{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Detection and dealing with bias in EHR data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Biases in EHR data, originating from sources like selective documentation and demographic disparities, challenge healthcare analytics by skewing research outcomes and clinical decisions. These biases can lead to misrepresentation of patient groups and minorities.\n",
    "Exploratory data analysis (EDA), through data visualization, statistical summaries, and pattern identification, is a critical step in uncovering and mitigating biases.\n",
    "\n",
    "In this tutorial, we outline the various sources of bias and show how they can be detected and potentially mitigated.\n",
    "Note that many biases are already inherent to the data collection process itself and can only be unveiled but not always dealt with.\n",
    "We make use of the [Diabetes 130-US Hospitals for years 1999-2008](https://archive.ics.uci.edu/dataset/296/diabetes+130-us+hospitals+for+years+1999-2008) dataset (\"Diabetes-130\") and synthetic datasets. ([Strack et al. 2014](https://www.hindawi.com/journals/bmri/2014/781670/))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Environment setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Install fairlearn if you do not already have it.\n",
    "# !pip install fairlearn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:20:43.430684Z",
     "start_time": "2024-05-13T12:20:41.744102Z"
    }
   },
   "outputs": [],
   "source": [
    "import ehrapy as ep\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from tableone import TableOne\n",
    "from anndata import AnnData\n",
    "\n",
    "import warnings\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# Custom plots: https://github.com/theislab/ehrapy-tutorials\n",
    "from bias_utils import distributions_plot, grouped_barplot, plot_hist_normalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-12T16:37:40.366001Z",
     "start_time": "2024-05-12T16:37:40.364069Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = [10, 5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The \"Diabetes 130-US Hospitals for years 1998-2008\" (\"Diabetes-130\") dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset encompasses ten years of clinical data from 130 US hospitals, detailing hospital records for diabetic patients, including laboratory tests, medications, and up to 14-day stays.\n",
    "This dataset is per-patient-visit, not a per-patient basis. Beware that the same patient may be included multiple times."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "|features| description|\n",
    "|---|---|\n",
    "| race, gender, age | demographic features |\n",
    "| medicare, medicaid | insurance information |\n",
    "| admission_source_id | emergency, referral, or other |\n",
    "| had_emergency, had_inpatient_days,<br>had_outpatient_days | hospital visits in prior year |\n",
    "| medical_specialty | admitting physician's specialty |\n",
    "| time_in_hospital, num_lab_procedures,<br>num_procedures, num_medications,<br>primary_diagnosis, number_diagnoses,<br>max_glu_serum, A1Cresult, insulin<br>change, diabetesMed | description of the hospital visit<br> |\n",
    "| discharge_disposition_id | discharched to home or not |\n",
    "| readmitted, readmit_binary,<br>readmit_30_days | readmission information |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading Diabetes-130"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We load a [preprocessed version derived by the fairlearn team](https://fairlearn.org/main/user_guide/datasets/diabetes_hospital_data.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-12T15:34:29.998973Z",
     "start_time": "2024-05-12T15:34:29.334611Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "❗ Feature types were inferred and stored in adata.var. Please verify and adjust if necessary.\n"
     ]
    }
   ],
   "source": [
    "adata = ep.dt.diabetes_130_fairlearn()\n",
    "ep.ad.move_to_obs(adata, [\"race\", \"gender\", \"age\"], copy_obs=True)\n",
    "\n",
    "# make prettier variable names\n",
    "adata.obs.rename(\n",
    "    columns={\"race\": \"Race\", \"gender\": \"Gender\", \"age\": \"Age\"}, inplace=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A quick check on the presence of missing data in the dataset can be obtained"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ep.pl.missing_values_matrix(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that the dataset contains mostly completely recorded variables, except for `max_glu_serum` and `A1Cresult` variables, which are often missing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selection bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Selection bias occurs when the data are not representative of the general population, often because the individuals in the dataset are more likely to seek care or have certain conditions.\n",
    "This can lead to skewed results and incorrect inferences about disease prevalence, treatment effects, or health outcomes.\n",
    "For example, a study using EHR data from a specialized clinic may overestimate the prevalence of a specific condition because patients visiting the clinic are more likely to have that condition compared to the general population."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Patient Demographics\n",
    "\n",
    "A popular option in clinical studies is by representing this information in a table:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "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></th>\n",
       "      <th>Missing</th>\n",
       "      <th>Overall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <th></th>\n",
       "      <td></td>\n",
       "      <td>101766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">Race, n (%)</th>\n",
       "      <th>AfricanAmerican</th>\n",
       "      <td>0</td>\n",
       "      <td>19210 (18.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Asian</th>\n",
       "      <td></td>\n",
       "      <td>641 (0.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caucasian</th>\n",
       "      <td></td>\n",
       "      <td>76099 (74.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hispanic</th>\n",
       "      <td></td>\n",
       "      <td>2037 (2.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td></td>\n",
       "      <td>1506 (1.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown</th>\n",
       "      <td></td>\n",
       "      <td>2273 (2.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Gender, n (%)</th>\n",
       "      <th>Female</th>\n",
       "      <td>0</td>\n",
       "      <td>54708 (53.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male</th>\n",
       "      <td></td>\n",
       "      <td>47055 (46.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown/Invalid</th>\n",
       "      <td></td>\n",
       "      <td>3 (0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">Age, n (%)</th>\n",
       "      <th>'30 years or younger'</th>\n",
       "      <td>0</td>\n",
       "      <td>2509 (2.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'30-60 years'</th>\n",
       "      <td></td>\n",
       "      <td>30716 (30.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Over 60 years'</th>\n",
       "      <td></td>\n",
       "      <td>68541 (67.4)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><br />"
      ],
      "text/plain": [
       "                                    Missing       Overall\n",
       "n                                                  101766\n",
       "Race, n (%)   AfricanAmerican             0  19210 (18.9)\n",
       "              Asian                             641 (0.6)\n",
       "              Caucasian                      76099 (74.8)\n",
       "              Hispanic                         2037 (2.0)\n",
       "              Other                            1506 (1.5)\n",
       "              Unknown                          2273 (2.2)\n",
       "Gender, n (%) Female                      0  54708 (53.8)\n",
       "              Male                           47055 (46.2)\n",
       "              Unknown/Invalid                     3 (0.0)\n",
       "Age, n (%)    '30 years or younger'       0    2509 (2.5)\n",
       "              '30-60 years'                  30716 (30.2)\n",
       "              'Over 60 years'                68541 (67.4)"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TableOne(adata.obs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ehrapy allows to represent this information graphically as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ct = ep.tl.CohortTracker(adata)\n",
    "ct(adata)\n",
    "ct.plot_cohort_barplot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can immediately observe how the different demographics are represented:\n",
    "\n",
    "- The age group \"Over 60 years\" is present more frequently than the other age groups \"30 years or younger\" and \"30-60 years\".\n",
    "- The gender groups are balanced, with females forming a slight majority in the dataset. Only 3 visits have a label of \"Unknown/Invalid\".\n",
    "- Caucasian are by far the most frequent group. While African American contributes a significant part of the dataset, Asian, Hispanic, Other and Unknown together form less than 7% of the data.\n",
    "\n",
    "Any analysis take aways may be primarily bias towards characteristics of the Caucasian group if not controlled for.\n",
    "Notice that a perfect balance does not imply unbiasedness; if a disease is more prevalent among a subgroup, we would expect a non-uniform distribution from a representative dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "- Discuss with data collectors early to ensure that the data collection and sampling process includes a wide range of patient demographics and health conditions.\n",
    "- Use stratified sampling techniques so that all relevant subgroups are represented according to their real-world or equal distribution.\n",
    "- Consider dropping groups that can lead to too small sample sizes when stratified sampling is used. See section \"Decision point: How do we address smaller group sizes?\" [here](https://github.com/fairlearn/talks/blob/main/2021_scipy_tutorial/fairness-in-AI-systems-instructors.ipynb).\n",
    "- Employ propensity score matching to adjust for variables that predict receiving the treatment, thus balancing the data.\n",
    "- Apply inverse probability weighting (that is, assign more weight to groups infrequently observed) to adjust the influence of observed variables that could lead to selection bias."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, **in the later discussed algorithmic bias example we will:**\n",
    "\n",
    "- merge the three smallest race groups *Asian*, *Hispanic*, *Other* (similar to [Strack et al., 2014](https://www.hindawi.com/journals/bmri/2014/781670/))\n",
    "- drop the gender group *Unknown/Invalid*, because the sample size is so small that no meaningful assessment is possible"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtering bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Filtering bias emerges when the criteria used to include or exclude records in the analysis are unintendedly or unexpectedly filtering for other variables as well, potentially leading to a non-representative sample of the original population.\n",
    "This bias can obscure the true relationships between variables by systematically removing certain patient groups based on arbitrary or non-transparent criteria."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Medicare"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Consider below an example where one filters to the subgroup of *[Medicare](https://www.hhs.gov/answers/medicare-and-medicaid/what-is-the-difference-between-medicare-medicaid/index.html)* recipients.\n",
    "*Medicare* is only available to people over the age of 65 and younger individuals with severe illnesses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_filtered = adata.copy()\n",
    "\n",
    "ct = ep.tl.CohortTracker(adata_filtered, columns=[\"Age\", \"Gender\", \"Race\"])\n",
    "ct(adata_filtered, label=\"Initial Cohort\")\n",
    "\n",
    "adata_filtered = adata_filtered[\n",
    "    adata_filtered.X[:, adata_filtered.var_names == \"medicare\"] == True\n",
    "]\n",
    "ct(adata_filtered, label=\"Filtered to medicaid recipients\")\n",
    "fig, _ = ct.plot_cohort_barplot(\n",
    "    subfigure_title=True,\n",
    "    show=False,\n",
    ")\n",
    "fig.subplots_adjust(hspace=0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While we would expect that our medicare-recipients filtered dataset will consist predominantly of patients over 60 years, we might not have expected that the imbalance of the different reported race groups is aggraveted."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "- Explicitly define and consistently apply inclusion and exclusion criteria for the dataset.\n",
    "- Document the rationale for all inclusion and exclusion decisions by tracking the cohort.\n",
    "- Track and report key variables of the patient population representation in the dataset.\n",
    "- Perform sensitivity analysis for any potentially confounding variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Surveillance bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Surveillance bias occurs when the likelihood of detecting a condition or outcome is influenced by the intensity or frequency of monitoring, leading to an overestimation of the association between exposure and outcome.\n",
    "For instance, individuals in a clinical trial may receive more rigorous testing and follow-up compared to the general population, thus appearing to have higher rates of certain conditions or side effects."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Hemoglobin A1c measurement frequency"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hemoglobin A1c (HbA1c) is an important measure of glucose control, which is widely applied to measure performance of diabetes care ([Strack et al., 2014](https://www.hindawi.com/journals/bmri/2014/781670/)).\n",
    "\n",
    "Strack et al. highlight that the measurement of HbA1c at the time of hospital admission offers an opportunity to assess the current diabetes therapy efficacy, but is only done in 18.4% of patients in the inpatient setting.\n",
    "Here, we can observe that differences between the patient admission type seem to exist: Namely, it appears to be measured more frequently for emergency admissions than for referrals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "ep.ad.move_to_obs(adata, [\"A1Cresult\", \"admission_source_id\"], copy_obs=True)\n",
    "adata.obs[\"A1Cresult_measured\"] = ~adata.obs[\"A1Cresult\"].isna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x34b840dd0>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 513.333x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ep.pl.catplot(\n",
    "    adata=adata,\n",
    "    y=\"A1Cresult_measured\",\n",
    "    x=\"admission_source_id\",\n",
    "    kind=\"point\",\n",
    "    join=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "When recording the data (talk to data collectors):\n",
    "- Ensure that all groups within the study are monitored with the same frequency and thoroughness, based on standardized clinical protocols.\n",
    "- Design prospective studies to specify and control the monitoring frequency and methods for all patient cohorts from the outset.\n",
    "- Apply universal screening or monitoring guidelines across all patient groups to minimize variability in data arising from differential surveillance.\n",
    "\n",
    "\n",
    "When evaluating the data:\n",
    "- Use statistical methods to adjust analyses for different levels of surveillance among patient groups, such as stratification or multivariable models that include surveillance intensity as a covariate.\n",
    "- Take particular care when drawing collective conclusions on patients experiencing different degrees of surveillance.\n",
    "- Consult the data collectors to learn when and why they record specific values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing data bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing data bias refers to the distortion in analysis results caused by systematic absence of data points. [Rubin (1976)](https://academic.oup.com/biomet/article-abstract/63/3/581/270932) classified missing data into three categories:\n",
    "- Missing Completely at Random (MCAR) where the probability of a value being missing is the same for all cases\n",
    "- Missing at Random (MAR) where the probability of a value being missing is depends on other observed variables\n",
    "- Missing Not at Random (MNAR) where the probability of a value being missing depends on variables that are not observed\n",
    "\n",
    "Each type affects the data and subsequent analyses differently, with MCAR having the least impact since the missingness is unrelated to the study variables or outcomes, whereas MAR and NMAR can introduce significant bias in an analysis.\n",
    "For instance, if patients with more mild symptoms are less likely to have complete records (NMAR), analyses may overestimate the severity and impact of certain conditions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: MCAR and MAR of number of medications"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We showcase this bias on the Diabetes-130 dataset, where we introduce missing data in the `num_medications` variable\n",
    "1. According to an MCAR mechanism\n",
    "2. According to an MAR mechanism"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 101766 × 24\n",
       "    obs: 'time_in_hospital'\n",
       "    var: 'ehrapy_column_type'\n",
       "    layers: 'original'"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reload dataset\n",
    "adata = ep.dt.diabetes_130_fairlearn()\n",
    "ep.ad.move_to_obs(adata, [\"time_in_hospital\"], copy_obs=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The original dataset does not contain missing values in this variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ep.pl.missing_values_matrix(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### MCAR\n",
    "We now introduce random missingness in the `num_medications` variable, causing 30% of the data to be missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create reproducible MCAR missing values\n",
    "rng = np.random.default_rng(2)\n",
    "mcar_mask = rng.choice([True, False], size=len(adata), p=[0.3, 0.7])\n",
    "# create a new AnnData with these missing values\n",
    "adata_mcar = adata.copy()\n",
    "adata_mcar.X[mcar_mask, adata_mcar.var_names == \"num_medications\"] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize the degree of missingness:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ep.pl.missing_values_matrix(adata_mcar)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that under the MCAR mechanism, the shape of the distribution, its mean and its variance here do not systematically deviate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distributions_plot(\n",
    "    [\"Complete\", \"MCAR\"],\n",
    "    [adata, adata_mcar],\n",
    "    \"num_medications\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Little's MCAR test](https://www.tandfonline.com/doi/abs/10.1080/01621459.1988.10478722) is a statistical test, with the null hypothesis being that the data is MCAR.\n",
    "Care is to be taken when interpreting such results, as the practical value of such statistical tests is still under discussion [van Buuren (2018)](https://stefvanbuuren.name/fimd/).\n",
    "We consider the relationship of two variables of interest in this example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pvalue of Little's MCAR test: 0.71\n"
     ]
    }
   ],
   "source": [
    "pvalue = ep.pp.mcar_test(\n",
    "    adata_mcar[:, adata_mcar.var_names.isin([\"num_medications\", \"time_in_hospital\"])]\n",
    ")\n",
    "print(f\"pvalue of Little's MCAR test: {pvalue:.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With a p-value of 0.71, we obtain no indication of the missingness in `Num. Medication` per stay with the observed data about the `time_in_hospital` being not MCAR: its important to note that this is not a prove of the data being MCAR. Rather, low p-values should spark attention in particular. See [Schouten 2021](https://journals.sagepub.com/doi/full/10.1177/0049124118799376) for more details."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### MAR\n",
    "\n",
    "We now introduce MNAR in the `num_medications` variable.\n",
    "We use `time_in_hospital` to have an impact on the probability of the `num_medications` variable by generating a synthetic example where the probability of the `num_medications` variable being missing is larger, the longer the `time_in_hospital` is.\n",
    "This simulates a situation where the medication sheet would get lost at one point during the patients stay, with longer stays making it more probable to have the sheet lost somewhen along the way."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scale the time_in_hospital variable\n",
    "continuous_values = np.array(\n",
    "    adata.obs[\"time_in_hospital\"] - np.mean(adata.obs[\"time_in_hospital\"])\n",
    ") / np.std(adata.obs[\"time_in_hospital\"])\n",
    "# small offset to steer the degree of missingness\n",
    "continuous_values *= 1.2\n",
    "continuous_values -= 0.6\n",
    "\n",
    "# Convert continuous values to probabilities using the logistic function\n",
    "probabilities = 1 / (1 + np.exp(-continuous_values))\n",
    "probabilities\n",
    "\n",
    "# Generate MAR mask based on probabilities\n",
    "rng = np.random.default_rng(2)\n",
    "mar_mask = rng.binomial(1, probabilities).astype(bool)\n",
    "\n",
    "adata_mar = adata.copy()\n",
    "adata_mar.X[mar_mask, adata_mar.var_names == \"num_medications\"] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize the degree of introduce missingness:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ep.pl.missing_values_matrix(adata_mar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distributions_plot(\n",
    "    [\"Complete\", \"MAR\"],\n",
    "    [adata, adata_mar],\n",
    "    \"num_medications\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that under the MAR mechanism, the shape of the distribution, its mean and its variance do systematically deviate from the complete case.\n",
    "This is different from the MCAR case.\n",
    "The mean droppped from 16.02 to 14.66. Also, the standard deviation changed form 8.13 to 7.14.\n",
    "\n",
    "Such a scenario illustrates that we do have interest in imputing missing data, in a meaningful way.\n",
    "\n",
    "We can again use Little's Test to evaluate the missing data behaviour between our two variables of interest, on our synthetic MAR data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pvalue of Little's MCAR test: 0.000\n"
     ]
    }
   ],
   "source": [
    "pvalue = ep.pp.mcar_test(\n",
    "    adata_mar[:, adata_mar.var_names.isin([\"num_medications\", \"time_in_hospital\"])]\n",
    ")\n",
    "print(f\"pvalue of Little's MCAR test: {pvalue:.3f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, the pvalue of (rounded) < 0.001 according to Little's Test should make us reject our Null Hypothesis being the data is MCAR with respect to these two variables: Indeed, we know by our constructed example that the data is missing according to an MAR mechanism between these two variables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "There is a lot of literature on missing data for a first dive into more details such as [van Buuren (2018)](https://stefvanbuuren.name/publication/vanbuuren-2018/), [Schouten 2021](https://journals.sagepub.com/doi/full/10.1177/0049124118799376).\n",
    "\n",
    "- Improve data collection processes to reduce the occurrence of missing data, including training for healthcare providers on the importance of complete data entry.\n",
    "- Preventing missing data is the most direct handle on problems caused by the missing data.\n",
    "- Determine the type of missing data (MCAR, MNAR, MAR) if possible.\n",
    "- Consider data augmentation strategies, such as linking EHR data with other databases (e.g., insurance claims, registries) to fill gaps.\n",
    "- Visualize missing data patterns to get an intuition of potential confounders and dependencies.\n",
    "\n",
    "Many algorithms require dense matrices without missing data.\n",
    "Therefore, a common task is imputing the missing data which can lead to further biases that are discussed next."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imputation bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Imputation bias, a specific form of algorithmic bias, occurs when the process used to estimate and fill in (impute) missing values introduces systematic differences between the imputed values and the true values.\n",
    "\n",
    "When the data is MCAR, mean, median, or mode imputation for continuous variables does not introduce systematic bias to these statistics of the overall distribution of this continuous variable.\n",
    "However, it commonly introduces an underestimation of the variance of the data.\n",
    "In the MAR case, mean imputation of continuous variables introduces bias into the overall distribution of the variable: both its location and variance can be significantly biased.\n",
    "\n",
    "See [van Buuren (2018)](https://stefvanbuuren.name/fimd/) for a detailed discussion."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We showcase this bias on the Diabetes-130 dataset, where we introduced missing data in the `num_medications` variable in the section before:\n",
    "\n",
    "1. According to an MCAR mechanism\n",
    "2. According to an MAR mechanism"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Mean Imputation in the MCAR case\n",
    "\n",
    "We start off by showcasing mean imputation's behaviour in the MCAR setting. We first perform a simple mean imputation on our `num_medications` variable, and consider the new distribution with a histogram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_mcar_mean_imputed = ep.pp.simple_impute(\n",
    "    adata_mcar, var_names=[\"num_medications\"], strategy=\"mean\", copy=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
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r1oy7d+9y7ty5FzLpsW7duhnSzM3NcXV1JSIiQp92/fp1wsPDqVSpEtOmTTO6L2tra65cuZLv+tOfz4JgrA7dZGU/P78MAb3uizm7Mfz81GtsKMFYvcePHwfg3r17Rucp3bhxA0i7cqZjx45cvXqVuLg4XnnlFaPvdd37Lif++usvVCoV7du3z1H+S5cuMXfuXP78809CQ0MzzLUIDg7O0X4yc+3aNeLi4mjSpIlBgKvTqlUrpk2bZvS9m9PXedWqVfHz82P9+vXcu3eP119/naZNm1K3bl0sLCxy3NZ3332XAwcOsGrVKubMmQOkBVvr16+ndOnSBsN2AE+fPuXbb79l69atXL9+nZiYGP1nPWR+7urXr5/jNkHa98fatWtZuXIl58+fJyIiwmBJjMyO8ZVXXkGtztgn0aJFCw4fPsy5c+cyBNPp6V7H58+fN/o6vn79OpD2On42mCloEqy8AAkJCYSHhwNQqlSpLPN+8803VKhQgRUrVjBr1ixmzZqFmZkZHTt25KuvvsLHxydXdbu5ueWpzZnNa9HtL7sx1uchKioKFxcXo29MMzMzSpYsycOHDzNsy2wujK63KSfr4OiON7Orp3TpkZGR2e6rIGR1TOmPRzfx88aNG0yZMiXT/eWkdym7+nNzPnPC2Je2ro6stiUnJxd6vbrzvmnTpizr0p133esru/ddTkRGRuLs7Gy0l+FZf/31F61atSIlJYXWrVvTpUsXHBwcUKvVBAQEsH37dv3E4rzKz3snp69zjUbDH3/8wdSpU9m8eTNjx44FwN7env79+zNz5swczWPq1q0bDg4O/PTTT8ycORONRsOuXbsIDw9n1KhRBj3UycnJtGrVipMnT1K9enXefPNNSpUqhbm5OZA2sT6zc5fbz+WPP/6YefPm4e7uTrt27fD09NT/fVeuXMm9e/eMlsvv57judfzjjz9mmS+3nx95IcHKC+Dv709KSgqurq7ZLqak0WgYNWoUo0aN4uHDh/j7+7NhwwY2bdrEpUuXuHTpktHuwMzkdXXLBw8eGE0PCwsDDD+0dZF7SkpKhvwF+eXt6OhIeHg4ycnJ+g8EnZSUFB4/fmy0B6Wg6oZ/j/9ZuquBTG19BF17unXrxpYtW154/Vm9NuDFBXcvmu68b9++nS5duuQ4f3bvu5xwcnLiyZMnxMfHZxuwTJs2jfj4eA4ePJihx3LmzJls3749x/Vm5kW9d5ydnfnmm2/45ptvuHnzJocPH2bx4sUsWLCAyMjIHE0it7a2plevXixdupQDBw7Qvn37TIeAtm/fzsmTJ3n33XczTCoPDQ3N8p+D3HwuP3z4kO+++47q1atz7NixDD3e69evz7Rsbj7HjdFtP3/+PDVq1Mhxm58HmbPynGm1WqZPnw5gMIs8J0qXLk337t35+eefadWqFbdu3eLixYv67RqN5rmtjnv27FliYmIypOsuT04/3qobD9ZdUppeZvMXdF34uWl/rVq10Gq1/Pnnnxm2/fnnn6Smpj63Wem64zV2eXZKSop+7De/9eflvGTF19cXJycn/vrrr3z3OORFVq+N6OhofTdycdOwYUOAbOcE6Pj6+mJjY0NAQIDR/3ZzswR6w4YNURSFX3/9Ndu8N2/exMXFxejQ6uHDh42Wye3nzksvvYSNjQ3nz583GpwePHgQyP97Jz0fHx8GDhzI4cOHsbOzy1XQpZsjs2rVKh49esTevXupUaNGhiuebt68CUD37t0z7COzc5cXt2/fRqvV0rZt2wyByv3797l9+3amZf39/Y0uTWDsc9yY3L6OnycJVp6jhw8f0rt3bw4dOkSZMmWYMGFClvkTExM5evRohvTk5GT9MFL6lSFLlCjBo0ePiI+PL9iGk9Y9OHXqVIO006dPs3btWhwdHenWrZs+XTf+umLFCoP/oIOCgjLsI33bgVxNSH3vvfcAGD9+vMGqnXFxcfrJlgMHDszx/nJDt97M+vXr+euvvwy2zZs3jzt37vDqq6/me76Ks7MzKpWqwCbqmpmZMWLECEJDQxk5cqTR10poaOhzmyBnb2+Pr68vR48eNagjNTWVjz/++Lm8dk3B66+/TsWKFfn+++/Zs2eP0TzHjx/Xv47Nzc15++23iYmJyTA3QPe+yyndZbeffPKJ0TkT6dPKlStHeHg4f//9t0GeZcuWZTppM7efOxYWFvpjmzRpksG2W7du8d1332Fubs4777yTo/0Zc+fOHaNf2hERESQmJuZoSEynSZMmVKpUie3bt7No0SKSk5ONrhOk6yV/NpC8ffu2fhiqIOjq8ff3NwgSY2NjGTx4cKa9lpA2/Ltw4UKDtO3bt3P48GF8fHyyvXR5wIABODk5MWXKFKMTmrVa7Qu7l5AMAxUQ3QeMVqvVL7fv7+9PUlIS9evXZ+3atdlezRMfH0/Tpk3x8fGhTp06lC1bloSEBA4cOMCVK1fo0qWLwVUKrVu35tSpU7Rv355mzZphaWlJzZo1ee211/J9PM2aNWPp0qWcOHGCJk2a6NdZ0Wq1LF682GC4pUGDBjRr1ow///yT+vXr06pVKx48eMDOnTtp166d0f+qW7duzdy5cxk8eDBvvPEG9vb2ODk5MXz48Ezb9NZbb7F9+3Z+/vlnqlWrRteuXVGpVGzbto07d+7w5ptv5uqqidyws7Nj+fLl9OzZk+bNm9OzZ0/KlCnDmTNn2L9/P25ubixevLhA6mnQoAFHjhzh7bffpnLlymg0Grp06ZLnbthJkyZx/vx5Fi1axM6dO2nVqhWenp48fPiQGzducPToUaZPn/7cJsj973//Y+DAgTRp0oSePXvq13hJTk6mZs2a+VrIzVSZm5uzZcsW2rVrR6dOnWjcuDF+fn7Y2NgQFBTEqVOnuH37NqGhofp/QGbMmMHvv//OvHnzOH36tH6dlY0bN9KxY0d27NiRo7rbtm3Lp59+yrRp06hSpYp+nZUHDx7g7+9Pw4YN9YsMjho1in379tG0aVP9uk6nT5/G39+fHj16sHnz5gz7z8vnzqxZszhy5AgLFizg1KlTtGzZUr/OSkxMDAsWLNCvUZQX58+fp3v37tSrV48qVarg4eHBo0eP2L59O8nJybkOHvr168ekSZP44osvMDMzM/q5oltz5Ouvv+bChQvUqlWLwMBAdu3aRadOnQrsHw43Nzd69+7Nhg0b8PPzo23btkRFRXHgwAGsrKzw8/PL9Aq49u3b88knn7B3715q1qypX2fFysqK5cuXG518m16JEiXYvHkz3bp1o2HDhrRu3Zpq1aqhUqkICgri+PHjPHnyxOgCeAXuhVwgXYzxz7XsuoeFhYVSokQJpXbt2sqgQYOUvXv3GlzLnt6zayQkJSUps2fPVtq3b694e3srlpaWSsmSJZUGDRooP/zwg5KYmGhQPjY2Vhk6dKji6empaDSaDNfnY2S9g/SyWmelf//+yuXLl5UuXbooTk5OirW1tdK4cWPl119/NbqviIgIZdCgQUqpUqUUCwsLpVq1asrixYuzXGfjq6++Unx9fRULCwsFMFi7wdj6EYqStmbC999/r9SpU0extrZWrK2tldq1aysLFiwwep6zOgfZrfVizMmTJ5WuXbsqJUuWVMzNzRVvb29l6NChSnBwcIa8eVlnRVEU5caNG0rnzp0VFxcXRaVSGaw1kd0+M1sDQ6vVKqtXr1ZatWqlODs7K+bm5oqHh4fSpEkTZfr06UpgYGCO2pbZ30VRFGXFihVG18VQFEVZunSpUrVqVcXCwkJxdXVVhgwZojx+/DjLdVaMHWN267Zk95rPSlbrBWV1bFm198GDB8rYsWOVatWqKdbW1oqtra3i4+OjvPHGG8qaNWsyrH8UGhqqDBgwQClZsqRiZWWl1KxZU1mxYkWmdWT199i9e7fSrl07xdnZWbGwsFC8vLyUrl27Kr///rtBvp07dyoNGjRQ7OzsFEdHR6VNmzbK4cOHMz3mvH7uREREKGPGjFF8fHwUCwsLxdHRUXn11VeVffv25eqcKkrG13lQUJAyfvx4pXHjxoqrq6tiYWGheHp6Ku3bt1f27NljdB9ZuXfvnqJWqxVA6dy5c6b5AgMDlbfeekvx8PBQrKyslKpVqyqzZ89WkpOTjZ6HrF5jipL56/vp06fKhAkT9Gv3eHl5KcOGDcvRe+jYsWNK69atFXt7e8XOzk5p06aNcvLkyQx1Z7de1gcffKD4+PgolpaWir29vfLSSy8pffv2VbZu3Zrp+SlIKkVJd52VEEIIIYSJkTkrQgghhDBpEqwIIYQQwqTJBFshRLG0bdu2HC29X65cuUzvCi2EMA0yZ0UIUSy9++67OVqivnnz5i/s8kshRN5IsCKEEEIIkyZzVoQQQghh0iRYEUIIIYRJk2BFCCGEECZNghUhhBBCmDQJVoQQQghh0iRYEUIIIYRJk2BFCCGEECZNghUhhBBCmDQJVoQQQghh0iRYEUIIIYRJk2BFCCGEECZNghUhhBBCmDQJVoQQQghh0iRYEUIIIYRJk2BFCCGEECZNghUhhBBCmDQJVoQQQghh0iRYEUIIIYRJk2BFCCGEECZNghUhhBBCmDQJVoQQQghh0iRYEUIIIYRJk2BFCCGEECbNrLAbUJRptVpCQkKwt7dHpVIVdnOEEEKIIkNRFGJiYvDw8ECtzrrvRIKVfAgJCcHb27uwmyGEEEIUWUFBQXh5eWWZR4KVfLC3twfSTrSDg0Mht0YIIYQoOqKjo/H29tZ/l2ZFgpV80A39ODg4SLAihBBC5EFOplHIBFshhBBCmDQJVoQQQghh0mQYSAiRrdTUVJKTkwu7GUKIIsbc3ByNRpPv/UiwIoTIlKIohIWFERkZWdhNEUIUUU5OTri5ueVriQ8JVoQQmdIFKqVLl8bGxkbWExJC5JiiKMTFxfHw4UMA3N3d87wvCVaEEEalpqbqA5USJUoUdnOEEEWQtbU1AA8fPqR06dJ5HhKSCbZCCKN0c1RsbGwKuSVCiKJM9xmSn3lvEqwIIbIkQz9CiPwoiM8QCVbEf8bu27v5PfD3wm6GEEKIXJI5K+I/ITYplgn+E1Cr1BztfRQbcxnaEEKIokJ6VsR/QmxyLFpFS4o2hesR1wu7OaKYK1euHNu2bSvsZghRbEiwIv4TElIS9L9fDb9aiC0Rz4u/vz8dOnTA2dkZJycnatasyZw5c0hKSirspmXpeQQ2CxYsoG7dulhaWtK1a1ejeXbs2IGfnx+2trZ4eHiwaNGiTPeXnJzM8OHDcXZ2xsXFhREjRpCSkgJAYmIigwcPpnz58tjb2+Pr68vy5csL7FiCg4Pp2rUrJUqUoGTJkvTq1YtHjx5lmj+7Yx8xYgTe3t44ODjg6enJqFGjTP41IiRYEf8RiamJ+t8lWCl+du3aRYcOHWjXrh03btwgMjKSjRs3cvnyZUJDQwu7eS+ch4cHn376KYMHDza6/ddff2XYsGHMmzeP6OhoLl26RIsWLTLd37Rp0/D39+fy5ctcunSJI0eOMGPGDABSUlJwd3fnt99+Izo6mpUrV/LJJ5+wf//+LNt46NChLOvU+eCDDwC4d+8ed+7cISEhgZEjR2aaP7tjHzZsGFevXiU6Oprz589z/vx55syZk207ROGSYEX8JySkSs9KcaUoCiNHjmTs2LGMGjWKkiVLAuDr68vKlSspW7YsDx48oFevXpQqVYoyZcowceJEfc8ApPVuzJw5k3r16mFra0uHDh0IDw9n2LBhODk5UalSJY4dO2aQf/r06dSuXRsHBwfatWtHSEiI0fbFxsYyfPhwypQpQ+nSpenXrx9RUVEA9OzZk8DAQPr06YOdnR1Dhw7NtkxOdO/ena5du+rPxbMmTZrEZ599RosWLdBoNDg7O+Pr65vp/pYvX86nn36Ku7s77u7uTJw4kWXLlgFga2vL1KlTqVixIiqVioYNG9KyZUv8/f1z3N6s3L59m169emFnZ4e9vT1vvvkmFy5cyDR/dsdepUoVbG1tgbTXjlqt5saNGwXSVvH8SLAi/hMSU/7tWbkRcYNkrdznJrcURSEuKeWFPRRFyVG7bty4wZ07d+jTp0+med566y3Mzc25c+cOR44cYdu2bRn+m964cSNbtmwhJCSEoKAgGjZsyKuvvsqTJ09466239IGEztKlS1m3bh1hYWG4ubnRt29fo3W/9957hIeH8/fff3Pnzh39kArApk2bKFOmDOvXryc2NlY/FJNVGYBZs2bRuXPnHJ2fZz19+pQzZ84QHBxM5cqVcXNzo2fPnpn2QEVERHD//n38/Pz0aX5+fgQGBhoNoBISEjh58iQ1atTIU/ue9fHHH7Np0yaioqKIjIxk/fr1vPbaa/na56xZs7Czs6N06dKcP3+eESNGFEhbxfNjclcDJSYm8tlnn7FmzRoiIiKoUaMG06ZNo02bNlmW27JlCxs3buTUqVOEhYXh7e1N586dmTRpEk5OThny79ixg8mTJ3P58mVKly7NgAEDmDRpEmZmJndKRAFI37OSpE3iTtQdKjtXLsQWFT3xyalU/WzfC6vv8tR22Fhk/37UzV/w9PQ0uj04OJg//viDsLAw7OzssLOzY+LEiUyePJkJEybo8/3f//0f3t7eAHTs2JEjR47QvXt3AN58802++OILkpKSsLCw0OfX9UbMmTMHNzc37t+/j5eXl0HbfvnlFx4/fqz/HJo6dSrVqlVj5cqVRlfzzEmZcePGZXteMhMREYGiKGzbto0DBw5QokQJhg4dSt++ffn994yX9sfGxgIYfI7qfo+JicHR0VGfrigKgwYNolKlSvpzl96wYcNYt24dkDZ8lJCQYLDfXbt20bRpU4MyTZo04ccff8TZ2RmARo0aMX78+Dwdu864ceMYN24cV65cYe3atbi5ueVrf+L5M7melXfffZevv/6at99+m2+//RaNRkPHjh2z7VIcMmQIV65coW/fvnz33Xe0b9+eBQsW0KhRI+Lj4w3y7t27l65du+Lk5MT8+fPp2rUr06ZNk+i6GEs/ZwXgWvi1QmqJKGi67v7g4GCj2+/fv4+VlRWurq76tAoVKnD//n2DfOm329jYZHiuu8+JTtmyZQ3KWlpaZmjD3bt30Wq1lC9fHicnJ5ycnKhXrx5qtZqwsDCj7c1Lmdyws7MDYOTIkZQtWxY7OzumTJnCwYMHefr0aab50/ei6H63t7fXpymKwrBhw7h27Rrbtm1Drc749bJw4UIiIyOJjIzUBya655GRkRkCFa1WS5s2bWjSpAmxsbHExsbSpEkT2rZtm+/zAGlDQjVr1uTdd98tkP2J58ekuhFOnjzJhg0bmDt3LqNHjwagX79+VK9enTFjxhiMGT9r8+bNGSZr1alTh/79+7N27VoGDRqkTx89ejQ1atRg//79+p4UBwcHZsyYwYcffpjl2K0omtJfDQRwJfwKr1XMX1fyf421uYbLU9u90PpyonLlypQrV44NGzYwceLEDNu9vLxISEjgwYMH+gDk7t27Bj0geXHv3j397w8fPiQxMTFD7463tzdqtZqQkJBMb1vw7Jd6Tsrkh5OTE2XKlDG6zdjQm7OzM15eXgQEBFCxYkUAAgIC8Pb21veqKIrCBx98wIkTJ/j9998NelvyIzw8nHv37jFy5Ej9uRgxYgRz587l8ePHmc5LyY3k5GSZs1IEmFTPyubNm9FoNAwZMkSfZmVlxcCBAzl+/DhBQUGZljU2q7xbt24AXLlyRZ92+fJlLl++zJAhQwyGfIYNG4aiKGzevLkAjkSYmvTDQCCTbPNCpVJhY2H2wh45XaJbpVIxf/58Zs2axfz583ny5AkA169fZ+DAgaSkpNCyZUtGjx7N06dPCQwMZPr06fTv3z9f52Px4sVcu3aN+Ph4xo4dS7NmzTIEQG5ubnTt2pXhw4fz+PFjIO1O1lu3btXncXV15datW7kqkx3dEEtKSgparZaEhASDy3OHDBnC/PnzCQ4OJj4+nqlTp9K6dWt9L8qzBgwYwPTp0wkLCyMsLIwZM2YY/AM4fPhwjh49yoEDB/TDNdlp0aIFhw4dyjJPyZIl8fHx4fvvvychIYGEhAS+//57vLy8Mg1Usjr22NhYVqxYQWRkJIqicOHCBaZNm0a7di8uCBd5Y1LByrlz56hcuTIODg4G6fXr1wfSovnc0HWZpn9Rnzt3DoC6desa5PXw8MDLy0u/3ZjExESio6MNHqJo0E2wLedQDkgLVnI6gVOYvs6dO7N37152795NxYoVcXJyokePHvj6+uLu7s66deuIj4+nbNmyNGnShE6dOjFmzJh81fnee+/Rp08fXF1dCQ4OZu3atUbzrVy5Uj+U4+DgwCuvvMKZM2f02ydMmMCCBQtwcnJi2LBhOSozY8YMOnTokGnbpk2bhrW1NdOnT2fnzp1YW1sbDJ2MGzeO1q1bU7NmTby9vYmLi2PNmjX67UOHDjWYUDxp0iQaNWpElSpVqFKlCk2aNNHP97l37x4LFy7k2rVr+mGl9Fc2pTd06FD9dmOPI0eOZCizfft2zp49i6enJ+7u7pw8eZIdO3Zk2tasjl2lUrFu3ToqVqyIvb09r7/+Op06dWLevHmZnkthIhQTUq1aNaVVq1YZ0i9duqQAyqJFi3K1v4EDByoajUa5fv26Pm3u3LkKoAQGBmbIX69ePaVhw4aZ7u/zzz9XgAyPqKioXLVLvHg//v2jUn1ldWXsn2OVGqtqKNVXVlcexT0q7GaZtPj4eOXy5ctKfHx8YTfF5JQtW1bZunVrYTdDiCIhs8+SqKioHH+HmlTPSnx8PJaWlhnSrays9Ntzat26dSxbtoxPPvmESpUqGdQBZFpPVnWMHz+eqKgo/SOrYSlhWnQTbO3M7bDS/PN6Ssn560kIIUThMakJttbW1iQmJmZIT0hI0G/PiSNHjjBw4EDatWvH9OnTM9QBZFpPVnVYWloaDXKE6dMNA1lprLDQWBCXEkdSqiyxLYQQRYFJBSvu7u5GLz/ULVbk4eGR7T7Onz9Ply5dqF69Ops3b86wboq7u7t+n7o1FdLXo5sfI4oX3QRbSzNLLNRp62RIsCLy6u7du4XdBCH+U0xqGMjPz4/r169nmLh64sQJ/fas3Lp1i/bt21O6dGn27NljdGa7bh+nT582SA8JCcmwSqMoPnTDQLqelfRpQgghTJtJBSs9evQgNTWVJUuW6NMSExNZsWIFDRo00PeEBAYGcvWq4aWnYWFhtG3bFrVazb59+yhVqpTROqpVq4avry9LliwhNTVVn/7DDz+gUqno0aPHczgyUdh066xYaiz1wYosuS+EEEWDSQ0DNWjQgJ49ezJ+/HgePnyIj48Pq1at4u7du/qbZkHaQnGHDx82uPS0ffv23L59mzFjxuDv72+w4q2rq6vBcv1z586lS5cutG3blt69e3Px4kUWLFjAoEGDqFKlyos5WPFC6YIVKzMrLDVp845kGEgIIYoGkwpWAFavXs2kSZMM7g20a9cumjVrlmW58+fPAxi91Xfz5s0NgpXOnTuzZcsWpkyZwogRIyhVqhQTJkzgs88+K9iDESZDN+RjqbHEXGNukCaEEMK0mVywYmVlxdy5c5k7d26meYyteqjkcoGvrl270rVr11y2ThRVRifYaqVnRQghigKTmrMixPOS/tJl3TBQcqrMWRFCiKJAghXxn6DvWZFhICGEKHIkWBH/CbrAxNrMWtZZEUKIIkaCFfGfoBsGstRYytVAxVCLFi1QqVT89ttvBulz585FpVIxatQofZq/vz8dOnTA2dkZJycnatasyZw5cwzuSgxpNypUqVQGd21PX5+lpSV2dna4uLjQvHnzDGs3ZWXBggXUrVsXS0vLTOfO7dixAz8/P2xtbfHw8GDRokWZ7i85OZnhw4fj7OyMi4sLI0aMICUlBUhb/mHw4MGUL18ee3t7fH19Wb58eY7bmhPBwcF07dqVEiVKULJkSXr16sWjR4+M5s3JsUParVF8fHxwcnIq0LaKokmCFfGfYDDBViMTbIujl156iRUrVhikrVixAl9fX/3zXbt20aFDB9q1a8eNGzeIjIxk48aNXL58Wb9SNkBMTAw///wzLi4uBssmpDd79mxiY2MJCwujQYMGdO/ePcdt9fDw4NNPP2Xw4MFGt//6668MGzaMefPmER0dzaVLl2jRokWm+5s2bRr+/v5cvnyZS5cuceTIEWbMmAFASkoK7u7u/Pbbb0RHR7Ny5Uo++eQT9u/fn207Dx06lGW9Oh988AGQdgfmO3fukJCQwMiRI43mze7YdT777DPKli2bbd3iv0GCFfGfYGwFW+lZKV569+7N3r17iYqKAv5d+bpBgwZA2hWDI0eOZOzYsYwaNYqSJUsC4Ovry8qVKw2+GDdu3IitrS2zZ89mzZo1JCdnPhnbwsKC/v37ExQUlGlvwrO6d+9O165d9W141qRJk/jss89o0aIFGo0GZ2dng6DrWcuXL+fTTz/F3d0dd3d3Jk6cqA+ybG1tmTp1KhUrVkSlUtGwYUNatmxpsBZVft2+fZtevXphZ2eHvb09b775JhcuXDCaN7tjBzhz5gy//vorY8eOLbA2iqJNghVR7GkVrcE6KzJnJY8UBZKevrhHLpcjcHJyon379qxfvx5I+wIfMGCAfvuNGze4c+cOffr0yXZfy5Yt4+2336Z37948ffqUnTt3Zpo3Pj6eZcuWUbJkSZydnQGYNWsWnTt3zlX7dZ4+fcqZM2cIDg6mcuXKuLm50bNnT4Oen/QiIiIy3CrEz8+PwMBAfeCWXkJCAidPnqRGjRp5ap8xH3/8MZs2bSIqKorIyEjWr1/Pa6+9lqd9paSkMHjwYL7//nssLCwKrI2iaDO5dVaEKGjpr/qxMrOSYaC8So6DGdnfTLTATAgBC9tcFRkwYACffvop/fv355dffuHixYuMGzcOQN/r4enpmeU+Ll++zF9//cWiRYuws7OjW7duLFu2LMMwz/jx45k8eTLR0dGULl2aLVu26G+cqqszLyIiIlAUhW3btnHgwAFKlCjB0KFD6du3L7///nuG/LGxsQAGczt0v8fExODo6KhPVxSFQYMGUalSpUyHrYYNG8a6deuAtMAhISHBYN+7du2iadOmBmWaNGnCjz/+qA/WGjVqxPjx43N97JA2z6hWrVo0a9bM6Jpa4r9JelZEsaebXAuG9waSnpXip3Xr1oSGhvLFF1/QqFEj3Nzc9Nt0ww7G7uye3rJly6hZsyY1a9YEoH///uzbty9DuZkzZxIZGUlQUBCenp78/fffBXIMuhuwjhw5krJly2JnZ8eUKVM4ePAgT58+zTR/+l4U3e/29vb6NEVRGDZsGNeuXWPbtm2o1cY//hcuXEhkZCSRkZH6wET3PDIyMkOgotVqadOmDU2aNCE2NpbY2FiaNGlC27Ztc33sN2/eZNGiRVkuCir+m6RnRRR7usm1ZiozzNRmctflvDK3SevteJH15ZJaraZ///5Mnz6dzZs3G2yrXLky5cqVY8OGDUycONFo+eTkZNasWUNsbKw+0FEUhdTUVFauXGm0nKenJz/++CPNmjWjW7dueHjkr/fJycmJMmXKGN1mbKVuZ2dnvLy8CAgIoGLFigAEBATg7e2t71VRFIUPPviAEydO8Pvvvxv0tuRXeHg49+7dY+TIkdjYpP3NRowYwdy5c3n8+HGWc1Oe5e/vz4MHD6hcuTKQ9veIiYmhZMmS7N69Wz//SPz3SM+KKPb081XM0i5Z1s1ZkRVsc0mlShuWeVEPlSpPzfzoo4/Yv39/hjkTKpWK+fPnM2vWLObPn8+TJ08AuH79OgMHDuTevXvs2LGD6Ohozp49S0BAAAEBAZw/f55JkyaxfPnyTG/rUbt2bVq0aKG/Aic7uuGVlJQUtFotCQkJBpdODxkyhPnz5xMcHEx8fDxTp06ldevW+l6UZw0YMIDp06cTFhZGWFgYM2bMYNCgQfrtw4cP5+jRoxw4cEA/VJMTLVq0yHYopmTJkvj4+PD999+TkJBAQkIC33//PV5eXkYDlayOvVevXty8eVN/7pcuXYq9vT0BAQHUqlUrx+0WxY8EK6LY091xWbe+ivSsFG8uLi68+uqrmJubZ9jWuXNn9u7dy+7du6lYsSJOTk706NEDX19f3N3dWbZsGX369MHX1xc3Nzf9Y+TIkYSEhHDw4MFM6504cSJLly4lKCiIGTNm0KFDh0zzTps2DWtra6ZPn87OnTuxtrY2GDYZN24crVu3pmbNmnh7exMXF8eaNWv024cOHcrQoUP1zydNmkSjRo2oUqUKVapUoUmTJkyYMAFIu5x44cKFXLt2TT+sZGdnZ1A+vaFDh+rzGHscOXIkQ5nt27dz9uxZPD09cXd35+TJk+zYscNoe7M6dhsbG7y8vPSPUqVKoVKp8PLyksm2/3EqJbd3ABR60dHRODo6EhUVhYODQ2E3R2Ti70d/8/aet/Gw9WBfj31su7mNSUcn0dSzKT+8+kNhN89kJSQkcOfOHcqXL4+VlVVhN0cIUURl9lmSm+9Q6VkRxZ5+jRWztDeJ3MhQCCGKFglWRLEXnxIPpBsGUsswkBBCFCUSrIhi79meFd1dl2WdFSGEKBokWBHF3rMTbOVGhkIIUbRIsCKKvfT3BQJkUTghhChiJFgRxV6GdVZkuX0hhChSJFgRxV6GdVbkRoZCCFGkSLAiij0ZBhJCiKJNghVR7OnuDaQbBpIJtkIIUbRIsCKKPd1dl3U9K+bqfy9dlgWchRDC9EmwIoo9fc/KM/cGAkjWyiq2Qghh6iRYEcWeboLts8vtg6xiK16cDRs20KtXr8JuRo5Vq1aNXbt2FXYz8mzbtm2UK1dO/7xt27b89ttvhdcgkS8SrIhi79kJtrphIJB5K8VFixYtUKlUGb6M5s6di0qlYtSoUfo0f39/OnTogLOzM05OTtSsWZM5c+aQlGT4WnjvvfdQqVRcuXLFaH2WlpbY2dnh4uJC8+bNOX36dKbt02q1TJgwgUmTJuXvQF+gS5cu0blz50Kpu1y5cmzbtq1A9zlx4kT+97//5arMggULqFu3LpaWlnTt2tVonh07duDn54etrS0eHh4sWrTIaL7k5GSGDx+Os7MzLi4ujBgxgpSUFAASExMZPHgw5cuXx97eHl9fX5YvX56rtuZETtsaHBxM165dKVGiBCVLlqRXr148evRIvz0n56WgSbAiir1nJ9iqVCr95csyDFR8vPTSS6xYscIgbcWKFfj6+uqf79q1iw4dOtCuXTtu3LhBZGQkGzdu5PLly4SGhurzxcTE8PPPP+Pi4sKyZcuM1jd79mxiY2MJCwujQYMGdO/ePdO27dmzBxcXF15++eV8HqXIq2bNmhEZGcnRo0dzXMbDw4NPP/2UwYMHG93+66+/MmzYMObNm0d0dDSXLl2iRYsWRvNOmzYNf39/Ll++zKVLlzhy5AgzZswAICUlBXd3d3777Teio6NZuXIln3zyCfv378+2jYcOHcq0zry29YMPPgDg3r173Llzh4SEBEaOHKnfnt15eR4kWBHF3rMTbOHfeSsyDJRziqIQlxz3wh65nfzcu3dv9u7dS1RUFAAnTpwAoEGDBvr2jxw5krFjxzJq1ChKliwJgK+vLytXrqRs2bL6fW3cuBFbW1tmz57NmjVrSE7OPKi1sLCgf//+BAUFGfz3md6OHTto1aqVQVq5cuWYOXMm9erVw9bWlg4dOhAeHs6wYcNwcnKiUqVKHDt2TJ8/NjaW4cOHU6ZMGUqXLk2/fv30xwrw9ddfU6lSJezt7alYsSILFizIUN+cOXNo2LAh9vb2NG/enKCgoEyPK33vRm7bWq5cOaZPn07t2rVxcHCgXbt2hISE6LerVCoCAgL0z+fNm6f/4uzZsyeBgYH06dMHOzs7hg4dmqPjv3//Pm3btsXBwYE6depw+fJlg+NRqVS0atWKHTt2ZHrMz+revTtdu3bVv1aeNWnSJD777DNatGiBRqPB2dnZIDhOb/ny5Xz66ae4u7vj7u7OxIkT9YGwra0tU6dOpWLFiqhUKho2bEjLli3x9/fPcVuzk5u23r59m169emFnZ4e9vT1vvvkmFy5c0G/P7rw8DxKsiGJPv4JturkqstZK7sWnxNNgXYMX9tDdLTunnJycaN++PevXrwfSvhwGDBig337jxg3u3LlDnz59st3XsmXLePvtt+nduzdPnz5l586dmZ+X+HiWLVtGyZIlcXZ2NponICDA6BfDxo0b2bJlCyEhIQQFBdGwYUNeffVVnjx5wltvvaX/ooa0Yanw8HD+/vtv7ty5ox9W0Clbtix//PEH0dHRLF26lP/9738ZehF++ukn1q9fz6NHj7C1tc3VsFRu2gqwdOlS1q1bR1hYGG5ubvTt2zdH9WzatIkyZcqwfv16YmNj9UMV2R3/W2+9hbu7O2FhYaxdu5Yff/wxw76rVq2qD5JmzZqVr2Gup0+fcubMGYKDg6lcuTJubm707NnToIdOJyIigvv37+Pn56dP8/PzIzAw0CDg0klISODkyZPUqFEjz+3La1sBPv74YzZt2kRUVBSRkZGsX7+e1157rUDaklcSrIhi79lhIJAl94urAQMGsGLFCuLj4/nll19455139Nt0vR6enp5Z7uPy5cv89ddf9O/fHzs7O7p162Z0KGj8+PE4OTlha2vLunXr2LJlC2ZmZkb3GRERgYODQ4b0//u//8Pb2xtHR0c6duxIiRIl6N69OxqNhjfffJOLFy+SlJTEo0eP+OWXX/j+++/1dU6dOpWNGzeSmpoKwBtvvIG3tzcqlYqWLVvSrl07Dh06ZFDfsGHDKF++PFZWVrz99tucOXMmy3ORl7amz+/r64uNjQ1z5szh4MGD3L9/P8f1pZfd8QcFBXHkyBHmzp2LjY0Nvr6+GYInAAcHByIiIgAYN25cviYQR0REoCgK27Zt48CBA9y8eRNLS0ujQVlsbCyQFlDr6H6PiYkxyKsoCoMGDaJSpUqZDi3qerScnJzo3Lkz/v7++udOTk4ZemRy01aAJk2a8PDhQ/38moiICMaPH5/TU/NcGH9nCVGMGB0GkiX3c83azJoTb514ofXlVuvWrRk4cCBffPEFjRo1ws3NTb9N12UdHBxMxYoVM93HsmXLqFmzJjVr1gSgf//+tG/fnuDgYINAZ+bMmYwaNYrg4GC6dOnC33//zSuvvGJ0n87OzkRHR2dId3V11f9uY2OT4bmiKMTFxXH37l20Wi3ly5c3KK9WqwkLC8PT05O1a9fy1Vdf6fPGxcVlyJ/+fNja2mb4osxKTttqYZH23ko/rObq6oqlpSXBwcF4eXnluE6d7I4/JCQEKysrSpcurd+Wvn6d6OjoTHu/csvOzg6AkSNH6uuaMmUKlSpV4unTp9ja2mbIGxUVpX8d6npU7O3t9fkURWHYsGFcu3aN3377DbXaeH/CwoULWbhwIZA2Z2Xy5MkZAtO8tlWr1dKmTRt69erFgQMHAJg8eTJt27blr7/+yuHZKXgSrIhiT39vIGM9KxKs5JhKpcLG3Kawm5EltVpN//79mT59Ops3bzbYVrlyZcqVK8eGDRuYOHGi0fLJycmsWbOG2NhY/Re7oiikpqaycuVKo+U8PT358ccfadasGd26dcPDwyNDHj8/P65evZrn4/L29katVhMSEoKNTca/QWBgIP379+fXX3+lRYsWmJmZ0bVr10Jd9PDevXv63x8+fEhiYqI+2LO1tSUuLk6//dnhiGe/pLM7fq1WS0JCAg8fPtQHLIGBgRnyXb582WAoJj+cnJwoU6aM0W3PnndnZ2e8vLwICAjQB8oBAQH6nipdmQ8++IATJ07w+++/69NfdFvDw8O5d+8eI0eO1J/rESNGMHfuXB4/fvxC56mkJ8NAotjTDQPJBNv/ho8++oj9+/dnGGNXqVTMnz+fWbNmMX/+fJ48eQLA9evXGThwIPfu3WPHjh1ER0dz9uxZAgICCAgI4Pz580yaNInly5dn+uVfu3ZtWrRoob+641mvvfYaBw8ezPMxubm50bVrV4YPH87jx48BCAsLY+vWrUDaMIOiKJQuXRq1Ws2ePXtydCXJ87R48WKuXbtGfHw8Y8eOpVmzZvpeldq1a7NmzRpSUlIICAhgzZo1BmVdXV25deuW/nl2x+/t7U2TJk0YN24c8fHxXLt2jcWLF2do08GDB3M1TyUlJYWEhARSUlL0AVH6oa4hQ4Ywf/58goODiY+PZ+rUqbRu3Vrfk5HegAEDmD59OmFhYYSFhTFjxgwGDRqk3z58+HCOHj3KgQMHctX706JFiyx7VXLb1pIlS+Lj48P3339PQkICCQkJfP/993h5eekDlezOy/MgwYoo9oxOsNVdupwqly4XNy4uLrz66quYm5tn2Na5c2f27t3L7t27qVixIk5OTvTo0QNfX1/c3d1ZtmwZffr0wdfXFzc3N/1j5MiRhISEZBlwTJw4kaVLlxq9wqZjx448fvyYixcv5vm4Vq5ciZOTE/Xq1cPBwYFXXnlFP+ekatWqTJw4kVatWlGiRAk2btxIly5d8lxXQXjvvffo06cPrq6uBAcHs3btWv22+fPnc/z4cZycnBg7diz9+/c3KDthwgQWLFiAk5MTw4YNA7I+foB169YRFBRE6dKleeutt3jvvfcM9nnkyBF9OYAZM2bQoUOHLI9h2rRpWFtbM336dHbu3Im1tTVt27bVbx83bhytW7emZs2aeHt7ExcXZxB4DR06VD93ZtKkSTRq1IgqVapQpUoVmjRpwoQJE4C0XqiFCxdy7do1ypYti52dncGVUM8aOnSoPo+xx5EjRzKUyU1bt2/fztmzZ/H09MTd3Z2TJ08aXEWV3Xl5HlSK3Bwlz6Kjo3F0dCQqKsro5DlR+BRFocbqtBn1B3sdpKR12n8Gg/YN4kTYCeY0m0OH8ll/YP1XJSQkcOfOHf2ETJE/69evZ9u2bWzcuLGwm/LclStXjnnz5r2wBcNyol27dowePZo2bdoUdlP+czL7LMnNd6jMWRHFWvphnvTDQOYa8wzbhXie+vTpk6PLpsXzsW/fvsJugsgHGQYSxVr6YMRggq1cDSSEEEWG9KyIYk13JZBGpTG4J5Bu/ooEK0IUvLt37xZ2E0QxIz0rolgzNrkW/h0GkkXhhBDC9EmwIoo1/eq1zwQrss6KEEIUHRKsiGJNd2myLjjRkWEgIYQoOiRYEcWabpjn2WBFJtjmnKxuIITIj4L4DJFgRRRrumBEF5zoyI0Ms6dbVC39suhCCJFbus8QYws15pRcDSSKNX2w8mzPisxZyZZGo8HJyYmHDx8CaTerU6lUhdwqIURRobu55cOHD3FyckKj0eR5XxKsiGJNF4zorv7RkWGgnNHdzE8XsAghRG45OTkZ3PE7LyRYEcWafs5KJsNAsoJt1lQqFe7u7pQuXZrkZLmPkhAid8zNzfPVo6JjcsFKYmIin332GWvWrCEiIoIaNWowbdq0bO/ncO3aNRYtWsSJEyc4e/YsiYmJ3Llzh3LlymXIW65cOYPbl+u8//77LFq0qKAORZiAbIeBZM5Kjmg0mgL5wBFCiLwwuWDl3XffZfPmzYwaNYpKlSqxcuVKOnbsyMGDB2natGmm5Y4fP853331H1apVqVKlCgEBAVnW4+fnxyeffGKQVrly5YI4BGFCsutZkbsuCyGE6TOpYOXkyZNs2LCBuXPnMnr0aAD69etH9erVGTNmDMeOHcu0bJcuXYiMjMTe3p4vv/wy22DF09OTvn37FmTzhQnKrmdFhoGEEML0mdSly5s3b0aj0TBkyBB9mpWVFQMHDuT48eMEBQVlWtbFxQV7e/tc1ZeUlMTTp0/z3F5h+jJbFE4/wVaGgYQQwuSZVLBy7tw5KleujIODg0F6/fr1AbLtLcmNP/74AxsbG+zs7ChXrhzffvttge1bmI7MFoWTFWyFEKLoMKlhoNDQUNzd3TOk69JCQkIKpJ4aNWrQtGlTXnrpJZ48ecLKlSsZNWoUISEhzJ49O9NyiYmJJCb+O2wQHR1dIO0Rz4/+0mX1M5cuyzorQghRZJhUsBIfH4+lpWWGdCsrK/32grBjxw6D5wMGDKBDhw58/fXXjBgxAi8vL6PlZs6cyZQpUwqkDeLFyKxnRRe8SLAihBCmz6SGgaytrQ16LnQSEhL0258HlUrFRx99REpKCocOHco03/jx44mKitI/sppDI0yDfs6KWoaBhBCiqDKpnhV3d3eCg4MzpIeGhgLg4eHx3Or29vYGIDw8PNM8lpaWRnt+hOmSdVaEEKLoM6meFT8/P65fv55hLsiJEyf025+X27dvA1CqVKnnVod48eSuy0IIUfSZVLDSo0cPUlNTWbJkiT4tMTGRFStW0KBBA33vR2BgIFevXs1THeHh4aSmphqkJScnM2vWLCwsLGjZsmXeD0CYHJlgK4QQRZ9JDQM1aNCAnj17Mn78eB4+fIiPjw+rVq3i7t27LFu2TJ+vX79+HD58GEVR9GlRUVHMnz8fgKNHjwKwYMECnJyccHJyYvjw4UDa5Npp06bRo0cPypcvT3h4OOvWrePixYvMmDEj3zdbEqYlu2GgFCWFVG0qGrUsJS+EEKbKpIIVgNWrVzNp0iSDewPt2rWLZs2aZVkuIiKCSZMmGaR99dVXAJQtW1YfrLz88stUrVqVn376iUePHmFhYYGfnx8///wzPXv2fD4HJQpNZsvt6ybY6vJYq5/P5G0hhBD5Z3LBipWVFXPnzmXu3LmZ5jF2xU65cuUMeloyU6dOnQyXLoviK7OeFXONuUEeazMJVoQQwlSZ1JwVIQpaZsGKmcoMFSoAkrVyM0MhhDBlEqyIYk0XiDw7DKRSqfRDQXIzQyGEMG0SrIhiLbOeFfh3KEiuCBJCCNMmwYoo1jJbZwVkFVshhCgqJFgRxVpm66yALAwnhBBFhQQroljT3xvISM+KLLkvhBBFgwQroljLbJ0V+DdYkQm2Qghh2iRYEcVaVhNsdQGMrvdFCCGEaZJgRRRrWU2wlWEgIYQoGiRYEcWWVtGSok0BMplgK8NAQghRJEiwIoqt9Ff5pL8XkI4uWJFhICGEMG0SrIhiK/3wTlbrrEjPihBCmDYJVkSxlb5nxdgwkC5N1lkRQgjTlq9gpUOHDqxbt474+PiCao8QBUY3vGOuNkelUmXYLhNshRCiaMhXsHL79m369u2Lq6sr/fv357fffkNRlIJqmxD5ktWVQCDL7QshRFGRr2Dl2rVrnDhxggEDBrB//37atWuHl5cX//vf/wgICCigJgqRN/o1VowsCAcyDCSEEEVFvues1KtXj2+//Zbg4GD27NlDq1atWLx4MXXq1KF69erMmTOH+/fvF0RbhcgVXc+K7u7Kz5JhICGEKBoKbIKtWq2mXbt2rFmzhsDAQHr06MHly5cZN24c5cqV49VXX2X37t0FVZ0Q2dLfFyiTnhUZBhJCiKKhQK8G8vf3Z+jQofj4+LBp0yZ9z8pXX33Fo0eP6NKlC5999llBVilEprJaaj99ugQrQghh2szyu4PLly/z008/sX79egIDAyldujT9+/fnnXfewc/PT5/vww8/ZMiQIXz//fdMnTo1v9UKka3sJtjqelxknRUhhDBt+QpW/Pz8uHDhApaWlrz++ussXLiQdu3aoVYb77Bp2bIlS5cuzU+VQuRYdhNs9SvYamUFWyGEMGX5ClacnJxYsmQJPXv2xMHBIdv8r7/+Onfu3MlPlULkWLY9KzIMJIQQRUK+gpXVq1dTqlQprK2tjW6Pj4/n0aNHlClTBgAbGxvKli2bnyqFyDH9BNtsghUZBhJCCNOWrwm25cuXZ+vWrZlu37FjB+XLl89PFULkmS4IyXQYSC09K0IIURTkK1jJbrXa5OTkTOevCPG86YKQ7NZZkTkrQghh2nI9DBQdHU1kZKT++ZMnTwgMDMyQLzIykg0bNuDu7p6vBgqRV7ogRIaBhBCiaMt1sPLNN9/oLz1WqVSMGjWKUaNGGc2rKArTpk3LVwOFyKtsrwaSYSAhhCgSch2stG3bFjs7OxRFYcyYMfTp04fatWsb5FGpVNja2lKnTh3q1q1bYI0VIjfkRoZCCFE85DpYadSoEY0aNQLg6dOndO/enZdffrnAGyZEfunnrKjl3kBCCFGU5evS5c8//7yg2iFEgctuuX3dxFvpWRFCCNOWq2Bl6tSpqFQqJk6ciFqtztGy+SqVikmTJuW5gULkVXYTbGUYSAghioZcBSuTJ09GpVIxduxYLCwsmDx5crZlJFgRhSXHE2y1SSiKgkqlemFtE0IIkXO5Cla0Wm2Wz4UwJTldbl+raElRUjBXGZ/bIoQQonDJim2i2Mpuzkr6dN3S/EIIIUxPvibYGhMXF8eGDRtITEykY8eOci8gUWj09wbKZhgI0gIbG3ObF9IuIYQQuZOvYGXgwIGcOHGCixcvApCUlETDhg31zx0dHfnjjz+oVatW/lsqRC5lNwykUWswU5mRoqTIKrZCCGHC8jUMdPDgQbp3765/vm7dOi5evMjatWu5ePEibm5uTJkyJd+NFCIvdAFIZvcGSr9N1loRQgjTla9gJSwsjHLlyumfb9u2jbp169KnTx+qVq3K4MGDOXHiRH7bKESeZDcMBOluZihzVoQQwmTlK1ixtbXV39QwJSWFQ4cO0a5dO/12e3t7oqKi8tVAIfIqu2EgAEt12lorMgwkhBCmK19zVmrXrs2PP/5Iy5Yt2bFjBzExMbz22mv67bdu3cLV1TXfjRQiL7JbZwVkGEgIIYqCfAUr06dPp127dtStWxdFUejRowf169fXb9+6dStNmjTJdyOFyIvsLl1Ov01WsRVCCNOVr2Clbt26XL16lWPHjuHk5ETz5s312yIjIxk2bJhBmhAvkq63JKsJtrLkvhBCmL58r7NSqlQpXn/99QzpTk5OfPjhh/ndvRB5lqMJtmrpWRFCCFNXIIvCxcTEcO/ePSIiIlAUJcP2Zs2aFUQ1QuRKTibY6rYlamWCrRBCmKp8BStPnjxh+PDh/PLLL6SmpmbYrrs5nLFtQjxvut4S3VCPMXLpshBCmL58BSuDBw9m586djBw5kldeeQVnZ+eCapcQ+aIoCsnatADEXJ35nBUZBhJCCNOXr2Bl//79fPTRR8yZM6eg2iNEgdAFKpDDYSBZZ0UIIUxWvhaFs7GxMVjBtiAkJiYyduxYPDw8sLa2pkGDBhw4cCDbcteuXeOjjz6icePGWFlZoVKpuHv3bqb5d+zYQe3atbGysqJMmTJ8/vnnpKSkFOCRiMKUvqckJ8FK+uBGCCGEaclXsNK3b1+2bt1aUG0B4N133+Xrr7/m7bff5ttvv0Wj0dCxY0f8/f2zLHf8+HG+++47YmJiqFKlSpZ59+7dS9euXXFycmL+/Pl07dqVadOmMWLEiII8FFGI0i/yltUwkG4+i/SsCCGE6crXMFCPHj04fPgw7du3Z8iQIXh7e6PRaDLkq127do72d/LkSTZs2MDcuXMZPXo0AP369aN69eqMGTOGY8eOZVq2S5cuREZGYm9vz5dffklAQECmeUePHk2NGjXYv38/ZmZpp8DBwYEZM2bw4Ycf4uvrm6P2CtOl61kxU5uhVmUek+sCGZmzIoQQpitfwUrTpk31vxsbqsnt1UCbN29Go9EwZMgQfZqVlRUDBw5kwoQJBAUF4e3tbbSsi4tLjuq4fPkyly9f5vvvv9cHKgDDhg1j+vTpbN68mU8//TRH+xKmKydL7UO6FWxluX0hhDBZ+QpWVqxYUVDtAODcuXNUrlwZBwcHg3TdEv4BAQGZBiu5qQPSVt9Nz8PDAy8vL/12UbTlZKl9kBVshRCiKMhXsNK/f/+CagcAoaGhuLu7Z0jXpYWEhBRIHen3+Ww9WdWRmJhIYuK/cxuio6Pz3R7xfOgXhMumZ0V/I0MJVoQQwmTla4JteqGhoZw/f56nT5/meR/x8fFYWmZcwMvKykq/Pb90+8isnqzqmDlzJo6OjvpHfnt5xPOjCz6yui8Q/BvMyARbIYQwXfkOVrZv346vry9eXl7Url2bEydOAPD48WNq1aqVq6uFrK2tDXoudBISEvTb80u3j8zqyaqO8ePHExUVpX8EBQXluz3i+dBdipzTYSBZwVYIIUxXvoKVnTt30r17d0qWLMnnn39ucF+gkiVL4unpycqVK3O8P3d3d/0wTXq6NA8Pj/w0V19H+n0+W09WdVhaWuLg4GDwEKYpISUtwLXSWGWZTybYCiGE6ctXsDJ16lSaNWuGv78/H3zwQYbtjRo1ytWEVT8/P65fv55hLoiut8bPzy8/zTXYx+nTpw3SQ0JCuH//foHUIQpffEracJ61Wda9cbKCrRBCmL58BSsXL16kV69emW53dXXl4cOHOd5fjx49SE1NZcmSJfq0xMREVqxYQYMGDfRzRAIDA7l69Wqe2lytWjV8fX1ZsmSJwSXVP/zwAyqVih49euRpv8K06IMV82yCFbXcyFAIIUxdvq4GsrGxyXJC7e3btylRokSO99egQQN69uzJ+PHjefjwIT4+PqxatYq7d++ybNkyfb5+/fpx+PBhg2GnqKgo5s+fD8DRo0cBWLBgAU5OTjg5OTF8+HB93rlz59KlSxfatm1L7969uXjxIgsWLGDQoEHZrn4rigZdsGJjZpNlPhkGEkII05evYKVly5asWrWKUaNGZdgWFhbGjz/+SOfOnXO1z9WrVzNp0iTWrFlDREQENWrUYNeuXTRr1izLchEREUyaNMkg7auvvgKgbNmyBsFK586d2bJlC1OmTGHEiBGUKlWKCRMm8Nlnn+WqrcJ0xaXEATIMJIQQxUG+gpXp06fTsGFD6tWrR8+ePVGpVOzbt48//viDxYsXoygKn3/+ea72aWVlxdy5c5k7d26meQ4dOpQhrVy5cgY9Ldnp2rUrXbt2zVXbRNGR2zkrss6KEEKYrnzNWXnppZfw9/enRIkSTJo0CUVRmDt3LjNmzODll1/myJEjBX5XZiFyIj45h8NAaglWhBDC1OWrZwXSJqz+9ttvREREcPPmTbRaLRUqVKBUqVIF0T4h8iSnPSv65fZlzooQQpisPAcriYmJ/PTTT+zfv59bt24RExODvb09Pj4+tG/fnrfeegsLi6wX5BLiecnpnBVZbl8IIUxfnoKVCxcu8Prrr3Pv3j0URcHR0RE7OzsePnzI2bNn2bRpE9OnT2fHjh1ydY0oFLnuWZFgRQghTFau56zExsbSpUsXHjx4wPTp0wkKCiIiIsLg57Rp0wgJCeG1117L172ChMgr/aXL5jJnRQghirpcBysrVqwgMDCQ3bt3M27cODw9PQ22e3p6Mn78eHbu3MmdO3dytdy+EAUlpz0r+mEgbVKuriYTQgjx4uQ6WNm9ezdt27alRYsWWeZr1aoVbdq0YefOnXltmxB5FpecszkrumEg+Pfmh0IIIUxLroOVCxcuZBuo6LRq1YoLFy7ktgoh8i2366yADAUJIYSpynWwEh4ejpubW47yurq6Eh4enutGCZFfOZ2zYq421/8uq9gKIYRpynWwkpiYiLm5efYZATMzM5KS5L9V8eLltGdFrVLrAxYZBhJCCNOUp0uX7969y9mzZ7PNd+fOnbzsXoh8URQlx+usQNpQULI2WYaBhBDCROUpWJk0aVKGmwYaoygKKpUqL1UIkWdJ2iS0ihbIWbBiqbHkafJTGQYSQggTletgZcWKFc+jHUIUGN19gSBnwYpuGEiW3BdCCNOU62Clf//+z6MdQhQY3XwVC7UFZursX+Jy52UhhDBt+brrshCmSD9fxTz7XhWQJfeFEMLUSbAiip2cXgmkoxsGkjkrQghhmiRYEcWOfo0Vs6zXWNHRBTW6ckIIIUyLBCui2Mltz4qtuS3w7xL9QgghTIsEK6LYyel9gXR0wcrTZLlDuBBCmCIJVkSxk9eeFQlWhBDCNEmwIood3dVA2d0XSEeX72mKBCtCCGGKJFgRxY7MWRFCiOJFghVR7OR6zoqZDAMJIYQpk2BFFDu57VnRDwNJsCKEECZJghVR7OR2nRUZBhJCCNMmwYooduRqICGEKF4kWBHFTm7vDaQPVuRqICGEMEkSrIhiR+asCCFE8SLBiih2cj0MZCZzVoQQwpRJsCKKnTxPsE2JQ1GU59YuIYQQeSPBiih28npvIK2ilTsvCyGECZJgRRQ7uR0GsjazRoUK+HdyrhBCCNMhwYoodnI7DKRSqWSSrRBCmDAJVkSxolW0JKQkADm/dBlkyX0hhDBlEqyIYiUhJQGFtEmyOe1ZAbl8WQghTJkEK6JYST9B1srMKsflZMl9IYQwXRKsiGJFF6xYaaxQq3L+8pYl94UQwnRJsCKKFf3kWvOcDwGlzy9L7gshhOmRYEUUK/r7AuXwsmUdGQYSQgjTJcGKKFZyu8aKjlwNJIQQpsussBsgRHZStQoRcUlEPE3CylyDp5M1arXKaN745DwGKzJnRQghTJYEK8IkpaRq+fVSGBdOH8H63kEqaW9RVvWQWMy4r7Likd1LOL7UHL9mXXB0ctaXy+swkFy6LIQQpkuCFWFSFEVh57lAru1bQsf4nXRW3wMVoHkm49OLcPYXEs58wln7Rpi93IMqzd/gcfxjAEpYl8hVvXbmdmm7lWBFCCFMjgQrwmQ8iE5gw+qFdH64hC7qUFBDisqc2DKtcKjUBHWpl0hNTeHxozDCrx3FMew4HtpQasf+Ccf/JO74GC54VAZLcLMqlau6ZRhICCFMlwQrwiQc//sqsVs+5EP+AjXEmzmhbvYRlnX74WTjos+nAVwB1+aDULRabl08zoNj6ygXtg8PHpGSEgKWNrgcWciVMwGUbPoupV5uk239MgwkhBCmS4IVUeh+37sZv78+ooQqmhQ0RNcehku7sWBpn2U5lVpNxRpNqFijCSkpqZw58TvXr04C4iiXEk+VB7vgl11c2NeUMn3n4+hWIdN96S9dlrsuCyGEyZFLl0WhUbRaDq+aTPO/BlNCFU2IZQW0g37Hpcu0bAOVZ5mZaajTpC1P7dKW2A+q9jm/2XQgWdHwcqw/5osaceG3NZmWl2EgIYQwXSYXrCQmJjJ27Fg8PDywtramQYMGHDhwIEdlg4OD6dWrF05OTjg4OPD6669z+/btDPlUKpXRx6xZswr6cEQmFG0qZ5e8T/M732Cm0nK5VEfcPzmKhVetPO8zISWB8IRwALq0eYtXx2zgZve9XNBUxYYEXvYfzrm1k0BRMpTV3fRQghUhhDA9JjcM9O6777J582ZGjRpFpUqVWLlyJR07duTgwYM0bdo003KxsbG0bNmSqKgoJkyYgLm5Od988w3NmzcnICCAEiUMrw5p06YN/fr1M0irVSvvX5QiF1JTuPxDX+o83gvAX5U+puFbn4HK+NopORX2NAxICzwcLBwAqFKzAQm+h/Bf8n80ffILtW58x+klj6gzeCEq9b+xuqxgK4QQpsukgpWTJ0+yYcMG5s6dy+jRowHo168f1atXZ8yYMRw7dizTsgsXLuTGjRucPHmSevXqAdChQweqV6/OV199xYwZMwzyV65cmb59+z6/gxHGaVO5+WNfqj3eS4qi5tjLX9Csx/AC2XXo01AA3G3dUaULfKwsLWkyfBkH11Sg5e251A1dz8nlVtQfNE+fRxesJKQmkKJNwUxtUm8NIYT4TzOpYaDNmzej0WgYMmSIPs3KyoqBAwdy/PhxgoKCsixbr149faAC4OvrS+vWrfn555+NlomPjychIaHgDkBkTVG4u2oIPmF7SVY07Kv+ZYEFKvBvz4qbnVuGbSqVipb9PuX4S+MAqH9/BadWjddv1wUrIJNshRDC1JhUsHLu3DkqV66Mg4ODQXr9+vUBCAgIMFpOq9Xy999/U7du3Qzb6tevz61bt4iJiTFIX7lyJba2tlhbW1O1alXWrVtXMAchMhW4aQzl7m0mVVGxreIUOvZ4r0D3rwtW3G3dM83TqM94jlYYBUC9Ows5s34KABYaC31vigwFCSGEaTGpYCU0NBR394xfNLq0kJAQo+XCw8NJTEzMcdnGjRszffp0tm3bxg8//IBGo+Htt9/mhx9+yLJ9iYmJREdHGzxEzgQe+IEyl5cAsMF9DG/0HW4wVFMQ0g8DZaVJvykc8XofgDrXviZg82xArggSQghTZVID8/Hx8VhaWmZIt7Ky0m/PrByQ47JHjx41yPPee+9Rp04dJkyYwLvvvou1tfH7ysycOZMpU6bk4EhEeo//3ofH0QkAbHHoS89B4zK9EWF+6IIVN9uMw0DPajpwNn8uTqBZ2Cr8Ls7gbwtrbM1siUqMkmBFCCFMjEn1rFhbW5OYmJghXTevJLMgQpeel7IAFhYWDB8+nMjISM6cOZNpvvHjxxMVFaV/ZDWHRqRJeHwP862DMEPLHxYtaTtsHhZmz+dll5NhIB2VSkXTwfP4s8SbAFQ/8xmahLTXjwQrQghhWkwqWHF3dyc0NDRDui7Nw8PDaDkXFxcsLS3zVFbH29sbSBtSyoylpSUODg4GD5E5JSWRB8t646hEc5nyVBq0HDsr8+dTl6LkqmcFQK1R02TYIo44dUWtUnB+mjZUKHNWhBDCtJhUsOLn58f169czzAU5ceKEfrsxarWal19+mdOnT2fYduLECSpUqIC9fdYrouoWjytVKnc3wBOZu7n2E8rGXyZSsSW+6wq8S7tkXyiPIhMjSUxNRIUKVxvXHJfTaNQ0Gr6Mo/btsdNqAbh58Y/n1UwhhBB5YFLBSo8ePUhNTWXJkiX6tMTERFasWEGDBg30vR+BgYFcvXo1Q9lTp04ZBCzXrl3jjz/+oGfPnvq0R48eZag3JiaGefPmUbJkSerUqVPQh/WfFHZ+P5XupC1v7199GnX8nu+Ce7pelZLWJbHQWOSqrJmZGfVG/ESqKi1QVV37iZvHtxd4G4UQQuSNSU2wbdCgAT179mT8+PE8fPgQHx8fVq1axd27d1m2bJk+X79+/Th8+DBKumXThw0bxo8//kinTp0YPXo05ubmfP3117i6uvLJJ5/o833//fds27aN1157jTJlyhAaGsry5csJDAxkzZo1WFjk7otOZJQSF4Vqe9r6KQesO9LhjQHPvc6cXgmUGQsLc2rU7cOJSz8SYqHGc98gbptbUaFuu4JsphBCiDwwqWAFYPXq1UyaNIk1a9YQERFBjRo12LVrF82aNcuynL29PYcOHeKjjz5i2rRpaLVaWrRowTfffGMwtNOkSROOHTvG0qVLefLkCba2ttSvX5/ly5fTqlWr5314/wk31n5MFe0D7iulqPrut2iew5U/z7oecR0AV9ucDwE9q7xzeQAuWThjTTiuu/oRaL6RMjVbFEQThRBC5JFKUYzc1U3kSHR0NI6OjkRFRclk2388unqUUhs6AvB7g2W07tDjudcZnRRNxy0diUqMYlqTabzu83qe9nP+0Xn67ulLaevSfHUjGb/k88RgQ0SPXyhTvXEBt1oIIf7bcvMdalJzVkQRp9USu/UjAA5ZtaZluzdeSLUrLq4gKjGKio4V6Vyhc573U8a+DAAP4x/iPvRnLppVw544HDb3JPDyyYJqrhBCiFwyuWEgUXRd3vsDVROvEatY4/3m3Hwv/JasTeZ02GkCHgZwLeIaIbEhpCqpmKvN8XXxxdfFF3O1OT9d/gmAkbVHolFr8lyfk6UT9ub2xCTHEKOOxXPYTq5+3wHf1Gtof36DwD7bKfNS7XwdkxBCiNyTYEUUiOS4KNxOpy1bf6LMIFqXr5in/WgVLSfDTrLj5g4OBR0iJjnGaL5LTy4ZPPcr5UdL75Z5qlNHpVLh7eDN5SeXCYwJxKeMDwzbzY2F7aiUegvt+m4Evb0D70o181WPEEKI3JFgRRSIS7/MxE+JIhA36vUen32BZ8Qlx7Ht5jZWX15NcGywPt3FyoXGHo2pWqIqZezLYK4x52nyUy49vsTtqNska5MxU5sxstbIArnXUFn7slx+cpmgmLTViZ1LlIL/28Pthe2ooL3Lw7VdCXpnN94Vq+a7LiGEEDkjwYrIt+gnYfjcWgnA3Rof0czWNsdlU7Qp/HL9FxaeX0h4Qtrqwfbm9nQo34HOFTtTo2QNo0M7bcq2KZC2P8vb4Z+1fKID9WnOJd1Q3t/NvcXtKasNInRNF4L67ca7wkvPpQ1CCCEMSbAi8u3q5inUJ56b6vI07jIox+XOPjjL1ONTuRV1CwBPO0/erfYur/u8jrVZ5vdyep50k2wDYwIN0l1cvVDe30PQ4vZ4a4O5v/o17g/YjVfZSoXRTCGE+E+RYEXky+OQ29QM2QQqiG48HjOz7F9ScclxzDs7jw1XN6Cg4GjpyLCaw+j5Uk/M1c/n3kE5VcYhLVjRDQOlV8K1DAzaQ8iP7fBSwri3sgv3B+zBq0z5F91MIYT4T5FLl0W+3P3lMyxVyVwyr06tVj2zzX878jZv73mb9VfXo6DQzacbu7vt5q0qbxV6oALgbZ82DBT6NJSk1KQM20t4lMNi0C4eqEpRVglBu6IjIYG3XnQzhRDiP0WCFZFnobcu4Pd4NwDaVp+hUmf9ctp/dz+9d/fmZuRNSlqXZHGbxUxtMhVHS8cX0dwcKWFVAhszG7SK1mCib3olPSuhGZAWsJT5J2AJDbzxglsqhBD/HRKsiDwL2zYJM5WWc1YNeLlR5vfQURSFxecX88nhT4hPiaeBWwM2vbaJxh6mtyqsSqXKcihIp2QZXzTv7SFE5YqXEoayohNh9669qGYKIcR/igQrIk/uXjhGrZiDaBUVth2mZJovISWBsUfGsiBgAQB9q/RlcZvFlLQu+aKammu6oaDbkbezzFfSuzLmg/YSrHLDQ3kAKzvx4N7VLMsIIYTIPQlWRJ7E7vkMgFP2ralcs5HRPI/jH/PevvfYe2cvZiozPmv0GWPrj83XKrMvQu3SaavU/nLjF7SKNsu8pTwrYj7oVwJVHrgpj1Ct7MjDu5eyLCOEECJ3JFgRuXbjxF6qx58iWdHg+vpko3nCnobRf29/Ljy+gIOFA4vbLKZn5ewn4JqCbpW6YW9hz93ouxwMPJht/tKe5bEc/Ct3VV6UVp6gXtWJR3cuvoCWCiHEf4MEKyJXFK0W5be0YZ9TLq9RrtLLGfKExoYy4NcBBMYE4mnnybpO66jvXv9FNzXPbM1t6f1SbwCWX1xOTm5M7upRFqvBe7mtKkNJJQLN6k48uh3wnFsqhBD/DRKsiFz5+/f1VE6+QrxiQfkeGeeqRCVGMeTAEO7H3sfLzovl7ZZT1qFsIbQ0f96q8hYWagv+fvw3p8JO5aiMm0cZrIfs5YaqHC5KJGarXyP02pnn3FIhhCj+JFgROZaSlECJY9MACPDsg7tnOYPtydpkPjn8CXej7+Jm68aK9ivwsPMohJbmX0nrknT16QrA//78H9fCc3alj7u7F7bv7+WauiLORGO9/nUCL//1HFsqhBDFnwQrIscCtn6FlxLCExyp9ubkDNvnnprLidATWJtZs6DVAtxs3V58IwvQyNojqeJShfCEcN7b9x4BDwNyVM7DzQOXoXu5qqmMEzE4/vwGd/72f76NFUKIYkyCFZEjsZGPqHRlIQDXqozAwdHFYPvvgb+z/up6VKiY9cosXnIp+jf5c7R0ZGm7pdQoVYPopGgG/DqA5ReXZ3uFEECp0q64frCXK2a+OBJLiS09uX4m+8m6QgghMpJgReTI9Y2f4kgst1RlqdttlMG2h3EPmXxsMgDvVn+XVmVavfgGPicOFg4sabOEduXakaKk8M2Zb3j/wPs8inuUbVlnl5J4jtjLZfPqOBCHx44+XPpr/wtotRBCFC8SrIhsPbpzkZdDNgEQ3vQzLCz+vYePVtHyqf+nRCZGUsWlCiP8RhRWM58bW3Nb5jaby5TGU7A2s+av0L/osbMHf97/M9uyDo4ulB25h0sWNbBTxVNu7zsEHNn5AlothBDFhwQrIlsPt4zBXJXKGYv61G31hsG21ZdWczz0OFYaK2Y1m4W5pvBvRvg8qFQqulfqzoZOG3jJ+SXCE8L54PcPmHxsMk+Tn2ZZ1tbekYqj9nDRqg62qgR8fxvAmd82vKCWCyFE0SfBisjS9b92Uy3mKCmKGstOM1CpVPptl55c4ttz3wIwtv5YKjhWKKxmvjAVnCqwttNa3qn6DipU/HLjF97Y8Ua2lzdb2dhTedQuzts2wUqVTI0jwzi568cX1GohhCjaJFgRmUpJSsBq/1gA/nLpSvWa9fTb4pLjGPvnWFK0KbQp24Y3Kr2R2W6KHUuNJWPqjWFZu2V42nkSHBvMe/veY/bJ2SSkJGRazsLKhmofbuWMw6uYq1Kpe+p//LF2bo4WnRNCiP8yCVZEpgI2fkEZbRDhOFD1rZkG22acmMG96Hu42brxeaPPDXpc/ivqudXjly6/6AO1n678RM+dPbnw6EKmZcwsLKn14c+cKdUNtUqh1Y1p7Fv4CQlJKS+q2UIIUeRIsCKMenTvKtVvLgbgao1xuJT6d82UvXf2sv3WdtQqNbNemYWjpWNhNbPQ2ZrbMrnxZBa2Xkgp61Lcjb7LO3vfYf65+SSnJhsto9ZoqDNsBRfLDwCg/aNlnPrydYLCHr/IpgshRJEhwYrISFF4tHE4Vqpkzpv70fD1/9Nvuhd9j6nHpwIwpMYQ6rjWKaxWmpRXvF5h6+tb6Vi+I6lKKkv+XkKf3X0yX/lWpaJ6/3ncaDCDZMx4Jcmf5B+ase/ArzIsJIQQz5BgRWRw+bdVVI07RaJihm23b1Fr0l4msUmxjPxjJLHJsdQuXZv3a7xfyC01LY6WjsxuNpuvmn+Fk6UT1yKu0Xt3b5ZeWEqK1vgwT6UOHxDVawtP1CWooAqmpf9b/PLNh9x/FPGCWy+EEKZLghVhID46HNd/Fnj7y/NdfKr6AWnrqYw/Mp7bUbcpbVOar1p8hZnarPAaasLalmvL1te30sK7BSnaFL49+y39f+3P3ai7RvOXrNocp49PcadUKyxUqfSIXkXSgsYc2L0JrVZ6WYQQQoIVYeDC6k8ooURwDw/qvD1Vn/59wPccun8IC7UF37X8jpLWJQuxlaavpHVJvmv5HdOaTMPO3I6/H/1Nz509WXtlrdHl+jV2JSg/bAsP2iwgUu1EBVUIbU4N4vDsbly6fqMQjkAIIUyHBCtC78KRndR/vAWAqFazsbO1BWD/3f0s+XsJAJMbT6ZayWqF1saiRKVS8brP62zpsoUG7g1ISE1g1slZDNk/hJDYEGMFcG3yDvajA7ji1QutoqJl4kG81jZj65IpPImOe/EHIYQQJkCCFQFAVGQ4JX//CICTJV6nRrMuAFwNv8qnRz8FoF/VfrxW8bVCa2NR5W7nzpI2S5jQYALWZtacCDtB9x3d2Xpjq9HJtBobZ6oM+pHIvnsJsqqMoyqObiFfE/J1U/bu2UZKavY3UhRCiOJEpcilB3kWHR2No6MjUVFRODg4FHZz8uWvb96iYdRuQlSuOH18Aht7Z8KehvH27rd5GP+QRu6NWPjqQpmnkk/3ou/xqf+nBDwKAKCFVws+b/x55sNq2lQC931LyRNzsCEegMPmr2DT8Qvq+vn9J9e3EUIUD7n5DpWeFcGZX1fRMGo3WkVFbPtvsbF3JiYphv/77f94GP8QHycfvmzxpQQqBaCsQ1lWtl/JR3U+wlxtzqH7h+i6vStbb2w1fsWQWkOZDh9j+XEAN7y6o0VF8+Qj1Nj2Kju/HMTZKzdf/EEIIcQLJj0r+VAcelYe37+JxdJmOPCUkx7vUH/IApK1yQz7bRh/hf5FKetSrO24Fnc798JuarFzPeI6E/0ncjX8KgDlHMoxuMZg2pdrj4XGwmiZqDtnebJlNBVizgAQp1jyp31HPDv+j5erylwiIUTRkZvvUAlW8qGoByspyUncmNuSKkkXuaapTPkx/phbWDDp6CS239qOtZk1q9qvokqJKoXd1GIrOTWZtVfWsuziMiITIwFwsXLhjUpv0OulXrjZumUspCg8ObeDhAPT8Iy/nrYfRcNRm1bYtBpNvboNZHhICGHyJFh5QYp6sHJiyQgahKwmVrHmyTu/UaZiNb49+y3LLi5Do9LwXavvaObVrLCb+Z8QmxTLhmsb2HB1Aw/iHgCgUWloVaYVb/m+RR3XOhkDEEXh4bk9xPw+l4pPzwGgVVQct2hEapNRNGnWFo1aghYhhGmSYOUFKcrByoXf1vGyf9oy+qfqfU3dju8x/9x8frzwIwCfNfqMnpV7FmYT/5NStCn8EfgH66+u5/SD0/r0ys6V6ePbh04VOmFtZp2h3KMr/oTvm81LkX/q006raxBVZzhN2ryBlYXMNxJCmBYJVl6QohqsBN44j9Pa9jgQx9FSvWg8bIlBoDKu/jjervJ2IbdSXAu/xvqr69l9ezcJqQkAOFg40L1Sd3q91Atve+8MZaLu/U3IrplUevQrZqRd4nxZVZGgqkNp3Lk/9taWL/QYhBAiMxKsvCBFMViJjnxE1LfN8FZCuGJelQqfHGTx5SUSqJiwqMQott3cxvqr6wmODdan1ypdi3bl2tHCuwWedp4GZeIf3eHOjllUDNqCJUkA3MGDqxUGULfL/1HKyf6FHoMQQjxLgpUXpKgFK0mJiVz/uh3VE88RSknM3j/ImuDNrLi0ApBAxdSlalPxD/Zn3dV1HA85jsK/b92KjhVp5tWMV7xewa+0H+ZqcwCSoh5wa9eXeN9Yix1PAQhTXDjn+TY1Or2Pp2fG3hkhhHgRJFh5QYpSsKJoUzn9bW/qRe3nqWJJYLctrInZw87bOwEJVIqaB08fsP/efn679xvnH50nVUnVb7M3t6exZ2NeLfsqzb2aY21mjTY+ipt751Py4lJctGl3dE5WNFyxb4h13Xeo2KQ7anMZIhJCvDgSrLwgRSVYUbRaTi8eSr0HG0lR1Jx55VuWK0c5FnIMjUrD5MaT6erTtbCbKfIoKjGKYyHH+PP+n/gH++svgQawMbOhdZnWdKzQkQbuDTBLTeHO78tQn1lJueR/b5AYhR13SjTHoVY3ytfvhMrCphCORAjxXyLBygtSFIIVRavlrx8/pFHoagD2vzyJZZanuPzkMtZm1nzV/Cte8XqlkFspCkqqNpULjy9wMOggv975lZCn/94w0dnSmbbl2tKxfEf8Svtx6+Jp7h9aTtXHv+KqitDni8eSmw4NwacN5Rp0wt61QmEcihCimJNg5QUx9WBFm5rKmcVDqPdwMwCbKg9mmeVFgmODcbZ05vvW3/NyqZcLuZXieVEUhfOPzrP79m7239tPeEK4fpu7rTuty7SmVulaVHGqRti5Uzw9v4PKEYfxUD022E+oxoMHJRti4dOccn4tsSlV9kUfihCiGJJg5QUx5WAlIS6GiwvfoW7sQVIVFfNe6s167WkSUxPxsvNiUZtFlHWQL53/ihRtCidCT7Dnzh5+u/cbcSlxBts97TypWaom1VxqYPsoFefrZyj94C98U69jpjK8y/NDdSkeOflhVrYBpao1w6V8bdCYv8jDEUIUAxKsvCCmGqwE3b5G0treVEy9zWOVGWMrNeNkctoN717xfIWZr8zE0dKxkFspCktCSgJ/3v+Tk2EnCXgYwI3IG2gVw4DE2syal0u+jLuFF7ZPnuL+4B41ntygZupdNCrDj4wELAi2qECsky8q95exL1sL98p1sLJzeoFHJYQoaiRYeUFMLVhRtFpObF9E1YAvsFfFsdG2BN+7uxGZGoNGpeH/av4fg2sMRq2Sm22Lf8UmxXLh8QUCHgVw/uF5zj86T2xyrNG8Ja1KUVpxoFRsCuVjwqkfH0SV1FhKpGp5dmH/+yo3wqwrEedcBY1bVZzLVse7YjXsbWXyrhCiiAcriYmJfPbZZ6xZs4aIiAhq1KjBtGnTaNOmTbZlg4OD+eijj9i/fz9arZaWLVvyzTffUKFCxgmCy5Yt48svv+TOnTt4e3szcuRIRowYkau2mlKwcvfWVR5u+oh6Ccc4Zm3F185uXLdM+2+5nEM5Zr4yk+olqxdqG0XRkKpN5XbUbS48vsDNyJvcirzFzcibPIx7mGkZc8wokWqBe1Iq5ZNiqJwSi0dKKh4pKbinpOCgTfuYSVY03Fe5EW7ljdbOHTMnDzSOHlg6e2Lj4oZjCXfsnUvL1UhC/AcU6WClT58+bN68mVGjRlGpUiVWrlzJqVOnOHjwIE2bNs20XGxsLLVr1yYqKopPPvkEc3NzvvnmGxRFISAggBIlSujzLl68mKFDh/LGG2/Qrl07jhw5wpo1a5g1axZjx47NcVtNIVh58vghFzbPwC/sJw7ZWbDe3p7LVhZAWlf+kBpDeKfqO1hqZA0NkT/RSdH6wEX3Myg6iLC4sAzDSM+y0YJHcjJeKcm4p6TinpqCQ6oWe60WO62S9lNJe26rVdAqlsSqHXhq5kSihTMpli4oNiVQ25bEzL4UZvYlsXIsjbWTK7bOrljZuYBaegyFKEqKbLBy8uRJGjRowNy5cxk9ejQACQkJVK9endKlS3Ps2LFMy86ZM4exY8dy8uRJ6tWrB8DVq1epXr06Y8aMYcaMGQDEx8fj7e1Nw4YN2bVrl75837592bZtG0FBQTg7O+eovYUZrIQFXufG3u+xffwLex3M2G1rS4wm7cPaSmNFj8o9GFB9AKVtSr/Qdon/nuTUZEKfhhIUE8T9mPsExQQR8jSE4NhgQmNDiUiMyH4nzzBTFBy0WpxStThpU3FM1eKs1eKYqsVBq8Va0WKlVbBWFKwUBQstpCg2aLElRW2PonYACxcszO0xs3BAY2WHmZUdaks7VBZ2qC2s0ZhbYmZuicYi7ae5pSVm5lZYWFhhYWmFuYUlFlbWaMws4Nk7Xgsh8q3IBitjxozh66+/Jjw83KDhM2fOZMKECQQGBuLtbXx58Pr16wNpAU967dq149atW9y8mTbBdM+ePXTq1Indu3fTsWNHfb7jx4/TuHFj1qxZQ9++fXPU3hcZrCTGPOH+jQBCLh8g+MEhHmpC+MPWmlsWFvo8XnZevFH5DbpX6o6LlctzbY8QORWXHEfo01BCYkMIfRpKcGwwD+IeEJMUQ2xSLDHJMcQkxfA06SmxybEGtxEoCGaKgrVWwUrRYvXP7+YoqBVQAxoUVApoABWgURQ0/5QzVxTMFFCjRqOoUClq1GhQoUH9zwPMQGWGCjMUlTmozFGrzEFlAWpzVCoL1CozzFRqNGozNCoNZioNGrUm7Xd12nO1WoNabYZGrUGt0WCmMUOtMsdMl67RoFaZodaY/ZPXPG0fajM0ajNUGnPUajVmags0GjNUGjM0KjPUGg0qtQZUalCpUKvN/vlVjUoFGrUate6h0v1UgVqNWkVamkqNSs0/P1WoUKFWq1GpVKj+2W8a1T+/P/NTgj1hRG6+Q03qvvHnzp2jcuXKGRqtC0QCAgKMBitarZa///6b9957L8O2+vXrs3//fmJiYrC3t+fcuXMA1K1b1yBfnTp1UKvVnDt3LtNgJTExkcTERP3zyMhIIG2uTHR0dM4PNCsHZ3L3yimU5AR+dEogRqMlBYVEtUKEWk20RpP2CatYQyxoSKGJZxM6VexM7dK1UavUxD2OI464bKsS4kWxxJLylKe8bXmwzTyfVtGSkJrA06SnRCdGE50cTVRiFDFJMUQnRROZEMnT5KckahNJTEkkPiWe+OR44pOeEp8cT6I2gWRtMolKMtp/gp4kMPJuUGXye06k/vMontSKwj9hxj/PQcW/aenCEnQXhqn+Odfq9NsVXX7l333ptitk2B8YT0u/7Z+iqHL1N1MZ/KYYTdXv+Jm6VKgyi51VoFJU+qI5b2PG9KxfjRlamu1e854vXV3pjrtXtDWuWg3lS9ph8cZCMC+YOWUxMTFA2nd4dkwqWAkNDcXd3T1Dui4tJCQkwzaA8PBwEhMTsy370ksvERoaikajoXRpw+ERCwsLSpQokWkdkNbDM2XKlAzpVatWzfygXoArXGUpywq1DUIIIYqn7emf/O+lAt9/aGgoTk5OWeYxqWAlPj4eS8uME0GtrKz02zMrB+SobHx8PBbphk6ezZtZHQDjx4/n448/1j9PTU1Fo9Fkml8IIYQQmQsODqZy5crZ5jOpYMXa2tpgmEUnISFBvz2zckCOylpbW5OUlGR0PwkJCZnWAWnBkLGASAghhBC5l9P5niZ1rZ+7uzuhoaEZ0nVpHh4eRsu5uLhgaWmZo7Lu7u6kpqby8KHhmhFJSUk8efIk0zqEEEIIUThMKljx8/Pj+vXrGSarnjhxQr/dGLVazcsvv8zp06czbDtx4gQVKlTA3t7eYB/P5j19+jRarTbTOoQQQghROEwqWOnRowepqaksWbJEn5aYmMiKFSto0KCB/kqgwMBArl69mqHsqVOnDIKQa9eu8ccff9CzZ099WqtWrXBxceGHH34wKP/DDz9gY2NDp06dnsehCSGEECKPTGqdFYBevXqxdetWPvroI3x8fFi1ahUnT57k999/p1mzZgC0aNGCw4cPk77pMTEx1KpVi5iYGEaPHo25uTlff/01qampBAQEUKpUKX3ehQsX8sEHH9CjRw/9CrarV69m+vTpTJgw4YUf83/VgwcPiIqKKuxm5IujoyOurq6F3QwhhCjWTC5YSUhIYNKkSfz000/6ewN98cUXtGvXTp/HWLACcP/+fYN7A7Vo0YJvvvkGHx+fDPX8+OOPfPXVV/p7Aw0fPpwPP/wQlSxe9EI8ePCAvu/0Izkp46ToosTcwpKf1qyWgEUIIZ4jkwtWxH/D9evXGTJkCPEVmqO1cnwudajjI7G+8yfx5ZuhtXYq+P0nRGF9+zBLlizJ0aV3Qggh8sakLl0WeZOQkEBgYCBlypTRrytTVGitHNHalny+dVg7Pfc6RNaK8mtUCFH4TGqCrcibwMBAhgwZQmBgYGE3RQij5DUqhMgPCVaEEEIIYdIkWBFCCCGESZM5K8XIvXv3CrsJOVaU2pqd4nQsz4uxc9SiRQv974cOHTL5tPzsq127diQmJmJra8vu3bsBaNu2LUlJSdjY2LBnzx4AOnfuTGxsLE5OTmzbtg2A3r17ExYWhre3N2vWrAHgtddeIyYmBmdnZ7Zu3QrAO++8Q1BQEBUrVmTZsrQbm37wwQdcunSJWrVq8c033wAwYsQILly4QJ06dfjqq68AGDhwILdu3aJKlSr6Nag+/fRT/P39ad26NZMmTQLg888/5/Dhw7Rt21a/zMM333zD9u3b6dWrF8OGDQNg+vTpHDhwgM6dOzN69GgANmzYwKJFixg5ciTdu3cHYM2aNSxbtoxhw4bRq1evTPP99ddfTJo0iZkzZ1K3bl0AduzYwddff824ceNo3749ADdu3GDChAnMnj2bChUqAHD27FkmTJjAnDlzqFGjRqZpz5aNjIxk1apVDBgwIMsl4R88eMDcuXMZO3aswRIZz0pISODo0aM0bdpUf9uWnNaRU8bqyE8+UyLBSjEyffr0wm7Cf5Kcd5Ed3X3Lnj59qk/T3aMsLi5OnxYbGwukfYnphIWFARAUFKRPi4mJASAiIkKfptt+69YtfdqlS5cAOHfunD7twoULAJw5c0afpitz5coVfZq/vz8Av//+uz5YOXz4MAD79+/XByvbt6fdk/fnn3/WBysHDhwAYNeuXfpgZdGiRQB89913+iBEF1QtXLhQH6wYyzdp0iTMzMwYP368ft9ff/01KpWKWbNm6YOVCRMmYGVlxdixY9m0aZM+zdzcnDFjxvDrr79mmZa+7KpVq7C1tWXFihV8+OGHZGbu3LnY2toye/Zsvvzyy0zzHT16FCsrK30ACOS4jpwyVkd+8pkSCVaKkYkTJ1K2bNnCbkaO3Lt3r9h8yRel815YitPfOy9sbW15+vQptra2+jQbGxvi4uKwsbHRpzk5OREZGYmTk5M+zdvbm6CgIP0K3gDOzs5ERETg7OysT6tYsSK3bt2iYsWK+rRatWpx7tw5atWqpU+rU6cOZ86coU6dOvq0KlWqcOXKFapUqaJPa926Nb///rvBl1nbtm3Zv38/bdu21af16tWLn3/+WR9sQFoP0a5du+jcubM+beTIkXz33XeMHDlSnzZs2DAWLlyoD3Iyyzdz5kzGjx/PzJkz9Wnjxo1j1qxZjBs3Tp82e/Zsxo4dy+zZs/Vpc+bMYcyYMcyZMyfLtGfLDhgwgBUrVjBgwACyoiszduzYLPM1bdoUf39/mjZtqk/LaR05ZayO/OQzJbLOSjGgW7OkKK33oWvz06pdnttlxeqnj7G9vOO51aHbf1E674WlKL5GhRCmQybYCiGEEMKkSbBSDJQpU4YlS5ZQpkyZwm6KEEbJa1QIkR8yZ6UYsLKykq51YdLkNSqEyA8JVkShUic8v7suq+MjDX4W+P6fY9uFEEL8S4IVUSgcHR0xt7CE24efe13Wd/58bvs2t7DE0fH53IhRCCFEGrkaqBgoN263/ve7szoVubT971UCoO3yG0UqLf1zUzqfkpZ1Wq1xu4kAnIFz/6TVHrebcMAFOPtP2mtTd3MhDl62gZ2fdaLP17s5/hAalYb1H6fl6TlnN6fCoZ4LbBqTlvb+0j3su6nQzkfF4kEdARjzsz8/n42iV21H5vRKu1x09MYjbD4XTY9aDnz55isATN56gp9OPKZvg5JM7tYAgEUHLrHI/y5Dm5ZjaJtqAEzddpI1fz3inYal+KxrfQCW/3GV7/1v8UHTirzXyheAzUfv8L3/TT5o6kOPJuUB2HLsrj6te+NyAPx0+IY+rW/ztNf7/tMhLD5xk/cb+NC2rgcAv50NZcmJmwxp4MOrtd0BOHb1MWtO3uSd+j409k276u7Q3w9YduImAxv40KKGKwCX70ez/Xwgr9csQ1WvtAXQLgRGseXcPbrXKsvLZRwzzRcWmcBfdx7RsHwp3JzSboR5MyyWvZfu06GaFz5udgBExSVz7UEUL7k64mhjDsCj6ETOBD6hTpkSlHKwzDTt2bJJKVoi4pJwtrHAwizz6Z3xSamERsXj7miNtYUm03ypWoX45FSszTVo1CqAHNeRU8bqyE8+UyITbEWhq1y5cob5DEUhTRRNEc/8BAh/5ifArbhnfj40/AlwK9zwJ8CtB4rBT4CbD2INfqZtjzX4CXDjQSwp//xMnxaZmDEt2Ui+J3GGaTefxHIvIombT9LVGx7L3fBEboUblg2N0RqUDYqN5XJoDEGx/6bdj43lUkg099OlPYiN5UxgNA/SpYXExvL3/WhC0qWFx8Zy/HY44enSnsTG8tedcJ5kky82IYHTdyOITUjQp0X+ky8yXb745GSuhMYQn5ysT3uamMi5wEie/rMwX2Zpz5ZN0Wp5FJNIilZLVpJSUwkKjyMpNTXLfFpF4WliCtp0/QM5rSOnjNWRn3ymRIIVIYQQQpg0CVaEEEIIYdIkWBFCCCGESZMJtkIIIYQwadKzIoQQQgiTJsGKEEIIIUyaBCtCCCGEMGkSrAghhBDCpMly+6LQPHr0iOjo6MJuRr44ODhQqlSpwm6GEEIUaxKsiELx6NEjRo4YTmJScvaZTZilhTnfzV8gAYsQQjxHEqyIQhEdHU1iUjJ9y4ThapX0XOp4kGDOT4Hu9C0TiqtVwQdFDxIs+CnQjejoaAlWhBDiOZJgRRQqV6skvG0Ss8+YrzqSn3sdQgghnh+ZYFsMJCYmcuvWLRIT5QtZmCZ5jQoh8kOClWLg/v37/O9//+P+/fuF3RQhjJLXqBAiPyRYEUIIIYRJkzkrxUhR+q+1KLU1O8XpWJ4XY+eoe/fu+t+3bNli8mk9e/YkNTUVKysr1q1bZ5BHrVazefNmAAYNGkR4eDiurq788MMPAIwePZrbt2/j6+vLjBkzAPi///s/Hjx4gJeXF9999x0AI0eO5P79+1SoUIEvv/wSgAkTJnD16lVq1KjB5MmTARg1ahSBgYH4+PgwZ86cTPMtXbqUPXv20K1bN9555x0AFi9ezL59++jSpQvvvvsuAFOnTiUgIID69eszbtw4ADZs2MDPP/9M37599cc5f/58Dh48SPv27RkyZAgA27ZtY/Xq1QwaNIiOHTtmWnbfvn0sXryY4cOH06pVKwD++usvvvzyS8aNG0fdunUBOHLkCPPmzWP06NE0atQIgDNnzjB79mwmTpxIzZo1M80XHR3Nxo0b6d27N/b29gAEBwczd+5cxo4di7u7OwDXrl1j+vTpTJo0iUqVKhnNZ2xfxuQ0X2JiIidPnqR+/fpYWlrmqmxOGasjP/lMiQQrxci3335b2E34T5Lz/t+QmpoKQEJCQoZtWq1W/3t4eDgADx480Kfdvn0bgKtXr+rTdNvTB3K633X505f5+++/9WmBgYEA3Lx5M8t8e/bsAWDr1q36YGXfvn0A7NixQx+sBAQEAHDy5El92Z9//hmAn376SR9wHDx4EIBff/1VH6ysXr0aSAuMdMGKsbKLFy9GpVKxYMECfbDy5ZdfotFomDVrlj7YmzdvHmq1mi+//JJffvkFgNmzZ2NmZsb06dP1+zaWb+PGjdjY2LBhwwYGDx4MwNy5c7G2tmb27NnMmzcPgOnTp2NhYcEXX3yhb/+z+Yzty5ic5jt58iSWlpacPHmSV155JVdlc8pYHfnJZ0okWClGPvzwQ7y8vAq7GTly//79YvMlX5TOe2EpDn9vKysrEhISsLKy0qep1Wq0Wi1q9b8j6q6urjx48ABXV1d9mq+vL1evXsXX11ef5uXlxf379w1eOxUqVOD27dtUqFBBn1ajRg3+/vtvatSooU/z8fHh5s2b+Pj4ZJmvW7dubN26lW7duunTunTpwo4dO+jSpYs+rX79+vr/tHX69u3LTz/9RN++ffVp7du359dff6V9+/b6tEGDBrF06VIGDRqUZdnhw4ezYMEChg8frk8bN24cs2bN0vfmQFov1Jdffsno0aP1aRMnTmT69OlMnDgxy3y9e/dmw4YN9O7dW582duxYZs+ezdixY/VpkyZN4osvvmDSpEmZ5jO2L2Nyms/YOc5p2ZwyVkd+8pkSlaIoSmE3QuTPrVu3+N///sfcuXOpWLFiYTcnR3Rt/qRy4HO7rDgozpKvrpd5bnXo9l+UznthKYqvUSGE6ZAJtkIIIYQwaRKsCCGEEMKkSbBSDHh5eTF37lyZNyFMlrxGhRD5IRNsiwFLS8siOw/gQYLFc9y3ucHPgt//82t7cVOUX6NCiMInwYooFA4ODlhamPNToNtzr+unQPfntm9LC3McHBye2/6FEELI1UDFw2THdL9HFZm0J0AkwDtn09LW1MapKKX987xEHo9f0vKT5gXEAPYw+Z91Sib7AI+AUjD5n/VHZraGxNNgWRfG/56WtqArPD4IJVvC8G1paV93hOij4NAEPk5bm4TFPSF0P7i3hfc3wS8j4cIqeLk/vJG2iBvrB8K1zfBSD+izLC3tty/h2LfQ+EN49Z/Lao+vhmNfQuPR0KhfWtrhhf+mNR+Wlua/9N+0pv9cCnxyw79p9f+5xPXo8n/TmryXeb7rx+Hcj1BrMFROWziNq/5wdjHUfh98m6alnd0Gf82DhqOgdte0tLsB8PdqqNEPyvmlpV38A87+ALX/D6qnrZXC/ctwcQNU7w1eVTMvG3YTrm4F327g9s8l1+HBcPt3qNAaXDzT0h4Hws1fwac9lCyTlhYZBvf+hLLNwMkt83wpSRD3BGxKgNk/PZ8JsRB+E1x8wMouLS02HELPgnttsHMxns/YvozJaT5tKiTHgbkNqDW5K5tTxurITz4TIj0rotCU+OfBM8MDRTFNvGgxz/yEtEAl/U8g8brhT4DH1w1/AkRfN/wJ8Oj6Mz+vGP40lke3XRv9TL5rEHMv7Wf6fIlPnsl35f/bu/eoquq0geNf5H55hXBMQF+8C4EysmI0WV6mxmVSScyYIlI64X1Mbc2yRS4MZ4HkcoY1Tk2ppJNUr42ULa1Vg5P2trwlIAUjRoKJgB4CKW4vl8Ph8nv/QHadOQcvI8Lm+HzWYm189rP3/u39ePQ5++x9NjR/Zx774VuoK+ma/jSvyXDzvBYDXMmCwMd+ErsKV3Pggcd/jNWXQnVh11TLq4TSUzB+jvmyhlx44CffSNxyDUpPwNhHgKAbLPs9XD4BI2cA15uVllooO93VNHC9WWmp6Vp2+BTgehNirIPyLBgWAvj0nNfZDo1V4OIJXP/Pv93YVZ/BI4DrzYqpEQx5MGQC4G09z9q6rLnVPNUJrY3g4ALY396yt8raNu4kT0fkAlshhBBC6Jo0K0IIIYTQNWlWhBBCCKFr0qwIIYQQQtfkbiAhhBBC6JqcWRFCCCGErkmzIoQQQghdk2ZFCCGEELomzYoQQgghdE2+wVboXlVVFXV1dXd1G15eXgwbNuyubkMIIcR/RpoVoWtVVVXEPh2LqdV0V7fj5OzE/v/ZLw2LEELokDQrQtfq6uowtZronNKJGtwLd9k3gH2OPR1TOuD6w5LtGuww5Zioq6uTZkUIIXRImhVhwWg0UlZWxsiRI3Fxcenv4QB0NSr39eIKB6OtT6GPrxrS43EXQgg9kAtshYWysjJWrFhBWVlZfw/lniLHXQghrJNmRQghhBC6Js2KEEIIIXRNrlmxATNnztR+P3HixB3Huunh44i+HEN/76+17fd2bSX2n8dmz56NyWTC3d2dzMxMsxxHR0c+++wzAObPn091dTV+fn4cOHAAgBUrVlBUVERISAivvfYaADExMRgMBsaMGUN6ejoAS5cu5fLlywQGBvLGG28AsHbtWgoKCggLC+PPf/4zAM8++yyXLl0iKCiI3bt395j317/+lffff5/Y2FhWrVoFwI4dOzh06BDR0dGsXbsWgBdeeIHs7GxmzpzJ1q1bAdi3bx/79u1j1apVxMbGArBt2zYyMzOJiori97//PQAHDhxg586dbNiwgfnz5/e47EcffURqaiqbNm0iIiJCO65btmwhJSWF8PBwAI4dO0ZycjJJSUnMmjULgKysLBISEti+fTthYWE95tXV1ZGenk5cXByDB3ddQV9eXk5iYiJbt25lxIgRAJw/f54XX3yR1NRUAgMDreZZW5c1t5pnNBo5deoUM2bMwNnZ+baWvVXWtnEneXoizYroUfc/WveKe21/xe0xmbpun29qarKY19bWpv1eXV0NQEVFhRYrKioC4Ny5c1rMYDAAUFJSosUuX74MwIULF7RYQUEBALm5uVrs0qVLABQWFt4w7/333wdg//79WrNy6NAhADIyMrRmJTs7GzB/w7Jv3z4A0tLStIaju0k7fPiw1qzs3LkTgFdeecWsWfn3ZVNTU7Gzs2Pbtm1as7Jlyxbs7e1JSEjg888/ByA5ORl7e3sSExM5fvw4AAkJCTg4OBAfH681hdby0tPTcXd358033+T5558HIDExETc3NzZv3qw1hS+++CJOTk5s3LiRjz/+2GqetXVZc6t5p06dwsXFhZMnTzJ79uzbWvZWWdvGneTpiTQrokebN29m5MiR/TqGsrKyPmsi+nt/+3Jfxe1zd3enqakJd3d3Lebo6EhbWxuOjo5azM/Pj4qKCvz8/LRYSEgI586dIyQkRIuNGTOGkpISxowZo8UCAwO5cOGC9m4fICwsjNzcXO2MAkBQUBCFhYUEBQXdMC82Npb9+/drDQNAdHQ0GRkZREdHa7GZM2dy4sQJs7NJq1atIi0tTWtyAKKiojh8+DBRUVFabMOGDbzyyits2LDhhstu2rSJbdu2sWnTJi2WkpJCQkICKSkpWiwpKYnExESSkpK02Pbt24mPj2f79u03zIuLi+PNN98kLi5Oi23dupXNmzebvbZSU1PZuHEjqampPeZZW5c1t5o3Y8YMTp48yYwZM2572VtlbRt3kqcndkopfdy3KXSjqKiIFStWsGfPHgICAnQxlo7ZHb1z63It2B+zN1/f9Vh/76+ejrsQQuiJXGArhBBCCF2TZkVYGDlyJHv27On3j4DuNXLchRDCOrlmRVhwcXGRjyH6gRx3IYSwTpoVMSDYNdj1ztfiN/zb9Pq6hRBC6Jc0K0LXvLy8cHJ2wpTTu09dts+xN/uzk7MTXl5evboNIYQQvUPuBrIBk96apP1esLTAZmMHHzoIwFNZT9212O2MTw/H5F6NTX5rMh10YI89+UvzAXjorYdoogl33MlamgVA9FvRFFJIEEFkLM0AYPn+5WS3ZzPVYSp7Y/cCsOStJeSRRyihvL30bQDWvLeGUy2nmO46nV0Ld/HS/77E4SuHifrvKJIfSQYg/kg8/6j6B48Ne4ztc7tuq9355U7ePv82SyYu4XcP/g6AgxcOsudfe1jx8xU8Fdj19y39XDp/+9ffWPbzZfw25LcAvPv1u1re4uDFAHx08SMtFjk+EoADhQe02KKgRT3m5VbmklGYQXRQNGE+Xbc053yXw9+//jsxwTFM8Z0CwKeXP2Xvv/ay/OfLmTN6DgDnqs/xYdGHPBnwJCFDu265/sLwBe8UvMMzk54hfHjXl7gV/lBI5reZRIyLIGhIUI/Lflv7LZ+VfsavRv2KcfeNA8DQYCCrIouH/B5i+ODhAJTXl3Pq6immj5iOv6c/AJX/V0luVS5hw8Lw+S+fHvNM7SbqTHV4OXnh5OAEQKOxkfLGcvw9/PFw8QCgpqmGwtpCgu4Lwtvd22qetXVZc6t5HZ0dGDuMuNi7YD/I/raWvVXWtnEneXoiF9iKASMgIMDimo7ejomBoYMOsylAE01mU4ASSsymACXtJWbTHvNaSsyntebTnmKXay/TRBOXay+bxSqMFRaxus46i9j3bd9bxMqbyi1i10zXbppX3VBNXnUe1Q3VWuxa/TXyv8/nWv01LVZeW86l+kuU15ZrsZqmGnKv5VLTVKPFKmsrKagpoLK2UovVtdRxtuosdS11N1y2obWBnKocGlp//Ay2qb2JL6u/pKn9x5o1tjWSey2XxrZGLdbc0UxedR7NHc03zGunne9bvqeddi1mwkRJQwkmfjw7a1RGvv7ha4zK2GOetXVZc6t5nXTS1NZEJ523veytsraNO8nTE2lWhBBCCKFr0qwIIYQQQtekWRFCCCGErskFtgNMa2ur9nyNgfK0TFsltdAXqYd+SC30w1ZqIc3KANPQ0ICnpyf19fW98khx8Z+TWuiL1EM/pBb6YSu1kI+BhBBCCKFr0qwIIYQQQtekWRFCCCGErkmzMsA4OzuzZcuWAX2hlK2QWuiL1EM/pBb6YSu1kAtshRBCCKFrcmZFCCGEELomzYoQQgghdE2aFSGEEELomjQrQgghhNA1aVYGiNbWVuLj4/Hz88PV1ZWpU6dy9OjR/h6WTTt79izPPfccwcHBuLu74+/vz8KFCykuLrbI/eabb5g7dy4eHh54e3vzzDPPUF1d3Q+jvnekpKRgZ2fHxIkTLeZ98cUXTJ8+HTc3N3x8fFi/fj2NjY39MErb9tVXXxEZGYm3tzdubm5MnDiRV1991SxHanH3Xbx4kUWLFjFixAjc3NwIDAwkKSmJ5uZms7yBXAu5G2iAiImJ4eDBgzz//POMHz+e9PR0zp49y+eff8706dP7e3g26amnnuL06dMsWLCAkJAQKisree2112hsbCQrK0v7T/Lq1auEhobi6empvfhTU1Px9/cnJycHJyenft4T23P16lUCAgKws7Nj1KhRnD9/XpuXn5/PtGnTeOCBB1i5ciVXr14lNTWVhx9+mMzMzH4ctW359NNPmTdvHqGhoURHR+Ph4cGlS5fo7Ozkj3/8IyC16AtXrlwhJCQET09PVq9ejbe3N2fOnCE9PZ3IyEg+/PBDwAZqoYTuZWdnK0D96U9/0mItLS1q7Nixatq0af04Mtt2+vRp1draahYrLi5Wzs7OKjY2VoutWbNGubq6qrKyMi129OhRBai0tLQ+G++9JDo6Wj3yyCNq1qxZKjg42GxeRESE8vX1VfX19Vpsz549ClD//Oc/+3qoNqm+vl4NGzZM/frXv1YdHR095kkt7r6UlBQFqPPnz5vFlyxZogBVU1OjlBr4tZCPgQaAgwcPYm9vz8qVK7WYi4sLy5Yt48yZM1y5cqUfR2e7wsPDLc6KjB8/nuDgYL755hst9sEHH/DEE0/g7++vxWbPns2ECRN47733+my894oTJ05w8OBB/vKXv1jMa2ho4OjRozz99NNmD21bsmQJHh4eUo9e8u6771JVVUVKSgqDBg2iqamJzs5OsxypRd9oaGgAYNiwYWZxX19fBg0ahJOTk03UQpqVASAvL48JEyZYPDFzypQpQNfpPdE3lFJUVVXxs5/9DACDwcC1a9cICwuzyJ0yZQp5eXl9PUSb1tHRwbp161i+fDmTJk2ymF9QUEB7e7tFPZycnJg8ebLUo5ccO3aMwYMHYzAYCAgIwMPDg8GDB7NmzRqMRiMgtegrv/zlLwFYtmwZ+fn5XLlyhYyMDHbt2sX69etxd3e3iVpIszIAfPfdd/j6+lrEu2MVFRV9PaR71v79+zEYDERHRwNdtQF6rE9NTQ2tra19OkZbtnv3bsrKykhOTrY6/2b1kNdK77h48SLt7e08+eSTPProo3zwwQfExcWxe/dunn32WUBq0Vfmzp1LcnIyR48eJTQ0FH9/fxYtWsS6devYsWMHYBu1cOjvAYiba2lpsfpcBxcXF22+uPsuXLjA2rVrmTZtGkuXLgV+PPY3q89Afy6HHvzwww8kJiby0ksvMXToUKs5N6uHvFZ6R2NjI83NzaxevVq7++c3v/kNJpOJtLQ0kpKSpBZ9aNSoUcycOZP58+czZMgQPvnkE15++WV8fHx47rnnbKIW0qwMAK6urlbfnXefbnV1de3rId1zKisrefzxx/H09NSuIYIfj73U5+7bvHkz3t7erFu3rsecm9VDatE7uo9jTEyMWXzx4sWkpaVx5swZ3NzcAKnF3XbgwAFWrlxJcXExI0aMALoax87OTuLj44mJibGJ14V8DDQA+Pr6aqfxfqo75ufn19dDuqfU19cTERFBXV0dR44cMTve3adVe6qPt7e3nFXpBRcvXuSNN95g/fr1VFRUUFpaSmlpKUajkba2NkpLS6mpqblpPeS10ju6j+O/X9R5//33A1BbWyu16CM7d+4kNDRUa1S6RUZG0tzcTF5enk3UQpqVAWDy5MkUFxdrV313y87O1uaLu8NoNDJv3jyKi4v5+OOPCQoKMps/fPhwhg4dSm5ursWyOTk5UpteYjAY6OzsZP369YwePVr7yc7Opri4mNGjR5OUlMTEiRNxcHCwqIfJZCI/P1/q0UsefPBBoKsuP9V97cPQoUOlFn2kqqqKjo4Oi3hbWxsA7e3ttlGL/r53WtxcVlaWxfesGI1GNW7cODV16tR+HJlta29vV5GRkcrBwUF98sknPeatXr1aubq6qvLyci127NgxBahdu3b1xVBtXnV1tTp06JDFT3BwsPL391eHDh1S586dU0opNXfuXOXr66saGhq05ffu3asAlZmZ2V+7YFO++uorBajFixebxWNiYpSDg4MyGAxKKalFX3jiiSeUk5OTKioqMotHRUWpQYMG2UwtpFkZIBYsWKAcHBzUCy+8oNLS0lR4eLhycHBQx48f7++h2awNGzYoQM2bN0+98847Fj/dysvL1ZAhQ9TYsWPVq6++ql5++WV13333qUmTJimj0diPe2D7rH0p3JdffqmcnZ1VaGio2rVrl0pISFAuLi5qzpw5/TRK2xQXF6cAtXDhQvX666+rBQsWKEBt2rRJy5Fa3H3Hjx9X9vb26v7771dJSUnq9ddfVxEREQpQy5cv1/IGei2kWRkgWlpa1MaNG5WPj49ydnZWv/jFL9SRI0f6e1g2bdasWQro8eenzp8/r+bMmaPc3NyUl5eXio2NVZWVlf008nuHtWZFKaVOnjypwsPDlYuLixo6dKhau3at2TtKcedMJpP6wx/+oEaOHKkcHR3VuHHj1I4dOyzypBZ3X3Z2toqIiFA+Pj7K0dFRTZgwQaWkpKi2tjazvIFcC3k2kBBCCCF0TS6wFUIIIYSuSbMihBBCCF2TZkUIIYQQuibNihBCCCF0TZoVIYQQQuiaNCtCCCGE0DVpVoQQQgiha9KsCCGEEELXpFkRQgghhK5JsyKEEEIIXZNmRQghhBC6Js2KEEIIIXRNmhUhhBBC6Nr/A0PhJ5/xpoAxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 600x450 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distributions_plot(\n",
    "    [\"Complete\", \"MCAR\", \"MCAR (mean imputed)\"],\n",
    "    [adata, adata_mcar, adata_mcar_mean_imputed],\n",
    "    \"num_medications\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see immediately how the overall location of the distribution is not affected by mean imputation in the MCAR case (even though the median might have tipped): however, we can see that the variance now gets severly underestimated: the standard deviation dropped from to 8.1 in the original data to 6.8 in the imputed data.\n",
    "\n",
    "The reason for this can be observed in the density plot, namely that the mean imputation leads to all formerly missing instances being assigned a single value."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Mean Imputation in the MAR case\n",
    "\n",
    "We now consider the MAR case from the previous section on missing data. We first perform a simple mean imputation on our `num_medications` variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_mar_mean_imputed = ep.pp.simple_impute(\n",
    "    adata_mar, var_names=[\"num_medications\"], strategy=\"mean\", copy=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now also perform a more sophisticated approach: e.g. Multiple imputation has been shown to [perform well for MAR data](https://www.frontiersin.org/articles/10.3389/fdata.2021.693674/full).\n",
    "Here, we apply one such strategy, the [MissForest imputation](https://academic.oup.com/bioinformatics/article/28/1/112/219101), as implemented in ehrapy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# consider for imputation only the two variables of our focus\n",
    "adata_mar_medication_hospital_time = AnnData(\n",
    "    adata_mar[:, adata_mar.var_names.isin([\"time_in_hospital\", \"num_medications\"])]\n",
    "    .X.copy()\n",
    "    .astype(np.float64),\n",
    ")\n",
    "adata_mar_medication_hospital_time.var_names = [\"time_in_hospital\", \"num_medications\"]\n",
    "ep.ad.infer_feature_types(adata_mar_medication_hospital_time)\n",
    "\n",
    "adata_mar_medication_hospital_time_imputed = ep.pp.miss_forest_impute(\n",
    "    adata_mar_medication_hospital_time, copy=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distributions_plot(\n",
    "    [\"Complete\", \"MAR\", \"MAR Mean Imputed\", \"MAR MissForest Imputed\"],\n",
    "    [\n",
    "        adata,\n",
    "        adata_mcar,\n",
    "        adata_mar_mean_imputed,\n",
    "        adata_mar_medication_hospital_time_imputed,\n",
    "    ],\n",
    "    \"num_medications\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see how the MAR missing data (orange) contains a systematic distortion towards smaller values compared to the complete, known data (blue) by our construction.\n",
    "\n",
    "The mean imputation (green), which yielded a valid estimate of the mean in the MCAR case, now is not a valid imputation anymore; both the location and the variance of the mean imputed dataset with MAR missing data are skewed compared to the (known) complete data.\n",
    "\n",
    "MissForest imputation (red) shows superior results in both location and scale of the data distribution: The imputed datasets has a mean of 16.04, close to the true, known mean of 16.02.\n",
    "Its flexible imputation also generates a more realistic distribution of the data, as opposed to the variance shrinking mean imputation.\n",
    "\n",
    "Importantly, imputation is not about \"recreating the lost data\", but about being able to make valid inference from the incomplete data [van Buuren (2018)](https://stefvanbuuren.name/fimd/).\n",
    "The behaviour of skewed location and variance in the data distribution here demonstrates how imputation methods under different missing data models can manifest biases in our analyses."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation Strategies\n",
    "\n",
    "As mentioned in the missing data section, extensive literature on missing data and imputation is available.\n",
    "For a first dive into more details e.g. [van Buuren (2018)](https://stefvanbuuren.name/publication/vanbuuren-2018/), [Schouten 2021](https://journals.sagepub.com/doi/full/10.1177/0049124118799376) can be considered.\n",
    "\n",
    "- Conduct thorough exploratory analysis to understand the patterns and mechanisms of missing data to guide the choice of the most appropriate imputation method.\n",
    "- Select imputation methods that best fit the data distribution and the mechanism of missingness. Multiple imputation methods have been shown to perform well under many circumstances.\n",
    "- Validate the imputation by comparing the characteristics of the imputed data with the observed data.\n",
    "- Avoid imputation in cases of high proportions of missing data where the imputation might dominate the analytical results.\n",
    "- Use robustness checks, such as repeating the analysis with different imputation methods or omitting imputation altogether (using sparse matrices), to assess the impact of the imputation on the study conclusions.\n",
    "- Be wary of clusters in the data that have high percentage of missing data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algorithmic bias\n",
    "\n",
    "Algorithmic bias occurs when algorithms systematically perform better for certain groups than for others, often due to biases inherent in the data used to train these algorithms.\n",
    "This can result in unequal treatment recommendations, risk predictions, or health outcomes assessments across different demographics, such as race, gender, or socioeconomic status.\n",
    "For instance, an algorithm trained predominantly on data from one ethnic group may perform poorly or inaccurately predict outcomes for individuals from underrepresented groups, exacerbating disparities in healthcare access and outcomes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Recommending patients for high-risk care management programs\n",
    "\n",
    "Here, we adapt an example from the [Fairlearn SciPy 2021 Tutorial: Fairness in AI Systems](https://github.com/fairlearn/talks/tree/main/2021_scipy_tutorial).\n",
    "\n",
    "We predict **hospital readmission within 30 days** from the earlier introduced dataset of hospital data of diabetic patients.\n",
    "Such a quick readmission is viewed as proxy that the patient needed more assistance at release time and is therefore our target variable.\n",
    "\n",
    "We follow the decision in the earlier work to measure the:\n",
    "- balanced accuracy to investigate the performance of the algorithm\n",
    "- selection rate to investigate how many patients are recommended for care\n",
    "- false negative rate to investigate how many patients would have missed the needed assistance\n",
    "\n",
    "An investigation is needed to determine whether any patient subgroups within the demographic variable `race` are negatively affected by a model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import balanced_accuracy_score, RocCurveDisplay\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.pipeline import Pipeline\n",
    "\n",
    "from fairlearn.metrics import MetricFrame, false_negative_rate, selection_rate\n",
    "from fairlearn.postprocessing import ThresholdOptimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Data Preparation\n",
    "We load the dataset, and put variables we don't want to pass to our model into the `.obs` field.\n",
    "We build a binary label `readmit_30_days` indicating whether a patient has been readmitted in <30 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_algo = ep.dt.diabetes_130_fairlearn(\n",
    "    columns_obs_only=[\n",
    "        \"race\",\n",
    "        \"gender\",\n",
    "        \"age\",\n",
    "        \"readmitted\",\n",
    "        \"readmit_binary\",\n",
    "        \"discharge_disposition_id\",\n",
    "    ]\n",
    ")\n",
    "adata_algo.obs[\"readmit_30_days\"] = adata_algo.obs[\"readmitted\"] == \"<30\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our dataset, our patients are predominantly *Caucasian* (75%). The next largest racial group is *AfricanAmerican*, making up 19% of the patients. The remaining race categories (including *Unknown*) compose only 6% of the data.\n",
    "In this dataset, gender is primarily reported binary, with 54% *Female* and 46% *Male*, and 3 samples annotated as *Unknown/Invalid*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "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></th>\n",
       "      <th>Missing</th>\n",
       "      <th>Overall</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <th></th>\n",
       "      <td></td>\n",
       "      <td>101766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">race, n (%)</th>\n",
       "      <th>AfricanAmerican</th>\n",
       "      <td>0</td>\n",
       "      <td>19210 (18.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Asian</th>\n",
       "      <td></td>\n",
       "      <td>641 (0.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caucasian</th>\n",
       "      <td></td>\n",
       "      <td>76099 (74.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hispanic</th>\n",
       "      <td></td>\n",
       "      <td>2037 (2.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td></td>\n",
       "      <td>1506 (1.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown</th>\n",
       "      <td></td>\n",
       "      <td>2273 (2.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">gender, n (%)</th>\n",
       "      <th>Female</th>\n",
       "      <td>0</td>\n",
       "      <td>54708 (53.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Male</th>\n",
       "      <td></td>\n",
       "      <td>47055 (46.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown/Invalid</th>\n",
       "      <td></td>\n",
       "      <td>3 (0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">age, n (%)</th>\n",
       "      <th>'30 years or younger'</th>\n",
       "      <td>0</td>\n",
       "      <td>2509 (2.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'30-60 years'</th>\n",
       "      <td></td>\n",
       "      <td>30716 (30.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>'Over 60 years'</th>\n",
       "      <td></td>\n",
       "      <td>68541 (67.4)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><br />"
      ],
      "text/plain": [
       "                                    Missing       Overall\n",
       "n                                                  101766\n",
       "race, n (%)   AfricanAmerican             0  19210 (18.9)\n",
       "              Asian                             641 (0.6)\n",
       "              Caucasian                      76099 (74.8)\n",
       "              Hispanic                         2037 (2.0)\n",
       "              Other                            1506 (1.5)\n",
       "              Unknown                          2273 (2.2)\n",
       "gender, n (%) Female                      0  54708 (53.8)\n",
       "              Male                           47055 (46.2)\n",
       "              Unknown/Invalid                     3 (0.0)\n",
       "age, n (%)    '30 years or younger'       0    2509 (2.5)\n",
       "              '30-60 years'                  30716 (30.2)\n",
       "              'Over 60 years'                68541 (67.4)"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TableOne(adata_algo.obs, columns=[\"race\", \"gender\", \"age\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Decision: How to address smaller group sizes?\n",
    "We have seen different strategies to address smaller group sizes in the selection bias part.\n",
    "\n",
    "- For the `race` variable, we will follow the strategy of using buckets to merge small groups *Other*, *Spanish*, *Asian*.\n",
    "- For the `gender` variable, we will remove the *Unknown/Invalid* annotated samples, as no meaningful assessment is possible with this sample size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 101763 × 19\n",
       "    obs: 'race', 'age', 'readmitted', 'readmit_binary', 'discharge_disposition_id', 'readmit_30_days', 'race_all'\n",
       "    var: 'ehrapy_column_type'"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# aggregate small groups\n",
    "adata_algo.obs[\"race_all\"] = adata_algo.obs[\"race\"]\n",
    "adata_algo.obs[\"race\"] = adata_algo.obs[\"race\"].replace(\n",
    "    {\"Asian\": \"Other\", \"Hispanic\": \"Other\"}\n",
    ")\n",
    "\n",
    "# drop gender group Unknown/Invalid\n",
    "adata_algo = adata_algo[adata_algo.obs[\"gender\"] != \"Unknown/Invalid\", :].copy()\n",
    "ep.ad.move_to_x(adata_algo, \"gender\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now prepare our variables required for model training, and encode categorical variables in the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_algo = ep.pp.encode(\n",
    "    adata_algo,\n",
    "    autodetect=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We split our data into train and test groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_idxs, test_idxs = train_test_split(\n",
    "    np.arange(adata_algo.n_obs),\n",
    "    stratify=adata_algo.obs[\"race\"],\n",
    "    test_size=0.5,\n",
    "    random_state=0,\n",
    ")\n",
    "adata_algo_train = adata_algo[train_idxs, :]\n",
    "adata_algo_test = adata_algo[test_idxs, :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "readmit_30_days\n",
       "False    45214\n",
       "True      5667\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_algo_train.obs[\"readmit_30_days\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To account for label imbalance of our target variable `readmit_30_days` with more `False` than `True` cases, we do balanced subsampling by performing [Random Undersampling](https://imbalanced-learn.org/stable/references/generated/imblearn.under_sampling.RandomUnderSampler.html):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "readmit_30_days\n",
       "False    5667\n",
       "True     5667\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_algo_train_balanced = ep.pp.balanced_sample(\n",
    "    adata_algo_train,\n",
    "    key=\"readmit_30_days\",\n",
    "    method=\"RandomUnderSampler\",\n",
    "    random_state=0,\n",
    "    copy=True,\n",
    ")\n",
    "adata_algo_train_balanced.obs[\"readmit_30_days\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Model Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "unmitigated_pipeline = Pipeline(\n",
    "    steps=[\n",
    "        (\"preprocessing\", StandardScaler()),\n",
    "        (\"logistic_regression\", LogisticRegression(max_iter=1000)),\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
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       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
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       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
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       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
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       "  overflow: hidden;\n",
       "  padding: 0;\n",
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       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
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       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, StandardScaler()),\n",
       "                (&#x27;logistic_regression&#x27;, LogisticRegression(max_iter=1000))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, StandardScaler()),\n",
       "                (&#x27;logistic_regression&#x27;, LogisticRegression(max_iter=1000))])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;StandardScaler<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.preprocessing.StandardScaler.html\">?<span>Documentation for StandardScaler</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>StandardScaler()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;LogisticRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LogisticRegression.html\">?<span>Documentation for LogisticRegression</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>LogisticRegression(max_iter=1000)</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('preprocessing', StandardScaler()),\n",
       "                ('logistic_regression', LogisticRegression(max_iter=1000))])"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unmitigated_pipeline.fit(\n",
    "    adata_algo_train_balanced.X,\n",
    "    adata_algo_train_balanced.obs[\"readmit_30_days\"].astype(bool),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can inspect our model's coefficients:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+Zk2uqtcdQggh5aOKBfnoqKqqYuDAgdi+fTtu3Lih0FwoPT29xibCkj8lLv2Uu7CwEBs2bFAav6ioCJGRkbzO25GRkZBIJLC1teXF9fHxwfTp0yEUCmFgYAA3Nzfe8oEDB2LevHnYt29fuZ23S+dPfjN44cIF/Pnnn7ymQPL5OMrePNUkZWXFGMOaNWt48YyNjdG2bVts2bIFM2fO5HXevnXrFlfx+JDWr1/P67y9fv16qKmpoXv37gBK9k3eWV4uJSVF6QzbWlpaVSpnFxcX6OrqYtGiRejatavCfBxvcx6/y3Hu3bs3jh07hri4OF7n7dIdy4GqH2e51q1bo3Xr1ti0aRPOnz8PPz8/3tuY3NxcaGpq8sJatWoFFRUVpUPd1jRdXV3Uq1cPp0+f5o3qVPY3/iGvO4TUpLfpiEvI+0IVC/JRWrx4MRITE2Fvb4+goCBYWVkhKysLly9fxokTJ5CVlVUj2+nUqRPq1q0LPz8/TJgwAQKBAFu3bi23OY2JiQmWLFmClJQUNGvWDDt37sTVq1cRFRWlcOPo7e2N6dOnY9++fRg9erTC8mnTpnE3eYGBgbC1tUVWVhYOHjyIiIgItGnTBn369OFGjXJ3d0dycjIiIiJgZWWFvLw8Li0NDQ1YWVlh586daNasGfT19WFjY1OlPhxV1aJFC1haWmLq1KlITU2Frq4u9uzZo7QPQHh4ONzd3dGlSxcEBgYiKysL69atg7W1NS/fH4JIJMKRI0fg5+cHe3t7JCQkID4+HrNnz+ZuFN3d3bFy5Uq4urrC29sbaWlp+OGHH9CkSRNcu3aNl56trS1OnDiBlStXwsTEBBYWFrC3t1fYrq6uLjZu3AgfHx+0b98eQ4YMgUQiwePHjxEfH4/OnTtj/fr11dqXdznOQUFBWL9+PXx9fXHp0iUYGxtj69atCpNEVuc4y/n6+mLq1KkAoNAM6uTJkxg3bhwGDx6MZs2aoaioCFu3buVu5D+EESNGYPHixRgxYgTs7Oxw+vRp7q1VaR/qukMIIZ8tRshH6vnz52zs2LGsYcOGTE1NjRkZGbHu3buzqKgoxhhjiYmJDADbvXs3b73k5GQGgEVHR3NhTk5OzNraWul2zp49yzp27Mg0NDSYiYkJmz59Ojt69CgDwBITExXSuHjxIvv666+ZSCRiZmZmbP369eXuQ+/evRkAdu7cOaXLMzMz2bhx41iDBg2Yuro6MzU1ZX5+fiwjI4MxxphMJmOLFi1iZmZmTCgUsnbt2rFDhw4xPz8/ZmZmxkvr3LlzzNbWlqmrqzMALCQkpNx8lVadcrx16xbr0aMH09bWZvXq1WNBQUHsn3/+UYjHGGN79uxhLVu2ZEKhkFlZWbG9e/cqzXdlyq4jz9eyZcsU4pbdbz8/P6alpcUePHjAevXqxTQ1NVn9+vVZSEgIKy4u5q27efNm1rRpUyYUClmLFi1YdHQ0CwkJYWUvk3fu3GGOjo5MQ0ODAWB+fn6MMcaio6MZAJacnMyLn5iYyFxcXJhYLGYikYhZWloyf39/dvHiRYV8lqVs+297nBlj7NGjR6xfv35MU1OT1atXj02cOJEdOXJE4VyvznFmjLF///2XqaqqsmbNmikse/jwIQsMDGSWlpZMJBIxfX191rVrV3bixIkq57ssd3d3hfPIzMyMubu7K42fn5/Phg8fzsRiMdPR0WGenp4sLS1NaflVdt2pCqlUygAwqVRa3V0jhJCPUlWvazSPBSFV5OzsjIyMjEr7RZTWv39/XL9+XWEGa/Jh+Pv7Iy4u7oO/JfnSZGRkwNjYGHPnzuXNw/Glqup474QQ8qmgeSwIqWX//vsv4uPj4ePjU9tZIeS9iomJQXFxMZ3rhBDyhaM+FoTUsOTkZJw9exabNm2CmpqawkzfH0phYWGlbcLFYrHSITo/hKysLBQWFpa7XFVVlTrLVkFtHueTJ0/i1q1bWLhwITw8PHgjo1WVVCrFq1evKoyjbLheQgghHx+qWBBSw37//XcEBASgUaNG2LJlS63dFJ07dw5du3atME50dDT8/f0/TIbKGDBgAH7//fdyl5uZmfEmsCPK1eZxnjdvHjd0bNnhlKtq4sSJ2LJlS4VxqMUuIYR8GqiPBSGfqezsbFy6dKnCONbW1jA2Nv5AOeK7dOlShSMNaWhooHPnzh8wR5+mj/04V+bWrVt49uxZhXE+tXklqI8FIeRzU9XrGlUsCCGEkBpEFQtCyOeGOm8TQkgtOHXqFAQCAeLi4mo7KxWS5/PUqVNcmL+//1v1kyCEEEIA6mNBCCGEEPLJMp8ZX9tZ+CzRjOZvhyoWhBBCAAA//vgjZDJZbWeDEELIJ4qaQhFCyCfo5cuXNZ6mmpoahEJhjadLCCHky0AVC0LIJy00NBQCgQD379+Hv78/9PT0IBaLERAQgPz8fABASkoKBAIBYmJiFNYXCAQIDQ1VSO/evXsYNmwYxGIxJBIJ5syZA8YYnjx5gm+++Qa6urowMjLCihUrlOaruLgYs2fPhpGREbS0tNCvXz88efJEId6FCxfg6uoKsVgMTU1NODk54ezZs0r38datW/D29kbdunXRpUuXKpfR06dP4eHhAS0tLRgaGmLy5MkoKChQiKesj8Xy5cvRqVMnGBgYQENDA7a2tkr7j7x69QoTJkxAvXr1oKOjg379+iE1NbXc8q3oeMkVFRVh/vz5sLS0hFAohLm5OWbPnq2Q94sXL8LFxQX16tWDhoYGLCwsEBgYyIsjk8mwevVqWFtbQyQSoX79+ggODlYYmawqaRFCCFGOmkIRQj4Lnp6esLCwQHh4OC5fvoxNmzbB0NAQS5Yseav0vv32W7Rs2RKLFy9GfHw8FixYAH19fURGRqJbt25YsmQJYmNjMXXqVHz11VdwdHTkrb9w4UIIBALMmDEDaWlpWL16NXr06IGrV69yk9WdPHkSbm5usLW1RUhICFRUVBAdHY1u3brhzJkz6NChAy/NwYMHo2nTpli0aFGV53Z49eoVunfvjsePH2PChAkwMTHB1q1bcfLkySqtv2bNGvTr1w9Dhw5FYWEhfvnlFwwePBiHDh2Cu/v/tUH29/fHrl274OPjg44dO+L333/nLS+rKsdrxIgR2LJlCwYNGoTvvvsOFy5cQHh4OG7fvo19+/YBANLS0tCrVy9IJBLMnDkTenp6SElJwd69e3nbCw4ORkxMDAICAjBhwgQkJydj/fr1uHLlCs6ePQs1NbUqp1VWQUEBr7KTm5tbpbIlhJDPDVUsCCGfhXbt2mHz5s3c98zMTGzevPmtKxYdOnRAZGQkAGDkyJEwNzfHd999h/DwcMyYMQMA4OXlBRMTE/z0008KFYusrCzcvn0bOjo6AID27dvD09MTP/74IyZMmADGGEaNGoWuXbsiISEBAoEAQMkNsLW1Nb7//nscO3aMl2abNm2wffv2au1HVFQU7t27h127dmHw4MEAgKCgILRp06ZK69+7d483a/e4cePQvn17rFy5kqs4XL58Gbt27cKkSZOwatUqAMCYMWMQEBCAf/75R2m6lR2vf/75B1u2bMGIESPw448/cmkaGhpi+fLlSExMRNeuXXHu3DlkZ2fj2LFjsLOz49JbsGAB9/cff/yBTZs2ITY2Ft7e3lx4165d4erqit27d8Pb27tKaSkTHh6OsLCwiguSEEK+ANQUihDyWRg1ahTvu4ODAzIzM9/66fGIESO4v1VVVWFnZwfGGIYPH86F6+npoXnz5nj48KHC+r6+vlylAgAGDRoEY2NjHD58GABw9epVJCUlwdvbG5mZmcjIyEBGRgZevnyJ7t274/Tp0wodqcvuY1UcPnwYxsbGGDRoEBemqamJkSNHVmn90pWK7OxsSKVSODg44PLly1z4kSNHAJTc+Jc2fvz4ctOt7HjJy2nKlCm8eN999x0AID6+ZCQcPT09AMChQ4fw5s0bpdvavXs3xGIxevbsyZVzRkYGbG1toa2tjcTExCqnpcysWbMglUq5j7Imb4QQ8iWgNxaEkM9Co0aNeN/r1q0LABXO7l2d9MRiMUQiEerVq6cQnpmZqbB+06ZNed8FAgGaNGmClJQUAEBSUhIAwM/Pr9w8SKVSbj8AwMLColr7AACPHj1CkyZNuDcics2bN6/S+ocOHcKCBQtw9epVXnOf0uk9evQIKioqCvlr0qRJuelWdLx0dXW5NMumYWRkBD09PTx69AgA4OTkhIEDByIsLAyrVq2Cs7MzPDw84O3tzXVET0pKglQqhaGhodK8pKWlVTktZYRCIXV6J4QQUMWCEPKZUFVVVRrOGFO4qZYrLi6uVnoVbaO65G8jli1bhrZt2yqNo62tzfte+u3Bh3DmzBn069cPjo6O2LBhA4yNjaGmpobo6OhqN8kqq6plWd6xK708Li4O58+fx6+//oqjR48iMDAQK1aswPnz56GtrQ2ZTAZDQ0PExsYqTUMikVQ5LUIIIeWjigUh5LMnfxqek5PDC5c/9X4f5G8k5BhjuH//Plq3bg0AsLS0BADo6uqiR48e7y0fZmZmuHHjhkIF6+7du5Wuu2fPHohEIhw9epT3RD46OlphGzKZDMnJybw3Nffv33+nfMtkMiQlJaFly5Zc+PPnz5GTkwMzMzNe/I4dO6Jjx45YuHAhtm/fjqFDh+KXX37BiBEjYGlpiRMnTqBz585VqpxVlBYhhJDyUcWCEPLZ09XVRb169XD69GlMmjSJC9+wYcN72+bPP/+MWbNmcf0s4uLi8O+//3Idv21tbWFpaYnly5fD29tb4Wl4eno69yT9XfTu3RvHjh1DXFwc13k7Pz8fUVFRla6rqqoKgUDAe7OTkpKC/fv38+K5uLjgf//7HzZs2MB13gaAdevWvVO+Z8+ejdWrV3Od6AFg5cqVAMB1HM/Ozoaenh6v0iR/AyRvuuXp6YkNGzZg/vz5WLRoEW87RUVFyMvLg56eXpXSIuRjQzNEk48JVSwIIV+EESNGYPHixRgxYgTs7Oxw+vRp3Lt3771tT19fH126dEFAQACeP3+O1atXo0mTJggKCgIAqKioYNOmTXBzc4O1tTUCAgLQoEEDpKamIjExEbq6uvj111/fOR9BQUFYv349fH19cenSJRgbG2Pr1q3Q1NSsdF13d3esXLkSrq6u8Pb2RlpaGn744Qc0adIE165d4+LZ2tpi4MCBWL16NTIzM7nhZuXlW1lzJmXatGkDPz8/REVFIScnB05OTvjrr7+wZcsWeHh4oGvXrgCALVu2YMOGDejfvz8sLS3x4sUL/Pjjj9DV1UXv3r0BlPSdCA4ORnh4OK5evYpevXpBTU0NSUlJ2L17N9asWYNBgwZVKS1CCCHlo4oFIeSLMHfuXKSnpyMuLg67du2Cm5sbEhISyu3Q+65mz56Na9euITw8HC9evED37t2xYcMG3g29s7Mz/vzzT8yfPx/r169HXl4ejIyMYG9vj+Dg4BrJh6amJn777TeMHz8e69atg6amJoYOHQo3Nze4urpWuG63bt2wefNmLF68GJMmTYKFhQWWLFmClJQUXsUCKHlDY2RkhB07dmDfvn3o0aMHdu7ciebNm0MkEr1V3jdt2oTGjRsjJiYG+/btg5GREWbNmoWQkBAujrzC8csvv+D58+cQi8Xo0KEDYmNjeZ3JIyIiYGtri8jISMyePRt16tSBubk5hg0bhs6dO1crLUIIIcoJ2Nv0OiSEEEIqcfXqVbRr1w7btm3D0KFDazs7H0xubi7EYjGkUil0dXVrOzuEEPLOqnpdo3ksCCGEvLNXr14phK1evRoqKioKkwcSQgj5PFFTKEII+QQVFhYiKyurwjhisfiDDVG7dOlSXLp0CV27dkWdOnWQkJCAhIQEjBw5Eg0bNvwgeSCEEFK7qGJBCCGfoHPnznEdmMsTHR0Nf3//D5KfTp064fjx45g/fz7y8vLQqFEjhIaG4n//+98H2T4hhJDaR30sCCHkE5SdnY1Lly5VGMfa2hrGxsYfKEdEjvpYEEI+N1W9rtEbC0II+QTVrVv3vU6sRwghhFQXdd4mhBBCCCGEvDN6Y0EIIaRcMTExCAgIQHJyMszNzQGUzL8BAKdOnar1vBDypTOfGV/bWfjgaLbxjxe9sSCEEPJRWbRoEfbv31/b2SCEEFJNVLEghBBSLceOHcOxY8feW/rlVSx8fHzw6tUrmJmZvbdtE0IIeXvUFIoQQki1qKur18p2VVVVoaqqWivbJoQQUjl6Y0EI+WKEhoZCIBDg/v378Pf3h56eHsRiMQICApCfnw8ASElJgUAgQExMjML6AoEAoaGhCundu3cPw4YNg1gshkQiwZw5c8AYw5MnT/DNN99AV1cXRkZGWLFiRbXzbG5ujj59+uDUqVOws7ODhoYGWrVqxfVv2Lt3L1q1agWRSARbW1tcuXJFIY07d+5g0KBB0NfXh0gkgp2dHQ4ePKgQ7+bNm+jWrRs0NDRgamqKBQsWQCaTKcRzdnbm+lnIvX79GqGhoWjWrBlEIhGMjY0xYMAAPHjwgIuzfPlydOrUCQYGBtDQ0ICtrS3i4uJ46QgEArx8+RJbtmyBQCCAQCDg5uKIiYmBQCBASkoKb50NGzbA2toaQqEQJiYmGDt2LHJychTybGNjg1u3bqFr167Q1NREgwYNsHTpUoX9W7duHaytraGpqYm6devCzs4O27dvV4hHCCGEjyoWhJAvjqenJ168eIHw8HB4enoiJiYGYWFhb53et99+C5lMhsWLF8Pe3h4LFizA6tWr0bNnTzRo0ABLlixBkyZNMHXqVJw+fbra6d+/fx/e3t7o27cvwsPDkZ2djb59+yI2NhaTJ0/GsGHDEBYWhgcPHsDT05NXGbh58yY6duyI27dvY+bMmVixYgW0tLTg4eGBffv2cfH+++8/dO3aFVevXsXMmTMxadIk/Pzzz1izZk2l+SsuLkafPn0QFhYGW1tbrFixAhMnToRUKsWNGze4eGvWrEG7du0wb948LFq0CHXq1MHgwYMRH/9/nU+3bt0KoVAIBwcHbN26FVu3bkVwcHC52w4NDcXYsWNhYmKCFStWYODAgYiMjESvXr3w5s0bXtzs7Gy4urqiTZs2WLFiBVq0aIEZM2YgISGBi/Pjjz9iwoQJsLKywurVqxEWFoa2bdviwoUL5eahoKAAubm5vA8hhHyJqCkUIeSL065dO2zevJn7npmZic2bN2PJkiVvlV6HDh0QGRkJABg5ciTMzc3x3XffITw8HDNmzAAAeHl5wcTEBD/99BMcHR2rlf7du3dx7tw5fP311wAAKysruLi4ICgoCHfu3EGjRo0AlMxtERwcjNOnT3NvFCZOnIhGjRrh77//hlAoBACMGTMGXbp0wYwZM9C/f38AwJIlS5Ceno4LFy6gQ4cOAAA/Pz80bdq00vz9/PPP+O2337By5UpMnjyZC585cyZKz8F67949aGhocN/HjRuH9u3bY+XKlXB3LxnlZdiwYRg1ahQaN26MYcOGVbjd9PR0hIeHo1evXkhISICKSsmzshYtWmDcuHHYtm0bAgICuPjPnj3Dzz//DB8fHwDA8OHDYWZmhs2bN8PNzQ0AEB8fD2tra+zevbvS/ZYLDw9/p4opIYR8LuiNBSHkizNq1CjedwcHB2RmZr71k+YRI0Zwf6uqqsLOzg6MMQwfPpwL19PTQ/PmzfHw4cNqp29lZcVVKgDA3t4eANCtWzeuUlE6XL6NrKwsnDx5kntDk5GRgYyMDGRmZsLFxQVJSUlITU0FABw+fBgdO3bkKhUAIJFIMHTo0Erzt2fPHtSrVw/jx49XWCYQCLi/S1cqsrOzIZVK4eDggMuXL1epHMo6ceIECgsLMWnSJK5SAQBBQUHQ1dXlvQkBAG1tbV5lRV1dHR06dOAdEz09PTx9+hR///13lfMxa9YsSKVS7vPkyZO32h9CCPnUUcWCEPLFKX0zDpQ86QdKbnZrIj2xWAyRSIR69eophL/NNpSlDwANGzZUGi7fxv3798EYw5w5cyCRSHifkJAQAEBaWhoA4NGjR0rfTjRv3rzS/D148ADNmzdHnToVvwQ/dOgQOnbsCJFIBH19fUgkEmzcuBFSqbTSbSjz6NEjpXlUV1dH48aNueVypqamvIoOUHLsSx+TGTNmQFtbGx06dEDTpk0xduxYnD17tsJ8CIVC6Orq8j6EEPIloqZQhJAvTnkjCzHGFG485YqLi6uVXkXbqK7y0qpsG/K+FlOnToWLi4vSuE2aNKl2ft7GmTNn0K9fPzg6OmLDhg0wNjaGmpoaoqOjP1jH6Kock5YtW+Lu3bs4dOgQjhw5gj179mDDhg2YO3cuNXcihJBKUMWCEEJKkb+9KDuqUNmn35+Cxo0bAwDU1NTQo0ePCuOamZkhKSlJIfzu3buVbsfS0hIXLlzAmzdvoKampjTOnj17IBKJcPToUa6vBwBER0crxC2vcqcsz/I8yvcVAAoLC5GcnFzpPpdHS0sL3377Lb799lsUFhZiwIABWLhwIWbNmgWRSPRWaRJCyJeAKhaEEFKKrq4u6tWrh9OnT2PSpElc+IYNG2ovU2/J0NAQzs7OiIyMxPjx42FsbMxbnp6eDolEAgDo3bs3Vq9ejb/++ovrZ5Geno7Y2NhKtzNw4EDEx8dj/fr1vM7bwP+9BVJVVYVAIOC9+UlJSVE6EZ6WlpZCxU6ZHj16QF1dHWvXroWrqytXIdm8eTOkUinXIbw6MjMzYWBgwH1XV1eHlZUVEhIS8ObNG6pYkI9OyuLqn+eEvC9UsSCEkDJGjBiBxYsXY8SIEbCzs8Pp06dx79692s7WW/nhhx/QpUsXtGrVCkFBQWjcuDGeP3+OP//8E0+fPsU///wDAJg+fTq2bt0KV1dXTJw4EVpaWoiKioKZmRmuXbtW4TZ8fX3x888/Y8qUKfjrr7/g4OCAly9f4sSJExgzZgy++eYbuLu7Y+XKlXB1dYW3tzfS0tLwww8/oEmTJgrp29ra4sSJE1i5ciVMTExgYWHBdUwvTSKRYNasWQgLC4Orqyv69euHu3fvYsOGDfjqq68qHVVKmV69esHIyAidO3dG/fr1cfv2baxfvx7u7u7Q0dGpdnqEEPIloYoFIYSUMXfuXKSnpyMuLg67du2Cm5sbEhISYGhoWNtZqzYrKytcvHgRYWFhiImJQWZmJgwNDdGuXTvMnTuXi2dsbIzExESMHz8eixcvhoGBAUaNGgUTExPe6FbKqKqq4vDhw1i4cCG2b9+OPXv2wMDAgKvQACUjWG3evBmLFy/GpEmTYGFhgSVLliAlJUWhYrFy5UqMHDkS33//PV69egU/Pz+lFQugZB4LiUTCvS3R19fHyJEjsWjRonKbZVUkODgYsbGxWLlyJfLy8mBqaooJEybg+++/r3ZahBDypRGwt+lJSAghhBClcnNzIRaLIZVKaYQoQshnoarXNRpulhBCCCGEEPLOqCkUIYTUgvT09AqHsFVXV4e+vv4HzBEhhBDybqhiQQghteCrr76qcAhbJycnnDp16sNliBBCCHlHVLEghJBaEBsbi1evXpW7XD6fBiGEEPKpoIoFIYTUgs6dO9d2FgghhJAaRZ23CSGkGszNzeHv71/b2VAqJiYGAoEAKSkp7yV9gUCAcePGvZe0a4JAIEBoaGiNpuns7AxnZ+caTZMQQj5X9MaCEEKUOHfuHI4dO4ZJkyZBT0+vtrND3gIdQ/IlMJ8ZX9tZeO9odvFPB72xIIQQJc6dO4ewsDDk5OTwwu/evYsff/yxdjJVCR8fH7x69QpmZma1nZVa8erVK95EduUdQ0IIIe8HvbEghJBqEAqFtZ2FcqmqqkJVVbW2s1FrRCJRbWeBEEK+aPTGghBCyggNDcW0adMAABYWFhAIBFzfhbJ9LOT9Gv744w9MmDABEokEenp6CA4ORmFhIXJycuDr64u6deuibt26mD59OhhjvO3JZDKsXr0a1tbWEIlEqF+/PoKDg5GdnV2tfCvrY2Fubo4+ffrgjz/+QIcOHSASidC4cWP8/PPPb10++/fvh42NDYRCIaytrXHkyBGFOFeuXIGbmxt0dXWhra2N7t274/z587w4b968QVhYGJo2bQqRSAQDAwN06dIFx48f5+L4+/tDW1sbDx8+hIuLC7S0tGBiYoJ58+YplGPpPhYVHUMAiI6ORrdu3WBoaAihUAgrKyts3LjxrcuEEEIIvbEghBAFAwYMwL1797Bjxw6sWrUK9erVAwBIJJJy1xk/fjyMjIwQFhaG8+fPIyoqCnp6ejh37hwaNWqERYsW4fDhw1i2bBlsbGzg6+vLrRscHIyYmBgEBARgwoQJSE5Oxvr163HlyhWcPXsWampq77Q/9+/fx6BBgzB8+HD4+fnhp59+gr+/P2xtbWFtbV2ttP744w/s3bsXY8aMgY6ODtauXYuBAwfi8ePHMDAwAADcvHkTDg4O0NXVxfTp06GmpobIyEg4Ozvj999/h729PYCSm//w8HCMGDECHTp0QG5uLi5evIjLly+jZ8+e3DaLi4vh6uqKjh07YunSpThy5AhCQkJQVFSEefPmKc1nZcdw48aNsLa2Rr9+/VCnTh38+uuvGDNmDGQyGcaOHVutMikoKEBBQQH3PTc3t1rrE0LI54IqFoQQUkbr1q3Rvn177NixAx4eHjA3N690nfr16+Pw4cMQCAQYM2YM7t+/j2XLliE4OJh7Ej5y5EiYm5vjp59+4ioWf/zxBzZt2oTY2Fh4e3tz6XXt2hWurq7YvXs3L/xt3L17F6dPn4aDgwMAwNPTEw0bNkR0dDSWL19erbRu376NW7duwdLSkstnmzZtsGPHDm7EqO+//x5v3rzBH3/8gcaNGwMAfH190bx5c0yfPh2///47ACA+Ph69e/dGVFRUhdt8/fo1XF1dsXbtWgDAmDFj0LdvXyxZsgQTJkzgKg2lVXYMf//9d2hoaHDfx40bB1dXV6xcubLaFYvw8HCEhYVVax1CCPkcUVMoQgipAcOHD4dAIOC+29vbgzGG4cOHc2Gqqqqws7PDw4cPubDdu3dDLBajZ8+eyMjI4D62trbQ1tZGYmLiO+fNysqKq1QAJU/tmzdvzstHVfXo0YOrVAAlN/C6urpcWsXFxTh27Bg8PDy4SgUAGBsbw9vbG3/88Qf3RF9PTw83b95EUlJSpdstPcytfNjbwsJCnDhxotr7AIBXqZBKpcjIyICTkxMePnwIqVRarbRmzZoFqVTKfZ48efJWeSKEkE8dvbEghJAa0KhRI953sVgMAGjYsKFCeOm+E0lJSZBKpTA0NFSablpaWo3nDSiZ2bu6fTiqklZ6ejry8/PRvHlzhXgtW7aETCbDkydPYG1tjXnz5uGbb75Bs2bNYGNjA1dXV/j4+KB169a89VRUVHiVFABo1qwZALz1nB1nz55FSEgI/vzzT+Tn5/OWSaVS7vhVhVAo/Kg79RNCyIdCFQtCCKkB5Y3GpCy8dKdjmUwGQ0NDxMbGKl2/on4d75q3sp2fP3Rajo6OePDgAQ4cOIBjx45h06ZNWLVqFSIiIjBixIhqp1dVDx48QPfu3dGiRQusXLkSDRs2hLq6Og4fPoxVq1ZBJpO9t20TQsjnjCoWhBCiROlmTe+TpaUlTpw4gc6dO/Oa53yqJBIJNDU1cffuXYVld+7cgYqKCu8tjr6+PgICAhAQEIC8vDw4OjoiNDSUV7GQyWR4+PAh95YCAO7duwcAFfZ/Ke8Y/vrrrygoKMDBgwd5b2BqotkZIYR8yahiQQghSmhpaQHAe59czdPTExs2bMD8+fOxaNEi3rKioiLk5eV9UrNGq6qqolevXjhw4AA3PC8APH/+HNu3b0eXLl2gq6sLAMjMzORGkgIAbW1tNGnSRGkfhfXr13OdtxljWL9+PdTU1NC9e/dy81LeMZS/dSn9lkUqlSI6Orr6O0xILaNZqcnHhCoWhBCihK2tLQDgf//7H4YMGQI1NTX07du3xrfj5OSE4OBghIeH4+rVq+jVqxfU1NSQlJSE3bt3Y82aNRg0aFCNb/d9WrBgAY4fP44uXbpgzJgxqFOnDiIjI1FQUIClS5dy8aysrODs7AxbW1vo6+vj4sWLiIuL43XUBkomvjty5Aj8/Pxgb2+PhIQExMfHY/bs2RU2FSvvGPbq1Qvq6uro27cvgoODkZeXhx9//BGGhob4999/30+hEELIF4AqFoQQosRXX32F+fPnIyIiAkeOHIFMJkNycvJ72VZERARsbW0RGRmJ2bNno06dOjA3N8ewYcPQuXPn97LN98na2hpnzpzBrFmzEB4eDplMBnt7e2zbto2bwwIAJkyYgIMHD+LYsWMoKCiAmZkZFixYwE1sJ6eqqoojR45g9OjRmDZtGnR0dBASEoK5c+dWmI/yjmHz5s0RFxeH77//HlOnToWRkRFGjx4NiUSCwMDA91ImhBDyJRCwt+lxRwghhHwA/v7+iIuLQ15eXm1npcpyc3MhFoshlUq5Zl+EEPIpq+p1jeaxIIQQQgghhLwzagpFCCEfuby8vEqf2EskknKHgq3Mf//9V+FyDQ2Nas3rQAgh5MtEFQtCCPnILV++HGFhYRXGSU5OrnDo1YoYGxtXuNzPzw8xMTFvlTYhhJAvB/WxIISQj9zDhw/x8OHDCuN06dIFIpHordI/ceJEhctNTExgZWX1Vml/iaiPBSHkc1PV6xpVLAghhJAaRBULQsjnhjpvE0IIIYQQQj4YqlgQUkWnTp2CQCBAXFxcbWflk/Yhy9Hf3/+t+x0QQgghpHqo8zYhpNry8/OxdOlSODs7w9nZubazQz5jp06dQteuXasUl1r2ki+R+cz42s5ClaQsdq/tLJAPgCoWhJBqy8/P50YpoooFeZ9atmyJrVu38sJmzZoFbW1t/O9//6ulXBFCCFGGKhaEfCD5+fnQ1NSs7WyQz4BMJkNhYeFbjwL1Kalfvz6GDRvGC1u8eDHq1aunEF7al1RGhBDysaA+FoT8f6mpqQgMDET9+vUhFAphbW2Nn376SSGeTCbDwoULYWpqCpFIhO7du+P+/fu8OM7OzrCxscGlS5fg6OgITU1NzJ49GwBw4MABuLu7w8TEBEKhEJaWlpg/fz6Ki4vLTaNTp07Q0NCAhYUFIiIiuDh5eXnQ0tLCxIkTFfL59OlTqKqqIjw8nAvLycnB5MmTYW5uDqFQCFNTU/j6+iIjIwMAUFhYiLlz58LW1hZisRhaWlpwcHBAYmIil0ZKSgokEgkAICwsDAKBAAKBAKGhodUq76qU45kzZzB48GA0atQIQqEQDRs2xOTJk/Hq1SuF9Pbv3w8bGxuIRCLY2Nhg37591cpPaRcuXICrqyvEYjE0NTXh5OSEs2fP8uKEhoZCIBDg3r17GDZsGMRiMSQSCebMmQPGGJ48eYJvvvkGurq6MDIywooVKxS2U1BQgJCQEDRp0oTbv+nTp6OgoIAXTyAQYNy4cYiNjYW1tTWEQiGOHDkCALh27RqcnJygoaEBU1NTLFiwANHR0RAIBEhJSeGlk5CQAAcHB2hpaUFHRwfu7u64efMmL46/vz+0tbWRmpoKDw8PaGtrQyKRYOrUqQrnqEwmw5o1a9CqVSuIRCJIJBK4urri4sWLAAAnJye0adNGaRk3b94cLi4ulR+MKiqvjOR9ek6dOsWLn5KSAoFAoDA/x507dzBo0CDo6+tDJBLBzs4OBw8erLF8EkLI54zeWBAC4Pnz5+jYsSN3cyKRSJCQkIDhw4cjNzcXkyZN4uIuXrwYKioqmDp1KqRSKZYuXYqhQ4fiwoULvDQzMzPh5uaGIUOGYNiwYahfvz4AICYmBtra2pgyZQq0tbVx8uRJzJ07F7m5uVi2bBkvjezsbPTu3Ruenp7w8vLCrl27MHr0aKirqyMwMBDa2tro378/du7ciZUrV/JmXt6xYwcYYxg6dCiAkkqIg4MDbt++jcDAQLRv3x4ZGRk4ePAgnj59inr16iE3NxebNm2Cl5cXgoKC8OLFC2zevBkuLi7466+/0LZtW0gkEmzcuBGjR49G//79MWDAAABA69atq1XmVSnH3bt3Iz8/H6NHj4aBgQH++usvrFu3Dk+fPsXu3bu5eMeOHcPAgQNhZWWF8PBwZGZmIiAgAKamptXKEwCcPHkSbm5usLW1RUhICFRUVBAdHY1u3brhzJkz6NChAy/+t99+i5YtW2Lx4sWIj4/HggULoK+vj8jISHTr1g1LlixBbGwspk6diq+++gqOjo4ASm7K+/Xrhz/++AMjR45Ey5Ytcf36daxatQr37t3D/v37FfK1a9cujBs3DvXq1YO5uTlSU1PRtWtXCAQCzJo1C1paWti0aROEQqHCfm3duhV+fn5wcXHBkiVLkJ+fj40bN6JLly64cuUKr5N7cXExXFxcYG9vj+XLl+PEiRNYsWIFLC0tMXr0aC7e8OHDERMTAzc3N4wYMQJFRUU4c+YMzp8/Dzs7O/j4+CAoKAg3btyAjY0Nt97ff/+Ne/fu4fvvv6/28amIsjLKycmp8vo3b95E586d0aBBA8ycORNaWlrYtWsXPDw8sGfPHvTv31/pegUFBbzKYG5u7rvuCiGEfJoYIYQNHz6cGRsbs4yMDF74kCFDmFgsZvn5+SwxMZEBYC1btmQFBQVcnDVr1jAA7Pr161yYk5MTA8AiIiIUtpWfn68QFhwczDQ1Ndnr168V0lixYgUXVlBQwNq2bcsMDQ1ZYWEhY4yxo0ePMgAsISGBl2br1q2Zk5MT933u3LkMANu7d6/C9mUyGWOMsaKiIt6+McZYdnY2q1+/PgsMDOTC0tPTGQAWEhKikFZlqlOOysoqPDycCQQC9ujRIy6sbdu2zNjYmOXk5HBhx44dYwCYmZlZlfMmk8lY06ZNmYuLC1cm8nxYWFiwnj17cmEhISEMABs5ciQXVlRUxExNTZlAIGCLFy/mwrOzs5mGhgbz8/PjwrZu3cpUVFTYmTNneHmIiIhgANjZs2e5MABMRUWF3bx5kxd3/PjxTCAQsCtXrnBhmZmZTF9fnwFgycnJjDHGXrx4wfT09FhQUBBv/f/++4+JxWJeuJ+fHwPA5s2bx4vbrl07Zmtry30/efIkA8AmTJigtBwZYywnJ4eJRCI2Y8YM3vIJEyYwLS0tlpeXp7BuVVhbW/PObcbKLyP5+ZaYmMgLT05OZgBYdHQ0F9a9e3fWqlUr3u9QJpOxTp06saZNm5abH/m5UPYjlUrfav8IqQ6zGYc+iQ/5tEml0ipd16gpFPniMcawZ88e9O3bF4wxZGRkcB8XFxdIpVJcvnyZix8QEAB1dXXuu4ODAwAozIwsFAoREBCgsD0NDQ3u7xcvXiAjIwMODg7Iz8/HnTt3eHHr1KmD4OBg7ru6ujqCg4ORlpaGS5cuAQB69OgBExMTxMbGcvFu3LiBa9eu8dqg79mzB23atFH61FUgEAAAVFVVuX2TyWTIyspCUVER7OzseGVQE6pSjqXL6uXLl8jIyECnTp3AGMOVK1cAAP/++y+uXr0KPz8/iMViLn7Pnj2rPVv01atXkZSUBG9vb2RmZnLnwcuXL9G9e3ecPn0aMpmMt86IESO4v1VVVWFnZwfGGIYPH86F6+npoXnz5rx92717N1q2bIkWLVrwzrlu3boBAK/5GVDSrKjs/hw5cgRff/012rZty4Xp6+tzb6nkjh8/jpycHHh5efG2paqqCnt7e4VtAcCoUaN43x0cHHj537NnDwQCAUJCQhTWlZ9PYrEY33zzDff2DCh5G7Jz5054eHhAS0tLYd13oayMqiorKwsnT56Ep6cn97vMyMhAZmYmXFxckJSUhNTUVKXrzpo1C1KplPs8efLkXXaDEEI+WdQUinzx0tPTkZOTg6ioKERFRSmNk5aWhrp16wIAGjVqxFsmD8/OzuaFN2jQgHfjLHfz5k18//33OHnypEKTCalUyvtuYmKicPPVrFkzACVtxDt27AgVFRUMHToUGzdu5DqIx8bGQiQSYfDgwdx6Dx48wMCBA8stB7ktW7ZgxYoVuHPnDt68ecOFW1hYVLpudVSlHB8/foy5c+fi4MGDCuUrL6tHjx4BAJo2baqwjebNm1erQpSUlAQA8PPzKzeOVCrl8qpsP8RiMUQiEerVq6cQnpmZydvW7du3uf4qZaWlpfG+Kyv/R48e4euvv1YIb9KkCe+7fL/klZayys6iKu8vUVrdunV5x+DBgwcwMTGBvr6+0jTlfH19sXPnTpw5cwaOjo44ceIEnj9/Dh8fnwrXexvvco7ev38fjDHMmTMHc+bMURonLS0NDRo0UAgXCoVKm58RQsiXhioW5IsnfwI9bNiwcm8oW7dujVu3bgEArx9DaazMGPqln7bL5eTkwMnJCbq6upg3bx4sLS0hEolw+fJlzJgxQ+FpeFX5+vpi2bJl2L9/P7y8vLB9+3b06dOH9wS/KrZt2wZ/f394eHhg2rRpMDQ05DqAP3jw4K3yVp7KyrG4uBg9e/ZEVlYWZsyYgRYtWkBLSwupqanw9/d/67KqiDzNZcuW8d4ClKatrc37rmw/qnKOyGQytGrVCitXrlQat2HDhrzvys6nqpLv19atW2FkZKSwvE4d/r+C8vL/NlxcXFC/fn1s27YNjo6O2LZtG4yMjNCjR48a24acsjKSvz0pS1lHdACYOnVquZ3Ky1bYCCGE8FHFgnzxJBIJdHR0UFxcXOHNjrxi8S5OnTqFzMxM7N27l+vECwDJyclK4z979gwvX77kvbW4d+8eAPA629rY2KBdu3aIjY2FqakpHj9+jHXr1vHSsrS0xI0bNyrMX1xcHBo3boy9e/fybsjKNncp72atJl2/fh337t3Dli1b4Ovry4UfP36cF8/MzAzA/z2VL+3u3bvV2qalpSWAkif47+PGt+y2/vnnH3Tv3v2ty9PMzExhJC0ACmHy/TI0NKyx/bK0tMTRo0eRlZVV4VsLVVVVeHt7IyYmBkuWLMH+/fsRFBRUo5WXisjfLpXtxC1/0yXXuHFjAICamtp7P/aEEPK5oooF+eKpqqpi4MCB2L59u8LoNUBJU6nymqu8zbYA/pPrwsJCbNiwQWn8oqIiREZGYsqUKVzcyMhISCQS2Nra8uL6+Phg+vTpEAqFMDAwgJubG2/5wIEDMW/ePOzbt0+hnwVjDAKBgJc/+c3uhQsX8Oeff/Ka/Mjn46jOiDvVpaysGGNYs2YNL56xsTHatm2LLVu2YObMmdxbmuPHj+PWrVtcxaMqbG1tYWlpieXLl8Pb21vh7URNnguenp44fPgwfvzxR4wcOZK37NWrV5DJZJX2QXBxccEPP/yAq1evcm9YsrKyeP1t5PF0dXWxaNEidO3aFWpqarzlb7NfAwcOxA8//ICwsDCFY1L6/AFKzs1Vq1YhODgYeXl5Fc4/UdPMzMygqqqK06dPw8PDgwsv+5szNDSEs7MzIiMjMX78eBgbG/OW1+SxJ6Qm0YzW5GNCFQtCUDL0aWJiIuzt7REUFAQrKytkZWXh8uXLOHHiBLKysmpkO506dULdunXh5+eHCRMmQCAQYOvWrQrNqORMTEywZMkSpKSkoFmzZti5cyeuXr2KqKgohZtDb29vTJ8+Hfv27cPo0aMVlk+bNg1xcXEYPHgwAgMDYWtri6ysLBw8eBARERFo06YN+vTpg71796J///5wd3dHcnIyIiIiYGVlhby8PC4tDQ0NWFlZYefOnWjWrBn09fVhY2OjUCl7Fy1atIClpSWmTp2K1NRU6OrqYs+ePQp9LQAgPDwc7u7u6NKlCwIDA5GVlYV169bB2tqal+/KqKioYNOmTXBzc4O1tTUCAgLQoEEDpKamIjExEbq6uvj1119rZP98fHywa9cujBo1ComJiejcuTOKi4tx584d7Nq1C0ePHoWdnV2FaUyfPh3btm1Dz549MX78eG642UaNGiErK4u7udfV1cXGjRvh4+OD9u3bY8iQIZBIJHj8+DHi4+PRuXNnrF+/vlr579q1K3x8fLB27VokJSXB1dUVMpkMZ86cQdeuXTFu3Dgubrt27WBjY8N1WG/fvn31C+wticViDB48GOvWrYNAIIClpSUOHTqk0IcFAH744Qd06dIFrVq1QlBQEBo3boznz5/jzz//xNOnT/HPP/98sHwTQsgn6T2NSkXIJ+f58+ds7NixrGHDhkxNTY0ZGRmx7t27s6ioKMbY/w1buXv3bt56yoatdHJyYtbW1kq3c/bsWdaxY0emoaHBTExM2PTp07khY0sPiSlP4+LFi+zrr79mIpGImZmZsfXr15e7D71792YA2Llz55Quz8zMZOPGjWMNGjRg6urqzNTUlPn5+XHD7MpkMrZo0SJmZmbGhEIha9euHTt06BDz8/NTGLb13LlzzNbWlqmrq1dr6NnqlOOtW7dYjx49mLa2NqtXrx4LCgpi//zzj0I8xhjbs2cPa9myJRMKhczKyort3btXab6r4sqVK2zAgAHMwMCACYVCZmZmxjw9Pdlvv/3GxZEPMZqens5b18/Pj2lpaSmkqeycKCwsZEuWLGHW1tZMKBSyunXrMltbWxYWFsYb0g8AGzt2bLl5dXBwYEKhkJmamrLw8HC2du1aBoD9999/vLiJiYnMxcWFicViJhKJmKWlJfP392cXL16sNP/y/S2tqKiILVu2jLVo0YKpq6sziUTC3Nzc2KVLlxTWX7p0KQPAFi1apHQ/qqO84WbLK6P09HQ2cOBApqmpyerWrcuCg4PZjRs3lJ5HDx48YL6+vszIyIipqamxBg0asD59+rC4uLgq56+qwzISQsinoqrXNQFj5TwqJYTUKmdnZ2RkZFTaL6K0/v374/r160rb3ZMvx6RJkxAZGYm8vLwP1pehMmvWrMHkyZORkpKiMJLW5yY3NxdisRhSqVRhxC1CCPkUVfW6RvNYEPKZ+PfffxEfH/9ehvEkH69Xr17xvmdmZmLr1q3o0qXLR1OpYIxh8+bNcHJy+uwrFYQQ8iWjPhaEfOKSk5Nx9uxZbNq0CWpqarwJ9T6kwsLCSvuiiMXidxo29V1kZWWhsLCw3OWqqqqfZOfcr7/+Gs7OzmjZsiWeP3+OzZs3Izc3t9y5GD6kly9f4uDBg0hMTMT169dx4MABhTif63EhhJAvEVUsCPnE/f777wgICECjRo2wZcsWpfMUfAjnzp1D165dK4wTHR0Nf3//D5OhMgYMGIDff/+93OVmZmZISUn5cBmqIb1790ZcXByioqIgEAjQvn17bN68mTeccW1JT0+Ht7c39PT0MHv2bPTr108hzud6XAgh5EtEfSwIITUiOzsbly5dqjCOtbW1wjCeH8qlS5eUjiglp6Ghgc6dO3/AHBHg8zwu1MeCEPK5qep1jSoWhBBCSA2iigUh5HPzyXTePnXqFAQCAeLi4mo7K+QdOTs7w9nZmfuekpICgUCAmJiY97I9+blz6tSp95L+h+bv78+bTbs6zM3Na62JUW1Tdp6FhoZ+kNnBP2efchnGxMRAIBBQEypCCPnAqI/FRyQ/Px9Lly5VuEEnpLpu3bqFXbt2vVNlpTKhoaEICwtTumzjxo0YNWrUe9nuh/Ldd98hISEBt27d4sKSk5OxYsUKHDt2DE+fPgVQUqnr2rUrgoOD0bp169rK7gdhbm6OR48ecd8lEgmaN2+OKVOmKMzm/iEsWrQIVlZWvBm1CfnSmM+Mr+0sVIpmB/9yUMXiI5Kfn8/dqH0OFQszMzO8evVKYQZootyPP/4ImUxWI2ndunULYWFhcHZ2fm8VC7mNGzdCW1ubF2Zvb/9et1na+zrP4uPj0bdvX+77oUOH8O2336JOnToYOnQo2rRpAxUVFdy5cwd79+7Fxo0bkZycDDMzsxrNx8embdu2+O677wAAz549Q2RkJAYMGFArlclFixZh0KBBChULHx8fDBkyBEKh8IPmhxBCvnSffMUiPz8fmpqatZ0NooRAIIBIJKrtbHwyPtUK2KBBg1CvXr1a2/77OM8ePnyIu3fvIiIiAgDw4MEDDBkyBGZmZvjtt98UOqAvWbIEGzZsgIpKrbcuLdfLly+hpaX1zuk0aNAAw4YN4777+vqiSZMmWLVqVbkVi6KiIshkMqirq7/z9qtCVVX1o5nDgxBCviTv/b9gamoqAgMDUb9+fQiFQlhbW+Onn35SiCeTybBw4UKYmppCJBKhe/fuCrMHOzs7w8bGBpcuXYKjoyM0NTUxe/ZsAMCBAwfg7u4OExMTCIVCWFpaYv78+SguLi43jU6dOkFDQwMWFhbcDQQA5OXlQUtLCxMnTlTI59OnT6Gqqorw8HAuLCcnB5MnT4a5uTmEQiFMTU3h6+uLjIwMACXj+8+dOxe2trYQi8XQ0tKCg4MDEhMTuTRSUlK4sdrDwsIgEAggEAgQGhpapXKW9zfYtWsXwsLC0KBBA+jo6GDQoEGQSqUoKCjApEmTYGhoCG1tbQQEBKCgoEAhnW3btsHW1hYaGhrQ19fHkCFD8OTJE4V4UVFRsLS0hIaGBjp06IAzZ84oxCmvj8WdO3fg6ekJiUQCDQ0NNG/eHP/73/+45Y8ePcKYMWPQvHlzaGhowMDAAIMHD66R9tJv3rxBWFgYmjZtCpFIBAMDA3Tp0gXHjx/n4vj7+0NbWxsPHz6Ei4sLtLS0YGJignnz5qHsWAcymQyrV6+GtbU1RCIR6tevj+DgYKWj3CQkJMDJyQk6OjrQ1dXFV199he3bt/O2W/btwvLly9GpUycYGBhAQ0MDtra2lfZHiomJweDBgwEAXbt25c6lU6dOwc/PD/Xq1cObN28U1uvVqxeaN29eaRlW1bVr1+Dv74/GjRtDJBLByMgIgYGByMzM5MWTt+W/d+8ehg0bBrFYDIlEgjlz5oAxhidPnuCbb76Brq4ujIyMsGLFCt76VenL4+TkhDZt2ihd1rx5c7i4uPDC4uPjIRaL0aVLFwDA0qVL8fLlS0RHRysd1apOnTqYMGECGjZsyAu/c+cOBg0aBH19fYhEItjZ2eHgwYO8OPL+AGfPnsWUKVMgkUigpaWF/v37Iz09XWFbCQkJcHBwgJaWFnR0dODu7o6bN2/y4sjP4QcPHqB3797Q0dHB0KFDAQBnzpzB4MGD0ahRIwiFQjRs2BCTJ09WmGivqoyMjNCyZUskJycD+L/jsXz5cqxevRqWlpYQCoW4detWla6FcjKZDGvWrEGrVq0gEokgkUjg6uqKixcvAiipUL58+RJbtmzhznF5P6Py+lhU9hsEgAsXLsDV1RVisRiamppwcnLC2bNn36psCCHkS/Ne31g8f/4cHTt2hEAgwLhx4yCRSJCQkIDhw4cjNzcXkyZN4uIuXrwYKioqmDp1KqRSKZYuXYqhQ4fiwoULvDQzMzPh5uaGIUOGYNiwYahfvz6Akn8k2tramDJlCrS1tXHy5EnMnTsXubm5WLZsGS+N7Oxs9O7dG56envDy8sKuXbswevRoqKurIzAwENra2ujfvz927tyJlStX8p587dixA4wx7p90Xl4eHBwccPv2bQQGBqJ9+/bIyMjAwYMH8fTpU9SrVw+5ubnYtGkTvLy8EBQUhBcvXmDz5s1wcXHBX3/9hbZt20IikWDjxo0YPXo0+vfvjwEDBgBAtdtsh4eHQ0NDAzNnzsT9+/exbt06qKmpQUVFBdnZ2QgNDcX58+cRExMDCwsLzJ07l1t34cKFmDNnDjw9PTFixAikp6dj3bp1cHR0xJUrV6CnpwcA2Lx5M4KDg9GpUydMmjQJDx8+RL9+/aCvr69wY1XWtWvX4ODgADU1NYwcORLm5uZ48OABfv31VyxcuBAA8Pfff+PcuXMYMmQITE1NkZKSgo0bN8LZ2Rm3bt16pzdUoaGhCA8Px4gRI9ChQwfk5ubi4sWLuHz5Mnr27MnFKy4uhqurKzp27IilS5fiyJEjCAkJQVFREebNm8fFCw4ORkxMDAICAjBhwgQkJydj/fr1uHLlCs6ePcu9hYiJiUFgYCCsra0xa9Ys6Onp4cqVKzhy5Ai8vb3Lze+aNWvQr18/DB06FIWFhfjll18wePBgHDp0CO7uytusOjo6YsKECVi7di1mz56Nli1bAgBatmwJHx8f/Pzzzzh69Cj69OnDrfPff//h5MmTCAkJqXaZlp0UT1VVFXXr1sXx48fx8OFDBAQEwMjICDdv3kRUVBRu3ryJ8+fPK3QM/vbbb9GyZUssXrwY8fHxWLBgAfT19REZGYlu3bphyZIliI2NxdSpU/HVV19Va54GHx8fBAUF4caNG7CxseHC//77b9y7dw/ff/89L/7hw4fRs2dP1KlTcok8dOgQmjRpUq0mXjdv3kTnzp3RoEEDzJw5E1paWti1axc8PDywZ88ehT4J48ePR926dRESEoKUlBSsXr0a48aNw86dO7k4W7duhZ+fH1xcXLBkyRLk5+dj48aN6NKlC65cucKrmBYVFcHFxQVdunTB8uXLud/N7t27kZ+fj9GjR8PAwAB//fUX1q1bh6dPn2L37t1V3j+5N2/e4MmTJzAwMOCFR0dH4/Xr1xg5ciSEQiH09fWrdC2UGz58OGJiYuDm5oYRI0agqKgIZ86cwfnz52FnZ4etW7dyv+ORI0cCACwtLcvNZ1V+gydPnoSbmxtsbW0REhICFRUVREdHo1u3bjhz5gw6dOigNO2CggLeg5rc3NxqlyMhhHwW2Hs0fPhwZmxszDIyMnjhQ4YMYWKxmOXn57PExEQGgLVs2ZIVFBRwcdasWcMAsOvXr3NhTk5ODACLiIhQ2FZ+fr5CWHBwMNPU1GSvX79WSGPFihVcWEFBAWvbti0zNDRkhYWFjDHGjh49ygCwhIQEXpqtW7dmTk5O3Pe5c+cyAGzv3r0K25fJZIwxxoqKinj7xhhj2dnZrH79+iwwMJALS09PZwBYSEiIQlqVkZejjY0Ntw+MMebl5cUEAgFzc3Pjxf/666+ZmZkZ9z0lJYWpqqqyhQsX8uJdv36d1alThwsvLCxkhoaGrG3btrx9ioqKYgB4ZZOcnMwAsOjoaC7M0dGR6ejosEePHvG2Iy8rxpQfyz///JMBYD///LPCPicmJpZfMGW0adOGubu7VxjHz8+PAWDjx4/n5c/d3Z2pq6uz9PR0xhhjZ86cYQBYbGwsb/0jR47wwnNycpiOjg6zt7dnr1694sUtvd9+fn68Y8KYYlkUFhYyGxsb1q1bN164mZkZ8/Pz477v3r1badkUFxczU1NT9u233/LCV65cyQQCAXv48GE5paIoJCSEAVD4yPdB2XHcsWMHA8BOnz6tkM7IkSO5sKKiImZqasoEAgFbvHgxF56dnc00NDR4+6rsPJOnKZeTk8NEIhGbMWMGLz8TJkxgWlpaLC8vjwt7+fIlE4lEXHpSqZQBYB4eHgr7k52dzdLT07lP6X3u3r07a9WqFe/6I5PJWKdOnVjTpk25sOjoaAaA9ejRg3c+TJ48mamqqrKcnBzGGGMvXrxgenp6LCgoiJeH//77j4nFYl64/ByeOXOmQp6VHZfw8HAmEAh4v8uyZchYyXnWq1cvbn//+ecfNmTIEN7vRX48dHV1WVpaGm/9ql4LT548yQCwCRMmKOS1dBlpaWnxzgU5eZkmJyczxqr2G5TJZKxp06bMxcVF4XpkYWHBevbsqbAdufJ+C1KptNx1CKkpZjMOffQf8umT/y+s7Lr23ppCMcawZ88e9O3bF4wxZGRkcB8XFxdIpVJcvnyZix8QEMBrf+vg4ACgpK1zaUKhEAEBAQrb09DQ4P5+8eIFMjIy4ODggPz8fNy5c4cXt06dOggODua+q6urIzg4GGlpadwEXz169ICJiQliY2O5eDdu3MC1a9d47Yv37NmDNm3aKB0RRf5EVlVVlds3mUyGrKwsFBUVwc7OjlcGNcHX15fXVt/e3h6MMQQGBvLi2dvb48mTJygqKgIA7N27FzKZDJ6enrxjZWRkhKZNm3JNFS5evIi0tDSMGjWKd7z8/f0hFosrzFt6ejpOnz6NwMBANGrUiLes9NPr0sfyzZs3yMzMRJMmTaCnp/fO5aWnp4ebN28iKSmp0rjjxo3j5W/cuHEoLCzEiRMnAJQ8+RWLxejZsyevzGxtbaGtrc2V2fHjx/HixQvMnDlToS9AZcN5li6L7OxsSKVSODg4vHU5qKioYOjQoTh48CBevHjBhcfGxqJTp06wsLCodpp79uzB8ePHuY/8N1M6769fv0ZGRgY6duwIAErzP2LECO5vVVVV2NnZgTGG4cOHc+F6enpo3ry5wnWhMmKxGN988w33xhEoeSu1c+dOeHh48PoenDx5EgUFBXBzcwPwf0+fy3ZQB0qaVkokEu7zww8/ACh5i3Py5El4enpy16OMjAxkZmbCxcUFSUlJSE1N5aU1cuRI3vng4OCA4uJibhSm48ePIycnB15eXrzzTVVVFfb29kqbE40ePVohrPRxefnyJTIyMtCpUycwxnDlypVKy/LYsWPc/rZp0wa7d++Gj48PlixZwos3cOBArnmnXFWvhXv27IFAIFD6Bu1thsCtym/w6tWrSEpKgre3NzIzM7nyffnyJbp3747Tp0+XO7jCrFmzIJVKuY+y5qOEEPIleG9NodLT05GTk4OoqChERUUpjZOWloa6desCgMKNpjy8bFv1Bg0aKO0AePPmTXz//fc4efKkwmtoqVTK+25iYqLQibFZs2YAStoHd+zYkbsB27hxI9dBPDY2FiKRiGu/DpR06hw4cGC55SC3ZcsWrFixAnfu3OG1b3+bG7mKlC1H+c1+2SZKYrEYMpkMUqkUBgYGSEpKAmMMTZs2VZquvLIiv8kpG09NTQ2NGzeuMG/ym8HSTVGUefXqFcLDwxEdHY3U1FRev4ayx7K65s2bh2+++QbNmjWDjY0NXF1d4ePjo9DkTEVFRWF/Sp8jAJCUlASpVApDQ0Ol20pLSwNQco4Ale+3MocOHcKCBQtw9epVXlOLd5lfwNfXF0uWLMG+ffvg6+uLu3fv4tKlS7x+RtXh6OiotPN2VlYWwsLC8Msvv3BlIafsOCo7d0UikULaYrFYoZ9GVfj6+mLnzp04c+YMHB0dceLECTx//hw+Pj68ePHx8bCzs+OaWero6AAoafZYVmRkJF68eIHnz5/zHjjcv38fjDHMmTMHc+bMUZqftLQ0NGjQgPte2TVQXhnu1q2b0vTKTlhUp04dmJqaKsR7/Pgx5s6di4MHDypcX6vy+7K3t8eCBQsgEAigqamJli1bcs0kSyvv2laVa+GDBw9gYmICfX39SvNTFVX5DcrL18/Pr9w4UqmUOy6lCYVCGoGKEELwHisW8ic7w4YNK/dC3bp1a26M+PJG8GBlOsuWftoml5OTAycnJ+jq6mLevHmwtLSESCTC5cuXMWPGjLcewtPX1xfLli3D/v374eXlhe3bt6NPnz6VPpkva9u2bfD394eHhwemTZsGQ0NDrgO4/B9eTSmvHCsrX5lMBoFAgISEBKVxlT2tfV/Gjx+P6OhoTJo0CV9//TXEYjEEAgGGDBnyzsOxOjo64sGDBzhw4ACOHTuGTZs2YdWqVYiIiOA9Ma8KmUwGQ0ND3lut0so+ra2uM2fOoF+/fnB0dMSGDRtgbGwMNTU1REdHK3Q4rQ4rKyvY2tpi27Zt8PX1xbZt26Curg5PT893ym9Znp6eOHfuHKZNm4a2bdtCW1sbMpkMrq6uSo+jsvOuqteFqnBxcUH9+vWxbds2ODo6Ytu2bTAyMkKPHj148Q4fPsx7KyoWi2FsbIwbN24opCnvc1G2k7B8/6ZOnarQMVyuSZMmvO9V+Y0CJf0sjIyMFOLJ+4PICYVChVGqiouL0bNnT2RlZWHGjBlo0aIFtLS0kJqaCn9//yr9vurVq6dQZsoou1Z/yGthdcn3fdmyZby+HqV9yOsgIYR8it5bxUIikUBHRwfFxcUV/hMqPfnU2zp16hQyMzOxd+9eXodO+SglZT179kxh6MV79+4BAK/zo42NDdq1a4fY2FiYmpri8ePHWLduHS8tS0tLpTccpcXFxaFx48bYu3cv70lz2df8tTnLraWlJRhjsLCw4J7MKyMfoz8pKYn35PTNmzdITk4ud+QdANwbgKqUl5+fH2/0n9evXyMnJ6cqu1IpfX19BAQEICAgAHl5eXB0dERoaCivYiGTyfDw4UNeWZQ9RywtLXHixAl07txZ6U2UnLxD6Y0bNxRuJiuyZ88eiEQiHD16lPc0NDo6utJ1KzuXfH19MWXKFPz777/Yvn073N3dlT6JfVvZ2dn47bffEBYWxhsgoCpN0N4XVVVVeHt7IyYmBkuWLMH+/fsRFBTEu6G/ceMGHj9+rNAx3t3dHZs2bcJff/1Vbgfe0uTnupqaWpVuwqtCfh4ZGhq+dZrXr1/HvXv3sGXLFvj6+nLhpUdFe5+qei20tLTE0aNHkZWVVeFbi6peM6vyG5TH0dXVrbFjRgghX5r3VrFQVVXFwIEDsX37doWRWICSplLv+kS39LYA/lPMwsJCbNiwQWn8oqIiREZGYsqUKVzcyMhISCQS2Nra8uL6+Phg+vTpEAqFMDAw4Npdyw0cOBDz5s3Dvn37FPpZMMYgEAh4+ZP/I7xw4QL+/PNPXvMH+agtNXUDXR0DBgzArFmzEBYWhm3btvH+YTPGkJWVBQMDA9jZ2UEikSAiIoLXLyYmJqbSfEskEjg6OuKnn37ClClTePteumxUVVUVnkivW7dOYejgt5GZmckbvUZbWxtNmjRR2iZ6/fr1WLt2LZe/9evXQ01NDd27dwdQ8kR+w4YNmD9/PhYtWsRbt6ioCHl5edDT00OvXr2go6OD8PBwuLq68tp4l97vslRVVSEQCHj7nZKSgv3791e6n/JKc3nHxMvLC9999x0mTpyIhw8fKoyc9q6U/SYBYPXq1TW6nery8fHBqlWrEBwcjLy8PF7zJaDkbUX9+vVhZ2fHC58+fTq2b9+OwMBA/Pbbb1wzKbmy+2loaAhnZ2dERkZi/PjxCkPUvs31z8XFBbq6uli0aBG6du2qMO9JVdJUdlwYY1izZk218vK2qnotHDhwIH744QeEhYUp5K30ulpaWlW6XlblN2hrawtLS0ssX74c3t7eCm8navJ/FiE1iWa1Jh+T9zrc7OLFi5GYmAh7e3sEBQXBysoKWVlZuHz5Mk6cOKEwTOXb6tSpE+rWrQs/Pz9MmDABAoEAW7duLbe5hImJCZYsWYKUlBQ0a9YMO3fuxNWrVxEVFaXwz9rb2xvTp0/Hvn37MHr0aIXl06ZNQ1xcHAYPHozAwEDY2toiKysLBw8eREREBNq0aYM+ffpg79696N+/P9zd3ZGcnIyIiAhYWVnx2m1raGjAysoKO3fuRLNmzaCvrw8bG5u3aptfXZaWlliwYAFmzZqFlJQUeHh4QEdHB8nJydi3bx9GjhyJqVOnQk1NDQsWLEBwcDC6deuGb7/9FsnJyYiOjq60jwUArF27Fl26dEH79u0xcuRIWFhYICUlBfHx8bh69SoAoE+fPti6dSvEYjGsrKzw559/4sSJEwrDWb4NKysrODs7w9bWFvr6+rh48SLi4uJ4HbUBQCQS4ciRI/Dz84O9vT0SEhIQHx+P2bNnczcXTk5OCA4ORnh4OK5evYpevXpBTU0NSUlJ2L17N9asWYNBgwZBV1cXq1atwogRI/DVV1/B29sbdevWxT///IP8/Hxs2bJFaV7d3d2xcuVKuLq6wtvbG2lpafjhhx/QpEkTXLt2rcL9bNu2LVRVVbFkyRJIpVIIhUJ069aN6w8inxNg9+7d0NPTK3fo2relq6sLR0dHLF26FG/evEGDBg1w7Nixct8ifijt2rWDjY0Ndu/ejZYtW6J9+/a85fHx8XBzc1Oo7DVt2hTbt2+Hl5cXmjdvzs28zRhDcnIytm/fDhUVFV6fhh9++AFdunRBq1atEBQUhMaNG+P58+f4888/8fTpU/zzzz/Vyruuri42btwIHx8ftG/fHkOGDIFEIsHjx48RHx+Pzp07Y/369RWm0aJFC1haWmLq1KlITU2Frq4u9uzZo3TelfehqtfCrl27wsfHB2vXrkVSUhLXfO7MmTPo2rUr93u1tbXFiRMnsHLlSpiYmMDCwkLpkMBV+Q2qqKhg06ZNcHNzg7W1NQICAtCgQQOkpqYiMTERurq6+PXXXz9IORFCyCerpoahKs/z58/Z2LFjWcOGDZmamhozMjJi3bt3Z1FRUYyx/xsydPfu3bz1lA0h6eTkxKytrZVu5+zZs6xjx45MQ0ODmZiYsOnTp3NDxpYeclOexsWLF9nXX3/NRCIRMzMzY+vXry93H3r37s0AsHPnzildnpmZycaNG8caNGjA1NXVmampKfPz8+OG2ZXJZGzRokXMzMyMCYVC1q5dO3bo0CGlw4ueO3eO2draMnV19WoNPVteOcqHXfz777954fLhEeVDp8rt2bOHdenShWlpaTEtLS3WokULNnbsWHb37l1evA0bNjALCwsmFAqZnZ0dO336NHNycqp0uFnGGLtx4wbr378/09PTYyKRiDVv3pzNmTOHW56dnc0CAgJYvXr1mLa2NnNxcWF37txRGFL1bYabXbBgAevQoQPT09NjGhoarEWLFmzhwoW8IXr9/PyYlpYWe/DgAevVqxfT1NRk9evXZyEhIay4uFghzaioKGZra8s0NDSYjo4Oa9WqFZs+fTp79uwZL97BgwdZp06dmIaGBtPV1WUdOnRgO3bs4G237PmwefNm1rRpUyYUClmLFi1YdHR0ucOAlh1288cff2SNGzdmqqqqSstp165dCsO8Vkd555Dc06dPueMsFovZ4MGD2bNnzxTO6/LSkR+HsspeB6oy3GxpS5cuZQDYokWLeOE5OTmsTp06bNeuXeXu8/3799no0aNZkyZNmEgk4s6hUaNGsatXryrEf/DgAfP19WVGRkZMTU2NNWjQgPXp04fFxcVxccr7jZZ3ficmJjIXFxcmFouZSCRilpaWzN/fn128eJGLU17ZMcbYrVu3WI8ePZi2tjarV68eCwoKYv/880+VytDMzKzS4Zrlx2PZsmUKy6pzLSwqKmLLli1jLVq0YOrq6kwikTA3Nzd26dIlLs6dO3eYo6Mj09DQYAC430DZ4WblKvsNMsbYlStX2IABA5iBgQETCoXMzMyMeXp6st9++63C/S6tqsMyEkLIp6Kq1zUBY2/RC/IT5uzsjIyMjErb+ZfWv39/XL9+XWEmcPJ58vf3R1xcnNJRgD4nBw4cgIeHB06fPs0N7/wlWLNmDSZPnoyUlBRe85tdu3Zh6NChyMjIqPYADYSUlpubC7FYDKlUqjBaFyGEfIqqel17b/NYfC7+/fdfxMfHKwxJScin7scff0Tjxo3RpUuX2s7KB8MYw+bNm+Hk5KQwvKuenh7Wrl1LlQpCCCHkLb3XPhafsuTkZJw9exabNm2Cmpoab0K9D6mwsLDSvihisbjCUYm+BK9evap0DH59fX2lc6B8aX755Rdcu3YN8fHxWLNmjUJ/AqlUilevXlWYhrLhTj9mL1++xMGDB5GYmIjr16/jwIEDCnF69epVCzkjhBBCPh9UsSjH77//joCAADRq1AhbtmyptRupc+fOoWvXrhXGiY6Ohr+//4fJ0Edq586dSmdkLy0xMRHOzs4fJkMfMS8vL2hra2P48OEYM2aMwvKJEyeW26Fc7lNrQZmeng5vb2/o6elh9uzZ6NevX21niRBCCPnsfHF9LD412dnZuHTpUoVxrK2tFYaz/NL8+++/uHnzZoVxbG1ta3Suhs/VrVu38OzZswrj0Dj/hJSP+lgQQj43Vb2uUcWCEEIIqUFUsSCEfG6o8zYhhBBCCCHkg6GKBakRp06dgkAgQFxcXG1nhaBkWOUvsT9J2f1OSUmBQCBATExMreXpfQkNDS131vYPzdzc/K36edF1gxBCPi/UeZuQGpafn4+lS5d+sTf35NPm7OyM33//HQAgEAigra0NY2NjdOjQAb6+vujZs2ct57Bi586dw7FjxzBp0iTo6enVdnYIee/MZ8Z/8G2mLHb/4NsknwaqWBBSw/Lz8xEWFgYAtVaxOHbsWK1s92NjZmaGV69eQU1NrbazUuO+//57zJw5872kbWpqivDwcAAlQ/Xev38fe/fuxbZt2+Dp6Ylt27bxyvTu3btQUfk4XoCfO3cOYWFh8Pf3p4oFIYR8YFSxIB+F/Px8aGpq1nY2PnnycvyY5utgjOH169e1MteKQCCASCT64Nv9EOrUqYM6dd7PJVwsFmPYsGG8sMWLF2PChAnYsGEDzM3NsWTJEm6ZUCh8L/kghBDyafk4HjGRj15qaioCAwNRv359CIVCWFtb46efflKIJ5PJsHDhQpiamkIkEqF79+64f/8+L46zszNsbGxw6dIlODo6QlNTE7NnzwYAHDhwAO7u7jAxMYFQKISlpSXmz5+P4uLictPo1KkTNDQ0YGFhgYiICC5OXl4etLS0MHHiRIV8Pn36FKqqqtxTWQDIycnB5MmTYW5uDqFQCFNTU/j6+iIjIwNAyWSFc+fOha2tLcRiMbS0tODg4IDExEQujZSUFEgkEgBAWFgYBAIBBAIBQkNDq1TO8jbnO3fuxOzZs2FkZAQtLS3069cPT548qXI5lm2GJU93165dCAsLQ4MGDaCjo4NBgwZBKpWioKAAkyZNgqGhIbS1tREQEICCggLe9qKjo9GtWzcYGhpCKBTCysoKGzduVNgHc3Nz9OnTB0ePHoWdnR00NDQQGRkJJycntGnTRul+N2/eHC4uLlUqI7moqChYWlpCQ0MDHTp0wJkzZxTiKOtjce3aNfj7+6Nx48YQiUQwMjJCYGAgMjMzFdY/deoU7OzsIBKJYGlpicjISKV9GwQCAcaNG4f9+/fDxsaG+40cOXJEIc0rV67Azc0Nurq60NbWRvfu3XH+/HlenDdv3iAsLAxNmzaFSCSCgYEBunTpguPHj3NxlOXj+PHj6NKlC/T09KCtrY3mzZtz58S7UlVVxdq1a2FlZYX169fzJqQs28ciKysLU6dORatWraCtrQ1dXV24ubnhn3/+UZp2cXFxpec7AFy4cAGurq4Qi8XQ1NSEk5MTzp49yy0PDQ3FtGnTAAAWFhbc7y8lJYWLs23bNtja2kJDQwP6+voYMmSIwraSkpIwcOBAGBkZQSQSwdTUFEOGDKl0Ek5CCPnS0RsLUqnnz5+jY8eO3M2TRCJBQkIChg8fjtzcXEyaNImLu3jxYqioqGDq1KmQSqVYunQphg4digsXLvDSzMzMhJubG4YMGYJhw4ahfv36AICYmBhoa2tjypQp0NbWxsmTJzF37lzk5uZi2bJlvDSys7PRu3dveHp6wsvLC7t27cLo0aOhrq6OwMBAaGtro3///ti5cydWrlwJVVVVbt0dO3aAMYahQ4cCKKmEODg44Pbt2wgMDET79u2RkZGBgwcP4unTp6hXrx5yc3OxadMmeHl5ISgoCC9evMDmzZvh4uKCv/76C23btoVEIsHGjRsxevRo9O/fHwMGDAAAtG7dulplvnDhQggEAsyYMQNpaWlYvXo1evTogatXr/Ke/JdXjuUJDw+HhoYGZs6cifv372PdunVQU1ODiooKsrOzERoaivPnzyMmJgYWFhaYO3cut+7GjRthbW2Nfv36oU6dOvj1118xZswYyGQyjB07lredu3fvwsvLC8HBwQgKCkLz5s2hra2NoKAg3LhxAzY2Nlzcv//+G/fu3cP3339f5fLZvHkzgoOD0alTJ0yaNAkPHz5Ev379oK+vj4YNG1a47vHjx/Hw4UMEBATAyMgIN2/eRFRUFG7evInz589zN+tXrlyBq6srjI2NERYWhuLiYsybN4+rOJb1xx9/YO/evRgzZgx0dHSwdu1aDBw4EI8fP4aBgQEA4ObNm3BwcICuri6mT58ONTU1REZGcv0a7O3tAZTcIIeHh2PEiBHo0KEDcnNzcfHiRVy+fLncPg43b95Enz590Lp1a8ybNw9CoRD379/n3Xi/K1VVVXh5eWHOnDn4448/4O6uvJ31w4cPsX//fgwePBgWFhZ4/vw5V7m8desWTExMePGrcr6fPHkSbm5usLW1RUhICFRUVLjK7pkzZ9ChQwcMGDAA9+7dw44dO7Bq1SrUq1cPALhjtnDhQsyZMweenp4YMWIE0tPTsW7dOjg6OuLKlSvQ09NDYWEhXFxcUFBQgPHjx8PIyAipqak4dOgQcnJyIBaLFfa3oKCAVxHPzc2tkfImhJBPDiOkEsOHD2fGxsYsIyODFz5kyBAmFotZfn4+S0xMZABYy5YtWUFBARdnzZo1DAC7fv06F+bk5MQAsIiICIVt5efnK4QFBwczTU1N9vr1a4U0VqxYwYUVFBSwtm3bMkNDQ1ZYWMgYY+zo0aMMAEtISOCl2bp1a+bk5MR9nzt3LgPA9u7dq7B9mUzGGGOsqKiIt2+MMZadnc3q16/PAgMDubD09HQGgIWEhCikVRl5OTZo0IDl5uZy4bt27WIA2Jo1axTKQFk5Ojk58fZPnq6NjQ1XNowx5uXlxQQCAXNzc+Ot//XXXzMzMzNemLJj4+Liwho3bswLMzMzYwDYkSNHeOE5OTlMJBKxGTNm8MInTJjAtLS0WF5enkL6yhQWFjJDQ0PWtm1b3vGIiopiAHj7nZyczACw6OjoCvdjx44dDAA7ffo0F9a3b1+mqanJUlNTubCkpCRWp04dVvbSCYCpq6uz+/fvc2H//PMPA8DWrVvHhXl4eDB1dXX24MEDLuzZs2dMR0eHOTo6cmFt2rRh7u7uFZZDSEgILx+rVq1iAFh6enqF61XGycmJWVtbl7t83759CueimZkZ8/Pz476/fv2aFRcX89ZLTk5mQqGQzZs3jwur6vkuk8lY06ZNmYuLC/d7ZKzkWFpYWLCePXtyYcuWLWMAWHJyMm/7KSkpTFVVlS1cuJAXfv36dVanTh0u/MqVKwwA2717d7llUJb8WJT9SKXSKqdByNsym3Hog3/Il0cqlVbpukZNoUiFGGPYs2cP+vbtC8YYMjIyuI+LiwukUikuX77MxQ8ICOC173dwcABQ8gSzNKFQiICAAIXtlX4a/+LFC2RkZMDBwQH5+fm4c+cOL26dOnUQHBzMfVdXV0dwcDDS0tK42cp79OgBExMTxMbGcvFu3LiBa9eu8dqQ79mzB23atEH//v0V8iR/gq2qqsrtm0wmQ1ZWFoqKimBnZ8crg5rg6+sLHR0d7vugQYNgbGyMw4cP8+KVV44VpVu60629vT0YYwgMDOTFs7e3x5MnT1BUVMSFlT42UqkUGRkZcHJywsOHDxWaiFhYWCg0bRKLxfjmm2+4t0VASROYnTt3wsPDA1paWlXah4sXLyItLQ2jRo3inWv+/v5KnyaXVXo/Xr9+jYyMDHTs2BEAuONYXFyMEydOwMPDg/d0vUmTJnBzc1Oabo8ePWBpacl9b926NXR1dblzv7i4GMeOHYOHhwcaN27MxTM2Noa3tzf++OMP7km3np4ebt68iaSkpEr3R07eUfnAgQOQyWRVXq+6tLW1AZT8PssjFAq5ztzFxcXIzMzkmmYp+61Udr5fvXoVSUlJ8Pb2RmZmJncNevnyJbp3747Tp09Xus979+6FTCaDp6cn7zpmZGSEpk2bck0a5efQ0aNHkZ+fX6UymTVrFqRSKfdR1oyLEEK+BFSxIBVKT09HTk4OoqKiIJFIeB/5DW1aWhoXv1GjRrz169atC6Ck2VJpDRo0UNrB+ObNm+jfvz/EYjF0dXUhkUi4CkDZm1cTExOFm9FmzZoBANemWkVFBUOHDsX+/fu5m4TY2FiIRCIMHjyYW+/Bgwe85jnl2bJlC1q3bs21e5dIJIiPj6/xttdNmzblfRcIBGjSpAmvrThQfjmWp+zxkd9ElW0+JBaLIZPJePt19uxZ9OjRA1paWtDT04NEIuHa7yurWCjj6+uLx48fc/0hTpw4gefPn8PHx6fK+/Do0SMAimWkpqbGu2EvT1ZWFiZOnIj69etDQ0MDEomEy698P9LS0vDq1Ss0adJEYX1lYYBi2QIl57/83E9PT0d+fj6aN2+uEK9ly5aQyWTcDem8efOQk5ODZs2aoVWrVpg2bRquXbtW4X59++236Ny5M0aMGIH69etjyJAh2LVrV41XMvLy8gCAVxEoSyaTYdWqVWjatCmEQiHq1asHiUSCa9euKf2tVHa+yytYfn5+CtehTZs2oaCgoNLfYFJSEhhjaNq0qUIat2/f5q5jFhYWmDJlCjZt2oR69erBxcUFP/zwQ4XpC4VC6Orq8j6EEPIloj4WpELym5Jhw4bBz89PaZzWrVvj1q1bAMDrx1Ca/Am1nLIRgnJycuDk5ARdXV3MmzcPlpaWEIlEuHz5MmbMmPHWN0i+vr5YtmwZ9u/fDy8vL2zfvh19+vSp0tPt0rZt2wZ/f394eHhg2rRpMDQ05DqAP3jw4K3y9q6qO9JSecensuP24MEDdO/eHS1atMDKlSvRsGFDqKur4/Dhw1i1apXCsSkvXy4uLqhfvz62bdsGR0dHbNu2DUZGRujRo0e19uNdeHp64ty5c5g2bRratm0LbW1tyGQyuLq6vtNNeFXP/apwdHTEgwcPcODAARw7dgybNm3CqlWrEBERgREjRihdR0NDA6dPn0ZiYiLi4+Nx5MgR7Ny5E926dcOxY8fKzV913bhxA0D5FSwAWLRoEebMmYPAwEDMnz8f+vr6UFFRwaRJk96qjOXrLFu2DG3btlUaR/4mpaI0BAIBEhISlJZF6fVXrFgBf39/rvwnTJiA8PBwnD9/HqamptXOPyGEfCmoYkEqJJFIoKOjg+Li4gpv/uQVi3dx6tQpZGZmYu/evXB0dOTCk5OTlcZ/9uwZXr58yXtrce/ePQAlo9TI2djYoF27doiNjYWpqSkeP36MdevW8dKytLTkbpjKExcXh8aNG2Pv3r280XhCQkJ48WpiNuSyTWAYY7h//361O4HXlF9//RUFBQU4ePAg78l86RGxqkJVVRXe3t6IiYnBkiVLsH//fgQFBVXrptfMzAxASRl169aNC3/z5g2Sk5PLHXkKKHlz9ttvvyEsLIzXMb1seRsaGkIkEimMaAZAaVhVSCQSaGpq4u7duwrL7ty5AxUVFd6bI319fQQEBCAgIAB5eXlwdHREaGhouRULoOQNXffu3dG9e3esXLkSixYtwv/+9z8kJibWSOWtuLgY27dvh6amJrp06VJuvLi4OHTt2hWbN2/mhefk5HAdqkur7HyXNzHT1dWtdD/K+/1ZWlqCMQYLCwvuzWZFWrVqhVatWuH777/HuXPn0LlzZ0RERGDBggWVrksIIV8qqliQCqmqqmLgwIHYvn27wmg+QEnzjvJGyXmbbQH8J7yFhYXYsGGD0vhFRUWIjIzElClTuLiRkZGQSCSwtbXlxfXx8cH06dMhFAphYGCg0E5+4MCBmDdvHvbt26fQz4IxBoFAwMuf/OblwoUL+PPPP3k32/L5OHJycqpbBJyff/4Zs2bN4pqbxMXF4d9//8WMGTPeOs13oezYSKVSREdHVzstHx8frFq1CsHBwcjLy1OYL6EydnZ2kEgkiIiI4PXpiYmJqbTMle0HAKxevVohXo8ePbB//348e/aM62dx//59JCQkVCu/pdPs1asXDhw4gJSUFK7y+/z5c2zfvh1dunThmtBkZmZyI0kBJU/TmzRpUmHb/aysLOjr6/PC5E/3yw4d/DaKi4sxYcIE3L59GzNnzqywuY+qqqpCGe/evRupqalK33RUdr7b2trC0tISy5cvh7e3t8LbidLXIfmDhrLnwoABAzBr1iyEhYVh27ZtvAoIYwxZWVkwMDBAbm4uNDU1eXOEtGrVCioqKjVSjoTUNJoFm3xMqGJBKrV48WIkJibC3t4eQUFBsLKyQlZWFi5fvowTJ04gKyurRrbTqVMn1K1bF35+fpgwYQIEAgG2bt1ablMSExMTLFmyBCkpKWjWrBl27tyJq1evIioqSmGmZW9vb0yfPh379u3D6NGjFZZPmzYNcXFxGDx4MAIDA2Fra4usrCwcPHgQERERaNOmDfr06YO9e/eif//+cHd3R3JyMiIiImBlZcW1OwdKmqRYWVlh586daNasGfT19WFjY1OlPhxy+vr66NKlCwICAvD8+XOsXr0aTZo0QVBQUDVKtOb06tUL6urq6Nu3L1ch+PHHH2FoaIh///23Wmm1a9cONjY22L17N1q2bIn27dtXa301NTUsWLAAwcHB6NatG7799lskJycjOjq60j4Wurq6cHR0xNKlS/HmzRs0aNAAx44dU/pWLDQ0FMeOHUPnzp0xevRoFBcXY/369bCxscHVq1erlWe5BQsWcHNNjBkzBnXq1EFkZCQKCgqwdOlSLp6VlRWcnZ1ha2sLfX19XLx4EXFxcRg3bly5ac+bNw+nT5+Gu7s7zMzMkJaWhg0bNsDU1LTCtwvKSKVSbNu2DUDJpIvymbcfPHiAIUOGYP78+RWu36dPH8ybNw8BAQHo1KkTrl+/jtjY2HKPT2Xnu4qKCjZt2gQ3NzdYW1sjICAADRo0QGpqKhITE6Grq4tff/0VALiHCv/73/8wZMgQqKmpoW/fvrC0tMSCBQswa9YspKSkwMPDAzo6OkhOTsa+ffswcuRITJ06FSdPnsS4ceMwePBgNGvWDEVFRdi6dSv3kIUQQkgF3seQVOTz8/z5czZ27FjWsGFDpqamxoyMjFj37t1ZVFQUY+z/ho0sO0SjsuE+KxrO8uzZs6xjx45MQ0ODmZiYsOnTp3NDxiYmJiqkcfHiRfb1118zkUjEzMzM2Pr168vdh969ezMA7Ny5c0qXZ2ZmsnHjxrEGDRowdXV1Zmpqyvz8/LhhdmUyGVu0aBEzMzNjQqGQtWvXjh06dIj5+fkpDM167tw5Zmtry9TV1as19Ky8HHfs2MFmzZrFDA0NmYaGBnN3d2ePHj3ixa2oHMsbbrbs8YmOjmYA2N9//80Llw+fWXro0oMHD7LWrVszkUjEzM3N2ZIlS9hPP/2kMLSnmZlZpUOlLl26lAFgixYtqjBeRTZs2MAsLCyYUChkdnZ27PTp0wr7rez8e/r0Kevfvz/T09NjYrGYDR48mD179kzpcfrtt99Yu3btmLq6OrO0tGSbNm1i3333HROJRLx4ANjYsWMV8lh2GFbGGLt8+TJzcXFh2traTFNTk3Xt2lXhnFywYAHr0KED09PTYxoaGqxFixZs4cKFvKGCyw43+9tvv7FvvvmGmZiYMHV1dWZiYsK8vLzYvXv3qliiJeTDGMs/2trarGnTpmzYsGHs2LFjStdRNtzsd999x4yNjZmGhgbr3Lkz+/PPP8s9L6tyvjNWMhTsgAEDmIGBARMKhczMzIx5enqy3377jRdv/vz5rEGDBkxFRUXh/NyzZw/r0qUL09LSYlpaWqxFixZs7Nix7O7du4wxxh4+fMgCAwOZpaUlE4lETF9fn3Xt2pWdOHGiymVY1WEZCSHkU1HV65qAsbfoWUhILXN2dkZGRkal/SJK69+/P65fv/7WbeQ/hFOnTqFr167YvXs3Bg0aVNvZeW/WrFmDyZMnIyUlReloSh8zDw+Pag8FS74subm5EIvFkEqlNEIUIeSzUNXrGg03S74I//77L+Lj46s1rCl5Pxhj2Lx5M5ycnD76SsWrV69435OSknD48GE4OzvXToYIIYSQjxj1sSCfteTkZJw9exabNm2Cmpoab0K9D6mwsLDSvijVHf72U/Py5UscPHgQiYmJuH79Og4cOKAQJysrC4WFheWmoaqqWmODBVRF48aN4e/vj8aNG+PRo0fYuHEj1NXVMX369A+Wh5qSnp6O4uLicperq6srdP4mhBBCqoMqFuSz9vvvvyMgIACNGjXCli1bYGRkVCv5OHfuHLp27VphnOjoaN4wuZ+b9PR0eHt7Q09PD7Nnz0a/fv0U4gwYMAC///57uWmYmZkpTBL4Prm6umLHjh3477//IBQK8fXXX2PRokUKE7p9Cr766ituckFlnJyccOrUqQ+XIUIIIZ8d6mNByAeQnZ2NS5cuVRjH2toaxsbGHyhHH6dLly4pzNJemoaGBjp37vwBc/T5OHv2rELTrtLq1q2rMEwzeTvUx4IQ8rmp6nWNKhaEEEJIDaKKBSHkc0Odtwkhn7RTp05BIBAgLi6utrPySUtJSYFAIEBMTExtZwXOzs68ju8fU94IIYS8O+pjQQghH7n8/HwsXbpU4cacVKyiYakzMjIgkUgQEhKC0NDQD585QmqI+cz4D7o9mumbVIQqFoQQ8pHLz89HWFgYAFS7YmFmZoZXr14pzDb/MfiY80YIIaT6qCkUIeSzlJ+fX9tZ+CgIBAKIRCKoqqrWdlYUfMx5I4QQUn1UsSCE1IrU1FQEBgaifv36EAqFsLa2xk8//aQQTyaTYeHChTA1NYVIJEL37t0VZk93dnaGjY0NLl26BEdHR2hqamL27NkAgAMHDsDd3R0mJiYQCoWwtLTE/PnzFeZ0KJ1Gp06doKGhAQsLC0RERHBx8vLyoKWlhYkTJyrk8+nTp1BVVUV4eDgXlpOTg8mTJ8Pc3BxCoRCmpqbw9fVFRkYGgJL5TebOnQtbW1uIxWJoaWnBwcEBiYmJXBopKSnc3B1hYWEQCAQQCARVbr6jrB+Dv78/tLW1kZqaCg8PD2hra0MikWDq1KkK5fLLL7/A1tYWOjo60NXVRatWrbBmzRpueWhoKAQCgcJ2Y2JiIBAIKhwe+F3zVtPk+3Lnzh14enpCV1cXBgYGmDhxIl6/fv1et00IIZ8DagpFCPngnj9/jo4dO0IgEGDcuHGQSCRISEjA8OHDkZubi0mTJnFxFy9eDBUVFUydOhVSqRRLly7F0KFDceHCBV6amZmZcHNzw5AhQzBs2DDUr18fQMkNrra2NqZMmQJtbW2cPHkSc+fORW5uLpYtW8ZLIzs7G71794anpye8vLywa9cujB49Gurq6ggMDIS2tjb69++PnTt3YuXKlbwn7Tt27ABjDEOHDgVQUglxcHDA7du3ERgYiPbt2yMjIwMHDx7E06dPUa9ePeTm5mLTpk3w8vJCUFAQXrx4gc2bN8PFxQV//fUX2rZtC4lEgo0bN2L06NHo378/BgwYAABo3br1Ox2D4uJiuLi4wN7eHsuXL8eJEyewYsUKWFpaYvTo0QCA48ePw8vLC927d8eSJUsAALdv38bZs2eVVq5qSlXy9j55enrC3Nwc4eHhOH/+PNauXYvs7Gz8/PPPSuMXFBSgoKCA+56bm/ve80gIIR8jqlgQQj64//3vfyguLsb169dhYGAAABg1ahS8vLwQGhrKmyH99evXuHr1KtTV1QGUzLcwceJE3LhxAzY2Nly8//77DxEREQqzq2/fvh0aGhrc91GjRmHUqFHYsGEDFixYAKFQyC179uwZVqxYgSlTpgAAgoODYW9vj1mzZsHHxwdqamrw9fVFbGwsjh8/DldXV27dbdu2wdHREY0aNQIALFu2DDdu3MDevXvRv39/Lt73338P+SjfdevWRUpKCrdvABAUFIQWLVpg3bp12Lx5M7S0tDBo0CCMHj0arVu3xrBhw96y1Plev36Nb7/9FnPmzOHKpX379ti8eTN38x4fHw9dXV0cPXr0gzZXqkre3icLCwtuZvixY8dCV1cXGzZswNSpU5VW6MLDw7k+MIQQ8iWjplCEkA+KMYY9e/agb9++YIwhIyOD+7i4uEAqleLy5ctc/ICAAN6Nt4ODAwDg4cOHvHSFQiECAgIUtle6UvHixQtkZGTAwcEB+fn5uHPnDi9unTp1eBUTdXV1BAcHIy0tjZvgsEePHjAxMUFsbCwX78aNG7h27Rrvpn/Pnj1o06YNr1IhJ286pKqqyu2bTCZDVlYWioqKYGdnxyuD92XUqFG87w4ODrxy1dPTw8uXL3H8+PH3npeyKsvb+zR27Fje9/HjxwMADh8+rDT+rFmzIJVKuc+TJ0/eex4JIeRjRBULQsgHlZ6ejpycHERFRUEikfA+8opBWloaF1/+BkCubt26AKAwQ3eDBg14FRC5mzdvon///hCLxdDV1YVEIuEqAFKplBfXxMQEWlpavLBmzZoBANdXQEVFBUOHDsX+/fu5DuKxsbEQiUQYPHgwt96DBw94b1TKs2XLFrRu3RoikQgGBgaQSCSIj49XyFtNE4lEXN8Nubp16/LKdcyYMWjWrBnc3NxgamqKwMBAHDly5L3mq6p5qynK+oc0bdqU993S0hIqKirl9hcRCoXQ1dXlfQgh5EtETaEIIR+UTCYDAAwbNgx+fn5K47Ru3Rq3bt0CgHKb4MibE8mVfjMhl5OTAycnJ+jq6mLevHmwtLSESCTC5cuXMWPGDC4v1eXr64tly5Zh//798PLywvbt29GnTx+IxeJqpbNt2zb4+/vDw8MD06ZNg6GhIdcB/MGDB2+Vt6qqStMmQ0NDXL16FUePHkVCQgISEhIQHR0NX19fbNmyBYDyG3MA79TRuqaaXYlEIrx69UrpMnmlUCQSVZpOeftICCGEjyoWhJAPSiKRQEdHB8XFxejRo0e58eQVi3dx6tQpZGZmYu/evXB0dOTCk5OTlcZ/9uwZXr58yXtrce/ePQCAubk5F2ZjY4N27dohNjYWpqamePz4MdatW8dLy9LSUunEbKXFxcWhcePG2Lt3L+/mNSQkhBevNm9s1dXV0bdvX/Tt2xcymQxjxoxBZGQk5syZgyZNmnBvkHJycqCnp8et9+jRo1rK8f8xMzPDyZMn8erVK4WK5927d7k4ZSUlJcHCwoL7fv/+fchkMt45QAghRBFVLAghH5SqqioGDhyI7du3K3TABkqaSpVtBvMu2wL4bzcKCwuxYcMGpfGLiooQGRnJdd4uLCxEZGQkJBIJbG1teXF9fHwwffp0CIVCGBgYwM3Njbd84MCBmDdvHvbt26fQz4IxBoFAwMufvPJw4cIF/Pnnn7wmYJqamgBKbt4/pMzMTK5zPVDSDEzeeVk+CpKlpSUA4PTp0+jXrx8A4OXLl9wbjdrUu3dvREVFITIykjfSmEwmw8aNG6Guro7u3bsrrPfDDz+gV69e3Hd5pbHsMSbkY0AzYZOPCVUsCCEf3OLFi5GYmAh7e3sEBQXBysoKWVlZuHz5Mk6cOIGsrKwa2U6nTp1Qt25d+Pn5YcKECRAIBNi6datCMyo5ExMTLFmyBCkpKWjWrBl27tyJq1evIioqSmF2aG9vb0yfPh379u3D6NGjFZZPmzYNcXFxGDx4MAIDA2Fra4usrCwcPHgQERERaNOmDfr06cONGuXu7o7k5GRERETAysoKeXl5XFoaGhqwsrLCzp070axZM+jr68PGxqZKfTjexYgRI5CVlYVu3brB1NQUjx49wrp169C2bVu0bNkSANCrVy80atQIw4cPx7Rp06CqqoqffvoJEokEjx8/fq/5q0zfvn3Rq1cvTJ48GX/99df/Y+++46I4/v+Bvw7kChwcgkdXBBQjIKJoNChFMaKiRiwELDRFghrbxxoTBLtYotEoEhSJoEERS0RsEdSg0ShWjA3BHukHeAqBm98f/G6/rHfAodjn+Xjc4+HNvnd2dnZZd25nZuHk5ASpVIr9+/cjIyMDixYtUtqIzcnJweDBg9GvXz+cOXMG8fHxGDlyJDp27PgO9oKiKOrDQQdvUxT11hkaGuLcuXMIDAxEcnIyJk2ahLVr16KoqIh5X0JT0NfXx4EDB2BsbIzvv/8eK1euxJdffonIyEil8c2bN8fBgwdx/vx5zJw5Ew8ePMD69esRHBysdB/kv2qPGTNGYblQKMSpU6cQGhqKgwcPYvLkydiwYQPatWsHMzMzADUvg1uyZAkuX76MyZMn4/Dhw4iPj0eXLl0U8ouJiYGpqSmmTZsGX19fJCUlvU7VqGT06NHg8/nYsGEDJkyYgLi4OHz99ddITU2FmlrNfx8aGhrYs2cPrKys8MMPP+Cnn37CuHHjMGnSpDdevoaoqalh//79CA8Px8WLFzFjxgwsWLAA1dXViI+Px7x585Sul5iYCB6Phzlz5iAlJQWTJk3C5s2b33LpKYqiPjwcUtdPdxRFUZ8QNzc3FBQUNDguojYvLy9cvXpV4U3g1IcpPDwcERERyM/PR4sWLV45n9LSUohEIkgkEjpDFEVRHwVVr2v0iQVFUdQrePLkCVJSUpQ+raAoiqKoTxEdY0FRFNUIOTk5yMjIQExMDDQ0NBTe9P22VFZWNjgWRSQSKZ2G90NXVFSEysrKOperq6s32QQAFEVRlOpow4KiKKoRTpw4gcDAQLRq1QpxcXEwMjJ6J+U4ffo0evXqVW9MbGwsAgIC3k6B3qKhQ4fixIkTdS43Nzev82V2FEVR1JtDx1hQFEV9gIqLi3HhwoV6Y2xtbWFsbPyWSvT2XLhwod63cAsEAvTo0eMtloiNjrGgKOpjo+p1jTYsKIqiKKoJ0YYFRVEfGzp4m6IoiqIoiqKot4Y2LCjqA5Seng4Oh/NW3mXwKZLXb3p6OpMWEBCA1q1bv1J+HA7nvXivw4ciNzcXHA4HW7dufddFoSiKohqBDt6mKOqDJpVKERkZCTc3N7i5ub3r4rwVjx8/RnR0NIYMGQIHB4c3tp2AgADExcVBW1sbT58+VZhh6vbt27C2tgYArFixAjNmzHhjZanPsmXLMHfuXBw6dAgeHh4KywcMGICMjAz8888/MDExeQclpKg3p/WclLe6vdxlnm91e9SHhT6xoCjqgyaVShEREcF6uvAm/PLLL7h58+Yb3YaqHj9+jIiICFy6dOmNb6tZs2aQSqX4/fffFZYlJCSAz+e/8TI05H//+x86dOiACRMm4Pnz56xlu3btQmpqKpYuXUobFRRFUW8YbVhQ1CdIKpW+6yJ8cDQ0NMDj8d51Md46Ho8Hd3d37NixQ2HZ9u3b4en57n+91NDQQHR0NHJzc7Fw4UImvaysDFOnTkX37t3xzTffvMMSUhRFfRpow4Ki3kOPHj1CUFAQDA0NwePxYGtriy1btijEyWQyLF68GGZmZuDz+XB3d8edO3dYMW5ubrCzs8OFCxfg4uICTU1NfPfddwCAffv2wdPTEyYmJuDxeLCyssLChQtRXV1dZx5OTk4QCASwsLBAVFQUE1NeXg4tLS1MmTJFoZwPHz6Euro6li5dyqSVlJRg2rRpaN26NXg8HszMzODn54eCggIANS+ACwsLg6OjI0QiEbS0tODs7Iy0tDQmj9zcXOZFaBEREeBwOOBwOAgPD1e5rh8+fIghQ4ZAS0sLBgYGmDZtGioqKhTilI2xWLlyJZycnKCvrw+BQABHR8d6x70kJCSgXbt24PP5cHR0xMmTJxViGjr26enp6Nq1KwAgMDCQ2efa4xHOnj2Lfv36QSQSQVNTE66ursjIyGBtR37TLa9/AwMDfPnll8jMzFQo08iRI5GamoqSkhIm7e+//8bt27cxcuRIpftaUlKCqVOnomXLluDxeGjTpg2WL18OmUymEBcQEACRSARdXV34+/uztqMqeeNh5cqVuH79OgDg+++/R15eHqKjo6GmpqZymX777Tc4OjpCW1sbOjo66NChA9auXdvoMlEURX1q6BgLinrPPH36FN27d2cG/IrFYqSmpmLs2LEoLS3F1KlTmdhly5ZBTU0NM2bMgEQiQWRkJEaNGoWzZ8+y8iwsLET//v3h4+OD0aNHw9DQEACwdetWCIVCTJ8+HUKhEMePH0dYWBhKS0uxYsUKVh7FxcUYMGAAvL294evri507dyI0NBRcLhdBQUEQCoXw8vJCYmIiVq9eDXV1dWbdHTt2gBCCUaNGAahphDg7O+Off/5BUFAQOnfujIKCAuzfvx8PHz5EixYtUFpaipiYGPj6+iI4OBhlZWXYvHkzPDw8cO7cOTg4OEAsFmPjxo0IDQ2Fl5cXhg4dCgCwt7dXqa6fP38Od3d33L9/H5MnT4aJiQm2bduG48ePq7T+2rVrMXjwYIwaNQqVlZX47bffMGLECBw4cEDhl/wTJ04gMTERkydPBo/Hw4YNG9CvXz+cO3cOdnZ2AFQ79u3bt8eCBQsQFhaG8ePHw9nZGQDg5OQEADh+/Dj69+8PR0dHzJ8/H2pqaoiNjUXv3r1x6tQpfP755wCAb775BklJSZg0aRJsbGxQWFiIP//8E//88w86d+7MKvvQoUPxzTffIDk5GUFBQQBqnlZ89tlnCrFAzRMxV1dXPHr0CCEhIWjVqhVOnz6NuXPn4smTJ1izZg0AgBCCr776Cn/++Se++eYbtG/fHnv27IG/v79K9f+ypUuXYu/evQgJCcGaNWvw888/Y+bMmejQoYPKZTp69Ch8fX3h7u6O5cuXAwD++ecfZGRkKG00A0BFRQWrMVpaWvpK5acoivrgEYqi3itjx44lxsbGpKCggJXu4+NDRCIRkUqlJC0tjQAg7du3JxUVFUzM2rVrCQBy9epVJs3V1ZUAIFFRUQrbkkqlCmkhISFEU1OTvHjxQiGPVatWMWkVFRXEwcGBGBgYkMrKSkIIIYcPHyYASGpqKitPe3t74urqynwPCwsjAEhycrLC9mUyGSGEkKqqKta+EUJIcXExMTQ0JEFBQUxafn4+AUDmz5+vkFdD1qxZQwCQnTt3MmnPnj0jbdq0IQBIWloak+7v70/Mzc1Z679cf5WVlcTOzo707t2blQ6AACDnz59n0u7du0f4fD7x8vJi0lQ59oQQ8vfffxMAJDY2lhUnk8lI27ZtiYeHB1OP8nJaWFiQL7/8kkkTiURk4sSJ9dROzT5raWkRQggZPnw4cXd3J4QQUl1dTYyMjEhERATJyckhAMiKFSuY9RYuXEi0tLTIrVu3WPnNmTOHqKurk/v37xNCCNm7dy8BQCIjI5mYqqoq4uzsrHT/VJGUlEQAED09PWJpacnUmaplmjJlCtHR0SFVVVUqb3P+/PnMMa79kUgkjS4/RTWW+ewDb/VDfZokEolK1zXaFYqi3iOEEOzevRuDBg0CIQQFBQXMx8PDAxKJhNVVJTAwEFwul/ku//X67t27rHx5PB4CAwMVtld7lp+ysjIUFBTA2dkZUqkUN27cYMU2a9YMISEhzHcul4uQkBDk5eUxb4Du06cPTExMkJCQwMRdu3YNV65cwejRo5m03bt3o2PHjvDy8lIoE4fDAQCoq6sz+yaTyVBUVISqqip06dJFaXedV3Hw4EEYGxtj+PDhTJqmpibGjx+v0vq166+4uBgSiQTOzs5Ky/fFF1/A0dGR+d6qVSt89dVXOHz4MKqrqxt97JW5dOkS0z2psLCQWf/Zs2dwd3fHyZMnmW4/urq6OHv2LB4/fqzSvo4cORLp6en4999/cfz4cfz77791doPatWsXnJ2d0bx5c9Z+9OnTB9XV1UwXsIMHD6JZs2YIDQ1l1lVXV8e3336rUpmUGTZsGAYMGICioiL8/PPPzDFStUy6urp49uwZjh49qvI2586dC4lEwnwePHjwyuWnKIr6kNGuUBT1HsnPz0dJSQmio6MRHR2tNCYvLw/NmzcHUHNzWps8vbi4mJVuamrKaoDIZWVl4fvvv8fx48cVum9IJBLWdxMTE2hpabHS5FON5ubmonv37lBTU8OoUaOwceNGSKVSaGpqMjMHjRgxglkvOzsbw4YNq7Me5OLi4rBq1SrcuHED//33H5NuYWHR4LqquHfvHtq0acM0ZuTatWun0voHDhzAokWLcOnSJVZXmJfzA4C2bdsqpFlbW0MqlSI/P58ZA9DQsa/P7du3AaDerkQSiQTNmzdHZGQk/P390bJlSzg6OmLAgAHw8/ODpaWl0vUGDBgAbW1tJCYm4tKlS+jatSvatGmD3NxcpeW4cuUKM/6lrv24d+8ejI2NIRQKWctVrf+6dO3aFQcPHkSXLl0aXaYJEyZg586d6N+/P0xNTdG3b194e3ujX79+dW6Px+N9kgP7KYqiXkYbFhT1HpH/mjx69Og6bw7t7e2Zwam1xzHURghhfX/5/QNAzaBZV1dX6OjoYMGCBbCysgKfz0dmZiZmz56tMKBVVX5+flixYgX27t0LX19fbN++HQMHDoRIJGpUPvHx8QgICMCQIUMwc+ZMGBgYMAPAs7OzX6lsTenUqVMYPHgwXFxcsGHDBhgbG0NDQwOxsbHYvn17o/NT9dirkseKFSvqfL+F/Cbe29sbzs7O2LNnD44cOYIVK1Zg+fLlSE5ORv/+/RXW4/F4GDp0KOLi4nD37t16B8jLZDJ8+eWXmDVrltLl8gbp26RqmQwMDHDp0iUcPnwYqampSE1NRWxsLPz8/BAXF/c2i0xRFPXBoQ0LinqPiMViaGtro7q6Gn369KkzTt6weB3p6ekoLCxEcnIyXFxcmPScnByl8Y8fP8azZ89YTy1u3boFAKzZkuzs7NCpUyckJCTAzMwM9+/fx7p161h5WVlZ4dq1a/WWLykpCZaWlkhOTmY9AZg/fz4rTtnTAVWZm5vj2rVrIISw8lHlfRW7d+8Gn8/H4cOHWb9Wx8bGKo2XP02o7datW9DU1GR+RVfl2AN177OVlRUAQEdHp8E8AMDY2BgTJkzAhAkTkJeXh86dO2Px4sVKGxZATXeoLVu2QE1NDT4+PnXma2VlhfLy8gbLYG5ujj/++APl5eWspxZv4n0hqpYJqOnmN2jQIAwaNAgymQwTJkzApk2b8MMPP6BNmzZNXjaKoqiPBW1YUNR7RF1dHcOGDcP27dtx7do1ZrYgufz8/Dq7crzKtgD2043Kykps2LBBaXxVVRU2bdqE6dOnM7GbNm2CWCxmjR0AgDFjxmDWrFng8XjQ19dXuFEdNmwYFixYgD179iiMs5Df5Ncun/xG+uzZszhz5gyrC5impiYAvNIUpQMGDMCRI0eQlJTEdNWSSqV1dkWqTV1dHRwOhzU1b25uLvbu3as0/syZM8jMzGRmUXrw4AH27duHfv36Mfuq6rGXN+5e3mdHR0dYWVlh5cqVGDlypEIXI3ke1dXVKC8vZz1FMjAwgImJidKpduV69eqFhQsXQl9fH0ZGRnXGeXt7Izw8HIcPH1Z4E3ZJSQmEQiGaNWuGAQMGIDo6Ghs3bsTMmTMBANXV1QoN0aagapkKCwuhr6/PLFNTU2OeFNVXNxT1rtA3YVPvE9qwoKj3zLJly5CWloZu3bohODgYNjY2KCoqQmZmJo4dO4aioqIm2Y6TkxOaN28Of39/TJ48GRwOB9u2bVPoRiVnYmKC5cuXIzc3F9bW1kxf++joaGhoaLBiR44ciVmzZmHPnj0IDQ1VWD5z5kzmZj4oKAiOjo4oKirC/v37ERUVhY4dO2LgwIFITk6Gl5cXPD09kZOTg6ioKNjY2KC8vJzJSyAQwMbGBomJibC2toaenh7s7OwUbsyVCQ4Oxvr16+Hn54cLFy7A2NgY27ZtYxor9fH09MTq1avRr18/jBw5Enl5efj555/Rpk0bXLlyRSHezs4OHh4erOlmgZr3b8ipeuytrKygq6uLqKgoaGtrQ0tLC926dYOFhQViYmLQv39/2NraIjAwEKampnj06BHS0tKgo6OD33//HWVlZTAzM8Pw4cPRsWNHCIVCHDt2DH///TdWrVpV5z6rqanh+++/b7BuZs6cif3792PgwIEICAiAo6Mjnj17hqtXryIpKQm5ublo0aIFBg0ahB49emDOnDnIzc2FjY0NkpOTFcb3NAVVyzRu3DgUFRWhd+/eMDMzw71797Bu3To4ODigffv2TV4uiqKoj8obnZuKoqhX8vTpUzJx4kTSsmVLoqGhQYyMjIi7uzuJjo4mhBBmutldu3ax1pNP/Vl7mk5XV1dia2urdDsZGRmke/fuRCAQEBMTEzJr1ixmytjaU63K8zh//jz54osvCJ/PJ+bm5mT9+vV17sOAAQMIAHL69GmlywsLC8mkSZOIqakp4XK5xMzMjPj7+zNTrcpkMrJkyRJibm5OeDwe6dSpEzlw4IDSaV9Pnz5NHB0dCZfLbfTUs/fu3SODBw8mmpqapEWLFmTKlCnk0KFDKk03u3nzZtK2bVvC4/HIZ599RmJjY5mpR2sDQCZOnEji4+OZ+E6dOrHyl2vo2Mvt27eP2NjYkGbNmikc84sXL5KhQ4cSfX19wuPxiLm5OfH29iZ//PEHIaRmquCZM2eSjh07Em1tbaKlpUU6duxINmzYwNpG7elm66JsullCCCkrKyNz584lbdq0IVwul7Ro0YI4OTmRlStXMtMTE1JzHowZM4bo6OgQkUhExowZQy5evPjK080S8n/Tv+bn5ze6TElJSaRv377EwMCAcLlc0qpVKxISEkKePHmi8vZVnZaRoijqQ6HqdY1DSB0/T1IURf1/bm5uKCgoaHBcRG1eXl64evWqwpvAKepjV1paCpFIBIlEAh0dnXddHIqiqNem6nWNvseCoqgm9+TJE6SkpGDMmDHvuigURVEURb0ldIwFRVFNJicnBxkZGYiJiYGGhgbrhXpvU2VlZYNjUUQikdJpeKn3Cz2WFEVRHw7asKAoqsmcOHECgYGBaNWqFeLi4uqdOehNOn36NHr16lVvTGxsLAICAt5OgahXRo8lRVHUh4OOsaAo6qNTXFyMCxcu1Btja2sLY2Pjt1Qi6lV9iMeSjrGgKOpjo+p1jTYsKIqiKKoJ0YYFRVEfGzp4m/oopaeng8PhICkp6V0XhULNbFFubm7vuhhv3cv7nZubCw6Hg61bt76zMr0p4eHhr/V287dh69at4HA4OH/+/LsuCkVR1CeNjrGgqA+UVCpFZGTkJ3tzT334CCGIj4/HL7/8gitXrqCyshJWVlYYMWIE/ve//zFvGJfbsGEDNDU16XgKiqql9ZyUN5o/fbM31Rj0iQVFfaCkUikiIiKQnp7+zspw5MgRHDly5J1t/31hbm6O58+ff5TT637//fd4/vx5k+dbXV0NHx8f+Pn5Aah5MrJmzRo4ODggIiIC3bt3x9OnT1nrbNiw4aN8KkRRFPWxoE8sqE+KVCqFpqbmuy7GB09ej1wu910XhUEIwYsXL97JtKMcDgd8Pv+tb/dtaNasGZo1a/r/KiIjI7Fz507MmDEDK1asYNLHjx8Pb29vDBkyBAEBAUhNTW3ybb+qZ8+eKTxFoSiKov4PfWJBvVcePXqEoKAgGBoagsfjwdbWFlu2bFGIk8lkWLx4MczMzMDn8+Hu7q7whmc3NzfY2dnhwoULcHFxgaamJr777jsAwL59++Dp6QkTExPweDxYWVlh4cKFqK6urjMPJycnCAQCWFhYICoqiokpLy+HlpYWpkyZolDOhw8fQl1dHUuXLmXSSkpKMG3aNLRu3Ro8Hg9mZmbw8/NDQUEBgJp5+8PCwuDo6AiRSAQtLS04OzsjLS2NySM3NxdisRgAEBERAQ6HAw6Hg/DwcJXqWT5WJTExEd999x2MjIygpaWFwYMH48GDByrX48vdsOT57ty5ExERETA1NYW2tjaGDx8OiUSCiooKTJ06FQYGBhAKhQgMDERFRQVre7GxsejduzcMDAzA4/FgY2ODjRs3KuxD69atMXDgQBw+fBhdunSBQCDApk2b4Orqio4dOyrd73bt2sHDw0OlOpKLjo6GlZUVBAIBPv/8c5w6dUohRtkYiytXriAgIACWlpbg8/kwMjJCUFAQCgsLFdZPT09Hly5dwOfzYWVlhU2bNikd28DhcDBp0iTs3bsXdnZ2zN/IoUOHFPK8ePEi+vfvDx0dHQiFQri7u+Ovv/5ixfz333+IiIhA27Ztwefzoa+vj549e+Lo0aNMjLJyHD16FD179oSuri6EQiHatWvHnBOqeP78OVasWAFra2vW34bcoEGD4O/vj0OHDjFlbt26NbKysnDixAnmfH+5C2BFRQWmT58OsVgMLS0teHl5IT8/XyH/1NRUODs7Q0tLC9ra2vD09ERWVhYrJiAgAEKhENnZ2RgwYAC0tbUxatQolfeRoijqU0SfWFDvjadPn6J79+7MzZNYLEZqairGjh2L0tJSTJ06lYldtmwZ1NTUMGPGDEgkEkRGRmLUqFE4e/YsK8/CwkL0798fPj4+GD16NAwNDQHUDPYUCoWYPn06hEIhjh8/jrCwMJSWlrJ+PQVqprscMGAAvL294evri507dyI0NBRcLhdBQUEQCoXw8vJCYmIiVq9eDXV1dWbdHTt2gBDC3JCUl5fD2dkZ//zzD4KCgtC5c2cUFBRg//79ePjwIVq0aIHS0lLExMTA19cXwcHBKCsrw+bNm+Hh4YFz587BwcEBYrEYGzduRGhoKLy8vDB06FAAgL29faPqfPHixeBwOJg9ezby8vKwZs0a9OnTB5cuXWL98l9XPdZl6dKlEAgEmDNnDu7cuYN169ZBQ0MDampqKC4uRnh4OP766y9s3boVFhYWCAsLY9bduHEjbG1tMXjwYDRr1gy///47JkyYAJlMhokTJ7K2c/PmTfj6+iIkJATBwcFo164dhEIhgoODce3aNdjZ2TGxf//9N27duoXvv/9e5frZvHkzQkJC4OTkhKlTp+Lu3bsYPHgw9PT00LJly3rXPXr0KO7evYvAwEAYGRkhKysL0dHRyMrKwl9//cXcrF+8eBH9+vWDsbExIiIiUF1djQULFjANx5f9+eefSE5OxoQJE6CtrY2ffvoJw4YNw/3796Gvrw8AyMrKgrOzM3R0dDBr1ixoaGhg06ZNcHNzw4kTJ9CtWzcANY2GpUuXYty4cfj8889RWlqK8+fPIzMzE19++aXS7WdlZWHgwIGwt7fHggULwOPxcOfOHWRkZKhcr3/++SeKi4sxZcqUOp+G+Pn5ITY2FgcOHED37t2xZs0afPvttxAKhZg3bx4AKJyH3377LZo3b4758+cjNzcXa9aswaRJk5CYmMjEbNu2Df7+/vDw8MDy5cshlUqxceNG9OzZExcvXkTr1q2Z2KqqKnh4eKBnz55YuXJlnU87KyoqWA3k0tJSleuCoijqo0Io6j0xduxYYmxsTAoKCljpPj4+RCQSEalUStLS0ggA0r59e1JRUcHErF27lgAgV69eZdJcXV0JABIVFaWwLalUqpAWEhJCNDU1yYsXLxTyWLVqFZNWUVFBHBwciIGBAamsrCSEEHL48GECgKSmprLytLe3J66ursz3sLAwAoAkJycrbF8mkxFCCKmqqmLtGyGEFBcXE0NDQxIUFMSk5efnEwBk/vz5Cnk1RF6PpqampLS0lEnfuXMnAUDWrl2rUAfK6tHV1ZW1f/J87ezsmLohhBBfX1/C4XBI//79Wet/8cUXxNzcnJWm7Nh4eHgQS0tLVpq5uTkBQA4dOsRKLykpIXw+n8yePZuVPnnyZKKlpUXKy8sV8lemsrKSGBgYEAcHB9bxiI6OJgBY+52Tk0MAkNjY2Hr3Y8eOHQQAOXnyJJM2aNAgoqmpSR49esSk3b59mzRr1oy8fIkGQLhcLrlz5w6TdvnyZQKArFu3jkkbMmQI4XK5JDs7m0l7/Pgx0dbWJi4uLkxax44diaenZ731MH/+fFY5fvzxRwKA5Ofn17tefdasWUMAkD179tQZU1RURACQoUOHMmm2trasepeLjY0lAEifPn2YvyNCCJk2bRpRV1cnJSUlhBBCysrKiK6uLgkODmat/++//xKRSMRK9/f3JwDInDlzGtwfeR29/JFIJA2uS1Gvy3z2gTf6oShCCJFIJCpd12hXKOq9QAjB7t27MWjQIBBCUFBQwHw8PDwgkUiQmZnJxAcGBrL69zs7OwMA7t69y8qXx+MhMDBQYXu1f40vKytDQUEBnJ2dIZVKcePGDVZss2bNEBISwnzncrkICQlBXl4e8+KuPn36wMTEBAkJCUzctWvXcOXKFYwePZpJ2717Nzp27AgvLy+FMsl/wVZXV2f2TSaToaioCFVVVejSpQurDpqCn58ftLW1me/Dhw+HsbExDh48yIqrqx7ry1dDQ4P53q1bNxBCEBQUxIrr1q0bHjx4gKqqKiat9rGRSCQoKCiAq6sr7t69C4lEwlrfwsJCoWuTSCTCV199xTwtAmoGCicmJmLIkCEq95E/f/488vLy8M0337DOtYCAAIhEogbXr70fL168QEFBAbp37w4AzHGsrq7GsWPHMGTIEJiYmDDxbdq0Qf/+/ZXm26dPH1hZWTHf7e3toaOjw5z71dXVOHLkCIYMGQJLS0smztjYGCNHjsSff/7J/KKuq6uLrKws3L59u8H9kdPV1QVQ051QJpOpvF5tZWVlAMA6914mX9aYX//Hjx/P6rbl7OyM6upq3Lt3D0DNU6SSkhL4+vqyrjHq6uro1q0bq7uhXGhoaIPbnTt3LiQSCfN5uTshRVHUp4I2LKj3Qn5+PkpKShAdHQ2xWMz6yG9o8/LymPhWrVqx1m/evDmAmm5LtZmamiodYJyVlQUvLy+IRCLo6OhALBYzDYCXb15NTEwUbkatra0B1PStBwA1NTWMGjUKe/fuhVQqBQAkJCSAz+djxIgRzHrZ2dms7jl1iYuLg729PdPvXSwWIyUlRaFsr6tt27as7xwOB23atGH2S66ueqzLy8dHfiP+cvchkUgEmUzG2q+MjAz06dMHWlpa0NXVhVgsZvrvK2tYKOPn54f79+8z4yGOHTuGp0+fNmrWJvnN6Mt1pKGhwbphr0tRURGmTJkCQ0NDCAQCiMViprzy/cjLy8Pz58/Rpk0bhfWVpQGKdQvUnP/ycz8/Px9SqRTt2rVTiGvfvj1kMhlz47tgwQKUlJTA2toaHTp0wMyZM3HlypV69+vrr79Gjx49MG7cOBgaGsLHxwc7d+5sVCND3miQNzCUUaXx8bKGrgvyBlTv3r0VrjNHjhxhXWOAmh8VzMzMGtwuj8eDjo4O60NRFPUpomMsqPeC/KZk9OjR8Pf3Vxpjb2+P69evAwBrHENt5KUXySubIaikpASurq7Q0dHBggULYGVlBT6fj8zMTMyePfuVf4X18/PDihUrsHfvXvj6+mL79u0YOHCgSr9u1xYfH4+AgAAMGTIEM2fOhIGBATMAPDs7+5XK9roaO9NSXcenoeOWnZ0Nd3d3fPbZZ1i9ejVatmwJLpeLgwcP4scff1Q4NnWVy8PDA4aGhoiPj4eLiwvi4+NhZGSEPn36NGo/Xoe3tzdOnz6NmTNnwsHBAUKhEDKZDP369XvlcwxQ/dxXhYuLC7Kzs7Fv3z4cOXIEMTEx+PHHHxEVFYVx48YpXUcgEODkyZNIS0tDSkoKDh06hMTERPTu3RtHjhyps3y1tW/fHkDNAPchQ4YojZE3cGxsbFTen4bqRl7v27Ztg5GRkULcy+M9eDwe1NTo728URVGqog0L6r0gFouhra2N6urqem/+5A2L15Geno7CwkIkJyfDxcWFSc/JyVEa//jxY4VpJm/dugUArIGednZ26NSpExISEmBmZob79+9j3bp1rLysrKxw7dq1esuXlJQES0tLJCcns7p1zJ8/nxXXFG9DfrkLDCEEd+7cafQg8Kby+++/o6KiAvv372f9+qysi0p91NXVMXLkSGzduhXLly/H3r17ERwcrNJNr5y5uTmAmjrq3bs3k/7ff/8hJyenzpmngJpfyP/44w9ERESwBqa/XN8GBgbg8/kKM5oBUJqmCrFYDE1NTdy8eVNh2Y0bN6CmpsZ6cqSnp4fAwEAEBgaivLwcLi4uCA8Pr7NhAdQ8oXN3d4e7uztWr16NJUuWYN68eUhLS1Op8SafUWr79u2YN2+e0uPy66+/AgAGDhzIpL3uOS/vQmZgYPBWG5kURVGfCtqwoN4L6urqGDZsGLZv364wmw9Q072jrllyXmVbAPsX3srKSmzYsEFpfFVVFTZt2oTp06czsZs2bYJYLIajoyMrdsyYMZg1axZ4PB709fUV+skPGzYMCxYswJ49exTGWRBCwOFwWOWT30idPXsWZ86cYd1sy2eoKSkpaWwVMH799VfMnTuX6W6SlJSEJ0+eYPbs2a+c5+tQdmwkEgliY2MbndeYMWPw448/IiQkBOXl5ayxLqro0qULxGIxoqKiWGN6tm7d2mCdK9sPAFizZo1CXJ8+fbB37148fvyYGWdx586dV35/g7q6Ovr27Yt9+/YhNzeXafw+ffoU27dvR8+ePZmuOoWFhcxMUgAgFArRpk2bescIFBUVQU9Pj5Xm4OAAAApTB9dFU1MTM2bMwPfff4958+Zh2bJlrOUpKSnYunUrPDw8mHEpAKClpfVa57uHhwd0dHSwZMkS9OrVizUOCGja6wxFvS30zdjU+4Q2LKj3xrJly5CWloZu3bohODgYNjY2KCoqQmZmJo4dO4aioqIm2Y6TkxOaN28Of39/TJ48GRwOB9u2bauzK4mJiQmWL1+O3NxcWFtbIzExEZcuXUJ0dLTCjcnIkSMxa9Ys7NmzB6GhoQrLZ86ciaSkJIwYMQJBQUFwdHREUVER9u/fj6ioKHTs2BEDBw5EcnIyvLy84OnpiZycHERFRcHGxgbl5eVMXgKBADY2NkhMTIS1tTX09PRgZ2en0hgOOT09PfTs2ROBgYF4+vQp1qxZgzZt2iA4OLgRNdp0+vbtCy6Xi0GDBjENgl9++QUGBgZ48uRJo/Lq1KkT7OzssGvXLrRv3x6dO3du1PoaGhpYtGgRQkJC0Lt3b3z99dfIyclBbGxsg2MsdHR04OLigsjISPz3338wNTXFkSNHlD4VCw8Px5EjR9CjRw+Ehoaiuroa69evh52dHS5dutSoMsstWrSIedfEhAkT0KxZM2zatAkVFRWIjIxk4mxsbODm5gZHR0fo6enh/PnzSEpKwqRJk+rMe8GCBTh58iQ8PT1hbm6OvLw8bNiwAWZmZujZs6fKZZwzZw4uXryI5cuX48yZMxg2bBgEAgH+/PNPxMfHo3379oiLi2Ot4+joiI0bN2LRokVo06YNDAwMWE+TGqKjo4ONGzdizJgx6Ny5M3x8fCAWi3H//n2kpKSgR48eWL9+vcr5URRFUS95U9NSUdSrePr0KZk4cSJp2bIl0dDQIEZGRsTd3Z1ER0cTQv5vOtNdu3ax1lM23aerqyuxtbVVup2MjAzSvXt3IhAIiImJCZk1axYzZWxaWppCHufPnydffPEF4fP5xNzcnKxfv77OfRgwYAABQE6fPq10eWFhIZk0aRIxNTUlXC6XmJmZEX9/f2aaXZlMRpYsWULMzc0Jj8cjnTp1IgcOHCD+/v4KU7OePn2aODo6Ei6X26ipZ+X1uGPHDjJ37lxiYGBABAIB8fT0JPfu3WPF1lePdU03+/LxkU8H+vfff7PS5dN01p66dP/+/cTe3p7w+XzSunVrsnz5crJlyxYCgOTk5DBx5ubmDU6VGhkZSQCQJUuW1BtXnw0bNhALCwvC4/FIly5dyMmTJxX2W9n59/DhQ+Ll5UV0dXWJSCQiI0aMII8fP1Z6nP744w/SqVMnwuVyiZWVFYmJiSH/+9//CJ/PZ8UBIBMnTlQoo7m5OfH392elZWZmEg8PDyIUCommpibp1auXwjm5aNEi8vnnnxNdXV0iEAjIZ599RhYvXsyaKvjl6Wb/+OMP8tVXXxETExPC5XKJiYkJ8fX1Jbdu3VKxRv9PdXU1iY2NJT169CA6OjqEz+cTW1tbEhERoXRa4H///Zd4enoSbW1t1pS/dZ1f8vOx9t+0PN3Dw4OIRCLC5/OJlZUVCQgIIOfPn2di/P39iZaWVqP3iRDVp2WkKIr6UKh6XeMQ8goj/ijqE+Hm5oaCgoIGx0XU5uXlhatXr75yH/m3IT09Hb169cKuXbswfPjwd12cN2bt2rWYNm0acnNzlc6m9D4bMmRIo6eCpd4PpaWlEIlEkEgkdIYoiqI+Cqpe1+h0FxTVhJ48eYKUlJRGTWtKvRmEEGzevBmurq7vfaPi+fPnrO+3b9/GwYMH4ebm9m4KRFEURVGvgI6xoKgmkJOTg4yMDMTExEBDQ4P1Qr23qbKyssGxKI2d/vZD8+zZM+zfvx9paWm4evUq9u3bpxBTVFSEysrKOvNQV1d/q4N4LS0tERAQAEtLS9y7dw8bN24El8vFrFmz3loZmkp+fj6qq6vrXM7lchUGf1MURVEfB9qwoKgmcOLECQQGBqJVq1aIi4tTOkf+23D69Gn06tWr3pjY2FjWNLkfm/z8fIwcORK6urr47rvvMHjwYIWYoUOH4sSJE3XmYW5urvCSwDepX79+2LFjB/7991/weDx88cUXWLJkicLL+T4EXbt2ZV4uqIyrqyvS09PfXoEoiqKot4aOsaCoj0hxcTEuXLhQb4ytrS2MjY3fUoneTxcuXFB4S3ttAoEAPXr0eIsl+nhkZGQodO2qrXnz5grTNH9s6BgLiqI+Nqpe12jDgqIoiqKaEG1YUBT1saGDtymKoiiKoiiKemtow4KiKEZ6ejo4HA6SkpLedVGoj1BAQMBHPb6HoijqU0cHb1MURSkhlUoRGRkJNze315r29Z9//oGNjQ14PB7+/fdf6OrqKsScO3cOW7duxdmzZ3HlyhVUVVXV+SZ4oOaR9I8//ojk5GRkZ2ejuroaVlZW8PT0xJQpU2BiYvLK5X2bmqqOKepT1npOyhvJN3eZ5xvJl/q40ScWFEVRSkilUkRERLz2DEbx8fHMLGF1PQk6ePAgYmJiwOFwYGlpWW9+d+/ehYODAxYuXAgbGxssX74cP/30E3r16oXNmzd/UDfoTVXHFEVR1PuBPrGgKKrJSKVSaGpqvutivDcIIdi+fTtGjhyJnJwcJCQkYNy4cQpxoaGhmD17NgQCASZNmoRbt24pza+qqgpDhw7F06dPkZ6ejp49e7KWL168GMuXL6+3TPQYURRFUW8KfWJBUZ+QR48eISgoCIaGhuDxeLC1tcWWLVsU4mQyGRYvXgwzMzPw+Xy4u7vjzp07rBg3NzfY2dnhwoULcHFxgaamJr777jsAwL59++Dp6QkTExPweDxYWVlh4cKFCi9Oq52Hk5MTBAIBLCwsEBUVxcSUl5dDS0sLU6ZMUSjnw4cPoa6ujqVLlzJpJSUlmDZtGlq3bg0ejwczMzP4+fmhoKAAQM1LBMPCwuDo6AiRSAQtLS04OzsjLS2NySM3N5d5QV5ERAQ4HA44HA7Cw8MbVd8ZGRnIzc2Fj48PfHx8cPLkSTx8+FAhztDQEAKBoMH8du/ejcuXL2PevHkKjQoA0NHRweLFi5nv9R2jiooKzJ8/H23atAGPx0PLli0xa9YsVFRUsPI8evQoevbsCV1dXQiFQrRr147JAwC2bt0KDoej8N4P+Xidup5GvG4dy/PfuXNng+fqqVOnMGLECLRq1YrZ12nTpilMixsQEAChUIhHjx5hyJAhEAqFEIvFmDFjRr0v/aMoiqJq0CcWFPWJePr0Kbp37w4Oh4NJkyZBLBYjNTUVY8eORWlpKaZOncrELlu2DGpqapgxYwYkEgkiIyMxatQonD17lpVnYWEh+vfvDx8fH4wePRqGhoYAam42hUIhpk+fDqFQiOPHjyMsLAylpaVYsWIFK4/i4mIMGDAA3t7e8PX1xc6dOxEaGgoul4ugoCAIhUJ4eXkhMTERq1evhrq6OrPujh07QAjBqFGjANQ0QpydnfHPP/8gKCgInTt3RkFBAfbv34+HDx+iRYsWKC0tRUxMDHx9fREcHIyysjJs3rwZHh4eOHfuHBwcHCAWi7Fx40aEhobCy8sLQ4cOBQDY29s3qs4TEhJgZWWFrl27ws7ODpqamtixYwdmzpzZqHzk9u/fDwAYM2aMyusoO0YymQyDBw/Gn3/+ifHjx6N9+/a4evUqfvzxR9y6dQt79+4FAGRlZWHgwIGwt7fHggULwOPxcOfOHWRkZLxS+WtrqjpW5VzdtWsXpFIpQkNDoa+vj3PnzmHdunV4+PAhdu3axcqvuroaHh4e6NatG1auXIljx45h1apVsLKyQmhoqNIyVFRUsBpkpaWljdoHiqKojwahKOqTMHbsWGJsbEwKCgpY6T4+PkQkEhGpVErS0tIIANK+fXtSUVHBxKxdu5YAIFevXmXSXF1dCQASFRWlsC2pVKqQFhISQjQ1NcmLFy8U8li1ahWTVlFRQRwcHIiBgQGprKwkhBBy+PBhAoCkpqay8rS3tyeurq7M97CwMAKAJCcnK2xfJpMRQgipqqpi7RshhBQXFxNDQ0MSFBTEpOXn5xMAZP78+Qp5qaKyspLo6+uTefPmMWkjR44kHTt2rHe9iRMnkrouzZ06dSIikUjlMtR1jLZt20bU1NTIqVOnWOlRUVEEAMnIyCCEEPLjjz8SACQ/P7/ObcTGxhIAJCcnh5UuP5fS0tKYNH9/f2Jubs58f506bsy5qux8XLp0KeFwOOTevXus8gEgCxYsYMV26tSJODo61lmW+fPnEwAKH4lE0uj9oqjGMp994I18KKo2iUSi0nWNdoWiqE8AIQS7d+/GoEGDQAhBQUEB8/Hw8IBEIkFmZiYTHxgYCC6Xy3x3dnYGUDNwuDYej4fAwECF7dXu1lNWVoaCggI4OztDKpXixo0brNhmzZohJCSE+c7lchESEoK8vDzmLeJ9+vSBiYkJEhISmLhr167hypUrGD16NJO2e/dudOzYEV5eXgpl4nA4AAB1dXVm32QyGYqKilBVVYUuXbqw6uB1paamorCwEL6+vkyar68vLl++jKysrFfKs7S0FNra2o1aR9kx2rVrF9q3b4/PPvuMdS707t0bAJhuYfIZrPbt2weZTPZKZX7TVDlXa5+Pz549Q0FBAZycnEAIwcWLFxXy/Oabb1jfnZ2dFc792ubOnQuJRMJ8Hjx48Mr7Q1EU9SGjDQuK+gTk5+ejpKQE0dHREIvFrI/8pjMvL4+Jb9WqFWv95s2bA6jptlSbqakp66ZOLisrC15eXhCJRNDR0YFYLGYaABKJhBVrYmICLS0tVpq1tTUAMP321dTUMGrUKOzduxdSqRRATTcjPp+PESNGMOtlZ2fDzs6uwfqIi4uDvb09+Hw+9PX1IRaLkZKSolC21xEfHw8LCwum+9CdO3dgZWUFTU1NVgOpMXR0dFBWVtaodZQdo9u3byMrK0vhXJDXu/xc+Prrr9GjRw+MGzcOhoaG8PHxwc6dO9+rRoYq5+r9+/cREBAAPT09ZtyEq6srAMXzkc/nM2M/auf58rlfG4/Hg46ODutDURT1KaJjLCjqEyC/ERw9ejT8/f2Vxtjb2+P69esAwBrHUBt56d0KygYcl5SUwNXVFTo6OliwYAGsrKzA5/ORmZmJ2bNnv/JNqZ+fH1asWIG9e/fC19cX27dvx8CBAyESiRqVT3x8PAICAjBkyBDMnDkTBgYGzADw7OzsVyrby0pLS/H777/jxYsXaNu2rcLy7du3Y/HixcxTFFV99tlnuHjxIh48eICWLVuqtI6yYySTydChQwesXr1a6TryvAUCAU6ePIm0tDSkpKTg0KFDSExMRO/evXHkyBGoq6vXuQ9va7BzQ+dqdXU1vvzySxQVFWH27Nn47LPPoKWlhUePHiEgIEDhfKwrP4qiKKphtGFBUZ8AsVgMbW1tVFdXo0+fPnXGyRsWryM9PR2FhYVITk6Gi4sLk56Tk6M0/vHjx3j27BnrqYV8utXab2m2s7NDp06dkJCQADMzM9y/fx/r1q1j5WVlZYVr167VW76kpCRYWloiOTmZdVM8f/58Vlxjb/prS05OxosXL7Bx40a0aNGCtezmzZv4/vvvkZGRoXRmp/oMGjQIO3bsQHx8PObOnfvK5bOyssLly5fh7u7e4H6qqanB3d0d7u7uWL16NZYsWYJ58+YhLS0Nffr0YZ4QlJSUsNa7d+9eg+V4nTpW1dWrV3Hr1i3ExcXBz8+PST969Ogb3zZFUdSnhjYsKOoToK6ujmHDhmH79u24du2aQneh/Px8he4fr7MtgP10o7KyEhs2bFAaX1VVhU2bNmH69OlM7KZNmyAWi+Ho6MiKHTNmDGbNmgUejwd9fX3079+ftXzYsGFYsGAB9uzZozDOghACDofDKp/8xvbs2bM4c+YMq1uN/F0PL98wqyI+Ph6WlpYKffWBmhmEli1bhoSEhEY3LIYPH46lS5di8eLFcHNzwxdffMFaXlZWhmXLlrGmnFXG29sbBw8exC+//ILx48ezlj1//hwymQxaWlooKiqCnp4ea7mDgwOzH0BNIwUATp48ySyrrq5GdHR0g/vzOnWsKmXnIyEEa9eufWPbpKi3ib4hm3qf0IYFRX0ili1bhrS0NHTr1g3BwcGwsbFBUVERMjMzcezYMRQVFTXJdpycnNC8eXP4+/tj8uTJ4HA42LZtm0I3KjkTExMsX74cubm5sLa2RmJiIi5duoTo6GhoaGiwYkeOHIlZs2Zhz549CA0NVVg+c+ZMJCUlYcSIEQgKCoKjoyOKioqwf/9+REVFoWPHjhg4cCCSk5Ph5eUFT09P5OTkICoqCjY2NigvL2fyEggEsLGxQWJiIqytraGnpwc7O7sGx3A8fvwYaWlpmDx5stLlPB4PHh4e2LVrF3766SdoaGjg3r172LZtGwDg/PnzAIBFixYBAMzNzZnpZTU0NJCcnIw+ffrAxcUF3t7e6NGjBzQ0NJCVlYXt27ejefPmDTYsxowZg507d+Kbb75BWloaevTogerqaty4cQM7d+7E4cOH0aVLFyxYsAAnT56Ep6cnzM3NkZeXhw0bNsDMzIxpFNna2qJ79+6YO3cu0xD57bffUFVVVW8ZXqeOG+Ozzz6DlZUVZsyYgUePHkFHRwe7d++ud8wERVEU9Yre5NRUFEW9X54+fUomTpxIWrZsSTQ0NIiRkRFxd3cn0dHRhJD/m8Jz165drPVycnIIABIbG8ukubq6EltbW6XbycjIIN27dycCgYCYmJiQWbNmMVPG1p5+VJ7H+fPnyRdffEH4fD4xNzcn69evr3MfBgwYQACQ06dPK11eWFhIJk2aRExNTQmXyyVmZmbE39+fmWZXJpORJUuWEHNzc8Lj8UinTp3IgQMHFKZCJYSQ06dPE0dHR8LlclWeFnXVqlUEAPnjjz/qjNm6dSsBQPbt20cI+b96V/apPZ2uXHFxMQkLCyMdOnQgmpqahM/nEzs7OzJ37lzy5MkTJq6+Y1RZWUmWL19ObG1tCY/HI82bNyeOjo4kIiKCmU7wjz/+IF999RUxMTEhXC6XmJiYEF9fX3Lr1i1WXtnZ2aRPnz6Ex+MRQ0ND8t1335GjR482ON0sIa9Wx7XrTJVz9fr166RPnz5EKBSSFi1akODgYHL58mWFOH9/f6KlpaWwLfl0sqpSdVpGiqKoD4Wq1zUOIXX8jEhRFPWGubm5oaCgoMFxEbV5eXnh6tWrCm9Xpqj3RWlpKUQiESQSCZ0hiqKoj4Kq1zU63SxFUR+MJ0+eICUlpVFvnqYoiqIo6u2gYywoinrv5eTkICMjAzExMdDQ0GC9UO9tqqysbHAsikgkUjrFK6UaWscURVEfLtqwoCjqvXfixAkEBgaiVatWiIuLg5GR0Tspx+nTp9GrV696Y2JjYxEQEPB2CvQRonVMURT14aJjLCiKolRUXFyMCxcu1Btja2sLY2Pjt1Sij8/HUMd0jAVFUR8bVa9rtGFBURRFUU2INiwoivrY0MHbFEW9Menp6eBwOEhKSnrXRfmg5ebmgsPhYOvWre+6KHBzc4Obmxvz/X0qG0VRFPVhoGMsKIqiXoNUKkVkZKTCjTlVv4CAAMTFxTHftbS0YGBggM6dO8PX1xdeXl5QU6O/fVFUQ1rPSWnyPOnbvKlXRRsWFEVRr0EqlSIiIgIAGt2wMDc3x/PnzxXeIP4+eBtl4/F4iImJAQA8f/4c9+7dw++//47hw4fDzc0N+/bto12JKIqiPiC0YUFR1FsnlUqhqan5rovxznE4HPD5/HddDKXeRtmaNWuG0aNHs9IWLVqEZcuWYe7cuQgODkZiYuIbLQNFURTVdOhzZoqiFDx69AhBQUEwNDQEj8eDra0ttmzZohAnk8mwePFimJmZgc/nw93dXeGN2G5ubrCzs8OFCxfg4uICTU1NfPfddwCAffv2wdPTEyYmJuDxeLCyssLChQtRXV1dZx5OTk4QCASwsLBAVFQUE1NeXg4tLS1MmTJFoZwPHz6Euro6li5dyqSVlJRg2rRpaN26NXg8HszMzODn54eCggIANe9TCAsLg6OjI0QiEbS0tODs7Iy0tDQmj9zcXIjFYgBAREQEOBwOOBwOwsPDVapnZeMYAgICIBQK8ejRIwwZMgRCoRBisRgzZsxQqJfffvsNjo6O0NbWho6ODjp06IC1a9cyy8PDw8HhcBS2u3XrVnA4HOTm5r6xsr2OOXPmoG/fvti1axdu3brFWrZhwwbY2tqCx+PBxMQEEydORElJCbP8p59+grq6Oitt1apV4HA4mD59OpNWXV0NbW1tzJ49m7W/K1euRHR0NKysrMDj8dC1a1f8/fffTbZvFEVRHzPasKAoiuXp06fo3r07jh07hkmTJmHt2rVo06YNxo4dizVr1rBily1bhj179mDGjBmYO3cu/vrrL4waNUohz8LCQvTv3x8ODg5Ys2YN856CrVu3QigUYvr06Vi7di0cHR0RFhaGOXPmKORRXFyMAQMGwNHREZGRkTAzM0NoaCjT4BEKhfDy8kJiYqLCTe6OHTtACGHKVl5eDmdnZ6xbtw59+/bF2rVr8c033+DGjRt4+PAhgJoZMGJiYuDm5obly5cjPDwc+fn58PDwwKVLlwAAYrEYGzduBAB4eXlh27Zt2LZtG4YOHfrqBwA1N70eHh7Q19fHypUr4erqilWrViE6OpqJOXr0KHx9fdG8eXMsX74cy5Ytg5ubGzIyMl5r201RtqYwZswYEEJw9OhRJi08PBwTJ06EiYkJVq1ahWHDhmHTpk3o27cv/vvvPwCAs7MzZDIZ/vzzT2a9U6dOQU1NDadOnWLSLl68iPLycri4uLC2u337dqxYsQIhISFYtGgRcnNzMXToUCZ/ZSoqKlBaWsr6UBRFfZIIRVFULWPHjiXGxsakoKCAle7j40NEIhGRSqUkLS2NACDt27cnFRUVTMzatWsJAHL16lUmzdXVlQAgUVFRCtuSSqUKaSEhIURTU5O8ePFCIY9Vq1YxaRUVFcTBwYEYGBiQyspKQgghhw8fJgBIamoqK097e3vi6urKfA8LCyMASHJyssL2ZTIZIYSQqqoq1r4RQkhxcTExNDQkQUFBTFp+fj4BQObPn6+QV0NycnIIABIbG8uk+fv7EwBkwYIFrNhOnToRR0dH5vuUKVOIjo4OqaqqqjP/+fPnE2WX+djYWAKA5OTkMGmurq6sOnqdsqnC39+faGlp1bn84sWLBACZNm0aIYSQvLw8wuVySd++fUl1dTUTt379egKAbNmyhRBCSHV1NdHR0SGzZs0ihNQcT319fTJixAiirq5OysrKCCGErF69mqipqZHi4mLW/urr65OioiIm/3379hEA5Pfff6+zrPJ6fvkjkUgaVScU9SrMZx9o8g9FvUwikah0XaNPLCiKYhBCsHv3bgwaNAiEEBQUFDAfDw8PSCQSZGZmMvGBgYHgcrnMd2dnZwDA3bt3WfnyeDwEBgYqbE8gEDD/LisrQ0FBAZydnSGVSnHjxg1WbLNmzRASEsJ853K5CAkJQV5eHvNCtT59+sDExAQJCQlM3LVr13DlyhVWX/7du3ejY8eO8PLyUiiTvOuQuro6s28ymQxFRUWoqqpCly5dWHXwpnzzzTes787Ozqx61dXVxbNnz1i/6L8tDZWtKQiFQgA15wUAHDt2DJWVlZg6dSprtqjg4GDo6OggJaVmZhw1NTU4OTnh5MmTAIB//vkHhYWFmDNnDgghOHPmDICapxh2dnbQ1dVlbffrr79G8+bNWfsGKJ7Ttc2dOxcSiYT5PHjw4DX3nqIo6sNEGxYURTHy8/NRUlKC6OhoiMVi1kfeMMjLy2PiW7VqxVpffkNWXFzMSjc1NWU1QOSysrLg5eUFkUgEHR0diMVipgEgkUhYsSYmJtDS0mKlWVtbAwAzVkBNTQ2jRo3C3r17IZVKAQAJCQng8/kYMWIEs152djbs7OwarI+4uDjY29uDz+dDX18fYrEYKSkpCmVranw+nxm7Ide8eXNWvU6YMAHW1tbo378/zMzMEBQUhEOHDr3RcqlatqZQXl4OANDW1gYA3Lt3DwDQrl07VhyXy4WlpSWzHKhpDFy4cAHPnz/HqVOnYGxsjM6dO6Njx45Md6g///yTaTTUpuo5XRuPx4OOjg7rQ1EU9Smis0JRFMWQyWQAgNGjR8Pf319pjL29Pa5fvw6g5ld9ZQghrO+1n0zIlZSUwNXVFTo6OliwYAGsrKzA5/ORmZmJ2bNnM2VpLD8/P6xYsQJ79+6Fr68vtm/fjoEDB0IkEjUqn/j4eAQEBGDIkCGYOXMmDAwMmAHg2dnZr1Q2VdVVr7UZGBjg0qVLOHz4MFJTU5GamorY2Fj4+fkx74dQNnAbwGsNtFalbE3h2rVrAIA2bdo0et2ePXviv//+w5kzZ3Dq1CmmAeHs7IxTp07hxo0byM/PV9qwUPWcpiiKohTRhgVFUQyxWAxtbW1UV1ejT58+dcbJGxavIz09HYWFhUhOTmYNoM3JyVEa//jxYzx79oz11EI+Y1Dr1q2ZNDs7O3Tq1AkJCQkwMzPD/fv3sW7dOlZeVlZWzI1rXZKSkmBpaYnk5GTWDfr8+fNZcXXdvL8NXC4XgwYNwqBBgyCTyTBhwgRs2rQJP/zwA9q0acP82l5SUsLq8lP71/331bZt28DhcPDll18CqHmvBgDcvHkTlpaWTFxlZSVycnJY5+vnn38OLpeLU6dO4dSpU5g5cyYAwMXFBb/88gv++OMP5jtFURTVdGhXKIqiGOrq6hg2bBh2796t9MY7Pz+/SbcFsH8JrqysxIYNG5TGV1VVYdOmTazYTZs2QSwWw9HRkRU7ZswYHDlyBGvWrIG+vj769+/PWj5s2DBcvnwZe/bsUdiOvDzKynf27Fmmj76c/H0ctac3fRsKCwtZ39XU1GBvbw+gZpYioKYBBYAZbwAAz549Y73x+n20bNkyHDlyBF9//TXatm0LoGb8DJfLxU8//cQ6Jps3b4ZEIoGn5/+9KZjP56Nr167YsWMH7t+/z3pi8fz5c/z000+wsrKCsbHx290xiqKojxx9YkFRFMuyZcuQlpaGbt26ITg4GDY2NigqKkJmZiaOHTuGoqKiJtmOk5MTmjdvDn9/f0yePBkcDgfbtm2rs8uJiYkJli9fjtzcXFhbWyMxMRGXLl1CdHS0wtuhR44ciVmzZmHPnj0IDQ1VWD5z5kwkJSVhxIgRCAoKgqOjI4qKirB//35ERUWhY8eOGDhwIJKTk+Hl5QVPT0/k5OQgKioKNjY2TP9/oKabl42NDRITE2FtbQ09PT3Y2dmpNIbjdYwbNw5FRUXo3bs3zMzMcO/ePaxbtw4ODg5o3749AKBv375o1aoVxo4di5kzZ0JdXR1btmyBWCzG/fv332j5VFFVVYX4+HgAwIsXL3Dv3j3s378fV65cQa9evVhT2IrFYsydOxcRERHo168fBg8ejJs3b2LDhg3o2rWrwov2nJ2dsWzZMohEInTo0AFATfexdu3a4ebNmwgICHhr+0lRb1LuMs+GgyjqLaFPLCiKYjE0NMS5c+cQGBiI5ORk5l0WRUVFWL58eZNtR19fHwcOHICxsTG+//57rFy5El9++SUiIyOVxjdv3hwHDx7E+fPnMXPmTDx48ADr169HcHCw0n3o27cvgJqnFy8TCoU4deoUQkNDcfDgQUyePBkbNmxAu3btYGZmBqDmZXBLlizB5cuXMXnyZBw+fBjx8fHo0qWLQn4xMTEwNTXFtGnT4Ovri6SkpNepGpWMHj0afD4fGzZswIQJExAXF4evv/4aqampzKxJGhoa2LNnD6ysrPDDDz/gp59+wrhx4zBp0qQ3Xj5VVFRUYMyYMRgzZgymTJmC+Ph4tG3bFklJSTh27BgzcFsuPDwc69evx/379zFt2jTs3LkT48ePx5EjRxQaj/KnFE5OTqxZpGo/vaAoiqKaFofQEWkURb3n3NzcUFBQ0OC4iNq8vLxw9epVhTeBU9SbVlpaCpFIBIlEQmeIoijqo6DqdY0+saAo6qPz5MkTpKSkKH1aQVEURVHUm0HHWFAU9dHIyclBRkYGYmJioKGhwXqh3ttUWVnZ4FgUkUikdBreD11RUREqKyvrXK6urq7wHgyKoijq40AbFhRFfTROnDiBwMBAtGrVCnFxcTAyMnon5Th9+jR69epVb0xsbOxHOYB46NChOHHiRJ3Lzc3NmRcaUhRFUR8XOsaCoiiqiRUXF+PChQv1xtja2n6U051euHCh3rdUCwQC9OjR4y2W6O2jYywoivrYqHpdow0LiqIoimpCtGFBUdTHhg7epiiKoiiKoijqraENC+qDlp6eDg6H81beG0C9WW5ubnBzc2O+5+bmgsPhYOvWrW9ke/JzJz09/Y3k/7YFBASgdevWr7Ru69atP+jxHvJzZeXKle+6KBRFUZ80Oniboj4SUqkUkZGRCjfoFNVY169fx86dO1+rsaKqjIwMrFy5EqdPn0ZJSQmMjY3h4eGBefPmoVWrVqzYgwcP4ty5cwgPD3+jZaKoD0nrOSmvtT59czfVlOgTC4r6SEilUkRERHw0v8Cbm5vj+fPn9F0UKvrll19w8+bNJsnr+vXriIiIeOOzN61btw7Ozs64evUqvv32W2zYsAHDhw9HYmIi7O3tcfr0aVb8wYMHERER8UbLRFEURb06+sSC+qRJpVJoamq+62JQSnA4HPD5/HddjA+GhobGuy5Co2RkZGDq1Kno2bMnDh06xPo7DA0NRY8ePTB8+HBkZWWhefPm77Ck/+fZs2fQ0tJ618WgKIp6b9EnFtR77dGjRwgKCoKhoSF4PB5sbW2xZcsWhTiZTIbFixfDzMwMfD4f7u7uuHPnDivGzc0NdnZ2uHDhAlxcXKCpqYnvvvsOALBv3z54enrCxMQEPB4PVlZWWLhwIaqrq+vMw8nJCQKBABYWFoiKimJiysvLoaWlhSlTpiiU8+HDh1BXV8fSpUuZtJKSEkybNg2tW7cGj8eDmZkZ/Pz8UFBQAKDmZWthYWFwdHSESCSClpYWnJ2dkZaWxuSRm5vLvHQsIiICHA4HHA5H5S4j8vEGO3fuREREBExNTaGtrY3hw4dDIpGgoqICU6dOhYGBAYRCIQIDA1FRUaGQT3x8PBwdHSEQCKCnpwcfHx88ePBAIS46OhpWVlYQCAT4/PPPcerUKYWYusZY3LhxA97e3hCLxRAIBGjXrh3mzZvHLL937x4mTJiAdu3aQSAQQF9fHyNGjGiSX9//++8/REREoG3btuDz+dDX10fPnj1x9OhRJiYgIABCoRB3796Fh4cHtLS0YGJiggULFuDlSfhkMhnWrFkDW1tb8Pl8GBoaIiQkROl0rampqXB1dYW2tjZ0dHTQtWtXbN++nbXdl7strVy5Ek5OTtDX14dAIICjo2OD45G2bt2KESNGAAB69erFnEvp6enw9/dHixYt8N9//yms17dvX7Rr167BOpRbuHAhOBwO4uLiFBr3VlZWiIyMxJMnT7Bp0yZm/37++WcAYMrE4XAU8pWfWzweD127dsXff/+tEHPjxg0MHz4cenp64PP56NKlC/bv369QDxwOBydOnMCECRNgYGAAMzMzlfePoijqU0SfWFDvradPn6J79+7gcDiYNGkSxGIxUlNTMXbsWJSWlmLq1KlM7LJly6CmpoYZM2ZAIpEgMjISo0aNwtmzZ1l5FhYWon///vDx8cHo0aNhaGgIoOYmQigUYvr06RAKhTh+/DjCwsJQWlqKFStWsPIoLi7GgAED4O3tDV9fX+zcuROhoaHgcrkICgqCUCiEl5cXEhMTsXr1aqirqzPr7tixA4QQjBo1CkBNI8TZ2Rn//PMPgoKC0LlzZxQUFGD//v14+PAhWrRogdLSUsTExMDX1xfBwcEoKyvD5s2b4eHhgXPnzsHBwQFisRgbN25EaGgovLy8MHToUACAvb19o+p86dKlEAgEmDNnDu7cuYN169ZBQ0MDampqKC4uRnh4OP766y9s3boVFhYWCAsLY9ZdvHgxfvjhB3h7e2PcuHHIz8/HunXr4OLigosXL0JXVxcAsHnzZoSEhMDJyQlTp07F3bt3MXjwYOjp6aFly5b1lu/KlStwdnaGhoYGxo8fj9atWyM7Oxu///47Fi9eDAD4+++/cfr0afj4+MDMzAy5ubnYuHEj3NzccP369dd6QhUeHo6lS5di3Lhx+Pzzz1FaWorz588jMzMTX375JRNXXV2Nfv36oXv37oiMjMShQ4cwf/58VFVVYcGCBUxcSEgItm7disDAQEyePBk5OTlYv349Ll68iIyMDOYpxNatWxEUFARbW1vMnTsXurq6uHjxIg4dOoSRI0fWWd61a9di8ODBGDVqFCorK/Hbb79hxIgROHDgADw9lferdnFxweTJk/HTTz/hu+++Q/v27QEA7du3x5gxY/Drr7/i8OHDGDhwILPOv//+i+PHj2P+/Pkq1aNUKsUff/wBZ2dnWFhYKI35+uuvMX78eBw4cABz5sxBSEgIHj9+jKNHj2Lbtm1K19m+fTvKysoQEhICDoeDyMhIDB06FHfv3mXqMisrCz169ICpqSnmzJkDLS0t7Ny5E0OGDMHu3bvh5eXFynPChAkQi8UICwvDs2fPlG63oqKC1dAuLS1VqR4oiqI+OoSi3lNjx44lxsbGpKCggJXu4+NDRCIRkUqlJC0tjQAg7du3JxUVFUzM2rVrCQBy9epVJs3V1ZUAIFFRUQrbkkqlCmkhISFEU1OTvHjxQiGPVatWMWkVFRXEwcGBGBgYkMrKSkIIIYcPHyYASGpqKitPe3t74urqynwPCwsjAEhycrLC9mUyGSGEkKqqKta+EUJIcXExMTQ0JEFBQUxafn4+AUDmz5+vkFdD5PVoZ2fH7AMhhPj6+hIOh0P69+/Piv/iiy+Iubk58z03N5eoq6uTxYsXs+KuXr1KmjVrxqRXVlYSAwMD4uDgwNqn6OhoAoBVNzk5OQQAiY2NZdJcXFyItrY2uXfvHms78roiRPmxPHPmDAFAfv31V4V9TktLq7tiXtKxY0fi6elZb4y/vz8BQL799ltW+Tw9PQmXyyX5+fmEEEJOnTpFAJCEhATW+ocOHWKll5SUEG1tbdKtWzfy/PlzVmzt/fb392cdE0IU66KyspLY2dmR3r17s9LNzc2Jv78/833Xrl1K66a6upqYmZmRr7/+mpW+evVqwuFwyN27d+uoFbZLly4RAGTKlCn1xtnb2xM9PT3m+8SJE4my/7bk54q+vj4pKipi0vft20cAkN9//51Jc3d3Jx06dGD9XctkMuLk5ETatm3LpMXGxhIApGfPnqSqqqrecs6fP58AUPhIJJJ616OopmA++8BrfShKFRKJRKXrGu0KRb2XCCHYvXs3Bg0aBEIICgoKmI+HhwckEgkyMzOZ+MDAQHC5XOa7s7MzAODu3busfHk8HgIDAxW2JxAImH+XlZWhoKAAzs7OkEqluHHjBiu2WbNmCAkJYb5zuVyEhIQgLy+Pedtynz59YGJigoSEBCbu2rVruHLlCkaPHs2k7d69Gx07dlT4lRQA081DXV2d2TeZTIaioiJUVVWhS5curDpoCn5+fqy++t26dQMhBEFBQay4bt264cGDB6iqqgIAJCcnQyaTwdvbm3WsjIyM0LZtW6bb1vnz55GXl4dvvvmGdbwCAgIgEonqLVt+fj5OnjyJoKAghdmCaneJqX0s//vvPxQWFqJNmzbQ1dV97frS1dVFVlYWbt++3WDspEmTWOWbNGkSKisrcezYMQDArl27IBKJ8OWXX7LqzNHREUKhkKmzo0ePoqysDHPmzFEYc6KsK1BtteuiuLgYEokEzs7Or1wPampqGDVqFPbv34+ysjImPSEhAU5OTnU+fXiZfF1tbe1647S1tRv16//XX3/NGo/x8nWgqKgIx48fh7e3N/N3XlBQgMLCQnh4eOD27dt49OgRK8/g4GDWU0dl5s6dC4lEwnyUdf+jKIr6FNCGBfVeys/PR0lJCaKjoyEWi1kfecMgLy+PiX/5RlN+c/FyX3VTU1PWDa1cVlYWvLy8IBKJoKOjA7FYzDQAJBIJK9bExERhAKe1tTUAMP345Tdge/fuhVQqBVBz88Xn85n+6wCQnZ0NOzu7BusjLi4O9vb2TL9+sViMlJQUhbK9rpfrUX6z/3IXJZFIBJlMxmz/9u3bIISgbdu2Csfrn3/+YY7VvXv3AABt27Zl5aehoQFLS8t6yya/OWyovp4/f46wsDC0bNkSPB4PLVq0gFgsRklJyWvX14IFC1BSUgJra2t06NABM2fOxJUrVxTi1NTUFPbn5XPk9u3bkEgkMDAwUKiz8vJyps6ys7NV2m9lDhw4gO7du4PP50NPT4/pMvc69eDn54fnz59jz549AICbN2/iwoULjZq9S96gqN04UaasrKzBxkdtDV0H7ty5A0IIfvjhB4U6l3fjqn1dAaBSY4nH40FHR4f1oSiK+hTRMRbUe0kmkwEARo8eDX9/f6Ux9vb2uH79OgDU+YsieWmwbO1fcOVKSkrg6uoKHR0dLFiwAFZWVuDz+cjMzMTs2bOZsjSWn58fVqxYgb1798LX1xfbt2/HwIEDG/xl/mXx8fEICAjAkCFDMHPmTBgYGDADwOU3nU2lrnpsqH5lMhk4HA5SU1OVxgqFwqYrZAO+/fZbxMbGYurUqfjiiy8gEonA4XDg4+PzysdSzsXFBdnZ2di3bx+OHDmCmJgY/Pjjj4iKisK4ceMalZdMJoOBgQHrqVZt8sH4r+rUqVMYPHgwXFxcsGHDBhgbG0NDQwOxsbGsQd+NZWNjA0dHR8THx8PPzw/x8fHgcrnw9vZWOY82bdqgWbNmShtlchUVFbh58ya6dOmicr6qnKcAMGPGDHh4eNRZttqUXTMoiqIo5WjDgnovicViaGtro7q6Gn369KkzTt6weB3p6ekoLCxEcnIyXFxcmPScnByl8Y8fP1aYdvLWrVsAwJqVx87ODp06dUJCQgLMzMxw//59rFu3jpWXlZUVrl27Vm/5kpKSYGlpieTkZFbXl5cHyjbULeZNsrKyAiEEFhYWzC/zypibmwOo+bW+d+/eTPp///2HnJwcdOzYsc515U8AVKkvf39/rFq1ikl78eIFSkpKVNmVBunp6SEwMBCBgYEoLy+Hi4sLwsPDWQ0LmUyGu3fvsuri5XPEysoKx44dQ48ePeq9ebWysgJQs98v3/TWZ/fu3eDz+Th8+DB4PB6THhsb2+C6DZ1Lfn5+mD59Op48eYLt27fD09OzUVPCamlpoVevXjh+/Dju3bvHnBe17dy5ExUVFaxB4q97jsvPIQ0NjXqvKxRFUdSroV2hqPeSuro6hg0bht27dyu9kczPz2/SbQHspxuVlZXYsGGD0viqqipmCkx57KZNmyAWi+Ho6MiKHTNmDI4cOYI1a9ZAX18f/fv3Zy0fNmwYLl++zHQrqU1eHmXlO3v2LM6cOcOKl8921FQ30I0xdOhQqKurIyIiQuEpESEEhYWFAIAuXbpALBYjKioKlZWVTMzWrVsbLLdYLIaLiwu2bNmC+/fvK2xDTl1dXaEM69atU5g6+FXI90NOKBSiTZs2SqfeXb9+Pat869evh4aGBtzd3QEA3t7eqK6uxsKFCxXWraqqYuqjb9++0NbWxtKlS/HixQtW3Mv7WZu6ujo4HA5rv3Nzc7F3794G91PeaK7rmPj6+oLD4WDKlCm4e/cua9yQqr7//nsQQhAQEIDnz5+zluXk5GDWrFkwNjZmjWdqqFwNMTAwgJubGzZt2oQnT54oLG/K6wpFvS25yzxf60NRTYk+saDeW8uWLUNaWhq6deuG4OBg2NjYoKioCJmZmTh27BiKioqaZDtOTk5o3rw5/P39MXnyZHA4HGzbtq3OmzYTExMsX74cubm5sLa2RmJiIi5duoTo6GiFl5SNHDkSs2bNwp49exAaGqqwfObMmUhKSsKIESMQFBQER0dHFBUVYf/+/YiKikLHjh0xcOBAJCcnw8vLC56ensjJyUFUVBRsbGxQXl7O5CUQCGBjY4PExERYW1tDT08PdnZ2r9Q3v7GsrKywaNEizJ07F7m5uRgyZAi0tbWRk5ODPXv2YPz48ZgxYwY0NDSwaNEihISEoHfv3vj666+Rk5OD2NjYBsdYAMBPP/2Enj17onPnzhg/fjwsLCyQm5uLlJQUXLp0CQAwcOBAbNu2DSKRCDY2Njhz5gyOHTsGfX39195PGxsbuLm5wdHREXp6ejh//jySkpJYA7UBgM/n49ChQ/D390e3bt2QmpqKlJQUfPfdd0wXJ1dXV4SEhGDp0qW4dOkS+vbtCw0NDdy+fRu7du3C2rVrMXz4cOjo6ODHH3/EuHHj0LVrV4wcORLNmzfH5cuXIZVKERcXp7Ssnp6eWL16Nfr164eRI0ciLy8PP//8M9q0aVNvFyQAcHBwgLq6OpYvXw6JRAIej4fevXvDwMAAQE0jr1+/fti1axd0dXXrnLq2Pi4uLli5ciWmT58Oe3t7BAQEwNjYGDdu3MAvv/wCmUyGgwcPsp6EyBvukydPhoeHB9TV1eHj49Oo7f7888/o2bMnOnTogODgYFhaWuLp06c4c+YMHj58iMuXLzd6XyiKoqj/7w3MSEVRTebp06dk4sSJpGXLlkRDQ4MYGRkRd3d3Eh0dTQj5vylDd+3axVpP2VSlrq6uxNbWVul2MjIySPfu3YlAICAmJiZk1qxZzJSxtafclOdx/vx58sUXXxA+n0/Mzc3J+vXr69yHAQMGEADk9OnTSpcXFhaSSZMmEVNTU8LlcomZmRnx9/dnptmVyWRkyZIlxNzcnPB4PNKpUydy4MABpdOLnj59mjg6OhIul9uoqWfrqkf5lJt///03K10+vaZ86lS53bt3k549exItLS2ipaVFPvvsMzJx4kRy8+ZNVtyGDRuIhYUF4fF4pEuXLuTkyZPE1dW1welmCSHk2rVrxMvLi+jq6hI+n0/atWtHfvjhB2Z5cXExCQwMJC1atCBCoZB4eHiQGzduKEyp+irTzS5atIh8/vnnRFdXlwgEAvLZZ5+RxYsXs6bo9ff3J1paWiQ7O5v07duXaGpqEkNDQzJ//nxSXV2tkGd0dDRxdHQkAoGAaGtrkw4dOpBZs2aRx48fs+L2799PnJyciEAgIDo6OuTzzz8nO3bsYG335fNh8+bNpG3btoTH45HPPvuMxMbGMseutpfrhhBCfvnlF2JpaUnU1dWV1tPOnTsJADJ+/HiV60+ZkydPkq+++oq0aNGCaGhokFatWpHg4GCSm5urEFtVVUW+/fZbIhaLCYfDYfZDfq6sWLFCYR1lfwfZ2dnEz8+PGBkZEQ0NDWJqakoGDhxIkpKSmJi6zn1VqDotI0VR1IdC1esah5B6nqVTFMXi5uaGgoKCBvv51+bl5YWrV68qvAmc+jgFBAQgKSmJ9TTpY7Rv3z4MGTIEJ0+eZKZ1pWqUlpZCJBJBIpHQGaIoivooqHpdo2MsKOoNevLkCVJSUho1FSdFfQh++eUXWFpaomfPnu+6KBRFUdR7go6xoKg3ICcnBxkZGYiJiYGGhgZrAOrbVFlZ2eBYFJFI9MlPqfn8+fMG3+2gp6en9B0on5rffvsNV65cQUpKCtauXaswU5NEIlEYjP0yIyOjN1lEiqIo6h2hDQuKegNOnDiBwMBAtGrVCnFxce/sRur06dPo1atXvTGxsbEICAh4OwV6TyUmJip9I3ttaWlpcHNzezsFeo/5+vpCKBRi7NixmDBhgsLyKVOm1DmgXI72wKUoivo40TEWFPURKy4uxoULF+qNsbW1hbGx8Vsq0fvpyZMnyMrKqjfG0dGxUe9q+FRdv34djx8/rjfmY3+HBB1jQVHUx0bV6xptWFAURVFUE6INC4qiPjZ08PZHJj09HRwOB0lJSe+6KJ+03NxccDgcbN26tcnylB/b9PT0JssTeDNlpRqvdevWKnU127p1KzgcDnJzc994mSiKoijqTaBjLKgPjlQqRWRkJNzc3Gifd+qTtnXr1nrHhpw5cwbdu3d/iyWiKOptaz0npdHr0DduU28KbVhQHxypVIqIiAgA+CgaFi4uLnj+/HmTzzhkbm6O58+fK7ztm3q7bt68CTW1N/tweMGCBbCwsFBIb9OmzRvdLkVRFEXVRhsWnwipVApNTc13XQxKCTU1NfD5/CbPl8PhvJF8P1QvXrwAl8t94zf5L+PxeG98G/3790eXLl3e+HZe1bNnz6ClpfWui0FRFEW9YXSMxXvi0aNHCAoKgqGhIXg8HmxtbbFlyxaFOJlMhsWLF8PMzAx8Ph/u7u4Kb3R2c3ODnZ0dLly4ABcXF2hqauK7774DUPO2XE9PT5iYmIDH48HKygoLFy5EdXV1nXk4OTlBIBDAwsICUVFRTEx5eTm0tLQwZcoUhXI+fPgQ6urqWLp0KZNWUlKCadOmoXXr1uDxeDAzM4Ofnx8KCgoA1LxzISwsDI6OjhCJRNDS0oKzszPS0tKYPHJzcyEWiwEAERER4HA44HA4CA8PV6meVdlG7fIGBARAJBJBV1cX/v7+KCkpUYgLCAiAUCjE/fv3MXDgQAiFQpiamuLnn38GAFy9ehW9e/eGlpYWzM3NsX37dtb6ysZY3L59G8OGDYORkRH4fD7MzMzg4+PDetfC0aNH0bNnT+jq6kIoFKJdu3bMcZbXlbIxFsePH4ezszO0tLSgq6uLr776Cv/88w8rJjw8HBwOB3fu3EFAQAB0dXUhEokQGBgIqVSqUl3L/fvvvwgMDISZmRl4PB6MjY3x1VdfKYwl2LBhA2xtbcHj8WBiYoKJEycq1Hdd4xVe7hYnr9PffvsN33//PUxNTaGpqYnS0lIAwNmzZzFgwAA0b94cWlpasLe3x9q1a1l53rhxA8OHD4eenh74fD66dOmC/fv3N2rf6ypzVlYWevfuDYFAADMzMyxatAgymazReatKfi6sXLkSP//8MywtLaGpqYm+ffviwYMHIIRg4cKFMDMzg0AgwFdffaX0/SepqanMuaOtrQ1PT0+F2bTkfw/Z2dkYMGAAtLW1MWrUKAA17wuZPHkyWrRoAW1tbQwePBiPHj1S+jesyjVRfpx37tzZ4HURqP+4x8bGgsPh4OLFiwrrLVmyBOrq6nj06FGj6p2iKOpTQ59YvAeePn2K7t27g8PhYNKkSRCLxUhNTcXYsWNRWlqKqVOnMrHLli2DmpoaZsyYAYlEgsjISIwaNQpnz55l5VlYWIj+/fvDx8cHo0ePhqGhIYCaPtlCoRDTp0+HUCjE8ePHERYWhtLSUqxYsYKVR3FxMQYMGABvb2/4+vpi586dCA0NBZfLRVBQEIRCIby8vJCYmIjVq1dDXV2dWXfHjh0ghDA3FOXl5XB2dsY///yDoKAgdO7cGQUFBdi/fz8ePnyIFi1aoLS0FDExMfD19UVwcDDKysqwefNmeHh44Ny5c3BwcIBYLMbGjRsRGhoKLy8vDB06FABgb2+vUl2rsg2gZp79r776Cn/++Se++eYbtG/fHnv27IG/v7/SfKurq9G/f3+4uLggMjISCQkJmDRpErS0tDBv3jyMGjUKQ4cORVRUFPz8/PDFF18o7boC1DR+PDw8UFFRgW+//RZGRkZ49OgRDhw4gJKSEohEImRlZWHgwIGwt7fHggULwOPxcOfOHWRkZNS7/8eOHUP//v1haWmJ8PBwPH/+HOvWrUOPHj2QmZmJ1q1bs+K9vb1hYWGBpUuXIjMzEzExMTAwMMDy5ctVqm8AGDZsGLKysvDtt9+idevWyMvLw9GjR3H//n1me+Hh4YiIiECfPn0QGhqKmzdvYuPGjfj777+RkZHxyt25Fi5cCC6XixkzZqCiogJcLhdHjx7FwIEDYWxsjClTpsDIyAj//PMPDhw4wDSSs7Ky0KNHD5iammLOnDnQ0tLCzp07MWTIEOzevRteXl6vVB6gpqHVq1cvVFVVMXlHR0e/1ksKJRIJ00CX43A40NfXZ6UlJCSgsrIS3377LYqKihAZGQlvb2/07t0b6enpmD17Nu7cuYN169ZhxowZrBv5bdu2wd/fHx4eHli+fDmkUik2btyInj174uLFi6xzp6qqCh4eHujZsydWrlzJPC0NCAjAzp07MWbMGHTv3h0nTpyAp6diX+/GXBMB1a6LDR334cOHY+LEiUhISECnTp0U6s3NzQ2mpqZK67+iogIVFRXMd3kDlqIo6pNDqHdu7NixxNjYmBQUFLDSfXx8iEgkIlKplKSlpREApH379qSiooKJWbt2LQFArl69yqS5uroSACQqKkphW1KpVCEtJCSEaGpqkhcvXijksWrVKiatoqKCODg4EAMDA1JZWUkIIeTw4cMEAElNTWXlaW9vT1xdXZnvYWFhBABJTk5W2L5MJiOEEFJVVcXaN0IIKS4uJoaGhiQoKIhJy8/PJwDI/PnzFfJqiKrb2Lt3LwFAIiMjWes6OzsTACQ2NpZJ9/f3JwDIkiVLWHkKBALC4XDIb7/9xqTfuHFDoezyY5uWlkYIIeTixYsEANm1a1ed+/Hjjz8SACQ/P7/OmJycHIWyyo9fYWEhk3b58mWipqZG/Pz8mLT58+cTAKw6IYQQLy8voq+vX+c2X1ZcXEwAkBUrVtQZk5eXR7hcLunbty+prq5m0tevX08AkC1btjBp5ubmxN/fXyEPV1dX1vkmr1NLS0vWOV9VVUUsLCyIubk5KS4uZuUhPw8JIcTd3Z106NCB9Tchk8mIk5MTadu2rSq7XmeZp06dSgCQs2fPMml5eXlEJBIRACQnJ0flvGNjYwkApR8ej8fEyc8FsVhMSkpKmPS5c+cSAKRjx47kv//+Y9J9fX0Jl8tl9r+srIzo6uqS4OBg1vb//fdfIhKJWOnyv4c5c+awYi9cuEAAkKlTp7LSAwICFP4mVLkmEkJUvi6qetx9fX2JiYkJ6zzMzMxU+Dt6mfzv5eWPRCKpcx2Kairmsw80+kNRjSWRSFS6rtGuUO8YIQS7d+/GoEGDQAhBQUEB8/Hw8IBEIkFmZiYTHxgYyBrk6+zsDAC4e/cuK18ej6d0tpjav4qWlZWhoKAAzs7OkEqluHHjBiu2WbNmCAkJYb5zuVyEhIQgLy+Peelanz59YGJigoSEBCbu2rVruHLlCkaPHs2k7d69Gx07dlT6Sy+HwwEAqKurM/smk8lQVFSEqqoqdOnShVUHr0PVbRw8eBDNmjVDaGgoa91vv/22zrzHjRvH/FtXVxft2rWDlpYWvL29mfR27dpBV1dX4XjVJhKJAACHDx+us9uRrq4ugJqubap2oXny5AkuXbqEgIAA6OnpMen29vb48ssvcfDgQYV1vvnmG9Z3Z2dnFBYWqvyLrEAgAJfLRXp6OoqLi5XGHDt2DJWVlZg6dSpr/ENwcDB0dHSQktL4GU/k/P39Wef8xYsXkZOTg6lTpzJ1KCc/D4uKinD8+HF4e3szfyMFBQUoLCyEh4cHbt++/VpdYg4ePIju3bvj888/Z9LEYjHzdO9V/Pzzzzh69Cjrk5qaqhA3YsQI5vwCgG7dugEARo8ejWbNmrHSKysrmf08evQoSkpK4Ovry7pGqauro1u3bkq7Etb+2wGAQ4cOAYDC27pf/ptq7DURaPi6qMpxBwA/Pz88fvyYtT8JCQkQCAQYNmyYwj7KzZ07FxKJhPk8ePCgzliKoqiPGW1YvGP5+fkoKSlBdHQ0xGIx6yNvGOTl5THxrVq1Yq0vfxPwyzdtpqamSmcZysrKgpeXF0QiEXR0dCAWi5kGQO3++wBgYmKiMODS2toaAJj+8Wpqahg1ahT27t3L3AQnJCSAz+djxIgRzHrZ2dmws7NrsD7i4uJgb28PPp8PfX19iMVipKSkKJTtdaiyjXv37sHY2BhCoZC1brt27ZTmyefzmbEfciKRCGZmZqwbF3l6XTfZAGBhYYHp06cjJiYGLVq0gIeHB37++WdW+b7++mv06NED48aNg6GhIXx8fLBz5856Gxn37t2rcx/at2+PgoICPHv2jJWu6vlWFx6Ph+XLlyM1NRWGhoZMV7F///23wXJxuVxYWloyy1/Fy93NsrOzAaDec/HOnTsghOCHH35Q+JucP38+APbfZGPdu3cPbdu2VUiv69xSxeeff44+ffqwPr169VKIe/l4yhsZLVu2VJouP863b98GAPTu3VuhTo4cOaJQH82aNYOZmRkr7d69e1BTU1M4Ji/PXNXYa6Ky/Xr5PFXluAPAl19+CWNjY+aHEplMhh07duCrr76CtrZ2nevxeDzo6OiwPhRFUZ8iOsbiHZPfCI4ePbrO/vv29va4fv06ALDGMdRGXnqBurL+2iUlJXB1dYWOjg4WLFgAKysr8Pl8ZGZmYvbs2a88eNTPzw8rVqzA3r174evri+3bt2PgwIGsX0ZVER8fj4CAAAwZMgQzZ86EgYEBMwBcfmPwut7UNuo6Lqoer5etWrUKAQEB2LdvH44cOYLJkydj6dKl+Ouvv5gBtidPnkRaWhpSUlJw6NAhJCYmonfv3jhy5Eid222sVy1/bVOnTsWgQYOwd+9eHD58GD/88AOWLl2K48ePK/Rlb8jLjTS56upqpWV9lXEL8r+DGTNmwMPDQ2nMhzqN66uep/I62bZtG4yMjBTiaj/tAGputF919i1Vr4m1NcV5Ks9n5MiR+OWXX7BhwwZkZGTg8ePHrKevFEVRVN1ow+IdE4vF0NbWRnV1Nfr06VNnnLxh8TrS09NRWFiI5ORkuLi4MOk5OTlK4x8/fqwwTeStW7cAgDVQ087ODp06dUJCQgLMzMxw//59rFu3jpWXlZUVrl27Vm/5kpKSYGlpieTkZNYNpPxXYrm6bi5Voeo2zM3N8ccff6C8vJz11OLmzZuvvO3G6tChAzp06IDvv/8ep0+fRo8ePRAVFYVFixYBqHla5O7uDnd3d6xevRpLlizBvHnzkJaWpvRcMjc3r3Mfbty4gRYtWryxKUGtrKzwv//9D//73/9w+/ZtODg4YNWqVYiPj2eVy9LSklmnsrISOTk5rH1p3ry50pm57t27x1q3vnIANd316vp7k+ejoaFR79/kqzI3N2eeANT2Ns+txpLXm4GBwSvXibm5OWQyGXJyclhPbF6evUnVa2JjqHLc5fz8/LBq1Sr8/vvvSE1NhVgsrrOBSVEURbHRrlDvmLq6OoYNG4bdu3crvfHOz89v0m0B7F/xKisrsWHDBqXxVVVV2LRpEyt206ZNEIvFcHR0ZMWOGTMGR44cwZo1a6Cvr4/+/fuzlg8bNgyXL1/Gnj17FLYjL4+y8p09exZnzpxhxctnmFF2g9kQVbcxYMAAVFVVYePGjUxadXW1QoPpTSgtLUVVVRUrrUOHDlBTU2NmnlE2Fah8Rqvas9PUZmxsDAcHB8TFxbHq7tq1azhy5AgGDBjQNDtQi1QqxYsXL1hpVlZW0NbWZsrZp08fcLlc/PTTT6zjsnnzZkgkEtasQVZWVvjrr79QWVnJpB04cEDlPu2dO3eGhYUF1qxZo3D+yLdtYGAANzc3bNq0CU+ePFHI43X/JgcMGIC//voL586dY+VZe5zS+8bDwwM6OjpYsmQJ/vvvP4XlqtSJ/Ob85evNy39Tb+KaqMpxl7O3t4e9vT1iYmKwe/du+Pj4KDyRoSiKopSjV8v3wLJly5CWloZu3bohODgYNjY2KCoqQmZmJo4dO6b0JvJVODk5oXnz5vD398fkyZPB4XCwbdu2OrsLmJiYYPny5cjNzYW1tTUSExNx6dIlREdHK0z/OXLkSMyaNQt79uxBaGiowvKZM2ciKSkJI0aMQFBQEBwdHVFUVIT9+/cjKioKHTt2xMCBA5GcnAwvLy94enoiJycHUVFRsLGxQXl5OZOXQCCAjY0NEhMTYW1tDT09PdjZ2ak0hkPVbQwaNAg9evTAnDlzkJubCxsbGyQnJzfpWI+6HD9+HJMmTcKIESNgbW2NqqoqbNu2jbnhAmretHzy5El4enrC3NwceXl52LBhA8zMzNCzZ886816xYgX69++PL774AmPHjmWmmxWJRCq/C6Qxbt26BXd3d3h7e8PGxgbNmjXDnj178PTpU/j4+ACo+YV67ty5iIiIQL9+/TB48GDcvHkTGzZsQNeuXVndUMaNG4ekpCT069cP3t7eyM7ORnx8PPOLdEPU1NSwceNGDBo0CA4ODggMDISxsTFu3LiBrKwsHD58GEDNYOiePXuiQ4cOCA4OhqWlJZ4+fYozZ87g4cOHuHz58ivXyaxZs7Bt2zb069cPU6ZMYaabNTc3x5UrV14pz9TUVIXJF4Cav3lVnuQ0REdHBxs3bsSYMWPQuXNn+Pj4QCwW4/79+0hJSUGPHj2wfv36evNwdHTEsGHDsGbNGhQWFjLTzcqfgtZ+gtjU10RVj7ucn58fZsyYAQC0GxT13stdpjhlM0W9M29kTiqq0Z4+fUomTpxIWrZsSTQ0NIiRkRFxd3cn0dHRhJD/m1bx5SlIlU0p6urqSmxtbZVuJyMjg3Tv3p0IBAJiYmJCZs2axUwZK5/utHYe58+fJ1988QXh8/nE3NycrF+/vs59GDBgAAFATp8+rXR5YWEhmTRpEjE1NSVcLpeYmZkRf39/ZkpJmUxGlixZQszNzQmPxyOdOnUiBw4cIP7+/sTc3JyV1+nTp4mjoyPhcrmNmnq2MdsoLCwkY8aMITo6OkQkEpExY8YwU8G+PN2slpaWwrbqOg7m5ubE09OT+f7ydLN3794lQUFBxMrKivD5fKKnp0d69epFjh07xqzzxx9/kK+++oqYmJgQLpdLTExMiK+vL7l16xYTo+zcIISQY8eOkR49ehCBQEB0dHTIoEGDyPXr11kx8ukzX57OVj69qapTohYUFJCJEyeSzz77jGhpaRGRSES6detGdu7cqRC7fv168tlnnxENDQ1iaGhIQkNDFaYGJYSQVatWEVNTU8Lj8UiPHj3I+fPn65xutq4pe//880/y5ZdfEm1tbaKlpUXs7e3JunXrWDHZ2dnEz8+PGBkZEQ0NDWJqakoGDhxIkpKSVNp3OWVT5F65coW4uroSPp9PTE1NycKFC8nmzZubdLrZ2sdefi68PO1vXfUkz/fvv/9WiPfw8CAikYjw+XxiZWVFAgICyPnz55mYuv4eCCHk2bNnZOLEiURPT48IhUIyZMgQcvPmTQKALFu2jBXb0DWxvvLXde6rctwJIeTJkydEXV2dWFtbK92Phqg6LSNFUdSHQtXrGoeQRo5uoz4Jbm5uKCgoaHBcRG1eXl64evWq0jfeUhRFKXPp0iV06tQJ8fHxrzXlblMqKCiAsbExwsLC8MMPPzR6/dLSUohEIkgkEjpDFEVRHwVVr2t0jAXVJJ48eYKUlBSMGTPmXReFoqj31PPnzxXS1qxZAzU1NdaEEu/a1q1bUV1dTa9nFEVRjUTHWFCvJScnBxkZGYiJiYGGhgbrhXpvU2VlZYP9rkUi0StNP0opJ5FIlN4o1qZsatKPRe13cSgjEAgaPeWyXHl5OWvMjzJisbjJphV+WyIjI3HhwgX06tULzZo1Q2pqKlJTUzF+/HiFd2m8C8ePH8f169exePFiDBkyhDX7HUVRFNUw2rCgXsuJEycQGBiIVq1aIS4u7p3dSJ4+fVrpC8Fqi42NRUBAwNsp0CdgypQpiIuLqzfmY+5paWxsXO9yf39/bN269ZXyXrlyJSIiIuqNycnJ+eBufJ2cnHD06FEsXLgQ5eXlaNWqFcLDwzFv3rx3XTQANZMiyKd2fhszwFEURX1s6BgL6qNQXFyMCxcu1Btja2vb4M0gpbrr16/j8ePH9ca8ifdAvC+OHTtW73ITExPY2Ni8Ut53797F3bt3643p2bMn+Hz+K+VPvVl0jAVFUR8bVa9rtGFBURRFUU2INiwoivrY0MHbFEVRFEVRFEW9NbRhQVHUO5Oeng4Oh4OkpKR3XZSPXm5uLjgcDlauXPmui0JRFEV9pOjgbYqiqPeAVCpFZGQk3Nzc4Obm9q6L81Fwc3PDiRMnMHDgQPz++++sZbm5ubCwsMCKFSuYt2xT1Ieo9ZyURsXTN3VTbxJ9YkFRFPUekEqliIiIQHp6+rsuykfnwIEDDU7uQFEURb0+2rCgKOqDJZVK33URqPdcq1at0Lx58wan76UoiqJeH21YUBT1xjx69AhBQUEwNDQEj8eDra0ttmzZohAnk8mwePFimJmZgc/nw93dHXfu3GHFuLm5wc7ODhcuXICLiws0NTXx3XffAQD27dsHT09PmJiYgMfjwcrKCgsXLkR1dXWdeTg5OUEgEMDCwgJRUVFMTHl5ObS0tDBlyhSFcj58+BDq6upYunQpk1ZSUoJp06ahdevW4PF4MDMzg5+fHwoKCgDUvLwxLCwMjo6OEIlE0NLSgrOzM9LS0pg8cnNzIRaLAQARERHgcDjgcDgIDw9Xua5fvHiB8PBwWFtbg8/nw9jYGEOHDkV2drZCbHR0NKysrMDj8dC1a1f8/fffrOVXrlxBQEAALC0twefzYWRkhKCgIBQWFrLiwsPDPj7riwABAABJREFUweFwcOfOHQQEBEBXVxcikQiBgYEKjb7nz59j8uTJaNGiBbS1tTF48GA8evRI6X6qet6oQltbG9OmTcPvv/+OzMzMBuPv3r2LESNGQE9PD5qamujevTtSUhrX1YSiKOpTRcdYUBT1Rjx9+hTdu3cHh8PBpEmTIBaLkZqairFjx6K0tBRTp05lYpctWwY1NTXMmDEDEokEkZGRGDVqFM6ePcvKs7CwEP3794ePjw9Gjx4NQ0NDAMDWrVshFAoxffp0CIVCHD9+HGFhYSgtLcWKFStYeRQXF2PAgAHw9vaGr68vdu7cidDQUHC5XAQFBUEoFMLLywuJiYlYvXo16+3WO3bsACEEo0aNAlDTCHF2dsY///yDoKAgdO7cGQUFBdi/fz8ePnyIFi1aoLS0FDExMfD19UVwcDDKysqwefNmeHh44Ny5c3BwcIBYLMbGjRsRGhoKLy8vDB06FABgb2+vUl1XV1dj4MCB+OOPP+Dj44MpU6agrKwMR48exbVr12BlZcXEbt++HWVlZQgJCQGHw0FkZCSGDh2Ku3fvQkNDAwBw9OhR3L17F4GBgTAyMkJWVhaio6ORlZWFv/76CxwOh7V9b29vWFhYYOnSpcjMzERMTAwMDAywfPlyJiYgIAA7d+7EmDFj0L17d5w4cQKenop9vRtz3qhqypQp+PHHHxEeHo79+/fXGff06VM4OTlBKpVi8uTJ0NfXR1xcHAYPHoykpCR4eXkpXa+iogIVFRXM99LS0kaXkaIo6qNAKIqi3oCxY8cSY2NjUlBQwEr38fEhIpGISKVSkpaWRgCQ9u3bk4qKCiZm7dq1BAC5evUqk+bq6koAkKioKIVtSaVShbSQkBCiqalJXrx4oZDHqlWrmLSKigri4OBADAwMSGVlJSGEkMOHDxMAJDU1lZWnvb09cXV1Zb6HhYURACQ5OVlh+zKZjBBCSFVVFWvfCCGkuLiYGBoakqCgICYtPz+fACDz589XyKshW7ZsIQDI6tWr6yxHTk4OAUD09fVJUVERs3zfvn0EAPn999+ZNGX1uWPHDgKAnDx5kkmbP38+AcDaD0II8fLyIvr6+sz3CxcuEABk6tSprLiAgACFfVblvFGVq6srsbW1JYQQEhERQQCQCxcuEEL+rz5WrFjBxE+dOpUAIKdOnWLSysrKiIWFBWndujWprq5Wuh15Pbz8kUgkKpeVol6V+ewDjfpQ1KuQSCQqXddoVyiKopocIQS7d+/GoEGDQAhBQUEB8/Hw8IBEImF1SwkMDASXy2W+Ozs7A4DC26d5PB4CAwMVticQCJh/l5WVoaCgAM7OzpBKpbhx4wYrtlmzZggJCWG+c7lchISEIC8vjxng26dPH5iYmCAhIYGJu3btGq5cuYLRo0czabt370bHjh2V/pIt/1VfXV2d2TeZTIaioiJUVVWhS5cuKnXNUcXu3bvRokULfPvtt3WWQ+7rr79G8+bNme/K6rp2fb548QIFBQXo3r07ACgt8zfffMP67uzsjMLCQuaX+0OHDgEAJkyYwIp7ubyNPW8aY8qUKQ2OtTh48CA+//xz9OzZk0kTCoUYP348cnNzcf36daXrzZ07FxKJhPk8ePDglcpIURT1oaMNC4qimlx+fj5KSkoQHR0NsVjM+sgbBnl5eUx8q1atWOvLb3yLi4tZ6aampqwGiFxWVha8vLwgEomgo6MDsVjMNAAkEgkr1sTEBFpaWqw0a2trADVjHQBATU0No0aNwt69e5mxAgkJCeDz+RgxYgSzXnZ2Nuzs7Bqsj7i4ONjb24PP50NfXx9isRgpKSkKZXtV2dnZaNeuHZo1a7h3qyp1XVRUhClTpsDQ0BACgQBisRgWFhYAFOtTlTzv3bsHNTU1Jg+5Nm3asL439rxpDJFIhKlTp2L//v24ePGi0ph79+6hXbt2Cunt27dnlivD4/Ggo6PD+lAURX2K6BgLiqKanEwmAwCMHj0a/v7+SmPs7e2ZX4Brj2OojRDC+l77l3S5kpISuLq6QkdHBwsWLICVlRX4fD4yMzMxe/ZspiyN5efnhxUrVmDv3r3w9fXF9u3bMXDgQIhEokblEx8fj4CAAAwZMgQzZ86EgYEBMwBc2cDqN02Vuvb29sbp06cxc+ZMODg4QCgUQiaToV+/fkrrU9Xj1xBVz5tXJR9rERERgTVr1rxyPhRFUZRytGFBUVSTE4vF0NbWRnV1Nfr06VNnXF1dSxojPT0dhYWFSE5OhouLC5Oek5OjNP7x48d49uwZ66nFrVu3AACtW7dm0uzs7NCpUyckJCTAzMwM9+/fx7p161h5WVlZ4dq1a/WWLykpCZaWlkhOTmZ1S5o/fz4r7uUuS41hZWWFs2fP4r///mMGYL+q4uJi/PHHH4iIiEBYWBiTfvv27VfO09zcHDKZDDk5OWjbti2T/vLMX6qeN69K/tQiPDxcacPF3NwcN2/eVEiXd6czNzdv8jJRFEV9TGhXKIqimpy6ujqGDRuG3bt3K73xzs/Pb9JtAexfxysrK7Fhwwal8VVVVdi0aRMrdtOmTRCLxXB0dGTFjhkzBkeOHMGaNWugr6+P/v37s5YPGzYMly9fxp49exS2Iy+PsvKdPXsWZ86cYcVramoCqHkC01jDhg1DQUEB1q9fX2c5VKWsvABe6xd+Dw8PAFA4Ji831N7GeTN16lTo6upiwYIFCssGDBiAc+fOsY7Ns2fPEB0djdatW8PGxua1t09RTS13mWejPhT1JtEnFhRFvRHLli1DWloaunXrhuDgYNjY2KCoqAiZmZk4duwYioqKmmQ7Tk5OaN68Ofz9/TF58mRwOBxs27atzhtqExMTLF++HLm5ubC2tkZiYiIuXbqE6OhohV/7R44ciVmzZmHPnj0IDQ1VWD5z5kwkJSVhxIgRCAoKgqOjI4qKirB//35ERUWhY8eOGDhwIJKTk+Hl5QVPT0/k5OQgKioKNjY2KC8vZ/ISCASwsbFBYmIirK2toaenBzs7O5XGcPj5+eHXX3/F9OnTce7cOTg7O+PZs2c4duwYJkyYgK+++krl+tTR0YGLiwsiIyPx33//wdTUFEeOHKnzCZAqHB0dMWzYMKxZswaFhYXMdLPyJ0W1n9a86fNGJBJhypQpSgdxz5kzBzt27ED//v0xefJk6OnpIS4uDjk5Odi9ezfU1OhvcRRFUfV6cxNTURT1qXv69CmZOHEiadmyJdHQ0CBGRkbE3d2dREdHE0IIM93srl27WOvJpwKNjY1l0mpPHfqyjIwM0r17dyIQCIiJiQmZNWsWM2VsWlqaQh7nz58nX3zxBeHz+cTc3JysX7++zn0YMGAAAUBOnz6tdHlhYSGZNGkSMTU1JVwul5iZmRF/f39mulSZTEaWLFlCzM3NCY/HI506dSIHDhwg/v7+xNzcnJXX6dOniaOjI+FyuY2eelYqlZJ58+YRCwsLpq6HDx9OsrOzCSHKp1eVe3lbDx8+JF5eXkRXV5eIRCIyYsQI8vjxY4U4+TSr+fn5rPxiY2MJAJKTk8OkPXv2jEycOJHo6ekRoVBIhgwZQm7evEkAkGXLlrHWb+i8UVVd50xxcTERiURK6yM7O5sMHz6c6OrqEj6fTz7//HNy4EDjpuhUdVpGiqKoD4Wq1zUOIY18Tk5RFPWBcnNzQ0FBQYPjImrz8vLC1atXFcYDUK/v0qVL6NSpE+Lj45mXDn4MSktLIRKJIJFI6AxRFEV9FFS9rtHnuhRFUXV48uQJUlJSMGbMmHddlA/e8+fPFdLWrFkDNTU11qB7iqIo6sNFx1hQFEW9JCcnBxkZGYiJiYGGhgbrhXpvU2VlZYNjCkQikdJpeN83kZGRuHDhAnr16oVmzZohNTUVqampGD9+PFq2bNmovPLz81FdXV3nci6XCz09vdctMkVRFNVItGFBURT1khMnTiAwMBCtWrVCXFwcjIyM3kk5Tp8+jV69etUbExsbi4CAgLdToNfg5OSEo0ePYuHChSgvL0erVq0QHh6OefPmNTqvrl271vmyOgBwdXVFenr6a5SWoiiKehV0jAVFUdR7qri4GBcuXKg3xtbWFsbGxm+pRO+HjIwMpV2r5Jo3b64wdfDbRMdYUBT1sVH1ukYbFhRFURTVhGjDgqKojw0dvE1RFEVRFEVR1FtDx1hQFEW9Ajc3NwBodF/+3NxcWFhYYMWKFZgxY0bTF+wD96r1SlGfqtZzUlSOpW/ept40+sSCoiiKoiiKoqjXRhsWFEVRFEVRFEW9NtqwoCiK+kRJpdJ3XYQ37lPYR4qiqPcFbVhQFPXOhYeHg8Ph4M6dOwgICICuri5EIhECAwOZG8Pc3FxwOBxs3bpVYX0Oh4Pw8HCF/G7duoXRo0dDJBJBLBbjhx9+ACEEDx48wFdffQUdHR0YGRlh1apVr70PlZWVCAsLg6OjI0QiEbS0tODs7Iy0tLQ61/nxxx9hbm4OgUAAV1dXXLt2rVHbTE9PB4fDQWJiIr777jsYGRlBS0sLgwcPxoMHD1ixbm5usLOzw4ULF+Di4gJNTU189913AIC8vDyMHTsWhoaG4PP56NixI+Li4hS2J5PJsHbtWnTo0AF8Ph9isRj9+vXD+fPnWXHx8fFwdHSEQCCAnp4efHx8FMoDANHR0bCysoJAIMDnn3+OU6dOKcRs3boVHA4Hubm5Sve99liM+vaxoqIC8+fPR5s2bcDj8dCyZUvMmjULFRUVrHyPHj2Knj17QldXF0KhEO3atWPyoCiKoupHB29TFPXe8Pb2hoWFBZYuXYrMzEzExMTAwMAAy5cvf6X8vv76a7Rv3x7Lli1DSkoKFi1aBD09PWzatAm9e/fG8uXLkZCQgBkzZqBr165wcXF55bKXlpYiJiYGvr6+CA4ORllZGTZv3gwPDw+cO3cODg4OrPhff/0VZWVlmDhxIl68eIG1a9eid+/euHr1KgwNDf8fe/ceV1P2/w/8dbqcS506wulO6TShjkRmMtFlqhHCSDQlupEmjMu4z+czkRlyvwwf0iB9chlUrmnERzEfDcY9tw9SjGulOsmhVOv3h9/Z33bnVCdFhvV8PM7j4azz3muvvfZu22vvtdZu0roXLFgADoeDWbNmoaCgAKtWrYKXlxcuXrzIeiv306dPMWDAAAQEBGDUqFEwMjLCixcv4O7ujtu3b2PixIno1KkTdu/ejdDQUJSWlmLy5MnM8mPGjMGWLVswYMAAjB07FlVVVfj9999x6tQp9OrViynLDz/8AH9/f4wdOxaFhYVYs2YNXF1dceHCBbRp0wYAsGnTJkRGRsLZ2RlTpkzBnTt3MGTIELRt27bJb+KuTdU21tTUYMiQIfjvf/+LcePGoWvXrsjJycHKlStx8+ZN7N27FwBw9epVDBo0CPb29pg/fz54PB5u376NkydPNrjOiooKVgOlrKzsjctPURT1t0YoiqJa2dy5cwkAEh4ezkr39fUl7dq1I4QQkpeXRwCQhIQEpeUBkLlz5yrlN27cOCatqqqKmJubEw6HQxYtWsSkl5SUEIFAQEJCQppUZjc3N+Lm5sbKv6KighVTUlJCjIyMWNul2A6BQEDu37/PpJ8+fZoAIFOnTlW7DJmZmQQAMTMzI2VlZUz6rl27CACyevVqVnkBkLi4OFYeq1atIgDI1q1bmbTKykry+eefE6FQyOR77NgxAoBMmjRJqRw1NTWEEELy8/OJpqYmWbBgAev3nJwcoqWlxaRXVlYSQ0ND4uDgwKqz+Ph4AoBVrwkJCQQAycvLU7ntmZmZjW5jUlIS0dDQIL///jsrPS4ujgAgJ0+eJIQQsnLlSgKAFBYWKm1jQxTHW92PTCZrUj4U9SYsZh1U+0NRb0omk6l1XqNdoSiKem988803rO8uLi54+vTpG98BHjt2LPNvTU1N9OrVC4QQjBkzhklv06YNOnfujDt37rxZoWvlz+VyAbzuMlRcXIyqqir06tUL58+fV4ofOnQozMzMmO+fffYZnJyccOjQoSavOzg4GHp6esz34cOHw8TERCkvHo+HsLAwVtqhQ4dgbGyMwMBAJk1bWxuTJk1CeXk5jh8/DgBISUkBh8PB3LlzldbP4XAAAKmpqaipqYG/vz+KioqYj7GxMT755BOmW9jZs2dRUFCAb775hqkzAAgNDYVIJGry9je2jbt370bXrl3RpUsXVrk8PDwAgCmX4mnKvn37UFNTo/Y658yZA5lMxnxUdfuiKIr6GNCuUBRFvTc6duzI+m5gYAAAKCkpaZH8RCIR+Hw+2rdvr5T+9OnTN1pHbYmJiVi+fDlu3LiBV69eMemdOnVSiv3kk0+U0mxsbLBr164mr7duXhwOB9bW1krjEszMzFgX8gBw9+5dfPLJJ9DQYN9n6tq1K/M7AOTm5sLU1BRt27attxy3bt0CIUTltgGvGyy186wbp62tDSsrq3rzV4eqbbx16xauX78OsViscpmCggIAr7vObdy4EWPHjsXs2bPh6emJYcOGYfjw4Ur1UxuPxwOPx2tWuSmKoj4EtGFBUdR7Q1NTU2U6IYS5K15XdXV1k/JraB3NsXXrVoSGhmLo0KGYMWMGDA0NoampidjYWOTm5jYr75ZSe7zF21BTUwMOh4P09HSV9SwUCpucZ1P3u6ptrKmpQbdu3bBixQqVyyjGdAgEApw4cQKZmZlIS0vDb7/9hp07d8LDwwMZGRn1HjsURVHUa7RhQVHU34Li6UVpaSkrXXH3u7UlJyfDysoKqamprIthVV2HgNd30eu6efMmLC0tm7zuunkRQnD79m3Y29s3uqyFhQUuX76Mmpoa1l35GzduML8DgEQiweHDh1FcXFzvUwuJRAJCCDp16gQbG5sG16kot6I7EgC8evUKeXl56N69O5PWEvtdIpHg0qVL8PT0rLehoqChoQFPT094enpixYoVWLhwIf7xj38gMzMTXl5eaq+ToijqY0THWFAU9begr6+P9u3b48SJE6z0devWtVKJ2BR3s2s/+Th9+jT++OMPlfF79+7FgwcPmO9nzpzB6dOnMWDAgCavWzHDlEJycjIePXqkVl4DBw7E48ePsXPnTiatqqoKa9asgVAohJubGwDAz88PhBDExMQo5aHY5mHDhkFTUxMxMTFKT4AIIUx3s169ekEsFiMuLg6VlZVMzJYtW5QaEBKJBABY+726uhrx8fGNbpuCv78/Hjx4gF9++UXptxcvXuD58+cAgOLiYqXfFbN51Z2WlqLeF/mLfNT+UNTbRp9YUBT1tzF27FgsWrQIY8eORa9evXDixAncvHmztYsFABg0aBBSU1Ph6+sLHx8f5OXlIS4uDra2tigvL1eKt7a2Rt++fREVFYWKigqsWrUK7dq1w8yZM5u87rZt26Jv374ICwvDkydPsGrVKlhbWyMiIqLRZceNG4cNGzYgNDQU586dg6WlJZKTk3Hy5EmsWrWKGRT+xRdfYPTo0fj5559x69Yt9O/fHzU1Nfj999/xxRdfYOLEiZBIJPjpp58wZ84c5OfnY+jQodDT00NeXh727NmDcePGYfr06dDW1sZPP/2EyMhIeHh44Ouvv0ZeXh4SEhKUxljY2dmhd+/emDNnDvO05Ndff0VVVZXa9TN69Gjs2rUL33zzDTIzM9GnTx9UV1fjxo0b2LVrFw4fPoxevXph/vz5OHHiBHx8fGBhYYGCggKsW7cO5ubm6Nu3b9N2CkVR1EeINiwoivrbiI6ORmFhIZKTk7Fr1y4MGDAA6enpMDQ0bO2iITQ0FI8fP8aGDRtw+PBh2NraYuvWrdi9ezfrJW4KwcHB0NDQwKpVq1BQUIDPPvsMa9euhYmJSZPX/f333+Py5cuIjY3Fs2fP4OnpiXXr1kFHR6fRZQUCAbKysjB79mwkJiairKwMnTt3RkJCAkJDQ1mxCQkJsLe3x6ZNmzBjxgyIRCL06tULzs7OTMzs2bNhY2ODlStXMk83OnTogH79+mHIkCFM3Lhx41BdXY2lS5dixowZ6NatG/bv348ffvhBqYzbtm1DZGQkFi1ahDZt2mDMmDH44osv8OWXX6pVPxoaGti7dy9WrlyJf//739izZw90dHRgZWWFyZMnM922hgwZgvz8fGzevBlFRUVo37493NzcEBMT0+zZqiiKoj4GHNLcEYsURVFUq8jKysIXX3yB3bt3Y/jw4a1dHOr/Kysrg0gkgkwmg76+fmsXh6IoqtnUPa/RMRYURVEURVEURTUb7QpFURRVS2FhYYNT2HK53Abf5dASKisrVQ4kro12zaEoiqLeN7RhQVEUVcunn37a4FSmbm5uKsdMtKTs7Gx88cUXDcYkJCS80dS0FEVRFPW20IYFRVFULdu2bcOLFy/q/V3xXoW3qXv37jhy5EiDMXZ2djAxMWn2i/0oiqIoqqXQwdsURVEU1YLo4G2Koj40dPA2RVH1ysrKAofDQXJycmsXhWomd3d3uLu7M9/z8/PB4XCwZcuWt7I+xbGjTnewumV7l0JDQ2lXMYqiqHeMdoWiKOqjJpfLsWTJkla9CKb+j7u7O44fP67yt+vXr6NLly7vuEQU9X6znJ2mMp2+aZtqDbRhQVHUR00ulzMvcvsQGhYWFhZ48eIFtLW130r+rq6uePHiBbhc7lvJHwDMzc0RGxurlG5qavrW1klRFEU1H21YUBTVZHK5XK23OlPvHofDAZ/Pf2v5a2hovNX8gddT6Y4aNeqtroOiKIpqeXSMBUV9gB48eIDw8HAYGRmBx+PBzs4OmzdvVoqrqanBggULYG5uDj6fD09PT9y+fZsV4+7uDqlUinPnzsHV1RU6Ojr4/vvvAQD79u2Dj48PTE1NwePxIJFI8OOPPyq9B6J2Hs7OzhAIBOjUqRPi4uKYmPLycujq6mLy5MlK5bx//z40NTVZd7FLS0sxdepUWFpagsfjwdzcHMHBwSgqKgLw+l0Q0dHRcHR0hEgkgq6uLlxcXJCZmcnkkZ+fD7FYDACIiYkBh8MBh8PBvHnz1KpnxXiDXbt2ISYmBmZmZtDT08Pw4cMhk8lQUVGBKVOmwNDQEEKhEGFhYaioqFDKZ+vWrXB0dIRAIEDbtm0REBCAv/76SykuPj4eEokEAoEAn332GX7//XelmPrGWNy4cQP+/v4Qi8UQCATo3Lkz/vGPfzC/3717F+PHj0fnzp0hEAjQrl07jBgxAvn5+Sq3ue4YC3XK1hLUPeZU+fXXX+Ho6Ag9PT3o6+ujW7duWL16NSumtLQUU6ZMQYcOHcDj8WBtbY3FixejpqbmrWwPRVHUh4Q+saCoD8yTJ0/Qu3dvcDgcTJw4EWKxGOnp6RgzZgzKysowZcoUJnbRokXQ0NDA9OnTIZPJsGTJEgQFBeH06dOsPJ8+fYoBAwYgICAAo0aNgpGREQBgy5YtEAqF+O677yAUCnHs2DFER0ejrKwMS5cuZeVRUlKCgQMHwt/fH4GBgdi1axeioqLA5XIRHh4OoVAIX19f7Ny5EytWrICmpiaz7I4dO0AIQVBQEIDXjRAXFxdcv34d4eHh6NmzJ4qKirB//37cv38f7du3R1lZGTZu3IjAwEBERETg2bNn2LRpE7y9vXHmzBk4ODhALBZj/fr1iIqKgq+vL4YNGwYAsLe3b1Kdx8bGQiAQYPbs2bh9+zbWrFkDbW1taGhooKSkBPPmzcOpU6ewZcsWdOrUCdHR0cyyCxYswA8//AB/f3+MHTsWhYWFWLNmDVxdXXHhwgW0adMGALBp0yZERkbC2dkZU6ZMwZ07dzBkyBC0bdsWHTp0aLB8ly9fhouLC7S1tTFu3DhYWloiNzcXBw4cwIIFCwAAf/75J7KzsxEQEABzc3Pk5+dj/fr1cHd3x7Vr1xp8QtWcsqlSXV3NNBAV+Hw+hEJhk4652o4cOYLAwEB4enpi8eLFAF6P2Th58iTTmJXL5XBzc8ODBw8QGRmJjh07Ijs7G3PmzMGjR4+watUqlXlXVFSwGoxlZWVN3maKoqgPAqEo6oMyZswYYmJiQoqKiljpAQEBRCQSEblcTjIzMwkA0rVrV1JRUcHErF69mgAgOTk5TJqbmxsBQOLi4pTWJZfLldIiIyOJjo4OefnypVIey5cvZ9IqKiqIg4MDMTQ0JJWVlYQQQg4fPkwAkPT0dFae9vb2xM3NjfkeHR1NAJDU1FSl9dfU1BBCCKmqqmJtGyGElJSUECMjIxIeHs6kFRYWEgBk7ty5Snk1RlGPUqmU2QZCCAkMDCQcDocMGDCAFf/5558TCwsL5nt+fj7R1NQkCxYsYMXl5OQQLS0tJr2yspIYGhoSBwcH1jbFx8cTAKy6ycvLIwBIQkICk+bq6kr09PTI3bt3WetR1BUhqvflH3/8QQCQf//730rbnJmZ2eSyqUNxrNT9hISE1FtOVcdcSEgIq64nT55M9PX1SVVVVb3r/vHHH4muri65efMmK3327NlEU1OT3Lt3T+Vyc+fOVVlmmUzWhC2nqDdjMeugyg9FtSSZTKbWeY12haKoDwghBCkpKRg8eDAIISgqKmI+3t7ekMlkOH/+PBMfFhbGGoTr4uICALhz5w4rXx6Ph7CwMKX1CQQC5t/Pnj1DUVERXFxcIJfLcePGDVaslpYWIiMjme9cLheRkZEoKCjAuXPnAABeXl4wNTXFtm3bmLgrV67g8uXLrD73KSkp6N69O3x9fZXKxOFwAACamprMttXU1KC4uBhVVVXo1asXqw5aQnBwMGuwtJOTEwghCA8PZ8U5OTnhr7/+QlVVFQAgNTUVNTU18Pf3Z+0rY2NjfPLJJ0y3rbNnz6KgoADffPMNa3+FhoZCJBI1WLbCwkKcOHEC4eHh6NixI+s3RV0B7H356tUrPH36FNbW1mjTpk2D9dWcstXH0tISR44cYX1mzpypVM7Gjrna2rRpg+fPnzf44sHdu3fDxcUFBgYGrP3h5eWF6upqnDhxQuVyc+bMgUwmYz6qurFRFEV9DGhXKIr6gBQWFqK0tBTx8fGIj49XGVNQUMC8PbruhaYivaSkhJVuZmamchagq1ev4p///CeOHTum1P1DJpOxvpuamkJXV5eVZmNjA+D1uIDevXtDQ0MDQUFBWL9+PTNAfNu2beDz+RgxYgSzXG5uLvz8/OqtB4XExEQsX74cN27cwKtXr5j0Tp06NbpsU9StR8UFdd1uQCKRCDU1NZDJZGjXrh1u3boFQgg++eQTlfkqGit3794FAKU4bW1tWFlZNVg2RSNRKpU2GPfixQvExsYiISEBDx48YL3Ru+6+rK05ZauPrq4uvLy8VP7WlGOutvHjx2PXrl0YMGAAzMzM0K9fP/j7+6N///5MzK1bt3D58mVm3E1dBQUFKtN5PB54PF5jm0VRFPXBow0LivqAKAaYjho1CiEhISpj7O3tce3aNQBgjWOorfZFJcC+S6xQWloKNzc36OvrY/78+ZBIJODz+Th//jxmzZr1xoNdg4ODsXTpUuzduxeBgYHYvn07Bg0a1OS731u3bkVoaCiGDh2KGTNmwNDQkBkAnpub+0Zlq0999dhY/dbU1IDD4SA9PV1lrFAobLlCNuLbb79FQkICpkyZgs8//xwikQgcDgcBAQHvzcDl5hxzhoaGuHjxIg4fPoz09HSkp6cjISEBwcHBSExMBPB6f3z55ZfM05G6FA1hiqIoSjXasKCoD4hYLIaenh6qq6vrveMLgGlYNEdWVhaePn2K1NRUuLq6Mul5eXkq4x8+fIjnz5+znlrcvHkTAFhvSJZKpejRowe2bdsGc3Nz3Lt3D2vWrGHlJZFIcOXKlQbLl5ycDCsrK6SmprK6/MydO5cVV/u3d00ikYAQgk6dOjV40WphYQHg9R11Dw8PJv3Vq1fIy8tD9+7d611W8dRAnfoKCQnB8uXLmbSXL1+itLS0weWaU7amauoxVxeXy8XgwYMxePBg1NTUYPz48diwYQN++OEHWFtbQyKRoLy8vMG/HYqiKKp+dIwFRX1ANDU14efnh5SUFJUXkoWFhS26LoD9dKOyshLr1q1TGV9VVYUNGzawYjds2ACxWAxHR0dW7OjRo5GRkYFVq1ahXbt2GDBgAOt3Pz8/XLp0CXv27FFaj6I8qsp3+vRp/PHHH6x4xWxHjV1Avw3Dhg2DpqYmYmJilJ4SEULw9OlTAECvXr0gFosRFxeHyspKJmbLli2NllssFsPV1RWbN2/GvXv3lNahoKmpqVSGNWvWNDqNa3PK1lRNPeZqU9SlgoaGBjP7l2JGJ39/f/zxxx84fPiw0vKlpaXM2BiKep/kL/JR+aGo1kCfWFDUB2bRokXIzMyEk5MTIiIiYGtri+LiYpw/fx5Hjx5FcXFxi6zH2dkZBgYGCAkJwaRJk8DhcJCUlKR0capgamqKxYsXIz8/HzY2Nti5cycuXryI+Ph4pbdEjxw5EjNnzsSePXsQFRWl9PuMGTOQnJyMESNGIDw8HI6OjiguLsb+/fsRFxeH7t27Y9CgQUhNTYWvry98fHyQl5eHuLg42Nraory8nMlLIBDA1tYWO3fuhI2NDdq2bQupVNromISWIJFI8NNPP2HOnDnIz8/H0KFDoaenh7y8POzZswfjxo3D9OnToa2tjZ9++gmRkZHw8PDA119/jby8PCQkJKg1juHnn39G37590bNnT4wbNw6dOnVCfn4+0tLScPHiRQDAoEGDkJSUBJFIBFtbW/zxxx84evQo2rVr12DezS1bUzT1mKtt7NixKC4uhoeHB8zNzXH37l2sWbMGDg4O6Nq1K4DXx9X+/fsxaNAghIaGwtHREc+fP0dOTg6Sk5ORn5+P9u3bt+g2URRFfVDeypxUFEW1qidPnpAJEyaQDh06EG1tbWJsbEw8PT1JfHw8IeT/pgzdvXs3azlVU5W6ubkROzs7les5efIk6d27NxEIBMTU1JTMnDmTmTJWMR1p7TzOnj1LPv/8c8Ln84mFhQVZu3ZtvdswcOBAAoBkZ2er/P3p06dk4sSJxMzMjHC5XGJubk5CQkKYaXZramrIwoULiYWFBeHxeKRHjx7k4MGDStOQEkJIdnY2cXR0JFwut0lTz9ZXjwkJCQQA+fPPP1npimlJCwsLWekpKSmkb9++RFdXl+jq6pIuXbqQCRMmkP/973+suHXr1pFOnToRHo9HevXqRU6cOEHc3NwanW6WEEKuXLlCfH19SZs2bQifzyedO3cmP/zwA/N7SUkJCQsLI+3btydCoZB4e3uTGzduEAsLC2aq19rbXHv/qls2dTR0vBGi/jFXdz8nJyeTfv36EUNDQ8LlcknHjh1JZGQkefToESv/Z8+ekTlz5hBra2vC5XJJ+/btibOzM1m2bBlrSuGGqDstI0VR1N+Fuuc1DiFq3OqhKIpqBnd3dxQVFTXaz782X19f5OTkKL0JnKLed2VlZRCJRJDJZNDX12/t4lAURTWbuuc1OsaCoqj3zqNHj5CWlobRo0e3dlEoiqIoilITHWNBUdR7Iy8vDydPnsTGjRuhra3NeqHeu1RZWdnoWBSRSKRyGl5KtcLCwgYHgnO5XLRt2/YdloiiKIpqabRhQVHUe+P48eMICwtDx44dkZiYCGNj41YpR3Z2Nr744osGYxISEhAaGvpuCvQB+PTTT5mX6ani5uaGrKysd1cgiqIoqsXRMRYURVF1lJSU4Ny5cw3G2NnZwcTE5B2V6O/v5MmTePHiRb2/GxgYKE07/HdFx1hQFPWhUfe8RhsWFEVRFNWCaMOCoqgPDR28TVEURVEURVHUO0MbFtR7IysrCxwOB8nJya1dlL+1d1mPoaGhsLS0fOvr+TvYsmULOBwO8vPzW7soTaI4Xuj4Bor6e7Kcncb6UFRrog0LinoPyeVyzJs3j17sqeFd19XChQuxd+/ed7Kuuj7G4yI/Px8cDketz9+tUUdRFPWhobNCUdR7SC6XIyYmBsDrl8tR9XvXdbVw4UIMHz4cQ4cOZaWPHj0aAQEB4PF4b23dH+NxIRaLkZSUxEpbvnw57t+/j5UrVyrFUhRFUa2HNiyoD4ZcLoeOjk5rF4P6SGlqakJTU7O1i/HB0dXVxahRo1hpv/76K0pKSpTSayOE4OXLl/RdIxRFUe8Q7QpFvTMPHjxAeHg4jIyMwOPxYGdnh82bNyvF1dTUYMGCBTA3Nwefz4enpydu377NinF3d4dUKsW5c+fg6uoKHR0dfP/99wCAffv2wcfHB6ampuDxeJBIJPjxxx+VXs5VOw9nZ2cIBAJ06tQJcXFxTEx5eTl0dXUxefJkpXLev38fmpqaiI2NZdJKS0sxdepUWFpagsfjwdzcHMHBwSgqKgLw+sVr0dHRcHR0hEgkgq6uLlxcXJCZmcnkkZ+fz9x5jYmJYbp5zJs3r0n1rU49/v777xgxYgQ6duwIHo+HDh06YOrUqSqnBd27dy+kUin4fD6kUin27NnTpPLUtnv3bjg6OkIgEKB9+/YYNWoUHjx4wIpxd3dXeVe+9riOxuoqNDQUQqEQd+7cgbe3N3R1dWFqaor58+ej7oR4y5Ytg7OzM9q1aweBQABHR0elcSocDgfPnz9HYmIisy7FuyzqG2ORnp4OFxcX6OrqQk9PDz4+Prh69arSNgmFQjx48ABDhw6FUCiEWCzG9OnTmeO2JY6L+/fvY+jQodDV1YWhoSGmTp2KiooKpTh1jouEhARwOBxcuHBBafmFCxdCU1OT2ae3bt2Cn58fjI2NwefzYW5ujoCAAMhkMrXL3hhLS0sMGjQIhw8fRq9evSAQCLBhwwamK9WWLVuUllFVf+qepyiKoihl9IkF9U48efIEvXv3BofDwcSJEyEWi5Geno4xY8agrKwMU6ZMYWIXLVoEDQ0NTJ8+HTKZDEuWLEFQUBBOnz7NyvPp06cYMGAAAgICMGrUKBgZGQF4fYEnFArx3XffQSgU4tixY4iOjkZZWRmWLl3KyqOkpAQDBw6Ev78/AgMDsWvXLkRFRYHL5SI8PBxCoRC+vr7YuXMnVqxYwbojvWPHDhBCEBQUBOB1I8TFxQXXr19HeHg4evbsiaKiIuzfvx/3799H+/btUVZWho0bNyIwMBARERF49uwZNm3aBG9vb5w5cwYODg4Qi8VYv349oqKi4Ovri2HDhgEA7O3tm1Tn6tTj7t27IZfLERUVhXbt2uHMmTNYs2YN7t+/j927dzNxGRkZ8PPzg62tLWJjY/H06VOEhYXB3Ny8SWVS7J+wsDB8+umniI2NxZMnT7B69WqcPHkSFy5cQJs2bdTOS526qq6uRv/+/dG7d28sWbIEv/32G+bOnYuqqirMnz+fiVu9ejWGDBmCoKAgVFZW4tdff8WIESNw8OBB+Pj4AACSkpIwduxYfPbZZxg3bhwAQCKR1Fu+pKQkhISEwNvbG4sXL4ZcLsf69evRt29fXLhwgTXwvbq6Gt7e3nBycsKyZctw9OhRLF++HBKJBFFRUc0+Ll68eAFPT0/cu3cPkyZNgqmpKZKSknDs2DGlWHWOi+HDh2PChAnYtm0bevTowVp+27ZtcHd3h5mZGSorK+Ht7Y2Kigp8++23MDY2xoMHD3Dw4EGUlpZCJBKpVX51/O9//0NgYCAiIyMRERGBzp07N2n5ppynaquoqGA10MrKypqzGRRFUX9fhKLegTFjxhATExNSVFTESg8ICCAikYjI5XKSmZlJAJCuXbuSiooKJmb16tUEAMnJyWHS3NzcCAASFxentC65XK6UFhkZSXR0dMjLly+V8li+fDmTVlFRQRwcHIihoSGprKwkhBBy+PBhAoCkp6ez8rS3tydubm7M9+joaAKApKamKq2/pqaGEEJIVVUVa9sIIaSkpIQYGRmR8PBwJq2wsJAAIHPnzlXKqzFNqUdVdRUbG0s4HA65e/cuk+bg4EBMTExIaWkpk5aRkUEAEAsLC7XLVllZSQwNDYlUKiUvXrxg0g8ePEgAkOjoaCbNzc2NVb8KISEhrHU2VFchISEEAPn222+ZtJqaGuLj40O4XC4pLCxk0uvWRWVlJZFKpcTDw4OVrqurS0JCQpTWlZCQQACQvLw8Qgghz549I23atCERERGsuMePHxORSMRKV5Rz/vz5rNgePXoQR0dHtba1MatWrSIAyK5du5i058+fE2trawKAZGZmMunqHheBgYHE1NSUVFdXM2nnz58nAEhCQgIhhJALFy4QAGT37t1NLnN9fHx8lI47CwsLAoD89ttvrPS8vDxWeWqrW5fqnKdUmTt3LgGg9JHJZG+0fRTVFBazDrI+FPU2yGQytc5rtCsU9dYRQpCSkoLBgweDEIKioiLm4+3tDZlMhvPnzzPxYWFh4HK5zHcXFxcAwJ07d1j58ng8hIWFKa2vdp/qZ8+eoaioCC4uLpDL5bhx4wYrVktLC5GRkcx3LpeLyMhIFBQUMG9e9vLygqmpKbZt28bEXblyBZcvX2b18U5JSUH37t3h6+urVCYOhwPgdT98xbbV1NSguLgYVVVV6NWrF6sOWoI69Vi7rp4/f46ioiI4OzuDEMJ0cXn06BEuXryIkJAQ1t3lL7/8Era2tk0q09mzZ1FQUIDx48eDz+cz6T4+PujSpQvS0t7OVIkTJ05k/q24G11ZWYmjR48y6bXroqSkBDKZDC4uLm+8X44cOYLS0lIEBgayjnlNTU04OTmxur8pfPPNN6zvLi4uSsf9mzp06BBMTEwwfPhwJk1HR4d58lKbOscFAAQHB+Phw4esbdm2bRsEAgH8/PwAgDlmDh8+DLlc3iLbUp9OnTrB29v7jZZt6nmqtjlz5kAmkzGfv/76qzmbQVEU9bdFGxbUW1dYWIjS0lLEx8dDLBazPoqGQUFBARPfsWNH1vIGBgYAXl/s1WZmZsa6cFa4evUqfH19IRKJoK+vD7FYzDQA6vbpNjU1ha6uLivNxsYGAJi+8hoaGggKCsLevXuZC6Nt27aBz+djxIgRzHK5ubmQSqWN1kdiYiLs7e3B5/PRrl07iMVipKWltWh/c0C9erx37x5CQ0PRtm1bpl+/m5sbgP+rq7t37wIAPvnkE6V1NLWriSIvVct16dKF+b0laWhowMrKipVWdx8DwMGDB9G7d2/w+Xy0bduW6Xr0pvvl1q1bAAAPDw+l4z4jI4N1zAMAn89XmtXIwMBA6bh/U3fv3oW1tTXTyFVQtS/UOS6A141LExMTptFdU1ODHTt24KuvvoKenh6A1xf73333HTZu3Ij27dvD29sb//rXv1r8eFes60019TxVG4/Hg76+PutDURT1MaJjLKi3rqamBgAwatQohISEqIyxt7fHtWvXAKDemXVIncG2qmZ7KS0thZubG/T19TF//nxIJBLw+XycP38es2bNYsrSVMHBwVi6dCn27t2LwMBAbN++HYMGDWpy//CtW7ciNDQUQ4cOxYwZM2BoaMgMAM/NzX2jstWnsXqsrq7Gl19+ieLiYsyaNQtdunSBrq4uHjx4gNDQ0Deuq5bC4XCU9jkApUH4LeH333/HkCFD4OrqinXr1sHExATa2tpISEjA9u3b3yhPRf0lJSXB2NhY6XctLfbp932ZUaopx4WmpiZGjhyJX375BevWrcPJkyfx8OFDpdmali9fjtDQUOzbtw8ZGRmYNGkSYmNjcerUqTcap1MfVeeEug2p2ttZm7rnKYqiKKp+tGFBvXVisRh6enqorq6Gl5dXvXGKhkVzZGVl4enTp0hNTYWrqyuTnpeXpzL+4cOHeP78Oeupxc2bNwGANbBWKpWiR48e2LZtG8zNzXHv3j2sWbOGlZdEIsGVK1caLF9ycjKsrKyQmprKuuCZO3cuK66+i6GWlJOTg5s3byIxMRHBwcFM+pEjR1hxFhYWAP7vDnxt//vf/5q0TkVe//vf/+Dh4aGUl+J34PXdelXdgOo+1WisrmpqanDnzh3mKQWgvI9TUlLA5/Nx+PBh1nsoEhISlPJTd98oBnUbGho2eNw3RXOOCwsLC1y5cgWEEFY+dfehuseFQnBwMJYvX44DBw4gPT0dYrFYZXekbt26oVu3bvjnP/+J7Oxs9OnTB3Fxcfjpp5/eeJvUoXhSV1paykqvexype56iKIqi6ke7QlFvnaamJvz8/JCSkqLywruwsLBF1wWwn25UVlZi3bp1KuOrqqqwYcMGVuyGDRsgFovh6OjIih09ejQyMjKwatUqtGvXDgMGDGD97ufnh0uXLqmchlVRHlXlO336NP744w9WvOJ9HHUvhlqSqrIQQrB69WpWnImJCRwcHJCYmMjqvnLkyJEmNwZ79eoFQ0NDxMXFsWbRSU9Px/Xr15nZl4DXF+Y3btxgHR+XLl3CyZMnWXmqU1dr165lbePatWuhra0NT09PAK/rgsPhsO5i5+fnq3zDtq6urlr7xdvbG/r6+li4cCFevXql9PubHPfNOS4GDhyIhw8fsqbQlcvliI+PZ8Wpe1wo2Nvbw97eHhs3bkRKSgoCAgJYT2PKyspQVVXFWqZbt27Q0NBQOdVtS9PX10f79u1x4sQJVnrdc8K7PE9RVEvKX+TD+lBUa6JPLKh3YtGiRcjMzISTkxMiIiJga2uL4uJinD9/HkePHkVxcXGLrMfZ2RkGBgYICQnBpEmTwOFwkJSUpLJLDfB6jMXixYuRn58PGxsb7Ny5ExcvXkR8fDy0tbVZsSNHjsTMmTOxZ88eREVFKf0+Y8YMJCcnY8SIEQgPD4ejoyOKi4uxf/9+xMXFoXv37hg0aBBSU1Ph6+sLHx8f5OXlIS4uDra2tigvL2fyEggEsLW1xc6dO2FjY4O2bdtCKpWqNYZDXV26dIFEIsH06dPx4MED6OvrIyUlRWWf/tjYWPj4+KBv374IDw9HcXEx1qxZAzs7O1a5G6OtrY3FixcjLCwMbm5uCAwMZKabtbS0xNSpU5nY8PBwrFixAt7e3hgzZgwKCgoQFxcHOzs71nSejdUVn8/Hb7/9hpCQEDg5OSE9PR1paWn4/vvvmTENPj4+WLFiBfr374+RI0eioKAA//rXv2BtbY3Lly+ztsHR0RFHjx7FihUrYGpqik6dOsHJyUlpW/X19bF+/XqMHj0aPXv2REBAAMRiMe7du4e0tDT06dOH1eBRR3OOi4iICKxduxbBwcE4d+4cTExMkJSUpPRSyaYcFwrBwcGYPn06ACh1gzp27BgmTpyIESNGwMbGBlVVVUhKSmIu5N+FsWPHYtGiRRg7dix69eqFEydOME+tantX5ymKoqgP1tuYkoqiVHny5AmZMGEC6dChA9HW1ibGxsbE09OTxMfHE0L+b5rUutNSqpou0s3NjdjZ2alcz8mTJ0nv3r2JQCAgpqamZObMmcyUsbWn1FTkcfbsWfL5558TPp9PLCwsyNq1a+vdhoEDBxIAJDs7W+XvT58+JRMnTiRmZmaEy+USc3NzEhISwkxfWVNTQxYuXEgsLCwIj8cjPXr0IAcPHlSaQpUQQrKzs4mjoyPhcrlNmmK0KfV47do14uXlRYRCIWnfvj2JiIggly5dUjk9Z0pKCunatSvh8XjE1taWpKamqiy3Onbu3El69OhBeDweadu2LQkKCiL3799Xitu6dSuxsrIiXC6XODg4kMOHDzeprkJCQoiuri7Jzc0l/fr1Izo6OsTIyIjMnTuXNUUqIYRs2rSJfPLJJ4TH45EuXbqQhIQEZhrR2m7cuEFcXV2JQCAgAJipZ+tON6uQmZlJvL29iUgkInw+n0gkEhIaGkrOnj3LxCjKWZeq9b/pcUEIIXfv3iVDhgwhOjo6pH379mTy5Mnkt99+U/rbaMpxQQghjx49IpqamsTGxkbptzt37pDw8HAikUgIn88nbdu2JV988QU5evSo2uWuq77pZn18fFTGy+VyMmbMGCISiYienh7x9/cnBQUFKuuvsfOUOtSdlpGiKOrvQt3zGoeQem7lUtQHzt3dHUVFRY2Oi6jN19cXOTk5Sm+wpt5PoaGhSE5ObtJTFarpioqKYGJigujoaPzwww+tXZxWV1ZWBpFIBJlMRmeIoijqg6DueY2OsaAoNT169AhpaWkYPXp0axeFot4rW7ZsQXV1Nf3boCiK+sjRMRYU1Yi8vDycPHkSGzduhLa2NuuFeu9SZWVlo328RSKRyik334Xi4mJUVlbW+7umpqbSexqo5mvN4+LYsWO4du0aFixYgKFDh7JmUlOXTCbDixcvGoxRNV0vRVEU9f6hDQuKasTx48cRFhaGjh07IjExsdUucrKzs/HFF180GJOQkIDQ0NB3U6A6hg0bhuPHj9f7u4WFBeuFdFTLaM3jYv78+czUsXWnX1bX5MmTkZiY2GAM7bFLURT190DHWFDU30RJSQnOnTvXYIydnR1MTEzeUYnYzp071+DMQQKBAH369HmHJfo4vO/HRWOuXbuGhw8fNhjzd3uvBB1jQVHUh0bd8xptWFAURVFUC6INC4qiPjR08DZFNVFWVhY4HA7rBWIUVReHw8G8efNauxgURVEU9d6hDQuKopTI5XLMmzcPWVlZrV0UilLpxIkTGDJkCDp06AA+nw9jY2P0799f6c3sCtnZ2ejbty90dHRgbGyMSZMmqZyGuKKiArNmzYKpqSkEAgGcnJxw5MiRt705FPXGLGensT4U1Zpow4KiKCVyuRwxMTG0YUG9t27evAkNDQ188803+Ne//oXp06fj8ePHcHV1xW+//caKvXjxIjw9PSGXy7FixQqMHTsW8fHxGDFihFK+oaGhWLFiBYKCgrB69Wpoampi4MCB+O9///uuNo2iKOpvi84KRVEtRC6XQ0dHp7WLQVH1ev78OXR1dVu7GCz379+Hrq4uDAwMmrTc2LFjMXbsWFba+PHjYWVlhVWrVqF///5M+vfffw8DAwNkZWUxfYMtLS0RERGBjIwM9OvXDwBw5swZ/Prrr1i6dCmmT58OAAgODoZUKsXMmTORnZ3dnE2lKIr64NEnFtRH48GDBwgPD4eRkRF4PB7s7OywefNmpbiamhosWLAA5ubm4PP58PT0VHrTtru7O6RSKc6dOwdXV1fo6Ojg+++/BwDs27cPPj4+MDU1BY/Hg0QiwY8//ojq6up683B2doZAIECnTp0QFxfHxJSXl0NXVxeTJ09WKuf9+/ehqamJ2NhYJq20tBRTp06FpaUleDwezM3NERwcjKKiIgCv33kQHR0NR0dHiEQi6OrqwsXFBZmZmUwe+fn5zPsmYmJiwOFwmjSuQDFWZdeuXYiJiYGZmRn09PQwfPhwyGQyVFRUYMqUKTA0NIRQKERYWBgqKipYeSQkJMDDwwOGhobg8XiwtbXF+vXrWTHHjh2DhoYGoqOjWenbt28Hh8NRim/M7t27YWtrCz6fD6lUij179iA0NLTRdzPUFzNv3jxwOJwmleHx48cICwuDubk5eDweTExM8NVXXylN05ueng4XFxfo6upCT08PPj4+uHr1qlK5hEIhcnNzMXDgQOjp6SEoKAjA64tqVdPPuru7w93dnfneEvuyMUePHoWpqSmCgoKQmZnZrKlldXR0IBaLUVpayqSVlZXhyJEjGDVqFGvAYXBwMIRCIXbt2sWkJScnQ1NTE+PGjWPS+Hw+xowZgz/++AN//fXXG5eNoijqY0CfWFAfhSdPnqB3797gcDiYOHEixGIx0tPTMWbMGJSVlWHKlClM7KJFi6ChoYHp06dDJpNhyZIlCAoKwunTp1l5Pn36FAMGDEBAQABGjRoFIyMjAK/fQiwUCvHdd99BKBTi2LFjiI6ORllZGZYuXcrKo6SkBAMHDoS/vz8CAwOxa9cuREVFgcvlIjw8HEKhEL6+vti5cydWrFgBTU1NZtkdO3aAEMJcLJaXl8PFxQXXr19HeHg4evbsiaKiIuzfvx/3799H+/btUVZWho0bNyIwMBARERF49uwZNm3aBG9vb5w5cwYODg4Qi8VYv349oqKi4Ovri2HDhgEA7O3tm1TnsbGxEAgEmD17Nm7fvo01a9ZAW1sbGhoaKCkpwbx583Dq1Cls2bIFnTp1YjUQ1q9fDzs7OwwZMgRaWlo4cOAAxo8fj5qaGkyYMAEA4OHhgfHjxyM2NhZDhw5Fz5498ejRI3z77bfw8vLCN998o3ZZ09LS8PXXX6Nbt26IjY1FSUkJxowZAzMzsyZtc3P5+fnh6tWr+Pbbb2FpaYmCggIcOXIE9+7dYxovSUlJCAkJgbe3NxYvXgy5XI7169ejb9++uHDhAquRU1VVBW9vb/Tt2xfLli174ydqzdmXjenXrx++/fZbJCUlYfv27bCyskJ4eDhCQ0PVqv+ysjJUVlaiqKgI//73v3HlyhWmkQ8AOTk5qKqqQq9evVjLcblcODg44MKFC0zahQsXYGNjozTjyWeffQbgdZeqDh06KJWhoqKC1aAqKytTb+MpiqI+NISiPgJjxowhJiYmpKioiJUeEBBARCIRkcvlJDMzkwAgXbt2JRUVFUzM6tWrCQCSk5PDpLm5uREAJC4uTmldcrlcKS0yMpLo6OiQly9fKuWxfPlyJq2iooI4ODgQQ0NDUllZSQgh5PDhwwQASU9PZ+Vpb29P3NzcmO/R0dEEAElNTVVaf01NDSGEkKqqKta2EUJISUkJMTIyIuHh4UxaYWEhAUDmzp2rlFdjFPUolUqZbSCEkMDAQMLhcMiAAQNY8Z9//jmxsLBgpamqQ29vb2JlZcVKe/78ObG2tiZ2dnbk5cuXxMfHh+jr65O7d+82qczdunUj5ubm5NmzZ0xaVlYWAaBUtrr1EhISohRDCCFz584lTTnFlpSUEABk6dKl9cY8e/aMtGnThkRERLDSHz9+TEQiESs9JCSEACCzZ89WysfCwoKEhIQopbu5ubGOqZbYl+p69eoV2bdvHxk6dCjR1tYmmpqaZODAgSQ1NZW17rq8vb0JAAKAcLlcEhkZSV68eMH8vnv3bgKAnDhxQmnZESNGEGNjY+a7nZ0d8fDwUIq7evVqvX/vhPzfvq77kclkTakCinojFrMOsj4U9TbIZDK1zmu0KxT1wSOEICUlBYMHDwYhBEVFRczH29sbMpkM58+fZ+LDwsLA5XKZ7y4uLgCAO3fusPLl8XgICwtTWp9AIGD+/ezZMxQVFcHFxQVyuRw3btxgxWppaSEyMpL5zuVyERkZiYKCAualZ15eXjA1NcW2bduYuCtXruDy5csYNWoUk5aSkoLu3bvD19dXqUyKLjmamprMttXU1KC4uJi5m1u7DlpCcHAwtLW1me9OTk4ghCA8PJwV5+TkhL/++gtVVVVMWu06lMlkKCoqgpubG+7cuQOZTMb8pqOjgy1btuD69etwdXVFWloaVq5ciY4dO6pdzocPHyInJ4fpGqPg5uaGbt26NWmbm0MgEIDL5SIrK6veFw0eOXIEpaWlCAwMZB3HmpqacHJyYnVpU4iKimp22ZqzL9WlpaWFIUOGYM+ePbh//z4WL16Mu3fvYtiwYTA3N8eMGTPw6tUrpeUWLVqEjIwMbNq0Cb1790ZlZSVr/S9evADw+u+1Lj6fz/yuiK0vrnZedc2ZMwcymYz50C5TFEV9rGjDgvrgFRYWorS0FPHx8RCLxayPomFQUFDAxNe9KFUMKq17sWdmZsZqgChcvXoVvr6+EIlE0NfXh1gsZhoAtS+KAcDU1FRpMK2NjQ0AMP3qNTQ0EBQUhL1790IulwMAtm3bBj6fz5rVJjc3F1KptNH6SExMhL29Pfh8Ptq1awexWIy0tDSlsjVX3XoUiUQAoNSVRCQSoaamhrX+kydPwsvLC7q6umjTpg3EYjHTvaVuOfv06YOoqCicOXMG3t7eShe7jbl79y4AwNraWuk3VWlvC4/Hw+LFi5Geng4jIyO4urpiyZIlePz4MRNz69YtAK+7gdU9ljMyMljHMfD6Yt3c3LzZZWvOvnwThoaGmDZtGrKzszF27FgUFBRg2bJleP78uVKsg4MDvvzyS4SHh+PIkSM4c+YMa/yIopGqauzHy5cvWY1YgUBQb1ztvOri8XjQ19dnfSiKoj5GdIwF9cGrqakBAIwaNQohISEqY+zt7XHt2jUAYI1jqI3UGVSq6iKjtLQUbm5u0NfXx/z58yGRSMDn83H+/HnMmjWLKUtTBQcHY+nSpdi7dy8CAwOxfft2DBo0iLnAU9fWrVsRGhqKoUOHYsaMGTA0NGQGgOfm5r5R2epTXz02Vr+5ubnw9PREly5dsGLFCnTo0AFcLheHDh3CypUrleqwoqKCmRY3Nzf3nc/OVd8A7bqD9dUxZcoUDB48GHv37sXhw4fxww8/IDY2FseOHUOPHj2YbU9KSoKxsbHS8lpa7FM6j8eDhoby/aOGyqxq/7zpvnwThBBkZWVh8+bNSElJwcuXL+Hp6YmxY8c2esHO5XIxZMgQLFq0CC9evIBAIICJiQkA4NGjR0rxjx49gqmpKfPdxMQEDx48UBkHgBVLURRFKaMNC+qDJxaLoaenh+rqanh5edUbp2hYNEdWVhaePn2K1NRUuLq6Mul5eXkq4x8+fKg0BejNmzcBgDUIVyqVokePHti2bRvMzc1x7949rFmzhpWXRCLBlStXGixfcnIyrKyskJqayrq4nDt3LiuuqbMZtaQDBw6goqIC+/fvZ90pV9XNB3hd9uvXr2PZsmWYNWsWZs+ejZ9//lnt9VlYWACA0sxf9aXVZWBgwJqFSEHxJKSpJBIJpk2bhmnTpuHWrVtwcHDA8uXLsXXrVkgkEgCv7+g3dCw3p8xWVlZvnG9z5OfnIzExEVu2bEF+fj7Mzc0xbdo0jBkzptGZuWp78eIFCCF49uwZBAIBpFIptLS0cPbsWfj7+zNxlZWVuHjxIivNwcEBmZmZKCsrYzViFBM3ODg4NHs7KYqiPmS0KxT1wdPU1ISfnx9SUlJUXngXFha26LoA9h3byspKrFu3TmV8VVUVNmzYwIrdsGEDxGIxHB0dWbGjR49GRkYGVq1ahXbt2mHAgAGs3/38/HDp0iXs2bNHaT2K8qgq3+nTp/HHH3+w4hV3/FVdfL5tqsook8mQkJCgFHv69GksW7YMU6ZMwbRp0zBjxgysXbsWx48fV3t9pqamkEql+Pe//816E/Px48eRk5PT6PISiQQymQyXL19m0h49eqRyPzRELpczXW5q562np8d0z/H29oa+vj4WLlyocryBuseyRCLBqVOnUFlZyaQdPHiwVcYG5OTkwMvLC1ZWVliwYAF69OiBtLQ05Ofn48cff6y3UVG32xfw+nhNSUlBhw4dYGhoCOB19ywvLy9s3boVz549Y2KTkpJQXl7O6k44fPhwVFdXIz4+nkmrqKhAQkICnJycVM4IRVGtLX+RD+tDUa2JPrGgPgqLFi1CZmYmnJycEBERAVtbWxQXF+P8+fM4evQoiouLW2Q9zs7OMDAwQEhICCZNmgQOh4OkpKR6u4aYmppi8eLFyM/Ph42NDXbu3ImLFy8iPj6eNVgWAEaOHImZM2diz549iIqKUvp9xowZSE5OxogRIxAeHg5HR0cUFxdj//79iIuLQ/fu3TFo0CCkpqbC19cXPj4+yMvLQ1xcHGxtbVkX1QKBALa2tti5cydsbGzQtm1bSKVStcZwNFe/fv3A5XIxePBgREZGory8HL/88gsMDQ1Z3VlevnyJkJAQfPLJJ1iwYAGA1+/dOHDgAMLCwpCTk6P2y+AWLlyIr776Cn369EFYWBhKSkqwdu1aSKVSVr2oEhAQgFmzZsHX1xeTJk1ipn+1sbFp0oD4mzdvwtPTE/7+/rC1tYWWlhb27NmDJ0+eICAgAACgr6+P9evXY/To0ejZsycCAgIgFotx7949pKWloU+fPli7dm2j6xo7diySk5PRv39/+Pv7Izc3l/VE5F06d+4cM1g7JCSEaRA0ZsCAATA3N4eTkxMMDQ1x7949JCQk4OHDh9i5cycrdsGCBXB2doabmxvGjRuH+/fvY/ny5ejXrx/rRXpOTk4YMWIE5syZg4KCAlhbWyMxMRH5+fnYtGlTi243RVHUB+mtzUtFUe+ZJ0+ekAkTJpAOHToQbW1tYmxsTDw9PUl8fDwh5P+m1ty9ezdruby8PAKAJCQkMGlubm7Ezs5O5XpOnjxJevfuTQQCATE1NSUzZ85kpozNzMxUyuPs2bPk888/J3w+n1hYWJC1a9fWuw0DBw4kAEh2drbK358+fUomTpxIzMzMCJfLJebm5iQkJISZZrempoYsXLiQWFhYEB6PR3r06EEOHjyocsrU7Oxs4ujoSLhcbpOmnq2vHhMSEggA8ueff7LSFVN1FhYWMmn79+8n9vb2hM/nE0tLS7J48WKyefNmAoDk5eURQgiZOnUq0dTUJKdPn2bld/bsWaKlpUWioqLUKq/Cr7/+Srp06UJ4PB6RSqVk//79xM/Pj3Tp0oUVp6ouMjIyiFQqJVwul3Tu3Jls3bq1ydPNFhUVkQkTJpAuXboQXV1dIhKJiJOTE9m1a5dSbGZmJvH29iYikYjw+XwikUhIaGgoOXv2LBMTEhJCdHV1613f8uXLiZmZGeHxeKRPnz7k7Nmz9U4325x92Zjy8nK1Y2tbu3Yt6du3L2nfvj3R0tIiYrGYDB48WOW0soQQ8vvvvxNnZ2fC5/OJWCwmEyZMIGVlZUpxL168INOnTyfGxsaEx+ORTz/9lPz2229NKpu60zJSFEX9Xah7XuMQ0oxRdhRFvTF3d3cUFRU1Oi6iNl9fX+Tk5KjV959qPsULA48cOdLaRaH+RsrKyiASiSCTyegMURRFfRDUPa/RMRYU9Tfx6NEjpKWlYfTo0a1dlA/Oq1evlN69kJWVhUuXLsHd3b11CkVRFEVRfzN0jAVFvefy8vJw8uRJbNy4Edra2qwX6r1LlZWVjY5FEYlE9c713xpkMlm9LzVTMDY2xoMHD+Dl5YVRo0bB1NQUN27cQFxcHIyNjfHNN9+8s3J8SD7GbaYoivrY0YYFRb3njh8/jrCwMHTs2BGJiYmtdjGWnZ2NL774osGYhIQE1svJWtvkyZORmJjYYAwhBAYGBnB0dMTGjRtRWFgIXV1d+Pj4YNGiRWjXrt07K8eH5GPcZoqiqI8dHWNBUZRaSkpKcO7cuQZj7OzsmBeSvQ+uXbuGhw8fNhjTnPdB/N3K8S59jNusQMdYUBT1oVH3vEYbFhRFURTVgmjDgqKoDw0dvE1RFEVRFEVR1DvzVhoWWVlZ4HA4SE5OfhvZU03k7u7+Uc5sU3e78/PzweFwsGXLllYr09syb948cDic1i7G35alpeVbGxui2DdFRUUtkh+Hw8G8efNaJK+moscZRVEU1RD6xOItk8vlmDdvHrKyslq7KBTVZO7u7qwLbkXjjMPh4KefflK5TFBQEDgcDoRC4TsqJaWOhw8fYt68ebh48eJbX1doaOgHtf/r/h1Q1PvEcnYa86Go1kYbFm+ZXC5HTExMqzYsMjIykJGR0Wrrf19YWFjgxYsXH+R7IP75z382OrVnS+Lz+dixY4dS+vPnz7Fv3z7w+fx3VhZKPQ8fPkRMTMw7aVhQFEVRH6f3smEhl8tbuwgfBEU9crlccLncVi7Na4SQd3oBXBuHwwGfz4empmarrP9t0tLSeqcX8wMHDsS1a9dw6dIlVvq+fftQWVmJL7/88p2VhaIoiqKo90OTGxYPHjxAeHg4jIyMwOPxYGdnh82bN6uMrampwYIFC2Bubg4+nw9PT0/cvn2bFePu7g6pVIpz587B1dUVOjo6+P777wG8vkjx8fGBqakpeDweJBIJfvzxR1RXV9ebh7OzMwQCATp16oS4uDgmpry8HLq6upg8ebJSOe/fvw9NTU3ExsYyaaWlpZg6dSosLS3B4/Fgbm6O4OBgpp90ZWUloqOj4ejoCJFIBF1dXbi4uCAzM5PJIz8/H2KxGAAQExPDdCFRt3+0YqzKzp078f3338PY2Bi6uroYMmQI/vrrL7Xrse5YA0W+u3btQkxMDMzMzKCnp4fhw4dDJpOhoqICU6ZMgaGhIYRCIcLCwlBRUcFaX0JCAjw8PGBoaAgejwdbW1usX79eaRssLS0xaNAgHD58GL169YJAIMCGDRvg5uaG7t27q9zuzp07w9vbW606UoiPj4dEIoFAIMBnn32G33//XSlG1RiLy5cvIzQ0FFZWVuDz+TA2NkZ4eDiePn2qtHxWVhZ69eoFPp8PiUSCDRs2qOxzzuFwMHHiROzduxdSqZT5O/ntt9+U8rxw4QIGDBgAfX19CIVCeHp64tSpU6yYV69eISYmBp988gn4fD7atWuHvn374siRI0yMqnIcOXIEffv2RZs2bSAUCtG5c2fmmGiuzz//HJ06dcL27dtZ6du2bUP//v3Rtm1bpWXqO/brjm9QZ3sB4MaNG/D394dYLIZAIEDnzp3xj3/8g/k9NDQUlpaWSutTd5zAnTt3MGLECLRt2xY6Ojro3bs30tKUuxqsWbMGdnZ20NHRgYGBAXr16qVUL3XdvXsX1tbWkEqlePLkCYDX55wpU6agQ4cO4PF4sLa2xuLFi1FTU9NoWRs7L2dlZeHTTz8FAISFhTHnIsXfwu+//44RI0agY8eO4PF46NChA6ZOndqiNwHOnj0Lb29vtG/fnjlHh4eHs2J+/fVXODo6Qk9PD/r6+ujWrRtWr17N/F7fvtuyZQs4HA7y8/NZ6enp6XBxcYGuri709PTg4+ODq1evsmIeP36MsLAwmJubg8fjwcTEBF999ZVSXhRFUVTjmvSCvCdPnqB3797MhZNYLEZ6ejrGjBmDsrIyTJkyhRW/aNEiaGhoYPr06ZDJZFiyZAmCgoJw+vRpVtzTp08xYMAABAQEYNSoUTAyMgLw+j8LoVCI7777DkKhEMeOHUN0dDTKysqwdOlSVh4lJSUYOHAg/P39ERgYiF27diEqKgpcLhfh4eEQCoXw9fXFzp07sWLFCtZd6x07doAQgqCgIACvGyEuLi64fv06wsPD0bNnTxQVFWH//v24f/8+2rdvj7KyMmzcuBGBgYGIiIjAs2fPsGnTJnh7e+PMmTNwcHCAWCzG+vXrERUVBV9fXwwbNgwAYG9v35Rqx4IFC8DhcDBr1iwUFBRg1apV8PLywsWLF1lvOa6vHusTGxsLgUCA2bNn4/bt21izZg20tbWhoaGBkpISzJs3D6dOncKWLVvQqVMnREdHM8uuX78ednZ2GDJkCLS0tHDgwAGMHz8eNTU1mDBhAms9//vf/xAYGIjIyEhERESgc+fOEAqFiIiIwJUrVyCVSpnYP//8Ezdv3sQ///lPtetn06ZNiIyMhLOzM6ZMmYI7d+5gyJAhaNu2LTp06NDgskeOHMGdO3cQFhYGY2NjXL16FfHx8bh69SpOnTrFXMRcuHAB/fv3h4mJCWJiYlBdXY358+czDce6/vvf/yI1NRXjx4+Hnp4efv75Z/j5+eHevXvMC9euXr0KFxcX6OvrY+bMmdDW1saGDRvg7u6O48ePw8nJCcDri6nY2FiMHTsWn332GcrKynD27FmcP3++3icDV69exaBBg2Bvb4/58+eDx+Ph9u3bOHnypNr12pjAwEBs3boVixYtYgYnZ2RkICkpSWUjSl3qbO/ly5fh4uICbW1tjBs3DpaWlsjNzcWBAwewYMGCZm/bkydP4OzsDLlcjkmTJqFdu3ZITEzEkCFDkJycDF9fXwDAL7/8gkmTJmH48OGYPHkyXr58icuXL+P06dMYOXKkyrxzc3Ph4eGBtm3b4siRI2jfvj3kcjnc3Nzw4MEDREZGomPHjsjOzsacOXPw6NEjrFq1qsGyNnZe7tq1K+bPn4/o6GiMGzcOLi4uAABnZ2cAwO7duyGXyxEVFYV27drhzJkzWLNmDe7fv4/du3c3uz4LCgrQr18/iMVizJ49G23atEF+fj5SU1OZmCNHjiAwMBCenp5YvHgxAOD69es4efKkyhtCjUlKSkJISAi8vb2xePFiyOVyrF+/Hn379sWFCxeYRqefnx+uXr2Kb7/9FpaWligoKMCRI0dw7949lQ1TVSoqKlg3X8rKyppcXoqiqA8CaYIxY8YQExMTUlRUxEoPCAggIpGIyOVyQgghmZmZBADp2rUrqaioYOJWr15NAJCcnBwmzc3NjQAgcXFxSutT5FdbZGQk0dHRIS9fvlTKY/ny5UxaRUUFcXBwIIaGhqSyspIQQsjhw4cJAJKens7K097enri5uTHfo6OjCQCSmpqqtP6amhpCCCFVVVWsbSOEkJKSEmJkZETCw8OZtMLCQgKAzJ07Vymvxijq0czMjJSVlTHpu3btIgDI6tWrlepAVT26ubmxtk+Rr1QqZeqGEEICAwMJh8MhAwYMYC3/+eefEwsLC1aaqn3j7e1NrKysWGkWFhYEAPntt99Y6aWlpYTP55NZs2ax0idNmkR0dXVJeXm5Uv6qVFZWEkNDQ+Lg4MDaH/Hx8QQAa7vz8vIIAJKQkNDgduzYsYMAICdOnGDSBg8eTHR0dMiDBw+YtFu3bhEtLS1S988IAOFyueT27dtM2qVLlwgAsmbNGiZt6NChhMvlktzcXCbt4cOHRE9Pj7i6ujJp3bt3Jz4+Pg3Ww9y5c1nlWLlyJQFACgsLG1yuqRR1uHTpUnLlyhUCgPz++++EEEL+9a9/EaFQSJ4/f05CQkKIrq4ua9n6/g4sLCxISEgI812d7XV1dSV6enrk7t27rHTF3ychhISEhCgdt4Qo15WqMkyZMoW1bYQQ8uzZM9KpUydiaWlJqqurCSGEfPXVV8TOzq7BsirWV1hYSK5fv05MTU3Jp59+SoqLi5mYH3/8kejq6pKbN2+ylp09ezbR1NQk9+7dY9Lq1qO65+U///xT6fhXUPV3EBsbSzgcDquOVdWdKnX3/549ewgA8ueff9a7zOTJk4m+vj6pqqqqN6a+9SckJBAAJC8vjxDyel+1adOGREREsOIeP35MRCIRk15SUsIcz82hKFfdj0wma1a+FKUOi1kHmQ9FvS0ymUyt85raXaEIIUhJScHgwYNBCEFRURHz8fb2hkwmw/nz51nLhIWFsfr2K+6S3blzhxXH4/EQFhamtM7ad+OfPXuGoqIiuLi4QC6X48aNG6xYLS0tREZGMt+5XC4iIyNRUFDAvC3Yy8sLpqam2LZtGxN35coVXL58GaNGjWLSUlJS0L17d+auZG2KO9iamprMttXU1KC4uBhVVVXo1auXUj00V3BwMPT09Jjvw4cPh4mJCQ4dOsSKq68eG8pXW1ub+e7k5ARCiFL3BCcnJ/z111+oqqpi0mrvG5lMhqKiIri5ueHOnTuQyWSs5Tt16qTUtUkkEuGrr75inhYBQHV1NXbu3ImhQ4dCV1dXrW04e/YsCgoK8M0337COtdDQUIhEokaXr70dL1++RFFREXr37g0AzH6srq7G0aNHMXToUJiamjLx1tbWGDBggMp8vby8IJFImO/29vbQ19dnjv3q6mpkZGRg6NChsLKyYuJMTEwwcuRI/Pe//2XuerZp0wZXr17FrVu3Gt0ehTZt2gB43Z1Qna40b8LOzg729vbMIO7t27fjq6++go6OTrPybWx7CwsLceLECYSHh6Njx46s31pqKtRDhw7hs88+Q9++fZk0oVCIcePGIT8/H9euXWPKev/+ffz555+N5nnlyhW4ubnB0tISR48ehYGBAfPb7t274eLiAgMDA9a51cvLC9XV1Thx4oTKPN/kvKxK7b+D58+fo6ioCM7OziCE4MKFC40u3xjF8Xjw4EG8evWq3pjnz58rdXl7E0eOHEFpaSkCAwNZdaKpqQknJyemy6pAIACXy0VWVhZKSkreeH1z5syBTCZjPnW7qlIURX0s1G5YFBYWorS0FPHx8RCLxayP4mK2oKCAtUzd//QV/5HWPYGbmZmpHFx89epV+Pr6QiQSQV9fH2KxmGkA1L14NTU1VboYtbGxAQCmr6yGhgaCgoKwd+9eZmDztm3bwOfzMWLECGa53NxcVvec+iQmJsLe3p7pBy4Wi5GWlqZUtub65JNPWN85HA6sra2V+gDXV4/1qbt/FBfidbsPiUQi1NTUsLbr5MmT8PLygq6uLtq0aQOxWMz031fVsFAlODgY9+7dY8ZDHD16FE+ePGnSrE13794FoFxH2trarAv2+hQXF2Py5MkwMjKCQCCAWCxmyqvYjoKCArx48QLW1tZKy6tKA5TrFnh9/CuO/cLCQsjlcnTu3FkprmvXrqipqWEuTubPn4/S0lLY2NigW7dumDFjBi5fvtzgdn399dfo06cPxo4dCyMjIwQEBGDXrl0t3sgYOXIkdu/ejdu3byM7O7ve7j9N0dj2Khpn6vyNvqm7d+/Wu28UvwPArFmzIBQK8dlnn+GTTz7BhAkT6u1uNnjwYOjp6eHw4cNKby29desWfvvtN6Vzq5eXFwDlc6vCm5yXVbl37x5CQ0PRtm1bCIVCiMViuLm5AVD+e34Tbm5u8PPzQ0xMDNq3b4+vvvoKCQkJrO5D48ePh42NDQYMGABzc3OEh4e/cZc6RaPUw8NDqV4yMjKYOuHxeFi8eDHS09NhZGQEV1dXLFmyBI8fP27S+ng8HvT19VkfiqKoj5HaYywUFySjRo1CSEiIypi6Ywfqm31HcYdaofbdMoXS0lK4ublBX18f8+fPh0QiAZ/Px/nz5zFr1qw3vkAKDg7G0qVLsXfvXgQGBmL79u0YNGiQWne3a9u6dStCQ0MxdOhQzJgxA4aGhswA8Nzc3DcqW3OpqseG1Ld/Gttvubm58PT0RJcuXbBixQp06NABXC4Xhw4dwsqVK5X2TX3l8vb2hpGREbZu3QpXV1ds3boVxsbGzMXUu+Dv74/s7GzMmDEDDg4OEAqFqKmpQf/+/Zt1Ea7usa8OV1dX5ObmYt++fcjIyMDGjRuxcuVKxMXFYezYsSqXEQgEOHHiBDIzM5GWlobffvsNO3fuhIeHBzIyMlpsZqzAwEDMmTMHERERaNeuHfr169fkPOpOxvAm26tKfU8v6q6vObp27Yr//e9/OHjwIH777TekpKRg3bp1iI6ORkxMDCvWz88PiYmJ2LZtG+vpKvD6/Prll19i5syZKtejuElS15ucl+uqrq7Gl19+ieLiYsyaNQtdunSBrq4uHjx4gNDQ0BZpjCpemHrq1CkcOHAAhw8fRnh4OJYvX45Tp05BKBTC0NAQFy9exOHDh5Geno709HQkJCQgODgYiYmJTD71bUNtijInJSXB2NhYKV5L6//+65syZQoGDx6MvXv34vDhw/jhhx8QGxuLY8eOoUePHs3edoqiqI+J2g0LsVgMPT09VFdXv5MLv6ysLDx9+hSpqalwdXVl0vPy8lTGP3z4EM+fP2c9tbh58yYAsAbgSaVS9OjRA9u2bYO5uTnu3buHNWvWsPKSSCS4cuVKg+VLTk6GlZUVUlNTWf/ZzZ07lxXXEl0z6nYJIYTg9u3bTR4E3lIOHDiAiooK7N+/n3VnvvaMWOrQ1NTEyJEjsWXLFixevBh79+5FREREky56LSwsALyuIw8PDyb91atXyMvLq3fmKeD1k7P//Oc/iImJYQ1Mr1vfhoaG4PP5SjOaAVCZpg6xWAwdHR3873//U/rtxo0b0NDQYD05atu2LcLCwhAWFoby8nK4urpi3rx5DV5oa2howNPTE56enlixYgUWLlyIf/zjH8jMzGyxv+GOHTuiT58+yMrKQlRUFOuCrS4DAwOUlpay0iorK/Ho0SOl2Ia2V/EkqrG/UVXrA/7vaUNDLCws6t03it8VdHV18fXXX+Prr79GZWUlhg0bhgULFmDOnDmsKYCXLl0KLS0tZkB/7ac7EokE5eXlTd4vTTkv13cuysnJwc2bN5GYmIjg4GAmvSW6JNXVu3dv9O7dGwsWLMD27dsRFBSEX3/9lTmOuVwuBg8ejMGDB6Ompgbjx4/Hhg0b8MMPP8Da2pp56l1aWsp0rwKU96miG6KhoaFadSqRSDBt2jRMmzYNt27dgoODA5YvX46tW7e20JZTFEV9HNTuCqWpqQk/Pz+kpKSo/A+9sLCwRQumuLisfYe3srIS69atUxlfVVWFDRs2sGI3bNgAsVgMR0dHVuzo0aORkZGBVatWoV27dkr95P38/HDp0iXs2bNHaT2K8qgq3+nTp/HHH3+w4hX9zVVd4Kjr3//+N549e8Z8T05OxqNHj+rt3/+2qdp2mUyGhISEJuc1evRolJSUIDIyEuXl5ayxLuro1asXxGIx4uLiUFlZyaRv2bKl0TpXtR0AlGbg0dTUhJeXF/bu3YuHDx8y6bdv30Z6enqTyls7z379+mHfvn2sLm1PnjzB9u3b0bdvX6Y7Rd2pb4VCIaytrZWmAK6tuLhYKc3BwQEAGlzuTfz000+YO3cuvv322wbjJBKJ0liB+Ph4pbvNjW2vWCyGq6srNm/ejHv37rFia+9LiUQCmUzG6kb16NEjlX/XdQ0cOBBnzpxh/T0/f/4c8fHxsLS0hK2trcqycrlc2NraghCiNJaAw+EgPj4ew4cPR0hICPbv38/85u/vjz/++AOHDx9WKktpaSlrfFNtTTkvK2661P27UPV3QAhhTfPaXCUlJUp/Z3WPx7p1qaGhwdw8UcQoGgy1j6Pnz58zTzQUvL29oa+vj4ULF6oc06GoF7lcjpcvX7J+k0gk0NPTa/G/E4p6W/IX+TAfimptTZpudtGiRcjMzISTkxMiIiJga2uL4uJinD9/HkePHlV5MfOmnJ2dYWBggJCQEEyaNAkcDgdJSUn1diUxNTXF4sWLkZ+fDxsbG+zcuRMXL15EfHw8a4Ay8Lpf+MyZM7Fnzx5ERUUp/T5jxgwkJydjxIgRCA8Ph6OjI4qLi7F//37ExcWhe/fuGDRoEFJTU+Hr6wsfHx/k5eUhLi4Otra2KC8vZ/ISCASwtbXFzp07YWNjg7Zt20IqlTapf3jbtm3Rt29fhIWF4cmTJ1i1ahWsra0RERHRhBptOf369WPuLCoaBL/88gsMDQ1V3n1uSI8ePSCVSrF792507doVPXv2bNLy2tra+OmnnxAZGQkPDw98/fXXyMvLQ0JCQqNjLPT19Zk+1a9evYKZmRkyMjJUPhWbN28eMjIy0KdPH0RFRaG6uhpr166FVCp94zcZ//TTT8y7JsaPHw8tLS1s2LABFRUVWLJkCRNna2sLd3d3ODo6om3btjh79iySk5MxceLEevOeP38+Tpw4AR8fH1hYWKCgoADr1q2Dubk5a0ByS3Bzc2P64zdk7Nix+Oabb+Dn54cvv/wSly5dwuHDh9G+fXtWnDrb+/PPP6Nv377o2bMnxo0bh06dOiE/Px9paWnM/ggICMCsWbPg6+uLSZMmMdON2tjYNDqgefbs2dixYwcGDBiASZMmoW3btkhMTEReXh5SUlKgofH6nky/fv1gbGyMPn36wMjICNevX8fatWvh4+PDmnBBQUNDA1u3bsXQoUPh7++PQ4cOwcPDAzNmzMD+/fsxaNAghIaGwtHREc+fP0dOTg6Sk5ORn5+vVE8K6p6XJRIJ2rRpg7i4OOjp6UFXVxdOTk7o0qULJBIJpk+fjgcPHkBfXx8pKSnNGsxcV2JiItatWwdfX19IJBI8e/YMv/zyC/T19TFw4EAAr4+P4uJieHh4wNzcHHfv3sWaNWvg4ODAjG3p168fOnbsiDFjxmDGjBnQ1NTE5s2bIRaLWY1MfX19rF+/HqNHj0bPnj0REBDAxKSlpaFPnz5Yu3Ytbt68CU9PT/j7+8PW1hZaWlrYs2cPnjx5goCAgBbbfoqiqI9GU6ebevLkCZkwYQLp0KED0dbWJsbGxsTT05PEx8czMYrpTHfv3s1aVtV0n25ubvVO13jy5EnSu3dvIhAIiKmpKZk5cyYzZWxmZqZSHmfPniWff/454fP5xMLCgqxdu7be7Rg4cCABQLKzs1X+/vTpUzJx4kRiZmZGuFwuMTc3JyEhIcyUjjU1NWThwoXEwsKC8Hg80qNHD3Lw4EGVU1xmZ2cTR0dHwuVymzT1rKIed+zYQebMmUMMDQ2JQCAgPj4+StNsNlSP9U03W3f/KKZsrDslZO3pMhX2799P7O3tCZ/PJ5aWlmTx4sVk8+bNrCkfCXk9jWdjU4cuWbKEACALFy5sMK4h69atI506dSI8Ho/06tWLnDhxQmm7VR1/9+/fJ76+vqRNmzZEJBKRESNGkIcPH6rcT//5z39Ijx49CJfLJRKJhGzcuJFMmzaN8Pl8VhwAMmHCBKUy1p3SlBBCzp8/T7y9vYlQKCQ6Ojrkiy++UDomf/rpJ/LZZ5+RNm3aEIFAQLp06UIWLFjAmiq47jSc//nPf8hXX31FTE1NCZfLJaampiQwMFBpOtOmqj3dbENUTTdbXV1NZs2aRdq3b090dHSIt7c3uX37tlK9qLO9hBBy5coVZt/x+XzSuXNn8sMPP7BiMjIyiFQqJVwul3Tu3Jls3bpVrelmCSEkNzeXDB8+nMn/s88+IwcPsqdz3LBhA3F1dSXt2rUjPB6PSCQSMmPGDNZ0fKr+fuRyOXFzcyNCoZCcOnWKEPJ6itQ5c+YQa2trwuVySfv27YmzszNZtmwZa9tVHZvqnJcJIWTfvn3E1taWmSZZ8bdw7do14uXlRYRCIWnfvj2JiIhgpkiu/ffyptPNnj9/ngQGBpKOHTsSHo9HDA0NyaBBg8jZs2eZmOTkZNKvXz9iaGhIuFwu6dixI4mMjCSPHj1i5X3u3Dni5OTExKxYsUJpulmFzMxM4u3tTUQiEeHz+UQikZDQ0FBmvUVFRWTChAmkS5cuRFdXl4hEIuLk5ER27drV6DY2RN1pGSmKov4u1D2vcQh5g9Gk7xl3d3cUFRU12ue6Nl9fX+Tk5LxxH/l3ISsrC1988QV2796N4cOHt3Zx3prVq1dj6tSpyM/PVzmb0vts6NChTZ4KlqKoD1tZWRlEIhFkMhmdIYqiqA+Cuuc1tcdYfEgePXqEtLS0Jk1rSr0dhBBs2rQJbm5u732j4sWLF6zvt27dwqFDh+Du7t46BaIoiqIoinqPNGmMxd9dXl4eTp48iY0bN0JbW1tpysd3pbKystHxKE2d/vbv5vnz59i/fz8yMzORk5ODffv2KcUUFxezBmTXpampCbFY/DaLyWJlZYXQ0FBYWVnh7t27WL9+Pbhcbr1ThL7PCgsLG5x2lcvlom3btu+wRBRFURRF/d19VA2L48ePIywsDB07dkRiYqLK+c3fhezsbHzxxRcNxiQkJLCmyf3QFBYWYuTIkWjTpg2+//57DBkyRClm2LBhOH78eL15WFhYKL0k8G3q378/duzYgcePH4PH4+Hzzz/HwoULlV7O93fw6aefNjjtqpubG7Kyst5dgSiKoiiK+tv7IMZY/N2UlJTg3LlzDcbY2dnBxMTkHZXo/XTu3LkGZ6YRCATo06fPOyzRh+PkyZNKXbtqMzAwUJqmmaIo9dAxFhRFfWjUPa/RhgVFURRFtSDasKAo6kNDB29TVBNlZWWBw+EgOTm5tYtCvcc4HA7mzZvX2sWgKIqiqPcObVhQFKVELpdj3rx5dJwF9d76z3/+g/DwcNjY2EBHRwdWVlYYO3ZsvS/pzM7ORt++faGjowNjY2NMmjSJ9TJThYqKCsyaNQumpqYQCARwcnLCkSNH3vbmUNQbs5ydBsvZaa1dDIoCQBsWFEWpIJfLERMTQxsW1Htr1qxZyMrKgq+vL37++WcEBARg165d6NGjBx4/fsyKvXjxIjw9PSGXy7FixQqMHTsW8fHxGDFihFK+oaGhWLFiBYKCgrB69Wpoampi4MCB+O9///uuNo2iKOpv66OaFYqi3ia5XA4dHZ3WLgZF1ev58+fQ1dVt7WKw3L9/H7q6ujAwMGjScitWrEDfvn2hofF/98f69+8PNzc3rF27Fj/99BOT/v3338PAwABZWVlM32BLS0tEREQgIyMD/fr1AwCcOXMGv/76K5YuXYrp06cDAIKDgyGVSjFz5kxkZ2c3d3MpiqI+aPSJBfXRePDgAcLDw2FkZAQejwc7Ozts3rxZKa6mpgYLFiyAubk5+Hw+PD09ld7Q7u7uDqlUinPnzsHV1RU6Ojr4/vvvAQD79u2Dj48PTE1NwePxIJFI8OOPPyq9N6J2Hs7OzhAIBOjUqRPi4uKYmPLycujq6mLy5MlK5bx//z40NTURGxvLpJWWlmLq1KmwtLQEj8eDubk5goODUVRUBOD1O1Sio6Ph6OgIkUgEXV1duLi4IDMzk8kjPz+feT9ITEwMOBxOk8YVKMaq7Nq1CzExMTAzM4Oenh6GDx8OmUyGiooKTJkyBYaGhhAKhQgLC0NFRQUrj4SEBHh4eMDQ0BA8Hg+2trZYv349K+bYsWPQ0NBAdHQ0K3379u3gcDhK8Y3ZvXs3bG1twefzIZVKsWfPHoSGhjY67XN9MfPmzQOHw2lSGR4/foywsDCYm5uDx+PBxMQEX331ldK0yunp6XBxcYGuri709PTg4+ODq1evKpVLKBQiNzcXAwcOhJ6eHoKCggC8vqgODQ1VWr+7uzvrhY8tsS8bc/ToUZiamiIoKAiZmZlQdz4RV1dXVqNCkda2bVtcv36dSSsrK8ORI0cwatQo1oDD4OBgCIVC7Nq1i0lLTk6GpqYmxo0bx6Tx+XyMGTMGf/zxB/76668mbRtFUdTHhj6xoD4KT548Qe/evcHhcDBx4kSIxWKkp6djzJgxKCsrw5QpU5jYRYsWQUNDA9OnT4dMJsOSJUsQFBSE06dPs/J8+vQpBgwYgICAAIwaNQpGRkYAgC1btkAoFOK7776DUCjEsWPHEB0djbKyMixdupSVR0lJCQYOHAh/f38EBgZi165diIqKApfLRXh4OIRCIXx9fbFz506sWLECmpqazLI7duwAIYS5WCwvL4eLiwuuX7+O8PBw9OzZE0VFRdi/fz/u37+P9u3bo6ysDBs3bkRgYCAiIiLw7NkzbNq0Cd7e3jhz5gwcHBwgFouxfv16REVFwdfXF8OGDQMA2NvbN6nOY2NjIRAIMHv2bNy+fRtr1qyBtrY2NDQ0UFJSgnnz5uHUqVPYsmULOnXqxGogrF+/HnZ2dhgyZAi0tLRw4MABjB8/HjU1NZgwYQIAwMPDA+PHj0dsbCyGDh2Knj174tGjR/j222/h5eWFb775Ru2ypqWl4euvv0a3bt0QGxuLkpISjBkzBmZmZk3a5uby8/PD1atX8e2338LS0hIFBQU4cuQI7t27xzRekpKSEBISAm9vbyxevBhyuRzr169H3759ceHCBVYjp6qqCt7e3ujbty+WLVv2xk/UmrMvG9OvXz98++23SEpKwvbt22FlZYXw8HCEhoY2uf7Ly8tRXl6O9u3bM2k5OTmoqqpCr169WLFcLhcODg64cOECk3bhwgXY2NgozXjy2WefAXjdpapDhw5K662oqGA1qMrKyppUboqiqA8GoaiPwJgxY4iJiQkpKipipQcEBBCRSETkcjnJzMwkAEjXrl1JRUUFE7N69WoCgOTk5DBpbm5uBACJi4tTWpdcLldKi4yMJDo6OuTly5dKeSxfvpxJq6ioIA4ODsTQ0JBUVlYSQgg5fPgwAUDS09NZedrb2xM3Nzfme3R0NAFAUlNTldZfU1NDCCGkqqqKtW2EEFJSUkKMjIxIeHg4k1ZYWEgAkLlz5yrl1RhFPUqlUmYbCCEkMDCQcDgcMmDAAFb8559/TiwsLFhpqurQ29ubWFlZsdKeP39OrK2tiZ2dHXn58iXx8fEh+vr65O7du00qc7du3Yi5uTl59uwZk5aVlUUAKJWtbr2EhIQoxRBCyNy5c0lTTrElJSUEAFm6dGm9Mc+ePSNt2rQhERERrPTHjx8TkUjESg8JCSEAyOzZs5XysbCwICEhIUrpbm5urGOqJfalul69ekX27dtHhg4dSrS1tYmmpiYZOHAgSU1NZa27IT/++CMBQP7zn/8wabt37yYAyIkTJ5TiR4wYQYyNjZnvdnZ2xMPDQynu6tWr9f69E/J/+7ruRyaTqVVuimoOi1kHicWsg61dDOoDJ5PJ1Dqv0a5Q1AePEIKUlBQMHjwYhBAUFRUxH29vb8hkMpw/f56JDwsLA5fLZb67uLgAAO7cucPKl8fjISwsTGl9AoGA+fezZ89QVFQEFxcXyOVy3LhxgxWrpaWFyMhI5juXy0VkZCQKCgqYlyh6eXnB1NQU27ZtY+KuXLmCy5cvY9SoUUxaSkoKunfvDl9fX6UyKbrkaGpqMttWU1OD4uJi5m5u7TpoCcHBwdDW1ma+Ozk5gRCC8PBwVpyTkxP++usvVFVVMWm161Amk6GoqAhubm64c+cOZDIZ85uOjg62bNmC69evw9XVFWlpaVi5ciU6duyodjkfPnyInJwcpmuMgpubG7p169akbW4OgUAALpeLrKysel8MeeTIEZSWliIwMJB1HGtqasLJyYnVpU0hKiqq2WVrzr5Ul5aWFoYMGYI9e/bg/v37WLx4Me7evYthw4bB3NwcM2bMwKtXr+pd/sSJE4iJiYG/vz88PDyYdMWLIHk8ntIyfD6f9aLIFy9e1BtXO6+65syZA5lMxnxolymKoj5WtGFBffAKCwtRWlqK+Ph4iMVi1kfRMCgoKGDi616UKgaV1r3YMzMzYzVAFK5evQpfX1+IRCLo6+tDLBYzDYDaF8UAYGpqqjSY1sbGBgCYfvUaGhoICgrC3r17IZfLAQDbtm0Dn89nzWqTm5sLqVTaaH0kJibC3t4efD4f7dq1g1gsRlpamlLZmqtuPYpEIgBQ6koiEolQU1PDWv/Jkyfh5eUFXV1dtGnTBmKxmBnDUrecffr0QVRUFM6cOQNvb2+li93G3L17FwBgbW2t9JuqtLeFx+Nh8eLFSE9Ph5GREVxdXbFkyRLWDEe3bt0C8LobWN1jOSMjg3UcA68v1s3NzZtdtubsyzdhaGiIadOmITs7G2PHjkVBQQGWLVuG58+fq4y/ceMGfH19IZVKsXHjRtZvikaqqrEfL1++ZDViBQJBvXG186qLx+NBX1+f9aEoivoY0TEW1AevpqYGADBq1CiEhISojLG3t8e1a9cAgDWOoTZSZ1CpqouM0tJSuLm5QV9fH/Pnz4dEIgGfz8f58+cxa9YspixNFRwcjKVLl2Lv3r0IDAzE9u3bMWjQIOYCT11bt25FaGgohg4dihkzZsDQ0JAZAJ6bm/tGZatPffXYWP3m5ubC09MTXbp0wYoVK9ChQwdwuVwcOnQIK1euVKrDiooKZlrc3Nzcdz47V30DtOsO1lfHlClTMHjwYOzduxeHDx/GDz/8gNjYWBw7dgw9evRgtj0pKQnGxsZKy2tpsU/pPB5PaYBzY2VWtX/edF++CUIIsrKysHnzZqSkpODly5fw9PTE2LFjVV6w//XXX+jXrx9EIhEOHToEPT091u8mJiYAoPL9Fo8ePYKpqSkr9sGDByrjALBiKYqiKGW0YUF98MRiMfT09FBdXQ0vL6964xQNi+bIysrC06dPkZqaCldXVyY9Ly9PZfzDhw+VpgC9efMmALAG4UqlUvTo0QPbtm2Dubk57t27hzVr1rDykkgkuHLlSoPlS05OhpWVFVJTU1kXl3PnzmXFNXU2o5Z04MABVFRUYP/+/aw75aq6+QCvy379+nUsW7YMs2bNwuzZs/Hzzz+rvT4LCwsAUJr5q760ugwMDFBaWqqUrngS0lQSiQTTpk3DtGnTcOvWLTg4OGD58uXYunUrJBIJgNd39Bs6lptTZisrqzfOtzny8/ORmJiILVu2ID8/H+bm5pg2bRrGjBlT78xcT58+Rb9+/VBRUYH//Oc/TCOiNqlUCi0tLZw9exb+/v5MemVlJS5evMhKc3BwQGZmJsrKyliNGMXEDQ4ODi2zsRRFUR8o2hWK+uBpamrCz88PKSkpKi+8CwsLW3RdAPuObWVlJdatW6cyvqqqChs2bGDFbtiwAWKxGI6OjqzY0aNHIyMjA6tWrUK7du0wYMAA1u9+fn64dOkS9uzZo7QeRXlUle/06dP4448/WPGKO/6qLj7fNlVllMlkSEhIUIo9ffo0li1bhilTpmDatGmYMWMG1q5di+PHj6u9PlNTU0ilUvz73/9mvYn5+PHjyMnJaXR5iUQCmUyGy5cvM2mPHj1SuR8aIpfLmS43tfPW09Njuud4e3tDX18fCxcuVDneQN1jWSKR4NSpU6isrGTSDh482CpjA3JycuDl5QUrKyssWLAAPXr0QFpaGvLz8/Hjjz/W26h4/vw5Bg4ciAcPHuDQoUP45JNPVMaJRCJ4eXlh69atePbsGZOelJSE8vJyVnfC4cOHo7q6GvHx8UxaRUUFEhIS4OTkpHJGKIpqbfmLfJC/yKe1i0FRAOgTC+ojsWjRImRmZsLJyQkRERGwtbVFcXExzp8/j6NHj6K4uLhF1uPs7AwDAwOEhIRg0qRJ4HA4SEpKqrdriKmpKRYvXoz8/HzY2Nhg586duHjxIuLj41mDZQFg5MiRmDlzJvbs2YOoqCil32fMmIHk5GSMGDEC4eHhcHR0RHFxMfbv34+4uDh0794dgwYNQmpqKnx9feHj44O8vDzExcXB1taWdVEtEAhga2uLnTt3wsbGBm3btoVUKlVrDEdz9evXD1wuF4MHD0ZkZCTKy8vxyy+/wNDQkNWd5eXLlwgJCcEnn3yCBQsWAHj93o0DBw4gLCwMOTk5ar8MbuHChfjqq6/Qp08fhIWFoaSkBGvXroVUKmXViyoBAQGYNWsWfH19MWnSJGb6VxsbmyYNiL958yY8PT3h7+8PW1tbaGlpYc+ePXjy5AkCAgIAAPr6+li/fj1Gjx6Nnj17IiAgAGKxGPfu3UNaWhr69OmDtWvXNrqusWPHIjk5Gf3794e/vz9yc3NZT0TepXPnzjGDtUNCQmBoaKjWckFBQThz5gzCw8Nx/fp11rsrhEIhhg4dynxfsGABnJ2d4ebmhnHjxuH+/ftYvnw5+vXrh/79+zNxTk5OGDFiBObMmYOCggJYW1sjMTER+fn52LRpU4ttM0VR1Afr7U1MRVHvlydPnpAJEyaQDh06EG1tbWJsbEw8PT1JfHw8IeT/ptbcvXs3a7m8vDwCgCQkJDBpbm5uxM7OTuV6Tp48SXr37k0EAgExNTUlM2fOZKaMzczMVMrj7Nmz5PPPPyd8Pp9YWFiQtWvX1rsNAwcOJABIdna2yt+fPn1KJk6cSMzMzAiXyyXm5uYkJCSEmWa3pqaGLFy4kFhYWBAej0d69OhBDh48qHLK1OzsbOLo6Ei4XG6Tpp6trx4TEhIIAPLnn3+y0hVTdRYWFjJp+/fvJ/b29oTP5xNLS0uyePFisnnzZgKA5OXlEUIImTp1KtHU1CSnT59m5Xf27FmipaVFoqKi1Cqvwq+//kq6dOlCeDwekUqlZP/+/cTPz4906dKFFaeqLjIyMohUKiVcLpd07tyZbN26tcnTzRYVFZEJEyaQLl26EF1dXSISiYiTkxPZtWuXUmxmZibx9vYmIpGI8Pl8IpFISGhoKDl79iwTExISQnR1detd3/Lly4mZmRnh8XikT58+5OzZs/VON9ucfdmY8vJytWNrs7CwUDnFK1RMEUwIIb///jtxdnYmfD6fiMViMmHCBFJWVqYU9+LFCzJ9+nRibGxMeDwe+fTTT8lvv/3WpLKpOy0jRVHU34W65zUOIc0YZUdR1Btzd3dHUVFRo+MiavP19UVOTo5aff+p5lO8MPDIkSOtXRTqb6SsrAwikQgymYzOEEVR1AdB3fMaHWNBUX8Tjx49QlpaGkaPHt3aRfngvHr1SundC1lZWbh06RLc3d1bp1AURVEU9TdDx1hQ1HsuLy8PJ0+exMaNG6Gtrc16od67VFlZ2ehYFJFIVO9c/61BJpPV+1IzBWNjYzx48ABeXl4YNWoUTE1NcePGDcTFxcHY2BjffPPNOyvHh+Rj3GaKoqiPHW1YUNR77vjx4wgLC0PHjh2RmJjYahdj2dnZ+OKLLxqMSUhIQGho6LspkBomT56MxMTEBmMIITAwMICjoyM2btyIwsJC6OrqwsfHB4sWLUK7du3eWTk+JB/jNlMURX3s6BgLiqLUUlJSgnPnzjUYY2dnp/JdAq3l2rVrePjwYYMxzXkfxN+tHO/Sx7jNCnSMBUVRHxp1z2u0YUFRFEVRLYg2LCiK+tDQwdsURVEURVEURb0ztGFBUc2UlZUFDoeD5OTk1i4K9R7jcDiYN29eaxeDoiiKot4a2rCgKKrFyOVyzJs3D1lZWa1dFIqiqI+C5ew0WM5Oa+1iUBQA2rCgKKoFyeVyxMTE0IYFRVEURX2EaMOColqZXC5v7SJQVIOeP3/e2kWgKIqi/gZow4KiGvHgwQOEh4fDyMgIPB4PdnZ22Lx5s1JcTU0NFixYAHNzc/D5fHh6euL27dusGHd3d0ilUpw7dw6urq7Q0dHB999/DwDYt28ffHx8YGpqCh6PB4lEgh9//BHV1dX15uHs7AyBQIBOnTohLi6OiSkvL4euri4mT56sVM779+9DU1MTsbGxTFppaSmmTp0KS0tL8Hg8mJubIzg4GEVFRQBevxwvOjoajo6OEIlE0NXVhYuLCzIzM5k88vPzIRaLAQAxMTHgcDhNGlegGKuya9cuxMTEwMzMDHp6ehg+fDhkMhkqKiowZcoUGBoaQigUIiwsDBUVFaw8EhIS4OHhAUNDQ/B4PNja2mL9+vWsmGPHjkFDQwPR0dGs9O3bt4PD4SjFN2b37t2wtbUFn8+HVCrFnj17EBoaCktLywaXqy9m3rx54HA4TSrD48ePERYWBnNzc/B4PJiYmOCrr75Cfn4+Ky49PR0uLi7Q1dWFnp4efHx8cPXqVaVyCYVC5ObmYuDAgdDT00NQUBAAwNLSUuV7Stzd3VlvKG+JfdkYRTkfPHiAoUOHQigUQiwWY/r06Up/M8uWLYOzszPatWsHgUAAR0dHlWOiOBwOJk6ciL1790IqlTJ/77/99luTykZRFPWxoi/Io6gGPHnyBL1792YuOMRiMdLT0zFmzBiUlZVhypQpTOyiRYugoaGB6dOnQyaTYcmSJQgKCsLp06dZeT59+hQDBgxAQEAARo0aBSMjIwDAli1bIBQK8d1330EoFOLYsWOIjo5GWVkZli5dysqjpKQEAwcOhL+/PwIDA7Fr1y5ERUWBy+UiPDwcQqEQvr6+2LlzJ1asWAFNTU1m2R07doAQwlwslpeXw8XFBdevX0d4eDh69uyJoqIi7N+/H/fv30f79u1RVlaGjRs3IjAwEBEREXj27Bk2bdoEb29vnDlzBg4ODhCLxVi/fj2ioqLg6+uLYcOGAQDs7e2bVOexsbEQCASYPXs2bt++jTVr1kBbWxsaGhooKSnBvHnzcOrUKWzZsgWdOnViNRDWr18POzs7DBkyBFpaWjhw4ADGjx+PmpoaTJgwAQDg4eGB8ePHIzY2FkOHDkXPnj3x6NEjfPvtt/Dy8mrSm7bT0tLw9ddfo1u3boiNjUVJSQnGjBkDMzOzJm1zc/n5+eHq1av49ttvYWlpiYKCAhw5cgT37t1jGi9JSUkICQmBt7c3Fi9eDLlcjvXr16Nv3764cOECq5FTVVUFb29v9O3bF8uWLYOOjs4blas5+1Id1dXV8Pb2hpOTE5YtW4ajR49i+fLlkEgkiIqKYuJWr16NIUOGICgoCJWVlfj1118xYsQIHDx4ED4+Pqw8//vf/yI1NRXjx4+Hnp4efv75Z/j5+eHevXv1viyxoqKC1TAqKytr0nZQFEV9MAhFUfUaM2YMMTExIUVFRaz0gIAAIhKJiFwuJ5mZmQQA6dq1K6moqGBiVq9eTQCQnJwcJs3NzY0AIHFxcUrrksvlSmmRkZFER0eHvHz5UimP5cuXM2kVFRXEwcGBGBoaksrKSkIIIYcPHyYASHp6OitPe3t74ubmxnyPjo4mAEhqaqrS+mtqagghhFRVVbG2jRBCSkpKiJGREQkPD2fSCgsLCQAyd+5cpbwao6hHqVTKbAMhhAQGBhIOh0MGDBjAiv/888+JhYUFK01VHXp7exMrKytW2vPnz4m1tTWxs7MjL1++JD4+PkRfX5/cvXu3SWXu1q0bMTc3J8+ePWPSsrKyCAClstWtl5CQEKUYQgiZO3cuacqpuaSkhAAgS5curTfm2bNnpE2bNiQiIoKV/vjxYyISiVjpISEhBACZPXu2Uj4WFhYkJCREKd3NzY11TLXEvmyMopzz589npffo0YM4Ojqy0uoeF5WVlUQqlRIPDw9WOgDC5XLJ7du3mbRLly4RAGTNmjX1lkWxz+p+ZDJZk7aJot6ExayDxGLWwdYuBvWBk8lkap3XaFcoiqoHIQQpKSkYPHgwCCEoKipiPt7e3pDJZDh//jwTHxYWBi6Xy3x3cXEBANy5c4eVL4/HQ1hYmNL6BAIB8+9nz56hqKgILi4ukMvluHHjBitWS0sLkZGRzHcul4vIyEgUFBQwb8f28vKCqakptm3bxsRduXIFly9fxqhRo5i0lJQUdO/eHb6+vkplUnTJ0dTUZLatpqYGxcXFqKqqQq9evVh10BKCg4Ohra3NfHdycgIhBOHh4aw4Jycn/PXXX6iqqmLSatehTCZDUVER3NzccOfOHchkMuY3HR0dbNmyBdevX4erqyvS0tKwcuVKdOzYUe1yPnz4EDk5OQgODoZQKGTS3dzc0K1btyZtc3MIBAJwuVxkZWWhpKREZcyRI0dQWlqKwMBA1nGsqakJJycnVpc2hdp3/N9Uc/aluuo+YXJxcVH6m6t9XJSUlEAmk8HFxUXlsevl5QWJRMJ8t7e3h76+vlKetc2ZMwcymYz5/PXXX03eDoqiqA8BbVhQVD0KCwtRWlqK+Ph4iMVi1kfRMCgoKGDi616UGhgYAIDSxZ6ZmRmrAaJw9epV+Pr6QiQSQV9fH2KxmGkA1L4oBgBTU1Po6uqy0mxsbACA6VevoaGBoKAg7N27lxkgvm3bNvD5fIwYMYJZLjc3F1KptNH6SExMhL29Pfh8Ptq1awexWIy0tDSlsjVX3XoUiUQAgA4dOiil19TUsNZ/8uRJeHl5QVdXF23atIFYLGbGsNQtZ58+fRAVFYUzZ87A29tb6WK3MXfv3gUAWFtbK/2mKu1t4fF4WLx4MdLT02FkZARXV1csWbIEjx8/ZmJu3boF4HU3sLrHckZGBus4Bl43XM3NzZtdtubsS3Xw+XxmXI+CgYGB0t/cwYMH0bt3b/D5fLRt25bptqdqfaoal6ryrI3H40FfX5/1oSiK+hjRMRYUVY+amhoAwKhRoxASEqIyxt7eHteuXQMA1jiG2gghrO+1754qlJaWws3NDfr6+pg/fz4kEgn4fD7Onz+PWbNmMWVpquDgYCxduhR79+5FYGAgtm/fjkGDBjEXeOraunUrQkNDMXToUMyYMQOGhobMAPDc3Nw3Klt96qvHxuo3NzcXnp6e6NKlC1asWIEOHTqAy+Xi0KFDWLlypVIdVlRUMNPi5ubmQi6Xv/FYgjdR3wDtugOP1TFlyhQMHjwYe/fuxeHDh/HDDz8gNjYWx44dQ48ePZhtT0pKgrGxsdLyWlrs/wp4PB40NJTvOzVUZlX75033pbrqy6e233//HUOGDIGrqyvWrVsHExMTaGtrIyEhAdu3b39rZaMoivoY0YYFRdVDLBZDT08P1dXV8PLyqjdO0bBojqysLDx9+hSpqalwdXVl0vPy8lTGP3z4EM+fP2c9tbh58yYAsAbhSqVS9OjRA9u2bYO5uTnu3buHNWvWsPKSSCS4cuVKg+VLTk6GlZUVUlNTWReXc+fOZcU1dTajlnTgwAFUVFRg//79rLvOqrr5AK/Lfv36dSxbtgyzZs3C7Nmz8fPPP6u9PgsLCwBQmvmrvrS6DAwMUFpaqpSueBLSVBKJBNOmTcO0adNw69YtODg4YPny5di6dSvTtcfQ0LDBY7k5ZbaysnrjfN+mlJQU8Pl8HD58GDwej0lPSEhoxVJRFEV9mGhXKIqqh6amJvz8/JCSkqLywruwsLBF1wWw74pWVlZi3bp1KuOrqqqwYcMGVuyGDRsgFovh6OjIih09ejQyMjKwatUqtGvXDgMGDGD97ufnh0uXLmHPnj1K61GUR1X5Tp8+jT/++IMVr7jjr+ri821TVUaZTKbyAvL06dNYtmwZpkyZgmnTpmHGjBlYu3Ytjh8/rvb6TE1NIZVK8e9//xvl5eVM+vHjx5GTk9Po8hKJBDKZDJcvX2bSHj16pHI/NEQul+Ply5dKeevp6TEzFXl7e0NfXx8LFy7Eq1evlPJQ91iWSCQ4deoUKisrmbSDBw++12MKNDU1weFwWE+C8vPzsXfv3tYrFEW1oPxFPshf5NN4IEW9A/SJBUU1YNGiRcjMzISTkxMiIiJga2uL4uJinD9/HkePHkVxcXGLrMfZ2RkGBgYICQnBpEmTwOFwkJSUVG/3C1NTUyxevBj5+fmwsbHBzp07cfHiRcTHx7MGywLAyJEjMXPmTOzZswdRUVFKv8+YMQPJyckYMWIEwsPD4ejoiOLiYuzfvx9xcXHo3r07Bg0ahNTUVPj6+sLHxwd5eXmIi4uDra0t66JaIBDA1tYWO3fuhI2NDdq2bQupVKrWGI7m6tevH7hcLgYPHozIyEiUl5fjl19+gaGhIR49esTEvXz5EiEhIfjkk0+wYMECAK/fu3HgwAGEhYUhJydHafxKfRYuXIivvvoKffr0QVhYGEpKSrB27VpIpVJWvagSEBCAWbNmwdfXF5MmTWKmf7WxsWnSgPibN2/C09MT/v7+sLW1hZaWFvbs2YMnT54gICAAAKCvr4/169dj9OjR6NmzJwICAiAWi3Hv3j2kpaWhT58+WLt2baPrGjt2LJKTk9G/f3/4+/sjNzeX9UTkfeTj44MVK1agf//+GDlyJAoKCvCvf/0L1tbWrEYdRVEU1Xz0iQVFNcDIyAhnzpxBWFgYUlNTMXHiRKxevRrFxcVYvHhxi62nXbt2OHjwIExMTPDPf/4Ty5Ytw5dffoklS5aojDcwMMChQ4dw9uxZzJgxA3/99RfWrl2LiIgIldvQr18/AK+fXtQlFArx+++/IyoqCocOHcKkSZOwbt06dO7cmRnAGxoaioULF+LSpUuYNGkSDh8+jK1bt6JXr15K+W3cuBFmZmaYOnUqAgMDVb6I7G3o3LkzkpOTweFwMH36dMTFxWHcuHFKLwn8/vvvcfv2bSQmJoLP5wN4PatWYmIi/vrrL8yYMUPtdQ4ePBg7duxAZWUlZs+ejdTUVGzZsgWdO3dm8q5Pu3btsGfPHujo6GDmzJlITExEbGwsBg8e3KTt7tChAwIDA5GVlYU5c+Zgzpw5KCsrw65du+Dn58fEjRw5Ev/5z39gZmaGpUuXYvLkyfj111/h4OCgcpYyVby9vbF8+XLcvHkTU6ZMwR9//IGDBw+2yEDvt8XDwwObNm3C48ePMWXKFOzYsQOLFy9WOQsaRVEU1TwcQkekUdTfiru7O4qKihodF1Gbr68vcnJy1Or7TzWf4oWBR44cae2iUK2grKwMIpEIMpmMzhBFUdQHQd3zGn1iQVEfuEePHiEtLU3l0wqqeV69eqX07oWsrCxcunQJ7u7urVMoiqIoimoldIwFRX2g8vLycPLkSWzcuBHa2tqsF+q9S5WVlY2ORRGJRCqn4W0tMpkML168aDDG2NgYDx48gJeXF0aNGgVTU1PcuHEDcXFxMDY2Vnpx29ssx4fkY9xmiqKoDwVtWFDUB+r48eMICwtDx44dkZiY2GoXY9nZ2fjiiy8ajElISEBoaOi7KZAaJk+ejMTExAZjCCEwMDCAo6MjNm7ciMLCQujq6sLHxweLFi1Cu3bt3lk5PiQf4zZTFEV9KOgYC4qi3qqSkhKcO3euwRg7OzuYmJi8oxI17tq1a3j48GGDMc15H8TfrRzv0oewzXSMBUVRHxp1z2u0YUFRFEVRLYg2LCiK+tDQwdsURbWYrKwscDicdzZ1LPVxCQ0NZb0xnqIoivp7og0LiqKoJpDL5Zg3bx6ysrKalc/169fB4XDA5/PrfVP5mTNnMH78eDg6OkJbWxscDqfBPMvKyhATE4Pu3btDKBRCIBBAKpVi1qxZjXYvep+0VB03xZYtW8DhcOr9bNu27Z2VhaIo6u+KDt6mKIpqArlcjpiYGABo1pSyW7duhbGxMUpKSpCcnIyxY8cqxRw6dAgbN26Evb09rKyscPPmzXrzu3PnDry8vHDv3j2MGDEC48aNA5fLxeXLl7Fp0ybs2bOnweXfJy1Vx03h6uqKpKQkpfSVK1fi0qVL8PT0fCfloCiK+jujDQuKot46uVwOHR2d1i7Ge4MQgu3bt2PkyJHIy8vDtm3bVDYsoqKiMGvWLAgEAkycOLHehkFVVRWGDRuGJ0+eICsrC3379mX9vmDBgkbfFP8h7aPLly/D3t6+SctYWVnBysqKlfbixQuMHz8eHh4edIpbiqIoNdCuUBRF4cGDBwgPD4eRkRF4PB7s7OywefNmpbiamhosWLAA5ubm4PP58PT0VHqbt7u7O6RSKc6dOwdXV1fo6Ojg+++/BwDs27cPPj4+MDU1BY/Hg0QiwY8//ojq6up683B2doZAIECnTp0QFxfHxJSXl0NXVxeTJ09WKuf9+/ehqamJ2NhYJq20tBRTp06FpaUleDwezM3NERwcjKKiIgCv37cRHR0NR0dHiEQi6OrqwsXFBZmZmUwe+fn5EIvFAICYmBimm8y8efOaVN8nT55Efn4+AgICEBAQgBMnTuD+/ftKcUZGRmq93yMlJQWXLl3CP/7xD6VGBQDo6+tjwYIFzPeG9lFFRQXmzp0La2tr8Hg8dOjQATNnzkRFRQUrzyNHjqBv375o06YNhEIhOnfuzOQB/F/Xovz8fNZyivE69XVzaok67t69Oz777DNs2LABZWVlai9X14EDB/Ds2TMEBQW9cR4URVEfE/rEgqI+ck+ePEHv3r3B4XAwceJEiMVipKenY8yYMSgrK8OUKVOY2EWLFkFDQwPTp0+HTCbDkiVLEBQUhNOnT7PyfPr0KQYMGICAgACMGjUKRkZGAF5fbAqFQnz33XcQCoU4duwYoqOjUVZWhqVLl7LyKCkpwcCBA+Hv74/AwEDs2rULUVFR4HK5CA8Ph1AohK+vL3bu3IkVK1ZAU1OTWXbHjh0ghDAXhOXl5XBxccH169cRHh6Onj17oqioCPv378f9+/+PvfOOi+ro/v9nQdhdWFgEFwRRxLUCKrpGCEqJDRVixIKASrNgizF51GgSKUbFEo1Gv4pEA0bRoID9wfaI0QdL7DUaFbBH+qKiIOz5/eFv78Nll6aoUef9eu1Ld+65M2fOzF5m5p45cxeNGjVCUVER1qxZA39/f4wZMwaPHj3C2rVr4enpiT/++AOOjo6QyWRYtWoVxo8fDx8fHwwaNAgA6rw6npCQALlcjo8++ggODg4wMDDApk2bMG3atDrlo2bHjh0AUKfT1bW1kUqlwoABA/Df//4XY8eORbt27XDx4kX8+OOP+Ouvv7Bt2zYAwOXLl+Ht7Y0OHTpg9uzZEAqFuHHjBtLT019K/4rUh41jY2Pxyy+/YNy4cfjqq68wdOhQjBo1Cq6urnXSJSEhAWKxmNOhKkpKSngTr1eZzDAYDMY7DTEYjA+aUaNGkaWlJeXm5vLS/fz8SCqVUnFxMaWlpREAateuHZWUlHAyy5YtIwB08eJFLs3d3Z0AUExMjEZZxcXFGmlhYWFkYGBAz54908hj8eLFXFpJSQk5OjqSubk5lZaWEhHR3r17CQClpqby8uzQoQO5u7tz38PDwwkApaSkaJSvUqmIiKisrIxXNyKigoICsrCwoNDQUC4tJyeHAFBERIRGXrWhtLSUzMzM6Ntvv+XSAgICqGPHjtXeN3HiRKrqkd2pUyeSSqW11qGqNlq/fj3p6OjQkSNHeOkxMTEEgNLT04mI6McffyQAlJOTU2UZcXFxBIAyMzN56eq+lJaWxqUFBQWRjY0N9/1VbazmypUrNHXqVLKwsCAA1Lp1a5o/fz49ePCgxnvz8vJIX1+ffH19a5SNiIggABofpVL5SvozGAzGPwWlUlmr5xpzhWIwPmCICMnJyfj0009BRMjNzeU+np6eUCqVOHPmDCcfEhICfX197rt6BTgjI4OXr1AoREhIiEZ5Fd16Hj16hNzcXLi6uqK4uBhXr17lyTZo0ABhYWHcd319fYSFhSE7O5s7cK9Xr16wsrLiRey5dOkSLly4gBEjRnBpycnJ6NixI3x8fDR0Ukda0tXV5eqmUqmQn5+PsrIydOnShWeDVyU1NRV5eXnw9/fn0vz9/XH+/Hlcvnz5pfIsKiqCkZFRne7R1kZbtmxBu3bt0LZtW15f6NGjBwBwbmEmJiYAXri2qVSql9L5TdCuXTssWrQId+/exfbt29GuXTvMmjULTZs2xcCBA3HhwoUq701KSkJpaWmt3KBmzpwJpVLJfe7cuVOf1WAwGIx3BjaxYDA+YHJyclBYWIjY2FjIZDLeRz3ozM7O5uSbNWvGu79hw4YAXrgtVaRJkya8CYiay5cvw8fHB1KpFMbGxpDJZNwEQKlU8mStrKxgaGjIS2vdujUAcH77Ojo6GD58OLZt24bi4mIAL9xXRCIRhg4dyt138+ZNODg41GiPdevWoUOHDhCJRDAzM4NMJsPu3bs1dHsVNmzYAFtbW8596MaNG5DL5TAwMHjpkKbGxsZ49OhRne7R1kbXr1/H5cuXNfqC2u7qvjBs2DB069YNo0ePhoWFBfz8/LB58+Z/7CSjQYMGGDBgALZu3Yr169fDwMAA27dvx8GDB6u8JyEhAaampujXr1+N+QuFQhgbG/M+DAaD8SHC9lgwGB8w6oHgiBEjEBQUpFWmQ4cOuHLlCgDw9jFUhIh437VtOC4sLIS7uzuMjY0xe/ZsyOVyiEQinDlzBl9//fVLD0oDAwOxaNEibNu2Df7+/ti4cSO8vb0hlUrrlM+GDRsQHByMgQMHYtq0aTA3N+c2gN+8efOldKtMUVERdu7ciWfPnqFVq1Ya1zdu3Ii5c+fWeF5FZdq2bYuzZ8/izp07aNq0aa3u0dZGKpUK7du3x5IlS7Teo85bLBbj8OHDSEtLw+7du7Fnzx4kJiaiR48e2LdvH3R1dausQ+WN+m+CW7duYd26dYiPj0dmZiaaN2+Of/3rX7y3RhW5ffs2jhw5grFjx0JPT+8Na8tgMBjvLmxiwWB8wMhkMhgZGaG8vBy9evWqUk49sXgVDh06hLy8PKSkpMDNzY1Lz8zM1Cp///59PHnyhPfWQh1uteIpzQ4ODujUqRMSEhJgbW2N27dvY/ny5by85HI5Ll26VK1+SUlJaNGiBVJSUniD4oiICJ5cXQf9FUlJScGzZ8+watUqNGrUiHft2rVr+O6775Cenq41slN1fPrpp9i0aRM2bNiAmTNnvrR+crmcO7Ohpnrq6OigZ8+e6NmzJ5YsWYJ58+bh22+/RVpaGnr16sW9zap8+N+tW7dq1ONVbKzm6dOn2Lp1K3755RccPHgQ+vr6GDhwIFavXo1evXpVW0blzf8MBoPBqB3MFYrB+IDR1dXF4MGDkZycrHXgnZOTU69lAfy3G6WlpVi5cqVW+bKyMqxevZonu3r1ashkMigUCp7syJEjsW/fPixduhRmZmYa7iuDBw/G+fPnsXXrVo1y1Ppo0+/EiRM4duwYT1591kNVp2VXx4YNG9CiRQuMGzcOQ4YM4X2mTp0KiUTyUu5QQ4YMQfv27TF37lwNfYEX+1m+/fbbGvPx9fXFvXv38PPPP2tce/r0KZ48eQIAyM/P17ju6OgIAFx0JLlcDgA4fPgwJ1NeXo7Y2Nga9XgVGwPAuHHjYGlpieHDh+Phw4dYsmQJ7t27h99++w29e/euceKyceNGNGvWrM4TPAaDwfjQYW8sGIwPnPnz5yMtLQ1OTk4YM2YM7OzskJ+fjzNnzuDAgQNaB5Evg4uLCxo2bIigoCBMnjwZAoEA69ev13CjUmNlZYUFCxYgKysLrVu3RmJiIs6dO4fY2FgN95SAgABMnz4dW7duxfjx4zWuT5s2DUlJSRg6dChCQ0OhUCiQn5+PHTt2ICYmBh07doS3tzdSUlLg4+MDLy8vZGZmIiYmBnZ2dnj8+DGXl1gshp2dHRITE9G6dWuYmprCwcGhxj0c9+/fR1paGiZPnqz1ulAohKenJ7Zs2YKffvoJenp6uHXrFnca9KlTpwAAc+bMAQDY2Nhw4WX19PSQkpKCXr16wc3NDb6+vujWrRv09PRw+fJlbNy4EQ0bNuSdZaGNkSNHYvPmzRg3bhzS0tLQrVs3lJeX4+rVq9i8eTP27t2LLl26YPbs2Th8+DC8vLxgY2OD7OxsrFy5EtbW1txg3N7eHs7Ozpg5cyby8/NhamqK3377DWVlZdXq8Co2VrNx40YMGzYMo0ePhpOTU63uUaPe/D9jxox6eXPCYDAYHxSvOToVg8F4B3j48CFNnDiRmjZtSnp6etS4cWPq2bMnxcbGEtH/QoRu2bKFd19mZiYBoLi4OC7N3d2d7O3ttZaTnp5Ozs7OJBaLycrKiqZPn86FjK0YflSdx6lTp+jjjz8mkUhENjY2tGLFiirr0L9/fwJAR48e1Xo9Ly+PJk2aRE2aNCF9fX2ytramoKAgLsyuSqWiefPmkY2NDQmFQurUqRPt2rVLIxQqEdHRo0dJoVCQvr5+rcOiLl68mADQf/7znypl4uPjCQBt376diP5nd22fiuF01RQUFFB4eDi1b9+eDAwMSCQSkYODA82cOZMXYrW6NiotLaUFCxaQvb09CYVCatiwISkUCoqKiuLCDP7nP/+hzz77jKysrEhfX5+srKzI39+f/vrrL15eN2/epF69epFQKCQLCwv65ptvaP/+/TWGmyV6ORurefz4ca1lKzNjxgwCQBcuXHjpPGoblpHBYDDeFWr7XBMQVbFcyGAwGG8JDw8P5Obm1rgvoiI+Pj64ePGixkngDMabpqioCFKpFEqlkkWIYjAY7wW1fa6xPRYMBuOd58GDB9i9e3edTp5mMBgMBoNRv7A9FgwG450lMzMT6enpWLNmDfT09HgH6r1JSktLa9yLIpVKtYZ4ZdQOZmMGg8H458MmFgwG453l999/R0hICJo1a4Z169ahcePGb0WPo0eP4pNPPqlWJi4uDsHBwW9GofcQZmMGg8H458P2WDAYDMYrUlBQgNOnT1crY29vD0tLyzek0fvHu2RjtseCwWC8b9T2ucYmFgwGg8Fg1CNsYsFgMN432OZtBoPBYDAYDAaD8cZgEwsG4wPi0KFDEAgESEpKetuqMF4RDw8PeHh4cN+zsrIgEAgQHx//1nT6JyEQCBAZGfm21WAwGIwPCjaxYDAYHyTFxcWIjIzEoUOH3rYqjP+PenKk7ePs7Py21WMwGAxGDbCoUAwG44OkuLgYUVFRAMBb+X9XsbGxwdOnT6Gnp/e2VXll/P390b9/f16aTCZ7S9owGAwGo7awiQWDwag1xcXFMDAweNtqMLQgEAggEoneaJlPnjyBoaFhvefbuXNnjBgxot7zZTAYDMbrhblCMRjvEffu3UNoaCgsLCwgFAphb2+PX375RUNOpVJh7ty5sLa2hkgkQs+ePXHjxg2ejIeHBxwcHHD69Gm4ubnBwMAA33zzDQBg+/bt8PLygpWVFYRCIeRyOb7//nuUl5dXmYeLiwvEYjFsbW0RExPDyTx+/BiGhob44osvNPS8e/cudHV1ER0dzaUVFhbiyy+/RPPmzSEUCmFtbY3AwEDk5uYCeHGQWnh4OBQKBaRSKQwNDeHq6oq0tDQuj6ysLG4FPCoqinO3qa1PvnqvyubNmxEVFYUmTZrAyMgIQ4YMgVKpRElJCaZMmQJzc3NIJBKEhISgpKREI58NGzZAoVBALBbD1NQUfn5+uHPnjoZcbGws5HI5xGIxunbtiiNHjmjIVLXH4urVq/D19YVMJoNYLEabNm3w7bffctdv3bqFCRMmoE2bNhCLxTAzM8PQoUORlZXFyyc+Ph4CgQC///47JkyYAHNzc1hbW3PXU1NT4erqCkNDQxgZGcHLywuXL1+ulT1rS23atioePXqEKVOmcP3G3NwcvXv3xpkzZ3hyJ06cQN++fSGVSmFgYAB3d3ekp6fXaz0YDAbjfYW9sWAw3hMePnwIZ2dnCAQCTJo0CTKZDKmpqRg1ahSKioowZcoUTnb+/PnQ0dHB1KlToVQqsXDhQgwfPhwnTpzg5ZmXl4d+/frBz88PI0aMgIWFBYAXg0yJRIKvvvoKEokEBw8eRHh4OIqKirBo0SJeHgUFBejfvz98fX3h7++PzZs3Y/z48dDX10doaCgkEgl8fHyQmJiIJUuWQFdXl7t306ZNICIMHz4cwItJiKurK/7880+Ehoaic+fOyM3NxY4dO3D37l00atQIRUVFWLNmDfz9/TFmzBg8evQIa9euhaenJ/744w84OjpCJpNh1apVGD9+PHx8fDBo0CAAQIcOHepk8+joaIjFYsyYMQM3btzA8uXLoaenBx0dHRQUFCAyMhLHjx9HfHw8bG1tER4ezt07d+5czJo1C76+vhg9ejRycnKwfPlyuLm54ezZszAxMQEArF27FmFhYXBxccGUKVOQkZGBAQMGwNTUFE2bNq1WvwsXLsDV1RV6enoYO3Ysmjdvjps3b2Lnzp2YO3cuAODkyZM4evQo/Pz8YG1tjaysLKxatQoeHh64cuWKxhuqCRMmQCaTITw8HE+ePAEArF+/HkFBQfD09MSCBQtQXFyMVatWoXv37jh79iyaN29eJ7sWFxdzE0U1Uqm0Vm1bFePGjUNSUhImTZoEOzs75OXl4b///S/+/PNPdO7cGQBw8OBB9OvXDwqFAhEREdDR0UFcXBx69OiBI0eOoGvXrlrzLikp4U0ci4qK6lRfBoPBeG8gBoPxXjBq1CiytLSk3NxcXrqfnx9JpVIqLi6mtLQ0AkDt2rWjkpISTmbZsmUEgC5evMilubu7EwCKiYnRKKu4uFgjLSwsjAwMDOjZs2caeSxevJhLKykpIUdHRzI3N6fS0lIiItq7dy8BoNTUVF6eHTp0IHd3d+57eHg4AaCUlBSN8lUqFRERlZWV8epGRFRQUEAWFhYUGhrKpeXk5BAAioiI0MirJtR2dHBw4OpAROTv708CgYD69evHk//444/JxsaG+56VlUW6uro0d+5cntzFixepQYMGXHppaSmZm5uTo6Mjr06xsbEEgGebzMxMAkBxcXFcmpubGxkZGdGtW7d45ahtRaS9LY8dO0YA6Ndff+XS4uLiCAB1796dysrKuPRHjx6RiYkJjRkzhpfH33//TVKpVCO9OtR10PZJS0urddsSkUbbSqVSmjhxYpVlq1QqatWqFXl6emrYx9bWlnr37l3lvREREVp1ViqVta47g8Fg/JNRKpW1eq4xVygG4z2AiJCcnIxPP/0URITc3Fzu4+npCaVSyXP5CAkJgb6+Pvfd1dUVAJCRkcHLVygUIiQkRKM8sVjM/f/Ro0fIzc2Fq6sriouLcfXqVZ5sgwYNEBYWxn3X19dHWFgYsrOzuZOUe/XqBSsrKyQkJHByly5dwoULF3i+9snJyejYsSN8fHw0dBIIBAAAXV1drm4qlQr5+fkoKytDly5dNNxeXpXAwEDeZmknJycQEUJDQ3lyTk5OuHPnDsrKygAAKSkpUKlU8PX15bVV48aN0apVK86159SpU8jOzsa4ceN47RUcHAypVFqtbjk5OTh8+DBCQ0PRrFkz3jW1rQB+Wz5//hx5eXlo2bIlTExMtNprzJgxvLdK+/fvR2FhIfz9/Xl10dXVhZOTU63clCozduxY7N+/n/fp2LHjK7WtiYkJTpw4gfv372u9fu7cOVy/fh0BAQHIy8vj6vHkyRP07NkThw8fhkql0nrvzJkzoVQquY82dzYGg8H4EGCuUAzGe0BOTg4KCwsRGxuL2NhYrTLZ2dlo2LAhAGgMNNXpBQUFvPQmTZrwBrRqLl++jO+++w4HDx7UcPtQKpW871ZWVhobfFu3bg3gxb4AZ2dn6OjoYPjw4Vi1ahW3QTwhIQEikQhDhw7l7rt58yYGDx5cpR3UrFu3DosXL8bVq1fx/PlzLt3W1rbGe+tCZTuqB/uVXZSkUilUKhWUSiXMzMxw/fp1EBFatWqlNV/1ZOXWrVsAoCGnp6eHFi1aVKubepLo4OBQrdzTp08RHR2NuLg43Lt3D0TEXavcloCmDa9fvw4A6NGjh9b8X+bk6VatWqFXr15ar71s2y5cuBBBQUFo2rQpFAoF+vfvj8DAQM6O6noEBQVVmYdSqeR+KxURCoUQCoU11ovBYDDed9jEgsF4D1CvpI4YMaLKgVGHDh1w5coVAOCtOFek4qAS4K9mqyksLIS7uzuMjY0xe/ZsyOVyiEQinDlzBl9//XWVq7o1ERgYiEWLFmHbtm3w9/fHxo0b4e3tXePKfGU2bNiA4OBgDBw4ENOmTYO5uTm3AfzmzZsvpVtVVGXHmuyrUqkgEAiQmpqqVVYikdSfkjXw+eefIy4uDlOmTMHHH38MqVQKgUAAPz8/rW1ZuU+oZdavX4/GjRtryDdoUH9/Zl6lbX19feHq6oqtW7di3759WLRoERYsWICUlBT069ePq8eiRYuq3KvxJtuFwWAw3kXYxILBeA+QyWQwMjJCeXl5lSu9ALiJxatw6NAh5OXlISUlBW5ublx6ZmamVvn79+9rhCX966+/AIC3qdfBwQGdOnVCQkICrK2tcfv2bSxfvpyXl1wux6VLl6rVLykpCS1atEBKSgrP5SciIoInV/Ham0Yul4OIYGtry7290YaNjQ2AF6vpFd8IPH/+HJmZmejYsWOV96pX4mtjr6CgICxevJhLe/bsGQoLC2tTFcjlcgCAubl5tX2vPqht21aFpaUlJkyYgAkTJiA7OxudO3fG3Llz0a9fP64exsbGr70eDAaD8b7C9lgwGO8Burq6GDx4MJKTk7UOJHNycuq1LID/dqO0tBQrV67UKl9WVobVq1fzZFevXg2ZTAaFQsGTHTlyJPbt24elS5fCzMwM/fr1410fPHgwzp8/j61bt2qUo9ZHm34nTpzAsWPHePLqaEe1HUDXJ4MGDYKuri6ioqI03hIREfLy8gAAXbp0gUwmQ0xMDEpLSzmZ+Pj4GvWWyWRwc3PDL7/8gtu3b2uUoUZXV1dDh+XLl2uEDq4KT09PGBsbY968eTzXJDWvu+9pa9vKlJeXa7h1mZubw8rKiovmpFAoIJfL8cMPP+Dx48caedRnPRgMBuN9hb2xYDDeE+bPn4+0tDQ4OTlhzJgxsLOzQ35+Ps6cOYMDBw4gPz+/XspxcXFBw4YNERQUhMmTJ0MgEGD9+vUag1M1VlZWWLBgAbKystC6dWskJibi3LlziI2N1TglOiAgANOnT8fWrVsxfvx4jevTpk1DUlIShg4ditDQUCgUCuTn52PHjh2IiYlBx44d4e3tjZSUFPj4+MDLywuZmZmIiYmBnZ0db8AoFothZ2eHxMREtG7dGqampnBwcKhxT0J9IJfLMWfOHMycORNZWVkYOHAgjIyMkJmZia1bt2Ls2LGYOnUq9PT0MGfOHISFhaFHjx4YNmwYMjMzERcXV+MeCwD46aef0L17d3Tu3Bljx46Fra0tsrKysHv3bpw7dw4A4O3tjfXr10MqlcLOzg7Hjh3DgQMHYGZmVqu6GBsbY9WqVRg5ciQ6d+4MPz8/yGQy3L59G7t370a3bt2wYsWKVzEXR23btjKPHj2CtbU1hgwZgo4dO0IikeDAgQM4efIk96ZGR0cHa9asQb9+/WBvb4+QkBA0adIE9+7dQ1paGoyNjbFz5856qQeDwWC8t7yeoFQMBuNt8PDhQ5o4cSI1bdqU9PT0qHHjxtSzZ0+KjY0lov+FSd2yZQvvPm2hSt3d3cne3l5rOenp6eTs7ExisZisrKxo+vTpXMjYtLQ0jTxOnTpFH3/8MYlEIrKxsaEVK1ZUWYf+/fsTADp69KjW63l5eTRp0iRq0qQJ6evrk7W1NQUFBXFhdlUqFc2bN49sbGxIKBRSp06daNeuXRQUFMQL+UpEdPToUVIoFKSvr1+n0LNV2VEdkvXkyZO8dHU40pycHF56cnIyde/enQwNDcnQ0JDatm1LEydOpGvXrvHkVq5cSba2tiQUCqlLly50+PBhcnd3rzHcLBHRpUuXyMfHh0xMTEgkElGbNm1o1qxZ3PWCggIKCQmhRo0akUQiIU9PT7p69SrZ2NhQUFBQjXWraBNPT0+SSqUkEolILpdTcHAwnTp1qiZzatRh0aJFWq/XpW0rtmdJSQlNmzaNOnbsSEZGRmRoaEgdO3aklStXapRx9uxZGjRoEJmZmZFQKCQbGxvy9fWl//znP7WuR23DMjIYDMa7Qm2fawKiKpYZGQwG4xXx8PBAbm5ujX7+FfHx8cHFixc1TgJnMN4VioqKIJVKoVQqXyoqFoPBYPzTqO1zje2xYDAY/xgePHiA3bt3Y+TIkW9bFQaDwWAwGHWE7bFgMBhvnczMTKSnp2PNmjXQ09PjHaj3JiktLa1xL4pUKtUahpdRNcyuDAaD8WHAJhYMBuOt8/vvvyMkJATNmjXDunXrtJ6H8CY4evQoPvnkk2pl4uLiEBwc/GYUek9gdmUwGIwPA7bHgsFgMP4/BQUFOH36dLUy9vb2sLS0fEMavR98aHZleywYDMb7Rm2fa2xiwWAwGAxGPcImFgwG432Dbd5+ixw6dAgCgQBJSUlvWxXGK+Lh4QEPDw/ue1ZWFgQCAeLj419Leeq+c+jQodeS/5smODiYd7p2XWjevDlzjXmNvO6+XFcEAgEiIyO57/Hx8RAIBMjKyqpTPq/S5xgMBoPxarCJBeO1UlxcjMjIyPdmoMx4e1y5cgWRkZF1HmjWhcjISAgEAuTm5tb53vv37yMyMpI7eO5dRF1/HR0d3LlzR+N6UVERxGIxBAIBJk2a9BY0ZDAYDMY/GTaxYLxWiouLERUV9d5MLGxsbPD06VMWDrWW/Pzzz7h27Vq95HXlyhVERUW91onFq3D//n1ERUW90xMLNUKhEJs2bdJIT0lJeWM6jBw5Ek+fPoWNjU2d7qvPPsdgMBiMusEmFv9AiouL37YKjCoQCAQQiUTQ1dV926q8E+jp6UEoFL5tNd5pnjx58sbL7N+/v9aJxcaNG+Hl5fVGdNDV1YVIJIJAIKjTfazPMRgMxtuDTSxegnv37iE0NBQWFhYQCoWwt7fHL7/8oiGnUqkwd+5cWFtbQyQSoWfPnhqnCXt4eMDBwQGnT5+Gm5sbDAwM8M033wAAtm/fDi8vL1hZWUEoFEIul+P7779HeXl5lXm4uLhALBbD1tYWMTExnMzjx49haGiIL774QkPPu3fvQldXF9HR0VxaYWEhvvzySzRv3hxCoRDW1tYIDAzkXERKS0sRHh4OhUIBqVQKQ0NDuLq6Ii0tjcsjKysLMpkMABAVFQWBQKDhR10d6v0GmzdvRlRUFJo0aQIjIyMMGTIESqUSJSUlmDJlCszNzSGRSBASEoKSkhKNfDZs2ACFQgGxWAxTU1P4+flpdfOIjY2FXC6HWCxG165dceTIEQ2ZqvzSr169Cl9fX8hkMojFYrRp0wbffvstd/3WrVuYMGEC2rRpA7FYDDMzMwwdOrReVt+fP3+OqKgotGrVCiKRCGZmZujevTv279/PyQQHB0MikSAjIwOenp4wNDSElZUVZs+ejcrxG1QqFZYuXQp7e3uIRCJYWFggLCwMBQUFGmWnpqbC3d0dRkZGMDY2xkcffYSNGzfyyq3s7/7DDz/AxcUFZmZmEIvFUCgUNe5Hio+Px9ChQwEAn3zyCdeXDh06hKCgIDRq1AjPnz/XuK9Pnz5o06ZNjTasDvXv68qVK/jkk09gYGCAJk2aYOHChZzMoUOH8NFHHwEAQkJCOP0q9pMTJ06gb9++kEqlMDAwgLu7O9LT03llqV2Rrly5goCAADRs2BDdu3cH8GLPibe3N/773/+ia9euEIlEaNGiBX799VdeHvn5+Zg6dSrat28PiUQCY2Nj9OvXD+fPn691nQMCAnDu3DlcvXqVS/v7779x8OBBBAQEaL2npKQEERERaNmyJYRCIZo2bYrp06dr/CZLSkrw5ZdfQiaTwcjICAMGDMDdu3c18qtqj0Vd+5z6N/vDDz9wv3GhUIiPPvoIJ0+e1Cj36tWrGDJkCExNTSESidClSxfs2LGjNmZjMBiMDx52jkUdefjwIZydnTkfY5lMhtTUVIwaNQpFRUWYMmUKJzt//nzo6Ohg6tSpUCqVWLhwIYYPH44TJ07w8szLy0O/fv3g5+eHESNGwMLCAsCLP6wSiQRfffUVJBIJDh48iPDwcBQVFWHRokW8PAoKCtC/f3/4+vrC398fmzdvxvjx46Gvr4/Q0FBIJBL4+PggMTERS5Ys4a24b9q0CUSE4cOHA3gxCXF1dcWff/6J0NBQdO7cGbm5udixYwfu3r2LRo0aoaioCGvWrIG/vz/GjBmDR48eYe3atfD09MQff/wBR0dHyGQyrFq1CuPHj4ePjw8GDRoEAOjQoUOdbB4dHQ2xWIwZM2bgxo0bWL58OfT09KCjo4OCggJERkbi+PHjiI+Ph62tLcLDw7l7586di1mzZsHX1xejR49GTk4Oli9fDjc3N5w9exYmJiYAgLVr1yIsLAwuLi6YMmUKMjIyMGDAAJiamqJp06bV6nfhwgW4urpCT08PY8eORfPmzXHz5k3s3LkTc+fOBQCcPHkSR48ehZ+fH6ytrZGVlYVVq1bBw8MDV65cgYGBQZ1sUpHIyEhER0dj9OjR6Nq1K4qKinDq1CmcOXMGvXv35uTKy8vRt29fODs7Y+HChdizZw8iIiJQVlaG2bNnc3JhYWGIj49HSEgIJk+ejMzMTKxYsQJnz55Feno69PT0ALzon6GhobC3t8fMmTNhYmKCs2fPYs+ePVUOPgFg2bJlGDBgAIYPH47S0lL89ttvGDp0KHbt2lXlaribmxsmT56Mn376Cd988w3atWsHAGjXrh1GjhyJX3/9FXv37oW3tzd3j3ogHBER8dK2VVNQUIC+ffti0KBB8PX1RVJSEr7++mu0b98e/fr1Q7t27TB79myEh4dj7NixcHV1BQC4uLgAAA4ePIh+/fpBoVAgIiICOjo6iIuLQ48ePXDkyBF07dqVV97QoUPRqlUrzJs3jzfxu3HjBoYMGYJRo0YhKCgIv/zyC4KDg6FQKGBvbw8AyMjIwLZt2zB06FDY2tri4cOHWL16Ndzd3XHlyhVYWVnVWF83NzdYW1tj48aNXN9ITEyERCLR2kYqlQoDBgzAf//7X4wdOxbt2rXDxYsX8eOPP+Kvv/7Ctm3bONnRo0djw4YNCAgIgIuLCw4ePFjrtyAv2+eAF29bHj16hLCwMAgEAixcuBCDBg1CRkYG16cvX76Mbt26oUmTJpgxYwYMDQ2xefNmDBw4EMnJyfDx8dGad0lJCW8CVVRUVKv6MBgMxnsHMerEqFGjyNLSknJzc3npfn5+JJVKqbi4mNLS0ggAtWvXjkpKSjiZZcuWEQC6ePEil+bu7k4AKCYmRqOs4uJijbSwsDAyMDCgZ8+eaeSxePFiLq2kpIQcHR3J3NycSktLiYho7969BIBSU1N5eXbo0IHc3d257+Hh4QSAUlJSNMpXqVRERFRWVsarGxFRQUEBWVhYUGhoKJeWk5NDACgiIkIjr5pQ29HBwYGrAxGRv78/CQQC6tevH0/+448/JhsbG+57VlYW6erq0ty5c3lyFy9epAYNGnDppaWlZG5uTo6Ojrw6xcbGEgCebTIzMwkAxcXFcWlubm5kZGREt27d4pWjthWR9rY8duwYAaBff/1Vo85paWlVG6YSHTt2JC8vr2plgoKCCAB9/vnnPP28vLxIX1+fcnJyiIjoyJEjBIASEhJ49+/Zs4eXXlhYSEZGRuTk5ERPnz7lyVasd1BQEK9NiDRtUVpaSg4ODtSjRw9euo2NDQUFBXHft2zZotU25eXlZG1tTcOGDeOlL1myhAQCAWVkZFRhFU0iIiIIAGcPov/9viq2U0lJCTVu3JgGDx7MpZ08eVKjbxC9sEerVq3I09NTo0/Y2tpS7969Ncr39/fX0M3GxoYA0OHDh7m07OxsEgqF9K9//YtLe/bsGZWXl/PuzczMJKFQSLNnz+alVda3Yv2nTp1KLVu25K599NFHFBISQkREAGjixInctfXr15OOjg4dOXKEV25MTAwBoPT0dCIiOnfuHAGgCRMm8OQCAgI0nhNxcXEEgDIzM4no5fucup5mZmaUn5/PpW/fvp0A0M6dO7m0nj17Uvv27XnPV5VKRS4uLtSqVSuqCrXdKn+USmWV9zAYDMa7hFKprNVzjblC1QEiQnJyMj799FMQEXJzc7mPp6cnlEolzpw5w8mHhIRAX1+f+65exczIyODlKxQKERISolGeWCzm/v/o0SPk5ubC1dUVxcXFPBcFAGjQoAHCwsK47/r6+ggLC0N2djZ3MFWvXr1gZWWFhIQETu7SpUu4cOECRowYwaUlJyejY8eOWlfn1P7Ourq6XN1UKhXy8/NRVlaGLl268GxQHwQGBnIrigDg5OQEIkJoaChPzsnJCXfu3EFZWRmAFxtNVSoVfH19eW3VuHFjtGrVinPbOnXqFLKzszFu3DheewUHB0MqlVarW05ODg4fPozQ0FA0a9aMd62ib3jFtnz+/Dny8vLQsmVLmJiYvLK9TExMcPnyZVy/fr1G2YqRfNRv3UpLS3HgwAEAwJYtWyCVStG7d2+ezRQKBSQSCWez/fv349GjR5gxYwZEIlGV9dZGRVsUFBRAqVTC1dX1pe2go6OD4cOHY8eOHXj06BGXnpCQABcXF9ja2r5UvhWRSCS834i+vj66du2q8VvWxrlz53D9+nUEBAQgLy+Ps+mTJ0/Qs2dPHD58GCqVinfPuHHjtOZlZ2fHPUcAQCaToU2bNjw9hEIhdHRePNrLy8uRl5cHiUSCNm3a1MnGAQEBuHHjBk6ePMn9W9VbgS1btqBdu3Zo27Ytr9/06NEDALh+8+9//xsAMHnyZN79Fd/0VsWr9DkAGDZsGBo2bMh9r/w8zs/Px8GDB+Hr68s9b3Nzc5GXlwdPT09cv34d9+7d05r3zJkzoVQquY82V0sGg8H4EGCuUHUgJycHhYWFiI2NRWxsrFaZ7Oxs7o9X5YGmOr2yr3qTJk14A1o1ly9fxnfffYeDBw9qvFpXKpW871ZWVjA0NOSltW7dGsALH2NnZ2duALZq1SoUFxfDwMAACQkJEIlEnP86ANy8eRODBw+u0g5q1q1bh8WLF+Pq1as8//b6GMhVpLId1YP9yi5KUqkUKpUKSqUSZmZmuH79OogIrVq10pqverJy69YtANCQ09PTQ4sWLarVTT0ocXBwqFbu6dOniI6ORlxcHO7du8dzb6nclnVl9uzZ+Oyzz9C6dWs4ODigb9++GDlypIbLmY6OjkZ9KvYRALh+/TqUSiXMzc21lpWdnQ3gRR8Baq63Nnbt2oU5c+bg3LlzPPeRum7SrUhgYCAWLFiArVu3IjAwENeuXcPp06d5+4xeBWtraw39GjZsiAsXLtR4r3rCFxQUVKWMUqnkDXqr+g1V/i2o9aj4TFGpVFi2bBlWrlyJzMxM3p4sMzOzGvVV06lTJ7Rt2xYbN26EiYkJGjduzE0UKnP9+nX8+eef3J6qyqj7za1bt6CjowO5XM67Xpt9MK/S54Can8c3btwAEWHWrFmYNWuW1jyys7PRpEkTjXShUMg2jDMYDAbYxKJOqFcVR4wYUeUgoUOHDrhy5QoAVBk5iCptlq24gqumsLAQ7u7uMDY2xuzZsyGXyyESiXDmzBl8/fXXGiuctSUwMBCLFi3Ctm3b4O/vj40bN8Lb27vGlfnKbNiwAcHBwRg4cCCmTZsGc3NzbgO4egBQX1Rlx5rsq1KpIBAIkJqaqlVWIpHUn5I18PnnnyMuLg5TpkzBxx9/DKlUCoFAAD8/v5duSzVubm64efMmtm/fjn379mHNmjX48ccfERMTg9GjR9cpL5VKBXNzc95brYpUNXCsLUeOHMGAAQPg5uaGlStXwtLSEnp6eoiLi+NtwK0rdnZ2UCgU2LBhAwIDA7Fhwwbo6+vD19f3lfRVU9vfsjbU7bto0SI4OjpqlancF7U9E2qrx7x58zBr1iyEhobi+++/h6mpKXR0dDBlypQ697WAgACsWrUKRkZGGDZsGPcmpDIqlQrt27fHkiVLtF6vaZ/Sm6A2zwsAmDp1Kjw9PbXKtmzZ8vUox2AwGO8JbGJRB9RRTMrLy9GrV68q5dQTi1fh0KFDyMvLQ0pKCtzc3Lj0zMxMrfL379/HkydPeG8t/vrrLwDgRUhxcHBAp06dkJCQAGtra9y+fRvLly/n5SWXy3Hp0qVq9UtKSkKLFi2QkpLCW8mtvFH2VVahXxW5XA4igq2tLbcyrw11nPzr16/zVmSfP3+OzMxMdOzYscp71W8AamOvoKAgLF68mEt79uwZCgsLa1OVGjE1NUVISAhCQkLw+PFjuLm5ITIykjexUKlUyMjI4Nmich+Ry+U4cOAAunXrVuXgVi0HvKh3XQZbycnJEIlE2Lt3L2+FNy4ursZ7a+pLgYGB+Oqrr/DgwQMuLGrFtwCvm6r0U9vK2Ni42udGfZGUlIRPPvkEa9eu5aUXFhaiUaNGdcorICAA4eHhePDgAdavX1+lnFwux/nz59GzZ89q28nGxgYqlQo3b97kvaWozbkTL9vnaov6t6ynp/dG2onBYDDeR9geizqgq6uLwYMHIzk5WetAMicnp17LAvgrkaWlpVi5cqVW+bKyMqxevZonu3r1ashkMigUCp7syJEjsW/fPixduhRmZmbo168f7/rgwYNx/vx5bN26VaMctT7a9Dtx4gSOHTvGk1dHO6qvAXRdGDRoEHR1dREVFaWxskxEyMvLAwB06dIFMpkMMTExKC0t5WTi4+Nr1Fsmk8HNzQ2//PILbt++rVGGGl1dXQ0dli9frhE6+GVQ10ONRCJBy5YttYbeXbFiBU+/FStWQE9PDz179gQA+Pr6ory8HN9//73GvWVlZZw9+vTpAyMjI0RHR+PZs2c8uepW8XV1dSEQCHj1zsrK4kUNqgr1pLmqNvH394dAIMAXX3yBjIwM3p6IN0FV+ikUCsjlcvzwww94/Pixxn31+dwAtPe1LVu2VLk/oDrkcjmWLl2K6OhojchVFfH19cW9e/fw888/a1x7+vQpdxaH+lnz008/8WSWLl1aoy4v2+dqi7m5OTw8PLB69Wo8ePBA43p9txODwWC8j7A3FnVk/vz5SEtLg5OTE8aMGQM7Ozvk5+fjzJkzOHDgAPLz8+ulHBcXFzRs2BBBQUGYPHkyBAIB1q9fX+UfUCsrKyxYsABZWVlo3bo1EhMTce7cOcTGxvI2PgMvViGnT5+OrVu3Yvz48RrXp02bhqSkJAwdOhShoaFQKBTIz8/Hjh07EBMTg44dO8Lb2xspKSnw8fGBl5cXMjMzERMTAzs7O97gSSwWw87ODomJiWjdujVMTU3h4ODw0n7SdUEul2POnDmYOXMmsrKyMHDgQBgZGSEzMxNbt27F2LFjMXXqVOjp6WHOnDkICwtDjx49MGzYMGRmZiIuLq7GPRbAi0FS9+7d0blzZ4wdOxa2trbIysrC7t27uVOYvb29sX79ekilUtjZ2eHYsWM4cOBAnXzeq8LOzg4eHh5QKBQwNTXFqVOnkJSUxNuoDQAikQh79uxBUFAQnJyckJqait27d+Obb77hXJzc3d0RFhaG6OhonDt3Dn369IGenh6uX7+OLVu2YNmyZRgyZAiMjY3x448/YvTo0fjoo4+4MxfOnz+P4uJirFu3TquuXl5eWLJkCfr27YuAgABkZ2fj//7v/9CyZcsa9ys4OjpCV1cXCxYsgFKphFAoRI8ePbj9IDKZDH379sWWLVtgYmLyxg5yUyOXy2FiYoKYmBgYGRnB0NAQTk5OsLW1xZo1a9CvXz/Y29sjJCQETZo0wb1795CWlgZjY2Ps3Lmz3vTw9vbG7NmzERISAhcXF1y8eBEJCQm16sva0Hb2TWVGjhyJzZs3Y9y4cUhLS0O3bt1QXl6Oq1evYvPmzdi7dy+6dOkCR0dH+Pv7Y+XKlVAqlXBxccF//vMfjfN9tPGyfa4u/N///R+6d++O9u3bY8yYMWjRogUePnyIY8eO4e7du3U6C4TBYDA+SOo5GtUHwcOHD2nixInUtGlT0tPTo8aNG1PPnj0pNjaWiP4XMnTLli28+7SFd3R3dyd7e3ut5aSnp5OzszOJxWKysrKi6dOncyFjK4bcVOdx6tQp+vjjj0kkEpGNjQ2tWLGiyjr079+fANDRo0e1Xs/Ly6NJkyZRkyZNSF9fn6ytrSkoKIgLs6tSqWjevHlkY2NDQqGQOnXqRLt27dIaXvTo0aOkUChIX1+/TqFnq7KjOgzlyZMneenaQoUSESUnJ1P37t3J0NCQDA0NqW3btjRx4kS6du0aT27lypVka2tLQqGQunTpQocPHyZ3d/caw80SEV26dIl8fHzIxMSERCIRtWnThmbNmsVdLygooJCQEGrUqBFJJBLy9PSkq1evaoRUfZlws3PmzKGuXbuSiYkJicViatu2Lc2dO5cXojcoKIgMDQ3p5s2b1KdPHzIwMCALCwuKiIjQCE1K9CLUrkKhILFYTEZGRtS+fXuaPn063b9/nye3Y8cOcnFxIbFYTMbGxtS1a1fatGkTr9zK/WHt2rXUqlUrEgqF1LZtW4qLi+PariKVbUNE9PPPP1OLFi1IV1dXq502b95MAGjs2LG1tl9Fqgo3q+03qq1u27dvJzs7O2rQoIFGPzl79iwNGjSIzMzMSCgUko2NDfn6+tJ//vOfastXY2NjozWscOU++uzZM/rXv/5FlpaWJBaLqVu3bnTs2LFa9eXqyq8IKoWbJXoRNnjBggVkb29PQqGQGjZsSAqFgqKionjhCZ8+fUqTJ08mMzMzMjQ0pE8//ZTu3LlTY7hZNXXtc+p6Llq0SGs9Kj+Pbt68SYGBgdS4cWPS09OjJk2akLe3NyUlJVVrk4rUNiwjg8FgvCvU9rkmIKqHd8iMt4qHhwdyc3Nr9POviI+PDy5evFirlULGu09wcDCSkpK0uuK8T2zfvh0DBw7E4cOHeWFZGYw3SVFREaRSKZRKJYyNjd+2OgwGg/HK1Pa5xvZYfIA8ePAAu3fvxsiRI9+2KgxGvfLzzz+jRYsW6N69+9tWhcFgMBiMDw62x+IDIjMzE+np6VizZg309PR4B+q9SUpLS2vciyKVSquNSvQh8PTp0xrPuDA1NdV6BsqHxm+//YYLFy5g9+7dWLZsmUZkIqVSiadPn1abR+PGjV+nigwGg8FgvPewicUHxO+//46QkBA0a9YM69ate2sDqaNHj+KTTz6pViYuLg7BwcFvRqF/KImJiVpPZK9IWloaPDw83oxC/2D8/f0hkUgwatQoTJgwQeP6F198UePmXuYVymAwGAzGq8H2WDDeOAUFBTh9+nS1Mvb29rC0tHxDGv0zefDgAS5fvlytjEKheKNnNbyrXLlyBffv369Whp1dwKgv2B4LBoPxvlHb5xqbWDAYDAaDUY+wiQWDwXjfYJu3GQwGg8FgMBgMxhuDTSwYDAYOHToEgUCApKSkt60K4xXx8PDg7bvJysqCQCBAfHz8W9OJwWAwGB8GbGLBYDAYFSguLkZkZCQOHTr0tlVh4MVESSAQ1PiJjIx826oyGAzGBw+LCsVgMBgVKC4uRlRUFAC8FxG3bGxs8PTpU+jp6b1tVV6Kb7/9FqNHj+a+nzx5Ej/99BO++eYbtGvXjkvv0KHD21CPwWAwGBVgEwsGg/HKFBcXw8DA4G2rwdCCQCCASCR6o2U+efIEhoaG9ZJX7969ed9FIhF++ukn9O7du9qJX33qwGAwGIzawVyhGIwPgHv37iE0NBQWFhYQCoWwt7fHL7/8oiGnUqkwd+5cWFtbQyQSoWfPnrhx4wZPxsPDAw4ODjh9+jTc3NxgYGCAb775BgCwfft2eHl5wcrKCkKhEHK5HN9//z3Ky8urzMPFxQVisRi2traIiYnhZB4/fgxDQ0N88cUXGnrevXsXurq6iI6O5tIKCwvx5Zdfonnz5hAKhbC2tkZgYCByc3MBvDiYMTw8HAqFAlKpFIaGhnB1dUVaWhqXR1ZWFmQyGQAgKiqqzm426r0qmzdvRlRUFJo0aQIjIyMMGTIESqUSJSUlmDJlCszNzSGRSBASEoKSkhKNfDZs2ACFQgGxWAxTU1P4+fnhzp07GnKxsbGQy+UQi8Xo2rUrjhw5oiFT1R6Lq1evwtfXFzKZDGKxGG3atMG3337LXb916xYmTJiANm3aQCwWw8zMDEOHDkVWVhYvn/j4eAgEAvz++++YMGECzM3NYW1tzV1PTU2Fq6srDA0NYWRkBC8vrxrDKNeVyMhICAQCXLlyBQEBAWjYsCF3+nrlPSdqgoOD0bx5c16aSqXC0qVLYW9vD5FIBAsLC4SFhaGgoKBe9WUwGIz3FfbGgsF4z3n48CGcnZ0hEAgwadIkyGQypKamYtSoUSgqKsKUKVM42fnz50NHRwdTp06FUqnEwoULMXz4cJw4cYKXZ15eHvr16wc/Pz+MGDECFhYWAF4MMiUSCb766itIJBIcPHgQ4eHhKCoqwqJFi3h5FBQUoH///vD19YW/vz82b96M8ePHQ19fH6GhoZBIJPDx8UFiYiKWLFkCXV1d7t5NmzaBiDB8+HAALyYhrq6u+PPPPxEaGorOnTsjNzcXO3bswN27d9GoUSMUFRVhzZo18Pf3x5gxY/Do0SOsXbsWnp6e+OOPP+Do6AiZTIZVq1Zh/Pjx8PHxwaBBgwDU3c0mOjoaYrEYM2bMwI0bN7B8+XLo6elBR0cHBQUFiIyMxPHjxxEfHw9bW1uEh4dz986dOxezZs2Cr68vRo8ejZycHCxfvhxubm44e/YsTExMAABr165FWFgYXFxcMGXKFGRkZGDAgAEwNTVF06ZNq9XvwoULcHV1hZ6eHsaOHYvmzZvj5s2b2LlzJ+bOnQvghcvR0aNH4efnB2tra2RlZWHVqlXw8PDAlStXNN5QTZgwATKZDOHh4Xjy5AkAYP369QgKCoKnpycWLFiA4uJirFq1Ct27d8fZs2c1BvavytChQ9GqVSvMmzfvpQ48DAsLQ3x8PEJCQjB58mRkZmZixYoVOHv2LNLT06t0JyspKeFNEIuKil66DgwGg/FOQwwG471m1KhRZGlpSbm5ubx0Pz8/kkqlVFxcTGlpaQSA2rVrRyUlJZzMsmXLCABdvHiRS3N3dycAFBMTo1FWcXGxRlpYWBgZGBjQs2fPNPJYvHgxl1ZSUkKOjo5kbm5OpaWlRES0d+9eAkCpqam8PDt06EDu7u7c9/DwcAJAKSkpGuWrVCoiIiorK+PVjYiooKCALCwsKDQ0lEvLyckhABQREaGRV02o7ejg4MDVgYjI39+fBAIB9evXjyf/8ccfk42NDfc9KyuLdHV1ae7cuTy5ixcvUoMGDbj00tJSMjc3J0dHR16dYmNjCQDPNpmZmQSA4uLiuDQ3NzcyMjKiW7du8cpR24pIe1seO3aMANCvv/7KpcXFxREA6t69O5WVlXHpjx49IhMTExozZgwvj7///pukUqlGem3ZsmULAaC0tDQuLSIiggCQv7+/hry7uzvPHmqCgoJ4tj9y5AgBoISEBJ7cnj17tKZXRF1+5Y9Sqaxz/RgMBuOfiFKprNVzjblCMRjvMUSE5ORkfPrppyAi5Obmch9PT08olUqcOXOGkw8JCYG+vj733dXVFQCQkZHBy1coFCIkJESjPLFYzP3/0aNHyM3NhaurK4qLi3H16lWebIMGDRAWFsZ919fXR1hYGLKzs7mT2Xv16gUrKyskJCRwcpcuXcKFCxcwYsQILi05ORkdO3aEj4+Phk4CgQAAoKury9VNpVIhPz8fZWVl6NKlC88G9UFgYCBvddvJyQlEhNDQUJ6ck5MT7ty5g7KyMgBASkoKVCoVfH19eW3VuHFjtGrVinPbOnXqFLKzszFu3DheewUHB0MqlVarW05ODg4fPozQ0FA0a9aMd01tK4Dfls+fP0deXh5atmwJExMTrfYaM2YM763S/v37UVhYCH9/f15ddHV14eTkxHNBqy/GjRv30vdu2bIFUqkUvXv35umrUCggkUiq1XfmzJlQKpXcR5vbGoPBYHwIMFcoBuM9JicnB4WFhYiNjUVsbKxWmezsbDRs2BAANAaa6vTKPuZNmjThDWjVXL58Gd999x0OHjyo4Q6iVCp5362srDQ217Zu3RrAi30Bzs7O0NHRwfDhw7Fq1Spug3hCQgJEIhGGDh3K3Xfz5k0MHjy4SjuoWbduHRYvXoyrV6/i+fPnXLqtrW2N99aFynZUD/YruyhJpVKoVCoolUqYmZnh+vXrICK0atVKa77qycqtW7cAQENOT08PLVq0qFY39STRwcGhWrmnT58iOjoacXFxuHfvHs+1qHJbApo2vH79OgCgR48eWvN/HSdSv0o7Xr9+HUqlEubm5lqvZ2dnV3mvUCiEUCh86bIZDAbjfYFNLBiM9xiVSgUAGDFiBIKCgrTKdOjQAVeuXAEA3opzRaiSv3rF1Ww1hYWFcHd3h7GxMWbPng25XA6RSIQzZ87g66+/5nSpK4GBgVi0aBG2bdsGf39/bNy4Ed7e3jWuzFdmw4YNCA4OxsCBAzFt2jSYm5tzG8Bv3rz5UrpVRVV2rMm+KpUKAoEAqampWmUlEkn9KVkDn3/+OeLi4jBlyhR8/PHHkEqlEAgE8PPz09qWlfuEWmb9+vVo3LixhnyDBvX/50dbvxQIBFr3W1QOKKBSqWBubs57O1YR9aZ+BoPBYFQNm1gwGO8xMpkMRkZGKC8vR69evaqUU08sXoVDhw4hLy8PKSkpcHNz49IzMzO1yt+/f18jJOhff/0FALxNvQ4ODujUqRMSEhJgbW2N27dvY/ny5by85HI5Ll26VK1+SUlJaNGiBVJSUnguPxERETy5itfeNHK5HEQEW1tb7u2NNmxsbAC8WGWv+Ebg+fPnyMzMRMeOHau8V/1Gozb2CgoKwuLFi7m0Z8+eobCwsDZVgVwuBwCYm5tX2/deNw0bNtRw5QP+99ZHjVwux4EDB9CtWzetExQGg8Fg1AzbY8FgvMfo6upi8ODBSE5O1jqQzMnJqdeyAP7bjdLSUqxcuVKrfFlZGVavXs2TXb16NWQyGRQKBU925MiR2LdvH5YuXQozMzP069ePd33w4ME4f/48tm7dqlGOWh9t+p04cQLHjh3jyaujHdV2AF2fDBo0CLq6uoiKitJYZSci5OXlAQC6dOkCmUyGmJgYlJaWcjLx8fE16i2TyeDm5oZffvkFt2/f1ihDja6uroYOy5cv11jprwpPT08YGxtj3rx5PLczNfXZ96pDLpfj6tWrvPLOnz+P9PR0npyvry/Ky8vx/fffa+RRVlb2VvoDg8FgvGuwNxYMxnvO/PnzkZaWBicnJ4wZMwZ2dnbIz8/HmTNncODAAeTn59dLOS4uLmjYsCGCgoIwefJkCAQCrF+/vsqwn1ZWVliwYAGysrLQunVrJCYm4ty5c4iNjdUI6xkQEIDp06dj69atGD9+vMb1adOmISkpCUOHDkVoaCgUCgXy8/OxY8cOxMTEoGPHjvD29kZKSgp8fHzg5eWFzMxMxMTEwM7ODo8fP+byEovFsLOzQ2JiIlq3bg1TU1M4ODjUuCehPpDL5ZgzZw5mzpyJrKwsDBw4EEZGRsjMzMTWrVsxduxYTJ06FXp6epgzZw7CwsLQo0cPDBs2DJmZmYiLi6txjwUA/PTTT+jevTs6d+6MsWPHwtbWFllZWdi9ezfOnTsHAPD29sb69eshlUphZ2eHY8eO4cCBAzAzM6tVXYyNjbFq1SqMHDkSnTt3hp+fH2QyGW7fvo3du3ejW7duWLFixauYq1aEhoZiyZIl8PT0xKhRo5CdnY2YmBjY29vz9gG5u7sjLCwM0dHROHfuHPr06QM9PT1cv34dW7ZswbJlyzBkyJDXri+DwWC807yeoFQMBuOfxMOHD2nixInUtGlT0tPTo8aNG1PPnj0pNjaWiP4XJnXLli28+7SFKnV3dyd7e3ut5aSnp5OzszOJxWKysrKi6dOncyFjK4YHVedx6tQp+vjjj0kkEpGNjQ2tWLGiyjr079+fANDRo0e1Xs/Ly6NJkyZRkyZNSF9fn6ytrSkoKIgLs6tSqWjevHlkY2NDQqGQOnXqRLt27dIIO0pEdPToUVIoFKSvr1+n0LNV2VEdkvXkyZO8dHWY0pycHF56cnIyde/enQwNDcnQ0JDatm1LEydOpGvXrvHkVq5cSba2tiQUCqlLly50+PBhjfCq2tqQiOjSpUvk4+NDJiYmJBKJqE2bNjRr1izuekFBAYWEhFCjRo1IIpGQp6cnXb16lWxsbCgoKKjGulW0iaenJ0mlUhKJRCSXyyk4OJhOnTpVkzm1Ul242cp2VLNhwwZq0aIF6evrk6OjI+3du1druxO9CNmrUChILBaTkZERtW/fnqZPn07379+vtY61DcvIYDAY7wq1fa4JiF7iFCEGg8F4BTw8PJCbm1ujn39FfHx8cPHiRY2TwBmMfxpFRUWQSqVQKpWvJfoVg8FgvGlq+1xjeywYDMY/ngcPHmD37t0YOXLk21aFwWAwGAxGFbA9FgwG4x9LZmYm0tPTsWbNGujp6fEO1HuTlJaW1rgXRSqVsmhCdYTZlcFgMN4v2MSCwWD8Y/n9998REhKCZs2aYd26dVrPQ3gTHD16FJ988km1MnFxcQgODn4zCr0nMLsyGAzG+wXbY8FgMBg1UFBQgNOnT1crY29vD0tLyzek0fvB+2pXtseCwWC8b9T2ucYmFgwGg8Fg1CNsYsFgMN432OZtxjvDoUOHIBAIkJSU9LZVYbwiHh4e8PDw4L5nZWVBIBAgPj7+tZSn7juHDh16Lfm/aYKDg3mnjteF5s2bvzMuQ6+zXwgEAkRGRtZ7vgwGg8GoGTaxYDD+QRQXFyMyMvK9GSgz3h5XrlxBZGQksrKyXlsZkZGREAgE0NHRwZ07dzSuFxUVQSwWQyAQYNKkSa9NDwbjQ6T5jN1oPmP321aDweDBNm8zGP8giouLERUVBQC8lf93FRsbGzx9+lTjpGyGdn7++WeoVKp6yevKlSuIioqCh4fHS78FqS1CoRCbNm3C9OnTeekpKSla5V9nv3j69CkaNGB/2hgMBuNtwN5YMN55iouL37YKjCoQCAQQiUTQ1dV926q8E+jp6UEoFL5tNepM//79sWnTJo30jRs3wsvLSyP9dfYLkUjEJhYMBoPxlmATC8Zr5969ewgNDYWFhQWEQiHs7e3xyy+/aMipVCrMnTsX1tbWEIlE6Nmzp8Ypyx4eHnBwcMDp06fh5uYGAwMDfPPNNwCA7du3w8vLC1ZWVhAKhZDL5fj+++9RXl5eZR4uLi4Qi8WwtbVFTEwMJ/P48WMYGhriiy++0NDz7t270NXVRXR0NJdWWFiIL7/8Es2bN4dQKIS1tTUCAwORm5sL4EW8/vDwcCgUCkilUhgaGsLV1RVpaWlcHllZWZDJZACAqKgoCASCOvmLq/cbbN68GVFRUWjSpAmMjIwwZMgQKJVKlJSUYMqUKTA3N4dEIkFISAhKSko08tmwYQMUCgXEYjFMTU3h5+en1c0lNjYWcrkcYrEYXbt2xZEjRzRkqvKlv3r1Knx9fSGTySAWi9GmTRt8++233PVbt25hwoQJaNOmDcRiMczMzDB06NB6cet5/vw5oqKi0KpVK4hEIpiZmaF79+7Yv38/JxMcHAyJRIKMjAx4enrC0NAQVlZWmD17NirHu1CpVFi6dCns7e0hEolgYWGBsLAwFBQUaJSdmpoKd3d3GBkZwdjYGB999BE2btzIK7fy24UffvgBLi4uMDMzg1gshkKhqHE/Unx8PIYOHQoA+OSTT7i+dOjQIQQFBaFRo0Z4/vy5xn19+vRBmzZtarRhZQICAnDu3DlcvXqVS/v7779x8OBBBAQEaMhr6xd///03QkJCYG1tDaFQCEtLS3z22We8Nj916hQ8PT3RqFEj7ncbGhrKy7vyb0btrnXjxg0EBwfDxMQEUqkUISEhGosST58+xeTJk9GoUSMYGRlhwIABuHfvHtu3wWAwGLWELeswXisPHz6Es7Mz52Mtk8mQmpqKUaNGoaioCFOmTOFk58+fDx0dHUydOhVKpRILFy7E8OHDceLECV6eeXl56NevH/z8/DBixAhYWFgAeDGYkkgk+OqrryCRSHDw4EGEh4ejqKgIixYt4uVRUFCA/v37w9fXF/7+/ti8eTPGjx8PfX19hIaGQiKRwMfHB4mJiViyZAlvZXXTpk0gIgwfPhzAi0mIq6sr/vzzT4SGhqJz587Izc3Fjh07cPfuXTRq1AhFRUVYs2YN/P39MWbMGDx69Ahr166Fp6cn/vjjDzg6OkImk2HVqlUYP348fHx8MGjQIABAhw4d6mTz6OhoiMVizJgxAzdu3MDy5cuhp6cHHR0dFBQUIDIyEsePH0d8fDxsbW0RHh7O3Tt37lzMmjULvr6+GD16NHJycrB8+XK4ubnh7NmzMDExAQCsXbsWYWFhcHFxwZQpU5CRkYEBAwbA1NQUTZs2rVa/CxcuwNXVFXp6ehg7diyaN2+OmzdvYufOnZg7dy4A4OTJkzh69Cj8/PxgbW2NrKwsrFq1Ch4eHrhy5QoMDAzqZJOKREZGIjo6GqNHj0bXrl1RVFSEU6dO4cyZM+jduzcnV15ejr59+8LZ2RkLFy7Enj17EBERgbKyMsyePZuTCwsLQ3x8PEJCQjB58mRkZmZixYoVOHv2LNLT0zl3n/j4eISGhsLe3h4zZ86EiYkJzp49iz179mgdfKtZtmwZBgwYgOHDh6O0tBS//fYbhg4dil27dml9GwAAbm5umDx5Mn766Sd88803aNeuHQCgXbt2GDlyJH799Vfs3bsX3t7e3D3qiUBERESdberm5gZra2ts3LiRs01iYiIkEkmVOlZm8ODBuHz5Mj7//HM0b94c2dnZ2L9/P27fvs1979OnD2QyGWbMmAETExNkZWVV6W5VGV9fX9ja2iI6OhpnzpzBmjVrYG5ujgULFnAywcHB2Lx5M0aOHAlnZ2f8/vvvtdK/pKSEN0kvKiqqlU4MBoPx3kEMxmtk1KhRZGlpSbm5ubx0Pz8/kkqlVFxcTGlpaQSA2rVrRyUlJZzMsmXLCABdvHiRS3N3dycAFBMTo1FWcXGxRlpYWBgZGBjQs2fPNPJYvHgxl1ZSUkKOjo5kbm5OpaWlRES0d+9eAkCpqam8PDt06EDu7u7c9/DwcAJAKSkpGuWrVCoiIiorK+PVjYiooKCALCwsKDQ0lEvLyckhABQREaGRV02o7ejg4MDVgYjI39+fBAIB9evXjyf/8ccfk42NDfc9KyuLdHV1ae7cuTy5ixcvUoMGDbj00tJSMjc3J0dHR16dYmNjCQDPNpmZmQSA4uLiuDQ3NzcyMjKiW7du8cpR24pIe1seO3aMANCvv/6qUee0tLSqDVOJjh07kpeXV7UyQUFBBIA+//xznn5eXl6kr69POTk5RER05MgRAkAJCQm8+/fs2cNLLywsJCMjI3JycqKnT5/yZCvWOygoiNcmRJq2KC0tJQcHB+rRowcv3cbGhoKCgrjvW7Zs0Wqb8vJysra2pmHDhvHSlyxZQgKBgDIyMqqwiiYREREEgHJycmjq1KnUsmVL7tpHH31EISEhREQEgCZOnMhdq9wvCgoKCAAtWrSoyrK2bt1KAOjkyZPV6lT596PWseLvjIjIx8eHzMzMuO+nT58mADRlyhSeXHBwcI2/SXUZlT9KpbJaXRmMV8Hm611k8/Wut60G4wNBqVTW6rnGXKEYrw0iQnJyMj799FMQEXJzc7mPp6cnlEolzpw5w8mHhIRAX1+f++7q6goAyMjI4OUrFAoREhKiUZ5YLOb+/+jRI+Tm5sLV1RXFxcU8Fw0AaNCgAcLCwrjv+vr6CAsLQ3Z2NndgV69evWBlZYWEhARO7tKlS7hw4QJGjBjBpSUnJ6Njx47w8fHR0EkgEAAAdHV1ubqpVCrk5+ejrKwMXbp04dmgPggMDORtinVycgIRabiMODk54c6dOygrKwPwYqOtSqWCr68vr60aN26MVq1acW5bp06dQnZ2NsaNG8drr+DgYEil0mp1y8nJweHDhxEaGopmzZrxrqltBfDb8vnz58jLy0PLli1hYmLyyvYyMTHB5cuXcf369RplK0YyUr91Ky0txYEDBwAAW7ZsgVQqRe/evXk2UygUkEgknM3279+PR48eYcaMGRCJRFXWWxsVbVFQUAClUglXV9eXtoOOjg6GDx+OHTt24NGjR1x6QkICXFxcYGtr+1L5BgQE4MaNGzh58iT3b3VvYioiFouhr6+PQ4cOaXUhA8C9Ldu1a5dWN66aGDduHO+7q6sr8vLyuLcLe/bsAQBMmDCBJ/f555/XmPfMmTOhVCq5jzbXQQaDwfgQYBMLxmsjJycHhYWFiI2NhUwm433UE4Ps7GxOvvJAs2HDhgCgMdBo0qQJb0Cr5vLly/Dx8YFUKoWxsTFkMhk3AVAqlTxZKysrGBoa8tJat24NAJxPt3oAtm3bNs4XOyEhASKRiPNfB4CbN2/CwcGhRnusW7cOHTp04Pz6ZTIZdu/eraHbq1LZjurBfmUXJalUCpVKxZV//fp1EBFatWql0V5//vkn11a3bt0CALRq1YqXn56eHlq0aFGtbupJYk32evr0KcLDw9G0aVMIhUI0atQIMpkMhYWFr2yv2bNno7CwEK1bt0b79u0xbdo0XLhwQUNOR0dHoz6V+8j169ehVCphbm6uYbPHjx9zNrt582at6q2NXbt2wdnZGSKRCKamppzL3KvYITAwEE+fPsXWrVsBANeuXcPp06cxcuTIl86zU6dOaNu2LTZu3IiEhAQ0btwYPXr0qNW9QqEQCxYsQGpqKiwsLODm5oaFCxfi77//5mTc3d0xePBgREVFoVGjRvjss88QFxendZ+QNmp6vty6dQs6OjoaE6uWLVvWSn9jY2Peh8FgMD5E2B4LxmtDHTZzxIgRCAoK0irToUMHXLlyBQCqjBBDlTbLVlzBVVNYWAh3d3cYGxtj9uzZkMvlEIlEOHPmDL7++uuXDuEZGBiIRYsWYdu2bfD398fGjRvh7e1d48p8ZTZs2IDg4GAMHDgQ06ZNg7m5ObcBXD3orC+qsmNN9lWpVBAIBEhNTdUqK5FI6k/JGvj8888RFxeHKVOm4OOPP4ZUKoVAIICfn98rh2N1c3PDzZs3sX37duzbtw9r1qzBjz/+iJiYGIwePbpOealUKpibm/PealVEvRn/ZTly5AgGDBgANzc3rFy5EpaWltDT00NcXBxv03ddsbOzg0KhwIYNGxAYGIgNGzZAX18fvr6+r6RvQEAAVq1aBSMjIwwbNgw6OrVfu5oyZQo+/fRTbNu2DXv37sWsWbMQHR2NgwcPolOnTtwhmsePH8fOnTuxd+9ehIaGYvHixTh+/HiN/bO2zxcGg8FgvDxsYsF4bchkMhgZGaG8vBy9evWqUk49sXgVDh06hLy8PKSkpMDNzY1Lz8zM1Cp///59PHnyhPfW4q+//gIAXlQeBwcHdOrUCQkJCbC2tsbt27exfPlyXl5yuRyXLl2qVr+kpCS0aNECKSkpPNeXyhtla3KLeZ3I5XIQEWxtbbmVeW3Y2NgAeLFaX3FF+vnz58jMzETHjh2rvFf9BqA29goKCsLixYu5tGfPnqGwsLA2VakRU1NThISEICQkBI8fP4abmxsiIyN5EwuVSoWMjAyeLSr3EblcjgMHDqBbt25aJ7xq5HI5gBf1rs0KuJrk5GSIRCLs3buXF4Y2Li6uxntr6kuBgYH46quv8ODBAy4srHoV/2UJCAhAeHg4Hjx4gPXr19f5frlcjn/961/417/+hevXr8PR0RGLFy/Ghg0bOBlnZ2c4Oztj7ty52LhxI4YPH47ffvutzpPCytjY2EClUiEzM5P3Nq5yZDoGg8FgVA1zhWK8NnR1dTF48GAkJydrHUjm5OTUa1kAf/WxtLQUK1eu1CpfVlaG1atX82RXr14NmUwGhULBkx05ciT27duHpUuXwszMDP369eNdHzx4MM6fP8+5lVRErY82/U6cOIFjx47x5NXRjuprAF0XBg0aBF1dXURFRWms4hIR8vLyAABdunSBTCZDTEwMSktLOZn4+Pga9ZbJZHBzc8Mvv/yC27dva5ShRldXV0OH5cuXa4QOfhnU9VAjkUjQsmVLrS41K1as4Om3YsUK6OnpoWfPngBeRBoqLy/H999/r3FvWVkZZ48+ffrAyMgI0dHRePbsGU+uuhVzXV1dCAQCXr2zsrKwbdu2GuupnjRX1Sb+/v4QCAT44osvkJGRwds39LLI5XIsXboU0dHR6Nq1a63vKy4u1rCLXC6HkZER1y4FBQUatnJ0dASAWrtDVYenpycAaDwzKi8kMBgMBqNq2BsLxmtl/vz5SEtLg5OTE8aMGQM7Ozvk5+fjzJkzOHDgAPLz8+ulHBcXFzRs2BBBQUGYPHkyBAIB1q9fX+WgzcrKCgsWLEBWVhZat26NxMREnDt3DrGxsRqnAQcEBGD69OnYunUrxo8fr3F92rRpSEpKwtChQxEaGgqFQoH8/Hzs2LEDMTEx6NixI7y9vZGSkgIfHx94eXkhMzMTMTExsLOzw+PHj7m8xGIx7OzskJiYiNatW8PU1BQODg4v5ZtfV+RyOebMmYOZM2ciKysLAwcOhJGRETIzM7F161aMHTsWU6dOhZ6eHubMmYOwsDD06NEDw4YNQ2ZmJuLi4mrcYwEAP/30E7p3747OnTtj7NixsLW1RVZWFnbv3o1z584BALy9vbF+/XpIpVLY2dnh2LFjOHDgAMzMzF65nnZ2dvDw8IBCoYCpqSlOnTqFpKQk3kZt4MVBa3v27EFQUBCcnJyQmpqK3bt345tvvuFcnNzd3REWFobo6GicO3cOffr0gZ6eHq5fv44tW7Zg2bJlGDJkCIyNjfHjjz9i9OjR+OijjxAQEICGDRvi/PnzKC4uxrp167Tq6uXlhSVLlqBv374ICAhAdnY2/u///g8tW7bUui+kIo6OjtDV1cWCBQugVCohFArRo0cPmJubA3gxyevbty+2bNkCExOTWoeFrQltZ7/UxF9//YWePXvC19cXdnZ2aNCgAbZu3YqHDx/Cz88PwIs9SitXroSPjw/kcjkePXqEn3/+GcbGxujfv/8r661QKDB48GAsXboUeXl5XLhZ9Vuqt/k2kcHQRtb8+vnNMhj1yusIScVgVOThw4c0ceJEatq0Kenp6VHjxo2pZ8+eFBsbS0T/Cxm6ZcsW3n3aQpW6u7uTvb291nLS09PJ2dmZxGIxWVlZ0fTp07mQsRVDbqrzOHXqFH388cckEonIxsaGVqxYUWUd+vfvTwDo6NGjWq/n5eXRpEmTqEmTJqSvr0/W1tYUFBTEhdlVqVQ0b948srGxIaFQSJ06daJdu3ZpDS969OhRUigUpK+vX6fQs1XZMS4uTmuYzoqhQiuSnJxM3bt3J0NDQzI0NKS2bdvSxIkT6dq1azy5lStXkq2tLQmFQurSpQsdPnyY3N3daww3S0R06dIl8vHxIRMTExKJRNSmTRuaNWsWd72goIBCQkKoUaNGJJFIyNPTk65evaoRUvVlws3OmTOHunbtSiYmJiQWi6lt27Y0d+5cXojeoKAgMjQ0pJs3b1KfPn3IwMCALCwsKCIigsrLyzXyjI2NJYVCQWKxmIyMjKh9+/Y0ffp0un//Pk9ux44d5OLiQmKxmIyNjalr1660adMmXrmV+8PatWupVatWJBQKqW3bthQXF8e1XUUq24aI6Oeff6YWLVqQrq6uVjtt3ryZANDYsWNrbb+KVNWHKoMaws3m5ubSxIkTqW3btmRoaEhSqZScnJxo8+bN3D1nzpwhf39/atasGQmFQjI3Nydvb286deqURlnaws1W1lH9u8jMzOTSnjx5QhMnTiRTU1OSSCQ0cOBAunbtGgGg+fPn19outQ3LyGAwGO8KtX2uCYjYzjXGh4WHhwdyc3Nr9POviI+PDy5evMj8rT8QgoODkZSUxHub9D6yfft2DBw4EIcPH+bCOzP4nDt3Dp06dcKGDRu4QzFroqioCFKpFEqlkkWIYjAY7wW1fa6xPRYMRg08ePAAu3fvfqVQnAzGP5Gff/4ZLVq0QPfu3d+2Kv8Inj59qpG2dOlS6Ojo8IJCMBgMBkM7bI8Fg1EFmZmZSE9Px5o1a6Cnp8c7UO9NUlpaWuNeFKlUWm1Uog+Bp0+f1ni2g6mpqdYzUD40fvvtN1y4cAG7d+/GsmXLNPYPKJVKrYPsijRu3Ph1qvhWWLhwIU6fPo1PPvkEDRo0QGpqKlJTUzF27FiNc2AYDAaDoQmbWDAYVfD7778jJCQEzZo1w7p1697aQOro0aP45JNPqpWJi4tDcHDwm1HoH0piYqLWE9krkpaWBg8Pjzej0D8Yf39/SCQSjBo1SuOkaeDFBuyqNpSreR+9aF1cXLB//358//33ePz4MZo1a4bIyEh8++23b1s1BoPBeCdgeywYjH84BQUFOH36dLUy9vb2sLS0fEMa/TN58OABLl++XK2MQqF45bMaPgSuXLmC+/fvVytT3dk0HzpsjwWDwXjfqO1zjU0sGAwGg8GoR9jEgsFgvG+wzdsMBoPBYDAYDAbjjcEmFow3yqFDhyAQCJCUlPS2VXmneZN2DA4ORvPmzV97Oe8C8fHxEAgEyMrKetuq1Al1fzl06NDbVuWN8K62E4PBYLzrsIkFg/GWKC4uRmRk5Acz2HsV3rSt5s2bh23btr2RsirzIfeLyMhICAQCrZ+YmJi3rR6D8Y+g+YzdvA+D8U+CRYViMN4SxcXFiIqKAgAWqagG3rSt5s2bhyFDhmDgwIG89JEjR8LPzw9CofC1lc36BbBq1SpIJBJempOT01vShsFgMBi1hU0sGO8UxcXFMDAweNtqMD5QdHV1oaur+7bVeO8ZMmQIGjVq9LbVYDAYDEYdYa5QjHrl3r17CA0NhYWFBYRCIezt7fHLL79oyKlUKsydOxfW1tYQiUTo2bMnbty4wZPx8PCAg4MDTp8+DTc3NxgYGOCbb74BAGzfvh1eXl6wsrKCUCiEXC7H999/j/Ly8irzcHFxgVgshq2tLc+t4vHjxzA0NMQXX3yhoefdu3ehq6uL6OhoLq2wsBBffvklmjdvDqFQCGtrawQGBiI3NxfAiwPtwsPDoVAoIJVKYWhoCFdXV6SlpXF5ZGVlQSaTAQCioqI4d4/IyMg62bs2djxy5AiGDh2KZs2aQSgUomnTpvjyyy+1HoC2bds2ODg4QCQSwcHBAVu3bq2TPhXZsmULFAoFxGIxGjVqhBEjRuDevXs8GQ8PD62r8hX3ddRkq+DgYEgkEmRkZMDT0xOGhoawsrLC7NmzNc5a+OGHH+Di4gIzMzOIxWIoFAqNfSoCgQBPnjzBunXruLLUZ4RU5bufmpoKV1dXGBoawsjICF5eXhqhb9V63rt3DwMHDoREIoFMJsPUqVO5flsf/eLu3bsYOHAgDA0NYW5uji+//BIlJSUacrXpF3FxcRAIBDh79qzG/fPmzYOuri7XptevX8fgwYPRuHFjiEQiWFtbw8/Pr8ZDC+vChQsXEBwcjBYtWkAkEqFx48YIDQ1FXl5ejfeeOnUKnp6eaNSoEfccCA0N5cmoVCosXboU9vb2EIlEsLCwQFhYGAoKCuqtDgwGg/E+w95YMOqNhw8fwtnZGQKBAJMmTYJMJkNqaipGjRqFoqIiTJkyhZOdP38+dHR0MHXqVCiVSixcuBDDhw/HiRMneHnm5eWhX79+8PPzw4gRI2BhYQHgxQBPIpHgq6++gkQiwcGDBxEeHo6ioiIsWrSIl0dBQQH69+8PX19f+Pv7Y/PmzRg/fjz09fURGhoKiUQCHx8fJCYmYsmSJbwV6U2bNoGIMHz4cAAvJiGurq74888/ERoais6dOyM3Nxc7duzA3bt30ahRIxQVFWHNmjXw9/fHmDFj8OjRI6xduxaenp74448/4OjoCJlMhlWrVmH8+PHw8fHBoEGDAAAdOnSok81rY8ctW7aguLgY48ePh5mZGf744w8sX74cd+/exZYtWzi5ffv2YfDgwbCzs0N0dDTy8vIQEhICa2vrOumkbp+QkBB89NFHiI6OxsOHD7Fs2TKkp6fj7NmzMDExqXVetbFVeXk5+vbtC2dnZyxcuBB79uxBREQEysrKMHv2bE5u2bJlGDBgAIYPH47S0lL89ttvGDp0KHbt2gUvLy8AwPr16zF69Gh07doVY8eOBQDI5fIq9Vu/fj2CgoLg6emJBQsWoLi4GKtWrUL37t1x9uxZ3sb38vJyeHp6wsnJCT/88AMOHDiAxYsXQy6XY/z48a/cL54+fYqePXvi9u3bmDx5MqysrLB+/XocPHhQQ7Y2/WLIkCGYOHEiEhIS0KlTJ979CQkJ8PDwQJMmTVBaWgpPT0+UlJTg888/R+PGjXHv3j3s2rULhYWFkEqltdJfTeWT5nV1ddGwYUPs378fGRkZCAkJQePGjXH58mXExsbi8uXLOH78uMYJ4mqys7PRp08fyGQyzJgxAyYmJsjKykJKSgpPLiwsjOu7kydPRmZmJlasWIGzZ88iPT0denp6WvMvKSnhTd6KiorqVF8Gg8F4byAGo54YNWoUWVpaUm5uLi/dz8+PpFIpFRcXU1paGgGgdu3aUUlJCSezbNkyAkAXL17k0tzd3QkAxcTEaJRVXFyskRYWFkYGBgb07NkzjTwWL17MpZWUlJCjoyOZm5tTaWkpERHt3buXAFBqaiovzw4dOpC7uzv3PTw8nABQSkqKRvkqlYqIiMrKynh1IyIqKCggCwsLCg0N5dJycnIIAEVERGjkVRN1saM2W0VHR5NAIKBbt25xaY6OjmRpaUmFhYVc2r59+wgA2djY1Fq30tJSMjc3JwcHB3r69CmXvmvXLgJA4eHhXJq7uzvPvmqCgoJ4ZVZnq6CgIAJAn3/+OZemUqnIy8uL9PX1KScnh0uvbIvS0lJycHCgHj168NINDQ0pKChIo6y4uDgCQJmZmURE9OjRIzIxMaExY8bw5P7++2+SSqW8dLWes2fP5sl26tSJFApFrepaE0uXLiUAtHnzZi7tyZMn1LJlSwJAaWlpXHpt+4W/vz9ZWVlReXk5l3bmzBkCQHFxcUREdPbsWQJAW7ZsqbPOFYmIiCAAGh91X9Cm86ZNmwgAHT58mEur3E5bt24lAHTy5Mkqyz5y5AgBoISEBF76nj17tKbXRm+lUlmH2jMYtcPm6128D4PxJlAqlbV6rjFXKEa9QERITk7Gp59+CiJCbm4u9/H09IRSqcSZM2c4+ZCQEOjr63PfXV1dAQAZGRm8fIVCIUJCQjTKE4vF3P8fPXqE3NxcuLq6ori4GFevXuXJNmjQAGFhYdx3fX19hIWFITs7mzvRulevXrCyskJCQgInd+nSJVy4cAEjRozg0pKTk9GxY0f4+Pho6KReLdXV1eXqplKpkJ+fj7KyMnTp0oVng/qgNnasaKsnT54gNzcXLi4uICLOxeXBgwc4d+4cgoKCeKvLvXv3hp2dXZ10OnXqFLKzszFhwgSIRCIu3cvLC23btsXu3a8nismkSZO4/6vfmpWWluLAgQNcekVbFBQUQKlUwtXV9aXbZf/+/SgsLIS/vz+vz+vq6sLJyYnn/qZm3LhxvO+urq4a/f5l+fe//w1LS0sMGTKESzMwMODevFSkNv0CAAIDA3H//n1eXRISEiAWizF48GAA4PrM3r17UVxc/Mr1SE5Oxv79+7mP+ndZUednz54hNzcXzs7OAFBtG6rfkO3atQvPnz/XKrNlyxZIpVL07t2b15YKhQISiURrW6qZOXMmlEol97lz505dq8xgMBjvBcwVilEv5OTkoLCwELGxsYiNjdUqk52djYYNGwIAmjVrxrumTq/sy9ykSRPewFnN5cuX8d133+HgwYMabgeVfbqtrKxgaGjIS2vdujWAFz7tzs7O0NHRwfDhw7Fq1Spug3hCQgJEIhGGDh3K3Xfz5k1uMFUd69atw+LFi3H16lXeQMbW1rbGe+tCbex4+/ZthIeHY8eOHRr2Vdvq1q1bAIBWrVpplNGmTZs6DbzVebVp00bjWtu2bfHf//631nnVFh0dHbRo0YKXVrGN1ezatQtz5szBuXPneK4rVbnQ1MT169cBAD169NB6vfLppCKRiNtDoaZhw4b15sN/69YttGzZUqM+2tqiNv0CeDG5tLS0REJCAnr27AmVSoVNmzbhs88+g5GREYAX/fqrr77CkiVLkJCQAFdXVwwYMAAjRoyosxsUALi5uWndvJ2fn4+oqCj89ttvyM7OrlLnyri7u2Pw4MGIiorCjz/+CA8PDwwcOBABAQFchK/r169DqVTC3Nxcax6Vy6uIUCh8rZHCGAwG412BTSwY9YJKpQIAjBgxAkFBQVplOnTogCtXrgBAlZF1qNJm24orlGoKCwvh7u4OY2NjzJ49G3K5HCKRCGfOnMHXX3/N6VJXAgMDsWjRImzbtg3+/v7YuHEjvL296zww2rBhA4KDgzFw4EBMmzYN5ubm3AbwmzdvvpRuVVGTHcvLy9G7d2/k5+fj66+/Rtu2bWFoaIh79+4hODj4pW1VXwgEAo02B6CxCb8+OHLkCAYMGAA3NzesXLkSlpaW0NPTQ1xcHDZu3PhSeartt379ejRu3FjjeoMG/EfsPyWiVF36ha6uLgICAvDzzz9j5cqVSE9Px/3793lv8gBg8eLFCA4Oxvbt27Fv3z5MnjwZ0dHROH78+Evt09GGr68vjh49imnTpsHR0RESiQQqlQp9+/atti+rD5M8fvw4du7cib179yI0NBSLFy/G8ePHuXzMzc15by0rUnlCyGAwGAxN2MSCUS/IZDIYGRmhvLwcvXr1qlJOPbF4FQ4dOoS8vDykpKTAzc2NS8/MzNQqf//+fTx58oT31uKvv/4CAN7GWgcHB3Tq1AkJCQmwtrbG7du3sXz5cl5ecrkcly5dqla/pKQktGjRAikpKbyV44iICJ7cy66S14WLFy/ir7/+wrp16xAYGMil79+/nydnY2MD4H8r8BW5du1ancpU53Xt2jWNlfxr165x14EXq/Xa3IDUbz3U1GQrlUqFjIwM7i0FoNnGycnJEIlE2Lt3L291OS4uTiO/2raNelO3ubl5tf2+LrxKv7CxscGlS5dARLx8KrdhbfuFmsDAQCxevBg7d+5EamoqZDIZPD09NeTat2+P9u3b47vvvsPRo0fRrVs3xMTEYM6cOYXrpSIAAQAASURBVC9dJzUFBQX4z3/+g6ioKISHh3Pp2vpsVTg7O8PZ2Rlz587Fxo0bMXz4cPz2228YPXo05HI5Dhw4gG7dumld0GAwGAxGzbA9Fox6QVdXF4MHD0ZycrLWgXdOTk69lgXw326UlpZi5cqVWuXLysqwevVqnuzq1ashk8mgUCh4siNHjsS+ffuwdOlSmJmZoV+/frzrgwcPxvnz57WGYVXro02/EydO4NixYzx59XkchYWF1db3VdCmCxFh2bJlPDlLS0s4Ojpi3bp1PJeS/fv313ky2KVLF5ibmyMmJobnbpSamoo///yTi74EvBiYX716ldc/zp8/j/T0dF6etbHVihUreHVcsWIF9PT00LNnTwAvbCEQCHhvQ7KysrSesG1oaFirdvH09ISxsTHmzZun1Xf/Zfr9q/SL/v374/79+7wQusXFxRruibXtF2o6dOiADh06YM2aNUhOToafnx/vbUxRURHKysp497Rv3x46OjpaQ92+DNp0BoClS5fWeG9BQYHGfY6OjgDA6efr64vy8nJ8//33GveXlZW91t8pg1EXsuZ78T4Mxj8J9saCUW/Mnz8faWlpcHJywpgxY2BnZ4f8/HycOXMGBw4c0Agh+bK4uLigYcOGCAoKwuTJkyEQCLB+/XqtLjXAiz0WCxYsQFZWFlq3bo3ExEScO3cOsbGxGuEjAwICMH36dGzduhXjx4/XuD5t2jQkJSVh6NChCA0NhUKhQH5+Pnbs2IGYmBh07NgR3t7eSElJgY+PD7y8vJCZmYmYmBjY2dnh8ePHXF5isRh2dnZITExE69atYWpqCgcHBzg4ONSLnYAXexrkcjmmTp2Ke/fuwdjYGMnJyVp9+qOjo+Hl5YXu3bsjNDQU+fn5WL58Oezt7Xl614Senh4WLFiAkJAQuLu7w9/fnws327x5c3z55ZecbGhoKJYsWQJPT0+MGjUK2dnZiImJgb29PW/vTE22EolE2LNnD4KCguDk5ITU1FTs3r0b33zzDefC4uXlhSVLlqBv374ICAhAdnY2/u///g8tW7bEhQsXeHVQKBQ4cOAAlixZAisrK9ja2mo9+dnY2BirVq3CyJEj0blzZ/j5+UEmk+H27dvYvXs3unXrxpvw1IZX6RdjxozBihUrEBgYiNOnT8PS0hLr16/XOFSyLv1CTWBgIKZOnQoAGm5QBw8exKRJkzB06FC0bt0aZWVlWL9+PbfgUB8YGxvDzc0NCxcuxPPnz9GkSRPs27evyjeVFVm3bh1WrlwJHx8fyOVyPHr0CD///DOMjY3Rv39/AC/2YYSFhSE6Ohrnzp1Dnz59oKenh+vXr2PLli1YtmwZb1M8g8FgMLTwOkJSMT5cHj58SBMnTqSmTZuSnp4eNW7cmHr27EmxsbFE9L8wqZXDUmZmZvLCVxK9CEVqb2+vtZz09HRydnYmsVhMVlZWNH36dC5kbMWQmuo8Tp06RR9//DGJRCKysbGhFStWVFmH/v37EwA6evSo1ut5eXk0adIkatKkCenr65O1tTUFBQVxYXZVKhXNmzePbGxsSCgUUqdOnWjXrl0aIVSJiI4ePUoKhYL09fXrFGK0Lna8cuUK9erViyQSCTVq1IjGjBlD58+f15AjIkpOTqZ27dqRUCgkOzs7SklJ0ap3bUhMTKROnTqRUCgkU1NTGj58ON29e1dDbsOGDdSiRQvS19cnR0dH2rt3b51sFRQURIaGhnTz5k3q06cPGRgYkIWFBUVERPBCpBIRrV27llq1akVCoZDatm1LcXFxXKjQily9epXc3NxILBYTAC70bOUwpmrS0tLI09OTpFIpiUQiksvlFBwcTKdOneJk1HpWRlv5L9sviIhu3bpFAwYMIAMDA2rUqBF98cUXXMjUir+NuvQLIqIHDx6Qrq4utW7dWuNaRkYGhYaGklwuJ5FIRKampvTJJ5/QgQMHaq030f9sUTFEcEXu3r1LPj4+ZGJiQlKplIYOHUr379/XsFHldjpz5gz5+/tTs2bNSCgUkrm5OXl7e/PaR01sbCwpFAoSi8VkZGRE7du3p+nTp9P9+/drXY/ahmVkMBiMd4XaPtcERFUs8zIY7wEeHh7Izc2tcV9ERXx8fHDx4kWNE6wZ/0yCg4ORlJRUp7cqjLqTm5sLS0tLhIeHY9asWW9bnX80RUVFkEqlUCqVGpHBGAwG412kts81tseCwajAgwcPsHv3bowcOfJtq8Jg/KOIj49HeXk5+20wGAwGo0rYHgsGAy8iSqWnp2PNmjXQ09PjHaj3JiktLa1xL4pUKn1rUWvy8/NRWlpa5XVdXV0WlvM18Db7xcGDB3HlyhXMnTsXAwcO5EVSqy1KpRJPnz6tVkZbuF4Gg8FgvFuwiQWDAeD3339HSEgImjVrhnXr1r21Qc7Ro0fxySefVCsTFxeH4ODgN6NQJQYNGoTff/+9yus2Nja8A+kY9cPb7BezZ8/mQsdWDr9cW7744gusW7euWhnmlctgMBjvPmyPBYPxD6KgoACnT5+uVsbe3h6WlpZvSCM+p0+frjZykFgsRrdu3d6gRh8G//R+URNXrlzB/fv3q5Wpr3NA/gmwPRYMBuN9o7bPNTaxYDAYDAajHmETCwaD8b7xXmzePnToEAQCAe+wJ8bbw8PDAx4eHm9bjTdO5XpnZWVBIBAgPj7+ren0uoiMjHwjJ4L/U/gn17d58+ZvzeWNwWAwGIyX4R89sWD8j+LiYkRGRuLQoUNvWxUGo854eHhoHSQXFRVh7ty56NKlC6RSKYRCIWxsbDBs2DDs3r37zSsKYN68eVpP42bUnuDgYEgkkretRr1RVf9lMN40zWfs1vgwGP8k2Obtd4Ti4mJERUUBwFt7a7Bv3763Uu4/DRsbGzx9+lTjVO73ge+++w4zZsx4I2XduHEDnp6euHXrFnx8fBAYGAiJRII7d+7g3//+N7y9vfHrr7++1vCm2uo7b948DBkyBAMHDnxt5daGa9euQUeHrf0wGAwG493hvZ5YFBcXw8DA4G2r8c6jtqO+vv7bVoWDiPDs2bO3EnZVIBBAJBK98XLfBA0aNECDBq//sVBWVgYfHx88fPgQv//+u8aG74iICOzbtw/l5eWvVY83Vd/aUrFfC4XCt6IDe24yGAwG42V5a8th9+7dQ2hoKCwsLCAUCmFvb49ffvlFq6xKpcLcuXNhbW0NkUiEnj17apyK7OHhAQcHB5w+fRpubm4wMDDAN998AwDYvn07vLy8YGVlBaFQCLlcju+//15j0FIxDxcXF4jFYtja2iImJoaTefz4MQwNDfHFF19o6Hn37l3o6uoiOjqaSyssLMSXX36J5s2bQygUwtraGoGBgcjNzQXwIj59eHg4FAoFpFIpDA0N4erqirS0NC6PrKws7myAqKgoCAQCCAQCREZG1srW6r0qiYmJ+Oabb9C4cWMYGhpiwIABuHPnTq3tWHmvgTrfzZs3IyoqCk2aNIGRkRGGDBkCpVKJkpISTJkyBebm5pBIJAgJCUFJSQmvvLi4OPTo0QPm5uYQCoWws7PDqlWrNOrQvHlzeHt7Y+/evejSpQvEYjFWr14Nd3d3dOzYUWu927RpA09Pz1rZSE1sbCzkcjnEYjG6du2KI0eOaMho22Nx4cIFBAcHo0WLFhCJRGjcuDFCQ0ORl5encf+hQ4fQpUsXiEQiyOVyrF69Wquvv0AgwKRJk7Bt2zY4ODhwv5M9e/Zo5Hn27Fn069cPxsbGkEgk6NmzJ44fP86Tef78OaKiotCqVSuIRCKYmZmhe/fu2L9/PyejTY/9+/eje/fuMDExgUQiQZs2bbg+8bJs2bIFly5dwqxZs6qMItWnTx/069ePl1ZYWIgpU6agadOmEAqFaNmyJRYsWACVSsXJqNvnhx9+4NpTKBTio48+wsmTJ3n5Va6vQCDAkydPsG7dOu53VtEFpjZ2rmrfRnx8PAQCAS8cb1X9Wn2tYtnq+9PT0/HVV19BJpPB0NAQPj4+yMnJ4ZX1Ms+8ir/3oKAgNGrUCM+fP9faLm3atNFIr4lTp07B09MTjRo14p6toaGhPJnffvsNCoUCRkZGMDY2Rvv27bFs2TLuel1sCwCpqalwdXWFoaEhjIyM4OXlhcuXL/Nk/v77b4SEhMDa2hpCoRCWlpb47LPPWNhkBoPBeAneylLdw4cP4ezszA2cZDIZUlNTMWrUKBQVFWHKlCk8+fnz50NHRwdTp06FUqnEwoULMXz4cJw4cYInl5eXh379+sHPzw8jRoyAhYUFgBd/dCQSCb766itIJBIcPHgQ4eHhKCoqwqJFi3h5FBQUoH///vD19YW/vz82b96M8ePHQ19fH6GhoZBIJPDx8UFiYiKWLFkCXV1d7t5NmzaBiDB8+HAALyYhrq6u+PPPPxEaGorOnTsjNzcXO3bswN27d9GoUSMUFRVhzZo18Pf3x5gxY/Do0SOsXbsWnp6e+OOPP+Do6AiZTIZVq1Zh/Pjx8PHxwaBBgwAAHTp0qJPd586dC4FAgK+//hrZ2dlYunQpevXqhXPnzvFW/quyY1VER0dDLBZjxowZuHHjBpYvXw49PT3o6OigoKAAkZGROH78OOLj42Fra4vw8HDu3lWrVsHe3h4DBgxAgwYNsHPnTkyYMAEqlQoTJ07klXPt2jX4+/sjLCwMY8aMQZs2bSCRSDBmzBhcunQJDg4OnOzJkyfx119/4bvvvqu1fdauXYuwsDC4uLhgypQpyMjIwIABA2BqaoqmTZtWe+/+/fuRkZGBkJAQNG7cGJcvX0ZsbCwuX76M48ePc4Ohs2fPom/fvrC0tERUVBTKy8sxe/bsKg+V++9//4uUlBRMmDABRkZG+OmnnzB48GDcvn0bZmZmAIDLly/D1dUVxsbGmD59OvT09LB69Wp4eHjg999/h5OTE4AXg7Lo6GiMHj0aXbt2RVFREU6dOoUzZ86gd+/eWsu/fPkyvL290aFDB8yePRtCoRA3btxAenp6re2qjZ07dwIARowYUet7iouL4e7ujnv37iEsLAzNmjXD0aNHMXPmTDx48ABLly7lyW/cuBGPHj1CWFgYBAIBFi5ciEGDBiEjI6NKN7b169dz9hk7diwAQC6XA6i9neuKtn5dHZ9//jkaNmyIiIgIZGVlYenSpZg0aRISExM5mbo887T93g0NDfHrr79i79698Pb25mT//vtvHDx4EBEREXWqY3Z2Nvr06QOZTIYZM2bAxMQEWVlZSElJ4WT2798Pf39/9OzZEwsWLAAA/Pnnn0hPT9e6kFMT69evR1BQEDw9PbFgwQIUFxdj1apV6N69O86ePcsd9Dd48GBcvnwZn3/+OZo3b47s7Gzs378ft2/frvVhgCUlJbxFk6Kiojrry2AwGO8F9BYYNWoUWVpaUm5uLi/dz8+PpFIpFRcXExFRWloaAaB27dpRSUkJJ7ds2TICQBcvXuTS3N3dCQDFxMRolKfOryJhYWFkYGBAz54908hj8eLFXFpJSQk5OjqSubk5lZaWEhHR3r17CQClpqby8uzQoQO5u7tz38PDwwkApaSkaJSvUqmIiKisrIxXNyKigoICsrCwoNDQUC4tJyeHAFBERIRGXjWhtmOTJk2oqKiIS9+8eTMBoGXLlmnYQJsd3d3defVT5+vg4MDZhojI39+fBAIB9evXj3f/xx9/TDY2Nrw0bW3j6elJLVq04KXZ2NgQANqzZw8vvbCwkEQiEX399de89MmTJ5OhoSE9fvxYI39tlJaWkrm5OTk6OvLaIzY2lgDw6p2ZmUkAKC4urtp6bNq0iQDQ4cOHubRPP/2UDAwM6N69e1za9evXqUGDBlT55wiA9PX16caNG1za+fPnCQAtX76cSxs4cCDp6+vTzZs3ubT79++TkZERubm5cWkdO3YkLy+vau0QERHB0+PHH38kAJSTk1PtfXWlU6dOZGJiopH++PFjysnJ4T5KpZK79v3335OhoSH99ddfvHtmzJhBurq6dPv2bSL6X/uYmZlRfn4+J7d9+3YCQDt37uTSKteXiMjQ0JCCgoI0dKutnbXlSUQUFxdHACgzM5NLq6pfq69V1EN9f69evbjnBxHRl19+Sbq6ulRYWMil1fWZV/n3Xl5eTtbW1jRs2DBe+pIlS0ggEFBGRoZG/hUJCgoiQ0ND7vvWrVsJAJ08ebLKe7744gsyNjamsrKyKmVqa9tHjx6RiYkJjRkzhif3999/k1Qq5dILCgoIAC1atKja+tSEWq/Kn4r9l8GoD2y+3qXxYTDeBEqlslbPtTfuCkVESE5OxqeffgoiQm5uLvfx9PSEUqnEmTNnePeEhITw/PtdXV0BABkZGTw5oVCIkJAQjTIrrsY/evQIubm5cHV1RXFxMa5evcqTbdCgAcLCwrjv+vr6CAsLQ3Z2NndAVa9evWBlZYWEhARO7tKlS7hw4QJvBTY5ORkdO3aEj4+Phk7qFWxdXV2ubiqVCvn5+SgrK0OXLl007PCqBAYGwsjIiPs+ZMgQWFpa4t///jdPrio7VpdvxRVgJycnEJGGm4OTkxPu3LmDsrIyLq1i2yiVSuTm5sLd3R0ZGRlQKpW8+21tbTVcm6RSKT777DPubREAlJeXIzExEQMHDoShoWGt6nDq1ClkZ2dj3LhxvL4WHBwMqVRa4/0V6/Hs2TPk5ubC2dkZALh2LC8vx4EDBzBw4EBYWVlx8i1bttRw+VHTq1cvbsUcePGWytjYmOv75eXl2LdvHwYOHIgWLVpwcpaWlggICMB///tfbvXUxMQEly9fxvXr12usjxoTExMAL1xrKrobvSpFRUVaowZ9++23kMlk3CcgIIC7tmXLFri6uqJhw4a850avXr1QXl6Ow4cP8/IaNmwYGjZsyH2v6rlRG+pi57qirV9Xx9ixY3nuQK6urigvL8etW7e4tLo887T93nV0dDB8+HDs2LEDjx494tITEhLg4uICW1vbWusL/K8f7dq1S6t7lVrmyZMnPNe8l2X//v0oLCyEv78/r6/o6urCycmJczUVi8XQ19fHoUOHqj34sSZmzpwJpVLJfSq7mDIYDMaHwhufWOTk5KCwsBCxsbG8AYRMJuP+uGVnZ/PuadasGe+7erBQ+Q9BkyZNtG4wvnz5Mnx8fCCVSmFsbAyZTMZNACoPXq2srDQGo61btwYAzudW/Ud327ZtKC4uBvDiD65IJMLQoUO5+27evMlzz6mKdevWoUOHDpzfu0wmw+7duzV0e1VatWrF+y4QCNCyZUsNX+Kq7FgVldtHPRCv7D4klUqhUql49UpPT0evXr1gaGgIExMTyGQyzn9f28RCG4GBgbh9+za3H+LAgQN4+PBhnaIJqQdllW2kp6fHG0hWRX5+Pr744gtYWFhALBZDJpNx+qrrkZ2djadPn6Jly5Ya92tLAzRtC7zo/+q+n5OTg+LiYq3uM+3atYNKpeIGObNnz0ZhYSFat26N9u3bY9q0abhw4UK19Ro2bBi6deuG0aNHw8LCAn5+fti8efMrTzKMjIzw+PFjjfQJEyZg//792L9/v4YL3vXr17Fnzx6N54b6xOaXfW7UhrrYua7UdZBem3rV5ZlX1e89MDAQT58+xdatWwG8cNk6ffr0S0Xpcnd3x+DBgxEVFYVGjRrhs88+Q1xcHM99aMKECWjdujX69esHa2trhIaGat1PVBvUk+cePXpo9Jd9+/ZxfUUoFGLBggVITU2FhYUF3NzcsHDhQvz99991Kk8oFMLY2Jj3YTAYjA+RN77HQj0gGTFiBIKCgrTKVN47UHEfQ0Wo0qHh2iIEFRYWwt3dHcbGxpg9ezbkcjlEIhHOnDmDr7/++qUHSIGBgVi0aBG2bdsGf39/bNy4Ed7e3rVa3a7Ihg0bEBwcjIEDB2LatGkwNzfnNoDfvHnzpXR7Veoaaamq9qmp3W7evImePXuibdu2WLJkCZo2bQp9fX38+9//xo8//qjRNlXp5enpCQsLC2zYsAFubm7YsGEDGjduzA043wS+vr44evQopk2bBkdHR0gkEqhUKvTt2/eVBuG17fu1wc3NDTdv3sT27duxb98+rFmzBj/++CNiYmIwevRorfeIxWIcPnwYaWlp2L17N/bs2YPExET06NED+/btq1K/mmjbti3OnTuHe/fuoUmTJlx669atuYl85chbKpUKvXv3xvTp07Xmqb5PTX3ari5UdeBeVRGu6uv3pq5XXZ95VZVvZ2cHhUKBDRs2IDAwEBs2bIC+vj58fX3rpC8A7qDT48ePY+fOndi7dy9CQ0OxePFiHD9+HBKJBObm5jh37hz27t2L1NRUpKamIi4uDoGBgVi3bh2XjzYq21Zdx/Xr16Nx48Ya8hUjgU2ZMgWffvoptm3bhr1792LWrFmIjo7GwYMH0alTpzrXlcFgMD5k3vjEQiaTwcjICOXl5W9k4Hfo0CHk5eUhJSUFbm5uXHpmZqZW+fv37+PJkye8txZ//fUXAPA28jk4OKBTp05ISEiAtbU1bt++jeXLl/PyksvluHTpUrX6JSUloUWLFkhJSeH90ay8ObI+Tgeu7AJDRLhx40adN4HXFzt37kRJSQl27NjBW4WtGBGrNujq6iIgIADx8fFYsGABtm3bhjFjxtRp0GtjYwPghY169OjBpT9//hyZmZlVRp4CXqwU/+c//0FUVBRvY3ple5ubm0MkEmlENAOgNa02yGQyGBgY4Nq1axrXrl69Ch0dHd6bI1NTU4SEhCAkJASPHz+Gm5sbIiMjq5xYAC/e0PXs2RM9e/bEkiVLMG/ePHz77bdIS0t76d+wt7c3fvvtNyQkJFQ5UaiMXC7H48ePX/tzQ9tvrS52Vr9BKCws5FyAAPBclV4ndX3mVUdgYCC++uorPHjwABs3boSXlxfPvayuODs7w9nZGXPnzsXGjRsxfPhw/Pbbb1z/09fXx6effopPP/0UKpUKEyZMwOrVqzFr1iy0bNmy1rZVuw+am5vXqr/I5XL861//wr/+9S9cv34djo6OWLx4MTZs2PDSdWUwGIwPkTfuCqWrq4vBgwcjOTlZ66C7ctjE+igP4K9SlpaWYuXKlVrly8rKuHCPatnVq1dDJpNBoVDwZEeOHIl9+/Zh6dKlMDMz0/CTHzx4MM6fP8+5ElRErY82/U6cOIFjx47x5NVx5QsLC6utb3X8+uuvPH/ppKQkPHjwoEr//teNtrorlUrExcXVOa+RI0eioKAAYWFhePz4cZ2iDQFAly5dIJPJEBMTg9LSUi49Pj6+RptrqwcAjShFurq66NWrF7Zt24b79+9z6Tdu3EBqamqd9K2YZ58+fbB9+3aeS9vDhw+xceNGdO/enXPLqBz6ViKRoGXLlhohgCuSn5+vkebo6AgA1d5XE76+vrCzs8P333+vEa5VTWV7+vr64tixY9i7d6+GbGFhIW/vzqtgaGio0eZ1sbN6UFtxz4c6hO2boK7PvOrw9/eHQCDAF198gYyMjDr/rtQUFBRotGflflS5f+ro6HCLHmqZ2trW09MTxsbGmDdvntY9Heq/M8XFxXj27Bnvmlwuh5GR0Sv1bwaDwfhQeSvhZufPn4+0tDQ4OTlhzJgxsLOzQ35+Ps6cOYMDBw5oHcy8LC4uLmjYsCGCgoIwefJkCAQCrF+/vkp3CCsrKyxYsABZWVlo3bo1EhMTce7cOcTGxmqEqAwICMD06dOxdetWjB8/XuP6tGnTkJSUhKFDhyI0NBQKhQL5+fnYsWMHYmJi0LFjR3h7eyMlJQU+Pj7w8vJCZmYmYmJiYGdnx/NBF4vFsLOzQ2JiIlq3bg1TU1M4ODjUag+HGlNTU3Tv3h0hISF4+PAhli5dipYtW2LMmDF1sGj90adPH26FUj0h+Pnnn2Fubo4HDx7UKa9OnTrBwcEBW7ZsQbt27dC5c+c63a+np4c5c+YgLCzs/7F351FNXG8fwL8BSQIBAmJYo2wVFRCx2LqyKLSUxVakWhBksxZRq2jFpbYsWjdQq9Uq8kOBulWLoNalLhVqi61WqYqoVRHcaoWwBDUKBe77hyfzMiRgWMTtfs7JOebOM3eeuRPi3MzcOxgxYgQ++ugjFBcXIy0t7aljLHR1dZl7s//77z+YmZnh8OHDSn8hjo+Px+HDhzF06FBERUWhvr4ea9euhb29Pc6ePduqnOW++uor5lkTkydPRpcuXbBhwwbU1NQgMTGRibO1tYWbmxucnJzQtWtXnD59GpmZmZg6dWqzdS9YsADHjx+Hj48PzM3NUVpainXr1kEsFmPYsGFtyhd40t7Z2dnw9PTEsGHDMHr0aOZ5A3fu3MHevXtx8+ZN+Pj4MOvExMRg79698PX1RVhYGJycnPDw4UMUFBQgMzMTJSUl6NatW5tzknNycsLRo0excuVKmJqawtLSEgMHDlS5nd9991306NEDEyZMQExMDNTV1bFp0yaIRCLcvHmz3fk9TWu/81oiEonw3nvv4YcffoCenh7reLRGRkYG1q1bBz8/P1hbW+P+/fv43//+B11dXXh7ewMAPv74Y1RUVGDEiBEQi8W4ceMG1qxZA0dHR/Tp0weA6m2rq6uL9evXY/z48XjzzTcREBDAxOzfvx9Dhw7F2rVrceXKFbi7uzMd3S5duiA7Oxv37t1DQEBAm/aVop6lkqVt+xukqE7zDGakUsm9e/fIlClTSPfu3YmGhgYxNjYm7u7uJCUlhYmRT2f6ww8/sNZVNt2nq6srsbOzU7qtvLw8MmjQIKKpqUlMTU3J7NmzmSljc3JyFOo4ffo0GTx4MOHz+cTc3JysXbu22f3w9vYmAMiJEyeULi8vLydTp04lZmZmhMvlErFYTEJDQ5mpdhsaGsjixYuJubk54fF4pH///mTfvn0kNDRUYWrWEydOECcnJ8Llcls19ay8Hbdv307mzZtHDA0NiaamJvHx8SE3btxgxbbUjs1NN9v0+Minfmw6taR8SsbGU5fu3buXODg4ED6fTywsLMiyZcvIpk2blE7L+bSpUhMTEwkAsnjx4hbjWrJu3TpiaWlJeDweGTBgADl+/LjCfiv7/N2+fZv4+fkRPT09IhQKyZgxY8g///yj9Dj9/PPPpH///oTL5RJra2uSmppKPvvsM8Ln81lxAMiUKVMUcmw6DSkhhOTn5xNPT0+ira1NtLS0yPDhwxU+k1999RV5++23iZ6eHtHU1CS9e/cmixYtYk0V3HQ6z59//pl88MEHxNTUlHC5XGJqakoCAwMVpnxtq6qqKrJgwQLSv39/oq2tTbhcLunevTv58MMPWdPCyt2/f5/MmzePvPHGG4TL5ZJu3bqRIUOGkOXLlzP7IT8+yqYQbXo8lE1fevnyZeLi4kI0NTUJAFZbq9LOhBBy5swZMnDgQMLlckmPHj3IypUrm51utrnPdXPTzTb9u5L/HTb+Lmvtd15L5NNSf/LJJy3GNdZ0utn8/HwSGBhIevToQXg8HjE0NCS+vr7k9OnTTExmZiZ59913iaGhIdNukZGR5O7du6y6VW1bedt4enoSoVBI+Hw+sba2JmFhYcx2JRIJmTJlCunduzcRCAREKBSSgQMHkp07d6q8r8qoOi0jRVHUy0LV7zUOIc94JONLxM3NDRKJ5KnjIhrz8/NDQUFBm++R7wy5ubkYPnw4fvjhB3z44YfPO51nZvXq1ZgxYwZKSkqUzqb0Ihs1alSrp4KlqM6wZ88ejBo1CsePH2em7KVaVl1dDaFQCKlUSmeIoijqlaDq91qnj7F4ldy9exf79+9v0/SLVMcihGDjxo1wdXV94TsVjx49Yr2/evUqDhw4ADc3t+eTEEW14H//+x+srKzadesbRVEU9Xp4LmMsXnbFxcXIy8tDamoqNDQ0WA/U60y1tbVPHY/S2ulvXzYPHz7E3r17kZOTg4KCAuzZs0chpqKigjUguyl1dXWIRKJnmSaLlZUVwsLCYGVlhRs3bmD9+vXgcrkqz470IikrK2t2GlXgySw/Xbt27cSMqI7y/fff4/z589i/fz9Wr17dITPTURRFUa822rFog19++QXh4eHo0aMHMjIylM6T3hlOnDiB4cOHtxiTlpbGmib3VVNWVoZx48ZBT08Pn3/+Od5//32FmNGjR+OXX35ptg5zc3OFhwQ+S++99x62b9+Of//9FzweD4MHD8bixYsVHs73MnjrrbdanEbV1dUVubm5nZcQ1WECAwOhra2NCRMmYPLkyc87HYqiKOolQMdYvMQqKytx5syZFmPs7OxgYmLSSRm9mM6cOdPi05Y1NTUxdOjQTszo1ZGXl6dwa1dj+vr6CtM0U9Srjo6xoCjqVaPq9xrtWFAURVFUB6IdC4qiXjV08DZFURRFURRFUZ2GdiwoimLk5uaCw+EgMzPzeadCtZObmxtrprGSkhJwOBykp6c/k+3JPzuqjKlpmhtFURT1aqCDtymKopSQyWRITEykJ8HPWXp6OsLDw58a19mTMFBUZ7OYu19pOX0aN/UioR0LiqIoJWQyGRISEgDglehYmJub49GjR9DQ0Hgm9bu4uODRo0fgcrkdXu/mzZtZZR9//DHefvttfPLJJ0yZtrZ2h26XoiiKaj3asaAoqsPIZDJoaWk97zQoJTgcDvh8/jOrX01N7ZnUb2VlBSsrK1bZpEmTYGVlheDg4GbXq6urQ0NDQ4d3dCiKoqjm0TEWFPUauXPnDiIiImBkZAQejwc7Ozts2rRJIa6hoQGLFi2CWCwGn8+Hu7s7rl27xopxc3ODvb09zpw5AxcXF2hpaeHzzz8HAOzZswc+Pj4wNTUFj8eDtbU1Fi5cqPAwvcZ1DBkyBJqamrC0tERycjIT8+DBAwgEAkyfPl0hz9u3b0NdXR1LlixhyqqqqjBjxgxYWFiAx+NBLBYjJCQEEokEwJMHS8bGxsLJyQlCoRACgQDOzs7Iyclh6igpKWEempiQkAAOhwMOh4P4+HiV2lk+3mDnzp1ISEiAmZkZdHR08OGHH0IqlaKmpgbR0dEwNDSEtrY2wsPDUVNTo1DPli1b4OTkBE1NTXTt2hUBAQG4deuWQlxKSgqsra2hqamJt99+G7/++qtCTHNjLC5fvoyxY8dCJBJBU1MTvXr1wvz585nlN27cwOTJk9GrVy9oamrCwMAAY8aMUbjtqLkxFqrk1l7yfVu+fDlWrVoFa2tr8Hg8XLx4Eenp6eBwOCrne/LkSbz33nsQCoXQ0tKCq6sr8vLyOjxniqKoVxG9YkFRr4l79+5h0KBB4HA4mDp1KkQiEQ4ePIgJEyaguroa0dHRTOzSpUuhpqaGWbNmQSqVIjExEUFBQTh58iSrzvLycnh5eSEgIADBwcEwMjIC8OS+eG1tbcycORPa2to4duwYYmNjUV1djaSkJFYdlZWV8Pb2xtixYxEYGIidO3ciKioKXC4XERER0NbWhp+fH3bs2IGVK1dCXV2dWXf79u0ghCAoKAjAk06Is7MzLl26hIiICLz55puQSCTYu3cvbt++jW7duqG6uhqpqakIDAzExIkTcf/+fWzcuBGenp44deoUHB0dIRKJsH79ekRFRcHPzw+jR48GADg4OLSqzZcsWQJNTU3MnTsX165dw5o1a6ChoQE1NTVUVlYiPj4ef/zxB9LT02FpaYnY2Fhm3UWLFuHLL7/E2LFj8fHHH6OsrAxr1qyBi4sL/vrrL+jp6QEANm7ciMjISAwZMgTR0dG4fv063n//fXTt2hXdu3dvMb/z58/D2dkZGhoa+OSTT2BhYYGioiL8+OOPWLRoEQDgzz//xIkTJxAQEACxWIySkhKsX78ebm5uuHjxYotXqNqTW1ukpaXh8ePH+OSTT8Dj8Vr91Pdjx47By8sLTk5OiIuLg5qaGtLS0jBixAj8+uuvePvtt5WuV1NTw+oYVldXt2s/KIqiXlqEoqjXwoQJE4iJiQmRSCSs8oCAACIUColMJiM5OTkEAOnTpw+pqalhYlavXk0AkIKCAqbM1dWVACDJyckK25LJZAplkZGRREtLizx+/FihjhUrVjBlNTU1xNHRkRgaGpLa2lpCCCGHDh0iAMjBgwdZdTo4OBBXV1fmfWxsLAFAsrKyFLbf0NBACCGkrq6OtW+EEFJZWUmMjIxIREQEU1ZWVkYAkLi4OIW6nkbejvb29sw+EEJIYGAg4XA4xMvLixU/ePBgYm5uzrwvKSkh6urqZNGiRay4goIC0qVLF6a8traWGBoaEkdHR9Y+paSkEACstikuLiYASFpaGlPm4uJCdHR0yI0bN1jbkbcVIcqP5e+//04AkO+++05hn3NyclqdW2sJBAISGhqqsG+6urqktLSUFZuWlkYAkOLiYlZ503wbGhpIz549iaenp8L+W1paknfeeafZfOLi4ggAhZdUKm3zPlJUU+Zz9il9UVRnkEqlKn2v0VuhKOo1QAjBrl27MHLkSBBCIJFImJenpyekUiny8/OZ+PDwcNa96c7OzgCA69evs+rl8XhKZ+zR1NRk/n3//n1IJBI4OztDJpPh8uXLrNguXbogMjKSec/lchEZGYnS0lLmyfIeHh4wNTXF1q1bmbgLFy7g/PnzrPvsd+3ahX79+sHPz08hJw6HAwBQV1dn9q2hoQEVFRWoq6vDgAEDWG3QEUJCQliDpQcOHAhCCCIiIlhxAwcOxK1bt1BXVwcAyMrKQkNDA8aOHcs6VsbGxujZsydz29bp06dRWlqKSZMmsY5XWFgYhEJhi7mVlZXh+PHjiIiIQI8ePVjL5G0FsI/lf//9h/LycrzxxhvQ09Nrsb3ak1tb+fv7M7ewtdbZs2dx9epVjBs3DuXl5UybP3z4EO7u7jh+/DgaGhqUrjtv3jxIpVLmpex2NYqiqNcBvRWKol4DZWVlqKqqQkpKClJSUpTGlJaWQl9fHwAUTjTl5ZWVlaxyMzMzpYNjCwsL8cUXX+DYsWMKt4VIpVLWe1NTUwgEAlaZjY0NgCf3zg8aNAhqamoICgrC+vXrmQHiW7duBZ/Px5gxY5j1ioqK4O/v32w7yGVkZGDFihW4fPky/vvvP6bc0tLyqeu2RtN2lJ9QN70NSCgUoqGhAVKpFAYGBrh69SoIIejZs6fSeuWdlRs3bgCAQpyGhobCgOem5J1Ee3v7FuMePXqEJUuWIC0tDXfu3AEhhFnW9Fg21p7c2qo9x+/q1asAgNDQ0GZjpFIp87fQGI/HA4/Ha/O2KYqiXhW0Y0FRrwH5L63BwcHNnjg5ODjg4sWLAMAax9BY45NKgP1rtlxVVRVcXV2hq6uLBQsWwNraGnw+H/n5+ZgzZ06zv/o+TUhICJKSkrB7924EBgZi27Zt8PX1bfWv31u2bEFYWBhGjRqFmJgYGBoaMgPAi4qK2pRbc5prx6e1b0NDAzgcDg4ePKg0tjOnVv3000+RlpaG6OhoDB48GEKhEBwOBwEBAW0+ls+Kss9j46svjTWdSEC+L0lJSXB0dFS6Dp3SlqIoqmW0Y0FRrwGRSAQdHR3U19fDw8Oj2Th5x6I9cnNzUV5ejqysLLi4uDDlxcXFSuP/+ecfPHz4kHXV4sqVKwAACwsLpsze3h79+/fH1q1bIRaLcfPmTaxZs4ZVl7W1NS5cuNBifpmZmbCyskJWVhbrpDMuLo4V19wJaWewtrYGIQSWlpbM1RtlzM3NATz5tX3EiBFM+X///Yfi4mL069ev2XXlVw1Uaa/Q0FCsWLGCKXv8+DGqqqpaXK89uXUk+RWGpvnKr6jIWVtbAwB0dXVb/BuhKIqimkfHWFDUa0BdXR3+/v7YtWuX0hPJsrKyDt0WwL66UVtbi3Xr1imNr6urw4YNG1ixGzZsgEgkgpOTEyt2/PjxOHz4MFatWgUDAwN4eXmxlvv7++PcuXPIzs5W2I48H2X5nTx5Er///jsrXj7b0dNOoJ+F0aNHQ11dHQkJCQpXiQghKC8vBwAMGDAAIpEIycnJqK2tZWLS09OfmrdIJIKLiws2bdqEmzdvKmxDTl1dXSGHNWvWKPzi31R7cutI8g7D8ePHmbL6+nqFWwKdnJxgbW2N5cuX48GDBwr1dOTfCEW1RclSH6UvinqR0CsWFPWaWLp0KXJycjBw4EBMnDgRtra2qKioQH5+Po4ePYqKiooO2c6QIUOgr6+P0NBQTJs2DRwOB5s3b1Y4OZUzNTXFsmXLUFJSAhsbG+zYsQNnz55FSkqKwlOix40bh9mzZyM7OxtRUVEKy2NiYpCZmYkxY8YgIiICTk5OqKiowN69e5GcnIx+/frB19cXWVlZ8PPzg4+PD4qLi5GcnAxbW1vWCaWmpiZsbW2xY8cO2NjYoGvXrrC3t3/qmISOYG1tja+++grz5s1DSUkJRo0aBR0dHRQXFyM7OxuffPIJZs2aBQ0NDXz11VeIjIzEiBEj8NFHH6G4uBhpaWkqjWP45ptvMGzYMLz55pv45JNPYGlpiZKSEuzfvx9nz54FAPj6+mLz5s0QCoWwtbXF77//jqNHj8LAwKDFutubW0exs7PDoEGDMG/ePFRUVKBr1674/vvvmYHycmpqakhNTYWXlxfs7OwQHh4OMzMz3LlzBzk5OdDV1cWPP/7YaXlTFEW9lJ7RrFQURb2A7t27R6ZMmUK6d+9ONDQ0iLGxMXF3dycpKSmEkP+fgvOHH35gradsqlJXV1diZ2endDt5eXlk0KBBRFNTk5iampLZs2czU8bKp/dsXMfp06fJ4MGDCZ/PJ+bm5mTt2rXN7oO3tzcBQE6cOKF0eXl5OZk6dSoxMzMjXC6XiMViEhoaykyz29DQQBYvXkzMzc0Jj8cj/fv3J/v27SOhoaGsKV8JIeTEiRPEycmJcLncVk0921w7yqc+/fPPP1nl8ulKy8rKWOW7du0iw4YNIwKBgAgEAtK7d28yZcoU8vfff7Pi1q1bRywtLQmPxyMDBgwgx48fJ66urk+dbpYQQi5cuED8/PyInp4e4fP5pFevXuTLL79klldWVpLw8HDSrVs3oq2tTTw9Pcnly5eJubk5a8rXptO3tia31mpuutmkpCSl8UVFRcTDw4PweDxiZGREPv/8c3LkyBGl+f71119k9OjRxMDAgPB4PGJubk7Gjh1Lfv75Z5XzU3VaRoqiqJeFqt9rHEKa+RmRoijqGXNzc4NEInnqff6N+fn5oaCgQOFJ4BT1oqiuroZQKIRUKoWuru7zToeiKKrdVP1eo2MsKIp6ady9exf79+/H+PHjn3cqFEVRFEU1QcdYUBT1wisuLkZeXh5SU1OhoaHBeqBeZ6qtrX3qWBShUKh02lNKubKyshYHgnO5XHTt2rUTM6IoiqLainYsKIp64f3yyy8IDw9Hjx49kJGRAWNj4+eSx4kTJzB8+PAWY9LS0hAWFtY5Cb0C3nrrLYWpXxtzdXVFbm5u5yVEURRFtRkdY0FRFKWiyspKnDlzpsUYOzs7mJiYdFJGL7+8vDw8evSo2eX6+voK0w6/6OgYC4qiXjWqfq/RjgVFURRFdSDasaAo6lVDB29TFEVRFEVRFNVpaMeCalZubi44HA4yMzOfdyqvtZKSEnA4HKSnp3dYnfJj29H3rj+LXKnWs7CwUGmcR3p6OjgcDkpKSp55Tk9z9epVvPvuuxAKheBwONi9e/fzTokRHx8PDofzvNOgXnMWc/crfVHUi4R2LChKBTKZDPHx8XQQKfXak3dG5K8uXbrAzMwMYWFhuHPnTpvrDQ0NRUFBARYtWoTNmzdjwIABHZg1RVEU1RnorFAUpQKZTIaEhAQATx7q9rJzcXHBo0ePwOVyO7Rec3NzPHr0CBoaGh1aL9U6f//9N9TUnu3vRgsWLIClpSUeP36MP/74A+np6fjtt99w4cIF8Pn8VtX16NEj/P7775g/fz6mTp36jDKmKIqinjXasaCeGZlMBi0treedBqWEmppaq0/+VMHhcJ5JvS+rx48fg8vlPvOT/KZ4PN4z34aXlxdzVeHjjz9Gt27dsGzZMuzduxdjx45tVV1lZWUAAD09vQ7Lr6W2f/jwIQQCQYdti6IoinqC3gr1Grtz5w4iIiJgZGQEHo8HOzs7bNq0SSGuoaEBixYtglgsBp/Ph7u7O65du8aKcXNzg729Pc6cOQMXFxdoaWnh888/BwDs2bMHPj4+MDU1BY/Hg7W1NRYuXKjwUKzGdQwZMgSampqwtLREcnIyE/PgwQMIBAJMnz5dIc/bt29DXV0dS5YsYcqqqqowY8YMWFhYgMfjQSwWIyQkBBKJBMCTB57FxsbCyckJQqEQAoEAzs7OyMnJYeooKSmBSCQCACQkJDC3gMTHx6vUzqpso3G+YWFhEAqF0NPTQ2hoKKqqqhTiwsLCoK2tjZs3b8LX1xfa2towMzPDt99+CwAoKCjAiBEjIBAIYG5ujm3btrHWVzbG4urVq/D394exsTH4fD7EYjECAgIglUqZmCNHjmDYsGHQ09ODtrY2evXqxRxneVspG2Nx7NgxODs7QyAQQE9PDx988AEuXbrEipHfx37t2jWEhYVBT08PQqEQ4eHhkMlkKrW13L///ovw8HCIxWLweDyYmJjggw8+UBhLsG7dOtjZ2YHH48HU1BRTpkxRaO/mxiu4ubmxrl7J2/T777/HF198ATMzM2hpaaG6uhoAcPLkSXh7e0NfXx8CgQAODg5YvXo1q87Lly/jww8/RNeuXcHn8zFgwADs3bu3VfveXM6FhYUYMWIENDU1IRaL8dVXX6GhoaHVdTfH2dkZAFBUVMQqf9o+xcfHw9zcHAAQExMDDocDCwsLZrkq31Mttb38b6WoqAje3t7Q0dFBUFAQAODXX3/FmDFj0KNHD/B4PHTv3h0zZsxocfpbiqIoqnn0isVr6t69exg0aBA4HA6mTp0KkUiEgwcPYsKECaiurkZ0dDQTu3TpUqipqWHWrFmQSqVITExEUFAQTp48yaqzvLwcXl5eCAgIQHBwMIyMjAA8uSdbW1sbM2fOhLa2No4dO4bY2FhUV1cjKSmJVUdlZSW8vb0xduxYBAYGYufOnYiKigKXy0VERAS0tbXh5+eHHTt2YOXKlVBXV2fW3b59OwghzEnDgwcP4OzsjEuXLiEiIgJvvvkmJBIJ9u7di9u3b6Nbt26orq5GamoqAgMDMXHiRNy/fx8bN26Ep6cnTp06BUdHR4hEIqxfvx5RUVHw8/PD6NGjAQAODg4qtbUq2wAAQgg++OAD/Pbbb5g0aRL69OmD7OxshIaGKq23vr4eXl5ecHFxQWJiIrZu3YqpU6dCIBBg/vz5CAoKwujRo5GcnIyQkBAMHjwYlpaWSuuqra2Fp6cnampq8Omnn8LY2Bh37tzBvn37UFVVBaFQiMLCQvj6+sLBwQELFiwAj8fDtWvXkJeX1+L+Hz16FF5eXrCyskJ8fDwePXqENWvWYOjQocjPz2edRALA2LFjYWlpiSVLliA/Px+pqakwNDTEsmXLVGpvAPD390dhYSE+/fRTWFhYoLS0FEeOHMHNmzeZ7cXHxyMhIQEeHh6IiorC33//jfXr1+PPP/9EXl5em2/nWrhwIbhcLmbNmoWamhpwuVwcOXIEvr6+MDExwfTp02FsbIxLly5h3759TCe5sLAQQ4cOhZmZGebOnQuBQICdO3di1KhR2LVrF/z8/NqUD/CkozV8+HDU1dUxdaekpHToE8LlnTZ9fX2mTJV9Gj16NPT09DBjxgwEBgbC29sb2traAFr3PQUob3sAqKurg6enJ4YNG4bly5czV1J/+OEHyGQyREVFwcDAAKdOncKaNWtw+/Zt/PDDDyrve01NDWpqapj38s4kRVHUa4dQr6UJEyYQExMTIpFIWOUBAQFEKBQSmUxGcnJyCADSp08fUlNTw8SsXr2aACAFBQVMmaurKwFAkpOTFbYlk8kUyiIjI4mWlhZ5/PixQh0rVqxgympqaoijoyMxNDQktbW1hBBCDh06RACQgwcPsup0cHAgrq6uzPvY2FgCgGRlZSlsv6GhgRBCSF1dHWvfCCGksrKSGBkZkYiICKasrKyMACBxcXEKdT2NqtvYvXs3AUASExNZ6zo7OxMAJC0tjSkPDQ0lAMjixYtZdWpqahIOh0O+//57pvzy5csKucuPbU5ODiGEkL/++osAID/88EOz+/H1118TAKSsrKzZmOLiYoVc5cevvLycKTt37hxRU1MjISEhTFlcXBwBwGoTQgjx8/MjBgYGzW6zqcrKSgKAJCUlNRtTWlpKuFwueffdd0l9fT1TvnbtWgKAbNq0iSkzNzcnoaGhCnW4urqyPm/yNrWysmJ95uvq6oilpSUxNzcnlZWVrDrkn0NCCHF3dyd9+/Zl/U00NDSQIUOGkJ49e6qy683mHB0dTQCQkydPMmWlpaVEKBQSAKS4uFjlutPS0ggAcvToUVJWVkZu3bpFMjMziUgkIjwej9y6davV+yT/3DQ9Zqp8TxHSfNsT8v9/K3PnzlXYF2XfTUuWLCEcDofcuHGDKZN/NpsjX970JZVKm12HolrLfM4+pS+K6gxSqVSl7zV6K9RriBCCXbt2YeTIkSCEQCKRMC9PT09IpVLk5+cz8eHh4axBvvJbHq5fv86ql8fjITw8XGF7jX8VvX//PiQSCZydnSGTyXD58mVWbJcuXRAZGcm853K5iIyMRGlpKfPEYw8PD5iammLr1q1M3IULF3D+/HkEBwczZbt27UK/fv2U/tIrnzpSXV2d2beGhgZUVFSgrq4OAwYMYLVBe6i6jQMHDqBLly6Iiopirfvpp582W/fHH3/M/FtPTw+9evWCQCBg3ePeq1cv6OnpKRyvxoRCIQDg0KFDzd52JL//fc+ePSrfQnP37l2cPXsWYWFh6Nq1K1Pu4OCAd955BwcOHFBYZ9KkSaz3zs7OKC8vV/lXYE1NTXC5XOTm5qKyslJpzNGjR1FbW4vo6GjWPfgTJ06Erq4u9u9v+xSOoaGhrM/8X3/9heLiYkRHRyuMIZB/DisqKnDs2DGMHTuW+RuRSCQoLy+Hp6cnrl692q4Zlw4cOIBBgwbh7bffZspEIhFzda8tPDw8IBKJ0L17d3z44YcQCATYu3cvxGJxh+xTa7+nAMW2b6zx35Vc49iHDx9CIpFgyJAhIITgr7/+Urkt5s2bB6lUyrxu3bql8roURVGvEtqxeA2VlZWhqqoKKSkpEIlErJe8Y1BaWsrE9+jRg7W+/FaHpidtZmZmSmcZKiwshJ+fH4RCIXR1dSESiZgOQOP79wHA1NRUYVCljY0NgP+/1UJNTQ1BQUHYvXs3cxK8detW8Pl8jBkzhlmvqKgI9vb2T22PjIwMODg4gM/nw8DAACKRCPv371fIrT1U2caNGzdgYmLC3AYi16tXL6V18vl8ZuyHnFAohFgsVphzXygUNnuSDQCWlpaYOXMmUlNT0a1bN3h6euLbb79l5ffRRx9h6NCh+Pjjj2FkZISAgADs3LmzxU7GjRs3mt2HPn36QCKR4OHDh6xyVT9vzeHxeFi2bBkOHjwIIyMj5laxf//996l5cblcWFlZMcvbountZvIxBy19Fq9duwZCCL788kuFv8m4uDgA7L/J1rpx4wZ69uypUN7cZ0sV3377LY4cOYLMzEx4e3tDIpGwBo23d59a+z0FKLa9XJcuXZgOT2M3b95kOr3a2toQiURwdXUFoPjd1BIejwddXV3Wi6Io6nVEx1i8huQngsHBwc3ev+/g4ICLFy8CAGscQ2OEENZ7Zb8UVlVVwdXVFbq6uliwYAGsra3B5/ORn5+POXPmtHnwaEhICJKSkrB7924EBgZi27Zt8PX1ZX55V9WWLVsQFhaGUaNGISYmBoaGhswA8KaDUNvqWW2jueOi6vFqasWKFQgLC8OePXtw+PBhTJs2DUuWLMEff/wBsVgMTU1NHD9+HDk5Odi/fz9++ukn7NixAyNGjMDhw4eb3W5rtTX/xqKjozFy5Ejs3r0bhw4dwpdffoklS5bg2LFj6N+/f6vyae7BaPX19Upzbcu4BfnfwaxZs+Dp6ak05o033mh1vc/S22+/zcwKNWrUKAwbNgzjxo3D33//DW1t7Xbvk6rfU4011/Y8Hk9hdqj6+nq88847qKiowJw5c9C7d28IBALcuXMHYWFhHTqwnaIo6nVBOxavIZFIBB0dHdTX18PDw6PZOHnHoj1yc3NRXl6OrKwsuLi4MOXFxcVK4//55x+FqSCvXLkCAKxBvvb29ujfvz+2bt0KsViMmzdvYs2aNay6rK2tceHChRbzy8zMhJWVFbKyslgnkPJfVOXa89RdVbdhbm6On3/+GQ8ePGBdtfj777/bvO3W6tu3L/r27YsvvvgCJ06cwNChQ5GcnIyvvvoKwJOrRe7u7nB3d8fKlSuxePFizJ8/Hzk5OUo/S/LZfpTtw+XLl9GtW7dnNu2ntbU1PvvsM3z22We4evUqHB0dsWLFCmzZsoWVl5WVFbNObW0tiouLWfuir6+vdGauGzdusNZtKQ/gye16zf29yevR0NBo8W+yrczNzXH16lWF8o76bMk7ysOHD8fatWsxd+7cdu+Tqt9TbVVQUIArV64gIyMDISEhTPmRI0c6fFsURVGvC3or1GtIXV0d/v7+2LVrl9ITb/mc8h21LYD9a3NtbS3WrVunNL6urg4bNmxgxW7YsAEikQhOTk6s2PHjx+Pw4cNYtWoVDAwM4OXlxVru7++Pc+fOITs7W2E78nyU5Xfy5En8/vvvrHj5LDLKTjCfRtVteHt7o66uDuvXr2fK6uvrFTpMz0J1dTXq6upYZX379oWamhoz201FRYXCevIZrRrPiNOYiYkJHB0dkZGRwWq7Cxcu4PDhw/D29u6YHWhEJpPh8ePHrDJra2vo6OgweXp4eIDL5eKbb75hHZeNGzdCKpXCx8eHte4ff/yB2tpapmzfvn0q30f/5ptvwtLSEqtWrVL4/Mi3bWhoCDc3N2zYsAF3795VqKO9f5Pe3t74448/cOrUKVadjccptZebmxvefvttrFq1Co8fP273Pj3r7yllf5eEEIUpgCnqRVGy1Efpi6JeJPSKxWtq6dKlyMnJwcCBAzFx4kTY2tqioqIC+fn5OHr0qNKTyLYYMmQI9PX1ERoaimnTpoHD4WDz5s3N3tZiamqKZcuWoaSkBDY2NtixYwfOnj2LlJQUhek/x40bh9mzZyM7OxtRUVEKy2NiYpCZmYkxY8YgIiICTk5OqKiowN69e5GcnIx+/frB19cXWVlZ8PPzg4+PD4qLi5GcnAxbW1s8ePCAqUtTUxO2trbYsWMHbGxs0LVrV9jb26s0hkPVbYwcORJDhw7F3LlzUVJSAltbW2RlZXXoWI/mHDt2DFOnTsWYMWNgY2ODuro6bN68mTm5A548afn48ePw8fGBubk5SktLsW7dOojFYgwbNqzZupOSkuDl5YXBgwdjwoQJzHSzQqFQ5WeBtMaVK1fg7u6OsWPHwtbWFl26dEF2djbu3buHgIAAAE9+DZ83bx4SEhLw3nvv4f3338fff/+NdevW4a233mJNAvDxxx8jMzMT7733HsaOHYuioiJs2bKFuRLxNGpqali/fj1GjhwJR0dHhIeHw8TEBJcvX0ZhYSEOHToE4MmYhWHDhqFv376YOHEirKyscO/ePfz++++4ffs2zp071+Y2mT17NjZv3oz33nsP06dPZ6abNTc3x/nz59tcb1MxMTEYM2YM0tPTMWnSpHbv07P8nurduzesra0xa9Ys3LlzB7q6uti1a5fKY3koiqIoJZ7FlFTUy+HevXtkypQppHv37kRDQ4MYGxsTd3d3kpKSQgj5/ykcm05BqmxKUVdXV2JnZ6d0O3l5eWTQoEFEU1OTmJqaktmzZzNTxsqnO21cx+nTp8ngwYMJn88n5ubmZO3atc3ug7e3NwFATpw4oXR5eXk5mTp1KjEzMyNcLpeIxWISGhrKTF/Z0NBAFi9eTMzNzQmPxyP9+/cn+/btI6GhocTc3JxV14kTJ4iTkxPhcrmtmnq2NdsoLy8n48ePJ7q6ukQoFJLx48czU8E2nW5WIBAobKu542Bubk58fHyY902nm71+/TqJiIgg1tbWhM/nk65du5Lhw4eTo0ePMuv8/PPP5IMPPiCmpqaEy+USU1NTEhgYSK5cucLEKPtsEELI0aNHydChQ4mmpibR1dUlI0eOJBcvXmTFyKfsbDqdrXx6U1WnRJVIJGTKlCmkd+/eRCAQEKFQSAYOHEh27typELt27VrSu3dvoqGhQYyMjEhUVJTClLCEELJixQpiZmZGeDweGTp0KDl9+nSz0802N2Xvb7/9Rt555x2io6NDBAIBcXBwIGvWrGHFFBUVkZCQEGJsbEw0NDSImZkZ8fX1JZmZmSrtu5yyKXLPnz9PXF1dCZ/PJ2ZmZmThwoVk48aNbZ5u9s8//1RYVl9fT6ytrYm1tTWpq6tTeZ+am26WkKd/TxHScts397dCCCEXL14kHh4eRFtbm3Tr1o1MnDiRnDt3TuEz/LTpZptSdVpGiqKol4Wq32scQloxIpKiniE3NzdIJJKnjotozM/PDwUFBQpPAqcoinpeqqurIRQKIZVK6QxRFEW9ElT9XqNjLKiX1t27d7F//36MHz/+eadCURRFURT12qNjLKiXTnFxMfLy8pCamgoNDQ3WA/U6U21t7VPv8RYKhW2afpRSTiqV4tGjRy3GGBsbd1I2na/xsziU0dTUbPWUy3IPHjxgjflRRiQSddi0whRFUdSrh3YsqJfOL7/8gvDwcPTo0QMZGRnP7UTyxIkTGD58eIsxaWlpCAsL65yEXgPTp09HRkZGizGv8t2dJiYmLS4PDQ1Fenp6m+pevnw5EhISWowpLi5mTftMURRFUY3RMRYU1UaVlZU4c+ZMizF2dnZPPRmkVHfx4kX8888/LcY8i2cevCiOHj3a4nJTU1PY2tq2qe7r16/j+vXrLcYMGzYMfD6/TfW/TugYC4qiXjWqfq/RjgVFURRFdSDasaAo6lVDB29TVCvl5uaCw+EgMzPzeadCvcA4HM4zef4GRVEURb3s6BgLiqIUyGQyJCYmws3NDW5ubs87HeoVFh8fj4SEBBgaGqK4uJh5yr2chYUF7O3tsW/fvueUIUU9fxZz9ze7jD59m3qR0CsWFEUpkMlkSEhIQG5u7vNOhXpNlJaWYv369c87DYqiKKodaMeCojqITCZ73ilQVIsePnz4vFNolqOjI5KSkp46nXB7NDQ04PHjx8+sfoqiqNcd7VhQr407d+4gIiICRkZG4PF4sLOzw6ZNmxTiGhoasGjRIojFYvD5fLi7uys82dvNzQ329vY4c+YMXFxcoKWlhc8//xwAsGfPHvj4+MDU1BQ8Hg/W1tZYuHAh6uvrm61jyJAh0NTUhKWlJZKTk5mYBw8eQCAQYPr06Qp53r59G+rq6liyZAlTVlVVhRkzZsDCwgI8Hg9isRghISGQSCQAnjx7IzY2Fk5OThAKhRAIBHB2dkZOTg5TR0lJCUQiEQAgISEBHA6nVeMK5GNVdu7ciYSEBJiZmUFHRwcffvghpFIpampqEB0dDUNDQ2hrayM8PBw1NTWsOtLS0jBixAgYGhqCx+PB1tZW4dfsY8eOQU1NDbGxsazybdu2gcPhtPrX7x9++AG2trbg8/mwt7dHdnY2wsLCnjq9anMx8fHx4HA4rcrh33//RXh4OMRiMXg8HkxMTPDBBx+gpKSEFXfw4EE4OztDIBBAR0cHPj4+KCwsVMhLW1sbRUVF8Pb2ho6ODoKCggA8ub1I2TTITW9964hjqarY2Fjcu3dPpeP28OFDfPbZZ+jevTt4PB569eqF5cuXK0w1zOFwMHXqVGzduhV2dnbg8Xj46aefkJ6eDg6Hg99++w3Tpk2DSCSCnp4eIiMjUVtbi6qqKoSEhEBfXx/6+vqYPXv2Kz2NMUVRVEehYyyo18K9e/cwaNAg5kRDJBLh4MGDmDBhAqqrqxEdHc3ELl26FGpqapg1axakUikSExMRFBSEkydPsuosLy+Hl5cXAgICEBwcDCMjIwBAeno6tLW1MXPmTGhra+PYsWOIjY1FdXU1kpKSWHVUVlbC29sbY8eORWBgIHbu3ImoqChwuVxERERAW1sbfn5+2LFjB1auXMl6ONn27dtBCGFOFh88eABnZ2dcunQJERERePPNNyGRSLB3717cvn0b3bp1Q3V1NVJTUxEYGIiJEyfi/v372LhxIzw9PXHq1Ck4OjpCJBJh/fr1iIqKgp+fH0aPHg0AcHBwaFWbL1myBJqampg7dy6uXbuGNWvWQENDA2pqaqisrER8fDz++OMPpKenw9LSktVBWL9+Pezs7PD++++jS5cu+PHHHzF58mQ0NDRgypQpAIARI0Zg8uTJWLJkCUaNGoU333wTd+/exaeffgoPDw9MmjRJ5Vz379+Pjz76CH379sWSJUtQWVmJCRMmwMzMrFX73F7+/v4oLCzEp59+CgsLC5SWluLIkSO4efMm03nZvHkzQkND4enpiWXLlkEmk2H9+vUYNmwY/vrrL1Ynp66uDp6enhg2bBiWL1+uMH5BVe05lqpydnbGiBEjkJiYiKioqGYfLEkIwfvvv4+cnBxMmDABjo6OOHToEGJiYnDnzh18/fXXrPhjx45h586dmDp1Krp16wYLCwucPXsWAPDpp5/C2NgYCQkJ+OOPP5CSkgI9PT2cOHECPXr0wOLFi3HgwAEkJSXB3t4eISEhSnOqqalhdaiqq6tbvf8URVGvBEJRr4EJEyYQExMTIpFIWOUBAQFEKBQSmUxGcnJyCADSp08fUlNTw8SsXr2aACAFBQVMmaurKwFAkpOTFbYlk8kUyiIjI4mWlhZ5/PixQh0rVqxgympqaoijoyMxNDQktbW1hBBCDh06RACQgwcPsup0cHAgrq6uzPvY2FgCgGRlZSlsv6GhgRBCSF1dHWvfCCGksrKSGBkZkYiICKasrKyMACBxcXEKdT2NvB3t7e2ZfSCEkMDAQMLhcIiXlxcrfvDgwcTc3JxVpqwNPT09iZWVFavs4cOH5I033iB2dnbk8ePHxMfHh+jq6pIbN260Kue+ffsSsVhM7t+/z5Tl5uYSAAq5NW2X0NBQhRhCCImLiyOt+YqtrKwkAEhSUlKzMffv3yd6enpk4sSJrPJ///2XCIVCVnloaCgBQObOnatQj7m5OQkNDVUod3V1ZX2mOuJYPo28ncrKysgvv/xCAJCVK1eycvXx8WHe7969mwAgX331FaueDz/8kHA4HHLt2jWmDABRU1MjhYWFrNi0tDQCgHh6ejJ/G/L8ORwOmTRpElNWV1dHxGIxq12a24emL6lU2qq2oKjmmM/Z1+yLojqDVCpV6XuN3gpFvfIIIdi1axdGjhwJQggkEgnz8vT0hFQqRX5+PhMfHh4OLpfLvHd2dgYAhYeH8Xg8hIeHK2yv8S+t9+/fh0QigbOzM2QyGS5fvsyK7dKlCyIjI5n3XC4XkZGRKC0tZR6+5+HhAVNTU2zdupWJu3DhAs6fP4/g4GCmbNeuXejXrx/8/PwUcpLfkqOurs7sW0NDAyoqKlBXV4cBAwaw2qAjhISEQENDg3k/cOBAEEIQERHBihs4cCBu3bqFuro6pqxxG0qlUkgkEri6uuL69euQSqXMMi0tLaSnp+PSpUtwcXHB/v378fXXX6NHjx4q5/nPP/+goKAAISEh0NbWZspdXV3Rt2/fVu1ze2hqaoLL5SI3NxeVlZVKY44cOYKqqioEBgayPsfq6uoYOHAg65Y2uaioqHbn1p5j2RouLi4YPnw4EhMTmx1rceDAAairq2PatGms8s8++wyEEBw8eJBV7urq2uxDAydMmMC6XU2+XxMmTGDK1NXVMWDAgBYfHjhv3jxIpVLmdevWrafuK0VR1KuIdiyoV15ZWRmqqqqQkpICkUjEesk7BqWlpUx805NSfX19AFA42TMzM2N1QOQKCwvh5+cHoVAIXV1diEQipgPQ+KQYePKkZIFAwCqzsbEBAOa+ejU1NQQFBWH37t3MAPGtW7eCz+djzJgxzHpFRUWwt7d/antkZGTAwcEBfD4fBgYGEIlE2L9/v0Ju7dW0HYVCIQCge/fuCuUNDQ2s7efl5cHDwwMCgQB6enoQiUTMGJameQ4dOhRRUVE4deoUPD09FU52n+bGjRsAgDfeeENhmbKyZ4XH42HZsmU4ePAgjIyM4OLigsTERPz7779MzNWrVwE8uQ2s6Wf58OHDrM8x8KTjKhaL251be45la8XHx+Pff/9ljTVq7MaNGzA1NYWOjg6rvE+fPszyxiwtLZvdVmv2q7nOHvDk2Onq6rJeFEVRryM6xoJ65TU0NAAAgoODERoaqjTGwcEBFy9eBADWOIbGSJPBm8ruAa+qqoKrqyt0dXWxYMECWFtbg8/nIz8/H3PmzGFyaa2QkBAkJSVh9+7dCAwMxLZt2+Dr68ucCKlqy5YtCAsLw6hRoxATEwNDQ0NmAHhRUVGbcmtOc+34tPYtKiqCu7s7evfujZUrV6J79+7gcrk4cOAAvv76a4U2rKmpYabFLSoqgkwma/NYgrZoboB208H6qoiOjsbIkSOxe/duHDp0CF9++SWWLFmCY8eOoX///sy+b968GcbGxgrrd+nC/krn8XhQU1P8/ailnJUdn7Yey7ZwcXGBm5sbEhMTWzVOpjnNjdUAWrdf7dkniqKo1wXtWFCvPJFIBB0dHdTX18PDw6PZOHnHoj1yc3NRXl6OrKwsuLi4MOXFxcVK4//55x88fPiQddXiypUrAMAahGtvb4/+/ftj69atEIvFuHnzJtasWcOqy9raGhcuXGgxv8zMTFhZWSErK4t1chkXF8eKa+1sRh3pxx9/RE1NDfbu3cv6RVnZbT7Ak9wvXbqE5cuXY86cOZg7dy6++eYblbdnbm4OAAozfzVX1pS+vj6qqqoUypv+cq4qa2trfPbZZ/jss89w9epVODo6YsWKFdiyZQusra0BAIaGhi1+ltuTs5WVVZvr7Sjx8fFwc3PDhg0bFJaZm5vj6NGjuH//Puuqhfw2Q/nxpCiKojofvRWKeuWpq6vD398fu3btUnriXVZW1qHbAti/btbW1mLdunVK4+vq6lgnT7W1tdiwYQNEIhGcnJxYsePHj8fhw4exatUqGBgYwMvLi7Xc398f586dQ3Z2tsJ25Pkoy+/kyZP4/fffWfHyX/yVnXw+a8pylEqlSEtLU4g9efIkli9fjujoaHz22WeIiYnB2rVr8csvv6i8PVNTU9jb2+O7777DgwcPmPJffvkFBQUFT13f2toaUqkU58+fZ8ru3r2r9Di0RCaTKTxjwdraGjo6OsyMQ56entDV1cXixYvx33//KdSh6mfZ2toaf/zxB2pra5myffv2vTBjA1xdXeHm5oZly5YptIm3tzfq6+uxdu1aVvnXX38NDoej8HdBUa+CkqU+zb4o6kVCr1hQr4WlS5ciJycHAwcOxMSJE2Fra4uKigrk5+fj6NGjqKio6JDtDBkyBPr6+ggNDcW0adPA4XCwefPmZm+jMDU1xbJly1BSUgIbGxvs2LEDZ8+eRUpKCmuwLACMGzcOs2fPRnZ2NqKiohSWx8TEIDMzE2PGjEFERAScnJxQUVGBvXv3Ijk5Gf369YOvry+ysrLg5+cHHx8fFBcXIzk5Gba2tqyTak1NTdja2mLHjh2wsbFB165dYW9vr9IYjvZ69913weVyMXLkSERGRuLBgwf43//+B0NDQ9y9e5eJe/z4MUJDQ9GzZ08sWrQIwJPnbvz4448IDw9HQUGBwviV5ixevBgffPABhg4divDwcFRWVmLt2rWwt7dntYsyAQEBmDNnDvz8/DBt2jRm+lcbG5tWDYi/cuUK3N3dMXbsWNja2qJLly7Izs7GvXv3EBAQAADQ1dXF+vXrMX78eLz55psICAiASCTCzZs3sX//fgwdOlThhFuZjz/+GJmZmXjvvfcwduxYFBUVsa6IvAji4uIwfPhwhfKRI0di+PDhmD9/PkpKStCvXz8cPnwYe/bsQXR09Au1DxRFUa8besWCei0YGRnh1KlTCA8PR1ZWFqZOnYrVq1ejoqICy5Yt67DtGBgYYN++fTAxMcEXX3yB5cuX45133kFiYqLSeH19fRw4cACnT59GTEwMbt26hbVr12LixIlK9+Hdd98F8OTqRVPa2tr49ddfERUVhQMHDmDatGlYt24devXqxQzgDQsLw+LFi3Hu3DlMmzYNhw4dwpYtWzBgwACF+lJTU2FmZoYZM2YgMDAQmZmZ7WkalfXq1QuZmZngcDiYNWsWkpOT8cknnyg8JPDzzz/HtWvXkJGRAT6fD+DJrFoZGRm4desWYmJiVN7myJEjsX37dtTW1mLu3LnIyspCeno6evXqxdTdHAMDA2RnZ0NLSwuzZ89GRkYGlixZgpEjR7Zqv7t3747AwEDk5uZi3rx5mDdvHqqrq7Fz5074+/szcePGjcPPP/8MMzMzJCUlYfr06fj+++/h6OiodJYyZTw9PbFixQpcuXIF0dHR+P3337Fv374OGejdUdzc3ODq6qpQrqamhr179yI6Ohr79u1DdHQ0Ll68iKSkJKxcufI5ZEpRFEXJcQgdkUZRz4WbmxskEslTx0U05ufnh4KCApXu/afaT/7AwCNHjjzvVKiXSHV1NYRCIaRSKZ0hiqKoV4Kq32v0igVFvSTu3r2L/fv3K71aQbXPf//9p/DshdzcXJw7dw5ubm7PJymKoiiKesnQMRYU9YIrLi5GXl4eUlNToaGhwXqgXmeqra196lgUoVDY4vSenU0qlTb7oDU5Y2Nj3LlzBx4eHggODoapqSkuX76M5ORkGBsbd8iUp6rm8Sp5HfeZoijqdUc7FhT1gvvll18QHh6OHj16ICMj47mdjJ04cULpYNrG0tLSEBYW1jkJqWD69OnIyMhoMYYQAn19fTg5OSE1NRVlZWUQCATw8fHB0qVLYWBg0Gl5vEpex32mKIp63dExFhRFqaSyshJnzpxpMcbOzg4mJiadlNHTXbx4Ef/880+LMe15HsTLlkdneh33WY6OsaAo6lWj6vca7VhQFEVRVAeiHQuKol41dPA2RVEURVEURVGdhnYsqGcuNzcXHA6n056DQClXUlICDoeD9PT0DqtTfmxzc3M7rE7g2eRKtZ6FhYVKY2bS09PB4XBQUlLyzHNqDofDwdSpU5/b9imqI1nM3a/yi6JeJLRjQVGdSCaTIT4+vsNPxCnqZVVYWIjg4GCYmZmBx+PB1NQUQUFBKCwsVIg9ceIE4uPjUVVV1fmJUhRFUU9FZ4WiqE4kk8mQkJAAAK/E8xFcXFzw6NEjcLncDq3X3Nwcjx49goaGRofWS7XO33//DTW1Z/f7U1ZWFgIDA9G1a1dMmDABlpaWKCkpwcaNG5GZmYnvv/8efn5+TPyJEyeQkJCAsLAw6OnpPbO8KIqiqLahHQvqhSeTyaClpfW806CUUFNTA5/P7/B6ORzOM6n3ZfX48WNwudxnepKvDI/He2Z1FxUVYfz48bCyssLx48chEomYZdOnT4ezszPGjx+P8+fPw8rK6pnl0RrP6zhQFEW9LOi3I9Vud+7cQUREBIyMjMDj8WBnZ4dNmzYpxDU0NGDRokUQi8Xg8/lwd3fHtWvXWDFubm6wt7fHmTNn4OLiAi0tLXz++ecAgD179sDHxwempqbg8XiwtrbGwoULUV9f32wdQ4YMgaamJiwtLZGcnMzEPHjwAAKBANOnT1fI8/bt21BXV8eSJUuYsqqqKsyYMQMWFhbg8XgQi8UICQmBRCIB8OThcbGxsXBycoJQKIRAIICzszNycnKYOkpKSpiTp4SEBHA4HHA4HMTHx6vUzqpso3G+YWFhEAqF0NPTQ2hoqNLbR8LCwqCtrY2bN2/C19cX2traMDMzw7fffgsAKCgowIgRIyAQCGBubo5t27ax1lc2xuLq1avw9/eHsbEx+Hw+xGIxAgICIJVKmZgjR45g2LBh0NPTg7a2Nnr16sUcZ3lbKRtjcezYMTg7O0MgEEBPTw8ffPABLl26xIqJj48Hh8PBtWvXmF+2hUIhwsPDIZPJVGpruX///Rfh4eEQi8Xg8XgwMTHBBx98oDCWYN26dbCzs2Nu5ZkyZYpCezc3XsHNzY119Urept9//z2++OILmJmZQUtLC9XV1QCAkydPwtvbG/r6+hAIBHBwcMDq1atZdV6+fBkffvghunbtCj6fjwEDBmDv3r2t2vfmci4sLMSIESOgqakJsViMr776Cg0NDa2uOykpCTKZDCkpKaxOBQB069YNGzZswMOHD5GYmAjgyXGNiYkBAFhaWjJ/P02Pxe7du2Fvb898F/30008K21blO+tpx4GiKIpSRK9YUO1y7949DBo0iBk4KRKJcPDgQUyYMAHV1dWIjo5mYpcuXQo1NTXMmjULUqkUiYmJCAoKwsmTJ1l1lpeXw8vLCwEBAQgODoaRkRGAJwNEtbW1MXPmTGhra+PYsWOIjY1FdXU1kpKSWHVUVlbC29sbY8eORWBgIHbu3ImoqChwuVxERERAW1sbfn5+2LFjB1auXAl1dXVm3e3bt4MQgqCgIABPOiHOzs64dOkSIiIi8Oabb0IikWDv3r24ffs2unXrhurqaqSmpiIwMBATJ07E/fv3sXHjRnh6euLUqVNwdHSESCTC+vXrERUVBT8/P4wePRoA4ODgoFJbq7IN4MlDxz744AP89ttvmDRpEvr06YPs7GyEhoYqrbe+vh5eXl5wcXFBYmIitm7diqlTp0IgEGD+/PkICgrC6NGjkZycjJCQEAwePBiWlpZK66qtrYWnpydqamrw6aefMk+13rdvH6qqqiAUClFYWAhfX184ODhgwYIF4PF4uHbtGvLy8lrc/6NHj8LLywtWVlaIj4/Ho0ePsGbNGgwdOhT5+fmwsLBgxY8dOxaWlpZYsmQJ8vPzkZqaCkNDQyxbtkyl9gYAf39/FBYW4tNPP4WFhQVKS0tx5MgR3Lx5k9lefHw8EhIS4OHhgaioKPz9999Yv349/vzzT+Tl5bX5dq6FCxeCy+Vi1qxZqKmpAZfLxZEjR+Dr6wsTExNMnz4dxsbGuHTpEvbt28d0kgsLCzF06FCYmZlh7ty5EAgE2LlzJ0aNGoVdu3axbi1qrX///RfDhw9HXV0dU3dKSkqbnrb+448/wsLCAs7OzkqXu7i4wMLCAvv3PxmcOnr0aFy5cgXbt2/H119/jW7dugEAq1Py22+/ISsrC5MnT4aOjg6++eYb+Pv74+bNm8yDDlvznQUoPw5N1dTUoKamhnlPOx8URb22CEW1w4QJE4iJiQmRSCSs8oCAACIUColMJiM5OTkEAOnTpw+pqalhYlavXk0AkIKCAqbM1dWVACDJyckK25LJZAplkZGRREtLizx+/FihjhUrVjBlNTU1xNHRkRgaGpLa2lpCCCGHDh0iAMjBgwdZdTo4OBBXV1fmfWxsLAFAsrKyFLbf0NBACCGkrq6OtW+EEFJZWUmMjIxIREQEU1ZWVkYAkLi4OIW6nkbVbezevZsAIImJiax1nZ2dCQCSlpbGlIeGhhIAZPHixaw6NTU1CYfDId9//z1TfvnyZYXc5cc2JyeHEELIX3/9RQCQH374odn9+PrrrwkAUlZW1mxMcXGxQq7y41deXs6UnTt3jqipqZGQkBCmLC4ujgBgtQkhhPj5+REDA4Nmt9lUZWUlAUCSkpKajSktLSVcLpe8++67pL6+nilfu3YtAUA2bdrElJmbm5PQ0FCFOlxdXVmfN3mbWllZsT7zdXV1xNLSkpibm5PKykpWHfLPISGEuLu7k759+7L+JhoaGsiQIUNIz549Vdn1ZnOOjo4mAMjJkyeZstLSUiIUCgkAUlxcrFK9VVVVBAD54IMPWox7//33CQBSXV1NCCEkKSmp2e0AIFwul1y7do0pO3fuHAFA1qxZw5Sp8p1FSPPHQRn5Z67pSyqVtrgeRTXHfM4+lV8U1RmkUqlK32v0ViiqzQgh2LVrF0aOHAlCCCQSCfPy9PSEVCpFfn4+Ex8eHs76tU/+S+X169dZ9fJ4PISHhytsr/Gvovfv34dEIoGzszNkMhkuX77Miu3SpQsiIyOZ91wuF5GRkSgtLWWeHu3h4QFTU1Ns3bqVibtw4QLOnz+P4OBgpmzXrl3o16+f0l96ORwOAEBdXZ3Zt4aGBlRUVKCurg4DBgxgtUF7qLqNAwcOoEuXLoiKimKt++mnnzZb98cff8z8W09PD7169YJAIMDYsWOZ8l69ekFPT0/heDUmFAoBAIcOHWr2tiP5oNs9e/aofAvN3bt3cfbsWYSFhaFr165MuYODA9555x0cOHBAYZ1Jkyax3js7O6O8vFzlX5M1NTXB5XKRm5uLyspKpTFHjx5FbW0toqOjWffdT5w4Ebq6usyv7W0RGhrK+sz/9ddfKC4uRnR0tMLAZfnnsKKiAseOHcPYsWOZvxGJRILy8nJ4enri6tWruHPnTptzOnDgAAYNGoS3336bKROJRMzVPVXdv38fAKCjo9NinHy5qsfMw8MD1tbWzHsHBwfo6uoyn9nWfmcBisdBmXnz5kEqlTKvW7duqZQvRVHUq4Z2LKg2KysrQ1VVFXOPdOOXvGNQWlrKxPfo0YO1vr6+PgAonLSZmZkpvd2gsLAQfn5+EAqF0NXVhUgkYjoAje/fBwBTU1MIBAJWmY2NDQAw92SrqakhKCgIu3fvZk6Ct27dCj6fjzFjxjDrFRUVwd7e/qntkZGRAQcHB/D5fBgYGEAkEmH//v0KubWHKtu4ceMGTExMoK2tzVq3V69eSuvk8/kK97gLhUKIxWLmhLVxeXMn2cCTe99nzpyJ1NRUdOvWDZ6envj2229Z+X300UcYOnQoPv74YxgZGSEgIAA7d+5ssZNx48aNZvehT58+kEgkePjwIatc1c9bc3g8HpYtW4aDBw/CyMiIuVXs33//fWpeXC4XVlZWzPK2aHq7WVFREQC0+Fm8du0aCCH48ssvFf4m4+LiALD/Jlvrxo0b6Nmzp0J5c5+t5sg7DPIORnNU7YDINT3mwJPjLj/mrf3OAhSPgzI8Hg+6urqsF0VR1OuIjrGg2kx+IhgcHNzs/fsODg64ePEiALDGMTRGCGG9V/brYFVVFVxdXaGrq4sFCxbA2toafD4f+fn5mDNnTpsGjwJASEgIkpKSsHv3bgQGBmLbtm3w9fVlfnlX1ZYtWxAWFoZRo0YhJiYGhoaGzABw+Qlhez2rbTR3XFQ9Xk2tWLECYWFh2LNnDw4fPoxp06ZhyZIl+OOPPyAWi6GpqYnjx48jJycH+/fvx08//YQdO3ZgxIgROHz4cLPbba225t9YdHQ0Ro4cid27d+PQoUP48ssvsWTJEhw7dgz9+/dvVT5NO2ly9fX1SnNty7gF+d/BrFmz4OnpqTTmjTfeaHW9HU0oFMLExATnz59vMe78+fMwMzNT+UT9acdc1e+sxtpyHCiKol5XtGNBtZlIJIKOjg7q6+vh4eHRbJy8Y9Eeubm5KC8vR1ZWFlxcXJjy4uJipfH//PMPHj58yLpqceXKFQBgDfK1t7dH//79sXXrVojFYty8eRNr1qxh1WVtbY0LFy60mF9mZiasrKyQlZXFOoGU/0os19zJpSpU3Ya5uTl+/vlnPHjwgHXV4u+//27ztlurb9++6Nu3L7744gucOHECQ4cORXJyMr766isAT64Wubu7w93dHStXrsTixYsxf/585OTkKP0smZubN7sPly9fRrdu3RSuUHUUa2trfPbZZ/jss89w9epVODo6YsWKFdiyZQsrr8ZTotbW1qK4uJi1L/r6+kpn5rpx44ZK06nKb/G5cOFCs39v8no0NDRa/JtsK3Nzc1y9elWhvC2fLV9fX/zvf//Db7/9hmHDhiks//XXX1FSUsK6pbE9fz+A6t9ZFEVRVNvQW6GoNlNXV4e/vz927dql9MS7rKysQ7cFsH9trq2txbp165TG19XVYcOGDazYDRs2QCQSwcnJiRU7fvx4HD58GKtWrYKBgQG8vLxYy/39/XHu3DlkZ2crbEeej7L8Tp48id9//50VL38eR1ueHKzqNry9vVFXV4f169czZfX19QodpmehuroadXV1rLK+fftCTU2NmTWnoqJCYT35jFaNZ9ZpzMTEBI6OjsjIyGC13YULF3D48GF4e3t3zA40IpPJ8PjxY1aZtbU1dHR0mDw9PDzA5XLxzTffsI7Lxo0bIZVK4ePjw1r3jz/+QG1tLVO2b98+le/Hf/PNN2FpaYlVq1YpfH7k2zY0NISbmxs2bNiAu3fvKtTR3r9Jb29v/PHHHzh16hSrzsbjlFQVExMDTU1NREZGory8nLWsoqICkyZNgpaWFjPFLACm89jWJ2935ncWRbVHyVIflV8U9SKhVyyodlm6dClycnIwcOBATJw4Eba2tqioqEB+fj6OHj2q9CSyLYYMGQJ9fX2EhoZi2rRp4HA42Lx5c7O3tZiammLZsmUoKSmBjY0NduzYgbNnzyIlJUVh+s9x48Zh9uzZyM7ORlRUlMLymJgYZGZmYsyYMYiIiICTkxMqKiqwd+9eJCcno1+/fvD19UVWVhb8/Pzg4+OD4uJiJCcnw9bWFg8ePGDq0tTUhK2tLXbs2AEbGxt07doV9vb2Ko3hUHUbI0eOxNChQzF37lyUlJTA1tYWWVlZHTrWoznHjh3D1KlTMWbMGNjY2KCurg6bN29mTugAYMGCBTh+/Dh8fHxgbm6O0tJSrFu3DmKxWOkv13JJSUnw8vLC4MGDMWHCBGa6WaFQqPKzQFrjypUrcHd3x9ixY2Fra4suXbogOzsb9+7dQ0BAAIAnv4DPmzcPCQkJeO+99/D+++/j77//xrp16/DWW2+xJgH4+OOPkZmZiffeew9jx45FUVERtmzZwhps3BI1NTWsX78eI0eOhKOjI8LDw2FiYoLLly+jsLAQhw4dAgB8++23GDZsGPr27YuJEyfCysoK9+7dw++//47bt2/j3LlzbW6T2bNnY/PmzXjvvfcwffp0ZrpZc3Pzp97W1FTPnj2RkZGBoKAg9O3bV+HJ2xKJBNu3b2e1j/xHgfnz5yMgIAAaGhoYOXJkq65WddZ3FkVR1GvpGc1KRb1G7t27R6ZMmUK6d+9ONDQ0iLGxMXF3dycpKSmEkP+ftrHpFKTKphR1dXUldnZ2SreTl5dHBg0aRDQ1NYmpqSmZPXs2M2WsfLrTxnWcPn2aDB48mPD5fGJubk7Wrl3b7D54e3sTAOTEiRNKl5eXl5OpU6cSMzMzwuVyiVgsJqGhocyUlQ0NDWTx4sXE3Nyc8Hg80r9/f7Jv3z4SGhpKzM3NWXWdOHGCODk5ES6X26qpZ1uzjfLycjJ+/Hiiq6tLhEIhGT9+PDMVbNPpZgUCgcK2mjsO5ubmxMfHh3nfdLrZ69evk4iICGJtbU34fD7p2rUrGT58ODl69Cizzs8//0w++OADYmpqSrhcLjE1NSWBgYHkypUrTIyyzwYhhBw9epQMHTqUaGpqEl1dXTJy5Ehy8eJFVox86s+m09mmpaW1akpUiURCpkyZQnr37k0EAgERCoVk4MCBZOfOnQqxa9euJb179yYaGhrEyMiIREVFKUwJSwghK1asIGZmZoTH45GhQ4eS06dPNzvdbHNT9v7222/knXfeITo6OkQgEBAHBwfWdKqEEFJUVERCQkKIsbEx0dDQIGZmZsTX15dkZmaqtO9yyqbIPX/+PHF1dSV8Pp+YmZmRhQsXko0bN7aqbZvWFxgYSExMTJjvj8DAQNY01I0tXLiQmJmZETU1NdY2AZApU6aotA9P+84i5OnHoSWqTstIURT1slD1e41DSCtGMlLUS8DNzQ0SieSp4yIa8/PzQ0FBgcKTwCmKolqruroaQqEQUqmUzhBFUdQrQdXvNTrGgnrt3b17F/v378f48eOfdyoURVEURVEvLTrGgnptFRcXIy8vD6mpqdDQ0GDNPtOZamtrn3pft1AopNNediCpVIpHjx61GGNsbNxJ2XS+xs/iUEZTU7PVUy7LPXjwgDXmRxmRSNRh0wpTFEVRLw7asaBeW7/88gvCw8PRo0cPZGRkPLcTyRMnTmD48OEtxqSlpSEsLKxzEnoNTJ8+HRkZGS3GvMp3iZqYmLS4PDQ0FOnp6W2qe/ny5UhISGgxpri4mDXtM0VRFPVqoGMsKOo5q6ysxJkzZ1qMsbOze+rJIKW6ixcv4p9//mkx5lV+zsHRo0dbXG5qagpbW9s21X39+nVcv369xZhhw4aBz+e3qf6XAR1jQVHUq0bV7zXasaAoiqKoDkQ7FhRFvWro4G2Kol54ubm54HA4yMzMfN6pvPJKSkrA4XCwfPny553KCyk9PR0cDgenT59+3qlQFEW9tOgYC4qiqBeATCZDYmIi3Nzc4Obm9rzTeaVkZ2cjJSUFf/75J6qrq9GtWzcMGzYMkyZNwogRI553ehTFYjF3f6vi6dO3qRcJ7VhQFEW9AGQyGTPomXYsOgYhBBEREUhPT0f//v0xc+ZMGBsb4+7du8jOzoa7uzvy8vIwZMiQ550qRVHUK4F2LCiKemnJZDJoaWk97zSoF9SKFSuQnp6O6OhorFy5EhwOh1k2f/58bN68GV260P8GKYqiOgodY0FR1DNz584dREREwMjICDweD3Z2dti0aZNCXENDAxYtWgSxWAw+nw93d3eFp6C7ubnB3t4eZ86cgYuLC7S0tPD5558DAPbs2QMfHx+YmpqCx+PB2toaCxcuRH19fbN1DBkyBJqamrC0tERycjIT8+DBAwgEAkyfPl0hz9u3b0NdXR1LlixhyqqqqjBjxgxYWFiAx+NBLBYjJCQEEokEwJPnlMTGxsLJyQlCoRACgQDOzs7Iyclh6igpKYFIJAIAJCQkgMPhgMPhID4+XuW2fvz4MeLj42FjYwM+nw8TExOMHj0aRUVFCrEpKSmwtrYGj8fDW2+9hT///JO1/Pz58wgLC4OVlRX4fD6MjY0RERGB8vJyVlx8fDw4HA6uXbuGsLAw6OnpQSgUIjw8HDKZjBX76NEjTJs2Dd26dYOOjg7ef/993LlzR+l+qvq5acmjR4+wZMkS9O7dG8uXL2d1KuTGjx+Pt99+m1VWU1ODmTNnQiQSQSAQwM/PD2VlZa3aNkVR1OuK/lRDUdQzce/ePQwaNAgcDgdTp06FSCTCwYMHMWHCBFRXVyM6OpqJXbp0KdTU1DBr1ixIpVIkJiYiKCgIJ0+eZNVZXl4OLy8vBAQEIDg4GEZGRgCeDLzV1tbGzJkzoa2tjWPHjiE2NhbV1dVISkpi1VFZWQlvb2+MHTsWgYGB2LlzJ6KiosDlchEREQFtbW34+flhx44dWLlyJetBbtu3bwchBEFBQQCedEKcnZ1x6dIlRERE4M0334REIsHevXtx+/ZtdOvWDdXV1UhNTUVgYCAmTpyI+/fvY+PGjfD09MSpU6fg6OgIkUiE9evXIyoqCn5+fhg9ejQAwMHBQaW2rq+vh6+vL37++WcEBARg+vTpuH//Po4cOYILFy7A2tqaid22bRvu37+PyMhIcDgcJCYmYvTo0bh+/To0NDQAAEeOHMH169cRHh4OY2NjFBYWIiUlBYWFhfjjjz8UTtLHjh0LS0tLLFmyBPn5+UhNTYWhoSGWLVvGxISFhWHnzp0YP348Bg0ahF9++QU+Por3hrfmc9OS3377DRUVFYiOjm7Vw/g+/fRT6OvrIy4uDiUlJVi1ahWmTp2KHTt2NLtOTU0NampqmPfV1dUqb4+iKOqVQiiKop6BCRMmEBMTEyKRSFjlAQEBRCgUEplMRnJycggA0qdPH1JTU8PErF69mgAgBQUFTJmrqysBQJKTkxW2JZPJFMoiIyOJlpYWefz4sUIdK1asYMpqamqIo6MjMTQ0JLW1tYQQQg4dOkQAkIMHD7LqdHBwIK6ursz72NhYAoBkZWUpbL+hoYEQQkhdXR1r3wghpLKykhgZGZGIiAimrKysjAAgcXFxCnU9zaZNmwgAsnLlymbzKC4uJgCIgYEBqaioYJbv2bOHACA//vgjU6asPbdv304AkOPHjzNlcXFxBABrPwghxM/PjxgYGDDvz5w5QwCQ6OhoVlxYWJjCPqvyuVGF/DOUnZ2tUnxaWhoBQDw8PJg2I4SQGTNmEHV1dVJVVdXsuvJ2aPqSSqUqbZuiGjOfs69VL4rqDFKpVKXvNXorFEVRHY4Qgl27dmHkyJEghEAikTAvT09PSKVS5OfnM/Hh4eHgcrnMe2dnZwBQeNAaj8dDeHi4wvY0NTWZf9+/fx8SiQTOzs6QyWS4fPkyK7ZLly6IjIxk3nO5XERGRqK0tJR5UKGHhwdMTU2xdetWJu7ChQs4f/48goODmbJdu3ahX79+8PPzU8hJ/qu+uro6s28NDQ2oqKhAXV0dBgwYwGqD9ti1axe6deuGTz/9tNk85D766CPo6+sz75W1deP2fPz4MSQSCQYNGgQASnOeNGkS672zszPKy8uZX+5/+uknAMDkyZNZcU3zbe3npiXybevo6KgUL/fJJ5+w2szZ2Rn19fW4ceNGs+vMmzcPUqmUed26datV26QoinpV0FuhKIrqcGVlZaiqqkJKSgpSUlKUxpSWljInuD169GAtk5dXVlayys3MzFgdELnCwkJ88cUXOHbsmMJtKFKplPXe1NQUAoGAVWZjYwPgyViHQYMGQU1NDUFBQVi/fj0zQHzr1q3g8/kYM2YMs15RURH8/f2bbQe5jIwMrFixApcvX8Z///3HlFtaWj51XVUUFRWhV69eKg1EVqWtKyoqkJCQgO+//x6lpaWs+Kbt+bQ6dXV1cePGDaipqSns7xtvvMF6r+rnRhXyBzjdv39fpXg5VT+LjfF4PPB4vFZth6Io6lVEOxYURXW4hoYGAEBwcDBCQ0OVxjg4OODixYsA0Ow98IQQ1vvGv6TLVVVVwdXVFbq6uliwYAGsra3B5/ORn5+POXPmMLm0VkhICJKSkrB7924EBgZi27Zt8PX1hVAobFU9W7ZsQVhYGEaNGoWYmBgYGhoyA8CVDax+1lRp67Fjx+LEiROIiYmBo6MjtLW10dDQgPfee09pe6p6/J5G1c+NKnr37g0AKCgowKhRo1TOoaP2haIo6nVEOxYURXU4kUgEHR0d1NfXw8PDo9k4eceiPXJzc1FeXo6srCy4uLgw5cXFxUrj//nnHzx8+JB11eLKlSsAAAsLC6bM3t4e/fv3x9atWyEWi3Hz5k2sWbOGVZe1tTUuXLjQYn6ZmZmwsrJCVlYW6xabuLg4VpyyWYtUZW1tjZMnT+K///5jBmC3VWVlJX7++WckJCQgNjaWKb969Wqb6zQ3N0dDQwOKi4vRs2dPprzpzF+qfm5UMWzYMOjr62P79u34/PPPWzWAm6IoimobOsaCoqgOp66uDn9/f+zatUvpiXdHTt8pP2Fs/ItybW0t1q1bpzS+rq4OGzZsYMVu2LABIpEITk5OrNjx48fj8OHDWLVqFQwMDODl5cVa7u/vj3PnziE7O1thO/J8lOV38uRJ/P7776x4+fM4qqqqWtxfZfz9/SGRSLB27dpm81CVsnwBYNWqVa3OS87T0xMAFI5J045aR35utLS0MGfOHFy6dAlz5sxR2g5btmzBqVOnVK6TojpDyVKfVr0o6kVCr1hQFPVMLF26FDk5ORg4cCAmTpwIW1tbVFRUID8/H0ePHkVFRUWHbGfIkCHQ19dHaGgopk2bBg6Hg82bNzd7Qm1qaoply5ahpKQENjY22LFjB86ePYuUlBSFX/vHjRuH2bNnIzs7G1FRUQrLY2JikJmZiTFjxiAiIgJOTk6oqKjA3r17kZycjH79+sHX1xdZWVnw8/ODj48PiouLkZycDFtbWzx48ICpS1NTE7a2ttixYwdsbGzQtWtX2Nvbw97e/qltEBISgu+++w4zZ87EqVOn4OzsjIcPH+Lo0aOYPHkyPvjgA5XbU1dXFy4uLkhMTMR///0HMzMzHD58uNkrQKpwcnKCv78/Vq1ahfLycma6WfmVosZXazrycxMTE4PCwkKsWLECOTk5+PDDD2FsbIx///0Xu3fvxqlTp3DixIk27xdFURTFRq9YUBT1TBgZGeHUqVMIDw9HVlYWpk6ditWrV6OiooL1fIP2MjAwwL59+2BiYoIvvvgCy5cvxzvvvIPExESl8fr6+jhw4ABOnz6NmJgY3Lp1C2vXrsXEiROV7sO7774L4MnVi6a0tbXx66+/IioqCgcOHMC0adOwbt069OrVC2KxGMCT5zcsXrwY586dw7Rp03Do0CFs2bIFAwYMUKgvNTUVZmZmmDFjBgIDA5GZmalSG6irq+PAgQOYP38+Tp48yTxpWldXF3379lWpjsa2bdsGT09PfPvtt5g3bx40NDRw8ODBVtfT2HfffYcpU6Zg//79mDNnDmpra5lnQ/D5fCauIz83ampq+O6775CZmYlu3bph+fLl+OSTT7BmzRpYWloiNzcXgwcPbtd+URRFUf+PQ+iINIqiXhNubm6QSCRPHRfRmJ+fHwoKChTGA1Dtd/bsWfTv3x9btmxhHjr4KqiuroZQKIRUKmVmp6IoinqZqfq9Rq9YUBRFNePu3bvYv3+/0qsVVOs8evRIoWzVqlVQU1NjDbqnKIqiXl50jAVFUVQTxcXFyMvLQ2pqKjQ0NFgP1OtMtbW1Tx1TIBQKlU7D+6JJTEzEmTNnMHz4cHTp0gUHDx7EwYMH8cknn6B79+6tqqusrAz19fXNLudyuejatWt7U6YoiqJaiXYsKIqimvjll18QHh6OHj16ICMjA8bGxs8ljxMnTmD48OEtxqSlpSEsLKxzEmqHIUOG4MiRI1i4cCEePHiAHj16ID4+HvPnz291XW+99VaLT8J2dXVFbm5uO7KlKIqi2oKOsaAoinpBVVZW4syZMy3G2NnZwcTEpJMyejHk5eUpvbVKTl9fX2Hq4M5Ex1hQFPWqUfV7jXYsKIqiKKoD0Y4FRVGvGjp4m6IoiqIoiqKoTkM7FhT1isnNzQWHw1H5GQgU1RphYWGwsLB43mlQFEVRLyA6eJuiqFeWTCZDYmIi3Nzc4Obm1uZ6Ll26BFtbW/B4PPz777/Q09NTiDl16hTS09Nx8uRJnD9/HnV1dc0+/Rt4cln566+/RlZWFoqKilBfXw9ra2v4+Phg+vTpMDU1bXO+nak9bVxSUgJLS0sAQGZmJvz9/VnL4+PjkZCQgLKyMnTr1q2jUqaoF5LF3P1tWq9kqU8HZ0JRbUevWFAU9cqSyWRISEho9wxBW7ZsYWaGau5K0IEDB5CamgoOhwMrK6sW67t+/TocHR2xcOFC2NraYtmyZfjmm28wfPhwbNy4sV2doM7WUW28YMGCFjtiFEVR1IuPdiwoimKRyWTPO4UXCiEE27Ztw7hx4+Dt7Y2tW7cqjYuKioJUKsXp06fxzjvvNFtfXV0dRo8ejXv37iE3Nxfbt2/HlClTMHHiRKxZswbXr1/HmDFjWszpVTtGjo6OOH/+PLKzs5/pdh4+fPhM66coinrd0Y4FRb1k7ty5g4iICBgZGYHH48HOzg6bNm1SiGtoaMCiRYsgFovB5/Ph7u6Oa9eusWLc3Nxgb2+PM2fOwMXFBVpaWvj8888BAHv27IGPjw9MTU3B4/FgbW2NhQsXKjyYrHEdQ4YMgaamJiwtLZGcnMzEPHjwAAKBANOnT1fI8/bt21BXV8eSJUuYsqqqKsyYMQMWFhbg8XgQi8UICQmBRCIB8OTBcbGxsXBycoJQKIRAIICzszNycnKYOkpKSiASiQAACQkJ4HA44HA4iI+Pb1V75+XloaSkBAEBAQgICMDx48dx+/ZthTgjIyOVHlS3a9cunDt3DvPnz8ewYcMUluvq6mLRokXM+5aOUU1NDeLi4vDGG2+Ax+Ohe/fumD17Nmpqalh1HjlyBMOGDYOenh60tbXRq1cvpg4ASE9PB4fDQUlJCWs9+Xid5q5GdFQbBwQEwMbGRuWrFj/88AOcnJygqamJbt26ITg4GHfu3GHFhIWFQVtbG0VFRfD29oaOjg6CgoIAABwOB1OnTsUPP/wAW1tbaGpqYvDgwSgoKAAAbNiwAW+88Qb4fD7c3NwU2oWiKIpSjo6xoKiXyL179zBo0CDmxEgkEuHgwYOYMGECqqurER0dzcQuXboUampqmDVrFqRSKRITExEUFISTJ0+y6iwvL4eXlxcCAgIQHBwMIyMjAE9ONrW1tTFz5kxoa2vj2LFjiI2NRXV1NZKSklh1VFZWwtvbG2PHjkVgYCB27tyJqKgocLlcREREQFtbG35+ftixYwdWrlwJdXV1Zt3t27eDEMKc9D148ADOzs64dOkSIiIi8Oabb0IikWDv3r24ffs2unXrhurqaqSmpiIwMBATJ07E/fv3sXHjRnh6euLUqVNwdHSESCTC+vXrERUVBT8/P4wePRoA4ODg0Ko237p1K6ytrfHWW2/B3t4eWlpa2L59O2JiYlpVj9zevXsBAOPHj1d5HWXHqKGhAe+//z5+++03fPLJJ+jTpw8KCgrw9ddf48qVK9i9ezcAoLCwEL6+vnBwcMCCBQvA4/Fw7do15OXltSn/xjqqjdXV1fHFF18gJCQE2dnZTD3KpKenIzw8HG+99RaWLFmCe/fuYfXq1cjLy8Nff/3FGv9SV1cHT09PDBs2DMuXL4eWlhaz7Ndff8XevXsxZcoUAMCSJUvg6+uL2bNnY926dZg8eTIqKyuRmJiIiIgIHDt2rNmcampqWJ256urqVu0/RVHUK4NQFPXSmDBhAjExMSESiYRVHhAQQIRCIZHJZCQnJ4cAIH369CE1NTVMzOrVqwkAUlBQwJS5uroSACQ5OVlhWzKZTKEsMjKSaGlpkcePHyvUsWLFCqaspqaGODo6EkNDQ1JbW0sIIeTQoUMEADl48CCrTgcHB+Lq6sq8j42NJQBIVlaWwvYbGhoIIYTU1dWx9o0QQiorK4mRkRGJiIhgysrKyggAEhcXp1CXKmpra4mBgQGZP38+UzZu3DjSr1+/FtebMmUKae7rtX///kQoFKqcQ3PHaPPmzURNTY38+uuvrPLk5GQCgOTl5RFCCPn6668JAFJWVtbsNtLS0ggAUlxczCqXf5ZycnKYstDQUGJubs68b08bFxcXEwAkKSmJ1NXVkZ49e5J+/foxxzkuLo6Ve21tLTE0NCT29vbk0aNHTD379u0jAEhsbCwrTwBk7ty5CtsFQHg8Hmt/N2zYQAAQY2NjUl1dzZTPmzdPads0Js+z6Usqlba6TajXl/mcfW16UVRnkEqlKn2v0VuhKOolQQjBrl27MHLkSBBCIJFImJenpyekUiny8/OZ+PDwcHC5XOa9s7MzgCcDhxvj8XgIDw9X2F7j23ru378PiUQCZ2dnyGQyXL58mRXbpUsXREZGMu+5XC4iIyNRWlrKPDnaw8MDpqamrDEKFy5cwPnz5xEcHMyU7dq1C/369YOfn59CThwOB8CTX7jl+9bQ0ICKigrU1dVhwIABrDZor4MHD6K8vByBgYFMWWBgIM6dO4fCwsI21VldXQ0dHZ1WraPsGP3www/o06cPevfuzfosjBgxAgCY28Lkv+Dv2bMHDQ0Nbcq5M8ivWpw7d4652tLU6dOnUVpaismTJ4PP5zPlPj4+6N27N/bvV5xVJyoqSmld7u7urGlzBw4cCADw9/dnHR95edO/m8bmzZsHqVTKvG7dutVsLEVR1KuMdiwo6iVRVlaGqqoqpKSkQCQSsV7yk87S0lImvkePHqz19fX1ATy5bakxMzMzVgdErrCwEH5+fhAKhdDV1YVIJGI6AFKplBVramoKgUDAKrOxsQEA5v50NTU1BAUFYffu3czg461bt4LP57MGKxcVFcHe3v6p7ZGRkQEHBwfw+XwYGBhAJBJh//79Crm1x5YtW2BpacncPnTt2jVYW1tDS0ur2UHcT6Orq4v79++3ah1lx+jq1asoLCxU+CzI213+Wfjoo48wdOhQfPzxxzAyMkJAQAB27tz5QnYygoKC8MYbbzQ71uLGjRsAgF69eiks6927N7NcrkuXLhCLxUq31fTvQygUAgC6d++utLzp301jPB4Purq6rBdFUdTriI6xoKiXhPxEMDg4GKGhoUpjHBwccPHiRQBgjWNorOkJm7IBx1VVVXB1dYWuri4WLFgAa2tr8Pl85OfnY86cOW0+KQ0JCUFSUhJ2796NwMBAbNu2Db6+vszJm6q2bNmCsLAwjBo1CjExMTA0NGQGgBcVFbUpt6aqq6vx448/4vHjx+jZs6fC8m3btmHRokXMVRRV9e7dG3/99Rdu3bqlcBLbHGXHqKGhAX379sXKlSuVriOvW1NTE8ePH0dOTg7279+Pn376CTt27MCIESNw+PBhqKurN7sPTQfqP2vyqxZhYWHYs2dPu+vj8XhQU1P++1lzfx+q/t1QFEVRimjHgqJeEiKRCDo6Oqivr4eHh0ezcfKORXvk5uaivLwcWVlZcHFxYcqLi4uVxv/zzz94+PAh66rFlStXAIB1u4m9vT369++PrVu3QiwW4+bNm1izZg2rLmtra1y4cKHF/DIzM2FlZYWsrCzWSXFcXBwrrrUn/Y1lZWXh8ePHWL9+vcLD2f7++2988cUXyMvLUzqzU0tGjhyJ7du3Y8uWLZg3b16b87O2tsa5c+fg7u7+1P1UU1ODu7s73N3dsXLlSixevBjz589HTk4OPDw8mKtZVVVVrPWaXgFQpj1trExwcDC++uorJCQk4P3332ctMzc3B/Ck/eW3fMn9/fffzHKKoijq+aAdC4p6Sairq8Pf3x/btm3DhQsXFG4XKisrY6b+7IhtAexfaWtra7Fu3Tql8XV1ddiwYQNmzpzJxG7YsAEikQhOTk6s2PHjx2P27Nng8XgwMDCAl5cXa7m/vz8WLFiA7OxshXEWhBBwOBxWfvIT25MnT+L3339n3eIinwWo6QmzKrZs2QIrKytMmjRJYVlNTQ2WLl2KrVu3trpj8eGHH2LJkiVYtGgR3NzcMHjwYNby+/fvY+nSpawpZ5UZO3YsDhw4gP/973/45JNPWMsePXqEhoYGCAQCVFRUoGvXrqzljo6OzH4ATzopAHD8+HFmWX19PVJSUp66P+1pY2UaX7VoasCAATA0NERycjIiIiLA4/EAPBkLc+nSJcTGxnZIDhT1PNAnaFOvAtqxoKiXyNKlS5GTk4OBAwdi4sSJsLW1RUVFBfLz83H06FFUVFR0yHaGDBkCfX19hIaGYtq0aeBwONi8eXOzt4OYmppi2bJlKCkpgY2NDXbs2IGzZ88iJSUFGhoarNhx48Zh9uzZyM7ORlRUlMLymJgYZGZmYsyYMYiIiICTkxMqKiqwd+9eJCcno1+/fvD19UVWVhb8/Pzg4+OD4uJiJCcnw9bWFg8ePGDq0tTUhK2tLXbs2AEbGxt07doV9vb2Tx3D8c8//yAnJwfTpk1TupzH48HT0xM//PADvvnmG2hoaODGjRvYvHkzgCeDjAHgq6++AvDkl3b59LIaGhrIysqCh4cHXFxcMHbsWAwdOhQaGhooLCzEtm3boK+v/9SOxfjx47Fz505MmjQJOTk5GDp0KOrr63H58mXs3LkThw4dwoABA7BgwQIcP34cPj4+MDc3R2lpKdatWwexWMx0iuzs7DBo0CDMmzeP6Yh8//33qKurazGH9rRxS4KCgrBw4UKcPXuWVa6hoYFly5YhPDwcrq6uCAwMZKabtbCwwIwZM9q8TYqiKKoDPNvJqSiK6mj37t0jU6ZMId27dycaGhrE2NiYuLu7k5SUFELI/08R+sMPP7DWk0/tmZaWxpS5uroSOzs7pdvJy8sjgwYNIpqamsTU1JTMnj2bmTK28fSj8jpOnz5NBg8eTPh8PjE3Nydr165tdh+8vb0JAHLixAmly8vLy8nUqVOJmZkZ4XK5RCwWk9DQUGaa3YaGBrJ48WJibm5OeDwe6d+/P9m3b5/CVKiEEHLixAni5OREuFyuytOirlixggAgP//8c7Mx6enpBADZs2cPIeT/213Zq/F0unKVlZUkNjaW9O3bl2hpaRE+n0/s7e3JvHnzyN27d5m4lo5RbW0tWbZsGbGzsyM8Ho/o6+sTJycnkpCQwEwJ+PPPP5MPPviAmJqaEi6XS0xNTUlgYCC5cuUKq66ioiLi4eFBeDweMTIyIp9//jk5cuTIU6ebJaRtbUwIe7rZpuRT4ELJVLk7duwg/fv3Jzwej3Tt2pUEBQWR27dvs2JCQ0OJQCBQul0AZMqUKSrl0tzfU0tUnZaRoijqZaHq9xqHEDoijaKotnNzc4NEInnquIjG/Pz8UFBQoPAkcIp6FVRXV0MoFEIqldIZoiiKeiWo+r1Gp5ulKKpT3b17F/v372/Vk6cpiqIoinrx0TEWFEV1iuLiYuTl5SE1NRUaGhqsB+p1ptra2qeORREKhUqneKVUQ9uYoijq9UQ7FhRFdYpffvkF4eHh6NGjBzIyMmBsbPxc8jhx4gSGDx/eYkxaWprSWYko1dA2piiKej3RMRYURb1WKisrcebMmRZj7OzsYGJi0kkZvXpe9zamYywoinrVqPq9RjsWFEVRFNWBaMeCoqhXDR28TVHUSy03NxccDgeZmZnPO5WXWklJCTgcDtLT0593KnBzc4Obmxvz/kXKjaIoimo/OsaCoijqBSeTyZCYmKhwYk61LCwsDBkZGejbty/OnTvHPKVdjsPhYMqUKVi7du1zypCiAIu5+9u1Pn1iN/UioR0LiqKoF5xMJkNCQgIAtLpjYW5ujkePHik84fxF0Fm5FRQUICsrC/7+/s90OxRFUa87eisURVGvJJlM9rxTeCFwOBzw+Xyoq6s/71QUdEZumpqasLGxwYIFC0CHFFIURT1btGNBUdRzcefOHURERMDIyAg8Hg92dnbYtGmTQlxDQwMWLVoEsVgMPp8Pd3d3hSd2u7m5wd7eHmfOnIGLiwu0tLTw+eefAwD27NkDHx8fmJqagsfjwdraGgsXLkR9fX2zdQwZMgSampqwtLREcnIyE/PgwQMIBAJMnz5dIc/bt29DXV0dS5YsYcqqqqowY8YMWFhYgMfjQSwWIyQkBBKJBMCT5z3ExsbCyckJQqEQAoEAzs7OyMnJYeooKSmBSCQCACQkJIDD4YDD4SA+Pl6ldlY2jiEsLAza2tq4c+cORo0aBW1tbYhEIsyaNUuhXb7//ns4OTlBR0cHurq66Nu3L1avXs0sj4+PV7jFCADS09PB4XBQUlLyzHJThZqaGr744gucP38e2dnZT40vLS3FhAkTYGRkBD6fj379+iEjI6PV26Uoinod0Y4FRVGd7t69exg0aBCOHj2KqVOnYvXq1XjjjTcwYcIErFq1ihW7dOlSZGdnY9asWZg3bx7++OMPBAUFKdRZXl4OLy8vODo6YtWqVcxzFNLT06GtrY2ZM2di9erVcHJyQmxsLObOnatQR2VlJby9veHk5ITExESIxWJERUUxHR5tbW34+flhx44dCie527dvByGEye3BgwdwdnbGmjVr8O6772L16tWYNGkSLl++jNu3bwN4MstGamoq3NzcsGzZMsTHx6OsrAyenp44e/YsAEAkEmH9+vUAAD8/P2zevBmbN2/G6NGj234AANTX18PT0xMGBgZYvnw5XF1dsWLFCqSkpDAxR44cQWBgIPT19bFs2TIsXboUbm5uyMvLa9e2OyK31hg3bhx69uz51KsWjx49gpubGzZv3oygoCAkJSVBKBQiLCyM1ZlqqqamBtXV1awXRVHUa4lQFEV1sgkTJhATExMikUhY5QEBAUQoFBKZTEZycnIIANKnTx9SU1PDxKxevZoAIAUFBUyZq6srAUCSk5MVtiWTyRTKIiMjiZaWFnn8+LFCHStWrGDKampqiKOjIzE0NCS1tbWEEEIOHTpEAJCDBw+y6nRwcCCurq7M+9jYWAKAZGVlKWy/oaGBEEJIXV0da98IIaSyspIYGRmRiIgIpqysrIwAIHFxcQp1PU1xcTEBQNLS0piy0NBQAoAsWLCAFdu/f3/i5OTEvJ8+fTrR1dUldXV1zdYfFxdHlP1XkpaWRgCQ4uJipszV1ZXVRu3JTRWhoaFEIBAQQgjJyMhQOB4AyJQpU5j3q1atIgDIli1bmLLa2loyePBgoq2tTaqrq5VuR94GTV9SqbRV+VKvJ/M5+9r1oqjOIJVKVfpeo1csKIrqVIQQ7Nq1CyNHjgQhBBKJhHl5enpCKpUiPz+fiQ8PDweXy2XeOzs7AwCuX7/OqpfH4yE8PFxhe5qamsy/79+/D4lEAmdnZ8hkMly+fJkV26VLF0RGRjLvuVwuIiMjUVpayjzwzcPDA6ampti6dSsTd+HCBZw/fx7BwcFM2a5du9CvXz/4+fkp5CS/dUhdXZ3Zt4aGBlRUVKCurg4DBgxgtcGzMmnSJNZ7Z2dnVrvq6enh4cOHOHLkyDPPpamn5dZaQUFBT71qceDAARgbGyMwMJAp09DQwLRp0/DgwQP88ssvStebN28epFIp87p161ab86QoinqZ0Y4FRVGdqqysDFVVVUhJSYFIJGK95B2D0tJSJr5Hjx6s9fX19QE8uW2pMTMzM1YHRK6wsBB+fn4QCoXQ1dWFSCRiOgBSqZQVa2pqCoFAwCqzsbEBAGasgJqaGoKCgrB7925mgPjWrVvB5/MxZswYZr2ioiLY29s/tT0yMjLg4OAAPp8PAwMDiEQi7N+/XyG3jsbn85mxG3L6+vqsdp08eTJsbGzg5eUFsViMiIgI/PTTT880L1Vzay11dXV88cUXOHv2LHbv3q005saNG+jZsyfU1Nj/Nfbp04dZrgyPx4Ouri7rRVEU9TqiHQuKojpVQ0MDACA4OBhHjhxR+ho6dCgT39yMQU1/dW58ZUKuqqoKrq6uOHfuHBYsWIAff/wRR44cwbJly1i5tFZISAgePHiA3bt3gxCCbdu2wdfXF0KhsFX1bNmyBWFhYbC2tsbGjRvx008/4ciRIxgxYkSbc1OVKjMxGRoa4uzZs9i7dy/ef/995OTkwMvLC6GhoUyMsoHbANo00Lo1ubVFUFAQ3njjDTpDFEVR1DNCn2NBUVSnEolE0NHRQX19PTw8PJqNu3jxYru3lZubi/LycmRlZcHFxYUpLy4uVhr/zz//4OHDh6yrFleuXAEAWFhYMGX29vbo378/tm7dCrFYjJs3b2LNmjWsuqytrXHhwoUW88vMzISVlRWysrJYJ+hxcXGsuOZO3jsDl8vFyJEjMXLkSDQ0NGDy5MnYsGEDvvzyS7zxxhvMFaSqqiro6ekx6zX36/7zJL9qERYWhj179igsNzc3x/nz59HQ0MC6aiG/Zc7c3LzTcqUoinoZ0Y4FRVGdSl1dHf7+/ti2bRsuXLigcLtQWVmZwm0w7dkWwL66UVtbi3Xr1imNr6urw4YNGzBz5kwmdsOGDRCJRHBycmLFjh8/HrNnzwaPx4OBgQG8vLxYy/39/bFgwQJkZ2crjLMghIDD4bDyk3ceTp48id9//511C5iWlhaAJyfvnam8vBwGBgbMezU1NTg4OAB4MhMS8KQDBQDHjx/H+++/DwB4+PDhCztFa3BwML766ivmgYONeXt74/Dhw9ixYwczzqKurg5r1qyBtrY2XF1dOztd6jVAn5xNvUpox4KiqE63dOlS5OTkYODAgZg4cSJsbW1RUVGB/Px8HD16FBUVFR2ynSFDhkBfXx+hoaGYNm0aOBwONm/e3OxtMKampli2bBlKSkpgY2ODHTt24OzZs0hJSVF4OvS4ceMwe/ZsZGdnIyoqSmF5TEwMMjMzMWbMGERERMDJyQkVFRXYu3cvkpOT0a9fP/j6+iIrKwt+fn7w8fFBcXExkpOTYWtriwcPHjB1aWpqwtbWFjt27ICNjQ26du0Ke3t7lcZwtMfHH3+MiooKjBgxAmKxGDdu3MCaNWvg6OjIjDt499130aNHD0yYMAExMTFQV1fHpk2bIBKJcPPmzWeaX1uoq6tj/vz5Sgf6f/LJJ9iwYQPCwsJw5swZWFhYIDMzE3l5eVi1ahV0dHSeQ8YURVEvDzrGgqKoTmdkZIRTp04hPDwcWVlZzLMsKioqmPEPHcHAwAD79u2DiYkJvvjiCyxfvhzvvPMOEhMTlcbr6+vjwIEDOH36NGJiYnDr1i2sXbsWEydOVLoP7777LoAnVy+a0tbWxq+//oqoqCgcOHAA06ZNw7p169CrVy+IxWIATx4Gt3jxYpw7dw7Tpk3DoUOHsGXLFgwYMEChvtTUVJiZmWHGjBkIDAxEZmZme5pGJcHBweDz+Vi3bh0mT56MjIwMfPTRRzh48CBzq5CGhgays7NhbW2NL7/8Et988w0+/vhjTJ069Znn11bBwcHMlZbGNDU1kZubi6CgIGRkZOCzzz5DRUUF0tLSlD4UkaIoimLjEDqCjaIoCm5ubpBIJE8dF9GYn58fCgoKFJ4ETr3eqqurIRQKIZVK6QxRFEW9ElT9XqNXLCiKotrg7t272L9/v9KrFRRFURT1OqJjLCiKolqhuLgYeXl5SE1NhYaGBuuBep2ptrb2qWNRhEKh0ml4X3YVFRWora1tdrm6unqHTQBAURRFqY52LCiKolrhl19+QXh4OHr06IGMjAwYGxs/lzxOnDiB4cOHtxiTlpaGsLCwzkmoE40ePbrZp2ADT6aFlT/QkKIoiuo8dIwFRVHUS6iyshJnzpxpMcbOzg4mJiadlFHnOXPmTItP4dbU1GQ9ZLGz0TEWFEW9alT9XqMdC4qiKIrqQLRjQVHUq4YO3qYoiqIoiqIoqtPQjgVFUYzc3FxwOJxOeUbCq6ykpAQcDgfp6enPOxW4ubnBzc2Nef8i5fa8paeng8Ph0PEYFEVRHYQO3qYoilJCJpMhMTFR4cSceroff/wRy5cvx6VLl/DgwQMYGxtjwIABiIiIwHvvvQcA+Oeff5CSkoJRo0bB0dHx+SZMUc+Bxdz9HVJPyVKfDqmHojoC7VhQFEUpIZPJkJCQAACt7liYm5vj0aNH0NDQeAaZtc+zzm358uWIiYmBq6sr5s2bBy0tLVy7dg1Hjx7F999/z+pYJCQkwMLCgnYsKIqiXhG0Y0FRVIeRyWTQ0tJ63mk8dxwOB3w+/3mnodSzzK2urg4LFy7EO++8g8OHDyssLy0tfSbbpSiKol4MdIwFRb1G7ty5g4iICBgZGYHH48HOzg6bNm1SiGtoaMCiRYsgFovB5/Ph7u6Oa9eusWLc3Nxgb2+PM2fOwMXFBVpaWvj8888BAHv27IGPjw9MTU3B4/FgbW2NhQsXor6+vtk6hgwZAk1NTVhaWiI5OZmJefDgAQQCAaZPn66Q5+3bt6Guro4lS5YwZVVVVZgxYwYsLCzA4/EgFosREhICiUQC4MmD5WJjY+Hk5AShUAiBQABnZ2fk5OQwdZSUlDAPWEtISACHwwGHw0F8fLxK7axsHENYWBi0tbVx584djBo1Ctra2hCJRJg1a5ZCu3z//fdwcnKCjo4OdHV10bdvX6xevZpZHh8fDw6Ho7BdVcYMtDe3lkgkElRXVzc71auhoSGAJ2N53nrrLQBAeHg4076Nczp58iTee+89CIVCaGlpwdXVFXl5eaz6bty4gcmTJ6NXr17Q1NSEgYEBxowZo3T/CwsLMWLECGhqakIsFuOrr75CQ0MDKyY0NBTdunXDf//9p7D+u+++i169eqncFhRFUa8jesWCol4T9+7dw6BBg8DhcDB16lSIRCIcPHgQEyZMQHV1NaKjo5nYpUuXQk1NDbNmzYJUKkViYiKCgoJw8uRJVp3l5eXw8vJCQEAAgoODYWRkBODJCa62tjZmzpwJbW1tHDt2DLGxsaiurkZSUhKrjsrKSnh7e2Ps2LEIDAzEzp07ERUVBS6Xi4iICGhra8PPzw87duzAypUroa6uzqy7fft2EEIQFBQE4EknxNnZGZcuXUJERATefPNNSCQS7N27F7dv30a3bt1QXV2N1NRUBAYGYuLEibh//z42btwIT09PnDp1Co6OjhCJRFi/fj2ioqLg5+eH0aNHAwAcHBzadQzq6+vh6emJgQMHYvny5Th69ChWrFgBa2trREVFAQCOHDmCwMBAuLu7Y9myZQCAS5cuIS8vT2nnqqOoktvTGBoaQlNTEz/++CM+/fRTdO3aVWlcnz59sGDBAsTGxuKTTz6Bs7MzAGDIkCEAgGPHjsHLywtOTk6Ii4uDmpoa0tLSMGLECPz66694++23AQB//vknTpw4gYCAAIjFYpSUlGD9+vVwc3PDxYsXmatn//77L4YPH466ujrMnTsXAoEAKSkpCk8lHz9+PL777jscOnQIvr6+TPm///6LY8eOIS4uTun+1NTUoKamhnlfXV2tUntRFEW9cghFUa+FCRMmEBMTEyKRSFjlAQEBRCgUEplMRnJycggA0qdPH1JTU8PErF69mgAgBQUFTJmrqysBQJKTkxW2JZPJFMoiIyOJlpYWefz4sUIdK1asYMpqamqIo6MjMTQ0JLW1tYQQQg4dOkQAkIMHD7LqdHBwIK6ursz72NhYAoBkZWUpbL+hoYEQQkhdXR1r3wghpLKykhgZGZGIiAimrKysjAAgcXFxCnU9TXFxMQFA0tLSmLLQ0FACgCxYsIAV279/f+Lk5MS8nz59OtHV1SV1dXXN1h8XF0eUfX2npaURAKS4uJgpc3V1ZbVRe3JThfwYCAQC4uXlRRYtWkTOnDmjEPfnn38q5EHIk+PUs2dP4unpyRwzQp58piwtLck777zDKmvq999/JwDId999x5RFR0cTAOTkyZNMWWlpKREKhaz2qq+vJ2KxmHz00UesOleuXEk4HA65fv260n2WH4+mL6lU2nxDUa898zn7OuRFUZ1BKpWq9L1Gb4WiqNcAIQS7du3CyJEjQQiBRCJhXp6enpBKpcjPz2fiw8PDweVymffyX5SvX7/OqpfH4yE8PFxhe41/Cb5//z4kEgmcnZ0hk8lw+fJlVmyXLl0QGRnJvOdyuYiMjERpaSnzZGkPDw+Ymppi69atTNyFCxdw/vx5BAcHM2W7du1Cv3794Ofnp5CT/NYhdXV1Zt8aGhpQUVGBuro6DBgwgNUGz8qkSZNY752dnVntqqenh4cPH+LIkSPPPJemnpabKhISErBt2zb0798fhw4dwvz58+Hk5IQ333wTly5deur6Z8+exdWrVzFu3DiUl5czn9OHDx/C3d0dx48fZ25havw5+++//1BeXo433ngDenp6rGN54MABDBo0iLnSAQAikYi50iWnpqaGoKAg7N27F/fv32fKt27diiFDhsDS0lJpzvPmzYNUKmVet27dUq2xKIqiXjG0Y0FRr4GysjJUVVUhJSUFIpGI9ZJ3DBoPrO3RowdrfX19fQBPbltqzMzMjNUBkSssLISfnx+EQiF0dXUhEomYDoBUKmXFmpqaQiAQsMpsbGwAgLlXXn7Ct3v3bshkMgBPTvb4fD7GjBnDrFdUVAR7e/untkdGRgYcHBzA5/NhYGAAkUiE/fv3K+TW0fh8PjN2Q05fX5/VrpMnT4aNjQ28vLwgFosRERGBn3766ZnmpWpuqgoMDMSvv/6KyspKHD58GOPGjcNff/2FkSNH4vHjxy2ue/XqVQBPxjs0/aympqaipqaGOU6PHj1CbGwsunfvDh6Ph27dukEkEqGqqop1LG/cuIGePXsqbEvZmImQkBA8evQI2dnZAIC///4bZ86cwfjx45vNmcfjQVdXl/WiKIp6HdExFhT1GpD/whscHIzQ0FClMQ4ODrh48SIAsMYxNEYIYb1veo868GTwtKurK3R1dbFgwQJYW1uDz+cjPz8fc+bMURgwq6qQkBAkJSVh9+7dCAwMxLZt2+Dr6wuhUNiqerZs2YKwsDCMGjUKMTExMDQ0ZAaAFxUVtSk3VTXXro0ZGhri7NmzOHToEA4ePIiDBw8iLS0NISEhyMjIAAClA7cBtGqgdVtyay1dXV288847eOedd6ChoYGMjAycPHkSrq6uza4j/3wkJSU1Ow2ttrY2AODTTz9FWloaoqOjMXjwYAiFQnA4HAQEBLT5c2ZrawsnJyds2bIFISEh2LJly/+xd+ZxNab//3+djjrn1KmT6rSJJEKFOEZECzFJMWVpKlot2cb2JcxSys7YhqHClCGkZBkm28gwMcaefS3GMu2dJEqd6/eH37k/3Z1Tnch+PR+P83i43/f7vq73tXS7rvu63u8LGhoa8PHxea30KBQK5XOCTiwolM8AsVgMbW1tVFVVoW/fvrXqyScWb8KxY8dQUFCA1NRUODk5MfKsrCyl+o8fP8azZ89Yqxa3bt0CALRs2ZKR2draonPnzkhMTISZmRkePHiA1atXs9KytLTElStX6rQvJSUFrVq1QmpqKmuAXtMxt7bB+7tAQ0MDAwcOxMCBAyGTyTB+/HjExsbihx9+QOvWrZkVpOLiYujq6jLP3b9//z1ZXD9du3bFpk2b8OTJEwC116+lpSWAV5OSuvoq8Kotg4KCsGzZMkb24sULFBcXs/TMzc2ZlZDq3Lx5U2m6gYGBmDZtGp48eYKtW7fCw8ODqXMKhUKh1A6dWFAonwFcLhdDhgzB1q1bceXKFYXtQnl5eQrbYN4kL4C9ulFRUYG1a9cq1a+srERsbCymTZvG6MbGxkIsFkMikbB0AwICEB4eDh6PB319fbi7u7PuDxkyBNHR0di1a5eCnwUhBBwOh2WffHB7+vRpnDp1irUFTB5RqOYg9W1TUFAAfX195lpNTY2JRiWPPCQffB8/fhyDBg0CADx79oxZ0XhflJWV4dKlS+jRo4fCvbS0NAD/234kn0jWrF+JRAJLS0v8+OOP8Pf3Z1Yn5FTvq1wuV2EVbfXq1QorNwMGDMDKlSvxzz//MH4WeXl5LJ+d6vj5+eH//u//MHnyZNy7d08hkhmF0hjQE7MpnyJ0YkGhfCYsWrQI6enpsLe3x+jRo2FtbY3CwkKcP38eR44cQWFhYaPk4+DggKZNmyIoKAiTJk0Ch8PB5s2bFQaAckxNTbF48WJkZ2fDysoKSUlJuHjxIuLi4hROh/b390d4eDh27dqFcePGKdyfMWMGUlJSMGzYMISGhkIikaCwsBB79+5FTEwMOnXqBE9PT6SmpsLb2xseHh7IyspCTEwMrK2tUVpayqQlEAhgbW2NpKQkWFlZQU9PD7a2tir5cLwJo0aNQmFhIfr06QMzMzPcv38fq1evhp2dHdq3bw/g1ZkKLVq0wMiRIzFjxgxwuVz88ssvEIvFePDgwVu1ry7Kysrg4OCA7t27o3///mjevDmKi4uxe/dunDhxAl5eXujcuTOAV5MjXV1dxMTEQFtbG1paWrC3t4eFhQU2bNgAd3d32NjYICQkBM2aNcOjR4+Qnp4OHR0d/PbbbwAAT09PbN68GSKRCNbW1jh16hSOHDnCmpgBQHh4ODZv3oz+/ftj8uTJTLhZc3NzZGZmKpRDLBajf//+SE5Ohq6uLjw86ACQQqFQVOItR6eiUCgfEDk5OWTChAmkefPmRF1dnRgbGxNXV1cSFxdHCCFMuNnk5GTWc8pClDo7OxMbGxul+WRkZJDu3bsTgUBATE1NSXh4OBMyNj09XSGNs2fPkh49ehA+n0/Mzc3JmjVrai3DgAEDCABy8uRJpfcLCgrIxIkTSbNmzYiGhgYxMzMjQUFBTJhdmUxGFixYQMzNzQmPxyOdO3cm+/btI0FBQcTc3JyV1smTJ4lEIiEaGhoNCj1bW0hXLS0tBd2aoWNTUlLIl19+SQwNDYmGhgZp0aIFCQsLI0+ePGE9d+7cOWJvb8/oLF++/I3CzapiW328fPmSrF+/nnh5eTH1q6mpSTp37kyWLl2qEOZ3z549xNramjRp0kTBpgsXLpDBgwcTfX19wuPxiLm5OfHx8SF//PEHo1NUVERCQkKIgYEBEQqFxM3Njdy4cYOYm5uToKAgVl6ZmZnE2dmZ8Pl80qxZMzJ37lyyceNGhfqSs2PHDgKAjBkzRuXyy1E1LCOFQqF8LKj6XuMQUstnRAqFQnnLuLi4ID8/v16/iOp4e3vj8uXLCieBUyiNyZ49e+Dl5YXjx48z4ZZVpaSkBCKRCFKplEaIolAonwSqvtdouFkKhfLR8OTJE+zfv7/O0J8USmOwfv16tGrVCr169XrfplAoFMpHA/WxoFAoHzxZWVnIyMjAhg0boK6uzjpQ711SUVFRry+KSCRSGob3Y6ewsBAVFRW13udyuY0WAOB9sn37dmRmZmL//v1YtWrVe40ORqFQKB8bdGJBoVA+eP7880+EhISgRYsW2LRpE4yNjd+LHSdPnkTv3r3r1ImPj0dwcPC7MegdMnjwYPz555+13jc3N2cONPyY8fPzg1AoxMiRIzF+/Pj3bQ6FQqF8VFAfCwqFQlGRoqIinDt3rk4dGxsbmJiYvCOL3h3nzp2r8xRugUCAnj17vkOLPlyojwWFQvnUUPW9RicWFAqFQqE0InRiQaFQPjWo83Y9HDt2DBwOBykpKe/bFMob4uLiAhcXF+Y6OzsbHA4HCQkJbyU/ed85duzYW0n/XRMcHMw64bohtGzZ8pPc9kOhUCgUCqXhUB8LCsrKyrBkyRKFATqF0lCuXbuGHTt2vNFkpT7mzJmDqKioWu8/efLkvflgfA789ttv+Oqrr2BlZYWbN2/Wqx8ZGYk5c+a8fcMolI+MlrP2N0o69ARvyocEnVhQUFZWxgzUPoWJhbm5OZ4/f65wKjNFOevXr4dMJmuUtK5du4aoqCi4uLi8tYmFnHXr1kEoFCrIdXV132q+nzv79++HRCLBggULkJOTw8jPnDmDn376Cd9++y1zQjgAdOzY8X2YSaFQKJT3AJ1YvCZlZWXQ1NR832ZQlMDhcMDn89+3GR8NH+sEbOjQoTAwMHjfZtTKp/qO+P333xEaGop+/fqx5Hw+Hz/99BP69etX5weKZ8+eQUtL6y1bSaFQKJT3wSfrY/Ho0SOEhobCyMgIPB4PNjY2+OWXXxT0ZDIZ5s+fDzMzM/D5fLi6uiqc6Ovi4gJbW1ucO3cOTk5O0NTUxLfffgvg1emsHh4eMDU1BY/Hg6WlJebOnYuqqqpa03BwcIBAIICFhQViYmIYndLSUmhpaWHy5MkKdj58+BBcLhcLFy5kZMXFxZg6dSpatmwJHo8HMzMzBAYGIj8/H8CrmPsRERGQSCQQiUTQ0tKCo6Mj0tPTmTSys7OZ2PNRUVHgcDjgcDgqb12Q+xvs2LEDUVFRaNasGbS1tTF06FBIpVKUl5djypQpMDQ0hFAoREhICMrLyxXS2bJlCyQSCQQCAfT09ODr64t///1XQS8uLg6WlpYQCATo1q0bTpw4oaBTm4/FjRs34OPjA7FYDIFAgLZt2+K7775j7t+/fx/jx49H27ZtIRAIoK+vj2HDhjVKCM2XL18iKioKbdq0AZ/Ph76+Pnr16oXDhw8zOsHBwRAKhbh37x7c3NygpaUFU1NTREdHo2aMBZlMhpUrV8LGxgZ8Ph9GRkYICwtTGrUnLS0Nzs7O0NbWho6ODr744gts3bqVlW/N1YUff/wRDg4O0NfXh0AggEQiqdcfKSEhAcOGDQMA9O7dm+lLx44dQ1BQEAwMDPDy5UuF57788ku0bdu23jpsKO+yb9b1jigoKEBAQAB0dHSgq6uLoKAgXLp0qdY+OnToUOjp6YHP56Nr167Yu3cvSychIQEcDgcZGRmYNm0axGIxtLS04O3tjby8PAX762r/yMhIqKurK31uzJgx0NXVxYsXLxjZ5cuX8e+//8LDQ7WtF3PmzAGHw8G1a9fg7++Ppk2bMgfOZWZmIjg4GK1atQKfz4exsTFCQ0NRUFDASqO2bXXytKvD4XAwceJEJCcnw9raGgKBAD169MDly5cBALGxsWjdujX4fD5cXFwU/rZPnDiBYcOGoUWLFuDxeGjevDmmTp2K58+fq1ReCoVC+dz5JFcscnJy0L17d+Y/GbFYjLS0NIwcORIlJSWYMmUKo7to0SKoqalh+vTpkEqlWLJkCYYPH47Tp0+z0iwoKIC7uzt8fX0xYsQIGBkZAXj1n7xQKMS0adMgFApx9OhRREREoKSkBEuXLmWlUVRUhAEDBsDHxwd+fn7YsWMHxo0bBw0NDYSGhkIoFMLb2xtJSUlYvnw5uFwu8+y2bdtACMHw4cMBvJqEODo64vr16wgNDUWXLl2Qn5+PvXv34uHDhzAwMEBJSQk2bNgAPz8/jB49Gk+fPsXGjRvh5uaGf/75B3Z2dhCLxVi3bh3GjRsHb29vDB48GEDDty8sXLgQAoEAs2bNwp07d7B69Wqoq6tDTU0NRUVFmDNnDv7++28kJCTAwsICERERzLPz58/HDz/8AB8fH4waNQp5eXlYvXo1nJyccOHCBWZry8aNGxEWFgYHBwdMmTIF9+7dw6BBg6Cnp4fmzZvXaV9mZiYcHR2hrq6OMWPGoGXLlrh79y5+++03zJ8/H8CrrRwnT56Er68vzMzMkJ2djXXr1sHFxQXXrl17o6/Pc+bMwcKFCzFq1Ch069YNJSUlOHv2LM6fP8/68ltVVYX+/fuje/fuWLJkCQ4cOIDIyEhUVlYiOjqa0QsLC0NCQgJCQkIwadIkZGVlYc2aNbhw4QIyMjKYVYiEhASEhobCxsYGs2fPhq6uLi5cuIADBw7A39+/VntXrVqFQYMGYfjw4aioqMD27dsxbNgw7Nu3r9ZBpZOTEyZNmqSwHaZ9+/YICAjAr7/+ioMHD8LT05N55r///sPRo0cRGRnZ4DpVdlBdkyZNFLZCvYu+CSh/R8hkMgwcOBD//PMPxo0bh3bt2mHPnj0ICgpSsP3q1avo2bMnmjVrhlmzZkFLSws7duyAl5cXdu7cCW9vb5b+N998g6ZNmyIyMhLZ2dlYuXIlJk6ciKSkJEanvvYPCAhAdHQ0kpKSMHHiROa5iooKpKSkYMiQIazVv99//x2Ghobo2rWryu0EAMOGDUObNm2wYMECZpJ8+PBh3Lt3DyEhITA2NsbVq1cRFxeHq1ev4u+//37tg+lOnDiBvXv3YsKECQBetb+npyfCw8Oxdu1ajB8/HkVFRViyZAlCQ0Nx9OhR5tnk5GSUlZVh3Lhx0NfXxz///IPVq1fj4cOHSE5OrjXP8vJy1qS0pKTktWynUCiUjx7yCTJy5EhiYmJC8vPzWXJfX18iEolIWVkZSU9PJwBI+/btSXl5OaOzatUqAoBcvnyZkTk7OxMAJCYmRiGvsrIyBVlYWBjR1NQkL168UEhj2bJljKy8vJzY2dkRQ0NDUlFRQQgh5ODBgwQASUtLY6XZsWNH4uzszFxHREQQACQ1NVUhf5lMRgghpLKyklU2QggpKioiRkZGJDQ0lJHl5eURACQyMlIhrfqQ16OtrS1TBkII8fPzIxwOh7i7u7P0e/ToQczNzZnr7OxswuVyyfz581l6ly9fJk2aNGHkFRUVxNDQkNjZ2bHKFBcXRwCw6iYrK4sAIPHx8YzMycmJaGtrk/v377PykdcVIcrb8tSpUwQA+fXXXxXKnJ6eXnvF1KBTp07Ew8OjTp2goCACgHzzzTcs+zw8PIiGhgbJy8sjhBBy4sQJAoAkJiaynj9w4ABLXlxcTLS1tYm9vT15/vw5S7d6uYOCglhtQohiXVRUVBBbW1vSp08fltzc3JwEBQUx18nJyUrrpqqqipiZmZGvv/6aJV++fDnhcDjk3r17tdSKIpGRkQSA0l/btm0ZvXfVNwmp/R2xc+dOAoCsXLmSVRd9+vRR6KOurq6kQ4cOrPeGTCYjDg4OpE2bNowsPj6eACB9+/ZltePUqVMJl8slxcXFhBDV279Hjx7E3t6edT81NVVpOzo6OrLauzrK2l7eVn5+fgr6yv7etm3bRgCQ48ePMzJl/bN62tUBQHg8HsnKymJksbGxBAAxNjYmJSUljHz27NkEAEtXmU0LFy4kHA5H4d2hzJaaP6lUWuszFIr5zH2N8qNQ3gVSqVSl99ontxWKEIKdO3di4MCBIIQgPz+f+bm5uUEqleL8+fOMfkhICDQ0NJhrR0dHAMC9e/dY6fJ4PISEhCjkJxAImH8/ffoU+fn5cHR0RFlZGW7cuMHSbdKkCcLCwphrDQ0NhIWFITc3lzl0q2/fvjA1NUViYiKjd+XKFWRmZmLEiBGMbOfOnejUqZPCV0wAzJc+LpfLlE0mk6GwsBCVlZXo2rUrqw4ag8DAQNZefXt7exBCEBoaytKzt7fHv//+i8rKSgBAamoqZDIZfHx8WG1lbGyMNm3aMNu2zp49i9zcXIwdO5bVXsHBwRCJRHXalpeXh+PHjyM0NBQtWrRg3av+VbR6W758+RIFBQVo3bo1dHV137i+dHV1cfXqVdy+fbte3epfjuWrbhUVFThy5AiAV19VRSIR+vXrx6oziUQCoVDI1Nnhw4fx9OlTzJo1S8HnpL6vwdXroqioCFKpFI6Ojq9dD2pqahg+fDj27t2Lp0+fMvLExEQ4ODjAwsKiwWnu3LkThw8fZv3i4+MV9N5235Sj7B1x4MABqKurY/To0ay6kH9Nl1NYWIijR4/Cx8eHeY/k5+ejoKAAbm5uuH37Nh49esR6ZsyYMax2dHR0RFVVFe7fvw9A9fYPDAzE6dOncffuXUaWmJiI5s2bw9nZmZEVFxfj1KlTKm+Dqs7YsWMVZNX72IsXL5Cfn4/u3bsDwBv9vbm6urK2Ttnb2wMAhgwZAm1tbQV59Xd9dZuePXuG/Px8ODg4gBCCCxcu1Jrn7NmzIZVKmZ+ybZwUCoXyOfDJbYXKy8tDcXEx4uLiEBcXp1QnNzcXTZs2BQCFgaZcXnOverNmzVgDWjlXr17F999/j6NHjyosf0ulUta1qampgtOilZUVgFd+Ad27d2cGYOvWrWOcPxMTE8Hn85n96wBw9+5dDBkypNZ6kLNp0yYsW7YMN27cYO1vf52BXF3UrEf5YL/mFiWRSASZTAapVAp9fX3cvn0bhBC0adNGabryAaF8sFRTT11dHa1atarTNvnAwdbWtk6958+fY+HChYiPj8ejR49Yfg0127KhREdHMyE6bW1t0b9/fwQEBChsOVNTU1MoT/U+AgC3b9+GVCqFoaGh0rxyc3MBgBko1lduZezbtw/z5s3DxYsXWVs8Xnd7CvBqALt48WLs2rULgYGBuHnzJs6dO8fyM2oITk5OKjlvv+2+KUfZO+L+/fswMTFR2EbXunVr1vWdO3dACMEPP/yAH374QWl+ubm5aNasWa3lqvnuUrX9v/76a0yZMgWJiYmIiIiAVCrFvn37MHXqVFZ7Hzx4EMArn5iGoux9U1hYiKioKGzfvp3ps3Le5O+tIe0NsN/1Dx48QEREBPbu3avwf0BdNvF4PPB4vNe2mUKhUD4VPrmJhTxs5ogRI5TuYwZe+Q9cu3YNAFh+DNUhNZxlq3/JklNcXAxnZ2fo6OggOjoalpaW4PP5OH/+PGbOnPnaITwDAwOxdOlS7N69G35+fti6dSs8PT3r/TJfky1btiA4OBheXl6YMWMGDA0NGQfw6l8nG4Pa6rG++pXJZOBwOEhLS1Oqqyyc6Nvim2++QXx8PKZMmYIePXpAJBKBw+HA19f3jcOxOjk54e7du9izZw8OHTqEDRs2YMWKFYiJicGoUaMalJZMJoOhoSFrVas6cmf81+XEiRMYNGgQnJycsHbtWpiYmEBdXR3x8fEsp++GYm1tDYlEgi1btiAwMBBbtmyBhoYGfHx83sje+nhXfVPZO0JV5P1r+vTpcHNzU6pTczKi6rurPpo2bQpPT09mYpGSkoLy8nLWCinwyr+iZ8+eDX4PAcrrxsfHBydPnsSMGTNgZ2cHoVAImUyG/v37s/7eapvM1gyQIed127uqqgr9+vVDYWEhZs6ciXbt2kFLSwuPHj1CcHBwo4VkplAolE+ZT25iIRaLoa2tjaqqKvTt27dWPfnE4k04duwYCgoKkJqaCicnJ0aelZWlVP/x48cKoRZv3boFAKyle1tbW3Tu3BmJiYkwMzPDgwcPsHr1alZalpaWuHLlSp32paSkoFWrVkhNTWX951zTUfZNvkK/KZaWliCEwMLCgvkyrwxzc3MAr77W9+nTh5G/fPkSWVlZ6NSpU63PylcAVKmvoKAgLFu2jJG9ePECxcXFqhSlXvT09BASEoKQkBCUlpbCyckJc+bMYU0sZDIZ7t27x6qLmn3E0tISR44cQc+ePesczFpaWgJ4Ve6ag9K62LlzJ/h8Pg4ePMj6Cqtsm1FN6utLgYGBmDZtGp48eYKtW7fCw8OD+dL+oaFq36wLc3NzpKenK4SerRl5Tt5H1dXV63xvNYSGtH9gYCC++uornDlzBomJiejcuTNsbGyY+4QQHDhwANOnT28U24qKivDHH38gKiqK5SyvbKtg06ZNlf4NylcxG4vLly/j1q1b2LRpEwIDAxl59chtFAqFQqmbT87HgsvlYsiQIdi5c6fSgaSysIpvkhfA/kJYUVGBtWvXKtWvrKxEbGwsSzc2NhZisRgSiYSlGxAQgEOHDmHlypXQ19eHu7s76/6QIUNw6dIl7Nq1SyEfuT3K7Dt9+jROnTrF0pcPeBprAN0QBg8eDC6Xi6ioKIUvrYQQJvRk165dIRaLERMTg4qKCkYnISGhXrvFYjGcnJzwyy+/4MGDBwp5yOFyuQo2rF69utYvow2hZghNoVCI1q1bKw1vumbNGpZ9a9asgbq6OlxdXQG8+tJbVVWFuXPnKjxbWVnJ1MeXX34JbW1tLFy4kBUyVJ5ubXC5XHA4HFa5s7OzsXv37nrLKZ8019Ymfn5+4HA4mDx5Mu7du6fwVfxDQtW+WRdubm54+fIl1q9fz8hkMhl+/vlnlp6hoSFcXFwQGxuLJ0+eKKTzOu+thrS/u7s7DAwMsHjxYvz5558K7XLmzBnk5ua+ln+FMpS9mwBg5cqVCrqWlpaQSqXIzMxkZE+ePFH67mtsmwghWLVqVaPmQ6HIyV7k0Sg/CuVD4pNbsQBehZBNT0+Hvb09Ro8eDWtraxQWFuL8+fM4cuSI0jCVr4ODgwOaNm2KoKAgTJo0CRwOB5s3b6510GZqaorFixcjOzsbVlZWSEpKwsWLFxEXF6ewX9vf3x/h4eHYtWsXxo0bp3B/xowZSElJwbBhwxAaGgqJRILCwkLs3bsXMTEx6NSpEzw9PZGamgpvb294eHggKysLMTExsLa2RmlpKZOWQCCAtbU1kpKSYGVlBT09Pdja2r7W3vyGYmlpiXnz5mH27NnIzs6Gl5cXtLW1kZWVhV27dmHMmDGYPn061NXVMW/ePISFhaFPnz74+uuvkZWVhfj4+Hp9LADgp59+Qq9evdClSxeMGTMGFhYWyM7Oxv79+3Hx4kUAgKenJzZv3gyRSARra2ucOnUKR44cgb6+/huX09raGi4uLpBIJNDT08PZs2eRkpLCctQGXh0yduDAAQQFBcHe3h5paWnYv38/vv32W2aLk7OzM8LCwrBw4UJcvHgRX375JdTV1XH79m0kJydj1apVGDp0KHR0dLBixQqMGjUKX3zxBXOOwKVLl1BWVoZNmzYptdXDwwPLly9H//794e/vj9zcXPz8889o3bo1a3CnDDs7O3C5XCxevBhSqRQ8Hg99+vRh/EHEYjH69++P5ORk6OrqvtFANSUlRelWuX79+jHhoN8EVftmXXh5eaFbt274v//7P9y5cwft2rXD3r17mXdQ9RWen3/+Gb169UKHDh0wevRotGrVCjk5OTh16hQePnyIS5cuNcj+hrS/uro6fH19sWbNGnC5XPj5+bHS2r9/P1q2bAlra+sG2VCXbU5OTliyZAlevnyJZs2a4dChQ0pXe319fTFz5kx4e3tj0qRJKCsrw7p162BlZdWoQSjatWsHS0tLTJ8+HY8ePYKOjg527typ9GwYCoVCodRC4wSh+vDIyckhEyZMIM2bNyfq6urE2NiYuLq6kri4OELI/0JRJicns55TFqrU2dmZ2NjYKM0nIyODdO/enQgEAmJqakrCw8OZkLHVwy7K0zh79izp0aMH4fP5xNzcnKxZs6bWMgwYMIAAICdPnlR6v6CggEycOJE0a9aMaGhoEDMzMxIUFMSE2ZXJZGTBggXE3Nyc8Hg80rlzZ7Jv3z6l4RtPnjxJJBIJ0dDQaFDo2drqUR4S88yZMyy5PCyjPHSqnJ07d5JevXoRLS0toqWlRdq1a0cmTJhAbt68ydJbu3YtsbCwIDwej3Tt2pUcP36cODs71xtulhBCrly5Qry9vYmuri7h8/mkbdu25IcffmDuFxUVkZCQEGJgYECEQiFxc3MjN27cUAip+jrhZufNm0e6detGdHV1iUAgIO3atSPz589nhUENCgoiWlpa5O7du+TLL78kmpqaxMjIiERGRpKqqiqFNOPi4ohEIiECgYBoa2uTDh06kPDwcPL48WOW3t69e4mDgwMRCARER0eHdOvWjWzbto2Vb83+sHHjRtKmTRvC4/FIu3btSHx8vNLwnjXrhhBC1q9fT1q1akW4XK7SetqxYwcBQMaMGaNy/VWnrnCz1fN7l32zrndEXl4e8ff3J9ra2kQkEpHg4GCSkZFBAJDt27ezdO/evUsCAwOJsbExUVdXJ82aNSOenp4kJSWlXvtr65f1tb+cf/75hwAgX375pcK9rl27kvHjxystn5y6ws3WrFNCCHn48CHz9ygSiciwYcPI48ePlb5/Dh06RGxtbYmGhgZp27Yt2bJlS63hZidMmMCSyd8HS5cuZcmV9Y9r166Rvn37EqFQSAwMDMjo0aPJpUuXlL5P6kLVsIwUCoXysaDqe41DSAM9/SivhYuLC/Lz8+vd518db29vXL58WWE/NuXTJDg4GCkpKazVpE+RPXv2wMvLC8ePH2fCO39u7N69G97e3vjrr7/Qs2fP920OAODSpUuws7PDr7/+ioCAAEaek5MDExMT7Nu3DwMGDHiPFn48lJSUQCQSQSqVQkdH532bQ6FQKG+Mqu+1T87H4lPhyZMn2L9/P+s/eArlU2D9+vVo1aoVevXq9b5NeSc8f/6cdV1VVYXVq1dDR0cHXbp0eU9WKbJ+/XoIhUIMHjyYJZdKpYiIiEDv3r3fk2UUCoVC+Vj4JH0sPmaysrKQkZGBDRs2QF1dnXWg3rukoqKiXl8UkUj0RiE2PwWeP39eb8x9PT09pWegfG5s374dmZmZ2L9/P1atWqUQQUoqlSoMwmtibGz8Nk18K3zzzTd4/vw5evTogfLycqSmpuLkyZNYsGDBB/H389tvv+HatWuIi4vDxIkTlZ61M2fOnPdjHIVCoVA+KujE4gPjzz//REhICFq0aIFNmza9t4HUyZMn6/1CGR8fj+Dg4Hdj0AdKUlKS0hPZq5Oeng4XF5d3Y9AHjJ+fH4RCIUaOHInx48cr3J88eXKtDuVyPsadm3369MGyZcuwb98+vHjxAq1bt8bq1asVHPffF9988w1ycnIwYMAAREVFvW9zKBQKhfIRQ30sKEopKirCuXPn6tSxsbGBiYnJO7Low+TJkye4evVqnToSieSDPavhQ+LatWt4/PhxnTqNdcYDhfI2oT4WFArlU0PV9xqdWFAoFAqF0ojQiQWFQvnUoM7bFAqFQqFQKBQK5Z1BJxYUCqVejh07Bg6Hg5SUlPdtCuUTJDg4GC1btnzfZlAoFArlDaHO2xQKhdIAysrKsGTJEri4uLyRU/7169dhbW0NHo+H//77D7q6ugo6//zzDxISEnD69GlkZmaisrKyTgf2kpISrFixAqmpqbh79y6qqqpgaWkJDw8PTJ48Gaampq9t77ukseq4oUilUsyfPx+7du3Cw4cPYWhoiL59+yIyMhItWrR4Z3ZQPm1aztrfqOllL/Jo1PQolDeBTiwoFAqlAZSVlTHRk95k0LtlyxYYGxujqKgIKSkpGDVqlILO77//jg0bNqBjx45o1aoVbt26VWt69+7dQ9++ffHgwQMMGzYMY8aMgYaGBjIzM7Fx40bs2rWrzuc/JBqrjhuCTCZDv379cO3aNYwfPx5WVla4c+cO1q5di4MHD+L69evQ1tZ+J7ZQKBTKxwqdWFAolLdOWVkZNDU137cZHwyEEGzduhX+/v7IyspCYmKi0onFuHHjMHPmTAgEAkycOLHWiUFlZSUGDx6MnJwcHDt2TOHwwfnz52Px4sV12vQptVFmZiY6duzYoGf+/vtvnDlzBmvWrMGECRMYedu2bREaGoojR47A29u7sU2lUCiUTwrqY0GhUPDo0SOEhobCyMgIPB4PNjY2+OWXXxT0ZDIZ5s+fDzMzM/D5fLi6uuLOnTssHRcXF9ja2uLcuXNwcnKCpqYmvv32WwDAnj174OHhAVNTU/B4PFhaWmLu3LmoqqqqNQ0HBwcIBAJYWFggJiaG0SktLYWWlhYmT56sYOfDhw/B5XKxcOFCRlZcXIypU6eiZcuW4PF4MDMzQ2BgIPLz8wG8OhQyIiICEokEIpEIWlpacHR0RHp6OpNGdnY2xGIxACAqKgocDgccDqfBB8hlZGQgOzsbvr6+8PX1xfHjx/Hw4UMFPSMjI5UO0du5cycuXbqE7777TumJ5jo6Opg/fz5zXVcblZeXIzIyEq1btwaPx0Pz5s0RHh6O8vJyVpqHDx9Gr169oKurC6FQiLZt2zJpAEBCQgI4HA6ys7NZz8n9dY4dO6a0LI1Rx506dUK3bt0QGxuLkpISlZ6R6xkZGbHk8pDaH8JhhhQKhfKhQ1csKJTPnJycHHTv3h0cDgcTJ06EWCxGWloaRo4ciZKSEkyZMoXRXbRoEdTU1DB9+nRIpVIsWbIEw4cPx+nTp1lpFhQUwN3dHb6+vhgxYgQzWEtISIBQKMS0adMgFApx9OhRREREoKSkBEuXLmWlUVRUhAEDBsDHxwd+fn7YsWMHxo0bBw0NDYSGhkIoFMLb2xtJSUlYvnw5uFwu8+y2bdtACMHw4cMBvJqEODo64vr16wgNDUWXLl2Qn5+PvXv34uHDhzAwMEBJSQk2bNgAPz8/jB49Gk+fPsXGjRvh5uaGf/75B3Z2dhCLxVi3bh3GjRsHb29vDB48GAAa/HU8MTERlpaW+OKLL2BrawtNTU1s27YNM2bMaFA6cvbu3QsACAgIUPkZZW0kk8kwaNAg/PXXXxgzZgzat2+Py5cvY8WKFbh16xZ2794NALh69So8PT3RsWNHREdHg8fj4c6dO8jIyHgt+6vTGHUcFxeHX375BWPHjsW0adMwbNgwjBw5Eo6OjrU+07VrV2hpaeGHH36Anp4e2rZtizt37iA8PBxffPFFnWeolJeXsyZeqk5mKBQK5ZODUCiUz5qRI0cSExMTkp+fz5L7+voSkUhEysrKSHp6OgFA2rdvT8rLyxmdVatWEQDk8uXLjMzZ2ZkAIDExMQp5lZWVKcjCwsKIpqYmefHihUIay5YtY2Tl5eXEzs6OGBoakoqKCkIIIQcPHiQASFpaGivNjh07EmdnZ+Y6IiKCACCpqakK+ctkMkIIIZWVlayyEUJIUVERMTIyIqGhoYwsLy+PACCRkZEKaalCRUUF0dfXJ9999x0j8/f3J506darzuQkTJpDaXtmdO3cmIpFIZRtqa6PNmzcTNTU1cuLECZY8JiaGACAZGRmEEEJWrFhBAJC8vLxa84iPjycASFZWFksu70vp6emMLCgoiJibmzPXb1rHcq5du0amT59OjIyMCABiZWVFFi1aRJ48eaJUf9++fcTExIQAYH5ubm7k6dOndeYTGRnJekb+k0qlb2Q/5dPEfOa+Rv1RKO8CqVSq0nuNboWiUD5jCCHYuXMnBg4cCEII8vPzmZ+bmxukUinOnz/P6IeEhEBDQ4O5ln8BvnfvHitdHo+HkJAQhfyqbyd5+vQp8vPz4ejoiLKyMty4cYOl26RJE4SFhTHXGhoaCAsLQ25uLnMqfN++fWFqaorExERG78qVK8jMzMSIESMY2c6dO9GpUyele+Q5HA4AgMvlMmWTyWQoLCxEZWUlunbtyqqDNyUtLQ0FBQXw8/NjZH5+frh06VK9p7jXRklJSYMdi5W1UXJyMtq3b4927dqx+kKfPn0AgNkWJo9gtWfPHshkstey+V3Qvn17LF26FA8fPsSePXvQvn17/PDDD2jevDm8vLyQmZnJ0heLxejcuTPmz5+P3bt3Y86cOThx4oTSvlyd2bNnQyqVMr9///33bRaLQqFQPljoxIJC+YzJy8tDcXEx4uLiIBaLWT/5YCo3N5fRrxlys2nTpgBebVuqTrNmzVgTEDlXr16Ft7c3RCIRdHR0IBaLmQmAVCpl6ZqamkJLS4sls7KyAgBm376amhqGDx+O3bt3o6ysDMCrbUZ8Ph/Dhg1jnrt79y5sbW3rrY9NmzahY8eO4PP50NfXh1gsxv79+xVsexO2bNkCCwsLZvvQnTt3YGlpCU1NTdYEqSHo6Ojg6dOnDXpGWRvdvn0bV69eVegL8nqX94Wvv/4aPXv2xKhRo2BkZARfX1/s2LHjg51kNGnSBIMGDcKuXbuwefNmaGpqYs+ePTh69Cijc+/ePfTu3RuhoaH49ttv8dVXXyEyMhJr165FSkoK0tLSak2fx+NBR0eH9aNQKJTPEepjQaF8xsgHgiNGjEBQUJBSnY4dO+LatWsAwPJjqA6pcbaCMkfX4uJiODs7Q0dHB9HR0bC0tASfz8f58+cxc+bM1x6UBgYGYunSpdi9ezf8/PywdetWeHp6QiQSNSidLVu2IDg4GF5eXpgxYwYMDQ0ZB/C7d+++lm01KSkpwW+//YYXL16gTZs2Cve3bt2K+fPnM6soqtKuXTtcuHAB//77L5o3b67SM8raSCaToUOHDli+fLnSZ+RpCwQCHD9+HOnp6di/fz8OHDiApKQk9OnTB4cOHQKXy621DDUd9d8F9+/fx6ZNm5CQkICsrCy0bNkS//d//8daNUpISMCLFy/g6enJenbQoEEAXjncu7u7v1O7KRQK5WODTiwolM8YsVgMbW1tVFVV1emcKp9YvAnHjh1DQUEBUlNT4eTkxMizsrKU6j9+/BjPnj1jrVrIw61WP6XZ1tYWnTt3RmJiIszMzPDgwQOsXr2alZalpSWuXLlSp30pKSlo1aoVUlNTWYPiyMhIll5DB/3VSU1NxYsXL7Bu3ToYGBiw7t28eRPff/89MjIylEZ2qouBAwdi27Zt2LJlC2bPnv3a9llaWuLSpUtwdXWtt5xqampwdXWFq6srli9fjgULFuC7775Deno6+vbty6xmFRcXs567f/9+vXa8SR3Lef78OXbt2oVffvkFR48ehYaGBry8vBAbG4u+ffsq5JGTkwNCiMLE5+XLlwBehfSlUCgUSt3QiQWF8hnD5XIxZMgQbN26FVeuXFHYLpSXl8eE/myMvAD26kZFRQXWrl2rVL+yshKxsbGYNm0aoxsbGwuxWAyJRMLSDQgIQHh4OHg8HvT19RW+LA8ZMgTR0dHYtWuXgp8FIQQcDodln3zQefr0aZw6dYq1BUx+1kPNAbMqbNmyBa1atcLYsWMV7pWXl2PRokVITExs8MRi6NChWLhwIebPnw8XFxf06NGDdf/p06dYtGgRK+SsMnx8fPD7779j/fr1GDNmDOve8+fPIZPJoKWlhcLCQujp6bHu29nZMeUAXk1SAOD48ePMvaqqKsTFxdVbnjepYwAYO3Ystm/fDqlUCltbWyxfvhwBAQHQ19ev9RkrKysQQrBjxw4EBwcz8m3btgEAOnfu/Fq2UCg1oSdlUz5l6MSCQvnMWbRoEdLT02Fvb4/Ro0fD2toahYWFOH/+PI4cOYLCwsJGycfBwQFNmzZFUFAQJk2aBA6Hg82bNytso5JjamqKxYsXIzs7G1ZWVkhKSsLFixcRFxcHdXV1lq6/vz/Cw8Oxa9cujBs3TuH+jBkzkJKSgmHDhiE0NBQSiQSFhYXYu3cvYmJi0KlTJ3h6eiI1NRXe3t7w8PBAVlYWYmJiYG1tjdLSUiYtgUAAa2trJCUlwcrKCnp6erC1ta3Xh+Px48dIT0/HpEmTlN7n8Xhwc3NDcnIyfvrpJ6irq+P+/fvYvHkzAODs2bMAgHnz5gEAzM3NmfCy6urqSE1NRd++feHk5AQfHx/07NkT6urquHr1KrZu3YqmTZvWO7EICAjAjh07MHbsWKSnp6Nnz56oqqrCjRs3sGPHDhw8eBBdu3ZFdHQ0jh8/Dg8PD5ibmyM3Nxdr166FmZkZMymysbFB9+7dMXv2bGYisn37dpW+/L9uHcvZunUrvv76a4waNQr29vYqPRMcHIwff/wRYWFhuHDhAmxsbHD+/Hls2LABNjY29HA8CoVCUYW3G5yKQqF8DOTk5JAJEyaQ5s2bE3V1dWJsbExcXV1JXFwcIeR/IUKTk5NZz2VlZREAJD4+npE5OzsTGxsbpflkZGSQ7t27E4FAQExNTUl4eDgTMrZ6+FF5GmfPniU9evQgfD6fmJubkzVr1tRahgEDBhAA5OTJk0rvFxQUkIkTJ5JmzZoRDQ0NYmZmRoKCgpgwuzKZjCxYsICYm5sTHo9HOnfuTPbt26cQCpUQQk6ePEkkEgnR0NBQOSzqsmXLCADyxx9/1KqTkJBAAJA9e/YQQv5X78p+1cPpyikqKiIRERGkQ4cORFNTk/D5fGJra0tmz57NCrFaVxtVVFSQxYsXExsbG8Lj8UjTpk2JRCIhUVFRTJjBP/74g3z11VfE1NSUaGhoEFNTU+Ln50du3brFSuvu3bukb9++hMfjESMjI/Ltt9+Sw4cP1xtulpDXq2M5paWlKutW5+HDhyQ0NJRYWFgQDQ0NYmJiQkaPHl1nWF1lqBqWkUKhUD4WVH2vcQip5XMhhUKhvCdcXFyQn59fr19Edby9vXH58mWFk8AplHdNSUkJRCIRpFIpjRBFoVA+CVR9r9FwsxQK5aPnyZMn2L9/f4NOnqZQKBQKhdK4UB8LCoXy0ZKVlYWMjAxs2LAB6urqrAP13iUVFRX1+qKIRCKlIV4pqkHrmEKhUD586MSCQqF8tPz5558ICQlBixYtsGnTJhgbG78XO06ePInevXvXqRMfH8+KNkRpGLSOKRQK5cOH+lhQKBTKG1JUVIRz587VqWNjYwMTE5N3ZNGnx8dUx9THgkKhfGqo+l6jEwsKhUKhUBoROrGgUCifGtR5m0L5jDh27Bg4HA5SUlLetymfJPL6PXbsGCMLDg5mnQDeEDgcDiZOnNg4xn0GZGdng8PhICEh4X2bQqFQKJQ6oD4WFArlk6KsrAxLliyBi4sLXFxc3rc574THjx8jLi4OXl5ezCnXb4Pg4GBs2rQJ2trayMnJUXCUvn37NqysrAAAS5cuxfTp09+aLfWRnZ0NCwsLAEBKSgqGDBnCuj9nzhxERUUhLy8PBgYG78NEyidKy1n732l+9CRvyocEXbGgUCifFGVlZYiKimKtLrwN1q9fj5s3b77VPFTl8ePHiIqKwsWLF996Xk2aNEFZWRl+++03hXuJiYng8/lv3YaGEh0dXesJ7xQKhUJpPOjEgkKhoKys7H2b8NGhrq4OHo/3vs145/B4PLi6umLbtm0K97Zu3QoPjw/r66mdnR0yMzOxa9eu920KhUKhfPLQiQWF8hHw6NEjhIaGwsjICDweDzY2Nvjll18U9GQyGebPnw8zMzPw+Xy4uroqnETt4uICW1tbnDt3Dk5OTtDU1MS3334LANizZw88PDxgamoKHo8HS0tLzJ07F1VVVbWm4eDgAIFAAAsLC8TExDA6paWl0NLSwuTJkxXsfPjwIbhcLhYuXMjIiouLMXXqVLRs2RI8Hg9mZmYIDAxEfn4+gFfnGEREREAikUAkEkFLSwuOjo5IT09n0sjOzoZYLAYAREVFgcPhgMPhYM6cOSrX9cOHD+Hl5QUtLS0YGhpi6tSpKC8vV9BT5mPx448/wsHBAfr6+hAIBJBIJHX6vSQmJqJt27bg8/mQSCQ4fvy4gk59bX/s2DF88cUXAICQkBCmzNX9EU6fPo3+/ftDJBJBU1MTzs7OyMjIYOXz9OlTTJkyhal/Q0ND9OvXD+fPn1ewyd/fH2lpaSguLmZkZ86cwe3bt+Hv76+0rMXFxZgyZQqaN28OHo+H1q1bY/HixZDJZAp6wcHBEIlE0NXVRVBQECufhuLr6wsrKyuVVy2Sk5MhkUggEAhgYGCAESNG4NGjR6+dP4VCoXxOUB8LCuUDJycnB927d2ccfsViMdLS0jBy5EiUlJRgypQpjO6iRYugpqaG6dOnQyqVYsmSJRg+fDhOnz7NSrOgoADu7u7w9fXFiBEjYGRkBABISEiAUCjEtGnTIBQKcfToUURERKCkpARLly5lpVFUVIQBAwbAx8cHfn5+2LFjB8aNGwcNDQ2EhoZCKBTC29sbSUlJWL58ObhcLvPstm3bQAjB8OHDAbyahDg6OuL69esIDQ1Fly5dkJ+fj7179+Lhw4cwMDBASUkJNmzYAD8/P4wePRpPnz7Fxo0b4ebmhn/++Qd2dnYQi8VYt24dxo0bB29vbwwePBgA0LFjR5Xq+vnz53B1dcWDBw8wadIkmJqaYvPmzTh69KhKz69atQqDBg3C8OHDUVFRge3bt2PYsGHYt2+fwpf8P//8E0lJSZg0aRJ4PB7Wrl2L/v37459//oGtrS0A1dq+ffv2iI6ORkREBMaMGQNHR0cAgIODAwDg6NGjcHd3h0QiQWRkJNTU1BAfH48+ffrgxIkT6NatGwBg7NixSElJwcSJE2FtbY2CggL89ddfuH79Orp06cKyffDgwRg7dixSU1MRGhoK4NVqRbt27RR0gVcrYs7Oznj06BHCwsLQokULnDx5ErNnz8aTJ0+wcuVKAAAhBF999RX++usvjB07Fu3bt8euXbsQFBSkUv0rg8vl4vvvv0dgYCB27drF9AllJCQkICQkBF988QUWLlyInJwcrFq1ChkZGbhw4QJ0dXWVPldeXs6afJaUlLy2vRQKhfJRQygUygfNyJEjiYmJCcnPz2fJfX19iUgkImVlZSQ9PZ0AIO3btyfl5eWMzqpVqwgAcvnyZUbm7OxMAJCYmBiFvMrKyhRkYWFhRFNTk7x48UIhjWXLljGy8vJyYmdnRwwNDUlFRQUhhJCDBw8SACQtLY2VZseOHYmzszNzHRERQQCQ1NRUhfxlMhkhhJDKykpW2QghpKioiBgZGZHQ0FBGlpeXRwCQyMhIhbTqY+XKlQQA2bFjByN79uwZad26NQFA0tPTGXlQUBAxNzdnPV+z/ioqKoitrS3p06cPSw6AACBnz55lZPfv3yd8Pp94e3szMlXanhBCzpw5QwCQ+Ph4lp5MJiNt2rQhbm5uTD3K7bSwsCD9+vVjZCKRiEyYMKGO2nlVZi0tLUIIIUOHDiWurq6EEEKqqqqIsbExiYqKIllZWQQAWbp0KfPc3LlziZaWFrl16xYrvVmzZhEul0sePHhACCFk9+7dBABZsmQJo1NZWUkcHR2Vlq8uqttRWVlJ2rRpQzp16sTUQ2RkJAFA8vLyCCGv2srQ0JDY2tqS58+fM+ns27ePACARERG15iVPq+ZPKpWqbC/l08F85r53+qNQ3gVSqVSl9xrdCkWhfMAQQrBz504MHDgQhBDk5+czPzc3N0ilUtZWlZCQEGhoaDDX8q/X9+7dY6XL4/EQEhKikF/1KD9Pnz5Ffn4+HB0dUVZWhhs3brB0mzRpgrCwMOZaQ0MDYWFhyM3NZQ4y69u3L0xNTZGYmMjoXblyBZmZmRgxYgQj27lzJzp16gRvb28FmzgcDoBXX57lZZPJZCgsLERlZSW6du2qdLvO6/D777/DxMQEQ4cOZWSampoYM2aMSs9Xr7+ioiJIpVI4Ojoqta9Hjx6QSCTMdYsWLfDVV1/h4MGDqKqqanDbK+PixYvM9qSCggLm+WfPnsHV1RXHjx9ntiLp6uri9OnTePz4sUpl9ff3x7Fjx/Dff//h6NGj+O+//2rdBpWcnAxHR0c0bdqUVY6+ffuiqqqK2QL2+++/o0mTJhg3bhzzLJfLxTfffKOSTbUhX7W4dOkSdu/erVTn7NmzyM3Nxfjx41kO6B4eHmjXrh3276890s/s2bMhlUqZ37///vtG9lIoFMrHCt0KRaF8wOTl5aG4uBhxcXGIi4tTqpObm4umTZsCeDU4rY5cXlRUxJI3a9aMNQGRc/XqVXz//fc4evSownYOqVTKujY1NYWWlhZLJg81mp2dje7du0NNTQ3Dhw/HunXrUFZWBk1NTSZy0LBhw5jn7t69qxAOVBmbNm3CsmXLcOPGDbx8+ZKRy8OKvin3799H69atmcmMnLZt26r0/L59+zBv3jxcvHiRtTWmZnoA0KZNGwWZlZUVysrKkJeXBzU1NZXavi5u374NAHVuJZJKpWjatCmWLFmCoKAgNG/eHBKJBAMGDEBgYCBatWql9LkBAwZAW1sbSUlJuHjxIr744gu0bt0a2dnZSu3IzMxk/F9qK8f9+/dhYmICoVDIuq9q/dfF8OHDMXfuXERHR8PLy0vh/v3792vNq127dvjrr79qTZvH432WjvwUCoVSEzqxoFA+YORfk0eMGFHr4LBjx464du0aALD8GKpDajit1jx/AHjlNOvs7AwdHR1ER0fD0tISfD4f58+fx8yZMxWcbFUlMDAQS5cuxe7du+Hn54etW7fC09MTIpGoQels2bIFwcHB8PLywowZM2BoaMg4gN+9e/e1bGtMTpw4gUGDBsHJyQlr166FiYkJ1NXVER8fj61btzY4PVXbXpU0li5dWuv5FvJBvI+PDxwdHbFr1y4cOnQIS5cuxeLFi5Gamgp3d3eF53g8HgYPHoxNmzbh3r17dTrIy2Qy9OvXD+Hh4UrvyyekbxP5qkVwcDD27Nnz1vOjUCiUzxE6saBQPmDEYjG0tbVRVVWFvn371qonn1i8CceOHUNBQQFSU1Ph5OTEyLOyspTqP378GM+ePWOtWty6dQsAWNGSbG1t0blzZyQmJsLMzAwPHjzA6tWrWWlZWlriypUrddqXkpKCVq1aITU1lbUCEBkZydJTtjqgKubm5rhy5QoIIax0VDmvYufOneDz+Th48CDr63V8fLxSfflqQnVu3boFTU1N5su+Km0P1F5mS0tLAICOjk69aQCAiYkJxo8fj/HjxyM3NxddunTB/PnzlU4sgFfboX755ReoqanB19e31nQtLS1RWlparw3m5ub4448/UFpaylq1aKzzQkaMGIF58+YhKioKgwYNUshbnlefPn1Y927evMncp1AoFErt0IkFhfIBw+VyMWTIEGzduhVXrlxhogXJycvLq3V7yevkBbBXNyoqKrB27Vql+pWVlYiNjcW0adMY3djYWIjFYpbvAAAEBAQgPDwcPB4P+vr6CgPVIUOGIDo6Grt27VLws5AP8qvbJx9Inz59GqdOnWJtAdPU1ASA1wpROmDAABw6dAgpKSnMVq2ysrJatyJVh8vlgsPhsELzZmdn17qn/9SpUzh//jwTRenff//Fnj170L9/f6asqra9fHJXs8wSiQSWlpb48ccf4e/vr7DFSJ5GVVUVSktLWatIhoaGMDU1VRpqV07v3r0xd+5c6Ovrw9jYuFY9Hx8fzJkzBwcPHoSbmxvrXnFxMYRCIZo0aYIBAwYgLi4O69atw4wZMwAAVVVVChPR16X6qkVNunbtCkNDQ8TExCA0NJSZHKalpeH69euIiIhoFBsonz70JGzK5wydWFAoHziLFi1Ceno67O3tMXr0aFhbW6OwsBDnz5/HkSNHUFhY2Cj5ODg4oGnTpggKCsKkSZPA4XCwefPmWmP/m5qaYvHixcjOzoaVlRWz1z4uLg7q6uosXX9/f4SHh2PXrl0YN26cwv0ZM2Ywg/nQ0FBIJBIUFhZi7969iImJQadOneDp6YnU1FR4e3vDw8MDWVlZiImJgbW1NUpLS5m0BAIBrK2tkZSUBCsrK+jp6cHW1lZhYK6M0aNHY82aNQgMDMS5c+dgYmKCzZs3M5OVuvDw8MDy5cvRv39/+Pv7Izc3Fz///DNat26NzMxMBX1bW1u4ubmxws0Cr87fkKNq21taWkJXVxcxMTHQ1taGlpYW7O3tYWFhgQ0bNsDd3R02NjYICQlBs2bN8OjRI6Snp0NHRwe//fYbnj59CjMzMwwdOhSdOnWCUCjEkSNHcObMGSxbtqzWMqupqeH777+vt25mzJiBvXv3wtPTE8HBwZBIJHj27BkuX76MlJQUZGdnw8DAAAMHDkTPnj0xa9YsZGdnw9raGqmpqQr+PW+C3Nei5inl6urqWLx4MUJCQuDs7Aw/Pz8m3GzLli0xderURrOBQqFQPlneamwqCoXSKOTk5JAJEyaQ5s2bE3V1dWJsbExcXV1JXFwcIYQw4WaTk5NZz8lDblYP0+ns7ExsbGyU5pORkUG6d+9OBAIBMTU1JeHh4UzI2OqhVuVpnD17lvTo0YPw+Xxibm5O1qxZU2sZBgwYQACQkydPKr1fUFBAJk6cSJo1a0Y0NDSImZkZCQoKYkKtymQysmDBAmJubk54PB7p3Lkz2bdvn9KwrydPniQSiYRoaGg0OPTs/fv3yaBBg4impiYxMDAgkydPJgcOHFAp3OzGjRtJmzZtCI/HI+3atSPx8fFMKNLqACATJkwgW7ZsYfQ7d+7MSl9OfW0vZ8+ePcTa2po0adJEoc0vXLhABg8eTPT19QmPxyPm5ubEx8eH/PHHH4SQV6GCZ8yYQTp16kS0tbWJlpYW6dSpE1m7di0rj+rhZmtDWbhZQgh5+vQpmT17NmndujXR0NAgBgYGxMHBgfz4449MeGJCXvWDgIAAoqOjQ0QiEQkICCAXLlx4o3CzNYmPj2dCwsrDzcpJSkoinTt3Jjwej+jp6ZHhw4eThw8fqpwvIaqHZaRQKJSPBVXfaxxCVDiKlEKhUKrh4uKC/Pz8ev0iquPt7Y3Lly8rnAROoXxqlJSUQCQSQSqVQkdH532bQ6FQKG+Mqu81eo4FhUJ56zx58gT79+9HQEDA+zaFQqFQKBTKW4L6WFAolLdGVlYWMjIysGHDBqirq7MO1HuXVFRU1OuLIhKJlIbhpXxY0LakUCiUDxc6saBQKG+NP//8EyEhIWjRogU2bdpUZ+Sgt8nJkyfRu3fvOnXi4+OVRguifFjQtqRQKJQPF+pjQaFQPnmKiopw7ty5OnVsbGxgYmLyjiyivC4fQ1tSHwsKhfKpoep7jU4sKBQKhUJpROjEgkKhfGpQ520KhUKhUCgUCoXyzqATCwqlBseOHQOHw0FKSsr7NuWj5l3WY3BwMFq2bPnW86F8PMyZM4c5oZ1CoVAo7wbqvE2hUGqlrKwMS5YsgYuLC1xcXN63OZTPgODgYGzatEnpvbS0NPTv3/8dW0T5XGk5a//7NkElshd5vG8TKBQGOrGgUCi1UlZWhqioKACgEwvKO4PH42HDhg0K8k6dOr0HaygUCoWiKnRiQaE0MmVlZdDU1HzfZlA+AWQyGSoqKsDn89+3Ke+UJk2aYMSIEe/bDAqFQqE0EOpjQfnsePToEUJDQ2FkZAQejwcbGxv88ssvCnoymQzz58+HmZkZ+Hw+XF1dcefOHZaOi4sLbG1tce7cOTg5OUFTUxPffvstAGDPnj3w8PCAqakpeDweLC0tMXfuXFRVVdWahoODAwQCASwsLBATE8PolJaWQktLC5MnT1aw8+HDh+ByuVi4cCEjKy4uxtSpU9GyZUvweDyYmZkhMDAQ+fn5AF4dMhYREQGJRAKRSAQtLS04OjoiPT2dSSM7OxtisRgAEBUVBQ6HAw6Hgzlz5jSovlWpxxMnTmDYsGFo0aIFeDwemjdvjqlTp+L58+cK6e3evRu2trbg8/mwtbXFrl27GmRPdU6fPo3+/ftDJBJBU1MTzs7OyMjIYOnI9+rfunULI0aMgEgkglgsxg8//ABCCP7991989dVX0NHRgbGxMZYtW6aQT3l5OSIjI9G6dWumfOHh4SgvL2fpcTgcTJw4EYmJibCxsQGPx8OBAwcAAJmZmXB2doZAIICZmRnmzZuH+Ph4cDgcZGdns9JJS0uDo6MjtLS0oK2tDQ8PD1y9epWlExwcDKFQiEePHsHLywtCoRBisRjTp09X6KMymQyrVq1Chw4dwOfzIRaL0b9/f5w9exYA4OzsXOtqQtu2beHm5lZ/Y6hIQ/pKTQ4fPoxevXpBV1cXQqEQbdu2Zf5e5ajaVhQKhUJRhK5YUD4rcnJy0L17d2YAJxaLkZaWhpEjR6KkpARTpkxhdBctWgQ1NTVMnz4dUqkUS5YswfDhw3H69GlWmgUFBXB3d4evry9GjBgBIyMjAEBCQgKEQiGmTZsGoVCIo0ePIiIiAiUlJVi6dCkrjaKiIgwYMAA+Pj7w8/PDjh07MG7cOGhoaCA0NBRCoRDe3t5ISkrC8uXLweVymWe3bdsGQgiGDx8O4NUkxNHREdevX0doaCi6dOmC/Px87N27Fw8fPoSBgQFKSkqwYcMG+Pn5YfTo0Xj69Ck2btwINzc3/PPPP7Czs4NYLMa6deswbtw4eHt7Y/DgwQCAjh07NqjOVanH5ORklJWVYdy4cdDX18c///yD1atX4+HDh0hOTmb0Dh06hCFDhsDa2hoLFy5EQUEBQkJCYGZm1iCbAODo0aNwd3eHRCJBZGQk1NTUEB8fjz59+uDEiRPo1q0bS//rr79G+/btsWjRIuzfvx/z5s2Dnp4eYmNj0adPHyxevBiJiYmYPn06vvjiCzg5OQF4NSgfNGgQ/vrrL4wZMwbt27fH5cuXsWLFCty6dQu7d+9WsGvHjh2YOHEiDAwM0LJlSzx69Ai9e/cGh8PB7NmzoaWlhQ0bNoDH4ymUa/PmzQgKCoKbmxsWL16MsrIyrFu3Dr169cKFCxdYTu5VVVVwc3ODvb09fvzxRxw5cgTLli2DpaUlxo0bx+iNHDkSCQkJcHd3x6hRo1BZWYkTJ07g77//RteuXREQEIDRo0fjypUrsLW1ZZ47c+YMbt26he+//77B7SOfBMtRV1eHSCRSua/U5OrVq/D09ETHjh0RHR0NHo+HO3fusCaSDW0rOeXl5ayJR0lJSYPLS6FQKJ8EhEL5jBg5ciQxMTEh+fn5LLmvry8RiUSkrKyMpKenEwCkffv2pLy8nNFZtWoVAUAuX77MyJydnQkAEhMTo5BXWVmZgiwsLIxoamqSFy9eKKSxbNkyRlZeXk7s7OyIoaEhqaioIIQQcvDgQQKApKWlsdLs2LEjcXZ2Zq4jIiIIAJKamqqQv0wmI4QQUllZySobIYQUFRURIyMjEhoaysjy8vIIABIZGamQVn00pB6V1dXChQsJh8Mh9+/fZ2R2dnbExMSEFBcXM7JDhw4RAMTc3Fxl22QyGWnTpg1xc3Nj6kRuh4WFBenXrx8ji4yMJADImDFjGFllZSUxMzMjHA6HLFq0iJEXFRURgUBAgoKCGNnmzZuJmpoaOXHiBMuGmJgYAoBkZGQwMgBETU2NXL16laX7zTffEA6HQy5cuMDICgoKiJ6eHgFAsrKyCCGEPH36lOjq6pLRo0eznv/vv/+ISCRiyYOCgggAEh0dzdLt3LkzkUgkzPXRo0cJADJp0iSl9UgIIcXFxYTP55OZM2ey7k+aNIloaWmR0tJShWdrQ25XzZ+8j6vaV+TtJmfFihUEAMnLy6s174a0VXXkedX8SaVSlctN+fAwn7nvo/hRKO8CqVSq0nuNboWifDYQQrBz504MHDgQhBDk5+czPzc3N0ilUpw/f57RDwkJgYaGBnPt6OgIALh37x4rXR6Ph5CQEIX8BAIB8++nT58iPz8fjo6OKCsrw40bN1i6TZo0QVhYGHOtoaGBsLAw5ObmMqcM9+3bF6ampkhMTGT0rly5gszMTNZ+9J07d6JTp07w9vZWsEkefpPL5TJlk8lkKCwsRGVlJbp27cqqg8ZAlXqsXlfPnj1Dfn4+HBwcQAjBhQsXAABPnjzBxYsXERQUBJFIxOj369cP1tbWDbLp4sWLuH37Nvz9/VFQUMD0g2fPnsHV1RXHjx+HTCZjPTNq1Cjm31wuF127dgUhBCNHjmTkurq6aNu2LatsycnJaN++Pdq1a8fqc3369AEA1vYz4NW2oprlOXDgAHr06AE7OztGpqenx6xSyTl8+DCKi4vh5+fHyovL5cLe3l4hLwAYO3Ys69rR0ZFl/86dO8HhcBAZGanwrLw/iUQifPXVV8zqGfBqNSQpKQleXl7Q0tJSeLYu+Hw+Dh8+zPrJt5ip0leUoaurC+DVFsWabSunoW0lZ/bs2ZBKpczv33//bVB5KRQK5VOBboWifDbk5eWhuLgYcXFxiIuLU6qTm5uLpk2bAgBatGjBuieXFxUVseTNmjVjDZzlXL16Fd9//z2OHj2qsDVCKpWyrk1NTRUGX1ZWVgBe+Tp0794dampqGD58ONatW8c4iCcmJoLP52PYsGHMc3fv3sWQIUNqrQc5mzZtwrJly3Djxg28fPmSkVtYWNT7bENQpR4fPHiAiIgI7N27V6F+5XV1//59AECbNm0U8mjbtm2DJkS3b98GAAQFBdWqI5VKGVuVlUMkEoHP58PAwEBBXlBQwMrr+vXrjL9KTXJzc1nXyur//v376NGjh4K8devWrGt5ueQD4ZrUPC1V7i9RnaZNm7La4O7duzA1NYWenp7SNOUEBgYiKSkJJ06cgJOTE44cOYKcnBwEBATU+ZwyuFwu+vbtq/SeKn1FGV9//TU2bNiAUaNGYdasWXB1dcXgwYMxdOhQqKm9+sbW0LaSw+PxlG5Lo1AolM8NOrGgfDbIv1KOGDGi1gFlx44dce3aNQBg+TFUR/5FVk71L6hyiouL4ezsDB0dHURHR8PS0hJ8Ph/nz5/HzJkza/1iWh+BgYFYunQpdu/eDT8/P2zduhWenp6sL/iqsGXLFgQHB8PLywszZsyAoaEh4wB+9+7d17KtNuqrx6qqKvTr1w+FhYWYOXMm2rVrBy0tLTx69AjBwcGvXVd1IU9z6dKlrFWA6giFQta1snKo0kdkMhk6dOiA5cuXK9Vt3rw561pZf1IVebk2b94MY2NjhftNmrBf+bXZ/zq4ubnByMgIW7ZsgZOTE7Zs2QJjY+NaJwivw5v0FYFAgOPHjyM9PR379+/HgQMHkJSUhD59+uDQoUPgcrkNbisKhUKhsKETC8png1gshra2Nqqqquoc7MgnFm/CsWPHUFBQgNTUVMaJFwCysrKU6j9+/BjPnj1jrVrcunULAFjOtra2tujcuTMSExNhZmaGBw8eYPXq1ay0LC0tceXKlTrtS0lJQatWrZCamso6nbjmdpd3cXLx5cuXcevWLWzatAmBgYGM/PDhwyw9c3NzAP/7Kl+dmzdvNihPS0tLAK++4DfmwLe2vC5dugRXV9fXrk9zc3OFSFoAFGTychkaGjZauSwtLXHw4EEUFhbWuWrB5XLh7++PhIQELF68GLt378bo0aMbdfKial+pDTU1Nbi6usLV1RXLly/HggUL8N133yE9PR19+/ZtlLaiUCiUzxk6saB8NnC5XAwZMgRbt25ViF4DvNoqVdsWiNfJC2B/ua6oqMDatWuV6ldWViI2NhbTpk1jdGNjYyEWiyGRSFi6AQEBCA8PB4/Hg76+Ptzd3Vn3hwwZgujoaOzatUvBz4IQAg6Hw7JPPoA6ffo0Tp06xdryIz+Po7i4uKFVoDLK6ooQglWrVrH0TExMYGdnh02bNmHWrFnMKs3hw4dx7do1ZuKhChKJBJaWlvjxxx/h7++vsDrRmH3Bx8cHv//+O9avX48xY8aw7j1//hwymaxeHwQ3Nzf8/PPPuHjxIrPCUlhYyPK3kevp6OhgwYIF6N27N9TV1Vn3X6dcQ4YMwc8//4yoqCiFNqnef4BXfXPFihUICwtDaWlpo59FoWpfUYayiZG8LuURnRqjrSifDvREawql4dCJBeWzYtGiRUhPT4e9vT1Gjx4Na2trFBYW4vz58zhy5AgKCwsbJR8HBwc0bdoUQUFBmDRpEjgcDjZv3qywjUqOqakpFi9ejOzsbFhZWSEpKQkXL15EXFycwuDQ398f4eHh2LVrF8aNG6dwf8aMGUhJScGwYcMQGhoKiUSCwsJC7N27FzExMejUqRM8PT2RmpoKb29veHh4ICsrCzExMbC2tkZpaSmTlkAggLW1NZKSkmBlZQU9PT3Y2toqTMrehHbt2sHS0hLTp0/Ho0ePoKOjg507dyrsnweAhQsXwsPDA7169UJoaCgKCwuxevVq2NjYsOyuDzU1NWzYsAHu7u6wsbFBSEgImjVrhkePHiE9PR06Ojr47bffGqV8AQEB2LFjB8aOHYv09HT07NkTVVVVuHHjBnbs2IGDBw+ia9eudaYRHh6OLVu2oF+/fvjmm2+YcLMtWrRAYWEhM7jX0dHBunXrEBAQgC5dusDX1xdisRgPHjzA/v370bNnT6xZs6ZB9vfu3RsBAQH46aefcPv2bfTv3x8ymQwnTpxA7969MXHiREa3c+fOsLW1ZZygu3Tp0vAKq4OG9JWaREdH4/jx4/Dw8IC5uTlyc3Oxdu1amJmZoVevXgAap60oFArls+atxKSiUD5gcnJyyIQJE0jz5s2Juro6MTY2Jq6uriQuLo4Q8r8wqcnJyaznsrKyCAASHx/PyJydnYmNjY3SfDIyMkj37t2JQCAgpqamJDw8nAkZm56erpDG2bNnSY8ePQifzyfm5uZkzZo1tZZhwIABBAA5efKk0vsFBQVk4sSJpFmzZkRDQ4OYmZmRoKAgJsyuTCYjCxYsIObm5oTH45HOnTuTffv2kaCgIIWwrSdPniQSiYRoaGg0KPRsQ+rx2rVrpG/fvkQoFBIDAwMyevRocunSJQU9QgjZuXMnad++PeHxeMTa2pqkpqYqtVsVLly4QAYPHkz09fUJj8cj5ubmxMfHh/zxxx+MjjyUaM0wpUFBQURLS0shTWV9oqKigixevJjY2NgQHo9HmjZtSiQSCYmKimKF7gNAJkyYUKutjo6OhMfjETMzM7Jw4ULy008/EQDkv//+Y+mmp6cTNzc3IhKJCJ/PJ5aWliQ4OJicPXu2Xvtrhmkl5FV43aVLl5J27doRDQ0NIhaLibu7Ozl37pzC80uWLCEAyIIFC5SWoz5qs0uOqn2lZjn++OMP8tVXXxFTU1OioaFBTE1NiZ+fH7l16xYrfVXbqi5UDctIoVAoHwuqvtc4hNTyCZVCobwTXFxckJ+fX69fRHW8vb1x+fJlpfvuKZ8PU6ZMQWxsLEpLSxvVl+FNWLVqFaZOnYrs7GyFSFqfCyUlJRCJRJBKpQqRuCgUCuVjRNX3Gj3HgkL5yHjy5An279//WmE8KR8vz58/Z10XFBRg8+bN6NWr1wczqSCEYOPGjXB2dv5sJxUUCoXyOUN9LCiUj4SsrCxkZGRgw4YNUFdXZx2o9y6pqKio1xdFJBK9UdjUN6GwsBAVFRW13udyuY3mmP0u6dGjB1xcXNC+fXvk5ORg48aNKCkpwQ8//PC+TcOzZ8+wd+9epKen4/Lly9izZ4+CzqfaLhQKhUL5H3RiQaF8JPz5558ICQlBixYtsGnTJqXnFLwLTp48id69e9epEx8fj+Dg4HdjUA0GDx6MP//8s9b75ubmyM7OfncGNRIDBgxASkoK4uLiwOFw0KVLF2zcuJEVzvh9kZeXB39/f+jq6uLbb7/FoEGDFHQ+1XahUCgUyv+gPhYUCqVBFBUV4dy5c3Xq2NjYwMTE5B1ZxObcuXN1RgkSCATo2bPnO7SIAnxe7UJ9LCgUyqeGqu81OrGgUCgUCqURoRMLCoXyqUGdtylvzLFjx8DhcJCSkvK+TaG8IS4uLnBxcWGus7OzweFwkJCQ8Fbyk/edY8eOvZX03zXBwcGsE9AbQsuWLd/btrD3TUJCAjgcDmuLU82+2BA4HA7mzJnTKLZRKBQKpfGhPhYUigqUlZVhyZIlbzQoolAA4Nq1a9ixY8cbTVZU5eLFi/jxxx/x559/Ijc3F1paWujSpQuGDx+OwMDADyaaFIXyrmg5a//7NqHRoSeEUz4k6MSCQlGBsrIyREVFAcAnMbEwNzfH8+fPFU7tpihn/fr1kMlkjZLWtWvXEBUVBRcXl7c6sdiwYQPGjh0LIyMjBAQEoE2bNnj69Cn++OMPjBw5Ek+ePMG333771vKvjUOHDr3zPCkUCoXybqATC8pbo6ysDJqamu/bDIoSOBwO+Hz++zbjo+Fjm4D9/fffGDt2LHr06IHff/8d2trazL0pU6bg7NmzDTqQsTZkMhkqKioa1Jc0NDTeOF8KhUKhfJhQH4vPmEePHiE0NBRGRkbg8XiwsbHBL7/8oqAnk8kwf/58mJmZgc/nw9XVVeHEZxcXF9ja2uLcuXNwcnKCpqYm8zV0z5498PDwgKmpKXg8HiwtLTF37lxUVVXVmoaDgwMEAgEsLCwQExPD6JSWlkJLSwuTJ09WsPPhw4fgcrlYuHAhIysuLsbUqVPRsmVL8Hg8mJmZITAwEPn5+QBenckQEREBiUQCkUgELS0tODo6Ij09nUkjOzubia8fFRUFDofToL3ecn+DHTt2ICoqCs2aNYO2tjaGDh0KqVSK8vJyTJkyBYaGhhAKhQgJCUF5eblCOlu2bIFEIoFAIICenh58fX3x77//KujFxcXB0tISAoEA3bp1w4kTJxR0avOxuHHjBnx8fCAWiyEQCNC2bVt89913zP379+9j/PjxaNu2LQQCAfT19TFs2LBGCRP68uVLREVFoU2bNuDz+dDX10evXr1w+PBhRic4OBhCoRD37t2Dm5sbtLS0YGpqiujoaNSMQyGTybBy5UrY2NiAz+fDyMgIYWFhSiMTpaWlwdnZGdra2tDR0cEXX3yBrVu3svKtubrw448/wsHBAfr6+hAIBJBIJPX6IyUkJGDYsGEAgN69ezN96dixYwgKCoKBgQFevnyp8NyXX36Jtm3b1luHcuT9NDExkTWpkNO1a1eW34eqZeFwOJg4cSISExNhY2MDHo+HAwcOAACuXr2KPn36QCAQwMzMDPPmzVO6yqNsO2Fubi5GjhwJIyMj8Pl8dOrUCZs2bVKprBcuXIC7uzt0dHQgFArh6uqKv//+W0EvMzMTzs7OLPvi4+NZPiCN2QYUCoXyOUJXLD5TcnJy0L17d2agIBaLkZaWhpEjR6KkpARTpkxhdBctWgQ1NTVMnz4dUqkUS5YswfDhw3H69GlWmgUFBXB3d4evry9GjBgBIyMjAK8GU0KhENOmTYNQKMTRo0cRERGBkpISLF26lJVGUVERBgwYAB8fH/j5+WHHjh0YN24cNDQ0EBoaCqFQCG9vbyQlJWH58uWsPeLbtm0DIQTDhw8H8GoS4ujoiOvXryM0NBRdunRBfn4+9u7di4cPH8LAwAAlJSXYsGED/Pz8MHr0aDx9+hQbN26Em5sb/vnnH9jZ2UEsFmPdunUYN24cvL29MXjwYABAx44dG1TnCxcy7pVDAABWy0lEQVQuhEAgwKxZs3Dnzh2sXr0a6urqUFNTQ1FREebMmYO///4bCQkJsLCwQEREBPPs/Pnz8cMPP8DHxwejRo1CXl4eVq9eDScnJ1y4cAG6uroAgI0bNyIsLAwODg6YMmUK7t27h0GDBkFPTw/Nmzev077MzEw4OjpCXV0dY8aMQcuWLXH37l389ttvmD9/PgDgzJkzOHnyJHx9fWFmZobs7GysW7cOLi4uuHbt2hutUM2ZMwcLFy7EqFGj0K1bN5SUlODs2bM4f/48+vXrx+hVVVWhf//+6N69O5YsWYIDBw4gMjISlZWViI6OZvTCwsKQkJCAkJAQTJo0CVlZWVizZg0uXLiAjIwMZhUiISEBoaGhsLGxwezZs6Grq4sLFy7gwIED8Pf3r9XeVatWYdCgQRg+fDgqKiqwfft2DBs2DPv27YOHh/I9z05OTpg0aRJ++uknfPvtt2jfvj0AoH379ggICMCvv/6KgwcPwtPTk3nmv//+w9GjRxEZGalSPZaVleGPP/6Ak5OTyqdfN6QsR48exY4dOzBx4kQYGBigZcuW+O+//9C7d29UVlZi1qxZ0NLSQlxcnEqHJD5//hwuLi64c+cOJk6cCAsLCyQnJyM4OBjFxcVKPyLIuXr1KhwdHaGjo4Pw8HCoq6sjNjYWLi4u+PPPP2Fvbw/g1UcU+URu9uzZ0NLSwoYNG8Dj8VjpvW4blJeXsz4GlJSU1FtuCoVC+SQhlM+SkSNHEhMTE5Kfn8+S+/r6EpFIRMrKykh6ejoBQNq3b0/Ky8sZnVWrVhEA5PLly4zM2dmZACAxMTEKeZWVlSnIwsLCiKamJnnx4oVCGsuWLWNk5eXlxM7OjhgaGpKKigpCCCEHDx4kAEhaWhorzY4dOxJnZ2fmOiIiggAgqampCvnLZDJCCCGVlZWsshFCSFFRETEyMiKhoaGMLC8vjwAgkZGRCmnVh7webW1tmTIQQoifnx/hcDjE3d2dpd+jRw9ibm7OXGdnZxMul0vmz5/P0rt8+TJp0qQJI6+oqCCGhobEzs6OVaa4uDgCgFU3WVlZBACJj49nZE5OTkRbW5vcv3+flY+8rghR3panTp0iAMivv/6qUOb09PTaK6YGnTp1Ih4eHnXqBAUFEQDkm2++Ydnn4eFBNDQ0SF5eHiGEkBMnThAAJDExkfX8gQMHWPLi4mKira1N7O3tyfPnz1m61csdFBTEahNCFOuioqKC2Nrakj59+rDk5ubmJCgoiLlOTk5WWjdVVVXEzMyMfP311yz58uXLCYfDIffu3aulVthcunSJACCTJ09WSb8hZQFA1NTUyNWrV1nyKVOmEADk9OnTjCw3N5eIRCICgGRlZTFyZ2dnVl9cuXIlAUC2bNnCyr9Hjx5EKBSSkpISVv7V/wa9vLyIhoYGuXv3LiN7/Pgx0dbWJk5OTozsm2++IRwOh1y4cIGRFRQUED09PZZ9r9sGkZGRBIDCTyqVKtWnvD/MZ+775H4UyrtAKpWq9F6jW6E+Qwgh2LlzJwYOHAhCCPLz85mfm5sbpFIpzp8/z+iHhISw9kU7OjoCAO7du8dKl8fjISQkRCG/6l8tnz59ivz8fDg6OqKsrAw3btxg6TZp0gRhYWHMtYaGBsLCwpCbm8scyta3b1+YmpoiMTGR0bty5QoyMzMxYsQIRrZz50506tQJ3t7eCjZxOBwAAJfLZcomk8lQWFiIyspKdO3alVUHjUFgYCBrr769vT0IIQgNDWXp2dvb499//0VlZSUAIDU1FTKZDD4+Pqy2MjY2Rps2bZhtW2fPnkVubi7Gjh3Laq/g4GCIRKI6bcvLy8Px48cRGhqq8JVbXlcAuy1fvnyJgoICtG7dGrq6um9cX7q6urh69Spu375dr+7EiRNZ9k2cOBEVFRU4cuQIACA5ORkikQj9+vVj1ZlEIoFQKGTq7PDhw3j69ClmzZql4CdQvdzKqF4XRUVFkEqlcHR0fO16UFNTw/Dhw7F37148ffqUkScmJsLBwQEWFhYqpSP/Wq5sC1RtNKQszs7OsLa2Zsl+//13dO/eHd26dWNkYrGYWT2si99//x3Gxsbw8/NjZOrq6pg0aRJKS0trPa27qqoKhw4dgpeXF1q1asXITUxM4O/vj7/++oupiwMHDqBHjx6ws7Nj9PT09BTse902mD17NqRSKfNTtkWRQqFQPgfoxOIzJC8vD8XFxYiLi4NYLGb95BOD3NxcRr/mQLNp06YAoLBXvVmzZkodM69evQpvb2+IRCLo6OhALBYzEwCpVMrSNTU1hZaWFktmZWUFAMw+aPl//rt370ZZWRmAV//x8/l8Zv86ANy9exe2trb11semTZvQsWNHZl+/WCzG/v37FWx7U2rWo3ywX3OLkkgkgkwmY/K/ffs2CCFo06aNQntdv36daav79+8DANq0acNKT11dnTXwUoZ8klhffT1//hwRERFo3rw5eDweDAwMIBaLUVxc/Mb1FR0djeLiYlhZWaFDhw6YMWMGMjMzFfTU1NQUylOzj9y+fRtSqRSGhoYKdVZaWsrU2d27d1UqtzL27duH7t27g8/nQ09Pj9ky9yb1EBgYiOfPn2PXrl0AgJs3b+LcuXMICAhQOQ35wUXVB8b10ZCyKBtc379/X6HfAVDJJ0H+rJoa+78j+TYxeb+uSV5eHsrKypTm0b59e8hkMmaAf//+fbRu3VpBT5nsddqAx+NBR0eH9aNQKJTPEepj8Rkid6gcMWIEgoKClOp07NgR165dA4BaY92TGs6yyvZTFxcXw9nZGTo6OoiOjoalpSX4fD7Onz+PmTNnvnYIz8DAQCxduhS7d++Gn58ftm7dCk9Pz3q/zNdky5YtCA4OhpeXF2bMmAFDQ0PGAVw+6GwsaqvH+upXJpOBw+EgLS1Nqa5QKGw8I+vhm2++QXx8PKZMmYIePXpAJBKBw+HA19f3jcOxOjk54e7du9izZw8OHTqEDRs2YMWKFYiJicGoUaMalJZMJoOhoSFrVas6cmf81+XEiRMYNGgQnJycsHbtWpiYmEBdXR3x8fEsp++GYm1tDYlEgi1btiAwMBBbtmyBhoYGfHx8VE6jdevWaNKkCS5fvqySfkPLoorfxMdMY7QBhUKhfK7QicVniFgshra2NqqqqtC3b99a9eQTizfh2LFjKCgoQGpqKpycnBh5VlaWUv3Hjx/j2bNnrFWLW7duAQArKo+trS06d+6MxMREmJmZ4cGDB1i9ejUrLUtLy3pDaqakpKBVq1ZITU1lbX2p6aRZ37aYt4mlpSUIIbCwsGC+zCvD3NwcwKuv9X369GHkL1++RFZWFjp16lTrs/IVAFXqKygoCMuWLWNkL168QHFxsSpFqRc9PT2EhIQgJCQEpaWlcHJywpw5c1gTC5lMhnv37rHqomYfsbS0xJEjR9CzZ886B8KWlpYAXpVb2dfr2ti5cyf4fD4OHjzIcgCOj4+v99n6+lJgYCCmTZuGJ0+eYOvWrfDw8GBWCVVBU1MTffr0wdGjR/Hvv//W67T/JmWRY25urnQL282bN1V6NjMzEzKZjLVqId8mKe/XNRGLxdDU1FSax40bN6CmpsaU3dzcXCGSHQClMuDN24BCoVA+V+hWqM8QLpeLIUOGYOfOnUoHknl5eY2aF8Be3aioqMDatWuV6ldWViI2NpalGxsbC7FYDIlEwtINCAjAoUOHsHLlSujr68Pd3Z11f8iQIbh06RKzpaE6cnuU2Xf69GmcOnWKpS+PdtRYA+iGMHjwYHC5XERFRSmsEhFCUFBQAOBVCFGxWIyYmBhUVFQwOgkJCfXaLRaL4eTkhF9++QUPHjxQyEMOl8tVsGH16tUKoYNfB3k55AiFQrRu3Vpp6N01a9aw7FuzZg3U1dXh6uoKAPDx8UFVVRXmzp2r8GxlZSVTH19++SW0tbWxcOFCvHjxgqVXs5zV4XK54HA4rHJnZ2dj9+7d9ZZTPmmurU38/PzA4XAwefJk3Lt3j+U3pCqRkZEghCAgIAClpaUK98+dO8eEc32TssgZMGAA/v77b/zzzz+MLC8vr9YVo5rP/vfff0hKSmJklZWVWL16NYRCIZydnZU+x+Vy8eWXX2LPnj2scMc5OTnYunUrevXqxWxJcnNzw6lTp3Dx4kVGr7CwsFb7GqMNKBQK5XOErlh8pixatAjp6emwt7fH6NGjYW1tjcLCQpw/fx5HjhxBYWFho+Tj4OCApk2bIigoCJMmTQKHw8HmzZtrHbSZmppi8eLFyM7OhpWVFZKSknDx4kXExcUpHFLm7++P8PBw7Nq1C+PGjVO4P2PGDKSkpGDYsGEIDQ2FRCJBYWEh9u7di5iYGHTq1Amenp5ITU2Ft7c3PDw8kJWVhZiYGFhbW7MGZAKBANbW1khKSoKVlRX09PRga2v7WnvzG4qlpSXmzZuH2bNnIzs7G15eXtDW1kZWVhZ27dqFMWPGYPr06VBXV8e8efMQFhaGPn364Ouvv0ZWVhbi4+Pr9bEAgJ9++gm9evVCly5dMGbMGFhYWCA7Oxv79+9nBmSenp7YvHkzRCIRrK2tcerUKRw5cgT6+vpvXE5ra2u4uLhAIpFAT08PZ8+eRUpKCstRGwD4fD4OHDiAoKAg2NvbIy0tDfv378e3337LbHFydnZGWFgYFi5ciIsXL+LLL7+Euro6bt++jeTkZKxatQpDhw6Fjo4OVqxYgVGjRuGLL76Av78/mjZtikuXLqGsrKzWsxQ8PDywfPly9O/fH/7+/sjNzcXPP/+M1q1bK/ULqY6dnR24XC4WL14MqVQKHo+HPn36wNDQEMCrSV7//v2RnJwMXV3dWkPX1oWDgwN+/vlnjB8/Hu3atWOdvH3s2DHs3bsX8+bNe+OyyAkPD8fmzZvRv39/TJ48mQk3K1+NqIsxY8YgNjYWwcHBOHfuHFq2bImUlBRkZGRg5cqVdTqhz5s3D4cPH0avXr0wfvx4NGnSBLGxsSgvL8eSJUtY9m3ZsgX9+vXDN998w4SbbdGiBQoLCxVWkRqjDSgfJtmLaFtSKG+VtxKTivJRkJOTQyZMmECaN29O1NXVibGxMXF1dSVxcXGEkP+FDE1OTmY9pyxUqbOzM7GxsVGaT0ZGBunevTsRCATE1NSUhIeHMyFjq4fclKdx9uxZ0qNHD8Ln84m5uTlZs2ZNrWUYMGAAAUBOnjyp9H5BQQGZOHEiadasGdHQ0CBmZmYkKCiICbMrk8nIggULiLm5OeHxeKRz585k3759SsOLnjx5kkgkEqKhodGg0LO11WN8fDwBQM6cOcOSy0NXykOnytm5cyfp1asX0dLSIlpaWqRdu3ZkwoQJ5ObNmyy9tWvXEgsLC8Lj8UjXrl3J8ePHFUJ8KmtDQgi5cuUK8fb2Jrq6uoTP55O2bduSH374gblfVFREQkJCiIGBAREKhcTNzY3cuHFDIaTq64SbnTdvHunWrRvR1dUlAoGAtGvXjsyfP58VojcoKIhoaWmRu3fvki+//JJoamoSIyMjEhkZSaqqqhTSjIuLIxKJhAgEAqKtrU06dOhAwsPDyePHj1l6e/fuJQ4ODkQgEBAdHR3SrVs3sm3bNla+NfvDxo0bSZs2bQiPxyPt2rUj8fHxTNtVp2bdEELI+vXrSatWrQiXy1VaTzt27CAAyJgxY1SuP2WcO3eO+Pv7E1NTU6Kurk6aNm1KXF1dyaZNm1j1pWpZAJAJEyYozSszM5M4OzsTPp9PmjVrRubOnUs2btxYb7hZQl69i+T9SkNDg3To0EGhb8rzr/l3d/78eeLm5kaEQiHR1NQkvXv3Vvo+uHDhAnF0dCQ8Ho+YmZmRhQsXkp9++okAIP/995+C/pu0gaphGSkUCuVjQdX3GoeQOtb7KZR3iIuLC/Lz8+vd518db29vXL58uda90pRPi+DgYKSkpCjd3vMpsWfPHnh5eeH48eNMeGdK4zNlyhTExsaitLRUITDCm7RBSUkJRCIRpFIpjRBFoVA+CVR9r1EfC8pHy5MnT7B///4GheKkUD4G1q9fj1atWqFXr17v25RPhufPn7OuCwoKsHnzZvTq1UtptDXaBhQKhdJwqI8F5aMjKysLGRkZ2LBhA9TV1VkH6r1LKioq6vVFEYlEn3x4zvp4/vx5vWc76OnpKT0D5XNj+/btyMzMxP79+7Fq1SqFvf9SqVRhgFwTY2Pjt2niR0uPHj3g4uKC9u3bIycnBxs3bkRJSQl++OEHll59bUChUCiU2qETC8pHx59//omQkBC0aNECmzZtem8DqZMnT6J379516sTHxyM4OPjdGPSBkpSUpPRE9uqkp6fDxcXl3Rj0AePn5wehUIiRI0di/PjxCvcnT55cq0O5HLq7VTkDBgxASkoK4uLiwOFw0KVLF2zcuJEVBhuovw0oFAqFUjvUx4JCeU2Kiopw7ty5OnVsbGxgYmLyjiz6MHny5AmuXr1ap45EIqHnBKjAtWvX8Pjx4zp16jqbhvJuoD4WFArlU0PV9xqdWFAoFAqF0ojQiQWFQvnUoM7bFAqFQqFQKBQK5Z3x2Uwsjh07Bg6Hg5SUlPdtCgWvQst+jnvqa5Y7OzsbHA4HCQkJ782mt8WcOXOo4+v/53Pt7xQKhUL5vKDO258hZWVlWLJkCR3sUD5KXFxc0LJlS2Yylp2dDQsLC+Y+h8OBrq4u7O3tERERgR49erwnS98ujx8/RlxcHLy8vGBnZ/e+zWExZ84cREVFIS8vDwYGBu/bnDcmODgY2dnZOHbs2Ps2hdJAWs7a/75NeOvQ08QpHxJ0YvEZUlZWhqioKAB4bxOLQ4cOvZd8PzTMzc3x/PlzqKurv29TGp3vv/8es2bNemf5+fn5YcCAAaiqqsKtW7ewdu1a9O7dG2fOnEGHDh3emR3KeBv9/fHjx4iKikLLli0/uIkFhUKhUD5P6MRCRcrKyqCpqfm+zfjokdfjh3RmASEEL168eC/nTXA4HPD5/Hee77ugSZMmaNLk3b1iunTpghEjRjDXjo6OcHd3x7p167B27dp3ZocyVOnvL168gIaGBtTU3u8O1WfPnkFLS+u92kChUCiUj5NPwsfi0aNHCA0NhZGREXg8HmxsbPDLL78o1ZXJZJg/fz7MzMzA5/Ph6uqKO3fusHRcXFxga2uLc+fOwcnJCZqamvj2228BAHv27IGHhwdMTU3B4/FgaWmJuXPnoqqqqtY0HBwcIBAIYGFhgZiYGEantLQUWlpamDx5soKdDx8+BJfLxcKFCxlZcXExpk6dipYtW4LH48HMzAyBgYHIz88H8OrAtoiICEgkEohEImhpacHR0RHp6elMGtnZ2RCLxQCAqKgocDgccDgczJkzR6W6lvuqJCUl4dtvv4WxsTG0tLQwaNAg/PvvvyrXY81tWPJ0d+zYgaioKDRr1gza2toYOnQopFIpysvLMWXKFBgaGkIoFCIkJATl5eWs/OLj49GnTx8YGhqCx+PB2toa69atUyhDy5Yt4enpiYMHD6Jr164QCASIjY2Fs7MzOnXqpLTcbdu2hZubm0p1JCcuLg6WlpYQCATo1q0bTpw4oaCjzMciMzMTwcHBaNWqFfh8PoyNjREaGoqCggKF548dO4auXbuCz+fD0tISsbGxSn0bOBwOJk6ciN27d8PW1pb5Ozlw4IBCmhcuXIC7uzt0dHQgFArh6uqKv//+m6Xz8uVLREVFoU2bNuDz+dDX10evXr1w+PBhRkeZHYcPH0avXr2gq6sLoVCItm3bMn2isXF0dAQA3L17lyUvLi7GlClT0Lx5c/B4PLRu3RqLFy+GTCZj6W3fvh0SiQTa2trQ0dFBhw4dsGrVKuZ+QkICOBwOjh8/jrCwMOjr60NHRweBgYEoKipipVVbf9++fTu+//57NGvWDJqamigpKUFhYSGmT5+ODh06QCgUQkdHB+7u7rh06RLr+S+++AIAEBISwvwdV+9HycnJkEgkEAgEMDAwwIgRI/Do0SOWXcHBwRAKhbh79y4GDBgAbW1tDB8+HJGRkVBXV0deXp5CvY4ZMwa6urp48eKFCq3wP27fvo0hQ4bA2NgYfD4fZmZm8PX1ZR2eWF//kNd5dnY2K215fdbcqnT69Gn0798fIpEImpqacHZ2RkZGBkvn6dOnmDJlCvNeNTQ0RL9+/XD+/PkGlY9CoVAon8CKRU5ODrp3784MnMRiMdLS0jBy5EiUlJRgypQpLP1FixZBTU0N06dPh1QqxZIlSzB8+HCcPn2apVdQUAB3d3f4+vpixIgRMDIyAvDqPzahUIhp06ZBKBTi6NGjiIiIQElJCZYuXcpKo6ioCAMGDICPjw/8/PywY8cOjBs3DhoaGggNDYVQKIS3tzeSkpKwfPlycLlc5tlt27aBEILhw4cDeDUJcXR0xPXr1xEaGoouXbogPz8fe/fuxcOHD2FgYICSkhJs2LABfn5+GD16NJ4+fYqNGzfCzc0N//zzD+zs7CAWi7Fu3TqMGzcO3t7eGDx4MACgY8eODar3+fPng8PhYObMmcjNzcXKlSvRt29fXLx4kfXlv7Z6rI2FCxdCIBBg1qxZuHPnDlavXg11dXWoqamhqKgIc+bMwd9//42EhARYWFggIiKCeXbdunWwsbHBoEGD0KRJE/z2228YP348ZDIZJkyYwMrn5s2b8PPzQ1hYGEaPHo22bdtCKBRi9OjRuHLlCmxtbRndM2fO4NatW/j+++9Vrp+NGzciLCwMDg4OmDJlCu7du4dBgwZBT08PzZs3r/PZw4cP4969ewgJCYGxsTGuXr2KuLg4XL16FX///TczWL9w4QL69+8PExMTREVFoaqqCtHR0czEsSZ//fUXUlNTMX78eGhra+Onn37CkCFD8ODBA+jr6wMArl69CkdHR+jo6CA8PBzq6uqIjY2Fi4sL/vzzT9jb2wN4NWlYuHAhRo0ahW7duqGkpARnz57F+fPn0a9fP6X5X716FZ6enujYsSOio6PB4/Fw584dhYFeYyEffFY/H6OsrAzOzs549OgRwsLC0KJFC5w8eRKzZ8/GkydPsHLlSgCv2sDPzw+urq5YvHgxAOD69evIyMhQ+BAwceJE6OrqYs6cObh58ybWrVuH+/fvM4Pdupg7dy40NDQwffp0lJeXQ0NDA9euXcPu3bsxbNgwWFhYICcnh5n4Xrt2Daampmjfvj2io6MRERGBMWPGMJMoBwcHAK/eUyEhIfjiiy+wcOFC5OTkYNWqVcjIyMCFCxegq6vL2FBZWQk3Nzf06tULP/74IzQ1NdGjRw9ER0cjKSkJEydOZHQrKiqQkpKCIUOGNGilraKiAm5ubigvL8c333wDY2NjPHr0CPv27UNxcTFEIlGj94+jR4/C3d0dEokEkZGRUFNTYz4+nDhxAt26dQMAjB07FikpKZg4cSKsra1RUFCAv/76C9evX0eXLl1Uyqu8vJz1oaOkpOS1bKZQKJSPHvKRM3LkSGJiYkLy8/NZcl9fXyISiUhZWRkhhJD09HQCgLRv356Ul5czeqtWrSIAyOXLlxmZs7MzAUBiYmIU8pOnV52wsDCiqalJXrx4oZDGsmXLGFl5eTmxs7MjhoaGpKKighBCyMGDBwkAkpaWxkqzY8eOxNnZmbmOiIggAEhqaqpC/jKZjBBCSGVlJatshBBSVFREjIyMSGhoKCPLy8sjAEhkZKRCWvUhr8dmzZqRkpISRr5jxw4CgKxatUqhDpTVo7OzM6t88nRtbW2ZuiGEED8/P8LhcIi7uzvr+R49ehBzc3OWTFnbuLm5kVatWrFk5ubmBAA5cOAAS15cXEz4fD6ZOXMmSz5p0iSipaVFSktLFdJXRkVFBTE0NCR2dnas9oiLiyMAWOXOysoiAEh8fHyd5di2bRsBQI4fP87IBg4cSDQ1NcmjR48Y2e3bt0mTJk1IzT9tAERDQ4PcuXOHkV26dIkAIKtXr2ZkXl5eRENDg9y9e5eRPX78mGhraxMnJydG1qlTJ+Lh4VFnPURGRrLsWLFiBQFA8vLy6nyuocjrMCoqiuTl5ZH//vuPnDhxgnzxxRcEAElOTmZ0586dS7S0tMitW7dYacyaNYtwuVzy4MEDQgghkydPJjo6OqSysrLWfOPj4wkAIpFIWH12yZIlBADZs2cPI6utv7dq1UqhvV+8eEGqqqoUysjj8Uh0dDQjO3PmjELfIeR//c/W1pY8f/6cke/bt48AIBEREYwsKCiIACCzZs1SKF+PHj2Ivb09S5aamkoAkPT09FrrhZD/tb28rS9cuKDQFjVRpX/I6zwrK4sll9en3C6ZTEbatGlD3NzcmPcjIa/+tiwsLEi/fv0YmUgkIhMmTKizPPUhL2/Nn1QqfaN0KW+O+cx9n/yPQnkXSKVSld5rH/VWKEIIdu7ciYEDB4IQgvz8fObn5uYGqVSqsJwdEhLC2u8s/9J37949lh6Px0NISIhCntW/xj99+hT5+flwdHREWVkZbty4wdJt0qQJwsLCmGsNDQ2EhYUhNzeXObG5b9++MDU1RWJiIqN35coVZGZmsvaL79y5E506dYK3t7eCTfKvolwulymbTCZDYWEhKisr0bVr10Zf1g8MDIS2tjZzPXToUJiYmOD3339n6dVWj3WlW92R2d7eHoQQhIaGsvTs7e3x77//orKykpFVbxupVIr8/Hw4Ozvj3r17rO0WAGBhYaGwtUkkEuGrr75iVosAoKqqCklJSfDy8lJ53/nZs2eRm5uLsWPHsvpacHAwRCJRvc9XL8eLFy+Qn5+P7t27AwDTjlVVVThy5Ai8vLxgamrK6Ldu3Rru7u5K0+3bty8sLS2Z644dO0JHR4fp+1VVVTh06BC8vLzQqlUrRs/ExAT+/v7466+/mC+xurq6uHr1Km7fvl1veeTIv5Lv2bNHYdtRYxAZGQmxWAxjY2NmdW/ZsmUYOnQoo5OcnAxHR0c0bdqU9b7o27cvqqqqcPz4ccbWZ8+esbZ21caYMWNYfXbcuHFo0qSJwt+CMoKCghR8e3g8HuNnUVVVhYKCAmZbkCp/x/L+N378eNaqgoeHB9q1a4f9+xWj5IwbN05BFhgYiNOnT7O2kiUmJqJ58+Zwdnau147qyPv9wYMHUVZWplSnMfvHxYsXcfv2bfj7+6OgoIBp52fPnsHV1RXHjx9n8tDV1cXp06frPdG8LmbPng2pVMr8am4LpVAolM+Fj3pikZeXh+LiYsTFxUEsFrN+8sFsbm4u65kWLVqwruXbJGruiW7WrJlSh8urV6/C29sbIpEIOjo6EIvFzASg5uDV1NRUYTBqZWUF4H/bNNTU1DB8+HDs3r2b+Q83MTERfD4fw4YNY567e/cua3tObWzatAkdO3Zk9r2LxWLs379fwbY3pU2bNqxrDoeD1q1bK+x9rq0ea6Nm+8gHJDW3D4lEIshkMla5MjIy0LdvX2hpaUFXVxdisZjZn61sYqGMwMBAPHjwgPGHOHLkCHJychAQEKByGe7fvw9AsY7U1dVZA/baKCwsxOTJk2FkZASBQACxWMzYKy9Hbm4unj9/jtatWys8r0wGKNYt8Kr/y/t+Xl4eysrK0LZtWwW99u3bQyaTMQOm6OhoFBcXw8rKCh06dMCMGTOQmZlZZ7m+/vpr9OzZE6NGjYKRkRF8fX2xY8eORptkjBkzBocPH8Zvv/2GqVOn4vnz5wq+T7dv38aBAwcU3hd9+/YF8L/3xfjx42FlZQV3d3eYmZkhNDRUqT8KoNjOQqEQJiYmCn8LylDWD2UyGVasWIE2bdqAx+PBwMAAYrEYmZmZKv0dy/ufsnZs164dc19OkyZNYGZmpqD79ddfg8fjMR89pFIp9u3bh+HDhzf4fBILCwtMmzYNGzZsgIGBAdzc3PDzzz+zytOY/UM+4Q0KClJo6w0bNqC8vJzJe8mSJbhy5QqaN2+Obt26Yc6cOQofmuqDx+NBR0eH9aNQKJTPkY/ax0L+H86IESMQFBSkVKem70B1P4bqyL9Qy1EWIai4uBjOzs7Q0dFBdHQ0LC0twefzcf78ecycOfO1B0iBgYFYunQpdu/eDT8/P2zduhWenp4qfd2uzpYtWxAcHAwvLy/MmDEDhoaGjAN4TQfWd0VDIy3V1j71tdvdu3fh6uqKdu3aYfny5WjevDk0NDTw+++/Y8WKFQptU5tdbm5uMDIywpYtW+Dk5IQtW7bA2NiYGXi+C3x8fHDy5EnMmDEDdnZ2EAqFkMlk6N+//xsNwlXt+6rg5OSEu3fvYs+ePTh06BA2bNiAFStWICYmBqNGjVL6jEAgwPHjx5Geno79+/fjwIEDSEpKQp8+fXDo0KFa7VOVNm3aMO3k6ekJLpeLWbNmoXfv3ujatSuAV++Mfv36ITw8XGka8om/oaEhLl68iIMHDyItLQ1paWmIj49HYGAgNm3a9EZ2VkdZP1ywYAF++OEHhIaGYu7cudDT04OamhqmTJnyVlZ6qq+QVKdp06bw9PREYmIiIiIikJKSgvLyctZKakNYtmwZgoODmT4zadIkLFy4EH///TfMzMxU6h+1TWhqTiDl9bR06dJaQ/EKhUIAr/7eHB0dsWvXLhw6dAhLly7F4sWLkZqaWuvqH4VCoVCU81FPLMRiMbS1tVFVVfVOBn7Hjh1DQUEBUlNT4eTkxMizsrKU6j9+/FghdOOtW7cAvIpMJMfW1hadO3dGYmIizMzM8ODBA6xevZqVlqWlJa5cuVKnfSkpKWjVqhVSU1NZ/wFHRkay9BrjNOSaW2AIIbhz506DncAbi99++w3l5eXYu3cv68t89YhYqsDlcuHv74+EhAQsXrwYu3fvxujRoxs06DU3Nwfwqo769OnDyF++fImsrKxaI08Br1bO/vjjD0RFRbEc02vWt6GhIfh8vkJEMwBKZaogFouhqamJmzdvKty7ceMG1NTUWCtHenp6CAkJQUhICEpLS+Hk5IQ5c+bUOrEAXq3Qubq6wtXVFcuXL8eCBQvw3XffIT09vdH/hr/77jusX78e33//PbPaYGlpidLSUpXy0tDQwMCBAzFw4EDIZDKMHz8esbGx+OGHH1irQrdv30bv3r2Z69LSUjx58gQDBgx4LbtTUlLQu3dvbNy4kSUvLi5mHTZX29+xvP/dvHmT1f/kMvl9VQgMDMRXX32FM2fOIDExEZ07d4aNjY3Kz9ekQ4cO6NChA77//nucPHkSPXv2RExMDObNmweg/v4hX2EuLi5mpVtzFUa+5U9HR0eltjYxMcH48eMxfvx45ObmokuXLpg/fz6dWFAoFEoD+agnFlwuF0OGDMHWrVsVIvkAr7Z21BYh53XzA9hfeCsqKmqNkV9ZWYnY2FhMmzaN0Y2NjYVYLIZEImHpBgQEIDw8HDweD/r6+gr/oQ0ZMgTR0dHYtWuXgp8FIQQcDodln3zQcfr0aZw6dYo12Jafx1HzP+eG8Ouvv2L27NmMn0VKSgqePHmCmTNnvnaab4KytpFKpYiPj29wWgEBAVixYgXCwsJQWlra4C+0Xbt2hVgsRkxMDMunJyEhod46V1YOAEy0oup6ffv2xe7du/H48WPGz+LOnTtIS0trkL3V0/zyyy+xZ88eZGdnM5PfnJwcbN26Fb169WK2eBQUFDCRpIBXX39bt25d597ywsJC6OnpsWTyr8k1Qwc3Brq6uggLC8OSJUtw8eJF2NnZwcfHB3PmzMHBgwcVfGyKi4shFArRpEkThfKpqakxk+aatsbFxSEkJITxs1i3bh0qKytfe1DK5XIV2j85ORmPHj1iTWjkHyxq9qmuXbvC0NAQMTExCA0NBY/HAwCkpaXh+vXrrAlrfbi7u8PAwACLFy/Gn3/+qRD5TlVKSkqgqanJOtekQ4cOUFNTY+pTlf4hnzAcP36cuVdVVYW4uDjWcxKJBJaWlvjxxx/h7+/PrE7Ikf/fUFVVhdLSUtbqsKGhIUxNTd9Kn6S8e+ip1BTKu+WjnlgAr8LHpqenw97eHqNHj4a1tTUKCwtx/vx5HDlyBIWFhY2Wl4ODA5o2bYqgoCBMmjQJHA4HmzdvrnUriampKRYvXozs7GxYWVkhKSkJFy9eRFxcnMJJy/7+/ggPD8euXbswbtw4hfszZsxASkoKhg0bhtDQUEgkEhQWFmLv3r2IiYlBp06d4OnpidTUVHh7e8PDwwNZWVmIiYmBtbU1SktLmbQEAgGsra2RlJQEKysr6OnpwdbWViUfDjl6enro1asXQkJCkJOTg5UrV6J169YYPXp0A2q08fjyyy+ZL8zyCcH69ethaGiIJ0+eNCitzp07w9bWFsnJyWjfvr3KISflqKurY968eQgLC0OfPn3w9ddfIysrC/Hx8fX6WOjo6MDJyQlLlizBy5cv0axZMxw6dEjpqticOXNw6NAh9OzZE+PGjUNVVRXWrFkDW1tbXLx4sUE2y5k3bx5zlsD48ePRpEkTxMbGory8HEuWLGH0rK2t4eLiAolEAj09PZw9e5YJ2Vkb0dHROH78ODw8PGBubo7c3FysXbsWZmZm6NWr12vZWx+TJ0/GypUrsWjRImzfvh0zZszA3r174enpieDgYEgkEjx79gyXL19GSkoKsrOzYWBggFGjRqGwsBB9+vSBmZkZ7t+/j9WrV8POzg7t27dn5VFRUQFXV1f4+Pjg5s2bWLt2LXr16oVBgwa9ls2enp6Ijo5GSEgIHBwccPnyZSQmJir0HUtLS+jq6iImJgba2trQ0tKCvb09LCwssHjxYoSEhMDZ2Rl+fn5MuNmWLVti6tSpKtuirq4OX19frFmzBlwuF35+fq9VpqNHj2LixIkYNmwYrKysUFlZic2bNzMfhwDV+oeNjQ26d++O2bNnMxOR7du3s4I4AK8mghs2bIC7uztsbGwQEhKCZs2a4dGjR0hPT4eOjg5+++03PH36FGZmZhg6dCg6deoEoVCII0eO4MyZM1i2bNlrlZVCoVA+a95WWKp3SU5ODpkwYQJp3rw5UVdXJ8bGxsTV1ZXExcUxOvJwhDXDHSoL9+ns7ExsbGyU5pWRkUG6d+9OBAIBMTU1JeHh4UzI2OohGOVpnP1/7d15VBTH2j/w7zCBmQEERAZhRNkMEtxAVIyIQFww4IYKEVFZ3BPcImr0vS4YA6LBN0YvKNEgl2CiuEdFRUXMdUFUjFtEIqAChlUWxUCE+v3Bb/plGEA22Xw+53BOqK7ufqqqJV3dVdU3brCPP/6YCYVCpq+vz3bs2FFrORwdHRkAduXKlRq35+XlMR8fH9atWzempKTE9PT0mIeHB7fUbkVFBfP392f6+vpMIBAwCwsLduLECebh4SG3NOuVK1eYpaUlU1JSatDSs9J6/Pnnn9mqVauYtrY2E4lEzMnJiT158kQmb131WNvym9XbR7q8ZEJCgkx69eUsGWPs+PHjrF+/fkwoFDIDAwMWGBjIfvzxR7nlKfX19d+6VKp0yVB/f/8689UlODiYGRoaMoFAwAYOHMguXbokV+6arr/09HTm7OzMNDQ0mLq6OnNxcWGZmZk1ttP58+eZhYUFU1JSYsbGxmz37t1s2bJlTCgUyuQDUOOSmvr6+szDw0Mm7datW8zBwYGpqqoyZWVlZm9vL3dNbty4kQ0ePJhpaGgwkUjETE1N2TfffCOz7Gr15WbPnz/PJkyYwCQSCVNSUmISiYS5ubnJLf3aUNI63LJlS43bPT09GZ/P55baLS4uZqtWrWI9e/ZkSkpKTEtLiw0dOpR9++23XPwHDx5ko0ePZtra2kxJSYn16NGDzZs3jz1//pw7rvTajIuLY3PnzmWdO3dmqqqqzN3dneXl5cnEUN/rnbHK5WaXLVvGdHV1mUgkYtbW1uzq1atyx2CMsWPHjjEzMzNuieGq19H+/fuZhYUFEwgETFNTk7m7u7P09HSZ/T08PJiKikqd9Xv9+nUGgI0ePbrOfFVV//eZkpLCvL29mbGxMRMKhUxTU5PZ29uzc+fOcfvU9/p4/PgxGzlyJBMIBKxr165s9erVLCYmpsZlcBMTE9mkSZNYly5dmEAgYPr6+szV1ZWdP3+eMVa5BPjy5ctZ//79WadOnZiKigrr378/Cw4OrndZa1LfZRkJIaS9qO/fNR5jjZi5Sd7Kzs4Oubm5b50XUZWzszPu3r3b6DHyLeHixYuwt7dHVFSUzDKeHc22bduwdOlSpKWl1biaUls2ceLEBi8FSxpO+hG6hIQEbnJ4R/T777/D3Nwc//nPfxq0Otr7rKioCOrq6igsLKQVogghHUJ9/6616+VmO5Lnz5/j5MmT9D/uNoAxhj179sDW1rbNdypev34t83tycjJOnToFOzu71gmIdDg//PADVFVVMWnSpNYOhRBCSBvX7udYtHepqam4fPkydu/eDUVFRZkP6rWksrKyt85Haejyt+3Nq1evcPz4ccTGxuLu3bs4duyYXJ78/HyUlZXVegw+n9+sCwa8jZGRETw9PWFkZIQnT54gJCQESkpKtS6n2pbl5OTILRtalZKSktzkXvLu/Prrr3jw4AFCQ0Ph4+NT7w9EEkIIeX9Rx6KVxcXFwcvLCz169EB4eDh0dHRaJY4rV67ILJlZk7CwMJllcjuanJwcTJs2DRoaGli9enWNk28nTZqEuLi4Wo+hr69frw+jNZcxY8bg559/xl9//QWBQICPP/4Y/v7+ch9taw8GDRokt2xoVba2trh48WLLBfSeW7hwIbKysuDo6Ag/P7/WDocQQkg7QHMsCIDK7yfcvHmzzjy9e/eGrq5uC0XUNt28eVPuK+1ViUQiWFtbt2BEHcfly5flhnZV1blzZ7llmglpi2iOBSGko6nv3zXqWBBCCCHNiDoWhJCOhiZvE0IIaXf27t0LHo/XokMKCSGENA+aY0EIIYSQds/gq5OtHUKroK+Lk7aE3lgQQgghhBBCmow6FoQQ8p569epVa4fwzr0PZSSEkLaCOhaEEPL/rV+/HjweD3/++Sc8PT2hoaEBdXV1eHl5oaSkBACQlpYGHo+HvXv3yu3P4/Gwfv16ueM9evQI06dPh7q6OsRiMdasWQPGGJ49e4YJEyZATU0NOjo6CAoKanDMBgYGGDt2LM6ePQtzc3MIhUKYmZnh8OHDMvmkcxfi4uLw+eefQ1tbG3p6etz24OBg9O7dGwKBABKJBF988QUKCgrkzhcfHw9HR0d07twZKioq6NevH7Zt2yaT5+HDh5gyZQo0NTUhFAoxcOBAHD9+XO5Y9+/fxyeffAKRSAQ9PT1s3LgRFRUVcvmq12vVsnt6eta7jNHR0bCxsYGKigo6deoEJycn3L9/X+aYf/31F7y8vKCnpweBQABdXV1MmDCB5nwQQkg90BwLQgipxtXVFYaGhggICMCtW7ewe/duaGtrIzAwsFHH++yzz/DRRx9h06ZNOHnyJDZu3AhNTU3s2rULn3zyCQIDAxEZGQlfX18MGjQIw4cPb9Dxk5OT8dlnn2H+/Pnw8PBAWFgYXFxccPr0aYwaNUom7+effw6xWIy1a9dyT/PXr18PPz8/jBw5EgsWLEBSUhJCQkKQkJCAy5cvQ1FREQAQExODsWPHQldXF4sXL4aOjg7++OMPnDhxAosXLwZQ2VmwtrZGt27d8NVXX0FFRQUHDhzAxIkTcejQITg7OwOovIG3t7fHmzdvuHyhoaEQiUSNquO3lTEiIgIeHh5wcHBAYGAgSkpKEBISgmHDhiExMZH7Rs/kyZNx//59LFy4EAYGBsjOzkZMTAyePn1a63d8SktLUVpayv1eVFTU5DIQQkh7RB0LQgipxsLCAnv27OF+z8vLw549exrdsRg8eDB27doFAJg7dy4MDAywbNkyBAQEYOXKlQAANzc3SCQS/Pjjjw3uWDx69AiHDh3CpEmTAACzZs2CqakpVq5cKdex0NTUxPnz58Hn8wFUfhgyICAAo0ePRnR0NBQUKl9km5qawsfHBz/99BO8vLxQXl6OefPmQVdXF7dv34aGhgZ3zKqrli9evBg9evRAQkICBAIBgMob/WHDhmHlypVcxyIwMBA5OTmIj4/H4MGDAQAeHh7N8nHH6mV8+fIlFi1ahNmzZyM0NJTL5+HhgV69esHf3x+hoaEoKCjAlStXsGXLFvj6+nL5Vq1aVef5AgIC6COChBACGgpFCCFy5s+fL/O7jY0N8vLyGv0kevbs2dx/8/l8DBw4EIwxzJo1i0vX0NBAr169kJKS0uDjSyQS7oYdANTU1DBz5kwkJibir7/+ksk7Z84c7oYbAM6dO4eysjIsWbKE61RI86mpqeHkycqVdhITE5GamoolS5bIdCqAyqFKAJCfn48LFy7A1dUVxcXFyM3NRW5uLvLy8uDg4IDk5GRkZGQAAE6dOoUhQ4ZwnQoAEIvFcHd3b3D5q6texpiYGBQUFMDNzY2LKTc3F3w+H1ZWVoiNjQVQ+YFLJSUlXLx4sc4PYVa3atUqFBYWcj/Pnj1rchkIIaQ9ojcWhBBSTY8ePWR+79y5MwA06GazruOpq6tDKBRCS0tLLj0vL6/Bx+/Zsyd3cy9lYmICoHJOiI6ODpduaGgok+/JkycAgF69esmkKykpwcjIiNv++PFjAECfPn1qjePPP/8EYwxr1qzBmjVrasyTnZ2Nbt264cmTJ7CyspLbXj2OxqhexuTkZADAJ598UmN+6ceeBAIBAgMDsWzZMnTt2hVDhgzB2LFjMXPmTJk6rE4gEHBvZwgh5H1GHQtCCKmm6tPuqhhjcjfwUuXl5Q06Xl3neJeaYw5DbaQTr319feHg4FBjnp49ezbb+Wqr8+pllMYVERFRYwfhgw/+73+FS5Yswbhx43D06FGcOXMGa9asQUBAAC5cuAALC4tmi50QQjoi6lgQQkgDSN9eVF8xSfpkvzVI3xRU7fQ8evQIAGqdcCylr68PAEhKSoKRkRGXXlZWhtTUVIwcORIAYGxsDAC4d+8el1addH9FRcVa81Q9r/RNQlVJSUlyaZ07d5ar77KyMjx//rzOc0hJY9fW1n5rXNL8y5Ytw7Jly5CcnAxzc3MEBQXhp59+qtf5CCHkfUVzLAghpAHU1NSgpaWFS5cuyaQHBwe3UkRAZmYmjhw5wv1eVFSE//znPzA3N69zCA8AjBw5EkpKSvj+++9l3pbs2bMHhYWFcHKq/KrvgAEDYGhoiO+++07uJl+6n7a2Nuzs7LBr164ab/pzcnK4/3Z0dMS1a9dw/fp1me2RkZFy+xkbG8vVd2hoaJ1viapycHCAmpoa/P398c8//9QaV0lJCf7++2+5c3fq1Elm1SdCCCE1ozcWhBDSQLNnz8amTZswe/ZsDBw4EJcuXeLeELQGExMTzJo1CwkJCejatSt+/PFHZGVlISws7K37isVirFq1Cn5+fhgzZgzGjx+PpKQkBAcHY9CgQZg+fToAQEFBASEhIRg3bhzMzc3h5eUFXV1dPHz4EPfv38eZM2cAAP/+978xbNgw9O3bF3PmzIGRkRGysrJw9epVpKen4/fffwcArFixAhERERgzZgwWL17MLTerr6+PO3fuyMQ4e/ZszJ8/H5MnT8aoUaPw+++/48yZM3JzVGqjpqaGkJAQzJgxAwMGDMDUqVMhFovx9OlTnDx5EtbW1tixYwcePXqEESNGwNXVFWZmZvjggw9w5MgRZGVlYerUqQ1pEtIK0jY5tXYIhLz3qGNBCCENtHbtWuTk5ODgwYM4cOAAPv30U0RHR0NbW7tV4vnwww+xfft2LF++HElJSTA0NMT+/ftrnedQ3fr16yEWi7Fjxw4sXboUmpqamDt3Lvz9/blvWACVT/5jY2Ph5+eHoKAgVFRUwNjYGHPmzOHymJmZ4caNG/Dz88PevXuRl5cHbW1tWFhYYO3atVw+XV1dxMbGYuHChdi0aRO6dOmC+fPnQyKRyKyWBVSu8pSamoo9e/bg9OnTsLGxQUxMDEaMGFHvOpo2bRokEgk2bdqELVu2oLS0FN26dYONjQ28vLwAAN27d4ebmxvOnz+PiIgIfPDBBzA1NcWBAwcwefLkep+LEELeVzz2rmcKEkIIeWcMDAzQp08fnDhxorVDIf9fUVER1NXVUVhYyK04RQgh7Vl9/67RHAtCCCGEEEJIk9FQKEIIaYNycnLqnJyspKQETU3NFoyIEEIIqRt1LAghpA0aNGhQnUvY2tra4uLFiy0XECGEEPIW1LEghJA2KDIyEq9fv651u/R7GmlpaS0UESGEEFI36lgQQkgbZG1t3dohEEIIIQ1Ck7cJIYQQQgghTUYdC9KmXbx4ETweDwcPHmztUNq1lqxHT09PGBgYvPN9WsPevXvB4/Ha3fAjafu/L3My2ms7EUJIe0dDoQhpJ0pKSrB582bY2dnBzs6utcPp0Pz9/WFmZoaJEye2+Lnf53Zev349/Pz8atwWEhKC+fPnt3BELc/gq5OtHQJpZ+iL46QtoY4FIe1ESUkJd9PV0W44f/jhB1RUVLR2GBx/f39MmTJFrmMxY8YMTJ06FQKB4J2duyO3c32FhIRAVVVVJs3KyqqVoiGEEFJf1LEgHVpJSQmUlZVbOwzyFoqKiq0dQr3w+Xzw+fzWDqPDmzJlCrS0tFo7DEIIIQ1EcyxIq8rIyIC3tze6du0KgUCA3r1748cff5TLV1FRgW+++QZ6enoQCoUYMWIE/vzzT5k8dnZ26NOnD27evInhw4dDWVkZq1evBgAcO3YMTk5OkEgkEAgEMDY2xtdffy33AbKqxxg6dChEIhEMDQ2xc+dOLs/Lly+hoqKCxYsXy8WZnp4OPp+PgIAALq2goABLly6FgYEBBAIB9PT0MHPmTOTm5gIAysrKsHbtWlhaWkJdXR0qKiqwsbFBbGwsd4y0tDSIxWIAgJ+fH3g8Hng8HtavX9+g+q5PPf72229wcXFBjx49IBAI0L17dyxdurTGpU+PHj2KPn36QCgUok+fPjhy5EiD4pGqPsciLS0NPB4P3377LUJDQ2FsbAyBQIBBgwYhISFBbl9VVVWkpKTAwcEBKioqkEgk2LBhAxhjMnm//fZbDB06FF26dIFIJIKlpaXcvBMej4dXr14hPDycq2dPT08AtY/dj46Oho2NDVRUVNCpUyc4OTnh/v37NcaZkZGBiRMnQlVVFWKxGL6+vtx12BztnJ6ejokTJ0JFRQXa2tpYunQpSktL5fLVp53DwsLA4/GQmJgot7+/vz/4fD4yMjIAAMnJyZg8eTJ0dHQgFAqhp6eHqVOnorCwsN6xv82dO3fg6ekJIyMjCIVC6OjowNvbG3l5eW/d98aNG3BwcICWlhb379rb21smT0VFBb777jv07t0bQqEQXbt2xbx58/DixYtmKwMhhHRk9MaCtJqsrCwMGTIEPB4PPj4+EIvFiI6OxqxZs1BUVIQlS5ZweTdt2gQFBQX4+vqisLAQmzdvhru7O+Lj42WOmZeXh08//RRTp07F9OnT0bVrVwCVN4Sqqqr48ssvoaqqigsXLmDt2rUoKirCli1bZI7x4sULODo6wtXVFW5ubjhw4AAWLFgAJSUleHt7Q1VVFc7Ozti/fz+2bt0q8wT7559/BmMM7u7uACo7ITY2Nvjjjz/g7e2NAQMGIDc3F8ePH0d6ejq0tLRQVFSE3bt3w83NDXPmzEFxcTH27NkDBwcHXL9+Hebm5hCLxQgJCcGCBQvg7OyMSZMmAQD69evXoDqvTz1GRUWhpKQECxYsQJcuXXD9+nVs374d6enpiIqK4vKdPXsWkydPhpmZGQICApCXlwcvLy/o6ek1KKa67Nu3D8XFxZg3bx54PB42b96MSZMmISUlReYtR3l5OcaMGYMhQ4Zg8+bNOH36NNatW4c3b95gw4YNXL5t27Zh/PjxcHd3R1lZGX755Re4uLjgxIkTcHKqHKccERGB2bNnY/DgwZg7dy4AwNjYuNYYIyIi4OHhAQcHBwQGBqKkpAQhISEYNmwYEhMTZTpM5eXlcHBwgJWVFb799lucO3cOQUFBMDY2xoIFC5rczq9fv8aIESPw9OlTLFq0CBKJBBEREbhw4YJc3vq085QpU/DFF18gMjISFhYWMvtHRkbCzs4O3bp1Q1lZGRwcHFBaWoqFCxdCR0cHGRkZOHHiBAoKCqCurl6v+KXy8/Nlfufz+ejcuTNiYmKQkpICLy8v6Ojo4P79+wgNDcX9+/dx7do18Hi8Go+XnZ2N0aNHQywW46uvvoKGhgbS0tJw+PBhmXzz5s3D3r174eXlhUWLFiE1NRU7duxAYmIiLl++XOubtdLSUpnOW1FRUYPKSwghHQWPVX+kR0gLmT17Nk6dOoW7d++iS5cuXLqbmxuio6Px/PlzxMfHw97eHh999BFu374NJSUlAMD333+PxYsX4+7du+jTpw+AyrcNcXFx2LlzJ+bNmydzrtevX0MkEsmkzZ8/HxEREcjPz+fGzEuPERQUhC+//BJA5RsFKysrZGZmIj09HYqKijh79iwcHBwQHR2NMWPGcMfs378/OnfuzK2+s27dOmzYsAGHDx+Gs7OzzPkZY+DxeCgvL0d5eTlXNqDyLYepqSmcnJywZ88eAEBubi7EYjHWrVvX4DcVFy9erHc91lRXmzZtwurVq5GWloYePXoAACwsLJCVlYU//viDu3GMiYnB6NGjoa+v36AVeTw9PXHx4kVun7S0NBgaGqJLly5ITk7mPgZ3/PhxTJgwAb/++ivGjh3L7RseHo6FCxfi+++/B1BZt+PGjUNMTAwyMjK4YTXVy/bPP/9gwIAB0NbWxvnz57l0VVVVTJkyBXv37pWJU3rTmZqaCgMDA7x8+RLdu3eHi4sLQkNDuXxZWVno1asXXF1duXRpnBs2bMCaNWu4vAMGDICCggJu3LgBoGntvG3bNixZsgQHDhyAi4sLgMrhgP3798eff/6J2NhYbt5Gfdt52rRpiIuLw7Nnz6CgUPmSOzExEQMGDEBYWBg8PT1x+/ZtWFhYICoqClOmTGlQzFXVNnlbej3VFPMvv/wCNzc3XLp0CTY2NgDk2+no0aNwdnZGQkICBg4cWOO5//vf/8LGxgaRkZGYNm0al37mzBmMGTNGLr0+cRcWFkJNTa3e5Qdo8jZpOJq8TVpCUVER1NXV3/p3jYZCkVbBGMOhQ4cwbtw4MMaQm5vL/Tg4OKCwsBC3bt3i8nt5ecnceEtvIFJSUmSOKxAI4OXlJXe+qjcjxcXFyM3NhY2NDUpKSvDw4UOZvB988IFMx0RJSQnz5s1DdnY2bt68CQAYOXIkJBIJIiMjuXz37t3DnTt3MH36dC7t0KFD6N+/v1ynAgD3dJXP53Nlq6ioQH5+Pt68eYOBAwfK1EFzqE89Vq2rV69eITc3F0OHDgVjjBsS8/z5c9y+fRseHh4yT6NHjRoFMzOzZov3s88+4zoVtcUr5ePjw/239C1YWVkZzp07V2PZXrx4gcLCQtjY2DS6nmNiYlBQUAA3NzeZa5jP58PKykpmOJtU9ZWNbGxsaixPY5w6dQq6uroyN/fKysrcm5eq6tPOADBz5kxkZmbKlCUyMhIikQiTJ08GAO4aOHPmDEpKSppcjkOHDiEmJob7kf47qxrz33//jdzcXAwZMgQA6mxDDQ0NAMCJEyfwzz//1JgnKioK6urqGDVqlExbWlpaQlVVtca2lFq1ahUKCwu5n2fPnjW0yIQQ0iHQUCjSKnJyclBQUIDQ0FCZJ71VZWdnczeV0qenUtL06mOfu3XrJnPjLHX//n3861//woULF+SGKVQfAy6RSKCioiKTZmJiAqDySfqQIUOgoKAAd3d3hISEcBPEIyMjIRQKuSfFAPD48WPu5qsu4eHhCAoKwsOHD2VufAwNDd+6b0PUpx6fPn2KtWvX4vjx43L1K62rJ0+eAAA+/PBDuXP06tWr2TpE9W13BQUFGBkZyaRVbTOpEydOYOPGjbh9+7bM0JXahtC8TXJyMgDgk08+qXF79ac6QqGQm0Mh1blz52Ybw//kyRP07NlTrjy9evWSy1ufdgYqO4u6urqIjIzEiBEjUFFRgZ9//hkTJkxAp06dAFRep19++SW2bt2KyMhI2NjYYPz48Zg+fXqDh0EBwPDhw2ucvJ2fnw8/Pz/88ssvyM7OrjXm6mxtbTF58mT4+fnhf//3f2FnZ4eJEydi2rRp3NvK5ORkFBYWQltbu8ZjVD9fVQKB4J2uFEYIIe0FdSxIq5AuLTp9+nR4eHjUmKdfv3548OABANS6Ek/1kXzVh0kAlcOKbG1toaamhg0bNsDY2BhCoRC3bt3CypUrG73M6cyZM7FlyxYcPXoUbm5u2LdvH8aOHdvgG6mffvoJnp6emDhxIpYvXw5tbW1uAvjjx48bFVtt3laP5eXlGDVqFPLz87Fy5UqYmppCRUUFGRkZ8PT0bPElYevb7vXx22+/Yfz48Rg+fDiCg4Ohq6sLRUVFhIWFYd++fY2KT1ofERER0NHRkdv+wQeyf2LbyopSDWlnPp+PadOm4YcffkBwcDAuX76MzMxMmTdzABAUFARPT08cO3YMZ8+exaJFixAQEIBr164127wbV1dXXLlyBcuXL4e5uTlUVVVRUVGBMWPG1HltSj8Oee3aNfz66684c+YMvL29ERQUhGvXrnHH0dbWlnkLWVX1DiEhhBB51LEgrUIsFqNTp04oLy/HyJEja80n7Vg0xcWLF5GXl4fDhw9j+PDhXHpqamqN+TMzM/Hq1SuZtxaPHj0CAJmJuH369IGFhQUiIyOhp6eHp0+fYvv27TLHMjY2xr179+qM7+DBgzAyMsLhw4dlnjSvW7dOJl9jn6o3xN27d/Ho0SOEh4dj5syZXHpMTIxMPn19fQD/98S+qqSkpHcbZA0qKiqQkpLCvaUA5Nvs0KFDEAqFOHPmjMzT5bCwMLnj1beupZO6tbW167yOG6Ip7ayvr4979+5x83ekqrdJfdtZaubMmQgKCsKvv/6K6OhoiMViODg4yOXr27cv+vbti3/961+4cuUKrK2tsXPnTmzcuLHRZZJ68eIFzp8/Dz8/P6xdu5ZLr+karM2QIUMwZMgQfPPNN9i3bx/c3d3xyy+/YPbs2TA2Nsa5c+dgbW1d4wMKQgghb0cdC9Iq+Hw+Jk+ejH379uHevXvcxGGpnJycZntCKH1KXPUpd1lZGYKDg2vM/+bNG+zatUtm8vauXbsgFothaWkpk3fGjBlYsWIFBAIBunTpgk8//VRm++TJk7FhwwYcOXKk1snbVeOT3gzGx8fj6tWrMkOBpN/jKCgoaGgV1FtNdcUYw7Zt22Ty6erqwtzcHOHh4fjqq69kJm8/ePCA63i0pB07dshM3t6xYwcUFRUxYsQIAJVlk06Wl0pLS8PRo0fljqWiolKvenZwcICamhr8/f1hb28vt2pQY67jprSzo6Mjzp49i4MHD8pM3q4+3LC+7SzVr18/9OvXD7t378a1a9fg4eEh8zamqKgIysrKMml9+/aFgoJCjUvdNkZNMQPAd99999Z9X7x4AQ0NDZnOlrm5OQBw8bm6uiI4OBhff/01/P39ZfZ/8+YNXr58yc3VeJdoIi4hpD2jjgVpNZs2bUJsbCysrKwwZ84cmJmZIT8/H7du3cK5c+fklpxsrKFDh6Jz587w8PDAokWLwOPxEBERUetwGolEgsDAQKSlpcHExAT79+/H7du3ERoaKnfjOG3aNKxYsQJHjhzBggUL5LYvX76cu8nz9vaGpaUl8vPzcfz4cezcuRP9+/fH2LFjuVWjnJyckJqaip07d8LMzAwvX77kjiUSiWBmZob9+/fDxMQEmpqa6NOnj1ynrClMTU1hbGwMX19fZGRkQE1NDYcOHapxDkBAQACcnJwwbNgweHt7Iz8/H9u3b0fv3r1l4m4JQqEQp0+fhoeHB6ysrBAdHY2TJ09i9erV3I29k5MTtm7dijFjxmDatGnIzs7Gv//9b/Ts2RN37tyROZ6lpSXOnTuHrVu3QiKRwNDQsMYvP6upqSEkJAQzZszAgAEDMHXqVIjFYjx9+hQnT56EtbU1duzY0aCyNKWd58yZgx07dmDmzJm4efMmdHV1ERERIfeRyIa0s9TMmTPh6+sLAHLDoC5cuAAfHx+4uLjAxMQEb968QUREBPcAoTmoqalh+PDh2Lx5M/755x9069YNZ8+erfXNY1Xh4eEIDg6Gs7MzjI2NUVxcjB9++AFqampwdHQEUDkPY968eQgICMDt27cxevRoKCoqIjk5GVFRUdi2bVuTVrwihJD3AiOkFWVlZbEvvviCde/enSkqKjIdHR02YsQIFhoayhhjLDY2lgFgUVFRMvulpqYyACwsLIxLs7W1Zb17967xPJcvX2ZDhgxhIpGISSQStmLFCnbmzBkGgMXGxsod48aNG+zjjz9mQqGQ6evrsx07dtRaBkdHRwaAXblypcbteXl5zMfHh3Xr1o0pKSkxPT095uHhwXJzcxljjFVUVDB/f3+mr6/PBAIBs7CwYCdOnGAeHh5MX19f5lhXrlxhlpaWTElJiQFg69atqzWuqhpSjw8ePGAjR45kqqqqTEtLi82ZM4f9/vvvcvkYY+zQoUPso48+YgKBgJmZmbHDhw/XGPfbVN9HGteWLVvk8lYvt4eHB1NRUWGPHz9mo0ePZsrKyqxr165s3bp1rLy8XGbfPXv2sA8//JAJBAJmamrKwsLC2Lp161j1P4UPHz5kw4cPZyKRiAFgHh4ejDHGwsLCGACWmpoqkz82NpY5ODgwdXV1JhQKmbGxMfP09GQ3btyQi7O6ms7f2HZmjLEnT56w8ePHM2VlZaalpcUWL17MTp8+LXetN6SdGWPs+fPnjM/nMxMTE7ltKSkpzNvbmxkbGzOhUMg0NTWZvb09O3fuXL3jZuz/6iInJ6fG7enp6czZ2ZlpaGgwdXV15uLiwjIzM+XqqHo73bp1i7m5ubEePXowgUDAtLW12dixY2XaRyo0NJRZWloykUjEOnXqxPr27ctWrFjBMjMz612OwsJCBoAVFhY2qPyEENJW1ffvGn3HgpAq7OzskJub+9Z5EVU5Ozvj7t27cl+wJi3D09MTBw8ebPG3JO+b3Nxc6OrqYu3atTLf4SDy6rveOyGEtBf1/btGQ6EIaYLnz5/j5MmT+J//+Z/WDoWQd2rv3r0oLy/HjBkzWjuUNk/6vI6+wE0I6Sikf8/e9j6COhaENEJqaiouX76M3bt3Q1FRUe5L3y2lrKzsrXNR1NXVW22Vm/z8fJSVldW6nc/n0zKe9dCa7XzhwgU8ePAA33zzDSZOnCizMlp9FRYW4vXr13XmqWm53vaquLgYANC9e/dWjoQQQppXcXFxncvqU8eCkEaIi4uDl5cXevTogfDw8Fa7Kbpy5Qrs7e3rzBMWFgZPT8+WCaiaSZMmIS4urtbt+vr6Mh+wIzVrzXbesGEDt3Rs9eWU62vx4sUIDw+vM09HGpUrkUjw7NkzdOrUqUWWiW5PioqK0L17dzx79oyGiTUDqs/mRfVZO8YYiouLIZFI6sxHcywIacdevHiBmzdv1pmnd+/e0NXVbaGIZN28ebPOlYZEIhGsra1bMKL2qa2389s8ePAAmZmZdeZpru+AkLaN5p80L6rP5kX12XTUsSCEEEJIi6Abt+ZF9dm8qD6bTqG1AyCEEEIIIYS0f9SxIIQQQkiLEAgEWLduHQQCQWuH0iFQfTYvqs+mo6FQhBBCCCGEkCajNxaEEEIIIYSQJqOOBSGEEEIIIaTJqGNBCCGEEEIIaTLqWBBCCCGEEEKajDoWhBBCCCGEkCajjgUhhBBC3omCggLMnTsXYrEYKioqsLe3x61bt+q17/Xr1/H555/D0tISioqK4PF47zjatqO0tBQrV66ERCKBSCSClZUVYmJi6rVvRkYGXF1doaGhATU1NUyYMAEpKSnvOOK2rbH1mZSUhKVLl2Lo0KEQCoXg8XhIS0t79wG3Y9SxIIQQQkizq6iogJOTE/bt2wcfHx9s3rwZ2dnZsLOzQ3Jy8lv3P3XqFHbv3g0ejwcjI6MWiLjt8PT0xNatW+Hu7o5t27aBz+fD0dER//3vf+vc7+XLl7C3t0dcXBxWr14NPz8/JCYmwtbWFnl5eS0UfdvT2Pq8evUqvv/+exQXF+Ojjz5qoWjbOUYIIYQQ0sz279/PALCoqCguLTs7m2loaDA3N7e37v/XX3+xkpISxhhjX3zxBXtfblni4+MZALZlyxYu7fXr18zY2Jh9/PHHde4bGBjIALDr169zaX/88Qfj8/ls1apV7yzmtqwp9ZmXl8eKiooYY4xt2bKFAWCpqanvMtx2j95YEEIIIaTZHTx4EF27dsWkSZO4NLFYDFdXVxw7dgylpaV17t+1a1eIRKJ3HWabc/DgQfD5fMydO5dLEwqFmDVrFq5evYpnz57Vue+gQYMwaNAgLs3U1BQjRozAgQMH3mncbVVT6lNTUxOdOnVqiTA7DOpYEEIIIaTZJSYmYsCAAVBQkL3VGDx4MEpKSvDo0aNWiqxtS0xMhImJCdTU1GTSBw8eDAC4fft2jftVVFTgzp07GDhwoNy2wYMH4/HjxyguLm72eNu6xtYnaRzqWBBCCCGk2T1//hy6urpy6dK0zMzMlg6pXWhsveXn56O0tJTqvBq6DlvWB60dACGEEELatoqKCpSVldUrr0AgAI/Hw+vXryEQCOS2C4VCAMDr16+bNcaOorH1Jk2nOpdF12HLojcWhBBCCKnTpUuXIBKJ6vWTlJQEABCJRDXOo/j777+57UReY+tNmk51Louuw5ZFbywIIYQQUidTU1OEhYXVK690iImuri6eP38ut12aJpFImi/ADkRXVxcZGRly6W+rN01NTQgEAqrzahpbn6RxqGNBCCGEkDrp6OjA09OzQfuYm5vjt99+Q0VFhcwE7vj4eCgrK8PExKSZo+wYzM3NERsbi6KiIpkJx/Hx8dz2migoKKBv3764ceOG3Lb4+HgYGRm9lyscNbY+SePQUChCCCGENLspU6YgKysLhw8f5tJyc3MRFRWFcePGyYx7f/z4MR4/ftwaYbY5U6ZMQXl5OUJDQ7m00tJShIWFwcrKCt27dwcAPH36FA8fPpTbNyEhQaZzkZSUhAsXLsDFxaVlCtDGNKU+ScPxGGOstYMghBBCSMdSXl6OYcOG4d69e1i+fDm0tLQQHByMp0+fIiEhAb169eLyGhgYAADS0tK4tCdPniAiIgIAcOLECcTHx+Prr78GAOjr62PGjBktVpaW5urqiiNHjmDp0qXo2bMnwsPDcf36dZw/fx7Dhw8HANjZ2SEuLg5Vb+OKi4thYWGB4uJi+Pr6QlFREVu3bkV5eTlu374NsVjcWkVqVY2tz8LCQmzfvh0AcPnyZZw+fRrLli2DhoYGNDQ04OPj0yrladNa9/t8hBBCCOmo8vPz2axZs1iXLl2YsrIys7W1ZQkJCXL59PX1mb6+vkxabGwsA1Djj62tbcsUoJW8fv2a+fr6Mh0dHSYQCNigQYPY6dOnZfLY2trW+DXyZ8+esSlTpjA1NTWmqqrKxo4dy5KTk1sq9DapsfWZmppa6zVY/XolleiNBSGEEEIIIaTJaI4FIYQQQgghpMmoY0EIIYQQQghpMupYEEIIIYQQQpqMOhaEEEIIIYSQJqOOBSGEEEIIIaTJqGNBCCGEEEIIaTLqWBBCCCGEEEKajDoWhBBCCCGEkCajjgUhhBBCCCGkyahjQQghhBBCCGky6lgQQgghhBBCmow6FoQQQgghhJAm+383RzTYrGiivgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 400x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "coef_series = pd.Series(\n",
    "    data=unmitigated_pipeline.named_steps[\"logistic_regression\"].coef_[0],\n",
    "    index=adata_algo_train_balanced.var_names,\n",
    ")\n",
    "coef_series.sort_values().plot.barh(figsize=(4, 12), legend=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check our model performance on the test data, we first look at the ROC curve of this binary classifier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Y_pred_proba = unmitigated_pipeline.predict_proba(adata_algo_test.X)[:, 1]\n",
    "Y_pred = unmitigated_pipeline.predict(adata_algo_test.X)\n",
    "\n",
    "RocCurveDisplay.from_estimator(\n",
    "    unmitigated_pipeline,\n",
    "    adata_algo_test.X,\n",
    "    adata_algo_test.obs[\"readmit_30_days\"].astype(bool),\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We observe an overall balanced accuracy of 0.59, well about random chance, albeit showing that the simplified model and assumptions are far from a reliable prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/latex": [
       "$\\displaystyle 0.591906498685087$"
      ],
      "text/plain": [
       "0.5919064986850869"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "balanced_accuracy_score(\n",
    "    adata_algo_test.obs[\"readmit_30_days\"].astype(bool), Y_pred.astype(bool)\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using fairlearn's MetricFrame utility, we can conveniently inspect our target model performance measurements:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "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>selection_rate</th>\n",
       "      <th>false_negative_rate</th>\n",
       "      <th>balanced_accuracy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>race</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AfricanAmerican</th>\n",
       "      <td>0.400833</td>\n",
       "      <td>0.419385</td>\n",
       "      <td>0.601196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caucasian</th>\n",
       "      <td>0.382129</td>\n",
       "      <td>0.461288</td>\n",
       "      <td>0.588269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>0.321224</td>\n",
       "      <td>0.483568</td>\n",
       "      <td>0.608668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown</th>\n",
       "      <td>0.231718</td>\n",
       "      <td>0.611650</td>\n",
       "      <td>0.586132</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 selection_rate  false_negative_rate  balanced_accuracy\n",
       "race                                                                   \n",
       "AfricanAmerican        0.400833             0.419385           0.601196\n",
       "Caucasian              0.382129             0.461288           0.588269\n",
       "Other                  0.321224             0.483568           0.608668\n",
       "Unknown                0.231718             0.611650           0.586132"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics_dict = {\n",
    "    \"selection_rate\": selection_rate,\n",
    "    \"false_negative_rate\": false_negative_rate,\n",
    "    \"balanced_accuracy\": balanced_accuracy_score,\n",
    "}\n",
    "\n",
    "mf1 = MetricFrame(\n",
    "    metrics=metrics_dict,\n",
    "    y_true=adata_algo_test.obs[\"readmit_30_days\"],\n",
    "    y_pred=Y_pred,\n",
    "    sensitive_features=adata_algo_test.obs[\"race\"],\n",
    ")\n",
    "\n",
    "mf1.by_group"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A barplot represents this information graphically:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped_barplot(mf1.by_group)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Certainly, here's a refined version:\n",
    "\n",
    "\"We observe comparable performance in terms of balanced accuracy across demographic groups. However, there is notable variation in selection rates, with African American, Caucasian, Other, and Unknown subgroups exhibiting higher rates in descending order. This discrepancy becomes particularly relevant in the context of fairness, as per fairlearn's framework, where the low selection rates and poorer False Negative rates could potentially harm these smaller subgroups. A False Negative prediction entails erroneously predicting 'no early readmission' following a visit where early readmission did occur. The model's performance disparities, especially concerning the Unknown racial group, highlight bias towards this demographic in this specific aspect.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Mitigation: fairlearn's ThresholdOptimizer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Towards a mitigation, we instantiate ThresholdOptimizer with the logistic regression estimator:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"3\" halign=\"left\">Unmitigated</th>\n",
       "      <th colspan=\"3\" halign=\"left\">ThresholdOptimizer</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>selection_rate</th>\n",
       "      <th>false_negative_rate</th>\n",
       "      <th>balanced_accuracy</th>\n",
       "      <th>selection_rate</th>\n",
       "      <th>false_negative_rate</th>\n",
       "      <th>balanced_accuracy</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>race</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AfricanAmerican</th>\n",
       "      <td>0.400833</td>\n",
       "      <td>0.419385</td>\n",
       "      <td>0.601196</td>\n",
       "      <td>0.374180</td>\n",
       "      <td>0.448276</td>\n",
       "      <td>0.599936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Caucasian</th>\n",
       "      <td>0.382129</td>\n",
       "      <td>0.461288</td>\n",
       "      <td>0.588269</td>\n",
       "      <td>0.400079</td>\n",
       "      <td>0.441990</td>\n",
       "      <td>0.589029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>0.321224</td>\n",
       "      <td>0.483568</td>\n",
       "      <td>0.608668</td>\n",
       "      <td>0.386711</td>\n",
       "      <td>0.413146</td>\n",
       "      <td>0.611416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unknown</th>\n",
       "      <td>0.231718</td>\n",
       "      <td>0.611650</td>\n",
       "      <td>0.586132</td>\n",
       "      <td>0.429956</td>\n",
       "      <td>0.466019</td>\n",
       "      <td>0.557203</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Unmitigated                                        \\\n",
       "                selection_rate false_negative_rate balanced_accuracy   \n",
       "race                                                                   \n",
       "AfricanAmerican       0.400833            0.419385          0.601196   \n",
       "Caucasian             0.382129            0.461288          0.588269   \n",
       "Other                 0.321224            0.483568          0.608668   \n",
       "Unknown               0.231718            0.611650          0.586132   \n",
       "\n",
       "                ThresholdOptimizer                                        \n",
       "                    selection_rate false_negative_rate balanced_accuracy  \n",
       "race                                                                      \n",
       "AfricanAmerican           0.374180            0.448276          0.599936  \n",
       "Caucasian                 0.400079            0.441990          0.589029  \n",
       "Other                     0.386711            0.413146          0.611416  \n",
       "Unknown                   0.429956            0.466019          0.557203  "
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "postprocess_est = ThresholdOptimizer(\n",
    "    estimator=unmitigated_pipeline,\n",
    "    constraints=\"false_negative_rate_parity\",\n",
    "    objective=\"balanced_accuracy_score\",\n",
    "    prefit=True,\n",
    "    predict_method=\"predict_proba\",\n",
    ")\n",
    "postprocess_est.fit(\n",
    "    adata_algo_train_balanced.X,\n",
    "    adata_algo_train_balanced.obs[\"readmit_30_days\"],\n",
    "    sensitive_features=adata_algo_train_balanced.obs[\"race\"],\n",
    ")\n",
    "Y_pred_postprocess = postprocess_est.predict(\n",
    "    adata_algo_test.X, sensitive_features=adata_algo_test.obs[\"race\"]\n",
    ")\n",
    "metricframe_postprocess = MetricFrame(\n",
    "    metrics=metrics_dict,\n",
    "    y_true=adata_algo_test.obs[\"readmit_30_days\"],\n",
    "    y_pred=Y_pred_postprocess,\n",
    "    sensitive_features=adata_algo_test.obs[\"race\"],\n",
    ")\n",
    "pd.concat(\n",
    "    [mf1.by_group, metricframe_postprocess.by_group],\n",
    "    keys=[\"Unmitigated\", \"ThresholdOptimizer\"],\n",
    "    axis=1,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAANIAAAAQCAYAAABjuSH9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAABJ0AAASdAHeZh94AAAHv0lEQVR4nO2bfZBXVRnHP2soFioZmNZUKowUWLj2gpKJkAYlaFA0NQ1OOQPmqCMKqGTZw7fGFAsKtRfURkyZmlIkTTKEmAi1nMmd0QZS4kXSigTDVoFMpT+ec9mzZ+/dvff+th//7HfmN2fvuc9znu89z73nPOc5Z1v27dtHH/rQh8bQL62Q9A7g68DHgUHA34HlgMzsX2UblrQVOLbg9nYzOyaSbQGmh9+JQAuwAbgNuMXMXs9pfypwBtAKnAQcDiw1s2kVOE4D7gyXM8zstuR+ZV5BbyIwExhBRx/+EVhoZo8eKJ2qvpU0H/ggMAwYDOwBngk6N5vZzgJepe3U7eOkjW79mMieCVwCjAaOBHYCTwKLzGxFXW4HJYpDcUecDzwGfAfYjDvrUUmDenqoBC8Cyvl9O5G7C7gFOA74SSD6JuAHwJKCtr+Kd0gr8FxFXkh6J3Az8FI3YpV5hZfvl8D7gQeBRcDjwCeBh4PTm65T07eXAwOAh0L7S4FXgXnAE6EPU15V7dTxfWyvjB8z2RuAVfjgcB+wAHgAOAoYm6NSmls6I30feCtwqZndFBFYiHfqtcCFPRGOsMvM5nUnIGkK8HlgCzDKzHaE+kOAe4DzJC03s2WJ6uXAs8Bf8JlpTVlSYaS5HR+NlgFzeoOXpGNCW9uBkWb2z+jeOOA3+Eh9V7N1qOfbI8xsb07fXAtcDXwZuCi5XdpOA77P2uzRj5HsDOAK4A7gAjN7Jbl/cHJdidtBkeJQYDywFfhewsOAl4PygCKyNTEllAsysgDhQa8Jl5ekSma2xsw2mlmdRd6lwEfxUfPlXuR1LN6nf4hf7owv0I6Pfk3VqevbvI8o4GehPCGurGGnlu8jlPEjkvrjH/A2cj6iYPO/SVUlbnFoNy6UK9O41MzagYfxae3Uwsfqiv6Spkm6WtJMSeMkvSGRydZKm3P0s7rTw0jQMCQNB67HY+K13YjW4bUReAUYJWlwYncMvo5blbTVDJ3e9u05oXwiqa9qp7bvK/gR4GP4wLIMeF3SRElXhXdydIFOJW5xaPfuUD5d0PBGfLQZBqzugXhM5s6kbouk883st+E6+9qPz9EfEsp+4e8/l7SbC0n9Ap9teGjSHSrzMrMXJF0FLATWS1qOhx1DgXPxtcaX4oaapNOQbyXNAQ4DBuLri4/gH9H1iWhVO7V8X9GPAB8K5V6gDXhvfFPSWmCqmT0fVVfiFs9IA0P5YgGZrP7NPdJ23A6ciX9MA4D3AYvxhduvJJ0U5B4I5SxJb8mUQ8yqqL0jS9rtDl8DTga+aGZ7epCtxcvMvgt8Cu/kGcBc4DPAX4ElaSjWJJ1GfTsHD80uwz+iB4HxyYtXx05d31fxI/iaDXyNtA84HZ+1RwIrgTHAzxOdSty6pL97C2ampOpPwIWSXgJm45mfKcBPgfOACfjo+gt85DgLeBs+6rwL6DEN2h0knYKPXguK0skJavGSdCXwTeBGPJv0D+A9wHXAUkmtZnblgdCpi2yrQtLRwIfxmahN0iQze7yBpiv3cQ0/QscS5lXgXDPbGq6fDEmFp4AzJI2O2qzELZ6RstFiIPnI6neVJF+EH4ZyDICZvYbH3HOB54EvhN9G3GntQb7LqFwWIRT4MR5yXNODOHV5SRoLzAfuM7NZZrbZzHaHl20KnqafLWlIk3V6xbdmtt3M7sXDs0F4n8aoZKdqH9fxY2wPaIs+ouyZdgO/DpejovpK3OIZ6alQDisgk2VoiuLfssjCgf0ZopAxmR9++yHp0GB3h5ltacDmYXQ8114pnSwBuFXSrfji9bKavCaFsksq3sx2S3oMf9FPpmPB2gydXvWtmT0jaT3QKmlwlNWqbKdiH9fyY8RrVwGvbJP4jXFlFW7xjJQ5ZbykdKP2cOA0YDfw+wIyZZFlbPKyISk+BxyCb4Y1gv8APyr4tQWZdeG6TLhQxKt/KNN0NUl9nH5ths7/w7dvD+VrUV1v2snr47p+XI2vjUakvAKy5EPZwboLt/0zkpltkrQSn7YvBm6KFIXPIIvNbH++PuwbHAxsivPwITW5LZYN9cfh8Tx03mA8wsz+nci2At/CR4s0O1QJYUE6Pe+epHn4yH1HzhGhqrx+h+8tXCBpsZk9F+l9An+R9gKPNFOnpm+H4Ue5OiUOwov4DXwB/0h85KemndJ9XNePYQa9H89ozsRPW2R64/F10C48iRK3WZpbmmy4CO/8G+VnkjYAp+D7A08DX0nkV+Obg8fjm3AZPovH6Gvxs1nteGp2InAosILOx4QekrQHT0i0A8OD7B7gHDP7W2IXSZOByeEyy/mPlrQk/L3DzAp3ukuiKq+78f2bs4ANku7FkwDD8XCsBZhrnc+oNUunqm/PBq6TtA4fqXcCR+OnSIYEezNy+qyqncq+r4mL8Q9tofyMYhv+3k7GZ9Xp6aBRhVunac7MNuH7BEvwh5+NfwCLgFOt4JBiDtbg58CG4scsZuEOWIcv2CYlu8t34+nIaUF2JH7GaUS035SilY4F4IRQNySqm1qSa3eoxCtsQp6NH4VZj69TZuPh7ApggpktOkA6VX27Cg+RjsLT7FcAnwZewGeXE81sfU4fVLVTx/eVYWbPAh/AI6IT8JlpLHA/cJqZ3ZOjVppbS9+/UfShD43jfz6vIGg8oAcoAAAAAElFTkSuQmCC",
      "text/latex": [
       "$\\displaystyle 0.591498880309469$"
      ],
      "text/plain": [
       "0.591498880309469"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_pred_mitig = postprocess_est.predict(\n",
    "    adata_algo_test.X, sensitive_features=adata_algo_test.obs[\"race\"]\n",
    ")\n",
    "balanced_accuracy_score(\n",
    "    adata_algo_test.obs[\"readmit_30_days\"].astype(bool), Y_pred_mitig.astype(bool)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped_barplot(metricframe_postprocess.by_group)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can observe that the performance especially across the subgroups under-represented in the dataset could be enhanced.\n",
    "In particular, the false negative rate, predicting patients of particular need to not belong to this class, could be increased for the underrepresented groups."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation Strategies\n",
    "\n",
    "- Engage diverse stakeholders, including ethicists and representatives from impacted groups, during the algorithm development and review process to provide perspectives on potential bias.\n",
    "- Ensure that the training data includes a diverse and representative sample of the population, covering various demographics to prevent skewed model outcomes.\n",
    "- Validate model outcomes across different demographic groups to ensure that the algorithm performs equitably before it is used widely in clinical settings.\n",
    "- Maintain transparency in algorithm development with clear documentation of decision criteria, data sources, and modeling techniques.\n",
    "- Conduct regular audits of algorithm performance to check for biases, involving external audits if possible to ensure impartiality.\n",
    "- Consider using toolboxes such as fairlearn to enhance model fairness."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Normalization bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normalization biases arise when the methods used to standardize or normalize data across different scales or distributions inadvertently distort the underlying relationships or magnitudes in the data.\n",
    "This can occur if the normalization technique does not account for intrinsic variability within subgroups or assumes a uniform distribution where it does not exist, leading to misleading interpretations of the data's true structure.\n",
    "For example, applying the same normalization method to clinical measurements that vary widely between demographic groups (e.g., pediatric vs. adult populations) can mask important physiological differences and affect the accuracy of subsequent analyses.\n",
    "\n",
    "### Scenario: Normalizing separately and jointly\n",
    "We consider for a visualization how the Number of Medications within one stay are distributed between stays of patients of two age groups (\"Younger than 30\", and \"Older than 30\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Detected feature types for AnnData object with 101766 obs and 24 vars</span>\n",
       "╠══ 📅<span style=\"font-weight: bold\"> Date features</span>\n",
       "╠══ 📐<span style=\"font-weight: bold\"> Numerical features</span>\n",
       "║   ╠══ num_lab_procedures\n",
       "║   ╚══ num_medications\n",
       "╚══ 🗂️<span style=\"font-weight: bold\"> Categorical features</span>\n",
       "    ╠══ A1Cresult (3 categories)\n",
       "    ╠══ admission_source_id (3 categories)\n",
       "    ╠══ age (3 categories)\n",
       "    ╠══ change (2 categories)\n",
       "    ╠══ diabetesMed (2 categories)\n",
       "    ╠══ discharge_disposition_id (2 categories)\n",
       "    ╠══ gender (3 categories)\n",
       "    ╠══ had_emergency (2 categories)\n",
       "    ╠══ had_inpatient_days (2 categories)\n",
       "    ╠══ had_outpatient_days (2 categories)\n",
       "    ╠══ insulin (4 categories)\n",
       "    ╠══ max_glu_serum (3 categories)\n",
       "    ╠══ medicaid (2 categories)\n",
       "    ╠══ medical_specialty (6 categories)\n",
       "    ╠══ medicare (2 categories)\n",
       "    ╠══ num_procedures (7 categories)\n",
       "    ╠══ number_diagnoses (16 categories)\n",
       "    ╠══ primary_diagnosis (5 categories)\n",
       "    ╠══ race (6 categories)\n",
       "    ╠══ readmit_binary (2 categories)\n",
       "    ╠══ readmitted (3 categories)\n",
       "    ╚══ time_in_hospital (14 categories)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Detected feature types for AnnData object with 101766 obs and 24 vars\u001b[0m\n",
       "╠══ 📅\u001b[1m Date features\u001b[0m\n",
       "╠══ 📐\u001b[1m Numerical features\u001b[0m\n",
       "║   ╠══ num_lab_procedures\n",
       "║   ╚══ num_medications\n",
       "╚══ 🗂️\u001b[1m Categorical features\u001b[0m\n",
       "    ╠══ A1Cresult (3 categories)\n",
       "    ╠══ admission_source_id (3 categories)\n",
       "    ╠══ age (3 categories)\n",
       "    ╠══ change (2 categories)\n",
       "    ╠══ diabetesMed (2 categories)\n",
       "    ╠══ discharge_disposition_id (2 categories)\n",
       "    ╠══ gender (3 categories)\n",
       "    ╠══ had_emergency (2 categories)\n",
       "    ╠══ had_inpatient_days (2 categories)\n",
       "    ╠══ had_outpatient_days (2 categories)\n",
       "    ╠══ insulin (4 categories)\n",
       "    ╠══ max_glu_serum (3 categories)\n",
       "    ╠══ medicaid (2 categories)\n",
       "    ╠══ medical_specialty (6 categories)\n",
       "    ╠══ medicare (2 categories)\n",
       "    ╠══ num_procedures (7 categories)\n",
       "    ╠══ number_diagnoses (16 categories)\n",
       "    ╠══ primary_diagnosis (5 categories)\n",
       "    ╠══ race (6 categories)\n",
       "    ╠══ readmit_binary (2 categories)\n",
       "    ╠══ readmitted (3 categories)\n",
       "    ╚══ time_in_hospital (14 categories)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "380fc324743b4917b13053cfd3ec5055",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata = ep.dt.diabetes_130_fairlearn()\n",
    "ep.ad.move_to_obs(adata, to_obs=[\"age\", \"num_medications\"], copy_obs=True)\n",
    "\n",
    "adata.obs[\"Age Group\"] = np.where(\n",
    "    adata.obs[\"age\"] == \"'30 years or younger'\", \"Younger than 30\", \"Older than 30\"\n",
    ")\n",
    "ep.ad.infer_feature_types(adata)\n",
    "adata = ep.pp.encode(adata, autodetect=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_scaled_together = ep.pp.scale_norm(adata, vars=\"num_medications\", copy=True)\n",
    "adata_scaled_separate = ep.pp.scale_norm(\n",
    "    adata, vars=\"num_medications\", group_key=\"Age Group\", copy=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fv16dO3dWTEyM2rdvr9KlS+vMmTNavny5vv/+e23ZskWPP/64pX1YWJjq1KmjK1euqHXr1qpSpYqOHj2qkJAQtW7dOsX1G4ahAQMGaN68ecqfP786d+4sf39/nTlzRlu2bFG5cuUsv/D6888/9corr6hBgwZq27atfH19derUKa1evVrr1q3TmjVr1KpVK0lK1THgfql5fyb03XffadWqVZZj/5EjR7R27Vr9+uuvOnLkiOWvSm/duqV69erp2LFjat68udq3by/DMHTy5EmtWrVKXbt2VcmSJVO8DwHAnvTk2j59+uiVV17RV199pdGjR9ssM3/+fMXFxVkdW83fHxs2bFC5cuXUq1cvubu7a8uWLXrmmWe0Z88eff311zbrSiqHff7551qxYoUaNmyoZs2aKT4+Xvv27dOUKVO0bt067dmzR3ny5En/zrLj+vXrqlevnlxdXdW1a1dFR0dryZIlGjhwoJycnNSvXz+r9n369NHChQtVtGhRDR48WCaTSStWrNCIESO0Y8cOLViwwGYbV69eVe3ateXl5aXOnTvLycnJavgycw158uRRz549dfXqVS1evFgtW7bU7t27NXToUF29elXt2rVTTEyMFi1apO7du6to0aKqXbu2ZT2p+f5MLXNOu9/27dv1448/Wt3eNjXnHY0aNdL169c1bdo0PfbYYwoJCbGsp0qVKknW9Ouvv6pZs2a6ceOGOnTooEceeUR//fWX5s+fr1WrVmnz5s2qUaOGzXIzZszQ6tWr1aFDBzVs2FB79uzRN998o0OHDungwYNyc3NLdn+kJoub95u9zJ9SL7zwgjZs2GDJgVu2bNHnn3+uo0eP6scff0z1+uwJDw9XrVq1VKFCBcsF4BUrVqhRo0bavXu3WrVqJW9vb3Xv3t3yHm3durX++eefdP0FX0Zl65MnT6pRo0YKDw9XcHCwWrVqpZs3b+q7775Tq1at9Omnn+qpp56ytI+OjlbTpk3166+/6rHHHtOTTz6p69ev680337R0Akipzz//XMOHD1euXLnUoUMHlSlTRhcvXtTevXs1Y8YMdevWzdJ2+PDhqlixoho0aKDAwEBduXJFa9euVZ8+ffT333/rzTfflPRwnCsCeLjky5dP0r1fTKXGwIEDNWfOHBUpUkRdunRR3rx59fPPP+u1117TDz/8oE2bNsnZ2fpXD9euXVPdunWVN29eSye3b7/9Vk8++aTOnj2r559/3tL26tWrGj16tOrWravmzZvL399f58+f15o1a9SmTRt9/vnnGjx4sE1dd+/eVZMmTXT16lW1aNFC3t7elo4FmZGFJkyYoPHjx8vPz0/t2rVTQECAfvvtN73//vtau3atdu/enaJrnGapyUNpzVwffPCBNm3apPbt26tx48Y2v9ybPn261q1bp5CQEDVq1EgbN27Uhx9+qKtXr6pjx47q0aOH2rZtqyFDhmjXrl2aP3++Ll++bNNR5J133tFff/2lunXrqm3btrpz54527typ8ePHa+vWrdq8ebNy5cqV4n1jFhQUZDe3xcTEaMqUKbpz545VBn7ppZfk5OSkWrVqqXDhwoqIiNCPP/6o0aNH69dff7U6RwoNDdXKlSt16NAhjR49Wnnz5pUky79JScv5SGrPeRLz3XffqUuXLjIMQ127dlXx4sW1b98+zZw5U6tWrdKOHTssn4PQ0FCFh4dr3rx5atiwoSUTJ3etziw1uSQ9Mup6a2rExMSoefPmlvf63bt3tWjRInXp0kUbN27UjBkztGfPHrVu3Vpubm5asmSJnnnmGfn7+6t79+5W60rtscGcB11dXdW9e3cFBgZqx44dqlOnjh599NEUP4dr166pcePGOnTokMqVK6eBAwfK1dVVx44d05w5c9S5c2fLOe/y5cs1a9YsNW7cWHXr1pWrq6sOHz6sL774QmvWrNHevXstQ6KZj4H3v2+k5DNwat6fCaX0XOu3335TrVq1ZDKZ1KFDB5UoUUKRkZE6evSoZsyYobfeeksuLi4p3ofIRAaQjTRp0sSQZHz22WfJtu3Vq5chyXjzzTct0+bMmWNIMkwmk7Fu3Tq7y0kyGjZsaDVt4MCBhiTjhRdesJp+8OBBw9XV1ZBkhIaGWs1r2LChcf9HaMuWLYYkQ5IxZ84cq3mzZs0yJBnDhw+3mn7hwgUjMjLSps6DBw8auXPnNlq1amU1/cSJE4Yko1+/fnaf3/3M7YsXL55ku6NHjxqSjFy5chkxMTGW6cWLF7da9vr164bJZDKqVatmxMbG2qzn8uXLVo/t7e/7a5NkjBs3zm6b5Pbz9OnTreatXLnSkGSULl3aiIuLs0zv16+fIck4ceKEzTbM60vJa5zQ/fvGMAzj7bffNiQZrVu3ttqPFy5cMIoXL25IMnbu3Gl3H4wfP95qXevXr7esyyy1+z8xLVq0MCQZb731ltX0nTt3Grly5TL8/PyMGzduWM1L6rVMjPk5t27d2rh165Zl+oULFwwfHx/Dx8fHuHv3rmV6Yq9FwvXdv8/Nn/tcuXIZW7dutUyPi4szmjVrZkgyfH19jfnz51stZ/7cr1y5MlXPycz8nipevLhx5swZy/Rr164Z+fLlMzw9PY38+fMbR44cscy7c+eOUaFCBcPV1dW4cOGCZfrVq1eNvHnzGvny5TMOHz5stZ3ff//dyJ07t1G1alWr6c2bNzckGVOnTrWabv4M2DsO2dt/n376qSHJqFGjhnH9+nWrebGxsca5c+csj69fv25cunTJZl+cPn3aCAwMNMqXL28zLyXHgPuPZ6l9fyZ8D2zevNlqmZdeesmQZLzzzjuWaatXrzYkGWPGjLGpKTo62u4xGQBSK7251nws/P33323aP/LII4arq6vV935oaKghyRg5cqRVRoiNjbX7nZeSHBYeHm43b3zxxReGJGPy5MlW083H45R8/yTFXNegQYOstn/48GEjV65cRoUKFazaL1y40JBkVK1a1er7ISoqyqhWrZohyViwYIHdbfTp08cqs90/f+jQoVaZ8quvvrJki3bt2hm3b9+2zNu2bZshyQgJCbFaV0Z9f5pf4y1btti0T+jQoUNGnjx5jPz58xtHjx61TM/o8w57uS0+Pt4oX768Ickmey1evNiQZJQrV85qn5qfV548eYzffvvNapmePXsakoxvvvkmyedsltosbhjJZ357zDmwaNGixsmTJy3TY2JijODgYEOSsWfPHqtlkspE9s5VEn5G789Eb7zxhuV9mNh71F7OSYmMztYNGzY0TCaTsWjRIqvp165dMx577DHD3d3d+Pfffy3TJ06caEgyOnfubPW8jh8/bvj6+tp9T9rbf4cPHzacnZ0NX19f448//rB5nqdPn7Z6nPCzYhYdHW00adLEcHZ2tsr75ueVU88VATxc9u/fb7i4uBgmk8no3bu3sWzZMiM8PDzJZczfFZ06dbK61mMY/32v33+twnw8e+KJJ+we311cXIxjx45Zpt+5c8fmWG0Y9451FStWNHx9fW22bT6WNm3a1IiKirJZNqOz0I8//mhIMurUqWNcu3bNap55H6X0+zi1eSg9mcvT09PYv39/ojV4e3vbXMt65JFHDCcnJ8PPzy/RfHDgwAGr9R07dsyIj4+32c6rr75qSDIWL15sd/v3Z92UXo8054H797m97/i4uDijb9++hiTj559/trsee9eQDcN+BkjP+UhKz3kSc+PGDcPPz89wcnIytm3bZjVv8uTJhiSjefPmVtOTu/5qT2pziWEkff6S2OcrI6+3pob5+NGuXTvjzp07lunmczxfX1+jevXqVp/1Y8eOGS4uLkaVKlWs1pXaY4P5NXR2djZ+/fVXq/Zjxoyx7Hd75wr37z/z8WLYsGFWn3/zdhJe+z1z5ozVczXbsGGD4eTkZAwbNsxqenLvG3vXA9Ly/kztudZzzz2X6DX+q1ev2uwHOA4dEpCtVKhQwZCUaGeChF588UVDsv4Fv/mgd/9FwITuDzHR0dGGh4eH4ePjYzeUDh48OMW/rDYflOvVq2eznrt37xrOzs5GtWrVkn1uZu3btzfc3NysfmGbWR0Sbt++bflyS/jFff+FlIiICEOSUbduXbuh8n4p+WVkgQIF7H75GUbS+/n+Tgf3L5MwIGdVh4TSpUsbJpPJ+PPPP23amy/eDxgwwDIt4etj76JRsWLFjHz58lkep3b/23P69GlDklGsWDGr95ZZ7969DUnGvHnzrKan9AQgIXOYCwsLs5lnDv4Jf9GSng4JvXv3tmk/b948Q5IRHBxsM2/r1q12Q3RKmd9TX3zxhc28AQMGGJKM1157zWbe+PHjbd6fU6dONSQZH3/8sd1tmcOnubOC+TUsUaKE3feN+b2bkl8IVapUyZBk92Q0NZ555hlDklVQNIzUd0hIy/vT/B548sknbdofP37ckGR06dLFMs3cISGxX8ABQEZIb65dsGCBIckYO3asVdtff/3VcgHYLC4uzvDz8zMKFixo95fr165dM0wmk/HEE09YpqUkhyUmPj7e8Pb2Nho3bmw1PSM7JHh6ehoRERE28xo0aGBIsrrQZ74IumHDBpv2mzdvNiTZ1CopyQtW5hruPz+IjY01nJ2dDUlWF83NgoKCjKCgoBQ9T8NI3fdnSjoknD171ihSpIjh7u5u84v3pKTlvMNebtuxY4fl4ps99evXNyQZP/30k83zeuWVV2zamy/m/e9//0vR80htFjeM9HVI+Pzzz23mffnll4Zk23E6qUyUVIeEoKAgm7x38uTJZN+jjRo1StVzMsvIbH3w4EFDktG1a1e72zJ3pP3kk08s00qXLm04OTnZ/eWB+b2Skg4JI0eONCQZU6ZMSe4pJ2nZsmV2z41y6rkigIfTN998YxQsWNByXVCS4efnZ4SEhBirV6+2aV+lShXD2dnZ5hdthnHveyhfvnxGjRo1rKZL9zq7HT9+3GYZ8/E9pddnPvjgA5s8YRj/XYM6ePBgitaTUFqyUEhIiCHJbsc3w7i3n/z9/VO0/dTmofRkrsQ6SZjnv/rqqzbzJkyYYEj3OvPeb+7cuYYkY+7cuck+T8MwjCtXrtjNZOnpkGCur2PHjin+5eO+ffsMScaECROspqelQ0Jaz0dSc86TmPnz5xuSjJ49e9rMi4mJMYKCgmzON9LTISGlucQw0tchISOut6aG+fhhL4OWKFHCkGT88MMPNvMaNWpkODs7W+2T1B4bzK9h3759bdpev37d8PHxSfRcIeH+u3DhguHk5GQEBgba7ZSVGpUrVzZKlChhNS0tHRLS8v5M7bmWuUOCvc8fsheGbECOVLNmzRS3/fvvv3X79m3LmDr3q1+/vr744otUbf/+8XwlycXFRQUKFLA73u7333+vWbNmae/evbp8+bJiY2Ot5l++fFmBgYGpqiG1DMOw/D+pcVO9vb3Vvn17rVmzRlWqVFGXLl0UHBysWrVqWd0OKzUee+yxFN2C9X7BwcF2b7XfqFEj/fTTTzpw4IBlTKyscOPGDR09elSFCxdW+fLlbeY3adJE0r3xVu9XpUoVu7cpK1q0qNXYwhmx/83bDw4Otnu7oiZNmmj+/Pk6cOCA+vbtm6J1JsXHx0elS5e2mV60aFFJyrAxqO197goVKiRJqlatms088y2n7h8TyxHbNb/Ghw4dsjtmm/nWiX/++aceeeQRy2tYv359u+8b82cgOTdv3tQff/yhAgUKqGrVqsm2l6SdO3dq2rRp2r17ty5evKi7d+9azT979my6bg+cnvenvdfC3vusYcOGKly4sCZPnqz9+/erTZs2qlevXqKfQwBwhE6dOsnHx0cLFizQ5MmTLccn85imCYdr+Oeff3T16lWVKVNGb731lt31eXh46M8//7SZnlQOi4mJ0aeffqrFixfryJEjioiIsBr/NLGxbDNCmTJl7N7eNuFx3cvLS5K0f/9+OTk52b3NaMOGDZUrVy67+SsoKEgBAQGJ1lC2bFmb84NcuXKpQIECunnzpt3hfQoXLqw9e/bYTM/s709JioqKUrt27XT27FktWrRIdevWtWmT2ecd+/fvl/Rf7r1fkyZNtGPHDh04cEANGjSwmpfS7/HEpCeLp1V6a04Je/nEnDWTeo9mp4wbERFhN+NeunRJkizHJvNrWLRoUZUqVcqmvXkYuZT4+eefJSnFQ5mdOnVK77zzjn744QedOnXKZgzi9B7vHpRzRQAPp27duqlTp07asmWL5Xt6x44dWrlypVauXKm+fftaxga/deuWDh06pPz582vq1Kl21+fm5mY3dxYrVszubbnNx/f7j4GHDx/We++9p23btun8+fO6c+eO1Xx7x2Z3d/ckb2+ekVlo9+7dcnFx0ZIlS7RkyRKb+Xfv3tWlS5d05coVy9AYyUlptkhP5kruunlGXV+7efOmpk2bphUrVuiff/7RjRs3rK4/Z9S5xIIFCxQaGqrq1atr4cKFNteKr1y5ovfee09r167V8ePHdfPmTav5GVFHWs9HUnPOk9S2JfvvBWdnZzVo0EDh4eE6cOBAus83pJTnkvRyxHXevHnz2s2ghQoV0okTJxLdbmxsrP79919LDak9NphfQ3u/x/Dx8VGVKlVSdJ33119/VXx8vBo0aKDcuXMn294wDC1YsEBz587VoUOHdO3aNcXFxVnmu7q6JruO5KTn/ZnS42H37t01bdo0hYSEqGvXrmrWrJnq1atn97WEY9EhAdlKwYIF9eeff+r06dPJtjW3MX8R3b+elDKPk5VwvNiEEpuelMTGlXJ2drY6qEvStGnTNGbMGPn6+qp58+YqVqyYPD09ZTKZLGNWRUdHp7qG1Dp37pykexewfH19k2z7zTff6J133tHChQstY3a5u7ura9euev/991O9z1LzeiWU2HbM67t/DLTMZt5eYicu5unXr1+3mZfUeybhhX8p/fs/PXWmRVLPTZLNZyKtfHx8Et1GUvNiYmIcvt0rV65IujfObVKioqIkJX/cSulnyvwamwNzclasWKGuXbvK3d1dzZs3V6lSpZQ7d245OTlp69at+umnn9J9vMroz5G995m3t7d+/vlnhYaGavXq1dqwYYMkKX/+/BoxYoReffVVxhYDkG7pzbUeHh7q1q2bPv/8c23cuFGtW7e2jGHp7+9v9Us28/dIWFhYkr+sM3+P3F9nYrp3764VK1aoZMmS6tixowoWLGjpvDB16tRMzaipyQ8RERHy8/Oze8HE2dlZ+fPn18WLF23mJfd9ae973LzOpObdf2E7K74/4+Li1L17dx04cECTJk2yGcNUyprzjqz4Hs+MbadVemtOidRmTfP87JRxN23apE2bNiW6rYzOuFLqcu7x48dVs2ZNXbt2TcHBwWrRooV8fHyUK1cuyxjL2e2zIWXOuSKAh5eLi4tatGihFi1aSLr3PbZs2TINHDhQX331lTp16qSQkBBdu3ZNhmHo0qVLKe4kZpaa63g///yzmjRpotjYWDVt2lQdOnSQt7e3nJycdPDgQa1atcrusTkgICDRP7TK6Cx05coVxcbGJrsfoqKiUtwhIaXZIj3fK2nJwKnNADExMWrSpIl++eUXVapUSd27d5e/v7/lWsuECRMy5Fzip59+0sCBA1W8eHF99913Nh3wrl+/rho1aujEiROqWbOm+vbtKz8/Pzk7O+v69euaNm1ahtSR1vORjLhmmp2u896fS9LDEdd5k8rWqdluao8NjrrO+9xzz2nq1KkKDAxUy5YtVbhwYXl4eEiS5s6dq5MnT6ZoPUnJivPDmjVravv27Zo4caKWLl2qr7/+WpJUrlw5hYaGqmfPnul5CshAdEhAtlK/fn1t2bJFmzdv1lNPPZVou7i4OG3dulWSVK9ePZv5Sf2F//3MvRAvXLhgd35i0zNCbGysxo8fr4IFC2r//v02B+aM7FWYnC1btki618PQfGBPjIeHh8aPH6/x48fr9OnT2rZtm+bOnav58+crPDxc27dvT9W2U/N6JZTYa/Pvv/9Ksg4J5t6x918gljIukJm3Z97+/c6fP29TV1qkd/9nVZ1pkdTrJN17rRILvg8y874+dOhQkj3572+f3GcgOeZ9mdLe4K+99ppcXV21d+9eVahQwWre0KFDU9RbNzlZ9f4sUqSIZs+eLcMwdOTIEf3444/65JNP9MYbbyg+Pl5vvvlmutYPABmRa/v166fPP/9c8+bNU+vWrfX999/rypUrGj16tFXHKfMxsVOnTlq+fHmq6kwsh+3du1crVqxQs2bNtG7dOqt8GB8fr3fffTdV28lMPj4+unr1qmJiYmw6lMXGxury5ct2//IorRk0tbLi+/OZZ57R2rVr9dRTT+mll16ymZ9V5x2OzJnZOeNK995vSWXcnMi8r6dNm6ZRo0aluH16M65knXPt3ZEgoSlTpujKlSuaM2eO1d1nJGnRokWWO9Okx4NyrggAZrly5VK3bt30+++/66233tKPP/6okJAQy3GqatWqlr98TanUXMd76623dPv2bW3ZssXmr84nTZqkVatW2V1XYvkuM7KQj4+P4uPjdfXq1VQvm17p+V7Jigy8atUq/fLLL+rfv7/mzJljU1tqO7PY89dff6lTp07y8PDQ2rVr7f4y94svvtCJEycUGhpqc7em3bt3a9q0aemuQ0r7+UhGbVvKnhk4K67HZ0epPTY44jrvxYsX9dFHH6lSpUratWuXzV3XFi1alKJtJier3p916tTRd999p+joaO3bt0/r16/X9OnT1atXL/n7+6tZs2bpWj8yhu29zgEH6t+/v3LlyqUVK1bo8OHDibb78ssvde7cOZUrVy7dt+QvX768PDw89Ntvv+nGjRs283fs2JGu9Sfl8uXLun79uurWrWsThKOiolId7NPq1q1b+uCDDyRJTz75ZKqWLVq0qJ588klt2LBBpUuX1o4dOyx/CSPdCx4Z9ddB99uxY4fdnpfmi/oJb0FvvuuDvb9S3Lt3r931m28/ldL68+TJo1KlSuns2bMKCwuzmW/u9PH444+naH0pkdz+t8e8X3bs2GE3EGZGnSmV1Ot09OjRLL/rRVapXbu2JKX4AmHC19De+9P8GUhO7ty5ValSJV24cCFFty8+evSoHnnkEZtfpsTHxyd6rEztMSCr358mk0kVK1bUM888Y/nLvZUrV2bIugE83DIi19arV09lypTRqlWrFBERYfmlWL9+/azalS9fXnnz5tXPP/+c7r+KNjt69KgkqUOHDjadVX/55Reb25k7UtWqVRUfH69t27bZzNu2bZvi4uIckmvM0vL9mRoffPCBZs6cqRYtWmjGjBl226TlvCO1WVj673s8sSySmTnTEVk8NXx9fe1m3Li4OB08eDDrC8oCqc24efLkUenSpXX27FkdO3bMZn5KM27Cba9bty7ZtubjXZcuXWzmJdZhKKeeKwLA/cy/pDLfat/Ly0sVK1bU4cOHU/2L+FOnTik8PNxmur3reEePHpWfn5/dW+CnpTNnZmSh2rVr69q1a0lm/cziyMyVEubv1s6dO9vMy4jOuJcuXVLbtm0VFRWlZcuW6ZFHHkmyjsz8jpccez6S1HshNjbWksOy23XexK7H5wSpPTaYXxt778mIiIgUnyvUrFlTTk5O2rZtm83QJPc7fvy44uPj1aJFC5vOCGfOnNHx48dtlsno88PMeH+6ubmpbt26euONN/TRRx9JUqId2JD16JCAbKVkyZJ6+eWXFRMTow4dOujIkSM2bVauXKnRo0crV65cmjlzps24UKnl6uqq7t27KyIiwmbM3UOHDumrr75K1/qTEhAQIE9PT+3bt8/qFroxMTEaPXq0Ll++nGnbNjtx4oTatm2rv/76S1WrVtXQoUOTbH/p0iX9/vvvNtNv3rypqKgoOTs7W92eKl++fCm6VXFahIWF2Vx0XbVqlX766SeVLl1awcHBlunm8dHuvyX+77//nmhvWPPt1E6dOpXimgYOHCjDMPT8889bfTlfvnzZ8hfXAwcOTPH67pfa/W9PkSJF1Lx5c4WHh9uM97dnzx4tXLhQvr6+6tSpU5rrTKvy5cvL29tbq1atsrqV2e3bt1P0V1UPqgEDBihv3ryaMGGCfvnlF5v58fHxVsHN/BqeOHFCH3/8sVVb82cgpcz7dejQoTYdPuLj4y09VaV7Y22HhYVZhniR7l2UGD9+vN3jtZT6Y0BWvD8PHz5st9exeRpj7ALICBmVa/v166c7d+5oxowZWrt2rR599FGri7XSvdsWPvPMMzp//rxGjRplt7PA+fPnEz1W2xMUFCTJ9sLBxYsX9fTTT6d4PVnBnK3GjRunW7duWabfunXLcreAQYMGOaQ2KW3fnym1fPlyvfDCC6pcubKWLFmS6J3O0nLe4evrK5PJlKosXK9ePZUrV047duzQ0qVLreYtXbpU27dvV9myZVW/fv0UrzM1MjuLp0fNmjV16tQpbdy40Wr6W2+9lSG3Q82OqlevruDgYC1fvlxffvml3Ta///67Ve4fMGCA4uPj9eKLL1p1Pj9x4oTlomJKDB8+XM7OznrzzTftfs4Sji+c2PFuw4YN+uKLL+yuP6eeKwJ4+CxatEibNm2y+wc///77r+U6WoMGDSzTn3vuOd29e1cDBw60+1fO165ds/sL/ri4uESP787Ozurdu7dlelBQkK5evarffvvNah2zZ8+2DLuYGpmRhZ599llJ0lNPPWWV88xu3rypn3/+OdW1poSjM1dyEvtuPX78uF588cV0rfvOnTvq0KGDjh8/rk8//VRNmzZNdR3mYc7sSet3vOSY85GQkBD5+flp0aJFNu+3qVOn6sSJE2rWrJmKFSuWKdtPivl6/Jw5c6z+6Oj06dN64403sryerJLaY0PHjh3l6+urhQsX2nTUGD9+fIr/QM/f3189evTQ+fPnNXbsWJvjelRUlGVd5s/G/X/sFhUVpaeeesruH4ml5bORFe/PXbt22b0GwnXe7IchG5DtjB8/Xjdv3tSUKVP02GOPqWXLlqpYsaJiYmK0a9cu7dmzRx4eHlq0aJEaN26cIducPHmyfvzxR7377rvas2eP6tatq/Pnz+vbb79VmzZttHLlynR3fLDHyclJo0aN0uTJk1W5cmV17NhRd+/e1ZYtW3T16lU1btzY0qM1va5fv265NVVsbKyuXbumQ4cOaffu3YqPj1erVq00b948y7jAiTl79qyqVq2qypUr69FHH1XRokUVGRmp7777Tv/++69GjRpl1auuadOmWrx4sdq3b6/HH39cLi4uatCggdWJTFq1atVK//vf/7Ru3To99thjOnr0qJYvXy53d3d9+eWXVq9Zx44dVaZMGS1atEhnzpxRrVq1dOrUKa1atUodO3bUt99+a7P+pk2basmSJercubPatGkjDw8PFS9eXH369Em0prFjx2rdunVatWqVHnvsMbVp00a3bt3SkiVLdPHiRb3wwgvpOhlI7f5PzKxZs1SvXj09//zz2rhxo6pXr67Tp09ryZIlcnJy0pw5c1K0nozm4uKi0aNH680331TVqlXVqVMnxcbGatOmTSpUqJDV2No5Sb58+bR06VJ16tRJtWvXVtOmTVWxYkWZTCadPn1au3fv1pUrV3Tnzh3LMp988onq1KmjMWPGaOPGjZbPwIoVK9S+fXutWbMmRdsePHiwtm/frq+//lplypRRx44d5e/vr3PnzunHH3/UwIEDLceOZ599VsOGDVPVqlXVpUsXubi4aOfOnTpy5Eii20zLMSCz35+bNm3S888/rzp16qhs2bIKCAjQmTNntGrVKjk5Oen5559P87oBIKGMyLV9+vTR66+/rtDQUMXExNjcHcHstdde06FDhzRr1iytWbNGTZo0UeHChXXx4kWFhYVp586dmjhxYqJ/PXS/GjVqqF69elq+fLnq1q2r+vXr68KFC1q3bp3KlSuXrb6Te/XqpVWrVunbb79VxYoVFRISYhkL+MSJE+revXuq7wKWkdLy/ZlSvXv3Vnx8vGrUqKEpU6bYzA8KClL//v3TdN7h5eWlWrVqafv27XryySdVtmxZ5cqVSx06dEh0iCmTyaR58+apefPm6t69uzp27Kjy5cvr77//1sqVK5UnTx599dVXmXJuJWV+Fk9vbRs2bFDHjh3VvXt3+fn5adeuXTpx4oQaNWqUqr/+f5AsXLhQTZo00aBBg/TRRx+pVq1ayps3r86cOaPffvtNf/zxh3bv3q2AgABJ0v/+9z+tXLlSy5Yt0+OPP66WLVvq+vXr+vbbb9WgQQOtXr06Rdt95JFHNGPGDMtnz3w+eOXKFf3666/y9va2vOdHjBihOXPm6IknnlDXrl1VqFAh/fHHH1q/fr26deumb775xmb9OflcEcDDZc+ePZo2bZoKFiyo+vXrq0SJEpLudRT4/vvvdfv2bXXs2FFdu3a1LDNw4EDt27dPM2bMUKlSpdSyZUsVK1ZMV69e1YkTJ7Rt2zYNGDBAs2bNstrWo48+qj179qhatWpq0aKF5fh+/fp1vfvuuypVqpSl7ZgxY7RhwwbVr19f3bp1k4+Pj/bu3asdO3aoa9euNr+ET05mZKGmTZtq8uTJGjdunMqUKaM2bdqoRIkSioqK0smTJ/XTTz+pfv36Wr9+fWpflmQ5OnMlp3379ipdurSmTJmi33//XVWrVtWpU6f03XffqW3btqn6heb9PvroI/38888qWbKkTp48aTMUg3TvbnVBQUHq27ev3nvvPY0ZM0ZbtmxRmTJlFBYWpu+++06dO3dO9Dv+vffe01NPPaUuXbooT548yps3r0aOHJloTY48H/Hy8tKXX36pJ554Qg0bNtQTTzyhYsWKad++fdq4caMKFiyoTz/9NFO2nZxatWqpQYMG2rZtm2rWrKkmTZrowoULWrNmjVq2bJlpf8ToaKk9Nnh5eemzzz5T9+7dFRwcrO7duyswMFA7duzQH3/8YdmHKfHxxx/rjz/+0KxZs7R161a1bNlSrq6uOnHihDZs2KDVq1erUaNGKliwoHr06KHFixerSpUqatGihSIiIrRp0ya5u7urSpUqNndmKFeunAoXLqzFixfLxcVFxYsXl8lkUp8+fVS8eHG79WTF+/Pdd9/Vjz/+qODgYJUoUUJeXl46fPiw1q1bJ19fXw0ZMiRd60cGMoBsas+ePUbfvn2NoKAgw93d3cidO7dRsWJF43//+59x+vRpu8vMmTPHkGTMmTMn0fVKMho2bGgz/cyZM0bfvn2N/PnzG+7u7sZjjz1mzJ0711iyZIkhyfjwww+t2jds2NC4/yO0ZcsWQ5IRGhpqd9vFixc3ihcvbjUtJibG+OCDD4wKFSoY7u7uRoECBYzevXsb4eHhRr9+/QxJxokTJyztT5w4YUgy+vXrl+hzTMjcPuGPm5ub4e/vb9SqVcsYOXKksX379kSXv7/ma9euGRMmTDAaN25sFCpUyHB1dTUKFixoNGzY0Fi4cKERHx9vtfyFCxeMnj17GgEBAYaTk5PV/knJc0luP+/atcto2rSpkSdPHsPLy8to3ry58csvv9hd16lTp4xu3boZvr6+hru7u1G9enVj2bJlib5usbGxxrhx44wSJUoYzs7ONu8de6+nYRjG7du3jYkTJxoVK1Y03N3dDS8vL6NevXrGwoULbdomtw/uf/6p3f9JOXPmjDFs2DCjWLFihouLi5EvXz6jY8eOie6/xD47SUlsHxmGYYSGhhqSjC1btlhNj4+PNyZNmmSULFnScHFxMYoWLWo8//zzxs2bN+2uL6nPfVKfydR+lu5n7/OZ3HNLrt4TJ04YTz/9tFG6dGnDzc3NyJMnj1GuXDmjd+/exooVK2zah4WFGV26dDF8fHwMT09Po3bt2sZ3332X6DaSej3mz59vNGjQwPD29jbc3NyMoKAgo1evXsa+ffts6n/ssccMT09PI1++fEZISIjx22+/Jfqc03oMSM37M7lj//3v3SNHjhjPPvusUa1aNSN//vyGq6urUbx4caNLly7Gzp077a4DANIjLbk2oaZNmxqSDGdnZ+Pff/9NtF18fLzx1VdfGU2aNDF8fX0NFxcXo1ChQka9evWMiRMnGqdOnbK0Tcn34JUrV4zhw4cbxYsXN9zc3IySJUsa48aNS/V3clLfP/YklTkS+/6Ni4szPvnkE6NatWqGh4eH4eHhYTz++OPGxx9/bMTFxaVqG8nNT+r52MuuhpH6709727fX9v6cf/9PwnWk9rzDMO5ljXbt2hl+fn6GyWSyen2Tyll//fWX0bt3b6NgwYKGs7OzUbBgQePJJ580/vrrL5u2SeWmtOS11GRxw0j8NUtKUjkwqf2yatUqo1q1aoabm5vh5+dndO/ePc3nfWl9jyYnM7J1ZGSkMXHiROPxxx83cufObbi7uxtBQUFGmzZtjE8//dSIioqyah8REWE8++yzRqFChQw3NzejXLlyxvvvv28cO3bM7jaSej127dpldO7c2fD39zdcXFyMwMBAo2XLlsaSJUus2u3cudNo3LixkTdvXst7ZsWKFQ/tuSKAh8epU6eMjz/+2AgJCTHKli1r5MmTx3BxcTEKFixotG7d2vj666/tZinDMIw1a9YYbdu2tRxjCxQoYNSoUcN45ZVXjD///NOqrfk4efbsWePJJ580/P39DTc3N6Nq1arGggULEl1/rVq1DC8vL8PHx8do3ry58dNPP6U5c2Z0FjLbvn278cQTTxiBgYGGi4uLkT9/fuOxxx4znn32WePXX39NtJ6E0pqHMipzJTc/Lfng1KlTRq9evYxChQoZ7u7uxiOPPGK88847RkxMTIqzrmHYZh5zu6R+Eq7j8OHDRvv27Q1/f3/D09PTePzxx43PP/88yf36wQcfGOXLlzdcXV0NSVbvq8SyY0aejySVbRLzyy+/GCEhIUb+/Pkt11OHDRtmnD171qZtcr/DsCe1ucTs2rVrxuDBgw1/f3/D1dXVqFixovHpp58mur7MuN6aEmk5x0uu3tQeGzZu3GjUq1fP8PDwMPLmzWt06NDB+PPPP1N9rhAVFWW89dZ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      "text/plain": [
       "<Figure size 2100x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_hist_normalization(\n",
    "    adata,\n",
    "    adata_scaled_together,\n",
    "    adata_scaled_separate,\n",
    "    group_key=\"Age Group\",\n",
    "    var_of_interest=\"num_medications\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On the left, we can see that the raw distribution of `num_medication` per stay is different for the age groups: the age group `Older than 30` seems to receive generally more medications per stay.\n",
    "\n",
    "For many downstream tasks, the units need to be normalized; e.g. for a model to consider the number of medications together with blood pressure, and arbitrary choices of units, can lead to vastly different scales of numbers.\n",
    "\n",
    "Here, we consider scaling the values to zero mean and unit variance. ehrapy supplies options for doing this in two ways:\n",
    "\n",
    "- Jointly normalizing (middle plot) normalizes the values across the entire dataset.\n",
    "\n",
    "- Separately normalizing by group (right plot) normalizes the values within groups. \n",
    "\n",
    "Which way to choose can depend on the data, the groups and the task at hand.\n",
    "For the number of medications, it is likely we want to normalize across the entire group, maintaining the relationships of high/low number of received medications across the entire dataset.\n",
    "\n",
    "For values known to show different physiological norms between groups, e.g. blood pressure between groups of gender and groups of age, it can make sense to normalize within groups. This way, within-group outliers are recognizable as such."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "- Ask data collectors to adhere to standardized protocols across all sites and providers to ensure consistency in how data is recorded.\n",
    "- Choose robust normalization methods that are suitable for the type of data and the analytical goals. Methods like z-score normalization or min-max scaling can be used to standardize data ranges without distorting relationships in the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To discuss the following biases, we will resort to synthetic datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Coding bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Coding bias is a special case of information bias that arises when there are discrepancies or inconsistencies in how medical conditions, procedures, and outcomes are coded, often due to variation in the understanding and application of coding systems by different healthcare providers.\n",
    "This can lead to misrepresentation of patient conditions, treatments received, and outcomes.\n",
    "For example, two providers may code the same symptom differently, leading to challenges in accurately aggregating and comparing data across EHR systems."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: High level vs fine grained ICD codes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata = AnnData(\n",
    "    obs=pd.DataFrame(\n",
    "        {\n",
    "            \"patient_id\": [\n",
    "                \"P1\",\n",
    "                \"P2\",\n",
    "                \"P3\",\n",
    "                \"P4\",\n",
    "                \"P5\",\n",
    "                \"P6\",\n",
    "                \"P7\",\n",
    "                \"P8\",\n",
    "                \"P9\",\n",
    "                \"P10\",\n",
    "                \"P1\",\n",
    "                \"P2\",\n",
    "                \"P3\",\n",
    "                \"P4\",\n",
    "                \"P5\",\n",
    "                \"P6\",\n",
    "                \"P7\",\n",
    "                \"P8\",\n",
    "                \"P9\",\n",
    "                \"P10\",\n",
    "            ],\n",
    "            \"provider_id\": [\"ProvA\"] * 10 + [\"ProvB\"] * 10,\n",
    "            \"condition_coded\": [\"E11\"] * 3\n",
    "            + [\"I11\"] * 7\n",
    "            + [\"E11.9\"] * 6\n",
    "            + [\"I11.0\"] * 4,\n",
    "        }\n",
    "    )\n",
    ")\n",
    "condition_counts = (\n",
    "    adata.obs.groupby([\"provider_id\", \"condition_coded\"]).size().unstack(fill_value=0)\n",
    ")\n",
    "\n",
    "condition_counts.plot(kind=\"bar\", figsize=(10, 6), alpha=0.75, rot=0)\n",
    "plt.title(\"Condition Coding Discrepancies Between Providers Using ICD-10\")\n",
    "plt.ylabel(\"Count of Conditions\")\n",
    "plt.xlabel(\"Provider ID\")\n",
    "plt.xticks(range(len(condition_counts.index)), condition_counts.index)\n",
    "plt.legend(title=\"ICD-10 Condition Coded\", bbox_to_anchor=(1.05, 1), loc=\"upper left\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, provider A used more general codes (E11 for type 2 diabetes mellitus and I11 for hypertensive heart diseases), whereas provider B used more specific codes (E11.9 for type 2 diabetes mellitus without complications and I11.0 for Hypertensive heart disease with heart failure.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Overlapping symptoms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A more nuanced example of coding bias might involve different providers using entirely different codes for conditions that have overlapping symptoms or can be classified in multiple ways. For instance, some conditions have both acute and chronic forms, and providers might differ in their thresholds for coding one over the other.\n",
    "\n",
    "Let's consider chest pain, which can be coded in multiple ways in ICD-10 based on its cause and nature:\n",
    "\n",
    "- R07.9: Chest pain, unspecified\n",
    "- I20.9: Angina pectoris, unspecified\n",
    "- R07.2: Precordial pain\n",
    "\n",
    "Let's assume that:\n",
    "\n",
    "- Provider A tends to code most cases as unspecified chest pain (R07.9), but sometimes as angina (I20.9).\n",
    "- Provider B tends to use the more specific precordial pain (R07.2) code frequently, but also uses the unspecified codes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata = AnnData(\n",
    "    obs=pd.DataFrame(\n",
    "        {\n",
    "            \"patient_id\": [\n",
    "                \"P1\",\n",
    "                \"P2\",\n",
    "                \"P3\",\n",
    "                \"P4\",\n",
    "                \"P5\",\n",
    "                \"P6\",\n",
    "                \"P7\",\n",
    "                \"P8\",\n",
    "                \"P9\",\n",
    "                \"P10\",\n",
    "                \"P11\",\n",
    "                \"P12\",\n",
    "                \"P13\",\n",
    "                \"P14\",\n",
    "                \"P15\",\n",
    "                \"P16\",\n",
    "                \"P17\",\n",
    "                \"P18\",\n",
    "                \"P19\",\n",
    "                \"P20\",\n",
    "            ],\n",
    "            \"provider_id\": [\"ProvA\"] * 10 + [\"ProvB\"] * 10,\n",
    "            # Different coding choices for chest pain by providers\n",
    "            \"condition_coded\": [\"R07.9\"] * 6\n",
    "            + [\"I20.9\"] * 4\n",
    "            + [\"R07.2\"] * 7\n",
    "            + [\"R07.9\"] * 2\n",
    "            + [\"I20.9\"] * 1,\n",
    "        }\n",
    "    )\n",
    ")\n",
    "\n",
    "condition_counts = (\n",
    "    adata.obs.groupby([\"provider_id\", \"condition_coded\"]).size().unstack(fill_value=0)\n",
    ")\n",
    "\n",
    "condition_counts.plot(kind=\"bar\", figsize=(10, 6), alpha=0.75, rot=0)\n",
    "plt.title(\"Condition Coding Discrepancies Between Providers for Chest Pain\")\n",
    "plt.ylabel(\"Count of Conditions\")\n",
    "plt.xlabel(\"Provider ID\")\n",
    "plt.xticks(range(len(condition_counts.index)), condition_counts.index)\n",
    "plt.legend(\n",
    "    title=\"ICD-10 Code for Chest Pain\", bbox_to_anchor=(1.05, 1), loc=\"upper left\"\n",
    ")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "- Ask data collection partners to enforce standardized protocols and training for coding practices to ensure consistency across different healthcare providers and settings.\n",
    "- Provide ongoing training and updates for medical coders and healthcare providers about the latest coding standards (e.g., ICD-11, CPT codes) to maintain accuracy and reduce variability.\n",
    "- Implement procedures for cross-checking codes entered into the EHR by different coders or systems, and validate coding accuracy with actual clinical documentation.\n",
    "- Consider using disease ontologies such as [Mondo](https://mondo.monarchinitiative.org) to reduce the variability in how different providers and ontologies code the same condition.\n",
    "\n",
    "We provide a tutorial on how to map against Disease ontologies [here](https://ehrapy.readthedocs.io/en/latest/tutorials/notebooks/ontology_mapping.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Attrition bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Attrition bias emerges when there is a systematic difference between participants who continue to be followed up within the healthcare system and those who are lost to follow-up or withdraw from the system.\n",
    "This can lead to skewed outcomes or distorted associations in longitudinal studies, as the data may no longer be representative of the original population.\n",
    "For example, if patients with more severe conditions are more likely to remain engaged in the healthcare system for ongoing treatment, studies may overestimate the prevalence of these conditions and their associated healthcare outcomes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Follow up severeity has censored patients\n",
    "To illustrate the attrition bias, we consider a hypothetical scenario of 100 patients, of which roughly 70% have a \"mild\" condition and 30% have a \"severe\" condition.\n",
    "\n",
    "We represent what a distribution could look like, if we assume that of the \"mild\" condition, only ~60% stay within the monitoring system, while all of the \"severe\" condition stay within the monitoring system due to continued visits to health facilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1400x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chi-square p-value: 3.000103672728807e-08\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import chi2_contingency\n",
    "\n",
    "NUM_PATIENTS = 100\n",
    "NUM_MILD = 70\n",
    "NUM_SEVERE = 30\n",
    "\n",
    "P_MILD_DROPPING = 1 - 0.6\n",
    "\n",
    "rng = np.random.default_rng(seed=42)\n",
    "patient_ids = np.arange(NUM_PATIENTS)\n",
    "condition_severity = rng.choice(\n",
    "    [\"Mild\", \"Severe\"],\n",
    "    size=NUM_PATIENTS,\n",
    "    p=[NUM_MILD / NUM_PATIENTS, NUM_SEVERE / NUM_PATIENTS],\n",
    ")\n",
    "follow_up_severity = [\n",
    "    severity if (severity == \"Severe\" or rng.random() > P_MILD_DROPPING) else \"Dropped\"\n",
    "    for severity in condition_severity\n",
    "]\n",
    "\n",
    "adata = AnnData(\n",
    "    X=np.zeros((len(patient_ids), 1)),\n",
    "    obs=pd.DataFrame(\n",
    "        {\n",
    "            \"Baseline_Severity\": condition_severity,\n",
    "            \"Follow_Up_Severity\": follow_up_severity,\n",
    "        },\n",
    "        index=patient_ids,\n",
    "    ),\n",
    ")\n",
    "\n",
    "baseline_counts = (\n",
    "    adata.obs[\"Baseline_Severity\"]\n",
    "    .value_counts()\n",
    "    .reindex([\"Mild\", \"Severe\", \"Dropped\"], fill_value=0)\n",
    ")\n",
    "followup_counts = (\n",
    "    adata.obs[\"Follow_Up_Severity\"]\n",
    "    .value_counts()\n",
    "    .reindex([\"Mild\", \"Severe\", \"Dropped\"], fill_value=0)\n",
    ")\n",
    "contingency_table = pd.concat([baseline_counts, followup_counts], axis=1)\n",
    "chi2, p_val, dof, expected = chi2_contingency(contingency_table)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(14, 5))\n",
    "adata.obs[\"Baseline_Severity\"].value_counts().plot(kind=\"bar\", ax=ax[0])\n",
    "ax[0].set_title(\"Baseline Condition Severity\")\n",
    "adata.obs[\"Follow_Up_Severity\"].value_counts().plot(kind=\"bar\", ax=ax[1])\n",
    "ax[1].set_title(\"Follow-Up Condition Severity (with Attrition)\")\n",
    "ax[0].set_ylabel(\"n Patients\")\n",
    "ax[1].set_ylabel(\"n Patients\")\n",
    "plt.show()\n",
    "\n",
    "print(f\"Chi-square p-value: {p_val}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The attrition bias is evident when the proportion of patients with 'Severe' conditions increases from baseline to follow-up, not because the condition of patients worsens over time, but because those with 'Mild' conditions are more likely to drop out ('Dropped').\n",
    "The chi-square test determined (p value < 0.05) that the distribution of categoricals differs between base line and follow up."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "- Encourage data collectors to implement robust follow-up procedures to minimize loss to follow-up. Use multiple contact methods and reminders to keep participants engaged over the study period.\n",
    "- Systematically collect and analyze reasons for dropout to understand if they are related to the study conditions or other factors, which could indicate bias.\n",
    "- Compare baseline characteristics of participants who drop out versus those who remain to identify any significant differences that could influence the findings."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confounding bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Confounding bias arises when an outside variable, not accounted for in the analysis, influences both the exposure of interest and the outcome, leading to a spurious association between them.\n",
    "This can distort the true effect of the exposure on the outcome, either exaggerating or underestimating it.\n",
    "For example, if a study investigating the effect of a medication on disease progression fails to account for the severity of illness at baseline, any observed effect might be due more to the initial health status of the patient than to the medication itself."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scenario: Severeity if illness as confounder\n",
    "\n",
    "We simulates a scenario where patients receive medication that has a positive effect on an outcome.\n",
    "However, the severity of illness at baseline (a confounder) also affects the outcome and is negatively correlated with it.\n",
    "We consider 100 patients, and a baseline health status quantity that follows a normal distribution with mean 50 and standard deviation 10. We model a positive medication effect with a mean of 5, and a standard deviation of 2.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between Medication Effect and Outcome: 0.3504454247641602\n",
      "Correlation between Baseline Health Status and Outcome: 0.5909710206762913\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                Outcome   R-squared:                       0.437\n",
      "Model:                            OLS   Adj. R-squared:                  0.425\n",
      "Method:                 Least Squares   F-statistic:                     37.62\n",
      "Date:                Wed, 08 May 2024   Prob (F-statistic):           8.06e-13\n",
      "Time:                        12:15:18   Log-Likelihood:                -304.74\n",
      "No. Observations:                 100   AIC:                             615.5\n",
      "Df Residuals:                      97   BIC:                             623.3\n",
      "Df Model:                           2                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "===============================================================================================\n",
      "                                  coef    std err          t      P>|t|      [0.025      0.975]\n",
      "-----------------------------------------------------------------------------------------------\n",
      "Intercept                      -0.2226      3.504     -0.064      0.949      -7.177       6.732\n",
      "Q('Medication Effect')          1.0356      0.267      3.884      0.000       0.506       1.565\n",
      "Q('Baseline Health Status')     0.4946      0.067      7.354      0.000       0.361       0.628\n",
      "==============================================================================\n",
      "Omnibus:                        3.227   Durbin-Watson:                   1.893\n",
      "Prob(Omnibus):                  0.199   Jarque-Bera (JB):                2.568\n",
      "Skew:                           0.345   Prob(JB):                        0.277\n",
      "Kurtosis:                       3.374   Cond. No.                         341.\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "from scipy.stats import pearsonr\n",
    "\n",
    "rng = np.random.default_rng(42)\n",
    "NUM_PATIENTS = 100\n",
    "BASELINE_MEAN = 50\n",
    "BASELINE_STD = 10\n",
    "TREATMENT_EFFECT = 5\n",
    "TREATMENT_EFFECT_STD = 2\n",
    "baseline_health_status = rng.normal(BASELINE_MEAN, BASELINE_STD, NUM_PATIENTS)\n",
    "positive_medication_effect = rng.normal(\n",
    "    TREATMENT_EFFECT, TREATMENT_EFFECT_STD, NUM_PATIENTS\n",
    ")\n",
    "negative_confounder_effect = baseline_health_status * -0.5\n",
    "outcome = (\n",
    "    baseline_health_status\n",
    "    + positive_medication_effect\n",
    "    + negative_confounder_effect\n",
    "    + rng.normal(0, 5, NUM_PATIENTS)\n",
    ")\n",
    "\n",
    "adata = AnnData(\n",
    "    X=outcome.reshape(-1, 1),\n",
    "    obs=pd.DataFrame(\n",
    "        {\n",
    "            \"Baseline Health Status\": baseline_health_status,\n",
    "            \"Medication Effect\": positive_medication_effect,\n",
    "            \"Outcome\": outcome,\n",
    "        },\n",
    "        index=pd.Index(\n",
    "            [f\"Patient_{i}\" for i in range(NUM_PATIENTS)], name=\"Patient ID\"\n",
    "        ),\n",
    "    ),\n",
    ")\n",
    "\n",
    "corr_med_effect_outcome, _ = pearsonr(\n",
    "    adata.obs[\"Medication Effect\"], adata.obs[\"Outcome\"]\n",
    ")\n",
    "corr_baseline_outcome, _ = pearsonr(\n",
    "    adata.obs[\"Baseline Health Status\"], adata.obs[\"Outcome\"]\n",
    ")\n",
    "\n",
    "print(f\"Correlation between Medication Effect and Outcome: {corr_med_effect_outcome}\")\n",
    "print(\n",
    "    f\"Correlation between Baseline Health Status and Outcome: {corr_baseline_outcome}\"\n",
    ")\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.scatter(\n",
    "    adata.obs[\"Baseline Health Status\"],\n",
    "    adata.obs[\"Outcome\"],\n",
    "    c=\"blue\",\n",
    "    label=\"Baseline Health vs. Outcome\",\n",
    ")\n",
    "plt.scatter(\n",
    "    adata.obs[\"Medication Effect\"],\n",
    "    adata.obs[\"Outcome\"],\n",
    "    c=\"red\",\n",
    "    alpha=0.5,\n",
    "    label=\"Medication Effect vs. Outcome\",\n",
    ")\n",
    "plt.xlabel(\"Baseline Health Status / Medication Effect\")\n",
    "plt.ylabel(\"Outcome\")\n",
    "plt.legend()\n",
    "plt.title(\"Confounding Bias Visualization\")\n",
    "plt.show()\n",
    "\n",
    "# Mitigation strategy: Include baseline health status as a covariate in a regression model\n",
    "\n",
    "adata = ep.ad.move_to_x(\n",
    "    adata, [\"Medication Effect\", \"Baseline Health Status\", \"Outcome\"]\n",
    ")\n",
    "model = ep.tl.ols(\n",
    "    adata, formula=\"Outcome ~ Q('Medication Effect') + Q('Baseline Health Status')\"\n",
    ")\n",
    "print(model.fit().summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The stronger correlation of the baseline health status and the outcome compared to the medication and the outcome suggests that the baseline health status is a confounder.\n",
    "It can be observed that patients with different baseline health statuses have different outcomes even before considering the medication effect."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mitigation strategies\n",
    "\n",
    "To mitigate confounding bias, including the baseline health status as a covariate in a regression model allows for the adjustment of the medication effect on the outcome for the variance explained by baseline health status.\n",
    "The ols regression model fits an ordinary least squares regression using the outcome as the dependent variable and both the medication effect and baseline health status as independent variables.\n",
    "The regression has adjusted for the confounding variable (baseline health status), and the medication effect remains significant.\n",
    "Finally, the results provide evidence against the null hypothesis (that the medication has no effect) and affirm that the medication does have a significant effect on the outcome when the baseline health status is taken into account.\n",
    "\n",
    "More generally, we recommend to:\n",
    "\n",
    "- Plan the study with consideration for potential confounders, ensuring that data on all relevant variables is collected.\n",
    "- Stratify the data during analysis to control for confounding factors, analyzing the effects within each stratum of the confounder.\n",
    "- Employ propensity score matching, stratification, or weighting to balance the distribution of confounding variables between treated and control groups.\n",
    "- Conduct sensitivity analyses to determine how robust the results are to potential confounding.\n",
    "- Consider reducing the feature representation to a smaller set of unrelated components through, for example, PCA."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fast option to detect biases with ehrapy\n",
    "\n",
    "Exploratory analysis remains the most important procedure for spotting and understanding bias in the dataset.\n",
    "\n",
    "To get an overview of potential biases, ehrapy provides a simple method to determine multiple key statistics involving feature correlations, standardized mean differences, categorical value counts and feature importances for predicting other features.\n",
    "\n",
    "First, we need to determine the feature types in the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:20:47.818948Z",
     "start_time": "2024-05-13T12:20:47.227400Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "❗ Feature time_in_hospital was detected as a categorical feature stored numerically. Please verify.\n",
      "❗ Feature num_procedures was detected as a categorical feature stored numerically. Please verify.\n",
      "❗ Feature number_diagnoses was detected as a categorical feature stored numerically. Please verify.\n",
      "❗ Feature readmit_binary was detected as a categorical feature stored numerically. Please verify.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Detected feature types for AnnData object with 101766 obs and 24 vars</span>\n",
       "╠══ 📅<span style=\"font-weight: bold\"> Date features</span>\n",
       "╠══ 📐<span style=\"font-weight: bold\"> Numerical features</span>\n",
       "║   ╠══ num_lab_procedures\n",
       "║   ╚══ num_medications\n",
       "╚══ 🗂️<span style=\"font-weight: bold\"> Categorical features</span>\n",
       "    ╠══ A1Cresult (3 categories)\n",
       "    ╠══ admission_source_id (3 categories)\n",
       "    ╠══ age (3 categories)\n",
       "    ╠══ change (2 categories)\n",
       "    ╠══ diabetesMed (2 categories)\n",
       "    ╠══ discharge_disposition_id (2 categories)\n",
       "    ╠══ gender (3 categories)\n",
       "    ╠══ had_emergency (2 categories)\n",
       "    ╠══ had_inpatient_days (2 categories)\n",
       "    ╠══ had_outpatient_days (2 categories)\n",
       "    ╠══ insulin (4 categories)\n",
       "    ╠══ max_glu_serum (3 categories)\n",
       "    ╠══ medicaid (2 categories)\n",
       "    ╠══ medical_specialty (6 categories)\n",
       "    ╠══ medicare (2 categories)\n",
       "    ╠══ num_procedures (7 categories)\n",
       "    ╠══ number_diagnoses (16 categories)\n",
       "    ╠══ primary_diagnosis (5 categories)\n",
       "    ╠══ race (6 categories)\n",
       "    ╠══ readmit_binary (2 categories)\n",
       "    ╠══ readmitted (3 categories)\n",
       "    ╚══ time_in_hospital (14 categories)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Detected feature types for AnnData object with 101766 obs and 24 vars\u001b[0m\n",
       "╠══ 📅\u001b[1m Date features\u001b[0m\n",
       "╠══ 📐\u001b[1m Numerical features\u001b[0m\n",
       "║   ╠══ num_lab_procedures\n",
       "║   ╚══ num_medications\n",
       "╚══ 🗂️\u001b[1m Categorical features\u001b[0m\n",
       "    ╠══ A1Cresult (3 categories)\n",
       "    ╠══ admission_source_id (3 categories)\n",
       "    ╠══ age (3 categories)\n",
       "    ╠══ change (2 categories)\n",
       "    ╠══ diabetesMed (2 categories)\n",
       "    ╠══ discharge_disposition_id (2 categories)\n",
       "    ╠══ gender (3 categories)\n",
       "    ╠══ had_emergency (2 categories)\n",
       "    ╠══ had_inpatient_days (2 categories)\n",
       "    ╠══ had_outpatient_days (2 categories)\n",
       "    ╠══ insulin (4 categories)\n",
       "    ╠══ max_glu_serum (3 categories)\n",
       "    ╠══ medicaid (2 categories)\n",
       "    ╠══ medical_specialty (6 categories)\n",
       "    ╠══ medicare (2 categories)\n",
       "    ╠══ num_procedures (7 categories)\n",
       "    ╠══ number_diagnoses (16 categories)\n",
       "    ╠══ primary_diagnosis (5 categories)\n",
       "    ╠══ race (6 categories)\n",
       "    ╠══ readmit_binary (2 categories)\n",
       "    ╠══ readmitted (3 categories)\n",
       "    ╚══ time_in_hospital (14 categories)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata = ep.dt.diabetes_130_fairlearn()\n",
    "ep.ad.infer_feature_types(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:20:48.338085Z",
     "start_time": "2024-05-13T12:20:48.269504Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Detected feature types for AnnData object with 101766 obs and 24 vars</span>\n",
       "╠══ 📅<span style=\"font-weight: bold\"> Date features</span>\n",
       "╠══ 📐<span style=\"font-weight: bold\"> Numerical features</span>\n",
       "║   ╠══ num_lab_procedures\n",
       "║   ╠══ num_medications\n",
       "║   ╠══ num_procedures\n",
       "║   ╠══ number_diagnoses\n",
       "║   ╚══ time_in_hospital\n",
       "╚══ 🗂️<span style=\"font-weight: bold\"> Categorical features</span>\n",
       "    ╠══ A1Cresult (3 categories)\n",
       "    ╠══ admission_source_id (3 categories)\n",
       "    ╠══ age (3 categories)\n",
       "    ╠══ change (2 categories)\n",
       "    ╠══ diabetesMed (2 categories)\n",
       "    ╠══ discharge_disposition_id (2 categories)\n",
       "    ╠══ gender (3 categories)\n",
       "    ╠══ had_emergency (2 categories)\n",
       "    ╠══ had_inpatient_days (2 categories)\n",
       "    ╠══ had_outpatient_days (2 categories)\n",
       "    ╠══ insulin (4 categories)\n",
       "    ╠══ max_glu_serum (3 categories)\n",
       "    ╠══ medicaid (2 categories)\n",
       "    ╠══ medical_specialty (6 categories)\n",
       "    ╠══ medicare (2 categories)\n",
       "    ╠══ primary_diagnosis (5 categories)\n",
       "    ╠══ race (6 categories)\n",
       "    ╠══ readmit_binary (2 categories)\n",
       "    ╚══ readmitted (3 categories)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Detected feature types for AnnData object with 101766 obs and 24 vars\u001b[0m\n",
       "╠══ 📅\u001b[1m Date features\u001b[0m\n",
       "╠══ 📐\u001b[1m Numerical features\u001b[0m\n",
       "║   ╠══ num_lab_procedures\n",
       "║   ╠══ num_medications\n",
       "║   ╠══ num_procedures\n",
       "║   ╠══ number_diagnoses\n",
       "║   ╚══ time_in_hospital\n",
       "╚══ 🗂️\u001b[1m Categorical features\u001b[0m\n",
       "    ╠══ A1Cresult (3 categories)\n",
       "    ╠══ admission_source_id (3 categories)\n",
       "    ╠══ age (3 categories)\n",
       "    ╠══ change (2 categories)\n",
       "    ╠══ diabetesMed (2 categories)\n",
       "    ╠══ discharge_disposition_id (2 categories)\n",
       "    ╠══ gender (3 categories)\n",
       "    ╠══ had_emergency (2 categories)\n",
       "    ╠══ had_inpatient_days (2 categories)\n",
       "    ╠══ had_outpatient_days (2 categories)\n",
       "    ╠══ insulin (4 categories)\n",
       "    ╠══ max_glu_serum (3 categories)\n",
       "    ╠══ medicaid (2 categories)\n",
       "    ╠══ medical_specialty (6 categories)\n",
       "    ╠══ medicare (2 categories)\n",
       "    ╠══ primary_diagnosis (5 categories)\n",
       "    ╠══ race (6 categories)\n",
       "    ╠══ readmit_binary (2 categories)\n",
       "    ╚══ readmitted (3 categories)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata.var[\"feature_type\"].loc[[\"time_in_hospital\", \"number_diagnoses\", \"num_procedures\"]] = \"numeric\"\n",
    "ep.ad.feature_type_overview(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Next, we encode the data and call the `detect_bias` function to identify potential biases in the dataset. The bias detection can be called for a pre-defined set of sensitive features, as done here, or we can detect biases for all features in the dataset by setting `sensitive_features=\"all\"`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:25:35.403136Z",
     "start_time": "2024-05-13T12:20:51.598025Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e6c10008d9a54ddcb8901b0ebc9d50d0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata = ep.pp.encode(adata, autodetect=True, encodings=\"label\")\n",
    "results_dict = ep.pp.detect_bias(adata, sensitive_features=[\"race\", \"gender\", \"age\", \"medicare\", \"medicaid\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The `detect_bias` function returns a dictionary of results, including standardized mean differences, feature correlations, feature importances, and categorical value counts for the sensitive features.\n",
    "We can look at each of these results to identify potential biases in the dataset.\n",
    "The feature correlations heatmap can help identify relationships between features that may influence each other:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:25:35.650038Z",
     "start_time": "2024-05-13T12:25:35.407886Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(adata.varp[\"feature_correlations\"], cmap=\"coolwarm\", vmin=-1, vmax=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:25:35.653579Z",
     "start_time": "2024-05-13T12:25:35.650819Z"
    },
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum correlation: -0.97; Features: ehrapycat_readmitted, readmit_binary\n"
     ]
    }
   ],
   "source": [
    "min_idx = np.where(adata.varp[\"feature_correlations\"] == np.min(adata.varp[\"feature_correlations\"]))[0]\n",
    "print(f\"Minimum correlation: {np.min(adata.varp['feature_correlations']).round(2)}; Features: {adata.var.index[min_idx[0]]}, {adata.var.index[min_idx[1]]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Based on the heatmap, we conclude that we do not have strongly correlating features in the dataset. The variables regarding readmission, stored as `readmit_binary` and `readmitted`, unsurprisingly show a strong correlation, however, this is not of interest as none of the sensitive features are involved in this correlation.\n",
    "Let's look at the standardized mean differences for the sensitive features, which look at each numerical feature's mean difference between the sensitive groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-05-13T12:26:39.431716Z",
     "start_time": "2024-05-13T12:26:39.402200Z"
    },
    "collapsed": false
   },
   "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>Sensitive Feature</th>\n",
       "      <th>Sensitive Group</th>\n",
       "      <th>Compared Feature</th>\n",
       "      <th>Standardized Mean Difference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ehrapycat_age</td>\n",
       "      <td>'30 years or younger'</td>\n",
       "      <td>number_diagnoses</td>\n",
       "      <td>-1.055740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ehrapycat_age</td>\n",
       "      <td>'30 years or younger'</td>\n",
       "      <td>num_medications</td>\n",
       "      <td>-0.750826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ehrapycat_gender</td>\n",
       "      <td>Unknown/Invalid</td>\n",
       "      <td>num_procedures</td>\n",
       "      <td>0.697295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ehrapycat_gender</td>\n",
       "      <td>Unknown/Invalid</td>\n",
       "      <td>number_diagnoses</td>\n",
       "      <td>-0.613955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ehrapycat_age</td>\n",
       "      <td>'30 years or younger'</td>\n",
       "      <td>num_procedures</td>\n",
       "      <td>-0.516568</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Sensitive Feature        Sensitive Group  Compared Feature  \\\n",
       "4     ehrapycat_age  '30 years or younger'  number_diagnoses   \n",
       "3     ehrapycat_age  '30 years or younger'   num_medications   \n",
       "0  ehrapycat_gender        Unknown/Invalid    num_procedures   \n",
       "1  ehrapycat_gender        Unknown/Invalid  number_diagnoses   \n",
       "2     ehrapycat_age  '30 years or younger'    num_procedures   \n",
       "\n",
       "   Standardized Mean Difference  \n",
       "4                     -1.055740  \n",
       "3                     -0.750826  \n",
       "0                      0.697295  \n",
       "1                     -0.613955  \n",
       "2                     -0.516568  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_dict[\"standardized_mean_differences\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The results above show that the age group \"30 years or younger\" has meaningfully fewer diagnoses and medications compared to all other age groups. For downstream analyses, this should be taken into consideration, especially when comparing outcomes across different age groups."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Biases in (EHR) data, as well as models and analyses building on it, can occur in many forms, and sometimes be hard to find.\n",
    "Discussions with experts in the domain where the data was acquired, exploratory data analysis, and reporting of processing steps and are required towards mitigating biases."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ehrapy",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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