CompareMutantSimilarity.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "library(tidyverse)\n",
    "library(jsonlite)\n",
    "library(tidystringdist)\n",
    "library(kableExtra)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "BASE_DIR <- '/Users/jon/Documents/NEU/Projects/llm-mutation-testing/mutation-testing-data'\n",
    "\n",
    "# find all mutants.json files in BASE_DIR\n",
    "mutants_files <- list.files(path = BASE_DIR, recursive = TRUE, pattern = \"mutants.json\", full.names = TRUE)\n",
    "\n",
    "# load in all mutants.json files, adding a column for the file path\n",
    "mutants <- map_df(mutants_files, ~fromJSON(.x) %>%\n",
    "                    mutate(file = .x)) %>%\n",
    "        extract(file, c('model','template','temperature','run','project'), \"mutation-testing-data/([^/]+)/template-([^-]+)-([^/]+)/run([^/]+)/projects/([^/]+)/\")  %>%\n",
    "        filter(!is.na(project))\n",
    "\n",
    "mutants <- tidy_stringdist(mutants, \"originalCode\", \"replacement\", method = \"lv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'project', 'model', 'template'. You can\n",
      "override using the `.groups` argument.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "\\begin{tabular}{lrrrrr}\n",
       "\\toprule\n",
       "project & codellama-34b-instruct_full_0.0 & codellama-13b-instruct_full_0.0 & llama-3.3-70b-instruct_full_0.0 & gpt-4o-mini_full_0.0 & mixtral-8x7b-instruct_full_0.0\\\\\n",
       "\\midrule\n",
       "Complex.js & 4.27 & 4.63 & 6.90 & 6.35 & 8.95\\\\\n",
       "countries-and-timezones & 11.13 & 9.78 & 11.71 & 11.33 & 13.65\\\\\n",
       "crawler-url-parser & 9.50 & 8.82 & 10.71 & 10.05 & 12.65\\\\\n",
       "delta & 9.55 & 8.88 & 13.01 & 11.44 & 14.15\\\\\n",
       "image-downloader & 12.67 & 10.74 & 12.66 & 13.88 & 14.21\\\\\n",
       "node-dirty & 7.53 & 7.42 & 12.08 & 10.20 & 12.08\\\\\n",
       "node-geo-point & 8.86 & 8.15 & 8.97 & 9.53 & 15.27\\\\\n",
       "node-jsonfile & 9.73 & 10.07 & 11.10 & 11.00 & 10.81\\\\\n",
       "plural & 8.14 & 6.29 & 9.27 & 8.31 & 10.37\\\\\n",
       "pull-stream & 6.72 & 8.71 & 7.82 & 8.06 & 9.67\\\\\n",
       "q & 8.61 & 9.71 & 11.17 & 9.92 & 13.23\\\\\n",
       "spacl-core & 9.30 & 10.84 & 8.95 & 8.70 & 12.61\\\\\n",
       "zip-a-folder & 9.85 & 12.38 & 11.87 & 11.23 & 11.61\\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "\\begin{tabular}{lrrrrrr}\n",
       "\\toprule\n",
       "project & codellama-34b-instruct_full_0.0 & codellama-34b-instruct_onemutation_0.0 & codellama-34b-instruct_noexplanation_0.0 & codellama-34b-instruct_noinstructions_0.0 & codellama-34b-instruct_full_genericsystemprompt-0.0 & codellama-34b-instruct_basic_0.0\\\\\n",
       "\\midrule\n",
       "Complex.js & 4.27 & 3.37 & 5.09 & 4.27 & 4.17 & 11.98\\\\\n",
       "countries-and-timezones & 11.13 & 7.75 & 11.17 & 10.87 & 10.85 & 11.29\\\\\n",
       "crawler-url-parser & 9.50 & 6.41 & 9.46 & 9.49 & 9.30 & 20.04\\\\\n",
       "delta & 9.55 & 7.38 & 9.91 & 9.43 & 9.14 & 19.63\\\\\n",
       "image-downloader & 12.67 & 8.82 & 12.89 & 11.01 & 11.48 & 21.92\\\\\n",
       "node-dirty & 7.53 & 6.90 & 7.58 & 7.41 & 7.51 & 17.52\\\\\n",
       "node-geo-point & 8.86 & 6.10 & 8.79 & 7.75 & 8.66 & 15.66\\\\\n",
       "node-jsonfile & 9.73 & 6.98 & 9.76 & 7.77 & 8.91 & 11.64\\\\\n",
       "plural & 8.14 & 5.21 & 8.41 & 7.58 & 7.80 & 23.64\\\\\n",
       "pull-stream & 6.72 & 4.57 & 7.53 & 7.48 & 7.30 & 11.92\\\\\n",
       "q & 8.61 & 7.61 & 9.21 & 8.60 & 8.58 & 16.18\\\\\n",
       "spacl-core & 9.30 & 5.86 & 10.44 & 9.43 & 9.44 & 14.27\\\\\n",
       "zip-a-folder & 9.85 & 5.33 & 9.02 & 10.05 & 10.10 & 24.60\\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate string edit distance between originalCode and replacement\n",
    "# mutants %>%\n",
    "# mutate(b=replacement,a=originalCode)%>%\n",
    "# head() %>%\n",
    "  # mutate(edit_distance = tidy_stringdist(a, b, method = \"jaccard\"))\n",
    "# mutants%>% head()\n",
    "mutantEditDistance <- mutants %>% group_by(project,model,template,temperature) %>% summarise(mean_edit_distance = mean(lv)) %>% ungroup() %>% \n",
    "mutate(mean_edit_distance = round(mean_edit_distance,2)) \n",
    "\n",
    "mutantEditDistance %>%\n",
    "filter(template==\"full\" & temperature==\"0.0\")%>%\n",
    "pivot_wider(names_from=c(\"model\",\"template\",\"temperature\"), values_from=mean_edit_distance) %>%\n",
    "select(project, `codellama-34b-instruct_full_0.0`, `codellama-13b-instruct_full_0.0`, `llama-3.3-70b-instruct_full_0.0`, `gpt-4o-mini_full_0.0`,  `mixtral-8x7b-instruct_full_0.0`) %>%\n",
    "kable(format.args = list(big.mark = \",\"), escape = F,\n",
    " format = \"latex\",booktabs = TRUE, linesep = \"\")\n",
    "\n",
    "\n",
    " mutantEditDistance %>%\n",
    "filter(model=='codellama-34b-instruct')%>%\n",
    "pivot_wider(names_from=c(\"model\",\"template\",\"temperature\"), values_from=mean_edit_distance) %>%\n",
    "select(project, `codellama-34b-instruct_full_0.0`,`codellama-34b-instruct_onemutation_0.0`,\n",
    "`codellama-34b-instruct_noexplanation_0.0`,\n",
    "`codellama-34b-instruct_noinstructions_0.0`,\n",
    "`codellama-34b-instruct_full_genericsystemprompt-0.0`,\n",
    "`codellama-34b-instruct_basic_0.0`\n",
    " ) %>%\n",
    "kable(format.args = list(big.mark = \",\"), escape = F,\n",
    " format = \"latex\",booktabs = TRUE, linesep = \"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# mutants %>% filter(project=='image-downloader' & (template=='full' | template=='basic') & temperature=='0.0') \n",
    "# pivot_wider()\n",
    "\n",
    "biggestDifferences <- mutants %>% group_by(project, template, temperature, model) %>%\n",
    "slice_max(lv,n = 2, with_ties= FALSE) %>% arrange(project, model, template, temperature)\n",
    "leastDifferences <- mutants %>% group_by(project, template, temperature, model) %>%\n",
    "slice_min(lv,n = 2, with_ties= FALSE) %>% arrange(project, model, template, temperature)\n",
    "\n",
    "write.csv(biggestDifferences, file = \"biggestDifferences.csv\", row.names = FALSE)\n",
    "write.csv(leastDifferences, file = \"leastDifferences.csv\", row.names = FALSE)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "mutants_baseline <- mutants %>% filter(template=='full' & temperature=='0.0' & model=='codellama-34b-instruct')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'project', 'model', 'template'. You can\n",
      "override using the `.groups` argument.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A tibble: 13 × 13</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>project</th><th scope=col>codellama-13b-instruct_full_0.0</th><th scope=col>codellama-34b-instruct_basic_0.0</th><th scope=col>codellama-34b-instruct_full_0.25</th><th scope=col>codellama-34b-instruct_full_0.5</th><th scope=col>codellama-34b-instruct_full_1.0</th><th scope=col>codellama-34b-instruct_full_genericsystemprompt-0.0</th><th scope=col>codellama-34b-instruct_noexplanation_0.0</th><th scope=col>codellama-34b-instruct_noinstructions_0.0</th><th scope=col>codellama-34b-instruct_onemutation_0.0</th><th scope=col>gpt-4o-mini_full_0.0</th><th scope=col>llama-3.3-70b-instruct_full_0.0</th><th scope=col>mixtral-8x7b-instruct_full_0.0</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Complex.js             </td><td>3.029531</td><td> 8.892899</td><td>1.978023</td><td>2.448525</td><td>4.379572</td><td>1.636050</td><td>2.346533</td><td>1.968825</td><td>1.858666</td><td>4.778237</td><td>5.050464</td><td> 6.205143</td></tr>\n",
       "\t<tr><td>countries-and-timezones</td><td>7.731699</td><td> 6.927419</td><td>5.964977</td><td>6.580906</td><td>8.674877</td><td>5.661265</td><td>6.633782</td><td>6.751040</td><td>6.127778</td><td>8.447989</td><td>8.692504</td><td> 9.216538</td></tr>\n",
       "\t<tr><td>crawler-url-parser     </td><td>6.407374</td><td>17.646591</td><td>4.714363</td><td>6.072846</td><td>8.710418</td><td>4.246158</td><td>4.992904</td><td>4.371172</td><td>3.949206</td><td>7.595414</td><td>8.720511</td><td>10.252970</td></tr>\n",
       "\t<tr><td>delta                  </td><td>6.173866</td><td>12.739788</td><td>4.024385</td><td>5.215778</td><td>7.883530</td><td>3.554530</td><td>4.605344</td><td>4.742474</td><td>3.989054</td><td>8.526899</td><td>9.576584</td><td> 9.268240</td></tr>\n",
       "\t<tr><td>image-downloader       </td><td>6.559651</td><td>17.385714</td><td>5.674227</td><td>6.432223</td><td>8.670696</td><td>5.374587</td><td>5.788618</td><td>5.784014</td><td>4.718535</td><td>8.667029</td><td>9.373552</td><td> 9.222222</td></tr>\n",
       "\t<tr><td>node-dirty             </td><td>4.308391</td><td> 9.668621</td><td>3.963428</td><td>4.584016</td><td>6.511032</td><td>3.290323</td><td>3.682717</td><td>4.050228</td><td>3.326154</td><td>6.262564</td><td>8.359389</td><td> 7.980945</td></tr>\n",
       "\t<tr><td>node-geo-point         </td><td>6.461708</td><td>14.053691</td><td>3.127130</td><td>4.589208</td><td>7.294772</td><td>2.596789</td><td>3.227074</td><td>3.991463</td><td>3.732180</td><td>7.195719</td><td>7.416413</td><td>11.665262</td></tr>\n",
       "\t<tr><td>node-jsonfile          </td><td>5.977654</td><td> 8.066667</td><td>4.964872</td><td>5.884913</td><td>8.132706</td><td>5.026067</td><td>4.859899</td><td>5.493874</td><td>4.400524</td><td>7.235451</td><td>7.274338</td><td> 7.524360</td></tr>\n",
       "\t<tr><td>plural                 </td><td>7.116323</td><td>20.358684</td><td>5.156992</td><td>6.015751</td><td>8.590891</td><td>4.239615</td><td>5.627558</td><td>5.120312</td><td>4.388862</td><td>8.086278</td><td>9.406288</td><td> 9.392463</td></tr>\n",
       "\t<tr><td>pull-stream            </td><td>5.208274</td><td> 7.742737</td><td>3.474531</td><td>3.897119</td><td>5.137072</td><td>3.357048</td><td>3.757894</td><td>4.301716</td><td>3.365128</td><td>4.850259</td><td>5.449412</td><td> 6.068680</td></tr>\n",
       "\t<tr><td>q                      </td><td>6.183249</td><td>11.048737</td><td>3.925634</td><td>4.715164</td><td>6.457132</td><td>3.368099</td><td>4.634959</td><td>4.165708</td><td>4.334220</td><td>6.652254</td><td>7.676440</td><td> 9.424085</td></tr>\n",
       "\t<tr><td>spacl-core             </td><td>7.461538</td><td>10.587952</td><td>5.269368</td><td>6.123014</td><td>7.726272</td><td>5.109531</td><td>6.321461</td><td>5.739273</td><td>5.093184</td><td>7.395125</td><td>7.619151</td><td>10.313216</td></tr>\n",
       "\t<tr><td>zip-a-folder           </td><td>6.802500</td><td>15.903571</td><td>5.012405</td><td>5.846969</td><td>7.221127</td><td>4.726056</td><td>5.050584</td><td>5.695489</td><td>5.428000</td><td>6.963855</td><td>8.586881</td><td> 8.314523</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 13 × 13\n",
       "\\begin{tabular}{lllllllllllll}\n",
       " project & codellama-13b-instruct\\_full\\_0.0 & codellama-34b-instruct\\_basic\\_0.0 & codellama-34b-instruct\\_full\\_0.25 & codellama-34b-instruct\\_full\\_0.5 & codellama-34b-instruct\\_full\\_1.0 & codellama-34b-instruct\\_full\\_genericsystemprompt-0.0 & codellama-34b-instruct\\_noexplanation\\_0.0 & codellama-34b-instruct\\_noinstructions\\_0.0 & codellama-34b-instruct\\_onemutation\\_0.0 & gpt-4o-mini\\_full\\_0.0 & llama-3.3-70b-instruct\\_full\\_0.0 & mixtral-8x7b-instruct\\_full\\_0.0\\\\\n",
       " <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t Complex.js              & 3.029531 &  8.892899 & 1.978023 & 2.448525 & 4.379572 & 1.636050 & 2.346533 & 1.968825 & 1.858666 & 4.778237 & 5.050464 &  6.205143\\\\\n",
       "\t countries-and-timezones & 7.731699 &  6.927419 & 5.964977 & 6.580906 & 8.674877 & 5.661265 & 6.633782 & 6.751040 & 6.127778 & 8.447989 & 8.692504 &  9.216538\\\\\n",
       "\t crawler-url-parser      & 6.407374 & 17.646591 & 4.714363 & 6.072846 & 8.710418 & 4.246158 & 4.992904 & 4.371172 & 3.949206 & 7.595414 & 8.720511 & 10.252970\\\\\n",
       "\t delta                   & 6.173866 & 12.739788 & 4.024385 & 5.215778 & 7.883530 & 3.554530 & 4.605344 & 4.742474 & 3.989054 & 8.526899 & 9.576584 &  9.268240\\\\\n",
       "\t image-downloader        & 6.559651 & 17.385714 & 5.674227 & 6.432223 & 8.670696 & 5.374587 & 5.788618 & 5.784014 & 4.718535 & 8.667029 & 9.373552 &  9.222222\\\\\n",
       "\t node-dirty              & 4.308391 &  9.668621 & 3.963428 & 4.584016 & 6.511032 & 3.290323 & 3.682717 & 4.050228 & 3.326154 & 6.262564 & 8.359389 &  7.980945\\\\\n",
       "\t node-geo-point          & 6.461708 & 14.053691 & 3.127130 & 4.589208 & 7.294772 & 2.596789 & 3.227074 & 3.991463 & 3.732180 & 7.195719 & 7.416413 & 11.665262\\\\\n",
       "\t node-jsonfile           & 5.977654 &  8.066667 & 4.964872 & 5.884913 & 8.132706 & 5.026067 & 4.859899 & 5.493874 & 4.400524 & 7.235451 & 7.274338 &  7.524360\\\\\n",
       "\t plural                  & 7.116323 & 20.358684 & 5.156992 & 6.015751 & 8.590891 & 4.239615 & 5.627558 & 5.120312 & 4.388862 & 8.086278 & 9.406288 &  9.392463\\\\\n",
       "\t pull-stream             & 5.208274 &  7.742737 & 3.474531 & 3.897119 & 5.137072 & 3.357048 & 3.757894 & 4.301716 & 3.365128 & 4.850259 & 5.449412 &  6.068680\\\\\n",
       "\t q                       & 6.183249 & 11.048737 & 3.925634 & 4.715164 & 6.457132 & 3.368099 & 4.634959 & 4.165708 & 4.334220 & 6.652254 & 7.676440 &  9.424085\\\\\n",
       "\t spacl-core              & 7.461538 & 10.587952 & 5.269368 & 6.123014 & 7.726272 & 5.109531 & 6.321461 & 5.739273 & 5.093184 & 7.395125 & 7.619151 & 10.313216\\\\\n",
       "\t zip-a-folder            & 6.802500 & 15.903571 & 5.012405 & 5.846969 & 7.221127 & 4.726056 & 5.050584 & 5.695489 & 5.428000 & 6.963855 & 8.586881 &  8.314523\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 13 × 13\n",
       "\n",
       "| project &lt;chr&gt; | codellama-13b-instruct_full_0.0 &lt;dbl&gt; | codellama-34b-instruct_basic_0.0 &lt;dbl&gt; | codellama-34b-instruct_full_0.25 &lt;dbl&gt; | codellama-34b-instruct_full_0.5 &lt;dbl&gt; | codellama-34b-instruct_full_1.0 &lt;dbl&gt; | codellama-34b-instruct_full_genericsystemprompt-0.0 &lt;dbl&gt; | codellama-34b-instruct_noexplanation_0.0 &lt;dbl&gt; | codellama-34b-instruct_noinstructions_0.0 &lt;dbl&gt; | codellama-34b-instruct_onemutation_0.0 &lt;dbl&gt; | gpt-4o-mini_full_0.0 &lt;dbl&gt; | llama-3.3-70b-instruct_full_0.0 &lt;dbl&gt; | mixtral-8x7b-instruct_full_0.0 &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| Complex.js              | 3.029531 |  8.892899 | 1.978023 | 2.448525 | 4.379572 | 1.636050 | 2.346533 | 1.968825 | 1.858666 | 4.778237 | 5.050464 |  6.205143 |\n",
       "| countries-and-timezones | 7.731699 |  6.927419 | 5.964977 | 6.580906 | 8.674877 | 5.661265 | 6.633782 | 6.751040 | 6.127778 | 8.447989 | 8.692504 |  9.216538 |\n",
       "| crawler-url-parser      | 6.407374 | 17.646591 | 4.714363 | 6.072846 | 8.710418 | 4.246158 | 4.992904 | 4.371172 | 3.949206 | 7.595414 | 8.720511 | 10.252970 |\n",
       "| delta                   | 6.173866 | 12.739788 | 4.024385 | 5.215778 | 7.883530 | 3.554530 | 4.605344 | 4.742474 | 3.989054 | 8.526899 | 9.576584 |  9.268240 |\n",
       "| image-downloader        | 6.559651 | 17.385714 | 5.674227 | 6.432223 | 8.670696 | 5.374587 | 5.788618 | 5.784014 | 4.718535 | 8.667029 | 9.373552 |  9.222222 |\n",
       "| node-dirty              | 4.308391 |  9.668621 | 3.963428 | 4.584016 | 6.511032 | 3.290323 | 3.682717 | 4.050228 | 3.326154 | 6.262564 | 8.359389 |  7.980945 |\n",
       "| node-geo-point          | 6.461708 | 14.053691 | 3.127130 | 4.589208 | 7.294772 | 2.596789 | 3.227074 | 3.991463 | 3.732180 | 7.195719 | 7.416413 | 11.665262 |\n",
       "| node-jsonfile           | 5.977654 |  8.066667 | 4.964872 | 5.884913 | 8.132706 | 5.026067 | 4.859899 | 5.493874 | 4.400524 | 7.235451 | 7.274338 |  7.524360 |\n",
       "| plural                  | 7.116323 | 20.358684 | 5.156992 | 6.015751 | 8.590891 | 4.239615 | 5.627558 | 5.120312 | 4.388862 | 8.086278 | 9.406288 |  9.392463 |\n",
       "| pull-stream             | 5.208274 |  7.742737 | 3.474531 | 3.897119 | 5.137072 | 3.357048 | 3.757894 | 4.301716 | 3.365128 | 4.850259 | 5.449412 |  6.068680 |\n",
       "| q                       | 6.183249 | 11.048737 | 3.925634 | 4.715164 | 6.457132 | 3.368099 | 4.634959 | 4.165708 | 4.334220 | 6.652254 | 7.676440 |  9.424085 |\n",
       "| spacl-core              | 7.461538 | 10.587952 | 5.269368 | 6.123014 | 7.726272 | 5.109531 | 6.321461 | 5.739273 | 5.093184 | 7.395125 | 7.619151 | 10.313216 |\n",
       "| zip-a-folder            | 6.802500 | 15.903571 | 5.012405 | 5.846969 | 7.221127 | 4.726056 | 5.050584 | 5.695489 | 5.428000 | 6.963855 | 8.586881 |  8.314523 |\n",
       "\n"
      ],
      "text/plain": [
       "   project                 codellama-13b-instruct_full_0.0\n",
       "1  Complex.js              3.029531                       \n",
       "2  countries-and-timezones 7.731699                       \n",
       "3  crawler-url-parser      6.407374                       \n",
       "4  delta                   6.173866                       \n",
       "5  image-downloader        6.559651                       \n",
       "6  node-dirty              4.308391                       \n",
       "7  node-geo-point          6.461708                       \n",
       "8  node-jsonfile           5.977654                       \n",
       "9  plural                  7.116323                       \n",
       "10 pull-stream             5.208274                       \n",
       "11 q                       6.183249                       \n",
       "12 spacl-core              7.461538                       \n",
       "13 zip-a-folder            6.802500                       \n",
       "   codellama-34b-instruct_basic_0.0 codellama-34b-instruct_full_0.25\n",
       "1   8.892899                        1.978023                        \n",
       "2   6.927419                        5.964977                        \n",
       "3  17.646591                        4.714363                        \n",
       "4  12.739788                        4.024385                        \n",
       "5  17.385714                        5.674227                        \n",
       "6   9.668621                        3.963428                        \n",
       "7  14.053691                        3.127130                        \n",
       "8   8.066667                        4.964872                        \n",
       "9  20.358684                        5.156992                        \n",
       "10  7.742737                        3.474531                        \n",
       "11 11.048737                        3.925634                        \n",
       "12 10.587952                        5.269368                        \n",
       "13 15.903571                        5.012405                        \n",
       "   codellama-34b-instruct_full_0.5 codellama-34b-instruct_full_1.0\n",
       "1  2.448525                        4.379572                       \n",
       "2  6.580906                        8.674877                       \n",
       "3  6.072846                        8.710418                       \n",
       "4  5.215778                        7.883530                       \n",
       "5  6.432223                        8.670696                       \n",
       "6  4.584016                        6.511032                       \n",
       "7  4.589208                        7.294772                       \n",
       "8  5.884913                        8.132706                       \n",
       "9  6.015751                        8.590891                       \n",
       "10 3.897119                        5.137072                       \n",
       "11 4.715164                        6.457132                       \n",
       "12 6.123014                        7.726272                       \n",
       "13 5.846969                        7.221127                       \n",
       "   codellama-34b-instruct_full_genericsystemprompt-0.0\n",
       "1  1.636050                                           \n",
       "2  5.661265                                           \n",
       "3  4.246158                                           \n",
       "4  3.554530                                           \n",
       "5  5.374587                                           \n",
       "6  3.290323                                           \n",
       "7  2.596789                                           \n",
       "8  5.026067                                           \n",
       "9  4.239615                                           \n",
       "10 3.357048                                           \n",
       "11 3.368099                                           \n",
       "12 5.109531                                           \n",
       "13 4.726056                                           \n",
       "   codellama-34b-instruct_noexplanation_0.0\n",
       "1  2.346533                                \n",
       "2  6.633782                                \n",
       "3  4.992904                                \n",
       "4  4.605344                                \n",
       "5  5.788618                                \n",
       "6  3.682717                                \n",
       "7  3.227074                                \n",
       "8  4.859899                                \n",
       "9  5.627558                                \n",
       "10 3.757894                                \n",
       "11 4.634959                                \n",
       "12 6.321461                                \n",
       "13 5.050584                                \n",
       "   codellama-34b-instruct_noinstructions_0.0\n",
       "1  1.968825                                 \n",
       "2  6.751040                                 \n",
       "3  4.371172                                 \n",
       "4  4.742474                                 \n",
       "5  5.784014                                 \n",
       "6  4.050228                                 \n",
       "7  3.991463                                 \n",
       "8  5.493874                                 \n",
       "9  5.120312                                 \n",
       "10 4.301716                                 \n",
       "11 4.165708                                 \n",
       "12 5.739273                                 \n",
       "13 5.695489                                 \n",
       "   codellama-34b-instruct_onemutation_0.0 gpt-4o-mini_full_0.0\n",
       "1  1.858666                               4.778237            \n",
       "2  6.127778                               8.447989            \n",
       "3  3.949206                               7.595414            \n",
       "4  3.989054                               8.526899            \n",
       "5  4.718535                               8.667029            \n",
       "6  3.326154                               6.262564            \n",
       "7  3.732180                               7.195719            \n",
       "8  4.400524                               7.235451            \n",
       "9  4.388862                               8.086278            \n",
       "10 3.365128                               4.850259            \n",
       "11 4.334220                               6.652254            \n",
       "12 5.093184                               7.395125            \n",
       "13 5.428000                               6.963855            \n",
       "   llama-3.3-70b-instruct_full_0.0 mixtral-8x7b-instruct_full_0.0\n",
       "1  5.050464                         6.205143                     \n",
       "2  8.692504                         9.216538                     \n",
       "3  8.720511                        10.252970                     \n",
       "4  9.576584                         9.268240                     \n",
       "5  9.373552                         9.222222                     \n",
       "6  8.359389                         7.980945                     \n",
       "7  7.416413                        11.665262                     \n",
       "8  7.274338                         7.524360                     \n",
       "9  9.406288                         9.392463                     \n",
       "10 5.449412                         6.068680                     \n",
       "11 7.676440                         9.424085                     \n",
       "12 7.619151                        10.313216                     \n",
       "13 8.586881                         8.314523                     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mutants %>% filter(!(template=='full' & temperature=='0.0' & model=='codellama-34b-instruct')) %>%\n",
    "inner_join(mutants_baseline, by=c('project','startLine','endLine','startColumn','endColumn','originalCode'), suffix = c(\"\",\".baseline\"), relationship = \"many-to-many\")  %>% \n",
    "mutate(lvDiff=abs(lv - lv.baseline)) %>%\n",
    "group_by(project,model,template,temperature) %>% summarise(mean_lvDiff = mean(lvDiff)) %>% ungroup() %>%\n",
    "pivot_wider(names_from = c(\"model\",\"template\",\"temperature\"), values_from = mean_lvDiff) \n",
    "# select(project,template,temperature,run,model,originalCode,replacement.baseline,replacement,lvDiff)%>%\n",
    "# head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'run', 'startLine', 'startColumn', 'endLine', 'endColumn',\n",
      "'originalCode'. You can override using the `.groups` argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'startLine', 'startColumn', 'originalCode'. You can override using\n",
      "the `.groups` argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature'. You can\n",
      "override using the `.groups` argument.\n",
      "\u001b[1m\u001b[22mAdding missing grouping variables: `model`, `template`, `temperature`\n"
     ]
    },
    {
     "data": {
      "image/png": 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90evBG52F9ueee26YY445YphdmmDgzUnXQhDgxUEkIaIwJu377rtvLI9JbyVDPFA/NkZA4DCpIAQLcYSxngUB+K9//SuKBQRbun62bITH7373uzDbbLNlD8cPSATiIossEo/jxcFbgtjAU1WNwZe1URjt23PPPaMAwIvEGprtt98+IDjSeYQBbUdk4cEhP/kQSHA+/vjjAx4gDM9UOUO4sJ6H8LPkZeOL8YknnoiiLNtHxcqhDjfffHPA84SIY21WPQ3BM2DAgDZFIrJgkMZH9iSCij7Ib1pBnnLrllIZfNFRriaBWgh0x5jh5gZ/WnUEZFUdJ1IRraFVR6De33nFrsr3vQKpGBmPSaCbCSBiknFnnskw4ggbOHBgfPzyyy/HEEicYOKPl+m4444Le+21V/R6xAwl/uGlSkbZhx9+eAzhuuWWW+JOZnhbMO7yZwUS1yc0Lhn1QzggzpjsIyRmnXXWGG7GJg2HHHJIPM9E+i9/+UsgbI7yEDeEcWUNbwVeK+qSN/IjBJMRAoeYYuOEzz77LIZ7pXMLLLBAQeilYzzieUmWuHJXCmO3O8LwCJlDhLFmC/6lDJFDO6s1NprA05fEEfnop2IGe8LXktGeWq6V8pV6RKxlv2zWXnvtWK/8ncz0OoncbHm0I53PHudOX7H02TQ8p+/zgiyfpprX1CGJ/mrSm6a5CdRjzFRLgJs8fD4wYcp+Blabv6elgxU3q7KfcT2NQbXthRXji8/K/PdgtWX0pHR8xjMHqPZmaHvZVFt+25lLe69mPglIoGoC+S//7ESTNUbljDc2235jxSau+bxJcHEcEYR3hi26WfvE3worrBC9Kvl83MHNeksQdXijBo/eEIE1UEmELLXUUtF7hZhCQGHUjy8DvBJMpPOGh4QwrWJbl1PfrLcirVviS4Y1L4QEJuNc8oSlYzwmPjxPIWMpHIRNIhAirBtiK23WTBEaV8zLRX62v05l8BpLZf3yqm0/ICyTKEvnSz0Wa08pgZS9ZjX9zjXxTGZ3JEQc4kV7Z/R6tawRsgfLLPd0nvT0IV9c2XFKnqmmmiolK/nIOKjHxICxq0AqibnlTrT3pwraC4KJLOM/O8bbW1ar5+PzAHGU/Zxt9Ta3t32w4rsLVorvyhT5nIdVo4hvBVLlPjOFBBqGANtgsxMZO5yxfoZ1QOU8INmKs4ED4W94ZNLvHCEUsOwEnNeUmd9yG8HDRCI/eUG0MWHGmLzjGfrDH/4QBRJbeLPJQHaSzJbUrA/KHouZR/9jQs86pLS2Bm8ZAoXJOL+PlP+NpFpilan73XffHQUd4oz2nD96S23WJ2211VaFTQhSXYo98iWXDy3J/rYTHkF+vyhrhNvxwc8W4lkr1p7seZ6nL4rsNbPXy6fPvj7ppJOyL+Nz+pU1ZPRT4v/iiy+OsS4pZWSTC9KRJu1SiNcLdtl1SSm9jxKQgAQkIIFWIDBWKzTCNkigJxBgS212DyNki00M+MFOxEgSCXhf8A4QwlbM8NpwRyutHWE9Ch4UjAl8JUOoLD3ai4SgYPMBJtkILP6S94i1SUzgWfdDPUnHsaxRx3KiDtFC2awXwtvErmnFvBvZMqt5ThnsjsfOf4gw2swaI9ZJcS559th0IRuali172mmnjZ6MW2+9NdbxgQceiGGGKQ11Zec7RCiihpA72p/WMFXqo1ROeqRe1A8OeFA+/PDDMXimtNU8smEGxuYgiBzEHOGW2R31OIcgwqjviiuuGEMlYYLIZAzijaJemgQkIAEJSKAVCSiQWrFXbVPLEWAyjxhizUza9prd0libk0QO5wiBy2+bnWCwtme11VaLO+Gx0QK73/1p9O8QEUbGRL4aw3PFuia8H6ussko47LDDYsgd61uYVCOeEEaEbE088cTR08UxxA6GOEOcsNlDMUOAEKbGBJwNH9hZjnrWwwhfRLghMtj0gY0aWE+FlwvDM5ZEJyKtmLFrG+L0mGOOiZs6sMaKbdqTsenEwQcfHEUMrPfff/+4A1/adKJSH6Vyso9sqkE94c0atLwXLZu20nMEFzv5IRRhDI911103etVSXgQkO/8lI/wQzxm/V0U/41Hadddd02kfJSABCUhAAi1HoNfo0Br3amy5brVBPZUA3iS8ROV2aEk7i6XfBmoPKzwJab1NCtVqTzml8hCyh8cK8dYZhjcG0ZnWOGWvwTmERLmFnLSfdIjAYsbHKptK4GXJryurpo/yZeLtSeXBpR6GuKZ+1ZZHn8AkH2JZj7pUKoO+YrwNGlR53VOlshrp/Eyj+naoOm+GPjXlH3nqyJrSp8Qjd2lfvpS/1sfeo37ZVKXWfO1Jzw5jjG28pa5BqkwQVq5BqsyJFLBifKWfRqguV89NxWc84fUptLy7SbgGqbt7wOtLoI4E+GCp9OHC+Y6II6qLAOvMNSgp3K2OaNoUxUSo1GSo1PFsAbS/nAhFFJXarKGaPspei+eImLRuLH+uva9rLa+z+6S97TCfBCQgAQlIoN4E6nMrst61sjwJSEACEpCABCQgAQlIQALdQECB1A3QvaQEJCABCUhAAhKQgAQk0JgEFEiN2S/WSgISkIAEJCABCUhAAhLoBgIKpG6A7iUlIAEJSEACEpCABCQggcYkoEBqzH6xVhKQgAQkIAEJSEACEpBANxBQIHUDdC8pAQlIQAISkIAEJCABCTQmAQVSY/aLtZKABCQgAQlIQAISkIAEuoGAAqkboHtJCUhAAhKQgAQkIAEJSKAxCSiQGrNfrJUEJCABCUhAAhKQgAQk0A0EFEjdAN1LSkACEpCABCQgAQlIQAKNSUCB1Jj9Yq0kIAEJSEACEpCABCQggW4goEDqBuheUgISkIAEJCABCUhAAhJoTAIKpMbsF2slAQlIQAISkIAEJCABCXQDAQVSN0D3khKQgAQkIAEJSEACEpBAYxJQIDVmv1grCUhAAhKQgAQkIAEJSKAbCCiQugG6l5SABCQgAQlIQAISkIAEGpOAAqkx+8VaSUACEpCABCQgAQlIQALdQKB3N1zTS0pAAhKQgARqJjBkyNAwYMCAmvM1bobhnVK1YcOGhREjRoT+/fu3KX+sndu8rPpFe/NVfQETSkACEmgwAnqQGqxDrI4EJCABCUhAAhKQgAQk0H0EFEjdx94rS0ACEpCABCQgAQlIQAINRkCB1GAdYnUkIAEJSEACEpCABCQgge4joEDqPvZeWQISkIAEJCABCUhAAhJoMAJu0tBgHWJ1JCABCUigOIGBA1tpg4bibWzP0ZlG9W2brV/bl5VevRn6VEpS8vzIU0eWPFfriZG71K+saq8Nucl+TfxzmUy9R/1Q5qynJCCBViOgB6nVetT2SEACEpCABCQgAQlIQALtJqBAajc6M0pAAhKQgAQkIAEJSEACrUZAgdRqPWp7JCABCUhAAhKQgAQkIIF2E1AgtRudGSUgAQlIQAISkIAEJCCBViOgQGq1HrU9EpCABCQgAQlIQAISkEC7CSiQ2o3OjBKQgAQkIAEJSEACEpBAqxFQILVaj9oeCUhAAhKQgAQkIAEJSKDdBBRI7UZnRglIQAISkIAEJCABCUig1QgokFqtR22PBCQgAQlIQAISkIAEJNBuAgqkdqMzowQkIAEJSEACEpCABCTQagQUSK3Wo7ZHAhKQgAQkIAEJSEACEmg3AQVSu9GZUQISkIAEJCABCUhAAhJoNQIKpFbrUdsjAQlIQAISkIAEJCABCbSbgAKp3ejMKAEJSEACEpCABCQgAQm0GgEFUqv1qO2RgAQkIAEJSEACEpCABNpNQIHUbnRmlIAEJCABCUhAAhKQgARajYACqdV61PZIQAISkIAEJCABCUhAAu0moEBqNzozSkACEpCABCQgAQlIQAKtRqB3qzXI9kigOwjcdtttYaKJJgoLL7xwePXVV8PTTz8dNtpoo+6oSslr/vzzz+Hxxx8Pb731Vph33nnDb37zm5JpOVFr+ueeey589NFHRctcfPHFw/jjjx/Pvffee+Ghhx4KE088cVh00UXDBBNMEI+/8cYbsX4bb7xx0TKKHRwxYkS44IILwsorrxwGDRpULElNx3766acwcuTI0Ldv35ry1ZL4u+++K7Aolm/48OHh6quvjv209NJLhyWWWKJYssKx9oy9Un1QKDT35JtvvgkPPvhg4JExPt100+VS+FICEpCABCTQOgT0ILVOX9qSbiRw++23h0cffTTWAIF0xRVXdGNtxrz0119/HdZdd91w1llnhbfffjvsu+++4ZRTThkz4a9Hak1PtsGDB8fyuUb6O+GEE8KRRx4Zvv3221jyRRddFDbffPPw0ksvhSuvvDLsuOOO4auvvornXn/99XDppZfG59X+Q8xceOGFJYVZteWQjsn/lltuGT755JNastWUFh6In3J2/vnnh4svvjj0798//pVLy7lax165Pih2LcbLWmutFev9wgsvhK233jo88sgjxZJ6TAISkIAEJNASBPQgtUQ32ggJlCfApHiqqaYKZ5xxRkzIBBeRtMEGG4QppphijMy1pqeA3XbbLf6lwoYNGxb+9Kc/hTXWWCNeA6/FeeedF04++eQw33zzRQ/VDjvsEMUkj+2xPn36RGHWnrz5PAik999/P3+4rq8RhpU8Qm+++WZYcsklwx577FHXa1NYe/rg6KOPDmuuuWbYfffdQ69evaLH7sQTTwyXX355fF33SlqgBCQgAQlIoJsJKJC6uQO8fOsT+PDDD8NVV10VJ6eEbs0zzzxRmDC5J4ztH//4R9hkk03CjTfeWAh/22yzzaJHivCpSSaZJKy22mphlllmKcAi3Om+++4LH3/8cZhsssnC8ssvHxZZZJHC+fyTpZZaKqy66qqFw4QDYnhvigmkWtMXCs48Oe2008J4440Xtttuu3j0sccei2FwiCOsd+/eMTTusssuC1mBRHjiddddF0aNGhWWXXbZsMwyy8T0xf4lfoQzTj311JElHqobbrghvPbaa2GaaaYJW2yxRZh00kljdkQQ13v55Zejd2ahhRYKq6++evjhhx8K4vHss8+Ooo6+ImyQ0D28NCuttFLsC9jvtNNOherQDwirTTfdNB7D+3bTTTeF559/Psw444yx/rPPPnsUFPTX/fffH8Yaa6zoSSsU8uuTM888M+BJw3t07LHHhp133jmceuqpgfFA+7BPP/00Ck3qQLparNo+SGV+8cUXkdUBBxxQEEPwghFib+65505JfZSABCQgAQm0DAEFUst0pQ1pRAKII8K2EBxMsPEOEELFJJoJLmtomEw/+eSTUQzMNddc4ZJLLgnPPPNMGDp0aMzDuqEDDzwwhqTRxmuvvTacfvrpcUI+//zzhwceeCB6g5hczznnnEUxpPVGrG+hbNbtcGy22WarS/p8IYic66+/PpxzzjlhnHHGiadZn5Qm+Sk94uPzzz+P6344hoA59NBDw3rrrRePH3HEEYFJ+vrrr5+ytHlERMFvueWWC1NOOWV8/uyzz0YRyrqna665JraXMDyM8uCKR2TIkCEBEUdfbLjhhlGA3nPPPWGmmWaK66NeeeWV6N1i7RSiFnbvvvtuuPPOO9sIJEIqn3rqqdgf33//fdhnn31i2nXWWSd88MEHMYyQkDnW7Yw77rhR0M4wwwyxPvl/M888c1yThSimL9P4QNwmdtSfNm+zzTY1C6RKfYBwyxqCDsuu76Ju9ClCrZJAQsDCraNGOZoEupMAawe1ENI6TcKbtfIEYIXxvZCel8/Rs8/yfQerH3/8sVNBjD322PG7uNJFFEiVCHleAh0gQEgTXpD99tsveg0oign5iy++2KZU0iQvCt6Iu+66K07uJ5988ugdYg0I4ooJNF6fXXbZJU7yKQTvEWFslFlKIKWL4VlhfRCTVsRCfkKc0qXHWtOnfKzB+t3vftdGgDHZHjBgQEoSH/GA8EWLWMH4gEQMJm8YXhzC8hAbfKhVY7DcdtttY1JEyZ577hnFFl4k1tBsv/32BW8a57k+E35EFiKT/BxHINFXxx9/fMADhMGjnCFc6B/Cz/AQYkzun3jiidhf5557bphjjjlKhtlRh5tvvjl6nhBxae1WuWvWcq5SHyTPYioTQUUf8Jc1+i2tHcsezz+n7Qg6TQLNTsBx3LYHmchq1REg3FyrjkBX3Azj+56blZVMgVSJkOcl0AECTPTx8uBheOedd+Ifk2V2cMsak+Zk3K0nNAtxhA0cODA+fvnll1Eg4TnA6/Kf//wnejTY/Q3Bw10X0txxxx0xPf8ogwl/MtYcITYI8zr44IOjGGEHuFJWKj1CIDt5X3vttQsfONTt4YcfDocffnibYlNIYfZg+jDs169fPMxEHF7JCIFDbLFxwmeffRbDvdK5BRZYIBTzxGRFYmJICB1GWwlpJGSOvmE9EKxLGXWeddZZS50e4zjhcXjmkjgiwV577TVGOg7g6SLULxntqeVaKV+px2J9VE0fZMsrlp7zCNnUZ9n0+efkT+M3f66W14wT7+DXQsy09SZQj3Fc7zp1R3kII8Kjs59x3VGPZrhm8oYQhQAzrTwBPuMRLtXeDC1fWumz1ZZvj5Vm6BkJdJgA4mXvvfeOH46//e1v4/bafGjiWcpa3rOSnXyyMD5r7P5GiB2hYGzXzRqd5JHCE5P1ciC8sgKJcvigJg+einvvvTeKhmz5+efF0uPhIsQqGcIj3ZGhXMKwFltssXQ6PuLBQSRmjbuyeC2Sh4JJSHpOuuTRQPyx5oV1Wsk4V0wgse4pWfKQEYqHsZEEQoR1Q+wmhzeNtUPJe5fypUe2IE9lpGOprPQ6iTxeI1CTKEvnSz0Wa08pgZS9ZvZ6pcrmeLE+qqYPsmWSHjHEHdDsmKTf2PSjkvFFlM1XKX2p89wAUCCVouPxriBQj3HcFfXs7Gvw+YM4yn7OdvY1m7V8WPHdxXdjCjVv1rZ0Rb25kQmrRhHfCqSu6HWv0WMJEFJFuNZJJ51UuCvCwv/2xm8zUfz3v/8dF++ndTlMYAmXYxKNN6TYVtnsiIZgwSOUDA9QXpilc5XS055SxnbnrP/J3zGjbmw6wZdGOoewS2trKA/RxTqktPkA668QKEzG+X2k/G8k1RLXzYfv3XffHX97CRb0wfmj14OxPmmrrbYqbEJQql0c50suH1qS/e0nvH/8zlTWCLej31iLlrVi7cme53n6osheM3u9fPrs62J9VE0fZMtgkwv6in7Cm4fh9YJddl1SNo/PJSABCUhAAs1OoO2K3GZvjfWXQIMRwJPChJ8JMgKG0LbBgwe3exEid+TxsuCpYJLKpJ9tsxEKXKOUIQjY/IF1TKRjAwUmvausskrMwuYDnKeuWKX0MVGJf3iJioWtsVYK4zrUHSFxyy23jLGbG6IFEcV6IbxR7JqW9SqVuGzFw5TB7nh431KfsMaIXQA5l8Qimy5kwwezBU877bTRm3LrrbfGOrJBBrvaJaOuCGDCAhE1hNyxIUZaw0TfwYcwxGqMelE/OODFYdMPymuvVdMH9E/ySFLfFVdcMa4DgwnjjR3s8BhSL00CEpCABCTQigT0ILVir9qmhiHA7mgIARbc431g1zh2r2OSTshQ8qRUW2HS8+OqeKYQOQgj1hSxuJ/JeCnj+mw7/afRv0tEPSiHzQvSFtrUkTrxGu9NpfSlrsPCfcQH4X95Y7KPp+uwww6LIokQDX68dtFFFy0kRYAg/piAI+SoD1td18MIVaTNtBNmeN7wTPFDthhx4gsvvHBcO0W/FRN57NrGDnvHHHNM/GPrdbbgZvtsjP5lbRfeG35zijBAPH1p0wnWPCFoWX/EboTVGCGaf/vb36KYpY78HlGqczX5s2mq6QP4EHKYdqjjOX3GRiDkJ1R01113zRbrcwlIQAISkEBLEeg1+q72L8H5LdUsGyOBxiLA2iDCpeoZx044Gps91CKy8AKwfoTfPqpmoWKt6aulzqYLeCDy63tSfurIOdYAdYbhjUGApTVO2WtwDiFQjg+eFNLlN9tI5fCxyqYStDG/hgxRizhLa7ZSnnKPeNxSeaWYlctf7FylPsjnoU9ggkjraqOvEM6DBlVe99TVdWuE6800qm+HqvFm6NPu/CNPrd92zyN3qV9Z7W5QiYy9R/2y0UuJ0z3mMJ8DrkGqrrthxY3Q9NMI1eXquan4jOcGbQot724SepC6uwe8fo8gQKhSva3azQCy10Vw1CI6ak2fvVa558V+nDabPoW7ZY/V8zlCtZRYLXU8e33ETTmBgygq1T98+Nf6BYAoqsQsW79qntdaXmf3STV1No0EJCABCUigKwi4BqkrKHsNCUhAAhKQgAQkIAEJSKApCCiQmqKbrKQEJCABCUhAAhKQgAQk0BUEFEhdQdlrSEACEpCABCQgAQlIQAJNQUCB1BTdZCUlIAEJSEACEpCABCQgga4goEDqCspeQwISkIAEJCABCUhAAhJoCgIKpKboJispAQlIQAISkIAEJCABCXQFAQVSV1D2GhKQgAQkIAEJSEACEpBAUxBQIDVFN1lJCUhAAhKQgAQkIAEJSKArCCiQuoKy15CABCQgAQlIQAISkIAEmoKAAqkpuslKSkACEpCABCQgAQlIQAJdQUCB1BWUvYYEJCABCUhAAhKQgAQk0BQEFEhN0U1WUgISkIAEJCABCUhAAhLoCgIKpK6g7DUkIAEJSEACEpCABCQggaYgoEBqim6ykhKQgAQkIAEJSEACEpBAVxBQIHUFZa8hAQlIQAISkIAEJCABCTQFAQVSU3STlZSABCQgAQlIQAISkIAEuoKAAqkrKHsNCUhAAhKQgAQkIAEJSKApCPRuilpaSQlIQAIS6PEEhgwZGgYMGNDjOYwJYHibQ8OGDQsjRowI/fv3b3O8M16MtXP9Sq1nWdXW6rvvvgtDhw4NAwcODP369as2m+kkIIEWJ6AHqcU72OZJQAISkIAEJCABCUhAAtUTUCBVz8qUEpCABCQgAQlIQAISkECLE1AgtXgH2zwJSEACEpCABCQgAQlIoHoCCqTqWZlSAhKQgAQkIAEJSEACEmhxAm7S0OIdbPMkIAEJtAqBgQNbb4OGmUb17VD3vBn6jJG/lr0GRp46coz8HT0wcpf6l9nROuXz9x71Q/6QryUgAQkUCOhBKqDwiQQkIAEJSEACEpCABCTQ0wkokHr6CLD9EpCABCQgAQlIQAISkECBgAKpgMInEpCABCQgAQlIQAISkEBPJ6BA6ukjwPZLQAISkIAEJCABCUhAAgUCCqQCCp9IQAISkIAEJCABCUhAAj2dgAKpp48A2y8BCUhAAhKQgAQkIAEJFAgokAoofCIBCUhAAhKQgAQkIAEJ9HQCCqSePgJsvwQkIAEJSEACEpCABCRQIKBAKqDwiQQkIAEJSEACEpCABCTQ0wkokHr6CLD9EpCABCQgAQlIQAISkECBgAKpgMInEpCABCQgAQlIQAISkEBPJ6BA6ukjwPZLQAISkIAEJCABCUhAAgUCCqQCCp9IQAISkIAEJCABCUhAAj2dgAKpp48A2y8BCUhAAhKQgAQkIAEJFAgokAoofCIBCUhAAhKQgAQkIAEJ9HQCCqSePgJsvwQkIAEJSEACEpCABCRQIKBAKqDwiQQkIAEJSEACEpCABCTQ0wkokHr6CLD9EpCABCQgAQlIQAISkECBgAKpgMInEpBAoxH47rvvqq7S559/Hs4999wwYsSIqvPUI+Fdd90VHnzwwaqKom7U8cMPPyyZfvjw4eGSSy4JRxxxRLj//vtLpksnbrvttvDoo4/Gl6+++mq4/PLL06mSj++9915Md8cdd4Rvv/22ZLp04ptvvglc56qrrgrk1SQgAQlIQAKtTECB1Mq9a9sk0MQETjjhhHD11VdX1YJRo0aFo48+Opx33nldLpDuueee8Mgjj1RVz5EjR4YLL7wwfPTRRyXTn3/++eHiiy8O/fv3j38lE/564vbbb28jkK644oqyWS666KKw+eabh5deeilceeWVYccddwxfffVVyTxvv/12WGuttWJfvPDCC2Hrrbeuur0lC/WEBCQgAQlIoIEJ9G7gulk1CUigBxNgAr/EEktURQAhRfrusKOOOqrqy/bp0ycMHjy4bPo333wzLLnkkmGPPfYom649J/H+ICJPPvnkMN9884Wff/457LDDDgFRxWMxQ3iuueaaYffddw+9evUKF1xwQTjxxBOjB4rXmgQkIAEJSKDVCOhBarUetT0SaBAChJGdffbZYZ999gnnnHNOePbZZ+NrqsfE/Nhjjw2IATxF++23X/RmDBs2LNaeMLGPP/44hpjh8ShneDiYtOMJKWbPP/98OPLII8Oee+4ZhcEnn3xSLFnh2DXXXBMee+yxcP3118d6HX/88TEkDq8PdT3kkEPCvffeW0h/7bXXBrw42Isvvhjr8sorr0SPFm2nLSnsL7X73XffLeTPPjnzzDPD66+/Hl5++eXIh/A3OP33v/8tJPv000/jMcLeajXaNWjQoCiOyNu7d++w8sorhzvvvLNoUV988UWsCx6kJIZWX331yKO7BGnRinpQAhKQgAQkUEcCepDqCNOiJCCBXwgMGTIkehwmnnjisMoqq4S77747rl+ZZJJJwrbbbhsFw0033RTX7vzhD38Iiy22WFx3g4hCzEw33XRh3HHHDZNNNlmYYYYZSmL96aefwmGHHRa22267MPXUU4+RjrVBBxxwQCx/qaWWClzz1ltvjeuAEArFDBHBGqBZZpklLLTQQuHGG2+M4m7ssccOiyyySAx7O/TQQ6PQmH322aOYol0rrbRSeP/992M7Wduz3HLLhSmnnDKcccYZ4fvvvw9bbbVVIBSQOnBu+umnH+PyM888c5hgggkC5c0555wFTquuumqhfUOHDo1lbLPNNlWF4GUvgsjLc4ID67cI/xtrrLb3zBCpWJYVdRtnnHECQm3uuefOFj/GcwQha6o6apSjSaCeBNL6xh9//DEWyzjl/amVJ8BnLp8V/GnlCcAK4/M/PS+fo2ef5XMeVuk92Vk0+J4bb7zxKhavQKqIyAQSkECtBC677LLwww8/hNNPPz16HtZee+247iX/pbrwwgtHAUP5iA3E0zPPPBMWXXTRKGLmmGOOsmF2Z511Vph88sljCNiTTz45RjVPOumksMIKK0SvDyepxwYbbBDIh8gpZYgzQufwsEwxxRThoIMOCrvsskvYcMMNYxbqyAYK1DlviENC2BA7GOLj8ccfjwIpnzb/GuF08803hxlnnDG2qZoNFPJllHuN4BkwYECbJKx1ol+o90QTTdTmHIKqb9++8S97gjzl1i2ltHzhIeg0CTQagfy45POKP606AkxkteoIpMiI6lL37FTpxkVnUuAGnwKpMwlbtgQkUJIAu6nhbUlhWSRE9DzwwANt8pAm2WyzzRYmnHDCQN75558/HY6PX375ZcArkwxRRFq8QYTXFTNC0BAEeJeyRj3wEhUrc9lll41J8R4hjrDkPUHMJePa5C9mfPgmccR56losHA1vGaF0yRZYYIEw66yzppcdfsRTlRVYiEPWQOW9Mel1v379xrhmsfQkImSwWPp8AeSHVUeNu69d8cXZ0Xqav3kIpHGJ54jJPuOZ965WngCs8KbLqjwnzsKK8UVUQPo+qZyr56bg+wrhwvjqTMtHSpS6lh6kUmQ8LgEJtJsA3oi55pqrTX6+JPJGCFoyxBRpit2ZpLwbbrghJQ14lliXw6SGNToYabCDDz44rLHGGgWRQphe1gj7Sx6TfJlJIA0cODCbJT4ff/zxxzhW7ADep6zxYVwsdAfRRPheMrw3pQRSNn8SNClfqUe2HycMLhlrjSaddNLwzjvvpEPxkTvpXBtPUd5IjxjiDmhWEJFnqqmmyicf4zVfdNXcqRsjY+4ADBVIOSi+7BCBNC75LOAzBzGfjnWo4BbPzM0KWVXXybBCIPHZqqCszIz3IawYX41gCqRG6AXrIIEWI0CI2GuvvdamVXht8kZYXFrHwuYJH3zwQcCTlDfKu/TSS9scRtxkw7zYFIJNEhBPiCBC47hrx28EsWNbMl7jISpWZkrTFY8bb7xx4K+cpS+KrGgst0V4tizCC/NGm/k9I0RWuqMJs/y6pJRvmmmmielIw3osDK8Xk8rkWUtpfZSABCQgAQm0CoG2K3JbpVW2QwIS6FYCf/zjH2MY2ymnnBLeeOONuIsdu8nljck6nhTC1VgXxEQ9iRm8OO+M9nawhqeYsfX0lltuWfhbccUVY7LNNtssii68F6QhNO/hhx+Od/IQVVxvmWWWKVZkwx3jbhoeMNYl4cVBBJYKKaym8ssvv3xMxiYUiJy33nor3HLLLXF9WMrPOQQRRh/Ala3BCX9gjQY7E+KNynvmUn4fJSABCUhAAs1OQIHU7D1o/SXQgATYvOCYY44JeIh22mmnKErYHjofZsBObbvuumtYf/31oxj6+9//HlIoG7+BNHjw4DHWENXS3O233z4suOCCYf/994+76Z0/+kdY+X2hJBRqKau70u69997hiSeeiPVnE4tKXqdy9URwHXHEEeG6666LIoetz9ddd924PizlY2MNNqFIxu8j0W+ELbKOCc8TfaZJQAISkIAEWpVAr9Gx7e5r2aq9a7sk0E0E8BoRHpbdypqQL36olN8SIi4bkcJub/POO2/0TuR3UKPqxHCzBia/rqfWZrFt6Ndffx03TKg1byOkx9vz2WefRa9NtQtMK9WbkEa8QNWWx7ojvHJJwFYqv57nGS94GQcNqrzuqZ7X7YqyZho15tqvWq77ZuhYvP7IU+u/XfPIXepfZi1Mqknbe9QvO9axto2xjbc0u86umjJ6YhpYuQapup6HFeMr/TRCdbl6bio+49khNYWWdzcJPUjd3QNeXwItSIAd2vA8PPfcczE0jN8jYkMCtrHOGx+GxcQR6TjXUXFEOXhA2E2uWQ0Rw5qqasVMNe2stTy2B+8OcVRNW0wjAQlIQAISqCcBN2moJ03LkoAEIoG11lor7qB23HHHhXfffTdMO+20MVRutdVWi+fZsY5tdtNGAWKTgAQkIAEJSEACjUJAgdQoPWE9JNBCBBA+O+64Y/wjvC2/9ojX2S2uW6jpNkUCEpCABCQggSYnYIhdk3eg1ZdAoxPIi6NGr6/1k4AEJCABCUigZxNQIPXs/rf1EpCABCQgAQlIQAISkECGgAIpA8OnEpCABCQgAQlIQAISkEDPJqBA6tn9b+slIAEJSEACEpCABCQggQwBBVIGhk8lIAEJSEACEpCABCQggZ5NQIHUs/vf1ktAAhKQgAQkIAEJSEACGQIKpAwMn0pAAhKQgAQkIAEJSEACPZuAAqln97+tl4AEJCABCUhAAhKQgAQyBBRIGRg+lYAEJCABCUhAAhKQgAR6NgEFUs/uf1svAQlIQAISkIAEJCABCWQIKJAyMHwqAQlIQAISkIAEJCABCfRsAgqknt3/tl4CEpCABCQgAQlIQAISyBBQIGVg+FQCEpCABCQgAQlIQAIS6NkEFEg9u/9tvQQkIAEJSEACEpCABCSQIaBAysDwqQQkIAEJSEACEpCABCTQswn07tnNt/USkIAEJNAsBIYMGRoGDBjQLNWtsp7Dq0xXfbJhw4aFESNGhP79+1fMNNbOFZPUnKAzyqy5EmaQgAQk0AECepA6AM+sEpCABCQgAQlIQAISkEBrEVAgtVZ/2hoJSEACEpCABCQgAQlIoAMEFEgdgGdWCUhAAhKQgAQkIAEJSKC1CCiQWqs/bY0EJCABCUhAAhKQgAQk0AECCqQOwDOrBCQgAQl0HYGBAweEXr1CQ/w9//6JXddwryQBCUhAAl1KQIHUpbi9mAQkIAEJSEACEpCABCTQyAQUSI3cO9ZNAhKQgAQkIAEJSEACEuhSAgqkLsXtxSQgAQlIQAISkIAEJCCBRiagQGrk3rFuEpCABCQgAQlIQAISkECXElAgdSluLyYBCUhAAhKQgAQkIAEJNDIBBVIj9451k4AEJCABCUhAAhKQgAS6lIACqUtxezEJSEACEpCABCQgAQlIoJEJKJAauXesmwQkIAEJSEACEpCABCTQpQQUSF2K24tJQAISkIAEJCABCUhAAo1MQIHUyL1j3SQgAQlIQAISkIAEJCCBLiWgQOpS3F5MAhKQgAQkIAEJSEACEmhkAgqkRu4d6yYBCUhAAhKQgAQkIAEJdCkBBVKX4vZiEpCABCQgAQlIQAISkEAjE1AgNXLvWDcJSEACEpCABCQgAQlIoEsJKJC6FLcXk4AEJCABCUhAAhKQgAQamYACqZF7x7pJQAISkIAEJCABCUhAAl1KQIHUpbi9mAQkIAEJSEACEpCABCTQyAQUSI3cO9ZNAhKQgAQkIAEJSEACEuhSAgqkLsXtxUoRuOaaa8JLL71U6nSb46+++mq4/PLL47Eff/wxnHvuueGTTz5pk6YRXrz55pvhkksuCYMHDw7ff/99ySo98cQT4a677iqc//nnn2ObPv7448KxSk9GjBgR83z44YeVklZ1/qeffgrDhw+vKm17E3333XftzdrQ+WptVzY94+DBBx/s9Pa999578T10xx13hG+//bbi9b755ptw2223hauuuiqQV5OABCQgAQm0MgEFUiv3bhO1DYH04osvVlVjBNIVV1wR0yKQzjvvvPDpp59WlberEv31r38Ne+yxR5xMnnHGGWGXXXYJQ4YMGePyCLuDDz443HnnnYVzCCTa9NFHHxWOVXoycuTIcOGFF9aUp1SZTIa33HLLThWdJ5xwQrj66qtLVaFpj9farnz6e+65JzzyyCOd2v6LLroobL755vGGxJVXXhl23HHH8NVXX5W85ttvvx3WWmut2F8vvPBC2HrrrTu9jiUr4wkJSEACEpBAFxDo3QXX8BIS6FEEnn/++eg1uuyyy8JUU00VEHHrrLNOuPXWW8NGG21UYIGoOeKII0KvXr0Kx9r7pE+fPvGa7c2fzYdAev/997OH6v4cb+ESSyxR93K7u8Ba25VPf9RRR3VqE/D+IL5PPvnkMN988wXE+A477BBvOPBYzI4++uiw5pprht133z2O1QsuuCCceOKJ0QNVj7Fb7Joek4AEJCABCXQnAQVSd9Jv4mt//fXX4aabbgqIgRlnnDEss8wyYfbZZ48tItzrxhtvDI899ljg+fzzzx/WX3/90Lv3/4Yb5+6+++4wbNiwsPrqq49B4vXXXw/XXnttIMxshhlmCJtuummYdNJJx0iXP4AYIQzolVdeCYQuTTfddFGUTDnllDEpnqppp502eloeeuihMNlkk4VNNtkkTvwQNNxJX3bZZWN7UtmEraXQor59+4Z55pknbLDBBgFRUsyo57HHHhvFEedp94ABA8KXX37ZJjnXY4LJ9T7//PM253gBYzwMXH+uueaKDLh+MWOi+49//CO2deqpp47P8RLccMMN4bXXXgvTTDNN2GKLLQoMEUFc/+WXXw79+/cPCy20UOyHH374IeDxws4+++ywxhprBK753HPPhUGDBoXbb789rLTSSmGSSSaJoWA77bRToTr33XdfFFb0FVZqjBAeSb/ef//9YayxxorejEIhmSeVxhF9Sbtg98ADD4Rxxhkn1nfBBRcslFJuHOGxfOqpp+L4vP7662MY5CqrrBIWXnjhyAZvCWN31VVXjf337LPPlm1zsXaVG4/F0jPmxx9//MiYRvD+om5ffPFFfB8gsKeYYorYPupPeCb1ve6662Ia2s7YHHvssQsMsk9439GPiCOMsbnyyivH9hYTSFyXMXLAAQcUhDzvV8YG4m7uuefOFu9zCUhAAhKQQEsQ+N+MtSWaYyO6ggDrafbZZ5+4RgXPyAcffBDDdC6++OI4+eKOMxNW7jqPN954cR0OYUPcdUYQ8PzAAw8MK6ywQphjjjkC6YcOHVqo+pNPPhn+/Oc/Rw8Dwuvmm2+OIV/cua4kkvbee+8ojLg2k1OE2sMPPxwngEzGmSCyLmiWWWaJooDzTHyZUC6yyCJRLBx66KGxHQg+xAnhZksttVSctLKu6Pzzz4+T/6w4KFR+9BO8Rvxhb7zxRrjllltieB3CIhlhgggUJppwK2ZwWXzxxQOTXkIKmcyfcsopxZKGUaNGRcG63HLLBcQg4pV2IeYoAzHxzDPPxDA8CsBzBXM4Efp32mmnxTZtuOGGkQ2hXjPNNFOYeOKJo9jk+kzcKY+1Se+++24MC8wyoE3UEYFUbowgWscdd9woThG/pazSOKIvYYhgYJzQ3r322iswThDtlcYRXjJECuGNTPqZ8B900EFRPCBof//734dLL700imbC0Cq1uVi7yo3HYulpE+KTscJaJITJYostFscffYoXkjV3iBzqj3BnHVHqd8Qt7LfaaquiWAnbREBnjbIQmXg0eY9kLa2DI00y6ocYJay1kkBCuCO6O2qU02g2fPiPVa3f6o56s4aQ/qxmfVl31K+Rrsn3BMbnGsy08gTgxc0r/rTyBNLY4jM5PS+fo2ef5XOem+albvDViw7lMzetZAqkSoQ8PwYBJmp4WphcJi8KA5u72bPOOmv0MqTJPZkRHtttt130GCy55JLhn//8Z/QapEkck1u8OMlOPfXUeFecdTwYk3jWPbDGhglwKWOiP9FEEwUmpWnizSR03333jZN/JvsYk3NCmbh7zuSaSTFrhBAHGEIC7wYCiZAkPDz77bdfYfKIZ6Sa9VKfffZZ2HnnnQteMjxXGF/ECBTOJc9WPJH7BxcmyNi8884bQ6FgnPWQ5LK0eUm9t91223gMDnvuuWecCCMy8Y5sv/320TtCAs4zOWDiy2T7zDPPjO3mON442nz88ccXvIR4pspZuTFCfzLJRxyXCrPDa4G3qtw44vp8yP3rX/+KfbPuuutGDxKMEEjVjCNEIl46+poxTL8zoT/ppJNi8xCeeGcQSJVs0UUXbdOuSuMxnz5fPnXgJsIhhxwST6299trRO3TWWWcFRDzGNQiXm3nmmeNrhM7jjz9eUiAheBB/WcODSN+n+mbPIajwIOY9l+Qpt24plQFTvJWtaLyPG71tTsqqH3m87+sh5qu/YvOmRIDLqvr+Y9KvVUegK1gxz1EgVdcfpqqRAGFLv/nNbwriiOxJuDBxRjQtsMAChVKZCCdPBKFceJyy57k7ncQDX+h4XbhLffrppxfK4M42HopyNnDgwHD44YcH6ofXBnGDVwFjMpMM71EK90t3xglTSjbhhBMWwuEQd4RZ4Rl555134h8T8CS2EALZu7RMYhFgGOF7TPJpD4KIzRj+/ve/x4n79NNPHwjnKmd/+MMfCqdhOMEEE0QG8EVAJINlEoTpGI9zzjln4eXkk08en6cvNcKqCMmjfrQRoYKoKGVcE/FbrZUbI/kyCD3EC5KMusK03DhCaGMIm+T14BHm6W5dNeOIO0mMBywJ5vxYIMysPVbteCxWNhNvxAw3FrKGqMLLlIwP+iSOOAY7PGFYsbEJU0RL1tLrfv36ZQ/H58XSc4K7x8XS5wsgPzctOmpMyLLvs46WV4/8fMHWo231qEu+jOQNqWYSkM/b017DikkZ4zl/I6CnsaimvbDis5LPHq08AVgxvrihlOYc5XP07LN87/GZ1dms0pyhEm09SJUIeX4MAkxo04Q7f5IBzkQ++8VMWB0TCe5S84HBXfm8ez65VFk3xHnyky8ZwooPmXLGBxGhe6zbwOPCH3fg8ZZkjYlr3ggfK2ZMsvFI8Yb97W9/G8tkAp62OmZb5uwOegiPJJBSeUzA//jHP4bjjjsusCMYHgnqhlcKI2wPYchrPEYpf5YxfLjzTzomwIQGJoNtMYGU7YP0gQBbbLfddosilXVD7CaHV4LQuGLrUEhPn6YyeI2lsn55FdpMvMuNkZQ+PeK5yHqkEINM+suNo5Q320aOpTpWO47o9zT2UpnZsZAdg5wv1+aUPz1WOx5T+uxj8kwg+LKGMM+GAaWxktLQ/lTHYmMT7yFCP2t40RhDxSaHpOe9miaQKR95UhhpOlbsEbZ5vsXSVTqW74dK6bvifJ8+vQvv1a64Xi3XYIzQb/nxUUsZPSVt+i5CzMurcq/zHSSrypxIASu+BxCTCsrKzPie4XuI8dUIpkBqhF5osjrgdXnrrbfa1JpwOz4ImKgTeoMHIXkcCPtBBLBpAJ4hJnncBcczg5Ge8xgTNe7kMTEjBCwZ6SvdVSA8inUnrJdJC9kRAFiaNKbyqn0kFIwwM8Kd0kSPDQvSJDWFYmXL4/ppzVU6zoSdPEzoU9hbOoeY4DwbMWQ/GBBnHMNYC8UfmxIg+jbeeOOUPT5yh71aw4vEBhl4I1jfQr3OH72uihBGwh6rmYzyYY9QzFp2W/JyY4Q1XVnDc8Van6z95z//KTuOsmmLPe/IOCpWHscqtTmfryPjkfHLeH/00UcLGypQPq+Txyt/vfzrYmMT1vyeEV6j9H4iXDS/LimVxXgjHWm4SYHU5+NbAABAAElEQVThvWTMJO9rSuujBCQgAQlIoFUItF2R2yqtsh2dSoAF7YgEhACTZMQQC+MJdyJci8kdmw+wiBzvCqFyhK3hgcEILWNh/NNPPx1j+BEhWWPjB0K/2OiBu3usCcKzgqehnCG+SJ/WRhCihGcEQ7y1xyiTu/nkR2Qx6R08eHDZBZdLL710bBteHiaihPmxSQLHWXOEQMj+wY0QQ45lvRfsaEZ4F3+0A29CqTU7tbSNOzR4seiX1DbWGFE+59IaFUIaS4U1UV/u9rBpAG2kr7I/cFpujFBXvHjvjPZkIJ6LWTXjqFi+7LH2jqNsGdnnldpM2my7qhmP2fTZayHGWatF6CGbjDD+8LLhPWRtWntt+eWXj1nZqASRw40OwlG5eZGMc2mNHfVbccUV49bgjAXENe9tPKV571bK76MEJCABCUig2QnoQWr2HuyG+s8222xxPQ13qNk1i7v1bOPNpBZji2s2QSBki7vP7IbGQnK8QhjrKhA7bJ7AJI0705SZDC8Gk2/W7DBRxOOEx6TSxBCP1GqrrRZ/r4VQCa7NLmtsLoCIK7fGJl07/8jGDUwimaziQaCelIm4wOuTFTQpLwKR34xhMwoY4WbH65PWaaV0lR5Zg8S2zggQwpmOOeaYuoSA4CFiwwbagIhAVFL+kUceGatEm1iHw3ou2l+MG7uXrbfeerFO1AuvxmabbVZYH1NpjCD0GBOIR4Rg3hBqlcZRPk/+dXvHUb6c9LpSm0mXb1el8ZhPn67FIx5UBMn+++8f3wfcZODHh5PIyaat9jlcWQ932GGHxd0c8WiyuQXexGSMC0It0w51PCd92vKdGx277rprSu6jBCQgAQlIoOUI9Bp9V/yXRQkt1zQb1NkEGDrs1Mad5GJhWaxT4HiptUPcFccDxcSvmCEMalnLksog3AwBlgRZOt6RR8oj/K2ahenpOtQfLxaehPxamZSm0iNtSd6dSmnbcx4hSj8gcvOW4oFTaGH+PK+ZwJMubVqRT1NujNA2xFmluP9K4yh/zfzr9o6jfDnpdaU259tVaTzm06frpEcENmMguyYtnevI4yeffBLfu2ndVqWy6AfGQrGbApXydvQ8Y5TPgkGDpupoUXXL/9x7J4Z5p92zbuXVsyDek7y3Sn321vNazV4WN7oY23hLa/l8b/Z2t7f+sOK7sL3fae29bjPmgxXjizmAa5Aq9yCf8XxmZZcaVM7VeSkUSJ3H1pIlIAEJSKAOBBRItUFUIFXPS4FUPStSKpCq56VAqp4VKRtNILkGqbb+M7UEJCABCUhAAhKQgAQk0MIEFEgt3Lk2TQISkIAEJCABCUhAAhKojYACqTZeppaABCQgAQlIQAISkIAEWpiAAqmFO9emSUACEpCABCQgAQlIQAK1EVAg1cbL1BKQgAQkIAEJSEACEpBACxNQILVw59o0CUhAAhKQgAQkIAEJSKA2Agqk2niZWgISkIAEJCABCUhAAhJoYQIKpBbuXJsmAQlIQAISkIAEJCABCdRGQIFUGy9TS0ACEpCABCQgAQlIQAItTECB1MKda9MkIAEJSEACEpCABCQggdoIKJBq42VqCUhAAhKQgAQkIAEJSKCFCSiQWrhzbZoEJCABCUhAAhKQgAQkUBsBBVJtvEwtAQlIQAISkIAEJCABCbQwAQVSC3euTZOABCQgAQlIQAISkIAEaiOgQKqNl6klIAEJSEACEpCABCQggRYmoEBq4c61aRKQgAQkIAEJSEACEpBAbQQUSLXxMrUEJCABCUhAAhKQgAQk0MIEerdw22yaBCQgAQm0EIEhQ4aGAQMGNEiL9myQelgNCUhAAhKoNwE9SPUmankSkIAEJCABCUhAAhKQQNMSUCA1bddZcQlIQAISkIAEJCABCUig3gQUSPUmankSkIAEJCABCUhAAhKQQNMSUCA1bddZcQlIQAISkIAEJCABCUig3gTcpKHeRC1PAhKQgAQ6hcDAgY2yQUOnNK+OhfarY1n/K2qmUX3Dqxv3Cr0v++F/B30mAQlIoAUJ6EFqwU61SRKQgAQkIAEJSEACEpBA+wgokNrHzVwSkIAEJCABCUhAAhKQQAsSUCC1YKfaJAlIQAISkIAEJCABCUigfQQUSO3jZi4JSEACEpCABCQgAQlIoAUJKJBasFNtkgQkIAEJSEACEpCABCTQPgIKpPZxM5cEJCABCUhAAhKQgAQk0IIEFEgt2Kk2SQISkIAEJCABCUhAAhJoHwEFUvu4mUsCEpCABCQgAQlIQAISaEECCqQW7FSbJAEJSEACEpCABCQgAQm0j4ACqX3czCUBCUhAAhKQgAQkIAEJtCABBVILdqpNkoAEJCABCUhAAhKQgATaR0CB1D5u5pKABCQgAQlIQAISkIAEWpCAAqkFO9UmSUACEpCABCQgAQlIQALtI6BAah83c0lAAhKQgAQkIAEJSEACLUhAgdSCnWqTJCABCUhAAhKQgAQkIIH2EVAgtY+buSQgAQlIQAISkIAEJCCBFiSgQGrBTrVJEpCABCQgAQlIQAISkED7CCiQ2sfNXBKQgAQkIAEJSEACEpBACxJQILVgpzZSk5588slw8803V1WlH3/8MZx77rnhk08+CdnnVWXuwkRvvvlmuOSSS8LgwYPD999/X/LKn3/+eWzPiBEjYpqff/45vv74449L5smfIC9MPvzww/ypdr/+7rvv2p23moydXX7iX01dqknT2fX96aefwvDhw2NVOqM/q2ljPs17770XLr/88nDHHXeEb7/9Nn96jNfffPNNuO2228JVV10VyKtJQAISkIAEWpmAAqmVe7cB2vbUU0/VJJDOO++88Omnn0aBlJ43QDMKVfjrX/8a9thjjzhJPOOMM8Iuu+wShgwZUjifnowaNSocffTRgTZkBRKvP/roo5Ss4uPIkSPDhRdeWFOecoWecMIJ4eqrry6XpEPnHn744bD33nt3qIxKmd966604ua+UrprznV1fhMWWW24ZRT/1qXd/VtPGfJqLLroobL755uGll14KV155Zdhxxx3DV199lU9WeP3222+HtdZaK46bF154IWy99dbhkUceKZz3iQQkIAEJSKDVCPRutQbZHgl0FoHnn38+eo0uu+yyMNVUU0URt84664Rbb701bLTRRm0uiwhhAtpR69OnT7xmR8tJ+anTEksskV7W/RHx8sMPP9S93GyBK6ywQuCvHtbZ9UUgvf/++4Wq1rs/CwVX+QTvDyL95JNPDvPNN1/Aq7nDDjuEK664Ij4WKwahv+aaa4bdd9899OrVK1xwwQXhxBNPjCKV15oEJCABCUig1QgokFqtR+vQHkJpHn/88TgZWnzxxQN/vXv/MlQQCddff3344osvwgwzzBCFwRRTTFG4KqFgN910U3j99dfjBCx5T1ICwpkuvfTS8Morr4QJJ5wwrLLKKmHBBRdMp8s+Pvjgg+G+++4LhKhNNtlkYfnllw+LLLJIzPPiiy8GvFXzzz9/rB+hb5S98MILBwQNd745t+qqq4YBAwbEPNQ1hQz17ds3zDPPPGGDDTYITGKL2aSTThqOPfbYKI44DxPK+vLLL9sk5447k0juzB933HFtzvHi66+/DnhyuP5cc80VNt1008D1ixkT2H/84x+R8/TTTx+uueaaMM000wTC9x544IEwzjjjhDXWWKMNQwQbnAjtmmWWWcImm2wS60lIFezuv//+MNZYY4UNN9wwTnSZ/F588cVh6qmnDltttVX45z//GTbbbLP4mjrh0WNSvdNOO4X+/fvHahYbI4yN//znPzE9nLLps22rpg3lxhl9fdddd8UJe+KDR+SGG24Ir732WuSzxRZbBPoL4xiCldDNQYMGRV5wf/rpp8eoL+2adtpp4/inX+GBt4Syll122UIzzjrrrDie0th9+eWXY50++OCDsNBCC8W04403XsDLiJ199tnxuozBbH/y/rjxxhvDY489Fj2NnF9//fUL77dKrBBgjG+uT99w7dVXXz2+dwuVzTzhOjBAHGGM4ZVXXjmWgVDKG+9zyj7ggAMKZVI+7UFszz333PksvpaABCQgAQk0PQEFUtN3YX0bcM4558TJJJNuRMhJJ50UPvvssygcEChMlBZbbLGw1FJLRSHEZJw1Mky6hg4dGsPPJppoojjpYrLJepHZZpstVhLRss0224Txxx8/TuKYeP35z3+Of0zSytm1114bTj/99CgmmEQiDvbdd99w5plnhjnnnDPepUcA3HnnnbFsJm8HHXRQnAgiYn7/+99HYUYoEcIFcULoE+1YaaWVYj3PP//8KF6Y2BczvEb8YW+88Ua45ZZbYngd+ZMhSg477LCw3XbbFQRGOpceuSOP6GRyzZ17hN0pp5ySTrd5JFQPwbnccssFBBITXCbEiNJlllkmPPvss2GvvfaKgmzGGWeM60T+9a9/BQTCwIEDw3XXXRfz0EfTTTddGHfccWO/Im4RF5SNUIAha1GYsHMMIYlgwuhXjtF3TMJLjREm54wZxBvlJVHdpkGjX1RqQ6Vx9t///jfcfvvtUSCl+sIBgQtXRMUzzzwTQxMRObvuumv0ODGmYU3/ImAZp/n6Pvroo9EzMuWUU8a2InIIw4NtViDde++9UeDThwi2PffcMyywwAJhySWXjH1wzz33xPcOApXnM800U5h44olDvj8ZC4xlRCrXYm0bggwPDd6ZSqyOOOKI2D/kJ9TztNNOi2MYwVjMCO9M/ZrO896lzwj/QzhnLa2XI02ySSaZJApzhHMlgcQYK7dOL5VZ6ZFytMYhgDBvFeMzG8Pznb+h1yptrGc7WB8MJ9+TlanCChs2bFhhHWrlXD03BWMKVvnvoXoTGXvssUO/fv0qFqtAqoio5yRgkoRIYIKd7jBz5xxvBBM7xBKhTYccckiEsvbaa0fhxN30Qw89NE72meQhZJjcEX62/fbbFwByF5870tx9nmCCCeJ57tYzqcuKjEKGzBOEDet9mAhieI+Y8DI5ZTKOMZHHMzP77LPHD288JXzpUW+MNiAYEEiEGjHh3W+//QpvRjw7lFfJEIw777xzfCNzN502JIPF5JNPHuvJBhXFDGGD0MTmnXfeGNr0xBNPtPECFcuXjsGYPuJDZN11140cyM8kHs8L7cc7RB/89re/jR4jPqgXXXTRKGbnmGOOGGbHBxG29NJLF8KrKi3YLzdG8HzgmUHApH5Kdc4/lmtDpXGWL4vX9OW2224bTyEEESzU9Z133olfTIg7BFESmoyFGUaLxGL1xZuHF40P0Wrs1FNPjTcEEKoYNxD+8pe/xHVjXA8RT/2oV5qMkY4bBAi9JJg5hkcUcc3YRWxh5VjhGeU9hqDFuAZCp5QheJIHNaVB9JIHgQWjrCGo4JH3cJKn3LqlVAZfeJXGVErrY/MQaMU+ZSOVtJlK8/RE99Q0+znWPTVorqvW4yZRc7W4/bVN85L2l1A5J5E3CqTKnEyRIUBYHOFlTKqTMZnnjzuGTK6YvGWNSTd3uTG8Knh3susSCHFj8o4xIeQuOuFcyRAbTLS4G41nqZQxwWXCSwjXu+++G6/Fl1m6Q0M+JrTcscfwXuBl4frJCOlDoGFMRKkrHgUm0fxRT+qH4ZGgvsnwDsw666zxJV4HJra0lzv4Bx98cPj73/8ey8KjhneinP3hD38onEasIBZfffXV6GVgV7FkCK1i64UQQOkOC4/UJ30AMyHfZ599YkgebaR/1ltvvZLeHK6FSKjWyo2RfBl4b/LtSV6YUm2oZpzlr8PrJJJ5DjcMcUzb8H6wRgwvIkzwVuJdK2XUrVpxhNBiHGy88caF4hhnCCwMT2UpSywZW8kYD4xBQlCTQCrFijy0hZA9xiNtY7wglDG8ftmJLDc0eH/n7/ym18W+MIqlp2zuIBdLz7mskT+9p7LHa33OhKyVvBa1tr/R0tejTxulTXxOMCnj+yd/I6BR6thI9SBMnu9XWVXuFVgxT+GmVKmIisql9JwUfMZzQ7CzWWXnqOXo6kEqR6eHnWNCy4descGTJidMxrPGF2W6Y02a7Hok0mUnmpwnxCtbPpNZ1rukCX+27OxzdtvCM0WoEl4XRFve28MXXPZ65M+Krux1mdSy2xpvRAQhZSIy0hbGhOixNiQZd9aTQErHEGN//OMf4zojPghZb8KkkfU3WNrdDgGFt4sQNCxN4HlOffnwROiRnnU0yZKnJ71Oj3yAZC3L7ne/+11cL8SEmdAwQhMJccQrw13/YlZMLDDxT5Ym0LwuN0ZS+vRYrD1JIJVqQzXjLJWffcyWl3jQBvoDr17igZhAvOC1gVUxy3tYSJPlwet0B5Uxw1/2+pyvxmgr4jiblzHKWEvvKcrJnud1ah/Pd9tttxjah5cXDy1tZU0b64lYp8WNh2SIKTzC3AzIGp5XrllswkN6xBATyKwgIk8KN82WlX/O+M6/J/NpfN18BIqNleZrxS81Tp9vTvqr60Em/Nz4aKUxUF3La08Fq8QLr4VWngDzKDgxvhrBFEiN0AsNUgfWJnDHGY9OCrVhgTtrTggZ4guENRop/I5q8zp5bbjTzaQ8a9kwM8rnjvr//d//FSZ5hGMRFsZddz5IihnH//3vf8ewNsK4MCZteG/yE9di+YsdS2tyEA5pAvfcc88VJqZ4BLJeAcpgvVBaH5LK5A3NZJaJ7WqrrdYm7Ii2IuKSVyDlQZwlrw1p+GPjBe78s4FF1tJEPHus3HP6g4ksnj7+6D8e8fLhXapk6YMpeaRIn92WvNwYYe1VVoQWa0+l6yOwK42zSmVkzyN48cYQisgf/UUoHOuUEEjZ+mbzZZ/zgZ3lwYQKzycGa8Yu10kbNjAeeL/guWMtUymjz3mv4UlK4hsvKev2Sq0hypbFne+77747egkJ6+O6548OkWVbeDaXSKGl2Tz0CWsDaQOcMcZofl1SykMdSUeaJPDxrHKt7LqklN5HCUhAAhKQQCsQaLsitxVaZBvaTYBF7qzLYOc1Ju1M3lgvxAQQTwzrSgiZQgQhWvB24GnBm4OxLoidwtgZjvMsTkf8JOO3VNKOaNw9ZzJ4+OGHh4ceeqjsHQMEDF4OvBdMzJgYsk0x4qGUqErXLPXIQnPqQH5EFms+Bg8e3CZkL5+XtTpsaIBniQkmYXhMtDnORBk+bPyQ/lZcccVYBB6y7GJ2vDqE+vHHHX+8csVC6fLXr+Y14uvII4+Mm1bQLpghJtMEGI54EGBfzLgrSH34cV+8BoyDbMhguTGCdxDvC+1CMKQ7s8WuU+oYfV1pnJXKW+r4UUcdFdhUAQ4IJPo98aimvqwxY4yyQx35WXNEWUmcU182zkCEMiYZE4htwv6SN4oQymy4G3UlJA5ByHuMrcB5b+Al5f2WDXMt1S76ijV15EljmXV09F+pu7u8RzE2g+C9xDbnbDaSFWScS95ZxgvjmF0MqT/vPeqLNyrvTS5VT49LQAISkIAEmo2AHqRm67FOrC93iplc45nBe0JoD5O4tPidxeBMkPbff//odWEix4+mpkkXIuDAAw+M3h42XiD8jokUa4YwJozcWSfEiUkY3gruulNGOaNebKyA14ctxpmEsgEEHhHuvrfH2MSAySGTWzwEhKGxuxmTTSbB2dC8VD6TWX4Lhvpzd56wODatSIvzU7pKj6xBYk0MAoIwpWOOOSaGHlbKV815PGwwIcSK+uEhIQwLLxaGEENcIu6ya8GyZRN6+Le//S1ukw4H2sy4wCqNESb2hIAR5gXLrDDMXqPc80rjrFze/Dk2LWBDDYQoQomxw053iFgsX998fl7TVwge3hOMFTZEYNwm7xM7BiJM2FURPowl3gcIRox1cNwIYMxlNy1BxBCOSb3gRV5CSOkfQtsqGddnMwo4835AtDGeUl8Vy881eX/j7eM9yHsczxpr1ZJRHuMn9R3PSU+YKPlhxs6AmgQkIAEJSKBVCfQafRf0f4sNWrWVtqtmAqwfQcBk1x2kQph4MyHMrqVJ59IjIUhM8tIkMh1Pj5xHYKWQrnS80iN32RFeTCbrYeXaWap8hA0bVuCFyq8PKZUnf5yJerrbnz9Xj9d4B2BMH+X7gGszmU4T+GLXS/nxEmTXvGTTlmOHR6PUmqdsGeWeVzPOyuXPn8OzxZqfYt6VauqLN473Qylu1BcvS7EF7HjjuG4K58zXjTU99FN7mVE+3tAUGpsvv9hrvL3l+jefhzpS/2I3D/Jp6/2atsF/0KCp6l205dVAYKZRfcOrG/cKvS/r3B+DrqFKHU7KDTHGNt7SYt93Hb5AixUAK7632/vd12I4yjYHVoyv9NMIZRN7Mn7G8x1Y67yws9ApkDqLrOVKQAISkEBdCCiQ6oKxw4UokDqMsOkLUCBV34UKpOpZkZKbYI0kkFyDVFv/mVoCEpCABCQgAQlIQAISaGECCqQW7lybJgEJSEACEpCABCQgAQnURkCBVBsvU0tAAhKQgAQkIAEJSEACLUxAgdTCnWvTJCABCUhAAhKQgAQkIIHaCCiQauNlaglIQAISkIAEJCABCUighQkokFq4c22aBCQgAQlIQAISkIAEJFAbAQVSbbxMLQEJSEACEpCABCQgAQm0MAEFUgt3rk2TgAQkIAEJSEACEpCABGojoECqjZepJSABCUhAAhKQgAQkIIEWJqBAauHOtWkSkIAEJCABCUhAAhKQQG0EFEi18TK1BCQgAQlIQAISkIAEJNDCBBRILdy5Nk0CEpCABCQgAQlIQAISqI2AAqk2XqaWgAQkIAEJSEACEpCABFqYgAKphTvXpklAAhKQgAQkIAEJSEACtRFQINXGy9QSkIAEJCABCUhAAhKQQAsTUCC1cOfaNAlIQAISkIAEJCABCUigNgIKpNp4mVoCEpCABCQgAQlIQAISaGECvVu4bTZNAhKQgARaiMCQIUPDgAEDWqhFndOUYcOGhREjRoT+/fvX+QLDQ7iszkVanAQkIIEGJKAHqQE7xSpJQAISkIAEJCABCUhAAt1DQIHUPdy9qgQkIAEJSEACEpCABCTQgAQUSA3YKVZJAhKQgAQkIAEJSEACEugeAgqk7uHuVSUgAQlIQAISkIAEJCCBBiTgJg0N2ClWSQISkIAExiQwcKAbNIxJpdiRfsUOtvvYTKP6htdvHDuM/GOf0Pv7Ie0ux4wSkIAEmoWAHqRm6SnrKQEJSEACEpCABCQgAQl0OgEFUqcj9gISkIAEJCABCUhAAhKQQLMQUCA1S09ZTwlIQAISkIAEJCABCUig0wkokDodsReQgAQkIAEJSEACEpCABJqFgAKpWXrKekpAAhKQgAQkIAEJSEACnU5AgdTpiL2ABCQgAQlIQAISkIAEJNAsBBRIzdJT1lMCEpCABCQgAQlIQAIS6HQCCqROR+wFJCABCUhAAhKQgAQkIIFmIaBAapaesp4SkIAEJCABCUhAAhKQQKcTUCB1OmIvIAEJSEACEpCABCQgAQk0CwEFUrP0lPWUgAQkIAEJSEACEpCABDqdgAKp0xF7AQlIQAISkIAEJCABCUigWQgokJqlp6ynBCQgAQlIQAISkIAEJNDpBBRInY7YC0hAAhKQgAQkIAEJSEACzUJAgdQsPWU9JSABCUhAAhKQgAQkIIFOJ6BA6nTEXkACEpCABCQgAQlIQAISaBYCCqRm6SnrKQEJSEACEpCABCQgAQl0OgEFUqcj9gISkIAEJCABCUhAAhKQQLMQUCA1S081YT2ffPLJcPPNN1dV8x9//DGce+654ZNPPonpb7vttvDoo49WlbcrE3399dfhhhtuCNdff3346KOPSl76888/j+0ZMWJEIc2dd94ZHn744cLrap7cdddd4cEHH6wmaVVpvvvuu6rStTdRZ5ff3npVm687xl2WWb37u1S733vvvXD55ZeHO+64I3z77belkhWOf/PNNwE2V111VSCvJgEJSEACEmhlAgqkVu7dbm7bU089VZNAOu+888Knn34aa3377bc3nEC65557wvrrrx8eeeSRMHjw4PCnP/0pPPHEE2NQHjVqVDj66KMD7emoQOKaXK8edsIJJ4Srr766HkUVLQPxt/feexc91ywHu3rc5fuknv1divlFF10UNt988/DSSy+FK6+8Muy4447hq6++KpU8vP3222GttdaKY+eFF14IW2+9dd3GZMmLekICEpCABCTQjQR6d+O1vbQEmobATz/9FE4//fSw7bbbho022ijWGxF01llnhQUXXLBNOxAhTD7rYUcddVQ9iollUKcllliibuXlC3rrrbfCDz/8kD/s6zIE8n1Sz/4udlm8Pwj3k08+Ocw333zh559/DjvssEO44oor4mOxPIzzNddcM+y+++6hV69e4YILLggnnnhi9EDxWpOABCQgAQm0GgEFUqv1aAfb8/LLLwfCfD744IOw0EILhWWXXTZMPPHEsdQvv/wyXHbZZeGNN96Ix1ZcccWw8MILF6744Ycfhptuuim8/vrrcfKV9Z6kRITpPPTQQ2H48OHhd7/7XVhvvfVC796VhyFlp/Cevn37hnnmmSdssMEGoU+fPuHFF18MeKvmn3/+GPr2/fffh1VWWSXWjfpy15tzq666ahgwYECsCiF9lPfKK68EQpymm266KHymnHLKVNU2j7Rll112aSOGJppoonjdbELutjOB5K78cccdlz0Vn+Nd4q79Y489FqaYYoqw4YYbxmuPkfDXA9dee20Yf/zxw0orrRTbiccK5tddd1344osvYn3gMPbYY8cct956a7jvvvsCgm6WWWYJm2yySWwz4VQff/xxuP/++8NYY40Vr8skl4nvxRdfHKaeeuqw1VZbhX/+859hs802i68pEI8eE+qddtop9O/fP16DPnz88cfjZHnxxRcP/D3//PPhP//5T0x/7LHHtkkfM/3675prrgnTTDNNIATxgQceCOOMM05YY4012nCtNM7or0svvTT23YQTThj7OolUvG208f/+7/8C5zAm/wi3LbfcMnD9qaaaKoaJEQI600wzxfwzzDBDTJv/V2ncVeqPcuMs3yd4dbL9TV3gSjgnfU0dEeeMG4xxX+n6MWHmH+Nu0KBB8f3JYd57K6+8cnxfI5TyxnX5TDjggANif3N+9dVXD2effXa8CTD33HPns/haAhKQgAQk0PQEKs9Mm76JNqBaAky49txzz7DAAguEJZdcMq45IOTntNNOC6xBILSGSfLaa68dRcd+++0X7yqvs846YejQoWGPPfYIiAYmXEyi33zzzTDbbLMVLs9da9bhMCnv169fnOQ+88wzMRytkKjIEyapTG6XWmqpKBQo9/zzzw+sB2Li/v7778e72ZTN5I278gcddFCcBCKIfv/738drEUaEcMEIBWOiTV2YxN54441xfRCCCgGRt3HHHTcy4TiTRiaaiJRtttmmkBRRcthhh4XtttuuIDAKJ399csstt4Tpp58+Xvfuu++OHinWXiEaihnXmWSSSWK7aSeijnUjyy23XEDMnXHGGQFBiLiB+b/+9a+wxRZbhIEDB8b6kZ/yEYC0YbLJJosTbTwHiNmnn346zDnnnHEdCiKQYwhJBBNGv3KMdtL355xzTgy1QtRQ1kknnRQ+++yzKKZ5jfChvFKil/rAmEn+MsssE5599tmw1157RVE544wzVhxntJW6IBrpaybvf/7zn+Mf4+43v/lN9G4MGzYsHHrooXH91r///e/IhfZwfcY5ImHdddcN9MFuu+0W20X9s1bNuCvXH5RVbpzl+4T02f5m7RnCZLHFFotjn35AANOf1L/SeKC8vLFuLvVtOkdZ9NvIkSPHGPuIaow0yRiPCFvEcyWBxHuCPuuoFbvZ0tEyzV87gdH3d+JnQu05GzcHYxRjnPK5qJUnwPclnBK38ql79lluBGPMNYyuqDwWGFewKjYHq5y7+hTMT5iDVjIFUiVCPej8qaeeGsUNE1aMidlf/vKX8O6778a1REw6mRDitcHzw4SSsDMm1NylH2+88eJrwm4QTdtvv32BHqE93L0/5JBDwgorrBCPL7300mHjjTeOk/RZZ521kDb/hLx4shBk6Y2DOGKim4yJPOs5Zp999vjhjReBDyQm8BieGwQNAmnIkCFRyDF55a48xmR13333jaIrecziiSL/Dj/88PDcc8/FSWM2ZI1wu8knnzyKH7wTxYyJ5ZlnnhkFBEITjggGrl2NUXeE5swzzxyTM7HFm4NAwttA+/FK0Qe//e1vozeFL7RFF100TqznmGOOGGZHX2L0QfIcVFqsz7UQpogwwrOwSSedNHqsWJs111xzhf/+97+x/fFkiX+ME8qgLxEpiC08IQgk1seUG2eELyJQ8WBMMMEEcZxNO+20UcTjZeNDjzG78847R68U4xNhP++88xZqwxc7oj95T+DFddO4TwmrGXfl+qPSOMv3SbpuemTs8l7hPYMxXvAWMs4Qf1i568cEuX8InuRFTacQvoijVN90nEcEFR5b/rJGnnLrllJahA1feFrrEGjV/uRzkj+tOgJp8l9d6p6dSnFUff/X44ZapasxD1MgVaLk+QIBBAShcwiWZIQoEXKFvfbaa3HCiThKhoBics9EkryEsWXXJBAKxsQXe/XVV6NIIaQND1AyJsucKyeQFllkkVg2YXTvvPNO/KPcrJAhxIyQMoyJLx6KbPgfbWFijeFdQeQQCohHh/rjycD40Oc5nolkeNSy9UOgINCYqBIWhfCjTdzdJ7yunOHNynpXCA2DCWFleIaSIbQQhXnjjZ3EEedIl9Y74VXaZ599YhgWzJiAVwphRNRUa/Ci/xFeyfAC8VfM8HhkRRcTfAwRl4Qujwjt9KFYaZzRL/Q7YYHJ8GAxWcejQb/j1cCLdswxx0RvKCGDWYN5tg/oE8Zg3qoZd+X6o9I4y18v+xqPLWIGb2TW6FO8TMnKXb8Yf/ovf5c8vS72hVEsPddG+BRLn+qVHqlf9n2ajtf6iKiFidb9BOrRn93fiv/VgMkrN2XwSudvBPwvlc8SAVjx+cl7WytPgJsJzCm4KZX9zimfq+ee5TOe75W0ZKCzSKT5R6Xy9SBVItRDzjNB5Q/BUsyY6BIaljXC6TDuPjOw09qIlCY7yDnPayZcWRHFBD55cVK+/CPiC28PHzBMzvEGUFeETTK+3LLX4zjHkmWvyQfWgQceGD0ulMUfd+pZq4QhOAi5S0Y7swKJ4wguJq8ILHZvwzvFG5v1Nxh347GDDz44ekiSpwlBkzUmG9y1JD3bhyfD01NMIBEmlzXe6IhbjDVdrBdiJzbqxHoWQhzxRHDHv5gxic9bKo/jafLMc0QcE4gsS46XMtaypV0JSUMIHJYfY9kPq2rGGQyydYApIihbTmpvtv7x4qP/sQYpa3x5JYGWPV7NuCvXH5XGWfZa+edJDOTD/hgvvN+Slbt+Mf54/LjJkDW8r4zxYpND0iOGmBRlBRF58hyzZabn9EmxctN5H5uLwGjHdMv1Z/qM4PvFsVp5PPK5JqvKnEgBK/6Y9ygoKzNDUMKKv0YwBVIj9EID1IHJD5N+REda8M5EjHAlRAxrZPK/S8RrRAmhUXgFmJRnLRtmRn4mWnidUrgTr1k3Q3hbOUtraJjoJxFEiFt2olguf/4c4XfUjbDAJOrY2ABDHOBFy3rSOM6kEpFGaFhaj8GdR9pAntVWW61NyBHrVwgBROhk77gy6c4a4XGEiMGQjQc6YvQH/Yhw4w9vDI94HPAuVbL0oZQVC9nfemLtCgIGb00Sx1yDdUmsvcqKFq6VwhsrXTd7vtI4ow6wZROGJIgI6yO8kPGLsVEGoXWsp2PswDXrRcqOS9LTB9m1chzDOjruKo2zX65S/D/jkkkIfZrCGUnJ6+QpLZ7zf0eL8Wec8Z5jUkj5GOM0vy4plUJ/kI40bNqC4cXjvZfeBymtjxKQgAQkIIFWITBWqzTEdnScABsWEDLHhJqQFkLHECIsuud3UJiIMtnkbjKbK+DxQPBwZ2T55ZePP/LKGiXumLC5A5PWZHg3EAJMppnAkoYJKAvos3emU/rsI4vCuaNOHsQIE8/Bgwe3O16c8hA2aQ0FoUyEy2Fco5jh5WLSysQbbw8/aMs6FjwwhGLBjo0k0h87/GFMzLML2eEJXyao8CO0i3U49TDE15FHHhkX78MJjw/tTJNf6orQYy1RMePuKR4LftyXPkaIZEMG2TkQDuzOxzn4sRYIYYInA08MYYyI7HRXtth1yh2rNM44n3bWY0zQFsIl2RkRgce4RawxLuHK1tTUESGXDE60kb7mkdBBdj3MW0fHXTXjrFSfcCOAMUXYJTceqCvjBe9mqZDGfP2LveZ9il1yySVR5LA1O15QQkWTcS6t76N+jGU8k4hjbgrAE29g3ruV8vsoAQlIQAISaHYCepCavQfrWH/WbbC2hg0DuGvMXXVC0Zj8sr5o//33D2zkwASJCRzbO3MMQwSQFsGDcMBrwiSKDR4wymNNCL/zwnUok7U0hKAxwWbyVcpYRM9EjgkjYox6sXsdYqU9C4ZpCx4fJs/Ug7pR3vHHHx8ny9xlL2Z4JP7617/GxfLcQSfkELGQvCnF8uSPMbllMwnWzeBxoczkscunrfU1GyUw2WfTBcL2KJ8d2vBiYYT5sX6KNVbZNTzZ6+Al+9vf/hYFAyGKMEJ0YXDi+RFHHBE9bITKIQ75bSiM8Ee8Optuumnsm6wwjAmq+FdpnCHW8WqyNo6JPKIIfuygiCF0EWlsYY4ROnnvvfdGEYU4x7jGhRdeGPsbAcC6LdaZ5a2j466acZbtE0Iis8YmJwgS3mO833if0M4kcrJpq32OCKb/EJHwow8RkqxtSsb7ijGU+o/npGczDfLTz7vuumtK7qMEJCABCUig5Qj0Gn2n+ZcFDC3XNBvUXgJMrhEs2dCwVBbDhTv43B1nwlzMmPyzdiEfcpXSUjaeDSantRieGybElTxO1ZaJt4EyqWstRvtpezE+1ZZDGeQvxbDacoqlQ7zRB6zNyfcBbYY9wrCUpfx4CFIYWz5tub7As5PWAOXzVfu62nGGaEihgdWUzU6IcEEIVhqnqbxybU1pyj1WGmeV+oT3Izcu8uvXyl2zmnN4Qcv1cb4M1h0h1LJr+/JpOuv1/2fvLMDkKtK2XYGEkEASXIIHd1hgYbHF3WFxWeRHg7vsh7uzBP8guMOHO4u7uwVf3BJIIECSn7ugmpOe1pmemZ7uu65r0t3n1Cm5q073+5z3rQoeNDyi/fuPvX6sveqz3LEJDBjTM7x9y7hh9IY9Qvcff19fOXaOrvuJh2zMbX6PavXb0nVplG85rPjOzV9LWv7K5ssBK+YX9pJrkMqPP9/x2A7V/KaXL7X1OQpbuK0vzysbgAA3cjHjH4M7rdsp1tVyoTdsz9yaVK2gKlcHN2G14ogya2Go1qKMYv1D1BQbI/pc7sun1PWpzlJj0VZxRB21mGeprcVey83TdF2pvqY8pV7LzbNyY8L92B7zpdgcKdaX/O3Bi+XzuAQkIAEJSKCrE3ANUlcfQdsvAQlUTABx7lPiinGZUQISkIAEJNCUBPQgNeWw22kJNCeB9J+uNmfv7bUEJCABCUhAApUQ0INUCSXzSEACEpCABCQgAQlIQAJNQUCB1BTDbCclIAEJSEACEpCABCQggUoIKJAqoWQeCUhAAhKQgAQkIAEJSKApCCiQmmKY7aQEJCABCUhAAhKQgAQkUAkBBVIllMwjAQlIQAISkIAEJCABCTQFAQVSUwyznZSABCQgAQlIQAISkIAEKiGgQKqEknkkIAEJSEACEpCABCQggaYgoEBqimG2kxKQgAQkIAEJSEACEpBAJQQUSJVQMo8EJCABCUhAAhKQgAQk0BQEFEhNMcx2UgISkIAEJCABCUhAAhKohIACqRJK5pGABCQgAQlIQAISkIAEmoKAAqkphtlOSkACEpCABCQgAQlIQAKVEFAgVULJPBKQgAQkIAEJSEACEpBAUxBQIDXFMNtJCUhAAhKQgAQkIAEJSKASAgqkSiiZRwISkIAEJCABCUhAAhJoCgLdm6KXdlICEpCABLo8gaFDh4W+fft2+X60dwdGjBgRRo0aFfr06VOjqkaGsGYI4/xYo+IsRgISkECdE9CDVOcDZPMkIAEJSEACEpCABCQggY4joEDqONbWJAEJSEACEpCABCQgAQnUOQEFUp0PkM2TgAQkIAEJSEACEpCABDqOgAKp41hbkwQkIAEJSEACEpCABCRQ5wTcpKHOB8jmSUACEpDA7wT69XODhsrmQu/KsrUh14AxPcOby3UL3e//qQ2leKkEJCCB+iSgB6k+x8VWSUACEpCABCQgAQlIQAKdQECB1AnQrVICEpCABCQgAQlIQAISqE8CCqT6HBdbJQEJSEACEpCABCQgAQl0AgEFUidAt0oJSEACEpCABCQgAQlIoD4JKJDqc1xslQQkIAEJSEACEpCABCTQCQQUSJ0A3SolIAEJSEACEpCABCQggfokoECqz3GxVRKQgAQkIAEJSEACEpBAJxBQIHUCdKuUgAQkIAEJSEACEpCABOqTgAKpPsfFVklAAhKQgAQkIAEJSEACnUBAgdQJ0K1SAhKQgAQkIAEJSEACEqhPAgqk+hwXWyUBCUhAAhKQgAQkIAEJdAIBBVInQLdKCUhAAhKQgAQkIAEJSKA+CSiQ6nNcbJUEJCABCUhAAhKQgAQk0AkEFEidAN0qJSABCUhAAhKQgAQkIIH6JKBAqs9xsVUSkIAEJCABCUhAAhKQQCcQUCB1AnSrlIAEJCABCUhAAhKQgATqk4ACqT7HxVZJQAISkIAEJCABCUhAAp1AQIHUCdCtUgISkIAEJCABCUhAAhKoTwIKpDaMy/XXXx9ee+21ikp48803w1VXXRXzZt9XdHEHZfr111/D448/Hi6//PLw0ksvlaz1mWeeCffee28uzzvvvBOuvPLK3OdK3gwZMiTWVUneSvL88ssvYeTIkZVkbXWe4cOHl7yW+uF35JFHhocffrhkXk7eeeed4cknn4z5su/LXlgnGUaNGhUuvPDC8Mknn3Rqizpi7Du1gxVWXimHDz/8MH4f3X333eGHH34oW/r3338f5+q1114buNYkAQlIQAISaGQCCqQ2jC4C6dVXX62oBETR1VdfHfNm31d0cQdk+u6778J6660Xzj///PDee++FfffdN5x55pkFa/7888/DIYccEu65557c+bfffjtcccUVuc+VvHn33XdzorGS/KXyYMBttdVWgba1VzrllFPCddddV7L4wYMHh8suuyz06dMn/pXM/NvJu+66KyeQsu/LXVcv50ePHh0uueSS8Omnn3Zakzpi7Dutc1VUXCmHSy+9NGyxxRbx4c4111wTdtppp/Dtt98WrYnvg7XXXjvO/VdeeSVss8024Yknniia3xMSkIAEJCCBrk6ge1fvgO2vDQGMpqmnnjqce+65sUAMIETSP/7xjzDllFPmKsEgxjvSrVu33LHWvllxxRUDf7VIGIcfffRRLYoqWgbewqWWWqroeU7gFVt66aXDHnvsUTJfo5zs0aNHeOCBBzq1Ox0x9p3awQorr4QD3p+LLroonH766WGBBRYIeI133HHH+PCG10Lp2GOPDWuttVbYfffd431/8cUXh1NPPTU+3KjF90ChOj0mAQlIQAIS6EwCTSWQ8JLceuut4eWXXw4zzTRTWHbZZcPss88e+RMqdMstt4Snnnoq8H7BBRcMG2ywQeje/U9EnLvvvvvCiBEjwhprrNFi3PCi3HDDDeGzzz4LM844Y9hss83CZJNN1iJf/oGff/45ELryxhtvBEK4pp9++rDxxhuHqaaaKmbFUzXddNPFp/SPPfZYmHzyycOmm24ajRXC2nj6u9xyy8X+pLIfffTR8NBDD8W2kH+FFVYIiy22WDrd4vXvf/97WG211XLHJ5544viesrMCifowiqjvq6++yuVPb55//vlw4403hjFjxrRoU8qTXvG+EaaH4YWhdvLJJ8cn2zfffHN46623wrTTThu23HLLHEMMQOp//fXXo3dmkUUWiePw008/5YTdBRdcENZcc83Qs2fPGCbYv3//6KVZeeWVY3sZD9qeEh4zxnrhhReOh4rNEcIjGVfC5sYZZ5zYzlRGej3vvPMCcwDv0fHHHx922WWXMGjQoLD55puHaaaZJmb74osvooG68847V+RhSmWnV0LZbr/99jhX5pxzztjup59+Omy33XYxC/MHTx5zaaKJJgqrrrpqrm+VMKYQQv2YZ4QL/uUvfwnrr79+7j5gnjIXqfObb76J44MXgvk6wwwzxDYwPozrxx9/HBgjeE8yySTx3B133BHnJaFgs8wyS5zHffv2jfce99VGG20U8/EP3kCMcTgizCsde+qshAP3EPc8nsx55503jhPhjvR/0kknDauvvnpsY+LG98FNN90U27XQQgvFude7d+/Y3nwuW2+9dbyP+a7hmq+//jp+J8Ap3U/V3tfcL3CnrdwjiFPuW0T7jz/+2OIegEN+4juMewJxROL7bZVVVolsCwkk2s14HnjggbmHInz3cZ/xwGDuuefOr8LPEpCABCQggS5P4E/rv8t3pXQHMCD22WefaPStu+660XgjtIRwKAwGnpI+8sgj8Ulpr1694joSvCg8KUUQ8P6ggw6KHo855pgj5h82bFiu0meffTbst99+0VhBeN12220x5AsDr5xI2nvvvaNBx1NaxBJGG2uBMAgxxjFqWNeCQYnRw/kXX3wxjDvuuFH0YJAfeuihsR8IPkTaOeecEwUaxj/9whuEAY9RXSjNN9988TBG8QsvvBANU47NNttsueyEBtImjCO45ScEDO3AoEY84WnCwMKwLJT++9//RvGCQEKUIl7p1zzzzBOWXHLJgAFJWwjhIlEezOE0dOjQcNZZZwUEDUY1bO6///4wYMCAaIwjEAhpnGCCCWJ59AumCOOsQPrPf/4ThQQCqdQcQbSOP/74UZwifgulmWeeOUw44YTRuIZz6hPCMwkk2k8/t91226oFEn2GFWID4YNYxzDHmEcg0X7Kpc8YsRi2zEn+MIJTe0oxxrNA6CSMMf4RW4wB9wcJAYFYRLwz7xCi9Gf55ZePAgkjfs899wwICDxpiA3GhbHi/b///e8oqvr16xeFNHObNUzcc6eddlpsN+0nIaYQnHymD5WOfaUcuGeZC3PNNVe8v+gndSCmESLc74i/xI2HDn/729/CEkssEfPD8aijjorfD/lc6A/5ERbkR8jAiT7RX75zqr2v8ZBy/yG4mPMI1MMPPzzsv//+sfz8eyBCzPuHUMg0F9Mp2sL9igjl+yabeChAIk9KzLfxxhsvIPbLCSSEMMK3rYkxMNUnAb6XunJijpL43kjvu3J/2rvt2Cg8NOLVVJpAYsQ6T+w1U2kCzCtY5f8Olb6q+rM8GEx2Rqmrm0YgYZzgDcG448kricFgs4FZZ501GuoYgRjmJLwt22+/ffQYYOidccYZ0WvAk2ESIogn0CnhKVh00UXDYYcdFg9hYBKrj3G/1157pWwtXvlxwVuDSEqGN8Y4ggbjPz15xzg/5phj4hNfnkAffPDBYeDAgbkn7hh3eDcQSPSTc7SBhPcIrwrGazGBlBrGk2m8KggKBEmaqOkzT/OTZytdk14xYjAqk6cK45lwHgRppV8OGKzJGwIHjG2MN0Qm6x922GGHnKeL8xh1GGsY6AhAruc4Agl+J510Us5LyIL0UqnUHIElhi3iuFiYHW1AGCPCyF/J4vdS7ck/h3GMtwzxi2hfZ5114pyEAYn1UQhSBCxCDe54exAnGP0pFWOMIYso/de//pULfVxmmWXCJptsEvAMIrZJjCv3A2Oab1BwHyDG0pxHHPzP//xP+OCDD6LnlvmJcU/7559//jhn+RGBKR5EwvXw3JBYk0WIJ6masSdctFIOyWuC+MDrRf+nmGKKeM+w7oaQSTyZJO5vBA+JfjBPue8KcSEPXkJCSOFJYrzoD/cXDxJI1dzX5GeM+I5BqJG4PxG11JN/D8QMef8gePDYZRNClzmUvouy5xBUjDd/2cQ1fM+US3wn1EIglavH851HoFHGl++hZNB2Hs2uUTO2k6lyAthPpsoIdMTDMGxGBVJmPHgSjUckiSNOJSMuhavw1DslDGHECYY2XhvChbLneaKK8UniS5Vd3HiyivGaEsYLXpdSiSfpRxxxRHxSTugUawR4Mk3K3lQ8HU7hfulpLgZbSoRT8USZhBcBUfHggw9Gw5S2UVb68kcIZI13DDcMNRIGHIY1YouNGBA8GLwYvoRQ4bkoljCikrFIHrjhxSFU6ssvv4wejXRtlmU6xmtWwGGokhAFJNqBEY3hjAjDqEaMFEuMNeK30lRqjuSXwRjhoUmJ/lRTV7qu2GuhMWIu0W/ERUqLL7549BDymfYwZ7PePbhjyPK0nzlCKsaY8gmNZM4jDFLCG8K5NLaIg0KCl2uZawiqlKgTMUXCgMeLS5gZ/aDt2fA9hDwiFoGEIGLecIxUzdhXyoF7PCXuKeZSmnPclyTuqSSQkvDnOJ5V+laMC95UxAgPWbKJPuM5Sqma+5prmNNpHPj817/+NXqzCm1OUmgOcX2+cZM+p3BByk2pUH7O8SNWKH+6Lr3yQ8T3YlsTQhzvnqn+CNRifDuzV/y+EJKLwZR+BzuzPfVeN6ywRfIfmtR7uzujfbBifvFQiu9SU2kCfMfzu5Js3dK5W382a0OVKqVpPEgYOsn4yQeCMcMTdwzBlACIZ4cnqzwhw/jLV7bJSOQm4DzXZ8EjEHjSWiohXBAhrFVgbQF/PA3GQMymZLBljxVTwIQFIdQIN6M8vF14j1LiSTkGc0oYn9kfBiZnChMkBA2DjHVFlEU4DwkDGsHF5/RUnTZmvzTTOibysV6B0MCUOJdllY5nxyB5r2BL2m233aJIZW0V3hKexLPOK3kBUhnplTFNZaRjqaz0OesBKTVHUv70Wqg/xQRSts5kjKZyir0WGiOe8BMOlk30MSXmMeOY5cqcZw1UlkMxxlzPnOaLPFsGImbGTFhhvgci1U+ICn/Z8tM5XlnPhEcRgUu4I6GgCA1C67hPCEXEQ4ioIw/ep1RXNWNfKYdUdmpj1uDP9j+dz3pOOQ97+ptStjzaQGL9XzYhYJPHj+PV3NfkR5Rl79VUJ+1AjGRToTmEJ/b999/PZovCg/sxe++mDORPXqAsH37I2NSlXGLe5ber3DWFzmfvoULnPdZ5BGoxvp3X+pDzgvO719X70hEcMfhlVRnp9HCX31TnVnlm/F7Aql7EZNMIJJ4Qsxg7mwi3Q6Bg/PGUHQ9CMnLxwCAC2A6XJ2QYNjz5TU9vyZ+esmNcYDxgTGDgpUT+ckoYTw1rIfC0pMXbCABSa4wC+nP22WfHhe1p7Q8GDuFyqTwM0vzErmsYpCmkifN4mTDAMHhT2Fu6DjGBMMRgT5MZ0YVhmEQh6ziY8BhSeBWyngXKKRfylurilS8a1tzwBJ52YmQOHjw4hjAS9ljIoM1ez3u+oLIGLWIFYzylUnOELcSzqVB/sud5n7hk66x0O+xCY4SHg80rsinrjWBtCZs4/L//9/9ygoh1XohvDOusYZ4tI73HU8JcgS9imMRn1g4RtlgucQ9QD17QtOkFdRJih8hCKJMHrwp/9IVX+oB3Cc8WXsoHfguzw/t5wAEHxCqrHfu2cijWT+7TtOYGjw1e5ewavex13Mvc+6xNShsicJ7PeI1am5ivhAMm7zUhwggmxiffi1RsDjGezP303cTDk/x1Sal9zAnykYcHPiQ8dIxr8mSnvL5KQAISkIAEGoXA2CtyG6VXBfrBonX+81OECAYrYogNFAgXInQGg4a1GxgfGPp4YDD2WCdBIrSMxeusxUAEsB4lmwhL46k3GyJgVLI2Ac9KuQWsiC/yp3h+wnLwjJAQO9UmPAA8lUbAYMRgXLJGH43Q/QAAQABJREFUAU9JqfIwitkIAtFHPhaCYxTRb0QSAiH7BzeMNI5lPVmIFowvPGCsx4F7oSfT1faLMvBiMS7wp42sMeIJPefSk3RCnrLhg9l6aC+7s2HYIu4IG4R9Eo6l5gjlwJWn74jnShLton1wwAuJeGHOtTZtuOGGUUzw/1MRyva///u/Ufyk8lgzw9zFSwMj2kn4Jn1OYi3lLfSKhwdGlMv/fQNj5jmCO+s9KHRtOsbaK9ZKIXqYc6zp4b5D/NBmNjXgHoM5cxT+WeOc8DpCBBG8hI+Rqh37tnJIfcl/RVjgOaTd3KO0Oyt+svm5D2HBQwC8ZbAklJfr8c62JXGP8X3B/UkYHfcoDyIquQdSyCL3Ot8PPDQitJcHQSlxjrJJzPmVVlopzinuK75P+J7E65zvHUvX+yoBCUhAAhLo6gSaxoPEk17W1PBUlf/rB68PHpa0roBtmdkEgZAtnpgSnoawwCtE4kk3YofNEzAseJqafXqMFwMjmDowjvA44WUoZwzhkcIoZHcyngRTN4u72VwAEVdqjU2hycf17M6HYYvIwUhFvPGEnvKKJYw5PA3//Oc/o6eFctggoVz7s+VhXGM8YjxhEHItmzrUImEw0x4EEv3BsMYzhcFNQqSxJgtBwCYAhbix9gVjnXHBm0RIF56O5H0qN0dY88ScYP0R4WGVJDbfOProo6MRSxsZ59TmSq7P5kGUHnfccXEzCoxtvDyIumTMIkLw1rDmByMXUUT/Kv0/mRhzyuc+YHt15iM78zGneVhQSeI6hCv3CeXBlBBSyuJ+Yw4SEok3Ce6EzmXXAmGMM8Z4MrmeVO3Ys0FJWzgU6yd8d9111yju+H444YQTxno4kH8d3mQEBZ4wvhNgyFgkkZKfv5LPzCHuaTxycOEegyEp/x6AQ35CbOJNZvc75gjeYf6DaDyzKcGfMUreMt6TP22fz0MjOJgkIAEJSEACjUqg229Pcn9f4NGoPczrF90lTIWnn8kwzmYhtp7jKUwse473GP54oIoZjHhPEAnF1jvll5c+Y/QgwJIgS8fb8oo3AaGWDM1KyuIpMQzwqGHUtSZxPU+0s+tjWlNOsWsQoowDIjc/cQ4jsFTbGR88IhjthVKpOcI4Ic6KXVuoPAR1mnNwaW3CA4PoSf/fEOUg+AlpO+WUU8YqlvqYo5V4jsa68I8PzAP6WWiNTKH8+ccQQJTB/MtPiQf3SP49iGcEgx0vSbafqYxqx76tHKiXuYaoQRwjSulXobmX2pj/CgtEY7XfCfnlpG3S8UjyXcEcZK7np0ruAa4hJI/vwUrnJPc19xVCrKMTY8B9279/+XVPHd22Zq1vwJie4c3luoXu9/++iU5X5UA0AXOb77pKPeVdta+1aDes+F0ptta0FnU0ShmwYn4RKeQapPKjync8tndr7ZbyNVSXo2k8SAkLBlkpQyWFqaT8+a8YJIWMkpQPMVKq/JQv/5UJUUtxRPmtaQeipq3CphzD/L5X+5kfsWI/ZMWOZ+soZLRnz5eaI4xTtTcvBmhaX5atp9r3eK4Ib8LbyToWwj3Z+CLtxpgtr63hT22dA/wYFONciAc/ImwFTkgeYWuFxBH9q3bs28ohy5T3jH014ohrYNGae5Fri6VSwrWSe4Byq52T7X1fF+urxyUgAQlIQAIdTaDpBFJHA7Y+CdSKQFpbc+KJJ0YxQUgjoZ/p/w2qVT2dUQ4eEULS2BQg3xvWGe3J1olgxhtXjSc2e32t3vNgppjnulZ1WI4EJCABCUhAAr+F9zdbiJ2DLoFGIEDYVqO57AmjKuWdbYRxsw+tI2CIXeu4tedVhti1J936LdsQu8rHxhC7ylmRs95C7Fq/IKK6fptbAhKoIYFGE0egURzVcIJYlAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSagQGo1Oi+UgAQkIAEJSEACEpCABBqNgAKp0UbU/khAAhKQgAQkIAEJSEACrSbQvdVXeqEEJCABCUigAwkMHTos9O3btwNr7JpVjRgxIowaNSr06dOnHTswMoT727F4i5aABCTQiQT0IHUifKuWgAQkIAEJSEACEpCABOqLgAKpvsbD1khAAhKQgAQkIAEJSEACnUhAgdSJ8K1aAhKQgAQkIAEJSEACEqgvAgqk+hoPWyMBCUhAAhKQgAQkIAEJdCIBN2noRPhWLQEJSEAClRPo169vGDCmZ4sLhoQeLY6VOjB60OhSpzvl3OiBtWvTeH/04NdO6UnXqpTZNLm8Kh603rKqipW8KsYV0vY7xb63uo/5qfLCapBTD1INIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBCQgAQlIQAISkIAEJNAYBBRIjTGO9kICEpCABCQgAQlIQAISqAEBBVINIFqEBFpL4Prrrw+vvfZaRZe/+eab4aqrrop5f/7553DhhReGzz//vKJrOzLTkCFDwuWXXx4eeOCB8OOPPxat+plnngn33ntv7vw777wTrrzyytznSt6MGjUqcvjkk08qyV42zy+//BJGjhxZNl9bMgwfPrzk5dQPvyOPPDI8/PDDJfNy8s477wxPPvlkzJedI+UuhN3FF18chg0bVi5r+P7772M91157bfjwww/L5jeDBCQgAQlIoCsTUCB15dGz7V2eAALp1VdfragfGL9XX311zItAuuiii8IXX3xR0bUdlemwww4Le+yxRzSizz333DBw4MAwdOjQFtUj7A455JBwzz335M69/fbb4Yorrsh9ruTN6NGjwyWXXBI+/fTTSrKXzIMI2GqrrdpVdJ5yyinhuuuuK9mOwYMHh8suuyz06dMn/pXM/NvJu+66ayyBlOZIuevOOuuscMEFF4QffvihZNb33nsvrL322rHdr7zySthmm23CE088UfIaT0pAAhKQgAS6MoHuXbnxtl0CEqgfAi+//HL0GuEFmnrqqQMibt111w133HFH2HjjjXMNRdTgHenWrVvuWGvf9OjRI9bZ2uuz1yGQPvroo+yhmr/HW7jUUkuVLBcP3NJLLx2FZsmMrTyJOD3ppJPCc889V1EJxx57bFhrrbXC7rvvHscMr9Opp54avZm1GMOKGmEmCUhAAhKQQAcSUCB1IGyr6voEvvvuu3DrrbcGxMBMM80Ull122TD77LPHjhGydMstt4Snnnoq8H7BBRcMG2ywQeje/c/bjHP33XdfGDFiRFhjjTVaAMGLcsMNN4TPPvsszDjjjGGzzTYLk002WYt8+QcQI4Q/vfHGG4EQrumnnz6KkqmmmipmxVM13XTTRU/LY489FiaffPKw6aabRoMXQfPtt9+G5ZZbLvYnlf3oo4+Ghx56KLaF/CussEJYbLHF0ukWr7Tz+OOPj+KIk/S7b9++4ZtvvhkrL/VhWFPfV199NdY5Pjz//PPhxhtvDGPGjGnRpvzMv/76azj55JNjX6eZZpr4fosttgg333xzeOutt8K0004bttxyyxxDRBD1v/7669E7s8gii8Rx+OmnnwIeLxJelTXXXDP07NkzvPTSS6F///7RS7PyyiuHSSedNMBl5513zjUFRggrxopUbI4QHsm4EjY3zjjjBNqZn84777zAHMB7BMtddtklDBo0KGy++eaB/pHwGuI9pA3kqzYdd9xxYdxxx43l77nnniUv//rrryOrAw88MCdombcwQuzNPffcJa/3pAQkIAEJSKArEjDEriuOmm3uFAKsp9lnn32isbzoootGD8lOO+0U0voXnrSfc8450SifY4454joS8mPokwhLOuCAA+J7zpMfgzmlZ599Nuy4445x3Q7CCwOUkK9CIiJdk1733nvvKLwWWmihKGIoiyf+eGtICDMMY4z7hRdeOBr++++/f8Dw7d27dxRUhx56aCCMj4RIO/zww6M4WHXVVQMCYt99943GcsxQ4B+8RnAhsZ7ozDPPjOF1CIuUKB+BcvDBB+cM7nSOVwQM7Zh55pnDRBNNFD1NpULSYItg/fLLL6Mo5T3MEWVLLrlkgMNee+2VqwLPFZ6TFVdcMcw555yBMDPC2RAMs8wyS8w3YMCAMMkkk0TRQ7gaogUhwtqgDz74YKywQC6gT4888ki8ttQcQbSOP/74UZwifgsl+j3hhBNGIUb7ENr0KSsyWTPEsdaulWIO4kFC9JZLaX4iElNCJI433ngVhXeyposQy7b+lVu3ldrmqwQkIAEJNCaBtv6OpOvLhZUnen8+2k5HfJWABAoSwCjF04IngNAuEh4MNhuYddZZo3BC9GCYk/C2bL/99tFjQMjUGWecEb0GW2+9dTyPCMKLkxKeAgQG63hIhDWx3oM1NlkjP57M/MNNP/HEEwdEUjK8McYRNHgzMPZJGOfHHHNM9OxMOeWUUaSwRmijjTaK51944YXYVjxi9JNztIGE9wivCuulMNxLJcQKno/kJcNzRcKgR6BwLnm28stBEBx00EE5TxVeHLwlhOohYipJeKa22267mBUOeEkQmXi4WEOzww47hNVWWy13HhGJwb/88stHMcT1XIc3Dn6IieQlxDNVKpWaI7BkYw3EcbEwO9pw2223Re8k+Sv9Ii/VpvxzjH2libVdjAF/2YRgZI6US4wn88AkAQlIQAISaAuBWv2W8HvPg8hySYFUjpDnJfAHAUKf5ptvvpw44nASLhjOiCY8OClhCCNOMLQJ5fr444/HOs9T+SQeCJHD68LTebxQKRGKlbw66Vj+a79+/cIRRxwRQ7Nuv/32uEHCiy++GLNlvQx4SFK4X/IIJI8PmfHYJE/FtttuG0XFgw8+GL0mtI2yaCcJIZA13tdZZ50owDiHZ4KNA7gGQcRmDCeccEIMFZthhhkCHqliCUOc0MSU4IYXh3UzCC9C41KCdRKE6RivWQE3xRRTxFN4wEirrLJKDMOjfQhYhAqhksUSY4r4rTSVmiP5ZTBG+f2ppq788vI/lxqj/LzFPtN/HgLkJ4QPnsdyiR+iSkJEy5XDvKtkt71y5XheAhKQgAS6JoFa/JbQ80rXziqQuuY8sdWdQADxkAzu/OoJDeOJRK9evXKnuAnx7OCh4MkH4WAYltmUvCKEEHGe67M3LwKh3DoThAteF9ZFzTvvvPGPEDK8JdmEkMpPE0wwQf6h+Pmaa66JQo1wM8rE25XdbY/tubM76CE88FBlE4Jsww03DCeeeGJgJzTWFVEWoX0kNiPA8E2hfhyjjVlvBfxI5CPkkDVeKXGukEDKjgECk5TCHHfbbbcoUlk3ROje+eefH9cOEdpYKDGmqYx0PpWVPmcFRKk5kvKn10L9KSaQsnVm60tlFXqtZIwKXZc9xg9S8gJlBRFihZDKcgl2+fzKXVPofAoVLXTOYxKQgAQk0PgEUuROR/VUgdRRpK2nyxPA6/Luu++O1Q/C7RAoGOqEHOFBSEYuYV2IABbj4xnCm8RaoOQhIT/nSRj7GKAYpISApUT+5PVJx/JfWfTPWhs8LSl8CgFAyhrW+dcV+0x/zj777BgKxyYTJIxkvEGpvNNOO63F5dTPOit2OEsJ4Ydxi2hJYW/pHGKC83PNNVfOK4foQmwmUfj0009HAxtjfJNNNol/6XpeWeNSacKLxAYZiy++eFhiiSViuwb/tqU2IYyEPWaFabEy8Yjk/99O2S3GS80R1pNlU6H+ZM/zPv0gZOvM1pefP/u50Bhlz1fynk0umH+IY8Q6Ca8XY5q8kJWUYx4JSEACEpBAVyLgJg1dabRsa6cSYPcudjVDCGCwIobY8pj1KYRrIU7Y3YsdzTD0CZUjbG3++eeP7Sa0jP/3h13aEAGsR8km1tkQ+sWCfwQJa4LYRIE1RqUS4ov8aU0IC+vxjJAQO9UmvFp4chAwGMIIi9NPPz2KkVLlLbPMMrFveHnwchBCxu55HGfNEQIh+wc3Qgw5lvVkIVq4Hg8Y63HgnvUqVduflJ8y8GIxLvCnL6wxIiSQc+y4RyKkMRs+mK7nlfbiDWTrctrIWLHxRUql5gh54Pr+++9XtPEG+WkX7YMD9bIhCHOuPRP/SW3yFtLelVZaKa4DgwlzgTmOx7CSTR7as52WLQEJSEACEmgvAnqQ2ous5TYcgdlmmy2up+HJPFtC4/XBw5K2vmZbZjZBYLtnnroTnoawSHGzbNiA2GHzBIQHT+QpMyW8GBjBrNlBpOBxwstAeFuphEdq9dVXj7vWEeZG3WwBzeYCiLhSa2wKlcv17M6HgLvpppuiMEK8sYEA5RVLCER2zmMzChgRFkeoX1qnVey67HEECMIMAxwBQ9/Z1KEWCQ8RGzYgkOgPohLP1FFHHRWLR6SxJov1XGxcUYgb21qvv/76cUdAdgUkjJAtuPH0kcrNEdY8MScQj+wUWEli842jjz46rt2ijTBOba7k+mrzwIeQw7SFN+/Z0TBtfY7g33XXXast1vwSkIAEJCCBLkOg228hM7/vQdxlmmxDJdC5BLhl2DCAJ+iFwrJYn8HxFCaW31oMfzxQeJcKJTwT1axlSWWkLZWTIEvH2/KKJwyhhmiqNNF+vFh4trLrgSq9nnwwZO1KJTvNVFNuyosQZRzSGqd0nFfO4blJ68Oy59J7PCnkg02hVGqOME6Is/w1W4XKSccQ1GnO1WJNTyq3mlfGBCZZb18117clL2PFPdG//9RhwJixd9Sj3CGhR1XFjx70+/b3VV3UzplHD6y/NrVzly1eAhKQQMUEuo/5fbOlii9oY0YFUhsBerkEJCABCbQvAQVS+/K1dAlIQAL1TqCjBZJrkOp9Rtg+CUhAAhKQgAQkIAEJSKDDCCiQOgy1FUlAAhKQgAQkIAEJSEAC9U5AgVTvI2T7JCABCUhAAhKQgAQkIIEOI6BA6jDUViQBCUhAAhKQgAQkIAEJ1DsBBVK9j5Dtk4AEJCABCUhAAhKQgAQ6jIACqcNQW5EEJCABCUhAAhKQgAQkUO8EFEj1PkK2TwISkIAEJCABCUhAAhLoMAIKpA5DbUUSkIAEJCABCUhAAhKQQL0TUCDV+wjZPglIQAISkIAEJCABCUigwwgokDoMtRVJQAISkIAEJCABCUhAAvVOQIFU7yNk+yQgAQlIQAISkIAEJCCBDiOgQOow1FYkAQlIQAISkIAEJCABCdQ7AQVSvY+Q7ZOABCQgAQlIQAISkIAEOoyAAqnDUFuRBCQgAQlIQAISkIAEJFDvBBRI9T5Ctk8CEpCABCQgAQlIQAIS6DACCqQOQ21FEpCABCQgAQlIQAISkEC9E1Ag1fsI2T4JSEACEpCABCQgAQlIoMMIdBvzW+qw2qxIAhKQgAQkUCWBkSNHhm+++SZMMMEEoW/fvlVe3XzZR4wYEUaNGhX69OnTfJ2vssfDhw8Pw4YNC/369Qu9e/eu8urmyw6rHj16hF69ejVf56vsMayYX5NOOmkYb7zxqry6+bLzHc93FvOrHpIepHoYBdsgAQlIQAISkIAEJCABCdQFAQVSXQyDjZCABCQgAQlIQAISkIAE6oGAAqkeRsE2SEACEpCABCQgAQlIQAJ1QUCBVBfDYCMkIAEJSEACEpCABCQggXog0L0eGmEbJCABCUhAAuUI9OvX+g0aBozpWa74sueHhPZfPDx60Oiy7SiXYfw/MrS9pHI1FT4/emBn1Vy4PaWOMism/yPDr6Uyei4SSNtYyKr0hOg+5qfSGTxb9wT0INX9ENlACUhAAhKQgAQkIAEJSKCjCCiQOoq09UhAAhKQgAQkIAEJSEACdU9AgVT3Q2QDJSABCUhAAhKQgAQkIIGOIqBA6ijS1iMBCUhAAhKQgAQkIAEJ1D0BBVLdD5ENlIAEJCABCUhAAhKQgAQ6ioACqaNIW48EJCABCUhAAhKQgAQkUPcEFEh1P0Q2UAISkIAEJCABCUhAAhLoKAIKpI4ibT0SkIAEJCABCUhAAhKQQN0TUCDV/RDZQAlIQAISkIAEJCABCUigowgokDqKtPVIQAISkIAEJCABCUhAAnVPQIFU90NkAyUgAQlIQAISkIAEJCCBjiKgQOoo0tYjAQlIQAISkIAEJCABCdQ9AQVS3Q+RDZSABCQgAQlIQAISkIAEOoqAAqmjSFuPBCQgAQlIQAISkIAEJFD3BBRIdT9ENlACEpCABCQgAQlIQAIS6CgCCqSOIm09EpCABCQgAQlIQAISkEDdE1Ag1f0Q2UAJSEACEpCABCQgAQlIoKMIKJA6irT1SEACEpCABCQgAQlIQAJ1T0CBVPdDZAMbmcD1118fXnvttYq6+Oabb4arrroq5v3555/DhRdeGD7//POKru3ITEOGDAmXX355eOCBB8KPP/5YtOpnnnkm3Hvvvbnz77zzTrjyyitznyt5M2rUqMjhk08+qSR72Ty//PJLGDlyZNl8bckwfPjwkpdTP/yOPPLI8PDDD5fMy8k777wzPPnkkzFfdo6UuvDDDz+Mc+nuu+8OP/zwQ6ms4fvvvw/ky/+DlUkCEpCABCTQiAQUSI04qvapyxBAIL366qsVtRfj9+qrr455EUgXXXRR+OKLLyq6tqMyHXbYYWGPPfYIGODnnntuGDhwYBg6dGiL6hF2hxxySLjnnnty595+++1wxRVX5D5X8mb06NHhkksuCZ9++mkl2UvmQQhstdVW7So6TznllHDdddeVbMfgwYPDZZddFvr06RP/Smb+7eRdd901lkBKc6TYdZdeemnYYostojC/5pprwk477RS+/fbbYtnDiy++GI455phw3nnnjfX3008/Fb3GExKQgAQkIIGuTKB7V268bZeABOqHwMsvvxy9RniBpp566oCIW3fddcMdd9wRNt5441xDETV4R7p165Y71to3PXr0iHW29vrsdQikjz76KHuo5u/xFi611FIly8UDt/TSS0ehWTJjK04iXBHWp59+elhggQXCr7/+GnbccccovHktlBCuc889dxg0aFCh0x6TgAQkIAEJNBwBBVLDDakdak8C3333Xbj11lsDYmCmmWYKyy67bJh99tljlYR73XLLLeGpp54KvF9wwQXDBhtsELp3//M249x9990XRowYEdZYY40WTcUYveGGG8Jnn30WZpxxxrDZZpuFySabrEW+/AOIkWuvvTa88cYbgRCu6aefPoqSqaaaKmbFUzXddNNFT8tjjz0WJp988rDppptGkYKgwYOw3HLLxf6ksh999NHw0EMPxbaQf4UVVgiLLbZYOt3ilXYef/zxURxxkn737ds3fPPNN2PlpT7EEfV99dVXY53jw/PPPx9uvPHGMGbMmBZtys+MgX/yySfHvk4zzTTxPd6Rm2++Obz11lth2mmnDVtuuWWOISKI+l9//fXonVlkkUXiOOANweNFuuCCC8Kaa64ZevbsGV566aXQv3//6KVZeeWVw6STThrgsvPOO+eaAiOEFWNFKjZHCI9kXAmbG2eccaIXJ1fIH2/w0jAH8B7BcpdddonCZPPNNw/0j4TXEJFDG8hXTWL+0R/EEYkxWmWVVSKTUgIpzfFq6jKvBCQgAQlIoKsS+NNy66o9sN0S6CACrKfZZ5994hoVPCMff/xxDE8iHAqj89hjjw2PPPJIWGuttUKvXr3iOpInnnginHrqqVEQ8P6ggw4KK664Yphjjjli/mHDhuVa/+yzz4b99tsvehgQXrfddlsM+br44otzBn4uc96bvffeOwoj6kYsIdQef/zxaPhijGMYs65llllmCYgCzhM6Ne6440bRg6F96KGHxn5gDCPSzjnnnGj0I/To17777htDrOacc8682n//iNeIPxLriW6//fYYXoewSIkwQQQKIgRu+QkBQzvWX3/9KJ7wNH399ddRaObn5TMiCsG6/PLLB8Qg7+nXPPPME5ZccsmAMHzhhRdiGB75KQ/mcCL076yzzoqCZqONNops7r///jBgwIAwySSTRLFJuNoEE0wQy2Nt0AcffBDDArMCiT4999xzkVWpOYJoHX/88aM4RfwWSjPPPHOYcMIJoxCDM0KbPq222mo5gUT7ObbttttWLZAIRUxCK9XP3EWo4tljruQnBBti8YADDohMaBehk/nl5F/HZ9YplVtzVei6/GNwMElAAhLoKgR4UMZvMYl1noW+W7tKXzqqnfxeYAO0NyseDPI7Wy4pkMoR8rwE/iCAUYqnBU8AoV0kPBhsNjDrrLNGLwMiCcOchLdl++23jx4DQqbOOOOM6DXYeuut43lEEF6clAhhWnTRRcNhhx0WD2HEb7PNNtG432uvvVK2Fq8Y+hNPPHFAJCXDG2McQcOXNMY+CeOctSR8OUw55ZTh4IMPjoYu4oCEkMC7gUCinxjBtIGE9wivCuuligmkmPG3f7788svo+UheMjxXJAQGAgWvSPJsxROZfzCEEZHJU4VhjrcEQYqYqyThmdpuu+1iVjjsueeeUQDg4XrllVfCDjvsEAUHGTiPMBhvvPGiyMKDw/UcxxsHv5NOOinnJcQzVSqVmiOwZGMNxHGxMDuEHsIY7yT5y22gUKothc7hwcKrl02IYxikeZQ9x48V1zBem2yySZzbrKFiDBG45X5kGM9SG3Vk6/K9BCQggUYhkP3ea++NfxqFGf3oCFb83pf77aItCiQomCRQAQGepM8333w5ccQlSbhgOCOaFlpooVxJGMLJE4HXBo9T9jxP7pN44EkTXhdCuPDcpMSTFDwUpVK/fv3CEUccEUOz8NqwzgQvCin7ZYP3CHFEom4SgiyliSaaKBcOh3cCr8KDDz4YvSa0jbLSEzGEQNZ4X2eddaIAoyzC8dg4gGsQRGzGcMIJJ8RQsRlmmCGsuuqqqcoWrwgiPFYpwQ0vDps6ILwIjUsJlkkQpmO8ZgXcFFNMEU+lDQUIJyMkj/YhwhAqiJFiiTFF/FaaSs2R/DIYo/z+VFNXfnn5nwuNEf1B1GdT+ty7d+/s4fieHxFCN5nH/KiQ5pprrujZJFR07bXXjseK/cM1zIe2JuZdoc0+2lqu10tAAhJoDwJ87/EbiVDitzU9VG2PuhqlTB5IErHR3qwqXf+sQGqUmWU/2p0Aa2mSwZ1fGU/aMSYJrUuJmxDPDk/n8aYQDpYfKpS8IoQhcZ7rszcvAqHcOhOEC14X1kXNO++88Y8wPrwl2YSQyk98GRVK7G6GUCPcjDLxdmV322N77uwOeggPPFTZhCDbcMMNw4knnhjee++9uK6Isvbff/+Yjc0IMHz5fOCBB8ZjtBGRlBL8SORjgwNCA1PiXCGBlB2D5KqHLWm33XaLIpV1Q3hCzj///BgaV2z9DWOaykj1prLS5yQw+FxqjqT86bVQf4oJpGyd2fpSWYVeC40RXrT3339/rOyE7MEyyz1lYC7me/uYE/z4V7JzIOzy+aWyq3nNv2+quda8EpCABDqaAA8j03cfv/Pp4WRHt6Mr1QcvONULKwVSV5o9trVTCeB1effdd8dqA+F2CBQMdcLS8CAkIxcPDCKATQPwDPEUnrVAyUNCfs6TMFB5go8BSwhYSuQv92VBWBzrl/C0EDpHQgCQsoZ1PFDBP/Tn7LPPjmFUbDJBwkDFG5TKO+2001qURP1pzVU6ifBDICJaUthbOoeY4DweifTECNGF2Eyi8Omnn44/MqxtIsSLv2yq5v/iwYuE12PxxRcPSyyxRGzX4N+21GabcMIes8I0W0f2PR6RbOgE57JCodQcYQvxbCrUn+x53icu2Tqz9eXnz34uNEZ4y/h/kxBZaV4hfIutJ0JMsSbsqKOOynk7qR9vXrFrsm3wvQQkIAEJSKArEmi5Ircr9sI2S6ADCLDrHLuaIQQwWBFDbKDAmh3CtRAnbD7AjmYY+nhgcK3PP//8sXWElvH//rBLGyKA9SjZxDobQr/YEAFBwpogPCvlQosQX+RHcJFYM4JnhITYqTbxtAtPDgIGcYOwYFtoxEip8pZZZpnYN7w8GOCEkLFJAsfxQiAQsn9wI8SQY1lPFqKF6/GAsR4H7oW8G9X2izLYHY9xgT99waWPN4RzaW0OIY3Z8MFsPbQXbyBbl9NGxopd7VIqNUfIA1dER6Hd+1IZ2VfaRfvgQL38h7jMudYm1pKR2LCDsUXwE5aJiE+Jc8lbiPDHMwgz5hfiiI0tEPSslzJJQAISkIAEGpGAHqRGHFX71C4EZptttriehifzbAmNkYiHJW0owLbMbILAds88nScUCWGBV4jEhg2IHTZPwDglfI4yU8KLgRHMmh1ECh4nvAyEt5VKeKRWX331sPvuu0djlrrZZY3NBRBxpdbYFCqX6/nPQxFwN910UxRGiDcMYsorlhCItIHNKGBEWByhfmmdVrHrsscRIAgzQvYQMPSdDQFqkfAQsWEDxj79QVTimcI7QkKksSaL9VxsXFGIG/8fEDvsHXfccfGPMEK24MbTRyo3R1jzxJxAPLJTYCWJzTeOPvrouHaLNsI4tbmS67N5EFx4Ag8//PAokvDsrbfeetGrlvLBh5BD+kqCGUxgRmJen3nmmdHjGQ/4jwQkIAEJSKDBCHT7LWTm9+D8BuuY3ZFAexHgliHEiCf7hcKyWNPB8RQmlt8ODP+0cDP/HJ/xTFSzliWVgYcHAZYEWTrellc8YQi1FI5VSVm0Hy8Wnq3seqBKrk15YEg8ciU7zaRrqnlFiDIOiNz8xDmERFofln+ez3jVyAebQqnUHGGcEGf5a7YKlZOOIajTnEtx7elca1/Z+II5XGl5eL0I+Su0lq21baj0OsaKe6J//6krvaRFvgFjerY4Vu2BIaFHtZdUnX/0oNFVX1NvF4we2PX7UG9MbU/XItB9zE/xv5QgjJzfwrTJTdfqRce2lu947KYUWt6xtbesTYHUkolHJCABCUigjggokOpoMCpoigKpAkhmaWgCCqTqh7feBJJrkKofQ6+QgAQkIAEJSEACEpCABBqUgAKpQQfWbklAAhKQgAQkIAEJSEAC1RNQIFXPzCskIAEJSEACEpCABCQggQYloEBq0IG1WxKQgAQkIAEJSEACEpBA9QQUSNUz8woJSEACEpCABCQgAQlIoEEJKJAadGDtlgQkIAEJSEACEpCABCRQPQEFUvXMvEICEpCABCQgAQlIQAISaFACCqQGHVi7JQEJSEACEpCABCQgAQlUT0CBVD0zr5CABCQgAQlIQAISkIAEGpSAAqlBB9ZuSUACEpCABCQgAQlIQALVE1AgVc/MKyQgAQlIQAISkIAEJCCBBiWgQGrQgbVbEpCABCQgAQlIQAISkED1BBRI1TPzCglIQAISkIAEJCABCUigQQkokBp0YO2WBCQgAQlIQAISkIAEJFA9AQVS9cy8QgISkIAEJCABCUhAAhJoUAIKpAYdWLslAQlIQAISkIAEJCABCVRPQIFUPTOvkIAEJCABCUhAAhKQgAQalED3Bu2X3ZKABCQggQYjMHTosNC3b99W9mpkK6/r2MvG2aXt9Y0YMSKMGjUq9OnTp+2FtaKEWvShFdW26pLhw4eHYcOGhX79+oXevXu3qoxmughWPXr0CL169WqmbtvXJiSgB6kJB90uS0ACEpCABCQgAQlIQAKFCSiQCnPxqAQkIAEJSEACEpCABCTQhAQUSE046HZZAhKQgAQkIAEJSEACEihMQIFUmItHJSABCUhAAhKQgAQkIIEmJOAmDU046HZZAhKQQFck0K9fazdoqF1vB4zpWbvC/ihpSOhR0zLz9xoYPWh0Tctva2GjB9ZPexjNyf/o0K9t7VgDX999zE8N3Du7JoGWBPQgtWTiEQlIQAISkIAEJCABCUigSQkokJp04O22BCQgAQlIQAISkIAEJNCSgAKpJROPSEACEpCABCQgAQlIQAJNSkCB1KQDb7clIAEJSEACEpCABCQggZYEFEgtmXhEAhKQgAQkIAEJSEACEmhSAgqkJh14uy0BCUhAAhKQgAQkIAEJtCSgQGrJxCMSkIAEJCABCUhAAhKQQJMSUCA16cDbbQlIQAISkIAEJCABCUigJQEFUksmHpGABCQgAQlIQAISkIAEmpSAAqlJB95uS0ACEpCABCQgAQlIQAItCSiQWjLxiAQkIAEJSEACEpCABCTQpAQUSE068HZbAhKQgAQkIAEJSEACEmhJQIHUkolHJCABCUhAAhKQgAQkIIEmJaBAatKBt9sSkIAEJCABCUhAAhKQQEsCCqSWTDwiAQlIQAISkIAEJCABCTQpAQVSkw683ZaABCQgAQlIQAISkIAEWhJQILVk4hEJSEACEpCABCQgAQlIoEkJKJCadODttgQkIAEJSEACEpCABCTQkoACqSUTj0igJgS++eabcOGFF4YRI0ZUVN6dd94ZnnzyyZj3zTffDFdddVVF13Vkpl9//TU8/vjj4fLLLw8vvfRSyaqfeeaZcO+99+byvPPOO+HKK6/Mfa7kzZAhQ2JdleStJM/w4cMrydamPOXqGDlyZOzTkUceGR5++OGSdf38889xDn3++ecxX3aOlLrwww8/jPPn7rvvDj/88EOprPHcJ598Eq6++upw3XXXBd5n0/fffx8oJ//vl19+yWbzvQQkIAEJSKBhCCiQGmYo7Ui9EUAgXXTRReHHH3+sqGl33XXXWAIJg7We0nfffRfWW2+9cP7554f33nsv7LvvvuHMM88s2EQM+kMOOSTcc889ufNvv/12uOKKK3KfK3nz7rvv1kwoIuz23nvvSqptdZ5TTjklioxSBQwePDhcdtlloU+fPvGvVF4EEnPoiy++iNmyc6TYdZdeemnYYostwmuvvRauueaasNNOO4Vvv/22WPbwr3/9K/zzn/8Mb731Vrj99tvjtbBK6cUXXwzHHHNMOO+888b6++mnn1IWXyUgAQlIQAINRaB7Q/XGzkhAAu1GAMN76qmnDueee26s44knnogi6R//+EeYcsopc/WOHj064B3p1q1b7lhr36y44oqBv1okxFZ7G/WIkqWWWqpkc/GKLb300mGPPfYoma81J/EcIahOP/30sMACCwQ8fjvuuGP0DvGan/BUPvTQQ+Haa68NU0wxRTx9+OGHhzPOOCP87W9/i58RtnPPPXcYNGhQ/uV+loAEJCABCTQkAQVSQw6rnWotAbwkt956a3j55ZfDTDPNFJZddtkw++yzx+JGjRoVbrnllvDUU08F3i+44IJhgw02CN27/34bEXJ08803h6effjpMNtlkYfHFF2/RDIzNG264IXz22WdhxhlnDJtttlnM2yJj3gE8CRixb7zxRiCEa/rppw8bb7xxmGqqqaIRfPLJJ4dNN900tg8hMO+884bNN988eqQIy5p00knD6quvHmaZZZZcyY8++mg0jmnL5JNPHlZYYYWw2GKL5c7nv/n73/8eVltttdzhiSeeOL7HO5EVSITRIY6WW2658NVXX+XypzfPP/98uPHGG8OYMWNiHhgXS6+++moM09t9991z/cQ7Amc8HtNOO23Ycsstcww5RpgYHqz+/fuHNddcM8w111yBOh988MHoiTn++OPDzjvvHL1ghAmSD8/MyiuvHNvL2NH2lPCYMdYLL7xwPFRsjhASCUvC5sYZZ5zoiUllpFe8MMwBvEe0Y5dddonCg7GaZpppYja8RYgc2lityGRu0h/EEYm5ucoqq8TQxkICibHbdtttc+KIa+jrAw88EMeH+mlvugc4b5KABCQgAQk0OgEFUqOPsP2rmAChcPvss09gjci6664bPv744xieRDgURuexxx4bHnnkkbDWWmuFXr16xXUkeFFOPfXUaMgSXoXo2GijjQJP8o844oix6n722WfDfvvtFz0MiILbbrstbLXVVuHiiy/OGfhjXZD5QGgYwoi6EUsINcKgECOINUQd5WPYIwhYI/TCCy+EYcOGRcMf0XbQQQfFkCuKRaSdc845UaBhENMvQuYw4Oecc85MzX++nW+++eIH+FA27ebYbLPNlsuER4I2XXDBBTGMLHfijzesZzn00EPD+uuvH8UInqavv/46Cs38vHz+73//G8ULAin1k5CveeaZJyy55JLh+uuvj2255JJLAiGNu+66a/Q4IYyee+65KDJoJ2IOEYhgo38Ih48++ih6ViaYYIJYHv2CKcI4K5D+85//hIkmmigKpFJzBNE6/vjjx3oQv4XSzDPPHCaccMIoWGlH6hPCMwkkxozxRLhQXjXp008/zZWTrmPu0m88ewi3bEIQ54vi++67LzJK4gyB1LNnz3DAAQdEgU67Bw4c2KKebLnpPXO13JqslLfUK5xMEpBA5xFIYbo8COS+bm9vfOf1tHY1p3Wa/O7lf/fWrpbGKQle/P61Nyt+/3lIWS4pkMoR8nzTEMAo5UcAT0CPHj1ivwlRYrOBWWedNRrqiCQMcxKG5fbbbx89BhihXI+hjoFN4jUblsT7RRddNBx22GHxPGJnm222idfstdde8Vihf4YOHRoNfERSMrwxxhE0eDMw8EkY9clLgPHPBgkICEKn8A6tvfbagfAujHT6iZFLG0icR1TgsSkmkGLG3/7Be4NXBUGBwElfZukzXhE8W4UShi5CLRnlGN54SxCk4447bqFLWhyjn9ttt108Doc999wzCoD3338/tglhgSBafvnlwwwzzBA9IXBDOCK4Up8pAH4nnXRSzkPCRgSlUqk5QrlsyjHHHHMUDbOjTQhj5gb5K9lAoVR78s/hwerbt+9Yh/khQByleTTWybwPrHtDgKYwSn7YKZPx3GSTTeLcx0PHGPPgALFXKlGvhlQpQp6TQNcgkL2P+R5Pxn/XaH3nthJBaaqMQEewGm+88SpqjAKpIkxmagYCPCnHI5LEEX1OwgVRwPGFFloohwJDeJJJJolP1dmpjvdJHJEJMZQEEjc9u7gR6obnJiXEBV6XUqlfv37RG0X7WESPdwojloQoSQKJ9qSEYKMtaV0JZZDwsiCQEBF4FQg7++CDD2LbKIt2kicrFCgj61FhzRGChlAyNmJA8BDGRV8RJKuuumpqRotXBBEeq5QWWWSR6MUhJA6PT1YwrLPOOinbWK9ZAZf6x483Aoh+E3r417/+NYow2pX6PlYhf3xgTBG/laZScyS/DMbo9ddfzx1m7lRTV+7CIm8Qa/m86A+iPpvS5969e2cPt3iPuMPzePTRR+cEIwKI0E7mdvpRgTOeTzxNiO5SifHGc9fWxLxE4JkkIIHOIZDuY75zeAJfrXe7c1rdubXCiqgDIhCydkXntqp+a+c7HnuG+dWeKUVHlKujfVtRrnbPS6COCCAMksGd3yyepGMsElqXEjcZngqeknOeV9bVpJsv6xEhzIhzXJ/OUw4CoZyrF+GCCGFdFGuL+GPjgldeeSU1Jb7mew6yBnG2TjKzuxlCbcCAAbE8Qv7wHpH4kkIQpoTwygokjvMFlsIECUFD9LCuiLbtv//+8VK8VRi2fD7wwAPjMcQKRnNKaR0T+fB4pd3aOI+4KZSyY5C8V7Clv3i2WE9EqBzrsthsAK/fX/7yl0JFxTFNZaQMlJVN2SelpeZI9hres2EDoZAp0ddiAilbZxI06bpir4V4sX7q/d88adlEyAJ1Z7lnzzNvYUV5eNOyApZ5k+8NZM5gLBHOVy5xfS1+7AyxK0fa8xJoXwLpPub7kt+29Ll9a+3apaffFnlVNo78XtQTKwVSZeNmriYggPeBDQ6yiXA7BMqMv4VoEZaGByEZuXhgEAFsGoDBSLgW59OaHNYEpYSBigGPAbvDDjukw3HDh3I/NHhqKIvwp7QZAjuPkbKGda7QMm/oz9lnnx3DpNhkgoQBSrgc5eF5KrQdN7uuLbHEEgEPUko8IUOYIVpS2Fs6h5hAGOJxSE/PEECIySQKWRvFjwi745122mnp0la94lljEwu2IuePuvEAEmaIQMoXiYUqwUuS3ZYdsfLll1/mspaaI3hVsomQNP5KpcQlW2clwoMyC/Fi7NiUg3aneYXwTeubCrWFccfbxZxA/GQTYos1Y0cddVSYbrrp4inaB5NSZWbL8L0EJCABCUigqxEYe8VuV2u97ZVADQmsscYa8T8/RYhgsCJ2WODPDl6smUGcsPkA63sw9PHA4Dqff/75Yx5E1ODf/o8bzhFOl/XC0EzC0vBusCECgoSNDvCslAsdIiyP/GmRLGtC8JSQEDvVJp7Q4MlBwKQ1ImwLjaekVHmII0KwEIXku+mmm6LXiZA6RBICIfsHN4xqjqUwQNoKIwx4PGCsx4F7Me9GtX3j/+vBowUvBBJiLBnytJENIRBSxbw0tPexxx6LG3RwPWGDlJWEaKk5QlvhiqhAPFeSUggaHAjT5D9pZc61NrGWjMQ4MbYI/vR/G6UyOZe8hXfccUf0HPH/IMEKoZT+6DdzmlAa5jrzD3F01lln5dZ4pTJ9lYAEJCABCTQSAT1IjTSa9qVNBPD8sKaGJ/MsUsfrg4clbSjAtswY4GzNzdN5nrYjLPAKkU444YT4tJ01MCReEUopbb311tEIpg5ECus68DCU2uaaawl5YotudnLDWKVutoAmHAoRh1ejmsT1/OehrDlB5CCMEG9sIEB5xRKbChDmhzGNp4Vy2CChXPuz5SFAEGaEzyGyuJYF/7VIbNhAWYhHxol+saFG8uwgZPFWMX7ZdWDZuhkztv5mXOgju8uxvXfyPpWbI/wfSMwJRAY7BVaS2HyDdT8ITYQk44zHpjUJwYVHiP/LCCGEZw9vWnbLefrOZh7830ZsuEA68cQTW1SHmMfryRizIyNzhMS85z8IzoZwtrjYAxKQgAQkIIEuTKDbb09Gxw6478KdsekSqAUBbglCiAibS4ZxtlzWdHA8hYllz/GeJ+0Yj8W8IngvqlnLksrH4MfblARZOt6WV7xdCDXETqWJsDoY4FFD6LUmpa08y+2C1pqyuQZPEWUXGoNsiF+x8hkfxrDYQuRSc4RxwvtS7NpCdeLtSXMuxa0XylfNMTa+YA7Xqjy8YoQEltr0opr2VZMXMc2Y9O8/dTWXtUveAWN61rzcIeH3XTNrXvAfBY4eNLq9im5VuaMH1ld7WtWJJruo+5ifYo/57uZ7ILsWtMlQVNxdWBGJQBRI2uSm4oubMCPf8dhVKfS8sxEokDp7BKxfAhKQgARKElAglcRT9qQCqSwiM5QhoEAqA6jAaQVSASglDtWbQHINUonB8pQEJCABCUhAAhKQgAQk0FwEFEjNNd72VgISkIAEJCABCUhAAhIoQUCBVAKOpyQgAQlIQAISkIAEJCCB5iKgQGqu8ba3EpCABCQgAQlIQAISkEAJAgqkEnA8JQEJSEACEpCABCQgAQk0FwEFUnONt72VgAQkIAEJSEACEpCABEoQUCCVgOMpCUhAAhKQgAQkIAEJSKC5CCiQmmu87a0EJCABCUhAAhKQgAQkUIKAAqkEHE9JQAISkIAEJCABCUhAAs1FQIHUXONtbyUgAQlIQAISkIAEJCCBEgQUSCXgeEoCEpCABCQgAQlIQAISaC4CCqTmGm97KwEJSEACEpCABCQgAQmUIKBAKgHHUxKQgAQkIAEJSEACEpBAcxFQIDXXeNtbCUhAAhKQgAQkIAEJSKAEAQVSCTiekoAEJCABCUhAAhKQgASai4ACqbnG295KQAISkIAEJCABCUhAAiUIKJBKwPGUBCQgAQlIQAISkIAEJNBcBLo3V3ftrQQkIAEJdFUCQ4cOC3379u3k5o/s5PrLVz9ixIgwatSo0KdPn5h5nF3KX9OROeqpPcOHDw/Dhg0L/fr1C7179+5IDNYlAQnUMQE9SHU8ODZNAhKQgAQkIAEJSEACEuhYAgqkjuVtbRKQgAQkIAEJSEACEpBAHRNQINXx4Ng0CUhAAhKQgAQkIAEJSKBjCSiQOpa3tUlAAhKQgAQkIAEJSEACdUzATRrqeHBsmgQkIAEJ/EmgX7/O3qDhz7bU97v232xgwJieYUjoEUbtOyqMe+KP9Y3D1klAAhKokoAepCqBmV0CEpCABCQgAQlIQAISaFwCCqTGHVt7JgEJSEACEpCABCQgAQlUSUCBVCUws0tAAhKQgAQkIAEJSEACjUtAgdS4Y2vPJCABCUhAAhKQgAQkIIEqCSiQqgRmdglIQAISkIAEJCABCUigcQkokBp3bO2ZBCQgAQlIQAISkIAEJFAlAQVSlcDMLgEJSEACEpCABCQgAQk0LgEFUuOOrT2TgAQkIAEJSEACEpCABKokoECqEpjZJSABCUhAAhKQgAQkIIHGJaBAatyxtWcSkIAEJCABCUhAAhKQQJUEFEhVAjO7BCQgAQlIQAISkIAEJNC4BBRIjTu29kwCEpCABCQgAQlIQAISqJKAAqlKYGaXgAQkIAEJSEACEpCABBqXgAKpccfWnklAAhKQgAQkIAEJSEACVRJQIFUJzOwSkIAEJCABCUhAAhKQQOMSUCA17tjaMwlIQAISkIAEJCABCUigSgIKpCqBmV0CEpCABCQgAQlIQAISaFwCCqTGHVt7JgEJSEACEpCABCQgAQlUSUCBVCUws0uglgSuv/768Nprr1VU5JtvvhmuuuqqmPfnn38OF154Yfj8888rurYjMw0ZMiRcfvnl4YEHHgg//vhj0aqfeeaZcO+99+bOv/POO+HKK6/Mfa7kzahRoyKHTz75pJLsZfP88ssvYeTIkWXztSXD8OHDS15O/fA78sgjw8MPP1wyLyfvvPPO8OSTT8Z82TlS6sIPP/wwzqW77747/PDDD6WyxnPff/99rOfaa68NXGuSgAQkIAEJNDIBBVIjj659q3sCCKRXX321onZi/F599dUxLwLpoosuCl988UVF13ZUpsMOOyzsscce0Yg+99xzw8CBA8PQoUNbVI+wO+SQQ8I999yTO/f222+HK664Ive5kjejR48Ol1xySfj0008ryV4yDyJgq622alfRecopp4TrrruuZDsGDx4cLrvsstCnT5/4VzLzbyfvuuuusQRSmiPFrrv00kvDFltsEYX5NddcE3baaafw7bffFsse3nvvvbD22mvHdr/yyithm222CU888UTR/J6QgAQkIAEJdHUC3bt6B2y/BCRQHwRefvnl6DXCCzT11FMHRNy6664b7rjjjrDxxhvnGomowTvSrVu33LHWvunRo0ess7XXZ69DIH300UfZQzV/j7dwqaWWKlkuHrill146Cs2SGVtxEu8Pwvr0008PCyywQPj111/DjjvuGIU3r4XSscceG9Zaa62w++67xzG7+PBUaj8AAEAASURBVOKLw6mnnho9ULUYw0J1ekwCEpCABCTQmQQUSJ1J37q7HIHvvvsu3HrrrQExMNNMM4Vll102zD777LEfhHvdcsst4amnngq8X3DBBcMGG2wQunf/8zbj3H333RdGjBgR1lhjjRb9x4tyww03hM8++yzMOOOMYbPNNguTTTZZi3z5BxAjhD+98cYbgRCu6aefPoqSqaaaKmbFUzXddNNFT8tjjz0WJp988rDppptGgxdBgwdhueWWi/1JZT/66KPhoYceim0h/worrBAWW2yxdLrFK+08/vjjozjiJP3u27dv+Oabb8bKS30Y1tT31VdfjXWOD88//3y48cYbw5gxY1q0KT8zBv7JJ58c+zrNNNPE93hHbr755vDWW2+FaaedNmy55ZY5hogg6n/99dejd2aRRRaJ4/DTTz8FPF6kCy64IKy55pqhZ8+e4aWXXgr9+/ePXpqVV145TDrppAEuO++8c64pMEJYMVakYnOE8EjGlbC5ccYZJ3pxcoX88ea8884LzAG8R7DcZZddwqBBg8Lmm28e6B8JryEihzaQr5rE/KM/iCMSY7TKKqtEJoUE0tdffx1ZHXjggTlBy7yFEWJv7rnnrqZ680pAAhKQgAS6BIE/Lbcu0VwbKYHOI8B6mn322SeuUcEz8vHHH8fwJMKhMDp50v7II4/Ep+29evWK60gIReJpO4KA9wcddFBYccUVwxxzzBHzDxs2LNehZ599Nuy3337Rw4Dwuu2222LIF0/sy4mkvffeOwojnvQjlhBqjz/+eDR8McYxjFnXMsssswREAedffPHFMO6440bRg6F96KGHxn4g+BBp55xzTjT6EXr0a9999w0Y8HPOOWeuzdk3eI34I7Ge6Pbbb4/hdQiLlAgTRKBgYMMtPyFgaMf6668fxROeJox0hGahhIhCsC6//PIBMch7+jXPPPOEJZdcMiAMX3jhhRiGx/WUB3M4Efp31llnRUGz0UYbRTb3339/GDBgQJhkkkmi2CRcbYIJJojlsTbogw8+iGGBWYFEn5577rnIqtQcQbSOP/74UZwifgulmWeeOUw44YRRiMEZoU2fVltttZxAov0c23bbbasWSIQiJqGV6mfuIlTx7DFXsglBRyJPSojE8cYbLwq1cgKJuVjJGqdUdrFX2maqXwL5D0Hqt6UtW8Y9RuLBEg9KTKUJ8FCK+7rU+tLSJTTPWViR+M7O/25tHgqV95Q1wLBq78gEIk8qebioQKp87MzZ5AQwSvG04AngBiPxBchmA7POOmv0MiCSMMxJeFu233776DEgZOqMM86IXoOtt946nkcE4cVJCU/BoosuGg477LB4CCOe9R6ssdlrr71SthavGPoTTzxxQCQlwxtjHEGDNwNjn4Rxfswxx0SvwZRTThkOPvjguEYIcUBCSODdQCDRT9YP0QYS3iO8KqyXKiaQYsbf/vnyyy+j5yN5yfBckRAYCBS8IsmzFU9k/sFYQUQmTxVeHLwlCFLEXCUJz9R2220Xs8Jhzz33jAIAkckamh122CEKDjJwHuMbgx+RhQDkeo7jjYPfSSedlPMS4pkqlUrNEViysQbiuFiYHW1AGOOdJH8txEW2vQgevHrZxA8FDNI8yp5DUDEG/GUT15Rat5TyUm57b3qR6vK18wg0whjzXZ4M2s4j2TVqTqKya7S281uJ4W+qjADiu70TD1YrSQqkSiiZRwK/ESD0ab755suJI6Ak4YLhjGhaaKGFcqwwhJMnAq8NHqfseZ7KJ/HAlwJeF57O47lJiadOeChKpX79+oUjjjgitg+vDetM8KKQsoYL3qMU7pc8AgiylCaaaKJcOBzeCbwKDz74YPSa0DbKSl9eCIGs8b7OOutEAUZZhOOxcQDXIIjYjOGEE06IoWIzzDBDWHXVVVOVLV4xxPFYpQQ3vDhs6oDwIjQuJVgmQZiO8ZoVcFNMMUU8lZ4ME05GSB7tQ4QhVBAjxRJjivitNJWaI/llMEb5/ammrvzy8j8XGiP6k28Eps+9e/fOLyLO6XQ+exIDqVD+bB7eM55pDPLPVfOZeYdYNdUngVqMcWf1DE8InmtEP55/U2kCsOJ7hAduptIEYMX84gEmzEylCfAdTwRFslNK52792Uo9VAqk1jP2yiYjQBhJMUOAL0Ju7OwPLDchX4w8RcebwlOL/CdvyStCeAfnuT578yIQyrmCES54XVgXNe+888Y/wvjwlmQTQio/ET5WKLG7GUKNcDPKxNuV3W2P7bmzO+ghPPJ/MBFkG264YTjxxBPjTmisK6Ks/fffP1bJZgQYvnxmjQuJNma9FfAjkY81L4QGpsS5QgIpOwYprCE9Mdptt92iSGXdELvJnX/++TE0rtD6G+phTFMZqd5UVvqcFRCl5kjKn14L9aeYQMrWma0vlVXotdAY4UV7//33x8pOSAMss9xTBvIzZ5m/WUHENSmcMuUt9MpcTnO80PlKj+WPQaXXma9jCNRijDumpS1rSd+3zLGu3I+WPWufI3CSVWVs0/eWvCrjxb1YT6wUSJWNm7kkENdhvPvuu2ORINwOgYKhTsgRHoRk5OKBQQSwaQCeIbxJrAVKHhLyc56EgYoBikFKCFhK5C/3NIWwONYv4WkhdI6EACBlDet4oIJ/6M/ZZ58dQ+HS2h+MZLxBqbzTTjutRUnUn9ZcpZMIPwQioiWFvaVziAnOzzXXXLmna4iu9DSXfE8//XT8wsQY32STTeJfup7XakIX8CKxQcbiiy8ellhiidiuwb9tqU0II2GPyVDKlp//nlC8/Nj77BbjeOaKzRG2EM+mQv3Jnud9euqYrTNbX37+7OdCY4S3jP83CZGV5hXCN39dUiqHTS7IRx7EOgmvF2OavJApr68SkIAEJCCBRiEw9orcRumV/ZBAOxBg9y52NUMIYLAihthAgTU7hGshTth8gB3NMPTxwBC2Nv/888fWEFrG//vDLm2IANajZBPrbAj9YkMEBAlrgvCsFPp/hLLXIb7In9aEsM4EzwgJsVNt4ikqnhwEDIYwwoJtocv9J6rLLLNM7BteHgxwQsjYJIHjrDlCIGT/4EaIIceynixEC9fjAWM9DtwLeTeq7Rdl4MViXOAPG1z6hARyLq3NIaQxGz6YrYf24k1h63LayFixq11KpeYIeeCKB6fQ7n2pjOwr7aJ9cKBe/kNc5lxrE2vJSGzYwdgi5gjLRMSnxLnkLaS9K620UlwHBhPmAnMcjyHtMklAAhKQgAQakYAepEYcVfvULgRmm222uJ6GJ/NsCY3XBw9L2lCAbZnZBIHtnnnqTngawgKvEIkNGxA7bJ6AccoTecpMCS8GRjBrdhApeJzwMhDeVirhkVp99dXj/1NDmBt1s8samwsg4kqtsSlULtfzn4ci4G666aYojBBvbCBAecUSApH/K4fNKGBEWByhfmmdVrHrsscRIAgzDHAEDH1nU4daJDxEbNiAQKI/iEo8U0cddVQsHpHGmizWc7FxRSFu7NrGDnvHHXdc/COMkC248fSRys0R1jwxJxCP7BRYSWLzjaOPPjqu3aKNME5truT6bB4EF57Aww8/PIokPHvrrbde9KqlfPAh5DDtUMd78qetzxH8u+66a8ruqwQkIAEJSKDhCHT7LWSmsu0cGq7rdkgCrSPALcOGATxBLxSWlbapLLZ2CMMfDxTepUIJz0Q1a1lSGXh4EGBJkKXjbXnFE4ZQQzRVmmg/Xiw8W9n1QJVeTz4YEovMGqD2SAhRxgGRm584h5AotR4BTwr5YFMolZojjBPiLH/NVqFy0jEEdZpzKa49nWvtKxtfMIcrLY8xgUnW29fauqu9jrHinujf//dt5Ku93vy1JzBgTM8wJPQIo/YdFcY98cfaV9BBJRLmy9zGW5pdZ9dB1Xe5amBF6G9rv9u7XIfb0GBYMb/4LSQ821SaAN/x2E0ptLx07vY/W7nV0/5tsQYJdAkCiKJimzXQgRSqVawzGN/8FUuIkVLlF7uOL5VaiiPqaU07aD9rV9qSyjFsS9lciyFUzBgqdjxbJ+KmlMApNUcYp2p/ABAxaX1Zth1teV9tee09Jm3pi9dKQAISkIAEaknANUi1pGlZEpCABCQgAQlIQAISkECXJqBA6tLDZ+MlIAEJSEACEpCABCQggVoSUCDVkqZlSUACEpCABCQgAQlIQAJdmoACqUsPn42XgAQkIAEJSEACEpCABGpJQIFUS5qWJQEJSEACEpCABCQgAQl0aQIKpC49fDZeAhKQgAQkIAEJSEACEqglAQVSLWlalgQkIAEJSEACEpCABCTQpQkokLr08Nl4CUhAAhKQgAQkIAEJSKCWBBRItaRpWRKQgAQkIAEJSEACEpBAlyagQOrSw2fjJSABCUhAAhKQgAQkIIFaElAg1ZKmZUlAAhKQgAQkIAEJSEACXZqAAqlLD5+Nl4AEJCABCUhAAhKQgARqSUCBVEualiUBCUhAAhKQgAQkIAEJdGkCCqQuPXw2XgISkIAEJCABCUhAAhKoJQEFUi1pWpYEJCABCUhAAhKQgAQk0KUJKJC69PDZeAlIQAISkIAEJCABCUiglgS617Iwy5KABCQgAQm0F4GhQ4eFvn37tlfxDVPuiBEjwqhRo0KfPn3asU8jY9njntiOVVi0BCQggU4ioAepk8BbrQQkIAEJSEACEpCABCRQfwQUSPU3JrZIAhKQgAQkIAEJSEACEugkAgqkTgJvtRKQgAQkIAEJSEACEpBA/RFQINXfmNgiCUhAAhKQgAQkIAEJSKCTCCiQOgm81UpAAhKQgAQkIAEJSEAC9UdAgVR/Y2KLJCABCUigAIF+/fqGbt1Czf6++O8tBWrxkAQkIAEJNDsBBVKzzwD7LwEJSEACEpCABCQgAQnkCCiQcih8IwEJSEACEpCABCQgAQk0OwEFUrPPAPsvAQlIQAISkIAEJCABCeQIKJByKHwjAQlIQAISkIAEJCABCTQ7AQVSs88A+y8BCUhAAhKQgAQkIAEJ5AgokHIofCMBCUhAAhKQgAQkIAEJNDsBBVKzzwD7LwEJSEACEpCABCQgAQnkCCiQcih8IwEJSEACEpCABCQgAQk0OwEFUrPPAPsvAQlIQAISkIAEJCABCeQIKJByKHwjAQlIQAISkIAEJCABCTQ7AQVSs88A+y8BCUhAAhKQgAQkIAEJ5AgokHIofCMBCUhAAhKQgAQkIAEJNDsBBVKzzwD7LwEJSEACEpCABCQgAQnkCCiQcih8IwEJSEACEpCABCQgAQk0OwEFUrPPAPsvAQlIQAISkIAEJCABCeQIKJByKHwjAQlIQAISkIAEJCABCTQ7AQVSs88A+y8BCUhAAhKQgAQkIAEJ5AgokHIofCMBCUhAAhKQgAQkIAEJNDsBBVKzzwD73yYCzz77bLjtttsqKuPnn38OF154Yfj8889j/jvvvDM8+eSTFV3bkZm+++67cPPNN4ebbropfPrppyWrvvbaa8M777yTy3PPPfeExx9/PPe5kjf33ntvePTRRyvJWlGe4cOHV5SvtZl++eWXMHLkyKKXw+PKK68ser6tJ2rB68MPPwxXXXVVuPvuu8MPP/xQtknff/99YL4y3lxrkoAEJCABCTQyAQVSI4+ufWt3As8991xVAumiiy4KX3zxRWzXXXfdVXcC6f777w8bbLBBeOKJJ8IDDzwQ/vnPf4ZnnnmmIMdbbrklnHHGGW0WSNRJfbVIp5xySrjuuutqUVTBMhAKW221VU7kFsr09ttvhyuuuKLQqZocayuvSy+9NGyxxRbhtddeC9dcc03Yaaedwrffflu0be+9915Ye+21I9dXXnklbLPNNjUbr6KVekICEpCABCTQiQS6d2LdVi0BCdQRATwj55xzTthuu+3CxhtvHFt27LHHhvPPPz8svPDCY7X0448/Duedd17o0aPHWMdb8+GYY45pzWUFr8HoX2qppQqeq8VBBNJHH31Ui6JaXUZbeOH9QaSffvrpYYEFFgi//vpr2HHHHcPVV18dXws1ijmw1lprhd133z1069YtXHzxxeHUU0+NHig+myQgAQlIQAKNRkCB1Ggjan/KEnj99dcDYUoY+YssskhYbrnlwiSTTBKv++abb2J4FGFSHFtppZXCoosumivzk08+CbfeemvAS4CBOWrUqNy59IZQpMceeyyGYf3lL38J66+/fujevfytRtkphKlnz55hnnnmCf/4xz+iCHn11VcD3qoFF1wwhr79+OOPYdVVV41tI5yLJ/ucW2211ULfvn1jUwjpo7w33ngjEHY2/fTTR+Ez1VRTpaaO9UpfBg4cOJYYmnjiiWO92YwY1UceeWT0pGBs5xvJY8aMiZ6Jp556Kkw55ZRho402inVny8i+v+GGG8IEE0wQVl555UA/8VjB/MYbbwxff/11bA8cxh133HjZHXfcER566KGAoJtlllnCpptuGvtMyNhnn30WHn744TDOOONELwn9n2666cLTTz8dGNvNNtssXH/99WHzzTcP00wzTSwPjx792HnnnUOfPn3isUJzpFevXuHcc8+N5y+44IKw5pprxvkTDxT45/nnn499gAdzbNlll83lKjXWZHrrrbeix4ZwzP79+8e65pprrnh9lhcHCrU1zed4QeYfxoTymLsk5uUqq6wS5zxCKT/Bn/IPPPDA3DivscYagf4jRueee+78S/wsAQlIQAIS6PIEylttXb6LdkACfxLAAN9zzz3DQgstFJZeeum4roKQpbPOOivgHSB8CCN5nXXWiaJj//33j0/O11133TBs2LCwxx57BEQDRiVCaMiQIWG22WbLVcCTedbh8MS9d+/eMdTqhRdeCDyFL5UwmAnd+vvf/x6FAuUOHjw4sB4Iwx2vBQKAsjFQMU4PPvjgaOgiiP7617/GugiVImSKtPfee0dhRFsQS4TEsT4IQYWAyE/jjz9+ZMJxDGOMaUTKtttuO1ZWPAj0DeGHsMhPt99+e5hhhhkig/vuuy96pFh7Ne200+ZnjZ+pZ9JJJ439pp+IGtbGLL/88gExhyhBEG699daR+b///e+w5ZZbhn79+sX2cT3lIwDpw+STTx5mnHHGWDZrvOBGOYwrggCBi5BMAolx5Rj9JE+xOXLaaadFQcZ8GTBgQE5UF+oUc+nQQw+NjL766qsoKGFK+GK5sUbI7brrrmHFFVeMwghhzByAO1yzvIq1lflcKLGmLPU7nUcw0cbRo0e3mBcIThJ5UmKsxhtvvBgqWk4gMe8qWeOUyi72StvaI/0wbHjo3uub9ii6U8vkYQfCnIcIptIE0kMuHiL99NNPpTN7NnqdWYPJd7KpNAEeJpL4jSn0m1v66uY7y/fV0KFD250VdkB6kFyKsgKpFB3PNRyBQYMGRXGz1157xb4tscQS4X/+53/CBx98ENcSjRgxIhrohI4hADC2CTvDoCYMCS8Cn/GaIJp22GGHHCPCl/BO/Otf/4rGLSeWWWaZsMkmmwS8CbPOOmsub/4brsXLgCBLX6SIIwzglPiSZY3N7LPPHn+k8JTwg47hTsIgQtAgkPiSQcghkpJYQEDsu+++UXQV8zCkuo444ojw0ksvRcM4G7KGp+r//u//oiDJ9xylazGeCb/jSwihCUdEGXVXkmg7QnPmmWeO2THe8QAhkF5++eXYf7xS1D///PNHjxGG+OKLLx7bNcccc4wVZoc3jrVSeKAqMdaLzRHEBaKNvjFW8CyWMLoOOuigsNhii8UstAExyZwpN9bvvvtu9D4i2BhD6kQYMb75qVhbmc9ck58QPPk/DIhCBEiaM9lr6DNt5y+buKbUuqWUl3JLbWiR8nXW68+/jqzr9rWVSzL+21pOM1yPMZsM2mbob1v7KKvKCfqgonJW7fUwLNuCQr+l2fPpvQIpkfC14QlwUxA6h2BJaaKJJorGM58Ja2KtTXZdDQIK4x6jlmsJY8sKA0LB0iYGb775ZjRiCWnDA5QSoopzpQQShjRl4y14//334x/lZoUMBj4hZSTEB+Fr2fA/+oKXgoR3BZFDKCAeHdr/4osvxnMYrLwndColPGrZ9iFQEGisP2JBP8IPLoTWsRYF4Vgs4c2ifSnBFCZ4RvAMpTTFFFNEoZE+p1cEVhJHHCMfHjMSYmGfffaJoYIwQxSVC2FEUKbwvFhIiX/KzRG8P9mE5ykruhCEJAQF45kSoZwIbELmyo01oXR4bFgHBkvy47H8/+2dBZwkxfm/647D4XB3zwUPrv/DXUNw1yDBXYK7hgQJ7h4IDgkuwd3d3YLbwfzrqfxqrndudmTlbnf2qc9ndnq6q6urnqqZrW+/b71NnxZTvbpWqxt9WDmxyZ+xClamavnJw8S7Wv7K8+HAOO1sQgA3Isiavc54444XJuqC+jV73e7Oz919+misscbq7kv1+vK5KYbFlxsH/FabahOAFb/vsqrNiaOwYnxxo4v/a6baBPiN5zerOAerfUb3Hh06i+ne61i6BEY4ASYNvNr7YWeiW3nXnR82Enc1+LGrnOwVJ94c5zNf7qKIYgKfrTjtQUB8Ye3hHw9Wkdlnnz3VFWGTE+t0itdjP/tyKl4TEYQFA4sLZfHCZQsLEAnBgctdTrSzKJDYj+Daeuutk8DCNQ/BhDUHNz9eJNxSmPhT/+233z7tQ9AUEyKPCS4WCsKH54SlB0tMZcJNrpiwqOU7PqzpwhJDBEDqxHocXByxomHVqJYqLSbkyeWxnQUC2/XGCHmKibVsOSoh+xEyJMRM0eqSxxEc6vU1wgNhmtt4/PHHJxGPmybtz6leXavVbcIJJ0ziO5fBO5ZJ6lesbz5Ofiba/JMvCiLOmWyyyXK2dt8Zk8Vx2W7GOge6ooxql+jXv1/ZYlvteG/dl7lna3RvbcfwqHceW7zLqz7xzElWjbEiF6zk1RivnsRKgVS/z8zRIgSY4DHpR3TkqGwIH1zsEDGskal8LhGfESXTTTddcu1iUl5MPAcpJ85nMonVCUFC4jNrlWq5Y5Evr6Fhop9FEC5uHTU3435H3RAvWdQR2ICEOMCKVrSksf/NaLlCpLHGJ685wYWPNnAOlg3W/hQTVi7yFgUgAqCYcI8jUAIMOxv+mv6gHxFuvLD68c66HKxL9VK+M4W4yAk3spzqjZHKABfZvTGfn98RTQjmLNpgwA8/ouLggw9O46G9vmZ8YnFbc8010wsRiksoVryiQKpX12p1ow8Yj4jCbOXDjbNyXVJuB2OafOTBCkbC8si4zGMk5/VdAhKQgAQk0CoE+rdKQ2yHBBohQMACXOaYUOMXzKQTITJo0KD0rJf33nsvTeK5Y05wBSweCB7M40svvXRykSKIABYaFutjocmJyStC4Oyzzw48O4Y8CJ/TTjutzd33nL/4zsJ3JtScgxhB4Nx1113J8lLM1+g25SFsslsSa0+wSpC4RrWEyEFMscYKaw/uYCz2xxqCm9ccc8yRAkkQTCK/sPawRmmllVYqFwlP+DIJhx/uhUz2uyIhvg477LAUtAJOuO3RzjzBp64IPSxd1RJWEtwDebgvfYzLHMEPiqnWGMnWKNpUdK0rnp+3z4tBNmCA1Y7rEVyD6zfS14TyvvPOO1PbEEiMjdzGXD7vtepazJe3GcOkiy++OIkc1jvhgokbZU4cy2vf4EkkR6x2tBfBTAQ7LGW13CxzWb5LQAISkIAEeiMBLUi9sdesc4cJYAHBVYyAAdwZxz0LVzQm+qwZ2XvvvQML35kEYslZdNFF0z4uSMQu8iJ4EA64jjFRZEE8ifKOOuqowOSW61Ama2n233//ZLmqNaEm6ACTVSa8iDHqReQyxAoT5GYTbUG0sF6IelA3yjvuuOPSuiQsCdUSEf4OOuigFFwBKwEuh8cee2xywaqWv9o+wlkTTOKTTz5J7lWUmS121fI3s48ocKyrIiQ17mq4e+y4444Bdz0SYo31U6yxwv2uWsJKdvjhh6cw6bgowgjRlVOtMUIe1n2xvos+Iyx6tYRQRrwxPhCkMMkuiPX6GmsjeRG0jCWEPOMQUVqZ6tW1Mj8CjXVkWLEQQribIl5Zy5UTYw6+OUId2+QnrDnn4wJKlD2TBCQgAQlIoFUJ9It3YYcNjdSqrbVdEvg/AkyuESzFIAgZDl8JXKS404+wqJaY/LM+I/uvV+ahbCwb3IFvJmG5wQ0M96muSDlsJnVtJtF+2l6NT6PlUAbnt8ew0XKq5UO80Qesd6rsA9oMe4RheymfjxWkPd/wWmME6xNiIbtDtnedHN612mL5RvqaoBucy7VqpVp1be88LIS12l95Hm2hvcV1b5V5uuszIhPBOfnk9dc9NVOHj969Pkw8xSrNnNIr8jI++Q5kF89eUekRVEluQDG2+a3uqt/dEdSU4XJZWPE/qr21vMOlEr3kIrBifDGXMEhD/U7jN57frOwKX/+M7s2hQOpevpYuAQlIQAKdJKBAag6gAqlxXgqkxlmRU4HUOC8FUuOsyNnTBJJrkJrrP3NLQAISkIAEJCABCUhAAi1MQIHUwp1r0yQgAQlIQAISkIAEJCCB5ggokJrjZW4JSEACEpCABCQgAQlIoIUJKJBauHNtmgQkIAEJSEACEpCABCTQHAEFUnO8zC0BCUhAAhKQgAQkIAEJtDABBVILd65Nk4AEJCABCUhAAhKQgASaI6BAao6XuSUgAQlIQAISkIAEJCCBFiagQGrhzrVpEpCABCQgAQlIQAISkEBzBBRIzfEytwQkIAEJSEACEpCABCTQwgQUSC3cuTZNAhKQgAQkIAEJSEACEmiOgAKpOV7mloAEJCABCUhAAhKQgARamIACqYU716ZJQAISkIAEJCABCUhAAs0RUCA1x8vcEpCABCQgAQlIQAISkEALE1AgtXDn2jQJSEACEpCABCQgAQlIoDkCCqTmeJlbAhKQgAQkIAEJSEACEmhhAgqkFu5cmyYBCUhAAhKQgAQkIAEJNEdgQHPZzS0BCUhAAhIYMQS+/PKrMHDgwC68+CpdWJZFSUACEpBAqxDQgtQqPWk7JCABCUhAAhKQgAQkIIFOE1AgdRqhBUhAAhKQgAQkIAEJSEACrUJAgdQqPWk7JCABCUhAAhKQgAQkIIFOE1AgdRqhBUhAAhKQgAQkIAEJSEACrUJAgdQqPWk7JCABCUhAAhKQgAQkIIFOEzCKXacRWoAEJCABCQwPAuOM05UR7IZHjUfUNcZo6sLTl0YNrzz8z9B//hWaOs/MEpCABFqVgBakVu1Z2yUBCUhAAhKQgAQkIAEJNE1AgdQ0Mk+QgAQkIAEJSEACEpCABFqVgAKpVXvWdklAAhKQgAQkIAEJSEACTRNQIDWNzBMkIAEJSEACEpCABCQggVYloEBq1Z61XRKQgAQkIAEJSEACEpBA0wQUSE0j8wQJSEACEpCABCQgAQlIoFUJKJBatWdtlwQkIAEJSEACEpCABCTQNAEFUtPIPEECEpCABCQgAQlIQAISaFUCCqRW7VnbJQEJSEACEpCABCQgAQk0TUCB1DQyT5CABCQgAQlIQAISkIAEWpWAAqlVe9Z2SUACEpCABCQgAQlIQAJNE1AgNY3MEyQgAQlIQAISkIAEJCCBViWgQGrVnrVdEpCABCQgAQlIQAISkEDTBBRITSPzBAlIQAISkIAEJCABCUigVQkokFq1Z22XBCQgAQlIQAISkIAEJNA0AQVS08g8QQISkIAEJCABCUhAAhJoVQIKpFbtWdslAQlIQAISkIAEJCABCTRNQIHUNDJPkIAEJCABCUhAAhKQgARalYACqVV71nb1CgL/+Mc/wvPPP99QXV966aVw2WWXpbw//fRTOOecc8JHH33U0LnDO9Mvv/wSzj///PDVV18Nc+nXXnstXHzxxeGuu+4K33//ffn4q6++Gi699NLy50Y2uA4c3n///Uay183z888/hx9//LFuvs5k+Pbbb2uezvXhc+ihh4Z77723Zl4O3nLLLeGhhx5K+YpjpNaJb7/9dhpL//rXv8I333xTK2s69vXXX6frXHnllYFzTRKQgAQkIIFWJqBAauXetW09ngAC6bnnnmuonkx+L7/88pQXgXTuueeGjz/+uKFzh3emU089NZx11lnDTL4POuigsPPOO6dJ9t///vewww47hC+//DJV75VXXgmXXHJJU1X99ddfwwUXXBA++OCDps6rlhkRsMkmm3Sr6DzhhBPCVVddVe3y5X3nnXdeuOiii8LYY4+dXuUD7WzceuutbQRSHiPtZA8XXnhh2GijjZIwv+KKK8K2224bvvjii/ayhzfeeCOsttpqqd7PPvts2HzzzcODDz7Ybn4PSEACEpCABHo7gQG9vQHWXwIS6DkEsGgdd9xx4fHHHx+mUs8880yyGmElmmyyyQIib4011gg333xzWHfddYfJ38iOkUceOZXZSN56eRBI77zzTr1snTqOtXCxxRarWQYWtsUXXzwJyZoZO3AQ6w/C+i9/+UuYa665wpAhQ8If//jHJLx5r5aOPPLIsOqqq4addtop9OvXL1kGTzzxxGSB4rNJAhKQgAQk0GoEFEit1qO2p1sJ/Pe//w033HBDYLI/3XTThSWWWCLMMsss6Zq4e11//fXh4YcfDmzPPffcYa211goDBgz9mnHs9ttvD999911YeeWVh6krVpSrr746fPjhh2HaaacNG2ywQZhwwgmHyVe5A7GB+9OLL74YcOGaeuqpk+iYdNJJU1YsVVNNNVWytPznP/8JE000UVh//fXThBfBggVhySWXTO3JZd9///3hnnvuSXUh/9JLLx0WXHDBfLjq+1FHHRVGGmmkcPTRR4dddtmlTR7awX7EEQkuAwcODJ9//nmbfE888US45pprQqlUGqZObTLGD0zwjz/++NTWKaaYIm1jHbnuuuvCyy+/HKaccsqw8cYblxkigmjvCy+8kKwz8803X+qHH374IWDRImH5WmWVVcKoo44ann766TD55JMHrDTLLbdcmGCCCQJctttuu5SXPzBCWNFXpPbGCO6R9Ctuc/37909WnHRC4c8ZZ5wRGANYj2C1/fbbh1NOOSVsuOGGgfaRsBoicqgD+ZpJjD/agzgi0QfLL798YlJNIH322WeJ1T777JPGCucwbmGE2Jt11lnZZZKABCQgAQm0FIGhM7eWapaNkUDXE2C9zO67757WqGD5ePfdd5N7Eu5QTDq5037fffelu+2jjz56WkeCKxJ327nTzva+++4blllmmfCb3/wm5S+u0XnsscfCnnvumSwMCK8bb7wxuXyxlqeeSNptt92SMOJOP2IJofbAAw+kiS+TcSbGrGuZccYZA6KA40899VQSM4geJtoHHnhgageCD5F2+umnp0k/Qo927bHHHoEJ/KBBg9qFu/fee4dJJpkkvPXWW8PkQRhlccR6o5tuuim51yE8ckLAUI/f//734dNPP03rcJikIzSrJUQUgnWppZYKiEG2addss80WFl100YAwfPLJJ5MbHuezrgfmcMK1D1dABM0666yT2Nxxxx1h+umnD+OPP34Sm7irjTnmmKk81gbRrn//+99tBBKuj1jMEEi1xgiidbTRRkviFPFbLc0wwwxhrLHGSkIMzght2rTiiiuWBRL1Z98WW2zRtEDCFTELrXx9xi6scVdkrBQTgo5EnpwQiaOMMkoSavUEEmORPu1som6m7iXwVeynX+J3ra8lvmMk1uIV10T2NQ6NtpebUvwWcpPPVJsArEj8r6n8ba19Zt88yhpgWHW3ZwI3BscZZ5y6kBVIdRGZQQL/I8CkFEsLlgBcu0j8AD766KNhpplmSlYGRBITcxLCY+utt04WA1ymTj755GQ12GyzzdJxRBBWnJywFCywwALhoIMOSruYxLPegzU2u+66a842zDs/KOONN15AJOWJN5NxBA2Tfyb7JCbnRxxxRLIaIGL222+/tAYIcUBCSGDdQCDRTtYHUQcS1iOsKqyXqiWQKLde+uSTT5JlJFvRsGzlxGQFEZktVVhxsJYgSLFMNZKwhG255ZYpKxywZCEAEJmsodlmm22S4CADx5l8M+FHZCEAOZ/9WOPgh8tgthJimaqVao0RWBJQAnHcnpsddUAYY50kfyMBFGrVp/IYggerXTEhjmGQx1HxGIKKPuBVTJxTa91Szku5iCRTzycwJE5Ofu7DfcVvTxZLPb+3RmwNvWHRHP8slJo7q2/mRiT1lKRA6ik9YT16PAFcn+aYY46yOKLCWbgwcUY0zTPPPOV2MBHOlgisNlicise5K5/FAZNIrCrcncdykxN3nbBQ1ErcCTnkkEOSaxZWGdaZYEUhFSOyYT3K7n7ZIoAgy2ncccctu7thnUBU3H333clqQt0oK092EQLFyfvqq6+eBFguq9Y77nq4rFEmFp39998/HHPMMekUJuJYrHKCG1Yc1jYhrHCNywmWWRDmfbwXBdzEE0+cDuFCR8KdDJc8ro8IQ6ggRtpL9Cnit9FUa4xUlkEfVbanmWtVllf5uVof0Z7Kf9b58xhjjFFZRBrT+XjxIBPJavmLedimP7ObZ+WxZj4z9hoRZM2Uad62BMaPN1n6/Z9Lbtsjrf2JGzVYZfkdxfJvqk0AVvyOyKo2J47CivHFPICbcKbaBHC35+Yb46snJAVST+gF69ArCPDlzRPuygrjRoRrVPGfBmZiLDvcbeNHEnewyjuU2SrCuiGOc37RvIxA4AejVmLyiNWFdVGzzz57euHGh7WkmKqZlHEfq5aIboZQw92MMrF2FaPt3XbbbW0i6CE8sFA1kxBsa6+9djj22GOTeyDnUseitQJ+JIQZa15wDcyJY9UEUrEPslsDbEk77rhjEqmsGyKa3Jlnnplc46qtvyE/fZrL4DMpl/W/T/+zIubtWmMk58nv1drTnkAqXrOaYMllFt+r9RFWtDfffLOYLf0Th2WRe85AfsYs47coiPjHn90lc95q78WxXO14o/u6qpxGr9cn88Xfq77Oua+3v5FxD6P8aiR/X86Tx5O8GhsFmVPm1thZ3ZdLgdR9bC25xQhgdXn99dfbtAp3OwQKE3XucGNByJNcLDBEJCNoAJYh7iKxFihbSMjPcRITVCagTEhxAcuJ/Nnqk/dVvuMWx/olLC3ZxQ0BQCpOrCvPa+8z7TnttNOSG1xe+8MkGWtPLu+kk05q7/R291O/vCYrZ0IYIiDzDyIBCBCbWRQ+8sgjSaAwGV9vvfXSK5/LezPmeKxIBMhYeOGFwyKLLJKue14MqY0LI26PuQ7F8iu3uQtYuU6hGGK81hghhHgxVWtP8Tjb+U5a8ZrF61XmL36u1kdYy3huEiIrjyuEb+W6pFwOQS7IRx7EOgmrF32WrZA5r+8SkIAEJCCBViHQdkVuq7TKdkigGwgQvYuoZkz0mbAihgigwPoU3LUQJ0T3IqIZE30sMLitzTnnnKk2K6ywQlrgT5Q2RADrUYqJdTa4fhEQAUHCmiCih7E2pFZCfJE/uyCxzgTLCAmx02zCqoUlB2sIE2GEBWGhO/sQ1cGDBwfajhWICTouZgRRYH/ROoFo4TgWMNbjwL2adaPZdlEG0fHoF/jDhjVGuPxxLK/NwaWx6D5YvA4ukVhTCE1OHekrotrlVGuMkAeuWHAQz40k6kX94MB1eSAuY66jibVkJAJ20LcIftwyEfE5cSxbC6nvsssum9aBwYSxwBjHYki9TBKQgAQkIIFWJKAFqRV71TZ1C4GZZ545rZfhzjwhobH6YGHJAQUIy0wQBKKZcdcd9zSEBVYhEgEbEDsET2Byyh15yswJKwaTYNbkIFKwOGFlwL2tVsIitdJKK6Xn1ODmxrUJAU1wAURcrTU21crlfB4eioC79tprkzBCvBFAgPI6mhCQPEuHYBUwxG0OV8C8jotyESAIMybgCBjaTqjrrkhYiAjYgECiPYhKLFOHHXZYKh53Q9ZksZ6LwBXVuBG1jQh7hDPnhZsgIbix9JHqjRHWPDEmEIdECmwkEXzj8MMPDwhs6gjDXOdGzi/mQXBhCTz44IOTSMIdcc0110xWtZwPPrgc5gh1bJM/hz5H8P/pT3/K2X2XgAQkIAEJtByBftFl5n/O+S3XNBskge4hwFeGgAHcQa/mlsX6DPZnN7HKWjDxxwKFdalawjLRzFqWXEYOkZkFWd7fmXcsYQg1RFNXJdqHlQvLV3G9ULF8GLL2hzVA3ZEQovQDIrcycQwhkdeHVR7nM5YU8sGmWqo1RugnxFkza7YQ1HnMVa6Jqnb9RvYR+IIx3Gh59AlM2lu31sg1O5qHvuI7Mfnk/3uGVkfL8bzqBKYvjRpeefifof/8K1TP0MJ7cfNlbGMtLVqyW7jJnWoarAzS0BhCWDG++F9nkIb6zPiNN0hDfU7mkECPJYD4aS9YA5XOrlrtNYDJN6/2EmKkVvntncc/ra4UR1ynI/Vor355P+1jbUutVI9hrXMbOcZEqL3JUHv7i+UibmoJnFpjhH7Ka4uKZdbaRsTk9WW18jVzrNnyurtPmqm7eSUgAQlIQALdScA1SN1J17IlIAEJSEACEpCABCQggV5FQIHUq7rLykpAAhKQgAQkIAEJSEAC3UlAgdSddC1bAhKQgAQkIAEJSEACEuhVBBRIvaq7rKwEJCABCUhAAhKQgAQk0J0EFEjdSdeyJSABCUhAAhKQgAQkIIFeRUCB1Ku6y8pKQAISkIAEJCABCUhAAt1JQIHUnXQtWwISkIAEJCABCUhAAhLoVQQUSL2qu6ysBCQgAQlIQAISkIAEJNCdBBRI3UnXsiUgAQlIQAISkIAEJCCBXkVAgdSrusvKSkACEpCABCQgAQlIQALdSUCB1J10LVsCEpCABCQgAQlIQAIS6FUEFEi9qrusrAQkIAEJSEACEpCABCTQnQQUSN1J17IlIAEJSEACEpCABCQggV5FQIHUq7rLykpAAhKQgAQkIAEJSEAC3UlAgdSddC1bAhKQgAQkIAEJSEACEuhVBBRIvaq7rKwEJCABCUhAAhKQgAQk0J0EBnRn4ZYtAQlIQAIS6CoCX375VRg4cGBXFdey5Xz33Xfhl19+CWOPPXaDbfwxhPkbzGo2CUhAAn2AgBakPtDJNlECEpCABCQgAQlIQAISaIyAAqkxTuaSgAQkIAEJSEACEpCABPoAAQVSH+hkmygBCUhAAhKQgAQkIAEJNEZAgdQYJ3NJQAISkIAEJCABCUhAAn2AgAKpD3SyTZSABCQgAQlIQAISkIAEGiOgQGqMk7kkIAEJSEACEpCABCQggT5AQIHUBzrZJkpAAhKQgAQkIAEJSEACjRHoV4qpsazmkoAEJCABCQx/Ar/++mv4+eefw0gjjRQGDPDxffV6gGcg8a9dVvVIhfS8qCFDhiRWjC9TbQKw6tevX/ou1s7pUVjxXRx55JFD//7aI+qNiPwb31NYKZDq9ZjHJSABCUhAAhKQgAQkIIE+Q0BJ22e62oZKQAISkIAEJCABCUhAAvUIKJDqEfK4BCQgAQlIQAISkIAEJNBnCCiQ+kxX21AJSEACEpCABCQgAQlIoB4BBVI9Qh6XgAQkIAEJSEACEpCABPoMAQVSn+lqGyoBCUhAAhKQgAQkIAEJ1COgQKpHyOMSkIAEJCABCUhAAhKQQJ8hoEDqM11tQyUgAQlIQAISkIAEJCCBegRGOiimepk8LgEJSEACEhgRBHjQ4hNPPBFuv/328NNPP4UppphiRFTDa/ZgAvfcc0/4/PPPw2STTdamll9//XW488470/gZe+yxwzjjjNPmeL2xVe84hb399tvh5ptvDu+//36YZJJJwiijjNLmGn7onQToz5tuuim8+OKLYdxxxw2Mn2KqN7bqHa83tuodL9bF7e4hoEDqHq6WKgEJSEACnSTAJOGPf/xjuP7668N4440XLrroovDhhx+GhRZaqJMle3qrEHjyySfDXnvtFaaeeuowxxxzlJv1xhtvhPXWWy988MEH4Ycffgh/+9vfwswzzxymnHLKlKfe2Kp3nEIuvPDCcMABB4QxxxwzPPjgg+Haa68NSyyxRBh99NHL9XCj9xGgT0855ZQw1lhjhUceeSSce+65aexMNdVUqTH1xla94/XGVr3jvY9oL61xySQBCUhAAhLogQQuueSS0rrrrlv65ptvUu3efPPN0mKLLVaKd3V7YG2t0vAk8PPPP5fOOeecUhQkpcGDB5eieG5z+a222qp04oknln799de0/7zzziutvfba5c/1xla942+99Va6drRupvKpzxZbbFE67bTT2tTDD72LAL8tiy++eOmjjz4qVzw6WqXfobyj3tiqd7ze2Kp3PNfD9+4l4BqkXipsrbYEJCCBVidw3333hWWWWSbdoaet00wzTZhtttnCv//971Zvuu2rQwD3pxtvvDEcccQRId/Zz6d89tln4YUXXgirrbZa6NevX9q98sorJze4559/Pn2uN7bqHX/44YfD5JNPHuaaa65U3oABA8Lyyy/v2Myd0Evfv/jiixCFbph44onLLZh77rmT5TpOx0O9sVXvOIXWG1v1jpcr5ka3ElAgdSteC5eABCQggY4SwD2KSWgx8fnjjz8u7nK7DxJYZJFFwmWXXRYWXHDBYVqPGyapOHYmmGCCtD4oj516Y6uR45Xr4bjep59+GqLVapg6uaN3EGA8bbzxxm0qy/rHQYMGJbFdb2zVO07BjYyt4tjlHH/3oDB8kwJp+PL2ahKQgAQk0ACBIUOGpMnmwIED2+TmMwvyTX2bAIIHq021xAR01FFHTa/icRbaYyGoN7bqHadMJsKVY5PyEUdffvll8bJu92ICl19+eXjqqafCTjvtlFpRb2zVO15vbNU73otR9rqqV/916XXNsMISkIAEJNBKBEYaaaTQv3//NJkttosJBIviTRJoj8DII488zLghL4vfxxhjjFBvbNU7TlnVrsHYJHENU+8nENe4hYsvvjgcfvjhYZZZZkkNqtbvHMhjq97xemOr3vHeT7X3tEALUu/pK2sqAQlIoM8QYO3I+OOPHwiXW0xfffVVmHTSSYu73JZAGwITTjhhmrB+9913bfYzdggFXm9s1TtOoVyj2tgk2iLWK1PvJYAV8Nhjjw1Yj4477riAO2dO9cZWveP1xla947kevnc/AQVS9zP2ChKQgAQk0AEC008/fXjuuefanMki+8q1H20y+KHPEyCUN+53xbFD0AYmvnltR72xVe/4dNNNl56Rk61GQOd6js3eP/wOPfTQ8MADD4QYkTAQoKGY6o2tescpq97Yqne8WB+3u4+AAqn72FqyBCQgAQl0gsBaa60VbrvttoAoIoLUP/7xj/Sw2BVXXLETpXpqqxPggbDLLrtsen5NDBGfnoN01llnpShzE000UWp+vbFV7/jSSy+dysEFC+H1+uuvpweLbrTRRq2Ot6Xbx0N/+c3ZdNNNk4WQ9Uf5hRtdvbFV7zjw6o2tesdbugN6UOP6EUW8B9XHqkhAAhKQgATKBFgHwAM58e3n7vz2228f5p133vJxNyRA1LHlllsubLDBBmUYBGM4+OCD0+QWl7c555wz7Lfffm0CK9QbW/WOx2cgpWvgysfDYQkrvvnmm5fr4EbvI0CI75dffrlqxW+99da0vqze2Kp3nMLrja16x6tW0J1dSkCB1KU4LUwCEpCABLqawE8//RRYP4J/v0kCzRBg3LDwvb3AHvXGVr3j1CU+VDRgmSKoiKnvEKg3tuodrze26h3vO6RHTEsVSCOGu1eVgAQkIAEJSEACEpCABHogAW939MBOsUoSkIAEJCABCUhAAhKQwIghoEAaMdy9qgQkIAEJSEACEpCABCTQAwkokHpgp1glCUhAAhKQgAQkIAEJSGDEEFAgjRjuXlUCEpCABCQgAQlIQAIS6IEEFEg9sFOskgQkIAEJSEACEpCABCQwYggMGDGX9aoSkIAEJCABCfRFAjxw8913303PDpp44omrIvj666/D559/HiaddNLAc4yGV/rggw/SpSabbLLhdckOX4fHWD733HPhtddeCzPPPHMYNGjQMGV9+umn4dtvv037p5lmmmGO5x2EpOb5PQMGDEjPG8v7fZdAXyWgBamv9rztloAEJCABCYwAAjw3aNpppw3TTz99mtxXq8J5552X8jzyyCPVDnfbvlVWWSWsuOKK3VZ+VxX8888/h//3//5fmH322cPqq68ejj/++KpF77LLLokjvJ9++umqedi55ZZbpnwLLbRQu3lqHXjmmWfCWWedVStLp4/R5mOOOSZ88sknnS7LAiRQj4ACqR4hj0tAAhKQgAQk0OUEsGxsvvnmAUuIqTkCt912W7j33nvDBhtsEJ588slw6KGH1iygX79+4Yorrqia55tvvgk33HBD1WON7pxnnnnCQw891Gj2DuU79thjw1577RV4gKpJAt1NQIHU3YQtXwISkIAEJCCBYQiMNtpo4Z577gl//etfhznmjtoE3nvvvZRh6623DnPOOWeo5xKIZejKK6+sWuh1110XcHucccYZqx5vZOeQIUMaydapPMPjGp2qoCe3FAHXILVUd9oYCUhAAhKQQO8gsPHGG4c77rgj7LPPPsmtrdYE/fnnnw+XX3552GijjdpM5N95553k2oWb2dxzz50afsYZZ4Txxx8/LLroouGCCy4Ijz/+eBIRG264YZhqqqnCAw88kMTCDz/8ENZff/2wyCKLBCwsxYQAOe2008LLL7+c3Ng23XTTdG4xD9u4lmGZeeGFF8LUU08dVl555bDkkkuWs7344ovh0ksvDTvssEM4/fTTw5tvvhnWXnvtsNxyy5XzVG58//33qU2PPvpoEi4IoK222iqMO+64Kespp5wSbrrpprR90UUXhdtvvz3st99+YZRRRqksqvx5nXXWCTvttFN46qmnEovygbhB/ZZffvnA+qsPP/ywfKgR5pNPPnk49dRTkxXwscceCwceeGBy14MziXpi6XrllVdS/WedddbUlrHGGqt8HfprvPHGC0sssUTAtZJ2I/j+8Ic/hIUXXjjlo+8ZK6Tjjjsu9TXj59dffw3XXHNNuOWWW9KaNdZi4SK52GKLpbz+kUCHCUTTtkkCEpCABCQgAQkMFwJRfOBTV9p5551LcfJc6t+/fymKmVK0YpSvf/LJJ6c8HCddddVV6fPNN99czsPGfffdl/afc8455f3zzTdfKYqe0nTTTVeK65xKcZ1OyhMn5yXyxUAEpSim0nHqEcVL+dzoKlaaZJJJSjE4ROl3v/td6fe//30pTt5LE0wwQek///lPOR8bUfCUoihJr7h2KeWnvN13372c75///Ge6dpzsp3faus0225SPV27AJq4XSmUus8wypSi4SmOOOWZpiimmKEXhkLJvttlmpSgEUnnzzjtvafDgwaXvvvuusqj0OYrClC8KydTufffdt02+GAgjXeuSSy4pwS0Km/LxRpi//vrr6fq0O4qatP3ss8+mMqL4TNemrmuuuWZiSr6ZZpqp9OOPP5avw3Xp/1lmmaU09thjl+LaqtTmkUYaKfU7Gf/85z8nLpwfRVNpjz32SOfvuOOOpShuUx+vtdZapSjY0ucTTjihXL4bEugIAVS/SQISkIAEJCABCQwXAkWBxAVjIIE0kT7xxBPL1++sQKoUKvvvv3+6BhPwGPghXSeuZSkhiBAgOfGZc3fbbbe8q/TWW2+lyf1cc81VihaLtD9aRJKwiFaPUgwaUM4bLTnp/LhGKO3LAmnCCScsxYhzJQRJtNKU81duREtOafTRRy/F9TzlQy+99FISbbPNNlspBipI+6N1K10nWm3K+aptZIEUrVIlykacFFMMrJDaH9chdUgg5bIQKTHQQ/5YitaeVL8999yzvA922267bdof3frK+xFIMEf0ZKEXLXelaGUqRdfAcr6DDz445YsRENO+GHmvhIjabrvtynkQ2QhiRG50ySvvd0MCzRJwDVL8VpokIAEJSED3yWUMAAAbrElEQVQCEhgxBA4//PAQJ+4hWjeSK1ZX1AKXuWLgghyZbt111w3R6pIuMfLIIyf3OoJFfPbZZ+XL4p5XPBfXuWipSMEQcNcj4VZGsIC99947RPFTPjcKq0C5uMEVEy5yv/3tb5MrWZy8Fw+Vtwl9jqsYeeeff/7yftzGCE4QLTPh7rvvLu9vdgM3O1zdCOqQ02WXXRaI3BdFYt7VJe/ReheiVSq5/uUC6ZNoSUofKyPREcr9sMMOS6HfycB4wLUwitN8etX3aJFLoc5zeHY+wwhXxiieqp7jTgk0QkCB1Agl80hAAhKQgAQk0C0EosUknHvuuSG6XYXoPpbWlXT2QqyNIQhEThNNNFHarHwW0DjjjJP2E6QgJ9bJUKdiitaj9DFac8rvTPhZP8OaovyK7nNhjDHGSGuXiucjcuol1jGRiuIon7PAAgukTdY0dTSxTot1SjlYw8cffxzuvPPOsN5663W0yHbPi26CqVx4sfaK9U/LLrtsWSBVRqJjzVLlGiqekcV6rPZStAYGwpgjiKILYhK+BxxwQIhuf236vr3z3S+BWgQUSLXoeEwCEpCABCQggW4nQKCEuCYp3H///eGkk05q+HpFYVM8Ka4ZKn4sb/Mg1GKKbjfFj2l74MCBw+zLQQUI7EDiAaxYPSgPq0XxRcCDBRdcsE0Z7dWnmClbsWpdn2cBdTQR5IHgEDncN0IJkUF9m0ntMS+WwYNnF1988ST2dt1118DzrAjCEddnFbOVtxGVlQkBWq1/ivmOPvroFAiCYBtvv/12skJhIdxkk02CUe+KpNxulkDbX4pmzza/BCQgAQlIQAIS6AICuFjxPJ64Xig9H6lYZHaXqhQITIq7IhUn4sVIbrns7Oo1wwwzpF085Pbhhx8OhxxySKi0DjExrxRiuZxa77ls3MMqU96XLVmVxxv9jJsd0fyIZodQikEohrHc5LI6w5yoekSvO/PMM5NYwe2QFAM/pPci77Sjg38Qa1imVlhhhSSmiICHCCN6IVHullpqqQ6W7Gl9nYAWpL4+Amy/BCQgAQlIoAcQKLraEWK7mHKI6+yGlo/l0M/5c1e8P/HEE+G1115rU9T555+fwlRngYLFi8REvJiefvrpgLUJl7Jm06BBg9IaJUJdVwqIGH0vFZev32zZOf+qq66a3M/+9re/hRgBsKZ7XTPMEVNFtzksRliFsORkcUQdbrzxxlSVjlh3smDL12EtFWunYnCPVCYWpxjwIYVUZ0c1oZsy+kcCDRDQgtQAJLNIQAISkIAEJND9BHjuDetKjj/++DYXY10OE3YCOvDMHKwtV199dbI4tcnYBR+YiOOKhqvflFNOmQIuxKh0IYaODnnNEmuNCNRAHtY3Lb300skqgxUMgYQVrNnEeZy//fbbp7U6MQJcsu6wzunaa68NRxxxRPlZSM2WnfPjUoe15eyzzw4Eixg8eHA+NMx7M8zpE9YzwYSgDwi5GIkvPeMKVrgPXnjhhemZS1zoyy+/HOZ69XZwDdKRRx6ZnnXEmiosREcddVQKyMDzp3h2E5xgSTtNEugoAS1IHSXneRKQgAQkIAEJdDkBREJ8Jk6bcrFG4J7F+pytt946TYyZgCNcujqxJmeNNdZIIoWHzxLpDSGEcMsJqwjBAYiOh0tXDMEdNthgg7TuhQev5qAQOX+j7zFkdcBaxFosxCLrae66664kznigblck3OywUPEg1myVqVZuM8wRhIggxB0PrkWkxLDfSRThgshDe3GHJMgED4FFTDWbqC/CC7c91quRsB6xtol1ThyjD3BvfPDBB9PDgpu9hvklkAn0i1+SYVco5qO+S0ACEpCABCQggR5EgPU4WAiK4bW7o3rxmTwhPmA1TcBrCQlcvl599dVkXSJ6Hq5eXZG4NtelzBGdGmHOeqD4nKfUL5lBfPZRiuhH9MDKyIAdbdMXX3yR3ASL5RE0g1Df08boeVjJTBLoLAEFUmcJer4EJCABCUhAAhKQgAQk0DIEdLFrma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhoEBqma60IRKQgAQkIAEJSEACEpBAZwkokDpL0PMlIAEJSEACEpCABCQggZYhMKBlWmJDJCABCUhAAhKQwAgkMKTfaMPl6gNKPwyX6xQv8uspYxQ/dtt2/+2/67ay2y94rPYPdfmRb7q8xHoFzhBGrZelS46/Fn7sknKaKaRfv2ZyN55XC1LjrMwpAQlIQAISkIAEJCABCbQ4AQVSi3ewzZOABCQgAQlIQAISkIAEGiegQGqclTklIAEJSEACEpCABCQggRYnoEBq8Q62eRKQgAQkIAEJSEACEpBA4wQUSI2zMqcEJCABCUhAAhKQgAQk0OIEFEgt3sE2TwIS6NsEPvvss/DWW2+Fn376qV0Q77zzTvjoo4/aPd4dB77//vtUL957Q/rvf/8bbr311nD77beH777rXJStH374IbW9I+W8//774cMPPxxuyHpbP3UFmB9//DH1z7ffftsVxVmGBCTQCwkokHphp1llCUhAAo0S2GeffcK0004bdtxxx3ZPmWuuucIGG2zQ7vHuOIDQoF7/+te/uqP4Li3zxhtvDBNMMEFYfvnlw9JLLx0+//zzquU/88wz4ayzzqp6rLjzrrvuSm2/6aabirsb2l5uueXC6quv3lDersjUm/qpK9pLGY8++mjqn6uuuqqrirQcCUiglxFQIPWyDrO6EpCABDpC4Iwzzgi33XZbR07t8+cccsghYbTRRgsIJUTQlFNOWZXJPPPMEx566KGqx4o7J5xwwrDMMsuESSaZpLjbbQl0O4FrrrkmINBbLb3xxhvhxBNPDH/9618D262UPv3008Dv99///vfw5ptvtlLT2rTl5JNPDk8//XSbfSPygwJpRNL32hKQgASGE4FRRx01bLHFFuHrr78eTldsncu89957YYEFFggrrrhimG222dpt2JAhQ9o9Vjww77zzJsvZYostVtzttgS6lcA999wT1llnnfDwww9363WGd+F/+MMfwpxzzhkef/zxcO6554bf/va3oSPW2eFd70aud8UVV4Rpppkm3HLLLQGLJu3EqttqCcv7TjvtFJ566qke07QBPaYmVkQCEpCABLqNwKGHHhr22GOPsNtuu6W7kbUudMopp4RRRhklbLXVVm2yXXDBBYG7mbvuumvaz13N8ccfPyy66KKBY0xQ+Ae+4YYbhqmmmio88MAD4corrwysuVl//fXDIossEvr1G/ax55dffnm4+eabk5VmqaWWCkx4KhOWGyYLL7zwQph66qnDyiuvHJZccsk22U477bQw8cQTp2vThkGDBiVRONFEE7XJlz+wvoZ/zLhU/fLLL6nutHncccdNWZ5//vlA3Vh/hEg68MADw8ILLxxwcysm1m+deuqpoVQqhcceeyzl23LLLQNrWC699NKwww47hNNPPz3d/V177bXDDDPMEC688MI0WWUylxOTunvvvTe88sorqQ6zzjpr6oOxxhorZxnm/ddffw1YBZhA4fo388wzJyHXiPiq1/7Ki9XrJ9aywRNu44wzTph99tkT/8r6IySZyDJRZx3W3HPPndrJOTlV60vcHOmH/fffPwwY0Hb6wt111g4VXUkbGTNcD+ZYBz/44IPA+Jt++ulzNVri/eeffw5HHnlkOOKII6p+/3pzI/nNYfxjWcmWXX5rdt555/Q96M1tY93o3nvvHfjtzr+5m2++eRr/jNNWSa+++mrYd999AzfxelSKP+gmCUhAAhJoUQJxwl+K/3RKX3zxRWnZZZdN2zHYQJvWRpFTiv9wy/uilaQULSblz3kjrr8pRXGSP5bmm2++UhQ9pemmm64UJ5WlOCFO5ceJfemcc84pxUlsKU5+03HqEIVC+dzrr78+5Y3rn0oDBw4srbnmmqX5558/7Yvrocr52IjiohQFW3qtssoqpd/97ncp3+67794mH2UNHjy4FAVRqX///un17rvvtsmTP8SJdimugUplRne3UhRcpTHHHLM0xRRTlKJgStnuvvvuVB7XjpPztB0n7rmI8vvrr7+ejtHGySabLG0/++yzpX/+85+pnlHwpXfqtM0225SiGEyfo3gslxEndWlfFDiJxaSTTpo+zzTTTKU48S/nq+ybKAhKUXQm9muttVZp8sknT59POOGE8jnVNhppP+c12k9R1CVGUVyWoqWtFAVa6v8oBktRVJer8PHHH5eiBa3c1rieqsQ58S556bnnnivnq9aXxx13XDrvhhtuKOdjIwrUdK0//elP5f2NjpljjjkmlRmFfeJOP+fxdd5555XLa3Tj5zBqaXi8Gq0P+eKNjMSXccf4Ofroo5s5vZz3l7+NXhoer/IFG9iINxVKhx9+eJuctJfvbLx50GZ/7Q9jxsPD61W7JvlovMFSiuKv9NVXX+VdpSiY0u9WeUeDG9OXRikNj1eD1Slni+I9/a+J7nXp9yPeOCofa3Qj/uzG73A3vBqtgPkkIAEJSKD3EcgCKVpBSm+//XYSI9G6U/ryyy/LjemMQEIUFIVKvLufJpxjjz126ZFHHknXiHdCS3F9ThIg+aJ54h0tPqV4BzHvLsWgEul8JgYkJt5MdpZYYonSJ598Us633377pXxxXVV5H5Nq6hPvtpaiZaL04osvlo9VbsSAC6XRRx+9FNcMlQ+99NJLpbguKE0i+cedE/sQZvUSQiVajsrZskCKa47S5D9aeEoxAt0wAumOO+5I9d5zzz3L5zK523bbbdP+6667rry/KJCYOI000kil7bbbrnw8WsKSWKLO0VJT3l+50Wj7G+2naJ1M/RStSOVLRYtfqn9cF1LeF++Ap31XX311eV+MspiEJaIqp2p9Gd1D0xhad911c7b0ftJJJ6UyozUhfW50zESXszK/PJmOUQKT2GcctYpAipaxEt9BUqsJpNSoij/Rspxu3FTsrvNxeIkjrtN8og8Zj9xMimutmi5geIgjrtFs+vOf/1ziBhXfP25O9CSB5Bqk+CtokoAEJNAXCOD2Fi0LAVcoXO26IuEyhwtITqzTIcVJbGCtDWnkkUdO7nW4nBF2vJhwHcHlLKcDDjgguZedffbZaReua9nVhOAGOVF/ysWVrpiilSbEO8ohip8wyyyzFA+Vt6NVKbmk4U4XrVbl/bin7bXXXiFaf0K0HpX3d3aD6+BKN95441UNzBAtcOGSSy4JUfSVLwXXaFVLn6MwLO+v3KC90fKS3MM4xmfqjstRFE+V2dPnjrS/Xj9xXfrpvvvuS+6KXAhXSdzWcDEk4aqIa91CCy0U1lhjjbSPP7hM4haFq1txkXZlX+KqR5lRMLZZS4e7Iq6duOqRGh0zUcAmRoxfeJOiBTC5NaUPLfInWiPTd6VFmlOzGQRqYK3VX/7yl5r5ettBooxuvfXWIVqIh2sUy+7khAs2rrT8JuTvX3der9my2zrxNnu2+SUgAQlIoFcRIFAD64JYKxJdsoZZT9NsY/iHTYS3nPJ6HxYWF1NeX8Jan2KKbnrFj0nYIFSiNSft551/nqx3os7FNMYYY4SXX365uCutPyrWp83B//vAOiZSURz936EUjIHtaH1K61Hy/s68055aadoY7pxXtLilNUzUj9eDDz6YTkN4VEvRShd22WWXEN3EQnQNDNE1LKywwgppAkVEvfZSR9pfr58YVxdddFFYb731wvbbb5+i9K200kphtdVWK1eDtVXxDnOIlq/AWqxiQrSR6M855pgjbSPoK/tys802C/FOelp3svHGG6f1Tqz7ilakdA5/Gh0zLAhn3Qrr6IqpFrtiPrd7FoGDDz44RPfBEK2TodX6kMAMrP9k/R1rE6M3QHr0QM/qgcZr880336S1qkSu47erJyYtSD2xV6yTBCQggW4kgNBAsBBIILraNXylSnHDiSycr5YqF9EzMa6WosvIMLuxFOQHyDIpYPEu5WFRKL54LtGCCy7Y5vz26lPMlK1Y7V2bvCxs76pUr04IhsUXXzwJNiw1CKUZZ5wxRNfFulVgQkhwBywwTJoOO+ywZLnbZJNNQntR9TrS/vZY5X6Ka6WSuOP6bCPCETBs33///akd9CUJ616xH9nGikSENURfTtW4wQk2iDES1iMsicXneDU6ZuBQGUCCMisFE/tMPZdAdM8KcW1fso4T7CW6w/bcynaiZljQsY7zve7tUfq44cVDr7Gcr7rqqunF7yAeDgQT6glJC1JP6AXrIAEJSGA4EuCuOf+IuOvPhLwy4ZpVTSAwAe9sqhRKcU3OMEXGNSlpEswBIooR7YxnEVVaYpgoVAqxYQqrsiO79OGGVpnyvrgGpvJQt33GtQ73sjPPPDMgbJjwk/KDSiuZFSuCaI3BN5LliHxE5ENYEVUQgVIt2lVH2l+vn6gTLoS0hRcR9RBJcX1UclmjfTk6HP148cUXF5uR3PLacwlskzF+2HTTTVOkwBjwIU2wmBAX3S8bHTP0MW52lYmJm6n3ENhoo42SWx1CPK6x6j0Vr1NTLL3cBLrzzjvL3x3clPndQxT25sRjE4ouxbSF5/Tx3S1G9hyRbdSCNCLpe20JSEACI4gA4WL55xujzaW1IcVqEOYakUII5pxipLa0L3/uqncm0cXEGpbXXnstDB48OO0mNDiJCX8xsVaFu/88O6PZRPhvJvO4alWKD3iQOiKQmOC35w5Xq45YjHAXLIoj8hN6mtSeJejJJ58MMfJeekAm+XBFxBUur/mpJmrI15H21+snrD+4xDGBI2GF4a7+b37zm5DrweSH9TCEZeZucTFhAcrjrri/2jac6DcmWIh23O6KqdExwySNdVGsaSomwpmbegeB888/P4XSj4v9Q4zUmW40IMZ5VbN4945W/a+WfE+xrBLqG2sna0djIJdktc9rPXtTe4p15TuKu2DxxW9gjGo5zPe5eN7w3NaCNDxpey0JSEACPYgAFgvuuFa62fGcHxb6c2cWCwD/mHHtQFR0deI5QTHiWnKR4nkYMVRzWoicg0gwyWbRPWtMWN8UQ42nhwniyoVA4h9ss4nzOJ+1MgRCYNIRI+WldU7XXnttel4Mk/VmE3y420t9m3HzQYzFaHohRvBLooLJEK5jsCFV9k+uF+dhITrqqKNSsAGeC8UziHjeDW1kPVK11JH21+sn+ovnVPEMLFw3seiwFoT60C4SlrFjjz02jSsmQjxXiknRZZddlp43RYCOyrVr1eqPBTRGvkpr0hBcCP1ianTMcJMASxbvrIUg0AMWJb4Xpt5BgH5DLBPAoDLxUGzGem9OMQJkWtfHWk8EH6IJ97q81rM3t62n112B1NN7yPpJQAIS6CYCTDSJ+sQEsZiwyrBYnkk6k1zWhSBEiEjG565MWGwOOuigNHGmXO4ssr4kT2yYVCPWEDO4jmVrCmtbmLR3dKKA8GMtDFHrePgrCdcvXA8JfNCRBCPEAHVl4t+ooETQMPmB9/HHH5/EDuKGQBHUDdHVnhCk/3Cly66SWJGY6BPgodZammbbX6+fCHiB6ESsZbc11i3xAMhilEMEFGIUxtlKiJskY7C9NlbrC6xG8XleSZBVulk2OmaoB9YsXE0RdaynYiKKVaIyiES1OvTGfTw8t5USATpaOXETBFc7gpgwrrmZ1Kopr1HsKe3rF5V39ZWzPaWG1kMCEpCABEYIAVzscGFCjDS6PqSjFX3jjTcCE+pqC/NzmbivYWUiwAQT2a4KDYuFjPZRZmcTQof1N1hQmq0f6woQplhREG/NJCYXCFii4RUDHTRSRjPtr9dP9BHlkXCpq8UA1zusZdQZV8HuSI2OGcQRa4/y+qyO1mVIv6ERHTtaRiPnDSj90Ei2Ls3z6yljdGl57RXWf/uhrr3t5en6/cPT0vRN11e/TokzhFHr5Oiaw6+FH7umoCZK6devicxNZFUgNQHLrBKQgAQkIAEJSKA9Agqk9sg0vl+B1DirRnMqkBolNTSfQRqGsnBLAhKQgAQkIAEJSEACEujjBBRIfXwA2HwJSEACEpCABCQgAQlIYCgBBdJQFm5JQAISkIAEJCABCUhAAn2cgAKpjw8Amy8BCUhAAhKQgAQkIAEJDCWgQBrKwi0JSEACEpCABCQgAQlIoI8TMIpdHx8ANl8CEpCABCQgAQlIQAISGEpAC9JQFm5JQAISkIAEJCABCUhAAn2cgAKpjw8Amy8BCUhAAhKQgAQkIAEJDCWgQBrKwi0JSEACEpCABCQgAQlIoI8TUCD18QFg8yUgAQlIQAISkIAEJCCBoQQUSENZuCUBCUhAAhKQgAQkIAEJ9HECCqQ+PgBsvgQkIAEJSEACEpCABCQwlIACaSgLtyQgAQlIQAISkIAEJCCBPk5AgdTHB4DNl4AEJCABCUhAAhKQgASGElAgDWXhlgQkIAEJSEACEpCABCTQxwkokPr4ALD5EpCABCQgAQlIQAISkMBQAgqkoSzckoAEJCABCUhAAhKQgAT6OAEFUh8fADZfAhKQgAQkIAEJSEACEhhKQIE0lIVbEpCABCQgAQlIQAISkEAfJ6BA6uMDwOZLQAISkIAEJCABCUhAAkMJKJCGsnBLAhKQgAQkIAEJSEACEujjBBRIfXwA2HwJSEACEpCABCQgAQlIYCgBBdJQFm5JQAISkIAEJCABCUhAAn2cgAKpjw8Amy8BCUhAAhKQgAQkIAEJDCXw/wErUtFoZcbkFgAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# for each model/template/temperature, calculate how often the same mutation was made\n",
    "# prepare to find which mutants are repeated across runs by ensuring that each mutant appears exactly once\n",
    "uniqueMutantsByRun <- mutants %>% group_by(model, template, temperature, project, run, startLine, startColumn, endLine, endColumn, originalCode, replacement) %>%\n",
    "    summarise(repeatPerRun=n()) %>% ungroup()\n",
    "\n",
    "mutantStability <-  uniqueMutantsByRun %>% group_by(model, template, temperature, project, startLine, startColumn, originalCode, replacement) %>% summarise(nOccurrence=n()) %>% ungroup() %>%\n",
    "group_by(model, template, temperature, nOccurrence) %>% summarise(n=n())  %>% mutate(label = paste(model, template, temperature, sep=\"-\")) \n",
    "\n",
    "# stacked bar chart of mutation stability\n",
    "mutantStability %>% select(label,nOccurrence, n) %>%\n",
    "mutate(nOccurrence=as.factor(nOccurrence))%>%\n",
    "ggplot(aes(fill=nOccurrence, y=label, x=n)) +\n",
    "# make the fill be a discrete scale from red (1) to green (5)\n",
    "scale_fill_manual(values = c(\"red\", \"orange\", \"yellow\", \"green\", \"blue\")) +\n",
    "geom_bar(stat=\"identity\") +\n",
    "    theme_minimal() + theme(legend.position = \"bottom\") + \n",
    "        theme_minimal() + theme(legend.position = \"bottom\") + \n",
    "    xlab(\"Number of Mutants\") +\n",
    "    ylab(\"\") +\n",
    "    # set legend title\n",
    "    labs(fill = \"Number of trials observed\") +\n",
    "    theme(legend.position = \"bottom\") \n",
    "    # output PDF\n",
    "    ggsave(\"mutantStability-all.pdf\", width = 9, height = 3, units = \"in\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'run', 'startLine', 'startColumn', 'endLine', 'endColumn',\n",
      "'originalCode'. You can override using the `.groups` argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'startLine', 'startColumn', 'originalCode'. You can override using\n",
      "the `.groups` argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature'. You can\n",
      "override using the `.groups` argument.\n",
      "\u001b[1m\u001b[22mAdding missing grouping variables: `model`, `template`, `temperature`\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# for each model/template/temperature, calculate how often the same mutation was made\n",
    "# prepare to find which mutants are repeated across runs by ensuring that each mutant appears exactly once\n",
    "uniqueMutantsByRun <- mutants %>% \n",
    "filter(model=='codellama-34b-instruct' & (temperature == 'genericsystemprompt-0.0' | temperature=='0.0'))%>%\n",
    "group_by(model, template, temperature, project, run, startLine, startColumn, endLine, endColumn, originalCode, replacement) %>%\n",
    "    summarise(repeatPerRun=n()) %>% ungroup()\n",
    "\n",
    "mutantStability <-  uniqueMutantsByRun %>% group_by(model, template, temperature, project, startLine, startColumn, originalCode, replacement) %>% summarise(nOccurrence=n()) %>% ungroup() %>%\n",
    "group_by(model, template, temperature, nOccurrence) %>% summarise(n=n())  %>% mutate(label = paste(model, template, temperature, sep=\"-\")) \n",
    "\n",
    "# stacked bar chart of mutation stability\n",
    "mutantStability %>% select(label,nOccurrence, n) %>%\n",
    "mutate(nOccurrence=as.factor(nOccurrence))%>%\n",
    "ggplot(aes(fill=nOccurrence, y=label, x=n)) +\n",
    "# make the fill be a discrete scale from red (1) to green (5)\n",
    "scale_fill_manual(values = c(\"red\", \"orange\", \"yellow\", \"green\", \"blue\")) +\n",
    "geom_bar(stat=\"identity\") +\n",
    "    theme_minimal() + theme(legend.position = \"bottom\") + \n",
    "    xlab(\"Number of Mutants\") +\n",
    "    ylab(\"\") +\n",
    "    # set legend title\n",
    "    labs(fill = \"Number of trials observed\") +\n",
    "    theme(legend.position = \"bottom\")\n",
    "    # output PDF\n",
    "    ggsave(\"mutantStability-codellama-34b-instruct-0.0.pdf\", width = 9, height = 2, units = \"in\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22mAdding missing grouping variables: `model`, `template`, `temperature`\n"
     ]
    },
    {
     "data": {
      "image/png": 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l5Qtf+EK56KKLZrJ5120SAnbeeeeSug2qHHDAAeXII4/sevhDDz20fOlLXyprr7129dV14+Urf/CDH6wQkOprZGX7HXzwweWzn/1sufbaa7tuet5555XnPve5Vb3/8Ic/lFe+8pXll7/8Zdd9rCRAgAABAgQIjKvA6uPacO2eKvD73/++GjXKKNC97nWvcvPNN5fnP//55Zhjjinbb7/9xA4JNRkdmTdv3sRnvS7Mnz+/Omev+zf3S0D661//2vyo78sZLdx66627HjcjcE94whOqoNl1wx5XJgB++MMfLieffPKMjrD//vuX5zznOeUNb3hD1WcZdfroRz9ajWb2ow9nVAkbESBAgAABAgTmiMDYBaQrr7yyfOc73ykJA/e///3Lk570pPKQhzyk6q5MWTr66KPLr3/965LlzTffvLzoRS8qq69+O1PW/fjHPy7XX399efaznz2lmzOK8o1vfKNcfPHFZaONNio77LBDWbRo0ZTtJn+QMJLpT3/6059KpnDd9773rULJ4sWLq00zUrXhhhtWIy0///nPyz3ucY/yspe9rLrhTaC54ooryjbbbFO1pz72z372s3LCCSdUdcn2T3nKU8rjHve4evWU76nnBz7wgSocZWXavc4665TLL798hW1zvtxY53yXXXbZCuvywymnnFK++c1vlmXLlk2p0+SNb7311vKRj3ykauu9733vannHHXcs3/72t8tZZ51V7nOf+5SddtppwjAhKOf/4x//WI3ObLHFFlU/3HjjjSUjXikZVdluu+3KggULymmnnVY22GCDapTmaU97Wlm4cGGJy2677TZRlRglWKWvUqa7RjI9Mv2aaXOrrbZaST0nl09/+tMl10BGj2K5++67l4MOOqi8/OUvL2lfyj/+8Y/y+c9/vqpDtlvV8v73v7/c6U53qo7/pje9qevuS5Ysqaz23nvviUCb6zZGCXsPe9jDuu5vJQECBAgQIEBg3ARuv/Mfg5bneZq3vOUt1TMqGRn529/+Vl772tdW06FyE53ftJ944onVb9vXWGON6jmSTEXKb9sTCLK8zz77lG233bZssskm1fbN5z9OOumk8j//8z/VCEOC13e/+91qyld+Y7+ykPTmN7+5Ckb5TX/CUoLaL37xiyoM5GY8wSzPtTzwgQ8sCQVZf+qpp1Y3ygk9udF+xzveUYWBBL6EtE9+8pPVTX+CXtr11re+teQGftNNN+3Y2xk1yldKnif63ve+V02vS7CoS6YGJqDkBjvTyCaXBJjU44UvfGEVnjLSlJv0BM1OJSEqgfXJT35ySRjMctr18Ic/vDz+8Y8vCYa/+93vqml42T/Hi3mcMvUv08wSaF7ykpdUNj/5yU/KxhtvXNZbb70qbGa62pprrlkdL88GXXDBBdW0wGZASpsyGpOA1O0aSWi9y13uUoXThN9O5QEPeEBZa621qiAW5wTttOmZz3zmREBK/fPZLrvsMqMpeJPP87a3va2sv/76VVsmr5v8cwJdSq7vuiQk3vnOd66C2soCUjziqxAgQIAAAQIEBi1Q37cM6jy5/8l90MrKWAWk3JRmpCUjAZnalZIRjLxs4EEPelA1ypCQlBvzlASPV73qVdWIQaZMffzjH69GDV7xildU6xOCMopTl4wUPPaxjy15jiclN/F53iPP2Oy5557VZ53+kxv9u9/97iUhqb7xzs14Ak1uTnOzn5Kb8/e9733VyE5ukN/+9rdXzwglHKQkSGR0IwEp7czzQ6lDSkaPMqqS56WmC0jVhsv/c+mll1YjH/UoWUauUhIwElAyKlKPbFUrGv9JIEiIrEeqMoqT0ZIE0ox6zKRkZGrXXXetNo1DRkkyUpWQmWdoXv3qV1eBIxtkfab85YJPyEoAzP75PKNx8ct0tHqUMCNT3Uq3aySWeaFEwvF00+xShwTjjE5m+5U9H9StLtOtS9/PtOTZrvRBvpolgTrXyMpKwnn9v5WVbdvr+vxvUCFAgAABAgQIZPbSIKf/N2eFddMeq4CUqU+bbbbZCjd8dXDJjXNuBB/96EdPeOVGuB6JyKhNRpya6/Nb+To8ZNQnoy5JpRm5qUtuMDNC0a3c7W53K+9617uqqVkZtclbxjKKktJ8I1tGj+qOrUcEEsjqsu66605Mh8voRELF8ccfX400pG45VuqZkiDQvHl/3vOeVwWwrMt0vLw4IPskEOVlDB/84AerqWL3u9/9yjOe8Yxs1rHkRjwjVnWJW0Zx8txMglemxtUllnUgrD/L92aAu+c971mtyhS6lKc//enVNLzULyEsQSVhZLqSPk34nWnpdo1MPkb6aHJ7VuVck483+edufTR52+l+Tvs7BZAE2bve9a7T7TbxeadwNbGyTwsZYVQIECBAgAABAvll+CAD0kyFxyog5Vma+oZ7MlCmhmVqVKbW1SUdlJGdjFBkNCXTwXJj2Sz1qEieG8r67N/s2ASElT1nkuCSUZc8F/WIRzyi+so0voyWNEuC1OSS6WOdyuGHH14FtUw3yzEz2tV8215ez51nYeqS4JERqmZJIHvxi19cPvShD5W8CS3PFeVYe+21V7VZXkaQwJWf84xLSurYHK2IX0q2yzMvmRpYl6zrFJCafZCAmRLblNe//vVVSM1zQ3mb3Gc+85lqatxrXvOaav3k/6RP62PU6+pj1T83A0S3a6Tevv7eqT3TBaTmOZvnq4/V6ftM+qjTfs3P8g9Nrtlcv81AlGl+9XTK5vaWCRAgQIAAAQLjLjBWASmjLueee+4KfZ7pdgkouVHPlKOMINQ3uRmBSQjIw/gZGcpoUp4FqkdIsn3Wp+RmPzeguSHNFLC6ZPt61Kf+bPL3TIvL80sZaamnTyUApDRvrCfvN93Pac8hhxxSTYWrn/3JTXJGg+rjHXjggVN2z/nrZ67qlQl+CYgJLfW0t3pdwkTWP/ShD50YlUvoStisQ+FvfvObKqDkZvylL31p9VXvn+/5u0UzLRlFygsyttxyy7LVVltV9Tp0+Su1M4Ux0x6bwXS6Y2Yq3uS/7dR8xXi3aySvEG+WTu1prs9yPT2tec7m+SZv3/y5Ux81189kOS+5yPWXcJywnpJRr/RpPQo5k+PYhgABAgQIECAwLgJj9XeQ8vauvNUsQSA3rAlDeYFCnk/JdK2Ek7x8IG80y41+pspl2tojH/nI6nrI1LL83Z+8pS0hIM+jNEues8nUr7wQIYEkzwRlZKXT3xFq7pfwle3rZ0LygFpGRlISdla1ZFQrIzkJMLkRTrD42Mc+VoWRbsd74hOfWLUtozwZ5cgUsrwkIZ/nmaMEhOZX3DLFMJ81R7ISWrJ/RsDyPE7cm6NKq9qeevscI6NY6Zf4py15xihTArMub9xLyZTG5vTBev98T30zmpJXl6eO6au81a4u3a6RbBPX888/v+Pb++pjNL+nXqlfHHLe/EHcXHODLHmZRz1amPo+9alPrZ4Di0muhVzjGTFMvRQCBAgQIECAAIEVBcZqBOnBD35w9TxNfjOfV0Jn1CcjLPULBfJa5rwEIW8zy2/dMz0twSKjQil5YUPCTl6ekOCR38jnmHXJKEZugvPMTkJKRpwyypDpbd1KRqSe9axnVX+nJtPccu68ZS0vF0iI6/aMTafjZv+8nS8B7lvf+lYVjBLe8gKBHG+6koCYv5WTl1HEKNPiMtWvfk5ruv2anyeAJJjlBjwBJm3PSx36UTJClBc2JCClPQmVGZl6z3veUx0+IS3PZOV5rry4opNb3tqWN+zlVdn5yjTCvII7I30pK7tG8sxTromEx7wpcCYlL99473vfWz27lTrGuK7zTPZf1W3ikymH9RvqsvzOd75z4tXnCfyve93rVvWwtidAgAABAgQIjIXAvOVTrv75cMdYNPefjUyT88KA/Aa907SsPJ+Rz+tpYpNpcuOfEaiMLnUqGZlYlWdZ6mNkulkCWB3I6s/vyPeMhCWoJTTNtKT+GcXKyFbzeaCZ7p/tYphnf/IM0CBKgmj6oX7GqXmOrMvITf18WHNdvZyRlGwXm06l2zWSfko4m/zMVqfj1J8lUNfX3ORnouptBv09fRKT5mjfoM85k+PnJQ2LFv3zlZsbL1vxbXv1/ueU+fViz9+XHrS0533btOPSPUajHW0yVRcCBAgQGL7ApReeV81Y6nRvPtu1G8uANNvIzkeAwPQCAtL0Np3WCEidVHxGgAABAnNdoE0BaayeQZrrF476EyBAgAABAgQIECAwWAEBabC+jk6AAAECBAgQIECAwBwSEJDmUGepKgECBAgQIECAAAECgxUQkAbr6+gECBAgQIAAAQIECMwhAQFpDnWWqhIgQIAAAQIECBAgMFgBAWmwvo5OgAABAgQIECBAgMAcEhCQ5lBnqSoBAgQIECBAgAABAoMVEJAG6+voBAgQIECAAAECBAjMIQEBaQ51lqoSIECAAAECBAgQIDBYAQFpsL6OToAAAQIECBAgQIDAHBIQkOZQZ6kqAQIECBAgQIAAAQKDFRCQBuvr6AQIECBAgAABAgQIzCEBAWkOdZaqEiBAgAABAgQIECAwWAEBabC+jk6AAAECBAgQIECAwBwSEJDmUGepKgECBAgQIECAAAECgxUQkAbr6+gECBAgQIAAAQIECMwhAQFpDnWWqhIgQIAAAQIECBAgMFgBAWmwvo5OgAABAgQIECBAgMAcEhCQ5lBnqSoBAgQIECBAgAABAoMVEJAG6+voBAgQIECAAAECBAjMIQEBaQ51lqoSIECAAAECBAgQIDBYAQFpsL6OToAAAQIECBAgQIDAHBIQkOZQZ6kqAQIECBAgQIAAAQKDFRCQBuvr6AQIECBAgAABAgQIzCEBAWkOdZaqEiBAgAABAgQIECAwWAEBabC+jk6AAAECBAgQIECAwBwSEJDmUGepKgECBAgQIECAAAECgxUQkAbr6+gECBAgQIAAAQIECMwhAQFpDnWWqhIgQIAAAQIECBAgMFgBAWmwvo5OgAABAgQIECBAgMAcEhCQ5lBnqSoBAgQIECBAgAABAoMVEJAG6+voBAgQIECAAAECBAjMIQEBaQ51lqoSIECAAAECBAgQIDBYAQFpsL6OToAAAQIECBAgQIDAHBIQkOZQZ6kqAQIECBAgQIAAAQKDFRCQBuvr6AQIECBAgAABAgQIzCEBAWkOdZaqEiBAgAABAgQIECAwWAEBabC+jk6AAAECBAgQIECAwBwSEJDmUGepKgECBAgQIECAAAECgxUQkAbr6+gECBAgQIAAAQIECMwhAQFpDnWWqhIgQIAAAQIECBAgMFgBAWmwvo5OgAABAgQIECBAgMAcEhCQ5lBnqSoBAgQIECBAgAABAoMVEJAG6+voBAgQIECAAAECBAjMIQEBaQ51lqoSIECAAAECBAgQIDBYAQFpsL6OToAAAQIECBAgQIDAHBIQkOZQZ6kqAQIECBAgQIAAAQKDFRCQBuvr6AQIECBAgAABAgQIzCEBAWkOdZaqEiBAgAABAgQIECAwWAEBabC+jk6AAAECBAgQIECAwBwSEJDmUGepKgECBAgQIECAAAECgxUQkAbr6+gECBAgQIAAAQIECMwhAQFpDnWWqhIgQIAAAQIECBAgMFgBAWmwvo5OgAABAgQIECBAgMAcEhCQ5lBnqSoBAgQIECBAgAABAoMVEJAG6+voBAgQIECAAAECBAjMIQEBaQ51lqoSIECAAAECBAgQIDBYAQFpsL6OToAAAQIECBAgQIDAHBIQkOZQZ6kqAQIECBAgQIAAAQKDFRCQBuvr6AQIECBAgAABAgQIzCEBAWkOdZaqEiBAgAABAgQIECAwWAEBabC+jk6AAAECBAgQIECAwBwSEJDmUGepKgECBAgQIECAAAECgxUQkAbr6+gECBAgQIAAAQIECMwhAQFpDnWWqhIgQIAAAQIECBAgMFgBAWmwvo5OgAABAgQIECBAgMAcEhCQ5lBnqSoBAgQIECBAgAABAoMVEJAG6+voBAgQIECAAAECBAjMIYF5y5aXOVRfVSVAYMQElixZUm6++eay/vrrl9VWG8/f2VxyySVV+0esa2fcnIsuuqjMnz+/LFq0aMb7jNKGt9xyS7n66qvLwoULR6lZM27LTTfdVC6//PKy5pprlnXWWWfG+43Shtddd13J7dhaa601Ss2acVuuueaacu2115b11luvLFiwYMb7jdKG+d/A2muvXf1bOErtmmlbLrvsspJ/CxcvXlzmzZs3090Gtt143o0MjNOBCRAgQIAAAQIECBCYywIC0lzuPXUnQIAAAQIECBAgQKCvAgJSXzkdjAABAgQIECBAgACBuSwgIM3l3lN3AgQIECBAgAABAgT6KiAg9ZXTwQgQIECAAAECBAgQmMsCAtJc7j11J0CAAAECBAgQIECgrwICUl85HYwAAQIECBAgQIAAgbksICDN5d5TdwIECBAgQIAAAQIE+iogIPWV08EIECBAgAABAgQIEJjLAgLSXO49dSdAgAABAgQIECBAoK8CAlJfOR2MAAECBAgQIECAAIG5LCAgzeXeU3cCBAgQIECAAAECBPoqICD1ldPBCBAgQIAAAQIECBCYywIC0lzuPXUnQIAAAQIECBAgQKCvAgJSXzkdjAABAgQIECBAgACBuSwgIM3l3lN3AgQIECBAgAABAgT6KjBv2fLS1yM6GAECBFZBYMmSJWXRooWrsEfvm268bEHvO9+BPc8p8+/A3rO769KDls7uCUf8bEv34DniXax5BAj0SeDSC88rixcvLvPmzevTEXs/jBGk3u3sSYAAAQIECBAgQIDAiAkISCPWoZpDgAABAgQIECBAgEDvAgJS73b2JECAAAECBAgQIEBgxAQEpBHrUM0hQIAAAQIECBAgQKB3AQGpdzt7EiBAgAABAgQIECAwYgIC0oh1qOYQIECAAAECBAgQINC7gIDUu509CRAgQIAAAQIECBAYMQEBacQ6VHMIECBAgAABAgQIEOhdQEDq3c6eBAgQIECAAAECBAiMmICANGIdqjkECBAgQIAAAQIECPQuICD1bmdPAgQIECBAgAABAgRGTEBAGrEO1RwCBAgQIECAAAECBHoXEJB6t7MnAQIECBAgQIAAAQIjJiAgjViHag4BAgQIECBAgAABAr0LCEi929mTAAECBAgQIECAAIERExCQRqxDNYcAAQIECBAgQIAAgd4FBKTe7exJgAABAgQIECBAgMCICQhII9ahmkOAAAECBAgQIECAQO8CAlLvdvYkQIAAAQIECBAgQGDEBASkEetQzSFAgAABAgQIECBAoHcBAal3O3sSIECAAAECBAgQIDBiAgLSiHWo5hAgQIAAAQIECBAg0LuAgNS7nT0JECBAgAABAgQIEBgxAQFpxDpUcwgQIECAAAECBAgQ6F1AQOrdzp4ECBAgQIAAAQIECIyYgIA0Yh2qOQQIECBAgAABAgQI9C4gIPVuZ08CBAgQIECAAAECBEZMQEAasQ7VHAIECBAgQIAAAQIEehcQkHq3sycBAgQIECBAgAABAiMmICCNWIdqDgECBAgQIECAAAECvQsISL3b2ZMAAQIECBAgQIAAgRETEJBGrEM1hwABAgQIECBAgACB3gUEpN7t7EmAAAECBAgQIECAwIgJCEgj1qGaQ4AAAQIECBAgQIBA7wICUu929iRAgAABAgQIECBAYMQEBKQR61DNIUCAAAECBAgQIECgdwEBqXc7exIgQIAAAQIECBAgMGICAtKIdajmECBAgAABAgQIECDQu4CA1LudPQkQIECAAAECBAgQGDEBAWnEOlRzCBAgQIAAAQIECBDoXUBA6t3OngQIECBAgAABAgQIjJiAgDRiHao5BAgQIECAAAECBAj0LiAg9W5nTwIECBAgQIAAAQIERkxAQBqxDtUcAgQIECBAgAABAgR6FxCQerezJwECBAgQIECAAAECIyYgII1Yh2oOAQIECBAgQIAAAQK9CwhIvdvZkwABAgQIECBAgACBERMQkEasQzWHAAECBAgQIECAAIHeBQSk3u3sSYAAAQIECBAgQIDAiAkISCPWoZpDgAABAgQIECBAgEDvAgJS73b2JECAAAECBAgQIEBgxAQEpBHrUM0hQIAAAQIECBAgQKB3AQGpdzt7EiBAgAABAgQIECAwYgIC0oh1qOYQIECAAAECBAgQINC7gIDUu509CRAgQIAAAQIECBAYMQEBacQ6VHMIECBAgAABAgQIEOhdQEDq3c6eBAgQIECAAAECBAiMmICANGIdqjkECBAgQIAAAQIECPQuICD1bmdPAgQIECBAgAABAgRGTEBAGrEO1RwCBAgQIECAAAECBHoXEJB6t7MnAQIECBAgQIAAAQIjJiAgjViHag4BAgQIECBAgAABAr0LCEi929mTAAECBAgQIECAAIERExCQRqxDNYcAAQIECBAgQIAAgd4FBKTe7exJgAABAgQIECBAgMCICQhII9ahmkOAAAECBAgQIECAQO8CAlLvdvYkQIAAAQIECBAgQGDEBASkEetQzSFAgAABAgQIECBAoHcBAal3O3sSIECAAAECBAgQIDBiAgLSiHWo5hAgQIAAAQIECBAg0LuAgNS7XbXnUUcdVc4444wZHeXMM88sX/va16ptm8sz2nkWNzrnnHPKl7/85XLccceVG264Ydoz//a3vy3HHnvsxPqzzz67fPWrX534eSYLt912W/nc5z5XLrzwwplsvtJtbrnllnLTTTetdLs7ssF1113XdfecP37vfve7y09/+tOu22bl97///fKrX/2q2m6m18Vf/vKX6lr64Q9/WK699tqu57jmmmtKtpv8FSuFAAECBAgQIEBgRQEBaUWPVf4pAen000+f0X65+f36179ebdtcntHOs7TRfvvtV974xjeW3IB/6lOfKnvssUe56qqrppz9kksuKfvuu2/50Y9+NLHuz3/+c/nKV74y8fNMFpYuXVq+8IUvlIsuumgmm3fdJkFg5513LqnboMoBBxxQjjzyyK6HP/TQQ8uXvvSlsvbaa1dfXTdevvIHP/jBCgGpvkam2++LX/xi2XHHHatgfvjhh5fXvva15Yorrphu83LqqaeW973vfeXTn/70Cl833njjtPtYQYAAAQIECBAYV4HVx7Xh2j1V4Pe//301apRRoHvd617l5ptvLs9//vPLMcccU7bffvuJHRJqMjoyb968ic96XZg/f351zl73b+6XgPTXv/61+VHflzNauPXWW3c9bkbgnvCEJ1RBs+uGPaxMcP385z9fPvaxj5VHPepR5dZbby2vec1rquCd751KguvDHvawctBBB3Va7TMCBAgQIECAAIGGwNgFpCuvvLJ85zvfKQkD97///cuTnvSk8pCHPKQiyXSvo48+uvz6178uWd58883Li170orL66rczZd2Pf/zjcv3115dnP/vZDcp/LuZm9Bvf+Ea5+OKLy0YbbVR22GGHsmjRoinbTf4gYeSII44of/rTn0qmcN33vvetQsnixYurTTNSteGGG1YjLT//+c/LPe5xj/Kyl72sCikJNBlB2Gabbar21Mf+2c9+Vk444YSqLtn+KU95Snnc4x5Xr57yPfX8wAc+UIWjrEy711lnnXL55ZevsG3Ol3CU81122WUrrMsPp5xySvnmN79Zli1bNqVOkzfODf5HPvKRqq33vve9q+WMjnz7298uZ511VrnPfe5TdtpppwnDhKCc/49//GM1OrPFFltU/ZDRkIx4pXz2s58t2223XVmwYEE57bTTygYbbFCN0jztaU8rCxcuLHHZbbfdJqoSowSr9FXKdNdIpkemXzNtbrXVVqtGcSYO8q+FjNLkGsjoUSx33333Kpi8/OUvL2lfyj/+8Y8q5KQO2W5VSq6/tCfhKCV99PSnP70y6RaQ6mt8Vc5lWwIECBAgQIDAOAqM1RS7PE/zlre8pbpZfuxjH1uNkGR6Uv38y/77718++clPVjflm2yySfUcSbbPjX7KL3/5y/K2t72tWs76bJ8b5rqcdNJJ1W/zc54Er4w2ZMpXpxBR71N/f/Ob31wFr0c/+tFViMmx3vCGN5SM1qTkxvj9739/dXP/mMc8prrx32uvvcree+9d7nrXu1aB6h3veEfJ1L2UhLR3vvOd1c30M57xjJIA8da3vrUKFtUGHf6TUaO4pOR5ok984hPV9LoEi7rk+Akob3/72zuOICXApB4PeMADyrrrrluNNHWbkhbbBNZLL720CqVZjnlC2eMf//gShz333LM+fXW8k08+uWy77bZl0003LQcffHA1ne1Od7pTeeADH1htt/HGG5f11luvCj2ZrpbQkiCSZ4MuuOCCFaYFZoe06cQTT6z27XaNJLTe5S53qcJpwm+nknavtdZaVRBL/RK006ZmyLz66qurz3p5VipTEeugVZ8/gSnXWH2t1J/X3xPYEqBz7T7vec+rrpm///3v9equ3xNg88uAQX5NV++uFbOSAAECBAgQGDmBQd5v5Ngzvfe6fWhk5IinNig3qrlRzEhApnal5AYwLxt40IMeVAWnhJ7cmKdktOVVr3pVNWKQKVMf//jHq1GDV7ziFdX6hKCM4tQlU5gSMPbbb7/qo+c85znlla98ZfWMTfMmv96+/p5nfO5+97uXhKT6xjs34wk0Gc3IzX5Kbs7zLElGDdZff/0qpOQZoZe85CXV+t/97ndVXTNakHZmXeqQktGjjKrkeancuHcrCSsZ+ciFlFGyjFyl5KLK1Lqsq0e2Jh8ngWCfffaZGKnKKE6mhGWqXkLMTEpGpnbddddq0zi86U1vqgJARrj+8Ic/lFe/+tXlmc985sT63GDf+c53Lk9+8pOrMJT9s19G4+L34Q9/eGKUMCNT3Uq3aySWeaFEwvF00+xSh+9+97vV6GS2X9kLFLrVpdO6BPKM6jVLwl8M6uuouS6BNfukv1760pdW13YCa/owz0klzHUreZFDp2fQuu1jHQECBAgQIECgF4H8EnmQJfeLuTddWRmrgJTfpG+22WYT4Sg4dXDJjXNCU0Zw6pIb4YST3GhnKtff/va3FdbnN/d1eMgUuYy6ZApXRqHqkqlY9ahO/dnk73e7293Ku971rmpq1ve+973qBQl5sD6lmXQzQlJP98u5U+oRnyxnxKYeqdhll12qUHH88cdXoyapW46VeqYkCDRv3jOykACWkul4eXFA9kkgyssYPvjBD1ZTxe53v/uVjEhNV3LRZWpiXeKWUZy8OCHBK1Pj6hLrOhDWn+V7M8Dd8573rFbVLxTIdLJMyUv9EmATVDJVcrqSPk34nWnpdo1MPkb6aHJ7VuVck483+edOfZT2JNQ3S/1zRhInlwSgTN3MdZx/FFIe+tCHViObmSr63Oc+d/IuK/yc800OZCts0IcfVvZWwD6cwiEIECBAgACBOSCQX/r24xn36Zo601/Wj1VASniob7gnw+U37bmZXGONNSZWpYMyspPfzmc0JdPBMkLSLDV0bvKyPvs3OzYBYWXPmSS4ZNQlz0U94hGPqL4yhSyjJc2SIDW5rLnmmpM/qn7O280S1DLdLMfMaFfzbXt5PXeehalLgkcdkOrPEshe/OIXlw996EPlvPPOq54ryrEytS8lLyNI4Kqn+uWz1LGZzOOXku0y5TDPeNUl6zoFpGYfJGCm1NMcX//611chNc8NZSTkM5/5TPXs0HTP36RP62PU562PVf9cB4z83O0aqbevv3dqz3QBqXnO5vnqY3X63qmPMop2/vnnr7B5ftsSy6Z7vUGuxcmjfbkmEoJn8ubABPI6lNfH7Pf3Ovz2+7iOR4AAAQIECMwtgdzXNu+jh1X7sQpIGXU599xzV7DOdLsElNyoZ1paRhDqm9w815EQkJcGZGQov4XPs0D1CEm2z/qU3KDmN/i5gc0UsLpk+5XdYOah/zxrk5GWTJ1LSQBIad5YVx/M4D9pzyGHHFJNo8pLJlIS7DIaVB/vwAMPnHKknD/PWX30ox+dWJfgl4CY0FJPe6tXJkxkfUYkMtKQktCVsFmHwt/85jdVQMnzTZnila9mWZW/xZMb6Yx6bLnllmWrrbaq6nXooYdWUxgz7XEm/4PKKMrkv+3UDArdrpE8T9YsndrTXJ/l2qV5zub5Jm/f/LlTH2W0LH83KSGrvq4SfCc/l1QfJ2Eqz4S95z3vmRjtzPkzmjfdPvW+vhMgQIAAAQIExlFgrF7SkOdp8lazBIHcsCYMHXbYYdXzKZmulXCSN6DljWa50c8ITKatPfKRj6yujUwty9/9yVvaEgLyPEqz5DmbTP3KA/8JJHkmKC9RWNkzHAlf2T6BKyXPjGRkJCVhZ1VLRrUykpMAk3CTYJHXQq/sj6g+8YlPrNqWUZ7cgGcKWd6el88zCpGA0PzKs06ZYpjPmiNZCS3ZPyNgeR4n7p1GN1a1XTlG3o6Xfol/bPKMUUZDsq6eCpYpjc3pg83zpL4ZDcyry1PH9FXealeXbtdItolrQsdMXryR7VOv1C8OOW9eCJJrrteSZ8lS8odo07cJ/JmWmRBfl6yrRwsT/DMyGLNcXwlHebFFAn2el1IIECBAgAABAgRWFBirEaQHP/jB1fM0+c18Xgmdm8SMsNSvvs5rmfMShLzuOb+dz1SkBIuMCqXkhQ0JO3l5Qm5OM30ux6xLRjFyE5xndhJSMuKUUYZMb+tWMiL1rGc9q3prXW5mc+68AjovF0iI6/aMTafjZv+8nS8B7lvf+lYVjBLeckOc401XEhDz5ry8jCJGmRaXqX71c1rT7df8PAEkwSxT9hJg0va8EKAfJSNEeWFDbvbTnoTKjExldCQlIS3PZOV5rry4opNb/h7QC1/4wuqNgHkrYKYR5hXcGelLWdk1kmeeck0kPOZNgTMpefnGe9/73urZrdQxxnWdZ7J/c5sErowE5g2FCUIZ2XvBC15QjarV28UnUw7T1pSYxSRmKbmu84bCTs8sVRv4DwECBAgQIEBgjAXmLZ9y9c93WI8RQpqcKUb5zX6naVl5piOf19PEJtPkxj8jUBld6lQyMrEqz7LUx6jfGFYHsvrzO/I9I2EJavV0rJkcK/XPKFZGtprPA81k33qbGObZn5W9Ja3eflW/J4imHxJyJ5esS5Conw+bvD4/Z1Qt28WmU+l2jaSfEs4mP7PV6Tj1ZwnU9TU3+ZmoeptV/Z4XX+QanunxMuqVKX+dnmVb1XP3c/slS5Ys/yXEwn4ectpjbbxswbTrBrninPLPKaiDPEe/jr30oH/+aYF+HW/cj7N0D57jfg1oPwECMxO49MLzqhlLne7NZ3aE/m01lgGpf3yORIDAHRUQkO6oYH/3F5D67Ckg9RfU0QgQGFmBNgWksXoGaWSvKA0jQIAAAQIECBAgQKAvAgJSXxgdhAABAgQIECBAgACBURAQkEahF7WBAAECBAgQIECAAIG+CAhIfWF0EAIECBAgQIAAAQIERkFAQBqFXtQGAgQIECBAgAABAgT6IiAg9YXRQQgQIECAAAECBAgQGAUBAWkUelEbCBAgQIAAAQIECBDoi4CA1BdGByFAgAABAgQIECBAYBQEBKRR6EVtIECAAAECBAgQIECgLwICUl8YHYQAAQIECBAgQIAAgVEQEJBGoRe1gQABAgQIECBAgACBvggISH1hdBACBAgQIECAAAECBEZBQEAahV7UBgIECBAgQIAAAQIE+iIgIPWF0UEIECBAgAABAgQIEBgFAQFpFHpRGwgQIECAAAECBAgQ6IuAgNQXRgchQIAAAQIECBAgQGAUBASkUehFbSBAgAABAgQIECBAoC8CAlJfGB2EAAECBAgQIECAAIFREBCQRqEXtYEAAQIECBAgQIAAgb4ICEh9YXQQAgQIECBAgAABAgRGQUBAGoVe1AYCBAgQIECAAAECBPoiICD1hdFBCBAgQIAAAQIECBAYBQEBaRR6URsIECBAgAABAgQIEOiLgIDUF0YHIUCAAAECBAgQIEBgFAQEpFHoRW0gQIAAAQIECBAgQKAvAgJSXxgdhAABAgQIECBAgACBURAQkEahF7WBAAECBAgQIECAAIG+CAhIfWF0EAIECBAgQIAAAQIERkFAQBqFXtQGAgQIECBAgAABAgT6IiAg9YXRQQgQIECAAAECBAgQGAUBAWkUelEbCBAgQIAAAQIECBDoi4CA1BdGByFAgAABAgQIECBAYBQEBKRR6EVtIECAAAECBAgQIECgLwICUl8YHYQAAQIECBAgQIAAgVEQEJBGoRe1gQABAgQIECBAgACBvggISH1hdBACBAgQIECAAAECBEZBQEAahV7UBgIECBAgQIAAAQIE+iIgIPWF0UEIECBAgAABAgQIEBgFAQFpFHpRGwgQIECAAAECBAgQ6IuAgNQXRgchQIAAAQIECBAgQGAUBASkUehFbSBAgAABAgQIECBAoC8CAlJfGB2EAAECBAgQIECAAIFREBCQRqEXtYEAAQIECBAgQIAAgb4ICEh9YXQQAgQIECBAgAABAgRGQUBAGoVe1AYCBAgQIECAAAECBPoiICD1hdFBCBAgQIAAAQIECBAYBQEBaRR6URsIECBAgAABAgQIEOiLgIDUF0YHIUCAAAECBAgQIEBgFAQEpFHoRW0gQIAAAQIECBAgQKAvAgJSXxgdhAABAgQIECBAgACBURAQkEahF7WBAAECBAgQIECAAIG+CAhIfWF0EAIECBAgQIAAAQIERkFAQBqFXtQGAgQIECBAgAABAgT6IiAg9YXRQQgQIECAAAECBAgQGAUBAWkUelEbCBAgQIAAAQIECBDoi4CA1BdGByFAgAABAgQIECBAYBQEBKRR6EVtIECAAAECBAgQIECgLwICUl8YHYQAAQIECBAgQIAAgVEQEJBGoRe1gQABAgQIECBAgACBvggISH1hdBACBAgQIECAAAECBEZBQEAahV7UBgIECBAgQIAAAQIE+iIgIPWF0UEIECBAgAABAgQIEBgFAQFpFHpRGwgQIECAAAECBAgQ6IuAgNQXRgchQIAAAQIECBAgQGAUBASkUehFbSBAgAABAgQIECBAoC8CAlJfGB2EAAECBAgQIECAAIFREBCQRqEXtYEAAQIECBAgQIAAgb4ICEh9YXQQAgQIECBAgAABAgRGQUBAGoVe1AYCBAgQIECAAAECBPoiMG/Z8tKXIzkIAQIEehBYsmRJufnmm8v6669fVlttPH9nc8kll1Tt74FvJHa56KKLyvz588uiRYtGoj2r2ohbbrmlXH311WXhwoWruutIbH/TTTeVyy+/vKy55pplnXXWGYk2rWojrrvuupLbsbXWWmtVdx2J7a+55ppy7bXXlvXWW68sWLBgJNq0qo3I/wbWXnvt6t/CVd13FLa/7LLLSv4tXLx4cZk3b97QmzSedyNDZ1cBAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEICEhDYXdSAgQIECBAgAABAgTaKCAgtbFX1IkAAQIECBAgQIAAgaEIzFu2vAzlzE5KgACB5QJLliwpixYtZNGDwMbLFvSwV3t2OafMb09l+liTpQct7ePRxvtQS/dgOd5XgNaPk8ClF55XFi9eXObNmzf0ZhtBGnoXqAABAgQIECBAgAABAm0REJDa0hPqQYAAAQIECBAgQIDA0AUEpKF3gQoQIECAAAECBAgQINAWAQGpLT2hHgQIECBAgAABAgQIDF1AQBp6F6gAAQIECBAgQIAAAQJtERCQ2tIT6kGAAAECBAgQIECAwNAFBKShd4EKECBAgAABAgQIECDQFgEBqS09oR4ECBAgQIAAAQIECAxdQEAaeheoAAECBAgQIECAAAECbREQkNrSE+pBgAABAgQIECBAgMDQBQSkoXeBChAgQIAAAQIECBAg0BYBAaktPaEeBAgQIECAAAECBAgMXUBAGnoXqAABAgQIECBAgAABAm0REJDa0hPqQYAAAQIECBAgQIDA0AUEpKF3gQoQIECAAAECBAgQINAWAQGpLT2hHgQIECBAgAABAgQIDF1AQBp6F6gAAQIECBAgQIAAAQJtERCQ2tIT6kGAAAECBAgQIECAwNAFBKShd4EKECBAgAABAgQIECDQFgEBqS09oR4ECBAgQIAAAQIECAxdQEAaeheoAAECBAgQIECAAAECbREQkNrSE+pBgAABAgQIECBAgMDQBQSkoXeBChAgQIAAAQIECBAg0BYBAaktPaEeBAgQIECAAAECBAgMXUBAGnoXqAABAgQIECBAgAABAm0REJDa0hPqQYAAAQIECBAgQIDA0AUEpKF3gQoQIECAAAECBAgQINAWAQGpLT2hHgQIECBAgAABAgQIDF1AQBp6F6gAAQIECBAgQIAAAQJtERCQ2tIT6kGAAAECBAgQIECAwNAFBKShd4EKECBAgAABAgQIECDQFgEBqS09oR4ECBAgQIAAAQIECAxdQEAaeheoAAECBAgQIECAAAECbREQkNrSE+pBgAABAgQIECBAgMDQBQSkoXeBChAgQIAAAQIECBAg0BYBAaktPaEeBAgQIECAAAECBAgMXUBAGnoXqAABAgQIECBAgAABAm0REJDa0hPqQYAAAQIECBAgQIDA0AUEpKF3gQoQIECAAAECBAgQINAWAQGpLT2hHgQIECBAgAABAgQIDF1AQBp6F6gAAQIECBAgQIAAAQJtERCQ2tIT6kGAAAECBAgQIECAwNAFBKShd4EKECBAgAABAgQIECDQFgEBqS09oR4ECBAgQIAAAQIECAxdQEAaeheoAAECBAgQIECAAAECbREQkNrSE+pBgAABAgQIECBAgMDQBQSkoXeBChAgQIAAAQIECBAg0BYBAaktPaEeBAgQIECAAAECBAgMXUBAGnoXqAABAgQIECBAgAABAm0REJDa0hPqQYAAAQIECBAgQIDA0AUEpKF3gQoQIECAAAECBAgQINAWAQGpLT2hHgQIECBAgAABAgQIDF1AQBp6F6gAAQIECBAgQIAAAQJtERCQ2tIT6kGAAAECBAgQIECAwNAFBKShd4EKECBAgAABAgQIECDQFgEBqS09oR4ECBAgQIAAAQIECAxdQEAaeheoAAECBAgQIECAAAECbREQkNrSE+pBgAABAgQIECBAgMDQBQSkoXeBChAgQIAAAQIECBAg0BYBAaktPaEeBAgQIECAAAECBAgMXUBAGnoXqAABAgQIECBAgAABAm0REJDa0hPqQYAAAQIECBAgQIDA0AUEpKF3gQoQIECAAAECBAgQINAWAQGpLT2hHgQIECBAgAABAgQIDF1AQBp6F6gAAQIECBAgQIAAAQJtERCQ2tIT6kGAAAECBAgQIECAwNAFBKShd4EKECBAgAABAgQIECDQFgEBqS09oR4ECBAgQIAAAQIECAxdQEAaeheoAAECBAgQIECAAAECbREQkNrSE+pBgAABAgQIECBAgMDQBQSkLl1w+eWXl8997nPl+uuv77LV7au+//3vl1/96lfVB2eeeWb52te+dvvKlizdeuut5Re/+EX58pe/XE477bSutfrtb39bjj322Iltzj777PLVr3514ueZLJxzzjnVuWay7Uy2ue6662ay2R3aZmXnuOmmm6o2vfvd7y4//elPu57r5ptvrq6hSy65pNqueY1Mt+Ntt91WTjrppPLFL36x/OY3v5lusxU+v/DCC8vXv/71cuSRR5YsN8s111xTfvjDH075uuWWW5qbWSZAgAABAgQIEFguICB1uQwSkD7/+c+XG264octWt6/6wQ9+sEJAyg1rm8qVV15ZXvCCF5TPfOYz5bzzzitvfetbyyc+8YmOVcwN/b777lt+9KMfTaz/85//XL7yla9M/DyThXPPPbdvQTHB7s1vfvNMTtvzNgcccEAVMrod4NBDDy1f+tKXytprr119dds2ASnX0D/+8Y9qs+Y10mm/hKPXvOY15R3veEf5+9//Xt71rneV1Klb+X//7/+V//7v/y5nnXVW+d73vld23HHHKgTX+5x66qnlfe97X/n0pz+9wteNN95Yb+I7AQIECBAgQIDAvwRWJzE+AhmRuNe97lU+9alPVY3+5S9/WYWk//qv/yrrr7/+BMTSpUtLRkfmzZs38VmvC9tuu23JVz9Kwtagb+rPOOMk3i38AABAAElEQVSMsvXWW3etbkbFnvCEJ5Q3vvGNXbfrZeXhhx9err322mo0aM011ywXXHBBFXie9axnlYc85CFTDpmRyhNOOKEcccQR5Z73vGe1/p3vfGf5+Mc/Xv7jP/6j+jnB9mEPe1g56KCDpuzvAwIECBAgQIAAgRUFRi4gZZTkO9/5Tvn9739f7n//+5cnPelJEzeW+e380UcfXX7961+XLG+++eblRS96UVl99X8yZMrRt7/97Wpa06JFi8qWW265otbyn3Kz+Y1vfKNcfPHFZaONNio77LBDybYrKxlJyE3sn/70p5IpXPe9733L9ttvXxYvXlwy7e0jH/lIednLXlbVL0HgEY94RHn5y19ejUhlWtbChQtLbpIf+MAHTpzqZz/7WXVznLrc4x73KE95ylPK4x73uIn1kxf+8z//szzzmc+c+Pjud797tXzFFVesEJAyjS7haJtttimXXXbZxPb1wimnnFK++c1vlmXLllXbxHi6cvrpp1fT9N7whjdMtDMjHHHOiMd97nOfstNOO00Y5rNME8sI1gYbbFC222678tCHPrTknMcff3w1EvOBD3yg7LbbbtUoWKYJZruMzDztaU+r6pv+SN3rkhGz9PVjHvOY6qPprpFMiYxlps2tttpqVTCpj1F/zyhMroGMHqUeu+++exU80lf3vve9q80yWpRRo9RxVUPmiSeeWAXKhKOU+93vfuXhD394NZLXKSCl73bZZZeJcJR90tbjjjuu6p+cP/XttG+2VQgQIECAAAECBFYUGKkpdpkK95a3vKW6WX7sYx9bEkpe+9rXTjyTsf/++5dPfvKT1U35JptsUj1Hku1zo5+SqUyHHXZYFU4SljK9qVnyXEimP+U8CQUZbdh55507hojmflnO1LAf//jH5dGPfnQVYnKshIaM1iSsJdRlm9yYJxDkGaHU7X//93+rG+S//e1vZZ999pk4bEJaRgoSDp7xjGdUIyuZMvfHP/5xYpvJC5tttll5wAMeUPIMTZ6V+tjHPlby2YMf/OCJTTMikYD09re/vePNfZ5nyfSvHGfdddetRpoSaKYrmSaW8JJStzPtyvTFxz/+8dWzNnvuuWe1Pp+97nWvK3e+852rYJSb+4SMjKIkzCUE3uUudymbbrppFWr/+te/ViMtCS0JLGlXpuH94Q9/qI5X/+f//u//qjCVn7tdIwmtOX7Os9Hy8NuppN1rrbVWFVhTj7pNqXtdrr766qo/U59VLRdddFHVp8390sf1FL3m51lOIE7AbJZcZ6lbHc4SkBKk3va2t5XnPe95Ze+9966m7zX3mW45bViyZMlAvzwLNZ2+zwkQIECAwHgJDPqe46qrrpoR6EiNICVk5EYwIwHz58+vADI6k5cNPOhBD6pu1BOScmOekpvLV73qVdWIQW5Cs/8XvvCFauQp6zMC1ZyWlOUEr/322y+ry3Oe85zyyle+stqnvsmvVkz6TzojN/gJQPWNd27GE2gymlGPFmTUIwEsJTf/eUHCUUcdVY0OZHTouc99bsn0rtykp5177LFHVYdsn/UZbcmITW6Ou5WM3mRUJTe/mUqXUJZS/5xRkYxsdSoJBAlq9UjVggULqtGS5z//+eVOd7pTp12mfJZ27rrrrtXncXjTm95Uhczzzz+/qkNGROL15Cc/uRpBSYCNW4JjAlfc6xK/D3/4wxMjJHkZQbfS7RrJcfNSjoTn6abZpU7f/e53q2sj22c6XL9KrtWM2K2zzjorHDI/Z2RtJiXPveWZo3oaZQJtRsXSny996Uuraz+BNn2c56gS9rqVBPj8okEhQIAAAQIECAxaoC2/NB2pgJTflGdEpA5H6cQ6uCQU5POM4NQlN8LrrbdeNe0tb6rLckJRXRKG6oCUm8S8xS1T3TIKVZeEi4y6dCt3u9vdqtGo1C8P0f/lL3+pbmKzT0JJHZBSn7oksKUu9XMlOUZKRioSkBIicjOdaWcZYUndcqzUM9s0g0KO0ZxylmeOEmgylSwvYkjgefrTn161NVO6MiI1XUkgyhSuumyxxRbVKE6mxJ188skrBIaMVnQqzQBXty/PFiUApd2Zevjv//7vVQhLveq2dzpW+jThd6al2zUy+RgJGs0RuVw7q3Kuyceb/HPCWjNgJQDnekpQapb8XF8jzc8nLyfcZeTxve9970RgTADK1M5c2xmZS4lzRj4z0pRzdisZUZsuLHfbb1XWNUffVmU/2xIgQIAAAQKjJZBn4usZMMNs2UgFpNxo1Tfck1Hzm/TcLK6xxhoTq9IBGanIb8mzPt8zWlF3THNEJM8NZV32r9fnQAkImd7VrSS4JITkuag8W5SvvLhg8lSwySMHd73rXScO2zxnPszD/AlqG2+8cXW8TPnL6FFKRqwSCOuS4NUMSPk8z11ln4yGZApaQk+eK0rd9tprr2rXjFYlcOXnTMtKSVhJSKpL/FKyXUa8mlPBEm46lWYf1KNXsU17M7KVKXmZKpfnsvKygYz6/du//VunQ1V9Wh+j3iDHapbmbyO6XSPNfbKcKZR5Zq0uaet0Aal5zskBp95/8vdOXgkyuRabJVP2uoWUXLexyvEymtYMsLluJu+baybTCDOdb2Vl8nW3su2tJ0CAAAECBAj0KpD7jjbce4xUQMroQ15w0CyZbpeAstHyKVqZlpYRhPomNyMwCQF5aUBuGDNdK+vrZ3LynFBdcnOcG/i8AODVr351/XH1wof6JQ8TH05ayEhNjpXpT/Xb4vLmsZTmjfWk3ab9Me055JBDqmlSeclESqa+ZbpcjpeRp06v485b17baaquSEaS6ZAQjwSyhpZ72Vq9LmEgwzIhDPSqXAJQb+DoU5u/0JKDk7XgHHnhgvWtP3zOylpdY5FXk+cq5MwKYaYYJSDP5H0xGSZqvZU9YufTSSyfq0+0ayahKs2RKWr66ldqlec6ZBI8cs5NXwkuCbl7IUZcEtbqf68+a39PvGe3KNZH9myXTFvPM2Hve856y4YYbVqtSv5jUL5Vobm+ZAAECBAgQIDDuAv98+GREFJ797GdXf/w0QSQ3rAk7eelC3uCVZ2YSTj772c9Wz/fkRj8jMHnRwCMf+chqm4SoQ5f/jZusy5S15ihMiDItLaMbedNYAsnvfve7amRlZQ98ZVpetk9AS8kzIRkpSUnYWdWSka2M5CTAZPQg09PywoWMlHQ7XsJRpmAlFGa7b33rW9XNeKbUJSQlIDS/4pab6nzWnOIVowSPjIBlBCruzVGlVW1Pc/v8vZ6MaMUrASlhrL6RTx3z8F6C1HSjNKnvz3/+85KXWmT/TJHMseog2u0aST3imlDR6e19zXrWy2l3wnUcMk0zf6Q111yvJUEoI0EJRalzwmFG55pvH0wf1qOFxxxzTLV9/g5SrBKU6q+0O9d0psnlWs/1l3B08MEHTzzj1Ws97UeAAAECBAgQGFWBkRpByshPnqnJb+bzkHpGfXLDWb9QIK9lzg14Xs2dUZ/8tj3Bon5N9wc/+MHqt+15BiYl3xOU6vKKV7yiugnOORJSMh0qIwzdXnOdfTPlKSMCeWtdblZz7rydLdOhEuIyqrEqJfvn7Xx55iQhJ8Eo4S0vEMjxpit5qUCm+eVmOiMtOU5ekLCy+jePlwCSYJbpcwlZ2TcP/Pej5IUNOVbCY/op7coLNeqRnQTZjFal/5rPgTXPnT7Lq7/TL2ljgkVe712PPq3sGsnLGXJNJGTkTYEzKXn5Rp77SdBMkEw/Z8Sml5JrNW2IQ0anEg5zvTVfppC252Ue+dtG9RsEP/ShD005XcJ8Rj3Tx3kjY66RlFz3+QPBzSmcU3b2AQECBAgQIEBgTAXmLf8t9YoPbIwARJqUKUT5zX59Y9xsVp7pyOf1NLHmuiznN+25eZxuVCSjF6vyLEt9/NzwZ7SpDmT153fke0a7EtQSdmZaMq0uBhlRaz5nNdP9s132T1hp3rivyv4r2zYjRTl2pz5oTvGb7jjpn/RhAmmn0u0aST9l9GW6fTsdLyN59TU3+ZmoTtuv7LOMGsW4n9dKRsUSurq99GJl9RrE+vT1okULB3HokT/mxssWzOk2nlP++bbROd2IDpVfetDSDp/6qBeBpXuw7MXNPgTmosClF55XPTfd6d59ttszkgFpthGdjwCB3gUEpN7tBKTe7Qa5p4DUP10BqX+WjkSg7QJtCkgj9QxS2zte/QgQIECAAAECBAgQaLeAgNTu/lE7AgQIECBAgAABAgRmUUBAmkVspyJAgAABAgQIECBAoN0CAlK7+0ftCBAgQIAAAQIECBCYRQEBaRaxnYoAAQIECBAgQIAAgXYLCEjt7h+1I0CAAAECBAgQIEBgFgUEpFnEdioCBAgQIECAAAECBNotICC1u3/UjgABAgQIECBAgACBWRQQkGYR26kIECBAgAABAgQIEGi3gIDU7v5ROwIECBAgQIAAAQIEZlFAQJpFbKciQIAAAQIECBAgQKDdAgJSu/tH7QgQIECAAAECBAgQmEUBAWkWsZ2KAAECBAgQIECAAIF2CwhI7e4ftSNAgAABAgQIECBAYBYFBKRZxHYqAgQIECBAgAABAgTaLSAgtbt/1I4AAQIECBAgQIAAgVkUEJBmEdupCBAgQIAAAQIECBBot4CA1O7+UTsCBAgQIECAAAECBGZRQECaRWynIkCAAAECBAgQIECg3QICUrv7R+0IECBAgAABAgQIEJhFAQFpFrGdigABAgQIECBAgACBdgsISO3uH7UjQIAAAQIECBAgQGAWBQSkWcR2KgIECBAgQIAAAQIE2i0gILW7f9SOAAECBAgQIECAAIFZFBCQZhHbqQgQIECAAAECBAgQaLeAgNTu/lE7AgQIECBAgAABAgRmUUBAmkVspyJAgAABAgQIECBAoN0CAlK7+0ftCBAgQIAAAQIECBCYRQEBaRaxnYoAAQIECBAgQIAAgXYLCEjt7h+1I0CAAAECBAgQIEBgFgUEpFnEdioCBAgQIECAAAECBNotICC1u3/UjgABAgQIECBAgACBWRQQkGYR26kIECBAgAABAgQIEGi3gIDU7v5ROwIECBAgQIAAAQIEZlFAQJpFbKciQIAAAQIECBAgQKDdAgJSu/tH7QgQIECAAAECBAgQmEUBAWkWsZ2KAAECBAgQIECAAIF2CwhI7e4ftSNAgAABAgQIECBAYBYFBKRZxHYqAgQIECBAgAABAgTaLSAgtbt/1I4AAQIECBAgQIAAgVkUEJBmEdupCBAgQIAAAQIECBBot4CA1O7+UTsCBAgQIECAAAECBGZRQECaRWynIkCAAAECBAgQIECg3QICUrv7R+0IECBAgAABAgQIEJhFAQFpFrGdigABAgQIECBAgACBdgsISO3uH7UjQIAAAQIECBAgQGAWBQSkWcR2KgIECBAgQIAAAQIE2i0gILW7f9SOAAECBAgQIECAAIFZFBCQZhHbqQgQIECAAAECBAgQaLeAgNTu/lE7AgQIECBAgAABAgRmUUBAmkVspyJAgAABAgQIECBAoN0CAlK7+0ftCBAgQIAAAQIECBCYRQEBaRaxnYoAAQIECBAgQIAAgXYLCEjt7h+1I0CAAAECBAgQIEBgFgUEpFnEdioCBAgQIECAAAECBNotICC1u3/UjgABAgQIECBAgACBWRQQkGYR26kIECBAgAABAgQIEGi3gIDU7v5ROwIECBAgQIAAAQIEZlFAQJpFbKciQIAAAQIECBAgQKDdAgJSu/tH7QgQIECAAAECBAgQmEUBAWkWsZ2KAAECBAgQIECAAIF2CwhI7e4ftSNAgAABAgQIECBAYBYFBKRZxHYqAgQIECBAgAABAgTaLSAgtbt/1I4AAQIECBAgQIAAgVkUEJBmEdupCBAgQIAAAQIECBBot4CA1O7+UTsCBAgQIECAAAECBGZRQECaRWynIkCAAAECBAgQIECg3QICUrv7R+0IECBAgAABAgQIEJhFgXnLlpdZPJ9TESBAYAWBJUuWlJtvvrmsv/76ZbXVxvN3NpdccknV/hVgxuiHiy66qMyfP78sWrRojFp9e1NvueWWcvXVV5eFCxfe/uEYLd10003l8ssvL2uuuWZZZ511xqjltzf1uuuuK7kdW2uttW7/cIyWrrnmmnLttdeW9dZbryxYsGCMWn57U/O/gbXXXrv6t/D2T8dn6bLLLiv5t3Dx4sVl3rx5Q2/4eN6NDJ1dBQgQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIiAgDYXdSQkQIECAAAECBAgQaKOAgNTGXlEnAgQIECBAgAABAgSGIjBv2fIylDM7KQECBJYLLFmypCxatJAFAQIECBAgMAcFNl62oGOtzynzJz5fetDSieUsLN1jxZ/z2aUXnlcWL15c5s2blx+HWowgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgNSm3lAXAgQIECBAgAABAgSGKiAgDZXfyQkQIECAAAECBAgQaJOAgHQHe+Ooo44qZ5xxxoyOcuaZZ5avfe1r1bbN5RntPIsbnXPOOeXLX/5yOe6448oNN9ww7Zl/+9vflmOPPXZi/dlnn12++tWvTvw8k4XbbrutfO5znysXXnjhTDZf6Ta33HJLuemmm1a63R3Z4Lrrruu6e84fv3e/+93lpz/9addts/L73/9++dWvflVtN9Pr4i9/+Ut1Lf3whz8s11577UrPcc0111TnOeKII0r2VQgQIECAAAECBDoLCEidXWb8aQLS6aefPqPtc/P79a9/vdq2uTyjnWdpo/3226+88Y1vrG6iP/WpT5U99tijXHXVVVPOfskll5R99923/OhHP5pY9+c//7l85Stfmfh5JgtLly4tX/jCF8pFF100k827bpMQsPPOO5fUbVDlgAMOKEceeWTXwx966KHlS1/6Ull77bWrr64bL1/5gx/8YIWAVF8j0+33xS9+sey4445VMD/88MPLa1/72nLFFVdMt3k577zzynOf+9yq3n/4wx/KK1/5yvLLX/5y2u2tIECAAAECBAiMs8Dq49x4bV9R4Pe//301apRRoHvd617l5ptvLs9//vPLMcccU7bffvuJjRNqMjoyb968ic96XZg/f351zl73b+6XgPTXv/61+VHflzNauPXWW3c9bkbgnvCEJ1RBs+uGPazM6M/nP//58rGPfaw86lGPKrfeemt5zWteUwXvfO9U9t9///Kc5zynvOENb6j67LDDDisf/ehHqxGofvRhp3P6jAABAgQIECAwVwXGLiBdeeWV5Tvf+U5JGLj//e9fnvSkJ5WHPOQhVf9lutfRRx9dfv3rX5csb7755uVFL3pRWX3125my7sc//nG5/vrry7Of/ewp/Z5RlG984xvl4osvLhtttFHZYYcdyqJFi6ZsN/mDhJFMf/rTn/5UMoXrvve9bxVKFi9eXG2akaoNN9ywGmn5+c9/Xu5xj3uUl73sZdUNbwJNRhC22Wabqj31sX/2s5+VE044oapLtn/KU55SHve4x9Wrp3xPPT/wgQ9U4Sgr0+511lmnXH755Stsm/Plxjrnu+yyy1ZYlx9OOeWU8s1vfrMsW7ZsSp0mb5wb/I985CNVW+9973tXyxkd+fa3v13OOuuscp/73KfstNNOE4YJQTn/H//4x2p0Zosttqj64cYbbywZ8Ur57Gc/W7bbbruyYMGCctppp5UNNtigGqV52tOeVhYuXFjisttuu01UJUYJVumrlOmukUyPTL9m2txqq61WjeJMHORfC5/+9KdLroGMHsVy9913LwcddFB5+ctfXtK+lH/84x9VyEkdst2qlFx/aU/CUUr66OlPf3pl0ikgLVmypLLae++9JwJtrtsYJew97GEP63r6hOF8DbLkOlEIECBAgAABArkvHOQvb3PsO93pTiuFvv3Of6Wbzv0N8jzNW97yluoZlYyM/O1vf6umJ2U6VG4685v2E088sfpt+xprrFE9R5KpSPlte0CzvM8++5Rtt922bLLJJtX2V1999QTMSSedVP7nf/6nGmFI8Prud79bTfnKb+xXFpLe/OY3V8Eov+lPWEpQ+8UvflHd+OZmPDfGea7lgQ98YEkoyPpTTz216uSEntxov+Md76jakcCXkPbJT36yuulP0Eu73vrWt5bcwG+66aYTdW4uZNQoXyl5nuh73/teNb0uwaIumRqYgJIb7LhNLgkwqccLX/jCKjxlpCk36QmanUpujhNYn/zkJ5eEwSynXQ9/+MPL4x//+JJg+Lvf/a6ahpf9c7yYxylT/w4++OAq0LzkJS+pbH7yk5+UjTfeuKy33npV2Mx0tTXXXLM6Xp4NuuCCC6ppgc2AlDadfPLJlVW3aySh9S53uUsVThN+O5UHPOABZa211qqCWJwTtNOmZz7zmRMBKfXPZ7vssssqB6RMRayDVn3+XLsJqgkyuVaaJYEuJdvUJSHxzne+cxXUVhaQYpbAqBAgQIAAAQIEBi3Q6Rfv/Txn7n9yH7SyMlYBKTelGWnJSECmdqUkqeZlAw960IOqUYaEpNyYpyR4vOpVr6pGDDJl6uMf/3g1avCKV7yiWp8QlFGcumSk4LGPfWzZb7/9qo9yE5/nPfKMzZ577llvNuV7bvTvfve7l4Sk+sY7N+MJNLk5zc1+Sm7O3/e+91WjBuuvv355+9vfXj0jlHCQkiCR0Y0EpLQzzw+lDikZPcqoSp6Xmi4gVRsu/8+ll15ajXzUo2QZuUrJzXICSkZF6pGtakXjPwkECZH1SFVGcTIlLIF0Jok9h8rI1K677lodNQ5vetObqgCQkJlnaF796ldXgSMbZH2CQS74hKwEwOyfzzMaF78Pf/jDE6OEGZnqVrpdI7HMCyUSjqebZpc6JBhndDLbz+QFCt3qM3ldAk9G9Zol4TgG9XXUXJdAlT7IV7Nkn27PLdXbps9y3Q2y5BcCCgECBAgQIEAg9yuDHEFqzgrrpj1WASlTnzbbbLOJcBSYOrjkxjmh6dGPfvSEV26E65GIjNpkxKm5Pr+Vr8NDbvIy6pJUmpGbuuQ3+hmh6Fbudre7lXe9613V1KyM2uQ5k4yipCSU1CWjR3XH1iMCCWR1WXfddSemw2V0Iin8+OOPr0ZNUrccq74ZTRBo3rw/73nPm7gRznS8vDgg+yQQ5WUMH/zgB6upYve73/3KM57xjPqUU77nws6IVV3illGcvDghwStT4+oSyzoQ1p/lezPA3fOe96xWZQpdSqaTZUpe6pcQlqCSMDJdSZ8m/M60dLtGJh8jfTS5PatyrsnHm/xzpz5KexLqm6X++a53vWvz42q50/ZZkSDbafvJB0jwzNcgS0YYFQIECBAgQIBABgwGGZBmKjxWASnP0tQ33JOBMjUsU6Myta4u6aB0VH47n9GUTAfLjWWz1KMieW4o67N/s2MTEFb2nEmCS0Zd8lzUIx7xiOor0/gyWtIsCVKTS6aPdSp5u1mCWqab5ZgZ7Wq+bS+v586zMHVJ8Jg8UpBA9uIXv7h86EMfqt6ElueKcqy99tqr2i0vI0jgys95xiUldWyOVsQvJdvlmZdMDaxL1nUKSM0+qKeM1c+pvP71r69Cap4bytvkPvOZz1RT4zo9f5PzpE/rY9TnrY9V/1wHjPzc7Rqpt6+/d2rPdAGpec7m+epjdfreqY8yinb++eevsHmm7MWy6V5vkO1zzeb6bQai7FNPp6y39Z0AAQIECBAgQGD5M97jhJBRl3PPPXeFJme6XQJKbtQz5SgjCPVNbkZgEgLy0oCMDGU0Kc8C1SMk2T7rU3KDmhvQ3JBmClhdsn096lN/Nvl7psXl+aWMtGTqXEoCQErzxrr6YAb/SXsOOeSQaipc/exPbpIzGlQf78ADD5xypJy/fuaqXpngl4CY0FJPe6vXJUxk/UMf+tCJUbmEroTNOhT+5je/qQJKbsZf+tKXVl/1/vmev1s005JRpLwgY8sttyxbbbVVVa9Dl79SO1MYM+2xGUynO2ZGQyb/bafmK8a7XSN5hXizdGpPc32WM4KT0jxn83zVymn+06mPMlqWv5uUkFVfVwm+k59Lqg+Zl1xku2yTsJ6SUa/0aT0KWW/rOwECBAgQIECAQCkrPtE94iJ5e1feapYgkBvWhKG8QCHP7GS6VsJJXj6QN5rlRj8jMJm29shHPrKSydSy/N2fvKUtISDPozRLnrPJ1K+8ECGBJM8EZWSl098Rau6X8JXt62dC8pxJRkZSEnZWtWRUKyM5CTC5EU6wyGuhV/ZHVJ/4xCdWbcsoT27AM4UsL0nI53nmKAGh+RW3TDHMZ82RrISW7J8RsDyPE/dOoxur2q4cI6NY6Zf4xybPGGVKYNbVz+ZkSmNz+mDzPKlvRlPy6vLUMX2Vt9rVpds1km3imhGcmT5EmHqlfnHIefMHcXPN9VryLFlKXtiRvk3gz7TMhPi6ZF09Wpj6PvWpT62eA4tJroVc4xkxTL0UAgQIECBAgACBFQXGagTpwQ9+cPU8TX4zn1dCZ9QnIyz1CwXyWua8BCGve85v3TM9LcEio0IpeWFDwk5enpCb0/xGPsesS0YxchOcZ3YSUjLilFGGTG/rVjIi9axnPav6OzWZ5pZz5y1reblAQly3Z2w6HTf754+HJsB961vfqoJRwlteIJDjTVcSEPO3cvIyihhlWlym+v3/9u4CTo4i7eN4xYEIkAQSLAR3dw8uhx8eXMLh7naBBILb4Rbc3TnkILi7h+DBEl4gASKk3/o/d9XbM5ndmdmd2e7Z+dXnk2xPa/W3emf76ZIO/bQa2y45XwGIAjPdgCuA0blrUIdKJNUQacAGBUg6HwWVqpkaMmSI7V5BmvpkqT+XBq4o5KZR2zTC3rBhw+yfmhFqCG7V9CkVu0bU50nXhIJHjRRYStLgG0OHDrW+W8qjjEOeS9k+uY4CLtUEDh482IIk1extueWWVqsW1pOPmhyGEeo0rfXD0OcK+A844ICwOj8RQAABBBBAAAEEEgLtfJOrunsJiU5ZAwboCXqhZlnqn6H5oZlYwssmdeOvGijVLhVKqpkopy9L2IdqeBSAhYAszG/JT9WEKVBT0FRqUv5Vi6WarWR/oFK313oyVN8f9QGqRlIgqnJQkJuftEyBROgflr9cn1WTovVkUyg1dY2onBSc5ffZKrSfME8Bdbjm8vtEhXXK/amBL3QNl7o/lYlMkrV95R6zGutrkIbevYsPuVmNY7NPBBBAAAEEEGiZwNxR7ki5YW8j3X+7GejzlIty36k4Zf/cz1rnx29HWYulQvfmWt6aqS4DpNYE5lgIINC0AAFS0z4sRQABBBBAIMsCbTFAqqs+SFm+uMgbAggggAACCCCAAAIIpC9AgJR+GZADBBBAAAEEEEAAAQQQyIgAAVJGCoJsIIAAAggggAACCCCAQPoCBEjplwE5QAABBBBAAAEEEEAAgYwIECBlpCDIBgIIIIAAAggggAACCKQvQICUfhmQAwQQQAABBBBAAAEEEMiIAAFSRgqCbCCAAAIIIIAAAggggED6AgRI6ZcBOUAAAQQQQAABBBBAAIGMCBAgZaQgyAYCCCCAAAIIIIAAAgikL0CAlH4ZkAMEEEAAAQQQQAABBBDIiAABUkYKgmwggAACCCCAAAIIIIBA+gIESOmXATlAAAEEEEAAAQQQQACBjAgQIGWkIMgGAggggAACCCCAAAIIpC9AgJR+GZADBBBAAAEEEEAAAQQQyIgAAVJGCoJsIIAAAggggAACCCCAQPoCBEjplwE5QAABBBBAAAEEEEAAgYwIECBlpCDIBgIIIIAAAggggAACCKQvQICUfhmQAwQQQAABBBBAAAEEEMiIAAFSRgqCbCCAAAIIIIAAAggggED6AgRI6ZcBOUAAAQQQQAABBBBAAIGMCBAgZaQgyAYCCCCAAAIIIIAAAgikL0CAlH4ZkAMEEEAAAQQQQAABBBDIiAABUkYKgmwggAACCCCAAAIIIIBA+gIESOmXATlAAAEEEEAAAQQQQACBjAgQIGWkIMgGAggggAACCCCAAAIIpC9AgJR+GZADBBBAAAEEEEAAAQQQyIgAAVJGCoJsIIAAAggggAACCCCAQPoCBEjplwE5QAABBBBAAAEEEEAAgYwIECBlpCDIBgIIIIAAAggggAACCKQvQICUfhmQAwQQQAABBBBAAAEEEMiIAAFSRgqCbCCAAAIIIIAAAggggED6AgRI6ZcBOUAAAQQQQAABBBBAAIGMCBAgZaQgyAYCCCCAAAIIIIAAAgikL0CAlH4ZkAMEEEAAAQQQQAABBBDIiAABUkYKgmwggAACCCCAAAIIIIBA+gIESOmXATlAAAEEEEAAAQQQQACBjAgQIGWkIMgGAggggAACCCCAAAIIpC9AgJR+GZADBBBAAAEEEEAAAQQQyIgAAVJGCoJsIIAAAggggAACCCCAQPoCBEjplwE5QAABBBBAAAEEEEAAgYwIECBlpCDIBgIIIIAAAggggAACCKQvQICUfhmQAwQQQAABBBBAAAEEEMiIAAFSRgqCbCCAAAIIIIAAAggggED6AgRI6ZcBOUAAAQQQQAABBBBAAIGMCBAgZaQgyAYCCCCAAAIIIIAAAgikL0CAlH4ZkAMEEEAAAQQQQAABBBDIiAABUkYKgmwggAACCCCAAAIIIIBA+gIESOmXATlAAAEEEEAAAQQQQACBjAgQIGWkIMgGAggggAACCCCAAAIIpC9AgJR+GZADBBBAAAEEEEAAAQQQyIgAAVJGCoJsIIAAAggggAACCCCAQPoCBEjplwE5QAABBBBAAAEEEEAAgYwIECBlpCDIBgIIIIAAAggggAACCKQvQICUfhmQAwQQQAABBBBAAAEEEMiIAAFSRgqCbCCAAAIIIIAAAggggED6AgRI6ZcBOUAAAQQQQAABBBBAAIGMCBAgZaQgyAYCCCCAAAIIIIAAAgikL0CAlH4ZkAMEEEAAAQQQQAABBBDIiAABUkYKgmwggAACCCCAAAIIIIBA+gIESOmXATlAAAEEEEAAAQQQQACBjAgQIGWkIMgGAggggAACCCCAAAIIpC9AgJR+GZADBBBAAAEEEEAAAQQQyIgAAVJGCoJsIIAAAggggAACCCCAQPoCBEjplwE5QAABBBBAAAEEEEAAgYwIECBlpCDIBgIIIIAAAggggAACCKQvQICUfhmQAwQQQAABBBBAAAEEEMiIAAFSRgqCbCCAAAIIIIAAAggggED6AgRI6ZcBOUAAAQQQQAABBBBAAIGMCLSLfMpIXsgGAgjUocCYMWPcxIkTXZ8+fVz79vX5zOb777+386/D4rdTHj16tOvUqZPr3bt3XRJMmjTJ/frrr65Xr151ef4TJkxwY8eOdV27dnU9evSoS4Px48c73Y5169atLs//t99+c+PGjXM9e/Z0Xbp0qUsD/Q50797dvgvrEeCnn35y+i7s27eva9euXeoE9Xk3kjo7GUAAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikIkCAlAo7B0UAAQQQQAABBBBAAIEsChAgZbFUyBMCCCCAAAIIIIAAAgikItAu8imVI3NQBBBAwAtMmjTJTZkyxXXu3Nm1a9euLk0mTJjgunTpUpfnrpPW+avsdQ3UY9L1/9dff7lOnTrV4+nb77++Bzp06OA6duxYlwYqf92O1ev5T548Of4daN++Pp/dh9+Bej3/iRMn2u9AVv4WEiDV5VcxJ40AAggggAACCCCAAAKFBOozTC8kwTwEEEAAAQQQQAABBBCoewECpLq/BABAAAEEEEAAAQQQQACBIECAFCT4iQACCCCAAAIIIIAAAnUvQIBU95cAAAgggAACCCCAAAIIIBAECJCCBD8RQAABBBBAAAEEEECg7gUIkOr+EgAAAQQQQAABBBBAAAEEggABUpDgJwIIIIAAAggggAACCNS9QH2+ka3uix0ABKor8OWXX7rnn3/e9ezZ06288squW7duTR7wt99+c88995zTzxVWWMH169cvZ/1iy3NW5kPqAnrp5Ztvvunef/99t+CCC7rllluuaJ6+/fZbN2LECHtZqK6ZWWedNd5G5f/CCy/En8PEmmuuWbcvVw0GWf1Z7jWg3//x48fnnM5CCy3k5phjjnheud8r8YZMpCJQzvf2v//9b3thcH5G9bdjlVVWsdmlXCP52/M5fQF9F9xwww1uiy22cD169GgyQ8WumWLLm9x5mQt5UWyZYKyOAAJNC1x//fXuyiuvdGussYbTTe+ECRPcBRdc4GacccaCG44aNcrtsccebu6553azzTabBUpDhgxxK664oq1fbHnBnTIzNQH9MfzHP/7hRo8e7VZddVUrTwUyhx56aKN5OuGEE9xLL73kVlttNafy/uKLL5yugZVWWsm2efbZZ93xxx/vevfunbOPa665xnXv3j1nHh/SFyj3GtD66623npVlx44Nz20HDRpk83VG5X6vpK9Q3zko93t7hx12cBMnTsxB++mnn9wCCyzgLrvsMlfKNZKzMR8yI3DhhRe62267zd166605D77yM1jsmim2PH9/Lf4ckRBAAIEKCfgb28jfDEdvvPGG7XHSpEmRD36iSy65pNEj7LXXXtG5554bTZkyxdYZPnx4tM0228Sfiy1vdMcsSEXgpptuirbbbrto3LhxdvzPP/888oFP9OGHHxbMj+avvvrq0ffffx8v/+c//2n7CDOuvvrqaN999w0f+ZlxgXKvAX/jE/lgOvI3xAXPrDnfKwV3xMxWE2jp9/Zrr70W+Yds0VtvvWV5LnaNtNqJcaCSBb777rvo8MMPj9Zaay37/f7mm2+a3LbYNVNseZM7b8ZC+iC1OMRkBwggEARefvlle0K05JJL2iw9Dd5ggw2cmk8USmPGjHEffPCB22yzzVy7du1slY033thqntQ8q9jyQvtkXroCqu1Zd911XdeuXS0jc845p1t00UUbvQZ+/vlnq0GceeaZ44wvtdRSzv9xdf5vms375JNP7ElyvAITmRYo9xpQ+ap2sFevXgXPq9zvlYI7YWarCbT0e/v33393p512mlOt0uKLL275LnaNtNrJcaCSBYYNG2bf4aeffnrRbYpdM8WWFz1AM1ZoqMtuxsZsggACCCQF1KxKzeSSSX1J1FTC1xC59u1zn8noJlgp2d9EN0mdO3d2P/zwQ7ybxpYvssgi8TpMZENA10CyvJQrfU6WZzKnakoZmlOG+U888YRT/5MQNOvmqEuXLu7oo492vsbJlu2///5TXWthe36mK1DuNfDpp59a87pzzjnHmmSqOe7OO+/sfM2inUi53yvpnj1HL/a9Xux7+9JLL7Xf99133z3GLHaNxCsykRkBfV/36dPHmkwXy1SxayZsn/zbkrxXKHZNhe3L+Zl7t1LOlqyLAAII5AnoSy6/E6b6iCg4+uWXX/LWdtZPRTe++pdM2kY1C7oxamp5chum0xeYPHmyBcP514A+jx07tqQMqp26b1bjDjroIFtfnXJ1XSnI3nTTTd2ee+5p18V+++3nfDO+kvbJSq0n0Jxr4OOPP7brY/7553dHHHGEBb7HHXdcPDBHud8rrXe2HKmQQEu+t/X7/uCDD7qtttrKJfujFbtGCuWDeekKKDgqNRW7ZootL/U45axHDVI5WqyLAAJNCnTq1MnpBimZwufpppsuOdumC62vBeqQq/WLLZ9qh8xIVaBDhw5WSxjKPGRGn0OTuzCv0E/f18jdeOONbujQoXGTOo1idfvtt9uIiKpZVFp44YXdLrvs4lTTpOaZpOwINOca8H3O7CFKGMhFNYqqMVCwrIE6Cn0PhGus0PdKdjTqMyeFyksS4Xu9KZXHHnvMAiMN2pFMxa6R5LpM155AsWum2PJqnDE1SNVQZZ8I1KmA+hHoCWAy/frrrzaCXX4tkdbR+vqjqTbnyaRtZplllqLLk9swnb6AmsRpaPdC10Dfvn0bzaBqGM8880y7IT7rrLPiYX21gfapbUNwpHka8XCmmWaymiR9JmVHoDnXwPTTTz/VKJcKjPTUWKnc75XsaNRnTop9rzelcv/997sNN9zQHpAl1yt2jSTXZbr2BIpdM8WWV+OMCZCqoco+EahTgbnmmsv6iISnu2J47733Gu0rMvvss9vTQq0TkgZt0A2z2hoXWx624Wd2BBS8JMtTOdOAG/l905I5PuWUU6w5lR/t0GmAhmTyo+BZbdFXX30Vz9aN848//tjkPuOVmWh1gXKvgaOOOsrdcccdOflUM8vQ36Dc75WcHfGh1QWa+72tjvgjR460V0TkZ7rYNZK/Pp9rS6DYNVNseTXOlgCpGqrsE4E6FVhnnXXszNVMSkHOZ5995h566CG30047xSLPPPOMe/jhh+2zngqqKYXeZ6P+JH/++ae9Q0kj36mGoNjyeKdMZEZAfQcef/xxC4o0Ct2dd95p7zfZaKON4jzq+ghBlK4Frb/rrrtazZNujMM/1S7279/fTTPNNE4dt0O/tIsvvthqHNZee+14n0xkR6DYNaD3XOkaCDWNCor1niMNxqH3puma0WAcfrh/O6lSvleyc/bkpJTv7eTfgSCmhyFKCojzU7FrJH99PmdfIHkNFLtmii2vxtnyothqqLJPBOpYwL8DyQ0ePNiazU077bTWRyQ5GtGJJ55ow3jrZbJKuunV+ropVjO8JZZYwqmDdujoX2x5HVNn9tTVl0g3vGo3rpojDaiw7LLLxvnVC2H1MtmBAwfaEN/qgF0oPfroo9bURjfLJ598sl03Wk81FOqT0K9fv0KbMS8DAk1dA0899ZTT90B4ceQff/zhVIs4YsQIa0qp74EDDzzQXhEQTqXY90pYj5/ZECj2vZ3/d0C5VmB87bXXuvvuu2+qkyjlGplqI2ZkQkAPRHbcccf49z1kKv8aKHbNFFse9lupnwRIlZJkPwggkCPgX/xptUD5Q3vnrJT4oH5H6uDdWGf+YssTu2IyAwITJ050KjO1Ha9U0kh2Crr0NJGUfYFyr4Hx48dbrZJGvwpDvOefZbnfK/nb87l1BSr9vV3KNdK6Z8jRKi1Q7JoptrxS+SFAqpQk+0EAAQQQQAABBBBAAIGaF6APUs0XISeAAAIIIIAAAggggAAClRIgQKqUJPtBAAEEEEAAAQQQQACBmhcgQKr5IuQEEEAAAQQQQAABBBBAoFICBEiVkmQ/CCCAAAIIIIAAAgggUPMCBEg1X4ScAAIIIIAAAggggAACCFRKoGOldsR+EEAAAQQQQMA5veD266+/dnoP2Mwzz1yQRC9JHTt2rOvbt6+9/6vgSlWYOXr0aNvrLLPMUoW9V3aXetGwXig8cuRIN//887uFFlpoqgNo6HcN/aw055xzTrU8zNDQwHqPSseOHe3dXGE+PxFAAIFCAtQgFVJhHgIIIIAAAs0U0Lt6+vfvby+01c19oTR8+HBb55VXXim0uGrzNtlkE7fRRhtVbf+V2vGkSZPcGmus4RZbbDG3+eabu7PPPrvgrg855BBzlPfbb79dcB3N3HPPPW29lVZaqdF1mlrwzjvvuPBy66bWa8kynfMZZ5zhfvzxx5bshm0RQKACAgRIFUBkFwgggAACCOQLqGZj9913d6oJIZUn8Pjjj7sRI0a4gQMHujfffNOdcsopTe5AL5a97bbbCq4zbtw498ADDxRcVurMZZZZxr300kulrt6s9c4880x31FFHOb1gl4QAAukKECCl68/REUAAAQTaqMA000zjnnnmGXfhhRe20TOs3ml98803tvNBgwa5JZZYwhVrEqiaodtvv71ghu677z5r9jjvvPMWXF7KzMmTJ5eyWovWaY1jtCiDbIxAHQnQB6mOCptTRQABBBBoPYGdd97ZPfnkk+6YY46xZm1N3aC///777tZbb3U77bSTS6731VdfWdMuNTNbaqmlLPOXX36569mzp1t11VXddddd515//XULInbccUc3xxxzuBdeeMGChT///NPtsMMObpVVVnGqYUkmBSCXXHKJ+/jjj60Z26677mrbJtfRtJqWqWbmgw8+cP369XMbb7yxW2utteLVPvzwQ3fzzTe7/fff31166aXu888/d9tss41bf/3143XyJ9SsUOc6atQoa/a24YYbunXWWSde7aKLLnIPPfSQfb7hhhvcE0884Y477jjXuXPneJ38iW233dYddNBB7q233jKL5HLlb4MNNnDqf/Xdd9/Fi0oxn3XWWd3FF19stYCvvfaaO+mkk6y5npyVlE/VdH3yySduhhlmcIsssojba6+9XLdu3eLjqLxmnHFGt+aaazo1rXz11Vct4Nt6663dyiuvbOvJQ9eK0llnnWVlretnypQp7u6773aPPPKI9VlTXyw1kVxttdVsXf5DAIEqCfiqfxICCCCAAAIIVEjABx9qUxcdfPDBkb95jtq3bx/5YCbygzfER7jgggtsHS1XuuOOO+zzww8/HK+jiWeffdbmX3311fH85ZZbLvJBTzTXXHNFc889d+T76dg6/uY80np+IILIB1O2XPnwwUu8rW8qFvXp0yfyg0NESy+9dPT3v/898jfvUa9evaLnn38+Xk8TPuCJfFBi/3zfJVtf+zv88MPj9e655x47tr/Zt58617333jtenj/hm8pFPlizfGsb5Vn7TG6z2267RT4QsPnLLrtsNGDAgOj333/P35V99kGhrecDSTvvY489Nmc9PxCG5f+mm26K5OYDm3h5KeafffaZHV959LVYNv3uu+/aPnzwacdWXrfccksz1XrzzTdfNGHChPg4Oq7Kf4EFFoi6d+8e+b5VUdeuXaMOHTpYuWvFE088Merfv7/tzwdN0RFHHGHbH3jggealMt5qq60iH7DZ53POOSfePxMIIFB5AT0VISGAAAIIIIBAhQSSAZJ26QcSsBvfc889Nz5CSwOk/EDl+OOPt2PoBtzX0NhxfF+WSAGRbsZD0mdte9hhh4VZ0RdffGE390suuWTkayxsvq8RscDC13pEftCAeF1fk2Pb+z5CNi8ESL179478iHORAhJfSxOvn5x47rnnLFjcbrvtIuVNScc79NBDbZ+33HJLvLqv3bJ5vtYmnldoIgRIf/zxR+RriSw4Sa7nB1aw8/f9kJoVIIV9KajzAz2Ej5Gv7bH8HXnkkfE8ncs+++xj832zvni+AiSZK+gJgZ6vuYt8LVPkmwbG6w0ePNjW8yMg2jw/8p4FUfvuu2+8joJsBUsKcn2TvHg+EwggUFkB+iD5by0SAggggAAC1RIYOnSo87UKztduWFOsShxHTeaSAxeEkel88OF8rYsdvtDctgAAHN9JREFUolOnTta8ToNFjBkzJj6smuclt1XTOV9TYYMhqLmekpqVabCAo48+2vngJ97WB1ZO+1UzuGRSs7KFF17YmpL5m/fkonja1245X2vizj//fNuHFug85KPh0P/1r3/F6zZnQs3s1NRNgzqE5IMup5H7fJAYZlXkp6+9c75Wypr+hR3qXHxNkn3MH4muS5cubsiQITb0u1bQ9aC+VT44DZsX/Olr5Gyo8zA8uz4//fTT1pRRliQEEKiOAH2QquPKXhFAAAEEEDABvQ/pmmuucauvvrrzzcds4IaW0qhvjAaBCGmmmWayyfx3AU0//fQ2X+9mCkn9ZJSnZPK1R/bxo48+chqxTT91w6/+M/nDW0833XTWdym5vfrGFEvqx6T85b8bSuehYOGNN94otosml6uflm+qZ/2vdD4//PCDe+qpp9xdd93V5HbNWdjfDyuuf+pPpb5JOjf9e/HFF213+SPRqc9Sfh8qOagfVGPJ1wY6DWOuob9nm20255tEOvXX0nmqjEgIIFA9AWqQqmfLnhFAAAEEEDABDZTg+yQ538zMnXfeeSWrJAOb5Ea+z1DyYzytF6Emk290kvxo0z169JhqXhhUQAM7KOkFrKr10P5Ua5H8pwEPVlxxxZx9NJaf5EqqxSp0bK2j4+s9QC1JGiRBg0OE4b41qp2CDOW3nNSYeXIfevGsAt7ll1/e+SaCFihpcA3fPyu5WjytoDI/KQAtVD7J9U4//XQbCEKDbXz55ZdWC6Uawl122cUx6l1SimkEKiuQ+01a2X2zNwQQQAABBBD4n4CaWOl9PL6/kL0fKQkTmkvlBwm6Ka5ESt6IJ0dyC/sOTb3mmWcem+UHf3Avv/yyO/nkk11+7ZBuzPMDsbCfpn5q3429S0ij34VarKb2UWyZmtlpND+NZqdAyQ9CMVXNTdhHS8w1qp5Gr7viiissWFGzQyU/8IP9THrbjGb+p2BtvfXWs5oj7VMj4CkI0+iFGuVu7bXXbuae2QwBBJoSoAapKR2WIYAAAgggUCGB0NTOj3BmQ2wnd6vaDyU100qmMPRzcl5Lp9WUbeTIkTm7ufbaa22Y6hCkqMZLSTfiyfT2229bbY+G1C43aZ+qRbr33ntzNlV+1G8oDGOes7DMD5tuuqk1PVR/Jj8CoNt+++0b3UM55gqmks3m1LROtUKqyQnBkQ704IMP2vGaU7sTArZwHJmo75Qf3MP2qRonP+CDDamuGYUCXVuR/xBAoMUC1CC1mJAdIIAAAgggUJqA3nujfiVnn312zgZqqqUbdg1YoHfmqLZFfWdU41TppBtxNUVTU7/ZZ5/dBlzwo9I5P3S0C32W1JdHAzVoHfVv0nuKVCujWjA1h1MtWLlJ560+Tbv6dy7pXT+y8ENmm4cGPdAAEC1NalKnfjpXXXWV02ARAwYMaHSX5ZirTNSfSSYa9EGBpGrD9I4rWSnwu/766+2dUDrgL7/80uhxG1ugYyiddtpp9q4j9TVSDdGwYcNscAu9f0p9lk499VQrA50nCQEEqiNADVJ1XNkrAggggAACBQUUZPh34uQsU22Emmepj86gQYPsxlg34ApcKp3UJ2eLLbawEddUa6OR3hQIKYAJSbUiGi1No+OpSdeiiy7qBg4caP1e9OLVMChEWL+Un6pBUx8s1STpHDXqnQat8MNWW/ChYK0SSc3s1BxNL2INtTKF9luOuQJCBUH77befvbhWQYof9tuCIjVB1Et71RxSL87170uy8yl0zKbmKb8KvNRsT/3VlFR7pL5N6uekZSoDNW/UYBAajZCEAALVEWjnv0Sm7sFZnWOxVwQQQAABBBAoIqD+OKqlSQ6vXWSTZi327+Rx/gWrdgPeVCChJl+ffvqp1S5p9Dw19Wpp8u8tsqGqdfOfbKLW0v02d/tSzNUfyL/nycolGPh3H9mIfhqdL39kwObm5eeff7Zmgsn9adAMDfXd34+cp1oyEgIIVFeAAKm6vuwdAQQQQAABBBBAAAEEakiAJnY1VFhkFQEEEEAAAQQQQAABBKorQIBUXV/2jgACCCCAAAIIIIAAAjUkQIBUQ4VFVhFAAAEEEEAAAQQQQKC6AgRI1fVl7wgggAACCCCAAAIIIFBDAgRINVRYZBUBBBBAAAEEEEAAAQSqK0CAVF1f9o4AAggggAACCCCAAAI1JECAVEOFRVYRQAABBBBAAAEEEECgugIESNX1Ze8IIIAAAggggAACCCBQQwIESDVUWGQVAQQQQAABBBBAAAEEqitAgFRdX/aOAAIIIIAAAggggAACNSRAgFRDhUVWEUAAAQQQQAABBBBAoLoCBEjV9WXvCCCAAAIIIIAAAgggUEMCBEg1VFhkFQEEEEAAAQQQQAABBKorQIBUXV/2jgACCCCAAAIIIIAAAjUkQIBUQ4VFVhFAAAEEEEAAAQQQQKC6AgRI1fVl7wgggAACCCCAAAIIIFBDAgRINVRYZBUBBBBAAAEEEEAAAQSqK0CAVF1f9o4AAggggAACCCCAAAI1JECAVEOFRVYRQAABBBBAAAEEEECgugIESNX1Ze8IIIAAAggggAACCCBQQwIESDVUWGQVAQQQQAABBBBAAAEEqitAgFRdX/aOAAIIIIAAAggggAACNSRAgFRDhUVWEUAAAQQQQAABBBBAoLoCBEjV9WXvCCCAAAIIIIAAAgggUEMCBEg1VFhkFQEEEEAAAQQQQAABBKorQIBUXV/2jgACCCCAAAIIIIAAAjUkQIBUQ4VFVhFAAAEEEEAAAQQQQKC6AgRI1fVl7wgggAACCCCAAAIIIFBDAgRINVRYZBUBBBBAAAEEEEAAAQSqK0CAVF1f9o4AAggggAACCCCAAAI1JNCxhvJKVhFAAAEEEEAgRYHJ7aZplaN3jP5sleMkDzLloumSH6s23X6/36u278Z33K3xRRVfMq7ieyy2w3lcl2KrVGT5SDehIvspZyft2pWzdsvWjaKWbd+WtqYGqS2VJueCAAIIIIAAAggggAACLRIgQGoRHxsjgAACCCCAAAIIIIBAWxIgQGpLpcm5IIAAAggggAACCCCAQIsECJBaxMfGCCCAAAIIIIAAAggg0JYECJDaUmlyLggggAACCCCAAAIIINAiAQKkFvGxMQIIpC0wZswY98UXX7iJEyc2mpWvvvrKff/9940ur8aCP/74w/Kln7WQ/u///s89+uij7oknnnC//96yUbb+/PNPO/fm7Ofbb7913333XauR1Vo5VQJmwoQJVj7jx4+vxO7YBwIIINDmBAiQ2lyRckII1JfAMccc4/r37+8OPPDARk98ySWXdAMHDmx0eTUWKNBQvh577LFq7L6i+3zwwQddr1693AYbbODWWWcdN3bs2IL7f+edd9yVV15ZcFly5n/+8x8794ceeig5u6Tp9ddf322++eYlrVuJlWqpnCpxvtrHq6++auVzxx13VGqX7AcBBBBoUwK8B6lNFScng0D9Clx++eVuq622shv8+lVo3pmffPLJbppppnG3336769evn5t99tkL7miZZZZxu+yyi9tzzz0LLg8ze/fu7dZdd13Xp0+fMIufCLSKwN133+1mnHFGN2DAgFY5XmsdZNSoUe6ee+5xHTt2dBtvvLGba665WuvQVT/OTz/95O666y4X+Zfw6AGJHiy1xXTBBRfYdbn44ou3idN7++23nR6aJVPfvn3d2muvnZxVs9PUINVs0ZFxBBBICnTp0sXtscce7rfffkvOZroEgW+++catsMIKbqONNnKLLrpoo1tMnjy50WXJBcsuu6zVnK222mrJ2UwjUFWBZ555xm277bbu5ZdfrupxWnvnW2+9tVtiiSXc66+/7q655hq38MILu+bUzrZ2vks53m233ebmnHNO98gjjzjVaOo8Vavb1pJq3g866CD31ltvtZlTO/PMM92+++7rjjvuuPjfVVdd1WbOjxqkNlOUnAgC9S1wyimnuCOOOMIddthhTrVJTaWLLrrIde7c2e211145q1133XVOTzMPPfRQm6/99OzZ06266qpOy3SDoj/gO+64o5tjjjncCy+8YLUu6nOzww47uFVWWcW1a9cuZ5/6cOutt7qHH37Yamn0dE03PPlJT+J0s/DBBx9YLY6eEq+11lo5q11yySVu5plntmPrHBZaaCELCmeaaaac9cIH9a/RH2Y1qfrrr78s7zrnGWaYwVZ5//33LW/qf6Qg6aSTTnIrr7yyPcUN+9BP9d+6+OKL7Qnva6+9ZuupFkl9WG6++Wa3//77u0svvdR9/vnnbptttnHzzDOPu/766+1mVTdzIemmbsSIEe6TTz6xPCyyyCJWBt26dQurTPVzypQpTrUCuoFS07/555/fArlSgq9i559/sGLlpL5s8pTb9NNP7xZbbDHzz8+/AkndyOpGXf2wllpqKTtPbRNSobJUM0eVw/HHH281BWFd/bzsssuc+g4lm5KWcs1oW5mrGeXo0aPt6e7cc8+t2W0mTZo0yZ122mnu1FNPLfj7V8snqu8cXf/63Qo1u/quOfjgg+33oJbPTf1Gjz76aKfv7vCdu/vuu9v131ZqIVQ+n376qTv22GOdHuK1pfTGG2+4IUOGuAMOOKAtnVbDufgqTRICCCBQswL+hj/y32jRzz//HK233no27QcbyDkfH+RE/g9uPM/XkkS+xiT+HCZ8/5vINzELH6Plllsu8kFP5JuzRP6mMvI3xLZ/f2MfXX311ZFv7hL5m19brjz4QCHe9v7777d1ff+nqEePHtGWW24ZLb/88jbP94eK19OEDy4iH7DZv0022SRaeumlbb3DDz88Zz3tyzcdinxAFLVv397+ff311znrhA/+RjvyTVVsn765W+QDrqhr167RbLPNFvmAyVZ7+umnbX86tr85t2l/4x52Ef/87LPPbJnOcZZZZrHpd999N/JNfiyfPuCzn8rT3nvvHflg0D77JnvxPvxNnc3zAY5Z+KYY9nm++eaL/I1/vF5+2fiAIPJBp9n7JpTRrLPOap/POeeceJtCE6Wcv7YrtZx8UGdGPriMfE1b5AM0K38fDEY+qI6z8MMPP0S+Bi0+V9+fKtI2/il59N5778XrFSrLs846y7Z74IEH4vU04QNUO5a/EYnnl3rNnHHGGbZPH9ibu8o5XF/Dhw+P91fqxCTXJWqNf6XmR+v5Bxnmq+tO18/pp59ezubxun/9a9qoNf7FByxhwj9UiIYOHZqzps5Xv7P+4UHO/KY/dPWLW+tf0zkJS/0DlsgHf9Gvv/4aZkU+YLLvrXhGiRNzR52j1vhXYnbi1Xzwbn9rfPM6+/7wD47iZaVO+K9d/zvcOv9KzZN/+BR16NAheu6550rdpObW0xNBEgIIIFCzAiFA8rUg0ZdffmnBiK/diX755Zf4nFoSICkoSAYq/um+3XB27949euWVV+wY/klo5PvnWAASDhpuvH2NT+SfIIbZkR9UwrbXjYGSbrx1s7PmmmtGP/74Y7yeb7Zg6z3++OPxPN1UKz/+aWvkayaiDz/8MF6WP+EHXIimnXba6KWXXooXffTRR5HvF2Q3kfrDHZLmKTArlhSo+JqjeLUQIPk+R3bz72t4Ij8C3VQB0pNPPmn5PvLII+NtdXO3zz772Pz77rsvnp8MkHTjpD/CvhlHvNzXhFmwpDz7mpp4fv5Eqedfajn52kkrJ1+LFB/K1/hZ/i+88MJ4nn8CbvN8n4p4nh9l0QJLBVUhFSpL3zzUrqHtttsurGY/zzvvPNunr02wz6VeM77JWewXbqb9KIEW7Os6aisBkq8Zi/Q7qNTWAiQ7qbz/fM2yPbjJm13kY2sFRzpO+UllqOtRD5POPffcsnfQGsGRjlFuOvHEEyM9oNLvnx5OtJUASX/79B2iv4d64KIHRUcddVSkwKmtJPog+RImIYBA2xBQszdfs+DUFEpN7SqR1GROTUBCUj8dJX8T69TXRqlTp07WvE5NzjTseDKp6YianIV0wgknWPOy0FZbTddCUxMNbhCS8q/9qildMvlaGuefKDsf/LgFFlgguSie9rVK1iRNzel8rVU8X83T/B8x52t/nK89iue3dELHUVM6dY4vNDCDOpTfdNNN1k49HEuuvlbNPvrAMMye6qfO19e8WPMwLdRn5V1NjnzwNNX6mtGc8y9WTjquyunZZ5+15oo6jppKqtmamhgqqamimtattNJKbosttrB5+k8DX6hZlJq6qWNzSPllqaZ62qcPGHP60qm5opp2qqmeUqnXjDr1y0jXr7yVfA2gNWuyD23kP3UM1+9KPSQfPDj1tTr//PPb1OlqlNFBgwY5X0PcqqNYVhNRTbDVlFbfCeH3r5rHa819v/nmm3Y4NWP2Nd/WnFrNgP1Dr9bMRlWPRR+kqvKycwQQaG0BDdSg0djUV0Sj2mlUpJYk/cHWCG8hhf4+6licTKF/ifr6JJNvppf8aIGNAhVfm2Pz9VN/PNXfSXlOpummm859/PHHyVnW/yiZn5yF//ugfkxKyeDof4tsMAZN+9qnio02pPNpKvX3o1Lpn3/q6NSHSfnTvxdffNE2U+BRKPlaOnfIIYc430zM+aaBzj+pdBtuuKHdQGlEvcZSc86/WDnpurrhhhvc9ttv7/bbbz8bpe9vf/ub22yzzeJsqG+Vf3rqfM2X9cWKF/gJBW1KKs8wipUC+vyy3G233dzw4cOt38nOO+9s/Z1k5muRbHv9V+o1ow7h6reifnTJ1JRdcj2msyUwePBg55sP2ohvba0MNTCD+n+q/536JvrWAPbqgWyVQOm5GTdunPVV1ch1+u5qa0n9cPVKCH2vK/kWENZvUiOinn322VN959hKNfYfNUg1VmBkFwEEigso0FDAooEEfFO74hv8b4384Eaz1XG+UNJwu8mkG+NCyTcZmWq2agr05E1JNwXqvKv9qUYh+U/vJVpxxRVztm8sP8mVQi1WY8fWuurYXqlULE8KGFZffXUL2FRTo0Bp3nnndb7pYtEs6IZQgzuoBkY3TeoUrJo7DTfe2Kh6zTn/xqxCOfm+Uhbc6fiaVhCuAEbTvh2+nYfKUkm1e8ly1LRqkTTCmoK+kAq5yUk2CsaUVHuk2pHke7xKvWbkkD+AhPaZHzBpHim7Ar55lvN9+6x2XIO9+Oaw2c1sC3KmGnTVjuv3utZH6dMDL730WjXnm266qf3T96BaOGgwoVpPerATgqNwLnp4paQXt7eFlPsXvi2cEeeAAAJ1L6Cn5vpDpKf+uiHPT2p2VChA0A14S1N+oOT75Ey1S/0B0U2wkkYU02hnevKWXxOjG4X8QGyqnRWYEZr0qRlafgrzfB+Y/EVV+6xhYNW87IorrrDAJjSHCi8qzTdLZkRBqx98w2qOtJ5G5FNgpVEFFaAUGu2qOedfrJyUJzUhDEPaakQ9BUka5lYjcen8wuhwKscbb7wxeRrWLK+xJoE5K/oPu+66q40U6Ad8sBss3RAnm1+Wes2ojNXMLj/pxo1UOwI77bSTNatTIO77WNVOxovkVDW9egj01FNPxb87aqas7z0FhbWc9NoEfVckk+9PaueZHNkzubyWpn2/S3uVg+/DGWdb34F6GJQfOMUr1NgENUg1VmBkFwEEShPQcLH64+tHm7O+IcmtNMy1ghQNwRySH6mtKk++dBOdTOrDMnLkSDdgwACbraHBlXTDn0zqq6Kn/3p3RrlJw3/rZl5NtfKDD3koNSdA0g1+Y83hmsqjaozUXFC1PiE40voaelqpsZogtXP3I+859btQUlNENYULfX4KBTVarznnX6ycVPujJnG6gVNSLYye6i+44IIu5EOBi/rDaFhmPS1OJtUAhesuOb/QtJxUbrrBUtCuZnfJVOo1o5s09YtSn6Zk0nDmpNoQuPbaa20ofd/Z3/mROi0Q142o/hWq8a6Ns/pvLvV7qppVPWBQbaf6jvqBXKzWPvT1rKXzSeZVv6NqLpj8p+9AP6rlVL/Pye1qZVrNi/XqBfU70sNGPxCPvepBD630t6ctJAKktlCKnAMCCBQUUI2FmtrlP41UvyT9QdaTWbV9VyChedX4Ytd7gvRHX/1B7rzzTuubon5NYRAJ3WTrRkF9TNTxWgMSqFmGBoFQgKQ/sOUmbaemYHqHigZCUGdh9WPRse699157X4xu1stN8tHTXg0SoJuZUpOCMQWjfgQ/eweS+h6pH49slBprBqntVEM0bNgwC5JkqG1U26ZzDE068vPRnPMvVk4qL9XoqO29Ajs/OqANeKF3IoX3Win408sT1SxPN0IaTELBobZVUKJ3GOX3XcvPuz6rBtSPfGV90hRwKdBPplKvGT0k0Du89FPXlK4tNWHS7wWpNgTUh0XBsgYwUPPL5L/Q/LM2zqRwLlUTofd56TtRg7noGlXzutDXs/BWzE1bQA+D1NdI321qnqzvKD3006AUbSb5XzwSAgggULMCyWG+C52E3lfkv7Bz3oOk92/4Zkw2BLKWachuvTvFv3xxqvcg+Q71ObvVEMvaxt+058z3gYzN97UJNj8MH61hXTUEqrbRP71XadSoUTnb6t05epeQ3qsU1tP7gR577LGc9XzAYEOq5sxs4oPOXe9MCvv0Tb+iQu8PKnWYbx/ARf4pqO3Pj8wUvwcpOUy3spP/HiQfjNrw4BryXHnxNVH2XiY56L1KGrY4pOQw35qnocn1zqpwDr4WKZKD3sNULJVy/uWUkw86Ix98xXnxNwaRfwFk5J/k52TFB0P2vqaQZ5Wrhv9Ovu+pWFnecsstdpzkEPPJg5R6zWjoeN8HwoZ8V378jWgUhif3DwaSuyxpujXegaRjpJFa4x1IOkY6KdvDfGv4/PDd2RyfrA7z3Zxzyd/G/9r674LW+Zd/7GKffYuCyLeIiPzL0outWnPL2ynH/kuThAACCNSdgGo11IRJHe1L7R/SXCQfDNiTtkId88M+1XxNb11XrZeeqFZqaFjV9uj8tM+WJjXrUf8b9YkpN3+qydMobqpF0UAG5SQNTKAhtdW+PTnQQSn7KOf8i5WTyijUnukpalMGanqnmkrlWU0Fq5FKvWZU26C+R6F/VnPzMrldw4iOzd1HKdt1jP4sZbWKrjPloukqur/GdtZ+v4amvY2tU/n53Sq/y0b3OK7RJdVaMI/rUq1d5+x3pJuQ87k1PrRr1xpH+e8xiAgarAmQGiyYQgABBBBAAIEmBAiQmsApcREBUolQZaxGgFQGVhOrEiA14NAHqcGCKQQQQAABBBBAAAEEEKhzAQKkOr8AOH0EEEAAAQQQQAABBBBoECBAarBgCgEEEEAAAQQQQAABBOpcgACpzi8ATh8BBBBAAAEEEEAAAQQaBAiQGiyYQgABBBBAAAEEEEAAgToXYBS7Or8AOH0EEEAAAQQQQAABBBBoEKAGqcGCKQQQQAABBBBAAAEEEKhzAQKkOr8AOH0EEEAAAQQQQAABBBBoECBAarBgCgEEEEAAAQQQQAABBOpcgACpzi8ATh8BBBBAAAEEEEAAAQQaBAiQGiyYQgABBBBAAAEEEEAAgToXIECq8wuA00cAAQQQQAABBBBAAIEGAQKkBgumEEAAAQQQQAABBBBAoM4FCJDq/ALg9BFAAAEEEEAAAQQQQKBBgACpwYIpBBBAAAEEEEAAAQQQqHMBAqQ6vwA4fQQQQAABBBBAAAEEEGgQIEBqsGAKAQQQQAABBBBAAAEE6lyAAKnOLwBOHwEEEEAAAQQQQAABBBoECJAaLJhCAAEEEEAAAQQQQACBOhcgQKrzC4DTRwABBBBAAAEEEEAAgQYBAqQGC6YQQAABBBBAAAEEEECgzgUIkOr8AuD0EUAAAQQQQAABBBBAoEGAAKnBgikEEEAAAQQQQAABBBCocwECpDq/ADh9BBBAAAEEEEAAAQQQaBD4f/3DuCsd7S5cAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mutantStability %>% select(label,nOccurrence, n) %>%\n",
    "# change n to be a percentage of the total n for that label\n",
    "group_by(label) %>% mutate(n=n/sum(n)) %>% ungroup() %>%\n",
    "mutate(nOccurrence=as.factor(nOccurrence))%>%\n",
    "ggplot(aes(fill=nOccurrence, x=n, y=label)) +\n",
    "# make the fill be a discrete scale from red (1) to green (5)\n",
    "scale_fill_manual(values = c(\"red\", \"orange\", \"yellow\", \"green\", \"blue\")) +\n",
    "geom_bar(stat=\"identity\") +\n",
    "    theme_minimal() + theme(legend.position = \"bottom\") + \n",
    "    xlab(\"Number of Mutants\") +\n",
    "    ylab(\"\") +\n",
    "    # set legend title\n",
    "    labs(fill = \"Number of trials observed\") +\n",
    "    theme(legend.position = \"bottom\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'run', 'startLine', 'startColumn', 'endLine', 'endColumn',\n",
      "'originalCode'. You can override using the `.groups` argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'startLine', 'startColumn', 'originalCode'. You can override using\n",
      "the `.groups` argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template', 'temperature',\n",
      "'project', 'startLine', 'startColumn'. You can override using the `.groups`\n",
      "argument.\n",
      "\u001b[1m\u001b[22m`summarise()` has grouped output by 'model', 'template'. You can override using\n",
      "the `.groups` argument.\n",
      "\u001b[1m\u001b[22mAdding missing grouping variables: `model`, `template`\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# for each mutant location, report simply whether the exact same 3 mutants were made across all runs (or not)\n",
    "\n",
    "# for each model/template/temperature, calculate how often the same mutation was made\n",
    "# prepare to find which mutants are repeated across runs by ensuring that each mutant appears exactly once\n",
    "uniqueMutantsByRun <- mutants %>% group_by(model, template, temperature, project, run, startLine, startColumn, endLine, endColumn, originalCode, replacement) %>%\n",
    "    summarise(repeatPerRun=n()) %>% ungroup()\n",
    "\n",
    "mutantStabilityByLocation <-  mutants %>% group_by(model, template, temperature, project, startLine, startColumn, originalCode, replacement) %>%\n",
    "    summarise(nOccurrence=n()) %>% ungroup() %>%\n",
    "    mutate(occurredAllRuns = (nOccurrence==5)) %>%\n",
    "    group_by(model, template, temperature, project, startLine, startColumn, originalCode) %>%\n",
    "    summarise(total=n(), occurredAllRuns=sum(occurredAllRuns), didNotOccurAllRuns=total-occurredAllRuns) %>%\n",
    "    ungroup()%>%\n",
    "    group_by(model, template, temperature) %>%\n",
    "    summarise(locations=n(),fullyStableLocations=sum(occurredAllRuns == total), unstableLocations=sum(occurredAllRuns != total))  %>%\n",
    "        mutate(label=paste(model, template, temperature, sep=\"-\"),\n",
    "        percentStable=fullyStableLocations/locations,\n",
    "        percentUnstable=unstableLocations/locations)        \n",
    "\n",
    "# # stacked bar chart of mutation stability, by percentage\n",
    "mutantStabilityByLocation %>% \n",
    "pivot_longer(names_to = \"cat\", values_to = \"n\", cols = c(\"percentStable\", \"percentUnstable\")) %>%\n",
    "select(label,cat, n) %>%\n",
    "ggplot(aes(fill=cat, x=n, y=label)) +\n",
    "# scale_fill_manual(values = c(\"green\", \"red\")) +\n",
    "geom_bar(stat=\"identity\") +\n",
    "    theme_minimal() + theme(legend.position = \"bottom\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# For each of the 5 experiments, look to see how often each mutant occurs"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.4.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}