diff --git a/figures/figure1.png b/figures/figure1.png
new file mode 100644
index 0000000..7ce9fd5
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diff --git a/figures/figure2.png b/figures/figure2.png
new file mode 100644
index 0000000..fe28cb5
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diff --git a/your-code/challenge-1.ipynb b/your-code/challenge-1.ipynb
index 9df5e53..ca7de55 100644
--- a/your-code/challenge-1.ipynb
+++ b/your-code/challenge-1.ipynb
@@ -19,8 +19,7 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt \n",
-    "import seaborn as sns\n",
-    "# Your Code Here"
+    "import seaborn as sns\n"
    ]
   },
   {
@@ -35,11 +34,400 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "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>Date</th>\n",
+       "      <th>Calorie burned</th>\n",
+       "      <th>Steps</th>\n",
+       "      <th>Distance</th>\n",
+       "      <th>Floors</th>\n",
+       "      <th>Minutes Sedentary</th>\n",
+       "      <th>Minutes Lightly Active</th>\n",
+       "      <th>Minutes Fairly Active</th>\n",
+       "      <th>Minutes Very Active</th>\n",
+       "      <th>Activity Calories</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Distance_miles</th>\n",
+       "      <th>Days</th>\n",
+       "      <th>Days_encoded</th>\n",
+       "      <th>Work_or_Weekend</th>\n",
+       "      <th>Hours Sleep</th>\n",
+       "      <th>Sleep efficiency</th>\n",
+       "      <th>Yesterday_sleep</th>\n",
+       "      <th>Yesterday_sleep_efficiency</th>\n",
+       "      <th>Months</th>\n",
+       "      <th>Months_encoded</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2015-05-08</td>\n",
+       "      <td>1934</td>\n",
+       "      <td>905</td>\n",
+       "      <td>0.65</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.355</td>\n",
+       "      <td>46</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.403891</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>92.086331</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2015-05-09</td>\n",
+       "      <td>3631</td>\n",
+       "      <td>18925</td>\n",
+       "      <td>14.11</td>\n",
+       "      <td>4</td>\n",
+       "      <td>611.000</td>\n",
+       "      <td>316</td>\n",
+       "      <td>61</td>\n",
+       "      <td>60</td>\n",
+       "      <td>2248</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.767545</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.566667</td>\n",
+       "      <td>92.464358</td>\n",
+       "      <td>6.400000</td>\n",
+       "      <td>92.086331</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2015-05-10</td>\n",
+       "      <td>3204</td>\n",
+       "      <td>14228</td>\n",
+       "      <td>10.57</td>\n",
+       "      <td>1</td>\n",
+       "      <td>602.000</td>\n",
+       "      <td>226</td>\n",
+       "      <td>14</td>\n",
+       "      <td>77</td>\n",
+       "      <td>1719</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6.567891</td>\n",
+       "      <td>Sunday</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.450000</td>\n",
+       "      <td>88.761468</td>\n",
+       "      <td>7.566667</td>\n",
+       "      <td>92.464358</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2015-05-11</td>\n",
+       "      <td>2673</td>\n",
+       "      <td>6756</td>\n",
+       "      <td>5.02</td>\n",
+       "      <td>8</td>\n",
+       "      <td>749.000</td>\n",
+       "      <td>190</td>\n",
+       "      <td>23</td>\n",
+       "      <td>4</td>\n",
+       "      <td>9620</td>\n",
+       "      <td>...</td>\n",
+       "      <td>3.119282</td>\n",
+       "      <td>Monday</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.183333</td>\n",
+       "      <td>88.857143</td>\n",
+       "      <td>6.450000</td>\n",
+       "      <td>88.761468</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2015-05-12</td>\n",
+       "      <td>2495</td>\n",
+       "      <td>502</td>\n",
+       "      <td>3.73</td>\n",
+       "      <td>1</td>\n",
+       "      <td>876.000</td>\n",
+       "      <td>171</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7360</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.317714</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.783333</td>\n",
+       "      <td>82.892057</td>\n",
+       "      <td>5.183333</td>\n",
+       "      <td>88.857143</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>362</th>\n",
+       "      <td>2016-05-03</td>\n",
+       "      <td>3796</td>\n",
+       "      <td>18588</td>\n",
+       "      <td>14.13</td>\n",
+       "      <td>16</td>\n",
+       "      <td>599.000</td>\n",
+       "      <td>275</td>\n",
+       "      <td>49</td>\n",
+       "      <td>79</td>\n",
+       "      <td>236</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8.779972</td>\n",
+       "      <td>Tuesday</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.283333</td>\n",
+       "      <td>91.951220</td>\n",
+       "      <td>5.233333</td>\n",
+       "      <td>90.229885</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>363</th>\n",
+       "      <td>2016-05-04</td>\n",
+       "      <td>3525</td>\n",
+       "      <td>16382</td>\n",
+       "      <td>12.39</td>\n",
+       "      <td>16</td>\n",
+       "      <td>684.000</td>\n",
+       "      <td>333</td>\n",
+       "      <td>10</td>\n",
+       "      <td>55</td>\n",
+       "      <td>2075</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7.698787</td>\n",
+       "      <td>Wednesday</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.766667</td>\n",
+       "      <td>95.081967</td>\n",
+       "      <td>6.283333</td>\n",
+       "      <td>91.951220</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>364</th>\n",
+       "      <td>2016-05-05</td>\n",
+       "      <td>3649</td>\n",
+       "      <td>21913</td>\n",
+       "      <td>16.40</td>\n",
+       "      <td>19</td>\n",
+       "      <td>701.000</td>\n",
+       "      <td>287</td>\n",
+       "      <td>29</td>\n",
+       "      <td>90</td>\n",
+       "      <td>2249</td>\n",
+       "      <td>...</td>\n",
+       "      <td>10.190484</td>\n",
+       "      <td>Thursday</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.666667</td>\n",
+       "      <td>88.888889</td>\n",
+       "      <td>6.766667</td>\n",
+       "      <td>95.081967</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>365</th>\n",
+       "      <td>2016-05-06</td>\n",
+       "      <td>3539</td>\n",
+       "      <td>19023</td>\n",
+       "      <td>14.79</td>\n",
+       "      <td>15</td>\n",
+       "      <td>575.000</td>\n",
+       "      <td>298</td>\n",
+       "      <td>8</td>\n",
+       "      <td>85</td>\n",
+       "      <td>2112</td>\n",
+       "      <td>...</td>\n",
+       "      <td>9.190077</td>\n",
+       "      <td>Friday</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.166667</td>\n",
+       "      <td>89.805825</td>\n",
+       "      <td>4.666667</td>\n",
+       "      <td>88.888889</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>366</th>\n",
+       "      <td>2016-05-07</td>\n",
+       "      <td>304</td>\n",
+       "      <td>9526</td>\n",
+       "      <td>7.08</td>\n",
+       "      <td>2</td>\n",
+       "      <td>564.000</td>\n",
+       "      <td>370</td>\n",
+       "      <td>13</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1604</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.399307</td>\n",
+       "      <td>Saturday</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.366667</td>\n",
+       "      <td>89.165187</td>\n",
+       "      <td>6.166667</td>\n",
+       "      <td>89.805825</td>\n",
+       "      <td>May</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>367 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Date  Calorie burned  Steps  Distance  Floors  Minutes Sedentary  \\\n",
+       "0    2015-05-08            1934    905      0.65       0              1.355   \n",
+       "1    2015-05-09            3631  18925     14.11       4            611.000   \n",
+       "2    2015-05-10            3204  14228     10.57       1            602.000   \n",
+       "3    2015-05-11            2673   6756      5.02       8            749.000   \n",
+       "4    2015-05-12            2495    502      3.73       1            876.000   \n",
+       "..          ...             ...    ...       ...     ...                ...   \n",
+       "362  2016-05-03            3796  18588     14.13      16            599.000   \n",
+       "363  2016-05-04            3525  16382     12.39      16            684.000   \n",
+       "364  2016-05-05            3649  21913     16.40      19            701.000   \n",
+       "365  2016-05-06            3539  19023     14.79      15            575.000   \n",
+       "366  2016-05-07             304   9526      7.08       2            564.000   \n",
+       "\n",
+       "     Minutes Lightly Active  Minutes Fairly Active  Minutes Very Active  \\\n",
+       "0                        46                      0                    0   \n",
+       "1                       316                     61                   60   \n",
+       "2                       226                     14                   77   \n",
+       "3                       190                     23                    4   \n",
+       "4                       171                      0                    0   \n",
+       "..                      ...                    ...                  ...   \n",
+       "362                     275                     49                   79   \n",
+       "363                     333                     10                   55   \n",
+       "364                     287                     29                   90   \n",
+       "365                     298                      8                   85   \n",
+       "366                     370                     13                   10   \n",
+       "\n",
+       "     Activity Calories  ...  Distance_miles       Days  Days_encoded  \\\n",
+       "0                 1680  ...        0.403891     Friday           4.0   \n",
+       "1                 2248  ...        8.767545   Saturday           5.0   \n",
+       "2                 1719  ...        6.567891     Sunday           6.0   \n",
+       "3                 9620  ...        3.119282     Monday           0.0   \n",
+       "4                 7360  ...        2.317714    Tuesday           1.0   \n",
+       "..                 ...  ...             ...        ...           ...   \n",
+       "362                236  ...        8.779972    Tuesday           1.0   \n",
+       "363               2075  ...        7.698787  Wednesday           2.0   \n",
+       "364               2249  ...       10.190484   Thursday           3.0   \n",
+       "365               2112  ...        9.190077     Friday           4.0   \n",
+       "366               1604  ...        4.399307   Saturday           5.0   \n",
+       "\n",
+       "     Work_or_Weekend  Hours Sleep Sleep efficiency  Yesterday_sleep  \\\n",
+       "0                  1     6.400000        92.086331         0.000000   \n",
+       "1                  0     7.566667        92.464358         6.400000   \n",
+       "2                  0     6.450000        88.761468         7.566667   \n",
+       "3                  1     5.183333        88.857143         6.450000   \n",
+       "4                  1     6.783333        82.892057         5.183333   \n",
+       "..               ...          ...              ...              ...   \n",
+       "362                1     6.283333        91.951220         5.233333   \n",
+       "363                1     6.766667        95.081967         6.283333   \n",
+       "364                1     4.666667        88.888889         6.766667   \n",
+       "365                1     6.166667        89.805825         4.666667   \n",
+       "366                0     8.366667        89.165187         6.166667   \n",
+       "\n",
+       "     Yesterday_sleep_efficiency  Months  Months_encoded  \n",
+       "0                      0.000000     May               5  \n",
+       "1                     92.086331     May               5  \n",
+       "2                     92.464358     May               5  \n",
+       "3                     88.761468     May               5  \n",
+       "4                     88.857143     May               5  \n",
+       "..                          ...     ...             ...  \n",
+       "362                   90.229885     May               5  \n",
+       "363                   91.951220     May               5  \n",
+       "364                   95.081967     May               5  \n",
+       "365                   88.888889     May               5  \n",
+       "366                   89.805825     May               5  \n",
+       "\n",
+       "[367 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "fitbit = pd.read_csv('../data/Fitbit2.csv')\n",
+    "fitbit"
    ]
   },
   {
@@ -59,20 +447,122 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "sns.set_context(\"poster\")\n",
+    "sns.set(rc={\"figure.figsize\": (12.,4.)})\n",
+    "sns.set_style(\"whitegrid\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Months_encoded\n",
+       "1      9892.064516\n",
+       "2      8922.866667\n",
+       "3     10312.935484\n",
+       "4     13079.033333\n",
+       "5     10620.096774\n",
+       "6     12536.166667\n",
+       "7      9193.322581\n",
+       "8     11584.774194\n",
+       "9      9191.333333\n",
+       "10     8272.451613\n",
+       "11     9467.466667\n",
+       "12     8470.064516\n",
+       "Name: Steps, dtype: float64"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# your code here\n",
+    "fitbit.groupby(\"Months_encoded\")[\"Steps\"].mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "average_month = sns.barplot(x=\"Months_encoded\", y=\"Steps\", data=fitbit) # default: average"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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EdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AHGQymWQ2m2UymVxdCgAAAAooD1cXAAB/NUtmpkxu977P0mw2Kzg42AkV3eKsugAAAFBwENoB3HdMbm5KX7tcloQ4V5diZSoVII9OXVxdBgAAAAyG0A7gvmRJiJNiz7m6DCuLqwsAAACAIXEeJgAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwDA4Ewmk8xms0wmk6tLAQAAfzEPVxcAAEBBZcnMlMnt3vePm81mBQcHO6GiW5xVFwAAyHuEdgAA8ojJzU3pa5fLkhDn6lKsTKUC5NGpi6vLAAAAuURoBwAgD1kS4qTYc64uw8ri6gIAAIBdODcOAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEHdU2ifN2+eunXrZrPs888/V+fOnVWvXj2Fh4frnXfeUXJysnV9SkqKoqKiFBYWpnr16mnIkCG6dOmSzRx79+5Vp06dVKdOHbVt21abNm2yWZ+bOQAAAAAAyO8cDu3Lly/XtGnTbJYdOnRIAwYM0OOPP65169ZpzJgx2rx5s6Kioqxjxo4dq//85z+aOXOmli5dqpMnT2rgwIHW9b/++qt69+6tZs2aae3atXr22Wc1fPhw7d27N9dzAAAAAABQENj9yLe4uDiNGTNG+/fvV6VKlWzWrVixQo888oj69OkjSapUqZIGDRqkyMhIRUVF6fLly1q/fr3mzp2rBg0aSJKmTJmitm3b6ttvv1W9evW0dOlSBQUFadCgQZKkKlWq6NixY1q4cKHCwsIUFxeX4xwAAAAAABQEdh9p//HHH+Xp6akNGzaoTp06Nut69uypESNG2L6Am5vS0tKUmJiow4cPS5IaNWpkXV+5cmUFBATo4MGDkm4drQ8LC7OZo1GjRjp8+LAsFkuu5gAAAAAAoCCw+0h7eHi4wsPDb7suODjY5uu0tDQtWbJEtWrVUokSJRQXF6fixYvL29vbZlzp0qUVGxsrSYqNjVVgYGC29UlJSbp8+XKu5nCExWLRzZs3Hd4+LyQlJdn8F7lD3+x3P/XMZDLJbDa7uow7SkpKksVicXUZeYbPmnHwWcPt0Df70TPH0Df70TPHGLlvFotFJpMpx3F2h/bcSk9P1/Dhw/XLL79o+fLlkm41ysvLK9tYb29vpaSkSJKSk5Ozjcn6OjU1NVdzOCItLU3Hjx93ePu8dPr0aVeXkC/RN/vdDz0zm83ZdjAayalTpwz5Q8XZ+Ky5Hp813A19sx89cwx9sx89c4xR+3a7bPtneRLaExMT9dprr+nAgQOaNWuWateuLUny8fFRampqtvEpKSnWoxHe3t7ZxmR9bTabczWHIzw9PVW1alWHt88LSUlJOn36tCpVqmToozVGQ9/sdz/1LDd7M12pcuXKBf7oJ581Y+Czhtuhb/ajZ46hb/ajZ44xct9iYmJyNc7poT0+Pl4vvfSSzp07p0WLFik0NNS6LjAwUFeuXFFqaqrNHoX4+HgFBARIksqUKaP4+Phsc/r6+qpw4cK5msMRJpNJvr6+Dm+fl8xms2FrMzL6Zj965npG+2GSV/isuR6fNdwNfbMfPXMMfbMfPXOMEfuW2x389/Sc9j+7evWqXnjhBV26dEnLly+3CeyS9PDDDyszM9N6Mznp1ul5cXFx1rENGjTQgQMHbLbbt2+f6tevLzc3t1zNAQAAAABAQeDU0P7222/r7Nmzmjx5skqUKKGEhATrn4yMDAUEBKhdu3aKjIzU/v37deTIEQ0ePFgNGzZU3bp1JUndunXTkSNHFB0drV9//VWLFy/W1q1bFRERIUm5mgMAAAAAgILAaafHZ2RkaPPmzUpLS9MLL7yQbf3OnTtVvnx5jRs3Tm+99ZYGDBggSWrevLkiIyOt46pVq6bZs2dr8uTJWrp0qcqXL6/JkyfbPAYupzkAAAAAACgI7im0T5w40fp3d3d3HTlyJMdtfH19NX78eI0fP/6OY5o3b67mzZvf0xwAAAAAAOR3Tj09HgAAAAAAOA+hHQAAAJJu3cnYbDYb/pGFAHA/yZPntAMAAOCvY8nMlMnt3o/FmM1mBQcHO6GiW5xVFwDczwjtAAAA+ZzJzU3pa5fLkhDn6lKsTKUC5NGpi6vLAIB8j9AOAABQAFgS4qTYc64uw8ri6gIAoIDgfCUAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAfxmTySSz2SyTyeTqUgAAAPIFD1cXAAAwPktmpkxu976f12w2Kzg42AkV/Y+zagMAADAiQjsAIEcmNzelr10uS0Kcq0uxYSoVII9OXVxdBgAAQJ4htAMAcsWSECfFnnN1GTYsri4AAAAgj3E+IQAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAI/hAgAAAAyKG9EB+RiP4QIAAAAKNkI7kI/xGC4AAACgYLun0D5v3jz95z//0QcffGBddvz4cU2YMEFHjx5ViRIl9OKLL6p79+7W9ZmZmZo1a5ZWr16t69evKzQ0VKNHj1aFChWcOgdwv+AxXAAAAEDB5fC5q8uXL9e0adNsll2+fFk9evRQxYoVtWbNGvXv31/R0dFas2aNdczs2bP10Ucfady4cVqxYoUyMzMVERGh1NRUp80BAAAAAEBBYPeR9ri4OI0ZM0b79+9XpUqVbNatWrVKnp6eevPNN+Xh4aEqVarozJkzmj9/vjp37qzU1FQtXrxYQ4cOVcuWLSVJU6dOVbNmzfTZZ5+pffv2TpkDAAAAAICCwO4j7T/++KM8PT21YcMG1alTx2bdoUOH1LBhQ3l4/G9fQKNGjXT69GlduHBBJ06c0I0bNxQWFmZdX6RIEQUHB+vgwYNOmwMAAAAAgILA7iPt4eHhCg8Pv+262NhYVa9e3WZZ6dKlJUm///67YmNjJUllypTJNiZrnTPmcITFYtHNmzcd3j4vJCUl2fwXuXO/9C3rMW1GlpSUJIvFWFe4G71v9Mwx9M1+RuyZM90vPwskPmuudj991pyJvtmPnjnGyH2zWCy5euSyU+8en5ycLC8vL5tl3t7ekqSUlBRro2435urVq06bwxFpaWk6fvy4w9vnpdOnT7u6hHypoPctLx7T5mynTp0y3DdIo/eNnjmGvtnPiD3LCwX9Z4HEZ80o7ofPWl6gb/ajZ44xat/+nGtvx6mh3cfHJ9vN4FJSUiRJvr6+8vHxkSSlpqZa/541JmsPsTPmcISnp6eqVq3q8PZ/lJu9JbmRkpKi8+fPq2zZstYdF85QkPd2S7f2op0+fVqVKlUy9JGHe+Wsz1leqly5suE+b0bvGz1zDH2znxF75kz3y88Cic+aq91PnzVnom/2o2eOMXLfYmJicjXOqaE9MDBQ8fHxNsuyvg4ICFB6erp1WcWKFW3GBAUFOW0OR5hMJvn6+jq8/R9ZMjNlcnP4xvxWZrNZxYoVu/eC/sBZteUHZrPZaf9P4RijfWPMD+iZY+ib/e6XnvGzwPX4rOFu6Jv96JljjNi33O50dWpoDw0N1YoVK5SRkSF3d3dJ0r59+1S5cmX5+/urcOHC8vPz0/79+62B+9q1azp27Ji6du3qtDlczeTmpvS1y289P9tATKUC5NGpi6vLAAAAAADkklNDe+fOnbVw4UKNGjVKEREROnLkiJYsWaKoqChJt87X79q1q6Kjo1WiRAmVK1dOkydPVmBgoFq3bu20OYzAkhAnxZ5zdRk2Cu6JaQAAAABQMDk1tPv7+2vhwoWaMGGCOnbsqFKlSmn48OHq2LGjdczAgQOVnp6uyMhIJScnKzQ0VIsWLZKnp6fT5gAAAAAAoCC4p9A+ceLEbMtq166tlStX3nEbd3d3DRs2TMOGDbvjGGfMAQAAAABAfnd/3JEMAAAAAIB8iNAOAAAAAIBBEdoBAAAAADAoQjsAAAAAGJzJZJLZbM71s71RcDj17vEAAAAAgP+xZGbK5Hbvx0rNZrOCg4OdUNH/OKs25C1COwAAAADkEZObm9LXLpclIc7VpdgwlQqQR6curi4DuUBoBwAAAIA8ZEmIk2LPuboMGxZXF4Bc41wIAAAAAAAMitAOAAAAAIBBEdoBAAAAADAoQjsAAChweDQS/ip81gDkNW5EBwAADINHI+GvwmcNQH5BaAcAAIbBo5HwV+GzBiC/ILQDAABD4dFI+KvwWQOQH3DeDQAAAAAABkVoBwAAAADAoAjtKHC4iysAAACAgoJr2mEYRr2LK3dwBQAAAOAqhHYYhhHv4sodXAEAAAC4EqEdhmK0u7hyB1cAAAAArsQ5vwAAAAAAGBShHQAAAAAAgyK0AwAAAABgUIR2AAAAAAAMitAOAAAAAIBBEdoBAAAAADAoQjsAAAAAoEAymUwym80ymUyuLsVhPKcdAAAAAGAolsxMmdzu/Riz2WxWcHCwEyq6xVl12YPQDgAAAAAwFJObm9LXLpclIc7VpViZSgXIo1OXv/x1Ce0AAAAAAMOxJMRJsedcXYaVxUWvyzXtAAAAAP5SBeE6Y+CvwpF2AAAAALnCdcbAX8/poT09PV3vvfee1q9frytXrig4OFjDhg1T3bp1JUnHjx/XhAkTdPToUZUoUUIvvviiunfvbt0+MzNTs2bN0urVq3X9+nWFhoZq9OjRqlChgnVMTnMAAAAAcD6uMwb+ek4P7XPmzNHq1as1ceJEVahQQQsWLFBERIQ2b94sT09P9ejRQ+Hh4YqKitJ3332nqKgoFSpUSJ07d5YkzZ49Wx999JEmTpyowMBATZ48WREREfr000/l5eWly5cv5zgHAAAAgLzBdcbAX8vpoX3Hjh1q3769mjZtKkl6/fXXtXr1an333Xc6deqUPD099eabb8rDw0NVqlTRmTNnNH/+fHXu3FmpqalavHixhg4dqpYtW0qSpk6dqmbNmumzzz5T+/bttWrVqrvOAQAAAABAQeH0Cz/8/f21a9cu/fbbb8rIyNDKlSvl5eWlhx56SIcOHVLDhg3l4fG/fQWNGjXS6dOndeHCBZ04cUI3btxQWFiYdX2RIkUUHBysgwcPSlKOcwAAAAAAUFA4/Uj7qFGj9Oqrr+qxxx6Tu7u73NzcNHPmTFWsWFGxsbGqXr26zfjSpUtLkn7//XfFxsZKksqUKZNtTNa6nOYoWbKkQ3VbLBbdvHnToW3/KOtOmEaWlJQki8VYJxIZvW/0zDH0zX70zDH0zX70zDH0zX70zDH0zX70zDH0zX7O6pnFYsnVExScHtpjYmJUuHBhvffeewoICNDq1as1dOhQffjhh0pOTpaXl5fNeG9vb0lSSkqKkpKSJOm2Y65evSpJOc7hqLS0NB0/ftzh7bM4+06YeeHUqVPWXhuF0ftGzxxD3+xHzxxD3+xHzxxD3+xHzxxD3+xHzxxD3+znzJ79OdvejlND+++//64hQ4ZoyZIlatCggSQpJCREMTExmjlzpnx8fJSammqzTVbQ9vX1lY+PjyQpNTXV+vesMVl7WnKaw1Genp6qWrWqw9tnyQ/PmqxcubIh96YZGT1zDH2zHz1zDH2zHz1zDH2zHz1zDH2zHz1zDH2zn7N6FhMTk6txTg3t33//vdLS0hQSEmKzvE6dOtqzZ4/Kli2r+Ph4m3VZXwcEBCg9Pd26rGLFijZjgoKCJEmBgYF3ncNRJpPpnkJ/fmLkU02Mip45hr7Zj545hr7Zj545hr7Zj545hr7Zj545hr7Zz1k9y+3OCafeiC4wMFCS9NNPP9ks//nnn1WpUiWFhobq8OHDysjIsK7bt2+fKleuLH9/fz300EPy8/PT/v37reuvXbumY8eOKTQ0VJJynAMAAAAAgILCqaG9du3aevjhhzVixAjt27dPp0+f1rRp07R37169/PLL6ty5sxITEzVq1CjFxMRo7dq1WrJkiXr37i3p1vn8Xbt2VXR0tHbu3KkTJ05o0KBBCgwMVOvWrSUpxzkAAAAAACgonHp6vJubm+bMmaNp06Zp5MiRunr1qqpXr64lS5aoTp06kqSFCxdqwoQJ6tixo0qVKqXhw4erY8eO1jkGDhyo9PR0RUZGKjk5WaGhoVq0aJE8PT0l3XqkXE5zAAAAAABQEDj97vFFixbVmDFjNGbMmNuur127tlauXHnH7d3d3TVs2DANGzbsjmNymgMAAAAAgILAqafHAwAAAAAA5yG0AwAAAABgUIR2AAAAAAAMitAOAAAAAIBBEdoBAAAAADAoQjsAAAAAAAZFaAcAAAAAwKAI7QAAAAAAGBShHQAAAAAAgyK0AwAAAABgUIR2AAAAAAAMitAOAAAAAIBBEdoBAAAAADAoQjsAAAAAAAZFaAcAAAAAwKAI7QAAAAAAGBShHQAAAAAAgyK0AwAAAABgUIR2AAAAAAAMitAOAAAAAIBBEdoBAAAAADAoQjsAAAAAAAZFaAcAAAAAwKAI7QAAAAAAGBShHQAAAAAAgyK0AwAAAABgUIR2AAAAAAAMitAOAAAAAIBBEdoBAAAAADAoQjsAAAAAAAZFaAcAAAAAwKAI7QAAAAAAGBShHQAAAAAAg8qT0L5+/Xo9+eSTCgkJUbt27bRlyxbrut9++029e/dW/fr11bRpU02bNk0ZGRk22y9fvlyPPfaYateurX/+8586duyYzfrczAEAAAAAQH7n9ND+ySefaNSoUerSpYs2bdqk9u3ba/Dgwfr222+VlpamXr16SZJWrFihsWPH6t///rfee+896/br1q3TpEmT9Oqrr2rt2rUqX768evTooUuXLklSruYAAAAAAKAg8HDmZBaLRdOnT1f37t3VpUsXSVLfvn116NAhHThwQOfOndP58+e1atUqFS1aVNWrV9fFixc1adIk9enTR15eXpo7d666du2qDh06SJLeeusttWrVSqtXr1bv3r21bdu2HOcAAAAAAKAgcOqR9lOnTuncuXN66qmnbJYvWrRIvXv31qFDh1SzZk0VLVrUuq5Ro0ZKTEzU8ePHdfHiRZ0+fVphYWHW9R4eHmrQoIEOHjwoSTnOAQAAAABAQeHUI+2nTp2SJN28eVO9evXSsWPHVL58efXt21fh4eGKjY1VYGCgzTalS5eWJP3+++/y8LhVTpkyZbKNOXHihCTlOEedOnUcqt1isejmzZsObftHJpNJZrP5nufJS0lJSbJYLK4uw4bR+0bPHEPf7EfPHEPf7EfPHEPf7EfPHEPf7EfPHEPf7OesnlksFplMphzHOTW0JyYmSpJGjBihAQMGaOjQodq2bZv69eun999/X8nJySpSpIjNNt7e3pKklJQUJSUlSVK2U9y9vb2VkpIiSTnO4ai0tDSnHKk3m80KDg6+53ny0qlTp6y9Ngqj942eOYa+2Y+eOYa+2Y+eOYa+2Y+eOYa+2Y+eOYa+2c+ZPcvN5d1ODe2enp6SpF69eqljx46SpBo1aujYsWN6//335ePjo9TUVJttsoK2r6+vfHx8JOm2Y7L2tOQ0x73UXrVqVYe3z5KbPSWuVrlyZUPuTTMyeuYY+mY/euYY+mY/euYY+mY/euYY+mY/euYY+mY/Z/UsJiYmV+OcGtoDAgIkSdWrV7dZXrVqVX3xxRdq2LChfv75Z5t18fHx1m2zTouPj49XlSpVbMZkzR0YGHjXORxlMpnuKfTnJ0Y+1cSo6Jlj6Jv96Jlj6Jv96Jlj6Jv96Jlj6Jv96Jlj6Jv9nNWz3O6ccOqN6GrWrKlChQrp+++/t1n+888/q2LFigoNDdWxY8esp9FL0r59+1SoUCE99NBD8vf3V+XKlbV//37r+vT0dB06dEihoaGSlOMcAAAAAAAUFE4N7T4+PoqIiNB7772njRs36r///a/mzJmjr776Sj169FCrVq1UqlQpvfbaazpx4oR27NihKVOmqGfPntZz+Xv27Kn3339f69atU0xMjN544w0lJyfrmWeekaRczQEAAAAAQEHg1NPjJalfv34ym82aOnWq4uLiVKVKFc2cOVOPPPKIJGnhwoWKiorS3//+dxUtWlT//Oc/1a9fP+v2f//733X9+nVNmzZNV65cUa1atfT++++rRIkSkm7ddC6nOQAAAAAAKAicHtolqUePHurRo8dt1z3wwANavHjxXbfv1auXevXqdcf1uZkDAAAAAID8zqmnxwMAAAAAAOchtAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIPK09B+6tQp1atXT2vXrrUuO378uLp27aq6desqPDxcy5Yts9kmMzNTM2bMULNmzVS3bl299NJLOnv2rM2YnOYAAAAAAKAgyLPQnpaWpqFDh+rmzZvWZZcvX1aPHj1UsWJFrVmzRv3791d0dLTWrFljHTN79mx99NFHGjdunFasWKHMzExFREQoNTU113MAAAAAAFAQeOTVxDNnzpSfn5/NslWrVsnT01NvvvmmPDw8VKVKFZ05c0bz589X586dlZqaqsWLF2vo0KFq2bKlJGnq1Klq1qyZPvvsM7Vv3z7HOQAAAAAAKCjy5Ej7wYMHtXLlSk2cONFm+aFDh9SwYUN5ePxvX0GjRo10+vRpXbhwQSdOnNCNGzcUFhZmXV+kSBEFBwfr4MGDuZoDAAAAAICCwulH2q9du6bhw4crMjJSZcqUsVkXGxur6tWr2ywrXbq0JOn3339XbGysJGXbrnTp0tZ1Oc1RsmRJh+q2WCw2p/I7ymQyyWw23/M8eSkpKUkWi8XVZdgwet/omWPom/3omWPom/3omWPom/3omWPom/3omWPom/2c1TOLxSKTyZTjOKeH9rFjx6pevXp66qmnsq1LTk6Wl5eXzTJvb29JUkpKipKSkiTptmOuXr2aqzkclZaWpuPHjzu8fRaz2azg4OB7nicvnTp1ytprozB63+iZY+ib/eiZY+ib/eiZY+ib/eiZY+ib/eiZY+ib/ZzZsz9n29txamhfv369Dh06pE8//fS26318fKw3lMuSFbR9fX3l4+MjSUpNTbX+PWtM1p6WnOZwlKenp6pWrerw9llys6fE1SpXrmzIvWlGRs8cQ9/sR88cQ9/sR88cQ9/sR88cQ9/sR88cQ9/s56yexcTE5GqcU0P7mjVrdPHiRetN5LKMGTNGmzdvVmBgoOLj423WZX0dEBCg9PR067KKFSvajAkKCpKkHOdwlMlkuqfQn58Y+VQTo6JnjqFv9qNnjqFv9qNnjqFv9qNnjqFv9qNnjqFv9nNWz3K7c8KpoT06OlrJyck2y1q3bq2BAweqQ4cO+uSTT7RixQplZGTI3d1dkrRv3z5VrlxZ/v7+Kly4sPz8/LR//35raL927ZqOHTumrl27SpJCQ0PvOgcAAAAAAAWFU+8eHxAQoAceeMDmjyT5+/srICBAnTt3VmJiokaNGqWYmBitXbtWS5YsUe/evSXdOp+/a9euio6O1s6dO3XixAkNGjRIgYGBat26tSTlOAcAAAAAAAVFnj2n/Xb8/f21cOFCTZgwQR07dlSpUqU0fPhwdezY0Tpm4MCBSk9PV2RkpJKTkxUaGqpFixbJ09Mz13MAAAAAAFAQ5Hlo/+mnn2y+rl27tlauXHnH8e7u7ho2bJiGDRt2xzE5zQEAAAAAQEHg1NPjAQAAAACA8xDaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABgUoR0AAAAAAIMitAMAAAAAYFCEdgAAAAAADIrQDgAAAACAQTk9tF+5ckWjR49W8+bNVb9+fT3//PM6dOiQdf3evXvVqVMn1alTR23bttWmTZtstk9JSVFUVJTCwsJUr149DRkyRJcuXbIZk9McAAAAAAAUBE4P7YMHD9a3336rKVOmaM2aNapRo4Z69eqlkydP6tdff1Xv3r3VrFkzrV27Vs8++6yGDx+uvXv3WrcfO3as/vOf/2jmzJlaunSpTp48qYEDB1rX52YOAAAAAAAKAg9nTnbmzBl99dVX+uijj/Twww9Lkv71r3/pyy+/1KeffqqLFy8qKChIgwYNkiRVqVJFx44d08KFCxUWFqa4uDitX79ec+fOVYMGDSRJU6ZMUdu2bfXtt9+qXr16Wrp06V3nAAAAAACgoHDqkfbixYtr/vz5CgkJsS4zmUwymUy6du2aDh06lC1YN2rUSIcPH5bFYtHhw4ety7JUrlxZAQEBOnjwoCTlOAcAAAAAAAWFU4+0FylSRC1atLBZtm3bNp05c0ZvvPGG1q1bp8DAQJv1pUuXVlJSki5fvqy4uDgVL15c3t7e2cbExsZKkmJjY+86R4kSJRyq3WKx6ObNmw5t+0cmk0lms/me58lLSUlJhtvBYfS+0TPH0Df70TPH0Df70TPH0Df70TPH0Df70TPH0Df7OatnFotFJpMpx3FODe1/9s0332jkyJFq3bq1WrZsqeTkZHl5edmMyfo6NTVVSUlJ2dZLkre3t1JSUiQpxzkclZaWpuPHjzu8fRaz2azg4OB7nicvnTp1SklJSa4uw4bR+0bPHEPf7EfPHEPf7EfPHEPf7EfPHEPf7EfPHEPf7OfMnt0u//5ZnoX2HTt2aOjQoapfv76io6Ml3Qrffw7WWV+bzWb5+PjcNninpKRY97TkNIejPD09VbVqVYe3z5KbPSWuVrlyZUPuTTMyeuYY+mY/euYY+mY/euYY+mY/euYY+mY/euYY+mY/Z/UsJiYmV+PyJLR/+OGHmjBhgtq2bat33nnHuvegTJkyio+PtxkbHx8vX19fFS5cWIGBgbpy5YpSU1Nt9jjEx8crICAgV3M4ymQyydfX1+Ht8xMjn2piVPTMMfTNfvTMMfTNfvTMMfTNfvTMMfTNfvTMMfTNfs7qWW53Tjj9kW8fffSRxo0bpy5dumjKlCk24btBgwY6cOCAzfh9+/apfv36cnNz08MPP6zMzEzrDemkW6cexMXFKTQ0NFdzAAAAAABQUDg15Z46dUpvvfWWHn/8cfXu3VsXLlxQQkKCEhISdP36dXXr1k1HjhxRdHS0fv31Vy1evFhbt25VRESEJCkgIEDt2rVTZGSk9u/fryNHjmjw4MFq2LCh6tatK0k5zgEAAAAAQEHh1NPjt23bprS0NG3fvl3bt2+3WdexY0dNnDhRs2fP1uTJk7V06VKVL19ekydPtnmE27hx4/TWW29pwIABkqTmzZsrMjLSur5atWo5zgEAAAAAQEHg1NDep08f9enT565jmjdvrubNm99xva+vr8aPH6/x48c7PAcAAAAAAAUBF4EDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQ+Ta0Z2ZmasaMGWrWrJnq1q2rl156SWfPnnV1WQAAAAAAOE2+De2zZ8/WRx99pHHjxmnFihXKzMxURESEUlNTXV0aAAAAAABOkS9De2pqqhYvXqyBAweqZcuWeuihhzR16lTFxsbqs88+c3V5AAAAAAA4Rb4M7SdOnNCNGzcUFhZmXVakSBEFBwfr4MGDLqwMAAAAAADnMVksFouri7DXZ599pldeeUXff/+9fHx8rMtfffVVJScna968eXbN980338hiscjT09Mp9ZlMJulGopSZ4ZT5nMbNXSrkJ6P+Lzdk3+iZY+ib/eiZY+ib/eiZY+ib/eiZY+ib/eiZY+ib/Zzcs7S0NJlMJtWvX/+u4zyc8mp/saSkJEmSl5eXzXJvb29dvXrV7vlMJpPNf52ikJ/z5nIyp75PZzNo3+iZY+ib/eiZY+ib/eiZY+ib/eiZY+ib/eiZY+ib/ZzVM5PJlKu58mVozzq6npqaanOkPSUlRWaz2e756tWr57TaAAAAAABwlnx5TXuZMmUkSfHx8TbL4+PjFRAQ4IqSAAAAAABwunwZ2h966CH5+flp//791mXXrl3TsWPHFBoa6sLKAAAAAABwnnx5eryXl5e6du2q6OholShRQuXKldPkyZMVGBio1q1bu7o8AAAAAACcIl+GdkkaOHCg0tPTFRkZqeTkZIWGhmrRokVOuwM8AAAAAACuli8f+QYAAAAAwP0gX17TDgAAAADA/YDQDgAAAACAQRHaAQAAAAAwKEI7AAAAAAAGRWgHAAAAAMCgCO0AAAAAABhUvn1O+/3EYrEoMzNT7u7uri7F8CwWizIyMpSZmSmTySRPT09Xl5QvWCwWpaeny2KxyM3NTR4efGuwR2pqqjw8POTmxn7QnGT9+8z6Y7FY5O3tzfe3HKSnpyszM1OS5OXl5eJqjC/rs/XHz1kWHx8fF1ZmfFmfNX6G5t4ff/dwd3fn+9ldZPXqz79n3LhxQ6mpqXJzc5Ofnx89/JM79U2Srl+/rsKFC7ugKmO7Xc8sFotu3LihtLQ0mUwm+fr65pufqfyGaXCpqal655131KdPH1eXYnixsbEaOnSoWrZsqcaNG+ull17Sd9995+qyDO/s2bPq16+fmjRporCwMA0aNEhnzpxxdVn5xoEDB1SvXj19/vnnri7F8E6cOKGaNWuqbt26qlu3rurVq6emTZvqiy++cHVphpWenq5ly5apdevWatCggf7xj39ox44dri7L0LZv367g4GCFhIQoJCTE+nmrW7eu/vnPf7q6PMO6ceOGxo8fr5YtWyosLEy9e/fWDz/84OqyDC8hIUFDhw5Vs2bN1KJFC40ZM0aXL192dVmGlPU7bd++fW2W79mzR88995zCw8P1zDPPaNmyZS6q0Jj+3Lc/7oT88ssvFRYWpuvXr7uqPEO63WctLS1Nq1at0jPPPKNWrVrp2Wef1bvvvqubN2+6sNLcI7QbWFpamhYsWKAlS5bIbDa7uhxDu3nzpgYOHKjz58/r/fff17p161SuXDlFREQoNjbW1eUZ1o0bN9SvXz+lpqZq9erVWrVqldLS0tSzZ09Xl5YvXLlyRSNHjsw3e2ld7aefflLRokX13Xffad++fTp06JC+/PJLPfroo64uzZAyMzP10UcfafLkyRo2bJi2b9+u5s2b67XXXtOJEydcXZ5htWjRQl9//bW+/vprHThwQAcOHNDbb78tLy8vDRkyxNXlGVJaWpqmTp2qXbt2ad68eVq/fr1Kliypl19+WYmJia4uz7CSkpLUv39/nThxQvPmzdMHH3yg+Ph4fobexp1+p/3111/Vv39/tWnTRjt37lTfvn01Y8YMrV271oXVGsft+mYymZSRkaGvv/5aAwcOVKFChaxnYuH2PbNYLNq+fbvGjBmjvn376vPPP9fYsWO1bds2jRs3zsUV5w6h3aD++9//qmfPnnr//fdVrVo1paamurokQ4uJidGxY8c0fvx4VatWTRUqVFBkZKSKFCmiDRs2uLo8w0pMTFSNGjU0btw4PfDAA6pSpYp69uyp2NhYnT592tXlGVpqaqpmzZql8uXLWy8twJ2lp6fr5MmTevDBB+Xp6amiRYvKz89PhQoV4rKCO7hx44bmz5+vV155RU888YQCAgI0YMAANW3aVN9++62ryzMsLy8vlShRQsWKFVORIkV048YNTZw4US+++KKaNGni6vIMKTU1VV999ZU6deqkmjVrqkKFCho0aJAuX76so0ePuro8w/r+++919OhRTZw4UbVr11bVqlX19ttv67ffftOWLVtcXZ5h3Ol32tTUVK1atUoPPPCABgwYoBIlSqhTp07q2rWrFixYIEn39c/Wu/Vt4sSJGjBggGrUqKHU1NT7uk9/dKeeJScna+vWrerQoYOefvppFS1aVE2aNFH//v3zzb9VflMyqKNHjyowMFAbN25UlSpV+MeYgwoVKmjevHmqXLmydVlGRoYyMjKUlJTkwsqMLSAgQJMmTVLZsmWVmZmpM2fOaPHixQoKClKlSpVcXZ6h7dmzRzt37tSkSZOs10bhzjIzM62hXZJSUlKUlpbm4qqM7dSpU7p8+bKeeOIJZWRkWH8xmzt3rp5//nlXl5cvpKena/bs2SpatKgGDRrk6nIMy8PDQ8WLF9f27dsVFxen69ev64MPPlDJkiX10EMPubo8wzp79qw8PT0VEhJi/T2tUKFCKlu2rA4dOuTi6ozjz7/TZh0VzsjI0LFjxxQaGmozvk6dOjp79qwSExPv65+td+pbamqqjh07poULF6pv3778LP2DO+Unb29vDRw4UAMGDLAZf/36dZlMpnzRQ+42ZVBPPvmknnzySeseIkL73RUvXtzmCIrFYtGnn36qixcvqmXLlq4rLJ9IS0vTyJEjtXHjRhUpUkSzZ892dUmG9vvvv+vNN9/U22+/bb35C6em3V1mZqZ++eUXlS1bVs8//7zOnDmjBx98UC+99JJatGjh6vIM6fTp0zKZTIqPj9frr7+ukydP6oEHHlBERIRatWrl6vLyhfPnz2vNmjWaOHHiff3Lf068vb31r3/9S6+++qpatGhhvUHTe++9p2LFirm6PMMKCAhQenq6zp8/r7Jly0q6dUTv3Llzqlq1qourM44//06bxWKxKCEhQY0bN7ZZXrp0aWVmZiouLk5+fn5/ZamGcqe++fn5afny5ZJkvccJOeGWO+UnNze3bP8m4+PjtWzZMjVp0iRf3HSTI+0GZzKZZDKZCAR22rNnj9566y117txZderUcXU5hufp6an+/fvrk08+0WOPPaaIiAiumb2D1NRU682a/rijiEBwd+np6Tp9+rRSUlI0cuRIvf/++6pVq5b69u2rAwcOuLo8Q0pOTlZ6err+9a9/6YUXXtCHH36oRx55RAMHDqRnuZCZmal///vfKlu2rJ566ilXl2NoFotFP/30kwICArRkyRKtW7dO7dq104ABA/TTTz+5ujzDql+/vsqWLavIyEglJCTo0qVLmjJlipKTk5WSkuLq8gznz7/Tmkwm69NX/sjLy0sWi4VLQ/9fVt9uF8yz7rJPaLd1t55J0qVLl/Taa6/JYrFo1KhRf3F1jiG0G5ybm5vc3Nz4x5hLFotFGzZsUP/+/fX4448rKirK1SXlG5UrV1ZQUJDGjRunsmXL6qOPPnJ1SYa0bt06HT9+XK+//royMjKsp1RlPa4Gt+fn56fvv/9eS5cuVe3atRUUFKQRI0aocePGWrRokavLMyRPT0+ZTCb17t1brVu3VpUqVfTaa6+padOmWrx4savLM7z09HRt2bJFnTt3dnUphnf69GlFRkbqjTfeUKNGjfTQQw8pKipK1atX16xZs1xdnmH5+flpzpw5unLlipo1a6bHHntMHh4eevTRR+Xr6+vq8gznz7/Turu7y2w2Kzk52WZc1s9SenhLVt9udwAvq5/kBFt369nvv/+uiIgInT17VnPnzlWZMmVcUKH9OD0eBYbFYtHChQv17rvv6h//+AeBPRcuXryoffv2qV27dtZlJpNJlSpVUkJCggsrM67169crISEh2w2txowZox07dvAL7l14eXllOyOhUqVK+uabb1xUkbEFBgZKkqpUqWKz/IEHHtDBgwddUVK+cvz4ccXFxdl8f8PtHTlyRJJUo0YNm+U1a9bk2uwcVK1aVWvXrtWNGzdkNpvl5uamp59+Wm3atHF1aYZnMplUpkwZnT9/3mZ5fHy83N3dVbp0aRdVln8Q2u3z66+/qlevXnJ3d9fSpUut99nJDzjSbnA5nd6B/1m6dKneffdd9e3bl8CeS3FxcRoyZIj27t1rXZaUlKQff/wx2y9vuGX69OnasmWLNm7cqK1bt1qfTvD666/r7bffdnF1xnX8+HHVr1/fJgCkpaXp+++/V82aNV1YmXGFhITIbDZn69mJEyeyBXlk98033yggIEAVKlRwdSmGV65cOWVkZOjHH3+0LktLS9OxY8dUrVo1F1ZmbFevXlWXLl30888/W5+EceLECcXExKhp06auLs9w/vw7rYeHhx555BHt27fPetZaamqqdu/erZo1a/K44/93tyzg5uZGTriN2/UsLi5OPXv2VLFixbRq1ap8FdgljrQbHte0505MTIzeeecdtW3bVs8//7zOnj0r6dbR90KFCsnf39/FFRpTjRo11KxZM7355puKioqSj4+P5s2bJ5PJpG7durm6PEP6857/9PR0SbdOk8y6KR2yq1atmqpUqaKoqCiNHj1ahQoV0ooVK3T69GlNnTrV1eUZkp+fn3r16qVZs2apZMmSCgoK0oYNG3TkyBHrTYhwexaLRSdOnCBw5lLdunVVr149DR8+XJGRkSpRooTWrl2rY8eOsRP8LrK+50+YMEFvvPGGrl27ptGjR+uxxx5T7dq1XVyd8WSdafXHa9o7d+6spUuXavjw4erSpYu+/fZbbd68WVOmTHFlqYaSUxbIyMggJ/xJ1mctIyND0q3P3NixY3Xx4kW9/fbbunjxouLj461nKVSvXt3wN6MjtBucyWSSp6en9UYTuL3t27fLZDJp+/bt2rZtm/UbnMlkUseOHTVu3DhXl2hIJpNJU6dO1dSpUzVs2DBdv35dYWFh+vDDD1W8eHFXl5cvuLm5ydvbm2eN58DDw0Pz58/XlClTNGTIEF2/fl116tTR0qVLVb58eVeXZ1j9+/eXn5+fZsyYofj4eAUFBWnu3LmqVauWq0szNJPJpCtXrqhEiRKuLiVf8PDw0Lx58zR9+nRFRkbq+vXrCg4O1gcffMBd0O/Czc1NU6dO1fjx49W9e3d5e3urffv2Gjx4sKtLMySTySQvLy+bG8+VKFFCS5Ys0YQJE9S3b1+VKVNG48aN46kif5CVBf58wz7p1pMfihYt6oKqjC3rs5YVxDMzM3X48GGZzWb17t1b0v/OUnBzc9OWLVsUEBDgypJzZLJwPgUAAAAAAIbEoSEAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABkVoBwAAAADAoAjtAAAAAAAYFKEdAAAAAACDIrQDAFBAWCwWV5cAAACcjNAOAIATdOvWTUFBQXruuefuOGbQoEEKCgrS66+/7tTXjo2N1csvv6xz585Zl4WHhzv9dfKz119/XeHh4U6ZKygoSDNnznTKXAAA5ITQDgCAk7i5uem7775TbGxstnU3b97Url278uR1v/76a+3evTtP5gYAAK5FaAcAwEmCg4Pl7e2trVu3Zlu3a9cumc1mBQQEuKAyAACQXxHaAQBwEl9fX7Vo0eK2oX3z5s1q06aNPDw8rMtSUlL03nvvqW3btgoJCVHr1q01f/58ZWZmWsd069ZNo0aN0vz589WyZUuFhIToueee05EjRyRJa9eu1ciRIyVJjz32mM0p8WlpaZo0aZKaNGmiunXrqmfPnjpz5ox1/aVLlzRkyBA1adJEISEhevrpp7V+/Xq733dKSoomTZqkFi1aqFatWnrqqae0efNmmzHh4eGaMWOG3nnnHTVu3Fi1a9dWr169dPr0aZtxu3fv1nPPPae6deuqadOmGj16tK5du2Zdf/r0aQ0cOND6nrp166bDhw/bzHH16lWNHDlSDRs2VGhoqCZPnmzT0yw7duxQp06dFBISoiZNmmj8+PG6efOmzZgDBw7oH//4h+rUqaM2bdro66+/trs/AADcC0I7AABO9OSTT2Y7RT4xMVF79uxR+/btrcssFov69OmjhQsX6tlnn9XcuXPVtm1bTZs2TWPGjLGZc9u2bdq5c6ciIyM1ZcoUXbhwQa+88ooyMjLUsmVL9e3bV5I0a9Ys9evXz7rd5s2b9csvv2jixIkaM2aMjh49qkGDBlnXDxs2TL/++quioqK0YMECBQcHa8SIEdq3b1+u36/FYlH//v21YsUK9ejRQ3PmzFG9evU0aNCgbDsAli1bppMnT+rtt9/W+PHjdfToUY0YMcK6fteuXerdu7f8/f01bdo0DR06VDt27LDWHBMTo06dOum3335TZGSkoqOjZTKZ9MILL+jAgQOSpMzMTEVERGj37t0aMWKEJk6cqG+++SbbToRPP/1U/fv314MPPqj33ntPAwYM0IYNG9SvXz/rDf1+/PFH9ezZU4ULF9aMGTPUvXt3DR48ONe9AQDAGTxyHgIAAHKrZcuWMpvN2rp1q1588UVJ0vbt2+Xv76+HH37YOm7Pnj36+uuvNWXKFLVr106S1KRJE/n4+Gj69Onq3r27qlWrJklKT0/XokWL5OfnJ0m6ceOGRowYoePHj6tWrVqqWLGiJKlGjRoqX7689TUCAgI0e/ZseXp6SpLOnDmjOXPmKDExUX5+fjpw4ID69++vVq1aSZIaNmyoYsWKycvLK9fv9+uvv9aXX36pqVOn6sknn5QkNWvWTElJSYqOjlb79u2tZxcUKVJEs2fPlru7uyTpv//9r2bOnKnLly+rePHimjlzpmrUqKFZs2bJZDJJkry8vDR9+nRduHBBs2bNkpeXl5YtW2btRcuWLdW+fXtNmjRJH3/8sfbs2aMjR45owYIFat68uSQpLCzM5iZ0FotF0dHRatasmaKjo63LK1WqpBdffFG7d+9Wy5YtNW/ePPn7+2vOnDnWHhYvXtxmxwcAAHmNI+0AADiRj4+PwsPDbU6R37Rpk5544glrEJVunXbt4eGhtm3b2mzfoUMH6/osVatWtYZUSdbr4pOSku5aS+3ata1hU5I10Gedbv7II49o5syZGjhwoFavXq0LFy5oxIgRql+/fq7f7969e2UymdSiRQulp6db/4SHhyshIUG//PKLdWxISIg1sEtSYGCg9X0kJyfr2LFjatWqlU2fnnzySW3btk0lS5bUgQMH9Oijj9r0wsPDQ+3atdPRo0d148YNHTp0SJ6enmrWrJl1TNZlC1lOnjyp2NhYhYeH29QcGhoqPz8/ffXVV5Kkw4cPq1mzZjY9bN26tc17AAAgr3GkHQAAJ3viiSc0YMAAxcbGytvbW3v37tVrr71mM+bq1asqXrx4tgBYqlQpSdL169ety8xms80YN7db+9xvd532H/n6+t51u6lTp2ru3LnasmWLtm3bJjc3NzVu3FhvvvmmypUrl6v3euXKFVksljsG/fj4eNWoUSPH93H16lVZLBb5+/vf8bWuXr2qkiVLZltesmRJWSwWJSYm6urVqypWrJhN8Jf+19esmiUpKipKUVFRt6056/WKFy9us87DwyPbMgAA8hKhHQAAJ2vevLkKFSqkrVu3ytfXV+XLl1etWrVsxhQtWlSXL19WRkaGTXDPCox/RTAsXLiwhg0bpmHDhunkyZPauXOnZs+eraioKM2fPz/Xc/j6+mrZsmW3Xf/AAw/kah4/Pz+ZTCZdunTJZnlKSor27dunOnXqqGjRorpw4UK2bRMSEiTd6lnx4sVv29esoC7dOk1fkoYPH66GDRtmm69o0aKSpGLFimV7PYvFoqtXr+bqPQEA4AycHg8AgJN5eXmpVatW2rZtm7Zs2WK9Zv2PGjZsqPT09Gx3mt+wYYMk2Vz/npOsI9b2OHfunM2d7h988EG99NJLaty4sc6fP5/reRo2bKibN2/KYrEoJCTE+ufnn3/We++9p/T09FzNU6hQIdWoUSPbs+z37Nmjl19+WfHx8QoNDdWuXbuUmJhoXZ+RkaFNmzYpJCREXl5eCgsLU3p6unbs2GEdk5qaaj3lPeu9+vv767fffrOpOSAgQO+++66OHTsm6da18Hv27LG5DOHLL79UWlparvsDAMC94kg7AAB54Mknn1Tv3r3l5uamyMjIbOubN2+uRx55RJGRkYqLi9NDDz2kAwcOaMGCBerYsaOqVq2a69fKOnK8fft2NW/eXFWqVMlxm3LlyikwMFDjx49XYmKiKlasqKNHj2r37t3q3bt3rl+7RYsWCg0NVb9+/dSvXz9VqVJFR44c0YwZM9SsWTOVKFEi13MNHDhQffv21eDBg/W3v/1NFy5c0JQpU9SqVStVr15dAwYM0J49e9S9e3e9/PLL8vT01IcffqizZ89q4cKFkm4F7aZNmyoyMlIXL15UuXLltGzZMl26dMl66r27u7sGDRqk0aNHy93dXY8++qiuXbum2bNnKy4uTjVr1pQk9e/fXzt27FCvXr0UERGhS5cuadq0aTbXuAMAkNcI7QAA5IHGjRurSJEiKlOmzG1DtMlk0rx58zRjxgwtWbJEly5dUvny5TV48GD16NHDrtd65JFH1LhxY7377rvau3dvrk9tnzVrlqZMmaLp06fr8uXLKlOmjAYMGKCXX34516/t5uam+fPna/r06Zo3b54uXryogIAA9ejRQ/3797frfTz66KOaO3euZs2apf79+6tEiRJ66qmn9Morr0iSqlWrpo8++khTpkzRyJEjZTKZVLt2bS1btkwNGjSweV/R0dGaMWOGUlJS9OSTT+rvf/+7du7caR3z7LPPqlChQlq4cKFWrlwpX19f1a9fX9HR0apQoYKkW3eT//DDDzVx4kQNGjRI/v7+1sfIAQDwVzFZsh5GCgAAAAAADIUj7QAAIJuMjAzltF/fZDLx+DMAAPIYR9oBAEA23bp1s3lW/O2UK1dOn3/++V9UEQAA9ydCOwAAyObkyZO6cePGXcd4eXkpKCjoL6oIAID7E6EdAAAAAACD4jntAAAAAAAYFKEdAAAAAACDIrQDAAAAAGBQhHYAAAAAAAyK0A4AAAAAgEER2gEAAAAAMChCOwAAAAAABvV/gntYSaFLn+QAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fitbit.groupby(\"Months_encoded\")[\"Steps\"].mean().plot(kind=\"bar\", color=\"salmon\", title=\"Average of steps\")\n",
+    "plt.xticks(rotation=0.5)\n",
+    "plt.savefig(\"../figures/figure1.png\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "fitbit.groupby([\"Months_encoded\",\"Work_or_Weekend\"])[\"Steps\"].mean().unstack().plot(kind=\"bar\")\n",
+    "plt.xticks(rotation=0.5)\n",
+    "plt.savefig(\"../figures/figure2.png\")"
    ]
   },
   {
@@ -88,10 +578,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 51,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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CsCkk2gmCIAiCIAiCIAjCppBoJwiCIAiCIAiCIAibQqKdIAiCIAiCIAiCIGwKiXaCIAiCIAiCIAiCsCkk2gmCIAiCIAiCIAjCpmjq004QViLwIXQcqUEo0AinJw+Zw4vg4Jyq7xEEQQBAiBew+0A9Glo6kO/NxMTRPjg5R6KnpZtUO55Ew/M8avy1aAw2I8+Vg6KCseA4TvMYgiAIgog3JNoJW9C2Zyv8761EqLW+9zVntg8F85YCgOx7WRNmxn2uBEHYjy2Vx/HM67tQ39zR+5ovJxN3XD8Js0qHJHBm+ki140k05Ud3YNX2NagPNvW+5nPlYsm0RZgxbCrzGIIgCIJIBLR8TCSctj1bcerV5RGiHABCrfU49epyxffa9myN51QJgrAhWyqP41erKyIELgDUN3fgV6srsKXyeIJmpo9UO55EU350B36/+ZkIMQ4A9cEm/H7zMyg/uoNpDEEQBEEkChLtREIR+BD8763U/Xn/+pUQ+JCJMyIIIpkI8QKeeX2X4phn36hCiBfiNCNjpNrxJBqe57Fq+xrFMX/7bA3+pjJm1faXwfO8mVMjCIIgCGZItBMJpeNITUwUXQuhlnp0HKkxcUYEQSQTuw/Ux0Sko/E3BbH7gP7fmXiSaseTaGr8tTHR82gaOprQoDKmPtiIGn+teRMjCIIgCA2QaCcSSijQaIttEASRnDS0KAtcreMSTaodT6JpDDbbclsEQRAEoQUS7URCcXrybLENgiCSk3xvpqnjEk2qHU+iyXPl2HJbBEEQBKEFEu1EQskcXgRntk/3551eHzKHF5k4I4IgkomJo33w5SgL2IJcFyaO1v87E09S7XgSTVHBWPhcuYpj8jNzka8yxufKQ1HBWPMmRhAEQRAaINFOJBQH5+xt66aHgrlLqV87QfRhnJwDd1w/SXHM7deVJE1/81Q7nkTDcRyWTFukOObWcxfhVpUxS6bdRP3aCYIgiIRBf4GIhJM1YSYGLrw3JuLu9PowcOG9iu9Rn3aCIGaVDsF9i8tiItQFuS7ct7gs6fqap9rxJJoZw6bintl3xETcfa483DP7DswYNpVpDEEQBEEkin6JngBBAD3C3V1Y1uMmH2iE05OHzOFFvVF0pfcIgiBmlQ7BjJLB2H2gHg0tHcj3ZmLiaF/SRqRT7XgSzYxhU1E2ZDJq/LVoDDYjz5WDooKxEdFzljEEQRAEkQhItBO2wcE54RpRovk9oKffO4l6grAPPM/HXfw4OQcmjS3Q9dkQL9hOIBs5HiIWjuNQPKDQ8BiCIAiCiDck2omkp23PVvjfWxnR792Z7UPBvKWUPk8QCaD86A6s2r4moj+2z5WLJdMW2TLNeEvlcTzz+q6I/ui+nEzccf0kSkUnCIIgCCLhUM4XkdS07dmKU68ujxDsABBqrcepV5ejbc/WBM2MIPom5Ud34Pebn4kQ7ABQH2zC7zc/g/KjOxIzMRm2VB7Hr1ZXRAh2AKhv7sCvVldgS+XxBM2MIAiCIAiiBxLtRNIi8CH431upOMa/fiUEPhSnGRFE34bneazavkZxzKrtL4Pn+TjNSBmeF/DM67sUxzz7RhVCvBCnGREEQRAEQcRCop1IWjqO1MRE2KMJtdSjueItEu6EbQjxAnbV+vHR9qPYVetPKUFY46+NibBHUx9sRI2/Nj4TUqHmcGNMhD0af1MQuw8o/84QBGF/eJ5Hdd0+bDpcgeq6fbZZPCQIgmCBatqJpCUUaGQa17BhFZrL36QadyLhpHrtdGOw2dRxVtPU2sk0rqFFWdgTBGFvks1ngyAIIhqKtBNJi9OTxzyWatyJRNMXaqfzXDmmjrOa3OwMpnH53kz1QQRB2JJk89kgCIKQgkQ7kbRkDi+CM9un6TNU404kglAfqZ0uKhgLnytXcYzPlYeigrHxmZAKRSPy4MtRFuQFuS5MHK3td4YgCHuQbD4bBEEQcpBoJ5IWB+dEwbylmj4TaqlHx5Eai2ZkPQIfQvBwFQLVGxE8XNUnFyCSsSZ894H6PlE7zXEclkxbpDhmybSbLO/XzgrHOXDH9ZMUx9x+XUnC+7UnC1QzTNiNZPPZIAiCkINq2om4IPChHuO4QCOcnjxkDi+Cg3Ma3m7WhJkYuPDemD7tSrDWwtsN6kefvDXhrDXRqVA7PWPYVNwz+w6J+tE8LJl2k2n1oyFewO4D9Who6UC+NxMTR/t0ietZpUNw3+KymPuqINeF268rsfV9ZSeoZjg14XkeNf5aNAabkefKQVHBWNssurGQbD4bBEEQcpBoJyzHarGZNWEm3IVlaK54Cw0bVqmO11ILbxfEfvTRiLX6Axfem/LCXawJj0asCb9vcZltBRZrTXSq1E7PGDYVZUMmW/awb/bizazSIZhRMtiURYC+iFgzHI1YM3zP7DtIuCchqbAQk2w+GwRBEHIkz3IpkZSIYjM6Cm62MZyDcyKn7CrVGnen14fM4UWm7DNeUD/65K8Jnzja1+dqpzmOQ/GAQlwwogzFAwpNFexWGPo5OQcmjS3AxdOGYdLYAhLsjFDNcGqSKuZtyeazQRAEIQeJdsIy4i02WWrcC+YuNSUtP56w9qNP5lp9NZK9JtxJtdOmkOyLN6kI1QynHqm0EJNsPhsEQRBy0K8UYRmJEJtijXt0xN3p9SVtCjlrDX6y1uqzkAo14WLtdHTEvSDXZevUfjuR7Is3qQjVDKceqbYQI/psREfcfa48Kt0gCCJpoJp2wjISJTbFGncrjO8SAWsNfjLW6rOSKjXhVDttjFRYvEk1qGY49UjFhRirfTYIgiCshkQ7YRmJFJsOzgnXiBLTt5sIxH70SlkLyVirrwWxJlwpyposNeFi7TShnVRZvEklxJphpcgs1QwnF6m6ECP6bBAEQSQjtMRIWIYoNpVIdbFpBqlaq68FqgkngL5p6Gd3qGY49SDzNoIgCPtBf0UJyyCxaR6pWKuvFaoJJ2jxxp5QzXBqQQsxBEEQ9oPS4wlLEcVmTJ92rw8Fc83p095XSLVafT1QTTghLt5E92kvyHXh9utKaPEmQVDNcGohLsTE9mnPw5JpN9FCDEEQRJwh0U5YDolN80ilWn29UE04QYs39oRqhlMLWoghCIKwDyTaibhAYpMgCDOhxRuCsB5aiCEIgrAHJNqJPonAhyjybzNCvECRU4IgCMKW8DxPWQcEQSQMEu2EIZJF/IbPs6vhBFp3bIissc/2oWAe1dgnii2Vx2NqlH05mbjj+kkpX6NMixUEYJ0goPur70Ii0zzKj+6QqO/PxZJpi6i+nyCIuECindBN256tsQZzGsRvvAS/1DyjCbXW49Sry/uME7ud2FJ5HL9aXRHzen1zB361uiKlneFZFytIeKU2VgmCvrwY1tdRu6dI0LNTfnQHfr/5mZjX64NN+P3mZ6hDAkEQcUGzaG9qasJjjz2GDz/8EIFAAOPHj8c999yD6dOnAwA++eQTLF++HPv378fgwYPx3//937j66qt7P9/Z2Ylf//rXeOedd9DR0YHLLrsM999/P/Lz83vHmLENwlra9mzFqVeXx7zOKn61CH4j4l5unnL416+Eu7BMdfvJkmFgd0K8gGde36U45tk3qjCjZLBhkWo34cu6WEHCyxhS191OWCUIUnUxjMSmOmr31LUT5mLz4QpDi0R95TrwPI9V29cojlm1/WWUDZmcksdPEIR90Czaf/SjH+H06dN47LHH4PP58Pzzz2PZsmX417/+BUEQ8N3vfhe33norli9fjg8//BA/+clPkJ+fj/PPPx8A8POf/xzbtm3Dn/70J6Snp+PBBx/ED37wA/z9738HAOzfv9/wNghrEfgQ/O+tVByjJH61CH4j0XyWecbMoaUeHUdqFE3zjGYYEGfZfaA+QoxK4W8KYveBekOmY3YTvqyLFbwg4DfPbYt5L9mFV7yQu+6LryyE1wbP11YJgnguhsUTSlFWh+WeWrtnfcxrWhaJ+tJ1qPHXRhynFPXBRtT4a8mwjyAIS9H02HL48GFs3rwZP//5zzF9+nSMGjUKP/vZzzBgwAC8+eabWL16NcaPH4+7774bY8aMwbJlyzB//nysWLECAHDq1Cm8/vrreOCBBzB9+nSUlpbiscceQ0VFBXbs2AEApmyDsJaOIzWKqebAWfEbDavgF/hQr7iP3pco7tv2bDU8T8m5Bxpl32Odk8CHEDxchUD1RgQPV0HgQ5rnEbF9XsCuWj8+2n4Uu2r9CPGCoe3ZhYYWZcGudZwUYsQxenFAFL5bKo/r3rZeWBcrnnq1UnHMs29Upcy9YDZK1/2xf1Zi95FggmZ2Fi2CQAtaFsOSBTF6HH2+RLFZfpT+/gNs95QSq7a/DJ7nZd9PhuvA8zyq6/Zh0+EKVNftUzweNRqDzaaOIwiC0IumSHteXh6eeeYZTJo0qfc1h8MBh8OBlpYWbNu2DXPmzIn4zMyZM/HII49AEAR89tlnva+JjBo1CgMHDkRFRQWmTp1qyjYIa1EStWrjWAV/8HC1oWi+lnlG4/TkSb7OvOAg8Khfv8q0SLzdosRmku/NNHVcNHaNOLIuQrS0dSm+b0YWQirCct3f+awJN8xJ7IKHVYIgHoth8YRSlNkxKh6VosbJcB3MzgLIc+WYOo4gCEIvmkS71+vFxRdfHPHau+++i8OHD+OnP/0p/vWvf2HQoEER7w8YMADBYBCNjY04deoU8vLykJGRETPm5MmTAICTJ08a3oYeBEFAe3u77s/Hg2AwGPH/iaK7n5t5XPQ5DdafYvpsa+1OJnHf9MVOZAwvMjTPcDhPPnjfSMl7oZNxwaHutd/Hvv5VJD53wQ+QOa6MeT7l1afw2D9jo61ilPhH3yjFjOKBzNuzGq336KhBLuR7M9DQ0ik7xpeTgVGDXLq+n9UHG5gijttrjqF4VPw8MdwZ6mNYOelvxpgh2u/1VIblure0h7Bz30lMmzA4TrOKxeVguxFcjgxN9z/r/eXOgO3/7gHsGQk7jlahqGBsfCZlMXr/3rPeU0qcaq7DKM+wmNftfh22najEE9tWS8ypJwvgrumLMX1wqaZtjsgagrzMHDR2yC+G5GfmYkTWkKT4LpmNXZ5LCUKOZLhHBUGAw6EeODLkHr99+3bcd999mDdvHi655BJ0dHQgPT09Yoz4766uLgSDwZj3ASAjIwOdnT0P7WZsQw/d3d2oqYlN57Yjhw4dSuwEBB45GdlwdLZC6hYTAAiZXhxo5YGoc9qvvhnZDLvw+/1wMYw7sq8a3QF984yeMwC0jL0E9Xv3So5JO14ND8OcBED2vDRsWIXmbjfgUI9C8LyAFWuVF6JWrK2GB/XgbFaXquUenTPZgzUb5b+7l5d6sHfvHl3zqD7E9hBVvecguA62BSVT4AV43U60tMuXTbgzOLR3qqd1NjecRE1Nk4mTS35Yr3vtweNwCU3WTkYBXuCR7cxCa6hNdkx2vyzwdZ2oOa3h7xPD/eV1O4H2k6ipieN9r5PdrfvZxh3YA5zutng28UXr33uWe0qN5pONqGmJvd/sfB14gcfqQ68ojlm98xW4Gp3gGP7+hnNx7nS8fvJ92fcvyj0Xe/dIPzf0FRL+XEoQKtj9HpXSttHoFu0bNmzAj3/8Y0ybNg2/+93vAPQI566uyHRO8d8ulwuZmZkx7wM9bvAul8u0beghLS0NY8fae4U+GAzi0KFDGDlypKFjNYOOtFvRtO6Pku85AOTNWYIh44pj3hP48Thd8zb4QIPstjlPPgZPvRBNBzarzmN4YbFspF1tnuE4PfnwXnIzBitEwTs9QGPlG6rbkpPPDgCOjhaMzuYU5yxSfbABLe3HFMe0tIcA9yAUxTFKrISee7SoCBg29BRWvbU3IuLuy8nA4ivHG8ok4DMb8OoW+XtNpHjCqLifw9vgk8yiELnjumI8984+1SyE+RdNsd2iTaJhve5jRw1BUQIj7QCwOO9rktHB3venfA3Fg2N/S9VQu79uu7YYxTbK0lHEn4Y3T32gOmzi6AkpFWnX+/de7Z5SIj8zF3OnXSotbG18HWr8tWjdr7xQ0XqmDdyADM1zK0IRhp0YhheqXo+IuOdn5uJbJddpjt6nEnZ6LiUIKZLhHq2tZfOt0SXa//73v+ORRx7B/Pnz8Zvf/KZ3dWDw4MGoq6uLGFtXVwe3243s7GwMGjQITU1N6OrqilhRqKurw8CBA03bhh4cDgfc7uRIMXW5XAmfq3vyxcjIyIh1Uff6UDBXpXb7imWKbdj6X7EM7sJpaM32KaajO70+5I6bothqzT35YqSnp8H/zrPg21t6X+ey85EzdS7S8gczt2xzjZuCFpU5sZB2pp3p+rV3qouOnnFI+P0QjdZ79NKyUbjo3JGmt2SbVuSCL6daMVW6INeFaUVD4+6ifWnZKKSlp+OpVysjatcLcl24/boSzCodApcrU7Jtl8gd15fC48mKx3STCpbr7nU7MaVwUMK/OxeNmYmMjAyJOtw8LJl2k2437kvLRiEjIyPGDyP8/rILau3Dpg4rgc+Vq5ia7XPlYeqwkpSradfz917pnpo9Yrqke7zIrecugidLOqfMztchKLBlWgaFTl3f+YvGzMQFo87rE23u9GCH51KCUMLO9yhLajygQ7S/+OKL+OUvf4nvfOc7uP/++yN2NH36dHz66acR47du3Ypp06aB4zice+654Hken332WW/7toMHD+LUqVMoKyszbRtEfMiaMBPuwjLN/cqzJszEwIX3qgr+gnlLFcV9wdylqvtq27MV9etXRQp2lxcFc2+Fp2gWy2H24uCcqnNiQc7oLhqrTdrshpNzmG6o5uQcuOP6SYrC9/brShLS9mpL5XGseKMqQrB7s9Kw7JriXkE1q3QI7ltclhTCy06wXPf55+baJkNhxrCpKBsy2XRBMKt0CGaUDDZ9McxMWIzDOI7DkmmLJHuPiyyZdhMJqDCU7qlxvlG6FonsfB3iYRjHcRy1dSMIImE4BEFgts89ePAgrrnmGlxyySV48MEHI97LzMzEyZMnccMNN2DJkiW44YYb8NFHH+H3v/89VqxY0Suw77nnHuzcuROPPvooXC4XHnzwQXg8Hjz//PMAgC+++MLwNrSya1ePy3C4K74daW9vR01NDYqKimy7WqQFgQ+pCn7Jnugs0XzI94MXybvo68idvVBV+EttV2pOvjlLYlzjo3F6fTjn+08x7TPEC1j28HuqUeIV98+1zUO4kXs0xAuWiQspB/5ECl+xHZkc0f3XrTw3qYzcdb9l/jh4uYaU+S1NVsT2YXJE9wyXFvjGMhLsitV/79WyG5Sw43XgeR7fX3e/ahbAkwseNryoYOTcpRqp9lxKpB7JcI+y6lBNov0vf/kLHn/8ccn3brjhBvz617/Gxx9/jOXLl+PQoUMYNmwY/vu//xtXXXVV77j29nY8+uijePfddwEAF110ER544AHk5Z2NPpqxDS2QaLc3LOI+ekzG0PE48ufvq6ay623FJjcntYWCgQvv1bQvreIu0ei9R6XElcedhmsvHINFcwpNEah2Eb4sizG+nEz88JvT0NzaSSLdIFLXvbMj2Cd/S+2EXpFlN8Fk1Xzs/vfebtcB0L4IFA3LMZndUi7Zsft9ShDJcI9aItpTFRLt2mER0lZ8VgqpyDfn9kakxKuhVUxrnQ9rdoAUdosSK6HnHlVbmPC40/DfN02x1bEaWQDYVevHT59SN1kMx5eTiTuun8R8DuyyQGFX7PRb2leprtuHhz6QDgKE8+Cld9s2JdlKAcdyj9pROEcT7znqzQJguZZGFwVSEfotJexOMtyjrDrUUMs3om8iKUoZI9ZGPiu3PanIthbBDgD+9SvhLiwztHggorfWX45kqEvVS4gX8MzruxTHBNq78avVFbbJKpBaRNEiqhtalPuHS1Hf3MF8DozOjyDiQWNQvu+1nnHxRk7AiT3BrRZwyRDxTcQc9fhDsFzLsiGTsWr7GsV9r9r+MsqGTLbdwglBEKkB/bIQmhBFcnTaeai1HqdeXY62PVst+awUAh+C/72Vmj4jR6ilHh1HNPRBVsHBOeEaUQJP8YVwjSgxvBggmrRdPG0YJo0tSAnBDgC7D9QrpomH8+wbVQjxiU0MErMCoucsiuotlcdVt2HEOFDtHJgxP4KIB/EwDrMKnueZBBzP85bsXxSZ0aUFosgsP7rDkv1qIZFzFA3jLhhRhuIBhYoimvVaVtftUyzlAID6YCNq/GytmwiCILRCop1ghkUk+9evhMCHTP2sHB1Hagy3XwsnFGg0bVsEG1qizv6mIHYfMO96a4UlK4BlYWHiaB98OfqEu9I5MGt+BBEPigrGwufKVRzjc+XZsu96jb82YQIu0QsGLCTDHEVYr2X16X1M27NrZghBEMkPiXaCGRaRLBexNvLZaAQ+hODhKrTt+UR1rBZYW7ER5qE16qwntdwsWLIC/E1B/OPdPdhV65cVx2I7Mr3InQPW+SVy4YMgRMT2YUrYtY2blan9PM+jum4fth7bji/bj4MXIoVtIhcMWEmGOYowXyPGtU47ZoYQBJEaUE07wQxrJFpqnJHPhiNVE28GnNuLzOFFpm6TUEeMOrOmyCeyJz3rgsFLG/bhpQ37FOvI5fqvsyB3Dljnl8iFD4IIZ8awqbhn9h22ax+mhlWp/VI14O80bMbSc7/eey6SwQsgGeYownqNigcW4qNDn6h2O7BjZghBEKkBiXaCGdZItNQ4I58VUWunJrm9bB8EQQAfaFAcVzD/dlNM6AhtiFFnJfd4kYJcFyaO9sVhVtJoXTBQM4+LNhjM9WTg8X9uVxTxSueAdX6JXPiIhlzuCT3GYWpY7VgupvabKeDkzNAaO5ojjO2SwQsgGeYownoti/sXYsm0RYru8XbNDCEIIjUg0U4wkzm8CM5sn2KU2+n1SUasjXwW0G86VzBvKQAoiv2cmdfBUzRL87YJcxCjzk+8vBOt7d2y426/riShgk5rVoDIs29UYUbJYMm5iwaDImoLGErngGV+iV74CIdc7gkR0TjMDOLhWC6m9psl4FhrwMuGTLZkwcBskmGOIlquZbJmhhAEkRrQkiDBjINzwlN8geIYz8QLJCPWDs7ZK6DlKJi7VDbardV0zun19fZez5owEwMX3gtndqRY4dxeDLjxHvguv4V5u4Q1zCodgucfuhLfumI8PK60iPcKcl22aPemtxZdSx25uIARbVTHcg5Y5pfohQ8RcrknrCCejuWigIs20/O58jS3e9NSA54MXgDJMMdwtFzLGcOm4skFj+DBS+/GD2YuxYOX3o0nFzxMgp0gCMuhSHsSwQs8vmw/juZjQQzMGWB6yp8aAh9CoHqT4pjA7k3Iv/TbkuJbFM8xfdq9PhTM7enTLvAhyf7mrDXx3unzkTXh/Ji+6Gb3TifMx8k58M15E7BoznjTUqbNTr/WW4uupY48Om1ey7zl5leQ68Lt15UkfOEDYHe5l8tOIAgptESrzfq7aVZqv9Ya8GSI+CbDHMPRci3NzAwhCIJghUR7klB+dAdWfvYSGjuaga+CUGan/KmhxQHeNaJE8n0l8SxlMufM9qFg3lLmmvisCefL7lvsnU7Ym+iUcb1YlX4dLqp3fnEaazaotwLSWkdu5BwYEf3xQIvLvRn3AdE30BKtNlNwmSHg9NSAW+EFYDbJMMdwSIwTBGFnSLQnAXIGNWLKn9ZUPL3odYCXip5Hi2c5k7lQaz1Ovboc/W+4G5zbC769RXa/SjXxiUYug6CvES/jMTH9Oho1czjW+YqieuJoH96v+NJ2deRmLXxYgRku92Rg13eRM5lLJsdyEfFY6tsb4c3woKUzIDtWqgY8GURmMsyRIAgiGSDRbnMSkfInhx4HeKXoedaEmQDYTOZOv/5/QFS/2miUauITCcs56AvEy3jMrPRrlvmyuN/bpY7cLhh1uScDu76LkslcMjmWA9LHooSdasAJgiCI+EN/AWyOlpQ/qxEd4JUIj3aL0fPolHoxet62ZysARpM5BcEuGsrZUQCznoNUJ57GY1rSr+XQMl8587gcTzr+55bpJCSjEF3ulZDLTiADu76LmslcS2drjJFYNHZxLJc7FinyM3Pjlk2XavA8j+q6fdh0uALVdfvA88oL/wRBEHaGIu02p6G9ydRxRhAd4JXap4nRbpbouX/9SrgLy5jT7uXg21tQv34VHA7OVsJdyzmwY4aAWeiNfOtNgTaafq1nvrNKh4DnBTz12udoaetpW9cc6MKKN6rAORwk3MPQm51ABnZ9F5aMs+d2vIrFU27CY588KzvGDtFqlmPxpnvwjeJr0XqqCXOnXQpPlidOs0sd4tH6jyAIIp5QpN3mtHS2mjrOKHLt0xwuD/Iu+jrchWUAtJnWsabdK25LZ+Ra4EMIHq5CoHojgoerIPAhw3MR0XIOrCLEC9hV68dH249iV60fIV6wbF9y6Il8b6k8jmUPv4efPrUZv3vhM/z0qc1Y9vB7qpHUEC+gqbWTaV5y6dd65/ub57f1CnYRigBL34N6WtuZkUFBJCesGWfZmR7T2rDJYTR6y3IsLV0B5GXm4Bz3EHAOekzTSjxb/xGECGV2EFZDkXabk53BtsLOOs4MRAf4xs2vouXTf4PvCEAIBtD48Uto2bEBBfOWQgh1q28IQNueT8C5vKbN7fRbTzFHrq2uNddr3GcWdqn9ZY18+5uD2FXrx9aqE1i78UDM+2omclLHK4eSOZzWSL2RCHCqG6qp3YNaXO7NMLAjkhMtJnMXjCizzLHcjOgt67E0d7YgBy4900xq5IwGtXzeLj5ARN+BMjuIeECi3ebkZTKa6zCOM4v2fRVo+vilmNfFiHfeRV9n2k7LtndMnRcfDKBx86vIv3CR4jg1t/qBC+81LNz1GPeZhVnu6WbAajy24o1dMZFqKaQEsNzxyqFkDqfVKE1vCzO7LKpYBes9yOpyb9TAjkhetJrMWeFYblYXF9ZjORnwIwfDNc8zmTFD+CSq9R/Rd7FLhyci9aFlRrvDGnSLY3BO4EM4/dZTimOaPv23qmmdVbRU/BvtBysjUt7D0+DbD1bi9Lt/VdyGf/1Kw6nyWo37zII18quWKm9Waj2L8RgAJsEOxKZAsxyviFL6tYhWozQ9EeBUN1Qz6x4Mx4iBHSFPMqR0FhWMTajJHGv0luXcFRWMRT7DIvvHX5aDV+mYkkqYldKejK3/okmG7yTRg5m/DQShBkXabU5TUL4vuZ5xZtC46RXwQfl+sgAgdASQXXYVmjYq/5hZAR8M4OSLD/X+m8v0AA6ozjkcsdY8up+8FrQY95mJ3shvOGZGgVmMx7QSLoBZjhcAbru2BAsuHK2afq7VKE1rBLgvGKqZcQ9GQ+31zCdZUjo5jsOSaYsko1kiVprMmRm95TgOc8ZeiDVV6xTHNXQ04WjwJIpRrHW6SYeZKe3J1vovmmT5ThI9UGYHEU8o0m5z7GZE17ZnK7sQ53lJ0zo9cG79de98R0CTYBcxo9ZczrjP6fWZkoIvhdHaXyuiwEpt0fQQLpRZjzc3O8MSQac1AtwXDNWo/tz+JJtZ14xhUy03mZPD7OjtIM8ApnGBUJBpXLJjZmvbRGdlGCHZvpNEamR2EMkDRdptTla629RxRmBpYRb1iV7Tuo4jNWjb84muGnan14fhdz6JzmN70bztbbTHqbe5WbXm4ecgFGiE05OHzOFFlrV5M1L7a2UUWMp4zN8UxGP/2K5pO9Ep0GbXOms9B1ojwH1B0FpRf94XMhTiRbKadc0YNtUykzklzI7eso7zOPuGEZ2ZwifRWRl60fqdNGrYR5hDsmd2EMkFiXab09bVbuo4I7C0MAsn86vUcgfn7E0z1yPaC+YuBdcvDa4RJcgcXoTDf1iqK3KuBbNrzcPPgdWIkV+laK5c7a8Vac3hODlHxOd21fo1byM6BdrI8Uqh5xyImQTRJQUFuS7cfl1JRElBXzBUM/uaANbfm32JZE7ptMJkTg0xeqt0zrREb1m2l5+Zi2GuQRpnmpyYLXzErIzYNPM8LJl2ky3TzLV8JwNdbZRCbxPM/m0gCCVItNscb0a2qeOMoCVd3JHuQijQiODhqt6osmjMpkX4A4AQZsbj4Jzof9WdinXiZlAwdykAIHi4Ki7RcTMxUvtrRhSY5wVUH2xAe2eDahsvFnEnIiWAgZ7jvXjqULz24X7Zz140ZQicnIOpxZrec8DawswKQWsU8bz4m4NoCXTBm5XeOwc9UWsr6s/7QoZCvOjLKZ16IpRGo7fh+8zJzAYEYMbwaXhr339kt/etkuvANfWNyKkVwkdrVkaiI9es37WKY59L3jfkVJ4YkjWzg0hOSLTbnHx3rqnjjKAlXVzoCuL02j/2fO6r3ucAIHR3at5v3b8eBwB4imYBOFsnHt1j3QycXl+vYP/yiTst6+FuFnIiVCnyu+zaYmS70/HR9qMxwtJoFLi8+hRWrD2JlvZjva8pGdixiLtrLxyNmSWDZQVkiBfw0Y5jEp88y8c7j2Pc8DysWFulaq5n5BxEZxJIYTdDNaX+9kZa0GnJPmChL2QoxIu+mtJpxORLb/RWap/hcHCAx9kuCuL2JuWPR01TDfOxJTNWCR/WrAw7mL+xftc2HSpXfN/MspZEL2TYdS7RJGNmB5GcOARB0NfHKYXYtaunTnLSpEkJnkksPM/j++vuV12BfnLBw5b/gAl8KEbIxpNo4zaBD/XWiXPuHNSt/RP4QIO2jTocyL3ga0j3De2Nprfvq1CM5FtlIKcVFof3aFHfHOhUFK4hXsCyh99TjQKvuH9ujKhU65Wu1GpN6lhYxd2uWj9++tRmxTFqhM/NyDnQgpFjNgvW/vZqbfKUYMluYN2OWdelvb0dNTU1KCoqgtttvR+I3bDT35V4IddLWYQ1QqlFPKjtM5yrCi9D2dDJvdvri/eotHi2VviYdV8YheU76c3woKVTvTTwwUvvNlxCwrqQEY/71A6LKizYeWGhL5MMv6WsOpQi7TbHTqk3LC3MrMS/fiXchWW9KerRdeL9r1imfW6CgKaNL2PgwnvhGlHCZLYXPY9EICe2RId3UWSFR363VB7Hb57fpvoZPVFgoyZhrKnlUpiRDm3EWE4veo7ZLAEsbou1v70RgzeW7APW7dgpQyGZsdPflXhgpvEea/SWZZ/hlB/ZgVsmL7TtOY+HIIm30aCdDBlZvpMXjDhPsaRCxGhZi9xCRiJS8O00FzUS4bdB9C3s+deBiEBMvcnLjEyfikerm2iyJsxEzszrAEf0rWP9g7LYO10Od2FZT092HfjXrzwbuVfJJFCbh9WwCuQQfzaJRstn5NqzFeS6ZCOuZrQxE8XdxdOGYdLYAmbxZUY6dPTc9JwDPWg55i2Vx7Hs4ffw06c243cvfIafPrUZyx5+T1cLPoC9vz1gnxZ08boufYFEtlCLN2a2FDNzn1bu30zKj+7A99fdj4c+eBx/3LoSD33wOL6/7n5LWpCJwueCEWUoHlAYI5Z5nkd13T5sOlyB6rp94HleZkvqJOK+UELtO1k2dDLTdoyUtbAuZBg578k4F4KwAxRpTxJmDJuK4rxxWL/9A+QMysPAnAFMK9DhKeRmmKm17dmK5q1vSO1J9za1oGSG13GkBnyHPld5UYizmu2Z0cNdL3pctLV+RmsUOJEmYVrM7JTQaywXD1gzK7Sg9VrYxeDNTtfFDhiJgCaqhVq8SYTxnp5tGd2/FdFwO0U6zU6TtqMho9J3kud5y53K7dRZwk5zIQg7QKI9ieAcHM5xD0HRULa6jLY9W2PM2oyYqWnv024+XaePRjjSh2NUSIsLGyyY1cNdD3oEsp7PaElrjpdJmFx6uJp7vN65mZXabQSr+pNrvRZ2Mnizw3WxA2aImL6Q0pkI4z092zKyfzMFrSj+69sb8dzOVxTHxit93IrFA7saMsp9J+NR1mKnhQw7zYUg7ACJ9hSlbc9WyfruUGs9Tr26XJeZmtY+7VrgMj3gO9sAFV/Eps2voGnzK5KLD0aFtJiJoNaWzuwe7lrRI5CtFtXxaGMmZ7ynJtivv3gMNu48ZqsWa1qwqj95c4C9kwPnAMaPzGceT1iPnSKgdicRvZRZ9mnW/s28F9Tc7mP3YX2k06ra82TssW21U7mdFjLsNBeCsAOplQNHAGCLiIs13FqwMiW8/9V3YsANP2Kfy1eLD217tva+JgpuPYhCXDTbU6Jg7tKEmtCJAlmJaBGq5zNaEE3ClDBiEiamh0eL1/rmDtUI+6bPj+O260oUx9jZwMyK0oMQL2DF2irm8bwA7D2ksTMDYRlU66kNMUKphNnGeyz7NGP/Zt4LovjXUosPWB/ptKr2PBH3hRnMGDYVTy54BA9eejd+MHMpHrz0bjy54GFTFunEhQwl4rWQYae5EIQdsNcvEWEKVpmpWZES7nB5eqP+nqJZGLjwXk3CO3zxgUVwyxEuxMU+8NHzcHp9tmj3pkcgWy2qgZ5a4x99oxRed+SChpxJWIgXsKvWj4+2H8WuWn+EcV70OFaXcyn8TUHkZGUkrYGZFVkSWkzoROxS007Yz0ArGUiE8Z7cPs3cv1n3gla3+3CsjnRamSadrIaMaoZ9RrZrl4UMO82FIOwApcenIFaZqbGkjmtl4A33wD2qtPffWRNmwl1Yho4jNQgerETT5lcVPy8uPoit30TBHV3LL4fT60PB3Nga//B5sJj4mW34p4booq2lz7eez2hlRvFAeFAPuAehvROyJmEsPeZF9AjMaBpaOnDxtGGYPnEQ3t58ECfq2zDYl4UrZ49Cej97/8G3ovRAjwC3U017X4dqPfWRCOO96H3mZGYDAtDc2WrK/s26F7S63YvEI9JpdZp0XzFkZMXqFPxknQuhHepdby4k2lMQ1oj4mUATBD7ELC7N7tPu9PrgGlEsuR/XiBLdiw+i4G7a/CoaP35J9nN5F30dubMXyh5/dB94Ocw2/GNFj4t2PJy3Oc6BolH5smaJWp3QzYjw5nszJRcK/vVRreRCgZ3Q259cqae7VgEutShgZs94QhtU66kfPcZ7Rh88rTT7M+te0LvAE49IZzxqz/uCIaMW7LSQYae5EOyY3e2BINGekrBGxBs2rELT5tdQcOXt8BTNYtq2XCTb6fXBN2cJ6tevYo7Eq9WGG3Vyb9mxQfFzLTs3IHf2QqZ9yGGF4Z8W9LhoJ9J5W48TutEIb0GuC81tnfjNc9ti3jPSMk0rRkSu1iyJTTuP4anXPkdLW3fva+GZDFrb5EUvCmjJlCDMJxkNtOyAHvFtlwdPubmz3AscHGhVaYeqdYHH58rF5WMuQHfoDKrr9lkqouLhmk7EYqeFDDvNhVCHjFKtgUR7CuLgnPDNXYK6136vOpYPtqDutd+jc2YtfJffwrR9pdRxh4MzLRJvxMldS10/SzRdClbDP3dhWUKN64xgdjRVjxO60T7sy64pxoo3lE3X9LRM04IZIpc1S+Jvb1ZJmvNFL1CoRe8B6UUBK3rGE9rQKmLslhWRiJRJPeLbLg+eanNXuxd4CHjsk2dxDyc/X61u912hbqypWic5HyugNGnzodRlwgqs6vZAkGhPSdr2bEX9+lWaPtO89Q1kDBnLHHGXSx0XI/F16/4MobNNcRun33oKrrHnovPYXslacJZ0fM/ECyQFsVV1/eHEY2EgkZghNKPFgr8pyPS56H7xagLzxkvG4KMdxySj0NnudEtaprFipshVy5LY9PkxVTd9cYFCLnrvzUrHJdOGYWbJ4BhxZ1XPeEI7rCLGblkRiYhc6xHfdnnw3HaiEk9sWx3zevTc7551G/5vy1/BQ75tqtJ8WRaCwmntivz7bvZChpSgpDRp87BLBgmRemgxx6TsCW2QaE8x5NK1WfC/8yyyxs8wHBV2F5YBDvU/onwwgEOPLQG6wwRaVC141oSZyJl5HZq3viG5jeatbyBzaGFMCrrR1HoW4rEwkCjMEJpSYsGblc60//CU+BAvINudjmsvHI0Ptx+JSPkOjwTfcnWxZDTxg8+OMO3T38y2oBCNUhQzniI3xAt46tVK1XHhCxRaPQ6s6hlP6ENNxNgtKyIRkWu94jtRD56iWD3VXIfG9ga8e2Sz4nhx7t6MbEXBzjLfGcOmYlHJgogIulbMWMhQEpRlQybr3i7Rg10ySIjUhIxSrYNEewrBkq6tBN/eYkpUuONIDYSOVrbB3ZECILoWXOBDCFRvUtyEVAq6kdR6VuKxMJAIzBCa5dWn8Ng/YwVkS1uX6v7DTc/khL9UJFguCt0SUN+nlnHhqEUx4ylydx+oZzq/QGwmA+u+regZTxhDrtbTblkRiYpc6xXfiXjwlBKraohzN2u+NxZdiQ21G9HQoe+4jC5kqAlKT3oWAmFRfooOa8MuGSRE6kJGqdZB38gUgiVdWw0zosJmbEPsv6635zxLz3Y1Izw1xIUBJYwuDCQCLUJTCp4XsOqtvbr3L5qeiVHC6Lm0tHVh7cYDaG3vYhIbrNF91nEicvMTo5ibPj+Gz784zbQtM0Sulm3oNfezomc8YQ48z6O6bh82Ha5Add0+VO0/beh7bDaJ6i2vV8zG+8FTFKt62q6JWRYsqI3jOA63nvt1zXOIno8eWARlQCYtv/zoDl377Gsk6ntI9B1EfwwlyChVHxRpTyHMEMtmRIU5t/GHGFGIa01Bj+6XPuDGe2Ic7eV6s2uFpebe6MKAEfSaTxmNph4+3YmGlk7Vz3uz0mRT3c2MEhbkulTnomUcwBbFXP78NvDK2aq9mCFyWbfhzUrX1NM9HCt6xhPGkYrQZvXLBpc3BnzjIMXPxisrIlEpk3rFbDwd+lnEqhJiWYRZ8xX9Ep6u+DsCXe265qMHvb3igeSJDifa/I1SlwmroW4P1mFItD/99NPYtGkTnn/++d7XHnjgAbz88ssR44YOHYr//Oc/AHp+sJ544gm8/PLLaG1tRVlZGf73f/8Xw4cP7x1fU1ODRx55BFVVVcjPz8eSJUtwyy1nnc1ZttEXMSq47RYVFoU3C05Pnmy/dN/cJXC6vZJmd0ZRaoFnxsKAXoyYTxmNpgaCPNPnb7tuEgpyXJKLCmamlVshNFnmxyrYzRK5E0f7kO1OQ2t7t+K4q2aP1L0PvT3jCeuQSyduO9OK9LE70VU7RVG4xysrIlEpk3rFLMuD5+VjZmPLkc8Miy8jYlWcuxUPynoEu5GFDCNCMRmMrexg/kapy0Q8oG4P1qBbtL/wwgv4wx/+gOnTp0e8vnfvXvzXf/0Xbr755t7XnM6zAunPf/4zXnzxRfz617/GoEGDsHz5ctx222148803kZ6ejsbGRtx666247LLL8NBDD2Hnzp146KGHkJWVhYULFzJto6/C2p9dDrOiwny7OSu0osBmqU0PtbdItrgLtdaj7rXfY+DCe+EpvtCUeUWj1AIvERg1nzIqcj0utofCghyXrOA2s3baCqFpZnTSTJHLsk7wz/f2YX35l7rdw7X2jCesQy1C6wCQds4edDYO/OpfkcQzKyJRveWNiFm5B09PehYAmNbyzIhYDZ+7WQ/KRiL/RiJoRoWinaPDdjF/S9T3kOh7ULcH89Es2k+dOoUHH3wQ5eXlGDlyZMR7giCgtrYWd9xxB/r37x/z2a6uLqxcuRI//vGPcckllwAAHn/8cVx44YV47733sGDBAqxZswZpaWn4xS9+gX79+mHMmDE4fPgwnnnmGSxcuJBpG30VlnRt74xrEdj1Ifj2lt7XWKPC0anncsLUlBT77HwIPI+2mi3InjoHTR+/JDvWN2eJaos7q/uly7XAizdmpJUbFbkj+mcg35uhmCKf7U5DSBAQ4gXJ7ZhdO2220DQjOqll3yylDrsP1COgEmUXMeoertV1nrAG1QitA+AyOsBlN4BvjRXn8cyKSGTKpBExG/3geTJQJ+mubkR86RGrcnM340FZT+TfjAia1l7x0eRkZuvet5XYyfyNUpeJeCJnlEroQ7Nor66uRlpaGtauXYsnn3wSx44d633vyy+/RHt7O0aPHi352T179qCtrQ3nn39+72terxcTJ05ERUUFFixYgG3btuG8885Dv35npzZz5kw8/fTT8Pv9OH78uOo2+jIs6dq+y27WHBWWSz0Pb88mkjF0fE/LN4EtTVqSM104+eJDvf/kMj2Ao6dNXPQxcS5PSvdL14JZaeVGRC7HObDkqvGS7vEire3d+Nlftsim7FuR0m6m0GSZnxKL5hTiW1dMYNo3a6mDnui/EfdwLa7zhDWwRhazcwQ0hzX0SFRWRCJTJo2IWfHBk+d5fH/d/Ypj9YivooKxMa7o0fhcefjejFvQ3NGqOnejD8qs99WNRVdiWM5g0yJoWnvFR/Nk+WrcakMnebv1rabUZYJITjSL9ssuuwyXXXaZ5Hv79u0DADz//PP4+OOPwXEcLrroItx9993Izs7GyZMnAQCDBw+O+NyAAQN63zt58iQKCwtj3geAEydOMG1DD4IgoL1de/1WPGlrb8OX7cdx+mAz+mcXYLxvNDiJfuiOc0pRsPQxdB3bC76tCVxWLtKHjgcANO79DKFAA/j2VnDubDj7dYJvD8Kh8Me244sKNK37Y8zrYnu23AU/QOa4st7XO4/U6BfsaZlAd0eEOAcAvqPn31kzb0S/vEHgsnKRNngcuk58gY5dyi3hRNrrT0HoL72glArwvIBtu4+pDwRw0t+MMUPcimOmjM3FEz+6ADWHG9HU2onc7AwUjcgDxzlkvyvBYE+v89LRXvzoG6VY9dZexYi7GPH90TdKMaN4YMR7i68sVBT+t8wfh84O7b3Vxwxx9x67ns+zzk+JCedkM+1brnWe1HnLTGMsog/D3xTE9ppjKB6Vr/mz4fC8IHmfJAKWuYj3qfj/yYrLkcE07oc3TocQ8DF/j61kUv54LL/8fuytP4DmzhbkZHgxLn8kvmg4hP98sQk5GV7Zv21mMMozDKM8wwAAHR3SC128wEfMT5wPq/jacbRKU3rxthOVioIdAL5ZfC3GZJ8DfBVMlpu7GbDeV+NyR/Yep1nzmZQ/HndNX4wXql5HY1jbOU+aG4Fu5fu14atsh7umL8b0waWmzMcMTjXXMY8T702rkfoeive5lt8Fs35L5b5zBGGUZPh7LwgCHA71ZyZT3eP37dsHjuMwYMAA/OUvf8GXX36J3/72t/jiiy+wevXq3hMWXXeekZGB5uaeH+eOjg7J9wGgs7OTaRt66O7uRk1NjfrABLE3cBDvn96K1lAbcLzntWxnFi7vPxPjPaMUPpkLBIC0j96Au2Y9uM7Y/ul8Rjbai+aie9CE2I8LPHLefwYOSFVE9tTQNmxYheauTPRrPAZHZwDOgB/sPtxnt9MxejYyjlXCgQ7ZfbXu3IDmi7+HtNo9cL/5J8njkeOovxlnbHyNjbD7SBDvfNaElvYQ0/jmhpOoqWliGssByE8D0AHs3XuK6TOHDh2ClwPuuqoAB+s68MqmBgS75EXlirXV8KA+Qlx5OWDRhb6Y4/K6nZh/bi68XANqahqY5hMNzws4fLoTgSAPj4vDiP4ZmkWm3PwcDkBQ0M9etxNoP4maGuVzyfMCVqxVXogUz9ueYx14Z5u+7hHVew6C62C7ruFzE89ffesZfFYbQGuYAaF4jSYO1/pLYAyp74HSXA4dOhTH2ZkPL/DIdmb1/F2QIbtfFoTTXeAcpzR/j60mBy7sad2LP5b/DUH+rOjzON24vGAm3M5MBEJBeJwuDHMNistDfMTf2q8Q/9aGGBejdx/YA5xmK1XhBR6rD72iOCaTy4Cr0Ymapvj8/WK9r/i6TtScNn9OWUjDbUMX4mjwZMT1/6LtMDbUfYIArywqV+98Ba5Gp21EX3M7229z88lG1LTE/xklBy4A3dh7Wn+rViO/pUrfOeXnW4Jgx+5/71k82UwV7XfeeSe+9a1vIS+vp6a5sLAQ/fv3x6JFi7Br1y5kZvbUgXZ1dfX+N9Ajxl2ungeqzMxMdHV1RWy3s7MnUud2u5m2oYe0tDSMHWtP441tJyrxeu37Ma+3htrw+sn3VVeVO76oQNPO12Tf5zpb4dn5WkzEHABat/4LbWfkV9AdABwdLcj76M9AZ0B2nBq5V9+FM/XH0XZAXoSL+xrWsg9tCscjBefJx9hZ8xQzCpKV8upTWLORPeLry8nA/IumWBIJDQaDOHToEEaOHHn2++huQPA/yuULLe0hwD0IRVER36Ii4IY55kZxy6tPxWQA5HszsOSq8ZhRPFBT1Fhqfi2BLvxhjbyvwG3XFqP4q+i40r6qDzagpV05c6KlPYSaugy8vJEtw0KK4gmjYs67ElLnT2peazbWS2ZQWIXc90BqLpL3aZKyOO9reGLbavn3p3wNxYOL4zgjdl7a/SbePvVhzOuBUDveOPWfiNfyMnPw7ZLrLY2gqv2tvb7wCoBhvWPi6AnMkfYafy1a9ytH2Tv4TnADMpi3aUbU0or7Suu8ilEc8+/C0+Pw261/UdxP65k2TefLasYL4/FOw+aIzIFo8jNzMXfapbZZaGDF6G+p0edbglAjGf7e19bWMo0zVbRzHNcr2EXGjRsHoCftXUxpr6urwznnnNM7pq6uDuPH96RvDxo0CHV1kalE4r8HDhyIM2fOqG5DDw6HA263crpwIuB5Hv+ofkNxzD+q1+KCUedJ1pMJfAinP3qBaV+tH7+AvEkX9Na3C3wIdTveY5uoAcEOAKg/gratyscpEmSdUxj9r1iGLI9H8+fsTogXsPrtfZo+c8f1pfB4siyaUQ8ul6v3+9TeyRYNb+9E72eijdemFQ01xTBrS+VxyXTzhpZOPPbPStx4yRh8tOOY5lZ5ZcVnz+eWyuOKc8jIyIDb7VatVWc9b29vPcI0ToqCXJemcyt3/uR47p0vcNG5Iy03O2P5HkjNJfw+TVYuGjMTGRkZSVef+smRz/D2/g+Zxzd2NOOJbastc9lm+Vu78cinyM/MQYOC+PK58jB1WAlzfXdQkF/8ih7Hcq+a1VbM7PtKbl6Lp9yE7EwPs89AB7pk3wuH9XzFi6Xnfl2xVv/WcxfBk5W8zyh6fkuNPt8ShBbs/PeeJTUeMFm0/+QnP0FdXR1WrVrV+9quXT0Rp7Fjx2L48OHweDwoLy/vFdwtLS3YvXt3b4u4srIy/POf/0QoFOptFbd161aMGjUKPp8P2dnZqttIJYwamHQcqWFuARdt1tZxpKa3ltxqmsvfZB6rZU6c24uC+bcnrF+61bAYz4nImU+xOJMbQasTvJSY9Wal45JpwzCzZHDE/LTMncVZ/7UP98e8psVpndW9nxcE/Oa5bYr7Yj1vrI7xUiy7ppj5WrMcWzTRpodW3WtmGTAmK8nWWofneazY9g9dn7XKZZv1b+2ikgWS7vEiWp23WZ3jmztawPO84rbNbitm1n2lNK/HPnk24rV8Vy4WT/0avBnZkvvU22ec53lTvh96t0Pmb7HYzaCPIOyOqaL9iiuuwPe+9z088cQTuPbaa3Hw4EH84he/wIIFCzBmzBgAwM0334zf/e53yM/Px9ChQ7F8+XIMGjQI8+bNAwAsXLgQK1aswP3334/bbrsNlZWVWLVqFR56qMdJPD09XXUbqQSri6s4LrotW9veck37CwUaJf/bcow4zSvAt7egfv0qOBxcSgp3Vsfwr88pxDcl3MpZncmNoMUJXq7HfEtbF9ZuPIC1Gw8g35uB797Qky6nZe5aFjikYHFaZxWPT72qHK1+9o0qPH3fHNXzlu1OQyuDaPe40hAIxo5bsbYKHOdgutZ6z594j2q917QIfNbvgR6H/WQhmVrr1Phr0apivCaHVQ/xrH9rB3kGmCq+WNucrd75Ctbt3SAbMbeqrRjHcSgqGNsrVGv8tZoEr9ae7w3BJjy+ZUXEa+GZAnr6jBvNPhCFesWxz7HpUDlawu5dLdtJtsU1q9H6fEsQfR1TRfvll1+OP/zhD3jmmWfw7LPPIjs7G9dccw1++MMf9o75wQ9+gDNnzuCBBx5AR0cHysrK8Ne//hVpaWkAAJ/PhxUrVuCRRx7BDTfcgP79++MnP/kJbrjhBuZtpBJaVpWl2rJp5UygCQIfgoNzmtJv3Q6ILvcDF96bcsKdNRqb7Y41uJATyEZ7eEfD2vcdAFMkt6GlU3ZbSnM3KtjESO3E0T5ZMcm6j5Y25RRPf1MQew81qJ637hDbYteCC0fjn+/FmgxJnS85saz3/OV7MzXfa1oFvtZsDiKxGH0IZ/m81oiolr+1xQMKTRNfWtqcKUXMrYpaGhW8enq+RxN93Fr6jBvNPpA6fj3bEUmmxTWr0Zs1QRB9FUOi/de//nXMa1deeSWuvPJK2c84nU7ce++9uPfee2XHlJaW4qWXXjK0jVSBdVX5nHo/Tr32e8P7a9iwCk2bXoH3vKuR5htivN+6jfCvXwl3YZlqT/pkgrVf+Iq1VfjXR7W9ooc1jVtvD289GI2EhyM1dzME2yv/+QK1z1VEiO5wMWmmKPQ3B3HpucNx3+IyPPHyTsmIekenercAX04m1pcfVhwjnq/yqhOyYlnPsRXkujB+ZD7ueHQ90/6dnEPXYpKWbA4i8Rh9CFf7vB6hqTWCa6b4kkudlkMqYl5x7HOmfWlZMDEj3d7MKKl43Kyp5kazD+SOX+t2CGlYvnPZ6Vm2MRQkiERDvy42R1yFV2LxlIVoWL/KtH3yHQE0ffwSTv/r8ZQR7MDZmn27IfAhBA9XIVC9EcHDVRB4trZtwNkoNgui6NlSeVxTDbARQryAnV+cxp/W7FQc9+wbVfA3m9dDU2ruorAzwva9dTFR8vDzyrKPrEy2tdKWQM9+ZpQMRlo//T/VV8wcwXSt12zYi1+trogZKx7fJ1XH4c3Sls207JpivL35IPO9xrqYFOIje+qxfA9uv64kbgtQhDJFBWOR78rV9dno1OdoRKEVLQREofnJkc9QXbcPmw5XoLpuH3i+528cy99arfXqWpgxbCqeXPAIFk/5murY+mAj3v7ig95jOBM6g02HP2XaD+uCCavgFc+f0f2xIGYKAGfP14OX3o0fzFyKBy+9G08ueDhiEUFL9kE0WtP65bZDyMPynWvtakPFcbYFKYJIdUxNjyesQVxVXvnZSxEtQ8RV5dJQGk4YSInvS8S1Tp8BqZIGZ7YPBfOWMqfyzyodgvsWl8VESOV49o0q3HJlEdO2jaSUS6U4y+FvCvaKVLOInjtLmr4RxGix2j4uPXcY1m0+pLo9b1ZPSUNPqrq6w7Q3Kz1iQUE0Huw+w7bwtvbjA4rvv7nxINN2xH1fNGUIVqytYs6eaGjpMGQoJ/c9kDNgJBIHx3G4lTElPBol4cwitP5vy1/B4+yiT3gE3qhZmFGzM47jkJPpZRq7eufZ3u7e9KyIOms5vOkeTa3ozEi3Z63ZZyU8cq+W7cAa5a849nnMdvSk9VPttXbKhkyGJ92NQFe77BjKYuhbmGUamYqQaE8SZgybiuK8cVi//QPkDMrDwJwBvTdyoHpjoqeXcLKnXYHW7e+qjrNTnX7bnq049erymNf11ODPKh2CGSWDsW7jAaxYW6U41t8UVK2pFtGb7l1efUpTazCgR3SyGquxED53sU67+wyPb10xAe9uPRQj7C6aMkTSPZ4VUUyqLaK8v+0o0/YKcnv6ibIunNx2bQkKcl0xtei7av1Mn5cyqmOlIDcT82aMxJCCLOR7M9Hc1inpjq9EvjfTsKGc+D2wshsCYQ6iQH664gUEogRnhjMdac60iNdZhDOL0AoX7EBsqrdeszCzWq2dDNSpD4qCRbADwAUj2VtnmZVur6VmnwUtkXvWsRsPluPcwZPQ3Nnae731CHCqvdZOjb9WUbAD5CDfl1D6HSUTRxLtKYGdhGgicHp98M29Fe1fbFM04XN6fcgczhZhthqBD8H/3krFMVpr8J2cA7nZGUxjvZ50y2qAeV7AqrdiTc/UaAp0QhAE9YEMhM9dKuKf783At64YjyEFnghhN35EPnN2gBSimJxVOkS2rVuw84ym+bMunBTkuiTbmbHUe+tZLMnxpGPZNSW9cw1vw/edB9/WtC1xG6zlGErnxMk5UrKtWyoiCuTqun2oPr0PEIDigYUo7t/zcK71Ac1IpDM8mqe1Xt2sVms8z2PD/k2a5q2FsqGTmcbxPI9Nh9g6z7AI1RnDpuLuWbfFZDloRa00IpqigrHwZnjQ0qncJra1uw2//Oj/wvaTi8vHXGDp3IgeyEGeEFH7HY3OyNCzKJrs9K0liiRm65ef4Z53f45/HH8Lf9n+Ah764HF8f939KD+6A5nDi+DM7rsGSwVzl4Lrl4aCeUtVx9nFhK7jSI2qy7+eGnxmgZfjsqwG+PDpTqZ07mhWvlmNQFBd0LIgzl00NYsWrA0tnXjx3b1I68dh0tiC3uOcVToEf31gHh69czaunj1K837F8x/iBax4QznjgWX+AFstvtICC0u99zUXjtE8x+ZAV+9CQfh9smu/X/MCgHi8Ro81WQjxAnbV+vHR9qPYVeuPqdHneV6y7joV4TgOkwZNwDcmXYtvlF6LSQMnRAjnC0aUoXhAIVNExUikU29Nslm130DPIkWDSWnk0WgRlTX+WrZ0+wz2dPvzh5+LH55/G9NYOWaPmK653OCCEedp3k99sAlrqtbBk57F/Bkr/Q5SGXKQJwC239HojAxRzJcf3WHl1GwF/cIkAR9tfQmPbXkWjV2Rq8XiDfvp8UpVwZoKcJmeiH87vb6IFPKsCTMxcOG9MQsY0ePsAGttvdYafC2iR0zjjh5fkOtSbPemJjgCwfgIjBsvGaM4dyOmZpPGFmC2xhrocDGp1wlf6tybYbKmdq0XzSnUZdInlaZexZiOH75/8Xjtbiindu+zsKXyOJY9/B5++tRm/O6Fz/DTpzZj2cPvYUvlcQA90Ybvr7sfD33wOP64dWXEAm1fhmUhQ6yf1oueaJ4RszMz9s+KFlHJOo8LRrCn2wPAzHOm4Z7Zd+i+Rmv3rEf50R2aFrVYswv04nPlMWdSELGwfGcpiyH1MdIaknVRNBWg9Hib01qzBX+vfR/oxwEO6QfVVdtfxpMLHsaAG+9B3WuPAQbSz+wK5/Kg4Mrvwun2IhRohNOTh8zhRTGR86wJM+EuLOuJZCuMSzSsJQ1aSx9Ye6KHR5a11ACz9M/2uKxdC8zJSsf3vjYZs0qH4Jari2XnbsTUDGBvpycSfl61Gvh9fU4hJo/rL3vuzTBZU7vWekz6pDI7WH99Lpk2DD/85rSY47WroZzW3vFy21BqZ3fTDR6sO/ZK7Psa06xTDdZ6caP103qieWam95oRTYxOB2c10dMzDz2CONwzoOLY59h4sByt3Ww1+QDwdMUL+JtzTURGglKarBEjvEBXGxaVLMD7+zdFfN6b4cEFI85D2dDJfbKu1kxYvrOUxZD6GFmw7EueByTabYzAh1Dx4So05ysLTvGGHe32IhUFOwDwwQDqXvs9Bi68F57iCxXHOjgnXCNK4jQzfYglDVbU4M8qHYIbLxmD1z/aj/BAIOcAZk8eiu4zPHbV+nsFG2sNMEv/7CljczGifwbyvRm6UuTV8GalY+X/XoF0hhZoRk3NWN3mpcSkVgO/4QOzVa+B1gUW0XwveqzcfrR2IZBLUy8dU4A1G/apfn5O2Tmyc7eboZye3vHRqGd+CPj3oXWAQlc9q12U7ejaq7VeXM4BnoNDsZ5abzTPzPReo07rPlce/nT1L7C3/oCha6i1Z71WxNKH4gGFuGXywl4B/+HBT9Derdz6M9q0EFBe1DK6kHOGD+GbpdejtTMAb0Y28t25tvheKGHH77ESRrs2EMmP0QXLvuJ5QKLdxnQcqUFTVwCA+s3cGGxGKKC/PVeyoNWcza44OCcK5i2VdI8X0VuDv6XyuKQLOi8AG3cew8adxwBoixKyppr/6e7Z4DgHllw1XrN7PAvf/9rkXsGuFvlkFc5K4+SErDcrHZdMG4aZJYMlxaTWKD3rXLUssOiJCoeL5a1VJ7B2o3wbOLk09ZKxBfC40xBQqGvPdqejROU47GIox3rvzygZrLiooJb5wWU3QEhTvl+sjCiY5X5uJqz14tELGVIO8K0dATz2ybOy29EbzTNT4BoVmEum3YR+zn6G7494Rj/DBfzovHPwRPkq3duSW9SSE4UsvLb7rKmm+H2wswA263scb+Gvt2sDkRoYXbDsK54HJNptTCjQCE+IrU4jJyMbTrgM7Y/L9GDAjfeAb2+G05OHUHsL/G89Db5D2Xk1nojmbHaPpLMg1uDH9Gn3+lAwl71PezgsAkNES5SQNdW85nAjOAAzigfKpjjPmzECL767h2mO4Z8Lj2azRD5nlAw2xSFfT9RXS094s43VjEaFRbE8aWwBikf7NKepOzkH/vumKYrHftdNk5OmDZvRMgsRtcwPRxpbZooVEQWz3M/NxkivcCkH+Hs486N5ZgtcUWCu/OwlNHacvdbiPAHEJSKZiOinz22sE47Sola0KMzJzMaT5as1Gf8l+vughlnf40Qt4Gnt2mCEZMtGSHWMLFj2Jc8DEu02xunJY052F4QQBJ6HI9MDQafI7n/1nXCPKj27TT6E+vWrABuJdkC7OZudMbsGX48BGkuUkDXVvKm1E/lfpffKiV0AWLtxv2IktiA3Ez/8+jQ0BTpjRLKWyKeW+n4l9ER9xSj9Ey/vVHRTN9NYzayosIjeNHXx2J/+V2VEmYTWGnCr4YUeQyulBzfWe//zL04rnqNcj3I7RqGbrV2j2REFvdHseGB2Oyg90TyWh3uzBe6MYVNRnDcO67d/gJxBeRiYMyBiv/GKSMY7+mk02gYo3wvRovBWnSIhUd8HJcz6Htt1Ac9M7JhVRMj/jmanZ6FVoZtFX/I8INFuYzKHFyHoYXtAO/DmH+E5zera7EB47TuXnY+CubeCc3kQqN7YKxxZ2pIlglTrS29mDb6/SbkeUO4zalFC1vTt3OwMIEzjSIndLZXHFQU7ANx+3SRMLuwv+Z6WyKfVpmZydeMiouhds2Ev1n58AIHg2eO2wljNrKhwOHrT1O1Wlx7N3sBBPLPh5ahoZuyDG+u9/1JYHX/04oRYrqAE35oPR3emYoq8FREFI9Fsq7GiHZSWaJ6Wh3uzBS7n4HCOewiKhhbB7XbrPgajxHtfRsoDAG33gt60eTsaX5nxPbbzAp5Z9IVFiWRG7ne04vjn5HkAEu22xsE5MXzalcD+d1XHZgW0pEz2CHbveQuQVViGUHsL6tevikzRzvYhq+h8rVO2HM7t1WXO1ldoaevS9Tm1aCJLjXZBrgtFI/Kwd+8p2TEskeBsdzpmlAyO+Ey48PM3sy1MiMc0o2Qw3K40VH5xGv7GIHx5LkwZ21+1ploN1rpxJ+fAN+dNwKI54y0VsCFewM4vTjON1epurxe71KVHs+1EJV4/+X7M61IPblr9CYDIUgQAjK78Dlw9coGke7yIFREFs6PZZmK1IZoSeh7u4ylwzSKeacJGshbyM3PRxXdLGtGJ6LkXokXC0eYTeK3mbdXPJdr4KvpcVhzdyfQ5pXlbsYBnpzT0vrAokQpI/Y6S50EPJNptztRp1yLvy41o7GqTbvkmCMg5w2NUUDlyKUXbnk+QOWw86l77fcx7odZ6tHy6Ts+ULaVg/u1Jb0JnJV5Puq7PqUUTWVvJcSoilCUS3Nre1RsJlhLG3iwFe+0w8r2Zkp8HgFfe/8JQqraeunErBazcccqh1d0+leB5Hi9Uva44JvzBTYs/QTSs/hLh9+L4o/lxjShYEc02i0S1g+orD/fxTBM2I2uh4vjnltwL4SKhum4fk2hPpPGV1LlkRWneZi/g2S0N3c5ZRYQ6ybgoajbJ+9emj8BxHJaed7OsYAeAa/wBXRcy1FIP/zvybrp2I2fmdfAUzUr0NGxNQY52M0JWIzQx1dyXEyn4CnJdTGZ2gLY2bKIwjhaiLW3qC1QFuS40BzolPy8iCuwtlceZ5iTCWjce4uPTflHuPMlhtvGdXQjxAnbV+vHR9qPYVeuXPf81/tqIlHgpxAc3Ebl7X4365g6m6/LDb07r/f7MGDYVTy54BA9eejd+MHMpHrz0bjy54GHLHnLFaLYSiTT6ESOv0XP0ufIsS2XV8nCfrIiZBNHHKWYSlB/dkdB9iQ/oF4woQ/GAQnAcF5d7wezvA8/3+GZsOlyB6rp94Hk2c2E55M4lC2rzNnMBL573Fyt2zioiCBYo0p4EzBg2FddOmIs392yAEFaL7gBwYVM7Str098Pm21tMmKECHAcY/CPFub0omH87CXYG9KTyKhmhRaemzygZLFunHOIFVB9sQPWhdvCZDZhW5IrZLmuENyc7A3/4x3bmY4hm2bXFWPFGFdNYLcZsgDV143rR0i1AxEzjO7ugpcWd3ge36Br9L0+1MvWjZ6G5NfI33G51xIk2+ol3amTFsc+ZxiXrwz1LJsGzFS/i3MGT0M9p7DHR7KwFq+8FM78PZkeaWc6lEmrzNqscxYxrbkVavZ2zigiCBRLtSUD50R1Yu2d9zOsCgI9z3Tin44wh4W4pOgU75/bCU3IRsgrLNLupRwvNopG56D62xxR3drujtdVYuBFa9HlrDnRixdoqSSEULl52H6iPGfvqlgb4cqpjRBNrbbxDgGYX/HCOnGpl/rxWgc2aLbD5qwi+Uu26mpGdGlq6BVhhfGcHtJYqGHlwCy9x2FXrN020J7pcIRHtvbQSr4WM8qM78Na+/zCNtfLhnhd4fNl+HM3HgjHu8UZhySRo6QrgtjfuxSWjZqFs6GTd+7ciJVnrvaBVAJrxfbDC8IzlXMpxVeFlqvsza8HC6DW3Kq0+kR4ZhD7s5IlgB0i02xzFFUuHAxAEvFngwcS2zqSudeBc2fCWXYX0/MGGhHV0xK007TC+5tmGHMdZ8xpntg8F8/T1QU8G5B3TMzFvxkgMKciKEYisNdGiEMp2pym2MQsfGy6anJwDF08ditc+3C/7uduvK0FTwNgi1JsbD2gar8WYLSebrTXXvzcfxL83H5SN+GqJDhud99fnFOKbV0wA0CM27ejmzkr4QkeuJ0Nzi7uigrHIy8yRT5EXAE+aV/XBbdyIXHj6NyMYaoPQnQG+NR89+U9nEdPp1Rap7FCukMpGP6wPfloimZ70LMse7suP7jjbp/2r6h0za4FZMwTauzvw1r7/4K19/9G9/3ikJCtdX70C0Mj3wSpPBCPnqGzoZKZxZixYGLnmVrq7J0NWEXEWu3ki2AES7TZHdcXS4UBzmhMHXWkYo8OMzi7wwVZk9D/HkJCOjriVph3GUs9HMeNCrfU49epyDFx4b0oLd9Z2W3KRSiXUBHs44aJpS+VxRcF+4yVjMKt0CHbVsrYvND4/QFuk06GxVF1cvPifW6YjJysDDS0dOO4P4MV398qOZfUIYJ335HH9UV51wvAigZWwZB1oNdwDYjMpOI7Dt0uuxxPbVkMQIu1CvrIJQX3NaGwdd1L2vDy36X38+9A6CKM6IFo/8p0Z6P6yCHzjoN5xd1w/CYCye7ydyhVS0ehHy4OflkhmoKsNFcc/t8SwzYhoYVmg0JMhoFc0mZmSLHVs0q2geq4vAEPnMvz7oGXh5+0vPrDE8ExvZofW6LHRBTy91zweBpDJkFVEUGs+OUi025zTbWx90hudyb8y6F+/Eu7CMl0R9ujaXgd43OjueVCW8vAzur9kgMWtXE9NtFZE0TRxtE91Xx/vPI5bri7WVZsfjceVFtEXXQ6tkU69WQDLn98GVm861jp71nKD5kAnfvP8tpj3tC4SWAVL1oGexSWR6IyEaQMnwfnlNHQPrIYj4+z1FLoy0f3lBPCNg2SvwXOb3sebR18B+kXG1R3pnUgfuxNdtVOQL4yKKEWQznxJzXIFO6H1wU9rJNNsB3mjooV1gYIlTVjP/qUwKyVZ6tg86VmSLeDE6+tJz1LcJuuxsJ5Xra7uWu83vddNT/TYyAKe3mseL3f3VM4qSgX6SvcOPfSto01CWHtvVnvYUnbtTKilHh1HanR9Nrq2d0y/OuQ522UFu9H9pQpaaqKNINa+sxq4ibX5RphRPEh9EIBl1xRj94F6VddxEb31x1rM5MXzoAbLeVp2bTFWrFU25Yun2300cu734e7+RheXoq9ZzeFGBE4OQOfnl6CzpgxdtaXorClD5+cX90bKpa5BdyiEfx/qaYUZ/dsi/jtj5B489f8uixDjs0qH4K8PzMOjd87Gj799Lh69czZW3D+XBLuFsD74hbt5a41kmu0gb8S1Xotbt5gmrAetx8yyLzVRKXdsSj3bWd5nORbW86rH1V3r/ab1ulnZYUEJvdc8nu7uUt0JwjHb9d/u2Ol4+0L3Dr1QpN3mBLvZonpdSurURBzpLhRc/V+of+dZ8MGA6dvvbjkN7U3LYiNpXi7I9LlQoFHH3pIPudRjLbXcRjjubwMvsIlCf3PPtZOrzWeNoE8u7I/zigfJplMX5Lpw0ZQhsmZ7coLKjCwAFqSujdR1lPcw6InkZrvTbeN2Hw1r+7yszDTd51sqk6Kp163dAb5VPssi+hq8U7kdQloH5H5tHQ4AaR1YX7UD10wti3iPJfOFMA89UTs9kUwzHeT1ihY9kSkxTfjZihfQoiJu9c5TxEhKslHHdDUqjn0uG7VlPa+Zzgw8/enfNe1Xr+GZ0rm8ZepCeDOybRE91nPN7eLu3tdqqe12vNSaTx4S7TbHlcYWQU9nFERGEbqCqH/nr5YIdgDoPPoFMOlSzZ+LjqS18GzS3+nJ07yvZEMp9fi4X9vDml7eKz+Eay8cwzS2JdDV+99StfkhQcDP/rJFdTsFOS5MGlvQ+3l/cxAtgS54s9J7UsbbOvGb57SnjGtx6DdC9D2tlkIu52Hw0fajTPuL1wJOOKzZF5X79XscSNWM5zKaCUZfg5MtDUyfYx1HWIeeBz8Wo6pozBQQekWL3rTiGcOm4tzBk/Bfb96Hlk72v+l6jllvSrIRx3QWNh36FLdMXig5D9bz+sjHf9K8XyOGZ8mS3q11nnZwd+9rtdR2PF67LN7YERLtNqd/PVsEvdig27YW+KDFvd11EB393H9mABpDbuRy8inyTq8PmcOL4jjL+KPWDivbnRaXefibOtDS3qU+EEBzWyc+2HYELW1d8HrSUZDjijAlC/ECUx23GF2VinCGeAHLHn5PcR5KdeVy0W2ziI4Os7Y1k4rksqbzJ6LtGOtCwZcntf/mKNWMF43Ig9ftREt7SPHz0RH6Qd584KT6vgd58zXPlzAXvQ9+YoTwb9vXoEFFsJktIPSKFiORqX7Ofrh9+reYFyo8aVngeR48z5tayy8n7KyOprV0BWRrpK3Yt1mGZ8liGqllnol2d+9rtdR2PV47LN7YFRLtNubMmTPw7N8KDFOPGmeHUqPeJi1/sK7PRUc/BXB4rb0MSz0fxThEixTMXQoH54TAh9BxpCZp+7jLpb6zpB5rdVk3gpOxhOPl97+IeS08oswS6V52TbGiiZuW+nq5lGYxur1u4wHVmnGthEeHu87wePKVzxXHKy0wsJrVJaLtGOtCwdYqdaXsy8nED785Dc2tnart7DjOgfnn5mLNRnnfAKkI/fzSafh79Yvg+3VI/qYIAsCdcWF+6TTV+aYiduqpa+TBT4wQvlbzNtZUrZP9vNkCgkW03DJ1Ycw5NhqZkktlliLQ3YZffvR/mtNn5VJwZ48ow+bDFbKpufGIpsmJc7P3/Z3JC3F14WUJ+U7Y6bupRCLd3eNlhGcX7Hq8iV68sTMk2m3M3k/LEcg4wzT2VHo/jE/ilm8AAAcH77nzdX88OvpZ2T0CKwMX9/RpR1ifdq8PBXN7+rS37dkK/3srEWo9+/CeTH3clVKmjdQBW0HJ2AJsqPhS15yiI8pqke4Va6vAcQ7ZunTWCK/aOCfnwIILR+NfH9Wacq6jo8NbKo/jiZd3qi6uKC0wsCxyJKrtmJn+AHdcPwlTxvVn3/dwF370jVKsfnsfs6t7mtOJq0cuwJtHX5FtF3f1yKuR5kyeRT+zsFtdpNEHP47j8LXiqzE8Z4ikgFg85WvwpGdh0+EKU0WQKFp6+7SH7XP2iOl4bscrMef4lqlfMxyZCk9lrjj2OTYd/lQxZV5L+qxSCu7aPesVt102ZLJup3tW5MS5EZd9Kf69dwMGeHyy58sqYW2376YaiUr/72u11HY+XmrNJw2JdhvT3uBHQxrbwx/rODuTM+MacP2MpWvH1vbORtHI76H72J6YSHrbnq049erymG0kSx93tZTpzHT73BMFuS5MGlNguBY8PKI8q3QIeEHQVZduNGU8OrvhtutKJOfBwreumIAhBVkx0WGtLc6UFhjkFjm8Wem4ZNowZLvTEeKFuAt3M/wBjLROm1E8EBedO1K1P3w4t1xwObAJPX3a086eS+6MC1ePvLrnfQuxY8TMjnWRgL4Hv+jzWzZkcoyAaOlsxeodL1smgmYMm4rivHFYv/0D5AzKw8CcAWjtCOCxT56NGVsfbMLjW1bg2glzJQWwCEtkSkxlLh5QiFsmL0T16X14fMuzCHS1y35GLX3WiJGcuG21xRdPujtijj5XHi4fM1sxS0LEm+6RXczQ43GgRENHs+z3wSphbdfvphqJSP9Pllpqs/4GxON4jcw1Wbwb4gmJdhvjzi8AjiV6FnHAwSFnxjXwXX6LKZuTqmHuN6Ik4t8CH4L/vZWK27FzH3eW1PeOLvl6XTPxuNNw5gyvuD8xkmu0FtzfFMSL7+7BlHH9MX5kPla8od7KTCpt3EjKuFx2w42XjMFHO45JRm0BaOrTHeIF/OnlnYrHFk2+N1O2VAKIXNDaWnUCH24/ipa2LqzdeABrNx5Qdc23ghAvINudjmsvHN07H1YWzSnElHH9VUW2Gnpc3W+54HJ88/xL8E7ldpxsacAgbz7ml06zPMJux4iZXesiRbQ8+LGc3/KjO/D4lhUxnzVbBHEODue4h6BoaBEyMzPx/XX3K47/z/4tuGni1Xj/wCY0REXo9USmOI4D5+AUBTugnj5rxEhO3Lba4kv09R3vG40af22MmJdi2fRvKN6XWkoHWIn+PlglrBPx3bTjoiIryVBLbebfAKuP14y5Jot3Q7wg0W5jxp83A599ugLIVR87vCP5UuPTBo9FdvEF8J4733CEXSsdR2oiUuKlEPu4u6IEvx0wq796tjsdrYwGcXIEvkrdvnDKEGzfW4e24NmSDilharQWfM2GfVizYR+8WWloadOXNq43ZVwpu+G1D/fjf74zHTmeDEnRLOfuLkVVrb/3vLIguuEve/g9xfZ1Ts6B1vYeoS51DErZCWYjtfjhzUrD2GF52L63TvXz5wzMTmgLtTSnM6atm5XYNWJm17rIcFge/FjOb9mQyQlZoGA5x4HuNry8+9/Id+ViUckCDPIMMCyazEifNZpaK35ebfFFvL7lR3fgv//9MyaBfe2EuTh/+Lmq46L3nZORjSfLV0Usjmgh/PtgpbCO93fTjouKWrB7LbXZfwOsPF67/r1KdpJj+auP0q9fP2SPZWt/lpuERnR5MxYgV0dKvMCHEDxchUD1RgQPV0HgtUeUWfuz27WPu1ntue66aTK+dcUEU7ZVWevH4qvG44ppXtz1tWI8eudsrLh/rmzbNNa2W3KoCXYRse97iBewq9aPj7Yfxa5aP2aUDMZ9i8vgy4lMgS/IdUkKV5bshr++WY2Jo324eNowTBpbECHKxYiu1HvRaG1xdtGUIfjNc9tiFnJEIb6l8jjzMTz7RhVCvLUtJMXFj+j5trR1Mwl24GzpQvR1tXruiYD1wZ7n4/93wM51kaywnt/qun3MIsjIXKrr9mHrse34sv04eIHXdO4agk1YU7UOac5+KB5QaEhgmJE+azSVOPzz4uLLBSPKJI9NFApq18ib4cEPz1+GqYNLsOlwBarr9ql+dziO6zX9a+5sxZyxF+o+JqCnPzygTVhrJZ7fzW0nKiXPvSjSyo/uMLyPeCBmVvhcuRGv+1x5CRWaVv0NsOJ47fz3KtmhSLvNue6qm7FuzTa0okvaAl0QkHOGx6gkNKHT0yPdLOM41n3btY+70fZc2e403HXTlK+i3gLe+eQgGlqMtQ1sDnThz69WAwAqamvx3RtKFYVpvFqMtQS6FA37/vrAPKYIuBmO86ywJnu7MvrhB4umqGYsiGUC8TwGOVgWDjgHoKS9xdIFtd71qYKdo9nJUgeqBOv5rT69j2l7ekWQVKTynYbNmKtDIJoR8TcjfdaImZuW1FwWoeBJy8Lds25DoLtN0tBPKSIsdW086VkABNUUfCne2vcfFPUfi+4Qm9mwnnsqXt9NXuDxQtXrimOSqVWaHWuprfwbYPbx2vnvVbJj/29PHye471Ncd/KrqJsQ9RT71b+v8QeS7kLq6ZEuGsdFp7WLxnFte7YybytzeBGc2cotruzcx12sydbLT24pi0iZ/u4NpWZNDQDQ0NIZEeGVwugxsHKqoU0yqitGocurTjBFwM1ynGehhFEw/7/FZcjxZDAL8XgegxwsCwdqwfLbrytBedUJxeuqdO8lG3aOZouiTIlE14GqwXzeGJM49IgguShxY0cz1lStgyfdrWl7RiP+wNn0WSXU0mdZtqF32+GwlhDsrd+Px7es0BQRlrs2ga42BLrasahkAf57xq3wpmcxzVVk1faXkZORzTRWzz0Vr+/m0eDJiE4HUphxP8YTtayOeGP13wAzj9fOf6+SnWTTen0K0SytpK0TN59sQc6ZyFSSnDM8bj7ZgpI2YxHSRCD2SGeF1TiONVXewTlRMG+pqXOMJ2JNth5EJ/dwRIO4aBGd7U7XPUdAOdXayDFo4aMdym6OrOngRh3n5ZBK7540pgDZbuWykWx3OiaP669JiFt1DFpgne+1F46WLV2YUTLYFmn+8cLO0WwzhF2iYT1vxQMLLRFBLFFiB3P+zVmMPBSLafrdoTNYVLIA+QbSZ5VScK+dMNeU1FzWY31r338U349O22W5Nu/v34zZ50zH7WXfZpqDSH2wEXDAMmEdr+9mIBRkGkciTT92/hugdw52mGuyQenxNibcLK2krRMT2jrxSY4LDWlO5HeHcH5z0LYXMPeir4MPtqL18w8hhKWOiT3S3YVlCB6uQijQCM7d88Xl25sj/ju8PZsVxnFZE2Zi4MJ7Y9Ptw/q4JwIlB/Bw5JzY1czlll1bLLn92HZ5Pe+VV53A0/+q1JU+r5ZqLXcMHlcafLmZOHyiVfM+w/Fmpas6kivNMfxa5GRnIN+boXge5Bzn5VBK777rpimKRnl33TQZTs6hSYgbcc03C9b5ziwZjKXXlkjeq7tq/QlP848ndnc1Tvaeuqznt7h/oSXGTSxR4tauNiwqWYD3929iTjXX8lAc7vp9MlCHDbUbI4zW8jNzDBncKaXgfmvS9YZTc1mPVasbPmuq79tffIArx12q2Wm+uaNV9Z6aMXwqavy1us7LjGFT8aPzb8eK7f9AS2eg93Uzv5sep4tpHIk0/dj9b0A4yTTXZMOumo9ApAlaVVYG1hZ40BLWj31jrhvX+gO2irRzrmz0v+q/4C4sQ8eRGmQMHotQewucWV70y+5JN2/fV4Evn7hTVYQDZ+vVhRBbzb5W47isCTN75xrdxz0RaK3RVRLaUi3GLpoyBCveqJLs1T2zZDAmjvbFiBxxH2s27MOL7+7RfExbv0o/lyP6GI77A3jnk0OGBTsAlIzxYUvlCdVxn39xOmZxROpaqEW/pRznAemFGDG9O5pwF3epBY2C3Ezcft3Z+0GLENfrmm8mWucrde/YIc0/ntjd1RiwZx0oK1rOrxULFKwRyEGeAXhywSNM/dO1PBRL1WtH0/BVmv49s+9QrEMVI/TVp/cBQk92QnH/nnRbORd/LW2d5FqKsQgFT1oWAt1tqvsIvx6s12b1zlewbu8GLJm2CE8ueARvf/EBVu98RfVzea4cFA8olLynODjAQ8Bb+/6Dt/b9R5cTe/nRHVi98+UIwe5Nz8ItUxeatpg2zDUIeZk5iinyJNKMkQx/A0SSaa7JhkMQogul+x67dvWkWU6aZH2qrhaCh6tw4u8PoiorA38f5O15MdyM7qtLF88Uec7lAR8MyL4/4MZ74HBwsmZxAHDq1eWa95t70dfR9PFLquMG3/yQLVu0sSDXTkxEayuuaKHYHOjEb57fpvgZNRMvKSHLAuvc1c6BFNdfPAYbdx4z3AIv/NjV5uFxp0W0ZFPquS51zvK9Geg+w6NVoa1bQa4LK+6fCwCqmRda7x2pOSkdg9kYvdd31frx06c2q+7n0TtnS4r+9vZ21NTUoKioCG63tlrhRCLdUik5otnJgJbza2Y/6uq6fXjog8dVxz146d0Rrc2UHopZ08vVthONz5WHJxc8LNvn/umKFxDoihTGnnQ3vlt2s+F7VK2lmNqxLCpZgDVV61T3E36eWa9NOGJ7wO+vu1812hh+LsV7quLY54pp/GZdWzPc0MXf0rbcbjyxbbWl+yKS62+AXeaaDH/vWXUoiXbYV7QLfAiHnrgTD/mAdicn6x7v6ZeBnx0PQggTyY5MD4QOeXGtleyyq5E1bjpOv/mEYoTcke6C0CVf36Qm+uVwZvsgCAL4QIP8GK8P53z/KdvWoSsR4oWYHtvR+HIy8cNvTkNza6dqn2892w/nW1eMx6I54xWjxv7mIFa8sYup9ZooQJXmq3WOAHDjJWNw6zUlCPGC7kyAaP7nO9OxYm2VSiQ4Ez/8+jQ0BZSvhZ5FiHDkRKcUWoU4axmGVRhZOGC5V5TuOav/iFt5bs0Ui0QsiTi/PM9rFniA8Ydilv1KES5qw+eiJv6vKrwMZUMn6zqnrAJU6ZzoFdJ3rr0PjZ0tzHMVt1Fx/HPNolnvvRCNWdtRI9AWwPrtHyBnUB4auppjyioSKShT9bcymY7LDnNNJdFO6fE2xsE54T//SrQfeE9hkAOBUBdOz7wCkwaO760RP/XaY+bNI9ODgjmLmerKlQQ7AF2CHehxiM+76OtoVIi229k4Tg0WR+365g787C9bev+tpbUVy/bDefHdvXh362HJ7YenLGekOZlEKUt9sZY55njS8V83luKCyUN7jNz2+7H24/1Mn1XjqdcqGergO3DoRItir3mW1mZqaEnvliuVkBOLcqnn8ULrfMOxQ5q/HFa3odOSSkxoJxHnV286qdGSBJZ6bSnCU8bFdPi/fPp31c/pTfNm7ftcNmSy7DkBeo53xvBpilHs6PP84q7X0dSprVRLrIvXU0phVruseLTdKj+6Ays/e6knLf6rZh35rlxD3gdmoZaVkcwk09+AZJprMkCi3ebsz2AToZ999jqKL/0+PMUXIni4CkKH8XpgEaEjgI4jNWjbpz9iaAZp+YNtaRxnBnpqb8Nrn9XEgJnbj44iXnPhKLy58aDq9hpaOhQjkKxz/PqcQnzziglwcg7d6fpKqAl2kfDe6FKiTOtCiRRaXdwTLcS1YmS+ciaG8Uzzj0Yus0LLd5Xom8gJvPzMXNx6rrzQMPJQrNfNWzQUY6mFl0JsryaXMh0dneMFXpMAjT4nUvMU68VFpIT03z9/DWv3rNd0bCLiudW6sGJWuyyr227JZT40BJuYvA+sRG5uavcdQdgdEu12R0OgyL9+JdyFZZrN2Fjoaj6FQNXHpm9XC05PHlwjSmxlHGcWRlpsPftGFWaUDFaMKpq1fSmR7M1SNmcTOe4PxKQ0h4td1jlOHte/dy5GUs/NREqUGTVBs9rFPRWIjtbnejIgOIDm1k7sqvXHNeWfJbOC5btKsGGHtEuzCRd4p5rr0HyyEXOnXQpPlseS/elx8xYNxbTWwkshRsfVUv5Ze9RLCVC5eYqCXS5l/0zoDNbt2cB6KDGEn1stCytmtcuysu2WlsyHeH8n7Tw3gjAKiXabU9y/EK/hbdVxY4LdCAXb0XGkBk5PnunzaNtTAb6dvabLbJzeHud5oKdsIFnN5uRgcdSWgyX13Iztt7Z3SYpklpr2bHc6Xnx3b8zr4WJ3RslgZldxM1LPlWBpFSdFuCgz2us8UendyYYYrd9SeRyP/3O7ZWnparBkVqRSG7pE0hdSX0d5hqGmpQacwzphweK4Hs2SaTcBgKowYiE6PVtOYKu1aROJFqAsAq78yA7cMnlhjIB7t/ajiEi8Fow4pZvVLsvKtlvxSL3Xi53nRhBGMfTX4Omnn8Z3vvOdiNdqampw8803Y8qUKbjsssvw3HPPRbzP8zz++Mc/4sILL8SUKVNw++2348iRI6ZvI1U4p8EPhyD0OsXHIAhwCAJGBnuEUyjQiIyh48G5vKbOI9TqN2U7nEtfxCCZ69VZEGt09RIe1Q3xAnbV+vHR9qPYVetHiBcMb9/fHDQkkrtDIcX3n32jJ9VcbY6ikDUj9VyOglwX7lxYquuzoigDzi6UKJHtTo8ZU5DriksatdR9YmRcIhGzLqLvCXFRaEvlccvn0Nfa0CUKUdhFP5iLqa/lR3ckZmJJiFhLz4LPldebVqy3Fl4KMTrOIrDV5hctQLUIuGhOBk7rnouRdlYs16RkwHi8VPUm/rlrLXad3AOe53VtZ/GUr6HGX4tNhytQXbdPcjtSWJ16rwXRU0E8hob2JqbPxWNuBGE2uiPtL7zwAv7whz9g+vTpva81Njbi1ltvxWWXXYaHHnoIO3fuxEMPPYSsrCwsXLgQAPDnP/8ZL774In79619j0KBBWL58OW677Ta8+eabSE9PN2UbqYLAh/DZR89ByFcQqw4HBACHXWkYE+xGd8MJHPnz98EHzY2Kd9d9acp2+l91JwDE1KXLkQr16qzI1eiyIEZ11Uyw7ltchide3qnYakyKptZOpjl53Wlokdh2R6eyaBfF7qzSIbjxkjF4/aP9CNeGnKOntZsoZLdWqfde14tYD80tdui6FqIoYzFLu+umybrN2IzAapZmtamaGdglLZ01s8JoBkZfhlJfzUfJLO3yMbMlDcXMFDxidNzoQsDsEdNjrrkRcTnI01/zHMxySpe7JiIfHd7a+9+v4W140rPw3bJvx+xX6drOHjEdq3e+rCtbxcrUey1IZdx407OYPmv13AjCCjSL9lOnTuHBBx9EeXk5Ro4cGfHemjVrkJaWhl/84hfo168fxowZg8OHD+OZZ57BwoUL0dXVhZUrV+LHP/4xLrnkEgDA448/jgsvvBDvvfceFixYYMo2UoWOIzVo6goAUP9xaXVy4FzZiu7qhuCVRZcaXHY++s9b1iu+w+vSOXfP8fHtzRH/nSr16kpEG7PNKBkcU6MbnfIbTUFuJnhewLOv78LajQdi3g9PQQegWbADwJoN+5jG3XJVIar2fokPd2k3Qmxo6cCWyuN47cNYF3heAF77cD/Gj8gHAMnj1ILDAeR60tHYejYFPtrALLpeuqm1M8J8To5wUcZqlhbPdGlWszQzTNXi0VbO6rR01mNgKUEhnwJpWOvT45H6moq18mpoNUszS/CER8eNLgSs3bMe43yjIgSnEXF5xdiL8fzOVxVT5Dk4cN/Fd6G1s830e0W8Jq/VvK3aWz7Q1SZrsCZ1bVs6W/H4lhUx22E1amMtq2jR6LqvBblSipauNtXPGilfIIhEolm0V1dXIy0tDWvXrsWTTz6JY8eO9b63bds2nHfeeejX7+xmZ86ciaeffhp+vx/Hjx9HW1sbzj///N73vV4vJk6ciIqKCixYsMCUbaQKZ1rqkR1iS1fKDvHyKfQi6S5wHAe+Q/1HzUxyL/o68mYvjBDfqViXrhXWKKZatLajK4QHnt4i+77Is2/sAq8ztTkQZBP6uZ4MbN/PVn8o9dnH/7ldcYxZdew3XDwGt1xdjF37/aiq9UMAUDqmACVRoi7c3TzEC/jXR7WaRZmR1mZmwxqVnj5xkOHodbyi9FampWs5Bju3obMzWurT4+GInaq18mqwmqXxPA9e4OFJdyvWmrv6ZWLSwAn49NhO2THhaeRmLAREZ1kYqevu5+yHBRPmKLrHL5gwB5MHTTQ8byXe37+Jeaxclkn4tRX7t+vZTvj2Fk+5CY998qzidp7b8SpmDJ1q+qKX0VIKI+ULhD3oi4urgA7Rftlll+Gyyy6TfO/kyZMoLIz80R8wYAAA4MSJEzh58iQAYPDgwTFjxPfM2IYeBEFAe7s+sWEVwaZ6jAh2nxXjDomHva/eKxw6BaFaFSftriDYlgDMw3vl95E5YSaCHZ1x3rO9Ka8+hcf+WRnzuhjF/NE3SjGjeCAAYMrYXPzoG6VY9dZeNLScPY/Z7jS0tncjwBg59zdZW0vry8lAV2cXWtq1Z2X4cjLQ2dnB1KuelekT+uOzvacj1rIcDmDqOB9KRufiw4qDeO6dfb3ndM2Gfcj3ZmDJVeN7z300s0oG4s3Nh2X3ecv8cejsCILnBdQcbkRTaydyszNQNCIPY4a4MWZIjwtyZ0eQ+TjMpPpgA1NU+o0P9zKN215zDMWj8mPe03J/G8WdwT5O/I0PBoMR/y+FnmOQ+676cjKw+MrxmDI213Z/ZxLJthOVeGLb6pjXxYjfXdMXY/rgs/4SLgfbxXY5MnrPMy/w2Ft/AM2dLcjJ8GK8b7SkuZvWuVgNyz0ab7adqMQLVa/39OVWYdmUr2P64FKcN3hyzGfyM3PxrZLrMCl/fO91GpE1BHmZOUzblqM+2IgdR6siRPg3i6+TvK5n378WHR3Sv3U3jpuP7u5uvLP/IwhhEXcHHJg/5mLcOG6+pd9nrSUDUsevZ5ss20ljkA8s29ED63nJTs9Ca1jkXeq+I5IPqd+hvMwcfLvkesnfaDv+lkYjCAIcUhovClPd4zs6OmJqyjMyev7IdnZ29p4wqTHNzc2mbUMP3d3dqKmp0f15K0hraMFxV5q0WBf56r3qk7sxIU7zYqWzYDQOCzmAzc5rouF5ASvWKi8wrVhbDQ/qwX0VlfNywPfm+1BRG0Bjawg5Hie21liXeqaHy0s92H9Yn+HX5aUe7N53yLS5zBzvwfxpGZhfOgQVtQHsP9GJI/4udHYL2L6vHtv3SfspNLR04rF/VmLRhT5MHO6KeG/3kSDe3CzvwzCryAMv14BX3zuGdz5rili8yHZxOHesB77sfvC4OIzon9F7beNJ9SG2B5U9tcfUBwGo3nMQXMepiNf03N/i5w6f7kQgyGs7R7wAr9upuFjkdTuB9pOoqYmc66FDh6Q3qfMYgJ7v6l1XFUgcSwNqahrUj6ePwAs8Vh96RXHM6p2vwNXo7BXZvMAj25mF1pB8tlh2vyzwdZ2oOV2DvYGDeP/01ojx2c4sXN5/JsZ7Rmmay1+3v4SMkQ704+LbdEfuHo03ewMH8frJ91XHZffLwuUFM5HVlIaaphpkIQ23DV2Io8GTCISC8DhdGOYaBK6JQ01T5LPBxbnTmfahxO4De4DTZxeys5CG6wddHnsfRM1TjlLHWEwcPRI7mmvQ1N2K3LRsTM0pQj9HP03PjLzAx54Dlc4Au1tjS8XUiD5+vduM13b0wLrvi3PLkN3PrXrfEcmD3O9QY0cznti2GtcPujzitz0cu/yWysHiyWbqX5/MzEx0dUW2Sers7Ik2uN1uZGb21Hp2dXX1/rc4xuVymbYNPaSlpWHsWHvVuATaD2NdHZtp0U43hwkBiyekkUGXfAMZX7VpI85SfbABLe3KoqilPQS4B6HoqyhmefUprHonMnqXKLJc/dAWPNP7bzGKOKN4ILbvOQFsYRcm4Z+tPtiAVzV8Vol5s8f3nrt27hTe3R4bMVXi/coAbpgztVeQ8byAP67bqPiZvce7MaM0H2s2xu6rNcjjw11nzSHlIvpSEXozxT2fyXaOJ4wdik+/UPcxKJ4wqvc8i+i+v6Oi02pZD+HcBp9kVLz3/WuLURy2nWAwiEOHDmHkyJGSfzf0HEM0xaqz7tvU+GvRul+5VKv1TBu4ARkRkbrFeV9TjJwunvI1FA8uxrYTlXi9NvbhrjXUhtdPvh8ROWeZS5DvwDNHX8bi0q/FJeKudo/GE17g8cyGlxXHZKW58f1zb8GEgjGSYrSY4RtRhCIMOzFMMjJ/0Tkz8Pq+d1W34cxJR9H4yOeOIhThWmE+U8aFHJOgv/uK1shgL/40vHnqA037mjh6gnJkm3GbcduOHhj3XTymiGrXUwiW36GPmz7DtdPnR3y37fRbKkdtbWwHCylMFe2DBg1CXV1dxGvivwcOHIgzZ870vnbOOedEjBk/frxp29CDw+GA2+3W/XkrCOX60MX4wM46Lp4Ip2rhGjfFkJFcPIys4k17J5swbe/sWajaUnlcUZDEm/+3+Dw4HQ7JazKlcBC87hrFqGeOJx3Lrinprf8WP9vZ3QjOASiV3Yvt0dTqyqcVDYWTcyDEC1j9NpuJXjj1zZ04eDLYW8++q9avumBS39yJv67bw7R9MaIfbuYWjxrwaUUu+HKqVc/fdZeMx7+3fMl8nsMx6/6WOkdyXFo2ChkZGaqGf9G4XC7J332tx0BoJyiwLUAGhc6Ic3zRmJnIyMiQdMQWnbt5nsc/qt9Q3O4/qtfiglHngeM45rm0drXhiW2rVY26zETuHo0n1XX7VNPW27rb4XK54MnS19ZV5KIxM3HBqPNi6lXLj+0At8+h2jv99X3vYkz/EZLX59ys+JU3iJQf3SG5yCRGBpXupanDSpCfmYMGxpIBnysPU4eVKNb2Th1WwlTnH6/tyKFUs2z1vgl7wvI71NDRhMNtxyX9OezwWyoHS2o8YLJoLysrwz//+U+EQiE4nT1CbevWrRg1ahR8Ph+ys7Ph8XhQXl7eK7hbWlqwe/du3HzzzaZtI1Xo5/VheLAbuz3q0fbhjEZh8aRp4xq0fPYOPCUXIauwTLMTfDK0m9KDltZQLMZh8aQg14VJYwpihFrXGR5vbz6II6eaMHpgOnYelK8d+t7CyTHXb0vlcfzm+W2q+xf7uLOafRnp5x5uXMZqYtbS1qU+KAzRzK286oRhp3YWWM3S0vtxuk3VWO/vptZOdJ3hTWvXZqbhH7VvMwelB28jzt5qbudaXea1mqBZ3VZOPG+7W/cD/rSEi4949+WONsUrP7pD0u1cDru0/TPaopDjOMwZe6Gqe7wIi8Ga2L9dynldZPGUr5myHb2Gb2qGkFbum7Av8f4dsiOmivaFCxdixYoVuP/++3HbbbehsrISq1atwkMPPQSgJ1//5ptvxu9+9zvk5+dj6NChWL58OQYNGoR58+aZto1UIXN4EZzpbA+FVsaeHekuCF36DBz49ha0fLoOLZ+ugzPbh4J5bD3XzWg3ZVe0tIYyIjqtQEqo/e3Nqpi+6gDgynAiGNafXS7qybIw4XAAP755eu9nWdqoAfocw0XCBZlV4szfFMSu/f649hlnbUPHOi4alvsbAFasrcKa9/eipU15wVFLu7Zwt38jUPs246g9eBtx9gaU3c61PtyxtrASMdpWTono8/bmqQ8S7mCfyL7cepzCrbw+WjCjReEgzwCmfV1VeBnKhkzuiUbKOGqLi0HdoTNYVLIAG/ZvQoPE/FbvfBkOzqF6v80YNhV3TV+M1TteifALMNKvXq6VW3Q7OqUe9Hr3TdibRP4O2QVTRbvP58OKFSvwyCOP4IYbbkD//v3xk5/8BDfccEPvmB/84Ac4c+YMHnjgAXR0dKCsrAx//etfkZaWZto2UgUH58SXOR4A6ql7h11pQLM1zojZUy5Hy6dsK71KhFrrcerV5Ri48F5F4c7alsosERNvWKKdsyb1RAz9Tda5Xd50+Ti8/ckhJvd5OaH2tzerJPuqA0CwM4QLJ/dEP5WiniwLE4IAPP3a5+jHOTCrdAhzVFWv2I4WZKxCVA9VtX5L+4xLwXr+9ESvWe5vETXBLmJk8UUP1L7NGKwP3lZFy7Q+3LFE7qKxIprDet7ijdEFFiNodVAXsUO0zYzIIOu97El34/vr7pddJJNaRMtKk67v1XK/TR9c2mMWOSADQaHTUPstrZkJahk3RGqRyN8hu2BItP/617+Oea20tBQvvfSS7GecTifuvfde3HvvvbJjzNhGKiDwIXQG2wGXekp5F2M9hB76eQsw4MZ74H/nWfDtLeofUMG/fiXchWWyqfIsIs5sERNv5KKYYk332o0HsHbjAXiz1N0k9ZLtTmcS7LddW4IFF46WTIl//SNlF9fNlccxZ8YINLR0YPeBeknBx5563h2RZSFGVUXfg007j8WISr1iO1qQaRGiWlGu0DyL2cKVNSqtJ3otd3/rJRFp6HozDfo6Wh68rYqW6Xm4E+fybMULaOlSNqUDzI/mGE2ltpJEpiPrFd92iLaZERls6WwFB+Va/uz0LMkUelF8XzthrmS/+bZu5aAAy/0muuLndOZhYM4AQ6JZT2aCUsYNkVpQWYTJkXbCXDqO1GBIMIgvXOrGLsM6ratpb9iwCs5sH7KKL0Rrxb8Nby/UUo+OIzVwjSiR3h+jOIl39M1swqOYW6tOYO3GAzEp5iw10r6cTPzwm9PQ3NqJnOwMPP7iZ0wu82s2sBm0ebPSJSOKb28+qGgaB/QsQDz4zCcRc432JNAqyMKzLNR8D7SKbSVBZrYQFfdXOqaA6VokW/20eH+v23gAK9ZW6d5OItPQzayT7ytoffC2Ilqm9+FuxrCpOHfwJPzXm/ehpVO+HYsV0RwzUqmtJFHpyHrEt12ibUYjg6y1/ILK0u+6PRtUtyGF2v1WfnQHVn72Uo852FfdXo2UclDNMqFGXy+LINFuY0KBRowLduMjhrHjLDaiC7XWmyLYe7cXaDz731EO8TnZGUzbSDYRI4WTc2DiaB9+/+Jnurdxx/WTMGVc/95/f/eGUiaRGmC8Z1asrUJGujNGyJ6oV49GRSPlSaA1Gi5mWbS2dzH5HihFTJddW4ycrAxmQWaWEBW5/boSlIwtSNn6aSfnQC7j91mORKehm1Un31fQ8+BtRbRM78NdP2c/3D79W3GP5iSDYElEOrJWvwHAPtE2I5FBlswLDg7cOPEqvLJb+dlMzXFfCbn7jaWUg+VeCTerrDy5m2lOdsiiIKxBybxUpC+XRZBotzFOTx5GB7uRzvM96e9SKfCCgAxBwOh4ucc7OEDgDW/G6ckDIO0Qn+/NQLY7Da0KqdvJKmKkYDWb82alRdQAy0WFRZH6xMs7Fc8hKy1tXREiWFxkaTdwz4VHy/Wknvubglj9lvIf+PB9mBkx1SJEr549CjmeDLy79ZBiinUq1k+L98mRU61M471Z6RGZJZSGnpzYySxI78NdIqI5djpvSpi9wKL2kK7FbyD6+rAIAKuRu5e86R4sm/4N2XuJJfOChwAexp/HlJC631gWFJ6peAF/416KaFcXHYWXqrNXwy5ZFIT5qJmXhtNXyyJItNuYzOFF4DI96McL6HIqGD+p5SibiRmC3etD5vAiWYd4ltTuZBQx4YRnF3zJKGpuu24SCnJcTKJTFKn/99IOfLDtiClzfvaNKvCCgBVvVBlOD4/2JBAXGp585XOmkoD1nyr3EJfaB0sNPCusWR6zS4dg0tgCLJpTqLhgEM/66ejMFivSvaUW45QoyHXh6fvmYO+hBkpDT3LsZhak9+Eu3tEcu523eMD6kC4nfPMzczFn7AUY5BkQc320CACtaF0MmDFsKgRewIrt/+gtu2jpCuC5Ha+Ac3CS82HOqLDw8U/ufmNZUGiV8IUIj8ID0GT8KHL5mNkpGVG1wwJTIrGrCafdINFucw6kCWjvp2BE53CgvZ8TB11pGBOnaLv3vAVoq/kEodb63tecXh88Ey9AoHpTxOtSFMxdCh6cqkN8tjsd6Wlc0phAsYohrYJGpCDHpTlNt2L3SaZxmRlOdIS1Z5PC3xTEb55T76XOSrQnwazSIZg+cRCWPPSOaobArv1+XftQq4FnRWtLMJYU63jUT5t1/Gr70GrYJ/aGpzT05CeVzILiGc1JpfPGgtaHdC2LKFYKAD2LAeVHd+CxT57VNB/WjIrigYX46NAniiJazchODrn7zWiJxt8+W6O7TzFrC7xkwsoFpmTAziacdoNEu40JHq5Gi3CGaWyrM343clZhGXyX34KOIzUIBRrh9OQhc3gRHJwT+Zd+Gx1HatC2rwKBXR+DD551m3d6fSiY29OnfRdDm6vW9i48/N1Z4DiH7aNvrGJIj6ARt6W1HGD3gXomd3gAuOaC0Xj5/S80z8sI0dHqEC9g76EGTBpbgC2VJ0zfh9y5l6qzV8OqlmBW1k+befxysLRrDMfOi3CEfvq6WZBe+sp50/uQzrKIYqUAYF0MCI+a5mRm42865sOaeVHcv1B1sWfBhDmS7vFyeNM9uL3sW7L3m9ESjYaOJt2fTXR5SDRGI+QUYba/CaedINFuY4KHd8ETYktHZx1nHAfSB4+Dg3NKur+Lr7tGlMgKe4Dd+b0p0ImLpw3TNdN4pAED7GIoxAt44uWduvbR1R1CedUJTeKG9Rxnu9NQOq6/KaK9rKgAuZld2FbbgcZW+TT3aE+CTZ8fw1OvVjKlxrMSvg8WMRleA89CMqW0W3H8UrD6MyyaU4gp4/rbdhGOME5fNgsygnjedhytwu4DezBx9ARMHVaSUufNyod0q7bNuhgg8AJW73xZU5221HxYMi8uHzMbW458hjxXDu6edRue2/GK7GLPmPwRWFHxD7R2KxvIejM8+Ms1v0I/p7w80GMOaAZ2Kw8xGiGnCHMPyWDCaRdItNuYM81+KCcsn4V1nHEEHHnyv9D/yu8ia8JMxZFywh5grwnW6xAfjzRgQJsYWrNhr25juNb2sz3KWVOoWc/dNReOxqQx6g7mLPTPdeG8UZmYNH4kHvtnpey48Cj0396swmsfKvd710P4PljEZHQNPAvJktJu1fFHw7pQdM7AbEqF7wP0VbMgo3Ac1yNOTnen5EKHlQ/pVm2bdTFAKg1e73zkMi886VkAENGb3efKxeIpNyE70xOzSFZ+dAee2/GKqmAHgNunf0tRsAPazAHNxE7lIWZEyCnC3EOymHDaAXvc/YQk/bwFOOhKYxrLOs4M+PYWnHp1Odr2bNW9DbEmWAm9DvFi5DtapIiR7y2VxzVvUw5WMbRrvx9rPz5geH9PvPw5lv7yXfz0qc343Quf4adPbcayh9+TPCaWc5ztTseiOeN7072N8tYnR7D7SBAzigfivsVlMfsvyHVFpGF/vP2oIcH+rSsmqO4DYBeTrOPCEVPaL542DJPGFpgu2M24l608/nCsXowjCCL5sfIh3aptWx3lk5vPjGFT8eSCR/DgpXfjBzOXYlHJAgS62hCIMnqrDzbhsU+eRaCrDReMKEPxgMJewf77zc+oikOfK09TKvaMYVNx7YS5cEQVpzvgQGY/5e4q+Zm5yHflMu0H6EnXv3vWbbZJE2eNkPO8cgYsRZh7EDM3lLBblkWioEi7jck8pxgNtWx1SA1KZnUW4V+/Eu7Cst6Udy1YVRMcrzRgEVaRU1XrZ+6LrkRre2z6uFxNMss5vuumyb3nQbGf+TXFWLGWzTX+nc+acMMcQTUKvenzY/jdC/r70zsAtLZ34offnAaH0FNKIRfpTkYxaea9HK/j12rQRxBE38NKp3yrtm1llE9tPmLGCs/z+P66+xW3FZ5OzSIuPelZuHvWbSjuX6i5FluqTl6AgI4zyh2Abj13EQBl93hXv0wEz/T8HVFz2o83ZkXIKcLcQ18z4TQCnQEb4+A4+NPYBDHrODMJtdSj40iN7s+LIpElUsqKljRgM2AVOfFoyvfsG1UIRbX/03qOZ5UOwV8fmIdH75yNH3/7XDx652ysuH8uLpgylDkS39IeQs3hRgDyUegtlcfxm+e2GTovAoA3Nx7Ez/6yBY//czvSvnIflxKwVmZ2aCXEC9hV68dH249iV60/5pqJmHkvx+v4WTI2kr1dI0EQ0vA8j+q6fdh0uALVdftkI40cx2HxlJsUt6X3IV0UAGZvmyUaqBfW+WgRi6zjA11t4BycpvPBuhgQHU0Pj+aLqf/R51RM/RcFu4iYdl5+dAfzPK3CrAg5RZjPInc/aM0ASXUo0m5j+PZmdDC6wrOOM5tQoNHQ582uCY5XGrBIc5t6T/mCXBdKxxRgzYZ9puxTDrmaZK3nWMnBPCPdic4udQeFptZOWfM0rQ7jLKg5oFuV2aEVLfXpZt7LLMe/7JriiOs1fmS+rr7pagZ9M0oGY1et3/YdIQhCC9RnWd2USzxHFcc+x6ZD5ZLbYXXKVzrfVrjwW1HHrXU+WsViIuv7A11t+Nkl/x84Byf7nYg2q8zJzMaT5asVt2sHYzazIuQUYY6EzEvVIdFuY5yePEBgjEWyjjMZpyfP+DZMbHMVzzToEC9gxRtVquOWXVOMkrHmGL2pISfgjJ5jra3qTvjbsezh9yTFqduVZtl5UEoXj6fbuxRaW66ZfS8rHf9FU4bElD9wDiA8CUCL+Z3cQlF51QnZ+4LavhHJSl/vs8xiygUg5hxJccvUharnjOV8WyEAlBYDbpm6MMa9PZr8zFx8f8ZiNHW0oKWzFdkZHnjSs8DzPNO8tIpFq9Kv69vZgjWNwWZcNHKG4phws8rqun1oSAJjNlb3/NaOgOq2+kqbR1bIvFQZEu02JmPoeGTxAhoYxmbJpNhaidPrQ+bworjvV4l41tSytrfK8WQwRTrNwIqabK2RcVcGh5c/iDXdE8VpRrp1pRxqDujxcHuXousMjydf+VxxTPSCgxX3stTxN7d14jfPbYsZG/2TorWfe/RCUTz6xBNEvEnFPstasgZYUqWfrnghxjhNjud2vIoZQ6fK7k/L+bZCACgtBnAOTjFqeuu5i9B+JogXK/+la4FHa72+VfX9rZ3qYlTLOJFkMWbjOA63TP0aHt+yQnHc6p2v4LxhU1QXZCjCTLBCd4SNaT+4C/ndbM3cWMeZScHcpTEmdAIfQvBwFQLVGxE8XAWBj++84llTqzV9Wa6+nJVMFbFbkOvC+JH5TPXSWmBdnOhFZZcs6fVGULsuVrq9S7Gl8jhu/cU7qj3oo+vTrbqXw49/4mgfU7ZIOFLeCWqwmuqZcb8SRLwwy0XaTpQf3YHvr7sfD33wOP64dSUe+uBxfH/d/bK1xKyp0qyE12RHw3K+n932Ij4+VK5YU28UcTEg3KUdUK/LBSDp5M5ar621Xl9vfb+aN4E3I1txm1rHiSSTMRvLsSndy9HI3VMEEQ5F2m1My6dvYnDnGSjH53oY3HnG8vmIOLN9KJi3NKZPe9uerfC/txKh1nrVsVaiNQ1arvZaDT3py+GRzs2Vx/HvzQeZtnHvt89Fv36cYqT+oilDcMej63WlHiudAy31/5npTgRNFuXZ7jRN/e3t5ACvtawg+lxbndKveUEG+vq5x6tPPEHEk1Trs6wna8CKqKfcNlnOd0tnAE+UrwKQmBIFuagpAE3O70rb15JOrXU8S+lBvjtX8ThEWMeJWNlVwGySJSuASC1ItNsYvqMN3hDbSjHrOMM40+Cbu0RSsJ96dXnM8FBrPU69uhwDF94bd+HOkgatxRgsGpb05RxPOsaPzI94LTxtmEW0f3NeIS6aNgwAFGuSpfqdK6Uei0J9a9UJfLj9CFrazgrj8HOgRQR3mCjYRWEKgFn42qmdmB7DPalzbWVKv15DRq2fi7dBJEHEg1R6cGfNGogWlVZEPeW2qfU8JqpEQSotv7pun2kLPFrTqVnHsy7aWCWutRqzJdL8MZmyAojUgUS7jUkfMhY5NV8yjc2Jl2gPdaPutd/DsZDrFeECH4L/vZWKHzPS010vauZrajW2/3PLdFwweaji9tXq1JsDXbjj0fW9Ajg8op3ryVAV/dnudHx97oTef0sJuPEj83HHo7H9UsOJrpeWWqyQOgf3LS7DjJLBcTHRAwBXRj/MPe8czCwZHCFMpRYrpLBTOzGtUWypBR4RM80aw9GblaD1c/E0iCSIeJFKD+56swZYTblYURJ7es+jHRzHzV7g0VqvrzZe66LN7BFlkn3aRWaPmK7rfLNkBvA8j9dq3sZb+/6DQFd72Jj4ZVbEOyugr3enIHog0W5jfJcvxojt78IhCD1lwg4JMSIIcAAYEWRPHzaDcBHecaQmIiVeCrGnu2tESZxmqAxLFHT589sAAbhgirxwl0tfDkcUwDdeMgYf7TgWMc7jTlOcw103TY4RodECbletX1PqsZaUbVHsx8NEDwDuX3IeJhf2j3k9fLGiJzPgaESNeLwc4LWgNWrcHOjC7Y+8h+/eUBq342DJFolGTzZDPA0iCSJexOvBPR4P7HpFJUt01JOexVzXrtTiSu8CgR1KFOy+wKNl0aaoYCw2H1Z+Hth8eBu+Nel63cJdLjOg/OgOPF3x9wixfnZ+8cusiGe7tr7enYI4Cy3T2BhnegZOjC2B4HBIC3YAcDggOBw45FIWf2YjinCAvVe70Z7uZsISBeUF4DfPb8OWyuOK42aVDsEzP50Lb5byNXjtw/0x+wx8VaudHSXeC3JdzG7aWlKPtaZsi2LfqIkeCwW5LpQoRJPFxYrbr5+E534+H4/eORs//va5ePTO2Vhx/1ymcxXiBdON+uT2ceRUq+bPNrR04lerK1TvObNgMbuLRq/5XbwMIgn7oWZslazoNfrSwrYTlZqM4fRiRFSqGbB9t+zbqtsVxyqJEJbzLUeiSxTEBQclElmvrWXRRovA14uUMZuYvi8l2MOJl/mj2n1vhqAWj1mveSGRWlCk3eYc6j8AOF2nOm6/Kw1j4xxtF0U4a692M3q6m4WWKKgYbQYgW1e891BDRE24VtLTnPjlf5WhubVTc82yltRjPcZj4e73M0oGY93GA1ixVt1x3JuVHhENz3ano7Vd3kFdi2jTky5uxL/AyD708MTLn8v2mzcbuWyR6D7tRrMZrDbVI+xJqkeJrOyzvDdwEK/Xvh/zuhURRaNZA2p101LnyJvhwQUjzkPZ0MnM2QNy51uNRJcoxDMyqwctizaJ8HJgSd8XiWdmhZXt2vT6TBCpC4l2GyPwIRw/uB3wpKuObewXv1pxEVGEZw4vgjPbp5gib7ee7lpqZ/1NQazZsBfvbj0sK/iMGmjVN3fA6XDg4q8M57SgJfV4085jmrcffq6cnAMLLhyNf31Uq7g/X04GnvnpPNQcqEflfj8cAErGFiDQ1oUVa6viLtri0SNcq1O8Eq3tXaiq9UuWCliBnFfC3kMNpprfWWmqR9iPVOxhLoUVD+68wOP901sVx5j5wG6GqFSqmzbzHInbeq3mbaypWqc6Pp4RbKVSBisXeIyiZdGGNYJu5kIJS3Q/nHhmVmj1F2Al1bpTEMYh0W5jgoerkdPVBUBdtOeeiXM/9DAR7uCcKJi3VNI9XkSqp7sW9LZlk0NrLe+L7+6NeS1c8JlhoKVX+LMY4olRbK3zDK8zDr8GV8wciRff3SP7ucVXjse23ScjoqovbdgHX04mbruuBDlZGXETbaw9wo1EtvU4xatRuV+faNf7XZHKXrDC/M4qUz3CXqRClEhLLbnZD+576w+gNaRcB272A7vVotLsc/T+/k1M4+IVwWbJKlFavEik2ZiWRZtEtGbTKsITnVlhBqnUnYIwBxLtNqbjcDVGMqa8s44zi2gRnjVhJgYuvDe2T7vXh4K5xvq0W5HWzCJ0WXn2jSo8fd8cww7rRoQ/a+rxxNE+5Hsz0NDSybRdUexLXQOPOw0OIKKHui8nA5eXegBIt2mrb+7Ab57bhvsWl+nKKtBDPHqEs5YdzCwZhI7OM9j5hV91rJ7lg3iUABAEC8keJUp0Wn9zZwvTOLMf2K1M99WCmoBljbwuKlkQl+ulJatEavEi0fcbwL5ok4hUfy0i3C693I3CeszNHS3ged62i5+EeZBotzUC6tLZLlFdej9MiINwVxLhWRNmwl1Y1uMmH2iE05OHzOFFhiLsVqY1zyodgv+5ZTqWP78NRvzI/E1B7D3UYGgRQItzthhJ9TcH0RLogjcrHQW5LswoGayaelxedQLdZ9QNWsLFvtw1EE30vnXFeAwp8CDfm4lRg1yoqanBE2/FZiaEYzSyrYV49Ahn/ezWqpPM21Qy5ZMiHiUABMFKMkeJ7JDWn5PhZRpnRUTRqnRfVlgELOt9M8gzwIopRmA0q8QO95sI66KNKPBXfvYSGjvOXgurUv21dA5YPOVrTALW7m3UWI959c5XsG7vhpTxCSHkIdFuYzKGT0TD3neZxjakWVvT7p0+H1kTzlcV4Q7OaVpbt3ikNV8weSjwlUu8ERpaOnDxtGG4b3EZ/vTyzl5BywqrCZuS0ZlaRFWt5tqd2Q9zyiJ7pLNcg/fKv8SK++fCyTnQ3t6Ow6c7VSP5LJFts0oi4tEj3Oz+4tnudEwaE3tu5M5JPL4rBKEFu7e4ksPKtH4tImG8bzSynVmKKfKpElEMh1XAWnF/6RVxRrJKEllGIne8rIs2M4ZNRXHeOKzf/gFyBuVhYM4Ay4QvS3RfZPXOl+HgHIoC1g6ZDWpoOeZU8wkhpCHRbmds9GydNeH8uPdYj0daM9DTh53jHJKp5fNmjFCs3RYRRdus0iHIykzDA09vYdq3FhM2NdGtFFFlEXXuzH5Yem3k4oGeaxAIsrVa2Vp1Qva6mZnmzeJf4M1Kx/iR+Zq2q3UfWrjrpskx4lrpnGS70+PyXSEIVhJR92oGVqX1axUJnIPD5f1n4vWTse7xIol0G7cCLQLW7PvLiIgzklWSqDISs0Qr5+BwjnsIioYWwe12mzY/KVg7B6gJWDtlNqihtVuC3X1CCGPQVbUxnV/WYGgHW8SWdZweuOz8hDi/xyOtWWRW6RD89YF5Mb2/F80pVO1NHp3aXjK2QPUz2e40PPzdWZr6i7ManT37RlVM/3E28d2B3QciOwDouQZZGWw/K2s3HpDsRy4uTkTPV1yU2PS5Ngd8lh7hLW1duOPR9br7o+vpdy5FQW6m5KKL2jnZWnWCaftmfFcIgoV49DC3AivS+vX2Wh7vGYW7pi+2tA+0ndAiYM28v4z2wjYS9a849jnTZ80sI0nm3t8zhk3Fkwsewc8u+f/gSVdeJJDq134mdAbPbntR8+cSiXjMi6d8TXWs+P0gUhOKtNuYUOgMgk62BxrWcXroP2+Zobp0vcQjrTkcOVdrVmf28O2ofeaum6ZocgbX0l9dKqKqdwFEzzUQHOwGAdEp2yyLE8uf3waeF5CXncmcOi9n1BcOS+23Uso+yz6k+PqcQgwfmC17HCzn5KMdR5n2ZXYaP0EoYecWV3KYnXZtNP15+uBSXDDqPFvX3pqF1gWTGcOm4kfn344V2/+Bls5A7/ta7i8z0tP1Rv3Lj+7AW/v+ozpHwLwyklTo6sBxHDgHh0BXu+K46AyF8qM78GzFC2jpim9XBjPgOA45mWw+F3b0CSHMgUS7jen2H0HQyZYjzzpODkd6JoSuSKHBuTzof9WdhpzfjaCl/7iVsDqzG/2MElojpGaIb0DfNWjvYBft0QsMLIsTvAAs//tnEa+xpM7PKh2C6RMH4dZfvIuWti7ZcU+8vBNZmWkoGVsQIaBZUvbFPuTrNh7AirVVischMnlcf8WUdZZz0hzogjcrDS1t8hk38fiuEEQ0dnEjZ8XstGsz0p/jZQyXaGMurQsm5Ud3YPXOlyMEuzc9C7dMXci8IGTW9dHqps4inkXMLCOxW1cHvfec1gUeuZR4o9uPJ8nqE0KYB4l2GxNqbYjbvgZ+7X8A9LSZAwRkjiiBa0RxQiLsIlr6j1uNKMa0GKPp+YwcWiOkZohvQN818Li0PeRt/iolfeJon+70bVaH9L2HGhQFO9DTwu6Bp7dECHItzuxOzoHc7AymeWe701SFNOs5uWTacKzdeED2/Xh9VwgimkS7kWvB7HZWyeKibwdjrqKCsfCkZyGgEAnNTs9CUcFYWRHW0tWGx7esADebY5q3WddHa1YJa8s6wNwyEjvdj0buOS0CVssCidbtx5Nk9QkhzINEu43huzrgYuxF5grp71nm9Pp6Bbp7VKnu7ViB2RFrI8ilz5v9GSm0GJ2ZJb71MqJ/hqZe8P/efBD/3nwQvpxMXDFzhKF9qzmka1kUEAX5/3xnumrUPHq/rIss11w4RvWcs25rZslgFI/22eK7QhDJjJlp/ckQHbOXMZfys4wAgBfMS/E28/poySphFcVXFV5m6rm3y/1o9J7TImC1LJCEf85umL2gSCQfJNptjCPTAw9jtN0T6jHN4IWzpvMORv1VMHdpQiPqapgZsU5WWES3iJz41rMAoqeVGMc5sOSq8Xjsn5Wqcw2nvrkDL767F9nuNLRqbJknouaQrqem+6nXKlWj89H7ZVlkyXanY9Ec9eijliwJJ+fo898VgjADs9L67R4ds1ONc42/VrVOOdDVhndrPzItxdvs68OaVcIqisuGTmYaxwpr7++WzlZT9xuOGfecFgGrNWvAzsI3GX1CCPMg0W5j0vMHIafpENPYnK9EO+cA3mqfjPMzvkCe8+wfP86VDSF0BkJXsPc1p9eHgrlLE1azrgWzItbJjJrRGUtEVesCiN62ezOKB+K+xWV44uWdOgS4MYEpFU0XDeT8TUF4s9JVRXg4rGP9TWHfLSYzwti2blJozZKg7wpBmFOfbUZav92jY3aqcWYVVycDp03bXqKuT6IWcziOw+IpN+GxT55VHPfcjlcxY+hUxeMWv2O7W/cD/jRMHVZieV/7cFgFLOsCiTfDg9unf8v2wjfZfEII8yDRbmOyJ12CUdUbkdMdQnM/Tjp0LgjIOcNjVPCsMDrNe/FQ840Y068OQz0h3HnzhXCPmAgA6DhSg1CgEU5PHjKHF9k6wm4GSm7fyUi46PY3B9ES6II3Kz0i0iqF3vNgpO2eONc1G/Zi7ccHEAiyiffW9i58c+54vLRhLxirQyKIjqZLGchZwYq1VchId0aY0plV2mGnMhGCsDt2qM8Ox87RMTvVOLOKq0Eets4rrNtLxPVJ5GJOVoZ6P3U10Rz9HXvz1Adx6WsfDYuAZVkg8aZ78JdrfoV+zuSQRUoLiok2lCSsIznuzj6Ke9QkcFw/XOMP4O+DvIAgRAp3oUfRXOMPIPzr2J9rgQAOtWcG4aZrzwXHNaGtZkufEeoiLG7fyYiTc2DiaB92H6gH53CoinAj58Fo2z0n58A3503AojnjsftAPTZXHse/Nx9U3V5bRzfuvXk6fvP8Nqb9i0TX88sZyGmFJTrf0tYVY0pnZmkHlYkQhDr2qs8+i12jY3apcQbYo89XjL0Y6/ZuMDVKnYjrk4jFgvKjO/B0xd+ZxsqJZqPfMbPvObWMGJYFktvLvpU0gl0Juy1YEuaS/HdoisNlZKKkLYCLmtrxcW7s6uhFTe0oaTtr+CUIwPkZ+1CfOQw3jmlD9n9ex4n2lt73ndk+FMxLjpR4I2hx+042WEV4iBewZsM+vPjunphtsJ4HlnpqX06mqgN6eMo2i2hfu/EAikf7NPc9D08TZ6nH92algeehmAVQkOvCsmuL8Zvn2BYQomv8zUxXp9R3gpDHTvXZUtjRRd9ONfes0ed+zn6WRKkTcX3iuVigte2ZlGhOZF97I9g528Us7LpgSZgH5UvYmI4jNeCDAVRlZUgKdgD4ONeNqqyz7aUcDiDPGcR3uH8j6+CH4MMEOwCEWutx6tXlaNuz1dK5JxJW87SQntzrBCMuRkSLWFGEb/mqfdqWyuNY+st3JQV7OGrnQaynVqKrO4TyqhNM8xcXAVgQxe9fH5iHR++cjR9/+1w8euds/M93psdsoyDXFbMAwVKP39LWjWsvGqM45vbrSnDB5KG4b3EZvFlpqvMWa/wJgogvWmpliR5EoaxEPGvuRXHlSY995vGkZ8WM87lyI8b4XHlJJ07ExYILRpSheEChJedaa9szOdFsxncsUffcjGFT8eSCR/DgpXfjBzOX4sFL78aTCx5OqntFDtbFFJ7n4zQjwgoo0m5jQoFG8ABe6+/peSG6pt3hAAQBr/X3YGJbp6YVGP/6lXAXlqVkqrxe8zS7w7oYwfMCc1o5y3kQ66n/9PJOBCRM5Vrbu3uj9lPG5iruT4sLfvjcoud3fukQ1TRx1nr8IQVZTPXis0qHoLM7hMde3K66Tb395gmC0I+d6rOTCTtGIaVc5ANdbRERQ7uWHNgRrW3PLh8z21CrOrP72puFHbNdzMBOhpKEdZBotzFOTx72u9LQ3k9BWDscaO/nxH5XGsYxGn0BQKilHh1HauAaUWLCTO2FEfM0O8O6GPHUa59r2u7n/397dx7eZJnuD/ybpGmbNt0LFCxLoXahLdBCWWRXZFwYFVDnODKjAsqZ49Ezo6AzPz2OjsfRM6A4bgcdNh11BKcMyqjjMjOuLFJ2aFhKgQGhLd23pEvy/v6oCU2b5UnyJnmTfj/XNdfY5MmbJ8nT0PtZ7vvERbdnoyflD8ZrWw+hBc7H2B/eO4wXfzHV7fNdMWYIbpg+Eu9/VeG2rbPPSGSbuCfn8QsyU4XOi6cm6ISvSUSBpaTz2aFGKQGwp9uvwzUIk5unE1Vp+oEObw9WXXtyjROW/QODdgWLHpqLU/F6obYVHgbtQPdKfjjyNXmaUolOMjS1ejYONn12HJ/t/pfLxHSiEwYf7fwXWhvbYImuQ1GuzulEwOT8wUJBuy+fkSf1zQGxiQBPr0lEgaOk89mhSAkBMFcM/cPTiSpn7YNV197fQj3jOics+wfZR2RVVRWys7P7/G/Lli0AAIPBgEWLFmHcuHG48sor8cYbb9g93mKx4IUXXsD06dMxbtw43H333Th79qxdG3fXCBcqtQYxo/y3LU2jT/LbtYNJ5Nx0KAZW/pxk6H0mvjfRCYM3PjqOku11+M36PVjyP584vV4gPiOR8/g9E9cF65pEJA+lnc8mz3HF0D+swbYIV0F3OP6O7Tq3D/f+9RE88c/VeGHnejzxz9W496+PYNe5fcHumjCRz5cTlqFP9t+qo0ePIioqCl999RW+/vpr2/+uu+461NfX46677sKwYcNQUlKCe++9F6tWrUJJSYnt8a+88grefvttPPnkk3jnnXdgsViwdOlSdHR0l1sSuUY4yYlNE2qX4eEquyY+BdFDc73pkuKFa2AlEugm6CN9eg5niem8mTBwNREQqM/Ieh5fJHFdMK9JRPIIpwRl/RFXDP1DJNi2chd0h9PvmDXjeu+dA9aM66ESuIfjZAr1Jfv2+OPHj2PEiBEYOLDveZjXX38dWq0Wv/nNbxAREYFRo0bhzJkzeO2117Bw4UJ0dHRg/fr1WL58OWbNmgUAWL16NaZPn45PPvkE8+bNw+bNm11eI5xIFjOa9nwMJLtPFudpaJN69eKwTEJnZQ2s3CUXCyUiSdz+fcEYrH3vsHCJtN6cJaYT2RbuTO8SaFaB+oz8Ud+cNdOJlItnZUMXjzj4j7Pkb1aeJIGz/o7tO3cYZRVHMXpkDgrT80Pqd0zpJSI9pcSEkiQv2YP2Y8eOYdQoxyWUSktLMXHiREREXHrayZMn49VXX0VNTQ3Onz+P1tZWTJkyxXZ/fHw8Ro8ejd27d2PevHlur5GaGjrZwN0xnTWgqaMFgPsZ5VaN2BeKJj4FqVeHf512QP7AymyRgh6kiQS6apVKKDu7M462wnuS9b03VxnqAxX8+qO+OWumEymXUs7KkmdEa7WHQhClRD0ntOraGtDU3oy4KD1SYpI8nthSq9XdkycXO0NyUiyQ+RMCdWaeE5bhzS8r7UlJSbj99ttx6tQpDB8+HD/72c8wY8YMVFZWIivLfuBbV+QvXLiAyspKAMDgwYP7tLHe5+4a3gbtkiShra1viZFgMtZWIc4sVlOxZzuVLg6SsfnSz9Fx0OVegahR4xF5WTZUarXiXqs/jRoSg1FDumu+tpuMXl1j15EqbPzwGOqa2m23JcdH4c7rsjEpb5As/RQ1LjMRLz0wDYYz9WhobkdiXBRyhydBrVahra0N4zIT8cC/jenT3/hYrVCSupgoOBwfzq4rorKm0fYZOCLHZ0Qkymg02v0/kdL05zFakJyN/5xwB946vBX1pktn15OjE/Hj/BtRkJzdr/6G8YcMfToy9Ol2t5lMnu+kC+VxWtVYLdyu93vlidILB/uM5aToBNyefxMmDB7j9XVd6fn5evO5hpNQGKOSJEHVu6y3A7IG7V1dXaioqEBmZiZ++ctfQq/X44MPPsA999yDDRs2wGQyITLS/sxtVFQUAKC9vd32hjpq09jYPdjdXcNbnZ2dMBgMXj/eHyJqG5Fh7ERCpxmNEeq+ddoBQJKQ0GVBhrETEgApOh6N0/8dEfXfQdXeAilKj67koYBKDbQAOHYs0C8j5JWdNWLzV7V9bq9rasdz7xzErdNTMHqoWCkwOakBJGsBmIBjx6rs7tNDwvUT9DhTFQkJQMbAKAwbEIkX/lqFpjaz02vGx2iAtkoYDFWO71cD/3ldKs5cbEeL0YIWUxc+3tvktq+NdZUwGBrEXxxRAJw+fTrYXSByqb+O0VhosfSyhThnrESL2Qi9Rod0XRrUDWoYGpT1txqF5jhtbBOroNRYWQ9Dk3dj7ljLKWyt/Huf2+tNjXip9HXclHYVsvUZXl2bPKP0Mdo7tnVE1qA9IiICu3btgkajQXR0d5Km/Px8nDhxAuvWrUN0dLQtoZyVNdCOiYmxPaajo8P239Y2Ol13UOTuGt7SarXIzFTWGSnJko2Lho/ww5oWvJkWD0iSfeAudScM+2FNiy2jYNKcOzHk8gIArpN8kRiLRcILf/3KZZu/H2zB/DmFUCvkPLOjXQFHznbgzuuysfSGVDz3zkGnj116Qx7yBHYO5H3//xaLhN3lX7lceU9JiMI1M8Yp5v0hMhqNOH36NEaMGGH7t4VISThGu+XZ/rUhJQrlcZotZeNvdd/YrYD3lhydiKuLZkOt8nx7uUWy4LXP3nXZ5suGPbhhwjVeXZ/EhMIYLS8vF2on+/b42NjYPrddfvnl+Prrr5GWlobqavvtKNafBw0ahK6uLtttw4YNs2uTnZ0NAG6v4S2VSuVT0O8vpvzpwKG/CbVNmvEjJI2d6ece9S+HymvcbgWvbWzHqUqjIs43bz943mFQbt0V8Ks7imVP/rZs/hiXZ93vuWkM9Pq+3wtEwabT6RT5vU9kxTFKoSBUx+ni8T9ymT/hrvG3Qh+r9+raR6qPu5wQAIA6UwPOtJ5n/o0AUPIYFdkaD8hc8u3EiRMoKirCrl277G4/fPgwMjMzUVxcjD179sBsvrQ9d+fOncjIyEBKSgpycnKg1+vtHt/U1ISysjIUFxcDgNtrhBPJYkbTka+xLfX7L4zeH+r3P29L1cMCQJtsnwuAfCdan1y0nT+ZLRJe23rIZRtrJvd1j87Fb382FctvH4/f/mwq1j5ytdfZ2lkCjYiIiEKNP8vX1RtdB+yetiOSdaV91KhRGDlyJH7zm9/giSeeQFJSEjZv3oz9+/ejpKQEKSkpWLt2LR555BEsXboUBw8exMaNG/HEE08A6N7Pv2jRIqxatQrJycm47LLLsHLlSqSlpWHu3LkAgIULF7q8RjgxnTWgvKsJjdok541UKjRqNTil0+IyvYt25BXR+uTe1DGXW1lFrduSbD0zucu5M8CaBX6v4TscOXoKeTkZKMq9jCXQiIiISLH8lXE9See+8pMn7YhkDdrVajXWrFmDZ599Fj//+c/R1NSE0aNHY8OGDbaM72vXrsVTTz2F+fPnY8CAAXjooYcwf/582zXuv/9+dHV14dFHH4XJZEJxcTHWrVsHrVYLALbA39U1woW5pR7NgqXcWvUJiB6a6+ce9T8i9clTE3UYPTL4uzyCvStAo1YhLyMZalMVcjOSGbATERGR4vmjRGRuaiZSdIkuy8ql6LpL7RGJkP1Me2pqKp5++mmn948ZMwabNm1yer9Go8GKFSuwYsUKr68RLjT6JOGSb0OLroVKrfFzj/ofkfrkd9+Yr4gANZR2BRARERGFK7VajTuLbnV5Zv7OoltYQ52EcaQoWPTQXGRGxCOh02zLFN+HJCFZG4PCohsC27l+JFTObDe2tMPd3IEnuwLMFgmHymvwxd5zOFReA7PFyRgkIiIiIjvWM/PJfjgzT/2P7CvtJB+VWoP4vGkYe+IzfJkY47jkm0qFqRlTOFPnIbNFQllFLeqaTEiOj8bokSkuV8utZ7Y9eUwgbT94Hv/7x1K37WaMGyLU5+0Hz/fJMJ+SEI17bipQzCQFERERkeL1WniTJLFdtOQdi8Viy1GgU0XBEibvN4N2BZMsZjTs/Rill7nIHi9J+PvRz3BT9BDE5V4R+E6GIG8DUo1apYiybr2JZI232vL5SWQPT3b5OrcfPO/wOEBtowlPv75bUbsLiIiIiJRo17l9DrfH15ka8ew3r3G13Q92nduHjXs32+USiNPE4o6kmzFj1OTgdUwGXJ5VsLZTh3BSY0abRt03YLdSqdCmVmHHRy+g9ejOwHYwBFkD0t6J5awB6faD54PUM++JZI3v6Q/vHXa61V20bBy3yhMRERE5ZrFYsHHvZpdtNu59FxZLeKwCK4F1kqR38r9mcyteKn0du87tC07HZMKgXcFaDn+BkzqtUNuTOi1qPl0PyWJ237ifCteA1NNs8Nayb454UjaOiIiIiPoy1JS7zBwPALXGehhqygPToTDXHyZJGLQrmNThWTBmbqqF6azBT70JfeEakHqTDd5ZoB/ssnFEREREoa7e2ChrO3KtP0ySMGhXsKihuRhp7BRqa21nPHWIq+1OhGtAaq0l7wlngT7LxhERERH5JkmXIGs7cq0/TJIwaFewhAnXYpSxCzFdrku+xXSZMer7oL3hmz/jXy/9jOfbHQjXgNRaS16Uq7JvIhMAnpSNIyIiIupvclMzkdKr1FtvKbok5KZmBqZDYa4/TJIwaFcwdYQWSZNvwITm71d+ewfu3/88odlk90Gam2tRVbKSgXsvjS3tbtuEQkDqqH66s1ryjtx9Y77Tsm8iEwCuHk9ERETU36nVatxZdKvLNncW3cKSzTLpD5MkLPmmcEmzF+FgzbeA1OW05NsBfTSuqW3tMwNT8+l6xGQVQ6XWBKy/SmW2SFj7/mG37ZbckKfogNRduTprLfmdhy/g873n0NTaYWuXmqjD3Tfmuy3XZp0A6P08oo8nIiIi6u8mpRfiwan39ClBlqJLwp1Ft7Dcm4yskySOSuxZhfokCYN2hdu39300wOyy5FujVoNTOq1ti7yVNTGdbnh+AHqqbKJl0RJiowLQG++I1k8vyExFQWYqFt+Qj7KKWtQ1mZAcH43RI1OEJyR6TgB483giIiKi/m5SeiGKh4yFoaYc9cZGJOkSkJuaGdLBo1I5mySJi4jFHeNuDvlJEgbtCiZZzDiz9yMgwf0vdqPGcRtzS73c3QpJoZ6ETrRc3aT8wbbAWqNWoSAz1evn9PXxRERERP2dWq1G3sCsYHejX+g9SaJTRcFS3Y68wXnB7prPOM2jYKazBjR3tAq1bXUStGv0SXJ2KWSFehK6cC1XR0REREQkF+skybThxd27GlThEe6Gx6sIU+aWeujNFqG2jtpp4lMQPTRX7m6FpFDPih7qOwWIiIiIiMg7DNoVTKNPQrxg0O6oXerVi5mE7nuhnhU91HcKEBERERGRdxi0K1j00FxkRsQjodN1nfYEs4SMHknoNPEpGLRwBWJzJgeop4HnqOyZO87KoqUm6mxJ3JQq1HcKEBEREfVksVhwpPo4vj6zG0eqj8NiEVuoIuqPmIhOwVRqDQbOXYwf/u0FvJkW3x2498wi//3PS6YtxWVTo2BuqYdGn4TooblhvcLuruyZK6GaFd26U8BR9ngrJe8UICIiIrLadW6fg1Joibiz6NaQz/JN5A9caQ8B+a3tWFTZhIQu+xnIhC4L7h0+C5OHjYdueD70edOhG54f9gH706/v7pOUzVr2bPvB826vYc2KPrMoHQWZqSET6IbyTgEiIiIioDtgf/ab1+wCdgCoNTbg2W9ew65z+4LTMSIF40q7gkkWM2o+WQ+gO3Af3dqOUzotmjVqxJktyDB2Qlv/d0gTbw7rQN3Km7Jn4SZUdwoQERERWSwWbNy72WWbjXvfRfGQsaxlTtQDg3YFM501wNx8qYSXGsCoHmfXAcDcVAvTWQN0w/MD3LvA86TsWTjXF2f9dCIiIgpFhpryPivsvdUa62GoKWdtc6IeGLQrmLmlXtZ2oU6usmeSxdw9IRKAHACBfC5/M1skn1f45bgGERERhaZ6Y6Os7eRgsVhgqClHvbERSbqE7treXOWXFd9j3zFoVzCNPsnuZwvQZ3u82kG7UOcssJOj7Fnr0Z2o+WS9/Q6GaD3iJ16PpKkLZQ2oHT2XJi4FqXMX+yWzvz8DYl+S/8l5DSIiIgocuYOtJF2CrO18xYR4/sf3WB4M2hUsemguNHEpMDfX4nBsFLal6tGovRRUJnSacWMbkDE0N4i9lJerwG5S/mCkJES73CLvquxZ69GdqCpZ2ed2i6kFDV9uQtO3H2DA9T+TJaB29lzm5lpUlayUvSSfPwNia/K/3qzJ/0SS4MlxDSIiIgocfwRbuamZSNElutwin6JLQm5qplfX94Q1IV5v1oR4D069h0Glj/gey4f7EhRMpdZAnzcNh2Oj8GZaPBoj7D+uxgg13kjQ4NvzB4PUQ3m5ywy/6/AF3HNTgctrOCt71jOpnzMWUwuqSlai9ehOzzvv4XPVfLoeksXs0XWd1aaXI6O+q+cUSf5n7Yu/rkFERBTulFS33F8Z3tVqNe4sutVlmzuLbvH71mnRhHisHe89vsfy4kq7gkkWM5qOfI1tqfruG1S9glGVCpAkbNy7GcVDxkIFKWTPavcM7FSwYFRENeLVRjRZdDjZNRAS1PjDe4ex9pGr8as7ivusKqcm6nD3jflOV2t7J/VzpebT9YjJKvb69Yg8l6cJBJ2tpC+9IR9r3z/s8rG+ZNSXI/lfIBMIOjsiwLP0FAhKGWehdnYw1PpL5I8xq6QtxKLB1sqr/p9X15+UXogHp97j4PUm4c6iWwLyepkQz//4HsuLQbuCmc4aUN7VhEatizPrKhVqjQ3Yt/d9pG7/MCDnp/1xVtsa2I3RnsGCmN1I0rTZ7qs3x2BLWzEONgxHWUWtV2XPWo/33ZrtjK8Z+eVOIOhqa/n//rHU7eN9CYjlSP4nVwJBd5xNbMwsvAxf7PuOZ+nJr5SSs0FJf/iLCLX+EvljzCptC7FosHWstsLr55iUXojiIWODNmGnxIR44Ybvsbw4la1g5pZ6NGvEPqIz32zus7prPT/t63bvnqxntZ09V4thO4xnDqPlyFcwnjksvAW8rqk7YF+s/wKJ6ja7+xLVbVis/wJjtGdsgZ217NnMonQUZKa6DNglixkth7706HX6kpFfNDGgSDuRreUivA2I5Uj+J8c13HF1RGDL5ye9Ojrg7DgCUW/+PKLiCX9tZ/WXUOsv+Y+StoW74o8xq8QtxKJBVGN7k0/Po1arkTcwC9OGFyNvYFZAd9goLSFeOOJ7LC+utCuYRp+EOLPYl7Srdtbt3gB82tJu6erExQ9fddmm+i+rAelSX9ytwFu32Q+oO4NbY7onF5ycAsCCmN2I1P+bcH+tTGcNsBg9+4fFl4z8PRMIOr1+fAqiBRIIimwtF5EQF4VD5TUeb9sdPTLFp+R/cl3DFV8mNhwdHTBbJGz+7Dje/+okWto6bbdzdZ4cEc3Z4O0RFVGif/gXDxmriK3nodZf8p9Q2W3hrzHrzy3E3m7jFw2iEqLiAXS6beePPvpKSQnxwhXfY3kxaFew6KG5yIyIR0KnuTsJXe9oFgAkCQld3eXfnDE31aLhmxI07fusz5b2lKvvhCYm3m0g33p0Jy5+9Kr74FeynzywrsAnzvhRn5JqPbfZRwOIdjF/oFIBSZo2DNJWARjoug+9eLpqLhpQO6NSa5A6d7HD7PFWqVcvFpow8XXLOADExURi9dt7UNfUbrtNNADVqFW456YCh9vzrZwl/5PzGq74MrHR++jA9oPn8eK7++2CdSs5Mt0r5cyzv8j9+kLh/QpkzgZXQu3sYKj11x+UeJY/0H0S2RYezC3UPflrzPprC7EvkyGiwVZ2ykgcu3jMo37J1UdfWRPiORp/VoFIiBfO+B7Li0G7gqnUGgycuxhjP38FXybGdC839wzcv/95bIvJ7TmH+i839bnN3FyL6i3P2t3maGXcWfkyTzR8uQmN336IAdfdA33uFV5fU2pr8Pgxnq6aiwbUrsTmTMaghSv6nv2PT0Hq1e7P/luDlbNVzT71AwCa2zr63OaPUmtmi4Qjp+pw5HQbLNF1KMrV2QKsSfmD8eMfZOP9LyvQ0mOCyV0CQRG+TmxYH+8sd0Bv3q6aBurMc7CS8cn9+pRyRtydQOVscMYaZO08u1eovVLODvb3s45KW122WCzYYvgIHx7/B1o6Lh1R82efRFauX9v9FjaoN6HOdGkciPZJdAJCtJ3oWKxtq8eR6uPCkwz+2ELs6xl54WBL5X2wpYRz/EpIiGelxEk8OSjpPQ51DNoVTpc1EYfK3gU6Wp3uGz+gj8Y1ta2yJCiwroxHjxwHff40ROhT3JYvEyWZmlG95VmYJp1Ay5GvvbqGN9vWRbarA/In7ovNmYyYrGKPjyQ4Cla8oVYBkVoNTB3O8wq4C0A7uix4+c/7XT7PH947jC6zBWu2HEBzWxcAoGR7HZLjD2PZ/DEA0Of16GO0mDdtJPJGpqCxuR2HymtcBpGuAk5fzsJbH+/JFntvVk0DVac+WMn45H59gXq/5BCInA3OOAr83FHK2cH+fNZRJFgpSM4OaH9e3f2mXbDuqE9y/3EtsnLd3NHqtE+T0wtx9agZDs9Ci06KeDJ5IjoW39j/ZzS1t7i9npXIqrZeGwuLxQKLxdLntfYO9i5PHoE/lL7tso8i2/itwdaGvZtR5yTYamvrO2ZEKOl4TLAT4gHKmsTzx+SBEt7jcMCgXeEMNeWo72xzvDUeAFQqNGo1OKXTYpSLLfKeMlXsh6liv2zX66lp1/tePc7bbesi29WTZvwIib2278tBpdZ4lIVedLVXhEWCy4AdcB2Abj94Hi//+QCaWl2Pq5oGI1a+uafP7XVN7U5fS0tbJ975xH5LnbMg0tWK66T8wTBLEvQ6rd0Kvii1Cmhsbfd4i70nq6aBOvPsKtDd8vlJh7fLEQDL/fr8cb3eEz5y8nfOBmecBX6uKOnsYH896+jvUlqeEh1H/gigfN1FsfPcPuw8tw/6yFgsK77dFtyIruB6stJrDZj12hi0dLoOVHsG7M6u15PIqnZLZyue/OL3fQI5R8GeCipIcJ041aNt/JLU60ffE+Ip7XiMNSGet3wJdJWw46BnX/w1eeDre0wM2hXvfLlYANcomGU+lMWNm+P1Y33drh4IcmWK99T+Exf7rGDLOXkgylEQ6W7FVR+jdXj+XJRFAv73jVLcMH2kR4/zZNU0EGee5U7G5wm5X5+c13M24XPHtVmIl+kr0985GxwRCfwcUdLZwf561tHbUlr+WP3yZBz5GkA56r9cuyhaOlrtzr+LTIqMH1wgvNK7+/wBj3e0uLqeo8/N2Rbi3noGcgAc/v64C9it3E2aOAsm60yNPu8ICafjMb4EukraceDpJBZXzQOPQbuCSRYzvjvwKZCsc9u2pR8E7Q1fbkLzvs+83sLu7Xb1QBFd7Z1dlI5/7j0n2/Nu/uy47b9TEqKx9MZ8rH3vsGzX99QrJQfQ3mFGcny020DUXcCemqjD9LGD8d6XFXBVse1zD95P0VVT6wrvN4Llvnw58yxnMj5PyX2mu6bBKEs7VxM+z71zELdOT0Gu9/km7VwxZgh+dUdxnwkCOXI2OCIS+PWk1LOD/fGsoyeltBLQ/W+/o6AgPjIWSybchilDx3vdF0/HkbcBlLOg5qeFN7vdbeGJjXvfRYxWJzQp8nH5F0Ltthg+wubDf3X73NER0TB1uf6OczfxYd1CfOTicaze/geHxxWsNu591+cV756TJr2DsOyUkX7dERIux2N8XSVXyo4DTyYPHE1iKbHaQzhi0K5gbacOoRVidc5bNcrKqOwv1jP3gxauEA7c+26Pzeuz6qWELNWiQU2MTuu3PtQ2mvC/b5T67foiGls68NyfxJJqORMXo8XDPylGfmYqyipq8ZcvKly2b2rtQHxsJJpa+ybt601k1dSbvAQ9V+89HY87D18Qfh5HfJkwkPtMt8hn4K6dyM6Dv+1pwPw5YitSIq4YMwST8gcH5HtENHj6QeZMTB5apOhVkP521tHTUlqlFw7ipdLX+9zf1NGK1dvX4mTOGSwau8CrvngahHsTQLkKalZvX4sbcq7G+0c/9fi6jtQa63Gk6rj7hgAqWy4Ktfvw+D9c3m/diu4uYLdy956r1WqoVWqXATvQ/Vp90fPoibNJoSYH+QR696H3jhBR4XA8Ro5VcqXsOBCdPHA2iRWMrfz9EYN2BWs5/AUaIsRWgUXbhQtr7Xlvkrr1PjutlCzVokHN4JRYP/ck9DW3dUKtVkGjVgkHpFnDklBqqHJ6vy5Kg5//W5HbMeHN0YKeq/eejkezRfJop4AjviRJk/tMd7w+0ud2IjsPmtrMMJypR3GefL9PGrXKr2XdrESDp8lDi0LiDGF/OuvoSSktQ7UBbx3e6vJ67x/9FJlJIzB5WJHHffEkCPcmgBIJav5RsR36yFi09AoQ9ZGxACS3wWsfgnNkafoBQu3cPb/oVnQrkfc8EFvCrUdPnE2quAvYrXruCPFEOByPOVJ93OdVcqXsOBAdc+4msQK1lb+/4ruqYJb2NuF/DuRbLwoN5qZamM4aXLaxBk+9/3i3nofefvC8UJtAsQY/rqQm6nDt1Ay37ejS6rFoQHr8X3Uu74+J1mJS/mCXbbw9W25dvfdmPJZV1AqvTjvia5I065luVzw5052aIPYHoKt2ohM1Dc3tQu2Uxhr4uaL0Var+yhqsuGItpXXOWIl6k/s/ptfu/RMsFs+3SouMI7s+efiHuMjqXUtHa5+A3Xr7lSOnevR8AJA3IEvod+MHmTPdttNr5Z0gF/2d9HeAdmv+PExKL/Q6N0ZP3TtCvGM9HtP7c0jRJSl+xXbXuX1Yvf0PQm1dBcRK+S4XHXMiO0AMNeVydIkcYNCuYJJkUWDQ7vwPb0nqk2TUr8wtzreHiWWgPoRX/3LQTZvDMLs6DC0j0eCntKwS7Z1ixyYAIFLbP3/NrcG6yGRIgj7SbZb82kYTyipclw309Gx5aqLOlnhPNGt67/Hoa/1vOZKkWc90936fe74+UaKTV64mGkQnahLjooT7pSTCgR9XOxRJNFhpMYvld2hqb/HqD2WRcRQXGet1AOXrivE3Z0rxiyuWIjlaLKBI0SUhb2CW0O9GhCbCbbvrsmcL91WE6O+kaCAn+r70lqYfCMDznAaO+pCd4lkS194mpRfi5XlP4dezf4H7Jy/Gr2f/Ai/P+x/FB+zPfvOa2yoCVq4CYqV8l4uMOdFJrFBIHhiquD1eySQV2gQTzIm2853jANYarLdaIqHXOF/1U+viYDE2y9ITVzXbxTJQuw92fE3S5Sl3Ca0AeLz1Wu2sXGAY6xnUiWT3nlmYjve/cn82z12ALBpAXz81A1PHDLE78+xt1nTRADU+Vms3MSF3kjS5znTLkY1dZMt+fIwGucOdf4coXX9M4hZORM7y6zXi2469/UPZ2TjSa2NxXfZsLMi91uuAwdcV41pjPeKj4vDKD38rlBDOGtyI/m64a1c8ZCz+fvJrnxPlefo7Kbp1HHCcPd4d6+fia3Bl3RHiq1A6HuPp7gSRVXIlfJeLjLnrsmcLJWVMiIqTs2vUA4N2BTO31CNSJbbKGxnAJe74ifPQathhVzqtwRKDLW3FONQ5FKMiqpGgbsNNEwdi5KghsBhboImJR8T3ddbbju92WHotZc6d0MTEo6upFrWfboTF2OS0D+5qtvu6+uiva4lwFvwAwJL/+UT4OikJ0fjB5BF4++OjHvdBrYLLbOu9qdB3OicmKgJt7V0eP7eIuJhINLc5nxzqHdS5mwyJi4kUCtrdBciiAfTUMUP6TAR5m4Vd9Ez5q7+ag2On6/yaJE2uM92+ZmMXCfyvGZ8IdYCTTcqtvyVxCzfugpV0XRr02li0dLo/X+xLgOyvcSRyft+demMj1Go1bs67HkMThuDV3W/22aIbFxmLe3rUaQfEX5O7du4CGVcWjL4WBYNyvHovRQM5kTJxPfUMIr0dMz370NbmYc6BEOfp7gTRVXIlfJfLNYn18q6NuGv8jzhx7AcM2pVME4H4DrFzavFdFllXsV2JyRyPmMzxMJ05gnPVzdhyNAJ7G5MgfX/aokGfgVtuzMc4J39Yi5ReU2ujUFWy0mkfUq9e7DIJnS+Jtfx5LVGOgp9D5TVCW69/NCcLYy8fgNEjU/D1/u+8ev6bZo7Cls9PCrd/6KcTEKeLxN6j53Gxphazii9Hazt8zgJvlZIQjZ/fVoTG5nZbwLnr8AWPgjpXK8FmiyRLMjVfkrJ5m4VddGU6MkIdsB0jcvB15d5V4P/Tay5HvNp1DoNQEUqrVOQZtUqNn45ZgFf2/NFlOznOvPpjHIms3rnTM7DsWRLtSNVxQNV9hj1vYJbD4Eb0Nblq5yyQUUMFVwcYU3RJuDVvnk9Bl+31Vh/HkYvHAQnIG5SFvAFZfdpYg73KlmqXq6E9g0hvJlUW5F6LW/N9e12hTHR3gj4yFst6TSS5o4TvcjkmsepMjcwk7ychG7RbLBa89NJLePfdd9Hc3Izi4mI89thjGDp0aLC7JpuIxIEY+q8z2CXQdqixE7Wjf4x043G0lm2Hv065q3V6XNz2km2VXA/grsQU3DrjZlyMHy38h7VKrYFueL7T+2NzJmPQwhUOV+RTr3Zfpz17RLLb1WK1qvssc32z8xVbX5N0yUl0JXbooDhbcObphEPPoDd7eHKfgKf3e9o7SL48PRYGQxdyR6Xg5HnxGfjoyAiYOpyvyt9zUwHGXd6d7ddaDq2zy4Kf31YElQQ0tLQLjT1nK8FybMn29Tq+BPyBrhMeKL6u3DsL/NtNRhgM4RG0U3ibOGQczrVWuiyLpuT8Bc6C3uToRHRYOh0mobNyNBmhVqtRMCgHBYNy/NXlPhwFMk3tzVi9fa3Tx8j1mfSuib3F8FGfmti9g72hCUOEtlp7M6lSkJbT53VZpO4a70apPex3+4juTvjFFUsDOkblJDKJtWHvZtS5mexhJnn5hWzQ/sorr+Dtt9/GM888g7S0NKxcuRJLly7Ftm3bEBkpVjJI6aIHZSDplEjIDlQYhyLn27fQ6uI8uZVKp4duxBi0GbZ73CeLsQVAi91t5uZaRH/zKiYsXIHYTLHa6SJEVuSdOXa6zu32bosEXHtFBt7++JjTNnIk6ZKLNyuxIoGgLioCP1s4BqkJOrug11HAkz0iWXiLtchzx8VoMW/qSPzpU+efwYJZo4TK8/m6iixX4OvtdXydOAhknfBQEqgybET+smjsAmQmjcDavX9CU/ulf39DJX+Bs9W73ecPhEzJL0eBjHqq2q/nkF3VuHe1kunJVmtPgjBHkyilFw7i9dN/RvPJ1h7t7CcVwoloycaeuyHCzaT0QsRodXjy89+7bOeu3B15LiSD9o6ODqxfvx7Lly/HrFmzAACrV6/G9OnT8cknn2DevHnB7aBMNPpEDDV2Xsry5iihmCQBUOFGczki3fzbptbpMXD+g9ANz4NKrUHr0akOV7L1o6eh5cjXdrer45KBro7vg3bHRGune8LdirwzoqvSQ1L1IbNCKbp7IHtEsu1nkUDw5/9W6DKQ7B3wiAZAIs/9HwvHYu37h11e58v95/HT6/Ow6/AFh9eylkPzNEu5I3IFvt5eR46z3AxQicLP5GFFmJg+LmTzFzgKepWQgMsX/jyHLJLwzNVKpidbra2vw12yv96TKLvO7cNLpa/3aeduUiGUhUN9eTk0msSO4jKTvLxCMmg/evQoWltbMWXKFNtt8fHxGD16NHbv3h02QXtbYw22J+gcB+tW39+3I1GHWY2uy8NYjC1QqdW2oNrVSnby7NvtbpcsFlS+/YTL61trp3sTZMvNk1XpgszUkFihFN09cOx0nV3gFsyt0yIJ4EQyph86WSNUDm1S/mCfPze5Al9vr8MVcyJyRAlnXuWmhARcvvDXZyKS8EzOlcyeyf5EJlF8nVQIZaE+2SQH0WMCvlaQIHshGbRXVlYCAAYPHmx3+8CBA233eUqSJMVlwTz97Q7sGyAWfO6Lj3YbtANAW20VpAG96moOGAn1gO5T8EZTu+Pbj+4Q6ofD6wdBRpoOyfFRqGtqd9omJSEKGWk62+c+akgMRg2JAQC0m8Tq4wZSZY3YjGVlTaPtdViNy0zESw9Mg+FMPRqa25EYF4Xc4UlQq1Wyjnuj0Wj3/+6e+5uDF4Suu89wQSi432v4DnkZyS7bhQqlj8dQ5micEilJfxujGfp0ZOjTAQAmU2ArtihRVWO1cDvr+yaHguRsrLzqERyrrUBjexMSouKRnTISapXa7m8F0UmFfecO+5wkUYlE36dwNTx2CJKiE1Bvcv53aXJ0IobHDgn6+xEK36WSJEElUJ45JIN26xvf++x6VFQUGhu924rR2dkJg8Hgc9/kZDG1wAyx1TXRdudqGtHlxeuMqG2ESOVFb6/vD3PG6rH5K+dB+1Vj9Dh2zPNyaMHSWCf2h0xjXSUMhgaH96kBJGsBmIBjx6pk61tvp0+fFnpu0ddUU1Mj1O7I0VNQm/z3uii8OBqnRErCMdo/NbbVi7WrrIehyT9/cyVAB6ATxy72zTlT1ixWXaas4ihwsVPmnimLq/cpnM1MnICtlX93ev+MxPE4dlQ574nSv0tF8rGFZNAeHd29+tzR0WH7bwBob2+HTqfz6pparRaZmcqaDdzxzVBkGE+gJsr9x5RhdJ+ATq1PRuYVc6HyYquSZMnGRcNHsLQ4z7jsy/X9ITcXSL+sChs/PGa34p6SEIU7rs3GpLxBQeyd57KzJWzb/ZXb3QPXzBgXtPrTRqMRp0+fxogRI4R+F0Vf04ziy/HlEffl4/JyMpAbJivt5D+ejlOiQOMY7d+ypWz8re4btyuZVxfNhloVhL+5arTYVvVPt81Gj8wJy5V2AnKRi/QL6Xjr8Fa7cZocnYgf59+ICYPHBLF3l4TCd2l5eblQu5AM2q3b4qurqzFs2DDb7dXV1cjOzvbqmiqVCjExMe4bBtCkxQ9iyPOLsDvh+0HmNBEdMO9iC9wttg/4wRLE6vXed+gHS1zWTvf5+n4wuzgDM8aPCJvzwcvmj3GZ2O2em8ZAr48NYI8c0+l0wr9PIq9pQt5gpCSUuS2HVpR7Wch+thR4noxTomDgGO2/Fo//kcuEZ3eNvxX62OD8zVWYni+URb0wPT/szrTTJTNGTca0jIkhkZNCyd+lIlvjge4dqyEnJycHer0eu3ZdKofW1NSEsrIyFBcXB7Fn8tLrdaiKGoXclu9XIaVeWci+zxwf0xCHSDivzK7WxWHQwhVua5u7Y62dromzrxOtiU+R5fr+Yk0INrMoHQWZqSEd1FkTu6Uk2Oc6SE3UyZI9PRhEXpM1E70rSirPR0RE5AtrwrMUXaLd7Sm6pKBnZrdmUXelP2RRp0vJGKcNL0bewCx+5n4UkivtkZGRWLRoEVatWoXk5GRcdtllWLlyJdLS0jB37txgd09Ws1b8Dlj5EICLMOijet2rwojYLPxkwk8wsPME6j7dYFemTaXTI7H4eiROXShbGTZfaqeTPMIxu7jIawpmFnwiIqJAU3J2/UnphfjPCXfg9X1/RrO5Z532/pNFnSiQQjJoB4D7778fXV1dePTRR2EymVBcXIx169ZBq9UGu2uym7Xid5jQYsRXG1bi28hKNOoicfnlE7Ck+FZERlgTF6RCnz0xIMG0t7XTST7hWI9b5DWF44QFERGRM0ou9Tdh8Bjo6jVQD4yCUWpX1KQCUbgJ2aBdo9FgxYoVWLFiRbC7EhB6vQ4zlyzHQIMBubm5Ds9lMJim/iAcJyyIiIhCkVqlRm5qpmLPCxOFC06FERERERERESkUg3YiIiIiIiIihWLQTkRERERERKRQDNqJiIiIiIiIFIpBOxEREREREZFCMWgnIiIiIiIiUiiVJElSsDsRbHv37oUkSYiMjHTfOIgkSUJnZye0Wi1UKtalJuXhGKVQwHFKSscxSqGA45SULhTGaEdHB1QqFYqKily2C9k67XJS6ofYm0qlUvzEAvVvHKMUCjhOSek4RikUcJyS0oXCGFWpVEKxKFfaiYiIiIiIiBSKZ9qJiIiIiIiIFIpBOxEREREREZFCMWgnIiIiIiIiUigG7UREREREREQKxaCdiIiIiIiISKEYtBMREREREREpFIN2IiIiIiIiIoVi0E5ERERERESkUAzaiYiIiIiIiBSKQTsRERERERGRQjFoJyIiIiIiIlIoBu0hwGKx4IUXXsD06dMxbtw43H333Th79mywu0X9SENDAx577DHMmDEDRUVFuO2221BaWmq7f8eOHViwYAHGjh2La665Bh988IHd49vb2/HEE09gypQpKCwsxIMPPoi6urpAvwzqJ06dOoXCwkJs2bLFdpvBYMCiRYswbtw4XHnllXjjjTfsHsPvWQqUrVu34rrrrkNBQQGuv/56fPTRR7b7zp07h2XLlqGoqAjTpk3D888/D7PZbPf4t956C1dddRXGjBmDH//4xygrKwv0S6Aw19XVhd///veYPXs2CgsLcfvtt2P//v22+/l9SsH06quv4ic/+YndbXKMSXfXCDYG7SHglVdewdtvv40nn3wS77zzDiwWC5YuXYqOjo5gd436iQceeAD79u3Dc889h5KSEuTm5mLJkiWoqKjAyZMnsWzZMkyfPh1btmzBLbfcgoceegg7duywPf7xxx/H119/jRdffBGvv/46KioqcP/99wfxFVG46uzsxPLly9HW1ma7rb6+HnfddReGDRuGkpIS3HvvvVi1ahVKSkpsbfg9S4Hw3nvv4ZFHHsHtt9+ODz74APPmzbN9v3Z2dmLJkiUAgHfeeQePP/44/vSnP+Hll1+2Pf4vf/kLfve73+G//uu/sGXLFqSnp+Ouu+7iJCjJ6v/+7//w7rvv4sknn8TWrVuRkZGBpUuXorq6mt+nFFRvvfUWnn/+ebvb5BiTItcIOokUrb29XSosLJTeeust222NjY3SmDFjpG3btgWxZ9RfnD59WsrKypJKS0ttt1ksFmnOnDnS888/L/33f/+3dPPNN9s95oEHHpAWL14sSZIkVVZWSjk5OdLnn39uu7+iokLKysqS9u7dG5gXQf3Gs88+K/30pz+VsrKypJKSEkmSJGnNmjXStGnTpM7OTrt2c+fOlSSJ37MUGBaLRZo9e7b0zDPP2N2+ePFiac2aNdK2bduk/Px8qaGhwXbfO++8IxUVFUnt7e2SJEnS3Llzpd/97ne2+zs7O6WZM2dKa9asCcyLoH7hhhtukJ5++mnbz83NzVJWVpb08ccf8/uUgqKyslJatmyZNG7cOOmaa66RFi1aZLtPjjHp7hpKwJV2hTt69ChaW1sxZcoU223x8fEYPXo0du/eHcSeUX+RlJSE1157DQUFBbbbVCoVVCoVmpqaUFpaajc+AWDy5MnYs2cPJEnCnj17bLdZZWRkYNCgQRzDJKvdu3dj06ZNeOaZZ+xuLy0txcSJExEREWG7bfLkyTh9+jRqamr4PUsBcerUKXz33Xf44Q9/aHf7unXrsGzZMpSWliIvLw8JCQm2+yZPnoyWlhYYDAbU1tbi9OnTduM0IiICEyZM4DglWaWkpOCf//wnzp07B7PZjE2bNiEyMhI5OTn8PqWgOHLkCLRaLd5//32MHTvW7j45xqS7aygBg3aFq6ysBAAMHjzY7vaBAwfa7iPyp/j4eMycORORkZG22z7++GOcOXMG06dPR2VlJdLS0uweM3DgQBiNRtTX16OqqgpJSUmIiorq04ZjmOTS1NSEhx56CI8++mif70tnYxQALly4wO9ZCohTp04BANra2rBkyRJMmTIFt9xyC/7xj38A4Dgl5XjkkUeg1Wpx1VVXoaCgAKtXr8YLL7yAYcOGcZxSUFx55ZV48cUXMXTo0D73yTEm3V1DCRi0K5zRaAQAu4AJAKKiotDe3h6MLlE/t3fvXvzqV7/C3LlzMWvWLJhMpj7j0/pzR0cHjEZjn/sBjmGS1+OPP47CwsI+q5gAHI5R6yRSe3s7v2cpIFpaWgAADz/8MObNm4f169dj6tSp+I//+A/s2LGD45QUo7y8HHFxcXj55ZexadMmLFiwAMuXL4fBYOA4JcWRY0y6u4YSRLhvQsEUHR0NoDv4sf430D2AdDpdsLpF/dRnn32G5cuXo6ioCKtWrQLQ/aXWO7mM9WedTofo6GiHyWc4hkkuW7duRWlpKbZt2+bwfkdj0PqPcExMDL9nKSC0Wi0AYMmSJZg/fz4AIDc3F2VlZdiwYYNH47R3G45TksuFCxfw4IMPYuPGjZgwYQIAoKCgAOXl5XjxxRf5fUqKI8eYdHcNJeBKu8JZt3JUV1fb3V5dXY1BgwYFo0vUT7355pu47777MHv2bKxZs8Y2Azl48GCH4zMmJgZxcXFIS0tDQ0NDny9DjmGSS0lJCWprazFr1iwUFhaisLAQAPDrX/8aS5cuRVpamsMxCgCDBg3i9ywFhHUsZWVl2d2emZmJc+fOcZySIhw4cACdnZ12eWwAYOzYsThz5gzHKSmOHGPS3TWUgEG7wuXk5ECv12PXrl2225qamlBWVobi4uIg9oz6E2uZjNtvvx3PPfec3RaiCRMm4Ntvv7Vrv3PnThQVFUGtVmP8+PGwWCy2hHRA99nOqqoqjmGSxapVq/Dhhx9i69attv8BwP3334+nnnoKxcXF2LNnj1296507dyIjIwMpKSn8nqWAyMvLQ2xsLA4cOGB3+/HjxzFs2DAUFxejrKzMto0e6B6nsbGxyMnJQUpKCjIyMuzGaVdXF0pLSzlOSTbWc73Hjh2zu/348eMYMWIEv09JceQYk+6uoQjBTl9P7j333HPSxIkTpc8++0wyGAzS4sWLpblz50odHR3B7hr1AxUVFVJeXp507733StXV1Xb/a2pqko4fPy7l5eVJK1eulMrLy6V169ZJo0ePlrZv3267xgMPPCBdeeWV0s6dO6UDBw5IN910k125DiK59Sz5VlNTIxUXF0sPP/ywdOLECamkpEQqKCiQtmzZYmvP71kKhJdfflkqLCyUtm3bJp05c0Z65ZVXpJycHGnnzp2SyWSS5syZIy1ZskQyGAzSp59+Kk2cOFF68cUXbY/ftGmTNGbMGGnLli3SiRMnpBUrVkiTJk2Samtrg/iqKJyYzWbptttuk6655hppx44d0qlTp6TVq1dLubm50v79+/l9SkH38MMP2/0NKceYFLlGsKkkSZKCPXFArpnNZjz33HPYsmULTCYTiouL8dhjjyE9PT3YXaN+YM2aNVi9erXD++bPn49nnnkGX375JVauXInTp08jPT0d9913H6677jpbu7a2Nvz2t7/Fxx9/DACYMWMGHn30USQlJQXkNVD/k52djaeffhoLFiwAABw8eBBPPfUUysrKMGDAACxevBiLFi2ytef3LAXKhg0b8Oabb6KqqgqjRo3Cfffdhzlz5gAAzpw5gyeeeAKlpaVISEjAzTffjPvuuw9q9aWNkevWrcMbb7yBhoYG5Ofn49FHH0Vubm6wXg6FocbGRjz//PP4/PPP0djYiKysLDzwwAOYOHEiAH6fUnD98pe/xHfffYc//vGPttvkGJPurhFsDNqJiIiIiIiIFIpn2omIiIiIiIgUikE7ERERERERkUIxaCciIiIiIiJSKAbtRERERERERArFoJ2IiIiIiIhIoRi0ExERERERESkUg3YiIiIiIiIihWLQTkRERERERKRQDNqJiIiIiIiIFIpBOxEREREREZFCMWgnIiIiIiIiUigG7UREREREREQK9f8BKNJxk4jIMSYAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1200x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#plt.scatter(x=penguins.body_mass_g, y=penguins.flipper_length_mm);\n",
+    "lst=[\"Minutes Lightly Active\",\"Minutes Very Active\",\"Minutes Sedentary\"]\n",
+    "for el in lst:\n",
+    "    plt.scatter(x=fitbit[el], y=fitbit[\"Steps\"])"
+   ]
   }
  ],
  "metadata": {
@@ -111,7 +617,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [
diff --git a/your-code/challenge-2.ipynb b/your-code/challenge-2.ipynb
index d7465f0..2f284ca 100644
--- a/your-code/challenge-2.ipynb
+++ b/your-code/challenge-2.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,13 +36,235 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "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>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Gender</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Fare</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>941</th>\n",
+       "      <td>942</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Smith, Mr. Lucien Philip</td>\n",
+       "      <td>male</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>13695</td>\n",
+       "      <td>60.0000</td>\n",
+       "      <td>C31</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1191</th>\n",
+       "      <td>1192</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Olsson, Mr. Oscar Wilhelm</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>347079</td>\n",
+       "      <td>7.7750</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>150</th>\n",
+       "      <td>151</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Bateman, Rev. Robert James</td>\n",
+       "      <td>male</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>S.O.P. 1166</td>\n",
+       "      <td>12.5250</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>830</th>\n",
+       "      <td>831</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Yasbeck, Mrs. Antoni (Selini Alexander)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2659</td>\n",
+       "      <td>14.4542</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>89</th>\n",
+       "      <td>90</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Celotti, Mr. Francesco</td>\n",
+       "      <td>male</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>343275</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>402</th>\n",
+       "      <td>403</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Jussila, Miss. Mari Aina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4137</td>\n",
+       "      <td>9.8250</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>356</th>\n",
+       "      <td>357</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Bowerman, Miss. Elsie Edith</td>\n",
+       "      <td>female</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>113505</td>\n",
+       "      <td>55.0000</td>\n",
+       "      <td>E33</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>971</th>\n",
+       "      <td>972</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Boulos, Master. Akar</td>\n",
+       "      <td>male</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2678</td>\n",
+       "      <td>15.2458</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>103</th>\n",
+       "      <td>104</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johansson, Mr. Gustaf Joel</td>\n",
+       "      <td>male</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7540</td>\n",
+       "      <td>8.6542</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>989</th>\n",
+       "      <td>990</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braf, Miss. Elin Ester Maria</td>\n",
+       "      <td>female</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>347471</td>\n",
+       "      <td>7.8542</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      PassengerId  Survived  Pclass                                     Name  \\\n",
+       "941           942       NaN       1                 Smith, Mr. Lucien Philip   \n",
+       "1191         1192       NaN       3                Olsson, Mr. Oscar Wilhelm   \n",
+       "150           151       0.0       2               Bateman, Rev. Robert James   \n",
+       "830           831       1.0       3  Yasbeck, Mrs. Antoni (Selini Alexander)   \n",
+       "89             90       0.0       3                   Celotti, Mr. Francesco   \n",
+       "402           403       0.0       3                 Jussila, Miss. Mari Aina   \n",
+       "356           357       1.0       1              Bowerman, Miss. Elsie Edith   \n",
+       "971           972       NaN       3                     Boulos, Master. Akar   \n",
+       "103           104       0.0       3               Johansson, Mr. Gustaf Joel   \n",
+       "989           990       NaN       3             Braf, Miss. Elin Ester Maria   \n",
+       "\n",
+       "      Gender   Age  SibSp  Parch       Ticket     Fare Cabin Embarked  \n",
+       "941     male  24.0      1      0        13695  60.0000   C31        S  \n",
+       "1191    male  32.0      0      0       347079   7.7750    U0        S  \n",
+       "150     male  51.0      0      0  S.O.P. 1166  12.5250    U0        S  \n",
+       "830   female  15.0      1      0         2659  14.4542    U0        C  \n",
+       "89      male  24.0      0      0       343275   8.0500    U0        S  \n",
+       "402   female  21.0      1      0         4137   9.8250    U0        S  \n",
+       "356   female  22.0      0      1       113505  55.0000   E33        S  \n",
+       "971     male   6.0      1      1         2678  15.2458    U0        C  \n",
+       "103     male  33.0      0      0         7540   8.6542    U0        S  \n",
+       "989   female  20.0      0      0       347471   7.8542    U0        S  "
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "titanic = pd.read_csv('../data/titanic.csv')\n",
+    "titanic.sample(10)"
    ]
   },
   {
@@ -54,10 +276,70 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 1309 entries, 0 to 1308\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column       Non-Null Count  Dtype  \n",
+      "---  ------       --------------  -----  \n",
+      " 0   PassengerId  1309 non-null   int64  \n",
+      " 1   Survived     891 non-null    float64\n",
+      " 2   Pclass       1309 non-null   int64  \n",
+      " 3   Name         1309 non-null   object \n",
+      " 4   Gender       1309 non-null   object \n",
+      " 5   Age          1309 non-null   float64\n",
+      " 6   SibSp        1309 non-null   int64  \n",
+      " 7   Parch        1309 non-null   int64  \n",
+      " 8   Ticket       1309 non-null   object \n",
+      " 9   Fare         1309 non-null   float64\n",
+      " 10  Cabin        1309 non-null   object \n",
+      " 11  Embarked     1309 non-null   object \n",
+      "dtypes: float64(3), int64(4), object(5)\n",
+      "memory usage: 122.8+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "titanic.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PassengerId      int64\n",
+       "Survived       float64\n",
+       "Pclass           int64\n",
+       "Name            object\n",
+       "Gender          object\n",
+       "Age            float64\n",
+       "SibSp            int64\n",
+       "Parch            int64\n",
+       "Ticket          object\n",
+       "Fare           float64\n",
+       "Cabin           object\n",
+       "Embarked        object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "titanic.dtypes"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -69,10 +351,347 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Fare</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>22.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.2500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>38.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>71.2833</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>26.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.9250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>53.1000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>35.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1304</th>\n",
+       "      <td>1305</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>29.513190</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1305</th>\n",
+       "      <td>1306</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>39.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>108.9000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1306</th>\n",
+       "      <td>1307</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>38.500000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>7.2500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1307</th>\n",
+       "      <td>1308</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>29.513190</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>8.0500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1308</th>\n",
+       "      <td>1309</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>25.315435</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>22.3583</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1309 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      PassengerId  Survived  Pclass        Age  SibSp  Parch      Fare\n",
+       "0               1       0.0       3  22.000000      1      0    7.2500\n",
+       "1               2       1.0       1  38.000000      1      0   71.2833\n",
+       "2               3       1.0       3  26.000000      0      0    7.9250\n",
+       "3               4       1.0       1  35.000000      1      0   53.1000\n",
+       "4               5       0.0       3  35.000000      0      0    8.0500\n",
+       "...           ...       ...     ...        ...    ...    ...       ...\n",
+       "1304         1305       NaN       3  29.513190      0      0    8.0500\n",
+       "1305         1306       NaN       1  39.000000      0      0  108.9000\n",
+       "1306         1307       NaN       3  38.500000      0      0    7.2500\n",
+       "1307         1308       NaN       3  29.513190      0      0    8.0500\n",
+       "1308         1309       NaN       3  25.315435      1      1   22.3583\n",
+       "\n",
+       "[1309 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "num_titanic=titanic.select_dtypes(include=['float64','int64'])\n",
+    "num_titanic"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "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>Name</th>\n",
+       "      <th>Gender</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1304</th>\n",
+       "      <td>Spector, Mr. Woolf</td>\n",
+       "      <td>male</td>\n",
+       "      <td>A.5. 3236</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1305</th>\n",
+       "      <td>Oliva y Ocana, Dona. Fermina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>PC 17758</td>\n",
+       "      <td>C105</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1306</th>\n",
+       "      <td>Saether, Mr. Simon Sivertsen</td>\n",
+       "      <td>male</td>\n",
+       "      <td>SOTON/O.Q. 3101262</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1307</th>\n",
+       "      <td>Ware, Mr. Frederick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>359309</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1308</th>\n",
+       "      <td>Peter, Master. Michael J</td>\n",
+       "      <td>male</td>\n",
+       "      <td>2668</td>\n",
+       "      <td>U0</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1309 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                   Name  Gender  \\\n",
+       "0                               Braund, Mr. Owen Harris    male   \n",
+       "1     Cumings, Mrs. John Bradley (Florence Briggs Th...  female   \n",
+       "2                                Heikkinen, Miss. Laina  female   \n",
+       "3          Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   \n",
+       "4                              Allen, Mr. William Henry    male   \n",
+       "...                                                 ...     ...   \n",
+       "1304                                 Spector, Mr. Woolf    male   \n",
+       "1305                       Oliva y Ocana, Dona. Fermina  female   \n",
+       "1306                       Saether, Mr. Simon Sivertsen    male   \n",
+       "1307                                Ware, Mr. Frederick    male   \n",
+       "1308                           Peter, Master. Michael J    male   \n",
+       "\n",
+       "                  Ticket Cabin Embarked  \n",
+       "0              A/5 21171    U0        S  \n",
+       "1               PC 17599   C85        C  \n",
+       "2       STON/O2. 3101282    U0        S  \n",
+       "3                 113803  C123        S  \n",
+       "4                 373450    U0        S  \n",
+       "...                  ...   ...      ...  \n",
+       "1304           A.5. 3236    U0        S  \n",
+       "1305            PC 17758  C105        C  \n",
+       "1306  SOTON/O.Q. 3101262    U0        S  \n",
+       "1307              359309    U0        S  \n",
+       "1308                2668    U0        C  \n",
+       "\n",
+       "[1309 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "titanic.select_dtypes(include=['object'])"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -84,11 +703,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# your code here\n"
+    "sns.set(rc={\"figure.figsize\": (12.,4.)})\n",
+    "plt.style.use('classic')"
    ]
   },
   {
@@ -100,11 +720,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here\n"
+    "sns.histplot(x=titanic.Age, bins=15);"
    ]
   },
   {
@@ -116,13 +747,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 39,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\n'"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "\"\"\"\n",
-    "your comments here\n",
-    "\"\"\""
+    "#"
    ]
   },
   {
@@ -135,22 +775,55 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 1 - matplotlib\n",
-    "# your code here"
+    "titanic.groupby(\"Gender\")[\"Gender\"].count().plot(kind='bar');"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\lucia\\AppData\\Local\\Temp\\ipykernel_24748\\1716843163.py:2: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.countplot(x=\"Gender\", data = titanic, palette='magma');\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 2 - seaborn\n",
-    "# your code here"
+    "sns.countplot(x=\"Gender\", data = titanic, palette='magma');"
    ]
   },
   {
@@ -162,11 +835,53 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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f0JEjR2S329Xb2zti/sDAgCTJbrdHtp07+3H+nKSkpMu+bmVlZeSGVo/HI4/HE81yAQCAIU1NTWpqapIkBQKBK86P+lLL+c59WkWS3G63Dhw4oHA4HLnc0traqpSUlMhZjuTkZB09elRZWVmSpHA4rI6ODi1duvSyr1NRUaHExMRrWSIAADDg/BMD/f392r59+2XnR3Vz6VtvvaX+/n5J0qlTp7R161ZNmzZNWVlZys3NlcVikdfrVSAQUGdnp+rr67Vy5crI/gUFBaqvr1dnZ6cCgYC8Xq+sVqtyc3Ov8TABAMBEFNUZjzfffFO1tbU6e/asnE6n5s+fr4qKisillPLyctXW1qqsrEx2u10rVqyIfJRWkgoLC+X3+yP3hKSnp2vTpk18lBYAgBtMVOHxyCOPXHbc5XJpy5YtlxyPiYlRcXGxiouLr251AABgUuGR6QAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxsdey07/+67/q4MGDqqio0MKFCyVJ77//vnbs2KGPP/5Y06ZNU1FRkQoKCiL7BINB1dXV6a233lIoFNL8+fN1zz33aMaMGaNzJAAAYNy76jMeb7zxhs6ePTtiW09Pj2pqapSfn6+tW7eqrKxMO3fuVEtLS2ROXV2dPvzwQz3++ON6+umnlZCQoKeeekpDQ0Of/SgAAMCEcFXhcfLkSf3sZz/TvffeO2L7/v37lZqaqlWrVik2NlY5OTnKz8/Xvn37JEmBQED79+9XcXGxkpOT5XA4tG7dOn300Uc6cuTI6B0NAAAY16IOj+HhYT3//PP6q7/6K82cOXPEWEdHhzIzM0dsy8jIUFtbmyTp+PHjCgQCI+YkJiYqOTk5MgcAAEx+UYdHQ0ODJGn58uUXjPl8PjkcjhHbnE6nfD5fZPzctkvNAQAAk19UN5d+8sknevXVV/VP//RPFx232+0aHBwcsW1gYEB2uz0yfm6bzWa76JyLqaysjMz3eDzyeDzRLBcAABjS1NSkpqYmSX+8teJKogqPw4cPq7+/X4899tiI7T/4wQ/0+c9/Xi6XS4cOHRoxduzYMaWlpUmSbrrpJtlsNrW2turWW2+VJPX396unpycy52IqKiqUmJgYzRIBAMAYOP/EQH9/v7Zv337Z+VGFx+c///nIx2bPefDBB/X1r39df/Znfyafz6ef//znamhokMfj0R/+8Ac1Nzdr/fr1kiSbzaZly5bplVdekdvtltPp1I4dOzRnzhxlZ2dfw2ECAICJKKrwmDJliqZMmXLB9sTERCUkJCghIUEbN25UXV2d6urqNG3aNK1du1a5ubmRuevWrVNdXZ02b96sYDConJwcbdiwQRYLzzADAOBGcU0PEJOkHTt2jPh6wYIFevLJJy85Py4uTqWlpSotLb3WlwQAABMcpxsAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgTOxYL2Ai8/v9CgaDY72MSSEuLk7x8fFjvQwAwHVGeFwjv9+vxbm3qa/3xFgvZVKYnjRTB1veJj4AYJIjPK5RMBhUX+8JLfzSE7LG8cPyswgH/frda5sVDAYJDwCY5AiPz8gaFy9rnH2slwEAwITAzaUAAMAYwgMAABhDeAAAAGOiusfD6/XqV7/6lfr7+2W1WpWenq67775baWlpkTkdHR2qra1VW1ub7Ha7li9frjVr1igmJkaSNDw8LK/Xq8bGRvl8PqWlpam0tFRz5869LgcGAADGn6jC4/bbb9edd94pp9OpUCikX/7yl6qqqtKPf/xjWSwW+Xw+VVVVKS8vT48++qi6urpUXV0th8Oh1atXS5L27Nmj5uZmlZeXKzU1Vbt27VJVVZVqamr4JAMAADeIqC61zJ49W06nU9Ifz1xYLBadPn1aZ86ckSS1tLRoaGhIJSUlstlscrlcKioq0t69eyPfo6GhQYWFhXK5XLLZbCopKVEoFFJLS8t1OCwAADAeRf1x2nfeeUc/+clPNDg4qJiYGK1evVpTp06VJLW3t8vtdstqtUbmZ2RkqLu7W4ODg5Kknp4eZWZmRsatVqvcbrfa29uVl5c3WscDAADGsajD4y/+4i+0detWnTlzRm+88YaSkpIiYz6fTw6HY8T8c2dIfD5fZNvF5pw/DgAAJrerfoBYQkKC/vIv/1Lr169Xamqq3G637Ha7ent7R8wbGBiQJNnt//dwrXNnP86fc37A/H+VlZWy2WySJI/HI4/Hc7XLBQAA11FTU5OampokSYFA4Irzr+nJpcPDwwqHw+rq6pLb7Zbb7daBAwcUDocjl1taW1uVkpISOcuRnJyso0ePKisrS5IUDofV0dGhpUuXXvJ1KioqlJiYeC1LBAAABpx/YqC/v1/bt2+/7Pyobi59/fXXderUKUnS6dOntW3bNsXGxio7O1uSlJubK4vFIq/Xq0AgoM7OTtXX12vlypWR71FQUKD6+np1dnYqEAjI6/XKarUqNzf3Wo4TAABMQFGd8Xj33Xf17//+7zp79qzsdrsyMjJUUVGh6dOnS/rj5ZTy8nLV1taqrKxMdrtdK1asiHyUVpIKCwvl9/tVWVkpn8+n9PR0bdq0iY/SAgBwA4kqPDZu3HjFOS6XS1u2bLnkeExMjIqLi1VcXBz96gAAwKTCI9MBAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGHNNDxADMH75/X4Fg8GxXsaEFxcXx8f9geuA8AAmEb/fr8W5t6mv98RYL2XCm540Uwdb3iY+gFFGeACTSDAYVF/vCS380hOyxvED81qFg3797rXNCgaDhAcwyggPYBKyxsXLGme/8kQAMIybSwEAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYExvNpJ07d+qdd97RiRMnFB8fr5ycHP3N3/yNZsyYEZlz4sQJbdu2TYcPH1ZsbKxuv/12rVu3TrGx//cSe/fu1Z49e3T69GnNnj1b69atU05OzugfFQAAGJeiPuNx33336bnnnlN1dbUkqaamJjI2NDSkmpoaJSQk6Omnn9bjjz+uw4cP66c//Wlkzttvv62XX35Z9913n7Zu3ar8/Hx9//vf18mTJ0fxcAAAwHgWVXjcfffdSk9PV2xsrJxOp4qKitTR0aGBgQFJ0ocffqiPP/5Y69atk8PhUHJysoqLi9XU1KRAICBJ2rdvn/Lz85WTk6PY2FitWrVKqamp2r9///U7OgAAMK5c0z0e7777rmbOnCmn0ylJam9vV0pKihITEyNzMjMzdfbsWXV1dUXmZGZmjvg+GRkZamtru8alAwCAieaqw+N3v/uddu/erXvuuSeyzefzyeFwjJh3Lkp8Pt9l55wbBwAAk19UN5eec+jQIT3zzDP65je/qUWLFkW22+12DQ4Ojph77jKM3W6/7Jxz4xdTWVkpm80mSfJ4PPJ4PFezXAAAcJ01NTWpqalJkiK3V1xO1OHx5ptvatu2bXrwwQd18803jxhzu93q7u5Wf39/5HJLa2urpkyZotTU1Mic1tZW3XHHHZH9jh07psWLF1/yNSsqKkZcvgEAAOPL+ScG+vv7tX379svOj+pSy969e1VbW6sNGzZcEB2S9LnPfU6zZ8/Wjh075PP5dOLECb3yyivKz8+PnLFYuXKlmpubdfjwYYVCITU0NOj48eNatmzZVR4iAACYqKI647F9+3ZZrdbIR2nP2bRpk+bPny+LxaJHHnlEtbW1uv/++xUXF6fbb79df/u3fxuZe9ttt+nUqVP6yU9+otOnT2vOnDnauHHjiGeBAACAyS2q8NixY8cV5yQnJ2vjxo2XnbNq1SqtWrUqupUBAIBJh0emAwAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMYQHgAAwBjCAwAAGEN4AAAAYwgPAABgDOEBAACMITwAAIAxhAcAADCG8AAAAMbERjvx17/+tfbt26f29nb5/X698MILslqtkfGOjg7V1taqra1Ndrtdy5cv15o1axQTEyNJGh4eltfrVWNjo3w+n9LS0lRaWqq5c+eO/lEBAIBxKeozHk6nUwUFBfrqV796wZjP51NVVZWys7P17LPPqry8XI2NjXr99dcjc/bs2aPm5maVl5fr2WefVXZ2tqqqquT3+0fnSAAAwLgXdXjcfPPNuuOOO5SSknLBWEtLi4aGhlRSUiKbzSaXy6WioiLt3bs3MqehoUGFhYVyuVyy2WwqKSlRKBRSS0vL6BwJAAAY90blHo/29na53e4Rl14yMjLU3d2twcFBDQ4OqqenR5mZmZFxq9Uqt9ut9vb20VgCAACYAKK+x+NyfD6fHA7HiG1OpzMyds7F5pw/DgAAJrdRCQ+73a7e3t4R2wYGBiJj5wwODl4wJykp6ZLft7KyUjabTZLk8Xjk8XhGY7kAAGCUNDU1qampSZIUCASuOH9UwsPtduvAgQMKh8ORyy2tra1KSUmJnOVITk7W0aNHlZWVJUkKh8Pq6OjQ0qVLL/l9KyoqlJiYOBpLBAAA18H5Jwb6+/u1ffv2y86P+h6PoaEhBQIBhUIhSVIwGFQgENDQ0JByc3NlsVjk9XoVCATU2dmp+vp6rVy5MrJ/QUGB6uvr1dnZqUAgIK/XK6vVqtzc3Gs4TAAAMBFFfcbjjTfe0PPPPx/5+utf/7okafPmzVqwYIHKy8tVW1ursrIy2e12rVixQqtXr47MLywslN/vV2VlpXw+n9LT07Vp0ybFx8eP4uEAAIDxLOrwyM/PV35+/iXHXS6XtmzZcsnxmJgYFRcXq7i4+OpWCAAAJg0emQ4AAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYQ3gAAABjCA8AAGAM4QEAAIwhPAAAgDGEBwAAMIbwAAAAxhAeAADAGMIDAAAYE2vyxYaHh+X1etXY2Cifz6e0tDSVlpZq7ty5JpcBAADGiNEzHnv27FFzc7PKy8v17LPPKjs7W1VVVfL7/SaXccM5ffz9sV4CMALvSYw3vCfNMRoeDQ0NKiwslMvlks1mU0lJiUKhkFpaWkwu44Zzuov/oDC+8J7EeMN70hxj4TE4OKienh5lZmZGtlmtVrndbrW3t5taBgAAGEPG7vHw+XySJIfDMWK70+mMjJ0zPDwsSTpz5oyZxV2Dc2sLDH4qa9z4vlQUDp5VYLBvrJdxSeHgH//8xvO/74liorwveU/eOHhPjp6J8L48t7ZzP8cvxlh42O12SX8883G+gYEBJSUljdh27p6PxYsXm1ncZ/DBL7431kuIysnWN8d6CVc0Ef59TxQT4X3Je/LGwnty9EyE96Xf75fT6bzomLHwcDgcSk5O1tGjR5WVlSVJCofD6ujo0NKlS0fMnT59un70ox8pPj5eMTExppYIAAA+g+HhYfn9fk2fPv2Sc4x+nLagoED19fX60z/9U82aNUuvvvqqrFarcnNzR8yzWCyaMWOGyaUBAIBRcKkzHecYDY/CwkL5/X5VVlbK5/MpPT1dmzZtUnx8vMllAACAMRLT2Nh46TtAAAAARhGPTAcAAMYQHgAAwBjC4wYyPDysDz74YKyXAQBjbnh4WP39/ZGvOzo61NLSolOnTo3hqm4MRm8uxdgKhUJ64oknVFdXN9ZLwQ1ocHDwggcIStKHH36oz33uc2OwItyo2tvbVVVVpdOnT+sLX/iC5s2bp61btyocDis2NlYVFRVKT08f62VOWpzxmGSGhoYu+xdg2smTJ/Wd73xH69ev10MPPaR33313xHh1dfUYrQw3qp07d6qoqEhf+cpX9Itf/EK9vb16/vnntXXrVi1ZskS7d+8e6yVOapzxmGS+9rWvjfUSgBFeeuklzZkzR2VlZfrv//5v/eAHP9A//MM/6NZbbx3rpeEG1dbWpg0bNmhoaEg7duxQXl6eYmJiZLVatXbtWn3nO98Z6yVOaoTHJBMfH6+vfvWrSklJuWAsGAzyf5cw7vDhw6qurpbD4ZDb7VZ6erp++MMf6lvf+pYWLlw41svDDSgUCslqtcpqtcput4944NXUqVMv+P1hGF2ExyTjcrlks9mUk5NzwVgwGByDFeFG5/f7NWXKlMjXCxcu1De/+U398Ic/1IYNG8ZwZbhRJSYmRu45uv/++0eMnTp1iodaXmfc4zHJrFy5UgkJCRcds1qtWr9+veEV4UY3c+ZMdXZ2jth2yy236O///u/11FNPKRQKjdHKcKNaunSpTp8+LUn68z//8xFjv/71r7mx9DrjyaUArqudO3fKYrFo7dq1F4zt3btXL7zwAp+0Am4ghAcAADCGSy0AAMAYwgMAABhDeAAAAGMIDwDXVXNzsx544IGxXgaAcYLneACIyuOPP64jR44oNjZWMTExmjlzplavXi2PxzPWSwMwgRAeAKJWVFSktWvXamhoSAcOHNAzzzyjlJQULViwYKyXBmCCIDwAXDWLxaKlS5fqxRdf1LFjxzRv3jy9+uqrevvtt/Xpp58qMTFRa9as0bJlyy7Y9+2339Zrr72m7u5uWSwWZWdnj3jMf3t7u1544QV1dHRIklJSUnT//fdr9uzZeu+99/TSSy+pq6tLVqtVN910kzZu3DjikdcAxjfCA8BVC4fDOnDggAYGBpSRkaF/+7d/0/Hjx/Xwww9r9uzZ+vTTT/Xpp59edN/4+HitX79ec+fO1cDAgJ577jn9+Mc/1j//8z9LkrZt26abb7458ou6Ojs7I2HxzDPPqKSkRMuWLVM4HNaxY8dktVqNHDOA0UF4AIhafX299u3bJ4vFopkzZ2r9+vX6kz/5E7355pv63ve+pzlz5kiSpk+frunTp1/0eyxatCjyz4mJiSouLtbmzZvl8/lkt9sVGxurkydP6sSJE5o1a5bS0tIi82NjY/XJJ5+or69PSUlJysrKuq7HC2D0ER4AovaFL3zhgkefHz16VJJ00003RfU9PvjgA+3evVv/8z//I7/fH9l++vRp2e12lZWV6dVXX9UTTzyhoaEh3XbbbSopKVF8fLwefvhhvfbaa3rssccUHx+vO+64Q1/+8pc56wFMIIQHgM8kOTlZktTV1XXFX64VCoVUU1OjL3/5y/r2t78tu92utrY2bd68WcPDw5Hv941vfCPyPf/lX/5FU6ZM0dq1a+VyuSIfzW1ra1NVVZWSkpK0fPny63iEAEYTz/EA8JlMnTpVt99+u7Zt26aPP/5YktTX16djx45dMDcUCikQCMjpdMput6uvr08/+9nPRsxpbm7WyZMnNTw8LLvdLqvVKovFolAopObm5shvFXU4HLJYLJztACYYzngA+Mzuvfde7d69W9XV1Tp9+rSmTp2qv/7rv77gDEh8fLzuvfde7dq1Sy+++KJmzZqlO++8U7/97W8jcz744AO9/PLLkXs+brnlFn3xi1+UJP3Xf/2Xdu7cqbNnzyohIUHLli1TXl6eyUMF8Bnx22kBAIAxXGoBAADGEB4AAMAYwgMAABhDeAAAAGMIDwAAYAzhAQAAjCE8AACAMYQHAAAwhvAAAADGEB4AAMCY/wUZ2a4L3em04gAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "titanic.groupby(\"Pclass\")[\"Pclass\"].count().plot(kind='bar');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\lucia\\AppData\\Local\\Temp\\ipykernel_24748\\1891691005.py:1: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.countplot(x=\"Pclass\", data = titanic, palette='magma');\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.countplot(x=\"Pclass\", data = titanic, palette='magma');"
    ]
   },
   {
@@ -185,22 +900,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.boxplot(data=titanic, x=\"Age\");"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 37,
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [],
    "source": [
-    "\"\"\"\n",
-    "your comments here\n",
-    "\"\"\""
+    "#min=0\n",
+    "#1quartil 22\n",
+    "#2quartil 37\n",
+    "#3quartil 60\n",
+    "#max=80\n",
+    "#median=29"
    ]
   },
   {
@@ -213,22 +944,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 1 - matplotlib\n",
-    "# your code here"
+    "plt.scatter(x=titanic[\"Age\"], y=titanic[\"Fare\"]);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Method 2 - seaborn\n",
-    "# your code here"
+    "sns.scatterplot(x=\"Age\", y=\"Fare\", data=titanic);"
    ]
   },
   {
@@ -240,11 +993,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "plt.subplots(figsize=(10, 10))\n",
+    "sns.heatmap(num_titanic.corr(), cmap = \"YlGnBu\", annot=True, fmt=\".2f\")\n",
+    "plt.show()"
    ]
   },
   {
@@ -256,12 +1022,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\nyour comments here\\n'"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "\"\"\"\n",
-    "your comments here\n",
+    "Fare and Pclass\n",
     "\"\"\""
    ]
   },
@@ -274,13 +1051,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "sns.boxplot(data=titanic, x=\"Pclass\", y=\"Age\");"
    ]
   },
   {
@@ -293,12 +1081,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<seaborn.axisgrid.FacetGrid at 0x1bf3d445950>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 480x240 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "# your code here"
+    "#sns.histplot(x=titanic.Age, bins=15);\n",
+    "g = sns.FacetGrid(data=titanic,col='Gender')\n",
+    "g.map(plt.hist,'Age')\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -318,7 +1136,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [
diff --git a/your-code/challenge-3.ipynb b/your-code/challenge-3.ipynb
index 74d5b31..a4767a6 100644
--- a/your-code/challenge-3.ipynb
+++ b/your-code/challenge-3.ipynb
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -34,6 +34,15 @@
     "* table: `titanic`"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "titanic = pd.read_csv('../data/titanic.csv')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -156,7 +165,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.11.5"
   },
   "nbTranslate": {
    "displayLangs": [
diff --git a/your-code/figure1.png b/your-code/figure1.png
new file mode 100644
index 0000000..7ce9fd5
Binary files /dev/null and b/your-code/figure1.png differ
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