RamanClassifier/data/data_processing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-02-26T18:00:51.600227Z",
     "start_time": "2024-02-26T18:00:50.046904700Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "                                                   strain  replica   phase  \\\nfile                                                                         \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...   A390      1.0  liquid   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...   A390      3.0  liquid   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...   A390      3.0  liquid   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...   A390      2.0   solid   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...   A390      2.0   solid   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...   A390      3.0   solid   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...   A390      3.0   solid   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...   A390      3.0   solid   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...   CHA0      1.0  liquid   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...   CHA0      1.0  liquid   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...   CHA0      1.0  liquid   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...   CHA0      3.0  liquid   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...   CHA0      3.0  liquid   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...   CHA0      1.0   solid   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...   CHA0      1.0   solid   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...   CHA0      NaN    soli   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...   CHA0      NaN    soli   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...   CHA0      NaN    soli   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...   CHA0      NaN     NaN   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...   F113      3.0  liquid   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...   F113      NaN   liqui   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...   F113      NaN   liqui   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...   F113      2.0   solid   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...   F113      2.0   solid   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...   F113      2.0   solid   \n\n                                                    objective substrate  \\\nfile                                                                      \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...         50       alu   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...         50       alu   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...         50       alu   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...         50       alu   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...         50       alu   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...         50       alu   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...         50       alu   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...         50       alu   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...         50       alu   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...         50       alu   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...         50       alu   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...         50       alu   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...         50       alu   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...         50       alu   \n\n                                                    laser_power[%]  grating  \\\nfile                                                                          \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...             100     1800   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...             100     1800   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...             100     1800   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...             100     1800   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...             100     1800   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...             100     1800   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...             100     1800   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...             100     1800   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...             100     1800   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...             100     1800   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...             100     1800   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...             100     1800   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...             100     1800   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...             100     1800   \n\n                                                    exposition[sec]  \\\nfile                                                                  \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...               20   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...               20   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...               20   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...               20   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...               20   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...               20   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...               20   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...               20   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...               20   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...               20   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...               20   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...               20   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...               20   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...               20   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...               20   \n\n                                                    confocalhigh  \\\nfile                                                               \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...          True   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...          True   \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...          True   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...          True   \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...          True   \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...          True   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...          True   \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...          True   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...          True   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...          True   \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...          True   \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...          True   \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...          True   \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...          True   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...          True   \n\n                                                    accumulations  \nfile                                                               \nA390SampleSpectraLiquid1_50x_dried_drop_alu_100...              2  \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...              2  \nA390SampleSpectraliquid3_50x_dried_drop_alu_100...              2  \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...              2  \nA390SampleSpectraSolid3_50x_dried_drop_alu_100p...              2  \nCHA0Liquid1_50x_dried_drop_alu_100percent_1800g...              2  \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraLiquid1_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...              2  \nCHA0SampleSpectraSolid1_50x_dried_drop_alu_100p...              2  \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...              2  \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...              2  \nCHA0SampleSpectraSolid_50x_dried_drop_alu_100pe...              2  \nCHA0SampleSpectra_50x_dried_drop_alu_100percent...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid3_50x_dried_drop_alu_100...              2  \nF113SampleSpectraLiquid_50x_dried3_drop_alu_100...              2  \nF113SampleSpectraLiquid_50x_dried_drop_alu_100p...              2  \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  \nF113SampleSpectraSolid2_50x_dried_drop_alu_100p...              2  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>strain</th>\n      <th>replica</th>\n      <th>phase</th>\n      <th>objective</th>\n      <th>substrate</th>\n      <th>laser_power[%]</th>\n      <th>grating</th>\n      <th>exposition[sec]</th>\n      <th>confocalhigh</th>\n      <th>accumulations</th>\n    </tr>\n    <tr>\n      <th>file</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>A390SampleSpectraLiquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraliquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraliquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>A390</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round211 (2).txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>A390SampleSpectraSolid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round211.txt</th>\n      <td>A390</td>\n      <td>3.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0Liquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round (2).txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round.txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2.txt</th>\n      <td>CHA0</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2 (2).txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid1_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2.txt</th>\n      <td>CHA0</td>\n      <td>1.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>soli</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu(1).txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>soli</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectraSolid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>soli</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>CHA0SampleSpectra_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>CHA0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu (2).txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2_otherdrop1 (2).txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid3_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2_otherdrop1.txt</th>\n      <td>F113</td>\n      <td>3.0</td>\n      <td>liquid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid_50x_dried3_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2_otherdrop.txt</th>\n      <td>F113</td>\n      <td>NaN</td>\n      <td>liqui</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraLiquid_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>F113</td>\n      <td>NaN</td>\n      <td>liqui</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu.txt</th>\n      <td>F113</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2 (2).txt</th>\n      <td>F113</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>F113SampleSpectraSolid2_50x_dried_drop_alu_100percent_1800gr_20sec_confocalhigh_2accu_round2.txt</th>\n      <td>F113</td>\n      <td>2.0</td>\n      <td>solid</td>\n      <td>50</td>\n      <td>alu</td>\n      <td>100</td>\n      <td>1800</td>\n      <td>20</td>\n      <td>True</td>\n      <td>2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open(\"../data_raw/metadata.csv\") as f:\n",
    "    df_all_experiments = pd.read_csv(f, index_col=\"file\")\n",
    "df_all_experiments"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-26T18:00:51.632216300Z",
     "start_time": "2024-02-26T18:00:51.602923Z"
    }
   },
   "id": "8ad20a80c1220f67",
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "0                #X      #Y        #Wave    #Intensity\n1      14537.392021 -1316.1  1927.490234  34298.539063\n2      14537.392021 -1316.1  1925.943359  34948.273438\n3      14537.392021 -1316.1  1924.396484  34378.742188\n4      14537.392021 -1316.1  1922.849609  34778.796875\n5      14537.392021 -1316.1  1921.300781  34488.968750\n...             ...     ...          ...           ...\n30326  14577.392021 -1284.1   188.570313   9527.851563\n30327  14577.392021 -1284.1   186.636719   9477.843750\n30328  14577.392021 -1284.1   184.701172   9612.567383\n30329  14577.392021 -1284.1   182.765625   9742.063477\n30330  14577.392021 -1284.1   180.828125   9698.495117\n\n[30330 rows x 4 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>#X</th>\n      <th>#Y</th>\n      <th>#Wave</th>\n      <th>#Intensity</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>1</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1927.490234</td>\n      <td>34298.539063</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1925.943359</td>\n      <td>34948.273438</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1924.396484</td>\n      <td>34378.742188</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1922.849609</td>\n      <td>34778.796875</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>14537.392021</td>\n      <td>-1316.1</td>\n      <td>1921.300781</td>\n      <td>34488.968750</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>30326</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>188.570313</td>\n      <td>9527.851563</td>\n    </tr>\n    <tr>\n      <th>30327</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>186.636719</td>\n      <td>9477.843750</td>\n    </tr>\n    <tr>\n      <th>30328</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>184.701172</td>\n      <td>9612.567383</td>\n    </tr>\n    <tr>\n      <th>30329</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>182.765625</td>\n      <td>9742.063477</td>\n    </tr>\n    <tr>\n      <th>30330</th>\n      <td>14577.392021</td>\n      <td>-1284.1</td>\n      <td>180.828125</td>\n      <td>9698.495117</td>\n    </tr>\n  </tbody>\n</table>\n<p>30330 rows × 4 columns</p>\n</div>"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with open(f\"../data_raw/{df_all_experiments.index[0]}\") as f:\n",
    "    df_experiment = pd.DataFrame([x.split() for x in f.readlines()])\n",
    "    df_experiment.columns = df_experiment.iloc[0]\n",
    "    df_experiment = df_experiment[1:].astype(float)\n",
    "df_experiment"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-26T18:05:49.594975900Z",
     "start_time": "2024-02-26T18:05:49.527469Z"
    }
   },
   "id": "4d6ba1f5360b6333",
   "execution_count": 12
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: >"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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nZyMlJQUxMTEICQkxuzmEm3D0O7OO376pmhEEQRAEQTiBlBzCRyi1BkeCIAhCJ6TklEaM7JAqvaubBEEQhI9BSo6ZkL7gBLpABEEQhH5IySEIgiAIokRCSg7hxVg0XhMEQRCEc0jJKY0Y8auhiMcEQRCEj0BKjpmQvuAE8skhCIIg9ENKDkEQBEEQJRJScsyEDBUEQRCED7No0SJERUWZ3QxNSMkxC/JtYYCuEUEQJZPLly8jKCgIt27dQl5eHsqUKYPU1FTr53Xq1MGMGTOYz7dhwwZYLBZkZGS4vrEOGDJkCI4dO2b9f8qUKWjVqpVH2+CIkpFL3Rfx1aB6Hm23oPGaIAjCt0lMTETLli1RpkwZbN++HeXLl0etWrXMbhY3oaGhCA0NNbsZmpAlpzRCViSCIAhTSUhIQOfOnQEAW7Zssb7WwmKxYN68eXj44YcRFhaG+vXr488//wQAnD592pqRvFy5crBYLHjqqacAAIWFhZg6dSpiYmIQGhqKli1b4ueff7aeV7IArV27Fu3atUNYWBjuvvtuHD161Fpm79696N69O8qWLYuIiAi0bdsWu3btAmC7XLVo0SK8++672Lt3LywWCywWCxYtWoSnn34aDz74oM33ycvLQ+XKlTF//nz9F5EBsuQQPgIpZgRBaCAIQN5tc+oODGOeOKampqJFixYAgNu3b8Pf3x+LFi3CnTt3YLFYEBUVhccffxxz5sxRlX/33Xfx8ccf45NPPsHnn3+OYcOG4cyZM6hZsyZ++eUXDBo0CEePHkVERITVujJ16lQsXrwYc+fORf369bFp0yb85z//QaVKlXDPPfdYz/3mm29i2rRpqFSpEkaNGoWnn34aW7duBQAMGzYMrVu3xhdffAF/f38kJycjMDDQrn1DhgzBgQMHsGrVKvz7778AgMjISDRo0ADdunXDxYsXUbVqVQDA8uXLcfv2bQwZMoTxQuuDlByzIGsKQRCEa8i7DXxYzZy637gABJVhKlqtWjUkJycjKysL7dq1w/bt21GmTBm0atUKK1asQK1atRAeHq4p/9RTT2Ho0KEAgA8//BCzZs3Cjh070Lt3b5QvXx4AULlyZatlJScnBx9++CH+/fdfxMbGAgDq1q2LLVu24Msvv7RRcv73v/9Z/3/99dfRt29fZGdnIyQkBKmpqZg4cSIaNWoEAKhfv75q+0JDQxEeHo6AgABER0db37/77rvRsGFDfPfdd3j11VcBAAsXLsQjjzzi8Pu6AlquMhOz9Bxf9QciCILwYQICAlCnTh0cOXIE7du3R4sWLZCWloYqVaqgW7duqFOnDipWrKgpL1mBAKBMmTKIiIjApUuXNMufOHECt2/fxv3334/w8HDr37fffouTJ09qnluytkjnnjBhAkaOHImePXvio48+spNlYeTIkVi4cCEAID09HX///Teefvpp7vPwQpYcsxAE3/SlJQsUQRDeRmCYaFExq25GmjZtijNnziAvLw+FhYUIDw9Hfn4+8vPzER4ejtq1a+PgwYPaVSmWiCwWCwoLCzXL37x5EwCwYsUKVK9e3eaz4OBgzXNbivp56dxTpkzB448/jhUrVuDvv//GO++8g2XLluHhhx9m+NYiTz75JF5//XUkJiYiISEBMTEx6Nq1K7O8XkjJIQiCIHwbi4V5ychMVq5ciby8PPTo0QMff/wx2rZti8ceewxPPfUUevfurernwkpQUBAAoKCgwPpekyZNEBwcjNTUVJulKT00aNAADRo0wPjx4zF06FAsXLhQVckJCgqyaYNEhQoVMGDAACxcuBCJiYkYMWKEofawQkqOWZBFhCAIolRRu3ZtpKWlIT09Hf3794fFYsHBgwcxaNAg6xKRkXNbLBYsX74cDzzwAEJDQ1G2bFm88sorGD9+PAoLC9GlSxdkZmZi69atiIiIwPDhw52e986dO5g4cSIGDx6MmJgYnDt3Djt37sSgQYNUy9epUwcpKSlITk5GjRo1ULZsWavVaOTIkXjwwQdRUFDAVLcrIJ8cgg9P+vOQ7xBBECWMDRs2oH379ggJCcGOHTtQo0YNwwoOAFSvXh3vvvsuXn/9dVSpUgVjx44FALz//vt4++23MXXqVDRu3Bi9e/fGihUrEBMTw3Ref39/XL16FU8++SQaNGiARx99FH369MG7776rWn7QoEHo3bs3unfvjkqVKuH777+3ftazZ09UrVoVcXFxqFbNM47iFkEovSNJVlYWIiMjkZmZiYiICM9UOiVSPAaGAeXvAtL3F72f6Zl6AaBhX+DoCvZ65bItHwf2LmWXNcIn9YFbRU5197wObPzIM/USBOHVZGdnIyUlBTExMQgJCTG7OQQjN2/eRPXq1bFw4UIMHDjQaXlHvzPr+E3LVYT3Il/So+U9giAIn6SwsBBXrlzBtGnTEBUVhX79+nmsblJyTMUkI5ovKgyl1+BIEATh06SmpiImJgY1atTAokWLEBDgOdWDlJzSiK8oDL7SToIgCEKTOnXqwCzPGHI8NhUftKgQBEEQhI9ASg5BEARBECUSUnLMwleXYjzpz+OLvkMEQXiMUrw5uFTgit+XlBzToIfTKdSBEQShgr+/PwAgNzfX5JYQ7uT2bTGzvJFI0OR4bBa+OoD7arsJgigxBAQEICwsDJcvX0ZgYCD8/Gi+XpIQBAG3b9/GpUuXEBUVZVVq9UBKjqmQwkAQBMGLxWJB1apVkZKSgjNnzpjdHMJNREVFITo62tA5SMkxDVJwuCD/HIIgZAQFBaF+/fq0ZFVCCQwMNGTBkSAlxyxo2YcgCMIQfn5+lNaBcAgtZJqGAIqTQxAEQRDug5QcwjcgyxdBEATBCSk5ZkGDNkEQBEG4FVJyzEIohE86H3vUAdgHrw9BEAThNZCSYxo+OoCTBYogCILwEUjJIbwYcswmCIIg9ENKDuEbUJwcwl3cSAMuHzO7FQRBuAFScjzJuV1mt8BcCguAzdOAszsZBWhpjPAA0xoC8e2BrAtmt4QgCBdDSo6nOL8bmNdD8WYps07s/gZY+x4wv6fZLSEIe9IPmt0CgiBcDCk5niI10ewWyDDJQnL5qDn1EgRBEKUSUnI8hprVhpZjHFPKLF0EQRCESzGk5Hz00UewWCwYN26c9b3s7GyMGTMGFSpUQHh4OAYNGoT09HQbudTUVPTt2xdhYWGoXLkyJk6ciPz8fJsyGzZsQJs2bRAcHIx69eph0aJFdvXHx8ejTp06CAkJQceOHbFjxw4jX8e9eJXjrDe1xQHya0Zb1wmCIAhOdCs5O3fuxJdffokWLVrYvD9+/Hj89ddf+Omnn7Bx40ZcuHABAwcOtH5eUFCAvn37Ijc3FwkJCfjmm2+waNEiTJ482VomJSUFffv2Rffu3ZGcnIxx48Zh5MiRWL16tbXMDz/8gAkTJuCdd97B7t270bJlS8TFxeHSpUt6vxLhDnJvAcnfA7evmd0SgiAIopShS8m5efMmhg0bhq+//hrlypWzvp+ZmYn58+dj+vTpuO+++9C2bVssXLgQCQkJ2LZtGwDgn3/+waFDh7B48WK0atUKffr0wfvvv4/4+Hjk5uYCAObOnYuYmBhMmzYNjRs3xtixYzF48GB89tln1rqmT5+OZ599FiNGjECTJk0wd+5chIWFYcGCBUauhxvxEeuJq1n5KvD7KOC7h3UIl9JrRhAEQbgEXUrOmDFj0LdvX/TsabtLJikpCXl5eTbvN2rUCLVq1UJiouh4m5iYiObNm6NKlSrWMnFxccjKysLBgwetZZTnjouLs54jNzcXSUlJNmX8/PzQs2dPaxk1cnJykJWVZfPnMbxqucqDHPxVPF5M5peVX7PSev0IgiAI3QTwCixbtgy7d+/Gzp32sU7S0tIQFBSEqKgom/erVKmCtLQ0axm5giN9Ln3mqExWVhbu3LmD69evo6CgQLXMkSNHNNs+depUvPvuu2xflPACSLEhPAndbwRR0uCy5Jw9exYvv/wylixZgpCQEHe1yW1MmjQJmZmZ1r+zZ896sHbqQAnCuyHndoIoaXApOUlJSbh06RLatGmDgIAABAQEYOPGjZg1axYCAgJQpUoV5ObmIiMjw0YuPT0d0dHRAIDo6Gi73VbS/87KREREIDQ0FBUrVoS/v79qGekcagQHByMiIsLmzyPk3fFMPSUNWqIiCIIgDMCl5PTo0QP79+9HcnKy9a9du3YYNmyY9XVgYCDWrl1rlTl69ChSU1MRGxsLAIiNjcX+/fttdkGtWbMGERERaNKkibWM/BxSGekcQUFBaNu2rU2ZwsJCrF271lrGa/h3CvC/aAoGqAsvUHLyc4B59wNrJjsvSxAEQXgVXD45ZcuWRbNmzWzeK1OmDCpUqGB9/5lnnsGECRNQvnx5RERE4MUXX0RsbCw6deoEAOjVqxeaNGmCJ554Ah9//DHS0tLw1ltvYcyYMQgODgYAjBo1CrNnz8arr76Kp59+GuvWrcOPP/6IFStWWOudMGEChg8fjnbt2qFDhw6YMWMGbt26hREjRhi6IC5nS9GOMMkBl2DHGyw5B38Hzu0Q/+5/z+zWEARBEBxwOx4747PPPoOfnx8GDRqEnJwcxMXFYc6cOdbP/f39sXz5cowePRqxsbEoU6YMhg8fjvfeKx5AYmJisGLFCowfPx4zZ85EjRo1MG/ePMTFxVnLDBkyBJcvX8bkyZORlpaGVq1aYdWqVXbOyARhiMI8s1tAEARB6MSwkrNhwwab/0NCQhAfH4/4+HhNmdq1a2PlypUOz3vvvfdiz549DsuMHTsWY8eOZW6r15F+gF/mTgYQGsVevrAA+OE/ije9wELChK+0kyAIgvBGKHeVL7F1FvB/tYFdC9llUjYBRx0rlF4L6TiER6EbjiBKGqTk+BJr3haPy8exyxTkuqUpnoEGHYIgCEI/pOQQBEEQBFEiISXHV8m5Cfz7LnAh2eyWuA9v2F1llLT9QOZ5s1tBKDmTAFxSRkf3ldAKBOEmziUBC3qLxxICKTm+yroPgC3Tga/u0SHsK525SUrOlRPAjBZA0jfGznP9NDC3C/BZE5c0i3AR108DC/sAczqa3RKC8C4W9BJjui3oZXZLXAYpOb6Knp1ZZiAYUKjMsuQsHwdknAH+esnYedL2u6Q5hIu5esLsFhCEd1KYb3ssAZCSUxq5ddnsFng3Pu2sTRAEQUiQklMaOWefQd5tGLLGlACfHMKHoPuNIEoapOQQnHAuP+ldrkr+Hrh2UvaGBwcgI0tshQXAoT+BG2muaw/hWnzFJY0gCMOQkkMw4OEZ7p0M4PdRnq3TVexaAPz4BPB5O7NbQhAEUeohJcdXMWJt4MXIkpMe2bzbKm/6yPc9/o94zL3hmrYQrodWpQii1EBKDsGAReM1QRCm4cmJDkH4KKTk+Cqe3F5tpC5f7IiNtNkXv29poyT8RCtfBT5rCty5bnZLCMKrISWnxOMCZcjiBbfJ9rlmt4AgvIcdXwJZ5/mS9RJEKcQLRi/C6zGi5OiyAqnIeHLG6mkfJMKzlKSfiO43gnAIKTm+ikeXRVy0XEVLOQRhPnuXAT8+CeTdMbslBOF2SMkhtCksBJY8CuT7aGeoV6kin5ySTWn/iX57Hjj0B7DjK37ZHV8D83oCt6+5vl2E71NYYHYL7CAlh9Dmwm7g+GrFmz6Si+riPuDT+kDSIs/VSRC+hJ4l4JWviBHTN09zfXsI15B1Edg8Hbh1xbP1Hv0b+KAysPcHz9brBFJyCG1ckaTNLJ+B30aJObr+ehnIywa+HQBsnen+eslHgigNqMayIryC7x4G1r4L/DzCs/V+/5g4Zvz2nGfrdQIpOb4K62Bq9qBr1vKNIDOb7l0KnFoPrJnMJlvatswTBFFyuHxYPKZsYiuflw1cPuq+9phMgNkNINyMq7d/Z55z7fnUcLVixutgSYpK6YSMcERpZGFv4MIe4LGlZrfELZCS46s4G4iPrwHWfwhUbeHaek9vdu35CMJbIN2WKI1c2CMe9yw2tx1ugpScksqSweLxwm5z2yGnNFhIzF4eJAiCIKyQT44Z+AeZ3QLCEeSTQ3gj2ZninzdA9znhI5CS4w6unADm3Q8c+0f98zZPerY93oKvWDmoAye8jYI84KNa4l+BC3Y9EkQpgZar3MHstuJx6SPqn/sFeq4thnBF3isfUWxcRWn7voRnkMe0yckyrx0E4WOQJccM0g+Y3QLPUdqsIqXt+xKlE1LmCR+BlBwzoB1KjiFFgTADGrcJosRBSo4ZVG1ldgsIgihNpG4DTm00uxUE4XFIyTGD9s+Y3QIvhyw5BOEyCvKBBXHAt/305asiCB+GlBwzqFDf7BZ4N7RcRZhBSb3tCvOKX7tKyaFnlJDw8nuBlBwzqB1rdgsIX+D4v8D5JLNbQXgDXj6QEKWUxHjgk7uAS0fMbokmtIXc0wSVNbsFPoALOnRfHxSunwaWDBJfT/GSAHAEQRByVr8hHldMMLcdDiBLjjsIidL+rFFf8Vizk0eaYghPbxO9fAz4+Rkg+XvP1uuNZKSa3QLCm6At2wShC7LkuIOKDYBzO9Q/k7KC+/l7rj168bQ15JuHgJtprjkXDQr6yc8V71P/UtY90C2jjSDYPlP0fBE+Ally3IGjWbhf0SW30KW3w1UKDqGfgnxgWgNgRnPfX/LTxAe/l5m/xQ//Aeb1BAoLzGsD4Zgrx4Gkbwz+RiVTcS1lUzUP0eJRIGGW+mdSSgdfsOS4YrZm1oyvxA7QbibrXNEOnOtAfjYQGGp2iwizOfyXeEzbZ247CG1mtxOPhUbympXMPpPMCe4gqIz2Z/5FSo7FB5QcV0OKh3ciCMCBX8TZYKnAB2es3rY8RM+yd3Jup9kt8DpIyXEHjmJRdH5ZPPqEJccVbTSpc/a2QYGV3NviAOLJQeTICuDnp4tng4T34Zb7wUefEYLggJQcd1ChnvZnZauKR2/3yREE1/SB8u+pV/Hw9mtlg4HBKP0g8GFV4M+xrmsOC+d3ebY+0yErhAhdB0JOyVR6fWn08B2qtdb+TBqwvXm5av/PwP/VBo6sNH4uV1hU/HS4jvmiOX3LZ+Jxz2LftUQRBOGj+GCfyQA5HruDyJran0mDl58X65e/FOXW2vypue2Q8AsECnLNbgUjPq6c+KJyyI2P/0YEQTDjxSOtD1O2ivMyZlhy2j7l+TpdMaDk3dJRLQ1khBalQZFzM/R8lUBK5m9KSo5ZGHY81tFRm6FYmfXcGLJImCXrBdDgRbBQKix+REmAlByzMEPh8PMHYrp5uFLZoEkdI0GYDCmxhBYls38mJceTRNUqfq3HmdYoFn/PK1c+aRkw0mYXfV+PKoS++BsZobR9Xzny+6o0XweitEBKjrvo/pb9ezcvF78OCDJYgY4OyuJngnJlUr4bQ3WZtFxlmqWrZM7gtClt31cL3utASlHJxgsmd26AlBx3cfeLjj83w5LjZ4KSQ2kd9EHXzQS8t6N2HWYp/0TJxnvvDVJy3EVgiP17Ty0vfi3lsPIk+bkmRFouDQOHizBtaY9+IxHv7ahNsxCWaqWXKAmQkuNJImsUv/Y3alHR0fmcSSg9lhxDkBWFKKkYucd88VkmSjuk5LiTUVuA7m8W/x8gs+6YsVz1n5/N9cnRQ3i0zmrJLK8Ln1RKSwP0uxDejPfenxTx2J1ENxf/ysUAQgEQGlX82e7vPNuWKs2AstGeVXK2zQVuXTJ2jptp+uR80URvoe32hLsh5d8nOPYPsOZt4OG5jtMEeQ3ee2+QJccTtHgEaPmY7Xu3r3i4EVI6CQ8pOZnngFWv2b6nd+Bu8ZjzMl6DgUGEFBtCE3fs+GO4V+meNIeljwCXjwBLHjW7JT4PKTlm0WOywRNwDqZScU85HufccN25PO4sbQQfHxRoUCM08d4lCYfcvgYcXwMUFpjdEn5yb5rdAka8997gUnK++OILtGjRAhEREYiIiEBsbCz+/vtv6+fZ2dkYM2YMKlSogPDwcAwaNAjp6ek250hNTUXfvn0RFhaGypUrY+LEicjPz7cps2HDBrRp0wbBwcGoV68eFi1aZNeW+Ph41KlTByEhIejYsSN27NjB81XMJ7S8wRPojHFhhi+QtQk6HoSo2j6m5LgI8o1xI1rX1puvuTvaVkoU2nk9gCWDge1zzW5JCcZ77yUuJadGjRr46KOPkJSUhF27duG+++5D//79cfDgQQDA+PHj8ddff+Gnn37Cxo0bceHCBQwcONAqX1BQgL59+yI3NxcJCQn45ptvsGjRIkyeXGzVSElJQd++fdG9e3ckJydj3LhxGDlyJFavXm0t88MPP2DChAl45513sHv3brRs2RJxcXG4dMmg/4cn8efYQl5YCPz+gmvqNVNh2P8Tv4zFYk4KDALePeiXNihQpG6unRKPB38ztx2EKXApOQ899BAeeOAB1K9fHw0aNMD//vc/hIeHY9u2bcjMzMT8+fMxffp03HfffWjbti0WLlyIhIQEbNu2DQDwzz//4NChQ1i8eDFatWqFPn364P3330d8fDxyc3MBAHPnzkVMTAymTZuGxo0bY+zYsRg8eDA+++wzazumT5+OZ599FiNGjECTJk0wd+5chIWFYcGCBS68NG7GnyPi8fF/gOQlxuqzFP3UHrPkqAyQt6/qO09ptOR4BSVggFNDfmvaLM/5yPfltfLREiRRitHtk1NQUIBly5bh1q1biI2NRVJSEvLy8tCzZ09rmUaNGqFWrVpITEwEACQmJqJ58+aoUqWKtUxcXByysrKs1qDExESbc0hlpHPk5uYiKSnJpoyfnx969uxpLaNFTk4OsrKybP5Mg8eSk+OCdkodoxGFodGDHIVd1LFa/MiS40lKxTKZC3exCQKQn2PsHHrqJEoH3L81BRRVwq3k7N+/H+Hh4QgODsaoUaPw22+/oUmTJkhLS0NQUBCioqJsylepUgVpaeI24LS0NBsFR/pc+sxRmaysLNy5cwdXrlxBQUGBahnpHFpMnToVkZGR1r+aNWvyfn3XwRXx2AU3kCssOWZYVCyl1JLjqwNZyibg1AazW+EYG0XO4HVe9CAwtSaQnWnsPN6Kr96HpRZa1lTCreQ0bNgQycnJ2L59O0aPHo3hw4fj0KFD7miby5k0aRIyMzOtf2fPnjWvMTzLVa7gntfFoxElx2LCZjyLnzn1llaMDGp52cA3DwHf9nft7jqXI7fkFBo71ZktQEEOcOJfY+dxKwa2kBPmUiosq+6Fe8QLCgpCvXr1AABt27bFzp07MXPmTAwZMgS5ubnIyMiwseakp6cjOlqMWhsdHW23C0rafSUvo9yRlZ6ejoiICISGhsLf3x/+/v6qZaRzaBEcHIzg4GDer+weeJarXIEUUMqQkmOCRSWmm+ctOaUtKJ+rOtL8O8Wvc28BwWVdc15XU9p+39KIIAAFuUCAl/T3JR7vVcYMT5ELCwuRk5ODtm3bIjAwEGvXrrV+dvToUaSmpiI2NhYAEBsbi/3799vsglqzZg0iIiLQpEkTaxn5OaQy0jmCgoLQtm1bmzKFhYVYu3attYxPkHfHeRlXYl2uMqAwcMm66Kbv+a4+5crIwO0NA58nZ3De8H09itZylYc76utngNNbPFsnNz56b3zbH/hfVTFGDlGq4ZrWT5o0CX369EGtWrVw48YNLF26FBs2bMDq1asRGRmJZ555BhMmTED58uURERGBF198EbGxsejUqRMAoFevXmjSpAmeeOIJfPzxx0hLS8Nbb72FMWPGWC0so0aNwuzZs/Hqq6/i6aefxrp16/Djjz9ixYoV1nZMmDABw4cPR7t27dChQwfMmDEDt27dwogRI1x4adzM3qXsZV0x4Fkdj31suSo4XGebXTRglWpzMcN3LywENn0C1GzvI+Hn4T2WnJktxONzG4FqrUxogI8qMCykbBSPR1ea2w6jlLoJiOvhGj0uXbqEJ598EhcvXkRkZCRatGiB1atX4/777wcAfPbZZ/Dz88OgQYOQk5ODuLg4zJkzxyrv7++P5cuXY/To0YiNjUWZMmUwfPhwvPfee9YyMTExWLFiBcaPH4+ZM2eiRo0amDdvHuLi4qxlhgwZgsuXL2Py5MlIS0tDq1atsGrVKjtnZK+m0wvA4b/0y5/ZylfeFY7HZu1y0mN9MqKclDbFRvP7MnSwh34HNnwovn7ttIsa5G5c6HjsCi7sdq+S45aB0guuW0njygnxXmj+iNktKVFwjXjz5893+HlISAji4+MRHx+vWaZ27dpYudKxdn3vvfdiz549DsuMHTsWY8eOdVjGq6nUyLP1uWR3lUkOwLqUKy9QVHw9SSgLGWeKX/vKrNPGkmPQ8ZjwbnzlngSA2W3FoyGLOU3ulNC2FbMIM5rWgRPpwTFijTFrl5Me5aqEPrBux5cGBd1oLVf5yHf35G9UKu4HL+PcTgPC9HspISXHF3CJT44LHI9NW67y8E40I/jioOCqNvukYumDv5fLMPJ7+chv7ZP3pAxfb78XQEpOSUNrwDLqeNznY/OC8ulps6HOwYBjqk92SqVsoJdbJAUTd1eptsEtFbj5/F6ML046CJdCSo43U1hQnFyOhSsngOmNgcQ5Kh8aTOvQ9ikTl6s8vbvKQMcov0bcCo+sXl/ZQi6X9ZUBxahPzs1L+iMcr30P2Dxdn6wrMHJPEh7CyO4/X5xkuRdPZWsk9PDLSODgr0C9ns7LAsDqN4AbF4HVk+w/k4Ji6dnRFV5FlGdZrirIB9L2AQEh/PXY1VsU3NGTu6s2T7ddE+c9j6aVwJvRaKfPtJ+Dk+uBv1+TvcH5HbMzgU/ri6+ncCo6GWeBzdPE151fLn7fk4qHER8kn7RSljZK4DNrEFJyvJmDv4pH1pDxhfnan0kd1IVk/nZIHSOLA/CKCcDub4AGffjrUdK/aJeeJy05a9/VJ2e0XqWsWc6l3EqdVnkvHRC/G2D7P+91vnJcf9352fpl5ZilfPqikzZR6qHlqpLEybXOy4RE6DixpOQwKBu7vxGPx/7WUY+CskVxj/SkwHBZqgLODNOG6vWCgcNlA6gXfBcWzm73XF1mXVtfDGVQqjFyzTn6n/xcYNdCA3X5BqTklDZ6vMMvY92Z5eFdToZi+7hIyVkxgbNaX3ykSvHuqu8fM7sFbIqEId8nuaXOwP3pi7+vmWSeA7Z9oSNZrYcmSomzgeXjDNTlG9BylZkEhLjOhM1KZA1+GVcEEtSFAWdp6pDZKW2Ox2bhsnvSVZYcekbcytc9gJtpQNp+YIDaZhCT4Y2a7xDvffZ9cdpZchiyRDyGezAdxc1LzsvYYXBnll6k+vQoV3oGXKODdO4t/btuShw0gNrhKiWQd0eYEZ8rzcFLx++bkQrs/1ncNVoauJkmHk+uM7cdpRyy5JiJ5B8TGOreeu57275OHvyLbhM9vjFGkHZz6VomM0HJ+ag2UJhn7BwSvrKFvLRZzFymqPAqHgYsZt6SumJGc/GYcwNo56lkyl4QB8mj8HxHF14PL7bikiXHG7h+2r3nr9O1+LUeq4gk4+nlqrxbRS90mOfN6NhdpeB4HK3ry+krwitb2jBrucqIguQOTm82qWIv+O5uh+M7lpIJCik5ZpKR6pl6bl8pfl2+Lr+8ZEnxuJJzRzwmLWKXEQRgQW/g4l4dFZrdCXrBFnLCMUYGBq3rzG2ZMVKecxu4ps+Vr9wzpWMgt2Las+y99wMpOWaSfsAz9Vw6VPxaT2LQPv8nHj2t5FRrLR5PczjI5d0Gzm7TV5+rO4hrJ3kb4Nr6PVFvKZkNWvGKLfYGlqu8ZenKY3jv4Gs+rlyu8t77ipQcM6nWxjP1VG9nTL5yY/HoLiUn46x6PBopSnPNDu6p1w4Xd4j/TnHt+dyFW+KolDLlx924agu5ISWNFAavx6xJhxdbg0nJMZMa7T1TT7CeAIAy3LmF/FwSMKMZ8PV92mX6TnN9vQThs7jK8ZhzQPTigUwbi8Zrwk4hchQx34chJcdM5LuVbl8zfr4AlV1aMfcUL/voRVJy3LG7at8P4tHR0l1oOdfXq4bpnbis0/HojMzs7+0lmLWjzVm9F/cBKyeqy7Igt5JyLyv4oh+OHF9vvztR3HfHVhk4l/deW1JyzERuGWHNT+WIcnXs3xv+J1vOKUdISo47NH2WgcWocvXPW4wFTX5QTTM1u2M93Xs7Pa/DmdLyZVfg6Aq5APu5E2YDn8uWxQ0tTeoXJUo45JNDqCJXcrz4JrEOvknfuP7c2+c6L2M0nQTrtTXbkuNtGcy9oQ2exFe+L087/3lTKWykYgOypYQtnwFfddeRykEOXWdXQsEAzcTGQuGGWXx4tGvOIw2+enctGcXTQQhNoyQ5DZL/g2N8JJO40bQdF5KB21eBej34ZX0RabPB9i9ddELea87x3Bm1HF8+WvzaiycIZMkxE/+g4tcV67n+/Foxcdo+xXceyRIyaL6h5uiGJ52EL+8eMW07tvd2UJ7FR66DoSUnDotxYaEiDIKOer+6B1g8ELiWwi/rcnQ8X2n7gVVv8PtMFuTy1yXB+/te5Q1VIWGgvzm5HoiX73r13meHlBwzsViACClhphsGuKha6u93ekE8sjr0hkSJx+ptDTeJGT3Z0gEYethMn42UJEuOD+IrlyFlowFhji+56jXgy24yUQNL6hln9MuaydwuwLZ44O9XTWqAkz7h4O+2PleeQtowIuHF7hak5JiN5BTMmrSu7r0OPlR0YK3/o1Gu6MGRD245N4A/xtonk7urR7GFQa+loUFvfpmQSO3PHA3Kvjxgl7bAekrSDwHnd5vdCs9g5D5dMcFF9Tq533Z8pb8er8TANU/b77pmOIWjnV7zG3lv30VKjtlIzscCo5LDsh182C/Ai7uBmK7qn0s5lrIzit/b+DGw5zvgu4dty55cW/zaojcLuQVoOpBPRLlEFRRe/NrhAOHDy1VmbSG3qctEX5EvYoGvu7smnAKhgS9bOj1EdiZw5YTZrXAfCZ8D8+6X5QbUg6J/uphspEVuhRyPzUZSHFi3Z9/JcF4mIAiocJf252d32L/HkiQ0sobzMmrcTAcqGPQ5slF63GTJMbsTL82WHLm5+9ZlfelHjDeCs7iByMNm8fdr+mW9eElCEz3P9LRGYnqY0Ymubw8LRnKEsfQhzCE1SgZkyTEbyZLDulx1aoPxOmO6qbzJ8DDpHYQv7NbeIVW5ifr7dp0Ta/JKkyw5RhWk3d+KljRXnc8leKANOTfZ731349FrbtLve4YjD5xL8QYFnrENebfF46n17muKQ7zh2S85kJJjNn6clpw2TwC1Yo3VKTkSA+IOCgA4/JexczpDa4eUZqoI5YPuxge/sAA4uxPI9+COCCV/vmhMXi8ZqYoEqB4cjG6kA1OrA/N6eq5OU/GGgd4IrnoGzVqKLQWkHzS7BV4HLVeZjTT4s5qCQyKBQJX0DXrqBETlyi9Iu6yr0Arop2XhKRdj+z+rCVePsrHxY2DjR8BdDvJnOcVHZ18zmptXtxTF98Ju91tRcm4AgWWcFDJrucpHss+v0bvj0WC9hqrywbQOXPeV7/jGmAVZcsyG1ycnINR4oky5YuGs3vvfM1aXhFab1ZyZH/jUfhdZrU7Fr109ICbOFo/KnWU8eMXykhfhTTPozHPA1BrAogccl6Pf0DHnd+mX9ab7waeg62YUUnLMhtcnp1JD40qOXP7SIcdlKzc1VhcAdH9L22ITEGz/Xodn7TtFm0zkKoPRnetinp4bF3U0kDqSYlw00PMqDO4cBA/8Ih5TTXIkVYNnK7fboPveO+F5dkxSzH1IaSUlx2ysy1WMSk6NdrY5jnTVKVNyDGWeZaTbK9o+OazfRe5HpDaA/j5GzNOz6EHu5rkGF3c2PtSJeD/uupZk+WHHG+5nb2gDA764xObFkJJjNlZLDsNy1V09bGV01ylTOM54YHZrsThIssn4EDuL5XJ8tXi8Y1KMFVcvdeTnuPZ8evDk8o1XLBV5QxtKKDbPry8qG96Kj1xLEyHHY7OxcEQ8lsoaVXLkOMux4qpniLXNWstjednFr7MuOI4DxIsRq0nafuD7xzW25RtgyWDXno+VAkbfMLfi4o6b9fc1bQu5LwymCrivlRcEnPSZ6+wr7fQNyJJjNlIemnXvi8eMs8CCPupbuqXO2pVKTsfnxWPZauqfByvSKwycx1lBUZv9Gdv8rIbzr9x3R20nmlmzrl+eBTJTgeTF5tTvauZ0dM15DC23+Ugn7xMzfS/BF5dffbHNHsN3rg1ZcryFjFTxuGICkJog/tnhQiWn/F1ihmEpR1RQmH2Zu18SfYDk1GwvHgNVyqvBan0aNB9o7sB6ERJR/FrNWdksCrxgWcmVuCqqrU8qAL7YZpNgUQC8wrnaR7iRXvyarptLIUuOt3H8H+3PrJYcZzmkGB4MSbmRlsnuXLcv0+t9lc6s6H8pKqgzJOVG0yeHg+AiRacgz/i5CC/DnQqGFw4UrhrIDCmTblbqvELR9QGF4fByYFoD2Rs+sJTppZdSDVJyfIn2I8Wj0d1VgP2uLta8VHLlhsV/o0xF8egK60tOlni8dcX4uWwwa5Ah1DGpB/W2XFQZZ4FbV81tgyFkbSPHY202fuSZelxBYYHPJdCl5Spfok4X8Zi0UP1znofSGoSwSMnxZ1RC5MsZBbnOfW0enCEeXbnEtP4DYLib01AQjHjzIFuEt/hWaD6fKu/fvgbMaKb/nMlLbcMucLXHRXjDBMAVE0JP4w3XTYvvBgApm4CqrcxuCTOk5PgSkmJSrTVwYY+xcyktOaxKiDzdAktsn/J1i84fwt42Z0j+S3IsFtePtyGRQHami0/qSxi4oF7leKzRFv8gxe5ClnplZYwEPHTm+3TpMN+55Vw/A/w+mqGgRvvzc53/fkzfXW7J8VN/3+2YtavLSxRrV5OySTz6UPoIUnJ8CamjaDbYuJLDs3Vdjk3eKwZZv6J6XGnJUfPJMTL70eqPanQATqxxIltCOzNmWLPDO8GM2atfoK2S4/blKncMuGpWIMblXLXvW5APTG8sKoBG8QYHWtMsOW72ldq1ADi1Abh63EA9pQNScszmvreAdR8AjRgi9VpcqDA4SwxauYmGnOyWYdmJY22zCy05YeVddy5HlKnkmXpKIoaUFg/Fycm7Zey8hiw5XrokceMCu5LkFC/4jr7gC6S8TCyXbfl4d7SkROKDC5YlDGnHUN4d52Ulq4jRLOSAvU+Okif/0JCT3TIsDsCSk5orlZx2z7juXI5gccb21sHKU8gHEZ+3avFmIefcbi9/dmxkjTi+6xd1/+4q2Xf0lLKReR5Y+ar7zs+Mrz8LJQdScswm/YB4PLmWXcYVCoOjnFmPfgeEV1aXk3dWW2eIx/wcYPWbwKmNKgJFHakr2ly/l3jUSvapG40OyelWfRdwJ8N3FaW17wH/TjG7FSbiquU5tfOwnlutnAcGWG+Nk/Pjk8COLz1fr0vx0f7ASyElx2xOrueXcYXCoGXJGbwAaNKP7RzJS8TjtjlA4mzgWxU5adlLa4nNyI4wdxJRvbg+PdRo77zMsX+A/6sN/P2a43LeqgRtnqb9GbdVx4Q4OTU7KZrgbksOh0+OIR8zA2ksXHqvcewmcxXndzmoy0ufIyXXTpndghIFKTlmo8cq4Q5Ljp7OTfLPcZTkU1pac7f1SYt2TzsvozYoWPyLlwd5ZQG2qNT/viMebWaeKrhaySksBI6vcX28IW9VxrR+o+6TjJ3XSHRon48szWnJ8UWDilmkeiBpcimClByzUcan0Rocm8lSHuRnq5fhQXN3FUdv1D9ePEoZwB3hCmdpRzvC1AayCvX1W2P8/NhktQYZ+VZ7TVivtYsHsj3fiQlA53RyXM5blRZuNK6zXWoSJ9/32D/Aj8NlxTmuz6mNwM8yhdtVSo7LlsyKcKlflRfsroKHfIFKAlr5C30cUnLMRhlML7Kmermu/5X944LBx9nuKkfU6CAeg8uyy7ii83TYZjVrjB+bX41aZ3/9tLEcYVJ8IFfgamXj6ErxeOuys4pdW69ZaN17SiXW2XVe+oi4+8hanuPZ+bafbdgHp7KM195X0jqYtsvJx+9hT040WJMo+xik5JhN2n62ckFlil+7ZOmn6IYulFIzFD1MLMqInhg7wRGOP2eql9Mnxz/QmF+NXsfj0HLGlrq8BU92sKbEyTHoWO6yuEBefh/oxgu+I1NQRAbcen96iSLmithIXggpOb5Al/FAudrF/ztb+mEZPKWEmYUM+afszl902/DMZF0R28aRT47ad75znW0gY53ps3Lnur0VSLWTNGm5ym14aTs1/aaUv68Hc1fZPDtGHIC9OABjiVnuNBFPToRckUTZCyElx2x6/5/iDUXH0KA30HOK7Xu17jZeb8YZ8ZiyuahaqV4WBYnRATg4UlfTNHFoyVFpd9Z5/ctV3SYam+nbKTlGnFRNGix46/3nbfe0wzAO0joYwRscj82CaQu5VpwcH1R+vN3qapT736flKsJNNOwjHpWDYsWG4vFhlZ03rrgZz2wVj87SFqghPfDOBsGm/fnP7bBeBxYkV1tjur9pzFma19/DIR7K5WSUvUvdc16jaN0byt+Xewu5O39TIz45BiyEZH0pnUQ3L7HLVSVTdfMlJOVGmWOlfzxQkyHWihmw+sZUb+faeiU/F1ULkkrH/uBnwI00fXVZLPa+T4LAPqMzvBSiqNeVMM9KPTngGawr/RCQcwOo1ZFdxqhv2xoDlqsDvxqr24pZ9xVvMEBO2dKCIMDh9fCU0mmx0HIV4SbsHIDNQofjsWRRCQpXLyd3lnYFVuWK0ZLT7mkgO0t/fXpn+hXqsfnkMPf1PrJc5Sr0LA18EQss6AVkXVQ7obqM0bAG+37QL7v2XWN1SxjaBu5iWV1lGEndBqx4xdjz7G38/Rowux2Qd9vsloi7el0eSd47ICXHbKTBUChUH7y58JTWr7CoaCloLLmfeNATDHD7F/rrs5vpM17fW1fsLTms297VYFE28nOBf98FTm9hOKE3WnLk1RqoN/Os/XtqA3e3V4EARQ44X1iquUcZHdskS44z2VtXxUzZRuoSBDErOgAsiAN2fg2s/x//eXTj5vth+1zg6gng2kn31uOMDs8DFe4iJYdwE/LBkGfwNkrbp8SjFABKl+Nx0cCtFtun90dALUWwOWUYfV54HY+NolyjVp01qzxC5eqoxNhxs0/Ojq+ALdOBRX0N1KOs1gcGfSZU7o37DPpcmUXLx9x7flf95ksftVVInO0mU2PxIODT+kDOzeL3rp5wSfOY4LkWubeAHV+7vg2ecHhu/JB4NLJcxRT81By4lJypU6eiffv2KFu2LCpXrowBAwbg6NGjNmWys7MxZswYVKhQAeHh4Rg0aBDS09NtyqSmpqJv374ICwtD5cqVMXHiROTn21oDNmzYgDZt2iA4OBj16tXDokWL7NoTHx+POnXqICQkBB07dsSOHTt4vo53IFdyPLlkVb2teKzShF/2atHM4/ZV8aiWFb2TSnyKvp/y1yVHulZq10mrM2g5VH99LJYctXqH/SQmLbURNbA0wNLZKmeD6QeLfye99ap938JCYP/PwPUzjOdgrUrH4Jpzo3im7whNp3SLwkHcB5Q6IwNRZC3FG25UvJU5pPT8vifXAneuAafW88u6Ap4dcP+8Dax8xX1tcStFv40RS44nkhnrhEvJ2bhxI8aMGYNt27ZhzZo1yMvLQ69evXDr1i1rmfHjx+Ovv/7CTz/9hI0bN+LChQsYOHCg9fOCggL07dsXubm5SEhIwDfffINFixZh8uTJ1jIpKSno27cvunfvjuTkZIwbNw4jR47E6tXF6QN++OEHTJgwAe+88w52796Nli1bIi4uDpcuXTJyPTyPfMZfmO+52bO0tn3iX37Zq8fFo5SBmtWBM7SceNTbUUtWkzvX1D5Ul6l7L8OJNa45k0+OSr3hlcWIySx1uIPb14Av7gY+b2PsPGrfN3kJ8MszwMwWxs7tCBYl7PY1YGoN8Xs6P6H2R15rzTGQE01LdpDC0uD2tA7yuuQKA2cdLH3iznnAho/4zqukIA84uU5eMXsb9OxSdQdSH8uD9NsYUnK8dw8Tl5KzatUqPPXUU2jatClatmyJRYsWITU1FUlJSQCAzMxMzJ8/H9OnT8d9992Htm3bYuHChUhISMC2bdsAAP/88w8OHTqExYsXo1WrVujTpw/ef/99xMfHIzc3FwAwd+5cxMTEYNq0aWjcuDHGjh2LwYMH47PPPrO2Zfr06Xj22WcxYsQINGnSBHPnzkVYWBgWLFhg33BvRqnkSDjrbB6aZaxeO98NDsdjidqd+WUAoDBPn//RgV/E4+5v7T/TaoORbZF6LTkAENNNIWrAJ4dXQVLzS9GFSr2nNzOKulmpk2b3V446Lgc4vj9tOnYf2PWjHIh4FJWIamzlWOD+fd18P6z4L7BhqrFzrP8f8N3Dxf97Q9gH3jboUTak9DxH/+aXNVKvhzDkk5OZmQkAKF9ejGablJSEvLw89OzZ01qmUaNGqFWrFhITxcyqiYmJaN68OapUqWItExcXh6ysLBw8eNBaRn4OqYx0jtzcXCQlJdmU8fPzQ8+ePa1l1MjJyUFWVpbNn+nIzeU8WaGNOokZMS+2eVI83tVd/fOxServZ8gG36zz/PXeUNs5I6HRYTvNz+RA1s6So7arS+MRYrECaclWbeVc1ghag1vZqi6sl0VWox0uV5AcKTkyJdgdVoyzO1WsegwwR2nmOSdLd+8mxdsXgh/uUk6QtXJvMWCWP5seZaNakcXXSOJnpnvLHHS3rLCwEOPGjUPnzp3RrFkzAEBaWhqCgoIQFRVlU7ZKlSpIS0uzlpErONLn0meOymRlZeHOnTu4cuUKCgoKVMtI51Bj6tSpiIyMtP7VrKmRDNOTyHMc8Swd1Yo1WK9WsDqOlBBKf4i7XwTeuAhUrKcuF1m9+DWT8sGBstlNBojHtH0MwooOaWCRWV8tTo5dvRqPkN2SHMeMW57CQ0tWCVenqlFvu6cVb7h5547NtfNkID4ZLJa+C3s0tqY74coJYH5PYGZLflktmJZ6XRwYUw3uwIk+oOQoMdRmH1JyjCr3XV8RfQC9FN1KzpgxY3DgwAEsW7bMle1xK5MmTUJmZqb17+xZV5n1XYSzJJZyAsOKXui8QY2YFyUrUmGe7fs1OwJBYfblJcpUKn59082+U7FjxWOrYbbvs3TO5eqIRzt/DY7oskZyVykVWE/NCstUZKjXhTN9Rw7BulHLRu/gfHKLolq5S4eBr+4Fpjfib0o6Y/JdHtzuHKrxuymtiyXRkqOE6ysq7h0zvq/RVDR6adDbszuDOdGl5IwdOxbLly/H+vXrUaNGcSyU6Oho5ObmIiMjw6Z8eno6oqOjrWWUu62k/52ViYiIQGhoKCpWrAh/f3/VMtI51AgODkZERITNn1dRVrvtdlhvZkFlMGKxxhhQciTfoYxUPjm5ZeSWUskxulSgkJcsZMqdX0wWhqJry7TkpOULxLCFXHNJwpXbz1UwkgLDlTvC3GLiZqg3XOM5U2vP2e2M1RpRCDnwD2I4r8Y10AraaSOqITtovnNZRxTkGpM3BSOWTBcpOTwKf5VmrrXWseLleb24ehlBEDB27Fj89ttvWLduHWJibPfGt23bFoGBgVi7dq31vaNHjyI1NRWxseLsNDY2Fvv377fZBbVmzRpERESgSZMm1jLyc0hlpHMEBQWhbdu2NmUKCwuxdu1aaxmfZPN09rLyDpnHl0dCayBluWF3zhOP+39SNsqxnPzceuJd9Jis/Zmy3dL1CXRgWdJE2lKpw5IjLX/cVCzH8QyCTFYgI7grKzeHbEG++615WlRqoPGBiztrV1uk2gwXz6kWskGO2v3Sb7aKI71a+zR+Nzsrn+Mm2CF36HU17rJ0GlFU7lx3XTtYuXXZHAfg3FvqsdK8BC4lZ8yYMVi8eDGWLl2KsmXLIi0tDWlpabhz5w4AIDIyEs888wwmTJiA9evXIykpCSNGjEBsbCw6dRIDwfXq1QtNmjTBE088gb1792L16tV46623MGbMGAQHi4PKqFGjcOrUKbz66qs4cuQI5syZgx9//BHjx4+3tmXChAn4+uuv8c033+Dw4cMYPXo0bt26hREjRrjq2niewBAw9x7yUOCbPuGvy5Xat55OZs9ifplKRUsGNTqofKj8PkX/2w0IDG3NKXJIV1pjWFIzSDPejNMMslpWIDdHHtW05Ci6A3dGxF3Qyza1gdcGHvTALJX1u/cr2lFpo6yoyaq81+YJ0bqpN1+XF++ecRtG7smkRS5rBjPVWpvjABxWAajS1PP1MsJ1537xhRgi/95777V5f+HChXjqqacAAJ999hn8/PwwaNAg5OTkIC4uDnPmzLGW9ff3x/LlyzF69GjExsaiTJkyGD58ON577z1rmZiYGKxYsQLjx4/HzJkzUaNGDcybNw9xcXHWMkOGDMHly5cxefJkpKWloVWrVli1apWdM7JPkZ0p+8dJ51qmcvFrh7uONFA+wDyOx65AT/RjZToJm88U7b56AqjWSl/ofqUVplhYu00SYeJOQzTuJ25rdSTL6iDqKQXgyArFG+4MFqexA88watdUQwG2K8bpzyPHk0lUA8M0YkUxtCUw1PEuGi1ZJv80k3DX88GlMLjrenD0xwW5wOXDjsu4+lr5B4sKjtfGm+JUcgSGCxQSEoL4+HjEx8drlqlduzZWrlzp8Dz33nsv9uzZ47DM2LFjMXbsWKdt8hnO7QSilFFJNQiQ7QqRUjTwcM9rYmA3s2jYh19GGvzVBkitDonFN0aJlpmaZclJamMYgxOv2kDW4Tng0B9Om2gMjY5TGQPHnZYct2HEF8iIgm/AJ4fXqupsucrRNQgsI1tKYbQCAaJ10eJfPMHQ+n2TvjEh2bC7lBzZ7+K1lkYZIVHOyzj6HhXqFwd6ZeWRheJ10msh9ADeu7mdcE7lopQMejzq5b4q8hufpcNtP5K/PomYe8Sjnoci61zxa2X+Knl+G6A4UKFyy63aQ658q9kgjQYwdHTSb+GnXPpRUZzU2hL3IZB+gL9eHtR+44dmqljX3Ly7yixuy3zYIlycRNZVOLTGOHl2HMkG6AiO2bbIBcBGuVKpI/c28NdLwIoJ/HUYwW0KiBc41HI5HrOk6HFwrRrpyHsn9WvXTvHLeghScryBkEjxWJUznoY1YaWOmZNNYtBCcA1Kkk9MXY1ggCz1OpsRqiEvq5TLv2P7f0RRYLugMsqTOK9HPhDIHep4dmbZwfg9/QOB7m8oRD3geNz2KaDjc66r17SIuAyDQppsa3cfeSoAA0qdoRQJKuUcOb3qcqYvwtnkQu17PDSDTVYZUsJlOLs3DN47m6cDf4yxP83pTcWvTdtBxFjvyHXOywD2v2/zR4pf3zuJ7RxypMnmuZ38sh6ClBxvoNMY8ShFnmRFshZIKRJ4BhYjiUEdJcp0KhtgXBYoHgQKC8VEjVooOye1a5STaf+ehBQzRxPF+XI12qL622j8XheVAQw9ZBW5wmmqdoiPxFEJd+LDZySZqSEcnO+cLPklz30F2CeO5UGu5HjT8o3Rtqx9V9wIoewHUjapl/corN+NsVyuwuItT/XhzEKoWq33xseRICXHGygo6niSFvL1lRaFVYQHucWhsIDP8Vgqq/ThYBkQrNYnHW1WKjm3rgLTGoqJGt2Fs3V5O4uS1iDC8cM26ee4Dh54LAzKUASetORs/1J/XbYVOy/SUGaWr95WJurq7+vC3FCNZfeEs+fd0dewyVavZkFiXSbzIiXHE23Rui75ucCdDPfX7wzWe1fZZxtRegEgqrYxeQ9ASo43cETFCZulf3SVVYRXPlU7P5jzeg0oZjZKTgGQtEAlqKAzeC0M8vIMs2atnSs8lop9PzquwynObh7GBI4su8lcxfr/uee8gL1SN1CmUPn5F/tvuXM3mSNUlU7F+Q7/6Zm2OLpPlTsVvQUzrUqftwH+rzZw28FuNyOwfjfW51KePxAwHt+mRjvxKPlaeiGk5HgDTndLaOBnxCoi98mRyTNZY5S3jY5lMj1tlitjmee1l1daPKZ9DmedRqcXbP/v9b5jWeV79Xral2GpFyheE49uxi9rK+D4Y80s1dVt/+exApWv61zWIzBYJ6Ssy0oZI9YYQz45jOfziKwDJUce4sKTGbqd1uXiJR01tH7LzCKlQbkMZASbnZmsSg7jvbZa4XejzFcnJelV7g51hrNlXxMhJccb0OtI6MrlKi5FxUBgMCPLVeVlEbZDywH7flAvV6mhg5MovqfS/0WpwFVrrS0L2HfAckfnpvIorwyy0m45eY4vLVl3YGfJUUFrxlj+LsUbRtrsYidPZ8+H1broYr8gZqsXR+RhpnIGZB1dg0x5GheG+9lVuMrp15v8iLRo/YS+YKB6g/EpE9TWv1883uaMor9faX32HkjJ8QbsdgAxcmaLeMy6wC/r5wdr56rX8VgPRpar5IkreeTl8SOkjk4QgM3T7KNFO+oI1TKn33Bw7cMqODmv4j0pv4/S0uApXxGm5SoN2eaDGeplhUGW5/zOFGppUFHLr2TI8diArKPvN3iBrAqVZ5H12qgtrbI+V+6yFqni5DqytsUXkoS2eNQ27AXrd9MbjE/Zl+/+Vt95vBhScrwBoyGxd3+nU7DoASrI43M8NpQJ2YAfkcUik+dQcnq8Lfun6Hse/A1Y+56Kr4ODTkUtCKGjHDXd35SdlqGDlb6T0x1dBtEauEPL2f7PoyDZ3RNeNGt2NnBLs9kCtS3QbliuClRMaliWQeXI/R9UJxyM115tV6IhRYBV2fDgTjRd5dREPXQ/h1VQPEturld5j2rGCPNdSMnxBjrI45Nw3NSSZ3urx23f5zXv8kbY1TPTkNCaNbO2WVJyHA1cShNsq/8Uv5bam6bcpi197sLZXlh5WeZnhuskRWdW+re4vKMzkKBTawmGJRVFQR7w7xTg1AYn7XMxF/c6/ly6p4xYctTuG61rVV/pt8W55CS/tspgl8rPlcjjqajtCmKdPBSo7Mph7gs472dnv4FWvXFTnZfztiWsslVtlRzeNtssr+tAUnKiW/DJjTawGcXNkJLjDQTJfHJ4tvTV7CgejSbPy5CttbN06lLwQkDRKbJYgYrMqvkqAwoLznx6qjQD2g7XlpcCwW35TP3zSAfb0SsqfH1UZ/4KJIdEls40OEL9fU86eTqrV+v+OLLceb1Ji8Tr/m1/JxW72CfHWbJEaRkydZuBtnBYvbooIgKzDGTyQUSu4NulLQFwUhEYrk7X4tcV6xe/VutrWO81lnvfY2i0uYMiuKUhPyIPKEN9PhEnRn5OLDmOFNFHvnFcR6MHHX8ujSW8LgkO/SDNhZQcb0AeZMva8TB0rgd/E4//TjFW/5Hl4HqI5VEyeX1rrEsDOuMzyJ1EK9Sz/azNk8DorfY+LXIlMDRK+9zBkUCH5x1UrrhGZ7fb/t9SYVGTY5eqQQXN7Zwu3kJuxM9Eyzph3YYtiarIekPodzUfFikkwoGfVcobWa7SKMvkP6F0Sm9c/Fq+k0VNMT72t+3/T8ostXL/P/k5rdU6eJ5tUsEwpilRg1tp12nJUSqAqm1mtNx6wuJzV1EEeWfuAI5+I7tNCwouOUngKfWvF/Y4Lqcl54WQkuMNyJdXHEXfVSKFUTcaTv2e1/jKyztK3l1SUqj0rTP55CSkQbYw397qcnqLuoy8s3MUmv6VY45z+/zybPHrszvt4wXZbU2Wodb5KGfDlRupy7o8RYKRzNoqso99D0Q352yDw4o5i3OU51XKNZeceinKsWQ/L0JpeWWx5MjPL3+9bY69rDKPm3wAkr+W71a01utg0O88rvi16nNvllWEVbkyIOsJS450rzlbrnLU5zoLR2ITDFIF+RJm7i3HZQfMdfy5l0BKjjdgVl6UmG7iMagMn+OxMpAgzyAjzxsEgLvzkMfZUfojOLIUBBctsWk5PDcb7DysubSF9tJhYH5PYN0Htp+rDRBS7Bk15episuP6ik/svIjWYMzy23R9hb1etXoaPWD//dzu/+AhXwqtZ1PzmjHA4vukFVRSido9fz3FsYzDOFIOlJyu/y1+rfYcucuSo9cnx76gylsmWXLUzidNhGwsxJxt1rpWJ9YCs9vLyvkBE1XuHfkSprPv7Exh8hJIyfFl2jwpHu1ilDBi9Y/hXDrSCiToCVgcj9WQLGQn1qp/zrMFU8uUq9b5ZJ0Xj452YanR+gnZeVmUHHnn5mRQUDrYKhOCOqpXc8eQcgbJ6UzrrF69FOjYxWcDozWGBxaF8OcR+s/vDOk3ZLESVGxQ/Nrf2bKvF+2ueqHIv0qedkBV8WbdaOBqJUel3hCVpUfVNit+owZ9nNe3eCBw5Vjx/4PmA2Uq2Jfj6duvnrD9X9rgIQUU9BJIyfFlqrYSj2pr6yxIs0D5zI/FqGQXSNCDGAkmCACJs8WjPGcRwKbkSL5Iyt1bEo46zJWKmb9dEk4FNoMoSwfLYQ1UBu7SXE/n8MlRKjmGLDkGBhSlEqZU6Gp2speRLBtqW/e1lDo7pZXx+o87oGLV0/F9axTNyuXKMCuOwjgo7+FhP9n+L+0WrKKIyg24Tnm5dARYNkz2hg5Lt1w5s+JNlhwDypWdIlrf9n/JN9BRqgWtTQ7yWGTOJgjKa9KgaAn3xkXHch6GlBxfRnpQ7Ha2MCKZGzd9Aq6O1iaQIKeycVcPvvJ2dcuDCSra/NoZ9vMot0g6ijXU/FHxWLVlURs0ZvHVWmmfQ76skJ8DbPvCcfskJ0TAeQeb9A2w82uNDzk7Z5vYPgyy0uyNaeB200xfXl4pm3fb9v9HVXaf1C7q2KWI0zaoDLBBZdX9WViIqslmyXGGNMFRJlVlwer8r7LDUTl7D4+2/V9S9Hmzn/OU+7YfX5+m1hapn8iQ9QlGnKVdvUvRUb/pyG9Q7XwZin5Pup8dnUdtVx4AlJNZvpRKcKpio0WX8bb/79WIQG8ypOT4MjyB7JjhjFfDG9Sv5VDxKN/WyoOUKybzvP1njnZOSVg7F8W1cuS8rQxAuGexfZne/8c2q869BfxfDLB3qe378h1rgG3WaWf89RJ7WWdbf3n9w2oVhTFgseQw46JZ8w//AT6RLeU+vRooG21fzmodVLmX1SxXI/+1D5zIgyssOZJSq9xJxVR/kdVSTcnZOd/2f+VOn6SF4lGyiMpxlU/OzXS28/BiZLnK1RGeHdXbbLD2ZwCQcdr2f7vYONJypIM61OIrSUhKsPJ5WKBwtlfG81Jb/vICSMnxVlgGG1eaUHlPpZaegaXN/gqFQS8/yhSKHu8Ar6dql5XjKIaOFn6KQfDEGtvPa3cBOo1yvI1SshylJgJ5KrsWHO2mYdl+zspVhbOgNVhhEc5ydSmRlCamgdvIri4ZqduBte87LgMAh/+y/b+WylIV4DiKtto9XbmRfb45tXJa38PPz3bJ09MB6aTve/OS/WdKC4rWPZ2TpfKmSTuVHF0/m2VpIz45RuCsN1llEiXn6/ts/2/9pO3/WkqKTRkHSg7rBFa5bO8ohIaJkJLjyxhJrwAATfrrl9VryZE6pNQE/XUrz1W2qm2AQjWaDhSPoeVtZVlwlsBRyiGmhmSRaVG05HVG63s7aI9qkDpHaJxr3f/sl7WUs0D5ciJLwDfp+ygHeUNZuZ38Ngt6KZJFMtQR5mCWqVRibU+oLsPiw2WWU6szpPhayUv4ZaNqiUc1/yWtiYvc+RfQoVg4uz4OPrcJ66CmiHrgNzISn4cFZegKR7nYJBw5zrP27cpzaPkqmgwpOd7CA5/yyxi9qYwMRFYTP+fDmn6Qr7wWPd7hK2+3K0vx3Z9e7VxWj/VJspRIspun8Z/DUWflDOk3zjwPbPoY2DlP8bni95P//mrLckp4nJZZMRIXSJJV3peOzPOOlFit58FiYfCdUNwvZWUJUOW/qfz75mUDWQrHzcELHddjUyfDtZOWfPUgzdbVfOu0Bu7nNynK8fpcOeljHJ3PVSlEeG9JuYWUZYeUEZTKhqSAn9mqLSPfaWV3PkdKv0o5Cfk97SzGjgchJcdbaOkgdoUWRi05Njcp51MsbcnWmlFr1il7IPWY6Z3tcNKs18GDG3OP9lIG4Nhng7VeI52a2k4Wh6gMzHl31Is6Utw0IzDL0FIeDBknXGDZOL3Z9n9Hz4rD39eB0u8vt+YwWAlUl3gAm+/7vyrAdFlQyJf3As0G2os8/JV4VEb9dne6hRsXxOOu+fafad3jymvP6/flLHUM87PFsWxkl/6A8550lmTTUd/HmzfKTzGMZ11wLhNURvszVkuO8neUKzZ5jHGePAApOd6CMjMxC9EtNT5gtcao/fycHdCeJeDbmSVXcnSYbCXlRh4sjaXTVCo5Uidz39vAcKUDt1JWYQWqdz9bW+WyzrZjygOtKWGxqDgjTSNJZYyKA7gUlKyqSme7d5nt/10n2JcB4FafHLvysvtIuhe+VThuOzqnQ58cP+3/nUUnV97f4ZU1yjloW0iU+vuS47PcYvD3a7aO1hUbAE/8bi+rto2eld3fan+m9j3G7XdsRWPBWT/BOvlQc2jWOnefjxXleJUcmQKsVsdRhcN4n0+KX/eP56tLiXxHoZalXXWLfRHS76W8rk1VlG0b5BZVT/g6sUFKjreg1MbVdg8pafGI8zKOOORkcGfBWZRgJfKtizYPEeMAKPkRrHsfupQr60NfJMukIMlSSQBABY7giyyzojfTgCpNtT8/v4u9PgDIuSH7p+h7/vy0fble/1OP3CvtQFKz/ty+avu/1rXw5O4qlkEu65z2Zzz+ZTydN/PyZtH3VbtmWhZLeeRvie1zba1FoxNtQxFIdH5ZPEr+Na5C7dpE1TKeQNiIklNVNhFUSwqsde4yFW2vPY/16aFZtulh1G7nP16w/V++M9QuRQonLBHpHSXU1HoenN77smvk6SCxDiAlx1thyUcl3Yx6fXOM5KCSqN2Fr7zyAfQURpaclP5HXE7Lig5D2kIvx1m+GTXysoHtX6mH9V/0gHP56ObA3WPVlVQp9ca/an5PBnbQaA0UvT9SiHIqOWrKmLNsy3IcLSnavefAR8dOVunvpOG/JH3f4//YfxYUZv8eYH9f2fm6WbT9paTnXo/12BFafYhyAqf1+x5bDexXSZL6+2jOemW/RdzU4teqcYG0dsAFKpYjOWj8kEKW4X6W7wJzplA5C78ht5zpUTaUCvTta8COr22D/N39or2cvC/xZN/uBFJyvBUp2JcjjEb/lUczlbKCs85YpLxXNmvPLFYRWfnCAoPxJwwoG1ZRjlxdWg/usF+0Zf0Vso52+fCw+VPg74nArDb65AMYFKvrp4tfZ2cC2Vo+JUXIY8fw/DbyrNqiMLssAMxqZf9ezQ7s8mpWEQnle8ps645QKjn9PndcXplgVsq3poZSMTufZPu5f5D2s8zqJ3bvJPv3HG0TNrJEIQjA0keBX56x/8yZ473yuXxKtg1enhhXVYnVaLOfH5Art4hyWHKCy/L7HvJYh535Xcmtd2qWnOGK0ApKlP3dL8+IEdulnFoPfwX0+sBertbdtvV6CaTkeBNyMyVLhyH3FdEVNVVmynWU3FINvXmv5Jm2jT4I1tD6HD45RmY2Wjuz6jmI4mxkZ5YjrAOik99dui+UYdzP7WCvKz8X+KgW8JETR2QpMrRmuwxk5c69BXw30H53GCAqYEqUkXodIU0W1Bw2lfcoi4VVQmldqS0Lmf/gZ7L6i7phpVLiyOdHORAp8wg5su6qTY5ybgKXjxXH/xmdCNz7ur2slC8vUmWpy9GzVamR9meAscmO0gIm/+0rOfA9AdT72TEcz4Ya/oHA5cOO63CGlPFdbRebNCFt+1Rxji455WTRuJX376spxRNULaTnQOpfT66z/Vzrd/bzkyVCpuUqQo0RMmc0u9mtCnIrip5dFWodIauToHSj8yaerCN7wAw7p+mIdWO9Thw+OZeKOixpgJU65OrtRMdKR+fQG0/I1bT+D3vZakXWISny6m3G1AHNZZFaeX7b7AzFGyq/646vgZNrgRUOHLT1It0Td67Zd87K/+VWBbtIswq2TNf+rF7P4tfSc5xz0/H55Cjvq2sptp/bWCGUsioK/5xOQHz7YqdVrejhUr0sy3NylMETeWSd8c9btv8rU3lIqC3zaPkRscAc4VnHdzu3UzyelCUUPrUBmHc/cCFZ/L9Jf/W8hfJlSj3KhhSs9O/X1D9XOk2r1W12fyeDlBxvIrisOIMatQUIDndeXq6k8MwwJdQ6KtZt6ZJ2/8+bjssp8fMrnrkafRB4Og8ppolkebJ2UAxKjlb6jHo9nHeIdstkio6xn0p4fCY4d8E5C5Yop+694lEy9acxRlyWLxEd/J1N5sHP7HfsqI0dOQ4GbVU4FGC5oq60TCpnrffJBlSb347z95DfN9IOqQZx7PLWwaToGVAmnOWRBdhj5ziKKeToebyw2/F5XbkbRznwS1ZnZVgBsWL7t9R85NR+XrU2P7vO/j21Opz5UarFuPm2f5EFtuh8Wj5DFovCB1GnlUzrnmjlYMnSWyZ1MkjJ8TaqNGH3rpc/KLzLRloY3QnBU4dhJYejrNQh5HLMlp2iY+u6stFtdGSR5kJHB6f8fZbq2MUXXsn+PTWlut3TbH4uvLFVlDy2VPszucOkcuBS+oPILTBh5Ytfa2Vnd4QUCVhy6NRyTFZD6Uhfs6N+WTW0tq47mqnzBgaV40olRzlRK3DQNzqqV77EpvYYqVlJImqoFFS5d43uoAIcK0rW0BVuiJukdW/I6yUlh3AJcrPkwV9dc05WJUDuQMu7nm5kp5MNHEtOktl37/f8snbVcnxf6btePmL7fv04YBJDmADN8xoc9Fs5WL6SBgln1sEHZ9i/Jzk08+z4azFE8YaL0xxUqA806qv9uXzmrrwn/1TZRSIRIYtgrCeppJQ9eoO0A0iHI711ZxnPPVnU7UuB/dQGa60df458zIykSDBry7GjZ1n5zNrJqnzfskVuBvWdWOXUtrPLue8tx58Drsk/pQcW5YqUHMIlyAc6ZeJFvbCu4bYZrr8OI864Pd8tfs0jn5rIX5cVpULBoSBJS13SzgSpU63SlG1J0lUoO/O+DtJLKGfrajvCxh8C2o2wfz+/aNBdM5m9bXaOxy6Y1Uvf964ewItO4gwFOLDksCLfbp93B7h5Wd95WJGus+SczKN4Kx2iVyuWnANCHezMcjCIKX23tKwVqlu53Rg8zpGVi7Ve1eUqB/2P9LyLBW0/y7lRbF1q/gjw7Hp7+bJVnbfJUf40eSJkVyeAtfOhk+Fop6JJkJJTUji2St/NLN/2B7A73ak5HLNaFySnSD3avrS7A9B2MGSBxyen3yz9spKToBKjlhheHxCrmD8wZInjII6S87kUpbnpw/ZlIqvrq18Npb+N6n2s9/syyMnD6Luic47vCHxaz3k5KZdVwyIrk/J7jz+kLXtJvntHgN1AqozYK0e5vV4ZKFFSoNRwFLbie0VqmuGyrdzyXHNqS+vuVHIkH5KGKvGjWPtMtaU4R22WKwLy6OybPgWm1ijOHdXhOaC6ShiIK8edt0mPRYWn32n8kPr7jhzuyZJDuA3eXU4StRVKDmu8BpvZt86ZwqE/+GXkfhCSuZ9lALxHuVOAwxpTvuiaKEOhM8nGKN5w8azKGdZOvOjYbgTQ2EmgPGtHVbRcFVpeu6wrcBR9VYJbKeS4ziGy7fXyzlnPpKEgX3ZfyqjR3v49abno6Arb96u1BqZkOlYk5QONtBNHTofntGWlZQ7JgqUWoFILnlAM8uV0KcoyYHCpS8bFvfZWKDV/EWlp6OhK+89YlxnVImbrUYjXvW/7P8uyrmbAQgc+XDbKBud93P5Z8ai17V8ZjkKzXu+AlJySgl4lJ3aMPjn5oKN3FrZ1lvMyLAQwdBSOEnA6Q3pwrZl7OTqNHoplGx4rkFtgqNfqk+PijkpLUXGULLBYmK0OuwGBUU4abOSDtx6nzaSF9u/1nQYMXWb/vh0c95XcH+j21eLvXbGhqCA5UgqV+d94YgrxbBEOLmsvB6grSHqclr/sBiTKdrjd/SIwVkXhO/ib9jm+USj8fR1s+1fiqN+r34vtHFpLTvKkrJrXWk/oCo7nXysIo7+DzSlSfCBXuU+4AFJySiI8s94wnbP0AzJHZ71KjqNYHjywhF+Xm8hzb/MpG/Lrefsan6wU70iZLdrocpXh5S4HWGMKaewIc4RkMWs/kl1G+V0MLV04yAPlCKlDl3JzXT6qnmbBGft+sH+v/UgxFxIzDL+t3GIRVhFclkm59eBCMrh+X1cEt4xQsVAx+8Y4+H6tn1RPgsrj1FyudvFrtai+Nud1cN0GfGH/nto1C9BYNi4vs6hrKduOfHKM+MZIW+23zhSPetIGLR/HL+MmSMkhis2T4xjjoQC2ToZ6t45KUT2NwrJ9V67k5N0GnwlX1rHeuV4sy6Jn2PkweHi5Ss+gL/nkZKaqfz7RQXRsqz+PWsfMqpip5b1i7KqMOlmu+594jO8A/DDM9jOWVBiOEq0quUcRUZhr157sWgaG8Cne8kHr+mnOe0O2lOlsh5AWR5bbv8eq5Dhqq9agz5NKRR5hWM2Hx6YtDhQINaVWre3OdrEB2pacsg4scBlFz+6da/zPhJS7TkJ69srVAV45YVfc2yElhwD6fiqauKOchO2XM1AWXt9Zbhktts4ofm3EMrHza+dl5BFX5Q89S73yAdamw+CIk3M9RbSMmL1cxfJ9U4tCxSs7OwB4+EugjINBQ5mrSw9qnTJzHBqFDxLvfSVPQiin2SDguQ3O5XmWuKKbiccakiOwzjZnZ/HJ2sXX0qkYHnGSA4kHXutdpoqPjJaS05UjSrb8+sn9E2t0sC+rbPPgBU5OrnKdtSw58u3hRp6lJYNt/zcSMmP4cvX4V14OKTm+jrOMtO5CHsL/KsNOAE1cYNloq7KVWYky4JteZcNi4Zxxyx6x87KtzN68XHVmi/r7HZ4HWj6m/pmEliVHEIAEhQ/Wf49qnERNydHrk8OJIKhv/x68wDbvmkSXCeJRCuzHlRhUKx4R52/7z5uclhzFAKq8Zpq/C2wnNHcyxOO5JGDjx7aWrqCysKNxP/GolnyYdUlJug/UdmhpLatIVhV5+y7uA+YzRJiWdnOq5UdTTgKUDvplipbOGvTWPr+WP5q831D7jdqpJDJ1F5IypyfgpRfgm60minF1DARW1AYdT0RLBmxj5QBAIydmZcC2AzSaLZln1my3A4Lj95InULWDd9DnqFcZV4TnHtNyWrx5yb6slrld1ZKjd6mLU2EozAe+uNt5OQlpeUry5WDxD5NQWr30PssX9hS/ZrJMyspUbADrNStfF3gnw/EyiDx+i/R63n3A+v8Vbz3v9iowWiUtQY124lFNYeBdrlKzgGgFx/NTcaT/sitwVpHcUi3itJRy5IqK4qe0kiivW7eJRW0tuifUfl+tNlssthMGuWyjB4E+/6cup4rRMYKjv6tSFBvJSBw1F0NKjq/jKKaFp3HkCOdKmvTjl5HPmApyYSzisfSCQfZMguwfi8ZrDfTM1rq9avu/3eDBUK+WCZ1pKURjZ5azmfrDX8nKqgx4vD45ehWGm+m2u4KcId3zedmOy6mhjEckoctKx/l9JUf4wjxbK5CzuuVKe2g59evcabStA6/E/p/E4/UU+8+4oyWr+bdoJAGVR/AWBPU2d38LGH/Q/n2e9AvKnFmS9dhqdeL8jbR2SPX7nD3HoF2sG4Z7S2mR4rHkSBnO9W5ocQOk5Pg655PMbkExrLPYevcbq6d8XX6ZKs2KXxfk8g2CcgVJPlizDEah5WT/aHSwWsiDhF1XxF7Rqlt5baT28tSrR4mU0FyucjKI3dVdXlilgE5LDq/CcOe6fewoR1gTv2ooOUNVdltJKOMRGZlx8y6/Xi1yID2yAtwKf8WiuEaF+cAllYCFWs608gCGSrTuD7nvn6NygHbcGBsn3gL17c0NewMRKlGGO47Srs8Z0vJYVlE8JOUzOHItHGIzYeC8N6S0LdXa8Cv8D80Qj9K9LcmzKDlSJOdTG/jqdCOk5Pg6UsZowODWWxfAmvdKHuNDb5slXyS1rZpqWCzFa+Q26/kMHbvcF6OwAHyB5qKKX/NakORLbNcc7GiSGLffPmaQcucbS73KoIc831fqmKVAdxLOHHLlW3/VBkOtdndXBIOz3k86FYYebwO1YtnLS5YcNR+Rlo87zizur7UTzYAlh1c0cTa/giS3MKg9vyzbopVo7dCUx4sBiuvTsyMMENusdi9p7Zw7+jd7PUqkiOxp++w/m3iqePlOC2uSTc5JGVD8UyqDHbI8/9JuNGv0e477Y2eRUipfQjUZUnJ8nUcWFb++5eZ8Oc4IiWQrJ1+T15oBO+Op5cBbl4tDtrNgMyBxzl4l/4NCzh1S8t0INo6RLP48jqJKq8hH1bIfYPQkPpS3U9qKqlWnEsn3Ru6UuXk6kPA5e/2bPmUva6eQ6HTIblW0Xdzix7fsKg2O1vu46Heq1xN4+AvH95f0+0oRko341/EsoWoJsz4Ll4qWddZMVvdj0TpP3IcOmqCh5CitM3omRTZKTp66s6/Wb6623Z0Vuw0Zst+XJYCpjZWQc0fonsXicftc52WV2Cix8np9U13wzVYTxcgfYFZLiqu4W5GhWS0HixpyZUhtBswKS0dhU76oIyvQUadamHReq4h/kD4nXoBdTtlZ64nPI1dyTvzLLgfYZ27e/zOw9l1g13z2c9w9lr2snbO70ieHM+JxPuesWdOSw7nL6fppmagHFBUbUZ07DdUsFI6QHHOlAJk2bVBRXtR2jqo50rd/Fnjjgn1ZCfl1VjrxWsto9CUPOYjKXk6ZskX5eR3b/3nDT0jW0J3z+WVtK+YrrmWpc+eOTjdCSo6vwxKgzF10eF6fnNy64MkcJ/6yAYnbRK8zgqjciZV7Z5YDJUcpL23PDVJkNrez5HAOvryDvtL58xcN5+lYFUVGGjQuH7P/TK3d/WYDZ1R28ejBRgFWfN+XHQzmznxyHCH3YcvOtK/XGZWbiMe7X5K96WEFSc9SJmsW8if/1C5n3WUVKsb5cpQaRK4Ip+2DapuDw+3fA4B6Pezfu7gXWD7BcTZuQNwFJaFMospzrfd8p1/WDo4docoM5qTkEKbgKI+Iu+EJHiinvsxPQW/UVD1Ilh+5bwwr1sjFOgL6Sc7ANvFQODuMvFu2/+corHaSBcVOydHhwyCf1cqtXiydnNZgIWfAF8B9b9m/L+262bvU+TkAoM0TQMM+jsuwdsxWS06O7bUavEB9p5CEI58cZwRp7AZivTckfzy/AP1LXWEV9VtyAL7lI00fJKgvq/qpDE960hTI74HtX6pfKy0lyTrRkJ3jy26iZVKeL/DeN+xlHYat4LzWhiw5nEhKYdZ5xUYL31QXfLPVhPcRUYO9rHz3jlbqAHfgrzIgsQ6CeperANs4HVxWEZl/jdT2gjzRSfPcDtuyUvJQpdldOSjwWpB4k1S2fqL4tSCob+tt9bj2DhxeNJNLcg76AbLtvtKAdFcPMdIxk9wd7e3JWih92HgVFbljKu89Ke2+aTWUX1aOss1vX9Uu6yjlB7evjc42590B171htWoK2s7RfacB975m/75NQL8C/YqoctmO9zvz1pslW/qT95Usu2eDGf0yPQgpOSURNWdAd/HUSnEXyfObPFenXgLUlqsYkfydbJbXOBUkeefOIirffh4SIXbQ0xsD05S7nwC8VLSbQZkzR5ejpjyNBae8PD7G2e3O/RbkSJ15hfrOyzZ/RDwGauzk4cVq5eN0Spf7QMmXYZisXrKlzECZJYHX+lSQx2+NkVJz2ChmBiw5ZauJqWEcWZb95ZZUjfM4w+7acLY5P9v22R80XwyAqIXc8dkuMnURd92nIavMP8W59NOwr3hs1BfcSrsWTMEiZd9ZnqOQxSG/L8emAQ9BSk5JRNMM7gbqdBZ3kTjKZ+QtpGwUjxd288tmnReP6z7gV5CskW05t58DQKWi7esFeWLsiVuX1XfRSUtiyiBcRhODVriLT1ZuSTq1UbYNlQEp/H211s7LSgOIlk8at+OxpADngiv4mXw3m96dggCQfgDcv5F0rQvzwG3ZsEkcq9MqUr2tTJbhWtlYRRQWRlYlR7rGeq0iAcGwttk/WExP43AHnMKqmaXi4KxcIrbKKpQc3iUnydJnt4WcQVaKL1S2GrjvK7nStneZePQPYrs/pAzzUrBJL4CUnJKAPFosoC/6qtl4cr132xzo7tjP7+KXlQd943Z4lkVr/d5J3ig19DgeA0B0C/FoY6JmcVqWWzZygBiO3Gpa0ZKB4i2xyrJKvw1Dgx/ENvP8RvLZrZGdgn/qcR4uaueV4/pj3QgF/LL3FC3NVGstUwh5HdoVfdRFhXN3cIT6OaxKhs7n9+bl4u/L22YtR2OtuEByJUf5fVnqTj8gHnfOA7cVSJrs2GVgZ1mulj1T2VnikTUJs9y66CWQklMSaPGo7f/KJQtfgCfnjyswFJOEc1CQolJL2b0BjiUJaanLwS40rU4W0OeoCRQvpWiZ6LWQm/fVlgXH7HQuq6bkKHMHSYkxNeEcBKXlyIO/8Q3cFot2PBMeJJ8eHhLjxePpzbbtYcHmWnMGEvSTWSatjwKnr5eU4kFi+Tjb/4drZDg3uhQvxfgRT+a8vN2Skwpa6STkz8K5neC+N6Qt+hmp/JYceSoLI2xnDLZqrVcjFYWJkJJTElB2MI52g3gr8p0K7kJKGmfjTGpgpwLvLHLrDPDHrGDorO57W/szPWkdAJkfEaeztPya5Ktsx66k4k+krFPZQd6+Zl+2PIevDwubp8v+4ViCAYpn6RlnZW9y3hu8/jwAkHND9o9OH7MLyTJR1qWuoutiE0eFM4K32rKPnEjZRoZHvil+bZfM1M1b5uVlrp/WiLGj4Yckl42q5bpYNzwKpVZcIHfh5yBMgEmQklNSeL5oNjdkibntYOXBz2z/P7Xe/XXu/V48HviFX7ZGB/FY734YcgLkHVCkBKz5OcWOiHIGzAU6KuIVyZMKKs3GzBYkFeWKV6mr1al4EGzxmOiY6ghpyeLoyuL3NnwELB/vWK6fSjRl3o5dHreHZ+CWs3IiX3k7ONs8YI5MlHPQlyJQX9gNbquXdamrEFwKoXwZRCv4noTcGt10QPHr24rdW54Mfvhtf/66JLbOhKFYN7wKktaEwd2xbqTf1ezo+zK4lZxNmzbhoYceQrVq1WCxWPD777/bfC4IAiZPnoyqVasiNDQUPXv2xPHjtuGtr127hmHDhiEiIgJRUVF45plncPOmbdyPffv2oWvXrggJCUHNmjXx8ccf27Xlp59+QqNGjRASEoLmzZtj5cqVdmVKDVVbiINI4wedl/UG2j1t+3/vj9xfp3xJjGddHije6XRijcFZpCTKKCulR9g53zbnl0SrofYZiUeuK35t9WXRaUHSs7Yu3/LKk9xPaa0qLAQ2TAUO/e5YLkw2IEr5gniRZ8bmvTckMs86L6OFxZ//vrosX8JzxTZwHUtdPEt7cqRAhtvmAvEd2eX0pCmxP4l4cEXww7Iqz6Qa55WbHRjq1tqZyORLpBLywhPcuFj82pMx0BzAreTcunULLVu2RHx8vOrnH3/8MWbNmoW5c+di+/btKFOmDOLi4pCdXex4NWzYMBw8eBBr1qzB8uXLsWnTJjz33HPWz7OystCrVy/Url0bSUlJ+OSTTzBlyhR89VWxg21CQgKGDh2KZ555Bnv27MGAAQMwYMAAHDhwgPcrEd5AaJT76+gjV6Q4O/bjq+1l3R0hVk5qArusPN2FTe4pDs5uLzruYK9Xwsb5kONaNe5n+7/WEmaZSurvA8C6/zmvRw350o/egVvX7qqiOuSpLFjrlc/SeRWVAfKcRpz3s5SCYt8PfEosUDxZkOI6rXrNPhUIC4a2veuUlZa7JWrFiklxWdCTZLPnFPFYoz10T1KkXaGeQsrxB9gn6TUJbiWnT58++OCDD/Dwww/bfSYIAmbMmIG33noL/fv3R4sWLfDtt9/iwoULVovP4cOHsWrVKsybNw8dO3ZEly5d8Pnnn2PZsmW4cEG8KEuWLEFubi4WLFiApk2b4rHHHsNLL72E6dOL181nzpyJ3r17Y+LEiWjcuDHef/99tGnTBrNnz9Z5KQiPI4U9f8BDsRXkwdeuKJPncZArRR9m7CS7F0X3rd9L9qYLAq+xcHItvwwA3Cnyg0le7LicGtadSrl8A4pysPukrn2Z8CrAQMVuwpodil+nS4MO58At9yGQlCtnfiNq5+D9jSSLZkAouAcym2zxnN83XTYZ5B30pUzTAP/SnnRt/31H/XOLP/DQTPv3mw1mO78WTQaIR8mCpIfTm4uvlX8w8PQq9ojzNs8++GIwCYX8y1Vyy6SNNVan9VkKHukMuc/d3h/01eViXOqTk5KSgrS0NPTs2dP6XmRkJDp27IjExEQAQGJiIqKiotCuXXGa+Z49e8LPzw/bt2+3lunWrRuCgopnpHFxcTh69CiuX79uLSOvRyoj1aNGTk4OsrKybP4IE3lsiZhJvMOznqlP7hjKO1uv0b74dQpn4ENJ0Tj+j0EnQJls2WrAZBWHXE1RD5qs5TmKrNeZQc4v0HmZV47ZB19zxW5CeYbs9UXWIGlXHCuNHyp+zRvQT88umAay9Ci8Cpk8e7u0BKTM+K2J/LtxWnLkqFnqntsAtH3K/v3jaxRvcO4Ik1JglIvRvxx57VTxa17ZgGAdfjXyJWNOf57anYtfuyJx8x2OvkbCk/HaHOBSJSctLQ0AUKWKbZbZKlWqWD9LS0tD5cqVbT4PCAhA+fLlbcqonUNeh1YZ6XM1pk6disjISOtfzZo6cy8RroM3k7gRbPwuONf25X4f0rKEp7NFS9w7CfjvYY5BSQZrvVJ6hgr1+BWkQ3+Ix/0/gWsQlOehKiwAanL4aijhtU5EqvQFoeXt31OjaZFVW64Is2INEaDDCiTP5n1WSvPB+H3lQRolyyRrGIfeU4tf613aA4Csi/bvqWUoB4AchdM6d0BOlcCJRnZm8XJCYVHl8aux2yHFEScHEGMDSXIsUYvV0DOR+Oct8Tl2FP7CA5Sq3VWTJk1CZmam9e/sWQOOgoTvITd585rZQzSCk7HQ7ZXi1xeS+eqVwzNwdyjycbPJUM3Bwd/E49UTxe/xDmRnt/PtJpOnsSjItbVUuBul8zYA1L6bTVYKXKdn26wUx+j8nuL3mKMWy8od/LXoPcYuvaIsdYaklLK2X/678PrkyFEbcOWpLpjg3C0oVyZ16Tg6FaQrR8GtIEnBJS8ftn2f9znc8aV4DCrDLtvrA9v/O4/jqxMQJw7zewGz25kaHNClSk50tJgsLz093eb99PR062fR0dG4dOmSzef5+fm4du2aTRm1c8jr0Cojfa5GcHAwIiIibP6IUoTcd0NyyGV96OWDgjTjVRsY1ZAP3lpRU5ngsAJJ/kdWZ1jODrZSQ77ymvBEl5VZ9Q5rBIPTol7R0rXc8ZG1XkD9tzyynE9WuazAwraibeBntvDJabaF0UdEniBV+p7KpK+asrJlCOuWbs6BNzhS3RqjZZ2089vjtIhKv1FGKoxZciRRgz51LPIX96rL8rb76CrxqBW0UA2lVbLCXeyyIVHisXJjMUL89RRjPpAGcamSExMTg+joaKxdW2yay8rKwvbt2xEbK64Bx8bGIiMjA0lJxevd69atQ2FhITp27Ggts2nTJuTlFWt/a9asQcOGDVGuXDlrGXk9UhmpHoKwQ7VjYeww2j1T/LqgaIblLNaHRJBsdspr3h+8sPj1JWlGx+G0aLfjh7HeDsW7Ha07YViRW4948kDJFY2T6+wHwUnntGWlAI9VmrK10ZWoJp40Eo/EgKyj6NeuQq4gSbvwWJdOJQtBgzj1JWOt5RT5BEUP53aJx2un+H1ypGehXAyMbcfmlG07ovi1FC8L4FewpKW+W5ccl5Mjd2ofy+mbJk3kjv9T/J7WMqQH4FZybt68ieTkZCQnJwMQnY2Tk5ORmpoKi8WCcePG4YMPPsCff/6J/fv348knn0S1atUwYMAAAEDjxo3Ru3dvPPvss9ixYwe2bt2KsWPH4rHHHkO1amLMgccffxxBQUF45plncPDgQfzwww+YOXMmJkwoDuX+8ssvY9WqVZg2bRqOHDmCKVOmYNeuXRg7dqyyyQShDesatTLxJcBu3g+WJ/CzKI5OKFen+LXk+Mgiak01UKSQ6Y14DAAn/uWTlawTNvWyOFrKBkp5e1s/IcaAcrSUIQ28ZuRtkxw7lfmXWOgh22XkCufwNMYtzUaQ71K8WTRwslo1rfflHdgl5XS0g0pKgilNGHiXjQ78KvuHU7ZaG/FoY83wgBIrzzt1JkEm7uaAfoDY3z3+EzD0B6CiC5Jt2vSBnoVbydm1axdat26N1q1bAwAmTJiA1q1bY/LkyQCAV199FS+++CKee+45tG/fHjdv3sSqVasQElI8w1iyZAkaNWqEHj164IEHHkCXLl1sYuBERkbin3/+QUpKCtq2bYv//ve/mDx5sk0snbvvvhtLly7FV199hZYtW+Lnn3/G77//jmbNmum+GEQpRBlBlYe/XmYrJ5lvgeIOirWjkg8oXIkj5fmUZLDWW71N8WtrPBYd8VukWR13hFdOx3DJFC8FA3RFwEZWdn8rHvVs11fLLcZzrZRLEJ6OiyL5ArHuRJOU0fyc4u9u8QdeSgYGz9eWk+5nyYrKaxWpKVt+kSYnvBGe9aRIGFCU++muHjomGrLh+abkmuGB+1miQS+gYW/XnIvV6u0GGBdwi7n33nshOPixLBYL3nvvPbz33nuaZcqXL4+lS5c6rKdFixbYvHmzwzKPPPIIHnnkEccNJghH/DsF6DTavXXIt1LeUNlR4lBWNgOSrDIsSwPSoCA5lfISUd3+Pda2D/wa+LUoLMB2Kegcb2A9zoze0uApd5Q2SmvG2CByeAcyuYWwgPM7A/ojPJuFdF/m3SlWZMMrO89FJo+9JI+ky6qo3De5+FlIP+i4rBLpeUvZCH5fIPlSpoGdlZJfjd7dUWbjCeuTBqVqdxVB2Dkwdv2v/nO9muK8jBasyoc8EnRuUVReFr+LZMeTCKeodabH/rF/T42Ybvbv8XZy1VrxlZcGvhwp9pWLtuqz0MhAKpU2Txa/3iilrjFpQJC3hRetFARKJGX09GaZvxaL0i67H3d8xW+pky+58MruXabyJqOsfNnYiHUxr2ibv66o2qUbUnKI0kX7kbb/3/Mqu6yfwvCp5qfDijJxnhZqyoZdHhwVNHdHGRhA5YkSHaFmmlZeOy2kvFdhFcG1JCFfdtQbl6OMbfwum0zYjlBzqtazqyvjjHjkSVbb/FHb//vPUS/Hwv3v65e9zqjwy/1wCnmc0mXPQap2wFcmdn5ddE5GP6LKjYpf895bkpIjz2umR/G+sMd5GWd0meC8jCt4boNn6mGElByidGFkZj/ZgP+OkooGtmizbPWVL8HdSHeNU+vub9jKqQ4enD5IciWQ5TcLlyko+dn6Zs16LRlSMECpbk9S/37b/1sP03+uYA+E1LgpC/vB43clDxoaXgWGLHWSwhDE6AzbQOaXIkX+Za1Xiup84yI8migTAJ743fb/ej1Vi7kcZRgHkyElhyh9DCpycBzOGAdFziNFA/0znDuOlPQ1kK/rntedl5E7LKd6eGeG2i6o5CVssn6yCMA8yDOf88bYkbjnNX0dtLxuV4TQ56H5I0CrIsWmMuf2+edlPo+BZWwdXZ0hRcTmRe7rJUVpzuRMIlu9rWuU9qAybOXkQSFvaEfUV0WeCsKTzvCAve8Rrz+gXpTPv3wHoQmQkkOUPpoPFrckx3R1XlZJ0wGibE3OEP5DFIM8awerRotHnZeR++3k64jE62pYoxcf+l087lrosJgd8iB4h/+CrllzQBDw3yPiTp+3LjstbkUe8j5pUdELDw1kFgswYI54T76Q4Ly8nKotgMnXxb83OXNf7f3e9v+R69jk6sksT/+8yVenxB8vyP4xcJ0vJvPLHPiFr942MmVQcornmWgYSUzapL/t/3W66D8XDzxBBz0AKTkE4QkaG3BOHbPT9n+W3VXygG13rkPXoN/nY9v/3zAwE7yXwfoEFCclvHJUf12n1gO3OZcV5JSP4cupJq9DiqQd6IGgfK7Az4/PgiOh9CmLbs4mxxqR2SkeXvqROPyneGS9ZuGyCPzW4Hgc96QyezkPkTWA8nXF1w9/CZTVzgbgUiwWYKLMgtXxec/UqwEpOQThKaRlDbXdR46o1ACo2lJ8LU8R4Qi5w3LlxrIPODpYZefEk1W4uSK0g9TZOqOOLHuy3nEs7zaw6WPn5dyJEUfRCEaHZzMZf8j2f1YnXlfDo8TGujBQbC7j1n25MnRmq3jkaXP6Adv/pWzqLFgswEt7RCtfy8fY5VxBmQpive9kGLNauwBScgjCUzzyDdDnk2K/Hh6e3yTOjl47zS4T3UI8GkmO9+AM8dhkAJ/coHn66mugFnzMpBQJRpD7YjhDmUR1xArXtsUdRFYHntsovm4/0vNxUPT4t7BOEFjQE9NIUnxZs70DQOUmtv8b2QFnBibGx5EgJYcgPEWZCkDH5/RvPS9TwXkZOVJAvbxb+h01240AXjkBPLKIX/bNNNHpcMJh52Ulrp4sfs26zd7X6f6G7f/yVB7eTLVW4my97zTP1CdZYu7qAV1mPmU06EEOIiy7EymXFAvynXuACxPnlh5IySGIkork17Lho+L39MyswivpkwsMBbpOACKqscu0e7r49Z7v+OpTOlr6CoGhwNtF4Qm6ccRt8lVYYyYpqVAU0E/uVM9zX8Z9aPs/z5ZqsxJMBoYAb6aLE4a3LvtuxGMTISWHIEo6lw7BNEdNXuRJEKWZ9/E1bLKSs7EcT5nLayiyZL9ynE/eP0C0itync8eRL9Ftou3/zzD+vpLfz9EV+iyTgaHFS2yAbTRxZ9zzGn99riIwRGw7jzM8YYWUHIIoVZi/Ru4QtZnqDcbtzacd57pzK49+a/t/eGX1coS9f5eU5dsZ1u3bcnSkC3k1RbSM8KDc5XTvG+rlCK+DlByCILybWrEGhD2k1EVUBZ5eLb5uOtAzdfoqlRsBvf+v6B8L+7Zyua+S5Eyvx1IXVt42xAILUTVtneK7vcIuy5oDjXALrgpaQBCEtxFarjis/GUDcWfMhjVXUb/ZwJ8u3CbMS61O4pZZL9hR4vV0GiX+8dDheWDXAvF1Nofzrqt4/Acg95boU8QSq0ri8hHb/4frjMhN6IIsOQRRUvmPzLx/drt4LMkDsFreKE9/35J8fc1GvrPImkfNw9c7qAy/8++AL2z/N8uJuZRCSg5BlFRCZVvV8xiDl3kDDfrY/v88o69NxQaubwvhPcgVSCnycNY5c9rCQ2AoMOzn4v8r1DevLaUQWq4iiJKK6tZtH7A0PLYEeE+moFVtwSZXs6P9e65I5EgQRql/v7h7jvA4ZMkhiJKKmlndSE4oT+HnX5yvayBH5GS1fFH7f3RNmwiC8EnIkkMQpYlDf5jdAjYqNaCZL0EQhiFLDkGUZIYsMbsFBEEQpkFKDkGUZBo/aPu/lM2cIHyR/6gFBCQIbUjJIYiSTtmqxa9HrjWvHZ5gkiIJ4wvbzWkH4R6U+aaUvzdBKCCfHIIo6by0B9i1ULTqSPl/SirB4UD/OcAfL4j/V25kbnsI1zMlU0w6W6Wp+HsThAMsglB691hmZWUhMjISmZmZiIiIMLs5BEG4iqyLQJlK7CkDCILwKVjHb+oBCIIoeURUdV6GIIgSD/nkEARBEARRIiElhyAIgiCIEgkpOQRBEARBlEhIySEIgiAIokRCSg5BEARBECUSUnIIgiAIgiiRkJJDEARBEESJhJQcgiAIgiBKJKTkEARBEARRIiElhyAIgiCIEgkpOQRBEARBlEhIySEIgiAIokRCSg5BEARBECUSUnIIgiAIgiiRkJJDEARBEESJhJQcgiAIgiBKJKTkEARBEARRIiElhyAIgiCIEgkpOQRBEARBlEhIyXEDl7Kycf1WrtnNIAiCIIhSDSk5LqawUMC4H5LRe+YmbDl+hVv+vb8O4d5P1mP9kUvcsh/9fQTdPl6P1QfTuGWnrzmGLv+3Div2XeSWjV9/Ap0/Woff95znlv160ynETl2Ln3adhSAIXLLfJJxGpw/X4vsdqdyyy3akouOH/+LbxNPcsr8knUPHD//FvM2nUFjIJ/vX3gvo8L9/MXfjSRRwyq46kIYO//sXn689zi277kg6OvzvX0xfcwx5BYVcspuPX0bHD//Fx6uOIDefT3bbqavo+OG/+N+KQ8jJL+CSTTpzHZ0+XIspfx5Edh6f7P5zmYiduhZv/34At3PzuWSPpGXh7qlrMenXfbiVwyd78vJNdP5oHV75aS+ysvO4ZFOv3kaX/1uHccv2IPM2n+yFjDvo9vF6jF26m3uCdelGNu75ZD1GL07ClZs5XLLXb+Wi+6cbMPKbXbiUlc0leyM7Dz2mbcCIhTtwMfMOl+yd3AL0+mwjnpi/Heeu3+aSzckvQJ+ZmzFs3jakXuWTzSsoRL/ZWzDky0ScunyTS7agUMDAOVsx+IsEnLh0g0tWEAQ89lUiHp6zFUfSsrhln5i/Hf1mb8GB85lcsgAw8ptd6DtrM5LPZnDLegOk5LiYKzdzkJaVjfSsHPxn/na8v/wQVwf9466zOH31NkYs2om3fz+AO7nssr/sPofUa7fx/HdJmPTrPq7O/fc953Hu+h2MWbob//1xL25wdNB/JJ/H+Yw7GPdDMl76fg8y77DLLt93ARczszHx530Ys3Q3Mm6zd9Ar919EWlY2Jv26H899l4SrHB303wfSkJ6Vg8l/HMTTi3bi8g122TWH0pGelYMPVhzG8IU7kM7Rua89nI5LN3Lw0d9HMGzeNpzPYO/cNxy9hEs3cjBtzTEM+TIRZ6+xd9Cbjl3BpRs5mLX2OB6Zm4jTV24xy245fgXpWTmYs+EkBn6xFScusXfuCSevIj0rB19vTkH/2VtxLJ29c9926irSsrKxKOE0Hvp8Cw5eYO+gt6dcxcXMbHy37Qwe/HwL9p9jl915+jouZGbj+x1n8cCszdidep1ZNunMdZzPuIOfk86hz4zN2Hn6GrPsnrPXce76HfyefAG9Z25Cwkn2SdK+c5lIvXYby/ddRNyMTdh07DKz7MELWThz9Tb+PpCG3jM2cU2wDl/MQsqVW/j3cDriZmzimmAdS7+Bk5dvYf3Ry+g9YzPXBOvk5Zs4ln4Tm49fQZ8Zm7kmWKlXb+PwxSxsPXEVfWZu4ppgXczIxr5zmdiecg19Z23B0u3sE6wrN3OwOzUDu85cR99ZW7gmWJl38rDt1DXsSc1A31lbuCZY2XmF2Hz8Cvady8SDn2/hmmAVFgr493A6Dl7IwoD4rbomWGZDSo6LqRwRghUvdsUTnWoDAOZvScGAeHbtOzTI3/pa7KA3M2vfoYHFst/vOIu+s7ZgL6P2HRJYfCv8svscHpi1GUln2Dro4IDiev/cewEPzNyM7aeuMskGBRTXu3J/GnrP2IytJ9g6d7nsmkPp6D1zMzYcZeugA/0t1tdiJ7sJ/x5KZ5L1l8luPn4FcTM2YdUBtg7az69Ydtupa+g9YxP+3HuBSdZiKZbddeY6+szcjF+SzjF1lDJRJJ/NwAOzNuOHnYwdtEz2wPksPPj5ZizedobbAnYk7QYe/HwLFm5N4ZY9fukmHo5PwFebTnJbz05dvoWH52xF/PoT3B30mau38cjcRMz49xjyOS1g5zPuYMiXifhk9RFu69nFzGwMm7cdU1ce5raAXbqRgycX7MC7f/FbwK7czNU1wQKA67fzdE2wAHEQ1zPBAoAbOfm6JlgAcCu3QNcECwDu5BXgjd/4J1gAkJNfiMl/HMSIRTtx6QafBaygUMAHKw7jyQV8EywJaYJ1gWOCJaFngmU2pOS4gdAgf7w/oBkWPNUOFcODcCTtBvrN3or5W1KcdtBB/uJP8kqvBqhcNhgnizpoFu1bGrjH92yAqpEhSLlyC4O+SMDsdc61b38/sd6X7quH6lGhOHvtDh6Zm4jpa5x37v5FA/eY7nehdoUwnM+4g8e+3ob/Y1je8CsafZ+/py7qViyDtCyxc2dZ3pAG/We7xqB+5XBcvpGDpxbuZFrekGSfursOGkWXxdVbuRj57S688dt+px20NOY/GVsbzapHION2HkYt3o1Xf96Lm06WNyxF0kM71EKrmlG4kZ2Pl77fg/E/JDtd3pAUlUfb1UC72uVwMycf//1pL8Z+z768MbB1dXSqWx63cwvw2i/7MXox+/LGQy2roWv9isjOK8Rbvx/As9/uYl7e6NMsGt0bVkJufiHe/esQhi/cyby80bNxFfRsXAW5BYX4cOUR/Gf+dubljXsbVsIDzaORXyjgk9VHMfTrbczLG53rVUD/VtVQUChgxr/H8eiXiczLGx1iymNQmxooFID49Scx6IsE5uWN1rWiMLRDTQgC8OWmU3g4PgHHGS1gzapH4MlYcYK1cOtp9J+9FYcvOplgFXUNDaqE4+nOMQDECdZDHMsbMRXL4Pl76sJiKZ5gsS5vVI8Kxdju9eBn4Z9gVQwPxrie9eHvZ+GeYEWGBmJiXEME+Fmwcn8a4mZsYp5ghQb6480HGiPI3497guXvZ8E7DzVBUIAfNhy9jD4zNjNPsADg/f5NERLohy0n+CZYAPBuv6YIC/K3TrD+cjLBko8akx9sgvDgAOsE69fdbBMssyElx43c16gK/n65G+5rVBm5+YV4f/khPPvtLqYZQ9f6lbBqXDfENa2CvAIBH/19BE8t3OFwxiDdbrF3VcCql7vhwRZVkV8o4NN/jmHYvG1MM4b2MeXx97iueLh1dRQKwKy1xzH0621Iy9SWleptXbMcVrzUFY+2qwFBAL7YcBKPfpnocElGkm1RPQrLX+qCxzvWAgB8vTkFg75IcDhjkB6wxlUj8NeLXfDU3XUAAIsSTmNA/FakOFiSkZ7NhtFl8cfYzhjZRezcl25PRf/ZWx2umUttvqtSOH4d3Rmj770LFgvw465z6Pf5FodWO6FIOqZiGH4aFYuXetSHnwX4bc95PDjL8aAitblmuTAse64T/nt/A/j7WbBi30U8MGuzQ6udJFstKhRLRnbC630aIdDfglUH09BnppNBpUg2OiIY34zogLcfbIIgfz/8e/gS+szcjG2OBpWiiiuVDcaCp9rjvf5NERzgh03HLqPPzM1MfmsVygTh6yfb4sOHmyM00B8JJ6+iD+OgEhUaiPjH2+CTwS1QJsgfO1Ku4YGZm7HG0aBS1OaIkEDMfKw1ZgxphbLBAdidKlrA/t7vYFApulZlgwMw7dGWiH+8DSJDA61LBX8kO19WKRMUgKkDW+DLJ9qiXFggDl3MwkOzt+DnpHMOpMSKQwP98V7/4gnW0fQb6B+/lclvLSTQH5MfaoJvn+6AymWDceLSTQyck+BwWUV6N8jfD5P6NMaSkR2tE6zBXyRg3uZT2rJFbwf6W/BKXEP88HysdYL16JfbMHejttVOLjuuZwP8NCoWtcoXT7A+X3tcW7bo6O9nwZju9fDrC3ejbsUyVheDaf8c1ZwUSs+vv58Fz3ari9/HdLaZYE39+7DmpFBqs58FGNE5Bn+N7WIzwXrvr0Oak0L5JRzWsTaWv9jVZoL19u8HNCeFgkxVebRdTax8qSta1YxCVnY+Xvx+D17/ZR+TxW9gm+r4++Wu1gnWhB/34r8/7eW22nkaUnLcTKWywZg/vB3eH9AMQQF+WHvkEvMsp3yZIMz9T1v836DmCAn0w+bjV9B31hbsYljnjwwLxOdDW2P6oy1Rpkhz7ztri+aAJO+IIkIC8dmQVpg1tDXKBgdg5+nr6DuLbUAKDw7Ax4Nb4othbRAREoDksxnoO2sz1jMMSGFBAfjw4eb4+sl2KBcWiAPns9B3lpMBCaKFIyTQH1P6NcXCEe2t1rOHPt/ieECCaJUJDvDHWw82wZKRHVG5bDCOX7qJfrO3Mg1IQQF+eK13I3z/bCdUjQzBqSu3MCB+q5MBSSTQ3w8T7hc76OpRoUi9dhsDv0hgWucP8PfDiz3q45fRd1utZ4PnJuCbBOfr/P5+Foy65y789kJn1K0kWs+GfLnN4YAk4ednwTNdYvDni53RoIrYuT/+9TZ8scH5MpLFYsGTsXWw/MUuaFw1Aldv5eKJBdsxy8GAJJd9vGMtrHipi7VzH7Fop8MBSZKzWCx4pF1NrHy5uHN/9ttdDgckUVY8DmhdHX+PK+7cRy/Z7XBAktO3RVWsGtfVaj17eVky3vp9P9MSVFzTaKwe181qPXvlp7147We2Aem+RlWwalw3q/Vs0q/78d8f1QckAbbXr1sDcYLVq4loPZv8x0G8tCzZqZUSAO6+qyJWvdwNfZuLE6wPVhzG6MW7mZyw29cRJ1gDiqxnH/19BM99t4vJStmmVjmsfLkrBrcVJ1jT1hzDiEU7cc2BlVKyyLaoIU6whnaoBUEAPl93Ak8u2M7kp9ekmjjBGl5kPfty4yk8/vV2pmUkaYL1TNEEa8HWFDz2VSLTMlK9yuIEa9Q9dwEQLW+PzGVbRqpTsYw4wbqvHiwWYNnOsxg4JwFnrtpPCpX9Qc3yxRMsPwvw6+7zGBC/FSc5nbA9CSk5HsBiseCJTrXxq2xAemRuAhYx+CZYLBYMaV8Lf4zpYh2QHvuKbUCyWCwY2KYG/hjbxWZAmrPhBJNfQ7+W1fCXYkCa+a/zAQkA+jSvihUvdUWLGpHigLRwJz5d7XhAkri/SRWseKkrWteSDUgrDzP5NXRvWBkrXuqKDnXKWwekd/86yDQgda5XESte6oq776rAPSB1qlsBK17qim4NKnEPSG1rl8eKl7qgR5HF743ftAckJa1qRuGvF7tYLX7v/HkQL36/h2lAalY9En+O7WK1+PEMSI2iI/D7mM4YWGTx+79VR5itlPWrlMVvL9yNx9qLSzLT1xzDU04GJIm6lcLx86i78Z9OxQPSE/PZBqTaFcrgx+djMaJzHQB8A1KNcmH4/rlOeL5bXQDigDSEcUCqGilaz8Z2rwcAWLwtlXlAqhwRgkUjOmB8zwawWIAfdp3Fw3MSHFopJSqGB2P+8PZ4tXdDcUDaIw5ILI7j5csE4csn2uKtvo0R4GfBX3svoN/sLTia5nzZLDIsELMfb433+je1Wgv7MTqOSxOsqQObIyhAtBb2/Xwz9p3LcCobHhyATx9piU8Gt0BIoB82HruMvrM2I+mMc8fxsKAATB3YHDMfa4WwIH9sPXEVfWdtxo4U5xPKkEB/vNu/GeIfb4Pw4ADsOH0NfWdtRgLD0ldwgD/efrAJvnqiLcqGiNbCvrPYrJRBAX54vU8jLHyqPaLCRGth31lsS1+B/n6Y0Kshvn26AyqUCcKhi1l4cNYWpqUvaYK19NlOqFQ2GMfSb6Lf51ucLn2ZBSk5HqRZ9Uj89WIX9G4ajbwCAVP+OoSxS9UHJLmjKCBq/X+O7YKHWlazDkijFifZDkiCumy9yuHigNRGHJA+XnVUc0CywFa4TsUyNgPSZ/8ew/CFO2wHpCJlS1lvzfLikozkhD17/Qn8Z55iQNJoc7WoUPzwXKzVR+DLTafw+NfbmAakKhEhWPpsRzx/jzggLdx6WmVAUle2KpUNxnfPdMSL9xUPSIO/UAxIGm0uXyYIi55qjwn32w5INjuZJFnFdY4KC8LXT7bDa70bwd/PojEgqV/niJBAzP1P8YC0fN9FzQFJKRseHIDPh9oOSMqdTIJV1lY4LEhckpEGJMlKKV82s8oq2hES6I+PBrXAp4+0REiguHylHJAEjfsqJNAfHwwoHpASTtoPSFr6f1CAH955qCnmDNMekLTU8EB/P0x6oDG+frIdIkICina6bMZG2U4mQeM38vcTl2QWjtAekASN+8rfz4KXe9bHd093RIUyQTh8MQv9PrcdkASN+8rPz4IX7q1nOyDN3mLj7F4sa4vFYsHIrnXxw/OdEB0RglOXb6F//Bb8IrNSarVZstr9NOpuVI8Kxemrt/HwnAQs25Equ1bFZZWyQzvUwq+j70at8mE4d/0OBn+RiO9kzu7W6wx7HmlXE7+P6Yy6FcvgYmY2hnyZiPlbiieUjuaG/VtVx59jxSWoSzdyMPRrcdlMKatWb98WVfHn2M5oFF0WV27m4j/zt9ssmxW32V66V9NorChagrpeZKWcLrNSypusvNbdG4kTO8lKOfLbXfjo7yNWK6X8+yplu9avhBUviVbKGzn5GLV4N95ffsg6obSpV9FucWLXBZ3qlset3AK8+P0eTP5De9nMLEjJ8TARIYH44j9tMPnBJgjws2DF/osYOGcrk0NjeHAAZj3WCu/3b4ogfz+sPpiOAfFbmRwaw4ICMO2RlvhINiD1j9/K5NAoDUjTigakzcevoN/sLc4dGiHOVN4f0AyzhrZGWJA/Ek9dZY7XEBTgh8kPNcEXw9pYl80e+pxtqS+gyEdAPiD1m8221OfvZ8F/ezXEohHtUS4sEPvPZ6Lf7C1IPOncodHPz4KXetTH4mc6omJ40YA0ews2H3e+pdfPz4LR996FpUXLZsfSb2JA/FasO+J8ZiYfkKpGhlh3FLFs6ZUGpJ+LBqQzV29j0BcJWL7P+cxMPiBZrZRfJuK3Pc6X6wBgcNsa4oBUSRyQHvsqET/uPMskqxyQHv96GxZvO8Mk+0DzqvjrxS7WAemJBTuYd31Jlsbm1SNx/XYenlq4A1/KBkJHSJZG+YD0+drjTLJd6ouWxvZ1igek6f8cZbKsSgNSbF3RSvnS93sw9e/DTJZVydIoLZv996e9eO+vQ0y7zVrVjMKKl7pY/RJf/3U/3vp9P5NVVpoUSstmb/9+AK//wmZZbRQdgT/GdkbfIivl+8sP4b8/7mWyrNarLC4jPdy6unXZ7MXv9zDtNqtbSZxQPtpOdDqftuYYRi9JYoq3VKtCGH4edTeGdRStlLPWncCz3+5i2m1WPSoUPz4fa/VLnLvxJEYs2sm01BcdGYLvn+uE54qslPO3pOCJ+duZLKuVy4Zg8TMdMaa7uGz2beIZDPt6O3e8JXfi80pOfHw86tSpg5CQEHTs2BE7duwwu0lOsVgseLpLDH54PrZ4dhW/BQknrzAtQT0RWwc/jYq1DmYD4rcyxcWwWCx4rEMt/PbC3ahRThzMHp6TwDSIAsCgtjXwx5guqFNBnF0N+iIBqw6wxcXo17Ia/hzbBXcVDWaD5yYwmzf7NK+KP1/sgoZVyuLSjRw8qhhE1WZGEtKA1KRqBK7czMXQr7fZDKLKmY2ce4sGpBY1xMHsifnb8R3jICotfbUpWnIbvmAHFmxJ0bQSyOlYtPTVIUZccnvmm11Fs0nnsuKA1BWd64mD2fPfJTEPoi2LBqR7ipbcxi7dg2mMg6g0IPVsXAW5+YUY/8NeTF3JNog2io7An2O74IHmooXz1V/24d2/DiKfQVYakPoVWTjf+v2AOIgWioOog58XMRXL4PcxnTGoTQ0UFAp4969DeP2X/dalTUf3lWSllHZBTf37CCb8uBc5DMui0oAk+XFMW3MMY7/fgzsMA3B0ZAiWPtvJ6ig/a90JjFqchFsMA3DlsiFYPLIjXrhXHJC+3HgKz367i2lps0J4MBaN6ICXe9QHIC7XjVi0k2nLdlRYEOY92Q4T4xrCYhGto6yDaGRoIL58oi3eeKAR/Iqso8O+3o6rN53Llg0JxOyhrfHOQ02s1tEhXxVbgx09+2FBAZj+aEt8MKAZAv1F6+gjXybgAsOuvpBAf3w8uCU+HtTCOhkd9EUCzl1nk/3fw80xY0grBAf4Yd2RS6I1WMVfRklQgB+m9GuK2Y+3RmigPzYfv4IBc9j8ZQL9/fDGA43x5RNtrT6c/ePZlicD/P0wMU5cNisbIu6+Yl2e9AQWwRf2gGnwww8/4Mknn8TcuXPRsWNHzJgxAz/99BOOHj2KypUrO5XPyspCZGQkMjMzERER4YEW25OWmY3nvtuFfecyEeBnsXbsf43tguY1Ih3KXr6Rg+e/24XdqRnws4g3W25+IX4eFYt2dco7lL16Mwejl+zGjpRrsFjE3RE5+YVYMrIjOter6FA243Yuxi7dgy1FJv6QQD9k5xViwVPtcF+jKg5ls7Lz8NL3e7DhqKiUhQb6405eAb4Y1gZ9mld1KHszJx/jliXj38PpNrIzhrTCgNbVHcrezs3HKz/txcr9aTay/zeoOYa0r+VQNjuvAK/9sg9/JF+wkX2/f1M8EVvHoWxOfgHe/O2A1RE5LMgft3ML8FbfxhjZta5D2dz8Qkz56yCWbk+1kZ0Y1xBjivw7tMgvKMQHKw5jUcJpG9mX7quHCb0aOpQtKBTwf6uO4KtNp2xkn+9WF5MeaOxQtrBQwPQ1xzB7/Qkb2afuroMp/Zo6lBUEAbPWnsBn/x6zkR3aoSamDmzhVHbuxlP4ePURCEKx7MDW1TF9SCunsvO3pODDlYdRKJPt27wq4oe1cSq7eNsZTPnrEAoKBatsz8ZVMG94O4eyAPD9jlRM/uMA8gqKZbvWr4jvnunoVPbnpHN449f9yC0otMp2iCmPH5+PdSr7594LmPiTqJRJsi1rRuGPMZ2dyv69/yIm/LgXd/IKrLKNosti1bhuTmX/PZSOl5ftwa3cYtm6Fctg3Sv3OpXdcPQSXvx+D25k51tlq0eFYuvr9zmVTThxBS8s3Y2M23lW2YrhQdj11v1OZXekXMOoxUm4divXKls2JAD7p8Q5ld2deh3PfStGkpZkgwL8cOyDPk5l953LwHPfJiEtK9sqCwCnP+rrVPbQhSw8++0unM+4YyN75P3eCJHFU1PjWPoNjPxmF1Kv3baR3ftOL0SGBjqUPXn5Jp79ZhdOXbmF0EB/fPpIS/Rt4bhf1wvr+O3Tlpzp06fj2WefxYgRI9CkSRPMnTsXYWFhWLBggdlNYyY6MgQ/Ph+L/q2qMc1c5VQqG4zvn+uEwW1F0yhPyP0K4cFY/ExHPF5kGmWZgUpEhQVh0Yj2VtNodh67bERIIOYPb2914GSZvUqEBwfgqyfaWh04eWTDggIQ/3gbTLi/AbdsSKA/Zgxphdd6N4LFwicbHOCPTwa3wFt9G8PPAmuHwUJQgB/+N6AZ3u/fFP5+Fi7ZAH9xVjd1YHME+vPJ+vtZ8MYDjTHtkZYI8vfjkvUr8j2ZNbQ1ggP4ZC0W0fdk7n/aIDTQn1t29L13Yd6T7RAeHMAtO7JrXSwc0QFlQ/hln4itg++e7oCosEAuWUCMl7RkZCeULxPELTu4bQ0se170teGV7deyGn4aFYvoiBBu2T7Nq+KX0eLSJq9szyZV8NuYzqhVPoxb9t6Gla2+Nryyd9eriD+KtnvzynaIKW/1teGVbVOrHP56sTOaV4/klm1RIwp/ju2MVjWjuGWbVBOX69rXKcct26BKWfwxprN1aZOHuyqF47cXOqNr/Yq4k1eAMUt3Y/qaY9wBPF2Jzyo5ubm5SEpKQs+ePa3v+fn5oWfPnkhMTDSxZfzIB1GJ8JAAJllpEH37wSaQgumWCWaTDQrww4cPN8f7A5pZA/qxykqD6EdFgyggxvdgwd/PgkkPNMb0R1taoxaz1isNop8PbW2N0hzOKGuxiP4yc//TFmFFkaXDgx3PTOSy8kGUp83KQZRXVj6IAkCZIMczMTnSIFqhTBBXvYC4PCkNoryy/VpWw8+j7kZ0REiRLHubezcrHkQB9vsKAHo0roLfXhD9gwD25wgA7mlQCX8U+QcB7PcVIA6if44RdzGKsuzfVz6I8tbbplY5/DlWHER5ZaVBtHWtKO42S4NohyKLMU+90iB6910VAPDdV3dVCsdvYzqjW4NKRbLsba5doQx+feFu9GxcmbvNNcqF4ZfRd6NPs2hu2aqR4vLkQy2rcctWjgjBsuc6YWAb0VLN8+xXDA/GkpGd8Fj7mgCA4AA/az/vjHJlgvDtMx2sS6qB/hYEB7CpC5FhgVj4VPviJdW1x7GVI0WJyxF8lPPnzwsAhISEBJv3J06cKHTo0EFVJjs7W8jMzLT+nT17VgAgZGZmeqLJTOxMuSr8knRWl2zSmWvCjztThcLCQm7Z5NTrwrIdZ3TJ7j+XIXy//YyQX8Ave+hCprBk2xkhN7+AW/ZoWpaweNtpISePX/Z4+g3h28TTwp3cfG7ZU5dvCt8mnhZu5/DLnrlyS/g2IUW4mZ3HLXv22i3hm4QUIetOLrfshYzbwqKtKULGbX7ZtMw7wqKtKcK1mzncspeysoVFW1OEKzeyuWWv3BBl07PucMtev5UjfJOQIqRl8stm3M4VvklIEc5fv80teyM7T/g2IUVIvXqLW/ZWTp7wbeJp4fSVm9yyd3Lzhe8STwsnLt3QJbt422nhWFoWt2xOXoGwdPsZ4dAF/j40N79AWLbjjLD/XAa3bH5BofDjzlQhOfU6t2xBQaHwS9JZIenMNV2yv+85J+xIucotW1hYKPyZfF5IOHFFl+zKfReEzccu65JddeCisP5IOresIAjCv4fShH8PpemS/XFnqvDhykO6ZJ2RmZnJNH77rE/OhQsXUL16dSQkJCA2tngN+tVXX8XGjRuxfft2O5kpU6bg3XfftXvfTJ8cgiAIgiD4KPE+ORUrVoS/vz/S0213BqWnpyM6OlpVZtKkScjMzLT+nT3LtlWVIAiCIAjfw2eVnKCgILRt2xZr1661vldYWIi1a9faWHbkBAcHIyIiwuaPIAiCIIiSCbsHlBcyYcIEDB8+HO3atUOHDh0wY8YM3Lp1CyNGjDC7aQRBEARBmIxPKzlDhgzB5cuXMXnyZKSlpaFVq1ZYtWoVqlRxHKuFIAiCIIiSj886HrsCbwgGSBAEQRAEHyXe8ZggCIIgCMIRpOQQBEEQBFEiISWHIAiCIIgSCSk5BEEQBEGUSEjJIQiCIAiiREJKDkEQBEEQJRJScgiCIAiCKJGQkkMQBEEQRInEpyMeG0WKg5iVlWVySwiCIAiCYEUat53FMy7VSs6NGzcAADVr1jS5JQRBEARB8HLjxg1ERkZqfl6q0zoUFhbiwoULKFu2LCwWi8vOm5WVhZo1a+Ls2bOULsIBdJ3YoWvFBl0nNug6sUPXig1PXydBEHDjxg1Uq1YNfn7anjel2pLj5+eHGjVquO38ERER9FAwQNeJHbpWbNB1YoOuEzt0rdjw5HVyZMGRIMdjgiAIgiBKJKTkEARBEARRIiElxw0EBwfjnXfeQXBwsNlN8WroOrFD14oNuk5s0HVih64VG956nUq14zFBEARBECUXsuQQBEEQBFEiISWHIAiCIIgSCSk5BEEQBEGUSEjJIQiCIAiiREJKjhuIj49HnTp1EBISgo4dO2LHjh1mN8ltTJkyBRaLxeavUaNG1s+zs7MxZswYVKhQAeHh4Rg0aBDS09NtzpGamoq+ffsiLCwMlStXxsSJE5Gfn29TZsOGDWjTpg2Cg4NRr149LFq0yBNfTzebNm3CQw89hGrVqsFiseD333+3+VwQBEyePBlVq1ZFaGgoevbsiePHj9uUuXbtGoYNG4aIiAhERUXhmWeewc2bN23K7Nu3D127dkVISAhq1qyJjz/+2K4tP/30Exo1aoSQkBA0b94cK1eudPn3NYKza/XUU0/Z3WO9e/e2KVMartXUqVPRvn17lC1bFpUrV8aAAQNw9OhRmzKefN68tZ9juU733nuv3T01atQomzIl/Tp98cUXaNGihTV4X2xsLP7++2/r5yXmXhIIl7Js2TIhKChIWLBggXDw4EHh2WefFaKiooT09HSzm+YW3nnnHaFp06bCxYsXrX+XL1+2fj5q1CihZs2awtq1a4Vdu3YJnTp1Eu6++27r5/n5+UKzZs2Enj17Cnv27BFWrlwpVKxYUZg0aZK1zKlTp4SwsDBhwoQJwqFDh4TPP/9c8Pf3F1atWuXR78rDypUrhTfffFP49ddfBQDCb7/9ZvP5Rx99JERGRgq///67sHfvXqFfv35CTEyMcOfOHWuZ3r17Cy1bthS2bdsmbN68WahXr54wdOhQ6+eZmZlClSpVhGHDhgkHDhwQvv/+eyE0NFT48ssvrWW2bt0q+Pv7Cx9//LFw6NAh4a233hICAwOF/fv3u/0asOLsWg0fPlzo3bu3zT127do1mzKl4VrFxcUJCxcuFA4cOCAkJycLDzzwgFCrVi3h5s2b1jKeet68uZ9juU733HOP8Oyzz9rcU5mZmdbPS8N1+vPPP4UVK1YIx44dE44ePSq88cYbQmBgoHDgwAFBEErOvURKjovp0KGDMGbMGOv/BQUFQrVq1YSpU6ea2Cr38c477wgtW7ZU/SwjI0MIDAwUfvrpJ+t7hw8fFgAIiYmJgiCIA5yfn5+QlpZmLfPFF18IERERQk5OjiAIgvDqq68KTZs2tTn3kCFDhLi4OBd/G/egHLgLCwuF6Oho4ZNPPrG+l5GRIQQHBwvff/+9IAiCcOjQIQGAsHPnTmuZv//+W7BYLML58+cFQRCEOXPmCOXKlbNeJ0EQhNdee01o2LCh9f9HH31U6Nu3r017OnbsKDz//PMu/Y6uQkvJ6d+/v6ZMab1Wly5dEgAIGzduFATBs8+bL/VzyuskCKKS8/LLL2vKlMbrJAiCUK5cOWHevHkl6l6i5SoXkpubi6SkJPTs2dP6np+fH3r27InExEQTW+Zejh8/jmrVqqFu3boYNmwYUlNTAQBJSUnIy8uzuR6NGjVCrVq1rNcjMTERzZs3R5UqVaxl4uLikJWVhYMHD1rLyM8hlfHVa5qSkoK0tDSb7xQZGYmOHTvaXJeoqCi0a9fOWqZnz57w8/PD9u3brWW6deuGoKAga5m4uDgcPXoU169ft5YpCdduw4YNqFy5Mho2bIjRo0fj6tWr1s9K67XKzMwEAJQvXx6A5543X+vnlNdJYsmSJahYsSKaNWuGSZMm4fbt29bPStt1KigowLJly3Dr1i3ExsaWqHupVCfodDVXrlxBQUGBzY8OAFWqVMGRI0dMapV76dixIxYtWoSGDRvi4sWLePfdd9G1a1ccOHAAaWlpCAoKQlRUlI1MlSpVkJaWBgBIS0tTvV7SZ47KZGVl4c6dOwgNDXXTt3MP0vdS+07y71y5cmWbzwMCAlC+fHmbMjExMXbnkD4rV66c5rWTzuEL9O7dGwMHDkRMTAxOnjyJN954A3369EFiYiL8/f1L5bUqLCzEuHHj0LlzZzRr1gwAPPa8Xb9+3Wf6ObXrBACPP/44ateujWrVqmHfvn147bXXcPToUfz6668ASs912r9/P2JjY5GdnY3w8HD89ttvaNKkCZKTk0vMvURKDmGIPn36WF+3aNECHTt2RO3atfHjjz/6nPJBeCePPfaY9XXz5s3RokUL3HXXXdiwYQN69OhhYsvMY8yYMThw4AC2bNlidlO8Gq3r9Nxzz1lfN2/eHFWrVkWPHj1w8uRJ3HXXXZ5upmk0bNgQycnJyMzMxM8//4zhw4dj48aNZjfLpdBylQupWLEi/P397TzQ09PTER0dbVKrPEtUVBQaNGiAEydOIDo6Grm5ucjIyLApI78e0dHRqtdL+sxRmYiICJ9UpKTv5eg+iY6OxqVLl2w+z8/Px7Vr11xy7Xz5fqxbty4qVqyIEydOACh912rs2LFYvnw51q9fjxo1aljf99Tz5iv9nNZ1UqNjx44AYHNPlYbrFBQUhHr16qFt27aYOnUqWrZsiZkzZ5aoe4mUHBcSFBSEtm3bYu3atdb3CgsLsXbtWsTGxprYMs9x8+ZNnDx5ElWrVkXbtm0RGBhocz2OHj2K1NRU6/WIjY3F/v37bQapNWvWICIiAk2aNLGWkZ9DKuOr1zQmJgbR0dE23ykrKwvbt2+3uS4ZGRlISkqyllm3bh0KCwutHXJsbCw2bdqEvLw8a5k1a9agYcOGKFeunLVMSbp2AHDu3DlcvXoVVatWBVB6rpUgCBg7dix+++03rFu3zm75zVPPm7f3c86ukxrJyckAYHNPlfTrpEZhYSFycnJK1r3kEvdlwsqyZcuE4OBgYdGiRcKhQ4eE5557ToiKirLxQC9J/Pe//xU2bNggpKSkCFu3bhV69uwpVKxYUbh06ZIgCOI2xFq1agnr1q0Tdu3aJcTGxgqxsbFWeWkbYq9evYTk5GRh1apVQqVKlVS3IU6cOFE4fPiwEB8f7/VbyG/cuCHs2bNH2LNnjwBAmD59urBnzx7hzJkzgiCIW8ijoqKEP/74Q9i3b5/Qv39/1S3krVu3FrZv3y5s2bJFqF+/vs226IyMDKFKlSrCE088IRw4cEBYtmyZEBYWZrctOiAgQPj000+Fw4cPC++8845XbYsWBMfX6saNG8Irr7wiJCYmCikpKcK///4rtGnTRqhfv76QnZ1tPUdpuFajR48WIiMjhQ0bNthsfb59+7a1jKeeN2/u55xdpxMnTgjvvfeesGvXLiElJUX4448/hLp16wrdunWznqM0XKfXX39d2Lhxo5CSkiLs27dPeP311wWLxSL8888/giCUnHuJlBw38Pnnnwu1atUSgoKChA4dOgjbtm0zu0luY8iQIULVqlWFoKAgoXr16sKQIUOEEydOWD+/c+eO8MILLwjlypUTwsLChIcffli4ePGizTlOnz4t9OnTRwgN/f927hhFYSCM4ni2cIYFsZAMFhYBCTY2HkDSDHgHK1HwBGJp7y3s01vnDJa29laCjcWzWFgILrsguyLf/n+QbgiZR2Z4hCTvStNUy+VS1+u1NqaqKg2HQznn1Ov1tN1unzG9h1VVpSRJ7o7pdCrp4zPy9XqtTqcj771ijDocDrVznE4nTSYTNZtNtVotzWYznc/n2pj9fq/RaCTvvbrdrjabzd21lGWpfr8v55wGg4F2u92fzfsR32V1uVw0Ho8VQlCj0VCWZVosFncb4H/I6quMkiSprYVnrrdX3ed+yul4PKooCrXbbXnvlee5VqtV7T85kv2c5vO5siyTc04hBMUYPwuOZOdeepOk33kmBAAA8Dp4JwcAAJhEyQEAACZRcgAAgEmUHAAAYBIlBwAAmETJAQAAJlFyAACASZQcAABgEiUHAACYRMkBAAAmUXIAAIBJlBwAAGDSDXMmnpttYBXDAAAAAElFTkSuQmCC"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_experiment[[\"#Wave\", \"#Intensity\"]].plot()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-26T18:05:51.419517500Z",
     "start_time": "2024-02-26T18:05:51.187293Z"
    }
   },
   "id": "1a9d17e12743f2bc",
   "execution_count": 13
  },
  {
   "cell_type": "code",
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-26T18:00:52.236580Z",
     "start_time": "2024-02-26T18:00:52.218164200Z"
    }
   },
   "id": "ce858af586a1dce1"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}