stats_jcs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f0232080-82e4-4a6a-80aa-fd5246cfd21c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f94df750-37f7-4813-98d1-cb776404884c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import ghibtools as gh\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import pingouin as pg\n",
    "from params import *\n",
    "from bibliotheque import *\n",
    "from configuration import *\n",
    "\n",
    "from compute_global_dataframes import hrv_concat_job, resp_features_concat_job"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ccb985f2-d49d-4b3f-9ab5-bff8385d84f0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "save_folder = base_folder / 'Figures' / 'Autres' / 'jcs'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b9c3b6dd-8751-47f6-8575-4e7eea391940",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "concat = []\n",
    "for participant in subject_keys:\n",
    "    ses01_folder = base_folder / 'Raw_Data' / f'{participant}' / 'questionnaires' / 'ses01'\n",
    "    df_participant = pd.read_excel(ses01_folder /  f'cotations_odeurs_relatives_{participant}_bis.xlsx')\n",
    "    concat.append(df_participant)\n",
    "cotations_relatives_odeurs = pd.concat(concat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ef9b8c0e-35c9-4250-aeda-c0baeea7d50f",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>participant</th>\n",
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       "      <th>hédonicité_absolue_brute</th>\n",
       "      <th>hédonicité_absolue</th>\n",
       "      <th>longueur_totale</th>\n",
       "      <th>intensité_relative_brute</th>\n",
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       "      <th>eveil_relatif_brute</th>\n",
       "      <th>eveil_relatif</th>\n",
       "      <th>familarité_relative_brute</th>\n",
       "      <th>familiarité_relative</th>\n",
       "      <th>valence_émotionnelle_relative_brute</th>\n",
       "      <th>valence_émotionnelle_relative</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>33</td>\n",
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       "      <td>82</td>\n",
       "      <td>0.82</td>\n",
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       "      <td>0.65</td>\n",
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       "      <td>1</td>\n",
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       "      <td>Floral Printanier</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>100</td>\n",
       "      <td>87</td>\n",
       "      <td>0.87</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
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       "      <td>0.74</td>\n",
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       "      <td>FoE</td>\n",
       "      <td>Fleur d’Oranger Epicée</td>\n",
       "      <td>77</td>\n",
       "      <td>0.77</td>\n",
       "      <td>100</td>\n",
       "      <td>21</td>\n",
       "      <td>0.21</td>\n",
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       "      <td>0.77</td>\n",
       "      <td>9</td>\n",
       "      <td>0.09</td>\n",
       "      <td>24</td>\n",
       "      <td>0.24</td>\n",
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       "      <td>0.80</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>P02</td>\n",
       "      <td>4</td>\n",
       "      <td>PL</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>100</td>\n",
       "      <td>78</td>\n",
       "      <td>0.78</td>\n",
       "      <td>87</td>\n",
       "      <td>0.87</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>79</td>\n",
       "      <td>0.79</td>\n",
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       "      <td>V</td>\n",
       "      <td>Vanille</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>100</td>\n",
       "      <td>96</td>\n",
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       "      <td>93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>17</td>\n",
       "      <td>0.17</td>\n",
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       "      <td>P30</td>\n",
       "      <td>6</td>\n",
       "      <td>FC</td>\n",
       "      <td>Fleur de coton</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>100</td>\n",
       "      <td>9</td>\n",
       "      <td>0.09</td>\n",
       "      <td>61</td>\n",
       "      <td>0.61</td>\n",
       "      <td>4</td>\n",
       "      <td>0.04</td>\n",
       "      <td>61</td>\n",
       "      <td>0.61</td>\n",
       "      <td>53</td>\n",
       "      <td>0.53</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>Vanille</td>\n",
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       "      <td>0.91</td>\n",
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       "      <td>88</td>\n",
       "      <td>0.88</td>\n",
       "      <td>68</td>\n",
       "      <td>0.68</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>80</td>\n",
       "      <td>0.80</td>\n",
       "      <td>65</td>\n",
       "      <td>0.65</td>\n",
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       "      <td>0</td>\n",
       "      <td>P31</td>\n",
       "      <td>2</td>\n",
       "      <td>FP</td>\n",
       "      <td>Floral Printanier</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>100</td>\n",
       "      <td>60</td>\n",
       "      <td>0.60</td>\n",
       "      <td>80</td>\n",
       "      <td>0.80</td>\n",
       "      <td>71</td>\n",
       "      <td>0.71</td>\n",
       "      <td>73</td>\n",
       "      <td>0.73</td>\n",
       "      <td>66</td>\n",
       "      <td>0.66</td>\n",
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       "    <tr>\n",
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       "      <td>1</td>\n",
       "      <td>P31</td>\n",
       "      <td>4</td>\n",
       "      <td>PL</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>100</td>\n",
       "      <td>66</td>\n",
       "      <td>0.66</td>\n",
       "      <td>89</td>\n",
       "      <td>0.89</td>\n",
       "      <td>82</td>\n",
       "      <td>0.82</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
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       "      <td>V</td>\n",
       "      <td>Vanille</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>100</td>\n",
       "      <td>32</td>\n",
       "      <td>0.32</td>\n",
       "      <td>57</td>\n",
       "      <td>0.57</td>\n",
       "      <td>54</td>\n",
       "      <td>0.54</td>\n",
       "      <td>79</td>\n",
       "      <td>0.79</td>\n",
       "      <td>68</td>\n",
       "      <td>0.68</td>\n",
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       "<p>90 rows × 18 columns</p>\n",
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      ],
      "text/plain": [
       "    Unnamed: 0 participant  odeur_num odeur_label              odeur_name   \n",
       "0            0         P01          1          FO       Feuille d’Olivier  \\\n",
       "1            1         P01          2          FP       Floral Printanier   \n",
       "2            2         P01          5         FoE  Fleur d’Oranger Epicée   \n",
       "0            0         P02          4          PL           Pêche Lavande   \n",
       "1            1         P02          7           V                 Vanille   \n",
       "..         ...         ...        ...         ...                     ...   \n",
       "1            1         P30          6          FC          Fleur de coton   \n",
       "2            2         P30          7           V                 Vanille   \n",
       "0            0         P31          2          FP       Floral Printanier   \n",
       "1            1         P31          4          PL           Pêche Lavande   \n",
       "2            2         P31          7           V                 Vanille   \n",
       "\n",
       "    hédonicité_absolue_brute  hédonicité_absolue  longueur_totale   \n",
       "0                         74                0.74              100  \\\n",
       "1                         85                0.85              100   \n",
       "2                         77                0.77              100   \n",
       "0                         94                0.94              100   \n",
       "1                         95                0.95              100   \n",
       "..                       ...                 ...              ...   \n",
       "1                         92                0.92              100   \n",
       "2                         91                0.91              100   \n",
       "0                         98                0.98              100   \n",
       "1                         94                0.94              100   \n",
       "2                         92                0.92              100   \n",
       "\n",
       "    intensité_relative_brute  intensité_relative  hédonicité_relative_brute   \n",
       "0                         33                0.33                         82  \\\n",
       "1                         87                0.87                         85   \n",
       "2                         21                0.21                         77   \n",
       "0                         78                0.78                         87   \n",
       "1                         96                0.96                         93   \n",
       "..                       ...                 ...                        ...   \n",
       "1                          9                0.09                         61   \n",
       "2                         88                0.88                         68   \n",
       "0                         60                0.60                         80   \n",
       "1                         66                0.66                         89   \n",
       "2                         32                0.32                         57   \n",
       "\n",
       "    hédonicité_relative  eveil_relatif_brute  eveil_relatif   \n",
       "0                  0.82                   65           0.65  \\\n",
       "1                  0.85                   74           0.74   \n",
       "2                  0.77                    9           0.09   \n",
       "0                  0.87                   96           0.96   \n",
       "1                  0.93                   17           0.17   \n",
       "..                  ...                  ...            ...   \n",
       "1                  0.61                    4           0.04   \n",
       "2                  0.68                   90           0.90   \n",
       "0                  0.80                   71           0.71   \n",
       "1                  0.89                   82           0.82   \n",
       "2                  0.57                   54           0.54   \n",
       "\n",
       "    familarité_relative_brute  familiarité_relative   \n",
       "0                          38                  0.38  \\\n",
       "1                          77                  0.77   \n",
       "2                          24                  0.24   \n",
       "0                          91                  0.91   \n",
       "1                          95                  0.95   \n",
       "..                        ...                   ...   \n",
       "1                          61                  0.61   \n",
       "2                          80                  0.80   \n",
       "0                          73                  0.73   \n",
       "1                          99                  0.99   \n",
       "2                          79                  0.79   \n",
       "\n",
       "    valence_émotionnelle_relative_brute  valence_émotionnelle_relative  \n",
       "0                                    74                           0.74  \n",
       "1                                    86                           0.86  \n",
       "2                                    80                           0.80  \n",
       "0                                    79                           0.79  \n",
       "1                                    95                           0.95  \n",
       "..                                  ...                            ...  \n",
       "1                                    53                           0.53  \n",
       "2                                    65                           0.65  \n",
       "0                                    66                           0.66  \n",
       "1                                    82                           0.82  \n",
       "2                                    68                           0.68  \n",
       "\n",
       "[90 rows x 18 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cotations_relatives_odeurs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "83a04dcb-a989-44fa-b9ce-a6e7a6a23298",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "label_odeurs_choisies = {}\n",
    "for p in cotations_relatives_odeurs['participant'].unique():\n",
    "    df_p = cotations_relatives_odeurs[cotations_relatives_odeurs['participant'] == p]\n",
    "    label_odeurs_choisies[p] = df_p.sort_values(by = 'hédonicité_relative')['odeur_name'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5e6984c3-ac4e-44eb-bc61-1d6c6f9c24be",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "      <th></th>\n",
       "      <th>participant</th>\n",
       "      <th>hédonicité_absolue_brute</th>\n",
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       "      <th>valence_émotionnelle_relative</th>\n",
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       "      <th>0</th>\n",
       "      <td>P01</td>\n",
       "      <td>85</td>\n",
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       "      <td>87</td>\n",
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       "      <td>0.77</td>\n",
       "      <td>86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Feuille d’Olivier</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>P02</td>\n",
       "      <td>96</td>\n",
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       "      <td>96</td>\n",
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       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>P03</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>100</td>\n",
       "      <td>86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>80</td>\n",
       "      <td>0.80</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>83</td>\n",
       "      <td>0.83</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>P04</td>\n",
       "      <td>86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>100</td>\n",
       "      <td>65</td>\n",
       "      <td>0.65</td>\n",
       "      <td>81</td>\n",
       "      <td>0.81</td>\n",
       "      <td>51</td>\n",
       "      <td>0.51</td>\n",
       "      <td>76</td>\n",
       "      <td>0.76</td>\n",
       "      <td>84</td>\n",
       "      <td>0.84</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>P05</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>100</td>\n",
       "      <td>73</td>\n",
       "      <td>0.73</td>\n",
       "      <td>86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>83</td>\n",
       "      <td>0.83</td>\n",
       "      <td>91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>P06</td>\n",
       "      <td>89</td>\n",
       "      <td>0.89</td>\n",
       "      <td>100</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>87</td>\n",
       "      <td>0.87</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>81</td>\n",
       "      <td>0.81</td>\n",
       "      <td>91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>P07</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>100</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>84</td>\n",
       "      <td>0.84</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>P08</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>100</td>\n",
       "      <td>84</td>\n",
       "      <td>0.84</td>\n",
       "      <td>87</td>\n",
       "      <td>0.87</td>\n",
       "      <td>64</td>\n",
       "      <td>0.64</td>\n",
       "      <td>70</td>\n",
       "      <td>0.70</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>P09</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>100</td>\n",
       "      <td>59</td>\n",
       "      <td>0.59</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>26</td>\n",
       "      <td>0.26</td>\n",
       "      <td>88</td>\n",
       "      <td>0.88</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>P10</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>100</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>P11</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>100</td>\n",
       "      <td>71</td>\n",
       "      <td>0.71</td>\n",
       "      <td>86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>63</td>\n",
       "      <td>0.63</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>75</td>\n",
       "      <td>0.75</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Fleur d'oranger épicé</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>P12</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>100</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>P13</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>100</td>\n",
       "      <td>81</td>\n",
       "      <td>0.81</td>\n",
       "      <td>91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>68</td>\n",
       "      <td>0.68</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>P14</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>100</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>67</td>\n",
       "      <td>0.67</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>P15</td>\n",
       "      <td>79</td>\n",
       "      <td>0.79</td>\n",
       "      <td>100</td>\n",
       "      <td>89</td>\n",
       "      <td>0.89</td>\n",
       "      <td>74</td>\n",
       "      <td>0.74</td>\n",
       "      <td>84</td>\n",
       "      <td>0.84</td>\n",
       "      <td>64</td>\n",
       "      <td>0.64</td>\n",
       "      <td>91</td>\n",
       "      <td>0.91</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>P16</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>100</td>\n",
       "      <td>65</td>\n",
       "      <td>0.65</td>\n",
       "      <td>81</td>\n",
       "      <td>0.81</td>\n",
       "      <td>73</td>\n",
       "      <td>0.73</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>81</td>\n",
       "      <td>0.81</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>P17</td>\n",
       "      <td>88</td>\n",
       "      <td>0.88</td>\n",
       "      <td>100</td>\n",
       "      <td>88</td>\n",
       "      <td>0.88</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>78</td>\n",
       "      <td>0.78</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>P18</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>100</td>\n",
       "      <td>74</td>\n",
       "      <td>0.74</td>\n",
       "      <td>93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>65</td>\n",
       "      <td>0.65</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>P19</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>100</td>\n",
       "      <td>74</td>\n",
       "      <td>0.74</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>P20</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>100</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>73</td>\n",
       "      <td>0.73</td>\n",
       "      <td>62</td>\n",
       "      <td>0.62</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>P21</td>\n",
       "      <td>93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>100</td>\n",
       "      <td>83</td>\n",
       "      <td>0.83</td>\n",
       "      <td>84</td>\n",
       "      <td>0.84</td>\n",
       "      <td>58</td>\n",
       "      <td>0.58</td>\n",
       "      <td>69</td>\n",
       "      <td>0.69</td>\n",
       "      <td>67</td>\n",
       "      <td>0.67</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>P23</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>100</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>79</td>\n",
       "      <td>0.79</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Fleur d'oranger épicé</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>P24</td>\n",
       "      <td>81</td>\n",
       "      <td>0.81</td>\n",
       "      <td>100</td>\n",
       "      <td>83</td>\n",
       "      <td>0.83</td>\n",
       "      <td>79</td>\n",
       "      <td>0.79</td>\n",
       "      <td>76</td>\n",
       "      <td>0.76</td>\n",
       "      <td>65</td>\n",
       "      <td>0.65</td>\n",
       "      <td>82</td>\n",
       "      <td>0.82</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>P25</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>100</td>\n",
       "      <td>80</td>\n",
       "      <td>0.80</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>72</td>\n",
       "      <td>0.72</td>\n",
       "      <td>77</td>\n",
       "      <td>0.77</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>P26</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>100</td>\n",
       "      <td>89</td>\n",
       "      <td>0.89</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>61</td>\n",
       "      <td>0.61</td>\n",
       "      <td>76</td>\n",
       "      <td>0.76</td>\n",
       "      <td>83</td>\n",
       "      <td>0.83</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>P27</td>\n",
       "      <td>88</td>\n",
       "      <td>0.88</td>\n",
       "      <td>100</td>\n",
       "      <td>94</td>\n",
       "      <td>0.94</td>\n",
       "      <td>93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Fleur d'oranger épicé</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>P28</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>100</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>100</td>\n",
       "      <td>1.00</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>P29</td>\n",
       "      <td>86</td>\n",
       "      <td>0.86</td>\n",
       "      <td>100</td>\n",
       "      <td>84</td>\n",
       "      <td>0.84</td>\n",
       "      <td>92</td>\n",
       "      <td>0.92</td>\n",
       "      <td>85</td>\n",
       "      <td>0.85</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>80</td>\n",
       "      <td>0.80</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>P30</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>100</td>\n",
       "      <td>88</td>\n",
       "      <td>0.88</td>\n",
       "      <td>96</td>\n",
       "      <td>0.96</td>\n",
       "      <td>90</td>\n",
       "      <td>0.90</td>\n",
       "      <td>95</td>\n",
       "      <td>0.95</td>\n",
       "      <td>97</td>\n",
       "      <td>0.97</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>P31</td>\n",
       "      <td>98</td>\n",
       "      <td>0.98</td>\n",
       "      <td>100</td>\n",
       "      <td>66</td>\n",
       "      <td>0.66</td>\n",
       "      <td>89</td>\n",
       "      <td>0.89</td>\n",
       "      <td>82</td>\n",
       "      <td>0.82</td>\n",
       "      <td>99</td>\n",
       "      <td>0.99</td>\n",
       "      <td>82</td>\n",
       "      <td>0.82</td>\n",
       "      <td>Odor</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   participant  hédonicité_absolue_brute  hédonicité_absolue  longueur_totale   \n",
       "0          P01                        85                0.85              100  \\\n",
       "1          P02                        96                0.96              100   \n",
       "2          P03                       100                1.00              100   \n",
       "3          P04                        86                0.86              100   \n",
       "4          P05                        95                0.95              100   \n",
       "5          P06                        89                0.89              100   \n",
       "6          P07                        97                0.97              100   \n",
       "7          P08                        94                0.94              100   \n",
       "8          P09                        99                0.99              100   \n",
       "9          P10                        96                0.96              100   \n",
       "10         P11                        92                0.92              100   \n",
       "11         P12                        90                0.90              100   \n",
       "12         P13                        98                0.98              100   \n",
       "13         P14                        94                0.94              100   \n",
       "14         P15                        79                0.79              100   \n",
       "15         P16                        99                0.99              100   \n",
       "16         P17                        88                0.88              100   \n",
       "17         P18                        97                0.97              100   \n",
       "18         P19                       100                1.00              100   \n",
       "19         P20                       100                1.00              100   \n",
       "20         P21                        93                0.93              100   \n",
       "21         P23                        97                0.97              100   \n",
       "22         P24                        81                0.81              100   \n",
       "23         P25                        90                0.90              100   \n",
       "24         P26                       100                1.00              100   \n",
       "25         P27                        88                0.88              100   \n",
       "26         P28                        85                0.85              100   \n",
       "27         P29                        86                0.86              100   \n",
       "28         P30                        95                0.95              100   \n",
       "29         P31                        98                0.98              100   \n",
       "\n",
       "    intensité_relative_brute  intensité_relative  hédonicité_relative_brute   \n",
       "0                         87                0.87                         85  \\\n",
       "1                         96                0.96                         99   \n",
       "2                         86                0.86                         80   \n",
       "3                         65                0.65                         81   \n",
       "4                         73                0.73                         86   \n",
       "5                         95                0.95                         87   \n",
       "6                         96                0.96                         93   \n",
       "7                         84                0.84                         87   \n",
       "8                         59                0.59                         94   \n",
       "9                         98                0.98                         97   \n",
       "10                        71                0.71                         86   \n",
       "11                        94                0.94                         95   \n",
       "12                        81                0.81                         91   \n",
       "13                        98                0.98                         94   \n",
       "14                        89                0.89                         74   \n",
       "15                        65                0.65                         81   \n",
       "16                        88                0.88                         94   \n",
       "17                        74                0.74                         93   \n",
       "18                        74                0.74                         99   \n",
       "19                        85                0.85                         98   \n",
       "20                        83                0.83                         84   \n",
       "21                        85                0.85                         98   \n",
       "22                        83                0.83                         79   \n",
       "23                        80                0.80                         96   \n",
       "24                        89                0.89                         97   \n",
       "25                        94                0.94                         93   \n",
       "26                        96                0.96                        100   \n",
       "27                        84                0.84                         92   \n",
       "28                        88                0.88                         96   \n",
       "29                        66                0.66                         89   \n",
       "\n",
       "    hédonicité_relative  eveil_relatif_brute  eveil_relatif   \n",
       "0                  0.85                   74           0.74  \\\n",
       "1                  0.99                   96           0.96   \n",
       "2                  0.80                  100           1.00   \n",
       "3                  0.81                   51           0.51   \n",
       "4                  0.86                   83           0.83   \n",
       "5                  0.87                   90           0.90   \n",
       "6                  0.93                   84           0.84   \n",
       "7                  0.87                   64           0.64   \n",
       "8                  0.94                   85           0.85   \n",
       "9                  0.97                   92           0.92   \n",
       "10                 0.86                   63           0.63   \n",
       "11                 0.95                   95           0.95   \n",
       "12                 0.91                   68           0.68   \n",
       "13                 0.94                   67           0.67   \n",
       "14                 0.74                   84           0.84   \n",
       "15                 0.81                   73           0.73   \n",
       "16                 0.94                   78           0.78   \n",
       "17                 0.93                   65           0.65   \n",
       "18                 0.99                   93           0.93   \n",
       "19                 0.98                   73           0.73   \n",
       "20                 0.84                   58           0.58   \n",
       "21                 0.98                   79           0.79   \n",
       "22                 0.79                   76           0.76   \n",
       "23                 0.96                   72           0.72   \n",
       "24                 0.97                   61           0.61   \n",
       "25                 0.93                   99           0.99   \n",
       "26                 1.00                   98           0.98   \n",
       "27                 0.92                   85           0.85   \n",
       "28                 0.96                   90           0.90   \n",
       "29                 0.89                   82           0.82   \n",
       "\n",
       "    familarité_relative_brute  familiarité_relative   \n",
       "0                          77                  0.77  \\\n",
       "1                          99                  0.99   \n",
       "2                         100                  1.00   \n",
       "3                          76                  0.76   \n",
       "4                          91                  0.91   \n",
       "5                          81                  0.81   \n",
       "6                          97                  0.97   \n",
       "7                          70                  0.70   \n",
       "8                          26                  0.26   \n",
       "9                          94                  0.94   \n",
       "10                         85                  0.85   \n",
       "11                         95                  0.95   \n",
       "12                         97                  0.97   \n",
       "13                         96                  0.96   \n",
       "14                         64                  0.64   \n",
       "15                         96                  0.96   \n",
       "16                        100                  1.00   \n",
       "17                         94                  0.94   \n",
       "18                         85                  0.85   \n",
       "19                         62                  0.62   \n",
       "20                         69                  0.69   \n",
       "21                         94                  0.94   \n",
       "22                         65                  0.65   \n",
       "23                         77                  0.77   \n",
       "24                         76                  0.76   \n",
       "25                         99                  0.99   \n",
       "26                         96                  0.96   \n",
       "27                         97                  0.97   \n",
       "28                         95                  0.95   \n",
       "29                         99                  0.99   \n",
       "\n",
       "    valence_émotionnelle_relative_brute  valence_émotionnelle_relative   \n",
       "0                                    86                           0.86  \\\n",
       "1                                    99                           0.99   \n",
       "2                                    83                           0.83   \n",
       "3                                    84                           0.84   \n",
       "4                                    92                           0.92   \n",
       "5                                    91                           0.91   \n",
       "6                                   100                           1.00   \n",
       "7                                    90                           0.90   \n",
       "8                                    88                           0.88   \n",
       "9                                    96                           0.96   \n",
       "10                                   75                           0.75   \n",
       "11                                   90                           0.90   \n",
       "12                                   91                           0.91   \n",
       "13                                   95                           0.95   \n",
       "14                                   91                           0.91   \n",
       "15                                   81                           0.81   \n",
       "16                                  100                           1.00   \n",
       "17                                   95                           0.95   \n",
       "18                                   92                           0.92   \n",
       "19                                   97                           0.97   \n",
       "20                                   67                           0.67   \n",
       "21                                   99                           0.99   \n",
       "22                                   82                           0.82   \n",
       "23                                   85                           0.85   \n",
       "24                                   83                           0.83   \n",
       "25                                   98                           0.98   \n",
       "26                                   96                           0.96   \n",
       "27                                   80                           0.80   \n",
       "28                                   97                           0.97   \n",
       "29                                   82                           0.82   \n",
       "\n",
       "   Stimulus             Odor_Label  \n",
       "0      Odor      Feuille d’Olivier  \n",
       "1      Odor          Pêche Lavande  \n",
       "2      Odor                   Rose  \n",
       "3      Odor      Floral Printanier  \n",
       "4      Odor          Pêche Lavande  \n",
       "5      Odor      Floral Printanier  \n",
       "6      Odor      Floral Printanier  \n",
       "7      Odor      Floral Printanier  \n",
       "8      Odor      Floral Printanier  \n",
       "9      Odor      Feuille d'Olivier  \n",
       "10     Odor  Fleur d'oranger épicé  \n",
       "11     Odor      Feuille d'Olivier  \n",
       "12     Odor      Floral printanier  \n",
       "13     Odor      Feuille d'Olivier  \n",
       "14     Odor      Floral Printanier  \n",
       "15     Odor      Floral Printanier  \n",
       "16     Odor      Floral Printanier  \n",
       "17     Odor      Floral Printanier  \n",
       "18     Odor          Pêche Lavande  \n",
       "19     Odor                   Rose  \n",
       "20     Odor      Floral Printanier  \n",
       "21     Odor  Fleur d'oranger épicé  \n",
       "22     Odor                   Rose  \n",
       "23     Odor                   Rose  \n",
       "24     Odor                   Rose  \n",
       "25     Odor  Fleur d'oranger épicé  \n",
       "26     Odor      Feuille d'Olivier  \n",
       "27     Odor      Floral Printanier  \n",
       "28     Odor          Pêche Lavande  \n",
       "29     Odor      Floral Printanier  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "odeurs_choisies = cotations_relatives_odeurs.groupby('participant').max(True).iloc[:,2:].reset_index()\n",
    "odeurs_choisies['Stimulus'] = 'Odor'\n",
    "odeurs_choisies['Odor_Label'] = odeurs_choisies['participant'].map(label_odeurs_choisies)\n",
    "odeurs_choisies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e8b0576a-4e11-42ff-a7f3-6908fa078f35",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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sTLvO226LI0eOiLZt2worKythYWEhPD09xU8//aR9PSsrS3z11VfC3t5eaDQanc+Ff11+LYQQ4eHhwsfHR1haWooSJUqI1q1bi2PHjums8/zy639f2vx8mx84cEC7zMnJKc9L3f/9/yXEs8vWx44dK6pUqSJMTExE6dKlRZMmTcSPP/6Y6//m119/FfXr1xfm5ubCyspKeHh4iG+//VbcuHFD+3X06tVLVKpUSZiamgoHBwfRsWNHnW1PpEQaIf51LJGIiIhIJThGhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUq8jPI5OTk4MbN27AysrqjW4MR0RERIVPCIFHjx6hfPnyMDDI/7hLkS8yN27c0Os04URERKQ/SUlJqFixYr6vF/ki8/wuxElJSXqdLpyIiIjenZSUFDg6Omr/juenyBeZ56eTrK2tWWSIiIhU5lXDQjjYl4iIiFSLRYaIiIhUi0WGiIiIVItFRg8OHTqETp06oXz58tBoNNiyZYv2tczMTIwePRoeHh6wsLBA+fLl0bdvX9y4cUNeYCIiIpVikdGDtLQ01K5dG/Pnz8/1Wnp6OsLDwzFu3DiEh4cjJCQEly5dQufOnSUkJSIiUjeNEELIDqFPKSkpsLGxwcOHD6VctaTRaLB582b4+vrmu86pU6fQsGFDXL16FZUqVSq8cERERApV0L/fPCKjAA8fPoRGo0HJkiVlRyEiIlIVFhnJnjx5gtGjR6NXr16c54aIiOg1schIlJmZie7du0MIgQULFsiOQ0REpDpFfmZfpXpeYq5evYr9+/fzaAwREdEbYJGR4HmJiYmJwYEDB1CqVCnZkYiIiFRJ6qmlojrfSmpqKiIjIxEZGQkAiI+PR2RkJBITE5GZmYmPPvoIYWFhWLNmDbKzs3Hr1i3cunULT58+lRuciIhIZaQWmaI630pYWBjq1q2LunXrAgACAgJQt25djB8/HtevX8e2bdtw7do11KlTB+XKldM+jh07Jjk5ERGRuihmHhl9zbciex4ZIiIien0F/futqjEyBZlvJSMjAxkZGdrnKSkphZCMiIiIZFBNkSnofCvTpk1DYGCgXjJUHvOHXj7um0iY/qHsCERERNKpYh6Z15lvZezYsXj48KH2kZSUVEgpiYiIqLAp/ojM6863YmpqClNT00JKR0RERDIpushwvhUiIiJ6GalFJjU1FbGxsdrnz+dbsbOzQ7ly5fDRRx8hPDwcO3bs0M63AgB2dnYwMTGRFZuIiIgUQmqRCQsLQ+vWrbXPAwICAAD+/v6YOHEitm3bBgCoU6eOzvsOHDiAVq1aFVZMIiIiUiipRaZVq1Z42TQ2CpnihoiIiBRKFVctEREREeWFRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVEtqkTl06BA6deqE8uXLQ6PRYMuWLTqvCyEwfvx4lCtXDubm5vD29kZMTIycsERERKQ4UotMWloaateujfnz5+f5+syZMzFv3jwsXLgQJ06cgIWFBXx8fPDkyZNCTkpERERKZCTzk7dv3x7t27fP8zUhBIKDg/H999+jS5cuAIBVq1ahTJky2LJlC3r27FmYUYmIiEiBFDtGJj4+Hrdu3YK3t7d2mY2NDd577z0cP3483/dlZGQgJSVF50FERERFk2KLzK1btwAAZcqU0VlepkwZ7Wt5mTZtGmxsbLQPR0dHveYkIiIieRRbZN7U2LFj8fDhQ+0jKSlJdiQiIiLSE8UWmbJlywIAbt++rbP89u3b2tfyYmpqCmtra50HERERFU2KLTLOzs4oW7Ys9u3bp12WkpKCEydOoHHjxhKTERERkVJIvWopNTUVsbGx2ufx8fGIjIyEnZ0dKlWqhBEjRmDKlClwc3ODs7Mzxo0bh/Lly8PX11deaCIiIlIMqUUmLCwMrVu31j4PCAgAAPj7+2PFihX49ttvkZaWhs8++wzJyclo1qwZdu7cCTMzM1mRiYiISEE0QgghO4Q+paSkwMbGBg8fPnzr8TKVx/zxjlK9vYTpH8qOQEREpDcF/fut2DEyRERERK/CIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqqXoIpOdnY1x48bB2dkZ5ubmcHV1xeTJkyGEkB2NiIiIFMBIdoCXmTFjBhYsWICVK1eiVq1aCAsLQ//+/WFjY4Nhw4bJjkdERESSKbrIHDt2DF26dMGHH34IAKhcuTLWrVuHkydP5vuejIwMZGRkaJ+npKToPScRERHJoehTS02aNMG+fftw+fJlAEBUVBSOHDmC9u3b5/ueadOmwcbGRvtwdHQsrLhERERUyBR9RGbMmDFISUlB9erVYWhoiOzsbAQFBcHPzy/f94wdOxYBAQHa5ykpKSwzRERERZSii8z69euxZs0arF27FrVq1UJkZCRGjBiB8uXLw9/fP8/3mJqawtTUtJCTEhERkQyKLjKjRo3CmDFj0LNnTwCAh4cHrl69imnTpuVbZIiIiKj4UPQYmfT0dBgY6EY0NDRETk6OpERERESkJIo+ItOpUycEBQWhUqVKqFWrFiIiIjB79mwMGDBAdjQiIiJSAEUXmZ9++gnjxo3DkCFDcOfOHZQvXx6DBw/G+PHjZUcjIiIiBVB0kbGyskJwcDCCg4NlRyEiIiIFUvQYGSIiIqKXYZEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1TJ6nZUNDAyg0Wheuo5Go0FWVtZbhSIiIiIqiNcqMps3b873tePHj2PevHnIycl561BEREREBfFaRaZLly65ll26dAljxozB9u3b4efnh0mTJr2zcEREREQv88ZjZG7cuIFPP/0UHh4eyMrKQmRkJFauXAknJ6d3mY+IiIgoX69dZB4+fIjRo0ejSpUqiI6Oxr59+7B9+3a4u7vrIx8RERFRvl7r1NLMmTMxY8YMlC1bFuvWrcvzVBMRERFRYdEIIURBVzYwMIC5uTm8vb1haGiY73ohISHvJBwAXL9+HaNHj8Zff/2F9PR0VKlSBcuXL4eXl1eB3p+SkgIbGxs8fPgQ1tbWb5Wl8pg/3ur971LC9A9lRyAiItKbgv79fq0jMn379n3l5dfv0oMHD9C0aVO0bt0af/31F+zt7RETEwNbW9tCy0BERETK9VpFZsWKFXqKkbcZM2bA0dERy5cv1y5zdnYu1AxERESkXIqe2Xfbtm3w8vLCxx9/DAcHB9StWxeLFy9+6XsyMjKQkpKi8yAiIqKiSdFF5sqVK1iwYAHc3Nywa9cufPHFFxg2bBhWrlyZ73umTZsGGxsb7cPR0bEQExMREVFheq3BvoXNxMQEXl5eOHbsmHbZsGHDcOrUKRw/fjzP92RkZCAjI0P7PCUlBY6OjhzsS0REpCIFHeyr6CMy5cqVQ82aNXWW1ahRA4mJifm+x9TUFNbW1joPIiIiKpoUXWSaNm2KS5cu6Sy7fPkyZw8mIiIiAAovMl9//TVCQ0MxdepUxMbGYu3atfj1118xdOhQ2dGIiIhIARRdZBo0aIDNmzdj3bp1cHd3x+TJkxEcHAw/Pz/Z0YiIiEgBXmseGRk6duyIjh07yo5BRERECqToIzJEREREL8MiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ0RERKrFIkNERESqxSJDREREqsUiQ1JNnDgRGo1G51G9enXZsYiISCUUf68lKvpq1aqFvXv3ap8bGfHbkoiICoZ/MUg6IyMjlC1bVnYMIiJSIZ5aIuliYmJQvnx5uLi4wM/PD4mJibIjERGRSrDIkFTvvfceVqxYgZ07d2LBggWIj49H8+bN8ejRI9nRiIhIBXhqiaRq37699t+enp5477334OTkhPXr12PgwIESkxERkRrwiAwpSsmSJVG1alXExsbKjkJERCrAIkOKkpqairi4OJQrV052FCIiUgEWGZJq5MiROHjwIBISEnDs2DF07doVhoaG6NWrl+xoRESkAhwjQ1Jdu3YNvXr1wr1792Bvb49mzZohNDQU9vb2sqMREZEKsMiQVL/99pvsCEREpGI8tURERESqxSMy9NYqj/lDdgQdCdM/lB2BiIgKCY/IEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQqcD06dOh0WgwYsQI2VEUh9uGqHhjkSFSuFOnTmHRokXw9PSUHUVxuG2IiEWGSMFSU1Ph5+eHxYsXw9bWVnYcReG2ISKARYZI0YYOHYoPP/wQ3t7esqMoDrcNEQGAkewARJS33377DeHh4Th16pTsKIrDbUNEz7HIEClQUlIShg8fjj179sDMzEx2HEXhtiGiF7HIECnQ6dOncefOHdSrV0+7LDs7G4cOHcLPP/+MjIwMGBoaSkwoD7cNEb2IRYZIgdq0aYOzZ8/qLOvfvz+qV6+O0aNHF+s/1Nw2RPQiVRWZ6dOnY+zYsRg+fDiCg4NlxyHSGysrK7i7u+sss7CwQKlSpXItL264bYjoRaq5aonzRRAREdG/qeKIzIvzRUyZMkV2HCIp/v77b9kRFIvbhqj4UsURmdeZLyIjIwMpKSk6DyIiIiqaFH9E5nXni5g2bRoCAwP1nIqoYCqP+UN2BB0J0z+UHUGL24aI3gVFH5F5Pl/EmjVrCjxfxNixY/Hw4UPtIykpSc8piYiISBZFH5F5k/kiTE1NYWpqWthRiYiISAJFFxnOF0FEREQvo+giw/kiiIiI6GUUPUaGiIiI6GUUfUQmL5wvgoiIiJ7jERkiIiJSLRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIqIiYsGCBfD09IS1tTWsra3RuHFj/PXXX7JjEekViwwRURFRsWJFTJ8+HadPn0ZYWBjef/99dOnSBdHR0bKjEemN6m4aSUREeevUqZPO86CgICxYsAChoaGoVauWpFRE+sUiQ0RUBGVnZ2PDhg1IS0tD48aNZcch0hsWGSKiIuTs2bNo3Lgxnjx5AktLS2zevBk1a9aUHYtIbzhGhoioCKlWrRoiIyNx4sQJfPHFF/D398f58+dlxyLSGx6RISIqQkxMTFClShUAQP369XHq1CnMnTsXixYtkpyMSD94RIaIqAjLyclBRkaG7BhEesMjMkRERcTYsWPRvn17VKpUCY8ePcLatWvx999/Y9euXbKjEekNiwwRURFx584d9O3bFzdv3oSNjQ08PT2xa9cutG3bVnY0Ir1hkSEiKiKWLl0qOwJRoeMYGSIiIlItHpEhIlKYymP+kB1BK2H6h7IjEL0Uj8gQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRarHIEBERkWqxyBAREZFqscgQERGRaim6yEybNg0NGjSAlZUVHBwc4Ovri0uXLsmORURERAqh6CJz8OBBDB06FKGhodizZw8yMzPRrl07pKWlyY5GRERECmAkO8DL7Ny5U+f5ihUr4ODggNOnT6NFixZ5vicjIwMZGRna5ykpKXrNSERERPIo+ojMvz18+BAAYGdnl+8606ZNg42Njfbh6OhYWPGIiIiokKmmyOTk5GDEiBFo2rQp3N3d811v7NixePjwofaRlJRUiCmJiIioMCn61NKLhg4dinPnzuHIkSMvXc/U1BSmpqaFlIqIiIhkUkWR+fLLL7Fjxw4cOnQIFStWlB2HiIiIFELRRUYIga+++gqbN2/G33//DWdnZ9mRiIiISEEUXWSGDh2KtWvXYuvWrbCyssKtW7cAADY2NjA3N5ecjoiIiGRT9GDfBQsW4OHDh2jVqhXKlSunffz++++yoxEREZECKPqIjBBCdgQiIiJSMEUfkSEiIiJ6GRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIiIqFg4dOoROnTqhfPny0Gg02LJli+xIiqHmbcMiQ0RExUJaWhpq166N+fPny46iOGreNoq+aSQREdG70r59e7Rv3152DEVS87bhERkiIiJSLRYZIiIiUi0WGSIiIlItFhkiIiJSLRYZIiIiUi1etURERMVCamoqYmNjtc/j4+MRGRkJOzs7VKpUSWIy+dS8bVhkiIioWAgLC0Pr1q21zwMCAgAA/v7+WLFihaRUyqDmbcMiQ0RExUKrVq0ghJAdQ5HUvG04RoaIiIhUi0dkiIhINSqP+UN2BK2E6R/KjqCjuG4bHpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVYpEhIiIi1WKRISIiItVikSEiIiLVUkWRmT9/PipXrgwzMzO89957OHnypOxIREREpACKLzK///47AgICMGHCBISHh6N27drw8fHBnTt3ZEcjIiIiyRRfZGbPno1PP/0U/fv3R82aNbFw4UKUKFECy5Ytkx2NiIiIJDOSHeBlnj59itOnT2Ps2LHaZQYGBvD29sbx48fzfE9GRgYyMjK0zx8+fAgASElJees8ORnpb/0x3pV38fW8K0raLgC3zctw2+SP2yZvStouALfNyxS1bfP8YwghXr6iULDr168LAOLYsWM6y0eNGiUaNmyY53smTJggAPDBBx988MEHH0XgkZSU9NKuoOgjMm9i7NixCAgI0D7PycnB/fv3UapUKWg0GonJnrVLR0dHJCUlwdraWmoWpeG2yR+3Tf64bfLHbZM/bpu8KW27CCHw6NEjlC9f/qXrKbrIlC5dGoaGhrh9+7bO8tu3b6Ns2bJ5vsfU1BSmpqY6y0qWLKmviG/E2tpaEd8kSsRtkz9um/xx2+SP2yZ/3DZ5U9J2sbGxeeU6ih7sa2Jigvr162Pfvn3aZTk5Odi3bx8aN24sMRkREREpgaKPyABAQEAA/P394eXlhYYNGyI4OBhpaWno37+/7GhEREQkmeKLTI8ePXD37l2MHz8et27dQp06dbBz506UKVNGdrTXZmpqigkTJuQ69UXcNi/DbZM/bpv8cdvkj9smb2rdLhohXnVdExEREZEyKXqMDBEREdHLsMgQERGRarHIEBERkWqxyBAREZFqscjoSVZWFiZNmoRr167JjkJUJGRmZqJNmzaIiYmRHYVUJDs7G4cOHUJycrLsKIpSlLYLi4yeGBkZ4YcffkBWVpbsKKRSsbGx2LVrFx4/fgwAr75xWhFnbGyMM2fOyI6haIcPH0afPn3QuHFjXL9+HQCwevVqHDlyRHIyeQwNDdGuXTs8ePBAdhRFKUrbhUVGj95//30cPHhQdgxSmXv37sHb2xtVq1ZFhw4dcPPmTQDAwIED8c0330hOJ1efPn2wdOlS2TEU4cSJE8jMzNQ+37RpE3x8fGBubo6IiAhkZGQAAB4+fIipU6fKiqkI7u7uuHLliuwYilNUtoviJ8RTs/bt22PMmDE4e/Ys6tevDwsLC53XO3fuLCmZsmRlZeHvv/9GXFwcevfuDSsrK9y4cQPW1tawtLSUHa/Qff311zAyMkJiYiJq1KihXd6jRw8EBARg1qxZEtPJlZWVhWXLlmHv3r15/kzNnj1bUrLCd+LECYwZMwbbtm2DlZUVpkyZgoULF6Jv37747bfftOs1bdoUU6ZMkZhUvilTpmDkyJGYPHlynt83SrmvUGErKtuFE+LpkYFB/ge8NBoNsrOzCzGNMl29ehUffPABEhMTkZGRgcuXL8PFxQXDhw9HRkYGFi5cKDtioStbtix27dqF2rVrw8rKClFRUXBxccGVK1fg6emJ1NRU2RGlad26db6vaTQa7N+/vxDTyDdr1iysWbMG4eHhKFGiBM6fP4/KlSvn+r6pWbMmnjx5IjuuNC/+LtZoNNp/CyGK9e/iorJdeERGj3JycmRHULzhw4fDy8sLUVFRKFWqlHZ5165d8emnn0pMJk9aWhpKlCiRa/n9+/dVN3X4u3bgwAHZERTlm2++0d5At2zZsoiNjUXlypV11jly5AhcXFwkpFMOft/krahsFxaZQvLkyROYmZnJjqE4hw8fxrFjx2BiYqKzvHLlytrBisVN8+bNsWrVKkyePBnAsz2lnJwczJw586VHJIqT2NhYxMXFoUWLFjA3N9fuQRZHTZo0AQB8+umnGD58OJYtWwaNRoMbN27g+PHjGDlyJMaNGyc5pVwtW7aUHUGRisp24WBfPcrOzsbkyZNRoUIFWFpaagdVjRs3jgMW/7+cnJw8D19eu3YNVlZWEhLJN3PmTPz6669o3749nj59im+//Rbu7u44dOgQZsyYITueVPfu3UObNm04EDoPY8aMQe/evdGmTRukpqaiRYsWGDRoEAYPHoyvvvpKdjzpnl/R1aRJE17R9YKisF1YZPQoKCgIK1aswMyZM3WOOLi7u2PJkiUSkylHu3btEBwcrH2u0WiQmpqKCRMmoEOHDvKCSeTu7o7Lly+jWbNm6NKlC9LS0tCtWzdERETA1dVVdjypvv76axgbGyMxMVHn9FuPHj2wc+dOicnk02g0+O6773D//n2cO3cOoaGhuHv3rvbIXnH24hVd4eHhvKLr/ysy20WQ3ri6uoq9e/cKIYSwtLQUcXFxQgghLly4IEqWLCkzmmIkJSWJmjVriho1aggjIyPRqFEjUapUKVGtWjVx+/Zt2fFIYcqUKSMiIyOFELo/U3FxccLCwkJmNOmSk5PFvXv3ci2/d++eePjwoYREylGnTh2xcuVKIYTu9014eLgoU6aMzGhSFZXtwjEyenT9+nVUqVIl1/KcnByd+R+Ks4oVKyIqKgq///47oqKikJqaioEDB8LPzw/m5uay4xWa15nozdPTU49JlI0DofPXs2dPdOrUCUOGDNFZvn79emzbtg1//vmnpGTyXbp0CS1atMi13MbGpkjMbPumisp2YZHRo5o1a+Lw4cNwcnLSWb5x40bUrVtXUirlMTIygp+fH/z8/GRHkaZOnTrQaDS5Bq2K/z87wovL1HJJpD5wIHT+Tpw4kec8Oq1atcJ3330nIZFy8IquvBWV7cIio0fjx4+Hv78/rl+/jpycHISEhODSpUtYtWoVduzYITueIqxcuRKlS5fGhx9+CAD49ttv8euvv6JmzZpYt25drhJYVMXHx2v/HRERgZEjR2LUqFHaS2uPHz+OWbNmYebMmbIiKsLMmTPRpk0bhIWFaQdCR0dH4/79+zh69KjseFJlZGTkeUuUzMxM7W0uiite0ZW3IrNdZJ/bKuoOHTokvL29hb29vTA3NxdNmzYVu3btkh1LMapWrSr27dsnhBDi2LFjwtzcXCxatEh06tRJdO3aVXI6ORo0aCD++OOPXMv/+OMPUa9ePQmJlCU5OVlMmTJFfPzxx6J9+/biu+++Ezdu3JAdS7pWrVqJL7/8MtfyIUOGiGbNmklIpBw5OTliypQpwsLCQmg0GqHRaISZmZn4/vvvZUeTqqhsF87sS1KVKFECFy9eRKVKlTB69GjcvHkTq1atQnR0NFq1aoW7d+/Kjljonl9B8OLtCQDgwoULqFevXrHfu6a8HT16FN7e3mjQoAHatGkDANi3bx9OnTqF3bt3o3nz5pITyvf06VPExsYiNTUVNWvWLJa3QMmL2rcLTy2RVJaWlrh37x4qVaqE3bt3IyAgAABgZmZWbP9g16hRA9OmTcOSJUu0l+0/ffoU06ZNy1VuioMzZ87A3d0dBgYGrxwUXZwHQjdt2hTHjx/HDz/8gPXr18Pc3Byenp5YunQp3NzcZMdTBBMTE9SsWVN2DMVR+3bhEZl3zM7ODpcvX0bp0qVha2v70tlG79+/X4jJlMnPzw8XL15E3bp1sW7dOiQmJqJUqVLYtm0b/vvf/+LcuXOyIxa6kydPolOnThBCaP8wnzlzBhqNBtu3b0fDhg0lJyxcBgYGuHXrFhwcHGBgYKAdFP1varo3DOlft27dsGLFClhbW6Nbt24vXTckJKSQUslXFLcLj8i8Y3PmzNHOSPviRG+Ut/nz5+P7779HUlISNm3apL3f0unTp9GrVy/J6eRo2LAhrly5gjVr1uDixYsAnk341rt371x3py0O4uPjYW9vr/03/Z+UlBTtHYpTUlJeuq5a7mT8rtjY2Gh3JG1sbCSnUY6iuF14RIaIVIP3LNNlaGiImzdv6hyt+jehsjsZE70uHpHRs5ycHMTGxuLOnTu57oad10RExVFycjKWLl2KCxcuAABq1aqFAQMGFJm9hTcRExODAwcO5Pl9M378eEmp5HNwcEDXrl3Rp08ftGnTBgYGxfsuK/v374ednR2AonMnY32YMmUK/Pz84OzsLDsK6QGPyOhRaGgoevfujatXr+Y6p889pGfCwsK09/p4Pvbj1KlTePz4MXbv3o169epJTlj4Fi9ejC+++AKlS5dG2bJldfayNRoNwsPDJaaTa/PmzVi7di3++OMP2NjYoEePHujTpw+8vLxkRyMFq127Ns6dO4f33nsPffr0Qffu3VG6dGnZsaS7ffs2Ro4ciX379uHOnTu5/k6p5W8Ui4we1alTB1WrVkVgYCDKlSuX67BvcT7i8Fzz5s1RpUoVLF68GEZGzw4QZmVlYdCgQbhy5QoOHTokOWHhc3JywpAhQzB69GjZURTr0aNH2LhxI9atW4f9+/fDxcUFffr0KdZHqwDgwYMHOkc3a9asif79+2uP2hRn0dHRWLNmDX777Tdcu3YNbdu2hZ+fH3x9ffO87UVx0L59eyQmJuLLL7/M829Uly5dJCV7PSwyemRhYYGoqKg877dEz5ibmyMiIgLVq1fXWX7+/Hl4eXkhPT1dUjJ5rK2tERkZqaopwmU6f/48/Pz8cObMGdXsQerDoUOH0KlTJ9jY2GiPUJ0+fRrJycnYvn07T2W/4OjRo1i7di02bNiAJ0+evHKgdFFlZWWFw4cPo06dOrKjvJXifYJZz9577z3ExsbKjqFo1tbWSExMzLU8KSlJe/VXcfPxxx9j9+7dsmMo2pMnT7B+/Xr4+vqiXr16uH//PkaNGiU7llRDhw5Fjx49EB8fj5CQEISEhODKlSvo2bMnhg4dKjueolhYWMDc3BwmJibF+ga+jo6OeU5loDYc7KtHX331Fb755hvcunULHh4eMDY21nm9OE/e9VyPHj0wcOBA/Pjjj2jSpAmAZ3tLI0eORM+ePSWnk6NKlSoYN24cQkND8/y+GTZsmKRk8u3atQtr167Fli1bYGRkhI8++gi7d+/m0QYAsbGx2LhxIwwNDbXLDA0NERAQgFWrVklMpgzx8fFYu3Yt1q5di0uXLqFly5YIDAzERx99JDuaNMHBwRgzZgwWLVqU68aRasJTS3qU1xUVL97huDgfBn/u6dOnGDVqFBYuXIisrCwIIWBiYoIhQ4YgKCgI5ubmsiMWupddWaHRaHDlypVCTKMsJUqUQMeOHeHn54cOHTrkKnnFWdOmTTFq1Cj4+vrqLN+yZQumT5+O0NBQOcEUoFGjRjh16hQ8PT3h5+eHXr16oUKFCrJjSWdra4v09HRkZWWhRIkSuX6e1DJpK4/I6BEn73o1ExMTzJ07F9OmTUNcXBwAwNXVFQsWLICzszNu3bolOWHh4/dN/m7fvl1sTzm+yrBhwzB8+HDExsaiUaNGAJ5dOTl//nxMnz5d5/YOxe1ocJs2bbBs2TJVT8OvD0Vl0lYekSEpMjIyMHHiROzZswempqbaPcnly5fj+++/h6GhIYYOHcord4iz1xbQq+bU4dFgKqpYZArB+fPnkZiYiKdPn+os79y5s6RE8o0ePRqLFi2Ct7c3jh07hrt376J///4IDQ3Ff//7X3z88cc65/qLm2vXrmHbtm15ft/Mnj1bUio5OHttwVy9erXA6zo5OekxiTIEBARg8uTJsLCw0N6MNj/F7WcqL0+ePMn1u0YtOwY8taRHV65cQdeuXXH27FmdG909/0VcnH/pbtiwAatWrULnzp1x7tw5eHp6IisrC1FRUS+90WZxsG/fPnTu3BkuLi64ePEi3N3dkZCQACFEsZwgkLPXFkxxKCevIyIiQntFUkRERL7rFeffN2lpaRg9ejTWr1+Pe/fu5XpdNX+jBOlNx44dRZcuXcTdu3eFpaWlOH/+vDh8+LBo2LChOHTokOx4UhkbG4tr165pn5uZmYkzZ85ITKQcDRo0EOPHjxdCCGFpaSni4uLEo0ePROfOncUvv/wiOR0p2apVq0STJk1EuXLlREJCghBCiDlz5ogtW7ZITkZKNGTIEFGjRg2xceNGYW5uLpYtWyYmT54sKlasKP73v//JjldgPCKjR8ePH8f+/ftRunRpGBgYwMDAAM2aNcO0adMwbNiwl+4lFHXZ2dkwMTHRPjcyMoKlpaXERMpx4cIFrFu3DsCz7fL48WNYWlpi0qRJ6NKlC7744gvJCQvXi4NUX6U4DWLdtWsXGjVqpJ0hfMGCBRg/fjxGjBiBoKAg7d50yZIlERwcrJpZWqnwbN++HatWrUKrVq3Qv39/7UzrTk5OWLNmDfz8/GRHLBAWGT3Kzs7WXmFRunRp3LhxA9WqVYOTkxMuXbokOZ1cQgj069cPpqamAJ6dn/38889hYWGhs15ISIiMeFJZWFhoz1WXK1cOcXFxqFWrFgDgn3/+kRlNijp16uicms1PcRsjc+vWLTRt2hQ7d+5ExYoV8dNPP2Hx4sXw9fXF9OnTtet5eXlh5MiREpPK0a1btwKvWxx/zwDPLq9+PoO4tbW19nLrZs2aqWqHiUVGj9zd3REVFQVnZ2e89957mDlzJkxMTPDrr78W++nn/f39dZ736dNHUhLladSoEY4cOYIaNWqgQ4cO+Oabb3D27FmEhIRoL6stTng5et78/f1haWkJHx8fREdHIz4+HnXr1s21nqmpKdLS0iQklIv3sns1FxcXxMfHo1KlSqhevTrWr1+Phg0bYvv27ShZsqTseAUn+9xWUbZz506xadMmIYQQMTExolq1akKj0YjSpUuLvXv3Sk5HShUXFyeioqKEEEKkpqaKwYMHCw8PD9GtWzftuAei52JjY4UQQtSoUUM7Fub52CohhJg3b56oW7eutHykXLNnzxZz584VQgixZ88eYWZmJkxNTYWBgYEIDg6WnK7gePl1Ibt//z5sbW2L9Uh5oje1YcMGrFu3DpcvXwYAVK1aFb179y7W08w/t2TJEkycOBGzZs3CwIEDsWTJEsTFxWHatGlYsmRJsb3lx3NnzpzRft9Uq1YNHh4ekhMpz9WrV3H69GlUqVJFXePNZDepoqx///4iJSUl1/LU1FTRv39/CYlIDQYOHCgOHDggO4aiZGdni+7duwuNRiOqVasmunTpIrp06SKqVq0qDAwMRI8ePUROTo7smNL973//E1WqVBEajUZoNBpRoUIFsWTJEtmxpDpx4oRwd3cXBgYG2u1iYGAgPDw8xMmTJ2XHk2rlypXiyZMnuZZnZGSIlStXSkj0Zlhk9MjAwEDcvn071/K7d+8KQ0NDCYlIDTp37ixMTU1FxYoVxciRI0VkZKTsSNLNnj1b2NnZie3bt+d6bevWrcLOzk7MmTOn8IMpVFpaWp6/e4qb6OhoYWlpKRo0aCDWrl0rIiIiREREhFizZo3w8vISVlZWIjo6WnZMafL7G/XPP/8IAwMDCYneDE8t6UFKSgqEELC1tUVMTAzs7e21r2VnZ2P79u0YM2YMbty4ITElKdmDBw+wYcMGrF27FocPH0b16tXh5+eH3r17q/outW/K09MTI0aMwIABA/J8fenSpZg7d+5rXapNRV/37t2RlZWFTZs25TqdL4RAt27dYGxsjPXr10tKKJeBgQFu376t8zcKAKKiotC6dWvV3DSSRUYP8ptG/TmNRoPAwEB89913hZiK1OratWtYt24dli1bhpiYGGRlZcmOVOjMzc1x6dIlVKpUKc/Xr169iurVq+Px48eFnIyUzN7eHn/99Re8vLzyfP3UqVPo0KED7t69W8jJ5Kpbty40Gg2ioqJQq1YtGBn93wXM2dnZiI+PxwcffKCagsfLr/XgwIEDEELg/fffx6ZNm7TTqwPP7vbs5OSE8uXLS0xIapGZmYmwsDCcOHECCQkJKFOmjOxIUpibmyM5OTnfIpOSkgIzM7NCTkVK9+jRo5f+zJQtWxaPHj0qxETK4OvrCwCIjIyEj4+PzmSkJiYmqFy5Mv7zn/9ISvf6WGT0oGXLlgCezX/h6Oj4yrvSEv3bgQMHsHbtWmzatAk5OTno1q0bduzYgffff192NCkaN26MBQsWYMGCBXm+Pn/+fDRu3LiQU5HSOTk54eTJk3B0dMzz9RMnThTLe1RNmDABAFC5cmX06NFD9TsBLDJ65OTkhOTkZJw8eRJ37txBTk6Ozut9+/aVlIyUrEKFCrh//z4++OAD/Prrr+jUqZN2BuTi6rvvvkOrVq1w7949jBw5EtWrV4cQAhcuXMCsWbOwdevWYn1DyczMTHzwwQdYuHAh3NzcZMdRjJ49eyIgIADVqlWDu7u7zmtnz57FyJEji/Xv4ecTkz59+jTPv1H5HQFVGo6R0aPt27fDz88PqampsLa21hk3o9FoVDOQigrX4sWL8fHHH6trZs1CsHnzZnz22We5fm5sbW2xaNEiVR0K1wd7e3scO3aMReYFT548QZs2bXDixAm0bdsWNWrU0BbgvXv3omHDhti/f7/qj0i8qZiYGAwYMADHjh3TWS6EUNUtP1hk9Khq1aro0KEDpk6dihIlSsiOQ6R66enp2LVrF2JiYgA8+xlr164df74AfP311zA1NdW5zxI9O9owZ86cXBMp9uzZU7vNiqumTZvCyMgIY8aMQbly5XJdpFK7dm1JyV4Pi4weWVhY4OzZs8X+vkr0+sLCwrB+/XokJiZqbyD5XHG9wR293FdffYVVq1bBzc0N9evXz3UD1tmzZ0tKRkplYWGB06dPo3r16rKjvBWOkdEjHx8fhIWFscjQa/ntt9/Qt29f+Pj4YPfu3WjXrh0uX76M27dvo2vXrrLjSbFq1Sqd58V5XEN+zp07h3r16gGA9sjDc7wlCuWlZs2a+Oeff2THeGs8IqNHS5cuxaRJk9C/f394eHjA2NhY5/XOnTtLSkZK5unpicGDB2Po0KGwsrLS3kF98ODBKFeuHAIDA2VHLHStW7fW/luj0WD//v0S05BaGBgY4IMPPkBQUFCedwYv7vbv34/vv/8eU6dOzfNvlLW1taRkr4dFRo9edtm1mgZSUeGysLBAdHQ0KleujFKlSuHvv/+Gh4cHLly4gPfffx83b96UHZEULDY2FnFxcWjRogXMzc21AzeLoxUrViAmJgZ79uzByZMnZcdRnOd/o/Ka9VhNf6N4akmP/n0pG1FB2NraaifpqlChAs6dOwcPDw8kJycjPT1dcjpSqnv37qF79+44cOAANBoNYmJi4OLigoEDB8LW1hazZs2SHbHQ9evXDwAQFBQkN4hCFZUpC1hkiBSmRYsW2LNnDzw8PPDxxx9j+PDh2L9/P/bs2YM2bdrIjlfoAgICCrxucR7Q+vXXX8PY2BiJiYmoUaOGdnmPHj0QEBBQLIsMvdzzyVvVjkXmHZs3bx4+++wzmJmZYd68eS9dd9iwYYWUitTk559/xpMnTwA8mwjO2NgYx44dw3/+8x98//33ktMVvoiICJ3n4eHhyMrKQrVq1QA8G9hqaGiI+vXry4inGLt378auXbtQsWJFneVubm64evWqpFTysADn7cyZM3B3d4eBgcErb7Lq6elZSKneDsfIvGPOzs4ICwtDqVKl4OzsnO96Go0GV65cKcRkpHbp6emIjIxEkyZNZEeRZvbs2fj777+xcuVK2NraAnh2p/D+/fujefPm+OabbyQnlMfKygrh4eFwc3PTDhJ3cXFBWFgYfHx8cO/ePdkRC9WLA8SBlxfg4jR43MDAALdu3YKDg4P2Bsd51QA1jZFhkSFSiaioKNSrV081v1z0oUKFCti9ezdq1aqls/zcuXNo164dbty4ISmZfB06dED9+vUxefJkWFlZ4cyZM3ByckLPnj2Rk5ODjRs3yo4oDQvw/7l69SoqVaoEjUbzyiN1arkPFU8t6UlmZiaqV6+OHTt26JyvJqI3l5KSgrt37+Zafvfu3WJ5F+MXzZw5E23atEFYWBiePn2Kb7/9FtHR0bh//z6OHj0qO55Us2bNwu7du7UlBng2qH7KlClo165dsSoyz8tJZmYmAgMDMW7cuJeePVAD3pZZT4yNjbXjHIjo3ejatSv69++PkJAQXLt2DdeuXcOmTZswcOBAdOvWTXY8qdzd3XH58mU0a9YMXbp0QVpaGrp164aIiAi4urrKjicVC3BuxsbG2LRpk+wY7wRPLenR1KlTcfnyZSxZsgRGRjz4RW+Hp5aejRMaOXIkli1bhszMTACAkZERBg4ciB9++CHXtPxEwLOZoA8fPoxZs2ahYcOGAIATJ05g1KhRaN68OVauXCk5oRz+/v6oU6cOvv76a9lR3gqLjB517doV+/btg6WlJTw8PHL9kuU9c+hF27Zte+nr8fHxCAgIKNZF5rm0tDTExcUBAFxdXVlggHyvQNFoNDAzM0OlSpWK7Q0SWYDzNmXKFMyaNQtt2rTJ8/5carmylkVGj/r37//S15cvX15ISUgNXjYT9HNqupKACtfzK1AAaK9CeXHGVmNjY/To0QOLFi2CmZmZlIyysQDrKipX1rLIEBEVAVu3bsXo0aMxatQo7emTkydPYtasWZgwYQKysrIwZswY9OjRAz/++KPktETvDouMHuTk5OCHH37Atm3b8PTpU7Rp0wYTJkyAubm57GhEVEQ1bNgQkydPho+Pj87yXbt2Ydy4cTh58iS2bNmCb775RntUgui5vI7iqQWvWtKDoKAg/Pe//4WlpSUqVKiAuXPnYujQobJjEVERdvbs2Tzn/XBycsLZs2cBAHXq1OFNR0nH0qVL4e7uDjMzM5iZmcHd3R1LliyRHeu1sMjowapVq/DLL79g165d2LJlC7Zv3441a9bwJpJEpDfVq1fH9OnT8fTpU+2yzMxMTJ8+HdWrVwcAXL9+HWXKlJEVkRRm/PjxGD58ODp16oQNGzZgw4YN6NSpE77++muMHz9edrwC46klPTA1NUVsbCwcHR21y8zMzBAbG5vrPihE9HpWr16NhQsXIj4+HsePH4eTkxOCg4Ph7OyMLl26yI4nzbFjx9C5c2cYGBho75Fz9uxZZGdnY8eOHWjUqBFWr16NW7duYdSoUZLTkhLY29tj3rx56NWrl87ydevW4auvvsI///wjKdnr4REZPcjKysp1VYCxsbH2sj8iejMLFixAQEAAOnTogOTkZO0VXCVLlkRwcLDccJI1adIE8fHxmDRpEjw9PeHp6YlJkyYhPj4ejRo1AgB88sknxbbErF69Gk2bNkX58uW1U/MHBwdj69atkpPJk5mZCS8vr1zL69evj6ysLAmJ3gyPyOiBgYEB2rdvrzNnw/bt2/H+++/rXO7HeWQoP8nJydi4cSPi4uIwatQo2NnZITw8HGXKlEGFChVkx5OmZs2amDp1Knx9fXVujHju3Dm0atVKNXuQVLgWLFiA8ePHY8SIEQgKCsK5c+fg4uKCFStWYOXKlThw4IDsiFJ89dVXMDY2znX375EjR+Lx48eYP3++pGSvh9PN6oG/v3+uZX369JGQhNTozJkz8Pb2ho2NDRISEvDpp5/Czs4OISEhSExMxKpVq2RHlCY+Ph5169bNtdzU1BRpaWkSEilLTEwMDhw4gDt37uQak6emMQ/v2k8//YTFixfD19cX06dP1y738vLCyJEjJSaTb+nSpdi9e7f2qN2JEyeQmJiIvn37IiAgQLvev8uOkrDI6AEnuqO3ERAQgH79+mHmzJmwsrLSLu/QoQN69+4tMZl8zs7OiIyMzHV1zs6dO4v9zVkXL16ML774AqVLl0bZsmV1LqPVaDTFusiwAOft3LlzqFevHgBoL8kvXbo0SpcujXPnzmnXU/ol2SwyRApz6tQpLFq0KNfyChUq4NatWxISKUdAQACGDh2KJ0+eQAiBkydPYt26dZg2bZrqLhl916ZMmYKgoCCMHj1adhTFYQHOW1E5pcYiQ6QwpqamSElJybX88uXLsLe3l5BIOQYNGgRzc3N8//33SE9PR+/evVG+fHnMnTsXPXv2lB1PqgcPHuDjjz+WHUORWICLNg72JVKYQYMG4d69e1i/fj3s7Oxw5swZGBoawtfXFy1atCj2V+c8l56ejtTUVDg4OMiOoggDBw5EgwYN8Pnnn8uOokhr1qzBxIkTtadQypcvj8DAQAwcOFByMnpbLDJECvPw4UN89NFHCAsLw6NHj1C+fHncunULjRs3xp9//lnsb3RHeZs2bRpmz56NDz/8EB4eHjA2NtZ5XS13MtY3FuCih0WGSKGOHDmCM2fOIDU1FfXq1YO3t7fsSFLUrVu3wIMNw8PD9ZxGuYrKnYyJXhfHyLxj27ZtK/C6nTt31mMSUrtmzZqhWbNmsmNI5+vrKzuCKsTHx8uOoCgswMUHj8i8YwYGBZssWaPRaGclJfq3ffv2Yd++fXnOB7Js2TJJqYjUIzAwsMDrTpgwQY9JlKUo7myzyBApTGBgICZNmgQvLy+UK1cu117l5s2bJSUjpbt27Rq2bduGxMREnZtHAsqe0IwKT1Hc2eapJSKFWbhwIVasWIFPPvlEdhRFsLW1LfApgvv37+s5jXLt27cPnTt3houLCy5evAh3d3ckJCRACKGd9Izo30d4iwIWGT1LS0vDwYMH89xD4lUElJenT5+iSZMmsmMoBi83L5ixY8di5MiRCAwMhJWVFTZt2gQHBwf4+fnhgw8+kB2v0LEAFx88taRHERER6NChA9LT05GWlgY7Ozv8888/KFGiBBwcHHgVAeVp9OjRsLS0xLhx42RHIRWxsrJCZGQkXF1dYWtriyNHjqBWrVqIiopCly5dkJCQIDtioVq5cmWB183r/njFRVHY2eYRGT36+uuv0alTJyxcuBA2NjYIDQ2FsbEx+vTpg+HDh8uORwry4s3ZcnJy8Ouvv2Lv3r3w9PTMNR9IcRvrkJKSAmtra+2/X+b5esWRhYWF9g9RuXLlEBcXh1q1agFAsbwreHEuJwX1qp1tFhlCZGQkFi1aBAMDAxgaGiIjIwMuLi6YOXMm/P390a1bN9kRSSEiIiJ0ntepUwcAdG7cBij/5m36YGtri5s3b8LBwQElS5bMcxsIIVQ1OFEfGjVqhCNHjqBGjRro0KEDvvnmG5w9exYhISHaOxsXJyzAr1ZUdrZZZPTI2NhYO0LcwcEBiYmJqFGjBmxsbJCUlCQ5HSlJUbl5mz7s378fdnZ2ALidXmb27NlITU0F8OzKt9TUVPz+++9wc3MrdkfxABbggigqO9ssMnpUt25dnDp1Cm5ubmjZsiXGjx+Pf/75B6tXr4a7u7vseKRQDx8+RHZ2tvaP93P379+HkZFRsdt7bNmyZZ7/pv+TnZ2Na9euwdPTE8Cz00wLFy6UnEouFuBXKyo72xzsq0fP75XTunVr3LlzB3379sWxY8fg5uaGZcuWoXbt2rIjkgK1b98enTp1wpAhQ3SWL1y4ENu2bcOff/4pKZl8hw4deunrLVq0KKQkymNmZoYLFy689FYFRC9q164d+vXrh969e+PTTz/FmTNnMGzYMKxevRoPHjzAiRMnZEcsEBYZPRFCICkpCQ4ODjAzM5Mdh1TEzs4OR48eRY0aNXSWX7x4EU2bNsW9e/ckJZMvr8m8XjxlUFxPEQCAl5cXZsyYgTZt2siOojgswHkrKjvbPLWkJ0IIVKlSBdHR0XBzc5Mdh1QkIyMDWVlZuZZnZmbi8ePHEhIpx4MHD3SeZ2ZmIiIiAuPGjUNQUJCkVMowZcoUjBw5EpMnT0b9+vVz3SW9uJ2SfFGrVq1yLSvuBVgIAQcHB+0wBwcHB+zcuVNyqjfDIzJ6VKtWLSxdurRYXjFAb65169Zwd3fHTz/9pLN86NChOHPmDA4fPiwpmXIdPHgQAQEBOH36tOwo0rx4tOrFP9LFfUAr8Gzc2Yv+XYCL41GsnJwcmJmZFYmdbR6R0aPp06dj1KhRWLBgAQf3UoFNmTIF3t7eiIqK0v6C3bdvH06dOoXdu3dLTqdMZcqUwaVLl2THkIoDWvNnY2OTa1nbtm1hYmJSbAuwgYEB3NzccO/ePdUXGR6R0SNbW1ukp6cjKysLJiYmMDc313md02JTfiIjIzFz5kxERUXB3Nwcnp6eGDt2rOp/4bytM2fO6DwXQuDmzZuYPn06srKycOTIEUnJSI0uXrwILy8v7WXrxc327dsxc+ZM1e9ss8jo0aumyObMk0Svx8DAABqNBv/+tdWoUSMsW7YM1atXl5RMGZKTk7F06VJcuHABwLPT2wMGDMjziERxwgKct6Kys80iQ6RAcXFxWL58Oa5cuYLg4GA4ODjgr7/+QqVKlbTTzhdHV69e1XluYGAAe3t7XhmIZ1eg+Pj4wNzcHA0bNgQAnDp1Co8fP8bu3buL9R2wWYDzVlR2tllk9Cw7OxtbtmzR2UPq3LkzDA0NJScjpUlKSoKjoyMOHjyI9u3bo2nTpjh06BAuXLgAFxcXTJ8+HWFhYdi4caPsqIrw5MkTFpgXNG/eHFWqVMHixYthZPRs+GNWVhYGDRqEK1euvPIS5KKMBbhoY5HRo9jYWHTo0AHXr19HtWrVAACXLl2Co6Mj/vjjD7i6ukpOSEqxcOFCLF26FKdOnUKjRo3QvXt3BAQEwMrKClFRUXBxccHJkyfRrVs3XLt2TXZcabKzszF16lQsXLgQt2/fxuXLl+Hi4oJx48ahcuXKGDhwoOyI0pibmyMiIiLX0YXz58/Dy8sL6enpkpIpCwuwrqKws517dil6Z4YNGwZXV1ckJSUhPDwc4eHhSExMhLOzs2ruKkr6N3v2bGzatAl///03gGc3iuzatWuu9RwcHIrlXYxfFBQUhBUrVmDmzJkwMTHRLnd3d8eSJUskJpPP2toaiYmJuZYnJSXByspKQiLlyM7OxuTJk1GhQgVYWlriypUrAIBx48Zh6dKlktPJExsbixo1aqBv374ICQlBSEgI+vTpg1q1aiEuLk52vAJjkdGjgwcPYubMmTr3zClVqhSmT5+OgwcPSkxGStKsWTNcu3YNa9euBQCULFkSN2/ezLVeREQEKlSoUNjxFGXVqlX49ddf4efnp7PHWLt2bVy8eFFiMvl69OiBgQMH4vfff0dSUhKSkpLw22+/YdCgQejVq5fseFKxAOetqOxscx4ZPTI1NcWjR49yLU9NTdX5YaLirWHDhjh58iRGjx4NAOjZsydGjx6NDRs2QKPRICcnB0ePHsXIkSPRt29fyWnlun79OqpUqZJreU5ODjIzMyUkUo4ff/wRGo0Gffv21c4MbWxsjC+++ALTp0+XnE6u5wW4TZs2+Pzzz7XLi3sBPnjwIEJDQ/Pc2W7atKnEZK+HR2T0qGPHjvjss89w4sQJCCEghEBoaCg+//xzdO7cWXY8UhArKyv88ssvAICpU6eievXqcHR0RGpqKmrWrIkWLVqgSZMm+P777yUnlatmzZp5zmy8ceNG1K1bV0Ii5TAxMcHcuXPx4MEDREZGIjIyEvfv38ecOXNgamoqO55ULMB5Kyo72zwio0fz5s2Dv78/GjduDGNjYwDPriLo3Lkz5s6dKzkdKZWJiQkWL16M8ePH4+zZs0hNTUXdunWL/WR4ADB+/Hj4+/vj+vXryMnJQUhICC5duoRVq1Zhx44dsuMpQokSJeDh4SE7hqI8L8BOTk46y4t7AX6+s7106VLtJfsnTpxQ3c42r1oqBDExMdrDlzVq1Mhzz4AoOzsbP/74I7Zt24anT5+iTZs2mDBhQq5Jqoq7w4cPY9KkSYiKikJqairq1auH8ePHo127drKjSTFgwACd58uWLZOURLm2bt0Kf39/jB07FpMmTUJgYKBOAW7btq3siFIkJyfD398f27dvz7WzvWLFCtVMpMgiQ6QQkydPxsSJE+Ht7Q1zc3Ps2rULvXr14h8mAFeuXIGzs7POzRDpmcDAQJ3nEyZMkJRE2ViA86f2nW0WmXcsICCgwOvOnj1bj0lIbdzc3DBy5EgMHjwYALB37158+OGHePz4sc6djYsjQ0ND3Lx5Ew4ODgCeXaEzb948lClTRnIyUjIW4OKBReYda926dYHW02g02L9/v57TkJqYmpoiNjYWjo6O2mVmZmaIjY1FxYoVJSaTz8DAALdu3dIWmRcnCiTKDwtwbkVxZ5uDfd+xAwcOyI5AKpWVlZVrxlFjY+NifVUFvVzdunULfLQhPDxcz2mU59/76X/++SemTZsmKY0yREREFGg9NR3FYpHRAx7OpDchhEC/fv10LpV98uQJPv/8c1hYWGiXhYSEyIgnlUajyfXzxJ8vwNfXV/vvJ0+e4JdffkHNmjXRuHFjAEBoaCiio6MxZMgQSQlJaYrizjaLjB64ubnxcCa9trzuNNunTx8JSZTn3yUvr4IHFL+S9+LA3kGDBmHYsGGYPHlyrnWSkpIKO5oisADnrajtbHOMjB7wfD7Ru9W/f/8Crbd8+XI9J1EuGxsbhIWF5ZpvKCYmBl5eXnj48KGkZPIYGBigffv22gK8fft2vP/++8W+ABe1sUM8IkNEilecC0pBmZub4+jRo7mKzNGjR4vt3Z7/fZSTRzifKWpjh1hk9ICHM4mosI0YMQJffPEFwsPDdWZpXbZsGcaNGyc5nRwswMUDi4we8Hw+ERW2MWPGwMXFBXPnzsX//vc/AM8mN1u+fDm6d+8uOR0pSVHb2eYYGT3g+XwiIlKqojZ2iEWGiIioGClqO9ssMkRERKRaxfsGLkRERKRqLDJERESkWiwyREQql5mZCVdXV1y4cEF2FKJCxyJDRKRyxsbGePLkiewYRFKwyBARFQFDhw7FjBkzkJWVJTsKUaHiVUtEREVA165dsW/fPlhaWsLDw0O1c4IQvS7O7EtEVASULFkS//nPf2THICp0PCJDREREqsUxMkRERKRaPLVERFQEODs7v/TGf1euXCnENESFh0WGiKgIGDFihM7zzMxMREREYOfOnRg1apScUESFgGNkiIiKsPnz5yMsLEw1NwAkel0sMkRERdiVK1dQp04dpKSkyI5CpBcc7EtEVIRt3LgRdnZ2smMQ6Q3HyBARFQF169bVGewrhMCtW7dw9+5d/PLLLxKTEekXiwwRURHg6+ur89zAwAD29vZo1aoVqlevLicUUSHgGBkiIiJSLY6RISIqIuLi4vD999+jV69euHPnDgDgr7/+QnR0tORkRPrDIkNEVAQcPHgQHh4eOHHiBEJCQpCamgoAiIqKwoQJEySnI9IfFhkioiJgzJgxmDJlCvbs2QMTExPt8vfffx+hoaESkxHpF4sMEVERcPbsWXTt2jXXcgcHB/zzzz8SEhEVDhYZIqIioGTJkrh582au5REREahQoYKERESFg0WGiKgI6NmzJ0aPHo1bt25Bo9EgJycHR48exciRI9G3b1/Z8Yj0hpdfExEVAU+fPsXQoUOxYsUKZGdnw8jICNnZ2ejduzdWrFgBQ0ND2RGJ9IJFhoioCElMTMS5c+eQmpqKunXrws3NTXYkIr1ikSEiIiLV4i0KiIhUKiAgoMDrzp49W49JiORhkSEiUqmIiIgCrffizSSJihqeWiIiIiLV4uXXREQqduXKFXB/lIozFhkiIhVzc3PD3bt3tc979OiB27dvS0xEVLhYZIiIVOzfR2P+/PNPpKWlSUpDVPhYZIiIiEi1WGSIiFRMo9HkuiqJVylRccLLr4mIVEwIgX79+sHU1BQA8OTJE3z++eewsLDQWS8kJERGPCK9Y5EhIlIxf39/ned9+vSRlIRIDs4jQ0RERKrFMTJERESkWiwyREREpFosMkRERKRaLDJERESkWiwyREREpFosMkSkd5UrV0ZwcLDsGC+1YsUKlCxZ8q0/jkajwZYtW9764xBRwbDIEFGBJSUlYcCAAShfvjxMTEzg5OSE4cOH4969e7KjoV+/fvD19ZUdg4gKGYsMERXIlStX4OXlhZiYGKxbtw6xsbFYuHAh9u3bh8aNG+P+/ft6+9xPnz7V28cmInVjkSGiAhk6dChMTEywe/dutGzZEpUqVUL79u2xd+9eXL9+Hd999x0A4M6dO+jUqRPMzc3h7OyMNWvW5PpYiYmJ6NKlCywtLWFtbY3u3bvj9u3b2tcnTpyIOnXqYMmSJXB2doaZmdlb5589ezY8PDxgYWEBR0dHDBkyBKmpqbnW27JlC9zc3GBmZgYfHx8kJSXpvL5161bUq1cPZmZmcHFxQWBgILKyst46HxG9GRYZInql+/fvY9euXRgyZAjMzc11Xitbtiz8/Pzw+++/a+/7k5SUhAMHDmDjxo345ZdfcOfOHe36OTk56NKlC+7fv4+DBw9iz549uHLlCnr06KHzcWNjY7Fp0yaEhIQgMjLyrb8GAwMDzJs3D9HR0Vi5ciX279+Pb7/9Vmed9PR0BAUFYdWqVTh69CiSk5PRs2dP7euHDx9G3759MXz4cJw/fx6LFi3CihUrEBQU9Nb5iOgNCSKiVwgNDRUAxObNm/N8ffbs2QKAOHHihAAgTp48qX3twoULAoCYM2eOEEKI3bt3C0NDQ5GYmKhdJzo6Wud9EyZMEMbGxuLOnTsFzujv7y+6dOlS4PU3bNggSpUqpX2+fPlyAUCEhobmyn7ixAkhhBBt2rQRU6dO1fk4q1evFuXKldM+f9l2IqJ3j0dkiKjAxCtuzXbhwgUYGRmhfv362mXVq1fXuRrowoULcHR0hKOjo3ZZzZo1UbJkSVy4cEG7zMnJCfb29u8s+969e9GmTRtUqFABVlZW+OSTT3Dv3j2kp6dr1zEyMkKDBg1yZX+eKyoqCpMmTYKlpaX28emnn+LmzZs6H4eICg+LDBG9UpUqVaDRaHSKxosuXLgAW1vbd3L58nMWFhbv7GMlJCSgY8eO8PT0xKZNm3D69GnMnz8fwOsNJE5NTUVgYCAiIyO1j7NnzyImJuadjOMhotfHIkNEr1SqVCm0bdsWv/zyCx4/fqzz2q1bt7BmzRr06NED1atXR1ZWFk6fPq19/dKlS0hOTtY+r1GjBpKSknQG0Z4/fx7JycmoWbOmXvKfPn0aOTk5mDVrFho1aoSqVavixo0budbLyspCWFhYruw1atQAANSrVw+XLl1ClSpVcj0MDPjrlEgGI9kBiEgdfv75ZzRp0gQ+Pj6YMmUKnJ2dER0djVGjRqFChQoICgqCnZ0dPvjgAwwePBgLFiyAkZERRowYoTNA2NvbGx4eHvDz80NwcDCysrIwZMgQtGzZEl5eXm+V8eHDh7kGBpcqVQpVqlRBZmYmfvrpJ3Tq1AlHjx7FwoULc73f2NgYX331FebNmwcjIyN8+eWXaNSoERo2bAgAGD9+PDp27IhKlSrho48+goGBAaKionDu3DlMmTLlrbIT0ZvhLgQRFYibmxvCwsLg4uKC7t27w9XVFZ999hlat26N48ePw87ODgCwfPlylC9fHi1btkS3bt3w2WefwcHBQftxNBoNtm7dCltbW7Ro0QLe3t5wcXHB77///tYZ//77b9StW1fnERgYiNq1a2P27NmYMWMG3N3dsWbNGkybNi3X+0uUKIHRo0ejd+/eaNq0KSwtLXVy+fj4YMeOHdi9ezcaNGiARo0aYc6cOXBycnrr7ET0ZjTiVaP3iIiIiBSKR2SIiIhItVhkiEjxEhMTdS55/vcjMTFRdkQikoSnlohI8bKyspCQkJDv65UrV4aREa9dICqOWGSIiIhItXhqiYiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFSLRYaIiIhUi0WGiIiIVItFhoiIiFTr/wFp9ipXs1nmSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "odeurs_choisies['Odor_Label'].value_counts().plot.bar(ax=ax)\n",
    "for bar in ax.containers:\n",
    "    ax.bar_label(bar)\n",
    "ax.set_title('Odeurs Sélectionnées')\n",
    "ax.set_ylabel('N')\n",
    "fig.savefig(save_folder / 'odeurs_choisies_emosens3.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5169f454-2934-451d-b004-59b1da7d0fa6",
   "metadata": {},
   "source": [
    "# Odeurs et coeur"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "30fafab0-7c01-41ca-84c5-9d50578b98dd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>participant</th>\n",
       "      <th>session</th>\n",
       "      <th>HRV_Mean</th>\n",
       "      <th>HRV_SD</th>\n",
       "      <th>HRV_Median</th>\n",
       "      <th>HRV_Mad</th>\n",
       "      <th>HRV_CV</th>\n",
       "      <th>HRV_MCV</th>\n",
       "      <th>HRV_Asymmetry</th>\n",
       "      <th>HRV_RMSSD</th>\n",
       "      <th>stai_state</th>\n",
       "      <th>stai_trait</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Maia_Mean</th>\n",
       "      <th>OAS</th>\n",
       "      <th>BMRQ</th>\n",
       "      <th>Odor_Label</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dim_0</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>P01</td>\n",
       "      <td>odor</td>\n",
       "      <td>767.753989</td>\n",
       "      <td>91.021796</td>\n",
       "      <td>759.5</td>\n",
       "      <td>52.632379</td>\n",
       "      <td>0.118556</td>\n",
       "      <td>0.069299</td>\n",
       "      <td>-8.253989</td>\n",
       "      <td>88.464355</td>\n",
       "      <td>40</td>\n",
       "      <td>61</td>\n",
       "      <td>F</td>\n",
       "      <td>1.019643</td>\n",
       "      <td>2.666667</td>\n",
       "      <td>2.727273</td>\n",
       "      <td>Feuille d’Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>P02</td>\n",
       "      <td>odor</td>\n",
       "      <td>740.212598</td>\n",
       "      <td>99.500337</td>\n",
       "      <td>722.5</td>\n",
       "      <td>112.677769</td>\n",
       "      <td>0.134421</td>\n",
       "      <td>0.155955</td>\n",
       "      <td>-17.712598</td>\n",
       "      <td>67.882486</td>\n",
       "      <td>24</td>\n",
       "      <td>37</td>\n",
       "      <td>F</td>\n",
       "      <td>3.354762</td>\n",
       "      <td>3.066667</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>P03</td>\n",
       "      <td>odor</td>\n",
       "      <td>815.740136</td>\n",
       "      <td>82.597783</td>\n",
       "      <td>814.0</td>\n",
       "      <td>81.543122</td>\n",
       "      <td>0.101255</td>\n",
       "      <td>0.100176</td>\n",
       "      <td>-1.740136</td>\n",
       "      <td>78.976706</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "      <td>F</td>\n",
       "      <td>3.664583</td>\n",
       "      <td>3.266667</td>\n",
       "      <td>3.136364</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>P04</td>\n",
       "      <td>odor</td>\n",
       "      <td>789.043421</td>\n",
       "      <td>55.528532</td>\n",
       "      <td>794.0</td>\n",
       "      <td>54.856282</td>\n",
       "      <td>0.070374</td>\n",
       "      <td>0.069089</td>\n",
       "      <td>4.956579</td>\n",
       "      <td>38.700056</td>\n",
       "      <td>27</td>\n",
       "      <td>33</td>\n",
       "      <td>F</td>\n",
       "      <td>3.196429</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.227273</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>P05</td>\n",
       "      <td>odor</td>\n",
       "      <td>909.593323</td>\n",
       "      <td>86.862903</td>\n",
       "      <td>894.0</td>\n",
       "      <td>74.130111</td>\n",
       "      <td>0.095496</td>\n",
       "      <td>0.082920</td>\n",
       "      <td>-15.593323</td>\n",
       "      <td>53.851860</td>\n",
       "      <td>27</td>\n",
       "      <td>21</td>\n",
       "      <td>M</td>\n",
       "      <td>4.107738</td>\n",
       "      <td>3.200000</td>\n",
       "      <td>3.227273</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>P06</td>\n",
       "      <td>odor</td>\n",
       "      <td>1041.115385</td>\n",
       "      <td>121.967856</td>\n",
       "      <td>1041.0</td>\n",
       "      <td>114.901672</td>\n",
       "      <td>0.117151</td>\n",
       "      <td>0.110376</td>\n",
       "      <td>-0.115385</td>\n",
       "      <td>94.988270</td>\n",
       "      <td>29</td>\n",
       "      <td>32</td>\n",
       "      <td>F</td>\n",
       "      <td>3.303869</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.045455</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>P07</td>\n",
       "      <td>odor</td>\n",
       "      <td>784.826999</td>\n",
       "      <td>106.342649</td>\n",
       "      <td>764.0</td>\n",
       "      <td>134.916802</td>\n",
       "      <td>0.135498</td>\n",
       "      <td>0.176593</td>\n",
       "      <td>-20.826999</td>\n",
       "      <td>70.432149</td>\n",
       "      <td>24</td>\n",
       "      <td>35</td>\n",
       "      <td>F</td>\n",
       "      <td>2.342262</td>\n",
       "      <td>3.133333</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>P08</td>\n",
       "      <td>odor</td>\n",
       "      <td>814.301630</td>\n",
       "      <td>111.874366</td>\n",
       "      <td>810.0</td>\n",
       "      <td>143.812415</td>\n",
       "      <td>0.137387</td>\n",
       "      <td>0.177546</td>\n",
       "      <td>-4.301630</td>\n",
       "      <td>72.418155</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>F</td>\n",
       "      <td>2.367857</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>2.590909</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>P09</td>\n",
       "      <td>odor</td>\n",
       "      <td>932.718069</td>\n",
       "      <td>91.302380</td>\n",
       "      <td>958.0</td>\n",
       "      <td>77.095315</td>\n",
       "      <td>0.097889</td>\n",
       "      <td>0.080475</td>\n",
       "      <td>25.281931</td>\n",
       "      <td>43.489612</td>\n",
       "      <td>55</td>\n",
       "      <td>53</td>\n",
       "      <td>F</td>\n",
       "      <td>2.391667</td>\n",
       "      <td>2.833333</td>\n",
       "      <td>2.818182</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>P10</td>\n",
       "      <td>odor</td>\n",
       "      <td>1069.426786</td>\n",
       "      <td>61.350384</td>\n",
       "      <td>1070.5</td>\n",
       "      <td>61.527992</td>\n",
       "      <td>0.057368</td>\n",
       "      <td>0.057476</td>\n",
       "      <td>1.073214</td>\n",
       "      <td>44.962159</td>\n",
       "      <td>39</td>\n",
       "      <td>52</td>\n",
       "      <td>F</td>\n",
       "      <td>2.660119</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.045455</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>P11</td>\n",
       "      <td>odor</td>\n",
       "      <td>718.056287</td>\n",
       "      <td>59.981038</td>\n",
       "      <td>710.0</td>\n",
       "      <td>66.717100</td>\n",
       "      <td>0.083533</td>\n",
       "      <td>0.093968</td>\n",
       "      <td>-8.056287</td>\n",
       "      <td>24.036069</td>\n",
       "      <td>31</td>\n",
       "      <td>39</td>\n",
       "      <td>F</td>\n",
       "      <td>2.451488</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>2.863636</td>\n",
       "      <td>Fleur d'oranger épicé</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>P12</td>\n",
       "      <td>odor</td>\n",
       "      <td>724.342201</td>\n",
       "      <td>15.521338</td>\n",
       "      <td>724.0</td>\n",
       "      <td>14.826022</td>\n",
       "      <td>0.021428</td>\n",
       "      <td>0.020478</td>\n",
       "      <td>-0.342201</td>\n",
       "      <td>10.710419</td>\n",
       "      <td>26</td>\n",
       "      <td>27</td>\n",
       "      <td>M</td>\n",
       "      <td>3.011905</td>\n",
       "      <td>3.233333</td>\n",
       "      <td>3.181818</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>P13</td>\n",
       "      <td>odor</td>\n",
       "      <td>770.676093</td>\n",
       "      <td>59.159455</td>\n",
       "      <td>767.0</td>\n",
       "      <td>48.925873</td>\n",
       "      <td>0.076763</td>\n",
       "      <td>0.063789</td>\n",
       "      <td>-3.676093</td>\n",
       "      <td>55.576029</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "      <td>F</td>\n",
       "      <td>3.465179</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.227273</td>\n",
       "      <td>Floral printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>P14</td>\n",
       "      <td>odor</td>\n",
       "      <td>593.162216</td>\n",
       "      <td>19.111506</td>\n",
       "      <td>592.0</td>\n",
       "      <td>19.273829</td>\n",
       "      <td>0.032220</td>\n",
       "      <td>0.032557</td>\n",
       "      <td>-1.162216</td>\n",
       "      <td>7.203616</td>\n",
       "      <td>41</td>\n",
       "      <td>36</td>\n",
       "      <td>M</td>\n",
       "      <td>3.459821</td>\n",
       "      <td>2.866667</td>\n",
       "      <td>2.954545</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>P15</td>\n",
       "      <td>odor</td>\n",
       "      <td>848.042433</td>\n",
       "      <td>81.663268</td>\n",
       "      <td>835.0</td>\n",
       "      <td>88.956133</td>\n",
       "      <td>0.096296</td>\n",
       "      <td>0.106534</td>\n",
       "      <td>-13.042433</td>\n",
       "      <td>33.474357</td>\n",
       "      <td>34</td>\n",
       "      <td>39</td>\n",
       "      <td>M</td>\n",
       "      <td>3.384226</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.227273</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>P16</td>\n",
       "      <td>odor</td>\n",
       "      <td>840.474719</td>\n",
       "      <td>63.676274</td>\n",
       "      <td>845.0</td>\n",
       "      <td>65.234498</td>\n",
       "      <td>0.075762</td>\n",
       "      <td>0.077201</td>\n",
       "      <td>4.525281</td>\n",
       "      <td>51.307380</td>\n",
       "      <td>22</td>\n",
       "      <td>40</td>\n",
       "      <td>F</td>\n",
       "      <td>2.158631</td>\n",
       "      <td>3.166667</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>P17</td>\n",
       "      <td>odor</td>\n",
       "      <td>952.670906</td>\n",
       "      <td>65.338654</td>\n",
       "      <td>951.0</td>\n",
       "      <td>65.234498</td>\n",
       "      <td>0.068585</td>\n",
       "      <td>0.068596</td>\n",
       "      <td>-1.670906</td>\n",
       "      <td>43.721287</td>\n",
       "      <td>24</td>\n",
       "      <td>36</td>\n",
       "      <td>M</td>\n",
       "      <td>2.264286</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>3.409091</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>P18</td>\n",
       "      <td>odor</td>\n",
       "      <td>837.235211</td>\n",
       "      <td>55.443814</td>\n",
       "      <td>846.0</td>\n",
       "      <td>41.512862</td>\n",
       "      <td>0.066223</td>\n",
       "      <td>0.049070</td>\n",
       "      <td>8.764789</td>\n",
       "      <td>28.119491</td>\n",
       "      <td>33</td>\n",
       "      <td>54</td>\n",
       "      <td>F</td>\n",
       "      <td>2.541667</td>\n",
       "      <td>2.933333</td>\n",
       "      <td>3.181818</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>P19</td>\n",
       "      <td>odor</td>\n",
       "      <td>866.171965</td>\n",
       "      <td>74.200347</td>\n",
       "      <td>870.5</td>\n",
       "      <td>79.319219</td>\n",
       "      <td>0.085665</td>\n",
       "      <td>0.091119</td>\n",
       "      <td>4.328035</td>\n",
       "      <td>45.193970</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>F</td>\n",
       "      <td>4.157738</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.181818</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>P20</td>\n",
       "      <td>odor</td>\n",
       "      <td>759.812421</td>\n",
       "      <td>52.986813</td>\n",
       "      <td>749.0</td>\n",
       "      <td>47.443271</td>\n",
       "      <td>0.069737</td>\n",
       "      <td>0.063342</td>\n",
       "      <td>-10.812421</td>\n",
       "      <td>48.926600</td>\n",
       "      <td>25</td>\n",
       "      <td>39</td>\n",
       "      <td>F</td>\n",
       "      <td>3.775893</td>\n",
       "      <td>3.166667</td>\n",
       "      <td>3.227273</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>P21</td>\n",
       "      <td>odor</td>\n",
       "      <td>894.875934</td>\n",
       "      <td>43.130467</td>\n",
       "      <td>896.0</td>\n",
       "      <td>42.995464</td>\n",
       "      <td>0.048197</td>\n",
       "      <td>0.047986</td>\n",
       "      <td>1.124066</td>\n",
       "      <td>36.537119</td>\n",
       "      <td>34</td>\n",
       "      <td>44</td>\n",
       "      <td>M</td>\n",
       "      <td>2.841964</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>P23</td>\n",
       "      <td>odor</td>\n",
       "      <td>771.073359</td>\n",
       "      <td>58.677124</td>\n",
       "      <td>764.0</td>\n",
       "      <td>53.373680</td>\n",
       "      <td>0.076098</td>\n",
       "      <td>0.069861</td>\n",
       "      <td>-7.073359</td>\n",
       "      <td>30.498014</td>\n",
       "      <td>28</td>\n",
       "      <td>40</td>\n",
       "      <td>M</td>\n",
       "      <td>1.941667</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.181818</td>\n",
       "      <td>Fleur d'oranger épicé</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>P24</td>\n",
       "      <td>odor</td>\n",
       "      <td>701.411082</td>\n",
       "      <td>94.212689</td>\n",
       "      <td>689.0</td>\n",
       "      <td>31.134647</td>\n",
       "      <td>0.134319</td>\n",
       "      <td>0.045188</td>\n",
       "      <td>-12.411082</td>\n",
       "      <td>84.040188</td>\n",
       "      <td>20</td>\n",
       "      <td>26</td>\n",
       "      <td>M</td>\n",
       "      <td>4.412500</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>P25</td>\n",
       "      <td>odor</td>\n",
       "      <td>810.339189</td>\n",
       "      <td>88.077100</td>\n",
       "      <td>803.5</td>\n",
       "      <td>100.075650</td>\n",
       "      <td>0.108692</td>\n",
       "      <td>0.124550</td>\n",
       "      <td>-6.839189</td>\n",
       "      <td>69.771937</td>\n",
       "      <td>34</td>\n",
       "      <td>32</td>\n",
       "      <td>M</td>\n",
       "      <td>3.169048</td>\n",
       "      <td>2.733333</td>\n",
       "      <td>2.954545</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>P26</td>\n",
       "      <td>odor</td>\n",
       "      <td>812.017639</td>\n",
       "      <td>119.512345</td>\n",
       "      <td>791.0</td>\n",
       "      <td>100.816951</td>\n",
       "      <td>0.147179</td>\n",
       "      <td>0.127455</td>\n",
       "      <td>-21.017639</td>\n",
       "      <td>65.462630</td>\n",
       "      <td>36</td>\n",
       "      <td>50</td>\n",
       "      <td>M</td>\n",
       "      <td>2.658631</td>\n",
       "      <td>3.033333</td>\n",
       "      <td>3.318182</td>\n",
       "      <td>Rose</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>P27</td>\n",
       "      <td>odor</td>\n",
       "      <td>758.012658</td>\n",
       "      <td>64.020862</td>\n",
       "      <td>752.0</td>\n",
       "      <td>66.717100</td>\n",
       "      <td>0.084459</td>\n",
       "      <td>0.088720</td>\n",
       "      <td>-6.012658</td>\n",
       "      <td>46.932900</td>\n",
       "      <td>27</td>\n",
       "      <td>35</td>\n",
       "      <td>F</td>\n",
       "      <td>3.882440</td>\n",
       "      <td>2.633333</td>\n",
       "      <td>2.772727</td>\n",
       "      <td>Fleur d'oranger épicé</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>P28</td>\n",
       "      <td>odor</td>\n",
       "      <td>983.157635</td>\n",
       "      <td>48.728477</td>\n",
       "      <td>989.0</td>\n",
       "      <td>42.995464</td>\n",
       "      <td>0.049563</td>\n",
       "      <td>0.043474</td>\n",
       "      <td>5.842365</td>\n",
       "      <td>22.315435</td>\n",
       "      <td>36</td>\n",
       "      <td>52</td>\n",
       "      <td>M</td>\n",
       "      <td>2.161607</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.227273</td>\n",
       "      <td>Feuille d'Olivier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>P29</td>\n",
       "      <td>odor</td>\n",
       "      <td>937.784038</td>\n",
       "      <td>85.617870</td>\n",
       "      <td>929.0</td>\n",
       "      <td>84.508326</td>\n",
       "      <td>0.091298</td>\n",
       "      <td>0.090967</td>\n",
       "      <td>-8.784038</td>\n",
       "      <td>65.987400</td>\n",
       "      <td>45</td>\n",
       "      <td>50</td>\n",
       "      <td>M</td>\n",
       "      <td>3.769048</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.272727</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>P30</td>\n",
       "      <td>odor</td>\n",
       "      <td>947.990491</td>\n",
       "      <td>55.019921</td>\n",
       "      <td>950.0</td>\n",
       "      <td>50.408475</td>\n",
       "      <td>0.058038</td>\n",
       "      <td>0.053062</td>\n",
       "      <td>2.009509</td>\n",
       "      <td>33.400432</td>\n",
       "      <td>25</td>\n",
       "      <td>29</td>\n",
       "      <td>M</td>\n",
       "      <td>3.071131</td>\n",
       "      <td>2.966667</td>\n",
       "      <td>3.045455</td>\n",
       "      <td>Pêche Lavande</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>P31</td>\n",
       "      <td>odor</td>\n",
       "      <td>823.986245</td>\n",
       "      <td>64.347384</td>\n",
       "      <td>825.0</td>\n",
       "      <td>68.199702</td>\n",
       "      <td>0.078093</td>\n",
       "      <td>0.082666</td>\n",
       "      <td>1.013755</td>\n",
       "      <td>36.267012</td>\n",
       "      <td>29</td>\n",
       "      <td>40</td>\n",
       "      <td>M</td>\n",
       "      <td>2.790774</td>\n",
       "      <td>2.933333</td>\n",
       "      <td>2.681818</td>\n",
       "      <td>Floral Printanier</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      participant session     HRV_Mean      HRV_SD  HRV_Median     HRV_Mad   \n",
       "dim_0                                                                        \n",
       "2             P01    odor   767.753989   91.021796       759.5   52.632379  \\\n",
       "5             P02    odor   740.212598   99.500337       722.5  112.677769   \n",
       "8             P03    odor   815.740136   82.597783       814.0   81.543122   \n",
       "11            P04    odor   789.043421   55.528532       794.0   54.856282   \n",
       "14            P05    odor   909.593323   86.862903       894.0   74.130111   \n",
       "17            P06    odor  1041.115385  121.967856      1041.0  114.901672   \n",
       "20            P07    odor   784.826999  106.342649       764.0  134.916802   \n",
       "23            P08    odor   814.301630  111.874366       810.0  143.812415   \n",
       "26            P09    odor   932.718069   91.302380       958.0   77.095315   \n",
       "29            P10    odor  1069.426786   61.350384      1070.5   61.527992   \n",
       "32            P11    odor   718.056287   59.981038       710.0   66.717100   \n",
       "35            P12    odor   724.342201   15.521338       724.0   14.826022   \n",
       "38            P13    odor   770.676093   59.159455       767.0   48.925873   \n",
       "41            P14    odor   593.162216   19.111506       592.0   19.273829   \n",
       "44            P15    odor   848.042433   81.663268       835.0   88.956133   \n",
       "47            P16    odor   840.474719   63.676274       845.0   65.234498   \n",
       "50            P17    odor   952.670906   65.338654       951.0   65.234498   \n",
       "53            P18    odor   837.235211   55.443814       846.0   41.512862   \n",
       "56            P19    odor   866.171965   74.200347       870.5   79.319219   \n",
       "59            P20    odor   759.812421   52.986813       749.0   47.443271   \n",
       "62            P21    odor   894.875934   43.130467       896.0   42.995464   \n",
       "65            P23    odor   771.073359   58.677124       764.0   53.373680   \n",
       "68            P24    odor   701.411082   94.212689       689.0   31.134647   \n",
       "71            P25    odor   810.339189   88.077100       803.5  100.075650   \n",
       "74            P26    odor   812.017639  119.512345       791.0  100.816951   \n",
       "77            P27    odor   758.012658   64.020862       752.0   66.717100   \n",
       "80            P28    odor   983.157635   48.728477       989.0   42.995464   \n",
       "83            P29    odor   937.784038   85.617870       929.0   84.508326   \n",
       "86            P30    odor   947.990491   55.019921       950.0   50.408475   \n",
       "89            P31    odor   823.986245   64.347384       825.0   68.199702   \n",
       "\n",
       "         HRV_CV   HRV_MCV  HRV_Asymmetry  HRV_RMSSD  stai_state  stai_trait   \n",
       "dim_0                                                                         \n",
       "2      0.118556  0.069299      -8.253989  88.464355          40          61  \\\n",
       "5      0.134421  0.155955     -17.712598  67.882486          24          37   \n",
       "8      0.101255  0.100176      -1.740136  78.976706          20          24   \n",
       "11     0.070374  0.069089       4.956579  38.700056          27          33   \n",
       "14     0.095496  0.082920     -15.593323  53.851860          27          21   \n",
       "17     0.117151  0.110376      -0.115385  94.988270          29          32   \n",
       "20     0.135498  0.176593     -20.826999  70.432149          24          35   \n",
       "23     0.137387  0.177546      -4.301630  72.418155          21          22   \n",
       "26     0.097889  0.080475      25.281931  43.489612          55          53   \n",
       "29     0.057368  0.057476       1.073214  44.962159          39          52   \n",
       "32     0.083533  0.093968      -8.056287  24.036069          31          39   \n",
       "35     0.021428  0.020478      -0.342201  10.710419          26          27   \n",
       "38     0.076763  0.063789      -3.676093  55.576029          32          40   \n",
       "41     0.032220  0.032557      -1.162216   7.203616          41          36   \n",
       "44     0.096296  0.106534     -13.042433  33.474357          34          39   \n",
       "47     0.075762  0.077201       4.525281  51.307380          22          40   \n",
       "50     0.068585  0.068596      -1.670906  43.721287          24          36   \n",
       "53     0.066223  0.049070       8.764789  28.119491          33          54   \n",
       "56     0.085665  0.091119       4.328035  45.193970          29          29   \n",
       "59     0.069737  0.063342     -10.812421  48.926600          25          39   \n",
       "62     0.048197  0.047986       1.124066  36.537119          34          44   \n",
       "65     0.076098  0.069861      -7.073359  30.498014          28          40   \n",
       "68     0.134319  0.045188     -12.411082  84.040188          20          26   \n",
       "71     0.108692  0.124550      -6.839189  69.771937          34          32   \n",
       "74     0.147179  0.127455     -21.017639  65.462630          36          50   \n",
       "77     0.084459  0.088720      -6.012658  46.932900          27          35   \n",
       "80     0.049563  0.043474       5.842365  22.315435          36          52   \n",
       "83     0.091298  0.090967      -8.784038  65.987400          45          50   \n",
       "86     0.058038  0.053062       2.009509  33.400432          25          29   \n",
       "89     0.078093  0.082666       1.013755  36.267012          29          40   \n",
       "\n",
       "      Gender  Maia_Mean       OAS      BMRQ             Odor_Label  \n",
       "dim_0                                                               \n",
       "2          F   1.019643  2.666667  2.727273      Feuille d’Olivier  \n",
       "5          F   3.354762  3.066667  3.000000          Pêche Lavande  \n",
       "8          F   3.664583  3.266667  3.136364                   Rose  \n",
       "11         F   3.196429  3.000000  3.227273      Floral Printanier  \n",
       "14         M   4.107738  3.200000  3.227273          Pêche Lavande  \n",
       "17         F   3.303869  2.966667  3.045455      Floral Printanier  \n",
       "20         F   2.342262  3.133333  3.000000      Floral Printanier  \n",
       "23         F   2.367857  2.900000  2.590909      Floral Printanier  \n",
       "26         F   2.391667  2.833333  2.818182      Floral Printanier  \n",
       "29         F   2.660119  2.966667  3.045455      Feuille d'Olivier  \n",
       "32         F   2.451488  2.900000  2.863636  Fleur d'oranger épicé  \n",
       "35         M   3.011905  3.233333  3.181818      Feuille d'Olivier  \n",
       "38         F   3.465179  2.966667  3.227273      Floral printanier  \n",
       "41         M   3.459821  2.866667  2.954545      Feuille d'Olivier  \n",
       "44         M   3.384226  3.000000  3.227273      Floral Printanier  \n",
       "47         F   2.158631  3.166667  3.000000      Floral Printanier  \n",
       "50         M   2.264286  2.900000  3.409091      Floral Printanier  \n",
       "53         F   2.541667  2.933333  3.181818      Floral Printanier  \n",
       "56         F   4.157738  3.000000  3.181818          Pêche Lavande  \n",
       "59         F   3.775893  3.166667  3.227273                   Rose  \n",
       "62         M   2.841964  2.966667  3.000000      Floral Printanier  \n",
       "65         M   1.941667  2.966667  3.181818  Fleur d'oranger épicé  \n",
       "68         M   4.412500  1.600000  3.000000                   Rose  \n",
       "71         M   3.169048  2.733333  2.954545                   Rose  \n",
       "74         M   2.658631  3.033333  3.318182                   Rose  \n",
       "77         F   3.882440  2.633333  2.772727  Fleur d'oranger épicé  \n",
       "80         M   2.161607  2.966667  3.227273      Feuille d'Olivier  \n",
       "83         M   3.769048  2.966667  3.272727      Floral Printanier  \n",
       "86         M   3.071131  2.966667  3.045455          Pêche Lavande  \n",
       "89         M   2.790774  2.933333  2.681818      Floral Printanier  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hrv = hrv_concat_job.get(global_key).to_dataframe()\n",
    "hrv = hrv[hrv['session'] == 'odor']\n",
    "hrv['Odor_Label'] = hrv['participant'].map(label_odeurs_choisies)\n",
    "hrv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "244edb0f-7ffa-42c1-a2dc-d2e3b59ddf9c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "hrv['Heart_Rate'] = 60000 / hrv['HRV_Median']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c6860b52-445a-4f62-8436-7497dc04283a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Feuille d’Olivier', 'Pêche Lavande', 'Rose', 'Floral Printanier',\n",
       "       \"Feuille d'Olivier\", \"Fleur d'oranger épicé\", 'Floral printanier'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hrv['Odor_Label'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b35dce70-c1c7-44d3-9004-5ee20ad44358",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = ['Feuille d’Olivier', 'Pêche Lavande', 'Rose', 'Floral Printanier',\n",
    "       \"Feuille d'Olivier\", \"Fleur d'oranger épicé\", 'Floral printanier']\n",
    "y = 'Heart_Rate'\n",
    "fig, ax = plt.subplots(figsize = (9,4))\n",
    "sns.boxplot(data = hrv,\n",
    "           x = 'Odor_Label',\n",
    "           y = y,\n",
    "           ax=ax,\n",
    "            order=order\n",
    "          )\n",
    "sns.stripplot(data = hrv,\n",
    "           x = 'Odor_Label',\n",
    "           y = y,\n",
    "           ax=ax,\n",
    "             color = 'k', alpha = 0.5, size = 3, jitter = 0.05,\n",
    "            order=order\n",
    "          )\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation = 45)\n",
    "ax.set_title(y, fontsize = 20)\n",
    "ax.set_ylabel(f'{y} (bpm)')\n",
    "fig.savefig(save_folder / 'coeur_hr_emosens3.png', dpi = 500, bbox_inches = 'tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "14c1a824-8ebd-49ca-89c6-542a07033b60",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "y = 'HRV_Mad'\n",
    "fig, ax = plt.subplots(figsize = (9,4))\n",
    "sns.boxplot(data = hrv,\n",
    "           x = 'Odor_Label',\n",
    "           y = y,\n",
    "           ax=ax,\n",
    "            order = order\n",
    "          )\n",
    "sns.stripplot(data = hrv,\n",
    "           x = 'Odor_Label',\n",
    "           y = y,\n",
    "           ax=ax,\n",
    "             color = 'k', alpha = 0.5, size = 3, jitter = 0.05,\n",
    "            order = order\n",
    "          )\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation = 45)\n",
    "ax.set_title(y, fontsize = 20)\n",
    "ax.set_ylabel(f'{y} (ms)')\n",
    "fig.savefig(save_folder / 'coeur_hrvmad_emosens3.png', dpi = 500, bbox_inches = 'tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec570ebd-028f-4ecc-b117-1372d6df4bb4",
   "metadata": {},
   "source": [
    "# Odeurs et respi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "2e4555e6-efcd-4cb9-9784-fd07046289f2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['odor'], dtype=object)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "resp['session'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "ddab53ef-e863-463a-a004-7e6e87bc3674",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "resp = resp_features_concat_job.get(global_key).to_dataframe()\n",
    "resp = resp[resp['session'] == 'odor']\n",
    "resp['Odor_Label'] = resp['participant'].map(label_odeurs_choisies)\n",
    "resp = resp.groupby(['participant','Odor_Label']).median(True).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "fbf526b2-a507-440d-bba7-f22739a926d0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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u3RoA8PTpU+zevRvz5s3DuXPncO7cOfTt2zfJ7jk/1LKuPd/R0fGj40xMnTp11Nc7duzAyJEj9bLeXr16YdOmTbh79y4OHz6MunXrYsWKFWrS3b1790Q/lytXLjx69AhPnz7VSxzacubMiSdPniAqKuqT9nda2bt3r/r6/YfMgf+1OMfFxSW7Hn2VZh04cECtX//jjz+SHAFY33edkuLo6IinT5+m6E6UphRL338vRKR/LOkhok8yZcoUtRVT03e3Rrly5dTXnzJia2Ly5s2L7t2748SJEyhfvjyA+IdRkyp3OHPmTLLr056v70TV09NT7Qf/6NGjOH/+vF7W26RJE+TPnx/A/x7e1fxbq1YtFClSJNHPabbX2bNndcqn9EGzz8+ePZuqZyzSg4jg999/V9+3adMmwTKaEp+3b98mu66AgAC9xHT16lX1dYcOHZJcTvt5mMToq0Ve87t//vx5xMTEJLncixcv1GdHjPHCjoh0MeEnok9StGhRtG/fHgBw6tQpnRbU8uXLqwnpwoULERERoffvt7CwUFvQY2JiEBgYmOhymucPkqKpezc3N0+2m8qPpX0x1L179xS3EAcGBiY5+JWZmZnair9+/Xrs3r1bTUQTe1hXo0WLFgDin5VYuHBhiuJIqZYtWwKI7zL0U3pVSgvTpk3D6dOnAcT/bib2fEPBggUBxCe8SZXOXL16FZcvX9ZLTNpJdVK/E3FxcVi0aFGy67G2tlZfR0ZGfnQ8moHJAgMDk+zyFQCWLFmibh/twcyIyDgx4SeiTzZ69Gi1hfHHH39Up5uZmamJ7p07d9CtW7dkk5Hg4GDMnTtXZ9rRo0dx+/btJD8TFRWljmSbLVu2ZLuC7NOnT6JJ1T///IOdO3cCiB+5NC0eZm3Tpg26desGALh8+TLq16+foHed9+3atQuVKlXC/v37k1ymR48eUBQFYWFhavJvZ2eHdu3aJfmZrl27qiOvjhkzRmck4Pc9evQo2Rjf5+3trfbdPnz4cBw5ciTZ5Y8dO5bs9+tDSEgIhg8frvYdb2tri8WLFye6rObi8cmTJ1i9enWC+e/evVN7SNIH7bswSY1H4OPj88G7Qtq/s5qucD9G9+7d1Qdthw0bhsePHydY5tKlS5gyZQqA+AfDNWV2RGS8WMNPRJ+sVKlSaNmyJbZs2YIjR47g2LFjan30N998g71792LTpk1Yt24dzp8/j759+6Jy5cpwcHBAcHAwbty4gUOHDmHr1q2wtrbGt99+q657//79mDx5MmrVqoVmzZqhdOnScHJyQnh4OAICArBgwQI1GerZsyeyZEn8sFaxYkWcPXsWFStWxMiRI+Hp6YmgoCCsX78ef/75J4D4RFnTVWRamD9/Pt6+fYtt27bh1KlT8PDwQPv27dG4cWMUKFAANjY2eP78Oc6fP49Nmzbh3LlzH1xngQIF0KBBA+zdu1etqW7fvn2y/f1bW1vj77//RqNGjRAWFoYGDRrgq6++QuvWrZE/f35ERkbixo0b2LlzJ7Zu3ZqqFmMrKyusXbsWdevWRUhICOrVq4eOHTuidevWKFiwIOLi4vD06VOcO3cOmzZtwpUrVzBnzhyd5xxSKzo6WqdryOjoaAQGBuLevXs4fvw41q9fr975cXBwwKpVq3TKzbR17doVEydORHBwMHr27Inbt2+jcePGUBQF586dw8yZM/Ho0SOUK1cu2TtGKdW4cWPkzp0bL168wNixY3Hv3j20adMGuXLlwu3bt7Fo0SLs378fNWrUSLYsrnr16urrIUOGYMyYMcibN696IV6gQIEk/za0OTk5YcaMGRgwYAAePXqEChUqYNSoUahevTpiYmKwb98+zJgxAyEhIVAUBQsXLky2+04iMhIGHOWXiIzYwYMH1WHvJ0yY8MHlT58+rS7fqFEjnXlRUVHSr18/URRFXSapn4IFC+p8dsKECR/8DABp1aqVhIWFJYhL+/+Q3Lrs7e3l0KFDH9wWBw8eTPE2TExsbKz88MMPYmdnl6L/V7NmzeTmzZvJrvPff//V+Yyfn1+KYtm9e7fkyJHjgzG8z9vbWwCIu7t7kus+ceKEuLq6puj/uHz58hTF+z53d/cUrR+AZMmSRdq2bSv37t374HrXrl0r5ubmia7HxsZG1q1bl+w2uHv3rrr80qVLP/h9u3fvFmtr6yRjr1u3rvj7+39wne3bt09yHXfv3lWXS8n+++mnn8TMzCzJ9VlZWSW531Lz/9fsQ29v7+Q3EhF9Epb0EJFeVKpUSe1ucs+ePToPwVpYWOCPP/7ApUuXMHDgQHh6esLBwQHm5uZwcHBA2bJl0bNnT6xfvx7Xr1/XWe/w4cOxYcMG9OvXD1WrVoWbmxusra1hbW2NAgUKoH379ti+fTs2b94MGxubZGOcOHEidu/ejWbNmsHZ2RmWlpYoUKAA+vfvj6tXr35SK3NKmZmZYdy4cbhz5w5+//13NG/eHAUKFEC2bNlgaWkJZ2dn1KlTB2PGjMG1a9ewfft2dVTdpLRu3VoduKxYsWI6rb3Jady4Me7cuYMpU6agevXqyJkzJ8zNzWFvb4/y5ctj8ODBas17alWtWhW3bt3CggUL0KxZM7i4uMDS0hLW1tZwdXVFo0aN8NNPP+HGjRtqqZO+2NraIm/evPD09ETXrl3x+++/4/79+9iwYQPc3d0/+Pl27drh+PHjaNOmDZycnGBpaQlXV1d4e3vjzJkzHxw1OrUaN26Ms2fPomvXrnBxcYGFhQWcnJxQp04dLFy4EPv370/RCM0rV67E9OnT1btnmh6HPsbo0aNx4cIF9O7dG4ULF4aNjQ2yZs2K4sWL47vvvkuT/UZEaUcRSYcOfYmIDERT0jBhwgRMnDjRsMGkkVu3bqkXBdOmTcP3339v4IiIiMiYsIWfiCiD0/QwlCVLFra6EhFRAkz4iYgysMDAQLVrzdatWyNPnjwGjoiIiIwNe+khIspgXrx4geDgYDx58gQTJ07EmzdvoCiK2u0kERGRNib8REQZzPfff4/ly5frTOvfv786gi4REZE2JvxERBmUpaUlChcujN69e2PgwIGGDoeIiIwUe+khIiIiIjJhJt/CHxcXhydPnsDOzk7tno+IiIiIKKMTEbx79w4uLi7Jjr1h8gn/kydP4OrqaugwiIiIiIjSxMOHD5E/f/4k55t8wm9nZwcgfkPY29sbOBoiIiIiIv0IDg6Gq6urmu8mxeQTfk0Zj729PRN+IiIiIjI5Hypb58BbREREREQmjAk/EREREZEJY8JPRERERGTCmPATEREREZkwJvxERERERCbMoAn/kSNH0KJFC7i4uEBRFGzevFln/saNG9GoUSPkzJkTiqLg4sWLBomTiIiIiCijMmjCHxoaijJlymDevHlJzq9ZsyamTZuWzpEREdHH8PPzQ7t27eDn52foUIiI6P8ZtB9+Ly8veHl5JTn/q6++AgDcu3cvnSIiIqKPFRERgV9//RWvXr3Cr7/+igoVKsDa2trQYRERZXqs4SciIr1YuXIlXr9+DQB4/fo1Vq1aZeCIiIgIMMGRdiMjIxEZGam+Dw4ONmA0RESZw6NHj7Bq1SqICABARLBq1So0btwYoaGhuH//Ptzd3eHh4WHgSImIMh+TS/inTp2KSZMmGToMIqJMQ0Tw22+/JTp93LhxcHNzg6IoOH78ODp16sSkn4gonZlcSY+Pjw+CgoLUn4cPHxo6JCIik3b//n2cOXMGsbGxOtNjY2Nx9uxZBAUF6SxLRETpy+QSfisrK9jb2+v8EBFR2nF3d0elSpVgbm6uM93c3ByVKlWCg4ODzrJERJS+DFrSExISgtu3b6vv7969i4sXL8LR0RFubm548+YNHjx4gCdPngAAbt68CQDIkycP8uTJY5CYiYhIl6IoGDJkiNqzmvb0yZMnIyQkhDX8REQGZNAW/rNnz6JcuXIoV64cAGDo0KEoV64cxo8fDwDYunUrypUrh2bNmgEAOnbsiHLlymHBggUGi5mIiBLKnz8/unTpAkVRAMQn+126dEG+fPng4eGBRo0aMdknIjIQRTRdKpio4OBgODg4ICgoiOU9RERpKCIiAp07d8arV6/g5OSEVatWsR9+ypBEBBEREXpdX2RkJG7duoVnz57B3d0dRYsW1cu6ra2t1QttynxSmueaXC89RERkGNbW1hg2bBhmzZqFwYMHM9mnDCsiIgKNGzfW6zrDwsLw8uVL9b2TkxNsbW0/eb2+vr6wsbH55PWQaWPCT0REelOjRg3UqFHD0GEQGR3tMYI07/WR8BOlBBN+IiIiIi3W1tbw9fXV2/oiIiLQsGFDAPHPI2bJkgXt27fXS1kP76RRSjDhJyIiItKiKIrey2RsbW3h5OSEmjVromjRonyIndIVE34iIiKidGBra4sGDRqw5p7SnckNvEVERERERP/DhJ+IiIiIyIQx4SciIiIiMmFM+ImIiIiITBgTfiIiIiIiE8aEn4iIiIjIhDHhJyIiIiIyYUz4iYiIiIhMGBN+IiIiIiITxoSfiIiIiMiEMeEnIiIiIjJhTPiJiIiIiEwYE34iIiIiIhPGhJ+IiIiIyIQx4SciIiIiMmFM+ImIiIiITBgTfiIiIiIiE8aEn4iIiIjIhDHhJyIiIiIyYQZN+I8cOYIWLVrAxcUFiqJg8+bNOvNFBOPHj0fevHlhY2ODBg0a4NatW4YJloiIiIgoAzJowh8aGooyZcpg3rx5ic6fPn06fv/9dyxYsACnTp1C1qxZ0bhxY0RERKRzpEREREREGVMWQ365l5cXvLy8Ep0nIpg1axbGjh2LVq1aAQBWrFgBZ2dnbN68GR07dkzPUImIiIiIMiSjreG/e/cunj17hgYNGqjTHBwcUKVKFZw4cSLJz0VGRiI4OFjnh4iIiIgoszLahP/Zs2cAAGdnZ53pzs7O6rzETJ06FQ4ODuqPq6trmsZJRERERGTMjDbh/1g+Pj4ICgpSfx4+fGjokIiIiIiIDMZoE/48efIAAJ4/f64z/fnz5+q8xFhZWcHe3l7nh4iIiIgoszLahL9gwYLIkycP9u/fr04LDg7GqVOnUK1aNQNGRkRERESUcRi0l56QkBDcvn1bfX/37l1cvHgRjo6OcHNzw+DBg/Hjjz+iSJEiKFiwIMaNGwcXFxe0bt3acEETEREREWUgBk34z549i88//1x9P3ToUACAt7c3li1bhu+//x6hoaHo06cPAgMDUbNmTezevRvW1taGCpmIiIiIKENRREQMHURaCg4OhoODA4KCgljPT0REROkuPDwcjRs3BgD4+vrCxsbGwBGRqUhpnmu0NfxERERERPTpmPATEREREZkwJvxERERERCaMCT8RERERkQljwk9EREREZMKY8BMRERERmTAm/EREREREJowJPxERERGRCWPCT0RERERkwpjwExERERGZMCb8REREREQmjAk/EREREZEJY8JPRERERGTCmPATEREREZkwJvxERERERCaMCT8RERERkQljwk9EREREZMKY8BMRERERmTAm/EREREREJowJPxERERGRCWPCT0RERERkwpjwExERERGZMCb8REREREQmzOgT/nfv3mHw4MFwd3eHjY0NqlevjjNnzhg6LCIiIiKiDMHoE/5evXph7969+Pvvv3HlyhU0atQIDRo0wOPHjw0dGhERERGR0TPqhD88PBwbNmzA9OnTUbt2bXz22WeYOHEiPvvsM8yfP9/Q4RERERERGT2jTvhjYmIQGxsLa2trnek2NjY4duyYgaIiIiIiIso4jDrht7OzQ7Vq1TB58mQ8efIEsbGxWLlyJU6cOIGnT58m+pnIyEgEBwfr/BARERERZVZGnfADwN9//w0RQb58+WBlZYXff/8dnTp1gplZ4qFPnToVDg4O6o+rq2s6R0xEREREZDyMPuEvXLgwDh8+jJCQEDx8+BCnT59GdHQ0ChUqlOjyPj4+CAoKUn8ePnyYzhETERERERmPLIYOIKWyZs2KrFmz4u3bt/D19cX06dMTXc7KygpWVlbpHB0RERERkXH6qIQ/Ojoaz549Q1hYGJycnODo6KjvuFS+vr4QEXh4eOD27dsYMWIEihUrhu7du6fZdxIRERERmYoUl/S8e/cO8+fPR506dWBvb48CBQqgePHicHJygru7O3r37p0mA2IFBQVhwIABKFasGLp164aaNWvC19cXFhYWev8uIiIiIiJTk6IW/pkzZ+Knn35C4cKF0aJFC4wePRouLi6wsbHBmzdv4O/vj6NHj6JRo0aoUqUK5syZgyJFiuglwPbt26N9+/Z6WRcRERERUWaTooT/zJkzOHLkCEqWLJno/MqVK6NHjx5YsGABli5diqNHj+ot4SciIiIioo+XooR/9erVKVqZlZUVvvnmm08KiIiIiIiI9CfV3XIGBQXhzZs3Caa/efOGg1wRERERERmZVCf8HTt2xJo1axJMX7t2LTp27KiXoIiIiIiISD9SnfCfOnUKn3/+eYLpdevWxalTp/QSFBERERER6UeqE/7IyEjExMQkmB4dHY3w8HC9BEVERERERPqR6oS/cuXKWLhwYYLpCxYsQIUKFfQSFBERERER6UeqR9r98ccf0aBBA1y6dAn169cHAOzfvx9nzpzBnj179B4gERERERF9vFS38NeoUQMnTpxA/vz5sXbtWmzbtg2fffYZLl++jFq1aqVFjERERERE9JFS3cIPAGXLlsU///yj71iIiIiIiEjPUt3CDwD//fcfxo4di86dO+PFixcAgF27duHq1at6DY6IiIiIiD5NqhP+w4cPw9PTE6dOncKGDRsQEhICALh06RImTJig9wCJiIiIiOjjpTrhHzVqFH788Ufs3bsXlpaW6vR69erh5MmTeg2OiIiIiIg+TaoT/itXrqBNmzYJpufOnRuvXr3SS1BERERERKQfqU74s2fPjqdPnyaYfuHCBeTLl08vQRERERERkX6kOuHv2LEjRo4ciWfPnkFRFMTFxcHPzw/Dhw9Ht27d0iJGIiIiIiL6SKlO+KdMmYJixYrB1dUVISEhKFGiBGrXro3q1atj7NixaREjERERERF9pFT3w29paYlFixZh/PjxuHLlCkJCQlCuXDkUKVIkLeIjIqI0IiKIiIjQy7oCAgJw//595MmTB0WKFIGVlRUURdHLugHA2tpar+sjIspMPmrgLQBwdXWFq6srYmNjceXKFbx9+xY5cuTQZ2xERJSGIiIi0Lhx409eT1hYGF6+fKm+d3Jygq2t7SevV5uvry9sbGz0uk4ioswi1SU9gwcPxpIlSwAAsbGxqFOnDsqXLw9XV1ccOnRI3/EREZGRi4yMTPY9EREZVqpb+NevX4+uXbsCALZt24Y7d+7gxo0b+PvvvzFmzBj4+fnpPUgiItI/a2tr+Pr6fvJ6AgICsHbtWsTExGDNmjWwsrLCli1bYG1trYco4+lzXUREmU2qE/5Xr14hT548AICdO3eiffv2KFq0KHr06IHZs2frPUAiIkobiqLopUymTJkysLa2RkBAAPbv3w9bW1tYW1uzBIeIyEikuqTH2dkZ165dQ2xsLHbv3o2GDRsCiK/hNDc313uARERk/Dw8PNCgQQO91+4TEdGnS3ULf/fu3dG+fXvkzZsXiqKgQYMGAIBTp06hWLFieg+QiIiIiIg+Xqpb+CdOnIjFixejT58+8PPzg5WVFQDA3Nwco0aN0mtwsbGxGDduHAoWLAgbGxsULlwYkydPhojo9XuIiIiIiEzVR3XL+eWXXyaY5u3t/cnBvG/atGmYP38+li9fjpIlS+Ls2bPo3r07HBwcMGjQIL1/HxERERGRqUlRC/+aNWtSvMKHDx/qraee48ePo1WrVmjWrBkKFCiAL7/8Eo0aNcLp06f1sn4iIiIiIlOXooR//vz5KF68OKZPn47r168nmB8UFISdO3eic+fOKF++PF6/fq2X4KpXr479+/cjICAAAHDp0iUcO3YMXl5eelk/EREREZGpS1FJz+HDh7F161bMmTMHPj4+yJo1K5ydnWFtbY23b9/i2bNnyJUrF77++mv4+/vD2dlZL8GNGjUKwcHBKFasGMzNzREbG4uffvoJXbp0SfIzkZGROoO+BAcH6yUWIiIiIqKMKMU1/C1btkTLli3x6tUrHDt2DPfv30d4eDhy5cqFcuXKoVy5cjAzS/UzwMlau3YtVq1ahX/++QclS5bExYsXMXjwYLi4uCT5zMDUqVMxadIkvcZBRERERJRRKWLEXd64urpi1KhRGDBggDrtxx9/xMqVK3Hjxo1EP5NYC7+rqyuCgoJgb2+f5jETEWVW4eHhaNy4MQDA19eXA28R/T/+bVBaCQ4OhoODwwfz3I/qpSe9hIWFJbhrYG5ujri4uCQ/Y2VlpXYVSkRERESU2Rl1wt+iRQv89NNPcHNzQ8mSJXHhwgXMnDkTPXr0MHRoREREREQZglEn/HPmzMG4cePQv39/vHjxAi4uLujbty/Gjx9v6NCIiIiIiDIEo0747ezsMGvWLMyaNcvQoRARERERZUj67VaHiIiIiIiMSqpb+GNjY7Fs2TLs378fL168SPAA7YEDB/QWHBERERERfZpUJ/zfffcdli1bhmbNmqFUqVJQFCUt4iIiIso0RAQRERF6XZ+mi2orKyv1XB0QEIAHDx7Azc0NRYsW/ah1W1tb89xPlMGkOuFfs2YN1q5di6ZNm6ZFPERERJlORESE2k97WgkLC8PLly/V905OTrC1tU31etiPPFHGk+oafktLS3z22WdpEQsRERGlEe1BKRN7T0SmK9Ut/MOGDcPs2bMxd+5c3tIjIiLSA2tra/j6+uptfREREWjVqhUAYMuWLbC2tkZAQADWrl2rLtO+ffuPKuuxtrbWW5xElD5SnfAfO3YMBw8exK5du1CyZElYWFjozN+4caPegiMiIsoMFEVJszIZa2tr2NjYoEyZMrC2tsb9+/fh7u4ODw+PNPk+IjI+qU74s2fPjjZt2qRFLERpQp8Pw2kehLt16xaePXsGd3f3j37w7X18EI6I0pqHhwcTfaJMKNUJ/9KlS9MiDqI0o++H4fT14Nv7+CAcERERpYWPHmn35cuXuHnzJoD4FgMnJye9BUVkzBJ78E0fCT8RERFRWkh1wh8aGoqBAwdixYoV6qBb5ubm6NatG+bMmcPEh4yOPh+Gi4iIQMOGDQEAHTt2RJYsWT76wbf38UE4IiIiSgupTviHDh2Kw4cPY9u2bahRowaA+Ad5Bw0ahGHDhmH+/Pl6D5LoU+j7YThbW1s4OTmhZs2aKFq0KOthiYiIyKilOuHfsGED1q9fj7p166rTmjZtChsbG7Rv354JP2UKtra2aNCgAWvuiYiIyOileuCtsLAwODs7J5ieO3duhIWF6SUoIiIiIiLSj1Qn/NWqVcOECRN0ujkMDw/HpEmTUK1aNb0GR0REREREnybVJT2zZ89G48aNkT9/fpQpUwYAcOnSJb2PEkhERBnDzZs3cf/+/UTv/hIRkeGlOuEvVaoUbt26hVWrVuHGjRsAgE6dOqFLly6sZyYiymRu3ryJ1atXAwCio6MRFhbG3tqIiIzMR/XDb2tri969e+s7FiIiymDu37+v857jUpAh6HNE9bSgHZsxxwlw1HdTlaKEf+vWrfDy8oKFhQW2bt2a7LItW7bUS2BERGT83N3dcfz4cfW9lZWVAaOhzErfI6qnpVatWhk6hGRx1HfTlKKEv3Xr1nj27Bly586N1q1bJ7mcoiiIjY3VV2xERGTkPDw80KlTJ7WG/+jRo4YOiYiI3pOihF8zou77r4mIiDw8PODh4YHw8HBDh0KEuvlywdzISlJEBHES/9pMgdGVzMSK4NDjV4YOg9JQqmv4V6xYgQ4dOiS4bRsVFYU1a9agW7dueguOiIiIKDXMFQVZzIwroQaMLZ73sC3X5KW6H/7u3bsjKCgowfR3796he/fuegmKiIiIiIj0I9UJv4gkeivq0aNHcHBw0EtQRERERESkHyku6SlXrhwURYGiKKhfvz6yZPnfR2NjY3H37l00adJE7wEWKFAgQbdvANC/f3/MmzdP799HRERERGRKUpzwa3rnuXjxIho3boxs2bKp8ywtLVGgQAF88cUXeg/wzJkzOj3/+Pv7o2HDhmjXrp3ev4uIiIiIyNSkOOGfMGECgPgW9w4dOsDa2jrNgtLm5OSk8/7nn39G4cKFUadOnXT5fiIiIiKijCzVvfR4e3unRRwpEhUVhZUrV2Lo0KFJdmkVGRmJyMhI9X1wcHB6hUdEREREZHRS/dBubGwsfvnlF1SuXBl58uSBo6Ojzk9a2rx5MwIDA/H1118nuczUqVPh4OCg/ri6uqZpTERERERExizVCf+kSZMwc+ZMdOjQAUFBQRg6dCjatm0LMzMzTJw4MQ1C/J8lS5bAy8sLLi4uSS7j4+ODoKAg9efhw4dpGhMRERERkTFLdUnPqlWrsGjRIjRr1gwTJ05Ep06dULhwYZQuXRonT57EoEGD0iJO3L9/H/v27cPGjRuTXc7KyirBoGCUsYgIIiIiDB1GorTjMtYYNaytrY1uNEciIiJKf6lO+J89ewZPT08AQLZs2dRBuJo3b45x48bpNzotS5cuRe7cudGsWbM0+w4yDhEREWjcuLGhw/igVq1aGTqEZPn6+sLGxsbQYRAREZGBpbqkJ3/+/Hj69CkAoHDhwtizZw+A+O4z06plPS4uDkuXLoW3t7dO//9ERERERJS8VGfPbdq0wf79+1GlShUMHDgQXbt2xZIlS/DgwQMMGTIkLWLEvn378ODBA/To0SNN1k/Ga17tQFiZi6HDUIkAUXHxry3NAGOrmImMVTDgSHZDh0FERERGJNUJ/88//6y+7tChA9zd3XH8+HEUKVIELVq00GtwGo0aNYKI8SR9lH6szAXW5oaOQpdxF8nw74SIiIh0pSrhj46ORt++fTFu3DgULFgQAFC1alVUrVo1TYIjIiIiIqJPk6oafgsLC2zYsCGtYiEiIiIiIj1L9UO7rVu3xubNm9MgFCIiIiIi0rdU1/AXKVIEP/zwA/z8/FChQgVkzZpVZ35a9cNPZIz+exWJx4FRyJfdEoVzcfwHIiIiMj6pTviXLFmC7Nmz49y5czh37pzOPEVRmPBTpvHfq0hsvRIIADj3MAwtPbMz6SciIiKjk+qE/+7du2kRB1GG8zgwKsF7JvxEmQdHBdcPjgpOlPY4ihXRR8qX3RLnHobpvCeizIOjgusHRwUnSnupTvg/NPjVX3/99dHBEGUkhXNZoaVndtbwExERkVFLdcL/9u1bnffR0dHw9/dHYGAg6tWrp7fAiDKCwrmsmOgTEVqW7Y8sZhaGDkMlIoiNiwEAmJtlMbqSmZi4aGy9+IehwyDKNFKd8G/atCnBtLi4OPTr1w+FCxfWS1BEREQZSRYzC2QxN66yPguwMYKI4qW6H/5EV2JmhqFDh+K3337Tx+qIiIiIiEhP9JLwA8B///2HmJgYfa2OiIiIiIj0INUlPUOHDtV5LyJ4+vQpduzYAW9vb70FRkREREREny7VCf+FCxd03puZmcHJyQm//vrrB3vwISIiIiKi9JXqhP/gwYNpEQcREREREaWBjxp469WrV7h37x4URUGBAgWQM2dOfcdFRERERER6kKqHdq9evYratWvD2dkZVapUQeXKlZE7d27Uq1cPN2/eTKsYiYiIiIjoI6W4hf/Zs2eoU6cOnJycMHPmTBQrVgwigmvXrmHRokWoVasW/P39kTt37rSMl4iIiIiIUiHFCf9vv/0Gd3d3+Pn5wdraWp3epEkT9OvXDzVr1sRvv/2GqVOnpkmgRESZnYggIiLC0GEkSTs2Y44TAKytrY1u9NlP8fzNI7wJfglHeyc4O+Y3dDhEZGRSnPDv3bsXo0aN0kn2NWxsbDBixAhMnz6dCT8RJUnfCauIwN/fHw8fPkThwoXh4eGht3UbY0IYERGBxo0bGzqMFGnVqpWhQ0iWr68vbGxsDB2GXjx/8wjnbhwBANx9ch0VitVm0k9EOlKc8N+5cwfly5dPcn7FihVx584dvQRFRKZJ3wlrWFgYXr58qb53cnKCra2tXtZtSgkhmbY3wS8TvGfCT0TaUpzwv3v3Dvb29knOt7OzQ0hIiF6CIiJKicjIyATv9ZXwG7uRACwNHcR7BED0/7+2AGBc90eAKADTDB1EGnC0d8LdJ9d13hMRaUtVt5zv3r1LtKQHAIKDgyEiegmKiEyTtbU1fH199ba+K1euoF27dgCAjh07onPnzihatKhe1p3Usc5YWAKwNLqUGrAydADJMs1zlLNjflQoVps1/ESUpBQn/CKS7IlURNKk3vXx48cYOXIkdu3ahbCwMHz22WdYunQpKlasqPfvIqK0pSiKXstkPD094eTkhMjISHTu3BllypTR27qJMhJnx/xM9IkoSSlO+A0xwu7bt29Ro0YNfP7559i1axecnJxw69Yt5MiRI91jISLjZGtrC1tbW7217BMREZmaFCf8derUScs4EjVt2jS4urpi6dKl6rSCBQumexxERERERBlVqkbaTW9bt25FxYoV0a5dO+TOnRvlypXDokWLDB0WEREREVGGYdQJ/507dzB//nwUKVIEvr6+6NevHwYNGoTly5cn+ZnIyEgEBwfr/BARERERZVap6qUnvcXFxaFixYqYMmUKAKBcuXLw9/fHggUL4O3tnehnpk6dikmTJqVnmEQmy9hHdr1y5Qrevn0LKysro44TMM6BvIiIKHMw6oQ/b968KFGihM604sWLY8OGDUl+xsfHB0OHDlXfBwcHw9XVNc1iJDJlxjyy6/uDbjVs2NCo++DnQF5ERGQoH53w3759G//99x9q164NGxubNOmWs0aNGrh586bOtICAALi7uyf5GSsrK1hZGXdP0ET06TLzoFtERESpkeqE//Xr1+jQoQMOHDgARVFw69YtFCpUCD179kSOHDnw66+/6i24IUOGoHr16pgyZQrat2+P06dPY+HChVi4cKHevoOIUia2RaxR3RO0eGGBuPNxQNz/v69ggVjnWMMG9b4YwHybuaGjSBcPwsLwPDICzlbWcOOFFxGRUUn1Q7tDhgxBlixZ8ODBA53WtA4dOmD37t16Da5SpUrYtGkTVq9ejVKlSmHy5MmYNWsWunTpotfvIaIUyGJcPzYuNnCq5AT7IvZwquIEm3w2Bo8p0Z9M4EFYGPa/fAH/4GDsf/kCD8LCDB0SERFpSfXpaM+ePfD19UX+/Loj+hUpUgT379/XW2AazZs3R/PmzfW+XiLK+GycbWDjzLp4Q3seGZHgPVv5iYiMR6pb+ENDQxOtk33z5g1r54mIMiFnK+tk3xMRkWGlOuGvVasWVqxYob5XFAVxcXGYPn06Pv/8c70GR0RExs/N1hb1nXKjlL096jvlZus+EZGRSXVJz/Tp01G/fn2cPXsWUVFR+P7773H16lW8efMGfn5+aREjEREZOTdbWyb6RERGKtUt/KVKlUJAQABq1qyJVq1aITQ0FG3btsWFCxdQuHDhtIiRiIiIiIg+0kf1IeHg4IAxY8boOxYiIiIiItKzFCX8ly9fTvEKS5cu/dHBEBERERGRfqUo4S9btiwURYGIJLucoiiIjTWygW+IiIiIiDKxFCX8d+/eTes4iIiIiIgoDaQo4Xd3d0/rOIiIiIiIKA2kupeeqVOn4q+//kow/a+//sK0adP0EhQREREREelHqnvp+fPPP/HPP/8kmF6yZEl07NgRI0eO1EtgRERExkz7ubaY2GgDRpLxaG+vDz0fSESfLtUJ/7Nnz5A3b94E052cnPD06VO9BEWZm/bBP5LPgKeK9vbiSZQobUVGRqqvt176w4CRZGyRkZGw5aBtRGkq1Qm/q6sr/Pz8ULBgQZ3pfn5+cHFx0VtglHlpn0QHHMlhwEgyNp5EiYiICPiIhL93794YPHgwoqOjUa9ePQDA/v378f3332PYsGF6D5CIiMgYWVlZqa9blumPLOYWBowmY4mJjVbvimhvRyJKG6lO+EeMGIHXr1+jf//+iIqKAgBYW1tj5MiR8PHx0XuAlPloH/zn1X4LK3MDBpPBRMb+764IT6JEaUtRFPV1FnMLZDG3NGA0GZf2diSitJHqhF9RFEybNg3jxo3D9evXYWNjgyJFijC5IL3RPvhbmQPWTPg/Ck+iREREBHxEt5xLly5FeHg4smXLhkqVKqFUqVJM9omICA/CwnDm7Rs8CAszdChERKQl1Qn/qFGj4OzsjJ49e+L48eNpERMREWUwD8LCsP/lC/gHB2P/yxdM+omIjEiqE/7Hjx9j+fLlePXqFerWrYtixYph2rRpePbsWVrER0REGcDzyIhk3xMRkeGkOuHPkiUL2rRpgy1btuDhw4fo3bs3Vq1aBTc3N7Rs2RJbtmxBXFxcWsRKRERGytnKOtn3RERkOKlO+LU5OzujZs2aqFatGszMzHDlyhV4e3ujcOHCOHTokJ5CJCIiY+dma4v6TrlRyt4e9Z1yw41jQBARGY2PSvifP3+OX375BSVLlkTdunURHByM7du34+7du3j8+DHat28Pb29vfcdKRERGzM3WFpVyODLZJyIyMqlO+Fu0aAFXV1csW7YMvXv3xuPHj7F69Wo0aNAAAJA1a1YMGzYMDx8+1HuwRERERESUOqnuhz937tw4fPgwqlWrluQyTk5OuHv37icFRkREREREny7VLfxLlixJNtkH4gf8cXd3/+igtE2cOBGKouj8FCtWTC/rJiIiIiIydSlO+A8cOIASJUogODg4wbygoCCULFkSR48e1WtwGiVLlsTTp0/Vn2PHjqXJ9xARERERmZoUl/TMmjULvXv3hr29fYJ5Dg4O6Nu3L2bOnIlatWrpNUAgvivQPHny6H29RESkPw/CwvA8MgLOVtZ8cJeIyIikOOG/dOkSpk2bluT8Ro0a4ZdfftFLUO+7desWXFxcYG1tjWrVqmHq1Klwc3NLdNnIyEhERkaq7xO7I0FElBGJiPo6Kn6KoUJJ4GFYGA6+fPn/74LxuZMTXI0s6Y/Seq29LYmITF2KE/7nz5/DwsIi6RVlyYKX6sFef6pUqYJly5bBw8MDT58+xaRJk1CrVi34+/vDzs4uwfJTp07FpEmT9B4HEZGhaTdmJN38kr7CwsLUhpZIrekXIyORw8gSfm2RkZGwNeL4iIj0KcU1/Pny5YO/v3+S8y9fvoy8efPqJShtXl5eaNeuHUqXLo3GjRtj586dCAwMxNq1axNd3sfHB0FBQeoPuwclIkobYWFhePnyJYKDgxESEoLo6Gh1npWVlQEjIyIibSlu4W/atCnGjRuHJk2awNpad8j08PBwTJgwAc2bN9d7gO/Lnj07ihYtitu3byc638rKiicaIjJJ2se2kQAsDRcKAOBsZCSuad5YWMDJygpOVlZwtrIyunIeIL6kR3NnhOcJIspMUpzwjx07Fhs3bkTRokXx7bffwsPDAwBw48YNzJs3D7GxsRgzZkyaBaoREhKC//77D1999VWafxcRkTFRFEV9bQnAEkrSC6eD/FbWuIn/PSdVzt7ByB/W/V/dvva2JCIydSlO+J2dnXH8+HH069cPPj4+6gNPiqKgcePGmDdvHpydnfUe4PDhw9GiRQu4u7vjyZMnmDBhAszNzdGpUye9fxcREaVO7v9vKfc0+mSfiCjzStVIu+7u7ti5cyfevn2L27dvQ0RQpEgR5MiRI63iw6NHj9CpUye8fv0aTk5OqFmzJk6ePAknJ6c0+04iiqfTk0mM4eLQFv4iHJFvI2GVwwo2uW0MHU7ytLaZqfUK8yAsDPtfvjB0GERElAKpSvg1cuTIgUqVKuk7lkStWbMmXb6HiBLS7hXGfJu5ASOJFxYWhtcvXwMAQhACJyenDNPTiqn1CvM8MiLBe7bwExEZpxT30kNEZGjaFyCJvaf042xlnex7IiIyHh/Vwk9EmYN2TyaxLWINfsSweGGBuPNx/3tf3gKxuWMNGNEHxPzvzoip9QrjZmuL+k65ObJuBvH8zSO8CX4JR3snODvmN3Q4RJTOmPATUZJ0ejLJAoMfMWxcbOBk7oTIN5GwcrSCjbOR1/BrMcVeYdxsbZnoZwDP3zzCuRtHAAB3n1xHhWK1mfQTZTJM+IkoQ7FxtslQiT6Rob0JfpngPRN+osyFNfxEREQmzNHeKdn3RGT62MJPRERkwpwd86NCsdqs4SfKxJjwExHRR3sQFsYHdzMAZ8f8TPSJMjEm/ERE9FG0B9/yRzDqO+Vm0k9EZIRYw09ERB8lscG3iIjI+LCFn4goA4oCAIhBY3C0soL2KAg5rKwQ8v8xWQAwto5IowwdABGRgTDhJyLKgKYZOgAAsLVFmJMTIiMjYWVlhfss5yEiMkpM+ImI6KPZ2trClok+EZFRY8JPRJRBWFtbw9fX19BhJCkiIgKtWrUCAGzZsgXW1tYGjihpxhwbEZG+MeEnIsogFEWBjU3GGGXY2to6w8SqDzFx0YYOQYeIIDYuBgBgbpYFimJcT1QY2/YiMnVM+ImIiD7R1ot/GDoEIqIksVtOIiIiIiITxhZ+IiJKMzdv3sT9+/fh7u4ODw8PQ4ejV8b8TAWfpyAibUz4iYgoTdy8eROrV68GABw/fhydOnUyqaQ/ozxTkdmepyCihFjSQ/SR/nsViSO33+G/V5GGDoXIKN2/fz/Z90RElD7Ywk9GLTJWgaFHE9UmAkTFAXdfR2LPtcD4kUTvh6FZqewolMvK0OH9//YiMg7u7u44fvy4znsiMn0igoiICEREROhlfXFxcQgODtbLujTu3LmDx48fI1++fChUqJDe1mtvbw8zM/20p1tbW8Pa2lovvWwx4SejNuBIdkOHkKi3b98iOPh/t8gPvbFCjhw5DBgRkfHx8PBAp06dTLaGn4gSFxERgcaNGxs6jCSFhYXh5cuX6nsnJyejHUDQ19dXLyV5TPiJUiEsLAyRkZEQ0b3rYGVl+NZ9ImPk4eHBRJ+IjEpkZGSC98aa8OsLE34yOvru+UK7t4pP8X6LgJ2dHRRFgZWVlV4OFPruSYM9XxARkSFozuPGWtJz584dbN26VX3fsmVLvZX1pEVJjz4w4SejY6w9X7zfIqAoil7LeNiTBhERmQLNeVyf57ScOXPqbV0FCxZE/vz5M1W5YYZK+H/++Wf4+Pjgu+++w6xZswwdDmUQ+rpjEBAQgLVr1yImJn64en13McgWeSIiovSR2coNM0zCf+bMGfz5558oXbq0oUOhDEZfdwzKlCkDa2vrTNUioCPG0AEkFP48HJGvI2GV3Qo2eW0AY+ukyAi3GRERZT4ZIuEPCQlBly5dsGjRIvz444+GDocysczWIqDNfJu5oUPQERYWhtcvXwMAQhBi1L0sEBERGVKGGHhrwIABaNasGRo0aPDBZSMjIxEcHKzzQ0SmJ7FeFoiIiCgho2/hX7NmDc6fP48zZ86kaPmpU6di0qRJaRwVUeag7x6T9CkgIAD//PMP1qxZAwBYsmQJPD09DRxV0viMBhERGYpRJ/wPHz7Ed999h71796b4ZOnj44OhQ4eq74ODg+Hq6ppWIRKZNGPtMQmIf6YCAHbu3AkrKyt4enoabaxERESGZNQJ/7lz5/DixQuUL19enRYbG4sjR45g7ty5iIyMhLm5bl2xlZUVB0EiyiSKFi3KEY6JiIg+wKgT/vr16+PKlSs607p3745ixYph5MiRCZJ9IiIiIiLSZdQJv52dHUqVKqUzLWvWrMiZM2eC6URERERElFCG6KWHiIiIiIg+jlG38Cfm0KFDhg6BiIiIiCjDyHAJPxFlXCKCiIiIT1pHQEAAHjx4ADc3N7i5uanTP3W977O2toaiGNvQvURERKnHhJ+I0k1ERAQaN2780Z8PCwvDy5cv1ffao+u2atXqk+PT5uvry24+iTIIEVFfx8ZJMksaj1fB7xAYGobsWW2Ry97OoLFobzPtbUmmgwk/EWUYiY2uq0n4iSjz0j42HHryyoCRpExyjReGxuOqaWLCT0Tp5lNH7g0ICMDatWvV9+3atYO7uzuA+DE49FmCw5FxiSitsPGC0hsTfiJKN586cm+ZMmVgbW2N+/fvw93dHR4eHnqMjogyKu0BN+u65IK5mXE/f/PK3hpX7seo7z3d8xq0rCc2TtQ7Ixy81DQx4SeiDMXDw4OJPhHp0Lm7Z4S5vohAUyZvpgC57O3g6e5qNDX82tuMnRWYJib8REREZDIOPTb+Gv7/McP94AggWL+9jBG9jwNvERERERGZMLbwExHRJ7l58ybu378PZ2dnQ4dCmdSndgiQ1iIiItSug7ds2WLUnQIYc2z08ZjwExHRR7t58yZWr14NAIiOjkZYWBh7G6F096kdArxPH4MEAv8bKDAtL4Y5SCClBBN+IiL6aPfv39d5z+4FyRR86iCBQNJ97XOQQDIE1vATEdFH04yDoMEu/YjiJdbXPpGhsIWfiIg+moeHBzp16qTW8B89etTQIRF9Mn08E/D+QIGtWrVCkSJFOEggGQQTfiIi+iSasRHCw8MNHQqRXujjmQAOFEjGhAk/ERERURrgQIFkLFjDT0RERERkwpjwExERERGZMJb0EBERGZi++n3X0F5XRESE2h+8m5sbihYt+knrZr/vRBkPE34iIiID00e/70lp2LBhov3Bfyz2+06U8TDhJyLKpNJyNFF9tlYDbFX+FIn1B8/B0YgyF0VExNBBpKXg4GA4ODggKCgI9vb2hg6HiMhohIeHp9loovpm6q3K+i7pERE10b9//z7WrVunzmvfvv0nlfXw4ovIeKQ0z2ULPxERfTS2HuuHPvp9f59mP+TIkQM2NjbsD54oE2MLPxFRJqWPVuX0HE2UrcpERLpMpoV//vz5mD9/Pu7duwcAKFmyJMaPHw8vLy/DBkZElMFxNFEioszB6BP+/Pnz4+eff0aRIkUgIli+fDlatWqFCxcuoGTJkoYOj4go0+NookRExi1DlvQ4OjpixowZ6Nmz5weXZUkPEREREZkikynp0RYbG4t169YhNDQU1apVM3Q4RERERERGL0Mk/FeuXEG1atUQERGBbNmyYdOmTShRokSiy0ZGRur0GhEcHJxeYRIRERERGR0zQweQEh4eHrh48SJOnTqFfv36wdvbG9euXUt02alTp8LBwUH9cXV1TedoiYiIiIiMR4as4W/QoAEKFy6MP//8M8G8xFr4XV1dWcNPRERERCbFJGv4NeLi4hIM9qJhZWUFKyurVK1P0xe1vkY5jIuL03sp0Z07d/D48WPky5cPhQoV0tt67e3tYWamnxs91tbW7CubiIiIyMgYfcLv4+MDLy8vuLm54d27d/jnn39w6NAh+Pr66u07IiIiPnl4+bSUXkPX64Ovr6/eR4skIiIioo9n9An/ixcv0K1bNzx9+hQODg4oXbo0fH190bBhQ0OHlm44dD0RERERfawMWcOfGimpbTL2kp47d+5g69at6vuWLVvqrayHJT1EREREGZNJ1/Drm2Z4eX2WouTMmVNv6ypYsCDy58/PoeuJiIiIKNWY8GcQHLqeiIiIiD5GhuiHn4iIiIiIPg4TfiIiIiIiE8aEn4iIiIjIhDHhJyIiIiIyYUz4iYiIiIhMGBN+IiIiIiITxoSfiIiIiMiEMeEnIiIiIjJhTPiJiIiIiEyYyY+0KyIAgODgYANHQkRERESkP5r8VpPvJsXkE/53794BAFxdXQ0cCRERERGR/r179w4ODg5JzlfkQ5cEGVxcXByePHkCOzs7KIpi6HA+WnBwMFxdXfHw4UPY29sbOpxMjfvCuHB/GBfuD+PBfWFcuD+Mi6nsDxHBu3fv4OLiAjOzpCv1Tb6F38zMDPnz5zd0GHpjb2+foX8xTQn3hXHh/jAu3B/Gg/vCuHB/GBdT2B/Jtexr8KFdIiIiIiITxoSfiIiIiMiEMeHPIKysrDBhwgRYWVkZOpRMj/vCuHB/GBfuD+PBfWFcuD+MS2bbHyb/0C4RERERUWbGFn4iIiIiIhPGhJ+IiIiIyIQx4SciIiIiMmFM+ImIiIgoUXzU0zQw4SciIqI0w4Qx44qNjcXRo0cBcD+mlfTarkz4KcU0v5TPnj1DTEyMgaPJ3HjgJUqe5m/k1KlTuHTpkoGjydwURcHGjRsxcuRIQ4dCqXT9+nXMmDEDYWFhhg7FJMXFxUFRFADA69ev0/S7mPBTiimKgjVr1qBx48Z48OABk04D0Gxzbnui5CmKAl9fXzRu3BhPnjxBbGysoUPKtK5evYrBgwejSJEi3A8ZTLZs2RAaGgpbW1s1MSX9MTOLT8MHDhyI0aNHIygoKM2+K0uarZlMhohAURSEh4dj1apV6NGjBwoVKmTosDIdzX7Yt28fVq5cicDAQLi5uWH8+PHImTMnD8bv0Wwvypxev36NgwcPYsyYMfDy8jJ0OJnW9evX8e+//6JVq1bo1asXE/4MKEuW+FRxyZIluH37NsLDw1GnTh20adPGwJGZhv/++w/79u3D4sWL4eDgkGbfwxZ++iBFUbB//360adMGlpaWaN68uaFDypQURcHmzZvRpk0b2NnZoVmzZlizZg3atm2Lx48fGzo8o6JJ9k+cOIEFCxZg1KhRuHLlCm9LZxKXLl1CwYIFsWnTJuTPn9/Q4WRagYGB6N27N37//Xf1GGVubo64uDgDR0Yp5ebmhj179uCXX36Bj48PIiIi8PjxY4wYMQLDhg0zdHgZ3pQpU/Dzzz+jTp06qFatWpp+FxN+SpHY2FhcuHABu3fvVg/WPGinrxcvXmDy5MmYNGkS5syZg3bt2sHS0hKlS5dmUvMeRVGwYcMGtGzZElu3bsWlS5dQtWpVzJw5E8HBwYYOj9JYmTJl0KZNG9y6dQtXr15FeHi4oUPKVDQlh9mzZ8fPP/+MMmXK4Ny5c9iyZQuA+DIGliVmDGZmZvD19cXcuXOxbds2/Pbbb2jfvj0eP36M8uXLGzq8DC0qKgpBQUFYsmQJ/P390/6OtBClQHR0tOzdu1dy584trVu3VqfHxcUZMCrTNXv2bPHz89OZ9ujRI/H09JSQkBB5+PChuLi4SJ8+fdT5vr6+6R2m0fL395f8+fPL0qVLRST+91dRFJk8ebJhA6M0kdRx6KuvvhJbW1tZv369REZGpnNUmY9mPwQFBUlERIRERUWJiMjp06elZs2a0rx5c53jFM8fGcPixYulTp06IiKybt06sbOzk/nz54uISEhIiBw9etSA0WUcsbGxCaYFBQXJlClTRFEUWbBgQZp+PxN+SkBzEA4ICJDDhw/LmTNn5Pnz5yIisnv3bsmRI4d06NBBXT6xX2L6eDExMVKrVi3JlSuXnD59Wp0eFBQkJUuWlHnz5kmhQoWkb9++6gn1zp07UrduXTlw4IChwjYqR44ckbp164qIyPXr18XV1VV69eqlzn/06JGhQiM90xyv/Pz8ZPLkyTJu3DhZtGiROr9z585ib28vGzZsYNKfhjT7YceOHdKgQQOpWrWqVKxYUT0mnTx5UmrVqiUtWrSQPXv2GDJUSkZi5/Nly5ZJ165dZefOnZItWzY12RcR2bhxo4wcOVJevHiRnmFmONrb9erVq3L48GF58OCBREREiIjI6NGjRVEUWb58eZrFwISfdGgO2hs2bBA3NzcpU6aMFC9eXOrVqyd79+4VkfiWZEdHR+ncubMhQzVp4eHh0rJlS3F2dpZTp05JbGysxMTEyLfffisODg7i5eWls7yPj49UqFCBiez/W7VqlZQoUUIePXokBQoUkN69e6sH3N27d0vv3r3l1atXBo6S9GXDhg2SPXt26dChg3Tr1k2yZ88uX331lTq/S5cukjNnTlm9erV6kUz6t23bNrGxsZGffvpJjh07Jq1bt5asWbPKuXPnRETk+PHj8vnnn0udOnVk//79Bo6W3qedlK5du1YuXbokIiLXrl0TCwsLURRFvWsqIhIWFiaNGzeWnj178m5NMrS3zahRo6RUqVLi5OQkdevWlfbt28vbt28lKipKxo8fL2ZmZrJixYo0iYMJP4mI7h+6n5+fODg4yNy5c0VEZPXq1WJmZiYzZswQkfhf3j179oiiKNKjRw+DxGuq4uLi1H3x5s0badCggRQvXlxOnTolIiLnzp2TOnXqSK1atWTWrFmydu1a6d+/v9jb28vFixcNGbrBaA6mN27ckMuXL4tI/N2QmjVrirm5uXTv3l1nue+//14aNmwor1+/NkzA9MliYmLU17dv35YCBQqox6uAgADJnj279O3bV+e41qxZM3Fzc5N3796le7yZQXh4uDRv3lwmTpwoIiKPHz+Wzz77TKfsUERk//790rRpU3nw4IEhwqQkaCel33//veTPn1+mTZsmgYGBIhJ/AWBtbS2jRo2SQ4cOycGDB6Vhw4ZSunRpiY6OTrAOSujXX38VJycnOXz4sIiI9O3bV2xtbeXQoUMiIhIaGirjx48XRVFk586dev9+JvyZ3IkTJxJMmzZtmrRv315ERB48eCAFChSQfv36qfNfvnwpIiIHDhyQGzdupE+gmYT2HRYvLy9p3LixKIoirq6ucvLkSRGJvyDr37+/uLi4SPny5cXLy0tNdDMbzfbauHGjFC1aVH777Td5/PixREVFyZw5c6RUqVLSvXt3CQwMlAsXLsioUaMke/bscuXKFQNHTh9j1qxZCVrojx8/LuXLlxcRkfv370v+/Pnlm2++Uedr1xfzDph+DB48WGbPnq0zLTg4WEqUKCHnz5+Xt2/fJnjGaPHixfL27VsRiW8ZJuPwfpI+e/ZsyZUrl5w9e1ZCQ0PV6ZGRkbJy5UpxcXERFxcXqVChgjRv3lz9e9S+CCfRyY3i4uIkNDRUWrdurdbpa8qjFi5cKCLxF8xRUVESFRUlixYtUi+i9IkJfya2atUqqV+/foKWzh9//FGGDRsmT58+lXz58kmfPn3UlrKdO3fK3Llz1boz0j8/Pz+xsrKSRYsWydWrV+Xo0aNSv359cXZ2VpN+kfhW7LCwsEx/8tyxY4fY2trK77//riYUIvEH0FmzZkmJEiXEyspKSpUqJWXKlJELFy4YLFb6eDdv3pSqVatKQECAzvSLFy9K9erV5cCBA+Lm5iZ9+/ZVT5YXLlwQb29v9YKYLZD6sWDBAjl//nyC6W3btpU+ffqIm5ub9OvXT31mIjAwUJo0aaLWfnM/GIf3z+NxcXHStWtXGTt2rIj8L4nX3l/Pnz+Xmzdvyr1799TpaZGcZmSDBg2SgQMHisj/tl1MTIw0atRIDhw4INu3b9d5FkKT5O/atUtnPfrerkz4M7GAgAC5f/++iIg8fPhQnT537lzJmTOn5M2bV7799lt1emxsrPTs2VP69u2b6ZPMtLRo0SKpUqWKhIeHq9MCAwOlXr164ubmJmfOnDFgdMYjLi5OgoODpUGDBjJhwgQRie8x4u7duzJnzhxZt26diMT/3u7cuVNu3rzJB8sysJiYGLUc58SJE2rL4q1bt6R8+fJia2srX3/9tc5nhg4dKvXr1+fzGmlk586dMn36dDUxmT17tuTLl09q1Kihs5yPj48UK1ZM7t69a4AoKTGdO3eWTp066UwLDQ2VIkWKyJAhQ9RpmoQ1PDxc/vvvvwTrYacdCe3du1c9Pj19+lRE4pP6Zs2aSbly5SRHjhw6PfI8fPhQGjRooNPZQFpgwp9JaV+xX7p0SSpVqiRz5sxRp3Xs2FEsLS3l0qVLEhYWJu/evZNRo0aJs7OzXL9+3RAhZxq//PKL5MyZU32vOZnu3r1bFEVRb7dS/O9xixYtZPDgwXL79m357rvv5PPPPxdXV1dxdHSUQYMGGTpE0rNXr15JqVKlxNPTU21BXrt2rZibm8uAAQPkwIEDcuHCBRkyZIhkz54905a7pYW4uDidc8fMmTNFURT59ddfRSS+rKdXr15SpkwZadeunUyePFm6dOki2bNn5501I3Pz5k3170e7JXngwIFSv359uXr1qs7yFy5ckE6dOsm9e/fSNc6M5P07VytXrpRatWqpz+Ddvn1bChUqJBUqVJDo6GgJCwuT169fi5eXl9SsWTPNy6I48FYmFxkZCUdHRxQoUABr167FggULAAC//PILqlWrhtq1a6Ny5cpo3rw5/v77b+zatQvFihUzcNSmrUOHDnB0dMTQoUMRFxenDmueK1cufPHFF6hXrx7s7OwMHKVxiIuLQ9GiRXH8+HF4eHjg8ePH6NGjBy5evIivv/4az549M3SIpGcODg6YPn06LC0tUbt2bURGRqJdu3ZYuHAh/Pz88MUXX6Bbt244cuQIDh48CE9PT0OHbDIURYGiKDhw4ADu3buHIUOG4Pfff8fw4cMxbdo02NnZ4ZdffkGvXr0QEhKCffv2wcbGBn5+fihbtqyhwyctRYsWhaWlJRYsWICiRYsiNDQUAFC3bl3cuXMHCxcuxMWLFwHED/o4YcIEPHv2DK6urgaM2ri9P3CWoigwNzfHlClTcPr0aRQuXBhz5szBrVu3UKFCBVSvXh0tW7bEs2fPcODAAZibmyM2Njbt4hPhcHeZ1fHjx/Hvv/9i9uzZuHbtGqZPn46AgAD07NkTPXv2BAAsX74cgYGBcHJyQo0aNeDu7m7gqE2HiEBRFJw7dw7+/v5wc3ND5cqVYWNjg+nTp2Pz5s2oUqUKfvvtNwQFBeHXX3/F1atX8e+//8LS0tLQ4ac7zfa6fv06Xr58iaioKDRo0ABxcXG4fPkyHj9+jGbNmqnLde/eHXFxcViyZIl60UQZj2Z/xsTEIDY2FlZWVoiOjsbhw4cxbNgw2NjY4PDhw7CyssKDBw/w7t07WFtbw9HRETly5DB0+CYnMjISTZs2hb29PdauXQsLCwvMnTsXgwYNwtSpUzFy5Eh1WYmvIoCZGdsWjdX58+fRqVMn2Nvb4/Dhw7C1tcVff/2FuXPnIjg4GFmzZlVHRj5z5gwsLCwQFxfHffqepLbJunXrsHDhQlhbW+OHH35AuXLl8OzZMyxfvhwigvz586NTp04wNzdHTExM2p6r0vT+ARm1P/74Q8zNzdVbdFevXhVvb2+pWrVqmo/4RvE2bdokVlZWUrp0aVEURXr16iU3btyQsLAwmT59uhQpUkSyZcsmnp6ekj179kQflMsMNLdK169fL7lz55ZSpUqJoihSt25d+fvvv3WWffz4sYwYMUJy5Mgh/v7+hgiX9ER7MKeOHTtK06ZN5d9//xWR+Nrhffv2SenSpaVKlSocVCsdzZkzR6pWrapT3jFnzhy1vIc9thinxOrtY2Nj5cqVK1KsWDEpW7as+nzeqVOnZMOGDTJmzBhZtmyZWvbDB3QT0t6uGzdulNWrV8umTZvUaWvWrJEGDRpI8+bNdTre0JYefzNM+DMh7TozLy8v8fb2Vp/Wv3Hjhnh7e0utWrUSdLtG+qHZ/o8ePZLmzZvLwoULJSoqSrZt2ybFixeXTp06qfWTb9++lYULF8ratWsTfWAqMzlz5ozkyJFDFi1aJM+ePZPr16/Ll19+KXXr1pVly5aJiMj27dulQ4cOUrx4cdYMm4i9e/dK1qxZpWvXrtKqVSsxMzOT8ePHS2RkpJr0ly9fXooXL85BtfREc4xKqjedsLAwKVCggE6nDiIi8+bNE0VRdJ4HI+OgnZTu3btX1q5dKydPnlT72ff391eTfu3uOLXxQi4h7b+RoUOHiqOjoxQuXFjy5cunjgEjEp/0N2zYUFq2bCl+fn6GCJUJf2bx/oE7JiZG4uLi5LfffpNKlSrp9E998+ZNadu2rTRq1Einm0PSn8OHD8ugQYOkdevW8uzZM3X6zp07pWTJktKpUyc5ffq0ASM0PvPnz5dy5cpJRESE+vv833//SatWrdSRhyMjI2X9+vUc1MdEPH/+XObNmye///67Om358uViZmYmY8aMkaioKLUXppo1a7IXGD15vyewc+fOyc2bN3USvhUrVki5cuXUUXQ1Fi5cKNeuXUuXOCn1vv/+e7Gzs5PPPvtMLCwspE2bNuogT/7+/lKiRAmpVKkSB6hLpWfPnknt2rXlypUrcufOHVm9erU4ODhIhw4d1GX+/fdfKVeunIwYMcIgMTLhN2ELFizQGa3t+PHj0qlTJ7l//77aoh8eHi5ubm4yYMAAnc/eunVLHj9+nK7xZiZLly4VCwsLyZEjh/oEv8auXbukbNmy0rJly0zbG8+DBw9k8eLFsnDhQjly5IiIiCxZskSKFi2qjhuhubV8/vx5URRFjh8/brB4Sf9u374tiqKIi4uL/Pnnnzrzli9fLoqiyLhx4yQyMlId2IY+3Y4dO8TOzk7evHkjMTExEhISIvny5ZMKFSpIp06d5OHDhxIXFyePHj2SYsWKyW+//SYi7J7RWGk39p0+fVo8PDzk6NGjEhYWJgcPHpSmTZtKo0aN5ODBgyIicvnyZcmVK5f06NHDQBFnPDNnzpT69evLV199peZWkZGRsnHjRnFwcJCOHTuqy+7bt89gfytM+E1QbGysPHz4UJo2bapTBrJo0SIpX7685MmTR7799lvZvXu3iMR3HVWzZk018eSgKOljw4YNkjt3bunbt2+CwYS2bt0q1apVy5QXXZcuXRJ3d3epXLmy5MyZUwoXLizbt2+XW7duiaIoMmvWLJ3lAwICpGTJknLp0iUDRUxpZdq0aaIoiowaNUpiY2N1jk0rV64URVFk8uTJBozQ9ISGhqrHHc2d32fPnsmSJUukTp06kitXLhk4cKBcvnxZli5dKs7OzryjZkRiYmLk+fPnCaZPnz5dBg8erDP6sUh8Q2CVKlXURr/Y2Fi5ffs2y3dSKCIiQn755RfJmzevVKhQQWdeZGSkbNq0SRwdHaVRo0Y68wyR9DPhN0GaAZs0t+ROnz4te/fuVefPmTNHOnbsKNbW1jJw4ECZPHmylC9fXhYvXmyQeE2dJkkJCQmRN2/e6MxbtmyZ5MuXT7777ju5deuWzryQkJB0i9FYXLp0SWxtbWXUqFESGhoqe/fuFRcXF7Vk59dff5UsWbLIjBkz5MGDBxIUFCSjR4+WggULqgOckGmZOnWqmJmZJWjlF4mvi2X5iH6sWrVKJ1G8efOmKIoiCxcuFJH/Hcf++OMP6dy5s1haWkqTJk1EURT5448/2FBkJFavXq3eFdXWv39/URRFKlasqNbta/bZn3/+KTY2NgmOoUz6E0rs+ZYXL17I/PnzxcrKSoYOHaqzfGRkpPzzzz/SqFEjg98FY8JvYpYtWyZdunRRa+/fvHkjderUkZo1a8qWLVvU5UJCQmTPnj3SsGFDady4sSiKIh4eHurtcdIPzbbctm2bNGrUSAoVKiTe3t6yY8cOdZmlS5dKvnz5ZOjQoXLjxo0En80sHjx4ILly5ZJ27drpTK9UqZIUKVJEAgMDJSoqSlauXClWVlZSuHBh8fDwkDx58iSoI6aMRfO7fvXqVfHz85M9e/bozJ88eXKSST99utevX4utra3UrVtXHY06JCREhg0bJlZWVrJixQqd5UNCQuTAgQNSv359KVy4cII7lGQ4Y8eO1RkpV9v48eNFURRZsmSJTjK/c+dOKVWqFBtNPkA7YX/16pW8e/dOLS19+fKlzJ07V3LkyJGgRl+7ZyNDJv1M+E1IXFycjB8/XipVqiQDBgxQk/6TJ09Kw4YNxcvLS6erKJH4K9MzZ85Ir1692KtJGtm6datky5ZNxowZI9u3b5dq1apJ9erVZcmSJeoyy5cvF2tra/Hx8cm0PY3cvXtXKlWqJC1btpRjx46JiMiUKVNEURR1+tdffy2bNm2SPXv2yLp168TX15cjP2ZwmmR/48aN4ubmJiVKlJBs2bLJl19+qXMBPHnyZLG2tmbvYWnk+vXrUrBgQalfv76a9IeGhsro0aNFURSd7m81ScubN2/YsYORmTx5sowcOVJE4uvxT5w4oTNq7nfffSeWlpYya9YsOX/+vNy/f18aNWokNWvWzHSNTKmhnahPnz5datasKZUrV5ZWrVpJcHCwiMRfBMydO1dy5syp7gNjwoTfxMTExMj06dOlWrVq0rdvX/UBxzNnzsjnn38uXl5eOi39lLZu374tZcuWVbupCw8Pl7x584q7u7tUrFhR7U5SJP6WemZvKQsICJAmTZpIy5YtpVevXuLk5CTr1q2T+/fvy8aNG+WHH36QXLlyScGCBRPcCaCMa8+ePZI9e3ZZtGiRxMXFyZEjR0RRFGnRooVOsuLj4yM5c+ZkkqknmiRG8++NGzckf/78Uq9ePXn58qWIxLfmv5/0x8XFMTk0UtevX5e3b9/K1KlTpUyZMuLs7Cz16tWTtm3bqsuMGDFCFEURW1tb6dWrl9SvX19taDJ02Ymx8/HxEWdnZ/nzzz9l3bp1UqRIESlbtqz63MurV6/kjz/+EEVRZN68eQaOVhcTfhOiOQDHxMTIlClTpGrVqkkm/du2bTNkqJnG06dP5eeff5aXL1/K48ePpVChQjJgwAB59uyZfPbZZ1KhQgX2Wf2emzdvSsOGDcXa2lpmzJiRYP6rV69k3bp1mf7iyFSEhIRIv379ZOLEiSIicufOHSlcuLB07txZnJ2dpUGDBnL58mV1eU0iSh8vuaTu+vXrki9fPqlfv36CpN/KykoWLVqUXmHSR5o1a5Zkz55djhw5IqGhoTJ48GBRFEUOHz6sLjNp0iRRFEX++ecfdRoH1Urerl27pEyZMuod6K1bt4q9vb24uLhIwYIF1aT/xYsXsmHDBqN7BoIJfwamOWiHh4fLu3fv5NGjR+pDV5qW/ipVqiRI+hs2bCjVq1eXXbt2GSx2U3fq1Cnx9fUVEZEnT56IiMiAAQOkU6dOEhQUJCIi3t7ekjNnTmnTpg1bLN9z+/ZtadSokXh5ecnRo0fV6Zm13MkUaCeZmteav43NmzdLQECAvHnzRipUqCA9e/YUkfgTqqIoUqdOHbl+/Xr6B22CNNv+zp07MnXqVGnfvr20bNlSFixYoF5YJZX0Dx48WBwdHdVjGBmf0NBQ+fLLL9W7x5puVjUXatrd1w4ePFisrKxk3bp1Bok1ozly5Ij88MMPIhL/3EOuXLlk3rx5cunSJXF0dJQKFSok6LHKmC6imPBnUJqD9rVr16RVq1ZSunRpsbW1FTc3N5k8ebKEhIRIXFyczJgxI0HSf+LECWnZsiW7UksDcXFxEhQUJPXq1ZNBgwap00REWrRoId9884267LfffitLly7NlF1vpoSmvKdx48ZqiwplbDdu3FBvc//7779So0YNefnypURGRoqIyNq1a6VKlSrqAFobN26Uxo0bi4eHBwfV0gPNeePSpUuSN29ead26tTRr1kwaNGggtra2Urp0afXub2JJf2hoqFrfT8YpOjpaqlevLlu3bpXt27dLtmzZZP78+SIS32Ayb9482bp1q7q8przn/ef7MjvtMXBmz56t3h158uSJRERESL169WTs2LEiIhIUFCRVq1YVRVGkTZs2Bok3JZjwZ0CaBPLy5cvi4OAg33zzjaxcuVKWLVsm3t7eYm5uLm3btpVHjx5JbGysTJ06VapWrSoDBgyQV69eiYiog0NQ2vjzzz8la9asatlJWFiYdOrUSRo3biwzZ86UIUOGiKOjo84Ix5RQQECANG/eXKpWrSonTpwwdDj0CeLi4mTevHmiKIr06NFDFEXReYZFJL7f/SJFiqhJpY+Pj0ybNs2oWskyujt37ki+fPlkzJgxOtt15cqVUr58eXF3d5d9+/aJSHzSX6hQIalQoYJ67iDjFhUVJZ06dZIGDRpIjhw55I8//lDnPXjwQLy8vHQ6jBARGTNmDLu31XL9+nUpUqSIfPfddzJkyBDJkiWLzh3GBw8e6PydvHnzRjp27Chnzpwx6mcgmPBnUC9evJAKFSok6P4pLCxMli9fLlZWVtK9e3cRib/inzZtmhQrVkyGDBmSYAAb+jTa21JTchIWFiZeXl4ydOhQ9eLqxo0bUr9+fSlXrpyULl2avSKl0PXr1+XLL7+U+/fvGzoU0oPOnTuLoijSpUsXEdF9ADQgIEDs7OykXLlyUqdOHXFwcJCLFy8aMlyTM3v2bGnatKmEhoYmqDHevHmz+kC8pszQ399fSpUqxb8/I/b++fzs2bOSLVs2qV69urx+/VpiYmLk1atX0rRpU6lZs6bR1ZYbm8DAQJk3b544OjqKnZ2d2nGA5vweExMjFStWlEqVKsmGDRukbt26UrNmTTXZN9bty4Q/gzp9+rSUKFFCrbl8/6pyzpw5oiiKeusuJiZGZs2axdviaeTkyZMJuoecMGGClCxZUh3kRCT+QBIYGMia/VTSlHxQxte/f39p06aNKIoiv/76qzpds48vX74svXv3lsGDB+v00EP60b59e2nYsKHONO2EceLEiZItWzad4xmfnTEuybUia+bt3LlTrK2tpWrVqlK2bFmpWbOmlC1bVidppYS0uwnOnj27FC5cWGdcA832O3r0qFStWlVKliwpjRo1yhC9HCkiIqAMQ0SgKAqWLVuGoUOH4vHjx7CxsUFcXBzMzMzU5e7cuYPatWtj4MCBGDlypAEjNn0vX75Ep06dcPDgQYwZMwbVq1dHkyZNEBsbizJlyqBu3bqYO3euocMkMgjNMUvzr8avv/6KESNGYMaMGRg2bJg6/cWLF8idO7chQjU572/zuLg49O7dGwEBAdizZw8sLS1hbm4OAIiJiUGWLFlw/fp1VKlSBRs2bEDDhg0NFTqlgI+PD8zNzfHjjz8mOv/GjRvYu3cvXr9+jaJFi6JDhw4wNzdX9zX9z/s51JMnTxAUFIQDBw5gwYIFqFOnToLzeGRkJN6+fQtnZ2coimL029V4IyOV9i+i5uBdtGhRBAYGYtu2bWjfvr3OLyoAFCpUCA4ODnj69Gm6x5vZODk5YceOHVi2bBm2b9+OP//8E02bNkXPnj3Rq1cvHDlyBP/99x8KFy5s6FCJ0pUm4Tx48CCOHDmCyMhIfPfdd3B2dsaQIUMAAN9//z0A4LvvvsPUqVNx4MABbN68GQ4ODoYM3SQoioLnz5/jyZMnKFeuHMzMzFCqVCksW7YM586dQ82aNdXziybxf/bsGfLkyYOCBQsaOHp6n/YF3I4dO7BhwwasWLEi0WXj4uJQrFgxFCtWTGd6bGysUSelhqCdY506dQoWFhZwdnZG8eLF4eTkhMjISCxduhTfffcdZs+eDQAYOXIkWrdujWrVqqnrMPrtaribC5Qat27dEi8vL533pUuXlkaNGsmlS5fU6XFxcRITEyOvX7+WmjVr6vSxS/qhueX39u1befz4sc7t8IcPH8q+ffukfPnyUr9+fcmfP78oiiKrVq0yVLhEBrVjxw7JkiWLNGrUSBwdHaVw4cKyfft2iY6Olri4OJk9e7YoiiLly5cXOzs7nd4x6NNERkZKx44dpX379nL69GkRiX/AsFq1auLk5KRz7tAYPny41KpVS968eZPe4VIK7dy5U/r06SPjx48XEZbn6MvIkSMlR44c4ubmJrlz55YDBw6ISPzfzMyZM6V48eJSr1498fLyknz58mW4zgSY8GcAsbGx4uvrK3ny5NFJHBcuXCiKoki7du0S9GAyfvx4cXNzS1BXTp9Gk9xv2bJF6tSpI3ny5JEOHTrI4sWLdZZ7+/at7NixQzp16iQWFhbi7+9viHCJDELzdxIYGCi9evXS+fto0qSJfPbZZ7Jlyxa17vXUqVOyePFiuXPnjkHiNTWHDx+WZ8+eiUj8QHatW7eWHj16yPHjx0Uk/iKsVKlS4ujoKDNnzpRjx47J4cOHZejQoZItWzY+KG3EHj58KJ6enmJjYyO9evVSp7MjjtTTrrc/deqUFCpUSI4ePSqHDh2SPn36iKWlpWzcuFFE4o9la9eulY4dO0r37t0z5LMQTPiNmPZB+927d9KzZ0+ZNGmSzjK//fabZMuWTQoUKCADBw6UIUOGSLdu3cTR0VHOnTtniLBN3rZt2yRr1qzy008/yaFDh6Rdu3ZSrFgx+fnnnxNdni1llBns2rVLZ0yJo0ePSsmSJaV27dri5+ens6yXl5cULlxYtm7dKmFhYekdqkk7dOiQFCxYUHx8fOTp06ciEj+QXdWqVeXvv/9Wlzt27Jh07txZsmTJImZmZlKiRAmpWbMmk30jo0nktRP648ePS+3ataVo0aI6feoz6U+Z9x9CnzlzpsyYMUMdVEskvuvyQYMGiaWlZZJjFLCFn/RC+6CtSfpv3LihJvHaV6bbt2+Xvn37SpEiRaRmzZry7bffclTKNHLv3j2pVKmS/P777yISfyHm4uIinp6eUrp0aZkxY4a6rKbXER6EyZTFxcXJgQMHpGjRomqCKRJ/MvT09EyypK1Fixbi6OgoO3bsSM9wMwUfHx+pUKGCjB49Wr0I0wye9b6rV6/KyZMn5e7duzo9ipHhaZ/nHz9+LI8fP1YvkE+fPi01a9aUFi1aqKO6i/B88yF16tSRqVOnqu9DQkLEy8tLFEVRuzLXbMOIiAj57rvvxNbWVtasWaOznoy4nZnwG7HEDtoi/zsIvN/9k+Zq05i7hcrogoODZfr06XL//n158uSJfPbZZ9K/f395+fKlVKtWTdzc3GTcuHGGDpMo3WkGywoICFBLc2JiYqR8+fJStGhROXXqVIKTZPv27eXWrVvpHqup0m659PHxkRo1asiYMWN0RsfVnB8yYsKSmWjvnx9++EEqVKggxYsXl6JFi8r27dtFROTEiRNSq1YtadmypezZs8dQoWYohw4dUsfG0fwtPHz4ULp37y7ZsmVTn3XRTvq9vb2lbt26hglYj5jwG6GkDtqakQ4TO1BrD6bFA3naCgoKEhGR77//XmeAmmHDhknBggWlRYsWSbamEZka7dvaT548EScnJxk5cqQ65kdMTIx4enpKiRIlEk36SX802/bkyZMyffp0cXV1FUdHRxk3bpx6TOL2z1gmTpwoTk5OsmnTJnn69KnasPTff/+JiIifn5/UrVtXatSoIadOnTJwtMZNuzH0559/lq5du6r51tOnT+WLL76Q7Nmzy/nz50Xkf38rUVFRJtGQavbhfnwovWm6djp16hRy5MiBBw8eYP78+Zg9ezZevXql9mmtzczMTO2uS7vfZUqduLg4APF9UifF3t4eAHD37l2ICLJnzw4AiIqKwqBBg7BkyRLkypUrzWMlMgaa7hx37doFa2trjB49Gv/++y+WLl2Ku3fvwtzcHBcuXECWLFnQu3dvHD9+PMHxi/RDURTs3LkT1apVQ1xcHEaOHInPP/8cq1atwqxZs5I8f5BxevPmDQ4cOID58+ejdevWOHv2LK5fvw4fHx8UKlQIcXFxqF69OsaOHYvSpUujYsWKhg7ZaGl3vfnff/+hTJkyWL16NYYPH47o6GjkyZMHc+fORb169VC/fn1cvHhR/VuxsLCAmZmZmh9kWAa93KAk7dixQxRFkZ9//lnmzp0rX3zxhRQqVEjGjBnDlpo0duvWLencubPcvHkz0flxcXESHR0tI0eOlDp16sj3338vAwcOlOzZs3MkY8qU/Pz8RFEUWbFihYiI/PLLL5IvXz4ZP368TnmPq6urVK1aVcLDww0ZrkmKi4uTiIgIadasmfTv319n3ogRI9Ryw+TuFJNxuXv3ruTJk0devXol+/btk2zZssn8+fNFJL72fPLkyQmeuzCFlui0NGrUKGnUqJEEBQXJjh07xMrKSvr376+29D979kzat28viqIkmQNkVEz4jQwP2oZ369YtURRFWrduLbdv304wX7PNb9++LV9//bVUqVJFKleuLBcuXEjnSInS3/ulgwEBAfLjjz8m6KVKO+nXXAjHxsaqpQiUNlq3bi29e/cWEd1yqxYtWkjevHll8ODBOjX9ZNxatGghX3zxhWTNmlWne9t79+5J9erVZcOGDSLCXCAp2tvlxIkTUrVqVZ3Sp23btiVI+h8/fixjxozJcL3wfIiRDwuW+SiKAisrK1hYWCA6OhrA/4Y8nz59Om7cuIHFixfj3bt3GD16NJycnAwcsWmJjY3FZ599hhs3bqBy5coYPHgwZs2apY6SK/8/0qGIoHDhwvjxxx/h5OSEiIgItdSHyBRpbolrlw7evXsX3bt3x507dzBu3DgA8aVtlpaWGDZsGABg7ty5CA0NxcCBA+Hu7o5ChQoZ7P+QGeTJkwd+fn4ICQlBtmzZEBsbC3Nzc1SqVAnnz5/HzZs3DR0ivUe73GTq1KkQEQwbNgwWFhaoXr06Zs+ejWbNmqFnz54AgLCwMPTv3x+2trZo1aoVAJbyJkWzXf7880+cPHkSBQsWRKVKldSytubNm2P9+vVo3749zMzM8Ouvv8LFxQU//vgjgP/lX6aANfxGKk+ePDh58iRCQkKQJUsWxMbGAgAqVaoEMzMzHrTTiLm5OWJjY1G0aFGcOnUKR48exeDBg/Hff/8B+N/BIzo6Gj179sTkyZNhbm7OZJ9MmiYhuX//PubOnYsZM2Zg165dKFiwID7//HNER0dj586dEBFYWloiKioKADBs2DD07NkTu3btQtasWQ38vzBtmgTm559/RnBwMNq3b4/g4GD1mBUcHIwxY8Zg2bJlbCgyItrJ/s2bN3Hjxg2MHTsWS5YsgZmZGQYMGICmTZvi+vXrqFevHvr06YOGDRvi0aNH2Llzp3rOouTdvn0by5cvx9mzZ/Hw4UMoiqI23jVv3hzr1q3DvHnzMHfuXJ3PmUqyD4A1/MZGe4RKd3d38fLykqCgILUub/jw4fLHH3/I8+fPDRmmydOMnnfjxg1xcHCQ5s2bq6UIMTExMnDgQLGwsJAzZ84YMkyiNKc59ly8eFHy5csnlStXFltbW3FxcZGZM2eKiMjkyZOlZMmSMmLECPW2uGYcChGR169fp3/gmZBmX505c0YKFCggxYsXly+//FLatm0rlpaWEhAQYOAIKSkjRoyQUqVKibe3t3h6eoqZmZlMmzZNROJ7hlu5cqV07txZevbsKT/88INabmJqZSf6kNRzDNOmTVN7rdIeM0STd/n5+Zn09mTCb4R40DYOiSX9169fl2+//VZsbGzUrruITJXmWHT58mWxtbWVsWPHSlBQkFy9elW6du0q+fPnl6tXr8q7d+9k9OjRUqVKFRk5cqR60tQk/6wvTluJbd+QkBAZPny4eHt7S9euXeXKlSsGiIxSYvPmzWJnZyenTp2S2NhYefv2rfz888+iKIpMnz49yc9pzlH0P9rJ/oULF+TixYs6Y32MGTNGXF1dZerUqeqgpu8z1aRfEWH/XMZC/r8+XFtoaCgmTpyIly9fIjY2FiNHjkSpUqUMFGHmo6l/vXnzJmrVqoXAwEDY2triwIEDKF++vKHDI0pzT58+RZUqVVCkSBHs379fnX7o0CE0bdoU27ZtQ/369RESEoKff/4Zhw4dQtmyZTFr1izTuh1uBDTniBcvXiAyMhJWVlbInTs3AN1aY+0ykffnkfH566+/MGfOHJw+fRpZsmRR84AJEybgxx9/xLx589C7d2+1C1xKnHYONXz4cKxfvx6vX79GkSJFULFiRSxcuBAAMGbMGKxcuRIDBgzAV199hbx58xoy7HTDI4ABJHXQVhQlwUE7a9asmDFjBgAetPVN++Dw/sWW5r2mPtLDwwNHjx5F69atsXr1apQtW9ZAUROlr+DgYJQuXRrh4eFYuXIlunbtCgCwtrZGlixZYG1tDQDIli0bRo0ahdDQUPj7++PNmzdqMkqfTnNM2rx5M2bMmIGHDx+iRIkSKFSoEP744w+dc4N2sg+AiaKRy549O65cuYJ79+6hSJEiakNT06ZNMWXKFAwcOBBmZmbo06dPog2DpHuRu23bNmzcuBF//fUXzMzMcP36dUyYMAGvXr3Cxo0b8dNPPyFLliwYO3YsXFxc1GOaqWMLfzr70EE7JZ+lT6fZlvv378fevXvh7++Pzp07o0KFCvDw8EiwvOZiixddlBlduXIFP//8M+7duwcfHx/UqFEDJUuWRMeOHTFz5kwA/zvhhoaGIiwsjA+GpgFfX1+0adMG06ZNQ4MGDbBp0yaMHTsW69atwxdffGHo8OgDtJPS6OhoWFhYAAACAwPRrl07WFlZYebMmShatCiA+AGiZs2ahbx582LSpEk4efIkypUrZ7D4M4Ldu3dj/fr1yJMnj9rTTnR0NPbv34+vv/4a/fv3x/jx4wEAS5Yswddff51pLojZS086UxQFvr6+6Ny5Mzp27AhfX1/Url0bCxYswIYNGz74WdIPRVGwadMmtG3bFq9fv4aHhwdGjBgBHx8fPHz4MMHymiQ/sxwYiLR5enpi5MiRKFCgAH744Qe4ubmhXbt2CZJ9zV1JJvufLiwsDEB8WaGIIDo6Gps2bcKIESMwcOBA5MyZEwsWLMC3337LZD8DEBE12Z83bx6++eYbDB06FNevX0f27NkxcOBAhIeHo3v37ti9ezcOHz6MgQMH4sGDB+jSpQucnZ1x8eJFw/4njNyDBw8wfPhwrF69Gk+fPlWnW1hYoH79+mjdujUuXryIyMhIAEDPnj0zVS9HTPjTGA/axun+/fsYN24cZsyYgUWLFuGXX35BYGAgPDw84OrqmuTneNFFpiy5oeNLly6NUaNG4bPPPkOuXLlQoUKFBMu8X0pCH2flypX4/PPP8fz5c7WRwcLCAnfv3kWePHnw9OlTlC9fHk2aNMHs2bMBAOvXr8e2bdsMGTYlQfvu/E8//YSRI0dCURT8/fff6N69OzZt2oSWLVvCx8cH+fPnR7NmzdC7d2+8efMGGzduRN68eeHg4AA7OzsD/0+Mm5ubGxYvXoxy5crh4MGD2L59uzrPwsIC7u7uePjwYYIEP7M05PHonIZ40DZecXFxsLKygre3NwICAuDq6oouXbpg6tSpAIDz588jNDTUwFESpZ9ff/0V//77r9qHfmI8PT0xevRoVK9eHQsXLsQ///wDgIm+vmguuDSlg927d8fz58+hKAqioqJQpEgRnDlzBjVq1ICXlxcWLlwIRVEQHByMXbt24datW4iJiTHw/4Lep0n2r1+/jmvXrsHX1xeLFy/G/fv34ejoiOnTp2P9+vVo0KAB/v33X/j7++PgwYM4ceIEzM3NMW7cOERERKBKlSoG/p8Yh+R+x6tWrYpffvkFLi4umD9/PjZu3AgAePnyJXx9fVGwYEHY2NikV6hGhUfpNMCDtnETEbx58wavX7/G5cuX0bRpUzRt2hQLFiwAEJ/sz5w5E3fv3jVwpETp5+jRo+jZsyd27NiRbNJfqlQpjBw5EoUKFcKUKVOwdu3adIzStF25cgUA4O3tjUGDBiEkJATdunXD8+fPYWlpibZt22LlypWwsbHBtGnTAMQfz6ZNm4YDBw6gZcuWfMbISC1evBgdO3bEzZs3kS9fPgCAra0t/v77bzg6OuK3337D6tWrERMTg+LFiyNfvnw4ceIEBgwYgCVLlmDt2rXJ3n3OLLp27frBhomqVati6tSpCAwMRLdu3VClShV88803iIuLw99//60OuJXppGMXoJnGxYsXRSS+b+Q1a9ZIrVq1pFGjRmqfr/v37xcLCwspUaKEOiBNXFycjB49WgoUKKDTZyx9mujoaLWP6vcH42jTpo0oiiKdO3fWme7j4yNVqlTRGZiDyFRp9+Hu7e0t9vb2sn79ep2BsxJz/vx56d27t9y9ezeNI8wcDhw4IIqiyKJFi0Qkfr+sXr1aatWqJQ0bNpTHjx+LiMiaNWvE3NxcWrRoIa1atZKOHTtKjhw5OC6Ikbtz545UrFhRbG1tZc2aNTrz3rx5Iy1atJCiRYvKnj171OkBAQEyffp0uXnzZnqHa7SaNWsm2bNnlw0bNnzwGHXq1CmpWrWqVKpUSebMmaNOj4iISOswjRITfj3jQds43LhxQ+f9wYMHZciQITJ58mQ5ffq0iIicPn1a6tSpI56ennL8+HHZunWrDBs2TOzs7OTSpUuGCJvIILQH8OnatWuKk/4PzaeUu3PnjgwbNkxy5MghS5YsERHd80eDBg3URgjN8ax9+/YyefLkBMc7MqykRnp9+PChVKhQQerWrSv79+/Xmffq1SsZPnx4gsG0OLhWPO1t2q1btxQfo44dOyY1a9aU1q1by6FDh9I6TKPGhF/PeNA2vH/++UcqV64s69atExGRffv2ibm5ubRu3Vpy5swpderUUffN0aNHpXnz5mJnZyclS5aUzz//XL1DQ5SZaI8umZqknz7N3Llz1dePHz+W77//Xuzs7BI9f2g3GnG/GCftxNTf31+OHTsmb9++lbCwMBGJzxHKli0r9evXT5D0azDJT9zHNkwcOXJE6tSpI59//nmmTvqZ8OsJD9rG4/Lly1KvXj1p1KiRrF69Wr777juZP3++iMS3sHTp0kWqV68uixcvVj/j7+8vgYGBEhQUZKiwidKddjnP+0lGly5dmPSnsXv37knx4sUlICBAnXb//v1kzx9NmjSRJ0+eGCpkSob239Po0aPls88+EycnJylZsqTMmDFDPe/fuXNHypUrJ40aNZKdO3caKtwMQ3u7fmzDxP79+6VJkyby8OHDNIvT2DHh1wMetI2HpnXl2rVr0rBhQ2nVqpVUrVpVTpw4oS7z4MED6dq1q1SvXl3++OMPQ4VKZFCak+jevXulX79+0qhRI1m8eLE8ePBAXaZz585ib28vGzduzLR1r2ktNDRURETnGJXU+ePff/+V0qVLS9u2bdkKbMQmT54sefPmld27d4uISNu2bSV//vwycuRINeG8e/eu5MuXT7777jsDRmr8tO+YREdHq38vGqlpmNDcZcmsmPDrCQ/axkG7JeDy5cvSuHFjsbCwkNmzZ+ss9+jRI/n666+lVKlSOi39RJnJpk2bxN7eXrp166YeqwYMGCDnzp1Tl+nWrZsoiiJbt241YKSmLTAwUPLlyyeVKlVSpyV2/oiNjZUNGzbIvXv3DBUqJUI7Kb1586bUqlVLNm/eLCIivr6+YmdnJ02aNBFXV1fx8fGRR48eiYjIkydPmAMkQ3u7zpgxQ1q3bi3FixeXWbNmye3bt9V5nTt3FgcHhw82TGjnB5kRE3494kHbsDR/zOfPn5fr16+LiMitW7ekUaNGUrt2bdmwYYPO8vfv35e+ffuylxHKlC5cuCAFCxaUhQsXqtPs7e3FwcFBunbtqvMsS+/evfmMkZ69n3wcO3ZMChUqJHXr1lWnac4fjo6OMm/evPQOkVJAez/evHlTXr58KRs3bpR3797J0aNHJU+ePLJgwQIREWnRooXkz59fvvnmG7XXPhHW7H/I6NGjJU+ePDJ58mT5/fffJVu2bNK/f3+dhomvvvpKFEXJ1DX6H8KE/xPxoG0cNPthw4YN4uLiIiNGjJCXL1+KyP/Kexo2bJgg6eeBljIT7ePVoUOHZOzYsSISf4xyd3eXwYMHy/bt20VRFOndu7fOHUvSP19fX1m4cKHaknny5Elxc3NLcP7o37+/uLq6SmBgYKZvpTQm2vvi22+/lSpVqsjz588lODhYRET69Okjffr0UevO+/fvLyVLlpR+/fpxP6bQxo0bpXDhwnLq1CkRETl37pwoiiKOjo7SuXNnnYaJiRMn6tT4ky4m/HrAg7Zx2L9/v9ja2sqSJUt0Wk9E4pP+Ro0aiZeXl6xatcpAERIZ3urVq2Xx4sXy4sULuXHjhkRHR0vbtm3l66+/Vmtcy5cvL+bm5jJw4EDW7qehMWPGiKIosmTJkmTPHw8fPpTnz58bKkz6gNevX0vz5s0TtC63a9dOunTpopb8tm/fXnbs2KGe/5kHJPR+l6a7d+9W+9Dfvn27ZM+eXf755x/x9fUVRVGkb9++4ufnp/MZJv2JY8KvBzxop6+k+jgeOnSoeHt76yyj3YJ//fp1qVKlirRp00ZtgSHKDDSJxX///SeWlpby+++/q/PevXsnlStXVkt7IiMjpU+fPrJgwQIOApgOJk6cKObm5jqNRqdOnZLChQtL2bJlmRQauZkzZ0rx4sWlYcOGCc7vo0ePlhIlSkiLFi2kcuXKUqxYMfWclNR5jOJ99913snz5cnn27Jk8efJEXr16JdWqVZNp06aJSPwDuAULFhRFUWTKlCkGjjZj4BjcevDjjz/CwsICffr0QWxsLHr27IkqVapg3bp16Ny5M8qVK4fz588jf/78hg7VJJiZmSWYFhsbizNnzsDd3V1dRkRgbm4OAHj69CmKFSuGZcuWwdbWFnZ2dukaM5EhKYqCo0eP4s6dOxg2bBgGDhyoznv79i1evXqF27dv4/jx49i9ezf279+P6dOnw8HBwYBRm6bXr18jZ86c6vsJEyYgNjYW/fr1AwD06NEDlStXxvLly9GvXz88ePBAPa6R8SlWrBiio6Nx6dIlxMXFAQBiYmKQJUsW/PTTT8iSJQuePXuGvHnzYt68eTA3N0dsbKx6bqJ4IgJFUQAAfn5+WL58Ob744gs4OzsDAO7du4egoCCUKFECAPDu3Ts0bdoUTZo0gZeXl8HizlAMfcWRUb169SrBtHHjxqktNZqr+GPHjomnpycf0NWDkydPSt++fWXIkCE6w2Rr+Pj4SPXq1XWGIY+Li5N79+7JgAED2FpJmVZQUJA0adJEFEWRNm3aiIju3a9ly5aJg4ODFC5cWPLly6fzMBzpj7+/v9ja2sq2bdsSzBs1apRYWVnJihUr1O4Fw8PD0ztESkZirfIRERGyf/9+yZ07t7Rs2VKdnlQXkSw3Sd4ff/whkydPTtBqf+3aNXF2dpYRI0bIhg0bpGnTplK3bl31Dhifx/swJvwfgQft9BcXFyfTp0+XcuXKyYEDB+TEiRMSHh4u9+7dU+sjDx48KO7u7jJy5Ei1R5Ho6GiZMGGCfPbZZ5l6wA2iY8eOSdu2bcXe3l4dMyQqKkqd7+/vL5cuXeL4IGlAu2a7Q4cO4ujoKLt27dKZ9+TJE8mZM6coiiLLly83WKyUOO1k/+LFi3LkyBF59OiR+ozL3r17xdHRUb744gt1OSb3qfP06VOpXbu2KIoigwYNEhHdbbh06VJxcXGRYsWKSa1atdTjF8veUoYJfyrwoG1Yx44dkyFDhoiIyNatW6VMmTJSsGBBKVeunIwcOVLCwsLkr7/+Ek9PT6lQoYI0bdpUmjZtKg4ODnL+/HkDR0+UfrSPVdpJ/aVLl6ROnTri6uqq9mOtPZ/0K6lE5KuvvpJs2bKp5w+R+GRnwIABMm7cOLl27Vp6hUgpoL0fR44cKa6uruLi4iJ2dnbSu3dvOXv2rIiI7Nu3T5ycnKRdu3aGCjVDSezv4/jx49KyZUvJnj27elde+xh17949efDggXoBxouqlFNERAxdVmTsRKu2TFu3bt2wadMmrFu3Dk2aNAEAPHv2DD/++CMcHR3RqVMnFC9ePL3DNVknTpxAlixZEBsbiwYNGuCHH35Ajx49MGXKFPz+++9YtWoVvvjiC+zbtw/+/v44cuQIPD090alTJxQrVszQ4ROlC83xas+ePfjnn3/w6NEjVK5cGZ07d0apUqVw9epVDBkyBLdu3cKBAwdQsGBB1hSnAc1+OHLkCHbs2IHQ0FC4u7tjxIgRAIDu3btj3bp1mDdvHkqVKoXt27djz549OHDgAKysrAwcPSVm3rx5mDRpElavXo2SJUti9+7dWL58ORwdHTFp0iSUKlUKBw4cQIMGDeDj44OffvrJ0CEbrbi4OPV5vOjoaISHh8Pe3h4AcOXKFQwaNAh3797F/v37UbhwYURHR8PCwiLJddCHMeH/AB60DSepC61evXohW7ZsmDVrFl68eIEqVaqgadOmmDt3LhRFUR+YSurzRKZuy5YtaN++PTp37oysWbNiy5YtKFq0KAYNGoRWrVrh4sWLGDNmDI4dO4ZLly6hQIEChg7ZpGiOPRs3bsTXX3+NDh06wNraGps2bUKxYsWwb98+AMDw4cPx559/IleuXIiMjMSOHTtQrlw5A0dP74uJiYG5uTk6deoEJycnzJkzR523ZcsWjB8/Hh06dMDo0aMRExODS5cuoWzZsryIToJ2oj59+nQcPHgQd+/eRb169dCjRw9UrFgR/v7+GDp0KG7fvo39+/ejYMGCTPA/lYHuLGQI2oM52dnZSa9eveTbb7+VfPnySf369dXlhg0bJtmyZZMCBQpI3rx5WT6iB5rbdW/fvpX//vtPZxjtL774Qv7991958eKFuLi4SJ8+fdR5mzdvlj179rDLM8o0NDXEcXFxEhcXJy9fvpRKlSrJ9OnT1WUePHggTZo0kXr16qm3yY8fPy5ffPEFH2bXg8SONw8ePJBixYqpHQzcuXNHnJycpFevXjrLnThxQs6cOSOPHj1Kl1gpZfz8/GTx4sXqe00pr6brZ+2HRL///ntxd3dPMGYFy02SN2bMGMmZM6dMnjxZpk2bJp999pnUq1dPtmzZIiLxo4F7eXmJjY2NPH782MDRZnxM+LXwoG0cNPvhypUrUrNmTcmfP78ULFhQvv32WxER+eabb6Rq1apSsGDB/2vvzoOiutI2gD/dtIgKaiCMKCDakihm3AERIxSow1AuEZMBMokGTcUYRdxYovIZQEAxiI7igltEECKRiEZj4YYpZcwIRHEJGokYcGkxsgko0HK+Pww3tESzuDQ0z6+qq+h7bl9O08Xp9773PeeKGTNmSINqZWWl8Pb2FsuWLeOMfWoVtmzZIoKCgkRJSYm07e7du6Jv375i69atQohfg47CwkLRpUsXER4eLu3Lm2o9vYbxKicnR4SFhUmJojNnzggbGxshxMO/vYWFhfjwww+l16Wnp7/4ztIfUlFRIYKDg4W7u7tITEyUtoeFhYmOHTuKvLw8jf03b94snJycuEDHE1RWVgohfk1M/PDDD6J3795i//790j5Xr14Vbm5uwtXVVVo8IDMzU8ydO5ff6c8Ar438ouFS0XfffYclS5ZA/FLpVFJSAplMBl9fXxQVFcHJyQkTJ07Epk2bAAAHDx4EADg4OMDW1hbm5uZaew+6oOFzyM3NxbBhw9C/f38sX74cTk5OSE1NRWRkJAIDA3H37l08ePAAa9euhULx8HYSkZGROHnyJN58801eSqVW4dSpUzhw4ADWrl2L0tJSAEBNTQ3q6upw5coVAJDK3CwtLTFy5EicP39eej3LDp9Ow3h19uxZ2NnZoby8XCoj7NSpE4yNjbFv3z68/vrrGDNmDGJjYwEAeXl5SExMRE5Ojja7T48IDw9HcXExjIyMMGXKFIwYMQJJSUmIi4sDAPzf//0fhg0bBnd3d2RlZeHWrVuoqqpCcnIyTE1NYWBgoOV30DwFBAQgJCQEpaWlkMlkkMlkUCgUqK6uhr6+PoCHdfxWVlbYvHkzsrOzsXv3bgCAo6MjYmJipPsX0F/HgB8ctJsTuVyO/Px8ODg4YO7cuVi7di3efvttrF+/Hn369MH+/fvRtWtXLF68GNXV1bC1tYWnpyfefPNNbNiwAbt374a1tbW23wbRc9Nwcx8A2LBhA9zc3JCWloY1a9ZIN3UKCAhAZGQkkpKSoKenJ50Ul5eXw8zMTFtd1ymNkxMODg74+OOPER0dLbWbmJhACAEPDw84Oztjw4YN0uewZcsWFBQUwNLSUlvdp0ecOHECCQkJmDJlCn7++WcolUp4e3tj4MCBePXVV6X94uPj0b9/f4wePRqOjo5wdHREcXExkpOTAUBKFtKvysrKkJGRgdjYWCkxoa+vj9raWil+ksvlUKvVsLCwwJAhQ3Djxo0mx2Ei7ylp+QqD1jVcjj1z5oxo166dWLhwoUZ7RUWFcHR0FAqFQkyaNEmjbf78+eL1119vcjtt+usePHggFixYIExNTcV//vMfjbawsDBhb28v7t27J+7fvy8uX74spk+fLt5//30REhIirS1OpKsal48sXrxY2j5//nwxZMgQERISIkpKSkR9fb0IDAwUMplMzJs3T0RHRws/Pz9haGjIJR+focuXLwsDAwMRHBwshPh13ld8fLy4ePGiyM7OFoaGhsLLy0ukpqaK48ePCz8/P9GpUyeRm5urza7TI+rq6kRycrIYPny4+Mc//iGKi4uFEA9vWvdbdu/eLeLj40V8fLxUbsKa/cfz9/cXQ4YMEaGhodKNS1evXi309PQ0yqZqa2vFgAEDxIoVK7TVVZ3V6gN+IThoNzfXr18Xs2fPFkOHDhURERFCCCFu374tDA0NxbJly7TcOyLtaAj2c3NzhVwuF/Pnz9donzdvnhg8eLAICwsTFRUVQoiHd9AdNGiQGDp0qBg1apQ4c+bMC++3rmqcnFi5cqW0fcmSJeLll18WJ0+eFEIIceTIEeHo6Ci6du0qXnvtNTF8+HB+Ds1M43Xet23bJhwdHcWECROkuTGN68cftyAEa8ybWrNmjVi0aJH0vCExERoaKkpLS0Vtba0ICgoSMplM+Pj4iLlz54qRI0eKvn378uTpOWj1AT8H7ebp5s2bwtfXVzg6OoqAgABhYWEhZs2aJbU3TPxp/JxIV/3elcgG8+fPF4MGDRJhYWFSsFJeXi7UarU0aY6encbJifXr14uoqChhamoqvv76ayGE5mpjP/30k7h27dpjM8akHY2/O2JiYoS3t7ewtrYWMplMjB8/Xty5c0cIwYD+z9q4caOQyWTiiy++0Nj+W4mJlJQUMXr0aDF+/HjxwQcfSCdg/Js/W1yHH8CNGzewfPlyfPvtt/Dx8UFFRQWio6MRHx8Pd3d3qVazrKwMFRUV0NPTg5GRkXSTCHo+bt68icjISKSmpsLc3BxZWVkAIK2zT9Sa5Ofno1+/fvD395cWFpDJZEhISICFhQVcXFwAPFzbPSMjAx4eHpg+fTpefvllLfdct6lUKkRERODQoUP48ccfkZ6eDldXV97MrIX59NNPsWTJEiQnJ8PMzAx79+7Fvn37YGZmhoSEBBgbG/Mz/YPi4uLg6+uLlJQUeHh4NGn39/fH0aNH4eHhgZkzZ8LY2Bj379/XmPTM7/nnQMsnHM1GQ0a5d+/eQqFQiCNHjggheIapbSqVSsyaNUsMHTpUo5yH6+xTa/KkK5Gmpqbi1KlTGvsHBgYKpVIpoqKiePXrBVCpVMLPz0/0799fREdHS9v5/dEyVFVViTFjxmjMi1Gr1eKzzz4T1tbWYuLEiaK0tFQIwe+e37N7924hk8nE3r17NbYvWLBAZGZmSs8bynvCwsLE7du3NfblmPV88PTpF2ZmZggODoZcLsexY8dw+vRpuLq6SktB8axeO7p06YKFCxciIiICX331FaqrqxEaGsq77VGrIpfL4evri+rqanz++ecwMDBARUUFVq9ejfj4eNjZ2QGANFZFRUVBX18f//rXv3i36RegS5cuWLBgAerr6/HFF19ArVYjKCgIenp6vDtoC9C+fXsAwKVLl6Rtenp68PHxweHDh5GUlISbN2/iwIED6NSpk7a62ezV1NQgPT0dSqUSBQUF0vYJEybg6tWr8PPzk65MRkdHIzAwEJs2bYKFhQWmTJki7c8x6/lgSc8jGi7PZmVlwcPDA0FBQQDAQVvLVCoVFixYgGvXruHzzz+HiYmJtrtE9ML9kfIRJii0p+HzOX36NEaOHInQ0FBtd4n+oLCwMOzfvx+rVq2Cvb299D+0YsUKpKenY9CgQVi6dCnjgN9x8+ZNREVF4X//+x+8vb1x4sQJ5OfnY9euXejVqxcAzTEqNjYWH330EcesF4AB/2/goN083bp1C8DDbBpRa3Xr1i1ERkbi2LFjmDx5MubPnw+AgX5zweRE89WQXX70Z+DhWvEjRoyAsbExgoODMWzYMMhkMkyaNAkODg4ICAiATCZj8u8PaIih9u/fj/Lycpw9exbm5uZPTExw/Hr+GPA/BgdtImqueCWyeWNyovlp/L9RWVkJQ0NDqa0h2Lxz5w7GjBmD+/fvo6ysDJ06dUJNTQ3Onz8PhULR5CSBHq8hMZGZmQlvb2/4+/sD4BilTQz4n4CDNhE1V7wSSfTHNA7U/fz8cPHiRezbtw/6+vrSPg1Bf2VlJY4fP44LFy6gffv2mDZtGhQKBTPQf8HjEhM8cdIOBvxERC0Ur0QSPVnj4DI7Oxtz5szB8uXL4ejo2GTfx2WfGez/dSqVCpGRkcjJyYGLiwvCw8O13aVWiwE/EVELxiuRRL9v586dSEpKgpGRERITE7nO+wukUqkQGBgIAwMDxMXFMbuvJQz4iYiISKc0ZOvr6+tRVVUFPz8/pKeno3v37vj2228BMHP/IpWUlKBz586Qy+Us6dESzpwgIiIindJQmnPnzh0YGRkhIiICb7/9NgoKCvDJJ58AgHSfBHr+jI2NpRMwBvvawYCfiIiIdE5KSgr69euHs2fPolu3bvD394eXlxfS09OxdOlSAA9PDB48eKDlnrYeXKFHe/iXJyIiIp1jamqKQYMG4d1338W5c+fQtWtXBAUFwd7eHnv37kVUVBQAsKyHWgUG/ERERNSi/dZ0RBcXFwQHB6N79+7w8vLCuXPnYG5ujqCgIAwdOhQbN25EQkKCFnpL9OJx0i4RERHphKSkJIwYMQKWlpbSthMnTmDZsmUoKCjArl27YGNjg8LCQqSmpsLPz48ZfmoVGPATERFRi3fp0iV4e3ujY8eOSE5ORrdu3aS2gwcPYurUqejSpQu2bt2KAQMGSG1crYdaA5b0EBERUYvzaL6yd+/eWLRoEfT09PDuu+/i2rVrUpurqyt69eqF69evS7X7Da9nsE+tAQN+IiIialEaL+9YUlKCgoICAMBbb72FwMBAqNVqvPfee7h9+zYAoKqqClZWVtiyZQsSExMBgMtDUqvC28wRERFRiyGEkJZ3DAkJwZEjR5Cbmwt3d3eMHDkS06ZNQ21tLVauXAk7Ozv4+Pjg0KFDUCgUcHd3l9aD5xKR1Jqwhp+IiIhanLCwMMTGxmLjxo2wsbHB1KlTUVxcjPT0dCiVSmRnZyMuLg6XLl2CpaUltm3bhjZt2jDYp1aJGX4iIiJq1qqqqtChQwep7v7GjRs4cOAAtm7dirFjx+Kbb77B6dOnsWbNGiiVSgCAra0tbG1tUVFRgY4dOwIA1Go1FAqGPtT68BSXiIiImq2AgACEhISgtLQUMpkMMpkMbdu2RU1NDZycnJCWloaxY8ciJiYG77//Pu7du4eEhARcvHgRAKRgXwjBYJ9aLQb8RERE1GyVlZUhIyMDsbGxKC0tBfBwKc2ysjLMmzcPU6dORVRUFKZPnw4A+PHHH5GYmIiioiKN43CSLrVmrOEnIiKiZi0gIAAZGRkYP348Zs6cCRMTE2zevBmzZs2Cp6cn4uPjIYTAvXv34OnpidraWhw4cIBLbhL9gte2iIiIqNmJjY2FSqVCeHg4Pv30U/j7+2Pv3r0QQsDPzw+TJk3CDz/8gOjoaKm2/9q1a7h9+za+++476OnpcYIu0S/4X0BERETNyqZNm+Dn54eBAwdK26Kjo+Hs7Iy9e/ciNjYWdXV1WL58OVJSUnD37l0oFAq4uLjg9OnTaNOmDdRqNYN9ol+wpIeIiIiajbi4OPj6+iIlJQUeHh5N2v39/XH06FF4eHhg5syZMDY2Rm1tLfT19aV9Hjx4wHIeokZ46ktERETNQlpaGj766CN8+eWXGsH+woUL8d///hfAw0y/q6sr9uzZg7Vr1+Lnn3+Wgv2GHCaDfSJNDPiJiIhI62pqaqSbZhUUFEjbJ0yYgK+//hpKpVIK6BuC/k2bNuGrr76S9uVKPES/jZN2iYiISOvatm2LxYsXo23btkhOToYQAidOnMBPP/2E1NRUmJmZAfi1XGf58uXo3r07Jk+erOWeEzV/rOEnIiKiZkOlUiEiIgL79+9HeXk5zp49C3Nzc426/Edr9FmzT/RkLOkhIiKiZsPMzAzBwcEYN24cevbsieTkZACQltls+LkxBvtET8YMPxERETU7DZn+rKwseHh4ICgoCMDDibms1Sf6cxjwExERUbOkUqkQGRmJnJwcuLi4IDw8XNtdImqRWNJDREREzZKZmRkWLlyIXr16obi4GMxREv01zPATERFRs1ZSUoLOnTtDLpezpIfoL2DAT0RERC1CfX095HIWJxD9WQz4iYiIiIh0GE+TiYiIiIh0GAN+IiIiIiIdxoCfiIiIiEiHMeAnIiIiItJhDPiJiIiIiHQYA34iIiIiIh3GgJ+IqBXq0aMHVq1ape1uPNG2bdvQuXPnpz6OTCZDWlraUx+HiKilYsBPRNSCFRUVYerUqejWrRv09fVhZWWF2bNn486dO9ruGnx8fDBhwgRtd4OIqNVjwE9E1EJduXIFtra2uHz5MpKTk5Gfn48NGzbgyJEjGDZsGEpKSp7b766trX1uxyYiomeLAT8RUQs1c+ZM6Ovr4+DBg3B2dkb37t3h7u6Ow4cP4/r161i0aBEAoLi4GOPGjUO7du3Qs2dP7Nixo8mxCgsL8cYbb8DQ0BAdO3aEp6cnbt26JbWHhIRg4MCB2Lx5M3r27AkDA4On7n9MTAz69euHDh06wNLSEjNmzEBlZWWT/dLS0vDKK6/AwMAAbm5uKCoq0mjfs2cPBg8eDAMDAyiVSoSGhkKtVj91/4iIdAUDfiKiFqikpATp6emYMWMG2rVrp9FmZmaGd955Bzt37oQQAj4+PigqKkJGRgZ27dqFdevWobi4WNq/vr4eb7zxBkpKSvDNN9/g0KFDuHLlCry8vDSOm5+fj9TUVHz55Zc4c+bMU78HuVyO1atX48KFC4iPj8fRo0cRGBiosU91dTUiIiKwfft2ZGZmoqysDN7e3lL78ePHMXnyZMyePRvff/894uLisG3bNkRERDx1/4iIdIVC2x0gIqI/7/LlyxBCwMbG5jfbbWxsUFpaiqysLBw4cACnTp2CnZ0dAGDLli0arzty5AjOnTuHgoICWFpaAgC2b9+O1157DVlZWdLramtrsX37dpiamj6T9zBnzhzp5x49eiA8PBzTp0/HunXrpO11dXWIjY3F0KFDAQDx8fGwsbHBqVOnYG9vj9DQUHz88cd47733AABKpRJLlixBYGAgPvnkk2fSTyKilo4ZfiKiFkwI8cT2vLw8KBQKDBkyRNrWp08fjdVv8vLyYGlpKQX7ANC3b1907twZeXl50jYrK6tnFuwDwOHDhzFy5EiYm5vDyMgIkyZNwp07d1BdXS3to1AopBOOxn1v6Fdubi7CwsJgaGgoPT744APcvHlT4zhERK0ZA34iohbI2toaMplMIyBvLC8vDy+99NIzWdayQYcOHZ7Zsa5evYqxY8eif//+SE1NRU5ODtauXQvgz00IrqysRGhoKM6cOSM9zp07h8uXLz+TeQZERLqAAT8RUQtkYmKC0aNHY926dbh3755Gm0qlwo4dO+Dl5YU+ffpArVYjJydHar906RLKysqk5zY2NigqKtKYDPv999+jrKwMffv2fS79z8nJQX19PVasWAEHBwe8+uqruHHjRpP91Go1srOzm/S9oSRp8ODBuHTpEqytrZs85HJ+xRERAazhJyJqsWJjY+Ho6Ag3NzeEh4ejZ8+euHDhAgICAmBubo6IiAgYGxvjn//8Jz788EOsX78eCoUCc+bM0ZjoO2rUKPTr1w/vvPMOVq1aBbVajRkzZsDZ2Rm2trZP1cfy8vImE3xNTExgbW2Nuro6rFmzBuPGjUNmZiY2bNjQ5PVt2rTBrFmzsHr1aigUCvj6+sLBwQH29vYAgMWLF2Ps2LHo3r073nrrLcjlcuTm5uL8+fMIDw9/qr4TEekKpj+IiFqoV155BdnZ2VAqlfD09ESvXr0wbdo0uLi44OTJkzA2NgYAfPbZZ+jWrRucnZ0xceJETJs2DX/729+k48hkMuzZswcvvfQSnJycMGrUKCiVSuzcufOp+3js2DEMGjRI4xEaGooBAwYgJiYGUVFR+Pvf/44dO3Zg6dKlTV7fvn17BAUF4d///jeGDx8OQ0NDjX65ublh3759OHjwIOzs7ODg4ICVK1fCysrqqftORKQrZOL3ZnwREREREVGLxQw/EREREZEOY8BPRER/WmFhocZSmI8+CgsLtd1FIiL6BUt6iIjoT1Or1bh69epj23v06AGFgutCEBE1Bwz4iYiIiIh0GEt6iIiIiIh0GAN+IiIiIiIdxoCfiIiIiEiHMeAnIiIiItJhDPiJiIiIiHQYA34iIiIiIh3GgJ+IiIiISIcx4CciIiIi0mH/D6Ta00NKk2F4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = 'cycle_duration'\n",
    "fig, ax = plt.subplots(figsize = (9,4))\n",
    "sns.boxplot(data = resp,\n",
    "           x = 'Odor_Label',\n",
    "           y = y,\n",
    "           ax=ax,\n",
    "            order = order\n",
    "          )\n",
    "sns.stripplot(data = resp,\n",
    "           x = 'Odor_Label',\n",
    "           y = y,\n",
    "           ax=ax,\n",
    "             color = 'k', alpha = 0.5, size = 3, jitter = 0.05,\n",
    "            order = order\n",
    "          )\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation = 45)\n",
    "ax.set_title('Respi Cycle Duration', fontsize = 20)\n",
    "ax.set_ylabel(f'Cycle Duration (sec)')\n",
    "fig.savefig(save_folder / 'resp_emosens3.png', dpi = 500, bbox_inches = 'tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3353b83-a1b6-4d59-b5ea-fdb6f681a905",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}