src/analysis/analyse_results.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "41e43c11-661c-406e-8c94-a4348d37fb9e",
   "metadata": {},
   "source": [
    "# FootballDB Results Analysis\n",
    "\n",
    "Code to reproduce the figures of **FootballDB: Exploring NL-to-SQL Systems in the Real-World**."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b5f81b4-9df0-4be7-ac50-1a5ef27da7c5",
   "metadata": {},
   "source": [
    "## Load results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7db3e679-88e0-4e97-af35-7721c8dbe44a",
   "metadata": {},
   "outputs": [],
   "source": [
    "RESULT_FOLDER = \"../../data/results\"\n",
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "dfs = []\n",
    "for subdir, dirs, files in os.walk(RESULT_FOLDER):\n",
    "    for file in files:\n",
    "        if \".csv\" in file:\n",
    "            df = pd.read_csv(os.path.join(subdir, file))\n",
    "            dfs.append(df)\n",
    "df_all = pd.concat(dfs)\n",
    "df_all['id_index'] = df_all['id']\n",
    "df_all = df_all.set_index('id_index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a1608adb-d586-48dd-a0bd-5fc0f1f4648a",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>db_id</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>hardness</th>\n",
       "      <th>split</th>\n",
       "      <th>label</th>\n",
       "      <th>prediction</th>\n",
       "      <th>system</th>\n",
       "      <th>number_of_joins</th>\n",
       "      <th>...</th>\n",
       "      <th>query_length</th>\n",
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       "      <th>full_column_match</th>\n",
       "      <th>full_value_match</th>\n",
       "      <th>partial_column_match</th>\n",
       "      <th>question_similarity_train_query_id</th>\n",
       "      <th>similarity_score_nl</th>\n",
       "      <th>sql_similarity_train_query_id</th>\n",
       "      <th>similarity_score_sql</th>\n",
       "      <th>no_tokens</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>exp_v1</td>\n",
       "      <td>2</td>\n",
       "      <td>Against which team did Switzerland loose in 2018</td>\n",
       "      <td>SELECT T1.teamname, T3.teamname, T2.home_team_...</td>\n",
       "      <td>extra</td>\n",
       "      <td>100</td>\n",
       "      <td>False</td>\n",
       "      <td>select t1.teamname, t2.year from national_team...</td>\n",
       "      <td>T5$_{Picard}$</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>625</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>600</td>\n",
       "      <td>0.761025</td>\n",
       "      <td>332</td>\n",
       "      <td>0.700800</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>exp_v1</td>\n",
       "      <td>6</td>\n",
       "      <td>All players that have the shirt number 13 and ...</td>\n",
       "      <td>select player.player_name\\r\\n from player join...</td>\n",
       "      <td>extra</td>\n",
       "      <td>100</td>\n",
       "      <td>False</td>\n",
       "      <td>select distinct t1.player_name from player as ...</td>\n",
       "      <td>T5$_{Picard}$</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>206</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>848</td>\n",
       "      <td>0.679872</td>\n",
       "      <td>310</td>\n",
       "      <td>0.466019</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>exp_v1</td>\n",
       "      <td>11</td>\n",
       "      <td>At how many woldcups did italy participate in?</td>\n",
       "      <td>SELECT count(*) FROM national_team AS T1 WHERE...</td>\n",
       "      <td>easy</td>\n",
       "      <td>100</td>\n",
       "      <td>True</td>\n",
       "      <td>select count(*) from national_team as t1 where...</td>\n",
       "      <td>T5$_{Picard}$</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>792</td>\n",
       "      <td>0.989651</td>\n",
       "      <td>792</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>exp_v1</td>\n",
       "      <td>22</td>\n",
       "      <td>For which club does Maradonna play</td>\n",
       "      <td>select T3.club_name\\n from player as T1\\n join...</td>\n",
       "      <td>extra</td>\n",
       "      <td>100</td>\n",
       "      <td>True</td>\n",
       "      <td>select distinct t1.club_team_name from player_...</td>\n",
       "      <td>T5$_{Picard}$</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>182</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>469</td>\n",
       "      <td>0.914928</td>\n",
       "      <td>41</td>\n",
       "      <td>0.931937</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>exp_v1</td>\n",
       "      <td>51</td>\n",
       "      <td>Give me all matches where stage is Quarter-fin...</td>\n",
       "      <td>SELECT m.year, nt.teamname, nt2.teamname, m.ho...</td>\n",
       "      <td>extra</td>\n",
       "      <td>100</td>\n",
       "      <td>False</td>\n",
       "      <td>select t1.teamname from national_team as t1 jo...</td>\n",
       "      <td>T5$_{Picard}$</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>276</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>50</td>\n",
       "      <td>0.749127</td>\n",
       "      <td>50</td>\n",
       "      <td>0.789855</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           db_id  id                                           question  \\\n",
       "id_index                                                                  \n",
       "2         exp_v1   2   Against which team did Switzerland loose in 2018   \n",
       "6         exp_v1   6  All players that have the shirt number 13 and ...   \n",
       "11        exp_v1  11     At how many woldcups did italy participate in?   \n",
       "22        exp_v1  22                 For which club does Maradonna play   \n",
       "51        exp_v1  51  Give me all matches where stage is Quarter-fin...   \n",
       "\n",
       "                                                      query hardness  split  \\\n",
       "id_index                                                                      \n",
       "2         SELECT T1.teamname, T3.teamname, T2.home_team_...    extra    100   \n",
       "6         select player.player_name\\r\\n from player join...    extra    100   \n",
       "11        SELECT count(*) FROM national_team AS T1 WHERE...     easy    100   \n",
       "22        select T3.club_name\\n from player as T1\\n join...    extra    100   \n",
       "51        SELECT m.year, nt.teamname, nt2.teamname, m.ho...    extra    100   \n",
       "\n",
       "          label                                         prediction  \\\n",
       "id_index                                                             \n",
       "2         False  select t1.teamname, t2.year from national_team...   \n",
       "6         False  select distinct t1.player_name from player as ...   \n",
       "11         True  select count(*) from national_team as t1 where...   \n",
       "22         True  select distinct t1.club_team_name from player_...   \n",
       "51        False  select t1.teamname from national_team as t1 jo...   \n",
       "\n",
       "                 system  number_of_joins  ...  query_length  \\\n",
       "id_index                                  ...                 \n",
       "2         T5$_{Picard}$                4  ...           625   \n",
       "6         T5$_{Picard}$                1  ...           206   \n",
       "11        T5$_{Picard}$                0  ...            68   \n",
       "22        T5$_{Picard}$                2  ...           182   \n",
       "51        T5$_{Picard}$                2  ...           276   \n",
       "\n",
       "          number_of_keywords  full_column_match  full_value_match  \\\n",
       "id_index                                                            \n",
       "2                          1                  0                 6   \n",
       "6                          2                  1                 6   \n",
       "11                         0                  0                 4   \n",
       "22                         0                  0                 0   \n",
       "51                         1                  1                 1   \n",
       "\n",
       "          partial_column_match  question_similarity_train_query_id  \\\n",
       "id_index                                                             \n",
       "2                           11                                 600   \n",
       "6                           11                                 848   \n",
       "11                           2                                 792   \n",
       "22                           3                                 469   \n",
       "51                           4                                  50   \n",
       "\n",
       "          similarity_score_nl  sql_similarity_train_query_id  \\\n",
       "id_index                                                       \n",
       "2                    0.761025                            332   \n",
       "6                    0.679872                            310   \n",
       "11                   0.989651                            792   \n",
       "22                   0.914928                             41   \n",
       "51                   0.749127                             50   \n",
       "\n",
       "          similarity_score_sql  no_tokens  \n",
       "id_index                                   \n",
       "2                     0.700800       77.0  \n",
       "6                     0.466019       21.0  \n",
       "11                    1.000000       10.0  \n",
       "22                    0.931937       26.0  \n",
       "51                    0.789855       34.0  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d1a1c7b-84c4-43f7-ac87-dd5be40bbc86",
   "metadata": {},
   "source": [
    "## Overall Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b827b4ab-6635-48c1-9743-2e92ae4a912d",
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>split</th>\n",
       "      <th>number_of_joins</th>\n",
       "      <th>number_of_projections</th>\n",
       "      <th>number_of_filters</th>\n",
       "      <th>number_of_aggregations</th>\n",
       "      <th>number_of_set_operations</th>\n",
       "      <th>number_of_subqueries</th>\n",
       "      <th>run</th>\n",
       "      <th>hardness_numeric</th>\n",
       "      <th>query_length</th>\n",
       "      <th>number_of_keywords</th>\n",
       "      <th>full_column_match</th>\n",
       "      <th>full_value_match</th>\n",
       "      <th>partial_column_match</th>\n",
       "      <th>question_similarity_train_query_id</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>14600.000000</td>\n",
       "      <td>9500.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>478.720000</td>\n",
       "      <td>69.904110</td>\n",
       "      <td>1.950959</td>\n",
       "      <td>2.037123</td>\n",
       "      <td>2.130274</td>\n",
       "      <td>0.566849</td>\n",
       "      <td>0.120685</td>\n",
       "      <td>0.030000</td>\n",
       "      <td>0.554795</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>233.433288</td>\n",
       "      <td>0.850000</td>\n",
       "      <td>0.479863</td>\n",
       "      <td>2.961781</td>\n",
       "      <td>7.154658</td>\n",
       "      <td>494.330000</td>\n",
       "      <td>0.782927</td>\n",
       "      <td>501.223014</td>\n",
       "      <td>0.794717</td>\n",
       "      <td>33.761368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>298.646062</td>\n",
       "      <td>98.363716</td>\n",
       "      <td>1.906307</td>\n",
       "      <td>1.287759</td>\n",
       "      <td>1.784741</td>\n",
       "      <td>0.820183</td>\n",
       "      <td>0.325772</td>\n",
       "      <td>0.221593</td>\n",
       "      <td>0.785432</td>\n",
       "      <td>1.054251</td>\n",
       "      <td>156.228566</td>\n",
       "      <td>1.033234</td>\n",
       "      <td>0.650422</td>\n",
       "      <td>2.590702</td>\n",
       "      <td>6.184465</td>\n",
       "      <td>282.699584</td>\n",
       "      <td>0.114464</td>\n",
       "      <td>320.742725</td>\n",
       "      <td>0.154950</td>\n",
       "      <td>22.376070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>0.489517</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>0.381579</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>211.500000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>179.000000</td>\n",
       "      <td>0.707716</td>\n",
       "      <td>197.000000</td>\n",
       "      <td>0.671429</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>491.500000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>186.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>526.500000</td>\n",
       "      <td>0.777947</td>\n",
       "      <td>490.000000</td>\n",
       "      <td>0.787313</td>\n",
       "      <td>26.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>673.750000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>288.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>728.250000</td>\n",
       "      <td>0.872010</td>\n",
       "      <td>792.000000</td>\n",
       "      <td>0.946970</td>\n",
       "      <td>39.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1075.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>831.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1074.000000</td>\n",
       "      <td>0.989651</td>\n",
       "      <td>1074.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>115.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id         split  number_of_joins  number_of_projections  \\\n",
       "count  14600.000000  14600.000000     14600.000000           14600.000000   \n",
       "mean     478.720000     69.904110         1.950959               2.037123   \n",
       "std      298.646062     98.363716         1.906307               1.287759   \n",
       "min        2.000000      0.000000         0.000000               1.000000   \n",
       "25%      211.500000      4.000000         1.000000               1.000000   \n",
       "50%      491.500000     20.000000         1.000000               2.000000   \n",
       "75%      673.750000    100.000000         2.000000               2.000000   \n",
       "max     1075.000000    300.000000        10.000000               9.000000   \n",
       "\n",
       "       number_of_filters  number_of_aggregations  number_of_set_operations  \\\n",
       "count       14600.000000            14600.000000              14600.000000   \n",
       "mean            2.130274                0.566849                  0.120685   \n",
       "std             1.784741                0.820183                  0.325772   \n",
       "min             0.000000                0.000000                  0.000000   \n",
       "25%             1.000000                0.000000                  0.000000   \n",
       "50%             2.000000                0.000000                  0.000000   \n",
       "75%             2.000000                1.000000                  0.000000   \n",
       "max             9.000000                3.000000                  1.000000   \n",
       "\n",
       "       number_of_subqueries           run  hardness_numeric  query_length  \\\n",
       "count          14600.000000  14600.000000      14600.000000  14600.000000   \n",
       "mean               0.030000      0.554795          3.100000    233.433288   \n",
       "std                0.221593      0.785432          1.054251    156.228566   \n",
       "min                0.000000      0.000000          1.000000     43.000000   \n",
       "25%                0.000000      0.000000          2.000000    139.000000   \n",
       "50%                0.000000      0.000000          3.000000    186.000000   \n",
       "75%                0.000000      1.000000          4.000000    288.000000   \n",
       "max                2.000000      2.000000          5.000000    831.000000   \n",
       "\n",
       "       number_of_keywords  full_column_match  full_value_match  \\\n",
       "count        14600.000000       14600.000000      14600.000000   \n",
       "mean             0.850000           0.479863          2.961781   \n",
       "std              1.033234           0.650422          2.590702   \n",
       "min              0.000000           0.000000          0.000000   \n",
       "25%              0.000000           0.000000          0.000000   \n",
       "50%              0.500000           0.000000          4.000000   \n",
       "75%              2.000000           1.000000          4.000000   \n",
       "max              5.000000           3.000000          9.000000   \n",
       "\n",
       "       partial_column_match  question_similarity_train_query_id  \\\n",
       "count          14600.000000                        14600.000000   \n",
       "mean               7.154658                          494.330000   \n",
       "std                6.184465                          282.699584   \n",
       "min                0.000000                           23.000000   \n",
       "25%                3.000000                          179.000000   \n",
       "50%                5.000000                          526.500000   \n",
       "75%               10.000000                          728.250000   \n",
       "max               41.000000                         1074.000000   \n",
       "\n",
       "       similarity_score_nl  sql_similarity_train_query_id  \\\n",
       "count         14600.000000                   14600.000000   \n",
       "mean              0.782927                     501.223014   \n",
       "std               0.114464                     320.742725   \n",
       "min               0.489517                      23.000000   \n",
       "25%               0.707716                     197.000000   \n",
       "50%               0.777947                     490.000000   \n",
       "75%               0.872010                     792.000000   \n",
       "max               0.989651                    1074.000000   \n",
       "\n",
       "       similarity_score_sql    no_tokens  \n",
       "count          14600.000000  9500.000000  \n",
       "mean               0.794717    33.761368  \n",
       "std                0.154950    22.376070  \n",
       "min                0.381579     8.000000  \n",
       "25%                0.671429    20.000000  \n",
       "50%                0.787313    26.000000  \n",
       "75%                0.946970    39.000000  \n",
       "max                1.000000   115.000000  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8f75d555-21eb-4f67-af80-c970cabda112",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hardness\n",
       "easy        308\n",
       "extra      1465\n",
       "extreme      20\n",
       "hard        858\n",
       "medium      649\n",
       "Name: label, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overall_counts = df_all[(df_all[\"split\"]==300) | (df_all[\"split\"]==30)].groupby([\"hardness\"])[\"label\"].count()\n",
    "overall_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "af8d2c50-cf8f-4686-84b1-b52fb9dd67c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hardness\n",
       "easy       206\n",
       "extra      293\n",
       "extreme      5\n",
       "hard       299\n",
       "medium     355\n",
       "Name: label, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true_counts = df_all[((df_all[\"split\"]==300) | (df_all[\"split\"]==30)) & (df_all[\"label\"]==True)].groupby([\"hardness\"])[\"label\"].count()\n",
    "true_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "93118fc7-2a28-4603-bcd1-d2bf2a2c9e2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "hardness\n",
       "easy       0.668831\n",
       "extra      0.200000\n",
       "extreme    0.250000\n",
       "hard       0.348485\n",
       "medium     0.546995\n",
       "Name: label, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hardness_accuracy = (true_counts/overall_counts)\n",
    "hardness_accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f1ec2b86-dde5-4be0-827c-c21029c2bad6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.63"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all[df_all[\"db_id\"]==\"exp_v2\"][\"number_of_joins\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dd6e5284-5145-4a56-bfd6-14107eee38e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "db_id   split  hardness\n",
       "exp_v1  0      easy         80\n",
       "               extra       358\n",
       "               extreme      10\n",
       "               hard        184\n",
       "               medium      168\n",
       "                          ... \n",
       "exp_v3  200    medium       95\n",
       "        300    easy         40\n",
       "               extra       185\n",
       "               hard        180\n",
       "               medium       95\n",
       "Name: label, Length: 134, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overall_counts = df_all.groupby([\"db_id\", \"split\", \"hardness\"])[\"label\"].count()\n",
    "overall_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7d121560-39a3-4367-9480-d06405048073",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "db_id   split  hardness\n",
       "exp_v1  0      easy        42\n",
       "               extra       20\n",
       "               hard        20\n",
       "               medium      38\n",
       "        2      easy        11\n",
       "                           ..\n",
       "exp_v3  200    medium      37\n",
       "        300    easy        27\n",
       "               extra       32\n",
       "               hard        58\n",
       "               medium      38\n",
       "Name: label, Length: 125, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true_counts = df_all[df_all[\"label\"]==True].groupby([\"db_id\", \"split\", \"hardness\"])[\"label\"].count()\n",
    "true_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d35748a7-40c8-4bb7-bfa0-7c08ebd83040",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "db_id   split  hardness\n",
       "exp_v1  0      easy        0.525000\n",
       "               extra       0.055866\n",
       "               extreme          NaN\n",
       "               hard        0.108696\n",
       "               medium      0.226190\n",
       "                             ...   \n",
       "exp_v3  200    medium      0.389474\n",
       "        300    easy        0.675000\n",
       "               extra       0.172973\n",
       "               hard        0.322222\n",
       "               medium      0.400000\n",
       "Name: label, Length: 134, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hardness_accuracy = (true_counts/overall_counts)\n",
    "hardness_accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "fca77f29-3583-4f91-b914-38bb6ab29245",
   "metadata": {},
   "outputs": [],
   "source": [
    "def count_token(row):\n",
    "    return len([v for v in row[\"query\"].split(\" \") if v !=\"\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a6695733-710a-4f18-a6ae-e22bdf9ba340",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all[\"no_tokens\"] = df_all.apply(count_token, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1dd26a8c-be9f-45e9-a78a-12140a875e26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33.75164383561644"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all[\"no_tokens\"].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7e42d94-d665-474c-80ac-85e81e0b1452",
   "metadata": {},
   "source": [
    "## Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cf6c42dd-6bef-4b0a-bfa8-12c11ba6cadc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['extra', 'easy', 'medium', 'hard'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from plotting import plot\n",
    "\n",
    "# nicer names\n",
    "renames = {\"GPT_SC\": r\"GPT-3.5$_{s+c}$\", \"GPT_S\": \"GPT-3.5\", \"GPT-3.5$_{s}$\" : \"GPT-3.5\",\n",
    "           \"T5$_{Picard}$\" : \"T5-Picard\",\n",
    "           \"T5-Keys\":r\"T5$_{Keys}$\", \"T5-Picard-Keys\":r\"T5-Picard$_{Keys}$\",\n",
    "          \"Llamav2\" : \"Llama2-70b\"}\n",
    "df_all = df_all.replace({\"system\": renames})\n",
    "\n",
    "# queries that cannot be classified by Spider parser\n",
    "df_all = df_all.replace({\"hardness\": {\"extreme\": \"extra\"}})\n",
    "df_all[\"hardness\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5bd424c1-2910-4378-8080-368159130183",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all = df_all[~df_all[\"system\"].isin([r\"GPT-3.5$_{s+c}$\", \"T5\", r\"T5$_{Keys}$\"])]\n",
    "\n",
    "hue_order= [\"ValueNet\",  \"T5-Picard\",\n",
    "            # r\"T5$_{Keys}$\",\n",
    "            \"T5-Picard$_{Keys}$\", \"GPT-3.5\", \"Llama2-70b\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "db3963c4-178e-4ab2-84bd-e1ec1c06f92b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['T5-Picard', 'Llama2-70b', 'GPT-3.5', 'T5-Picard$_{Keys}$',\n",
       "       'ValueNet'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all[\"system\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "323add28-7112-4b75-9a2c-1df940191f79",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "054805a9-feda-4f6f-8991-8b5edc8bf62d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ee630c11-f0d8-4502-baf3-f48370b5a6d5",
   "metadata": {},
   "source": [
    "### Spider Hardness vs. Execution Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5ea1421b-f74a-426e-a24d-3e360bb06dcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.plot_bars_counts(df_all[(df_all[\"split\"]==300) | (df_all[\"split\"]==30)  | (df_all[\"split\"]==8)], x=\"hardness\", hue=\"system\", system = \"\",\n",
    "                 order=[\"easy\", \"medium\", \"hard\", \"extra\"],\n",
    "                      hue_order= hue_order, filename=\"data_model-system-hardness-new\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5b4dd4c0-d9a9-4573-8c26-3fe7b80fcd43",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# plot.plot_bars_counts(df_all[(df_all[\"split\"]==300) | (df_all[\"split\"]==30)], x=\"hardness\", hue=\"system\", system = \"\",\n",
    "#                  order=[\"easy\", \"medium\", \"hard\", \"extra\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77bc2743-ae3f-4822-b3ef-01275481cb74",
   "metadata": {},
   "source": [
    "### Query Characteristics vs. Execution Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0dbf58f5-bc26-458d-a384-d10fd7ffe23d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def binarize(column):\n",
    "    return (column > 0).astype(int)\n",
    "\n",
    "def categorize_joins(column):\n",
    "    return column.apply(lambda x: 0 if x == 0 else (1 if x == 1 else 2))\n",
    "\n",
    "def zero_component(column):\n",
    "    return column.apply(lambda x: 1 if x == 0 else 0)\n",
    "\n",
    "def one_component(column):\n",
    "    return column.apply(lambda x: 1 if x == 1 else 0)\n",
    "    \n",
    "def one_and_more_component(column):\n",
    "    return column.apply(lambda x: 1 if x >= 1 else 0)\n",
    "\n",
    "\n",
    "def two_and_more_component(column):\n",
    "    return column.apply(lambda x: 1 if x >= 2 else 0)\n",
    "\n",
    "\n",
    "df_all[r'$\\geq 1$ agg'] = binarize(df_all['number_of_aggregations'])\n",
    "df_all[r'$\\geq 1$ set'] = binarize(df_all['number_of_set_operations'])\n",
    "df_all[r'$\\geq 1$ subquery'] = binarize(df_all['number_of_subqueries'])\n",
    "df_all[r'$1$ join'] = one_component(df_all['number_of_joins'])\n",
    "df_all[r'$\\geq 2$ join'] = two_and_more_component(df_all['number_of_joins'])\n",
    "df_all[r'$1$ project'] = one_component(df_all['number_of_projections'])\n",
    "df_all[r'$\\geq 2$ project'] = two_and_more_component(df_all['number_of_projections'])\n",
    "\n",
    "df_all[r'$1$ filter'] = one_component(df_all['number_of_filters'])\n",
    "df_all[r'$\\geq 2$ filter'] = two_and_more_component(df_all['number_of_filters'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cc367633-1161-4a23-9cce-ecad7c6a9ad4",
   "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>system</th>\n",
       "      <th>db_id</th>\n",
       "      <th>split</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>label</th>\n",
       "      <th>$\\geq 1$ agg</th>\n",
       "      <th>$\\geq 1$ set</th>\n",
       "      <th>$1$ join</th>\n",
       "      <th>$\\geq 2$ join</th>\n",
       "      <th>$1$ project</th>\n",
       "      <th>$\\geq 2$ project</th>\n",
       "      <th>$1$ filter</th>\n",
       "      <th>$\\geq 2$ filter</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>Against which team did Switzerland loose in 2018</td>\n",
       "      <td>SELECT T1.teamname, T3.teamname, T2.home_team_...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>All players that have the shirt number 13 and ...</td>\n",
       "      <td>select player.player_name\\r\\n from player join...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>At how many woldcups did italy participate in?</td>\n",
       "      <td>SELECT count(*) FROM national_team AS T1 WHERE...</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>22</td>\n",
       "      <td>For which club does Maradonna play</td>\n",
       "      <td>select T3.club_name\\n from player as T1\\n join...</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>51</td>\n",
       "      <td>Give me all matches where stage is Quarter-fin...</td>\n",
       "      <td>SELECT m.year, nt.teamname, nt2.teamname, m.ho...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             system   db_id  split  id  \\\n",
       "id_index                                 \n",
       "2         T5-Picard  exp_v1    100   2   \n",
       "6         T5-Picard  exp_v1    100   6   \n",
       "11        T5-Picard  exp_v1    100  11   \n",
       "22        T5-Picard  exp_v1    100  22   \n",
       "51        T5-Picard  exp_v1    100  51   \n",
       "\n",
       "                                                   question  \\\n",
       "id_index                                                      \n",
       "2          Against which team did Switzerland loose in 2018   \n",
       "6         All players that have the shirt number 13 and ...   \n",
       "11           At how many woldcups did italy participate in?   \n",
       "22                       For which club does Maradonna play   \n",
       "51        Give me all matches where stage is Quarter-fin...   \n",
       "\n",
       "                                                      query  label  \\\n",
       "id_index                                                             \n",
       "2         SELECT T1.teamname, T3.teamname, T2.home_team_...  False   \n",
       "6         select player.player_name\\r\\n from player join...  False   \n",
       "11        SELECT count(*) FROM national_team AS T1 WHERE...   True   \n",
       "22        select T3.club_name\\n from player as T1\\n join...   True   \n",
       "51        SELECT m.year, nt.teamname, nt2.teamname, m.ho...  False   \n",
       "\n",
       "          $\\geq 1$ agg  $\\geq 1$ set  $1$ join  $\\geq 2$ join  $1$ project  \\\n",
       "id_index                                                                     \n",
       "2                    0             1         0              1            0   \n",
       "6                    0             0         1              0            1   \n",
       "11                   1             0         0              0            1   \n",
       "22                   0             0         0              1            1   \n",
       "51                   0             0         0              1            0   \n",
       "\n",
       "          $\\geq 2$ project  $1$ filter  $\\geq 2$ filter  \n",
       "id_index                                                 \n",
       "2                        1           0                1  \n",
       "6                        0           0                1  \n",
       "11                       0           1                0  \n",
       "22                       0           1                0  \n",
       "51                       1           0                1  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_qc = df_all[[\"system\", \"db_id\", \"split\", \"id\", \"question\", \"query\", \"label\",\n",
    "                  r'$\\geq 1$ agg', r'$\\geq 1$ set',\n",
    "                  # r'$\\geq 1$ subquery',\n",
    "                  r'$1$ join', r'$\\geq 2$ join',\n",
    "                 r'$1$ project', r'$\\geq 2$ project', r'$1$ filter', r'$\\geq 2$ filter'\n",
    "                 ]]\n",
    "df_qc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ce8cb539-38c1-44e2-a524-b8c70ccf54e0",
   "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>system</th>\n",
       "      <th>db_id</th>\n",
       "      <th>split</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>label</th>\n",
       "      <th>Query Characteristic</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>At how many woldcups did italy participate in?</td>\n",
       "      <td>SELECT count(*) FROM national_team AS T1 WHERE...</td>\n",
       "      <td>True</td>\n",
       "      <td>$\\geq 1$ agg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>94</td>\n",
       "      <td>How many games did Brazil win?</td>\n",
       "      <td>SELECT count(*)\\nFROM national_team AS T1\\n   ...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\geq 1$ agg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>104</td>\n",
       "      <td>How many goals did each player score over all ...</td>\n",
       "      <td>select nt.teamname, p.player_name, count(*)\\n ...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\geq 1$ agg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>120</td>\n",
       "      <td>How many goals did Ronaldo Score?</td>\n",
       "      <td>SELECT T2.player_name, count(*) FROM match_fac...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\geq 1$ agg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>122</td>\n",
       "      <td>How many goals did switzerland score in 2018</td>\n",
       "      <td>select sum(t.g)\\nfrom\\n    (select sum(T2.away...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\geq 1$ agg</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       system   db_id  split   id  \\\n",
       "2   T5-Picard  exp_v1    100   11   \n",
       "6   T5-Picard  exp_v1    100   94   \n",
       "7   T5-Picard  exp_v1    100  104   \n",
       "9   T5-Picard  exp_v1    100  120   \n",
       "10  T5-Picard  exp_v1    100  122   \n",
       "\n",
       "                                             question  \\\n",
       "2      At how many woldcups did italy participate in?   \n",
       "6                      How many games did Brazil win?   \n",
       "7   How many goals did each player score over all ...   \n",
       "9                   How many goals did Ronaldo Score?   \n",
       "10       How many goals did switzerland score in 2018   \n",
       "\n",
       "                                                query  label  \\\n",
       "2   SELECT count(*) FROM national_team AS T1 WHERE...   True   \n",
       "6   SELECT count(*)\\nFROM national_team AS T1\\n   ...  False   \n",
       "7   select nt.teamname, p.player_name, count(*)\\n ...  False   \n",
       "9   SELECT T2.player_name, count(*) FROM match_fac...  False   \n",
       "10  select sum(t.g)\\nfrom\\n    (select sum(T2.away...  False   \n",
       "\n",
       "   Query Characteristic  value  \n",
       "2          $\\geq 1$ agg      1  \n",
       "6          $\\geq 1$ agg      1  \n",
       "7          $\\geq 1$ agg      1  \n",
       "9          $\\geq 1$ agg      1  \n",
       "10         $\\geq 1$ agg      1  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_qc_melt = df_qc.melt(id_vars=[\"system\", \"db_id\", \"split\", \"id\", \"question\", \"query\", \"label\"],\n",
    "                       value_vars=[\n",
    "                  r'$\\geq 1$ agg', r'$\\geq 1$ set',\n",
    "                           # r'$\\geq 1$ subquery',\n",
    "                           r'$1$ join', r'$\\geq 2$ join',\n",
    "                 r'$1$ project', r'$\\geq 2$ project', r'$1$ filter', r'$\\geq 2$ filter'\n",
    "                       ],\n",
    "                       var_name=\"Query Characteristic\")\n",
    "df_qc_melt = df_qc_melt.drop(df_qc_melt[df_qc_melt.value == 0].index)\n",
    "df_qc_melt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "db48bbfc-e5d4-453d-a68d-523cf0fcca78",
   "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>system</th>\n",
       "      <th>db_id</th>\n",
       "      <th>split</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>label</th>\n",
       "      <th>Query Characteristic</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [system, db_id, split, id, question, query, label, Query Characteristic, value]\n",
       "Index: []"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_qc_melt[df_qc_melt[\"system\"] == \"Llama2-70b$_{Keys}$\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7612c8e3-75dc-4946-b821-fdc1405f4cb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x900 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [\n",
    "    r'$1$ filter',\n",
    "    r'$\\geq 2$ filter',\n",
    "    r'$1$ project',\n",
    "    r'$\\geq 2$ project',\n",
    "    r'$1$ join',\n",
    "    r'$\\geq 2$ join',\n",
    "    r'$\\geq 1$ agg',\n",
    "    r'$\\geq 1$ set',\n",
    "]\n",
    "\n",
    "plot.plot_bars_vertical(df_qc_melt[((df_qc_melt[\"split\"]==300) | (df_qc_melt[\"split\"]==30) | (df_qc_melt[\"split\"]==8))],\n",
    "                x=\"Query Characteristic\", hue=\"system\", system = \"\", order=order, figsize=(11,9),\n",
    "               filename=\"sql-query-characteristic-without-subquery-300-data-model-v1-v2-v3-new\",\n",
    "                        hue_order= hue_order\n",
    "                       )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5af9cfb-4153-4116-b209-6c9818c443f0",
   "metadata": {},
   "source": [
    "### NL-SQL overlap based on SQL keywords (KW) and full columns or value matches "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ee47b44e-5789-42d9-a398-392495112a35",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all[r'$0$ KW'] = zero_component(df_all['number_of_keywords'])\n",
    "# df_all[r'$1$ number_of_keywords'] = one_component(df_all['number_of_keywords'])\n",
    "# df_all[r'$\\geq 2$ number_of_keywords'] = two_component(df_all['number_of_keywords'])\n",
    "df_all[r'$\\geq 1$ KW'] = one_and_more_component(df_all['number_of_keywords'])\n",
    "\n",
    "\n",
    "df_all[r'$0$ column'] = zero_component(df_all['full_column_match'])\n",
    "# df_all[r'$1$ full_column_match'] = one_component(df_all['full_column_match'])\n",
    "# df_all[r'$\\geq 2$ full_column_match'] = two_component(df_all['full_column_match'])\n",
    "df_all[r'$\\geq 1$ column'] = one_and_more_component(df_all['full_column_match'])\n",
    "\n",
    "\n",
    "df_all[r'$0$ value'] = zero_component(df_all['full_value_match'])\n",
    "# df_all[r'$1$ full_value_match'] = one_component(df_all['full_value_match'])\n",
    "# df_all[r'$\\geq 2$ full_value_match'] = two_component(df_all['full_value_match'])\n",
    "df_all[r'$\\geq 1$ value'] = one_and_more_component(df_all['full_value_match'])\n",
    "\n",
    "\n",
    "# df_all[r'$0$ col$_{partial}$'] = zero_component(df_all['partial_column_match'])\n",
    "# df_all[r'$1$ partial_column_match'] = one_component(df_all['partial_column_match'])\n",
    "# df_all[r'$\\geq 2$ partial_column_match'] = two_component(df_all['partial_column_match'])\n",
    "# df_all[r'$\\geq 1$ col$_{partial}$'] = one_and_more_component(df_all['partial_column_match'])\n",
    "\n",
    "\n",
    "\n",
    "                  # r'$0$ KW', r'$\\geq 1$ KW',\n",
    "                  # r'$0$ column', r'$\\geq 1$ column',\n",
    "                  # r'$0$ value', r'$\\geq 1$ value',\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "dd09fd44-f524-4ef8-a3ff-a6e45b26a57d",
   "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>system</th>\n",
       "      <th>db_id</th>\n",
       "      <th>split</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>label</th>\n",
       "      <th>$0$ KW</th>\n",
       "      <th>$\\geq 1$ KW</th>\n",
       "      <th>$0$ column</th>\n",
       "      <th>$\\geq 1$ column</th>\n",
       "      <th>$0$ value</th>\n",
       "      <th>$\\geq 1$ value</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id_index</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>Against which team did Switzerland loose in 2018</td>\n",
       "      <td>SELECT T1.teamname, T3.teamname, T2.home_team_...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>All players that have the shirt number 13 and ...</td>\n",
       "      <td>select player.player_name\\r\\n from player join...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>At how many woldcups did italy participate in?</td>\n",
       "      <td>SELECT count(*) FROM national_team AS T1 WHERE...</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>22</td>\n",
       "      <td>For which club does Maradonna play</td>\n",
       "      <td>select T3.club_name\\n from player as T1\\n join...</td>\n",
       "      <td>True</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>51</td>\n",
       "      <td>Give me all matches where stage is Quarter-fin...</td>\n",
       "      <td>SELECT m.year, nt.teamname, nt2.teamname, m.ho...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             system   db_id  split  id  \\\n",
       "id_index                                 \n",
       "2         T5-Picard  exp_v1    100   2   \n",
       "6         T5-Picard  exp_v1    100   6   \n",
       "11        T5-Picard  exp_v1    100  11   \n",
       "22        T5-Picard  exp_v1    100  22   \n",
       "51        T5-Picard  exp_v1    100  51   \n",
       "\n",
       "                                                   question  \\\n",
       "id_index                                                      \n",
       "2          Against which team did Switzerland loose in 2018   \n",
       "6         All players that have the shirt number 13 and ...   \n",
       "11           At how many woldcups did italy participate in?   \n",
       "22                       For which club does Maradonna play   \n",
       "51        Give me all matches where stage is Quarter-fin...   \n",
       "\n",
       "                                                      query  label  $0$ KW  \\\n",
       "id_index                                                                     \n",
       "2         SELECT T1.teamname, T3.teamname, T2.home_team_...  False       0   \n",
       "6         select player.player_name\\r\\n from player join...  False       0   \n",
       "11        SELECT count(*) FROM national_team AS T1 WHERE...   True       1   \n",
       "22        select T3.club_name\\n from player as T1\\n join...   True       1   \n",
       "51        SELECT m.year, nt.teamname, nt2.teamname, m.ho...  False       0   \n",
       "\n",
       "          $\\geq 1$ KW  $0$ column  $\\geq 1$ column  $0$ value  $\\geq 1$ value  \n",
       "id_index                                                                       \n",
       "2                   1           1                0          0               1  \n",
       "6                   1           0                1          0               1  \n",
       "11                  0           1                0          0               1  \n",
       "22                  0           1                0          1               0  \n",
       "51                  1           0                1          0               1  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_nl_complexity = df_all[[\"system\", \"db_id\", \"split\", \"id\", \"question\", \"query\", \"label\",\n",
    "                  # r'$0$ number_of_keywords', r'$1$ number_of_keywords', r'$\\geq 2$ number_of_keywords',\n",
    "                  # r'$0$ full_column_match', r'$1$ full_column_match', r'$\\geq 2$ full_column_match',\n",
    "                  # r'$0$ full_value_match', r'$1$ full_value_match', r'$\\geq 2$ full_value_match',\n",
    "                  # r'$0$ partial_column_match', r'$1$ partial_column_match', r'$\\geq 2$ partial_column_match',\n",
    "                  r'$0$ KW', r'$\\geq 1$ KW',\n",
    "                  r'$0$ column', r'$\\geq 1$ column',\n",
    "                  r'$0$ value', r'$\\geq 1$ value',\n",
    "                  # r'$0$ col$_{partial}$', r'$\\geq 1$ col$_{partial}$',\n",
    "                           \n",
    "                 ]]\n",
    "df_nl_complexity.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c76feb37-f0cd-4e6f-ba5f-9ea4a1fb2187",
   "metadata": {
    "scrolled": true
   },
   "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>system</th>\n",
       "      <th>db_id</th>\n",
       "      <th>split</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>label</th>\n",
       "      <th>NL Characteristic</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>At how many woldcups did italy participate in?</td>\n",
       "      <td>SELECT count(*) FROM national_team AS T1 WHERE...</td>\n",
       "      <td>True</td>\n",
       "      <td>$0$ KW</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>22</td>\n",
       "      <td>For which club does Maradonna play</td>\n",
       "      <td>select T3.club_name\\n from player as T1\\n join...</td>\n",
       "      <td>True</td>\n",
       "      <td>$0$ KW</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>89</td>\n",
       "      <td>Give me the year of the first world cup played.</td>\n",
       "      <td>select t1.year from world_cup as t1 order by t...</td>\n",
       "      <td>True</td>\n",
       "      <td>$0$ KW</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>94</td>\n",
       "      <td>How many games did Brazil win?</td>\n",
       "      <td>SELECT count(*)\\nFROM national_team AS T1\\n   ...</td>\n",
       "      <td>False</td>\n",
       "      <td>$0$ KW</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>108</td>\n",
       "      <td>How many Goals did Germany score against Brazil?</td>\n",
       "      <td>SELECT T3.year, T2.away_team_goals\\n FROM nati...</td>\n",
       "      <td>False</td>\n",
       "      <td>$0$ KW</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      system   db_id  split   id  \\\n",
       "2  T5-Picard  exp_v1    100   11   \n",
       "3  T5-Picard  exp_v1    100   22   \n",
       "5  T5-Picard  exp_v1    100   89   \n",
       "6  T5-Picard  exp_v1    100   94   \n",
       "8  T5-Picard  exp_v1    100  108   \n",
       "\n",
       "                                           question  \\\n",
       "2    At how many woldcups did italy participate in?   \n",
       "3                For which club does Maradonna play   \n",
       "5   Give me the year of the first world cup played.   \n",
       "6                    How many games did Brazil win?   \n",
       "8  How many Goals did Germany score against Brazil?   \n",
       "\n",
       "                                               query  label NL Characteristic  \\\n",
       "2  SELECT count(*) FROM national_team AS T1 WHERE...   True            $0$ KW   \n",
       "3  select T3.club_name\\n from player as T1\\n join...   True            $0$ KW   \n",
       "5  select t1.year from world_cup as t1 order by t...   True            $0$ KW   \n",
       "6  SELECT count(*)\\nFROM national_team AS T1\\n   ...  False            $0$ KW   \n",
       "8  SELECT T3.year, T2.away_team_goals\\n FROM nati...  False            $0$ KW   \n",
       "\n",
       "   value  \n",
       "2      1  \n",
       "3      1  \n",
       "5      1  \n",
       "6      1  \n",
       "8      1  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_nl_complexity_melt = df_nl_complexity.melt(\n",
    "    id_vars=[\"system\", \"db_id\", \"split\", \"id\", \"question\", \"query\", \"label\"],\n",
    "    value_vars=[\n",
    "                  # r'$0$ number_of_keywords', r'$1$ number_of_keywords', r'$\\geq 2$ number_of_keywords',\n",
    "                  # r'$0$ full_column_match', r'$1$ full_column_match', r'$\\geq 2$ full_column_match',\n",
    "                  # r'$0$ full_value_match', r'$1$ full_value_match', r'$\\geq 2$ full_value_match',\n",
    "                  # r'$0$ partial_column_match', r'$1$ partial_column_match', r'$\\geq 2$ partial_column_match',\n",
    "                  r'$0$ KW', r'$\\geq 1$ KW',\n",
    "                  r'$0$ column', r'$\\geq 1$ column',\n",
    "                  r'$0$ value', r'$\\geq 1$ value',\n",
    "                  # r'$0$ col$_{partial}$', r'$\\geq 1$ col$_{partial}$',\n",
    "        \n",
    "                ],\n",
    "                var_name=\"NL Characteristic\")\n",
    "df_nl_complexity_melt = df_nl_complexity_melt.drop(df_nl_complexity_melt[df_nl_complexity_melt.value == 0].index)\n",
    "df_nl_complexity_melt.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1583bebc-c194-4c48-8770-d7fb4b3063ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x900 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [\n",
    "      # r'$0$ number_of_keywords', r'$1$ number_of_keywords', r'$\\geq 2$ number_of_keywords',\n",
    "      # r'$0$ full_column_match', r'$1$ full_column_match', r'$\\geq 2$ full_column_match',\n",
    "      # r'$0$ full_value_match', r'$1$ full_value_match', r'$\\geq 2$ full_value_match',\n",
    "      # r'$0$ partial_column_match', r'$1$ partial_column_match', r'$\\geq 2$ partial_column_match',\n",
    "                  r'$0$ KW', r'$\\geq 1$ KW',\n",
    "                  r'$0$ column', r'$\\geq 1$ column',\n",
    "                  r'$0$ value', r'$\\geq 1$ value',\n",
    "                  # r'$0$ col$_{partial}$', r'$\\geq 1$ col$_{partial}$',\n",
    "]\n",
    "plot.plot_bars_vertical(df_nl_complexity_melt[((df_nl_complexity_melt[\"split\"]==300) | (df_nl_complexity_melt[\"split\"]==30) | (df_nl_complexity_melt[\"split\"]==8))],\n",
    "                x=\"NL Characteristic\", hue=\"system\", system = \"\", order=order,\n",
    "               filename=\"NL-characteristics-new\", figsize=(11,9), rotation=0,\n",
    "                        hue_order= hue_order\n",
    "                       )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "64d472a4-92b0-4904-bdb0-7aed3c0ca429",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "cc2363d2-b0af-4e1d-b235-63ab81664693",
   "metadata": {},
   "source": [
    "### Train-Test Similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bf7b69c1-9ebc-4224-9631-8e670e3d4860",
   "metadata": {},
   "outputs": [],
   "source": [
    "def lower_25(column):\n",
    "    t = column.describe().loc[\"25%\"]\n",
    "    return column.apply(lambda x: 1 if x <= t else 0)\n",
    "\n",
    "def upper_25(column):\n",
    "    t = column.describe().loc[\"75%\"]\n",
    "    return column.apply(lambda x: 1 if x >= t else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7bb667e9-6d28-49d5-bf0f-3114ffb413bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all[r'$\\leq$ 25th %ile NL']  = lower_25(df_all['similarity_score_nl'])\n",
    "df_all[r'$\\geq$ 75th %ile NL']  = upper_25(df_all['similarity_score_nl'])\n",
    "\n",
    "\n",
    "df_all[r'$\\leq$ 25th %ile SQL']  = lower_25(df_all['similarity_score_sql'])\n",
    "df_all[r'$\\geq$ 75th %ile SQL']  = upper_25(df_all['similarity_score_sql'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cbd852d9-6f8d-4431-943f-535556c9b89c",
   "metadata": {},
   "outputs": [
    {
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       "      <td>True</td>\n",
       "      <td>select count(*) from national_team as t1 where...</td>\n",
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       "      <td>How many goals has Giroud scored?</td>\n",
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       "      <td>How often did italy participate?</td>\n",
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       "      <td>select count(*) from national_team where teamn...</td>\n",
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       "      <td>SELECT T1.player_name\\n FROM player AS T1 JOIN...</td>\n",
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       "      <th>928</th>\n",
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       "      <td>928</td>\n",
       "      <td>Who won the world cup 1994?</td>\n",
       "      <td>SELECT T1.teamname FROM national_team AS T1 JO...</td>\n",
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       "      <th>1024</th>\n",
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       "      <td>toatal Goal score of shirt number 13?</td>\n",
       "      <td>SELECT count(*)\\n FROM match_fact AS T1\\n JOIN...</td>\n",
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       "    <tr>\n",
       "      <th>1027</th>\n",
       "      <td>exp_v3</td>\n",
       "      <td>1027</td>\n",
       "      <td>total Goal score of shirt number 13?</td>\n",
       "      <td>SELECT count(*)\\n FROM match_fact AS T1\\n JOIN...</td>\n",
       "      <td>medium</td>\n",
       "      <td>200</td>\n",
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       "      <th>1043</th>\n",
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       "      <td>1043</td>\n",
       "      <td>Goal score of shirt number 13?</td>\n",
       "      <td>SELECT count(*)\\n FROM match_fact as T1\\n JOIN...</td>\n",
       "      <td>medium</td>\n",
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       "      <th>1075</th>\n",
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       "      <td>1075</td>\n",
       "      <td>Against which country lost germany in wm 2014.</td>\n",
       "      <td>SELECT T1.teamname\\n FROM national_team AS T1\\...</td>\n",
       "      <td>hard</td>\n",
       "      <td>200</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ValueNet</td>\n",
       "      <td>2</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2371 rows × 49 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           db_id    id                                        question  \\\n",
       "id_index                                                                 \n",
       "11        exp_v1    11  At how many woldcups did italy participate in?   \n",
       "120       exp_v1   120               How many goals did Ronaldo Score?   \n",
       "124       exp_v1   124               How many goals has Giroud scored?   \n",
       "173       exp_v1   173                How often did italy participate?   \n",
       "246       exp_v1   246         players of switzerland at worldcup 2018   \n",
       "...          ...   ...                                             ...   \n",
       "928       exp_v3   928                     Who won the world cup 1994?   \n",
       "1024      exp_v3  1024           toatal Goal score of shirt number 13?   \n",
       "1027      exp_v3  1027            total Goal score of shirt number 13?   \n",
       "1043      exp_v3  1043                  Goal score of shirt number 13?   \n",
       "1075      exp_v3  1075  Against which country lost germany in wm 2014.   \n",
       "\n",
       "                                                      query hardness  split  \\\n",
       "id_index                                                                      \n",
       "11        SELECT count(*) FROM national_team AS T1 WHERE...     easy    100   \n",
       "120       SELECT T2.player_name, count(*) FROM match_fac...     hard    100   \n",
       "124       SELECT count(*) FROM match_fact AS T1 JOIN pla...   medium    100   \n",
       "173       SELECT count(*) FROM national_team AS T1 WHERE...     easy    100   \n",
       "246       SELECT T1.player_name\\n FROM player AS T1 JOIN...     hard    100   \n",
       "...                                                     ...      ...    ...   \n",
       "928       SELECT T1.teamname FROM national_team AS T1 JO...   medium    200   \n",
       "1024      SELECT count(*)\\n FROM match_fact AS T1\\n JOIN...   medium    200   \n",
       "1027      SELECT count(*)\\n FROM match_fact AS T1\\n JOIN...   medium    200   \n",
       "1043      SELECT count(*)\\n FROM match_fact as T1\\n JOIN...   medium    200   \n",
       "1075      SELECT T1.teamname\\n FROM national_team AS T1\\...     hard    200   \n",
       "\n",
       "          label                                         prediction     system  \\\n",
       "id_index                                                                        \n",
       "11         True  select count(*) from national_team as t1 where...  T5-Picard   \n",
       "120       False  select count(*) from player as t1 join match_f...  T5-Picard   \n",
       "124       False  select count(*) from player as t1 join match_f...  T5-Picard   \n",
       "173        True  select count(*) from national_team where teamn...  T5-Picard   \n",
       "246        True  select t1.player_name from player as t1 join p...  T5-Picard   \n",
       "...         ...                                                ...        ...   \n",
       "928        True                                                NaN   ValueNet   \n",
       "1024       True                                                NaN   ValueNet   \n",
       "1027       True                                                NaN   ValueNet   \n",
       "1043       True                                                NaN   ValueNet   \n",
       "1075       True                                                NaN   ValueNet   \n",
       "\n",
       "          number_of_joins  ...  $0$ KW  $\\geq 1$ KW  $0$ column  \\\n",
       "id_index                   ...                                    \n",
       "11                      0  ...       1            0           1   \n",
       "120                     1  ...       1            0           0   \n",
       "124                     1  ...       1            0           0   \n",
       "173                     0  ...       1            0           1   \n",
       "246                     2  ...       0            1           1   \n",
       "...                   ...  ...     ...          ...         ...   \n",
       "928                     1  ...       1            0           1   \n",
       "1024                    1  ...       0            1           0   \n",
       "1027                    1  ...       0            1           0   \n",
       "1043                    1  ...       0            1           0   \n",
       "1075                    2  ...       0            1           0   \n",
       "\n",
       "          $\\geq 1$ column  $0$ value  $\\geq 1$ value  $\\leq$ 25th %ile NL  \\\n",
       "id_index                                                                    \n",
       "11                      0          0               1                    0   \n",
       "120                     1          0               1                    0   \n",
       "124                     1          0               1                    0   \n",
       "173                     0          0               1                    0   \n",
       "246                     0          0               1                    0   \n",
       "...                   ...        ...             ...                  ...   \n",
       "928                     0          1               0                    0   \n",
       "1024                    1          1               0                    1   \n",
       "1027                    1          1               0                    0   \n",
       "1043                    1          1               0                    0   \n",
       "1075                    1          0               1                    0   \n",
       "\n",
       "          $\\geq$ 75th %ile NL  $\\leq$ 25th %ile SQL  $\\geq$ 75th %ile SQL  \n",
       "id_index                                                                   \n",
       "11                          1                     0                     1  \n",
       "120                         1                     0                     1  \n",
       "124                         1                     0                     1  \n",
       "173                         0                     0                     1  \n",
       "246                         0                     0                     1  \n",
       "...                       ...                   ...                   ...  \n",
       "928                         1                     0                     1  \n",
       "1024                        0                     0                     1  \n",
       "1027                        0                     0                     1  \n",
       "1043                        0                     0                     1  \n",
       "1075                        1                     0                     1  \n",
       "\n",
       "[2371 rows x 49 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all[df_all['similarity_score_sql'] > df_all['similarity_score_sql'].describe().loc[\"75%\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "aa7bdd7b-f0cc-4bd9-bc95-3ffe1315b3c7",
   "metadata": {},
   "outputs": [
    {
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       "  </thead>\n",
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       "      <th>2</th>\n",
       "      <td>T5-Picard</td>\n",
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       "      <td>100</td>\n",
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       "      <td>Against which team did Switzerland loose in 2018</td>\n",
       "      <td>SELECT T1.teamname, T3.teamname, T2.home_team_...</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>All players that have the shirt number 13 and ...</td>\n",
       "      <td>select player.player_name\\r\\n from player join...</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>11</td>\n",
       "      <td>At how many woldcups did italy participate in?</td>\n",
       "      <td>SELECT count(*) FROM national_team AS T1 WHERE...</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>22</td>\n",
       "      <td>For which club does Maradonna play</td>\n",
       "      <td>select T3.club_name\\n from player as T1\\n join...</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>51</td>\n",
       "      <td>Give me all matches where stage is Quarter-fin...</td>\n",
       "      <td>SELECT m.year, nt.teamname, nt2.teamname, m.ho...</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             system   db_id  split  id  \\\n",
       "id_index                                 \n",
       "2         T5-Picard  exp_v1    100   2   \n",
       "6         T5-Picard  exp_v1    100   6   \n",
       "11        T5-Picard  exp_v1    100  11   \n",
       "22        T5-Picard  exp_v1    100  22   \n",
       "51        T5-Picard  exp_v1    100  51   \n",
       "\n",
       "                                                   question  \\\n",
       "id_index                                                      \n",
       "2          Against which team did Switzerland loose in 2018   \n",
       "6         All players that have the shirt number 13 and ...   \n",
       "11           At how many woldcups did italy participate in?   \n",
       "22                       For which club does Maradonna play   \n",
       "51        Give me all matches where stage is Quarter-fin...   \n",
       "\n",
       "                                                      query  label  \\\n",
       "id_index                                                             \n",
       "2         SELECT T1.teamname, T3.teamname, T2.home_team_...  False   \n",
       "6         select player.player_name\\r\\n from player join...  False   \n",
       "11        SELECT count(*) FROM national_team AS T1 WHERE...   True   \n",
       "22        select T3.club_name\\n from player as T1\\n join...   True   \n",
       "51        SELECT m.year, nt.teamname, nt2.teamname, m.ho...  False   \n",
       "\n",
       "          $\\leq$ 25th %ile NL  $\\geq$ 75th %ile NL  $\\leq$ 25th %ile SQL  \\\n",
       "id_index                                                                   \n",
       "2                           0                    0                     0   \n",
       "6                           1                    0                     1   \n",
       "11                          0                    1                     0   \n",
       "22                          0                    1                     0   \n",
       "51                          0                    0                     0   \n",
       "\n",
       "          $\\geq$ 75th %ile SQL  \n",
       "id_index                        \n",
       "2                            0  \n",
       "6                            0  \n",
       "11                           1  \n",
       "22                           0  \n",
       "51                           0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_similarity = df_all[[\"system\", \"db_id\", \"split\", \"id\", \"question\", \"query\", \"label\",\n",
    "                  # r'$0$ number_of_keywords', r'$1$ number_of_keywords', r'$\\geq 2$ number_of_keywords',\n",
    "                  # r'$0$ full_column_match', r'$1$ full_column_match', r'$\\geq 2$ full_column_match',\n",
    "                  # r'$0$ full_value_match', r'$1$ full_value_match', r'$\\geq 2$ full_value_match',\n",
    "                  # r'$0$ partial_column_match', r'$1$ partial_column_match', r'$\\geq 2$ partial_column_match',\n",
    "                  r'$\\leq$ 25th %ile NL', r'$\\geq$ 75th %ile NL',\n",
    "                  r'$\\leq$ 25th %ile SQL', r'$\\geq$ 75th %ile SQL',\n",
    "                           \n",
    "                 ]]\n",
    "df_similarity.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fb552608-511f-4c3f-b73b-4455c842709e",
   "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>system</th>\n",
       "      <th>db_id</th>\n",
       "      <th>split</th>\n",
       "      <th>id</th>\n",
       "      <th>question</th>\n",
       "      <th>query</th>\n",
       "      <th>label</th>\n",
       "      <th>Similarity</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>All players that have the shirt number 13 and ...</td>\n",
       "      <td>select player.player_name\\r\\n from player join...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\leq$ 25th %ile NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>144</td>\n",
       "      <td>How many players have played so far?</td>\n",
       "      <td>SELECT count(distinct p.player_id) from player...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\leq$ 25th %ile NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>184</td>\n",
       "      <td>In which country were the least amounts of gam...</td>\n",
       "      <td>select s.country, count(*)\\r\\n from stadium as...</td>\n",
       "      <td>True</td>\n",
       "      <td>$\\leq$ 25th %ile NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>186</td>\n",
       "      <td>In which coutry is A.C. Milan playing?</td>\n",
       "      <td>select c.country from club as c where c.club_n...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\leq$ 25th %ile NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>T5-Picard</td>\n",
       "      <td>exp_v1</td>\n",
       "      <td>100</td>\n",
       "      <td>214</td>\n",
       "      <td>List all clubs from Switzerland that were foun...</td>\n",
       "      <td>select * from club as c where c.country = 'Swi...</td>\n",
       "      <td>False</td>\n",
       "      <td>$\\leq$ 25th %ile NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       system   db_id  split   id  \\\n",
       "1   T5-Picard  exp_v1    100    6   \n",
       "15  T5-Picard  exp_v1    100  144   \n",
       "22  T5-Picard  exp_v1    100  184   \n",
       "23  T5-Picard  exp_v1    100  186   \n",
       "25  T5-Picard  exp_v1    100  214   \n",
       "\n",
       "                                             question  \\\n",
       "1   All players that have the shirt number 13 and ...   \n",
       "15               How many players have played so far?   \n",
       "22  In which country were the least amounts of gam...   \n",
       "23             In which coutry is A.C. Milan playing?   \n",
       "25  List all clubs from Switzerland that were foun...   \n",
       "\n",
       "                                                query  label  \\\n",
       "1   select player.player_name\\r\\n from player join...  False   \n",
       "15  SELECT count(distinct p.player_id) from player...  False   \n",
       "22  select s.country, count(*)\\r\\n from stadium as...   True   \n",
       "23  select c.country from club as c where c.club_n...  False   \n",
       "25  select * from club as c where c.country = 'Swi...  False   \n",
       "\n",
       "             Similarity  value  \n",
       "1   $\\leq$ 25th %ile NL      1  \n",
       "15  $\\leq$ 25th %ile NL      1  \n",
       "22  $\\leq$ 25th %ile NL      1  \n",
       "23  $\\leq$ 25th %ile NL      1  \n",
       "25  $\\leq$ 25th %ile NL      1  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_similarity_melt = df_similarity.melt(\n",
    "    id_vars=[\"system\", \"db_id\", \"split\", \"id\", \"question\", \"query\", \"label\"],\n",
    "    value_vars=[\n",
    "                  # r'$0$ number_of_keywords', r'$1$ number_of_keywords', r'$\\geq 2$ number_of_keywords',\n",
    "                  # r'$0$ full_column_match', r'$1$ full_column_match', r'$\\geq 2$ full_column_match',\n",
    "                  # r'$0$ full_value_match', r'$1$ full_value_match', r'$\\geq 2$ full_value_match',\n",
    "                  # r'$0$ partial_column_match', r'$1$ partial_column_match', r'$\\geq 2$ partial_column_match',\n",
    "                  r'$\\leq$ 25th %ile NL', r'$\\geq$ 75th %ile NL',\n",
    "                  r'$\\leq$ 25th %ile SQL', r'$\\geq$ 75th %ile SQL',\n",
    "        \n",
    "                ],\n",
    "                var_name=\"Similarity\")\n",
    "df_similarity_melt = df_similarity_melt.drop(df_similarity_melt[df_similarity_melt.value == 0].index)\n",
    "df_similarity_melt.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "085cfa4d-d892-49c9-a55c-d02d59d3c660",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1100x900 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [\n",
    "  r'$\\leq$ 25th %ile NL', r'$\\geq$ 75th %ile NL',\n",
    "  r'$\\leq$ 25th %ile SQL', r'$\\geq$ 75th %ile SQL',\n",
    "]\n",
    "plot.plot_bars_vertical(df_similarity_melt[((df_similarity_melt[\"split\"]==300) | (df_similarity_melt[\"split\"]==30) | (df_similarity_melt[\"split\"]==8))],\n",
    "                x=\"Similarity\", hue=\"system\", system = \"\", order=order,\n",
    "               filename=\"nl-characteristic-300-all-data-models\", figsize=(11,9), rotation=0,\n",
    "                        hue_order= hue_order\n",
    "                       )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "862c1765-4808-44ba-a590-6cb16b11e676",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot.plot_bars_counts(df_similarity_melt[((df_similaritydata:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABFAAAAN1CAYAAABYQQ83AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdeVxU1f8/8NcwMzDsqyKbC+KuCFZKfQvNXTI1s8gdRHPFFjU1l7Q0lz6SCriluWS5pOSKpuFWuS9lmfsGCgIjsskMDDC/P/jNxDDDAApzIV7Px6NHeM+5577vnXsP8Obcc0RqtVoNIiIiIiIiIiIqlZnQARARERERERERVXdMoBARERERERERlYEJFCIiIiIiIiKiMjCBQkRERERERERUBiZQiIiIiIiIiIjKwAQKEREREREREVEZmEAhIiIiIiIiIioDEyhERERERERERGVgAoWIiIiIiIiIqAxMoBARERHVUN26dUOzZs20/505c+a525w2bZpOm5GRkZUQacXcuHEDwcHBaNasGWJiYkx+fCIiIkMkQgdARERE1ce4ceMQFxdnsMzc3Bx2dnZwc3ND27Zt0a1bNwQEBFRJHJpf2ocPHw47O7sqOUZJQ4cOxdmzZ3W2TZ06FSNGjCjX/snJyejWrRtyc3O12zw8PHDkyJFKjbO4bdu2oaCgAAMGDMCjR48qpc0ZM2Zg0qRJmD9/Pg4cOFApbZZXXl4eVq5ciW+++QYqlcqkxyYiIioLR6AQERGR1sKFC/Hbb79pkwb16tXDb7/9ht9++w2xsbGIjIxEUFAQTp8+jeHDh6Nv3764cuVKpccRFRWFqKgoZGZmVnrbpYmMjNQ5dwBYvXo1srOzy7V/dHS0NnnSq1cv/Pbbb9ixY0eVxKrh5OSEOnXqQCwWV1qbtra2qFOnDmQyWaW1WR7x8fHo168ffvzxR3z11Vfw8PAw6fGJiIjKwgQKERERadnZ2aFOnTqwsrICAIjFYtSpUwd16tSBl5cX2rVrhxEjRmDfvn2YNGkSrl+/juDgYBw9elTgyJ+fg4OD9tytra0hlUqRnp6OtWvXlrlvfHw8YmJi4ODgAACQyWSoU6cOnJycqjjq/46bN2+iXbt2iI2NRa9evYQOh4iISA8TKERERFRhIpEI77//PkaPHg2VSoUPP/wQ9+/fFzqsSuPg4IDg4GAAwMaNG/H48WOj9ZcvX45XXnkFTZs2NUV4/0mdOnXCvHnzTPbKFhERUUVxDhQiIiJ6ZuPGjcOOHTsgl8sRERGBZcuWactUKhV+/fVXHD58GH/99ReSkpKQn58Pd3d3dOzYEaNGjYKzs7NOeyXnIenSpYtOeVxcHDw9PaFWq3H69GkcPnwYFy5cQFJSEhQKBVxdXfHKK69g1KhR8PLyeq5zGzt2LGJiYpCTk4OVK1di5syZBuvduHEDsbGx2LFjBxYsWFBmu+np6Vi/fj2OHDmChIQEAICXlxc6d+6M0NBQ7SiWkq5cuYLo6GhcuHABCoUCHh4eePPNNzFy5Mgyj5mWloZ169bhyJEjePjwIcRiMRo0aICuXbti+PDhsLW1LbONssTExGD69Ol62zdt2oQOHToA0P9827dvj++++w4AKvU1JCIioqrABAoRERE9MwsLC/To0QPff/89jhw5AoVCAUtLSwDA3bt3MXbsWDRv3hwff/wxmjRpAqVSiYsXLyIyMhL79+/Hli1b4OnpqW0vMjISKpUKr776KgDgxx9/hJubm7Zc80pMTk4OQkJC4OHhgcmTJ6N169ZQqVT4559/EBUVhX379mHTpk1o3br1M5+bi4sLhg0bhlWrVmHr1q0ICQnRiVVj2bJl6Nq1K1q2bFlmm9evX8eoUaOQkZGBiRMnahNER44cwbJly/DTTz9h7dq1eiNZ4uLi8MEHH8Dc3ByTJ0/Ga6+9BoVCgd27d2P8+PEoLCws9ZjXrl3DyJEjkZGRgQ8++ACBgYHIzc3FoUOHEB0djT179mDjxo061/lZBAUF4bXXXkNYWBiuX7+O999/H8OGDYO9vb22TmRkJO7du4fg4GCsXr0afn5+z3VMIiIiU+IrPERERPRcfH19ARStoFJ8QlmpVApPT0+sWbMGnTt3hpeXF5o0aYLg4GB8/fXXSElJwaJFi3Ta0sxDoqGZJFXzn2aUgpmZGTw8PLBs2TIEBQWhfv36aNy4Md58802sW7cOOTk5mD179nOf28iRI+Hg4ACVSoXly5frlV++fBlHjx7FxIkTy2xLoVBg7NixSE5Oxty5cxEWFoaGDRuiYcOGGDFiBObMmYPk5GSMHTsWCoVCu9/jx48xbdo0qFQqzJ8/H4MGDYKXlxeaNm2KKVOmwN3dHUlJSQaPmZOTg7FjxyI1NRVz587FyJEj0bRpU7Rp0waTJk3CuHHjcP/+fUybNu3ZL9L/p5n3ZeDAgQCAgwcPwsXFBebm5to6Dg4OOHr0KBo3boxOnTqVOtqGiIioOmIChYiIiJ5L8YlS5XK59utGjRohLi4Orq6uevu0a9cOAHD8+PFnWq7W0tISR44cQZs2bfTKPD094erqiitXrjz30r62trYYNWoUAGDv3r24efOmTvnSpUvxxhtvwMfHp8y2du7ciYcPH6JOnTro06ePXnnfvn1Rp04dPHjwADt37tRu37FjBzIzM+Hq6oqePXvq7RcSEmL0mImJiahTpw769eunVz548GAAwOnTp3Ht2rUyz6E8+vTpA2tra8THx+P333/XKcvPz8fOnTu188sQERHVJEygEBER0XNRq9WlliUlJWHhwoXo168fAgIC4O/vD39/f7z44osAgNzcXKSlpT3TcdPT07F8+XK88847eOWVV7Rt+/v7Izk5GQCQmJj4TG0XN2TIENStWxeFhYWIiIjQbj979izOnDmD8PDwcrVz7NgxAEUjdszM9H8EMzMz0yaETpw4od1++vRpAECbNm0gEon09mvYsCGkUqnBYx4/ftzoMZ2cnGBjYwMAOHfuXLnOoyzW1tbaBNHWrVt1yuLi4pCZmWkwmUNERFTdcQ4UIiIiei7FEyAuLi7ar//880+MGDECT58+xaBBg9CjRw+4urpqkwDdu3cHgGcagRIfH4/BgwcjJSUFQUFB+Oijj1CvXj3tKz5Dhw5FcnLyM7Vdkkwmw/jx4/HZZ5/hyJEjuHTpEvz9/REREYH+/fujfv365WpHk8wpfo1K0pQ9fPhQu00ziqbkhLsaIpEILi4uBl/j0RzzxIkT8Pf3N7i/5nUhTdKpMgwaNAhbtmzB0aNHkZycrB2FtG3bNvTq1UtnXhQiIqKaQtAESlRUFMLCwrSTzREREVHNc/nyZQBFE8q2atVKu33WrFnIzs7GgAEDKmU+kuIWLFiAlJQUvPzyy/j666/1yiWSyv0RZ8CAAfj2229x//59REREICwsDFeuXDF47OqoR48eZc7TUhkr8Wg0bdoUL7zwAi5cuIAff/wREyZMQHx8PE6ePIkffvih0o5DRERkSoK+whMdHY2MjAwhQyAiIqLnkJubi59//hlA0ZLDmj+KPHnyBNevXwcABAYGVvpxNa+1VEXbhkgkEnzwwQcAil7d+fTTTxEcHFyhlWvc3d0B6M4TU5KmzMPDQ7utXr16AIomkzVErVaX2qbmmCqVCg0aNDD6X/G5bCqDZjLZHTt2oKCgANu3b0eTJk20898QERHVNIImUNRqNd58803MmzcPt2/fFjIUIiIiegYrVqzA48ePYWlpiY8//li73di8KADKnNzV0FwfaWlpyM7OLrP9goICpKamGm3/WQQFBaFFixYAila3GTNmTIX279ixI4CiV5sMLTtcWFioHc1TPDH08ssvAyga6WPovO/du1fqq0rFj1naNdu7dy/69u1baZPIavTo0QNOTk5ISkrCL7/8gpiYGE4eS0RENZrgk8iOHz8ef//9N3r37o2hQ4ciNjYW+fn5QodFRERERqjVaqxevRqrV6+GVCrFsmXL4OXlpS13cnLSzg1y9OhRvf337dtntH3NHBk5OTnabd26dcPKlSsBAH5+fqW2fejQIeTl5VXshMpBJBJh2rRp6NKlCyZPnmx0LhND3n77bXh4eEAul2P37t165bt374ZcLoeHhwfefvtt7fYBAwbAzs4OKSkpOHjwoN5+GzZsKPOYjx49MnjM7OxsREVFIT8/H82bN6/Q+ZTF3NwcAwYMAADMnj0bOTk56Nu3b6Ueg4iIyJQEn0T2zTffREhICK5du4Zt27Zh9uzZmD9/PgYMGIB3331XZwgrERERVa3MzEzk5uZqExfFR3MolUo8fvwYly5dwo4dO3Dr1i20aNECX375JVq2bKnX1rRp0zBhwgTs2rUL9vb26Nu3L8zNzREXF4c1a9Zo66WlpcHCwgJ16tTRbuvQoQN+/vlnxMTEYPDgwTh06BCys7PxyiuvAAAmTZqEIUOG4OzZs5gyZQqGDh0KW1tbnDp1CkuXLoVEIkF+fj4yMjKQmpoKJycn7QSzpcnKyoJSqUROTo7OeRffNyAgAAEBAXr7pqWloaCgQDsSRKlUIjU1FVKpFA4ODgAAKysrrFy5EiNHjsScOXOQlpaGLl26AACOHDmCZcuWwdXVFatWrdKZH87JyQlfffUVJkyYgBkzZiA9PR2vvvoqlEoldu3ahYsXL8LZ2RmPHz/Wnq+9vT3Mzc21xxw1ahRmzZqFxMREdOvWDTKZDNeuXUNUVBSysrLw3Xff6V0HpVIJoCiJlZqaCisrK1hbWxu9hiUFBwdj7dq1SE9PR//+/cucZ0VzHQFo/5+VlaX9LGxtbSGTySoUAxERUWURqcsaY2tiCoUCe/fuxbZt23D16lW8+uqrGDRoEDp27GhwOC8RERFVnnHjxiEuLs5gmVQqha2tLdzd3eHn54euXbtqXy8pzfnz57Fy5Ur8+eefUCgUcHJywksvvYTRo0drl7rV0MyZAgCpqan4/PPPcfr0aSiVSnh4eGDo0KEYPHiwTv2oqCicPXsWWVlZsLe3R9u2bTFy5Eh88sknOivZxMXFwdPT02is06ZNw08//aS3vTz7du7cWed4Gu3bt9dJTgBF88Ns2LABcXFxSEhIAAB4eXmhS5cuCAkJgaOjo8Fj/PPPP4iKisL58+eRk5MDV1dXdO7cGePHj0f//v11jr9+/XptsgkoWvJZc8z4+HhIJBK4u7ujU6dOGDZsmE7yqrTrMGHChHIv2Vzc+++/j+PHj2P79u1o27at0bqlXUeNBQsWoH///hWOgYiIqDJUuwRKccePH8fkyZORnZ0NNzc3vPvuuxgwYECFh8wSERERERERET0PwedAMeTs2bP4+OOPMWHCBGRnZ0OtViM7Oxu7du1Cp06dMGnSpGeedLagoAAbNmxAu3bt0Llz5zLrX7lyBRMmTEBAQAB8fX3Ru3dvrFmzptTJ2oCime7XrFmD3r17w9fXFwEBARg/fjyuXLlisH5OTg5mz56NDh06wNfXF0OHDi21LlA0b0zXrl2hUCjKPmEiIiIiIiIiem6CJlBatGihXZIvKysLmzZtwhtvvIHhw4cjNjYWKpUKrVq1wvz583HixAkcPHgQ69evR0FBAfr371/qEOPSXLhwAW+99RZWrlyJp0+flln/2LFjCA4ORlZWFrZs2YLTp08jJCQEy5cvR1hYmMEJ6vLy8hAWFobly5cjJCQEp0+fxpYtW5CVlYXg4GAcO3ZMb59Zs2bh8OHDWLVqFY4ePQobGxuEhobiyZMnenVjY2Pxyy+/4IsvvtB5P5qIiIiIiIiIqo6gr/A0b94cq1atwuHDhxEbGwulUgm1Wg1LS0u88cYbGDhwIFq1amVw35iYGKxbtw779+8v17H279+PmTNnYty4cWjZsiVGjBgBDw8PHDlyxGD9J0+eoEePHgCAw4cPa1cDAIDIyEhERUVh/PjxmDhxos5+y5Ytw4oVKxAeHo4JEyZot6enp6N79+4AilYH0Ewol5CQgG7duiE8PBzjx48HADx8+BCdO3c22EZQUBA6d+6MefPmleu8iYiIiIiIiOj5Cf4Kz9ixY7Fz504oFAp4e3tjxowZOHHiBObNm1dq8gQAXnrpJe3Ea+Xh4eGB2NhYjBo1ChJJ2YsPbd26FRkZGejVq5dO8gQomlEeADZu3Ijc3Fzt9tzcXGzcuFGnjoaDgwN69uyJjIwMbN26Vbv91q1bUKvVaNGihU6s9vb2uHHjhk4bX375JcRiMaZOnVrOsyYiIiIiIiKiyiB4AkUsFqNXr17YtGkT9u/fr12G0Jhr165h0aJFsLKyKvdx/Pz84ObmVu76mteDXnjhBb2yunXron79+sjOzsbp06e120+fPo2nT5+iQYMGOrPZa2jaKv7qkWaJvpIrDIlEIm0ZAJw4cQK7d+/GZ599Vub1ISIiIiIiIqLKVfZQjCq2Z88eeHt7V2ifs2fPIikpCV26dKmSmAoKCrSjP7y8vAzW8fLyQnx8PK5du4aOHTsCAK5evVrmPgBw48YNFBYWwszMTHvu169fx+uvvw4ASElJQXp6Oho3bgwAePr0KT777DMEBQWha9eulXSWRRwcHJCbm1uh5BIRERERERGR0JKSkmBhYYH09HSTHE/QBMpbb72FunXrVni/YcOGYdiwYVUQUZHMzEztqzklX9/RsLOzAwCkpqZqt2m+Lm0fzXalUonMzEw4ODjA29sbgYGB2Lx5M7p16wYvLy8sWbIEMpkMAwcOBAAsWbIEOTk5mDVrVuWcYDG5ublQqVR6E+KamZlBIpFArVYbXHHI3NwcQNGKQyWn0ZFIJDAzM0NBQYHOKBqgaGSNVCoFAIOT8BprVywWQywWo7CwEPn5+RVqVyqVQiQSIT8/H4WFhQbbLetcjbVr6Fxr4zU01G7xmCrablVdw8po15TX8HnaLe+5Gmq3qq9hTbu/2Uewj6hIu+wjat/9zT6CfURF2mUfUfvub/YRVXN/G1sdtyoImkBZsGCB0fKEhIRSR3NUJaVSqf1a8yGXpLlxii8lrPm6rH1KHmPhwoWYPn06evfuDbFYjHr16mH58uVwc3PD+fPn8cMPP2Dx4sVwcnJCcnIyIiIicPbsWUgkEgQGBuKjjz6CjY3NM52rZuTJ33//rbNdLBbDwsIChYWFOrFqaF6fUiqVeje4ubk5JBIJVCqV3g1tZmYGmUwGtVptcBlmS0tLiEQi5Obm6j3MUqkUUqkU+fn5eg+dSCTSrkqUk5Oj165MJoOZmZnBdiUSCczNzVFQUKAzp03JdhUKhV4nYWFhAbFYjLy8PL2HubzX0FC7xq6hpt2yrqGhz8bYNdR8NkDFr6Gm3bKuoaF2jV1DzWdTVdewtHaNXUNNu8auYWmfTXmu4fPc38auoaHPBjB+DTWfzbNcQ/YRRdhH6LbLPoJ9RMl22UewjyjeLvsI9hEl22UfwT6ieLuGrmGrVq30psOoSoImUBISEjBgwACo1WrY2NjorYgze/ZsyOVyREREoEmTJiaLS/PBAqVntDQ3RPGlhDVfl7VPyWM4OztjzZo1yMnJgVKphJOTE4Ci0SEzZ85EYGAg+vTpA5VKhdDQUIhEIkREREChUOCTTz7BvXv3sG7dumc82yKlzSdjZmZmdK6Z4udRkuZGN0QkEhlt18LCotQyiURidCLgZ21XLBYb3dfYstHm5uY6CbLiyrqGxtp9nmto7LMR6hoaKxPiGj7P/W3sGgp1fxu7hs9zf1fVNWQfUYR9RPnaZR9RdrsA+wgN9hFF2EcUYR/xL/YRRdhHFPkv9BGmTJ4AAk8iu3fvXmRkZKBBgwYYO3asXvnbb7+NgoICDB48GImJiSaLy87OTvvBZWRkGKyTmZkJADqTxWq+Lm0fzXaZTKZ9Bag4KysrbfIEAKKiopCSkoK5c+cCKFqK+fbt25gxYwb8/f3xyiuvIDw8HL/99hvOnz9f0dMkIiIiIiIionISNIFy6tQpBAYGYuvWrXjnnXf0ynv37o2YmBg0bdoUa9asMVlcYrEYTZs2BYBSl0rWbG/evLl2m2Yp4rL2adq0KczMjF/6f/75B99++y2mTJmifc3m+vXrAABfX19tvbZt2+qUEREREREREVHlEzSBcuvWLYSFhUEsFpdaRyaTYcyYMTrLBZuCZrWbixcv6pWlpqYiPj4eNjY2CAgI0G4PCAiAtbU14uPjIZfL9fbTtFXWSjr5+fmYMWMG2rVrh/fee0+7XfMuWPHki+balXxPjIiIiIiIiIgqj6AJlKysrHJNEtuoUSMkJSWZIKJ/BQcHw97eHgcOHNC+rqOxbds2AMDw4cN13tGysLDA8OHDoVartXU0MjMzcfDgQdjb2yM4ONjosdetW4c7d+7giy++0HmnSzMPTPHRJteuXdMpIyIiIiIiIqLKJ2gCxdra2uBIjZIeP35sdJKaquDo6IhFixYhOzsbEydOxL1796BQKBATE4PVq1ejffv2GDNmjN5+Y8eORfv27bFq1SrExMRAoVDg3r17mDhxIrKzs7Fo0SI4ODiUety7d+8iOjoa4eHhaNiwoU7Zm2++CTc3NyxevBhJSUm4e/cuVqxYAT8/P52RMERERERERERUuUTqkmsamVBYWBhsbW2xdOlSo/U+/PBDZGZm4ttvv32u4zVr1qzUsgkTJiA8PFxv+5UrVxAdHY0LFy4gJycHXl5e6Nu3L0JDQ0udCTkvLw8bNmzArl27kJCQACsrK7zwwgsYP348WrVqVWoMarUagwcPRm5uLrZv327w1aY7d+7gyy+/xPnz52FmZobAwEDMmDFDZzLbivD29ta2S0RERERERFRTmPr3WUETKPv378ekSZPw6quvIiQkBH5+frCxsQEAZGdn448//sD69etx8uRJLFmyBEFBQUKF+p/FBAoRERERERHVRKb+fbb0xZlN4I033sDPP/+MQ4cO4ffffwcA7TrUKpUKQNGojO7duzN5QkRERERERESCEXQOFACIiIjAiBEjIJVKoVarkZeXh7y8PKjVakilUoSFhSEiIkLoMImIiIiIiIioFhP0FZ7injx5glOnTiExMREA4O7ujpdffhmOjo4CR/bfxld4iIiIiIiIqCaqVa/wFOfo6MjXdIiIiIiIiIioWhL8FZ7yyMjIwLBhw4QOg4iIiIiIiIhqqRqRQFGpVDh37pzQYRARERERERFRLSX4Kzz5+fnYtm0b4uLikJiYqF19p7jCwkIBIiMiIiIiIiIiKiJoAiU/Px9hYWE4c+ZMmXVFIpEJIiIiIiIiIiIi0idoAmXz5s24cOECwsPD0a5dO4wZMwbz5s2Dq6srAODRo0fYt28fzpw5g6+++krIUImIiIiIiIioFhM0gbJ//36MHj0a48ePBwCYmZnBz88PXl5e2jp9+vTB9OnTcfHiRXTv3l2oUImIiIiIiIioFhN0Etk7d+6gS5cuZdYbNGgQjh07VvUBEREREREREREZIPgcKI6Ojtp/S6VSPHnyRGcECgDY2NggKSnJ1OERVVsJCQnYtm0bjh8/DrVajfz8fHh6emLMmDF48cUXtfUiIyOxc+dO2Nvb6+xvZ2eH7777ztRhE9VafGaJapbExERs3boVv//+OwoLC5GbmwuJRIIBAwZg6NCh2rn5Tpw4gb179+LatWsQi8VQKBRo0KABxo0bBz8/P2FPgqgWKe/3WT6z9LwETaDUq1cPjx49gpubGwDAyckJFy5cgK+vr069kydPwsysRqy4TGQSc+bMQVpaGtauXQtXV1eoVCrMmzcPQ4YMQVRUFLp27aqtO3HiRPTv31/AaImIzyxRzXL69Gl89913+Pbbb+Hv7w8AOHToECZOnIinT59i7NixAIBvvvkGYrEY33//Pezs7JCbm4vp06cjNDQUMTExaNSokZCnQVRrlPf7LJ9Zel6CZiUaN26MjRs3av/t6+uLFStWYN++fcjIyEBGRgZ27dqFpUuXonHjxgJGSlT9jBs3TjvhslQqxfTp0yEWi7F+/XqBIyMiQ/jMEtUcLi4uCAsL0yZPAKB79+5o2rQpDh06pN3WvHlzfPTRR7CzswMAWFhYYOTIkcjJycGvv/5q8riJarPyfJ/lM0vPS9ARKJ07d8bMmTMRGhqK9evXY9CgQdi7dy+mTJmiV3fQoEECREhUPa1atQoSie7jK5PJYG9vj8zMTIGiIqLS8JklqlkCAwMRGBiot/3p06do2LCh9t8zZswwWAcoGllNRKZR3u+zfGbpeQmaQOnevTtyc3NhbW0NAPDz88PMmTOxcOFCqFQqAEUr84SGhnI4M1ExUqlUb1t6ejrS0tIQFBSks/3XX3/Fnj17kJaWBrVajQ4dOuD9999H3bp1TRUuUa3HZ5aoZsvOzsaaNWugUCgwadKkUuvdvn0bixYtQmBgIHr27GnCCIlqt4p8ny2OzyxVlKAJFDs7OwwePFhn2+DBg9GzZ09cuHABhYWF8PX1hbu7u0AREtUcW7duhaOjI0aPHq3dJpPJIBKJsGTJEjg7OyMhIQEff/wx+vfvjx07dqBevXoCRkxUu/GZJaoZgoKCcO/ePXh7eyMyMhItW7bUqxMXF4e5c+ciJSUFb731FqZNm6b313AiMi1D32c1+MzSsxKp1Wq1UAePiooCAFhbWyM0NFSoMGo1b29vAEVLSlPNdeXKFYSEhCAyMhIBAQFG6968eRO9e/dGcHAwPv/8cxNFSETF8Zklqlny8vKwZ88ezJkzBx9++CFGjhxpsF5KSgrmzZuHS5cuYe3atWjWrJmJIyUioPzfZ/nM1nym/n1W0Elko6KiEB0djRMnTggZBlGNdvv2bYwfPx6LFy8u8xcxAGjSpAlsbGxw6dIlE0RHRCXxmSWqeczNzTFgwAD069cPERERiI+PN1ivbt26WLRoERQKBebNm2fiKIkIqNj3WT6zVFGCrw38+eefcwUComd09epVjBo1CvPnz8frr7+uV56ammpwPzMzMxQWFlZ1eERUAp9ZoppBqVSioKBAb3uLFi1QUFCAK1euQK1WQ6FQ6NWxtLREgwYN8Ndff5kiVCIqxtj3WT6zVBkETaDY29vj//7v/4QMgajG+vPPPzFu3DgsXrxY5zkqPuHyq6++iuTkZJ394uPjkZmZiTZt2pgsViLiM0tUk4waNQoHDhzQ2/7gwQMAgKOjIx4+fIiAgAC9REtBQQGSk5Ph6OhokliJqEhZ32f5zFJlEDSB0rp1azx8+LDMetnZ2Zg+fboJIiKqGc6dO4fQ0FB06dIFDx8+xO7du7X/XblyRaduREQElEolACArKwtz5syBra2twQm1iKhq8JklqnlWr16tTZgAwNmzZ7F161b4+vripZdeAlA0UuV///sf8vLyABTNlfLVV18hNTUVI0aMECRuotqovN9n+czS8xJ0EtkzZ84gKioK69atg7m5ean15HI5XnvtNVy9etWE0dUOnES2Znrrrbfwzz//lFp+/fp1AMC+ffsQGxuL+/fvQyQSISsrC+3atUN4eLj2syeiqsdnlqhmuXjxImJiYnDp0iWYmZlBoVBAKpWia9euGD16NGxsbJCXl4fdu3fj4MGDSEpKglgsRkZGBho0aIBBgwahV69eQp8GUa1Rnu+zfGb/m0z9+6ygCZRz587h559/xqFDhxAcHAxvb284OztDJBLp1EtPT8fEiROZQKkCTKAQERERERFRTWTq32cFXex66NChEIlEUKvV2iWNiYiIiIiIiIiqG0ETKADg6uoKMzPjU7EUFhbqTapHRERERERERGQqgiZQRCIRdu7cCWdnZ6P1UlNTERgYaKKoiIiIiIiIiIh0CboKj5eXF8RicZn1zM3N8eKLL5ogIiIiIiIiIiIifYJOIkvC4ySyREREREREVBOZ+vdZQUeglFdeXh727t0rdBhEREREREREVEvViARKZmYmPvnkE6HDICIiIiIiIqJaStBJZHft2lWuellZWVUbCBERERERERGREYImUKZNmwaRSCRkCEREREREREREZRI0gQIAbdu2hVQq1duelpaGxMREKBQK+Pn5GaxDRERERERERGQKgidQoqOj4ezsbLBMM3nsvn37EB0dbeLIiIiIiIiIiIiKCJpACQ4OhkwmK7Xc3Nwcb7/9NkQiEZYvX45p06aZLLYzZ85g2LBh5ap7/fp17dfNmjUzWvebb75BYGCgzra//voLCxcuxOXLl2FjY4OePXvik08+gaWlpd7+SUlJeOONNzBo0CBMnjy5XPERERERERER0fMRNIEyd+7cctXr0KEDIiMjTZpA0WjUqFGpZQ8ePED9+vX1tnt5eUEiMXxpraysdP6dlpaG0NBQtG/fHseOHUN8fDzGjh2Lp0+fYvHixXr7f/bZZ6hTpw7Cw8MreCZERERERERE9KwEf4WnPORyOeRyuSDHPnjwoMHtCQkJ6N69u8FRKhs2bICnp2e52v/++++RlZWFWbNmwdnZGc7OzhgyZAiioqIwceJEnXZ2796NEydOYPPmzbCwsHi2EyIiIiIiIiKiCjMTOoCyZGVlYdmyZXBxcTHpcZ2dnREUFFRq+XfffQc7Ozv069fvuY5z8+ZNODg4wM3NTbutRYsWUKvVuHXrlnZbWloavvzySwwcOBAvvvjicx2TiIiIiIiIiCpG0BEoxuYYKSwsREZGBu7evYuCggKEhISYLjAAPj4++Prrrw2WZWdnY+fOnRg0aJDROVzKo6CgQG+bmVlRXis/P1+77YsvvoCVlRUmTZr0XMcjIiIiIiIioooTNIFy9uzZMuuIRCL06NEDH374YdUHVE47duyAUqnEkCFDDJb/+OOP+PXXXxEfH4+8vDy4u7sjMDAQYWFhcHV11anr7e2NX375BcnJydqymzdvassA4MiRI4iNjcWaNWtgY2NTJeeUk5Oj82+xWAwLCwsUFhZCqVTq1dfM5aJUKlFYWKhTZm5uDolEApVKBZVKpVNmZmYGmUwGtVoNhUKh166lpSVEIhFyc3P1kktSqRRSqRT5+fnIy8vTKROJRNpJd0ueCwDIZDKYmZkZbFcikcDc3BwFBQXIzc0ttV2FQgG1Wq1TbmFhAbFYjLy8PJ2EF1D+a2ioXWPXUNNuWdfQ0Gdj7BpqPhug4tdQ025Z19BQu8auoeazqaprWFq7xq6hpl1j17C0z6Y81/B57m9j19DQZwMYv4aaz+ZZriH7iCLsI3TbZR/BPqJku+wj2EcUb5d9BPuIku2yj2AfUbxdQ9dQrVZDJBLptVdVBJ8D5dNPP4Wtra3edjMzM9jZ2aFly5Z6SQchFRYWYvPmzejRo0epcZ05cwaffvopWrduDaVSibi4OMyfPx+7d+/GN998A19fX23dgQMHYuPGjVi0aBEWLFiAR48eYfPmzejUqRO8vb2RlZWFOXPmoG/fvujYsWOVnFNBQQGuXr2qs83JyQmNGjVCXl6eXhkAvPDCCwCAe/fu4enTpzplDRs2hLOzM548eYKEhASdMjs7OzRp0gSFhYUG2/X19YVUKkVCQgIyMjJ0yjw9PeHq6oqsrCzcuXNHp8zS0hItW7YEAFy7dk2vk2jZsiUsLS2RlJSEx48f65TVq1cPHh4eyMnJwY0bN3TKpFKp9vO6efOmXgfTtGlT2NraIjU1FY8ePdIpc3Z2RsOGDZGbm6t3riKRCO3atQMA3L17V69z8vb2hqOjI9LS0vDgwQOdMnt7e/j4+CA/P9/gNfTz84NYLEZCQgIyMzN1yry8vFC3bl1kZGTg3r17OmXW1tZo3rw5ABhst1WrVpDJZEhMTERaWppOmZubG9zd3ZGdna3z6hlQ1PG3bt0aQNE1LNn5N2vWDDY2NkhOTkZKSopOWZ06dVC/fn0olUq9mMzMzODv7w8AuHPnjt43jsaNG8PBwQFyuRyJiYk6ZQ4ODmjcuHGp19Df3x8ikQj3799Hdna2TlmDBg3g4uKC9PR03L9/X6fMxsYGzZo1g1qtNthumzZtYG5ujgcPHiA9PV2nzN3dHW5ubsjOzsbt27d1ymQyGVq1agWgaNWvkt+sWrRoASsrKzx69Aipqak6ZXXr1oWXlxcUCoXOimFA0Tf0tm3bAgBu376t9w3Jx8cH9vb2SE1NRVJSkk4Z+4gi7CP+xT6iCPuIIuwjirCP+Bf7iCLsI4qwjyjCPuJfz9pHqFQqmJub67VXVUTqkp++CTVv3hy///47nJ2dhQqhwg4fPowJEyZg+/bt2g6juGPHjuGVV17R+xB37tyJTz/9FB4eHjh48KBO+fHjxzF37lykpKSgsLAQr732Gr788ks4Oztj1qxZOHLkCPbv3w8HBwccO3YMa9asQXx8PFxdXTF06NDnmodFM8rl77//1tnOrLB+u8wK8y9HxdvlX47YR5Rsl30E+4ji7bKPYB9Rsl32EewjirfLPoJ9RMl22Uc8Wx/RqlUriEQivaRXVRE0gXLq1Cm89NJLpS75Wx0NGTIEKpUK27Ztq9B+BQUFaN++PbKzs7F69Wp06tRJr05aWhosLS21D9Hp06cxfPhwLF26FL169cL58+cxZMgQDBkyBO+++y7i4uKwdOlSLFmyBL17936m89EkUEx1wxERERERERFVBlP/PivoKjwvv/xyjUqeXLlyBefOncPw4cMrvK9YLNYuSVxy2JGGk5OTTgZy1qxZ6Nq1K3r16gUAiIyMhJubGz799FM0bdoUY8eOhb+/P5YtW/aMZ0RERERERERE5SFoAiUrKwvh4eGYMGECpkyZolceHh6OefPm6b33JpSNGzfCzc0N3bt3f6b9NYN9yjPJzbJly5Ceno7PPvtMu+3atWto1aqVdpUeoOg9vvj4eIPDoIiIiIiIiIiocgiaQNm3bx8OHz6MU6dOGRyJ0qBBA2zbtg1Dhw4VPEGQkpKC2NhYDBo0qNRRM/PmzcMnn3xisKygoEA7QU/jxo2NHuvy5cvYtGkTpk6dirp162q3FxYW6iRPgKKRLZoyIiIiIiIiIqoagiZQfv31VzRu3BixsbFYsGCBXvnkyZOxZ88epKenY/PmzQJE+K8ffvgBEokEwcHBpdbJzs7Gr7/+iqysLL2ymJgYPH36FO7u7njllVdKbUOlUmHGjBkICAjAgAEDdMp8fHz0Zm6+fv063Nzcqmx5YyIiIiIiIiISOIFy9epVTJw40egyxY0aNcKHH36I2NhYE0amKzc3F1u3bkXfvn1hb29faj2RSIS0tDS8//77uHDhAp4+fYqMjAzs2LEDX375Jezs7PD1118bXWZp9erVePDgAT7//HO9stGjR+Pu3btYs2YNsrKysGfPHpw8eRKjR4+ulPMkIiIiIiIiIsMEncFVLpejRYsWZdZr27at3vrUpqQZBTNs2DCj9TQjRw4dOoSPP/4Yjx8/1k4e++677yI0NBT16tUrdf+bN29i1apVmDJlinbC2eI6deqEBQsWYM2aNVi+fDnq1q2LKVOmYODAgc99jkRERERERERUOkGXMX7hhRewffv2MucEuX37Nt555x1cvHjRRJHVHlzGmIiIiIiIiGqiWrWMcaNGjbB///4y6+3fvx+NGjUyQURERERERERERPoETaD06NEDq1evxurVqw0uVfz06VOsXLkSa9asQa9evQSIkIiIiIiIiIhI4Fd4FAoFBgwYgDt37kAqlcLHxwdOTk4AgMePH+P27dtQqVTw8fHBjz/+CJlMJlSo/1l8hYeIiIiIiIhqIlP/PivoJLKWlpb49ttvER4ejsuXL+Off/7Rq+Pr64vIyEgmT4iIiIiIiIhIMIImUADA1dUV27dvx7Fjx3Ds2DEkJiYCANzd3dGxY0e8/vrrAkdIRERERERERLWd4AkUjU6dOqFTp05Ch0FEREREREREpEfQSWSJiIiIiIiIiGoCQUegZGVl4dNPP4VarYalpSW++uornfLw8HC4urrio48+grW1tUBREhEREREREVFtJ+gIlH379uHw4cM4deoUJBL9XE6DBg2wbds2DB06FDk5OQJESEREREREREQkcALl119/RePGjREbG4sFCxbolU+ePBl79uxBeno6Nm/eLECEREREREREREQCJ1CuXr2KiRMnwtXVtdQ6jRo1wocffojY2FgTRkZERERERERE9C9BEyhyuRwtWrQos17btm3x4MEDE0RERERERERERKRP0ASKubk5VCpVmfXy8/NRWFhogoiIiIiIiIiIiPQJmkBp1KgR9u/fX2a9/fv3o1GjRiaIiIiIiIiIiIhIn6AJlB49emD16tVYvXo1nj59qlf+9OlTrFy5EmvWrEGvXr0EiJCIiIiIiIiICBCp1Wq1UAdXKBQYMGAA7ty5A6lUCh8fHzg5OQEAHj9+jNu3b0OlUsHHxwc//vgjZDKZUKH+Z3l7ewMA7ty5I3AkREREREREROVn6t9nJSY5SiksLS3x7bffIjw8HJcvX8Y///yjV8fX1xeRkZFMnhARERERERGRYARNoACAq6srtm/fjmPHjuHYsWNITEwEALi7u6Njx454/fXXBY6QiIiIiIiIiGo7wRMoGp06dUKnTp0MluXm5uLAgQPo16+fSWMiIiIiIiIi4cTHx0Mulwsdhh4XFxfUr19f6DDIxKpNAsWYrKwsTJ8+nQkUIiIiIiKiWiI+Ph4tWrRATk6O0KHosbKywtWrV5lEqWWqfQLl0aNH2Lhxo9BhEBERERERkQnJ5XLk5ORg0qRJ8PT0FDocrQcPHmDJkiWQy+VMoNQy1TaB8uuvv2LLli04fvw4CgsLhQ6HiIiIiIiIBODp6QkfHx+hwyCqXgmU9PR07Ny5E9u2bUNCQgIAQLPKskgkEjI0IiIiIiIiIqrFqkUC5dKlS9iyZQt+/vln5OXlaZMm7u7u6NevH1577TUMGjRI4CiJiIiIiIiIqLYSLIGiUCiwZ88ebNmyBdevXwdQNNpEIpGgsLAQ//vf/9CrVy+IRCKkpaXBzc1NqFCJiIiIiIiIqJYzeQLl5s2b2LJlC/bs2YOnT59qR5u4urrivffew4ABA9C9e3e0adNG+9qOk5MTjhw5YupQiYiIiIiIiIgAmDiBMnjwYFy8eBHAv3ObBAQEYPDgwejcuTPEYrEpwyEiIiIiIiIiKheTJlAuXLgAkUgEGxsb9OvXDwMHDoS3t7cpQyAiIiIiIiIiqjAzUx5s6NChsLOzQ25uLrKysvD06VNTHp6IiIiIiIiI6JmYNIEyY8YMnDhxAnPnzsW9e/fwzjvvYMCAAfjpp5+Ql5dnylCIiIiIiIiIiMrNpAkUALCwsMBbb72FrVu3YteuXWjdujXmz5+P1157DV999RUSEhK0k8cSEREREREREVUHJk+gFNe8eXPMmTMHJ06cwKRJk3D69Gl0794dSqUSFy5cQGFhIQAgLS0NXbp0ETJUIiIiIiIiIqrFBE2gaFhZWeHdd9/Fzp07sX37drz11luYO3cuOnbsiP/973+4ceMGEhMThQ6TiIiIiIiIiGopk67CUx5t2rRBmzZtMH36dOzevRvbtm3D2rVr+VoPERERERERVRtXr14VOgQdLi4uqF+/vtBh/KdVuwSKho2NDQYPHozBgwfjxIkTGD16tNAhERERERERUS335MkTmJmZYciQIUKHosPKygpXr15lEqUKVdsESnGtW7eGm5ubyY8bGRmJqKioUsvbtm2L7du3621PSEjA8uXLcerUKWRkZKBevXro0aMHxo4dC2tra736f/31FxYuXIjLly/DxsYGPXv2xCeffAJLS0u9uklJSXjjjTcwaNAgTJ48+flOkIiIiIiIiCokOzsbhYWFiIqKgo+Pj9DhAABu3bqFCRMmQC6XM4FShWpEAsXJyQlHjhwR5Ng2NjaoU6eOwTIPDw+9bX///TeGDRsGT09PrFmzBt7e3vj9998xdepUHDt2DN9//z3s7e219dPS0hAaGor27dvj2LFjiI+Px9ixY/H06VMsXrxYr/3PPvsMderUQXh4eOWdJBEREREREVWIj48PfH19hQ6DTKhGJFCE1K1bNyxcuLBcdfPy8vDxxx8jNzcXUVFR2sxfly5d8Omnn2L69On48ssvsWjRIu0+33//PbKysjBr1iw4OzvD2dkZQ4YMQVRUFCZOnAhPT09t3d27d+PEiRPYvHkzLCwsKvdEiYiIiIiIiKhU1WIVnv+KgwcP4v79+3j55Zf1hk317t0bNjY22L17Nx49eqTdfvPmTTg4OOi8otSiRQuo1WrcunVLuy0tLQ1ffvklBg4ciBdffLHqT4aIiIiIiIiItJhAqURxcXEAgBdeeEGvzNzcHG3atIFardZ5HamgoECvrplZ0ceSn5+v3fbFF1/AysoKkyZNquywiYiIiIiIiKgMfIWnDA8ePMDkyZNx4cIFpKamwtraGq1atcI777yDXr166dS9du0aAMDLy8tgW15eXjh16pS2HgB4e3vjl19+QXJyMlxdXQEUjUrRlAHAkSNHEBsbizVr1sDGxqbSzxEAcnJydP4tFothYWGBwsJCKJVKvfpWVlYAAKVSicLCQp0yc3NzSCQSqFQqqFQqnTIzMzPIZDKo1WooFAq9di0tLSESiZCbm6uXXJJKpZBKpcjPz0deXp5OmUgk0k66W/JcAEAmk8HMzMxguxKJBObm5igoKEBubm6p7SoUCqjVap1yCwsLiMVi5OXl6SS8gPJfQ0PtGruGmnbLuoaGPhtj11Dz2QAVv4aadsu6hobaNXYNNZ9NVV3D0to1dg017Rq7hqV9NuW5hs9zfxu7hoY+G8D4NdR8Ns9yDdlHFGEfodsu+wj2ESXbZR/BPqJ4u+wj2EeUbNfQMck4hUKBnJycWtNHqNVqiEQiY5ekUjGBUoY///wTHTt2xJQpU+Do6Ii7d+/i66+/xocffohjx45h4cKF2g8sJSUFAHQmiS3Ozs5Opx4ADBw4EBs3bsSiRYuwYMECPHr0CJs3b0anTp3g7e2NrKwszJkzB3379kXHjh2r5BwLCgr01jB3cnJCo0aNkJeXZ3B9c80om3v37uHp06c6ZQ0bNoSzszOePHmChIQEnTI7Ozs0adIEhYWFBtv19fWFVCpFQkICMjIydMo8PT3h6uqKrKws3LlzR6fM0tISLVu2BFCUyCrZSbRs2RKWlpZISkrC48ePdcrq1asHDw8P5OTk4MaNGzplUqlUOzHUzZs39TqYpk2bwtbWFqmpqTqvZgGAs7MzGjZsiNzcXL1zFYlEaNeuHQDg7t27ep2Tt7c3HB0dkZaWhgcPHuiU2dvbw8fHB/n5+QavoZ+fH8RiMRISEpCZmalT5uXlhbp16yIjIwP37t3TKbO2tkbz5s0BGF7TvlWrVpDJZEhMTERaWppOmZubG9zd3ZGdna3z6hlQ9M2zdevWAIquYclvzM2aNYONjQ2Sk5N1ng0AqFOnDurXrw+lUqkXk5mZGfz9/QEAd+7c0fvm27hxYzg4OEAulyMxMVGnzMHBAY0bNy71Gvr7+0MkEuH+/fvIzs7WKWvQoAFcXFyQnp6O+/fv65TZ2NigWbNmUKvVBttt06YNzM3N8eDBA6Snp+uUubu7w83NDdnZ2bh9+7ZOmUwmQ6tWrQAA169f1/tm1aJFC1hZWeHRo0dITU3VKatbty68vLygUChw/fp1nTKJRIK2bdsCAG7fvq33DcnHxwf29vZITU1FUlKSThn7iCLsI/7FPqII+4gi7COKsI/4F/uIIuwjipS3jyh57als9+7dg6WlZa3pI1QqFczNzY1ckcolUpf8DkFad+/ehUqlQtOmTXW2q1QqBAUFIT4+HnPnzsV7770HoKjzKSwsxMaNGxEQEKDX3rJly7BixQq8/PLL2LBhg3b78ePHMXfuXKSkpKCwsBCvvfYavvzySzg7O2PWrFk4cuQI9u/fDwcHBxw7dgxr1qxBfHw8XF1dMXToUPTr1++Zz1EzyuXvv//W2c6/HOm3y78c8S9HxdvlX47YR5Rsl30E+4ji7bKPYB9Rsl32EewjirfLPqJ89/epU6fwyiuv4Ouvv642ywUDwNGjRxEREYGDBw9Wm1V4Ll++jJ49e+K3336Dv79/rekjWrVqBZFIpJcYryo1YgSKSqXCH3/8gZdeesmkx23UqJHB7VKpFO+99x4WL16MH3/8UZtAkclkyMnJ0bsJNTQ3kebG0ejYsSOOHDmCtLQ0WFpaaju406dPY/v27Vi6dCkcHBxw/vx5jBkzBkOGDMGcOXMQFxeHqVOnQiKRoHfv3s91rpoHrCQzM7NSywydS3GaG90QkUhktF1jqwxJJBJIJKXfus/arlgsNrqv5nMxxNzcvNTMZ1nX0Fi7z3MNjX02Ql1DY2VCXMPnub+NXUOh7m9j1/B57u+quobsI4qwjyhfu+wjym4XYB+hwT6iCPuIIuwj/lXT+giuPFpxlpaWOtf0v95HmPL1HaCGTCKbkZGBYcOGCR2GjgYNGgCAzhC5unXrAoDekFENzRAnTb2SnJycdP5KMWvWLHTt2lU710pkZCTc3Nzw6aefomnTphg7diz8/f2xbNmyyjkpIiIiIiIiIjKoWoxAuXz5Mv7++29kZGQYXJXG0BAfoWmGQRXPeDVv3hz37t3Te19XQ7Nd8+6XMcuWLUN6ejo+++wz7bZr167hpZde0q7SAxS967tx40adiYKIiIiIiIgqIj4+HnK5XOgwdBiaK4NISIImUNLT0zF27Fj88ccfRuuZemZdAEhKSsKAAQOwbt06gwkPzaQ4mjlEAKBr1644ePAgLl68qFc/Ly8Pf/31F0QiEbp06WL02JcvX8amTZvw+eef64xWKSws1EmeAEXDmDRlREREREREFRUfH4/mzZsbnPOCiP4laALlq6++wqVLl+Do6IjWrVvD3t7e4DtYCoUCP//8s0ljKygogFwux7Fjx/QSKHl5edi6dSsA4O2339Zu79GjByIjI3Hy5EkkJCToLGccGxuL7Oxs9OvXT7tcsSEqlQozZsxAQEAABgwYoFPm4+OjN7v79evX4ebmVmXLGxMRERER0X+bXC6HQqHA66+/DkdHR6HD0YqPj8f58+eFDoNIS9AEyvHjxxEUFITFixcbnWQmNTUVBw8eNGFk/76aEx0dDalUiqCgIDg7O+POnTuIiIjAgwcP0Lt3b+0EskDRxEtLlizB8OHDMWHCBCxatAiNGjXC77//jvnz58PHxwfTp083etzVq1fjwYMHWLlypV7Z6NGjMXr0aKxZswYDBw7E0aNHcfLkSZ3XfIiIiIiIiJ6Fo6MjXFxchA5D68mTJ0KHQKRD0ARKRkYGwsLCjCZPgKI1oydMmGCiqIp4eHjgp59+woEDB7B//35ER0cjNzcXdnZ2aNmyJb7++msEBQXp7demTRvs2rULkZGRCAsLQ0ZGBurVq4fg4GCMGTPG6EiRmzdvYtWqVZgyZQo8PT31yjt16oQFCxZgzZo1WL58OerWrYspU6Zg4MCBlXruRERERERERKRL0ASKu7s77OzsyqxnZWVl8gQKALRs2RItW7bEpEmTKrRf/fr18dVXX1X4eE2aNMHff/9ttE7//v3Rv3//CrdNRERERERERM9O0GWM+/Tpg7i4uDLrVcdljImIiIiIiIio9hA0gTJ69GhcvHgRUVFRSElJKbWeSqXCuXPnTBgZEREREREREdG/BH2Fp0ePHlCr1Th8+DCio6Mhk8ng6Oiot2Qxl+glIqLqKD4+HnK5XOgw9Li4uKB+/fpCh0FERET0nyJoAuXhw4c6/1YoFKWuPV4yqUJERCSk+Ph4tGjRAjk5OUKHosfKygpXr15lEoWIiIioEgmaQAGAqKioMieSTU9PxwcffGCiiIiIiMoml8uRk5ODSZMmGVw5TSgPHjzAkiVLIJfLmUAhIiIiqkSCJ1D8/f3h7OxstI5cLodarTZRREREROXn6ekJHx8focMgIiIioiom6CSy33//PRwcHMqs5+TkVK7VeoiIiIiIiIiIqoKgI1BeeOGFctUzMzODh4dHFUdDRERERERERGSY4K/waBw/fhwnTpzQTizr4eGBwMBAdOzYUeDIiIiIiIiIiKi2EzyBkpKSgokTJ+LPP/8EAO1cJyKRCD/88APatm2L5cuXo27dukKGSURERERERES1mKAJFKVSibCwMNy8eRMSiQSNGzeGi4sLgKKJY2/fvo0//vgDYWFh+PHHHyGTyYQMl4iIiIiIiIhqKUETKJs3b8bt27cxYcIEhISEwMbGRqc8KysLGzduxIoVK/D9998jLCxMoEiJiIiIiIiIqDYTNIFy8OBBjB49GhMmTDBYbmtriwkTJkClUuHAgQNMoBARERERUY0WHx8PuVwudBg6rl69KnQIRDWCoAmUu3fvYtGiRWXW69OnDzZv3myCiIiIiIiIiKpGfHw8mjVrBqVSKXQoRPQMBE2g5Ofnw8LCosx65ubmyM/PN0FEREREREREVUMul0OpVMLBwQESieDreWgplUpkZ2cLHQZRtSfoU+vm5obTp09jwIABRuudPn0abm5uJoqKiIiIiIio6kgkEpibmwsdhhb/WE1UPmZCHvy1117D//73P5w/f77UOufOncOSJUsQGBhowsiIiIiIiIiIiP4l6AiUkSNH4qeffsLQoUPh6+sLPz8/ODs7AwAeP36MS5cu4a+//oKtrS0nkCUiIiIiIiIiwQiaQHF1dUVUVBTCw8Px559/4vLlyzrlarUadnZ2iIyMhKurq0BREhER1TzVcUUFFxcX1K9fX+gwiIiIiJ6J4DMXBQQEYN++fdiwYQOOHz+OxMREAIC7uzs6duyIkJAQJk+IiIjK6cmTJzAzM8OQIUOEDkWPlZUVrl69yiQKERER1UiCJ1CAopEoU6dOxdSpU4UOhYiIqEbLzs5GYWEhoqKi4OPjI3Q4Wrdu3cKECRMgl8uZQCEiIqIaqVokUMqSm5uLAwcOoF+/fkKHQkREVCP4+PjA19dX6DCIiIiI/jMEXYWnvLKysjB9+nShwyAiIiIiIiKiWsqkI1Dy8vJw8+ZNtGzZEiKRCLt27SrXfllZWVUbGBERERERERGRESZNoAwbNgx//vkn+vbti4ULF2LatGkQiUSmDIGIiIiIiIiIqMJMmkB58uQJ1Go10tPTtdvatm0LqVRqdD+VSoU///yziqMjIiIiIiIiIjLMpAmUH374AefPn8f//d//abdFR0fD2dnZ6H6pqakIDAys6vCIiAhAfHw85HK50GHocXFx4eotRERERCQYkyZQnJ2d0aNHD+2/X3rppTJHnwCAubk5XnzxxaoMjYiIUJQ8adasGZRKpdCh6JHJZLh+/TqTKEREREQkCEGXMf7uu+/KrJObmwt7e/ty1SUioucjl8uhVCrh4OAAiaT6rHSfn5+P9PR0yOVyJlCIiIiISBCCLmM8ffp0ZGdnl1oul8vh5+eHwYMH4+HDhyaMjIiodpNIJDA3N682/1WnZA4RERER1U6CJlB27dqF3NzcUsttbW0xdepUZGRkYNGiRSaMjIiIiIiIiIjoX4L+SU+tVhstt7CwQEhICDp06ICwsDATRUVEREREREREpEvQESgAIBKJyqyTn5+PrKwsE0RDRERERERERKTPpCNQfvnlF8TFxelsmzdvHiwsLErdJycnBxcuXOCkgUREREREREQkGJMmUK5du4affvpJZ1tsbGyZ+4lEIkyaNKmqwiKiMsTHx0Mulwsdhh4XFxcmV2uZq1evCh2CVnWKhYiIiIiqnkkTKO3bt8eECRMAFM1/smLFCoSEhMDa2tpgfZFIBHt7e3To0AFNmjQxZagAgEuXLmHv3r04d+4cEhISkJ+fj7p16+Kll15CaGgomjdvrrdP586dja4YNGfOHAwcOFBn2/379zF//nycPXsWEokEHTt2xIwZM+Dk5KS3f3Z2Nt588034+fnh66+/fv6TJCpDfHw8WrRogZycHKFD0WNlZYWrV68yiVILFBQUQCQSYciQIUKHQkRERES1lMkTKO3bt9f+Ozo6GiNHjoSzs7MpwyiXPXv2YMqUKfDw8MCnn36KF154AQDw+++/Y/78+di3bx8WLVqE3r176+3r5uYGmUxmsF17e3udf+fl5WHEiBFwcXHBgQMH8PTpU4wdOxYTJ07E5s2b9fb/3//+h5ycHMyaNasSzpKobHK5HDk5OYiKioKPj4/Q4WjdunULEyZMgFwuZwKlFlCr1VCr1Xj99dfh6OgodDgAipKL58+fFzoMIqqg6jiqkiMqiYhqBkFX4dm0aZNeQqG60CyvvHz5crRu3Vq7vXfv3rC2tsaYMWMwa9YsvPbaa3rnsGjRInTo0KFcx9m3bx8ePHiARYsWwc3NDQAwfvx4TJ06FefOncNLL72krXv+/Hls3boVixcvNjg6hagq+fj4wNfXV+gwqJZzdHSEi4uL0GEAAJ48eSJ0CERUQdV1VCVHVBIR1QyCJlCKj0YxJj8/H5cvX0a7du2qOKJ/OTo6olOnTjrJE42OHTvC3NwcOTk5OH/+PLp06fLMx7l58yYA6LwOpPn6xo0b2gRKbm4uZsyYgcDAQPTp0+eZj0dERERUW2lGVU6aNAmenp5ChwMAePDgAZYsWYJff/0VLVq0EDocHRwZQ1TzVMc52v5LfYmgCZTySk9Px+DBg016M3Tt2hVdu3Y1WGZmZgYrKyvk5eWVaxlmYwoKCgDoLudsZla0unR+fr52W2RkJFJTU7Fhw4bnOh4RERFRbefp6VltXkt98uQJzMzMquUcTxwZQ1RzpKSkwEyE6tmXWMpw9dr1/0RfImgC5dy5c+Wql56eXrWBVFBaWhrS09Mhk8ng5+enV3748GEsXboUd+7cQU5ODurWrYuXX34ZI0aMgLe3t05dzb+vX7+uHWGjGZXSuHFjAMA///yD9evXY+bMmdrXfCpbyaGsYrEYFhYWKCwshFKp1KtvZWUFAFAqlSgsLNQpMzc3h0QigUqlgkql0ikzMzODTCaDWq2GQqHQa9fS0hIikQi5ubna5JKGVCqFVCpFfn4+8vLydMpEIhEsLS0NngsAyGQymJmZGWxXIpHA3NwcBQUF2le3DLWrUCigVqt1yi0sLCAWi5GXl6eT8ALKfw0NtWvsGmraLesaGvpsjF1DzWcD6F5DQ8eobp71Gpb22Ri7hpp2jV3D0j4bY/dhZdzfhu5DY/c3oH8f1oTPm2o2hUKhcx+XdX8b62c193dV9bPsI4xfQ81n8yzXUKifI6qj7OxsFBYWVtu5xhISErSvTj7LzxEa5bm/y/pZ7L/QR5SMkaiyZGRkoFANLAl3RmOP6tPf3X6owqTIx3j48KE2gVKZfYRarX7uQQ0VIWgCZejQoSY92coSExMDoCh+Q3ORnDp1Cp988gleeuklFBYW4uTJk/j888+xd+9efP311+jcubO2bu/evREZGYmvv/4aK1asQG5uLlavXo1mzZrhlVdeQX5+Pj799FO0a9cO7733XpWcT0FBgd7oHicnJzRq1Ah5eXkGR/5oJtW9d+8enj59qlPWsGFDODs748mTJ0hISNAps7OzQ5MmTVBYWGiwXV9fX0ilUiQkJCAjI0OnzNPTE66ursjKysKdO3d0yiwtLdGyZUsARctll/wm2LJlS1haWiIpKQmPHz/WKatXrx48PDyQk5ODGzdu6JRJpVLtvB83b97U+wbatGlT2NraIjU1FY8ePdIpc3Z2RsOGDZGbm6t3riKRSJswu3v3rt4Pgd7e3nB0dERaWhoePHigU2Zvbw8fHx/k5+cbvIZ+fn4Qi8VISEhAZmamTpmXlxfq1q2LjIwM3Lt3T6fM2tpa+/pY8XZL1quO7ty5o/cDTOPGjeHg4AC5XI7ExESdMgcHBzRu3LjUa+jv7w+RSIT79+8jOztbp6xBgwZwcXFBeno67t+/r1NmY2ODZs2aQa1WG2y3TZs2MDc3x4MHD/QSw+7u7nBzc0N2djZu376tUyaTydCqVSsARcnWkj+MtWjRAlZWVnj06BFSU1N1yurWrQsvLy8oFApcv35dp0wikaBt27YAgNu3byM3N7dGfN5Us927d09nonULCwvt67I3b97U++WiWbNmsLGxQXJyMlJSUnTK6tSpg/r160OpVOo9c2ZmZvD39wfAPqIy+4jifHx8YG9vj9TUVCQlJemUVdefI6qz6jrXWPFn9ll+jtBo1aoVZDIZEhMTkZaWplPm5uYGd3d3ZGdn49atWzpl/7U+IisrS68+UWVq7CFFa28LocPQU/w5qsw+QqVSwdzcvGqCNkDwV3hcXV21r6wUl5aWpu3I3N3dTR1WqZKSkrBy5Uq0adMGEydO1CufP38+WrVqBTs7O+227t27w87ODsOHD8fkyZPxyy+/aBMvNjY2WLFiBWbOnKmdeNbPzw8LFiyAmZkZ1qxZg7t372L37t0QiUS4dOkSoqKicOPGDTg4OKB///4ICQl5rkSUWCzWe+dWLBYDKMq+G3sft2HDhgb/cgQUzSNjY2OjU6b5rM3MzAy2K5EU3ZJeXl56n7vmL0e2trZ6+xY/f0PLS1tYFHUibm5uqFu3rsFjWllZGW23SZMmBv/6BhR9gy65MojmGlpYWBi9ho0aNTL4Vw+g6AdQW1tbg+1KJBKD7WqusZeXl8ERKEBREqbkvsWfw+Jlhv6yUt14e3uXeg1dXFz0Jnou6xpqPvcGDRqUen87ODho/3KlobmGIpHI6P3t6empN5pM89nY2NgYvQ+bNWum167mB9t69erpTbCqOaalpaXR+7Bx48ZQq9U14vOmmq1hw4Y692LJfrYkTT/r6uqqt2qf5v6WyWRG72/2EZXXRxRX/Hugg4ODTll1/Tni4cOHpcZChhV/Zp/l5wgNzefq7u4OV1dXnbLy3t//hT7i77//LjUOov+y4n1yZfYRph5dKHgCZefOnaUuY5ycnIxt27bh9u3biIiIMHFk+rKzszF+/Hi4urpi9erVBjNdL7/8ssF9AwIC0KRJE9y8eRMHDhzA4MGDtWVt27bF3r17kZ6eDolEov1h4fbt24iOjsYHH3yAhg0b4v79+xg+fDhef/11rF27Fn/88Qc+//xz5OXlYfTo0c91biV/yNPQzPdSmtKWawb+HWpliEgkMtqu5puhIRKJRPsN0ZBnbVcsFhvdVzN81BBzc/NSM59lXcPi7VbHpRVrwogEY5+Nsfvwee5vY/ehUPe3sfuwvPe3sWtJVBnu3btX7e6z0ia3Yx/xLyH62ar6OYIqxtLSUu9aC/Wz2LPe3xX5Waykyr6/jV03ov+y4s9+ZfYRpn6jRdAn+NVXXzU63MbV1RUTJ07Ehg0bsHr1aowbN86E0enKzs7G+++/D5VKhQ0bNpSa9DGmfv36uHnzpt6wI43if70pLCzEzJkz0bRpU4SGhgIAVq9eDTMzM8yfP187DPjs2bNYtWoVQkNDTTp0iSpfdV1akYioMnByOyIiIqrpBE2grF27tlz1unTpgrCwMMESKE+ePMGoUaMgFouxefNmvWF85aUZGlieLNn333+Pv/76Czt27NAOE7x27RoaNWqkM5zV19cX+/btw/379w0Oa6SaozourQgAFy5cwObNm4UOg4hquOo+uZ1cLmcChYiIiIyqEWPIMjMz9SYnM5Xk5GSEhYXB2dkZK1asgLW1tbYsNjYW9erV004Gum7dOhw7dgzfffedwbY0k8lpVtcpzcOHDxEREYFRo0bpzOdRWFioTaZoaIYBlpypmGqu6rS0IgC9CfyIiJ5HdZ3cjoiIiKgs+rO3VjOFhYVYv379M4/6eB4JCQkYNGgQvLy88M033+gkTwBgy5Yt+P3337X/zsnJwaVLl/RWTQGAkydP4vbt27CyskLPnj2NHnf27Nlwd3fH2LFjdbb7+Pjg/v37OrPgX7t2Debm5mjYsOEznCERERERERERlYegI1CmT59eallhYSEyMjLw999/4/Hjx3j77bdNGBlw69YthIaG4vHjx2jVqhWmTp1qsE779u21/xaJRFCpVBgzZgymTp2Ktm3bQiwW47fffsMXX3wBCwsLfPXVV0bnT/npp59w8uRJbN26VW9Ok5EjRyI2NhZfffUVwsPDcfnyZezduxfDhw83OgkbERERERERET0fQRMoP/30E0Qikd6yYSX5+vpi8uTJJoqqyIEDB7Rryf/888/l2mfUqFFo1qwZDh48iDlz5iA5ORkikQj16tXD66+/jpCQEKOv78jlcixcuBBDhw5F27Zt9cqbN2+OFStWYNmyZfi///s/ODg4YMiQIfjggw+e7SSJiIiIiIiIqFwEnwMlJCRE79UYoGhZMDs7O7Rq1Qr+/v4mjys8PBzh4eEV2sfCwgLdunVDt27dnumYLi4uOHPmjNE6nTp1QqdOnZ6pfSIiIiIiIiJ6NoInUEaOHPlMSwITPY/4+HjI5XKhw9Bx9epVoUMgIiIiIiKiUgiaQPniiy9ga2srZAhUC8XHx6N58+ZQKBRCh0JEREREREQ1hKAJlHfeeUfIw1MtJZfLoVAo8Prrr8PR0VHocLTi4+Nx/vx5ocMgIiIiIiIiAwRNoCiVSixduhRqtRoymQwfffSRTvlnn32Ghg0bYtiwYRCLxQJFSf9Vjo6OcHFxEToMrSdPnggdAhERUaXh67JERPRfI2gC5eeff8aGDRsgEonQoUMHvfLc3FwsWrQIp06dQnR0NKRSqQBREhEREVFF8HVZIiL6LxI0gXL06FG4urpi9erVaN68uV75woUL0b9/f0ycOBE7duzAwIEDBYiSiIiIiCqCr8sSEdF/kaAJlCtXruDDDz80mDzRaN++PSZOnIiYmBgmUIiIiIhqEL4uS0RE/yVmQh48JSUFbdu2LbNehw4dEB8fb4KIiIiIiIiIiIj0CZpAMTMzg0RS9iAYiUSCvLw8E0RERERERERERKRP0ASKp6cnjhw5Uma9o0ePwtPT0wQRERERERERERHpEzSB0rlzZyxbtgz79u0rtc6ePXuwbNkydOnSxYSRERERERERERH9S9BJZEeMGIGffvoJU6ZMweLFi9G2bVs4OTkBAB4/fozLly8jNTUVdevWRWhoqJChEhEREREREVEtJmgCxd7eHt988w3Gjh2LxMRE/PLLL9oytVoNAPDw8MDKlSthb28vVJhEREREREREVMsJmkABgGbNmiE2NhY7duzA8ePHkZiYCABwd3dHx44d8fbbb8PS0lLgKImIiIiIiIioNhM8gQIAMpkMQ4YMwZAhQ4QOhYiIiIiI/r+rV68KHYIeFxcX1K9fX+gwiKgWqhYJFCIiIiIiqj5SUlJgJkK1/AOnlaUMV69dZxKFiEyuWiRQsrOzsWvXLpw9exYpKSlYtmwZXF1dsXPnTrz66qtwdXUVOkQiIiKiaik+Ph5yuVzoMHRUx1ELVDEZGRkoVANLwp3R2EMqdDhatx+qMCnyMeRyORMoRGRygidQTp06hY8//hjp6elQq9UQiUTIy8sDAHz33XeYM2cOlixZgu7duwscKREREVH1Eh8fj2bNmkGpVAodCv1HNfaQorW3hdBhEBFVC4ImUOLj4zFu3DgoFAr4+Pigfv36OHHihLZ86dKlWL58OT7++GPExMSgadOmAkZLREREVL3I5XIolUo4ODhAIhH872JaSqUS2dnZQodBRERUqQT9Trt27VpIpVKsXr0a7du3BwD4+/tryxs2bIiIiAiEh4fj22+/xcKFC4UKlYiIiKjakkgkMDc3FzoMrfz8fKFDICIiqnRmQh789OnTmDJlijZ5Upphw4bhjz/+ME1QREREREREREQlCJpASU5OxgsvvFBmPQ8PDyQnJ5sgIiIiIiIiIiIifYImUCQSSbnej5XL5dXqvV4iIiIiIiIiql0ETaD4+Phgx44dZdb74Ycf0KxZMxNERERERERERESkT9BhHW+++Sbmz5+P/Px8vP/++2jYsKFOeXx8PFavXo3du3dj7ty5wgRJzy0+Ph5yuVzoMLSuXr0qdAhUiarj5+ni4oL69esLHQYREREREVUiQRMowcHB2LdvH2JiYvDTTz/Bzs4OeXl5CAsLQ3Z2Np48eQIAaNeuHd5++20hQ6VnFB8fj2bNmkGpVAodCv3HpKSkwEwEDBkyROhQ9FhZynD12nUmUYiIiIiI/kMETaBIpVJ88803mDFjBg4dOoSMjAwARb90a/Ts2RPz5s2DWCwWKkx6DnK5HEqlEg4ODtVmHhulUlmuuXeoesvIyEChGlgS7ozGHlKhw9G6/VCFSZGPIZfLmUAhIiIiIvoPEfw3WltbWyxfvhzXr1/HiRMnkJiYCABwd3dHx44d0bRpU4EjpMogkUhgbm4udBgAgPz8fKFDoErU2EOK1t4WQodBRERERET/cYInUDSaNWvGiWKJiIiIiIiIqFoSdBWeqKgoKBSKMuvJ5XK0aNHCBBEREREREREREekTNIESHR1drgTKgwcPTBANEREREREREZFhgiZQ1Go1IiIijK7Q8v333yMkJMR0QRERERERERERlSBoAgUALl26hLfeegvXrl3T2f7kyROMGTMG8+bN4xK4RERERERERCQowRMoa9euxf/93//h3XffxYYNGwAAJ0+eRJ8+fXDs2DHY2tpi9uzZwgZJRERERERERLWaoKvwxMXFoV69epg5cyZefPFFzJw5EzExMbh16xYKCwvh6+uLiIgIODg44K+//hIyVCIiIiIiIiKqxQQdgeLh4QGRSAQAcHNzg42NDW7cuIHCwkL069cPW7ZsgaenJ2xsbLBgwQIhQ60QlUqFNWvWoHfv3vD19UVAQADGjx+PK1eu6NXNycnB7Nmz0aFDB/j6+mLo0KEG62mMHz8eXbt2Ldfku0RERERERERUOQRNoAwbNgyZmZnYsGEDhgwZguTkZLi4uKB79+44cuQIDhw4AKAoIXHu3DkhQy23vLw8hIWFYfny5QgJCcHp06exZcsWZGVlITg4GMeOHdOpP2vWLBw+fBirVq3C0aNHYWNjg9DQUDx58kSv7djYWPzyyy/44osvYGlpaaIzIiIiIiIiIiJBEyhnz57FxIkTsWjRIqhUKrz++uvYs2cPli9fjjlz5uDzzz/HpEmTkJCQgGHDhgkZarmtXLkSZ86cwZgxYzBgwABYWVmhUaNGWL58OaysrPDJJ58gPT0dAJCQkID9+/djyJAh8Pf3h7OzM2bOnImMjAx8//33Ou2mp6dj3rx5eOedd/Dyyy8LcGZEREREREREtZfgk8ieOXMGMpkMc+fOxYoVK+Dk5AQACAoKwq5du5CSkoLBgwcLHGX55ObmYuPGjQCA4OBgnTIHBwf07NkTGRkZ2Lp1KwDg1q1bUKvVaNGihbaeh4cH7O3tcePGDZ39v/zyS4jFYkydOrWKz4KIiIiIiIiIShI8gdKyZUvExMToJRwAwN3dHZs2baoxCZTTp0/j6dOnaNCgAerUqaNX/sILLwAomjwXAAoKCgBAOw+Mhkgk0pYBwIkTJ7B792589tlnsLW1rarwiYiIiIiIiKgUgidQVq1ahUaNGpVaLhKJ8N5770GtVpswqmdz9epVAICXl5fBcs12zUS53t7eAIDr169r66SkpCA9PR2NGzcGADx9+hSfffYZgoKC0LVr16oMn4iIiIiIiIhKIVILmJmYPn06ZsyYARsbG6P1cnNzERsbi7feestEkT2bL774Aps3b8Ybb7yBiIgIvfLbt28jKCgIQNGrSw4ODhg1ahSuXr2KjRs3wsvLC7NmzcLBgwdx8OBBuLm54fPPP8f+/ftx4MAB7etNlcnS0hL5+fnw9PTUK9OMjDF0i5SnDACUSiWSkpJgZiZ4rk5LrVZDrVZDJpNVq7jy8/ORl5cHe3t7iMViocPRysvLQ3Z2NpydnSGVSoUOR0uhUCAjIwNOdmaQSkRl72Aiqnw10jIL4ebmBgsLC52y8j43z/rMldadV2Tf3NzcavfMAtXzueUzWzE17ZmtjO+Blfksl9Yun9mKqY7PLZ/Ziin5zFbm90BDZc+zr6GyvLw8JCYmVqvnAuAzW1HV8bmt7s+su7u79vtsZT6PDx48gEQiMdkqtRKTHKUU5V2a2MLCotonTwBoP7TSHiJzc3Pt10qlEgCwcOFCTJ8+Hb1794ZYLEa9evWwfPlyuLm54fz58/jhhx+wePFiODk5ITk5GRERETh79iwkEgkCAwPx0UcflZmAMkZzE5d8jai4Zy0DAJlMZnSEEdUMhl5JE5qlpWWVJBUrg72z8fKynpuqeh7Lsy+f2f8GPrMVY+yZrepn7nnb5TP738BntmIMPbNV9Tw+z76GyiwsLPjM/kdUt+e2Jj2zlfk8SiQSvT9aViVBEyjGFBQU4OLFizrbXnrpJYGiKR/N0sIqlcpgeV5envZrmUwGAHB2dsaaNWuQk5MDpVKpvelzc3Mxc+ZMBAYGok+fPlCpVAgNDYVIJEJERAQUCgU++eQT3Lt3D+vWrXvmmDUrAhERERERERFR6UyaQCm+2sypU6fg4OBQat2cnBwMHToUIpEIarUaZmZm+Oeff0wQ5bPTZCEzMjIMlmu2y2Qy2NnZ6ZRZWVnByspK+++oqCikpKRg/fr1AID9+/fj9u3bWL9+Pfz9/QEA4eHhmD17Ns6fP48XX3yx0s+HiIiIiIiIiIqYNIGiVqvx6aefwtbWFtbW1kbr2tjYaFeruXv3LkaNGmWKEJ+LJkGUkJBgsFyzvWnTpkbfLfznn3/w7bffYubMmXBzcwPw70Szvr6+2npt27bVljGBQkRERERERFR1TP4KzxtvvAFn56KXoIYNG6ZXvmnTJgBF7zZ5eHgAKBqNUhMEBATA2toa8fHxkMvlcHFx0SnXvJJkbDWd/Px8zJgxA+3atcN7772n3a5Z1rh44kUzkVLxJY+JiIiIiIiIqPIJOsWyh4eH9r+LFy8afaWnJrCwsMDw4cOhVquxbds2nbLMzEwcPHgQ9vb2CA4OLrWNdevW4c6dO/jiiy90Jshp0qQJAN0lj69du6ZTRkRERERERERVo9qswnPw4EFMmTJFwGgqx9ixY3H+/HmsWrUKbm5u6NWrF5KTkzFnzhxkZ2cjKiqq1ETR3bt3ER0djYkTJ6Jhw4Y6ZW+++Saio6OxePFiREREQKlUYsWKFfDz80NAQEDVnxgRERERERFRLVZ9Fvn+jzA3N8e6desQHh6OtWvXon379ggODoaVlRW2b9+O119/3eB+arUaM2bMQJMmTRAaGqpXLpPJ8O2338La2hq9evXC22+/jWbNmiEqKqrMpZ6IiIiIiIiI6PmI1Gq12lQHa968OX7//XftHCjF+fv7Y8+ePfDy8tIru3nzJvr06YOrV6+aIkwiIiIiIiIiIh0cgUJEREREREREVAaTJ1D4ugkRERERERER1TQmf4XHzc1NZylejaSkJNStW1e7NG9x+fn5SElJ4Ss8RERERERERCQIk6/Ck5SUVGrZo0ePSi3jyBUiIiIiIiIiEorJEyihoaGwtrau0D6PHz/G1q1bqygiIiIiIiIiIiLjTJ5AGTlypMFVeIy5ceMGEyhEREREREREJBiTTiLbvXt3WFhYVHg/Ozs7dOvWrQoiIiIiIiIiIiIqm0knkSUiIiIiIiIiqolMvowxEREREREREVFNwwQKEREREREREVEZmEAhIiIiIiIiIioDEyhERERERERERGVgAoWIiIiIiIiIqAxMoBARERERERERlYEJFCIiIiIiIiKiMjCBQkRERERERERUBiZQiIiIiIiIiIjKwAQKEREREREREVEZmEAhIiIiIiIiIioDEyhERERERERERGVgAoWIiIiIiIiIqAxMoBARERERERERlYEJFCIiIiIiIiKiMjCBQkRERERERERUBiZQiIiIiIiIiIjKwAQKEREREREREVEZmEAhIiIiIiIiIioDEyhERERERERERGVgAoWIiIiohurWrRuaNWum/e/MmTPP3ea0adN02oyMjKyESImIiGo+idABEBERUfUxbtw4xMXFGSwzNzeHnZ0d3Nzc0LZtW3Tr1g0BAQFVEofml/bhw4fDzs6uSo5R0tChQ3H27FmdbVOnTsWIESPKtX9ycjK6deuG3Nxc7TYPDw8cOXKkUuMsbtu2bSgoKMCAAQPw6NGjSmlzxowZmDRpEubPn48DBw5USpvlce/ePezduxcnT57E7du38fTpU1hbW6Nx48bo3r07Bg4cCJlMZrJ4iIiISuIIFCIiItJauHAhfvvtN23SoF69evjtt9/w22+/ITY2FpGRkQgKCsLp06cxfPhw9O3bF1euXKn0OKKiohAVFYXMzMxKb7s0kZGROucOAKtXr0Z2dna59o+OjtYmT3r16oXffvsNO3bsqJJYNZycnFCnTh2IxeJKa9PW1hZ16tQxabJiz5496NWrF7755hu0b98ea9euxcGDB7FkyRKIxWIsXLgQffv2RWJiosliIiIiKokJFCIiItKys7NDnTp1YGVlBQAQi8WoU6cO6tSpAy8vL7Rr1w4jRozAvn37MGnSJFy/fh3BwcE4evSowJE/PwcHB+25W1tbQyqVIj09HWvXri1z3/j4eMTExMDBwQEAIJPJUKdOHTg5OVVx1P8NaWlpKCwsxKxZs/DRRx/B19cXXl5eeO2117Bx40a0atUK9+7dw/Tp04UOlYiIajEmUIiIiKjCRCIR3n//fYwePRoqlQoffvgh7t+/L3RYlcbBwQHBwcEAgI0bN+Lx48dG6y9fvhyvvPIKmjZtaorw/pMsLS3Rt29fve1isVj7WZw+fRpyudzUoREREQHgHChERET0HMaNG4cdO3ZALpcjIiICy5Yt05apVCr8+uuvOHz4MP766y8kJSUhPz8f7u7u6NixI0aNGgVnZ2ed9krOQ9KlSxed8ri4OHh6ekKtVuP06dM4fPgwLly4gKSkJCgUCri6uuKVV17BqFGj4OXl9VznNnbsWMTExCAnJwcrV67EzJkzDda7ceMGYmNjsWPHDixYsKDMdtPT07F+/XocOXIECQkJAAAvLy907twZoaGh2lEsJV25cgXR0dG4cOECFAoFPDw88Oabb2LkyJFlHjMtLQ3r1q3DkSNH8PDhQ4jFYjRo0ABdu3bF8OHDYWtrW2YbZYmJiTE4QmTTpk3o0KEDAP3Pt3379vjuu+8wePBgBAcHw9zc3GDb9erV036dkZEBFxeX546XiIioophAISIiomdmYWGBHj164Pvvv8eRI0egUChgaWkJALh79y7Gjh2L5s2b4+OPP0aTJk2gVCpx8eJFREZGYv/+/diyZQs8PT217UVGRkKlUuHVV18FAPz4449wc3PTlmteicnJyUFISAg8PDwwefJktG7dGiqVCv/88w+ioqKwb98+bNq0Ca1bt37mc3NxccGwYcOwatUqbN26FSEhITqxaixbtgxdu3ZFy5Yty2zz+vXrGDVqFDIyMjBx4kRtgujIkSNYtmwZfvrpJ6xdu1ZvJEtcXBw++OADmJubY/LkyXjttdegUCiwe/dujB8/HoWFhaUe89q1axg5ciQyMjLwwQcfIDAwELm5uTh06BCio6OxZ88ebNy4Uec6P4ugoCC89tprCAsLw/Xr1/H+++9j2LBhsLe319aJjIzEvXv3EBwcjNWrV8PPzw8AIJVKIZVKS207JSUFAGBlZYX69es/V5xERETPiq/wEBER0XPx9fUFAOTl5elMKCuVSuHp6Yk1a9agc+fO8PLyQpMmTRAcHIyvv/4aKSkpWLRokU5bmnlINDSTpGr+00yWamZmBg8PDyxbtgxBQUGoX78+GjdujDfffBPr1q1DTk4OZs+e/dznNnLkSDg4OEClUmH58uV65ZcvX8bRo0cxceLEMttSKBQYO3YskpOTMXfuXISFhaFhw4Zo2LAhRowYgTlz5iA5ORljx46FQqHQ7vf48WNMmzYNKpUK8+fPx6BBg+Dl5YWmTZtiypQpcHd3R1JSksFj5uTkYOzYsUhNTcXcuXMxcuRING3aFG3atMGkSZMwbtw43L9/H9OmTXv2i/T/aeZ9GThwIADg4MGDcHFx0RlV4uDggKNHj6Jx48bo1KlTqaNtStKsZDR48GCjiRYiIqKqxAQKERERPZfiE6UWn5+iUaNGiIuLg6urq94+7dq1AwAcP34cKpWqwse0tLTEkSNH0KZNG70yT09PuLq64sqVK8+9tK+trS1GjRoFANi7dy9u3rypU7506VK88cYb8PHxKbOtnTt34uHDh6hTpw769OmjV963b1/UqVMHDx48wM6dO7Xbd+zYgczMTLi6uqJnz556+4WEhBg9ZmJiIurUqYN+/frplQ8ePBhA0dwi165dK/McyqNPnz6wtrZGfHw8fv/9d52y/Px87Ny5UzunSXn89ddfOH78OHx8fDBu3LhKiZGIiOhZMIFCREREz0WtVpdalpSUhIULF6Jfv34ICAiAv78//P398eKLLwIAcnNzkZaW9kzHTU9Px/Lly/HOO+/glVde0bbt7++P5ORkAKiUZW+HDBmCunXrorCwEBEREdrtZ8+exZkzZxAeHl6udo4dOwagaMSOmZn+j2BmZmbahNCJEye020+fPg0AaNOmDUQikd5+DRs2LHVUxvHjx40e08nJCTY2NgCAc+fOles8ymJtba1NEG3dulWnLC4uDpmZmQaTOYZkZmZi8uTJsLe3R2RkpHZ1KCIiIiFwDhQiIiJ6LsUTIMUn9/zzzz8xYsQIPH36FIMGDUKPHj3g6uqqTQJ0794dAJ5pBEp8fDwGDx6MlJQUBAUF4aOPPkK9evW0r/gMHToUycnJz9R2STKZDOPHj8dnn32GI0eO4NKlS/D390dERAT69+9f7jk5NMkcYxOgasoePnyo3aYZRVNywl0NkUgEFxcXg6/xaI554sQJ+Pv7G9xf87qQJulUGQYNGoQtW7bg6NGjSE5O1o5C2rZtG3r16qUzL0ppsrOzMWrUKGRmZmLjxo3w9vautPiIiIiehaAJlKioKISFhWknmyMiIqKa5/LlywCKJpRt1aqVdvusWbOQnZ2NAQMGVMp8JMUtWLAAKSkpePnll/H111/rlUsklfsjzoABA/Dtt9/i/v37iIiIQFhYGK5cuWLw2NVRjx49ypynpTJW4tFo2rQpXnjhBVy4cAE//vgjJkyYgPj4eJw8eRI//PBDmfunp6dj9OjRSE1NxQ8//IBGjRpVWmxERETPStBXeKKjo5GRkSFkCERERPQccnNz8fPPPwMoWnJY80eRJ0+e4Pr16wCAwMDASj+u5rWWqmjbEIlEgg8++ABA0as7n376KYKDgyu0co27uzsA3XliStKUeXh4aLdplvB9/PixwX3UanWpbWqOqVKp0KBBA6P/FZ/LpjJoJpPdsWMHCgoKsH37djRp0kQ7/01pHj16hMGDByMnJwdbtmxh8oSIiKoNQRMoarUab775JubNm4fbt28LGQoRERE9gxUrVuDx48ewtLTExx9/rN1ubF4UAGVO7mporo+0tDRkZ2eX2X5BQQFSU1ONtv8sgoKC0KJFCwBFq9uMGTOmQvt37NgRQNGrTYaWHS4sLNSO5imeGHr55ZcBFI30MXTe9+7dK/VVpeLHLO2a7d27F3379q20SWQ1evToAScnJyQlJeGXX35BTExMmZPH3rlzBwMHDoSdnR2+//57vQmIw8LC9CamJSIiMhXBJ5EdP348/v77b/Tu3RtDhw5FbGws8vPzhQ6LiIiIjFCr1Vi9ejVWr14NqVSKZcuWwcvLS1vu5OSknRvk6NGjevvv27fPaPuaOTJycnK027p164aVK1cCAPz8/Ept+9ChQ8jLy6vYCZWDSCTCtGnT0KVLF0yePNnoXCaGvP322/Dw8IBcLsfu3bv1ynfv3g25XA4PDw+8/fbb2u0DBgyAnZ0dUlJScPDgQb39NmzYUOYxHz16ZPCY2dnZiIqKQn5+Ppo3b16h8ymLubk5BgwYAACYPXs2cnJy0Ldv31LrX758GYMGDUKzZs2wfv162NnZ6dX57bffKnWuFiIioooQfBLZN998EyEhIbh27Rq2bduG2bNnY/78+RgwYADeffddnSGsREREVLUyMzORm5urTVwUH82hVCrx+PFjXLp0CTt27MCtW7fQokULfPnll2jZsqVeW9OmTcOECROwa9cu2Nvbo2/fvjA3N0dcXBzWrFmjrZeWlgYLCwvUqVNHu61Dhw74+eefERMTg8GDB+PQoUPIzs7GK6+8AgCYNGkShgwZgrNnz2LKlCkYOnQobG1tcerUKSxduhQSiQT5+fnIyMhAamoqnJyctBPMliYrKwtKpRI5OTk6511834CAAAQEBOjtm5aWhoKCAu1IEKVSidTUVEilUjg4OAAArKyssHLlSowcORJz5sxBWloaunTpAgA4cuQIli1bBldXV6xatUpnfjgnJyd89dVXmDBhAmbMmIH09HS8+uqrUCqV2LVrFy5evAhnZ2c8fvxYe7729vYwNzfXHnPUqFGYNWsWEhMT0a1bN8hkMly7dg1RUVHIysrCd999p3cdlEolgKIkVmpqKqysrGBtbW30GpYUHByMtWvXIj09Hf379y91npWzZ89i9OjRyMnJQVJSEgYNGlSh4xAREZmCSF3WGFsTUygU2Lt3L7Zt24arV6/i1VdfxaBBg9CxY0eDw3mJiIio8owbNw5xcXEGy6RSKWxtbeHu7g4/Pz907dpV+3pJac6fP4+VK1fizz//hEKhgJOTE1566SWMHj1au9SthmbOFABITU3F559/jtOnT0OpVMLDwwNDhw7F4MGDdepHRUXh7NmzyMrKgr29Pdq2bYuRI0fik08+0VnJJi4uDp6enkZjnTZtGn766Se97eXZt3PnzjrH02jfvr1OcgIomh9mw4YNiIuLQ0JCAgDAy8sLXbp0QUhICBwdHQ0e459//kFUVBTOnz+PnJwcuLq6onPnzhg/fjz69++vc/z169drk01A0aSsmmPGx8dDIpHA3d0dnTp1wrBhw3SSV6VdhwkTJpR7yebi3n//fRw/fhzbt29H27ZtDdaZP38+Nm3aVK72FixYgP79+1c4DiIioudV7RIoxR0/fhyTJ09GdnY23Nzc8O6772LAgAEVHjJLRERERERERPQ8BJ8DxZCzZ8/i448/xoQJE5CdnQ21Wo3s7Gzs2rULnTp1wqRJk5550tmCggJs2LAB7dq1Q+fOncusf+XKFUyYMAEBAQHw9fVF7969sWbNmlInawOKZrpfs2YNevfuDV9fXwQEBGD8+PG4cuWKwfo5OTmYPXs2OnToAF9fXwwdOrTUukDRvDFdu3aFQqEo+4SJiIiIiIiI6LkJmkBp0aKFdkm+rKwsbNq0CW+88QaGDx+O2NhYqFQqtGrVCvPnz8eJEydw8OBBrF+/HgUFBejfv3+pQ4xLc+HCBbz11ltYuXIlnj59Wmb9Y8eOITg4GFlZWdiyZQtOnz6NkJAQLF++HGFhYQYnqMvLy0NYWBiWL1+OkJAQnD59Glu2bEFWVhaCg4Nx7NgxvX1mzZqFw4cPY9WqVTh69ChsbGwQGhqKJ0+e6NWNjY3FL7/8gi+++ELn/WgiIiIiIiIiqjqCvsLTvHlzrFq1CocPH0ZsbCyUSiXUajUsLS3xxhtvYODAgWjVqpXBfWNiYrBu3Trs37+/XMfav38/Zs6ciXHjxqFly5YYMWIEPDw8cOTIEYP1nzx5gh49egAADh8+rF0NAAAiIyMRFRWF8ePHY+LEiTr7LVu2DCtWrEB4eDgmTJig3Z6eno7u3bsDKFodQDOhXEJCArp164bw8HCMHz8eAPDw4UN07tzZYBtBQUHo3Lkz5s2bV67zJiIiIiIiIqLnJ/grPGPHjsXOnTuhUCjg7e2NGTNm4MSJE5g3b16pyRMAeOmll7QTr5WHh4cHYmNjMWrUKEgkZS8+tHXrVmRkZKBXr146yROgaEZ5ANi4cSNyc3O123Nzc7Fx40adOhoODg7o2bMnMjIysHXrVu32W7duQa1Wo0WLFjqx2tvb48aNGzptfPnllxCLxZg6dWo5z5qIiIiIiIiIKoPgCRSxWIxevXph06ZN2L9/v3YZQmOuXbuGRYsWwcrKqtzH8fPzg5ubW7nra14PeuGFF/TK6tati/r16yM7OxunT5/Wbj99+jSePn2KBg0a6Mxmr6Fpq/irRwUFBQCgt8KQSCTSlgHAiRMnsHv3bnz22WdlXh8iIiIiIiIiqlyCJ1D27NmDr7/+Gu3bty/3PmfPnkVSUhK6dOlSJTEVFBRoR394eXkZrKPZfu3aNe22q1evlmufGzduoLCwEADg7e0NQHfpxpSUFKSnp6Nx48YAgKdPn+Kzzz5DUFAQunbt+sznRURERERERETPpux3WarQW2+9hbp161Z4v2HDhmHYsGFVEFGRzMxM7as5JV/f0bCzswMApKamardpvi5tH812pVKJzMxMODg4wNvbG4GBgdi8eTO6desGLy8vLFmyBDKZDAMHDgQALFmyBDk5OZg1a1blnGAxDg4OyM3NrdDoHCIiIiIiIiKhJSUlwcLCAunp6SY5nqAJlAULFhgtT0hIKHU0R1VSKpXar6VSqcE65ubmAKCzlLDm67L2KXmMhQsXYvr06ejduzfEYjHq1auH5cuXw83NDefPn8cPP/yAxYsXw8nJCcnJyYiIiMDZs2chkUgQGBiIjz76CDY2Ns90rrm5uVCpVHorCpmZmUEikUCtVhtcsllzLiqVCiXnIZZIJDAzM0NBQYHOa0hA0atJmutjaBUjY+2KxWKIxWIUFhYiPz+/Qu1KpVKIRCLk5+drR/+UbLesczXWrqFzrY3X0FC7xWOqaLtVdQ0ro11TXsPnabe852qo3aq+hjXt/mYfwT6iIu2yj6h99zf7CPYRFWmXfUTtu7/ZR1TN/W3o3KuSoAmUhIQEDBgwAGq1GjY2Nnor4syePRtyuRwRERFo0qSJyeKSyWTar0v7QDQfevGlhDVfl7VPyWM4OztjzZo1yMnJgVKphJOTE4Ci5MbMmTMRGBiIPn36QKVSITQ0FCKRCBEREVAoFPjkk09w7949rFu37pnOVTPy5O+//9bZLhaLYWFhgcLCQp1kj4Zm/hmlUql3g5ubm0MikUClUuldCzMzM8hkMqjVap3kk4alpSVEIhFyc3P1HmapVAqpVIr8/Hy9h04kEmmvf05Ojl67MpkMZmZmBtuVSCQwNzdHQUGBzqTAJdtVKBR6nYSFhQXEYjHy8vL0HubyXkND7Rq7hpp2y7qGhj4bY9dQ89kAFb+GmnbLuoaG2jV2DTWfTVVdw9LaNXYNNe0au4alfTbluYbPc38bu4aGPhvA+DXUfDbPcg3ZRxRhH6HbLvsI9hEl22UfwT6ieLvsI9hHlGyXfQT7iOLtGrqGrVq10ptPtCoJmkDZu3cvMjIy0KZNG7z77rt65W+//TZWrFiBwYMHY9euXXB3dzdJXHZ2drCwsEBubi4yMjIM1snMzAQAncliNV+Xto9mu0wm074CVJyVlZXOxLhRUVFISUnB+vXrARQtxXz79m2sX78e/v7+AIDw8HDMnj0b58+fx4svvljRU9U5tiFmZmZGJ+stnggqSXOjGyISiYy2a2FhUWqZRCIxupLSs7YrFouN7ls8WVaSubm5zgij4sq6hsbafZ5raOyzEeoaGisT4ho+z/1t7BoKdX8bu4bPc39X1TVkH1GEfUT52mUfUXa7APsIDfYRRdhHFGEf8S/2EUXYRxT5L/QRpkyeAAJPInvq1CkEBgZi69ateOedd/TKe/fujZiYGDRt2hRr1qwxWVxisRhNmzYFgFKXStZsb968uXabZinisvZp2rQpzMyMX/p//vkH3377LaZMmaIdJaKZaNbX11dbr23btjplRERERERERFT5BE2g3Lp1C2FhYRCLxaXWkclkGDNmjM5ywaagWe3m4sWLemWpqamIj4+HjY0NAgICtNsDAgJgbW2N+Ph4yOVyvf00bZW1kk5+fj5mzJiBdu3a4b333tNu1wxlKp580Vy7ksOciIiIiIiIiKjyCJpAycrKKtcksY0aNUJSUpIJIvpXcHAw7O3tceDAAe3rOhrbtm0DAAwfPlxniJGFhQWGDx8OtVqtraORmZmJgwcPwt7eHsHBwUaPvW7dOty5cwdffPGFzpAkzTwwxUebaJZRNuUcMURERERERES1jaAJFGtra4MjNUp6/Pix0XesqoKjoyMWLVqE7OxsTJw4Effu3YNCoUBMTAxWr16N9u3bY8yYMXr7jR07Fu3bt8eqVasQExMDhUKBe/fuYeLEicjOzsaiRYvg4OBQ6nHv3r2L6OhohIeHo2HDhjplb775Jtzc3LB48WIkJSXh7t27WLFiBfz8/HRGwhARERERERFR5RKpS07Ja0JhYWGwtbXF0qVLjdb78MMPkZmZiW+//fa5jtesWbNSyyZMmIDw8HC97VeuXEF0dDQuXLiAnJwceHl5oW/fvggNDS11Ip+8vDxs2LABu3btQkJCAqysrPDCCy9g/PjxaNWqVakxqNVqDB48GLm5udi+fbvBV5vu3LmDL7/8EufPn4eZmRkCAwMxY8YMnclsK8Lb21vbLhEREREREVFNYerfZwVNoOzfvx+TJk3Cq6++ipCQEPj5+cHGxgYAkJ2djT/++APr16/HyZMnsWTJEgQFBQkV6n8WEyhERERERERUE5n691lBlzF+44038PPPP+PQoUP4/fffAUC7jJJmPWq1Wo3u3bszeUJEREREREREghF0DhQAiIiIwIgRIyCVSqFWq5GXl4e8vDyo1WpIpVKEhYUhIiJC6DCJiIiIiIiIqBYT9BWe4p48eYJTp04hMTERAODu7o6XX34Zjo6OAkf238ZXeIiIiIiIiKgmqlWv8BTn6OjI13SIiIiIiIiIqFoS/BWe8sjIyMCwYcOEDoOIiIiIiIiIaqkakUBRqVQ4d+6c0GEQERERERERUS0l+Cs8+fn52LZtG+Li4pCYmKhdfae4wsJCASIjIiIiIiIiIioiaAIlPz8fYWFhOHPmTJl1RSKRCSIiIiIiIiIiItInaAJl8+bNuHDhAsLDw9GuXTuMGTMG8+bNg6urKwDg0aNH2LdvH86cOYOvvvpKyFCJiIiIiIiIqBYTNIGyf/9+jB49GuPHjwcAmJmZwc/PD15eXto6ffr0wfTp03Hx4kV0795dqFCJiIiIiIiIqBYTdBLZO3fuoEuXLmXWGzRoEI4dO1b1ARERERERERERGSD4HCiOjo7af0ulUjx58kRnBAoA2NjYICkpydThEVVbCQkJ2LZtG44fPw61Wo38/Hx4enpizJgxePHFF7X1IiMjsXPnTtjb2+vsb2dnh++++87UYRPVWnxmiWoWPrNENUt5n9kTJ05g7969uHbtGsRiMRQKBRo0aIBx48bBz89PuBOgGkPQBEq9evXw6NEjuLm5AQCcnJxw4cIF+Pr66tQ7efIkzMxqxIrLRCYxZ84cpKWlYe3atXB1dYVKpcK8efMwZMgQREVFoWvXrtq6EydORP/+/QWMloj4zBLVLHxmiWqW8j6z33zzDcRiMb7//nvY2dkhNzcX06dPR2hoKGJiYtCoUSOBz4SqO0GzEo0bN8bGjRu1//b19cWKFSuwb98+ZGRkICMjA7t27cLSpUvRuHFjASMlqn7GjRunnXBZKpVi+vTpEIvFWL9+vcCREZEhfGaJahY+s0Q1S3me2ebNm+Ojjz6CnZ0dAMDCwgIjR45ETk4Ofv31V0HipppF0BEonTt3xsyZMxEaGor169dj0KBB2Lt3L6ZMmaJXd9CgQQJESFQ9rVq1ChKJ7uMrk8lgb2+PzMxMgaIiotLwmSWqWfjMEtUs5X1mZ8yYobfv06dPARS9DUFUFkETKN27d0dubi6sra0BAH5+fpg5cyYWLlwIlUoFoGhlntDQUA6NJCpGKpXqbUtPT0daWhqCgoJ0tv/666/Ys2cP0tLSoFar0aFDB7z//vuoW7euqcIlqvX4zBLVLHxmiWqWijyzxd2+fRuLFi1CYGAgevbsWZUh0n+EoAkUOzs7DB48WGfb4MGD0bNnT1y4cAGFhYXw9fWFu7u7QBES1Rxbt26Fo6MjRo8erd0mk8kgEomwZMkSODs7IyEhAR9//DH69++PHTt2oF69egJGTFS78Zklqln4zBLVLIaeWY24uDjMnTsXKSkpeOuttzBt2jS9ESxEhojUarVaqINHRUUBAKytrREaGipUGLWat7c3gKIlpanmunLlCkJCQhAZGYmAgACjdW/evInevXsjODgYn3/+uYkiJKLi+MwS1Sx8ZolqlvI+sykpKZg3bx4uXbqEtWvXolmzZiaMkiqDqX+fFXQS2aioKERHR+PEiRNChkFUo92+fRvjx4/H4sWLy/yhDgCaNGkCGxsbXLp0yQTREVFJfGaJahY+s0Q1S0We2bp162LRokVQKBSYN2+eiSKkmkzwtYE///xzzmZO9IyuXr2KUaNGYf78+Xj99df1ylNTUw3uZ2ZmhsLCwqoOj4hK4DNLVLPwmSWqWYw9s2q1GgqFQm8fS0tLNGjQAH/99ZepwqQaTNAEir29Pf7v//5PyBCIaqw///wT48aNw+LFi3Weo+ITLr/66qtITk7W2S8+Ph6ZmZlo06aNyWIlIj6zRDUNn1mimqWsZ/bhw4cICAhAQUGBzn4FBQVITk6Go6OjSeOlmknQmXJat26Nhw8fljlJbHZ2NubPn48FCxaYKDKi6u3cuXMYPXo0+vfvj4cPH+Lhw4fasitXrujUjYiIwNy5cyGTyZCVlYU5c+bA1tbW4IRaRFQ1+MwS1Sx8ZolqlvI+s0qlEv/73//w0UcfwdzcHHl5eYiIiEBqaipmzpwpROhUwwg6ieyZM2cQFRWFdevWwdzcvNR6crkcr732Gq5evWrC6GoHTiJbM7311lv4559/Si2/fv06AGDfvn2IjY3F/fv3IRKJkJWVhXbt2iE8PFz72RNR1eMzS1Sz8JklqlnK88zm5eVh9+7dOHjwIJKSkiAWi5GRkYEGDRpg0KBB6NWrlwkjpspi6t9nBU2gnDt3Dj///DMOHTqE4OBgeHt7w9nZGSKRSKdeeno6Jk6cyARKFWAChYiIiIiIiGoiU/8+K+grPEOHDoVIJIJardYuaUxEREREREREVN0ImkABAFdXV5iZGZ/LtrCwUG+CLiIiIiIiIiIiUxE0gSISibBz5044OzsbrZeamorAwEATRUVEREREREREpEvQZYy9vLwgFovLrGdubo4XX3zRBBEREREREREREekTdBJZEh4nkSUiIiIiIqKayNS/zwo6AqW88vLysHfvXqHDICIiIiIiIqJaqkYkUDIzM/HJJ58IHQYRERERERER1VKCTiK7a9euctXLysqq2kCIiIiIiIiIiIwQNIEybdo0iEQiIUMgIiIiIiIiIiqToAkUAGjbti2kUqne9rS0NCQmJkKhUMDPz89gHSIiIiIiIiIiUxA8gRIdHQ1nZ2eDZZrJY/ft24fo6GgTR0ZEREREREREVETQBEpwcDBkMlmp5ebm5nj77bchEomwfPlyTJs2zWSxnTlzBsOGDStX3evXr2u/btasmdG633zzDQIDA3W2/fXXX1i4cCEuX74MGxsb9OzZE5988gksLS319k9KSsIbb7yBQYMGYfLkyeWKj4iIiIiIiIiej6AJlLlz55arXocOHRAZGWnSBIpGo0aNSi178OAB6v8/9u48Lqrq/x/4a4YBBkR2QVZlUcQFxb0+ueWWZmpmmopbaGaCWWamZi7lnitgykdLTVP7uKdomYr6Tc1cyjJUxGUgUBgRZJmBgZnfH/xmYphhQIW5KK/n4+HjIfece+77npl7Bt5z7zm+vgbbfXx8IJEY71pbW1u9nzMzMzF27Fi0b98e8fHxkMlkmDhxIvLy8rB06VKD/efMmYN69eohMjLyMc+EiIiIiIiIiJ6U4I/wVIZcLodcLhfk2EeOHDG6PTk5Gb169TJ6l8qmTZvg7e1dqfa3bduGnJwczJ49Gy4uLnBxcUFYWBiio6MxefJkvXb279+PU6dOYevWrbC2tn6yEyIiIiIiIiKixyYWOoCK5OTkYPXq1XB1dTXrcV1cXNC3b99yy7/99lvY29tj4MCBT3WcxMREODo6wsPDQ7ctODgYGo0GN2/e1G3LzMzEwoULMWzYMLRt2/apjklEREREREREj0fQO1BMzTGiVquRnZ2N27dvo7i4GGPGjDFfYAACAwOxcuVKo2W5ubnYvXs3hg8fbnIOl8ooLi422CYWl+S1ioqKdNs+//xz2NraYurUqU91PCIiIiIiIiJ6fIImUM6fP19hHZFIhN69e2PKlCnVH1Al7dq1C0qlEmFhYUbL//e//+H06dOQyWQoLCyEp6cnOnfujPDwcLi7u+vV9ff3x88//4z79+/ryhITE3VlAHD8+HHExcUhNjYWdnZ21XhmRERERERERGSM4HOgzJw5E3Xr1jXYLhaLYW9vj6ZNmxokHYSkVquxdetW9O7du9y4fv31V8ycORPNmzeHUqnEsWPHsGDBAuzfvx///e9/ERISoqs7bNgwbN68GUuWLMGiRYtw7949bN26FV27doW/vz9ycnIwd+5cDBgwAF26dKm288rPz9f72cLCAtbW1lCr1VAqlQb1tZPhKpVKqNVqvTIrKytIJBKoVCqoVCq9MrFYDKlUCo1GA4VCYdCujY0NRCIRCgoKDO7OsbS0hKWlJYqKilBYWKhXJhKJdKsWlT0XAJBKpRCLxUbblUgksLKyQnFxMQoKCsptV6FQQKPR6JVbW1vDwsIChYWFencMAZXvQ2PtmupDbbsV9aGx18ZUH2pfG+Dx+1DbbkV9aKxdU32ofW2qqw/La9dUH2rbNdWH5b02lenDp3l/m+pDY68NYLoPta/Nk/Qhx4gSHCP02+UYwTGibLscIzhGlG6XYwTHiLLtcozgGFG6XWN9qNFoIBKJDNqrLoInUF599VW4uLgIHUalHTt2DMnJyVi+fLnR8vXr1+PFF1+ElZUVgJI3whtvvAGgJFk0ZcoUHDlyRFfu6emJqKgozJs3D23atIFarUanTp2wcOFCAMDSpUtRXFyMmTNnAgDi4+MRGxsLmUwGd3d3jBw58qnnYSkuLkZCQoLeNmdnZ/j5+aGwsNCgDADatGkDALhz5w7y8vL0yho2bAgXFxc8fPgQycnJemX29vZo1KgR1Gq10XZDQkJgaWmJ5ORkZGdn65V5e3vD3d0dOTk5uHXrll6ZjY0NmjZtCgC4du2awSDRtGlT2NjYIC0tDQ8ePNArq1+/Pry8vJCfn48bN27olVlaWuoSXomJiQYDTOPGjVG3bl1kZGTg3r17emUuLi5o2LAhCgoKDM5VJBKhdevWAIDbt28bDE7+/v5wcnJCZmYmUlJS9MocHBwQGBiIoqIio33YqlUrWFhYIDk5GY8ePdIr8/HxgZubG7Kzs3Hnzh29sjp16qBJkyYAYLTdZs2aQSqVIjU1FZmZmXplHh4e8PT0RG5urt7cPUDJwN+8eXMAJX1YdvAPCgqCnZ0d7t+/j/T0dL2yevXqwdfXF0ql0iAmsViM0NBQAMCtW7cMPjgCAgLg6OgIuVyO1NRUvTJHR0cEBASU24ehoaEQiUS4e/cucnNz9coaNGgAV1dXZGVl4e7du3pldnZ2CAoKgkajMdpuixYtYGVlhZSUFGRlZemVeXp6wsPDA7m5uUhKStIrk0qlaNasGYCSZdPLflgFBwfD1tYW9+7dQ0ZGhl6Zm5sbfHx8oFAo9JZcB0o+0Fu2bAkASEpKMvhACgwMhIODAzIyMpCWlqZXxjGiBMeIf3GMKMExogTHiBIcI/7FMaIEx4gSHCNKcIz415OOESqVSve3tTmINGVffTM6e/Ys2rVrV+6SvzVRWFgYVCoVdu7c+Vj7FRcXo3379sjNzcX69evRtWtXgzqZmZmwsbHRZSHPnTuH0aNHY9WqVejTpw8uXLiAsLAwhIWFYciQITh27BhWrVqF5cuXo1+/fk90PtrHhP766y+97cwKG7bLrDC/OSrdLr854hhRtl2OERwjSrfLMYJjRNl2OUZwjCjdLscIjhFl2+UY8WRjRLNmzSASiQySXtVF0ATKs+bq1asYNGgQVq5caXKFnvIMGDAA165dw7Rp0zBu3DiTdRUKBfr374/GjRsjJiYGADB69GjIZDIcO3ZMN9HsW2+9hQcPHuDo0aOPf0L4N4FirjccERERERERUVUw99+zgi5jnJOTg8jISERERGDatGkG5ZGRkfjiiy8MbtsSyubNm+Hh4YFevXo90f7aXFVlntFavXo1srKyMGfOHN22a9euoVmzZrrkCVByG5pMJjOaxSMiIiIiIiKiqiFoAuXgwYM4evQozp49a/QxngYNGmDnzp0YOXKk4AmC9PR0xMXFYfjw4eU+cvTFF1/g448/NlpWXFyse74sICDA5LGuXLmCLVu2YPr06XBzc9NtV6vVeskToOQWK20ZEREREREREVUPQRMop0+fRkBAAOLi4rBo0SKD8o8++ggHDhxAVlYWtm7dKkCE//ruu+8gkUgwdOjQcuvk5ubi9OnTyMnJMSjbs2cP8vLy4OnpiRdffLHcNlQqFWbNmoWOHTti8ODBemWBgYEGEw9dv34dHh4eXN6YiIiIiIiIqBoJmkBJSEjA5MmTTS5T7OfnhylTpiAuLs6MkekrKCjAjh07MGDAADg4OJRbTyQSITMzE++88w4uXryIvLw8ZGdnY9euXVi4cCHs7e2xcuVKk7MEr1+/HikpKZg/f75B2YQJE3D79m3ExsYiJycHBw4cwJkzZzBhwoQqOU8iIiIiIiIiMk7Q5W/kcjmCg4MrrNeyZUuD5ZXMSXsXzKhRo0zW09458tNPP+HDDz/EgwcPYGFhAW9vbwwZMgRjx45F/fr1y90/MTER69atw7Rp0+Dt7W1Q3rVrVyxatAixsbFYs2YN3NzcMG3aNAwbNuypz5GIiIiIiIiIyifoKjxt2rTB999/X+GcIElJSXjzzTdx6dIlM0VWe3AVHiIiIiIiInoW1apVePz8/HDo0KEK6x06dAh+fn5miIiIiIiIiIiIyJCgj/D07t0bq1atgrW1NcLCwlCnTh298ry8PGzZsgWxsbGYMmWKMEESERERERGRIGQyGeRyudBhGHB1dYWvr6/QYZCZCfoIj0KhwODBg3Hr1i1YWloiMDAQzs7OAIAHDx4gKSkJKpUKgYGB+N///gepVCpUqM8tPsJDREREREQ1kUwmQ3BwMPLz84UOxYCtrS0SEhKYRBGYuf+eFfQOFBsbG3z99deIjIzElStX8PfffxvUCQkJQVRUFJMnREREREREtYhcLkd+fj6mTp1qdJENoaSkpGD58uWQy+VMoNQygiZQAMDd3R3ff/894uPjER8fj9TUVACAp6cnunTpgm7dugkcIREREREREQnF29sbgYGBQodBJHwCRatr167o2rWr0GEQERERERERERkQdBUeIiIiIiIiIqJngaB3oOTk5GDmzJnQaDSwsbHBsmXL9MojIyPh7u6ODz74wGCFHiIiIiIiIiIicxH0DpSDBw/i6NGjOHv2LCQSw1xOgwYNsHPnTowcObJGzrxMRERERERERLWDoAmU06dPIyAgAHFxcVi0aJFB+UcffYQDBw4gKysLW7duFSBCIiIiIiIiIiKBEygJCQmYPHky3N3dy63j5+eHKVOmIC4uzoyRERERERERERH9S9AEilwuR3BwcIX1WrZsiZSUFDNERERERERERERkSNAEipWVFVQqVYX1ioqKoFarzRAREREREREREZEhQRMofn5+OHToUIX1Dh06BD8/PzNERERERERERERkSNAESu/evbF+/XqsX78eeXl5BuV5eXn46quvEBsbiz59+ggQIRERERERERERYLh2sBmFhYVh3759WLVqFWJiYhAYGAhnZ2cAwIMHD5CUlASVSoXAwECEhYUJGSoRERERERER1WKCJlBsbGzw9ddfIzIyEleuXMHff/9tUCckJARRUVGQSqUCREhEREREREREJHACBQDc3d3x/fffIz4+HvHx8UhNTQUAeHp6okuXLujWrZvAERIRERERERFRbSd4AkWra9eu6Nq1q9GygoICHD58GAMHDjRrTERERERERLWBTCaDXC4XOgw9CQkJQodgUk2Lz9XVFb6+vkKH8VyrMQkUU3JycjBjxgwmUIiIiIiIiKqYTCZDkyZNoFAohA7lmfDw4UOIxeIaN0+nra0tEhISmESpRjU+gXLv3j1s3rxZ6DCIiIiIiIieS3K5HAqFAt26dYOTk5PQ4ejIZDJcuHBB6DAM5ObmQq1WIzo6GoGBgUKHAwC4efMmIiIiIJfLmUCpRjU2gXL69Gls374dJ0+ehFqtFjocIiIiIiKi55qTkxNcXV2FDkPn4cOHQodgUmBgIEJCQoQOg8yoRiVQsrKysHv3buzcuRPJyckAAI1GAwAQiURChkZEREREREREtViNSKBcvnwZ27dvx48//ojCwkJd0sTT0xMDBw5Ep06dMHz4cIGjJCIiIiIiIqLaSrAEikKhwIEDB7B9+3Zcv34dQMndJhKJBGq1Gl9++SX69OkDkUiEzMxMeHh4CBUqEREREREREdVyZk+gJCYmYvv27Thw4ADy8vJ0d5u4u7vjrbfewuDBg9GrVy+0aNFC99iOs7Mzjh8/bu5QiYiIiIiIiIgAmDmBMmLECFy6dAnAv3ObdOzYESNGjMDLL78MCwsLc4ZDRERERERERFQpZk2gXLx4ESKRCHZ2dhg4cCCGDRsGf39/c4ZARERERERERPTYxOY82MiRI2Fvb4+CggLk5OQgLy/PnIcnIiIiIiIiInoiZk2gzJo1C6dOncK8efNw584dvPnmmxg8eDD27t2LwsJCc4ZCRERERERERFRpZk2gAIC1tTVef/117NixA/v27UPz5s2xYMECdOrUCcuWLUNycrJu8lgiIiIiIiIioprA7AmU0po0aYK5c+fi1KlTmDp1Ks6dO4devXpBqVTi4sWLUKvVAIDMzEx0795dyFCJiIiIiIiIqBYTNIGiZWtriyFDhmD37t34/vvv8frrr2PevHno0qULvvzyS9y4cQOpqalCh0lEREREREREtZRZV+GpjBYtWqBFixaYMWMG9u/fj507d2LDhg18rIeIiIiIiIiIBFMj7kAxxs7ODiNGjMCBAwcQGxsrdDhEREREREREVIvV2ARKac2bN4eHh4fZjxsVFYWgoKBy/w0ZMsTofsnJyZg2bRpeeukltGjRAj179sSXX35Z7rLNf/75J0aMGIEWLVrghRdewLx586BQKIzWTUtLQ+vWrfHll19W2XkSERERERERkWk17hEeY5ydnXH8+HFBjm1nZ4d69eoZLfPy8jLY9tdff2HUqFHw9vZGbGws/P398csvv2D69OmIj4/Htm3b4ODgoKufmZmJsWPHon379oiPj4dMJsPEiRORl5eHpUuXGrQ/Z84c1KtXD5GRkVV3kkREREREZBYymQxyuVzoMPQkJCQIHQLRM+GZSKAIqWfPnli8eHGl6hYWFuLDDz9EQUEBoqOj4evrCwDo3r07Zs6ciRkzZmDhwoVYsmSJbp9t27YhJycHs2fPhouLC1xcXBAWFobo6GhMnjwZ3t7eurr79+/HqVOnsHXrVlhbW1ftiRIRERERUbWSyWQICgqCUqkUOhQiegJMoFShI0eO4O7du+jUqZMueaLVr18/LFiwAPv378cHH3yA+vXrAwASExPh6Oio94hScHAwNBoNbt68qUugZGZmYuHChRg2bBjatm1rvpMiIiIiIqIqIZfLoVQq4ejoCImk5vwpplQqkZubK3QYRDVezblqnwPHjh0DALRp08agzMrKCi1atMDZs2dx/PhxDB8+HABQXFxsUFcsLpmapqioSLft888/h62tLaZOnVodoRMRERERkZlIJBJYWVkJHYZO6b87iKh8z8QkskJKSUnBRx99hG7duqF58+bo0KED3n77bRw+fNig7rVr1wAAPj4+RtvSbtfWAwB/f39kZWXh/v37um2JiYm6MgA4fvw44uLiMHfuXNjZ2VXNiRERERERERFRpfEOlAr88ccf6NKlC6ZNmwYnJyfcvn0bK1euxJQpUxAfH4/FixdDJBIBANLT0wFAb5LY0uzt7fXqAcCwYcOwefNmLFmyBIsWLcK9e/ewdetWdO3aFf7+/sjJycHcuXMxYMAAdOnSpdrOMz8/X+9nCwsLWFtbQ61WG31G09bWFkDJ7X5qtVqvzMrKChKJBCqVCiqVSq9MLBZDKpVCo9EYXWnIxsYGIpEIBQUFBnfnWFpawtLSEkVFRSgsLNQrE4lEsLGxMXouACCVSiEWi422q/0GoLi4GAUFBeW2q1AooNFo9Mqtra1hYWGBwsJCg8x9ZfvQWLum+lDbbkV9aOy1MdWH2tcGePw+1LZbUR8aa9dUH2pfm+rqw/LaNdWH2nZN9WF5r01l+vBp3t+m+tDYawOY7kPta/MkfcgxogTHCP12OUZwjCjbLscIjhGl260NYwTv9KDqplAokJ+fX2vGCI1Go/t73ByYQDGhX79+6N27Nxo3bqzbFhQUhKioKPTt2xf79u1DaGgo3nrrLQDQDaCWlpZG29Pepld6oPX09ERUVBTmzZuHNm3aQK1Wo1OnTli4cCEAYOnSpSguLsbMmTMBAPHx8YiNjYVMJoO7uztGjhyJgQMHPtV5FhcXG8y87ezsDD8/PxQWFhqdlVv7mNKdO3cMlmdu2LAhXFxc8PDhQyQnJ+uV2dvbo1GjRlCr1UbbDQkJgaWlJZKTk5Gdna1X5u3tDXd3d+Tk5ODWrVt6ZTY2NmjatCmAkjt8yg4STZs2hY2NDdLS0vDgwQO9svr168PLywv5+fm4ceOGXpmlpSVCQkIAlNwZVHaAady4MerWrYuMjAzcu3dPr8zFxQUNGzZEQUGBwbmKRCK0bt0aAHD79m2Dwcnf3x9OTk7IzMxESkqKXpmDgwMCAwNRVFRktA9btWoFCwsLJCcn49GjR3plPj4+cHNzQ3Z2Nu7cuaNXVqdOHTRp0gSA8ZnYmzVrBqlUitTUVGRmZuqVeXh4wNPTE7m5ubh586ZembW1NZo3bw6gpA/L/uIQFBQEOzs73L9/Xy+5CAD16tWDr68vlEqlQUxisRihoaEAgFu3bhn8AhMQEABHR0fI5XKkpqbqlTk6OiIgIKDcPgwNDYVIJMLdu3cNngdu0KABXF1dkZWVhbt37+qV2dnZISgoCBqNxmi7LVq0gJWVFVJSUpCVlaVX5unpCQ8PD+Tm5iIpKUmvTCqVolmzZgCA69evG3xYBQcHw9bWFvfu3UNGRoZemZubG3x8fKBQKHD9+nW9MolEgpYtWwIAkpKSDD6QAgMD4eDggIyMDKSlpemVcYwowTHiXxwjSnCMKMExogTHiH9xjCiRk5NjUJ+oKt25cwc2Nja1ZoxQqVRmfRxOpCn7CVEDqVQq/P7772jXrp3Qoehs3LgRS5cuRfPmzbF7924AJYNlfn4+NmzYgE6dOhnss2zZMmzYsAHdunXDunXrDMozMzNhY2Ojy7KfO3cOo0ePxqpVq9CnTx9cuHABYWFhCAsLw5AhQ3Ds2DGsWrUKy5cvR79+/Z7oPLSPCf3111962/nNkWG7/OaI3xyVbpffLnOMKNsuxwiOEaXb5RjBMaJsuxwjOEYAJb9zd+jQAa6urjVqDpT8/HxkZWVh0KBBcHV1FTocncTERJw4cQIrV65EYGCg0OHonDhxAitWrMCRI0d0SVKhXblyBa+88gr+7//+D6GhobVmjGjWrBlEIpFBYry6PBN3oGRnZ2PUqFE1an3yBg0aAIDet0Bubm64c+eOwTceWtoMnZubm9FyZ2dn3f8VCgVmz56NHj16oE+fPgCAqKgoeHh4YObMmRCLxWjcuDFOnjyJ1atXP3ECRUt7gZUlFovLLQOguwiM0b7RjRGJRCbbNbVMs0QiMTlr+ZO2a2FhYXJf7Ye3MVZWVuV+CFbUh6bafZo+NPXaCNWHpsqE6MOneX+b6kOh3t+m+vBp3t/V1YccI0pwjKhcuxwjKm4X4BihxTGiBMeIEjVpjKhJK+/Q88nGxkbvffm8jxHmfHwHqCEJlCtXruCvv/5Cdna20VVpjGWohKbN4pV+wZo0aYI7d+4Y3G6qpd2uvXXJlNWrVyMrKwtz5szRbbt27RratWunW6UHKLlVdfPmzXrPuRERERERERFR1RI0gZKVlYWJEyfi999/N1nP3BPDAEBaWhoGDx6MjRs3Gk14aJ/p0j4CAwA9evTAkSNHcOnSJYP6hYWF+PPPPyESidC9e3eTx75y5Qq2bNmC+fPn692tolar9ZInQEkWTltGRERERERERNVD0ATKsmXLcPnyZTg5OaF58+ZwcHAweguRQqHAjz/+aNbYiouLIZfLER8fb5BAKSwsxI4dOwAAb7zxhm577969ERUVhTNnziA5OVlvOeO4uDjk5uZi4MCBcHd3L/e4KpUKs2bNQseOHTF48GC9ssDAQIPJya5fvw4PDw8ub0xERERERERUjQRNoJw8eRJ9+/bF0qVLTT4jlZGRgSNHjpgxsn8fzYmJiYGlpSX69u0LFxcX3Lp1CytWrEBKSgr69eunW4EHKHn2cvny5Rg9ejQiIiKwZMkS+Pn54ZdffsGCBQsQGBiIGTNmmDzu+vXrkZKSgq+++sqgbMKECZgwYQJiY2MxbNgwnDhxAmfOnNF7zIeIiIiIiIiIqp6gCZTs7GyEh4dXOJlSnTp1EBERYaaoSnh5eWHv3r04fPgwDh06hJiYGBQUFMDe3h5NmzbFypUr0bdvX4P9WrRogX379iEqKgrh4eHIzs5G/fr1MXToULz77rsm7xRJTEzEunXrMG3aNHh7exuUd+3aFYsWLUJsbCzWrFkDNzc3TJs2DcOGDavScyciIiIiIiIifYImUDw9PWFvb19hPVtbW7MnUACgadOmaNq0KaZOnfpY+/n6+mLZsmWPfbxGjRoZLCdc1qBBgzBo0KDHbpuIiIiIiIiInpy44irVp3///jh27FiF9bTLGBMRERERERERCUHQBMqECRNw6dIlREdHIz09vdx6KpUKv/32mxkjIyIiIiIiIiL6l6CP8PTu3RsajQZHjx5FTEwMpFIpnJycDJYs5hK9RERUE8lkMsjlcqHDMODq6gpfX1+hwyAiIiJ6rgiaQPnnn3/0flYoFFAoFEbrlk2qEBERCUkmkyE4OBj5+flCh2LA1tYWCQkJTKIQERERVSFBEygAEB0dXeFEsllZWXj//ffNFBEREVHF5HI58vPzMXXqVKMrpwklJSUFy5cvh1wuZwKFiIiIqAoJnkAJDQ2Fi4uLyTpyuRwajcZMEREREVWet7c3AgMDhQ6DiIiIiKqZoJPIbtu2DY6OjhXWc3Z2rtRqPURERERERERE1UHQO1DatGlTqXpisRheXl7VHA0RERERERERkXGCP8KjdfLkSZw6dUo3sayXlxc6d+6MLl26CBwZEREREREREdV2gidQ0tPTMXnyZPzxxx8AoJvrRCQS4bvvvkPLli2xZs0auLm5CRkmEREREREREdVigiZQlEolwsPDkZiYCIlEgoCAALi6ugIomTg2KSkJv//+O8LDw/G///0PUqlUyHCJiIiIiIiIqJYSNIGydetWJCUlISIiAmPGjIGdnZ1eeU5ODjZv3oy1a9di27ZtCA8PFyhSIiIiIiIiIqrNBE2gHDlyBBMmTEBERITR8rp16yIiIgIqlQqHDx9mAoWIiIiIiIiIBCHoMsa3b99Gv379KqzXv39/3L592wwREREREREREREZEjSBUlRUBGtr6wrrWVlZoaioyAwREREREREREREZEvQRHg8PD5w7dw6DBw82We/cuXPw8PAwU1RERETPvoSEBKFDMODq6gpfX1+hwyAiIiJ6IoImUDp16oQvv/wSDRs2RNu2bY3W+e2337B8+XL079/fzNERERE9ex4+fAixWIywsDChQzFga2uLhIQEJlGIiIjomSRoAmXcuHHYu3cvRo4ciZCQELRq1QouLi4AgAcPHuDy5cv4888/UbduXU4gS0REVAm5ublQq9WIjo5GYGCg0OHo3Lx5ExEREZDL5UygEBER0TNJ0ASKu7s7oqOjERkZiT/++ANXrlzRK9doNLC3t0dUVBTc3d0FipKIqHaRyWSQy+VCh2GgoKCgUvNmmUtNfESmtMDAQISEhAgdBhEREdFzQ9AECgB07NgRBw8exKZNm3Dy5EmkpqYCADw9PdGlSxeMGTOGyRMiIjORyWQICgqCUqkUOhQDIpEIGo1G6DCIiIiIqJYSPIEClNyJMn36dEyfPl3oUIiIajW5XA6lUglHR0dIJDXiIwIAoFQqkZubi27dusHJyUnocACUJJsuXLggdBhEREREZCY157djEwoKCnD48GEMHDhQ6FCIiGoFiUQCKysrocPQ0S5l7+TkBFdXV4GjKfHw4UOhQyAiIiIiMxILHUBl5OTkYMaMGUKHQURERERERES1lFnvQCksLERiYiKaNm0KkUiEffv2VWq/nJyc6g2MiIiIiIiIiMgEsyZQRo0ahT/++AMDBgzA4sWL8cknn0AkEpkzBCIiIiIiIiKix2bWBMrDhw+h0WiQlZWl29ayZUtYWlqa3E+lUuGPP/6o5uiIiIiIiIiIiIwzawLlu+++w4ULF/Cf//xHty0mJgYuLi4m98vIyEDnzp2rOzwiIiIies7JZDLI5XKhw9Dj6uoKX19focMgIqIKmDWB4uLigt69e+t+bteuXYV3nwCAlZUV2rZtW52hEREREdFzTiaTITg4GPn5+UKHosfW1hYJCQlMohAR1XCCLmP87bffVlinoKAADg4OlapLRERERFQeuVyO/Px8TJ06Fd7e3kKHAwBISUnB8uXLIZfLmUAhIqrhBE2gzJgxA7NmzYKdnZ3Rcrlcjk6dOqF169ZYunQpvLy8zBwhERERET1vvL29ERgYKHQYRET0jBELefB9+/ahoKCg3PK6deti+vTpyM7OxpIlS8wYGRERERERERHRvwS9A0Wj0Zgst7a2xpgxY9ChQweEh4ebKSoiIiIiIiIiIn2CJlAAQCQSVVinqKgIOTk5ZoiGiIiIiMj8EhIShA7BAFcHIiLSZ9YEys8//4xjx47pbfviiy9gbW1d7j75+fm4ePEiB28iIiIieu48fPgQYrEYYWFhQodigKsDERHpM2sC5dq1a9i7d6/etri4uAr3E4lEmDp1anWFRUQVkMlkkMvlQodhgN+MERHRsy43NxdqtRrR0dE1amLbmzdvIiIigqsDERGVYtYESvv27REREQGgZP6TtWvXYsyYMahTp47R+iKRCA4ODujQoQMaNWpkzlABAJcvX8YPP/yA3377DcnJySgqKoKbmxvatWuHsWPHokmTJgb7vPzyy/jnn3/KbXPu3LkYNmyY3ra7d+9iwYIFOH/+PCQSCbp06YJZs2bB2dnZYP/c3Fy89tpraNWqFVauXPn0J0lUAZlMhuDgYOTn5wsdigF+M0ZERM+LwMBAhISECB0GERGZYPYESvv27XU/x8TEYNy4cXBxcTFnGJVy4MABTJs2DV5eXpg5cybatGkDAPjll1+wYMECHDx4EEuWLEG/fv0M9vXw8IBUKjXaroODg97PhYWFePvtt+Hq6orDhw8jLy8PEydOxOTJk7F161aD/b/88kvk5+dj9uzZVXCWRBWTy+XIz8/nN2NERERERFSrCTqJ7JYtWwwSCjWFdnnlNWvWoHnz5rrt/fr1Q506dfDuu+9i9uzZ6NSpk8E5LFmyBB06dKjUcQ4ePIiUlBQsWbIEHh4eAIBJkyZh+vTp+O2339CuXTtd3QsXLmDHjh1YunSp0btTiKoTvxkjIiIiIqLaTCzkwdu3bw+JpOIcTlFRES5dumSGiP7l5OSErl276iVPtLp06QIrKyvk5+fjwoULT3WcxMREANB7HEj7/xs3bui2FRQUYNasWejcuTP69+//VMckIiIiIiIioscj+DLGlZGVlYURI0aYdXm3Hj16oEePHkbLxGIxbG1tUVhYWKllmE0pLi4GoL+cs1hcktcqKirSbYuKikJGRgY2bdr0VMcjIiIiIiIioscnaALlt99+q1S9rKys6g3kMWVmZiIrKwtSqRStWrUyKD969ChWrVqFW7duIT8/H25ubnjhhRfw9ttvw9/fX6+u9ufr16+jdevWAP69KyUgIAAA8Pfff+Obb77Bp59+qnvMh4iIiIiIiIjMR9AEysiRI5/6Dg4h7NmzB0BJ/MbmIjl79iw+/vhjtGvXDmq1GmfOnMH8+fPxww8/YOXKlXj55Zd1dfv164eoqCisXLkSa9euRUFBAdavX4+goCC8+OKLKCoqwsyZM9G6dWu89dZb1XZOZVdYsbCwgLW1NdRqNZRKpUF9W1tbAIBSqYRardYrs7KygkQigUqlgkql0isTi8WQSqXQaDRQKBQG7drY2EAkEqGgoEB3d46WpaUlLC0tUVRUhMLCQr0ykUgEGxsbo+cCAFKpFGKx2Gi7EokEVlZWKC4u1s19Y6xdhUIBjUajV25tbQ0LCwsUFhbq3TEEVL4PjbVrqg+17VbUh8ZeG1N9qH1tAP0+NHaMmuZJ+7C818ZUH2rbNdWH5b02pt6HVfH+NvY+NPX+Bgzfh8/C603PNoVCofc+ruj9bWqc1b6/q2uc5Rhhug+1r82T9KFQv0fQ4yt9zT7J7xFalXl/V/S72PMwRpSNkaiq/f7771AoFLrrRqlUGry/LS0tdZ9Vxt7fVlZW0Gg0Rt/fUqlUN84a+1vDWLuurq5o0KBBtYwRGo3GrDkFwR/hcXd31z2yUlpmZqbuBfP09DR3WOVKS0vDV199hRYtWmDy5MkG5QsWLECzZs1gb2+v29arVy/Y29tj9OjR+Oijj/Dzzz/rEi92dnZYu3YtPv30U93Es61atcKiRYsgFosRGxuL27dvY//+/RCJRLh8+TKio6Nx48YNODo6YtCgQRgzZsxTvWmKi4sNHo9ydnaGn58fCgsLjT46pV2V6M6dO8jLy9Mra9iwIVxcXPDw4UMkJyfrldnb26NRo0ZQq9VG2w0JCYGlpSWSk5ORnZ2tV+bt7Q13d3fk5OTg1q1bemU2NjZo2rQpAODatWsGg0TTpk1hY2ODtLQ0PHjwQK+sfv368PLyQn5+vt68M0DJxaqdODUxMdFggGncuDHq1q2LjIwM3Lt3T6/MxcUFDRs2REFBgcG5ikQi3R1Ht2/fNvgl0N/fH05OTsjMzERKSopemYODAwIDA1FUVGS0D1u1agULCwskJyfj0aNHemU+Pj5wc3NDdnY27ty5o1dWp04d3fw7pdstW68munXrlsEAHxAQAEdHR8jlcqSmpuqVOTo6IiAgoNw+DA0NhUgkwt27d5Gbm6tX1qBBA7i6uiIrKwt3797VK7Ozs0NQUBA0Go3Rdlu0aAErKyukpKQY3Fnn6ekJDw8P5ObmIikpSa9MKpWiWbNmAEruViv7YRUcHAxbW1vcu3cPGRkZemVubm7w8fGBQqHA9evX9cokEglatmwJAEhKSkJBQcEz8XrTs+3OnTt6K9VZW1vr5htLTEw0+OMiKCgIdnZ2uH//PtLT0/XK6tWrB19fXyiVSoNrTiwWIzQ0FADHiKocI0oLDAyEg4MDMjIykJaWpldWU3+PoMdX+pp9kt8jtJo1awapVIrU1FRkZmbqlXl4eMDT0xO5ubm4efOmXtnzNkbk5OQY1CeqCunp6RCLgPDwcKFDMSCVWuHQocO6GwmqcoxQqVSwsrKqvuDLEDyBsnv37nKXMb5//z527tyJpKQkrFixwsyRGcrNzcWkSZPg7u6O9evXG32hXnjhBaP7duzYEY0aNUJiYiIOHz6MESNG6MpatmyJH374AVlZWZBIJLCzswNQ8stKTEwM3n//fTRs2BB3797F6NGj0a1bN2zYsAG///475s+fj8LCQkyYMOGJz8vCwgLBwcEG24CS7HvZstIaNmxo9JsjoGQiXu25aGmTZWKx2Gi72kmFfXx8DBJn2m+O6tata7Bv6QRS6Ql5taytrQGUXHxubm5Gj2lra2uy3UaNGhn99g0o+YB2cnLSK9P2obW1tck+9PPzM/qtB1DyC2jdunWNtiuRSIy2q+1jHx8fo1lhoCQJU3bf0onM0mXGMs81jb+/f7l96OrqarBSVkV9qH3dGzRoUO7729HRUffNlZa2D0Uikcn3t7e3t8HjeNrXxs7OzuT7MCgoyKBd7S+29evXh6urq9Fj2tjYmHwfBgQElPtNA1FVatiwod57sew4W5Z2nHV3dzf4fUH7/pZKpSbf3xwjqm6MKK30Z6Cjo6NemYWFBWQyGdLT043e2aJdHMDYN5hJSUm4e/eu0W9GCwsLkZOTU+54deXKFYhEIhQWFhp8g3n37l3dY9JUeaWv2Sf5PUJLe214enrC3d1dr6yy7+/nYYz466+/yo2D6GlkZ2dDrQGWR7ogwKvm3HGX9I8KU6Me6O6IAap2jDD33YWCJlBeeuklk9kid3d3TJ48GZs2bcL69evx3nvvmTE6fbm5uXjnnXegUqmwadOmcpM+pvj6+iIxMdEga6ZV+pcPtVqNTz/9FI0bN8bYsWMBAOvXr4dYLMaCBQt032KdP38e69atw9ixY58q81b2lzwt7YS55Sn9LWJZ2lutjBGJRCbb1X4YGiORSEyu3vSk7VpYWJjct/RFX5aVlVW5/V9RH5pq92n60NRr8zh9aCq+muJJ+/Bp3t+m+lCo97ep92Fl39/PwutNzzYbG5ty34tP+v6urnGWY8S/HrcPZTIZmjRpwscCnwPGrlmhfhd7HsaIyqxASvQ0Arws0dy//OtMKKWv/aocI8w9JYigV/CGDRsqVa979+4IDw8XLIHy8OFDjB8/HhYWFti6datBFrqytJntyrzI27Ztw59//oldu3bpstzXrl2Dn5+f3l0dISEhOHjwIO7evWs0K09ERFSTmHNFvcpydXWFr6+v0GE8V+RyORQKBbp162Zwh6aQZDIZLly4IHQYRET0jHomUqCPHj0yeLbWXO7fv4/w8HC4uLhg7dq1qFOnjq4sLi4O9evX181lsXHjRsTHx+Pbb7812pb2WWjt6jrl+eeff7BixQqMHz9e73EUtVqtS6ZoabPYZW9TJSIiqkm0z2aHhYUJHYoBWxspEq5dZxKlGjg5ORk8NiSkhw8fCh0CERE9w2p8AkWtVuObb7554rs+nkZycjLGjBmDxo0bY/Xq1Qa3BW7fvh3t27fXJVDy8/Nx+fJlpKSkGExUdubMGSQlJcHW1havvPKKyeN+9tln8PT0xMSJE/W2BwYGIj4+HgUFBbpbm65duwYrKys0bNjwKc+WiIio+tT0Z7PlcjkTKERERGSSoAmUGTNmlFumVquRnZ2Nv/76Cw8ePMAbb7xhxsiAmzdvYuzYsXjw4AGaNWuG6dOnG63Tvn173c8ikQgqlQrvvvsupk+fjpYtW8LCwgL/93//h88//xzW1tZYtmyZyflT9u7dizNnzmDHjh0GCZtx48YhLi4Oy5YtQ2RkJK5cuYIffvgBo0ePNvkcNhERUU1RU5/NJiIiIqqIoAmUvXv3QiQSGcx6XVZISAg++ugjM0VV4vDhw7ql0H788cdK7TN+/HgEBQXhyJEjmDt3Lu7fvw+RSIT69eujW7duGDNmjMnHd+RyORYvXoyRI0fqlg0srUmTJli7di1Wr16N//znP3B0dERYWBjef//9JztJIiIiIiIiIqoUwR/hGTNmjN68IlpisRj29vZo1qyZbo12c4qMjERkZORj7WNtbY2ePXuiZ8+eT3RMV1dX/PrrrybrdO3aFV27dn2i9omIiIiIiIjoyQieQBk3btwTLQlM9DRkMhnkcrnQYRgoPb9NTVETV8wgIiIiIiIyN0ETKJ9//jnq1q0rZAhUC8lkMjRp0gQKhULoUAyIxWKo1WqhwyAiIiIiIqIyBE2gvPnmm0IenmopuVwOhUKBbt26wcnJSehwdGQyGS5cuICpU6carOIkpIsXL2Lr1q1Ch0FERERERCQoQRMoSqUSq1atgkajgVQqxQcffKBXPmfOHDRs2BCjRo2ChYWFQFHS88rJyQmurq5Ch6Hz8OFDAIC3tzcCAwMFjuZfycnJQodAREREREQkOEETKD/++CM2bdoEkUiEDh06GJQXFBRgyZIlOHv2LGJiYmBpaSlAlERERERERERU24mFPPiJEyfg7u6OvXv3YtOmTQblixcvxpYtW3DlyhXs2rXL/AESEREREREREUHgBMrVq1cxZcoUNGnSpNw67du3x+TJk7Fnzx4zRkZERERERERE9C9BEyjp6elo2bJlhfU6dOgAmUxmhoiIiIiIiIiIiAwJOgeKWCyGRFJxCBKJBIWFhWaIiIiIiIiItBISEoQOwYCrqyt8fX2FDoOIaiFBEyje3t44fvw4xowZY7LeiRMnatSyrkREREREz7P09HSIRUBYWJjQoRiwtZEi4dp1JlGIyOwETaC8/PLLWL16NVxdXdGvXz+jdQ4cOIDVq1dj9OjRZo6OiIiIiKh2ys7OhloDLI90QYBXzVkJM+kfFaZGPYBcLmcChYjMTtAEyttvv429e/di2rRpWLp0KVq2bAlnZ2cAwIMHD3DlyhVkZGTAzc0NY8eOFTJUIiIiIqJaJ8DLEs39rYUOg4ioRhA0geLg4ID//ve/mDhxIlJTU/Hzzz/ryjQaDQDAy8sLX331FRwcHIQKk4iIiIiIiIhqOUETKAAQFBSEuLg47Nq1CydPnkRqaioAwNPTE126dMEbb7wBGxsbgaMkIiIiIiIiotpM8AQKAEilUoSFhdXISaqIiIiIiIiIiMRCB0BEREREREREVNPViDtQcnNzsW/fPpw/fx7p6elYvXo13N3dsXv3brz00ktwd3cXOkQiIiKiGkkmk0Eulwsdhp6EhAShQyAiIqpygidQzp49iw8//BBZWVnQaDQQiUQoLCwEAHz77beYO3culi9fjl69egkcKREREVHNIpPJEBQUBKVSKXQoREREzz1BEygymQzvvfceFAoFAgMD4evri1OnTunKV61ahTVr1uDDDz/Enj170LhxYwGjJSIiIqpZ5HI5lEolHB0dIZEI/r2YjlKpRG5urtBhEBERVSlBP2k3bNgAS0tLrF+/Hu3btwcAhIaG6sobNmyIFStWIDIyEl9//TUWL14sVKhERERENZZEIoGVlZXQYegUFRUJHQIREVGVE3QS2XPnzmHatGm65El5Ro0ahd9//908QRERERERERERlSFoAuX+/fto06ZNhfW8vLxw//59M0RERERERERERGRI0ASKRCKp1POxcrm8Rj3XS0RERERERES1i6AJlMDAQOzatavCet999x2CgoLMEBERERERERERkSFBb+t47bXXsGDBAhQVFeGdd95Bw4YN9cplMhnWr1+P/fv3Y968ecIESU9NJpNBLpcLHYZOQkKC0CFQFaqJr6erqyt8fX2FDoOIiIiIiKqQoAmUoUOH4uDBg9izZw/27t0Le3t7FBYWIjw8HLm5uXj48CEAoHXr1njjjTeEDJWekEwmQ1BQEJRKpdCh0HMmPT0dYhEQFhYmdCgGbG2kSLh2nUkUIiIiIqLniKAJFEtLS/z3v//FrFmz8NNPPyE7OxtAyR/dWq+88gq++OILWFhYCBUmPQW5XA6lUglHR8caM4+NUqms1Nw7VLNlZ2dDrQGWR7ogwMtS6HB0kv5RYWrUA8jlciZQiIiIiIieI4L/RVu3bl2sWbMG169fx6lTp5CamgoA8PT0RJcuXdC4cWOBI6SqIJFIYGVlJXQYAICioiKhQ6AqFOBlieb+1kKHQUREREREzznBEyhaQUFBnCiWiIiIiIiIiGokQVfhiY6OhkKhqLCeXC5HcHCwGSIiIiIiIiIiIjIkaAIlJiamUgmUlJQUM0RDRERERERERGScoAkUjUaDFStWmFyhZdu2bRgzZoz5giIiIiIiIiIiKkPQBAoAXL58Ga+//jquXbumt/3hw4d499138cUXX3AJXCIiIiIiIiISlOAJlA0bNuA///kPhgwZgk2bNgEAzpw5g/79+yM+Ph5169bFZ599JmyQRERERERERFSrCboKz7Fjx1C/fn18+umnaNu2LT799FPs2bMHN2/ehFqtRkhICFasWAFHR0f8+eefQoZKRERERERERLWYoHegeHl5QSQSAQA8PDxgZ2eHGzduQK1WY+DAgdi+fTu8vb1hZ2eHRYsWCRnqY1GpVIiNjUW/fv0QEhKCjh07YtKkSbh69apB3fz8fHz22Wfo0KEDQkJCMHLkSKP1tCZNmoQePXpUavJdIiIiIiIiIqoagiZQRo0ahUePHmHTpk0ICwvD/fv34erqil69euH48eM4fPgwgJKExG+//SZkqJVWWFiI8PBwrFmzBmPGjMG5c+ewfft25OTkYOjQoYiPj9erP3v2bBw9ehTr1q3DiRMnYGdnh7Fjx+Lhw4cGbcfFxeHnn3/G559/DhsbGzOdEREREREREREJmkA5f/48Jk+ejCVLlkClUqFbt244cOAA1qxZg7lz52L+/PmYOnUqkpOTMWrUKCFDrbSvvvoKv/76K959910MHjwYtra28PPzw5o1a2Bra4uPP/4YWVlZAIDk5GQcOnQIYWFhCA0NhYuLCz799FNkZ2dj27Zteu1mZWXhiy++wJtvvokXXnhBgDMjIiIiIiIiqr0En0T2119/hVQqxbx587B27Vo4OzsDAPr27Yt9+/YhPT0dI0aMEDjKyikoKMDmzZsBAEOHDtUrc3R0xCuvvILs7Gzs2LEDAHDz5k1oNBoEBwfr6nl5ecHBwQE3btzQ23/hwoWwsLDA9OnTq/ksiIiIiIiIiKgswRMoTZs2xZ49ewwSDgDg6emJLVu2PDMJlHPnziEvLw8NGjRAvXr1DMrbtGkDoGTyXAAoLi4GAN08MFoikUhXBgCnTp3C/v37MWfOHNStW7e6wiciIiIiIiKicgieQFm3bh38/PzKLReJRHjrrbeg0WjMGNWTSUhIAAD4+PgYLddu106U6+/vDwC4fv26rk56ejqysrIQEBAAAMjLy8OcOXPQt29f9OjRozrDJyIiIiIiIqJyiDQCZiZmzJiBWbNmwc7OzmS9goICxMXF4fXXXzdTZE/m888/x9atW/Hqq69ixYoVBuVJSUno27cvgJJHlxwdHTF+/HgkJCRg8+bN8PHxwezZs3HkyBEcOXIEHh4emD9/Pg4dOoTDhw/rHm+qSjY2NigqKoK3t7dBmfbOGGNvkcqUAYBSqURaWhrEYsFzdToajQYajQZSqbRGxVVUVITCwkI4ODjAwsJC6HB0CgsLkZubCxcXF1haWgodjo5CoUB2djac7cWwlIgq3sFMVEUaZD5Sw8PDA9bW1npllb1unvSaK284f5x9CwoKatw1C9TM65bX7ON51q7ZqvgMrMprubx2ec0+npp43fKafTxlr9mq/Aw0VvY0+xorKywsRGpqao26LgBes4+rJl63Nf2a9fT01H3OVuX1mJKSAolEYrZVaiVmOUo5Krs0sbW1dY1PngDQvWjlXURWVla6/yuVSgDA4sWLMWPGDPTr1w8WFhaoX78+1qxZAw8PD1y4cAHfffcdli5dCmdnZ9y/fx8rVqzA+fPnIZFI0LlzZ3zwwQcVJqBM0b6Jyz5GVNqTlgGAVCo1eYcRPRuMPZImNBsbm2pJKlYFBxfT5RVdN9V1PVZmX16zzwdes4/H1DVb3dfc07bLa/b5wGv28Ri7ZqvrenyafY2VWVtb85p9TtS06/ZZumar8nqUSCQGX1pWJ0ETKKYUFxfj0qVLetvatWsnUDSVo11aWKVSGS0vLCzU/V8qlQIAXFxcEBsbi/z8fCiVSt2bvqCgAJ9++ik6d+6M/v37Q6VSYezYsRCJRFixYgUUCgU+/vhj3LlzBxs3bnzimLUrAhERERERERFR+cyaQCm92szZs2fh6OhYbt38/HyMHDkSIpEIGo0GYrEYf//9txmifHLaLGR2drbRcu12qVQKe3t7vTJbW1vY2trqfo6OjkZ6ejq++eYbAMChQ4eQlJSEb775BqGhoQCAyMhIfPbZZ7hw4QLatm1b5edDRERERERERCXMmkDRaDSYOXMm6tatizp16pisa2dnp1ut5vbt2xg/frw5Qnwq2gRRcnKy0XLt9saNG5t8tvDvv//G119/jU8//RQeHh4A/p1oNiQkRFevZcuWujImUIiIiIiIiIiqj9kf4Xn11Vfh4lLyENSoUaMMyrds2QKg5NkmLy8vACV3ozwLOnbsiDp16kAmk0Eul8PV1VWvXPtIkqnVdIqKijBr1iy0bt0ab731lm67dlnj0okX7URKpZc8JiIiIiIiIqKqJ+gUy15eXrp/ly5dMvlIz7PA2toao0ePhkajwc6dO/XKHj16hCNHjsDBwQFDhw4tt42NGzfi1q1b+Pzzz/UmyGnUqBEA/SWPr127pldGRERERERERNWjxqzCc+TIEUybNk3AaKrGxIkTceHCBaxbtw4eHh7o06cP7t+/j7lz5yI3NxfR0dHlJopu376NmJgYTJ48GQ0bNtQre+211xATE4OlS5dixYoVUCqVWLt2LVq1aoWOHTtW/4kRERERERER1WI1Z5Hv54SVlRU2btyIyMhIbNiwAe3bt8fQoUNha2uL77//Ht26dTO6n0ajwaxZs9CoUSOMHTvWoFwqleLrr79GnTp10KdPH7zxxhsICgpCdHR0hUs9EREREREREdHTEWk0Go25DtakSRP88ssvujlQSgsNDcWBAwfg4+NjUJaYmIj+/fsjISHBHGESEREREREREenhHShERERERERERBUwewKFj5sQERERERER0bPG7I/weHh46C3Fq5WWlgY3Nzfd0rylFRUVIT09nY/wEBEREREREZEgzL4KT1paWrll9+7dK7eMd64QERERERERkVDMnkAZO3Ys6tSp81j7PHjwADt27KimiIiIiIiIiIiITDN7AmXcuHFGV+Ex5caNG0ygEBEREREREZFgzDqJbK9evWBtbf3Y+9nb26Nnz57VEBERERERERERUcXMOoksEREREREREdGzyOzLGBMRERERERERPWuYQCEiIiIiIiIiqgATKEREREREREREFWAChYiIiIiIiIioAkygEBERERERERFVgAkUIiIiIiIiIqIKMIFCRERERERERFQBJlCIiIiIiIiIiCrABAoRERERERERUQWYQCEiIiIiIiIiqgATKEREREREREREFWAChYiIiIiIiIioAkygEBERERERERFVgAkUIiIiIiIiIqIKMIFCRERERERERFQBJlCIiIiIiIiIiCrABAoRERERERERUQWYQCEiIiIiIiIiqgATKEREREREREREFWAChYiIiIiIiIioAkygEBERET2jevbsiaCgIN2/X3/99anb/OSTT/TajIqKqoJIiYiInn0SoQMgIiKimuO9997DsWPHjJZZWVnB3t4eHh4eaNmyJXr27ImOHTtWSxzaP9pHjx4Ne3v7ajlGWSNHjsT58+f1tk2fPh1vv/12pfa/f/8+evbsiYKCAt02Ly8vHD9+vErjLG3nzp0oLi7G4MGDce/evSppc9asWZg6dSoWLFiAw4cPV0mblXHv3j2cPn0ap0+fxtWrV5Geng6NRgMXFxe0aNECb775Jrp06WK2eIiIiMpiAoWIiIh0Fi9ejIKCAnz99df4+uuvUb9+fezatQsAoFQqkZGRgd9//x27d+/G1q1b0aRJEyxcuBDNmjWr0jiio6MBAK+//rrZEihRUVFQqVS6cweA9evXY8iQIbCzs6tw/5iYGF3ypE+fPpg1axYsLCyqNWZnZ2cAqNLj1K1bF3Xr1oVUKq2yNitj+PDh+Oeff/DKK69g4cKF8PLyQm5uLs6cOYOoqCgcPXoU48aNw7Rp08waFxERkRYf4SEiIiIde3t71KtXD7a2tgBK/jCvV68e6tWrBx8fH7Ru3Rpvv/02Dh48iKlTp+L69esYOnQoTpw4IXDkT8/R0VF37nXq1IGlpSWysrKwYcOGCveVyWTYs2cPHB0dAQBSqRT16tXTJTiocl588UWsXr0aHTp0gLe3N5o0aYK3334bM2fOBABs3Lixyu60ISIielxMoBAREdFjE4lEeOeddzBhwgSoVCpMmTIFd+/eFTqsKuPo6IihQ4cCADZv3owHDx6YrL9mzRq8+OKLaNy4sTnCey7NmTMHn376qdGykJAQAIBGo0FmZqY5wyIiItLhIzxERET0xN577z3s2rULcrkcK1aswOrVq3VlKpUKp0+fxtGjR/Hnn38iLS0NRUVF8PT0RJcuXTB+/Hi4uLjotVd2HpLu3bvrlR87dgze3t7QaDQ4d+4cjh49iosXLyItLQ0KhQLu7u548cUXMX78ePj4+DzVuU2cOBF79uxBfn4+vvrqq3L/uL9x4wbi4uKwa9cuLFq0qMJ2s7Ky8M033+D48eNITk4GAPj4+ODll1/G2LFjdXexlHX16lXExMTg4sWLUCgU8PLywmuvvYZx48ZVeMzMzExs3LgRx48fxz///AMLCws0aNAAPXr0wOjRo1G3bt0K26jInj17MGPGDIPtW7ZsQYcOHQAYvr7t27fHt99+CwAm5ze5fPkyAKB+/foIDAx86liJiIieBBMoRERE9MSsra3Ru3dvbNu2DcePH4dCoYCNjQ0A4Pbt25g4cSKaNGmCDz/8EI0aNYJSqcSlS5cQFRWFQ4cOYfv27fD29ta1p52H5KWXXgIA/O9//4OHh4euXPtITH5+PsaMGQMvLy989NFHaN68OVQqFf7++29ER0fj4MGD2LJlC5o3b/7E5+bq6opRo0Zh3bp12LFjB8aMGaMXq9bq1avRo0cPNG3atMI2r1+/jvHjxyM7OxuTJ0/WJYiOHz+O1atXY+/evdiwYYPBnSzHjh3D+++/DysrK3z00Ufo1KkTFAoF9u/fj0mTJkGtVpd7zGvXrmHcuHHIzs7G+++/j86dO6OgoAA//fQTYmJicODAAWzevFmvn59E37590alTJ4SHh+P69et45513MGrUKDg4OOjqREVF4c6dOxg6dCjWr1+PVq1aldtecXEx0tPT8eOPP2LlypUICAjAl19+CSsrq6eKk4iI6EnxER4iIiJ6KtrHKwoLC3H16lXddktLS3h7eyM2NhYvv/wyfHx80KhRIwwdOhQrV65Eeno6lixZoteWdh4SLWdnZ90cLPXq1dNNlioWi+Hl5YXVq1ejb9++8PX1RUBAAF577TVs3LgR+fn5+Oyzz5763MaNGwdHR0eoVCqsWbPGoPzKlSs4ceIEJk+eXGFbCoUCEydOxP379zFv3jyEh4ejYcOGaNiwId5++23MnTsX9+/fx8SJE6FQKHT7PXjwAJ988glUKhUWLFiA4cOHw8fHB40bN8a0adPg6emJtLQ0o8fMz8/HxIkTkZGRgXnz5mHcuHFo3LgxWrRogalTp+K9997D3bt38cknnzx5J/1/2nlfhg0bBgA4cuQIXF1d9RIejo6OOHHiBAICAtC1a9dy77aZP38+mjdvjq5du2Lt2rWIjIzEvn37KpWkIiIiqi5MoBAREdFTKT1Rqlwu1/3fz88Px44dg7u7u8E+rVu3BgCcPHkSKpXqsY9pY2OD48ePo0WLFgZl3t7ecHd3x9WrV596wtG6deti/PjxAIAffvgBiYmJeuWrVq3Cq6++WqnHSnbv3o1//vkH9erVQ//+/Q3KBwwYgHr16iElJQW7d+/Wbd+1axcePXoEd3d3vPLKKwb7jRkzxuQxU1NTUa9ePQwcONCgfMSIEQCAc+fO4dq1axWeQ2X0798fderUgUwmwy+//KJXVlRUhN27d+vmlylPREQE4uLisG3bNgwbNgxRUVEYMGAA/vzzzyqJkYiI6EkwgUJERERPRaPRlFuWlpaGxYsXY+DAgejYsSNCQ0MRGhqKtm3bAgAKCgqeeFLQrKwsrFmzBm+++SZefPFFXduhoaG4f/8+ACA1NfWJ2i4tLCwMbm5uUKvVWLFihW77+fPn8euvvyIyMrJS7cTHxwMouWNHLDb8FUwsFusSQqdOndJtP3fuHACgRYsWEIlEBvs1bNgQlpaWRo958uRJk8d0dnbWLdH822+/Veo8KlKnTh1dgmjHjh16ZceOHcOjR4+MJnPKxuXn54e2bdvigw8+wMaNG3Hnzh0MHz4cf/31V5XESURE9Lg4BwoRERE9ldIJEFdXV93///jjD7z99tvIy8vD8OHD0bt3b7i7u+uSAL169QKAJ7oDRSaTYcSIEUhPT0ffvn3xwQcfoH79+rpHfEaOHIn79+8/UdtlSaVSTJo0CXPmzMHx48dx+fJlhIaGYsWKFRg0aBB8fX0r1Y42mVO6j8rSlv3zzz+6bdq7aMpOuKslEong6upq9DEe7TFPnTqF0NBQo/trHxfSJp2qwvDhw7F9+3acOHEC9+/f192FtHPnTvTp00dvXpTKaNu2LV566SWcOnUKUVFRWL9+fZXFSkREVFmCJlCio6MRHh6um2yOiIiInj1XrlwBUDKhbLNmzXTbZ8+ejdzcXAwePLhK5iMpbdGiRUhPT8cLL7yAlStXGpRLJFX7K87gwYPx9ddf4+7du1ixYgXCw8Nx9epVo8euiXr37l3hPC1VsRKPVuPGjdGmTRtcvHgR//vf/xAREQGZTIYzZ87gu+++e6I2W7RogVOnTuHixYtVFicREdHjEPQRnpiYGGRnZwsZAhERET2FgoIC/PjjjwBKlhzWfiny8OFDXL9+HQDQuXPnKj+u9rGW6mjbGIlEgvfffx9AyaM7M2fOxNChQx9r5RpPT08A+vPElKUt8/Ly0m2rX78+gJLJZI3RaDTltqk9pkqlQoMGDUz+Kz2XTVXQTia7a9cuFBcX4/vvv0ejRo1089+UduvWLWzfvh3FxcXltqd9TKmwsLBK4yQiIqosQRMoGo0Gr732Gr744gskJSUJGQoRERE9gbVr1+LBgwewsbHBhx9+qNtual4UABVO7mpsro/MzEzk5uZW2H5xcTEyMjJMtv8k+vbti+DgYAAlq9u8++67j7V/ly5dAJQ82mRs2WG1Wq27m6d0YuiFF14AUHKnj7HzvnPnTrmPKpU+Znl99sMPP2DAgAFVNomsVu/eveHs7Iy0tDT8/PPP2LNnT7mTx/7++++YO3cu7t69W2572oRcw4YNqzROIiKiyhJ8EtlJkybhr7/+Qr9+/TBy5EjExcWhqKhI6LCIiIjIBI1Gg/Xr12P9+vWwtLTE6tWr4ePjoyt3dnbWzQ1y4sQJg/0PHjxosn3tHBn5+fm6bT179sRXX30FAGjVqlW5bf/000/VcpeCSCTCJ598gu7du+Ojjz4yOZeJMW+88Qa8vLwgl8uxf/9+g/L9+/dDLpfDy8sLb7zxhm774MGDYW9vj/T0dBw5csRgv02bNlV4zHv37hk9Zm5uLqKjo1FUVIQmTZo81vlUxMrKCoMHDwYAfPbZZ8jPz8eAAQNM7lPe4z3Xrl3Dzz//DAC6NomIiMxN8ElkX3vtNYwZMwbXrl3Dzp078dlnn2HBggUYPHgwhgwZoncLKxEREVWvR48eoaCgQJe4KH03h1KpxIMHD3D58mXs2rULN2/eRHBwMBYuXIimTZsatPXJJ58gIiIC+/btg4ODAwYMGAArKyscO3YMsbGxunqZmZmwtrZGvXr1dNs6dOiAH3/8EXv27MGIESPw008/ITc3Fy+++CIAYOrUqQgLC8P58+cxbdo0jBw5EnXr1sXZs2exatUqSCQSFBUVITs7GxkZGXB2dtZNMFuenJwcKJVK5Ofn65136X07duyIjh07GuybmZmJ4uJi3Z0gSqUSGRkZsLS0hKOjIwDA1tYWX331FcaNG4e5c+ciMzMT3bt3BwAcP34cq1evhru7O9atW6c3P5yzszOWLVuGiIgIzJo1C1lZWXjppZegVCqxb98+XLp0CS4uLnjw4IHufB0cHGBlZaU75vjx4zF79mykpqaiZ8+ekEqluHbtGqKjo5GTk4Nvv/3WoB+USiWAkiRWRkYGbG1tUadOHZN9WNbQoUOxYcMGZGVlYdCgQeXOs6Lt32+//RaZmZl488034e3tjaysLJw9exZfffUVVCoVBg4cqFt6mYiIyNxEmorusTUzhUKBH374ATt37kRCQgJeeuklDB8+HF26dDF6Oy8RERFVnffeew/Hjh0zWmZpaYm6devC09MTrVq1Qo8ePXSPl5TnwoUL+Oqrr/DHH39AoVDA2dkZ7dq1w4QJE3RL3WppH9EAgIyMDMyfPx/nzp2DUqmEl5cXRo4cqffH8/Xr1xEdHY3z588jJycHDg4OaNmyJcaNG4ePP/5YbyWbY8eOwdvb22Ssn3zyCfbu3WuwvTL7vvzyy3rH02rfvr1ecgIomR9m06ZNOHbsGJKTkwEAPj4+6N69O8aMGQMnJyejx/j7778RHR2NCxcuID8/H+7u7nj55ZcxadIkDBo0SO/433zzjS7ZBJQs+aw9pkwmg0QigaenJ7p27YpRo0bpJa/K64eIiIhKL9lc2jvvvIOTJ0/i+++/R8uWLcutd/HiRfz000+4dOkSZDIZcnJyYGlpiXr16qFly5Z4/fXX8dJLLz328YmIiKpKjUuglHby5El89NFHyM3NhYeHB4YMGYLBgwc/9i2zRERERERERERPQ/A5UIw5f/48PvzwQ0RERCA3NxcajQa5ubnYt28funbtiqlTpz7xpLPFxcXYtGkTWrdujZdffrnC+levXkVERAQ6duyIkJAQ9OvXD7GxseVO1gaUzHQfGxuLfv36ISQkBB07dsSkSZNw9epVo/Xz8/Px2WefoUOHDggJCcHIkSPLrQuUzBvTo0cPKBSKik+YiIiIiIiIiJ6aoAmU4OBg3ZJ8OTk52LJlC1599VWMHj0acXFxUKlUaNasGRYsWIBTp07hyJEj+Oabb1BcXIxBgwaVe4txeS5evIjXX38dX331FfLy8iqsHx8fj6FDhyInJwfbt2/HuXPnMGbMGKxZswbh4eFGJ6grLCxEeHg41qxZgzFjxuDcuXPYvn07cnJyMHToUMTHxxvsM3v2bBw9ehTr1q3DiRMnYGdnh7Fjx+Lhw4cGdePi4vDzzz/j888/13s+moiIiIiIiIiqj6CP8DRp0gTr1q3D0aNHERcXB6VSCY1GAxsbG7z66qsYNmwYmjVrZnTfPXv2YOPGjTh06FCljnXo0CF8+umneO+999C0aVO8/fbb8PLywvHjx43Wf/jwIXr37g0AOHr0qG41AACIiopCdHQ0Jk2ahMmTJ+vtt3r1aqxduxaRkZGIiIjQbc/KykKvXr0AlKwOoJ1QLjk5GT179kRkZCQmTZoEAPjnn3/w8ssvG22jb9++ePnll/HFF19U6ryJiIiIiIiI6OkJ/gjPxIkTsXv3bigUCvj7+2PWrFk4deoUvvjii3KTJwDQrl073cRrleHl5YW4uDiMHz8eEknFiw/t2LED2dnZ6NOnj17yBCiZUR4ANm/ejIKCAt32goICbN68Wa+OlqOjI1555RVkZ2djx44duu03b96ERqNBcHCwXqwODg64ceOGXhsLFy6EhYUFpk+fXsmzJiIiIiIiIqKqIHgCxcLCAn369MGWLVtw6NAh3TKEply7dg1LliyBra1tpY/TqlUreHh4VLq+9vGgNm3aGJS5ubnB19cXubm5OHfunG77uXPnkJeXhwYNGujNZq+lbav0o0fFxcUAYLDCkEgk0pUBwKlTp7B//37MmTOnwv4hIiIiIiIioqoleALlwIEDWLlyJdq3b1/pfc6fP4+0tDR07969WmIqLi7W3f3h4+NjtI52+7Vr13TbEhISKrXPjRs3oFarAQD+/v4A9JduTE9PR1ZWFgICAgAAeXl5mDNnDvr27YsePXo88XkRERERERER0ZOp+FmWavT666/Dzc3tsfcbNWoURo0aVQ0RlXj06JHu0Zyyj+9o2dvbAwAyMjJ027T/L28f7XalUolHjx7B0dER/v7+6Ny5M7Zu3YqePXvCx8cHy5cvh1QqxbBhwwAAy5cvR35+PmbPnl01J1iKo6MjCgoKHuvuHCIiIiIiIiKhpaWlwdraGllZWWY5nqAJlEWLFpksT05OLvdujuqkVCp1/7e0tDRax8rKCgD0lhLW/r+ifcoeY/HixZgxYwb69esHCwsL1K9fH2vWrIGHhwcuXLiA7777DkuXLoWzszPu37+PFStW4Pz585BIJOjcuTM++OAD2NnZPdG5FhQUQKVSGawoJBaLIZFIoNFojC7ZrD0XlUqFsvMQSyQSiMViFBcX6z2GBJQ8mqTtH2OrGJlq18LCAhYWFlCr1SgqKnqsdi0tLSESiVBUVKS7+6dsuxWdq6l2jZ1rbexDY+2Wjulx262uPqyKds3Zh0/TbmXP1Vi71d2Hz9r7m2MEx4jHaZdjRO17f3OM4BjxOO1yjKh972+OEdXz/jZ27tVJ0ARKcnIyBg8eDI1GAzs7O4MVcT777DPI5XKsWLECjRo1MltcUqlU9//yXhDti156KWHt/yvap+wxXFxcEBsbi/z8fCiVSjg7OwMoSW58+umn6Ny5M/r37w+VSoWxY8dCJBJhxYoVUCgU+Pjjj3Hnzh1s3Ljxic5Ve+fJX3/9pbfdwsIC1tbWUKvVeskeLe38M0ql0uANbmVlBYlEApVKZdAXYrEYUqkUGo1GL/mkZWNjA5FIhIKCAoOL2dLSEpaWligqKjK46EQika7/8/PzDdqVSqUQi8VG25VIJLCyskJxcbHepMBl21UoFAaDhLW1NSwsLFBYWGhwMVe2D421a6oPte1W1IfGXhtTfah9bYDH70NtuxX1obF2TfWh9rWprj4sr11Tfaht11QflvfaVKYPn+b9baoPjb02gOk+1L42T9KHHCNKcIzQb5djBMeIsu1yjOAYUbpdjhEcI8q2yzGCY0Tpdo31YbNmzQzmE61OgiZQfvjhB2RnZ6NFixYYMmSIQfkbb7yBtWvXYsSIEdi3bx88PT3NEpe9vT2sra1RUFCA7Oxso3UePXoEAHqTxWr/X94+2u1SqVT3CFBptra2ehPjRkdHIz09Hd988w2AkqWYk5KS8M033yA0NBQAEBkZic8++wwXLlxA27ZtH/dU9Y5tjFgsNjlZb+lEUFnaN7oxIpHIZLvW1tbllkkkEpMrKT1puxYWFib3LZ0sK8vKykrvDqPSKupDU+0+TR+aem2E6kNTZUL04dO8v031oVDvb1N9+DTv7+rqQ44RJThGVK5djhEVtwtwjNDiGFGCY0QJjhH/4hhRgmNEiedhjDBn8gQQeBLZs2fPonPnztixYwfefPNNg/J+/fphz549aNy4MWJjY80Wl4WFBRo3bgwA5S6VrN3epEkT3TbtUsQV7dO4cWOIxaa7/u+//8bXX3+NadOm6e4S0U40GxISoqvXsmVLvTIiIiIiIiIiqnqCJlBu3ryJ8PBwWFhYlFtHKpXi3Xff1Vsu2By0q91cunTJoCwjIwMymQx2dnbo2LGjbnvHjh1Rp04dyGQyyOVyg/20bVW0kk5RURFmzZqF1q1b46233tJt197KVDr5ou27src5EREREREREVHVETSBkpOTU6lJYv38/JCWlmaGiP41dOhQODg44PDhw7rHdbR27twJABg9erTeLUbW1tYYPXo0NBqNro7Wo0ePcOTIETg4OGDo0KEmj71x40bcunULn3/+ud4tSdp5YErfbaJdRtmcc8QQERERERER1TaCJlDq1Klj9E6Nsh48eGDyGavq4OTkhCVLliA3NxeTJ0/GnTt3oFAosGfPHqxfvx7t27fHu+++a7DfxIkT0b59e6xbtw579uyBQqHAnTt3MHnyZOTm5mLJkiVwdHQs97i3b99GTEwMIiMj0bBhQ72y1157DR4eHli6dCnS0tJw+/ZtrF27Fq1atdK7E4aIiIiIiIiIqpZIU3ZKXjMKDw9H3bp1sWrVKpP1pkyZgkePHuHrr79+quMFBQWVWxYREYHIyEiD7VevXkVMTAwuXryI/Px8+Pj4YMCAARg7dmy5E/kUFhZi06ZN2LdvH5KTk2Fra4s2bdpg0qRJaNasWbkxaDQajBgxAgUFBfj++++NPtp069YtLFy4EBcuXIBYLEbnzp0xa9YsvclsH4e/v7+uXSIiIiIiIqJnhbn/nhU0gXLo0CFMnToVL730EsaMGYNWrVrBzs4OAJCbm4vff/8d33zzDc6cOYPly5ejb9++QoX63GIChYiIiIiIiJ5F5v57VtBljF999VX8+OOP+Omnn/DLL78AgG4ZJe161BqNBr169WLyhIiIiIiIiIgEI+gcKACwYsUKvP3227C0tIRGo0FhYSEKCwuh0WhgaWmJ8PBwrFixQugwiYiIiIiIiKgWE/QRntIePnyIs2fPIjU1FQDg6emJF154AU5OTgJH9nzjIzxERERERET0LKpVj/CU5uTkxMd0iIiIiIiIiKhGEvwRnsrIzs7GqFGjhA6DiIiIiIiIiGqpZyKBolKp8NtvvwkdBhERERERERHVUoI/wlNUVISdO3fi2LFjSE1N1a2+U5parRYgMiIiIiIiIiKiEoImUIqKihAeHo5ff/21wroikcgMERERERERERERGRI0gbJ161ZcvHgRkZGRaN26Nd5991188cUXcHd3BwDcu3cPBw8exK+//oply5YJGSoRERERERER1WKCJlAOHTqECRMmYNKkSQAAsViMVq1awcfHR1enf//+mDFjBi5duoRevXoJFSoRERERERER1WKCTiJ769YtdO/evcJ6w4cPR3x8fPUHRERERERERM817ZfzI0eOFDoUesYIPgeKk5OT7mdLS0s8fPhQ7w4UALCzs0NaWpq5wyOqsZKTk7Fz506cPHkSGo0GRUVF8Pb2xrvvvou2bdvq6kVFRWH37t1wcHDQ29/e3h7ffvutucMmqrV4zRI9Wyp7zQJAUlISFi9ejOTkZGg0GjRt2hSffPKJ7pF0Iqp+qamp2LFjB3755Reo1WoUFBRAIpFg8ODBGDlypG4+zcLCQkRFReGnn35CZmYmr1N6bIImUOrXr4979+7Bw8MDAODs7IyLFy8iJCREr96ZM2cgFj8TKy4TmcXcuXORmZmJDRs2wN3dHSqVCl988QXCwsIQHR2NHj166OpOnjwZgwYNEjBaIuI1S/Rsqew1m5qaiuHDh+ONN95AbGwsiouL8fHHHyMsLAx79+6FnZ2dwGdCVDucO3cO3377Lb7++muEhoYCAH766SdMnjwZeXl5mDhxIgDg1KlTyM7Oxp49e/Daa68JGTI9owTNSgQEBGDz5s26n0NCQrB27VocPHgQ2dnZyM7Oxr59+7Bq1SoEBAQIGClRzfPee+/psuaWlpaYMWMGLCws8M033wgcGREZw2uW6NlSmWs2KioKarUa77//PkQiESQSCaZPn46UlBRs2rRJoMiJah9XV1eEh4frkicA0KtXLzRu3Bg//fSTblvXrl0xf/581KlTR4gw6Tkg6B0oL7/8Mj799FOMHTsW33zzDYYPH44ffvgB06ZNM6g7fPhwASIkqpnWrVsHiUT/8pVKpXBwcMCjR48EioqIysNrlujZUplrtri4GD/++CPatWsHa2trXT13d3f4+/vj8OHDiIiIMGvcRLVV586d0blzZ4PteXl5aNiwoe7nstc10eMS9B3Uq1cvFBQU6DKArVq1wqefforFixdDpVIBKFmZZ+zYsbydmagUS0tLg21ZWVnIzMxE37599bafPn0aBw4cQGZmJjQaDTp06IB33nkHbm5u5gqXqNbjNUv0bKnMNZucnIy8vDyDufsAwMfHBydPnkRhYSGsrKyqPV4i0pebm4vY2FgoFApMnTpV6HDoOSJoAsXe3h4jRozQ2zZixAi88soruHjxItRqNUJCQuDp6SlQhETPjh07dsDJyQkTJkzQbZNKpRCJRFi+fDlcXFyQnJyMDz/8EIMGDcKuXbtQv359ASMmqt14zRI9W8pes5mZmQBgdJ4TOzs7qNVqZGVlMflJZGZ9+/bFnTt34O/vj6ioKDRt2lTokOg5ImgCJTo6GgBQp04djB07VrfdxcUFvXr1EiosomfO1atXsXHjRkRFRaFevXq67ePHj9er5+Pjg4ULF6Jfv35Yu3Yt5s+fb+5QiQi8ZomeNeVds0RU88TFxaGwsBAHDhzA6NGjMWXKFIwbN07osOg5IegkstHR0YiJicGpU6eEDIPomZaUlIRJkyZh6dKl6NixY4X1GzVqBDs7O1y+fNkM0RFRWbxmiZ4t5V2zTk5OAEoeFSgrNzcXYrEYjo6O5gqTiEqxsrLC4MGDMXDgQKxYsQIymUzokOg5IfjawPPnz+cKBERPKCEhAePHj8eCBQvQrVs3g/KMjAyj+4nFYqjV6uoOj4jK4DVL9Gwxdc36+vqiTp06SElJMdgvJSUF/v7+nP+EyEyUSiWKi4sNtgcHB6O4uBhXr14VICp6HgmaQHFwcMB//vMfIUMgemb98ccfeO+997B06VK966j0hMsvvfQS7t+/r7efTCbDo0eP0KJFC7PFSkS8ZomeNRVdsxYWFujVqxcuXbqEwsJCXXl6ejqSkpLQp08fs8dMVFuNHz8ehw8fNtiuTXBq7xgjelqCJlCaN2+Of/75p8J6ubm5mDFjhhkiIno2/Pbbbxg7diy6d++Of/75B/v379f9K5thX7FiBZRKJQAgJycHc+fORd26dfUmriSi6sVrlujZUtlrNjIyEiKRCKtXr4ZGo0FRURGWLFkCb29vjBkzRrgTIKqF1q9fr3dH2Pnz57Fjxw6EhISgXbt2AkZGzxORRqPRCHXwX3/9FdHR0di4caPJWxzlcjk6deqEhIQEM0ZXO/j7+wMAbt26JXAk9Dhef/11/P333+WWX79+HQBw8OBBxMXF4e7duxCJRMjJyUHr1q0RGRmpe+2JqPrxmiV6tlT2mgWAmzdvYvHixUhJSYFGo0FwcDA++eQTrppFZEaXLl3Cnj17cPnyZYjFYigUClhaWqJHjx6YMGGC3mpZgwYNQnFxMZKSkmBpaQlfX194eHhg3bp1Ap4BPSlz/z0raALlt99+w48//oiffvoJQ4cOhb+/P1xcXCASifTqZWVlYfLkyUygVAMmUIiIiIiIiOhZZO6/ZwVdxnjkyJEQiUTQaDS6JY2JiIiIiIiIiGoaQRMoAODu7g6x2PRULGq12mBSPSIiIiIiIiIicxE0gSISibB79264uLiYrJeRkYHOnTubKSoiIiIiIiIiIn2CrsLj4+MDCwuLCutZWVmhbdu2ZoiIiIiIiIiIiMiQoJPIkvA4iSwRERERERE9i8z996ygd6BUVmFhIX744QehwyAiIiIiIiKiWuqZSKA8evQIH3/8sdBhEBEREREREVEtJegksvv27atUvZycnOoNhIiIiIiIiIjIBEETKJ988glEIpGQIRARERERERERVUjQBAoAtGzZEpaWlgbbMzMzkZqaCoVCgVatWhmtQ0RERERERERkDoInUGJiYuDi4mK0TDt57MGDBxETE2PmyIiIiIiIiIiISgiaQBk6dCikUmm55VZWVnjjjTcgEomwZs0afPLJJ2aL7ddff8WoUaMqVff69eu6/wcFBZms+9///hedO3fW2/bnn39i8eLFuHLlCuzs7PDKK6/g448/ho2NjcH+aWlpePXVVzF8+HB89NFHlYqPiIiIiIiIiJ6OoAmUefPmVapehw4dEBUVZdYEipafn1+5ZSkpKfD19TXY7uPjA4nEeNfa2trq/ZyZmYmxY8eiffv2iI+Ph0wmw8SJE5GXl4elS5ca7D9nzhzUq1cPkZGRj3kmRERERERERPSkBH+EpzLkcjnkcrkgxz5y5IjR7cnJyejVq5fRu1Q2bdoEb2/vSrW/bds25OTkYPbs2XBxcYGLiwvCwsIQHR2NyZMn67Wzf/9+nDp1Clu3boW1tfWTnRARERERERERPTax0AFUJCcnB6tXr4arq6tZj+vi4oK+ffuWW/7tt9/C3t4eAwcOfKrjJCYmwtHRER4eHrptwcHB0Gg0uHnzpm5bZmYmFi5ciGHDhqFt27ZPdUwiIiIiIiIiejyC3oFiao4RtVqN7Oxs3L59G8XFxRgzZoz5AgMQGBiIlStXGi3Lzc3F7t27MXz4cJNzuFRGcXGxwTaxuCSvVVRUpNv2+eefw9bWFlOnTn2q4xERERERERHR4xM0gXL+/PkK64hEIvTu3RtTpkyp/oAqadeuXVAqlQgLCzNa/r///Q+nT5+GTCZDYWEhPD090blzZ4SHh8Pd3V2vrr+/P37++Wfcv39fV5aYmKgrA4Djx48jLi4OsbGxsLOzq8YzIyIiIiIiIiJjBJ8DZebMmahbt67BdrFYDHt7ezRt2tQg6SAktVqNrVu3onfv3uXG9euvv2LmzJlo3rw5lEoljh07hgULFmD//v3473//i5CQEF3dYcOGYfPmzViyZAkWLVqEe/fuYevWrejatSv8/f2Rk5ODuXPnYsCAAejSpUu1nVd+fr7ezxYWFrC2toZarYZSqTSor50MV6lUQq1W65VZWVlBIpFApVJBpVLplYnFYkilUmg0GigUCoN2bWxsIBKJUFBQYHB3jqWlJSwtLVFUVITCwkK9MpFIpFu1qOy5AIBUKoVYLDbarkQigZWVFYqLi1FQUFBuuwqFAhqNRq/c2toaFhYWKCws1LtjCKh8Hxpr11QfatutqA+NvTam+lD72gCP34fadivqQ2PtmupD7WtTXX1YXrum+lDbrqk+LO+1qUwfPs3721QfGnttANN9qH1tnqQPOUaU4Bih3y7HCI4RZdvlGMExonS7HCM4RpRtl2MEx4jS7RrrQ41GA5FIZNBedRE8gfLqq6/CxcVF6DAq7dixY0hOTsby5cuNlq9fvx4vvvgirKysAJS8Ed544w0AJcmiKVOm4MiRI7pyT09PREVFYd68eWjTpg3UajU6deqEhQsXAgCWLl2K4uJizJw5EwAQHx+P2NhYyGQyuLu7Y+TIkU89D0txcTESEhL0tjk7O8PPzw+FhYUGZQDQpk0bAMCdO3eQl5enV9awYUO4uLjg4cOHSE5O1iuzt7dHo0aNoFarjbYbEhICS0tLJCcnIzs7W6/M29sb7u7uyMnJwa1bt/TKbGxs0LRpUwDAtWvXDAaJpk2bwsbGBmlpaXjw4IFeWf369eHl5YX8/HzcuHFDr8zS0lKX8EpMTDQYYBo3boy6desiIyMD9+7d0ytzcXFBw4YNUVBQYHCuIpEIrVu3BgDcvn3bYHDy9/eHk5MTMjMzkZKSolfm4OCAwMBAFBUVGe3DVq1awcLCAsnJyXj06JFemY+PD9zc3JCdnY07d+7oldWpUwdNmjQBAKPtNmvWDFKpFKmpqcjMzNQr8/DwgKenJ3Jzc/Xm7gFKBv7mzZsDKOnDsoN/UFAQ7OzscP/+faSnp+uV1atXD76+vlAqlQYxicVihIaGAgBu3bpl8MEREBAAR0dHyOVypKam6pU5OjoiICCg3D4MDQ2FSCTC3bt3kZubq1fWoEEDuLq6IisrC3fv3tUrs7OzQ1BQEDQajdF2W7RoASsrK6SkpCArK0uvzNPTEx4eHsjNzUVSUpJemVQqRbNmzQCULJte9sMqODgYtra2uHfvHjIyMvTK3Nzc4OPjA4VCobfkOlDygd6yZUsAQFJSksEHUmBgIBwcHJCRkYG0tDS9Mo4RJThG/ItjRAmOESU4RpTgGPEvjhElOEaU4BhRgmPEv550jFCpVLq/rc1BpCn76pvR2bNn0a5du3KX/K2JwsLCoFKpsHPnzsfar7i4GO3bt0dubi7Wr1+Prl27GtTJzMyEjY2NLgt57tw5jB49GqtWrUKfPn1w4cIFhIWFISwsDEOGDMGxY8ewatUqLF++HP369Xui89E+JvTXX3/pbWdW2LBdZoX5zVHpdvnNEceIsu1yjOAYUbpdjhEcI8q2yzGCY0TpdjlGcIwo2y7HiCcbI5o1awaRSGSQ9KougiZQnjVXr17FoEGDsHLlSpMr9JRnwIABuHbtGqZNm4Zx48aZrKtQKNC/f380btwYMTExAIDRo0dDJpPh2LFjuolm33rrLTx48ABHjx59/BPCvwkUc73hiIiIiIiIiKqCuf+eFXQZ45ycHERGRiIiIgLTpk0zKI+MjMQXX3xhcNuWUDZv3gwPDw/06tXrifbX5qoq84zW6tWrkZWVhTlz5ui2Xbt2Dc2aNdMlT4CS29BkMpnRLB4RERERERERVQ1BEygHDx7E0aNHcfbsWaOP8TRo0AA7d+7EyJEjBU8QpKenIy4uDsOHDy/3kaMvvvgCH3/8sdGy4uJi3fNlAQEBJo915coVbNmyBdOnT4ebm5tuu1qt1kueACW3WGnLiIiIiIiIiKh6CJpAOX36NAICAhAXF4dFixYZlH/00Uc4cOAAsrKysHXrVgEi/Nd3330HiUSCoUOHllsnNzcXp0+fRk5OjkHZnj17kJeXB09PT7z44ovltqFSqTBr1ix07NgRgwcP1isLDAw0mHjo+vXr8PDw4PLGRERERERERNVI0ARKQkICJk+ebHKZYj8/P0yZMgVxcXFmjExfQUEBduzYgQEDBsDBwaHceiKRCJmZmXjnnXdw8eJF5OXlITs7G7t27cLChQthb2+PlStXmpwleP369UhJScH8+fMNyiZMmIDbt28jNjYWOTk5OHDgAM6cOYMJEyZUyXkSERERERERkXGCLn8jl8sRHBxcYb2WLVsaLK9kTtq7YEaNGmWynvbOkZ9++gkffvghHjx4AAsLC3h7e2PIkCEYO3Ys6tevX+7+iYmJWLduHaZNmwZvb2+D8q5du2LRokWIjY3FmjVr4ObmhmnTpmHYsGFPfY5EREREREQ1jUwmg1wuFzoMA66urvD19RU6DDIzQVfhadOmDb7//vsK5wRJSkrCm2++iUuXLpkpstqDq/AQEREREVFNJJPJEBwcLPh8mMbY2toiISGBSRSBmfvvWUHvQPHz88OhQ4cwefJkk/UOHToEPz8/M0VFREREREREQpPL5cjPz8fUqVON3qEvlJSUFCxfvhxyuZwJlFpG0ARK7969sWrVKlhbWyMsLAx16tTRK8/Ly8OWLVsQGxuLKVOmCBMkERERERERCcbb2xuBgYFCh0EkbAIlLCwM+/btw6pVqxATE4PAwEA4OzsDAB48eICkpCSoVCoEBgYiLCxMyFCJiIiIiIiIqBYTNIFiY2ODr7/+GpGRkbhy5Qr+/vtvgzohISGIioqCVCoVIEIiIiIiIiIiIoETKADg7u6O77//HvHx8YiPj0dqaioAwNPTE126dEG3bt0EjpCIiIiIiIiIajvBEyhaXbt2RdeuXYUOg4iIiIiIiIjIgFjoAIiIiIiIiIiIajpB70DJycnBzJkzodFoYGNjg2XLlumVR0ZGwt3dHR988IHBCj1EREREREREROYi6B0oBw8exNGjR3H27FlIJIa5nAYNGmDnzp0YOXIk8vPzBYiQiIiIiIiIiEjgBMrp06cREBCAuLg4LFq0yKD8o48+woEDB5CVlYWtW7cKECERERERERERkcAJlISEBEyePBnu7u7l1vHz88OUKVMQFxdnxsiIiIiIiIiIiP4laAJFLpcjODi4wnotW7ZESkqKGSIiIiIiIiIiIjIkaALFysoKKpWqwnpFRUVQq9VmiIiIiIiIiIiIyJCgCRQ/Pz8cOnSownqHDh2Cn5+fGSIiIiIiIiIiIjIkaAKld+/eWL9+PdavX4+8vDyD8ry8PHz11VeIjY1Fnz59BIiQiIiIiIiIiAgwXDvYjMLCwrBv3z6sWrUKMTExCAwMhLOzMwDgwYMHSEpKgkqlQmBgIMLCwoQMlYiIiIiIiIhqMUETKDY2Nvj6668RGRmJK1eu4O+//zaoExISgqioKEilUgEiJCIiIiIiIiISOIECAO7u7vj+++8RHx+P+Ph4pKamAgA8PT3RpUsXdOvWTeAIiYiIiIiIiKi2EzyBotW1a1d07drVaFlBQQEOHz6MgQMHmjUmIiIiIiIiIiJA4ElkKysnJwczZswQOgwiIiIiIiIiqqVqzB0o5bl37x42b94sdBhEREREREREVIvV2ATK6dOnsX37dpw8eRJqtVrocIiIiIiIiIioFqtRCZSsrCzs3r0bO3fuRHJyMgBAo9EAAEQikZChEREREREREVEtViMSKJcvX8b27dvx448/orCwUJc08fT0xMCBA9GpUycMHz5c4CiJiIiIiIiIqLYSLIGiUChw4MABbN++HdevXwdQcreJRCKBWq3Gl19+iT59+kAkEiEzMxMeHh5ChUpEREREREREtZzZEyiJiYnYvn07Dhw4gLy8PN3dJu7u7njrrbcwePBg9OrVCy1atNA9tuPs7Izjx4+bO1QiIiIiIiIiIgBmTqCMGDECly5dAvDv3CYdO3bEiBEj8PLLL8PCwsKc4RARERERERERVYpZEygXL16ESCSCnZ0dBg4ciGHDhsHf39+cIRARERERERERPTaxOQ82cuRI2Nvbo6CgADk5OcjLyzPn4YmIiIiIiIiInohZEyizZs3CqVOnMG/ePNy5cwdvvvkmBg8ejL1796KwsNCcoRARERERERERVZpZEygAYG1tjddffx07duzAvn370Lx5cyxYsACdOnXCsmXLkJycrJs8loiIiIiIiIioJjB7AqW0Jk2aYO7cuTh16hSmTp2Kc+fOoVevXlAqlbh48SLUajUAIDMzE927dxcyVCIiIiIiIiKqxQRNoGjZ2tpiyJAh2L17N77//nu8/vrrmDdvHrp06YIvv/wSN27cQGpqqtBhEhEREREREVEtZdZVeCqjRYsWaNGiBWbMmIH9+/dj586d2LBhAx/rISIiIiIiIiLB1Ig7UIyxs7PDiBEjcODAAcTGxgodDhERERERERHVYjU2gVJa8+bN4eHhYfbjRkVFISgoqNx/Q4YMMbpfcnIypk2bhpdeegktWrRAz5498eWXX5a7bPOff/6JESNGoEWLFnjhhRcwb948KBQKo3XT0tLQunVrfPnll1V2nkRERERERERkWo17hMcYZ2dnHD9+XJBj29nZoV69ekbLvLy8DLb99ddfGDVqFLy9vREbGwt/f3/88ssvmD59OuLj47Ft2zY4ODjo6mdmZmLs2LFo37494uPjIZPJMHHiROTl5WHp0qUG7c+ZMwf16tVDZGRk1Z0kEREREREREZn0TCRQhNSzZ08sXry4UnULCwvx4YcfoqCgANHR0fD19QUAdO/eHTNnzsSMGTOwcOFCLFmyRLfPtm3bkJOTg9mzZ8PFxQUuLi4ICwtDdHQ0Jk+eDG9vb13d/fv349SpU9i6dSusra2r9kSJiOixyWQyyOVyocMw4OrqqvsMIiIiouqRkJAgdAh6+Plf/ZhAqUJHjhzB3bt30alTJ4M3br9+/bBgwQLs378fH3zwAerXrw8ASExMhKOjo94jSsHBwdBoNLh586YugZKZmYmFCxdi2LBhaNu2rflOioiIjJLJZAgODkZ+fr7QoRiwtbVFQkICf4kiIiKqBg8fPoRYLEZYWJjQoejh53/1YwKlCh07dgwA0KZNG4MyKysrtGjRAmfPnsXx48cxfPhwAEBxcbFBXbG4ZGqaoqIi3bbPP/8ctra2mDp1anWETkREj0kulyM/Px9Tp07Vu1tQaCkpKVi+fDnkcjl/gSIiIqoGubm5UKvViI6ORmBgoNDhAABu3ryJiIgIfv5XMyZQKpCSkoKPPvoIFy9eREZGBurUqYNmzZrhzTffRJ8+ffTqXrt2DQDg4+NjtC0fHx+cPXtWVw8A/P398fPPP+P+/ftwd3cHUHJXirYMAI4fP464uDjExsbCzs6uys+RiIienLe3d4355YmIiIjMJzAwECEhIUKHQWbEBEoF/vjjD3Tp0gXTpk2Dk5MTbt++jZUrV2LKlCmIj4/H4sWLIRKJAADp6ekAoDdJbGn29vZ69QBg2LBh2Lx5M5YsWYJFixbh3r172Lp1K7p27Qp/f3/k5ORg7ty5GDBgALp06VJt51n2FnQLCwtYW1tDrVZDqVQa1Le1tQUAKJVKqNVqvTIrKytIJBKoVCqoVCq9MrFYDKlUCo1GY3SlIRsbG4hEIhQUFBjcnWNpaQlLS0sUFRWhsLBQr0wkEsHGxsbouQCAVCqFWCw22q5EIoGVlRWKi4tRUFBQbrsKhQIajUav3NraGhYWFigsLNS7YwiofB8aa9dUH2rbragPjb02pvpQ+9oAj9+H2nYr6kNj7ZrqQ+1rU119WF67pvpQ266pPizvtalMHz7N+9tUHxp7bQDTfah9bZ6kD2vDGFHeamk1hUajMXquHCNKcIwowTGiBH+P+BfHiBIcI0oIPUYYOyaZplAokJ+fX2vGCI1Go/t73ByYQDGhX79+6N27Nxo3bqzbFhQUhKioKPTt2xf79u1DaGgo3nrrLQDQXfyWlpZG27OystKrBwCenp6IiorCvHnz0KZNG6jVanTq1AkLFy4EACxduhTFxcWYOXMmACA+Ph6xsbGQyWRwd3fHyJEjMXDgwKc6z+LiYoMJkJydneHn54fCwkKjkyNpH1O6c+eOwfLMDRs2hIuLCx4+fIjk5GS9Mnt7ezRq1AhqtdpouyEhIbC0tERycjKys7P1yry9veHu7o6cnBzcunVLr8zGxgZNmzYFUHInUNlBomnTprCxsUFaWhoePHigV1a/fn14eXkhPz8fN27c0CuztLTUZZUTExMNBpjGjRujbt26yMjIwL179/TKXFxc0LBhQxQUFBicq0gkQuvWrQEAt2/fNhic/P394eTkhMzMTKSkpOiVOTg4IDAwEEVFRUb7sFWrVrCwsEBycjIePXqkV+bj4wM3NzdkZ2fjzp07emV16tRBkyZNABifEKtZs2aQSqVITU1FZmamXpmHhwc8PT2Rm5uLmzdv6pVZW1ujefPmAEr6sOwHc1BQEOzs7HD//n295CIA1KtXD76+vlAqlQYxicVihIaGAgBu3bpl8OEbEBAAR0dHyOVypKam6pU5OjoiICCg3D4MDQ2FSCTC3bt3kZubq1fWoEEDuLq6IisrC3fv3tUrs7OzQ1BQEDQajdF2W7RoASsrK6SkpCArK0uvzNPTEx4eHsjNzUVSUpJemVQqRbNmzQAA169fN/iwCg4Ohq2tLe7du4eMjAy9Mjc3N/j4+EChUOD69et6ZRKJBC1btgQAJCUlGXwgBQYGwsHBARkZGUhLS9Mr4xgBg2uopjE2tgMcI7Q4RpTgGFGCv0f8i2NECY4RJYQeI8r2PVXszp07sLGxqTVjhEql0v2dbQ4iTdlPiBpIpVLh999/R7t27YQORWfjxo1YunQpmjdvjt27dwMoGSzz8/OxYcMGdOrUyWCfZcuWYcOGDejWrRvWrVtnUJ6ZmQkbGxtdhvjcuXMYPXo0Vq1ahT59+uDChQsICwtDWFgYhgwZgmPHjmHVqlVYvnw5+vXr90TnoX1M6K+//tLbzm+ODNvlN0f85qh0u/zmiGPE5cuX8dJLL2HlypU16hGemzdv4oMPPsCFCxcQHBxsUM4xogTHiBIcI0rw94h/cYwowTGihNBjxNmzZ/Hiiy/WuM/aEydONsYsBQAAbKFJREFUYMWKFThy5EiNeYTnypUreOWVV/B///d/CA0NrTVjRLNmzSASiQwS49XlmbgDJTs7G6NGjapRy0Q1aNAAAPQyvG5ubrhz547BNx5a2gydm5ub0XJnZ2fd/xUKBWbPno0ePXro5lqJioqCh4cHZs6cCbFYjMaNG+PkyZNYvXr1EydQtLQXWFlisbjcMgC6i8AY7RvdGJFIZLJdU8s0SyQSSCTlv3WftF0LCwuT+2o/eIyxsrIqN/NZUR+aavdp+tDUayNUH5oqE6IPn+b9baoPhXp/m+rDp3l/V1cfPutjhKk+qwk4RvyLY0QJjhEl+HtECY4R/+IYUaImjhGmzpWMs7GxqfTvK8/DGGHOx3eAGpJAuXLlCv766y9kZ2cbXZWmJi4Rqc3ilX7BmjRpgjt37hjcbqql3a69dcmU1atXIysrC3PmzNFtu3btGtq1a6dbpQcouVV18+bNes+5EREREREREVHVEjSBkpWVhYkTJ+L33383Wc/cE8MAQFpaGgYPHoyNGzcaTXhon+nSPgIDAD169MCRI0dw6dIlg/qFhYX4888/IRKJ0L17d5PHvnLlCrZs2YL58+fr3a2iVqv1kidASRZOW0ZERERERERE1UPQBMqyZctw+fJlODk5oXnz5nBwcDB6C5FCocCPP/5o1tiKi4shl8sRHx9vkEApLCzEjh07AABvvPGGbnvv3r0RFRWFM2fOIDk5WW8547i4OOTm5mLgwIG65YqNUalUmDVrFjp27IjBgwfrlQUGBhpMTnb9+nV4eHhweWMiIiIiIiKiaiRoAuXkyZPo27cvli5davIZqYyMDBw5csSMkf37aE5MTAwsLS3Rt29fuLi44NatW1ixYgVSUlLQr18/3Qo8QMlzg8uXL8fo0aMRERGBJUuWwM/PD7/88gsWLFiAwMBAzJgxw+Rx169fj5SUFHz11VcGZRMmTMCECRMQGxuLYcOG4cSJEzhz5ozeYz5EREREREREVPUETaBkZ2cjPDzcZPIEKFnyKCIiwkxRlfDy8sLevXtx+PBhHDp0CDExMSgoKIC9vT2aNm2KlStXom/fvgb7tWjRAvv27UNUVBTCw8ORnZ2N+vXrY+jQoXj33XdN3imSmJiIdevWYdq0afD29jYo79q1KxYtWoTY2FisWbMGbm5umDZtGoYNG1al505ERERERERE+gRNoHh6esLe3r7Cera2tmZPoABA06ZN0bRpU0ydOvWx9vP19cWyZcse+3iNGjUyWE64rEGDBmHQoEGP3TYRERERERERPTlxxVWqT//+/XHs2LEK62mXMSYiIiIiIiIiEoKgCZQJEybg0qVLiI6ORnp6ern1VCoVfvvtNzNGRkRERERERET0L0Ef4enduzc0Gg2OHj2KmJgYSKVSODk5GSxZzCV6iYiIiIiIiEhIgiZQ/vnnH72fFQoFFAqF0bplkypEREREREREROYiaAIFAKKjoyucSDYrKwvvv/++mSIiIiIiIiIiItIneAIlNDQULi4uJuvI5XJoNBozRUREREREREREpE/QBMq2bdvg6OhYYT1nZ+dKrdZDRERERERUk8lkMsjlcqHDMFBQUABra2uhw9CTkJAgdAhEegRNoLRp06ZS9cRiMby8vKo5GiIioudHTfyl09XVFb6+vkKHQUQkGJlMhqCgICiVSqFDMSASiXjXP1EFBH+ER+vkyZM4deqUbmJZLy8vdO7cGV26dBE4MiIiomfHw4cPIRaLERYWJnQoBmxtbZGQkMAkChHVWnK5HEqlEo6OjpBIasyfYlAqlcjNzUW3bt3g5OQkdDg6MpkMFy5cEDoMIh3Br9r09HRMnjwZf/zxBwDosp4ikQjfffcdWrZsiTVr1sDNzU3IMImIiJ4Jubm5UKvViI6ORmBgoNDh6Ny8eRMRERGQy+VMoBBRrSeRSGBlZSV0GDpFRUUAACcnJ7i6ugoczb8ePnwodAhEegRNoCiVSoSHhyMxMRESiQQBAQG6C1YulyMpKQm///47wsPD8b///Q9SqVTIcImIiJ4ZgYGBCAkJEToMIiIioueGoAmUrVu3IikpCRERERgzZgzs7Oz0ynNycrB582asXbsW27ZtQ3h4uECREhEREREREVFtJmgC5ciRI5gwYQIiIiKMltetWxcRERFQqVQ4fPgwEyhEREREREREJAixkAe/ffs2+vXrV2G9/v374/bt22aIiIiIiIiIiIjIkKAJlKKiokqtNW5lZaWb2IiIiIiIiIiIyNwETaB4eHjg3LlzFdY7d+4cPDw8zBAREREREREREZEhQRMonTp1wpdffmlybe/ffvsNy5cvR+fOnc0YGRERERERERHRvwSdRHbcuHHYu3cvRo4ciZCQELRq1QouLi4AgAcPHuDy5cv4888/UbduXU4gS0RERERERESCETSB4u7ujujoaERGRuKPP/7AlStX9Mo1Gg3s7e0RFRUFd3d3gaIkIiIiIiIiotpO0AQKAHTs2BEHDx7Epk2bcPLkSaSmpgIAPD090aVLF4wZM4bJEyIiIiIiIiISlOAJFKDkTpTp06dj+vTpQodCRERERGRWMpkMcrlc6DAMuLq6wtfXV+gwiIhqjBqRQKlIQUEBDh8+jIEDBwodChERERFRlZHJZAgODkZ+fr7QoRiwtbVFQkICkyhERP/fM5FAycnJwYwZM5hAISIiIqLnilwuR35+PqKjoxEYGCh0ODo3b95EREQE5HI5EyhERP+fWRMohYWFSExMRNOmTSESibBv375K7ZeTk1O9gRERERERCSgwMBAhISFCh0FERCaYNYEyatQo/PHHHxgwYAAWL16MTz75BCKRyJwhEBERERERERE9NrMmUB4+fAiNRoOsrCzdtpYtW8LS0tLkfiqVCn/88Uc1R0dEREREREREZJxZEyjfffcdLly4gP/85z+6bTExMXBxcTG5X0ZGBjp37lzd4REREbgaBBERERGRMWZNoLi4uKB37966n9u1a1fh3ScAYGVlhbZt21ZnaEREhJLkSVBQEJRKpdChGJBKpf+vvfsOa+p8+wD+DXsJiCgioCIKKorgAG1duFqtWhfuverCUQd11jrqBkVw1IXUgXXgwFn3Rqm2OBBcCG6QoeyV9w/e5EdMAmGG8f1cl9dlznPGnXCek5z7PAOhoaFMohARERGRUih1Fp4///wzz3VSU1NhYGCg0LpERFQ40dHRSElJgaGhIdTUSs9EbRkZGYiLi+NsEERERESkNCrKPPjcuXORkJAgtzw6Ohr29vYYMmQI3rx5U4KRERFVbGpqatDQ0Cg1/0pTMoeIiIiIKialJlCOHj2K1NRUueWVKlWCm5sb4uPjsWrVqhKMjIiIiIiIiIjof5T6SE8oFOZarqmpiZEjR8LJyQljxowpoaiIiIiIqLwqbQNlh4SEKDsEIiJSkNLbRAsEgjzXycjIwJcvX0ogGiIiIiIqryIiItCgQQMkJSUpOxQiIiqDSjSBcv78eVy4cEFi2bJly6CpqSl3m6SkJPzzzz8cNJCIiIiICiU6OhpJSUmYOXMmzM3NlR0OAOCff/7Bnj17lB0GEREpoEQTKE+ePIG/v7/EslOnTuW5nUAgwMyZM4srLCIiIiKqQMzNzVG3bl1lhwEAiIyMVHYIRESkoBJNoDg6OmLKlCkAssc/2bRpE0aOHAldXV2Z6wsEAhgYGMDJyQn16tUryVABAPfv38eJEydw9+5dREZGIiMjA9WqVUOLFi0watQo1K9fX2qbDh065Dpj0OLFizFo0CCJZa9evcLy5ctx584dqKmpoV27dpg/fz6MjIyktk9ISECPHj1gb28PDw+Pwr9JIqIypDSNFVCaYiEiIiKi4lfiCRRHR0fxa29vb4wdOxZVqlQpyTAUcvz4ccyePRtmZmaYN28emjVrBgC4ceMGli9fjoCAAKxatQrdu3eX2tbU1BRaWloy92tgYCDxOi0tDaNHj4axsTFOnz6NxMRETJw4EVOnTpXZnHPt2rVISkrCwoULi+BdEhGVDZmZmRAIBBg6dKiyQyEiIiKiCkqpg8j6+vpKJRRKC9H0yp6enmjUqJF4effu3aGrq4sJEyZg4cKFaNOmjdR7WLVqFZycnBQ6TkBAAF6/fo1Vq1bB1NQUADB58mS4ubnh7t27aNGihXjdoKAg+Pn5YfXq1TJbpxARlVdCoRBCoRDOzs6oXLmyssMBkD0YZVBQkLLDICIiIqISotQESs7WKLnJyMhAcHAwmjZtWswR/U/lypXRvn17ieSJSLt27aChoYGkpCQEBQWhY8eOBT7O06dPAUCiO5Do/2FhYeIESmpqKubPn4+2bduiZ8+eBT4eEVFZVrlyZRgbGys7DABAbGysskMgIiIiohKk9GmMFREXF4chQ4aUaH/zTp06oVOnTjLLVFRUoKOjg7S0NIWmYc5NZmYmAMnpnFVUVABkJ45ENm7ciKioKPj4+BTqeERERERERFQ+lcYx2oyNjcvNrLpKTaDcvXtXofXi4uKKN5B8iomJQVxcHLS0tGBvby9V/vfff2P9+vV48eIFkpKSUK1aNbRq1QqjR49GnTp1JNYVvQ4NDRW3sBG1SrGysgIAPH78GLt27cKCBQvE3XyISlJERASio6OVHYaU8nQxJiIiIiIqqI8fP0JFgFI5XpyOthZCnoSWi9/tSk2gDBs2rNAtOJThyJEjALLjlzUWya1btzBnzhy0aNECWVlZuHnzJpYsWYITJ07Aw8MDHTp0EK/bvXt3bNy4ER4eHti0aRNSU1OxdetW2NjY4JtvvkFGRgbmzZuHpk2bYuDAgcX2npKSkiReq6qqQlNTE1lZWUhJSZFaX0dHBwCQkpKCrKwsiTINDQ2oqakhPT0d6enpEmUqKirQ0tKCUChEcnKy1H61tbUhEAiQmpoqbp0joq6uDnV1dWRkZCAtLU2iTCAQQFtbW+Z7AQAtLS2oqKjI3K+amho0NDSQmZkpHvtG1n6Tk5MhFAolyjU1NaGqqoq0tDSJFkOA4p+hrP3m9hmK9pvXZyjrb5PbZyj62wCSn2FkZCSaNm0q83NVNh0dHYSEhKBq1aoF+gzl/W1y+wxF+83tM5T3t8ntPCyK81vWeZjb+Q1In4ey4iYqSsnJyRLncV7nd27XWdH5XVzX2bJyjXj9+jUSEhLE7/VrmpqaUFFRQXp6uszPUF1dHZmZmVL7Fb1XIPv7XtZnqKqqioyMDJmfoVAohLq6usxrj2i/qampMr+rRJ+hrN8Rou9AWX8bLS0tCAQCpKWlyfwMRQ+pSHE562xBfkeIKHJ+5/VbrDxcI76OkaioxMfHI0sIrHOtAiszdWWHI/b8TTpmbvyEN2/eiBMoRXmNEAqFJZpTUHoXHhMTE3GXlZxiYmLEF6QaNWqUdFhyvXv3Dps3b0bjxo0xdepUqfLly5fD1tYW+vr64mVdunSBvr4+RowYgVmzZuH8+fPixIuenh42bdqEBQsWiAeetbe3x4oVK6CiooI//vgDL1++xLFjxyAQCHD//n14eXkhLCwMhoaG6NOnD0aOHFmokyYzM1OqqZeRkREsLS2RlpYmsxmYaFai8PBwJCYmSpTVrl0bVapUQWxsLCIjIyXK9PX1Ua9ePWRlZcncr52dHdTV1REZGYn4+HiJMnNzc5iYmODLly948eKFRJm2tjYaNmwIAHjy5InUl2DDhg2hra2Nd+/e4dOnTxJl1atXh5mZGZKSkhAWFiZRpq6uDjs7OwDZLYO+/gK1trZGpUqVEBUVhffv30uUValSBbVr10ZqaqrUexUIBOIWRy9fvpT6wVunTh1UrlwZMTExeP36tUSZgYEB6tati4yMDJmfob29PVRVVREZGYnPnz9LlFlYWKBatWqIj49HeHi4RJmurq54/J2c+33y5AmSkpLg5eWFunXrSh1PWZ49e4YpU6YgOjoaX758kfoBY2VlBUNDQ0RHR+Pt27cSZYaGhrCyspL7GTo4OEAgEODVq1fimxKRWrVqwdjYGHFxcXj16pVEmZ6eHmxsbCAUCmXut3HjxtDQ0MDr16+lWtbVqFEDpqamSEhIwPPnzyXKtLS0YGtrCyC7tdrXP8YaNGgAHR0dvH//HlFRURJl1apVg4WFBZKTkxEaGipRpqamhiZNmgAAnj9/jtTUVKnzgqiohYeHS8xUp6mpKR5v7OnTp1I3FzY2NtDT08OHDx/w8eNHibKqVauiZs2aSElJkapzKioqcHBwAAC8ePGi3F4j3r9/j759+8pMUiibQCCQ+j6msidnnS3I7wgRW1tbaGlp4e3bt4iJiZEoMzU1RY0aNZCQkIBnz55JlJW3a8SXL1+k1icqSlZm6mhUR1PZYUjJWY+K8hqRnp4ODQ2N4glaBqUnUA4fPix3GuMPHz7gwIEDeP78Odzd3Us4MmkJCQmYPHkyTExMsHXrVpl/qFatWsnctmXLlqhXrx6ePn2K06dPY8iQIeKyJk2a4MSJE4iLi4Oamhr09PQAZN/QeHt7Y9q0aahduzZevXqFESNGwNnZGdu3b8e///6LJUuWIC0tDT/99FOB35eqqioaNGggtQzIzr5/XZZT7dq1ZT59A7IHexS9FxFRskxFRUXmftXUsk9JCwsLqcSZunp2JrVSpUpS2+ZMIOUckFdEUzP7ImJqaopq1arJPKaOjk6u+61Xr57MFihA9hf01zODiD5DTU3NXD9DS0tLmU89gOxEVqVKlWTuV01NTeZ+RZ+xhYWFzKd6QHYS5uttcyYyc5aJflDUrVtXnEwqberUqSP3MzQ2NpaaKSuvz1D0d69Vq5bc89vQ0FD85EpE9BkKBIJcz29zc3Op7niiv42enl6u56GNjY3UfkU/bKtXry41wKromNra2rmeh1ZWVnKf6BIVpdq1a0uci19fZ78mus6amJhI/V4Qnd9aWlq5nt/l+RqRkpKC1NRUGBoaircvDVJSUpCQkFCqZs4COHtWQeSsswX5HSEiqhs1atSAiYmJRJmi34Hl4Rrx8OFDuXEQlWc57+2K8hohKispSv2mbd26da7ZIhMTE0ydOhU+Pj7YunUrJk2aVILRSUpISMD48eORnp4OHx8fuUmf3NSsWRNPnz6VypqJGBoaiv+flZWFBQsWwNraGqNGjQIAbN26FSoqKli+fLn4KdadO3ewZcsWjBo1qlCZt69/5ImIBsyVJ+dTxK+JmlrJIhAIct2v6MtQFjU1tVx/JBZ0v6qqqrluK2o+KouGhobczz+vzzC3/RbmM8ztb5OfzzC3+EqLgn6GhTm/c/sMlXV+53YeKnp+l4W/N5Vt2tracs/Fgp7fxXWdLQvXCNF7E3VVKC1ErQRK08xZAGfPKghZdVZZv8XKwzWiNCU6iUpSzrpflNeIkh4SRLrvTAnavn271NN1WTp27IijR48Wf0ByxMbGYuTIkcjMzMSePXukWjAoSpTZVuSPvHfvXjx48ADLly8XZ7mfPHkCS0tLiVYddnZ2SEpKkmomTERERERERERFR6kJFEV9/vwZ7969U8qxP3z4gGHDhkFXVxc7d+6UaMJ36tQp3Lt3T/x6x44dGDZsmNx9iZIcotl15Hnz5g3c3d0xbtw4ie4oWVlZUuPFiLLYXw+0Q0RERERERERFp9QnULKysrBr1y6pvoclITIyEoMHD4aFhQW2bdsGXV1difL9+/fjxo0b4tdJSUm4f/++1KCfAHDz5k08f/4cOjo6+P7773M97qJFi1CjRg1MnDhRYnndunXx6tUriYHinjx5Ag0NDdSuXbsA75CIiIiIiIiIFKHUTnhz586VW5aVlYX4+Hg8fPgQnz59Qt++fUswsuwZPkaNGoVPnz7B1tYWbm5uMtdxdHQUvxYIBEhPT8eECRPg5uaGJk2aQFVVFdevX8fSpUuhqamJNWvW5Dp+ir+/P27evAk/Pz+pfpxjx47FqVOnsGbNGri6uiI4OBgnTpzAiBEjcu2HTURERERUELJmy1A2Y2Nj8XSoREQlSakJFH9/f4WmuLOzs8OsWbNKKKpsp0+fFk+FdvbsWYW2GTduHGxsbHDmzBksXrwYHz58gEAgQPXq1eHs7IyRI0fm2n0nOjoaK1euxLBhw8RTi+ZUv359bNq0CRs2bMC3334LQ0NDDB06FNOmTSvYmyQiIiIikuHjx49QEQBDhw5VdihSdLS1EPIklEkUIipxSh8GeuTIkVJdY4DsUa319fVha2srnqO9JLm6usLV1TVf22hqaqJz587o3LlzgY5pbGyMwMDAXNdp37492rdvX6D9ExEREREpIj4+HllCYJ1rFViZlew0obl5/iYdMzd+QnR0NBMoRFTilJ5AGTt2bIGmBCYqjyIiIhAdHa3sMCSUxqa7RFR2lcZrCrsDEMlnZaaORnXkTytKRFSRKDWBsnTpUoWmMSaqCCIiItCgQQMkJSUpOxQioiLH7gBERERU1ik1geLi4qLMwxOVKtHR0UhKSsLMmTNhbm6u7HDE/vnnH+zZs0fZYRBRGcfuAERERFTWKTWBkpKSgvXr10MoFEJLSwszZsyQKP/1119Ru3ZtDB8+HKqqqkqKkqhkmZubo27dusoOQywyMlLZIRBROcLuAERERFRWKTWBcvbsWfj4+EAgEMDJyUmqPDU1FatWrcKtW7fg7e0NdfXS88SKiIiIiIiIiCoOFWUe/NKlSzAxMYG/vz98fHykyleuXAlfX18EBwfj0KFDJR8gERERERERERGUnEB59OgRpk+fjvr168tdx9HREVOnTsWRI0dKMDIiIiIiIiIiov9RagLl48ePaNKkSZ7rOTk5ISIiogQiIiIiIiIiIiKSptQEioqKCtTU8h6GRU1NDWlpaSUQERERERERERGRNKUmUMzNzXHx4sU817t06VKpmtaViIiIiIiIiCoWpSZQOnTogA0bNiAgIEDuOsePH8eGDRvQsWPHEoyMiIiIiIiIiOh/lDqN8ejRo+Hv74/Zs2dj9erVaNKkCYyMjAAAnz59QnBwMKKiolCtWjWMGjVKmaESERERERERUQWm1ASKgYEBtm3bhokTJ+Lt27c4f/68uEwoFAIAzMzMsHnzZhgYGCgrTCIiIiIiIiKq4JSaQAEAGxsbnDp1CocOHcKVK1fw9u1bAECNGjXQrl079O3bF9ra2kqOkoiIiIiIiIgqMqUnUABAS0sLQ4cOxdChQ5UdChERERERERGRFKUOIktEREREREREVBaUigRKQkIC9uzZg6lTp2LgwIH48OEDAODw4cPi/xMRERERERERKYvSu/DcunULP//8M+Li4iAUCiEQCJCWlgYA+PPPP7F48WKsW7cOXbp0UXKkRERERERERFRRKbUFSkREBCZNmoTY2FhYWVmhQ4cOUFVVFZevX78enTt3xs8//4ywsDAlRkpEREREREREFZlSW6Bs374d6urq2Lp1KxwdHQEADg4O4vLatWvD3d0drq6u2LlzJ1auXKmsUImolAoJCVF2CFKMjY1Rs2ZNZYdBRERERERFSKkJlNu3b2P27Nni5Ik8w4cPx8KFC0soKiIqCz5+/AgVAUrl7F062loIeRLKJAoRERERUTmi1ATKhw8f0KxZszzXMzMz42CyRCQhPj4eWUJgnWsVWJmpKzscsedv0jFz4ydER0czgUJEREREVI4oNYGipqaGhISEPNeLjo6GmprSx7slolLIykwdjepoKjsMIiIiIiIq55Q6iGzdunVx6NChPNfbt28fbGxsSiAiIiIiIiIiIiJpSm3W0aNHDyxfvhwZGRkYP348ateuLVEeERGBrVu34tixY/jtt9+UEyQVWkREBKKjo5UdhoTU1FRoapauVgulcTBUIiIiIiIiyqbUBMqAAQMQEBCAI0eOwN/fH/r6+khLS8OYMWOQkJCA2NhYAEDTpk3Rt29fZYZKBRQREQEbGxukpKQoOxQJAoEAQqFQ2WEQERERERFRGaHUBIq6ujq2bduG+fPn49y5c4iPjweQfdMt8v3332PZsmVQVVVVVphUCNHR0UhJSYGhoWGpGccmJSUFCQkJcHZ2RuXKlZUdjlhERASCgoKUHQYRERERERHJoPQ72kqVKsHT0xOhoaG4evUq3r59CwCoUaMG2rVrB2trayVHSEVBTU0NGhoayg4DAJCRkQEAqFy5MoyNjZUczf+IWlwRERERERFR6aP0BIqIjY0NB4olIiIiIiIiolJJqbPweHl5ITk5Oc/1oqOj0aBBgxKIiIiIiIiIiIhImlITKN7e3golUF6/fl0C0RARERERERERyabUBIpQKIS7u3uuM7Ts3bsXI0eOLLmgiIiIiIiIiIi+otQECgDcv38fvXv3xpMnTySWx8bGYsKECVi2bFmpmwKXiIiIiIiIiCoWpSdQtm/fjm+//Rb9+/eHj48PAODmzZvo2bMnLl++jEqVKmHRokXKDZKIiIiIiIiIKjSlzsJz4cIFVK9eHQsWLEDz5s2xYMECHDlyBM+ePUNWVhbs7Ozg7u4OQ0NDPHjwQJmhEhEREREREVEFptQWKGZmZhAIBAAAU1NT6OnpISwsDFlZWejVqxf2798Pc3Nz6OnpYcWKFcoMNV/S09Pxxx9/oHv37rCzs0PLli0xefJkPHr0SGrdpKQkLFq0CE5OTrCzs8OwYcNkricyefJkdOrUSaHBd4mIiIiIiIioaCg1gTJ8+HB8/vwZPj4+GDp0KD58+ABjY2N06dIFFy9exOnTpwFkJyTu3r2rzFAVlpaWhjFjxsDT0xMjR47E7du3sX//fnz58gUDBgzA5cuXJdZfuHAh/v77b2zZsgWXLl2Cnp4eRo0ahdjYWKl9nzp1CufPn8fSpUuhra1dQu+IiIiIiIiIiJSaQLlz5w6mTp2KVatWIT09Hc7Ozjh+/Dg8PT2xePFiLFmyBDNnzkRkZCSGDx+uzFAVtnnzZgQGBmLChAno168fdHR0YGlpCU9PT+jo6GDOnDmIi4sDAERGRuLkyZMYOnQoHBwcUKVKFSxYsADx8fHYu3evxH7j4uKwbNkyuLi4oFWrVkp4Z0REREREREQVl9IHkQ0MDISWlhZ+++03bNq0CUZGRgCAbt264ejRo/j48SOGDBmi5CgVk5qait27dwMABgwYIFFmaGiI77//HvHx8fDz8wMAPHv2DEKhEA0aNBCvZ2ZmBgMDA4SFhUls//vvv0NVVRVubm7F/C6IiIiIiIiI6GtKT6A0bNgQR44ckUo4AECNGjXg6+tbZhIot2/fRmJiImrVqoWqVatKlTdr1gxA9uC5AJCZmQkA4nFgRAQCgbgMAK5evYpjx47h119/RaVKlYorfCIiIiIiIiKSQ+kJlC1btsDS0lJuuUAgwMCBAyEUCkswqoIJCQkBAFhYWMgsFy0XDZRbp04dAEBoaKh4nY8fPyIuLg5WVlYAgMTERPz666/o1q0bOnXqVJzhExEREREREZEcAqESMxNz587F/Pnzoaenl+t6qampOHXqFHr37l1CkRXM0qVLsWfPHvzwww9wd3eXKn/+/Dm6desGILvrkqGhIcaNG4eQkBDs3r0bFhYWWLhwIc6cOYMzZ87A1NQUS5YswcmTJ3H69Glx96aipK2tjYyMDJibm0uViVrGyDpFFCkDgJSUFLx79w4qKkrP1YkJhUIIhUJoaWmVqrgyMjKQlpYGAwMDqKqqKjscsbS0NCQkJKBKlSpQV1dXdjhiycnJiI+Ph5G+CtTVBHlvUELSM4SI+ZwFU1NTaGpqSpQpWm8KWufkXc7zs21qamqpq7NA6ay3rLP5U9bqbFF8BxZlXZa3X9bZ/CmN9ZZ1Nn++rrNF+R0oq6ww28oqS0tLw9u3b0tVvQBYZ/OrNNbb0l5na9SoIf6eLcr6+Pr1a6ipqZXYLLVqJXIUORSdmlhTU7PUJ08AiP9o8iqRhoaG+P8pKSkAgJUrV2Lu3Lno3r07VFVVUb16dXh6esLU1BRBQUHYt28fVq9eDSMjI3z48AHu7u64c+cO1NTU0LZtW8yYMSPPBFRuRCfx192IcipoGQBoaWnl2sKIygZZXdKUTVtbu1iSikXBoEru5XnVm+Kqj4psyzpbPrDO5k9udba461xh98s6Wz6wzuaPrDpbXPWxMNvKKtPU1GSdLSdKW70tS3W2KOujmpqa1EPL4qTUBEpuMjMzce/ePYllLVq0UFI0ihFNLZyeni6zPC0tTfx/LS0tAECVKlXwxx9/ICkpCSkpKeKTPjU1FQsWLEDbtm3Rs2dPpKenY9SoURAIBHB3d0dycjLmzJmD8PBw7Nixo8Axi2YEIiIiIiIiIiL5SjSBknO2mVu3bsHQ0FDuuklJSRg2bBgEAgGEQiFUVFTw+PHjEoiy4ERZyPj4eJnlouVaWlrQ19eXKNPR0YGOjo74tZeXFz5+/Ihdu3YBAE6ePInnz59j165dcHBwAAC4urpi0aJFCAoKQvPmzYv8/RARERERERFRthJNoAiFQsybNw+VKlWCrq5uruvq6emJZ6t5+fIlxo0bVxIhFoooQRQZGSmzXLTc2to6176Fjx8/xs6dO7FgwQKYmpoC+N9As3Z2duL1mjRpIi5jAoWIiIiIiIio+JR4F54ffvgBVapkd4IaPny4VLmvry+A7L5NZmZmALJbo5QFLVu2hK6uLiIiIhAdHQ1jY2OJclGXpNxm08nIyMD8+fPRtGlTDBw4ULxcNK1xzsSLaCClnFMeExEREREREVHRU+oQy2ZmZuJ/9+7dy7VLT1mgqamJESNGQCgU4sCBAxJlnz9/xpkzZ2BgYIABAwbI3ceOHTvw4sULLF26VGKAnHr16gGQnPL4yZMnEmVEREREREREVDxKzSw8Z86cwezZs5UYTdGYOHEigoKCsGXLFpiamqJr16748OEDFi9ejISEBHh5eclNFL18+RLe3t6YOnUqateuLVHWo0cPeHt7Y/Xq1XB3d0dKSgo2bdoEe3t7tGzZsvjfGBEREREREVEFVnom+S4nNDQ0sGPHDri6umL79u1wdHTEgAEDoKOjg7/++gvOzs4ytxMKhZg/fz7q1auHUaNGSZVraWlh586d0NXVRdeuXdG3b1/Y2NjAy8srz6meiIiIiIiIiKhwBEKhUFhSB6tfvz5u3LghHgMlJwcHBxw/fhwWFhZSZU+fPkXPnj0REhJSEmESEREREREREUlgCxQiIiIiIiIiojyUeAKF3U2IiIiIiIiIqKwp8S48pqamElPxirx79w7VqlUTT82bU0ZGBj5+/MguPERERERERESkFCU+C8+7d+/klr1//15uGVuuEBEREREREZGylHgCZdSoUdDV1c3XNp8+fYKfn18xRURERERERERElLsST6CMHTtW5iw8uQkLC2MChYrd/fv3ceLECdy9exeRkZHIyMhAtWrV0KJFC4waNQr169eX2mbjxo3w8vKSu88mTZrgr7/+klp+/vx5hISEoHfv3jA3NxcvDwoKwpAhQ8Svp0yZAldX10K+s2zXrl2Dh4cHwsLCYGRkhD59+sDV1VVmt7mHDx+if//+WLhwIQYNGiRzfxMmTMDDhw/h6+uLOnXqAACOHDmCuXPnitdZsWIF+vTpUyTxf83Gxkbi9dKlS9G/f3+Z6w4bNgx37tyRWObo6Ig///wTANChQwe8efNGajtfX184OTkVUcRUlAIDAzF8+HCF1g0NDRX/n3WWdZaIiIiooEo0gdKlSxdoamrmezt9fX107ty5GCIiynb8+HHMnj0bZmZmmDdvHpo1awYAuHHjBpYvX46AgACsWrUK3bt3l9pWT08PVatWlblfMzMzmcvPnz8Pf39/ODo6StyMNW/eHKGhoVI3NYX17NkzTJgwAS4uLti5cyfu37+PadOmQSAQYNq0aRLrpqenY/78+WjWrBkGDhwod5+RkZGIiYlBfHy8eFmfPn3Qp0+fPG9Si4Loplh0I7V06VLUr18fdnZ2UuuKbrp++eUXAMDKlSslyi9evCixL96ElR2WlpZyy16/fo2aNWtKLWedZZ0lIiIiKogSTaB4enoWaLvq1asXeFuqGFJTU/HhwweZN0uKbg9kn6ONGjUSL+/evTt0dXUxYcIELFy4EG3atIGBgYHEtp07d5b6cV/abN++HZqamnBzc4O2tjacnZ3xww8/YOfOnZgwYYJEYnPbtm0IDw/HsWPHch176MiRI0hISMh3i7LioK+vj8+fP8PV1RX+/v4wMjJSdkgVzosXL1CzZk2oqZVsw8YzZ87IXB4ZGYkuXbrIbKXCOss6S8WHrTn/pyy0DBMJCQmBr68vgoKC8OHDB6ioqKBKlSowNTVF48aNYW9vj7Zt20JbW1vm9llZWfj7779x8uRJ/Pfff4iJiYGGhgaqV68OJycnDBw4ENbW1lLbsTWZcrE1pyTWWdZZRZT4NMZEReXly5fw9fXF2LFj4ejoiE2bNhV4X5UrV0b79u0lkici7dq1g4aGBpKSkhAUFFSYkJUmLCwMtWvXlriINmjQACkpKYiIiBAve/78OTZv3gxXV1fUrl07131qamqWihsxAHB1dUWdOnXw/v17TJ8+HZmZmcoOqcL59ddf0bJlS7i6uuKvv/7KdcDwolClShV069ZNbvmff/4JfX199OrVq1jjKC6ss1QWHT9+HAMHDsTly5cxbdo0XLp0CdeuXcPPP/+Mq1evom/fvggICJC5rZ6eHiwtLWX+y61lmJeXl9SPeVHLsBUrVhTp+xO1DLOzs8P169fx22+/YefOnTJvJAvbMiw0NBRTpkwp0vjlCQgIQN++fREREYHly5fj2rVruHXrFv744w+0aNECvr6+mDp1Kp49eyZz+7dv32LgwIGYN28ebG1tsWvXLgQFBeHSpUtYvHgxYmJi0LNnT/z+++/IyMiQ2PbixYsIDQ0V/419fX0RGhpaYW7ESgt5dc/S0hLq6uqwsrKS2oZ1lnUWqJh1tsTHQCEqqMTERNy+fRvXrl3DtWvX8Pr1awDZMzQ1aNAA33zzTYH33alTJ3Tq1ElmmYqKCnR0dJCWllbo2aC+zlDnzPqbmZmJm6XndPv2bWzYsAEhISFQV1dHq1atMH/+fJiYmCh83KysLKnpw0WvRTcuWVlZmD9/PqytrTFq1Ci5+/r6aUVBnhIEBwdj27ZtCAoKwpcvX2BkZIRWrVphwoQJuXbJkEdPTw+bNm2Ci4sLAgMDsWbNGnHTfyoZHTt2RHR0NM6dO4dz584BAOrWrYs2bdqgTZs2aNGiBTQ0NIrseHXr1oWHh4fMsoSEBBw+fBiDBw+GlpZWoY7DOpuNdbZiYGvO3JXHlmEpKSn49ddfoaOjg61bt0JPT09cZmVlhWnTpkFLSwvu7u4yt4+KisLQoUPx5csX7N+/X+KJtaamJlq0aIEWLVpg8+bNWL9+PWJjY7FmzZpif19lFVtzFi3WWWmss4XHFihUqj158gTbtm3D8OHD4eTkhEmTJmH//v1ISEhAt27dsHLlSly/fh3+/v7o2bNnscQQExODuLg4aGlpwd7eXqr89evXmDVrFpydndGoUSM4OTlh9OjROH36tNS6ogx17969AfwvaxsaGirzRuzevXvw8fHBsmXLcP36dfzyyy84f/48Jk2alK/3UKdOHbx69Ur84xbIfsKtpqYm/qG8Z88ePHz4EMuXL5fZrFHEycmpUE8J/P39MXDgQERHR2P37t24d+8evLy88PjxY/Tt2xf3798v0H4tLS2xbt06qKioYNeuXTh16lSB9kMFM3LkSJw+fRoXL17E4sWL0aFDB7x9+xa7du3C6NGj4ejoiPHjx2PPnj149epVscZy6NAhpKSkYOjQoTLLWWfzh3W2fGNrTsWVx5ZhYWFhSEhIQK1atSRuxHL68ccfYWxsDHV1damy+fPn482bN5g2bZrM5v4iEyZMQKNGjXD8+HEcP368yOIvb9ias2ixzrLOFgcmUKhU8vb2Rps2bfDjjz9i7dq1uHv3LmxsbDBp0iT4+fnh1q1b8PDwQO/evWFsbFyssRw5cgRA9qwQsvrp//fff7CxsYGfnx/u3bsHX19faGhoYPr06XBzc4NQKCzwsR89egR3d3dYWVlBT08Pffv2RatWrfDw4UOJvqh5GTFiBBISErB+/XpkZGQgODgYAQEBGDBgAHR0dPDmzRt4eHhg3LhxMvunF5WXL19i4cKFUFdXh6enJ6ytraGhoQE7OzusW7cOSUlJmDNnToGb87dr1w7Tp08HkP0FERYWVoTRkyLMzMwwaNAgbN68GYGBgfDx8cHo0aNhYWGBK1euYOnSpejSpQs6d+4ss390YWVlZWHPnj347rvv5Lb4YJ1VHOts+ZOYmIgLFy5g8eLF6NixI77//nssX74c169fR506dQrdmnPr1q0yy0StOQEUSWtOGxsb+Pv7A8huGWZjYwMbGxt06NBB5ja3b9/GoEGDYG9vjxYtWmDq1Kn48OFDvo6blZUltawwLcNEMdvY2GDjxo35igXIbhnm6uqKVq1aoVGjRmjbti3c3Nzw8uVLhfehq6sLILuux8TEyFynevXquHHjhtS1Jjg4GFeuXIGGhkaeN9gCgQAuLi4AgC1btigcX0XTsWNHVK1aFefOncPChQvRvn17/PDDD1i5ciVu3LiBtLS0Ij2eIq05+/fvXyStOVlnWWfLCyZQqFS6ffs2Pn78CADQ0dHBpEmT4OHhgWnTpsHBwUGqaXtxeffuHTZv3ozGjRtj6tSpUuXdu3fH4cOHMW7cOJiYmEBDQ0N8Ua1ZsyaOHj2KAwcOFPj4bdq0Ef/gFKlXrx4A5Oti26RJE6xYsQLHjh2Dvb09Bg8ejE6dOmHWrFkAgEWLFqFGjRqYOHEigOwnzn379kXr1q0xePBgXLlypcDvIad9+/YhPT1d/AMhJ2trazRs2BARERG4ceNGgY/x008/oWvXrkhKSsKUKVPw5cuXwoZNBaShoYFWrVrBzc0N69atw4gRI8RPQyIiInDv3r0iP+aFCxcQGRmJESNGyCxnnc0f1tnyga052TJMnlq1asHU1BSJiYkYMWIEzp8/LzXmgTyXLl0CkH2Nk/ckPKemTZsCyH7aHxkZqdAxKhq25szGOisf66zyMYFCpdLMmTMxevRoWFtbIykpCV5eXujcuTM6d+6MJUuW4NKlS0hKSirWGBISEjB58mSYmJhg69atMsdvsLS0lNn8TV1dXTwA1cGDBwscQ/Xq1aWWiW7OkpOT87WvPn364Pr167hy5Qr++ecfrF69Gjo6Ojh8+DBu3ryJ33//HRoaGjh27Bh++eUXdO7cGbt27UL9+vUxYcIE/PPPPwV+HyKiL4cGDRrILK9RowaA7BYChbFixQrY2Njg1atXmD17dqFaFFDBfP78GWfOnMH8+fPRrl079OjRA7t370ZmZiYaN26MSZMmYfTo0UV+3N27d8Pe3h5NmjSRWc46mz+ss2UbW3NmY8sw+dTU1LB06VJoaWkhLCwMkydPxrfffouZM2fiyJEjiI6Olrvt8+fPAcif/v1rousFkD3WB8nH1pyss/KwziofB5GlUsne3h729vZwc3PD+/fvxQPH3rx5E3v37sXevXuhrq6O5s2biwepzK0fX34lJCRg/PjxSE9Ph4+PT4H6OtaqVQvA/y5WBSGryaSo6XNBvphEU5yJREVFYdWqVRg2bJj4hnPjxo1o2rQpJkyYACC7Wf2FCxewceNG+Pj4FOBd/M/nz58BAGvXrsXatWvlrpfbxV8R2tra8Pb2Rr9+/XDp0iV4e3uX2MjoFVVWVhYePnworqvBwcHiHwJVqlRBz5490aZNG7Ru3brYpqx99OgR7t69K7c5cl5YZ6WxzpZtX7fmHD16NH788ccCDxJbUIq05vzuu+8kvsdFLcO6deuGo0ePwsHBIdeZMXIjr2XY9evX8fLlS9jY2Ci0H1HLsLVr1+LPP/8EAHTr1i3XlmF79uwRD8z7008/oV27dgV6DzmJWoZ16dJFbsuwR48e4caNG2jbtm2e+2vTpg0CAgKwY8cOnD59GnFxcQgICEBAQABUVFTQtm1bzJgxQ+oGU9RaTNHuHTnHoRBdWyhvotacrVq1Qu/evXHo0CHxOSBqzdm/f/8iPaaoNee6detklrPO5g/rbPnCBAqVetWrV4eLiwtcXFyQkZGBf//9F1evXsW1a9dw+/Zt3Lp1C6tXr8agQYOwePHiQh8vNjYW48aNg6qqKvbs2SM1U4CiRDdLhe3rXZyWLFkCfX19zJgxA0B23/jIyEh07NhRvI6qqioaNWpUJE+z9fX1AQALFizAsGHDCr2/3FhYWGD9+vUYO3YsvLy8ZA5qSEVn/PjxuHbtGoDsc8bOzg5t27ZFmzZt0KhRoxKpB7t374apqSm6dOlSoO1ZZ6WxzpZtM2fOxNmzZ3H9+nWEhYXBy8sLXl5eqFmzpvjhg5OTk9SNSlFStDWnLKKWYatXr8bBgwcLfDNW1C3DevXqhdjYWOjp6Yln8RC1DPPz85NoGTZjxgx07NgR+/fvx4QJE7Bnzx40a9asQO9DRJGWYY8ePcJ///2n0M0YkF3/Fi9ejIULF+L+/fu4du0aLl68iLCwMFy+fBk3b96Er68vHBwcxNtUqlQJQPasIIrI+VmLxnGg3H3+/Bk3b97EtWvXcP36dbx//x5AdnK9cePGaNOmDbp27Vrkx1WkNacsrLOysc6WL0ygUJmipqaG5s2bo3nz5vj5558RHR0tfuKdM0taUB8+fMCYMWNQpUoVbNq0SeJicerUKVSvXl3cH/Ddu3fo168fduzYIbPZX3h4OIDs/pdfKw03aGfPnsW5c+fg4+Mj/uxEg219PcaMqqqqzIG48svBwQEPHjyQ248yJSUFd+7cgbW1tcwvz/xq1aoVZs+ejRUrVmD27NmwtraGhYVFofYpGkhL9LSfshkYGKBPnz5o27Ytvv32W/GNd0n5+PEjTp06halTp8qd/pF1Nv9YZ8s2tubMxpZhilNVVRX/zpoxYwbu378PNzc3vHr1CmvXrsXevXvF64qulW/evFFo32/fvhX/XzQ2FElia85srLOKY50teRwDhco0Y2Nj9O7dG+7u7nBzcyvUviIjIzF48GBYWFhg27ZtUpnW/fv3SwyUmJmZiejoaFy+fFlqX2lpafDz8wMA9O3bV6pc1KpFlAFOSUlB9+7dcevWrUK9B0XFx8dj6dKlcHFxQatWrcTLK1WqBBMTE6mZMEJDQ4vkwjl48GCoq6sjICBA5hMEPz8/TJw4scAzesgycuRI9OrVC58/fy6SqTPDw8PFN9r0P+vWrcOKFSvQtWvXEk+eANnNY9XU1DBgwAC567DO5h/rbPkhas3p6emJ27dvY+/evfjpp59Qr1493L59G6tXr0aPHj2KpCUnkN2ac+TIkcjMzMSePXtQrVq1Au2nLLcMs7OzE68jahn25MmTQh8vZ8sw0UCcsv799ttvee4rNTUVgYGBcp9IOzg4YP78+QCAx48fS5S1b98eAPD06VMkJCTkeSzRwOH16tUrdGK0vBo/fry4ngYHB8POzg7Tpk3DoUOHcOPGDaxZswY9e/YstuQJULFbc7LOSmKdlY0tUKhUmjNnDoKDg/O1TefOnTFz5swCHe/Zs2cYNWoUPn36BFtbW5nJmGfPnsHR0VH8WvTF4O3tDXV1dXTr1g1VqlTBixcv4O7ujtevX6N79+4ymy+Kst23bt2Ck5MTDh8+jJcvX5bYxWnlypUQCAQy3+dPP/2EZcuW4ejRo+jYsSP8/PwQHh4uvhgXhqWlJZYtW4b58+dj1KhRcHNzg7W1NRITExEQEAB3d3fMnj1b4cGtFLVkyRI8f/4cDx48kFmekJCArKws8RP7pKQkuX0909PTxTPJ0P+UdJ3NKTU1FX5+fvjxxx9z7XLHOpt/rLPlE1tzFp2y3jIsKioKw4cPx59//inxGycn0SCioq4PIvb29nByckJgYCCOHj0qd7YWIPumWjRAd0Fbg1WE1mRszVn8WGdZZwuLCRQqld69e5evKT+B7AtKQZ0+fVo80N7Zs2cV2sbMzAz+/v44ffo0Tp48CW9vb6SmpkJfXx8NGzaEh4cHunXrJnPb77//HuPGjcOJEyewb98+mJmZYeXKlQAgMTCWqL+6r68vzMzMJMY5mDt3LubOnYsLFy7A3Nxc4fd648YNHDlyBN7e3uK+kDkNHjwYycnJ8PT0xIIFC2Bubo5Vq1aJ+2QGBgZi+PDhUjGKpnWbO3euVIy+vr5wcnICAPTq1Qt169bF9u3bMWXKFMTHx6NKlSqoX78+tmzZgtatWyv0PnJ+TqLjTJkyBa6urlLrampqwtvbW2bLAgDo2bOnRHPGvC70omn46H9Kus7mdPz4ccTFxUmcl7KwzkrGyDpLIqLWnEXxOUVGRmLkyJGwtrbGhg0bpMY82b9/PxwdHcUJlJwtw76+GStIy7B+/fph/vz5Ei21iosyW4bt378fAQEBmDFjhlTSy8/PD2vWrMG5c+cU3mdAQIDcm7GrV68CgMy6vmrVKri4uGDDhg1wcnKS+/62bNmChw8folevXujevbvCceVUEVqSyRu0taTktzUn66xiWGfLFyZQqFQSjZRdUlxdXWX+iM9Lw4YN0bBhw3w/RRcIBJg1a5Z4FPCccpueLT9Tt8nz7bff5rofgUCAsWPHYuzYsTLLnZycct2+T58+ecbQqFEjrF+/Ps/1cpPfz8LExATXr1+XWXbx4sVCxUIlX2dzEg0yrQjWWWmss+UXW3MWr/LUMuzAgQMQCoUYOHAgLCwsoKamhrdv3+LEiRPYtm0bzM3NZV7/TE1NsX//fkybNg2DBg3C+PHj0aVLF9SoUQNpaWl48uQJ9u7dizNnzmDMmDFS5xZbk0lia87ixTrLOlsUBMLCTNJNRERERKXSsGHDcOfOnXxt07t3b3HrqvzauHEjvLy88lzv65ZHjx8/xunTp3Hjxg2Eh4dLtAzr27ev3JZhQqEQ69atw4kTJxAbGwszMzNMmjQJDg4OEq2/RGS1DBMpSMuw0aNHw9vbG506dZIZ244dO7Bv3z58/PgR5ubmmDBhAnr16gVAumWYiKyWYTnjF7UMA4CHDx9i+/btuHv3rkTLsGHDhincMiwrKwv//vsvbt++jaCgILx58wafPn1CcnIy9PT0YGlpiQ4dOmDw4MHQ09OTux+hUIi///4bp0+fxn///YeYmBgkJyejatWq+OGHHzBw4ECZM7d06NBB4QEtgcKdn2VBSdfZnA4ePIiFCxfi5MmTsLKyynVd1tn/YZ3NXXmss0ygEBERERFRkfrtt99w7NgxLFq0CN26dZM5hTURlR6ss4phAoWIiIiIiIpUSkoKpk6diitXrkBTUxNVq1aFj48PZ/MgKqVYZxXDaYyJiIiIiKhIaWlpYcuWLVi2bBlsbW2RkJCA9PR0ZYdFRHKwziqGLVCIiIiIiIiIiPLAFihERERERERERHlgAoWIiIiIiIiIKA9MoBARERERERER5YEJFCIiIiIiIiKiPDCBQkRERERERESUByZQiIiIiIiIiIjywAQKERERURHq0KEDbGxsxP8CAwOVHRIREREVASZQiIiISOnS09Nx4MABjB49Gq1bt0ajRo3QrFkzfPfddxg2bBhWr16Nc+fOISYmRmrbwMBAODk5YenSpSUac0BAAJo1a4Zt27ZJLD906BCuX7+O6tWrl2g8X8vrc9m4cSM2btyIz58/l3BkREREZRMTKERERKRUMTExcHFxwaJFi1C5cmWsXr0aJ0+exPHjx7F8+XI0atQIvr6+cHV1xc6dO6W2P3v2LOLi4nDkyJESjfvEiRNISEjAsWPHJJYbGRmhatWqUFVVLdF4vpbX5+Ll5QUvLy8mUIiIiBSkpuwAiIiIqGJbtWoVQkJC0K9fPyxfvlyizMzMDM2bN4elpSUWLlwoc/v+/fvj8ePH6NKlS0mEKzZy5Eh8+vQJw4cPL9HjKkpZnwsREVF5xQQKERERKdWlS5cAZI8dIk+/fv2wbt06mWX169eHn59fscSWm1atWuHQoUMlflxFKetzISIiKq+YQCEiIiKlysrKAgC8f/9e7joqKirYv38/dHV1JZbb2NhIvL5w4QLMzc0BAJs2bcKGDRvEZb1798bMmTOxbt06XLlyBSkpKbCxscHEiRPRrl07AMDhw4fh4+OD8PBwGBoa4vvvv8esWbOgqakp3s/r16/RsWNHieOGhobm6z3/+++/OHfuHAIDA/H27Vt8+fIFxsbGaNasGcaNG4f69etLrB8UFIQhQ4aIX5uZmeHcuXPYuXMnjh07hsjISKSmpoo/g6/jy/m5DBs2DHfu3BGXyVr362UAMGXKFLi6ugLIHj/Fy8urUJ8BERFRWSMQCoVCZQdBREREFdeQIUMQFBQEY2NjbN68GXZ2dgpvGxUVBQBo3bo1AMlEQVJSEhITE7Fz507s3LkTzs7OSExMxOjRo1G3bl2EhIRg8eLFiI2NxdatWxEWFobU1FR0794d8fHx8PT0xLVr19C9e3eJ1i+ZmZmIiYnBu3fv4OLiAkB28qBDhw548+YNfH194eTkJFEmej1r1iw0a9YMqqqqePr0KTZv3ozQ0FBs3LgRzs7O4vXT09MRFxeH+/fvw9XVFTVq1ICtrS3q1KmDnj17QiAQYO3atbh48SIuXLggTvjI+lzi4uKQnp4uLjt48CBMTU3FxzIyMkJMTAy8vLzg5+eHFi1awMPDAzo6OuIEVmJiIhITE9GvXz/07t0bQ4cORdWqVRX+uxEREZVFHESWiIiIlGratGkQCASIjo6Gi4sLBg0ahF27duHp06d5blu1alW5N+46OjqoWrUqdHR0AGR3FZoxYwacnZ1hYWGBLl26YPr06cjKysKKFSvw7t07TJ48GbVq1YKdnR08PDygrq6OU6dO4ePHj+L9qqqqomrVqjAyMirwe65RowaWL18OFxcX1KlTB7Vq1UKnTp2we/duaGlpYeHChUhLSxOvr66ujqpVq8LAwAAA8PbtW5iamuLnn39G3bp1YWVlhRkzZsDY2Fgcn7zPxdDQUKJMNOit6J9oe9HYLv/88w9SU1MlWv/o6uoiLCwMnz59wpAhQ5g8ISKiCoEJFCIiIlIqR0dHbNu2DZaWlgCAe/fuYeXKlejevTtat26NefPm4datW4U+jqWlJZo2bSqxrHHjxgCAFy9eoEePHhJllSpVQp06dZCVlYXHjx8X+vg5+fv7o1OnTlLL9fT0YG1tjaioKAQHB+e6jxEjRki8tra2xo0bNyRakxSGlZUVHB0dkZWVhQMHDkiV+/n5oWPHjqhWrVqRHI+IiKi04xgoREREpHRt2rTB6dOnERgYiPPnz+PGjRt48eIFoqKicPjwYRw+fBhNmzaFu7t7gRMEtWrVklqmp6cn/n/NmjWlyvX19QFkd3spSsnJydi3bx8uXryIV69eITExUVyWkpICAHj37p3c7bW0tMRdcorToEGDcOfOHRw+fBiurq7Q0NAAAHz8+BGXLl3C9u3biz0GIiKi0oIJFCIiIioVBAIBWrZsiZYtWwLIHlT24sWL8Pf3R3BwMO7du4dp06bBz88PKir5b0RraGgo85gilStXllsuGui2KMTGxmLo0KF49uwZvvnmGyxbtgwWFhZQU8v+WTZr1iwEBwcjPT1d7j4K030oPzp37gxjY2NER0fj77//xg8//AAge9wUc3NztGrVqkTiICIiKg3YhYeIiIhKperVq2Pw4ME4ePAgZs6cCQD477//8PDhwwLtL2eypCDlRcXb2xvPnj1DnTp18Mcff6B9+/awsrJCrVq1UKtWLWhpaeW5j5KKVV1dHf369QMA7N+/H0B2MunQoUMYNGhQicRARERUWjCBQkREREr1xx9/4Pr167muM3bsWGhrawPInka4LAsMDAQAfPPNN1BXV1dyNHnr378/VFRUcPfuXTx79gxXrlxBTEwMevfurezQiIiIShQTKERERKRUfn5+OHHiRK7rqKioiMffqFKlSkmEVWzy6g70/v37EolDViuWmJgYJCQkSCwzMzNDu3btAGT/rfz8/NC1a1fxjEBEREQVBRMoREREpHTnzp1DZGRkruXx8fGoXr261Ew6ZY29vT0A4Pr16xJTFQPZXZRy+xyKkigBkpSUJF7WuXNnbN68WWrdgQMHAgCOHDmCq1evsvsOERFVSEygEBERkdIlJSVhwIAB2L59Ox48eIB3797hxYsXuHnzJhYtWoSff/4ZBgYG8PDwkOj2EhUVhaioKPHrmJgYREVFITMzEykpKYiKihInCESvRTPeREVFISYmRmJfotl2EhMTERUVJR7I9cuXL4iKikJKSgoyMzNlbiuKI2cMABAfH4+oqChxsmTixIkwMjJCeHg4Jk6ciKCgIERERODEiROYPHmy+P2JjpmWliY+Znx8PACIX+fcb065fS4iTk5OALKTIpGRkdixYwcSEhLwzTffSO2vbdu2MDMzQ2JiIurXr48mTZrk8tckIiIqnwRCoVCo7CCIiIio4oqOjsbVq1dx9+5dhIaG4u3bt+JuJJUqVUKdOnXw7bffYuDAgVKzz9jY2Mjc54ULF3Dnzh3MnTtXqmzKlClwdXWVua2joyP+/PNPbNy4EV5eXlLlK1asgKOjIzp27CjzuKGhoejQoQPevHkjVebr6ytOWrx58waenp64ceMGYmNjoauri4YNG2LYsGHw8fHBnTt3JLYzMzOTe8yc+xXJ7XMRTX8cFRWFJUuW4Pbt20hJSYGZmRmGDRuGIUOGyNx269atcHd3x9KlS9G/f3+Z6xAREZVnTKAQERERUZ5OnDiBxYsX49q1a9DR0VF2OERERCWOXXiIiIiIKE8HDx7Ejz/+yOQJERFVWGoF2Sg9PV2iDy0RERERlR8REREIDAyEi4sLACA8PByvX7/GvHnzkJKSouToiIiICk9FRQXq6uoyZ6WTJ19deD5//ozo6GikpqYWKEAiIiIiKv1SUlIQExMDIyMjqKqqIj4+HqqqqqhcubKyQyMiIioyqqqq0NHRQbVq1aChoZHn+gonUD5//ow3b95AT08PBgYG+c7UEBEREVHZkJycjPfv3yMjIwMCgQC6urqoVq0aVFVVlR0aERFRoQmFQmRmZiI5ORnx8fHIysqCubl5nt1UFU6gvHjxAurq6jA3N2fihIiIiIiIiIjKvMzMTLx69QpqamqoWbNmrusqNIhseno6UlNTYWBgwOQJEREREREREZULqqqqMDIyQmJiIjIyMnJdV6EEimjAWHV19cJHR0RERERERERUSmhqagJA0SRQRNj6hIiIiIiIiIjKE0VzHflKoBARERERERERVURMoBARERERERER5YEJFCIiIiIiIiKiPDCBQkRERERERESUB7Wi3FlERASio6OLcpfFwtjYOM/5nYmKS1mpJwDrCuWO5zJR6cY6SlQ6sC4SlR9FlkCJiIiAjY0NUlJSimqXxUZLSwuhoaG8OFCJi4iIQP369ZGcnKzsUBSira2NJ0+eFLquDBs2DHfu3Mn3dhcuXIC5uTk2btwILy8vues1adIEf/31V2FCpHyKiIhAgwYNkJSUpOxQFKKjo4OQkBCey1RhVNQ6Ksvly5dx8uRJ/Pvvv4iOjkZ6ejoqVaqEmjVrwtbWFo6OjmjdujX09PTE23To0AFv3ryRuT8VFRUYGBigUaNGGDRoEDp27Aig8NeH3AQHB+PKlSu4ffs23rx5g0+fPsHQ0BA1a9ZEr1698OOPP0JDQyNfx+X1qGRERESgQX0bJCWX/nskANDR1kLIk6K5T5JXj3x9feHk5CRzmyNHjmDu3Lni1ytWrECfPn0KHYuy3b9/HydOnMDdu3cRGRmJjIwMVKtWDS1atMCoUaNQv379fO0vMDAQw4cPV2jd0NBQqWXp6enYtWsXjh8/joiICOjo6KBZs2aYNGkSbG1txeuV179HYRRZAiU6OhopKSkwNDSEmlqRNmwpUhkZGYiLi0N0dHShLgzyTlp5J9XXFxBHR0f8+eefCh3LxsamQNsVpa/fr7a2Nvz8/ORW9pwxi0yZMgWurq4FjiEkJATnz5+Ho6Oj3ItuaRcdHY3k5GQ4OzujcuXKyg4nV7Gxsbh06VKh64qIrL+/qF58/UX6+vVr8Q9SET09PVStWlXmvs3MzAodH+VPdHQ0kpKSMHPmzDx/+Cvb69evsW7dOp7LVKGI6qiXlxfq1q2r7HBy9ezZM0yZMqXI6qjIu3fvMGPGDDx9+hSjRo3CuHHjYGFhgYyMDLx9+xanTp3Cnj17sHfvXhgYGEgkPy5evAhAdt2OjY3FP//8g+XLl2PSpEkYM2YM5syZA6Dw1wd5xo0bh8TERMyePRvff/89DA0NER4eDg8PDyxYsAAnT57Ezp07oaKSv975vB4Vv+joaCQlp2CdaxVYmakrO5xcPX+TjpkbPxVZXcytHsnTp08f9OnTJ88EX1ly/PhxzJ49G2ZmZpg3bx6aNWsGALhx4waWL1+OgIAArFq1Ct27d8/3vi0tLeWWvX79WubfMS0tDWPHjsW9e/ewePFidOvWDR8+fMCvv/6KAQMGwMvLC+3btwdQPv8ehVXkmQ41NbV8Z8DLIicnJ4SGhmLDhg3YtGkTateujbNnz8pd/+LFi7h8+TKmT5+Oa9euoVKlSgofKzQ0NF9fssVB9H5FcSQnJ2PKlCk4fPgwDAwMpNYXZTo7dOiAKVOmFEmmMiQkBF5eXpgyZUqZTaCIVK5cGcbGxsoOo0zp3LkzVq5cqeww6Cvm5ual/uastOG5TCWpbt26sLOzU3YYJe7Dhw8YOHAgkpOT4efnh3r16kmU29jYwMbGBs7OzhgxYgTS09MV3nflypXRqVMnGBoaYsiQIdixY0eBbnzya8yYMRgxYoT4tY2NDTZs2IC2bdvi1q1buHv3br5/H/F6VHKszNTRqI6mssMgJUhNTQUAeHp6olGjRuLl3bt3h66uLiZMmICFCxeiTZs2Mu+rcnPmzBmZyyMjI9GlSxeZD/w3b96MwMBAuLq6ol+/fgCyEzGenp7o0qUL5syZg3PnzsHQ0DBfsVQUHES2kPr16wcVFRWEh4cjMDAw13X9/PzQrVu3fCVPSit9fX1ERkZi1qxZyMrKUnY4VMqNGTMGHTp0UHj9ypUrY9myZaW+lQ5VPDyXicqGefPm4f3795g2bZpU8iQne3v7Aj/kadasGXR0dABkt9QtzuuDl5eXRPJERFNTU9xS5PPnzwofm4hKTuXKldG+fXuJ5IlIu3btoKGhgaSkJAQFBSm8zypVqqBbt25yy//880/o6+ujV69eEstTU1Oxe/duAMCAAQMkygwNDfH9998jPj4efn5+CsdS0TCBUkhmZmb45ptvACDXfqLv37/H1atXpU7UsmrFihXQ1tbG1atX4enpqexwqJRr3769RH/KvOjq6sLFxQW6urrFGBVR/vFcJir9goODcf36dWhoaEjdPMgybNgw/PTTT/k+jkAgkHhdnNeHFi1awMjISGp5bGwsXrx4AV1dXTg4OCh8bKKySigU4tSpU5g5cya+++47NGnSBA4ODujfvz8OHDgAoVAoXjcoKEjc2szGxgYbN27EnTt3MGjQINjb26N169ZYtmyZeGzCU6dOoWfPnmjcuDE6dOiAbdu2FToGAOjUqRO2bt0qc18qKiriROzX15Tc1K1bFx4eHjLLEhIScPjwYfTv3x9aWloSZbdv30ZiYiJq1aols/ueqHvRhQsX5B7777//xoABA+Dg4ICmTZtizJgx+O+//xSOvawrvYOVlCEuLi64fv06zp07h9jYWJlPEg4dOoR69eqhSZMmiIyMxLFjx3D9+nVERkYiPj4exsbGaNmyJSZOnIhatWopdNygoCAMGTJE/Drn+CsPHjwQN8n6uiyn4OBgbNu2DUFBQfjy5QuMjIzQqlUrTJgwIdc+dfXr18fvv/+OGTNmYMuWLWjcuHG+uxilpKRg9+7dOHnyJF69egUVFRXUrVsXffr0wYABA8T9eL/uvuTl5SXRB0+Rwdeo7Hv9+jVmzZqFf/75B1FRUdDV1YWtrS1cXFzQtWtXZYdHpDCey0TF69KlSwAAa2trhZITderUwYQJE/J9nKCgIPEgvSXZtVgoFCImJgYPHz7Ehg0bUKlSJaxcubJAXYN5PaKyJi0tDTNmzICjoyM8PDxgZWWFuLg4nDx5Er/99hsePXqEJUuWAACaN2+O0NBQ8UCo9+/fR2hoKFasWAEjIyP89ddfWLNmDaKjo9GxY0eEh4dj586dyMzMxPLly7F27Vro6+tLPQDPTwx5iYmJQVxcHLS0tGBvb18kn9GhQ4eQkpKCoUOHSpWFhIQAACwsLGRuK1oeFhaGrKwsqXGVAgICoKuri9WrV8PU1BTBwcFwc3PDkCFDsHnzZrRp06ZI3kNpxhYoRaBjx44wMjJCWloajh49KlWemZmJgwcPon///gCAAwcOYMuWLejRowcCAgJw584deHh4IDw8HH379sXz588VOq7oojBlyhSpssaNG8stE/H398fAgQMRHR2N3bt34969e/Dy8sLjx4/Rt29f3L9/P9fjd+vWDePGjYNQKISbmxtevnypUNxAdmZ08ODB8PT0xIABA3Djxg1cvHgRHTp0wG+//YYZM2aIs7fm5ubiix2QPUBbaGio+B+TJxXDf//9BxsbG/j5+eHevXvw9fWFhoYGpk+fDjc3N6lsPwD8/vvvEk8eWrZsiZ9//hmfPn0Sr3Po0CE0a9YMGRkZJfl2JHTu3BkbN25U2vGpZPFczr/ff/9d6gY1NTUVU6dOhb29vXigQiIA4t9RNWrUKJb9x8XF4fz585g9ezaA7K59DRs2LJZjydK6dWt88803GD9+PKpVqwYfHx98++23BdpXQa9HrI+kLAKBAA0aNICHhwcaNmwITU1NmJiYYPTo0Rg0aBAOHDiAsLAwmds+evQIa9euRe3ataGvr4+xY8eiTp06OHv2LC5fvgxXV1cYGxvDxMQE8+fPByC7h0FhYvjakSNHAGS3hJPVyiy/srKysGfPHnz33XcwMTGRKo+KigIAuWOtiJanpKTI7Bb49OlTrFu3DrVq1YKGhgaaN28ODw8PpKen45dffpGakbc8Xi+YQCkC6urq4iaisirZlStX8PnzZ/z4448AgGrVqmHChAkYMmQIKleuDB0dHTg4OGDTpk1ITEzEhg0bij3mly9fYuHChVBXV4enpyesra2hoaEBOzs7rFu3DklJSZgzZw4yMzNz3c/PP/+Mtm3b4suXL3B1dUViYqJCx1++fDkePXqEoUOHYsiQIdDT00PlypUxceJEfPfddzhz5gz8/f2L4q1SOdC9e3ccPnwY48aNg4mJCTQ0NMRNMWvWrImjR4/iwIEDUtuFhYXBwcEBBw4cgJ+fHyZPnoxz587ht99+E6/zzTffYP/+/UqbPSwhIQGRkZFo0KCBUo5PJYvncsGEhYXB2tpa/DouLg4jR47E3bt34evrm69xJ6j8+/LlCwBINV0vjOHDh4sTmK1atcL8+fNRp04deHt7i2fgKSk3btzA3bt3sW/fPqSkpKBHjx7w9PSUmezITWGuR6yPpCwaGho4evSozBZXou8fedOJt27dWuq6YGVlhaysLKmbfBMTE1SqVAkvXrwo0hhyevfuHTZv3ozGjRtj6tSpea6viAsXLiAyMlLmmEkAxN2V1NVlzwiVczKYr5MhAPDDDz9ITRhjZ2cHS0tLREdHSyVEyuP1ggmUIuLi4gIAePHiBe7evStR9tdff6Fr167Q09MDkP0lLKtliJGREUxMTPIcjLYo7Nu3D+np6ejYsaNU/zdra2s0bNgQERERuHHjRq77UVFRwbp161C7dm08ffoU8+bNy/PYMTExOHbsGADpwYsAiBNNHLyIRCwtLSUuviLq6uoYOHAgAODgwYNS5WFhYWjcuDHs7e3h4OCAYcOGoUuXLrh586Z4nRo1asjcd1FKS0uTWxYSEgKhUChz6m8qf3guZwsMDMzXOR8WFiZe//Xr1xg0aBA+ffoEPz+/CjnDDOVONFi/6EZBliVLlki06hIlDuTx9fUVt3wNCQlBYGAgduzYgU6dOhV5/IrQ19dHs2bNsH37dtSrVw/e3t7igSEVVZjrEesjKdOzZ88wZ84cODs7o1GjRuI6LGo1EhcXJ3O76tWrSy0T3Z/Jaq2hr68v7qZXVDGIJCQkYPLkyTAxMcHWrVuLbBbb3bt3w97eHk2aNJFZrq2tDQByZx7L+T0vKwktb3pzKysrANnDSORUHq8XTKAUkTp16qB58+YAIJGtf/fuHa5evSr+IgKAjIwM7N27FwMHDkSzZs1Qv359caV79+4d4uPjiz1eUfcceU8KRc1eFRkQSF9fH5s2bYKuri7OnDmD7du357r+gwcPkJmZCR0dHZnjrIiO/fjx43xNK0gVk2jMoK+7vkVHR+PTp09Ssy/o6uqKM+pZWVlwcHCQaDmWmZkJHx8f9OjRA40bN0br1q0xc+ZM8ZO948ePY8iQIXBycoKDgwMGDBgg0d1NtE8fHx8sW7YMLVu2FLdQS0hIwKJFi+Do6AgnJyds27YNjx8/hp6eHruiEc9lOUTv39raGo8ePcLAgQOhp6cHPz8/qTHDUlNT4enpic6dO8POzg59+vSRmNXgxx9/xMKFC6WOMWvWLAwePFj8+urVqxg0aBCaN2+Opk2bok+fPnk+UKDSQ/RD/s2bN3LXWbRokTgh0rt375IKTa6vkzk2Njbipv25UVNTE3cR379/f5HFk9f1KK/6mFddBFgfqWDu37+Pvn374sqVK5g9ezauXbsmrsui7v7yWmPl1iotPy3WChMDkP0dOn78eKSnp8PHxwdVqlSRuV5+rwuPHj3C3bt35bY+ASB+cC7vflO0XEtLC/r6+lLl8saVEg2EK2oBCJTf728OIluEXFxcEBQUhHPnziEuLg6GhoY4dOgQrK2tJTJs06dPx99//41u3bph+fLlsLCwEGcdO3TokOsXflER9Wlbu3Yt1q5dK3e96OhohfZnZWWF1atXY8qUKXB3d4etrS1atWolc11RxUxKSkL9+vXl7jM9PV08wC6RPKIvqK9HLhf1PRX9kBat+++//4oTh5GRkUhKShJnxrOysjB16lTcuXMH48ePh62trTgJKtr/s2fP0KtXL5ibmyMtLQ0HDx7E5MmTcfnyZWhoaIj3uX37dnTu3Bnr1q2Duro60tLSMGbMGCQmJmLx4sXQ1taGu7s7UlJSUL9+/XyNvE7lE89l2UTv//3791ixYgWcnJzg4eEhfoomkpGRgfHjx+P58+eYMmUKLCwscPDgQYwfPx7nzp2DsbExmjRpIvV0LDg4GCdPnhQ//AgMDMTkyZPx008/YerUqUhJScE///wDVVXVIn1fVHycnZ2xadMmPH36FPHx8XL7+pcmoaGhBd5WlLQsyt+PeV2PcquPitRFAKyPVCDe3t5ISUnBjBkzcp3Gt7TGEBsbi3HjxkFVVRV79uzJ9fqU3+vC7t27YWpqii5dushdJ+fvBllEy62traUGkAUgd7gGUUsdUQtAoPx+fzOBUoS+//57LF++HJ8/f8bRo0cxbNgwHDp0SGJqvP/++w9///03KleujFWrVhVJcy3Rl5usTKe8ZmeijOKCBQswbNiwQscAZE/RNWXKFGzcuBEzZsyQmyEVXSgMDQ1LpLsSlW3v3r1Dv379sGPHDpkJt/DwcADZrcByEl20LS0tkZGRgQ8fPuCPP/5AWFgYvL29xeuoqKiIn+z7+Pjg5s2bOHTokMTNat++fcX///nnn8X/z8jIgIWFBbp27YrIyEhYWVmJj9u3b1/MmDFDvK6XlxfCw8Nx5swZ8UxdlSpVwpAhQ9C2bdsCfz5UdlTkc1koFEqMqZWVlSU+bk6yxm8RxeHt7Y2uXbti3bp1Mn8M7dy5E8HBwThy5Ii4daOjoyOcnZ1x9uxZDBkyBHZ2djhy5AhSU1OhqakJIHuAux9++EH8oOPEiRNo3769RFdbZ2dnme+LSic7Ozt8++23uHHjBv766y+MGzdO2SEVytGjR7FixQrcvn1bZoLyw4cPALJ/VymqsNej3OqjInURAOsjSdiyZQsA5DkjlugGX1YrdlljdhSHgsbw4cMHjBkzBlWqVBG33hc5deoUqlevjqZNmxYopo8fP+LUqVOYOnVqrmOhtWzZErq6uoiIiEB0dLTUg+p79+4BgNzuiW/fvpW5/NmzZwCyJzIRKa/f3+zCU4S0tLTQo0cPANl9Ri9fvozPnz+jZ8+e4nUiIiIAZD8tkJU8KUjFFzU5k9XX9/379zK3cXBwACA/+5iSkoKrV6/K3V6eyZMno3PnzoiNjYWrq6vM/vKNGzeGqqoq4uLiJJp55RQaGiqVXOET+oopMzMT0dHRuHz5slRZWlqaeKycnDeGwP+y9q1atYKtrS06dOiAK1euYPXq1eIvhdDQUFhYWEBHRwdZWVnYtm0bhgwZInHDmVNKSgq2bduGHj16wN7eHra2tuJpHkX1MDQ0FNra2pg4caLEe/jzzz8xcOBAiWnORV8SubXEovKjIp/L/v7+sLW1Ff8bOXIkAEgss7W1lbltaGgozMzM0KhRIzx69Ejmg4GsrCzs2rULvXr1goWFBTIyMpCRkQGBQICaNWuKf/DZ29sjPT1dPI3jqVOn8PjxY4lkkpaWFq5fvw4fHx/xbAVU9qxYsQLVqlWDt7d3nt2RlTlzlSKysrIQFxeH27dvyywTPbDq2LGjVLmPjw9cXFykxucrzPUot/qoaF0EWB9JUnh4uDhxlxvRGByPHz+WKlNk4NaiUJAYIiMjMXjwYFhYWGDbtm1SXWH2799fqK4m+/btg5qamszxJXPS1NTEiBEjIBQKpQaJ/vz5M86cOQMDAwO5+zl58qTU/V1wcDDCw8NhbGwscR0qr9/fbIFSxFxcXLB37148e/YMK1asQLdu3cSDEwH/q3CvXr1CUlKSuL8YkN3PNOeUlIoSPR0QZf5EEhIScPXqVZnbDB48GPv370dAQABmzJgh1ZTKz88Pa9aswblz5/IVi0AgwKpVqxAeHo6HDx/KXMfIyAg9e/aEv78//vrrL4wZM0aiPCkpCePGjUPbtm0lRsTOOa2WyIwZM9CgQQOMHz8+X3FS2SFKnHl7e0NdXR3dunVDlSpV8OLFC7i7u+P169fo3r27xDhDQPZF28nJCbNnz4aKigr09fWl5rzPObBVaGgoYmJi0LlzZ5lxCIVCjBs3Dq9evcKoUaNgbW0NfX19HD58GEePHoWpqal4n46OjhJ9acPCwhAXFyeVzRdd3JlAqRgq8rns7OyMQ4cOiV8/evQIv/76q8QyeUJDQ9GwYUO4ubmhV69emDdvntRgn2FhYYiJicG+ffuwb98+qX20adMGQPb3pZ6eHh48eIAGDRpg7dq1GDVqlMR0t9OmTUNWVhY2bdqEVatW4ZtvvsEvv/wiNQYNlW4mJibYv38/pk+fjuHDh2P48OH44YcfUKtWLaiqquLjx4/4999/ceLECVy+fBkGBgaldjBv0bVj1qxZ+Pnnn9G6dWvo6+vjxYsX8PLywv3792FtbY3p06dLbbthwwYkJSVhx44daNGihdQ+C3I9yq0+KloXAdbHiiAhIQFZWVniVodJSUkyp8YFsrvuy5sZJqdx48bh9u3b+OOPP1CjRg04OzsjNTUVBw4cwNmzZ4s0/qKK4dmzZxg1ahQ+ffoEW1tbuLm5yVzH0dGxQPGkpqbCz88PP/74o0JdFidOnIigoCBs2bIFpqam6Nq1Kz58+IDFixcjISEBXl5eclu0GRgYYNasWZg1axaqV6+O4OBg/PLLL1BXV8eKFSvErUOA8vv9XeQJlNKexS/u+Bo0aIBGjRrh4cOHiIyMhLu7u0S5g4MDHB0dcefOHcyYMQNz5sxBjRo1xD8mBQJBvqeh+/bbb1G9enUcP34crVu3RqtWrfDu3TusWrUKTZo0kZnNtLS0xLJlyzB//nyMGjUKbm5usLa2RmJiIgICAuDu7o7Zs2fLHWk5N7q6uti0aRP69esnd4CiBQsW4OnTp9iwYQNUVFTw3XffoXLlyggJCcGaNWugo6ODadOmSWxja2sLdXV1/PPPP0hISMDLly9x/vz5MtmUMzY2Vtkh5Kk4Y/x6rJ/hw4cDyJ7l4Otp5MzMzODv74/Tp0/j5MmT8Pb2RmpqKvT19dGwYUN4eHhI9T/NysrC8+fPMXLkSImmhF8LDQ1F9+7dAWQ3fQQgd8ydu3fv4s6dO/jrr78kRjZfvXq1RD/R0NBQ8ZN8EdG+vx4k7O+//4aqqmqxz5xSnF6/fq3sEPJUnDHyXM6W17lcuXJliRYroqdQub0n4H/vv3379rCwsMCyZcswffp0+Pj4iFux5IzLx8dH4qGFiOi7TEVFBXZ2dnjw4AGSkpKQmpoq1b2jUqVKWLRoEebPn49bt27h119/xfz58yUG6C1Lvn64UhoVV4zm5uY4ePAgLly4gFOnTmHSpEmIiYlBRkYGdHV1UaNGDdSvXx/u7u5wdnaWeKglr2737t0bK1euVOj4+bk+5KZHjx4wNjbGmTNnsG3bNixduhRpaWmoVKkS6tati3nz5mHgwIESNy4iPXv2xIkTJ8TXB5HCXI9yq4+K1kWg4tXH529K/8QIRR1jz549JepAXt1zevfujSNHjmDu3LniZXPnzsXcuXPF9aZVq1bYv38/vLy8sHr1asyfPx8mJiZo3749Zs6ciTVr1sDLywteXl5YsWKFxL5Ey319ffHmzRuJsuHDh8PMzAwXL17Exo0b4eXlJS6zsbERlwHIVwy+vr64c+eOuG4UR5Ln+PHjiIuLE19j8qKhoYEdO3bAx8cH27dvx6+//godHR00a9YMf/31l0SL0K//HqNGjUJaWhqmTp2Kly9fQkVFBQ4ODli7di3s7e3F65Xr72+hApKTk4WPHz8WJicny13n1atXQi0tLSGAUv9PS0tL+OrVK0XeeoH4+fkJra2thT/++KPM8qSkJOHGjRuF3bp1EzZu3FjYtGlT4dChQ4Vnz54VOjs7C62trYXW1tbCoUOHCoVCofh1zn9ubm4S+3z27Jlw7NixQnt7e6G9vb1w6NChwqCgIKGnp6fEdo8fP5bY7sGDB8Jp06YJv/nmG6Gtra2wbdu2wvHjxwuvXbsmsd7t27dlxnH79m25n8O1a9eEDRo0EB4+fFhmeUpKinDbtm3CXr16CZs0aSJ0cHAQdu/eXbhhwwZhTEyMzG2OHz8u/P7774WNGzcWtmnTRrhmzRphVlaW3BhKm1evXgm1tbWVXgcU/aetrV2sdaW4PH/+XGhtbS08efKk3HWSk5OF9evXF549e1YoFAqFjx49ElpbWwuvXr0qc/1jx44Jra2thXFxceJlV65cEVpbWwsXLlwosc/Tp09LbPvff/8Jra2thdevXxcvi4mJETo6Ogq7du1a4PepTK9evRLq6Ogo/RxV9J+Ojg7P5f9XGs5l0XdKXkTvP2ccixcvFtra2gr//fdf8bKQkBChtbW18MGDB3nu093dXdi2bVuhg4OD0M/PL8/1Fy1aJOzTp0+e65U2rKNU1BSpj/mpi0JhxaiPr169Eupol417JABCHe3ivU+iiqEsfn8rkvMQCoXCImuBUrNmTYSGhio8a4syGRsbo2bNmsW2/wEDBuTa/0xbWxtTpkyRGOBGRNaoyYqMwGxlZYVt27ZJLW/WrBlcXV3lbteoUSOsX78+z/07OTnleyTo1q1by+wbKKKpqYmxY8di7NixCu+zR48e4nFmyqKaNWviyZMnZaKeAMVfV4qLaNCq3JpjP336FFlZWeJ1rK2tUa9ePSxevBhTp05FtWrV8Pz5c7x79w6zZ8+Gra0tVFRUsHz5cvTu3RsPHjyAv78/BAKBeB+ifX7djaF+/fqoXr06li1bhlmzZiEjI0M8gru8qcRLu5o1ayIkJITncjGr6Oey6P3nbNkyd+5c3L9/H9OnT4e/vz8MDQ1Rt25dNGjQADNnzsTEiRNhZmaGmJgYBAcHo27duhLT1DZp0gRbtmyBtbU1+vXrJ3G8RYsWQU1NDY6OjjA0NERQUBAOHz6MJUuWFPl7K26so1TUFKmP+amLQMWojzVr1kTIk7JxjwSwLlLRKM/f30XahadmzZqscER5YD0pfmFhYdDU1ETt2rVzXUdHR0f8t1BTU8PmzZuxevVqrFixAikpKahVq5Z4fB0rKyssWrQI3t7euHDhAtq0aYOlS5diyJAh4pvMr/cpoqGhAU9PTyxatAjTp0+HmZkZRo8eDS8vr1Lb514RPJeLX0U/l0Xvv1atWhIxrF+/Hn369IGbmxu2bNkCNTU1bNmyBWvWrMHatWvx+fNnVK1aFQ4ODlI/soyMjAAAc+bMkZoNwNLSEidPnsTx48eRlZWFevXqYf369XJnIyjtWEepKClaHxWti0DFqY+si1TRlOfvb4FQmPeAGykpKXj58iUsLS0lBpMjIiIiKksmTJiAzMxMma02iahksT4SkaKK+3qhaM6Ds/AQERFRuZaamorQ0FCcOXMGt2/fxrFjx5QdElGFxfpIRIoqjdcLJlCIiIioXLtz5w7GjRsHc3NzeHh4SDQpJqKSxfpIRIoqjdcLduEhIiIiIiIiogpL0ZyHSgnGRERERERERERUJjGBQkRERERERESUByZQiIiIiIiIiIjywAQKEREREREREVEemEAhIiIiIiIiIsoDEyhERERERERERHnIVwJFgRmPiYiIiIiIiIjKDEVzHQolUFRVVQEA6enpBY+IiIiIiIiIiKiUSU1NBQCoqanlup5CCRR1dXVoamoiPj6erVCIiIiIiIiIqFzIzMxETEwMdHV180ygCIQKZkQ+f/6MN2/eQE9PDwYGBlBXV4dAICiSgImIiIiIiIiISoJQKERmZiaSk5MRHx+PrKwsWFhYQFtbO9ftFE6gANlJlOjoaHHzFiIiIiIiIiKiskhVVRU6OjqoVq0aNDQ08lw/XwkUkfT0dGRmZhYoQCIiIiIiIiIiZVJRUcl3z5oCJVCIiIiIiIiIiCqSfE1jTERERERERERUETGBQkRERERERESUByZQiIiIiIiIiIjywAQKEREREREREVEemEAhIiIiIiIiIsoDEyhERERERERERHlgAoWIiIiIiIiIKA//B3UvRzDTQZ6tAAAAAElFTkSuQmCC_melt[\"split\"]==300) | (df_similarity_melt[\"split\"]==30))],\n",
    "#                 x=\"Similarity\", hue=\"system\", system = \"\", order=order, rotation=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df8c665b-873c-4b18-b16c-3992e4f6f4fb",
   "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": "3.10.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}