUWiSg570dmfdoZOcbjTz8Ru+zu353fUwNaFpNWxOUAZ87rP932PnGij5feyzo7+/xQJ97LH8e0dtY/u/jdDo9qMeN2eA/r+fcVWNMr2M99XxMX4/fk8f0dP311/OlL32p8OdUKsW0adM466yzxnSpgOd5PP7445x55plEIpHRvhwxAuQej39yj8c/ucfj32je49e3tvG5+18hYisSEYd41Cpq5pbxNJmcz48/+b4xsfN/9a9fJpXxcbUmolTR/z4LtMY3hqPqKrjvkhP6TfF+bv0O/vWB15lYGqOriTw7O3M0pLLDdq1TWxu47sl7+NAbzxUdd+0Id5/wcf7rpE/QGUvCqmF7yyLdO/vna/VtCw6uLiFm27iBprnTJZX1wu/QhE0B+xLrahygjWFaVQmdOZ/G9rD/gaXAVoqIZeHYFlUlkX53sdduS/GF37xCMuoUNfDL6+u3prXhjYZ2WtI5qpJRjqgtG3Tq/t48d0/09/d4Tz63GJv2h/8+zmeg786YDf5ra8Pap4aGBqZMmVI43tjYWNilr62tJZfL0dLSUrT739jYyPz58wuP2b59e6/Xb2pqKnqdFStWFJ1vaWnB87xeGQHdxWIxYrFYr+ORSGTM/jC621+uU+w5ucfjn9zj8U/u8fg3Gvf4mOk1zJhczrr6dkoTNr4pHv3X1OkzZ0oZ86ZVj3rN/7xp1UyfWM5fN7fha4Nrwo71GEPQ1SAu6lh8/sOzicWKm8F1b7TWktEEBnZmfCylCLTB1+AGe//5Stw0V73wP1z64u+JBcU77FtOOYV/PPoiNpZ11fXvo81+i3AhIIKiscPHsgIilqKmLMGOdACEo/S8rj4BPUcCBtpglCIRsbFsi51pr/Bd1ZREqUhESHSVETSkXG5f9h7zD5vc6/fS6mo6PSiJ23im93dtWYpO36fV1UV/D445eOjp8KNZX9/z7/Gefm4xdo3l/z4e7HWN6qi/gRx66KHU1tYWpVfkcjmWLl1aCOyPO+44IpFI0WPq6+t5/fXXC4856aSTaGtrY+XKlYXHrFixgra2tqLHvP7669TX1xce89hjjxGLxTjuuONG9HMKIYQQQuxr+RnppTGbhpRLxgvQ2pDxgjE3Gi1/rdUlEeIRh6it8AKNG4SBP4Sz5X/w+Nsse7up8Lzl63cUxtdd999/5Vt/WsuOTo/NLRk2NafZ0pqhIeX2866DvDYdcMFfH+PpOy7nsy/8T1Hg/+qUw/iHJd9h1XXXsbWy/82kkRJxFAfXJCmLR5hWneSW84/m9iUf4JJTZoAxWEphqXDnPh/4d7/b2oS7+xPL4rSkPdI5XVgcaMt6bG/P0pkLUEpRmYywobGDNdt67z52nzLRl/66+A9VvpnjuvoUJTGHSWUxSmIO6+rbR2V85b763EIMxaju/Hd0dLB+/frCn9955x1effVVqqurmT59Otdccw0333wzhx12GIcddhg333wzyWSSxYsXA1BRUcEll1zCtddeS01NDdXV1Vx33XXMmzev0P1/zpw5fOQjH+Gyyy7j9ttvB8JRf+eccw6zZ88G4KyzzuLII49kyZIl3HLLLTQ3N3Pddddx2WWXjen0fSGEEEKIPZWfkZ7fKW3TYef/sTAaraf8tX77z+tYV58qamYHkM0FvLallUt/+RLXnnk4c+sqirr6u37QNdYwfPxwjO47cdNrfPWJO5nbuLHoeENpNd9ZcBG/n7uQqKP45D6r69+lKzECpRRVJVEaU1lqSmPMm1rBzg4Xy1JobTCWwVYKHKswPSFPKZhQFkVrw/Z2t/CdOXY4li/jaba2ZDioKkEyYtOmDc3pXK9r6T5lorbcKirZ2F0X/8HS2nDb0g10uD615btGBMYtm9pyi4aUu8+nV+yLzy3EUI1q8P/SSy8VddLP189feOGF3HPPPXzlK18hk8lw1VVX0dLSwgknnMBjjz1GWVlZ4Tk//OEPcRyHCy64gEwmwxlnnME999yD3a1t669+9SuuvvrqwlSAc889l5/85CeF87Zt86c//YmrrrqKk08+mUQiweLFi/ne97430l+BEEIIIcSo6T4jfayMRhtIW1dw2TNF3QC2AtfTfP/xt5g1saQQCHbk/KLAf29Nb6nnhqd/zkfeer7oeMaJcfsJf8ftx59PJhrvdmV7TnX9vwEmEfbiWArHUnja0JjKMKksTmcuYNWmFubWlVNTGqM8HqEt4+EHBtsKa/gjtoUfGMAQj9gcNqmU7aks29oz6K7VlogddvqHcLqApw1N7Vkml8f73cXOZ27c8MBqGlIulclIoYt/a9obliyTNdtSbGjsoCoZ7dWvq2dmwrypFXv8PkOxLz63EEM1qsH/woULMQP820wpxde+9jW+9rWv9fuYeDzOrbfeyq233trvY6qrq7nvvvsGvJbp06fz0EMP7faahRBCCCHGk/yM9L3RvbZ+JBYQ8ju7qayP6hb6dw+OtQlT3V1f80ZDB4fUJOnMBWxtHp7Av8zt5HPLf8vFL/2RqPaLzv3+yAV8Z8FF1JdP3PPXjzm0u36v46arHt+ywj4FeT0XQLofR4W7/+mcZlNzBoPhp0+u54l127nsQ4cyrTpJZnsKrcHXGlAoBfGIhWMrjp5ayd0XfpAHX6vnW39aSyJq05r2yHoBBoMibLroWOD6mp0dOeZNreh3F3uks0ya0zm8wBC1+65ojtlWv5kJI2l/yq4RB4Yx2/BPCCGEEEKMfSPRZK3nYoI2hg2NHSSjDu3ZYFd9etf6gqJrd7wrUA60IdCGpg4Xv2eNwBDZOuCTf32ULy77FRPSbUXnXq6bzTfOuJxX62b3ep5jKdQgdv7zgX1p3KEz5/cqabAUOF1BbaANjgKUojzu0JbxsBR43crKPW3wtSm8szaGZNSmIunw181tXH7vKqK2heuFNfwR26Ii4RBzbDJeQGnM4coFM3Eci+rSKJZSVMQjRGyLrS2ZQrZAOCwgfK+YY+12F3sks0y619fHLbvX+dGsr9/fsmvE+CbBvxBCCCGE2CP5Jmv52vqobZELdKHJ2s3nzRvyAkD3xYScr0FBSdQhlfGZWBbte8u72+6/UgpjDO2uT8YL9irx/uR3X+WrT9zBETveKzq+tWwi/77wIh6cc2oYBRdfCoYwUI9Gio9biqIsBMcKH5uIWCQjNpYKFwwc28ILNI6lsCyFQqG7smUDA8mIRVUySlvWx+tjcaP7EcdWTCqPE2jIej5eEO7cT61O0JjK4foBOzpyVCUjHFlXUbRo0z2oLo05HFSVoKndxfUDjA7fKWpbfP6MwwZ1n4cjy6QvY72+fqQ+txBDJcG/EEIIIYQYspFostZ9MSHmWGS8oJBWboBca4CtFGHyOah8CkC+kZ8xRB2LQEHaDein0fpuHdq8lRueuosz168sOt4ZiXPbiZ/gjg+ehxvpPe4ZwmAbwoWIyWUxoJPSqE1LVhft6juW6upVEHbUj0cslAoXL2orYtS3ugTGoAwY9K4ddxS2ZRV23rvra13koMoEJVGbd3d2Epiwbt/XmohlM3NSCRk3YEeHy7TqEu6+8IM4jlXIvNjR6TKpPM6WljS15XFKYw4lMZtsTuMFAW1Zn6PqKlh8/PQ9+6KHidTXCzE4EvwLIYQQQoghG+4ma90XE0pjDttaswTG4FgK2wLXN+S6GtLlGYr+iGWFnegnV8Zp6cyB1/NdBlae7eALz/2af3z5ISK6uEv//xz1YW45dQmNZQPPnzfGYHd10+/MhjX8P/z7Y9nUmuPXKzexpSVDe9ZDG0PMsZlUFsO2FNvbc1SXhGnpna5mQlmUtrSH62uCrtF8R04p49xj6njm7R28Ud9eFOhHLIVlga9NYdHDtsIGfVlP4/phJoFS4AcGX2sUNsmYw0RL0ZjKsq6hnfasV1TGoY2mMxewuSXNxLI4sXAFgs6cpjIR4aqFYyOolvp6IXZPgn8hhBBCCDFkw91kLb+YUJmI0JAKA/+IpboWFhSOpQes37etsL4962ta0h5D2fR3Ap/Fr/6ZLy67n6pse9G5lVOP5BtnXM7rtbMG+WoKv+vND55QAricNHMCp0YiLD5+Omu2pVi2volH12xne1uGtBcQCXQhSAUKAWwiapOI2tSWx/nk8dNZfPx0LEtxySkz+OUL7/HDx94iEbVpz+bIBWHQH35bYeAP+YZ++dF/u/6Z79oPu+7VsvVN/PbFzb3KOLwgTPVv6cxhWWrMBtVSXy/EwCT4F0IIIYQQQ9ZXkzWDIZvT+FoTdO28DrbJWn4xQRvIegGWUmENP+Fuv97NvLtAhyntk8riVCYipLIe7dne3fN7WrjhJW588k5mNW8pOr65YjI3L7yYP88+uVddf38cCyaURml3fQ6bWMYvL/4Ajz32SOF8vvZ73tQKrjh1Zr9B6u4CWMtSHDe9ipKYTTJmUxJNkPbCTIVExGJ7yiWTC1Aq7MZvq3DHX2PQGuIRm3h0V/Cfb4j36JrtfZZxTK9OUN+WZVp1kmvOOIya0tiIBdV7OzlC6uuF6J8E/0IIIYQQYsh6NlnrzAWFZnC6q9t8eSJCW2ZwO//5xYS2TK5r53xXin/3WvaorQgMTCiJUhpzMBi2tGTxAs20qgQlsbDLnreb+X6zdmzixifvYuE7q4qOd0QT/OSkv+fuD5yL6wytO7yvoSHlYluKwGhWbWrp97EDBamDCWDn1pVTUxrljYb2rtr/MMCPOTZRJ7wfGGhsd1HGoOkah2gpJpbFukYm7mqIN7Uqwfa2TL9lHFUlURpTWWpKYyMWXI/E5AghxC5952kJIYQQQggxgHyTtdKYzeaWNJub02RyXTvtiq66d7jx96+zfP2O3b5ePphtSfcu1C8K41XYNb8sHiEZc7CUhTEGS1FoqNfU7tKQyvb5PlXpNr7++G088vPPFQX+GsWvjz6L0y77L/7zxE+go1H2dGO7MuFQ3+byjYfW7tkLDMILG3fS2O4SaIMxYIWl+KRdn5a0hwJiTjg9wNCV7g9EHavQkyDjBTSkXEpjNovm1uJrBizj8IZQxjFU+WaP6+pTlMQcJpXFKIk5hckRg/kNCSEGJjv/QgghhBBij8yfNYFvffwoPvfrV9BdTekAEhGbiWVxSqJ2v13/e6Z3z6ktA8IgdSC+b0jGbOKRMEj1tUazq47dGENje+/APxJ4LHn5Yb7w3P1UuJ1F556fPo9vnn4ZayfPKBzz9nBSAEAq43NQVYIO1y981uGUb44YaMP06iQ7OlxcXxcyLiAM/GdNKiPrhWUYtlI0dbhYliLt+r0a4pXFI9z7/LtFZRzd5UsDBlvGsSefZzgnRwghepPgXwghhBBC7LGKRJSEY1FWmSh0lw/H1oVBWl9d//tK755UHmdba5aoo3D9/oNlDUwojRVe31aqa8RfWMfemvaKRuphDGdsWMm/PnkXM1q2Fb3Wu5VT+PZpF/PoYScNuq6/P/lnGyAwJhyfVxGOA3yjoZ1jDh54SsBQdJ+0EI/YlMYcsp6mM+fT1O6iFAQGsp4mEbWBMJifZCk6sx5fXnQE1aXRopp6rU1RGUf31P98acCcKWXMrSsfts/R1+cZjskRQoi+SfAvhBBCCCH2WHM6rNGvLon0uSvbs+t/Pr27Z0f5jU2ddLhhyn/MsdDG4HeltPfka4PWJpzjnvGIOhZRR4GBtsyusoHZTe9y4xN38qH3Xi16fiqa5D9O/iS/fP/HyDmRXq/fvcfAYI/nT+Y77bu+Ljz2lc2ttLp62LrP95y0oJQiEbULnf0tFTZADP+8axc/Zlu0GagujbLg8IlFr5kv47j+gdVsac2QjNjEIzaWBa1pn9KYzZULRmas33BPjhBC9E2CfyGEEEIIscf66vrfXfd08YHSuyeWRmnPehgolBDEHIUxYSmAwRS6/6ddH9cPX/fIunJOPWwCv1qxic0taTqyPjWdrXxp2X188q+PYZtd+fuBsrj/2I/ww1M+RXOy/x3k/gL8iGPhB5o+s/hN+DxL7Qq+W7uaHd729HqygSJqW8yuLeOqhXvXwK6/79yxrLCrfx/j/GBwqfvlcYf61iyprkWUiG1x+ORSrj97zog13RvKb0gIseck+BdCCCGEEHusZ9f/3uniOaZWJdnR6fKHV7f1m94ddNvi9wKDwoQBrG1hqbAGP2pbVCYcvvKROb3S1udMKeeL967g8hX/x2eX/5byXLro9Z89+Fi+ecalvDXxkH4/y0ABfsSxsJUC2yLnFzcEMN2e73TtXhs0rV3NCztcj6wfduNf8U6Otxvb+eEFx+5xMN3fdx6PWERti3QuIBktHue3u9T97hkZ06sThZGL6VxQWAgYKbv/DY1cyYEQBxIJ/oUQQgghDlB7O1MddqWL3/DAahpSLpXJCDHbwg00Te1ZXF+zubmTr/zPawRa0+76RByLWMQimwub0eUCzY724pTufIf6nK+xu6YHRGyLWZPL+Ntj64qv0ximPf0oD/z0K0xtri96nQ3VB3HTaZfw5MwP7rau37YUtlJYjoXWkAu60ujJZ/UbVNef8+F/vhQgDPzD7vqeH47Wc7o2sW1lEenKYvADTVO7y7f/vI4/fPaUPUqjH+g7ty0L29I4tiLr6cLx1rTXb+p+fxkZJTGHamNGvOHeQJ9noOvel4bj74oQo02CfyGEEEKIA9BwzlSfP2sCN583r/B6bfmafF8TtS2qS2JEbYtU1qM147GlOU3UsQo1/UHXNrttKbQxvXbdDRCP2FSXRHoHga+8Al/8IgcvXVr0nLZYCT8+eTH3vv9v8Ozedf39MeSvSRfq98EQaB2Oy1Ng24qKmBM21gsM0YhVKEXIBeFCQH6RAMBSCmXCnf+IY+H5mre2d7B6axvHTKsc0ned19d3HrEUx0yr4NTDJvDM2zuKjue7+vd1b8dCw73+Ps9A172vDPR35YMHSwNCsf+Q4F8IIYQQ4gDTX9O9/Ez1m8+bt0cLACfOqGHNthQ7O1x+9MTbbG7upDIRxQvCwLk84dDUYZH1NBlPE3MsjAob+EH4T8dSVCZs0jkfT3eN/jMwY2IpX1k0e9d1NTTAjTfCz39eNB8wsCx+84Fz+N6Jn6QlMbQ08XAxIiw3sCzFxJIol5xyKEvf2sGbDe3kAl1Utw8UgsJkNEIyCpPKYxxaU8LDr9fj9LEzrFDYlsILNK9uat3j4B+Kv/OeO9KXnDJj0DvVw9lwb292yAf6PKNld39XvnXunFG7NiGGSoJ/IYQQQogDyEjOVLcsxbypFaze0sbm5jTpnCaVTRd2zKO2Vdjlh3B3vSdfG5rTPgqoSjqUxaO0ZT2+8OHDwsA/m4Uf/hBuvhk6Ooqe++pRJ/FvH7qYTZMPLur6P5D87r5lKfxAk4g6JCJ2IcA/cUYNxx9awyubW1EGjp1eybyDKgrfzfGHVPPga/VsbU1zUGWSjx09hftWbuLh1+t3zf/r600BMwwxbf47H+zxvgxXw73hyCYZynWPtMH8XbnruXf4+PBNcRRiREnwL4QQQghxANkXKd7L1jfR2rVL7NgWygo357NeQNAtpd/vHfsXGKA57eNrQ2kswoRkFP7nf+ArX4F33y1+8Jw5/Pni6/hyRx0dbgBDaFBnW4pp1UkSjsW2VJZLTzmUBYdPYm5dOS9s3MmFd6/sM5g9cUYN96/cxK9XbqIx5QIQsRX/98oWzjxyMo5lEeig9+cyhiAwOJbF+/Zi1384DUfDvZHIJhltg/m78k5TJ0jwL/YTEvwLIYQQQhxARnqmutaGR9dsRxuw7V0Z+YowYOqeoj8YqWzAae3vcdTir8GyZcUna2rg61/nzjkf5t//soFABzhWOGZvsO8SscMUfFtBMmKz4PBJzJtaMWAw+8X/fpVk1GZTc4ZAG+yuqQTl8Qhrt6XY1JzmoKo4Da2d4XdiTNe4QvC1xgCza0uZd9DY2OHeXcO9kqjForm1PLt+R5+p+COZTTKaBvN3JeMO7fcsxGiS4F8IIYQQ4gAy0jPV12xLsWlnJ0qBH0C+L36+K/5QTG7fwVee+SXnv/5k0XHjOGz99CW0XXs9hx0+lZ/8+xME2hB1FJaycGyDF2iCATIL8jKeZktLBgUcMiHJ3LryAYPZ0phmU3O6aFEjMBD4mqYOl3jEwgsMB9ckqCmJAhkCYwpZDpZSVJdGuf7ssFZ89Za2MVHf3l/DvSkVMQB+9tT6flP5x0LDwJEw2L8rQuwvJPgXQgghhDiADNdM9f4auy1bv4PWPtLuhxL4x70sl618gCtX/I6k5xade/mYU/jOGZeyseogIg+upzT+LqmMh2OHgX94beH/DYUB3tuZ5q5lGzlxxoQ+g1mDYUdHDkz/nyfraQJt2Naa4YtnzIKm1VQkInR6YZbBEbVlXLVwFkC/JQWjlR7fs+He5uY0dzy7kc7dpPKPdDbJaBnM35V5dSVA5+hdpBBDIMG/EEIIIcQYN5wzxruneNe3ZUlEbWylCIwhkwsoizu7naneX2O3K06dwaNrGsL3UfQa2bdbxnDuumf456fv4aD2pqJTb008mG+feTmvHfEBqktiTOoKRLc0Z8ISA5N/CVNIrR8qbeDHT65nRk1Jn8FsNqdx/QDVI42hEBN2LQpobUhlfeoq47Q3wW2fOo5WVxfu3QsbdxZKCiqTEbQO+yGs3trG9Q+s5tvDWB8/1N9OvuGe1oYL715J5yBS+Uc6m2S07K4cojRmc8nJh7LzjcbRvlQhBkWCfyGEEEKIMax7oJ3xAiwVNqi77qzDOeWwiYN6jZ4B4IkzavjUCdP56dMbqG8Ng2eloCTq8A/HT+838NTacP/KTdz65Nu4nmZCWZSYbXftBqe46r5VpL0AbYYe+L9v6xt89ck7eP+2N4uO70yU8/1Tl/C7Y87Ct2wOTUSJR2xMVx19ImqR9gI8bUCF2/35996DFgN0ZH2+/qd1aGN6BbO+DkcWdq9hUNArDUCp8LtqS/tYwJF15UQikfDaupUUlMYcGtpcXD/ouk5Dp+vz7T+v4w+fPaUQpHe/f5WJ8HVaM95ug/m96b4/lFT+oWSTDOdC1r7QXznEnCllXLlgJh88uIKH3xjtqxRicCT4F0IIIYQYo/JN51rSOXK+wQvCILElnePSX77EtWcezmWnziw8vq/A6oWNO3sFgDWlURrbXYw2OLaF19Uhr9P1+eH/z96dx0dVnY8f/5x776zZE5awKyCIgGvdUAHr3qpV+61tba2lirTa1rWLa621uLQu/Wm1blXr2lVb24pbK2pRcUMREASUPSRAkkky213O74+bmWSyBxJIwvN+vVrhzp07Z+ZOgOec5zzPSyswFDnXzYzl7ldWsvDTar9AnuG35RtcECKRdv10+O0wLFbFT+Y/zGlL5+ccTxsWD33uVO6a9lXqQnkAGEB9yiFhu9QmbJKOl9M60HZbROHNfmsZCqeLMxKbauKYpoHjeYwqiWaDWcswAI1utqWgrSt6nr9qvKEmzij8+5KRCapDlsnGmiSe1piGauyI4LcbXLqpjicWruWbh43JCeAbUi4J2888CAdM8oJmu8H8jlbf704qf1dWyL83Y1yb38VdvdWhK1puh2g+aWHbXe8sIcSuJsG/EEIIIUQflFkhro6niadcNGAaRnZVOWV73PriCiYNK+TIvQa3ucqbCfJdT2cDwJTr8nFFHa6nsxX4A2b71wV4/ZMqfvSXD4kl0rieh2WCoQyStsvabfGcALyrIukk333rr5y/8G9EnNx9/fMmHM6NM2expmR47mei8SctuvgamfMMRZcDf/AL+AVQpByPiliS4miQkGmA0iil6GxTgQegNY++sYYr94XvPv4us6fvlbM/Pp628bTGMhXKzx9AKbBMRdrVPLVwLXuURbn6mY+oTzmELIOE7WQ/67inyQ9ZbQbzPVF9v7up/J2tkAP9uhVgZjuEEP2ZBP9CCCGEEH1QZoU47Wg05ASJpqFAeaQdj1+/sAIgGyRmg3ynKcgfXRolHGgM4ByF1jqbGh8y/Qr0bV132rhBLFi1he8/+T6xxiJ+ngbtgjL9MSXt7lXWU9rj9CX/5cfzH6G8flvuex4yll8ccx5vjt633ed3d5phexPKNX7rv5ElUSpjyWwwO3FoAR9XxLLV+9sTsgzKC8NAkuUV9dkANxMspxzXn8xpNUKFqaAiluTXL6ygPuUwtCDEmm1xf1LCNECB42pqEzZjyiJsjqVzgvmeqL6/PYUh21shB7+44UBrBShEfyPBvxBCCCFEH7QtniZhu9hu20GigUIpWLu1IRskNg+sMmGvArbUp8kPWyhUYzG8pk3rmqY+9EqRzQZYu7WBJxau5bf/XUksYfup6UDa1XiA7XoY3YzED1q/lGtfvp/9Kj7JOV6VV8yvjvoWf5l6DF4bq8w7QtP9ff9+m0IPL2Bw0bF7MSgvlA1mPa35zsNvU5d0SHfQS7AkGsQ0/XswtCDEulo/QH/onIMZUhhiS30K08gUEGgcq9Y4niZsGTiux9qtDZTlh0g5mpTjYRkqe39Nw59ASNm6VTDfE9X3u5rK3zJYb2uFfPH62gHZClCI/kaCfyGEEEKIPqg0GsRQKhuU5wToyg9qDSDtadZui5MXNKlPOViGQThoZIvTmYYi5bgk0x6RoNm4b72J7Wj8JnZNYahh+NX/n1y4loaUA7qpeF5m2kADHcS+OUbWbuanrzzMyR+/lnM8ZQZ44ODTuPuwr9AQiu7Ix9WjXA8w/M93UF4oJyCdv6IKQynGD8mjJm6zLZ7GcXXj55HZSgFBq+lzVopsgLusoo6vHzKan/1jCY6rscymqRjH05hKURQNkGpsGRg0DRrSTvbeN7+m9vwihHlBKyeY76nq+52l8nc1TX+gtgIUor+R4F8IIYQQog+aPLyQUaVRtjWkSdpeNkDMBugKgpYJniaWtokl0tCYDRCyTAojlh8sNgsSwSQcNAiaBgnPhWbXbN69zvM0WmsqYylClkEdkHa6v68/LxXngjf/zHlvP0PIzS2M9s+JR3LTzG+zvri8+x/OTuBpzeiyvJy0dmgKrOuSDkHLYERRBJTfJWBLfQqjMfpvOcnSPMA965DR/PHttXxcUZczqRMJGAzKD1GfchlVGmVzbYK062E11npofv8zz7EMo1Uwvz0p++3pqNhdVw3UVoBC9DcS/AshhBBC9EGGoThpSjkfrKsBmgLzzH9d7Qdyaa2zFeNNw88USNouKdvFNBW246GUnwGQSLs4nkdxxCJhu9nXahnWa2hMNbdxPN3tffaG5/J/i1/mR6/9gcENNTmPfVg+nl98/jzeHjWlm1fduQKG4vLjJ7QKcmsTaeK2Syxho/DvU2ayxTAUnqeJBPxJluafbPMA1zAUV5w0iSv+9iG1CYdI0CQSMFEKahMO+SGTy4+fwL2vrmbZpjqGFgQbC/55BAxA+VkG4YBJKKDYHEvnBPPbm7Lfnh0tdteTkxFCiO0nwb8QQgghRB/keZrXV24hEvCDvuYBeGaVPu165AVNAgYkHQ9T+8X7lOkXhEM3hZ8ba5LZVoHtFb7PrioDqc4q2jUKGNC85t9haz/kmpcfYHLl6pzzNueXcsv0c/jblKPRqu30794UsRSJbmQvfOOwMdluBxkLVm7h6mc+wvP8yRavsZhAIu2QSDt+lgUwKD/YWKOhsa6CplWAO238IG48Y99sSn1dymmVUm8oxZVPL2ZzXZrCSIC0k/LbMuLf56JIgM2xdJvBfE+l7PeEnp6MEEJsHwn+hRBCCCH6oEzF9hElUWzXY3Ms6ReYa0z3Ng0D2/EojgaxTIMN1QlsT2MZZPedp12P/JBJ0vZIOf5Kv1IKywDb1ZgKTFP57eMaJwW6u8o/uiyPr35uJE8++Qo/+e/vOXHFGzmPJ60g9x5yBvce+mXiwUjPfDjbwdH+VomOOv4Zyg+q9y4v4Jov7pPzWPP2eaNLozSkXarqkqQcz2//p/0V//yQRU3CJu14FIb8SY7NdSnyQ1abAXpHKfUtA/hI0CKRdlEKwgETrXWHwXxPpOz3lL40GSHE7kqCfyGEEEKIPsLzdDZQ+3RLA2nHoyRqEG4MKpO2h+P5e8DTjsu6mgRKQX7IYkRJJBuMZgrzGcqvOr+lPpUtSKc9jdcY+2kgYBgMzg/guJqq+lSnlfGb1wYwAGdbDac9+TdmPfA7Ai329T+zzwxumXEOGwuHdPrem1+3pxnKTy8fUxalLmGzrcHGa3xNw1AETUUkaOJ5UBSxuPILk1oFyC3b5+WHLPKCedl74niaeMohP2RR3ZAglrCpNjWMg/LCEJefuE+bAW5nKfUtA/jiSACAmoTdpWC+L/Wn70uTEULsjiT4F0IIIYTYhTxPs3h9La+v3MLzSyqojCWxXT8MjiUdQoE0pXkhlPIDVPALpiUdF4OmNnZtBaOxRJr1NUl/Zb9RZnXb0xpPQ0PaJeW4eC22A7QXjOvGawTx+L9Fz3Ppa49R2lCbc877wybyi2PO470Rk7r8OWReyzRgdEmUgrDF6qp66tOdbz/ICxo0tHGe0fhGAqbC9fzPalhxlKGFHmu2xdFAxDJAKYKmwbgh+a1WoTMTMvNXVBJPu9ngG8i5J7GETU3Cr5EwujTif56uAzRQl7TZEX0pgN9RA+m9CNHfSPAvhBBCCLELfffxd/lwQx3VcT9ADFkmQwpDBExFTSLNptokAdOgINwUdGqtSaRdCiIBErZLkdYopbLBqNYGa7clSDa2i2vOD/J142p482O542pvFd40FNPXLOInL97P3lWf5Ty2qWAQN878Ns9Omr5d+/rDAYPywjC/PH1qdoX4sTc/44/vrO/weZ5WmI2LxyXRIAHLwAAq61MYjcXllNLZCvyGYVBeFCGecvjRCXtTmh9scxV6wcot2TT1hO1Sl7T5zPEYWhQmP9T0z2itNZV1KQAG54eIBP3HAsoAGmhIe9wzfxWHjS2TVe5dpHlWjWQciN2VBP9CCCGEELvAW6u3AvDxphiJtPb38SuF7XpsqkkyoiTCiOIIa7fF2VCTYHSpImyZ2SJpBWGLbxw6msffWtuqiFp1Q5q062IaBrhum6/fPNjvaB98c3tu28BV/32QY1cuzDnuRqLcf9iXufOg02gwQ51eJ6dtoWoqNBgOmNxw2pTsyvvUkUV887A9eO6jTdQnXVqu7VuNHQ5sx22c/IChhSEMw6AuafuTG0rjev61/Qr8vkzrvdL8IDMmDKalBSu3cOXTi6lPOZREgxRHAyRtj4TtsqE6zoiSaHYCINGYPRGyTCKh1q3siiIBVlXWs2RjTFa9d4Hmkzi2qwmYqs0sDyEGup1falUIIYQQYjfneZoH//cpAMWRIHbjPn7TMLBMPyW/qi5FfthiWFEEQylqEzaV9SniKYdJwwqYe/pUZk8fx9zTpzJpWAHxlJN9fFRplLygRSTYM//UK0zWc/XL9/PCgxe0CvxXnHA6etnH3HXUWR0G/gFTURQ2GVoQYnBhiEjAxDT8f4wqBQHTwEBTFMnt9b4tniZkWUwcms+g/KC/bQEImH7wr9G4GgrCFqV5QTbXpUnYbnbF33E1hlIMLgg1VuD3ddRbvnlxv/LCMOGAiWkYlBeFsQyF7WoqapO4rj8ZUFWfRgFDCnNfIyNkGtieZls83fUPXfSIzCTOsk0x8kIWQwpC5IUslm2q48qnF7Ng5ZZdPUQhdhpZ+RdCCCGE2MmWbIzxaVUDlIGrtV+grzFmVChMA1KOSzLtURwJkHY8vn/0ePYYnNdmRfiWRdS21qe46I+LaEjt2F5z03M5a9FzXPL6E5QmYjmPvTtyErecMIeKCVM55sMY8XRThkHLegFmY3V6pRThgMmm2iSu9tPwM+c6nkdNwuP1lVtyVsdLo0ECpsLRMKwoQkE4kC1s6DSmLARMg8uOn8jYQXnZFd6062EohVYwvLh1mn5HveVbFvfLyA9ZjCyNUlGbJO24bIwliQZMxg7OY922OEGz7cmWjiYaRO9pOYmTuZdhw6S80KAilpLtGGK3IsG/EEIIIcROti2ezhb1M5WBUs3S4PEnArTnB8S4/qr5gWNK2k0Zb1lE7YN1NSRtF6/zWnntmrH6Xa76z4NM2Lo25/iGoiHcPPPb/GvvozBMA2qTPL5wbWPnAJWdzKDZ+wmYCquxyEBVXQpX+23eMsGYwt/y4GjN80sqmDN9LIah8DyNpzWleUHWVycY0RjEZwob2q5HbcJmyohCzjpkNIahciZC1m2Lc/9rq6lPuVim0eXe8pn701Ywnx+y2HNQlE21Sc49ck9mTBjCpPICZj3yNss21VFeaORMGADUJmzGDS1sc6JB9J72JnHAL9ZYHJXtGGL3IsG/EEIIIcROllnNBr/IXcgySNgeAcMPSjKZAKZSHa5QO47Hsx9uYkNNnBHFUU7ZdxiW5QesOjOb0M3+eeO2rOPq/z7A0avfzTleH4zwu8PP5PcHfwk3FCbQeGnb9bBdv4CgYSjMxvE3z2ZwPA/TUJTmhVhZWY9lqpxgTON3HghZJpWxJEs2xqhL2tlV/Ia0S33KYUVlPYMLQpREgqD8TgXF0QAXzByfDeJbToQ0zwboam/5zP1Jux5ho/Ue/rSriQRMZkwYkn2t780Yx5VPL86pv5BonH3paKJB9J6OJnGgqe6DbMcQuwsJ/oUQQgghdpJMxfGt9SkGF4SABgAGF4TZUJ3A9jSmoXFdTdAyqU3a5IcsvjdjHOCv6C9aW4NW8NmWep55fyN1Sb9nvQH8/J9LuHDmOCaUFxIJmH6bvC4G/8WJGBf970nOfu9fWLopZcBD8eepx/Lr6WeztaCUoGk0VdDHT+n3NKD9ID9gND7eGOd62sP1YGhhmC9OLefWF1bguhpl+kUOtQbX8/flDykMEU+7vL6yij++vS5bbK8kGqQmYVNZl2RzLEVDyiUvaHYaxMP29ZafPLyQcUPy21zJb2/LwLTxg5h7+tSciYa8xn9pX3vyPlJYbhfobBJHtmOI3Y0E/0IIIYQQO0HLiuOW8mAErK9OUJQfZlhRmM0xfy+7AoKmYu/yAi6YOR6AL/32dVZsrsd2vZzq/JYBQUPhaaiN29w8bzlnHz4Gy1TZ9PuOWK7D2e//i4tff4KiVEPOY2+NmsL1x8xmyVB/8qF5qn6WakovMFDYnsYympIObMcP8j83poRhRVGKo0HiaRfH89Ce//RwwGRwQQjTUAQMj+eXbG61T7s0L0hx1GJDTZIRxRHmnj6VqSOKurSa3t3e8oah2lzJ72zLQMuJhuKQwWeLXufQsWVdfm3Rc7ZnEkeIgUyCfyGEEEKIHtJeL/GWbeOCpoH2XCBB2nWpbkjheOBpjWUqgqZB0DIBxZKNtTzw+qdU1aVyV9obOZ4frFqGwlAeaUfzt/fWg+6khZ/WfH7V21z1398zbtv6nIfWFg3ll0efy/MTDm/K3W98jkZnK9pr/P39RmPNgpK8IA0ph5TjobWmMSEAy1D8e3EFLyypwNWaoKUYlhchaXtoIBo0CQcMNsfSjCyJsLk20eY+bUMZDMoPUd2QxlCqV9Po21rJ78qWgeYTDbZt89miXhui6MT2TuIIMVBJ8C+EEEII0QPa6yU+Z/pY7n11dauV7EDjPuS8kEUkFKQu5aCwGFQQJGSapF2PjytivLNmG7brZwNYpsJtI6J3XA/DMjCUgWV61CUdogELy/AnB1qaUPUZV//nQaZ/9n7O8bpghLumfZWHDvoSaSvQ6nm2B472U/uVakrXL4oEqEnYNKQcf3za38OfGWlhOMCQghBp16MhlqIh5VCfcvzsgMbaAEopyvKCnDC5nN+//mmf2Ke9PVsGRN+yvZM4QgxEEvwLIYQQQuygtlb2067Hsk11/OgvH5J2XErzQq1T5oGicIBVWxNEgyYjSyI57ciKwgG21qf91XMFtqvbXM33GvfNm4a/Cu9o8NCURkNU1aeyQXhpvJZLX3uMr3/wPGazff2uMvjjvsdz21HfYEteSZvvMTORoDWkXb+AXyRgMig/SH3KZXRphE21SdKuX2cg85oGUJd0KIy45IcsSvMC1CVt0GAaKjexACgIW31qn3Z3twyIvkcmcYTwSfAvhBBCCLEDOuslvm5bnLjtMrQg3ObzMz3uo8HWae6u1tm9804n+/dtV+O4/vlKQdA0CAUMvwJ/Os233nuWH/7vKQrT8ZznvT5mP274/Hl8PGTPDq+vtT8BkVnRtxSUF4aoSTjkBQ3yQxb5IYuiogBx26WqLoVhgKEUjuu3+MsLmmypT2Mof4zlhWEsU2EZBiFLsbkuzbyPKhg7OI+PK+pln7boMTKJI8R2BP8vvvgiRxxxBNFotDfGI4QQQgjRr3TWS7wwEqA+5VCXcihuY7U6YbuAX/QO/Or4tXEH2/Wye+a7Knu+9gPlqliCYz5+gyv/+3v2qNmUc+7qkuHMPfpcXhp/SO6+/na4zfb2ayDlajbFkhwwqoQTp5Rz939XUhINEg6YuLqpAKBCYRqQclxqEjYpx8VsLFBomYqCcNP2guJogNVV9Vxw9HjWV6+WfdpCCNGDuh38f/nLXyaVSnHQQQcxY8YMZs6cyRFHHEF+fn5vjE8IIYQQok/rrJd4QdjCMBS1CYeiSKDVBEEy7RIwDQwDqupSVNUlcbsT8bdjxJoVXPOf+zl87eKc47WhPP7fEV/nDwd+Edtsva+/O+Jpl5p4mlgiTcJ2sx0GMun8GrKZCNrDn9DQoBq7AVhG7meW2c8/qjQq+7SFEKKHdTv4r66uZuHChcyfP59XXnmF3/72tySTSQ488EBmzpzJTTfd1BvjFEIIIYTokzrrJZ52NYXhAEHLyFnJTnj+nvvCiMWQ4iCrq+ppSLdRna+bBtdXc+lrj/LVD1/EaJY34CiDxw84iTuOOIvq6PalP2fqDWS2IihgWUWMZZtifqvBhI1p+N0KTEP5hQ+NxnNVpsihxnUh0ljhv7nm+/mnjixqtU97UnkByyrqmL+iSvZtCyFEN3U7+DdNk8MPP5zDDz+cn/70p3z00Uf8+te/5vHHH+ftt9+W4F8IIYQQu5Wu9BLfZ3hhtup/ZiU7r/FfYT87ZTKeMvj2Q29nn5e5QncSAEJOmu+883cufONP5KcTOY/N3/NAfvH581g5aPR2vstcGn8LgALcZvMVWoPnajzPbdxJ4E+KAEQCJmHL/3w8rRmUH+p0P3/zfdoLVm5h1iNvt+qmIJkAQgjRNd0O/pctW5Zd9Z8/fz6u63LkkUdy6623MmPGjN4YoxBCCCFEn9XVXuLTxg9i2rhB2ZXs4pDBZ4te59CxZfxzcWXONbOV8pWfGp92O8gI0JovLP8fV7zyEKNqN+c8tLJ0JDd8/jxeGfe57PW07t6kQnsUKru3vyW3efGBRinHozpus3d5AZV1KepTLpZpdGk/f0fdFK58ejFzT58qEwBCCNGJbgf/kydPZvDgwVx88cVcc801TJ48uTfGJYQQQgjRb3S1l3jzlWzbtvlskf/8DTVxfy88bQTmyg/a22rxN6ViJde+fB+HrF+ac7w6XMDtR57FE/ufhGM2/XPP02AZCtfTOzwB0Fbgbxq5mQAAYcsv6pdyNEHL4Ccn7o2hVJf38zfvpjC0METK1jSkHSzDYGhhkM2xNPfMX8VhY8tkC4AQQnSg28H/D3/4Q1599VWuu+46nnnmGWbOnMnMmTM56qijpOifEEIIIXZbHfUS9zzd6nhzDWk3G4w3D189DbbTetV/SN1WfvzqH/i/j17OOW4bJo8e8EV+c8TXqY0UtDlOV2syMfL2FBZUjTMUbT21ZeCvgKGFYQojQbTWVMRS3Pvqah6ZdUiX+65nuimELJM1WxOkHNefKFEQskyKIgFWVdazZGNsQLRya+u70tmkxvY8Rwix++l28H/HHXcAUFNTw2uvvcb8+fO59tprWbx4Mfvvvz9vvvlmT49RCCGEEKJfaKuX+IKVW7Kr3AnbxVCKUaVRLj1mLOAHbh+uq8mu+mcK6WWC6+ZBdthOMnvh03zvrb8QtVM5r/PSuIOZe/S5rC4b2eEYtYZgwKQ4arGpNtXhue09v8vnAnZjyoJSiuJobqDelWB9WzxNQ9olnnLQNHYSMPxxJG2XlO0SDVlsi6e7/V76mubflbbqGrQV5L+5emuHzxFCiIxuB/8ZnufhOA7pdJpUKuWnrn32WQ8OTQghhBCif8vsVa+Op0k7Gtv1V62r42l+8OT7XH8gfFxRx6dbGijLC7KlwQ9gW8XXWnPqslf5ySsPM6KuKuehjweN4YbPn8frex7Q6XiCpsLVMLQwRNJ2u/VeAobKBvJtaXPLAhBL2JTmBVGobCu/7gTqxZEASdvF05qAZaAacyOUAmX6mRFJ26U4smNtC3e1zuoafOPQ0bz6yZacIL8sP0hlXQrX01ILQQjRqW4H/xdddBGvvPIKS5YsobS0lOnTp3P++eczc+ZMpkyZ0htjFEIIIYTodzJ71avjaeIpt3HV2kApcFyPVGM6//9WVmK7mqGFYerTDkk7N3d+/43Luebl+zlo48c5x7dGCrntqG/y1H4n4LbRYrDNMWndWKFfU5dygPbrCTRnKsXw4jC2p9lanybteK0C/bYuETAVKccjmfaIBM2cVn7doZunQTTPZtctHu+nmtc1KC8MZ7sghA2T8kKDtdsS3PriCvJDVjbIT7kuH1fU4Xqa0aVRwgEz5zkVsZTUQhBC5Oh28L9hwwZmz54twb4QQggh+pye2vvcE9dZsjHGysp6kraHqzUB0/DT4B0PT4PZGK//7pXVWIEAibSdE/gPi1Xx4/mPcPrSV3KumzYsHj7oFO6a9lVi4a7VW7IUOBoczy/Kl7Bdxg/KZ2lFDLfZxn+lWgfShgKlNKZhELAU6bBH0DSYPmEQLyzdzLYGu81Vf1P5KfqOq3E8D62NVq38uqImYRMJmCRsje1pLKMpy8DxNKahiARNahJ2l6/Z12TqGpREgzntDzNs1yPteBQVBbJBPo5CN07mbKlPkR+yss9ta4tFfyX1DIToOd0O/v/yl7/0xjja5DgO1113HY8//jgVFRUMGzaMb3/721x99dUYhgH4PWF//vOfc99991FdXc2hhx7Kb3/725wuBKlUissvv5wnn3ySRCLBMcccw913383IkU174qqrq/nhD3/IP/7xDwBOPfVU7rzzToqLi3fa+xVCCCHE9utsv3RvXae94OT1lVVU1aVwGpfVU20U7gNIeZpY3GZb3A9eI+kkcxb+lTlv/ZWIk5se/8Jeh/HLo7/DmpLhXX4/AVPhNfb3U0DAMLAd/zcjisOs2ZrIntuy40DAAJTCUIq6pEPAVEwaVpj9LKaMWMP1zy7F9Rrfm/KzBLzGgoCu51cxcD2/2F97rfw6UhoNkhcyyQ+b1CZsUo6XLfgXCRgURgKg/fP6a6C4LZ7GdjVB02j1WNL2cFzPz9hoNjPjeB6gME3/u5W0/eyKjO3ZYtHX9NTPtBDCt117/letWsUdd9zBsmXLUEoxadIkLrroIsaNG9ejg7v55pv53e9+xyOPPMLkyZN55513mDVrFkVFRVx00UUA3HLLLdx22208/PDDTJgwgRtuuIHjjjuO5cuXU1DgV7m9+OKLefbZZ3nqqacoKyvjsssu4+STT+bdd9/FbJx2P+uss1i/fj3z5s0D4Pzzz+fss8/m2Wef7dH3JIQQQoie11N94JtfJxIwsUyF1rBsU6zN67RdzC/CAaOK+fuijY3Bb9co7XHaklf48fxHGFa/NeexpUP25Befn80bY/Zt//k0ZsUr/9eq8aDrajLTDkHLwPU09WmHxRtqsQxFXsgkYbvZSv2ZEZsKoiGL4kiA2dPHMao02iqgPuuQ0cz7aBMfbYhRFAkQMA3CAYOGtEtlLEnCdjEbWwu218qvM5OHFzJuSD7LNtUxpjRKyvEzCSzDIGQpNtelmTSsgNpEmnMeWtgvA8XSaJCAqUi7HuEWWzgcz8PDv6+W0TQ5YDVuIUH7kzb+ZEDTc7d3i0Vf0VM/00KIJt0O/p9//nlOPfVU9t9/f4444gi01ixYsIDJkyfz7LPPctxxx/XY4N544w2+9KUv8cUvfhGAPfbYgyeffJJ33nkH8Ff977jjDq666irOOOMMAB555BGGDh3KE088wZw5c6itreXBBx/k0Ucf5dhjjwXgscceY9SoUbz00kuccMIJLFu2jHnz5vHmm29y6KGHAnD//fdz+OGHs3z5ciZOnNhj70kIIYQQPauz/dJd3fvcfI++42pqE3Z2hTloGtiul3OdbDG/hjRJx8N2/RXprQ1pFq2r7dZ7OHD9Mq79z33sv+mTnONV0WJ+Pf1s/jz1WLxO9vUHTPCAiGVSFA1SEDKpSzpsiiVRXmMKvqexDIWJf67taMBj76GFrK9OUJ920NpPpS8MB9hneGGHwbNhKC6YOb4xSHMpjhpo7b9WOGBSGAnwrcPHcOT4wdu9Cm8Yiu/NGMeVTy9mc12a4miAvKBFyvXYXJcmP2Qyfa9BXP3MR/02UGw+wVFeaOSk/pvKT+8PWibhYFPwHw4ahCyTRNrBMFTOxIDWeru2WPQVPfUzLYTI1e3g/6c//SmXXHIJN910U6vjP/nJT3o0+D/yyCP53e9+x4oVK5gwYQIffPABr7/+erbd4KeffkpFRQXHH3989jmhUIgZM2awYMEC5syZw7vvvott2znnDB8+nClTprBgwQJOOOEE3njjDYqKirKBP8Bhhx1GUVERCxYsaDf4T6VSpFJNLXJisRgAtm1j231331lmbH15jGLHyD0e+OQeD3xyj7tu6cYY67bUMSQvQNDINMtrpGBwnsW6LXUsXreNfToIhJZujLGyohbH8QvhRUyV3QPvahfHgZUVtSxet429ywu4/9VPiDUks1XzA60ztjsUMjSRykrueOZRTlr6Ws5jadPioUNO495pX6EhFMWvY99xFoECikIWhqFwHZuY56K1JmqCshSO1gSU/54yz3CVxtEe0YDm4W8fSHU8TW3coThiUZofYu/yAgxDdfg9PHhMETecOokH//cpn1Y1kEhpAoZi3xH5nHvEnhw6tgwA13Vwu9dgoNPXmDo8j1nT9uChBZ+Rtm1GFYUb358mZCryA0E216W4/9VPOGjUzt8C0J2f4zlHjuH6fy5lW32SokiAkGmQcj3iqTQFQUXIggAapZq+B8MLA6yrtjEVBJSHqRUp16M2YVMaMZlz5Jgd+tx3lZ76md4Z5M/qga8/3OOujk1p3b36qOFwmMWLF7PXXnvlHF+xYgX77rsvyWSyO5frkNaaK6+8kptvvhnTNHFdl1/+8pdcccUVACxYsIAjjjiCDRs2MHx40963888/nzVr1vD888/zxBNPMGvWrJwgHeD4449nzz335N5772Xu3Lk8/PDDrFixIuecCRMmMGvWrOzrtXTdddfx85//vNXxJ554gmg0uqNvXwghhBADlJlIsNff/sb4v/8dM527J3vDtGksPecc4kOH7qLRCSGE6E/i8ThnnXUWtbW1FBa2PyHW7ZX/wYMHs2jRolbB/6JFixgyZEj3R9qBP/7xjzz22GM88cQTTJ48mUWLFnHxxRczfPhwzjnnnOx5Lauiaq3brJTa0Tltnd/Zda644gouvfTS7O9jsRijRo3i+OOP7/BD39Vs2+bFF1/kuOOOIxDo3z1xRdvkHg98co8Hvt35Hr+1eisPvP4pn2yux3Y9AqbBXkPzOe/IplXk5pZujHHRU+8TDVqE21h+T9geibTDb752QIerhP/8YBNXPfMhhspNoc5wPA9Pa3552r4URyy+/9T7OJ5ut799W5T2OP3D/3DJK39gSEN1zmMflY/jxmPP453RU2AN/v+6wGgssjeqJI9I0E+731yXYmJ5Pj/8/F5877F3iaWcxlX/3H/XeFrjao+CUICbvrwvR/Th1Pj2/G/lFq56+iMG54do47bheVDVkOKXp03Z6e9ve36OPU/zcUUd1fE0JdFgNvvirdVbs5kPtudnPuw5OI9zj9iTg/cobfM5/VVP/UzvDLvzn9W7i/5wjzMZ6J3pdvA/e/Zszj//fFavXs20adNQSvH6669z8803c9lll3V7oB350Y9+xE9/+lO+9rWvATB16lTWrFnDjTfeyDnnnEN5eTlAthNARmVlJUMbZ8vLy8tJp9NUV1dTUlKSc860adOy52zevLnV61dVVWWv05ZQKEQoFGp1PBAI9NkvRnP9ZZxi+8k9HvjkHg98u9s9XrByC5f99SO2NaTxPJ3dc1/ZUM2yzQ3cfub+rfZuTx1VyqhBBY37pUM5Aa7WmqoGh0nDCpg6qrTDgKi4IIytDTxPE9C0uo7tgaEMigvC1DTYJBzwdNcDrEPWfcQ1L9/P1M2rco5X5pdyy/Rv8dcpn0crA1w/hd9Q4GqwDAiZirjtTzEYCgylcLXGNMD1FGbAxAyY2I3jiYaDLN8cxzAtykvyqVxfg2P6kwTZ94TGcSFgWhimRVlBtF9+18oKomhl0ODopjZ4zSQcF42xS99fd3+O9xvTepLryInlTNtraLvdDNp6Tn/VUz/TO9Pu9mf17qgv3+Oujqubu9Pgmmuu4dprr+XOO+9kxowZTJ8+nbvuuovrrruOq666qtsD7Ug8Hs+29MswTROvsZ3MnnvuSXl5OS+++GL28XQ6zfz587OB/UEHHUQgEMg5Z9OmTXz00UfZcw4//HBqa2tZuHBh9py33nqL2tra7DlCCCGE6F2ep7nxuWVUxlLYrsbVflE6V4PtaipjKW58bhleiwr6mYJw+SGTiliKhO3ieZqE7XarvdygvBCFYQtDKWxP42mN1v5/bU9jKEVh2GJQXojivK7/A3BkTQW/feZG/vTET3MC/6QVZPlXvsIJ3/0df5l6rB/4N/88tF9xvyAcwDT9zgOG4b9f19N4GlzXnwgojFjUJx0SaReNJmQa2J6mJmFz+fETCFp+ez/X89D478lx/ayFoOVXxe+PheGgqVheddym5W7WTOG7/vz+mjMMxdSRRcyYMJipI4v6TODb03rqZ1oIkavbK/9KKS655BIuueQS6urqALIt9XraKaecwi9/+UtGjx7N5MmTef/997ntttv4zne+kx3LxRdfzNy5c9lrr73Ya6+9mDt3LtFolLPOOguAoqIizj33XC677DLKysooLS3l8ssvZ+rUqdnq/5MmTeLEE09k9uzZ3HvvvYBfN+Dkk0+WSv9CCCHETrJ4Qy0fV9RlU+gzrepo7BmvgY8r6li8oZb9RhXnPHfa+EHMPX1qtu1ebWNadHfay00eXsg+w4v4YF0trueRdpv6yYctA9Mw2Gd4EZOHF/KLfy2lsy5++ak4F77xJ77zzjOEXCfnsb9PmsHtn/8WlxxXRnyhCS0KsmmgOBKgOGpRE7cpiQbJ9zxq42nSrm5q8QYYBlTVpbJjDVmm33avsc3b1JFFXHbcBG59cQVpx0N5/vMDpknQUpREg/06kGreDaAilqI42lQsryZuS6DYT/XEz7QQIle3g//meivoz7jzzju55ppruOCCC6isrGT48OHMmTOHa6+9NnvOj3/8YxKJBBdccAHV1dUceuihvPDCCzlju/3227EsizPPPJNEIsExxxzDww8/jGk2pYY9/vjj/PCHP8x2BTj11FO56667evX9CSGEEKLJe2ursV0/os7Zmt7Yt143ZgC8t7a6VfAPfrBw2NiydtOiO9M8iKxLOpTkBTEb0+sTaZeCsMX3Zoxjwaot/OGNz9q/judy5ocvctlrjzE4XpPz2PvDJvKLY87jvRGTCJmaVlE/EDAVc0+fSjzt8st/LcPTmvpUIttycHC+3xN+Y20S29WkbY+AZaAM/zNKpB3iaYfJwwuzq92zp49j0rBCfv3CCtZti+NpTSRgMm5I/oAIpCRQHJh29GdaCJGrS8H/AQcc0GkBvYz33ntvhwbUXEFBAXfccUe2tV9blFJcd911XHfdde2eEw6HufPOO7nzzjvbPae0tJTHHntsB0YrhBBCiB1RUdO1jkEdnZdJi95eLYPIlOcRMBT7DC9kzvSx5IUs5jz6Dq7X9vMPX/MB1758P5OqPss5vrFgEDfPOId/7DOjVXp/c6aCH58wkRHFES750yK/4KGlMFBoIOl42PVphpeEMZXCRjemSEBOykQbWQlH7jWYaeMG9dtAyvN0h2OXQHFg2tGfaSFEky4F/6eddlovD0MIIYQQu7uhxeHsrzMp7M1/39Z5vaGtILI2kebeV1ezdGMtWxta91PeY9sGrnzlIY7/5M2c4/FAiN8d+n/cd8jpJAMdj1sB35q2B+ceOZZzHlpIyvYwDVD4VfoVEDDA9jSba1PYrofRmObveE1bFCIBk8JIgK31aZZsjOUETv01kFqwckt2QsZ2NQFTtZm10F/fnxBC7AxdCv5LSko4//zzCYfDrF27lpEjR7YqxCeEEEIIsSMOGl2CZSicxs30uo3Va8tQHDS6pPUDPax5ELlg5RaufuYj6lNOq0zIwmQ931/wR7797rMEvdx9/X+dfDS/mn4OFYUdp5wrYHB+EE9rZk4cwpKNMVZV1jOoIIjjaZK2izKbJgEsA9Kuh6shL2iyR1mUlKNxPA/LMAgH/HZ/lfUptsXTPfq57AoLVm7hyqcXU59yKIkGCZoGaddj2aY6rnx6MXNPnypp/UII0QVdiuAvvfTSbO/APffcky1btvTqoIQQQgix+5k6oohJwwpoL0lbgd/ea0TXV3Y9T7N4fS3zV1SxeH1tq04BXXn+PfNXUZ9yKC8ME2hMITc9l2++/2/+e9/5nP/20zmB/zsjJvGls2/lspMv6zTwB4gG/ZX6kGVSGg2yLZ7GdjUh02RwQQhDKRy3sfsAjR0IPI2hoDgawDAMIkGTgnCASNBEKUXK9bIF//qzlp9/OGBiGIpwwKS8MER9yuWe+au6fV+FEGJ31KWV/+HDh/PXv/6VL3zhC2itWb9+Pclk2/vtRo8e3aMDFEIIIUT/09n+7LYYhuKKkyZxyZ8WsbXer16v8YN+paAsP8QVJ01q8zptvd6bq7d2KVW8I5lV+JJoEKUUpqE46tP3uPo/DzBxy9qcc9cXDuGmmd/mn3sf1aJiYccG5YfYlvD7lk8eXsiSjTECpiLteuSHLEaURKiqS5FyXLQHoAlaBqNKItQkHLTWrfqg18Tt7PX6s5aff3NKKYqjAVZV1rfa3iCEEKK1LgX/V199NT/4wQ/4/ve/j1KKgw8+uNU5mb94XLd11VohhBBC7D66uj+7LdPGD+L2M/fn7ldW8nFFXfb5e5cXcMHM8W0+v63XK80LsrE2ScpxiQZM8sMWpqG6lCrefCLh0y0NpB2PkqjByM1ruOKvdzLt47dyzm8IhLn7sK/wwMGnkQqEuvw5hS0DcKlPueSHrGw7ukzf+mWb6igvNMgPWeSFTJJpD9t1qU06TBlexHdnjOXqZz4a0O3tMlkQQbPtZNWQaVDr6QGxvUEIIXpbl4L/888/n69//eusWbOGfffdl5deeomysrLeHpsQQggh+pme2J992Ngy8kIWi9bWoBUcMKqYqSOK2gxk23q96niKjzbGsuc0pFy21KcJWgbFkQA1CZu7X1nFYWPLWl2z5UQCgKqu5px5T3HGm//A8poWOTwUf556LL+efjZV+aWdfjblhSH2HVnMysp6YkmboKEBm4nl+cyevlf2c2mvbz0KGtIexZEAJ04px9Vw3lFjmffRJlZXNQzI9nal0WA2CyJsmK0eHyjbG4QQYmfoUvAPftu9KVOm8NBDD3HEEUcQCnV9ZlsIIYQQA1/L/dmZNO2wYVJeaFARS3HP/LaD7ozuZA209Xr1KYfNsVSr62og5XhsrkthKHj7s208sXAt3zxsTM5rN59IiOBx/Gt/45vzHqY4WZ9zvbdGTeH6z5/HkvLxXfpsAobi+5/fi28eNiabWbC1Lk7tioX87hsHEQrlBq/t9a0fVuT/++vu/67Mfj5jB+dzwdHjGVUaHXDt7VpmQQzU7Q1CCLEzdDn4zzjnnHN6YxxCCCGE6Od2dH92d7MGWr6e1prKWAK3k9pvnvar5d/58ieMHZTHtPGDcicSCkIcvOxNzn36t4yszN3Xv6GknBtmfofn9jq8y/v6S6MBDEMxqjQKNHUSsO0o/15Bu4F6y5aD67bFuf/VVTSk3ZzP5+OKOtZXx5l7+tQBt++9vSyIgba9QQghdoZuB/9CCCGEEG3Zkf3ZLVfxUZBMezieR1HYojZpt8oaaPl6SdsjYXtdGqupFCnHy14zM5Gwf2wDFzx+Nwd+/HbO+Q2hKHcf8VX+fPjpbHGNbLuk9orMW4by5wY05IUsXE9vV2p6ZqLA8zTnPLSQhrS73VkV/VV7WRADaXuDEELsDBL8CyGEEKJH7Mj+7Oar+A1pt6m6vfYX2C3DYOnGGEs2xrIV8T+rakCjSTkukaCF7brtBuMtWaaiLD+YzUSIrd/EJc/8hjPe/hembppAcJXBi4d/kUdPOpcV5HHBzHH85b31bKhJMKIozOotcX+cgG58bUOBaYDrQcgySNguk4YV7lBq+u5e9b5lFsRA294ghBA7gwT/QgghhOgRO7I/O7OKn3Y9NtUk8bTGNBTK8IPqtOOSdlwef+szNtQkszUB6pIOtQmbEcUR3K4t+gP+REXYMonXJ4j+9jfsc/etmLFYzjkfTDiQB07/AZ+NGE/CdgmkHD63RykTywu48unFbK5LU5oXpDKWxGk266AUOK7fBckyVU4l/+0lVe+bsiCEEEJsHwn+hRBCCNEjdmR/diZroDKWwtMay1Qo/POUAtNU2I7mb+9vpDBsZfe8By2DTbUJ1m6LUxwNdGmcCiiJWBz0wavM/sc9jNq6IefxjYNG8ODp32fhlCOgsZZA84kLw1A5aejRkEXSdvE8jYcG7X8WheEA+wwv7JHUdKl6L4QQYkd1O/i/9NJL2zyulCIcDjN+/Hi+9KUvUVraecsbIYQQQgws27s/e/LwQoYUhqmIJf398uRmDfgr6eA4HkXhAOGAHwCX5vlB8YaaBHVJp0tjnFT1Kb/46+85cOX7OcedgkJ+N+MbPHbQKeQXRglpSDlumxMXLdPQiyP+xMO2eJqaBpuSaICy/FCPpaZL1XshhBA7qtvB//vvv897772H67pMnDgRrTWffPIJpmmy9957c/fdd3PZZZfx+uuvs88++/TGmIUQQgjRh23P/mzDUJwwuZwP19fgao3SmsZ6eTiexlAKP7Fe4+rcjf0F4QBjyhQ1cRvLMNgcS9LW1v9BDdVc+tpjfPXDF3P29WOaMGcO1s9/zoE18FYXJy52Zhq6VL0Xu6tMa0yp9SDEjut28J9Z1X/ooYcoLPRnl2OxGOeeey5HHnkks2fP5qyzzuKSSy7h+eef7/EBCyGEEKLv257A+Mjxg3jgtQCJtIftedlif5GAQV7IYkt9Olv8r6WQaaKUwwmTh/LYW2tB62wnPsu2Oeedv/P9BX+kIJ3IfeLxx8Ntt8HkyQBMG0SHExe7MhCRqvdid7Ng5Zbs9912NQFTMW5IvnzfhdhO3Q7+f/WrX/Hiiy9mA3+AwsJCrrvuOo4//nguuugirr32Wo4//vgeHagQQgghBrbJwwvZZ3gRSzfGGBYJ42qNZRiEAwaJtEuVThG0TMLB1sF/Zs/7GQeO5L211XxcUYf2PE5Y/gY//e+DjKrZnHO+njgRddttcNJJ0KJ6fnsTF30hEJGq92J3sWDlFq58ejH1KSdb4yPteizbVMeVTy9m7ulTZQJAiG7qdvBfW1tLZWVlq5T+qqoqYo1VcouLi0mnB261WSGEEEL0vOap7bVJJ5vanrBdttSnMA2/+N66rXFcDdGgyeB8v/VdTdxm7/ICAL4wdTily1/kB/+8m8+tWZzzGrFIAcu/dxmJ78ympCiPydpvzdeezEr/6yur+MMba0g7LqV5oV0aiEjVezHQeZ7mnvmrqE85lBeGszUuwoZJeaFBRSzFPfNXcdjYMpn4EqIbtivt/zvf+Q633norBx98MEopFi5cyOWXX85pp50GwMKFC5kwYUJPj1UIIYQQA1zL1PaqtEsi7aLR2K7GRpN0/P369SmHyroUYcugOBqgNpHm6rtfYPYLv+eh917AaLbz3zFM/n3UaTx54izW6DD200s7XblvvtJfVZ/C9TSRgInjacIBJYGIEL1kycYYqyrrKYkGc4pbgl9kvDgaYFVlPUs2xmQiTIhu6Hbwf++993LJJZfwta99Dcfxq+palsU555zD7bffDsDee+/NAw880LMjFUIIIUS/sSN74zOp7U8sXMud//kEx/NoSHntnp90PBKxek787xN859UniaSTOY9/dthMPrzoam5dq2hIu5RErU5X7punHEcCJlprTEORdDw2VCcYURIhP2T1yUBECqSJ/m5bPI3taoJm6y0+ACHToNbTbItLprEQ3dHt4D8/P5/777+f22+/ndWrV6O1Zty4ceTn52fP2X///XtyjEIIIUSfJsFWrp7aG//8kgpcT+M6bvsnac3JH7/GT195iJGxqpyH1pTvwa+OP5+ao46GekVDOtalFOKWKcf1KQdQmIbC1GB7mqq6JHnBPJRSfSoQ6Qt1CYTYUaVRv4Vn2vUIG2arxzM1PkqjwV0wOiH6r24H/xn5+fnsu+++PTkWIYQQot/prWDL8/yU9f+t3EJZQbRXJhR6Y9Kip4p0ZdJ+IwGTbfVtn7PfxuVc858H+NyGZTnHY3lFPPaFc3l+2ik0eIqaijoUqsspxC1Tji3DQCnQGgylsAxIOR5J2yMSNPtMIJL57OuSNtGgRcA08LRm6caYFEgT/crk4YWMG5LPsk11lBcaOT+3Wmtq4jaThhUweXhhB1cRQrTU7eC/oaGBm266iZdffpnKyko8LzcNb/Xq1T02OCGEEKIv661q1AtWbuH+Vz/htDK46umP0Mro8dXb3pi06MkiXZm0X8tUtEz4L49t4UevPsKXl/w357htWPxz5v/xx+O/RUPUL/4XUn6tAOh6CnHLlONwwMAyDFKOR8AE0GgNjuehtdGlQKStiZaelPnstzWkcT1NLJnMtkoMmga2q6Uugeg3mhf/rIilssU/U65HTdwmP2TyvRnj5LssRDd1O/g/77zzmD9/PmeffTbDhg1rNYMuhBBC7A56qxp1ZkIhbdtQBoPzQzQ4ulsTCp2t6PfWpMX2FOnyPM3iDbUsWluDVnDAqGKmjijKpv1qDQbgAWE7yZy3/sZ33/oLESc3xf75vQ7jtyfORu+VW3A45XoETIWi6ynEzVOOHVtTVZci7Xp4WpNy/IwM01A4nqYiluo0EGlvomXOkWO69Ll2JUNjycYYSzfWkrBdPA2WofxsBfyaCIbyWLqxts/UJRCiMy2Lf9Z6moChmDSsQLaxCLGduh38P/fcc/zrX//iiCOO6I3xCCGEEP1Cb1Sjbj6hMKooDCQwDAgHuj6h0NmKfm+20OqsSFfQVGy1XeavqASgNpHm5nkfs2JzPWnXX9+3DMXEoQX89KS9G9N+Y4QMjxMWz+fH8x9heN2WnGsuG7wH1x8zmzfG7EdAwUTtB+dJ28N2PWoTNpOHF6CUwccVXUshzqQcf7i+hnjKRTeOy1QqO07X08RTNpNHFHcYiHQ00XL9P5dy4fimc9sK8t9cvbVLGRpbGlLEkg6e1gSMpveogIABtucRSzpsaUh18W4Ksetlin9KTRUheka3g/+SkhJKS0t7YyxCCCFEv9Eb1ahzJxRyH+vKhEJXVvQLwoEenbRoHrBuq0+3W6SrPuVQUZsk7bg88NqnPPS/z6hL2qRdnXOe7Wo+2hjjB0++zwUzx1Hw/tt875m7mLphec55W6JF/Gr6t/jz1GPxGl/L1rCpNkHS9kg5Hq7WGEoRSzqcut9w1lfHu5RCbBiKOdPHct4f3sHxNAFLoQAUmAYoFCFTMbosn4fOORjLavs70NlEy7b6ZPa8tiZtyvKDVNb5LQY7y9CoabDxPI1hqDbvq6H8QoY1DXan91SIvsQwlGSrCNFDuh38/+IXv+Daa6/lkUceIRqN9saYhBBCiD6vN6pR504o6FaPdzSh0NUV/XOP2LPHJi1aBqyWAQnHoyHtMKokmh1Dfcph/bY4jqcJBwyKoxYba5M5gX8muG5cuCe6aQMTLrmZ2e/9J+c106bFg587jd8efib1If/fIYbyn+9q2NoY3JoKogGT4miQTbUpHn9rLd84dDSvfrKFlZvr2OJ4GMDosjwuP35Cq5X7okiQvKCJgcL2PBytUQoiAZPBBWFMQ1EZS7Ksoq7dwKSz7JCiSACAP7+7ngf+tyZn0ibluHxcUYfraUaXRgn7xQbazdAoiQaynQq0oWmcrgBAo7MTAyXRQKf3VQghxMDU7eD/1ltvZdWqVQwdOpQ99tiDQCD3L5H33nuvxwYnhBBC9FW9UY26+YRCyGyd1trRhEJXtyFUx+0embRoL8ugIZYinnZZVx1ncEGYoKmoqE3ieBpD+Sv7a7cl8FrMbWj8AD7PTjDnjb9w/ttPE26xr/9fE4/gppmz2FBcDvir8CaAMrDdprKApqEImgaDC0MUhAJo7e/Nf/WTLZx/5FhufWkF67bF8bSmMpbk3ldXYyiVMwGwLZ7GUAZ7lIVJuxrH87AMg3DAv9eepzudJOlKdgjAX99d32rSpnE6BAVsqU+TH7ayAX1bGRpl+SEKwwFqEzaOq/0MhcbJFNfTKKUoDAcoyw91eF+FEEIMXN0O/k877bReGIYQQgjRv/RGNermEwr5gdzgu7MJha5uQyjOC+zwpEVHWQajSyOs3ZZAKYinHLbaLinH3zfvF91vndEAoLTHlxf/hx+9+geG1m/Leezj4XvxqxPm8PKQvQEImH77PfADW9v1snkSClBo0q7LxuokI0oU+SGL4miApRtr+fHfPsR2PUrzOk6jz0zE2J4mEjRpnGbI6sokSVeyQwA21yUpiYZy7oXfScCfyEg5Lsm01zgOX8sMjcnDC9lneCEfrq/BcTVp10N7/gRAyDKwTMU+wwu73ZFA9lYLIcTA0e3g/2c/+1lvjEMIIYTod3q6GnXzCYXNdX5hNs+DhON2OqHQ1W0Ig/JCOzxp0VmWwZDCEA1Jmx+dsDcLVm3hL++u7/B9H7LuI655+X6mbl6Vc7wyr4TfHDOLt486GStgEqqqJ+U0tu7THkppbDd3g4QGHC/za4+quiR5wTyChr/3PxLw0+g7K3TYE5kdnV2jNmFnB91y0sYyDL/ugwLt+ZMBzScgWk4+NP/u1KccSgPB7Mp/wnbJD1nb1ZFAqqoLIcTA0e3gXwghhBBNeroadWZC4f5XPwHiVDWk0BidTih0J1g1DLVDkxZdyjLQUJwX4JPNdW1UL/CNrKngilce4ovL/5dzPGkFuf/g07nnsP+jfHgZeSF/i+Hw4ihrtzbgarBb7htogwfE0y5J2yPpuHiepigS6FKhw57I7OjsGqURP5gPWkarSZtwwCBkGSTSLkqRzXSA9icfWk5G2dn7WrjdHQl2pPWjEEKIvqVLwX9JSUmrvyjbs23bts5PEkIIIQaQnq5GPW38IA4aVci8ec/xy9OmUFYQbTWh0FaKdneC1R2ZtOgoy0BrTW3SxnU9Fq+rZe22hlbPz0/FueDNP3Hu288Qcp2cx/4xaTo3z/g2G4qGoMhd1c8PWYwuy2NDTZy003nwD+BpSDsOsYSLYSgKwm3/06etQoc9kdnR0TXmHDmGrR+/xZ6D81i8sSFn0kYpxaD8EGu3xTGUAuUX7Wvvfma+D7anufz4iQDUJOxO72tvtn4UQgjRt3Qp+L/jjjt6eRhCCCGEaC4TaB0xflCr4rodpWh3J1jdnkkLz9N4WlMSDbBmW4LSaICgZRIOGDSkXSpjSRK2i2koHn7jM2qTbtPreS5fWfwSl7/6KIPjNTnXXTRsAtd/fjbvjZyUc3xDs337AHkhk4BhYOMSCZrE0y6dqaq3KY4G/D38jcXwWmpvD39PZHa0dw3Xdfj3x3DuEXty9T+WtZq0qU+5DC4IMaQgxNb6NLWe0+b97Oj70Nn97WqhyK62fhRCCNF3dSn4P+ecc3p7HEIIIYTogq6kaD8y65BeKdyWCTKXboz5VeU9TX3KwVD+nnXb81enTUMxvDiC52mqG/yV9MPXfMg1/7mffSo/zbnmpvwybp75bf6+zwy0MjAVjYX2/Gr+nqepqkuRFzJRKJJpj5TjTy6ETEW8C+MenB9k7hlTuffV1du1h78nMjvauobbOG9x6NiyDidtOpp82NGU/a4WiuxK60chhBB9m+z5F0IIIfqJ7qRo9/QqbSbIrI6naUi5aK2xDL+4nqch2VhlL2wphhVHyQ9ZaDT56z7l4hce4IRP3sy5XsIKcu+hX+beQ75MIhgGoDgSYFB+iJClWLMtTsL2MBU51e5t18X1IBo0yAtZVCecVmNtTgEXHTuBI/cajKFUj3Zn6EmdZRi0dT97ImW/q4UiO2v9KIQQou+T4F8IIYToYzxPs3RjDIClG2NMHVWKYahdlqLdPMh0XH+vfcAyUChMw8N2NB5gAJZpkhcyyYvX8dUX/sDJ8/9CoMW+/r9NPppbpp9DRWHuinR+yMq2sxtcEGZDdQJXe6Ah7bpgQ23SwTD891oUCbCpNonbxvb/TL2AomiAL+03HOj57gw9rbsZBj3xfeiJrgZCCCH6Bwn+hRBCiD4kk1q/bksdl+wNFz31PqMG+cGp7eldkqKdCTIjAZPahI1pKBR+kGgoA9Pw8DyNYYCTTnPsK88z6/nfU9RQm3Odd4fvzfXHzOaD4ROzx0wFrgZDQVGk6Z8l+SGLESURKmqTpB2XusY2fVOGF1GbSLOpNoVSisEFYSpiyVZj1vjXvHDmOCyr6fPq6e4Mu1JPpOz3RFcDIYQQ/YME/0IIIUQf0Xz/9pA8v8hfNGhl92+fd9TYLqdot9UNoGVl+K4Gv5kg0zIVWoNqEWtmFounrX6fq19+gAlb1uQ8vqFwMDfP/Db/2Ht608mAZYDr+av0YctstXqdFzSJBk0mlhdw8TF7UZYfYvLwQt5cvTUbrAYtlZ1AyBkTUBQJMHl46xXvnu7OsKv0VMp+X8+IEEII0TMk+BdCCCF2oUwgvrU+xR0vf0Jd0mZYUYSg4Uez4YBBeWGIiliKeR9tYuzgfD6u6DhFuzaR5pyHFrZZ/R1otzJ8e0FeJsjU2o/ds/9FozWMqlzHFf99kGNXvZ3zvHggzD2Hf4UHDzkNIxplaNBiS30qG6g7nr/P/4tTy/nfqq1trjwXhC1+fMLEnLFlgtW7X1nJwk+r8bSfQWCZBtGgSV7IoihssbkuPaDb1PVkyv5AyogQQgjRti4F/2eccUaXL/i3v/1tuwcjhBBC7E6at2hL2C6xhE3IMmlIuwTDTcvrmf3bq6sauODo8ayvjreboj19r0Fc/cxH1KccIgEzu1q/bFOMS/60CADX092qDN8UZMYImgYpx0MryGuo5QevP8nZ7/+LgNfUcs9D8dcpx/Cr6WdTWVCGZShGFYTJD1kMyg9Sm3CIpx08rXlo1sEcMLok57PoysrztPGDyAtZnPfIOwRMRTRoEQ4a2e0IwIBvU9fTKfsDJSNCCCFE27oU/BcVyV8EQgghRE9q2aLNMhWxhE3KddlQnSBYFs45P7N/e1RptN0U7TnTx3Lvq6upjqdxXH/lN7NKH7QUKcfDUIoJQ/IxDH9yoSuV4ZsHmbbr4SRtvvb+c1z8+hOUJOtyzn1r5GR+ccxsPiofnz2m0fi78MEwDEryghRFAlTWp4gl/WKA27PyXJOwASiJBts8b3doUycp+0IIIbqqS8H/Qw891NvjEEIIIXYbbbVo09oPshXgas2Wutwids33b08dWdRmoLxkY4ylG2PUJx08nQm3AQ1OuvF3SpNyNJHGbeBaa5K2R8BULNsUY/GGWvYbVdxqzJkg8/X/9yhnPHEb47euz3l8bdFQ5h79HeZNmJazrx/8ff1rtyUYXQr5oUCr95PR3ZVnaVPnk5R9IYQQXSF7/oUQQoidrK0WbeGgQcgySdoupgEpx8ue39b+7bYC5a31KWoTdnZPvcr8X7OJAFeD7XpEMKlPOVTVJf00fg2e1lz59GKu+sKk1ivGS5Yw6Xs/YNpr/805XB+McNfhX+Whz51Kymo/yHY9zfrqBCNLFHlBs0dayEmbuiaSsi+EEKIz2xX8/+Uvf+FPf/oTa9euJZ3OTaV77733emRgQgghxEDVVos2hWJwQcjvbe96eI1/Qydsj6oGp0v7t7c2pHE8P8zPWXxXoJpPAHge9SnHfy2tsQzVmJoPG2oSufv/t2yBn/0Mfe+9lLi5+/qf2u94bjvqm2zJK+nS+3ZcTUVtkryQSX7I2uEWctKmTgghhOi6thvDduD//b//x6xZsxgyZAjvv/8+hxxyCGVlZaxevZqTTjqpN8YohBBCDCjN09Wby/S2D1qmX1IfSKQdJg0raLcYX3Oxxj3wkH160++b/dp2XKrqkrja3x+uFHgawgGLEcVh6lMu9738Md5tt8H48XD33ahmgf+C0fvyxVm/4coTf9DlwB/8CYm04zKyJNql99MVme0Ik4YVEE85VNaniKe6/pkJIYQQu4tur/zffffd3HfffXz961/nkUce4cc//jFjx47l2muvZdu2bb0xRiGEEGJA6ShdPS9okhcy2bM0D9jGb752AFNHlXZp9Vo11gzIBPotJwAyYkkX29OYhn+u62oM5WceGChOWr2Q2XfcjbF1Q87zNgwawU3HnMezYz7Xal9/VxjKn2C46Ni9ejQolz3vQgghROe6HfyvXbuWadOmARCJRKir86v8nn322Rx22GHcddddPTtCIYQQYoDpPF3d4qJj9mLrx2+xTzeC2ANGFRMwDZzGjIJMjX3V+D8A01CUF4dZszWOdsEwIBwwGVwQYsqWzzj36bvYf8W7Odd1Cgq584iv89yML/NpnY2p/T383eV5kLD9bgY9Tfa8CyGEEB3rdtp/eXk5W7duBWDMmDG8+eabAHz66afo9pYYhBBCCJGjs3T1Q8eWdfuaU0cUMbE8PxvtW6YiYCgsU2WPTSzP58KZ4ykIByjJCzK6NMp+oRQ/efp27rjl3JzAXxsGXHABK157jz9P/wr12sDTTRMJ3ZGZvzAUzPuoAm87Jg+EEEIIsf26vfL/+c9/nmeffZYDDzyQc889l0suuYS//OUvvPPOO5xxxhm9MUYhhBBiQOooXd227c4v0IJhKK44aRKX/GkR2xrSTWn/2l/xzw9ZKKW49YXlxNMOZjrN1195lu++/hR5qXjOtRbvcwiTn3wAte9U9vY0Za9uZNmmunZX/JtvN2iPZRoMLgixuqqeJRtjslIvhBBC7ETdDv7vu+8+PM9PJ/zud79LaWkpr7/+Oqeccgrf/e53e3yAQgghxEDW0+nq08YP4vYz9+fuV1bycUUdtqsJmIrywjBV9Sk21SYpiQQ4dtn/mP3P3zG6piLn+Z8NGsnvTrmAU684D2OvwQC8uXorlXUpvA4y/CzDbyPY1tyAaUAkYDG4IEQ0YFJZn2JbPN36RCGEEEL0mm4H/4ZhYBhNuwXOPPNMzjzzzB4dlBBCCCF8SzfGqEl53Spi1zKjoDgS4FfPL6cilmRabC3nP3wnU1Z9kPOcmnA+Dx17Dh+c/HXOP2ZitiCf52numb8K19OMLo1SEUuStL1Wr+l4/kTG2LIoW+tTREMmpjIwDQiYJuGggUKRsF0ChqI0GuyZD0gIIYQQXdLt4P/VV1/t8PHp06dv92CEEEII4XtrtV9f54LH36Pe1gRNg4nlBVwwc1yXKuU3zyhYvL6W2lVr+MV/HuGEt5/DaLaC7xoGfzvsS/z2qLO46MzDuWj/4RiGwvM0SzbGeG9NNcs2xSiOBIgELfJDFtviabY1pHFcL7vSv0dZHt85ck++9rlRzHrkbZZtqqOsMJDTyUBrTU3cZtKwAiYPL+zBT0sIIYQQnel28D9z5sxWx5r/xe426wMshBBCiO5bsHILVzy9mMsnQU0iRdJRKAVvfZrmk8o6bj9z/663ykskyL/tFp767e3kpXOr7L+9z2H8/rQLWTtkDA31KUrzgxiGYsHKLdwzfxWrKutpSLvUJW0SaZchhWHyQxZleSFKo0GStoftetQmba45ZR+OnjgEoJNOBibfmzFO2vAJIYQQO1m3q/1XV1fn/K+yspJ58+Zx8MEH88ILL/TGGIUQQojdhudpbnxuGVvqUwCYyiBgGZiGgedpqupS3Pjcss6r5WsNf/wjTJrEnrfPzQn815bvwbXf+zXXf/dXrC/fg5TrZVPxF6zcwpVPL2bZphh5IYuyvCCGgmRji776lAP4E/+RoEnAMogGTAblhbLX76yTQZcnLoQQQgjRY7q98l9U1Loo0XHHHUcoFOKSSy7h3XffbeNZQgghhOiKxRtqWbG5HrPx94ZSKO2v/AcsA9vxWLG5nsUbatlvVHHbF3n7bbjkEvjf/3IO10QKeeKL5/L8Eafimf4/AZqn4k8qL2DWI29Tn3IoLwyjlEKjCQcsEmkHV3tU1SXJC+b5j3WQxt9RJwMhhBBC7HzdDv7bM3jwYJYvX95TlxNCCCF2S4vW1mC7HkGrdZCsUJiGwnY9Fq2taR38b9gAV1wBjz6ac1hbFpu+NZvzx5zEJhUmkvIwlY2rNYm0S0HY4nszxrGsoo5VlfWURIPZLX0KxeCCEBuqPVzPI2l7xNMuhqE6TePv6U4GQgghhNh+3Q7+P/zww5zfa63ZtGkTN910E/vtt1+PDUwIIYTYHelMDN3eArlqcR5APA6//jXcfLP/62Zem3Q4//jGJZz+1aP50sZafvvKKjbVJPDw9/4VRAJ849DRTBs/iPkrqrBdv7hgc/khixElESpjSRK2y9aGNHlBk0nDCvjejK4VIBRCCCHErtXt4H///ffPpvo1d9hhh/H73/++xwYmhBBCDGSZavotU+IPGFWMZRi4Xm4BXa01ntY4rsYwFPuNLALPgyefhJ/+FNavzzl/dflYHjjjB7w97gCq4zav/mkRAJahGF4cQSm/LEDCdnn8rbVMHl5EaTRIwFTEkjamobAMI9uiLz9kYRaHqY07XPj58Rw0ukTS+IUQQoh+pNvB/6effprze8MwGDx4MOFwuMcGJYQQQvQH7QXwnVmwcgt3v7KK5RV1pF0vp43fYWPLmFiez8rNtf5rNAb8jqfJTLubCp6552+Me+5uCj94L+fa26JFPH7KbF46/GQ8wyQMDC1QrKisB2DC0HwM1bSyX6Q1FbEU98xfxeyj9iRuu8QSNgo/bT9kmQwuCJEXNKmJ+0X7vnXYGAn6hRBCiH6m29X+58+fT3l5OWPGjGHMmDGMGjWKcDhMOp3mD3/4Q48PcMOGDXzzm9+krKyMaDTK/vvvn1NUUGvNddddx/Dhw4lEIsycOZMlS5bkXCOVSvGDH/yAQYMGkZeXx6mnnsr6Fisk1dXVnH322RQVFVFUVMTZZ59NTU1Nj78fIYQQA8OClVs456GFzHn0HS7/0wfMefQdznloIQtWbun0eZf8aRFvfbqV6niK+qRNdTzFW59u5ZI/LeLN1Vu54qRJDMr3q+fbnofdLPAfGavkzmd/zc9vOi8n8E+bFvcf/n987Ud/4IUjvoRnmOjGPf3b4jaeB9rTpOzczD2lFMXRAEs3xrj0Tx+Qtl0MpbLbCxJph3Xb4qyrjkubPiGEEKIf63bwP2vWLGpra1sdr6urY9asWT0yqIzq6mqOOOIIAoEAzz33HEuXLuXWW2+luLg4e84tt9zCbbfdxl133cXbb79NeXk5xx13HHV1ddlzLr74Yp5++mmeeuopXn/9derr6zn55JNx3aaUyrPOOotFixYxb9485s2bx6JFizj77LN79P0IIYQYGFq2wxtSECIvZLFsUx1XPr243QkAx/G45u8fURlL4boa02i7jd9hY8u48fSpAJhKoYACO8GP/vc4L93/XU5c/N+c686beAT/94MHmTvj23yatqhPOdSnHD7b2sCabQ1sjiVxtcbRZFv1ZWg09UmbbQ1pttSnSTkeGg0aPO1PDnhao5TihtOmyP5+IYQQop/qdtq/bvwHQEvr169vsw3gjrj55psZNWoUDz30UPbYHnvskTOWO+64g6uuuoozzjgDgEceeYShQ4fyxBNPMGfOHGpra3nwwQd59NFHOfbYYwF47LHHGDVqFC+99BInnHACy5YtY968ebz55psceuihANx///0cfvjhLF++nIkTJ/bo+xJCCNF/eZ7mnvmrctrhAYQNk/JCI5tCf8gepSyrqMtuCahNpPn18ytYVdWQvZbtelimgalUqzZ+h44t498fQ3HI4qsf/4fvPf8Ag+q25YzloyFj+cUxs3lr9FRM5bcF9LRmU20Cz9O42t/jrwxIu/6K/9aGFJGgSX7InySoqE2QsL3sNTX+hIOnNQooyw8SMA1c16MoEuz1z1cIIYQQvaPLwf8BBxyAUgqlFMcccwyW1fRU13X59NNPOfHEE3t0cP/4xz844YQT+MpXvsL8+fMZMWIEF1xwAbNnzwb8+gMVFRUcf/zx2eeEQiFmzJjBggULmDNnDu+++y62beecM3z4cKZMmcKCBQs44YQTeOONNygqKsoG/uAXMCwqKmLBggXtBv+pVIpUKpX9fSwWA8C2bWzb7tHPoidlxtaXxyh2jNzjgU/u8a6zdGOMdVvqGJIXIGhooFkavYLBeRYrK2r4+n3/o6ouhe36hfriaQetIWTqzKloQGkXy8hMAICjXRZ9tpW9yoKULl3Kg797iIkbPskZQ1VeCbfN/BbPTD0azzAJNY7BUI0r9p6LpSBiGihFYyDvn2MqTawhSdAIsqU2ied5hMzc96jQhC0DD41jO5TnR9jS4LK1Lo5tR3vpk939yM/xwCf3eOCTezzw9Yd73NWxdTn4P+200wBYtGgRJ5xwAvn5+dnHgsEge+yxB1/+8pe7N8pOrF69mnvuuYdLL72UK6+8koULF/LDH/6QUCjEt771LSoqKgAYOnRozvOGDh3KmjVrAKioqCAYDFJSUtLqnMzzKyoqGDJkSKvXHzJkSPacttx44438/Oc/b3X8hRdeIBrt+/84evHFF3f1EEQvk3s88Mk93jUu2bsrZyW7ccXcyv7RZS9T/dNHOGrBgtyzAgFWnnYaK884g8MiEQ5r47kdXTf3eKqdx1o+18meW7tiIf9e0cnTRLfJz/HAJ/d44JN7PPD15Xscb9Hmtz1dDv5/9rOfAX7a/de+9jVCodD2jawbPM/jc5/7HHPnzgX87IMlS5Zwzz338K1vfSt7XsttCO1tTejonLbO7+w6V1xxBZdeemn297FYjFGjRnH88cdTWFjY8ZvbhWzb5sUXX+S4444jEAjs6uGIXiD3eOCTe9w7PE/zcUUd1fE0JdEge5cXtCput3RjjIueep9o0CIcyC2dozV8uqWBlOuyR2kekaBJIu2xrroBBTiexmt2vsos/wMBQxFKNvDdBX/hO+/8AyOdG5z/e9JR/Orz32ZT0RD04rbHr4CIZRB3PEzl/92mgJBlMqjA/3u7KpYk7rigwVDgaggY/n893XQdwE/39zzygxaTRxbxu28cJMX+OtCV709z8nM88Mk9HvjkHg98/eEeZzLQO9PtPf/77LMPixYtykmRB3jrrbcwTZPPfe5z3b1ku4YNG8Y+++yTc2zSpEn89a9/BaC8vBzwV+6HDRuWPaeysjKbDVBeXk46naa6ujpn9b+yspJp06Zlz9m8eXOr16+qqmqVVdBcKBRqcxIkEAj02S9Gc/1lnGL7yT0e+OQe95wFK7dwz/xVrKqsx3Y1AVMxbkg+35sxLqfI3dRRpYwaVMCyTXWUF4ZyJonjKYdY2iNkWZgBC1srEq5L0lVYpsJTmrSjW7224bmc9tHLXPbqHxjcUJPzWN3U/bl82rd5oXi8P0/Q0UI/kHT9ietBeUHyQhaWYRAOGqjGkL6kQOHWpXA8TXE0QEVtEg+F1v7kRHOO1nhaURwIMHv6XoRCsue/PV39/rRFfo4HPrnHA5/c44GvL9/jro6r29X+L7zwQtatW9fq+IYNG7jwwgu7e7kOHXHEESxfvjzn2IoVKxgzZgwAe+65J+Xl5TkpGOl0mvnz52cD+4MOOohAIJBzzqZNm/joo4+y5xx++OHU1taycOHC7DlvvfUWtbW12XOEEEIMXN2p3m8Yiu/NGEd+yKQiliJhu3ieJmG7VNWnUcCQwlA22LYMf9+91mCgMJWi+WLwYWs/5NlHLuGm5/5fTuCvhw/n3YsvJvz2m5x92VlEgy025rfDbOzSt6U+TSLdOFPQGNNrralNOOw5OJ/CsJWtVmC7ulXgD342QGEkwC3/t69U+e/A9nZ/EEIIIXambgf/S5cu5cADD2x1/IADDmDp0qU9MqiMSy65hDfffJO5c+eycuVKnnjiCe67777sJINSiosvvpi5c+fy9NNP89FHH/Htb3+baDTKWWedBUBRURHnnnsul112GS+//DLvv/8+3/zmN5k6dWq2+v+kSZM48cQTmT17Nm+++SZvvvkms2fP5uSTT5ZK/0IIMcC1rN4fDpgYhiIcMCkvDFGfcrln/iq8ZsHxtPGDmHv6VCYNKyCecqisTxFPOYwdnEdxNEjQbPrrNRw0CFkmrqfx0BgGlBeF2bt+M/c+/UueevJKJleubhpQJAI/+xnOkiWsnzkTDINp4wax56AonSXchwMGgwvCBC0DDWyuS/HZ1gY+3dLA1oYUFbEU+SGTy4+fwKCCEBW1SVqH/D5DwdCCEHd9/QCO3Gvw9n68A972fH+EEEKIXaHbaf+hUIjNmzczduzYnOObNm3K6QDQEw4++GCefvpprrjiCq6//nr23HNP7rjjDr7xjW9kz/nxj39MIpHgggsuoLq6mkMPPZQXXniBgoKC7Dm33347lmVx5plnkkgkOOaYY3j44YcxzaZVlMcff5wf/vCH2a4Ap556KnfddVePvh8hhBB9z5KNMVZV1lMSDbaq86KUojgaYFVlPUs2xpg6sqml7bTxgzhsbBlLNsay7fwmlRcw65G3G7cEGI177hWDC0Ks3xbHdjSD3CSXvvAoX3r1LwRcJ+f1Np/yZbZdcz0TD5oEzR5bsjHGtgab4cVhtjakSdleq6DdVIqSaJCt9WlcrbEMcDxwPU087ZJ0PPYZVsAVJ03isLFlTe8RCJjKn5xodtFo0OTXX9lPAv9ObO/3p7/yPJ3znZ88vFDqQAghRD/R7Wj9uOOO44orruDvf/87RUX+X2I1NTVceeWVHHfccT0+wJNPPpmTTz653ceVUlx33XVcd9117Z4TDoe58847ufPOO9s9p7S0lMcee2xHhiqEEKIf2hZPY7s6Z7W+uZBpUOtptsXTrR4zDNUqoPvejHFc+fRiKmIpiqMBQqaBaSjyLc0pbz/Hxa8+Rmm8Nuc5K8dO5qYTvssHw/cm8NImxn1Yx5wjx7Qa45CCECXRIAnbpbohTU3CxjIUhqGwHY/quB/4GwrcxsqCmXhU4W89yExYbK1PM6woQm3CJuW4GI3bESxTURC2CBgGRRHZ49+ZHfn+9Dc7UtdACCHErtft4P/WW29l+vTpjBkzhgMOOADw2/8NHTqURx99tMcHKIQQQvSm0miQgKlIux5ho/W++pTrETAUpdGuBcKZLQGZIKnW0xy84m0umXcfe1V+lnNu/eBh3Hbcufxj76MoyQsxxDRIux7LNtVx/T+XcuH4NsYYMIkGLRSKupSDUn6xPqXAcXX2v5lFfMs0/E4DrseyijqeWLiWUaXRxsmEICV5AZJpD8fzssUBtQeV9akBEbDuiK6scvf096evytQ1qE85lDRubcl8V698ejFzT58qEwBCCNHHdTv4HzFiBB9++CGPP/44H3zwAZFIhFmzZvH1r3+9z1Y/FEIIIdozeXgh44bk56TqZ2itqYnbTBpWwOThXW/hmtkS8Mlr7xK64sfs8cZ/cx5PBMM8fNRX+d3nTkOHI4wuimRfN2yYlBcabKtPAn4A2tYYwwGDkGWQsP22fQHLwHE1brPA31D+/xR+t4G0q3lq4Vp+efrUnIA1EjSBpsA16boDImDdEV1d5e6N709f07KuQcvvakUsxT3zV3HY2DLZAiCEEH3Ydm3Sz8vL4/zzz+/psQghhBDd0hP7jzPV+1um6qdcj5q4TX7I5HszxnXvutXVGNdfz4S77kI5ufv6Xzr0JB49+XzWh4up29pA2G1dCE4pRVHEn1BfuimGZQWYNm4QKyvrqYglKY4GCZkGhZEA8caK/gWhANvi6Wzgr8is+qvsEVNBRcyfVBjoAeuO6M4qd698f/qY3a2ugRBCDFTbXaFv6dKlrF27lnQ6NyXw1FNP3eFBCSGEEJ3pyf3HbaXqBwzFpGEF3buebcO998LPfgbbtuVU518ydir3n3ERq0b7XWTcpI0CbNcjaXuNq+9NQo17yH/+7FIq621sV+NpD1dDdUMaw1AEDJUN0LfUpbLPVfiZAGZjoKa138ovbPnXrEnYAz5g3V7bs8rdY9+fPmp3qmsghBADWbeD/9WrV3P66aezePHixn2G/hpD5i9H13V7doRCCCFEC5mV2bqkTTRoETANPK1ZujG23fuP26re361Mgueeg0svhY8/zjm8oXgo95/yPd753NEo1RQ8WYaBUuABjufRPO0eoCbpB1KbahIU5oWzq8/bGtIELYNvHT6GI8cPzgb/SzbG+Mu763j0zTUoMgX+/C0AjqcxlaIoGgDt71OfOrJoQAes26snuz8MlEr4u0tdAyGEGOi6HfxfdNFF7Lnnnrz00kuMHTuWhQsXsnXrVi677DJ+/etf98YYhRBCiKzMyuy2hjSup4klk9mCd0HTwHb1du8/bqt6f6eWLoXLLoN583IOJ0IR7j3q69yz/8k4VpDI1gSDC0Lkh/y/esNBg4BpknLc7Ap903v0siv5w4rDuI0TA2HDZFhRmIpYigWrtjJnetPq/NSRRUweXsh7a6v5uKIOT+vs5xIJGAzK93vON0/nH8gB6/bq6e4PA8HuUNdACCF2B23/zdaBN954g+uvv57BgwdjGAaGYXDkkUdy44038sMf/rA3xiiEEEJkLdkYY+nGWhK237veUMpvd6cUSccjYTss3VjLko2x3h3Ili3w/e/DvvvmBP5aKZ753El8fs593Pm5M0iZQVwN9SmHddvi1KcaawBoCFqKoGVQk7BJ2C6ep0nYLhtqkjR26sPoZPW5OcNQXHHSJIYXhckLWgwuCDGqJMrQwjD1KbfNdP5MwDpjwmCmjizarQN/yF3lbsvuuMqdqWuQHzKpiKVyvqsVsdRuvU1ECCH6k24H/67rkp+fD8CgQYPYuHEjAGPGjGH58uU9OzohhBC7Jc/TLF5fy/wVVSxeX4vnNRXF29KQIpZ08LSfpm4ohVL+fwOGwtOaWNJhS0Oqg1fYAek03HEH7LUX/Pa30Gy7m54xg4t+9ACXHnshldESLNMgYDYFRI6n2VQTJ2E7VMRSlESDXHbcBPYZXkg85VBZnyKechhZEiE/2H5yXsg0sNtZfZ42fhA3nrEvU0cWoYC6lEMi7a/4Szu2jr9b0LTKXR23s1sbMzKr3OOG5O92q9yZugaThhXkfFfleyWEEP1Ht9P+p0yZwocffsjYsWM59NBDueWWWwgGg9x3332MHTu2N8YohBBiN9JZIb+aBhvP0xiGanNPtqEUnqepabB7dmBawz//6af4f/JJ7mPjxsGvfsWHB83k+fveRLkeAcuvtG8ohULjeB6ehqSTSZMuzL6nc48cm5N672nNRU+80+5QOlt9lnT+tnWlSOTuUL1/e8n3Sggh+rduB/9XX301DQ0NANxwww2cfPLJHHXUUZSVlfHHP/6xxwcohBBi99GVFmsl0QCG4Qf42tDNWtmBRmcnBkqigZ4b2OLFfjG/l17KPV5YCNde66f/h0Is+t9n2K6HZaiccZmGwlAGjufhevDlA0byk5P2zgZNLfeKe55mz8F5QAMtFp+7vMd6oO4/317dad830Kv37wj5XgkhRP/V7eD/hBNOyP567NixLF26lG3btlFSUtJqBUYIIYToqq62WLv8+IkUhgPUJmwcV2MaflE7rcH1NEopCsMByvJDOz6oyko/uL//fvCa7QE3DJgzB37+cxg8OHtYZ/4abOOvQ6WUP2mhNcNKIh2ulhqG4twj9mTrx5VsrksRDQdl9XkHbG/7PlnlFkIIMZB0O/hvS2lpaU9cRgghxG6sqy3WAPYZXsiH62twXE3a9dCePwEQsgwsU7HP8MId25OdSsH/+39www0Qa1E48Nhj4fbbYcqUVk87YFQxlmHguh6GqVtVRXddjWUYHDCquNMhHDq2jH9/DBPL81m+OS6rzztge9v3ySq3EEKIgaRHgn8hhBBiR3W1xVpNws7uya5POZQGgtmV/4Ttkh+ytn9VXGt45hm4/HJYvTr3sb328oP+L3zBn2low9QRRUwsz2fJxhi252EZBgrQgON5aPxgfuqIrgeUv/vGQayoSsjq8w7YkfZ9QgghxEDR7Wr/QgghRG/oTou1psrjhbieJmF7uJ5m0rDC7a88/v77cPTRcMYZuYF/cbEf9H/0EXzxi+0G/tDUam9wQQhDKVxP43ga19MYSjG4IMQVJ03qVvAurfh2nLTvE0IIIWTlXwghRB+RabG2bFMd5YVGq5T5mniakSVRtjSkWLy+lsPGlvXMnuyKCrj6avj978mprmeacMEF8LOfQVlZly83bfwgbj9zf+5+ZSUfV9Rlq8rvXV7ABTPHS7r+LtD5d6vzAopCCCFEfyfBvxBCiD6hoxZrVXVJUo7Hum0N/PjPH7bZoq3bkkl/RX/uXKivz33spJPg1lth0qTturQUi+tbpH2fEEIIIWn/Qggh+pCmdP4C4imHyvoU1Q1pUo5H0DQozQsxpCBEXsjKtmhbsHJL915Ea/jzn/3A/sorcwP/SZNg3jz497+3O/DPkHT9vqWt71Y85TBpWMH2bxURQggh+hFZ+RdCCNGnZFbNF2+o5f011fzhzTU4rsfIkgiG4c9Zd9SirUPvvAOXXAKvv557vKwMrr8ezj8fLPmrcaCSjAwhhBC7M/kXjhBCiD7nzdVbuWf+Kj7eVMfWhhSGUqzZFmdwQZj8kP9XV0ct2lrZsMFf5f/DH3KPWxb84AdwzTVQUtKtMXqeliCyH5L2fUIIIXZXEvwLIYToUxas3JJt4xc0/VZ5hgEJ22NDdYIRJZHsBECnLdricfj1r+Hmm/1fN3fKKf5jEyZs1xjvmb+KVZX12YJ+Xa1BIJMGQgghhNgVJPgXQog+aHcNED1Pc8/8VdSnHMoLwyRtD8NQKBQBA2xPU1WXJC+Yh1Kq/RZtngdPPglXXAHr1uU+Nnky3HEHHHvsdo2x+eRESWMLubqkw4frarjszx/wq//blyP3Gtzuc7d30kAIIYQQYkdI8C9EB3bXAEzsWrtzgLhkY4xVlfWURIMopQgHDUKWSdJ2sUyFZShSjkfS9ggHjLZbtL35Jlx8Mbz1Vu7FBw+GX/wCzj13u/f1t5ycaEi7bKpNknJcPE9Tl3L4/pPvc9fXD2g1AdBy0iBoGqRdL1u4UIrOCSGEEKI3SfAvRDt25wBM7Dq7e4C4LZ7GdjVB0y/sp1AMLgixoTqB42oM5Rfrb0g71CR0bou2devQP/kp6sknci8aCPiTAVddBUU7tte7+eREQ9plQ3UCT2tMQ2FaCtfTxBI2P/rLh9z6lf2y96rlpEGmz/x2Fy4UQgghhOgmafUnRBsyAdiyTTHyQtaOtxYTogtaBojhgIlhKMIBk/LCEPUpl3vmr8Lz9K4eaq8pbUyjT7te9lh+yGJESYRwwMTTGk9rbNdratFWHoZrr8WdMKFV4P/OATN477nX4ZZbdjjwh6bJiYCpqKpL4WmNZSoM5W9NMJX/64YW96plRkNzLQsXCiGEEEL0Bln5F6IFWaETu0p3AsS9h0a36zWab2UpjgQAqEnYfWZby+ThhYwbks+yTXWUFxrZzyE/ZBENGmyoSTKiOMLc06cydVgBxuOP+VX8N27EbHad1cPH89svXcj84VPIf6+BuWO29EjGRGmzPf4px8VsrEeQoQGloDBi5XQhaJnR0FKnhQuFEEIIIXaQBP9CtNCdAEzaRYme1L0AsfvBf/OtLA1pl6TtojVEAiZ5IbNPbGsxDMX3ZozjyqcXUxFLURwNEDINUq5HTdymOBLgqi9MYr81H8EZl8A77+Q8vzq/hEdPOZ+XDz0JzzAp17pHJ+wykxMfrqvB8zSm1Szw1xrH00QCBoUhi6qGdDaYb57REDbMVtdtt3ChEEIIIUQPkbR/IVroSgBmywqd6AVtpbw3tyMBYvOtLEop4ikHx/VwPY+E7aAUPbqtxfM0i9fXMn9FFYvX13Zrq8K08YOYe/pUJg0rIJ5yqKxPEU85TBpWwK2fK2TalRfAUUflBP5pM8CTx3yDOdc+xYuHn4zXGGD3dEp9ZnIiGrLQGhzX8//nedieh6kUgwvCpD2dc68ykwbVcRutcz8LrTU1cZtxQ/JzCxcKIYQQQvQgWfkXogVZoRO7Snsp79AUIGYq27uu0+XrNt/KMrQwxJqtCTQQsAzQfvu82oTNmNIom+vSO7xK3p1ime111Jg2fhCHjS3LPjbIS7HPI79FXXg7pFI516g88RTO2+dM3NFj2hxzT6fUTxs/iG9P24NfPb8cx9P4yf5gKijND5IXNKmIpXK6EHSW0ZBTuFAIIYQQohdI8C9EC90JwIToSd0JEF2369dtvpUlZevcveoKLANSjkfK0Tu8raU73Qo6myQwDMXUYfnw8MN+pf7Nm3Nf7MAD4Y472Lznvmx59B3ydtKE3YKVW3hy4VqiQYOGlL91wjDA07C1IUU87VKaF2gVzGcyGjLvubYxO2DSsIJdvt1CCCGEEAOfBP9CtCArdGJX6o0AsflWloa0g9agmu1qUfjt8xzPIy9obfcqeXeKZb65emvnkwTrP0JffDHqgw9yX6i8HG66Cc4+GwyDyZ7eaRN2zd/j6NI8GtIuVXUpUo6L0hrX0xgG3HDalDbvVcuMhr5SaFEIIYQQA58E/0K0QVboxK7U0wFi860slmGglB/sZ2LkTIV6yzB2aJW8q8UyF2+ozZkkQEEy7e+bLwpb5G9cQ+DMn8P782l+lZQV5N8nfpNhN1zDYfvtkT2+MyfsWr7H/JBFXsjMjt/1/AmAokj7n59hKCkWKoQQQoidToJ/IdohK3RiV+rJALH5VpahhUFClknSdlEmoMlWqA9Zis116e1eJe9qt4L319VkA+jmK+fRRAMXLvgj337n7wRb1DR45cBjue8Ls1kRKiX/hU+Zm5efMwm3sybs2nqPCkUkaAImnqeprE9JQVAhhBBC9DkS/AvRAVmhEwNB85XxzbE0RZEAKdvFdvyuAqahKIwE2FyX3qFV8q4Wy1QabFeTdj021STBsfnKBy9w2auPUpbIrcj/wfAJ/L9TLmTNXvsRDhiUQ7ut+3bGhJ0UBBVCCCFEfyXBvxBC9EHtVcHfXi1XxqMhi6TtF6uLBE3Q7PAqeVeLZe4/upiAqaiMpTh09Xtc9dL97L1lTc61NuWXcePRs3h20nS0MjC21BOyTIYWhjosStjbE3b9tSBoT3+fhBBCCNH/SPAvhBB9THda5XVHy5Xx4kgAgJqE3SMBYVf33k8dUcT+iUrOeOoOjl25MOcacSvEPYf9H/cfcjrJQDh73NOQsF3WbI0zuCCEhp2SWt9W0NzfCoL21vdJCCGEEP2LBP9CCNGHdKdV3vbo7ZXxTvfel5lw+WXc9f/uxGixr/+vk4/mlhnnsLmg/fengaq6FCVRq9dT6zsKmvtLQdDe/j4JIYQQov+Q4F8IIfqI7rTK6yvaWhlvc+/9kCjG/ffBz34GW7fSvCTgOyMmcf0xs/lw2IQuvaYG0h5MKi/olfcEXQuaH5l1SKep9Lsy3b4736e+lKkghBBCiN4hwb8QQvQRXW2Vt2RjjL2HRnfRKJt0lk6ezTCYNw8uvRSWLct5/ubiIVw/fRb/2vvIpr6DXaQ0LKuo65Ushu4EzR29/q5Ot+/O90kKmwohhBADX9v9mIQQQux0XWmVZ3u6T7SRy6yML9sUIy9kMaQgRF7Iyq6ML1i5xQ/2TzrJ/1/zwD8/H++Xv+S7Vz/OvyYd1a3AX+F3JzBN1WufQ3eC5vZ06fPpZf3p+ySEEEKI3ifBvxC7Mc/TLF5fy/wVVSxeX4vn6V09pN1a8zZybdnVbeQy35f/Lq/klueXZ1fGwwETw1CEAyblhSHM6mrq51yAnjrVX/XPUAq+8x345BOWfOtCNqcVZXnBLsX+lqEImgrDgKBpELGMXvscdjRobpk50PLzqU+53DN/Va//vPX175MQQgghdi5J+xdiN7WrU5JFa11tIzepvIAlG6oBWLoxxtRRpd3as+04Hs9+uIkNNXFGFEc5Zd9hWFbHc8GvLa/iF/9exqbaBK6nSdouIcukIe2SH/L/KrEcmy+89jRff+4h8pP1uReYPh3uuAMOOACAbSuqsF1NeWGYwohFRW2KlOPSVjwcMBSGoXA8jakUAdNg/NDea6fXPGgOG2arxzsLmvtKun1/bUsohBBCiN4hwb8QuyGpAN43daVV3vS9BjHrkbdZt6WOS/aGi556n1GDul5l/v5XV/HbV1ZRl7Dx8NO/fv7PJVw4cxyzp49r8zlX/e1Dnnx7XavAPGm7bKhOMKI4zNErF3Lu03cxomp97kl77gm33gqnnZaT3t88wM4PBRg3xCKZ9nA8D8fT1CZs6pJ+NwAPwPNX4gOmQWleoFfb6e1o0NyVzIHanZBu39XWi1LsTwghhNg9SNq/ELuZvpKSLNqWaZU3aVgB8ZRDZX2KeMph0rACvnHoaB5/ay3LNsWIBv2522iw6/vI7391FTfPW05t3MbIptErauM2N89bzv2vrmr1nPvmr+Txha0Df/Cr7o+rWM3cey7l2vt+mhP4NwQjbLry5/5e/9NPb7WvPxNgV8dttNYoFJGgSUE4QHEkQMgymTK8kP1GFlEUtsgLWxRHLPYbVdTrk1OZoDk/ZFIRS5GwXTxPk7BdKmKpDoNmz9Nsq0/jaU0saaNp/cHtzHT7jr5PMsknhBBC7F5k5V+I3UxfSUkW7WurVd6k8gJmPfJ2dtImaPhBZThgUF4Y6rRtm+N4/PaVVbieJmgpDOXP/RoKDOWRdjS/fWUVs6btmd0C4Dget7/0SZtjLI3Xculrj/H1D+Zh6qYA11MGTx90Iv856/vcedGJ/gu0oSur0ld+YVLrloE7qVVeJmjObI2p9TQBQzFpWPtZFpmtNCs31xFL2lTH02xrSDOkMJzdGrEr0u3bbL24E1sOCiGEEKJvkOBfiN1MX0lJFh0zDJUz+bJ4fW2LSZumgLsrkzbPfriJuoSNZTYF/tnXUgaW6VGXsHn2w02cfuAIAP7+wUYSdm6xuKBjc867z/LDBU9RkI7nPPb++AO46YTvsXnMeOaeMrXT4LKrAfaumoTqTtDcaiuNZbKxNkE87bJuW5wRJRECprHL0u1bfp+EEEIIsfuR4F+I3cyOFjMTu8aOTtpsqInjAVY78aahwG08L2PR2pqmE7TmhE/e4Mr//p4xNRU5z/20eBi/POY8Xpt4GBPKC5h70qQup5PvylVpz9Odvm5XguaWW2mUUtntNJWxJAnbZWNNgsH5oQ4zB4QQQgghepME/0LsZqQCeP+0o5M2I4qjGICn287E9zSoxvMyIiH/dfbZvJprXr6Pw9d9lPOc2lAevzniLJ486AsUl+QTSXvEEna339uuWJXuyW4X7W2lyQ9Z5A3KoyZhE085/OiEvfnS/sMl3V4IIYQQu4QU/BNiN7MjxczErtOyQF5zmUmbcUPy2520OWXfYRREAjiuxtO5qfye9nBcTUEkwCn7Dmt6zhDFzf/+Df98+KKcwN9RBn844AvMPP8+fn/wlyguKWBQfpiRJREa0l6bBSM9T7N4fS3zV1SxeH3tLi0omUnRX7YpRl7IYkhBiLxQ1wsnttRRVoZSiqJwANM0KM0Pys+VEEIIIXYZWfkXYje0PcXMxK7VskDe4Dz/j++E7VHV4HQ6aWNZBhfOHMfN85aTdjSW6WEof8XfcTWmobhw5ji/2F8yCXfcwZRf/pKp9fU513l1jwO4/pjZrBw02r+uoSjL97MN2qs90N4q+5zpYymKBHdqun9bKfoAYcOkvNDotHBiW2QrjRBCCCH6Awn+hdhNSQXw/qf5pM26LXUAJNJOlydtZk8fB8BvX1lFXcLGxU/1L4oGuHDmOGYfNRb+/Gf40Y9gzRqafxNWlY7gF5+fzSvjPpc9ZigYVRpFNTuzZe2BVoXwTIO06/Hh+hrO+8M75AVNDGXsUNp9d/RGtwvZSiOEEEKI/kCCfyF2Y1IBvP/JTNosXreNzxa9zm++dgBTR5V2edJm9vRxzJq2J89+uIkNNXFGFEc5Zd9hWB+8D0cdBf/7X+4TSkpY/YMf8/PyI/iwMk7Y9ki5HmHLoLwokm1hl9F8lbu9VXbH1sRTLo6nMVDsURbG9nQ27b43+8/3RreLrrQtlK00QgghhNjVJPgXQoh+xjAU+wwv5LNFsM92ZGtYlpFt58fGjXDed+CRR1qeBBdcAD/7GWNLS3m4sTL+loYUv3npE9ZXx8kL5qa4t1zlbmuVXaOpqkuhgYClsD2PtKuJBLc/7b47eitFX7bSCCGEEKKvk+BfCCF2R/E43Hor3HST/+vmvvAFuO02mDgxe6h5lkjINLq0yt3WKnsy7ZFyXEzD3yzgaI3jeYC53Wn33dGbKfqylUYIIYQQfZkE/0II0Y9lquh3OdjUGp56Cn78Y1i/PvexyZPh9tvhuOM6fL2CcICvHjya55dUUBlLtrvK3dYqu+N5aA3K8IeiFFhG0+RAd9LuvcZshO4E2r2doi9baYQQQgjRV0nwL4QQO9H2BKwdmfPYO3y4Pka97YGGoYUhfnHaFGZOHJo9x3E8nv1wE84bb/D5e2+kbPF7uRcpK4MbboDzzvPT/dvRsmq/ZcDQoggnTB7KkeMHt3ovba2yW4aBUv7n4GqIBAzCgabgv6tp9+11EOhKir2k6AshhBBidyTBvxBC7CQ7ErC29NbqrQC8sXobKbcp4F5XneTbD73DMXsP5sFvH8L9r67iL8+8wfeef4CvLJ2fe5FAAH7wA7jmGigu7nTsbVXtX1+d4I9vr2O/kcWtJjHaWmUPWv4EQNJ2CZiKwQVNhQC7mnbf3li6UzBQUvSFEEIIsbtpu9yxEEKIHpUJWJdtipEXshhSECIvZGUD1gUrt3T5Wp6nue3FFR2e8/LHVXz1theJX3kNz9x5Lqe1CPxfHH8of3z4OX/ffyeBf8uq/eGAiWEowgGT8sIQ9SmXe+avwvN0q+dmVtknDSsgnnKoqk8TDZqEAgbhgIVpKDxPk7BdKmKpTtPud2QsLWVS9GdMGMzUkUUS+AshhBBiQOtXwf+NN96IUoqLL744e0xrzXXXXcfw4cOJRCLMnDmTJUuW5DwvlUrxgx/8gEGDBpGXl8epp57K+hZ7Xaurqzn77LMpKiqiqKiIs88+m5qamp3wroQQA11PBqwAizfUsnRTrN3HlfY4/aP/8JuffY2L/vckEadp//yywXvw9a/NZfaXr+EXy20cx+v09dqq2p99rRZF+toybfwgHpl1CPee/Tl+/ZX9eHjWITzwrc+x36gi4imHyvoU8ZTDpGEFna7a7+hYhBBCCCF2V/0m7f/tt9/mvvvuY9999805fsstt3Dbbbfx8MMPM2HCBG644QaOO+44li9fTkFBAQAXX3wxzz77LE899RRlZWVcdtllnHzyybz77ruYpl+E6qyzzmL9+vXMmzcPgPPPP5+zzz6bZ599due+USH6mZ7ewz4QdSdg7UqxuLc/20p70wQHrl/Gz16+j/0qPsk5vjVaxK9mfIs/Tz0WT/l/7tWnXP7+wUa+fNDIDl+vrar9zXWlSF9bhfCmjRvU7e9OT4xFCCGEEGJ31C+C//r6er7xjW9w//33c8MNN2SPa6254447uOqqqzjjjDMAeOSRRxg6dChPPPEEc+bMoba2lgcffJBHH32UY489FoDHHnuMUaNG8dJLL3HCCSewbNky5s2bx5tvvsmhhx4KwP3338/hhx/O8uXLmdis3ZUQoklP7mEfyHo6YP3fyq2tjo2oreQnrzzEqR+/lnM8bVg8eMiXuPvwr1IfijY90Dh78P66mk6D/7aq9oP/Z3DSWnqutQAASg5JREFU9mhIO2itKY4EujT+jO2pjN/eWDK6WjBQCCGEEGJ30y+C/wsvvJAvfvGLHHvssTnB/6effkpFRQXHH3989lgoFGLGjBksWLCAOXPm8O6772Lbds45w4cPZ8qUKSxYsIATTjiBN954g6KiomzgD3DYYYdRVFTEggUL2g3+U6kUqVQq+/tYzE8ztW0b27Z77P33tMzY+vIYxY7ZGff4rdVbuf6fS6lPORRHmoqurdoc47q/f8i1J+/DoWPLeu31+5PikEFeALTnEmhjAiDheeRZ/nlduWcWLiHDj96LnTjffv2vzHrracJu7nPnTZzGr46ZxYaScgBCzfIFdOMvC6zOvycTBkeYODTK8op68gMhlIKGtMuWuiQpx8PRmqBhcPsLyzjvyD179b63NZbm7ymeTDOxPJ8JgyP9/s84+bN64JN7PPDJPR745B4PfP3hHnd1bH0++H/qqad47733ePvtt1s9VlFRAcDQoUNzjg8dOpQ1a9ZkzwkGg5SUlLQ6J/P8iooKhgwZ0ur6Q4YMyZ7TlhtvvJGf//znrY6/8MILRKPRNp7Rt7z44ou7egiil/X2Pb5wfOZXiVaPbf34Lf79ca++fL9yyd6dn/PZotf5bFHn551cCicXe4x++b/Mf+wxwtXVOY/XjB3L4nPPJTV5Mj8EwG3/Yu4q/v3vVZ2+5mllQBlAvL0LAZVs/biy1+9752OJM2/ec707iJ1I/qwe+OQeD3xyjwc+uccDX1++x/F4e/8mytWng/9169Zx0UUX8cILLxAOh9s9r+UeWq11q2MttTynrfM7u84VV1zBpZdemv19LBZj1KhRHH/88RQWtt+malezbZsXX3yR4447jkCge2m6on/o7Xu8dGOMi556n2jQyunRnpGwPRJph9987QD26aBl2+6kKVPCpSgSIGQapFyP2oRNfsjsVqbEosf/Tv4VP2FSxeqc41V5Jfz66HP4+9Sj0Q0GLOz4OnuURfnHhUd2uUbDW6u38sDrq3n3sxpsz8M0IGxZDCoIkRc00Ro216WYWJ7P775xUK/Wfnhr9VYe/N+nfFrVgO1pAoZiz8F5nHtE72Ye7EzyZ/XAJ/d44JN7PPDJPR74+sM9zmSgd6ZPB//vvvsulZWVHHTQQdljruvy6quvctddd7F8+XLAX7kfNmxY9pzKyspsNkB5eTnpdJrq6uqc1f/KykqmTZuWPWfz5s2tXr+qqqpVVkFzoVCIUCjU6nggEOizX4zm+ss4xfbrrXtck/JosCEvbGLr1gGeYSgaHIealCffsUZHTiznOtNqqpHgOQQMxbihhV2vkbB6NfzoRxz8t7/lHE6aAe4/5HTuOewrxIMRaCzgP2FIHptiKeqSTs75CiiOBvjZqfsSCnV9b/yRE8spiIY575F3KDCVP/kTNFAo7MZtBNFwkOWb46yoSnR7P393HDmxnGl7Dd0tik3Kn9UDn9zjgU/u8cAn93jg68v3uKvj6tPB/zHHHMPixYtzjs2aNYu9996bn/zkJ4wdO5by8nJefPFFDjjgAADS6TTz58/n5ptvBuCggw4iEAjw4osvcuaZZwKwadMmPvroI2655RYADj/8cGpra1m4cCGHHHIIAG+99Ra1tbXZCQIhRBMpurZ9po0fxGFjy7ofsMZicMMN8JvfQDq3KOC/Jh3FL2fOYmNh7tal/JDJkMIIWxvSWAa4HigF0aDFfiOLuPDo8dtVlLEm4e8pK4kG2xz3zqy2vz0FA4UQQgghdld9OvgvKChgypQpOcfy8vIoKyvLHr/44ouZO3cue+21F3vttRdz584lGo1y1llnAVBUVMS5557LZZddRllZGaWlpVx++eVMnTo1W/1/0qRJnHjiicyePZt7770X8Fv9nXzyyVLpX4g2TB5eyLgh+SzbVEd5oZGzPUZrTU3cZtKwAiZLyn8r3QpYXRd+/3u46iqoqsp5qG7q/rz/ja/xi/R+JFxNIO2htR/gF0UsTNPk44oYpXkhhhaEqUv9//buPLzJKu//+PtOmqR7oYW2VBChIFbADZVFpbgMqLigj+M6uIyjiLKJC4o64sIy6iguIzLODMwjbvP8FMcZGQRHqUtRFEVLrQgVEKS1rF1oSdPc5/dHbCCUnbZJ08/runppzjlJvrlPqv3eZ6ujvKaOBI+TkYMO/TSGaL/xo6MrRUREJFpFdPJ/IO6++25qamq49dZb2bp1K3379mXBggUkJSUF2zz11FPExMRw+eWXU1NTw9lnn83s2bNxOnf+4fryyy8zZsyY4KkAF110Ec8991yzfx6RlsDhsBiZm83EuQWUVnhpE79zDfu26sAa9pG52UqaDsf778O4cbDb7CeOOAL+8AdiL7uMrfPnk7M5hRU/V+N2Bda9d22fQHmNj5LyHWQkefDWGap9fjwxTjq1jeHnylpmfvgDA7LbHVL/RPONHx1d2fh0M0VERCRytLjkf9GiRSGPLcti0qRJTJo0aa/PiY2N5dlnn+XZZ5/da5vU1FTmzJnTSFGKRL8B3dox5ZLewWSp/JdN13I6JClZOhwrV8Kdd8Lbb4eWx8fD3XfDXXcF/v2XI11euKYP32+sCSZXtjGMnLMUT4yDtVuq8dbtnBHgiXGQHOeiuKyKwg0VhzRlPlpv/OSv2sTEuQVUeetoG7/z6Mqikkomzi1gyiW99Z0+SLqZIiIiEllaXPIvIpHjkNewS0PbtsHDD8NzzwUT+6Df/AamTQuM+u9m92UEed9vZLvXT42vDr+BGIeFZYEhcApDbZ2XOHfMYa3Jj7YbP7ZtmJFXTJW3jszk2OBshliHk8xkB6UVXmbkFdOva5q+2wdIN1NEREQij5J/ETks2nTtMNXVwZ//DA88AFu2hNb16xfY5O+XjUgPRJs4FzU+P37b4HLunJZvAS4H+Pw2NbV+2sQd3m610XTjp3BDBcVlVbSNdzc43tWyLNrEH95sidZGN1NEREQik5J/EZFwWbAgsK6/qCi0/Mgj4bHH4PLLA/P1D1LwKbs/1dqt/jBFy42fLdW1+PwGt9Oxx/rmPMEgGuhmioiISGTa8186IiLSdL77DoYOhSFDQhP/+Hh45JFA/RVXHFKWvq3GR6zLicOyqPMbbGMwBP5Z5zc4LItYlzN4ZJ+EnmCwJy39BIPmdiA3U3y6mSIiItLslPyLiDSXLVtgzBjo3RvmzdtZbllw/fWwahXcfz/ExR3yW6TGu0lwO0lPjiXW5Qwm/bYxxLoC5QlupxLZXdSfYLC12ocxJqSu/gSD7PTEFnmCQTjoZoqIiEhkUvIvItLUfD545hnIzoZnnw2s8693+unwxRcwaxZ06HDYb1WfyHrrbDqnxdE5NYGObQP/7JwWh7fOViK7m/oTDBI9TkorvNT4/Ni2ocbnp7TC22JPMAgX3UwRERGJTEr+RUSaijHwzjvQqxeMHRvY0b9e587wxhvw4Ydw0kmN9pa7JrI/V9SCBQnuGLDg54paJbJ7UX+CQU6HJKq9dZRVean21pHTIUk70x8k3UwRERGJTNrwT0SkKRQWwu23w8KFoeWJiYGp/ePGgcfTJG8diUfx2baJ+JMBoukEg3CLxO+giIhIa6fkX0SkMW3cCL//feD4PnuXNc8OB9xwA0yeDBkZTR5GJCWy+as2BZNAn9/gclpkpydGZBIYLScYRIJI+g6KiIiIkn8RkcZRWwvPPQcPPQQVFaF1gwbB9Olw/PHNGlIkJLL5qzYxcW4BVd462sa7cTsd1PptikoqmTi3QFPqo1wkfAdFREQkQGv+RUQOhzHwz3/CscfCHXeEJv5duwbq3n+/2RP/SGDbhhl5xVR568j85fQBhyNw1GBmsocqr58ZecXYttn/i4mIiIjIYVHyLyJyqL75Bs46C4YNg+LineXJyfDHP0JREVx0UeAov1aocEMFxWVVtI13Y+12DSzLok28i+KyKgo3VOzlFURERESksSj5FxE5WD//DDfdBCeeCIsW7Sx3OmHkyMCNgPHjwd26zzHfUl2Lz29wO/f8vxqP04HPNmyprm3myERERERaH635FxE5UF5vYO3+5MlQWRlad845gbqePcMRWURKjXfjclrU+m1iHc4G9V6/jcthkRrfum+SiIiIiDQHJf8iIvtjDLz5Jtx5J6xZE1p39NGBpP+888IRWUTrmZVMdnoiRSWVZCY7Qqb+G2PYVu0jp0MSPbOSD/g1W8KRgSIiIiKRSMm/iMi+fPkljB0LH38cWt6mTWBn/5EjweUKS2iRzuGwGJmbzcS5BZRWeGkT78LjdOD122yr9pHocTIyN/uAk/eWdGSgiIiISKTRmn8RkT0pKYEbboCTTw5N/GNiYPTowLr+MWMaJfG3bUPB+nLyvt9IwfryqNr9fkC3dky5pDc5HZKo9tZRVuWl2ltHToekgzrmr/7IwKKSChI8MaQneUjwxASPDMxftamJP4mIiIhIy6aRfxGRXdXUBHbqnzYNtm8PrTvvPHjqKejRo9HerjWMZg/o1o5+XdMOebr+7kcG1i8fiHU4yUx2UFrhZUZeMf26pmkJgIiIiMheKPkXEYHAuv7XX4e774Z160LrcnIC6/oHD27Ut6wfza7y1tE23o3b6aDWbwdHsw9mZDzSORwWvTumHNJzD+bIwEN9DxEREZFop2n/IiJLlsCAAXDVVaGJf1oa/OlP8M03jZ747z6aHety4nBYxLqcZCZ7qPL6mZFXHFVLAA6VjgwUEREROXxK/kWk9Vq/Hq65Bvr2hU8/3VnucsHtt8OqVXDrrYF1/o3sYEazW7tdjwzcEx0ZKCIiIrJ/Sv5FpPXZvh0efDBwTN8rr4TWXXghFBbCk08GdvRvIhrNPnD1RwZurfZhTOhMiPojA7PTEw/qyEARERGR1kbJv4i0HrYNc+YEkv6HHw5s7levVy/473/h7behe/cmD0Wj2Qeu/sjARI+T0govNT4/tm2o8fkprfAe9JGBIiIiIq2Rkn8RaR0WLw5M7x8+HDZs2Fnevj288AIsWwZnndVs4Wg0++A01pGBIiIiIq2VdvsXkei2di1MmBDYyX9XbjeMHQv33w/JzZ9g149mT5xbQGmFlzbxLjxOB16/zbZq3yGPZtu2OeQj9SLd4R4ZKCIiItKaKfkXkehUVQXTpsEf/wg7doTWXXIJPPEEdO0anth+UT+aPSOvmOKyKsptg8thkdMhiZG52Qc8ml2f8H+8aiPvFv7Mz+U11Nngclpkpyce1GtFusM5MlBERESkNVPyLyLRxbbhf/8X7r0XSktD644/Hp55BgYODE9se3C4o9mf/bCZmR+v5dsNFWyrrsUAsTFO2id5cMc4KCqpZOLcAk2NFxEREWnllPyLSPT48MPAVP5ly0LL09Nh6lS4/npwRN5WJ4czmv3wv79lS42f6lo/ADFOC6/fpqR8B0e0jSMz2UNphZcZecX065qmKfIiIiIirVTk/RUsInKwVq+G//kfyM0NTfxjYwMzAIqL4be/jcjE/1DZdmCTwCpvHSmxLupsmxinA6flwOWw8BvDxsrAcoc28S6Ky6oo3FARzpBFREREJIw08i8iLVdFBUyeDNOnQ21taN2vfw2PPw6dO4cltKb2XWklAG3i3FTXGYwB65d7G5ZlEeMAb53NDp+NJ8ZBuW3YUl27j1cUERERkWim5F9EWh6/H2bNgokTYePG0Lo+fQLr+gcMCE9szWTrL4m82+mg1jZYFoEbAL/M6rcIPK6zbfCDy2GRGu8OX8AiIiIiElbRMwdWRFqHDz6AE0+Em24KTfw7dIC//x2WLIn6xB+g7S+JfK3fJtbtwBPjxG8bDIHlAIbAjQCnZbGt2kd2eiI9s5r/SEMRERERiQxK/kWagW0bCtaXk/f9RgrWlwfXa8tBWLUKLr4YzjoLCgp2lsfGwgMPwMqVcO21UbWuf1+OyUwCYFuNDwy0T/LgsCzq/Aa/bQf2AHA42FbjI9HjZGRutjb7ExEREWnFNO1fpInlr9oUPMfd5zdRefZ6k9q2DR5+GJ57Dny+0Lqrr4Y//AE6dgxLaOFUn8gnepyUVnhpE++iQ5tYyiq8eOsCO//Hux0cm5Ws75qIiIiIKPkXaUr5qzYxcW4BVd462sa7A+uz/bbOXj8QdXXw4ouBUf3Nm0PrTj0Vnn028M9W7vcXHMvMj9cGbi7ZhrbxLtKTkxjSM5PTu7WjZ1ayRvxFRERERMm/SFOxbcOMvGKqvHVkJsdi/bITW6zDSWayQ2ev78uCBTBuHBQVhZZ37AiPPQZXXrlzZ7tWrm/XNAZ0z6BwQwVbqmtJjXcr4RcRERGRBpT8izSRwg0VFJdV0TbeHUz861mWFXL2eu+OKWGKMsJ89x2MHw//+U9oeXw83HMP3HknxMWFJ7YI5nBY+g6JiIiIyD4p+RdpIluqa/H5DW7nnjeg8zh19nrQli3w4IPwwguB6f71LAuuuSYw2t+hQ/jiExERERFp4ZT8izSR1Hg3LqcVOIrN4WxQ7/XbOnvd54MZMwKJ/7ZtoXWnnQbPPAMnnRSW0EREREREoknrOBNLJAx6ZiWTnZ7I1mofxoQe7WeMad1nrxsD8+ZBr14wdmxo4t+5M/zjH/DRR0r8RUREREQaiZJ/adVs21Cwvpy87zdSsL4c2zb7f9IBcjgsRuZmB49iq/H5sW1Djc9PaYW39Z69XlgIQ4bA0KHw/fc7yxMTYerUwLr/X/9aG/qJiIiIiDQiTfuXVit/1SZm5BUHjkjzG1xOi+z0xEY9E31At3ZMuaR38H3KbYPLYZHTIan1nb2+aVPg2L4XXwS/f2e5ZcENN8CUKZCREb74RERERESimJJ/aZXyV21i4twCqrx1tI1343Y6qPXbFJVUMnFuAVMu6d2oNwD6dU1rvUex1dbCc8/BQw9BRUVo3RlnwLPPwvHHhyc2EREREZFWQsm/tDq2bZiRV0yVt47M5NjgMXyxDieZyQ5KK7zMyCumX9e0RkvQW+VRbMbAv/4VOLqvuDi0rksX+OMfYdgwTe8XEREREWkGWvMvrU7hhgqKy6poG+8OJv71LMuiTbyL4rIqCjdU7OUVZL+++QbOPhsuvjg08U9ODhzb9913cMklSvxFRERERJqJRv6l1dlSXYvPb3A793zvy+N0UG4btlTXNnNkUaCsDO67D/72N7DtneUOB9x0EzzyCLRvH774RERERERaKSX/0uqkxrtxOS1q/TaxDmeDeq/fxuWwSI13hyG6FsrrhenT4dFHoaoqtO6ss+DppwPH+omIiIiISFho2r+0Oj2zkslOT2RrtQ9jQo/2M8awrdpHdnoiPbOSwxRhC2IMvPEGHHMM3HNPaOLfrVtgzf977ynxFxEREREJMyX/0uo4HBYjc7NJ9DgprfBS4/Nj24Yan5/SCi+JHicjc7Nbz278h+rLL2HgQLjsMlizZmd5mzbw5JPw7bdwwQVa1y8iIiIiEgGU/EurNKBbO6Zc0pucDklUe+soq/JS7a0jp0NSox7zF5VKSuCGG+Dkk+Hjj3eWO51w662BDf5uvx1crvDFKCIiIiIiIbTmX1qtAd3a0a9rGoUbKthSXUtqvJueWcka8d+bmprA8XzTpsH27aF1gwcH1vzn5IQlNBERERER2Tcl/9KqORwWvTumhDuMyGYMvP463H03rFsXWtejRyDpP/fcsIQmIiIiIiIHRsm/iOzd55/DmDHw6aeh5W3bwkMPwciRENM0/xmxbaNZGSIiIiIijUTJv4g09NNPgZH+V14JLXe5Agn/Qw8FNvZrIvmrNjEjr5jisip8foPLaZGdnsjI3GztxyAiIiIicgi04Z+I7FRdDZMmQffuDRP/oUOhsBCefho7OYWC9eXkfb+RgvXl2LbZ48sdivxVm5g4t4CikgoSPDGkJ3lI8MRQVFLJxLkF5K/a1GjvJSIiIiLSWmjkX0TAtgPJ/oQJsGFDaF3PnvD003D22UDTjsrbtmFGXjFV3joyk2OxfjkmMNbhJDPZQWmFlxl5xfTrmqYlACIiIiIiB0Ej/yKt3eLF0LcvDB8emvi3awczZsDXX4ck/k05Kl+4oYLisiraxruDiX89y7JoE++iuKyKwg0Vh/U+IiIiIiKtjZJ/kdbqxx/hiitgwAD44oud5W433HEHFBfDLbeA0wk0HJWPdTlxOCxiXU4ykz1Uef3MyCs+rCUAW6pr8fkNbuee/9PkcTrw2YYt1bWH/B4iIiIiIq1RRCf/U6dO5ZRTTiEpKYn09HSGDRvGihUrQtoYY5g0aRJZWVnExcUxaNAgCgsLQ9p4vV5Gjx5Nu3btSEhI4KKLLmL9+vUhbbZu3crw4cNJSUkhJSWF4cOHs23btqb+iCLNr6oK7rsvcEzfP/4RWnfxxVBUBE88AcnJIVXNMSqfGu/G5bSo9dt7rPf6bVwOi9R49yG/h4iIiIhIaxTRyX9eXh633XYbn376KQsXLqSuro7Bgwezffv2YJvHHnuMJ598kueee47PP/+czMxMfvWrX1FZWRlsM27cOObOnctrr73Gxx9/TFVVFRdccAF+vz/Y5uqrr2bZsmXMnz+f+fPns2zZMoYPH96sn1ekSdk2zJoF3brBlCmwY8fOut69YdEieOst6Np1j09vjlH5nlnJZKcnsrXahzGhMwiMMWyr9pGdnkjPrOS9vIKIiIiIiOxJRG/4N3/+/JDHs2bNIj09naVLlzJw4ECMMUyfPp377ruPSy+9FIC///3vZGRk8MorrzBixAjKy8v561//yksvvcQ555wDwJw5c+jUqRPvvfceQ4YMoaioiPnz5/Ppp5/St29fAF588UX69+/PihUr6NGjR/N+cJHG9tFHMGYMLFsWWp6eHrgRcMMN4Nj3vcBdR+VjHc4G9Y0xKu9wWIzMzWbi3AJKK7y0iXfhcTrw+m22VftI9DgZmZutzf5ERERERA5SRCf/uysvLwcgNTUVgNWrV1NaWsrgwYODbTweD7m5ueTn5zNixAiWLl2Kz+cLaZOVlUWvXr3Iz89nyJAhLF68mJSUlGDiD9CvXz9SUlLIz8/fa/Lv9Xrxer3BxxUVgenOPp8Pn8/XeB+8kdXHFskxyuGp79u6lStx3ncfjrfeCqk3bjf22LHY994LiYng9wd+9uHo9nH0yIhnRWkViS4Pu878Nwaqd9TSIzORo9vHHdZ365TOKTx6UQ5//WQ1qzdup8ZrcDksemclcONpXTilc4q+u+j3uDVQH0c/9XH0Ux9HP/Vx9GsJfXygsbWY5N8Yw/jx4zn99NPp1asXAKWlpQBkZGSEtM3IyGDt2rXBNm63m7Zt2zZoU//80tJS0tPTG7xnenp6sM2eTJ06lYceeqhB+YIFC4iPjz+ITxceCxcuDHcI0kRiqqs59v/9P9xvv42jri6kbv3pp/PttddSk54OH354UK87LA1IA6jeS4tq5s//z6GEvI/3qredzd+VMe+7Rnn5qKHf4+inPo5+6uPopz6Ofurj6BfJfVxdvbe/zUO1mOR/1KhRfPPNN3z88ccN6nbffMwY06Bsd7u32VP7/b3Ovffey/jx44OPKyoq6NSpE4MHDyY5OXLXJPt8PhYuXMivfvUrXC5XuMORxuT3Y82ahfP3v8faFHrsnn3CCdhPPUXGaaeRsZenH4jPftgcHJX32YFR+S7tA6Pyfbum7f8FmohtG74rrWRrdS1t490ck5kU1csD9Hsc/dTH0U99HP3Ux9FPfRz9WkIf189A358WkfyPHj2at99+mw8//JCOHTsGyzMzM4HAyH2HDh2C5WVlZcHZAJmZmdTW1rJ169aQ0f+ysjIGDBgQbPPzzz83eN+NGzc2mFWwK4/Hg8fjaVDucrki9ouxq5YSpxygDz4IrOtfvjy0vEMHmDoVx/DhOPazrv9AnN4jkwHdMyjcUMGW6lpS4930zEoOa6Kdv2oTM/KKKS6rwuc3uJwW2emJjMzNZkC3dmGLqzno9zj6qY+jn/o4+qmPo5/6OPpFch8faFwRvdu/MYZRo0bx5ptv8v7779OlS5eQ+i5dupCZmRkyBaO2tpa8vLxgYt+nTx9cLldIm5KSEpYvXx5s079/f8rLy1myZEmwzWeffUZ5eXmwjUjEWrUKLroIzjorJPGvc7vx33svrFwJ11233w39DobDYdG7Ywq5R7end8eUsCf+E+cWUFRSQYInhvQkDwmeGIpKKpk4t4D8VZv2/yIiIiIiIlEuokf+b7vtNl555RX++c9/kpSUFFx/n5KSQlxcHJZlMW7cOKZMmUL37t3p3r07U6ZMIT4+nquvvjrY9sYbb+SOO+4gLS2N1NRU7rzzTnr37h3c/T8nJ4dzzz2Xm266iZkzZwJw8803c8EFF2inf4lc5eXw0EPw3HOw2yYf9mWX8d9zz+Wsa6/FGaF3KBuDbRtm5BVT5a0jMzk2uEwn1uEkM9lBaYWXGXnF9OuaFtVLAERERERE9ieik/8ZM2YAMGjQoJDyWbNmcf311wNw9913U1NTw6233srWrVvp27cvCxYsICkpKdj+qaeeIiYmhssvv5yamhrOPvtsZs+ejdO587iyl19+mTFjxgRPBbjooot47rnnmvYDihyKujr485/h97+HzZtD6045BZ59Fv9JJ7Fj3rzwxNeMCjdUUFxWRdt4d4P9OSzLok28i+KyKgo3VNC7Y0qYohQRERERCb+ITv6NMfttY1kWkyZNYtKkSXttExsby7PPPsuzzz671zapqanMmTPnUMIUaT4LFsC4cVBUFFqelQWPPQZXXw2W1WAmQLTaUl2Lz29wO/e8pMHjdFBuG7ZU1zZzZCIiIiIikSWik38R+cWKFXD77fCf3Y7Ri4+Hu+6CCRMgLi48sYVRarwbl9Oi1m8T63A2qPf6bVwOi9R4dxiiExERERGJHBG94Z9Iq7d1a2AH/169Gib+11wT2Mxv0qRWmfgD9MxKJjs9ka3VvgYzhYwxbKv2kZ2eSM+syD16U0RERESkOSj5F4lEPh888wxkZ8OzzwbW+dfr1w8+/xzmzAlM92/FHA6LkbnZJHqclFZ4qfH5sW1Djc9PaYWXRI+TkbnZ2uxPRERERFo9Jf8ikWbePOjZE8aODYz81+vUCV57DfLz4eSTwxdfhBnQrR1TLulNTockqr11lFV5qfbWkdMhiSmX9GZAt3bhDlFEREREJOy05l8kUnz7bSDhf++90PLExMCa/jvvhNjY8MQW4QZ0a0e/rmkUbqhgS3UtqfFuemYla8RfREREROQXSv5Fwm3TJrj/fvjLX8Dv31luWXDddTBtGmRkhC++FsLhsHScn4iIiIjIXij5FwmX2trAuv5HH4Xy8tC6008P1J14YnhiExERERGRqKLkX6S5GQP/+lfg6L4ffgitO+ooeOIJuPTSwMi/iIiIiIhII1DyL9KcCgoCR/ctWhRanpwM994buCHg8YQlNBERERERiV5K/kWaQ1kZTJwIs2aBbe8sdzjghhtg6lRo3z588YmIiIiISFRT8i/SlLxeeOopmDIFKitD6wYNCqzr7907LKGJiIiIiEjroeRfpCkYA2++GTieb82a0LrsbHjySbjwQq3rFxERERGRZuEIdwDS/GzbAPDJqk0UrC8PPpZG8tVXcMYZcNlloYl/Sgo8/jgUFcFFFynxFxERERGRZqOR/1Ymf9UmXvxwJcPS4L65yzGWg+z0REbmZjOgW7twh9eylZbChAnw0kuBkf96Tif87ncweTKkpYUvPhERERERabU08t+K5K/axMS5BawoDaw9b5/oIcETQ1FJJRPnFpC/alOYI2yhduyARx+Fbt3gf/83NPE/5xz45ht44QUl/iIiIiIiEjZK/lsJ2zbMyCumyltHRlIsENhoPtblJDPZQ5XXz4y8Yi0BOBjGwGuvwdFHwwMPwPbtO+u6d4d//xsWLoRjjw1fjCIiIiIiIij5bzUKN1RQXFZF23h3g6XmlmXRJt5FcVkVhRsqwhNgS/P559C/P1x1Faxbt7O8bdvA7v7ffgtDh4YvPhERERERkV1ozX8rsaW6Fp/f4HY6gIaj+x6ng3LbsKW6tvmD24VtGwo3VLClupbUeDc9s5JxOCJoY7yffoK774ZXXgktj4mBESPgkUcCNwBEREREREQiiJL/ViI13o3LaVHrt/E4GybTXr+Ny2GRGu8OQ3QB+as2MSOvmOKyKnx+g8tpRc5mhNXV8NhjgZ+amtC6IUPg6aehR4/wxCYiIiIiIrIfmvbfSvTMSiY7PZGt1b6Q/egAjDFsq/aRnZ5Iz6zksMRXvxlhUUkFCZ4Y0pMiZDNCY2DOnMAa/oceCk38jzkG5s8P/CjxFxERERGRCKbkv5VwOCxG5maT6HHyc6UXANuGGp+f0goviR4nI3OzwzLFftfNCDOTY4l1OXE4rPBvRrh4MZx6KgwfDhs27CxPS4NnnoGCgsCov4iIiIiISIRT8t+KDOjWjimX9KZHZiIAG7d7qfbWkdMhiSmX9A7b1PrQzQhDbz6EZTPCdevgiitgwAD44oud5S4XjB0LxcUwenRgnb+IiIiIiEgLoOyllRnQrR19OiUzf/5/mDysF2lJ8WHfVC90M8KGmm0zwqoqmDIlsFv/jh2hdUOHBsq7d2/aGERERERERJqAkv9WqD7RP61bO1wuV5ijCd2MMNbhbFDf5JsR2jbMng333QelpaF1vXrB9Olw9tlN894iIiIiIiLNQNP+JexCNyMMXdff5JsRfvQR9OkDN94Ymvi3bw8zZsCyZUr8RURERESkxVPyL2G362aEpRVeanx+bNs07WaEq1fDpZfCwIGBBL+e2w133BFY13/LLeBsOBNBRERERESkpVHyLxGhfjPCnA5JVHvrKKtqos0IKyvh7rshJwfmzg2tu/hi+O47eOIJSEpqnPcTERERERGJAFrzLxFjQLd29OuaRuGGCrZU15Ia7268zQj9fvjrX+H++2HjxtC6448PrOsfNOjw30dERERERCQCKfmXiOJwWPTumNK4L/r++4Ej+pYvDy3PyIDJk+GGG8ChSTAiIiIiIhK9lPxL9CouhnHj4N//Di33eALlDzwACQnhiExERERERKRZKfmX6FNeDpMmwfPPQ21taN1llwXW9HfuHJbQREREREREwkHJv0SPujqYORMefBA2bw6tO+kkePppOP308MQmIiIiIiISRkr+JTq8+y7cfjsUFYWWZ2UF1vVfdx1YjXhU4F7YtmmaDQtFREREREQOg5J/adlWrAis358/P7Q8Lg7Gj4eJEyE+vllCyV+1iRl5xRSXVeHzG1xOi+z0REbmZjfeUYUiIiIiIiKHQFucS8u0dSuMGgW9ejVM/K+8Er7/Hh59tFkT/4lzCygqqSDBE0N6kocETwxFJZVMnFtA/qpNzRKHiIiIiIjInij5l5bF54Pp06FrV/jTnwLr/Oudcgrk58Orr0LHjs0Wkm0bZuQVU+WtIzM5lliXE4fDItblJDPZQ5XXz4y8YmzbNFtMIiIiIiIiu1LyLy3HO+8ERvpvvx22bdtZ3rEjzJkDn30G/fs3e1iFGyooLquibbwba7d9BSzLok28i+KyKgo3VDR7bCIiIiIiIqA1/9ISFBbC2LHw3/+GlickwJ13wj33QGxseGIDtlTX4vMb3M4930vzOB2U24Yt1bV7rBcREREREWlqSv4lcm3eDPfdB3/5C/j9O8stC665Bh57DDp0CF98v0iNd+NyWtT6bWIdzgb1Xr+Ny2GRGu8OQ3QiIiIiIiKa9i+RqLYWnngCsrNh5szQxL9//8D0/pdeiojEH6BnVjLZ6YlsrfZhTOi6fmMM26p9ZKcn0jMrOUwRioiIiIhIa6fkXyKHMfDWW5CTA3fdBeXlO+uOPBJefx0++SSwsV8EcTgsRuZmk+hxUlrhpcbnx7YNNT4/pRVeEj1ORuZm43BY+38xERERERGRJqDkXyLDN9/AmWfCJZfADz/sLE9MhIcfDhzdd/nlgSn/EWhAt3ZMuaQ3OR2SqPbWUVblpdpbR06HJKZc0psB3dqFO0QREREREWnFtOZfwmvjRrj3Xpg1C2x7Z7nDAddeC9OmQUZG+OI7CAO6taNf1zQKN1SwpbqW1Hg3PbOSNeIvIiIiIiJhp+RfwsPrhSefhKlTobIytO6MM+Dpp+HEE8MT22FwOCx6d0wJdxgiIiIiIiIhlPxL8zIG3ngjsKZ/zZrQui5dAhv9XXJJxE7vFxERERERaYmU/Evz+fJLGDMmsGnfrpKTA1P/x48Ht47DExERERERaWxK/qXplZbC3XfDnDmBkf96Tidcf31g6n/79mELT0REREREJNop+Zems2MHPP44/OEPsH17aN2ZZ8L06XDccWEJTUREREREpDVR8i+Nzxh47TWYMAHWrQut69YN/vhHuOii8MQmIiIiIiLSCin5l8b1+ecwejR89lloeZs2cN99MHYsuFxhCU1ERERERKS1UvIvjWPDBrjzTnj11dDymBj43e9g8mRITQ1PbCIiIiIiIq2ckn85PNXVMG1a4Ii+mprQusGD4cknoWfP8MQmIiIiIiIigJJ/OVTGBHbvv+eewKj/rnr0CKzrHzo0PLGJiIiIiIhICCX/cvDy8wNr97/4IrQ8NRUefBBuvTUw3V9EREREREQigjI0OXA//hhY1/9//xda7nLBiBHwyCOBjf1ERCQq2LahcEMFW6prSY130zMrGYfDCndYIiIicgiU/Mv+bd8Ojz4K06fDjh2hdeefH5jif8wxYQlNRESaRv6qTczIK6a4rAqf3+ByWmSnJzIyN5sB3dqFOzwRERE5SI5wByDNK/+HdfSa9C4AvSa9y1H3vMNziz7ZY1u7zs/6J56j9qgugU39dk38jz0W5s+Hd95pEYm/bRsK1peT9/1GCtaXY9sm3CFFrL1dK11DkdYjf9UmJs4toKikggRPDOlJHhI8MRSVVDJxbgH5qzaFO0QRERE5SBr5383zzz/P448/TklJCT179mT69OmcccYZ4Q6rURx1zzsAeJyh5U/M38YT899hzbSdG/QVvPovkifcQed1K0Pa+tqm4XrkIbjlFnDu9kL7sL+po005tTQaRq92vz45mUkUlVY2+vXa27Ua2L0dH67c1KKvYVPT9GiJFrZtmJFXTJW3jszkWCwr8D2OdTjJTHZQWuFlRl4x/bqm6TsuIiLSgij538Xrr7/OuHHjeP755znttNOYOXMm5513Ht9++y1HHnlkuMM7LPWJ//7arBlxLJtvvo3e7/0npK7WGcPLJw3lpSHX8+iQ0xlwEIn//pLvpkzO60evqrx1tI1343Y6qPXbwdGrKZf0jvjkdffrYxuD3xicFjgsR6Ndr71dq2/Wb2Nx8Wbi3U4ykmNb5DVsatFwg0mkXuGGCorLqmgb7w4m/vUsy6JNvIvisioKN1TQu2NKmKIUERGRg6Vp/7t48sknufHGG/nd735HTk4O06dPp1OnTsyYMSPcoR2W/B/W7bdNgreaie//BX+PHqTtlvj/t3tfzr95Bo+efRNr6lxM/U/RAU/53t/U0Rc/LG6yqaW7j17Fupw4HBaxLieZyR6qvH5m5BVH9PT13a9fvMdJeY2P8mofFTvqiHc7G+V67e1aeVwO6vwGvx348cQ4Wtw1bGqaHi3RZkt1LT6/we3c858IHqcDn23YUl3bzJGJiIjI4VDy/4va2lqWLl3K4MGDQ8oHDx5Mfn5+mKJqHFf/+Zu91jlsP9d8NY8PZ/6Omz9/C6fPF6xbkX4U118zhVFXTOKntI64YhxYwPc/V1HwU/l+33d/yXfljjr+tKjpkvODGb2KRLtfP4/LweaqwB/b7hgL28Dm7V48MY7Dvl57u1Y7am1q/TYxTotav80Onx2sawnXsKlFww0mkd2lxrtx/fI7vydev43LYZEa727myERERORwaNr/LzZt2oTf7ycjIyOkPCMjg9LS0j0+x+v14vV6g48rKgIJkM/nw7dLEh1uHmdo4uFxBB6f8eMy7p7/F47etDakflN8Cn8aNJy3+pyLsRx42Pl8VwzUGT/L1mzm2MyEfb7vtxsqWLepkvQEF26HgV1eBwtSYh2UlteQlhK3x/r2CTGs21RJwbotHJuVfNCfe3NlNZaxSYixcFgN/4h1xljUeG02V1bj88Uf9Os3td2vX02tDXYd8TEWDsvCdhhs24+/zk+c2xFyvbq3jwM44O/h3q6VFz9uR2CJgd+AAz+uXW4ORPo1bGr7+44f7nd4X+r7NpL+WyONK1x9fHT7OHpkxLOitIpEl4dd750aA9U7aumRmcjR7eP0/TtM+j2Ofurj6Kc+jn4toY8PNDbLGKMhKWDDhg0cccQR5Ofn079//2D55MmTeemll/juu+8aPGfSpEk89NBDDcpfeeUV4uMjNxGKLymh59//Ttann4aU+91uVl18MSsvvRR/XFyYohMREREREZEDVV1dzdVXX015eTnJyXsfcNLI/y/atWuH0+lsMMpfVlbWYDZAvXvvvZfx48cHH1dUVNCpUycGDx68z4ve3OqP9vP4vIz56BWu/fxt3P66kDYLju7PtLN/S8bRmSwvdOA3Ni6HI2QKuDEGn23jtBz8742n0uuIfW/09O2GCsa+9hXx7hhiXQ1XmGyr8VFaXkOHlDhS4lwN6mt8NjW1dTx95YmHNGpq24ZbXl7KitIqMpIajl79XOmlR2YiL1zTJyJ3rN79+tXU2qzbuh2H9cvIvwls/tepbQJxbkfI9erePo6FCxfyq1/9Cper4bXd3d6ulQHWbtpOtc9PvMtJ57SEnXUt4Bo2tf19xw/3O7wvPp/voPpYWp5w9/FnP2zmr5+sZvXG7fhsg8th0aV9Ajee1oW+XdOaPZ5oFO4+lqanPo5+6uPo1xL6uH4G+v4o+f+F2+2mT58+LFy4kEsuuSRYvnDhQi6++OI9Psfj8eDxeBqUu1yuiPpi5FgWy+qgDhcDV34RkvgvT+/Kw2ffxJIjewMw/9Zz+Z+Z+RRuqMBrG2IcFhaBJLDONhhj0TMrieOP3P8RT707pdKpXRJFJZVkJnsa3Ego32Hjdrsp99rEeawG9Ru315HTIYnenVIPObG8aWB3Js4tYF15LW3iXXicDrx+m23VPhI9Mdw0sDseT2SuW939+jldTnDEUO3z43QY6myIczlxxjiptQm5Xv5f+vhgvot7u1Z+y0GdMdThpNJnWtQ1bGr7+443xnd4fyLtvzfS+MLVx6f3yGRA9wwdYdkM9Hsc/dTH0U99HP0iuY8PNC5t+LeL8ePH85e//IW//e1vFBUVcfvtt/Pjjz9yyy23hDu0w/LWo0MB8DucTD7rRgBq0tKYeP4YLrx+ejDxv+/8Y3C7ndx7Xg7tkzw4LAu/baj7Zad3h2XRPsnDveflHNAffw6HxcjcbBI9TkorvNT4/Ni2ocbnp7TCS1JsDLcNyibRE7PH+kSPk5G52Yf1h+aAbu2YcklvcjokUe2to6zKS7U3kJBF+hF1u1+/HT6btMRAkl1bZ3BYkJbgYUed3SjXa2/X6riObZhwbg+O75TS4q5hU9vfd7wxvsMi4eRwWPTumELu0e3p3TFF32UREZEWTCP/u7jiiivYvHkzDz/8MCUlJfTq1Yt58+bRuXPncId22NZMG8pR97xDXtc+3H3h7Qz8TT/e+Doe4w/8IXff+cdw08BsIJAEPnX5CTy/aBXflVYGzy0/JjOJWwd1O6hkrz6hrD8DvfyXqaM5HZKCZ6D3zErZZ/3hGtCtHf26prXI0avdr5/PNqTEufCbwCZ81T4/Lr/daNdrX9fqxtO7tshr2NQO5DsuIiIiIhJuSv53c+utt3LrrbeGO4wmsWbaUIbd/w7/7H0Wp3n8ALQFPn/0PGJiQieBNGbCvL/Xao7kvH70qiXa0/XJyUyiqLSySa7X3q5VS76GTa0l32ASERERkdZByX8r89ajQ/H5fMybN4/lk4bsc31IYyZ7+3stJZb7tqfro+sVWfQdFhEREZFIpjX/IiIiIiIiIlFOyb+IiIiIiIhIlFPyLyIiIiIiIhLllPyLiIiIiIiIRDkl/yIiIiIiIiJRTsm/iIiIiIiISJRT8i8iIiIiIiIS5ZT8i4iIiIiIiEQ5Jf8iIiIiIiIiUU7Jv4iIiIiIiEiUU/IvIiIiIiIiEuWU/IuIiIiIiIhEOSX/IiIiIiIiIlFOyb+IiIiIiIhIlFPyLyIiIiIiIhLllPyLiIiIiIiIRDkl/yIiIiIiIiJRTsm/iIiIiIiISJRT8i8iIiIiIiIS5ZT8i4iIiIiIiEQ5Jf8iIiIiIiIiUS4m3AFEE2MMABUVFWGOZN98Ph/V1dVUVFTgcrnCHY40AfVx9FMfRz/1cfRTH0c/9XH0Ux9Hv5bQx/X5Z30+ujdK/htRZWUlAJ06dQpzJCIiIiIiItKaVFZWkpKSstd6y+zv9oAcMNu22bBhA0lJSViWFe5w9qqiooJOnTqxbt06kpOTwx2ONAH1cfRTH0c/9XH0Ux9HP/Vx9FMfR7+W0MfGGCorK8nKysLh2PvKfo38NyKHw0HHjh3DHcYBS05OjtgvsDQO9XH0Ux9HP/Vx9FMfRz/1cfRTH0e/SO/jfY3419OGfyIiIiIiIiJRTsm/iIiIiIiISJRT8t8KeTweHnzwQTweT7hDkSaiPo5+6uPopz6Ofurj6Kc+jn7q4+gXTX2sDf9EREREREREopxG/kVERERERESinJJ/ERERERERkSin5F9EREREREQkyin5FxEREREREYlySv5bmeeff54uXboQGxtLnz59+Oijj8IdkuzB1KlTOeWUU0hKSiI9PZ1hw4axYsWKkDbGGCZNmkRWVhZxcXEMGjSIwsLCkDZer5fRo0fTrl07EhISuOiii1i/fn1Im61btzJ8+HBSUlJISUlh+PDhbNu2rak/ouxm6tSpWJbFuHHjgmXq45bvp59+4je/+Q1paWnEx8dzwgknsHTp0mC9+rhlq6ur4/7776dLly7ExcXRtWtXHn74YWzbDrZRH7csH374IRdeeCFZWVlYlsVbb70VUt+c/fnjjz9y4YUXkpCQQLt27RgzZgy1tbVN8bFblX31sc/nY8KECfTu3ZuEhASysrK49tpr2bBhQ8hrqI8j2/5+j3c1YsQILMti+vTpIeVR28dGWo3XXnvNuFwu8+KLL5pvv/3WjB071iQkJJi1a9eGOzTZzZAhQ8ysWbPM8uXLzbJly8zQoUPNkUceaaqqqoJtpk2bZpKSkswbb7xhCgoKzBVXXGE6dOhgKioqgm1uueUWc8QRR5iFCxeaL7/80px55pnm+OOPN3V1dcE25557runVq5fJz883+fn5plevXuaCCy5o1s/b2i1ZssQcddRR5rjjjjNjx44NlquPW7YtW7aYzp07m+uvv9589tlnZvXq1ea9994zq1atCrZRH7dsjz76qElLSzP//ve/zerVq83//d//mcTERDN9+vRgG/VxyzJv3jxz3333mTfeeMMAZu7cuSH1zdWfdXV1plevXubMM880X375pVm4cKHJysoyo0aNavJrEO321cfbtm0z55xzjnn99dfNd999ZxYvXmz69u1r+vTpE/Ia6uPItr/f43pz5841xx9/vMnKyjJPPfVUSF209rGS/1bk1FNPNbfccktI2THHHGPuueeeMEUkB6qsrMwAJi8vzxhjjG3bJjMz00ybNi3YZseOHSYlJcW88MILxpjA/8BcLpd57bXXgm1++ukn43A4zPz5840xxnz77bcGMJ9++mmwzeLFiw1gvvvuu+b4aK1eZWWl6d69u1m4cKHJzc0NJv/q45ZvwoQJ5vTTT99rvfq45Rs6dKj57W9/G1J26aWXmt/85jfGGPVxS7d70tCc/Tlv3jzjcDjMTz/9FGzz6quvGo/HY8rLy5vk87ZG+0oM6y1ZssQAwcEy9XHLsrc+Xr9+vTniiCPM8uXLTefOnUOS/2juY037byVqa2tZunQpgwcPDikfPHgw+fn5YYpKDlR5eTkAqampAKxevZrS0tKQ/vR4POTm5gb7c+nSpfh8vpA2WVlZ9OrVK9hm8eLFpKSk0Ldv32Cbfv36kZKSou9FM7ntttsYOnQo55xzTki5+rjle/vttzn55JP59a9/TXp6OieeeCIvvvhisF593PKdfvrp/Pe//+X7778H4Ouvv+bjjz/m/PPPB9TH0aY5+3Px4sX06tWLrKysYJshQ4bg9XpDlg5J0ysvL8eyLNq0aQOoj6OBbdsMHz6cu+66i549ezaoj+Y+jgnLu0qz27RpE36/n4yMjJDyjIwMSktLwxSVHAhjDOPHj+f000+nV69eAME+21N/rl27NtjG7XbTtm3bBm3qn19aWkp6enqD90xPT9f3ohm89tprfPnll3z++ecN6tTHLd8PP/zAjBkzGD9+PBMnTmTJkiWMGTMGj8fDtddeqz6OAhMmTKC8vJxjjjkGp9OJ3+9n8uTJXHXVVYB+j6NNc/ZnaWlpg/dp27Ytbrdbfd6MduzYwT333MPVV19NcnIyoD6OBn/4wx+IiYlhzJgxe6yP5j5W8t/KWJYV8tgY06BMIsuoUaP45ptv+PjjjxvUHUp/7t5mT+31vWh669atY+zYsSxYsIDY2Ni9tlMft1y2bXPyySczZcoUAE488UQKCwuZMWMG1157bbCd+rjlev3115kzZw6vvPIKPXv2ZNmyZYwbN46srCyuu+66YDv1cXRprv5Un4eXz+fjyiuvxLZtnn/++f22Vx+3DEuXLuXpp5/myy+/POjrHA19rGn/rUS7du1wOp0N7jKVlZU1uCMlkWP06NG8/fbbfPDBB3Ts2DFYnpmZCbDP/szMzKS2tpatW7fus83PP//c4H03btyo70UTW7p0KWVlZfTp04eYmBhiYmLIy8vjmWeeISYmJnj91cctV4cOHTj22GNDynJycvjxxx8B/R5Hg7vuuot77rmHK6+8kt69ezN8+HBuv/12pk6dCqiPo01z9mdmZmaD99m6dSs+n0993gx8Ph+XX345q1evZuHChcFRf1Aft3QfffQRZWVlHHnkkcG/v9auXcsdd9zBUUcdBUR3Hyv5byXcbjd9+vRh4cKFIeULFy5kwIABYYpK9sYYw6hRo3jzzTd5//336dKlS0h9ly5dyMzMDOnP2tpa8vLygv3Zp08fXC5XSJuSkhKWL18ebNO/f3/Ky8tZsmRJsM1nn31GeXm5vhdN7Oyzz6agoIBly5YFf04++WSuueYali1bRteuXdXHLdxpp53W4IjO77//ns6dOwP6PY4G1dXVOByhf0o5nc7gUX/q4+jSnP3Zv39/li9fTklJSbDNggUL8Hg89OnTp0k/Z2tXn/ivXLmS9957j7S0tJB69XHLNnz4cL755puQv7+ysrK46667ePfdd4Eo7+Nm21pQwq7+qL+//vWv5ttvvzXjxo0zCQkJZs2aNeEOTXYzcuRIk5KSYhYtWmRKSkqCP9XV1cE206ZNMykpKebNN980BQUF5qqrrtrjcUMdO3Y07733nvnyyy/NWWedtcdjSo477jizePFis3jxYtO7d28dHxUmu+72b4z6uKVbsmSJiYmJMZMnTzYrV640L7/8somPjzdz5swJtlEft2zXXXedOeKII4JH/b355pumXbt25u677w62UR+3LJWVlearr74yX331lQHMk08+ab766qvgTu/N1Z/1R4SdffbZ5ssvvzTvvfee6dixo46BawT76mOfz2cuuugi07FjR7Ns2bKQv8G8Xm/wNdTHkW1/v8e72323f2Oit4+V/Lcyf/rTn0znzp2N2+02J510UvDoOIkswB5/Zs2aFWxj27Z58MEHTWZmpvF4PGbgwIGmoKAg5HVqamrMqFGjTGpqqomLizMXXHCB+fHHH0PabN682VxzzTUmKSnJJCUlmWuuucZs3bq1GT6l7G735F993PL961//Mr169TIej8ccc8wx5s9//nNIvfq4ZauoqDBjx441Rx55pImNjTVdu3Y19913X0iSoD5uWT744IM9/v/3uuuuM8Y0b3+uXbvWDB061MTFxZnU1FQzatQos2PHjqb8+K3Cvvp49erVe/0b7IMPPgi+hvo4su3v93h3e0r+o7WPLWOMaY4ZBiIiIiIiIiISHlrzLyIiIiIiIhLllPyLiIiIiIiIRDkl/yIiIiIiIiJRTsm/iIiIiIiISJRT8i8iIiIiIiIS5ZT8i4iIiIiIiEQ5Jf8iIiIiIiIiUU7Jv4iISCt31FFHMX369OBjy7J46623mj2OSZMmccIJJ+y1ftGiRViWxbZt25o8lrfeeotu3brhdDoZN24cs2fPpk2bNk3+viIiIk1Fyb+IiIiEKCkp4bzzzjugtvtL2FuqESNGcNlll7Fu3ToeeeSRcIcjIiJy2GLCHYCIiIgcvtraWtxud6O8VmZmZqO8TktVVVVFWVkZQ4YMISsrK9zhiIiINAqN/IuIiESYQYMGMWrUKEaNGkWbNm1IS0vj/vvvxxgTbHPUUUfx6KOPcv3115OSksJNN90EQH5+PgMHDiQuLo5OnToxZswYtm/fHnxeWVkZF154IXFxcXTp0oWXX365wfvvPu1//fr1XHnllaSmppKQkMDJJ5/MZ599xuzZs3nooYf4+uuvsSwLy7KYPXs2AOXl5dx8882kp6eTnJzMWWedxddffx3yPtOmTSMjI4OkpCRuvPFGduzYcVDXqX4q/rvvvktOTg6JiYmce+65lJSUBNvU1dUxZsyY4HWcMGEC1113HcOGDdvjay5atIikpCQAzjrrLCzLYtGiRXtsO2PGDLKzs3G73fTo0YOXXnopWHfHHXdw4YUXBh9Pnz4dy7J45513gmU9evRg5syZB/WZRUREDpWSfxERkQj097//nZiYGD777DOeeeYZnnrqKf7yl7+EtHn88cfp1asXS5cu5YEHHqCgoIAhQ4Zw6aWX8s033/D666/z8ccfM2rUqOBzrr/+etasWcP777/P//t//4/nn3+esrKyvcZRVVVFbm4uGzZs4O233+brr7/m7rvvxrZtrrjiCu644w569uxJSUkJJSUlXHHFFRhjGDp0KKWlpcybN4+lS5dy0kkncfbZZ7NlyxYA/vGPf/Dggw8yefJkvvjiCzp06MDzzz9/0NepurqaJ554gpdeeokPP/yQH3/8kTvvvDNY/4c//IGXX36ZWbNm8cknn1BRUbHP/QwGDBjAihUrAHjjjTcoKSlhwIABDdrNnTuXsWPHcscdd7B8+XJGjBjBDTfcwAcffAAEbuB89NFH2LYNQF5eHu3atSMvLw+A0tJSvv/+e3Jzcw/6M4uIiBwSIyIiIhElNzfX5OTkGNu2g2UTJkwwOTk5wcedO3c2w4YNC3ne8OHDzc033xxS9tFHHxmHw2FqamrMihUrDGA+/fTTYH1RUZEBzFNPPRUsA8zcuXONMcbMnDnTJCUlmc2bN+8x1gcffNAcf/zxIWX//e9/TXJystmxY0dIeXZ2tpk5c6Yxxpj+/fubW265JaS+b9++DV5rVx988IEBzNatW40xxsyaNcsAZtWqVcE2f/rTn0xGRkbwcUZGhnn88ceDj+vq6syRRx5pLr744r2+z9atWw1gPvjgg2DZrFmzTEpKSvDxgAEDzE033RTyvF//+tfm/PPPN8YYs23bNuNwOMwXX3xhbNs2aWlpZurUqeaUU04xxhjzyiuvhMQpIiLS1DTyLyIiEoH69euHZVnBx/3792flypX4/f5g2cknnxzynKVLlzJ79mwSExODP0OGDMG2bVavXk1RURExMTEhzzvmmGP2uYv9smXLOPHEE0lNTT3g2JcuXUpVVRVpaWkhsaxevZri4mIAioqK6N+/f8jzdn98IOLj48nOzg4+7tChQ3AmQ3l5OT///DOnnnpqsN7pdNKnT5+Dfp/dFRUVcdppp4WUnXbaaRQVFQGQkpLCCSecwKJFiygoKMDhcDBixAi+/vprKisrWbRokUb9RUSkWWnDPxERkRYqISEh5LFt24wYMYIxY8Y0aHvkkUcGp7PvelNhf+Li4g46Ltu26dChwx7Xyjf2cXkulyvksWVZIXsj1Jftavf6Q7Wn1921bNCgQSxatAi3201ubi5t27alZ8+efPLJJyxatIhx48Y1ShwiIiIHQiP/IiIiEejTTz9t8Lh79+44nc69Puekk06isLCQbt26Nfhxu93k5ORQV1fHF198EXzOihUr2LZt215f87jjjmPZsmXBtfq7c7vdIbMR6uMoLS0lJiamQRzt2rUDICcnZ4+fsTGlpKSQkZHBkiVLgmV+v5+vvvrqsF87JyeHjz/+OKQsPz+fnJyc4OP6df/vv/8+gwYNAiA3N5fXXntN6/1FRKTZKfkXERGJQOvWrWP8+PGsWLGCV199lWeffZaxY8fu8zkTJkxg8eLF3HbbbSxbtoyVK1fy9ttvM3r0aCCwu/y5557LTTfdxGeffcbSpUv53e9+t8/R/auuuorMzEyGDRvGJ598wg8//MAbb7zB4sWLgcCpA6tXr2bZsmVs2rQJr9fLOeecQ//+/Rk2bBjvvvsua9asIT8/n/vvvz9442Hs2LH87W9/429/+xvff/89Dz74IIWFhY109XYaPXo0U6dO5Z///CcrVqxg7NixbN269aBmP+zJXXfdxezZs3nhhRdYuXIlTz75JG+++WbIZoMDBw6ksrKSf/3rX8Hkf9CgQcyZM4f27dtz7LHHHlYMIiIiB0PJv4iISAS69tprqamp4dRTT+W2225j9OjR3Hzzzft8znHHHUdeXh4rV67kjDPO4MQTT+SBBx6gQ4cOwTazZs2iU6dO5ObmcumllwaP49sbt9vNggULSE9P5/zzz6d3795MmzYtOAPhf/7nfzj33HM588wzad++Pa+++iqWZTFv3jwGDhzIb3/7W44++miuvPJK1qxZQ0ZGBgBXXHEFv//975kwYQJ9+vRh7dq1jBw5shGuXKgJEyZw1VVXce2119K/f//gPgixsbGH9brDhg3j6aef5vHHH6dnz57MnDmTWbNmBZN8CMw8qN8voT7RP+OMM7BtW6P+IiLS7CzTWAvfREREpFEMGjSIE044genTp4c7lKhj2zY5OTlcfvnlPPLII+EOR0REpNlowz8RERGJWmvXrmXBggXk5ubi9Xp57rnnWL16NVdffXW4QxMREWlWmvYvIiIiUcvhcDB79mxOOeUUTjvtNAoKCnjvvfdCNuYTERFpDTTtX0RERERERCTKaeRfREREREREJMop+RcRERERERGJckr+RURERERERKKckn8RERERERGRKKfkX0RERERERCTKKfkXERERERERiXJK/kVERERERESinJJ/ERERERERkSin5F9EREREREQkyv1/Y3R8tmhW/vQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "sns.regplot(x=yhat[:, 0], y=y_test.iloc[:, 0], line_kws={'color':'red'})\n",
    "plt.xlabel(\"predicted lng flow\")\n",
    "plt.ylabel(\"actual lng flow\")\n",
    "plt.grid()\n",
    "plt.savefig(\"lng pred\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f84ee14f-6cee-4d3f-9c57-9a4124226e6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "sns.regplot(x=yhat[:, 1], y=y_test.iloc[:, 1], line_kws={'color':'red'})\n",
    "plt.xlabel(\"predicted LNG Rundown Temperature\")\n",
    "plt.ylabel(\"actual LNG Rundown Temperature\")\n",
    "plt.grid()\n",
    "plt.savefig(\"temp pred\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7be0c467-3f1b-476f-b362-e84c4283af28",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Hyper parameter Tuning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b6999190-23a3-4eef-abfb-5afca5ebf588",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import RandomizedSearchCV\n",
    "from sklearn.model_selection import RepeatedStratifiedKFold\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4b6157e7-2262-4381-9ce4-f7a03a628793",
   "metadata": {},
   "outputs": [],
   "source": [
    "cv = KFold(n_splits=5, shuffle=True, random_state=42) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba2328ad-2139-45aa-8f47-284f06dd760c",
   "metadata": {},
   "source": [
    "Hyper parameters to search for:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "80d7c321-932b-421c-ae90-acae34c49917",
   "metadata": {},
   "outputs": [],
   "source": [
    "space = dict()\n",
    "space['n_neighbors'] = [i for i in range(2, 20)]\n",
    "space['weights'] = ['uniform', 'distance']\n",
    "#space['algorithm'] = ['auto', 'ball_tree', 'kd_tree', 'brute']\n",
    "space['p'] = [1, 2, 5]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "750ce620-3f5f-4489-a24a-1db8e2f090d8",
   "metadata": {},
   "source": [
    "search:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "97d60ede-8a2f-4ce6-bdb6-77f948d747e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define search\n",
    "search = GridSearchCV(KNeighborsRegressor(), space, scoring='neg_root_mean_squared_error', n_jobs=-1, cv=cv)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "08848a62-f9e3-44e6-8045-254003113317",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_t, y_t = np.array(X_train), np.array(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "47a27481-2e33-4325-9a99-d1d9723e16c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# execute search\n",
    "result = search.fit(X_t, y_t[:, 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "08963b47-486f-496d-b13f-03f4341f3912",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best Score: -447.71178828314316\n",
      "Best Hyperparameters: {'n_neighbors': 9, 'p': 1, 'weights': 'distance'}\n"
     ]
    }
   ],
   "source": [
    "# summarize result\n",
    "print('Best Score: %s' % result.best_score_)\n",
    "print('Best Hyperparameters: %s' % result.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "2c866a5a-65de-4cf6-8858-f1844232eed8",
   "metadata": {},
   "outputs": [],
   "source": [
    "pipe = Pipeline(\n",
    "            [('scalar', StandardScaler()),\n",
    "            ('regressor', RegressorChain(KNeighborsRegressor(n_neighbors= 9, weights = 'distance', p = 1), order=[0, 1]))]\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5c6f02ec-e7a0-444c-baa2-097e40e3a0b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {color: black;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;scalar&#x27;, StandardScaler()),\n",
       "                (&#x27;regressor&#x27;,\n",
       "                 RegressorChain(base_estimator=KNeighborsRegressor(n_neighbors=9,\n",
       "                                                                   p=1,\n",
       "                                                                   weights=&#x27;distance&#x27;),\n",
       "                                order=[0, 1]))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;scalar&#x27;, StandardScaler()),\n",
       "                (&#x27;regressor&#x27;,\n",
       "                 RegressorChain(base_estimator=KNeighborsRegressor(n_neighbors=9,\n",
       "                                                                   p=1,\n",
       "                                                                   weights=&#x27;distance&#x27;),\n",
       "                                order=[0, 1]))])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">StandardScaler</label><div class=\"sk-toggleable__content\"><pre>StandardScaler()</pre></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">regressor: RegressorChain</label><div class=\"sk-toggleable__content\"><pre>RegressorChain(base_estimator=KNeighborsRegressor(n_neighbors=9, p=1,\n",
       "                                                  weights=&#x27;distance&#x27;),\n",
       "               order=[0, 1])</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">base_estimator: KNeighborsRegressor</label><div class=\"sk-toggleable__content\"><pre>KNeighborsRegressor(n_neighbors=9, p=1, weights=&#x27;distance&#x27;)</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsRegressor</label><div class=\"sk-toggleable__content\"><pre>KNeighborsRegressor(n_neighbors=9, p=1, weights=&#x27;distance&#x27;)</pre></div></div></div></div></div></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('scalar', StandardScaler()),\n",
       "                ('regressor',\n",
       "                 RegressorChain(base_estimator=KNeighborsRegressor(n_neighbors=9,\n",
       "                                                                   p=1,\n",
       "                                                                   weights='distance'),\n",
       "                                order=[0, 1]))])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.fit(X_t, y_t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "34844e69-651c-45c9-a480-2dcec89793c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "Xtest = np.array(X_test)\n",
    "yhat = pipe.predict(Xtest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "977be2d3-d4ae-42ab-888f-89b3dc3cd154",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "149.00483795116412"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_squared_error(y_test, yhat, squared= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "2bb6c544-a67e-4cc0-8f8b-128d2676777f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>predicted lng flow</th>\n",
       "      <th>predicted LNG Rundown Temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13509.923222</td>\n",
       "      <td>-145.550721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12170.430456</td>\n",
       "      <td>-145.727184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13404.951410</td>\n",
       "      <td>-145.707795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12735.611069</td>\n",
       "      <td>-145.785677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11952.358026</td>\n",
       "      <td>-146.056697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   predicted lng flow  predicted LNG Rundown Temperature\n",
       "0        13509.923222                        -145.550721\n",
       "1        12170.430456                        -145.727184\n",
       "2        13404.951410                        -145.707795\n",
       "3        12735.611069                        -145.785677\n",
       "4        11952.358026                        -146.056697"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(yhat, columns=['predicted lng flow', 'predicted LNG Rundown Temperature']).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "855fa20c-7a3b-41b7-9930-76960edec80f",
   "metadata": {},
   "source": [
    "#### visualize the performance of the pipe after hyperpararmeter fix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "65413979-3376-4b6a-9fce-6954465bfbbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((8006, 2), (8006, 2))"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.shape, yhat.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "56bb70d6-e2e2-4789-be33-70d5dd1f169e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "sns.regplot(x=yhat[:, 0], y=y_test.iloc[:, 0], line_kws={'color':'red'})\n",
    "plt.xlabel(\"predicted lng flow\")\n",
    "plt.ylabel(\"actual lng flow\")\n",
    "plt.grid()\n",
    "plt.savefig(\"improv lng pred\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "064bcb40-117b-4031-9484-5e5f939673ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "sns.regplot(x=yhat[:, 1], y=y_test.iloc[:, 1], line_kws={'color':'red'})\n",
    "plt.xlabel(\"predicted MR return temperature\")\n",
    "plt.ylabel(\"actual MR return temperature\")\n",
    "plt.grid()\n",
    "plt.savefig(\"improv temp pred\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "175df0fd-089e-4b47-9c05-ed1d3d466b85",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Export Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "51826444-d948-439b-b225-88c7b56f9d66",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle as pkl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "ab7239aa-fedc-4285-ac85-204d5335b478",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done!\n"
     ]
    }
   ],
   "source": [
    "with open(\"model.pkl\", \"wb\") as obj:\n",
    "    pkl.dump(pipe, obj)\n",
    "    print(\"Done!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b9f2f3fa-ad60-4039-a748-f8ee9cc59d51",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.5"
  },
  "vscode": {
   "interpreter": {
    "hash": "72c4305ed16563862b7b8f497eeac66b171a2e02864ff61cfb80a89c78fe124b"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}