mlearn

Mathematics of Machine Learning
git clone git://popovic.xyz/mlearn.git
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Analysis of Mystery Machine.ipynb (545512B)

      1 {
      2  "cells": [
      3   {
      4    "cell_type": "code",
      5    "execution_count": 1,
      6    "metadata": {},
      7    "outputs": [],
      8    "source": [
      9     "import numpy as np\n",
     10     "import matplotlib as mpl\n",
     11     "import matplotlib.pyplot as plt\n",
     12     "import pandas as pd\n",
     13     "import seaborn as sn\n",
     14     "import scipy.stats as stats\n",
     15     "\n",
     16     "from scipy.optimize import curve_fit\n",
     17     "\n",
     18     "from sklearn.model_selection import train_test_split\n",
     19     "from sklearn.tree import DecisionTreeClassifier "
     20    ]
     21   },
     22   {
     23    "cell_type": "markdown",
     24    "metadata": {},
     25    "source": [
     26     "Two files will be supplied to you via Moodle. A test and training set 'data_train_db.csv' and 'data_test_db.csv'.\n",
     27     "They were taken by observing a mystery machine. The first entry 'Running' is 1 if the machine worked. It is 0 if it failed to work.\n",
     28     "In the test set, the labels, are set to 2. You should predict them.\n",
     29     "\n",
     30     "\n",
     31     "Let us look at out data first:"
     32    ]
     33   },
     34   {
     35    "cell_type": "code",
     36    "execution_count": 2,
     37    "metadata": {
     38     "scrolled": true
     39    },
     40    "outputs": [
     41     {
     42      "data": {
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     44        "<div>\n",
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     54        "    .dataframe thead th {\n",
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     57        "</style>\n",
     58        "<table border=\"1\" class=\"dataframe\">\n",
     59        "  <thead>\n",
     60        "    <tr style=\"text-align: right;\">\n",
     61        "      <th></th>\n",
     62        "      <th>Running</th>\n",
     63        "      <th>Blue Switch On</th>\n",
     64        "      <th>Battery level</th>\n",
     65        "      <th>Humidity</th>\n",
     66        "      <th>Magnetic field</th>\n",
     67        "      <th>Controller beige</th>\n",
     68        "      <th>Controller bisque</th>\n",
     69        "      <th>Controller black</th>\n",
     70        "      <th>Controller blanchedalmond</th>\n",
     71        "      <th>Time since restart</th>\n",
     72        "      <th>...</th>\n",
     73        "      <th>Waste level right tank</th>\n",
     74        "      <th>Waste level left tank</th>\n",
     75        "      <th>Helium reservoir</th>\n",
     76        "      <th>alpha-radiation</th>\n",
     77        "      <th>Active motion supression</th>\n",
     78        "      <th>Blade density</th>\n",
     79        "      <th>Blade rotation</th>\n",
     80        "      <th>Controller mintcream</th>\n",
     81        "      <th>Controller mistyrose</th>\n",
     82        "      <th>Controller moccasin</th>\n",
     83        "    </tr>\n",
     84        "  </thead>\n",
     85        "  <tbody>\n",
     86        "    <tr>\n",
     87        "      <th>0</th>\n",
     88        "      <td>1.0</td>\n",
     89        "      <td>1.0</td>\n",
     90        "      <td>2.668066</td>\n",
     91        "      <td>2.061727</td>\n",
     92        "      <td>2.549782</td>\n",
     93        "      <td>1.835225</td>\n",
     94        "      <td>2.259989</td>\n",
     95        "      <td>2.686942</td>\n",
     96        "      <td>2.879310</td>\n",
     97        "      <td>9.671808</td>\n",
     98        "      <td>...</td>\n",
     99        "      <td>2.971298</td>\n",
    100        "      <td>0.937030</td>\n",
    101        "      <td>2.074836</td>\n",
    102        "      <td>2.640988</td>\n",
    103        "      <td>0.884307</td>\n",
    104        "      <td>1.861668</td>\n",
    105        "      <td>1.395146</td>\n",
    106        "      <td>2.685994</td>\n",
    107        "      <td>1.246004</td>\n",
    108        "      <td>1.804786</td>\n",
    109        "    </tr>\n",
    110        "    <tr>\n",
    111        "      <th>1</th>\n",
    112        "      <td>1.0</td>\n",
    113        "      <td>1.0</td>\n",
    114        "      <td>2.168779</td>\n",
    115        "      <td>3.064346</td>\n",
    116        "      <td>2.378786</td>\n",
    117        "      <td>1.786132</td>\n",
    118        "      <td>3.317119</td>\n",
    119        "      <td>1.764618</td>\n",
    120        "      <td>3.480051</td>\n",
    121        "      <td>3.649143</td>\n",
    122        "      <td>...</td>\n",
    123        "      <td>1.941678</td>\n",
    124        "      <td>1.072903</td>\n",
    125        "      <td>2.814709</td>\n",
    126        "      <td>3.053056</td>\n",
    127        "      <td>3.801458</td>\n",
    128        "      <td>3.598227</td>\n",
    129        "      <td>3.437533</td>\n",
    130        "      <td>2.007573</td>\n",
    131        "      <td>1.256223</td>\n",
    132        "      <td>2.444261</td>\n",
    133        "    </tr>\n",
    134        "    <tr>\n",
    135        "      <th>2</th>\n",
    136        "      <td>0.0</td>\n",
    137        "      <td>1.0</td>\n",
    138        "      <td>3.480841</td>\n",
    139        "      <td>1.947822</td>\n",
    140        "      <td>0.980785</td>\n",
    141        "      <td>2.974871</td>\n",
    142        "      <td>3.170290</td>\n",
    143        "      <td>2.179338</td>\n",
    144        "      <td>3.924941</td>\n",
    145        "      <td>1.990325</td>\n",
    146        "      <td>...</td>\n",
    147        "      <td>3.586487</td>\n",
    148        "      <td>0.820349</td>\n",
    149        "      <td>3.065853</td>\n",
    150        "      <td>1.348861</td>\n",
    151        "      <td>1.684723</td>\n",
    152        "      <td>2.547239</td>\n",
    153        "      <td>1.851281</td>\n",
    154        "      <td>0.912038</td>\n",
    155        "      <td>3.122452</td>\n",
    156        "      <td>1.915503</td>\n",
    157        "    </tr>\n",
    158        "    <tr>\n",
    159        "      <th>3</th>\n",
    160        "      <td>1.0</td>\n",
    161        "      <td>1.0</td>\n",
    162        "      <td>2.543543</td>\n",
    163        "      <td>3.168781</td>\n",
    164        "      <td>1.132832</td>\n",
    165        "      <td>1.109508</td>\n",
    166        "      <td>1.875743</td>\n",
    167        "      <td>2.314667</td>\n",
    168        "      <td>2.058042</td>\n",
    169        "      <td>8.846448</td>\n",
    170        "      <td>...</td>\n",
    171        "      <td>3.573916</td>\n",
    172        "      <td>3.103271</td>\n",
    173        "      <td>3.795463</td>\n",
    174        "      <td>1.994397</td>\n",
    175        "      <td>3.329407</td>\n",
    176        "      <td>2.953250</td>\n",
    177        "      <td>2.114900</td>\n",
    178        "      <td>3.287708</td>\n",
    179        "      <td>3.580659</td>\n",
    180        "      <td>1.270540</td>\n",
    181        "    </tr>\n",
    182        "    <tr>\n",
    183        "      <th>4</th>\n",
    184        "      <td>1.0</td>\n",
    185        "      <td>1.0</td>\n",
    186        "      <td>2.899545</td>\n",
    187        "      <td>3.131062</td>\n",
    188        "      <td>3.601594</td>\n",
    189        "      <td>2.031428</td>\n",
    190        "      <td>1.199504</td>\n",
    191        "      <td>1.857449</td>\n",
    192        "      <td>2.714846</td>\n",
    193        "      <td>5.864011</td>\n",
    194        "      <td>...</td>\n",
    195        "      <td>3.613841</td>\n",
    196        "      <td>1.466398</td>\n",
    197        "      <td>1.195874</td>\n",
    198        "      <td>2.773077</td>\n",
    199        "      <td>2.855805</td>\n",
    200        "      <td>3.384410</td>\n",
    201        "      <td>1.450015</td>\n",
    202        "      <td>1.731059</td>\n",
    203        "      <td>2.789938</td>\n",
    204        "      <td>0.966252</td>\n",
    205        "    </tr>\n",
    206        "  </tbody>\n",
    207        "</table>\n",
    208        "<p>5 rows × 100 columns</p>\n",
    209        "</div>"
    210       ],
    211       "text/plain": [
    212        "   Running  Blue Switch On  Battery level  Humidity  Magnetic field  \\\n",
    213        "0      1.0             1.0       2.668066  2.061727        2.549782   \n",
    214        "1      1.0             1.0       2.168779  3.064346        2.378786   \n",
    215        "2      0.0             1.0       3.480841  1.947822        0.980785   \n",
    216        "3      1.0             1.0       2.543543  3.168781        1.132832   \n",
    217        "4      1.0             1.0       2.899545  3.131062        3.601594   \n",
    218        "\n",
    219        "   Controller beige  Controller bisque  Controller black  \\\n",
    220        "0          1.835225           2.259989          2.686942   \n",
    221        "1          1.786132           3.317119          1.764618   \n",
    222        "2          2.974871           3.170290          2.179338   \n",
    223        "3          1.109508           1.875743          2.314667   \n",
    224        "4          2.031428           1.199504          1.857449   \n",
    225        "\n",
    226        "   Controller blanchedalmond  Time since restart  ...  Waste level right tank  \\\n",
    227        "0                   2.879310            9.671808  ...                2.971298   \n",
    228        "1                   3.480051            3.649143  ...                1.941678   \n",
    229        "2                   3.924941            1.990325  ...                3.586487   \n",
    230        "3                   2.058042            8.846448  ...                3.573916   \n",
    231        "4                   2.714846            5.864011  ...                3.613841   \n",
    232        "\n",
    233        "   Waste level left tank  Helium reservoir  alpha-radiation  \\\n",
    234        "0               0.937030          2.074836         2.640988   \n",
    235        "1               1.072903          2.814709         3.053056   \n",
    236        "2               0.820349          3.065853         1.348861   \n",
    237        "3               3.103271          3.795463         1.994397   \n",
    238        "4               1.466398          1.195874         2.773077   \n",
    239        "\n",
    240        "   Active motion supression  Blade density  Blade rotation  \\\n",
    241        "0                  0.884307       1.861668        1.395146   \n",
    242        "1                  3.801458       3.598227        3.437533   \n",
    243        "2                  1.684723       2.547239        1.851281   \n",
    244        "3                  3.329407       2.953250        2.114900   \n",
    245        "4                  2.855805       3.384410        1.450015   \n",
    246        "\n",
    247        "   Controller mintcream  Controller mistyrose  Controller moccasin  \n",
    248        "0              2.685994              1.246004             1.804786  \n",
    249        "1              2.007573              1.256223             2.444261  \n",
    250        "2              0.912038              3.122452             1.915503  \n",
    251        "3              3.287708              3.580659             1.270540  \n",
    252        "4              1.731059              2.789938             0.966252  \n",
    253        "\n",
    254        "[5 rows x 100 columns]"
    255       ]
    256      },
    257      "execution_count": 2,
    258      "metadata": {},
    259      "output_type": "execute_result"
    260     }
    261    ],
    262    "source": [
    263     "data_train_db = pd.read_csv('data_train_db.csv')\n",
    264     "data_test_db = pd.read_csv('data_test_db.csv')\n",
    265     "data_train_db.head()"
    266    ]
    267   },
    268   {
    269    "cell_type": "code",
    270    "execution_count": null,
    271    "metadata": {},
    272    "outputs": [],
    273    "source": []
    274   },
    275   {
    276    "cell_type": "markdown",
    277    "metadata": {},
    278    "source": [
    279     "Lets look at some more properties of the data:"
    280    ]
    281   },
    282   {
    283    "cell_type": "code",
    284    "execution_count": 3,
    285    "metadata": {},
    286    "outputs": [
    287     {
    288      "data": {
    289       "text/html": [
    290        "<div>\n",
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    303        "</style>\n",
    304        "<table border=\"1\" class=\"dataframe\">\n",
    305        "  <thead>\n",
    306        "    <tr style=\"text-align: right;\">\n",
    307        "      <th></th>\n",
    308        "      <th>Running</th>\n",
    309        "      <th>Blue Switch On</th>\n",
    310        "      <th>Battery level</th>\n",
    311        "      <th>Humidity</th>\n",
    312        "      <th>Magnetic field</th>\n",
    313        "      <th>Controller beige</th>\n",
    314        "      <th>Controller bisque</th>\n",
    315        "      <th>Controller black</th>\n",
    316        "      <th>Controller blanchedalmond</th>\n",
    317        "      <th>Time since restart</th>\n",
    318        "      <th>...</th>\n",
    319        "      <th>Waste level right tank</th>\n",
    320        "      <th>Waste level left tank</th>\n",
    321        "      <th>Helium reservoir</th>\n",
    322        "      <th>alpha-radiation</th>\n",
    323        "      <th>Active motion supression</th>\n",
    324        "      <th>Blade density</th>\n",
    325        "      <th>Blade rotation</th>\n",
    326        "      <th>Controller mintcream</th>\n",
    327        "      <th>Controller mistyrose</th>\n",
    328        "      <th>Controller moccasin</th>\n",
    329        "    </tr>\n",
    330        "  </thead>\n",
    331        "  <tbody>\n",
    332        "    <tr>\n",
    333        "      <th>count</th>\n",
    334        "      <td>2000.000000</td>\n",
    335        "      <td>2000.000000</td>\n",
    336        "      <td>2000.000000</td>\n",
    337        "      <td>2000.000000</td>\n",
    338        "      <td>2000.000000</td>\n",
    339        "      <td>2000.000000</td>\n",
    340        "      <td>2000.000000</td>\n",
    341        "      <td>2000.000000</td>\n",
    342        "      <td>2000.000000</td>\n",
    343        "      <td>2000.000000</td>\n",
    344        "      <td>...</td>\n",
    345        "      <td>2000.000000</td>\n",
    346        "      <td>2000.000000</td>\n",
    347        "      <td>2000.000000</td>\n",
    348        "      <td>2000.000000</td>\n",
    349        "      <td>2000.000000</td>\n",
    350        "      <td>2000.000000</td>\n",
    351        "      <td>2000.000000</td>\n",
    352        "      <td>2000.000000</td>\n",
    353        "      <td>2000.000000</td>\n",
    354        "      <td>2000.000000</td>\n",
    355        "    </tr>\n",
    356        "    <tr>\n",
    357        "      <th>mean</th>\n",
    358        "      <td>0.391000</td>\n",
    359        "      <td>0.606125</td>\n",
    360        "      <td>2.322544</td>\n",
    361        "      <td>2.418220</td>\n",
    362        "      <td>2.378835</td>\n",
    363        "      <td>2.481214</td>\n",
    364        "      <td>2.420077</td>\n",
    365        "      <td>2.326200</td>\n",
    366        "      <td>2.310508</td>\n",
    367        "      <td>4.962612</td>\n",
    368        "      <td>...</td>\n",
    369        "      <td>2.433046</td>\n",
    370        "      <td>2.422304</td>\n",
    371        "      <td>2.347551</td>\n",
    372        "      <td>2.391701</td>\n",
    373        "      <td>2.346847</td>\n",
    374        "      <td>2.269898</td>\n",
    375        "      <td>2.414802</td>\n",
    376        "      <td>2.405840</td>\n",
    377        "      <td>2.496285</td>\n",
    378        "      <td>2.432145</td>\n",
    379        "    </tr>\n",
    380        "    <tr>\n",
    381        "      <th>std</th>\n",
    382        "      <td>0.488096</td>\n",
    383        "      <td>2.218381</td>\n",
    384        "      <td>2.950372</td>\n",
    385        "      <td>2.140909</td>\n",
    386        "      <td>2.312733</td>\n",
    387        "      <td>2.932640</td>\n",
    388        "      <td>2.228293</td>\n",
    389        "      <td>2.262024</td>\n",
    390        "      <td>2.590223</td>\n",
    391        "      <td>3.198438</td>\n",
    392        "      <td>...</td>\n",
    393        "      <td>2.583671</td>\n",
    394        "      <td>2.378098</td>\n",
    395        "      <td>2.952354</td>\n",
    396        "      <td>1.936729</td>\n",
    397        "      <td>2.625252</td>\n",
    398        "      <td>2.527564</td>\n",
    399        "      <td>2.105146</td>\n",
    400        "      <td>2.320366</td>\n",
    401        "      <td>2.419193</td>\n",
    402        "      <td>1.726589</td>\n",
    403        "    </tr>\n",
    404        "    <tr>\n",
    405        "      <th>min</th>\n",
    406        "      <td>0.000000</td>\n",
    407        "      <td>-41.461832</td>\n",
    408        "      <td>-78.053448</td>\n",
    409        "      <td>-34.781219</td>\n",
    410        "      <td>-54.894945</td>\n",
    411        "      <td>-32.776029</td>\n",
    412        "      <td>-34.825272</td>\n",
    413        "      <td>-48.711770</td>\n",
    414        "      <td>-51.333718</td>\n",
    415        "      <td>-27.754378</td>\n",
    416        "      <td>...</td>\n",
    417        "      <td>-39.336963</td>\n",
    418        "      <td>-19.295385</td>\n",
    419        "      <td>-77.392514</td>\n",
    420        "      <td>-35.076539</td>\n",
    421        "      <td>-60.830264</td>\n",
    422        "      <td>-51.524385</td>\n",
    423        "      <td>-33.421008</td>\n",
    424        "      <td>-46.570217</td>\n",
    425        "      <td>-14.431300</td>\n",
    426        "      <td>-18.016197</td>\n",
    427        "    </tr>\n",
    428        "    <tr>\n",
    429        "      <th>25%</th>\n",
    430        "      <td>0.000000</td>\n",
    431        "      <td>0.000000</td>\n",
    432        "      <td>1.570550</td>\n",
    433        "      <td>1.620464</td>\n",
    434        "      <td>1.564938</td>\n",
    435        "      <td>1.555495</td>\n",
    436        "      <td>1.629284</td>\n",
    437        "      <td>1.546645</td>\n",
    438        "      <td>1.589647</td>\n",
    439        "      <td>2.559334</td>\n",
    440        "      <td>...</td>\n",
    441        "      <td>1.631260</td>\n",
    442        "      <td>1.538100</td>\n",
    443        "      <td>1.633180</td>\n",
    444        "      <td>1.621354</td>\n",
    445        "      <td>1.573365</td>\n",
    446        "      <td>1.604577</td>\n",
    447        "      <td>1.648309</td>\n",
    448        "      <td>1.656220</td>\n",
    449        "      <td>1.616580</td>\n",
    450        "      <td>1.599820</td>\n",
    451        "    </tr>\n",
    452        "    <tr>\n",
    453        "      <th>50%</th>\n",
    454        "      <td>0.000000</td>\n",
    455        "      <td>1.000000</td>\n",
    456        "      <td>2.399510</td>\n",
    457        "      <td>2.442420</td>\n",
    458        "      <td>2.351945</td>\n",
    459        "      <td>2.383485</td>\n",
    460        "      <td>2.420951</td>\n",
    461        "      <td>2.379612</td>\n",
    462        "      <td>2.403005</td>\n",
    463        "      <td>5.001151</td>\n",
    464        "      <td>...</td>\n",
    465        "      <td>2.455453</td>\n",
    466        "      <td>2.418505</td>\n",
    467        "      <td>2.445824</td>\n",
    468        "      <td>2.398215</td>\n",
    469        "      <td>2.390431</td>\n",
    470        "      <td>2.346763</td>\n",
    471        "      <td>2.433182</td>\n",
    472        "      <td>2.412098</td>\n",
    473        "      <td>2.419774</td>\n",
    474        "      <td>2.380269</td>\n",
    475        "    </tr>\n",
    476        "    <tr>\n",
    477        "      <th>75%</th>\n",
    478        "      <td>1.000000</td>\n",
    479        "      <td>1.000000</td>\n",
    480        "      <td>3.198364</td>\n",
    481        "      <td>3.208682</td>\n",
    482        "      <td>3.192416</td>\n",
    483        "      <td>3.169260</td>\n",
    484        "      <td>3.246819</td>\n",
    485        "      <td>3.194218</td>\n",
    486        "      <td>3.194958</td>\n",
    487        "      <td>7.348914</td>\n",
    488        "      <td>...</td>\n",
    489        "      <td>3.201254</td>\n",
    490        "      <td>3.206414</td>\n",
    491        "      <td>3.214889</td>\n",
    492        "      <td>3.232094</td>\n",
    493        "      <td>3.228444</td>\n",
    494        "      <td>3.167007</td>\n",
    495        "      <td>3.191491</td>\n",
    496        "      <td>3.229920</td>\n",
    497        "      <td>3.207462</td>\n",
    498        "      <td>3.218650</td>\n",
    499        "    </tr>\n",
    500        "    <tr>\n",
    501        "      <th>max</th>\n",
    502        "      <td>1.000000</td>\n",
    503        "      <td>54.033952</td>\n",
    504        "      <td>37.703573</td>\n",
    505        "      <td>66.014742</td>\n",
    506        "      <td>38.637138</td>\n",
    507        "      <td>75.279747</td>\n",
    508        "      <td>71.305690</td>\n",
    509        "      <td>35.009305</td>\n",
    510        "      <td>56.524760</td>\n",
    511        "      <td>30.384880</td>\n",
    512        "      <td>...</td>\n",
    513        "      <td>59.993885</td>\n",
    514        "      <td>81.003906</td>\n",
    515        "      <td>42.301300</td>\n",
    516        "      <td>32.972503</td>\n",
    517        "      <td>44.019583</td>\n",
    518        "      <td>32.855782</td>\n",
    519        "      <td>47.702903</td>\n",
    520        "      <td>54.749561</td>\n",
    521        "      <td>68.158383</td>\n",
    522        "      <td>40.218134</td>\n",
    523        "    </tr>\n",
    524        "  </tbody>\n",
    525        "</table>\n",
    526        "<p>8 rows × 100 columns</p>\n",
    527        "</div>"
    528       ],
    529       "text/plain": [
    530        "           Running  Blue Switch On  Battery level     Humidity  \\\n",
    531        "count  2000.000000     2000.000000    2000.000000  2000.000000   \n",
    532        "mean      0.391000        0.606125       2.322544     2.418220   \n",
    533        "std       0.488096        2.218381       2.950372     2.140909   \n",
    534        "min       0.000000      -41.461832     -78.053448   -34.781219   \n",
    535        "25%       0.000000        0.000000       1.570550     1.620464   \n",
    536        "50%       0.000000        1.000000       2.399510     2.442420   \n",
    537        "75%       1.000000        1.000000       3.198364     3.208682   \n",
    538        "max       1.000000       54.033952      37.703573    66.014742   \n",
    539        "\n",
    540        "       Magnetic field  Controller beige  Controller bisque  Controller black  \\\n",
    541        "count     2000.000000       2000.000000        2000.000000       2000.000000   \n",
    542        "mean         2.378835          2.481214           2.420077          2.326200   \n",
    543        "std          2.312733          2.932640           2.228293          2.262024   \n",
    544        "min        -54.894945        -32.776029         -34.825272        -48.711770   \n",
    545        "25%          1.564938          1.555495           1.629284          1.546645   \n",
    546        "50%          2.351945          2.383485           2.420951          2.379612   \n",
    547        "75%          3.192416          3.169260           3.246819          3.194218   \n",
    548        "max         38.637138         75.279747          71.305690         35.009305   \n",
    549        "\n",
    550        "       Controller blanchedalmond  Time since restart  ...  \\\n",
    551        "count                2000.000000         2000.000000  ...   \n",
    552        "mean                    2.310508            4.962612  ...   \n",
    553        "std                     2.590223            3.198438  ...   \n",
    554        "min                   -51.333718          -27.754378  ...   \n",
    555        "25%                     1.589647            2.559334  ...   \n",
    556        "50%                     2.403005            5.001151  ...   \n",
    557        "75%                     3.194958            7.348914  ...   \n",
    558        "max                    56.524760           30.384880  ...   \n",
    559        "\n",
    560        "       Waste level right tank  Waste level left tank  Helium reservoir  \\\n",
    561        "count             2000.000000            2000.000000       2000.000000   \n",
    562        "mean                 2.433046               2.422304          2.347551   \n",
    563        "std                  2.583671               2.378098          2.952354   \n",
    564        "min                -39.336963             -19.295385        -77.392514   \n",
    565        "25%                  1.631260               1.538100          1.633180   \n",
    566        "50%                  2.455453               2.418505          2.445824   \n",
    567        "75%                  3.201254               3.206414          3.214889   \n",
    568        "max                 59.993885              81.003906         42.301300   \n",
    569        "\n",
    570        "       alpha-radiation  Active motion supression  Blade density  \\\n",
    571        "count      2000.000000               2000.000000    2000.000000   \n",
    572        "mean          2.391701                  2.346847       2.269898   \n",
    573        "std           1.936729                  2.625252       2.527564   \n",
    574        "min         -35.076539                -60.830264     -51.524385   \n",
    575        "25%           1.621354                  1.573365       1.604577   \n",
    576        "50%           2.398215                  2.390431       2.346763   \n",
    577        "75%           3.232094                  3.228444       3.167007   \n",
    578        "max          32.972503                 44.019583      32.855782   \n",
    579        "\n",
    580        "       Blade rotation  Controller mintcream  Controller mistyrose  \\\n",
    581        "count     2000.000000           2000.000000           2000.000000   \n",
    582        "mean         2.414802              2.405840              2.496285   \n",
    583        "std          2.105146              2.320366              2.419193   \n",
    584        "min        -33.421008            -46.570217            -14.431300   \n",
    585        "25%          1.648309              1.656220              1.616580   \n",
    586        "50%          2.433182              2.412098              2.419774   \n",
    587        "75%          3.191491              3.229920              3.207462   \n",
    588        "max         47.702903             54.749561             68.158383   \n",
    589        "\n",
    590        "       Controller moccasin  \n",
    591        "count          2000.000000  \n",
    592        "mean              2.432145  \n",
    593        "std               1.726589  \n",
    594        "min             -18.016197  \n",
    595        "25%               1.599820  \n",
    596        "50%               2.380269  \n",
    597        "75%               3.218650  \n",
    598        "max              40.218134  \n",
    599        "\n",
    600        "[8 rows x 100 columns]"
    601       ]
    602      },
    603      "execution_count": 3,
    604      "metadata": {},
    605      "output_type": "execute_result"
    606     }
    607    ],
    608    "source": [
    609     "data_train_db.describe()"
    610    ]
    611   },
    612   {
    613    "cell_type": "markdown",
    614    "metadata": {},
    615    "source": [
    616     "How is the distribution of the labels?"
    617    ]
    618   },
    619   {
    620    "cell_type": "code",
    621    "execution_count": 4,
    622    "metadata": {},
    623    "outputs": [
    624     {
    625      "data": {
    626       "image/png": 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\n",
    627       "text/plain": [
    628        "<Figure size 432x288 with 1 Axes>"
    629       ]
    630      },
    631      "metadata": {},
    632      "output_type": "display_data"
    633     }
    634    ],
    635    "source": [
    636     "data_train = data_train_db.values\n",
    637     "\n",
    638     "labels = 'Runs', 'Does not run'\n",
    639     "sizes = [np.sum(data_train[:,0]), np.sum(1-data_train[:,0])]\n",
    640     "\n",
    641     "fig1, ax1 = plt.subplots()\n",
    642     "ax1.pie(sizes, labels=labels, autopct='%1.1f%%',\n",
    643     "        shadow=True, startangle=90)\n",
    644     "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    645     "\n",
    646     "plt.show()"
    647    ]
    648   },
    649   {
    650    "cell_type": "markdown",
    651    "metadata": {},
    652    "source": [
    653     "Lets look at some standard statistics of the data:"
    654    ]
    655   },
    656   {
    657    "cell_type": "code",
    658    "execution_count": 5,
    659    "metadata": {},
    660    "outputs": [
    661     {
    662      "data": {
    663       "text/plain": [
    664        "Text(0.5, 1.0, 'Distribution of min value--- not running')"
    665       ]
    666      },
    667      "execution_count": 5,
    668      "metadata": {},
    669      "output_type": "execute_result"
    670     },
    671     {
    672      "data": {
    673       "image/png": 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\n",
    674       "text/plain": [
    675        "<Figure size 1008x288 with 2 Axes>"
    676       ]
    677      },
    678      "metadata": {
    679       "needs_background": "light"
    680      },
    681      "output_type": "display_data"
    682     },
    683     {
    684      "data": {
    685       "image/png": 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\n",
    686       "text/plain": [
    687        "<Figure size 1008x288 with 2 Axes>"
    688       ]
    689      },
    690      "metadata": {
    691       "needs_background": "light"
    692      },
    693      "output_type": "display_data"
    694     },
    695     {
    696      "data": {
    697       "image/png": 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\n",
    698       "text/plain": [
    699        "<Figure size 1008x288 with 2 Axes>"
    700       ]
    701      },
    702      "metadata": {
    703       "needs_background": "light"
    704      },
    705      "output_type": "display_data"
    706     },
    707     {
    708      "data": {
    709       "image/png": 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\n",
    710       "text/plain": [
    711        "<Figure size 1008x288 with 2 Axes>"
    712       ]
    713      },
    714      "metadata": {
    715       "needs_background": "light"
    716      },
    717      "output_type": "display_data"
    718     }
    719    ],
    720    "source": [
    721     "fig = plt.figure(figsize = (14, 4))\n",
    722     "\n",
    723     "plt.subplot(1,2,1)\n",
    724     "plt.hist(data_train[data_train[:,0] == 1,1:].std(1))\n",
    725     "plt.title('Distribution of standard deviation--- running')\n",
    726     "plt.subplot(1,2,2)\n",
    727     "plt.hist(data_train[data_train[:,0] == 0,1:].std(1))\n",
    728     "plt.title('Distribution of standard deviation--- not running')\n",
    729     "\n",
    730     "fig = plt.figure(figsize = (14, 4))\n",
    731     "\n",
    732     "plt.subplot(1,2,1)\n",
    733     "plt.hist(np.sum(data_train[data_train[:,0]==1,1:], 1)/100)\n",
    734     "plt.title('Distribution of means--- running')\n",
    735     "plt.subplot(1,2,2)\n",
    736     "plt.hist(np.sum(data_train[data_train[:,0]==0,1:], 1)/100)\n",
    737     "plt.title('Distribution of means--- not running')\n",
    738     "\n",
    739     "fig = plt.figure(figsize = (14, 4))\n",
    740     "\n",
    741     "plt.subplot(1,2,1)\n",
    742     "plt.hist(np.amax(data_train[data_train[:,0] == 1,1:], axis = 1))\n",
    743     "plt.title('Distribution of max value--- running')\n",
    744     "plt.subplot(1,2,2)\n",
    745     "plt.hist(np.amax(data_train[data_train[:,0] == 0,1:], axis = 1))\n",
    746     "plt.title('Distribution of max value--- not running')\n",
    747     "\n",
    748     "fig = plt.figure(figsize = (14, 4))\n",
    749     "\n",
    750     "plt.subplot(1,2,1)\n",
    751     "plt.hist(np.amin(data_train[data_train[:,0] == 1,1:], axis = 1))\n",
    752     "plt.title('Distribution of min value--- running')\n",
    753     "plt.subplot(1,2,2)\n",
    754     "plt.hist(np.amin(data_train[data_train[:,0] == 0,1:], axis = 1))\n",
    755     "plt.title('Distribution of min value--- not running')"
    756    ]
    757   },
    758   {
    759    "cell_type": "markdown",
    760    "metadata": {},
    761    "source": [
    762     "The distribution of the min values is a bit worrying. Since some very few entries have very high standard deviation, some very few and possibly the same values have very low negative values, but almost all other entries have only positive values. This may be a problem in the data set. We decide that these entries are outliers and drop these entries from the data base."
    763    ]
    764   },
    765   {
    766    "cell_type": "code",
    767    "execution_count": 6,
    768    "metadata": {},
    769    "outputs": [],
    770    "source": [
    771     "# It seems like there are some data points which have much higher standard deviation than most. Lets just remove those.\n",
    772     "\n",
    773     "def clean_dataset(data):\n",
    774     "    to_drop= []\n",
    775     "    for k in range(data.shape[0]):\n",
    776     "        if data[k,:].std()>15:\n",
    777     "            to_drop.append(k)   \n",
    778     "    return np.delete(data, to_drop, axis = 0)"
    779    ]
    780   },
    781   {
    782    "cell_type": "markdown",
    783    "metadata": {},
    784    "source": [
    785     "Let us apply the cleaning and look at the data set again"
    786    ]
    787   },
    788   {
    789    "cell_type": "code",
    790    "execution_count": 7,
    791    "metadata": {},
    792    "outputs": [
    793     {
    794      "data": {
    795       "text/plain": [
    796        "Text(0.5, 1.0, 'Distribution of min value--- not running')"
    797       ]
    798      },
    799      "execution_count": 7,
    800      "metadata": {},
    801      "output_type": "execute_result"
    802     },
    803     {
    804      "data": {
    805       "image/png": 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\n",
    806       "text/plain": [
    807        "<Figure size 1008x288 with 2 Axes>"
    808       ]
    809      },
    810      "metadata": {
    811       "needs_background": "light"
    812      },
    813      "output_type": "display_data"
    814     },
    815     {
    816      "data": {
    817       "image/png": 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\n",
    818       "text/plain": [
    819        "<Figure size 1008x288 with 2 Axes>"
    820       ]
    821      },
    822      "metadata": {
    823       "needs_background": "light"
    824      },
    825      "output_type": "display_data"
    826     }
    827    ],
    828    "source": [
    829     "data_train = clean_dataset(data_train)\n",
    830     "\n",
    831     "fig = plt.figure(figsize = (14, 4))\n",
    832     "\n",
    833     "plt.subplot(1,2,1)\n",
    834     "plt.hist(data_train[data_train[:,0] == 1,1:].std(1))\n",
    835     "plt.title('Distribution of standard deviation--- not running')\n",
    836     "plt.subplot(1,2,2)\n",
    837     "plt.hist(data_train[data_train[:,0] == 0,1:].std(1))\n",
    838     "plt.title('Distribution of standard deviation--- not running')\n",
    839     "\n",
    840     "fig = plt.figure(figsize = (14, 4))\n",
    841     "\n",
    842     "plt.subplot(1,2,1)\n",
    843     "plt.hist(np.amin(data_train[data_train[:,0] == 1,1:], axis = 1))\n",
    844     "plt.title('Distribution of min value--- running')\n",
    845     "plt.subplot(1,2,2)\n",
    846     "plt.hist(np.amin(data_train[data_train[:,0] == 0,1:], axis = 1))\n",
    847     "plt.title('Distribution of min value--- not running')\n"
    848    ]
    849   },
    850   {
    851    "cell_type": "markdown",
    852    "metadata": {},
    853    "source": [
    854     "This looks much better.\n",
    855     "\n",
    856     "Now we start understanding our data set a bit more in detaill. Let us try to get a feeling of the dependencies between the columns."
    857    ]
    858   },
    859   {
    860    "cell_type": "code",
    861    "execution_count": 8,
    862    "metadata": {},
    863    "outputs": [
    864     {
    865      "data": {
    866       "text/html": [
    867        "<div>\n",
    868        "<style scoped>\n",
    869        "    .dataframe tbody tr th:only-of-type {\n",
    870        "        vertical-align: middle;\n",
    871        "    }\n",
    872        "\n",
    873        "    .dataframe tbody tr th {\n",
    874        "        vertical-align: top;\n",
    875        "    }\n",
    876        "\n",
    877        "    .dataframe thead th {\n",
    878        "        text-align: right;\n",
    879        "    }\n",
    880        "</style>\n",
    881        "<table border=\"1\" class=\"dataframe\">\n",
    882        "  <thead>\n",
    883        "    <tr style=\"text-align: right;\">\n",
    884        "      <th></th>\n",
    885        "      <th>Running</th>\n",
    886        "      <th>Blue Switch On</th>\n",
    887        "      <th>Battery level</th>\n",
    888        "      <th>Humidity</th>\n",
    889        "      <th>Magnetic field</th>\n",
    890        "      <th>Controller beige</th>\n",
    891        "      <th>Controller bisque</th>\n",
    892        "      <th>Controller black</th>\n",
    893        "      <th>Controller blanchedalmond</th>\n",
    894        "      <th>Time since restart</th>\n",
    895        "      <th>...</th>\n",
    896        "      <th>Waste level right tank</th>\n",
    897        "      <th>Waste level left tank</th>\n",
    898        "      <th>Helium reservoir</th>\n",
    899        "      <th>alpha-radiation</th>\n",
    900        "      <th>Active motion supression</th>\n",
    901        "      <th>Blade density</th>\n",
    902        "      <th>Blade rotation</th>\n",
    903        "      <th>Controller mintcream</th>\n",
    904        "      <th>Controller mistyrose</th>\n",
    905        "      <th>Controller moccasin</th>\n",
    906        "    </tr>\n",
    907        "  </thead>\n",
    908        "  <tbody>\n",
    909        "    <tr>\n",
    910        "      <th>Running</th>\n",
    911        "      <td>1.000000</td>\n",
    912        "      <td>0.142302</td>\n",
    913        "      <td>0.017820</td>\n",
    914        "      <td>0.020910</td>\n",
    915        "      <td>-0.005103</td>\n",
    916        "      <td>-0.026189</td>\n",
    917        "      <td>0.011414</td>\n",
    918        "      <td>0.007581</td>\n",
    919        "      <td>0.024917</td>\n",
    920        "      <td>0.004160</td>\n",
    921        "      <td>...</td>\n",
    922        "      <td>-0.003036</td>\n",
    923        "      <td>-0.000267</td>\n",
    924        "      <td>0.028839</td>\n",
    925        "      <td>0.019230</td>\n",
    926        "      <td>0.025991</td>\n",
    927        "      <td>0.032544</td>\n",
    928        "      <td>0.061764</td>\n",
    929        "      <td>-0.002125</td>\n",
    930        "      <td>-0.035509</td>\n",
    931        "      <td>-0.080258</td>\n",
    932        "    </tr>\n",
    933        "    <tr>\n",
    934        "      <th>Blue Switch On</th>\n",
    935        "      <td>0.142302</td>\n",
    936        "      <td>1.000000</td>\n",
    937        "      <td>0.085980</td>\n",
    938        "      <td>0.010917</td>\n",
    939        "      <td>0.453213</td>\n",
    940        "      <td>-0.256682</td>\n",
    941        "      <td>0.395337</td>\n",
    942        "      <td>-0.053934</td>\n",
    943        "      <td>0.511684</td>\n",
    944        "      <td>0.041501</td>\n",
    945        "      <td>...</td>\n",
    946        "      <td>0.142301</td>\n",
    947        "      <td>-0.338354</td>\n",
    948        "      <td>-0.188773</td>\n",
    949        "      <td>0.286469</td>\n",
    950        "      <td>-0.360740</td>\n",
    951        "      <td>-0.059795</td>\n",
    952        "      <td>-0.281912</td>\n",
    953        "      <td>-0.261851</td>\n",
    954        "      <td>-0.055126</td>\n",
    955        "      <td>-0.376401</td>\n",
    956        "    </tr>\n",
    957        "    <tr>\n",
    958        "      <th>Battery level</th>\n",
    959        "      <td>0.017820</td>\n",
    960        "      <td>0.085980</td>\n",
    961        "      <td>1.000000</td>\n",
    962        "      <td>0.135179</td>\n",
    963        "      <td>0.453659</td>\n",
    964        "      <td>-0.423902</td>\n",
    965        "      <td>-0.025855</td>\n",
    966        "      <td>-0.114770</td>\n",
    967        "      <td>0.290171</td>\n",
    968        "      <td>-0.047395</td>\n",
    969        "      <td>...</td>\n",
    970        "      <td>-0.188997</td>\n",
    971        "      <td>0.257791</td>\n",
    972        "      <td>0.357651</td>\n",
    973        "      <td>-0.217664</td>\n",
    974        "      <td>0.253307</td>\n",
    975        "      <td>-0.006822</td>\n",
    976        "      <td>-0.344960</td>\n",
    977        "      <td>0.141722</td>\n",
    978        "      <td>-0.616985</td>\n",
    979        "      <td>-0.489590</td>\n",
    980        "    </tr>\n",
    981        "    <tr>\n",
    982        "      <th>Humidity</th>\n",
    983        "      <td>0.020910</td>\n",
    984        "      <td>0.010917</td>\n",
    985        "      <td>0.135179</td>\n",
    986        "      <td>1.000000</td>\n",
    987        "      <td>0.310727</td>\n",
    988        "      <td>0.184007</td>\n",
    989        "      <td>0.035603</td>\n",
    990        "      <td>-0.597343</td>\n",
    991        "      <td>0.172276</td>\n",
    992        "      <td>0.012291</td>\n",
    993        "      <td>...</td>\n",
    994        "      <td>0.408127</td>\n",
    995        "      <td>-0.099491</td>\n",
    996        "      <td>-0.431891</td>\n",
    997        "      <td>0.211459</td>\n",
    998        "      <td>0.098269</td>\n",
    999        "      <td>-0.323472</td>\n",
   1000        "      <td>-0.191757</td>\n",
   1001        "      <td>-0.117132</td>\n",
   1002        "      <td>-0.160719</td>\n",
   1003        "      <td>-0.488834</td>\n",
   1004        "    </tr>\n",
   1005        "    <tr>\n",
   1006        "      <th>Magnetic field</th>\n",
   1007        "      <td>-0.005103</td>\n",
   1008        "      <td>0.453213</td>\n",
   1009        "      <td>0.453659</td>\n",
   1010        "      <td>0.310727</td>\n",
   1011        "      <td>1.000000</td>\n",
   1012        "      <td>-0.344852</td>\n",
   1013        "      <td>-0.010073</td>\n",
   1014        "      <td>-0.436788</td>\n",
   1015        "      <td>0.313958</td>\n",
   1016        "      <td>0.105562</td>\n",
   1017        "      <td>...</td>\n",
   1018        "      <td>-0.121953</td>\n",
   1019        "      <td>-0.145483</td>\n",
   1020        "      <td>-0.195793</td>\n",
   1021        "      <td>0.173101</td>\n",
   1022        "      <td>-0.301443</td>\n",
   1023        "      <td>-0.365754</td>\n",
   1024        "      <td>-0.412580</td>\n",
   1025        "      <td>-0.033184</td>\n",
   1026        "      <td>-0.123513</td>\n",
   1027        "      <td>-0.424851</td>\n",
   1028        "    </tr>\n",
   1029        "    <tr>\n",
   1030        "      <th>...</th>\n",
   1031        "      <td>...</td>\n",
   1032        "      <td>...</td>\n",
   1033        "      <td>...</td>\n",
   1034        "      <td>...</td>\n",
   1035        "      <td>...</td>\n",
   1036        "      <td>...</td>\n",
   1037        "      <td>...</td>\n",
   1038        "      <td>...</td>\n",
   1039        "      <td>...</td>\n",
   1040        "      <td>...</td>\n",
   1041        "      <td>...</td>\n",
   1042        "      <td>...</td>\n",
   1043        "      <td>...</td>\n",
   1044        "      <td>...</td>\n",
   1045        "      <td>...</td>\n",
   1046        "      <td>...</td>\n",
   1047        "      <td>...</td>\n",
   1048        "      <td>...</td>\n",
   1049        "      <td>...</td>\n",
   1050        "      <td>...</td>\n",
   1051        "      <td>...</td>\n",
   1052        "    </tr>\n",
   1053        "    <tr>\n",
   1054        "      <th>Blade density</th>\n",
   1055        "      <td>0.032544</td>\n",
   1056        "      <td>-0.059795</td>\n",
   1057        "      <td>-0.006822</td>\n",
   1058        "      <td>-0.323472</td>\n",
   1059        "      <td>-0.365754</td>\n",
   1060        "      <td>-0.197764</td>\n",
   1061        "      <td>0.220780</td>\n",
   1062        "      <td>0.364569</td>\n",
   1063        "      <td>0.010155</td>\n",
   1064        "      <td>0.116971</td>\n",
   1065        "      <td>...</td>\n",
   1066        "      <td>0.034377</td>\n",
   1067        "      <td>-0.070913</td>\n",
   1068        "      <td>0.318141</td>\n",
   1069        "      <td>0.061712</td>\n",
   1070        "      <td>0.381020</td>\n",
   1071        "      <td>1.000000</td>\n",
   1072        "      <td>-0.149659</td>\n",
   1073        "      <td>0.110383</td>\n",
   1074        "      <td>-0.146524</td>\n",
   1075        "      <td>0.154362</td>\n",
   1076        "    </tr>\n",
   1077        "    <tr>\n",
   1078        "      <th>Blade rotation</th>\n",
   1079        "      <td>0.061764</td>\n",
   1080        "      <td>-0.281912</td>\n",
   1081        "      <td>-0.344960</td>\n",
   1082        "      <td>-0.191757</td>\n",
   1083        "      <td>-0.412580</td>\n",
   1084        "      <td>-0.108025</td>\n",
   1085        "      <td>-0.151012</td>\n",
   1086        "      <td>0.362259</td>\n",
   1087        "      <td>0.123801</td>\n",
   1088        "      <td>0.056536</td>\n",
   1089        "      <td>...</td>\n",
   1090        "      <td>-0.136104</td>\n",
   1091        "      <td>0.300145</td>\n",
   1092        "      <td>0.109506</td>\n",
   1093        "      <td>-0.087121</td>\n",
   1094        "      <td>-0.278081</td>\n",
   1095        "      <td>-0.149659</td>\n",
   1096        "      <td>1.000000</td>\n",
   1097        "      <td>-0.286417</td>\n",
   1098        "      <td>0.151956</td>\n",
   1099        "      <td>0.249235</td>\n",
   1100        "    </tr>\n",
   1101        "    <tr>\n",
   1102        "      <th>Controller mintcream</th>\n",
   1103        "      <td>-0.002125</td>\n",
   1104        "      <td>-0.261851</td>\n",
   1105        "      <td>0.141722</td>\n",
   1106        "      <td>-0.117132</td>\n",
   1107        "      <td>-0.033184</td>\n",
   1108        "      <td>0.244462</td>\n",
   1109        "      <td>-0.423174</td>\n",
   1110        "      <td>0.175089</td>\n",
   1111        "      <td>-0.413617</td>\n",
   1112        "      <td>0.009026</td>\n",
   1113        "      <td>...</td>\n",
   1114        "      <td>0.052346</td>\n",
   1115        "      <td>-0.143134</td>\n",
   1116        "      <td>0.528566</td>\n",
   1117        "      <td>0.109838</td>\n",
   1118        "      <td>0.502678</td>\n",
   1119        "      <td>0.110383</td>\n",
   1120        "      <td>-0.286417</td>\n",
   1121        "      <td>1.000000</td>\n",
   1122        "      <td>0.052587</td>\n",
   1123        "      <td>0.012654</td>\n",
   1124        "    </tr>\n",
   1125        "    <tr>\n",
   1126        "      <th>Controller mistyrose</th>\n",
   1127        "      <td>-0.035509</td>\n",
   1128        "      <td>-0.055126</td>\n",
   1129        "      <td>-0.616985</td>\n",
   1130        "      <td>-0.160719</td>\n",
   1131        "      <td>-0.123513</td>\n",
   1132        "      <td>0.180529</td>\n",
   1133        "      <td>-0.089244</td>\n",
   1134        "      <td>-0.149480</td>\n",
   1135        "      <td>-0.313713</td>\n",
   1136        "      <td>0.060318</td>\n",
   1137        "      <td>...</td>\n",
   1138        "      <td>0.168399</td>\n",
   1139        "      <td>0.089697</td>\n",
   1140        "      <td>-0.151666</td>\n",
   1141        "      <td>0.404632</td>\n",
   1142        "      <td>-0.425254</td>\n",
   1143        "      <td>-0.146524</td>\n",
   1144        "      <td>0.151956</td>\n",
   1145        "      <td>0.052587</td>\n",
   1146        "      <td>1.000000</td>\n",
   1147        "      <td>0.450278</td>\n",
   1148        "    </tr>\n",
   1149        "    <tr>\n",
   1150        "      <th>Controller moccasin</th>\n",
   1151        "      <td>-0.080258</td>\n",
   1152        "      <td>-0.376401</td>\n",
   1153        "      <td>-0.489590</td>\n",
   1154        "      <td>-0.488834</td>\n",
   1155        "      <td>-0.424851</td>\n",
   1156        "      <td>0.149769</td>\n",
   1157        "      <td>-0.223025</td>\n",
   1158        "      <td>0.267447</td>\n",
   1159        "      <td>-0.395596</td>\n",
   1160        "      <td>-0.020053</td>\n",
   1161        "      <td>...</td>\n",
   1162        "      <td>-0.159872</td>\n",
   1163        "      <td>0.064195</td>\n",
   1164        "      <td>0.013373</td>\n",
   1165        "      <td>-0.126641</td>\n",
   1166        "      <td>-0.114146</td>\n",
   1167        "      <td>0.154362</td>\n",
   1168        "      <td>0.249235</td>\n",
   1169        "      <td>0.012654</td>\n",
   1170        "      <td>0.450278</td>\n",
   1171        "      <td>1.000000</td>\n",
   1172        "    </tr>\n",
   1173        "  </tbody>\n",
   1174        "</table>\n",
   1175        "<p>100 rows × 100 columns</p>\n",
   1176        "</div>"
   1177       ],
   1178       "text/plain": [
   1179        "                       Running  Blue Switch On  Battery level  Humidity  \\\n",
   1180        "Running               1.000000        0.142302       0.017820  0.020910   \n",
   1181        "Blue Switch On        0.142302        1.000000       0.085980  0.010917   \n",
   1182        "Battery level         0.017820        0.085980       1.000000  0.135179   \n",
   1183        "Humidity              0.020910        0.010917       0.135179  1.000000   \n",
   1184        "Magnetic field       -0.005103        0.453213       0.453659  0.310727   \n",
   1185        "...                        ...             ...            ...       ...   \n",
   1186        "Blade density         0.032544       -0.059795      -0.006822 -0.323472   \n",
   1187        "Blade rotation        0.061764       -0.281912      -0.344960 -0.191757   \n",
   1188        "Controller mintcream -0.002125       -0.261851       0.141722 -0.117132   \n",
   1189        "Controller mistyrose -0.035509       -0.055126      -0.616985 -0.160719   \n",
   1190        "Controller moccasin  -0.080258       -0.376401      -0.489590 -0.488834   \n",
   1191        "\n",
   1192        "                      Magnetic field  Controller beige  Controller bisque  \\\n",
   1193        "Running                    -0.005103         -0.026189           0.011414   \n",
   1194        "Blue Switch On              0.453213         -0.256682           0.395337   \n",
   1195        "Battery level               0.453659         -0.423902          -0.025855   \n",
   1196        "Humidity                    0.310727          0.184007           0.035603   \n",
   1197        "Magnetic field              1.000000         -0.344852          -0.010073   \n",
   1198        "...                              ...               ...                ...   \n",
   1199        "Blade density              -0.365754         -0.197764           0.220780   \n",
   1200        "Blade rotation             -0.412580         -0.108025          -0.151012   \n",
   1201        "Controller mintcream       -0.033184          0.244462          -0.423174   \n",
   1202        "Controller mistyrose       -0.123513          0.180529          -0.089244   \n",
   1203        "Controller moccasin        -0.424851          0.149769          -0.223025   \n",
   1204        "\n",
   1205        "                      Controller black  Controller blanchedalmond  \\\n",
   1206        "Running                       0.007581                   0.024917   \n",
   1207        "Blue Switch On               -0.053934                   0.511684   \n",
   1208        "Battery level                -0.114770                   0.290171   \n",
   1209        "Humidity                     -0.597343                   0.172276   \n",
   1210        "Magnetic field               -0.436788                   0.313958   \n",
   1211        "...                                ...                        ...   \n",
   1212        "Blade density                 0.364569                   0.010155   \n",
   1213        "Blade rotation                0.362259                   0.123801   \n",
   1214        "Controller mintcream          0.175089                  -0.413617   \n",
   1215        "Controller mistyrose         -0.149480                  -0.313713   \n",
   1216        "Controller moccasin           0.267447                  -0.395596   \n",
   1217        "\n",
   1218        "                      Time since restart  ...  Waste level right tank  \\\n",
   1219        "Running                         0.004160  ...               -0.003036   \n",
   1220        "Blue Switch On                  0.041501  ...                0.142301   \n",
   1221        "Battery level                  -0.047395  ...               -0.188997   \n",
   1222        "Humidity                        0.012291  ...                0.408127   \n",
   1223        "Magnetic field                  0.105562  ...               -0.121953   \n",
   1224        "...                                  ...  ...                     ...   \n",
   1225        "Blade density                   0.116971  ...                0.034377   \n",
   1226        "Blade rotation                  0.056536  ...               -0.136104   \n",
   1227        "Controller mintcream            0.009026  ...                0.052346   \n",
   1228        "Controller mistyrose            0.060318  ...                0.168399   \n",
   1229        "Controller moccasin            -0.020053  ...               -0.159872   \n",
   1230        "\n",
   1231        "                      Waste level left tank  Helium reservoir  \\\n",
   1232        "Running                           -0.000267          0.028839   \n",
   1233        "Blue Switch On                    -0.338354         -0.188773   \n",
   1234        "Battery level                      0.257791          0.357651   \n",
   1235        "Humidity                          -0.099491         -0.431891   \n",
   1236        "Magnetic field                    -0.145483         -0.195793   \n",
   1237        "...                                     ...               ...   \n",
   1238        "Blade density                     -0.070913          0.318141   \n",
   1239        "Blade rotation                     0.300145          0.109506   \n",
   1240        "Controller mintcream              -0.143134          0.528566   \n",
   1241        "Controller mistyrose               0.089697         -0.151666   \n",
   1242        "Controller moccasin                0.064195          0.013373   \n",
   1243        "\n",
   1244        "                      alpha-radiation  Active motion supression  \\\n",
   1245        "Running                      0.019230                  0.025991   \n",
   1246        "Blue Switch On               0.286469                 -0.360740   \n",
   1247        "Battery level               -0.217664                  0.253307   \n",
   1248        "Humidity                     0.211459                  0.098269   \n",
   1249        "Magnetic field               0.173101                 -0.301443   \n",
   1250        "...                               ...                       ...   \n",
   1251        "Blade density                0.061712                  0.381020   \n",
   1252        "Blade rotation              -0.087121                 -0.278081   \n",
   1253        "Controller mintcream         0.109838                  0.502678   \n",
   1254        "Controller mistyrose         0.404632                 -0.425254   \n",
   1255        "Controller moccasin         -0.126641                 -0.114146   \n",
   1256        "\n",
   1257        "                      Blade density  Blade rotation  Controller mintcream  \\\n",
   1258        "Running                    0.032544        0.061764             -0.002125   \n",
   1259        "Blue Switch On            -0.059795       -0.281912             -0.261851   \n",
   1260        "Battery level             -0.006822       -0.344960              0.141722   \n",
   1261        "Humidity                  -0.323472       -0.191757             -0.117132   \n",
   1262        "Magnetic field            -0.365754       -0.412580             -0.033184   \n",
   1263        "...                             ...             ...                   ...   \n",
   1264        "Blade density              1.000000       -0.149659              0.110383   \n",
   1265        "Blade rotation            -0.149659        1.000000             -0.286417   \n",
   1266        "Controller mintcream       0.110383       -0.286417              1.000000   \n",
   1267        "Controller mistyrose      -0.146524        0.151956              0.052587   \n",
   1268        "Controller moccasin        0.154362        0.249235              0.012654   \n",
   1269        "\n",
   1270        "                      Controller mistyrose  Controller moccasin  \n",
   1271        "Running                          -0.035509            -0.080258  \n",
   1272        "Blue Switch On                   -0.055126            -0.376401  \n",
   1273        "Battery level                    -0.616985            -0.489590  \n",
   1274        "Humidity                         -0.160719            -0.488834  \n",
   1275        "Magnetic field                   -0.123513            -0.424851  \n",
   1276        "...                                    ...                  ...  \n",
   1277        "Blade density                    -0.146524             0.154362  \n",
   1278        "Blade rotation                    0.151956             0.249235  \n",
   1279        "Controller mintcream              0.052587             0.012654  \n",
   1280        "Controller mistyrose              1.000000             0.450278  \n",
   1281        "Controller moccasin               0.450278             1.000000  \n",
   1282        "\n",
   1283        "[100 rows x 100 columns]"
   1284       ]
   1285      },
   1286      "execution_count": 8,
   1287      "metadata": {},
   1288      "output_type": "execute_result"
   1289     }
   1290    ],
   1291    "source": [
   1292     "data_train_db.corr()"
   1293    ]
   1294   },
   1295   {
   1296    "cell_type": "code",
   1297    "execution_count": 9,
   1298    "metadata": {
   1299     "scrolled": false
   1300    },
   1301    "outputs": [
   1302     {
   1303      "data": {
   1304       "image/png": 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\n",
   1305       "text/plain": [
   1306        "<Figure size 864x864 with 2 Axes>"
   1307       ]
   1308      },
   1309      "metadata": {
   1310       "needs_background": "light"
   1311      },
   1312      "output_type": "display_data"
   1313     },
   1314     {
   1315      "data": {
   1316       "image/png": 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\n",
   1317       "text/plain": [
   1318        "<Figure size 864x432 with 1 Axes>"
   1319       ]
   1320      },
   1321      "metadata": {
   1322       "needs_background": "light"
   1323      },
   1324      "output_type": "display_data"
   1325     }
   1326    ],
   1327    "source": [
   1328     "corrMatrix = data_train_db.corr()\n",
   1329     "plt.figure(figsize = (12,12))\n",
   1330     "sn.heatmap(corrMatrix, annot=False)\n",
   1331     "plt.show()\n",
   1332     "\n",
   1333     "plt.figure(figsize = (12,6))\n",
   1334     "plt.scatter(np.arange(1, 100), corrMatrix['Running'][1:100])\n",
   1335     "plt.title('Correlation with Running')\n",
   1336     "plt.show()"
   1337    ]
   1338   },
   1339   {
   1340    "cell_type": "markdown",
   1341    "metadata": {},
   1342    "source": [
   1343     "The first row of the data set (after the row 'Running' itself), seems to be suspiciously important. Lets look at it in isolation."
   1344    ]
   1345   },
   1346   {
   1347    "cell_type": "code",
   1348    "execution_count": 10,
   1349    "metadata": {},
   1350    "outputs": [
   1351     {
   1352      "data": {
   1353       "text/plain": [
   1354        "Text(0.5, 1.0, 'Blue Switch On')"
   1355       ]
   1356      },
   1357      "execution_count": 10,
   1358      "metadata": {},
   1359      "output_type": "execute_result"
   1360     },
   1361     {
   1362      "data": {
   1363       "image/png": 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\n",
   1364       "text/plain": [
   1365        "<Figure size 432x288 with 1 Axes>"
   1366       ]
   1367      },
   1368      "metadata": {
   1369       "needs_background": "light"
   1370      },
   1371      "output_type": "display_data"
   1372     }
   1373    ],
   1374    "source": [
   1375     "plt.hist(data_train[:,1])\n",
   1376     "plt.title(data_train_db.columns[1])"
   1377    ]
   1378   },
   1379   {
   1380    "cell_type": "markdown",
   1381    "metadata": {},
   1382    "source": [
   1383     "We see that 'Blue Switch On' only takes two values (On and Off). Let us look in detail, what the effect of this switch is on whether the mechanism runs or not."
   1384    ]
   1385   },
   1386   {
   1387    "cell_type": "code",
   1388    "execution_count": 11,
   1389    "metadata": {},
   1390    "outputs": [
   1391     {
   1392      "data": {
   1393       "text/plain": [
   1394        "[Text(0.5, 0, 'Blue Switch On'), Text(1.5, 0, 'Blue Switch Off')]"
   1395       ]
   1396      },
   1397      "execution_count": 11,
   1398      "metadata": {},
   1399      "output_type": "execute_result"
   1400     },
   1401     {
   1402      "data": {
   1403       "image/png": 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\n",
   1404       "text/plain": [
   1405        "<Figure size 648x432 with 2 Axes>"
   1406       ]
   1407      },
   1408      "metadata": {},
   1409      "output_type": "display_data"
   1410     }
   1411    ],
   1412    "source": [
   1413     "runs_switchon = np.count_nonzero((data_train[:,0]==1)*(data_train[:,1]==1))\n",
   1414     "runs_switchoff = np.count_nonzero((data_train[:,0]==1)*(data_train[:,1]==0))\n",
   1415     "runsnot_switchon = np.count_nonzero((data_train[:,0]==0)*(data_train[:,1]==1))\n",
   1416     "runsnot_switchoff = np.count_nonzero((data_train[:,0]==0)*(data_train[:,1]==0))\n",
   1417     "conf_matrix = [[runs_switchon, runs_switchoff], [runsnot_switchon, runsnot_switchoff]]\n",
   1418     "\n",
   1419     "sn.set(color_codes=True)\n",
   1420     "plt.figure(1, figsize=(9, 6))\n",
   1421     "\n",
   1422     "plt.title(\"Confusion Matrix\")\n",
   1423     "\n",
   1424     "sn.set(font_scale=1.4)\n",
   1425     "ax = sn.heatmap(conf_matrix, annot=True, cmap=\"YlGnBu\", fmt='2')\n",
   1426     "\n",
   1427     "ax.set_yticklabels(['runs', 'does not run'])\n",
   1428     "ax.set_xticklabels(['Blue Switch On', 'Blue Switch Off'])"
   1429    ]
   1430   },
   1431   {
   1432    "cell_type": "markdown",
   1433    "metadata": {},
   1434    "source": [
   1435     "Now this is fantastic. If the Blue Switch is off, then the mechanism never works. \n",
   1436     "\n",
   1437     "Next, we would like to extract additional important parameters of the machine. We rank the columns according to their correlation with 'Running':"
   1438    ]
   1439   },
   1440   {
   1441    "cell_type": "code",
   1442    "execution_count": 12,
   1443    "metadata": {},
   1444    "outputs": [
   1445     {
   1446      "name": "stdout",
   1447      "output_type": "stream",
   1448      "text": [
   1449       "[ 0  1 18 96 77 23 16 63 33 39 40 78 36 95 92 13 44 94 11 60 17  8 41 79\n",
   1450       " 37 26 45 38 56  3 52 57 93 24  2 64 70 61 20 29 86 80 32 34  6 49 58  7\n",
   1451       " 21 14 66 12 22 35  9 19 62 85 46 91 65 74 69 76 59 27 97 71 90 88 89  4\n",
   1452       " 81 15 67 68 48 47 43 54 51 10 50 84 31 55 53 42 75 25  5 28 30 87 73 72\n",
   1453       " 98 83 82 99]\n"
   1454      ]
   1455     }
   1456    ],
   1457    "source": [
   1458     "S = np.argsort(np.array(corrMatrix['Running']))[::-1]\n",
   1459     "print(S)"
   1460    ]
   1461   },
   1462   {
   1463    "cell_type": "markdown",
   1464    "metadata": {},
   1465    "source": [
   1466     "We saw that the first entry is always 1 if the method is working. \n",
   1467     "Also from the ranking above, we expect that large values in coordinates 39 and 17 seem to indicate that the algorithm works.\n",
   1468     "\n",
   1469     "Let us describe a Hypothesis set that thakes this observation into account, by defining a classifier below. The hypothesis set is characterised by a threshholding value 'thresh'."
   1470    ]
   1471   },
   1472   {
   1473    "cell_type": "code",
   1474    "execution_count": 13,
   1475    "metadata": {},
   1476    "outputs": [],
   1477    "source": [
   1478     "def myclassifier(data, thresh):\n",
   1479     "    if data[1] == 0:\n",
   1480     "        return 0 # If the blue switch is off, then we know that the mechanism wont work.\n",
   1481     "    if data[18] > thresh:\n",
   1482     "        return 1\n",
   1483     "    return 0\n"
   1484    ]
   1485   },
   1486   {
   1487    "cell_type": "markdown",
   1488    "metadata": {},
   1489    "source": [
   1490     "Next we find the value thresh, that yields the best classification on the test set:"
   1491    ]
   1492   },
   1493   {
   1494    "cell_type": "code",
   1495    "execution_count": 14,
   1496    "metadata": {},
   1497    "outputs": [
   1498     {
   1499      "name": "stdout",
   1500      "output_type": "stream",
   1501      "text": [
   1502       "Train accuracy:0.7748743718592965\n"
   1503      ]
   1504     }
   1505    ],
   1506    "source": [
   1507     "best_thresh = 0\n",
   1508     "best_err = data_train.shape[0]\n",
   1509     "\n",
   1510     "for tr in range(200):\n",
   1511     "    thresh = tr/20\n",
   1512     "    err = 0\n",
   1513     "    for t in range(data_train.shape[0]):\n",
   1514     "        err = err + (myclassifier(data_train[t, :], thresh) != data_train[t, 0])\n",
   1515     "    if err < best_err:\n",
   1516     "        best_err = err\n",
   1517     "        best_thresh = thresh\n",
   1518     "\n",
   1519     "print('Train accuracy:' + str(1-best_err/data_train.shape[0]))    "
   1520    ]
   1521   },
   1522   {
   1523    "cell_type": "markdown",
   1524    "metadata": {},
   1525    "source": [
   1526     "The test accuracy above is quite terrible. It is your task to perform better than this."
   1527    ]
   1528   },
   1529   {
   1530    "cell_type": "code",
   1531    "execution_count": 15,
   1532    "metadata": {},
   1533    "outputs": [],
   1534    "source": [
   1535     "predicted_labels = np.zeros(data_test_db.shape[0])\n",
   1536     "data_test = data_test_db.values\n",
   1537     "\n",
   1538     "for k in range(data_test_db.shape[0]):\n",
   1539     "    predicted_labels[k] = myclassifier(data_test[k, :], best_thresh)\n",
   1540     "    \n",
   1541     "np.savetxt('PhilippPetersens_prediction.csv', predicted_labels, delimiter=',') "
   1542    ]
   1543   },
   1544   {
   1545    "cell_type": "markdown",
   1546    "metadata": {},
   1547    "source": [
   1548     "send your result via email to philipp.petersen@univie.ac.at. \n",
   1549     "your email should also include \n",
   1550     "\n",
   1551     "- the names of all people who worked on your code, \n",
   1552     "- their student identification number,\n",
   1553     "- a name for your team, \n",
   1554     "- the code used.\n",
   1555     "- a short (3-4 sentence) explanation of the main idea.\n",
   1556     "\n",
   1557     "The winners of the challenge receive extra points, a certificate, and may be asked to present their idea during one of the lectures. "
   1558    ]
   1559   },
   1560   {
   1561    "cell_type": "code",
   1562    "execution_count": 16,
   1563    "metadata": {},
   1564    "outputs": [],
   1565    "source": [
   1566     "X = data_train[:,1:]\n",
   1567     "y = data_train[:,0]\n",
   1568     "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.20, random_state=42)"
   1569    ]
   1570   },
   1571   {
   1572    "cell_type": "markdown",
   1573    "metadata": {},
   1574    "source": [
   1575     "**Classic Least Square prediction**"
   1576    ]
   1577   },
   1578   {
   1579    "cell_type": "code",
   1580    "execution_count": 17,
   1581    "metadata": {},
   1582    "outputs": [
   1583     {
   1584      "data": {
   1585       "text/plain": [
   1586        "0.8567839195979899"
   1587       ]
   1588      },
   1589      "execution_count": 17,
   1590      "metadata": {},
   1591      "output_type": "execute_result"
   1592     }
   1593    ],
   1594    "source": [
   1595     "def lstsqr_classifier(X_data, y_data):\n",
   1596     "    x, r, rank, s = np.linalg.lstsq(X_data, y_data, rcond=None)\n",
   1597     "    return x\n",
   1598     "\n",
   1599     "x = lstsqr_classifier(X_train, y_train)\n",
   1600     "pred = np.int64(np.round(X_valid @ x))\n",
   1601     "#\n",
   1602     "np.count_nonzero(pred == y_valid)/y_valid.shape[0]"
   1603    ]
   1604   },
   1605   {
   1606    "cell_type": "markdown",
   1607    "metadata": {},
   1608    "source": [
   1609     "# Distribution Observings"
   1610    ]
   1611   },
   1612   {
   1613    "cell_type": "markdown",
   1614    "metadata": {},
   1615    "source": [
   1616     "**K-Nearest-Neighbor prediction**"
   1617    ]
   1618   },
   1619   {
   1620    "cell_type": "code",
   1621    "execution_count": 18,
   1622    "metadata": {},
   1623    "outputs": [],
   1624    "source": [
   1625     "#distance = {}\n",
   1626     "#for i in range(x_data.shape[0]):\n",
   1627     "#    distance[i] = np.zeros(x_data.shape[0])\n",
   1628     "#    for j in range(x_data.shape[0]):\n",
   1629     "#        distance[i][j] = np.linalg.norm(x_data[i] - x_data[j])\n",
   1630     "#k = 5 \n",
   1631     "#prediction = np.zeros(len(distance[0]))\n",
   1632     "#for i in range(len(distance)):\n",
   1633     "#    if sum(y_data[distance[i].argsort()[:k]]) >= 3:\n",
   1634     "#        prediction[i] = 1\n",
   1635     "#    elif x_data[:,1][i] == 0:\n",
   1636     "#        prediction[i] = 0\n",
   1637     "#    else:\n",
   1638     "#        prediction[i] = 0\n",
   1639     "#        \n",
   1640     "#np.count_nonzero(prediction == y_data)/y_data.shape[0]"
   1641    ]
   1642   },
   1643   {
   1644    "cell_type": "code",
   1645    "execution_count": 19,
   1646    "metadata": {},
   1647    "outputs": [
   1648     {
   1649      "data": {
   1650       "text/plain": [
   1651        "<matplotlib.collections.PathCollection at 0x7f122148f490>"
   1652       ]
   1653      },
   1654      "execution_count": 19,
   1655      "metadata": {},
   1656      "output_type": "execute_result"
   1657     },
   1658     {
   1659      "data": {
   1660       "image/png": 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IamMDzomTiJ44nng8w0gi8R5YS+/B0xc/CNhzcml/43VijQ3Jq4tTWG2cDMJux4jFaPzrgwS2brYM2X4TVejgAZTsbPI/fjtpU6eRNnU6o78zjWjFCbSOdhxl5diysuh4953kFUT3xGdqmjUR6Tr6IBZ30v5DRLSqktpf/wrX2HEU3PkZmh99JPlaU8RxJLsdyX6Sldgg0DraidbWYsvNw56XN6R9jEiY2vt+TeTYEYSiYKoa6QsXkn/bHSOuGkaIPAmGllz6Dd0lzadoVXqXnAuSoPXZZ9Da2rDl5JJ97fWknzM3adv7n99HZ0jFlGwA6ECdM5fNOTO5oNyOZ9bshGVsdACNj2hVFUKxoQeaaXri0SH5jiNHj5B54UW0v/zSkK9NbWgc8rZnA8Jmw5aXR9PDfzsrpJ3qfOnz5tP4lz8T2L5t4GfCNNFaWqi973/IveZ6MldfgBACZ/mYhM3UpsbkiThhg7N7TWY0SvjoEQI7tlH4+S9Q/7+/7XUp6jp5t92BLSf3zJzLMGj8y5/xb9qEsCmYmoZrwkSKvnAXksMx6L6ND/2VyNHDmJoWn7j8mzdhLywm68KLzsj4PswYIfJ+8MycRfvLL2H2CwQKIUibMeuUj+tdtATvoiWDbhMIq1Q2+pMSAzRJYW/RTD7xmfOSfJGS250yC0RyuxFC0PzkYzDUNENdp/21V4e2bTfMM+WyOAVILjeOUaNofOgvJw8MDwKhKEgeT0r3V+/JpN7y/ddfPXm6Yg9UlZa/P4V32XkpyUpKSxswpvFBwYzF6Hx/HWX/7z8Z+4t7Ce7bA7qBc+JEJFkZUu2DaRh0rn2XzrffwlBjhM5bimPpSmRXr7xB+6uv4N+yGVNT489N+NBBmh55iII7PjXgsQ1VJbBtS9KkacZidLy5ZoTIGWkskQTnqDK8y8+3fIZCgBDx9Cz7INWMZwL6IMVSpmxL+TJlrr7AGmsfCLsd38rVlkLecPOdPyiJ4pNYYP0Rv8Y+98CIRYkcO3paJI6ikHvzrYz92a9Imz1n4O36Eu1QSbwbQpaJVlclfd657j3aXnz+7JG4LA/5PvfcVsnpJG3qdAK7dlDxja9y7F/v4cS/f90SMBsEDX/8Pc2PP0q0phq1sZHavz9H9fe/k5AZ1f7WmuTsLU3Dv2njoKtdU43FtXH6o78EwD8rRizyFMj72E2kz52Hf/MmkAQZCxYPSQUwWldHy1OPEzp8CNmdRubqC/CtXI2QJKu4Z/t29EAA16RJOEeVJe3vTbOTn+mmtiXRwlZkwfzJqX2JWZdcjtbZRde69xCygqlrZCxaQtq06Rz/6lc+EHfDsCFJyC4X+skIWAiw2ci+5DICu3YSPXE8kUS7K077o+ezoWTX5914M75ly1FbW3CNm0Bwx5nPrDE1HTnDm/CZEY0m1BYMG0IgORyYuj6wj1wIhG6ctFZA2O1knLss/nfd7+4jfOhgnFy1lmZqf/0rRv2//8JRnFz5GauvI7BjW2LqoqqitrcR2LIFz5w5ND36yIArHtMwMDVtQNEuyeXGlpOD2tjPjScE7ilnXrMlWluDf9tWANLnzhuw2vUfCSNEPgBcY8cNqECXCmpLM9U/+E68PF6LRGj5+9PEmprIWLSE2l/+tPeBlWU8s2ZT8KnPJgVqPn35FH78yHZ03SSmGThsMlkZDi5fnCigZKgxMEwkh4P8Wz5OztXXoLa0YMvOQSgKx7/6FYxw6iAlioKkKMml/EL6YApcDAM5Ozvli21ixQUUsIgICGzfhtqWOlUzFXQkwpIdh6FixyL7gUi96fFHaX9zDVpLy5DV/4YFScJRWpoU1ItUnEDI8qkVZAlBwSc/TcaixRz54udIKT0AVsD0ZMdSFNyTJuNdshSAWHMT4cOHkt0Ymkb766+kdIGEjx/r9av33ScaJXhwP51r3yVy4viAQ7DnFyA5nQN+L4Qg/7Y7qP2fX1jjMgzrGbbbybn2zKY2tr7wHG2vvBS//vZXXiLr8ivJvuSyM3qeM40RIj9DaHv1FYx+lpEZi9G19j38WzcnLAFNXSewayf+zRst7Y4+GJWfzk8+v5gNexto6ggzrtjLnAm5KLL1omgd7TQ8+GdrqWuaOMeMpeD2O7EXFCCPsgSP/Fs2Yw5EyJKEZ8Yspv/7v1K9bS+hffvoePsNjEBg+CQ+SKXfyfaLVVQM+HVcHbtbDiBaUz0sktWFxB/LrmRsqJYxwVrcepQx4brUG6sqan09cOrZH4PCNHGOG5/kZ5ZcrgGzowaEEAiXi9zrPkbGIuu5sWVlEasf4NoGOozdjqnrOIpLyL3xFlzjx8fH1vlOiiwaAMMg1n2f+kPxZaaue1AUJJuNSGXFAK4TgbDbyL/t9pOO2T1xEmX/+W3aX3+NWH0dzrHjyFx1AYrPd9J9h4pYfR1tL7+YuLIwDNpeeI70c+Zhz88/Y+c60xgh8jOEyInjqf3LspRadjQapXPte0lEDpDmtLFqbmnyPrpO1Y++j9bWFverRo4dpeqH36P8Rz+NB5b0YGBAX3f6osUU3vEpJLvdSmOUZSt4dyqQ5bh1hGHE89JPCtMccHwpLWfDsApq+hcvKbZ4friOQBPWFPBM4flEZQf708ewP30MEwMVAxP5IJBcLmvVMtzJSpZ7r8806XznLRzFxXGrF8BROgrF2527f7LjC4G9dBRFn/uCteLq0wgibcaM4RG5rJB30y24xk9IamKhtrfT/ubrA16Ta1xqXXr35CnILjdaP2VJIck4SkthU+pQnJKdRclXvjbk2JO9oHBIpH+qCOzYnnJyNU2TwM7tZF148Vk79+lihMjPEOyFRVYqYH/VP02ziC4FhmuRBffuSZCHtQ5iWjKkmzfiO+98gARVwr4QDgfp58xD9/upePV5WjZvsyzdU3WnaBrC4cC3YhXO0lE4J07ixFfvOTUr/WQwTdJmzCS0dw8gQNfwzDmHSFUlakM9mpB5NXcRfsXN0radXFP/DgHFxSbfFEaHG07xpCdZcQyUbdJvkjJjMdpeeTmByIUQFN/9L1aTiIA/dcDW7iD78itxT5iAc8xYq5DINAnu3UO0vs5ySbjcw7oiyW7Du/S83rFpGkYshhbw0/n2W9Y5UuwnJInMCy5MeUwhSZR+/d+p+9191qQiBDaPh7xPfho5IyPlpG11qzrvrCcQDAsD5KMLxD98rvoIkZ8hZF10MYHtWxODVzYbaVOnET56JMkqF3Y73sWDpyP2h9rclHKJasZiVjFMN+wFhWQsPpeujevjBCHsDlxjxuIoK6Piv7+JEQpiDiCH2jM+4XRhdHUOOiYzGkVtbCD32uvpePftk5O4LFsFHbHY8AjfMAhu24q9dBR5N9+Co7AY2eMhfPw4NT//MQ5VZXygkvHhWmzdTR0cqsrqls3IpzhRDRhj6DOmoSJVQY89P5/yH/2UyPFjRGuq6Xzv3V5jQAiEaeDfsI6MufMQQhDYs4v6397Xu/TvdrVgtydqvQx6TWErF9s0aH70EbrWr+t9piQ53tWoP7zLzx+0ktKWm0vZf34bta0VU1UpmjqOlhZLqtg1cZIVPO07brsd73nLhzTmDwqec+bS+tzfk1UbBXjmJNd8/CPhH3ua+RDBUVJK8V33YMvPt8jKZsO7cDGFn/k8RZ/9gkWMNqvIp0cFLuMkeeWpzpGqv6JwOJKyYPJuvY3CT30G9/QZuCZNJu/mWym++1/oWPMaenAAEu8+tnA4cJSOwrf8/CGNqyc1sHPd2pNsKOFdtpySf/l6/F4MF7HqKur/8HtEd1qd5HSSNm0GAFNCVSj9OvPYTKP3IZck6xolCeF0IZzOAVdLZxRCIKd7aHr0YYL79yWk0hmBAOFDhwgdOGB1T+r5zjS7pWvrqfnFT4nU1lJ3372J/mvTxAyFLIt3iAqYkstlaY//6Q+WXG1fw2AAEhc2OxlLluLftoXae39J7a9/hX/b1pQrSltWNvb8goR4QNEX78J3/kqrtkFRSJs+g1H/8Z8o6RlDGvMHBXtuHrnX34iw2axepjYbwmYj98ZbsGVn/18Pb1AIc6AEzbOAf5bGEkYkjFBsCQE6rbMT/+aNaH4/aZOn4Jo0edgNJkzTpOr73yFWU937AsoySmYWo7/7A6QhkGPFf32TWG1N0ufCbid97jxLp2X6TOzFRVR+6/8NaVxyZha+lavpWvceakPqgBiSROZFl5Db3a8xUlVJ1fe/E08hHNadUBQKPvkpJLuD+t//bkgpfJ6587AXFZM+dx6K12e1TIvFaH3pBdQU92NIkJWTKk72BoQFYCIcDtyTplD0xbtQm5qo+sF3MFV10ECrsNlxT5s2eGrkUALPQpB9xVV4l53HiW98bUjFXMJmw3fBRWjNTQR27exd4TkceGafQ+GnPpNyv3+k93G4UNvaCO7cbr0Ls+Zgyzz7mi5nvbHECIYPqU+z3h4oXi+Zq1P7GIcKIQSlX/0GLc/9na4N74Nh4Jkzl9xrr4+TuBGJ0PrCc3Rt3ABAxsJFZF9+ZTy9S/F6UxI5pkn2lVfHu5zX/e43gw0kgTT09jZan3rcssz7Bvr6QPH5yLqgtwLPOaqM4rvuoe63v4bubjJDJnNNo2vLZkK7dw25gMlZVk7mhRfFfZ3uqdM48W9fjTcxHi56iq7a17yeLMhlt+MqH0Osob7P8a37ZUajBPfvJbB9Kx3vvmNlM52EgE01RvjwSUTqTBNsNhylo4geP5ZyE/f0GWRdermV+mhTTk7ksmxl29jtBHbuSJgwzWiUwPatRCpWD9roOlZfR9fGDRiRCJ7ZcyyBrlPokPVBwpaVdUqaSv+XGLHIP0IwDYOq7/43sfq6uMUuFAV7UTGjvvlfCEkiuHcPdb/9daIVK0nYS0ZR9s3/jBPd8a//K9oAuduSx2OlK6ZCCstQcqdR9p3vY0uRKhZrbqLt5RfpWvve0C9UkqzzDKcKVZaRnE6yr7oGIcm0vvgcevupdd9UMjPJvfFmPHPm0vzEY3S8uSbRXy5Er3LhQI0YikvQ6mqHHicYYqqnsNsp+NRnaPjj7y3Xh6Yh7HZc4ydQ/OWvIGQZPRjk+FfvGXq6pSRZ5+5/fkki56pryEqRY52bm86Rp1+g+dGHExpLeGbNoeBTn/mHJ/MPGqdrkY/4yD9CCO7dQ6ypMcHvaWoascaGeKeYtGnTybn6OiSHw/IRdxOE2lDH8a9+heDePdZ+g7WwHIjEISXZmGqMjrfeSLm5PTePgk98EmWIKnjWAIzhSwnoOkYwSPMjf6Pp0b+dMokDaH4/4WPHrKbI138Myd0vc8Q0E7XEUx2jtsYKLg4VQyV8w8A9fiKjv/dDsi+/kvTF5+IoLiV0+BDHv3oPLc89g+Rw4F2+IknaYVCkytowTTR/6mdB7fJbJK72itCZ0SiBndsteeURnFGMuFZOA6Zh0L7mdTreeA09FMY9YQI519+Io6jotI4bOnyItheeI9bUiLOsnOwrrsRRkpxX3h+RihMp09jMWIxIZQVp062gYObqCxhz9SVs++I9aLFYvPBGj8Wo/fWvrIDPaciUJp1fVfFvWB/3j4PVGLn5iUfxb97UW603BNhLSlCbWzCjgzeYHngwZ0AbXdPoWPMajsIi3NOmn7TZ9YDQtQFdUacKyeVGSktDltLxnruUim/9R9x9o6sq7a++QqSiAkNVe1dlQiBcboQkLAG2/pNGdxZNEkyTjrfW4CgbhbdfPUTHzp3WtfUvkotG8W/ZRNrUaWfsmkcwQuSnhaaHH7Ii/90vRHDPbkJHDjP629+L+5qHC//2bTT88f74MQNtbQT37qb0G/+Bs2z0oPtGu/tmJkGWk8YTrqpGD/iTCVTXLcXEs4DOdWvpXPceJpZ+h97ZOWRL015cTNm3vk2kqoqan//4rIxvWDBNGh96EMe4cac3MRiGNWl2yzecDoTdTu7Hboy7xzreehOjX5qnqapWa76+xCwEkk2h6Et3U/OTHyUpfyLJ5F7/MZoffyT599J1Gv/4e9SGBrKvvDruMhmwElcIhHJqGUsjGBgjrpVThObvouv9dclqbqpK2zClYOP7mibNj/YTUjJNzFiM5qeeGHxfwyB48EDqL3UdTz/t81hb+8B+Sl0/syqIkgSKQtMjfyNy9AjRo0e6+1QOI14iWfnnzvLyYXdpOmswDKKHD5/2YTxz5g6o7jdkSBKFn/1CQqVw5MTxgSeZvuczDIxoFLWpCe+y85JTMk2Dlr8/NWDBDED766/StX5d/O/MObNT/r7CZiNj8blDu6ZBYBoGgZ07aH3xefxbNifJY/yzYYTITxGx+nqELYXVoetEBsgaMDUNtbl5wKW4EQ6jdXWl/C46iOgQdOuEDPQwdwsM9YVn3Njkwod+EDZbPLf8dCCnp6N1dmDGTl1uNlZTTaSq0vJL33jzaY/pHwamaWWknCaRS3a7lYfeB/bikiH/fmYkgtrUiJyZheifP2QYlstukOelp3q1B7LTSdEX7rLqJxyOeB1F1iWX4RozZsDjDAV6MEjlf3+T+j/cT+tzf6fhwT9z4t+/niCsZqix4WvZnAXEGhpoffEFWp5/lmhN9Vk7z4hr5RRhy8lJvRSWJOyFyT7yjrffpOWZpzB1A0yD9AWLyL/1toQlqGS3W4p4KV6Y/jKo/SHsdhSvD629Lem7VJK59qxM3JOnEty/d0CrTcgy2VdebVW7DZrnbBv0e/fMWfiHk5WSCqZJ6wvP4TvvfPybN57esf7BoHV1nrYmuWmaSLbEyTpz5Sqr2rbv8zRABopwOLDl5dP44J9PuVmI7k80QtKmTmPMz/+H4M4dGLEYadOmn5HCmpZnniTW2Bi/LjMaQVdjND74ANmXX0HjQ38hVl+HUBQyFp9L7sduOq3WdKeK9jWvWe98dwPy9ldeJvPCi8i56pozfq4RIj8JwseP0fL0k0Srq7FlZ5F9xdV4Zs/BlpWNe+o0q+N9HxITikLWRYniOoEd22h+8vEEl4l/0waEJCWIAAlFwbtsOZ3vvZPU3zNVilcP6luDbDvUTLHLR1oKIvfMnZ/wd6yxga3f+ClqMIggtbYGWJnPvpWrCR8/RnD7tgHPf7I0tsiBA919Fk9v+RvcuYPwgQODEk21K4/ccBtOtG5JXAkE1DlyiAg748M1wys+OgMwAb/swqOHUy+Bu3O1UxU2BSUHAhOHoRKWHdQ6chkbqkHp96spGRnYS0oSPtM6OlDSPGix3mci7Zy5xKqrUJubewlelrFlZaP4fAhFxjyVn0kIXOMnJH0su1xxpcYzBf+WzcmrA8MgdHA/oSOH4u+jqap0rV+H1tlB8ZfuPqNjOBnU1haLxBOUFGO0v/Yq6fPm4yguGWTv4WOEyAdB+Pgxan724/gLFg0Fqf/D/5J388fxnruUws98nubHHrECnrqOLTeP/I9/IulHan3xhZS+9K4N71vWQp8uLrnX3WDJ365/31oWmyZZl1xKxpLUfsWXN1Tw3PsV2NQIX6irSLlNYNsWslZfYJ3XNKm995eobW2JVpkQvWQrywhJpvDOzyDZbKcsFWp2/6e2NA9pe6N7+wGdAaaJERm4I8yBtFE8V3AelzS+z9TAcV7NW4SBoMGZQ6vdx6hQPaMj9djNM+j/HwIE4DA0ApKTDCPRrWYAkhDIGRnoHR3xVV5MKDyffy4n3EUI6FZ2tMqmVjVvZpb/CFK3/ICckUHRXV9JiHmorS3U/PJniVlMsoxaX0fpv3+T1meexr9lEwDp8+aTc831lnjXYO42ux3JZrOyYFLkzef0yUrqD8M0eWtbDWu2VhOKakwty+La5WPJ9SUXz50UA7mhui3fhE1VldC+vahtrdiyPrgy+8DOHSk/N3UN/7atI0SeCkYkTNNbW+mob8E1aXJKV8KpoOWpJ5MJOBaj5aknyFi8BMluJ/+228m75eOYqjqgOH4qdwcAQqAHgwlELhSF/NtuJ+f6j6F3dqJkZQ24LGxoC/Hc+xWUdlZzRcN7yKRenmstLfF/x2pq0No7UqaY2QsLcY4Zi5yegXfJufGmu545c+l8683U15ACOvBe5my2Z05CFQo5aicXdGxnVNfApfAmsNdTjjBhSrACCXNolnO3ro2pabyUfy4SJpXuAlrsPg54ytGk3ke81pWHRX1niMgVxdJtEZK1SjDNAV0kQcVJhbOA2f4jCdclAYamo4UjVhecBkv87OW8RZxwF6FLfV9Ra8838hawJXMKM7qOctn8YnKuuT5Jg6fjnbeTXX+6jtrcjNrQQP7HP0H+xz8R/0rzdw2ulaMoOEtKKbrrHvwb1+PfugWtowMhBK4JE8m69PJB9br/9vph1u+pJ6ZZ92fLwSb2VrTxvU8twOcZXts/z9z5VmC1n8tI2O1W/n4/CEVBbWr6QIl8wEQCcXaUFD/0RB4+fozaX/wUsJq0DtZ9Z7hI1WcRrInDCIWQPVbFlZDllGJWPXCOGUtw185kv6TNhuJN7fuWXa6ExrWpsONwM2nRAFc3vBNX/EsFe2kpneves1T2GhoGDDoKxUb+rZ9I+Kzj7TdpfvLxQcfRH6/mLuJAei+Jtth9PJpzHjdHX6c0mmid99yRDnsGb+QtJCbZ2BidxtK2XZSFG7AZGprHizPclTLY5poyFfeEiejeXJQ3m7m17jXStRDrsmYmkDiALmSeL1jG1Q3vIJv66Uf6NY2MpeeRuXIV4SNHaH7q8ZR5/CoSG33TyI11pJycJEwIBlBDVou/iGTjSNoo9EEKhjpt6WzInc0d169I+b3aUA+6TkhysC+9nJDsYlS4gXKzHa21Ffp0v9L8XVT+97fQA8FE7ZjuFaGSm0fWBReSsfhcJJuNzNUXDktuojMYY93uejS9d5IzgZiq88bWaq5bPvROXAC5115P+PAhK4AeiSAcTiSnA/eUaVb8pL+MsKqmjFudTXjmnJPyvRGSZGkanWF8qIncNAzq7rs3IQsk3n1nyyYyFiw6reMrWVnEalNImXaXew8VOVdfS+jA/gTpVmG3k3vdDYNOACeDEIIpXUcRJ8l4CB06aLXvGqRHprDbSZ+X6EsPHTyQ5Nvvc/K4vkffGEFIsho69CchU0g8XryaT1c+i9uIYCKQTRNVknm9cAkXXTwP6f1mUA1aHZk8W7gcAJsi8a1LRxG+94fJy36bjVhFBZFuHZIvxjQk00DGJF0LIRk6Rr9xHE8r5v5RV3FR0wbGnUKzif73wJaXj6OklI6330pdjAXImNQ5slElhViXgt0cPCUwIjsHiVz0wuMe2JJ1TZjIgaONPJG7DLO76cZW3ySKoy18rXRU9+lMYjXVtL76iqVznyTfKjHm579E8Zy8RHww1DQHsCkCrd/hNd3kSM3wtW5kj4fR3/k+wd07rdhVfj6eOeegd3VZvUP7XIew20mfv2BAg+lsQfFlknfLbTQ9/NeEz3OuuS6poccZOd8ZP+IHiGhlBUYK6zLefec0iTz7iitp+NMfkgKPvhWrhtV6zFFcwqj/+E9annuGyLFj2LKzybrsCjwzZp7W+OZMyKFDC6OkcKkkiFB1i1INBiU7G/uo0bS+9AJyWhrpc+fTvua11CQuy+RcdS3pCxbi37zRmigOHsDUNDptHiRTR+/v6RYCDZkHSy/BbqgUR1vxK26qnfkgBKGDIe65YRb3PrkTYRjokoxumNy6egIlk4toOu98Ot97t3c1YbeDpsUzJTQkKt2FRCU7ZeF6pncd493sOSmvNaC4OZpWcvpEbpqE9u5GW7ickD3NcrX0c2dYv4HJitZtPF20giVtuwhLDnQhaHJk02bPoDjSzKRAZXxV5dLCGCfRIrHbJC5aYFX7tnVFqG0JkudzkZ9lyQV4Fp3L37cYqFJv8Y0qbNS68tnUYLBYbqL2f36O1tExoDa8ZFNQmxpPm8hzvE40PcXxhaAga3iNMXogZBnP7HPwzD6n93jZOYz692/R/MSjhI8cRnK5yFy5msyLLjnlsZ8OvOcutRIidmzDNEw8s2efcqHgyfChJnLTMLrFQVNgAG3l4SD9nHnowSAtTz9lEYgQ+FasIufqa4d9LEdxMcVfuOu0x9QX7qrDZBhhYiLZyjuZfzmB6BUFxeuj7n9+gampCEWh+cnHUbrlO6NCYatvMgc8o7GZGks79+Hav5fA3j0cTS/lUGs6s3GRLkKk66EkK7h3UIKw7CKsuOm0J1pI9TUt2B58ibtqqsEw0POKKbrjTnzjrCVx7sduIm36DKsIS9dASAS2bgagzpHN40WrLK+6sDJVlrTv5nOVT/PbsmsxU4ynznFmXij/4SM8+Ls3MSQ3d+gmqWoWBVASaUIXMi/mLWFe5wFez12ILiQ0SWFf+hjWZc3kE9Uv4zaitCoZGAM6fkwUTBZnmyyfnMUfXtjP1oNNKIpA003Gl3i565oZ1Ad0DIcL1MRJXkVi3e46ch78G0qwc1D3kqlpZ0QzPD/TzbhiL0dqOhIIXZEFF8wfddrH7wtHcTElX/nqGT3m6cCWmfmBKCl+qIncObo8ZcGDsDvOSPUYgG/ZcrznLkMPBpBd7rPTaf0U0bVhPeP8VWhI6AiG05PdQPBI0QVc0ryBbDNE5PixuPVtxmIYCI6EHDRmz2KHZyxh2YEuKczqPERpoJbQAR0BFHCQIsw4IdgMjcmBSvZ6ylPrcwxgaX6s/k1i0Zb45CI31tD4ix/h+cGPrbQ4IUibOo20qdNQ29qo+Na/A1avzieLVhKVE90M6zNnMCrcyKyuw+zw9Wt9JwQufWDp3OFI6mpCwhUNUO3K56mCFdxYvyblvlHJTmasi5vr1vBw8YVEJVv8XqiSDb+QeC97Fhc2b2JT5pQB75Ns6HzhxFOkVQmObn2aI0UXo0ppqN12y+HqDv625hCr55YOGC621VVCKDh4jECWcYwqw5abO8Q7MTBi9XV8TNvH07jYL3wIIZGZ7uATF0+iOCfttI8/gg95ZaeQZYo+90Wraqw7s0M4HLgmTBh2951BzyNJKOkZ/1AkDiAk60VVMAYm8RSEoCOocBdS68rlbyUXYebkJ7hQIpKdP5VeznM5i1nrm05AcaNLCjZDZWXLVmymHqcIpQ+J9+CSxnWk66EhVysWhpvIi7Yl0I4AdFWl9tXXErZVW1up/Pa34q3zqlwF6CL5MdaExK6M8cztTK3jPct/ktL6/vetp7tQPyimTnP36qIyrZCd3glJK5KYkNnincSC9r1oQqLZ4Us6viFkDnnK6JLdHMoYuPLREBIPl15EWDOQImGWNyQWR2m6yab9jRRku3E7k59XuyJBODig60ZHYCo2nOVjKPrSl5O+N02Tjnff5sR/fIOjX/4itb+5l9hAzUSAwK6dVH73v4msfYtLD73AV6qe4u6ONXz/thlMGZ014H4jGB4+1EQOVgfv8h/9jNEfv4XMSy6j+Et3U3z3v5xWEPHDgozFS+Itz5KgKFZbrTnnYC8pwUAQEzJRodBp8/By3hIQErrdyWFvInG8kz2Hdlu65V8VIk46hZHWlKTZHxJwR/NbeLXAAGRuIkwDux5DMTTGhmpTpk4qpkHzoURpgtYXnkMPheOkr0pKat+akIhKNtL0MIqR6HaSDZ10LTSg1S2ArrRsImk+kBWkgmLKvvgFK020DwHGhMJW7yQicm/g+43sebQVjAFFISbZ0ITM3vSxtCnplESaUEyDgex9yTR4qmjlAKOyYAqJDiWdjb5pSJiMCdXyxRNPclPta5R2N5k2rOJhvnTNdFwOGYdNRpYFdpvE+FIfjWn53eNIREzIbM2aStNNX2bUv/2/lG6VlqeeoPnxR1GbGjFCQYI7d1D1ve+krBUwDYPGB/5oGQndaZlKNIy9rYn2109Nj2gEqfGPZWKeIpSMDHKvuAzbP1ljCffU6WQsXEzb+g2ogFNYMYPCz38RZ1k5ksOB5HBgmiYv/uJBTrREaLelU+kqjBNSTIfw6AmYxzchulXvDnhGp/RzR2Q70hCt7AyHxMVNG3iiaBVGP+KyCbi6bQNaNEZWrIscNXXmQkzItHoTI/xde/ci+pDQqHADRorJxWaoTApUYjdUSsJNVLoLMBFIkiAv2kpedIDcfqzA6XvuiezNGGsdS5EQawKsXnEHi5q3Ez6wD8Pp5m1pDDvSxsb3UwyNi1s2kR2sAMDhdvFGzjyqJS/XVL5Gmh5C6h5zpasAs8+4ZdNgbHkeB+qCkCIw2Be6JFPrzEEVMrKpk66HSQ+HKap7k+fylxIePRmHXaa8MIOff3EJ2w830xVUmTjKR2G2m3vu7WC9bxoLO/bFYyuqkOmwpbMpdxbnTkiuw+gKxXj01QNsP5IJJdcyKVDJipatuIwYRixK26uvkH/rbQn7xOrrU4pZmZpGYNs2cq8euIBoBMPDR4LI/1kR0wxezJrHpvJRmKaBzy74xEUT8UwuTthOCEH5NVfw8tO7iWqJJOGwyUw4ZxLhExNQjh9EMbUBPe1N9kz8iptMtSthKdffp2woNvZOPp8X6+29dnb3BGAzNW6d6SHaMpPSdc8l5L/3HKdd8fB04fm02H0QEbx9/wY+e8VUSj0Q1KCvV9VpqKxs2cKbOfPQhYQpJGyGSmGkhZJwI1Fh49qGt3k5bzGFy89F9ncy5+W/DmiNG0C9M5v96aPjn6ndRSxrjgWxLbyAKz79WQDefn4f9iPNaDEVm6FxedP7jA7VI7qvyQz4WRVbR2zSTBS9dwVwaeP7PFx8ISHZiSGs0idDkjnUEMLltFHmc1LXEsLrsdPUHkZP0VXrvJYdSbUDNlNndetWfJ+9qvf+2BUWT0ucDFeeU8Ib20zqnTmc03kQpx7joKeMfVkTKC/Nprww0RLXdIPv/2UrbV2ReIHSPk85dc4c7qx6AckwCB87kjRGyekcsEBqOOm7Izg5Roj8HwCRmMaza0+wYW8DhmlyzsRcrls+Do9rcN3m/31uL/tPtKMZFgW2RuG+l47wzWwvJXmJKWNTRmdRkOOhrjmI2l2YIUvgdiiouknuHZ/hwT+8Som/Do8eoq1PMC4OIXiiaCW31LxKut5bKm9CN2ELIoqLgls/zssbo2hSYhk3pokqJKpt2RROKWbX7n3M6DyKgk4MmWZHFk49ygNll1tZG93nb2oP86O/bOZTNS+QFgsmTRyzu45Q4Sykwl2ATwsyOlRPTFL4c+nllIfruLRpA8suW8yCRRN58GePYQ6gMGMAL+Yt4WB6eUorP6YaHHxrA7PXP47W3s7l4yewwPBjO7EHYZpIZv+1h1WM4qw4nFBLmq6H+UzVc5xwF3LEXcIu7wRMIKoaxNQYaU6FX9+zFCEE33tgE7bj+8mNtNNhS+egp4yScCPFsRZSwasFGZs/eErfdcvHkpFm5+WNCk+nFSMkQZpTYfXsYi5dNDpp++2Hm+kKqQkLBUOS6VLSOO4uYly4DnteQdJ+tuxs7MUlRKsqkwg9VltD54b38Z7BWNY/M0aI/ANCOKoRimhkpjuQpN7X3TRNfvroDqqbAvHUrPf3NHCgsp3vfWohNiW1T7q1M8L+E+1xUu6Bqhu8sqmKT18+JeFzSQj+7eY5vLD+BO/vaSAc1dAMk0BY5YGXD6DIEuOmTGRrRR6xfilrNkWKW6UBxY3d0JICkzGhcHTOhZx/2xXUNQeRpT3JgxYCkNmws5pP1r9Gob/VqmoEnOgURFvZ4pucQOI90E2TzWnjWR3Zat237s8bHNm8lLfYst6FoFFx0ujsLcU+5BnNkvQgixZOAsAroqRyqptAnbeU/Rljk77rwczOQ6xs2Uq42xJWmxo5qVKIaaYU+ZIwKQ03st07KcHFYgKtXRHqW0Pku+DGw08TaW3DbmjEhMKKli0Jweb+EA7HSYPyQggunD+KC4eY+lfbHCSqJqfzakKm2Z7JeK2ZrIsvTblv0RfuovpnP0Jrbk5qcNH00F9wFBTiLD89WdsRjBD5WUdM1Xnw1YNsPdiEJAR2m8xNq8azaKplwRyq6qCuJZSQX6sbJl1BlW2Hm1g4JdnSAWjpDKMogv7vl2lCQ1sw5T4Ou8x1y8dRkJXGw2sOYxgGBmb3MXRqm4PcOQFatmwnLDnomjqfjLwcCrLdvL65mrrWICX+xpQkYjc15sZqkI8dQIrI6IOIL81s2YvD3xYn8R7YMMiJdSAwk1LnDCHT7MiM/y2ADjmNR4ovSCh66Q8DgVJ5lNp7f4V76jSmHF2XcvyGkPBceyP2Dc1JExmAbOqsaNk+bMEtU0jYxowndvhAUnGVACpdyb+vJASRmE7dg7/DaG6iR2nHbmrYBnOfKzYyV64+41oeBdluHDY5icxtpk6uw6Dwti/iHD065b62rCyKPv8lqn/w3ST1S1NVaX9jDYXdrqoRnDpGiPws448vHWDX0ZZuojaJaQZ/eeUgPo+DyWWZVDUF0FP4EaOqTmWDf0AiL8xJi1vJfSFLgjFFg5cjv7OzNqWF1dERRDvwGmODLZYYVeNu8m67A++0xcyZkMtza09Qs6EeZYAS89De3YS7ZUTTii9DtaUnWJuSaeDUo0zxV6SsRgXIiXWk/Fw2dIoiie6E7ZmTkvRUUmGjbwoX7dlEaM+uZNcHVh537ufuYtLsKRwLHeXd7ZWMDdTijgWod+RQ58whM+ZngNKzAWFgBRH/EBrHTRltpLf0NhYwgYiwpUzqEQLywq3Upej4NJAlbgKe6dPJvvLqYY1xKJg7MZcn3z5KTNPj45UEpHvTWP31f8WmDJ4hpnd1pZYxNs2BBeVGMCx86NMP/5HhD8XYeaQliXBjmsFLGyoAyPU5UeTkn8Fhk+Ll1qmQ4bazbGaRlRfcDYFVun3xgsGXzLqemkSFYaD1ELyudy9/H8SIhHHaFT62cjyfXjl64Jz17u7xQtf5WN2b+NQAsqHF0wyXtWzn85XPDDgRAGRqQUrCjf2Oa6CYOud0Hkz4uN3hO7lGohBWls5AXwOe4gLy58xACMFV0zO4uG07UVMQkF1M9R8jO9pBi93Lr0dfz6s5CwaYgnrPFxUKYcnOkbRSHiy5lDYpjfszlhLrYzcJwGFqjNZb4r+hJKw87zsunoz/nTcGv65+0IVE7i23nRVlPZsi883b5jJ9TDaSsFYMM8bm8M1PzDspiQM4y0anbMIibDZs+QUE9+6J1wWM4NQwYpGfRXQGYihyslgQQEunJfQ1Y2w2aU4bMVWnJzlBAIoisWDywLKgADevnkBBlpvXtlQTimhMGuXjuuVjcTXX0PTSJhCC9PkLk1prLZxaQH3b8SQXgmJo5PaziIUkEzp4EM+s2QD4t24Z0rX7tACfqXqWBkcWEclBYbQFp2FZZB4thI6UMndcANfVvcWvx9yAZJoYQmJUuIGVLVvjAdaeaaQo2MAJR/5JrfJ0LbWrqQc9PUAN0+SP//syTsOOVwtwwF3GIU93Kp4QaLKNnd4JVLnz+XTV8ymnEF1W+EvRpbTZ+2V+CJnnCpdyaeN63IZFWnZT41OTZQ5PmMDuY6340h2cP7uYopw0ql4YuqUaEwr7feNwhiTG+Ia827CQleHknutnYnSb5NJJtGD6QvZ4yLrkMtpeeanXvSTLmJqGf/NGujZvAk1FstsxolEcJSXk3ngL7gkTz8alfCQxQuRnEXmZrpRNdSUB40ss94csSfzHx8/hzy/t52BVByZQXpjOnZdOweUY/OeRhGDV3FJWzS2Nf9b85GPUvP1WfBnb+d47ZK66IEH0f8WcYnYcbaGy3k9U1VFkCaFrXNG4NslvDd29O3v+PYzqVgEUpsjX1pFodmRSHG2hS0ljs28Ktc5cstQuFrbvxasGyYt14NKjXNnwXkq1QAHM7jrMFt+UeNohYAUJ+pCMzVBZ2LFv4DHa7XFJ1v2/+T0rajYjTBNDCMK5dg6m95MaEII2m5dHilaTqfqZ4T9GScQqhjGBDRlTaLOnpziR4IS7iAdKL+PO6udxGiqGJKOkp7N0ZhFLZ/bKrNY2B3hUmUqwqJTR4QbmdB6Kk39fmECXnMb6rGkcypnMvH7capom2w+3sHZ3HYZhsmhaAQsm5ycE24eL4RB4X2RffiWO0lG0v/E6ur/LatVmmgmKkUbYmqijVVXU/urnlH79Pwb0vY8gESNE3g3TMDAiESSXa2BR+GHCbpO5Ykk5z71/Im79CmF9fvni0fHtMtMd/OuNs4mplg/SYT+1qtRoTTUdb72FqfYG1cxYjPY1r5G+cDGOIossbIrMT760lDUbKth/tBFnUw2Ta3dgjzYlHC8i2QjbMhg1treFl3fpMoJ7dp9WI2WEYId3Io3hTN7NOQdNkjGETKMji8Npo7i64R3abem0KR5a7V4Kom2YmGhCTsjYcBoqt1e/xLvZszmWVoJi6tiNGB2KJ+6DX96ynTGhgVUOsy69grSp0wgdPoS8azOyqWMCjfYcTqQVD6h5Uu0upNrMZ3/6GBa27+Xc9t0IoDTcgM2YkjIAawiZsOxgV8Z4FnTsRzPhZ/tkbp/SzsRRViB37/FW7ntmDzHNDW439c4ctnsnckf1iwkpn2AVLv151GVEZQcZNpmygsQJ5C+vHmTT/kai3c/ekZoONu9v5MvXzThjz/hw4Jk1G8+s2fi3bqHhwT+l7nnbDTMWo/X5v1P85a98gCP88OKfnshN06TtpRdof/UVDDWG7E4j59rr8Z679Iwc/+KFZeT4XLy0oYLOQIwJpT6uXjaGvMxk/7fddnqyAoFdOy1lwH7QdZ11T79BweWXMaUsEyEEsiwxM1/Bd//vMcJhy4Lvfrk1xc5ruQvY7x6FYlN48LcbuOrcclZNySKwZxdmDwcIyaoFHwSpBKgkTI6llXA0rYSYpFjHwcrw0ITEi3lLME2TyxvXkR9tjStc1jtyWJc1g5DsYnKggnkd+8nQQ1ze9H7C8YOSg5DiwhfrGjCoCoDNhuSyClM633sXydRRhcwTRStpcGSjCjnJwreuW8SvXxMSGzKnMd1/DK8WZFS4kWmdR9mbMbZX4qAPNEnhuKuImV1HeC5/GY2qjV8+uYvv3rmAHK+TB145GO+iA6BLCmEhsTZrJpc09+qqmFgaO9c1vM1bRedyxzXnJVjLNU0BNu5rTDiWiISw7TrMIe0oo5fMPWOdtIaCUESjuslPRpoddzg0pGbT0ZqBO0qNIBEfSSI3DJOjtZ3ENJ3xxb5BLdy2l16g7eUX47473d9F0yMPITmdp93Jo6EtRFWjnxyvi/+6fd5pW0GBsMqL6yvYeqgJh03m/DnFrJhdEl8qi+7WY/1fEt0UHKz189TTu5lans0Xrp4GQMuzz1gNBXq273YDvZG3gIOecnQDdM1qYfzMW4eJPbOVie1H+jQgMHsbTPRBz1+i+z+9+189Qk0v5S0mIjtSkyQQlp18rvIZPFpvs2JdyLyZM5em7hzxjbZpHPSM5vbqF5IaEacZUdJiUcIoHBu/mOmdh1GbmkiCqhLavw/Z6Yrrmr+fOYM6R06/FmuDQwIq3IXM7DqKAC5s3cIFrVuoc+TwSt5iWhy+PjfHpMXh497yGzCE9VzqusnbO2pZdU4J4WCYhW37mNF1FIHJnoyxbPZN5WhaKWbzxvik1nPXSsLN3F7/KuW+xE5B+yvb4/5sgLJQPdfWv2X90WhSvfY10ucvJP8TdyCEwIhG6XjnbfxbNiI5nPhWrMQzZ+4ZsdxfXF/BC+srUGSBrptMTDe4NEW1an/Yi4pPus0ILHzkiLyioYtfPbErbokYpsntF01i4dTkND7TMGh/9ZWUfTlbn/v7KRO5phvc//w+dh9rRZYEpmn5y7964yzS3an7b54M0ZjOdx7cQkcgGs85f+qdYxyr6eSzV1rEnD53Pq3PPpMyp+SQp4yoarDvRBs7DrdwUV4Gwd27kkhfFTJ7naX0z2xUkVjnGsfElj6ZI6aZ0uLu/3eXksaujPHEJBuHPKMIKoNXHkoYuPs1zJBNnRWt23is2GoirUkKnbY0mh1ZFEZbk45hAm12L7typzH7onPZ/9ATeENt5HUHc3WEJY61dy/B/ftBUxHAnoxx6JKCYmhM6zpGhhbk/ayZGEJ0+86Ti5UwDWxGsh58YbSFW2tf4f6yqwn3CGsJkXT9umHS0BrErkhcW/U6BdHWePn9ora9jAvW8Lfii6i3Z1EY668SaYKm0fn+OrIuvCj+eZpTQZYkNF1HNnWubngnIQdei2ns3l1BxprNzFg8g6af/QC1sSEeW4lUnMB7+DB5N90y6G91Muw43MyLGypQNQO1+xbt7xSML5zOxMa9qRuXYMUusq+48rTO/c+EjxSRq5rBzx7bSSiS+FI9+MpBygrSKcxO1D42olEMNfWDpLYlk8NQ8drmKvYca7Ue3u7P6lqC/PnlA9x93al1BVq/r56uUCyhcCimGmw60ITbdYibVo7Hlp1N3sdvt1IGEaiagcDk5dxFBLrJI6rqbNrfwEXnjkFyOtG7uhLOE5UGnmgCJyHgVAhLDvxKGnZdZYtvCqYAux7DFIJpXUfZmzEuyZ88pesE9n4uEUtsqjHBilclGx2ym0KSfysBZGp+uoJRvremASlnEYZhkh9tZVXjRrL0gEVs/aouNSGhGBq31byMT/VjN3XmdB7keFoxXbKbtdmz0UW/10YIxgST3QASoBg6szsOsSVzCrKpE5XsCbn1Pdh5tJX7fvF3Lou2JWio2NDJjnUyvesoebH2lPfYjMXoWr+OSGUFaZMmk75gIXMm5PLwGkuqtzTciOgzu9c4c3mqcAUGArG9i0lrH+bClkakPnneZjRqBcovuAhb9qk3LX5tS1VSdpRumLzgnsHcO87F2LoBPRpBdjgIHdiPEQphLywi7+ZbcY0ZuMp2BIn4SBH53uOtGCmWbJphsHZ3PTecn9jkVXI6kd1p8WV1X5zOsu7tHbUJvkmwHt69x9uIxvSTBjOjNdW0vfYqamMDrnHjybzgQg5VdqSsOAR4b2cdbV0R7r5uJt7FS0ibNp01L27k3WMB2mRPUnpeT9m/b8UqWp55KsEqSiOGXYK+U6Fk6kwIVDHJX5F0bq3bsu3v3jCBt7LPYbt3IoppoAuJIq2dYpdJXu1+xgVrsZkaErDTO4F4K2QhOL91W8rr1PtZw7KhWy6aAWAzdTr90e7rl0Gy/OwvFC7jtppXErbtUDy8mLeYqGRnTsfBOIkDOE2NKYFKAFxGjDW5C5B6YgMCxkkBYmleHIHWpNWIgsGi9r1MCxzHpwZ4puA8jqWVpCTzTH8jcorKUbupMSVwgtfyFrK6eUvKLJ5YXS2x2hqCO3fQ9upLjPrmf/GVG2by66f3YI9J9PhkVCHzZOFKonLvhF3mr0FKZdBIEuGjh7FlD61lohGNWo3I+2Q2+UPJ8gQAsixQyyZQOi+xHZ9pGGclF/6jjo8UkQcjWsp0P8Ow/Mv9IYQg57rraXr4ocS+nDY7uddef8rjGIhwwdJCcfTvZ9kHwX17qfvNvdYS1zSJnDhO+1tvMHrepWyXMtCMFI0iDJP9Fe3UtgQpzHLzm9dOcLDeTtTmS9rWbpM4d4aVveJbsYpodRX+zZsQsoJp6DiKirlh5Xj+9nYFmmHi0KPcVvMy6Vo4iUB0BGHZicuIYfbT/zjsLrUIWlLiglH1rly8SoDl3aQIsLplC0vadlPtzKXaVUBAcRFUXLhj0YTjaUhW16E+EJiUD5KRctxdlDSJ6ZJMm93bO3FgkdtfSy4mLFt64xODVQOW4s/0H2NisIoKVyGKqVNutDP67nsI7JVof+n5lPvY0MlS/azLnEGFe+Bu7gHFjSZk5H73WRUyBzzl7Ekfx4yuYxREW7D1DzJ3P/dmLIrW1kbbKy8z/trr+eVdSzhW2Yr503chBsfcxUmut4DsSt1hSgjkIbR6Cx85TMNfH0BtbLS6xC9YSNaXPw/AjDHZKRUchYDC7OQV3giJnxo+UndtcllmymC4wyYze1zqHo3eJUspuPPT2IuKEA4nzvIxFN/9FdyTJqfcfiiYOc6qgOuPvEzXoIqGpmnS+NcHEpvhmpYPtHzTC3yi8kXsRmpXkCwJapoCbDrQyMGq9njKWV8okmDlnBIml1mpbkKSKLjjU4z+3o8ouPNTlP7b/yPva/+PN3Y3YTc1SsMNrGregk8NJJB4j9phrTOXgOJGSSHilKEFk1wmmm5yMJaG6kh0cbmNKBNDNaxq3cpVjWvJi3UkkriQaHJkssM7EcXQsBkqbi3MdfVv49NDSdfZUxr/XtaslPfKRGD2sewPecpQhRK3ksOyY9BifKehMilYxbhQLTZZgCzTsWbwRgmN9kw2Zk5Dk5SU1jjAobRR6CKxTMrESls8kF4WV5/clTGBiGRDFTJailfY1DQC3YVbsiQxoTyX4s99AWG3E7O5Eq4drBVRktqjEEhOF66JkzhR38WByvaUsg6xhnpqfvkz1Pp6MAyryGfTRg7++GeEoxoLpuTjcdlQ5N5z2hWJW1ZPSFnRPIJTw0fKIs/2Olk9r4Q3ttXErWKHTaK8MJ2ZAxA5WE2W0885vQyVvrhm2Vj2Hm8jHNWIaQayLFAkiU9eMvjkoAf8aB0dKb8ThkF2tINlLTt4I28+/UOKpgm5Phd/X3ssJYnbZIk7Lkkd9LVlZ8f9oM+8e4yGtjALWvewuG1PynJ8gSVG9VTRSu45/ljKCsf8WOrKRCEJVHcaNjVMEBtrs2dxNK0Utxbi5ro1OAy193hCEHGkUSN5WZc1E7up8YnqFzGEIC/WiSkEhqxgX3Ehiq7Ruu8AXR0Bapz5bPJNtoKKKTJjJNNgY+Y0lrXtRDZ12mzpVqehbmz3TmJMqDbBKk8Z1LXZKPz8l2h/951kHZF+OOgpQztJdyVNUni45EKubHiPLLULE0Gn4uG5/KVEu4OlqmTjjdz5vJE7H4ce44aGtygOJ2fkCEdirMMzYyblP/wJ0tpNvL4vsatSm93LK8XncXnzBmRhYhomSqYP262f5Rv3byIQVpGElThw64UTWdJH37z99deS8sFNTaN11x5++rOX8TszUCTBjDHZdARiZHmdXDCvlHHFg+sBjWB4+EgROcB1y8cxqSyTd3fWEVV1FkzOZ8GU06tmGy4y0x18/9MLWbu7jiM1HRRmpXH+nGKyMgYX05fsjj6pfSm+x2RO1yHezZmTYO3KkqAgy015YfqAlXeyLE56foBNBxrRdINxwZoBNVVMoNnuI9vnsnqlpigOUoWSkkQ9bjujr7qCpkceIi0a5bzWHTgMlU2+qdw/6ipWRQ4x2uxEaa6zRLYiAcYQoCzcwOs58/l74fnM69hPVHJQ58xlm28y0WM2rql7i6eKVqKl93ukTRPJ0DEkGcnUkU2D1U2beCN3PjXOPCYHKghLdiTMeCejKncB67JmsbRtJzoSApOI7OCwq5iYbCdL7WKC2kTgzq/xv282cP7hCiakcunRf8l78mewQ0nngZJLSTOiCEz8SvfqxTTi+fY90CSZvHwfVLUkZB8Jux3f8sR0RLCkCMZediEXpR/j9a3VCcaOPGYG466+iVh1NZLDgVJQyFd/t57OQOIK8K+vHmJUXjql3Xr30bralDnhqinwRLtolT3EgL0n2rj7+pnx1eAIzixOSuSvv/46DzzwAMePHycUCpGfn8/q1av5whe+QHp6ilLkfwBMK89mWvmpR9rPBNxOZciaz4Zhsud4K3U1zcjuQspC9QO+8hJwS+1rvJK7iCZHFpIsMWt8Dp+4aBJCCJbOKOJwdUeSVa7IEmOLT+7vlLt9lCE5Nek3OLJ4pmA5IcWJHDbZ6Z3AjJZ9yH18thoSOzPGp8wRv3G8RPPDD0B3TMJlxFjStgubobEuexYveGaxqGMvi82aePaGhBVwXd2yhXvLb+C1vEVIptHrDjBNXsw/tzcA2Q85aiceLUR2rJNzOg/i04KMD9WwL72cTsVDSbiJnd6JCRPP5syp7MoYR3GkmYjsoM6RuKKTJIH0VhWabnIkrZTRofqkGIIhJEzTQAYmBSrY5JtCmh4lJDvRRao4iUlPR8+kDKF+JC4B86cXMWHRZ6n+6Y/QA35r/IaBZ85cvMuWp7wXANecN5bJo7N4dVMlzR1hinLSuPLcMcg2W1yX50CFFZjvD003eGdHLR+/cCJ6ODxgYY9i6rTaffG/e4TiRoj87OCkRN7Z2cm8efO444478Hq9HDp0iPvuu49Dhw7x5z//+YMY40cancEYP3hoG/5QDDWmIhcsxxfzc3vNSyl1TwAKom3cUfMSYXsaU+79dULziXMm5rLrWB5bDjRhGCayLCEE3HXt9DhJD4ZlM4t4du1xtvimUBpuSiCnqFB4tOiCeMaDpursdJQyURzGZVpWuYkVUHsvZ07SsR02ma4tm/H2CSybQKvdR1asE8nUMZAY569KamPWg8sa1hJSnEimwdrsOQQVFwhBSHamFOECKCv0cvOcUTT+72+t8ynpnHAXkRPt4JzOQ1bg0tBQ5UR3RFR2cDytJOUxDROM7lTQ/enlzOk8SHasE3t3ib8qZDZ5pzI60kBppIncWAd3n3gCqVtrfYtvMmuzZvWb7ASmJKcM2CedH9h+qJmrzx1D+Q9+TPjwIbT2dpxjxmDPTy193BcHK9s5VNWBqhs0tYfZc7yNK5aMjncICkZSl8+bJnQFYxhqjKoffBe1qTFpG1XI7PeMTpqMWruF4kZw5nFSIr/++sTsjQULFuBwOPjP//xPGhsbyc8fXKFvBIPjL68cpLUr3G3YSOiSRIvdy9qsGZzXtgsdgTSAWKvsdCSQuGma1DYHWXlOCavOKeVQVTtpLhtzJuSeVICrB6vmlrDzaAtHjSIeLb6AZS3bGBVpRAYOe0YlBMUy1AA3167Bbvb6tTUkTCESskJ6YKgx7LUV8b8DspPHilbTafNYxTbd+4QHyGW3mRoTQtXxc9lMnRcKlgGkbEYBYLfLnH/hHPR96+m0p/NEwfl0KWnoQqIsVE9ZfWP36uPUXW+6kPlb8cVM8x9lUqCSiORgh3cidc4cplafACwL2tFnUpzXsR9VUtiYOd3SWo8202z3EZGdIATCNAYMivYgGtO59/43+K8vrxpWcL6mOcCrm6vi8somYGgGz79fwbxJeeRluhlf4k2oWeiBw2atAP2bN6O1taZ0Be7KnMSbmbMTPpMEjC/1DXmMIxgeTslHnplpLY/UkwR4RjA4dMNg9/HWpNWpIcls907mvLZd3e20fORH27D1sThjQsF38WXxv2uaAtz79G78oRhCCBRZ4rNXTmXq6KxhjWndnnpO1HeBCfXOHJ4pWskkfwWXNK8nJLvQ+1iQczsOIPfLWLFhMDFYRVasizZHb0BLmAbeWFdCUcuzBefRavcmEFaaGiQ/1j5gxWjfzyYEq8mNttPsyMSjhVnVspnnCs4DrApM2WZj+axiJo7ycfzXa3jXN4NWmzduBS9p34MAiiNNcfmAk0ExNMYFqxkVbsBhqLTYfezJGEdAcbPLO5Fd3m7pVdOgINpKlupPeRy7qbOgfR+bMyZxY/0b5MY6UAydSlcBO7wTYOwkYqZEdVNg4AwaIagzXBz//R8Zf/ddQxo/wI4jLSk16U3TZOeRFi6YPwqvx8ElC0fx6ubegh67TaIgO435k/Np+csLCcqF8SE5HIyaPgF7sy3umukRirusj1DcCM4shkzkuq6jaRpHjhzhN7/5DStWrKCkJPWycwRDg2lCf52SHvQQi0MYZHzis+x/4kmmdh6zPjdBXbSC4lXnA6BqOj95dDuBcN/lsM6vn9rNDz+7iMz0gYtm+sIfivHoG0cSGmGoksLB9DKmBo5TGm5ENo24RkhBtDWlKJUALmjeyDOF53dfi0R+tJWr6t+NE3FAdlHvyE6yOi9rWo9bjyQQds8diko2KlxFCAzKQ/XIps64YDXNdh8BxYVi6nym6jmOe8twnbeKc+ZPpCjHChYakQiHs8oSXBk93Yh8WpBZXUfY3afKVBi6lUdtGhhCYCAojLbxsbo12Lsza6zsHVjUvoenCldS5U50aXhPooPuNGLYTR2PFo5rtY8J11EWrkdu30TNhbfyRKtATWEZ995rk+Chgxw/WstbhzrpDMSYOS6bpdOLBiw8kyVhaaj0e/aEEAlJAVctHcO4Ei9vba8lHNGYPzmPc2cUYlMkbFnZoCjQX8FQCGbPGUteZhmPvnaAzmCMiaMyuWppOXm+k3Y4HcEpYshEvmDBAvx+y7pYunQpP//5z4d9suxsz8k36oNgZRWVDz2M/9Bh7Jk+Sq67ltxl5w64fW7uP2bwdTBMG5vD3mMt9K2X6KmkBHDk5nLRJbMJr5zO9l2VCH8Xs+ZNJMPbm4v9/u66pIILsAhw5/FWbliVKNB/uKqdJ5/eRSyms2RmEedMsrJ69m2rRpYE/ddZqlA46CnjwuZNjA7Vc8JdiCbZaHJkURxpTpndMjrSyN0nnqBdSSNL8yc5WqKSgoQZLxayGSozOw9TFq5P2lYAMSFz3+jr4wFNUwiuaHjPyo4RAl0oPF28ip8stbNy+blEGhoQcgBPdh5CkmiZMR2zJdHq7lQ8OLtXCKtatlAabmKbdyKqpDApUMHMjsOEFGvC2e8ZzWXNG+KEG/+tsKzryxvX8pvR1yUoIx7zjCJgc+NRk3Pdwaomjcp21uQu4Ib6N+PXqmBCNEzRSw+y3D2aWnc++z2jkwKemCZZsU5cpsqfnthKg5yOacLRmk7e21XPL+45L6VL7YJF5Ty/7kRykQ5wweJysr29hHt+bjrnzx+ddIyMqy+l443XMfoSuSRh83goWzqf0bLMkpkDFz+NIBmnw19DJvKHHnqIcDjMkSNH+N3vfsfnPvc5HnjgAWR56NKrra2BlCX0qRCrr6Pye9+OL9+0ri6O/Po3tFXVkXXhxUnb5+am09ycehn7j4ybV43n+3WdRGM6Mc3AZqi49Cgr2rYj7HZyP347LS0BACaOyQfyicaMhGutre9M6c9UNYOaBn/Cti9vrOD5dRWouoFpwrpddUwrz+ILV08jGEytMS4wkU0rOe/qhnfZlTGO3RnjqHAVMLvz0IDXJmOQoyX/JibwcOFqK8Ao2XDpEW6vfgm3HhmwQk0VSlKV5rMF58X96mD55/9zo8bHn/gqrrAf0zTRFDux5ZcSSy/H3hQjLJxxsl2bPYsrG96La5xPClYyMVgZF9Q67i7mzZx5dNg8jOmWFBgIDkMlW+1MyNSQMWmXPSmJXBUyb+bOwxQSFe7UregkXeUc/xGmBU4wr30/D5VcHBftEqaB3dC4vHEdMc2kUbjjBnZU1Yk2NPDSAy+yeMUcbJm9mSLRujrUpkaunVfAU5sbrFshrOzGWy6YgBHThvgeOSm66x7q/3C/1RDCNLAXFlL0+btoaQt9aN/H/ysMdL8kSQzJAB4ykU+ebAVT5syZw9SpU7n22mtZs2YNF1100Un2PDW0PP9salXC55/Dt2Ilku3UVAT/0ZDnc/Hjzy1i84Emaus7yGmpYFzTEdKWLcG3ctWQMhAmDBBEcthkppb3+sjb/VGeXVuB1sc/GlV19p5oY9+JNqaPyU6QPu2BbBpM8x8HLL2TrFgXmbEuLm96/5RDhNMDJyiKtvBC/lLObd1JWj+1w77QkTjsSUzjTNNCzO04QGmkiTZbBpt9U2hxZBKMGbzsncNNQavnpUPVcK95kqhQ+BzwRs489njHA3AivZTXWcyypq2k6RFiQkYXMnZDpc6Zw3MFy+KThylE96SROptGdDe+SBi3kMiiN1OjyplHttpJmy2DtVmz466YgdIme+6tw7Ra8K1s3owhJNrtGWSrXUz1n8BuxHgje27c3WUzVK6pf5uSSDNGhcSRVx+hKnc83ms/RslbjxM5cRwhy4zWNL4yfR518y9CyDJzxufg9QzNBdcD96TJjPnpL1CbGhE2+2mJa43g9HBKwc7JkycjSRJVVVVnejxxRI4fG9B/rLW0YC/86CzbnHaFZTOLYGYRMAW4ZFj75xoBFtCA3t6IhswhzygirgxK8tKY1aeidX9FG7KU3EM0qupsO9zMxEyJa/3beMo+HbqzQEygINyMYug02X3sTh/Hdt9EZNOg0n+c0eF6sNuxF5UQqzg+5DHnxdopD9Vxe/VLePTQgCRuAjFJSSi396oBbq9+EZuhoWBQGGlhUqCCZwrPp8JdRLWrwFIx7CZIAdS58ngxbwmqpCBMM16mfuu/3sT/+305aBrLW7Yyq+soCgbrsmYmrABqXHmIAcZoAB02D5223qWxTRjM8BlkNIKuWb7kfelj2Zs+Bl3qJXzZ0JjiP3HS+6VgMClSR9WM5Zyz7eV4amq7khafmAAuaNpESaTJ0mLpTuEsaT5C2wP3EYx1IBl63BEm79nKjJI8si+/ktbOCK2dEbK9Jy8a6wshSdgLBm5uPYIPBqdE5Dt27MAwjLMa7LTl5KK1ppCSNXRk70h5bw8CO7ZT97v7WGIYmICJxHlt2+lYfAnzblqaELyy2+SUncuEAKddpv63v6asroIvcpAjaaVoQqEsVMf7mTP5U9kVCfsYSBx0lzJab0OYRhKJB2UnNj2GLV4vmYg6Ry5+JY1zOg4kZOP0RQ/htNkyEkh1Wet2HEYs7lSRMZFNnYubNvC7smu69+09a5vi4ZmC5ckCWgY8895xTAS6pHA0rZRxoVp8WpA2e+Izpko2Xs5bzKVN65FNK7myR3MmLDl4puB8RPfEYTdUZnUeZumRnYSwXCGSx8tyqZYjZikh0/pMNnTL0m7ZmvL6+yM93cniHIP2PjEJnxYkQwvSZstAwmRyoCJpUrSbOvmRZGVGU43R9tab/Lw+nza/5VbL9bn4wlXT4kHiocI0TYI7t9O59j1MXce8YCVMnjkigvUB4aREfuedd7Jw4ULGjx+Pw+HgwIED/OlPf2LixImsWrXqrA0s+7IrqD1xvJ8qoY30eQuQ3cN7yD6qMDWN+j/9HgyjT2qeASbkbHgZrloJffyjM8Zkp1zk2GSJRcUOojXVYBg4MZju7yXmOV2H2OdN1IYWmGRrnVZzib461sC2jIm8nTMXr+rn09WJioBWvyGJbd6JZKldzOs4kDLVsIeKJKAo2sLEQBWHPKNQhUJ5KDkgCpCmh0nTwmSrnQkFRZYoVKrpxLQKp7rvSaW7kL+WXMJnK/5ObrSdgOxKyHI5mF5Okz2T1c2bMIVEmy2DClcBJ9KKkUyDKxrWssM7kRpXHlsyp1LtyueypvfxqgEaNTuvll5MqKO376ZHC3Fz7WspNV363xNVyGQtWYpn6lQ63n4z/l4I4Pq6t3isaBWaYu9eQw0dsVCYxvbeMdW1BPnRw9v42ReWDKv1YNNfH6Rr88Z4TOvY0SO4Jk6i6K57/k/6g/6z4aREPn36dJ5//nlquvvnlZSUcOONN3LHHXdgt589P7V78hTyb7uD5scfwYhYfsaMRUvIPc2OJR9WGKbJgYp2apoD5Ge5mTYqg8DG9QN2WKHbQvKdvzL+kcMuc/d1M7j3qV0IYb3ymm5y/fnjyHYaVBiQSpvRYSbXC5hCYkaoCvrpWAtgcqCSN/IW0Obw8XjhKq5qeDd+DBN4NXcBSBKLOvaSaDsT3yYkOXEJHXQr1e/SpveZ7j+KbBq4UnSU79lRNnUubNqY8HGXkhb3IfffPkFpUEjEJIW93rEsbdtJtSsfrU8TCdnQcaMyscCNPb+A1spaXIFKZvqPMSrcwB/KriQou+IplXXOHB4quZjPVzxDXqSV9vYAQvTm+HTa03kpbwmXNG1AYCKZBjIGzbYMXEYMm6HFK0G7soqZcullIMukL1hI0+Zt7HSN5oS7CK8a4OqGdy3JYElB7pdZYwAxYcPZ73c0haAyhayuqplsP9ycUmAtFaK1NXRtXJ8woRvRKKFDBwkfPIB78hTrfKZJ57r36HjzDYxIGM+s2WRfegXyP6jUx4cJJyXye+65h3vuuecDGEoyMhYuIn3+AnR/F5LLjXQWJ45/ZIQiGj9+ZDtN7WE0w2BsuB659h0cEkNqYtsDtaUZ98P/yxera6hwFWJk+Fh00+XkTCzhxXXHKDVFEpHrQiZz3jyUFpGQGVOa58FxNEwquIzeAF9FWhG/GnMjLi3MxGAVK1q30ei0/PaFkdYB1RXLb72Jlkf+ltD/syzcmNJ6B0uNMSg7+XT188jdZfI925WF6znoGZ1S+6U/NMlGnSOb2Z2HuLruLd7LOYcmRybCNFnavpNbvnsXsvNjAGTVVOP60Q8wYlEOukuICVtiXryQurXERzM1cJw0SScgKQn38VD6aI6mlVASbeH85q3kx9rYnz6Grd5JjA3VkaaF6MosoN6Vx+O/3cCiqflccNVNPNg6mkBEQ5MUhGmwP72cyxvXUiQMTFnG0A1kTDQkNEnhlbxFXNb0PjZhWtWYikX6b2afEx9LbrSdGV1HcJoq0X0RzMl5Q3KNhA4cINVCwIxGCe7dEyfypr/9la4N78eNj4633yKwbRtl3/k+smskx/x08A+vfigkCcXr+78exv8pnnrnKPWtQTTdJE0Lc1n1m9ZyfGChRJAk0mb16p2Yuk71j3+A1tGBzTQZr1ZAF3T8+iCZP/wpa/c2kpm7iMub1nVbhiaqkAnKLiZcfin3ZqSz80gL7f4IUyM1iE1vEE5VEAJW9WRfCIEhySxt20WbLYNmRyZFOWnkO0aj79uVPHZZJn32bPTWFtrXvI4Z69VxSWW9g6UM6e2jTd6XVzJjw0iDM00k02R95gy6FDddshuHoXJD3ZsUm13okszjaw7z3u46VNWg/JzbudxeQ+euE2hSstWvSTY2ZE4jJ9ZBSHayYnYxmzYfZVS4jnY5nXpHFvOnF7No51bs3dK/57XtZEHHPhrs2TxfsIwQTugu9np9Sw3v7qxD04g3iDaFhCYkXslbxPgTT+KZNpWuKDTUNFDlLmC7bwo5JXkUfPoC9I3vEautwTlmLLXlswm/UQWqzszOQ6xq2Rr3//NONbV1+yj+8j2DkrlpGJi6BnK/tlIAioKUZqXOqW2tdK1flyj3q+vowQCda98l64Kzk/32z4J/eCIfQY+0rEVNU/wnUvqTez4TAJJE1iWX0fHG62jtbaRNm4FwOiy1uv4d73WdzvXvo+vpHE4v46/2DOZ0HsSrBjjuLmZf1gS+73TjtCssnFpAyzNP0f7Gmji59kdPfnRfSKbOstYdtNsz+HvBcgDK8j0Ur7yS6iMHkuIgnnPmoqRnkHP1tbgmTKTjnbdo3X8QZzR1YY2GwNbPJOx7j7psHhRTQxP91hs91Y09lnq3VKwwTWZ0HaHemcPkQCWjwg0oikzGuUv53fP72V/RHq9+Pd4Y5H57DjddMZl1a2tShm07bR6eLTiPS4J7WNhYy5zKt7s1awSyBEVXfJkIU2mrOxEnOqeh0ujMJJSilV0qvXmwVk+tDh/SgQPYbXYKdY0iVxoX3zaX7OI8a6Oym+LbZxkmRTtbaW5oZVXL1kShsliM8JFDBHZsG1Cr3799G00PPYgeiWCqatJzKSSJjIVWm7hoZYXVhaqfrIcZixE+cABGiPy0MELkHwL09Z649AhKnxdui3cS72bNYor/BOWRBjocXiZOH4N47WVMXQddJ7BrJ5LLldQAAMBUVdTmJuZPGccbW6tpdmTyWl5vj8bCLDe+7vxirauL9jWvJTdREAJNUqi1Z7E2axY1rkQhNQOJDZnTCdisILXdJjGu2IutrIjIuReivPcakhZDKAoZS5eRd0Mv2aRNnUba1GnUfP9nOE7sjQcC96WPYXvGBDRJYZK/grmdBxOUGntumSZkMtWu1PnufbswQbc+jI/d3vGUOWJMbdzdLQplgmlSuWkn+0tKUM3Eo2m6QXVEwZBtVipMPxeOKSQisp3suqN0VHcCvTrlJlB73/9Q9l/fpfP9teidndb9FYJ96WOH5A7qvWaBQ4uCrmPoltvLrKsm8MDvyP7mfyVtL0mCr988m/VPvIp5TIqnK8bHHY3S8c7bKYk8UlFBwx/vTwi6WllTorvaFszLb8WWZdUxKL5MzFT58pKELTd3yNc4gtQYIfIzgPV763l27Qk6AlHyM93csGIc08ecueKIORNy2HygCd0wqXQXMrfjAHaszjbvZs9BkxR2+yaym4kI02DWe09g9mkJZ0aj6CkEjsASOXKNn8BlM0ez62gLbV1RoqqOXZGQJcFnLp8a3zZScSKlVYVpUm3P4fHi1akvQIg4icuSIM1p45yJuTz3nd8wsXYnokf6VTPp7AqTJ8tsO9TMuj11GIbJkumFFEwcS+TEXgBezl3EwfTRcV2UNlsGB9NH84nql+NStrqQeapwBZmq1Vhbp5/13T2uHiiGilcL0mVPx+a0M/fOT2L8/udEKyusS9R1WoUbSVehnzqjppscru5AkQV6ip6qAMI0Byz8IRaj8pv/hunJYEPhQrbbiymwqTg9mdCeOphtdezpe3yDQq2DjP6t7wyDWG0tsYYG7AXJwUuHTWb+jFLqN8gYkeSgdvjQQWL1dUl1G+2vv5r0HAis+/x67nwOpo+mqN7JjJ7zjC7HlpNDrLslXHwfRcG3YiUnQ3DfXjrefAM94Mczew6+81cgOUf86j0YIfLTxDs7a3nszSNxhbjaliC/eWYPX7p2+hlrbvGxFeM5XNNJIKRS6SrAkGRMQ+dw2qiktLq8aDvSAHnZ/SEUBSUzi/Rz5iIUhW9/cj7bDzdztKaTXJ+LRdMKEnqMKhnelFaVgaCrfyOEFHA7FWaXpbOsfTevfH8T05v2JuQ829FRt2/mD4/PZEdtOO5COFzdQZkvl8uQCNjSOJBenpATrkkK7bZ0DnrKmBqsICIUXsldRKW7kEr6Fav0WOH97psm2WizpTO3Yz83//cXUJrrqaxIdGNlxzpTyvPKsiA7w0ltc2qRrIJIC5qQSNMH0eM2TYS/k3mB9VQXLKfamcvktn2UqGFqnHlUufITxrxgYjZbDjYjGxoGgkzVz9VNa1MeWigyut8PKYgcrAyxAS1/06T15ZcovPPTCR+rLc0pC/Y0ScavpFlunq7e6xVCUPIvX6P+978jcuwYSBKSy03BHXeetKCo9ZWXaHvhubj1H62uonPde5R969tIzuEVMH1UMULkpwHTNHnm3eNxEu9BTDN46p1jZ4zIM9Ls/ODTC9l2qImGY1U4KozupWzyy6dKCtIQGhPYsrLwzJ1P1mVXIBTrMVBkifmT85kzIRddNxPU80zDQO3sQNhsmLEYpmnSbktHFxJeNcA238B62JKAe66fyYRMwRM//Sv3uscx3ggyvcdI7rNti5LO1soAWh/3RVQ1ONwcY4tvKi4jkjJXWpVsVLgKmRCu4Tdl1yW0wrMbKlO7jlEUaaHVlsF23yRicnIGVKfNw1bfFMr21DNl3eNJ3/u0AOWhOo67i+KBRrDy8K88t5ydR5rpH461GSozuw5b5fQDNMtI2N7UWdGylXQ9hGSa3b59hTpnDmty5lMWbmDm1GJG7V3L3JoGGuxZeLQQebH2AeUSTF3HMWrgTlVCUci57mM0PfRgip1NotXJFdyuSZOJVFUmBbsVU6fJYdUulOYmaoQoXh+lX/t3tK4ujEgEW07OSbNi9GCQtuefTaxVUFW0tjY61r5L1uoLB93/nwUfeSIPHz9O28svEKuvx1k+huxLLztj5f2RmE44mlpIqaEtdWDuVGFTJBZOLSDsClL7ug1D15gQrOL9rBn0Xc232TLosnnIVrsGlDiIyXZOzFzN7AuWI7td+EMx3txWw4HKdrqCMVo6w5imID/LxScumsS4Ajc1P/sJ0ZpqzGiUFruXZwqW06WkIbp7XepS6kcp3W3jy9fOYGyxlz/95gU2eSYjYbKydVu8hL4vKt1FAw2btdmzGB2qS/mdZOqka0EM00pTPOYuwhQSHi3EJ6pfwm7EqHAX0WL3JlV4xiEkNODxN49weWOQqSk2uaLhPR4vWkVrZjFR1WB8sZdbLphA+vE9nN+0hX0ZY2h0ZMcDqZKpMzrUMGDHo1TIVjsT7H67qTEq3MidNS8gKQpiw06isRhpwFitdtBjCbudnGuuR3IMrqOSNmMmyHJyowhJwlFSmrR95qoL6HrvXfRQMO4qiQmFbd5JRGQHDpvMdcvHJu0HoGRkQMbJ2w7CwO48U1UJ7to5QuTd+EgTeXDvbup+e198SaY2NxHYsY3Sb/wHzlFlp318h13GYZMJpSDzXO/Z8d85ikswDetly1a7WNi+m/ezZlnWuQCE4L1zrufaA09j+LtSdnAxDYP1R7t49k+b+cJV0/jjS/uJRLV+utcm9a0hfvHETv6tvBO1qgpTjaEh8UjRhYRke7KsagpEojr5WW5CEZVNXU40SaY8WIsupJTk5tSjKIqMriWSvDANpnYdJ6g4rWBaPxhIzPAfpdaZS352GnXBGDGhsLxlGy49wnMF51HhLrQsddPoEYMHRLJbQQheyluCVwtSEmlO+ErBIJaZx2++cl78s/DRo1T/8ffMN03CipNWu88qJBKCmGTnr6WXcGfV87j1CDoS9VmjmTqlBP/G9SnTN1NBwsQ0oU7y4tYj+BigEKx7/PbiEpTMTLIuuCiex50KhqrS/NgjdK1fl/JZEYpC1iWXJn2uZGQw6r++Q9sLzxLcu4eo4mRzxmS22UuZkJfOp6+eQXZaqvKy4UFO86QOkgqBkjEi1dGDjyyRm6ZJ498eSqx8NAzLonzycUr+9esnPYbm7yJ85Aiy241rwsSkZaAkBJctHs2z6xLdK4osWDytAMMwE7ROzgQkh4Oc626g5aknMGMxVGFDMo0Ei/hEu8bha+9mcfgYTY8/kvCCGkBYdlBtzwFV508v7ScYUQesK9I0g/Z160jrruA8llaCJqSU2tip/KyyLOjwR9ENE1lYqcYxyYZIYXabwLhoPW+nOo5psLxtO3ZD43BaKS/mn9svWKnh1qP8PXs2ZeUTubrIwwtr9jE+WEOVu7CXxKF37IYJInWJkSHJvJM9h1trX0u4d8fSSli+2BKp0jo7qf/j/YQP7AcszfQuxY1sGvGUalNIRIWNzb4pTApU8mL+uXQ4fdx381KcxSW0/P2phGdUFRKYAilFkUCz3cdjRaswhERetI1rG95J6XcXikLZN/8r7jIbDI1/+TOBbVuTA9iAo2w0eTffiqOoOOW+tsxM8m+7I/73ZOCT3f8+UzK2jrIyFF+m1Ru0zzMjbDZ8K8+eRMiHDR9ZRRszGrV6CqZA+Pixk+7f+uLznPjav9D45z9Se9//cPzr/0qsPnlZf+H8Uq5ZNiYhKCiE4IX1FfzLb9632qadYWSuWEXxXffgmjqd7b5JSW6NmGbw+tYafCtWkv/x2xEOBxFhIyYUOmzpPFa0Ok6CXaGBSRwsrutrqQdlV0LfzjhSdJwB0HWDtMYKvFogrvpX68wlKtmTPN2akElTQ9wU24XbIeO0W5KyDj3GNQ3v4NEj2E3LpdRfBz1dD/FQycU0O7M5f3Yx08flEbanoQmJI+6SBJ95D5SUoctetNh98THGhEJIdhFdfTUXzB+FaRhU/fC7cRIHyz98QfNmvlTxJBP9Fb33UJKpdBXwSt5i2uxeBFb2ju/8FdiLe4XnTKDKmW81lO4HVcjszBhPTLajSQoNzmyeLjg/aTths5GxZOmQSFwPBAhsTU3i7ukzKPvWf+MaOy7+WW1zgB2Hm2lqP7Nuw8FgBUm/ir2wEGG3IzldCIeD3BtvSRjbPzs+sha5sNks35qRvASVPYNrO4QO7Kft5RcxNS2ee61HItT86ueU/+hnCSJAQggumDeKORNy+eYfNhHTDFTNQMXyof/ssZ388kvDEyAaCtyTpxBpaUZdl3ppHgpbL6f33KWkz5vPD3/yLH5DpsmemWDJ9uT/DgRZFnSOn4Vvp6XvXRJJ7poOlkVs0K3Z3X18GwYLW/bS+vtDmJrGjDEXsEfKRjUETxStirdNA6sJxfrMaYwJ1VNasZtvzFZoP2cFDQ/9hZJQY2J2i6kz3X+MHb5J8c/au9UKPU4bE0dZwbalMwpprM7BYahIpp6ktyJhMsF/gv3pY1KuJpx6FCHLOKfOwDdjJmlz5jEnw0qj7Hx/LVpLS7/j9TZYvqrxPdSm9dQ4c3k7ew5+xU1IcSNhMHV0DoGwxt7fP0B2ZVX8JRRAWbSZ3WnlTAlW9Al2ytQ5c9npnRA/lyFkmhyZdOaU4m2tAcm67+nzFpB3482920Ui3e9CiqrT9jaEImNqyUSuNjXF/x2Oatz71G5O1HchSQLdMJkxNpvPXjEVRT77tqAtO4eyb3+fWF0tejCIs2z0SX3+/2z46BK5LONdtozO997D7CPsJOx2Mi9K7jDUF33V5fpCDwSInDiBa8yYpO/W721I3W7NNNl5tIX5k/OTvjtdBNe/T05sEi0OX9J3o7J6szIkh4NxS+bw1vZa6ON79giVBZ0HKe2oICw72eKbwvG03mW0AOyKxORFMwntfgsMg7xYB+OCNRxLK45buZKpo5g6EckeJ0QPMc5r3c609sNxCl51fA2eKRezLuSlxeHjt6OvpTTchNOIUe3KQxcSebFOiDQR3rGNcStW4gzVp7z2dC00oDunB7esnsC+A8V4Dx5kq28yqVK8L27eiMNQ2ZUxHqNvib1psqxlOy1KBuqCS1ld7iAQ8kM3kTe++tqAui/xe2dqlIfrKal9jb8WX4Qm2fDoYVbmefnWHzbyuYNbUfp1HVIMjamBEzQ5svCqAdps2WzLmsoRV3HStSo2hbTPfYWjte1s3NuAw2FjxbxR5MsyoQP7afzbX1CbmxGy3C04d3NCQxZbbh5miibMSBLO8t5n/OE1hzlWl9iFavexVl5cX8FVS5PfhbMBIQSO4rMnm/1hx0eWyAFyr78RPRwmsGWzZZ3rGr6Vq/AtXzHofnowdT6wkCSMSGqhqEBITUnkumESDCdbPGcEksTqlk08Wbgy7rcWpoFiGlw3OzEz59rzxtLWFWXnkRYURSDFotxZ8xJKJGA1IcDqJv9+5kw2ZU0DYMa4bG44fxzZmp8KSY5nJ1zRuJZdGWPZlTEBTchM8Z9gTudB2u0ZvJR3Lm1OH9e1bkAJdCQOV42xZP/LlHzymzz5znFUXUpoWKwYGoWRbivXNGl46C8DXrpLjzIhWJ3UOcjs60cVguIpY2k+uIMLmzfyWu5C0tUg8zr3UxZuJE0LYzN1VnXsQGCy3TcpvjxZ1LYbOzoHXCUs/OMP2WO3IRkGjpISXJ/4HOGmZoYSzhZYLperG97Fb0ujLNzA855rCcfcA7aOs5sapRHLInYbEbzNm6kuu4JIv9fVEBKPvnmEpvZwt2RAlOMv7OedtQe4fM+T2LslDUzDoGvD++iBAEVf+FJ8f8npJPPCi6zinr4yCYpC9mWW/rxuGGzuIxHRA1UzeHtH7SkRuanrBPftRWtrxVk+BmfZ6GEfYwSJ+EgTuVAUCj/5afQbbkJta8WWmzcklTXP3PlE+mmhg/UADuSXmzYmi7W765J0MDTdIKLqaLoxrGVoVyjG+j31tHZFmFCayezxOUn7e5cuY/RDf+HjNa+wPnM6LQ4f+dE2zlUrmDj7OwnbKrLE56+aRltXhMa2EPkHN9JaEU7ICLCbOue272KndwKmw8nd183s/iYNR0kx0YoKwHJJzO46yuyuo6hC5pirGKepURBtY3HbLl4qXMYjvsWYPkjXglxf/zaZqhX4MjWNxZNyeX1rLR2BaJwgbIbKJH8FPs3qT6pkZqIPEOMAK3tkTufBJCIfW+xFDwTo2rQBtaUZR8kohKIw3X+c8YEqlG6p2LhtK0l4z5nLrdfdwuxaP4+9cRg1GGJr5hQaw41c1fCulV0TtapPI1WVtPzmXoK2NFzRQTJH+kDCJF0Pk635QZI4FnVhImi0Z1HQLZTVF33tbsU08Ghh5gaPsTFjUvx+2W0Scyfmsu1Qc1z3Bax56FibxoP5q7m9+qW4bIGpqgT37ELraEfxZRKpOEHXhvUYmkrarNkENm/qPrnANAza31pD3k23YhjmgH12Y+rQUyp7oLa2UP3jH6CHQlYQXghcEyZS/KW7h+TXH0FqfGSDnX0hezw4R5UNWSrTe+652AsKEfZuP5wQCLudvJtvHdA3N21MNmOKvdhtibfUNOH5dSf48SPbE3plDoZjdZ1843838Pe1J3hzWy1/fukA33lwC5FYogWXPn8haTNmUUCQq1ve5zONr3FV51Zmfs7KJIhUVRKprMDsE83MynAyeXQW0X27Uwa5dCQKY61M69PrE7B0zVO4MSTToDjShI6g1ebl5fwl6Ahikg1VstFmy+CRogvifngTiG5ax9eXZbHynBJy0u3kqp2sat/OJc0bQJYRDgeOUWXxJgUDwaknEqksCa4sVjn21XtofvxROta8TuPDf0VJz8AxuhynabWGS7gKwyC4czsZaXaWTCskFNWJyQ5Uycb8jv3JRTy6jrO5jlYlg5BkY2f6ON7Inku1MweD1PEGA2jqbsqsKg707mDx63kLEmpwB9rfZuqsSO/kwvmjKM3zMK08i7uunYEQIqWAliFZ2TN70vs1A1EU1JYWWl98nuqf/JCOt96g6913ekkcrAdW0+h6fx3B3buwKTIlecnNf4WAKaOzkj4/Gep//zu0jg7MbqEtMxYjfOgQ7WteO/nOIxgQI1NgCkg2O6X//k38mzcS2LEdOT0d3/IVgy4BJSH4yvUzeW9XHQ+/fjjhhYyqBtVNATbua2TJ9AI27mvk9S1VBCMaM8Zmc/mScrxplu/SNE3uf24f0ZjeZ3+dxrYwr26qSljKCkmi6LOfJ1JZQfjQQWRPOp455xCrr+PEN/7VsnoQSA47hZ/7Iu4JE+P79ogZ9YeMieH28LGV4xO/MM14VWf/7d1GFBmTHd7xcZLqM0iiso0qV76lJ26aND/xOMKmsCArm2u/9m8ISaLjXYXIMSf2omJ8K1bStWE9wT27QdNS+qJVZA54EmsBSmMtqH/+S+L2sRhqSzOZF12CEY2g1if73COqwYZ3drLkgvnkeF00d3fxEabJEXcJHj1MQbQVTcjUOHMZFW5kfKgayTSZGjjBHs8YNvqmcUHLZjK0UNJ4BZAd6wBJonH0dMoCdRx3FVLnzKVT8ZDZvQoRDOxzjx0+yCLPK6yePYeOt15F29KOrXghksiNa64Uh5tY3L6bTNVPnSOHalde4k+oaQibjbaXXkg5iSdsG43SufZdPDNn8YmLJvGTR3agGQa6bmKTBTabzMdWDC9rRPf7iVZWJmnom2qMzvfeJevi5Hz1EQwNI0Q+ACSbDe+SpXiXLB3yPooskeN14bTLhGOJllxMtXyNdS0B3tpRG887f3dnHdsONfPdTy3A47LR0hmB9lYub9pGeaieqGRjq28y27yT2LivMbVPsrCEKtWDLAsm6Do1v/gpRrjXl69HI9T+zy8Y86OfYbrTeOKtoxyp8XGdkBOKcgwERmY2X/3yJQnplADuiZNTphcaiHhziIDiTmys0AMTQrK1GpIADB0zqhNraqThz3+g+O5/IbJgBbE555Gf50GRJbxLzqXt5Rc56Cik0pnPqtatcaIzgZDsSMhawTS5vMrKrEkiQ8PAv2kDcm4+pCByyTR4dlsjacU1XH/eGP7w4n5U3eSx4tXYDA1TCNK0MDqS1bgCE7n7XsjdGTQz/McGbCAtAJepgQkFR7ZyJRIBxc3fSi5iV8Z4FrTvJai4yFEHT1UN7NhOYHtvf89ZnW9geCewJ2M8ObEOrmhci2LqCKwG1ZMClb1jsNvJWLKUyPHjqe5QSvSQfXlhBt/71ALe3FZDTXOAMUUZrJhTQkba8Bq9mLo24LlTKXOOYOgYIfIzDKc9Vc8bCzZF4s1ttah9XCy6YRKKary9o4bLF5cjgn5uqXgRhxFFAtxGlPNat5MT62B3Tq9KnNraihmLsr1N8OCrh5C7W7cJXedaJYsS+pVuGwZdWzbxZKCQbYebUW05vJ4zn1UtW0AIHBK4SooZ96W7UVzJOde23Fy8y1fQ/Oab2AzrpYsJhZhQcBsRJGBssJbj7uKknG1dSBSHm5KOia5Tc6Sa3/5+A22BGJIQSEJw52WTmT0+F3H7XbzwRh231LyKSa8fUAAZeojJXSfY5bNS8rLUroFbwAHtAZVXnMVcLQ4lTF46gpBk5/bjzyL/6hkcOTmsnnEpr1bqGEKKa7J02BQcRixlK+kkd80gUEwDBQNZ9XNR0wZeyF9Ki907tAbM/SocnabKoo59zOs8iEZipayMiYkJkoTi8+FbdYFVVr/+fZAEOoJ96WPYl16OzdCZ2XWEcaGaXl17h4OMRYvjx8v2OrlhmBZ4f8heH0p2NmpjQ+IXioJn3vzTOvY/O0aI/AxjXLEXh00m0s8iFwJMTGRZ0D9GpGoG+0+0c/nicszN72E31X5aG5bVlzP+atTmZup+92ti9fW029L5c+HFaP3yo5/IXcaXAk8m6HObqkrHxo0cN6ahKpbOxR7vePanjyE/1s7YcQXcceuyQa8t94YbqfUUUbnmDWRdY396Oe2KhxvqrY5FUwIn2OKbQrstPa5nYuvuKN8jr6oKmYNpZZRGGvFqQZ7JPZeW9sTqxPuf28d/f3I+61sVslU/2bEuQHR3r+y+n8AFLZuod+XQ5MjCENLAolHAfkcxDYqXLtlFlhaIb9sTiOy532pzM7sO1mP001S3yu1tdClpONWOxK8GvWupoWAyLliDLiSOppUyPlhNhj+YsvVd/2vpe06B5UNXUlSCCkByOBnzk1/EP/PMmk3DI3/j8aJV1Dtz4pNupbuAGV1HWd2yJS5tnD5vwSlc2cAQQlD46c/y/9k77zC5zvLs/95zzvTZ3dnei3bVe6+2ZcuyLffe6YROqAFCEkggQCAE8gEJNRTb2Lh3S7Ysq0tW772stL3vzE6fOe3746xGOzuzKzk2BLDu69J1ac+c+s6Z533ep9x3y398D3TdEqNwOFB8+RTedPM7eq13Gy4Z8iw41NjHur1txJM68yeVsHhqOTbl4vLCkiT44r0z+Y/H9xJL6qmKAtOEQ439GWVcYLEDFvksOs7YiRPIWbglTFlhXoFKy/e/i+bvB9PkkLdqRMLak55qpoTPpG1Tz5zmvZxhfeEsdvss/g1dkml3FkH8wg0WQghm3bgUY+wknll/mp7+CHlamIDipUQdQDEN3tv+KvuLpnGydg4ul53JjW/S0L+fhLAho3Mop57VRfNxmBqzAsfoG1YDLxk6M3oOcfJXh1A85XiSYXbmTmRB8EhGW7+EyQL/YV4qu5yA4kEdDBVlM6wzgyeZGzyGNIwzMltcOiFlDxmYCNQshFsG/7uqgVSoSAi2FkxnQqQZDG1UY24A2VrLRppM5GHkVLLXS/9tH6Zjlz9t5aRKNvbnT2TZ5EJqZk/BPXkKQpLQBgIkWlqwFRa+I2RzzroxjPm3fye4dQtqdzeucePwzpmHZHv7vCzvZlwy5MPw7IbTrN7Vkophn24fYNOBDv7+wdkXXT5YVeLl+59czGd/vJmhKaVzRnx4N6UiS1w7zyqjc5SVEz99KiMhZJfACAYttrlBgxaX7VYn5TAYkkzSnqVCxzSxoXNV315OeGsJKVZzixAwpnz0blfDNLFW6oI5E0oYH2qi47dPcUouYmPhbAQmswPHqNX6uOMjN+OqGwNAIjmbb373OdxqlC5HAeFB3vKECdsKpmXE1GUMShN+Sk+eoVixE8qdQrOnjDmh4xlsiQIoUAcGQw6CVSWLuKVrc/p9Y421I0NQcmSMDzdbFL1ZjPbWgmnc1rnREorAQBcyTc5SauNdaaGN4Z7zcBhAi7MkRXcwYMvhd1U3cnn/fhoirRmrsnPnVIUNkeWzbFCFwnrHeGp3NHHN3JoU789JIxdVCmfsL3Sd0xGZcYNsh12/f5jg5o1WklvXcdbVUfHpzyG7L8w9PxqUnFwKrhu9Ke8S3hreFeWHFwt/KMGrO5rTCLCSqkFbT4Tdx3tGOTIT3f7YiHSsNkVCkQV2m0SO28bHbp1C9WCJl++a6zLraRUF55h6JElKSzg2RNqyNpUIRWHm8vkkXTlZfTsTaIi0pv62KzI3LqrLeq+haJKfPn+Ij31/PR/5/jq+/4e9dPujxE4cZ413Gi+UXcEpbzUnvTU8W3EVfyi7mmhjY+r4zv4ofk8Rpz1VKSMOYAp5BD51G6c8VgefpCU5kmPRwg434iYwILtocRRTkgwwN3CUk54aniy/mgHZbdV8Szb8Sk5WD3Y0zB84glePoQzmAoRppP5/2lPNL2puY1PBdEKym5PuSnod+YRkF+f4FMOyizcK57AlbwoDspuI5CApFMzBrkpdthGXHKwaIqkHELDn8lLZ5ezOm5h1AgjKLvbmjs0IpQ0fl4RQUIXMm74pbLPV8tzGMzz82rHUPl63DTkLmZswDcwTh2n65j/Tv/pVSyxZ0zBiMatMsLGRzt/9+i2N5duFqWmEdu/C/8brxBpPpzV8XcJ5XPLIh+B4ix9FltCG0XkmVJ29J3tYMPni2+yddsXyYrOgqtjLZ+6aTiyhUexzpTEkOioqqPzbz9H50G/QAwFME7wzZlH6gQ+hBwfSPPW6WAd10Y40Zj+7TeKqWZU82x6kwj2G+bGDGUt1SZJwueyWdmZFHvcsG0tZgWVk+4NxTrcHyXXbaKjK47uP7qHbH0t1rR5r9vOth3fz0epC9uaVpHmtqmSj057PsaSHJYPb8rx2tGzxH9NihhzeayJMA+cQfpyY7ECTFPbkjmdm8AR2U+ewt443iuaRkGyAYFroNEv79pCvBtmWP41f1t5OSbKfxf0HGBsdna87m+fsNFQ+1vQcBhJh2TXIkCjxcukSWl2lhBUXvXYfNl1lUqQZHYl2p7UyOeatHUyIWELOm4vnAFbX6ox4C3eOt7GjT2JlpIhklhCOzdSIyzZMREpAI6B4ea5sKb12H7qQ0CUbCwKHObe+G5oL2Zw/nZOeavy2HOpj7dzTvgbZNDgaaMC/uJb8PDeXTSvntR0tGZ3IApOGcDOGIuNf9UomTYWmETmwHyMe+5PIrCW7umj53ncwkgmrdFKScI0bT+Xffu5S89AwXBqNIfA6s8fpJAG57rdWalWY56SyyENzVzjNoNttEsvnWqVbI5VvuSdNZsy/fR89HEKyO1JNSLLLhXfefMK7dmImkwjgzt7NnCqdQuO0ZdjsMpdNr8Bpk1m/t51+Tx1z+w8jDxfVNQwO2yu5bl4Nt10+BiEEpmnyhzUnWb+vHUW2TIjDJpFI6mk/eNO0Ovq2mGVIdGek2FTJxgk9J2XIfV4HEyvcHGsJoQ01lyLTiINlTOyGin+wvros0Uerq5S1RXPpt+VSmejhteKFaeIQh3Lq0ZG4sWcrc4In0s5nBV0yYYUpZCKyi6PeWqaEzpCrR4ckQUHCwKdHUue5t30NawvnsNc3kdPeGh6rzuX9ra9gM3XspkZYcSFhYtPVwUnmPDRJ4WBeA8sum05hKIFYfRyGNfPIkuCf7pxC8mer0CSBYVjp3d9XrSAiO1NhqM2FMzmYO5YxkVYK1CDzB857203uCrqdhVzftYVJ4aaUkS/v6qPrv3rxffXvKcl389GbJ/M/Lx5K8RDZDI27O9aimAamaqQ1kaV/PwIjkfiTGPKOX/wUPXReIMUEYidP4F+zmoIVN/zRr/+XhEuGfAgm1eVjU6SMihNFllg6860nej59xzT+4/F9+EMJhABdN7liesVFefZCCJScTBWVsg98mIGx4xlYvxYjmSBn7nyuu+76tK7V9XvbMEzTEiX21jIl1IiOhCkEAnilZDFB7Ly2s5myAjeLppax81g3Gw+0o+kG2uDjJ5LZW7CTmkFUE0h2O2jp1lgWkOs5r6MY2LCOG9Y/wg2mSUyys9M3kW3508895PkDz/1YTdidN5E9eROZ7z/M1QP7ecx9Dappss83gX3m+Cx6mwpHcsZwdd9OnEamIPDwBh0VwRtF82h2l9NvywUh2Fowgzva1zIm3pnV8EtY5GDL+nZzOKeeaaFTzAscw0CgIchPDHB/5xv0Kbk8WXYliSxScknVIBhTmT2+mNU7W+jsj6a11xuGyb8+e4KGGQ/Q3BmkIdhEbmKAuGTPyCUM2Lzszx3H+1tXgaJYwsomlObaSEQCTA6fTYvZ200N2pqIHjmMZ+o0K89x1xi2//g3yGqMinhvGm2Brag4gwMcQM7LRf4TCDpogQDJ9raM65vJJAObNl4y5MNwyZAPgSxJfOm+WfznU/uJJSz/0TBN3rdiIpXFmW3KF0JBrpNvf2QBje1BAuEE9RV55Oe8dfpN0zQJrF+L/7VVGOEwzrHjKPvwR7KywemxGHkuGUyDyaEzyIZBEhubimaiCZkT3hpismVok6rBqu1NLJpaxhu7WzO0R0eCwyYxc3wxjR1BEsMaOWRZ4rIZlphuvLWF7kceSiViPEaCkuQAiqlnyq0NGmdTyCkvf2vBdI5JCW6JH+SgmkeXo4CI7LLUd4ZBwiAiu3AaKjqCs65yamOdGU06JtDormLfkGaiokSAB9teRTYuzB2iC4mbuzZRG+tMte8bgC5JbJpxG5GiSsKNmfwp5/CLFw4PyvaVsmByKVsPdtDRF03F1zXd5HhbCBAc8tSBhxEl+8ZGWykXERx1Y6j6/N8hORzc3hvhxR8+nP2YZILIkUN4pk4DIGfMGMYVyCRa/en7yTKFt95B16MPWTQJmgaShFAUSt/3wTQa5z8WzEEelhE/u4Q0vKsNuR6NoodC2AoLUzG3cxUnZzqCJJI6DYN14f9bCCFoqHx7HkzvM08RWLsmFbOMHjpI88kT1H79m9hLLe8+dvIEnQ/9lm5/lIcrrkOX7BzObeCkpwaPHiWoeLJWYYSilgc7kvaogBQHNVhhJpdDYfGUMurLc/nR0/vTVjB3Lq3Habeu0/f8cxnn89tyRk3WpV9c0G86SfoHuCO8D4DnSy/nuLc2w0M9183Ya8vjscpryVXDVLd3ZzTRCKB4sA48PxlkQqSJ2YFjOI3kBbnZwaoeGhPtSJsgJEA2dFxnj7E76kYSZA0bnYOqGWw73MXcCcVUFHno6LuAUEMWg2YzVCbEO6j63N/hHDs2ZVwrijxctWQc6gt7MiqfABJtbZimmdq/6nNfpOPXvyR67OjgpQSmbtD1218hud24pkxD8/djLysj/5rrRlQLeqehFBSg5BdYq4IhEDYbuQsW/knu4S8J70pDbqhJuh7+HeGdO0GWEEKi6I678C2zOiclIWio+PPQA9SjUQJvvJ5VfLZ/1cuUfeDDJLs6af3P/8BMJnm5cgUx6byeZlK2oQsvIkvFuRAwqdYSYZg3sYQuf1PaUh/A5ZCZN6mE7Ue6MQyTGWOLuO/qcSAgmtD49B3TMEyTU60DvLajmafWneaJtacYU57L3a2tGdcsSg4gmzp6Fq96KGyGysRwEx4tRlh2kUTGjs5l/Qc44amxuhYHjZEwdBb37UNg8FTFMqKyw5qARqiyj8pO5gaOsLRvL8LUkbBCTrtzx+PSE4yLto4olmzPySERCoOWnghUMCiPdqGqBhXJPjrshZijeK6qZrDzWDcl+e4LTh5AGve6bGjkqhGSigNnQ0OGhzxu+eU0vvoMRhb65NiJ4wTWriH/6musc+XkUPW5L6JHI5bAdlurRaFg6OgDA0T27aHmH/8ZR+WfxoCfgxCC8o9+nNb/+B6mYVg5IYcDW3HJJU6WLHhXGvKuRx6yEoaaChYFBj1PP4FSUIB35qz/69tLg9rdnVVFHMMgPihZ5399NaamkRAKHc6iDD1NXZKx6zqKoaV4yxVZYFdkbrvC4m5ZPreaNw930R+Kk1QNJGHlBj5842RmjS/m/Ssmpc63+UAHv3/dogUwTHA7FcKxJOqQePnptgEadQ91w55nbKSFHC1KwJYz4tK5JNHPA22rkUxj0OjLCEw0BF2OfKuaY8ixppA47q2lNtZFVHaCkIgoLlqcJVTHutO856SQOeytY1nfnpSxNjFJCBvriuZiIljeu52poTNIpoGEmWrCkbxeYjfcS/zx39LsHYMpBPWRNtxGwmJ/tOdxef8+ZgeO8/O6O9Lj5KY52JtqwuCKRKhJpsV66JKKs3LZZ2AwXDIpdJa5A0d5vmwpi7/3Har+7stpghGSw0Hl579Ey7/9a2aIRVXpf+WllCE/By0QINnZkSHAbGoa/jWvUfb+D/GnhrNuDGO++x8Et21F7e21modmzLpUsZIF77oRMeIxwjt2ZMhbmckk/a+89GdlyHsDMV4+GORoyXLyE0EWBQ5Rnhjk6BYCW5kVi052tINhIEZRtVdMnbva17C9aAaRmvFMr89noTeKbedGzm7dgtbTzYdKKzgz53qOxx0U5DhZUqng6z5KJNmZ6vRr7grx+9XHSQ7x3BNZeKkNEzb7plEXaoUhYy1j8r7WVawqWcQpT7XljQoozHUyEEmiaQa3dWzAMRjqAJBNDVXIdNgL2FQwMzNEJAQ9jgJiIl3U+YWyK7izYx1liX5MIWE3VOKSg4p4X9p+AuhwFiGZBknZzp68SSQkB7Kpc8xTQ0Wij2tjR8n/+3/h7x8+gFZ3N2AimwaiGK7t2c7E0FkO5IzlgfbV2EydFd1bebHsckwkJoXPckXfXlx6gt2+CezMm0RcdqIKhbKTu5mWP559rjGjvwxDJq5jOXUc91YzKdxEorOZwLq1FFy7Im13V339iLF1PZQpiqz19yHkLD2lhpEm+/anhuz1kr/82v+z6/+l4F1nyPVw2NI3zALVP3KS6k+Nzv4o3/zdTpKajmHPp8eWR6Onkts6NzA22oaw2Si84SYAnGPHEjt9CrumURnrptVVkhZDlg2dKdEmSolww/IpVMZ76X/q18SA6NBa4aZG6jp+xcKPfpzQm6uJPLufbiGBJJDdbqq//FXW7e1LI/0aDV2OAkJ3fIjCzS+TbLfuOXfxZRRXVfPgm1tAtKEsvJzc+Qvwuh10B2KsXbOPnMZoRuWIzdRxmJrlyWeBISSKkoFU7TVAXHbyaNX1FCcHuLZOpnr7SnITUaaFGzOOdxhJTCFY3H+ARf6DqZLNmcGTHM8fx7jvfpdP/89+qyZeWM31KV7x4gVUxLqZGziKLizyqomRZg5H2pkQPsvU8JnU88z3H2VCuJnfVd+EJmSeKrmCT4fWExk3k5OtAxc1rpqQcRoaV/Tvx9SThN7cmmHIAWylZZkEVYCtrCxjm6O6Jiu1rbDZcE+YmLH9Ev688K4z5Iov3xKcHS7uIgSuseOyHvN/gafXnyah6uedKiGhCYnXShYyIbyBsgffh3OwDT5/2XIG1q3F0HVu7N7C76uuJynZ0CQFmyKjaCqyafJC4ULMdce4pXVtisFwOMxkkq6HfouZSKT9sLV4nOZvfQNl0nWYhntUrcxzUDWDmvkzKb52kVWXLEQqnpt/VabcXonPxR2X19O4mqxZR2GC00gSlzMrf1x6HI+Z4KauLbxQdgWGEBhCxmaouEqLWHzrTM6++QpHcuppcRZzXc+OtEapskQfRQk/i/wH0+LjkqkzwX+StdtOE41lHzMDwUlvLXMHjqY8fQHc2bku9f9zsKGTq0WZEjrN/rwJaEKmUfWwYn4NLd1HMkpfs0E2re/Zqw/ypivZk8cl9z1A+8/+K72xx27Hc/u9GYpVSp6P3CuWEty86fz+koTkdFqiIpfwZ413nSEXikLRXffS8/ij519YIRAOB0W33v5/e3NDcLzFn3VlHHN4cS67Gz0UQgsEUHw+lDwfNV/7F3qfehLp6GE+2buaE44yAoad4oSf6mgHJhKmJLAb6gXZ+owsS2+wVjNz9r6Ix13Ni8VLLsqYF/us+nYhScQSGkfO+gfVZfJT1S1DYSspQXG5MCLpXCCqkDmQ20B9pJUT3tq08kXF0LiqdxcGMmOjrXyg5RUO5jUQVdxMG1fCle+5BtM0eWTcHXTFJUxJpi7awaRIcxqL4JTQmQxiLrD4yvve3I4hW5S5Tj3BrIHj1MU6CCheduVNRJNkiwvc7YVEDPTs5F1g1XQ3RNrYnzcBQwji+aVMrM3PlFQ7F1fP4KMxGRPrICw7OZlXj3fcPDwDcQrznGn7eaZNp/Izn6f3uWdIdnZyrGwKrzsnEXvDj7RuI8tmVXLnlQ3IgyvUkvvfg6OqmsDrq9FjUTzTZlB4y23IOedXQcnOTsJ7dwMC7+w5qaqpt4pkZwfxM40ovnxcEyYiRlglX8LF4V1nyAF8VyzFlp9P3ysvovX14xw7lqJbb8c+GHP+c4DXZSOSxQM0NY2Bxx4mamqgGxTedhsFK27EXlxCxSc/TaKlheZ/+1cmhk8MO9JgRKrE4RBixPiqpKmMCzdTnzeORsfoP2Kf93wCbvfxbn718hGkQeNvmCYfvXkys8enq9hEDx/ESKTT2p6rsQ4pbm7s2szs4HE2FMymx+HDp0a4rH8fY6NtxCQbNkOndmoDkydNxj1tOvZi6/y/fuUwnUlbil3o5bIrCPbuYeHAkSHXEValScajC5xOO6jg1mJ8sOVlnEYSm6lTRTeTw2cJyy4E4J08CSMaI3bimHWaLIIJBqQIy0Aw67ol9IcS1JR6OdUWBEwUXeXe9jWsL5pDt6MAVbIhmTqSaXKDfwfHchtYVTjfondoFrz4q23cubQ+Rb52Du6Jk6j56j9xsLGPl589SDIx+BLoJmv3tKEbcP9yayUqhMB3xZX4rrgy6/fZ/+or9L3wfKrrs+/F5yi8/c6sYZ2RYBoGnf/zS2sykCQQAtmbQ/WX/x5bQeFFn+cS0vGuNORgeSueadP/r29jRFw/v4ZH15xMKwdUDI2J4SaUeCRla/pefAH3hEk4x1jVJ/2vrbywjBcX4NAeZsQNBH5bDk4jiUePYzM0loUOohomTkOlsCiXPWp+WgLUbpO4ZYkV+gmEEzzy3B4u79nHuEhrSvXoly+YfO+TvpTMHUD/ylcyjN85zu1buzYhgKp4Lw+2rx52j3DIU8/8xBk8kybjW7Y89VkommTLwfR6ZENIbCiazZhYO6XJAAlhY3/uWGaGTmYOhxCcLWyATp3F/oO49QTy4KxoqQXp5Gthksg8FyzihvdezxgPRA4dpOs3v8o4ny5k9uaNx2bqzKnLwayq418f2jnkuxbMHzhGRaKXB9tWc9JTxWl3JW49zrRQI5U338C3DtrQTWE1Tw0e9/T604SjKoosMXlMAQ0VuQghiDed5ekXjpPU0mkDkprBhn1t3Lm0HvsFeiWSnZ2WER/ybpm6Tt9zz5Azaw624uJRjz+HwIb1hPftyQjbtf7w+4z51ncv6hyXkIl3rSH/s4cgTaxZmCZ1sU6u69mWtpupqgxs2Zwy5MmOjhG96SGnvmgO7WOeGl4rWYgmZAwkquLd3NS5CU+wlwcDq+l0FHBMraMqV6fdWYymG9htMrcsqUvRGuza18R7z76IS4unSgGv6dlBRbKfXcfGcfWcKgw1SXjvHhJt2UmuRmvWObd9R8EU5rU14pk5Gy0YZGDjehLtbTRJPhx6fkbbvIlgfcEsZoVOsSt3An32PF4rXsCy3l00u8oAk5pYFxsKZ7O/04pdj420poz48Hs446lgt17E4T/s5XsfX4TsdmPaHRjJJNLgXepIbMqfjttl4/YbprFgSinfeWR3RlftlFDjIGujyYRICxMiLanr9K5ahV5xS8ZsrOkmK7c1Y5omK7c3MbOhiDv0Y3SuXUdb1W0jzt7hmErBBQx5eO/urPwrpmkS3rub/Iv0ygfWvZFJxgWonZ30PPMkxXfec1HnuYR0XDLkf4aIJTQee/1kmj1uiLRwc/fmzEYV08QYojbvrG8g0XR21PNrSChOO8Tjo+8nJNx6nPJ4L42D1LItrhKeqViGQ09SkvSzN28C2qA6j6zp3HLZGG5YWIckCTr6IqzZ1Yr05lrK9URaPbfd1Jg2cIKWgJ9kl0Lzd/4VQ1Uhy4/8HEZaRQggiczEcBNCEpz5x6+kiMBQVXKFzEclGw9V3UDQNoRqQQjOeippdZel2CMP5Y7lUE4DkmmAwOJ7H5ILiI8gOmEg8VrRAhBWF+yWQ504hY8nK29DFTI+NUSOFsOhx1kUPcX9S+aQN9WqHjnbmZmTyEbxe+5ZHfEw+WqQfntm09o5grakarDvVA+VHUfYW7goK289gCyLi9TeHG0NN3quxDRNYsePEW88jRYcWZfU//pqClbciOzxjLjPJWTHJUP+Z4gTLYEMvug2VwlSFk9bOBzkzJmb+rtgxfUMbFyPOUKyrU/Joc/hI18NUszohlwxDWri3ZR1bmRD4Ux2+yZjCJkuRwGYBi2uEozBpKOJtcJ/aUsTs8eX0NQZ4nerjqIbJnf1t2AzdY55atmUP52Y7KAwOcCSwEHGJ7to+sZPsnppbwVCwOyB45iDHZdDR8pm6si6zrLe3WwonMU1vTuoiXayvnA2u30TMzRGGax4yYadvklc17MtxbMClu5ni6uEqM2iAlY1g2Nn+znWEiA5WGHT58inz5EPpkljTi05ReM417HgcSopqoRzOJDbwJV9e7KaXwMxYtXRUCQ1k72eBlqcJVkT00LA7ZfXZxVMaeuNsOVAO9GExuzxJYyfNRvx4nMZPCdCCLyzZwPWCrIvGCdniOaroaq0/ecPiDedsb7jUZKaQlGInz2DZ8rUCz7bJaTjkiH/M4TdltmYEZOdrC2cw/L+PVaNs2kiHA7ck6fgmT4jtZ+tsIjyz3ye1v/8QZqsmYrgubKraHaXIZkGhpAoT/RyV/taHFnEKdLux9S4qnc3R7xjiCmuwSoKkTXUoRkGX//1jjTq3qjkYE/uOHrs+TzQ8TouPUFcsrPVN5Wql55GeQtGfCTlHdtgnHokSEB9pJW6WAd2I4kEnPDWZFSEXAiHc+opSfYzZ+A4+qDgsYFETLJTmAzQZ/fhsEl09Eezk5AJgYrMI6+fZMb4EiQhuGZuNS9vPYtIxPGpIYI2D7t8k5g1cCLrMxlCotuRf1H3awiBjIGOzORgI4v9B/DqMTocReyqms/yudUZx2za386jr59A0w0ME7Yf6WZijY8Hb7sT//PPpMQdhBAU3XUPtqJi1u9r46l1pzAME90wWTy9ggeWjSW8ZjXxM40putzhnaNpMM20CplLuHhcMuR/ZtBDISp6T6NkMZOHiydzzR1L8Z3ZjxGPkzN7Lu4pUzNLt8aM57c1N3NF716q413EJTvPl15Bl7MwzTNrdxSxungBN3dvSV1tqFr9UMiYfLDlFX5dc4sVax6Jmc60Wt6HIikkuu35LOvbnfJk3UaCpf59iBE4TdLOSbrY8Dn5tqH3ee7zqOSg0VOJZBrUR9syaG1lU08dl30qugCEYF3RPJpc5dzesR4TSz5vfKSFhmg7T1QuR8+vIZIY/bkicY2BcJL8HAfXz6/GePU5GjoOoQsJxdQ54q3jocoV/E3ry3h1a+VkINCExMull6VNQAKw2aSMicOuCGYNnGBV8ULm+Q9zef++1PjXxTqoaVxJomUujurzxjwaV/n96yfSkuwJVedYs5+mm2Yz7ZuziezdAwhcM2dxOqqwYVMjr25vTkt2bzvYQTyuct3OzeeN+GiQJGyFhTiqay687yVk4JIh/zNC36pX6H/hOYRi4y6bj8eLl4LDgYmEYZhcv6CWifPHwPwpo57H47QRVtw8W3HVqPvpksIxbx03dG+l2+bjtZJFXNG/l/pYR8a+AnDrceYFjrC5cObFP5RpctpTw7W929PCEWB50RdjSodPGRJWTDzmzac430WyvR10nX0541hTPA+BiTBNDCFxS9cmxkdaUJGJKK40D3da8DTb8qdmUuqOApuhMjV4miv692EbEvO3qlc0bunYiKtf5vV5D3I8HMWlxwkp7oxQjWmauBzWtuC6NTR0HMZm6iQlG4dz6olLdqaHG/lF7W18tvEJFExUofBI1Qp6h3jjkrAUp+5dNpYfP3MA07RCHLIkmBhrY2K0Ba1HYkKkOW38BRb5Vu8Lz1L56c+mth9tssJ6w+ueEqrBjqPdzLltKvZrV3CqdYD/99h+DMMkkcz8HpOawZ4TPVxhytmNjCyDLCNJEqZhYC8to+JvP/cnocj9a8QlQ/5nguiJ4/S/9AKmpmFqGmXxGJ8OPUlzyXjy7n8/E+sKLprLXJIEV5lNvG6MuaCRMoQgLtl5vOpaErKD7flTqY51pRmpc1AwmBg+m9WQK7JIiUunQQiCioccLXZR936xsKHzUNHlfH5cHD0YIhBOsKFwZsbzvlh6OR9peo5+ex6d9gLmDRxLJV0XBg5xxl1Ot6MA7ZyG6CiGxK3F+EDLKziNRMakdA55ehSicPXux7kuEsKwphU2FM5kj88iHlNkwezxxamGKP/qV7GZGic81bxYejlgfS+SaaIJCU0oKKaKw1SZHzjCmpL5SA4numFSVezlb++chs/r4N8/sZgNf1hF//HTjEl0URqxSi6nhRsxsmVMTDMjMW5TRg41+cNxkqpltH/45L4LdqHKkoSYsxDx+gsZJbG2omJqvv4Nkq0tyB7Pn1UPx18iLhnydxhDuZ7fCgbWr81I+CkYNATPUuUM48p5ay/6dctnoDz1BptypxBW3MimbsmPDYsJFyUDbCqYSWIwKdfkLmdz/nSu9O/Lmix16un3KAmor8hl3sQSnlrfmFYyacHEq0eJSXY8RoLhMBAZmqIXAwP48NnnCJ+1/nYh+GTTs7xWvIBDuWNT+wlMXii7gojiZnyoKa10UDEN7m9bTaurhC5HIZsLZqCK7HJ/Nj3B0r49ePTYRd2vIxxIG78r+/YQUdycyq1jcm0BH7je4i/RoxG0UJikUHip9LK0icgQloZpl7OA2phllKeHTjMl1oL8iS/jq62kxHdeGUrfsZkJu7NobUKq/DHjuYrS678n1eaP+P42dYb5+m92cNMIQt3DIQQ03LCczuP7SLS2YCYSCLsDIUuUf+wTyA4HroaxGceF9+/D/9oqtIEBPNOmUXD9jSh5vou65rsVlwz5O4Qthzp4dkMj/lCC/BwHd1xRz5JpF2989Ugk63aBwIi/dW82Z/4CLmttYerrLyNsNvpx8lDFCjRZRtXNlBpOSHaxzzch7diDeeO40r8v63mVYZ6o3SbzNzdPocTnYiCSZM0QpSEhwC5LTIo24zCS6MOM9sUa8WwNTNKwbQommDrX9Wyny1FIz2D4wRQSU2MtzO63OjijksMKsSSDKZHkulgXdbEuem0+DueOyQiDOPQEZfE+xkZbL3rSGX6/dlNncf8BovWT+dw9M0h2dtL0P78g0dIMuo4m2fElQ/Q4C4Y9u+Cgp57yeF9Kf1PWktif/R1FX/2ntH39q197S9U/wm6n8Jbb0rdFgrzHcYbfxcpQhZK2QlE1g/5gnG1HOkcUFj8Hm6Fx59Lx2J1Oqr/yD0SPHiF++hSKLx/vvPlp0oRD0f/qKvpefC71HIHeHkLbt1H7L99Cyfvz0Aj4c8QlQ/42oQX8HH7kCZQjR7hBdrI9fwqnqOaR146DgCVTL86Yu+fMpaOxDUcinJagM3Ud5/+CzEsIQfGdd1Nw3fUkWpqp8fmYmFvE2j2tnDjSTO7Zo8z0H6HbUcSuvPG0uUpTCTRNktERWROuNslkcrKdo/Zy3E4btywZk/IK71zaQFmBm1e3NREKx5lQ7uauFdMI7JAIP9uKS4+nnXEkLzHjWS5yG1jJzBnBk6wpnj94EYmZU6tR97bzgncWZ9wVKJLANAyu6NmVJtZ8Zf8eGj2VxGQ7hpARpoGJlTCMyM4RlY0u2Ck7iBwtSjSuYyQSNH/3WxiRSKp5y2Ukua9jDT+tuxN92HWO5DVwNLeeSeEzXNezHZupo3Z10vPs05Q+8J7Uflpo5BrtDCgKpR/4EO5Jk1ObjESC5m99g8KBAT4oufmf2lsxSL8XTTdp740MF14CrNWDU0+Qr4ZYZu9h2RyLflZIEp4pUy9YVmjE42lGHABdR4/F8L/+GsV3XWoWGgmXDPnbgDYQoOlfvo49HMGFQb4apLSzn80FM9iRP4XnNjZelCHfdKCdJ3YL1IobMIAJ4Sau79mGXZEovue+Eb2Xi4Hs9aZ+rPrJE0x/6edMCYctGTC7HbctSp6jl8baOrY1x1BNQVKy0+SuoC7anuGByrrGipb1jHNX8kLZFTy78TSRhMptl9UjhGBS8y5K976EUBTM0wbRo0XUfOYLfPngXczr3MPsgeMjqu+8E5CwmBAxDRTTYGHgEFLzcZ4rvoKz7nJ0A3QTEBIbiuZQoIWpjXYQUtwc91QTl2ypeLIwTXxqiLGRVmymxoGcsSwMHE67fx1xUROSidVgNb02h9CuHVbMeBgnus3QGBdu5ljOEG5yIaz7EXAkZ8xgAnczpqYR2rY1zZDL3hy02MWt3mSvl9z56ZJpwe1vokeiYBg4GZlczWGTWTKtnNd3tZBUdUBgM1SqY13c3bEWyW5n4pe/yFv9lhNtrdk50TWN6OFDcMmQj4hLhvxtwP/aq+ixaFrc1W5qXN6/j7154+m/CAfp0Jk+Hl19wirdGvTETuTUoRSX8PHbpqWoat8utICf1v/3A0tM9xx0Ha/DwbS//zRLZZklLQFe39mCP5RAn/cAzs1PoHZ2wrDyMbup0RBtozbWSZMoZ9WbzSyfUw0nD9O/8mVMVU0lt5Id7bR842t8UkgY0Wgq0XixXuxbhQGoQmFu4BhTw42UJfqJyE4a7SUMD9+rko3XiuYTl53oQrI87iGhBEOSCdvcRGUHDdFe+pUcmlyl1Ma6MBCWapFQcGeJ/Q+HAFx6gsvPrEetqkz/HgZhQ6fAiKJIKfqU9GcTMsc9tcSkHbiMJOYQThotFER7C3z62cr84mfOYCat+3IbVjip3VmUVupoVySunFXJdfNrmFxXwMZ9bYTb2hl/ZhfjBhpRfD6K776Pgnlz6enJzqI5EpTcvLRnSvusoCDr9kuwcMmQvw1EjhzO2uCgY4kcJEsymy2GNlMAvLK1Ka3+FqwW+iNqDlpp1Tt2rwObNmaqj5smeixG9OhhPFOnM77ax/hq3/mPl32Dvheepf/VVRlEVjZTY1ykmSZ3Obph8L0freS2jg3kDI/RmiZmLIpEZt13Nr6XbAZeOJwYhkFSN8EwsaOl7TP0GAmYGTqVdnxUdiCbVlNMxriMIjkHlrFfXzCTulgHk6LN6Ej4bV7sRhJVKPTafEyIZWqTZoMNA/XQAULjp6LJNhQ9vZJDsju4+c7L8J80OdoUGOEsJmHFhUvT8MyYmdqaaG5GKLbshnAYm6Ww2ykaFhsHsFdUIOz2VGjj1q6NPFp5HTHZCTYrUT5lTAHL51rv5aTa/EHN16mYxnJMVUXY7f/rEkJbcTHOMfXETp9K+10Ju538667/X53z3YJLhvxtwFZQSLK1JWO7jEHS4eHOpfWpbUY8RvcTfyC07U1MTcM1cRKlD76PvmD2NnlZlghFk3hd2aso3irUvr6slKoYBprfn/UYIQRqb+8IVKyC5GBru9A1lrVtwpO4eI/wjKuM0oQfp3GeUEpDImDPxYZOnhlHIFAKC6j4+KewlZRydutOdh7upK0/xlWtm1EMDXkwWCuNyCYC+cnQKEQtFzA6pkm/s4Dnyq7khu6tOI0kPjVMi6uElSWLmRg+S7EeoiB5ceo+fkcuv9tv8IDsoUAPplYompAQDhdyRzOlUjFHRzyDIF9SkXNzKbn3/tTWHt1OMpFk+NtiCoGztg7N348eDuOoqqb43vtTJGtDkbf4MvpfegE9qdLpKMQQgr9pfZnOsvHYbniA+oo8qkq8GceBFQcXjosrjx0NFZ/8W9p//t/ET58CWUYgKL7vAdzjJ1z44HcxLmjIV61axUsvvcThw4cZGBigurqa+++/n/vuuw/pXU4Gn7/ieqLHjqQlZzQkejwl3H3rPOZPtvi6k6rGyW/9G3J3G9JgtUjs2FGav/NNxl71MfqDcYZrCgigKM/FwcY+Xth8ht5AjNqyXO64op7aMquN2TBNGtuDxBIaDRV5uJ0jf53uCRMJ7dyeuaQ3wVmfWQIGENq9i9DuXVk/M4TEoZwGMA0K1CCVid7Rhmr4JVlZsgQJk+U9O6iPtqMLicM5Y1hXNBdNUphdLPE3t0zBVlSc8vDqr1xC2UKVz//XFg7X3UVxMoAuJPKTQW7u3oLDyE7fq2BwZe9u1hTNw5BGZ/nLwOC1z3gq+e+6u8hVw+SpYRymisDkRMF4bvnkvRS7JVq+9230QGDU073pnUjSEPy+agVL+vczJXQWgYldT2IEg/S/8BxVOZUoJVdmSa6aXJEbouKye8hdsAhpiOH8zU4/y+w+ShL9aUlqDYnAVbcxY8kMLgTZ40H78Bf575UnUU2Lb1KSJD528yRmTKm82BF7W5C9Xqr/7itoAT96KIy9vPyS2PJF4IIj9Nvf/paKigq+/OUvU1hYyPbt2/n2t79NS0sLX/nKV/4U9/hnC/f4CZQ8+F56Hn8M0zBB18gdP5EJH/tEisEtHFP52X+/wvVd7UhDk3ymiRGPc+WWh6nQvezIm0Sr0xJBsCsSd1xRz67j3Ty06lgq9HKwsY/jzX6+8uBsHDaZHz65j2hMQwjQDJN7rmrg6jnnwzl6OIyhqig+H9658+hf+TJqT3dq+S3sdjzTZyCVltEbiJHndaQ1hPSvehmGNXLoCEwhsa50Af32PMrjPdzZse4tjVtUdhKVneiSzDMVwyTfTCtQsrcP2lQnW14/Qd9AnCljClg8tYxHXjuOqlkCC3Y9ydK+vcRlOyILxepQzAqeoNeex568iRelbGSTBeqwBiePHuOuznXkqyEk00itJCL/+jgxtxsjmQS73WJwlBUw9IyQRnfxGIw4JCU764rmsa5oHu9vfplSPZ5aUVSG2pjqPsOhnIa0INLiqWW896Z02bVEUmft3lZaeyI8VnktN3RtZXy0BQMJVZJ5tXgR+mmVGUsu+MjEkxo/fqOVuLCnrWB+9uppvltbgs/79j3ui4Xiy0fxXRyfzCVchCH/+c9/TsGQRMPChQuJRqM8+uijfP7zn8duvxgKzL9e5C25nNwFi0h2dSJ7vRmNC89uaEQJ9GavazAMCPQxnj4aom1sqlhEV910blxUx8xxRXz+J5sz4udJzeCpdafo8sfwh9K966fWnaauLJdar0nHr35B7NRJhBDIeXmUfegjVP/D1/C/upLQzh3YXA7cS5ayXtSw+kebAOu3u2JBLbcsqUMIgT6QGS6QMTEUhesevJaDLzfy3tZXs1ZtjERuZQCSoWOOYEtztQghxY1pynz30d3oholhwtEmP89saKQq1MLfdO2gUA0Skxzs9E1k6sBpELC6cB45WpQ5A8cyOi8FMD9whP2549DF6K99ic/JHUsb+O3KoySG8Jfc3rGewuRA1lpyIxpN+7vbkc+6uitpTjqwGyoL9HZuuWYKVZ1eOo6dV6V36XGKk4GM/MF1XVuZYXbRvuxeFEVi0ZQyCvpbaf3RD4n39HLWVc4brgn0arbUvKRJNl4sX4pDi+M2kgRsXkwhkR+6cDIWYM+JnqxU9oZhsu1wJysW1F7UeS7hT48LGvKCLNniSZMmkUgkCAQClJSUZDnq3QWhKDgqsycmd5/oxq3kXZCgSdY1rureScM/vBfJZicUTRJLZM/gn+kIZXUqVc1g3d5Wrt7+qKWebhhW2VtvL63f/y65V15J0c23U3T7nRQX5/DQi4dYvfVMGtnSqu1NeJwKy+dW4xo3gdDO7RlCFYpNoWF8NVfPUWlpKaM62pEyRB2OQk56qijSw4wfOJPGQW4COrC1YJpVUmeaad6xzVBZ6D9ISTLA3rwJHPXWpppzkppBVayL29rXpcr/3EaCRf5DtLhKyYnFMZDYVDiLzQUz+GTTM3j0dAPm0yLMCxy1qGuHNbtgmilWSK/LzvxJpQjgdy8dImmauJMxypL+i2oICihefl+2HFskyZWBXdRGO4grTtYeKuH6Gyez71RvGilVNgigWvWzdLmlEzqweRNtjz2SCuNV0ElxsYOu3IaMFUZCcZLAmTrP0AT2aIjENPQsKxtNN2jZvo+wK4Bn6rRL+pp/hvhfBZ92796Nz+ejsPCSxt6FIEuCLmchXY5CyhO9KNk6KQYhBCRbW3GOqcflUAb1LTMNh8epEI4mmRo8zcyBE8gYHPKOYV/eBAZ6B9D6+yxvfyhMk+D69UR27ab2n78JxTms2t5EUjUQpsH4SAt10Q5Ciov1G+Isn1tN4a23EzmwHyOZoEvJ41BOPZpiZ9HiSSBJ3L6wgr1rXYio5WmvKZrPgdyxyIbG3zY9nWbEwUqQdjsKmBRuYkyknQ1Fc+i1+1BMHU1IzBo4wazgSQRQkvAzJ3CUR6tWpBpkLu/fn1GDbjd1amJd2EydikQvB82x+LQwMcmRYcgBlvbvpS7Wwd7c8Zzw1iCZBtd3v8nEcBMIiElOAmNuJdHWSulzv+GzZ85gCIG/sMaK1Y9ix5NCodfuY3feeIoSfu5vew1lkErYVAdg2zOISCOfueM9/OzFw0TjGjHZSY/dR2myP90rt9nIWbTY+uo0jZ4nHkvLxSgYNHoqLxgmcthlbrv84kpYJ9T4sr5zNkOj9uQ2Wo68jHfMGCq/8CUk2zuThL+EdwZv2ZAfPHiQZ599lk996lPI8ltLHBUWZs94v1MoLv7z4zK+bmEdz60/xZMVV3NV726mhhqxmVr2IgrDoKi6FNfgc9ywZAyrtp4loZ43Xg6bTGWJl9otzzM+0pJq2y5KBpgSbUKadQeSJGVvxjBN9GiE6NrXMBo+TCSuoRgaD7S9RlFyALupoSGx0H8YW9t4imfOoPBH/8Ejv3qNlf4cdGExnB89bnLMcYprjq8kv68FE2hxlnAwtwFNUihKBtCQMwy5jInd1Pl1zS2MCzez0H+Qs+5yZNNgTuAYhdr5umO7qVGc8PNA62t0OIvYkzuewhEqQ2RTxwDK4z18tvFxTCFQTA1jeLOOJOGtH0N9axt1PZvZHp9AUTJITbzDulcTcvQouRufoWXTsynlJck0ye85O2rd+/a8yWwqnIlsGiQkG7XRjpQRh/MhpsTh/cy440Ye/9YN7D/Zw+b97fRNupfyNx5BMjSMRALJ4cBVWcGE99+P7HQSbW7OKt9nG4VH3uuyMX9KKfddM5HyootT3CkuzmHJjA62HuhIvXM2Q6Uq1k1trAMBxM6eRd/zJqU33XhR57uEi8fbGa+3ZMh7enr4zGc+w7Rp0/jIRz7yli/W1xfGGF6e8Q6huDjnLTcg/CmwbGY5+050c6YjyLqKxWyUljAx2cGK5rXpsmaShL2yirDiITz4HDcuqCYcTrBxfzsIy7u/alYVezcf4NpIc5p3ajN1ihN+Su0R/CM0VQCg65zZfQjp5iClPic1Z3ZTnAykzmUZNINj3/8h9T/8MYGowqpQAZo4b5TjSZ3Nu5sobe+kdjAZetRbh2mazPMfZkqoEbuZWUFiAL12HwAnPdWcdZejSjYUQ+Ng7ljubV9DVbzn/DNhUJnopTzRy4zgSbocBXj1zM7Fc55skRq0DObgK6ZjYiBQhYLARM/Np/4Tn8FIJPC/torLT50k0d6BGLZKMpNJzGGergQkhcymgpkczB2LLiQaIq0s691Nl6OAzYUz0CSFcyPv0WNoQs7sYjUMWlevQ61qoDLfxb1XNgANGCtmEt69C7WvF3tFJfGWZvZ87ksYNjv73XVMSCQzfqwzB06wuWAm+rBKHAE0VOZy+HQf/3hqM4umlHH9gloc9gs7Xg8uH4dpGLy5p4nieB/Tg6eZGmo8P4mpSdpfX4ttwRWjnufP4feY7O6m54nHiB49guRwkLf0KgpvuuXPsgpmpPGSJHFRDvBFP1EoFOIjH/kITqeTn/3sZ9guLa0uCjZF5sv3z6KxI0hzR5DiSBdlAy4SOVOJHjpotbLrOvaycio+/Zm0Y2VJ4oFrxnPXlQ2EYyq5Hjvr97ZRGevKfi1Dw+jqxDtrjiWWO6ziJCbsPFe+FMU0uPYzn+UDqvXiZPM0DU0j0dLMoYDdUucaZo+SBpxwVVEbsbjLZVPnvW2vUaAGU8YrW3NP7rUrEAejmIgU0+A5xr+ny5fh1mKEbB4Kk0Gu7NtNXazTaiYanKjUbMZxEEOv1W33sblgBh2OInQh4TSSRNz5fMO0U1KSh+/q5UhuN8mO9uzhkiwe8FPlV9PuLEIfvN/j3lpaXGX41FCGXJwmKdmpY4Hgm1sI79tDeMkKXjerOdsZItdt58ZFY1g0Zy7N//rPaL29qeqicaKFiOTEo8fTVjkzB46z0zeJqOROv3XgUGM/umFSGu8jcWoD61bCkntW4J0xIxXjVvv7MWJR7GXliMHVtSQEDRV5nNgV4572takVX9o4v9USzv8DaMEgzd/6F4xYzFqJJpP4X3uVRFsrlZ/6zIVP8BeGizLkiUSCT3ziE/T19fH444+Tn3+pLOitQAhBfVkOrucfJnLoEP1qEmGzYSIovPk2PFOn4qgYuU7XbpNTKucuh0JccWU1EoasIPvyKb7vAQJr36D32afS4qrPVFyFAdzb/kZWJfj0kxkIxTZYjnj+WnlqiMX9B6iOdaXdwZyB43j0WJqRHRptFYP/Sp79FTTcn0GnC5awcXywNrrTWcjjFddQEu9jSeAQ4yPNvFkwnS67j6v69lCUDKTOORyd9gIerboOVcip60RxgWbw6At7uf3sq1Yj1wUY/IaiyVlKq6skrV3dFBIJSaHflrkkPuOuGDUU06k7eKTRhSr5AUEsEeP3r5+gY30nMzo70/a1mzqKHrUStKaJJmRkTLYXziSquLOeXzdM5gSOcGXfXuTBUsn2X57BO3kKJQ++l45f/JREcxNIEkJRKH3fB8iZMw+AGWOLeNieR1R2YNOGhQFtdvKuuPLiBu3/EIF1b2Am0/lsTDVJ9NBBkl1d2EtL/w/v7p3HBQ25pml89rOf5fjx4zzyyCNUVv5pGgP+2hDauZ3I4UMpLotzBrb/lRfJv3r5RZ9n9vhi/uCtQhcy5rBYuyRL5C1ejJAk8pdfQ+7CRbT9149JNJ1hwOalOtbFtOBppAsZcUDJ82GvqGB6oY7JMcAy4h9seRmboWVUb4ykl2lAqjFeADI6PjWEP4sCfEbiTgi6XUU877ycqcHTHMmpR5cUzniqqIl2cmdHpt6oCawpnpdZlQLIhs7yzb8hMVKOYhSsKl2cVdlek2zkqhESg4yJ56BKNl4qWcIdXRtSzz50hWJxnw+ZJE2Ty9u3MWXgxIi0vQ5TQxUyHc4iBm56D3csbOCaqMpja05wpj2EaZ4X2XNrMa7q25tGOyzUJNFjR2j53retbt7BhLiZSND5619hLynFUV2D12XjQzdO5sVnl3FP82sIDGTDQJJlcqfPIHfxRRSl/x8jfqYRU8sM7wlFIdne+u4z5N/85jdZt24dX/rSl4jH4+zbty/12dixY/F6/7gJzL8WDGzelJUoydR14o2NuMZdHFWty6Hwt/fO5rFHQ9zYvAa3FgcBitNBzSc+ldZEIXu91Pz9P9D70osYL7/IZdEDSCMu+IdAkqj49GcRQuB2Knzq9mn817MHuKJzL3ZDzd4KryhZW/mHL8IlYG7gKK8XL7ioxhwAU8gczB2bdt8trhISsh2bpiFhGcmw7ALTsBqrspzbFLA1fyqKaTA1dBqfFhl1LEwgIjt5tnQpA7IruxK9aeUUQFi0t0IC00QxNcZFW0c8f6ejMG1VMmfgGDOCJzMSxMNhM3Wq4j3k2xMU5bkoynPxj++dy/5Tvfzs+YMkNYuxcWLo7CAV8bBnSiTQVDWjqsnUNPxvvE7ZBz4MwILJpUysvZm9h2ZhazxKtcekZMZUnLV1o97faEi0thDYsB49FMQ7YxY58+b/0eLVjsoqokePZHAhmbqOraTsj3LN/0tccBQ3b94MwPe///2Mzx5++GEWLFjwzt/VXyHeSS3CCTX5fO3Lt3Cy+XKM7k5qil146+qy1vdqAT/+lS8hdC0LZdQIkGQcgysvTTd481AnpgkNkbbsRlwIKj/9Wdr/+ycXJbQ7OXSGjQWzSCgjdwoqhsaUUCPjIi2EZRd788bT5SgE06Qm1sW4SAsn3VU0RNvoteWxumQhEdlplSqOMNYGEtvzLU7sflsuK7rfxDEK2eo5alkJazIBwDSpjPdQGe8morg57q6m3+GzjPKgUc/Rolzf/Waa9ulwL3tS6AzbC6al/p4fODKifFzmfZnUJ3vStu071YszFuLBjnUUqEFrMsk2KQiRfXwMw+LjGYI8j50rF9TDgkxelreKgTe30P3wQ5aXbJpEDh7A/8brVH/lq0i2d76p0LdsOYH1a9OI4oSi4Kwbk3q3/5pwQUO+du3aP8V9/NUjd8nlxE6fyvDKhaLgrH/rPxRFlpg0phDGjF7LH96/76I933OwFZz36p9ef5rdJ3qoCbZmrUQBQJJx1tdT9jcfpet3v7YYD3XdStZliUM7TZWyRC8tchlIMnZFRpIhGh+snDFU3te6Cp8awm7qGAimhM/wWuE8xsQ7GRdpRTE1TAR9tlyerbgqQ9UnA6nmI2ssTnhruaF76wXpdE0hrISfEEimwZ0da6mOdSOZOrqQWS528FjldZYi0aAx1xF0OQqojncjTBM5yyroiv697MsdR0KxGneGS+iNBpvdhmNYnkqR4P721eSpkVH50YWiWHQSw7fb7BcUfvjfwkgk6P79w2mTvJlIkGxvI7h1C76lV73j17QVFlL9pa/S9cjvSDQ3IWQZ7/wFafztf03486vD+StFzrz5hPfsJnJwP6amWUtKIaj4xKdTFQN/HGQ3UyO10Au7nYKbbwMsUq71e9tQNYN5gSMjsgvaSkoQkkTOnLl4Z8wk3tyE5HCS7Omm46c/SVvG60h0OXzc1bcVW/FkTs27hRe3nCEeH9zHNDGETFIoKQ9VwkQyda7v3Y4upCGeq8n+3HFZY9cXQqE6AEIgLpDvlE2DVpelazlz4ATVsa7U9RVTwzTh9s71/LLmtkFvV0olRB+pu4X3nXkh693JwOean2Z/4RTW+GbS5i5lTGTkUMxQCEXBM3NW2raFuXFiWjzDiFvdtBK6kJAxUK6+iXwSBNa+kcrXIMvg9pB7+dKLuPpbR7zxNEJkTi9mMklox/Y/iiEHcNbVUfu1f8FQVYQs/1V3pL5rDXlS1dl5rJvG9iDlhW4WTy3D7fzjlVQKSaL8458kfqaR2LGjSB4POXPnp8i1/ljwzpxJz+OPZmyX7HaK7ryH6PGjRA4dQhg6wu6g8LbbyRvsKDQME3VQjcGTpX77HII9/Tzzrz/Hu+Im5kytpKS+gdjpU3T+8mdpRtwA9uSOY2PRbGRFpr4on2MbG9P1H4WwuFW8dVQNY1SUMJGHhR/89ty0SpIRMWxVMjV4OuNccD4EYiDQhcSaorkkJWvpPyN4MiuHS44WJV8NkZBszAscYVykFUdJMdeU9RA+M0onr2Ewa+A4l00rx/fgx2n77rcw4+m0xq4pU0m2tmDE41a4JDePik99BmkYx1GxotKRJZQigG57PrvyJ9HkKmexbxz3XT0OZ20dXatW4e/2c8xdxe7Cqdge2sfHb51KQ+U7q40pHE7METqaJXf2qpt3Eu+GLtR3pSEPRpL860O7CMdUEqqOXZF4fvMZ/uE9c6i4yC64/w2EELjqG3DVN/zRrjEcSp6P/HvfQ/ejD1sbTBNTCHb6pnLVlAXUXr0cU9MspSOPN81rUWSJsgI3HX1RTrurKEgGM+KuJiDpGpO7D7H+FTvPb5/CrZfVMXXjUxlCwBIwJXyWN4rnoxqCI82ZnZqKoWHXk1zu35/1eYaHQmpinTS7ytLU5y+EpT27mTNwdETvt1/20uQuY1/eBLqc50NXI/HlmAg8WpT3dG7AYajWGLUNEG47lXX/tGOTScIb3qD4+hVUf/mrtHzvO2nhtxPNfl6vuxUx4MeUJERRKTkbupk2RmPZnCo8g86HkKSMxibr3qDJXcaRnHqEsL5TIQTOWXP4ydYEIbt6fsdggh88sY/vfXwROe53Lm7trKtD9njRhocV7XZ8Vy4b4ahLeCv4611rjIKn158mEE6k2pCTmkE0rvHblSPT+f8lY7Nczf+MuZ11hbPZWDiLX1ffzMbcqfz8hUOYpolQFJSc3KxLzweuHockYEf+ZGKyw6rNxvrdnzOqDlPDZupc2beHonAXL2w+S7jxbNZ7sRsqTiMzHuzQk9zasYHPNT7Op5qewZ6FWzxb3fjM4EkcRjI9Fm+apKkDD/msON7HgoHDyFnOde4abxTP5bXSxWlGHOBQTn3q+YciJtuZHGrEYSQvWHWSFbrO2a/9AwMb1qdVWfTYfTxZfAXdMeiy59Ot5NEViHOqdYCXtzbxtf/ZTjBqjWXfC8+OePpz92yTJRYMcuTvO9WXWm2l3Yph8ubhzoztYKlb7TzWzQ8e38v3Ht3Dpv3taFnOMRxCkqj87BeQc/MQTqf1T1HIv3bFHy0u/27Du9Ij33OiBz1LwudMR4hEUr+oVua/JLx5uJOA5Ga3b1La9v5Qgv5ggsI854jHbjvahSQJYrKTX9fczNzAMSaFzlCghTIMoWzqzBo4wUpnMX7JRTGZ5ZaGkFLKQkNxV8cblMf7LsoQWpOIQBWyxYOSDBJ1u5AkgW6YTA41UqAGOe6tw2aolCT9HMxpQJcUlvgPZjXg594GA5FSHRqOXb5Jg1zkJuWJHgqTwcH4vcm08Jk0QYe3AhPo1ew8d8KkvfIWfGqIxf6DHMxpyCIuYUHVDcJRlVXbmrhtvJNkZ3bjqyKRsHuwyRK3XFZHTanVvBQIJbIaYVUz6A9mp7397cpj7DzWlaL2PdMZZPvRLr5w78xBsi3L2AfWvcHZV18hGRjAXlFByb0P4J40mfrv/5Do8WMYkQiuceNRfL63OFKXMBLelYZclrIvqoWAC+VD1P5+9HAIe3nFX0TsrTcQo38EPmrTMJFGGAuAaFxl+5EutEGBhbjsZHPhTDqdhdzSuTEjXmwp2CfANNmcP50bu7ek7ZMUMrvyJmIMi2kXJQKUJfov2psVwIDiYlPhbE56qkhKdkrjvdzdtwVnPExc2HAaCS7zH0wdMybSzsull1GS8I/oiYNF7HVz9xZ+7SwkMKxj0xAyrxUvRAymV/OSIe5pe50cI4EizFGZEYdiaHhIFTK7cscjEEwaOE2uK8j+3PE8Xb4Mjx4bNf6vGSb7TvZynRQbrEnPjPkrkmDyjVdx35SatAl7bFWe9d0PE89w2GQm1PgyztPaE2b70a40+t2kanC6LcjhM/1Mq7dWL/0rX6H/lRdTYbVkayttP/l/VH3+73CNG49n8pRRxyYQTrD5YAf9Awkm1vqYPb4YRX5XBg7eEt6VhnzxtDLW7m5LW1pKEkypK8CmZPeA9HA4pSUoZKuvsfie+/Fd8fYz/aZpEjtxnGRXJ46KSpwNY9+RunPTNPn+4/vQ9ewWRjNMVm1r4r7l41Ie1VAEwkkUWUIb1lTR6ixBylJWmBQKx721IATHc+pwGkmu7NuDbbCEcHfeRDYXzhzscjxvznxaaFBx8+LqqDUkDuWM5XCOVbaZnwzyYNtr2EwdAXhNHZN0ceew4sIUgpDipmAIy2I2CNNgevAUGwuHVIYMNv0gLDNuAkGbh/2+8bTnVnFXZRzHjg0Z/DbD0TduNqHWdkoSfoKKh8M5Y7i8fz+SaaBgUB9rZ0HgCL+rvpGI7EIy9VFLK70uG0qeHaHIWTsZfYuXMHHx+IztY8pzWZwbw3NsD7Kucsxbx5m8WgrzHIzNkuw83hzIev2EqqcMualp9K98OSM3YiaT9D73DNVf/uqoY3OiJcB/PrkP3TDRdCvE88qbTXz1PbNx2t+Vpuqi8a4cndsur+d02wAt3REM00SWBLkeOx+8YeKIx7T/9Ccpde9zP9aexx/FXlKCe+KkEY+7EPRIhJbvfxe1pztV6+yorKLqC19Cco4c8rgYNLYHCUZGr0/euL+dglxHVvWXojwnZhaDHZcdrC+YxVX9exCYg8yAFhf30Zy61H7788ZzIHcsTiNJQrIhyQpXz66iptTLqg3H6AxZBr7b5huVknWoB6shEZMd7PKd/66WDPKUD52KrMlCYGCiC5m9eRPQJIXdvklUdvaM6v0rmLi1IVU65iCn+LDJTpcUDuSOpcCI0jvrKpQ4FO5+I1UCmDE1CsEr8TLaK8/HhT/U/GIaMZXN1JF0g6W9e1hZshjZNKwq9CyeuU0WjKnIZaC8FBQbBvG0pJcmyeTddGvWZ+x75SUW7X0JI2lpj46NtNIcPMVL4mr+7r+3Mn9yCe9fMTHlDXucCrIkGD5VKLJEjmeQ/CwUyuTBH0Syoz3r9nMwTZOfP7MvTZEpoep09kVYvbOFW5ZcHKf6uxXvyjWLwybz1ffM4Qv3zuDeZWP55G1T+c5HFpI3giah2ttD/ExjZrtvMkn/6ldHvZZpmpxqHeDFLWd4Y3croWi6Ye1+9GGSHe2YiYRFn5pIkGhuoufpJ9/eQwLBaJJRIieAlehdvbMl62d2m8yNi+qw2zJfk10FU3iiYjmn3JWcdlXwevF8Hq26LiUCcQ6mkIjJTgwh8/HbpnL/8nEsmVbO9EmVluiwkeQDLa+M3sSCFbvusvnYVTCF31bfmBY7rop3jxAuMQlJLgwk3LpV1nfCU82B3Aa0wStmu2pSKDR6zis+leeM7BHrQiEgnDSUenkpVISJGJHMy1ZSSr9yPlzj0JNZOdZlTBqibUiYPNj6KmOiHSiGhjQY+nPYrLMbJmw+0ME3f7+X/6q6lV6bD3WwBj8su3imcjlvnMhcfWgBP/0vW+GPc5U4dlOjJtZJ1UALqm6w42g3f3jjZOqYWeOKs/aVabrBK1ubeGrdKXC5GemFs5WVjziGAM1HGolEM50OVTfZfiQ72+clnMe70iMHqxRwXJWPcVW+C+6rBYMIWcm6bNb8/Zimyab97azZ3UosoTNjbCG3LBmD12XjZy8c4lBjH0nVwKZIPLX+FJ+5czqT6wowDcNSqR8+QWgaoW1vUvqe972tZ2yoyEvFt0dDKKoSjCbJzVJyduOiWgpyHfxhzUki8XSvudldTouzBJupowvJMuJDQhDnH8hECPj1K0cpzHWw/UgXr+5sBSFTG+9gW8FUJgTPUqH2j1gSKCRB0w0f5HBbhPhAHNMwcegJ8pOhNGKotGOAHCOGAVzVt5sd+hSOe2tYXbKIhGRnfuBIBvlXUsh0Ogo4OWjIJdPgwRtn8MhDa+lyFKQ9lzANGqKteLUoee2VlARasvKbnIPm76eBNo546zCF1aSTzhE5ZF8hMy3cSLkU4z7/FoqvuhvfsmW09oT5/eoTnG4bQDdM9KT17CoSv6m5mXw1hGwa9NrzQAjCBzq4aXFd2rmjR45k7fa1mxrjws2c9lShagabD3Rw/9XjUGQJh13m7+6bxY+fPkAsqaXJA8aTOmt2t9ITiHHPtSvwv7YqLbwi7HaKbr19hFGxENmyEZPsrfMjJZ8v4TzelR75W4WjsgrTyGIsFAXP5Kn8fvUJHnvjJK09EfqCcTbsa+dffruDzQfaOdTYR0K1tDOTmkFSNfjp84fOVwyMsBQ19eyhBsMwOdTYx8b97bT2ZGccPIdcj50VC2qyetRp5zRNvvTTrWw52JHxmRCCxVPLqSzOTo5mpqpQBE49zthQ8+AH6U0+JoJYQuOHT+5nze4W3FoMh56gxVXKDt8UfHp2AqvkoOctebysP9xHTyCOYVphjoRkp8+RNyINmAlEJCcyUJbo54auLXzq7DMUxfstg5fFgAZsOawrnIPdUKmIdXO/cpqaUCvXd7+J3VSRDet7UQwVt55gae8eruzbQ7zxFO680XsQjGSSpb27cekJFENDkxROuyvQh/0MVSHTN3YWV7/vZjZc+RHWXP0pVpk1/PCJvTy7sZFTg0Y8A0Lgt+fS6/ClDLWR5f3So5GMODaAjjWmqfs1TOLJ8+/9mPJcfvDpJcxoKMpwvFXNYP+pPli6gsJbbkPJsVYetpJSyj/+yQuGHz3dzfjUUHrZKFZfwZKakTl5LsHCu9YjfyuQHA4Kb72DvheePf8DkGVklxtpyTI2PXo4rZRLN0wicY1V25vTYn7nYBgmje1Bxlf7cE2YSOz4sQzD5542PeO43oEY3310D9G4ZnVDmjCtoZCP3zoFeUi5jZFIENqxjfjZs1xZUUHNNeNZtXI3/qTEgM2TEXM1TeuH+PBrxxlj+FFffJJEawtKTg7519+Ib9lyqku8KS8QQDJ0q/pk0GDoQsY0TM54q0fldglFLdKkQi1Ct6MAU0jYDBVXltpysPzVA77xrCuamxnVFgIVmY2Fs7ipe2vaR6qQaXcUIZs63kTcIsDCQNHjPNCxhuSU2agH2zJEKkqSAd7ftur8Jex2On62izJV5aNNL7Avdxy99jwq4r1MD53CaagIux1bQQELpkyh42f7qYz3Zpx3cJ1Crh7jo80vsD93LAlhoyA5gMBAR0ITEhImTa5StHlL+fHLJ1E1I3O6GSZaPRJkiVTd+FCEDxzIur8hJA7mnm9Wy3Xb8TjTTYQkBIFwgmzziKIIuvwxpqy4gQnvvZfuroGLbot3NTRwx+ZNPFq+HFUoqcqmsbF2rlp0iZjvQrhkyC8SBdetwF5ejn/1KrSBATxTp1Gw4gYOdqvYZIE2zGFXNYNIfPQKBoDS976f5u/8K6aqWjFLuwPJ6aDkvgcy9v3Z84fwhxJpNv/g6T7W7W1j+ZxqALSBAM3f+gZ6NIqZSCDsdnKAe00TU1XpsufzSskSuh35mcbAMFj3yEvMC5y1zhUI0PP0k+iRCNdccR2bD3SgGzq1kTaa3BUZxxuSkpUkK0XvOojCRCBlxAFUoZCQbFmN+YDiYVXRwpEj6EKiw1GUtumwt45XSxYhBrtY3Xqcu9vXUqQOIACPpDPx1ms5e2wPRvK8P5yNf2ao5+rVY1zmzzSCQpLZ5qjjhZUnoOY6HPEw97e9Tv6Q6pihcXOnkWRB4EjqmgLQsCafp8uvptdVgNjZkbVhxzqZuChjLgnBtfNqMrbHT1sdpwlhS11fxmBN0Vx6HfmAiU2WeOCacVmrp2pKc2hsD2asCjTNpLTANWRcLn7Bn3/t9RRt3cInm56l0VVBWHFRpQcYO3869rx3ljLgrxGXDPlbgHf6DLzTZ6RtK4iF0rlCBiEJ64U/3TaQ4ZXLkqChMhcAe2kZY/7t3wlu3UKitRVHbR15ixYhOV1pxwTCCVq6Ixl2MqkZrN/bnjLkPU8+gTYwcF40YNAQnTusNOlnUvgsvY48jGHEtrquD5YBDoGq0r9qJWOvv4EvPzCLx149QvTsW2vfNjlveBw2idxIFD95542zELyZP43L+vel1Z2rQmZT4SxsepKqeDcBxWtRxqad3KRAPZ8w7LH7WFWyOK1lf0DIPF55DZ88+4yV4hQCyelkzD99jdbf/AbtbCOmJBDV9SjhAHpfOsfLufEbbtI0BMfzx1F68028sL2N5GCNddLm5Zc1t1AX62Ju4Cg1sU5sI5RWnjungoHD1KiNtSNVVNHTHwYx+s/zXGniuTBNxrklwf7TvVw+vSJtu+x2oyXi7M+pp9VdhgDOuspIyI7Bidjk41MkZk0oyXrda+dVpyb1c7ApEtMbCinKc2U9ZjiMRILQrp1o/X0468bgnjKVmn/8Z3qefoIJx48h2dzk33AdvmUXL7rybsYlQ/42UVPqpSTfTVtvOC3crcgS9y8fx0tbzrLvVC+aZqR4Lj59x7S0UIjs9pC//NoRr6GHw0S7AyM6YOqQ5UB4/94R4+7nMDbawpaC6RjDzieZJmMjWSpYDB2130/+iSNcv/8VflZybXZv0DSRMDImCJup4TFVVE8uH7xxEr9/LkFNqIMmd3nKK9/hm4wBLPEfxGGoRGQn6wpmMSV4mts6N6TOFZTdPFx1AxHbebKlxf5Dqf/vzR0/mEQcAiGRFArNrlLqYp3IXi+2klKEEDT809cszmohEJJEx69+TiiLIYfztAQaCrok8VLJZYQVF/7NHRmanUgyZz0VtLhK8OoxPtjyCgyuTEYKI9lMnQmxNvLjTWzSvbjNOCHFnQoznONSOReOqo+2YwpBZbyH7aVziOrp30lSNdh/KtOQe+cvIPDaKuYFjxNRPOz2TUTCQBosdZwUPov35R0M5ErkXXZ5xn0W+1z8/YOzefR1K+nqsMssnVnBHVdcHIdQsqOd5u99x1qFJhIIhwN7WTnVX/4qlZ/+bOb+Pd30PPUEsSOHEQ4nvmVXU7Dihj8ya+hfFi4Z8rcJIQRfvHcmv3jxMCdbA0iDqjofumES5YUels6spKLIQyKpU5zvYt7EkhTR0YWgRyJ0/s8viB49gilJuCtvZkBOT6gpsmDexPOe07lmpdFQnBxgbuAou/InoQvFUhgSMM9/hEI1mNrvXBIxYcpE9u+n7/mnieBBNo2s/qVs6oyJttPkLk8ZNsVQqYj3MC94jLERjTGFU/jyvdM58Jvf06/lEZfs6EJGwuBk7hgOFE7B0DQ0IbO8d0eGyk6uHuV9rSv52Zi7wDSpj7RQnjgviBBRnCN2Q8ZkK2nmmT4zLTQx1CB4Z80mvG9vJm/8kP/rQtDoquCOrvXoWPe+3TeZzQUzsZkaYyOtuPQETe4y+uw+Qrj5bdUNhGzWd9cQbuX2rg0ZlQYmUDOmjNJDrzN1cPwNIbOucDb788YjmwYL/IfYUjgTCbipews2U8d0uXlTmg/DQjFCQJ4nM1GYM28egTWrQddZ5D/IgsAhDufUsyV/GkIIqmPdBAwb0vPPkHfZ5TR3hVizuxV/KMG0+kKumFFObVkO//DeORZXz1tsXuv41S8wIpFUGO4cN3nfypcovv2utH21gQGav/UNjGjU2j8ep/+Vl0i2tVH+0Y+/pev+NeOSIX8HkOux86X7ZxGMJkkkdQrznPQOxPnKz95Mxcl13eSy6eUsnVFxgbOdR9tPfkT8zOlUeeLNHRt5omI5pmJDM8Bhk8jPcXLDwrrz97JoMQPr16UU2AGQJJSCAvSBgZTnuVw9xZXXX8++fqtU0JmMsmFHHdt8U8nRIjj0BD2OAgBqox04tnRyWzJJIVrWImlh6lzmCbGgcQMHcxo4kDsWQwimB08xPXjKqhAJQ9O3vokZjTJGkfmEdoI2JZ+BvBLKp4xnzs1X8cq+HlZtb8ahJZk5cDKTLx3LmBckB+i35bKk/2BaB+fYSCuN7soMD1kXMnZdJSi7SG7cRPDNrThqavBdvZyc2XPRDBPdMPHOmoNz3VriZ85gJhMZIRWBtcKYEGlGwUg1Fi0IHKE62kVZ0g+YVginzyLaeq14IQO2nNTEcdJbQ7/fR1EykPFsUmggvdzO1Fneu5OYZKc+2s7UcCN7c8dzV+d6qwnKbqfolttwnbARV9MnH5ssceWszJI+Z00dssuNHg4hMDnpqaHdWQQINCGxvmg2bzCXGcFTzDnUzkOvnkDVDUwTTrYEWLu7la9/YB5up0J47x76nnsGtbcXW2kpxXfejSdLov4ctFCQRHtbRi7FVFVCb27NMOSBdW9gJBLpIsrJJOG9u1H7erEVpudH3q0QZrbWvT8S+vrCGNnS3e8Aiotz6OkZvfX6T4mv/3o7bb3pMW2HTeL9KyaycMqFNQOTnZ00ffPrGWViIcXN8clXEm+YxsRaH/MmlqTRChiJBK0/+HcSba2DXqeEku+j5Atf4ZmNZ9l6wo82WO1y77JxlBW42XGki9+sPJqK8QLpHqtpLbvvbn+DungX+3MaeL14PtqgwLFs6Lhs8JWpOpHnnhy5pBIIKh42FM5iUqiRsdH2lJF01NRS+dkvoOTlEUto7Pzq1ykNtmebMzCBRyuvo9VVii8Z5P721ZbCjml9+ruamwjYclKeuTANq0N1UCFIYDIm2s6N3Vtx6XH2FU3lkLuWTkchVSVePnjdeGJ7dhF+6Rlys/Cwj6QqlG17Uii8XHoZJ7zpScdl/XuY13/ooiUxDATSILGBiTVxyd4cCm66Bd/Vy+nyx/jPJ/cRjKhIwmoWet+KCSwa4V2LHDlM+3/9iIBwYuoGT5VfRb89L201YzM1UGyow3oRFFnipsW1XCl30vXwb9Nrxm12yj/xKcZcfVnW36MWCtL4pS9k1XdVCgqo//cfpm1r/cH3iR49nLGv5HJR9pGP4Z0+c+RB+wvCSPZLkgSFhRfWRb7kkf8R0O2P0uWPZSQmE6rBym1NHG3yMxBOMmNsIYunleOwZcb6tIA/a5gkR4tyWeQENTfek/XaksNB9Vf/ifipUyRaW7CVlOCaOInv/XoLZ/qTaIO+64HTfZxsGeA7H1vI0xtOo6sqMwdOMTl8lqSksC9vPKfcVVYNuJAwgJ2+SdR1djEjdJoCNcR232TCjlxmzh3HiqUTiD33+KjxeQF4tCiakKmNpXdjRpub2fK1b7Npzj34wwlihZfzydAzae3rQ9E1uFoI2HP5Wc0d1MS7cetxWl0lhBUrfi5hIumaFTOXzo+xieCMu4LHKq7lwy0vMr33CFPFMbodPp7Ul/O9x/fzNzdOZ1NJE9d0vjniPWR7vuGwmxrTgycyDHl1JPskNRKGtv0LQCkuof7f/j31eVmBm+9+bBEt3WFiCY36itysvEFGPI4ejeAvquG3099P30Ac0zTRzGFNXFjVRCKL46XpBruP9zD16JOZvCpqkt6nn2TM1ZdZf+s6kUMHSXZ24Kiswj15Co7KShLNzeleuWIjd9GSjGvZKyuInjiWXUS5KHsy9t2IS4b8j4CEamQloQJo64mkPPVjzX7W7G7la++fm0EK5Kiqzk7ApCi4LtBcIYTANW4crnHjADjw6NOc7c1Nq2wwTUjG4rz4k8fpMyp4sG01JQl/ymjVxLrYVDCdnYNixSaCkO28Z1Ad76amL0D5xz6Bd6YlImzW1hF0ODLiy0OhC4m5gSMZxlHGpCzazdLtv2dLwUxOeGt4tXgBN3dvSS8HBPbmjkuFTjx2QSKu0+xO9zxtukpVrJMznqqsiVlTSARtHtqcJVTHu8E0KIv3s7xnJ6srLqe5O8yZ/Hp6+49SnPSn6sKTyJhC4LhI4w5k7Twd2njzVmACO/MmscMzhcR/rGdMsYsVcitF3Y04xoyh4qrlKKX5GccZapLuRx4mtGMbqmTjv6puIS45SE0NI8wqI63XvXYJze/P+lmyy6LU1QYGaPnut9FCQUxVRSgKtqJiSj/wIdp/9EOMVMmtHXt5BQU33JRxLt/V1zCwcWOaiDKKgnNMPY6Kiw9T/rXjUmfnHwGVRR5sSvahNTn/40hqBr0DcdbvbcvYT/Z68S2/FmEfkqySJGSni/yrr7noe1H7+zmz+ygiC0mUJim0hnRmBE+mGXGAY95a9uZNPH+zQtDtKOBM2SSQZGylZZR/9ON4h2hH5sxbgOlwjZhsPeWu5Ef19+MaQWhYAKXJADd1bWZ24ChHcht4oeQyEkIZrBaRWFcwi9Uli7DJgs/eNY1vzJeRTTNDWELCpC7adcFa64Ehk5OCwZRQIx859SQTHvkOnwpuYHPpXDYUz6XFWUKjp5ITC27B8+AHUYWcGtHRgoWmkOiyF6IY58dWMnUOe8egy2/dj1pbOIdNhTMJK25UzeBER4Qft/j4VmwaT+7o5sTXv0ayM7NDt+u3vyG4YxumpnHMXoZuZr6fwxWGbIpEnseW0cXpsEksn1eD7E2n+T0HJd9aLXU98hBqX68lX6frVlKzs4OBDesZ870fUPqe91F46+1UfOLT1PzD15AcmYlZe3EJVV/8EvbKSpAkhKKQM2celX+bWd3ybsYlj/yPAEkS/M1Nk/jpc4csPgzDRJEt0YPhHo6qGew61pOdffDOu3FUVuJf/Rp6JIyzYSxyTg59LzyLZ/pMPNOmX7DpIn7qJIVmOLM+HJANjdJEP5NCZ9KMeFIorC5ekLU2+bXSJfzwW18BrHh8oq0NJd+H7PYgORyYH/4cLb/4OdXRzjQnLyI7eb5sKYaQOOWpIj8QGpGB0G5qLO3dQ8CWw6LAYWTTIKh42JQ/gyO+scweW8R9y8dRlOfiUMCPLs6kG2xhiU50O0ZvJDERlCb607ZJmOTpUeuP1rPca2un546PkCi5jWB/hNNtA7T2KlRd+QCuHessUQvFSUmsD/vwWh5JQrLbmTNwFFVS2J87Dl1IjI80s8B/mEOuWqZEzgLZvXYA4XRaiWtNIy7Z2JM3AX349yIESdnOvpyxdDgK+dgfHqP6819MfawNDBDauT012YUVN3qW98ZEUBHrpt1ZjE9Sycnx8vG7ZvGTZw7iDyWQJKvp55q51cwcX0zgplvoffapDF6VwttuxzQMIgf2Z4badJ3Qrh2UfeBDWUMp2eBqGEvdN76NEY8jFMUSLr+ENFwakT8SpjcU8Y0Pz2f93jb6gwkqizys3NaUnlAchNuV/WsQQpC7aAm5i5YQ3LmDrt/8j8X5ousEt72Jq76Bys99cdR6WsnrpVQdoDzeS7uzKGUEHFocm6kzM3gSjx5PS9S1OYuRRiAqCkQSmKZJ30sv4H91JYO/bnIWLqb0Pe+jYWINP629jk8efSjtuGPe8xPVjvwpTAmdwWXEsZlG1iShgsENnVswJUv9PU+LcF3fDh5cWkPpivNVEQf8ZJ1wJEyO5VjUp8LULbLdIcZeNjRqYx0UD6kcGXofAcXL3rzxBGxe6nbt51g5dPRGUt/fEZvMlbe8H2eBG0VAQeN2ImteBSFhJpMoRYUU330fsZMnCKxdw2X+A2ldoRoShWqQuLChSgp5eiQrx7uZTFLxqc8QWLOanr4YiiRGZG3XJYUeu49TZ/dSPWR792O/T1uxVMR7LHpckVnvf3XvLvLNKC49gRACYT/Gv77/vTT3JxiIJKmvyE2Rq/muXg6Y9L30Isag5mvh7XeQt3BxqrEo632qOt3+KCX5b014+e3SOv8145Ih/yOiNN/NvcusOLVpmmw/2kVnfzTNK7fbJJbPqRrhDBaMRIKu3/0aUz3v+ZiJBLHG04R2bCd3UPU+G9wTJyE5ndzdsZa1RXPodBRyffebFCcDKaUbSDekNjN7iSGAZBgMbFiH/9WVaZ5YaMc2JIedkvvfw0dvn4Z2TE7jG0lItlSjzjnZuNkDx5kWPI0vi2ycieCpyqvps/tw6Qmu73mT+mg7oZUvkj9nDrLHg+x2Y1MkJCEyuD80IacMt4mgMBEgbHOjCRmnkWR27CwLu/YMaZG3JgyAJlcpT5cvQxcShpA5aWgYncG0UUqqBuv2tPH9Ty4mElcZyL+KqquvRQn0ovh8KHk+wOIQCb65xaqDHvROVSxOlapEj3V/o/VvSRJafx9VX/wyedEk+n9vyVD1SR836HYXp/7Wo1Ei+/em7VMd76Yi3kubszg1CSqGxsTQWSoSvWnfRWjHdoxYnDGf/DTawAD9zz9J7/59yC4XvmuuxXf1NfiuvgYjHiOwYT3+VSvpe+F5gosX4Bo3ntjJE2leuY7guLuKVb/ewQevv7gKrku4MC4Z8j8RhBB89u4Z/Mcf9hKOqiCs7P+K+TVMbxi9FjZ26iRCymTsNhMJgtvfHNWQC0mi+u++QtuP/5MVgb2QTI5YPocsI9nsVJlBbIZGUtjSvFjJ1Lm8fz/9qzqyqsAMbNxI8d33MaW+iJbFlxHZtgVpkMWxPtrO1vzpaIPGPCE7eLNgOvlqkIJQZtmVIQSlST9dziJkLcrG/Bl41Qgl0QHOfu0fEJi4p89g4U33sWa3hKEZeLQoC/yHqY11ElQ87C6cQrstn+U9O5kcPoNkGnQ6CtlRPIMZt15DtW0x3U/8Aa2/D2WQhMwEVhYvSqtDN7J4/GCF0L79yC4CoQSSoaEbsCxngNvvWGwJDQuBkuej9uvfpP/lFwgeOEhHDHLVCG7jfEJ41Ci+ptH9+GMku7spvuc+5k8qZeex7jTJtbR7Aqonn++w1AcCICtp5X4CuKf9DXblTeRA3lhMBNOCp1gQyCzzM1WVyIH9JDraaf3Bv6OHQqDraED3o4+QaG6i5P730PW73xA5eCD1XnStXoOUk4Pk8aDHEwg1SVIoxGQHawrnomoGv1t1jBlji3A5Lpmht4tLI/gnRInPxfc+vojTbUFCsSQNFXnkei5cvSBstqxKPQCSPfvxSVWnqSuEy65QWVpGzde+Qccvfkr0UHbxYQD3jBkULL8OyWbjvc+s5H+S49BQUEwNE4lF/oMsChxipHoN09AxkklkRaHyPQ/SEQ0ROXgATJOyhJ/5/sO8mT8Vc0gpoN+Wi47IoJQ1EegIPtz0Aj4tnJJXA0BTLYraA/txxWLcufQ+Xn39IB9sfgG7oSKAkqSfhlgbEWy4TDUljFye6OPW1rXwm4105xdgRMJWGMA0CcsuQoqLy/v38XLZFSM85ZAx1nR6A/rgmWWKkgFKjm7n7NdfRsgyuQsXUXL/g9gKCih93wcpMU1+898bef++313w3OdgYDWTDWxcj3vCRD5w/Qy8Lhvr9raiamZavb9k6niExvx7b0gdrxQWZS09kTCYN3CUBQNHhox59klFKAqBtWusbswh1SNmMkngjTUYySSRA/vTqqxMXceIRim8/U42HO0n1NxKtyOf455a9MHvX5IEx5sDzBx3qann7eKSIf8TQwjB2Kq3xubmGjsOyWZDj8fTP7DbOVMxhRP72pg9rjg1KWw52MHvV5/A0tY1yXfK3HHyBfKi/VnOfh62PB/u8RMAmHHfrXzx377NaamApGynJtaJV4+PerySm4fkskiTJJudnDlziR46OFg6ZnKZ/wB1sQ4er7gGY/DHfCB3LAv9h5CHJFt1BFHJwZV9e/HosZFLqzSN0LHjdFS28jH7MRg04jBYVGeaeElmdGaeO1br6Qas5O6LZZdxxl0xGDuWcOgJi0RqFAy1j24txnvaVqUmEnSd4PZtJDs7qfnqP1nXFoKP3TGD2L5RT3v+/MDGgpmc8NbyvtaVBDaso2rmLO67ehz3LBvLuj2tPPb6ydQkL5sGYbub9Qe6WD7XipJLdjsFN95E/ysvZTTubPJOYmHgMCYCCYOkUHAaycxJVddItrePqEca3LI5e4lnMkn89Gl6xixlWzSTThcsiolLePu4VH74FwAhSVT87eeRXG6E04mw2zFkhZ2ecTx8UvD4Gyf50s+2su1IJ02dIR557TgJVSeW1EmqBt3BBH8ouBxzhGYdHcFJVwUDR4/R9fuH6Hn2aYRiY8zX/4VxZj+Tw2cvaMSF3U7xvfcT2rGNzt/9mp5nnqLrod9aP/5BQyNhUhXvZnL4TGpbRHHzePnVhGQXBpbxancWsaloJnZDu+ALqgmJ08ea0I4fyepNqkJhZ97EUUsEV5Us4oy7Al1SSMp2NEkZFMsYDWaaYMfM4Alkc1htkKYRP32K7if+kDK2xYG2NMK0NAxJWmtItNsLOeGpYWH/QYvqt+ksiXZL+1IAJ9Zt5/quLVzTs4PyRC+qZEPVTF7YciaNkbPghpsoeeC92EpLkVwu3JOnUPPVf6R10hJ+POYeHq+8hl9X38zD1TegifRaImG3k3/NddhLy0Yu5TSMjIYdABQFe2kpl08rzypuIoRgQk1mzfslvHVc8sj/QuCqr6f+B/+PyMH99HX5+eW+BH2Sx0p8DSa/frvyGLPHFWXwWJtCIqo4aXcUUjmEYApARabdWYRsGiS7ehnobAdZpn/1a4SX306O3QHDVwJDIQSuceMpuPEWep56HLWn22oIkqSsXZ4SMCl0hkO5Y1PbOlwl/Kr6Fj5x9hlcaBzz1mIzNEav0Laac455a+mwF9LkKqMh2pYy5kmhcMJTTURxsSNvEqWJfmri3WhI7Msbz8GcBuYHDlMfaeOEpya13B86ZkNr6IdDMXSkIT+f0oQ/Q0ziHAJvrCGyfx/CNphzyKY2JUmIWfPpPHgcYRocyqmn1VnCB1pXIps6MiZ6KE7zt/6Fyi98mYG1r3PF8V0WaRYwI3iSN/OnsqVwJvGETiKpp2LPQgjyLrs8g8lQMzrQJIUO5/nQxkPVN3Bl/14mmn3IOTnkX3c9eZddQbK9neC2rVmVhQYHyeJuHvKdC1kmb+lVFBUUcPXsKtbsbrUedXA8P3PntBH7LS7hreGSIX+HYZgmR5v8nO0IUpDrZM74YuxZWvD/N5DsdnLmzGPNpkb88tkMOyeA1p5MznIATJOofJ4rOjko5nAgdyx9tjxW9Gw7X0uu6wh0nK89Q7/iJp9REnKShKNuDLHGU1Yjyrmk2ih8KxmUr0KgSwo7CqawtH8/y3t3cdRbg5ylzvxcHNewDsOv5KBLCs+XXUFRcoAH2lbTa8/j8Ypr0IScChvsyRtPVbybJyqX0+EoQpMUNhbOpjTRPzT6ngbF1MlXg/TafemMiqaBzVCp9rlp7NHQTJN2RyH10UzFIWssdNTurtSzZo1F22w4p87goYFxqQqc97SuSu+ANU3MZJKu3/zKIowavJbAKte8zH+ANkcRuTYQ/d1QPnrnY38wswO3357HCxVXsewzl+EewtLpqKyk/OOfov2/f5zd+7bbcI2pJ3bqFEKAo6iI4g/+DbYCqzno7qvGsnRmBYfP+nHZZWaOK8roZr6E/z0ujeQ7iISq8/0/7KWtJ0JS07HbZB5fc5K/f89sygtH13N8KzCyNBaBZeQqi9z0DMTSxHHBao2vjFvlbs3OUh6rvIZzcm+3d6zLyieiIyFMc/SqCl0nuHUzRnh0/dBzUIXF45JxGknmcE4DS/v3I4DJ4easz3cOElZyb4n/AD2OfBo9VfTYfWzOn8a+vAkk5fNJYB2J495a1msROh2FqZK7AZuXl0svQzF1tCw/BbuhckvnJp6ovIaEZLMmINMywzHFxeneJJIiU0+Ibkdh6h5HG6+g5MRlJDMMvp5UOdUawDDOVwqVx7PzoqcmhSy4u3Mtwuag5ZubcE+cRPkn/xbJlj1MVFHoobEjmLHd5VBwZqkk8U6fQdWX/p7WH/w7DImXC7udgutvpPDmW9EjEUxVpWxsFb296e9ESb77LdeOX8LF4dK65iJgmibR48fo/N1v6Pztr4kcOZy1imTVtiZausMkVB3ThERSJxxT+cWLmWVdbwdzJhRnX5KacOtldfiEmtYSbhMGi4JH8MiWcd9SOIOhmp2aULL6pAJocxZxoUj1aEb8XGu9gRXP3uWbyFl3dk8x65QhBEZ+EdHBxOPwPeymzvxB2TRdUtjhm5w1vm0KmUM5DRmrgU5nEXGhIGXxpKOyk0errqM83sOSvv3kqqHUPYEV0VI1g0hOEV/9u5up+djHECNUEZ3DLt8k3vRNQRMyycFxGSRtpOiNp/lQy0s4dMtTHjFOP0KM3ZJsA0lNYKoq0WNH6Xv+2RHv5c4rG7APfY9MkwnxNj4c2kLbD7/PwOaN6XTIgHvsOKo++wUc1TWWbq3PR9Gdd1Nw0y0AyB4Pis/3ljnKL+Ht4ZJHfhHoefJxBjasS8UHQzt3kLtwEaXv+0DaflsPdWbU95pAe2+EYCSZUWqoR6OWxFtbC46aWnIXLkZ2pUtlmZqGqetpPBR1ZblcNbuSdXvaUHUDIUCWJO5cWo99xwbee3ole1x1HPfU4DSSzI2cZv51CxHyFLTgAAPNRRA/f58HcscyLtKS4ZUbQrCuaC61sS7cRiKdJ3vI8432k1XKylmfNxNXTxt7cxosXu4skA2NKaHGjHO7xo6jr6Qe+9bXR7yOR40yO3CURf5DePQ4vfY83iiaa+mKDoE2giya3TRYJHXib5jJ2c4gkZhqaTQIQVx2ctJTTZOrPK3JaCi6/DH2dcSZWlKK7HShjxhHhjPucnochRzKHcttnRspTfQhYSJjIJsGBckgy3t38krpZezOm8j8wOE0+Tths+GaOInowewCymnjp6oMbNpI8d33Zv18Um0+n71rOk+uP017b4Rr/XuY2n8MoSaJAfHTpwlu3ULV330ljQrCPXEStf/8Tfae7OHJdafo3hUj7+hWbl1SwxUzqy4Z8f8DXDLkF0Civc0SahjaVZlMENy2lbwrrsRZV3d++yi5ueEfJXu6af72NzGTyRQDXP9LL1Dzj1/HVliEkUjQ/dgjhLZvwzQM7KVllL7vgylGw3uXjWPBpFKe29jIqfYBi1r0WDd121/BloixIHEkJfALEHgjlOJ6HvPMAfaePL9sb3KXs8s3kfmBo4MeovWjfbp8GRHFzUNVN3CrOE1ttBMzFsWIhK04rjlc1C0dIieXg/NupzsgcFWPR+qLQGiYkRsctAI1xEL/wbTxEkJQ+ZnPk/jyFzBHSCRqSMQUB1f27UkZvJJkgLs61vFExXJaXaWp61THupgfOIomZA7kjeW4x6INkITJXe9fgae8lFhC43M/2Yw+NMYvJJKSLSvx2Dk8+vJBPtr4NHIye2LYxMpL9Nus0tOg4qEk2Z9R6qdgMDHcxCull7GlYDo5WpQp4UZsTgeoKt458yh93/s5/fnPYiZGryQC610dDZPqCvjnDxSg9vRw9uuPpteCJxPEm84S2b8X76w5accdON3HL144jKpqLOnfz9zTx3DsUzlcUEr933wIiude8N4u4Z3DJUM+iGAkiSJLuJ3pQxI5eMDiNxkGU1UJH9iXZsgXTSnltZ0tGV55eaGHvGHeePcjD6XLXSWT6KpK9x8epfLTn6X9pz8hdvxYammb7Gin9T+/T+3Xv4m9zGprPnC6j+OtgVQ8/HRrADMey+q5agPnBYpvvWwMR876Sajnn2tj4Wz2546nNtZBQrJx2lWJJtuQDI2w4uIPYipG7nTIHSSWSgb5m+YXso6liaXBua5oLhw9H3ZRJFKiB0P3vrFrMyHZQ0jxoKghkkKhw1mIy1QRX/4iZixT3OHcdeKSjbKEP81rBUv/8vK+ffyh6jrAkqGbN3CU2rgVX66OdzPe28qW2sv5zD0L8ZT7AOjsj2YXPxEC05TSGnCGorL/DLqqZUxsmiTzZt4UthTMwD5Mq1OM1OR17p0QEqtKF1Ny113ML5WxFZegDCrKV3/lq7T+8PuYCUvFiBFqvIWioEcjqN09BLduwkgmyZk7D/eUaWmec/T4sawhGzORILx/f4Yhf2bDaZKawXU925kaakzF/O39XbT9vx9QVPFv4C3Mek+X8M7jXW/Iz3QE+dVLR+gdsIQgxlf7+MjNk/F5rVCGZHdYAg/DM/WynEG7eeOiOg6e6aezL0pC1XHYZBRZ8NFbpqTtZ5om0aNHMl1407RI+Lu7iZ04nhGfNDUN/+uvUfre95NUdVZub0pLahpCYkDx4tMyY9aOyvN8LjWlOXznk0v45bMHONsZwjAMVN1kwOblgG3ckAsaltEaFJZIXQdBRHaOGjnfnTcxY5tmgNMuDZYdG+iGid1QGRdtw2lYhmhX7gTWF81BMg1MIfBoce7pWEOBml39qcNRRH0sk7YVsKTUTKsndObACepi55OEdlNjSryF6++ox1nhS223KRL6SCpWQgwSo2Qa8mM5dZTHe5kXPJ62XTZ0GiKtFKghDuXUc+ZcuEcIGt2VNERb08bRAE67LXk2ScCsccUsXZI5ls6aWhp+8CNiJ45jxGNIHq+VhBz2nhqqSst/fA+1szNV0x/auQPPtOmUf+yTKWMue9wIkaV+R5aRczPDYd3+GE49wbTQaZRhITdTVWl56mkKP/ixjOP+tzANg/5XV+Jf/SpGJIKjqpri+x9MNbC92/GuNuSBcIJ/f2xvmmd6vNnP9x7bw7c/shBJCLxz5tLz5B8yjhVCkDNvQdo2h13ma++by6EzfZzpCFGQ42DepJLsZVaynFXuSsgyak83QlEyO+kMg0S7VYvbH0ogshiUNUVzubVrU1pVhLDbKb7nvrT9xtfk85UHZwPw7Yd3cbo9s3rhnLRYNuRqMTQhZy23i0l2gjYvimFpW3q0KG3OEtqcxSSSBt/88Hz2vvgGnccbqYz34Bg04q3OYtYXzUmLYQdsMk9ULOfjTc+lPa0qZBLCRlR2ogspa/zekGRceoLJoUaW9+3KfAjTJHbsKM6a88yMCVXPsmoYCoFkaBn8K4aQ2VA0B58WYVy0Ne2zsmQ/Fcl+xkVa+G31TfgH9TtfL56P0q2xN3cCfnsOFaqf2cGTbK5aTIHXwfI5VVw7L11ZKO1OZBn3pMnnNyhKZmmgrpNsTq8AMhMJIgcPED1yGM8USzjEPXV6WkNS6hqSTFvlFF5aeRSPU+Gy6RVUFnkoznehtnSjCznDkGOaRM8280764z3PPMnAurWpPFWipZm2//cDqr/8D2mr4ncr3tWGfOP+9jTvS5gGRYkA9Ds43hxgUm0+Sm4u5R/7JB2//JnVtIHFI1E6WCNrqEliJ04A4Bo/HslmZ3pD0ahEWEIIcubOJ7RrR7oxVxRyFyzEXlGJqWZhNFEUXA1WI02ex57WvXcOp7w17Ky4hWUDB1G7OrFXVFF0+52p2DpYZF2/e/kwK7eeIZE0KMxzosgCbTirnkkaL8pQBG3ZyykNoMVVSnHCzwNtryGZBrKpYwiZVmcxT1dcTX6Og8WVNvp2HsHUzk9We/ImpEi1zg+WRFR20uEooizRi4Gg157P+qJZJCQ7PfZ8gn4vCwKH0sIrpqzglCAh25Eg+6Sj60RPnsS3bHmK47rE5xq93FIIJMOwxn5YiEWTFLYUTEsZ8nOJ4HN72U2Nu9vf4JGq61Elhbgrlycqz4mECPocBRzPH88/vm8OlcXZdRojhw7Q++wzJLu7ELKMMdis5Zk2PatjMBLMRILwnl0pQy7ZbFR98cu0/eiHGAmLwtY0DHaNv5qNm3tSE9zaPW2899oJ3LW0nl8/7UfOlrsQAk993UXfy4VgxOMMrF2blqcCKxzZ99LzVP7t596xa/2l4l1tyLv6o2iDXZANkVZu7NqCbOqWJ/rTzST/7ovYi0vwzpxFww9/ROTwITDBPXkKsttN5NBBOn7+35z/qZqUf/yTeKaOrCJ+DiX3P0iitQW1pzsVd7WXlVN0933ILhc5CxYQ2rnjfCedEEg2O/nLrwWsWt/Lp5ez+UBHGse5XZFYfPNSaqpvHfHav3zpCAdO96bCMj2BmBVBEYO3YloVFDMGTrAvb3ymkAFWadyevAnMGjieZkA1IbMlfzq3dW7AaQzhOTE1quLdzA4ex+1cjn3hIvpefJ6YZGdD4SyOe2tJCFtaWeQ5CNMkLtvRhMJjldfSOdiJKATYZcGWgukkJYVF/kO4jAT9tlw651zDpP2vIjA5kvP/2zvv8DjKa/9/Zmb7alVtSZZkFVuSbdlyxb1hG4MBY8CU0FsKIQRCEu7lF+5NyAVy07jhBggJJIRQb0LupRhjmnvvuDdZkq1m9bZabZuZ9/fHrlZa7crIYFzwfp6HBzS7M/POy+yZM+c953vymNn8WcRxEQLXZzs4+tD3yXvyVxgSE3HYTEwblc6GPdURet1dWDQfXknCL0WmBzaZEjlhSsak+4lXXRh7LZAmq06+WbkEq8XInzMX4qOHyiLg8Wu8teooP7xxbGCbENQ0ujAaZGzlB6n9ywuhe6LnY9e1e1dUjxros8rWWxnuqVuycxjy26fxlJch/H72+Rys/fRo6I1VF6CrOq9/cpinH5jBHdeM4/Df9lDQeCgisybrhuvpjD6aU8bf3AyKDFGWAbxVVZEbL0AuaENekJXIjiMN2F2tXFO7Jtxja66n6re/Ju9Xv0WSZWSLFceEiaGPNaeTmuefjShZrnn+OfJ+9RSG+Pg+z+suK8O5fSu2opGY0ueBAHNGBpb8glDMMu3OezClpdOycjm624Nt+HAG3nAThsRubYqbLynAbFRYubMav6qTFG/m1vmFFA5O7PPcjW1udpc0RpTxy5LE8JxEyk848fo0QGFf6qhAsnQfcYZVKRPolE1Mbj2IRfdRZ05m+YCJeBUT8aoras73NN8xAAyJSaTeez+PLzlGm8HWbTSjeLq6JJPmaaLJlECtufuFXQjQg02DtyWNZFvSyEBMXJa4eHAmWZOyKfjnTkqsWbydfjHX1K4NHDrYCq7r/7fweDjxlxdIv+se6l5/lekH9jMViTWJo9maNDK8qhO4pm4t/8y4JHJChMAvGXgleyFZ7lpuqFkZITYuALvmwdep0a4pUXM395Y18/DzGxgzNIXthxvw+XWEEMR721gszCQTJb1RiECKoMUCuh7KhMIQkLCNVlrvqajAfbQEa37321pDuxc1YRDpKTa2vr0Xrz/yAdClWjhhWCrjf/FjmpYtpXX5J+idnZhzckm96RbsOdl0RukK/0UwJidFryYlUHEa4wI35FNHpvPBpuOMOXEksiOOEGidLtyHD4XHIYM4t2+NflAhcG7fStLcKD90oOGff6d11cpQ/FsyGkm67HISZ18c9j1Jlkm+YmHUhrRdKLLMDXPyuW72UPyqjskof24Ob12zG4NBwt87yqALfH6dZ34wk4PHW6hpdJGRYidnkIMPNh5jza4aPD4NSQKHzYjfrzOifh/TWvYjIdAliTpzEicsKcT53X3G1hNs3R7oYVM6nZamcOmR0GtB4N9GoTGzeRfVtjSWDZwa2em91wMJScIgSwgheOGgILcwmylbPyTN3YgqKZRb0mk0JTKll/Z2fckx2h97DMXrRg4mYM5s3s3IjnL+Oviq0HmTfO2k+VqY27id5QMndhcYCR1FCBxqB62mBKotqaiyAbOm0mqwc8yWgUn3k++qwiRUDEJFDiotRqO53cuqz2rCtjXKdt7IvIz7j/1v1IVm4fORcPFcTBkZeI8fx5yVRfy0GbSs+JTmJe9G7hCsyrXmF3CiycUf3t5LQ5sHWQq88WUM6Lsa2SDpNH3wPu0butxkvQAAM4FJREFU1iF0nYTZF5Ny+cKvpIuPbLGSMHsObWtXR7aVW3TNaT/f+cgFbcjNJoWf3nUR+3+7FqU1es272h65CAigu90RWSUQyCzRO6O/VHorKwNG3NczJ91Hy0fLiJ8yFSXOga+mGkNyCsaU/i8VybKE2fT5ei6a00mCM3pTAkWWyE5zIEsSI3OTGZmbHPrsG3ML+MbcAlRNR9MEZpPCS7/5HyY37sDUI3Qwsr0MHZlPBk6mU7Fi6pU9IxmNJEzr7tN47EQ73j76lllVN7n+Ria4ShmaM4AXW4ZExs97YFDkoGZTwCPfsK8Ws6eDS4+/h0kEpGWNQiPPfYIMb1OEIbRqHmQtsMAbOiY6Cf4Ost11VNgCKZ82zYMmyYxxHsWhdbIxqRinwU6Wu44ZLXsosWWyPnksPsXEWxnzyO6sZWfCcCT0QFphqsQNNSsY7KlnlLOUfY6hUVvVRUWS8UsGTkQRP4NAnvohfxyz5swLe6CbB2WA2QzeXjnlQiBUDVXT+fUbO3F2+kNX7/X7cHlUjAYpoHveA0WWiHvnbzSXlYQcktZPPsa1ezc5P/35SVsP9hd/UxPuo0dQ7HHYRhQx8MabUBxxtHzyMbrLhSkzi9Sbb8WSm/elz/V14II25ADxNhNF86ZR/2Z5ZPGErmHNz4+6n61oFNLSJRGvrJLRGFpA6k3Hrp3Rjb8Q1L36NzxlpYFsFVXFOmw4Gd+9/7R4OELTqHvtFZybNyEZDQxJnEK5PRN/D3NmUGQunTj4JEcJfMcQ/I1OqdseEf81ojO6/SgHhs1iqXoxN1Z8hFGo3SsIqopk6PbIB9qVqF6pUahc2rCFEa5ADNfbWsEd7GRV8ni2J44IaZn3JCctjunFg9hX3syukgZ0AdNaD6EIrVcbOx10Px7JiEV0B12jixQEDHuKv5UKAoa83pwUensb0lnDkM5wr/mitsOMay9haep0DjtyqTMlB7357jH/76C5PFD+Fpc0bsMjmyiJy0aXlZMWlHUhJIlGYyKZ3qawhhw6gXWLfzbGYzlYz+SiNJydwdqIopFIuh5xhZLZjGPSZPaWNuFTIz8XQlCQlcDRqnZkWQquo0jcNzUZ/6ul4cVDfj/+hnpce3ZF5JyfCkKIQCX16pUgB0JPssnM4H95hJQrF5Fy5SKEELHq0V7EtFYAx+QpGAekBGRGg0gmM/HTZ2JMiZ59YsnNxXHRJKQeueSS2Uzc+Iuw5A2Juk9IxrQ3QuA+GvBudLcb4ffjPnSQuldfPuVr8Tc0UP38s5Tc/11Kf/Qgje+9Q+OSd3Fu3YxQA8dfdGIN49qPYJIC6iZDM+P5f7eOZ2Ci9XOP34XR2RJ1uwGdn31jFA/dNz8Q6ul1nY1v/xNvVSUAk0amRxbFCIFZ81HoqgzbLBEo4umr23xqso2Lx2VypLI1FNJP9TVjiFKNqSNTZ47UwY4qGolEkzEx9LdfNrI6ZQJ+qXdNZoCu2PvC+g0kaR3RGy4AFbZ0DELn2pYt/PQiA0U5/dTlVgwMlpx4DWYOxeWgSjIaEkdtWbySdQWdmsy768r4979s4Ud/2MCDv1/Hfy8twXrjHYH7L+gtSyYzceMmYBs5ilaXL2ruvKoJ0pPt3HZpIfF2I4osMTI3CUNdVXSHxOvFXVrav+voA9eunbStWY3w+xFeD8LjQWtvo/r3T4f0jWJGPJIL3iOHQDeb7Ed/SsvyT3Fu34pstpA49xIckyafdL+0u79J3PgJtG9cjxCQMG069rHj+vy+46KJNL33TmRxUZSFHKGqdOzcge71RhQe9YXqbOf4kz8PhHaEQPN6Ak2Sewn/G9CZW7+VS5x7yfrXn9DwP2/g/tnzHDWZSJg1m5Rrr+9TMa97gH27j8d+/lNsw4ZHN2KaRtvGDaTeeBPOjRsoai9lb0J+KFslXu3glqpPIkrXAXLdJ4jTOhnbvJs0bzN15mS2J47Aa4tnxqiAx2wxKXS4A55irTmFnM7aCGMuo+NVwittBXDCnIJHMZPhrsci1JDQVyikIwQInT3x+QzwtTKu/UjoyL09IkkIRnWUsy6hOHKCJNCC5xd+P553/s78ixdSYnCEZSB1FTN1LbYahcq43EQm/8uvaKht4Q9v7uV9VY9YIK5rCa+EPXi8mefbbDz28yfp2LIJzeslbsxYrAWFgY5VmQlRUy7NRgVV03lj+ZFQhtP2ww3skU3cbUkiyRWuziiZTKcUEoxGIPQYKSugOtvxVVUGxLpiRBAz5EFki5WUhYtICaq49QdJkogbO464kxjvnhgHDCT11tupf+O17nJoXQdZDjRjiDxDoGqvn4a85ZOPQ0a8i77ac0Egzl/56/9EBHORdY+H1lUr8dXXk/n9H5z0XLLNFpAYiHbcDicdu3ZGN/a6ju7xsmR9OUt3CLSEfCBYMSnJZHgasOrR9UGMQuObFUsQyBjQyfQ0MKa9hCWFi0JppJOkOj7R7aiygZ0Jw5jQdghZ7+7c4w/ms2d3dld5thji+EfGfFwGC7Kuc1njFoZ1HEdBYNF93FTzKVsSR7EpeRSTWvczylnOAH8bfknhhDmZQd7mCPVEBZ3C1jI2JYyMUI8UihGT7uXdtJm0GR1ku2uZtPZT7pp1OW/XmGl268hCZ4SznES/k4OOvIARbzvC6Opq1EvzGZCejNmkBAx/rwdm13pxjymntcPLMa+JYVEWBwenxjF6aAp7giEWCFS4piZZ2XqwLkIS2afD39Lmc0v1x6R5u9sHSoqCY/KUqP/v+oveVxMTSUaP+huJATFDfsZJmDEL++ixuPbsBgnixoyj+vXX2HqkiRJbFnbNzfi2w6T6WlHi4lDiI/t7+lUdVdPDuo8LVaV1xafRjWfvX3YQ2eGIWJgVfn8gP/7Pf0JzubCNKCJh5mwUW7iOdPJlV9D0/rt9Pyj6SBeTzGb2Dyxi2ZbjqFKP20+ApKuU2rPwyUZMmhrVS5QhJF5lCCoGTjm+nj+8G8+Nk9Ip3v0hFUkTORiXg18y8HrmAuY1biPbXYdfMtBoiifHXRsyrQJ4K+MS2ox2hCQz2FtLvqsq9EYgE0ybbNlDvTGBqa37UaSAp77fkcf2hBHcWbUs8jqBAf42cjqqqYzLwIeCIgdCNcNbSvhn2pyApy/J1JmS2BOfzz1rPuRbuhuvKjAEuwIBTG/d12MCZJqWvEv6Xfdw6/xC/vrBwZDxVeSgvG6UMIkQgsY2D30VtH/36lGs3V3D6l3VqJpgSlEaY4am8J+v74z6fa9s5M2sBXyv8h0sQsU4YADp3/4uiu3L6e47Jk3GW1UZsfYkhGBLm4mMylYKshJi4ZVexAz5WcAQHx9qu+Xza/xFHkPdgA78siHY5msolzdvY/4dV4bdsC6Pn1c+PMRnJY0IICPFxt1XjCBvUDwduz+LDNl0Ics4DXZsfheKroEsIxuNGJOT8Tqj5PqqKs6tWwKx+8OHaV3+Kdk/+zkGRyA3vrK+gw2mAtIzi0g/tjusevGkGI3YikbyycFWfP5eC5aShJAM+IHXMi7lvsrogly9zyMBmZ56fH6djat38w2DwsL6Dcxs3kW9KYkEtQMJwdbEkaR5m8lz14Qdo86cTIfBGgpfFHRUYojSZENGsLh+LSdMybyfNgOXwYovqJG+K76QMe0lYQu7XWO7vnYV5XFZHJxwFW1+iZrGDo7aB4dlquiygkdIrI8v4vKGzZz0/UvXad+wDm/lccb/4Mck3zSOZZuP0dDqoXBwIkkOM0s3HYvwooWAnLToEsIQyHy6eFwmF4/rzsvu9PjDVSB7IYwm6m79EbOLBmBMOj29NxNmXUz7xg346mpDLQNVZD4cMJWSVeVIkkRaspV/vXl8hMDdhUy/ZuL48eO89NJL7N69m5KSEoYMGcLSpUu/6rFdEKzdXUN9uw9/8IctgjHZT9KnceWI7viqEIL/+vsuKus7Qh5XVYOL37z5Gb/49mT0qqqoXrCGxAljMm/lXoGsqcz1lTB9kIH8W2+k/P2PApVx0R4AXQp8fh9qexvNyz4g9Rs38+m2Sv5vTSl+TUcYxhCXk8+M5l3UmVPQJIXhruPkdQaMZYRWuRB4qqpwxhX0XYUoBE5T3wYnGv6gZ99uigu9ISSoLhLU7tDPQN0VtYTdI5tCaoMQyPwQwdHrSGxIGs3OxGH4ZCMZ7gYuadzGnKadbEgeTVJnDYcceawYcBGl9kyuqluHXQt//ZeAjM469pQdpcI8KLAxSrqhkGTKbP0sbhECb2UlNX98jvxHHuXB68eEPvL6NFbvqqZV84VUHI0GmRE5SWSlRi/77wubxchFw1LZeqg+qiKkT9Vp8UmnzYhDoJ1h9qM/xbl9K669ezjYpPGxlkmDEh9QXSOg7//3FSXcc+WI03be851+Za2UlJSwZs0acnJyGDp06Fc9pguKbYfqwxe4gkiyTHmPNlzH65zUNLkiXps1XWfVzmpMaWlI5vBURR2Jw/Zs3sqYh08VeITCcmsRdbMXY8seTNK8+WGZOn2iaXR8tpM2l4+3Vh0NpKoFh9FhtPNR6jR2JRSyJz6fd9Jn837aDKJqBKoqWkMDWZ76iIrH7guXEJJMuxK9JVjvvfySwu6EQGVim2zHUDgi6iKr3EfnngxPI1qP9Mf9cXmhTkXLUqexJWkkbsWCJilUWtN4PWsBA3ytOBUrV9RvJMPTAJLEMVsG++OGRO2mpAidWrnbiKp9lP7b+lgbiIqu4z1Wjr8lPHvIbFL42Z0TmTl6EA6bkeR4Mwun5XD/4iiLrv3grsuHMzw7MepnZqNCfmZk6O/LIhkMxE+ZxqBvf5d/GEYGjHgPVE2w5WDf7e4uRPplyOfOncuaNWt45plnGDly5Ofv8DWizeXj3XVlPPX3z/if5UdoaI2ujf1F6ev1UAjCVBMbWj2h7uM9UTVBTZOLuAkXBXLOg4uoPhSezvsGSwbNxid3GzGfqvP+xnIAjCkpZD/yKJaCwqBwianPNmKKzcp768qiS7wGjS+ShF82BjvqpPdxxYLZTTsDaYR9Zb4IwcepU9B7tEXuahlXaUnDLyl4JCN+SaHcmsGalPFIEiTHm2lKykREmae+irRMQmVe2+5AazxdY0bLbkDgVKwcjMsJL9aRJDRJZltiEVbNy/O51+OSAw9PWZYwzZiDbAzPSPejcMw6iNaenZGirFmYFJjiCe+QBIE3Kr2vwJWsoHdGLjjH203cuWA4v39wJk99bzpXTcvDoHyxTGOTUeHH3xhLQVZC2DGMSmAxdHT+6dM4FEJEpDVG1YYn+jrAhUy/QityHz/urzv1LZ088cp2vP7A4uLhilbW7j7BwzePZWjG6fFE5o7P4uDxloiYZrzdSHZatxc3ODUu6s1rRGdIelwohbLu1ZfpPHiAToOtz/BFi7Pb8zMPzib7kUdDRRaVv/kl7qMlYSJLkslE4rz5bNtW369r8ksGSuyDyXPXRv18oK+NuyuX8rfBC6MKTyFJlNmzeCPzUm6pDqQidoVq/i9jDlbNS6KvgzpLEh4laEiBxjYPf1GTyUmbzeITq8OqNPtCMpmYN3M4udW1HC5toNBViQFBsykeg9DpHXTSJYUTlgG0mBICsW3FDEIwKi+F668ejW9CGvVvvIa7tBS/pLAnPp9VKVEKZHo8bCQJZo3L4rIRw9j6/N/YwwCEJFHoPM7O+EIy3XVc1HooIo1SUhRMaX09ME8fkiTx8E3j+HhrBev3nkDXBVNGpnH5hAya332b9nVrEX4/9tGjGXDDTaccahGqSuO7b9O6agXC58OYmkbqLbdhHzmKotxk9pU3hT33JAlG9ag8jhFb7Dwpb608SqdXDd1Emi7QdI1XPjzE4988eY55fykeksJlk7L5aHMFihL4cdtMMg/OGYTmdIbEt9KTbYwYaORAtSvkJUpCx6j7GH5gFUwfgjElhawfPoxQVVRdYPzDJvzecA9Hkoj6EOpaVB10731U/e4p/I0NSJKMUP3ET5+JbfI0XOvW9O+iJAmfZDxpP88Uv5PFJ1bzf4Pm9NkLs96czAFHHsXBXp66pJDTWUtJXHaw96cIebY6AS9Xkw0ct6azOz6fce0lJxsk1mGFgETLsvdJ8vuZ0sNaJPmcUSUBJKEHRL56VpdKEiUVLTQ7PQzIziH7J//O0coWfv1GpOKiFPh6uA6ZgJ2HG1A1nQ1J01GDVZafxQ0FJKosAylyHsOqezAKHR1QTCZSb7sjJL97uhC6jreiAqTAQ76rV6fRILNwWi4Lp+WGvlv19FOBBijBdQnn9m10HjpI7pO/Avq/zlH/5uu0b94YylTx19VS84dnGPyvP+H2SwsDzpSq4fMH9ITMBoVbLy08bdf8dSBmyE/CgeMtUd/+axpdeH1av/RN+sO1M4cwd3wWJZWtxFUewbjsLToPeCjXdSz5BQy69z4MjniubdhIfIvMroRh+CUDQzuruLhpJ3qVH811E4o9kPolGQwYgevnDOXvK0pC3r4kgcmgcM2s6JWnAIaERHJ+/gTe48dRW1sw5+RiTEpCCEGc1Rgqtvk8Su2ZaA1Sn6XvAHnuE9zVsJKlhVdR2+aht9kXhEvFykLDqHl7FMBIUZ8UftnIrviCkCGP9kCRLRbiZ8yi/vVXoyoDxmudFLiqOGrPCguvGISGHCWTw+3XePTFzcwck8Ft8wtZt7c29BYRfk3Bh2bPXH+gpcPL6l4iWV2jdisWXsq+ivFth8nrrMFldnDZA7ef9oYK7pIj1PzxOXSfL6AQabGScf8DWIdErot5KytxlxwJTz/VdXSPh/aN60nPua5f59RcLto3bYhIYxU+H01Ll5D5/R/wq+9OZeO+WirrnQxOdTB5RCo1TZ20dfgYkhGPLMdSEc+oIU9JObVV81Nl4MBTy3b4PKxmAx5fZEaHLMukp8d/4bhjNAYOhEF0sOfZV9G83YbFXXKEuuf+m7G/+y3HmxuY0VLPjB5NigFkq4V4RcXW6/pvmD+cnMxE/vHpERpb3QzPTeK2BSMYHExDO+l8pRajajolFa3InX7yBydx82XD+PO7+/rcxaBIyJLE9fMK2HagjtWdk5jdsD2kdxLt51ZYlM2D37iIx55fiz9KK+e8zuru46Mz1H2CI4688Bz0KHSlE3YtuupIHIrL4WBcLmZJ57JpeXh3bO2jECvAwrr1rE4Zz+6EAvySgTRvM3Mat/NWZjRly0BjjtWfVbO3tAmXx9/nIyxa3PfzdFa8iplNyaPZNnAM8yZmM3jiF1u87At/u5Ojv/9dWEGO5vVS8/RTXPTXFzH0qiOo31ePJEcGr4TPh6gJaOT05/focjUhGwxoUeoRtLra0DGyswLhmp2H6/nJn7cg9ED3KqNB5t/unkRR3vnfH/TL2K8zasibmjr6XLz4sgwc6KDhNOkfdzF7bAbLNh0PyyoxKBIXDR9IS3P0qsYvQ+0/30Xv3RlI0+isrKJq5wFMuXl4GxoifvW6LnDKVly9rl/rdKF9upT5O3bQKZtRU2ai+/JpaHB+7nztP9bMn97dF4rLmwwy9y8uJi3JGlECDgEH+arpuVw8NhOHzcQl4zLpcBdT+R/HkBv7yDAwmTCPn0SiojJU6eCIGhfQJQ/qhU9oPRjWfzTwMBBE6SwZPhahk99REYood8pmlqTPosYyICA7K3QO7/IztRWmRdlfAMgKiq5xSdN25jVtRxBY6FyXNLrPhhOB81aR3NxOgymRcltGhJb5F0GRJTRdYDEpJMaZWTgl+7Tf662rVgSkHHqh6zrHPl5FwoxZYds9lviQ9klPJKMRkZwK0K8x6ooNPVpnI0nCkDU47BhtHV5+8fKWsPUktxcee3ET/3X/9LACufONvn6Psiz1ywE+f6/8DHDFlBxqGl18dqQRg0FC0wR5GfHcfulX0/DV39gQtZOLpCiorS2kLLqGjt27wrxIyWQieeFVEel1mtvNkX//d4SzDYfQcQC+5W/x9r4jXPPovQzs8V0hBB2f7aR94/rAD2jCFJ5d78LXQ77U49N4+q3d/OTW8Tz+yjZ6y4APHhjHwqm5oVi71tlJ25//hNKXEQfsI0eh+/3s/MlPOZp+WZgKoo7EzJbdEV78kM6aUHpgGD00zIUkszF5NNsTi7i9+iOajPHdRhwCcrDIrE0czTZHARPajjC1ZW+oktIjGdmQehEWXyd5rioG+lpxKVY2JhWz1xE9/dauurmt6kNsmgeD0FAlhXaDndezFuBVopT49NBHkYSOSfejS3L3GIMYDTI3XDyUTo9KVmocY/JTUL6C5APN6YwaYhJ+P1qUojHL0HyMA1PxnagJq0OQFAMJM2f3+7yyxUrivEtoXbkiXGvcaCRlYXiXq4+2VkSVYBYCdhxuYMboQf0+79eNmCE/CQZF5rtXj6Kx1U1Vg4vUJOtJxfa/LLYRRXhKj0bGC/0qhpQUPOXlJC+8GvehA3iOHcOQkEDylQuJnzw14lgtq1eiO9sDsq1BTEJlfO1OPl17iO/cFvBFhRDU/uXFgMRu8AGh793LZbZs3k+dHnZMIQQV9R08cssEXvpgPw1tHhBQPDSFW4os1L/+CkLTiZ88haYPP8B9JLyjfE9kq40BN95Exc/+jXfTLgmESroWPIP/ViUDBhFuXCy6n8vqN/Fx6lR0SULvmUHbUzxKkvHJRpakziDV1xJhILvO4zbY2Jw0imrzAJLVdloNDppMCbSa4rEYZXZ4hpHsa2NMWwkzm3dzwDEkIpMF4LL6zcSrrtDDQBEqSX4ncxu382Fa+DxKQgOk0ItVot/JjdUraDU5evTwDHhjd10+nKkj+5eZIkQg3BAtTfXzsBYOQzKbI0JNksGINUqnekmSGPzwI9S++nKgzZwQmAdnk37XPRgSTi2ja8DiGzAkJNHy8TI0lyvQZegbN4d1/zlwrJlPt1VGDUFpmo7L07+1m68r/TLkbrebNWsCGQvV1dV0dHTw0UcfAVBcXEzm17zd0oBEKwNOQeL1i5J48VxaV60IeEBBL0cymbDkF1DxxM+DOd4Bgan0b9+L4yS6z607P4va4V6VFGr2HKIrqOApL6fjsx1h3pCs+ilwHiM5YRTN5u4fpdevc+yEk2mj0rn7iiLW7anBoMgUNx+i9bllgQeQELRv2YyuqhFdl7oWHSWTiQE3fAPXzh3oQlBrHhA1a2W3Yyjj2w6H6Z6rBKRxr61fy9ups6DnQpfQu1YTA39LEg3mRDI9DUhC7zPMocoGyu2ZHCM8FOL1qQjFQrXVQp05hdmNOxnfdpBtiUWE9RYVgqGdVRGKjQZ0RnZW8CG9HohIYft3GGw0mRPIcdeS6GunzRyPxaTw2F0TSU2KXhjVE10XvLe+nOXbK3H7NDJSbNw6v5ARp5CiZx02HGtBYSALJXgvSCYztqKRWKIsdgIocXFkfu8BhKoiNK3f4m69kWSZpPmXkjT/0qifCyF49aPDfXUcRJYlRvRXBvhrSr8MeVNTEz/4QbgaXtffv/zlL1m8ePHpH9kFiGK3k/PT/6B52ft07NqFYrfhmDSVxnf/D6GqlNsyKLcOwqr7KH7pNcb+shDFEX2BxJCUjKc8suJLFgIprnufzgP7ogpf7YwfRmuUUvlN+0+gC50N+2rx+QOlKht0G5PsI5jVshuAg6ZBDFFrMPfOewY0WWHN4NmcOGplVGsVw7W+vcd1yWPJ9DaS6m1GICEBjaYEPh04GUWK7O2JJEddNRzlLGVf/NCTdhhCksJDNkKEGXVVNrBmwHjGtx0MXEmPUE7XtUXDIEsMSrFR29TZbeZ7jcMvG9mRMJwsTz0Jagc+o5k5eckMSOhfU5E3lh9hQ48m3DVNnfz+f/fwyK3jyRvUd+/YnkiSROYDD9G+cT1t69eBJJEwcxbxU6d/rkCVZDBEpEE2trr567KD7CtrwmYxcunEwcwcPegLiV15fBpN7X2oIgIThqeSfRIdmVNBaBqeslKEpmEZmv/5cs7nCP0y5FlZWRw+3PdrcozThyEhgdSbbyP15tsAaFq6BF3APwfNo8qail8yoAidjUnF3LliO9OvmRP1OGkLFlC+ayey3r2QpCHRboxj0sVjQ9tkmy3QlaiHMXcpFtaljI3aT9Ln11m/5wR+LajFQsDIbU0aSXFHGUl+J+uSxzC0M7K7uYrMZ44CtkqDoL6DSpGOYstAFhp6lCwUTZL5R8Z8kvztDPC10mxwBJovy3LfHrYUboxtmocsbyOXNGxl+cBJ6EiB6/o8gxI00uneRq47sZpacwrrkorZkVgUvm/wv8ttg8jtPBHmleuSTMK48Tx6+wRe/+Qw2w7W9+lVehQTRl3jqtr1mISKVCY4sPYfFPz4x2EhBl99PW3r1qC2NGMfWYwyahzrd5+I6F3qU3WWbjzGA9eNPvl19rxkRSFh5uyoMW5V02lq8xBnM2K3nNy4tbt8/Oyv6+no9KELaO3w8ebyI1Q3uLj5koKT7hsNo0FGliS0KIvccVYD3zpNmivu0qPUPPt7dDXYTxdI//Z3iRsz9rQc/6skFiM/xxF+P/ttOQEjHozzasGsideP6ExSdYyGSINmHTKEuBtvZesHG2g2Okj1tZDod/L2oDmYV5WSmGQn1y4wZw6OMGoV1nSUKFWNAGoflkgAR22ZTGw7hNNoZ1viCKa07A8ZNq+ksN8xhLUpPbTbJYndCcO4oWY5KwdMosGc1D0WIRCShF9SqDcnU28OhAkUXcXh60CXJFyKFe1k/S4liQG+VnSg2FlKQWcVK1PGs7/3gqWI4t0H928yJeI02BnaWUWbwcYqc1JU9/vj1KncUbkMo+7HLFT8shFTvAPH4huxW4zcu2gUdyzwc//v1kXsa9BVCjoqAUGc3u156u3NHP+Pn2LJG0LivEuQLRZO/On5gMplUP+GpA8wJ84Ja9vXRXVDILNqX3kT/1xVSm1zJynxZhbPGspFw1P7nrderNpZxT9XlyJEQNtnfOFA7rliBCZj9Oyd5TsqcXvUsIeWz6+z+rNqrpyaQ7w9uu5NXxgUmWnF6WzcVxu22GkyyiyanndaJG11j4fqp58KS78UwIk/PU/uL36JMfncTm885w25EALXrp20rl6F7vPhmDSFhBkzz5tXni+Lfcw49u/yhi3W2VQ3+Z1VGBSZ0iMFDC+K7JrS1Obh6UNGPFkz8Pq1sNixt7WDw7/6LeVCpcaWht2WywgqMfoCaYVGve+FI4lATLK3XIAUbHEGML1pNxPaA29wAnAqVv42eCFuxRzmRU9p3sP0lr0YhMbdVUtpMThYmTKeUkcOSFKgn2ev82uygXjVhVsx4ZeNuEX0qtDAyXUc/k7KbJl8OHAKboM1etf6kxgCgcQJSwqDvI2U2bJCD9HeWAamUDr5QUwlezG1NnLQY6U0Pgf1r7u4yNDEFfZGEmfMZN74DFbsrAk9PAy6nzjVjcPvos6URKqvNVSKLwPoOp7So9RWVgQymnqk6gmvF5rqKdYOsikhXANJAganxbGvrInn3t4bCrvUNrv5y9IDeP0a04s/P8tj99FG/rHyaFgK7mcljbz84UHuXRS9N+2hitaINwQAg0GiqqGDIvupl9ffPK+Ajk4/e0qbMBgk/KrOrNEZzJ2QdcrHikbHrp1R0ymF0GnfvImUKxaelvN8VZzzhrzh72/Qtn5daDXde/wYzs0bGfyvPzkt3brPdaxDhmBOPAjBZIJR7Ue5rGFLKJ4rP7OFttvvImH6jLD9/vbhQZwuX9ArCq+AvKJ2A1sTh1NrSUGVFAxCY0XSeG7v2MKAhnJyO0/0qVNy9YxcPthcEUX3RaKwI1AIMrntQJjT+snAyRFGHBHQM+ky/hKQojq5tn49L1gH4DTYkaKUZEpCJ8nvxKI4uNF9gP8xjqbZFN+HMZYY4q7BqPvxy8boRvxzEST4OzgQl0eFLa1Po9/c5mXupDy2J9h5Z10ZPlmHoM3d5olHPlHJrN3PMH/WxWQtmM1768txeVTSkhKpazHxoXF6SAf9upqV5HjCdW3K5WQy/I2RWuV+PxPVKnYYisOMrdEgc9W0XF7q0XiiC5+q87+rS5k2Kv1zvdmlm45F7O9XdXYcbqDT48cWJcySmmSlrLotIoykaYIkxxdbEDUZFe5fXEyL00tTu4f0ZBtx1tPnzGmdnVFTf1FVtI7Tm7P/VXBOq2H5GuppW7smLCVK+Hx4qyoDr5UXCJdcMRGTIuHwu7isYQtGoWESKiahgqpS//or+JubQt9XNZ2Dx1ujx2OFoM0Ux4lgXrUI5i57ZSNvx08AiwWDInFjzQosmheT7sMgB7zwxbPyWDRjCLddWojRIGM2yph0PwZd5aq6dSEZ1p6mQQBl9qzIeLYkUWobHDk8ID/YeNmhuiJaqBmExjjnEW6/tJDRP7yfO9TPsOi+cFlcEdBgkYXO+uSxJPvbA3PVl3RuX4hAp54hnTVsSxyBGi2FMYjRKFPd6OKjLRURAmiqbGR7YhHC56NtzSqmpsv87vszeOHhi3HYTGh6IJ7uk034ZBMuJTxDqtGYwKoBE/oshEpOiefqGXnE200ossSQjHgevnkc2WkOapujqz46O31Rc7J701NgrSeKLOPsjP7mdtnEbIyGcCfLIEvkpDsYlPLl0neTHGbyMxNOqxEHsA0fQbSYmWQ2Yx/V/3WGs8U57ZG7jxyOKqsqvF5c+/bguGjiWRjVmWd84UCmFg/Cs3ZF9B+zgI7t20m69LLPPZYE7HXkh8uzAkgS7cJM3MM/w7h1LdaK4/w0u53awkloFjvDc5JCP56ZozMYVzCQvaVNaC1NpHz4JgZfA5hMyGYzmscDYZkw0Q1QtGsRgAj6Fym+dhL9HVTa0pCEwKp5ubJ+IwP9TgaNH41sNlP8+H/w3d89yyfNNo5ZBwUMr6uK6c27qbIN4lh8Nsdv/jH3+Bp4ZZ8Hjy4hyzKqLhg2OJFDFS2oWl+VoiKkouiJVtTTA00TDEy09KlF45WN6EgoAlz79mFKH0Rzu4ej1W0R1c7txjg0pND6wq74AhqCsfokf3uY9yWMJhLnzOPyyTlcPiUn4rzJDnPUSlyr2RB1baU3BVmJbDtYF+EUyDKk9JFVMzg1jv9350R+//eddHpUdCEYmZfMtxcWfe75zhbmjEzip06jfcumkOMomc1YC4YFjfy5zTltyBV7XPRXWUVBie9fWtXXAUmSuHPBcI51HMT7yY4IuyiEjtC6Y6cGRaYoL4n95c0R2XjiJOXtkiShJCQy8MabQtv6iqLGWY1MHZUOpCNmPIk/KB0g2+2U/8uPQmeRgMKOSo7EDQ4vbReCAldF5BiAEnvAUy+1ZXB13TquqN+AkCRsqgckCfWaW0M5y5IkkTYoiUUHV0Qca0THMUZqdeRffA9QwOj5gtLqNtxelfzMRCQJfvHadhrbPBFetFGGoW0VZAdDHPkdlexMGBauehhEkQOKkoNS7GSnxVF+IvJVPNnfFghXKTKyNWAA21w+DLJEb9O/K76ACW2HUIJvIy6DBSEr/O+gudxS/TEm3R9Yq0CgjhiHY1LfSpzXzhzCX5eFh1dMxoCSYX8WCa+Zmcfuo434/FrImJuMgWrTk2kNXTQijafun05LuxerWYkagjnXSL39TuzFo2lbtwahqsRPnY5j0uSQAuS5zDltyO2jigOCOr22S4pCwoz+lwF/XRg0bTIVK5ZFaGJIsox9zLiwbXctGM4vXtuB26vi9WsoshRcX1NIlnTadDXCK0+Mt5D6BQqfJEnClNqdBZH2zW9T99KLIb3WS1t3UpOQRbsethMWzRuI0csSUnB823Nn4pFtKEBKop0PDLPJ6Kwjt6MazWiG4vHcfUW4Qkri3Pm0rYw05AD2sd3zIksSBVmJYZ8/dtckth+qZ3dpIw2tbpraAoZnzvgsxtW5aPnACH4/U1v3cciRi0exoIruH7Ysw6QR6dwWlFW9aV4B//X3Xd2GMxiemd+wLbRPXLCQK2OAHS3KApvTksDxmddRuOMD0DTyvXUcjcumxRTP87nXkeOuxa66qbWn85O75p/UIE8qSgvExNeU0tHpw2o2sHBaLpdOjAxrRSMtycZjd0/kvXXllFS1keQIdBwaPXTA5+4rS1KfXvu5iCRJxI0bT9y48Wd7KKeMJKIt1X5FfBHRLG9VJdXPPI3mcgVvWIn0b34r9GPo4qsQzToXaXz3bVo++SiU9y0ZjSRduoAB10QWZamazmcljdQ1d5I1MI7RQ1OQ5cCK/+9e3UR5fSc+IWOUBAaTgX+9ZQI56aensEJtbw9UjPr92EePRU9M5v/9aRNOtz/0lmCQJYoSBXcOUZEUhbhx4zEkJtHh9iNLgZ6RJ5pcbNhbi8enMq5wIEU5SVENV9MH79P0zv+FbZPtdnIeewJj8hdvQuCtrMS5bQtWs4K3oJiNjQYOHmshJdHCrDGDyI2ignm81sl768s4XtVMUks1M50HyfQ1gwQZ33sA24juEMMn2yp4e21Z6I1AkSWsZgNPfHMS8VYD3qpKdIOJ335azYlGV+gBYTbKzBmfxY1z8vt1HUIIfKqOySCfkQ70F8rv8XTxZUWzznlDDoGb0Hv8OMLvw5I3JKqY/oV043iOHwt0uQcckyZjyck95WMMGBDH2u0VHK1uIzHOzMThqV+5epyz08fba8vYcbgeWZaZXpzOoul5mPvIRz5VvCdqaHrvHdSWFuzFo0m8eC5K3OmRTv6i95fu9dJ5+CCSrGAdNjxq2uye0kY+3FJBW4ePkXnJXDk1h8S48Ji8X9VYs7uGrQfqA28M47IYk59yRozyF+FC+j2eDi4IQ94fYjfOqRGbr1MjNl+nRmy+To0va8jP/Sh+jBgxYsQ4KTFDHiNGjBjnOTFDHiNGjBjnOTFDHiNGjBjnOWc0j/yr7nYd66Z9asTm69SIzdepEZuvUyPafPV3Ds9o1kqMGDFixDj9xEIrMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGeEzPkMWLEiHGec14Y8ttvv51hw4ZF/efFF18E4Nlnn436+UsvvXSWR392WL58Oddffz3jxo1j+vTpPPDAAxw7dizie++++y4LFiyguLiYK6+8kmXLlp35wZ4D9Ge++roP9+7de3YGfRZZu3Yt1113HcXFxcyYMYNf/vKXeDyeiO/t2bOHm2++mdGjRzNz5kyeeeYZNK1388avP/2Zry9jw87pnp1dPPbYY3R0dIRte++993jzzTeZNWtWaJvFYuGVV14J+15GRsYZGeO5xKZNm/j+97/PokWL+OEPf0h7ezvPPfccd999N++//z5xwa45H330EY888gjf+c53mD59OsuXL+dHP/oRdrud2bMvnJ6o/Z0vgPHjx/PII4+E7T906NAzPeSzyubNm7n33nu54ooreOihhygtLeW///u/aWho4He/+13oe5WVldx1111MmjSJF154gbKyMn7zm9/g8/l4+OGHz+IVnFn6O1/wJWyYOE+57rrrxMKFC0N/P/PMM2Ls2LFncUTnDo8++qiYM2eO0HU9tG337t2isLBQrF69OrRtwYIF4sEHHwzb9+677xbXXXfdGRvruUB/5+u2224T3/nOd87GEM8pbr/9dnHttdeGbXv55ZdFYWGhOHDgQGjbz372MzF79mzh9XpD2/74xz+KUaNGiZaWljM13LNOf+fry9iw8yK00ptjx46xd+9eFi1adLaHck6iqip2uz2sn6PDEd5UubKykrKyMq688sqw7QsXLmTv3r00NzefkbGeC/RnvmJ0s3fvXqZPnx62revvlStXhratXbuWSy65BJPJFNq2cOFCfD4fmzdvPjODPQfo73x9Gc5LQ75kyRJkWeaqq64K2+7xeJg6dSpFRUUsWLCAN9544yyN8Oxy7bXXUlZWxmuvvUZ7eztVVVX8+te/ZujQoUydOhWAsrIyIDIskJ+fH/b5hUB/5quLrVu3Mm7cOIqLi7n55pvZtGnTWRr12UOSpDDjDGAMNpUuLS0FoLOzk5qamoj7KysrC6vVekHdX/2Zry6+qA07L2LkvXn//feZOHEi6enpoW3Z2dk8/PDDFBUV4fP5+Oijj3j88cdpbm7mgQceOIujPfNMmTKFZ599locffpgnn3wSgMLCQl5++eXQDdXW1gZAfHx82L4JCQlhn18I9Ge+ACZOnMiiRYvIzc2lsbGRV155hXvuuYe//vWvEQb/60xubi579uwJ29b1d9d943QGGgn3vr+6tl1I91d/5gu+nA077wz5rl27qKio4N577w3bfvXVV4f93bVY9+c//5lvfvOb2Gy2MzbGs83OnTt55JFHuP7665k7dy6tra08//zz3Hfffbz55ptYLJazPcRziv7O14MPPhi237x581i0aBHPPffcBWXIb7nlFv7t3/6NV155hauvvpqysjKefvppFEUJC0/FCNDf+foyNuy8C60sWbIEs9nMggULPve7CxYswOv1cvTo0TMwsnOHJ598ksmTJ/Poo48yZcoUFixYwIsvvsiBAwd47733gG7Pu729PWzfLg+h6/MLgf7MVzRMJhPz5s1j//79Z3C0Z5/Fixdz55138pvf/IbJkydzxx13cNNNN5GQkMDAgQOB7jWG3vdX17YL6f7qz3z1RX9t2HllyFVVZdmyZcyZMycsJSxGOKWlpQwfPjxsW3p6OklJSVRUVAAwZMgQIDIW3hWz6/r8QqA/8xWjG1mWefTRR9m8eTPvvfcemzZt4oYbbqC5uZlx48YBYLPZyMjIiIgBV1dX43a7L6j7qz/z9aXPcVqOcoZYv349LS0t/c5WWbZsGRaLhYKCgq94ZOcWGRkZEV5idXU1LS0tZGZmAjB48GCGDBkSUQC0dOlSiouLSU5OPmPjPdv0Z76i4fP5WL58OcXFxV/1EM9JHA4Hw4cPx+Fw8NprrxEfHx/2pjxr1ixWrFiBz+cLbfvggw8wmUwXVCiqi8+br2j014adVzHyJUuWkJiYGFYE1MXixYu55ppryMvLw+/3s2zZMt5//30eeughrFbrWRjt2ePWW2/liSee4IknnmDevHm0trbyxz/+kZSUFC6//PLQ9x588EF++MMfkp2dzbRp01ixYgUbNmzghRdeOIujP/P0Z762b9/OX/7yF+bPn09mZiaNjY28+uqrVFVV8fjjj5/lKziz7Nmzh82bN1NUVITX62XlypW8/fbbPPXUU2GLm9/61rdCv8Hbb7+dsrIynn/+ee68884LKrTS3/n6MjbsvGm+7HK5mD59Otdccw0///nPIz5/6KGH2Lt3Lw0NDUAgje7WW2/luuuuO8MjPfsIIXjrrbd48803qaiowG63M2bMGH70ox9FpIO98847/OlPf6K6uprs7Gzuv//+iNzyrzv9ma/jx4/z+OOPc/jwYVpbW7FYLIwZM4bvfe97TJgw4SxfwZnl4MGDPPbYY5SUlCCEYOTIkdx3333MmDEj4rt79uzhP//zP9m/fz8JCQnccMMNfP/730dRlLMw8rNDf+fry9iw88aQx4gRI0aM6JxXMfIYMWLEiBFJzJDHiBEjxnlOzJDHiBEjxnlOzJDHiBEjxnlOzJDHiBEjxnlOzJDHiBEjxnlOzJDHiBEjxnlOzJDHiBEjxnlOzJDHiBEjxnnO/wcqKhmXpt++/AAAAABJRU5ErkJggg==\n",
   1661       "text/plain": [
   1662        "<Figure size 432x288 with 1 Axes>"
   1663       ]
   1664      },
   1665      "metadata": {},
   1666      "output_type": "display_data"
   1667     }
   1668    ],
   1669    "source": [
   1670     "color = ['r' if c==0 else 'b' for c in data_train[:,0]]\n",
   1671     "plt.scatter(np.linalg.norm(data_train, axis=1), data_train[:, 82], c=color)"
   1672    ]
   1673   },
   1674   {
   1675    "cell_type": "markdown",
   1676    "metadata": {},
   1677    "source": [
   1678     "**Blue Switch Off & Row 82 > 3.5 & Random Forest classification**"
   1679    ]
   1680   },
   1681   {
   1682    "cell_type": "code",
   1683    "execution_count": 236,
   1684    "metadata": {},
   1685    "outputs": [
   1686     {
   1687      "data": {
   1688       "text/plain": [
   1689        "DecisionTreeClassifier(criterion='entropy', max_depth=10, min_samples_leaf=2,\n",
   1690        "                       min_samples_split=7, random_state=100)"
   1691       ]
   1692      },
   1693      "execution_count": 236,
   1694      "metadata": {},
   1695      "output_type": "execute_result"
   1696     }
   1697    ],
   1698    "source": [
   1699     "dum2_train = data_train[data_train[:,1]==1]\n",
   1700     "d2_train = dum2_train[dum2_train[:,82] <= 3.5]\n",
   1701     "\n",
   1702     "Xfor_train = d2_train[:,1:]\n",
   1703     "yfor_train = d2_train[:,0]\n",
   1704     "\n",
   1705     "clf = DecisionTreeClassifier(criterion='entropy', random_state=100, \n",
   1706     "                             max_depth=10,\n",
   1707     "                             min_samples_leaf=2,\n",
   1708     "                             min_samples_split=7)\n",
   1709     "clf.fit(Xfor_train, yfor_train)"
   1710    ]
   1711   },
   1712   {
   1713    "cell_type": "code",
   1714    "execution_count": 237,
   1715    "metadata": {},
   1716    "outputs": [],
   1717    "source": [
   1718     "def predict(X_data, classifier, y_data=None):\n",
   1719     "    failed = []; pred = []\n",
   1720     "    for i in range(X_data.shape[0]):\n",
   1721     "        if X_data[:,0][i] == 0:\n",
   1722     "            pred.append(0)\n",
   1723     "        #elif X_data[:,0][i] not in [0, 1]:\n",
   1724     "        #    pred.append(0)\n",
   1725     "        #elif X_data[:,81][i] > 3.5:\n",
   1726     "        #    pred.append(0)\n",
   1727     "        else:\n",
   1728     "            clf_pred = int(classifier.predict(X_data[i:i+1]))\n",
   1729     "            if np.all(y_data != None):\n",
   1730     "                if clf_pred != y_data[i]:\n",
   1731     "                    failed.append(i)\n",
   1732     "            pred.append(clf_pred)\n",
   1733     "\n",
   1734     "    if np.all(y_data != None):\n",
   1735     "        print(np.count_nonzero(pred == y_data)/y_data.shape[0]*100, \"%\")\n",
   1736     "        return pred, failed\n",
   1737     "    return pred"
   1738    ]
   1739   },
   1740   {
   1741    "cell_type": "code",
   1742    "execution_count": 238,
   1743    "metadata": {},
   1744    "outputs": [
   1745     {
   1746      "name": "stdout",
   1747      "output_type": "stream",
   1748      "text": [
   1749       "Training Data\n",
   1750       "98.54510184287099 %\n",
   1751       "Given Data all toghether\n",
   1752       "91.05 %\n"
   1753      ]
   1754     }
   1755    ],
   1756    "source": [
   1757     "print(\"Training Data\")\n",
   1758     "pred1, failed = predict(Xfor_train, clf, yfor_train)\n",
   1759     "print(\"Given Data all toghether\")\n",
   1760     "pred2, failed = predict(np.array(data_train_db)[:,1:], clf, np.array(data_train_db)[:,0])"
   1761    ]
   1762   },
   1763   {
   1764    "cell_type": "markdown",
   1765    "metadata": {},
   1766    "source": [
   1767     "**Prediction**"
   1768    ]
   1769   },
   1770   {
   1771    "cell_type": "code",
   1772    "execution_count": 239,
   1773    "metadata": {},
   1774    "outputs": [],
   1775    "source": [
   1776     "X_test = np.array(data_test)[:,1:]\n",
   1777     "pred3 = predict(X_test, clf)\n",
   1778     "np.savetxt('./prediction.csv', pred3, fmt='%1g', delimiter=',')"
   1779    ]
   1780   },
   1781   {
   1782    "cell_type": "code",
   1783    "execution_count": 240,
   1784    "metadata": {},
   1785    "outputs": [
   1786     {
   1787      "data": {
   1788       "text/plain": [
   1789        "Text(0.5, 1.0, 'y_train')"
   1790       ]
   1791      },
   1792      "execution_count": 240,
   1793      "metadata": {},
   1794      "output_type": "execute_result"
   1795     },
   1796     {
   1797      "data": {
   1798       "image/png": 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\n",
   1799       "text/plain": [
   1800        "<Figure size 1152x720 with 4 Axes>"
   1801       ]
   1802      },
   1803      "metadata": {},
   1804      "output_type": "display_data"
   1805     }
   1806    ],
   1807    "source": [
   1808     "fig, ax = plt.subplots(2, 2, figsize=[16, 10])\n",
   1809     "ax[0][0].hist(pred2)\n",
   1810     "ax[0][0].set_title(\"Prediction of Test Data\")\n",
   1811     "ax[0][1].hist(data_train[:, 0])\n",
   1812     "ax[0][1].set_title(\"All Data\")\n",
   1813     "ax[1][0].hist(y_valid)\n",
   1814     "ax[1][0].set_title(\"y_valid\")\n",
   1815     "ax[1][1].hist(y_train)\n",
   1816     "ax[1][1].set_title(\"y_train\")"
   1817    ]
   1818   },
   1819   {
   1820    "cell_type": "code",
   1821    "execution_count": null,
   1822    "metadata": {},
   1823    "outputs": [],
   1824    "source": []
   1825   }
   1826  ],
   1827  "metadata": {
   1828   "kernelspec": {
   1829    "display_name": "Python 3",
   1830    "language": "python",
   1831    "name": "python3"
   1832   },
   1833   "language_info": {
   1834    "codemirror_mode": {
   1835     "name": "ipython",
   1836     "version": 3
   1837    },
   1838    "file_extension": ".py",
   1839    "mimetype": "text/x-python",
   1840    "name": "python",
   1841    "nbconvert_exporter": "python",
   1842    "pygments_lexer": "ipython3",
   1843    "version": "3.10.4"
   1844   }
   1845  },
   1846  "nbformat": 4,
   1847  "nbformat_minor": 4
   1848 }