From 586b8050c3456c1bc409e63476ff8d61b27b6663 Mon Sep 17 00:00:00 2001
From: Siddharth Chaini <40721514+sidchaini@users.noreply.github.com>
Date: Wed, 4 Dec 2024 20:55:25 -0500
Subject: [PATCH] Added tutorial to docs

Tutorial is from TVS colloquium
---
 docs/index.rst      |    1 +
 docs/tutorial.ipynb | 1912 +++++++++++++++++++++++++++++++++++++++++++
 docs/tutorial.rst   |    9 +
 3 files changed, 1922 insertions(+)
 create mode 100644 docs/tutorial.ipynb
 create mode 100644 docs/tutorial.rst

diff --git a/docs/index.rst b/docs/index.rst
index 5cdc844..4f7d652 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -67,5 +67,6 @@ API Documentation
    :maxdepth: 2
    :caption: API Reference
 
+   tutorial
    classifier
    distances
\ No newline at end of file
diff --git a/docs/tutorial.ipynb b/docs/tutorial.ipynb
new file mode 100644
index 0000000..b7f4b5a
--- /dev/null
+++ b/docs/tutorial.ipynb
@@ -0,0 +1,1912 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "view-in-github"
+   },
+   "source": [
+    "# DistClassiPy Tutorial\n",
+    "\n",
+    "**Author**: Sid Chaini, October 22, 2024\n",
+    "\n",
+    "This notebook gives a quick demo of using DistClassiPy to classify light curve features. For this demo, I will use the data from the Zwicky Transient Facility Source Classification Project (SCoPe, [Healy et al. 2024)](https://arxiv.org/abs/2312.00143).\n",
+    "\n",
+    "<!-- [![github-badge](https://img.shields.io/badge/GitHub-sidchaini/DistClassiPyTutorial-blue)](https://github.com/sidchaini/DistClassiPyTutorial) -->\n",
+    "[![colab-button](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sidchaini/DistClassiPyTutorial/blob/main/tutorial.ipynb)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 0. Prerequisites"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us first install DistClassiPy from PYPI. I am installing 0.2.1, the latest as of 2024-10-22"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:52.501496Z",
+     "iopub.status.busy": "2024-10-22T15:07:52.501255Z",
+     "iopub.status.idle": "2024-10-22T15:07:53.780448Z",
+     "shell.execute_reply": "2024-10-22T15:07:53.779566Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:52.501473Z"
+    },
+    "id": "ZZ5CAUOfHwO4",
+    "outputId": "d49967a0-e20f-497b-b5f4-bfb4e138d628",
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: distclassipy==0.2.1 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (0.2.1)\n",
+      "Requirement already satisfied: joblib>=1.3.2 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from distclassipy==0.2.1) (1.4.2)\n",
+      "Requirement already satisfied: numpy>=1.25.2 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from distclassipy==0.2.1) (1.26.4)\n",
+      "Requirement already satisfied: pandas>=2.0.3 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from distclassipy==0.2.1) (2.2.2)\n",
+      "Requirement already satisfied: scikit-learn>=1.2.2 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from distclassipy==0.2.1) (1.5.1)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.2 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from pandas>=2.0.3->distclassipy==0.2.1) (2.9.0.post0)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from pandas>=2.0.3->distclassipy==0.2.1) (2024.1)\n",
+      "Requirement already satisfied: tzdata>=2022.7 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from pandas>=2.0.3->distclassipy==0.2.1) (2024.1)\n",
+      "Requirement already satisfied: scipy>=1.6.0 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from scikit-learn>=1.2.2->distclassipy==0.2.1) (1.14.1)\n",
+      "Requirement already satisfied: threadpoolctl>=3.1.0 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from scikit-learn>=1.2.2->distclassipy==0.2.1) (3.5.0)\n",
+      "Requirement already satisfied: six>=1.5 in /Users/sidchaini/miniconda3/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas>=2.0.3->distclassipy==0.2.1) (1.16.0)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install distclassipy==0.2.1 # latest as of 2024-10-22"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's download a dataset I prepared from the ZTF SCoPE data for this tutorial."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:53.782596Z",
+     "iopub.status.busy": "2024-10-22T15:07:53.781887Z",
+     "iopub.status.idle": "2024-10-22T15:07:56.317781Z",
+     "shell.execute_reply": "2024-10-22T15:07:56.315576Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:53.782567Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "!wget https://github.com/sidchaini/DistClassiPyTutorial/archive/refs/heads/main.zip\n",
+    "!unzip main.zip\n",
+    "!mv DistClassiPyTutorial-main/* .\n",
+    "!rm -rf main.zip DistClassiPyTutorial-main"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:56.328985Z",
+     "iopub.status.busy": "2024-10-22T15:07:56.328617Z",
+     "iopub.status.idle": "2024-10-22T15:07:57.224943Z",
+     "shell.execute_reply": "2024-10-22T15:07:57.224680Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:56.328958Z"
+    },
+    "id": "9GC3xlkMQu-Z"
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "seed = 0\n",
+    "np.random.seed(seed)\n",
+    "import pandas as pd\n",
+    "import distclassipy as dcpy\n",
+    "import utils\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.metrics import accuracy_score, f1_score"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 1. Visualizing 2D distance metric spaces\n",
+    "\n",
+    "We can visualize the distance metric space by plotting the locus of a central point, such as (5, 5) in a given two dimensional space. The locus appear as contour lines, which can illustrate geometry of the space when plotted in Euclidean space."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:57.225415Z",
+     "iopub.status.busy": "2024-10-22T15:07:57.225315Z",
+     "iopub.status.idle": "2024-10-22T15:07:57.319570Z",
+     "shell.execute_reply": "2024-10-22T15:07:57.319113Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:57.225404Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "utils.visualize_distance(\"euclidean\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2. Data\n",
+    "\n",
+    "For this example, we will be using data from \"The ZTF Source Classification Project: III. A Catalog of Variable Sources\" through which they have made available on Zenodo.\n",
+    "\n",
+    "[![zenodo-badge](https://zenodo.org/badge/DOI/10.5281/zenodo.13920513.svg)](https://zenodo.org/records/13920513)\n",
+    "\n",
+    "I downloaded and sampled them to choose 4000 objects from 4 classes of variable stars:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:57.320140Z",
+     "iopub.status.busy": "2024-10-22T15:07:57.319962Z",
+     "iopub.status.idle": "2024-10-22T15:07:57.536012Z",
+     "shell.execute_reply": "2024-10-22T15:07:57.535695Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:57.320125Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "features = pd.read_csv(\"data/ztfscope_features.csv\", index_col=0)\n",
+    "labels = pd.read_csv(\"data/ztfscope_labels.csv\", index_col=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:57.536467Z",
+     "iopub.status.busy": "2024-10-22T15:07:57.536386Z",
+     "iopub.status.idle": "2024-10-22T15:07:57.540395Z",
+     "shell.execute_reply": "2024-10-22T15:07:57.540168Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:57.536459Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "class\n",
+       "CEP      1000\n",
+       "DSCT     1000\n",
+       "RR       1000\n",
+       "RRc      1000\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "labels.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For the sake of simplicity, let us focus on three features from the complete ZTF SCoPE features (refer to [Healy et al. 2024](https://arxiv.org/abs/2312.00143) for more details):\n",
+    "- ```inv_vonneumannratio```: Inverse of von Neumann ratio ([von Neumann 1941](https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-12/issue-4/Distribution-of-the-Ratio-of-the-Mean-Square-Successive-Difference/10.1214/aoms/1177731677.full), [1942](https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-13/issue-1/A-Further-Remark-Concerning-the-Distribution-of-the-Ratio-of/10.1214/aoms/1177731645.full)), which is the ratio of correlated variance and variance - it detects non-randomness, and a high value implies periodic behaviour.\n",
+    "- ```norm_peak_to_peak_amp```: Normalized peak-to-peak amplitude [(Sokolovsky et al. 2009)](https://arxiv.org/abs/0901.1064) - it tells us about the source brightness.\n",
+    "- ```stetson_k```: Stetson K coefficient ([Stetson 1996](https://iopscience.iop.org/article/10.1086/133808/meta?casa_token=EMo0hxKqIkUAAAAA:b8y8ONGzEQAJq2WJfrCASQt_FMw7HX_h7i-VChDbTYc1ShDkEih4I2Sm184VFLTS1UpDbATGN8GPmTY4YXRG87jP2Q)) is related to the observed scatter - it tells us about the light curve shape."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:57.540916Z",
+     "iopub.status.busy": "2024-10-22T15:07:57.540804Z",
+     "iopub.status.idle": "2024-10-22T15:07:57.543236Z",
+     "shell.execute_reply": "2024-10-22T15:07:57.542191Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:57.540908Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "feature_names = [\"inv_vonneumannratio\", \"norm_peak_to_peak_amp\", \"stetson_k\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:57.546430Z",
+     "iopub.status.busy": "2024-10-22T15:07:57.545773Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.801178Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.800898Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:57.546394Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 837.75x750 with 12 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df = features.loc[:, feature_names]\n",
+    "df[\"class\"] = labels[\"class\"]\n",
+    "sns.pairplot(df, hue=\"class\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.802094Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.801943Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.804457Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.804043Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.802079Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "X = features.loc[:, feature_names].to_numpy()\n",
+    "y = labels.to_numpy().ravel()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.805018Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.804901Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.813308Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.812865Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.805010Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "X_train, X_test, y_train, y_test = train_test_split(\n",
+    "    X, y, test_size=0.25, random_state=seed\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 3. DistanceMetricClassifier\n",
+    "\n",
+    "The DistanceMetricClassifier calculates the distance between a centroid for each class, and each test point, and scales it by the standard deviation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.814506Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.814217Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.822433Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.822171Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.814482Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --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",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --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",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\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",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\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",
+       "}\n",
+       "\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>DistanceMetricClassifier()</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\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;DistanceMetricClassifier<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DistanceMetricClassifier()</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "DistanceMetricClassifier()"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clf = dcpy.DistanceMetricClassifier()\n",
+    "clf.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.825060Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.824927Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.831469Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.830648Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.825051Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "y_pred = clf.predict_and_analyse(X_test, metric=\"euclidean\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.832094Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.832007Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.848732Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.846298Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.832086Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy = 0.642\n",
+      "F1 = 0.635\n"
+     ]
+    }
+   ],
+   "source": [
+    "acc = accuracy_score(y_true=y_test, y_pred=y_pred)\n",
+    "f1 = f1_score(y_true=y_test, y_pred=y_pred, average=\"macro\")\n",
+    "\n",
+    "print(f\"Accuracy = {acc:.3f}\")\n",
+    "print(f\"F1 = {f1:.3f}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.850852Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.850293Z",
+     "iopub.status.idle": "2024-10-22T15:07:58.862163Z",
+     "shell.execute_reply": "2024-10-22T15:07:58.861732Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.850840Z"
+    }
+   },
+   "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>CEP_dist</th>\n",
+       "      <th>DSCT_dist</th>\n",
+       "      <th>RR_dist</th>\n",
+       "      <th>RRc_dist</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.805759</td>\n",
+       "      <td>2.641208</td>\n",
+       "      <td>0.824424</td>\n",
+       "      <td>2.848626</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.220526</td>\n",
+       "      <td>1.423540</td>\n",
+       "      <td>2.151157</td>\n",
+       "      <td>1.164521</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.325282</td>\n",
+       "      <td>3.792195</td>\n",
+       "      <td>1.503853</td>\n",
+       "      <td>4.076885</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.064865</td>\n",
+       "      <td>8.376741</td>\n",
+       "      <td>1.781160</td>\n",
+       "      <td>1.323827</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.480929</td>\n",
+       "      <td>2.229321</td>\n",
+       "      <td>0.915641</td>\n",
+       "      <td>2.055988</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>995</th>\n",
+       "      <td>1.015133</td>\n",
+       "      <td>3.548696</td>\n",
+       "      <td>1.743593</td>\n",
+       "      <td>0.106400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>996</th>\n",
+       "      <td>0.957050</td>\n",
+       "      <td>10.627296</td>\n",
+       "      <td>1.705001</td>\n",
+       "      <td>1.205451</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>997</th>\n",
+       "      <td>0.810418</td>\n",
+       "      <td>14.319456</td>\n",
+       "      <td>1.574726</td>\n",
+       "      <td>1.767178</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>998</th>\n",
+       "      <td>1.023541</td>\n",
+       "      <td>2.556731</td>\n",
+       "      <td>1.699193</td>\n",
+       "      <td>0.937611</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>999</th>\n",
+       "      <td>1.452081</td>\n",
+       "      <td>1.219772</td>\n",
+       "      <td>2.336256</td>\n",
+       "      <td>2.059953</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1000 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     CEP_dist  DSCT_dist   RR_dist  RRc_dist\n",
+       "0    0.805759   2.641208  0.824424  2.848626\n",
+       "1    1.220526   1.423540  2.151157  1.164521\n",
+       "2    1.325282   3.792195  1.503853  4.076885\n",
+       "3    1.064865   8.376741  1.781160  1.323827\n",
+       "4    0.480929   2.229321  0.915641  2.055988\n",
+       "..        ...        ...       ...       ...\n",
+       "995  1.015133   3.548696  1.743593  0.106400\n",
+       "996  0.957050  10.627296  1.705001  1.205451\n",
+       "997  0.810418  14.319456  1.574726  1.767178\n",
+       "998  1.023541   2.556731  1.699193  0.937611\n",
+       "999  1.452081   1.219772  2.336256  2.059953\n",
+       "\n",
+       "[1000 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clf.centroid_dist_df_"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4. EnsembleDistanceClassifier\n",
+    "\n",
+    "The EnsembleDistanceClassifier splits the training set into multiple quantiles based on a feature (```feat_idx```), iterates among all metrics to see which one performs the best on a validation set, and then prepares an ensemble based on the best performing metric for each quantile."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:58.863114Z",
+     "iopub.status.busy": "2024-10-22T15:07:58.862945Z",
+     "iopub.status.idle": "2024-10-22T15:07:59.859816Z",
+     "shell.execute_reply": "2024-10-22T15:07:59.859430Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:58.863103Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --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",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --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",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 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",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 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",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 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-2 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-2 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-2 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-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 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-2 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-2 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-2 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-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 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-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 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-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 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-2 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-2 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-2 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-2 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-2 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-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 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-2 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-2 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-2 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-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 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-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 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-2 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-2 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-2 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-2 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-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>EnsembleDistanceClassifier(feat_idx=0, random_state=0)</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\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;EnsembleDistanceClassifier<span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>EnsembleDistanceClassifier(feat_idx=0, random_state=0)</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "EnsembleDistanceClassifier(feat_idx=0, random_state=0)"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_clf = dcpy.EnsembleDistanceClassifier(feat_idx=0, random_state=seed)\n",
+    "ensemble_clf.fit(X_train, y_train, n_quantiles=6)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:59.860407Z",
+     "iopub.status.busy": "2024-10-22T15:07:59.860317Z",
+     "iopub.status.idle": "2024-10-22T15:07:59.895733Z",
+     "shell.execute_reply": "2024-10-22T15:07:59.895452Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:59.860399Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "y_pred_ensemble = ensemble_clf.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:59.896335Z",
+     "iopub.status.busy": "2024-10-22T15:07:59.896230Z",
+     "iopub.status.idle": "2024-10-22T15:07:59.906534Z",
+     "shell.execute_reply": "2024-10-22T15:07:59.905742Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:59.896327Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Accuracy = 0.783\n",
+      "F1 = 0.783\n"
+     ]
+    }
+   ],
+   "source": [
+    "acc = accuracy_score(y_true=y_test, y_pred=y_pred_ensemble)\n",
+    "f1 = f1_score(y_true=y_test, y_pred=y_pred_ensemble, average=\"macro\")\n",
+    "\n",
+    "print(f\"Accuracy = {acc:.3f}\")\n",
+    "print(f\"F1 = {f1:.3f}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:59.908546Z",
+     "iopub.status.busy": "2024-10-22T15:07:59.908325Z",
+     "iopub.status.idle": "2024-10-22T15:07:59.917280Z",
+     "shell.execute_reply": "2024-10-22T15:07:59.915140Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:59.908536Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Quantile 1               taneja\n",
+       "Quantile 2         kumarjohnson\n",
+       "Quantile 3            hellinger\n",
+       "Quantile 4             canberra\n",
+       "Quantile 5    vicis_wave_hedges\n",
+       "Quantile 6            euclidean\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_clf.best_metrics_per_quantile_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:59.919950Z",
+     "iopub.status.busy": "2024-10-22T15:07:59.919549Z",
+     "iopub.status.idle": "2024-10-22T15:07:59.938890Z",
+     "shell.execute_reply": "2024-10-22T15:07:59.938380Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:59.919919Z"
+    }
+   },
+   "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>Quantile 1</th>\n",
+       "      <th>Quantile 2</th>\n",
+       "      <th>Quantile 3</th>\n",
+       "      <th>Quantile 4</th>\n",
+       "      <th>Quantile 5</th>\n",
+       "      <th>Quantile 6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>euclidean</th>\n",
+       "      <td>60.8</td>\n",
+       "      <td>59.2</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>braycurtis</th>\n",
+       "      <td>53.6</td>\n",
+       "      <td>59.2</td>\n",
+       "      <td>72.8</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>50.4</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>canberra</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>72.8</td>\n",
+       "      <td>80.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>59.2</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cityblock</th>\n",
+       "      <td>63.2</td>\n",
+       "      <td>58.4</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>chebyshev</th>\n",
+       "      <td>62.4</td>\n",
+       "      <td>60.8</td>\n",
+       "      <td>57.6</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>clark</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>77.6</td>\n",
+       "      <td>67.2</td>\n",
+       "      <td>57.6</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>correlation</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>20.8</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>48.8</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>83.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>cosine</th>\n",
+       "      <td>48.8</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>69.6</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>hellinger</th>\n",
+       "      <td>88.0</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>67.2</td>\n",
+       "      <td>49.6</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>jaccard</th>\n",
+       "      <td>52.8</td>\n",
+       "      <td>64.8</td>\n",
+       "      <td>70.4</td>\n",
+       "      <td>58.4</td>\n",
+       "      <td>49.6</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>lorentzian</th>\n",
+       "      <td>65.6</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>56.0</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>marylandbridge</th>\n",
+       "      <td>24.8</td>\n",
+       "      <td>18.4</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>37.6</td>\n",
+       "      <td>41.6</td>\n",
+       "      <td>87.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>meehl</th>\n",
+       "      <td>44.0</td>\n",
+       "      <td>52.8</td>\n",
+       "      <td>57.6</td>\n",
+       "      <td>62.4</td>\n",
+       "      <td>46.4</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>wave_hedges</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>72.0</td>\n",
+       "      <td>79.2</td>\n",
+       "      <td>65.6</td>\n",
+       "      <td>56.8</td>\n",
+       "      <td>87.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>add_chisq</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>75.2</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>67.2</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>acc</th>\n",
+       "      <td>64.0</td>\n",
+       "      <td>59.2</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>chebyshev_min</th>\n",
+       "      <td>70.4</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>56.8</td>\n",
+       "      <td>36.8</td>\n",
+       "      <td>40.8</td>\n",
+       "      <td>52.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>dice</th>\n",
+       "      <td>0.8</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>34.4</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>50.4</td>\n",
+       "      <td>26.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>google</th>\n",
+       "      <td>64.0</td>\n",
+       "      <td>63.2</td>\n",
+       "      <td>75.2</td>\n",
+       "      <td>56.8</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>89.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>jeffreys</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>72.8</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>67.2</td>\n",
+       "      <td>49.6</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>jensenshannon_divergence</th>\n",
+       "      <td>85.6</td>\n",
+       "      <td>66.4</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>50.4</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>kumarjohnson</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>76.0</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>48.8</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>penroseshape</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>53.6</td>\n",
+       "      <td>60.8</td>\n",
+       "      <td>59.2</td>\n",
+       "      <td>48.8</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>prob_chisq</th>\n",
+       "      <td>80.8</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>50.4</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>taneja</th>\n",
+       "      <td>92.8</td>\n",
+       "      <td>74.4</td>\n",
+       "      <td>85.6</td>\n",
+       "      <td>67.2</td>\n",
+       "      <td>50.4</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vicis_symmetric_chisq</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>64.8</td>\n",
+       "      <td>77.6</td>\n",
+       "      <td>67.2</td>\n",
+       "      <td>56.8</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vicis_wave_hedges</th>\n",
+       "      <td>91.2</td>\n",
+       "      <td>66.4</td>\n",
+       "      <td>79.2</td>\n",
+       "      <td>68.0</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>90.4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                          Quantile 1  Quantile 2  Quantile 3  Quantile 4  \\\n",
+       "euclidean                       60.8        59.2        56.0        53.6   \n",
+       "braycurtis                      53.6        59.2        72.8        60.0   \n",
+       "canberra                        91.2        72.8        80.0        68.0   \n",
+       "cityblock                       63.2        58.4        56.0        55.2   \n",
+       "chebyshev                       62.4        60.8        57.6        53.6   \n",
+       "clark                           91.2        68.0        77.6        67.2   \n",
+       "correlation                     30.4        20.8        53.6        48.8   \n",
+       "cosine                          48.8        43.2        69.6        52.0   \n",
+       "hellinger                       88.0        68.0        85.6        67.2   \n",
+       "jaccard                         52.8        64.8        70.4        58.4   \n",
+       "lorentzian                      65.6        54.4        56.0        55.2   \n",
+       "marylandbridge                  24.8        18.4        40.0        37.6   \n",
+       "meehl                           44.0        52.8        57.6        62.4   \n",
+       "wave_hedges                     91.2        72.0        79.2        65.6   \n",
+       "add_chisq                       91.2        75.2        85.6        67.2   \n",
+       "acc                             64.0        59.2        55.2        55.2   \n",
+       "chebyshev_min                   70.4        52.0        56.8        36.8   \n",
+       "dice                             0.8        20.0        34.4        44.0   \n",
+       "google                          64.0        63.2        75.2        56.8   \n",
+       "jeffreys                        91.2        72.8        85.6        67.2   \n",
+       "jensenshannon_divergence        85.6        66.4        85.6        68.0   \n",
+       "kumarjohnson                    91.2        76.0        85.6        68.0   \n",
+       "penroseshape                    34.4        53.6        60.8        59.2   \n",
+       "prob_chisq                      80.8        64.0        85.6        68.0   \n",
+       "taneja                          92.8        74.4        85.6        67.2   \n",
+       "vicis_symmetric_chisq           91.2        64.8        77.6        67.2   \n",
+       "vicis_wave_hedges               91.2        66.4        79.2        68.0   \n",
+       "\n",
+       "                          Quantile 5  Quantile 6  \n",
+       "euclidean                       43.2        90.4  \n",
+       "braycurtis                      50.4        90.4  \n",
+       "canberra                        59.2        90.4  \n",
+       "cityblock                       43.2        90.4  \n",
+       "chebyshev                       44.0        90.4  \n",
+       "clark                           57.6        90.4  \n",
+       "correlation                     44.0        83.2  \n",
+       "cosine                          43.2        90.4  \n",
+       "hellinger                       49.6        90.4  \n",
+       "jaccard                         49.6        90.4  \n",
+       "lorentzian                      44.0        90.4  \n",
+       "marylandbridge                  41.6        87.2  \n",
+       "meehl                           46.4        90.4  \n",
+       "wave_hedges                     56.8        87.2  \n",
+       "add_chisq                       48.0        90.4  \n",
+       "acc                             43.2        90.4  \n",
+       "chebyshev_min                   40.8        52.8  \n",
+       "dice                            50.4        26.4  \n",
+       "google                          44.0        89.6  \n",
+       "jeffreys                        49.6        90.4  \n",
+       "jensenshannon_divergence        50.4        90.4  \n",
+       "kumarjohnson                    48.8        90.4  \n",
+       "penroseshape                    48.8        90.4  \n",
+       "prob_chisq                      50.4        90.4  \n",
+       "taneja                          50.4        90.4  \n",
+       "vicis_symmetric_chisq           56.8        90.4  \n",
+       "vicis_wave_hedges               60.0        90.4  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ensemble_clf.quantile_scores_df_.drop_duplicates()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2024-10-22T15:07:59.939568Z",
+     "iopub.status.busy": "2024-10-22T15:07:59.939471Z",
+     "iopub.status.idle": "2024-10-22T15:08:00.089074Z",
+     "shell.execute_reply": "2024-10-22T15:08:00.088103Z",
+     "shell.execute_reply.started": "2024-10-22T15:07:59.939559Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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3b3bu3Mk777zDe++9h62tLY888sgDndva2poff/yRF154gfDwcFq1asX7779vsNjK09OTkydPMm/ePAYMGIBarcbPz49BgwZhZmaGSCRi+/btzJo1izZt2hASEsLHH39M79696/tSPRSu51bw5r44pvX0Z0JXX3LKVHz8azJH4gr0fXoEOrLgsRD967eHtATgq1NpfHUq/aFrbghcrKUseiwYW5mEMmUNV7PLmbHjCmU3jRNfBxlTu/tiI5OQq1Dz9blMdl7OMbLq+sfJyoK5/QJvXodaYnLLeW1vrD4l1r6reViIzZjSzRcbqYSUoioWHrhukh56J0tzXuntj41UgkJVy/W8Ct7cH49CbdoZBP4OYnNzCpJiSDj2AzXKCqQ29rgEtqbvK6uQ2dgbW169Y2ct4+0Zj+Plakexoop9R6+y5LOD1N7MOLJm6zEs5Rasmz8Se2sZp6JTGfryBtPJ4WrioQKiujuDFQUEBP4WQslXHULJVx1CyVcdQslXHULJ11sIJV91NHjJ167/++ziHyhPv1dvY9UXpm2WCwgICAgICAgImAzCI7GAwP+Iu5OVsSU0CgrLTCuO9J8SFZVlbAmNgsAgV2NLaBRYSoWfWYGHjImHCgjfKAEBAQEBAQEBU0HIKiAgIGBsRrfzYHS4h0FbVqmKl/fE3tV3waOBhHvb8X5kkslVC5rQxYcJXXwM2tKLq3h2SxQAnnZSpvf0J9TTFnOxiHNppXx8LIUSE8mqcDtn3h2Azz28/ZuOJ7NgezTvP9OOHi1ccLOTU6Wu5UJyMcv2XCMpr8IIahsWZ2sLXujpR4S/AzJzM7JKVaw4lEj8be91UjdfhrRxw1om5mpWOR9EJpFZajqzBE+GuvFkqJtBW3aZijcOJABgbiZibHsPuvjZIzETcTWngs0XsvQL+kwJa0spS6YNZGivNrg4WBOdkMWcD/ZxMe5W8Y1FUwcwcVgE9tZyTl9JZdbK3SRlFP7FqAKNBcFwFRBoIqSXKHn70K30Vxrt3esqB7dyxdRXW6YUVjF79620NX9cB5nEjFVPtiapsJJXd+n2P9/Nh+VDWzBj+1WTuy6Pv3cMsdktz0oLT1u2v9yD/Rd1oQpX0kvZfS6DrGIl9lbmzB7ckm9ndafLwkPc46PTZLGWivnk6VAuZ5Qxd08spVU1eDvIKb/NIHumkxdPtfNgxaEbZJepmNzNl9UjWvPs5ktUa0znYmSWqnj/12T9a81ta6+f6eBJO08b/nMiDWW1lmc7eTKrpx/vHkkyhtQG5bM3R9Iq0J1JS78lp1DB2EHtObBuKu3HrCa7QMHs8b2ZMboHU97eQWp2MYunDeTHtZMJH7PaNDILmHiogGm/OwEBE0KjraNUWavfytUag/3+jnKGtHHl05tlYU0VTV0dxVU1+u2PYgNtPG1wt5Xy3uFEUoqqSCmqYsWhRELcrGnvY2dk1fVPcUU1BQq1fusf6k5KfgWnb+i8Rt+cSOVsYhGZxVVcyyhj5Q+xeDla3tNL25QZ18mb/HI17x1OJC63ghyFmvNppWTfFnM9KtyTrWczOJFUTHJhFcsO3sDJ2oIezZ2MqLz+0dTVUaaq1W8VN+8RcnMzejVzYNulHOLyKkktUbL+TCbBLlYEOlkaWXX9IpNKGN4nlAXrDnAyKoXkzCKWbThCUmYRU0boSoe/OKYn72+MZP9vMVxLzGHy0u14ONsytFdrI6uvJ0Si+tsaIYLHVUCgieBhK+XLp9tQo6kjIb+Sby5mUVipmwK3EIt4uZc/G85k3DPhuinhZS/j+8kdqdZoickpZ/3JNPLLqzEX657DazS3yvVWa7TU1UGoly0XTahS0p2Yi0WM6OzDl5H3LjAgtxDzdFc/0goryS6pumefpkr3QEfOpZby1uAQ2nnbUlBRzd7oXPZfzQPAw06Kk7UFF24Lm6ms1hCXW04bDxt+jTed6WF3Gylrh7ekRqslsbCKnVG5FFXV4O8oRyI2Iyb3VonTHIWawspqmjtbklRkOp8JiViMRCJGdUceX5W6hm5hAfh7OuLhbMuv527NXikqVZyPSSci1I+dR6IftuT6R/C4CggIGJsbBZV8ciKNZYeT+PJUOq42FrzzeDAyie4rPCHCm/j8SpOLab2T2Nxy3jucyNy9sXz4azIetlI+HhWK3NyM2NxylDUapvXwQyoxQyYxY3pPf8RmIhytzI0tvUEZFOaJrdyc704bFpp47pEAEj4cQuLaofRp7cbYtSepMaGpcQAPOxnDwtzJLFEyZ1cs+6JzeblPAINauQDgZKmrJFdSZVgpq7iyBkerhq9697BIKqziy9MZrD6WwubzWbhYWbDg0UBkEjPsZebUaLRU1WgNjilT1WJnYnmHK6rUnLmSyvxJ/fFwtsXMTMSYQe2JaOOHu7MN7k66vLr5xeUGx+UXV+DmKOTcbQqY1idWQMBEuZyl0P+dVgI3Cqv4bFQbugU4oFDVEuphw+v7rhtR4cPhXGqp/u/kwiricsvZPqkDfYKd+Skmn6UH4nm1byAj2nlQVweR8QXE51Vg6mVWxnT342hMHnl3pCTbfS6D3+LycbWT8cKjQXw+pRPDV/2Gulb7JyM1PcxEEJ9XwfqTOqP9RkElAc6WDG3rzsHYgvscbTpcyblliGWU6gzZD4a1pLOvnck9rNyPSUu388XCUSQfWERtrYao+Cy+OxxFeAsvY0t7OJi4x1UwXAUEmiBV1RpyylS420rxdZDjZiNl87gwgz5z+jTjel4FSw7e+JNRmj4Vag2ZJSq87GUAXEgvY9ymS9jJJGjq6qhQa9g9pSO/JpjO6vE78XKU07OFK5O/OHvXvnJVLeWqWlIKKrmUUkzsmsEMaufJvguZ9xipaVJUWU1qkdKgLa1ISa8gXfxq0U1Pq4OlBUWVt7JLOFqZk5hf+fCEPmSqarTklqtxs5FyLbccc7EZluZmBl5Xu5slg02NlKwiBkz/HEuZObZWMnKLytn67jhSsovJLdIZ+K6ONvq/da+tuXIj21iS6xezxhmbWl8IhquAQBNEJjHDzVZKaVIxp1JLiEwwjNP78MlWbD6XyQUTjusE3aITT3sph68bTgP/sWAr3NsWe0tzTiUXG0PeQ+Hprn4UlquJvJb7l/1EIhEiEUglpuWNuZpdjo+DzKDNx0FOnkINQE6ZmqKKajr42pFYoDNULS3EtHS3YW/0X1+zpoxUYoartQUnlTWkFiup1Whp5W7NhQzd7I27jRRnKwsSC00nvvVOqlQ1VKlqsLeR079LCAvWHSA1u5icQgV9OjXXG6o2VlI6tfZl/e7TRlYs8CAIhquAQBPg2U5eXEgvo6CyGkdLc0a380BbV8eJ5BIU6tp7LsgqqKwmv6L6HqM1Xab39ONUcgl55WqcrCyY2MUHrRYiby6wGdTKlfTiKkqVNbT2sGFmrwB2Xsoho8Q0Pa4ikc5w3Xkm3SA9mq+zJUM7eHM8Lp+icjWeDnJeHBiMqlpLZIxpGWs7L2bz6ZhQ/q+zN0cTCmnpbs2Qtm6svi3N087L2Twb4UNmiYochYrnu/lSVFHNicQiIyqvX8aEe3A5S0FRZTX2cnNGhLqhrYMzaaUoa7QcTy7hmfaeVKo1KGu0jO/oyY2CSpNamPUH/SOCEYlEJKTlE+jjzPKXBpOQls+WH88D8Mn235k3sR+JGYWkZhezZNpAcgoV/HA85j4jNxGEUAEBAQFj42Rpziu9/bGRSlCoarmeV8Gb++NRqE1vmu+vcLGWsuixYGxlEsqUNVzNLmfGjiv66U5fBxlTu/tiI5OQq1Dz9blMdl7OMbLqhqNnC1e8nSzZccowBZq6Rkvn5k5M7huInaUFhQoVZxKLGLb6OEXlpvUwcz2vggU/XGdaTz+e6+JDbpmK/xxL4cj1W/Gt285nITMXM+fRQKylEq5mKZizO8akcrg6Wpozo5sv1lIx5epaEgqqePtwoj5t3raL2dTVefBSTz/MxWZczSln83nTLE9sZy3j7RmP4+VqR7Giin1Hr7Lks4PU3sw4smbrMSzlFqybPxJ7axmnolMZ+vIG08jhCo02jVV9IaqrM/VlCwICDcvIjZeMLaFRUFhmml7Nv8uN+DxjS2gUBAa5GltCo8DfXVip/gc71241toRGgfLsqgYdX95veb2NpYx8s97Gqi8Ej6uAgICAgICAgKkghAoICDwcevfuTbt27fjoo4+MLeVvceDTr40toVHg2LGnsSU0CkoLS40toVGQZ2taFZn+KWYmvsJboBFi4qECguEqINBEsLaUsuSFxxjauw0uDjZEJ2QyZ81eLsZmADCsTyiTR3QjvIU3TvZWRIxbzZUEE0nvcpMz7w64Z8nSTceTWbA9mvefaUePFi642cmpUtdyIbmYZXuukZRXYQS1DYeZmYgFo9ox5pFA3Ozl5BRX8fWxRN7fZVj1Z+HT4UzsF4ydlQVnrufz8vrTJOUq/mTUpomrrZTXHwumZ4gzcgsxaYVVvLnzGtdu5j62tBAz+7Fg+rd2xd7SnMxiJVtPprH9rOmkBAOY0MWHCV18DNrSi6t4dksUAJ52Uqb39CfU0xZzsYhzaaV8fCyFkqqae4zWtLG2lLJk2kCG9mqDi4M10QlZzPlgHxfjbv3PF00dwMRhEdhbyzl9JZVZK3eTlGE6VdRMGcFwFTBpNBoNIpEIMzPDqZPq6mosLJpW1ZzPFo6mVaAHk5ZsI6dAwdjHOnDgkxdoP3ol2QVlWMosOBWdwq5fovhs4dPGltsgPP7eMcS3ebBaeNqy/eUe7L+oW2RyJb2U3ecyyCpWYm9lzuzBLfl2Vne6LDyE1oSi+V8bFsrkAS2Y+snvxGWU0j7Qic9n9ERRVc1nP8fp+0x/rCVT150gLb+cRWPas2/hADq8ugd1jcbI76B+sJVL+HZ6BGeTi5ny1SVKKqvxc7akTHnLGHtjcAhdAp14ffsVskqUdA9yZsnwluQr1PwaZ1oFClIKq5i9+9bK+D8yTcgkZqx6sjVJhZW8uku3//luPiwf2oIZ269iQl8NAD57cyStAt2ZtPRbcgoVjB3UngPrptJ+zGqyCxTMHt+bGaN7MOXtHaRmF7N42kB+XDuZ8DGrTWOBlomHCpj2uxOoV7RaLStXrqR58+ZIpVJ8fX1ZtmwZAPPmzSM4OBhLS0uaNWvGokWLqKm59eOxdOlS2rVrx9atW/H398fOzo4xY8ZQXm5Ydq+2tpaZM2diZ2eHs7MzixYt4vb1g2q1mjlz5uDl5YWVlRUREREcO3ZMv3/Tpk3Y29vzww8/0KpVK6RSKenp6fj7+/POO+/w7LPPYmtry9SpUx9Id2NBJjVneJ+2LPj4R05eTiY5s5Bl6w+RlFHIlKe6AfDtzxdZseEwv55LMLLahqO4opoChVq/9Q91JyW/gtM3dJ6Sb06kcjaxiMziKq5llLHyh1i8HC3v6aVtynQJceXAhXQOXcokvaCCvWfSiIzOomNzF32fF59oxcpdVzhwIZ1r6SVMWfcbHg5yhnTyNaLy+mVKrwByy1S8ufMaVzPLyCxRcvJGERnFtwoShPvZs/dSFueSS8gqUfHduUyu55TT1sfOiMobBk1dHcVVNfrtj3zGbTxtcLeV8t7hRFKKqkgpqmLFoURC3Kxpb2LXQSaVMLxPKAvWHeBkVArJmUUs23CEpMwipozoCsCLY3ry/sZI9v8Ww7XEHCYv3Y6Hsy1De7U2svp6QiSqv60RIhiuAg/M/Pnzee+991i0aBGxsbFs27YNNzc3AGxsbNi0aROxsbGsXbuW9evX8+GHHxocn5SUxN69e9m/fz/79+/n+PHjvPfeewZ9Nm/ejEQi4dy5c6xdu5YPPviADRs26PfPnDmT06dPs337dq5cucKoUaMYNGgQN27cqg5VVVXF+++/z4YNG4iJicHVVbe6efXq1YSFhXH58mUWLVr0wLobAxKxGRKJGNUd3gCVuoZu7QKMpMq4mItFjOjsw47TaffcL7cQ83RXP9IKK8kuMa1clWfi8+ndxoPmHrYAhPo50K2FG4cv66ZC/V2tcXew5OjVW6EiiqoazicWEhFiOqv9+7Zy5VpmGWvHhXFqUW/2zOrKqM7eBn0up5XSt6UrrrZSACKaORLgYsWJG6aTw/UPvOxlfD+5I9smtmfBoCBcbXSzSuZi3U99jeZW1axqjZa6Ogj1sjWK1oZCIhbr7pXqe9wrwwLw93TEw9mWX8/d+s1QVKo4H5NORKjfw5bbMIjM6m9rhAihAgIPRHl5OWvXrmXdunU899xzAAQGBtKjRw8AFi5cqO/r7+/PnDlz2L59O3PnztW3a7VaNm3ahI2NLj3M+PHjiYyM1HttAXx8fPjwww8RiUSEhIRw9epVPvzwQ6ZMmUJ6ejobN24kPT0dT09PAObMmcPBgwfZuHEjy5frUoDU1NTw6aefEhZmWAK1b9++zJ4926DtQXQ3Biqq1Jy5ksL85x8lPiWPvOJyRg9sT0SoP0mZ/864rEFhntjKzfnudLpB+3OPBLDgyTZYySQk5pYzdu1Jk6vVvmbvFWwtzbn80Qg02jrEZiLe+vYiO04kA+Bmr1sYlV9qWAo1v1SJq738oettKHwc5Yzt4sPG39P4/Ggyod52LBzagppaLXsv6Yz2d/bF8c5Trfl9QW9qbhprC3fFcCGlxMjq65fY3HLeO5xIRokSJysLnovw5uNRoUzcepnY3HKUNRqm9fBj/cl0RMDUHn6IzUQ4WpkbW3q9ortXpjJ/Un/iU/N198oB4US08SMpsxB3J93vT36x4WxffnEFbo5C6rKmgGC4CjwQcXFxqNVq+vXrd8/9O3bs4OOPPyYpKYmKigpqa2uxtTV8kvf399cbrQAeHh7k5+cb9OnSpQui26Ynunbtypo1a9BoNFy9ehWNRkNwcLDBMWq1GicnJ/1rCwsL2rZte5fGjh07/iPdd55LrVYbtNVpaxGZNfxXadLibXyxeAzJPy+ltlZDVHwW3x2+THgL7/sfbIKM6e7H0Zg88u7IH7v7XAa/xeXjaifjhUeD+HxKJ4av+g11rfZPRmp6PNU1gKd7BDJx7XHiMktp6+/I+xM6k1Oi5JvjicaW99AQiURcyyrjw0M671lcdjlB7taM6eKjN1zHd/ejna89L2y6RHaJko4BjjdjXFWcTjSdUsDnUkv1fycXVhGXW872SR3oE+zMTzH5LD0Qz6t9AxnRzoO6OoiMLyA+rwJTzOQ+ael2vlg4iuQDi267V0YR3sLL2NIeDo10ir++EAxXgQdCLv9zL83p06cZN24cb731FgMHDsTOzo7t27ezZs0ag37m5oZP9iKRCK32wY2JiooKxGIxFy9eRCwWG+yztrY20Cq6xxfXysowzvFBdd/OihUreOuttwzaxB5dMPfq+sDv45+SklXEgGmfYCmzwNZKSm5ROVuXjycly/SmPO+Hl6Ocni1cmfzF2bv2latqKVfVklJQyaWUYmLXDGZQO0/2XTCdVeTLxndizd4rfH8qBYCY9BJ8nK2Z/WQo3xxPJK9UFxrhai8n9zavq6u9nKuppmOsFZSrScqrNGhLzq9kYBtdCJNUYsarA4OYufUyx6/rZibicyto6WnD848EmJTheicVag2ZJSq87GUAXEgvY9ymS9jJJGjq6qhQa9g9pSO/Jphe4ZCUrCIGTP8cS5k5tlYy3b3y3XGkZBeTW6TztLo62uj/1r225soNE8nC0kin+OsL0353AvVGUFAQcrmcyMjIu/adOnUKPz8/FixYQMeOHQkKCiIt7d5xh/fj7FlDQ+TMmTMEBQUhFosJDw9Ho9GQn59P8+bNDTZ3d/e/fa5/onv+/PmUlZUZbBKPTn/73P8LVapqcovKsbeR079LC/b/du2hnr8x8HRXPwrL1URey/3LfiKRCJFIZ8CYEnKpGO0drjKtVovZzQe21PwKckuq6N3GQ7/fRm5Op+bOnI03nOVoylxKLSXAxfCB1N/ZkqybxrpELMJCYnaXV1FTV2fqTink5mZ42kspqjQs8VumqqVCrSHc2xZ7S3NOJZuu8V6lqrntXhnC/t9iSM0uJqdQQZ9OzfX9bKykdGrty9mr/+x3S+DhInhcBR4ImUzGvHnzmDt3LhYWFnTv3p2CggJiYmIICgoiPT2d7du306lTJw4cOMCePXv+0XnS09N57bXXmDZtGpcuXeI///mP3gMaHBzMuHHjePbZZ1mzZg3h4eEUFBQQGRlJ27ZteeKJJ/7Wuf6JbqlUilQqNWh7GGECAP27hCASiUhIyyfQ25nlLw8hITWfLT+cA8DB1hIfd3s8nHWrhIP9dItw8orKySsq/9Nxmxoikc5w3XkmXZ/uB8DX2ZKhHbw5HpdPUbkaTwc5Lw4MRlWtJTLmrw3cpsbPFzOYOyKMjMJK4jJKCQtwZOaQNmz99daCk08OxDL3qTAScxWk5Vew6OlwckqU/Hg+/S9GblpsPpHKtzMimNYngJ+v5NHWx47REd4s3hULQKVaw9mkYl5/PBhVjYbsEhWdmjkwvL0n7+2PN7L6+mV6Tz9OJZeQV67GycqCiV180GohMl7naR7UypX04ipKlTW09rBhZq8Adl7KIaPE9Dyu/SOCb90rfZxZ/tJgEtLy2fLjeQA+2f478yb2IzGjkNTsYpZMG0hOoYIfjsfcZ+Qmgok/lQmGq8ADs2jRIiQSCYsXLyY7OxsPDw9eeOEFnn/+eV599VVmzpyJWq3miSeeYNGiRSxduvRvn+PZZ59FqVTSuXNnxGIxL7/8sj51FcDGjRt59913mT17NllZWTg7O9OlSxcGDx78t881dOjQetP9MLCzlvH2i0/g5WpPsaKKfb9eYcmnP1F7c6XwE4+0Zv2Ssfr+W5c/C8C7Xx5i2fpDRtHcEPRs4Yq3kyU7Thl6R9Q1Wjo3d2Jy30DsLC0oVKg4k1jEsNXHKSqv/pPRmiaz/3uGxWPa89HkrrjYycgpruKrI/Gs+D5K3+eDfVexlElYN60bdpYWnL6ez/Blh00mhyvA1UwFM7dE8dqgIF7sF0hmiZLlP8bzY1SOvs9r26J57bFgVo9pi52lOdklSj48dINvz2QYUXn942ItZdFjwdjKJJQpa7iaXc6MHVcoU+pW1/s6yJja3RcbmYRchZqvz2Wy83LOfUZtmthZy3h7xuN4udrp7pVHr7Lks4P6e+WarcewlFuwbv5I7K1lnIpOZejLG0wjhyuYfKiAqK7OFEOzBQQeHvJOrxlbQqNAKPmqQyj5qsO7maexJTQKPDyElep/cPbbfzYTZ2ooz65q0PHlg9fV21jK/TPrbaz6QvC4CggICAgICAiYCibucRUMVwEBAQEBAQEBU0GIcRUQEPgr2gwfamwJjQIbG+n9O/0LkEv/Jbki74PYxH88H5QwX3tjS2g03J28TkDg7yMYrgICTQQXGwte6hNI10BHZOZmZJYoeXt/PHE5uowBU3r6M6CVK262Umo0Wq7nVvDpsWRisk0no8BzEd48F+Fj0JZerGTC11EAOFia80IPPzr42CG3EJNZouTr81n8nmRaKX+e6eDFuI6GBnJGiZIXvruqf93CzZpnO3kT4mqFtg6SiypZdCCeahOrIja2gydjOxhei8xSJTO+06WJWzY4hFBPw6IiP8fm89kJ0019FHdkJ1f3byao11DCR+gWt17YsY68+ChUimIkFjKcAlrSdugEbN187jNa08PaUsqSaQMZ2qsNLg7WRCdkMeeDfVyMu5XLedHUAUwcFoG9tZzTV1KZtXI3SRkmUoVQCBUQEBAwNjYyCRuebc/FtBJe3nGF0soafBzlKJQ1+j7pxVWsOnSDrFIlUokZYyN8WDc2jCc/O0tpVc1fjN60SCmqYs6eWP3r21NizR/QHGsLCQv3x1OmrKFfiDOLHwtm+o4rJBZUGUNug5FaXMXC21I6aW5bZ9vCzZq3HwtmZ1QOn59MQ6OtI8DJEq1p2ax60oqrWHTgtmtxR12TQ3H5fHMhS//alKqo3UlxWgLJpw5i5+lv0O7g0xy/Dr2xdHChuqqcmIPb+O3TxTy+ZANmZuJ7D9ZE+ezNkbQKdGfS0m/JKVQwdlB7DqybSvsxq8kuUDB7fG9mjO7BlLd3kJpdzOJpA/lx7WTCx6w2jcwCJj7bYdpmuYCAifBcV1/yFCre3h9PbHY52WUqzqaUkFV6KwfjoZh8zqXq2pILq/joSCLWMglBrlZ/MXLTQ6Oto6SqRr8pVLd+aFq727DnSg7X8yrIUaj5+nwWFepagl2t/2LEpolWW0eJska/3X4dpnT15YdreeyMyiG9RElWmYoTycXUmqjlqtFCqbJWv5WrDY0Pda3WYL+yxjQN1xq1kjNbV9NxzEtYWBp+5gO7DcKleRusnNxw8GlOm8fHU1VaQFWx6RSkAJBJJQzvE8qCdQc4GZVCcmYRyzYcISmziCkjdBUOXxzTk/c3RrL/txiuJeYweel2PJxtGdqrtZHV1xMis/rbGiGCx1VAoAnQM8iJM8nFrBjRiva+9hSUq/n+YjZ7o+6dh1FiJuLJcE/KVbUk3FESs6njZS/ju0kdqNZoic0pZ8OpdPIrdHlaY3LL6R3kzJmUUirUtfQOcsJCYkZUpsLIqusfTzsZW/6vHTUaLXF5FWw+l0lBRTV2Mgkt3Kw5dqOI1cNa4m4rI7NUyZbzmcTmVhhbdoPgaSdl47gwXYhMXiVbzmVSeFvFqF7Nnegd5ERJVQ3n08rYfimb6jvdsibApZ2f4dGqE24h7Yg9vP1P+9WqVaSc/QUrJzfk9s4PUWHDIxGLkUjEqO54eFGpa+gWFoC/pyMezrb8eu5WsQ5FpYrzMelEhPqx80j0w5Ys8DcRDFcBgSaAl4Ocpzp4se1sBhtPptPa04bZA5pTo9Fy4Gqevl+P5k4se7IVMnMzCiuqmbktmjKl6YQJxOVWsPJIIhklKhytzHkuwoe1I9sw6ZsolDVa3vopgcWPBbNvWidqNVpUtVqWHIgnu8y0qgPF51fw4bFkMktVOFpa8EwHT1YObcmMnVdxt9Utknumoxf/PZNOcmEV/YKdWT64BTO+u0q2Qm1k9fVLfH4la4+lkFWmwsHSnDHtvXhvaAte+v4ayhotvyUWk1+hpriyBn8nOc919sHLXsaKI4nGll6vpF86TmlmEv1nf/infRJ/P8CVHzZSW63CxtWbXjPeRSwxf4gqG56KKjVnrqQyf1J/4lPzySsuZ/SAcCLa+JGUWYi7ky6vbn6xYex/fnEFbo4mknNXCBUQEBAwNmYiiM8t59NjKSTkVbDncg57o3IY0d4wyfuFtBLGbbjA85suczqpmOUjWuFgaTo/TOfSSjmeWExyURUX0st4Y18cVlIxvYN0XqNJXX2wloqZvTuGF3Zc5fvLOSx+LJgAJ0sjK69fLmaUcSK5hNRiJZcyy1jycwJWFmJ6NnPE7OaP1s9x+fwSX0hyURXrT6eTWari0RYuRlZe/1zKKONkiu5aXM5U8PbBBKykYno0cwTg0PUCLmcqSCtRcjyxmI+OJdM1wAF3E8qCUVVSwOVd64kYPwexucWf9vPt2JtHX19Ln5few8bVk9Mb30NTY1pV5QAmLd2OSATJBxZR9vsKXhzdne8OR6E10VCZOxGJRPW2/R00Gg2LFi0iICAAuVxOYGAg77zzDrfXuaqrq2Px4sV4eHggl8vp378/N27c+ItR70bwuAoINAEKK6pJLjRcXJRaWEXfOwwRVY2WzBIlmSVKrmUr2DW9M8PaebDplOnUp7+dymoNmaUqvOxleNpJeTLMg0lfR5FarAQgubCKUE8bhrV146OjKUZW23BUVmvIKlPhYScjOlsXFpFRojTok1GqxMX6z40aU6GyWkN2qRoPW9k998fn60JnPOyk5Jabhve5JCMRdUUpR1a/rG+r02opSIoh8ff9PLVmD2ZmYizkVljIrbBx9cLRP4S988eQdeU0vh16GVF9/ZOSVcSA6Z9jKTPH1kpGblE5W98dR0p2MblFOk+rq6ON/m/da2uu3Mg2lmST4P333+ezzz5j8+bNtG7dmgsXLjBx4kTs7OyYNWsWACtXruTjjz9m8+bNBAQEsGjRIgYOHEhsbCwy2b2/s3ciGK4CAk2A6Iwy/BzlBm2+jnJy7zMFbiYSYS423YkVmbkZnnYyjlwvQCrRrYy+06mirUPvhTRVZBIzPGxl/HqjiLzyagorq/GyM/wR8LKTcSGjzEgKHx4yiRnutlKO3ri3J7HZTe97iQll2nANDmPgPMMyn+e2rcXWzZsW/Z7686wBdaCpNZ3rcCdVqhqqVDXY28jp3yWEBesOkJpdTE6hgj6dmusNVRsrKZ1a+7J+92kjK64f/q6ntL44deoUw4YN44knngDA39+fb7/9lnPnzgE6b+tHH33EwoULGTZsGABbtmzBzc2NvXv3MmbMmAc6j2C4Cgg0Ab49l8l/nwtnQjdffokroLWnDU+Ge7L8J10KIJm5GZO6+/FbQhGFFWrsLc0Z1dELFxspkXGms2r4hR5+nEopIU+hxtnKnOe6+KCtq+PXhEIq1BoyS5W81rcZn59IQ6GqoXszRzr42rHgh+vGll6vPN/Fh7NppeSXq3GysmBcRy+0dXUcTywCYHd0DuM6eJFSVEVykS7G1dteznITi+sEmBjhw7n0UgrK1Tha6eJ9tXV1/JZUjLuNlF7NHbmQUUa5qhZ/J0ue7+rDtWyF3itvCpjLLO9KfyWRSrGwssHO05+KwlwyLv+GW4v2SK1sUZYVcf2XnYjNLfBo1dE4ohuQ/hHBiEQiEtLyCfRxZvlLg0lIy2fLj+cB+GT778yb2I/EjEJSs4tZMm0gOYUKfjgeY2Tl9UQ92q1qtRq12nBmQiqVIpXeHWrTrVs3vvzySxISEggODiY6OpoTJ07wwQcfAJCSkkJubi79+/fXH2NnZ0dERASnT58WDFcBAVMiNqec17+P4cU+AUzu6U92qZIPjiRyMEZnlGq14O9kyRMj3bGXm1OmrCE2p5ypWy7fFWLQlHG2tmDhwCBs5RLKlDVczS5n5ndXKVPqVhDP33edKd19eXdICHJzMdmlKt4/ksjZtFLjCq9nnKwsmNsvEFuZhDJlLTG55by2N1afEmvf1TwsxGZM6eaLjVRCSlEVCw9cJ9fEFmYBOFmbM6dvM/21iM0r5/W9cShUtViIzQjzsmVIqDsyiRmFldWcTilhx6V/15Sw2NycgqQYEo79QI2yAqmNPS6Bren7yipkNvbGllfv2FnLeHvG43i52lGsqGLf0ass+ewgtTczSazZegxLuQXr5o/E3lrGqehUhr68wTRyuNYzK1as4K233jJoW7JkCUuXLr2r7xtvvIFCoaBFixaIxWI0Gg3Lli1j3LhxAOTm5gLg5uZmcJybm5t+34Mgqrs9alZAQOBv02nZMWNLaBQIJV91yKWmlcz9nyKUfNUhlHy9xeolXxpbQqNAeXZVg45vPXpTvY1VtHXsA3tct2/fzuuvv86qVato3bo1UVFRvPLKK3zwwQc899xznDp1iu7du5OdnY2Hh4f+uNGjRyMSidixY8cDaRI8rgICAgICAgICJkJ9xrj+mZF6L15//XXeeOMN/ZR/aGgoaWlprFixgueeew53d3cA8vLyDAzXvLw82rVr98CaBMNVQOB/xMxM8CwBVAvTbACIhc8DAHZWpp/B4EGo+ZekYBIQqKqqwszMcDGwWCxGq9WFaAQEBODu7k5kZKTeUFUoFJw9e5bp06c/8HlMd7mxwD8iNTUVkUhEVFTU/zSOv78/H330Ub1ouhcTJkxg+PDhDTa+gICAgIBAU8RYeVyHDBnCsmXLOHDgAKmpqezZs4cPPviAJ598Uq/rlVde4d133+WHH37g6tWrPPvss3h6ev6t33PB4yog0ERwsbbgxT7N6BboiFRiRmaJkncOxHM9twKxmYgXHvGnW6AjXvZyKtS1nE8t4ZNjKRRWmFaCcWdrC6Y/EkCXAAdkEjMyS1UsP5hAfJ6unOkjQU4MD/MgxM0aO7k5EzZfIrHAtMreju/szbOdvQ3a0kuUPP+Nrlylg6U5U7v50t7HDrmFmMwSFdsuZnEiqdgYchuU0e08GB3uYdCWVari5T2xd/Vd8Ggg4d52vB+ZxPl0000NFv/LTmIPbCHwkaG0fXKKwb66ujpOf7mUvOuXiJj0Jp6hXY2ksuGwtpSyZNpAhvZqg4uDNdEJWcz5YB8X4zL1fRZNHcDEYRHYW8s5fSWVWSt3k5RRaETV9Yex0mH95z//YdGiRcyYMYP8/Hw8PT2ZNm0aixcv1veZO3culZWVTJ06ldLSUnr06MHBgwcfOIcrCIargECTwEYm4cvx4VxKL+WVHVcpqarB11FO+c1V5DJzM0LcbfjqZDo38iuwlUl49dHmrB7ZhgmbLhlZff1hI5Xw2dgwLmWUMmfXNUqVNXjb37oOAHJzMVeyFPwaX8AbA4ONqLZhSSmqYt6+OP1rzW1T0vP6B2IllbD4QDxlqlr6BjuzcGAQL353lSQTyjLxB+klSt4+dKv6juYe0/ODW7nyb5i0L0lPIPX0QWzvSI/1B0nH95l8SdDP3hxJq0B3Ji39lpxCBWMHtefAuqm0H7Oa7AIFs8f3ZsboHkx5ewep2cUsnjaQH9dOJnzMatPILGCkf6+NjQ0fffTRX862ikQi3n77bd5+++1/fB4hVOBfilarZeXKlTRv3hypVIqvry/Lli3T709OTqZPnz5YWloSFhbG6dOGiZlPnDhBz549kcvl+Pj4MGvWLCorDb1a5eXljB07FisrK7y8vPjkk0/0+yZNmsTgwYMN+tfU1ODq6sp///tfAL7//ntCQ0ORy+U4OTnRv3//u86xevVqPDw8cHJy4sUXX6Sm5lYybbVazZw5c/Dy8sLKyoqIiAiOHTsG6OJq5HI5P//8s8F4e/bswcbGhqqqxvXjPr6LD/nlat45EE9sTjk5ZSrOppSQVaorQFCp1jBr+xUirxeQXqzkWnY5qw8n0tLDBjdb01ntP66zN/nlalYcvEFcbgU5ZWrOp5WSfVshhkOx+Ww6nc4FE0uBdSdabR0lVTX6TXGb8d7K3YZ9V3KJz68kV6Fm24UsKqtrCXa1MqLihkOjraNUWavfytUag/3+jnKGtHHl0xNpRlL4cKhVKzn/9RrCR7+Ehdz6rv2lWcncOLaX9mNevsfRpoFMKmF4n1AWrDvAyagUkjOLWLbhCEmZRUwZofMuvzimJ+9vjGT/bzFcS8xh8tLteDjbMrRXayOrF3gQBMP1X8r8+fN57733WLRoEbGxsWzbts0gt9qCBQuYM2cOUVFRBAcHM3bsWGprdT+MSUlJDBo0iKeeeoorV66wY8cOTpw4wcyZMw3OsWrVKsLCwrh8+TJvvPEGL7/8MkeOHAFg8uTJHDx4kJycHH3//fv3U1VVxdNPP01OTg5jx45l0qRJxMXFcezYMUaMGGFQ8/jo0aMkJSVx9OhRNm/ezKZNm9i0aZN+/8yZMzl9+jTbt2/nypUrjBo1ikGDBnHjxg1sbW0ZPHgw27ZtM9D8zTffMHz4cCwtG1dt+0eCnIjLKWf58Fb8PKsrWya2Z1iY+18eYy0Vo62ro0JlAh6Em3Rv7sT13AreGdKCH2dE8NX4cIaE/vV1MFU87WVsn9ieLePb8cajzQ3KucbmltMryAkbqRgR0DvICXOxGdFZCuMJbkA8bKV8+XQbPhnZmpcf8cfZyly/z0Is4uVe/mw4k0Gp0nS+C/ci6vvPcW/ZEdeQdnftq61WcWHrasKeegGZrcPDF/eQkIjFSCRiVGrD/7VKXUO3sAD8PR3xcLbl13O3PPSKShXnY9KJCPV72HIbBGPFuD4shFCBfyHl5eWsXbuWdevW8dxzzwEQGBhIjx49SE1NBWDOnDn6sm1vvfUWrVu3JjExkRYtWrBixQrGjRvHK6+8AkBQUBAff/wxvXr14rPPPtPHqnTv3p033ngDgODgYE6ePMmHH37Io48+Srdu3QgJCWHr1q3MnTsXgI0bNzJq1Cisra1JSEigtraWESNG4Oenu5mEhoYavA8HBwfWrVuHWCymRYsWPPHEE0RGRjJlyhTS09PZuHEj6enpeHp66t/TwYMH2bhxI8uXL2fcuHGMHz+eqqoqLC0tUSgUHDhwgD179vzptbtXFRFtbTVmkoZdQe1pL2dEeznfnstk0+l0WnnY8NqjzanR1vHT1by7+luIRczs3YzDsflUVmvuMWLTxNNOxvB2Huy4kMmWsxm0dLfhlb7NqNFq9cUY/g1cz61g9S9JZJSqcLIy5/86efPhiNZM+TYaZY2Wdw7eYOGgIHZP6UStRou6VstbPyWQXWZ6BQhuFFTyyYk0ssvU2MsljA734J3Hg3l1TxyqWi0TIryJz6806ZhWgMxLv1GWlUTvVz+45/6rezfg6N8Cz9AuD1nZw6WiSs2ZK6nMn9Sf+NR88orLGT0gnIg2fiRlFuLuZANAfnG5wXH5xRW4OdoYQ3K901gNzvpC8Lj+C4mLi0OtVtOvX78/7dO2bVv933/kW8vP1xkG0dHRbNq0CWtra/02cOBAtFotKSkp+uO6djUM+u/atStxcbdi8iZPnszGjRsBXR63n3/+mUmTJgEQFhZGv379CA0NZdSoUaxfv56SkhKD8Vq3bo1YfCvZu4eHh17j1atX0Wg0BAcHG+g8fvw4SUlJADz++OOYm5vzww8/ALBr1y5sbW0NytHdyYoVK7CzszPYso9986f96wszEcTnlvPZ8RQS8irYG5XDvugcRoR73tVXbCZi2ZOtQAQrD964x2hNFzMRJORV8OWJNG7kV/LDlVx+uJrL8DCP+x9sQpxPL+W3pGJSiqq4kF7Ggh+vYy0V06u5EwATuvhgZSFh7t5YXvzuGt9H5bBwUBD+TnIjK69/LmcpOJ1aSlqJkujscpYdScLSQkK3AAc6+tgR6mHDprOZ9x+oCVNVUsCVPevp+H+zEZvf/RCdc+0sBTeu3LVQy1SZtHQ7IhEkH1hE2e8reHF0d747HIVWSE1mEgge138hcvn9f7zMzW9Ntf3x9PZHLraKigqmTZvGrFmz7jrO19f3gXU8++yzvPHGG5w+fZpTp04REBBAz549AV3utyNHjnDq1CkOHz7Mf/7zHxYsWMDZs2cJCAi4S+MfOm/XKBaLuXjxooFxC2BtrYv9srCwYOTIkWzbto0xY8awbds2nn76aSSSP/9azJ8/n9dee82grd/asw/8nv8phRXVpNyxqCa1sIo+IS4GbWIzEcuHt8LDVsaMb6NNytsKUFRZTWqR4XVIK1LSO8jZSIoaB5XVGjJLVXjay/CwlTK8rTuTt0WTVqwEILmoilBPW4aFurP2WMp9RmvaVFVryClT4W4rxddBjpuNlM3jwgz6zOnTjOt5FSwxkQe70sxE1BWlHF3zir6tTqulMDmG5BP7Cej2OJVFuex/07AW/NmN7+HcrBU9Z654yIoblpSsIgZM/xxLmTm2VjJyi8rZ+u44UrKLyS3SeVpdHW30f+teW3PlhmmUAjZ1j6tguP4LCQoKQi6XExkZyeTJk//28e3btyc2NpbmzZv/Zb8zZ87c9bply5b6105OTgwfPpyNGzdy+vRpJk6caNBfJBLRvXt3unfvzuLFi/Hz82PPnj13GY73Ijw8HI1GQ35+vt4Yvhfjxo3j0UcfJSYmhl9//ZV33333L8e9VxWRhg4TALiSWYafk2Hcra+jJbm3LUr6w2j1cZQz45toFCYYz3c1S4Gvo+GDl4+DnFyF6U2B/x1k5mZ42Mkoji9Eaq6bSLuzmre2rs7UF5MDIJOY4WYrpTSpmFOpJUQmGKY4+vDJVmw+l8mFDNMJHXAJCqPf3HUGbRe//QgbV2+C+43EwsqWgG6DDPZHrpxJ2+HP496688OU+lCpUtVQparB3kZO/y4hLFh3gNTsYnIKFfTp1FxvqNpYSenU2pf1u0/fZ8SmgWC4CpgcMpmMefPmMXfuXCwsLOjevTsFBQXExMT8ZfjAH8ybN48uXbowc+ZMJk+ejJWVFbGxsRw5coR1627dPE+ePMnKlSsZPnw4R44cYefOnRw4cMBgrMmTJzN48GA0Go0+3hbg7NmzREZGMmDAAFxdXTl79iwFBQUGhu9fERwczLhx43j22WdZs2YN4eHhFBQUEBkZSdu2bfXxu4888gju7u6MGzeOgIAAIiIiHmj8h82357PYML4dz3X1JfJ6Pq08bBnezoMVBxMAndH63pOtCHG3ZvbOa5iZgePNBSoKZS21JjJFtuNiFp+PDWN8hA+/xhfQyt2GoWHurDx8y3NmI5PgZiPF+eZipT8M3eLKaoqrau45blNjandfzqSUkFdejZOVOc929kZbV8fRhEIqqjVklSp5uXczvjyZhkJVS/dmjrT3sWPR/nhjS693nu3kxYX0Mgoqq3G0NGd0Ow+0dXWcSC5Boa6954Ksgspq8k0ov7G5zBJzD8OFRRILGRZWttjebL/Xgiy5gwtWTqa3uLF/RDAikYiEtHwCfZxZ/tJgEtLy2fLjeQA+2f478yb2IzGjkNTsYpZMG0hOoYIfjscYWbnAgyAYrv9SFi1ahEQiYfHixWRnZ+Ph4cELL7zwQMe2bduW48ePs2DBAnr27EldXR2BgYE8/fTTBv1mz57NhQsXeOutt7C1teWDDz5g4MCBBn369++Ph4cHrVu31i+iArC1teW3337jo48+QqFQ4Ofnx5o1a3jsscce+D1u3LiRd999l9mzZ5OVlYWzszNdunQxSMMlEokYO3YsK1euNEiS3NiIyyln7u4YZvQK4PkefmSXKvnwl0QO3VyQ5GpjwSPBuunyr5/vaHDs9G+iuGQiC1Ou51bw5r44pvX0Z0JXX3LKVHz8azJH4gr0fXoEOrLgsRD967eH6B52vjqVxlen0h+65obA2cqCNwcGYSOTUKas4Vp2ObN2XqPsZgaJBT/G83w3H94ZHILMXEx2mYpVvyRxzgRThDlZmvNKb39spBIUqlqu51Xw5v54FGrTm3EQeDDsrGW8PeNxvFztKFZUse/oVZZ8dpBajS6UbM3WY1jKLVg3fyT21jJORacy9OUNppHDFYyWx/VhIaq7cz5JQOAhUlFRgZeXFxs3bmTEiBHGlvOPiFhx3NgSGgXm5sJaTwC5zPz+nf4F2Fk1fAhNU6C52935VP+trH1rvbElNAqUZ1c16PjOE7bX21iFm8bcv9NDRvC4ChgFrVZLYWEha9aswd7enqFDhxpbkoCAgICAgEAjRzBcBYxCeno6AQEBeHt7s2nTpr9cyd/YubJ7n7ElNAp8+w68f6d/AflZplHv/H/Fw9fl/p3+BZRVmk4srUDTQFicJSDQAPj7+9+16lngr7G2lLLkhccY2rsNLg42RCdkMmfNXi7GZgAwrE8ok0d0I7yFN072VkSMW82VBNNI73I7rrZSXn8smJ4hzsgtxKQVVvHmzmtcu1kVytJCzOzHgunf2hV7S3Myi5VsPZnGdhPK5Rn94TB8Xe6egt5wJIHXN5/H1U7G22Pb07uNO9YycxJzFazZd40fz2cYQW3D42orZfbAIHqGOCMzF5NeVMWCXTHE3PxMxC4fcM/jVv+cwFe/pz5EpQ3H+M7ePNvZ26AtvUTJ899EA+Bgac7Ubr6097FDbiEms0TFtotZnEgqNobcBsXaUsqSaQMZ2qsNLg7WRCdkMeeDfVyMu3UPWDR1ABOHRWBvLef0lVRmrdxNUoZpPHQKhquAgECj4LOFo2kV6MGkJdvIKVAw9rEOHPjkBdqPXkl2QRmWMgtORaew65coPlv49P0HbILYyiV8Oz2Cs8nFTPnqEiWV1fg5W1KmvJUt4I3BIXQJdOL17VfIKlHSPciZJcNbkq9Q8+tti7iaMn0XH0RsduvHqaW3PXvn92PvuTQAPnuhG3aW5jzzwXGKytWM7ObPxpd60GfRQa6mlfzZsE0SW5mEb6Z15lxyMdM2XaK4sgY/J0sUt30mHll+zOCYnsHOvDOiNYev3V11rimTUlTFvH23irxobssmMq9/IFZSCYsPxFOmqqVvsDMLBwbx4ndXSbojR3RT57M3R9Iq0J1JS78lp1DB2EHtObBuKu3HrCa7QMHs8b2ZMboHU97eQWp2MYunDeTHtZMJH7PaNBZombbdKlTOEhBoCsik5gzv05YFH//IycvJJGcWsmz9IZIyCpnyVDcAvv35Iis2HObXcwlGVttwTOkVQG6Zijd3XuNqZhmZJUpO3igi42aifYBwP3v2XsriXHIJWSUqvjuXyfWcctr62BlRef1SVK4mv0yl3waGe5GcV87JOF2Wic5Bzqw/nMCl5CLSCipYs+8aZZU1tAtwNLLy+uf5m5+JBbtiuJqpIKtEyalEw89EYUW1wda3lSvnUorJLFH+xchND622jpKqGv2mUN0ywlq527DvSi7x+ZXkKtRsu5BFZXUtwa5WRlRc/8ikEob3CWXBugOcjEohObOIZRuOkJRZxJQRumqOL47pyfsbI9n/WwzXEnOYvHQ7Hs62DO3V2sjqBR4EwXAVEGgCSMRmSCRiVHd4A1TqGrq1CzCSqodP31auXMssY+24ME4t6s2eWV0Zdcf06OW0Uvq2dMXVVlcoIqKZIwEuVpy4UWQMyQ2OudiM0d39+eZ4kr7t3I1Cnuzih72VBSIRjOjih9RczIk40/IwAvRt6cK1TAUfjm3L72/2ZtfMLozs6PWn/Z2sLXgkxJldF7IeosqHg6e9jO0T27NlfDveeLQ5Lta3MjvE5pbTK8gJG6kYEdA7yAlzsRnRN8MpTAWJWKy7V6rvca8MC8Df0xEPZ1t+PXcr97OiUsX5mHQiQv3uHK5JIhKJ6m1rjAihAgICTYCKKjVnrqQw//lHiU/JI6+4nNED2xMR6k9SpmnEZT0IPo5yxnbxYePvaXx+NJlQbzsWDm1BTa2WvZd08bzv7Ivjnada8/uC3tRotNTVwcJdMVxIMa0p8j94oqM3dpYWbPstWd828T+/89XMHqR8MYqaWi3K6lrGf3SclLwKIyptGLwd5IyJ8GbzyTS+PJZCG29b3hzSghpNHfsu3x3jPSzckyq1hiM3cyCbCtdzK1j9SxIZpSqcrMz5v07efDiiNVO+jUZZo+WdgzdYOCiI3VM6UavRoq7V8tZPCWSXmVbVOd29MpX5k/oTn5qvu1cOCCeijR9JmYW4O9kAkF9cbnBcfnEFbo42xpBc7zRWg7O+EAxXAYEmwqTF2/hi8RiSf15Kba2GqPgsvjt8mfAW3vc/2EQQiURcyyrjw0M6b0lcdjlB7taM6eKjN1zHd/ejna89L2y6RHaJko4BjjdjXFWcTjS9hSj/1yuQX6KzyS29Ne29YGQYdpYWDFvxC8Xlah7v4MPGl3ry+DtHiM0sNZ7YBsBMJOJaloKPDicCumIdQW7WPB3hfU/DdURHL/ZH51Bdq33YUhuU8+ml+r9TiiAut4JvngunV3MnDsYVMKGLD1YWEubujaVMWUu3Zg4sHBTEq7tjSC0yrZCJSUu388XCUSQfWHTbvTKK8BZ/7okXaDoIhquAQBMhJauIAdM+wVJmga2VlNyicrYuH09KlmlOgd+LgnI1SXmVBm3J+ZUMbOMGgFRixqsDg5i59TLHr+s80fG5FbT0tOH5RwJMznD1cbKidxt3xn/0u77N39WaqQNC6DpvP9ezdBXTrqWX0jXEhcmPBvPaxnPGktsgFJSrSco39CQnFVTyaGu3u/p28LenmYsVs7+NfljyjEZltYbMUhWe9jI8bKUMb+vO5G3RpN2M/U0uqiLU05Zhoe6sPZZiZLX1S0pWEQOmf46lzBxbK5nuXvnuOFKyi8kt0nlaXR1t9H/rXltz5YZpZGExdY+rEOMqINDEqFJVk1tUjr2NnP5dWrD/t2vGlvTQuJRaSoCL4WISf2dLsm56GyViERYSM+7MtKapq8MU7+XP9GpGgULN4ahb8ZqWFjp/hPaOi6DRmuY1uJR+j8+EkxXZpaq7+o7o4MW1zDLic00vZOJOZOZmeNjJKK6sQXqzqt2dKQi1Jvq9+IMqVc1t98oQ9v8WQ2p2MTmFCvp0aq7vZ2MlpVNrX85eTTOi2vrD1GNcBcNVQKCJ0L9LCI92bYGfpyN9Owdz8PMZJKTms+UHnQfNwdaStsGetAxwByDYz5W2wZ64OZlG3BbA5hOphPnaMa1PAL5Olgxu58HoCG+2ndLlJ61UazibVMzrjwfTuZkD3g5ynuzgyfD2nvxiYjGNIhGMeySQ7b8nG6Q9SsgpIylXwYeTImjfzAl/V2tefKwFfdp48NNF08ll+wdbTqTR1seOqb0C8HWU80SYO6M6e/PtmXSDflZSMQND3U1yURbA1O6+tPW0wc1GSit3a5Y+Foy2ro6jCYVklKjIKlXycu9mhLha4WErZWQ7D9r72HEq2fRiv/tHBPNolxD8PBzo2zmIg5++QEJaPlt+PA/AJ9t/Z97EfjzRsxWtA93575Ix5BQq+OF4jJGVCzwIQqiAgEATwc5axtsvPoGXqz3Fiir2/XqFJZ/+RK1GF6v3xCOtWb9krL7/1uXPAvDul4dYtv6QUTTXN1czFczcEsVrg4J4sV8gmSVKlv8Yz49ROfo+r22L5rXHglk9pi12luZklyj58NANvj1jWsn3e7d2x8fZiq9vyyYAUKupY/SqYyx5uh3fzu6FldSclLxyZnxxmiPRpjEVejvXshTM+jqKVwcGMb1vMzJLlLy3/zr7o3MN+j3e1h0RcOCOdlPB2cqCNwcGYSOTUKas4Vp2ObN2XqPsZkqsBT/G83w3H94ZHILMXEx2mYpVvyRxLq3UuMIbADtrGW/PeBwvVzvdvfLoVZZ8dlB/r1yz9RiWcgvWzR+JvbWMU9GpDH15g2nkcAWTz+MqqhPKFwkI/E/IO71mbAmNAqHkqw6h5KsOoeSrDi9PW2NLaDSc2LrL2BIaBcqzqxp0fK/pe+ptrKzPnqy3seoLIVRAQEBAQEBAQECgSSCECggICAgICAgImAiNdVFVfSEYrgJGJTU1lYCAAC5fvky7du2MPs4/4dv/zn2o52us+NpaGltCo2D50URjS2gUOFhZ3L/TvwAna+E6/MEJF9OoTNXYEQxXAYFGxoQJEygtLWXv3r36Nh8fH3JycnB2djaesAbk9KG9nDm8j5IC3cISN29/+o16jhbhXQCoqVZzYMunRJ/8ldqaGoLbdWL45FexsTet2vR7t2/k/MmjZGekYWEhJbhVW8Y+PxNPH399n8ifdnPy6CFSE+NRVlWyYdevWFmbTmYFgNHtPBgd7mHQllWq4uU9sXf1XfBoIOHedrwfmcT59LKHJdEoDGrhzFNt3fkloZAdUbrviouVBaPC3GnubIlELCImt4Jtl7IpV2uMrLbhiP9lJ7EHthD4yFDaPjnFYF9dXR2nv1xK3vVLREx6E8/QrkZS2TCYmYlY+ExnxvYOwc3BkpziSrZGxvHe9gv6Pgue6cyonkF4u1hTXavhcmIBS7ec4XyCiZRENm27VTBcBf53qqursbC426tQU1ODubn5Q9EgFotxd3d/KOcyBnZOLjw2bhrOHt7U1dVx8dhBtry/gFmrNuDuE8D+TeuIu3SGca+9hczSin3//Yitqxcx491PjC29Xom7cokBQ0bRLLgVWo2G7Zs+ZcWbL7Fq/XfIZHIA1CoVYR27EtaxK9u/Mq33fzvpJUrePnSr3vrtKbH+YHArV/4tq2/9HeT0auZIxm0VxCzEIl7p5U9mqZI1x3VJ9oe1ceOlHn6siEw2yWtTkp5A6umD2Hr633N/0vF9mHLy1tlPtWfKY22Y8uEvxKYX0yHIlS9e7oeisppPf7wCQGJWKa9+fpyUXAVyqYSXhoXx4ztDaTNlK4WKu/P/CjQuhMVZ/1K0Wi0rV66kefPmSKVSfH19WbZsGQBXr16lb9++yOVynJycmDp1KhUVtxJ2T5gwgeHDh7Ns2TI8PT0JCQkhNTUVkUjEjh076NWrFzKZjG+++QaADRs20LJlS2QyGS1atODTTz/9U10ajYbnn3+egIAA5HI5ISEhrF27Vr9/6dKlbN68mX379ukTJB87dkx//qioKH3f48eP07lzZ6RSKR4eHrzxxhvU1t5Kd9K7d29mzZrF3LlzcXR0xN3dnaVLl9bTFa5fWnXsTov2XXD28MbF04dBz0zBQiYnPSEWZWUF53/9icHPvUjz0PZ4B4Yw6sU3SIu/RlqCaeUlnL/8P/QaMAQf/0D8AoOZPnsJhfm5pNyI0/d5fMQzDHt6AkEtQo2otOHRaOsoVdbqtzs9iP6Ocoa0ceXTE6aRVP2vkErMmNzFmy0XsqiqvlXKtbmzFc6W5mw8l0VWmZqsMjUbz2Xi5yinhavVX4zYNKlVKzn/9RrCR7+Ehdz6rv2lWcncOLaX9mNeNoK6h0OXlh7sP5vCwQtppOeXs+dkEpGXM+gYfKuS2o7jCRyNziQ1T0FcejHzNpzAzkpKmwDTmLEz9QIEgsf1X8r8+fNZv349H374IT169CAnJ4fr169TWVnJwIED6dq1K+fPnyc/P5/Jkyczc+ZMNm3apD8+MjISW1tbjhw5YjDuG2+8wZo1awgPD9cbr4sXL2bdunWEh4dz+fJlpkyZgpWVFc8999xdurRaLd7e3uzcuRMnJydOnTrF1KlT8fDwYPTo0cyZM4e4uDgUCgUbN24EwNHRkexsw/yUWVlZPP7440yYMIEtW7Zw/fp1pkyZgkwmMzBON2/ezGuvvcbZs2c5ffo0EyZMoHv37jz66KP1d7HrGa1Gw5Uzx6hWq/ALbk1WcgIaTS1BbTvo+7h6+WHv7EZ6Qgx+wa2NqLZhqarUPVBZ2/z7Ug552Er58uk21GjqSMiv5JuLWRRW1gA6T+PLvfzZcCaDUqWJ5Kb8C55p78GVnHLi8it5otWtdomZiDqg9jZvdI2mjro6aO5iRVx+5d2DNWGivv8c95YdcQ1pR/yRHQb7aqtVXNi6mrCnXkBm62AkhQ3Pmbgcnh/Umuae9iRmlxIa4ETXVh688d8T9+xvLjHj+UFtKK1QczXFNFLZNVaDs74QDNd/IeXl5axdu5Z169bpjcfAwEB69OjB+vXrUalUbNmyBSsrnUdi3bp1DBkyhPfffx83N91Tq5WVFRs2bNCHCKSmpgLwyiuvMGLECP25lixZwpo1a/RtAQEBxMbG8sUXX9zTcDU3N+ett97Svw4ICOD06dN89913jB49Gmtra+RyOWq1+i9DAz799FN8fHxYt24dIpGIFi1akJ2dzbx581i8eDFmZrrJhrZt27JkyRIAgoKCWLduHZGRkY3ScM1JS+LTBS9SW1ONhUzOs6+/i5uPP9mpNxBLzJFbGcZxWts5UF5abCS1DY9Wq2XL5x8Q0joMH//m9z/AhLhRUMknJ9LILlNjL5cwOtyDdx4P5tU9cahqtUyI8CY+v9LkY1oBOvnY4WsvZ9kvSXftSy6uQl2r5am2buy5qotffKqtO2IzEXYy0/r5y7z0G2VZSfR+9YN77r+6dwOO/i3wDO3ykJU9XFZ/fxFbSwuiPx+HRqtFbGbGkq1n2H4swaDfY5382TJ3AJZSc3JLKhm8aB9FQphAk8C0vrkCD0RcXBxqtZp+/frdc19YWJjeaAXo3r07Wq2W+Ph4veEaGhp6z7jWjh076v+urKwkKSmJ559/nilTbi0QqK2txc7O7k/1ffLJJ3z11Vekp6ejVCqprq7+25kC4uLi6Nq1q8GTZ/fu3amoqCAzMxNfX19AZ7jejoeHB/n5f14aVK1Wo1arDdpqqtWYW0j/lr5/gounLy+v2oCqqpKrZ47z3brlTHvr4wY/b2Nl47qVZKQlsXTNemNLeehczlLo/04rgRuFVXw2qg3dAhxQqGoJ9bDh9X3Xjajw4eAgN2dMuAcfHE8x8Kr+QYVawxenMxjXwZO+QU7U1cG59DLSipWYUu2dqpICruxZT/fpbyM2v/u+nHPtLAU3rtB3ztp7HG1ajOwZxJjewUxYfZjYtGLaNnNm1ZSe5BRV8s2vt74Tx69kEjFrB862MiYObM3X8wbxyOydFJQp/2L0poHgcRUwOeRy+f88xu2G7Z+1/xEXu379eiIiIgz6icXiex6/fft25syZw5o1a+jatSs2NjasWrWKs2fP/s+a78Wdi8dEIhFarfZPesOKFSsMPMIAT78wmzHT5zSIvtuRmJvj7OENgHdgCJlJ1znx0/eEdeuLprYGZWW5gde1oqzE5LIK/MHGdSu5dPZ3lqz5EicXt/sfYOJUVWvIKVPhbivF10GOm42UzePCDPrM6dOM63kVLDl4409GaXr4OciwlUlY9Ogtj7vYTESQiyV9mjsxfVcMsXkVLPgpAWsLMZq6OpQ1WlYPCaHgZliFKVCamYi6opSja17Rt9VptRQmx5B8Yj8B3R6nsiiX/W+OMTju7Mb3cG7Wip4zVzxkxQ3H8ondWP39JXb+pvucx6QV4etqw+ujOhgYrlXqWpJzykjOKeNcfB5Xv/w/nhvQitU7LxpLer0hGK4CJkdQUBByuZzIyEgmT55ssK9ly5Zs2rSJyspKvRF68uRJzMzMCAkJ+VvncXNzw9PTk+TkZMaNG/dAx5w8eZJu3boxY8YMfVtSkuEUoIWFBRrNX6eyadmyJbt27aKurk7/JT558iQ2NjZ4e3v/rfdxO/Pnz+e11wxLvB5KKPnH4/0v1Gm1aGpq8GoWjFgsIfHqJUK79AKgICud0sI8fE0svrWuro5Nn6zi/KljLFr1Oa7uXsaW1CiQScxws5VSmlTMqdQSIhMMY/U+fLIVm89lciHDtEIH4vIr7zLEJ3b2IkdRzcHrBdzuVK2o1t0zWrhaYSOTEJ2twFRwCQqj39x1Bm0Xv/0IG1dvgvuNxMLKloBugwz2R66cSdvhz+PeuvPDlNrgyKXmaO/wvmu0dZiZ/bUxZyYSITW/t0NFoHEhGK7/QmQyGfPmzWPu3LlYWFjQvXt3CgoKiImJYdy4cSxZsoTnnnuOpUuXUlBQwEsvvcT48eP1YQJ/h7feeotZs2ZhZ2fHoEGDUKvVXLhwgZKSkrsMQNAZ1Vu2bOHQoUMEBASwdetWzp8/T0BAgL6Pv78/hw4dIj4+Hicnp3uGHcyYMYOPPvqIl156iZkzZxIfH8+SJUt47bXX9PGt/wSpVIpUahgWYG5R9Y/He1B+/uZLQsIjsHd2Ra2sIupEJMmxUUxasAq5lTWd+j7O/s2fYGltg1Ruxb6v1uIb3NrkFmZ9te59Th09xOylq5HLLSkt1hlollbWWEhlAJQWF1JaUkRudgYAGSmJyCwtcXZxx9r2z0NUmhLPdvLiQnoZBZXVOFqaM7qdB9q6Ok4kl6BQ195zQVZBZTX5FdVGUNtwqGu1ZCvUd7TVUVldq2/v5m9PrkJNuVpDMyc5Y8I9+CWhiLxy07kW5jJLzD0Mk/tLLGRYWNlie7P9Xguy5A4uWDmZVhrBn86lMO/pjmQUlBObXky7QBdmDW/HliO6HMeWUgnznu7IgbMp5BZX4WQrY9rgUDydrNh9wkSKh5i2w1UwXP+tLFq0CIlEwuLFi8nOzsbDw4MXXngBS0tLDh06xMsvv0ynTp2wtLTkqaee4oMP7h3wfz8mT56MpaUlq1at4vXXX8fKyorQ0FBeeeWVe/afNm0aly9f5umnn0YkEjF27FhmzJjBzz//rO8zZcoUjh07RseOHamoqODo0aP4+/sbjOPl5cVPP/3E66+/TlhYGI6Ojjz//PMsXLjwH70PY1NRVsJ365ajKClCZmmFh18gkxasIjisEwCDJ8xEZGbG1tWLqa2tITisE09OftXIquufX/bvAuCd118waH9h9mJ6DRii63NgN7u+vhX3+tacqXf1aeo4WZrzSm9/bKQSFKparudV8Ob+eBRq088g8Hdxt5EyItQNKwsxRVU1/BRXwJGEImPLEmggXvviN5b8XwRrZ/TCxU5XgOC/P19j+fbzgM77GuLtwP/1a4GTrZxihYoLN/LoP283cemmsZjV1EMFRHWmFKEuIGAE9l7JNbaERoFQ8lWHUPJVh1DyVYdQ8vUWaz89bGwJjQLl/pkNOn6z136qt7GSP3i83saqLwSPq4CAgICAgICAiWDqHlfBcBUQEBAQEBAQMBFM3G4VDFcBgf+VA9dNo9rK/4q7bcPnsm0KXLoqhI4ARLTzNLaERoHwvbiNAtMvP9wYEDyuAgICjY5BLZx5qq07vyQUsiNKZyi5WFkwKsyd5s6WSMQiYnIr2HYp+64a9qZE3JGdXN2/maBeQwkfoVuEdWHHOvLio1ApipFYyHAKaEnboROwdfMxstr65beFvfF2vDuueOuJNJbsjsFCYsaCoS0ZHO6BhcSM3+MLWfz9NQpNLLPAU2HujAwzXBmfVaZizr7rWFmIGdXOnVAPG5ytLFCoa7mQXsZ3UTkoa/48X3NT59/8vQCwtpSyZNpAhvZqg4uDNdEJWcz5YB8X4zL1fRZNHcDEYRHYW8s5fSWVWSt3k5QhOCGaAoLhKiDQxPB3kNOrmSMZpbcqvFiIRbzSy5/MUiVrjqcAMKyNGy/18GNFZDKmuAKzOC2B5FMHsfP0N2h38GmOX4feWDq4UF1VTszBbfz26WIeX7IBMzPTydM4/MNT3J7ZLcTdhq3TI/gpOgeARcNa0qeVKzM3X6ZcVcPSEa35dGJ7Rv/njJEUNxwZJUqWHbmV71l7c82xg6U59nJzvrmYTWapChdrC57v4o2DpTkfHU81ktqG5d/+vQD47M2RtAp0Z9LSb8kpVDB2UHsOrJtK+zGryS5QMHt8b2aM7sGUt3eQml3M4mkD+XHtZMLHrEZd3fQzc5i4w5V/ntBSQEDgoSOVmDG5izdbLmRRVX3LY9Tc2QpnS3M2nssiq0xNVpmajecy8XOU08L13lXOmjI1aiVntq6m45iXsLC0NtgX2G0QLs3bYOXkhoNPc9o8Pp6q0gKqiv+8lG9TpLiymsLyW1vf1q6kFlZyNqkYG5mEURE+LNsXx+nEIq5lKpi7/QodAxxp52dvbOn1jqYOylS1+u2PWYbMUhUfHU/lUqaC/IpqYnIr2HE5h/bettwnH32TRPhegEwqYXifUBasO8DJqBSSM4tYtuEISZlFTBnRFYAXx/Tk/Y2R7P8thmuJOUxeuh0PZ1uG9jKNvNcikajetsaIYLgKCDQhnmnvwZWccuLyKw3aJWYi6sCgXnuNpo66OmjuYnqG66Wdn+HRqhNuIe3+sl+tWkXK2V+wcnJDbu/8cMQZAXOxiGHtvfj+rG4qtI23HRYSM07cVkErOb+SrGIl7U3QcHW3seDTka356MmWvNjDFycr8z/ta2kuRlmjRWuC0xDC9wIkYjESiRjVHTmNVeoauoUF4O/piIezLb+eu1VxTVGp4nxMOhGhfncOJ9AIEUIFBASaCJ187PC1l7Psl6S79iUXV6Gu1fJUWzf2XM0D4Km27ojNRNjJTOtrnn7pOKWZSfSf/eGf9kn8/QBXfthIbbUKG1dves14F7Hkz42Zps6jbdywlUv4/rzOcHWxlaKu1VCuMvzxLqxQ42Jii4USCyr5/JSSnDI19pbmPNXWnSUDg5j7w3VUtYZxrDZSMU+2db+rJK4pIHwvdFRUqTlzJZX5k/oTn5pPXnE5oweEE9HGj6TMQtydbADILy43OC6/uAI3RxtjSK53GqmjtN4wrV80AQETxUFuzphwDz44nmLgVf2DCrWGL05nMK6DJ32DnKirg3PpZaQVKzGlGiNVJQVc3rWeXjPeQWz+54ndfTv2xi2kHSpFCfFHd3N643v0fWXVXx7TlBkd4cPx6wXk31H+9N9AdPYtAyS9VEViQRX/eaoVXfztOZZ4qxKS3NyMuX2bkVWmYle0aWV+EL4Xhkxaup0vFo4i+cAiams1RMVn8d3hKMJbeBlb2kPBzBTjYG5DMFwFBJoAfg4ybGUSFj3aXN8mNhMR5GJJn+ZOTN8VQ2xeBQt+SsDaQoymrg5ljZbVQ0IoqKwxovL6pSQjEXVFKUdWv6xvq9NqKUiKIfH3/Ty1Zg9mZmIs5FZYyK2wcfXC0T+EvfPHkHXlNL4dehlRfcPg6SCje7Az0zde1LcVKNRIJWJsZBIDr6uztZQCEzduq2o05CjUuNvc8izLJGa80S8QZa2WD46moDGdZzlA+F7cSUpWEQOmf46lzBxbKxm5ReVsfXccKdnF5BbpHnRcHW30f+teW3PlRraxJAv8DQTDVUCgCRCXX8mSgzcM2iZ29iJHUc3B6wXc7lStqNYtTGnhaoWNTEJ0tuJhSm1QXIPDGDhvnUHbuW1rsXXzpkW/p/58dXQdaGpNx4C/nVGdfSiqUHM0rkDfdi2zjOpaLd2DnTl4syRxgIsVXo5yLqWVGknpw0EqMcPNxoLfk3X/b7m5GW/0D6RWU8fqX5OpMcHgVuF7cW+qVDVUqWqwt5HTv0sIC9YdIDW7mJxCBX06NdcbqjZWUjq19mX97tNGVlw/CKECAgICRkddqyX7Dk+ZuraOyupafXs3f3tyFWrK1RqaOckZE+7BLwlF5JWbTt5Oc5nlXWl+JFIpFlY22Hn6U1GYS8bl33Br0R6plS3KsiKu/7ITsbkFHq06Gkd0AyISwchO3uw+n4XmNoOsXFXLzrMZLBjaktKqaipUtSx5sjUXU0qIMjHDdVwHTy5lllFQUYODpYRRYR5o6+BUSglyczPm9w9EKjFjze8pyM3FyG+GdCrUtZhKFI3wvTCkf0QwIpGIhLR8An2cWf7SYBLS8tny43kAPtn+O/Mm9iMxo5DU7GKWTBtITqGCH47HGFl5/dBYswHUF4LhKiBgIrjbSBkR6oaVhZiiqhp+iivgSEKRsWU9VMTm5hQkxZBw7AdqlBVIbexxCWxN31dWIbOxN7a8eqd7kDNejnJ2nsu8a987++LQ1sGnE9pjIdYVIFi065oRVDYsjpbmvNTTH2upGIWqlvj8Shb9lEC5WkNLN2uCbmbVWDuilcFxL+2KpbDSdB7q/op/2/fCzlrG2zMex8vVjmJFFfuOXmXJZwep1egW663ZegxLuQXr5o/E3lrGqehUhr68wSRyuP4bENWZ0soNAQEjMOU70zMG/glCaUsd3xy+cf9O/wKEkq86mptgHuV/yuolXxpbQqNAeXZVg44fuuhIvY119Z1H622s+kLwuAoICAgICAgImAhCqICAgMBf8vW6740toVHg27WrsSU0CnKumUac3P9KtInlD/6nyC08jC1B4F+GqRuuQuUsgb9F7969eeWVV/7x8UuXLqVdu3b61xMmTGD48OH1Nr6AgICAgICA6SI8Egs0Knbv3o25uWlVcqkPzMxELJzYm7ED2uLmaE1OYTlbf47ivS2/6ftYyS14d1p/hvRogaOdnNScUj79/iwbfrhgPOENgKutlNcfC6ZniDNyCzFphVW8ufMa17J0ab8sLcTMfiyY/q1dsbc0J7NYydaTaWw/e/cCpqaKmZmIheO7MbZfK9wcrMgpqmTrkWu8941hOp8QH0fendyLnm19kIhFXE8rYuzb+8goKP+TkZsmrrZSZg8MomeIMzJzMelFVSzYFUPMzc9E7PIB9zxu9c8JfPV76kNU2nAMa+PKsDZuBm05ChULftLFXEvMRIwJ96Czrx0SMxHXciv4+kI2CrXpLUiytpSyZNpAhvZqg4uDNdEJWcz5YB8X427dAxZNHcDEYRHYW8s5fSWVWSt3k5RhGhXVTNzhKhiuAo0LR0dHY0sAoLq6GguLxlNNZvYzPZgyrBNTlu8hNrWADiGefDF/GIpKNZ/uOgvA+y8OpHf7ACa+u5u03FL6dwpk7atPkFNUzoGT8UZ+B/WDrVzCt9MjOJtczJSvLlFSWY2fsyVlylu5KN8YHEKXQCde336FrBIl3YOcWTK8JfkKNb/eluu0KTN7dGemDG7HlFU/E5tWSIdgd76Y/Zju87D3EgABHvZEfvgMmw9e5d0tJ1FUVdPKzwlVjcbI6usXW5mEb6Z15lxyMdM2XaK4sgY/J0sUt30mHll+zOCYnsHOvDOiNYev5T1ktQ1LZqmK1cdS9K+1t6VIGxvuQVtPGz49mY6yRsO4Dl682MOXFZHJxpDaoHz25khaBbozaem35BQqGDuoPQfWTaX9mNVkFyiYPb43M0b3YMrbO0jNLmbxtIH8uHYy4WNWm0RmASFUQEDgDrRaLXPnzsXR0RF3d3eWLl2q31daWsrkyZNxcXHB1taWvn37Eh0d/cBj3xkq4O/vz/Lly5k0aRI2Njb4+vry5ZeGK1NPnTpFu3btkMlkdOzYkb179yISiYiKitL3uXbtGo899hjW1ta4ubkxfvx4CgtvPV337t2bmTNn8sorr+Ds7MzAgQP/9nVpSLq08WH/yescPHOD9NxS9hyPJfJ8Eh1behn0+fpgFL9HpZKeW8pXP17kSlKuQZ+mzpReAeSWqXhz5zWuZpaRWaLk5I0iMoqV+j7hfvbsvZTFueQSskpUfHcuk+s55bT1sTOi8vqlSysv9p9O5OC5ZNLzFOz5PYHIi6l0DLkVT/nWxB4cOpfMgg3HiU7KJyWnlANnkigorTKi8vrn+ZufiQW7YriaqSCrRMmpRMPPRGFFtcHWt5Ur51KKySxR/sXITQ9tXR0KVa1++6MYidzcjJ7NHNh+OYfr+ZWklaj46mwmQS5WNHOSG1l1/SKTShjeJ5QF6w5wMiqF5Mwilm04QlJmEVNG6OLwXxzTk/c3RrL/txiuJeYweel2PJxtGdqrtZHVCzwIguEq8LfZvHkzVlZWnD17lpUrV/L2229z5Igu/caoUaPIz8/n559/5uLFi7Rv355+/fpRXFx8n1H/nDVr1tCxY0cuX77MjBkzmD59OvHxOg+iQqFgyJAhhIaGcunSJd555x3mzZtncHxpaSl9+/YlPDycCxcucPDgQfLy8hg9evRd78vCwoKTJ0/y+eef/2O9DcGZaxn0ad+M5t5OAIQGutE11JfDZ28Y9BncPQRPZxsAHgn3J8jHiV/OJxlFc0PQt5Ur1zLLWDsujFOLerNnVldGdfY26HM5rZS+LV1xvZmeK6KZIwEuVpy4YTo5bc/EZtGnnR/NvRwACG3mQtc2Xhw+r/OeiUQwqHMgN7JK+GH5SNK+m8FvH49jSLfmfzVsk6RvSxeuZSr4cGxbfn+zN7tmdmFkxz9/WHOytuCREGd2Xch6iCofDm42Uj4Y1oL3B4cwpYsPjpa6sCs/BzkSsRmxeRX6vrnlagorqwl0sjSW3AZBIhYjkYhR3RECoVLX0C0sAH9PRzycbfn13K17p6JSxfmYdCJC/R623AZBJKq/rTEihAoI/G3atm3LkiVLAAgKCmLdunVERkYil8s5d+4c+fn5SKU6o2H16tXs3buX77//nqlTp/6j8z3++OPMmDEDgHnz5vHhhx9y9OhRQkJC2LZtGyKRiPXr1yOTyWjVqhVZWVlMmTJFf/y6desIDw9n+fLl+ravvvoKHx8fEhISCA4O1r+XlStX/qUWtVqNWm1YwapOW4vIrGG/Squ/OYGtlZTor2ei0WoRm5mxZH0k249c1fd5be1PfPL6EJJ2z6amVoNWW8eMVT9yMjqtQbU9THwc5Yzt4sPG39P4/Ggyod52LBzagppaLXsv6co3vrMvjneeas3vC3pTo9FSVwcLd8VwIaXEyOrrj9U7zmJrKSX6v8/f+jxs+p3tv8YB4GpvhY2lBXOe7sxbm06wcMNvDOjkz/bFwxn4+nZOXDWdeF9vBzljIrzZfDKNL4+l0MbbljeHtKBGU8e+y3fXnh8W7kmVWsORmHwjqG04kouq+O/ZDHIV1djJJQxr48ob/Zqx+Ocb2Mkl1Gi0KGu0BscoVLXYyU1rTUFFlZozV1KZP6k/8an55BWXM3pAOBFt/EjKLMTdSfdgn19sGOedX1yBm6ONMSTXO6YeKiAYrgJ/m7Zt2xq89vDwID8/n+joaCoqKnBycjLYr1QqSUr6516/288nEolwd3cnP1/3oxMfH0/btm2RyWT6Pp07dzY4Pjo6mqNHj2JtbX3X2ElJSXrDtUOHDvfVsmLFCt566y2DNrFvL8z9ej/w+/knjOzTmjGPhjLh7V3EpubTtrk7q14aRE5ROd8c1IVizHgqgs6tvHnqjW2k55bRo50fH736ODmF5Ry9aBpxbCKRiGtZZXx4SOcticsuJ8jdmjFdfPSG6/jufrTzteeFTZfILlHSMcDxZoyritOJ/9zz35gY2asFY/q1ZMJ7+4lNLaRtoCurpvclp6iCb47EYHbzd2v/qUT+s/siAFeS84lo5cWUwe1MynA1E4m4lqXgo8OJAMTllBPkZs3TEd73NFxHdPRif3QO1bXau/Y1Za7m3PKmZpbpDNlVQ1rQydeOao1pvdf7MWnpdr5YOIrkA4uordUQFZ/Fd4ejCG9hOmFT/2YEw1Xgb3Pnqn+RSIRWq6WiogIPDw+OHTt21zH29vb1fr4HpaKigiFDhvD+++/ftc/D41ZMoJXV/SvczJ8/n9dee82gzfXxv/bS1gfLZzzK6m9OsPNXXZWumOR8fN3teX1cT745GI3MQsJbU/rx9ILtHDyjM+quJefRtrk7r4zpZjKGa0G5mqS8SoO25PxKBt5cTS2VmPHqwCBmbr3M8eu6GOb43Apaetrw/CMBJmO4Lp/Si9Xbz7Hz2HUAYlIL8XWz5fUxEXxzJIZChZKaWg1x6YbhEfHpRXRr432vIZssBeVqkvIrDNqSCip5tLXbXX07+NvTzMWK2d8+eNx9U0VZoyWvXI2rtQUxuRWYi82Qm5sZeF1tZRKDhY2mQkpWEQOmf46lzBxbKxm5ReVsfXccKdnF5BbpPK2ujjb6v3Wvrbly4+4HnaaIiTtcBcNVoP5o3749ubm5SCQS/P39H8o5Q0JC+Prrr1Gr1frwhPPnz9+la9euXfj7+yOR/G8fealUqj/PHzR0mACAXGpusEIYQKPRYnbTtWYuEWNhLkZ7RwVnjfZWH1PgUmopAS6GDxj+zpZkleoW2UjEIiwkZtxZyFpTV2dSN3O51Pwe/+s6zG6+yZpaLRfjcwn2NszSEeTtSHpe2UPT+TC4lH6Pz4STFdmlqrv6jujgxbXMMuJzK+7aZ2pIJWa4WFtQllpLWomSWo2WVm7WXMzUpQhzt7HA2cqCpCLTWqx3O1WqGqpUNdjbyOnfJYQF6w6Qml1MTqGCPp2a6w1VGyspnVr7sn736fuM2DQw9VABYXGWQL3Rv39/unbtyvDhwzl8+DCpqamcOnWKBQsWcOFCw+QSfeaZZ9BqtUydOpW4uDgOHTrE6tWrgVtf3hdffJHi4mLGjh3L+fPnSUpK4tChQ0ycOBGNpmmkBvrpVALzxj/CoC5B+LrbM7RnC2Y93ZUfftfFNJZXqfntcirLpw+gZzt//Dzs+b9B7Rg3MIwffoszsvr6Y/OJVMJ87ZjWJwBfJ0sGt/NgdIQ3205lAFCp1nA2qZjXHw+mczMHvB3kPNnBk+HtPfnFhGIafzqTxLyxXRjUuRm+brYM7R7ErBEd+eHkrQUnH35/npG9WjDxsbY087TnhaHhPN4lkC9/jDKe8AZgy4k02vrYMbVXAL6Ocp4Ic2dUZ2++PZNu0M9KKmZgqLtJLsoCGN3OnWAXK5yszAl0smRmD1/q6uBseinKGi2/J5fwdLgHLVyt8HOQMSnCm8TCSpKLTCuzAkD/iGAe7RKCn4cDfTsHcfDTF0hIy2fLjzqnxifbf2fexH480bMVrQPd+e+SMeQUKvjhuFD1rikgeFwF6g2RSMRPP/3EggULmDhxIgUFBbi7u/PII4/g5nb3tF19YGtry48//sj06dNp164doaGhLF68mGeeeUYf9+rp6cnJkyeZN28eAwYMQK1W4+fnx6BBgzAzaxrPbq999BNLJvdl7WtP4OJgRU5hOf/94SLLNx3X93n2re95e2o/Ni0agYOtnPTcMpau/5X1+0ynAMHVTAUzt0Tx2qAgXuwXSGaJkuU/xvNjVI6+z2vbonntsWBWj2mLnaU52SVKPjx0g2/PZBhRef3y2ie/sOS5Hqx9qT8u9pbkFFXy35+iWf71KX2fH07e4KWPD/P6mC6smdGXhMwSxr69j1MxpmW4XctSMOvrKF4dGMT0vs3ILFHy3v7r7I/ONej3eFt3RMCBO9pNBQe5OS9088HKQky5WsONgkre/SWJcrXu4fzbyznUATO6+2IuNuNaTjlbL5rG1Pid2FnLeHvG43i52lGsqGLf0ass+ewgtTdjfddsPYal3IJ180diby3jVHQqQ1/eYBI5XMH0QwVEdXV3TqoJCDRtvvnmGyZOnEhZWRlyecPnKJQ/srTBz9EU8O3a1dgSGgXpl68YW0KjIKBjmLElNAq6tPW4f6d/Cd9+uMXYEhoFyrOrGnT8iBXH79/pATk7v1e9jVVfCB5XgSbPli1baNasGV5eXkRHRzNv3jxGjx79UIxWAQEBAQGBxoSpe1wFw1WgyZObm8vixYvJzc3Fw8ODUaNGsWzZsod2/qHPD3to52rMxKeYxor9/xX3Vq2MLaFR4O5uGjkxBQQEGheC4SrQ5Jk7dy5z5841towGZWSYO6PaGU45ZpWpeG2vbuHVlC4+tPG0wVFujqpWQ3x+JdsuZpOtUN9ruCaNq42Ulx8NpHtzZ2TmZmQUK1myL5bYbF1qm7eHt2RoO0+DY04mFvHi11FGUNtw/L64D96Od1c92vp7Kot3xWAhMWPhsJYMbu+JhcSM364XsHjnNQorqo2gtuF4LsKb5yJ8DNrSi5VMuPn/drA054UefnTwsUNuISazRMnX57P4Pcm0HrSGtXFlWBvDtQQ5ChULftIt2JOYiRgT7kFnXzskZiKu5Vbw9YVsFGrTiOu8HWtLKUumDWRorza4OFgTnZDFnA/2cTHuVv7iRVMHMHFYBPbWck5fSWXWyt0kZRT+xahNB1PPKiAYrgICTYSMEiXv3EyyDhikQ0ouquJESjGFFTVYS8WMbOfBgkebM3N3zF2poZoyNjIJm57vwPmUEmZ+E0VxZTV+TpYolIY/viduFLJk361sCqaWbB5g2JqTBqnOQjys+XpGFw5E6xaqLXqyFX1aufLipkuUK2t4a2QbPpvUgVEfm0bKn9tJKapizp5Y/WvNbanj5g9ojrWFhIX74ylT1tAvxJnFjwUzfccVEgtMKxVUZqmK1cdS9K9vT6E3NtyDtp42fHoyHWWNhnEdvHixhy8rIk0jx/PtfPbmSFoFujNp6bfkFCoYO6g9B9ZNpf2Y1WQXKJg9vjczRvdgyts7SM0uZvG0gfy4djLhY1abxAItE7dbhXRYAgJNBU1dHWWqWv32x2phgMgbRcTlVVJQWU1KsZIdl7NxtrbA1drCiIrrn4k9/MgtU7NkXxzXshRkl6o4nVRMZolhSp8aTR1FFdX6rVzV9H+M7qS4sprCcrV+69vajdSCSs4mFmMjkzA6wodle2M5faOIa5kKXt8WTcdmjrTzsze29HpHo62jpKpGvylu+3+3drdhz5UcrudVkKNQ8/X5LCrUtQS73l1Jr6mjratDoarVbxXVunuE3NyMns0c2H45h+v5laSVqPjqbCZBLlY0czKttQAyqYThfUJZsO4AJ6NSSM4sYtmGIyRlFjFlhG4B6YtjevL+xkj2/xbDtcQcJi/djoezLUN7tTayeoEHQTBcBQSaCO42Uj4b1YaPR7TipZ5+OFndu8a4VGJG7+ZO5JWrKaw0rao4vUJciM1WsGpUG359vSfbp3VmRHvPu/p19Lfn19d7sndmF958IgQ7uWlPLpmLRQzv4MXOs7qUX2187LCQmHEi4dbUZ3J+JVnFVbT3dzCWzAbDy17Gd5M68PVz4bw5oLnBA1tMbjm9g5yxkUoQAX2CnLCQmBF1MxG/KeFmI+WDYS14f3AIU7r44Gipu0f4OciRiM2IzbtVeCG3XE1hZTWBTneHmzRlJGIxEokY1R0hECp1Dd3CAvD3dMTD2ZZfz93KeayoVHE+Jp2IUL+HLbdBEIlE9bb9XbKysvi///s/nJyckMvlhIaGGuRxr6urY/HixXh4eCCXy+nfvz83btz4ixHvxrTv5gICJkJiYRWfnUwnW6HCQW7OU2HuvDUomDn74lDdnAYfEOLMuA6eyMzFZJWpWHYk0WDK1BTwdpAxqpMXX5/OYMPvqbTxsmXuY8HUaLT8eDM/58nEYiLjCsgqUeLjKGdmv+Z88n/teHbDBUzscugZEOqOrVzC9+d0MXwuNlLUtRrK7wihKCyvxsVWeq8hmixxuRWsPJJIRokKRytznovwYe3INkz6JgpljZa3fkpg8WPB7JvWiVqNFlWtliUH4skuu7uyVlMmuaiK/57NIFdRjZ1cwrA2rrzRrxmLf76BnVxCjUZrUO4VQKGqxU5+7wfgpkpFlZozV1KZP6k/8an55BWXM3pAOBFt/EjKLMTdSbdoML+43OC4/OIK3BxNY0GhsUIFSkpK6N69O3369OHnn3/GxcWFGzdu4OBw62F55cqVfPzxx2zevJmAgAAWLVrEwIEDiY2N1edevx+C4Sog0ASIyrrlHUovUXGjoIpPRramq789RxN1i0x+Ty7mSnY5DpYSBrd245VeASz+KYEaE7LWzEQiYrMV/CcyCYD43AoCXa0Z2dFbb7geupan75+YX0lCXgUHXu5OR38HzqWUGEV3QzO6iw/H4wrIN8HFePfjXFqp/u/kIp0h++3E9vQOcubn2HwmdfXBWipm9u4YylS19GjmyOLHgnn5+xhSTKjc6dWcW97UzDKdIbtqSAs6+dpRrTG9GO+/YtLS7XyxcBTJBxZRW6shKj6L7w5HEd7Cy9jSTJr3338fHx8fNm7cqG8LCAjQ/11XV8dHH33EwoULGTZMl41ny5YtuLm5sXfvXsaMGfNA5xFCBQQEmiBVNRpyFCrcb/OeKWu05Jaricur5INjKXjaSulkYvGMBeVqkgoqDdpSCirxsPtzL2JWiYriymp87rEC3xTwcpDTPdiZHbdVBisoVyOViLG5I0TC2caCAhM3biurNWSWqvCyl+FpJ+XJMA9W/ZLE5UwFyYVVbDmXSXxeBcPaNkw1v8aCskZLXrkaV2sLypS1mIvNkJsb/uTbyiSUKU0rnAggJauIAdM/x6nXmwQNXUbPSf/BXGJGSnYxuUU6T6vrHd5VV0dr8u7wwjZV6jNUQK1Wo1AoDDa1+t73kB9++IGOHTsyatQoXF1dCQ8PZ/369fr9KSkp5Obm0r9/f32bnZ0dERERnD794ItGBcNVQKAJIpWY4WYjpaTq3ouOROhuXuZmprW8NDqjDH8nK4M2PydLcv5i2tfVVoq9pTmFFaZpsI2M8KaoXM2vsfn6tmsZZVTXauke5Kxva+ZqhZejJZdSTdPr/AcyczM87WQUVVYjlYgB7goR0dbpvPemjFRihstNozWtREmtRksrt1sL0txtLHC2siDJhLzOd1KlqiG3qBx7Gzn9u4Sw/7cYUrOLySlU0KdTc30/GyspnVr7cvZqmhHV1h/1abiuWLECOzs7g23FihX3PG9ycjKfffYZQUFBHDp0iOnTpzNr1iz+n73zDo+i6uLwu5tks+m9dyCFQAKB0HsHRUCaIIpURUQURJBepCiCih+KCkqTJipFem8BQieQhPSQ3nvblM33x+LCkiioSTZZ5+WZ58nee+fOb4fd2TNnzj1n69atgCLnOlClBLyNjY2y73kQQgUEBBoAr/nbczM+j4yCUsz0dRjR0hZ5ZSUBMdlYG0ro6GrG3aQ88mTlWOhLGOxjQ2m5nNuJmrUA5acrcWyZ6M/ELi6cCE6juYMxw1o78PHvitRXehItpnRz41RoGpkFpTia6fF+nybEZxVzOTJTzeprHpEIRrR15NfrCSrxzPkl5fwcGM+CIU3JKSqjoKSMJcOaczMmmztPPFrXBKZ0duFyTDapeTIsDXR4o70T8spKzoRnUCCrICGnmJk9G/HtpYfklZTRqZE5rZ1NmH/wgbql1ygjW9pyJzGfzKJSTKU6DPGxprISAuNyKC6TczE6m1f87CgsrXiUDsueyIxCojOLnz15A6N3Ow9EIhHhD9No7GTJyncHEv4wjW2/Xwfg690XmTO+F5HxGcQmZbH4rX4kZ+Rx8HywmpXXP+bOncvMmTNV2nR1q3/CJZfL8ff3Z+XKlQD4+flx//59vv32W954440a0yQYrgICDQALfQnTu7pipKtFXkk5YWmFLDgSTr6sHG2xNl42BgzwtsJQokVOSTkPUgtYeDRcJS2QJhCclM/MPUFM79WEN7u5kZhdwmfHwjlyTxHXKpdX4m5jyEst7TCSapOeL+NKVBZfn4mmrEJzYn3/oLOHJQ7m+uwNTKjS9/G+ECrlTdkwvtWjAgQZLPzlvhpU1i6WhhIW9HPHWE/x2PteUj7Tfr5H7qOFaXMPPGByJ2eWv+SJno4WSTklfHoykkANM+DN9HSY0tEJA4kW+bIKItILWX4qSpk2b9ftZCqBqZ2c0dEScz85n+03k9QrupYwMZSybOoLOFibkJVXxIGz91i84Rjlj2J9124/h76ehPVzh2NqKOXy3VgGvbdJI3K4Qs0uztLV1f1TQ/Vp7Ozs8H6qcmDTpk359ddfAbC1tQUgNTUVO7vHBXVSU1Np2bLlc2sSVVZqUnpyAYG655Wtt9UtoV4glHxVkJujWavV/ylujczVLaFe4KqB+WL/Kbu+2KZuCfWC4sDPanX+7l9errG5zr3f8bnHvvrqq8THx3Px4kVl24wZMwgMDOTy5ctUVlZib2/PrFmz+OCDDwDIy8vD2tqaLVu2PPfiLMHjKiAgICAgICCgIagrfHvGjBl07NiRlStXMnLkSK5du8b333/P999//0iXiPfff5/ly5fj7u6uTIdlb2/PkCFDnvs4guEqICAgICAgICDwr2jTpg379u1j7ty5LFu2DDc3N7788kvGjBmjHDN79mwKCwt58803ycnJoXPnzhw7duy5c7iCECog8ATdu3enZcuWfPnll+qW8rdRp3bfRafq/Jj1kUbOpuqWUC8o+4/lzPwztDR81f7z4u1oom4J9YZ1Szc+e9B/gNoOFej51fOnlnoWZ6Z3qLG5agrB4ypQ7xg3bhw5OTns37//uff57bff0NHRrAowT2NtpMv7fZvQ2d0CqY4W8VnFLNwXTEjS49yDbpb6zOjrTmtXM7TFIqLSC5i5O4iUXM1IBTWqlT2jnirxmpBTzLRfqq4GXtjPndZOJqzSwIU4r7Z2YIy/ajL1+Oxipvx8T/nay8aQsW0c8bQ2QF4J0ZmFLDwcRqmGLVIb3dqe0a1Vz0VCTjFTf1YsRFsx0BMfe2OV/qMhaWy4pBmpj6oj7NReQg5vo3HXQfi+PFmlr7KykivfLyH1wS3aTZiHvU/9M0z+LYb6uix+qx+DujXHysyQu+GJzPr8ADdDHy9iXPhmX8YPboepoR5XgmKZvvo3ouIz/mLWhoOm3zMKhqtAjVBRUYFIJEIsVk9qYHNzzV4IYiTVZuskf67HZDN1+x2yC0txttAn74mSno5memyd5M++W0l8cyaaAlk5TawNKC3XLA/gw6xiFh8NU76uzsH5UnPNTi4PEJtVxIJDT5yHJx6eedkYsmyAB3vvJPNtwEMq5JW4WehrbMnbh1lFLDz855+J46Fp7LiRqHwt07DvxJNkx4UTe+UYxvau1fZHnT+g8ZbNhnnD8W5sy4Qlu0jOyGN0/1YcXv8mrUatISk9jw9e787UkZ2ZvGwPsUlZLHqrH7+vm4TfqDUak1lAkxEKEAhUS3Z2NmPHjsXMzAx9fX0GDBhARESEsn/Lli2Ymppy8OBBvL290dXVJS4uDplMxqxZs3BwcMDAwIB27dpx7ty5KvsdP36cpk2bYmhoSP/+/UlOTgZgyZIlbN26lQMHDigTIJ87d44lS5ZUmxx5y5YtgCJU4P3331ceZ/v27fj7+2NkZIStrS2vvvoqaWmPE7SfO3cOkUjE6dOn8ff3R19fn44dOxIW9vjHrz4xoYsrqXklLNofwv3EPBJzSrgSlUVC9uMcjO/2bszF8Ey+OBHJg5R8ErKLOReWQVahZlXGkVdWklNcrtzyZao/NG7megz2seF/F2LUpLBukMsryS4uU25Ppj6b3MGZg/dT2XsnmbjsYhJzS7gUnUW5hlquFXL+8jMhK5er9BeXaabhWi4r5vpPa/Eb+S4SvarZDHISo4k4t59Wo95Tg7q6QaqrzZAePsxff5iAOzFEJ2SyYtNJohIymTxU4V1+Z1QXPt18mkMXgrkfmcykJbuxszRmULdmalZfM4hFohrb6iOC4SpQLePGjePGjRscPHiQK1euUFlZyQsvvEBZ2WMjqKioiE8//ZRNmzYRHByMtbU106ZN48qVK+zevZugoCBGjBhB//79VYzeoqIi1qxZw/bt27lw4QJxcXHMmjULgFmzZjFy5EilMZucnEzHjh2ZNWuW8nVycjJr1qxBX18ff3//avWXlZXx8ccfc/fuXfbv309sbCzjxo2rMm7+/PmsXbuWGzduoK2tzYQJE2r2RNYQ3T0tCU7MZ81IH87N7sqet9sxrPXjR+YiEXT1sORhZhEbxvpxbnZXdrzZhh5eVmpUXTvYGevy42hfvh3pw4zublgaSJR9Ei0xM3s04vuAOHKKNdtzYm8iZdtrLflhtC+zejbCylBxHkyk2njZGJJbXM6awU356XU/PnnJC29bzU3LZG+iy+YxLfh+lA8zezRS+UwAdGtiwU9jW/K/4c0Y28YRiZZm/vTd+eVbbJv6Y+3ZskpfeWkJN7avocWwKUiNzepeXB2hraWFtrYWJU/dvJTIyujYwg1Xe3PsLI05c+3xb1JeYQnXg+No5+NS13JrBZGo5rb6iBAqIFCFiIgIDh48SEBAAB07KnK47dixAycnJ/bv38+IESMAhXH4zTff0KJFCwDi4uLYvHkzcXFx2NsrjKpZs2Zx7NgxNm/erKymUVZWxrfffkvjxo0BmDZtGsuWLQPA0NAQPT09ZDKZMlkxgEQiwdBQ8cN79epVFixYwNatW2nevHm17+FJA7RRo0Z89dVXtGnThoKCAuU8ACtWrKBbt24AfPTRR7z44ouUlJT86QpHmUxWpU6zvLwUsbak2vE1haOZHiPbOLD9ShybLsTSzMGYOS94UlZRycE7yZgbSDDQ1WZiF1f+dzqKL09E0Mndgi9G+TJxy01uxubUqr66IjytgK8uKDyIZno6jGplz8qBnkz/LZiSMjkT2zvxIK2Aa3E56pZaq4SlFfDFuWgSckow15fwamt7Vg9qytS997A1ViQLf9XfgR+uxhGdUUQvD0tWDvRi6s/3SMrTjHjnPwhLK2TduRjFZ0Jfh1GtHPhkkBfv/nKf4jI5FyKzSCuQkVVYhquFHm+0dcLBVMqqk5Hqll6jJNy6QG5iFN1nfF5t/739mzB39cLep30dK6tbCopkXA2KZe6E3oTFppGalc/Ivn60a+5CVEIGthZGAKRl5avsl5ZVgI25kTokC/xNBMNVoAqhoaFoa2vTrl07ZZuFhQWenp6EhoYq2yQSCb6+vsrX9+7do6KiAg8PD5X5ZDIZFhYWytf6+vpKoxUU1TaefIz/V8TFxTFkyBClZ/bPuHnzJkuWLOHu3btkZ2cjl8uV+z9Z2eNJ/X9U8khLS8PZ2bnaeVetWsXSpUtV2qy7vo5Nt7HPpf+fIhaJCE7K46tTUQA8SMmniY0BI9o4cPBOMuJHd8ZnH6Tz05U4AMJSCmjpZMpIf0eNMVxvJTwuYfuQYiLSC/l+lA+d3czJLSnDx96ImftC1KiwbrgZn6v8OzarmLC0Aja/2oIujcyJf1QA4WhoGqfCFItNoq/E0cLBmD5eVmy9VrXKVkPm1lPnIjytkE2v+tK5kTknwzI4/iBd2f8wu5jsojKWD/TC1kiXlHzNMOKLstMJ2reRTm8vQ0un6k108v1A0iOC6DlrnRrU1T0TluzmuwUjiD68kPLyCu6EJfLziTv4eTk8e2cNQFRfXaU1hGC4Cvxj9PT0VL4gBQUFaGlpcfPmTbS0tFTGPunlfHr1v0gk4nmyshUWFjJo0CA6dOig9ND+2bh+/frRr18/duzYgZWVFXFxcfTr14/S0lKVsU9q+eO9/GHkVkd1dZs7fnLpmdr/LekFMqLTC1XaYtIL6e1tDUB2URllFXKinhoTnV6In4tpretTF4WlFSTlyrA11sXFXA9bY112jPVTGTO7V2NCUwtYcLh+xi/XBIWlFSTmlmBnIuVuksK4j89WrUEfn1OsDCfQZApLK0jKkWFnXP1Tk7A0xXfEzkRzDNechEhkBTmcXfu+sq1SLicjOpjoS4dw6/gChZkpHJqnWpkocPMnWDbypsu0VXWsuHaJScyk79vfoi/VwdhASkpmPtuXjyEmKYuUTIWn1drcSPm34rUhQRGaUQJXrNl2q2C4ClSladOmlJeXExgYqAwVyMzMJCwsrEod4ifx8/OjoqKCtLQ0unTp8o+PL5FIqKioUGmrrKzktddeQy6Xs3379r+8o3zw4AGZmZl88sknODk5AXDjxo1/rOdJqqvbXNthAgB34nJxtdRXaXOxMCD5kXetvKKS4MQ8XC2eHqOvHKOJSLXF2Brpcq64jIDoLE6Gpav0fzWsOT8GxnNdw9JhPY1UW4ydsZQzEZmk5peSUViKg4mq4eZgIuXGE95JTUWqLcbWWJezEaXV9jd69B3JLtKcRYtW7i3oNXu9StvNXV9iZO2IR6/hSAyMcevYX6X/9Opp+A6ZiG2ztnUptU4pKimjqKQMUyM9erf3ZP76w8QmZZGckUePNk2UhqqRgS5tmjmz8beay3+qTgSPq8B/Dnd3dwYPHszkyZP57rvvMDIy4qOPPsLBwYHBgwf/6X4eHh6MGTOGsWPHsnbtWvz8/EhPT+f06dP4+vry4osvPtfxXV1dOX78OGFhYVhYWGBiYsLy5cs5deoUJ06coKCggIKCAgBMTEzQ09NT2d/Z2RmJRML//vc/pkyZwv379/n444//+QmpB2y/HMe2yf5M6urK8fup+DgYM9zfgaUHH4dubAl4yGcjfLj1MJtrMdl0amJBN09LJm6+qUblNcu4to5cj8shvaAUM30dRrd2QF5ZycWoLPJKyqtdkJVRUEpaQfVGTENlYnsnAh/mkJYvw8JAwhh/xXk4H5kJwG93kxnT2oGYzCKiMxUxro6meqzUsLhOgPHtnLgWl0N6vgxzA0W8r7yykgtRWdga6dKtiTk34nPJLynH1UKfiR2cuJ+UR2xW8bMnbyDoSPXRsVNdWKQtkSIxMMb4UXt1C7L0zKwwsLCt0t7Q6d3OA5FIRPjDNBo7WbLy3YGEP0xj2+/XAfh690XmjO9FZHwGsUlZLH6rH8kZeRw8XzUftED9QzBcBapl8+bNvPfeewwcOJDS0lK6du3KkSNHnpnkf/PmzSxfvpwPPviAxMRELC0tad++PQMHDnzuY0+ePJlz587h7+9PQUEBZ8+e5fz58xQUFCg9wE8e7+lsAVZWVmzZsoV58+bx1Vdf0apVK9asWcOgQYOeW0N9Izgpjxm7gnivTxPe6uZGYk4Jq4+GcSQoRTnmTGg6H//+gIldXZnzgiexGUXM3HOP23Ga42WzMJDwQY9GGEm1yS0pJzSlgDkHH6ikgvovYGEgYXavxhhLtcktLic4JZ+Z+0OU5+HAvVQkWmImd3TGSFebmMwiFhx+QIqGLcwCsDDUYVbPRspzEZKaz4f7Q8krKUeiJaaFgzEv+dgi1RaTUVjKlZhs9tzSjEfCAtVjYihl2dQXcLA2ISuviANn77F4wzHKHyX4Xbv9HPp6EtbPHY6poZTLd2MZ9N4mjcnhquEOV6Hkq4DAv0Uo+apAKPmqQCj5qkAo+apAKPn6GKHkq4LaLvk68LvrNTbXobfa1NhcNYVmJrMTEBAQEBAQEBDQOIRQAQGBf8k3r7dWt4R6gYneX4eR/Fc4GpGqbgn1AgOJ1rMH/QfI0vBCGH8LfWN1K/hPIGQVEBAQEBAQEBAQaBAIWQUEBATUzuGft3LryjmSEx4ikejSuKkPI8a9g63j45XEqz96m7D7t1X269b/ZcZOm1PXcmuVkKBbHNizjeiIULIzM5i9dA1tO/dQ9hcXF7Fj4/+4FnCOgrxcrG3tGTB0FP1eGq5G1bXL3WM/c2P/Fpr1HEz7kW8BUF5WyrVfNhJ94wIV5WU4erei4+h30NOwcp9BZ3/n3tnD5GUoPN0WDi60fWkMrr6K2LzC3Cwu/byJ+OBblJYUYWbrRJuBo2ji/89T9tV37p/4mTsHtuLVYzD+w99EVphP0OGfSAq9TVF2OrqGJjj5tqfFS68j0TNQt9waRSwWseCNbozu0xwbc0OSM/LZfjyIT7ZfVI4pPruw2n3nfXuKL/ZoRkosTUYwXAUEGgDh92/T48VhuLl7I6+o4NdtG1i78D2Wb9iFrvRxOrCu/QYz5LU3la8lutUnYW/IlBQX49rYg54DBvHZ4g+r9G/d8Dn3b19n+tyPsba15+6Nq2xc9wnmFla06dhNDYprl/TYcB5cPIq5g5tKe+De74m/d52ek+ci0TPg8u4NnPp2OS/NXqsmpbWDoZkVnYZPwNTGgcrKSkIDTnLof0sYveRrLBxcObHpM0qLChg4fQl6hiaEBZ7l6IaVvLLof1i7NFG3/Bon42E4EZeOYfrE56E4N5Oi3CxaD52Iia0zhVlpBO5eT3FuFl0nz1Oj2prng9EdmTy4NZM/OUBITDqtPe35bs5L5BWW8M1vikVLrkNVy+L2bdeEbz98iX0XQqubssGh4Q5XYXGWgEBDYMayL+nceyAOLo1wauTOxBkLyUpPITbygco4ia4UEzML5aanr1neFIBW7ToxesJU2nXuWW1/WHAQ3foOpHlLf6xt7ekzcCiujd2JfKB5ORrLSoo59+NqOr82HYn+4+p0pcWFhAecoN3wydh7tcTSxZ2ub8wgLTqUtOgHfzFjw6NRy/a4+rbF1MYBM1tHOg4bj45USkqU4n2mRIbg22swto28MLG2o+1Lr6Krb0Dawwg1K695ykqKCdjyGe1ffVfl82Bq70q3yfNx9GmHkZUdtp4taPnSWBLuByJ/qthLQ6d9M0cOBYRx7Gokcam57LsQyukb0fg/Ue41NbtQZXupkyfn78QSm5yjPuE1iFgkqrGtPiIYrgICDZCiQkUBBgND1cUOV88d571X+7Fw6qv8uuUbZCWaWzXrz/Bs5suNKxfITE+jsrKS+7evk5QQRwv/9uqWVuNc3v0NTs3b4tBUtcxtxsMI5BXl2DdtqWwztXXCwNyKtGjN8CpVh1xeQXjgOcpkMmwbNwXAtok3EdfOU1KQR6VcTnjgOcrLSnH09FWz2prn+s8bcGjWBjsvv2eOLS0uQkeqj1hLsxbRXQ1OoEcrN5o4mgPg09iGDs2dOHGt+uIb1mYG9G/fhK1H7tShSoF/gxAqICDQwJDL5eze+CVNvH1xdG2sbG/XvR8WVraYWliSEBPJL1u+JiXxIe/M/1SNauueidNm8+3ny3lr1AC0tLQQicVMmbkAb99W6pZWo0RdP09mXCSD5q6r0lecl41YWxvdJ7xuAHpGZhTlZdeVxDojIyGGvSvep7ysFB1dPQZOW4SFgyL++4W353N0w0q+nz4CsZYW2hJdXpy2GFMbh2fM2rCIvXGerPhIBsz+8pljSwpyuX90F+6d+j9zbENjzc4AjPV1ubt1KhVyOVpiMYt/OMvuU/erHf9aP1/yi0rZryFhAqD5oQKC4Sog0MDYseEzEh9G8dHq71Xau/Ufovzb0bUJJuaWrJk/jbTkBKztHOtYpfo4sn83EaH3+ejjL7C0sSP03i02ffUp5hZW+LZup255NUJBVjpXf/6OAe+tQFtHom45asfM1pHRS76htLiIiBsXObFpDcPmfIaFgwtX9m1FVlTAy7M+QWpoTPTtKxzdsILhc9di6ej27MkbAIXZ6dz45Xt6vbscrWd8HkqLizj7zRJM7JzxfXFMHSmsO4Z3b8ao3s0Zt3wfIbHp+Dax4bN3+pKcmc+O40FVxo8d0JI9p+4hK9OckAkhq4CAgEC9YceGNdy9HsCcT77F3NL6L8c28mwGQFrSf8dwlclK2PXD13y4dA2t2ytWjbs2dic2MoyDe7drjOGaERdBSX4O+1e+q2yrlMtJibxPyLnf6T99OfLycmRFBSpe1+L8bPQ1LKsAgJa2jtKDau3qTlpMGHdP7afVgBEEnT7ImI+/w8LBFQAr58Ykhd8j6MxBeo59T42qa46suEhK8nM48sl0ZVulXE5a5H3Czv/O6HX7EYu1KCsp4szXC9GR6tHtzQWItTTPBFg5pRdrdl1m71lFTHtwTBrONiZ8+GqnKoZrJx8nPJ0teX3Zb+qQWmtouN0qGK4CAg2ByspKdn67lltXzjN71ddY2do/c5+46HAATMwtaltevaGivJzy8nJEItXwfbFYC7lcc0qx2nu15OWF36i0Xdz2BSa2jvj2HYGhuRViLW2SHtzBrVVnAHJSEijMSse6UVN1SK5TKisrqSgvo7xUBlDl8yASa1Ep15xq57aeLRg4/2uVtsvbv8TExpFmfYcjFmtRWqwwWsXaOnSfsuiZntmGip6uDvKn/m8r5JXVLjR64wU/boYlcS9KKBrSkBAMVwGBBsBPGz4j8PwJ3l2wGqm+AbnZmQDo6Rsg0ZWSlpxA4LkT+LTpiKGRMQmxkezeuA6P5n44ubmrWX3NUlxcREpivPJ1akoSMZFhGBoZY2Vjh3eL1mz/fh0SXV2sbOwIuXuT8ycP88bbM9SoumaRSPUxf+RB/ANtiRSpgbGy3aNTXwJ/2YiugRESqT5X9nyLdaOmWDfyqnvBtUjALz/i6tMGIwsrSkuKCbt6loSwIIbMXIGZrRMm1vac2baOziMnK0IFbl0mLuQWg95bpm7pNYaOVB9Te1eVNm1dKbqGxpjauyqM1vULKC+V0e2NWZQVF1FWXASArpEJYrHmLNA6ciWCOa91Jj4tl5CYdFq62zJ9RDu2Hb2rMs5IX8LQbk35aMNJNSmtPeprNoCaQjBcBQQaAOeOKB5lrZ47VaV9/PsL6Nx7INraOoTcvc7Jg7uRlZRgbmlN647dGThqgjrk1ipRYSEs+eAt5eutGxQ5Gbv3Hci0OUuZsWAlOzet56uVCyjIz8PSxpbRE6bSV4MLEFRHuxFvIhKJOP3dCuTlZTh4t6bj6KnP3rGBUZyXw4lNn1GYm4Wunj6Wjm4MmbkC52aKUsyDZywn4Jcf+P2rxZSVFGNqbU+fibNw9W2rZuV1R1Z8JBmxYQAcWDJJpW/Ish8xtLBRh6xaYeZXx1g8oTvr3huAlZkByRn5/PD7LVZuu6AybkTPZohEIn4+o3lp8jTbbAVRZWWl5jwvERBQA5ciNG+V9j/BRE9H3RLqBUcjhMeOAAYSzfHi/RuyisvVLaHesHLFLnVLqBf8WeWummLU1tvPHvSc7H7j2anV6hrB4yogICAgICAgoCEIWQUEBDSAc+fO0aNHD7KzszE1Na12zJIlS9i/fz937tz5W3Mfikj/9wI1gJj0QnVLqBdk5cvULaFekCecBwDaNdWcx/D/mqI8dSv4TyDWbLtVMFwFBBoiYaf2EnJ4G427DsL35ckqfZWVlVz5fgmpD27RbsI87H06qEllzTO8hS0jWtqptCXmljBzvyJ5+OT2TjS3N8JcT4eS8grC0grZeTOJpDzNMqJeb+vI2LaqKc7isouZuEOxAMVMX4c3OzrTyskEPYkWCdkl7LyZyKWoLHXIrXWsDCW806MRHRubo6stJiG7mI8Ph/EgpQAtsYgpXV3p2NgcB1M9CmTlXI/N5utzMWQUlKpbeq3Q292cQc2sOReVxW/30pTtrmZSBnpb4WKmR2VlJQm5MjZcjqdMgzIsABjq67L4rX4M6tYcKzND7oYnMuvzA9wMTVCOWfhmX8YPboepoR5XgmKZvvo3ouIz1Kha4HkRDFcBgQZGdlw4sVeOYfzUKuI/iDp/QKMT+cVnF/PxicflG+VPhOlHZxZxKSaLjIIyDHW1GN7Sjvl9mjDtt2A0LZo/JrOIOQceV/upeML4mNO7MQa62iw6HEZuSTk9PSxZ0M+dd36+R1RGkTrk1hpGUm2+f92PW3E5vL/nHtlFZTib65FfoogtleqI8bQ14seAOCLSCjCWajOjTxPWDG/OuC231Ky+5nE2ldLJ1ZTEXNVyz65mUt7u6MTJ8Ex+CUpFXgkOxrpo2NcCgA3zhuPd2JYJS3aRnJHH6P6tOLz+TVqNWkNSeh4fvN6dqSM7M3nZHmKTslj0Vj9+XzcJv1FrkJU2/JhkTQ8VED97iIBAzdK9e3feffdd3n//fczMzLCxsWHjxo0UFhYyfvx4jIyMaNKkCUePHlXuc//+fQYMGIChoSE2Nja8/vrrZGQ8vjuWy+WsWrUKNzc39PT0aNGiBb/88kuVY9+8eRN/f3/09fXp2LEjYWFhdfKea4pyWTHXf1qL38h3kegZVunPSYwm4tx+Wo3SjMTq1VFRWUluSblyy5c9rnhzOiKT0NRC0gtLickqZs/tJCwNJVgbal7OSrm8kuyiMuWWV/L4B9fb1ogDQSmEpRWSkidj541ECkvL8bA2UKPi2uH19k6k5cv4+HAYIcn5JOeWEBiTTWKOwnArlFUwfXcQpx+kE5dVzP2kfNaciKSpnRE2xrpqVl+zSLREjPW3Z9edFIrKVPMWD/Wx4Xx0NqciskjJLyWtoJTbSfmUa5i3VaqrzZAePsxff5iAOzFEJ2SyYtNJohIymTxU8fTpnVFd+HTzaQ5dCOZ+ZDKTluzGztKYQd2aqVl9zSAS1dxWHxEMVwG1sHXrViwtLbl27Rrvvvsub7/9NiNGjKBjx47cunWLvn378vrrr1NUVEROTg49e/bEz8+PGzducOzYMVJTUxk5cqRyvlWrVrFt2za+/fZbgoODmTFjBq+99hrnz59XOe78+fNZu3YtN27cQFtbmwkTGla6qDu/fIttU3+sPVtW6SsvLeHG9jW0GDYFqQZWR/oDWyNdNoxozldDvXm3iwsWBtVnM9DVFtO9iQWp+TIyCsvqWGXtY28qZff4Vmx7vSUf9WmC1RPGeUhKPt3cLTDS1UIEdHe3QEdLzN1EzYsx7OpuQWhyPiuHeHN0ege2jW/F4Ba2f7mPoa4W8spKCkoavnftSUa0sCU4pYDwdFWvuqFEC1dzPQpkFczo4szy/k2Y3tmZRuZ6alJae2hraaGtrUWJTPX/tkRWRscWbrjam2NnacyZaxHKvrzCEq4Hx9HOx6Wu5Qr8A4RQAQG10KJFCxYsWADA3Llz+eSTT7C0tGTyZEW85qJFi9iwYQNBQUGcOnUKPz8/Vq5cqdz/xx9/xMnJifDwcFxcXFi5ciWnTp2iQwfFHXWjRo24dOkS3333Hd26dVPut2LFCuXrjz76iBdffJGSkhKkUmldvfV/TMKtC+QmRtF9xufV9t/bvwlzVy/sfdrXsbK6IzKjiA0BcSTllWCmp8OwFrYs7e/BrAOhlJQrPEx9PS0Z09oeqY4WibklrDgZqfIYXRN4kFLAmlNRxOeUYGGgw2ttHPliaDMm77pLcZmcj49FsKC/O79NbkN5hRxZuZylR8JJytWsWF8Ae1M9hrbSY9e1BLZcicPbzoiZfZpQJq/kyL2qqckkWiKmdW/EiZA0Cks1pz59KwcjnEx0WXP+YZU+y0c3dwO8LNl/P43E3BLaOJkwrZMTq87EkK5BN3YFRTKuBsUyd0JvwmLTSM3KZ2RfP9o1dyEqIQNbCyMA0rLyVfZLyyrAxtxIHZJrHE0PFRAMVwG14Ovrq/xbS0sLCwsLfHx8lG02NoqVuGlpady9e5ezZ89iaFj10XhUVBRlZWUUFRXRp08flb7S0lL8/FRz0D15XDs7O+UxnJ2dn0u3TCZDJlP98S8vK0W7lssnFmWnE7RvI53eXlZtqcbk+4GkRwTRc9a6WtWhbu484TGMyy4hIr2Ir4c3o4OrKWcjFQuPLkZnEZSUj5m+NgOb2fB+NzcWHQnXqAUo1+NylH/HZEJoSgE73vCjWxMLjoWmM669EwYSbWbvDyG3uJyOjcxY0N+dGb8FE5tZrD7htYBYBKHJ+Ww4HwNAeGoBjaz0GepnX8Vw1RKLWPGyN4hg9bGI6qZrkJjqaTPUx4ZvLsdX++j/D0MmICabwLhcABJy0/Cw0qe9iym/h2hWZpQJS3bz3YIRRB9eSHl5BXfCEvn5xB38vBzULa1OELIKCAjUAjo6qo93RSKRStsfF1q5XE5BQQEvvfQSn376aZV57OzsuH//PgCHDx/GwUH1wqSrqxrD9mfHeF5WrVrF0qVLVdo6vTqNzmPefe45/gk5CZHICnI4u/Z9ZVulXE5GdDDRlw7h1vEFCjNTODRvlMp+gZs/wbKRN12mrapVfeqiqKyC5LwSbJ+IVSwuk1NcJiMlX0Z4egw/jvKhjYspl2M0t1BEYWkFCTkl2JtKsTPWZYivLZN23uVhlsJIjc4swsfemME+tqw7F6NmtTVLRkEpMU8tOIvNKKKHp5VKm5ZYxMoh3tgZS5m6665GeVudTKUYS7X5sLursk1LLKKxhR5d3MxYcSoagJR81SwKqfmlmOlpnhkQk5hJ37e/RV+qg7GBlJTMfLYvH0NMUhYpmQpPq7W5kfJvxWtDgiKS1CW5RhE8rgICaqZVq1b8+uuvuLq6oq1d9SPr7e2Nrq4ucXFxKmEBtcHcuXOZOXOmStuys3G1ekwAK/cW9Jq9XqXt5q4vMbJ2xKPXcCQGxrh17K/Sf3r1NHyHTMS2meaWttTVFmNjpMuFqOqNUhGPboo03AUh1RFjZyIlKywDXR3F0oWniyLKKyvr7WKLf0NQQi4uFvoqbc7m+qQ8sar+D6PVyVyPqTvukqdh1azC04tYdTpape3VVnakFZRyKjyTjKIycorLsDZSfVpjbSghJLWgLqXWKUUlZRSVlGFqpEfv9p7MX3+Y2KQskjPy6NGmidJQNTLQpU0zZzb+dkXNigWeB8FwFaj3vPPOO2zcuJHRo0cze/ZszM3NiYyMZPfu3WzatAkjIyNmzZrFjBkzkMvldO7cmdzcXAICAjA2NuaNN96oMS26urpVvLi1HSYAoCPVR8dOdeGAtkSKxMAY40ft1S3I0jOzwsDirxeqNCRe87fnZnweGQWlmOnrMKKlLfLKSgJisrE2lNDR1Yy7SXnkycqx0Jcw2MeG0nI5tzVsUdKbnZy5GpNNan4pFgY6jG3riLyykrPhGRSUVpCYU8x73RvxfcBD8krK6dTInFZOJiw81LCyaDwPu64nsun1lrzRwZnTD9LwtjNmSEs7Vh0LBxRG6ycve+Npa8gHe+8jFoP5o5jPvOJyjVhVLyuXk/yUN7W0opLC0gpl+5nILAZ4WZKUKyMht4S2ziZYG0n48VquOiTXKr3beSASiQh/mEZjJ0tWvjuQ8IdpbPv9OgBf777InPG9iIzPIDYpi8Vv9SM5I4+D54PVrLxm0MD7UxUEw1Wg3mNvb09AQABz5syhb9++yGQyXFxc6N+/P2Kxwrv08ccfY2VlxapVq4iOjsbU1JRWrVoxb948NasXqEks9CVM7+qKka4WeSXlhKUVsuBIOPmycrTF2njZGDDA2wpDiRY5JeU8SC1g4dFwlVRRmoClgYR5/dwxkmqTW1zG/aR8pu+9T+6j9zn/9zAmdnTi44GeSHW0SMot4bNTUVx7mKNe4bVAaHI+s38LZmo3NyZ2diEpp5gvTkVyPFiReN/aSEJXD0sAfpror7Lv2zvucCtO8wy36jgXlY22WMTLza3Rlyg+E98ExJNRpDkLs/7AxFDKsqkv4GBtQlZeEQfO3mPxhmOUVyjCwtZuP4e+noT1c4djaijl8t1YBr23SSNyuAKINfHRyhOIKp9+niQgIPC3+OhIuLol1AuEkq8KhJKvCoSSrwqEkq+P2bjqB3VLqBcUB35Wq/NP2nO/xuba9ErzGpurphA8rgICAgICAgICGoKGO1wFw1VAQEBAQEBAQFMQsgoICAj8JesWf6tuCfUCy7a1m9GhoZCTkaNuCfUCN8//Rs7MZxGR/N+IoX0u9I3VrUBAAxAMVwGBBoKhvi6LpwxgUPfmWJkZcTc8gVlr93MzJB6AwT18mDS0I35ejliYGtBuzBqCwjUjL+EfXF7WB6enUh8BbD0fw5pDocx80YuuTa1xMNMjs0DG8aAU1vweSr6GLc66/79huFhXLcjx/fEHfPBjIG42Rqx4zZ8OXtZItMWcupvErM2BpD+RIkpTsDbS5f2+TejsboFUR4v4rGIW7gsmJOlxjk43S31m9HWntasZ2mIRUekFzNwdRIoGVRIb4+/Aa20cVdris4t5c3cQ1kYStr7mV+1+K45HcCk6qy4k1glisYgFb3RjdJ/m2JgbkpyRz/bjQXyy/aJyTPHZhdXuO+/bU3yxp+GnxNJwh6tguAoINBQ2LBiJd2M7JizeSXJ6HqMHtObw11NoNXI1Sem56EslXL4bw6+n7rBhwSvqllsrDFx9Hq0ncrJ62hmza3pHDt1OxMZEio2JlOW/3SciJR8Hc31WjWqBjYmUKZuuq1F1zdN93iHET5wHb2czfl/Ql31XY9HX1Wb/vD7cj8vixWXHAVj4ih8/z+5FzwWH0aTluEZSbbZO8ud6TDZTt98hu7AUZwt9lTytjmZ6bJ3kz75bSXxzJpoCWTlNrA0oLX/+wiMNhdisIuYdfKB8XfHoPzujoJRXt9xSGTvA25phLe248UQVNk3gg9EdmTy4NZM/OUBITDqtPe35bs5L5BWW8M1viuuA61DVstl92zXh2w9fYt+FUHVIrnE0PauAYLgKCDQApLo6DOnhy4hZPxJwW5FofMXG47zQxZvJwzqy9Nuj7Dp6EwBnu6r5XDWFrALVXJVT+9gQm17A1YhMAN56wkB9mFHE6t9DWfdGK7TEIio0IF/nH2Q8tWJ/ZitHolLyuBSSSk9fe1ysDej80e/kFytSHb319SXifxxNt+Z2nLuXrA7JtcKELq6k5pWwaH+Isi0xR9Wr/G7vxlwMz+SLE5HKtoRszSp7+wcV8kqyi6umt5JXUqW9o5sZF6MyKdEwA759M0cOBYRx7Kri/zsuNZeRvZrh7+UAKK4PqdmqGVBe6uTJ+TuxxCbn1LFagX+CWN0CBAQEno22lhhtbS1KnsozWCIro2NLNzWpUi86WiKGtnVkz5U/r1xmpKdNQUm5RhmtT6OjJWZU50b8dFbxQ62rLaayEmRlj0ualpRVIK+spIOntbpk1grdPS0JTsxnzUgfzs3uyp632zGstb2yXySCrh6WPMwsYsNYP87N7sqON9vQw8vqL2ZtuDiYSPlprB8/jmnB7F6NsTKsvjhKE0t9GlsZcDw0vY4V1j5XgxPo0cqNJo7mAPg0tqFDcydOXIusdry1mQH92zdh65E7daiydhGJam6rjwiGq4BAA6CgSMbVoBjmTuyDnaUxYrGIUQNa087HFVvL/+aCh34t7DDW02Hv1fhq+80MJLw3wJOdAQ/rWFndMrCNEyYGEn46r/hhvh6RTqGsnGVjWqMn0UJfV5sVr/ujrSXG1kxPzWprFkczPUa2cSAuq4gp227z87UE5rzgyaCWdgCYG0gw0NVmYhdXAiIyeWvbLU6HpvHFKF9au5qqV3wNE5ZWwNoz0Sw49ID1F2KxMdblsyHe6OlU/Znv19SauKxiQjWw3OuanQHsPRPM3a1TyTs5j6vfT2b9r9fYfar63Kav9fMlv6iU/RoSJgCKrAI1tdVHhFABAYEGwoRFO/lu0Siijy6hvLyCO2GJ/HziNn5ejs/eWQMZ1cGFsyFppFaz4MhQqs3Wqe2JSM7n88MPqtlbcxjb052TdxJJefT4OyNfxtgvzvPFxPa83b8p8spK9gbEcDs6E7lmPRVGLBIRnJTHV6eiAHiQkk8TGwNGtHHg4J1k/ggDPvsgnZ8eeebDUgpo6WTKSH9HbsbmqEl5zXPjiQpgsVnFhKUWsPW1lnRpbMGJB489qxItEd3dLdh1M1EdMmud4d2bMap3c8Yt30dIbDq+TWz47J2+JGfms+N4UJXxYwe0ZM+peypPKBo6mu6RFAxXAYEGQkxiJn3f+hp9qQRjA11SMvPZvvJ1YhIz1S2tznEw16OzlxVvbrxWpc9AV5vt73SgoKScyd9f04ha9H+Gk6UBPXzsGLP2nEr7maAkWrz3GxZGupRXyMktKiPyu5H8mpZf/UQNlPQCGdFPVWyLSS+kt7ciJCK7qIyyCjlRT42JTi/Ez8W0rmSqhcLSChJzS7A3kaq0d25sga62mNNhGWpSVrusnNKLNbsus/dsMADBMWk425jw4audqhiunXyc8HS25PVlv6lDqsA/RNMNcwEBjaOopJSUzHxMjfTo3d6LQxdqrrxfQ2Fke2cy8mWcvp+q0m4o1WbHtA6UlcuZ8G0gMg1bePI0r3VvQnpuCcduJVTbn5kvI7eojK7NbLEylnLkRvVhFQ2VO3G5uFqqpkdzsTAg+dECrfKKSoIT83C1eHqMvnKMpiLVFmNnLCWrSHVBYz8vKwJjc8jVsBRxf6Cnq4P8qZvVCnlltSvt33jBj5thSdyLSq3S15ARQgUEBATqBb3beyISiQh/mEZjR0tWvvcS4bFpbDuo8DqaGevjZGuKnaUJAB4uCq9TamY+qZma42kTiWBkB2d+CYxXWXT1h9GqJ9Hiva03MdLTxkhPcYnLzJehaY5XkUhhuO48H1Vl8dlr3ZsQlphDRp6Mtu5WrB7Xhq+PhBCRnKcmtbXD9stxbJvsz6Surhy/n4qPgzHD/R1YevBxvOKWgId8NsKHWw+zuRaTTacmFnTztGTi5ptqVF7zTOrgTGBsNqkFMiz0JbzWxhF5ZSXnIx4/kbEz1qW5vRGLDoepUWntcuRKBHNe60x8Wi4hMem0dLdl+oh2bDt6V2Wckb6Eod2a8tGGk2pSWnuI66e9WWMIhquAQAPBxFDKsndexMHalKy8Ig6cCWLxN0cor1B4FV/s2oyNi0crx29fORaA5d8fZ8XG42rRXBt08bTC0VyfPVdUF101dzKhlZtiJfGlpX1U+josPEFClmalQOrhY4+zlSHbz1VdLe1uZ8yS0a0wM5QQl1bAZ/vusf5wSDWzNGyCk/KYsSuI9/o04a1ubiTmlLD6aBhHglKUY86EpvPx7w+Y2NWVOS94EptRxMw997j9REyoJmBpIGFOnyYYS7XJLS4nODmfGb8Fq3hW+za1IqOglFvxmvXen2TmV8dYPKE7694bgJWZAckZ+fzw+y1WbrugMm5Ez2aIRCJ+PhOsJqUC/xRRZaUmpaMWEKh79NrMVLeEeoFQ8lWBUPJVgVDyVYGDnZG6JdQbzv18Qt0S6gV/Vrmrpph5sOYWpH4+yKvG5qopBI+rgICAgICAgICGUF9jU2sKwXAVEBCoEWTFmlP3/d9Qnp2mbgn1gvJyO3VLqBc4WxmqW0L9oUizYqwF1IOQVUDgHxMbG4tIJOLOnTt/OubcuXOIRCJycnL+9fG6d+/O+++//5djRCIR+/fv/9fHEhAQEBAQaIiIRTW31UcEj6uARpGcnIyZmZm6ZdQKhvq6LJ4ygEHdm2NlZsTd8ARmrd3PzRBFiqPBPXyYNLQjfl6OWJga0G7MGoLCk9Ssuma5sfpFnC0NqrT/eCaSj366xb7Z3enkpVrWdOvZKD7crlkryMViEQte78joXt7YmBmQnFnI9pP3+WTHFZVxnk7mLJ/UjS6+TmhriXjwMJPRyw4Qn645WSYArI11+aCfO108LZHqaBGXWcT8X4MJTlR4+EJW9q12vzVHw/nxYmwdKq0b+nlaMtTHhtMRmfx8V7FQzVhXm2G+NjS1MUCqrUVqvowjD9K5nahZnwV4dK18qx+DujXHysyQu+GJzPr8ADdDH6eNW/hmX8YPboepoR5XgmKZvvo3ouI1I7ethkcKCIargGZha2urbgm1xoYFI/FubMeExTtJTs9j9IDWHP56Cq1GriYpPRd9qYTLd2P49dQdNix4Rd1ya4V+H59C64mrspejMb/M6s7B64/zk247H8XqfY9XCheVal6+yg9GtmXywJZM/uwoIQ8zaO1hy3cfDCCvUMY3+28B4GZnyukvXmXrsXss3xZAXlEp3i4WlGhQhSAAY6k2O95qy7XoLN7acouswjJcLPTJKy5Tjum68pzKPl08LPl4aDNO3Nes/J0ALmZSujYyI/6pPLXj2zqgpyPmm4B4CkrLaetkwpvtnVh5OrrK2IbOhnnD8W5sy4Qlu0jOyGN0/1YcXv8mrUatISk9jw9e787UkZ2ZvGwPsUlZLHqrH7+vm4TfqDXINPB6oWkIoQICSo4dO0bnzp0xNTXFwsKCgQMHEhUVpey/du0afn5+SKVS/P39uX37dpU5jhw5goeHB3p6evTo0YPY2Ni/pSEgIIDu3bujr6+PmZkZ/fr1Izs7W9kvl8uZPXs25ubm2NrasmTJEpX9nwwVKC0tZdq0adjZ2SGVSnFxcWHVqlXKsREREXTt2hWpVIq3tzcnT56st6EGUl0dhvTwZf5XvxNwO5rohAxWbDxOVHwGk4d1BGDX0Zus2nSCM9fC1ay29sjMl5GWV6Lc+rSwJyY1n8thj0taFpdWqIwp0MBE6+29HTh0JZJj16KJS81j38VwTt+Mxd/zcVzp0vGdOX4tmvmbznM3Ko2Y5BwOX40iPadIjcprnond3EjJLWH+r8HcS8gjMbuYy5GZxD+R/iyjoFRl6+ltzbWYLBKyNStFmq6WmIltHdl+M4mip25QGlnocTYyi9jsYjIKyzjyIIOi0gqcTaV/MlvDRKqrzZAePsxff5iAOzFEJ2SyYtNJohIymTy0AwDvjOrCp5tPc+hCMPcjk5m0ZDd2lsYM6tZMzeprBrFIVGNbfUQwXAWUFBYWMnPmTG7cuMHp06cRi8W8/PLLyOVyCgoKGDhwIN7e3ty8eZMlS5Ywa9Yslf3j4+MZOnQoL730Enfu3GHSpEl89NFHz338O3fu0KtXL7y9vbly5QqXLl3ipZdeoqLi8QV469atGBgYEBgYyOrVq1m2bBknT1afQPqrr77i4MGD/Pzzz4SFhbFjxw5cXV0BhQE8dOhQJBIJgYGBfPvtt8yZM+fvn7Q6QltLjLa2FiVPeQNKZGV0bOmmJlXqRUdLzPD2Luy8FKvSPqy9M6HrBnN+WT/mD/NBT6KlHoG1yNWQRHq0dKGJgyIsxqeRFR2aO3DiejSgeFTYv21jIhKzObhyOA9/nsqFr8bwUscm6pRdK/RsasX9hDy+GO3LxXnd+XVae4b7/3kqLgtDCV09Lfn1RmIdqqwbRvvZcS+lgAdphVX6ojOL8XcyQV9HCxHg72iMjpaY8HTNupHR1tJSXCtl1VwrW7jham+OnaUxZ65FKPvyCku4HhxHOx+XupZbK4hrcKuPCKECAkqGDRum8vrHH3/EysqKkJAQLl++jFwu54cffkAqldKsWTMSEhJ4++23leM3bNhA48aNWbt2LQCenp7cu3ePTz/99LmOv3r1avz9/fnmm2+Ubc2aqd4B+/r6snjxYgDc3d1Zv349p0+fpk8f1YTzAHFxcbi7u9O5c2dEIhEuLo8vSqdOneLBgwccP34ce3t7AFauXMmAAQP+UqNMJkMmU109XykvRySu3a9SQZGMq0ExzJ3Yh7CYVFKz8hnZrxXtfFyJStCMuKy/y4BW9pjo67A7IEbZ9ltgHAkZhaTklODtZMLC4b40sTVi/NeX1ai05lmzJxBjfV3u/jCRCrkcLbGYxVsusvuMomKUtakBRvoSZr3SlqVbLrFg0wX6tnFl96Ih9PtwN5fuVV8itiHiaKbHqHaObA14yPfnYmjuaMy8l7woq6jkwO2qMd6D/ewpklVwMlizsj/4OxrjbCZl5enoavu/vxrP5HZOfDHYiwp5JaUVcjZciSO9sLTa8Q0VxbUylrkTehMWm6a4Vvb1o11zF6ISMrC1UOTVTctSje1NyyrAxlwzcu7WU0dpjSEYrgJKIiIiWLRoEYGBgWRkZCCXKyoyxcXFERoaiq+vL1Lp48dKHTp0UNk/NDSUdu3aqbQ9PeavuHPnDiNGjPjLMb6+viqv7ezsSEur/gdo3Lhx9OnTB09PT/r378/AgQPp27evUquTk5PSaH1eratWrWLp0qUqbVp27dFxeP73+U+ZsGgn3y0aRfTRJZSXV3AnLJGfT9zGz8ux1o9dHxnTpRGn76WQ+kR83vbzj3+0QxNzSc0p4bfZ3XG1MiA2vaoXqqEyvJsXo3o1ZdwnhwiJzcC3sTWfvd2T5MwCdpwMVq4GPnQ5kv/9pliYFhSdRjtvByYPbKlRhqtYJOJ+Yh5fnlBUEAtNzsfdxpBX2jlWa7gO9Xfg0N1kSsvldS211jDT0+aVlnZ8eTGW8j+pbTy4mTX6EjFfXIilQFZOS3tj3mznxGfnYkjK06xUdhOW7Oa7BSOIPrzwiWvlHfy8hKIYmoBguAooeemll3BxcWHjxo3Y29sjl8tp3rw5paV1c0eup6f3zDE6Ojoqr0UikdLAfppWrVoRExPD0aNHOXXqFCNHjqR379788ssv/1jj3LlzmTlTtVKWdY8F/3i+v0NMYiZ93/oafakEYwNdUjLz2b7ydWISM5+9s4bhaKFPV29rxq//a0/qrWjFuXGzNtQow3Xl5G6s2X2NvecUFXKCYzNwtjHmw1Ht2HEymIy8YsrKKwiNU/1shMVl0rG5Zt3opOfLiEorUGmLSi+kTzObKmNbu5rSyMqAD3bdrdLXkHE208NYqs38Xo2VbVpiEe6W+nRvbM6i4xH0aGLBkhORJD8yUhNy02nyqH/n7WR1Sa8VYhIz6fv2t+hLdTA2kCqulcvHEJOURUqmwtNqbW6k/Fvx2pCgCM3IwlJfY1NrivoawiBQx2RmZhIWFsaCBQvo1asXTZs2VVkU1bRpU4KCgigpeezdunr1qsocTZs25dq1ayptT4/5K3x9fTl9+vQ/fAfVY2xszCuvvMLGjRvZs2cPv/76K1lZWTRt2pT4+HiSkx9fsJ9Hq66uLsbGxipbbYcJPE1RSSkpmfmYGunRu70Xhy7cr9Pj1wdGd3YjI0/GyaC//sFt7mwKQGquZq2a1tPVQf5Ute4KeaXyB6usXM7NsBQ8HM1Vxrg7mhOXqll16m/F5eBmpZoizdXCgKRqVsoPbe3A/YRcwlIKqvQ1ZB6kFbL0RCTLT0Upt9isYq7F5bL8VBQSLcVP/dMV3uWV9TdXZ01QVFL2xLXSk0MXgolNyiI5I48ebR7HexsZ6NKmmTOB9x6qUW3NIRLV3FYfEQxXAQDMzMywsLDg+++/JzIykjNnzqh4Fl999VVEIhGTJ08mJCSEI0eOsGbNGpU5pkyZQkREBB9++CFhYWHs3LmTLVu2PLeGuXPncv36daZOnUpQUBAPHjxgw4YNZGT8sxjOzz//nF27dvHgwQPCw8PZu3cvtra2mJqa0rt3bzw8PHjjjTe4e/cuFy9eZP78+f/oOHVF7/ae9OnghYu9OT3benDs26mEx6ax7aDiZsHMWB9fD3uauilSgnm4WOPrYY+NhWbEbf2BSASjOrmy53IsFU88FnW1MmDmS974upjhZKFPv5b2rJ/UjsthaYQkaJaxduRqFHNGt6d/20Y42xgzqJM704f6czDg8YKTL365zvBuXowf4Esje1OmDPLjhfaN+f73O+oTXgtsu/QQXycT3uzmhrO5Hi+2sGVEW0d2XY1TGWegq0U/H1uNXJQlK5eTlCdT2WQVcgpLK0jKk5GSLyM1X8ZrrexxNdPD0kCH3u4WNLUx4E6S5uVx7d3Ogz7tPXGxM6NnW3eOfTOF8IdpbPv9OgBf777InPG9eLGLN80a2/LD4lEkZ+Rx8HzwM2YWqA8IoQICAIjFYnbv3s306dNp3rw5np6efPXVV3Tv3h0AQ0NDfv/9d6ZMmYKfnx/e3t58+umnKgu6nJ2d+fXXX5kxYwb/+9//aNu2LStXrmTChAnPpcHDw4MTJ04wb9482rZti56eHu3atWP06NH/6D0ZGRmxevVqIiIi0NLSok2bNhw5cgSxWHG/tm/fPiZOnEjbtm1xdXXlq6++on///v/oWHWBiaGUZe+8iIO1KVl5RRw4E8Tib45QXqEIlXixazM2Ln58rravHAvA8u+Ps2LjcbVorg26edvgZGnAzosxKu2l5XK6elvzZh939HW1Scoq4tDNBD7/PURNSmuPmV+fYvEbnVn3bm+sTPVJzizkhyN3WfnT49CJgwERvPvVCT4c1Z61U3sSnpDN6GUHuBysWYbb/cQ8pv90hxn93Hm7ZyMSsov55NADDj1KvP8HL/jaIgIOP9X+X0BeCesD4ni5uQ3vdHJGV1tMWkEpW64ncl/DvM/w6Fo59QUcrE0U18qz91i84ZjyWrl2+zn09SSsnzscU0Mpl+/GMui9TRqTw1WTvegAosqnnx0ICPyHEYlE7Nu3jyFDhjz3PnptZj570H8AI5/26pZQL8hP0IzHjf8WN/8W6pZQL+jSSlgQ9AfbPtuibgn1guLAz2p1/mUnI2tsrkV96l8KPSFUQEBAQEBAQEBAoEEghAoI1BkDBgzg4sWL1fbNmzePefPm1bGimsF70EvqllAvMDLSVbeEeoFx+/9mQQiB6rE2lKhbgsB/jPq6qKqmEAxXgTpj06ZNFBdXX2LR3Ny82va6pj5HzlgZSZjeqzEdG1sg1RGTkF3MkoMPCE2uurhi7gseDG/twJrjEey6pjk5O8e1d2JceyeVtrisIsZuuwOAvYkub3dxxcfeGB0tEdce5vDVuRiyi8qqma3hMrq1PaNbqz6CTsgpZurPigwTKwZ64mNvrNJ/NCSNDZc0L4xBOBdVCT25l3uHtuLebRB+Q98E4Mae9aSG3aEkLwttiRQLt6b4DhqHsY3TM2ZreBjq67L4rX4M6tYcKzND7oYnMuvzA9wMfXwtXPhmX8YPboepoR5XgmKZvvo3ouI1o5iLpse4CoarQJ3h4CDEev1TjKTa/DiuFTdic5i+6y7ZRWU4m+uRX1LVIOvhaYmPgzFpGpZU/A9iMor44LfHq3//yCwg1Rbz2cvNiMooZMaviv6JHZ1YOciLqbvvUX9vSf4ZD7OKWHg4TPm64ql0xsdD09jxxAp6mQYl3H8a4Vw8JuthONGXj2Fi76rSbubUBJfW3dE3s6K0KJ/gYzu58M0iXli8CbFYs8oib5g3HO/GtkxYsovkjDxG92/F4fVv0mrUGpLS8/jg9e5MHdmZycv2EJuUxaK3+vH7ukn4jVqjMQu0NBkhxlVAoAEwrqMzqXkylv7+gOCkfJJySrganU1CtmquSisjCR/2d2fB/hDK/6QwQ0OnorKSrKIy5ZZbovihaW5vhK2xLp+ciCQms4iYzCJWHY/E08aQVk4malZd81TIIae4XLnlP1WbXVYuV+kvLtPMzwMI5+IPymTFXN2+Bv9R7yLRN1Tpa9yxP1ZNmmNgYYOZUxOav/A6RTnpFGVpVulbqa42Q3r4MH/9YQLuxBCdkMmKTSeJSshk8lBFhcN3RnXh082nOXQhmPuRyUxashs7S2MGdWv2jNkbBqIa/PdP+eSTTxCJRLz//vvKtpKSEt555x0sLCwwNDRk2LBhpKam/u25BY+rgEADoKuHJVeisvh0WDNauZiSli/jlxuJ7Hui4o0I+HiwN9uvxBOdXqQ+sbWMg6mUXyb5U1ohJzg5n40BD0nLL0XnUZL1sifcbaUVciorwcfBmJvxmpXL1d5El81jWlBWIedBaiHbriWQ8UTd+W5NLOjubkF2URnXH+ay+1YSpU+7IjUE4VwouLV3A3bebbDxbEnIid1/Oq5cVkJM4CkMLGzQM7WsQ4W1j7aWFtraWpQ8dfNSIiujYws3XO3NsbM05sy1xzmP8wpLuB4cRzsfF/aebPhV1dQdKnD9+nW+++67KiXaZ8yYweHDh9m7dy8mJiZMmzaNoUOHEhAQ8LfmFwxXAYEGgIOZlOH+9uy4msCPAQ/xtjNiVj93yioqORSkyEs5rpMzFfJKjYppfZqQlHw+ORFJfHYxFgYS3mjnyFcjfBi//TYhKfkUl1XwVmcXNgbEIQLe7OyClliEuYHOM+duSISlFbLuXAyJuSWY6eswqpUDnwzy4t1f7lNcJudCZBZpBTKyCstwtdDjjbZOOJhKWVWDaXLqC8K5UBB36zw5CVH0/uCLPx0TefEwQQc3U15agpG1I92mLkdLW7O+GwVFMq4GxTJ3Qm/CYtNIzcpnZF8/2jV3ISohA9tHBVnSslTXBqRlFWBjrhnFWtRpuBYUFDBmzBg2btzI8uXLle25ubn88MMP7Ny5k549ewKwefNmmjZtytWrV2nf/vnTKQqGq4BAA0AsEhGSlM/XZ6MBCEspoIm1IcNa23MoKAUvW0NGtXVkzMYbalZau1yLzVH+HZ1RRGhKPrsntKaHhyVHgtNYcjiMGT0bM7SlHZWVcDosnbDUAurxmrt/xK0nvMexWcWEpxWy6VVfOjcy52RYBscfpCv7H2YXk11UxvKBXtga6ZKSr1mxz8K5gKLsdG7/upFuUz9GS+fPsxg4+3fHxrMlJXnZhJ39jSubP6Hn+5/95T4NkQlLdvPdghFEH15IeXkFd8IS+fnEHfy8hHUWfxeZTIZMpvo90dXVRVe3+iwy77zzDi+++CK9e/dWMVxv3rxJWVkZvXv3VrZ5eXnh7OzMlStXBMNVQEDTyMgvJSajUKUtJqOQnl5WAPg5m2JuIOHwex2U/dpiMTP6NOHVdo689L+rdaq3riiQVZCQXYKDqRSAG3G5jNlyCxOpNhWVlRTIKvhtsj9nwqvWrdckCksrSMqRYWcsrbY/LE3x2bEz0Rxj7c/4L56L7PhIZAU5nFzznrKtUi4nPSqYyIuHGLZ2H2KxFhI9AyR6BhhZO2Du6sn+uaNIDLqCc+tualRf88QkZtL37W/Rl+pgbCAlJTOf7cvHEJOURUqmwtNqbW6k/Fvx2pCgiCR1Sa5RRDWYD2vVqlUsXbpUpW3x4sUsWbKkytjdu3dz69Ytrl+/XqUvJSUFiUSCqampSruNjQ0pKX+vmp1guAoINADuJuTiYqGv0uZsrk9yrsIgO3IvhWsx2Sr9619twZF7KRy8m4ymoqcjxt5UlxMPSlXa/1iw5edojKm+Dpejs9Qhr86QaouxNdblbERptf2NHn12NC0tWHX8F8+FtUcL+s1Zr9J2bec6jG0c8eo17M+zBlRCRbnmnIenKSopo6ikDFMjPXq392T++sPEJmWRnJFHjzZNlIaqkYEubZo5s/G3K2pWXDPUZKjA3LlzmTlTtTpkdd7W+Ph43nvvPU6ePIlUWv1NY00hGK4CAg2AHVfj2Ty+FeM7uXAyJI3mDkYMbWXPikcpgHKLy8ktVl2MUC6Xk1FQysPM6nPnNkTe7uLC5ehsUvNlWBhIGN/eCbkcTocp8i/297YmLquInOIymtkZMa2bG3tvJROfrVke1/HtnLgWl0N6vgxzAwmvtrZHXlnJhagsbI106dbEnBvxueSXlONqoc/EDk7cT8ojNktzPgt/IJwL0JHqV0l/pa2ri8TACBN7VwoyUoi/fQEbr1boGhhTnJvJg1N70dKRYOftrx7RtUjvdh6IRCLCH6bR2MmSle8OJPxhGtt+V3gCv959kTnjexEZn0FsUhaL3+pHckYeB88HP2Pm/x5/FRbwJDdv3iQtLY1WrVop2yoqKrhw4QLr16/n+PHjlJaWkpOTo+J1TU1NxdbW9m9pEgxXAYEGQEhyPrP23mdaz0ZM7upCUk4Ja09EcPT+308l0pCxMtRl4QAPjKXa5BaXcS8pn6l7gpRGu7OZlDc7OWMk1SYlT8ZP1xLYe1vzPM4WhjrM6tno0XkoJyQ1nw/3h5JXUo5ES0wLB2Ne8rFFqi0mo7CUKzHZ7LmlGY9Bn0Y4F89GS0eH9Khgws8dpKy4AF0jU6waN6Pn+58hNTJVt7wax8RQyrKpL+BgbUJWXhEHzt5j8YZjlD/KJLF2+zn09SSsnzscU0Mpl+/GMui9TRqTw1UdlbN69erFvXv3VNrGjx+Pl5cXc+bMwcnJCR0dHU6fPs2wYcMACAsLIy4ujg4dOlQ35Z8iqqzPpYIEBBoArT8+q24J9QKh5KsCY33NWqUt8O9o4Wyqbgn1hjWLv1e3hHpBceBntTr/lxdjamyu97v88xLW3bt3p2XLlnz55ZcAvP322xw5coQtW7ZgbGzMu+++C8Dly5f/1ryCx1VAQEBAQEBAQKBW+eKLLxCLxQwbNgyZTEa/fv345ptv/vY8guEqICAgICAgIKAhqLsAwR+cO3dO5bVUKuXrr7/m66+//lfzCoZrPSI2NhY3Nzdu375Ny5Yt//E8rq6uvP/++yql1mqScePGkZOTw/79+2tl/tqitnRnZWpulaq/g4eLmbol1AtyCjUjxdK/ZXBLG3VLqBdkFVWoW0K9YdDUV9Ut4T+BOmJc6xLBcBX4z7Bu3Toaakj3xUU9cDTXr9K+/WIsi34NRqItZsHgpgxsZY9EW8yFB+ks2nufjILqUwI1VIa1sGV4C9UVqIm5Jcw68AADiRYjWtriY2eEpYGEPFk5N+Jy+flOssbVph/j78BrbRxV2uKzi3lzdxDWRhK2vuZX7X4rjkdwScNSg9098ztBZw6Tl6FYqGjh4EK7wWNw821DbnoKP374RrX7vTh1Ph5tu9al1Drj3vGfuXVgC017DKbtiLcACL90lOjr58iKj6SspJjRa35Gom+oZqU1z/AWtoxoaafSlphbwsz9oQBMbu9Ec3sjzPV0KCmvICytkJ03k0jKE244GwqC4Srwn8HExETdEv4xg9cGIH7i+Y+nnSE/TW3P4Uc5Whe+7E0Pb2ve2XKL/OIylg5vzoYJrRnxlWbkJXyS+OxiVpyMUr6WP7oZMdPXwVRPhx03k0jIKcHKUMLE9o6Y6evw5flYNamtPWKziph38IHydcWj85BRUMqrW26pjB3gbc2wlnbciMupS4l1gqGZFZ1HTMDUxgGoJOTSSQ6uW8KYZV9jbufEm1/uUhl/7/wRbhz9BVffNuoRXMtkxIYTfukoZg6qi2rKS2U4eLfGwbs1tw5sUY+4OiI+u5iPTzwu6St/wmERnVnEpZgsMgrKMNTVYnhLO+b3acK034I1psKeGM12uYrVLeC/iFwuZ/Xq1TRp0gRdXV2cnZ1ZsWKFsj86OpoePXqgr69PixYtuHJF1fi4dOkSXbp0QU9PDycnJ6ZPn05hoWpVpfz8fEaPHo2BgQEODg4qMSUTJkxg4MCBKuPLysqwtrbmhx9+AOCXX37Bx8cHPT09LCws6N27d5VjrFmzBjs7OywsLHjnnXcoK3ucyFomkzFr1iwcHBwwMDCgXbt2yniXvLw89PT0OHr0qMp8+/btw8jIiKKiv370Hhsbi0gk4ueff1aehzZt2hAeHs7169fx9/fH0NCQAQMGkJ7+uNzjuHHjGDJkiPJ19+7dmT59OrNnz8bc3BxbW9tqq4HUB7IKS8nIlym3ns1siE0vJDAyCyOpNiPbObFifwhXIjK5n5DHhzvv4t/InJYupuqWXuNUVCoKDPyx5csUj2ITckr48nwstxLySCsoJTilgD23k2nlaFxvYr5qkgp5JdnFZcot71HRBXklKu3ZxWV0dDPjYlQmJeWa5XkGaOzXHrcWbTGzdcDM1pFOw8ejI5WSEvkAsVgLA1NzlS3y5mU82nRFItVTt/Qap6ykmItbVtNhzPQq3lTvnkPw6TcSKzcvNamrOyoqK6u9RgCcjsgkNLWQ9MJSYrKK2XM7CUtDCdaGmlP2ViSqua0+IhiuamDu3Ll88sknLFy4kJCQEHbu3ImNzeN4sPnz5zNr1izu3LmDh4cHo0ePprxc8aMUFRVF//79GTZsGEFBQezZs4dLly4xbdo0lWN89tlntGjRgtu3b/PRRx8pK1oATJo0iWPHjpGc/Di/5aFDhygqKuKVV14hOTmZ0aNHM2HCBEJDQzl37hxDhw5Vecx+9uxZoqKiOHv2LFu3bmXLli1s2bJF2T9t2jSuXLnC7t27CQoKYsSIEfTv35+IiAiMjY0ZOHAgO3fuVNG8Y8cOhgwZgr5+1Ufi1bF48WIWLFjArVu30NbW5tVXX2X27NmsW7eOixcvEhkZyaJFi/5yjq1bt2JgYEBgYCCrV69m2bJlyvNUX9HREjGktQN7A+MBaO5kgkRbzKXwDOWY6LRCErOKaOWqeXGntkYSvhnejC9fbso7nZ2xMPjz9FP6OloUl8mRa4gn5UkcTKT8NNaPH8e0YHavxlj9yQ9vE0t9GlsZcDw0vdp+TUIuryDs6jnKZTLsmjSt0p8aG0F6XBTNu/ZTg7raJ3DPNzg0b4u9V/WhIv8VbI102TCiOV8N9ebdLi5/eo3Q1RbTvYkFqfkyMgo1p4KYWFRzW31ECBWoY/Lz81m3bh3r16/njTcUsVeNGzemc+fOxMbGAjBr1ixefPFFAJYuXUqzZs2IjIzEy8uLVatWMWbMGOXCK3d3d7766iu6devGhg0blKXWOnXqxEcffQSAh4cHAQEBfPHFF/Tp04eOHTvi6enJ9u3bmT17NgCbN29mxIgRGBoaEh4eTnl5OUOHDsXFxQUAHx8flfdhZmbG+vXr0dLSwsvLixdffJHTp08zefJk4uLi2Lx5M3Fxcdjb2yvf07Fjx9i8eTMrV65kzJgxvP766xQVFaGvr09eXh6HDx9m3759z30uZ82aRb9+ih+g9957j9GjR3P69Gk6deoEwMSJE1WM6erw9fVl8eLFynO5fv16Tp8+TZ8+fZ5bR13T18cWYz1tfrmWAICVkS6y8gryn6qclZFfipWxZuVWjUwv5NvLxSTnyjDV12GYry2L+7kz++CDKt5EI10tXva15fQTBr2mEJZWwNoz0STkFGNuIGGMvwOfDfHm7T1BVeJ5+zW1Ji6rmNDUAjWprX0y4mPYvfx9ystKkejq8dK7i7BwcKky7v6FY5jbO2Pv3kwNKmuXmBvnyYyPZOCcdeqWolYiM4rYEBBHUl4JZno6DGthy9L+Hsw6EKq8RvT1tGRMa3ukOlok5paw4mQkFZp4d6uhCB7XOiY0NBSZTEavXr3+dIyvr6/ybzs7RZB5WloaAHfv3mXLli0YGhoqt379+iGXy4mJeZx0+OlKFB06dCA0NFT5etKkSWzevBlQlFw7evQoEyZMAKBFixb06tULHx8fRowYwcaNG8nOzlaZr1mzZmhpPa5/bWdnp9R47949Kioq8PDwUNF5/vx5oqIUsYkvvPACOjo6HDx4EIBff/0VY2Njevfu/Tynscp5+sNj/aSBbWNjo9T0PHM8/T6qQyaTkZeXp7JV1nGt75HtnTgfmk7af3Axwd2kfAIf5hKXU0JQUj6fno7GQKJFe1dTlXF6OmJm92xEYm4Jv95NUY/YWuRGXC6XorOIzSrmVnwuiw6HYSjRoktjC5VxEi0R3d0tOP7gr78HDR0zO0deW/YNoxd9hW/PgRzftIbMxIcqY8pLZYRdOUvzLprnbS3MSufa3u/oMm42Wjqa88j7n3AnMY+rD3OIyy7hblI+n5xSXCM6PHGNuBidxZzfw1hyLJzkPBnvd3NDp766F/8BYpGoxrb6iOBxrWP09J4dV6Wj8/ixhujRB0cuV9wpFhQU8NZbbzF9+vQq+zk7Oz+3jrFjx/LRRx9x5coVLl++jJubG126dAFAS0uLkydPcvnyZU6cOMH//vc/5s+fT2BgIG5ublU0/qHzSY1aWlrcvHlTxbgFMDRUxF1JJBKGDx/Ozp07GTVqFDt37uSVV15BW/v5P5LVnaen2/7Q9DxzPM8+q1atYunSpSptJu1GY9Z+zHPr/jc4mOnRycOSt3+8qWxLz5ehq62FkZ62itfV0khCuoYbt0VlFSTnybB9omqXVFvMR70aU1wu5/OzMVT8BxwphaUVJOaWYG8iVWnv3NgCXW0xp8M0z+v8JFraOo8WZ4GNqzspMWHcPrmf3uPeU44Jv36RslIZTTs9/81xQyEzLoKS/BwOffKusq1SLic18j4Pzv/Oa18dQCzW+osZNBfFNaIE2yeePhWXySkuk5GSLyM8PYYfR/nQxsWUyzHZfzFTw6Ge2ps1hmC41jHu7u7o6elx+vRpJk2a9Lf3b9WqFSEhITRp0uQvx129erXK66ZNH8d8WVhYMGTIEDZv3syVK1cYP368yniRSESnTp3o1KkTixYtwsXFhX379jFz5sxnavTz86OiooK0tDSlMVwdY8aMoU+fPgQHB3PmzBmWL1/+zLnVzdy5c6ucA995Z+rs+MPbOZKZL+NMyGMP2v34XErL5XRyt+RYkMK72MjaAAdzfW7FasaF+M/Q1RZjYyThYrTC662nI+aj3o0pr6hkzZloyv4jj/+k2mLsjKWcLlI1UPt5WREYm0NuiWbUYH9uKiupKFN9EhJ84TiN/Nqjb2yqHk21iJ1XSwYtUK1AFLDtC0xsHWned8R/1miFP64RulyIqv5aKELxe6dJHldNRzBc6xipVMqcOXOYPXs2EomETp06kZ6eTnBw8F+GD/zBnDlzaN++PdOmTWPSpEkYGBgQEhLCyZMnWb9+vXJcQEAAq1evZsiQIZw8eZK9e/dy+PBhlbkmTZrEwIEDqaioUMbbAgQGBnL69Gn69u2LtbU1gYGBpKenqxi+f4WHhwdjxoxh7NixrF27Fj8/P9LT0zl9+jS+vr7K+N2uXbtia2vLmDFjcHNzo127ds81vzrR1dVFV1c1blSkXTe16UUiGNHWkV+vJ6jEY+WXlPNzYDwLhjQlp6iMgpIylgxrzs2YbO48zKkTbXXFmNb23ErIJb2gDDN9bUa0sENeCZdjstHTETO3d2N0tcWsvRiDno4Weo/+a/Jk5RqT6gZgUgdnAmOzSS2QYaEv4bU2jsgrKzkfkakcY2esS3N7IxYdDlOj0trn0t4fcfVtg5G5FWUlxTy4epb4B0EM/eBxppac1EQSwu/x8oyP1ai09tCR6mNm76rSpq0rRdfAWNlenJtFcV42eelJAGQnxaKjq4eBuTW6BkZ1rLj2eM3fnpvxeWQUlGKmr8OIlrbIKysJiMnG2lBCR1cz7iblkScrx0JfwmAfG0rL5dxOzFO39Bqjvj7irykEw1UNLFy4EG1tbRYtWkRSUhJ2dnZMmTLlufb19fXl/PnzzJ8/ny5dulBZWUnjxo155ZVXVMZ98MEH3Lhxg6VLl2JsbMznn3+uXMj0B71798bOzo5mzZopF1EBGBsbc+HCBb788kvy8vJwcXFh7dq1DBgw4Lnf4+bNm1m+fDkffPABiYmJWFpa0r59e5U0XCKRiNGjR7N69epnrv4XgM4eljiY67M3MKFK38f7QqiUN2XD+FaPChBksPCX+2pQWbuY6+vwbhdXDHW1yCspJyytkIVHwsmXVdDUxhB3KwMA1g31Vtnv3V9DyCjUnGIMlgYS5vRpgrFUm9zicoKT85nxW7CKZ7VvUysyCkq5FZ+rRqW1T1FeDse//4zC3CwkevpYOrkx9IMVuDRvrRxz/+JxjMwsVdr+a4RdPMLdI48zuRz7XLEwt9PrM2jSof4uRv27WOhLmN7VFaMnrhELjoSTLytHW6yNl40BA7ytMJRokVNSzoPUAhYeDVemk9MENNxuRVTZUEsJCfxrCgoKcHBwYPPmzQwdOlTdchosbu8ffvag/wDtWzmoW0K9QCj5qkAo+apAKPn6mLsJmuPV/DfseaN205X9eD2uxuaa0Ob5187UFYLH9T+IXC4nIyODtWvXYmpqyqBBg9QtSUBAQEBAQKAG0PR0UYLh+h8kLi4ONzc3HB0d2bJly99ayV8XrFy5kpUrV1bb16VLlyoVt9RN6JoX1S2hXhCamK9uCfWCe+k56pZQLwhJK1a3hHpBUk6JuiXUG95qV/+8d5qISMNjBeqXxSJQJ7i6ulKfI0SmTJnCyJEjq+17nnRiAgICAgICApqJYLgK1DvMzc0xNzdXt4x6xe6dO9i6+QcyMtLx8PTio3kL8XmqeMKT/LRtCz/v2UVKcjKmZmb06dOP6TM+qJIRoaGxf9dmrgWcJSk+FolEFw9vX16d9C72Tq7KMaWlMn767ksunztBWVkpLfzbM+HdjzA1s/jziRsYN08d5Nap38lJTwXAytGFzi+/TpOWbVXGVVZWsnv1PKKDrjN8xlI8/TupQ26dEXZqLyGHt9G46yB8X56s0ldZWcmV75eQ+uAW7SbMw96nw5/M0jB52ceGl31U44qTckv46HA4ADpiEaNb2dHexRRtsYh7yQVsvZGoUYuSAI79so07V86RkhCHjq6Exl4+DBk7FVtH1Upq0Q/uceCn74gND0EsFuPo5s67S75E0sCvkaBI8aXJCIargEA959jRI6xZvYoFi5fi49OCHdu38vZbEzlw6BgWFlWNsSOHfmfdF2tZ+vFKWvj58TA2lkXzPwKRiA/nzFXDO6g5Qu/dou+gETT28EZeUcHuzV+zcu401mzci/SRN37bt59zO/AS7y/4BH0DQzZ/vZrPl37Isi9/VLP6msPI3IoeoyZhbutAZSUEXTzB3s8XMWnlt1g5uirHXTv2q8Y/NvyD7LhwYq8cw/iptFB/EHX+gMYvt07IKeHTM9HK1xVPPFl7tbU9Le2N+N+lhxSXyhnbxp7pXVxYfjJKHVJrjYj7t+n2wjBc3Jsir6jgwPZv+d+S91m0fie6UsU1IvrBPf63dCb9h73OK2/ORCzWIjE2EpGG5HLV9HRYmh7DKyDQ4Nm+dTNDh49kyMvDaNykCQsWL0UqlbL/t1+rHX/nzm1a+rXihYEv4eDgSMdOnen/wkDu3wuqY+U1z9yV/6N735dwcm2MS2MP3p61hIy0FGIiFOWMiwoLOHvsAK+/NYPmfm1o5NGUKR8sJjwkiIjQe2pWX3N4tOpAk5btMLd1xMLOkR4jJyCR6pEY+bisc0psJIGHf2Hgm7PUqLRuKJcVc/2ntfiNfBeJnmGV/pzEaCLO7afVqPeq2VtzqKisJLekXLkVyBQZDfR0xHRrZMbOW8mEphYSm13MxqsJeFgZ0NhCX82qa5Z3l3xBh14vYu/cCEc3d8a+t4Cs9FTioh4ox+z94St6DBxBv+FjsXduhK2jC60790JHQ8rlimpwq48IhquAQD2mrLSU0JBg2nfoqGwTi8W0b9+RoLu3q92nZUs/QkOCuRekMFQT4uO5dPE8Xbp2qxPNdUlRYQEAhkbGAESHh1JRXo5Pq8fFLBycXbG0tiU8pOEb7tUhl1cQfOUsZbISHJoo8teWyUo48PVK+o17F0NTzQ+7ufPLt9g29cfas2WVvvLSEm5sX0OLYVOQGpvVvbg6xNZIl3VDmrJmkCdTOjphoa+owOFqroe2lpjglMcLKJPzZGQUltLEUrMM16cpLioEQN9QcY3Iy8kiNjwYIxMzPpv9JrPHvsjn86YSGXJXnTIF/gZCqICAQD0mOyebioqKKiEBFhYWxMREV7vPCwNfIjsnm3GvvwpUUl5ezohXRjHpzecrctFQkMvlbP12LZ7NWuDkpiiBnJOdibaODgaGqpWATMzMycnOrG6aBktaXDRblkynvKwUiVSP4TOWYPUoju/kTxtw8Gim8TGtAAm3LpCbGEX3GZ9X239v/ybMXb2w92lfx8rqlqiMIr6/Ek9KvgxTPW2GNLdhfp/GzDscjqlUh7IKOUVlcpV9ckvKMdHTXDNALpezd9OXNG7qi4NLYwAyUhWVww7v/oGh46bh1Midq2eOsW7hdBb+7yes7Z3UKblG0PBIAcFwFRDQNK5fC+SH779j/sLF+Pj6EhcXx+pVK/huw9e89fY76pZXY/y4/lPiY6NY+vkmdUtRCxb2Tkxa+R2y4kIeBF7g929X89qCz8lOTSQ2+A6TVn6rbom1TlF2OkH7NtLp7WVoVfOYN/l+IOkRQfSctU4N6uqWoOTH3tT4HIUh+/ngprR1NqGsov5mkalNdn+3lqS4aGatevxdqHxULrtzvyF07K2o5OjUyJOwoBtcPnWIIWPfVovWmkTT49oFw1VAoB5jZmqGlpYWmZmq3sLMzEwsLS2r3efr/61j4KBBDB0+AgB3D0+Ki4v4eMkiJr/1NmJxw48Q+nH9p9y6eokla7/HwurxSmpTMwvKy8ooLMhX8brmZmdpVFYBAC1tHcxtFdXK7Nw8SIoO4/rx39CW6JKdlsSayYNVxv/65VKcvJrz+oLqPZMNkZyESGQFOZxd+76yrVIuJyM6mOhLh3Dr+AKFmSkcmjdKZb/AzZ9g2cibLtNW1bHiuqOoTE5KvgwbI13up+SjoyVGX0es4nU1eVQyWBPZ/d1a7l8PYOaqbzCztFa2m5grrgN2T2QiAbB1dCXrUZYOgfqNYLgKCNRjdCQSmno3I/DqFXr26g0oHn8FBl5h1OjXqt2npKQEkUjVONUSawHU6/y9z0NlZSWbv17N9YBzLFrzHdZ2qmVmG3k0RUtbm/u3r9GuSy8AkuJjyUhLwcP7z9OHaQKVlZVUlJXRddgbtOw+QKVv40eT6fPa27i30qzH5VbuLeg1e71K281dX2Jk7YhHr+FIDIxx69hfpf/06mn4DpmIbTPV1GGahq62GGtDCQHFZcRmFVNeIcfb1pAb8Yqyq7ZGulgaSIjMKFKz0pqlsrKSPd9/zp2r55m54mssbexV+i2s7TAxtyQ1UbUsampSHM1aa0aKtIbvmvhrBMNVQKCe8/ob41k4bw7NmjWnuY8vP23fSnFxMUNeHgrA/Lmzsba24b0ZHwDQrXsPtm/djFdTb3x8fYmPi+Pr/62ja/ceaGlpqfOt/Gt+/N+nBJw9xqyla9HT0ycnKwMAfQNDJLpS9A0M6dF/MNu/+wJDIxP09A3Y/M1nuHv74t7UR83qa46zuzfRuEVbjC2tKS0uIvjyGR6G3mX0nE8wNDWvdkGWsaU1ptZ2alBbe+hI9dGxU83PqS2RIjEwxvhRe3ULsvTMrDCwsK0TjXXFKD87bifmkVlYiqmeDkN9bJBXwtWHORSXyTkfnc2rrewplFVQXCbndX97ItILicrULMN193druH7hJFPmfYqunj65j2Lb9fQNkejqIhKJ6PPyGA7t2oSjaxMcG3lw9cwRUhMf8uacFWpWXzMIoQICAgJqpf+AF8jOyuKb9V+RkZGOp1dTvvluExaPQgVSkpMRP+FhnfzW24hEIr7+6kvS0lIxMzOnW/ceTHtvhrreQo1x8tAvACyb9ZZK+5RZi+ne9yUAxk6ZiVgk5vOPZ1NeWoqvfwcmvjunzrXWJoV5ORz89lMKcrLQ1TfA2smN0XM+oZFPa3VLE1AT5vo6TO3ojKGuFvmycsLTi1h2IpL8Rymxdt5MorLSjne7uKCjJeZecj5bryeqWXXNc+HoPgC+mK8azz92+nw69FKU5+416BXKS2X88sNXFBbk4ejahOlL12Fl51jnegX+PqLKhv7sUEBAzWhY4Zl/TGhi/rMH/Qe4l56jbgn1gpC0YnVLqBck5ZSoW0K9YVwrh2cP+g/Q06t24+333kmqsblGtLR/9qA6RvC4CggICAgICAhoCEKogICABiESidi3bx9DhgypsTk7rTpbY3M1ZMQaUi7x3/IwKk3dEuoFrdu4PHvQf4AWLppd9ODv8OL4z9QtoV5QfOUTdUto0AiGq4BAA8HKSML0Xo3p2NgCqY6YhOxilhx8QGhy1Uf0c1/wYHhrB9Ycj2DXtQQ1qK09rIwkvNujMR0amyvPw7JDYcrzMLmLK329rbEx1qWsQs6DlAK+ORdNcJJmhTLcWP0izpYGVdp/PBPJRz/dYt/s7nTyslbp23o2ig+336wriXXCGH8HXmujGpsYn13Mm7uDsDaSsPU1v2r3W3E8gkvRWXUhsc4JO7WXkMPbaNx1EL4vT1bpq6ys5Mr3S0h9cIt2E+Zh76MZK+mfxFBfwuI3+zKoazOszA25G57ErC9+52bo42vhwsl9GD+oDaZGelwJimX66v1EJWhGkRIhq4CAgIDaMZJq8+O4VtyIzWH6rrtkF5XhbK5HfklZlbE9PC3xcTAmLU+mBqW1i5FUm01jW3HzYTbv7Qkip7AMJ3M98oofn4e4rCI+Ox5BYk4xutpiRrdzYv3oFry8IZCcoqrnq6HS7+NTaD3xSNDL0ZhfZnXn4PV4Zdu281Gs3hesfF1UqpkB2bFZRcw7+LgWfcWjpRsZBaW8uuWWytgB3tYMa2nHjbicupRYZ2THhRN75RjG9q7V9kedP6DxpZU2zB2GdyNbJiz7meSMPEb38+PwV5No9ernJKXn8cFr3Zg6oiOTP95LbFIWi97sy+9fTsDv1S+QacB3RNNDBTTdMBeoJ+Tn5zNmzBgMDAyws7Pjiy++oHv37rz//vsAZGdnM3bsWMzMzNDX12fAgAFERESozPHrr7/SrFkzdHV1cXV1Ze3atSr9ycnJvPjii+jp6eHm5sbOnTtxdXXlyy+//FNd8fHxjBw5ElNTU8zNzRk8eDCxsbE1/O7/PeM6OpOaJ2Pp7w8ITsonKaeEq9HZJGSrLvywMpLwYX93FuwPoVwu/5PZGi5vdHAmNa+EZYfCCEnKJym3hMCYbBKfWABzPDiNa7GKtuiMIr48GYmhVBt366reyYZMZr6MtLwS5danhT0xqflcDktXjikurVAZU6ChKwkr5JVkF5cpt7xH71NeiUp7dnEZHd3MuBiVSUm55n0/ymXFXP9pLX4j30WiZ1ilPycxmohz+2k16j01qKsbpLraDOnenPlfHyHgTgzRCZms+OEUUQkZTH5Zkcf4nVc68emWMxy6GML9qBQmLduDnaUxg7p6q1l9zSCqwa0+IhiuAnXCzJkzCQgI4ODBg5w8eZKLFy9y69ZjT8i4ceO4ceMGBw8e5MqVK1RWVvLCCy9QVqbwkN28eZORI0cyatQo7t27x5IlS1i4cCFbtmxRzjF27FiSkpI4d+4cv/76K99//z1paX8eb1hWVka/fv0wMjLi4sWLBAQEYGhoSP/+/SktLa21c/FP6OphSUhSPp8Oa8bJmZ3YMdmfl/1Uc3KKgI8He7P9SjzR6ZqVm/EPurhbEJqcz6qh3hx/vyM/TWzNkJZ/nptUWyziZT978kvKCU8trEOldYuOlpjh7V3YeSlWpX1Ye2dC1w3m/LJ+zB/mg56kYefx/TMcTKT8NNaPH8e0YHavxlgZVi3/CtDEUp/GVgYcD02vtr+hc+eXb7Ft6o+1Z8sqfeWlJdzYvoYWw6ZUm9tWU9DWEqOtrUXJU57TElk5HVu44mpvjp2lMWeuRyr78gplXA+Jp11zIS67ISCECgjUOvn5+WzdupWdO3fSq5eimtHmzZuxt1ek2YiIiODgwYMEBATQsWNHAHbs2IGTkxP79+9nxIgRfP755/Tq1YuFCxcC4OHhQUhICJ999hnjxo3jwYMHnDp1iuvXr+Pv7w/Apk2bcHd3/1Nde/bsQS6Xs2nTJuWjlc2bN2Nqasq5c+fo27dvrZ2Tv4uDmZTh/vbsuJrAjwEP8bYzYlY/d8oqKjkUlALAuE7OVMgrNS6m9UkczPQY1tqBnYHxbA6Io5m9ER/0bUJZhZzD9x6Xa+zcxIIVL3sj1RGTUVDKtJ13yS3WnDCBpxnQyh4TfR12B8Qo234LjCMho5CUnBK8nUxYONyXJrZGjP/6shqV1jxhaQWsPRNNQk4x5gYSxvg78NkQb97eE0RxmapXtV9Ta+KyiglNLVCT2toj4dYFchOj6D6j+pK+9/ZvwtzVC3sfzaqe9jQFRaVcvfeQueN7ERabRmpWASP7tKBdc2eiEjKxtVB4otOyVD8DaVkF2FhU9VI3RDQ8UkAwXAVqn+joaMrKymjb9nGJRRMTEzw9PQEIDQ1FW1ubdu3aKfstLCzw9PQkNDRUOWbwYNXa6506deLLL7+koqKCsLAwtLW1adWqlbK/SZMmmJn9uWfh7t27REZGYmRkpNJeUlJCVFRUtfvIZDJkMtXYUXl5KWLt6j08NYVYJCIkKZ+vz0YDEJZSQBNrQ4a1tudQUApetoaMauvImI03alWHuhGLIDQ5n2/OKQy08NQCGlkZMLSVvYrheuNhNmM23cBUT4chfnasHOrN+M23yNagGNcnGdOlEafvpZD6RMjE9vPRyr9DE3NJzSnht9ndcbUyIDZdc7zPN+JylX/HZhUTllrA1tda0qWxBScePPasSrREdHe3YNdNzUu6X5SdTtC+jXR6exlaOlWvRcn3A0mPCKLnrHVqUFf3TFi6h+/mDyf69/mUl1dwJzyJn0/exc/rv5FHVlxvH/LXDILhKvCfpaCggNatW7Njx44qfVZWVtXus2rVKpYuXarSZtt9LPY9x9WGRCUZ+aXEZKgaGzEZhfT0Uuj0czbF3EDC4fcerxDWFouZ0acJr7Zz5KX/Xa1VfXVFRkEp0U/VVo/NKFKehz8oKZOTkF1MQnYx95Py+PXttgxuaceWy6r1yTUBRwt9unpbM379X3tSb0UrVky7WRtqlOH6NIWlFSTmlmBvIlVp79zYAl1tMafDMtSkrPbISYhEVpDD2bXvK9sq5XIyooOJvnQIt44vUJiZwqF5o1T2C9z8CZaNvOkybVUdK65dYhKz6Dv1e/SlOhgbSEnJzGf7x6OJScwiJVPhabU2NyQl83GmEWtzQ4LCk9UlWeBvIBiuArVOo0aN0NHR4fr16zg7OwOQm5tLeHg4Xbt2pWnTppSXlxMYGKgMFcjMzCQsLAxvb0WwfNOmTQkICFCZNyAgAA8PD7S0tPD09KS8vJzbt2/TurWi7GVkZCTZ2dl/qqtVq1bs2bMHa2trjI2Nn+u9zJ07l5kzZ6q0dVt75flOxL/gbkIuLhb6Km3O5vok5yo8bEfupXAtRvW9rn+1BUfupXDwruZcjO/G5+JirqfS5myuR0ruX1cnEotE6GhpZkj/6M5uZOTJOBn01//PzZ1NAUh9xrlq6Ei1xdgZSzldpGqg9vOyIjA2h1wNXKBm5d6CXrPXq7Td3PUlRtaOePQajsTAGLeO/VX6T6+ehu+Qidg2a4umUlRSRlFJGaZGevRu58H8r48Sm5RFckYePfybEBSh+M4Y6evSxtuJjb9pxg2+ECogIPAvMTIy4o033uDDDz/E3Nwca2trFi9ejFgsRiQS4e7uzuDBg5k8eTLfffcdRkZGfPTRRzg4OCjDAz744APatGnDxx9/zCuvvMKVK1dYv34933zzDQBeXl707t2bN998kw0bNqCjo8MHH3yAnp7en6YGGTNmDJ999hmDBw9m2bJlODo68vDhQ3777Tdmz56No2PVutW6urro6uqqtNV2mADAjqvxbB7fivGdXDgZkkZzByOGtrJnxeEwAHKLy8ktVv1BLpfLySgo5WGm5pTe3HUtgR/e8GNcR2dOhabTzN6Il/3sWXlEcR6kOmImdHLhQngmGQUyTPV1GOHvgJWRLqdDNa8wgEgEozq5sudyLBXyx9W7Xa0MGNrehVNByWQXyPB2MuXjUS25HJZGSELuX8zY8JjUwZnA2GxSC2RY6Et4rY0j8spKzkc8zslpZ6xLc3sjFj36vmgaOlJ9dOxUFxZpS6RIDIwxftRe3YIsPTMrDCxs60RjXdK7nTsikYjwh+k0drRg5bQXCH+YzrZDilCqr/cEMGdcTyLjM4hNzmLx5L4kZ+Rx8EKImpXXDCIhVEBA4N/z+eefM2XKFAYOHIixsTGzZ88mPj4eqVTxOG/z5s289957DBw4kNLSUrp27cqRI0fQ0dEBFN7Rn3/+mUWLFvHxxx9jZ2fHsmXLGDdunPIY27ZtY+LEiXTt2hVbW1tWrVpFcHCw8hhPo6+vz4ULF5gzZw5Dhw4lPz8fBwcHevXq9dwe2LoiJDmfWXvvM61nIyZ3dSEpp4S1JyI4ej/12TtrECHJ+Xz4SzDv9HBjUhdXknKK+fxkJMeCFUapXA6uFvq8ONwWUz0dcovLCEnO581tt6uEGGgC3bxtcLI0YOfFGJX20nI5Xb2tebOPO/q62iRlFXHoZgKf/64ZP8xPYmkgYU6fJhhLtcktLic4OZ8ZvwWreFb7NrUio6CUW/GaZbQLVI+JoZRlU/rjYG1CVl4RB87dZ/G3xymvUCzWW/vTefT1JKz/aCimhlIuB8UyaMZmjcjh+l9AVFlZWfnsYQICNUthYSEODg6sXbuWiRMn1soxEhIScHJy4tSpU8psBrVB64+Fkq8glHz9A6HkqwKh5KsCoeTrY9Z9/KO6JdQLarvk65HgmrsGvdDM+tmD6hjB4ypQJ9y+fZsHDx7Qtm1bcnNzWbZsGUCVTAH/hjNnzlBQUICPjw/JycnMnj0bV1dXunbtWmPHEBAQEBAQqM8IWQUEBGqINWvWEBYWhkQioXXr1ly8eBFLS8sam7+srIx58+YRHR2NkZERHTt2ZMeOHcpwAwEBAQEBAYGGjWC4CtQJfn5+3Lx5s1aP0a9fP/r161erx6iOkIO/1/kx6yPm/l3ULaFekJ/wUN0S6gUPbU3VLaFeYGem/+xB/xXkFepW8J9AyCogICBQLzDU12XxlAEM6t4cKzMj7oYnMGvtfm6GxAMwuIcPk4Z2xM/LEQtTA9qNWUNQeJKaVdcsV5f3xcnCoEr7lvPRzN99l09fbUlnLytsTPQokpVzIzqLFfvuE6VhlZLEYhELXu/I6F7e2JgZkJxZyPaT9/lkh2pqNk8nc5ZP6kYXXye0tUQ8eJjJ6GUHiE/P/5OZGybWxrp80M+dLp6WSHW0iMssYv6vwQQn5gEQsrL6Knhrjobz48XYOlRaewxubs3g5jYqbcl5Jcw/EgEoyh+P8rOjrbMJ2mIR91MK+OlGEnkyzVuQZKivy+K3+jGoW3OszAy5G57IrM8PcDP0cVXBhW/2Zfzgdpga6nElKJbpq38jKl4zcvwKhquAgEC9YMOCkXg3tmPC4p0kp+cxekBrDn89hVYjV5OUnou+VMLluzH8euoOGxa8om65tcILn5xD64lFYF72xux+rzOHHlVDCorL4bdr8SRmFWNqoMMHA5uya3on2i84jlyDlqF+MLItkwe2ZPJnRwl5mEFrD1u++2AAeYUyvtl/CwA3O1NOf/EqW4/dY/m2APKKSvF2saCkTLO8XsZSbXa81ZZr0Vm8teUWWYVluFjok/dEid+uK8+p7NPFw5KPhzbjhIZl5UjIKWHNuccZJuRPfOhH+9nha2/ENwFxFJdVMKa1A+90dmbV6ejqpmrQbJg3HO/GtkxYsovkjDxG92/F4fVv0mrUGpLS8/jg9e5MHdmZycv2EJuUxaK3+vH7ukn4jVqjEZkFhHRYAgICakeqq8OQHr6MmPUjAbcVPzQrNh7nhS7eTB7WkaXfHmXXUUUohrOd5q5iziooVXk9rZ8tMWkFXIlQeEp2XIpV9iVkweqDIZxa0AsnCwMeZmhOtaj23g4cuhLJsWuKz0Jcah4juzfF39NOOWbp+M4cvxbN/E3nlW0xyTl1LbXWmdjNjZTcEub/GqxsS8xWzV2c8dTnpqe3NddiskjI1pwcxwDyykryqimwoKcjpksjM767Es+DNMX34MfABFa+6EEjCz2iNSjXs1RXmyE9fBgxewsBdxRG/IpNJxXXyqEdWPrdcd4Z1YVPN5/m0AXFZ2bSkt08PLqIQd2asffkXXXKF3gONLOUjICAhqGtJUZbW4uSp7wBJbIyOrZ0U5Mq9aKjJWJoWyf2XKk+plRPosUrHVx4mFFIUrZm5XC9GpJIj5YuNHFQ3KT4NLKiQ3MHTlxXGLIiEfRv25iIxGwOrhzOw5+ncuGrMbzUsYk6ZdcKPZtacT8hjy9G+3JxXnd+ndae4f5/XpPewlBCV09Lfr2RWIcq6wYbI10+H+zFpwM9mdzeCXN9xcJUFzM9tLXEhDwRMpOSLyOjsJTGFpoVg6utpaW4VsqquVa2cMPV3hw7S2POXItQ9uUVlnA9OI52PpqRwk0sqrmtPiJ4XAUEGgAFRTKuBsUwd2IfwmJSSc3KZ2S/VrTzcSUqQTPisv4u/VvYY6ynw89X4lTa3+jqxvyXm2Mg1SYyJZ/R6wIoq9CgOAFgzZ5AjPV1ufvDRCrkcrTEYhZvucjuM6EAWJsaYKQvYdYrbVm65RILNl2gbxtXdi8aQr8Pd3PpXsIzjtBwcDTTY1Q7R7YGPOT7czE0dzRm3ktelFVUcuB21RjvwX72FMkqOFmDuS7rA9GZRfwQGE9KXikmetoMbm7NR70asehoBCZ62pRVyCkuk6vsk1dSjomeZmVdUVwrY5k7oTdhsWmKa2VfP9o1dyEqIQNbCyMA0rJU47zTsgqwMTdSh+QaRwgVEBAQqBdMWLST7xaNIvroEsrLK7gTlsjPJ27j51W1NO1/gVGdXDgbnEpqbolK+2/X4rkQmoa1iZQpfdz5dnIbhnx2AVm5/E9mangM7+bFqF5NGffJIUJiM/BtbM1nb/ckObOAHSeDlZ6SQ5cj+d9vihCSoOg02nk7MHlgS40yXMUiEfcT8/jyRCQAocn5uNsY8ko7x2oN16H+Dhy6m0ypBn0eAO4lP/amJuQqDNnPXvKijbMJpRWa9V6fq5YgawAAgipJREFUxYQlu/luwQiiDy984lp5Bz+vP/fECzQcBMNVQKCBEJOYSd+3vkZfKsHYQJeUzHy2r3ydmMTMZ++sYTiY69HFy5pJ3wVW6csvKSe/pJyY9EJuxWQRsnYg/Vvac+CG5hhrKyd3Y83ua+w99wCA4NgMnG2M+XBUO3acDCYjr5iy8gpC41Q/G2FxmXRsrlk3Oun5MqLSVLNGRKUX0qeZTZWxrV1NaWRlwAe7ND+OsbhMTmq+DGtDCcEpBehoidHTEat4XRVlcsv+YpaGSUxiJn3f/hZ9qQ7GBlLFtXL5GGKSskjJVHharc2NlH8rXhsSFKEZWVg0PauAEOMqINDAKCopJSUzH1MjPXq39+LQhfvqllTnvNLBhYx8Gafvp/zlOJFIhEgEutqadanT09VB/lS17gp5JeJHv1hl5XJuhqXg4WiuMsbd0Zy41Nw601kX3IrLwc1KNUWaq4UBSTklVcYObe3A/YRcwlI0Kz1adehqi7EylJBbXM7D7GLKK+R42xgq+22NJFgaSIjK1Kz47ycpKil74lrpyaELwcQmZZGckUePNo/jvY0MdGnTzJnAe5qRg1lUg//qI4LHVUCggdC7vScikYjwh2k0drRk5XsvER6bxraD1wAwM9bHydYUO0sTADxcFDWmUzPzSc3UnLydIpHCcN17NY6KJ9L9OFvqM6i1I+dD08jMl2Fvpsc7/TwoKZVzOvivDdyGxpGrUcwZ3Z74tDxCHmbQsokN04f6s+34PeWYL365zvZ5L3HpXgLn78bR19+NF9o3pt+s3WpUXvNsu/SQHVPa8mY3N47dS8HHyYQRbR1Zsi9YZZyBrhb9fGz57EiYmpTWLiNb2nInMZ/MolJMpToM8bGmshIC43IoLpNzMTqbV/zsKCyteJQOy57IjEKNyijwB73beTy+VjpZsvLdgYQ/TGPb79cB+Hr3ReaM70VkfAaxSVksfqsfyRl5HDwf/IyZBeoDguEqINBAMDGUsuydF3GwNiUrr4gDZ4JY/M0Ryh/Fr73YtRkbF49Wjt++ciwAy78/zoqNx9WiuTbo4mWNo4U+ey6rekdkZXLaNrFgUs/GmOhLyMgr4WpkJoPXnCczv/RPZmuYzPz6FIvf6My6d3tjZapPcmYhPxy5y8qfLivHHAyI4N2vTvDhqPasndqT8IRsRi87wOVgzVpNfz8xj+k/3WFGP3fe7tmIhOxiPjn0gEN3VW9WXvC1RQQcvqtZNzF/YKanw5SOThhItMiXVRCRXsjyU1HkyxR5e3fdTqYSmNrJGR0tMfeT89l+UzMejT+NiaGUZVNfwMHaRHGtPHuPxRuOKa+Va7efQ19Pwvq5wzE1lHL5biyD3tukETlcof5mA6gpRJWVlZq13FZAoI7RazNT3RLqBULJVwVZUZHqllAvcPNvoW4J9YL2vnbPHvQfYdcX29QtoV5QHPhZrc5/MTy7xubq4lH/8oJrVuCXgICAgICAgICAxiKECggI/FvMBI8KgJmF4bMH/QfIilK3gvpBhYblzv2nlGtSrWGBBoGQVeApxo0bx5AhQ2pBinoQiUTs379f3TLUhqurK19++aXy9X/9fAgICAgICDRkRDW41Uf+tsd13bp1CGGxmktycjJmZvUvpuW/jlgsYsHrHRndyxsbMwOSMwvZfvI+n+y4ojLO08mc5ZO60cXXCW0tEQ8eZjJ62QHi0zUnq4C1kS4z+7nT2cMCqY4WcZlFLPwthOCkPOWYRlYGzOjrjr+bKVpiMdFpBby/K4iU3KopkhoiwufhMdbGunw4wIMunpboSbR4mFHEvL33uZ+o+DzoS7T4YIAHvZtZY6qvQ0JWMdsDHrI7UHPy+gK87GPDyz6quWuTckv46HA4ADpiEaNb2dHexRRtsYh7yQVsvZFIXolmLEh6EkN9XRa/1Y9B3ZpjZWbI3fBEZn1+gJuhj//PF77Zl/GD22FqqMf/27vv8CiqLoDDv03vPSG9ACGhBEgooTeB0EU6RkCQooAoiCIgVYoFRBQLitIEIihSpUvvNQQISUjvvZdN2++PkQ0LqPgZsmS5r0+eJzszO3tyGHfP3rnl/M0Ypn2yk8h4zViFUEvDm1z/deFqbm7+NOIQnhH29vZP9fwVFRXIZDK0tET36n/jnWGtmdCvORM+PcCd2AxaNLBn7Tu9ySuU8/WuawB4OFhwbNXLbDwYwpJNZ8krKqWRmzUlZRVqjr76mBnosHliKy5FZ/H6xutkF5XiZm1EXknVJOouVoZsmtCSnVeT+OqPSArl5dSzM6G0XHPyIK4HiZmhDtve8OdiVBYTfrxGdmEpbjZGKpPqv9/Pizb1rHk36CaJ2cW097RhwcCGpOXJ+SM0XY3RV7+EnBI+/iNK+bjigUaml1s40tzRlC/PxFJcWsnoVo5M6+jGkiOa17flmzlDaFTPnnELt5GckcfIXn7sXzMRvxErSErP451RXZg8rAMTFv9MTFIW8ycFsHf1eHxHrNCYmQU02X/qKlBZWcny5cvx8PDA0NCQZs2a8csvvyiPPXHiBDKZjGPHjtGyZUuMjIxo164dYWFV8+gFBwfTtWtXTE1NMTMzo0WLFly5ckW5/8yZM3Ts2BFDQ0NcXFyYNm0ahYWFyv3u7u4sW7aMcePGYWpqiqurK999951yf2lpKVOnTsXBwQEDAwPc3NxYvny5yt+UkZHBSy+9hJGREZ6enuzZs0e5r6Kigtdee035N3p5ebF69erH5mTFihU4ODhgbW3NlClTKCurevP8pzgBQkJC6NatG4aGhlhbWzNx4kQKCgr+1ev8nbS0NPr374+hoSEeHh5s2bLlkWMe7CrQrl07Zs2apbI/PT0dXV1dTp06BYBcLmfmzJk4OTlhbGyMv78/J06cUB6/YcMGLCws2LNnD40aNUJfX5+4uDiSk5Pp27evMpatW7c+0m0hJyeH8ePHY2tri5mZGd26dSM4uGrFm4ULF9K8eXM2b96Mu7s75ubmjBgxgvz8qtakyspKPvnkE+rXr4++vj6urq4sXbpUuT8+Pp5hw4ZhYWGBlZUVL774IjExMU+Uz5rUppET+87f4+ClKOJS8/jtdDjHrsbQ0quqf+2isR04dCmKuetOEhyZRnRyDvsvRJKeozkTjI/r5E5Kbgnzdt7hVmIeidklnLuXRXxW1VyU07rX53R4Bp8diuBucj7xWcWcuJtOVqHmrBAkrgfJhM4epOSWMGfHLUIScknILuZsRKbK9eDrZsGua4lcisomMbuE7ZcSuJucT1MXzWuEqVAoyC0pV/4U/DkVlqGuFp3rWrL1WjKhqYXEZBfz/YUEGtgaU8/aSM1RVy8DfR0GdvVh7pr9nL0RTVRCJkvXHSEyIZMJg9oCMGVERz5ef4x9p25z614y4xcG4WBjxoDOjdUcffXQ9K4C/6nZa/ny5WzatIlvv/2W27dvM336dF555RVOnjypctzcuXNZuXIlV65cQUdHh3Hjxin3BQYG4uzszOXLl7l69Srvv/8+urq6AERGRtKrVy8GDx7MzZs3+fnnnzlz5gxTp05VOf/KlStp2bIl169fZ/LkybzxxhvK4viLL75gz549bN++nbCwMLZs2YK7u7vK8xctWsSwYcO4efMmffr0ITAwkKysLEAqfJydndmxYwd37txh/vz5zJkzh+3bt6uc4/jx40RGRnL8+HE2btzIhg0b2LBhwxPHWVhYSEBAAJaWlly+fJkdO3Zw9OjRR/7WJ3mdv/Lqq68SHx/P8ePH+eWXX/j6669JS0v7y+MDAwMJCgpS6Rry888/4+joSMeO0tRHU6dO5fz58wQFBXHz5k2GDh1Kr169iIiIUD6nqKiIjz/+mHXr1nH79m3s7OwYPXo0SUlJnDhxgl9//ZXvvvvukViGDh1KWloaBw4c4OrVq/j5+fHCCy8o/21AukZ27drFvn372LdvHydPnuSjjz5S7p89ezYfffQR8+bN486dO2zdupU6daTbaWVlZQQEBGBqasrp06c5e/YsJiYm9OrVi9LSZ2vezwt3Euna3I36TlI3Dp+6trRt4sThy1LrikwGvVrXIyIxmz3LhhC7fTKnvgikf7v6f3faWqerty23E/NYOaIpJ9/vzI7J/gxuWbX+uEwGnbxsiMkoYu0YX06+35mtk1rTraGtGqOufuJ6kHRrZMethFxWBzbj3Lwu/DatLUNbqy5pez02h24N7bAz0wfAv64VHrbGnInQvKWS7U31WT2wISsGePF6OxesjaTPUncrQ3S0tbidUvWlPjlPTkZhKfVtNKtw1dHWRkdHmxK5astpibyMds08cHe0wsHGjD8uVX1G5RWWcPl2HP4+bjUd7tOh4ZXr/z2rgFwuZ9myZRw9epS2baVvMXXr1uXMmTOsXbuWzp07K49dunSp8vH7779P3759KSkpwcDAgLi4ON599128vb0B8PT0VD5v+fLlBAYG8vbbbyv3ffHFF3Tu3JlvvvkGAwMDAPr06cPkyZMBmDVrFqtWreL48eN4eXkRFxeHp6cnHTp0QCaT4eb26IX56quvMnKkNHH7smXL+OKLL7h06RK9evVCV1eXRYsWKY/18PDg/PnzbN++nWHDhim3W1pasmbNGrS1tfH29qZv374cO3aMCRMmKI/5uzi3bt1KSUkJmzZtwthYWr5wzZo19O/fn48//lhZbD3J6zxOeHg4Bw4c4NKlS7Rq1QqAH374gYYNG/7lc4YNG8bbb7+tbPUG2Lp1KyNHjkQmkxEXF8f69euJi4vD0dERgJkzZ3Lw4EHWr1/PsmXLAKlA/Prrr2nWTJrX8e7duxw9epTLly/TsmVLANatW6fyb3/mzBkuXbpEWloa+vrSB86KFSvYtWsXv/zyCxMnTgSkLxYbNmzA1NQUgFGjRnHs2DGWLl1Kfn4+q1evZs2aNYwZMwaAevXq0aFDB0AqwisrK1m3bh2yP/sErV+/HgsLC06cOEHPnj0fyYlcLkcul6tsU1SWI9N6uhN0rPj5ImZG+gT/8BoVlZVoa2mxYMNpgv4IBcDOwhhTIz1mDm/Nog1n+GDdKXq2cido/kAC3g3iTIhm9OdztjRkeGtnNp2L4/uT0TRxMmN2Xy/KKirZcz0ZK2M9jPV1eK2TB18evcdnhyLo0MCGz0c2Y9yPV7kSU33zG6qTuB4kLlaGjGzjwvrTsXx7PAofZ3M+GOBNWXklu65Jk+t/uDuUDwc35vTcLpRVVKJQwAe/3uZKtGZcC/dFZhTx3fl4UvLlWBjqMLBJHeb2qMec/eFYGOhSVlFJUVmlynNyS8oxN9SsyYUKiuRcuBnD7HHdCYtJIzUrn2E9ffFv4kZkQgb21tJnRVqWaj/vtKwC6liZqiNk4V/6v6/Ye/fuUVRURI8ePVS2l5aW4uvrq7KtadOmyt8dHKRbWWlpabi6ujJjxgzGjx/P5s2b6d69O0OHDqVevXqA1I3g5s2bKre0FQoFlZWVREdHK4uuB88vk8mwt7dXtt69+uqr9OjRAy8vL3r16kW/fv0eKUgefL6xsTFmZmYqrX9fffUVP/74I3FxcRQXF1NaWkrz5s1VztG4cWO0tbVV/s6QkBCVY/4uztDQUJo1a6YsWgHat29PZWUlYWFhysL1SV7ncUJDQ9HR0aFFixbKbd7e3lhYWPzlc2xtbenZsydbtmyhY8eOREdHc/78edauXQtIXRsqKipo0KCByvPkcjnW1tbKx3p6eip/e1hYGDo6Ovj5+Sm31a9fX2VQWHBwMAUFBSrnASguLiYysqpPlru7u7JoBSkfD+ZULpfzwgsvPPbvCw4O5t69eyrPBygpKVF5jQctX75c5YsMgHbd7ujWe7TIrU5DOnsz4oWGvPrRPu7EZNC0nh2fvtGN5MwCthy5rVwpZd+5e3y58yoAN6PS8G/kxIR+zTWmUNGSybidlMfqI9Ik/3eT8/GsY8KwVs7suZ6sHJRwPDSNzefiAAhLKaC5iwXDWjtrTOEqrgeJTCbjVmIuqw5JrWehSfl42pswoo2LsnAd1d6N5q4WvL7hGknZxbT0sPqzj2sJ5+9l/d3pa5WbyVWFWHyOVMh+9mJDWruaU/acTU02bmEQaz8YStT+eZSXV3AjLJHth2/g6+30z0/WALJntam0mvzfhev9vpf79+/HyUn1YrjfQnbf/Vv/gLJlq7JS+ua3cOFCXn75Zfbv38+BAwdYsGABQUFBvPTSSxQUFDBp0iSmTZv2yOu7uro+9vz3X+P++f38/IiOjubAgQMcPXqUYcOG0b17d5W+uH/3/KCgIGbOnMnKlStp27YtpqamfPrpp1y8ePEv/8aHz/Fvjvkn1XGOfyMwMJBp06bx5ZdfsnXrVnx8fPDx8QGka0BbW5urV6+qFNMAJiZVc3oaGhoq/92fVEFBAQ4ODir9Ze97sNj+u3wYGhr+42u0aNHisX19bW0ff2t59uzZzJihulKW3aCv/vZ1qsOyCZ1ZEXSJHSfuAnA7JgPXOma8O8KfLUduk5FXTFl5BaFxqrc/w+IyadfE+XGnrJXSC+REphWqbItKL6R7YzsAsotKKauoJDL94WMK8HPTnNkyxPUgSc+XE5n60L91WiEBTaQv+vo6WkwP8GTq5uucvCuNGA9LKaChoymvdfLQqML1YUVllaTky6ljqs+tlHx0tbUw0tVSaXU1N9Aht1jzBiNFJ2bS841vMTLQxczYgJTMfDYvCSQ6KYuUTKnAt7MyVf4uPTbhZoRmLIGr4ZMK/P+F64MDbR7sFvD/aNCgAQ0aNGD69OmMHDmS9evX89JLL+Hn58edO3eoX/+/9csyMzNj+PDhDB8+nCFDhtCrVy+ysrKwsrL6x+eePXuWdu3aKW/xA3/ZGvdfNGzYkA0bNlBYWKhsdT179ixaWlp4eXn95/N7e3tTXl7O1atXlV0FwsLCyMnJ+dvnvfjii0ycOJGDBw+ydetWRo8erdzn6+tLRUUFaWlpyq4ET8LLy4vy8nKuX7+ubAG+d+8e2dlVrWF+fn6kpKSgo6PzSJ/kJ+Xp6YmhoSHHjh1j/Pjxj+z38/Pj559/xs7ODjMzsyc6p76+/iNfzJ52NwEAQ31dKh+ahq6iUqFsYSwrr+RqWAoNnFWvaU9nK+JSc596fDXlemwO7g/1yXOzNiI5R5rmqrxCwe3EPDweOsbdxpiknGI0hbgeJNdicvCwNVbZ5m5jROKf/9Y62jL0dLR4eAbHCoVC4z/c9XW0sDPR42xxGTFZxZRXVNLI3oQr8dI0Yfam+tgY63EvQ3MG6z2sqKSMopIyLEwN6d7Gi7lr9hOTlEVyRh5dW9VXFqqmxvq0auzK9zvP/8MZhWfB/z04y9TUlJkzZzJ9+nQ2btxIZGQk165d48svv2Tjxo1PdI7i4mKmTp3KiRMniI2N5ezZs1y+fFnZBWDWrFmcO3eOqVOncuPGDSIiIti9e/cjA5b+zmeffca2bdu4e/cu4eHh7NixA3t7+7+9Rf4gT09Prly5wqFDhwgPD2fevHlcvnz5iV//SQUGBmJgYMCYMWO4desWx48f580332TUqFHKbgL/xf2uEpMmTeLixYtcvXqV8ePH/2OrpLGxMQMHDmTevHmEhoYq+wKD9IUjMDCQ0aNHs3PnTqKjo7l06RLLly9n//79f3lOb29vunfvzsSJE7l06RLXr19n4sSJKi2z3bt3p23btgwcOJDDhw8TExPDuXPnmDt3rsqsE3/HwMCAWbNm8d5777Fp0yYiIyO5cOECP/zwAyDl3MbGhhdffJHTp08THR3NiRMnmDZtGgkJz9at1N8vRDJrZBt6ta6Lax0zBrT3ZNqgluw5WzXAYNUvlxnS2ZuxvZtS19GC1wf40qdNPb7be0N9gVezzefiaOpizoTO7rhYGdKnqT1DWjmz7WK88pj1p2Po1cSewS2dpD6Q/i509rIh6NKz9W/6X4jrQbLxTAzNXM2Z1NUDV2sj+jV3YJi/M1vPSddDobyCi5FZvNunAa3rWuJsachLLRwZ6OfI0dt/PTC1Nhrh64CXnTE2xrrUtzHirY5uVCrgQmwOxWWVnIzK5mU/RxraGeNuaciENs5EpBcSmal5hWt3/wb0aOOFm4Ml3Vp7cvDr1wmPTWPTXumz+6ug08wa+wJ9OzaicT17flgwguSMPPacvK3myKuHho/N+m9Lvn744YfY2tqyfPlyoqKisLCwwM/Pjzlz5jzR87W1tcnMzGT06NGkpqZiY2PDoEGDlH0ImzZtysmTJ5k7dy4dO3ZEoVBQr149hg8f/sQxmpqa8sknnxAREYG2tjatWrXi999/f+J5RCdNmsT169cZPnw4MpmMkSNHMnnyZA4cOPDEMTwJIyMjDh06xFtvvUWrVq0wMjJi8ODBfPbZZ9X2GuvXr2f8+PF07tyZOnXqsGTJEubNm/ePzwsMDKRPnz506tRJpYvG/XMuWbKEd955h8TERGxsbGjTpg39+vX723Nu2rSJ1157jU6dOmFvb8/y5cu5ffu2csCdTCbj999/Z+7cuYwdO5b09HTs7e3p1KnTvyrk582bh46ODvPnzycpKQkHBwdef/11QMr5qVOnmDVrFoMGDSI/Px8nJydeeOGFJ26BrSkzvjrKgjEdWP1md2wtjEjOLOSH34NZ9tM55TF7zkbw5heHeXdEG1ZO7kZ4QjYjF+/m3O1ENUZevW4l5vH21mDe6lGf17vUJTG7mI9/D2N/cIrymGOh6SzeE8r4Th7M7utFTEYR07fd5HpsjvoCr2biepCEJOQxddMNZvTyZMoL9UjILmbZ3jD23khWHjNjazAzejdgxYimmBvpkpRdzKpDEWy7EP83Z659rIx0mdzOFRN9bfLl5YSnF7H48D3y/5wSa+vVJBQKB97s6IauthYhyflsvKw518KDzE0MWDy5D0525mTlFbH7eAgLvjlIeYXUTWLl5hMYGeqxZvYQLEwMOBccw4C31mnOHK7PasVZTWSKf7kM1siRI9HW1uann356WjEJz6GEhARcXFw4evToXw6melYZ9vxU3SE8E+q1bq7uEJ4JkZduqDuEZ4Krb9N/Pug54N/M4Z8Pek7sWL1Z3SE8E4ovPt3PjMvR1dcdqJXHszff8RO3uJaXlxMeHs758+eZNGnS04xJeA788ccfFBQU4OPjQ3JyMu+99x7u7u506tRJ3aEJgiAIQq0lZhX4061bt2jXrh1du3ZV3moVnh2nT5+md+/ef7n/wRW4ngVlZWXMmTOHqKgoTE1NadeuHVu2bHlkloBaITv5n495DqQkuKg7BEF45ujriOWthZql6QMPn7hwbd68OUVFmteJW1O0bNmSGzduqDuMJxYQEEBAQIC6w6hVTIz0WfB6bwZ0aYKtpSnB4QnMXLmLq3ekvnovdvVh/KB2+Ho7Y21hjH/gCm6Ga8b0LvddW9EfVxvjR7b/cCyCWZul+Upb1rNm7uCm+NWzprJSwa24bIauOElJWUVNh/vUaGnJ+GBUO0a+0Ig6lsYkZxay+cgtPtqiOiray8WKJeM707GpCzraMu7GZjJy8W7i0/P/4sy1j52ZPu/2bkBHLxsM9bSJzShizo5b3EqURs8b6WnzTu8GdG9sh4WRLglZxWw+G0vQRc0ZrPewXt42DG5qz9HwDH6+IfX/tjXWY2gze+rbGKGjLeN2SgFbryUp+8BqEhMjfRZMCmBA5ybYWpoQHJ7IzM92czW06t983sSejH3RHwsTQ87fjGHaJzuJjM9QY9TVR1116/Lly9m5cyd3797F0NCQdu3a8fHHH6vMjFRSUsI777xDUFAQcrmcgIAAvv766381dkWzlsx4jhkaGv7nacOEZ9s3HwyjUT0Hxi3YSnJ6HiN7t2D/V6/jN+wTktJzMTLQ41xwNL8evcE3Hzz5AMbapMeiw2hrVb0tezuZs/O9ruy5LBXvLetZs/2dzny+P5T3f7pKRaWCxi4Wj0wdVdu9M6w1E/o1Z8KnB7gTm0GLBvasfac3eYVyvt51DQAPBwuOrXqZjQdDWLLpLHlFpTRys9aoAt7MUIdtb/hzMSqLCT9eI7uwFDcbI3KLy5THvN/Pizb1rHk36CaJ2cW097T5cwECOX+Epqsx+qfD3dKQznWtiH9g+jc9bRlvd3YnIaeYlSejAXixSR3e7ODG8mNRaNb/HfDNnCE0qmfPuIXbSM7IY2QvP/avmYjfiBUkpefxzqguTB7WgQmLfyYmKYv5kwLYu3o8viNWaM4ALTU4efIkU6ZMoVWrVpSXlzNnzhx69uzJnTt3lNN8Tp8+nf3797Njxw7Mzc2ZOnUqgwYN4uzZs0/8OqJwFYRawEBfl4FdmzJ05o+cvS6tR7/0+0P06diICYPbsejbA2w7ILU4ujpozkT7D8vMV11ud1rfhkSl5nP2rjS10ZKXffnuaARf7A9VHnMvRXNaF+9r08iJfefvcfCSdC3EpeYxrEtDWnpVDQRaNLYDhy5FMXfdSeW26OScmg71qZrQ2YOU3BLm7Lil3JaQrTpfr6+bBbuuJXIpSponevulBIb7O9PUxVzjCld9HS3Gt3Fm05VE+jayU26vb2OMjZEuHx6+R0m5NLJ+/aUEPh/YEG87Y0IfWtSjNjPQ12FgVx+GvreBszekIn3puiPSe+Wgtixae4gpIzry8fpj7DslTX81fmEQsQfmM6BzY3YcCVZn+NVDTU2uBw8eVHm8YcMG7OzsuHr1Kp06dSI3N5cffviBrVu30q1bN0Camahhw4ZcuHCBNm3aPNHriM43glAL6GhroaOjTclDrQEl8jLaNfdQU1TqpautxdC27mw9LX042Zjq07KeDRl5Jfw+tzt3Vg9kz/vd8Pe0UXOk1e/CnUS6NnejvpP0JcWnri1tmzhx+LJUyMpk0Kt1PSISs9mzbAix2ydz6otA+rfTrLsy3RrZcSshl9WBzTg3rwu/TWvL0NaqK4Ndj82hW0M77MykhUP861rhYWvMmYjMx52yVnvZz4GbyfmPFKI6WjIUQHllVdtqWYUChQLq2z7a9aY209HWlt4r5Y95r2zmgbujFQ42ZvxxqWrO47zCEi7fjsPfx62mw30qZNX4n1wuJy8vT+VHLpf/cxBAbq40u8H9xZ6uXr1KWVkZ3bt3Vx7j7e2Nq6sr588/+eIPonAVhFqgoEjOhZvRzH6tBw42ZmhpyRjRuwX+Pu7Y2zxbc87WlD5+Tpgb6RJ0RirW3OykZYbfG9iEzScjGb7yBDdjs9n5Xlfq1jH5u1PVOit+vsiOE3cJ/uE18n6fwYWvx7Dmt6sE/SG1NNtZGGNqpMfM4a05ciWa/u//wp6zEQTNH0gHH81Z8tXFypCRbVyIySjitR+usu1CPB8M8Gagn6PymA93h3IvrYDTc7twa1kP1r3WgkW7QrkSnf03Z659WrmY42phyM6bqY/si8oqQl5eyeCmddDTlqGnLWNoM3u0tWSYG2jWjVfpvTKG2eO6V71X9vLDv4kb9jam2FubApCWpXonJi2rgDpWpuoI+Zm2fPlyzM3NVX6WL1/+j8+rrKzk7bffpn379jRp0gSAlJQU9PT0HlkAqk6dOqSkpDzmLI+nWVesIGiwcfO3snb+CKIOLKS8vIIbYYlsP3wdX2/NKUT+jcBOdTkWkkzKn8u93u/6uvF4JNvOSK2wIXHX6dioDi93rMuSX26qK9RqN6SzNyNeaMirH+3jTkwGTevZ8ekb3UjOLGDLkdvKXOw7d48vd0pdSG5GpeHfyIkJ/ZpzJkQzBibJZDJuJeay6pDUehaalI+nvQkj2riw65o0MHFUezeau1rw+oZrJGUX09LD6s8+riWcv5elzvCrjaWhLiN8HfjsZLRKq+p9BfIK1p6PJ7CFI908rVEo4FJcLrFZxfzLqdxrhXELg1j7wVCi9s974L3yBr7eTuoOrUZU56wCs2fPZsaMGSrbHl72/HGmTJnCrVu3OHPmTPUF8ydRuApCLRGdmEnPSV9hZKCHmbE+KZn5bF42iuhEzbvl+U+crY3o3LgOr35Z1aE/9c8CNjxJdfLtiKQ8nK2NajS+p23ZhM6sCLrEjhN3Abgdk4FrHTPeHeHPliO3ycgrpqy8gtA41WsjLC6Tdk0054tOer6cyFTV2+JRaYUENJFGKOvraDE9wJOpm69z8q40YjwspYCGjqa81slDYwpXN0sDzAx0mNejqiuItpYMT1sjuta35o1fb3MntYC5v4djoqdNhUJBcVklK/p7kV5Y9jdnrp2iEzPp+ca3GBnoYmZsIL1XLgkkOimLlEyppdXOylT5u/TYhJsRmjELS3V2cdXX13+iQvVBU6dOZd++fZw6dQpn56r3G3t7e0pLS8nJyVFpdU1NTcXe3v6Jzy8KV0GoZYpKSikqKcXC1JDubbyZ++VedYdU417uWJeMPDmHg6s+aOIyCknOLqKeg2rXibr2phy7qVlz7Rrq6z4yU0JFpQKtP5taysoruRqWQgNnK5VjPJ2tiEutvlV11O1aTA4eD/XRdLcxIvHPEfU62jL0dLR4uFGxQqHQqLkuQ9MKWXAwQmXb2NZOJOeVcvBuusrfX1AqzSrhbWeMqYEOwUl5NRlqjSoqKaOopOzP90ov5q7ZT0xSFskZeXRtVV9ZqJoa69OqsSvf73zyfpbCoxQKBW+++Sa//fYbJ06cwMNDdfxFixYt0NXV5dixYwwePBiAsLAw4uLiaNu27RO/jihcBaGW6N7GC5lMRnhsGvWcbVj2Vn/CY9LYtOcSAJZmRrjYW+BgIy3R18BNGlWcmplPaqbmjKyXyWBkBw+CzkZT8dBt0TUH7jJrYBNux2VzKy6H4R088HQwZdyaJ59qpTb4/UIks0a2IT4tjzuxGTSvX4dpg1qy6VCI8phVv1xm85z+nAlJ4GRwHD1betCnTT0CZgapMfLqtfFMDNsm+zOpqwcHbqbS1MWcYf7OzP/1DgCF8gouRmbxbp8GlJRVkJRdQqu6lgz0c+SjfWFqjr76yMsrScqTP7RNQWFpuXJ7O3cLUvLk5MsrqGttyAhfB46GZ5KaX6qOkJ+q7v4Nqt4rXWxY9mY/wmPT2LT3MgBfBZ1m1tgXuBefQUxSFgsmBZCckceek7fVHHk1UdOXsilTprB161Z2796Nqampst+qubk5hoaGmJub89prrzFjxgysrKwwMzPjzTffpG3btk88owCIwlUQag1zEwMWT+mLk50FWXlF7P7jJgu+/p3yCml6m76dGvP9gpHK4zcvGw3Aku8OsfT7Q2qJ+Wno3MgeFxtjtp6KfmTf2sPh6Otqs2SkHxYmetyOy2HIpyeISX+2Vo77r2Z8dZQFYzqw+s3u2FoYkZxZyA+/B7Psp3PKY/acjeDNLw7z7og2rJzcjfCEbEYu3s2524lqjLx6hSTkMXXTDWb08mTKC/VIyC5m2d4w9t6oamGfsTWYGb0bsGJEU8yNdEnKLmbVoQi2XYhXY+Q1z95Un0E+dTDW0yazqIzfQ9M5Eq6Z3YzMTQxYPLkPTnbm0nvl8RAWfHNQ+V65cvMJjAz1WDN7CBYmBpwLjmHAW+s0Zg5XdS35+s033wDQpUsXle3r16/n1VdfBWDVqlVoaWkxePBglQUI/g2ZQhN7ZgtCDTJsNeOfD3oOGDdure4QngmFSc9XQfRXXH2bqjuEZ0KnFs/HgKAn8dPKjeoO4ZlQfPHTp3r+m/HV90W9qcuzNyOLaHEVBEEQBEHQEJrUf/txROEqCIIgCIKgITS8bhWFq/DscXd35+233+btt99WdyhPZO0309UdwjNhT4hmLZ/5/0rJFLeGAXR0tNUdgiA8nzS8chWFqyDUAleP7uHa0b3kpEur4tg6u9HhpVHUb67ar1ShUBD0yRyibl5myPRFeLVsr45wn5phzR0Y5uugsi0xp4S3frvzyLFze9TD19mcj49FcjlOc6aAus/GRI83OnnQxsMSAx0tEnJKWHYwnLBUqX9bJ09rBjZzwKuOCeaGury68Rr30jVnTfr7Xm3jwqttXFS2xWUVMXrTDQAczfV5o6M7Po5m6GrLuBSbwxcnosku0rz5S+/r5W3D4Kb2HA3P4Ocb0shuW2M9hjazp76NETraMm6nFLD1WhL58go1R1v9TIz0WTApgAGdm2BraUJweCIzP9vN1dCqhTfmTezJ2Bf9sTAx5PzNGKZ9spPI+Aw1Ri08KVG4CipKS0vR09NTdxjCQ0ytbOk6YjxW9k4oFHDz9GF2fDaf8cu+xdbZXXncpYO/ItPwDk5x2cUsPlQ1Z+XDU2IB9GtkhyaPOjXV1+Gbkc24Fp/DzF9vkVNchrOFIfklVaOiDXW1uZmYxx9h6bwf0ECN0T590RlFvLOzaiqj+9eEgY4Wn77UmMiMQqb/Ku1/rZ0LywZ4MzkoRCOvEXdLQzrXtSL+z7lsAfS0Zbzd2Z2EnGJWnpRm43ixSR3e7ODG8mNRGpeHb+YMoVE9e8Yt3EZyRh4je/mxf81E/EasICk9j3dGdWHysA5MWPwzMUlZzJ8UwN7V4/EdsUIjZhZQ16wCNUVL3QEIf61Lly5MnTqVqVOnYm5ujo2NDfPmzVMu0SeXy5k5cyZOTk4YGxvj7+/PiRMnlM/fsGEDFhYWHDp0iIYNG2JiYkKvXr1ITq6aKubVV19l4MCBLF26FEdHR7y8vAAICQmhW7duGBoaYm1tzcSJEykoqBqpeOLECVq3bo2xsTEWFha0b9+e2NhY5f7du3fj5+eHgYEBdevWZdGiRZSXS28ICoWChQsX4urqir6+Po6OjkybNk3lby8qKmLcuHGYmpri6urKd999p7J/1qxZNGjQACMjI+rWrcu8efMoK6tqQVm4cCHNmzdn7dq1uLi4YGRkxLBhw8jNVW15W7duHQ0bNsTAwABvb+9/PS1HTWng15b6zf2xsnfG2sGZrsPGoWdgSOK9UOUxKTH3uLj/F/pNnKnGSJ++ikoFOcXlyp+HW4zcrQzp38SOr8/E/sUZar/A1s6k5ctZfjCC0JQCknPlXI7NISm3RHnMoTtpbDgfx5XYHPUFWkMqFAqyisqUP7l/FvBNHE2xN9Pno8P3iM4sIjqziOWH7uFVxwQ/F3M1R1399HW0GN/GmU1XEikqrVRur29jjI2RLusvJZKYKycxV876Swm4WRnibWf8N2esfQz0dRjY1Ye5a/Zz9kY0UQmZLF13hMiETCYMkia5nzKiIx+vP8a+U7e5dS+Z8QuDcLAxY0DnxmqOvnrIZNX38ywSheszbuPGjejo6HDp0iVWr17NZ599xrp16wBpWbXz588TFBTEzZs3GTp0KL169SIioqo1qqioiBUrVrB582ZOnTpFXFwcM2eqFjbHjh0jLCyMI0eOsG/fPgoLCwkICMDS0pLLly+zY8cOjh49ytSpUwEoLy9n4MCBdO7cmZs3b3L+/HkmTpyobOk7ffo0o0eP5q233uLOnTusXbuWDRs2sHTpUgB+/fVXVq1axdq1a4mIiGDXrl34+PioxLRy5UpatmzJ9evXmTx5Mm+88QZhYVUThpuamrJhwwbu3LnD6tWr+f7771m1apXKOe7du8f27dvZu3cvBw8eVJ7rvi1btjB//nyWLl1KaGgoy5YtY968eWzc+GxP2VJZWcHt88cpk5fgVL8RAGXyEnZ/tYyAV9/ExMLqH85QuzmY6fPd8CZ8NaQxb3Vyx8ZYV7lPT1vGW53dWXchnpzi2t9y8lfa17fmbkoBH/b3Zu9kf34c5Ut/nydfMlHTOFkY8Mv4lmwd68fcXp7YmUp3jXS1pY+4soqqIq60ohKFAnyczB57rtrsZT8HbibnE5qm2iVER0uGAih/4O5EWYUChQLq22pW4aqjrY2OjjYlctX//0vkZbRr5oG7oxUONmb8canqczKvsITLt+Pw93Gr6XCF/4PoKvCMc3FxYdWqVchkMry8vAgJCWHVqlUEBASwfv164uLicHR0BGDmzJkcPHiQ9evXs2zZMgDKysr49ttvqVevHiAVu4sXL1Z5DWNjY9atW6fsIvD9999TUlLCpk2bMDaW3tTWrFlD//79+fjjj9HV1SU3N5d+/fopz9uwYUPl+RYtWsT777/PmDFjAKhbty4ffvgh7733HgsWLCAuLg57e3u6d++Orq4urq6utG6t2lezT58+yiJz1qxZrFq1iuPHjytbhD/44APlse7u7sycOZOgoCDee+895fb7f4OTkzRY5ssvv6Rv376sXLkSe3t7FixYwMqVKxk0aBAAHh4eykL7fuzPkrS4KDYsnEZ5WSl6BoYMmb4QW2fpjfbIT9/g1KCxxvVpfVhEeiFfnYklKVeOhaEOw3wd+LBPA6b/FkpJeSWv+jsTllaokX1aH+RobsDA5g78fCWBTRfjaWhvytvd6lJWWcnB22nqDq9G3UnJ56PD94jPLsbaWI8x/s58MdSHsZuvcycln+KyCiZ1cOP7s3HIgIkd3NDWkmH1wBceTdDKxRxXC0OWHo18ZF9UVhHy8koGN63DbyFSP/nBTe3R1pJhbqBZZUBBkZwLN2OYPa47YTFppGblM6ynL/5N3IhMyMDe2hSAtCzV1QTTsgqoY2WqjpCr3TPaUFptNOuK1UBt2rRR6bPYtm1bVq5cSUhICBUVFTRooNp3TS6XY21trXxsZGSkLC4BHBwcSEtT/WDz8fFR6dcaGhpKs2bNlEUrQPv27amsrCQsLIxOnTrx6quvEhAQQI8ePejevTvDhg3DwUEaNBMcHMzZs2eVLawAFRUVlJSUUFRUxNChQ/n888+pW7cuvXr1ok+fPvTv3x8dnarLsWnTqsnLZTIZ9vb2KnH//PPPfPHFF0RGRlJQUEB5eTlmZqotKK6ursqi9X7u7v8NpqamREZG8tprrzFhwgTlMeXl5Zib//UtRLlcjlyuurRiWakcXT39v3xOdbF2dGH8srXIiwu5e/EUe7/9hFc++Izs1ERibt9g/LJvn3oM6nY9sWpd9dhsiMgo4puhTWjnYUleSTk+Dqa8u/uuGiOsGVoyuJtSwHd/doeISCvEw8aIgc0cnrvC9VJMjvL3qIwiQlPyCRrXgq4NbPj9dhoL94cxvVs9BjV3QKGAY2HphKUWoElL71ga6jLC14HPTkartKreVyCvYO35eAJbONLN0xqFAi7F5RKbVYwmrkE0bmEQaz8YStT+eZSXV3AjLJHth2/g6/2czPih4ZWrKFxrqYKCArS1tbl69Sra2qrTzpiYVK10oaur2qogk8keeaN6sEB9UuvXr2fatGkcPHiQn3/+mQ8++IAjR47Qpk0bCgoKWLRokbIl80EGBga4uLgQFhbG0aNHOXLkCJMnT+bTTz/l5MmTyngfF3dlpXS77/z58wQGBrJo0SICAgIwNzcnKCiIlStXPnH89/vrfv/99/j7+6vsezifD1q+fDmLFi1S2TZwwtu8NPHpr56lraOLlb30xuvg0YCkqDAuH9qJjp4+2WlJrJjwosrxv36+CBfvJoz64LOnHpu6FJVWkJxbgr2ZPq6WhtQx1WdjYDOVY2Z2rcvd1AIWHIz4i7PUPpmFpcRkFqlsi80spounjZoienYUyCtIyC7BycIAgCtxuQRuuIa5gQ4VCgUF8gp2TmjJH+El/3Cm2sPN0gAzAx3m9aiv3KatJcPT1oiu9a1549fb3EktYO7v4ZjoaVOhUFBcVsmK/l6kF2re7ArRiZn0fONbjAx0MTM2ICUzn81LAolOyiIlU2pptbMyVf4uPTbhZkSSukIW/gVRuD7jLl68qPL4woULeHp64uvrS0VFBWlpaXTs2LFaX7Nhw4Zs2LCBwsJCZVF79uxZtLS0lLfqAXx9ffH19WX27Nm0bduWrVu30qZNG/z8/AgLC6N+/fp/9RIYGhrSv39/+vfvz5QpU/D29iYkJAQ/P79/jO/cuXO4ubkxd+5c5bYHB4bdFxcXR1JSkrIrxYULF5R/Q506dXB0dCQqKorAwMAnzs3s2bOZMUO1SN1xSz0tXAqFgoqyMjoNHkPzLr1V9n3//gR6vPIGnn5t1BJbTTHQ0aKOmT45kVmci8nmWLjqdDarXmrExksJXInXrK4DIYl5uFoZqmxzsTQkJU/+F894fhjqauFooc/hu6Uq2+8P2PJ1NsPCSJdzUVnqCO+pCE0rfOSL2djWTiTnlXLwbrpK63JBqTSY0dvOGFMDHYKT8tBURSVlFJWUYWFqSPc2Xsxds5+YpCySM/Lo2qq+slA1NdanVWNXvt95Xs0RVw9Nn1VAFK7PuLi4OGbMmMGkSZO4du0aX375JStXrqRBgwYEBgYyevRoVq5cia+vL+np6Rw7doymTZvSt2/f//s1AwMDWbBgAWPGjGHhwoWkp6fz5ptvMmrUKOrUqUN0dDTfffcdAwYMwNHRkbCwMCIiIhg9ejQA8+fPp1+/fri6ujJkyBC0tLQIDg7m1q1bLFmyhA0bNlBRUYG/vz9GRkb89NNPGBoa4ub2ZB3jPT09iYuLIygoiFatWrF//35+++23R44zMDBgzJgxrFixgry8PKZNm8awYcOwt5cGsSxatIhp06Zhbm5Or169kMvlXLlyhezs7EeK0/v09fXR11ftFqCr9/SLouNB66jXrDVmNnaUFhdx+9wfxIYGM3LWR5hYWD12QJaZjR0Wdg6POVvtNbqVE1fickkvLMXKSJdhzR2oVCg4E5VNnrz8sQOy0gtLSSsofczZaq+fryby7chmjPJ34Y+wdBrZmzKgmT2fHK4qXkwNdKhjqo+NidQN6H6hm1VYSpYGzWH6Rkc3zkVlk5ovx9pYj7FtXKishGNh0peYXo3siMsqIqe4jMYOpkzt7MGOa8nEZ2tOi6u8vJKkh760yMsVFJaWK7e3c7cgJU9OvryCutaGjPB14Gh4Jqn5mvX/BkB3/wbIZDLCY9Oo52LDsjf7ER6bxqa9lwH4Kug0s8a+wL34DGKSslgwKYDkjDz2nLz9D2euHZ7V2QCqiyhcn3GjR4+muLiY1q1bo62tzVtvvcXEiRMB6Xb9kiVLeOedd0hMTMTGxoY2bdrQr1+///SaRkZGHDp0iLfeeotWrVphZGTE4MGD+eyzz5T77969y8aNG8nMzMTBwYEpU6YwadIkAAICAti3bx+LFy9WDuby9vZm/PjxAFhYWPDRRx8xY8YMKioq8PHxYe/evSp9c//OgAEDmD59OlOnTkUul9O3b1/mzZvHwoULVY6rX78+gwYNok+fPmRlZdGvXz+V6a7Gjx+PkZERn376Ke+++y7Gxsb4+Pg8kyt2FeblsOfbjynIyULfyBg7Fw9GzvqIuj4t1B1ajbI20uXtLu6Y6uuQV1LO3dQC5uwLI0+uuTMIPM7dlALm7A5lUkd3Xm3rSnJuCV/8EcWR0KrVyzrUs2Ju76o7JIv7SwMofzwXy4/n4mo85qfF1kSfeb0bYGagQ25xGSFJ+Uz++Sa5f36JcbU0YGJ7V0wNdEjJk/PTpQR2XE/+h7NqHntTfQb51MFYT5vMojJ+D03nSHimusN6KsxNDFg8uQ9OduZk5RWx+3gIC745SPmfs0us3HwCI0M91swegoWJAeeCYxjw1jqNmMP1eSBTaGLPbA3RpUsXmjdvzueff67uUGqdhQsXsmvXLm7cuPHUX2vTlfin/hq1gVjyVZKSqXmrU/0/xJKvEk9HzZt26//108pne6rBmlJ88dOnev7wlKJ/PugJNbA3qrZzVRfR4ioIgiAIgqApRFcBQRAEQRAEoTbQ9MFZoquAIPxHRoN/VHcIz4SGzT3UHcIz4c7pK+oO4Zng6tv0nw96Dvg306wBkv/FjtWb1R3CM+FpdxWISC2utnN51jH854NqmGhxFYRaQEtLxgfDfBnRqR51LAxJzi7ip+MRfPRLsPKYF/3deK2nN771rLE2NaDNO7u4GaM5U/7cZ2uqx7QX6tGunjUGulokZBezcM9dQpPzHzl2dp8GDGnhxIpDEWy7lKCGaJ8OLS0ZH4xqx8gXGlHH0pjkzEI2H7nFR1tUp/PxcrFiyfjOdGzqgo62jLuxmYxcvJv49EdzVVvZmenzbu8GdPSywVBPm9iMIubsuMWtPxerMNLT5p3eDeje2A4LI10SsorZfDaWoIuacz0AvORTh5d86qhsS8ot4f394QDoaskY6edAGzcLdLRkhCQXsPFKInklmjcgycRInwWTAhjQuQm2liYEhycy87PdXA2t+jefN7EnY1/0x8LEkPM3Y5j2yU4i4zP+5qy1h5hVQBAEtXtnoA/jA7yZ+OUp7sTn4FfPhrVTO5JbVMY3v98BwMhAh/N3U9l5LpqvJ3dQc8RPh6mBDj++6seVmBymbQsmu6gMVytD8ksend6pq5cNPk5mpGng3KbvDGvNhH7NmfDpAe7EZtCigT1r3+lNXqGcr3ddA8DDwYJjq15m48EQlmw6S15RKY3crCkpq1Bz9NXHzFCHbW/4czEqiwk/XiO7sBQ3GyNyi6uuh/f7edGmnjXvBt0kMbuY9p42LBjYkLQ8OX+EataAwoScEj7+I0r5uOKBG6ovt3CkuaMpX56Jpbi0ktGtHJnW0Y0lRx5dIra2+2bOEBrVs2fcwm0kZ+Qxspcf+9dMxG/ECpLS83hnVBcmD+vAhMU/E5OUxfxJAexdPR7fESs0YmYBDa9bReEqCLVBGy879l+O4+A1qcUgLr2AYR3r0rJ+1UpJ205KH0CutiaPPYcmeLWdK6l5chbtrVrWNSnn0fk4bU31eLeXJ1O3BrN6hObdsm7TyIl95+9x8JJUpMSl5jGsS0NaelXdll40tgOHLkUxd91J5bbo5JyaDvWpmtDZg5TcEubsuKXclpCtepvU182CXdcSuRSVDcD2SwkM93emqYu5xhWuFQqFcqGFBxnqatG5riXfnIsnNFWa9eL7Cwl83M+LetZGRGZW3yh0dTPQ12FgVx+GvreBszeiAVi67gh9OjZiwqC2LFp7iCkjOvLx+mPsOyXN2zp+YRCxB+YzoHNjdhwJ/rvTC88ALXUHIAjCP7sQlkYXHwfqO0hT6/i4WdHWuw6Hr2vW7c5/0qmBDXeS8vl4cGOOzGjPlgkteclXtQ+hDPjwxUZsPh9PVLrmfCA/6MKdRLo2d6O+kyUAPnVtadvEicOXpUJWJoNeresRkZjNnmVDiN0+mVNfBNK/3V+vZlcbdWtkx62EXFYHNuPcvC78Nq0tQ1s7qxxzPTaHbg3tsDOTFg7xr2uFh60xZyI0bw5Te1N9Vg9syIoBXrzezgVrI2npbHcrQ3S0tbidUtVFJDlPTkZhKfVtnr3pjv4LHW1tdHS0KXlobucSeRntmnng7miFg40Zf1yqWqwjr7CEy7fj8Pd5skVwnnmyavx5BokWV0GoBVb8dhNTIz1ufDGYikoF2loyFm69ys+no/75yRrEydKAIS0d2XIhgR/PxtLIwZSZAZ6UVSjYdzMFgFfbu1JRqdCoPq0PW/HzRcyM9An+4TUqKivR1tJiwYbTBP0RCoCdhTGmRnrMHN6aRRvO8MG6U/Rs5U7Q/IEEvBvEmRDNyI2LlSEj27iw/nQs3x6PwsfZnA8GeFNWXsmua9Jynh/uDuXDwY05PbcLZRWVKBTwwa+3uRKdreboq1dkRhHfnY8nJV+OhaEOA5vUYW6PeszZH46FgS5lFZUUlVWqPCe3pBxzQ80qAwqK5Fy4GcPscd0Ji0kjNSufYT198W/iRmRCBvbWpgCkZan2807LKqCOlak6Qq52mj6rgGZdsYKgoQa382BEx7q8+vkJQuNzaOphxSdj/UnOLmLLiXvqDq/GaMlk3EnK56vjUsEellJAfTsTBrdwZN/NFLztTRjR2pnA7zV7ZP+Qzt6MeKEhr360jzsxGTStZ8enb3QjObOALUduo/Xn59a+c/f4cudVAG5GpeHfyIkJ/ZprTOEqk8m4lZjLqkNS61loUj6e9iaMaOOiLFxHtXejuasFr2+4RlJ2MS09rP7s41rC+XuaM3jx5gODE+NzpEL2sxcb0trVnLKK52vyoHELg1j7wVCi9s+jvLyCG2GJbD98A19vJ3WHJlQDUbgKQi2wbHQrVv4Wwi9npT5bt+OycbUxYeagps9V4ZqRX0p0hurKVNEZhXTztgXA19UCK2M99r/VVrlfR0uL6T3q87K/M/2/vFCj8T4tyyZ0ZkXQJXackPr63o7JwLWOGe+O8GfLkdtk5BVTVl5BaJzq7fCwuEzaNXF+3ClrpfR8OZGpqtdDVFohAU2k0fX6OlpMD/Bk6ubrnLwrjRgPSymgoaMpr3Xy0KjC9WFFZZWk5MupY6rPrZR8dLW1MNLVUml1NTfQUS6Nq0miEzPp+ca3GBnoYmZsQEpmPpuXBBKdlEVKplTg21mZKn+XHptwMyJJXSFXKzGrgCAIameor0PlQ1MuV1Qq0NL0d6iHBCfk4mat2ifP1cqI5FxpgNbvISlceugW8JqXm/F7SAp7gjVnfXpDfd2/vR7Kyiu5GpZCA2crlWM8na2IS82tsTiftmsxOXjYGqtsc7cxIjFHGqCloy1DT0eLh2crr1AoNP7DXV9HCzsTPc4WlxGTVUx5RSWN7E24Ei9NE2Zvqo+NsR73MjSzHzhAUUkZRSVlWJga0r2NF3PX7CcmKYvkjDy6tqqvLFRNjfVp1diV73ee/4cz1g4afmmLwlUQaoPfr8Tz3uBmxKcXcCc+h+Ye1rzZvzGb/qgaYGBpooeLjQkOVlJh5+loDkBqTjGpOdU3IbU6bbkQz/qxfoxt78aRO2k0cTJlkJ8jS/eHAZBbXP5IC1J5ZSUZBaXEZmpGDgB+vxDJrJFtiE/L405sBs3r12HaoJZsOhSiPGbVL5fZPKc/Z0ISOBkcR8+WHvRpU4+AmUFqjLx6bTwTw7bJ/kzq6sGBm6k0dTFnmL8z83+VpogrlFdwMTKLd/s0oKSsgqTsElrVtWSgnyMf7QtTc/TVa4SvA9cT88gsLMXCUJdBPnWoVMCF2ByKyyo5GZXNy36OFMorKC6rZFRLRyLSCzVqRoH7uvs3QCaTER6bRj0XG5a92Y/w2DQ27b0MwFdBp5k19gXuxWcQk5TFgkkBJGfksefkbTVHLjwJsXKWIPxHNbFylomBDvNHtmCAvxu2ZgYkZxex40wUy3bcoKxcuvX3Stf6fDe10yPPXfrzdZZuv/7UY6yplbM6eloztVtdXKwMScopYcuFeH67/tetqXvfbMPWiwk1NlirJlbOMjHUZcGYDgxo74mthRHJmYVsPxHKsp/OKa8HgNEBTXh3RBucbEwIT8hmyaaz7DtfM11LamrlrC7etszo5Ym7jREJ2cWsPx3Ljgf+rW1M9JjRuwEdPK0xN9IlKbuYny8lsOF0bI3EV1MrZ01u74qXrTEm+trky8sJTy/il+AU0gpKAdUFCHS1tQhJzmfj5cTHTp/1tNTUylmDX2jK4sl9cLIzJyuviN3HQ1jwzUHyCqumzps3sSfjBrbBwsSAc8ExvPXJTu7V0AIET3vlrJjMR6cI/H+5WxtU27mqiyhcBeE/Eku+SsSSrxKx5KtELPkqEUu+VhFLvkqeduEam1l9i664WetX27mqi+gqIAiCIAiCoCE0vf+2KFwF4T9SRF1TdwjPhEQrM3WHIDxDtLU1/NNTEAS1ECtnCc+NEydOIJPJyMnJUXcogiAIgvBUaPjCWaLFVah5Xbp0oXnz5nz++ec1+rrt2rUjOTkZc3PzGn3d6mJipM+Cyf0Y0K0ZtpYmBIclMPOTX7h6Jw6AuZP6MDTAD2d7S0rLKrgeGsfCNXu5fKtmBqHUhMvLe+NiY/zI9vXH7zF76w2VbVundaCbjz2vfnWOgzc0Y37G+7S0ZHwwqh0jX2hEHUtjkjML2XzkFh9tUZ3Ox8vFiiXjO9OxqQs62jLuxmYycvFu4tPz/+LMtZOdmT7vBHjS0csGA11t4jKLmPvrbW4nSlM/3VnW87HPW3EgnB9Px9RgpE/PSz51eMmnjsq2pNwS3t8fDqgOztLRkhGSXMDGK4nk1eDgrJpiYqTPgkkBDOjcRHqvDE9k5me7uRpaNWhv3sSejH3RHwsTQ87fjGHaJzuJrKHBWU+b6CogCBpCT08Pe3t7dYfxf/tm/ss0qu/IuA82kpyey8g+rdn/7Zv4DV5CUnou92LTmP7xDqITMjDU1+XNV7qx9+upNHlxERnZBeoOv1r0WnoMLa2qd2VvJ3N2zOjE3iuJKsdN7O6JAs0dd/rOsNZM6NecCZ8e4E5sBi0a2LP2nd7kFcr5epfUdcXDwYJjq15m48EQlmw6S15RKY3crCkpq1Bz9NXLzECHLZNacykqi0kbrpFVWIabtRF5xWXKYzotO6HynI4NbPhwUGMO30qt4WifroScEj7+o2oZ6IoHxl6/3MKR5o6mfHkmluLSSka3cmRaRzeWHIlUR6hP1TdzhtConj3jFm4jOSOPkb382L9mIn4jVpCUnsc7o7oweVgHJiz+mZikLOZPCmDv6vH4jliBvFTzCnlNI7oKCDXq1Vdf5eTJk6xevRqZTIZMJiMyMpLXXnsNDw8PDA0N8fLyYvXq1Y88b+DAgaxYsQIHBwesra2ZMmUKZWVVH05yuZyZM2fi5OSEsbEx/v7+nDhxQrn/4a4CmZmZjBw5EicnJ4yMjPDx8WHbtm01kYZ/zUBfl4EvNGfu57s4ey2SqPgMlq79ncj4dCYM7QjAzwevcPxiGDGJmYRGpTBr5U7MTQ1p4umo5uirT2ZBKel5cuVPj6YORKcVcC48XXlMYxdzXu/pydsbNHd0f5tGTuw7f4+Dl6KIS83jt9PhHLsaQ0uvqhHsi8Z24NClKOauO0lwZBrRyTnsvxBJeo5mzdv5WmcPUnJLmPvrbUIS8kjMLubcvUzis6rm7c0oKFX56dbIjkvRWSRka87cviAVqrkl5cqfArn0JcVQV4vOdS3Zei2Z0NRCYrKL+f5CAg1sjan30IIetZ2Bvg4Du/owd81+zt6IJiohk6XrjhCZkMmEQdKKelNGdOTj9cfYd+o2t+4lM35hEA42Zgzo3FjN0VcXze4sIApXoUatXr2atm3bMmHCBJKTk0lOTsbZ2RlnZ2d27NjBnTt3mD9/PnPmzGH79u0qzz1+/DiRkZEcP36cjRs3smHDBjZs2KDcP3XqVM6fP09QUBA3b95k6NCh9OrVi4iICB6npKSEFi1asH//fm7dusXEiRMZNWoUly5depop+L/oaGuho6NNSWmZyvYSeRntfOs9cryujjavDWpPTn4RIeGJj+zXBLraMgb7u7LtbIxym6GeNt+M92f2luuk51XflDDPmgt3Euna3I36TpYA+NS1pW0TJw5fllrbZDLo1boeEYnZ7Fk2hNjtkzn1RSD929VXZ9hPRbeGttxKyGPVyKacntOFX6e2YUjLv16T3tpEj05eNvx6RfP+v7A31Wf1wIasGODF6+1csDbSBcDdyhAdbS1up1R1EUnOk5NRWEp9G80qXHW0taX3Srlqy2mJvIx2zTxwd7TCwcaMPy5VfS7kFZZw+XYc/j5uNR3uUyGTVd/Ps0h0FRBqlLm5OXp6ehgZGanctl+0aJHydw8PD86fP8/27dsZNmyYcrulpSVr1qxBW1sbb29v+vbty7Fjx5gwYQJxcXGsX7+euLg4HB2lFsaZM2dy8OBB1q9fz7Jlyx6JxcnJiZkzZyofv/nmmxw6dIjt27fTunXrx8Yvl8uRy1ULIkVlBTIt7f8vIU+ooEjOheAoZk/oTVh0KqmZeQzr1RL/ph5Exle1Nvbu2IRNH43FyECXlIw8+r2+hsycwr85c+3V29cJcyNdfn6gcF00rBmXIzM5pEHLuz7Oip8vYmakT/APr1FRWYm2lhYLNpwm6I9QAOwsjDE10mPm8NYs2nCGD9adomcrd4LmDyTg3SDOhNTMYgw1wdnSkBH+zmw8G8t3J6Jp4mzGnP7elFUo2H390b7NL/o6UiSv4MjtNDVE+/REZhTx3fl4UvLlWBjqMLBJHeb2qMec/eFYGOhSVlFJUVmlynNyS8oxN9SsMqCgSM6FmzHMHtedsJg0UrPyGdbTF/8mbkQmZGBvbQpAWpZqP++0rALqWJmqI2ThX9KsK1aotb766it+/PFH4uLiKC4uprS0lObNm6sc07hxY7S1qwpEBwcHQkKkJS5DQkKoqKigQYMGKs+Ry+VYW1s/9jUrKipYtmwZ27dvJzExkdLSUuRyOUZGf90CsXz5cpUiG0C7Tit0HR5f6FancR9sYu3CQKIOL6W8vIIbd+PZfvAKvg1dlcecvByO/4jl2FiYMHZQO376ZBydRq0gXUP6uD5oZAd3/riVQmqutEpMz2YOdPC2pfuHR9Uc2dM3pLM3I15oyKsf7eNOTAZN69nx6RvdSM4sYMuR29zvBrzv3D2+3HkVgJtRafg3cmJCv+YaVbhqyWTcSszj88PSimChyfl41jFhuL/zYwvXQS2d2BecTGl55SP7arObyVWFWHyOVMh+9mJDWruaU1ahuf29H2fcwiDWfjCUqP3zpPfKsES2H76Br/dft8Rrkme0obTaiMJVULugoCBmzpzJypUradu2Laampnz66adcvHhR5ThdXV2VxzKZjMpK6cOnoKAAbW1trl69qlLcApiYmDz2dT/99FNWr17N559/jo+PD8bGxrz99tuUlpb+ZayzZ89mxowZKtvsOs564r/1v4hOyKDn+NUYGehhZmJASkYemz8aS3Ri1UjYopJSouIziIrP4FJIDCG75zPmpXas+PFwjcRYU5ytjOjUsA7jvj6n3NbB2w53WxPCV7+ocuwPb7TlYkQGg1acrOkwn5plEzqzIugSO07cBeB2TAaudcx4d4Q/W47cJiOvmLLyCkLjMlWeFxaXSbsmzuoI+alJz5cTmab6xSwyvZAejes8cmwLdwvq2hrzzrbgmgpPbYrKKknJl1PHVJ9bKfnoamthpKul0upqbqBDbrHmDUaKTsyk5xvfYmSgi5mxASmZ+WxeEkh0UhYpmVKBb2dlqvxdemzCzQjNmH3kWb3FX11E4SrUOD09PSoqqkY2nz17lnbt2jF58mTltsjIfzfS1dfXl4qKCtLS0ujYseMTPefs2bO8+OKLvPLKKwBUVlYSHh5Oo0aN/vI5+vr66OurLoH3tLsJPKyopJSiklIsTA3p3q4hcz/f/ZfHaslk6Otq3v/mI9q7k5FXwtGQFOW2Lw/cZevpaJXjTizqyfyfgzlyUzM+kO4z1Nel8qHVuisqFWj9+YlVVl7J1bAUGjhbqRzj6WxFXGpujcVZE67F5eBhqzpFmru1MUk5j67XPqiFE7cScglL0bw7EA/T19HCzkSPs8VlxGQVU15RSSN7E67ES1OE2ZvqY2Osx70MzRqs96CikjKKSsqk98o2Xsxds5+YpCySM/Lo2qq+slA1NdanVWNXvt95/h/OKDwLNO8TTXjmubu7c/HiRWJiYjAxMcHT05NNmzZx6NAhPDw82Lx5M5cvX8bDw+OJz9mgQQMCAwMZPXo0K1euxNfXl/T0dI4dO0bTpk3p27fvI8/x9PTkl19+4dy5c1haWvLZZ5+Rmpr6t4WrOnVv2xCZDMJj0qjnYsuy6QMJj05l057zGBnoMWt8APtPhpCSkYu1hQmThnXC0c6CnUc0a2UvmQxGtHdj+/lYKiqrirf7Mw08LDGriDgN+3D+/UIks0a2IT4tjzuxGTSvX4dpg1qy6VCI8phVv1xm85z+nAlJ4GRwHD1betCnTT0CZgapMfLqt+lMLFteb83Ezh4cDEnBx8Wcoa2dWfjbbZXjjPW1CfCx59Pfw9QU6dM1wteB64l5ZBaWYmGoyyCfOlQq4EJsDsVllZyMyuZlP0cK5RUUl1UyqqUjEemFRGZq1v8bAN39GyCTyQiPTaOeiw3L3uxHeGwam/ZeBuCroNPMGvsC9+IziEnKYsGkAJIz8thz8vY/nLl2kGl4ZwFRuAo1bubMmYwZM4ZGjRpRXFzM3bt3uX79OsOHD0cmkzFy5EgmT57MgQMH/tV5169fz5IlS3jnnXdITEzExsaGNm3a0K9fv8ce/8EHHxAVFUVAQABGRkZMnDiRgQMHkpv7bLZImZsYsPjNATjVsSArt4jdx26w4Ku9lJdXoq1ViZd7HV7p74+1hTFZuUVcuR1L93GrCI1K+eeT1yKdGtbB2dpYZTaB582Mr46yYEwHVr/ZHVsLI5IzC/nh92CW/VTVdWLP2Qje/OIw745ow8rJ3QhPyGbk4t2cu61Zo+lvJeYx7acbTA/w5I1udUnILuajfXfZF6x63fdpao8M2B+sWf8/3GdlpMvkdq6Y6GuTLy8nPL2IxYfvkf/nlFhbryahUDjwZkc3dLW1CEnOZ+NlzboW7jM3MWDx5D442ZmTlVfE7uMhLPjmIOUVUjeJlZtPYGSox5rZQ7AwMeBccAwD3lqnOXO4anbdikyhUDxfvbaF59ahQ4fo3bs3JSUl6OnpVdt5DX2nVtu5ajPzll3UHcIzITc2+p8Peg54tGym7hCeCS2b1N5FT6rbjtWb1R3CM6H44qdP9fypeWX/fNATqmOm+88H1TAxj6vwXEhNTWX37t14enpWa9EqCIIgCELNEV0FhOdCnz59yM/P5+uvv67+k+uIQhjA/s/J8J938mLNXfhA+PfSczVrdS7h2SdmFRAEDXD16lV1h/CfmRjps+D13gzo0gRbS1OCwxOYuXIXV+/EA/BiVx/GD2qHr7cz1hbG+Aeu4Ga4Zo2mB7Az1eetHvVoX98GA10t4rOKWbD7DneSpKltFg9syIDmqsvcnr2XyZSfbqgh2qcjeNWLuNo+Os3buiPhvLvxMnbmBiwe6UeXJvaYGOhyLyWPlbtvsfdyvBqiffrszPR5J8CTjl42GOhqE5dZxNxfb3M7URpBf2dZz8c+b8WBcH48HVODkT49gS2deKWV6lRn8dnFTAy6iZ2pHhtf8X3s85YeiuBMVFZNhFhjTIz0WTApgAGdm2BraUJweCIzP9vN1dCq+YvnTezJ2Bf9sTAx5PzNGKZ9spPI+Iy/OWvtIQZnCYLwTPjmg2E0qufAuAVbSU7PY2TvFuz/6nX8hn1CUnouRgZ6nAuO5tejN/jmg+HqDvepMDXQYcNrLbgcnc3ULTfIKizFzdqIvIfmojwTkcGC3aHKx5o22Xy3+QfR1qr6cGrobMGu2S+w61IsAN+83g5zI11e/uwkmflyhrRzZ/2bHeg67yAhsdnqCvupMDPQYcuk1lyKymLShmtkFZb9eU1U9fPrtOyEynM6NrDhw0GNOXwrtYajfbpisoqYs+eu8nHFn0NYMgpKeXmD6uwivRvZMbi5A1ficmoyxBrxzZwhNKpnz7iF20jOyGNkLz/2r5mI34gVJKXn8c6oLkwe1oEJi38mJimL+ZMC2Lt6PL4jVmjOAC0NJgpXQagFDPR1Gdi1KUNn/sjZ69J69Eu/P0Sfjo2YMLgdi749wLYDUquyq4Pm3rIf28GNlFy5SlH6uPk6yyoUZBb89UIStV1mvmp3hLf7OxGVms/ZUGkZ09aeNsxcf5lrUdICBCt332JyL2+ae1hpXOH6WmcPUnJLmPtr1VRGidmqt+czHroWujWy41J0FgnZmnUbv6JSQXbxowNzKhU8sr2dhyWnIzMp0bAvdQb6Ogzs6sPQ9zZw9oY0UHLpuiPSe+Wgtixae4gpIzry8fpj7DslXTPjFwYRe2A+Azo3ZscRDVicQrMbXEXhKgi1gY62Fjo62pQ81BpQIi+jXfMnn++2tuvsZcv5e5l8OrQJLdwtScuTs/1yAjuvqXaJaOluwR/vdiSvuIxL0dl89UekRq4QBKCrrcWw9u58faCqpe1SRAYvtXHj0I1EcotKecnfDX1dbc6EalYLI0C3hracCc9k1cimtPSwIi2vhG0X4vnlyuOnerI20aOTlw1zfrlVw5E+fU7mBvw02pfSikruphSw/mI86Y/5Alffxoh6tsZ8pSHdJB6ko60tvVfKH/Ne2cwDd0crHGzM+ONShHJfXmEJl2/H4e/jphGFq4bXraJwFYTaoKBIzoWb0cx+rQdh0amkZuUzLMAPfx93IhM0o1/Wk3C2NGBoKyd+Oh/PutMxNHEy473eDSirqGTvn/Nznr2XxbHQdBKzi3GxMmTqC/X56pXmjF53hUoNnPyvb0tnzI302HoqSrlt7Jen+XFqB6LXDqWsvJLi0nJGfX6S6FTNWzHK2dKQEf7ObDwby3cnomnibMac/t6UVSjYff3RPt4v+jpSJK/gyO00NUT79ISlFbDyjygScoqxMtYjsKUTnw5sxBs/36S4TLVVNaChHXFZxYRq4PUgvVfGMHtcd8Ji0qT3yp6++DdxIzIhA3trUwDSsvJVnpeWVUAdK1N1hCz8S6JwFYRaYtz8raydP4KoAwspL6/gRlgi2w9fx9dbs9ae/ztaMhl3kvL48pi0JHBYSgH17EwY0tJZWbgeeqDf4r20QsJTC9j/VntaultyKVqzbpMDvNK5HkeDk0jJqbrtPXdIM8yN9Hhx+VGy8uX0aeHC+jc70ufDI9xJyFFfsE+BlkzGrcQ8Pj98D4DQ5Hw865gw3N/5sYXroJZO7AtO1rh+z1fiqhZOickqJiy1gI2vNKdjPWsO301X7tPTltHF05ptVzVz8QGAcQuDWPvBUKL2z3vgvfIGvt5O6g6tRohZBQRBeCZEJ2bSc9JXGBnoYWasT0pmPpuXjSI6MVPdodWY9Hw5kemFKtui0wvp3tD2L5+TmF1CVmEpLlZGGle4ulgb06WJPaM+P63c5m5nwsSeXrSdtY+7iVIxcysuh7Zetozv0YAZ6y+pK9ynIj1fTmSaasthZHohPRrXeeTYFu4W1LU15p1ttf928D8pLK0gMbcER3MDle0d6lmjr6PFsTDNvVMTnZhJzze+xchAFzNjA+m9ckkg0UlZpGRKLa12VqbK36XHJtyM0IxZWDR9VgGxAIEg1DJFJaWkZOZjYWpI9zbe7DuleX31/kpwfC7u1sYq29ysjUjOfXSA1n12ZvpYGOmSUaB586u+3Lku6XlyDt+oaj0z0pPaIyofWhSxolKhkS0x1+Jy8LBVvSbcrY0fO2hvUAsnbiXkEpaiebfIH2ago4WDmQFZRap9XAO8bbkYk0NuiWb2+X5QUUnZA++VXuw7dZuYpCySM/Lo2qq+8jhTY31aNXblYkisGqMVnpQoXAWhlujexosebb1xc7SiW+sGHPx2MuExaWzaI7WgWZoZ0bSBIw09pCUmG7jZ0bSBI3WsNaff1k/n4/BxNuO1jm64WBnS26cOg1s48fMlaX5GQz1tpveoj4+zGY4WBrT2sOTzEU2Jzyrm3D3NapmWySCwUz2CTkdR8UDn3fDkXCJT8lg1zh+/uta425kwpbc3XZs48PvVhL85Y+206UwsTV3MmdjZA1crQ/o2s2doa2e2XYhTOc5YX5sAH3t+/YtBW7Xd+Lau+DiYYmeqR8M6Jszr1YBKhYKTEVXXvYOZPk0cTTkYqln9ex/W3b8BPdp44eZgSbfWnhz8+nXCY9PYtPcyAF8FnWbW2Bfo27ERjevZ88OCESRn5LHn5O1/OHPtIJNV38+zSHQVEIRawtzEgMVT+uJkZ0FWXhG7/7jJgq9/p7xC6qvXt1Njvl8wUnn85mWjAVjy3SGWfn9ILTFXt9tJ+cz4+SbTXqjPxM4eJGaX8OnBcH4Pkfq1VlYq8KxjQv/mDpga6JCeL+d8ZBZf/RFFWYVmjczq0tgeFxtjfjoZqbK9vELBsE9PsGB4c7a90xljfV2iU/OZvPY8R4I141bog24l5jHtpxtMD/DkjW51Scgu5qN9d9n3Z5/n+/o0tUcG7H9ou6awMdZjVo/6mBnokFtczu3kfKbvvK3SstqzoS0ZBaVci8/9mzPVfuYmBiye3AcnO3PpvfJ4CAu+Oah8r1y5+QRGhnqsmT0ECxMDzgXHMOCtdWIO11pCplAoNOvdXBBqmGGrGeoO4Zng1bevukN4JsTe08zC6N9ycP3rfsfPEzcXc3WH8Mw4seEXdYfwTCi++OlTPX9OcUW1ncvCULvazlVdRFcBQRAEQRAEoVYQXQUEQRAEQRA0hKbPKiAK139h4cKF7Nq1ixs3bjzR8TKZjN9++42BAwc+1bieJSdOnKBr165kZ2djYWFRred+HvNZm5Rr2LyY/6/yMtFPDqBCw/oU/78KNXTFNuHZ9awOqqouonD9F2bOnMmbb775xMcnJydjaam568YLNcvESJ8Fr/dmQJcm2FqaEhyewMyVu7h6Jx6AF7v6MH5QO3y9nbG2MMY/cAU3wzVvMI6dqT4zAjzp0MAaA11t4jKLmLfzDreT8pTH1LU1ZnpPT1p6WKCtpUVUWgFvb7tJyt9Mm1Wb3PpyMG52Jo9s/+7QXd758SIedUxZ+kpL2nrboaejxdHgJGauv0i6hvz9D7Iz0+fd3g3o6GWDoZ42sRlFzNlxi1uJ0vVgpKfNO70b0L2xHRZGuiRkFbP5bCxBFzVvhgUbEz1e7+iGv7slBrpaJOaUsPzQPcIeWCFrXDtX+jepg4mBNiGJ+Xx2LJKEx0wdVpuZGOmzYFIAAzo3wdbShODwRGZ+tpuroVX/5vMm9mTsi/5YmBhy/mYM0z7ZSWS85s5tq0lE4fovmJiYYGLy6IfFX7G3t3+K0QjPm28+GEajeg6MW7CV5PQ8RvZuwf6vXsdv2CckpediZKDHueBofj16g28+GK7ucJ8KMwMdNk9sxaXoLF7feJ3solLcrI3IKylTHuNiZcimCS3ZeTWJr/6IpFBeTj07E0rLq2/Agrp1mbMPLa2qZpVGrpbs/aAnv12IwUhfh11zenArLou+i6XZJOYN92X7ey/Q7YP9aNJwXDNDHba94c/FqCwm/HiN7MJS3GyMyC2uuh7e7+dFm3rWvBt0k8TsYtp72rBgYEPS8uT8EZr+N2evXUz0tflquA/X43N577c75BSV4WxpSP4Dswq83MqJwc0dWH4ogqTcEsa3c2XFoMaM3niNUg1qIf9mzhAa1bNn3MJtJGfkMbKXH/vXTMRvxAqS0vN4Z1QXJg/rwITFPxOTlMX8SQHsXT0e3xErNGJmAQ1vcBWDsx703Xff4ejoSGWl6i3PF198kXHjxrFw4UKaN2+usu/HH3+kcePG6Ovr4+DgwNSpU5X7ZDIZu3btAqC0tJSpU6fi4OCAgYEBbm5uLF++/B9jmjlzJv369VM+/vzzz5HJZBw8eFC5rX79+qxbtw6Ay5cv06NHD2xsbDA3N6dz585cu3ZNeezLL7/M8OGqRU1ZWRk2NjZs2rQJgMrKSpYvX46HhweGhoY0a9aMX375d6NBr169SsuWLTEyMqJdu3aEhYWp7N+9ezd+fn4YGBhQt25dFi1aRHl51RtGREQEnTp1wsDAgEaNGnHkyJFHXuPcuXM0b94cAwMDWrZsya5du5DJZCpdOW7dukXv3r0xMTGhTp06jBo1ioyMqm/Vv/zyCz4+PhgaGmJtbU337t0pLCx85LXUzUBfl4FdmzL3i72cvR5FVEIGS78/RGR8BhMGtwNg24GrLF93mD8uhas52qdnXCd3UnJLmLfzDrcS80jMLuHcvSzis6qWO53WvT6nwzP47FAEd5Pzic8q5sTddLIKy/7mzLVLRr6ctNwS5U8vP2ciU/I4cyeVNl52uNkZ8/rXZ7kTn8Od+BwmfXUGv7rWdG7ioO7Qq9WEzh6k5JYwZ8ctQhJyScgu5mxEpsr14Otmwa5riVyKyiYxu4TtlxK4m5xPUw0b7R/Yypm0fDkfHb5HaEoByXlyLsfmkPRAK/tQX0c2X4znTGQWURlFLD0YgbWJHh3qW6sx8uploK/DwK4+zF2zn7M3oolKyGTpuiNEJmQyYVBbAKaM6MjH64+x79Rtbt1LZvzCIBxszBjQubGao68msmr8eQaJwvUBQ4cOJTMzk+PHjyu3ZWVlcfDgQQIDAx85/ptvvmHKlClMnDiRkJAQ9uzZQ/369R85DuCLL75gz549bN++nbCwMLZs2YK7u/s/xtS5c2fOnDlDRYXUWnTy5ElsbGw4ceIEAImJiURGRtKlSxcA8vPzGTNmDGfOnOHChQt4enrSp08f8vOlpe0CAwPZu3cvBQVVt44OHTpEUVERL730EgDLly9n06ZNfPvtt9y+fZvp06fzyiuvcPLkyX+M9765c+eycuVKrly5go6ODuPGjVPuO336NKNHj+att97izp07rF27lg0bNrB06VJAKpwHDRqEnp4eFy9e5Ntvv2XWrFkq58/Ly6N///74+Phw7do1Pvzww0eOycnJoVu3bvj6+nLlyhUOHjxIamoqw4YNA6SuHCNHjmTcuHGEhoZy4sQJBg0axLM4Q5yOthY6OtqUPNQaUCIvo11zDzVFVfO6ettyOzGPlSOacvL9zuyY7M/gllXrj8tk0MnLhpiMItaO8eXk+53ZOqk13f5mSdjaTldbixEd6vLT8XsA6OtooVCAvKyqhbmkrIJKhYK2XnbqCvOp6NbIjlsJuawObMa5eV34bVpbhrZ2VjnmemwO3RraYWemD4B/XSs8bI05E6FZC1K0r2dFWGohi/p5sfv1Vqx7pRn9fKqWvXUw18faRI8rcVVzuBaWVhCakk8TB81ZpERHW1t6r5Q/5r2ymQfujlY42Jjxx6UI5b68whIu347D38etpsMV/g+iq8ADLC0t6d27N1u3buWFF14ApBY5GxsbunbtyunTp1WOX7JkCe+88w5vvfWWclurVq0ee+64uDg8PT3p0KEDMpkMN7cn+x+kY8eO5Ofnc/36dVq0aMGpU6d49913lS25J06cwMnJSVkwd+vWTeX53333HRYWFpw8eZJ+/foREBCAsbExv/32G6NGjQJg69atDBgwAFNTU+RyOcuWLePo0aO0bSt9O61bty5nzpxh7dq1dO7c+YniXrp0qfLY999/n759+1JSUoKBgQGLFi3i/fffZ8yYMcrzf/jhh7z33nssWLCAo0ePcvfuXQ4dOoSjoyMAy5Yto3fv3srzb926FZlMxvfff69slU1MTGTChAnKY9asWYOvry/Lli1Tbvvxxx9xcXEhPDycgoICysvLGTRokPLfw8fH52//LrlcjlyuunSoorIcmdbT/V+poEjOhZvRzH6tB2HRqaRm5TMswA9/H3ciE56fflnOloYMb+3MpnNxfH8ymiZOZszu60VZRSV7ridjZayHsb4Or3Xy4Muj9/jsUAQdGtjw+chmjPvxKldistX9J1S7fq1cMDfW46eTUuF6OSKdQnk5iwNbsGjbNWQyGYte9kNHWwt7S0M1R1u9XKwMGdnGhfWnY/n2eBQ+zuZ8MMCbsvJKdl2T+nd/uDuUDwc35vTcLpRVVKJQwAe/3uZKtGZdCw7mBrzYzJ7tVxP56WIC3vYmvNXVg/KKSg7eScfaSA+A7IeWgM0qLMPKWE8dIT8V0ntlDLPHdScsJk16r+zpi38TNyITMrD/cyXBtKx8leelZRVQx0ozCnhNn1VAtLg+JDAwkF9//VVZnGzZsoURI0agpaWaqrS0NJKSkpQF7j959dVXuXHjBl5eXkybNo3Dhw8/0fMsLCxo1qwZJ06cICQkBD09PSZOnMj169cpKCjg5MmTKsVkamoqEyZMwNPTE3Nzc8zMzCgoKCAuTlr+UEdHh2HDhrFlyxYACgsL2b17t7JF+d69exQVFdGjRw9ln14TExM2bdpEZGTkowH+haZNmyp/d3CQbk+mpUnLDAYHB7N48WKV80+YMIHk5GSKiooIDQ3FxcVFWbQCyiL6vrCwMJo2bYqBgYFyW+vWrVWOCQ4O5vjx4yqv4+3tDUBkZCTNmjXjhRdewMfHh6FDh/L999+Tnf33H2bLly/H3Nxc5ac8+fIT5+W/GDdfKtajDiwk9+wnTBneke2Hr1NZ+ey1ED8tWjIZocn5rD5yj7vJ+fxyJZFfryQyrJWzcj/A8dA0Np+LIyylgB9OxXAyLINhD7XEaYrR3Tw5ciORlGzp9nhGvpzRq07S28+FlI2BJK4fibmRHtejMqnUsIkfZDIZt5PyWHUogtCkfLZfSmD7pQRGtHFRHjOqvRvNXS14fcM1Bn9xno/2hbFgYEPa1rdSY+TVT0sGEWkFfH82joj0QvaGpLI3JJUBTZ+/sRbjFgYhk0HU/nnknl7OlGHt2X74xnPzXimWfH3O9O/fH4VCwf79+2nVqhWnT59m1apVjxxnaPjvWi78/PyIjo7mwIEDHD16lGHDhtG9e/cn6jvapUsXTpw4gb6+Pp07d8bKyoqGDRty5swZTp48yTvvvKM8dsyYMWRmZrJ69Wrc3NzQ19enbdu2lJZWfcsODAykc+fOpKWlceTIEQwNDenVqxeAsgvB/v37cXJyUolDX1//if9eXV1d5e+yP6/++32HCwoKWLRoEYMGDXrkeQ8Wov9VQUEB/fv35+OPP35kn4ODA9ra2hw5coRz585x+PBhvvzyS+bOncvFixfx8Hj87ffZs2czY4bqSll2XT+otpj/TnRiJj0nfYWRgR5mxvqkZOazedkoohM165bn30kvkBOZptoHOSq9kO6NpVvg2UWllFVUEpn+8DEF+Llp3gwfLjbGdPVxIHDlCZXtf9xMotlbO7E21ae8opLcojLurR3Gr2n5jz9RLZWeLycy9aF/67RCAppIt8j1dbSYHuDJ1M3XOXlXujMRllJAQ0dTXuvkwfl7WTUe89OSWVhKTGaxyrbYzGI6e0r9VzP/bGm1NNIj84H+3lbGutxLe/b69f8X0YmZ9HzjW4wMdDEzNpDeK5cEEp2URUqm9P+AnZWp8nfpsQk3IzRvFhZNJArXhxgYGDBo0CC2bNnCvXv38PLyws/P75HjTE1NcXd359ixY3Tt2vWJzm1mZsbw4cMZPnw4Q4YMoVevXmRlZWFl9fff/Dt37syPP/6Ijo6OssDs0qUL27ZtIzw8XNm/FeDs2bN8/fXX9OnTB4D4+HiVwUgA7dq1w8XFhZ9//pkDBw4wdOhQZaHZqFEj9PX1iYuLe+JuAf+Wn58fYWFhf9kfuGHDhsTHx5OcnKxsrb1w4YLKMV5eXvz000/I5XJlQX35smrLp5+fH7/++ivu7u7o6Dz+UpfJZLRv35727dszf/583Nzc+O233x4pTu/T19d/pIB/2t0EHlZUUkpRSSkWpoZ0b+PN3C/31ujrq9P12BzcbYxUtrlZG5H853Q+5RUKbifm4fHQMe42xiTlqH6oa4JXutQnPbeEg9ceP7VTZr5056hTY3tszQz4/Up8TYb31F2LycHD1lhlm7uNEYl//lvraMvQ+7PP74MqFIpntjXp/xWSlI+LpeoXfxdLQ1LzpGsgOVdOZkEpLVzNuffnFzsjPW0a2puyK1gzlykuKimjqKTsz/dKL+au2U9MUhbJGXl0bVVfWaiaGuvTqrEr3+88r+aIq4eGXdqPEIXrYwQGBtKvXz9u377NK6+88pfHLVy4kNdffx07Ozt69+5Nfn4+Z8+efexcr5999hkODg74+vqipaXFjh07sLe3f6JJ+jt16kR+fj779u3jo48+AqTCdciQITg4ONCgQQPlsZ6enmzevJmWLVuSl5fHu++++9jW4Zdffplvv/2W8PBwlcFopqamzJw5k+nTp1NZWUmHDh3Izc3l7NmzmJmZKful/hfz58+nX79+uLq6MmTIELS0tAgODubWrVssWbKE7t2706BBA8aMGcOnn35KXl4ec+fOfST+uXPnMnHiRN5//33i4uJYsWIFUNXCO2XKFL7//ntGjhzJe++9h5WVFffu3SMoKIh169Zx5coVjh07Rs+ePbGzs+PixYukp6fTsGHD//w3Pg3d23ghk8kIj02jnrMNy97qT3hMGpv2XALA0swIF3sLHGyk0dIN3KRWyNTMfFIzNaOlbfO5ODZPbMWEzu4cDEnFx9mcIa2cWbT7jvKY9adjWDG8KVdicrgUlUUHTxs6e9kw9seraoy8+slkUuG69WQkFQ/dAn2lS33CEnPIyJPT2tOWT15txVe/3yEiOe8vzlY7bTwTw7bJ/kzq6sGBm6k0dTFnmL8z83+VrodCeQUXI7N4t08DSsoqSMouoVVdSwb6OfLRvrB/OHvtsuNqEl+P8OGV1s4cD8+gob0J/ZvWYcWRqi5eO64nMdrfhYTsEpLzSnitnSuZBaWcuadZd226+zeoeq90sWHZm/0Ij01j016pceOroNPMGvsC9+IziEnKYsGkAJIz8thz8raaI68mGl65isL1Mbp164aVlRVhYWG8/PLLf3ncmDFjKCkpYdWqVcycORMbGxuGDBny2GNNTU355JNPiIiIQFtbm1atWvH7778/0nf2cSwtLfHx8SE1NVXZR7NTp05UVlY+0ir6ww8/MHHiRPz8/HBxcWHZsmXMnDnzkXMGBgaydOlS3NzcaN++vcq+Dz/8EFtbW5YvX05UVBQWFhb4+fkxZ86cf4z1SQQEBLBv3z4WL17Mxx9/jK6uLt7e3owfPx4ALS0tfvvtN1577TVat26Nu7s7X3zxhbK1GaTW67179/LGG2/QvHlzfHx8mD9/Pi+//LKyu4GjoyNnz55l1qxZ9OzZE7lcjpubG7169UJLSwszMzNOnTrF559/Tl5eHm5ubqxcuVJlENizxNzEgMVT+uJkZ0FWXhG7/7jJgq9/p7xC6oLRt1Njvl8wUnn85mWjAVjy3SGWfn9ILTFXt1uJeby9NZi3etTn9S51Scwu5uPfw9j/QIvRsdB0Fu8JZXwnD2b39SImo4jp225yPTZHfYE/BV19HHG1NWHziXuP7PN0MGPhSD8sTfSISyvg099CWLP/zmPOUruFJOQxddMNZvTyZMoL9UjILmbZ3jD23khWHjNjazAzejdgxYimmBvpkpRdzKpDEWy7oFmtz3dTC5i75y6TOroxpo0LKbklfHkimiN3q+aq3Xo5EQNdbWb2qIeJvg4hiXnM3Hlbo+ZwhT/fKyf3wcnOXHqvPB7Cgm8OKt8rV24+gZGhHmtmD8HCxIBzwTEMeGudRszhCpo/OEumeBbn/hGE/8OWLVsYO3Ysubm5/7oP8n9h2Orx3QqeN/UCns2Cv6bFin5yADi6P3+Dgh6nTp0nX7RG013+eZe6Q3gmFF/89OmevxqnrDbU/edjappocRVqrU2bNlG3bl2cnJwIDg5m1qxZDBs2rEaLVkEQBEF4lmha/+1HKAS1+umnnxTGxsaP/WnUqJG6w3vEpEmT/jLeSZMm1WgsH3/8scLNzU2hr6+vcHd3V7z99tuKwsLCGo3hWVBSUqJYsGCBoqSkRN2hqJXIg0TkQSLyIBF5qCJyoRlEVwE1y8/PJzU19bH7dHV1n3ihgpqSlpZGXt7jB3iYmZlhZ6dZK/PUBnl5eZibm5Obm4uZmZm6w1EbkQeJyINE5EEi8lBF5EIziK4CamZqaoqpae1ZrcPOzk4Up4IgCIIgqIVYOUsQBEEQBEGoFUThKgiCIAiCINQKonAVhFpOX1+fBQsW/KsleTWRyINE5EEi8iAReagicqEZxOAsQRAEQRAEoVYQLa6CIAiCIAhCrSAKV0EQBEEQBKFWEIWrIAiCIAiCUCuIwlUQBEEQBEGoFUThKgiCIGik6OhoysvL1R2G8IwQ14JmEIWrIGiIyMhIunXrpu4wakxycjI//fQTv//+O6WlpSr7CgsLWbx4sZoiq1lHjhxhwYIF/PHHHwCcOnWK3r17061bN9avX6/m6NTLy8uLiIgIdYehNklJSSxYsIDAwEBmzpzJ3bt31R1SjTh48CAhISEAVFZW8uGHH+Lk5IS+vj7Ozs589NFHiAmVai8xHZYgaIjg4GD8/PyoqKhQdyhP3eXLl+nZsyeVlZWUlZXh5OTErl27aNy4MQCpqak4OjpqfC5++uknxo4dS9OmTQkPD+fLL79k+vTpDBkyhMrKSn766Se2bNnCkCFD1B3qUzVo0KDHbt+9ezfdunVTLqu9c+fOmgyrxhkZGREbG4utrS137tyhXbt22Nra4uvrS0hICHFxcZw/f56mTZuqO9Snytvbm++//56OHTuyfPlyVq5cydy5c2nYsCFhYWEsX76c6dOnM2vWLHWHKvwfROEqCLXEF1988bf7ExMTWbFihcYXawA9evTAxcWFdevWUVhYyKxZs9i+fTtHjhzB19f3uSlcfX19GTt2LNOmTePYsWP079+fpUuXMn36dABWrlzJb7/9xpkzZ9Qc6dOlpaVFp06d8PDwUNm+adMmBgwYgIWFBYDGt0BraWmRkpKCnZ0dAwcOpLKykp07d6Kjo0NlZSWBgYEUFBSwd+9edYf6VBkYGBAeHo6rqys+Pj7Mnz+foUOHKvfv37+ft99++7luja/NROEqCLWElpYWDg4O6OnpPXZ/aWkpKSkpGl+sAVhZWXHhwgUaNGig3PbRRx/xySefcOjQIVxdXZ+LwtXExISQkBBlwaanp8eVK1eULWp3796lQ4cOZGRkqDPMpy4oKIh3332XxYsXM3bsWOV2XV1dgoODadSokRqjqzkPFq6urq5s2bKFjh07Kvdfv36dvn37kpSUpMYonz5HR0d27txJmzZtsLe358CBA/j6+ir3R0RE0KxZM4qKitQYpfD/En1cBaGWcHNzY9WqVURHRz/2Z//+/eoOsUaVlJSoPH7//feZM2cOPXv25Ny5c2qKqmbp6uqq9O/V19fHxMRE5XFxcbE6QqtRI0aM4PTp0/zwww8MHjyY7OxsdYekFjKZDJlMBkhFrLm5ucp+CwuL5yI3L730EkuXLqWiooIXX3yRr7/+WqVP65dffknz5s3VF6Dwn4jCVRBqiRYtWnD16tW/3C+TyZ6bAQdNmjR5bHE6c+ZMZs+ezciRI9UQVc2rX7++yoCbxMREldvlkZGRODs7qyO0Gufu7s6pU6do0qQJzZo149ChQ8oi7nmhUCho0KABVlZWJCUlcfPmTZX99+7dw97eXk3R1Zxly5aRkpKCt7c3xcXF/PTTT3h4eNCzZ0/q1q3Lpk2bWLVqlbrDFP5POuoOQBCEJ7N48eK/vbXVqFEjoqOjazAi9Rk9ejQnT57k9ddff2Tfe++9h0Kh4Ntvv1VDZDVrzpw5WFpaKh+bmZmp7L9y5QrDhg2r6bDURktLi0WLFtGjRw9Gjx6t8V1FHvZwH9769eurPL5w4QIvvfRSTYakFubm5pw7d44ffviBvXv34u7uTmVlJaWlpYwcOZI33njjuflCp4lEH1dBEARB4xQUFBAZGUnDhg3/sl+4IAi1jyhcBUEQBEEQhFpB9HEVBEEQBEEQagVRuAqCIAiCIAi1gihcBUEQBEEQhFpBFK6CUIs9PJfp80zkQiLyIBF5kIg8SEQeNIcoXAWhlqmsrOTDDz/EyckJExMToqKiAJg3bx4//PCDmqOrWSIXEpEHiciDRORBIvKgmUThKgi1zJIlS9iwYQOffPKJyjQ/TZo0Yd26dWqMrOaJXEhEHiQiDxKRB4nIg4ZSCIJQq9SrV09x9OhRhUKhUJiYmCgiIyMVCoVCERoaqrCwsFBnaDVO5EIi8iAReZCIPEhEHjSTaHEVhFomMTHxkRVxQLotVlZWpoaI1EfkQiLyIBF5kIg8SEQeNJMoXAWhlmnUqBGnT59+ZPsvv/yCr6+vGiJSH5ELiciDRORBIvIgEXnQTDrqDkAQhH9n/vz5jBkzhsTERCorK9m5cydhYWFs2rSJffv2qTu8GiVyIRF5kIg8SEQeJCIPGkrdfRUEQfj3Tp06pejevbvC1tZWYWhoqGjfvr3i0KFD6g5LLUQuJCIPEpEHiciDRORB88gUCoVC3cWzIAiCIAiCIPwT0cdVEARBEARBqBVEH1dBqAUsLS2RyWRPdGxWVtZTjka9RC4kIg8SkQeJyINE5EHzicJVEGqBzz//XN0hPDNELiQiDxKRB4nIg0TkQfOJPq6CIAiCIAhCrSBaXAWhFsjLy8PMzEz5+9+5f5ymErmQiDxIRB4kIg8SkQfNJ1pcBaEW0NbWJjk5GTs7O7S0tB7bh0uhUCCTyaioqFBDhDVH5EIi8iAReZCIPEhEHjSfaHEVhFrgjz/+wMrKCoDjx4+rORr1ErmQiDxIRB4kIg8SkQfNJ1pcBaGWiYuLw8XF5ZGWBIVCQXx8PK6urmqKrOaJXEhEHiQiDxKRB4nIg2YShasg1DIP3gp7UGZmJnZ2ds/V7S+RC4nIg0TkQSLyIBF50ExiAQJBqGXu9896WEFBAQYGBmqISH1ELiQiDxKRB4nIg0TkQTOJPq6CUEvMmDEDAJlMxrx58zAyMlLuq6io4OLFizRv3lxN0dUskQuJyINE5EEi8iARedBsonAVhFri+vXrgNSKEBISgp6ennKfnp4ezZo1Y+bMmeoKr0aJXEhEHiQiDxKRB4nIg2YTfVwFoZYZO3Ysq1evFnMQInJxn8iDRORBIvIgEXnQTKJwFQRBEARBEGoF0VVAEGqZwsJCPvroI44dO0ZaWhqVlZUq+6OiotQUWc0TuZCIPEhEHiQiDxKRB80kCldBqGXGjx/PyZMnGTVqFA4ODo8dNfu8ELmQiDxIRB4kIg8SkQfNJLoKCEItY2Fhwf79+2nfvr26Q1E7kQuJyINE5EEi8iARedBMYh5XQahlLC0tlUsaPu9ELiQiDxKRB4nIg0TkQTOJwlUQapkPP/yQ+fPnU1RUpO5Q1E7kQiLyIBF5kIg8SEQeNJPoKiAItYyvry+RkZEoFArc3d3R1dVV2X/t2jU1RVbzRC4kIg8SkQeJyINE5EEzicFZglDLDBw4UN0hPDNELiQiDxKRB4nIg0TkQTOJFldBEARBEAShVhB9XAVBEARBEIRaQXQVEIRapqKiglWrVrF9+3bi4uIoLS1V2Z+VlaWmyGqeyIVE5EEi8iAReZCIPGgm0eIqCLXMokWL+Oyzzxg+fDi5ubnMmDGDQYMGoaWlxcKFC9UdXo0SuZCIPEhEHiQiDxKRBw2lEAShVqlbt65i3759CoVCoTAxMVHcu3dPoVAoFKtXr1aMHDlSnaHVOJELiciDRORBIvIgEXnQTKLFVRBqmZSUFHx8fAAwMTEhNzcXgH79+rF//351hlbjRC4kIg8SkQeJyINE5EEzicJVEGoZZ2dnkpOTAahXrx6HDx8G4PLly+jr66sztBonciEReZCIPEhEHiQiD5pJFK6CUMu89NJLHDt2DIA333yTefPm4enpyejRoxk3bpyao6tZIhcSkQeJyINE5EEi8qCZxDyuglDLnT9/nvPnz+Pp6Un//v3VHY5aiVxIRB4kIg8SkQeJyINmEIWrIAiCIAiCUCuIeVwFoZbZtGnT3+4fPXp0DUWifiIXEpEHiciDRORBIvKgmUSLqyDUMpaWliqPy8rKKCoqQk9PDyMjo+dqUm2RC4nIg0TkQSLyIBF50ExicJYg1DLZ2dkqPwUFBYSFhdGhQwe2bdum7vBqlMiFRORBIvIgEXmQiDxoJtHiKgga4sqVK7zyyivcvXtX3aGonciFRORBIvIgEXmQiDzUbqLFVRA0hI6ODklJSeoO45kgciEReZCIPEhEHiQiD7WbGJwlCLXMnj17VB4rFAqSk5NZs2YN7du3V1NU6iFyIRF5kIg8SEQeJCIPmkl0FRCEWkZLS/VGiUwmw9bWlm7durFy5UocHBzUFFnNE7mQiDxIRB4kIg8SkQfNJApXQRAEQRAEoVYQfVwFoZbKyMggLy9P3WE8E0QuJCIPEpEHiciDRORBs4jCVRBqkZycHKZMmYKNjQ116tTB0tISe3t7Zs+eTVFRkbrDq1EiFxKRB4nIg0TkQSLyoLlEVwFBqCWysrJo27YtiYmJBAYG0rBhQwDu3LnD1q1b8fb25syZM9y8eZMLFy4wbdo0NUf89IhcSEQeJCIPEpEHiciDhlMIglArvPXWW4omTZooUlJSHtmXnJys8PHxUQwZMkRhZmam2LBhgxoirDkiFxKRB4nIg0TkQSLyoNlE4SoItYSbm5vi4MGDf7n/wIEDCplMpli4cGENRqUeIhcSkQeJyINE5EEi8qDZRFcBQagl9PX1iYyMxNnZ+bH7ExIScHd3p7y8vIYjq3kiFxKRB4nIg0TkQSLyoNnE4CxBqCVsbGyIiYn5y/3R0dHY2dnVXEBqJHIhEXmQiDxIRB4kIg+aTRSuglBLBAQEMHfuXEpLSx/ZJ5fLmTdvHr169VJDZDVP5EIi8iAReZCIPEhEHjSb6CogCLVEQkICLVu2RF9fnylTpuDt7Y1CoSA0NJSvv/4auVzO5cuXcXV1VXeoT53IhUTkQSLyIBF5kIg8aDh1da4VBOHfi4qKUvTq1UuhpaWlkMlkCplMptDS0lIEBAQoIiIi1B1ejRK5kIg8SEQeJCIPEpEHzSVaXAWhFsrOziYiIgKA+vXrY2VlpeaI1EfkQiLyIBF5kIg8SEQeNI8oXAVBEARBEIRaQQzOEgRBEARBEGoFUbgKgiAIgiAItYIoXAVBEARBEIRaQRSugiAIgiAIQq0gCldBEARBEAShVhCFqyAIgiAIglAriMJVEARBEARBqBVE4SoIgiAIgiDUCv8DQShUdT/av9UAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.heatmap(\n",
+    "    ensemble_clf.quantile_scores_df_.drop_duplicates(), annot=True, cmap=\"Blues\"\n",
+    ")\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "authorship_tag": "ABX9TyM7Z9RCnKuC6XRx+E5OPsey",
+   "include_colab_link": true,
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/tutorial.rst b/docs/tutorial.rst
new file mode 100644
index 0000000..bb5ed9d
--- /dev/null
+++ b/docs/tutorial.rst
@@ -0,0 +1,9 @@
+   .. _tutorial:
+
+   Tutorial
+   ========
+
+   .. toctree::
+      :maxdepth: 2
+
+   .. nbsphinx:: tutorial.ipynb
\ No newline at end of file