play_with_data.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Integrity of xylan backbone affects plant responses to drought\n",
    "\n",
    "This notebook represents the data processing and visualization work to produce Clustering figures of genotypes according to their early and late responses in analyzed parameters to moderate and severe drought and some basics statistics. \n",
    "\n",
    "We try to design this Python notebook with flexibility in mind for encouraging the audience to make the tool their own and adapt it to their unique research contexts. You are encouraged to explore and modify the code according to your specific research requirements (most of the function are inside the `utils.py` file). \n",
    "\n",
    "Hope your innovations and adaptations will not only benefit your work but also enrich the scientific community 😎\n",
    "\n",
    "Link of the paper [here](...)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils import * \n",
    "import warnings\n",
    "pd.set_option('display.max_columns', None)\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import datasets\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading the original data\n",
    "# change the path below according to your files\n",
    "data = \"/Users/mac/Downloads/Tdata_Amiens.csv\" \n",
    "df = pd.read_csv(data, sep=';', decimal=',', na_values='#N/A')\n",
    "drr = pd.read_csv('/Users/mac/Downloads/drr1_drr2_3rd.csv', sep=';', decimal=',', na_values='#N/A')\n",
    "wli = pd.read_csv('/Users/mac/Downloads/wli.csv', sep=';', decimal=',', na_values='#N/A')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature engineering and filtering \n",
    "\n",
    "Perform some feature engineering with the `merge_all(.,.,.)` function and drop intermediate columns in order to filtrate the dataset by `treatement` and `Day_after_sowing` parameters \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "merge_data = merge_all(df,drr,wli)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Measuring_date</th>\n",
       "      <th>Round_Order</th>\n",
       "      <th>plant_ID_treatment</th>\n",
       "      <th>plant ID 2</th>\n",
       "      <th>Day_after_sowing</th>\n",
       "      <th>transgenic_line</th>\n",
       "      <th>treatement</th>\n",
       "      <th>ratio_Fo</th>\n",
       "      <th>ratio_Fm</th>\n",
       "      <th>ratio_Fv</th>\n",
       "      <th>ratio_QY_max</th>\n",
       "      <th>ratio_NDVI2</th>\n",
       "      <th>ratio_PRI</th>\n",
       "      <th>ratio_SIPI</th>\n",
       "      <th>ratio_NDVI</th>\n",
       "      <th>ratio_PSRI</th>\n",
       "      <th>ratio_MCARI1</th>\n",
       "      <th>ratio_OSAVI</th>\n",
       "      <th>ratio_Slenderness</th>\n",
       "      <th>ratio_WLI/NDVI</th>\n",
       "      <th>ratio_%RGB(72,84,58)</th>\n",
       "      <th>ratio_%RGB(73,86,36)</th>\n",
       "      <th>ratio_%RGB(57,71,46)</th>\n",
       "      <th>ratio_%RGB(59,71,20)</th>\n",
       "      <th>drr1</th>\n",
       "      <th>drr2</th>\n",
       "      <th>outlier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-04-19</td>\n",
       "      <td>16</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544670</td>\n",
       "      <td>19</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.728118</td>\n",
       "      <td>0.714936</td>\n",
       "      <td>0.712677</td>\n",
       "      <td>0.997298</td>\n",
       "      <td>0.367279</td>\n",
       "      <td>-0.384003</td>\n",
       "      <td>0.888215</td>\n",
       "      <td>0.855334</td>\n",
       "      <td>1.663124</td>\n",
       "      <td>0.683597</td>\n",
       "      <td>0.859863</td>\n",
       "      <td>0.041739</td>\n",
       "      <td>1.891518</td>\n",
       "      <td>0.601143</td>\n",
       "      <td>0.731762</td>\n",
       "      <td>1.357306</td>\n",
       "      <td>0.560506</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>18</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544671</td>\n",
       "      <td>20</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.790029</td>\n",
       "      <td>0.736884</td>\n",
       "      <td>0.727778</td>\n",
       "      <td>0.987442</td>\n",
       "      <td>0.484567</td>\n",
       "      <td>-1.018026</td>\n",
       "      <td>0.905391</td>\n",
       "      <td>0.872751</td>\n",
       "      <td>2.267280</td>\n",
       "      <td>0.761049</td>\n",
       "      <td>0.915367</td>\n",
       "      <td>0.055829</td>\n",
       "      <td>2.126071</td>\n",
       "      <td>0.946979</td>\n",
       "      <td>0.774231</td>\n",
       "      <td>1.406258</td>\n",
       "      <td>0.441796</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-04-21</td>\n",
       "      <td>20</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544672</td>\n",
       "      <td>21</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.772257</td>\n",
       "      <td>0.727725</td>\n",
       "      <td>0.720095</td>\n",
       "      <td>0.988540</td>\n",
       "      <td>0.602841</td>\n",
       "      <td>-1.572017</td>\n",
       "      <td>0.915380</td>\n",
       "      <td>0.884324</td>\n",
       "      <td>2.587088</td>\n",
       "      <td>0.777744</td>\n",
       "      <td>0.931163</td>\n",
       "      <td>0.057184</td>\n",
       "      <td>1.638025</td>\n",
       "      <td>0.744381</td>\n",
       "      <td>0.709575</td>\n",
       "      <td>1.465160</td>\n",
       "      <td>0.419937</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-04-22</td>\n",
       "      <td>22</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544673</td>\n",
       "      <td>22</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.808324</td>\n",
       "      <td>0.745102</td>\n",
       "      <td>0.734269</td>\n",
       "      <td>0.985817</td>\n",
       "      <td>0.700204</td>\n",
       "      <td>-0.679460</td>\n",
       "      <td>0.912743</td>\n",
       "      <td>0.894603</td>\n",
       "      <td>1.979029</td>\n",
       "      <td>0.809201</td>\n",
       "      <td>0.934326</td>\n",
       "      <td>0.191227</td>\n",
       "      <td>1.717645</td>\n",
       "      <td>0.411842</td>\n",
       "      <td>0.775014</td>\n",
       "      <td>1.244413</td>\n",
       "      <td>0.465728</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-23</td>\n",
       "      <td>24</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544674</td>\n",
       "      <td>23</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.858954</td>\n",
       "      <td>0.804701</td>\n",
       "      <td>0.795404</td>\n",
       "      <td>0.989249</td>\n",
       "      <td>0.952928</td>\n",
       "      <td>-0.330063</td>\n",
       "      <td>0.930660</td>\n",
       "      <td>0.919801</td>\n",
       "      <td>1.909950</td>\n",
       "      <td>0.827104</td>\n",
       "      <td>0.942283</td>\n",
       "      <td>0.161725</td>\n",
       "      <td>1.485783</td>\n",
       "      <td>0.381980</td>\n",
       "      <td>0.776349</td>\n",
       "      <td>1.026069</td>\n",
       "      <td>0.533027</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8298</th>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>45</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944685</td>\n",
       "      <td>34</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.129880</td>\n",
       "      <td>1.155380</td>\n",
       "      <td>1.159639</td>\n",
       "      <td>1.006971</td>\n",
       "      <td>1.365522</td>\n",
       "      <td>2.525368</td>\n",
       "      <td>0.981997</td>\n",
       "      <td>0.976926</td>\n",
       "      <td>1.169230</td>\n",
       "      <td>1.128456</td>\n",
       "      <td>1.081418</td>\n",
       "      <td>0.841591</td>\n",
       "      <td>1.268470</td>\n",
       "      <td>4.043450</td>\n",
       "      <td>0.550706</td>\n",
       "      <td>1.972339</td>\n",
       "      <td>0.193281</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8299</th>\n",
       "      <td>2022-05-05</td>\n",
       "      <td>47</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944686</td>\n",
       "      <td>35</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.147465</td>\n",
       "      <td>1.184669</td>\n",
       "      <td>1.190884</td>\n",
       "      <td>1.008935</td>\n",
       "      <td>1.370721</td>\n",
       "      <td>2.137834</td>\n",
       "      <td>0.998004</td>\n",
       "      <td>0.990361</td>\n",
       "      <td>1.156596</td>\n",
       "      <td>1.117322</td>\n",
       "      <td>1.080376</td>\n",
       "      <td>0.809919</td>\n",
       "      <td>1.231791</td>\n",
       "      <td>3.777299</td>\n",
       "      <td>0.518348</td>\n",
       "      <td>2.480676</td>\n",
       "      <td>0.253138</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8300</th>\n",
       "      <td>2022-05-06</td>\n",
       "      <td>49</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944687</td>\n",
       "      <td>36</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.154363</td>\n",
       "      <td>1.199917</td>\n",
       "      <td>1.207526</td>\n",
       "      <td>1.009805</td>\n",
       "      <td>1.399128</td>\n",
       "      <td>2.689216</td>\n",
       "      <td>0.992008</td>\n",
       "      <td>0.985577</td>\n",
       "      <td>1.198041</td>\n",
       "      <td>1.126561</td>\n",
       "      <td>1.083290</td>\n",
       "      <td>0.724117</td>\n",
       "      <td>1.215491</td>\n",
       "      <td>3.780053</td>\n",
       "      <td>0.493681</td>\n",
       "      <td>2.475436</td>\n",
       "      <td>0.288339</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8301</th>\n",
       "      <td>2022-05-07</td>\n",
       "      <td>51</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944688</td>\n",
       "      <td>37</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.142939</td>\n",
       "      <td>1.181925</td>\n",
       "      <td>1.188437</td>\n",
       "      <td>1.009017</td>\n",
       "      <td>1.439536</td>\n",
       "      <td>2.967161</td>\n",
       "      <td>0.987046</td>\n",
       "      <td>0.984964</td>\n",
       "      <td>1.132790</td>\n",
       "      <td>1.197310</td>\n",
       "      <td>1.099395</td>\n",
       "      <td>1.030985</td>\n",
       "      <td>1.216527</td>\n",
       "      <td>3.729011</td>\n",
       "      <td>0.437602</td>\n",
       "      <td>2.399275</td>\n",
       "      <td>0.315516</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8302</th>\n",
       "      <td>2022-05-08</td>\n",
       "      <td>53</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944689</td>\n",
       "      <td>38</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.145005</td>\n",
       "      <td>1.204280</td>\n",
       "      <td>1.214181</td>\n",
       "      <td>1.012131</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8303 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Measuring_date  Round_Order plant_ID_treatment      plant ID 2  \\\n",
       "0        2022-04-19           16                MD5  FC5 1-MD544670   \n",
       "1        2022-04-20           18                MD5  FC5 1-MD544671   \n",
       "2        2022-04-21           20                MD5  FC5 1-MD544672   \n",
       "3        2022-04-22           22                MD5  FC5 1-MD544673   \n",
       "4        2022-04-23           24                MD5  FC5 1-MD544674   \n",
       "...             ...          ...                ...             ...   \n",
       "8298     2022-05-04           45               SD39  Col0-SD3944685   \n",
       "8299     2022-05-05           47               SD39  Col0-SD3944686   \n",
       "8300     2022-05-06           49               SD39  Col0-SD3944687   \n",
       "8301     2022-05-07           51               SD39  Col0-SD3944688   \n",
       "8302     2022-05-08           53               SD39  Col0-SD3944689   \n",
       "\n",
       "      Day_after_sowing transgenic_line      treatement  ratio_Fo  ratio_Fm  \\\n",
       "0                   19           FC5_1  medium drought  0.728118  0.714936   \n",
       "1                   20           FC5_1  medium drought  0.790029  0.736884   \n",
       "2                   21           FC5_1  medium drought  0.772257  0.727725   \n",
       "3                   22           FC5_1  medium drought  0.808324  0.745102   \n",
       "4                   23           FC5_1  medium drought  0.858954  0.804701   \n",
       "...                ...             ...             ...       ...       ...   \n",
       "8298                34            Col0  severe drought  1.129880  1.155380   \n",
       "8299                35            Col0  severe drought  1.147465  1.184669   \n",
       "8300                36            Col0  severe drought  1.154363  1.199917   \n",
       "8301                37            Col0  severe drought  1.142939  1.181925   \n",
       "8302                38            Col0  severe drought  1.145005  1.204280   \n",
       "\n",
       "      ratio_Fv  ratio_QY_max  ratio_NDVI2  ratio_PRI  ratio_SIPI  ratio_NDVI  \\\n",
       "0     0.712677      0.997298     0.367279  -0.384003    0.888215    0.855334   \n",
       "1     0.727778      0.987442     0.484567  -1.018026    0.905391    0.872751   \n",
       "2     0.720095      0.988540     0.602841  -1.572017    0.915380    0.884324   \n",
       "3     0.734269      0.985817     0.700204  -0.679460    0.912743    0.894603   \n",
       "4     0.795404      0.989249     0.952928  -0.330063    0.930660    0.919801   \n",
       "...        ...           ...          ...        ...         ...         ...   \n",
       "8298  1.159639      1.006971     1.365522   2.525368    0.981997    0.976926   \n",
       "8299  1.190884      1.008935     1.370721   2.137834    0.998004    0.990361   \n",
       "8300  1.207526      1.009805     1.399128   2.689216    0.992008    0.985577   \n",
       "8301  1.188437      1.009017     1.439536   2.967161    0.987046    0.984964   \n",
       "8302  1.214181      1.012131          NaN        NaN         NaN         NaN   \n",
       "\n",
       "      ratio_PSRI  ratio_MCARI1  ratio_OSAVI  ratio_Slenderness  \\\n",
       "0       1.663124      0.683597     0.859863           0.041739   \n",
       "1       2.267280      0.761049     0.915367           0.055829   \n",
       "2       2.587088      0.777744     0.931163           0.057184   \n",
       "3       1.979029      0.809201     0.934326           0.191227   \n",
       "4       1.909950      0.827104     0.942283           0.161725   \n",
       "...          ...           ...          ...                ...   \n",
       "8298    1.169230      1.128456     1.081418           0.841591   \n",
       "8299    1.156596      1.117322     1.080376           0.809919   \n",
       "8300    1.198041      1.126561     1.083290           0.724117   \n",
       "8301    1.132790      1.197310     1.099395           1.030985   \n",
       "8302         NaN           NaN          NaN                NaN   \n",
       "\n",
       "      ratio_WLI/NDVI  ratio_%RGB(72,84,58)  ratio_%RGB(73,86,36)  \\\n",
       "0           1.891518              0.601143              0.731762   \n",
       "1           2.126071              0.946979              0.774231   \n",
       "2           1.638025              0.744381              0.709575   \n",
       "3           1.717645              0.411842              0.775014   \n",
       "4           1.485783              0.381980              0.776349   \n",
       "...              ...                   ...                   ...   \n",
       "8298        1.268470              4.043450              0.550706   \n",
       "8299        1.231791              3.777299              0.518348   \n",
       "8300        1.215491              3.780053              0.493681   \n",
       "8301        1.216527              3.729011              0.437602   \n",
       "8302             NaN                   NaN                   NaN   \n",
       "\n",
       "      ratio_%RGB(57,71,46)  ratio_%RGB(59,71,20)      drr1      drr2 outlier  \n",
       "0                 1.357306              0.560506  0.497962  0.523980      no  \n",
       "1                 1.406258              0.441796  0.497962  0.523980      no  \n",
       "2                 1.465160              0.419937  0.497962  0.523980      no  \n",
       "3                 1.244413              0.465728  0.497962  0.523980      no  \n",
       "4                 1.026069              0.533027  0.497962  0.523980      no  \n",
       "...                    ...                   ...       ...       ...     ...  \n",
       "8298              1.972339              0.193281  0.312947  0.299581      no  \n",
       "8299              2.480676              0.253138  0.312947  0.299581      no  \n",
       "8300              2.475436              0.288339  0.312947  0.299581      no  \n",
       "8301              2.399275              0.315516  0.312947  0.299581      no  \n",
       "8302                   NaN                   NaN  0.312947  0.299581      no  \n",
       "\n",
       "[8303 rows x 27 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Measuring_date</th>\n",
       "      <th>Round_Order</th>\n",
       "      <th>plant_ID_treatment</th>\n",
       "      <th>plant ID 2</th>\n",
       "      <th>Day_after_sowing</th>\n",
       "      <th>transgenic_line</th>\n",
       "      <th>treatement</th>\n",
       "      <th>ratio_Fo</th>\n",
       "      <th>ratio_Fm</th>\n",
       "      <th>ratio_Fv</th>\n",
       "      <th>ratio_QY_max</th>\n",
       "      <th>ratio_NDVI2</th>\n",
       "      <th>ratio_PRI</th>\n",
       "      <th>ratio_SIPI</th>\n",
       "      <th>ratio_NDVI</th>\n",
       "      <th>ratio_PSRI</th>\n",
       "      <th>ratio_MCARI1</th>\n",
       "      <th>ratio_OSAVI</th>\n",
       "      <th>ratio_Slenderness</th>\n",
       "      <th>ratio_WLI/NDVI</th>\n",
       "      <th>ratio_%RGB(72,84,58)</th>\n",
       "      <th>ratio_%RGB(73,86,36)</th>\n",
       "      <th>ratio_%RGB(57,71,46)</th>\n",
       "      <th>ratio_%RGB(59,71,20)</th>\n",
       "      <th>drr1</th>\n",
       "      <th>drr2</th>\n",
       "      <th>outlier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>32</td>\n",
       "      <td>SD3</td>\n",
       "      <td>FC5 2-SD344678</td>\n",
       "      <td>27</td>\n",
       "      <td>FC5_2</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>0.908543</td>\n",
       "      <td>0.980159</td>\n",
       "      <td>0.992532</td>\n",
       "      <td>1.017049</td>\n",
       "      <td>1.617025</td>\n",
       "      <td>0.005809</td>\n",
       "      <td>0.996733</td>\n",
       "      <td>0.987069</td>\n",
       "      <td>1.780356</td>\n",
       "      <td>1.040433</td>\n",
       "      <td>1.041799</td>\n",
       "      <td>0.189552</td>\n",
       "      <td>1.358660</td>\n",
       "      <td>1.417246</td>\n",
       "      <td>1.087745</td>\n",
       "      <td>2.125231</td>\n",
       "      <td>1.148606</td>\n",
       "      <td>0.280143</td>\n",
       "      <td>0.468326</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2022-04-28</td>\n",
       "      <td>34</td>\n",
       "      <td>SD3</td>\n",
       "      <td>FC5 2-SD344679</td>\n",
       "      <td>28</td>\n",
       "      <td>FC5_2</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>0.896835</td>\n",
       "      <td>1.008610</td>\n",
       "      <td>1.027923</td>\n",
       "      <td>1.023254</td>\n",
       "      <td>1.626452</td>\n",
       "      <td>0.232859</td>\n",
       "      <td>1.005975</td>\n",
       "      <td>0.989448</td>\n",
       "      <td>1.934540</td>\n",
       "      <td>1.022688</td>\n",
       "      <td>1.040904</td>\n",
       "      <td>0.103559</td>\n",
       "      <td>1.289762</td>\n",
       "      <td>2.417862</td>\n",
       "      <td>0.891748</td>\n",
       "      <td>2.646295</td>\n",
       "      <td>1.092510</td>\n",
       "      <td>0.280143</td>\n",
       "      <td>0.468326</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2022-04-29</td>\n",
       "      <td>36</td>\n",
       "      <td>SD3</td>\n",
       "      <td>FC5 2-SD344680</td>\n",
       "      <td>29</td>\n",
       "      <td>FC5_2</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>0.958229</td>\n",
       "      <td>1.072976</td>\n",
       "      <td>1.092802</td>\n",
       "      <td>1.022558</td>\n",
       "      <td>1.694192</td>\n",
       "      <td>0.114574</td>\n",
       "      <td>1.010813</td>\n",
       "      <td>0.997866</td>\n",
       "      <td>1.824424</td>\n",
       "      <td>1.087743</td>\n",
       "      <td>1.061833</td>\n",
       "      <td>0.111872</td>\n",
       "      <td>1.269434</td>\n",
       "      <td>2.829299</td>\n",
       "      <td>0.810499</td>\n",
       "      <td>2.601550</td>\n",
       "      <td>1.169748</td>\n",
       "      <td>0.280143</td>\n",
       "      <td>0.468326</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>38</td>\n",
       "      <td>SD3</td>\n",
       "      <td>FC5 2-SD344681</td>\n",
       "      <td>30</td>\n",
       "      <td>FC5_2</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>0.958089</td>\n",
       "      <td>1.079076</td>\n",
       "      <td>1.099980</td>\n",
       "      <td>1.022930</td>\n",
       "      <td>1.739882</td>\n",
       "      <td>-0.112527</td>\n",
       "      <td>1.013826</td>\n",
       "      <td>1.003230</td>\n",
       "      <td>1.767233</td>\n",
       "      <td>1.076757</td>\n",
       "      <td>1.060469</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.275346</td>\n",
       "      <td>3.161386</td>\n",
       "      <td>0.683181</td>\n",
       "      <td>2.744598</td>\n",
       "      <td>1.302823</td>\n",
       "      <td>0.280143</td>\n",
       "      <td>0.468326</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2022-05-02</td>\n",
       "      <td>41</td>\n",
       "      <td>SD3</td>\n",
       "      <td>FC5 2-SD344683</td>\n",
       "      <td>32</td>\n",
       "      <td>FC5_2</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>0.955106</td>\n",
       "      <td>1.075873</td>\n",
       "      <td>1.096738</td>\n",
       "      <td>1.023523</td>\n",
       "      <td>1.740206</td>\n",
       "      <td>-0.128016</td>\n",
       "      <td>1.014715</td>\n",
       "      <td>1.005863</td>\n",
       "      <td>1.632701</td>\n",
       "      <td>1.110700</td>\n",
       "      <td>1.071886</td>\n",
       "      <td>0.246719</td>\n",
       "      <td>1.186979</td>\n",
       "      <td>2.803764</td>\n",
       "      <td>0.587107</td>\n",
       "      <td>2.700146</td>\n",
       "      <td>1.195075</td>\n",
       "      <td>0.280143</td>\n",
       "      <td>0.468326</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8297</th>\n",
       "      <td>2022-05-03</td>\n",
       "      <td>43</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944684</td>\n",
       "      <td>33</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.140054</td>\n",
       "      <td>1.162545</td>\n",
       "      <td>1.166301</td>\n",
       "      <td>1.006679</td>\n",
       "      <td>1.293310</td>\n",
       "      <td>2.087679</td>\n",
       "      <td>0.986550</td>\n",
       "      <td>0.977121</td>\n",
       "      <td>1.325372</td>\n",
       "      <td>1.035878</td>\n",
       "      <td>1.054384</td>\n",
       "      <td>0.654378</td>\n",
       "      <td>1.244776</td>\n",
       "      <td>3.800398</td>\n",
       "      <td>0.523566</td>\n",
       "      <td>1.818542</td>\n",
       "      <td>0.200723</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8298</th>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>45</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944685</td>\n",
       "      <td>34</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.129880</td>\n",
       "      <td>1.155380</td>\n",
       "      <td>1.159639</td>\n",
       "      <td>1.006971</td>\n",
       "      <td>1.365522</td>\n",
       "      <td>2.525368</td>\n",
       "      <td>0.981997</td>\n",
       "      <td>0.976926</td>\n",
       "      <td>1.169230</td>\n",
       "      <td>1.128456</td>\n",
       "      <td>1.081418</td>\n",
       "      <td>0.841591</td>\n",
       "      <td>1.268470</td>\n",
       "      <td>4.043450</td>\n",
       "      <td>0.550706</td>\n",
       "      <td>1.972339</td>\n",
       "      <td>0.193281</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8299</th>\n",
       "      <td>2022-05-05</td>\n",
       "      <td>47</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944686</td>\n",
       "      <td>35</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.147465</td>\n",
       "      <td>1.184669</td>\n",
       "      <td>1.190884</td>\n",
       "      <td>1.008935</td>\n",
       "      <td>1.370721</td>\n",
       "      <td>2.137834</td>\n",
       "      <td>0.998004</td>\n",
       "      <td>0.990361</td>\n",
       "      <td>1.156596</td>\n",
       "      <td>1.117322</td>\n",
       "      <td>1.080376</td>\n",
       "      <td>0.809919</td>\n",
       "      <td>1.231791</td>\n",
       "      <td>3.777299</td>\n",
       "      <td>0.518348</td>\n",
       "      <td>2.480676</td>\n",
       "      <td>0.253138</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8300</th>\n",
       "      <td>2022-05-06</td>\n",
       "      <td>49</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944687</td>\n",
       "      <td>36</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.154363</td>\n",
       "      <td>1.199917</td>\n",
       "      <td>1.207526</td>\n",
       "      <td>1.009805</td>\n",
       "      <td>1.399128</td>\n",
       "      <td>2.689216</td>\n",
       "      <td>0.992008</td>\n",
       "      <td>0.985577</td>\n",
       "      <td>1.198041</td>\n",
       "      <td>1.126561</td>\n",
       "      <td>1.083290</td>\n",
       "      <td>0.724117</td>\n",
       "      <td>1.215491</td>\n",
       "      <td>3.780053</td>\n",
       "      <td>0.493681</td>\n",
       "      <td>2.475436</td>\n",
       "      <td>0.288339</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8301</th>\n",
       "      <td>2022-05-07</td>\n",
       "      <td>51</td>\n",
       "      <td>SD39</td>\n",
       "      <td>Col0-SD3944688</td>\n",
       "      <td>37</td>\n",
       "      <td>Col0</td>\n",
       "      <td>severe drought</td>\n",
       "      <td>1.142939</td>\n",
       "      <td>1.181925</td>\n",
       "      <td>1.188437</td>\n",
       "      <td>1.009017</td>\n",
       "      <td>1.439536</td>\n",
       "      <td>2.967161</td>\n",
       "      <td>0.987046</td>\n",
       "      <td>0.984964</td>\n",
       "      <td>1.132790</td>\n",
       "      <td>1.197310</td>\n",
       "      <td>1.099395</td>\n",
       "      <td>1.030985</td>\n",
       "      <td>1.216527</td>\n",
       "      <td>3.729011</td>\n",
       "      <td>0.437602</td>\n",
       "      <td>2.399275</td>\n",
       "      <td>0.315516</td>\n",
       "      <td>0.312947</td>\n",
       "      <td>0.299581</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2220 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Measuring_date  Round_Order plant_ID_treatment      plant ID 2  \\\n",
       "141      2022-04-27           32                SD3  FC5 2-SD344678   \n",
       "142      2022-04-28           34                SD3  FC5 2-SD344679   \n",
       "143      2022-04-29           36                SD3  FC5 2-SD344680   \n",
       "144      2022-04-30           38                SD3  FC5 2-SD344681   \n",
       "145      2022-05-02           41                SD3  FC5 2-SD344683   \n",
       "...             ...          ...                ...             ...   \n",
       "8297     2022-05-03           43               SD39  Col0-SD3944684   \n",
       "8298     2022-05-04           45               SD39  Col0-SD3944685   \n",
       "8299     2022-05-05           47               SD39  Col0-SD3944686   \n",
       "8300     2022-05-06           49               SD39  Col0-SD3944687   \n",
       "8301     2022-05-07           51               SD39  Col0-SD3944688   \n",
       "\n",
       "      Day_after_sowing transgenic_line      treatement  ratio_Fo  ratio_Fm  \\\n",
       "141                 27           FC5_2  severe drought  0.908543  0.980159   \n",
       "142                 28           FC5_2  severe drought  0.896835  1.008610   \n",
       "143                 29           FC5_2  severe drought  0.958229  1.072976   \n",
       "144                 30           FC5_2  severe drought  0.958089  1.079076   \n",
       "145                 32           FC5_2  severe drought  0.955106  1.075873   \n",
       "...                ...             ...             ...       ...       ...   \n",
       "8297                33            Col0  severe drought  1.140054  1.162545   \n",
       "8298                34            Col0  severe drought  1.129880  1.155380   \n",
       "8299                35            Col0  severe drought  1.147465  1.184669   \n",
       "8300                36            Col0  severe drought  1.154363  1.199917   \n",
       "8301                37            Col0  severe drought  1.142939  1.181925   \n",
       "\n",
       "      ratio_Fv  ratio_QY_max  ratio_NDVI2  ratio_PRI  ratio_SIPI  ratio_NDVI  \\\n",
       "141   0.992532      1.017049     1.617025   0.005809    0.996733    0.987069   \n",
       "142   1.027923      1.023254     1.626452   0.232859    1.005975    0.989448   \n",
       "143   1.092802      1.022558     1.694192   0.114574    1.010813    0.997866   \n",
       "144   1.099980      1.022930     1.739882  -0.112527    1.013826    1.003230   \n",
       "145   1.096738      1.023523     1.740206  -0.128016    1.014715    1.005863   \n",
       "...        ...           ...          ...        ...         ...         ...   \n",
       "8297  1.166301      1.006679     1.293310   2.087679    0.986550    0.977121   \n",
       "8298  1.159639      1.006971     1.365522   2.525368    0.981997    0.976926   \n",
       "8299  1.190884      1.008935     1.370721   2.137834    0.998004    0.990361   \n",
       "8300  1.207526      1.009805     1.399128   2.689216    0.992008    0.985577   \n",
       "8301  1.188437      1.009017     1.439536   2.967161    0.987046    0.984964   \n",
       "\n",
       "      ratio_PSRI  ratio_MCARI1  ratio_OSAVI  ratio_Slenderness  \\\n",
       "141     1.780356      1.040433     1.041799           0.189552   \n",
       "142     1.934540      1.022688     1.040904           0.103559   \n",
       "143     1.824424      1.087743     1.061833           0.111872   \n",
       "144     1.767233      1.076757     1.060469                NaN   \n",
       "145     1.632701      1.110700     1.071886           0.246719   \n",
       "...          ...           ...          ...                ...   \n",
       "8297    1.325372      1.035878     1.054384           0.654378   \n",
       "8298    1.169230      1.128456     1.081418           0.841591   \n",
       "8299    1.156596      1.117322     1.080376           0.809919   \n",
       "8300    1.198041      1.126561     1.083290           0.724117   \n",
       "8301    1.132790      1.197310     1.099395           1.030985   \n",
       "\n",
       "      ratio_WLI/NDVI  ratio_%RGB(72,84,58)  ratio_%RGB(73,86,36)  \\\n",
       "141         1.358660              1.417246              1.087745   \n",
       "142         1.289762              2.417862              0.891748   \n",
       "143         1.269434              2.829299              0.810499   \n",
       "144         1.275346              3.161386              0.683181   \n",
       "145         1.186979              2.803764              0.587107   \n",
       "...              ...                   ...                   ...   \n",
       "8297        1.244776              3.800398              0.523566   \n",
       "8298        1.268470              4.043450              0.550706   \n",
       "8299        1.231791              3.777299              0.518348   \n",
       "8300        1.215491              3.780053              0.493681   \n",
       "8301        1.216527              3.729011              0.437602   \n",
       "\n",
       "      ratio_%RGB(57,71,46)  ratio_%RGB(59,71,20)      drr1      drr2 outlier  \n",
       "141               2.125231              1.148606  0.280143  0.468326      no  \n",
       "142               2.646295              1.092510  0.280143  0.468326      no  \n",
       "143               2.601550              1.169748  0.280143  0.468326      no  \n",
       "144               2.744598              1.302823  0.280143  0.468326      no  \n",
       "145               2.700146              1.195075  0.280143  0.468326      no  \n",
       "...                    ...                   ...       ...       ...     ...  \n",
       "8297              1.818542              0.200723  0.312947  0.299581      no  \n",
       "8298              1.972339              0.193281  0.312947  0.299581      no  \n",
       "8299              2.480676              0.253138  0.312947  0.299581      no  \n",
       "8300              2.475436              0.288339  0.312947  0.299581      no  \n",
       "8301              2.399275              0.315516  0.312947  0.299581      no  \n",
       "\n",
       "[2220 rows x 27 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sd_27_37 = filter_date_treatment(merge_data, 27,37,'severe drought') ; sd_27_37"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Measuring_date</th>\n",
       "      <th>Round_Order</th>\n",
       "      <th>plant_ID_treatment</th>\n",
       "      <th>plant ID 2</th>\n",
       "      <th>Day_after_sowing</th>\n",
       "      <th>transgenic_line</th>\n",
       "      <th>treatement</th>\n",
       "      <th>ratio_Fo</th>\n",
       "      <th>ratio_Fm</th>\n",
       "      <th>ratio_Fv</th>\n",
       "      <th>ratio_QY_max</th>\n",
       "      <th>ratio_NDVI2</th>\n",
       "      <th>ratio_PRI</th>\n",
       "      <th>ratio_SIPI</th>\n",
       "      <th>ratio_NDVI</th>\n",
       "      <th>ratio_PSRI</th>\n",
       "      <th>ratio_MCARI1</th>\n",
       "      <th>ratio_OSAVI</th>\n",
       "      <th>ratio_Slenderness</th>\n",
       "      <th>ratio_WLI/NDVI</th>\n",
       "      <th>ratio_%RGB(72,84,58)</th>\n",
       "      <th>ratio_%RGB(73,86,36)</th>\n",
       "      <th>ratio_%RGB(57,71,46)</th>\n",
       "      <th>ratio_%RGB(59,71,20)</th>\n",
       "      <th>drr1</th>\n",
       "      <th>drr2</th>\n",
       "      <th>outlier</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-04-22</td>\n",
       "      <td>22</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544673</td>\n",
       "      <td>22</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.808324</td>\n",
       "      <td>0.745102</td>\n",
       "      <td>0.734269</td>\n",
       "      <td>0.985817</td>\n",
       "      <td>0.700204</td>\n",
       "      <td>-0.679460</td>\n",
       "      <td>0.912743</td>\n",
       "      <td>0.894603</td>\n",
       "      <td>1.979029</td>\n",
       "      <td>0.809201</td>\n",
       "      <td>0.934326</td>\n",
       "      <td>0.191227</td>\n",
       "      <td>1.717645</td>\n",
       "      <td>0.411842</td>\n",
       "      <td>0.775014</td>\n",
       "      <td>1.244413</td>\n",
       "      <td>0.465728</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-23</td>\n",
       "      <td>24</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544674</td>\n",
       "      <td>23</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.858954</td>\n",
       "      <td>0.804701</td>\n",
       "      <td>0.795404</td>\n",
       "      <td>0.989249</td>\n",
       "      <td>0.952928</td>\n",
       "      <td>-0.330063</td>\n",
       "      <td>0.930660</td>\n",
       "      <td>0.919801</td>\n",
       "      <td>1.909950</td>\n",
       "      <td>0.827104</td>\n",
       "      <td>0.942283</td>\n",
       "      <td>0.161725</td>\n",
       "      <td>1.485783</td>\n",
       "      <td>0.381980</td>\n",
       "      <td>0.776349</td>\n",
       "      <td>1.026069</td>\n",
       "      <td>0.533027</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-04-24</td>\n",
       "      <td>26</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544675</td>\n",
       "      <td>24</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.903268</td>\n",
       "      <td>0.850845</td>\n",
       "      <td>0.841862</td>\n",
       "      <td>0.991230</td>\n",
       "      <td>0.875763</td>\n",
       "      <td>0.270387</td>\n",
       "      <td>0.948872</td>\n",
       "      <td>0.942715</td>\n",
       "      <td>1.683619</td>\n",
       "      <td>0.853953</td>\n",
       "      <td>0.953095</td>\n",
       "      <td>0.136707</td>\n",
       "      <td>1.383999</td>\n",
       "      <td>0.337792</td>\n",
       "      <td>0.963936</td>\n",
       "      <td>1.042887</td>\n",
       "      <td>0.590085</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-04-25</td>\n",
       "      <td>28</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544676</td>\n",
       "      <td>25</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.921387</td>\n",
       "      <td>0.862457</td>\n",
       "      <td>0.852359</td>\n",
       "      <td>0.989034</td>\n",
       "      <td>1.127202</td>\n",
       "      <td>0.499599</td>\n",
       "      <td>0.955140</td>\n",
       "      <td>0.948110</td>\n",
       "      <td>1.799318</td>\n",
       "      <td>0.876950</td>\n",
       "      <td>0.961356</td>\n",
       "      <td>0.235961</td>\n",
       "      <td>1.284788</td>\n",
       "      <td>0.396080</td>\n",
       "      <td>1.062548</td>\n",
       "      <td>0.703712</td>\n",
       "      <td>0.807426</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-04-26</td>\n",
       "      <td>30</td>\n",
       "      <td>MD5</td>\n",
       "      <td>FC5 1-MD544677</td>\n",
       "      <td>26</td>\n",
       "      <td>FC5_1</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.926482</td>\n",
       "      <td>0.898717</td>\n",
       "      <td>0.893960</td>\n",
       "      <td>0.997127</td>\n",
       "      <td>1.271593</td>\n",
       "      <td>1.270484</td>\n",
       "      <td>0.963065</td>\n",
       "      <td>0.962101</td>\n",
       "      <td>1.536562</td>\n",
       "      <td>0.928185</td>\n",
       "      <td>0.982128</td>\n",
       "      <td>0.256010</td>\n",
       "      <td>1.254369</td>\n",
       "      <td>0.497496</td>\n",
       "      <td>0.874526</td>\n",
       "      <td>0.980814</td>\n",
       "      <td>0.367372</td>\n",
       "      <td>0.497962</td>\n",
       "      <td>0.523980</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8216</th>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>32</td>\n",
       "      <td>MD23</td>\n",
       "      <td>Col0-MD2344678</td>\n",
       "      <td>27</td>\n",
       "      <td>Col0</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.925461</td>\n",
       "      <td>0.952813</td>\n",
       "      <td>0.957381</td>\n",
       "      <td>1.007677</td>\n",
       "      <td>0.903700</td>\n",
       "      <td>2.377605</td>\n",
       "      <td>0.995677</td>\n",
       "      <td>0.977792</td>\n",
       "      <td>1.597171</td>\n",
       "      <td>0.976339</td>\n",
       "      <td>1.012290</td>\n",
       "      <td>0.395505</td>\n",
       "      <td>1.229662</td>\n",
       "      <td>1.065818</td>\n",
       "      <td>1.196320</td>\n",
       "      <td>1.077575</td>\n",
       "      <td>0.837245</td>\n",
       "      <td>0.587654</td>\n",
       "      <td>0.543157</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8217</th>\n",
       "      <td>2022-04-28</td>\n",
       "      <td>34</td>\n",
       "      <td>MD23</td>\n",
       "      <td>Col0-MD2344679</td>\n",
       "      <td>28</td>\n",
       "      <td>Col0</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.972349</td>\n",
       "      <td>1.010041</td>\n",
       "      <td>1.016336</td>\n",
       "      <td>1.009175</td>\n",
       "      <td>1.101697</td>\n",
       "      <td>1.999537</td>\n",
       "      <td>1.004494</td>\n",
       "      <td>0.991260</td>\n",
       "      <td>1.469813</td>\n",
       "      <td>0.998048</td>\n",
       "      <td>1.016624</td>\n",
       "      <td>0.229892</td>\n",
       "      <td>1.140656</td>\n",
       "      <td>1.305324</td>\n",
       "      <td>1.102971</td>\n",
       "      <td>0.924771</td>\n",
       "      <td>1.270612</td>\n",
       "      <td>0.587654</td>\n",
       "      <td>0.543157</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8218</th>\n",
       "      <td>2022-04-29</td>\n",
       "      <td>36</td>\n",
       "      <td>MD23</td>\n",
       "      <td>Col0-MD2344680</td>\n",
       "      <td>29</td>\n",
       "      <td>Col0</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.985323</td>\n",
       "      <td>1.018502</td>\n",
       "      <td>1.024044</td>\n",
       "      <td>1.008657</td>\n",
       "      <td>1.211429</td>\n",
       "      <td>2.563956</td>\n",
       "      <td>1.011841</td>\n",
       "      <td>1.002644</td>\n",
       "      <td>1.316911</td>\n",
       "      <td>0.988265</td>\n",
       "      <td>1.014070</td>\n",
       "      <td>0.297588</td>\n",
       "      <td>1.105096</td>\n",
       "      <td>1.710932</td>\n",
       "      <td>1.033091</td>\n",
       "      <td>0.821489</td>\n",
       "      <td>1.075732</td>\n",
       "      <td>0.587654</td>\n",
       "      <td>0.543157</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8219</th>\n",
       "      <td>2022-04-30</td>\n",
       "      <td>38</td>\n",
       "      <td>MD23</td>\n",
       "      <td>Col0-MD2344681</td>\n",
       "      <td>30</td>\n",
       "      <td>Col0</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>0.997995</td>\n",
       "      <td>1.024222</td>\n",
       "      <td>1.028603</td>\n",
       "      <td>1.006540</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.587654</td>\n",
       "      <td>0.543157</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8220</th>\n",
       "      <td>2022-05-02</td>\n",
       "      <td>41</td>\n",
       "      <td>MD23</td>\n",
       "      <td>Col0-MD2344683</td>\n",
       "      <td>32</td>\n",
       "      <td>Col0</td>\n",
       "      <td>medium drought</td>\n",
       "      <td>1.058518</td>\n",
       "      <td>1.103573</td>\n",
       "      <td>1.111099</td>\n",
       "      <td>1.010426</td>\n",
       "      <td>1.397193</td>\n",
       "      <td>2.905623</td>\n",
       "      <td>1.028960</td>\n",
       "      <td>1.024082</td>\n",
       "      <td>1.221372</td>\n",
       "      <td>1.019369</td>\n",
       "      <td>1.032593</td>\n",
       "      <td>0.674094</td>\n",
       "      <td>0.987089</td>\n",
       "      <td>2.434626</td>\n",
       "      <td>0.877689</td>\n",
       "      <td>1.086001</td>\n",
       "      <td>1.421700</td>\n",
       "      <td>0.587654</td>\n",
       "      <td>0.543157</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2150 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Measuring_date  Round_Order plant_ID_treatment      plant ID 2  \\\n",
       "3        2022-04-22           22                MD5  FC5 1-MD544673   \n",
       "4        2022-04-23           24                MD5  FC5 1-MD544674   \n",
       "5        2022-04-24           26                MD5  FC5 1-MD544675   \n",
       "6        2022-04-25           28                MD5  FC5 1-MD544676   \n",
       "7        2022-04-26           30                MD5  FC5 1-MD544677   \n",
       "...             ...          ...                ...             ...   \n",
       "8216     2022-04-27           32               MD23  Col0-MD2344678   \n",
       "8217     2022-04-28           34               MD23  Col0-MD2344679   \n",
       "8218     2022-04-29           36               MD23  Col0-MD2344680   \n",
       "8219     2022-04-30           38               MD23  Col0-MD2344681   \n",
       "8220     2022-05-02           41               MD23  Col0-MD2344683   \n",
       "\n",
       "      Day_after_sowing transgenic_line      treatement  ratio_Fo  ratio_Fm  \\\n",
       "3                   22           FC5_1  medium drought  0.808324  0.745102   \n",
       "4                   23           FC5_1  medium drought  0.858954  0.804701   \n",
       "5                   24           FC5_1  medium drought  0.903268  0.850845   \n",
       "6                   25           FC5_1  medium drought  0.921387  0.862457   \n",
       "7                   26           FC5_1  medium drought  0.926482  0.898717   \n",
       "...                ...             ...             ...       ...       ...   \n",
       "8216                27            Col0  medium drought  0.925461  0.952813   \n",
       "8217                28            Col0  medium drought  0.972349  1.010041   \n",
       "8218                29            Col0  medium drought  0.985323  1.018502   \n",
       "8219                30            Col0  medium drought  0.997995  1.024222   \n",
       "8220                32            Col0  medium drought  1.058518  1.103573   \n",
       "\n",
       "      ratio_Fv  ratio_QY_max  ratio_NDVI2  ratio_PRI  ratio_SIPI  ratio_NDVI  \\\n",
       "3     0.734269      0.985817     0.700204  -0.679460    0.912743    0.894603   \n",
       "4     0.795404      0.989249     0.952928  -0.330063    0.930660    0.919801   \n",
       "5     0.841862      0.991230     0.875763   0.270387    0.948872    0.942715   \n",
       "6     0.852359      0.989034     1.127202   0.499599    0.955140    0.948110   \n",
       "7     0.893960      0.997127     1.271593   1.270484    0.963065    0.962101   \n",
       "...        ...           ...          ...        ...         ...         ...   \n",
       "8216  0.957381      1.007677     0.903700   2.377605    0.995677    0.977792   \n",
       "8217  1.016336      1.009175     1.101697   1.999537    1.004494    0.991260   \n",
       "8218  1.024044      1.008657     1.211429   2.563956    1.011841    1.002644   \n",
       "8219  1.028603      1.006540          NaN        NaN         NaN         NaN   \n",
       "8220  1.111099      1.010426     1.397193   2.905623    1.028960    1.024082   \n",
       "\n",
       "      ratio_PSRI  ratio_MCARI1  ratio_OSAVI  ratio_Slenderness  \\\n",
       "3       1.979029      0.809201     0.934326           0.191227   \n",
       "4       1.909950      0.827104     0.942283           0.161725   \n",
       "5       1.683619      0.853953     0.953095           0.136707   \n",
       "6       1.799318      0.876950     0.961356           0.235961   \n",
       "7       1.536562      0.928185     0.982128           0.256010   \n",
       "...          ...           ...          ...                ...   \n",
       "8216    1.597171      0.976339     1.012290           0.395505   \n",
       "8217    1.469813      0.998048     1.016624           0.229892   \n",
       "8218    1.316911      0.988265     1.014070           0.297588   \n",
       "8219         NaN           NaN          NaN                NaN   \n",
       "8220    1.221372      1.019369     1.032593           0.674094   \n",
       "\n",
       "      ratio_WLI/NDVI  ratio_%RGB(72,84,58)  ratio_%RGB(73,86,36)  \\\n",
       "3           1.717645              0.411842              0.775014   \n",
       "4           1.485783              0.381980              0.776349   \n",
       "5           1.383999              0.337792              0.963936   \n",
       "6           1.284788              0.396080              1.062548   \n",
       "7           1.254369              0.497496              0.874526   \n",
       "...              ...                   ...                   ...   \n",
       "8216        1.229662              1.065818              1.196320   \n",
       "8217        1.140656              1.305324              1.102971   \n",
       "8218        1.105096              1.710932              1.033091   \n",
       "8219             NaN                   NaN                   NaN   \n",
       "8220        0.987089              2.434626              0.877689   \n",
       "\n",
       "      ratio_%RGB(57,71,46)  ratio_%RGB(59,71,20)      drr1      drr2 outlier  \n",
       "3                 1.244413              0.465728  0.497962  0.523980      no  \n",
       "4                 1.026069              0.533027  0.497962  0.523980      no  \n",
       "5                 1.042887              0.590085  0.497962  0.523980      no  \n",
       "6                 0.703712              0.807426  0.497962  0.523980      no  \n",
       "7                 0.980814              0.367372  0.497962  0.523980      no  \n",
       "...                    ...                   ...       ...       ...     ...  \n",
       "8216              1.077575              0.837245  0.587654  0.543157      no  \n",
       "8217              0.924771              1.270612  0.587654  0.543157      no  \n",
       "8218              0.821489              1.075732  0.587654  0.543157      no  \n",
       "8219                   NaN                   NaN  0.587654  0.543157      no  \n",
       "8220              1.086001              1.421700  0.587654  0.543157      no  \n",
       "\n",
       "[2150 rows x 27 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "md_22_32 = filter_date_treatment(merge_data, 22,32,'medium drought') ; md_22_32"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute some stats about ratio features for `medium drought` and `severe drought` datasets \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">Col0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC4_1</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC4_2</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC5_1</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC5_2</th>\n",
       "      <th colspan=\"2\" halign=\"left\">irx10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">irx14</th>\n",
       "      <th colspan=\"2\" halign=\"left\">irx9_2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ratio_Fo</th>\n",
       "      <td>1.051891</td>\n",
       "      <td>0.003324</td>\n",
       "      <td>1.022294</td>\n",
       "      <td>0.005508</td>\n",
       "      <td>1.039590</td>\n",
       "      <td>0.004227</td>\n",
       "      <td>1.041521</td>\n",
       "      <td>0.004523</td>\n",
       "      <td>1.038700</td>\n",
       "      <td>0.004463</td>\n",
       "      <td>1.003063</td>\n",
       "      <td>0.004409</td>\n",
       "      <td>1.044543</td>\n",
       "      <td>0.004211</td>\n",
       "      <td>1.044280</td>\n",
       "      <td>0.004957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_Fm</th>\n",
       "      <td>1.120280</td>\n",
       "      <td>0.003586</td>\n",
       "      <td>1.099018</td>\n",
       "      <td>0.005825</td>\n",
       "      <td>1.106759</td>\n",
       "      <td>0.004795</td>\n",
       "      <td>1.115615</td>\n",
       "      <td>0.004789</td>\n",
       "      <td>1.111249</td>\n",
       "      <td>0.004295</td>\n",
       "      <td>1.122655</td>\n",
       "      <td>0.004475</td>\n",
       "      <td>1.141368</td>\n",
       "      <td>0.004665</td>\n",
       "      <td>1.102438</td>\n",
       "      <td>0.004844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_Fv</th>\n",
       "      <td>1.131703</td>\n",
       "      <td>0.003732</td>\n",
       "      <td>1.112360</td>\n",
       "      <td>0.006055</td>\n",
       "      <td>1.118460</td>\n",
       "      <td>0.005032</td>\n",
       "      <td>1.128311</td>\n",
       "      <td>0.004949</td>\n",
       "      <td>1.123783</td>\n",
       "      <td>0.004608</td>\n",
       "      <td>1.144359</td>\n",
       "      <td>0.004611</td>\n",
       "      <td>1.158034</td>\n",
       "      <td>0.004843</td>\n",
       "      <td>1.112175</td>\n",
       "      <td>0.004922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_QY_max</th>\n",
       "      <td>1.013196</td>\n",
       "      <td>0.000285</td>\n",
       "      <td>1.014561</td>\n",
       "      <td>0.000645</td>\n",
       "      <td>1.013193</td>\n",
       "      <td>0.000495</td>\n",
       "      <td>1.014335</td>\n",
       "      <td>0.000403</td>\n",
       "      <td>1.013576</td>\n",
       "      <td>0.000863</td>\n",
       "      <td>1.023231</td>\n",
       "      <td>0.000384</td>\n",
       "      <td>1.018915</td>\n",
       "      <td>0.000379</td>\n",
       "      <td>1.012819</td>\n",
       "      <td>0.000495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_NDVI2</th>\n",
       "      <td>1.551325</td>\n",
       "      <td>0.027310</td>\n",
       "      <td>1.463935</td>\n",
       "      <td>0.027474</td>\n",
       "      <td>1.398384</td>\n",
       "      <td>0.022406</td>\n",
       "      <td>1.401886</td>\n",
       "      <td>0.028205</td>\n",
       "      <td>1.572550</td>\n",
       "      <td>0.020536</td>\n",
       "      <td>1.477036</td>\n",
       "      <td>0.030702</td>\n",
       "      <td>1.724728</td>\n",
       "      <td>0.035269</td>\n",
       "      <td>1.503045</td>\n",
       "      <td>0.031048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_PRI</th>\n",
       "      <td>1.546620</td>\n",
       "      <td>0.042343</td>\n",
       "      <td>1.614667</td>\n",
       "      <td>0.066058</td>\n",
       "      <td>1.466372</td>\n",
       "      <td>0.044385</td>\n",
       "      <td>1.542313</td>\n",
       "      <td>0.052883</td>\n",
       "      <td>1.381828</td>\n",
       "      <td>0.048675</td>\n",
       "      <td>2.008399</td>\n",
       "      <td>0.092899</td>\n",
       "      <td>2.386658</td>\n",
       "      <td>0.086844</td>\n",
       "      <td>1.260973</td>\n",
       "      <td>0.050789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_SIPI</th>\n",
       "      <td>1.015397</td>\n",
       "      <td>0.001298</td>\n",
       "      <td>1.009161</td>\n",
       "      <td>0.001596</td>\n",
       "      <td>1.013121</td>\n",
       "      <td>0.001418</td>\n",
       "      <td>1.008876</td>\n",
       "      <td>0.001400</td>\n",
       "      <td>1.011271</td>\n",
       "      <td>0.001006</td>\n",
       "      <td>1.014457</td>\n",
       "      <td>0.001392</td>\n",
       "      <td>1.021520</td>\n",
       "      <td>0.001508</td>\n",
       "      <td>1.018976</td>\n",
       "      <td>0.001346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_NDVI</th>\n",
       "      <td>1.009656</td>\n",
       "      <td>0.001593</td>\n",
       "      <td>1.000234</td>\n",
       "      <td>0.001854</td>\n",
       "      <td>1.006375</td>\n",
       "      <td>0.001701</td>\n",
       "      <td>0.998053</td>\n",
       "      <td>0.001856</td>\n",
       "      <td>1.004278</td>\n",
       "      <td>0.001212</td>\n",
       "      <td>1.006902</td>\n",
       "      <td>0.001674</td>\n",
       "      <td>1.014083</td>\n",
       "      <td>0.001826</td>\n",
       "      <td>1.003140</td>\n",
       "      <td>0.001674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_PSRI</th>\n",
       "      <td>1.316078</td>\n",
       "      <td>0.012910</td>\n",
       "      <td>1.391250</td>\n",
       "      <td>0.017273</td>\n",
       "      <td>1.378249</td>\n",
       "      <td>0.014897</td>\n",
       "      <td>1.512463</td>\n",
       "      <td>0.020272</td>\n",
       "      <td>1.442269</td>\n",
       "      <td>0.014798</td>\n",
       "      <td>1.362775</td>\n",
       "      <td>0.013201</td>\n",
       "      <td>1.338022</td>\n",
       "      <td>0.013261</td>\n",
       "      <td>1.467528</td>\n",
       "      <td>0.015881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_MCARI1</th>\n",
       "      <td>1.134294</td>\n",
       "      <td>0.004394</td>\n",
       "      <td>1.111869</td>\n",
       "      <td>0.006396</td>\n",
       "      <td>1.112470</td>\n",
       "      <td>0.005140</td>\n",
       "      <td>1.119166</td>\n",
       "      <td>0.005717</td>\n",
       "      <td>1.111080</td>\n",
       "      <td>0.005361</td>\n",
       "      <td>1.113732</td>\n",
       "      <td>0.005064</td>\n",
       "      <td>1.140607</td>\n",
       "      <td>0.005463</td>\n",
       "      <td>1.089272</td>\n",
       "      <td>0.005954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_OSAVI</th>\n",
       "      <td>1.079076</td>\n",
       "      <td>0.001372</td>\n",
       "      <td>1.083708</td>\n",
       "      <td>0.002045</td>\n",
       "      <td>1.070173</td>\n",
       "      <td>0.001577</td>\n",
       "      <td>1.078433</td>\n",
       "      <td>0.001825</td>\n",
       "      <td>1.073620</td>\n",
       "      <td>0.001703</td>\n",
       "      <td>1.079000</td>\n",
       "      <td>0.001696</td>\n",
       "      <td>1.084831</td>\n",
       "      <td>0.001731</td>\n",
       "      <td>1.074788</td>\n",
       "      <td>0.002035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_Slenderness</th>\n",
       "      <td>0.958588</td>\n",
       "      <td>0.031388</td>\n",
       "      <td>1.038431</td>\n",
       "      <td>0.055231</td>\n",
       "      <td>0.509507</td>\n",
       "      <td>0.017700</td>\n",
       "      <td>0.846186</td>\n",
       "      <td>0.045892</td>\n",
       "      <td>0.669920</td>\n",
       "      <td>0.034585</td>\n",
       "      <td>1.018255</td>\n",
       "      <td>0.051758</td>\n",
       "      <td>1.001954</td>\n",
       "      <td>0.039325</td>\n",
       "      <td>1.612842</td>\n",
       "      <td>0.076600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_WLI/NDVI</th>\n",
       "      <td>1.087457</td>\n",
       "      <td>0.007094</td>\n",
       "      <td>1.113770</td>\n",
       "      <td>0.008256</td>\n",
       "      <td>1.123715</td>\n",
       "      <td>0.008030</td>\n",
       "      <td>1.139397</td>\n",
       "      <td>0.008260</td>\n",
       "      <td>1.130894</td>\n",
       "      <td>0.006758</td>\n",
       "      <td>1.114021</td>\n",
       "      <td>0.007449</td>\n",
       "      <td>1.063406</td>\n",
       "      <td>0.007942</td>\n",
       "      <td>1.127171</td>\n",
       "      <td>0.006328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(72,84,58)</th>\n",
       "      <td>2.612471</td>\n",
       "      <td>0.047530</td>\n",
       "      <td>3.660677</td>\n",
       "      <td>0.064144</td>\n",
       "      <td>2.997612</td>\n",
       "      <td>0.059749</td>\n",
       "      <td>3.590948</td>\n",
       "      <td>0.059418</td>\n",
       "      <td>3.221070</td>\n",
       "      <td>0.052316</td>\n",
       "      <td>3.492051</td>\n",
       "      <td>0.056483</td>\n",
       "      <td>2.884254</td>\n",
       "      <td>0.046895</td>\n",
       "      <td>1.560623</td>\n",
       "      <td>0.030462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(73,86,36)</th>\n",
       "      <td>0.735650</td>\n",
       "      <td>0.015374</td>\n",
       "      <td>0.389519</td>\n",
       "      <td>0.018595</td>\n",
       "      <td>0.818053</td>\n",
       "      <td>0.015771</td>\n",
       "      <td>0.494383</td>\n",
       "      <td>0.015041</td>\n",
       "      <td>0.532462</td>\n",
       "      <td>0.018881</td>\n",
       "      <td>0.514241</td>\n",
       "      <td>0.017272</td>\n",
       "      <td>0.643876</td>\n",
       "      <td>0.017032</td>\n",
       "      <td>0.164991</td>\n",
       "      <td>0.013013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(57,71,46)</th>\n",
       "      <td>2.085571</td>\n",
       "      <td>0.051895</td>\n",
       "      <td>2.800275</td>\n",
       "      <td>0.069866</td>\n",
       "      <td>2.102237</td>\n",
       "      <td>0.071956</td>\n",
       "      <td>2.430187</td>\n",
       "      <td>0.047097</td>\n",
       "      <td>2.634719</td>\n",
       "      <td>0.066823</td>\n",
       "      <td>2.607347</td>\n",
       "      <td>0.043674</td>\n",
       "      <td>2.081376</td>\n",
       "      <td>0.043508</td>\n",
       "      <td>2.676398</td>\n",
       "      <td>0.042029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(59,71,20)</th>\n",
       "      <td>0.850504</td>\n",
       "      <td>0.027661</td>\n",
       "      <td>0.580718</td>\n",
       "      <td>0.027693</td>\n",
       "      <td>1.004038</td>\n",
       "      <td>0.029126</td>\n",
       "      <td>0.723050</td>\n",
       "      <td>0.024780</td>\n",
       "      <td>0.833821</td>\n",
       "      <td>0.023745</td>\n",
       "      <td>0.815594</td>\n",
       "      <td>0.031264</td>\n",
       "      <td>0.956340</td>\n",
       "      <td>0.036625</td>\n",
       "      <td>0.203367</td>\n",
       "      <td>0.013735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drr1</th>\n",
       "      <td>0.551828</td>\n",
       "      <td>0.018543</td>\n",
       "      <td>0.320878</td>\n",
       "      <td>0.014471</td>\n",
       "      <td>0.485287</td>\n",
       "      <td>0.016993</td>\n",
       "      <td>0.378320</td>\n",
       "      <td>0.012334</td>\n",
       "      <td>0.379953</td>\n",
       "      <td>0.012043</td>\n",
       "      <td>0.456210</td>\n",
       "      <td>0.019338</td>\n",
       "      <td>0.624006</td>\n",
       "      <td>0.024184</td>\n",
       "      <td>0.191600</td>\n",
       "      <td>0.011473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drr2</th>\n",
       "      <td>0.540035</td>\n",
       "      <td>0.025754</td>\n",
       "      <td>0.327222</td>\n",
       "      <td>0.028458</td>\n",
       "      <td>0.516884</td>\n",
       "      <td>0.026018</td>\n",
       "      <td>0.566107</td>\n",
       "      <td>0.023814</td>\n",
       "      <td>0.484534</td>\n",
       "      <td>0.032963</td>\n",
       "      <td>0.464551</td>\n",
       "      <td>0.022120</td>\n",
       "      <td>0.870232</td>\n",
       "      <td>0.034735</td>\n",
       "      <td>0.354187</td>\n",
       "      <td>0.021994</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Col0               FC4_1               FC4_2  \\\n",
       "                          mean        se      mean        se      mean   \n",
       "ratio_Fo              1.051891  0.003324  1.022294  0.005508  1.039590   \n",
       "ratio_Fm              1.120280  0.003586  1.099018  0.005825  1.106759   \n",
       "ratio_Fv              1.131703  0.003732  1.112360  0.006055  1.118460   \n",
       "ratio_QY_max          1.013196  0.000285  1.014561  0.000645  1.013193   \n",
       "ratio_NDVI2           1.551325  0.027310  1.463935  0.027474  1.398384   \n",
       "ratio_PRI             1.546620  0.042343  1.614667  0.066058  1.466372   \n",
       "ratio_SIPI            1.015397  0.001298  1.009161  0.001596  1.013121   \n",
       "ratio_NDVI            1.009656  0.001593  1.000234  0.001854  1.006375   \n",
       "ratio_PSRI            1.316078  0.012910  1.391250  0.017273  1.378249   \n",
       "ratio_MCARI1          1.134294  0.004394  1.111869  0.006396  1.112470   \n",
       "ratio_OSAVI           1.079076  0.001372  1.083708  0.002045  1.070173   \n",
       "ratio_Slenderness     0.958588  0.031388  1.038431  0.055231  0.509507   \n",
       "ratio_WLI/NDVI        1.087457  0.007094  1.113770  0.008256  1.123715   \n",
       "ratio_%RGB(72,84,58)  2.612471  0.047530  3.660677  0.064144  2.997612   \n",
       "ratio_%RGB(73,86,36)  0.735650  0.015374  0.389519  0.018595  0.818053   \n",
       "ratio_%RGB(57,71,46)  2.085571  0.051895  2.800275  0.069866  2.102237   \n",
       "ratio_%RGB(59,71,20)  0.850504  0.027661  0.580718  0.027693  1.004038   \n",
       "drr1                  0.551828  0.018543  0.320878  0.014471  0.485287   \n",
       "drr2                  0.540035  0.025754  0.327222  0.028458  0.516884   \n",
       "\n",
       "                                   FC5_1               FC5_2            \\\n",
       "                            se      mean        se      mean        se   \n",
       "ratio_Fo              0.004227  1.041521  0.004523  1.038700  0.004463   \n",
       "ratio_Fm              0.004795  1.115615  0.004789  1.111249  0.004295   \n",
       "ratio_Fv              0.005032  1.128311  0.004949  1.123783  0.004608   \n",
       "ratio_QY_max          0.000495  1.014335  0.000403  1.013576  0.000863   \n",
       "ratio_NDVI2           0.022406  1.401886  0.028205  1.572550  0.020536   \n",
       "ratio_PRI             0.044385  1.542313  0.052883  1.381828  0.048675   \n",
       "ratio_SIPI            0.001418  1.008876  0.001400  1.011271  0.001006   \n",
       "ratio_NDVI            0.001701  0.998053  0.001856  1.004278  0.001212   \n",
       "ratio_PSRI            0.014897  1.512463  0.020272  1.442269  0.014798   \n",
       "ratio_MCARI1          0.005140  1.119166  0.005717  1.111080  0.005361   \n",
       "ratio_OSAVI           0.001577  1.078433  0.001825  1.073620  0.001703   \n",
       "ratio_Slenderness     0.017700  0.846186  0.045892  0.669920  0.034585   \n",
       "ratio_WLI/NDVI        0.008030  1.139397  0.008260  1.130894  0.006758   \n",
       "ratio_%RGB(72,84,58)  0.059749  3.590948  0.059418  3.221070  0.052316   \n",
       "ratio_%RGB(73,86,36)  0.015771  0.494383  0.015041  0.532462  0.018881   \n",
       "ratio_%RGB(57,71,46)  0.071956  2.430187  0.047097  2.634719  0.066823   \n",
       "ratio_%RGB(59,71,20)  0.029126  0.723050  0.024780  0.833821  0.023745   \n",
       "drr1                  0.016993  0.378320  0.012334  0.379953  0.012043   \n",
       "drr2                  0.026018  0.566107  0.023814  0.484534  0.032963   \n",
       "\n",
       "                         irx10               irx14              irx9_2  \\\n",
       "                          mean        se      mean        se      mean   \n",
       "ratio_Fo              1.003063  0.004409  1.044543  0.004211  1.044280   \n",
       "ratio_Fm              1.122655  0.004475  1.141368  0.004665  1.102438   \n",
       "ratio_Fv              1.144359  0.004611  1.158034  0.004843  1.112175   \n",
       "ratio_QY_max          1.023231  0.000384  1.018915  0.000379  1.012819   \n",
       "ratio_NDVI2           1.477036  0.030702  1.724728  0.035269  1.503045   \n",
       "ratio_PRI             2.008399  0.092899  2.386658  0.086844  1.260973   \n",
       "ratio_SIPI            1.014457  0.001392  1.021520  0.001508  1.018976   \n",
       "ratio_NDVI            1.006902  0.001674  1.014083  0.001826  1.003140   \n",
       "ratio_PSRI            1.362775  0.013201  1.338022  0.013261  1.467528   \n",
       "ratio_MCARI1          1.113732  0.005064  1.140607  0.005463  1.089272   \n",
       "ratio_OSAVI           1.079000  0.001696  1.084831  0.001731  1.074788   \n",
       "ratio_Slenderness     1.018255  0.051758  1.001954  0.039325  1.612842   \n",
       "ratio_WLI/NDVI        1.114021  0.007449  1.063406  0.007942  1.127171   \n",
       "ratio_%RGB(72,84,58)  3.492051  0.056483  2.884254  0.046895  1.560623   \n",
       "ratio_%RGB(73,86,36)  0.514241  0.017272  0.643876  0.017032  0.164991   \n",
       "ratio_%RGB(57,71,46)  2.607347  0.043674  2.081376  0.043508  2.676398   \n",
       "ratio_%RGB(59,71,20)  0.815594  0.031264  0.956340  0.036625  0.203367   \n",
       "drr1                  0.456210  0.019338  0.624006  0.024184  0.191600   \n",
       "drr2                  0.464551  0.022120  0.870232  0.034735  0.354187   \n",
       "\n",
       "                                \n",
       "                            se  \n",
       "ratio_Fo              0.004957  \n",
       "ratio_Fm              0.004844  \n",
       "ratio_Fv              0.004922  \n",
       "ratio_QY_max          0.000495  \n",
       "ratio_NDVI2           0.031048  \n",
       "ratio_PRI             0.050789  \n",
       "ratio_SIPI            0.001346  \n",
       "ratio_NDVI            0.001674  \n",
       "ratio_PSRI            0.015881  \n",
       "ratio_MCARI1          0.005954  \n",
       "ratio_OSAVI           0.002035  \n",
       "ratio_Slenderness     0.076600  \n",
       "ratio_WLI/NDVI        0.006328  \n",
       "ratio_%RGB(72,84,58)  0.030462  \n",
       "ratio_%RGB(73,86,36)  0.013013  \n",
       "ratio_%RGB(57,71,46)  0.042029  \n",
       "ratio_%RGB(59,71,20)  0.013735  \n",
       "drr1                  0.011473  \n",
       "drr2                  0.021994  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calculate_mean_se(sd_27_37)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">Col0</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC4_1</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC4_2</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC5_1</th>\n",
       "      <th colspan=\"2\" halign=\"left\">FC5_2</th>\n",
       "      <th colspan=\"2\" halign=\"left\">irx10</th>\n",
       "      <th colspan=\"2\" halign=\"left\">irx14</th>\n",
       "      <th colspan=\"2\" halign=\"left\">irx9_2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "      <th>mean</th>\n",
       "      <th>se</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ratio_Fo</th>\n",
       "      <td>0.973446</td>\n",
       "      <td>0.005359</td>\n",
       "      <td>0.968677</td>\n",
       "      <td>0.006747</td>\n",
       "      <td>0.987794</td>\n",
       "      <td>0.005336</td>\n",
       "      <td>0.986855</td>\n",
       "      <td>0.004294</td>\n",
       "      <td>0.993630</td>\n",
       "      <td>0.005363</td>\n",
       "      <td>0.995970</td>\n",
       "      <td>0.005417</td>\n",
       "      <td>0.974225</td>\n",
       "      <td>0.006736</td>\n",
       "      <td>1.005549</td>\n",
       "      <td>0.007513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_Fm</th>\n",
       "      <td>0.961557</td>\n",
       "      <td>0.007046</td>\n",
       "      <td>0.962645</td>\n",
       "      <td>0.007265</td>\n",
       "      <td>0.986819</td>\n",
       "      <td>0.006246</td>\n",
       "      <td>0.977984</td>\n",
       "      <td>0.005589</td>\n",
       "      <td>0.988170</td>\n",
       "      <td>0.006473</td>\n",
       "      <td>1.010970</td>\n",
       "      <td>0.006366</td>\n",
       "      <td>1.004172</td>\n",
       "      <td>0.007418</td>\n",
       "      <td>1.002290</td>\n",
       "      <td>0.008361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_Fv</th>\n",
       "      <td>0.959571</td>\n",
       "      <td>0.007415</td>\n",
       "      <td>0.961596</td>\n",
       "      <td>0.007483</td>\n",
       "      <td>0.986649</td>\n",
       "      <td>0.006500</td>\n",
       "      <td>0.976464</td>\n",
       "      <td>0.005914</td>\n",
       "      <td>0.987226</td>\n",
       "      <td>0.006816</td>\n",
       "      <td>1.013692</td>\n",
       "      <td>0.006916</td>\n",
       "      <td>1.009327</td>\n",
       "      <td>0.007619</td>\n",
       "      <td>1.001744</td>\n",
       "      <td>0.008684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_QY_max</th>\n",
       "      <td>0.998843</td>\n",
       "      <td>0.000679</td>\n",
       "      <td>1.000032</td>\n",
       "      <td>0.000691</td>\n",
       "      <td>1.001111</td>\n",
       "      <td>0.000559</td>\n",
       "      <td>0.999443</td>\n",
       "      <td>0.000600</td>\n",
       "      <td>0.999772</td>\n",
       "      <td>0.000804</td>\n",
       "      <td>1.004057</td>\n",
       "      <td>0.001004</td>\n",
       "      <td>1.008181</td>\n",
       "      <td>0.000505</td>\n",
       "      <td>1.000462</td>\n",
       "      <td>0.000879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_NDVI2</th>\n",
       "      <td>1.116727</td>\n",
       "      <td>0.033926</td>\n",
       "      <td>1.111984</td>\n",
       "      <td>0.030896</td>\n",
       "      <td>1.085958</td>\n",
       "      <td>0.029045</td>\n",
       "      <td>1.128113</td>\n",
       "      <td>0.030111</td>\n",
       "      <td>1.068982</td>\n",
       "      <td>0.029554</td>\n",
       "      <td>1.153152</td>\n",
       "      <td>0.033973</td>\n",
       "      <td>1.182822</td>\n",
       "      <td>0.038374</td>\n",
       "      <td>1.124527</td>\n",
       "      <td>0.038753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_PRI</th>\n",
       "      <td>0.919127</td>\n",
       "      <td>0.068906</td>\n",
       "      <td>0.650034</td>\n",
       "      <td>0.114437</td>\n",
       "      <td>0.965024</td>\n",
       "      <td>0.076737</td>\n",
       "      <td>0.895275</td>\n",
       "      <td>0.065730</td>\n",
       "      <td>0.845001</td>\n",
       "      <td>0.072591</td>\n",
       "      <td>1.317762</td>\n",
       "      <td>0.098870</td>\n",
       "      <td>1.235892</td>\n",
       "      <td>0.147554</td>\n",
       "      <td>0.951107</td>\n",
       "      <td>0.095605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_SIPI</th>\n",
       "      <td>0.989585</td>\n",
       "      <td>0.002539</td>\n",
       "      <td>0.990513</td>\n",
       "      <td>0.002414</td>\n",
       "      <td>1.000041</td>\n",
       "      <td>0.002090</td>\n",
       "      <td>0.992735</td>\n",
       "      <td>0.002024</td>\n",
       "      <td>0.998287</td>\n",
       "      <td>0.002305</td>\n",
       "      <td>1.008701</td>\n",
       "      <td>0.002016</td>\n",
       "      <td>1.004915</td>\n",
       "      <td>0.002404</td>\n",
       "      <td>1.002964</td>\n",
       "      <td>0.002122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_NDVI</th>\n",
       "      <td>0.983065</td>\n",
       "      <td>0.002921</td>\n",
       "      <td>0.982669</td>\n",
       "      <td>0.002881</td>\n",
       "      <td>0.994247</td>\n",
       "      <td>0.002390</td>\n",
       "      <td>0.986145</td>\n",
       "      <td>0.002456</td>\n",
       "      <td>0.990572</td>\n",
       "      <td>0.002870</td>\n",
       "      <td>1.007098</td>\n",
       "      <td>0.002353</td>\n",
       "      <td>0.998438</td>\n",
       "      <td>0.002882</td>\n",
       "      <td>0.993761</td>\n",
       "      <td>0.003136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_PSRI</th>\n",
       "      <td>1.308336</td>\n",
       "      <td>0.015111</td>\n",
       "      <td>1.327444</td>\n",
       "      <td>0.018527</td>\n",
       "      <td>1.301337</td>\n",
       "      <td>0.014389</td>\n",
       "      <td>1.388550</td>\n",
       "      <td>0.020923</td>\n",
       "      <td>1.330780</td>\n",
       "      <td>0.017188</td>\n",
       "      <td>1.142252</td>\n",
       "      <td>0.013136</td>\n",
       "      <td>1.234440</td>\n",
       "      <td>0.016490</td>\n",
       "      <td>1.340343</td>\n",
       "      <td>0.035526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_MCARI1</th>\n",
       "      <td>0.989414</td>\n",
       "      <td>0.005837</td>\n",
       "      <td>0.993990</td>\n",
       "      <td>0.006530</td>\n",
       "      <td>1.007491</td>\n",
       "      <td>0.005307</td>\n",
       "      <td>1.006898</td>\n",
       "      <td>0.004725</td>\n",
       "      <td>1.014056</td>\n",
       "      <td>0.004966</td>\n",
       "      <td>1.035596</td>\n",
       "      <td>0.005308</td>\n",
       "      <td>1.029647</td>\n",
       "      <td>0.005367</td>\n",
       "      <td>1.016316</td>\n",
       "      <td>0.006996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_OSAVI</th>\n",
       "      <td>1.011380</td>\n",
       "      <td>0.002265</td>\n",
       "      <td>1.011466</td>\n",
       "      <td>0.002670</td>\n",
       "      <td>1.015780</td>\n",
       "      <td>0.001947</td>\n",
       "      <td>1.015788</td>\n",
       "      <td>0.001788</td>\n",
       "      <td>1.016049</td>\n",
       "      <td>0.001864</td>\n",
       "      <td>1.026250</td>\n",
       "      <td>0.001974</td>\n",
       "      <td>1.024882</td>\n",
       "      <td>0.002013</td>\n",
       "      <td>1.024681</td>\n",
       "      <td>0.002577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_Slenderness</th>\n",
       "      <td>0.505786</td>\n",
       "      <td>0.023708</td>\n",
       "      <td>0.408057</td>\n",
       "      <td>0.026025</td>\n",
       "      <td>0.429364</td>\n",
       "      <td>0.024741</td>\n",
       "      <td>0.465093</td>\n",
       "      <td>0.030553</td>\n",
       "      <td>0.411422</td>\n",
       "      <td>0.029269</td>\n",
       "      <td>0.591219</td>\n",
       "      <td>0.036084</td>\n",
       "      <td>0.487049</td>\n",
       "      <td>0.024975</td>\n",
       "      <td>0.512730</td>\n",
       "      <td>0.038764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_WLI/NDVI</th>\n",
       "      <td>1.147115</td>\n",
       "      <td>0.010817</td>\n",
       "      <td>1.165223</td>\n",
       "      <td>0.015182</td>\n",
       "      <td>1.133941</td>\n",
       "      <td>0.011563</td>\n",
       "      <td>1.152134</td>\n",
       "      <td>0.010385</td>\n",
       "      <td>1.126099</td>\n",
       "      <td>0.011450</td>\n",
       "      <td>1.060521</td>\n",
       "      <td>0.009382</td>\n",
       "      <td>1.084810</td>\n",
       "      <td>0.010476</td>\n",
       "      <td>1.112302</td>\n",
       "      <td>0.009706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(72,84,58)</th>\n",
       "      <td>1.094671</td>\n",
       "      <td>0.028189</td>\n",
       "      <td>1.045427</td>\n",
       "      <td>0.026879</td>\n",
       "      <td>1.147033</td>\n",
       "      <td>0.028621</td>\n",
       "      <td>0.962789</td>\n",
       "      <td>0.026288</td>\n",
       "      <td>1.035054</td>\n",
       "      <td>0.030665</td>\n",
       "      <td>1.167021</td>\n",
       "      <td>0.031339</td>\n",
       "      <td>1.147517</td>\n",
       "      <td>0.029438</td>\n",
       "      <td>1.305951</td>\n",
       "      <td>0.023354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(73,86,36)</th>\n",
       "      <td>0.980633</td>\n",
       "      <td>0.012983</td>\n",
       "      <td>0.994918</td>\n",
       "      <td>0.015049</td>\n",
       "      <td>1.093130</td>\n",
       "      <td>0.014498</td>\n",
       "      <td>0.987173</td>\n",
       "      <td>0.014083</td>\n",
       "      <td>1.081397</td>\n",
       "      <td>0.016447</td>\n",
       "      <td>1.053942</td>\n",
       "      <td>0.013284</td>\n",
       "      <td>1.048818</td>\n",
       "      <td>0.013943</td>\n",
       "      <td>0.833741</td>\n",
       "      <td>0.021980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(57,71,46)</th>\n",
       "      <td>1.092568</td>\n",
       "      <td>0.018711</td>\n",
       "      <td>1.099581</td>\n",
       "      <td>0.018197</td>\n",
       "      <td>1.094124</td>\n",
       "      <td>0.022295</td>\n",
       "      <td>0.993057</td>\n",
       "      <td>0.016631</td>\n",
       "      <td>0.987934</td>\n",
       "      <td>0.018413</td>\n",
       "      <td>1.030050</td>\n",
       "      <td>0.019864</td>\n",
       "      <td>1.039299</td>\n",
       "      <td>0.016514</td>\n",
       "      <td>1.183771</td>\n",
       "      <td>0.023057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ratio_%RGB(59,71,20)</th>\n",
       "      <td>0.703308</td>\n",
       "      <td>0.024531</td>\n",
       "      <td>0.674187</td>\n",
       "      <td>0.023746</td>\n",
       "      <td>0.841235</td>\n",
       "      <td>0.028712</td>\n",
       "      <td>0.784541</td>\n",
       "      <td>0.029345</td>\n",
       "      <td>0.836801</td>\n",
       "      <td>0.029438</td>\n",
       "      <td>0.850826</td>\n",
       "      <td>0.029260</td>\n",
       "      <td>0.856281</td>\n",
       "      <td>0.034176</td>\n",
       "      <td>0.662526</td>\n",
       "      <td>0.033417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drr1</th>\n",
       "      <td>0.812282</td>\n",
       "      <td>0.024003</td>\n",
       "      <td>0.817124</td>\n",
       "      <td>0.025309</td>\n",
       "      <td>0.924905</td>\n",
       "      <td>0.022363</td>\n",
       "      <td>0.885820</td>\n",
       "      <td>0.019224</td>\n",
       "      <td>1.082072</td>\n",
       "      <td>0.023065</td>\n",
       "      <td>1.151555</td>\n",
       "      <td>0.032286</td>\n",
       "      <td>1.056450</td>\n",
       "      <td>0.023903</td>\n",
       "      <td>0.933784</td>\n",
       "      <td>0.028827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>drr2</th>\n",
       "      <td>0.809249</td>\n",
       "      <td>0.019254</td>\n",
       "      <td>0.812942</td>\n",
       "      <td>0.020477</td>\n",
       "      <td>0.882892</td>\n",
       "      <td>0.019709</td>\n",
       "      <td>0.876941</td>\n",
       "      <td>0.017510</td>\n",
       "      <td>0.927791</td>\n",
       "      <td>0.023209</td>\n",
       "      <td>1.141527</td>\n",
       "      <td>0.026121</td>\n",
       "      <td>0.986355</td>\n",
       "      <td>0.025762</td>\n",
       "      <td>0.934504</td>\n",
       "      <td>0.031138</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Col0               FC4_1               FC4_2  \\\n",
       "                          mean        se      mean        se      mean   \n",
       "ratio_Fo              0.973446  0.005359  0.968677  0.006747  0.987794   \n",
       "ratio_Fm              0.961557  0.007046  0.962645  0.007265  0.986819   \n",
       "ratio_Fv              0.959571  0.007415  0.961596  0.007483  0.986649   \n",
       "ratio_QY_max          0.998843  0.000679  1.000032  0.000691  1.001111   \n",
       "ratio_NDVI2           1.116727  0.033926  1.111984  0.030896  1.085958   \n",
       "ratio_PRI             0.919127  0.068906  0.650034  0.114437  0.965024   \n",
       "ratio_SIPI            0.989585  0.002539  0.990513  0.002414  1.000041   \n",
       "ratio_NDVI            0.983065  0.002921  0.982669  0.002881  0.994247   \n",
       "ratio_PSRI            1.308336  0.015111  1.327444  0.018527  1.301337   \n",
       "ratio_MCARI1          0.989414  0.005837  0.993990  0.006530  1.007491   \n",
       "ratio_OSAVI           1.011380  0.002265  1.011466  0.002670  1.015780   \n",
       "ratio_Slenderness     0.505786  0.023708  0.408057  0.026025  0.429364   \n",
       "ratio_WLI/NDVI        1.147115  0.010817  1.165223  0.015182  1.133941   \n",
       "ratio_%RGB(72,84,58)  1.094671  0.028189  1.045427  0.026879  1.147033   \n",
       "ratio_%RGB(73,86,36)  0.980633  0.012983  0.994918  0.015049  1.093130   \n",
       "ratio_%RGB(57,71,46)  1.092568  0.018711  1.099581  0.018197  1.094124   \n",
       "ratio_%RGB(59,71,20)  0.703308  0.024531  0.674187  0.023746  0.841235   \n",
       "drr1                  0.812282  0.024003  0.817124  0.025309  0.924905   \n",
       "drr2                  0.809249  0.019254  0.812942  0.020477  0.882892   \n",
       "\n",
       "                                   FC5_1               FC5_2            \\\n",
       "                            se      mean        se      mean        se   \n",
       "ratio_Fo              0.005336  0.986855  0.004294  0.993630  0.005363   \n",
       "ratio_Fm              0.006246  0.977984  0.005589  0.988170  0.006473   \n",
       "ratio_Fv              0.006500  0.976464  0.005914  0.987226  0.006816   \n",
       "ratio_QY_max          0.000559  0.999443  0.000600  0.999772  0.000804   \n",
       "ratio_NDVI2           0.029045  1.128113  0.030111  1.068982  0.029554   \n",
       "ratio_PRI             0.076737  0.895275  0.065730  0.845001  0.072591   \n",
       "ratio_SIPI            0.002090  0.992735  0.002024  0.998287  0.002305   \n",
       "ratio_NDVI            0.002390  0.986145  0.002456  0.990572  0.002870   \n",
       "ratio_PSRI            0.014389  1.388550  0.020923  1.330780  0.017188   \n",
       "ratio_MCARI1          0.005307  1.006898  0.004725  1.014056  0.004966   \n",
       "ratio_OSAVI           0.001947  1.015788  0.001788  1.016049  0.001864   \n",
       "ratio_Slenderness     0.024741  0.465093  0.030553  0.411422  0.029269   \n",
       "ratio_WLI/NDVI        0.011563  1.152134  0.010385  1.126099  0.011450   \n",
       "ratio_%RGB(72,84,58)  0.028621  0.962789  0.026288  1.035054  0.030665   \n",
       "ratio_%RGB(73,86,36)  0.014498  0.987173  0.014083  1.081397  0.016447   \n",
       "ratio_%RGB(57,71,46)  0.022295  0.993057  0.016631  0.987934  0.018413   \n",
       "ratio_%RGB(59,71,20)  0.028712  0.784541  0.029345  0.836801  0.029438   \n",
       "drr1                  0.022363  0.885820  0.019224  1.082072  0.023065   \n",
       "drr2                  0.019709  0.876941  0.017510  0.927791  0.023209   \n",
       "\n",
       "                         irx10               irx14              irx9_2  \\\n",
       "                          mean        se      mean        se      mean   \n",
       "ratio_Fo              0.995970  0.005417  0.974225  0.006736  1.005549   \n",
       "ratio_Fm              1.010970  0.006366  1.004172  0.007418  1.002290   \n",
       "ratio_Fv              1.013692  0.006916  1.009327  0.007619  1.001744   \n",
       "ratio_QY_max          1.004057  0.001004  1.008181  0.000505  1.000462   \n",
       "ratio_NDVI2           1.153152  0.033973  1.182822  0.038374  1.124527   \n",
       "ratio_PRI             1.317762  0.098870  1.235892  0.147554  0.951107   \n",
       "ratio_SIPI            1.008701  0.002016  1.004915  0.002404  1.002964   \n",
       "ratio_NDVI            1.007098  0.002353  0.998438  0.002882  0.993761   \n",
       "ratio_PSRI            1.142252  0.013136  1.234440  0.016490  1.340343   \n",
       "ratio_MCARI1          1.035596  0.005308  1.029647  0.005367  1.016316   \n",
       "ratio_OSAVI           1.026250  0.001974  1.024882  0.002013  1.024681   \n",
       "ratio_Slenderness     0.591219  0.036084  0.487049  0.024975  0.512730   \n",
       "ratio_WLI/NDVI        1.060521  0.009382  1.084810  0.010476  1.112302   \n",
       "ratio_%RGB(72,84,58)  1.167021  0.031339  1.147517  0.029438  1.305951   \n",
       "ratio_%RGB(73,86,36)  1.053942  0.013284  1.048818  0.013943  0.833741   \n",
       "ratio_%RGB(57,71,46)  1.030050  0.019864  1.039299  0.016514  1.183771   \n",
       "ratio_%RGB(59,71,20)  0.850826  0.029260  0.856281  0.034176  0.662526   \n",
       "drr1                  1.151555  0.032286  1.056450  0.023903  0.933784   \n",
       "drr2                  1.141527  0.026121  0.986355  0.025762  0.934504   \n",
       "\n",
       "                                \n",
       "                            se  \n",
       "ratio_Fo              0.007513  \n",
       "ratio_Fm              0.008361  \n",
       "ratio_Fv              0.008684  \n",
       "ratio_QY_max          0.000879  \n",
       "ratio_NDVI2           0.038753  \n",
       "ratio_PRI             0.095605  \n",
       "ratio_SIPI            0.002122  \n",
       "ratio_NDVI            0.003136  \n",
       "ratio_PSRI            0.035526  \n",
       "ratio_MCARI1          0.006996  \n",
       "ratio_OSAVI           0.002577  \n",
       "ratio_Slenderness     0.038764  \n",
       "ratio_WLI/NDVI        0.009706  \n",
       "ratio_%RGB(72,84,58)  0.023354  \n",
       "ratio_%RGB(73,86,36)  0.021980  \n",
       "ratio_%RGB(57,71,46)  0.023057  \n",
       "ratio_%RGB(59,71,20)  0.033417  \n",
       "drr1                  0.028827  \n",
       "drr2                  0.031138  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calculate_mean_se(md_22_32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ML exploration\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore polynomial regressions for `Area_(mm2)` feature \n",
    "\n",
    "Use the `plot_polynomial_regression()` function to plot the `Area_(mm2)` over `Day_after_snowing` features. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--- Regression 3 dregree with coefs : [ 0.00000000e+00  9.78818922e+01 -3.37411406e+00  3.81974844e-02] ---\n",
      "\n"
     ]
    }
   ],
   "source": [
    "plant_id = ['irx9_2_SD15','FC4_1_SD28', 'FC4_2_SD23','irx10_SD32','Col0_SD32',\n",
    " 'FC5_2_SD37', 'FC5_2_SD16', 'irx10_SD16',\n",
    " 'FC4_1_SD16', 'FC4_2_SD16', 'irx9_2_SD16', 'irx14_SD16',\n",
    " 'irx14_MD26', 'irx9_2_MD32']\n",
    "\n",
    "for p in plant_id : \n",
    "    plot_polynomial_regression(df, p, 3)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate a 2d dendrograms example for fixed features \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fixed `Day_after_sowing` parameter\n",
    "\n",
    "2d dendrogram generation for the `day=27` for the `severe drought` treatement and `day=32` for the `midium drought` treatement using the previous compputed ratios with the `plot_heatmap_with_dendrogram_2d_ratio()` function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#for severe drought\n",
    "day = 27\n",
    "sd = sd_27_37[sd_27_37['Day_after_sowing']==day]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "features = ['ratio_Slenderness','ratio_Fo', 'ratio_Fm', 'ratio_QY_max', 'ratio_NDVI2', 'ratio_PRI',\n",
    "            'ratio_SIPI', 'ratio_NDVI', 'ratio_PSRI', 'ratio_OSAVI','ratio_MCARI1',\n",
    "            'ratio_%RGB(72,84,58)', 'ratio_%RGB(73,86,36)', 'ratio_%RGB(57,71,46)', 'ratio_%RGB(59,71,20)', 'drr1']\n",
    "plot_heatmap_with_dendrogram_2d_ratio(sd,'severe drought',day, features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "day = 32\n",
    "md = md_22_32[md_22_32['Day_after_sowing']==day]\n",
    "features = ['ratio_Slenderness','ratio_Fo', 'ratio_Fm', 'ratio_QY_max', 'ratio_NDVI2', 'ratio_PRI',\n",
    "            'ratio_SIPI', 'ratio_NDVI', 'ratio_PSRI', 'ratio_OSAVI','ratio_MCARI1',\n",
    "            'ratio_%RGB(72,84,58)', 'ratio_%RGB(73,86,36)', 'ratio_%RGB(57,71,46)', 'ratio_%RGB(59,71,20)', 'drr1']\n",
    "plot_heatmap_with_dendrogram_2d_ratio(md,'medium drought',day, features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate dendrogram for multiple `Day_after_sowing`\n",
    "\n",
    "Concatenate two `Day_after_sowing` values (E:early, L:late)\n",
    "\n",
    "You can notice that some features have been renamed for fitting the paper nomenclature, more informations check the `preprocess_dataset_dendrogram()` function for more informations 🤓\n",
    "\n",
    "#### Severe drought dendrogram\n",
    "\n",
    "The example below is the dendrograms for the `severe drought` treatment for the `Day_after_sowing=[27,37]` parameters. The `Day_after_sowing=27` is called `Early (_E)` and the `Day_after_sowing=37` is called `Late (_L)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PVXZu/i+/52wuUI/2tS/7+cPB++jxL75TcVl4J3o9EtO0pnjrSJPs4jz1SKr+F2tGamdlpHbRs2Mn6flx52q/HoPCaqtS906pytm4dd3WbipQt47V1628IqR/PP2xXphypt6/bbIG9uys179sfIDSvVOqcjZUaWtjgbp3qt7Wypxc9evZST27tld8nGns7jupR+fGh7E9UlK1unBrW2sK89Ujpf5LtU4aMlyfrljS6HYkKT0lVWsKtraVXZCv9NTwL1tvDuvnF+vdy5bq07+t0Oafwz95laT01Orrt6Zg29uyqdJTU7Umv+r2LKi1PdNTU5VdsO15guiR1F7ZRVtHb9Z1zA1I66KM1C56buw5enHcJO3fhGOuR1qq1myu0u+8AvVIq7vfj5x+rL760/kqLC3V+/OaVi5jfbb082JpYI1cNHe9qXO3rSFXp67h/7HfGBs+y1b7EeFfqtk9MU3ZxVv3W05xnnok1v0+0Supg/qkdNT0dfWPKGouZSVOS78v1c77hHdZe02V+21Arf0mdeq29ffm2m/rsqXli+I0aEjTv7wJV++Bpllfee0vn++0Kad2SLU9tiVJJRtLlTNjs/of1LRyO0Hlri7XloKQXrt2rV66LFs/fdz4L2uDypyYqPUrKnT3WZs19aI8HTw5WRYXfqmMShuypRWLpYwIHQPbUrbFadn3WzR4n6aFvsHbC2n59yXaaZ/wQ9+qIv1+kp1tWrwoXkN2rX+E+XvvJmjPvcIPRyutWiP9uFAaObT64znrpA+/kE49uslNqEdymlYXbv3cWVNU+1xot8491DMlTZ+sCu988pe2ktK0ptq5SX6tcxNJOrTvEL196Hm6b9/j1HNb33A1g40LivTRnxbq/25eqrwVjS/v1hglG0u1dsYm9Z3QreGZm1lTz0+CaOltaWZPNvtC60F5B2xTZmbmVZIi86kJoMk6pB7X5GU8MvUTbdxYqLZt43XZ5YfplFN/raee/DLs5Y0cO1SHnDNOlx14Y73z3DF5quLiTL+/62yNPXFvTXvy87Db25YhPbupb+cOuvWtz9SrU9MvRapPG4tT/9TOOuvzJ9Qjqb2eHnO2jvroIeWXNS3Y22ab8XE6YdwInX7TM1q5brOuPPUATTp8Tz369rcNP7mR8ou26NYnPtLNvz9Czjn9sHC1+nTv2OztVHXMTkM1omu6Tn6z7pId25vOAxN11EM7qW1SnFZ/V6DPb12pI+9v2pcDO7J4M2WkdtaZnz+p9KT2embsWZr44cMtesxJ0nnPvKqE+Hjdftxh2ntAX/3fktp1y4MoKZYeuClOJ18QUlLtQcURl//jJq3/PFu7/GVURNo7vM8wvb/qR4XCGi/dOItnbFHvXds26dLvSiXF0kM3SSdfoIjst5Ji6e4b2+qM35UrOYqvkwknmV55yOnW31eoZ4apzyAproWGEkWyLUma9/gq7XJar2YJQ4MIVUjrFpfqqJu6qbzU6ZUr1yp9lwR17N30kXM1Lfm+TD0GxuuMv6dq05qQnrmuQP12a692yeGva0mx9PBN0okROgYasuTbEvXeNaFZju8gln67Rb12DX6VwbZE+v2kuFi6aUqyLvh9iVLqaW/m/+L1/rttdee/mnbFWmGRdPH10lV/kGpeOPOPe6XLz2/Z47qSSbpuzwP1py/fbvnGJH20apHeXD5PpaEKnTroV7pt9JE645NnW6StjgOSdOgDu6hNUryyv8/T9H8u18H37tLwE8M0/8kVGnxan4i9V1aKxPlJONvSzCZLmlzloanOuan+tDdqzi7pADPrKEnOuaOasfu1EPqiIYlZWVlTot0JAMGMH/f3akVzjz5mDx0+0ftQvObPL2jDhoIGl7FxozfKpKysQu+994NOOnl04PaPPP8gHXbuAZKkvxzzT3XokqZLHjxPfznqn8rfuO22QyGnT1+arpMumxg49D1175E6YS/v5gJzVuYovWOa5Jfp69EhVTl51dsc2a+nduvTQ9P+fK7i4+LUJSVZj00+QZOmvhx4HXNK8tUzaesNUtKT2v9yg4ZK2cV5+mHTKpW7kFYV5WpZwUb1T+2iOZuC1w47cdxIHTvGW7d5S3OqjaTt3ilV63Krr9vOfb1v2leu80Yhf5C1QOccVvtGCHU5YfxIHTN2+Na2uqRJ/qDF7p1TtXZT7X335cwl+nKmN0rimHHDFQo1PqzJKSxQryrlGnqmpCmnsHZb+/bur4t+tbdOfvN5lYbCq3eYXVignqlb20pPTVN2QcPHQ0tpm7x1BH2vPVKV9e9sbckrV7v24Z2aZRdUX7+eqXVvy6Y4c+RInTzMe538kJOjnmlVt2dqre3pjezd9jxB5BTnKT1565c0dR9z+Zq10TvmVvrHXEZqZ83etCZQG6ftOVIn7u4db7NX56hnhzTJL/WW3j5VOfn197u0okIfzV+s8bsMCiv0LS+XHrwpTnsf6LTHfrWnd+zqtHGdSX4gumm9dzlwSyn6uUDLH12gnf40XG1Sww+e1pbkKz1p637rkdReOSX5dc57WJ/ddNOsd8JuqzF+/LxppR0qlZd7Ac3oA6Xd69xv0qYqlzE3db+Vl0t3/7Wt9jkwpD33j0yZpvokpZhOv9z7Q985p7+e7dQl/HLMMdOWJG1eUqSZ9yyTJJXmlWvd//Jk8ab0PVvmi83ULvFKTEtU28Q4tU2Ueu7WTuuXlbVI6Dvrwy3a54REmZk694pXxx5xWr+iQr13Ce9zp6JcmnqTtNeB0q8icAwE8dMXTS/t0BgLvijWzk0o7VApGu8nN01J1oHjy7Tf/nWP4l2yOE7/uiNJf/tHkdp3CP8LubJy6Y/XS0dOkA4eU3v6nPnS5f64kNzN0ufTvVrAE/ZvfFs5RfnqlbL1c6dncvVzodS2Cdq5Y1c9f+hpkqRuSSl65MDjdN7HrzT6Zm45xfnqWe3cJK3WuUlu6dYSdi8smak/jzygUW00RtXzyvTd22vWI6ubdF7ZkM1LCvXDPd7fAWX55Vo3c7Pi4kzd92xijY5taK7zk4aEsy39gHdqPZP7SJon6RF5J3MmKVPSHc3V520h9AWAVuz1177T669916jndO6c8kvwu+9+O2vp0jqKb9XjzYc/0JsPfyBJ6ta3i65/4RLddu6DWrWo/hOpXgN7aPWSHEnSr4/YXSvmBw9Gn5s+S89N98pGjNllgE7bZ6TemTVfI/qmq6CkVOvzq18m+cI3P+iFb37w2u3UXg+cfXSjAl9Jmr1plfqndlbv5I5aW5ynw/vspj/NeLXaPB+uma+JfYbpleWz1DEhSRmpnbWycFOj2nnp01l66VNv3fYbPkAnHTBS7387X8MGpquguFTrN1dft7WbCjSwZxd1TE1SbkGx9h7aT8vWbKxr0bW8/NEsvfyR19a+IwfoxAmjNG36fA0b1FMFxaXasLn25aad0pK0Kb9YacntdMKBI3XN/W81av0kada6Ncro0El90joopzBfRw4aoos/rr6c3bp019/3P1hnv/OSNpSEP9Lkh5xsZXTsqD7t2yunoEBH7ryL/vh+ZEKmuhRvKldix3iZmTYsLJZzUkJa+KVUaq7fxMG76JJmXr+nZs3SU7O818kBAwbozJGj9Ob8+RqV3lP5paVaV1j9dbKusFAFpaUald5TM7PX6Nhdh+rJmTMb3e7sTauVkdpZfZI7Kqc4T0f02U2XfVvjmFs9XxP77qZXls9SJ/+YW1FY9w146vLsjFl6doa3bmMHD9Dpe47U23Pma2TvdOVvKdW6gurrlty2rVLaJWhdQaHizTR28AB99/OqRq+bc9ITd5p69nU6+Pi6/6getbfTx2/Eaa9xTkt+8mq6tlRwUrqhREvvnauM84coMb1pN6D03iu7VHuvvGLGK7XmG5DaRR3aJmnmxpVNai+ILYUhrZxTpiMu79DwzNvgnPTknV7tzYOOr3uekXtLn7wh7TnOu/FSU/abc9Ijd7RRr34hHX5C+Df6ai5FBU4J7aQ2bU1fv+c0aLgpKaVlRntFsi1JOuC+3X75edYDy9V99/YtFvhKUsboJH0xdZNCFU4V5U5rF2zRyKNapjRP+25xWjqrXP2GtVXBppA2rqxQp/Twhlc6Jz11p1fLd0I9x8CIvaVP35Ayx209Bjq0YOjrHd+lOvyyph3fjWtviw65rGmvj2i8n9x5e6L69qvQ8SeW1jnP2hzTjVOSdcXVxerTN/wvmZyT/nKrNLC/dM7Jdc/z4Qtbf776H9K4X4cX+ErSrPVrlNG+k/qkdlBOUb6OHLCrLv5i681/88tKtfsL9/7y+/OHnKqbsz5pdOArST9sXK2MtE7qk9JBOcX5mthvqC79+vVq83RLTNG6Eu/8YUKvwVqU13L1TUo2laldxzYyM21cWCQXatp5ZUPG3DPil5/nPLhUXXfv0KKBb3OenzSkBbZlpqQ/SrpW0hXOuZlmVuyc+6xZOtwAQl8A2EF06pyiBx+epOTkdnLO6fgT9tS5Z09VUVGp/n7LSbrjtne0YUOBrvnL0erQMVlmpsWLcnTXne+G1d7p1xyrtM5puujuSZKkivIK/WHf6yRJN712he763b+1KXuz/vToBUpOS5KZtGT2z7r3D4+F1d7n85dqzJAMvXvFJJWUlesvL22tDfzfi0/X8fc8E9Zya6pwTjfNfFeP7nu64sz03+UztSh/nf6w6zjNyV2tT9Ys0Jc5i7Vf90F6a8LvFHIh3Tbnw2rf9jfWl7OXat/hGXr95kkqKS3XlMe3rtuz15+u0258Rus3F2rqW9P1yJUnqrwipDUb8jXlsfcb3dZXs5ZqnxED9Mpt56pkS7luemTrMp6+8Qydcf3TkqTLzjhAg/3RxY++Pl0/5wQP2CpVOKfrv/pQTx52guLj4vTi/NlauGmDLt1jX81en60Ply/W1aPHKblNWz0wwSv2tqowT799/9UGllx3Wzd89rGePOp4xcXF6aV5c7Rw4wZdOnofzV6bow+XLtaI7j300BFHq0O7RI3PGKRLRu+jQ559otFtSdJXd67S2rlF2pJfodd+u0jDT+6qUIUX6g0+pJNWfJ2vhe9vUly8KT7BtM+lvWQWfpBR4ZymfPqxnjjaX7+53vpd4q/fR/76PTjRX78Bg/TH0fvo0GfCW79Pli7VuIwB+mTSuSopL9eV07a+Tt46/QxNfMZ7nVz/8Uf658GHKLFNG322bJk+Xdb4mq0VzunGme/p0f1OU7yZXl42S4vy1+nioWM1Z9Mafbxmgb7IWaz9egzUOwddoArn9M/ZH4V9zH22cKnGDM7QtD947yXXvL71eHv1/NN17MPPKCmhrR445SgltPGC+2+XrdDzWT80uq1Fc6WvP4pT7wFOf/2dt/+PnRTSxrXez+MmOg3fS5o9w+maSXFKaCdNujz8P8CXPjBP+T9tVnlBmWZf8rV6Hpsh578uux3YS2teW67ygnKteNIb6m9xpiF/3SOstiqc099mvaNH9j1DcTK9UvW9ctNqfZK9QJJX2uGdVeHfwK3Sm7dt1orZZSrOC+nBc9Zr39NSVHlhwKjDvJF4C7/eooxfJSghsWmh4aK50vSPTL0HON34O++xYydJG9d6P4+dKA3fS5ozQ7p2kpTQTjrn8vDbWzDX9OWH8eo7IKRrzvdCupPOrdAGv73xR4aUu1G67sIEFRdJcSa990q8bn2kNKwyEI//I6RFPzgV5EnXnVGhw88wVfjbcr8j4pTzs/T0HSGZpPT+0mmXhn9ddiTbkqT/3b1UG+cVqDS/XB//bo4Gn9jzl/fmlqjjO+32DVo9p0QleSE9ce5q7Xlqe4X8gZXDDktV575t1e9XiXrh4mxZnLTrQanq0j8hrLZe+WeBfp5drqI8p7vPztWY05N+aWuPw9tp/1OS9Ma/CvXwhZslJx04KUnJHcLbnovnSt98JPUeIN3sHwNHVzkGxkyUhvnHwPX+MXBWE46Bt2/L1co5pSrOC2nqpLX69ampvxzfIw/zAqBF00uU8at2apvY9DoB7962SSvnbFFJXkiPTsrW6FPTfmlvxGHeQbV4eon6N0N7kX4/mTsnXh99kKABAyr0u8leHDTpN1u01v/cmXhkmZ55qp3y80z33e2Nmo6Pl+57sPH1pr+fLb0xzbTzQKdjf+M9dslvpTXeWA+d0gx1fKuqcE7Xf/OBnpxwkuLjTC8unK2Fuet16aj9NHtDtj5csahZ2/rrd9P0+NhTFBcXp5eXzNLCvPW6ZNgYzd64Rh+tXqizd95T43sPVkUopM2lJbrym8YPkKg0418/a93cQpXml+vd83/Urif1+OXze8DBXbRq+mYtnbZR5p9X7nlp3yadV/5wzxJt/DFfZfnl+uzCWRp0Qi+5cq+9vgd1D3u59Ynk+Umkt6VzLiTp/9m7z/Coqv3t4989KYT0BFLohNBDkyoIAQJSFFCRotRjwS6iqIAewIN6ju3YRQUBGwqIighSFBQVRXqR3oQQUoCQXkjZz4tJSEISyAyZ8f/k3J/r8jJhVnJnt7XW/GbNntcMw/ii4P/xOLEWa5iV8AnOUnV17NjxGd3eQeT/H316/dtpnbrrpr3OiuLUpI5OywLI61z2W5AdxWuVYz/YoTiXC84d9xOuc96qNCPbuZ9PO763Y+49XZ6P15fxvkhHyXPuPdpc6zvuw4suZfnTuR/gN3f8O07Lmh0X5bQsgJ2xdZyaNzniB6dlNXGPd1oWgKel7BV3jpCY59hVUn+31cltrtyokjT0cOCnypUh0MV5tyWq42bbO5Su1uFsB963owx5TvxM+4hqtr8T5Go0cHXePLa+q/PmsACN1tzltCyXas59Z8XwltudmpeeWzkfaFoRZy8496bfDTwr9m7HyvJCm6UVnjgbhnEjcJ1pmk858E+6SCt9RURERERERERERBzINM2VwEoAwzC8TdN06Kt5zl0SIyIiIiIiIiIiIvK/bZ+jA7TSV0RERERERERERKQSGYbxWHkPAQ6/55hW+oqIiIiIiIiIiIhUrn8DAYDPJf9544SarFb6ioiIiIiIiIiIiFSu7cAy0zS3XfqAYRh3OzpcRV8RERERERERERGRynUHdnwCmgAAIABJREFUcK6cxzo6OlxFXxEREREREREREZFKZJrmQQDDMDxM08y65OE8R+frnr4iIiIiIiIiIiIijrHFMIxrC78xDONW4DdHh2qlr4iIiIiIiIiIiIhjjALmG4bxE1AbqAFEOTpURV8RERERERERERERBzBNc49hGM8DnwCpQKRpmqccnauir4iIiIiIiIiIiIgDGIYxDwgH2gBNgRWGYbxlmuY7jszVPX1FREREREREREREHGM30Ns0zeOmaa4BugDtHR2qoq+IiIiIiIiIiIhIJTMMwwW43zRNs/DfTNNMNk3zLkdnq+grIiIiIiIiIiIiUslM08wDDhqGUd/Z2bqnr4iIiIiIiIiIiIhjBAB7DcPYDKQX/qNpmkMcGaqir4iIiIiIiIiIiIhjTP87QlX0FREREREREREREXEA0zQ3/B25KvqKiIiIiIiIiIiIVCLDMH41TbO7YRipgFn8IcA0TdPXkfkq+oqIiIiIiIiIiIhUItM0uxf83+fvyLf8HaEiIiIiIiIiIiIi4hgq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUIa5/9x8gIiKV52zb6k7Lqtawg9OynM3T44JT8852zXFaVoMGZ5yWBXAk4munZT13NsJpWQAfbrnOqXlNJm1yWpaLj4/TsgBwc96UNC2yqdOyAB6b9YDTstzSTKdlAWRfZzg1b071Hk7LStkU5LQsAJdMJ4Y5edlPvptz8zJD85yW5Vc/2WlZAIPq73Va1vTfb3FaFkDQT849UXKrO7H/cm7XTPVz+U7LSqnv3A6l8WbndZbGr7uclgWwKyzMqXnkO+/EPDmijtOyAP6o5dyL7oU2To2ziVb6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUISr6ioiIiIiIiIiIiFQhKvqKiIiIiIiIiIiIVCEq+oqIiIiIiIiIiIhUIa5/9x8gIiLOM2VoL7q3DCMrJ4fpC9dy4FRCqTauLhamDYuiU+O65Jsmb63cyLpdR+zKmzy6N93ahJF1IYdZH6zh4InSeX07N+WOwV1wsRj8uvM4b3/xi11ZANMG9yKyWRiZOTk8/cVa9p8unVfo7XFDqBvox82vf2JzTreaTXi85Q24GBa+jt7Gh8d+LvF4qIcf/2p7Kz6uHrgYFt48uJaNZw7ZnFOoZ50wZl7bBxfDYNGh3by7+48Sj49u1o5xLa4hz8wnIzeHaRvXcDjpnF1ZnQObMbHpECyGhZWnN7PwxI8lHg/x8GdqixH4u3mTkpvBc3s/50x2sl1ZsQkw7XkL586DYcDwwSZjh5lltt2zH0Y/aOHlGfn072VXHJveieX01jQ8/Fy44fVGpR6P/zOdX16MwSvYDYB6XXxoNaKmfWFYj9uMLtbjtvjQbt7dU/q4jW1xDfn5+aQXHLcjyfYdN4CoUd0Z+eTNGIZBRmombz4wl2O7T5Rq99gH99O0QyMMw+DUoVhevuMdstKzbMrqPfxaRkwaCIZBZloWbz32Ccf/jC7V7sm5E2h6TRi5Obkc3HacNyd9TF5uns3b1ntYZ0Y8PKAo74mFHN97qlS7wXf15pZ7+1C7UTAjmj5GSmKazVn16wTy1EMDaNoomLmf/crn32wts92MSTfQPDyU3Lx89h+O5aX3vicvL9/mPIDJo3pzXWtrX/mveWs4eLJ033V9p6bcMcjaV/6y6zhvL7W9r2xQO5CnH+hP07Bg3l+0kc+/LXvbbu3fjpE3tqduaAAD75pNcmqmzVkAkQ0aMqNnLyyGhSV79/De1i0lHnd3ceGVfgNoFRxCUlYmD3+3kpjUFLuyAK6t2YTJLQZhwcI3p7bw8fFL+2Z/pre+FX93T1JyMpm5awkJ2fbnPT2wF5FNrGPqtGVr2Rdb+rjNHXMLQd5euFgsbDsZw6yV68k3y+7nrmTakGJj3JKyx7gF9wwjyNeL7JxcACZ88BWJ6fYdv4tj6oUcnl56hTF1bMGY+obtYyrAUzcU7cunvi57X84ZewtBPl64WixsPRHDsyvs25c96zVkRvcoXCwGi/ft4d0dm0s8flfbDtzWog25Zj6JmRk8uX4NMWn2nSfdghozJeJGLIbB1ye3Mf9oyes21MOP59oNxcetOhbD4I0Da/k14bBdWVtnxxC7LZVqfq70e7VxqccT9qbz24sn8Qp2B6BOFx9aDg+2KwugZ+0wZnTqg4thYfGRXbz75x9lthtQvynv9bqFwSs/Ys+5OLvzwHl9ZaEnh/fiughr3sxP1nIgumSeZzU35j824uL3wf4+fLd5P698ucH+rJwcZn5cgayAgqyltmc1qB3I0/cXGwtWXGYsuKFgLLjb/rFg2k296NHcum1PL17L/pgy+q77hlHTx4vsXGvfdc8c+/quevVr8MTUG2ncJJQFH2zgi8Vln5dPTB1Em3b1SU/LBuDlF77l6JHy+7iyRI3qzsgnhhTNux6cV/a8a+69NO0QjmHAqcOxvHzHbLLSs23etrqNgnjsxZE0jqjDR/9dzZfzyj72ba8N5+5pg3B1c+XIn6d4bdoX5NsxP6nbKIjHXhpJ44i6fPTfVXz5QTl5XRuXzJu6xK68ijyPW3DPMIJ8io1x8+w7T5w9P/k7qegrIvI/onvLhtQP8mfwcwto3SCUfw6PYsxri0q1m9CvC4mpGQx5/kMMA/w8PezK69YmjHoh/tw6ZT6twmsxZVwf7nz28xJt/Lw8mDgyknHPLCQpNZOZd/enU4t6bNlfunh0JT2aNaRBTX8GvrKANvVCmXFzFLfPLr19AH0jGpNxIceu7bJgMCViMA9sXkB8VgqfXncfGxL2czztzMU2dzfuxfexf7L05GbCvIN4q+M4Bv30X/vyDINnu/Zl9JolxKWnsnzIOH44eaREUfebY/tYeHCnddvqNeafnXszfu1Su7bt0Wa38NiOOZzJTmZOp4n8enYvJ9KLJl0PNB7EmthtrI7bRvuAcO4JH8jz+8rez1fi6gJPPphPy6aQngHDJ1jo2tGkccOS7fLy4NX3LXTraFfMRY16+dF0YACb3jxdbpugFtXp+VS9qwvCetxmXduXMWuWEJeRyvLB4/j+5JESRd1Lj9v0zr0Z/73tx61Q3PEEJveaSVpSOp0GtGPS+/cysetTpdq99+iHZBQ8cbv3v+O56aEBLH5xmW1ZJ87wxI0vkpaUQce+rXnkjfFM6vNcqXY/LtnESxPmAjB13r0MGN+DlfN+sn3bTpzliSGvkJacQcc+rXjk1bFM6v+fUu32bT7C5rW7eembyTZnFEpJy+L1eeuJ7Fy6aFLc2p/3M+v17wB45tEbGdy3NcvW7LI5r1vrMOqH+DN02nxaNarF1HF9uOO5MvrKEZGMnVXQV95lX1+ZkpbJawvWE9np8tu25+BpNm4/xjszR1y23eVYDIN/9Ypi3NdfEpeWyrLbRvPDsaMcSUy82GZERCtSsrOI+mg+g5o2Y0r3HkxctdK+PAyebDmEh7bMJyErhY+6PsAvCQc4Xqz/eqT5QL6L2c7K0zvoGNiIB5r255k9X9iVF9mkIQ0C/en/5gLa1g1l5o1RjPygdF846YuVpGdfAODNEYMYENGE7/60/UXAi2PcywtoUz+UGbdEcfs7Zfe9Uz5fzd6YeJszSuXVcPyYCgX7soY/A96w7ssZg6O4bU7prEeXFO3LN0baty8thsGsyL6M+fYL4tJSWT5sDN//dZQj54v65n1nEhi89xOycnMZE9GWad0ieWjtCpu3y4LBU60Gc+8fHxKfmcJnPe7jp/gDHCs2X5jQpCdrYv/kixNbaOQdxNudx3LD+ldtzgJo0Muf8AGBbHk7ptw2NVt40n1aA7t+f3EWw2BWl+sZ8/1i6xh3w3i+jz5S6oVLL1d37mjRkR1nyh93K8qZfSVA9wjrvPmmZxbQumEoT90WxbiXS56XGdk53PafhRe/XzhlFOvtWCjRPaIh9YNtzJo6ivU77VuUkZKWyWsfrieyYwXHghn2jwU9mjekfk1/bnjR2ndNHxrFqLfK7kumfr6avaeuru9KTcnknTe/p1v3pldsO+fd9fyy4YDdWXHHE5jc+19F8673JjCx2z9LtXvvsY+L5l2vjOWmBwew+KVvbM5LTcrgvVnL6Hp9q3LbGIbB5JdvY9rY94n56yxjH+lH36EdWPvFlnJ/pty85Ezem/UNXa+PqEDee8QcP8vYSf3pe2tH1i7ZXO7PlMWW53FTFl3dGOfs+cnfTbd3EBH5H9G7VTjfbtkPwJ4TcfhUr0ZNX69S7W7uEsH8H6wDtWlCko0rAAtFXhPOdxv3AfDn0Vh8PKtRw69kXu1gP6Ljk0gqmAht3neS3h2b2JUX1TKc5dut27c7umD7fEpvn6e7G+N7tOf99WW/8n8lrfzrcirjHDGZ58k181gTu4deIS1KtDEBL9dqAPi4enAmO9WuLIB2NWvxV0oS0anJ5OTn8+2x/Vxfv+QkPS3nwsWvPd3c7M5q4VufmMyzxGYlkmvmsS5+J91rlpzoNfQKYft565OM7eeP0j2o/InglQTVgJYFc3IvT2jUABLOlG638CuD63uaBAbYtzquUHCEJ+7ezpn6tKtZixOpSUSnFR23fpc7bq5uXN3Wwb7fD5GWlA7A/k2HCapbo8x2GcVW6lSr7m690G20f/NR0pIyADiw9Sg1aweU2W7L93sufn1w2zFq1g60OQtg/5ZjpCUX5h2jZm3/Mtsd3RNNfLT9q6UBkpIzOHAkjtwrrFLZtP34xa/3HY4juIaPXXk9rwln5W8FfeWxsvvKOkGl+8qoDrb3ledTMtl/NP6K23borwTizlzdipa2IaGcSE4iOsV6Daw4dIDrG4WXaNO3UThf7rNu+6rDh+hWr77deREFffPpgr55bdxuIi/pm8O8gtmSeAyArYnHSj1uiz7Nwvlml3XM2XUqDl+PagR5lx5zCouUrhYLbi4u9lxuAERFhLN8W8EYd7L8Ma6yRLUIZ/mOYmOqx2XG1O7tef9H+8ZUgKjm4Xyz08Z96epiV5/ZLjiUE8nnL56X3x45QL+wkufl76ejySpYbbgjPpZQL/uu7Vb+dYlOP0dMhvWcXB1Ter4A4O3qcfH/Z7Lsny8EtfTC3dvF7p+3Rbsal4xxf+2nX73SfdLkdj14789NZOflXnWmM/tKgJ5twlnxR8G8+a/y582F6gf7E+jjyfYj5RfdK5zl6bgscO5Y0PvSvqucvqSyJCVlcPBALHm59r3zxhbOnHcBJCemc2jPKXIv844p3wBPcnPyiPnrLADbNx6me//W9uWdS+PQ7mhyL7MvrXm5xBwvzDtE9wG251X0eVxlcPb85O+moq+IyP+IYH9v4pOKnkzEJ6cR7Oddoo1PdWuh8sEburHo8VG8/I8bCfTxtC8vwJv4xKK8hPNpBAeUzDsVn0T90ABq1fTFxWLQs31jQuwsnAT7ehN3yfaF+HqXavdwv258+Ms2MnPsewIS5OFLXFbR7QwSMlMIruZbos37h9dxQ522rOr9BG92GsdLe21fIVQo1Mub2PSi7YpNTyXUs/Q+GtfiGn4eNoFpHXsyc9M6u7JqeviSkJV08fsz2ckEVfMr0eZIWiyRwdbJXGRQK7xcPfB1te8cKS4mFvYfhjYtS/57/BlY94vBbTddbUm0Ys4ezGTVY8f56blokk/a/ta7QiGe3pwuftwyUgkpo3Awtvk1bLh1AlM79eSZP+w7bmUZcFcUW1bvKPfxx+c9wJLYudRrVptlb626qqz+Y3uw9Yc9l23j4upCn9u6XbFdhfLGXMfWdX9e9e+pLC4uFvr3asmmHcev3LgMQZf2lYml+8rohIK+soa1r+x1TWNCAu3rK50l1Nub2NRi10BaGiHeJf/mEC9vYtOsbfJMk9TsbAI87Ht3SVA1P+Izi/XNWckEXdI3H06No3eI9YWqXiEReLt64OdW3a68EF9vYlOKti8upewxB+CDMbew8Yl7Sb9wgTX77HvrfrCvN3HJVx7jAJ4b3o8vHxnNfX262JUFEOxXwTH1+oIx9YL9Rb2QS7YtLiWN4HK2be64W/h1yr2kZ19gzV7b92WIlw+n0y45Ly9T1B3RojU/nbTv2g6ufsl8ISuZkOols949tJ4b67RlbZ/HeafzWF7Y69iVZImHMvn+8SP88vwJkqPte1EfIMTTh9PpRcXA2IxUQjxLHrOIwBBqefnwY8wxu3OKc3ZfWeoaSEoj2L/s8xJgQIdmrN120L4sf2/izhfLOu+4LGcLKWt+7lf2tj07oh9LHx3NvX3t77tscefdPZkz/27uf7Avbm5X94LJgDt7s2X1znIff3ze/Sw5/T71mtVh2durryrrcpIT07G4WGjSqi4A3Qe0pmatsl8or7Q8VxeatC7Ma2NXXkWfx0HBGDdxNPdF2XeeOHt+UsgwjOaGYfQxDMP7kn8fcFW/+ApU9BURkYtcLAahAT7sPB7Lba98xu6/Ypl8U6TD8lIzsnnx43U8f/+NzHlqJLFnk8nPd1xxr3mtIOoF+rFu71GHZQD0r92Gb0/tYOCPLzNxy8c823YYBoZDMz/ev4PIpXN5YesGHm7b1WE5sw+voJ1/Iz7oPIl2AY1IyEoin6tbTZGeAZNmWJj6cD6XLu564S0Lj92bj8UJM5bARh4Mea8xA18No+nAAH5+sfQ9YyvbJwd20PPLyj1ubXtFMPDOKOZO+bTcNq/cNZvb6tzLyQMx9BrZze6sNj2a039sD+bNuPxb5B96dQx7Nh5i7+/2Fbwu5nVvRv/R3Zn3r6+u6vdUpsn39GXXvlPs3m/fiquKSM3I5sVP1vHv+29kztSRxJ5LJs+BfWVV9cbB72gfEMYn3R6ifUAY8VnJ5Nm79NYGd3/6NT3+Owd3FxeuDbv628dczpRFq7jl9U8Y++4S2jesw5D29q9mvpKLY+o+x46pxU34+GsiXy7Yl40cuy9vbtqCNkEhzNlh+9uiK2pg7TYsP7Wdfute4cHNn/B8u1sdNl8ICPPghtlNuP6VxjQeGMjvL9l+y4OKMoDpHaN4fut6h2WU5e/sK/t3aMbqrc4pxPbv2IzVW/7/KPpW1JTPVjH01U8YN3sJHcLqMKSD4/ougHlzfuSOse/z4L0L8PH1YOQo++dgF+ddUxeW2+aVu97ltrr3XfW8qyJemLSQe54ezOtfPkxmejb5eY69Bl6Y+Cn3/HMIr389sSDPcausL45x7zl+jKtMhmFMBL4BHgb+NAzjpmIP/9uR2bqnr/x/qWPHjlOBq3upRaQqum50iW9Hdm/L0K7W+z7tPRlPiH/Rq5ghft4kJJf8kKOk9Cwys3NYt9tamFm78xC3XFv+faMuNaxPW27uaV0Fuu94fInVFcEB3iScL/2hSr/uPMavO62rQG7u2dqmou/t17ZlWGfr3/fnqXhC/X3gRNH2xaeUzGtbvxYRdUNYO+VOXCwWanh5suCeYdwxp+L3UT2TlUKoR9Hq1+DqvqU+COjmuh14aMvHAOxOisbdxRV/d0/OX0ivcE6huPQ0ahVbhVTLy4e4jPLf/rn82H6e69YP7PjckrNZKQR7FL06H1TNr9SHtJ27kMI/91i3rbqLO5FBrUnLtX+1UE6uteB7Y1+T68t4fWHvQXh8lrXiez4Zftlk4OqST58edkeWy82zaJVH7Q7ebJ0bR3ZKLtV8bZ8uxWekUbv4cfP0IT69/OP27bH9PNe1n805Qx7ozw139wXg6Rv/jW9NHx6bex9P3fBvUq/wIWb5+fn8tGgjI564iTUf/nTFrMF3RzFgvPUgTR/+On41vJn01j+YfutrpJ4v/9wePWUIfjV8ePORdyq+YcDgO3sxYKz1QE+//U38Ar2Z9No4pt/2xmXz7DF0QDsGX98GgMef+5JzFfz9d4zoir9vdZ5+aa1NecOj2nJzZDl9ZWDZfeUvu47xyy5rX3lLz9YVLmQM7d+OIX2sWY//5yvOVvK+K09cWhq1fIpdA97exKeVvAbi09Oo5e1DXFoaLoaBT7VqnM+yrz85k51MSPVifbOHH2cu6ZvPZqcyZaf1SXl1F3d6h0bY1H+N6tSW4R2sY86emHhq+RZtX6hv6TGnuAu5eaw7eJQ+zcP57djJCuXd3vWSMc6v5BheVl5CivX4ZlzI4budB2hdL/TiW2avmHdtW4Z1smNMfbLYmDphGHfMvfKYOqpzW4YV7Ms/Y0puW6ivNwlX2JfrDxwlqnk4vx2t2L4sFJ+eSm3vS87LMvrm6+rW56EO1zJy2WIu5Nv+4ZNgfSdQifmChx/xmSWzbqnfgfv/+AiwzheqWVwJcPck0Y75wpUUH+NqtfdhxwexVzHGpVLbq2glfS1PH+Izio6Zt5s7Tf1rsqj/KACCqnvxQe+h3P3jVzZ9mJsz+0qAEZFtGXpdwbz5RME1UCDE35uEpLLPy6Z1auJisbA/uuIfBFYqK6BYVkDlZgEM7VdsLHjBsWPBbd3aMqxLwfUdfcl+9PMmPvkyfVd2Dit3HKBVvdCLt4W4kiE3d+CGQe0AeHrKYs6du/KHuCYmWvNycvJYs2o3w0dWbNXokPv7ccPdfaxZg16wzrvm3MNTN75QgXmXyU+Lf2PEE4MrNO8CGDSmGwNGWP+2GXfPIzHhyrfbOLDjBE/c/i4A7bs3pU5YUIWyAAaN7caAgn0x404b8kbOtjnP1udxcMkYt+sAretWfIwr5Ij5iWEY9wD3FPunOaZpzin2/QSgg2maaYZhNASWGobR0DTNN8CxK4NU9JX/X3ls3br1mb/7jxD5v6btI6/NLP794l93sfhX6wcL9WgZxm092rJ6+0FaNwglLesCZ1NKT/g27D1Gp8b12Hw4mi5N63M0ruL3x1y6bhdL11nzrmsbxvA+7Vj7x0FahdciLfMC55JL5wX4VOd8aiY+ntUY1qctT71T8VshfL5pF59vsuZFNgtjVLe2fLfrIG3qFWxfasm8xX/sZvEfuwGoHeDL7PE32VTwBdibHEM9rxrUrh5AQlYK/Wu15qmdJVc5xmUm07lGI76N2UGYVxDVLK52FXwBdp2NJcwvgHrefsRlpDK4UQsm/vRtiTYNfQP4K+U8AFH1wi9+basDqdHU9axJLY8AzmSn0CekHbP2flaijZ+b9VPvTUxGN4jiu1j7V0CZJsx40aBRA5N/jCz7SdnaxUWrBZ76j0HPrqZDCr4Amedz8fB3wTAMzh3OxDTB3ce+t/vtOhtLQ98A6nr7EV943DZU/nFbPnsNy2evASCoXk1mfvkEL457i5jDseX+TO3wUE4ftT7p7jqkI9EHK7ZC9dsP1vPtB9ZVW0F1A5n+6YO8fM9cYo6W/2EaA8b1oEOfVkwd8jKmjSsqv53/E9/O/8maVyeQ6R/ez8sPzCPmqG1PdCviq9U7+eoyb8ssy6C+rencriGPPPOFzbfn+2L9Lr5YX9BXtgljRGFf2agWaRkV6Ct7t2XauxXrK79as5Ov1ti2bZVhd3wcDf39qevrS3xaGoOaNmfS6u9KtFl37Ci3tmzJjrhYBjZpyu/RthXwituXHEM9z5oX++Z+oW2YvntxiTbF+69/NOrJt6e22ZTx2ZZdfLbFetx6NgljdOe2rPzzIG3rhpKafYEzaSWPm6e7G17u7pxJS7fewqhJGNtOVnxF+Oe/7+Lz3wvGuObFxrj6ZY9xLhYDH49qJGVk4Wqx0LNFI34/XPF9WmpM7WrDmOpfMKZWoOAL8NnmXXy2uWBfNg1jVJe2fLenYF9mVWBfNg1j6wnbV9fvSoijoV8AdX38iE9PZXDj5kz8vuQtFSJqBvPvnv0Yv2Ip5zIzbM4otDc5hvpeNahT3Z/4rFQG1GnNtO0l5wuxmUl0qRnO8lM7CPMOwt3F1SEFX4Cs8zlU83fFMAwSD2dg5l/FGHculoY+xca4hi2Y+EvRGJeac4H2S966+P2ifrfz/LYfbSr4gnP7SoAlP+9iyc/WvO4RYdzWsy2rtx2kdcNQ0jLLnjcDDOjYnNU23m6hRFargqytFcyyY0XxV2t38tVa54wFi37bxaLfivqu269ry6qdtvVdm2zou5Yv28byZbb154GBXhcLv926N+Wv42V8qERZWe+uZfm71hd6g+rVYObSybw4/p0rzLtCOF0wV+o6uAPRByr+wYYrPv2NFZ/+VuH2AH6BXiQnpuPm7sLwe3qxaHbFbx+24pPfWPGJjXk1vEk+l2bNu683i96pWJ6tz+NKnSfNG/H7EdvnDY6YnxQUeOdcponFNM1NR8YsAAAgAElEQVS0grZ/GYbRC2vhtwEq+oqISGX4Zd9xurdsyIrpd5B1IZcZnxWtTFv8xGhGvmxd/fT68l94fswAnhjak/NpmSXa2WLjruN0axPGVy/dSVZ2Ls/OW3PxsU9njWHMDOtbzx8b3Zsm9ayvCM9bvomT8Ull/r4r+fngcSKbN2TVE3eQlZPLP78o+ru/nDiaW98s/y1Xtsgz83lx7wre6TweCxaWn9rGsbQE7mvSh33JMfyccIBXD6xiequbGR3WDROYudv+t6LnmSYzfv+Bj/sPx8UwWHJ4D4eTzvHYNd3ZfTaOH6KPML7FNXSv3ZCc/DxSLmTz2M/23RMwz8zn9YPLeOWaCViw8F3sZv5Kj+fORv04mHKKjWf30S4gnHvDB2ICu84f47WDX9u9bdv3wPK1Fpo2Mhl6l3W+M2lCPrHx1q9HVvJ9fDe+GkPC3gyyU/NYNuEIrUfWvPiWtyb9A4j+PZXDa85jcTFwcTfo9mhtDMO+eVieaTJj0w983K/kcXv0mu7sKXbcrqvVkNz8PJIvZDP5l6u7l+PYGcPwreHNxHcmWP+G3Dwe7DwVgOdXTOPVCe+RGJfEkx8+iKevJxhwbNcJ3nxgrs1Zo6cMwSfQm4f+O9aalZfPxF6zAJj1xSRef/hDEuOSePi1ccRHn+O1758GYOO32/jspW/L/b3l5j1xIz6BXjz00uiCvDwm9rW+G27W5w/z+qMfkxiXzE0Tohj2cH8Cg3159+cZbPlhD69P+sSmrEB/Tz54eSxe1d3JN02GD+rAmIkLyMi8wMtPD+WF2Ws4dz6dx++9nvgzKbz/H+tKtg2bDvPhF7/bvG0bdx/nujZhfP3CnWRdyGXW/KK+cuEzYxj9jLWvnDyqqK/8wM6+MtDPk/kvjLm4bSNvaM+oxz4kI/MCr0y9hRfeX8vZ8+kMH3gNo4d0ItDfi49fHsfvO47zwvu2jQV5pskzP/3IRzffisUw+GLfnxxOPMeka7uxJz6OdcePsXjvn7zafyDrx99JclbWVX0ydp6Zz8v7lvNmxzuwGAbfFvTN9zTuy/7kU/xy5gAdAhvxQFPrivodicd5ad9yu/M2HD5OZJOGrJ1oHXOe+qZo/3x932hueW8h1d3cmH37ENxdrS8mbT4ezaKtu+3K+/nAcSKbNWTVk9YxvMQY98hobn1jIe4uLsy5ayiuLhZcLBZ+P3ySpZvtu4/2zwcL8h4vGFOXFst7eDS3vlU5YyrAhkPWfblmUsG+/Loo66v7RzP0Xeu+fGf0ENxdXLAYBn8cj2axHfsyzzSZ8cs6Ph58Ky6GhSUH9nD4/Dke7XQde87E8cNfR5nWtSeebm7M7j8EgJjUFCasWmZHVj7/2buCd7uMx2JYWBa9naNpCTzQNIq9yafZEH+A/+5bzYw2NzGmUTdM02TGTvvnC3+8Hs2ZvRlkp+ay8t6DtBwRfHGMC+8XyKlNKRxbex7DBVzcLXR5tO7VjXGbv+fjviOsY9yRPRxOPsujbbuz51wcP5w6Yvd2lMeZfSXAr3uP0z2iIcufsV5zz3xadF4umjaa2/5TdA1c374pD8+2fz70658FWf8qyPrkMlkdmvLwO/ZnQcFY8J9LxoLJZYwFA4qNBS+N4/edto8FPx84To8WDVk19Q4yL+QyfUnRzy99dDTDXrP2Xe9PGIqbiwWLYWHT4ZMs/cO+visg0IvZ79+Bp1c1zHyTocM6cdf4OWRkXOD5F0fw6kvfce5cGtOm34S/vydgcPRIPK+/avvnG4ydXjDvevsuoGDe1eUpAJ5fMZVXJ7xvnXcteBBP3+pgGBzbfYI3H/jAvm2r6cObyybi6e1Bfr7JzXd0594Br5CRls2sD+7k9aeWkpiQwrAJvejcuwUWi8HKz35n1yb7bsETUNOHN795xJpnmtx8Rw/u7f+yNW/+Xbw+9YuivKiCvIW/s+t326//ijyPc3dxYc6dxca4I/aNcc6enxSINwyjnWmaOwEKVvwOAuYD9n3SXgUZtq66kP8tHTt2fOb/4ora/6t/l8jfre0jrzmtU6+W7LzxIz3UsffDvVS1yIqvbq4M5+J8r9yokjRoULGVDJVlfcTVPTGxxXNnI5yWBfDhluucmtfkLsfdV/JSLj72ffCN3dyctw4hLbKp07IAsv2d9xEabmnOndfHXefcvrlms7NOy0rZVPG3w1YGl8wrt6k0Tv5Ul3w35+Zlhtp3OwZ7+NVPvnKjSjSo/l6nZS3c6ZwP0yoU9JNzT5Tc6k7sv5xccql+znH3VL1USn3ndiihm53XWRoF75Z0Ftew+k7Nw4mfDXByRB2nZQFk1nLuRXfskccu26EYhlEXyDVNs9TbHQzDuM40zY0FXweYpmnfWzbLoQ9yExEREREREREREalkpmmeKqvgW/DYxmLfVvxeHBWkoq+IiIiIiIiIiIjI36fS34Kgoq+IiIiIiIiIiIjI36fS70uhoq+IiIiIiIiIiIhIFaKir4iIiIiIiIiIiMjfp9Jv7+C8j0oWERERERERERER+R9jGEYQUBfIA46Zppl2SZM+lZ2poq+IiIiIiIiIiIhIJTMMoyXwJtAQqA/sAIINw9gAPGKaZjKAaZqJlZ2t2zuIiIiIiIiIiIiIVL75wIOmaTYGugMHTNMMAzYC8xwZrKKviIiIiIiIiIiISOWrbprmQQDTNDcDrQu+ngtEODJYt3cQERERERERERERqXxHDcOYDqwHhgI7AQzDcMPBi3G10ldERERERERERESk8t0J+ADTgCzgkYJ/9wTGOzJYK31FREREREREREREKplpmknAk4ZheJimmVXs35MNwzjiyGyt9BURERERERERERFxnM2GYVxb+I1hGLcCvzkyUCt9RURERERERERERBxnNDDfMIyfgNpADSDKkYEq+oqIiIiIiIiIiIg4iGmaewzDeB74BEgFIk3TPOXITBV9RURERERERERERBzEMIx5QDjQBmgKrDAM4y3TNN9xVKbu6SsiIiIiIiIiIiLiOLuB3qZpHjdNcw3QBWjvyEAVfUVEREREREREREQcwDAMF+B+0zTNwn8zTTPZNM27HJmroq+IiIiIiIiIiIiIA5immQccNAyjvjNzdU9fEREREREREREREccJAPYahrEZSC/8R9M0hzgqUEVfEREREREREREREceZ7uxAFX1FREREREREREREHMQ0zQ3OzlTRV0RERERERERERKSSGYbxq2ma3Q3DSAXM4g8Bpmmavo7KVtFXREREREREREREpJKZptm94P8+zs62ODtQRERERERERERERBxHRV8RERERERERERGRKkRFXxEREREREREREZEqREVfERERERERERERkSpERV8RERERERERERGRKkRFXxEREREREREREZEqREVfERERERERERERkSpERV8RERERERERERGRKkRFXxEREREREREREZEqxPXv/gNERKTyeA+Kc1pWQpKP07J2dp/rtCyAmQnXOjXvm/TWTssK80l0WhZAp1kPOi0rqUW+07IAjMALTs07NLeT07Jq1k52WhZAemY1p2VlxxhOywLwP+C8vNzqBjmeToujuvOGHACyjwY5Lcs32XRaFliPndM49xLAOybXqXnVYzOclpVez89pWQAr6vVwWlZgltOiAPAfd9Kpeb7u2U7LOpns77QsgNNnfZ2W5XLG3WlZAKd6VXda1oVbujgtC6B6vHM753w352WZTl5uGvqbc8dwHnFunC200ldEREREpApwZsFXRERERP5vU9FXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkClHRV0RERERERERERKQKUdFXREREREREREREpApR0VdERERERERERESkCnH9u/8AERFxji41mjKp2RAshsG3MVv49K+fSjwe4uHPUy2H4+/uRUpOBrP+XMyZ7GS783qENOKf1/THxTBYcmwncw7+VqrNwLotmBgRiWnCgeR4HvtjmV1ZcQkw499unDtvYBgwdFAeo4blldl27wGDfzzgzn9m5NC3V75deTtnnyR+ewrV/Fzp9d/m5bZLOpLBr/88RPtJDal9rb9dWeDcfXl07iHO7ziPm68bbV9oX+rxxG3nOPXlCTAMDBeDBqPD8G3mZ1dWoSeH9+K6iDCycnKY+fFaDkQnlHjcs5ob8x8bcfH74AAfvtu8n1eWbrApJ7J+Q2ZG9sZiGCze9yfvbdtc4vHOteswvUdvmtcMYuLqFaw6etj+jQIiazViZse+WAwLi4/s5L19m0o8fmuj1ky7Jor4jFQAPj60jcVHd9md17NOGDOv7YOLxWDRwd28u/uPEo+Pbt6OcS2uIc/MJyMnh2kb13A46ZxdWV1rNuHxFjfiYlhYdmorHx77ucTjoR5+/KvNMLzdPHDBwluH1rDxzCG7t617SDhPt+mPxbCw9K8dzD20sVSbAXVa8lCLnpiYHEyO5/EtX9uV5ezzBIpdAxdymPlJBa4B/4Jr4EvbroFC027qRY/m1mvu6cVr2R+TUKrNgvuGUdPHi+zcXADumfMViemZtmcN7kVkszAyL+Tw9NK17D9dOqvQ22OHUDfQj5vf+MTmnEJTbu1F95bWfTl94VoOnCqd5+piYdqwKDo1qUu+afLWio2s23XE5qzJo3vTra01a9bcNRw8UTqrb+em3DGkCy4Wg193HuftJb/YtV0AT4zoRfdWBefJR6XPE4D+HZtx58DOYJqcSU7nn/NXkZSeZV9W4TlZTr88b3LJfnnV5v288oXt52T9OoFMfWQgTcOD+eCTX1m0bEuZ7aY/diPNGoeSm5fH/sNxvPLOWvLybB/H6zWowWMzbqJx81p89O56ln76e7lt/3F/FD36tCQ/P58VX27lm8Wby21blvp1AnnqoQE0bRTM3M9+5fNvtpbZbujAaxgxqD11awVw4/h3SE61/VorNGVowTWQU4FroHHBNbDSvmvgiZHFzskPyzknO11yTs6z/Zyc3Ow2utRoSVJOGvdseanMNg80voXONVqQnZfDywc+50jaKZu3p9CpeftI3XUWV193mjx3banHk36P48x3J8A0sXi4UntcM6rX97E7r2vNJkxuMQiLYeGbU1v46JIxNcTDj2faDMfHzQMLBm8fWsNvVzGm9qwdxoyOfXExLCw+sot3924qs92A+s14r+ctDF75IXsS4+zOm9G7N73CwsjMyeHJNWvYm1D6PGkVHMxLAwbg4erKT8ePM+vHH+3Oe3pgLyKbWK+BacvWsi+2dN7cMbcQ5OOFi8XCthMxzFq5nnzTtDkrskFDZvTshcViYcmfe3hva8n+y93FhVf6D6BVcAhJWZk8/N1KYlJS7N42Z4+pT91QtC+f+rrsfTlnrHVfulosbD0Rw7Mr7NuXFT5u3gXH7aT9x61B7UCevr8/TcOCeX/RRj5fUXbffGv/doy8oT11QwMYePfsq+qb/y4q+oqI/A+wYDC5+c1M2v4BCVnJfNDlIX49s4+/0osG04ea3sjq2G2sit1O+4Bw7ms8gGf3LrY775n2A/nHzwuJy0jhy753sf70IY6knr3YpoF3APc1v46R6z8iJSeLwGqedm+fiws8+kAuLZqapGfA6HvcubZjPo0alpwE5OXBG++7cm0n+4q9her1CqThgJrsfOdkuW3MfJN9C08T1Nb+JwHg/H0Z1COE0Otrc+S9sp9M+EX4E9A+EMMwSD+ZzuG3D9DupQ5253WPaEj9YH9uemYBrRuG8tRtUYx7eVGJNhnZOdz2n4UXv184dRTrd9r25NRiGMzq1Yexy5YSl5bKNyNH88OxIxw5n3ixTUxqKk/8sJoJ7TvavT0l8jr1Y+z6RcRlpPDNgH/ww6nDHEkpWWRdeWI/M7eurZS8Z7v1ZfTqJcSlp7J8yDh+OHmkRFH3m6P7WHhgJwB96zfmn116M37NUtuzMJgaMZgHNi8gPiuFT7rdz4aE/RxPO3OxzV3hvfk+bg9LT24mzDuINzuMZ/CGV+zbNgxmtB3Inb9+SnxmCl/0vpv1sQc5Wvwa8ArknmbXMWrDgqu6Bpx9nkDBNRBk4zUwZRTr7SjQAPRo3pD6Nf254cUFtKkfyvShUYx6a1GZbad+vpq9p+LtygHo0awhDWr4M/CVBbSpF8qMm6O4fXbZWX0jGpNxIcfuLIDuLa37cvCz1n35zxFRjHm1dN6Efl1ITMtgyHMfYhjg5+lhc1a3NmHUC/Xn1ifn0yq8FlPG9+HOWZ+XaOPn5cHE2yIZN3MhSamZzJzQn04t67FlX7TNede1KugrZyygdVgo00ZFMf7FktvmYjF4YkQvhv3rI5LSs3hkaA9G9m7H+yvKLuiUm1XYL88syLo9ivEvlT4nb/93sXNy2ijW77DvnExJy+LNOevofm3jy7b7fsM+nn11JQAzHh/EoH5t+GbVTtvzUjJ597+r6daz/BdtAfoNbkdQiC93D38b0wS/ANv7lZS0LF6ft57Izpfftj0HYvht61HeenakzRnFXbwGnltA6wah/HN4FGNeK+caSM1gyPP2XwMXz8npBefJ6CjGv1DOOfnM1Z2Ta+M2803MrzzZYlSZj3cObEGd6kH8449/08K3ARObDmPi9tdt3qZCAd1rUaNPXU59sK/Mx91retBoantcvNxI3X2W0x8dIHx6J7uyLBg8GTGEhzbPJz4rhY+6PcDPCQc4nlY0R78rvDc/xO3hy5N/EOYdzOsdxnPThpftyzMMZnXux5gfFhGXkcrygf/g+1OHOZJccn7i5erOHc07suNMjF05hXqFhdHQ35+o+fNpV6sWs/r04dbPPy/Vblbfvjz1/ffsjI1l/i230LNhQzb89ZfNeZFNrONO/zcX0LZuKDMHRTFybulrYNIXK0nPvgDAmyMHMSCiCd/9aVsh3WIY/Kt3FOO++pK4tFSW3T6aH44d5Uhi0ZxhREQrUrKyiPpwPoOaNmNK9x5M/G6lzdsFzh9TC/flgDes+3LG4Chum1M679ElRfvyDTv3ZWSThjQILHbcboxi5AdXOG4j7MsCSEnL5LUP1xPZ8Qp988HTbNx+jHdmjLhsu//LdHsHEZH/AS386nEq4xynMxPJNfNYF7eLHkEtS7QJ8wphW+JRALafP0qP4JZl/aoKaRNYmxNpiUSnJ5Fj5rMyei996jQt0WZk2DV8enQrKTnW1R6J2Rl25wXVgBZNrQVeL08Ia2CScNYo1W7RVy70icwn0P5FtwDUaOmNu7fLZdscX3WGWl38cPe9utdXnb0vfZv74eJV/t/s4uGCYVj3bX52HpTezTbp2SacFX/sB2DPX3H4eFajpq9Xue3rB/sT6OPJ9iO2PQlpGxLKiaQkolOSycnP59tDB7m+UcmJXkxqCgfOnbVrxUCpvBq1OZF6nui0JGveif1cX6/plX/QTu2CavFXShLRqQXbd2w/19cvuX1pORcufu3p6gZ2bmaEf12i0xOJyTxPrpnH2tjd9ApuUaKNiYmXazUAvF09OJNt/6qWNoF1OJl+nlMZ1mvgu1N76VOrWYk2w8Pa89mxq78GnH2eQBnXQHXHXAOFekeEs3ybNW/3yTh8PKpR06f8vKsR1SKc5TsKsqLLz/J0d2N89/a8/+MfpR6zRe/W4Xy7+cr78uZrI5j/vXXFpmli10rYyPbhfLfRWhD682gsPp7VqOFXMqt2sB/RcUkkFawM2rz3JL07NrE5C6BXm3BWbCrYtuNlb5uB9d0u1au5AeDl4c6ZpHTbs9peklWBfjnA2/5zMik5gwNH4q64anfTtuMXv95/KJagGt525SWfz+DQvtPk5pb9jqBCg27tyMIPNlB4qSeft71fKdy23Cts2+HjCcSdsb+fLNS7VTjfbik4dicucw10iWD+D1d3DZQ6Typ6Tibbfk7uST5Gam75P9e1Zit+iLeusNyfcgJv1+oEuvvanFPIq1kALt5u5T7u2cQfFy/r457hfuQkZtudZR1Tz10cU7+P3U3PUmMqxcbUapy9ijG1XY1aBfOTgnHuxD761SvdL01u14P39m4iO+/y18mV9A0P5+t91r5yZ2wsvtWqEeRV8jwJ8vLC292dnbGxAHy9bx/XN758Ma48fZqH881O63m561Qcvh7VCPIufQ0UFg5dLRbcXFywZ0hvGxrKieSiOcOKQwe4Pjy8RJu+4eF8ud+6/asOH6Jbvfq2BxVw9pgaZc++dHWxa3rZp1k43+xyznEDOJ+Syf6j8Vfsmw/9VTl9899JK31FRP4HBFXzIyE76eL3CdnJRPiWnHQcTj1Nz+BWfBG9kZ7BEXi5euDr5klKju1PckKr+xCbUTRAxmWk0rZG7RJtGvrUAGBR7/G4GAZv7v2ZX+KP2Zx1qdOxBgcPW2jVouSr2wln4MdfXZjz2gX+dcCxr3lmJl4gdnMy3WY2Zue75a8Groi/c1+WJ3HrWU4uOUFOSg7NJ9v/4gBAsL83cedTL34ffz6NYH9vzqaU/eRuQIdmrN120OacUC9vYtOKcuLSUmkXWsv2P7iiedW9Sx23dpccN7C+dbJzcD2Opyby7LYfiM1ILdWmQnme3sSmF/1sbEYq1wSVzhvX4hrubtURN4sLt6+ybyV/sIcv8VlFt36Jz0qhlX+9Em3mHFnPO53+wcgGXanu4s79m+fblQUQ4uFDbGZRXlxmCm0D65Ro09A7EIDPet6BxTB4e/8Gfo0/anOWs88TgGA/b+KSil0DSY65BgqF+F6Sl5xGiJ83Z1NL5z07oh/5Zj7f7znC+z/Y/uSx1LYlpxHiWzrr4eu78eEv28i8kGtzxqV58ZfuS7+S+9KnurVw8uCN3ejYuC7RZ5P5z9IfSUy1bawLDvAm/lxRVkJiGsEB3pwrVtA6FZ9E/VoB1KrpS0JiKj3bN8bN1b7xJ9jfm/hifWVCUhpBl5wnufn5/Pvz9SyePpbMC7lEJ5znhc/XX33W+dJZxfXveHXnpK1cXCz07x3Bm3PXOTSnVp0Ael7fim69mpOclM7sV1ZzOjrxyj/4Nwr2v+QaSL7MNXBDsWvgSzuuAX9v4hMvOScDyjgnP1vP4hlXd05eSc1L5rlns5OoWc2PxAuOL9ac//k0Pq1r2P3zQR5+l4ypyWWMqet4u9MdjCgYUx/cPM/uvBBPH04Xny+kp9KuZsn5QkRgCLU8ffkx5ij3tuxidxZAiLc3p1OLj6tphHp7cya96DwJ9fYmrlib2LQ0Qrzte1EnxMeb2JRieSnWcedMWun+64Oxt9C6Tii/HP6LNftsv1VTqJc3scX/7tS0UnOGkGJt8kyT1OxsAjw8OJ9l+wstzh5TQ3y9iUsuuS+Dy9mXc8cV25d7bd+XIb42HLcxBVlH7Dtu/2u00ldERAB45/BKrgloxIIuE2kX0IiErGTyzau7DcLluBoWGvgEMuanT3h00zKe7zgIH7dqV/U7MzLg8ZluTH4oh0tfHH7lbTcm3pODxQkj394PY2g5ujaG5SqXwVaQI/bl5QR2rEm7lzrQbFILor884bCcsvTv2IzVW5xXXHCkdaeO0GPZbAZ+N49fYo/zStdBDs/8eP8OIr+YywtbNvBwu64Oy+lfqw3fntrODT++xMStH/Fs2+EYV7ss/DJcDQsNvAMZ9/NHTN78Fc9e49hr4O/Uv0MzVm91/DUw5bNVDH31E8bNXkKHsDoM6dDiyj9kh+a1gqgX6Me6fbYX6e3hYjEIDfBh5/FYbnv5M3b/FcvkmyMdkpWakc2LH63j+QduZM7TI4k9m0x+fuWsEC+Lq8XC8Mg2jHp+If2nzOFwzFnuGGDfW85t0b9jM9Y44Zws9Nh9fdm1N5rd+67ubedX4ubuyoULuTw8fi6rlm1n8v9j777jo6jzP46/vklIIJ0gkFATkF4CiIJIBwULKKCigF3Pa7azN+x3nnqnd56N8yxYwYJK76JYQBRC76GnQEJ6QhLy/f2xC0lIQnaXZIz83s/Hw4fsTnnPzM53ZvaT2e88OrpW85xSrg284G4Dl9ZOGwjw8+OKQd2Z8PQHjLhvCtv2HeKGC2t/n3RKzqZ0Dn97gKZX+nZXqqdGxHRn1r5fuGTp37lz1Ts8EX9lrZ1TDfDoWcN45ueaL87XNTe/N4MBL0whMMCfvnEtq5/gN8Dpc+oxt0ydwcDnpxDo70/fNrW7LW9+fwYD/uHO+g1/bsaYyU7k6E5fkTqkd+/eDwDed6ol4hb0t2GVvn/wSCZNgkr7NGgSFFHhIW2HjmTz0FpXR/8N/AMZ3KQbOcXe/xUaIDk/m5jg0p/VRQeHkZKffcI4WSSkH6DYlrAvL4PE7DRiQ6NYdzjJp8yiYlfB96LhRxk2sGKxeuMWw4NPBgKQkQnLV/jh71/EkAE1X9jO2JHPz//aBUBh1lFSV2dj/CDmHO/7lfg1tqWnwjtGcCS1gKLsIuqFVf0zyBNdOTCesed1BWDD7hSiG5b2e9y0YSipGTmVTte++Rn4+/mxqZIHxVQnOTeHmOvwDkkAACAASURBVNDSnOjQMJJzKs+pCcn5ORU+t+QTPreMwtKHQUzbkcADPYf4npeXQ0xI6frFBIeRnFv1XcNf7dzE0+dd4FNWakEWTeuXPryvaf1wDhaUP55c2uIsblv1LgDrMvYS6BdAZGAwhwu9/1lvSkE2MQ1K86IbhFfaBtYe3k+xLWF/Xga7ctJpHdqI9YcPeJXl1H5SoQ1ElmkDkTXfBq7qF8/lfVx56/eekBcRSkpmxbxU9916eUeKmL16M11bRh/vFuJkru4bz+Vnu7P2ubN2l8nKKp8V3yqGLi2asuC+G/H386NRSDBv33I5N/zXs/6mxw+IZ+y57m25J4WmJ27LE9YtI7eA/CNFLE5w3R20YPVWxvTt6lHW5cPiuWxQNwA2JqbQtFEYuG8yahIVSurhittx+ZqdLF/j+uXFZYO7eVX0vXJQPGP6l+4nTcscK5tEhnLwhP2kfcvGAOw75GqPC1dt5XoPi75XDopnzHlVZDWsmHVMu2P75B7v9skxF/Xkkgu6A3Dfk5+Slu7ZseH6q/oRGRHMI3/z7mGlo644mwsvcz2c9JE7PiD9UPXt+lBqFsuXuvb575Zu5u7Jl3qUNXZkD0ad71q3e57+jLTD3h/3vDG+/0naQMRJ2sBadxtY43kbuHJwmX1yVwpNo8LAXVtqEhnKwcPV7JM/b+X6ETVf9D3kvs7d4H59RlAkh07hYcSeKNibzf63NxP7lx4EnKQriOocLMg84ZwawcGC8ncoX9qiN7evegdwnVODTuWcmpdNs7LXCyHlrytD6wXRPvIMPr7A1X9y4wYhvDlkHDcv/czjh7lNio9nfDfXsXJdSgrNwsL42T0sOjS0wnk1OSeH6LAyyxQaSooX594J58RzRS/XfrnuQAox4WXO4+EVzztlFRYfZfHmHQzr2Jbvd3r367zk3Bxiyi53WCgpJ1x7pbjHSc7Jwd8YwoKCvLrL1+lz6oRz4rn8LHfe/hSiI8pvy9RqtuWSzTsY2rEt3++ofltOODueK9xZ6/b78Llt8e5zG3tBD0YPc+2X9zz7OYdq8NhsjPkd8Lsyb02x1k6pZrKbgSdrbCGqoKKvSN1Sf9WqVY//2gshv13nLbz/scre35y1jxbBjYip35CDR7IYFh3PE+vKd44fUS+YrKJ8LJZrYocw+0DlT8/2xLrDB4gNjaJFcCQp+Vlc3LILf1kxo9w4C/dv4ZJWXflsVwINAxsQF9aIvbkZVczx5KyFJ5+rR1wry6QrK+97bNbHpf2ZPva3egw492itFHwBhr9S2uXB6ld20/SsCJ8KvuD8tqxOQUo+QU3qux7ktiuHkmJLQKh3lxPTv0lg+jcJAPTvGsdVg+KZt2oL3WKjyckvrPpn7b07+nyH49qUZGIjI2kRHk5KTg6j2nfgjvlzfJqXR3lpB4gNa0iLkAhS8rMZ1boTd3z3VblxGtcP4WCBa12HN2/HjhMe8uaNhINJxIU3pGVoBMl52Yxq04nbv55ZbpzY8IbsyjoMwNCWbdmVedinrI2Z+2kZ0ohmDRqSWpDFBTHdeThherlxkgsyOadRG2buX01sSGOC/AJ8+nIKsO7wflqHRtE8OJLU/CwuatGFe34q3wYWJW3hkhZd+Xx3ApGBDYgNjWJfrvfr59R+Uq4NdHG3gZ89bAM+/Iz+4+8T+Ph7V97AjnFcfV48c9dsoXuraHIKCiv8NNTfzxBWP4iMvAIC/PwY1KkNP27z7EvVRz8m8NGP7qwOcUw4N545CVvo3rLyrGkr1jJtxVoAmkWG8+p1l3r85RRg2rcJTPvWlTegcxxXDYxn3i/ubVlQ+bZctn4nZ5/ZkpXb9tKnfSt2JHvW9j5dnMCni11Z58XHccXwHiz4cQtd28aQk19YrmuHYxqGNeBwdj5hwUFcPjSeh16Z5fG6TV+WwPRlpcfK8YPjmb9qC93iKl+31Iwc4mIaERnagIycfPp0akVikmfdEZw062T75NkdfbrLd8ac1cyYs9qraS4+vxvn9Izlzkene92P48xPfmLmJ95d13y/bDPxZ8Wy4MAauvdqzb49nu0nn89bw+fzvH/AnK+mLU9g2vIybWCAuw20Pkkb2OBbG5j+dQLTvy6znwyJZ/5PVe8nle6TyTXfRcYPhzZwafP+LE1dTafw1uQW59dq1w6FaQXs+c86Wt7SmaBo3x+eC65zaquQM46fU8+P6c6jCeW7X0ouyODsRm2Ztf8XYkMaE3gK59SEtCRiw6JoERpBSl42o1p35vblpdcn2UVH6PXJv4+//vj8CTzz8xKPC74A7yck8H6Caz8ZHBfHtT16MHPLFnrExJBdWFiuaweAg7m55BQW0iMmhjVJSYzp3JmpazxvQx+uTODDla68Qe3imNgnntnrtxDfIprsgsIKXQQEB9YjJDCQgzm5+PsZBrWP4+fd3v9yYG1y+WuGS9p35M655a8ZFu/YwbhOnVmdlMSF7drzw17vCstOn1PLbcv2cUzoE8+cdd5ty1UebssPf0rgw5/KfG7nlPncjniQ1S6On/d4/rl9vmANny+onWOzu8BbochrjKnqQGSABrWyMCdQ0VdE5P+Bo7aEF7d8yT973YS/8WPWgZ9IzE3h5rbnszlrH8sPbqJnw7b8vt1IrLUkZCTyj03e3UVTPs/yxOp5vDXwavyNH58mrmF71iHu6DKIdekHWJK0jW9TdtI/ug1zR9zKUWv5+9pF5e589MaadYbZC/w5s00JV93kupv3z7cUk5zi+unb5Zee2kMoTvTzS7tI25hDYXYxC3+/gQ5XRlNS7PoGGnvBGTWa5fS23PbKZrI2ZVKcU8wvt6+kxdhW2KOudWs6LIa0n9I4tDwV42/wC/Sj3Z86HH+wmy+Wr0+kf5dYvnriBgoKi3n8vQXHh3384ESu+lvp0+HPP6s9t70yo7LZVOuotTy2bAlTR4/Dz8+PTzauZ1t6Gnf16ce61BQWJe6ge5OmvH7xpUQE1WdYbFvu7NOPER++63veqoVMHXoVfsbwyY61bMs8xF3dB7AuLYlF+7dzfcfeDG/ejqO2hIwjBdzzg+fFoMryJv+wiKkjr8DfGKZvXce2jDT+0qs/aw8ls2jPdq7r3JP+zWIpKjlK1pEj/OUb354efdSW8NzGmfzn7OvxN4Yv9/3CzpxUft9uGBsz9/NN6mZe3DyHR7qOYULseVjg8XWfndK6PbVmLv87byJ+xvDZ7jVszz7IbZ0Gsz7jAEuTtrI8ZQf9m7Rl1vA/UGJLeH69b23A6f0EYPkGdxt43N0G3j9JG+jVntte9a0NHPPN5kQGdIpl7gM3kF9YzKPTS/M+vWsil7/4AYH+/rxxy1jq+fvhZ/z4cdsePl2xzvusLYkM7BDL3HtuoKComEc+Lc367LaJjHv5g5NM7b1vN7q25azJrm05+YPSvGn3TWT8c668l776lmeuGcm9YwdxOCefyR8uqGqWVfouIZF+3eP4/PkbKThSzFNvzj8+7P0nJzFp8vsA/GXSENq573b835c/sifFtz/ILV+fSP+usXz5lHs/ebd0mT96eCJXP/MBhzJzmTLrR/539xUUHy0hKT2bx96df5K5VpP1pDtrapmshyZy9V/LH5dv/8+p7ZNRkSFM+ec1hAQHUlJiuXz0WVz7p7fIyy/kucnj+Pt/5pGWnsvdf7yAlNQsXntuIgDf/LCVd6f94HVew0YhvPzu7wgOCcJay2VX9eV3418hL7eQp16awItPf0X6oRymvbOc+58ay9gJfcnPK+Slp2dWP/MK6xbMm89fQ0iDQEqs5YpLzmLS7W+Tl1/I8w+P5dlX55N2OJfLL+rJhDHnEBUZwrsvXscPv+zk7696v19+uzGR/p1jmfWouw2U2ben3TuR8c+XaQOTTq0NLF+fSP9usXz5dCX75CMTufrpMvvkPWX2yXe83ycf6nQN3SPPJKJeCB+e+xhTE+cR4Od6oO6sA9+zMn0jfRp14t0+D3PkaCEvbPm4mjme3N7X15O7+TDFOUVs/stymlzWBtwPfIoa0oKDXyZSnFPEgffcf/DwN5z52Dk+ZbnOqV/x77NvwN8Yvtr3MztzUrm13XA2Ze7jm9TNvLR5Lg93HcPVsecBlifWeV7Eq5hnmbxyAVOHjXddL2x3X5/Eu69P9m33ed6V+ToxkcFxcSy58UYKiou5f37p5z9z0iRGve86Vj62eDHPjRhBUEAAy3bt4uvExKpmeVLLtiUysH0sC+5wnXce+qJ0v5zx+4mMef0DGtSrx6sTRhPo73o48cpde/l41Vqvs45ay+NLl/LumHGua70NrmuGO/v2Y11qMot37mTahvX8c8SFLLn+RjILCrh9jm/XXuD8OXXZ1kQGtotl/p3ubTmjNO/zP0xk7GuubfnKRNe29DOGFYl7mebDtly2zZW14HZ31pdVfG5XjyYwwP25Jfr2uQFERQTz1t8mHT82j7+oFxPufoe8/EJeeGAMz76xgEOHc7liZE8mjj6bqMgQpj53LT+sSeTZN7w6XmYAZ1trU04cYIzZ69PCe8nYGnrysJyeevfu/XhdvPO0ri7XqTpd10ucc97C+x07qKdmhFU/Ug1Z0/+/jmUBPJba19G8L7d2cyyrX2vfLqJ9tfYdz34yWhMyOtVeH9SViiqsfpwaVFLg71jWGc1q92exJ8rNd67/3SP7Kz4NujZF1vKDI8sqOrUbzrxmHb59JKB2fyVfTlCms9+Rihs40wc8QC12r12p0P2n9jAhbzVI8v4BtL7Kbens8SS7pXPnAX/fevjyWaOrT+3Bt94KDzziWNaeTN9+7eWrg4fCqx+phvgfDHQsC6BepnMHsMKGzp4HGqQ4e3Au8b1XEq9Zh58mFrXJ2e8E30+7u9IPzxjzNPCVtXZlJcP+bq29v7aXTXf6ioiIiIiIiIiIiNQQa+0jJxlW6wVfAIfr7SIiIiIiIiIiIiJSm1T0FREREREREREREXGAMeYXJ3JU9BURERERERERERFxgLW2lxM56tNXREREREREREREpIYZY5oCzd0v91trU5zKVtFXREREREREREREpIYYY3oArwMRwH732y2MMRnAH621td7Fg4q+IiIiIiIiIiIiIjXnHeBWa+2Ksm8aY/oCbwPxtb0A6tNXREREREREREREpOaEnFjwBbDW/giEOLEAutNXREREREREREREpObMNcbMBqYCe93vtQSuBeY5sQAq+oqIiIiIiIiIiIjUEGvt7caYC4FLKfMgN+AVa+0cJ5ZBRV8RERERERERERGRGmStnQvM/bXy1aeviIiIiIiIiIiIiAOMMVOcyNGdviIiIiIiIiIiIiI1xBgTVdUg4CInlkFFXxEREREREREREZGacxDYjavIe4x1v27ixAKo6CsiIiIiIiIiIiJSc3YCw6y1e04cYIzZ68QCqE9fERERERERERERkZrzEtCwimHPObEAutNXREREREREREREpIZYa185ybCXnVgGFX1FREREREREREREaogxZuzJhltrP6/tZVDRV0RERERERERERKTmjDrh3zPLvLaAir4iIiIiIiIiIiIivxXW2huO/dsYs7rsa6foQW4iIiIiIiIiIiIitcP+GqEq+oqIiIiIiIiIiIicRtS9g4iIiIiIiIiIiEgNMcbMpPQO3zbGmK+ODQKstXZ0bS+Dir4iIiIiIiIiIiIiNeeFMv/+h/v/x4rAxokFUNFXREREREREREREpOZEAi2sta8AGGNWAo1xFX7vd2IB1KeviIiIiIiIiIiISM25D/iqzOtAoDcwGPi9EwugO31FREREREREREREak6gtXZvmdfLrbVpQJoxJsSJBdCdviIiIiIiIiIiIiI1p2HZF9baP5d52diJBVDRV0RERERERERERKTmrDDG3HLim8aYW4GVTiyAuncQERERERERERERqTl3AV8YYyYAv7jfOwsIAi5zYgFU9BURERERERERERGpIdbaVKCfMWYo0MX99mxr7RKnlkFFXxEREREREREREZEa5i7yOlboLUt9+oqIiIiIiIiIiIicRlT0FRERERERERERETmNqHsHEZHTSPvIVMeyIoPyHcvqsbzCQ09r1dF9wY7mteu1x7GsLYebOJYFUBjmXFbMcueyAMI35Tqa13CKc+37x586OJYFgHEuyq/QwTAgK846lhW619l1OxLiaBwBec5l5bR0dlsWdHbunFpS5O9YFkBBhHPrBlCQF+hYVkmmY1EARK11LisvxrksgIIFrRzN2+9gE2+8tti5MCDwXOfKPAE5jkUBUNDYuXOqKXEsCoCSes7m5bdwbr+Mbp3uWBbAzRO+dTQP7nY4z3O601dERERERERERETkNKKir4iIiIiIiIiIiMhpREVfERERERERERERkdOIir4iIiIiIiIiIiIipxEVfUVEREREREREREROIyr6ioiIiIiIiIiIiJxGVPQVEREREREREREROY2o6CsiIiIiIiIiIiJyGlHRV0REREREREREROQ0oqKviIiIiIiIiIiIyGlERV8RERERERERERGR04iKviIiIiIiIiIiIiKnERV9RURERERERERERE4jKvqKiIiIiIiIiIiInEZU9BURERERERERERE5jajoKyIiIiIiIiIiInIaUdFXRERERERERERE5DSioq+IiIiIiIiIiIjIaURFXxEREREREREREZHTiIq+IiIiIiIiIiIiIqcRFX1FRERERERERERETiMq+oqIiIiIiIiIiIicRlT0FRERERERERERETmNqOgrIiIiIiIiIiIichpR0VdERERERERERETkNBLway+A1HkFvXv3fvzXXohKxP7aCyAiIiIiIiIiIlIXqegrJ7Vq1apnf+1lqEwdLUSLiIiIiIiIiIj86tS9g4iIiIiIiIiIiMhpRHf6ilSjd+/eDwD1HYqLdShHREREREREREROUyr6ilSv/qpVqx53IkjdVoiIiIiIiIiIyKlS9w4iIiIiIiIiIiIipxEVfUVEREREREREREROI+reQUTk/4ntU7aTviadeuH16PlszwrD039OZ8+ne8CA8TfETYojvEO4T1kp76wnb+1B/MMCafXEeRWGFyblkPLOeo7syaLRZe1oOCLOp5xjBjRtwyM9R+BvDNN3rmHKlu8rjHNhi07c3mUg1sLmzBT+suKLU8qcPHgIg+PiKCgq4t4F89mQmlphnK5NmvD8iJEEBQTwdWIiT3691Oucv7S/mj6NOpNRlMOtq/5e6Th/aDuWcxp1ouBoEf/Y8iHbc/Z5nXNM3zPac1fHS/Azfny17yfeS1xWbnh0/Uge7jqOhoEhZBXl89jaaRw8kuVzHsCDowczsEMc+UVFPDx9AZsOVNyWb//uchqHh3CkqBiAW978nPTcfK9yWjeL4uE/jKB9XBPe+Pg7Ppq1qtLxxo3owfiLetEiuiEX3vwqmdne5RzTIvYM7n5qLG07NePdlxfy2bvfVTreC+/cTIPgIAAio0LYsn4fT975oVdZu9/cQuaaNALC69H5r2dXGJ7+fQrJs/cC4F/fn5bXtSO4VaiXa1RqYKtYHhs4BD9jmLZxPa//vLLc8HOaNefRAUPoeEZjbp83i7k7tvmcdTxvQJm8XyrJ6+/Om3/qeZOHuNp3fnER982run0/N3Ik9Y+176Xet+/jeUPL5M2tIq/pCXlLfM+7f+xg+nd2Hb8e/WABm/dVzAvw9+PBy4dy9pktKLGWl2d/x+KE7V5nPXzhYAa2c2U9+MUCNiZVzPrvpDE0Dg3B38+Pn/fs58nZSyixts6v20MXD2Zge9ex66HPFrCpknU75j8TR9MyKoJLX37P6xyAgTFtmHzW+fgZw/QdCby+8Ydyw8fFdeOBnsNIyc8GYOrWVUzfkeBT1qBmcUw+Zxj+xo9p2xJ4bf2KSscb2ao9rw8Zw6hZ77IuLdmnLID+Tc7kwW4j8Td+fLr7F97ctrzc8Pu7jqBPY9d1Qn3/ekQFhdB39rM+5zm6LVvGMrn/UPyNYdqmdby2uvyx66buZ3FVp+4U2xLS8/O4b+l89uec2jn13isH079LHAWFRTw2dQGb91bcL0f07sCNI88BazmYmcsjb88lI7fA6yyn2/dDl7ivFwrdba6S64Vj/nONu839y7c2B+423qFMGz9Z3iR33r+9z2vVIooH7riQdm2b8OZ7y5k246dKx7vvthF0aBeNwbD3QDrPvjSX/IIir/MAHjl/MIPaus47D8xcwMaU8utWPyCAf4+9mFYNIzlaYlm6bScvfL28irmdnJOf28DWsUwePBg/Pz+mr1/H6z+V35aB/v68MGIkXZs2JSM/n9vmzGZ/1qm1uePXDEVF3De/dq8ZHrqotM09NKPyNjflmjE0DgshwM+PVbv389Qs39rcoBaxTO43zHX82ryW1xJOOH51681VHbtRXGJJL8jjvmXzfD5+Ofn9Y86/stnx0xGCI/y46ZWoCsOP5JYw8x/ZZB08SslROGdsMN2HO/WIp5qnoq+IyP8TjQc2Jvr8aLa9UXkxJKJLBPG94jHGkLsnl60vb6Xn8xWLw54I79eMiCGtSH1rXaXD/ULq0fiqTuSuqfqiz1N+GB7vdSHXf/MByXlZfDb8JpYc2Mr27EPHx2kd2pDfdzyP8UveJauogKig4FPKHBwbR2xkJEPffose0TE8NXQYYz/+qMJ4Tw0bzoMLF7ImOYm3LhvDoNhYlu3a5VXWgpQVfHXgW+7tOLHS4WdHdaJ5cGNuWPkMHcNac1u7K7hj9Yu+rBZ+GO7pNJrbV/2P1IIs3j73T3ybuolduaWf020dLmLugdXMOfALZ0W14Y/tR/LEuuk+5QEM6BBL6zMiufD5t+neKprJY4Zy9SsfVzru/R/NY8P+FJ+zsnLyefGdJQzsfeZJx1u35QDf/bKTVyZf6XMWQHZWPq89O5tzh3Y66Xj3XP/m8X8/8s+r+WHpJq+zovo3pfHwZuyasrnS4YGN69P+oXgCQuqRmZDGnre30vGxXl7nAPgZw5ODh3HNF5+SnJPNl+MnsmjndrYfTj8+zv7sbO5dNI9bevX2KaNC3qBhXPOlO+/KiSxKrCRv8Txu6XnqeYPj4ohtGMnQt96iR0wMTw4fxrgPK7bvJ4cP56GFC1mTlMRbY31r3+Xy/ufOO38Y4z6oIm+BO2/cGAbFxbIs0fu8/p1jadU4klFPv0231tE8csVQJr1Ysc3dckEf0rPzGP3MOxgDEcHef+EZ2C6W1lGRjPj328S3iOaxi4cy/s2KWXd+MpvcI4UA/PvKSxjZpR1z1m+t2+vWPpbWjSIZ+eLbdG8RzWOjh3LVG5Ufu4Z3PpO8Qt8KM+BqA0/0HsG1Sz4iOT+LL0bcwKJ929iedajceLP3bOTxVQt8zjmW9WTf85m0YBrJedl8dfF1LNy7ne2ZaeXGCwkI5IbOvVl98MCp5WF4JP4ibv7uPVLys5g2+BaWJm9hR/bB4+P8ff384/+e2OYcOkXE+J7n9LYcMJxJMz8hOTebr8ZNYuGuHWw/XLotNx5KZdRn71FQXMykLvE8eO5A/rxwls+Z53WJpVWTSC597G26xUXz4NVDue658vulv5/h3isHc/kT75KRW8AdYwYwfnAP3pj9o1dZTrfv423uH2/TvWU0j106lKteq6LNdTm1Nnc874xIRv7TnTd6KFe9XjttPCu7gH9PWUz/vie/PvnPm0vJy3dtyz/dNIQxl/Tkw09XnnSaygxqG0tsVCTnv/428c2ieWLkUK54t+K6/W/Fz6zYvY96fn68O/FyBraJ5Zudu7zKcvJz8zOGJ4YO5drPPyM5O5svJkxk0Y4dbE8vvV64sktXso4UMPTtt7ikfQfu7z+A2+fM9jlzcJz7O8Gxa4Zhwxj3UTXXDGN8u2YY2M69Lf/lanOTRw3lqikVt+Vd00vb3L/G+9bm/Izhyf7nM2n2dNfxa8w1LNy9g+0ZZY9fKYz6fA0FR4uZ1KkHD/YZxJ8Xz/QqB5z//tFtWBC9Lq7P7BezKx3+y+x8zmjlz+WTI8jLLOG/v0+ny6Ag/OsZn/J+bereQUTk/4mIjhEEhFb9tz7/+v4Y4zqZlRwpgVM4rzVoH4V/SL0qhweEB1E/LgL8T/3k2T2qGbtz0tmbm0GRLWH23g0Ma96+3Djj43ry/o5VZBW57mJJP5J3SpnD27ZlxqaNAKxJTiI8KIjGISHlxmkcEkJoYCBrkpMAmLFpI+e3PfnFfGXWZ+4ku6jq5T23UTcWJbvuYticvZuQgAZEBfp2h3bniJbsy0vjQP5hiu1RFiYlMLBJ+YJlXGgTVqXvAODn9J0VhntraJe2fPWzq8i5dk8yYQ2COCMspJqpfHM4K59NO1IoPlpy0vG27kol+eCp3fUBkJmey9YN+zlafPK8Y4JDgog/pw0/LPG+6BvWMfKkbS60XQQB7uEhZ4ZTlH7E64xj4ptGszsjg71ZmRSVlDBz6xbOb1N+396fncXmtEM+381VIS+zTN622s0b3rYtMza623fSSdp3UCBrktzte+NGzj/T+/YNMPzMtszY4EFeYJm8Db7nDenalpk/ufaxdbvdbS68Ypu7rE8X3lrkKiZYi093AQ7r0JYvE1xZCfuSCa8fROPQilnHvpwG+PlRz98fXz9GJ9dtaKe2fLnGfezal0xY/SDOqGTdggPrcd15vXjj68rvlvVEfKNm7M457DrPlZQwa/dGzm/Rzuf5nUyPM2LYnZXB3hx3e0vcxAUtK2bd3XMAr6/7kSNHi08pr1vD5uzJSWdf3mGK7FHm7lvP0OgOVY5/UfNuzN5X+R+UPeHotmwSze7Mw+zNdm/L7Zu5ILZtuXF+OLCXgmLXNlydkkR0SNgpZQ6Ob8usH91tIDGZsOCKbcBgMECDIPc5oX4gBzNzvc5yun0P7dyWL1e729xed5ur5HrheJtb6nubA3cbdygvIzOPzduSKa7meuFYwRcgKDDA5205rH1bZqxzNC9C+AAAIABJREFUf3YHXOt24nmnoLiYFbtdvxwrKilhQ3Iq0eHe/0LIyc8tPtp9fZLpanOztmzm/Lbl29zwtm35zH2On7ttK/1atfI579j8PLpmCDz1a4ahHUvPOx63uQB/fNlNejSOKX/82rGZC2LLL/MPSXspcJ8DVqce8Pn45fT3j5ZdA2kQdpJSqDEU5lmstRTmW+qHGfz8fY771anoKyIix6X9lMbqe1ez6YVNnHmLbwUFp0U3CCMpr7RAl5yXTdMG5S86YsMaERcaxcdDruOTodczoGmbU8sMDSUpu/Svw8k5OUSHhlYYJznn5OPUhDOCIjh45PDx14eOZNAoMMKneTWuH05qQebx16kFWTSuX35e27KTGNykCwCDm3QhJKA+4fV8v3O6SXgoyZml2yklM4emVXypePqKC/jsjon8flgfn/PqsnOHdmLNih3k5fpekPVE2rJkwrtX/Dmbp6JDQkkqt29n18q+XS4v+4S8kNrLaxoayoGyedlVtO8y4yRl59DUx23gcV5OzeQ1iQwlJaN8m2sSUX5eYQ1c3Y386aJ+fHzPBJ6//mKiwrxv503DQ0nKKrNuWVW37zcnjeG7e28lt7CQ+Rt9657DyXVrEnbCsauKdbttWD/eWf4z+UW+F0ejG4SRlFt6nkvKy6ZpcMUv1yNbdmTOhTfzSv+xxFQy3BNNg8M4cGLWCe2tS1RTYkLCWLp/p08Z5fIahJOcX+YcXpBFkwaV/+GyWYMIWoREsuJgos95jm7LkDAO5JZpt7k5ND1JUeTKjt34eo/v6wbuNnC4NDP1cA6NI8t/fsUlJfz1oyVMe+Qa5j/7O9rERPHFd+u9znK8fZ94vVBVmxvubnOFp/YHCa/yvju1Nu6NB+4YyYypf6RViyg+n/WLT/NoGhpKcpnPLiU7h6ZhVZ9TwoKCGHpmG37YtdfrLCc/txOvz5NycmgaWr7NNS0zzlFryT5yhIb1ff/pfoVzeFXfCSosl/fn8KYnbMvkrByaVNHm/nvtGJbffyu5RwqZv8H7Ntc0JPSE41fFc0FZV3bsxtd7fTsn/BrfP06m18X1Sdt3lFeuS+et29IZfksoxu+3eZcvqOgrIiJlNDq7ET2f70mHuzq4+vc9TQQYP1qHRTHp6/e468cveKb3JYTVC/q1F+s36eUtc+gVFce7595Gz6g4UgsyKbGe3cl6Ku7/eC5jXnqPa16bTq/Y5ozudWp3GNdFgy/sztdz19ZqRvamwxz6Jpnm40/tDx9yevP3M0Q3DGNNYhJXvfAha3clcfelA2s18+b3ZzDgH1MI9Penb1zLWstxct06RjemZVQEizftqJX5l7V4/3YGfvkKF819k+XJiTzfd1St5Bjg0bOH8sxPS2pl/idzYYuuLDiwkRKf7lvznFPbsqzL2nWie5OmTFlTeV+uNSnAz48rBnZnwl8/YMQDU9i2/xA3jKzYF3xNcqp9d4xpTMtGESzeWPtt7nhelHN5AM/+ax7jrn+N3fvSGNq/Y63n+RvDi5ddyNRVq9mbkVn9BD5w+nP7/+CWqTMY+Ly7zbWpvTYHcNmZnel+RjRTEmrv+OXk94/E1UU0iQvgT+9GccO/olj4eg5H8nzPMsaMMMbcZIyJPeH9G09xUT2iPn1FfqN69+79APDb7VFcakW317rVyHwiOkawPXU7RdlF1Aur+ifjdUFyfjYxwaV3BUUHhx1/+ErpOFkkpB+g2JawLy+DxOw0YkOjWHc4yeOca+LjGd/VtX3XpqQQE1Z654DrLryc8pk5OUSHnnycmnDoSCaNgxoCrruDzgiKJK3Qt4vygwVZNCnzl/Um9cM5WFB+XoeOZPPAmg8AaOAfyJCmXckp9u6n0VefG8/l53QFYP2+FKIjSrdT04hQUrIqbqfULNdPT/MKi5izZjPdWkbz1S/Vd4Mw9oIejB7m+tzuefZzDh32/ies3hg1vg8jx7n6lX30T1NJP1h5f2EnCo8MpkPXFl4/wM0beXty2P2/rZx5TzcCQn1v18m5OcSU27fDamXfLpcXdkJebs3mTeoRz/hurv1kXXIKzcLC+PlYXlgV7bvMMsWEhZLixTaY1COe8d29zAv1PW98/3jGnutqcxv2pNA0snybS80sP6+M3ALyjxSxeK3r7qAFa7Yypm9Xj7ImnB3PFWe5xl23P4WY8DKfXXjl7fuYwuKjLN6yg2Ed2/L9Ts/+8Ojkul3dJ54repeuW7ljVyXrFt8qhq7Nm7Lw7hvx9/OjUUgw79x0Odf/71OP8o5Jzs8mJqT0PBcTHEZKXvljS0Zh6QMnp+1YwwM9hniVcUxKXjbNTswq095C6wXSPvIMPh45AYDGDUJ4c+hYbl7yuU8Pc0vJzyK6zJ290fXDSc2vvHudi5p35am1c7zOKMvRbZmbTbMyd/bGhISSklvxnHBe81b8+ay+jP9yGoUlR73OuXJQPGPOc7eB3Sk0bVia2aRhKAczyu+X7Vs2BmDfIdf5feHPW7l+hGdFX6fb99V9fWxz95ZpczdfzvVvetbmru4TzxVnu/NOvD6pLK+lO+8e79v4ZRf15JIR3QG4/4lPSUv3/PqkpMSy+JvNXD3uHOYu9uwu7YlnxXNlD/e6HUghusxn1zQslJTsyj+7py4azq70DN79abXHy+f053ZMck7564WY0FBScsq3uRT3OMk5OfgbQ1hQEIcLvLuOnRRf5poh5YRzeFXfCSosl2fn8AnnxHO5u82tP2FbRoeHklpNm1uyeQdDO7bl+x3e3cyTkptzwvGr/LngmPOat+bPPfsyfubHPh2/wLnvH55at6iAvpc3wBhDw2b+RET7k7bvKM3aV33PrDHmd8Dvyrw1xVo7xRjzV6A/8AvwkDHmJWvty+5x/gy8VSsrUYaKviK/XfVXrVr1+K+9EFK33PDTDY/5Om1+cj71m9bHGENOYg622J60D+C6Yt3hA8SGRtEiOJKU/CwubtmFv6yYUW6chfu3cEmrrny2K4GGgQ2IC2vE3twMr3LeS0jgvQTX07uHxMVxTXwPZm7ZQo/oGLILCzmYW/5i/WBuLjmFhfSIjmFNchJjOnVm6po1p7aylfgxbT2jmw/g64O/0DGsNXnF+aQX+tYf7aasfbQMPoOYBg05WJDF+THxTE4o/4CIiHrBZBXlY7FcFzeYmftXeZ3z0Q8JfPSDa1sO7BjHhH7xzEnYQvdW0eQUFHIou/y29PczhNUPIiOvgAA/PwZ1asMP2zy7eP18wRo+X1Dz270qM6etYOY07/uj639+F1Z8s4WiU/w5alUK0wpIfHkDsbd2pH70qf0cbm1KMrGRkbQIDyclJ4dR7Ttwx/xTK8RUmxcRSYuwcFJycxjVrgN3LKjZvPfXJPD+Gtc+OTgujmt79mDm5i30iIkh+0gV7ftIIT1iYliTlMSYzp2Zutrz/axcXhsP8wrL5HXpzNRfPM+btjyBactdeQM6x3HVgHjm/bKFbq3dbS6rYrFh2YadnH1mS1Zu20uf9q3YkZxWYZzKfPhTAh/+5Moa1C6OiefEM3v9FuJbRLvWLad8VnBgPUICAzmYk4u/n2FQuzh+3rO/Tq7bRysS+GiF+9jVPo6JfeOZs3YL3d3rduiEdZu2ci3TVrru3m8WGc5r11zqdcEXYG3aAWLDGtIiJIKU/Gwuad2ZO7//stw4jeuHcLDAlT+8eTu2Z3m2TidKOJREbHhDWoRGkJKXzai4Ttz+bemDebKLCuk17eXjrz8ecTXPrFrqU8EXYH3GAVqHNqJ5cCSp+dlc2KIr9636rMJ4caFnEB7YgDXp3v+8vCxHt2VqMrGRDWkRFkFKbjajzuzI7YvKPzCqyxlN+OugC7hu9qek5fv2vIHpyxKYvsy1X/bvGsf4wfHMX7WFbnHR5ORXbAOpGTnExTQiMrQBGTn59OnUisTk9MpmXYHT7fujHxP46Ed3m+tQps21jCa7kuuFaSvWMm1FmTZ33aVeFQ7LtfET845UkndiG7/W8zb+xZzVfDHH80IqQPOYSPYnua5fz+tzJnv2efa5AXzwcwIf/Ow+77SNY1LveGZv3EJ8s2hyKjnvANw5qB9hQUE8PHuhV8vp9Od2zNrkZGIbll6fXNKhI3fOLX+9sHjnDsZ17szqpCQubNeeH/Z6/8vG9xMSeD+hzDVDD/d3gphqvhOUvWbw8DvBhysT+HClu821j2NCn3jmrHO3uQIP2lz7OFbt9rzNHZNwMInYiDLHr7YduX1J+YdMdmnUhL8OuIDr5nxCWoHvz0tx6vuHp8Ib+7E7oYiWXQLJPVxC+r6jRDY9eae+1topwJRKBo0Celpri40xjwMfGmPaWGvv4pSeoOO5uv9tXkREasTW/2wlc1MmxTnFrLptFS3HtcQedf1EMnpYNGk/pXFw+UGMv8Ev0I/2f25//MFu3kqekkD+1nSO5hSReO/XNBp95vGsiMEtKc48wt6nf6CkoBhjDBmLdtP6yf74NfD+tHTUWp5YPY+3Bl6Nv/Hj08Q1bM86xB1dBrEu/QBLkrbxbcpO+ke3Ye6IWzlqLX9fu6jcnTzeWpqYyODYOJbecCMFxcXct6D0yeKzJk7ikg/eB2DyksU8d8EI6gcEsGzXLr7e5X1ffQ90upbuEW2JqBfK+30f571dcwkwrguP2UnfszJ9I2dHdeLtcx7hyNFC/rGl4hODPXXUlvDCpq/411k34mcMs/avIjE3lVvOHM7mzP18e3ATvaLa8Md2I7DAmsOJPL/xy2rnezLfbE5kYIdY5t53AwWFxTzySenT0j+7YyLj/vUBgf7+TLlpLAH+fvj7+fHDtj18utL7B/lERQTz1t8mEdIgkBJrGX9RLybc/Q55+YW88MAYnn1jAYcO53LFyJ5MHH02UZEhTH3uWn5Yk8izb3j/FPeGjUL598d/IDgkCFtiuWxSP2697N/k5R7hyVeu4aXHvzh+J/Dgkd2Z9tY3Xmcck/jqRrI3Z1KcU8S6O38gZkzs8TbXeGgzkr7YTXFOMXunuu5uNH6Gjk+c5VPWUWt5bNkSpo4eh5+fH59sXM+29DTu6tOPdakpLErcQfcmTXn94kuJCKrPsNi23NmnHyM+fNf3vG+WMPXScfiZMnnnuPN2ufMucufFteXOc/ox4iPf8r5OTGRwmziW3HQjBUXF3D+/tH3PvGYSo95zte/HFi/muZEjCAoIYFniLr5O9K0vzq93JjI4Lo4lN7vz5pXJu3YSo6a68xYt5rkLTz3v242J9O8cy6xHXW1u8oel+/a0eycy/nnXnTQvffUtz0wayb1jB3E4J7/ceJ5ati2Rge1iWXD7DRQUFfPQl6XzmPH7iYx5/QMa1KvHq1ePJjDA9TDRlYl7+XiVb92cOLlu32xNZGD7WOb9xZX18Oel8/j8TxMZ+8oHPq1DZY5ay+OrFvDukKtcbWBnAtsyD3Fnt4GsS09i8f5tXN/hbIY1b8dRW0JGYQH3/jir+hlXkTV5xUKmDr8Sfz/D9G3r2JZxiLt69GddWjKL9m6vsfVy5ZXwzNo5/LffNfgZw4zdq9mefZA/dxzChowDLE3eAsBFLboyZ5/3/c5WzHN4W367mKmXjMPf+DF98zq2HU7jrrPPY93BZBbt2sGD5w4iuF49Xr1gNAD7c7K4Ze4XPq/f8vWJ9O8ay5dPuvbLx6eW7pcfPTSRq//6AYcyc5ky+0f+95crKD5aQlJ6No9NnX+SuVbO6fb9zRbX9cK8u115D39Wps39eSJj/1Nzbe543rE2XnRCG6/hvKjIEN548RpCggMpKbFcPvosrvvjW+TlF/L3x8bx3MvzSD+cy4N3XkRIcCAY2JF4kH++6l0x9pivdyQy6MxYFv3hBvKLinlwVum6fXnTRC793wc0DQvlj+f1YcehNL64aSIA769K4JME79qhk5/bUWt5fMlS3h07Dj9j+GTDeralpXHnuf1Yl5LM4p07mbZ+Pf8ceSFLbriRzIICbp8zu/oZn8TXie5z+I2u7wTlrhkmTWLU+2WuGUa4z+G7fDuHL9vqanPz73S3uRlltuUfJjL2NVebe2XiaAL9/fEzhhWJe5nmQ5s7ai2Tv1vE1Asvx9/Pj+lb3Mevs85j3aFkFu3ewYN9BhMcUI9Xh18KwP7cLG6ZP6OaOVeW5ez3j6+ez2LPuiLys0p45fo0+k8I5thNyj0vbEC/8cHMeSmb//05HSwMvj6E4Aife8YNsNYWA1hrM4wxo4ApxphPgECfV8ILxtbAU45FnNa7d+/HnbrLta5mOblc8ttxw083OHZQT80/tSdMe2NrShPHsgCO7qudBwNUpV0v5/pPzixo4FgWQPYS5z67iF2137dwWeGbDlc/Ug1qOCXVsawff+rgWBbg0L0OLn5HHH4Yh4OX2qF7nV23Iw0djSPIwSZX5NwpDoCCzr7/IdJbJUXOPoY8OMK5dQMoyHPkezQAJZnOZQFErXXus8tr6lgUAH6FzuY5ed5pvNaZh7wdk3Suc/f2BdRe706VKmjs3EnVOFwqC8xw9hye38K5/TK6ted3pdeE38V962jeje2XV/rhGWNmAc9ba5ed8P7TwEPWWo+qycaYYOBuoJW19hZjTDugg7W22r9K6kFuIiIiIiIiIiIiIjXnCmDliW9aax8BvHnC3tvAEeBc9+v9wNOeTKiir4iIiIiIiIiIiEgNsdbmW2sr/bmLtdabzpbbWmufA4rc0+bh4e8VVPQVERERERERERERcYAx5hcvRi80xjTA3WmYMaYtrjt/q6UHuYmIiIiIiIiIiIg4wFrby4vRHwPmAS2NMR8A5wHXezKhir4iIiIiIiIiIiIiNcwY0xRo7n6531qb4s301tqF7juD++Lq1uEOa+0hT6ZV0VdERERERERERESkhhhjegCvAxG4Hr4G0MIYkwH80VrrTRcP9YHDuOq4nY0xWGu/qW4iFX1FREREREREREREas47wK3W2hVl3zTG9AXeBuI9mYkx5u/AeGADUOJ+2wIq+oqIiIiIiIiIiIg4KOTEgi+AtfZHY0yIF/O5DOhgrfXo4W1lqegrIiIiIiIiIiIiUnPmGmNmA1OBve73WgLX4nowm6d2AvUAFX1FREREREREREREfi3W2tuNMRcCl1LmQW7AK9baOV7MKg9YY4xZTJnCr7X29uomVNFXREREREREREREpAZZa+cCc09xNl+5//Oair4iIiIiIiIiIiIiDjDGTLHW/s6Tca217/qao6KviIiIiIiIiIiISA0xxkRVNQi4yIPpp1trrzTGrAPsicOttd2rm4eKviIiIiIiIiIiIiI15yCwG1eR9xjrft3Eg+nvcP//El8XQEVfERERERERERERkZqzExhmrd1z4gBjzN7qJrbWJrn/v9vXBVDRV0RERERERERERKTmvAQ0BCoUfYHnqpvYGJNNJd064LpT2Fprw6ubh4q+IiIiIiIiIiIiIjXEWvvKSYa97MH0YZ7kGGMaWmsPVzZMRV8RERERERERERGRGmKMGXuy4dbaz2soajHQq7IBKvqKiIiIiIiIiIiI1JxRJ/x7ZpnXFqipoq+paoCKviIiIiIiIiIiIiI1xFp7w7F/G2NWl31d01FVDfCrpUARERERERERERGR/++qLMzWJhV9RURERERERERERH571L2DiIiIiIiIiIiISG0zxsyk9A7fNsaYr44NAqy1drSH8+kLbLDWZrtfhwOdrLUr3KMMq2paFX1FREREREREREREas4LZf79D/f/jxWBq7w7txKvAb3KvM4p+561Nr2qCVX0FREREREREREREak5kUALa+0rAMaYlUBjXIXf+72Yj7HWHu8T2FpbYozxqJ6rPn1FREREREREREREas59wFdlXgcCvYHBwO+9mM9OY8ztxph67v/uAHZ6MqGKviIiIiIiIiIiIiI1J9Bau7fM6+XW2jRr7R4gxIv5/B7oB+wH9gF9gN95MqG6dxARERERERERERGpOQ3LvrDW/rnMy8aezsRamwpc5csCqOgrIiIiIiIiIiIiUnNWGGNusdb+t+ybxphbgZXVTWyMuc9a+5wx5mVKHwB3nLX29urmoaKviIiIiIiIiIiISM25C/jCGDMB+MX93llAEHCZB9Nvcv9/la8LoKKviIiIiIiIiIiISA1xd8vQzxgzFOjifnu2tXaJh9PPdP//XV+XQUVfERERERERERERkRrmLvJ6VOitjDGmPXAPEEuZOq61dmh106roKyIiIiIiIiIiIlL3fAK8DrwJHPVmQhV9RUREREREREREROqeYmvta75MqKKviMhpZOnKrs6FBXv1R8ZTEr62nmNZAFntnVs3gKw3WjqWFbanwLEsgLRLnMs6FO7nXBiQ3bKRo3mJC53Li0h1LAqA4gbOZUVtLnYuDMiJce5yu0Gas8eu3BbOtrniEOeywrukOxcG5KWEOxdWZJzLAvy+i3A0L9jBLD9nmxyZ7So8vL3WmBZ5jmUBhH7rYAMHShyshOwa49znBmCKnTvPBeQ6W1KaOPxbx7Jm7nHwexXQPCzT0bz92c4dm9NznDwyw98+H+do3o0P1HrETGPMH4EZwJFjb1prq71YUdFXREREREREREREpO65zv3/e8u8Z4E21U2ooq+IiIiIiIiIiIhIHWOtjfN1Wmd/kyUiIiIiIiIiIiIi1TLGBBtjHjHGTHG/bmeM8agTPRV9RUREREREREREROqet4FCoJ/79X7gaU8mVNFXREREREREREREpO5pa619DigCsNbmAR49lVVFXxEREREREREREZG6p9AY0wDXw9swxrQFjngyoR7kJiIiIiIiIiIiIlL3PAbMA1oaYz4AzgOu92RCFX1FRERERERERERE6hhr7UJjzC9AX1zdOtxhrT3kybQq+oqIiIiIiIiIiIjUMcaYXu5/Jrn/38oYEwHsttYWn2xaFX1FRERERERERERE6p5XgV7AWlx3+nYFNgARxpg/WGsXVDWhHuQmIiIiIiIiIiIiUvccAHpaa3tba88CegI7gfOB5042oYq+IiIiIiIiIiIiInVPe2vthmMvrLUbgY7W2p3VTajuHURERERERERERETqng3GmNeAj92vxwMbjTFBQNHJJtSdviIiIiIiIiIiIiJ1z/XAduBO93873e8VAUNONqHu9BURERERERERERGpY6y1+cA/gH8YY6KAFtbaPPfgnJNNqzt9RUREREREREREROoYY8zXxphwd8H3Z+C/xpgXPZlWRV8RERERERERERGRuifCWpsFjAWmWmv7AMM8mVBFXxEREREREREREZG6J8AYEwNcCczyasLaWR4R8VFB7969H/dw3NhaXA4REREREREREfl1PQnMB5Zba38yxrQBtnkyoYq+InXIqlWrnvV0XC+KwyIiIiIiIiIi8htjrf0E+KTM653AOE+mVdFXREREREREREREpI4xxjQGbsH1a+/jdVxr7Y3VTauir4iIiIiIiIiIiEjd8yXwLbAIOOrNhCr6ioiIiIiIiIiIiNQ9wdba+32Z0K+ml0RERERERERERERETtksY8xFvkyooq+IiIiIiIiIiIhI3XMHrsJvvjEmyxiTbYzJ8mRCde8gIiIiIiIiIiIiUsdYa8N8nVZFXxEREREREREREZE6yBjTEGgH1D/2nrX2m+qmU9FXREREREREREREpI4xxtyMq4uHFsAaoC/wAzC0umnVp6+IiIiIiIiIiIhI3XMHcDaw21o7BOgJZHgyoYq+IiIiIiIiIiIiInVPgbW2AMAYE2St3Qx08GRCde8gIiIiIiIiIiIiUvfsM8ZEAl8AC40xh4Hdnkyooq+IiIiIiIiIiIhIHWOtHeP+5+PGmKVABDDPk2lV9BURERERERERERGpQ4wx/sAGa21HAGvtMm+mV9FXROT/iUGtYpncfwj+foZpG9fz2i8ryw0/J6Y5kwcMoWOjxty2YBZzd2w7tbzmcUzuMwx/Y5i2dS2vrVtRbvjEDj24plNPSkpKyC0u4sHv5rM9M83nvPvHDGZApzgKiop49KMFbNqXWmGcAH8/Hho3lN5tW2Ct5eU537Fo7Xbv161lLJP7D3Wt26Z1vLa6/La8qftZXNWpO8W2hPT8PO5bOp/9OVk+r1vrZlE8fOsIOsQ24Y3p3/Hh7FWVjhfTOJynbruEiND6bE5M5YlX51B8tMSrrJatGnHPQ5dwZvto3v7v13z60YpKx7v3oUvo1qM1eblHAHj+mZns2J7i3Yq5PTp8MIPaxpFfVMT9sxewMaXiZ3fXwH6M6dqZ8PpB9PjnKz7lADxyQWnWA7MWsDG5fFb9gAD+Pe5iWkVGctRalm7byQtLl/uc98Cl7v2ysIhHpi1g0/6K6/bWHy7njLD/Y+++46Oo8z+Ov2YTCCSbQoAUmgmhtwRFUWoSqjSlCCjFcpYrnmdvCCL6O3s9sXAqqCBFBQXpxS6otNB7C5AChJRNIW1/f+wG0rO7LOsd934+Hj4esju77/3Ozvc73/lkdsaPcwWFANzz74WkWXJdyps0IJbeLWz94PHFlbfvzVGDaVbP3r59h3h1nWvte3RkLD3a29o2ZfYq9pTrc74+tZh5/+jz/w4J8mfZ77t5eaFTc9XznhgWS882trZNWlD5upx5zygaBFxYl3f/eyFp2c6ty2aNg3n8H9fTKiqEDz79iXlf/V7pcpMfHEzrFmEUFhWxe38yr0xfRZGT/a3EI2Ni6dHBti6fnrWKPYkV2zbg6tbccf01YLVyKiObpz5cTnp2nnNtaxTMpL8NpFXzEGbM/Ym5iysfS0YO7MzowVfSJLweg26fTkaWa9sjwOT4OGKbR5JbWMBjy1ayM7Vi2x7s0Z3h7W39O/rNt13O8mRetwYtebjdILwME4sSNzHr0A9lng+rE8gz0SPx966Dl2Hirb2r+PnUPpeywLP71N5NIpjSzZ61ZxvvJpTbx3Xswtg2HSkstpKWl8Oj36+4qH0cwBM3lOrfVYwplZtiAAAgAElEQVSVM/9sHysL7f17hvP9+4/IOz8/ybfPTyrJ8vYy8eSIUvOT5a7NTwCmxMURG2nbzz26svI+0CEkhJcGDqSOtzffHT7MtG+/dTqnV1hznooZgJdhsODwVt7f80uZ50dEdOLxTn1Izs0CYPaBjSw4vNWlNpXw9H7HU3PL3o0jefpaW5+bt28b726r2L8ntu1MkbWYHHv/3p/u+pzZ0338ycGx9Gpt2yaf/HIVu09WXI8l3h4/jKbBgdzw1qdO5/w2/SRJm7LwCfRm4OtRFZ5P3ZHNzy8l4hdSC4DGXQNof1NDp3NK69awBY+2G4zJMFiUuImZB38s83xYnUCejRmBv3ddTIbBW3tW8dMp54+xUmbtIGfbKbz8a9Psme4Vns9PspAyawfnjmVS/8aW1BsQ6XKbSniqbQA9Q6OYFG0bTz4/vIUZ+36psMz1jdvx93a9sAJ70lN46PdFLmWV8OTxx8WwWq1FhmHsNQyjmdVqPebs61X0FRH5H2AyDKb16sP4xV+QbMli8U3jWH34AAfOpp1f5qQli4fXruCumC7uybu2L+NXLiA5J4vFQyey+tiBMgegXx/axZy9tsl/36YtmHxNHLeu/sKlvB5tI7iiYRBD/jmTTleE8dSoeMa9Ma/Ccnf360paVg7Dnp+FYUCgbx3X2tazL+OXfE5ydhaLR45n9ZGDHDh7oW27Tqcy9MtPySssZHz7aJ64rhf3rv7GpbYBZFpyef3jdfTq0qLa5f52cy/mLd/EmvV7efSOvgyN68iiNQlOZWVl5jL9jVV071XzvQH+/c5afvxuj1PvX17v5hFcUS+Ivu/PJKZRGNMGxDPqk4rf3bcHDjF7UwKr77nN9ayoCCKCg+j37kyiG4XxzMB4bppVMevDDZv49ehxaplMfDxuFL2iIvjh4BGn83q2sW2Xg1+YSadmYTw1Mp5xb1XMA3j8sxXsOu5a0bxErxa29vWfPpPoxmFMHRTP6I8q5n20/kL7Zk1wrX092kXQLCSIYdNm0jEijElj4pnwatmsnHMFjHlxzvl/f/bILaxNcK2I0bNNBM0aBDHoJdu6nDw8nlvermJdzl3BzotYl5mWPN6asZYe11bf31Z/v4tnX1sKwJSHhzCkfye+Xu58QaN7B9u6vGHyTDpGhvHEuHhufaFs27xMBo+MjmXU1I9Jz87jHyN6MiYuhve/2eBUVqYlj9c/Wkeva6pv27a9J/h500HefmaM0+0prXdkJBH1gujzwUfEhIfzTL8+jJozt8Jy6w4e4tMtW1lz5+3/FXkmDB5rP5S//jaTlLxMZnf/M9+n7uaw5dT5Ze5sEcvqpB18cew3Is0N+VeXiQz57lXX8jy4TzUZBtN69GP80gW2fdzwCaw+epAD6aX3cSkMXbiVvKJCxreN4Ymuvbl37RKX2gal+veL9v49Ip5b/nVp+ren83q0jeCKBuXmJ29WMj/p25U0Sw7DXnB9fgIQGxlJRFAQ8R/Z+sC0Pn0YObdiH5jWty9Prl7N1qQkPho+nN4REXx/5IjDOSbDYOqV13Pr93NIzs1kYd8/sfbkPg5kni6z3NLEXTyzZaVLbSnP0/sdT80tTYbBs9f1ZdxKe58bNpE1xw6UKeqW799PXRPHratcmzN7uo/3amXrAwNfm0mnpmE8PSyese9V3t/6tmtBTn6BSzkAkXGBtLy+Hr/+62SVyzRo40vPJ5u5nFGaCYMn2g/lz7/OIiUvkzk9/sz3KXs4VGpfcFfL3qw6uYPPj/1Oc3ND3r56AoO+fc3prIBujQiMa0bqR9sr/yx+tWg4ti3ZW6suqDvDk20zYfB0zEBu/2kOyTmZfBl/J2uT9nEw68J4coU5mHvadGfsd7PILMgj2Mf3otrnyeMPN6kH7DQM4zcgu+RBq9U6rKYXmi7lpxIRkf8MMSFhHM1IJzEzg4LiYpbs30v/yLIH/cezMtlz5jRWq/Xi8xqEczQrnUSLPe/Qbvo3K5tnKcg///++3rW4mNS4DlEs+X03ANuOJuNf14cGAX4VlrvxmvZ8uNZ2NoPVitNnyUHJujxLYpa9bQf20D+i7NkE608mkmc/M2hLShJhfv5O55R2NjOX3YdSajxr96r2zfj2V9uZZMt+3Fljkbgy6ek57NuTRGFhkUuf1Vl9W0bx1Q7bd7f1ZDL+Pj409Kv43W09mcyp7OwKjzujT6soFm2zZSWcTMa/jg8NzWWz8goL+fXocQAKiovZmZxKmL/Zpby49lEs3mjfLo/Z8hr4V2ybu/RpFcVXJe07kUyAA+3blZRKaIDz7YvtGMU3v9myth+pus+VaNYwiGB/XzYfPOF0FkBcuygWby61LuteunWZnpHDngPJNZ61u2HT4fP/v3tfEg3ru7adxEZH8c0G+7o8XPm6NDAwDKjrYzs7ya9ObU5lON8f0jNz2HMwucaxZP/hVJJPXdyZm2Dr34t27gJga1KSbZusrH8nJV10//ZkXoegJhzPOcOJ3LMUWotYmbSd2NC2ZZaxAn7ePgD4e9fh1Lksl/M8uU+NaRhedh93cA/9I8pmrU9KJK/Ivo9LPXnR+7i49lEs3uS5sdKTeXEdoliysdz8pJIsd8xPAPpGRbFoV6k+UMk+taGfH+batdmalATAol276NfCuflCdHAjjlrSSMxOp6C4mKXHdtK3USuXPrOjPL7f8dDcMqZBOEcy0y/0uUO76Vdd/65Vy9mmlM3zcB+PbxvF11vs6zGx6v7mW7sWt3a/kve/rfwXZo5o2M6P2mYvl1/vrA5BTUgsvS84Wcm+wAp+3rY/BJgvYl9Qt1UwXn5Vf/feAT7UiQwEL8Ol9y/Pk23rFNyIo9lnbeOJtZilx3fSt1HZk09GR3RmzsHfySyw9a+0czkuZZXw5PGHm9QBhgDTgFeB14BQR16oM31FRP4HhJrNnLRc2BEnWbKICQ2/dHm+Zk5ml8rLySKmYaMKy01o05k723ehlpcXt6yY73JeSKCZ5PQLeSnpFkICzZzOvLCT9q9jO/j+2/XduLpFExJPZ/DPL78lzeLcpCHUz79s27ItxIRUvS5Ht+nId8cOV/m8uwT618WSnUdRse1QP/WMhYb1XCtCOer2u2MZf1sPtmw6wofvfUtBgfOF4lB/M0lZF9ZncpaFUH/zJZlghfqbSc4stZ1k2rMslWf5+/gQ37I5n/y+xaW8Cttlhn27zKqY99yY/hQVF7Nm+wHeX+PaAU/59iU70L64Vs35+Dfn2xcSZCb5bPV9rrSBV7Vm5ea9TueUCK2kj4dWsS6fvak/xdZiVm8/wPtrXT94dJSXl4kBce15699rXXp9SJCZlLQLbUtNt/Xd0uuysLiYf362jvlTJpCbX0hi6llemLvuoj/7pRZqrqR/my9N//ZkXsM6ASTnZZz/d2puJh2CmpRZ5v39a5l+zW2MveJa6nrX5i+/znQ5z5P71FC/clnZWTXv4xIPuZR1PjOg4lhZZf8eXap/uzpWejAvpHxWesX9wPn5ycBS85OFzs9PwD7fK90HLBbCyvWBMLOZ5KzSc0JbP3Eqp64/STkX/jCUnJtFdHDFbXJAkzZc3bAZR7LS+L+tq0nKdf2PSZ7e73hqbhnmZyapXJ/rXEn/ntjW3r9NXtx8EXNmT/fxkAAzyRnl5l4BFfvb3/t2Y9bPm8i1X57pUjmzL5eVDx2kbj1vom8NJbCpa2fVA4TUCSA598K+ICUvg47l9gXv7V/Hu9fcxs0RXanrXZt7NsxyOc+TPNm20LoBJJcZTzKJDm5cZplI//oAzO19G16Gwb92/8CPKQddygPPHn8YhmEA1wAljToB/GZ17kwr7/LX8jUMo65DL3QiRET+R3Xp0uVxbH9dkv90t9/8R38Cp3y6Zwuf7tnCsOZt+Xv0dTz047JLluXlZRBWz5+EI0m88vUPTOh9JQ/d0ItJcxy68alLbmzZlk4hoYz5yvXJ+X+qD9//jrQzFmrV8uL+RwcxZtx1zJ7l+rVv/9N4GQavD7+eT37fQmJ6Rs0vuAiPz1lOamY2vj61eH3iUIZe1ZYl9rPQLhUvw+C1Edfz6W9bOH6J2wcw4MrWPPXppetrJR6be2FdvjFhKMOubHv+DOFL5cE/9yVhZyLbdrl2NpkjvE0mburdiVuem8Px0xk8NjaO26+/mg+X/Vbzi+UPMaBRJ5Yc38Lswz/TKagpz0aP4qYf/4X1on7XUj1P7lMBbmzRjk4NwhizpPKfarvbY5+V6t8ThzLsqrbnz9j9b84rMz9ZbJ+fDOvFpM8u/Zh5Ka07uZ9vju0kv7iIsc2v5KVrhjHh+9key/fEfseTc8tPdm/hk91buMFD/Rs818fbhDekaXAgLy77nkZBAZcsp17zOgx+tyW16ppI2pzFzy8eZ9Dbzv8qzhkDG3Vi8fHNfHr4FzoFNeW5mJGM+uHtS7ov8BRPts3LMIgwBzPhh08IqxvAnN4TGbLmfbIKzrk9yxWGYdwN3F3qoRlWq3WGYRj9gXeA/diKvQBNgBaGYfzVarWuquF9/wL8FWhuGMa2Uk/5Az878tlU9BURR9TZuHHj1D/6Q0jNIqa/+nRlj6dYLDQyX/hpVrjZn5RsyyX7HCk5FhqV+ilYuK8/KdlV/+RnyaHdPHddf6cyxnSPZuR1HQDYeSyFsKALeaFBZlIzyrYvPTuP3HMFrNlmu8HAqoR9DL+2g1OZACnZWWXb5meutG3dGzfj3quuZczX88kvdv4M2JH9YhgW1xGAh15ayOn06v/ynJGVi9mvDl4mg6JiKyH1zZw669h3PGzEVQwa2hmASQ/P48yZml+XZl+moKCIlcsSuGnstQ5lAYy7Mpox0bZ1vy0phXD/C+szzN9MSpb7ts1xV0UzurMta/vJFMICSm0nAVVnPTu4L0fS0vnYybN8x3aLZmRXW96OxHLbZWDF7RIg1X7WUM65ApZt2UPHZmEOF31v6VJ1+8Kqa98Qe/ucOMt3TM9oRnQr1efqVd/nSrRq3ABvLxO7K7k5WXXGXhfNqKrWZZCZlBrW5dIte+jQNMyhou/wQZ0Z0r8TAI9O+4IzaY6d6XHb2G4EBfry1PNfObR8idGx0QzvYV+XR1IIDfYH+wkrIUEV+26rprYbzRw/bSvQr960j9sGXO1Q1oiBMQzrY2vbw//8ktNnL+3PFMd3jmZ0J9vYtb2y/m1x777H03kAp/IyCasTeP7fIXUDSD1X9gzGG5tcxb2/fwLAtvREant5E1Tbl7P5zq9/T+xTz2dll8vyq3y+0L3xFdzb+VrGLJnn0j5ubLdq+negE/3bwbHSk3ljukcz0j6/2FnJ2FXl/GR7qflJV8fnJ+OjoxnT0d4HUlJo5O/PJvtzYWYzyeX6QLLFQph/6Tmh8/0kJTeLcN8Lxbmwuv6k5JbdJtPzL9z0bsHhLTzWKd6pDPD8fuePmFsmZ1sIL9fnknOq7t+LD+3muW794ccqF6mWJ/r4zV2juelq+9zkeAphgeXmXpll86KbhtOhcSirH74DL5OJ+n6+zPrTKG770LXrFlellu+FSz+EX+nPpn8ncy6zEJ8A18piqXmZhNW9sC8IrRNIal7Z725406v4628fA7Z9gc9F7As8yZNtS8nNJKzMeBJQYTxJzs0iIe0EhdZijuekc8SSRoQ5mO1nkxzOuZTHH1ardQYwo5Kn3gT6Wq3WI6UfNAwjElgGtK3kNaV9BiwHngceL/V4ltVqTav8JWWp6Csi8j8gITWZiMAgmvgHkJJtYWjL1ty3+tKdIZBwOomIgHo0MQeSkpPF0OZtue/7sjeAiAiox5HMswDEN406//+Omv9zAvN/tt2krGe7SG7uEc3yLXvpdEUYWbn5lf7c77udh7g6qim/HUika8tmHEp2/s7HCanJRATVo4l/ICnZWQxt0Yb71iwts0z7BiH8s3d/bl36BWdyXbvm1Jert/LlauduCrV51zHiurZizfq9DOrZnh83OnbzksULN7F44aaaFywluL75fOG3e8/WHDl8qoZXXDBncwJzNtu+u9ioSMZfGc03u/cS0yiMrHP5bv1p1ZxNCczZZM9qEcn4LtEs3bWX6EZhWM7lV3rpg/t7d8Pfx4dJ36x2Om/eLwnM+8W+XbaN5Jbu0SzfupdOzcKw5OVX+Dmjl8nAv44P6Tl5eJtM9GrXnA37Hb8x72cbE/hsoy2vd4tIxl8dzdKde4luHEZWXhXti+2G2ceHSUuca9/8HxOY/6O9be0jGdMrmhWb9tIxwt62Kn9i24YVm5z/ie289QnMW2/L69Umkpu7lVqXuTWvy95tm7PhgGPrctGyLSxa5lyBf3C/jlzTOYL7Jy/A2UuhL/gugQXf2drWo0MkY+KiWfn7XjpG2ttWbl2mpluIDK9PkLku6ZZcurZtxuFkh+b6LFyxlYUrnL/BnKtmb0lg9hZ7n2seyYTOMXyzZy8x4eFu799/RB7AzowTNPWrT6O69UjNy2RAeEee3Pp5mWWSczO4pn5zlpzYQqRfQ3xM3i4f5Htin3o+61QSEYGl9nFRbbhvXdkbkbavH8I/e/bn1mWfcybPtX1c6bGyV5tIbnZyrOzd1rmx0pN5ZeYnbcvNTyrJAvhul+vzk9kJCcxOsPeByEgmxsSwZK+9D+RX7AOnsrOx5OcTEx7O1qQkhrdrxydbnRsjtqWd5ApzME38gkjJzWRws/Y8uGFRmWUa1jFzKs82T+jTqFWZmzI5ytP7nT9ibplwOonIwHo0NQeSXNK/v7s0/Rs808fn/prA3F/t/a11JOOujWbZtr10amqb55XvA/N/28b832wnMTYKCuDdiTe4veALkHu2kDpBXhiGwZn9uWC1Utvf9WsA78w4QTO/+jSqG0RqXhYDGnXkyS1l9wVJuel0bRDF4uNbiDQ3pPZF7As8yZNt2372JBHmYJr42seTJu158Ley48mak3sZ0rQ9C48mUK92XSLMwSRmpzuV48njj1K8geOVPH4CqPEC3VarNQPIAFz+Oa/hjhv2iHhaly5dpnrqzFNPZjlD60AqEzH91SoH9dgrIpnSIxYvw8SC3TuYvulXHrimG9tTU1hz5CCdQkJ5//obCPSpw7miQk7lZNN/7sdVh/lW/1f/2CbNmXJNPF6GwYL925m+bQMPdO7B9tPJrEk8wNNd4+keHkFhcREZ+eeYsmF1mTsVlxawreabVjw5Mo7ubSLIyy9k8rxV7Eq03W17wcPjGP2K7U7O4fX8+ee4gfjX9eGsJZfJc1eVuV5bicxWNbStWSRTusfZ1uWe7Uzf/CsPXN2d7aeSWXPkILOH3kTr4AacyrFNHk5YMrlredVnAob/WP1NF4IDfZn53Hj86tam2GolN6+Amx+dRU5uPq8+OpznZ6zidHo2jUICefbvgwnwq8O+o6lMnb6cgnI3ZDMfq/4GI/WC/Zj+wR34+vlgLbaSm5vPnePfJycnn/97eQyvvbCUM2csvPTmOIKCfMGAg/tTePOV5eTlVrzj8pEhNd9d9+l+cfRqHkFuQSGPL1vFjmTbd7f49nEMm2n77h6N7cnQdq0J8TeTmmVhwbYd/OunDWXex3DgRJSnB8TRM8qW9cQ3q9iRZMv6+s5x3PDBHEL9zfx4310cPH2G/CLbG87emMDnW3dUeC8fB465Jg2Po3vrCPIKCnlq/ip22e8C//kD47jp9TnUre3NrL+OxttkwmQysWH/MV5e/D3FlczP8gMrPFTBlIH29hUW8uTiC+376q5x3PhvW/t+uN/ePvu2Mfv3BL4o1766Dpwc9cRNcXRra2vb07Mv9Ln5j40rc/f0b56+g3vfW8SRlKpXWKEDVyWbdGMcPVpHkJtfyOTPV7HTvi6/uH8co96YQ91a3sz6y2hqeZkwGSY2HDjGS0sqrsvgPdVfLzA4yI8Zr03Az7c2xcW2/jbxbx+Rk5vPS1NG8uLbKziTls26RQ+RkppJTq7tBjs/rN/Hx/PXV3g/S3jN51g8fnMc17W3jV9TP17F7qO2ts19ahw3P2dblyN7deKW+BgKi4pJSsvi6VkrySh3w6C6Z6rvBMFBvnz44oQyY8m4+2eSk5vPK0+O4IV3V3L6bDajBnVm3A3XEBzkR3pGDus3H+KF9yr+AjGla833hJ7aN55ekbY+99jylexIsffvW8cz7GPbT70f7d2TYW3bEGI2k2qx9e+3fqm4Lh3hrryA9tUX1bs3bMXD7QZhwsTi45v48OD3/LllH3ZlnOCH1D1EmhsyucON+HrXxgq8uWclG05X/Ye4tJTqf9Lszn0qBdXvc2KbRjLluni8TCYW7N3O9C0beOCq7rasoweZPWh02X1cdiZ3rVxU5fuZ99fcByYNL9W/F5Tq3w+MY9Tr9v7911L9e3/l/dtR7sozObDfeXKEfX5SUMjkuRf2AwseGsfoV0vNT24pNT+ZV/n8JLtJze2dGh9Pr4gI8goLeWzlSrbb+8CS8eMZOtvWBzqGhvLSgAH4eHvz/ZEjPLOu4jXCjSbVF/t6h0XxVOf+eBkmPj+8lXd3/8w/2vdmx9mTrD25n4c7xtGnUSsKrcVk5OcyZdNyDmVVXRA1/1jzzfTcud8pduD0N3fNLTM6VpwflRbXpDlTul7o328nbODBzj3YVqp/92gUQUFxEZn555i8vpr+DRiFnuvjvkdrXpFPDY2jR0vb9zZp4Sp2nrCtx4X3jmPE23PKLFtS9L3hrU8rfa+RY3+oMmf968c5tTOHc1mF1An0pv2YhhQX2vpMiwHB7F+exsGVZzG8wKu2iZhbQ2nQpup56pJjNZ+13aNhSx5pNwiTYeLr45v54MD3/KVVPLvST/J96h6amxsypeMN1PX2AauVN/asZP3pyq9F29i/6sttJc9IIHdfGkWWArz8a1N/WAusRba2BcY2pTDjHInPrac4rxDDMDB8vLhiWg9Mdav+fk5kVT+xdGfbcvJqV5vVO6wFT3bqj5dh8MWRBN7b+xP3tevNjrNJrEuy3aT6iU796BkaRZHVynt7fmLp8Z1Vvp91f83XKXfX8QfA/scfqLTTGYbxBDAamAck2h9uCowFFlit1udr/KAXSUVf+a+kgqfWgVSuuqKv29VQ9HUnR4q+7lRT0dfdair6ulNNRV93c6To6y6OFH3dyZGirzs5UvR1F0eKvu7kSNHXXWoq+rqbI0Vfd6mp6OtujhR9/1vVVPR1t5qKvm5VQ9HX3Rwp+v63cqTo606OFH3dpaair7s5UvR1J0eKvu5SU9HX3Woq+rqTI0Vfd6qu6OtujhR93am6ou+lUFPR151qKvq6myNFX3eqqugLYBhGO2AYZW/ktthqte7yxGe7fPfAIiIiIiIiIiIiIn8Ae3HXIwXeyqjoKyIiIiIiIiIiIuImhmFsByr7iYYBWK1Wa6dL/RlU9BURERERERERERFxnyF/9AdQ0VdERERERERERETETaxW69GS/zcMIxS42v7P36xWq0fuoHH53n1BRERERERERERE5A9iGMZo4DfgJmA08KthGKM8ka0zfUVERERERERERETcbxJwdcnZvYZhNATWAF9c6mCd6SsiIiIiIiIiIiLifqZyl3M4g4fqsTrTV0RERERERERERMT9VhiGsRKYa//3GGCZJ4JV9BURERERERERERFxE8MwWgChVqv1EcMwRgA97E+tB+Z44jOo6CsiIiIiIiIiIiLiPm8ATwBYrdaFwEIAwzA62p8beqk/gK7pKyIiIiIiIiIiIuI+oVardXv5B+2PRXjiA6joKyIiIiIiIiIiIuI+QdU8V9cTH0BFXxERERERERERERH32WgYxl3lHzQM405gkyc+gK7pKyIiIiIiIiIiIuI+9wOLDMMYx4UibxegNjDcEx9ARV8RERERERERERERN7FarSlAN8Mw4oAO9oeXWq3WdZ76DCr6ioiIiIiIiIiIiLiZ1Wr9Fvj2j8jWNX1FRERERERERERELiMq+oqIiIiIiIiIiIhcRlT0FREREREREREREbmMqOgrIiIiIiIiIiIichlR0VdERERERERERETkMqKir4iIiIiIiIiIiMhlREVfERERERERERERkcuIir4iIiIiIiIiIiIilxEVfUVEREREREREREQuIyr6ioiIiIiIiIiIiFxGVPQVERERERERERERuYyo6CsiIiIiIiIiIiJyGVHRV0REREREREREROQyoqKviIiIiIiIiIiIyGVERV8RERERERERERGRy4iKviIiIiIiIiIiIiKXERV9RURERERERERERC4j3n/0BxAREffp23W7x7J+OBrlsaysKC+PZQEYhYZH8wIT0jyWlREd7LEsgHp7rB7Lqv9TkseyACwdQjyad/LmfI9lpYfW9lgWgP9ez01J01p7dvpreK4LUODvRU6Y5wIjF+d6LAvAO91zeZaWQR7LAjAXeO578zpX7LEsgKI6hR7Nyw7xXB/3S/Fs23JCPde2ogLPzr2yIj04WAJWD071vLI8u98xnfNc487V9+z3dq7Yc+uyZb3THssC2HS0qUfzwhtkeCwrJ8+z88pamR6N+4+moq/If6+8Ll26TPVQVoSHckRERMRFniz4ioiIiMh/NhV9Rf5Lbdy48QVPZXmwuCwiIiIiIiIiIhdJ1/QVERERERERERERuYyo6CsiIiIiIiIiIiJyGVHRV0REREREREREROQyoqKviIiIiIiIiIiIyGVERV8RERERERERERGRy4iKviIiIiIiIiIiIiKXERV9RURERERERERERC4jKvqKiIiIiIiIiIiIXEZU9BURERERERERERG5jKjoKyIiIiIiIiIiInIZUdFXRERERERERERE5DKioq+IiIiIiIiIiIjIZcT7j/4AIi7K69Kly1QPZUV4KEdEREREREREROSiqegr/5U2btz4gqeyPFhcFhERERERERERuWi6vIOIiIiIiIiIiIjIZURFXxEREREREREREZHLiIq+IiIiIiIiIiIiIpcRFWz2LicAACAASURBVH1FRERERERERERELiMq+oqIiIiIiIiIiIhcRlT0FREREREREREREbmMqOgrIiIiIiIiIiIichlR0VdERERERERERETkMqKir4iIiIiIiIiIiMhlREVfERERERERERERkcuIir4iIiIiIiIiIiIilxEVfUVEREREREREREQuIyr6ioiIiIiIiIiIiFxGVPQVERERERERERERuYyo6CsiIiIiIiIiIiJyGVHRV0REREREREREROQyoqKviIiIiIiIiIiIyGXE+4/+ACIi4hn7ZhwgbctZagXU4qoXYyo8f2ZjGke+SMQwwPAyaD4hgsDWAS7n9QyNYlL0ALwMg88Pb2HGvl8qLHN943b8vV0vrMCe9BQe+n2RS1m9mkXwdM84TIbB/F07eG/zb2Wev6ZRYyb3iKNNg4bct/Iblh/c71JOmbxepfI2VZLX05634uLzmkQ24KHnRhLVrhEfv7maL2f9VOlyMV2bc+fD12OYDPJyzvHKpC9JOpbmVNYVjYKZdM8AWkeE8P6Cn/ls6cZKlwtvGMCzfx9CoLkOew6n8sw7yygsKna6bQAPjYujW6dI8vILmPbBSvYeTa2wTN9rWnH70K54mQx+2nqYtz//0emcJs0b8uCLY2jRvjEfv7qCLz/8vtLloq+N4s4nhuBdy5sDO47z+hOfU+xC25o1DuaJv19Pq6gQ/j37J+Z9/Xuly01+YDBtWoRRWFjE7v3JvPzuKopcyOsV1pzJnfvjZRjMP7SV9/esL/P8yIhOPBYdT0quBYBPD2xkwaGtTucA9G4SwZRufWxZe7bxbkLZPvCnjl0Y26YjhcVW0vJyePT7FZywZLqUVeLxG2Pp2da2nTw1bxW7T1TcTj76yygaBPhxrqAQgHtmLCTNkut01hM3xNKzTSR5BQVMml951sw/j6KBvx/nCm1Zd89YSFq281kAj99Qqm1V5H30F3teSdv+7VrbAKbExxEbGUluYQGPLl/JztSKeQ/16M7wdu0IqONDp7fedimnabP6PPL4EFq0CmPmB9/x+bxfK13ukSeG0CnmCrIt5wB4+fklHDyQ4nRek4gGPPTsCKLaNuLjf63my49/rnS5V2bdSV1fHwCCgv3Yu+M40+7/zKmsZo2DefJvA2nVPIR/f/YTcxdXPlaOuL4zowdfSZPwegy+bToZWa59Z80aB/P4P2zjyQef/sS8r6oYTx4cTOsWYRQW2caTV6Y7P540bRrMYw8OomWLUD78+EcWfPFbpcs98sD1tG4VBsDxE2d54ZWl5OUVONcw7G27z9622Q60zT5WvvKOa2MlwCNjY+ne0dbnps5cxZ5jFfvAgGtac8f112DFyqn0bCZ/uJx0S57zbfPQ93b+vfrEEhsVSW5BAY8tW8XOlIpte7BnN4Z3sPXv6Nenu5TTK7w5T3fpi8kwMf/AVt7btaHM8yObd+SJzvGk5GQB8Mm+Tcw/mOBSVokpcfaxq6CAR1dWPnZ1CAnhpYEDqePtzXeHDzPt229dz4u15eUVFPDIqqrzXh4wEJ+SvO+cz+t1RQRTesdiMkws2Lmd9zaW3U5qe3nxSv+BdAgJJT0vl78vW8qJrIvbp07uE0tsc/t2srya7aS9fTt5w7XtBDz3vW15J5HkzZn4BHoT/2rrKpc7eyCHH586QJf7m9Ho2iCnc0okfribzITTeAfUpvVzXSvmrE/m1LKjYAVTHS8aT2xN3Wb+Luf1Cm/OlCv7YTIMFhxM4L3d5eZ5kR15PKYPKbklfW4jCw653ue61m/F/a2HYTIMlpz4ndlHvivzfGidIJ5sdxNBtf3ILMhh2o75nDqX4VKWJ48bSzw5JJZerSPJzS/gyS9Xsftkxe2yxNsThtE0OJAb3vz0ojL/CCr6ioj8jwjtGUKjfmHsfe9Apc8HdQjkyqvqYRgG2cey2f3WPrq80tmlLBMGT8cM5Paf5pCck8mX8XeyNmkfB7NOn1/mCnMw97TpztjvZpFZkEewj69rWYbBtN59mPD1FyRbsvh69DjWHD7AgbMXip0nsrJ4ZO0K7urcxaWMCnmxfZjwlT1vzDjWHKokb80K7rry4vMAsjJyeff5b7guvl21y9075Qae+ftsEg+dYsjYrtxyTxyvTvrSqaxMSy6vf7yOXl1aVLvc327uxbzlm1izfi+P3tGXoXEdWbTG+Yllt06RNA0NYuRjH9EhKpzHJvbhjmfnllkm0K8O943pxcSpc0jPyuXpOwdwddum/L470amsrPQc3pv2Fdf161DlMoZh8NDLY3liwvucOHKaCf/oT98RV7Hq88oP1KuTacnjzQ/W0rNr9ety9Q+7ePb1pQA8/eAQhvbrxFcrnCvGmgyDqVcN5NbvPiM5N5NF/e5g7cn9HMg8XWa5pYm7eWbzSucaUknWtB79GL90AcnZWSwePoHVRw9yIP3M+WV2nU5h6MKt5BUVMr5tDE907c29a5e4nNmzTQRXNAhi8PMz6dQsjKdGxjPurXmVLvv4nBXsOu58wbB0VrMGQQx60ZY1eUQ8t/yriqy5K9h5EVkleVc0DGLwCw607bOLaxtAbGQkEfWCiP/wI2LCw5nWrw8j58ytsNzag4f4ZMtW1v7pdpezsjJzmf7WKrr1qPrgu8SMd9by4/d7XM4qyXv3haVcF9+22uUevu2D8///1Gs3s/7b3U5nZWbl8caH6+hVQ//evucEv2w8yL+mjXE6o0yeJY+3Zqylx7U1jCff7+LZ12zjyZSHhzCkfye+Xu7ceJKVmce/3l1Dj24tq11u+vtrycnJB+Cvd8czfNiVzF1QeWG/OpmWPN76t5Nte2gIQ/p14msnx0qA7h0iaBoSxI2TZtKheRhPjIvn1ufL9jkvk8HDY2K56emPSbfkcd/InoyOi2HGkg1VvGvlPPm9AfRuHkFEcBB9ZswkplEYz/SPZ9SnFceTdQcP8enmBNbcfZvTGWDfD1zdnwnr5pGck8nXA29jzfH9HMg8U2a5pUd38/TGVS5llBcbGUlEUBDxH9nHrj59GDm34tg1rW9fnly9mq1JSXw0fDi9IyL4/sgR5/Mi7HkzPyImLJxn4/swYl7FvGf79OWJ1avZmpzERzc6n2cyDJ6JjWfioi9JtmTx1dhxrDl0kANpF+aVo9t3IPNcHvEff8SQVq15rEdP7lu+1Ok2lejdPIKIekH0+fdMYsLDeKZfPKNmV7KdHLBvJ3fd5nKWJ7+3prH1iBxYn83Tq54fWout7JqTRMNo14uvJer1CKN+nyYkfrCr0udrN6hL88evxNuvFpnbznD84720nOzasYHJMHjmqgFM/HYuybmZfNX/dtacqGSed2wXUzddfJ8zYfBQmxu5f/MHpOZl8EHXe/np1C6OZF8ojN7bajArkjaxPGkzV9aL4s8tBvLszvkuZXnquLFEr1YRXFE/iIGvzqRT0zCeviGese9WPvfq274FOfnO/0HzP4Uu7yAi8j8isG0A3uaq/9bnVccLwzAAKDpXDPb/d0Wn4EYczT5LYnY6BdZilh7fSd9GZQ/6R0d0Zs7B38kssJ01k3Yux6Ws6NAwjmakk5iZQUFxMUv276Vf87IHVyeyMtlz5jTFVqtrDSqfl14qb9+lzQPISMtm344TFBUWVb+g1Yqvn+3sNT+zD2dSnT8L5GxmLrsPpdR41u5V7Zvx7a/7AFj2484ai8RV6dU5imU/2ybLOw4m4e/rQ/1AvzLLNAoJJDElnXT7GXK/7TpGXJfqixGVyUjLZt/24xRWsx4D6vlSWFDEiSO2iebmn/fTY0BHp7MA0jNy2HMgucZ1uWHT4fP/v3t/Eg3rm53Oig5uxNGsNFufKy7mm2O76Nu4ldPv44iYhuEczThLYpa9DxzcQ/+Ist//+qRE8opsZ6RuST1JmN/FHVzFdYhi8SZbYW7bsWT86/rQwN+vhle5mNW+XFadS5d1Pm+j5/L6tohi0U5bn9ualESAjw8N/SrmbU1K4lR29kVlpafnsHdPEkVFNYxdbpKRls2+nScoKnTsDElfPx+ir2nO+nXOF33TM3PYczCZwhqy9h9OJfnUxZ2RBxfGk5rO/iwznuxzbTxJz8hh776a21ZS8AWo7eONq3u8822rIa/CWNnA+bYB9I6JYukG23e+41AyZl8fGpTb7xiGgWFAndq1APCrW5tT6c73B09+bwB9W0axaIetbVtPJlfdv08mX1T/jq7fiKNZZ0m02PY5S47upl/TS7PPKdE3KopFu6ofuxr6+WGuXZutSUkALNq1i34tXJuf9I2KYtFue15yDXnJ9rzdu+gX5Vxe+XnsN/v20K95VNnP0jyKL+1tX75/H92aNnOpTeffr0UUi3bat5OkZALqVLUfuLjtBDz7vTVoZ6Z2Ncc6AIeWnya8ayA+ARd//qO5db1qj638Wgbi7WcbQ3yjAihIc+6XAqVFBzfiqOVsmXlevybOz4Ud1TawKcdzznAyN41CaxFrkxPo2bDsySeRfqFsSjsIwOazB+kZUv3JKVXx5HFjifh2UXy9xT73Sqx67uVbuxa3dr+S9791/g+a/ylU9BURkfNO/36GjQ9vYefLu2l1d1TNL6hCaN0AknMuHOQm52YSWrds0SfSvz4R5vrM7X0bC2Jvp2eoa3lhfmaSsrIuZFmyCPNz7WDJ4TxLuTzzpctzxutTFvHse7fy6dpHiR/WmQUf/HBJcgL962LJzqOo2HaIn3rGQsN6rq2DkHpmUtIurM/UsxZCyr3X8ZR0moXVI7xBAF4mg95XtiC0/sWfoVGZjLRsTF4mWnZoAkCPgR1pEO76T/+c4eVlYkBse37dcrjmhcsJretPUm6p7TKnYp8DGNikDUsH3Mnb3UYQXsnzDmX5mTmZfSErKTuL0Gr63Og2Hfku8ZBLWSVCAs0kp1/ITMmwEBJYeeZzY/vz+YPjuKdvxZ9aOiI0oGJWaBVZz47uzxcPuJ4FTrZtTH8+v8i8ULOZk6XHzCzLf8QYdsddscyYeSd/ubcvtWp5eSTzuvi2bP31IDnZ5zyS50leXiYGxLXnt83OjyfOePShQXw5716aNQ1m0debLmlWiZKx0tW2VbbfaRhUtg8UFhXz/Ox1zJ86gZUv303z8GC+/mnHRX1uR1zs9xZqNpOUWbZ/h/q7v3+H1TWTVHqel5NFWGX7nGatWT7oT7zTczjhvhe3364wdlkqjl1hZjPJpZZJslgIdXF8CzOXn19WkWepfhlnc2yfuey6Ci019yyyWsk6d456deo4lVPm/fw9s52A57+36uSmFZD0WyaR/eu7/b1rcvaHJPw7up4b5utfps8l5WRVPs9r2oZl19/J9O4jLqrPNfQJJPVc+vl/p57LoKFPYJll9medpHeI7ddzvUPa4+ddh4Bazp+B68njxhIhAWaSM0rNvTIthAZU3Ob+3rcbs37aRG5+4UXl/ZF0eQcRETmvwdX1aXB1fTJ2Z3L080Q6PunaX2wd4WUYRJiDmfDDJ4TVDWBO74kMWfM+WQWX38G3p4yY2J3Jf/6YvduPM+r2Htz96CDeePrirnf1nyAr5xwvfrKW//vLYKxWK9sOnKRJyKUrxL5w/xzunjSUWrW92fzTPoqL3HPGdk0euqcvW3clsm3XiUvy/mtP7mfJsZ3kFxdxc1RnXu46jPHfzbkkWSVubNGOTg3CGLOk8p/Mudvjc5aTmpmNr08tXr91KEOvasuSTc6fxemIxz67kPXGxKEMu6rt+TOEL4UybZt4advmaR/O+I60MxZq1fLigUcGMeaW65j9ceXXLnen2Os7sWJh5dfi/W/34J/7krDz0o0nJV56dRkmk8F9f+1LXO+2rFi1/ZLmgWfa5u1lYlRsJ8Y9O4fjpzJ49OY4bh90NR8urfz6xu7iqe/NE9YeP8CSI7ts+5wWMbxy3RDGra34s34RT9kx6yTtxoVhmFz/NaMrLLvPkvbjSaKevOqS5qw9cYAlR3ddmOddO5Tx65y7Xr0zpu9fyoOtb2RQo6vYmn6Y1LwMiq2uXYu8Jn/EcWOb8IY0rR/Ii8u+p1GQa/e5MQzDC7gTaAKssFqtP5d67imr1fqcez5t1VT0FRFH5HXp0mXqH/0hpGYx71V9rVJnBLYNIO/9PAqyCqjlX8vp16fkZhLme2HnGFY34PxNBUok52aRkHaCQmsxx3PSOWJJI8IczPazSU5lJWdbCPe/8NfgMLM/ydkWpz+zU3nmcnkW9+cNvbkrA0ddDcDkP39M2qmsapcPrOdLZOsw9m4/DsD3K7bz3Pu3OZQ1sl8Mw+JslzB46KWFnK7hJ6wZWbmY/ergZTIoKrYSUt/MqbOOr4NRfaK5sbctb9fhFEKDL6zPkHpmUit5r5+2HuKnrbazRW/s3ZHiYscKsUPGd2PgaNtZkVPu/JA0By55sWfLUR65+V0AruzRisaRDR3KAhh+fWeG9u8EwCPTvuDMWcd+FnnbmG4EBfry8gtfOZxVWkpuVpkzd8N8K/a59PwLN5Caf2grj3WKdy0r20KjUpdrCPfzJ6WSPte98RXc2/laxiyZR36x8z/vH9s9mpFdbWPajsQUwoIuZIYGmknNqJiZmmlb3znnCli2ZQ8dm4U5VBgd2y2aUdVkpdSQtXTLHjo0DXO46Du2m+faBjA+JpoxnWx9bntyCo38/Sk5JzPM3+zWMWzY8KsYNMR2PfhJj87jzJma3zvNvkxBQRErlyVw09hrHc4bOqYrA0farpE4+W+f1DhWlggI8qV1hyZO3cBtxMAYhva19e+H/+9Lh/u3q4YP6swQ+3jy6LQvOJPm4Hgy1jaePPW84+PJjUM7M/j6aAAef+oLzqQ5vk0UF1tZ991uxo7u6nDRd/igzgzpZ2/bs060bUw3ggJ8eeod58bKm2KjGd7L1ucq2++cSi/b3lZNbeP+8VO2mxKt3riP266/2qEsT35vAOM7RzM62ta27ckphAf4g71mHOZvJiXL/XOU5FwL4aXneb7+JFe3zzmYwOOd45zOGR8dzZiO9rErpdzYZa44diVbLISVmhOGm82kODG+TYiOZkwHW962lJRy88sq8szVL1OTZEvZeaztM5ddlyn2uWeyxYKXYeDv48PZPOcuFTC+czSjO3lmO/H09+ao9IM5bHzzGAD5mUWkbMnEMBmEXxNYwytdl5to4fjM3UQ+GIO32fljqhLJOVll+ly4r3+N87zHY5zvcyVOncsgxOfCCRYhPoEVbtJ2+lwWT26z3disrldtYkM6Yil0/hIWnjpuvPnaaG7qYu8DJ1IICyw19wowk5JZdpuLbhZOh8ahrH7kDrxMJur7+TLrzlHc9sEXFd7bMIy7gbtLPTTDarXOAN4HfIHfgLcMw/jearU+aF9mBKCir4j88TZu3PjCH/0ZxDF3brztaVdfm5ucS53QOhiGgeWwheLC4mqvU1Wd7WdPEmEOpolvECm5mQxu0p4Hfyt7xumak3sZ0rQ9C48mUK92XSLMwSRmp1fxjlXblpJMRGAQTfwDSMm2MLRla/6xaplLn9vhvKAgmgQEkGKxMLRVa/6x0v15S+b+ypK5jl8/KiszDz//OjS+oj4njp7hyutakHio6rvQlvbl6q18udq5G8Zs3nWMuK6tWLN+L4N6tufHjZXfILAyX6xN4Iu1tpu+dY+O5KY+Maz6dS8dosKx5OZzJqPiAXI9/7qczcrF39eHUX2ieXL6Nw5lfTP7F76ZXfEOwNUJDPYjIy2bWrW9uOnuWOa9s9bh1y5avoVFy7c4lTekb0eu6RzB/VMW4OploLelnSTCP5gmfoGk5GYxpFk7HlhftnDQsI6ZU3m2CW3fRq04kHWmsreqUcKpJCIC69HEP5CU7CyGRrXhvnVlv4/29UP4Z8/+3Lrsc87kuXbdtXk/JzDvZ9t20rNtJLd0j2b5lr10ahaGJS+f01lltxMvk4F/XR/Ss/PwNpno1bY5G/YfcyzrlwTm/WLL6tUmkpu7R7N8aw1ZdXxIz7Fl9XYiq3ze+bY5kdernXN5s7cmMHurLS+2eSQTO8ewZM9eYsLDyTqXf9HXbCxt8aJNLF7k3M/8g+ubzxd+u/VszZHDpxx+7ZL5v7JkvvPX2uvRrz2//rCXAid+srlwxVYWunDjMFctWraFRcucG08G97OPJ5OdG0++WrKFr5Y4l9WoURAnT9r2292ua8mxxLQaXnGBy2270vm2AXz+XQKff2frAz06RjI6LpqVv+2lQ/MwLLn5nC6330k9a6F5eH2CzHVJt+RybbtmHElyrH2e/N4AZm9JYPaWC/17wlXRfLN7LzGNwtzev0tsO3OSCP965/c5Q69oyz9+XlxmmYZ1/DiVZ8vu27glBzOd3+fMTkhgdoK9bZGRTIyJYcle+9iVX7Ftp7KzseTnExMeztakJIa3a8cnWx3vs58mJPCpPS8uMpIJ0fa8sBrywsLZmpzE8LbO5UHFeeWQVm24f0XZeeXaQwcZ2a4dW5KTuL5lK9YnOj7+l6iwnVxp307C3b+dePp7c1S/6Rdu8rl5eiJhV/lf0oJv/pk8jr69naZ3tccn7OJuPGab59UrM8+7/5evyyxTvs+Vv7GiM/ZkHqeJb33C69Tj1LlM+oRF88z2sr/aCqzlS2ZBLlasTIiIY+lJ5296DJ47bpy7IYG5G+xzvdaRjLs2mmXb9tKpaRhZlcy95v+6jfm/bgOgUVAA7956Q6UFXwB7gXdGJU9dY7VaOwEYhvE28I5hGAuBmwGPnHJuWN10kxmRy1WXLl2mbty4ceof/TlEHHHnxtuqHNT3vL2P9N2ZFGYVUiugFleMaoK10LZ4eN8wEpecIPXHUxheBqbaJiJvuYLA1lX/lOWHo9VfS6l3WAue7NQfL8PgiyMJvLf3J+5r15sdZ5NYl2S7AdgTnfrRMzSKIquV9/b8xNLjOyt9r4Kk6idKsVdEMqVnLCbDxOe7djB90688cE03tqemsObIQTqFhPLeoBsI9KnDuaJCTmVnM2Dux1W/YQ27xvN5Jnvexl95oKs977A9b7A9r7CQUznZDPis6rzW71V/IFmvgZm35v8VX7MP1mIruTn53DPsTXKyzzHt3Ym8MWURaaey6NanHRPu7YPVasWSkctrkxeSfPxsmffKiA6uNis40JeZz43Hr25tiq1WcvMKuPnRWeTk5vPqo8N5fsYqTqdn0ygkkGf/PpgAvzrsO5rK1OnLKajkBmlFtWuezzwyIZ7rOkaQd66QZz9cye4jKQDMnjae8VNmA/DsnwfR0n7m1YeLN7D6170V3qf+T9X/tb9eA3/e+uo+fM11KC62kpdzjnsGvkKO5RzTPriDN578grTUTP702GCuiWuLyWSw9LP1fDWr8p+ZWzqEVJsXHOTHv1+ZgJ+vfV3mFjDh7x+Rk5vPS5NH8uLbKzhzNptvv3yIlFOZ5OTabor0w/p9zFqwvsL7nbw5v8JjpcWGR/FU536YDBNfHErgnd0/c3+HXmxPS2Ltyf083DGWPo1bUWQtJuNcLpM3reBQFYXfooza1Wc1jWTKdfF4mUws2Lud6Vs28MBV3dl+Opk1Rw8ye9BoWgc34FSObQJ9IjuTu1ZWfakR/701/4Fp0og4ureOIK+gkKfmrWLXcdt28vmD47jptTnUre3NrL+OxtvLhMlkYsO+Y7y8+PsKN1S0OnBHi0nD4+jROoLc/EImL1jFTnvWFw+MY9Trc6hby5ZVy8uEyTCxYf8xXlpSMQvAcGCqPWl4qbbNL9W2B8Zx0+ul2mayt21/5W3LCXNsXj+1Tzy9Im15j61YyfYUW96SieMZ+omtzz3WqydD27Yh1H7G1YLtO3jrl7LbZeTi3PJvXUa9YD/emXEHvn72sSs3nz9NfJ+cnHz+76UxvPbiUs6csfDyG+MICrKN8wcPpPDGq8vJy614p2zv9Bry6pt5a95fyuTdc+NbtrFy+gTemPrV+TOBX/rwT8z/6Ac2/by/0veytKz+EjLBQb588NKEMmPl+H/MJCc3n5cnjeCFd1Zy5mw2owZ15pYbryE4yI/0jBzWbz7Ei+9WvLO6qaD67y44yI8Zr9nHk2Jb3sS/2ceTKfbxJC2bdYseIiW17Hjy8fyy35vXuep/fluvnh/v/+tWfH1rY7WPXbfd/QE5Ofk8/+woXnl9BWlnLbz16jh8fX0wDDh4KJXX/7WqzM3dShTVqb7TBQf5MePVcm27t9RYOd3etoXl2rahYtsAskNqHk8euyWObu0jyMsvZOqsVew+ausDn00Zxy3TbJe9Gdm7Ezf3iaGwqJikM1lMnbmSjOyyZ7H5pVT/RwN3fm8AJ7vX3Lap/eLoFRlBbmEhjy1bxY5kW9sW3zaOYbNsbXs0tifD2rUmxGwm1WJhQcIO3vp5Q5n3KWpS/Rl7sY2imHJVX0yGwecHtzF95y880Kkn288ksebEAR6J6U3fxi0pshaTfi6Pp35fwaHMquc7phSfmtsWH0+viAjyCgt5bGWpsWv8eIbOto1dHUNDeWnAAHy8vfn+yBGeWbeu0veyOlBueSbuQt6jqy7kfTNuPEPmlMrrP4A69ryp31aSV8N+JzYiksm9Ym3rctcO3vn9N+6/thvbU5JZe/gQtb28eG3A9bRrGEJGXh73LV9KYmZGle9nOldz46b2LbWdLC+1ndw6jmEf27eT3uW2k20VtxOrd837HXd+byP7VOwXJTa+cZTTu7LJzyrEJ7AWbUaHUmw/1il/Hd+Som+ja6se6w9nN6i2XUff20H2nnQKLQXUCqhN6I2RWO2XBKsf15jEj3aTuekUterbrr9seBm0fLrqXwxsOtq02rzY8CgmX9nXdrxzKIF3dv3C/R3t87wT+3kkOpY+jVtSVFxMen4ek3+vep4HEN6g6m0I4LoGrbmv1VC8DBPfnPydTw5/y51R/diTeZyfTu0mNqQjf245EKvVSkL6YV7d/RUF1sp/2XUqs/prNLvzuBHAe1PN14R+algcPVra5kKTvlzFwDYGtAAAIABJREFUzhO27XLhveMY8XbZy5+VFH1vePPTSt9r1z8fqLTTGYaxx2q1tin32BRgABBitVov3d34SvJU9BWpnoq+8t+kuqKvu9VU9HWnmoq+bufhXWNNRV93qqno626OFH3dpaair7vVVPR1t5qKvu5UU9HX3Rwp+rqLI0Vfd3Kk6OsujhZ93aWmoq+71VT0daeair7uVlPR151qKvq6W01FX3dzpOjrLjUVfd3NkaKvu9RU9HU3R4q+7uRI0ddtPLzfcaTo6y6OFH3dqbqir7vVVPR1t5qKvu5WU9HXnWoq+rqbI0Vfd6qm6DsbmG21WleUe/xO4F2r1er6NT8c5OHhR0REREREREREROTyZbVax5cv+Nof/8ATBV9Q0VdERERERERERETEIwzDCPNEjoq+IiIiIiIiIiIiIp7xoSdCVPQVERERERERERER8QCr1TrYEzkq+oqIiIiIiIiIiIh4gGEYHrnbnIq+IiIiIiIiIiIiIp6xyxMh3p4IEREREREREREREflfYBjGg1U9BehMXxEREREREREREZH/Mv8E6gH+5f4z46F6rM70FREREREREREREXGfzcBXVqt1U/knDMO40xMfQEVfEREREREREREREfe5HThTxXNdPPEBVPQVERERERERERERcROr1bq3mudSPPEZdE1fEREREREREREREQ8wDGOGJ3J0pq+IiIiIiIiIiIiImxiGEVzVU8AgT3wGFX1FRERERERERERE/p+9+w6PqszfP/4+k94LpFETeguhg9TQpKMUQWn2st9dd11dBRt2V3dtq2JBsSOCXQQEBQuogLQA0nuAJJT0Rtr5/TGBJKSQmSTH/WXv13XttRnmOPd5TnnOM5955kztOQ0cxV7kPc8sfhxqxQqo6CsiIiIiIiIiIiJSew4BQ03TPHbxE4ZhxFuxArqnr4iIiIiIiIiIiEjteQEIquS5f1mxAprpKyIiIiIiIiIiIlJLTNOcV8VzL1mxDir6ioiIiIiIiIiIiNQSwzAmVvW8aZqf1fU6qOgrIiIiIiIiIiIiUnvGXfT30lKPTUBFXxEREREREREREZH/X5imef35vw3D2Fr6sVX0Q24iIiIiIiIiIiIidcP8I0JV9BURERERERERERGpR3R7BxEREREREREREZFaYhjGUkpm+LYwDOOr808Bpmma4+t6HVT0FREREREREREREak9z5T6+9ni/z9fBDasWAEVfUVERERERERERERqTyDQxDTNeQCGYWwEQrAXfmdbsQK6p6+IiIiIiIiIiIhI7bkH+KrUY3egBxAL3GbFCmimr4iIiIiIiIiIiEjtcTdNM77U43WmaZ4FzhqG4WPFCmimr4iIiIiIiIiIiEjtCSr9wDTNv5R6GGLFCqjoKyIiIiIiIiIiIlJ7NhiGcfPF/2gYxq3ARitWQLd3EBEREREREREREak9fwe+MAxjGrCl+N+6Ax7AlVasgIq+IiIiIiIiIiIiIrXENM1TQF/DMIYAHYv/eZlpmmusWgcVfUVERERERERERERqWXGR17JCb2m6p6+IiIiIiIiIiIhIPaKZviIi9civH8dYlnWuTb5lWYH7rP2MMuLHZEvzfN5IsSwr/rSbZVkAWUk+lmVlXOFrWRbAuRzrzgEA9z3elmUVNLG2baNm/WJZlrdLnmVZAEs+jLUsyyPZILu1dfvuVHfrjkmA3BDr8nyPWRYFgGuuaVmWabhYlgWQHG1pHN4nrcsq9LT27XTYpiLLsjy/sSwKAKMo19I8l2zr+sqMKGvHJ25ZBZZlma6GZVkAP2y/zLKs7BBr2xaQZWkc+VmelmW5NrV2W/qetO6a+t9OM31FREREROoBKwu+IiIiIvLfTUVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGResT1j14BERGxzr3jYxnYNoqc/HzuX7KK3SdPlVvm7VsmE+Lvw7n8AgBufvMzkrNyHM4a1DiKh/oMxcVm8NHe7by6fUOZ56e368Ks9l0pNIvIzs/n3p9Xsj/1rHMNA2ZPiqV/hyhy8/J5cOEq9hwv3zZXFxv3Th5Cz9ZNKDJNXvr6Z1bHHXA4q0lkQ+56dAIt2zfi3Ze+49P3fq5wuWfevhEvbw8AAoN92LvzBI/+/UOHso4v2EVG3Blc/d1p/Xifcs+fS8ji+IJd5B7NIGxiSxqOau5we0rrH9qKOdEjccHGp8e28Ob+dWWen91pBL0aRgHg6eJGsIcPly1/yum8QU0imdt3KC6GweI923k1bmOZ52+M7sHV7aIpKDJJzs3mnh+/4URmulNZ/UNbcl/nkdgMG58c3cKb+8rutznRI+jVMBIAL1c3gt196L3saaeyAAZGtGBu9+HYDIMlB+N4bdevZZ6fFBXNnK5DScrJAOC9fZtYcjDO6TyA+0fGMrB1FLn5+dz7xSp2JZY/D96YPoEQXx9cbDY2HzvBo8vXUGSaDuVYeX5vfSWexC3peAS4MuTZtpUul3Igm7UPHKDHHc1o1CfQqSyA9fMSOLkpE88AF0a/0KLc80k7s1j79Al8Qt0AaNrbj05TGjqdB3Df2OK+OS+f+z6tuG8+7+WZ42kaHMAV/3nfqaxBjaOY27v4nNu3nVd3XLTv2nZhZvuuFBUVkVVg33cH0mrQN0+IZUB7+zH54KJV7K6kb75v0hB6tGyCaZq8tPxnvtvueN8M8MDwWAa1jCKnIJ85S1exK6lsnqerKy9OHEOzoEAKi0y+33+IZ35YV8mrVe3uKbH072S/7jz07ir2xJdv24gebblhVC8wTU6nZfHAWytIzcp1Ku+u6YPp29me9+ibK9l7tHzesF5tuH5cb1xsBuu2Heblj9c6lzVtMP2Ksx5ZUHHW8F5tuH6sPWttnPNZAHMHDyY2yj4+uWflSn4/VT6vU2go/xo5Ek9XV344fJhHv//e6bw5VxQfl3n5PLB4FbtPlM9760+TaehXMh669Y3PSM50fDx0z6RY+ne0Z839oPz4xNvDjbfvmHLhcWigH8t/282/P/vR4axmjYK5/88jaBMVyvxFP7No6aYKl5s0sgtTxnSjSXgQo294hbQMx9vVtGkw98weS6vWYby14Ec+XrKxyuX/fPtwRo3qzNjRzzqcBdC0WQPunjOGVq3DefvNH/l48YYKl7t7zlg6d2lGVuY5AP791FIOHqi8T60wq3kD7px7Ba3aRfDuq2v45INfK132uj8NYcDQDhQVFfH1p5v4cnHV26EizRsFc///2ffb6x9Vsd9GdGFq8X4bdaNz+w2gWZNg5twxitatwnjzvbUs/uy3Cpe7528jadsqHMOA+BMpPPX8cnJy8x3LahzMnL+Ook3LUN78YB0ffVFx1oN3jqFtq3AKCgrZvT+RZ15ZRWFhkcNtA2v7ynuviGVAO/s17v5K+pK3byvuSwrsfckt8517bwVwz1Wx9Otoz3vovfLXHW8PN966s1R/EuTH8o27eeYTx/sTKN6WMcXb8o0qtuX4UttyiXPb8r4xsQxsY78O3PfpKnYnVDEWml48FnrJubEQWHuc/JFU9BUR+R8xoG0kzRsGMurfb9O5WThzJwzhmnkfVbjs7EXf8PuJJKezbIbBY32HMf2bJSRmZfDV+Fl8d+xAmaLPlwd3sXDPNgCGNWvFA70Hc+3KT5zK698hkmYhgYx77G2iI8N5YMoQZjxXvm03X96b5Mxsxj/+DoYBAd6eTuVlpOfw6tPLuWxw+yqX+8f1Cy78/cCzV/Pr93sczgrqH0GDoU04/uauCp938XEjYlpbMraedvi1L2bD4P7Oo7n5l/dJykln8aCb+T5xLwczSl776Z0rL/w9LaoX7QMinM8zDB7tP5wZy4qPkwkz+fboQQ6UOk52nUli3GfbyC0sYEb7LtzbexB/Wb3UqbY9GDOaG3+2t23J4Jv5PmEvBzPOXFjmqR0lbZveohftA8Nr1LZHeoxg1ppFJOak88WI6/nu+H4OpJ8ps9yyY7t4eNMqp3NKG9gqkubBgYx46W1iGofz0JghTF1Q/jy44+NlZOXlAfDiVWMZ2aE1y3/fV+0cq8/vprFBRI1swJZ58ZUuYxaZ7FqYQEiMn1MZpbWIDaDNqCDWv3iy0mVC2nsx6L6mNc4CGNgmkuYNAhn57Nt0bhrOQ1cM4epXK+6bh3VsRXaeY2+4S7MZBo/2GcaMlUtIzM7gq3Gz+PbYgTJF3S8P7WLh3uJ917QVD/YazLXfOtk3t4+keUggY598m87Nw3lg8hCmv1C+bbcM701yRjbj/1mzvnlQy0gigwMZ/trbxDQK55GRQ7jq3fJ5CzZsZsPR47jZbLw7fTIDW0Ty06EjDmX16xRJs9BArpj7NtFR4dw7bQjXPl02y8VmcPeUWCY/8i6pWbn8beIApg7uwutfr3e4bX07R9E0LJBJs9+iU8sIZs8ayg2PLSqzTICPJ3+dOpBZDy8kNSOHh24aQc/2Tfltd+XnTmVZzcICmTjnLTq1iGDOzKFc/3gFWVMGMvORmmUBxEZFERkYyJC33qJLRASPDh3KpEWLyi336LBh3Pftt2xLSOCtCRMYFBnJj0eOOJw3oJ39uBzzlH089MCkIUx/seJzbs6H37DruPPjof4d7MfJ+Eft45P7pw5h5rNls7LP5TP16YUXHn949zSnPpAGSM/M4fm31jCwV6sql9u+5yQ/bz7Eyw9PqXK5qmRk5PLyS9/Sr3/rSy7bpk04fr7OndcX8tJzmPfit/Tt3+aSy85/dQ1rf3R8zHVeenoOrz77DX0HtatyucvHdSEkzJ+brnoZ04SAIG/n8jJzeP7tNQzsWfV+27H3JD9vOcS8h5zfbwDpGbm8+Ppq+l9W9b57ef4asnPs44U/3zSYCeO68eHHFRfbK83KzOXFN1bTv0/Vbfv2x1089twyAObeNZaxwzvz5TfbHMoCa/vKAe0iadYwkNFP2/uSBycOYdpLlfQli77h9xr0JQD9OxZfdx629yf3XT2EWf8u359c/c+S/mThnGms2eZcf9K3cxRNwwOZdE/xtrx2KDc8WsG2vHogsx4q3pY3j6Bnh6b8tsuxbXlhLPT823RuEs5D44dw9euVjIU61GwsBNYeJ3803d5BROR/xJCOLflq824Ath9LxM/Lg4Z+PnWS1SUkgiPpqcRnpJFfVMTSQ7sZ3qzsYC8zP+/C396ubuDYRMMyBke3ZOlGe9t2HClum3/5tl3ZpyNvfWufgWGaOD3bKi05i32/n6CwoLBay3v7eBDTqwW/fr/b4SyftkG4+LpV+ryrvzveLfzBxXD4tS8WHdSY+KxkjmenkG8WsvzETgaHVz6zcnSTaJaf2OF0XpeQCI6mpZQcJwf3cHlk2ePk14R4cgvtMyO2njpJuI9zRb3OwY05lpXM8exU8s0ilh//nSERlb+ZG9OkE8vjdzqVBRDToBFHM1OIz0olv6iIr4/uYniTS78xromh7Vry5Xb7MRZ3IhF/Tw9CfMufB+cLvq42G24uLg6felaf3w07+OLuW/U8hUMrzhDROwAP/5rPZwjt6I27r3VD5CEdWvLl1uK+OT4RP8+K+2Zvdzeu7deN17937A13aV0aRnA0I5X4zJJ9d/kl9l0Ndh2DO7Vk6W/FbTtaRd/cqyMLVte8bx7apiWf7yg+B07at2WIT9m83IICNhw9DkB+URG/J54i3N/X4azYzi35en3xdedwxW0zMDAM8PKw9+E+nu6cTs1yOAtgYNeWLP/Z/uHfzoMJ+Hl70CCgbF6j0ADik1JJLZ79t3HXMQb3cLzfGdS1Jct+Kc46VHFW44uzfj/GECeyAIa1bMnnu+x52xIS8Pcov99CfHzwdXdnW0ICAJ/v2sXwVlUXkSozuGNLvtpUajxUyTlXG2KjW/J1NcYn5zULCSTYz5stB084lZeansOeg0kUFFQ9Q3L/kVMknnbuWzMXslKz2bs34ZJZNpvBrbcNYf7ra2qetyeBwkvk1Ya0lGz27TpJwSXGeWMn9WDhmz9y/ssyaSnZTuWlpOew+2ASBZeY2bqvFvYbQGpaNnv2J15y350v+AJ4uLtiOvitoAtZBxIvud/Wbz584e/d+xMIaeh4vwzW9pWDL35vVYd9CcCgzi35ekOp/sT7Ev1JaHF/csC5/mRgt2puy8Sy1wJntuWQ9i35clvxtjxevC0rGMNeGAv94PxYCKw9Tv5omukrIvI/ItTfl8S0jAuPk9IyCfP35UxG+Tegj191OUVmEd/uPMBrqx2/qIZ7+5KQVZKVkJ1B15BG5Zab1b4rN3XqgZvNhWtWLHY457zQAF+SUku1LTWT0ABfzqSXtM3Py36bhT+P6UuPVk2IP5PGPz/5nuQM5wbojrhscHu2bThEdta5Os+qiTBPfxJySt5MJOWk0zmoSYXLRngF0MQ7kA2nD1f4fLXyfHw5Wfo4ycqgS2jlM4entIvmh/hDTmWFevqRWK5tjStctpFXAE18Allfg7aFe/mRkFWSl5CdQZeG5c+BkU3b0SukGYczknl8y7ckZGeUW6a6wvx8SSh1jiemZxLm58vpzPLn+JvTJxDdOJy1B46wctd+h3KsPr8vJSc5n4SN6fR7qAVbXz1eZzmlndmbw4o7D+MV7ErXWaEENPNw+rXK9c3pFffNtw/ryzvrNpOTV+B0Vpj3RedcdgZdKth3M9t15aaOPXBzcWHaNzXrmxMv1Td7FvfNo/rSs7hvfvLT70nOdLxvDvP1JTG9VF5G8TmQVXGh1c/DgyGtWvDeb1sdzgoN9CUppSTrVGomIYFl21ZQVMSTi9aw+MGZ5OQVEH8qhacWOVf4Cg3yJSm5VF5KJqFBvpxNK8k7npRKs/AgIhr6cyo5g0HdWuHm6vgHGCGBl86KP5/VwJ9TKRnEOpkF9v12MqNU35WZSbhv2f0W7utLYqllEjIzCfN1rihU7rhMKz4uKxoPTb2cwqIivttxgNe/c3w8FBroS2JK1edAaSO7t2Xllr0O5/w3u3JCd375ZT/Jyc594OGMG24axMxr+7N18xHenP89+fnV+5DeURGNgxg0vBN9Y9uRlprFK898w8n45DrJ+qPMuWMUvXu04Gj8WeYtcP6WKtXl4mJjRGxHXnxztVP/vZV9ZZh/+b4krJK+5LEpxe+tnOxLoIL+JCWT0MCq+5NVm53vT0KDfEk6W2pbJleyLSNqvi1D/SoZC100hr19aPFYKN/5sRBYe5z80f7/W2MREalTsz9awYQX3mfmq0voFtmY8d2qvoVBTby3eysDP36Dp377kdu7XFZnOWD/mm14kB/bDidw9b8/ZPuRBO66cmCdZp4XOyqaH1ZstyTLKqMbd2LVyV0U1WgeYPVd2aoDnRuGMz+u4nvB1abRTTqx8sTuOm/b6hMHGPjlPEaveJN1iYf5d59xdZpX2k0LP2fAs/Nxd3GhT1Tt3KbgYlad3zvfOUmH6eEYtprPdq+O4BaejH+tFaOei6LNqCB+erruC83tIkJo2iCA1bsO1nkWwPt7tjLo0zd4atOP3B5Tx32zi71vjjuSwNRnPyTuSAJ3XVH3fbOLYfD8laN4b9NW4lPT6iTD1WbjqoGdmfbEQkbMns/+E2e4fmTPOskCyMg+x9PvreaJP41h/n1TSTiTRlFR3fRj57Oe/NMY5t9rzyqso6w/ypyFK5j47Ptc+8oSukU1Zlz3uhsPnTeiW1u+qUGR5r9Ngwa+DBzUjs8/q/getXVhwfzvuX7m6/z51rfx8/dk6rS668Pc3F3Jyyvg9mvfYMUXW7jrwfF1lvVHeeqFFUya9QpH488yZEDVt7uoDXfeNoy43+PZvsu52anVYWVfCTD7wxVMfO59Zr2yhO5RjRlvQV8C9nvKf/Nb3fYnGdnnePrd1Tzxf2OYf3/dbst24SE0DQ5g9W5rxkJ1fZwYhjG/1l6sCprpK2KhHj16zAFqdkMrkaoMnV7m4TWXxTC5VycAdh5PIjyg5KvxYQG+JKVnlnuJU8WfFmfn5bN82x6im4bz1RbHbkuQmJ1JRKmv4Ud4+5GYVfkMxq8O7ebxfpc7lDF1QAwTL7O37fdjSYQFlmpboC+n0sq2LTUrl5xz+ayOs89qXLV1HxP6dKp23ripvRg5sQcAD/7lfZJPV29Gpn+gN207NeHRv5e/P+F/m6TcdCK8/C88DvPyJym34q8Rjmrcice3L69ZXlYmjUofJz5+JGWVPyb7NW7OX7r2YerSj8grcm62zqncDMLLta3ifTiqSUcei6tZ2xJzMojwKcmL8PYj6aJZvKl5JT/isfjgNuZ0GexwzrSeMVzVzX4c7ziZRESAHxTfaizc35ekjPLb87y8wkJW7z3I0LYt+eXQsWpnWnF+OyL1YDab/mNf/7z0QpK2pmPYDCJ6BdRJnpu3y4W/G3X3ZdMbiZxLL3Do1hLX9Inhqh7F++3ERX2zf/m+OaZZBJ0ah/Ht3TfgYrPRwMebd26azHVvOnav3aTsi845bz+Sqth3Sw/t5vHLHOyb+8UwqVTfHF7Nvvm77cV9c5xjffP07jFM6VJyDoT7l8rzq/wceGz0MI4kp/KuA7N8pwyKYUL/4rYdTSIsqCQrNNCX06lls9o0DQHg+Bl7UfnbTfu4zoGi7+ShMVw5KBqAXYeTCAsulRfky6mU8m1bt+0Q67bZvxFx5aDoar9BvWqI41lr4w6xNs6eNWFQtENF3xkxMUyNtuftSEqikZ8fm4ufC/f1JTGzbF5iZibhfqWOXV9fkjIr798udnXfGCb1Lh4PxV90XAaUPy6h1HjoXD7Lt+4hulk4Szdfejw0dUAME/uWOgeCqj4HzmvTuCGuLjZ2V/CDgFWZOKIL44fZt+U/nvyMMyl1N6P2iiu7MXpMFwDum7OEs2er3getWofRuHEQ7y+8DQAPDzfe++A2Zs14rVp546/szuix9rz7Zy++ZB5wYUZxfn4hK1ds56qpvauVNe6qnoy6shsAD/xtIclnLp115lQ664pv3fXz93u4a+4V1cqC4v02tHi//bNu9xvAlWO6MnZkZwBmP/QpZ5Orf/4UFZms/nE310zuzYrvLn3rqwmjuzJ2uD3rnsc+4Ww1Z3lfN7Uvgf7ePPDKF9VeN7C2r7y6bwyTq+hLki7RlyzbuodOTcMv3BbiUqYMjGFiv5LrTpn+JMiXU6mV9ycuNsf7k3LbsoEfFH8hLDS4Gtsytvrb8preTo6F7io1FrpxMtctqN5YqC6PE8MwbgFuKfVP803TnG8YRnAlq2MAo6u14jWkoq+ItTw3bdr08B+9ElJ/dZz9/EOlHy/6NY5Fv8YBMLBdFNP6xrA8bi+dm4WTmZtX7utHLjYDP08PUrNzcbXZGNS+Bb/ur34x6Ly40wlE+QfR1DeAxOwMxrVoz19/KPvjW5H+QRxJTwFgSNOWHElLcShj8do4Fq+1t21AhyiuHhjDN1v2Eh1Z3LYKvur0485D9GzVlI374+ndphkHE6v/i/RLF29kqRO/yNx/eEc2/LSX/Bp8JdsqO1NP0synAY29AzmVk8Hoxp24e/On5ZaL8m2Iv7sX21Jq9kMGcacTiAwIoolfAElZGYxr2Y6/rvm6zDIdG4Ty5IDLuXb5x5zNdf5WHDtSTtDc93zb0hndpCN3//ZZueWifBsQ4ObFtuSazd7cfvYkkX5BNPEJICkng7HNO3DHL1+WWSbE04fTufbjdFjj1hxIr/7xeN6Hv8Xx4W/282BQ6yim94xh2c69xDQOJ+NcXrlbO3i7ueHj4c7pzCxcDINBraPYfMyx2TRWnN+OGD6vZMbMlnnxhHf3q7OCL0BOSgGegS4YhsHZ/TmYJrj7uVz6Pyxl0fo4Fq0v7pvbRjG9TwzLt++lc9NwMiromxdv2M7iDfZvCzQK9OfVa69wuOALEHcmgUj/IJr4BpB0ft/9eIl9l+5g3/xzHIt/Lumbr+kfw4qte+ncPJyMnIr75h9+P0TPlk3ZeCCe3q2bcciBvnnh5jgWbrbnxbaMYkaPGJbt2ktMo3Ayz+VVeGuHOwb1xc/Dg/uXfetQ25b8GMeSH+1Z/TtFMTU2hpWb9hIdVfF151RqJlERDQj09SI1M4fe7ZtxOKH6X/3+ZHUcn6y25/WLieKqoV1YtWEvnVpGkJmTV+ZrqOcF+XmRkpGDn7cHk4fGcN+8r8stU5GP18Tx8ZrirM5RTDmf1aKaWUNiuPeV6mUBfBAXxwdxxfstKopZXbqwdO9eukREkJFXfr+dzsoiMy+PLhERbEtIYEKHDry3rfo/8vTRL3F89Evxcdk+imn9YlixrfrjoYEdWrC+muOhMuOTjlFMHRjDN5urHp8AjOzezqlZvp+t3MZnKx3/wStnfPnFFr78Yku1l9+w/iBXTXrpwuOvl99V7YIvwFdfbOarLzZfesFSgoN9LhR++/Zvw5HD1fuh26U4ybc7AAAgAElEQVQf/8bSjx37NtEvP+4hpnskq05uo3O35hw/Vv2+y8r9BvDFsq18scyxW9k0jgjkREIqAP36tOLY8eq17/PlW/l8uWNZY4ZH06tbJHc8uARHbx1sZV9Zui8Z2C6KaxzsSwa1r35fArDkpziW/FRy3bl6UAzfbCruTyq5pgKM7NGObzY53p+U25bDurBqvQPbckj1t+WiDXEs2lC8LduUGgs1sY9hL761w+KN21m8sdRYaOYV1S74Vti2WjxOTNOcD1Q0c/c0cBR7kffC4sWPQ6u98jWgoq+IyP+In/YcZmDbSFbccz25eQU88PGqC899+rfpTPrPQtxdXJh/40RcXWy42Gz8uv8Yn2x0/Ie6Ck2Tub9+x3sjr8LFMFiybwf7U89yZ7f+bD+TyHfHDnBth670bxRJflEh6efOcedPy5xu29pdh+nfMZKv59rbNndhSdsW3zOdqf+y/4rtC1+t5YmZI7l74iBSMnOY++Gqyl6ySkENfHlx0W14+3hgFplcOeMybp3wEtlZ53j05Zm88MgXF2YCx46IZvFbPzndtvjXdpK1J4WCzHz23LmO0CtbQPEPfQQPbkJ+2jkOPvIbRTkFYBic+Tae1k/0wcXL8Ut8oVnEE9uXM/+ymdgMg8+PbeVgxmn+0m4wv6ee5PtE++BxVONOrDjh/I+cleSZzP35O94bNRkXm40le3ewP+Usf+/ejx1nEvnu6EHu7R2Lt6sbrwyzz545kZXOzSs/dyrr8bjlvNlvBjYMPju6jQMZp7m9fSw7U07yfeI+wH5rh+W11LaHN63i3cFXYzNsfHwojv1pZ7gjeiA7khNYfWI/17XtydDGrSk0i0jNy+Xu9dUvmFTkx/2HGdg6klW3X09ufgH3fVlyfH9+63QmvL4QL3c3Xrl6PO6u9qLlxiPxfLTJsVuPWH1+b3rhKGd2ZZGXUcDK23bTbkoYRQX2d4RRlzdw+nUr8/NzJzj1ezbnMgr54uYDRE9tSFGhPa/1iCDif81g/8oUbC4GLu4Gff/eCMNw/tYSP+21983f3GXfb/d/WrLfPvvLdCa+vLCK/9oxhabJ3PXf8d7lxftuv33f/b1rf/s5F3+Aa9t3pV9EJAVFhaTlneOutTXrmwe0j2TZ/fa++cGPStq25B/TmfJMcd/89VqenD6Se7zsffODi5zrm384eJhBrSL57k/Xk5NfwL1fl7zOlzdO54oFCwnz8+X/+vXm4JmzfHGj/dsxH2yK4+M4x877dTsP079TJF8+Zm/bw++WZC26fzrXPLGQM2lZzP96PQvuuoqCwiISkjN46N2VTrXt57jD9O0cxWf/uoHccwU8tqDkdT54dAYz5n4AwJ3TB9O6eIbxgq/Wcywp1fGs7Yfp1zmKz5++gdy8Ah4tlbXwkRlMf8iedde0kqw3ncwC+OHwYWKjolhzww3kFhQwe2VJ3tIZMxj3gT3vodWr+deIEXi4uvLjkSP8cNi5+66v3X2Yge0iWT7Hfs49sLhk33389+lc9fxC3F1deP2WibjabNhsNtbvP8an6x0fD639/TD9O0SydK4966EPSo1PZk9n6tMl5/flXdvwl9ccv76VFhzozYKnZuDj5U6RaTJlTDem//0dsnPyeObeCTz12irOpGQxeVRXpl/Rk+BAH957Zha/bj3MU685dt4FBfnw6uvX4e3tgWmaTJrckxuue4Ps7Dye/OcUnn1mebVm5lY7L9iHV16//sLYa+Lkntx47Xyys/N44ukpPPcve969D15BYKA3YHDwQBIvPLfC8awGPrz07i32LNPkyqv7cMvUeWRn5fHYC9N4/vGvSD6TyeJ31jH7sYlMnNaHnOw8Xnh86aVfvALBAd68VWq/TR3djWl3Fu+3ORN46nX7frtqVFemjy/eb/8u3m+vO95fBgf58PoLs/DxdqeoyGTyFT249rYFZOfk8fTDk/jXiytJTsnk3jtH4+Ntv+/6wcOneW6eE1mBPsx/dmZJ1rjuzPrLW2Tn5PGvByfx9LxvOJucxV1/upykU+m8+rS9X/5p/T7eXfyrw3lW9pU/7bFf41bMuZ6cvAIeXFKyfT75+3QmP29/b/X6zRNxc7FhM+x9yScbnPsR5HU77e93vnqk+LrzfkneR/dO5+p/lvQnw7u34fZ5NetPLmzLfxdvyzcr2ZYzSm3LL53clvsOM7BNJN/caW/b/Z+VGgv9eToT59XeWAgsPU4OAUNN0yxX6TcMo2azZ6rJcOYXGEX+l/To0ePh2pqdW5uvJVKRjrOft6xTz2yTb1UUgXFulmUBRPxo7Y9w+Lzq+AxPZ+05bcmHyhdkJdXdrxhfzCuk7n+Ur7RzOdYel+77vSzLymli3fkNMLVH3d+r+Txvl7xLL1SLlnwYa1lWdmtr95v/dmvPgdwQ67J8Hf+SS4245lr3nsy05vbXFyRHW5vnfdK6BrpY/PusPolFlmV5nrG2rzQsvie0S7Z1/WVGlHM/Ougst6y6+eG6ipiu1nYouUGOfbOmJrJDrG2bm3W/dVicZ905l9nU2m3pe9za/mTjO3dW2EDDMP4MrDNNM66C5243TfOlCv6zWqWZviIiIiIiIiIiIiK1xDTNeVU8V+cFXwCbFSEiIiIiIiIiIiIi/+sMwwi3IkdFXxERERERERERERFrLLAiREVfEREREREREREREQuYpjnGihwVfUVEREREREREREQsYBiGJb/wqKKviIiIiIiIiIiIiDV2WRHiakWIiIiIiIiIiIiIyP8CwzDurOwpQDN9RURERERERERERP4/8yQQBPhd9D9fLKrHaqaviIiIiIiIiIiISO3ZAnxhmubmi58wDOMmK1ZARV8RERERERERERGR2nM9cLaS53pYsQIq+oqIiIiIiIiIiIjUEtM091bxXJIV66B7+oqIiIiIiIiIiIhYwDCM+VbkaKaviIiIiIiIiIiISC0xDCO4sqeA0Vasg4q+IiIiIiIiIiIiIrXnNHAUe5H3PLP4cagVK6Cir4iIiIiIiIiIiEjtOQQMNU3z2MVPGIYRb8UK6J6+IiIiIiIiIiIiIrXnBSCokuf+ZcUKaKaviIiIiIiIiIiISC0xTXNeFc+9ZMU6qOgrIiIiIiIiIiIiUksMw5hY1fOmaX5W1+ugoq+IiIiIiIiIiIhI7Rl30d9LSz02ARV9RURERERERERERP5/YZrm9ef/Ngxja+nHVtEPuYmIiIiIiIiIiIjUDfOPCFXRV0RERERERERERKQe0e0dRERERERERERERGqJYRhLKZnh28IwjK/OPwWYpmmOr+t1UNFXREREREREREREpPY8U+rvZ4v//3wR2LBiBVT0FREREREREREREak9gUAT0zTnARiGsREIwV74nW3FCuieviIiIiIiIiIiIiK15x7gq1KP3YEeQCxwmxUroJm+IiIiIiIiIiIiIrXH3TTN+FKP15mmeRY4axiGjxUroJm+IiIiIiIiIiIiIrUnqPQD0zT/UuphiBUroKKviIiIiIiIiIiISO3ZYBjGzRf/o2EYtwIbrVgB3d5BREREREREREREpPb8HfjCMIxpwJbif+sOeABXWrECKvqKiIiIiIiIiIiI1BLTNE8BfQ3DGAJ0LP7nZaZprrFqHVT0FREREREREREREallxUVeywq9pemeviIiIiIiIiIiIiL1iIq+IiIiIiIiIiIiIvWIbu8gcmm5PXr0eLiWXiuyll5HpEIBR4osy8psa1kUnqmmdWFAXkMfS/MOnvCwLMtlp7VtC0ixLsscXmhdGGB4W3tcunXPsSxrbNN9lmUBLNnS07KsW3v/YFkWQN+JcZZljQjaYVkWQJfhCZbmjd14m2VZuR2su54C5Oa4W5YVGpxhWRaAe7anpXnDhuy2LGtXWrhlWQBJnzS3LOucv3VjE4Cc8emW5mVnWjj2Om7tXDvXHOvy8oKsHQv5HTIsy8rsmGdZFgCmdW0DcD3lZllWqyetHZ+cujra0rz/Zir6ilzCpk2bnqqt16rF4rGIiIiIiIiIiEiFdHsHERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGRekRFXxEREREREREREZF6REVfERERERERERERkXpERV8RERERERERERGResT1j14BERGxRvNGwdz/pxG0iQrl9Y9+ZtHXmypcbtKILkwd3Y0m4UGMuukV0jJynMob1DiKh/oMxcUw+Gjfdl7dvqHM89PbdmFW+64UmkVkF+Rz788r2Z961qksgDtnDKZvTBS55/J57I2V7D16qtwyw3q34bpxvXGxGazbdph5S9Y6ldW0aTD33DOG1q3CeOutn1jy8cYql//Ln4cxalRnxox9zqm8AWEteKDrCFwMgyWHtjF/7y/llhnVpD1/7TgQ04Q9aUncueELp7IA7h8Vy8DWUeTm53PvF6vYlVB+W74xYwIhfj642GxsPnqCR5etocg0ncqbPSmW/h2iyM3L58GFq9hzvGyet4cbb/9tyoXHYYF+LNu0m39/9qNDOf1CWjG702hshsFnx7bw1oGy+//ujiPp2SAKAE8XN4I9fOj/zT+dahNA/9BW3Bs9EhfDxidHt/Dm/nVlnp/daQS9Q8rm9Vn2lNN5fUNaMbvjGGyGwefHNvPWwbLtC/cM4PEuE/Fz88JmGPxnzyrWndrvVNa2V46RtCUdjwBXYp9tV+lyqQeyWffAPrrdEUmjPoFOZYG9P5nb296fLN63nVd3lO9PZrbvSlFREVnF/cmBNOf6k3UvneL4piw8A1y48sVmFS6TsDOHjQvOYBaaePi5MOqJxk5l7Zt/gOStKbj5u9H96S7lnj+7KZkjn8RjGGC4GLSYGUlAW3+nsgA+ez6XvRsL8Qk0+Our3uWez80y+fjfuaSdNikqhH4T3eh+uZtTWadPGTz3lCepKQaGASPG5HPFpPwyy3z/nSuffuSOCXh5wf/dkUuLlkVO5QEMCGvJ/Z1HYDNsfHxkK2/s+7ncMqMad+Av7QdhYrInLYl//Pa5U1lWn98DI1owt9twbIbBkoNxvLb71zLPT4qKZk6XoSTlZADw3r5NLDkU51RWn4Zt+Hu7sdgMG18d/433D5fta8M9A7m/0ySC3H1Iz8/hoe2LOX0u3bmGAf1DW3Jf55HYzm/Li/bbnOgR9GoYCYCXqxvB7j70Xva0U1nbXz3KqS3puPu7MvDZ9pUul3ogi18f3EeXv0US0SfIqSyAO9tcQ+8GHUjNz+TWTRWv859aTqRXg/bkFubz7N4POZB53Ok8gHsmxdK/o/2aOveDSq6pd5RcU0MD/Vj+m+PXVIB/XDOYftH2rIffWsneY+XHCyN6teX6Mb0xTZPTqVk8+OZy0jJzHc7qH9qKOdEjccHGp8cqPud6NSx7zl22vGbn3EM9hmEzbCw+sI3Xdq0v8/ykFtHc23UISdnnz7nNLD7o3DkH8ODQWGJbRpGTn8/s5av4Pan8trxzQF8mdOqAv6cHMc/PczoLHBjr+RaP9Y45N9Yb2DySuYNisRk2lvy+g9c2/VbmeXcXF565fCSdQsNIzc3h9uXLOJHhfH8CMHti8bgyv+JxJYCri417Jw+hZ6smFJkmLy37mdVxBxzOGtQ4irm9huJi2Fi8P67c+OS8kc3b8NrgCYxb+i47ziY6nHMhy6Kx0HlWHZeDr+rDlDtGgWGQk5nLS3e+z+Gd8eWWu+eNm2nTNYqC/AL2bj7Mi3e8R2FBoVOZd0+NpX8ne//10Dur2BNfQf/Vsy03jOoFpsnptCweWLCC1CzH+68/koq+IiL/I9Izc3j+nTUM7NGqyuV27D3Jz1sOMW/ulCqXq4rNMHjssmFMX7mExKwMvho/i++OHShT1P3y0C4W7t0GwLCmrXig12CuXfWJU3l9O0fRNCyQyXe/RaeWEdxz3VBufGRRmWX8fT25/eqBXDt3IakZOcy9ZQQ9OjRl067yA4pLycjI5eWXv6VfvzaXXLZNm3D8/DwdzjjPhsHD3UZx3U8LScxO59NhN7Lm5D4OZJy5sExz3yBua9ePqWveJT0/l2CP8sWc6hrYOpLmDQIZ8eLbxDQJ56GxQ5j6xkfllrvj42VkncsD4MWpYxnZsTXLd+5zOK9/h0iahQQy7rG3iY4M54EpQ5jxXNm87HP5TP3XwguPF909zeGBuQ2D+6LHcsv6d0nKSWfRgFv5IXEPhzJPX1jm379/c+HvayJ70y4gwuH2lM57IGY0N/38Pkk56SyOvZnvE/dyMKMk7+mdKy/8Pb1FL9rXMO++TuO4dcM7JOWk8+GA2/ghqWz7bm49iJUJO/n46G+08A3h5V4zGb3GuQ8imsYGEzmyIdvmHat0GbPIZNfCk4TE+DmVcZ7NMHi0zzBmrFxCYnYGX42bxbfHDpR5I3Nxf/Jgr8Fc+61z/UmrIX60Hx3A2v8kVfj8uaxC1r9+muFzI/ANcSMntcCpHICwAaE0Gh7O3tcqPp4DOwXQrXsQhmGQdSyL3S/uo8czXZ3O6zrMjT7j3Pjk2XMVPr/+63xCm9mY+bAHWWkmL9ycRcxgV1zdDIezXFzgxtvO0apNEdnZcMdtPnTtXkizyJKibnhEEU89n42vH2za4MLLz3ny3Lxsp9pmw2BuzCiuX/cBSTnpfDL4JtYk7OVg6b7SJ5hb2vbjmh/frlFfafn5bRg80n0Es75fRGJOOl9cfj3fndjPgfQzZZZbdmwXD29e5XQO2Nv2j/bj+eumBZzKTefty/7M2lO7OZJV8mb49rajWXFyK8tPbqF7cAv+r81IHtmxxOm8B2NGc2Pxtlwy+Ga+v2i/PbXjom0ZGO50+5oMakDzESHEzTta6TJmkcneD0/SsLPzH7CctyppA1+dXMvd7aZX+HzP4PY09g7h+o1P0M6vObe3voq/bX3e6bz+HSJpFhrI+Eft19T7pw5h5rMVXFOfLrmmfujENRWgX7R97DXhvrfo1CKCe2cO5bonyo69XGwGd10zmKsefIe0zFz+OnkAU4d0Zf5Xv1byqhWzYXB/59Hc/EvxOTeo6nNuWlTNz7lHe17OzDUfkZidzpcjr+O74/s5kF62gLbs6G4e2lSzcw5gUItIIoMDGTr/bbo0CueRy4cw+f3yY681Bw/x/pY4vrvluhrlDWwdSfPgUmO9MUOY+uYlxnpTHB/r2QyDR2KHMOvzT0nMzOCLq6fz3aGDHEhOvrDMlI6dSD+Xy5B332Jsm7bM7j+Av65Y5nTbLowrH3+b6ObhPHDVEGY8X75tN1/em+SMbMY/8Q6GAQHejo/VbYbBo72HM2PVYvv4ZOy15cYnAD6u7lzfvgdbT590tlmWj4XA2uMy8ehp7h7zNJmp2fQYFs3f/nMtdwx9vNxy3y9Zz79ufgOAOQtuZeS1A1i24AeH8/p1sveVVzz4NtFR4dw7fQjXPlW2bS42g7unxDL54XdJzcrlbxMHMHVwF17/en0lr/rfSbd3EBH5H5GSnsPug0kUFFY9i2rfkVMknq7ZJ+xdGkZwJD2V+Iw08ouKWHpoN8OblS02Z+bnXfjb2825mWTnDezWkhU/7wJg58EE/Lw9aBDgU2aZxiEBxCemklo8c/m3nccY3LO1U3mpqdns3ZtIYUHV29JmM7j11sG8Pv97p3IAOgc34mhmMvFZqeSbRSyL/52hjcsWm6dGdeWDg5tIz7d/8px8zrmiCcDQdi35cttuAOKOJ+Lv6UGIr0+55c6/CXC12XBzccHJSb4Mjm7J0o32vB1HEvHz8qChf/m885qHBBLs682WgyccyukU1IRjWcmcyE6hwCzkm5M7GBxe+QzVUY2jWXFih0MZpUUHNeZYZjLHs1PINwtZcXwnQ8LbVrr86MbRLDvufF6nwCbEZ50tad+JHcSGlZ/F5uvqeeH/T+dmOJ3XoIMv7r4uVS5zeMVpInoH4O5fszkGXRpGcDQjlfjMkv7k8qr6E1c3nDwcAQjv6IW7X+VD5MM/ZdK8jw++IfZ+yyvQ+fYFtPfH1bfy/97F0wXDsBdcC88VgeF48bW0qGgXvPwqfw0DOJdjYpom53JMvPwMbFXv5koFNzBp1cbeR3p7Q9PmhZw9Uza7fccifIs/E2jXoZAzp51vX+fgxhzNSuF4dnFfefx3hkaUPeemRHVj4aGa95VWn98xwY04mplivw4UFfH1sV0Mb+Lc9etSOgQ05Xj2WU7m2PuSbxPiGBhati+J8g1lU/JBADYnHyr3vCM6BzfmWFbyhf22/PjvDImovG8e06QTy+N3Op0X3MEXt0v0XUdWnCasdyDuATWfH7Uz7RAZ+ZUfZ5c1iOa7RPvMxz0ZR/Fx9SLY3flic2x0S7524JraLCSQYD/Hr6kAg7q0ZPkvxWOvQxWPvTDsM/29POz9pY+XO6dTMx3Oig5qTHxWyTm3/MROBld1zjWJZnkNruExDRpxNCOF+Ez7Obf06G6GN730B/3OGta6JZ/vtO+3bScT8ffwIMSn/H7bdjKR01lZNc4b2rYlX8bV/VgvJiyco2mpxKfbr99f79vD8BYtyywzrEVLPt1lP45W7N9H36YVf8OmugZ3asnS34rPgaOVnwNX9u7IW9/Zv6lnmjg1e7Pc+OTwbi5vVr5vvqvbAF7buZ5zhc5/SGz1WAisPS53bzxIZqq9r9yz6SANG1X8DYvfvi05r/duPkTDRsFO5cXGtOTr9cXHyeGKjxODi/ovT3dOp9X8/LOaZvqKiEitC/fxJSGrpKCUkJVB15BG5Zab1b4rN3XsgZvNhWu+Wex0XkiwL0nJJXmnkjMJCfblbKkL8/GkVJpHBBHR0J9TyRkM6t4KV9e6/ezzyiu78+svB0hOdn6AEO7lR0J2SRE+MTuDmAZlt2WkXwMAPhp8LS6GwYu//8TapENO5YX5+ZKQXrItE9MzCfP35XRm+Ta8OXMC0Y3DWbv/CCt3OXebgNAAX5JSS/KSUjMJDfDlTHrF22xk97as3LLX4ZwwTz+SctJKcnLTiQ5sUuGyEV4BNPYOYuMZ57YhQJiXP4k5pfZbbjqdgyrOa+QVQBOfQDacPux0XqiXP4m5Je07lZtG9EV5r+5bw2u9r+OayN54ubhzy4Z3nM67lJzkPBI2ptH3oVZse7Xy2cDVEebty8nS/Ul2Bl0q6E9mtivuT1xcmFaD/uRS0k7mYxaYrHjgBAU5RbQfG0irwTWbzVyVM7+d5cjiY+Sn59PxbueLa9XRZ5wbHzyay9MzssnLMZk6xxObrWaFZoCkRINDB1xo277yN9WrVrjRo1cNZk17+pFY+hzPSadzcNnbbkT62t8cLhp0PTbD4OXdP7I26aDjWRaf3+HeZa8DCdkZdGlQ/hwY2bQdvUKbcTg9mce3fktCtuMf7IR4+nOqTF+STsfApmWW2Z+RQGxoR5Yc+4XY0I74uHri7+ZNehXFzcqEevqV2ZZJOel0Dqr4dinnt+X6GmzLS8lNziPptzR6z23F9oM167uqo6FHAKfPpVx4fOZcKg3cA0jOc+7D99BAXxJT6v6aChAS5EtiqbFXUkomoYFlx16FhUU89f5qPnpkFrnn8jl2KpWnP1jjcFaYpz8J5Y6Tyq/hTbxreM55+ZYbe1V4zjVrS6/QphzOSOaxzd85dc4BhPleNPbKyCTMz7dWCrwV5vk7MNabUTzWO+D4WC/c15eEjFLX78xMuoSXnYEd5uNLQqZ9mULTJOPcOYI8PUnJde4r9KGBF40r08qfA35eHgD8eXRferRqQvyZNP756fckZzjWh4V5+3Eyq1TfnJVBl5Cy7esYHEaEtx/fHz/ErZ16O9Ok4izrx0JWH5fnjZg5gE3fVf2hjYurC0Ov7sursz90KiM08KL3jqmZhASVPU4Kiop48sM1LJ47k5y8AuJPpfDUIsf7LwDDMNoBVwDnL3AngK9M09zt1As6QEVfEWvl9ujR4+E/eiWk/nJvec0fvQoOeW/3Vt7bvZUrWrTn9pjLuGvt8jrLysg+x9PvrObxP4/BNE227z9Jk1Dn7zF6KQ0a+DJoYFv+fqdzgxFHuBo2mvsFM+OH9wn38ufDwbMYs+p1MvIr/gp3bbnp/c9xd3XhmUmj6BPVlF8O1f0b5BHd2nL/+99cesEaGNkomm8TfqeoxnMkqmdUk06sOrmrzvNGNerMV8e38N6hX+gc2JQnukxi0o8vY9ZB7u/vnKDD9EYYtVAwrK7392zl/T1bGV/H/YlZaHLm0DlGPNKIwjyTZXNOENLGg4DG7nWS17BnAxr2bEDa7nSOfhxP9H0d6iQHYP+WQiJa2Ljhn54kJ5i8fX8OzTu54Ont/H7MyYEnH/bi5v87h3clEw63b3Vh1Qo3/vWC899SqA4Xw0Zz32Bm/vQu4V7+fDDwWsatfq1O+0qrzu/VJw6w9Ogu8ooKuaZlV/7dZxwz1tTN9eelvcv5R/vxjGncnW0phzmVm0aR6fy9mKtrdJNOrDyxu0635a53TtB2mrV91x9pRLe2PFCH1ykTnMMAACAASURBVFQXFxuTBscw/ZEPOHE6jXumDeH6Mb1Y8HXF9z2tDaMbW3TOHT/A0iPF51yrLjxz2Vimr1506f/w/zM3fVA81pto3VivrrnYDMKD/Nh2OIFnvviJmbHduOuKgdz/Qe2eCwbwYK8h/GOd87ercJRVY6G60nlAO0bMHMBdI6r+TY2/PDeDHT/v4/dfnZt0Uh2uNhtXDerMtMcXcvxMGrOvHsz1o3qyYHn533IxDOMW4JZS/zTfNM35xc/NBq4BPgLO/8dNgEWGYXxkmqbzNx+vTjvq8sVFpKxNmzbV6Qkt0nfqsw+Vfjzx8i6MHxoNwD+e+owzKdZ8JSUxK5MIn5KZbxE+fiRWMfvhq0O7ebzv5eDA76pNHhrDFbH2tu06nERYcEleaLAvp5PLf31w3bZDrNtmn715ZWw0RUXVf0NwxRXdGDM6BoB77/uYs2er/npiq1ZhNG4cxAfv3waAh4cb7793KzNnvV7tTIDEnAwivEu+6hnu7Xfhh3pKlkknLvkkBWYRx7NTOZxxlkjfYHakJFQrY1qvGK7q1gmAHSeTiPAv2Zbh/r4kpVfe1ryCQlbvOcjQdi2r/UZg6oAYJl5mz/v9WBJhgSV5YYG+nEqrOK9No4a42mzsruCHFi4lKTeDMK+AkhxPf07lVjyTamTjaJ7c8bXDGWXyctIJ9yq13zz9OZVTcd7oxp14bHvNBuWnctIJ9yxpX6hnQLnjZEKz7vxpw7sAbE+Nx8PmSpC7N8l5td8vpB7MYfN/jgCQl17Iqa0ZGDaI6OX4By1J2Zk0Kt2fePuRlFV5f7L00G4ev+xyh3Oqy7uBK439XHDztOHmCeEdPEk5kldnRd/zAtr7k/t6LvkZ+bj51eyWOJXZ8m0+A69yxzAMGjQyCAqzcSa+iCZtnbvHQ0GBveAbOzSfvgMqnsV7+KCNF5/15JF/ZuMfUOEi1ZKUm0F46XPcy7/cOZCUk05cyokLfeWRzGQifRuwI8Wx+yxafX4nZpe9DkRUcB1IzSv50dXFh7Yxp8tgp7JO56YTWqYv8ed0qZm/AGfOZTBnm/2esF4u7gwO60RmgXOz8k7lZpTZlmFe/iRVcuuZUU068lhc3RYw0g5ls+3FIwDkpRdwems6hotBeM+6+ZD4zLk0QjyCAPus1IYegZzN+3/t3XecFdX5x/HPQ1OkY8WCoIINRbBG0Shq1MSYqLFiNzHFGvMzamJLYkksiUbTbLFFRYO9BRtoVNSANCsqKCKgiEgHWZ7fH2cu3L3sLrvLzLl7Z7/v14uXd++s93tn78zcc56ZOeeruv+nEkfs3pdDdl3+nbpel3p+p26wFq1aNuw79bC9+vL9PZK216TprNe1A4Wpy9bt0p7PSoZu2HyjtQGY8nlYp6f/9y4nHLBTvfMKpi+cTbcVtpOa97kDNujDpau6zy2Yu0Lba1pd+9wHYzivX8P2uWP69eXwvknba1rS9kpG2VivQ3umz2n4MBh1OXrHvhy2fZI3pRFtvXcb1tYDmDZ3Lt06FH1/t2/P9Lklx+V5c+nWvgPT5s6lpRkdVlutwVf5HjGgjnZlpxX3gVnzFrJg0dc8OzYUDIeOfo+Dd+nToEyA6fPnsH67omNzuw5Mn788q33rNvTuvBb37n80AGu3bcfNex/CD599oMGTucVqC8XcLr/7w4Hsf/weAFx42LV0WrM9Z11/Ahce+ifm1NFnHXTuQXRaswN/PrNhk8YdvmdfDh6QbCeTkr5jcrPPOp3b8/mX1detd3L8+mRGcvwa+R4n7Ldjja+dFHhvrCX6ZGBrd682m62Z/RF4E1DRV0REGueBoaN5YOjo6LljZkylZ6cubNS+E9Pmz+G7m2zJGcMerfY7PTp2YdLscEvjwI02Xfa4vv797Bj+/WzoauzWtyc/2Gc7ho54lz6bdmPu/MXVbi8s6NKhLV/OWUCHNVbj0L378qu/1L+w9/DDo3j44VH1/v1XX/2AHxx2w7KfH3/s7AYXfAHGffkpPdp3ZcM1OjN9wWy+s9HWnP1q9dnmn57yLgd278OQSWPo0qYtPTusyeR5s+qdcfdrY7j7tfC3/GavngzauS+Pj3+Xvhuux5yFi1e43W+NNq1p16YNn8+dR8sWxjd792TkR/UfD3Dwi2MY/GLI232rnhy5R1+eGvUu2/RYj7kLF9d6G+oB22/BkyMbdxvqm7OmsHG7rmzQtjPTF85h//W34bxR96/wez3ar0XH1qsz5suGT/BXbPysT9m4/ZpssEZnPlswhwM27MMv/zdkhd/r2X4tOrZpy+iZq5b35ldT6N5uzeXrt8E2nF+yflMXzGLntTblkU/eoGf7tWnTslUmBV+Aff6y/GrUN/7yEetu36lRBV8Ix5MeHbuwYftOTC8cT4anezxpiO47tePVm2awtMpZusT5/L2FbPXdVahW1mHBtAWsvu7qmBlzJ85l6ZKldY4BvKo6r218MHoJPfq0ZO6XS5kxZSld1mvcMDjucN3Vq7NR96UcfNjXNf7OZ9ONyy9pyy/OX8AGG63aVXnjvpxS/Vi54db84vXqx8pnpr7LdzbswwMfhWNlj/ZdmTyv4dtK7P177MxP6dGhCxu2CydzDuy+FWe9/HC131l79XZ8vjDsz/ts0GuFCafq6+3Zn7DRGmvRrW0XPl84m3279eWiMdUnt+nUeg1mf70Axzm+5548OuV/jVsxwue2/G85m29vuDXnvP7ACr/Xs/2adGrdltEzP2l0Vn3sdcPWyx6P+etHrNO/Y2YFX4ARX4znoA12Z9jno9iiw8bMX7KgwUM7VPtO3bonR+zRl6dGrvw7df/tt+CpBn6n3v/8GO5/Pml7bduTwwdux39ee5c+m9Tc9vps1lw26daVzu3bMmvuAnbeamMmTm34tjl+1qfhOy7Z5769QR/OGVnHPreK3+Fjv6i+z3134y0586VHqv1O6T73QQP3ubveGMNdb4S/5Z6b9OTY7fvy2Nvvst366zFn0eLUb6G/+/Ux3P16UVtvp6K23qJ6tPV69WTkxw0b+3ns9Gn06NyZDTt2ZPrcuRzYewvOeqp6Qf7ZDz/g0K224o1pUzmgV29emdzwK4kH/3cMg/9b1K7cPWlXblz7PjD8zQ/ZcbONeG3CZHbu3Z0PpjV8u1yhfdJzS854YXn7ZM7Xi+l/7/XLfr53/6O47PXnG1zwrTEro7ZQzO3y0Zuf49Gbw3AJa2/YlQvvOpWrTrmJKR/UPJEuwP7H7c72e/fhvIOuwhs4yPR9w8Zw37CwbgP69OSIvfryn9ffZZue6zF3wYrbyWez5tKz25rLj19bdmfitJk1vfTKLAXWB0pnEO2WLMuUir4iIs1E105rcOsVx9CubRuWunPEt/tz9C9uY/6CxVx93sH8/h9DmfHlPA7bvx+DDtqRrp3bcceVx/HK6In8/h8Nm5m4yp2LXnmGO/Y7jJZm3DdhHBNmfcHZ/QYwdsY0npn8Psdv2Y8B6/fg66VVzF68iLNfaPytTy+NmciufXsy5KqTWLh4Cb+7efkMznf+7hiOvfAuAM4+Zi96dQ9nbW95aASTp9W/MFqsS5d2/P1vx7PGGqvh7hx66A6ceNLNzJ+/mCsuP4yrr3lypVcC11eVO7954ylu3eMoWloL/j1xNO/PnsGZW3+TcTM/5bmpE3hx+ocMWG8Tntzvx1S584exz1S7AqUhhk+YyB69ezD0zBNZ+PUSfvXQ8s/+wZ8M4uC//4u2rVvz16MPok3LMMnUa5Mmc+//xjYq78W3JjJg6x48dtGJLFy8hIv+tTxv8C8HccSVy2cY/1a/3pz69wdrepmVqvKlXD7+cf62y3G0tBY8NHkUH8z9nJ9tPpC3Zk1h2PTQ8T1g/W14akrjJwkqzrts7BPctOuxtDDjwY/e4P05n3PaFnvx5qxPeX5ayPv2hn144pN08q548zH+tvPxtFi2fp/xs94DefOrTxk+/R2ueespLtr2exyzya64OxeNXrGwUl8jr53EF2/NZfGcJTz9kzfZ/PD1WLokNL57fGutVV6fYlXuXDTiGe74VvXjyc/7DWBc0fFkt249WLK0iq8WL+IXLzb+eDL8mulMe3MBC2dXcd8PJ7HdkV2XrdsW+3ei80Zt2KBfWx4+azJm0GvfjnTZeLVGZb1zw3vMens2S+Ys4dXTRrLxDzbEk6xu+6zHjNdn8tmLn2MtjRZtWrDF6b2XTezWGIP/sJCJY6uYP9u58th5DDymDUuTC3B3+k5r9jyqDUP+uIjrfzofB/Y7sQ3tOjUu763xLXn+6db06FnF6aesAcBxJy/i889CEfnb3/2ae+9sw+zZxl+vCxMMtmwJ1/6tcUM8VLnz29FPcvNug2hpxpCPRvP+nM85Y8s9GT/rU56b+h4vTv+A3dbZlMf3+SlVvpQrxzfuWBl//3Yu+d9Qbt/zSFpYC+7/cAwTZs/grG32YNzMqTw7ZQInbL4je2/Qi6qlS5m1eCHnjGjc3QpVvpSr336E67Y/iRZmPDblf0yc9xk/2mwf3vlqCi9+/jb9u27Cz3rthwOjv5zIVW89vNLXrWvdLh3zBDfvdgwtMB5IPrfTt9yT8V9+yvPT3gOSv2UKx+Y3rpvIzOTY9dxPx9PrsG4srQr73Mb7pnvsAjhvy+PYttOmdGrdnrt2uYQ7Jz1JKwtXzj8+9WVem/kWO3bdkn/udAGLqhZzzburNjzAi29OZMBWPXj0ovAdfvFdRd+p5w7iiD9U/049rZHfqQAvjZ3Ibtv05KErQtvrN7cub3v96+JjGPSbu5gxax43PTKCm849nCVVS5n6xexqv1dfhX3uxm8k+9zHb/BBDfvcARv04clUvsOdi//3NHcMPJIWZtz/wVgmfDWDn2+7O+O+mMozU97nhC12YJ8NelHlS5m1aCH/90rj7xAa9uFE9ty0B8+dciILlizh3CeWf26PnDCIg24Ln9sv99ydg7banLatW/Pfn/2Q+8aM588vjWhw3vAJE9mjVw+GnpG09R6upa131EG0aZW09SY2vK1X5c4lw57n9u8fGv6Ob41nwswvOGuXXRk3fRrPTvyQwW+O54/7HcBzx5/EVwsXcsaTqzYUwotvhX3gsQuTduXdRfvAOYM44qrwt7z2kRe57Jj9OeeQb/Ll3AXVfq8h63fRiKe5Y9/DQ/vk/XFMmDWDn283gHFfhPZJWmK3hSDudjno3IPo0LU9p11zbFjfqqWcsedvAfjt/Wdx7em3MXPaLE7/03FMn/wFf3r61wC89OhI7r7y0Vpftzb/HT+RAdv04OFLw3Zyye3L1+2eCwZx1KX/YsZX87jxsRHc8n+HhePXzDlcfFvDj1/AWcCzZjYBKJyR6g5sBpzWmBdsCGtodVxERJquXY+4JtpBfcp+VbGiWG9Y3HOU7aYsXvkvpWjyTxo/eVFDtRxf+yzeWVgtuwsuV+D7RgwDllRlOxFgqdat4u1z+270XrQsgH+P2j5a1o93HhYtC+CD+etEy9qvS+Nnq2+M7Var3xAyaTnwtZ9Ey2rZIvsxaostXJDt8CDF1unauMmmGuur+atHzdu/Z+bz4izz1lfrRcsCmP7vjaNltZoft06w4KDGTV7XWPPnNu5kXWO0/CTuPtCqcef9G2Vxl7jbSYcP4423/VW/uP0BPO5Y4q0+y2aoqJpsdnnc9slnR24TNW/UP35e54dnZi2Anag+kdvr7p55415X+oqIiIiIiIiIiIikzN2XAitc/mxm7d093QG8S8S9REVERERERERERESkeXsr6wBd6SsiIiIiIiIiIiKSIjM7u7ZFQPus83Wlr4iIiIiIiIiIiEi6Lge6AB1K/rUnQk1WV/qKiIiIiIiIiIiIpGsU8JC7jyxdYGY/zDpcRV8RERERERERERGRdJ0IfFHLsh2yDlfRV0RERERERERERCRF7v4ugJmt7u4LSxZXZZ2vMX1FREREREREREREsvG6me1S+MHMDgVezjpUV/qKiIiIiIiIiIiIZONo4FYzGwasD6wJDMw6VEVfERERERERERERkQy4+zgzuwy4E5gD7OHun2Sdq6KviIiIiIiIiIiISAbM7BZgU2BboDfwmJld7+5/yTJXY/qKiIiIiIiIiIiIZGMssJe7T3T3/wA7A/2zDlXRV0RERERERERERCRlZtYS+Km7e+E5d//K3U/OOltFXxEREREREREREZGUuXsV8K6ZdY+drTF9RURERERERERERLLRBXjTzF4D5hWedPeDsgxV0VdEREREREREREQkGxeWI1RFXxEREREREREREZEMuPvwcuSq6CsiIiIiIiIiIiKSIjP7r7sPMLM5gBcvAtzdO2aZr6KviIiIiIiIiIiISIrcfUDy3w7lyG9RjlARERERERERERERyYaKviIiIiIiIiIiIiI5oqKviIiIiIiIiIiISI6o6CsiIiIiIiIiIiKSIyr6ioiIiIiIiIiIiOSIir4iIiIiIiIiIiIiOaKir4iIiIiIiIiIiEiOqOgrIiIiIiIiIiIikiMq+oqIiIiIiIiIiIjkiIq+IiIiIiIiIiIiIjmioq+IiIiIiIiIiIhIjqjoKyIiIiIiIiIiIpIjKvqKiIiIiIiIiIiI5IiKviIiIiIiIiIiIiI5Yu5e7vcgIiJlZmanuPuNecuKnZfndYudp3WrzLw8r1vsPK2b8ppaVuw8rZvymlpW7Lw8r1vsPK2b8ppaViy60ldERABOyWlW7Lw8r1vsPK1bZebled1i52ndlNfUsmLnad2U19SyYufled1i52ndlNfUsqJQ0VdEREREREREREQkR1T0FREREREREREREckRFX1FRAQg5thFscdJ0rpVZp7WrTLz8rxusfO0bspralmx87RuymtqWbHz8rxusfO0bsprallRaCI3ERERERERERERkRzRlb4iIiIiIiIiIiIiOaKir4iIiIiIiIiIiEiOqOgrIiLSxJlZxzqWdY/5XqTpaq7biZm1Kvd7EBERESmm9ok0BSr6iog0I821KJQDwwoPzOzZkmUPxX0rYGZnxc6MxcyuruCsYUWvXdbtxMxeSvn1/lv0+M6Sxa+lmVWP9/JxzLw8y0OHuCl9r+bh7ynZiv39bWaHRs5bP2aepMPMdo6YVdHtk6bynVOOtlDs7zgzGxwzLysq+oqINC/DCg+aQFEo9caCmf2y6PFhJcsuTztvJe8lzUalFT3uWseyWM5O88XM7Nqix2eWLLstzax6OLyCs5rSdpJ2x6Nd0eOtS5bFXrdM8sxsYNHjniXLDskis5b3Uekd4tjHk2FFr5/592rMv6eZbVH0eLWSZbukmZW85n1Fj/9QsmxoylnHFD3erWTZaWlmJa/ZVNonqX5/18OfIueNiBWU9rGyHnnRimxlKOjdHzGr0tsnw5a9eHn7clm1hZrMSX7gG5HzMqGir4hI89KUikJZ5B1Z9Pj8kmX7Z5BXlzQblV7L45p+jiHtz26PosfHlyzbNuWslYm5H6Sd1ZS2k7Tz6nq9Sl+3guIrv4eULLsgo8yaVHqHOPbxJPb3asy/591Fj18pWfbXlLMAehU93rdk2dopZxUXP68vWXZSylnQdNoneWjrNZW82HfIVXL7pCnlVXr7pKn05bJqCzWlk/y5oFuARESalzwXhaB6Y6C0YRC7oZDm+q1jZmcT1qHwmOTntDvC9ZH2Z1fX55Y6MyttJBdnp5ofM4vI20kdV58a0DbluM5mdjDhgoXORdkGdEo5i6K/3QqLgPZp5xW9dk2Pa/o5S3nqEMf4u8X+Xo3594y9TeZ53fK6fzfnPK1bE83Lc/uEiN85ZWoLRW0zmFn/2hYBrdPOKwcVfUVEmpfYRaHYjYWone+IjcqbgA41PAa4OcWcZcxsDjX/zbJoMLcwsy6EBnPhcaET3DLlLICRhHWrqaO9uIKzYm8n361j2WMpZw0HDip6XJz9QspZUP1vV+q6DPIgbkcuzx3i2MeT2CflYv49Yxe01zCzfoR1a5s8LpwgS3u7LGexPuv9O+b3N2Y2ro68dTPIu76OvM4pZ8U8VkZtN8duo5vZo9T+ua2Zclye2ycxv3PK0RaK3Wa4po5l72SQF525l+OuUBERKQczu7iu5e7+mwrPqwLmsbwxPr+wCFjd3VM9Y2tm/6xrubufmGbeypjZ+e5+ReTMLu7+5Sq+xiRgKTUXRt3dN1mV128sM9va3d/MYVbU7cTMjnf32/OWleSl9rc0s1mEDqIBu7O8s2jAAHfvkkZOkhXt2BX7OBn7eFKG77mYn91nwL2Ev+URyWOSnw9391QLemb2fF3L3X2vFLPmA+8T1mXT5DHJz5u4e7va/t9G5kVtn9TzPa3y93fyOhvXtdzdP1rVjJK80mFbSvNS+w4ow/Er2vGkDMeub64kb3iaefVRie2T2J9bfaTcFmpSfasCM9vX3Z8uR/aqUtFXRERWUIaiUOy8VDo6DciL0qg0s1HuXtttShWfGbMwmuTFXLdcZsXOq+R1U4c4esE+9vGk4k62xCyuNUQane/Yhcr6itk+KcPx8hV3jzYxkpld7+6nR8qq2BOOTSkryRvi7odGyspz+yTmNlKO/kfsfS76OqZFE7mJiEhNDlv5r1R0Xulst1k7c+W/kopyTHAQM7N0Ft+s5XXSlDxP0FKx6+buw+v6tyzQrHSStyzFOnbFzoL4x5PY33Or/Pd099vr+lf4veR2+5j+sKov4O4f1fWv8HtmVjqBXdZitk9iHy9Xj5y3W8Ss2MevmMeT2MeumHd35bl9EvNzK0f/I/Y+V7GTyKnoKyIiNanYwkkzzyvH7TsxMyt5Mr7mmhU7L8/rVqAOsfKaWl7M4hrEXbfYhUpN6laZ8rx/q+1VeVmQ72MJ5Hu7TJWKviIiUpO8dwTymlexZ6HrqWIbXE2MOqeVmwf57aTm9bjcXPJi0nYpTU2et5M8b5N5bp/k+aIMyPd2mSoVfUVEpCbNoXASU6z1uz9STrE8f3aLc5oVezt5KadZUJ59LqY8d4hj0/eqNDV53ybzfPzSuqUjz+2TmH/H5tD/mBQ5LzUq+oqISE1if3nHzovdUFilhp6ZrVXy8zFm9mczO8XMlq2Lu1++KjklGV3r+lf0q3unlVkPqRZGzWw3M2uXPD7GzP5YPLmPu++SQkb/uv6lnHVw4bMxs7XN7A4zG2dmg81sw6KsVLYTCw43s8OSx3sn2+XPzGxZG9PdT6ukrCQv+j7XAOoQpyPmiRbI98mWPHe+K67g1US/vwGOTfPFir9Da3FdmnkrUZEnHM2spZn9PEZWA5ybxYua2XOlz6XVZoidFetzi92ubKDU9jkz62hmm9bw/LaFx+5+SFp5sZm7rooWEWkukslWaj3wu/sZFZ7Xta7l7j6z8HuFxynldgIuAXZPnhoO/Nbdv0rp9ZfNGGtmFyQ5dwMHAp+4+8oafo3JnEj47GrqgLq7pz6uqJntBox293lmdgzQH7guq1nUzWws0BfYFrgNuBk43N2/mWLG83UsdncfmGLWW+6+VfJ4MDCC0OjfBxjk7vumlZVk/BVYB2gDzAZWAx4BvgNMd/fUJtmImZXkRd/nGvDevuXuQ1N6rTuB0wrHquSkx63unnoxKFbWygpB7j4qzbyVvJeL3P23Gb12Z+A4oAfQqvB82t+rSVb/uv5uZnaCu9+WUlZHYG13/6Dk+W3dfWwaGQ18P33cfXwKrxOtfRL7+9vM5lBzW8+SvI5p5hXlPg+sB/wbGJzG51RHVrT9rY73kMnxxMxec/ed0n7dGnLGUfd2sm0NyxqbVXqsMKA38C4hrCKzSnIz/9xitytLsjPtWxXlHA5cC3wGtAZOcPfXk2XL2oKVTEVfEZFmxMyOr2t58WzcFZoXvVCZ5A4BxgOF9TkW6JvWWWEze8Pd+yWPRwG7J4XR1sAod98mjZxyi1GELckb5e79zewiYIq735J2A8/MWrv712m93kqy3nX3zZPHI919+6Jlo919u5Tzxrn7Nsl2OA3o5u6LzawVYbtMs1MVLSvJi77PxewQF2X+GPg5cDawAXAO8At3f7RSs2KeaKnHe/nY3btn9NovEzrg44ClhefT/l5NsqIU12J2vmMXKsvVPsk7M1sPOBw4AuhI2D4vzSAn2v5Wx3vI5HhiZn8i7G+DgXmF59M+QWZFd1LVJM0T/Gb2COEE8aXAAsJ+9yIwoJKzSnIz/9xitytLsjPtWxXljAYOcPepZrYTcAdwvrs/WNwWrGStVv4rIiKSI/OBR919YR7z3L1njJwabOruhxb9/JukEZGWtmbWjzAsU0t3nwfg7l+bWVWKOStlZr2Bc9z9Rxm8/BJ3dzP7HnBDUoQ9OYOcgjlmdj5wDLCHhWECWqecMSXpENwNPO/Znm0fZma/Ba5IHh+cNFr3AlK9MiKxBJZth6+7++Lk5yVmtrTu/7VJZ0F59rkDM3rdWrn7P8zsTeB5YAbQz92nVXjWt2KdaAEws9m1LQLaZhi9urufneHrL+PuexUV1/6RXI2bRXHtV8D2RZ3vO83sfHd/kJSHWXD3Dmm+Xj3yorVPzGwdwt9yM2As8Ht3r207TSPvccJ33EOFY2UsyTHkz8mJiV8CFxGKb2mLsr+V6XhSKNwVX0XsQKonyGorfiZtr6OA1Iqj7n6QmR0M3Ahc7e6PmNnXWRRgY2aViPG5xW5XFsu6b1XQ0t2nArj7a8m6PWZmG5GTyeI0pq+ISPNyNPCxmd1pZt82s5Y5y6uRmfU2s5syjFhgZgOK8nYjnO1Py1Tgj8DVwEwz65bkrElSDEubmW1rZkPNbLyZXWpm3ZKz7s8Bb2WRSfUi7OMZFWGLHQEsAk5OOo4bAlelnLEl8DpwITDZzK4zs1Uev7cWpxGuQHoXOAwYklzN9iNSHksxMc3M2gO4+/6FJ5PiUNrjpcbMgjLsc+7+UU3/gMkkVwylzcyOBW4l3LZ8G/CEmfWt8KwpZnazmQ00s1QLhbWYBfRyT9j+MgAAGqFJREFU944l/zoQtqOs3GlmP0qOzTWN15oqd5/m7n8GfgKMJhTX0lat8w3sBVxgZmeQcufbzB43s0GWjOueNTNbx8yuNbPHzOzypHCelTsIV/5dD3QA/pxhFoRi14HAJDO7z8I4oG0yzsTMtjSzS5K7JK4HXiZ8j2ch1v4W9XiStMsfcfe9Sv6lfkeEhXFTzzezG8zsWxacDnxIOKGUquRk0QHAnmb2MGF4qEzEzIKon1vsdmWxrPtWBXOsaDzf5DtoT+B7wNYZ5EWn4R1ERJqZpKNxMHAk4Szxw8A97j680vMsDLh/NbA+8BDwF+AGYGfgGnf/U9qZSW5fQierU/LUl8DxnvH4g0mjbzV3n5/Ba78K/A14BdifcNXQ7cBFWV25nRTwjgZed/cXzaw7sKe735FRXjtgobtXJVcwbwE8mdVVgma2PqHRfCRhfNp73f3XGWV1Alq5+xdZvP5KstsB7dz9szxlJXlZ7nMdgVMJQx88AjxN6HD9Ahjj7t/LIPMh4JTC3y+5uvLGLG7ZjJWVFOZ/QNjPegFDCN85I9LMKcq7lND5fq2GZX9w96wmJToVuIxQJCp06DIZJsDMtiScJDsU+IJwO/GQtPc7C7fQH+tF4/maWQfC9/kAd18txazvEbaRfQhXn98DPF64iyBtZvYUMBJ4gVAg7eDuJ2SUNcbd+xb9HGVcSjNbA/gu4e/6DeBJ4G53fzqjvFeAe4H73f3TLDKKsqLsb+U4nli8MX0fJrSPXyFMIrgO4QrmM909iys4i7P7At9w979nmRMzK9bnVpQXtV0Zq2+V5Mx39wklz7cmDDH3rzTzykFFXxGRZqyoc/wzoKu7b1TJebELlWbW3d0/Lvq5I0CWt1HGYiVjdZnZh1kUE0oyYxdhRxImiOhCmAX4dWCxuw/KIi/JbA8cQhjXtJu7r5tVllSWcnaIS95Hm6wKX7GzYp5oic3MPgR2cvcZEbKiFNfK0fmOVaiMWYg1szGEK9UKV7o/X/yzpziRbR3vYVtC+2tbd0/1Lq/StlcMMfe32CzemL7jPBkPPzmBOhXontWFBHkX63OLLc99q3JR0VdEpJkysy6EAuxRhKuh/u0ZzkgfIy92obK402ZmQ0rGnqpoZvYO4bMqdBr/RbgKt9BpTL1RGbsIa8sncjsdaOvuV5Z2zFPKWZ1QVDgK2BV4ilBAedrdo47JLE1XOTrEybZ5MuEWxtULz7v7SZWcVZKb6YkWM6uzcJdVB9zMhgLfz+Kq86KM6MW1csq4UBmtEGtmkwi3ZMee1HZdwm36RwLdgPsIV9mPSTknetsrxv6W5EQ/ntjyyS8LhaHCZIapDhVQeqIj1hXoeRXrc4st9v5tkSf1LAdN5CYi0owknd+DCcWnfoRbiH8HDPMMzgLGzgNWtzD5UqGjs6j45wway8UdqrzNvD2NMKZpTT+nPsFHwtx9voXJ2/5aKMJmkLMsz8y+AQwiFKMg5fkOzOxuwu3Dw0kK57qqRWqx7Ir25Gr3TyJsK3cC7wD7ESaDGQS8XelZtZxoOY8wZEbarqljWVbHSghXdo1OOv6LlgW6n5FixkNArjvftRQqT0g7h3CL8kiqtxsKbRInxTaEu/dI67Xqw8x+RNjXNgceIEz2+nKWkUWPY7W9YuxvEPF4YmaFiekeS167+O+aRRu9r4WJ6go5bYt+zkVxLYYyfG6xRd2/PfKknuWgoq+ISPMyidD5/Svwn6xumy9jXuxCpdfyODMWJjXo5e7/NLO1gfbuPjHtHHffM+3XrIfMi7AlzgLOBx509zfNbBPC1Vdpegr4sbvPKTyRDGNxCHCku38n5bxCRpTtpBx5OV63cnSIN3P3w8zse+5+e3KS4sUMcqJlxT7R4u57ZfXaK/FQ8i9Lue18xy5UxizEluFq0W8AVwDPuvvSlF+7JtHbXsTZ32IfTwr72+bAjoQ5N4xwwmyFMYVXVdpXz9dXDtsnUT+3goh/x6j7t5k9DtwNPOTu81b2+5VIwzuIiDQjZtbW3ReYWWfCEAsA77n7V3nIi83MqghXfxjQFijc9pdJkcbMLgZ2ADZ3997JeJX3u/tuaeYkWTsCk919WvLzcYRJfD4CLsliTEAz+yZh0qqX3P0PSRH2rAyupCnNXSPCLZttgO8QhsjYjzC51APu/mgGWdG2k9h5eV63crBkIhgze4Ew1vo04LUsbv+OlZUcqx6MfaKlhvexL/BLd9835deNNuRCyW22md+KHbPzbWa3EiZvi1KojFmILbrtu1pEUVbqV59bmLPhaMJY/BCu4r/HM5j0KWbbq6kMcZLV8SR57ReA7xSOmRYmT3zc3fdIOWd14CfAZsBY4FZ3X5JmRg2ZeW6fRPnckteO+XeM3beKOqlnOehKXxGR5qXKzP4JfJ9wFa4BG5vZg8BPMviCi5oXu1BZhqsWDiYMkzEqyf80aeRl4R+EBhBmtgfwe+B0YDvgRsL4zKly9+HAcAsT6+DuHwKZFXyTq4pvAdoD3S1MIvRjd/9ZihnfIlxN9i1CY/IOYEd3PzGtjBrE3E5i5+V23crRIQZutDDe+oWE4XfaAxdVcpa73wG1nmhJfTZ1MxuYvO76hCsB/wD8k/B9d1naecQdcqH46vPCleeQ3dXnNxI639cmhcvMOt/uflJSqDzVzDIvVFLzbfvFV1+lWYg9l9AWmgpgZscT2kKTgEtSzCF5/S2B54D/AG8Qto8dgV+Z2UB3fyfNvMhtr9hDnMQ+ngCsCxTvY4uT59J2O2EYoxeBbxPGdz8zg5xieW6fxPrcIOK6xe5bufvDwMO2fFLP44C/mVkmk3qWg4q+IiLNy4VAG8LkQMVnhv+SLLuwwvOiFyojW+zubmYOy65ey0rLoiL5EcCN7j4EGGJmo7MIjFGELXEtoRj0CIC7j0m2mzQ9RejgDCjcBmdm16WcUSrmdhI7L8/rFr1D7O43Jw+Hk/Ht+7GyynCi5RrgFOAV4IDkv+e5+w0Z5UUbciHPne/YhUriFmL/TvW20BVk2xb6HXCmu99X/KSZHUooVFbyJLexxw+OfTyBcIx8LbkgA8KFGrdlkLOVL5+s9BYyHIqgSJ7bJ7E+N4i/btEld/wNBgbb8kk9jwPKMixJmlT0FRFpXg4Gdiq+ld3d55jZz4ARpF+EjZ0XvVAZ2X1m9g+gs4XxCE8Cbsooq6WZtUquNNyb0AkpyKr9EKMIW427TzarNsF5VcoR/QlXrj1jZh8C95J9AzLmdhI7L8/rFr1DbGHoneOAHhTt11kMqRIxK/aJFnf3Ycnjh8xsSsYFmnKMZxpVpM537EJlzEJs7LbQNu6+wvt39yFmdnkGeTHF3t9iH09w98uSEyu7J0+d6O5vZBBVPFnpkpK2V1Zy2z6J+LlB/LZXdBZvUs/oVPQVEWlelnoNY5e6+9zC2dsKzytHoTIad7/awrhuswkTOFyU4W1H9xCGWpgBLCCZcMnMNgMyG5M5QhG22GQz2xVwM2tNuKry7TQD3H00MBo4L8k6CmidNNQfdPcb08xLMmNuJ1Hz8rxulKdD/AThBNw4IOtxTWNlxT7R0tnMDin6uVXxz+7+QMp5sYdciC5S5zt2oTJmITZ2W6iu8ZcrfWKk2Ptb7ONJ4XVHkdy6n6G+JX+/zCcrzXP7JMmM8bmVZd1isciTepaDJnITEWlGzGwMsCfVb1creN7d+1Z43q8Jt0XPALoD/ZPbkTYDbvecTL4Ui5ntQuhwD/VkUh0z602YsTf1RqaZ/Rv4I3ADsDOhCLuDux+ZdlaStxZwHeHqKwOGEq78ymI8x+LcFoSO+FHuflKWWVI5bPnkJVB9ApPMOsQWYXKucmQVZRZOtBwKjCGDEy0Wxq2vjWsfr78aOt/3ZNX5rmt7zGJbNbPxwHbJCZ13gFPc/YXCMnfvk2JW1LaQmX1C+O5eYRFhMtaN0szLMx1PROKyyJN6loOKviIizYiZTSJcYVVTEdY9/VnUo+YlmVELlTGZ2RyW317YBmgNzMuoGFQ8qdQ44BbPfpblshRhs5SMTfm1u3+d/Lw5oTP+UVZX7MTcTmLn5XndysHMfg7MBR4DFhWe95QnvYydVUN2WU60mNm67j49Vl6li9n5jl2oLEMhNlpbyMwurmu5u/8mzbzmSseThstz+ySmPK8bgIVJPY8GYkzqGV3F3+oqIiL15+498pyXFCp3IRQq1zGzW9x9ibu/F/N9ZMXdl82Ua+He7+8R1jcLxZNKHQBsRfaTSs0ABmWZUczM1gZ+xIpjjKZZFHoKOBmYkHTuXwH+BRxoZju6+/kpZgHRt5OoeXletzJZDFwF/JrlHTonmwmLomSt5ERL5gXfZOziQwkdyC2B9bPOzAt3PynpfJ9qZll3vm8Capt9/uZanm+0ZPzNZ1leiC3sAy0IY/umnTeihucyaQupqJsdHU9WTZ7bJzHled0s/qSe0elKXxGRZsTMute13N0/rvC8wVQvVH7k7pkWKsvNzN5w934ZvO44Xz6pVCvgtaxvzY5UhC3Oe5mwrYykaOzgZJzFtDKK/46/A7q6+6lm1gYYWViWtay2k6aQl+d1y1oy5u1OyQmXXGSZ2QvAye5eONHyGuFEy1aE41jqJ1rMrC2hE3w00I9QTPw+8EJebxfNQi2d737AvkAuOt95ZGYX1bHY3f130d5MDuh4kq08t09iysu6JUPL3ec1T+p5tLunPalndLrSV0SkeXmccGVV8XALDqwNrEP6k93EztuqqMB2C6Gznxslk3u0AHYAFmYUV45JpR4mFGGfIdsJ3ArWcPdzM84oPrs+kHClI+6+2Mwy6bxF3k6i5uV53crkfcK4wXnK6uLuE5LHxxOuEj29cKIFSLXoa2Z3E2ZPHwpcTyhavu/uw9LMaSZ+RxjSp6bO92WEKx5ToUJlqmqarK0d4S6XNQmfq9SDjifpynP7JKY8rxvxJ/WMTkVfEZFmpPSqQjPrAZxLGEM19S+22HmUp1AZ03eLHi8BJhGuBslC9FmWiVOELfaYmX3b3Z/IMGOsmV0NfEoYdmQoLLtlMysxt5PYeXlet3KYB4w2s+epPs7uGRWcFftEy1bAl4RhCN529yoz062UjROz861CZUrc/ZrCYzPrQBgK6kTgXuCa2v4/qZGOJ+nKc/skpjyvW03fBfVZVjE0vIOISDNkZr0I4yruTGiQ314Y/7CS88ysiuVf0Aa0JVxZlmWhUlJiZpcCL2dchC3Om0Po5C8inDBIfTtJbtM8kzBkxV3ALMIVj/2BTd39zrSyRBrKzI6v6Xl3v71Ss8zsLmAa4UTLuUBPd5+fnGgZ7u5908xLMrcAjgKOIEzUtTnQR5MuNYyZjaptGKG6lqWQWyhUngzcB1zj7p9lkZVXZtYVOJswLv/twHXu/mV531Vl0vFEJJ7Yk3qWg4q+IiLNiJn1IRRftwauJNz2mtlt9LHz8srMrqf61WvVZHRVXnQxirBFWS2Ab7j7S2m/dklOK8JV7ScBHxHWaSPgNuBXaZ78iL2dxMzL87o1ZWY2JNZ4dmlllftEi5ltTyjYHA584u67ZpmXJ7E73ypUpsPMrgIOAW4E/uLuc8v8lnJDx5PGyXP7JKY8r1uBmV1c1/I8TFSp4R1ERJqXMcBkwli7OwE7FQ+BkMGXd+y8vPpf0ePfAHU2UCpRUoTdP+sibIG7LzWzGwiTpGTpKqA94WrDOQBm1hG4Oll2VopZsbeTmHl5XrembJMKzPoa6Ar8gDADd7UTLSll1MrdRwIjzewcwticUn83ESatqsnNaQaVFCq3UaFylfyCcLL2AuDXRe083WW1inQ8abQ8t09iyvO6Afko6q6MrvQVEWlGaru9tiCD22yj5jUHeZkttyax1y0Za/cV4AHPqEFkZhOA3qWvb2YtgXfcvVdGubH/lrmdDTvP+9zKZHlLfVZZZvYnwomWs2s40TLf3dM80VIoHr7v7v8oef7HhJM956WZJ+lIxndeRBifsvj4rEKllI2OJ+nLc/skpryuW3OY1FNX+oqINC/rA0+5+xs5zWsO8ny29tlklvbMirAlfky4tbfKzBaQTWffa1qXCJOzxN5OYubled1k1R1IyYkWd59tZj8F3iHdq+shTBb3yxqevwkYC6hIU08xO9/u3iKt1xJJkY4n6ctz+ySmvK5b7if1VNFXRKR5+RA408z6EoZeeBIYmuEYdrHzpLLFKMIu4+613UacprfM7Dh3v6P4STM7hlCAEmnKbOW/0uSyYp9oWa2WvKVWPJ6R1EfuO98iK6HjiUhE7n5N4XHRpJ4nAvcSJh+veCr6iog0I+4+GBgMYGb9gP2BB5JbzZ8hXJX7WqXm5VUywVmhE7CGmc0uLCJHt6FGKsIuk3SgBhFumfydmW0EdEt5mzyVsM2fBIxMntsBaAscnGJO9O0kZl6e160czOxc4Op6TKx5biVlJWKfaFlgZr3cfUJJXi9gQQZ5udUcOt8iK6HjSQry3D6JKc/rVqyGST375+kCJY3pKyIihfEO9wX2c/dT8pYnlSFSEbY472/AUmCgu29pZl0IV6LvmEHWQGDr5Me33P3ZtDNE6iuZxHAAcGrWkyfGzEryNgAeIBRIVjjR4u5TUs47ALgeuLQk73zgLHd/Is28vKuh831dnjrfInXR8UQkrpJJPf+Sx0k9VfQVEWlGzOyQupa7+wOVnCeVLWYRNskb5e79iyenMLMx7t43izyRpsTM+gM3AG8DhX0PAHcfValZRZnRTrSYWR/gHKBP8tSbwFXuPi6rzDxqDp1vkZXR8UQknuYwqaeKviIizYiZ/bOOxe7uJ1VynlS22EVYM3sV2BV4Pcldm1Bkzt3sxCI1MbM9gSHAOJZ3dtzdB1ZyllSm5tD5FhERiUlj+oqINCPufmJty8zs0ErPk4r3dTLeswMkRdildf8vq+TPwIPAOmZ2GfAD4IIM80SaBDNbhzBG6iaEK+vH5CGrHMzskbqWu/tBsd5LpXP3FuV+DyLlpOOJiKRNV/qKiAgAZvaxu3fPa540fWY2CDgC6E8Yy/EHwAXufn+GmVsAexOuJHvW3d/OKkukqTCzicAVwN2EYizAu+6+qJKzysHMPgcmA/cArxKOJcu4+/ByvC8RqTw6nohI2lT0FRERAMxssrtvlNc8qQwxirDJREG1cveZaWeKNCXJ1be/Ao4FJhH2t3WB693992a2nbuPrrSsckjuTtgXOArYFngcuMfd3yzrGxORiqPjiYikTUVfEREBdKWvlE/sImxy5aETik/dgS+Tx52Bj929Z5p5Ik2Nmf0ZaAuc7e5zkuc6AlcDVcD+ae0HMbPKzcxWIxRrrgJ+4+43lPktiUiF0vFERNKgoq+ISDNiZsUT6FRbBPR299UqOU8qU7mKsGZ2E/Cguz+R/HwA8H13/3EWeSJNhZm9D/Tyko5AcpXZDOAAdx9RaVnlkhRnvkMo0PQAHgFudfcp5XxfIlJ5dDwRkTRpIjcRkeblVuAlYCbwdQ7zpAIVirq1FWEzjN7F3X9U9D6eNLMrM8wTaSqWlhZhAdy9ysw+T7kIGzMrOjO7A+gDPEG4Gm98md+SiFQoHU9EJG260ldEpBkxs6uBXYEtgHGEguzLwMtZjGMaO08qm5mNc/dtVvZcinn/AV4E7kqeGgTs4e77ZZEn0lSY2UPAA+5+R8nzxwCHufv3KjGrHMxsKTAv+bG4Y2WAu3vH+O9KRCqRjicikjYVfUVEmiEzawPsQCjIfiP5N8vdt8pDnlSm2EXYZCzhi4E9kqdeIFxZoxMSkmtmtgHwALAAGJk8vQNh7N2D07yNOGaWiIiIiCyn4R1ERJqntkBHoFPy71PClbh5yZPKdBShCPtg8vMLyXOZSIq7Z2b1+iJNVVJo3dnMBgJbJ08/4e7PVnKWiIiIiCynK31FRJoRM7uR0OmeA7wKjABGuPuXecgTaQgz6w38H2GilGUnwt19YLnek4iIiIiISBp0pa+ISPPSHVgNmABMAT4BZuUoTypYGYqw9wN/B24GqjLKEBERERERiU5X+oqINDNmZoSrb3dN/vUBZgKvuPvFlZ4nlcvMxhCKsCMpKsK6+8ha/6dVyxvp7ttn8doiIiIiIiLlpKKviEgzZWYbArsRCrEHAmu6e+e85EnliV2ENbNLgM8IYwgvKjyvidxERERERKTSqegrItKMmNkZLL/i9mvg5aJ/49x9aSXnSWWLXYQ1s4k1PO3uvkkWeSIiIiIiIrGo6Csi0oyY2R+Bl4CX3X1q3vKksqkIKyIiIiIikg4VfUVERKRZMrM1gLOB7u5+ipn1AjZ398fK/NZERERERERWSYtyvwERERERCEVYM7vAzG5Mfu5lZgdmGPlPYDFh+BGAKcClGeaJiIiIiIhEoaKviIiINBWxi7CbuvuVhPGmcff5gGWYJyIiIiIiEoWKviIiItJUxC7CLjaztoADmNmmFE0gJyIiIiIiUqlalfsNiIiIiCRiF2EvBp4CNjKzfwG7ASdkmCciIiIiIhKFJnITERGRJsHM9gUuALYChpIUYd19WIaZawK7EK4oHuHuM7LKEhERERERiUVFXxEREWkyYhRhzax/XcvdfVTamSIiIiIiIjGp6CsiIiJlFbsIa2bPE4aQKIwXXK0x5O4D08wTERERERGJTUVfERERKavYRVgz2wmY7O5Tk5+PBw4FJgGXuPvMNPNERERERERiU9FXREREyip2EdbMRgH7uPtMM9sDuBc4HdgO2NLdf5BmnoiIiIiISGwtyv0GREREpNn7O7AIICnCXgHcDnwF3JhBXsuiQvIRwI3uPsTdLwQ2yyBPREREREQkKhV9RUREpNxiF2Fbmlmr5PHewHNFy1rV8PsiIiIiIiIVRR0bERERKbeWZtbK3ZcQirCnFC3Loq1yDzDczGYAC4AXAcxsM8LVxSIiIiIiIhVNRV8REREpt6hFWHe/zMyeBboBQ335BActCGP7ioiIiIiIVDRN5CYiIiJlZ2a7sLwIOy95rjfQ3t1HlfXNiYiIiIiIVBgVfUVERERERERERERyRBO5iYiIiIiIiIiIiOSIir4iIiIiIiIiIiIiOaKir4iIiIiIiIiIiEiOqOgrIiIiIiIiIiIikiMq+oqIiIiIiIiIiIjkyP8DbtwjeLR6PbMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1296x864 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "example_sd_pipeline_dendrogram(df,drr,wli)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}