Final_Report.ipynb

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   "source": [
    "# Final Report: Analysis On Factors Leading to Obesity in America\n",
    "**Team: Mind Masters** - Om Gor, Manh Phan, Vincenzo Murray, Ali Alshaheen, Rafay Khan **Github Repository**: https://github.com/uic-cs418/group-project-mind-masters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "adc02311-4440-41c1-8074-4d52437ac7e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import plotly.express as px\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from Analysis.helper_functions.obesity_children import *\n",
    "from Analysis.helper_functions.data1_helper import *\n",
    "from Analysis.helper_functions.inactivity_model import *\n",
    "from Analysis.helper_functions.obesity_visualization import *\n",
    "from Analysis.helper_functions.data_cleaning_physical import *\n",
    "from ipywidgets import interact, Dropdown, fixed\n",
    "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n",
    "from sklearn.feature_selection import SelectKBest, f_classif\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, mean_squared_error, r2_score, confusion_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d896c3f-ed54-4bff-9570-1eaf9c032831",
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   "source": [
    "## Reading Data / Cleaning Data\n",
    "To clean this Obesity Among Children and Adults 20+ data we removed all the NA values and emoved columns such as Panel_Num, Year_Num, and others as they were numerical representations of other columns. Kept important columns that gave us obestity rates by the stub_name and labels.\n",
    "\n",
    "**Data - Obesity Among Children and Adolescents 2-19** - https://catalog.data.gov/dataset/obesity-among-children-and-adolescents-aged-219-years-by-selected-characteristics-united-s-3ead4"
   ]
  },
  {
   "cell_type": "code",
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   "id": "1336fb56-002e-4e46-99af-2f96f68b2414",
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    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PANEL</th>\n",
       "      <th>STUB_NAME</th>\n",
       "      <th>STUB_LABEL</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>AGE</th>\n",
       "      <th>ESTIMATE</th>\n",
       "      <th>SE</th>\n",
       "      <th>FLAG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>2-19 years</td>\n",
       "      <td>Percent of poverty level</td>\n",
       "      <td>Below 100%</td>\n",
       "      <td>1988-1994</td>\n",
       "      <td>2-19 years</td>\n",
       "      <td>12.6</td>\n",
       "      <td>1.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>2-19 years</td>\n",
       "      <td>Percent of poverty level</td>\n",
       "      <td>Below 100%</td>\n",
       "      <td>1999-2002</td>\n",
       "      <td>2-19 years</td>\n",
       "      <td>17.6</td>\n",
       "      <td>1.1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>2-19 years</td>\n",
       "      <td>Percent of poverty level</td>\n",
       "      <td>Below 100%</td>\n",
       "      <td>2001-2004</td>\n",
       "      <td>2-19 years</td>\n",
       "      <td>17.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>2-19 years</td>\n",
       "      <td>Percent of poverty level</td>\n",
       "      <td>Below 100%</td>\n",
       "      <td>2003-2006</td>\n",
       "      <td>2-19 years</td>\n",
       "      <td>18.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>2-19 years</td>\n",
       "      <td>Percent of poverty level</td>\n",
       "      <td>Below 100%</td>\n",
       "      <td>2005-2008</td>\n",
       "      <td>2-19 years</td>\n",
       "      <td>19.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "          PANEL                 STUB_NAME  STUB_LABEL       YEAR         AGE  \\\n",
       "171  2-19 years  Percent of poverty level  Below 100%  1988-1994  2-19 years   \n",
       "172  2-19 years  Percent of poverty level  Below 100%  1999-2002  2-19 years   \n",
       "173  2-19 years  Percent of poverty level  Below 100%  2001-2004  2-19 years   \n",
       "174  2-19 years  Percent of poverty level  Below 100%  2003-2006  2-19 years   \n",
       "175  2-19 years  Percent of poverty level  Below 100%  2005-2008  2-19 years   \n",
       "\n",
       "     ESTIMATE   SE FLAG  \n",
       "171      12.6  1.2  NaN  \n",
       "172      17.6  1.1  NaN  \n",
       "173      17.9  1.3  NaN  \n",
       "174      18.9  1.4  NaN  \n",
       "175      19.9  1.4  NaN  "
      ]
     },
     "execution_count": 2,
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   ],
   "source": [
    "obesity_children = pd.read_csv(\"Datasets/Obesity_among_children_and_adolescents_aged_2_19_years__by_selected_characteristics__United_States.csv\")\n",
    "obesity_single_unique = remove_single_unique(obesity_children)\n",
    "obesity_clean = remove_num_columns(obesity_single_unique)\n",
    "sex_race_his_obesity, race_his_obesity, total_obesity, poverty_obesity, sex_obesity, age_obesity = final_clean(obesity_clean)\n",
    "poverty_obesity.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5dea49f0-23e7-44dc-96ed-00da4cb80de3",
   "metadata": {},
   "source": [
    "**Data - Obesity Among Adults 20+** - https://catalog.data.gov/dataset/normal-weight-overweight-and-obesity-among-adults-aged-20-and-over-by-selected-characteris-8e2b1"
   ]
  },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>INDICATOR</th>\n",
       "      <th>PANEL</th>\n",
       "      <th>PANEL_NUM</th>\n",
       "      <th>UNIT</th>\n",
       "      <th>UNIT_NUM</th>\n",
       "      <th>STUB_NAME</th>\n",
       "      <th>STUB_NAME_NUM</th>\n",
       "      <th>STUB_LABEL</th>\n",
       "      <th>STUB_LABEL_NUM</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>YEAR_NUM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>AGE_NUM</th>\n",
       "      <th>ESTIMATE</th>\n",
       "      <th>SE</th>\n",
       "      <th>FLAG</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Race</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Normal weight, overweight, and obesity among a...</td>\n",
       "      <td>Normal weight (BMI from 18.5 to 24.9)</td>\n",
       "      <td>1</td>\n",
       "      <td>Percent of population, age-adjusted</td>\n",
       "      <td>1</td>\n",
       "      <td>Sex and race and Hispanic origin</td>\n",
       "      <td>4</td>\n",
       "      <td>Male: Not Hispanic or Latino: White only</td>\n",
       "      <td>3.111</td>\n",
       "      <td>2015-2018</td>\n",
       "      <td>10</td>\n",
       "      <td>20 years and over</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>.</td>\n",
       "      <td>Male</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Normal weight, overweight, and obesity among a...</td>\n",
       "      <td>Normal weight (BMI from 18.5 to 24.9)</td>\n",
       "      <td>1</td>\n",
       "      <td>Percent of population, age-adjusted</td>\n",
       "      <td>1</td>\n",
       "      <td>Sex and race and Hispanic origin</td>\n",
       "      <td>4</td>\n",
       "      <td>Female: Not Hispanic or Latino: White only</td>\n",
       "      <td>3.112</td>\n",
       "      <td>2015-2018</td>\n",
       "      <td>10</td>\n",
       "      <td>20 years and over</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>.</td>\n",
       "      <td>Female</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>Normal weight, overweight, and obesity among a...</td>\n",
       "      <td>Normal weight (BMI from 18.5 to 24.9)</td>\n",
       "      <td>1</td>\n",
       "      <td>Percent of population, age-adjusted</td>\n",
       "      <td>1</td>\n",
       "      <td>Sex and race and Hispanic origin</td>\n",
       "      <td>4</td>\n",
       "      <td>Male: Not Hispanic or Latino: Black or African...</td>\n",
       "      <td>3.121</td>\n",
       "      <td>2015-2018</td>\n",
       "      <td>10</td>\n",
       "      <td>20 years and over</td>\n",
       "      <td>1.0</td>\n",
       "      <td>26.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>.</td>\n",
       "      <td>Male</td>\n",
       "      <td>Black or African American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>Normal weight, overweight, and obesity among a...</td>\n",
       "      <td>Normal weight (BMI from 18.5 to 24.9)</td>\n",
       "      <td>1</td>\n",
       "      <td>Percent of population, age-adjusted</td>\n",
       "      <td>1</td>\n",
       "      <td>Sex and race and Hispanic origin</td>\n",
       "      <td>4</td>\n",
       "      <td>Female: Not Hispanic or Latino: Black or Afric...</td>\n",
       "      <td>3.122</td>\n",
       "      <td>2015-2018</td>\n",
       "      <td>10</td>\n",
       "      <td>20 years and over</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>1.2</td>\n",
       "      <td>.</td>\n",
       "      <td>Female</td>\n",
       "      <td>Black or African American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>Normal weight, overweight, and obesity among a...</td>\n",
       "      <td>Normal weight (BMI from 18.5 to 24.9)</td>\n",
       "      <td>1</td>\n",
       "      <td>Percent of population, age-adjusted</td>\n",
       "      <td>1</td>\n",
       "      <td>Sex and race and Hispanic origin</td>\n",
       "      <td>4</td>\n",
       "      <td>Male: Not Hispanic or Latino: Asian only</td>\n",
       "      <td>3.131</td>\n",
       "      <td>2015-2018</td>\n",
       "      <td>10</td>\n",
       "      <td>20 years and over</td>\n",
       "      <td>1.0</td>\n",
       "      <td>41.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>.</td>\n",
       "      <td>Male</td>\n",
       "      <td>Asian</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "                                             INDICATOR  \\\n",
       "49   Normal weight, overweight, and obesity among a...   \n",
       "59   Normal weight, overweight, and obesity among a...   \n",
       "79   Normal weight, overweight, and obesity among a...   \n",
       "89   Normal weight, overweight, and obesity among a...   \n",
       "109  Normal weight, overweight, and obesity among a...   \n",
       "\n",
       "                                     PANEL  PANEL_NUM  \\\n",
       "49   Normal weight (BMI from 18.5 to 24.9)          1   \n",
       "59   Normal weight (BMI from 18.5 to 24.9)          1   \n",
       "79   Normal weight (BMI from 18.5 to 24.9)          1   \n",
       "89   Normal weight (BMI from 18.5 to 24.9)          1   \n",
       "109  Normal weight (BMI from 18.5 to 24.9)          1   \n",
       "\n",
       "                                    UNIT  UNIT_NUM  \\\n",
       "49   Percent of population, age-adjusted         1   \n",
       "59   Percent of population, age-adjusted         1   \n",
       "79   Percent of population, age-adjusted         1   \n",
       "89   Percent of population, age-adjusted         1   \n",
       "109  Percent of population, age-adjusted         1   \n",
       "\n",
       "                            STUB_NAME  STUB_NAME_NUM  \\\n",
       "49   Sex and race and Hispanic origin              4   \n",
       "59   Sex and race and Hispanic origin              4   \n",
       "79   Sex and race and Hispanic origin              4   \n",
       "89   Sex and race and Hispanic origin              4   \n",
       "109  Sex and race and Hispanic origin              4   \n",
       "\n",
       "                                            STUB_LABEL  STUB_LABEL_NUM  \\\n",
       "49            Male: Not Hispanic or Latino: White only           3.111   \n",
       "59          Female: Not Hispanic or Latino: White only           3.112   \n",
       "79   Male: Not Hispanic or Latino: Black or African...           3.121   \n",
       "89   Female: Not Hispanic or Latino: Black or Afric...           3.122   \n",
       "109           Male: Not Hispanic or Latino: Asian only           3.131   \n",
       "\n",
       "          YEAR  YEAR_NUM                AGE  AGE_NUM  ESTIMATE   SE FLAG  \\\n",
       "49   2015-2018        10  20 years and over      1.0      23.4  1.4    .   \n",
       "59   2015-2018        10  20 years and over      1.0      31.9  1.7    .   \n",
       "79   2015-2018        10  20 years and over      1.0      26.4  1.7    .   \n",
       "89   2015-2018        10  20 years and over      1.0      19.2  1.2    .   \n",
       "109  2015-2018        10  20 years and over      1.0      41.9  1.7    .   \n",
       "\n",
       "     Gender                       Race  \n",
       "49     Male                      White  \n",
       "59   Female                      White  \n",
       "79     Male  Black or African American  \n",
       "89   Female  Black or African American  \n",
       "109    Male                      Asian  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obesity_adult = pd.read_csv(\"Datasets/Normal_weight__overweight__and_obesity_among_adults_aged_20_and_over__by_selected_characteristics__United_States.csv\")\n",
    "panelDict, unitDict, stubNameDict, stubLabelDict, yearDict, ageDict = getMapping(obesity_adult)\n",
    "raceGender_df = cleanGenderRace(obesity_adult)\n",
    "age_df = cleanAge(obesity_adult)\n",
    "raceGender_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a993f428-72d3-4bf3-8166-f1313a8e114e",
   "metadata": {},
   "source": [
    "**Data - Nutrition, Physical Activity, and Obesity** - https://catalog.data.gov/dataset/nutrition-physical-activity-and-obesity-behavioral-risk-factor-surveillance-system\n",
    "\n",
    "To clean this dataset we removed columns that were unnesscary for analysis. The NaN values you see below are there because they only give data based on stratification. We subsetted the data to only keep the stratifications needed which were education, gender, race/ethnicity, and income."
   ]
  },
  {
   "cell_type": "code",
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   "id": "8337a5be-8cb2-4662-98c4-8af78bb75045",
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>YearStart</th>\n",
       "      <th>LocationAbbr</th>\n",
       "      <th>LocationDesc</th>\n",
       "      <th>Datasource</th>\n",
       "      <th>Class</th>\n",
       "      <th>Topic</th>\n",
       "      <th>Question</th>\n",
       "      <th>Data_Value_Type</th>\n",
       "      <th>Data_Value</th>\n",
       "      <th>Data_Value_Alt</th>\n",
       "      <th>...</th>\n",
       "      <th>Education</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Income</th>\n",
       "      <th>Race/Ethnicity</th>\n",
       "      <th>GeoLocation</th>\n",
       "      <th>LocationID</th>\n",
       "      <th>StratificationCategory1</th>\n",
       "      <th>Stratification1</th>\n",
       "      <th>StratificationCategoryId1</th>\n",
       "      <th>StratificationID1</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015</td>\n",
       "      <td>GU</td>\n",
       "      <td>Guam</td>\n",
       "      <td>Behavioral Risk Factor Surveillance System</td>\n",
       "      <td>Physical Activity</td>\n",
       "      <td>Physical Activity - Behavior</td>\n",
       "      <td>Percent of adults who achieve at least 150 min...</td>\n",
       "      <td>Value</td>\n",
       "      <td>27.4</td>\n",
       "      <td>27.4</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>(13.444304, 144.793731)</td>\n",
       "      <td>66</td>\n",
       "      <td>Race/Ethnicity</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>RACE</td>\n",
       "      <td>RACEHIS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012</td>\n",
       "      <td>WY</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Behavioral Risk Factor Surveillance System</td>\n",
       "      <td>Obesity / Weight Status</td>\n",
       "      <td>Obesity / Weight Status</td>\n",
       "      <td>Percent of adults aged 18 years and older who ...</td>\n",
       "      <td>Value</td>\n",
       "      <td>48.5</td>\n",
       "      <td>48.5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>American Indian/Alaska Native</td>\n",
       "      <td>(43.235541343, -108.109830353)</td>\n",
       "      <td>56</td>\n",
       "      <td>Race/Ethnicity</td>\n",
       "      <td>American Indian/Alaska Native</td>\n",
       "      <td>RACE</td>\n",
       "      <td>RACENAA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2011</td>\n",
       "      <td>AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>Behavioral Risk Factor Surveillance System</td>\n",
       "      <td>Obesity / Weight Status</td>\n",
       "      <td>Obesity / Weight Status</td>\n",
       "      <td>Percent of adults aged 18 years and older who ...</td>\n",
       "      <td>Value</td>\n",
       "      <td>35.2</td>\n",
       "      <td>35.2</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>(32.840571122, -86.631860762)</td>\n",
       "      <td>1</td>\n",
       "      <td>Age (years)</td>\n",
       "      <td>25 - 34</td>\n",
       "      <td>AGEYR</td>\n",
       "      <td>AGEYR2534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2015</td>\n",
       "      <td>RI</td>\n",
       "      <td>Rhode Island</td>\n",
       "      <td>Behavioral Risk Factor Surveillance System</td>\n",
       "      <td>Obesity / Weight Status</td>\n",
       "      <td>Obesity / Weight Status</td>\n",
       "      <td>Percent of adults aged 18 years and older who ...</td>\n",
       "      <td>Value</td>\n",
       "      <td>40.2</td>\n",
       "      <td>40.2</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>(41.708280193, -71.522470314)</td>\n",
       "      <td>44</td>\n",
       "      <td>Race/Ethnicity</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>RACE</td>\n",
       "      <td>RACEHIS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2020</td>\n",
       "      <td>DE</td>\n",
       "      <td>Delaware</td>\n",
       "      <td>Behavioral Risk Factor Surveillance System</td>\n",
       "      <td>Physical Activity</td>\n",
       "      <td>Physical Activity - Behavior</td>\n",
       "      <td>Percent of adults who engage in no leisure-tim...</td>\n",
       "      <td>Value</td>\n",
       "      <td>15.3</td>\n",
       "      <td>15.3</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Missing Data</td>\n",
       "      <td>Asian</td>\n",
       "      <td>(39.008830667000495, -75.57774116799965)</td>\n",
       "      <td>10</td>\n",
       "      <td>Race/Ethnicity</td>\n",
       "      <td>Asian</td>\n",
       "      <td>RACE</td>\n",
       "      <td>RACEASN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    YearStart LocationAbbr  LocationDesc  \\\n",
       "5        2015           GU          Guam   \n",
       "6        2012           WY       Wyoming   \n",
       "9        2011           AL       Alabama   \n",
       "11       2015           RI  Rhode Island   \n",
       "14       2020           DE      Delaware   \n",
       "\n",
       "                                    Datasource                    Class  \\\n",
       "5   Behavioral Risk Factor Surveillance System        Physical Activity   \n",
       "6   Behavioral Risk Factor Surveillance System  Obesity / Weight Status   \n",
       "9   Behavioral Risk Factor Surveillance System  Obesity / Weight Status   \n",
       "11  Behavioral Risk Factor Surveillance System  Obesity / Weight Status   \n",
       "14  Behavioral Risk Factor Surveillance System        Physical Activity   \n",
       "\n",
       "                           Topic  \\\n",
       "5   Physical Activity - Behavior   \n",
       "6        Obesity / Weight Status   \n",
       "9        Obesity / Weight Status   \n",
       "11       Obesity / Weight Status   \n",
       "14  Physical Activity - Behavior   \n",
       "\n",
       "                                             Question Data_Value_Type  \\\n",
       "5   Percent of adults who achieve at least 150 min...           Value   \n",
       "6   Percent of adults aged 18 years and older who ...           Value   \n",
       "9   Percent of adults aged 18 years and older who ...           Value   \n",
       "11  Percent of adults aged 18 years and older who ...           Value   \n",
       "14  Percent of adults who engage in no leisure-tim...           Value   \n",
       "\n",
       "    Data_Value  Data_Value_Alt  ...  Education        Gender        Income  \\\n",
       "5         27.4            27.4  ...        NaN  Missing Data  Missing Data   \n",
       "6         48.5            48.5  ...        NaN  Missing Data  Missing Data   \n",
       "9         35.2            35.2  ...        NaN  Missing Data  Missing Data   \n",
       "11        40.2            40.2  ...        NaN  Missing Data  Missing Data   \n",
       "14        15.3            15.3  ...        NaN  Missing Data  Missing Data   \n",
       "\n",
       "                   Race/Ethnicity                               GeoLocation  \\\n",
       "5                        Hispanic                   (13.444304, 144.793731)   \n",
       "6   American Indian/Alaska Native            (43.235541343, -108.109830353)   \n",
       "9                    Missing Data             (32.840571122, -86.631860762)   \n",
       "11                       Hispanic             (41.708280193, -71.522470314)   \n",
       "14                          Asian  (39.008830667000495, -75.57774116799965)   \n",
       "\n",
       "   LocationID StratificationCategory1                Stratification1  \\\n",
       "5          66          Race/Ethnicity                       Hispanic   \n",
       "6          56          Race/Ethnicity  American Indian/Alaska Native   \n",
       "9           1             Age (years)                        25 - 34   \n",
       "11         44          Race/Ethnicity                       Hispanic   \n",
       "14         10          Race/Ethnicity                          Asian   \n",
       "\n",
       "   StratificationCategoryId1 StratificationID1  \n",
       "5                       RACE           RACEHIS  \n",
       "6                       RACE           RACENAA  \n",
       "9                      AGEYR         AGEYR2534  \n",
       "11                      RACE           RACEHIS  \n",
       "14                      RACE           RACEASN  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "activity_df = pd.read_csv(\"Datasets/Nutrition__Physical_Activity__and_Obesity_-_Behavioral_Risk_Factor_Surveillance_System.csv\")\n",
    "cleaned_df = clean_data(\"Datasets/Nutrition__Physical_Activity__and_Obesity_-_Behavioral_Risk_Factor_Surveillance_System.csv\")\n",
    "cleaned_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "755c6161-2f3c-4dd8-bd48-5bdb65e6d0f0",
   "metadata": {},
   "source": [
    "## Machine Learning Analysis\n",
    "**Linear Regression Model**\n",
    "\n",
    "**Question**: Based on the trend of the rate of obesity of adult in the US between 1988 and 2018, what will be the rate of obesity in the US in 2024?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2574edb1-342b-4316-9b30-fd5b9e8dceae",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "import sklearn.metrics as sm\n",
    "\n",
    "# prepare data for ML\n",
    "middleYearDict = getMiddleYear(yearDict)  \n",
    "generalObesity = getFilteredData(obesity_adult, 1, 3, 1, 1.1, middleYearDict)\n",
    "x = generalObesity[\"MiddleYear\"]\n",
    "y = generalObesity[\"ESTIMATE\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "475ffd3d-a180-49a8-8c4d-c3f18d89c9d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean squared error:  22.442400000000003\n"
     ]
    }
   ],
   "source": [
    "# baseline ML model: mean\n",
    "baselineML = MeanModel()\n",
    "fitAndEvaluate(baselineML, x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0875df65-e303-4551-8606-9be6b989baf0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean squared error:  0.5901431713657087\n"
     ]
    }
   ],
   "source": [
    "# linear regression model\n",
    "linRegressML = LinearRegressionModel()\n",
    "fitAndEvaluate(linRegressML, x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f9a968b4-66ee-4eeb-b3e2-4e3c85c01c6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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6Ta4bkJKEX375Bd9//z2OHj2KP//8E5cvX4aNjU2W/paa3Dt13r59m+5nJ227pt6+fQtdXV2VDhUymQx2dnYqZWZ0b9P2ffXqFW7evKlyjWZmZhBCKP5Wnp6e2LdvH5KTk9GnTx8UL14cbm5u2LZtm8bXkaZDhw5wdnZWtIXz9/dHbGwshg0b9tllZuUz9TmMjY1haGioUm58fLxi+dWrV4iIiIC+vr7K/QwLC1P5rvmUrq4uUlJS0t2enJwMPT09lfUVK1bE6NGjsXnzZoSGhmLRokV4+/Ytpk6dquFVUlYUri44hCJFiqBp06Y4cuQInj9/nukPctqX0MuXL1X2ffHiBaytrTWOQVdXF2PHjsXYsWMRERGBEydOYNKkSWjRogWePXuWbi8pd3d3bN++HUII3Lx5E/7+/pgxYwaMjIwwYcKEDM9pbW0NDw8PzJo1S+32tB+zvMrGxkalgX56Pm0gmvY3Wr58ebq9oIoVKwYA2Lx5M/r06YPZs2crbQ8PD4eFhYViObO/oaWlJYoUKYLevXun+yNYqlQpANJ7LCwsTGW7unUZ+fS6IyMjcfDgQUyfPl3p/ZGQkJDl7tua3Dt1ihYtipcvX6qsf/HihVL5mihatCiSk5Px5s0bpQRKCIGwsDBF7VCajO5t2ufb2toaRkZGajsqfBpnhw4d0KFDByQkJODixYvw8/NDz5494ezsjLp162p8PTo6Ohg2bBgmTZqEhQsXYuXKlWjatCnKly+vcVl5gbW1NYoWLZpuj+WPa8TUKVasGOLj4/Hu3TtYWVkpbXv79i0SEhIyfM8B0mdhzJgxmDFjBm7fvq3ZBVCWsOapEJo4cSKEEBg4cCASExNVticlJeGPP/4AIPV4AaQf1Y9dvnwZf/31F5o2bfpFsVhYWKBLly4YNmwY3r17l6XeajKZDJUrV8bixYthYWGhePQApP+vy7Zt2+L27dsoU6YMatSoofL6nOQpJ2ujPtWqVSucPn36s6rg69evDwsLC9y9e1fttdeoUQP6+voApHv7aQ/MQ4cOZfh4Rt3f0NjYGE2aNMH169fh4eGh9pxpP9xNmjTBnTt3cOPGDaVyt27dqvG1fkwmk0EIoXI9a9euVfmXfXp/S03unTpNmzbF3bt3ld6jALBx40bIZDI0adJE4+tK+8x9+pncvXs3YmNjVT6T6d1bMzMzVKtWDYD0+fjnn39QtGhRtdeobiBKAwMDNGrUCHPnzgUg9YZNT2afle+//x76+vro1asX7t+/j+HDh2dwB3JOdnym27Zti7dv3yIlJUXtvcwsKfz6668BADt27FDZ9vvvvyvtA0Btcg5ICXpUVFSe/4dhfsWap0Kobt26WLVqFYYOHYrq1avD29sblSpVQlJSEq5fv47ffvsNbm5uaNeuHcqXL49BgwZh+fLl0NHRQatWrfDkyRNMnToVJUqU+KyB/Nq1awc3NzfUqFEDNjY2ePr0KZYsWQInJye4uLioPebgwYNYuXIlOnbsiNKlS0MIgT179iAiIgLNmjVT7Ofu7o4zZ87gjz/+gL29PczMzFC+fHnMmDEDx48fR7169TBy5EiUL18e8fHxePLkCQ4fPozVq1dn+bHYx+cCgLlz56JVq1YoUqQIPDw8Mvwx/VwzZszAkSNH4OnpiUmTJsHd3R0REREIDAzE2LFjUaFChXSPNTU1xfLly+Hl5YV3796hS5cusLW1xZs3b3Djxg28efMGq1atAiB98fv7+6NChQrw8PDA1atXMX/+fJV7k5W/4dKlS9GgQQM0bNgQ3t7ecHZ2RnR0NB4+fIg//vhD0XZn9OjRWL9+Pdq0aYOZM2eiWLFi2LJlC+7du/dF98zc3Byenp6YP38+rK2t4ezsjKCgIKxbt06pFg0A3NzcAAC//fYbzMzMYGhoiFKlSqFo0aJZvnfqjBkzBhs3bkSbNm0wY8YMODk54dChQ1i5ciW8vb1Rrlw5ja+rWbNmaNGiBcaPH4+oqCjUr18fN2/exPTp01G1alX07t1baX8HBwe0b98ePj4+sLe3x+bNm3H8+HHMnTtXUcs7evRo7N69G56enhgzZgw8PDyQmpqK0NBQHDt2DOPGjUPt2rUxbdo0PH/+HE2bNkXx4sURERGBpUuXQk9PD40aNUo35rTPytKlS+Hl5QU9PT2UL19eUQtjYWGBPn36YNWqVXByclJpV5RbypQpAyMjI2zZsgUVK1aEqakpHBwcNEpAvv32W2zZsgWtW7fGqFGjUKtWLejp6eH58+c4ffo0OnTogE6dOqV7fJMmTdC+fXuMGjUKT548QaNGjSCEwNmzZ7F48WK0b99eaQiWQYMGISIiAp07d4abmxuKFCmCe/fuYfHixdDR0cH48eMV+86YMQMzZszAyZMnM/x7URZoq6U6aV9ISIjw8vISJUuWFPr6+oquztOmTVPqpZGSkiLmzp0rypUrJ/T09IS1tbX47rvvFF140zRq1EhUqlRJ5Tyf9ohZuHChqFevnrC2thb6+vqiZMmSYsCAAeLJkyeKfT7tbXfv3j3Ro0cPUaZMGWFkZCTkcrmoVauW8Pf3V7mm+vXrC2NjYwFANGrUSLHtzZs3YuTIkaJUqVJCT09PWFlZierVq4vJkyeLmJgYIcR/PYU+7sadBoCYPn26YjkhIUF8//33wsbGRshksnR7E318H9T1tlPXw6pRo0ZKsQshdfnu37+/sLOzE3p6esLBwUF069ZNvHr1SgjxX2+7nTt3qj1/UFCQaNOmjbCyshJ6enrC0dFRtGnTRmn/9+/fiwEDBghbW1thbGwsGjRoIM6dO6cST1b+hkJI97N///7C0dFR6OnpCRsbG1GvXj0xc+ZMpf3u3r0rmjVrJgwNDYWVlZUYMGCA2L9/v0a97T4eNiPN8+fPRefOnYWlpaUwMzMTLVu2FLdv3xZOTk4qvTKXLFkiSpUqJYoUKaLS4yor9y49T58+FT179hRFixYVenp6onz58mL+/PkiJSVFab+s9rYTQuqROX78eOHk5CT09PSEvb298Pb2Fu/fv1db5q5du0SlSpWEvr6+cHZ2FosWLVIpMyYmRkyZMkWUL19e6OvrK4aZGDNmjAgLCxNCCHHw4EHRqlUr4ejoKPT19YWtra1o3bq1OHfunKIcdb3thBBi4sSJwsHBQejo6Kj9u545c0YAEHPmzMnSPRAi/d52w4YNU9lX3d9cnW3btokKFSoIPT09pc98er3g0t5/H0tKShILFiwQlStXFoaGhsLU1FRUqFBBDB48WDx48CDTGBITE8Xs2bNFpUqVhIGBgTAwMBCVKlUSs2fPFomJiUr7Hj16VPTv31+4uroKuVwudHV1hb29vfjmm29EcHCw2lgz+0xR5mRCcPhRIiLSrnHjxmHVqlV49uyZ2gbfRHkJH9sREZHWXLx4EX///TdWrlyJwYMHM3GifIE1T0REpDUymQzGxsZo3bo1NmzY8NljOxHlJtY8ERGR1vDf75QfcagCIiIiIg0U6OTp49nuM3qdOXNGMbP5rl27tB12puLi4uDj45Ptw/xrIjExEUOGDIG9vT2KFCmCKlWqfHGZffv21UqVvbOzs9JUFy9evICPjw9CQkKy9Tz+/v6QyWRZGssqq2bPno19+/ale66MRm3PDpmdp23btipjBL19+xYTJ06Eq6srTExMIJfLUaFCBfTu3Rs3b97M8HxPnjyBTCaDv79/Nl2BNO5Tx44d4ezsDCMjI5QtWxbe3t7pjp+zfft2VKlSBYaGhnBwcMDo0aMRExOjtM+pU6fQv39/VKhQASYmJnB0dESHDh1w9erVDGMRQsDT0xMymSzLYx19+v7N7z69nrTvZk2/7y5cuAAfHx9ERERka3yA9F2lbuyrT61cuTJb36tpnJ2d0bZt22wvNzPfffcdZDKZ2nM7Ozur/X0dMmRIlspO7/d5zpw5GR43ZcoUyGQyxXAjH1u1ahWcnZ1haWmJ7777TuW9kDZtzrRp07IU48cK9GO74OBgpeWff/4Zp0+fVplPytXVVWUQu7wsLi4Ovr6+AKA03kduWrVqFX799VcsX74c1atXz9ftFPbu3Qtzc3PF8osXL+Dr6wtnZ+dsSQrTtGnTBsHBwWqn6/hcs2fPRpcuXdCxY8dsKzMnxcTEoE6dOoiJicGPP/6omPbl77//xp49exASEqKYR1Ade3t7BAcHo0yZMtkW0/Tp09GkSRPMnj0bjo6OuH//Pn7++Wfs378f169fVxrNecuWLfjuu+/w/fffY/Hixfj7778xfvx43L17F8eOHVPst2rVKrx9+xajRo2Cq6sr3rx5g4ULF6JOnTo4evSoYvDZT61YsQIPHz7UKP5P378FTbVq1RAcHAxXV1eNjrtw4QJ8fX3Rt29flXG9csvKlSthbW1dIJLbQ4cOYd++fRm+1+rXr48FCxYorctsNPSPdenSBePGjVNa9/G8n58KCQnBggUL1J7j7NmzGDFiBBYuXIiyZctizJgx+OGHH7B27VrFPosWLUJcXBwmT56c5RjTFOjk6dPpFGxsbKCjo5PuNAvakpSUBJlMBl3d/PPnuH37NoyMjLQ2EnB2qlq1aq6cx8bGRmU+ssJm586dePjwIU6dOqUyuvbYsWORmpqa4fEGBgbZ/vm9fv06bG1tFcuNGjVCtWrVULNmTaxZswZTpkwBAKSkpODHH39E8+bNsWbNGgD/TUDbq1cvHDlyRDHR9IoVK5TKBICWLVuibNmymD17ttrk6cmTJ5g4cSI2btyIb775Jsvx59b7NzNxcXHpTq30JczNzfPcd3ZhExkZicGDB+Pnn3/G0qVL093PwsLii/5WxYoVy/LxycnJ6NevHwYPHowbN26ozBl46NAhNG3aFKNGjVJcw9ixYxXbHz9+DF9fXxw8eFBlFoKsKNCP7T5HUlISJk+eDAcHB5ibm+Prr79WOyXGiRMn0LRpU5ibm8PY2Bj169dXmc1cnbQq6E2bNmHcuHFwdHSEgYEBHj58iDdv3mDo0KFwdXWFqakpbG1t8dVXX+HcuXOK4588eaL4Afb19VVUbX78L5sHDx6gZ8+esLW1hYGBASpWrKiYdDMz8fHxmDhxIkqVKgV9fX04Ojpi2LBhStWdMpkMa9euxYcPHxTnz6xqev369ahcuTIMDQ1hZWWFTp06pTur/Z07d9C0aVOYmJjAxsYGw4cPR1xcnNI+QgisXLkSVapUgZGRESwtLdGlSxc8evRIab/r16+jbdu2invh4OCANm3aKM0T9/FjgjNnzijmBuvXr5/i+nx8fLBp0ybIZDKVGk1AGrlXT09PMWeZOuoe2zVu3Bhubm64fPkyGjZsCGNjY5QuXRpz5szJNJGQyWSIjY1FQECAIs5PayKjo6Ph7e2tmG/rm2++URvjjh07ULduXZiYmMDU1BQtWrTIcLqNz5XRRNOANM9ZRtQ9tvPx8YFMJsOdO3fQo0cPyOVyFCtWDP3790dkZGSmMX2a5ABA9erVUaRIETx79kyx7uLFi3j58iX69euntG/Xrl1hamqKvXv3ZlimqakpXF1dlcr82KBBg9CsWbMMR59W59PHXKmpqZg5cybKly8PIyMjWFhYwMPDI8MfPeC/76bNmzdj7NixsLOzg5GRERo1aqTyXkh7xH7r1i00b94cZmZmimlhEhMTMXPmTFSoUAEGBgawsbFBv3798ObNG6UykpKS8NNPP8HOzg7GxsZo0KAB/vzzz3Tj+vSx3aVLl9CuXTsULVoUhoaGKFOmDEaPHg1Aek/8+OOPAKQ5FD9uopEmq+95f39/lC9fXvFdunHjxgzvYxpnZ2fcuXMHQUFBivN//KgvNDQU3333ndL39MKFCzP93H9s79698PDwgKGhIUqXLo1ly5ap7BMVFYUffvhB6Tt99OjRiI2NzfJ5xo0bB3t7e4wcOTLLx+S0OXPm4N27d+nOVxofHw8TExPFsqmpqdIEzt7e3ujevftnTZEEoHCNMJ7eCLFC/Dc6s7Ozs+jVq5c4dOiQ2LZtmyhZsqRwcXERycnJin03bdokZDKZ6Nixo9izZ4/4448/RNu2bUWRIkXEiRMnMowh7TyOjo6iS5cu4sCBA+LgwYPi7du34t69e8Lb21ts375dnDlzRhw8eFAMGDBA6OjoKEaEjY+PF4GBgQKAGDBggAgODhbBwcHi4cOHQggh7ty5oxgZeOPGjeLYsWNi3LhxQkdHR/j4+GQYW2pqqmjRooXQ1dUVU6dOFceOHRMLFixQjDweHx8vhBAiODhYtG7dWhgZGSnO//GI5J+aPXu2ACB69OghDh06JDZu3ChKly4t5HK5+Pvvv5X+PmmjVc+aNUscO3ZM+Pj4CF1dXdG2bVulMgcOHCj09PTEuHHjRGBgoNi6dauoUKGCKFasmGI05JiYGFG0aFFRo0YN8fvvv4ugoCCxY8cOMWTIEHH37l1FWR+PPBwZGakY3XzKlCmK63v27JlISEgQdnZ2olevXkqxJCUlCQcHB9G1a9cM7++no6YLIY0kXrRoUeHi4iJWr14tjh8/LoYOHSoAiICAgAzLCw4OFkZGRqJ169aKOO/cuaN0rtKlS4sRI0aIo0ePirVr1wpLS0vRpEkTpXJmzZolZDKZ6N+/vzh48KDYs2ePqFu3rjAxMVGUl9k1Xb58We32Nm3aKI0Aff78eQFA1KxZU+zdu1eEh4dnWP6n1I1enTZqcvny5cW0adPE8ePHxaJFi4SBgYHo16+fRuWnSfucLl26VLFu9erVAoDae1KjRg1Rt27dDMuMiIgQcrlcdOrUSWXbmjVrhFwuF//++68QIv1RstX5dORsPz8/UaRIETF9+nRx8uRJERgYKJYsWZLp5z/tmkuUKCE6dOgg/vjjD7F582ZRtmxZYW5uLv755x/Fvl5eXkJPT084OzsLPz8/cfLkSXH06FGRkpIiWrZsKUxMTISvr684fvy4WLt2rXB0dBSurq4iLi5OqQyZTCZ+/PFHcezYMbFo0SLh6OgozM3Nla4nLa6PR8UODAwUenp6wsPDQ/j7+4tTp06J9evXi2+//VYIIY3GP2LECAFA7NmzR/H5iIyMFEJk/T2f9v7+9H6UKFFCZWTzT127dk2ULl1aVK1aVXH+a9euCSGEeP36tXB0dBQ2NjZi9erVIjAwUAwfPlwAEN7e3hmWK4T0N3d0dBQlS5YU69evF4cPHxa9evVSmR0hNjZWVKlSRVhbW4tFixaJEydOiKVLlwq5XC6++uorkZqamum5jh8/LvT09ERISIji3OpGwndychJmZmbC1NRU6OrqiooVK4oFCxYo/XZmBICwtLQUhoaGQl9fX1SrVk2sX79e7b537twRBgYG4tChQ0II9bNbbN++XZiYmIgLFy6IV69eiaZNm4pWrVoJIYTYsmWLsLGx0fj7Rynezz4yH8pK8tS6dWul9b///rsAoBjmPjY2VlhZWYl27dop7ZeSkiIqV64satWqlWEMaefx9PTMNN7k5GSRlJQkmjZtqvSF++bNG5WpQtK0aNFCFC9eXPElkWb48OHC0NBQvHv3Lt3zpSVl8+bNU1q/Y8cOAUD89ttvinUZ3cuPvX//XvED/7HQ0FBhYGAgevbsqVTmpz9YQkhfdADE+fPnhRBS0gBALFy4UGm/Z8+eCSMjI/HTTz8JIYS4cuWKACD27duXYYyf/vhcvnxZ7fQSQkg/1Pr6+oopUYT47/4EBQVleJ70kicA4tKlS0r7urq6ihYtWmRYnhBCmJiYqJ1yIu1cQ4cOVVo/b948AUC8fPlSCCH9HXR1dcWIESOU9ouOjhZ2dnaiW7duWbqmrCZPQggxY8YMoa+vLwAIAKJUqVJiyJAh4saNG5lcbcbJ06fv26FDhwpDQ8Ms/UB8LCoqSlSsWFGUKFFCREdHK9anvQ/T7t3HmjdvLsqVK5dhub169RK6urriypUrSuufP38u5HK5+PXXXxXrviR5atu2rahSpUqWjv1Y2ndTtWrVlO7ZkydPhJ6envj+++8V69I+q5/+uG3btk0AELt371Zan/aZWrlypRBCiL/++ksAEGPGjFHab8uWLQJApslTmTJlRJkyZcSHDx/SvZ758+ernTIpq+/5lJQU4eDgkO79yCx5EkKISpUqqUyzJIQQEyZMUPu59/b2FjKZTNy/fz/Dcp2cnIRMJlMkNGmaNWsmzM3NRWxsrBBCSqR1dHRUPp+7du0SAMThw4czPE90dLRwdnYWEydOVDq3uuRp6NChYv369SIoKEjs27dPkcx99913GZ4jTc+ePcWWLVvE2bNnxa5du0SrVq0U/4j9WEpKiqhdu7bo0aOHYp265Ck1NVXxPk37x9Xff/8t3r59K2xtbcWmTZuyFFd6+NjuE+3bt1daTmu8+vTpUwBSI8R3797By8sLycnJildqaipatmyJy5cvZ6k6tHPnzmrXr169GtWqVYOhoSF0dXWhp6eHkydPpvuI62Px8fE4efIkOnXqBGNjY6X4Wrdujfj4eFy8eDHd49Ma0n/auLFr164wMTHJ0mPJTwUHB+PDhw8qZZYoUQJfffWV2jJ79eqltNyzZ08AwOnTpwFIkwTLZDJ89913StdoZ2eHypUrK6rmy5YtC0tLS4wfPx6rV6/G3bt3NY7/U97e3gCgaPMCAL/88gvc3d3h6en5WWXa2dmhVq1aSus8PDwU77kvkdn7+ejRo0hOTkafPn2U7qWhoSEaNWqUIz06p06ditDQUKxfvx6DBw+GqakpVq9ejerVq2Pbtm2fXa66a42Pj8fr16+zXEZ8fDy++eYbPH36FDt37lTbEUImk6k9Nr31gHTNW7ZsweLFi1G9enWlbUOGDEHlypUxcODALMeZkVq1auHGjRsYOnQojh49iqioKI2O79mzp9K1ODk5oV69eorP38c+/R47ePAgLCws0K5dO6X3U5UqVWBnZ6d4P6WV9elnvVu3bpm2/fz777/xzz//YMCAATA0NNTo2oCsv+fv37+PFy9epHs/vsSpU6fg6uqq8rnv27cvhBAqnZrUqVSpEipXrqy0rmfPnoiKilJ0gDp48CDc3NxQpUoVpWtt0aJFlnowTpgwAXp6elnqjbZixQr069cPnp6e6NChAzZv3ozhw4dj8+bNWWoCsGXLFvTs2RMNGzZE586dcfjwYbRt2xZz5sxReuS7aNEiPHjwAEuWLMmwvLTH+69fv8aDBw9w9+5duLi4KDqqfPfdd7h16xYaNWoES0tL1KhRQ6mJTGaYPH3i06kB0hqSffjwAQDw6tUrAFKvAD09PaXX3LlzIYTAu3fvMj2PujYfixYtgre3N2rXro3du3fj4sWLuHz5Mlq2bKk4f0bevn2L5ORkLF++XCW21q1bA4BKo7pPj9fV1VVp1CyTyWBnZ6dor6KJjNq4ODg4qJSpq6ur8jews7NTKuvVq1cQQqBYsWIq13nx4kXFNcrlcgQFBaFKlSqYNGkSKlWqBAcHB0yfPh1JSUkaXwsgNWjs3r07fv31V6SkpODmzZs4d+7cFzWcVzcdhYGBQZb+5pqWnd77uWbNmir3cseOHRm+XwAofuhSUlLUbk9OToaenp7K+mLFiqFfv35YvXo1bt68iaCgIOjr6ysad36OzK41MwkJCejUqRPOnz+PAwcOoHbt2mrLV/c5ePfuHaysrNSW6+vri5kzZ2LWrFkq75Ndu3YhMDAQ8+bNQ2RkJCIiIhTtCxMTExEREaHxe3XixIlYsGABLl68iFatWqFo0aJo2rRploetSPu8fbru0+s2NjZW6Xn16tUrREREQF9fX+X9FBYWpng/pZX16bnUff4/lfZDWrx48Sxdz6ey+p5PL8b01mni7du36X4nfnzujGQU18fflTdv3lS5TjMzMwghMvx8//nnn1i5ciXmzZuH+Ph4xXszNTUVycnJiIiIQEJCQoYxfvfddwCQ4T/aMzs+OTlZ8d4NDQ3FtGnTMH36dOjr6ytiSqvAiIiIUPm829jYoGzZstDR0UFQUBC2b9+OVatWISkpCR07dkTjxo3x4sULDBo0CB06dMjS7zdQwHvb5QRra2sAwPLly9PtFZCVrpnq/pW6efNmNG7cGKtWrVJaHx0dnaXYLC0tUaRIEfTu3RvDhg1Tu0+pUqXSPb5o0aJITk7GmzdvlBIoIQTCwsIUDak1kfZFqG7MnBcvXijuZ5rk5GS8fftW6Qs0LCxMqSxra2vIZDKcO3dObS+Jj9e5u7tj+/btEELg5s2b8Pf3x4wZM2BkZIQJEyZofD0AMGrUKGzatAn79+9HYGAgLCwsVP4FnV+k3f9du3bByclJ4+PT3uv//vuv2u3//vtvlj4Pnp6eaN68Ofbt24fXr1+rbXCdkxISEtCxY0ecPn0a+/fvVzR+/pi7uzsA4NatW0rd5pOTk3Hv3j306NFD5RhfX1/4+PjAx8cHkyZNUtl++/ZtJCcnq/0uWbNmDdasWYO9e/dqNBSFrq4uxo4di7FjxyIiIgInTpzApEmT0KJFCzx79izTHnFpn7dP132a1Kj7DkvrmBAYGKi2bDMzMwD/fZbDwsLg6Oio2J72+c9I2nfTx50+NJHV9/zHMX5K3TpNFC1aNN3vxI9jzEhGcX38XWlkZIT169erLSOj89y9exdCCLUdGJ49ewZLS0ssXrxY0UhfHfH/o8dn1hEkq8c/evQIHz58wKhRo9T+Q8vS0hKjRo1SWyuVkJCAwYMHY+rUqShTpgxu376NR48e4YcffoCRkREGDRqEiRMnIjg4GG3atMk0NiZPGqpfvz4sLCxw9+7dbO+mL5PJVJKBmzdvIjg4GCVKlFCsS+9f1MbGxmjSpAmuX78ODw8P6Ovra3T+pk2bYt68edi8eTPGjBmjWL97927Exsaq/UHJTN26dWFkZITNmzeja9euivXPnz/HqVOn0KVLF5VjtmzZotSrY+vWrQD+G9MqrSr333//Rbdu3bIUh0wmQ+XKlbF48WL4+/tnOK5XZjUW1atXR7169TB37lzcvn0bgwYNUurVkZu+tIaqRYsW0NXVxT///JPuo+SM1KlTB6amptixY4dK9/q7d+/izp07SlX+r169UgwZ8rGUlBQ8ePAAxsbGuT4mT1qN06lTp7Bnzx60aNFC7X61a9eGvb09/P390b17d8X6Xbt2ISYmRuX6f/75Z/j4+GDKlCmYPn262jL79u2rdqy2Jk2aoGPHjhg1apTawf+yysLCAl26dMG///6L0aNH48mTJ5mOl7Rt2zaMHTtWkRw9ffoUFy5cQJ8+fTI9X9u2bbF9+3akpKSo1Nx9LO2at2zZovQY8/fff0dycnKG5yhXrhzKlCmD9evXY+zYsel2M0/vc5zV93z58uVhb2+f7v1IqyXKSHqfz6ZNm8LPzw/Xrl1DtWrVFOs3btwImUyWpR5gd+7cwY0bN5Qe3W3duhVmZmaKMtu2bYvZs2ejaNGiGf7DWZ2WLVuqfVT77bffolSpUvDz80PZsmUzLCOtZ+LnDl+wadMm6OnpKd4jVapUURvT6NGjERkZiQ0bNqRbIzl79mzo6+vjhx9+APBfYhYbGwszMzMkJSUhISEhy9MFMXnSkKmpKZYvXw4vLy+8e/cOXbp0ga2tLd68eYMbN27gzZs3KjVHWdW2bVv8/PPPmD59Oho1aoT79+9jxowZKFWqlNIXipmZGZycnBT/QraysoK1tTWcnZ2xdOlSNGjQAA0bNoS3tzecnZ0RHR2Nhw8f4o8//sjwWXqzZs3QokULjB8/HlFRUahfvz5u3ryJ6dOno2rVqujdu7fG12RhYYGpU6di0qRJ6NOnD3r06IG3b9/C19cXhoaGKj8q+vr6WLhwIWJiYlCzZk1cuHABM2fORKtWrdCgQQMAUgI7aNAg9OvXD1euXIGnpydMTEzw8uVLnD9/Hu7u7vD29sbBgwexcuVKdOzYEaVLl4YQAnv27EFERASaNWuWbsxlypSBkZERtmzZgooVK8LU1BQODg5KX5ajRo1C9+7dIZPJMHToUI3vS3Zxd3fHmTNn8Mcff8De3h5mZmYoX758lo93dnbGjBkzMHnyZDx69AgtW7aEpaUlXr16hT///BMmJiaKAVnVMTMzg6+vL8aNG4fU1FR0794dlpaWuHXrFmbPng0nJyelRHjTpk349ddf0bNnT9SsWRNyuRzPnz/H2rVrFYmWpkn/l+rSpQuOHDmCyZMno2jRokqPGMzNzRXJRpEiRTBv3jz07t0bgwcPRo8ePfDgwQP89NNPaNasGVq2bKk4buHChZg2bRpatmyJNm3aqDy2SPsxcXZ2TnekakdHx88aBLddu3Zwc3NDjRo1YGNjg6dPn2LJkiVwcnKCi4tLpse/fv0anTp1wsCBAxEZGYnp06fD0NAQEydOzPTYb7/9Flu2bEHr1q0xatQo1KpVC3p6enj+/DlOnz6NDh06oFOnTqhYsSK+++47LFmyBHp6evj6669x+/ZtLFiwIEsDfq5YsQLt2rVDnTp1MGbMGJQsWRKhoaE4evQotmzZAuC/msKlS5fCy8sLenp6KF++fJbf8zo6Ovj555/x/fffK+5HREQEfHx8svzYLq3me8eOHShdujQMDQ3h7u6OMWPGYOPGjWjTpg1mzJgBJycnHDp0CCtXroS3tzfKlSuXadkODg5o3749fHx8YG9vj82bN+P48eOYO3euonZx9OjR2L17Nzw9PTFmzBh4eHggNTUVoaGhOHbsGMaNG5dukmtnZ6f2Og0NDVG0aFGl9+bWrVuxZ88etGnTBk5OToiIiMDOnTuxfft29O3bVynBCwoKQtOmTTFt2jTFP6zmz5+Pu3fvomnTpihevDhev36NdevW4dixY/Dx8VHUkFlYWKj9TFhYWCA5OTndz8u9e/cwb948nD59WtHUoHz58nBycoK3tzeGDRuGHTt2QFdXN+uJ3hc1N89nstLbbufOnUrr1fXuEUKIoKAg0aZNG2FlZSX09PSEo6OjaNOmjcrxWT2PEEIkJCSIH374QTg6OgpDQ0NRrVo1sW/fPuHl5aXSs+PEiROiatWqwsDAQKV3yuPHj0X//v2Fo6Oj0NPTEzY2NqJevXpi5syZGcYmhBAfPnwQ48ePF05OTkJPT0/Y29sLb29v8f79e6X9strbLs3atWuFh4eH0NfXF3K5XHTo0EGly3damTdv3hSNGzcWRkZGwsrKSnh7e4uYmBiVMtevXy9q164tTExMhJGRkShTpozo06ePojfTvXv3RI8ePUSZMmWEkZGRkMvlolatWsLf31+pnE97Kwkh9RqqUKGC0NPTU9uzMSEhQRgYGIiWLVtm+R6k19vu014iafciK715QkJCRP369YWxsbEAoOjZk14vOHU9l4QQYt++faJJkybC3NxcGBgYCCcnJ9GlS5dMh95I8/vvv4sGDRoIMzMzoaurK0qWLCm8vb0Vw0akuXv3rhg3bpyoUaOGsLGxEbq6usLS0lI0atQoS71fMupt9+bNG6V91d1vdfD/vXHUvdT1lNq6davivWxnZydGjhyp1CtPiP96Uab3ygy+oLfdwoULRb169YS1tbVi6I8BAwaIJ0+eZFhO2ntj06ZNYuTIkcLGxkYYGBiIhg0bqvQQzOjzn5SUJBYsWCAqV64sDA0NhampqahQoYIYPHiwePDggWK/hIQEMW7cOGFraysMDQ1FnTp1RHBwsMr1pPeeDQ4OFq1atRJyuVwYGBiIMmXKqPTemzhxonBwcBA6OjoqZWT1Pb927Vrh4uIi9PX1Rbly5cT69euz/Pl88uSJaN68uTAzMxMAlI55+vSp6NmzpyhatKjQ09MT5cuXF/PnzxcpKSmZlpvW423Xrl2iUqVKQl9fXzg7O4tFixap7BsTEyOmTJkiypcvr/j+dXd3F2PGjFH5fGaFut52wcHBomnTpsLOzk7o6ekJY2NjUbNmTbFy5UqV60n7e378nXrgwAHRoEEDxXeCmZmZaNiwodi2bVuWYkrve1QIqdddw4YN1X6erl69KurUqSNMTEyEu7t7lr/vhBBCJgSntCbS1B9//IH27dvj0KFDisb4RPnZmTNn0KRJE+zcuVPt43Qi+g8f2xFp4O7du3j69CnGjRuHKlWqKKbjICKiwoNDFRBpYOjQoWjfvj0sLS2xbdu2DMf2ISKigomP7YiIiIg0wJonIiIiIg0weSIiIiLSAJMnIiIiIg0weSIiIiLSAIcqUCM1NRUvXryAmZkZe1MRERHlE0IIREdHw8HB4bPn1MsKJk9qvHjxQmkuOSIiIso/nj17lu48d9mByZMaaTN/P3v2LEvzLBEREZH2RUVFoUSJEorf8ZzC5EmNtEd15ubmTJ6IiIjymZxucsMG40REREQaYPJEREREpAEmT0REREQaYPJEREREpAEmT0REREQaYPJEREREpAEmT0REREQaYPJEREREpAEmT0REREQa4AjjRERElGsi4xIRHpOIqPgkmBvpwdpEH3JjfW2HpREmT0RERJQrXkR8wPjdN3HuQbhinaeLNeZ09oCDhZEWI9MMH9sRERFRjouMS1RJnADg7INwTNh9E5FxiVqKTHNMnoiIiCjHhcckqiROac4+CEd4DJMnIiIiIoWo+KQMt0dnsj0vYfJEREREOc7cUC/D7WaZbM9LmDwRERFRjrM21Yeni7XabZ4u1rA2zT897pg8ERERUY6TG+tjTmcPlQTK08Uaczt75KvhCjhUAREREeUKBwsjLO9RFeExiYiOT4KZoR6sTTnOExEREVG65Mb5L1n6FB/bEREREWmAyRMRERGRBpg8EREREWmAyRMRERGRBpg8EREREWmAyRMRERGRBpg8EREREWmAyRMRERGRBpg8ERERUe569w6Ii9N2FJ+NyRMRERHlnoMHgUqVgEmTtB3JZ8szyZOfnx9kMhlGjx6tWCeEgI+PDxwcHGBkZITGjRvjzp07mZa1e/duuLq6wsDAAK6urti7d28ORk5ERESZiowE+vcH2rUDwsKAY8eADx+0HdVnyRPJ0+XLl/Hbb7/Bw8NDaf28efOwaNEi/PLLL7h8+TLs7OzQrFkzREdHp1tWcHAwunfvjt69e+PGjRvo3bs3unXrhkuXLuX0ZRAREZE6x48D7u7Ahg2ATAaMGwdcvQoYGWk7ss+i9eQpJiYGvXr1wpo1a2BpaalYL4TAkiVLMHnyZHzzzTdwc3NDQEAA4uLisHXr1nTLW7JkCZo1a4aJEyeiQoUKmDhxIpo2bYolS5bkwtUQERGRQkwMMHQo0Lw58OwZUKYMcPYssGBBvk2cgDyQPA0bNgxt2rTB119/rbT+8ePHCAsLQ/PmzRXrDAwM0KhRI1y4cCHd8oKDg5WOAYAWLVpkeAwRERFls7NngcqVgVWrpOVhw4AbN4AGDbQbVzbQ1ebJt2/fjmvXruHy5csq28LCwgAAxYoVU1pfrFgxPH36NN0yw8LC1B6TVp46CQkJSEhIUCxHRUVlKX4iIiL6xIcPUmPwpUsBIYCSJYH164GmTbUdWbbRWs3Ts2fPMGrUKGzevBmGhobp7ieTyZSWhRAq6770GD8/P8jlcsWrRIkSWbgCIiIiUnLxIlClCrBkiZQ4DRgA3LpVoBInQIvJ09WrV/H69WtUr14durq60NXVRVBQEJYtWwZdXV1F7dGnNUavX79WqVn6mJ2dncbHTJw4EZGRkYrXs2fPvuDKiIiICpmEBGDiRKB+feDvvwF7e+DQIWDtWsDcXNvRZTutJU9NmzbFrVu3EBISonjVqFEDvXr1QkhICEqXLg07OzscP35ccUxiYiKCgoJQr169dMutW7eu0jEAcOzYsQyPMTAwgLm5udKLiIiIsuDaNaBGDWDOHCA1FfjuO+D2baB1a21HlmO01ubJzMwMbm5uSutMTExQtGhRxfrRo0dj9uzZcHFxgYuLC2bPng1jY2P07NlTcUyfPn3g6OgIPz8/AMCoUaPg6emJuXPnokOHDti/fz9OnDiB8+fP597FERERFXRJScDs2cDMmUByMmBjA/z6K9Cpk7Yjy3FabTCemZ9++gkfPnzA0KFD8f79e9SuXRvHjh2DmZmZYp/Q0FDo6PxXgVavXj1s374dU6ZMwdSpU1GmTBns2LEDtWvX1sYlEBERFTy3bwNeXlKtEwB06QKsXCklUIWATAghtB1EXhMVFQW5XI7IyEg+wiMiIkqTnCyN0TR9OpCYCFhZAStWAN27S4Nfallu/X7n6ZonIiIiyiPu35dqm9Jm7GjbFvjtN6lxeCGj9UEyiYiIKA9LTZWGHqhSRUqczM2laVYOHCiUiRPAmiciIiJKz6NHQL9+0mjhANCsGbBuHVDIx0NkzRMREREpE0KaVsXDQ0qcTEyA1auBo0cLfeIEsOaJiIiIPhYaKo0MfuKEtNyokTS9SunS2o0rD2HNExEREUm1TRs2AO7uUuJkaCi1dTp1ionTJ1jzREREVNi9fAkMGgQcPCgt16kDBAQA5cppN648ijVPREREhZUQwNatQKVKUuKkrw/MnQucP8/EKQOseSIiIiqM3rwBvL2B3bul5WrVpNqmT6ZOI1WseSIiIips9uyRapt27wZ0dQFfX+DiRSZOWcSaJyIiosLi3TtgxAjpUR0gJUsbNwJVq2o3rnyGNU9ERESFweHDUrK0dSugowNMnAhcucLE6TOw5omIiKgAiwwLh2zsWJhv2wQASClXDkU2bgRq19ZyZPkXa56IiIgKqPB9h5BUyQ3m2zYhFTKsqdkRg0b/hhflPbQdWr7GmiciIqKCJiYGCWPHwXrNbwCApxZ2+LH1aPxZwg14GoOk3TexvEdVyI31tRxo/sTkiYiIqCA5dw7o2xcGjx4BADZWbYM5jfsiTt9IscvZB+EIj0lk8vSZmDwREREVBB8+AJMnS1OqCIFEB0f0a+iN/zlXUbt7dHxSroZXkLDNExERUX536ZLUa27xYmnU8P798W/QpXQTJwAwM9TLvfgKGCZPRERE+VVCAjBpElCvHnD/PmBvL02zsm4drBxs4OlirfYwTxdrWJvykd3nYvJERESUH12/DtSsCfj5AampQK9ewO3bQJs2AAC5sT7mdPZQSaA8Xawxt7MH2zt9AbZ5IiIiyk+SkoDZs4GZM4HkZMDGBli9GvjmG5VdHSyMsLxHVYTHJCI6PglmhnqwNtVn4vSFmDwRERHlF3fuAH36ANeuScudOwOrVkkJVDrkxkyWshsf2xEREeV1KSnA3LlAtWpS4mRpKU2zsnNnhokT5QzWPBEREeVlf/8NeHkBFy9Ky23bAr/9JjUOJ61gzRMREVFelJoqjdlUubKUOJmbA+vXAwcOMHHSMtY8ERER5TWPHgH9+gFnz0rLzZoBa9cCJUtqNy4CwJonIiKivEMIqeech4eUOJmYSA3Cjx5l4pSHsOaJiIgoL3j2DBgwADh+XFr29AQ2bABKl9ZuXKSCNU9ERETaJATg7w+4uUmJk6GhNM3K6dNMnPIo1jwRERFpy8uXwKBB0pQqAFCnjpRIlS+v1bAoY6x5IiIiym1CANu2AZUqSYmTvr40zcq5c0yc8gHWPBEREeWmN28Ab29g925puWpVYONG6bEd5QuseSIiIsote/ZItU27dwO6uoCPD3DpEhOnfIY1T0RERDnt/XtgxAhgyxZp2c0NCAiQpluhfIc1T0RERDnp8GGptmnLFkBHB5gwAbhyhYlTPqbV5GnVqlXw8PCAubk5zM3NUbduXRw5ckSxXSaTqX3Nnz8/3TL9/f3VHhMfH58bl0RERCSJipLGbWrTRupVV7488L//SQ3DDQy0HR19Aa0+titevDjmzJmDsmXLAgACAgLQoUMHXL9+HZUqVcLLly+V9j9y5AgGDBiAzp07Z1iuubk57t+/r7TO0NAwe4MnIiJKz8mTQP/+QGgoIJMBo0cDs2YBRkbajoyygVaTp3bt2iktz5o1C6tWrcLFixdRqVIl2NnZKW3fv38/mjRpgtKZDBomk8lUjiUiIspxMTHA+PHAypXScqlS0rhNnp5aDYuyV55p85SSkoLt27cjNjYWdevWVdn+6tUrHDp0CAMGDMi0rJiYGDg5OaF48eJo27Ytrl+/nhMhExER/efcOaBy5f8SJ29v4OZNJk4FkNZ72926dQt169ZFfHw8TE1NsXfvXri6uqrsFxAQADMzM3zzzTcZllehQgX4+/vD3d0dUVFRWLp0KerXr48bN27AxcVF7TEJCQlISEhQLEdFRX3ZRRERUeHx4QMwZYo0pYoQQIkSwPr1wNdfazsyyiEyIYTQZgCJiYkIDQ1FREQEdu/ejbVr1yIoKEglgapQoQKaNWuG5cuXa1R+amoqqlWrBk9PTyxbtkztPj4+PvD19VVZHxkZCXNzc43OR0REhcilS4CXF5DWzrZ/f2DRIkAu125chVRUVBTkcnmO/35rPXn61Ndff40yZcrg119/Vaw7d+4cPD09ERISgsqVK2tc5sCBA/H8+XOlnnwfU1fzVKJECSZPRESkXkIC4OsLzJ0LpKYCdnbA2rVSzzrSmtxKnrT+2O5TQgilRAYA1q1bh+rVq39W4iSEQEhICNzd3dPdx8DAAAbsNkpERFlx/bpU23TrlrTcsyewfDlgZaXduCjXaDV5mjRpElq1aoUSJUogOjoa27dvx5kzZxAYGKjYJyoqCjt37sTChQvVltGnTx84OjrCz88PAODr64s6derAxcUFUVFRWLZsGUJCQrBixYpcuSYiIiqgkpKkMZp+/hlITgZsbIBVq4BMhs+hgkerydOrV6/Qu3dvvHz5EnK5HB4eHggMDESzZs0U+2zfvh1CCPTo0UNtGaGhodDR+a/TYEREBAYNGoSwsDDI5XJUrVoVZ8+eRa1atXL8eoiIqIC6c0eqbbp6VVr+5hspcbK11W5cpBV5rs1TXpBbz0yJiCiPS0kBFi4Epk4FEhMBS0vgl1+AHj2kwS8pTym0bZ6IiIjyhL//Bvr2BYKDpeU2bYDffgMcHLQaFmlfnhkkk4iIKE9ITQWWLgWqVJESJzMzadymP/5g4kQAWPNERET0n8ePpbGazpyRlr/+Gli3DihZUqthUd7CmiciIiIhgF9/BTw8pMTJxESaZuXYMSZOpII1T0REVLg9ewZ8/72UKAFAw4bAhg1AmTLajYvyLNY8ERFR4SQEEBAAuLtLiZOhoTS1ypkzTJwoQ6x5IiKiwicsDBg0SGoEDgC1a0uJVPny2o2L8gXWPBERUeGyYwdQqZKUOOnpSaOGnz/PxImyjDVPRERUOISHA0OHAjt3SstVq/732I5IA6x5IiKigm/fPqm2aedOQFcXmD4duHSJiRN9FtY8ERFRwfX+PTByJLB5s7RcqZJU21S9eo6dMjIuEeExiYiKT4K5kR6sTfQhN9bPsfNR7mPyREREBVNgIDBgAPDiBaCjA/z4I+DrCxgY5NgpX0R8wPjdN3HuQbhinaeLNeZ09oCDhVGOnZdyFx/bERFRwRIVBQwcCLRqJSVO5coB//sfMGdOjiZOkXGJKokTAJx9EI4Ju28iMi4xx85Nueuzap5SU1Px8OFDvH79GqmpqUrbPD09syUwIiIijZ06BfTrB4SGAjIZMGoUMGsWYGyc46cOj0lUSZzSnH0QjvCYRD6+KyA0Tp4uXryInj174unTpxBCKG2TyWRISUnJtuCIiIiyJDYWmDAB+OUXablUKcDfH8jFf9BHxSdluD06k+2Uf2icPA0ZMgQ1atTAoUOHYG9vD5lMlhNxERERZc3//gf07Qs8fCgtDxkCzJ8PmJrmahjmhnoZbjfLZDvlHxonTw8ePMCuXbtQtmzZnIiHiIgoa+LjgSlTpClVhACKFwfWrweaNdNKONam+vB0scZZNY/uPF2sYW3KR3YFhcYNxmvXro2Hadk9ERGRNly+DFSrBixcKCVOffsCt25pLXECALmxPuZ09oCni7XSek8Xa8zt7MH2TgWIxjVPI0aMwLhx4xAWFgZ3d3fo6SlXQ3p4eGRbcEREREoSE4EZM6SecykpgJ0dsGYN0LattiMDADhYGGF5j6oIj0lEdHwSzAz1YG3KcZ4KGpn4tNV3JnR0VCurZDIZhBAFpsF4VFQU5HI5IiMjYW5uru1wiIgIAG7cAPr0AW7elJZ79ACWLweKFtVuXJRn5Nbvt8Y1T48fP86JOIiIiNRLTpZqmmbMAJKSAGtrYPVqoHNnbUdGhZTGyZOTk1NOxEFERKTq7l3Aywu4ckVa7tRJSpxsbbUbFxVqnzVI5j///IMlS5bgr7/+gkwmQ8WKFTFq1CiUKVMmu+MjIqLCKCVF6kU3dSqQkABYWEhjOPXsKQ1+SaRFGve2O3r0KFxdXfHnn3/Cw8MDbm5uuHTpEipVqoTjx4/nRIxERFSYPHggDW75009S4tSqFXD7NtCrFxMnyhM0bjBetWpVtGjRAnPmzFFaP2HCBBw7dgzXrl3L1gC1gQ3GiYi0IDUVWLECGD8e+PABMDMDFi8G+vdn0kRZklu/3xonT4aGhrh16xZcXFyU1v/999/w8PBAfHx8tgaoDUyeiIhy2ZMnUpJ0+rS0/NVX0oCXbGdLGsit32+NH9vZ2NggJCREZX1ISAhs2YCPiIg0IYQ0TpO7u5Q4GRtLbZuOH2fiRHmWxg3GBw4ciEGDBuHRo0eoV68eZDIZzp8/j7lz52LcuHE5ESMRERVEz58DAwcCgYHScoMGwIYNAKf/ojxO48d2QggsWbIECxcuxIsXLwAADg4O+PHHHzFy5MgCMVEwH9sREeUgIYBNm4CRI4HISMDAAJg9Gxg1CihSRNvRUT6WZ9s8fSw6OhoAYGZmlm0B5QVMnoiIcsirV8DgwcD+/dJyzZpAQABQsaJ246ICIc+2efqYmZlZgUuciIgoh/z+O1CpkpQ46ekBs2YBFy4wcaJ8J0ttnqpVq4aTJ0/C0tISVatWzfDRXEEYqoCIiLJReDgwbJiUPAFAlSpSbVM2TSQfGZeI8JhERMUnwdxID9YmnIiXclaWkqcOHTrAwMBA8f8FoV0TERHlggMHgEGDpMd1RYoAkyYBU6YA+tmT3LyI+IDxu2/i3INwxTpPF2vM6ewBBwujbDkH0ae+qM1TQcU2T0REXygiQmoAvnGjtOzqKtU21aiRbaeIjEvE8G3XlRKnNJ4u1ljeoyproAqZPNvmqXTp0nj79q3K+oiICJQuXTpbgiIionzs6FHAzU1KnGQyaZqVq1ezNXECgPCYRLWJEwCcfRCO8JjEbD0fURqNx3l68uQJUlJSVNYnJCTg+fPn2RIUERHlQ9HRwA8/AL/9Ji2XLSvVNtWrlyOni4pPyjicTLYTfa4s1zwdOHAABw4cACBNDpy2fODAAezduxc///wzSpUqpdHJV61aBQ8PD5ibm8Pc3Bx169bFkSNHFNv79u0LmUym9KpTp06m5e7evRuurq4wMDCAq6sr9u7dq1FcRESkodOnpQbgaYnTyJHAjRs5ljgBgLmhXobbzTLZTvS5slzz1LFjRwCATCaDl5eX0jY9PT04Oztj4cKFGp28ePHimDNnDsr+/2iyAQEB6NChA65fv45KlSoBAFq2bIkNGzYojtHPpJFhcHAwunfvjp9//hmdOnXC3r170a1bN5w/fx61a9fWKD4iIspEXBwwYQKwfLm07OwsjRLeuHGOn9raVB+eLtY4m06bJ2tTtneinKFxg/FSpUrh8uXLsLa2zpGArKysMH/+fAwYMAB9+/ZFREQE9u3bl+Xju3fvjqioKKUarJYtW8LS0hLbtm3LUhlsME5ElAUXLgB9+wIPHkjLgwYBCxYAuTj+34uID5iw+6ZSAuXpYo25nT1gz952hU5u/X5r3Obp8ePHOREHUlJSsHPnTsTGxqJu3bqK9WfOnIGtrS0sLCzQqFEjzJo1K8MJiIODgzFmzBildS1atMCSJUvSPSYhIQEJCQmK5aioqM+/ECKigi4+Hpg2DVi4EEhNBRwdgXXrgBYtcj0UBwsjLO9RFeExiYiOT4KZoR6sTTnOE+UsjZMnAIiNjUVQUBBCQ0ORmKjcm2HkyJEalXXr1i3UrVsX8fHxMDU1xd69e+Hq6goAaNWqFbp27QonJyc8fvwYU6dOxVdffYWrV68qxp36VFhYGIoVK6a0rlixYggLC0s3Bj8/P/j6+moUNxFRoXTlCuDlBdy9Ky17eQFLlgAWFloLSW7MZIlyl8aP7a5fv47WrVsjLi4OsbGxsLKyQnh4OIyNjWFra4tHjx5pFEBiYiJCQ0MRERGB3bt3Y+3atQgKClIkUB97+fIlnJycsH37dnzzzTdqy9PX10dAQAB69OihWLdlyxYMGDAA8fHxao9RV/NUokQJPrYjIkqTmAjMnClN4JuSAhQrBvz6K9Chg7YjI1LIs+M8jRkzBu3atcO7d+9gZGSEixcv4unTp6hevToWLFigcQD6+vooW7YsatSoAT8/P1SuXBlLly5Vu6+9vT2cnJzwIO35uhp2dnYqtUyvX79WqY36mIGBgaLHX9qLiIj+382bQO3awM8/AykpiO7QGTcDz+Ofek0RGcexlKjw0Th5CgkJwbhx41CkSBEUKVIECQkJKFGiBObNm4dJkyZ9cUBCCKVaoI+9ffsWz549g729fbrH161bF8ePH1dad+zYMdTLwe6yREQFUnKyNHlvjRpASAhSrIpi+eCZcK/QD+2330fThUEYse06XkR80HakRLlK4zZPenp6irntihUrhtDQUFSsWBFyuRyhoaEalTVp0iS0atUKJUqUQHR0NLZv344zZ84gMDAQMTEx8PHxQefOnWFvb48nT55g0qRJsLa2RqdOnRRl9OnTB46OjvDz8wMAjBo1Cp6enpg7dy46dOiA/fv348SJEzh//ryml0pEVHj99ZfUnunyZQBAUtt2GN1kCA69Vm7pcfZBOCbsvsmpUKhQ0Th5qlq1Kq5cuYJy5cqhSZMmmDZtGsLDw7Fp0ya4u7trVNarV6/Qu3dvvHz5EnK5HB4eHggMDESzZs3w4cMH3Lp1Cxs3bkRERATs7e3RpEkT7NixA2YfdYMNDQ2Fjs5/FWj16tXD9u3bMWXKFEydOhVlypTBjh07OMYTEVFWpKRIDcAnTwYSEgC5HFi+HKHNO+LQ4rNqD0mbCoXJExUWGjcYv3LlCqKjo9GkSRO8efMGXl5eOH/+PMqWLYsNGzagcuXKORVrruE4T0RUKD18KI3b9L//ScstWwJr1wKOjrge+h6dVl5I99B9Q+uhSknL3ImTKB15dpynGh9N7GhjY4PDhw9na0BERJTLUlOBlSuB8eOlEcNNTYFFi4Dvv5cm9gWnQiH6mMYNxomIqAB5+hRo1gwYMUJKnJo0AW7dAgYOVCROwH9ToajDqVCosMlSzVPVqlUVjcQzc+3atS8KiIiIcoEQ0qjgY8cC0dGAkREwbx4wdCigo/rvarmxPuZ09kh3KhS2d6LCJEvJU9qkwEREVAD8+69Us5Q2B2i9eoC/P+DikuFhnAqFSKJxg/HCgA3GiahAEgLYskV6RBcRARgYSKOGjxkDFCmi7eiIvliebTBORET50KtXwJAhwL590nKNGkBAAKBmKiwiypjGDcZ1dHQUo4urexERUR6zcydQqZKUOOnpSdOsBAczcSL6TBrXPO3du1dpOSkpCdevX0dAQAB8fX2zLTAiIvpCb98Cw4cD27dLyx4ewMaNQAEYj49Im7KtzdPWrVuxY8cO7N+/PzuK0yq2eSKivCIyLhHhMYmIik+CuZEerE2y2ED7jz+AQYOAsDCpPdPEicDUqYA+G3dTwZXv2jzVrl0bAwcOzK7iiIgKvRcRHzB+902c+2RogDmdPeBgYaT+oIgIYPRoqT0TAFSsKP1/zZo5Hi9RYZEtg2R++PABy5cvR/HixbOjOCKiQi8yLlElcQL+m4g3Mi5R9aBjxwB3dylZksmAH34Arl1j4kSUzTSuebK0tFQaMFMIgejoaBgbG2Pz5s3ZGhwRUWEVHpOokjilUZmINzoa+PFH4NdfpeWyZaVxm+rXz51giQoZjZOnJUuWKC3r6OjAxsYGtWvXhqUlJ4UkIsoOUfFJGW6PTtt+5gzQrx/w5Im0PHw4MGcOYGKSo/ERFWYaJ09eXl45EQcREX0ks4l4zVOTgFGjgGXLpBVOTsD69cBXX+VCdESF22c1GH///j3WrVuHv/76CzKZDBUrVkS/fv1gZWWV3fERERVKaRPxnlXz6K6/7AWcmtUHHj6UVgwcCCxYALB3MFGu0LjBeFBQEJydnbFs2TK8f/8e7969w7Jly1CqVCkEBQXlRIxERIVO2kS8ni7WinUGyYn45cZ2TJ03BEUePgQcHIDDh4HffmPiRJSLNB7nyc3NDfXq1cOqVasUI4qnpKRg6NCh+N///ofbt2/nSKC5ieM8EVFekTbOU/Llyyg1bij079+TNvTuDSxdCrCtKZFCbv1+a5w8GRkZISQkBOXLl1daf//+fVSpUgUfPnzI1gC1gckTEeUZiYnArFnSKyUFsLWVapo6dNB2ZER5Tm79fmv82K5atWr466+/VNb/9ddfqFKlSnbEREREAHDzJlC7NjBjhpQ4de0K3LnDxIlIyzRuMD5y5EiMGjUKDx8+RJ06dQAAFy9exIoVKzBnzhzcvHlTsa+Hh0f2RUpElAs+ezqU7JScDMybB/j4AElJgJUVsHIl0L177sZBRGpp/NhORyfjyiqZTAYhBGQyGVJSUr4oOG3hYzuiwumzpkPJbvfuAV5ewJ9/Ssvt20uDX9rZ5c75ifKxPDu33ePHj3MiDiIircpsOpTlParmbA1USorUAHzyZCA+HpDLpeU+faSpVogoz9A4eXJycsqJOIiItEqj6VCy2z//AH37AufPS8vNmwPr1gGcL5QoT/qsQTL/+ecfLFmyRGmQzFGjRqFMmTLZHR8RUa7I8nQo2Sk1FVi9WpqXLi4OMDUFFi6UBr1kbRNRnqVxb7ujR4/C1dUVf/75Jzw8PODm5oZLly6hUqVKOH78eE7ESESU4zKbDsUsk+0ae/pUqmEaNkxKnBo3Bm7dAgYNYuJElMdpXPM0YcIEjBkzBnPmzFFZP378eDRr1izbgiMiyi0ZTYfi6WINa9NsemQnhDQH3ZgxQHQ0YGQEzJ0rJVGZdMghorxB40/qX3/9hQEDBqis79+/P+7evZstQRER5TZ106EAUuI0t7NH9rR3evECaNsW+P57KXGqWxe4cQMYMYKJE1E+onHNk42NDUJCQuDi4qK0PiQkBLa2ttkWGBFRbnOwMMLyHlURHpOI6PgkmBnqwdo0G8Z5EgLYulVKkt6/B/T1gZkzgbFjgf+f5oqI8g+Nk6eBAwdi0KBBePToEerVqweZTIbz589j7ty5GDduXE7ESESUa+TG2Two5uvXwJAhwN690nKNGkBAAODqmn3nIKJcpfEgmUIILFmyBAsXLsSLFy8AAA4ODvjxxx8xcuRIyApAQ0cOkklE2WLXLsDbGwgPB3R1genTgfHjAb1sbnxORADy8MTACQkJSE5OhomJCaKjowEAZmZmORKctjB5IqIv8vYtMHw4sH27tOzhIdU2cf5PohyV5yYGDg8PR5s2bWBqagpzc3PUq1cP4eHhBS5xIiL6IgcPAm5uUuJUpIg0Yvjly0yciAqQLCdPEydOxNWrV+Hr64v58+cjPDwcgwYNysnYiIjyj8hIoF8/oF07ICwMqFgRCA6WGobr5/LEwkSUo7LcYPzo0aNYv349WrduDQBo3bo13NzckJSUBD0+vyeiwuzYMWDAAOD5c2mAy3HjgJ9/BgwNtR0ZEeWALNc8vXjxAlWrVlUsV6hQAfr6+opG40REhU5MjNQgvEULKXEqUwY4exaYP5+JE1EBluXkSQgBXV3liipdXV2kpqZ+9slXrVoFDw8PmJubw9zcHHXr1sWRI0cAAElJSRg/fjzc3d1hYmICBwcH9OnTJ9Nkzd/fHzKZTOUVHx//2XESEakICpIagq9eLS0PHy4NeNmggXbjIqIcl+XHdkIING3aVCmBiouLQ7t27aD/0fP8a9euZfnkxYsXx5w5c1C2bFkAQEBAADp06IDr16+jePHiuHbtGqZOnYrKlSvj/fv3GD16NNq3b48rV65kWK65uTnu37+vtM6Q/wokouwQFwdMmgQsXSotlywJbNgAfPWVduMiolyT5eRp+vTpKus6dOjwRSdv166d0vKsWbOwatUqXLx4EQMGDFCZaHj58uWoVasWQkNDUbJkyXTLlclksLOz+6LYiIhUXLwIeHkBf/8tLX//PbBwIcAhTYgKlS9KnrJTSkoKdu7cidjYWNStW1ftPpGRkZDJZLCwsMiwrJiYGDg5OSElJQVVqlTBzz//rNRe61MJCQlISEhQLEdFRX3WNRBRAZWQIA1wOX8+kJoKODgAa9cCrVppOzIi0gKtz0R569YtmJqawsDAAEOGDMHevXvhqmbagvj4eEyYMAE9e/bMcOCrChUqwN/fHwcOHMC2bdtgaGiI+vXr48GDB+ke4+fnB7lcrniVKFEiW66NiAqAq1eB6tWBuXOlxKl3b+D2bSZORIWYxiOMZ7fExESEhoYiIiICu3fvxtq1axEUFKSUQCUlJaFr164IDQ3FmTNnNBo1NDU1FdWqVYOnpyeWLVumdh91NU8lSpTgCONEhVliIjBrlvRKSQFsbYHffgO+sLkCEeWc3BphXOOJgbObvr6+osF4jRo1cPnyZSxduhS//vorAClx6tatGx4/foxTp05pfDN0dHRQs2bNDGueDAwMYGBg8PkXQUQFy61bUtum69el5a5dgZUrAWtr7cZFRHmC1h/bfUoIoagFSkucHjx4gBMnTqBo0aKfVV5ISAjs7e2zO1QiKmiSkwE/P+kx3fXrgJWVNM3K778zcSIihSwlT1ZWVggPDwcA9O/fXzEh8JeaNGkSzp07hydPnuDWrVuYPHkyzpw5g169eiE5ORldunTBlStXsGXLFqSkpCAsLAxhYWFITExUlNGnTx9MnDhRsezr64ujR4/i0aNHCAkJwYABAxASEoIhQ4ZkS8xEVEDduyeN0TRpEpCUJE2zcucO0L27tiMjojwmS4/tEhMTERUVBWtrawQEBGDu3LnZMiHwq1ev0Lt3b7x8+RJyuRweHh4IDAxEs2bN8OTJExw4cAAAUOWTCTVPnz6Nxo0bAwBCQ0Oho/NfDhgREYFBgwYhLCwMcrkcVatWxdmzZ1GrVq0vjpeICqDUVGnMpkmTgPh4QC6Xlvv0kaZaISL6RJYajDdr1gyvXr1C9erVERAQgO7du8PIyEjtvuvXr8/2IHNbbjU4IyIt++cfaTLfc+ek5ebNgXXrgOLFtRsXEX2WPNVgfPPmzVi8eDH++ecfyGQyREZGcroTIsq/UlOlaVV++gmIjQVMTaXBLgcOZG0TEWVK46EKSpUqhStXrnxW4+38gjVPRAVYaCgwYABw4oS03LgxsH49UKqUVsMioi+XW7/fGve2e/z4cYFOnIiogBJCSpLc3aXEychIatt08iQTJyLSyGcNVRAUFIR27dqhbNmycHFxQfv27XEurc0AEVFe8+KF1HtuwAAgKgqoWxcICQFGjgR08tyILUSUx2n8rbF582Z8/fXXMDY2xsiRIzF8+HAYGRmhadOm2Lp1a07ESET0eYQAtm4F3NyAQ4cAfX1g3jypgXi5ctqOjojyKY3bPFWsWBGDBg3CmDFjlNYvWrQIa9aswV9//ZWtAWoD2zwRFQCvXwPe3sCePdJy9epAQABQqZJ24yKiHJNn2zw9evQI7dq1U1nfvn17PH78OFuCIiL6Irt3S7VNe/YAurrAjBlAcDATJyLKFhonTyVKlMDJkydV1p88eRIlSpTIlqCIiD7Lu3dAr15Aly7AmzdS4/A//wSmTgX09LQdHREVEBpPDDxu3DiMHDkSISEhqFevHmQyGc6fPw9/f38sXbo0J2IkIsrcoUPSOE0vX0qNwCdMAKZNAzjpNxFlM42TJ29vb9jZ2WHhwoX4/fffAUjtoHbs2IEOHTpke4BERBmKjATGjAE2bJCWK1SQ2jZxSiYiyiEaNxgvDNhgnCj3RMYlIjwmEVHxSTA30oO1iT7kxvpZO/jECaB/f+DZM2lk8DFjgJkzpTGciKjQyVPTsxAR5YQXER8wfvdNnHsQrljn6WKNOZ094GCRQQIUEyNNrbJqlbRcpoxU89SwYQ5HTET0mYNkEhF9qci4RJXECQDOPgjHhN03ERmXqP7As2eBypX/S5yGDQNu3GDiRES5hskTEWlFeEyiSuKU5uyDcITHfJI8ffgAjB0rzUX36BFQsqT02O6XXwATk5wPmIjo//GxHRFpRVR8Uobboz/efukS4OUF3L8vLQ8YACxaBLBNIhFpwWfXPCUmJuL+/ftITk7OzniIqJAwN8x43CUzQz0gIQGYOBGoV09KnOztpSEJ1q5l4kREWqNx8hQXF4cBAwbA2NgYlSpVQmhoKABg5MiRmDNnTrYHSEQFk7WpPjxdrNVu83Sxhu2DO0CNGsCcOUBqqjT45e3bQOvWuRwpEZEyjZOniRMn4saNGzhz5gwMDQ0V67/++mvs2LEjW4MjooJLbqyPOZ09VBKoJqUssOLhHzBr3EBKlmxspGlWNm8GrKy0FC0R0X80bvO0b98+7NixA3Xq1IFMJlOsd3V1xT///JOtwRFRweZgYYTlPaoiPCYR0fFJKPr4ARxGD0GRkOvSDp07S73qbGy0GygR0Uc0Tp7evHkDW1tblfWxsbFKyRQRUVbIjfUhNygCLFghTaeSmAhYWgIrVgDffisNfklElIdo/NiuZs2aOHTokGI5LWFas2YN6tatm32REVHhcP8+0KCBNBddYiLQti1w5w7QowcTJyLKkzSuefLz80PLli1x9+5dJCcnY+nSpbhz5w6Cg4MRFBSUEzESUUGUmgosWyb1pouPl3rPLV0qDUnApImI8jCNa57q1auH//3vf4iLi0OZMmVw7NgxFCtWDMHBwahevXpOxEhEBc2jR0CTJtJcdPHxQLNmUuPwvn2ZOBFRnseJgdXgxMBEOUQI4NdfgR9+AGJjpZHBFywABg9m0kREXyzPTgwcFRWldr1MJoOBgQH09bM4GzoRFS7Pnkkjgx8/Li17ekqT+ZYurd24iIg0pPFjOwsLC1haWqq8LCwsYGRkBCcnJ0yfPh2pqak5ES8R5TdCAP7+gJublDgZGgKLFwOnTzNxIqJ8SeOaJ39/f0yePBl9+/ZFrVq1IITA5cuXERAQgClTpuDNmzdYsGABDAwMMGnSpJyImYjyi5cvgUGDgIMHpeU6daREqnx5rYZFRPQlNE6eAgICsHDhQnTr1k2xrn379nB3d8evv/6KkydPomTJkpg1axaTJ6LCSghg+3Zg+HDg3TtAXx+YMUNq61SkiLajIyL6IhonT8HBwVi9erXK+qpVqyI4OBgA0KBBA8Wcd0SUt0TGJSI8JhFR8UkwN9KDtYk+5MbZ2FbxzRtg6FBg1y5puWpVYONG6bEdEVEBoHHyVLx4caxbt05lEuB169ahRIkSAIC3b9/C0tIyeyIkomzzIuIDxu++iXMPwhXrPF2sMaezBxwsjL78BHv3Sj3n3rwBdHWBKVOASZMAPb0vL5uIKI/QOHlasGABunbtiiNHjqBmzZqQyWS4fPky7t27h13//y/Ny5cvo3v37tkeLBF9vsi4RJXECQDOPgjHhN03sbxH1c+vgXr/HhgxAtiyRVp2cwMCAoBq1b4waiKivEfj5Kl9+/b4+++/sXr1aty/fx9CCLRq1Qr79u2Ds7MzAMDb2zu74ySiLxQek6iSOKU5+yAc4TGJn5c8HT4MfP+91DhcRwf46SfAxwcwMPiygImI8iiNkycAcHJygp+fX3bHQkQ5KCo+KcPt0ZlsVy0wChg7Fli3TlouX17qSVenzucFSESUT3xW8gQAcXFxCA0NRWJiotJ6Dw+PLw6KiLKfuWHG7Y7MMtmu5ORJoH9/IDRUGhl89Ghg1izAKBvaTRER5XEaJ09v3rxBv379cOTIEbXbU1JSvjgoIsp+1qb68HSxxlk1j+48XaxhbZqFR3axscD48cCKFdJy6dLSKOGentkcLRFR3qXxCOOjR4/G+/fvcfHiRRgZGSEwMBABAQFwcXHBgQMHNCpr1apV8PDwgLm5OczNzVG3bl2lpEwIAR8fHzg4OMDIyAiNGzfGnTt3Mi139+7dcHV1hYGBAVxdXbF3715NL5OowJEb62NOZw94ulgrrfd0scbczh6Zt3c6fx6oXPm/xGnoUODGDSZORFT4CA3Z2dmJS5cuCSGEMDMzE/fv3xdCCLF//35Rv359jco6cOCAOHTokLh//764f/++mDRpktDT0xO3b98WQggxZ84cYWZmJnbv3i1u3bolunfvLuzt7UVUVFS6ZV64cEEUKVJEzJ49W/z1119i9uzZQldXV1y8eDHLcUVGRgoAIjIyUqPrIcoPImITxMNX0eL603fi4atoERGbkPEBcXFCjBsnhEwmBCBEiRJCHD+eO8ESEWkgt36/NU6ezMzMxOPHj4UQQjg5OYnz588LIYR49OiRMDIy+uKALC0txdq1a0Vqaqqws7MTc+bMUWyLj48XcrlcrF69Ot3ju3XrJlq2bKm0rkWLFuLbb7/NcgxMnoj+36VLQlSoICVNgBD9+wsREaHtqIiI1Mqt32+NH9uVL18e9+/fBwBUqVIFv/76K/7991+sXr0a9vb2n10DlpKSgu3btyM2NhZ169bF48ePERYWhubNmyv2MTAwQKNGjXDhwoV0ywkODlY6BgBatGiR4TEJCQmIiopSehEVagkJwOTJQN26wL17gJ2dND/dunWAXK7t6IiItErjBuOjR4/Gy5cvAQDTp09HixYtsGXLFujr68Pf31/jAG7duoW6desiPj4epqam2Lt3L1xdXRXJTrFixZT2L1asGJ4+fZpueWFhYWqPCQsLS/cYPz8/+Pr6ahw7UYEUEgJ4eQE3b0rLPXsCy5cDVlZaDYuIKK/QOHnq1auX4v+rVq2KJ0+e4N69eyhZsiSsra0zOFK98uXLIyQkBBEREdi9eze8vLwQFBSk2C6TyZT2F0KorPuUpsdMnDgRY8eOVSxHRUUpppohKjSSkoA5c6QJfJOTARsbYNUqoHNnbUdGRJSnaPzYbsaMGYiLi1MsGxsbo1q1ajAxMcGMGTM0DkBfXx9ly5ZFjRo14Ofnh8qVK2Pp0qWws7MDAJUao9evX6vULH3Mzs5O42MMDAwUPf7SXkSFyp070iO6adOkxOmbb4Dbt5k4ERGpoXHy5Ovri5iYGJX1cXFx2fLoSwiBhIQElCpVCnZ2djh+/LhiW2JiIoKCglCvXr10j69bt67SMQBw7NixDI8hKrRSUoD586U56K5eBSwtpfnpdu0CbG21HR0RUZ6k8WO79B6B3bhxA1YatomYNGkSWrVqhRIlSiA6Ohrbt2/HmTNnEBgYCJlMhtGjR2P27NlwcXGBi4sLZs+eDWNjY/Ts2VNRRp8+feDo6KiYLmbUqFHw9PTE3Llz0aFDB+zfvx8nTpzA+fPnNb1UooLtwQOgb18grTNFmzbAb78BDg5aDYuIKK/LcvJkaWkJmUwGmUyGcuXKKSVQKSkpiImJwZAhQzQ6+atXr9C7d2+8fPkScrkcHh4eCAwMRLNmzQAAP/30Ez58+IChQ4fi/fv3qF27No4dOwYzMzNFGaGhodDR+a8CrV69eti+fTumTJmCqVOnokyZMtixYwdq166tUWxEBVZqqjTQ5fjxwIcPgJkZsHSplEhl0p6QiIgAmRBCZGXHgIAACCHQv39/LFmyBPKPuivr6+vD2dkZdevWzbFAc1NUVBTkcjkiIyPZ/okKlidPgH79gDNnpOWvv5aGHyhZUptRERFli9z6/c5yzZOXlxcAoFSpUqhXrx709DSYRJSItEsIYM0aYNw4ICYGMDEB5s0DvL1Z20REpCGN2zw1atQIqamp+Pvvv/H69WukpqYqbffkPFdEecvz58D33wNHj0rLDRtKk/mWKaPduIiI8imNk6eLFy+iZ8+eePr0KT594ieTyZCSkpJtwRHRFxAC2LQJGDkSiIwEDA2B2bOBUaMAHY072hIR0f/TOHkaMmQIatSogUOHDsHe3j7TASuJSAvCwoDBg4EDB6Tl2rUBf3+gQgWthkVEVBBonDw9ePAAu3btQtmyZXMiHiL6Ujt2AEOHAu/eAXp60ojhP/wA6Gr8cSciIjU0rruvXbs2Hj58mBOxENGXCA8HuncHvv1WSpyqVpUGvpwwgYkTEVE20vgbdcSIERg3bhzCwsLg7u6u0uvOw8Mj24Ijoizavx8YNAh4/VpKlCZPll7sFUtElO2yPM5TGh01DU1lMpli5PGC0GCc4zxRvvH+vdQAfNMmablSJSAgAKheXbtxERFpQZ4b5ynN48ePcyIOItJUYCAwYADw4oXUe+7HHwFfX8DAQNuREREVaBonT05OTjkRBxFlVXS0NNjlmjXScrlyUm1TnTrajYuIqJD4rMFeNm3ahPr168PBwQFPnz4FACxZsgT79+/P1uCI6BOnTwPu7v8lTqNHA9evM3EiIspFGidPq1atwtixY9G6dWtEREQo2jhZWFhgyZIl2R0fEQFAbKw02OVXXwFPnwKlSknz0y1eDBgbazs6IqJCRePkafny5VizZg0mT56MIkWKKNbXqFEDt27dytbgiAjA//4HVKkCLF8uLQ8ZAty8CTRqpNWwiIgKK42Tp8ePH6Nq1aoq6w0MDBAbG5stQRERgPh4qRF4w4bAw4dA8eLS/HSrVgGmptqOjoio0NI4eSpVqhRCQkJU1h85cgSurq7ZERMRXb4MVKsGLFggzVHXty9w6xbQvLm2IyMiKvQ07m33448/YtiwYYiPj4cQAn/++Se2bdsGPz8/rF27NidiJCo8EhOl6VTmzAFSUgA7O6lxeNu22o6MiIj+n8bJU79+/ZCcnIyffvoJcXFx6NmzJxwdHbF06VJ8++23OREjUeFw4wbg5SX9FwB69JDaORUtqt24iIhIicYjjH8sPDwcqampsLW1zc6YtI4jjFOuSk6WappmzACSkgBra6ldU5cu2o6MiChfydMjjCcnJ8PFxQXW1taK9Q8ePICenh6cnZ2zMz6igu3uXam26coVablTJ2D1aqCA/YOEiKgg0bjBeN++fXHhwgWV9ZcuXULfvn2zIyaigi8lRWoMXq2alDhZWACbNwO7dzNxIiLK4zROnq5fv4769eurrK9Tp47aXnhE9IkHD6Qxmn78EUhIAFq1Am7fBnr1AmQybUdHRESZ0Dh5kslkiI6OVlkfGRmpGG2ciNRITQV++QWoXFka+NLMDFi7Fjh0CHB01HZ0RESURRonTw0bNoSfn59SopSSkgI/Pz80aNAgW4MjKjCePAG+/hoYMQL48EGaZuXWLWDAANY2ERHlMxo3GJ83bx48PT1Rvnx5NGzYEABw7tw5REVF4dSpU9keIFG+JoRUuzR2LBATI81DN28e4O0N6HzWvNxERKRlGn97u7q64ubNm+jWrRtev36N6Oho9OnTB/fu3YObm1tOxEiUP/37L9C6NTBokJQ4NWggjeE0bBgTJyKifOyLxnkqqDjOE30RIaSecyNHAhERgIEBMHs2MGoU8NFk2kRElL1y6/f7s/75e+7cOXz33XeoV68e/v33XwDApk2bcP78+WwNjijfefVKGqupTx8pcapVCwgJkR7bMXEiIioQNE6edu/ejRYtWsDIyAjXrl1DQkICACA6OhqzZ8/O9gCJ8o2dO4FKlYD9+wE9PWDWLKlXXYUK2o6MiIiykcbJ08yZM7F69WqsWbMGenp6ivX16tXDtWvXsjU4onwhPBz49lugWzfg7VugShVp4MtJkwBdjftkEBFRHqdx8nT//n14enqqrDc3N0dERER2xESUfxw4ALi5ATt2SI/lpk0DLl0CPDy0HRkREeUQjZMne3t7PHz4UGX9+fPnUbp06WwJiijPi4iQ5qTr0EFq5+TqCly8CPj6Avr62o6OiIhykMbJ0+DBgzFq1ChcunQJMpkML168wJYtW/DDDz9g6NChOREjUd5y9KhU27RxozTkwE8/AVevAjVqaDsyIiLKBRo3yPjpp58QGRmJJk2aID4+Hp6enjAwMMAPP/yA4cOH50SMRHlDdDTwww/Ab79Jyy4uQEAAULeuduMiIqJc9dnjPMXFxeHu3btITU2Fq6srTE1Nszs2reE4T6Ti9Gmgf39pmhVAGsPJz08aMZyIiPKEPDfOU1xcHIYNGwZHR0fY2tri+++/h7OzM2rVqlWgEiciJXFxUqL01VdS4uTsLCVSS5cycSIiKqSynDxNnz4d/v7+aNOmDb799lscP34c3t7eX3RyPz8/1KxZE2ZmZrC1tUXHjh1x//59pX1kMpna1/z589Mt19/fX+0x8fHxXxQvFTIXLkjDDixfLi0PHgzcvAk0bqzNqIiISMuy3OZpz549WLduHb799lsAwHfffYf69esjJSUFRT5z5OSgoCAMGzYMNWvWRHJyMiZPnozmzZvj7t27MDExAQC8fPlS6ZgjR45gwIAB6Ny5c4Zlm5ubqyRihoaGnxUnFTLx8dKQAwsXAqmpgKMjsG4d0KKFtiMjIqI8IMvJ07Nnz9CwYUPFcq1ataCrq4sXL16gRIkSn3XywMBApeUNGzbA1tYWV69eVYwlZWdnp7TP/v370aRJk0yHRZDJZCrHEmXqyhVpCIK7d6VlLy9gyRLAwkKbURERUR6S5cd2KSkp0P9k/BpdXV0kJydnWzCRkZEAACsrK7XbX716hUOHDmHAgAGZlhUTEwMnJycUL14cbdu2xfXr17MtTiqAEhOl2qY6daTEqVgxaZoVf38mTkREpCTLNU9CCPTt2xcGBgaKdfHx8RgyZIjiERsgPd77HEIIjB07Fg0aNICbm5vafQICAmBmZoZvvvkmw7IqVKgAf39/uLu7IyoqCkuXLkX9+vVx48YNuLi4qOyfkJCgmKMPkFrrUyFy86ZUwxQSIi137w6sWAEULarVsIiIKG/K8lAF/fr1y1KBGzZs+KxAhg0bhkOHDuH8+fMoXry42n0qVKiAZs2aYXlaA94sSk1NRbVq1eDp6Ylly5apbPfx8YGvr6/Keg5VUMAlJwNz50qjgiclScnSqlVA167ajoyIiD5Dbg1V8NnjPGWnESNGYN++fTh79ixKlSqldp9z587B09MTISEhqFy5ssbnGDhwIJ4/f44jR46obFNX81SiRAkmTwXZX39JtU2XL0vLHTsCq1dLj+uIiChfyq3kSatTvgshMGLECOzduxdnzpxJN3ECgHXr1qF69eqflTgJIRASEgJ3d3e12w0MDJQeR1IBlpIiNQCfPBlISJDaMy1fDvTqBchk2o6OiIjyAa0mT8OGDcPWrVuxf/9+mJmZISwsDAAgl8thZGSk2C8qKgo7d+7EwoUL1ZbTp08fODo6ws/PDwDg6+uLOnXqwMXFBVFRUVi2bBlCQkKwYsWKnL8oyrsePgT69gX+9z9puWVLYO1aaSgCIiKiLNJq8rRq1SoAQONPBh3csGED+vbtq1jevn07hBDo0aOH2nJCQ0Oho/Nfx8GIiAgMGjQIYWFhkMvlqFq1Ks6ePYtatWpl+zVQPpCaCqxcCYwfL40YbmoKLF4MDBjA2iYiItJYnmjzlNdwbrsC5OlTaU66U6ek5SZNgPXrpWlWiIioQMlzc9sR5StCSI/k3N2lxMnYGPjlF+DECSZORET0RbT62I4oR/z7LzBwIJDWs7J+fWmwy7JltRoWEREVDKx5ooJDCGDzZsDNTUqcDAyABQuAoCAmTkRElG1Y80QFw6tXwJAhwL590nLNmkBAAFCxolbDIiKigoc1T5T/7dwp1Tbt2wfo6QEzZwIXLjBxIiKiHMGaJ8q/3r4Fhg8Htm+XlitXlmqbPmMgVSIioqxizRPlT3/8IdU2bd8OFCkCTJkC/PknEyciIspxrHmi/CUiAhg9WqphAqRHcwEBUhsnIiKiXMCaJ8o/jh2Txm0KCJBGBv/xR+DaNSZORESUq1jzRHlfdLSUKP36q7Rctqw0blP9+loNi4iICifWPFHeduYM4OHxX+I0YgQQEsLEiYiItIY1T5Q3xcUBkyYBS5dKy05OwIYN0tx0REREWsTkifKe4GDAywt48EBaHjgQWLgQMDPTblxERETgYzvKS+LjgfHjgQYNpMTJ0VGaZuW335g4ERFRnsGaJ8obrl4F+vQB7t6Vlvv0kR7ZWVhoNSwiIqJPseaJtCsxEZg+HahdW0qcbG2laVYCApg4ERFRnsSaJ9KeW7ekGqaQEGm5WzdgxQrA2lqrYREREWWENU+U+5KTgdmzgerVpcSpaFFgxw7pxcSJiIjyONY8Ue66d0/qSffnn9Jy+/bSGE52dtqNi4iIKItY80S5IyUFWLQIqFpVSpzkcqld0759TJyIiChfYc0T5bx//gH69gXOn5eWW7QA1q4FihfXalhERESfgzVPlHNSU4GVK6XpVc6fB0xNpTGbjhxh4kRERPkWa54oZ4SGAv37AydPSsuNG0vTqzg7azMqIiKiL8aaJ8peQgDr1gFublLiZGQELFsm/T8TJyIiKgBY80TZ58ULaR66w4el5bp1pUbhLi7ajYuIiCgbseaJvpwQwJYtUm3T4cOAgQEwbx5w7hwTJyIiKnBY80Rf5vVrYMgQYO9eablGDam2ydVVu3ERERHlENY80efbtQuoVElKnPT0gJ9/Bi5cYOJEREQFGmueSHNv3wIjRgDbtknLHh5SbVOVKloNi4iIKDew5ok0c/Cg1LZp2zagSBFg8mTg8mUmTkREVGiw5omyJjISGD0a8PeXlitWlGqbatbUZlRERES5jjVPlLljx6TaJn9/QCYDfvgBuHaNiRMRERVKrHmi9MXEAD/+CKxeLS2XKSMlUA0aaDUsIiIibWLNE6kXFCQ1BE9LnIYPB27cYOJERESFHpMnUhYXJ7VtatwYePwYKFlSmlpl+XLAxETb0REREWmdVpMnPz8/1KxZE2ZmZrC1tUXHjh1x//59pX369u0LmUym9KpTp06mZe/evRuurq4wMDCAq6sr9qYN4kjpu3gRqFoVWLpUWv7+e+DWLeCrr7QbFxERUR6i1eQpKCgIw4YNw8WLF3H8+HEkJyejefPmiI2NVdqvZcuWePnypeJ1OG3utHQEBweje/fu6N27N27cuIHevXujW7duuHTpUk5eTv6VkABMmADUrw/8/Tfg4CBNs7JmDWBuru3oiIiI8hSZEEJoO4g0b968ga2tLYKCguDp6QlAqnmKiIjAvn37slxO9+7dERUVhSNHjijWtWzZEpaWltiWNrBjBqKioiCXyxEZGQnzgp48XL0KeHkBd+5Iy717SzVPlpbajYuIiEhDufX7nafaPEVGRgIArKyslNafOXMGtra2KFeuHAYOHIjXr19nWE5wcDCaN2+utK5Fixa4cOFC9gacnyUlAT4+QO3aUuJkaytNs7JxIxMnIiKiDOSZoQqEEBg7diwaNGgANzc3xfpWrVqha9eucHJywuPHjzF16lR89dVXuHr1KgwMDNSWFRYWhmLFiimtK1asGMLCwtTun5CQgISEBMVyVFRUNlxRHnbrllTbdP26tNy1K7BiBWBjo924iIiI8oE8kzwNHz4cN2/exPnz55XWd+/eXfH/bm5uqFGjBpycnHDo0CF888036ZYnk8mUloUQKuvS+Pn5wdfX9wuizyeSk4H584Hp06WaJysrYOVK4KN7TERERBnLE4/tRowYgQMHDuD06dMoXrx4hvva29vDyckJDx48SHcfOzs7lVqm169fq9RGpZk4cSIiIyMVr2fPnml+EXnd/fvSGE2TJkmJU7t20uM6Jk5EREQa0WryJITA8OHDsWfPHpw6dQqlSpXK9Ji3b9/i2bNnsLe3T3efunXr4vjx40rrjh07hnr16qnd38DAAObm5kqvAiM1FVi8WJq499IlQC6XRgnfvx+ws9N2dERERPmOVh/bDRs2DFu3bsX+/fthZmamqC2Sy+UwMjJCTEwMfHx80LlzZ9jb2+PJkyeYNGkSrK2t0alTJ0U5ffr0gaOjI/z8/AAAo0aNgqenJ+bOnYsOHTpg//79OHHihMojwQLvn3+Afv2Ac+ek5ebNgXXrgExq94iIiCh9Wq15WrVqFSIjI9G4cWPY29srXjt27AAAFClSBLdu3UKHDh1Qrlw5eHl5oVy5cggODoaZmZminNDQULx8+VKxXK9ePWzfvh0bNmyAh4cH/P39sWPHDtSuXTvXr1ErUlOltkyVK0uJk4mJNM1KYCATJyIioi+Up8Z5yivy9ThPoaHAgAHAiRPScqNGwIYNQBYeiRIREeVnhXKcJ/oCQgDr1wPu7lLiZGQkDXZ56hQTJyIiomyUZ4YqoC/w4gUwaBBw6JC0XLeu1Ci8XDmthkVERFQQseYpPxMC2LoVcHOTEid9fWDuXKmdExMnIiKiHMGap/zq9WvA2xvYs0darl4dCAgAKlXSblxEREQFHGue8qPdu6Xapj17AF1dwNcXCA5m4kRERJQLWPOUn7x7B4wYIT2qA6TG4QEBQNWq2o2LiIioEGHNU35x6JBU27R1K6CjI02zcvkyEyciIqJcxpqnvC4yEhgzRhqrCQDKl5dqmwrLgJ9ERER5DGue8rITJ6RHcxs2ADIZMHYscP06EyciIiItYs1TXhQTA/z0E7BqlbRcurQ0blPDhloNi4iIiFjzlPecPSvNSZeWOA0dCty4wcSJiIgoj2DylFd8+CA9lmvcGHj0CChZUnpst2IFYGqq7eiIiIjo//GxXV5w6RLg5QXcvy8tDxgALFoE5LdJiYmIiAoB1jxpU0ICMHEiUK+elDjZ20tDEqxdy8SJiIgoj2LNk7ZcuybVNt2+LS336gUsWwZYWWk3LiIiIsoQa55yW1KSNJ1K7dpS4mRjI02zsnkzEyciIqJ8gDVPuenOHaBPH6nWCQA6d5Z61dnYaDcuIiIiyjLWPOWmV6+kxMnSUppmZedOJk5ERET5DGuectNXXwFr1gBt2kiNw4mIiCjfYfKU277/XtsREBER0RfgYzsiIiIiDTB5IiIiItIAkyciIiIiDTB5IiIiItIAkyciIiIiDTB5IiIiItIAkyciIiIiDTB5IiIiItIAB8nMRZFxiQiPSURUfBLMjfRgbaIPubG+tsMiIiIiDTB5yiUvIj5g/O6bOPcgXLHO08Uaczp7wMHCSIuRERERkSb42C4XRMYlqiROAHD2QTgm7L6JyLhELUVGREREmmLylAvCYxJVEqc0Zx+EIzyGyRMREVF+weQpF0TFJ2W4PTqT7URERJR3MHnKBeaGehluN8tkOxEREeUdTJ5ygbWpPjxdrNVu83SxhrUpe9wRERHlF1pNnvz8/FCzZk2YmZnB1tYWHTt2xP379xXbk5KSMH78eLi7u8PExAQODg7o06cPXrx4kWG5/v7+kMlkKq/4+PicviS15Mb6mNPZQyWB8nSxxtzOHhyugIiIKB/R6lAFQUFBGDZsGGrWrInk5GRMnjwZzZs3x927d2FiYoK4uDhcu3YNU6dOReXKlfH+/XuMHj0a7du3x5UrVzIs29zcXCkRAwBDQ8OcvJwMOVgYYXmPqgiPSUR0fBLMDPVgbcpxnoiIiPIbrSZPgYGBSssbNmyAra0trl69Ck9PT8jlchw/flxpn+XLl6NWrVoIDQ1FyZIl0y1bJpPBzs4uR+L+XHJjJktERET5XZ5q8xQZGQkAsLKyynAfmUwGCwuLDMuKiYmBk5MTihcvjrZt2+L69evZGSoREREVUnkmeRJCYOzYsWjQoAHc3NzU7hMfH48JEyagZ8+eMDc3T7esChUqwN/fHwcOHMC2bdtgaGiI+vXr48GDB2r3T0hIQFRUlNKLiIiISB2ZEEJoOwgAGDZsGA4dOoTz58+jePHiKtuTkpLQtWtXhIaG4syZMxkmT59KTU1FtWrV4OnpiWXLlqls9/Hxga+vr8r6yMhIjc5DRERE2hMVFQW5XJ7jv995ouZpxIgROHDgAE6fPp1u4tStWzc8fvwYx48f1/iG6OjooGbNmunWPE2cOBGRkZGK17Nnzz7rOoiIiKjg02qDcSEERowYgb179+LMmTMoVaqUyj5pidODBw9w+vRpFC1a9LPOExISAnd3d7XbDQwMYGBgoHG5REREVPhoNXkaNmwYtm7div3798PMzAxhYWEAALlcDiMjIyQnJ6NLly64du0aDh48iJSUFMU+VlZW0NeXeq716dMHjo6O8PPzAwD4+vqiTp06cHFxQVRUFJYtW4aQkBCsWLFCOxdKREREBYZWk6dVq1YBABo3bqy0fsOGDejbty+eP3+OAwcOAACqVKmitM/p06cVx4WGhkJH578nkBERERg0aBDCwsIgl8tRtWpVnD17FrVq1cqxayEiIqLCIc80GM9LcqvBGREREWWfQtVgnIiIiCi/YPJEREREpAGttnnKq9KeZHKwTCIiovwj7Xc7p1skMXlSIzo6GgBQokQJLUdCREREmoqOjoZcLs+x8tlgXI3U1FS8ePECZmZmkMlkAKRstkSJEnj27Bkbkecg3ufcwfucO3ifcw/vde7I6/dZCIHo6Gg4ODgo9cLPbqx5UkNHR0ftSOcAYG5uniffMAUN73Pu4H3OHbzPuYf3Onfk5fuckzVOadhgnIiIiEgDTJ6IiIiINMDkKYsMDAwwffp0zoGXw3ifcwfvc+7gfc49vNe5g/dZwgbjRERERBpgzRMRERGRBpg8EREREWmAyRMRERGRBpg8EREREWmgUCVPZ8+eRbt27eDg4ACZTIZ9+/YpbX/16hX69u0LBwcHGBsbo2XLlnjw4IHSPv/88w86deoEGxsbmJubo1u3bnj16pXSPu/fv0fv3r0hl8shl8vRu3dvRERE5PDV5R25dZ+dnZ0hk8mUXhMmTMjpy8sT/Pz8ULNmTZiZmcHW1hYdO3bE/fv3lfYRQsDHxwcODg4wMjJC48aNcefOHaV9EhISMGLECFhbW8PExATt27fH8+fPlfYp7O/n3LzXfE9/+X3+7bff0LhxY5ibm0Mmk6l9rxbm93Ru3ueC/H4uVMlTbGwsKleujF9++UVlmxACHTt2xKNHj7B//35cv34dTk5O+PrrrxEbG6s4vnnz5pDJZDh16hT+97//ITExEe3atUNqaqqirJ49eyIkJASBgYEIDAxESEgIevfunWvXqW25dZ8BYMaMGXj58qXiNWXKlFy5Rm0LCgrCsGHDcPHiRRw/fhzJyclo3ry54h4CwLx587Bo0SL88ssvuHz5Muzs7NCsWTPF3I0AMHr0aOzduxfbt2/H+fPnERMTg7Zt2yIlJUWxT2F/P+fmvQb4nv7S+xwXF4eWLVti0qRJ6Z6rML+nc/M+AwX4/SwKKQBi7969iuX79+8LAOL27duKdcnJycLKykqsWbNGCCHE0aNHhY6OjoiMjFTs8+7dOwFAHD9+XAghxN27dwUAcfHiRcU+wcHBAoC4d+9eDl9V3pNT91kIIZycnMTixYtz/Bryg9evXwsAIigoSAghRGpqqrCzsxNz5sxR7BMfHy/kcrlYvXq1EEKIiIgIoaenJ7Zv367Y599//xU6OjoiMDBQCMH3szo5da+F4Hv6Y59znz92+vRpAUC8f/9eaT3f08py6j4LUbDfz4Wq5ikjCQkJAABDQ0PFuiJFikBfXx/nz59X7COTyZQGBzM0NISOjo5in+DgYMjlctSuXVuxT506dSCXy3HhwoXcuJQ8Lbvuc5q5c+eiaNGiqFKlCmbNmoXExMRcuIq8JzIyEgBgZWUFAHj8+DHCwsLQvHlzxT4GBgZo1KiR4n149epVJCUlKe3j4OAANzc3xT58P6vKqXudhu9pyefc56zge1pZTt3nNAX1/czk6f9VqFABTk5OmDhxIt6/f4/ExETMmTMHYWFhePl/7dtPSJN/HAfwt/lbJSHLke5ZDMVDdDGDPPSH6BASBWIQXmQHD15UFpIQXoJdvRTVNaiDl/7QiE5BsVWHRlE9od6cgoI8YznKYkYie/8O0uNvbZRPv+2Zbe8XDGR++LLvm7fwcWyWBWDjD2zPnj0YHx/H6uoqstksLl++jFwuZ8+kUim0tLQUnN/S0oJUKuXqnbajUuUMAKOjo7h79y7i8TjC4TCuX7+OkZGRSl2tYkhibGwMJ0+eREdHBwDYXfP7/Xmzfr/f/l0qlcLOnTvR1NT0yxn1eVM5swbU6R/+NOetUKc3lTNnoLr7/E+lX8B24fF48PDhQwwODsLn86G+vh7d3d04d+6cPdPc3IwHDx5geHgYN2/exI4dO9Df348jR46gvr7enqurqys4n2TR52tNKXO+dOmS/XNnZyeamprQ19dn/6dTK8LhMKampgrelQMKu7iVHv48oz5vKnfW6vSGUuf8uzP+9Jy/XblzruY+652n/+jq6sKHDx/w+fNnWJaFJ0+eIJPJoL293Z45c+YM5ubmkE6nsby8jMnJSSwtLdkzhmEUfCsMAD5+/FiwydeqUuRczLFjxwAAyWSy7HfYLi5evIjHjx8jHo8jGAzazxuGAQAF/ymm02m7h4ZhYG1tDZ8+ffrljPq8odxZF6NOO8t5K9TpDeXOuZhq6rOWpyK8Xi+am5sxOzuLt2/f4vz58wUz+/btw969exGLxZBOp9Hb2wsAOH78OFZWVvDmzRt79vXr11hZWcGJEydcu8Pf4P/kXIxpmgCAQCBQtte8XZBEOBxGNBpFLBYrWCrb29thGAaePn1qP7e2toYXL17YPezq6oLH48mbsSwLMzMz9oz67F7WxajTm7aS81bUeqfdyrmYquqz6x9Rr6CvX7/SNE2apkkAvHbtGk3T5MLCAkny/v37jMfjnJub46NHj9jW1sYLFy7knXH79m0mEgkmk0lOTk7S5/NxbGwsb+bs2bPs7OxkIpFgIpHgoUOH2NPT49o9K82NnF+9emWfOz8/z3v37nH//v3s7e119a6VMjw8TK/Xy+fPn9OyLPuxurpqz0xMTNDr9TIajXJ6epr9/f0MBAL88uWLPTM0NMRgMMhnz57x/fv3PH36NA8fPsz19XV7ptb77FbW6nRpcrYsi6Zp8tatWwTAly9f0jRNZjIZe6aWO+1WztXe55pann58pfLnx8DAAEnyxo0bDAaD9Hg8bG1t5ZUrV/j9+/e8M8bHx+n3++nxeHjgwAFevXqVuVwubyaTyTAUCrGxsZGNjY0MhUJFv8ZZrdzI+d27dzx69Ci9Xi93797NgwcPMhKJMJvNunnViimWLwDeuXPHnsnlcoxEIjQMg7t27eKpU6c4PT2dd863b98YDofp8/nY0NDAnp4eLi4u5s3Uep/dylqdLk3OkUjkt+fUcqfdyrna+1xHkqV/P0tERESkOukzTyIiIiIOaHkSERERcUDLk4iIiIgDWp5EREREHNDyJCIiIuKAlicRERERB7Q8iYiIiDig5UlERETEAS1PIiIiIg5oeRIRERFxQMuTiIiIiANankREREQc+BevT/arDrfDvQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotML(generalObesity, linRegressML, x) # plot data and best fit line"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0d5c305-013c-48a9-a53a-ccb14eaa65ea",
   "metadata": {},
   "source": [
    "**Comment:** The linear regression outperforms the baseline model with mean squared error = 1. The model predicts that in 2024, 45.54% of the population in US are obese. The result is reasonable in the fact that the rate of obesity always increases according to our data and 2024 is close to this year range 1988-2018 so it is safe to predict based on this trend."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3696848-687b-4c88-a492-9ea7c7f546b5",
   "metadata": {},
   "source": [
    "**Logistic Regression**\n",
    "\n",
    "The Logistic Regression model predicts the likelihood of an individual being physically inactive based on age, gender, and race/ethnicity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "883601e5-60a2-43a9-ac33-792822422ea6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.80\n",
      "Confusion Matrix:\n",
      "[[1274   41]\n",
      " [ 304   76]]\n",
      "\n",
      "Sample Input 1:\n",
      "Age: 25 - 34\n",
      "Gender: Male\n",
      "Race/Ethnicity: Non-Hispanic White\n",
      "Predicted Inactivity: Active\n",
      "\n",
      "Sample Input 2:\n",
      "Age: 45 - 54\n",
      "Gender: Female\n",
      "Race/Ethnicity: Non-Hispanic Black\n",
      "Predicted Inactivity: Inactive\n",
      "\n",
      "Sample Input 3:\n",
      "Age: 65 or older\n",
      "Gender: Male\n",
      "Race/Ethnicity: Hispanic\n",
      "Predicted Inactivity: Inactive\n",
      "\n",
      "Baseline Accuracy: 0.22418879056047197\n",
      "Baseline Confusion Matrix:\n",
      "[[   0 1315]\n",
      " [   0  380]]\n",
      "\n",
      "Logistic Regression Accuracy: 0.7964601769911505\n",
      "Logistic Regression Confusion Matrix:\n",
      "[[1274   41]\n",
      " [ 304   76]]\n"
     ]
    }
   ],
   "source": [
    "# Train the model\n",
    "lr_model, X_test, y_test = train_model(cleaned_df)\n",
    "# Evaluate the model\n",
    "evaluate_model(lr_model, X_test, y_test)\n",
    "# Create sample inputs for different types of individuals\n",
    "sample_inputs = [\n",
    "    {\"Age(years)\": \"25 - 34\", \"Gender\": \"Male\", \"Race/Ethnicity\": \"Non-Hispanic White\"},\n",
    "    {\"Age(years)\": \"45 - 54\", \"Gender\": \"Female\", \"Race/Ethnicity\": \"Non-Hispanic Black\"},\n",
    "    {\"Age(years)\": \"65 or older\", \"Gender\": \"Male\", \"Race/Ethnicity\": \"Hispanic\"},\n",
    "]\n",
    "# Predict inactivity for sample inputs\n",
    "predict_inactivity(lr_model, sample_inputs)\n",
    "# Evaluate the baseline model\n",
    "y_pred = lr_model.predict(X_test)\n",
    "baseline_model(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8662970-056b-44a4-b11b-d716abeb2869",
   "metadata": {},
   "source": [
    "## Visualizations + Additional Visualization\n",
    "**Wealthy adults in 2018 are more likely to be obese than Low-Income Adults in 1988**\n",
    "\n",
    "1988\n",
    "- In the normal BMI range, as the income range increases, the percentage of normal weight population increases. \n",
    "- In the obesity BMI range, as the income range increases the percentage of obese population decreases.\n",
    "  \n",
    "2018\n",
    "- In the normal BMI range, the percentage of normal weight population is unaffected by the increase in income. \n",
    "- In the BMI(25+), those in poverty level of 200%+ have higher obese rates. In the BMI(30+) level in 2018, adults with higher income have less percentage of obesity.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2519fd6e-9c25-41af-9fb8-bbcf6fece045",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x350 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "poverty_visual(obesity_adult)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a93b8fd-b56a-429f-b9dd-e0846f6a1468",
   "metadata": {},
   "source": [
    "**Hispanic individuals aged 2-19 have the highest obesity rate from 1988-2018**\n",
    "This is an interactive visual where you can select the different races to see the trend of obesity throughout the years.\n",
    "- From 1988 - 1994 hispanic or latino, mexican have the highest percentage of obesity at 14.3% with black or african american with the second highest percentage at 12.5%.\n",
    "- In recent years in individuals 2-19, asians have the lowest obesity rate and hispanic or latino, mexican have the highest. Caucasians have one of the lower obesity rates trailing near 15%.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f1d99292-373b-43b8-9a9c-d68689722e31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "RACE=Not Hispanic or Latino: White only<br>YEAR=%{x}<br>ESTIMATE=%{y}<extra></extra>",
         "legendgroup": "Not Hispanic or Latino: White only",
         "line": {
          "color": "#636efa",
          "dash": "solid",
          "width": 2.75
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Not Hispanic or Latino: White only",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          "1988-1994",
          "1999-2002",
          "2001-2004",
          "2003-2006",
          "2005-2008",
          "2007-2010",
          "2009-2012",
          "2011-2014",
          "2013-2016",
          "2015-2018"
         ],
         "xaxis": "x",
         "y": [
          9.2,
          12.6,
          15.1,
          14.7,
          14.1,
          14.6,
          14,
          14.7,
          14.7,
          15.1
         ],
         "yaxis": "y"
        },
        {
         "hovertemplate": "RACE=Not Hispanic or Latino: Black or African American only<br>YEAR=%{x}<br>ESTIMATE=%{y}<extra></extra>",
         "legendgroup": "Not Hispanic or Latino: Black or African American only",
         "line": {
          "color": "#EF553B",
          "dash": "solid",
          "width": 2.75
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Not Hispanic or Latino: Black or African American only",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          "1988-1994",
          "1999-2002",
          "2001-2004",
          "2003-2006",
          "2005-2008",
          "2007-2010",
          "2009-2012",
          "2011-2014",
          "2013-2016",
          "2015-2018"
         ],
         "xaxis": "x",
         "y": [
          12.5,
          18.2,
          18.8,
          20.7,
          20.7,
          22.1,
          22.1,
          19.5,
          20.4,
          23.1
         ],
         "yaxis": "y"
        },
        {
         "hovertemplate": "RACE=Not Hispanic or Latino: Asian only<br>YEAR=%{x}<br>ESTIMATE=%{y}<extra></extra>",
         "legendgroup": "Not Hispanic or Latino: Asian only",
         "line": {
          "color": "#00cc96",
          "dash": "solid",
          "width": 2.75
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Not Hispanic or Latino: Asian only",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          "1988-1994",
          "1999-2002",
          "2001-2004",
          "2003-2006",
          "2005-2008",
          "2007-2010",
          "2009-2012",
          "2011-2014",
          "2013-2016",
          "2015-2018"
         ],
         "xaxis": "x",
         "y": [
          null,
          null,
          null,
          null,
          null,
          null,
          null,
          8.6,
          9.8,
          9.8
         ],
         "yaxis": "y"
        },
        {
         "hovertemplate": "RACE=Hispanic or Latino: All races<br>YEAR=%{x}<br>ESTIMATE=%{y}<extra></extra>",
         "legendgroup": "Hispanic or Latino: All races",
         "line": {
          "color": "#ab63fa",
          "dash": "solid",
          "width": 2.75
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines",
         "name": "Hispanic or Latino: All races",
         "orientation": "v",
         "showlegend": true,
         "type": "scatter",
         "x": [
          "1988-1994",
          "1999-2002",
          "2001-2004",
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   "source": [
    "obesity_Visual2(race_his_obesity)\n",
    "import plotly.offline as pyo\n",
    "pyo.init_notebook_mode(connected=True)"
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   "id": "b1c34bf5-c5df-47e8-9a5a-182ddd470c2c",
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    "**Asians have less obesity rate than people of other races in all levels of Obesity**\n",
    "\n",
    "**Description:** We created this visualization to test the hypothesis that Asians have a lower obesity rate than other races, the visualization shows that Asians have a lower obesity level than other races in all 3 different types of obesity:\n",
    "- Obesity grade 1: 10% asians have grade 1 obesity and other races average is around 20%;\n",
    "- Obesity grade 2: 4% of Asians have grade 2 obesity and other races average is around 10%;\n",
    "- Obesity grade 3: 1% of Asians have grade 3 obesity and other races average is around 9%"
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   "cell_type": "code",
   "execution_count": 12,
   "id": "95232521-de40-4518-b7bf-27a7cd7ee677",
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",
      "text/plain": [
       "<Figure size 1300x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "obesityRaceVsObesity(raceGender_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ad71da5-f6b6-4349-a7f9-5395b2b3f3ad",
   "metadata": {},
   "source": [
    "**Interactive Visualization**\n",
    "\n",
    "**Directions for the interactive visual are in the README**.\n",
    "This is an interactive visual where you can select options from the dropdown menu to get a different heatmap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ff857826-360d-4b36-a2ef-dfda9557a748",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "82715a0dde8d42039df0180fe6aa74b0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Dropdown(description='Select Race:', options=('American Indian/Alaska Native', 'Other', …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<function Analysis.helper_functions.obesity_visualization.update_plot(race, concatenated_df)>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "concatenated_df = load_and_prepare_data()\n",
    "races_with_total = concatenated_df['Race/Ethnicity'].dropna().unique()\n",
    "race_dropdown = Dropdown(options=races_with_total, description=\"Select Race:\")\n",
    "interact(update_plot, race=race_dropdown, concatenated_df=fixed(concatenated_df))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01718955-02bc-4f2b-9d8a-feff6882dae0",
   "metadata": {},
   "source": [
    "## Results\n",
    "Our initial analysis delved into the relationship between income level and obesity rates, aiming to understand if income plays a significant role in the escalating rise of obesity within the United States. Our analysis examined data from 1988 to 2018, revealing evolving patterns between income levels and obesity. One visualization, \"Adolescents Below the Poverty Line Face Highest Obesity Rates from Ages 2-19,\" depicted on our progress report by highlighting the correlation across different age groups. It shows that higher poverty correlates with increased obesity rates and that obesity decreases as poverty decreases. Notably, adolescents aged 12-19 consistently show the highest rates regardless of poverty level. The data also indicates that children aged 2-5 in households with an income 400% above the poverty line are least at risk of obesity, suggesting that economic challenges limit access to nutritious food and health activities, particularly among lower-income groups. Initially, higher incomes correlated with lower obesity rates, but by 2018, this pattern blurred in the highest obesity categories (BMI of 30+), showing a convergence of rates across income levels. Despite this convergence, the general trend remains: lower incomes are associated with higher obesity rates.\n",
    "\n",
    "We then investigated how obesity rates differ among various races and age groups with the United States. We hypothesized that Asians typically have lower obesity rates compared to other ethnic groups. Our analysis included a visualization titled, \"Hispanic Individuals Aged 2-19 Have the Highest Obesity Rate from 1988-2018.\" Our data indicated that Hispanic children, particularly those of Mexican descent, exhibited the highest obesity rates. From 1988 to 1994, Hispanics recorded the highest obesity rate at 14.3%, with Black or African Americans following at 12.5%. This trend has persisted over time, with Hispanic rates peaking at 26.9% by 2018, and Black or African Americans at 23.1%. Conversely, Asians maintained the lowest obesity rates, consistently below 10%.\n",
    " \n",
    "After examining the growing trends in obesity rates among children, it was equally important for us to consider how these patterns manifest in adult populations across different races. By broadening our perspective to include adults, we created our visualization titled, \"Asians Have Lower Obesity Rates Than People of Other Races in All Levels of Obesity,\" focused on adults aged 20 and above. This visualization categorized obesity into grades by percentage: Grade 1 (BMI of 30 to 34.9), Grade 2 (BMI of 35 to 39.9), and Grade 3 (BMI of 40 or more). The insights from this chart showed that Asians consistently had the lowest rates across all obesity grades. Specifically, only 10% of Asians fell into Grade 1 obesity, compared to an average of 20% among other races. For Grade 2 obesity, 4% of Asians were affected, versus an average of about 10% for other groups. In the most severe category, Grade 3, only 1% of Asians were impacted, while the average for other racial groups hovered around 9%. Notably, Black or African American females exhibited the highest percentages within Grade 3 obesity.\n",
    "\n",
    "**ML Results**\n",
    "\n",
    "Based on the trend of the rate of obesity of adult in the US between 1988 and 2018, what will be the rate of obesity in the US in 2024? We data clean by extracting rate of obesity in general and the timeline. We used linear regression model to graph the best fit line so we can tell the trend of the rate of obesity in the US. Based on this increasing trend, we predict the rate of obesity in US in 2024, which is 45.54%, and claim that the rate of obesity still increases according to this trend. "
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