3716 lines
934 KiB
Plaintext
3716 lines
934 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "f756c5c5",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"# Lecture 19: Unsupervised learning"
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]
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},
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{
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"cell_type": "markdown",
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"id": "05e057af",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"source": [
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"\n",
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"[Run in colab](https://colab.research.google.com/drive/1N2lOE8YOXNuekxMtflQCB3eM3I6Bx7-w)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "bd0c5278",
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"metadata": {
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"editable": true,
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"execution": {
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"iopub.execute_input": "2025-03-07T05:32:18.896747Z",
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"iopub.status.busy": "2025-03-07T05:32:18.896515Z",
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"iopub.status.idle": "2025-03-07T05:32:18.902967Z",
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"shell.execute_reply": "2025-03-07T05:32:18.902404Z"
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},
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Last executed: 2025-03-07 05:32:18\n"
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]
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}
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],
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"source": [
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"import datetime\n",
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"now = datetime.datetime.now()\n",
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"print(\"Last executed: \" + now.strftime(\"%Y-%m-%d %H:%M:%S\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fa389c67-03a7-46cc-b849-7963cd86ebc9",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "slide"
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},
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"tags": []
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},
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"source": [
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"## Unsupervised learning overview"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d792ecf7-e0dd-4a17-a021-7cec1e0d5f83",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "subslide"
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},
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"tags": []
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},
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"source": [
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"### Labelled data is scarce\n",
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"\n",
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"The majority of data is unlabeled: we have input features $\\mathbf{X}$, but no labels $\\mathbf{y}$."
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]
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},
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{
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"cell_type": "markdown",
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"id": "01ba1b5a-00a3-443c-aad2-3b01d0a90b3e",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"source": [
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"Imagine that you want to detect defective items on a manufacturing line. You can collect images of the items on the manufacturing line easily and automatically, but if you want to train a classifier to predict whether an item is defective or not, you will need to label every image.\n",
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"\n",
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"This labelling generally requires human experts to sit down and go through the images by hand, which is time consuming, tedious, and prone to errors. As a result, labelling is often only done on a small subset of the available images.\n",
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"\n",
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"With unsupervised learning, you do not need labelled data!"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9b67f95a-003a-4d7e-9138-bff388491356",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "subslide"
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},
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"tags": []
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},
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"source": [
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"### Types of unsupervised learning\n",
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"\n",
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"We will cover three types of unsupervised learning.\n",
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"\n",
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"1. *Clustering*: Group similar data instances into clusters.\n",
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"2. *Density estimation*: Estimate the probability distribution of data (for use as a generative model to generate new data instances or to estimate probability densities).\n",
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"3. *Anomaly detection*: Detect anomalous data."
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]
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},
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{
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"cell_type": "markdown",
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"id": "f1aedd59-5c76-4866-ae55-0745009652fe",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "slide"
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},
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"tags": []
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},
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"source": [
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"## Clustering with K-means"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d879db6b",
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": "slide"
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},
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"tags": []
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},
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"source": [
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"### Clustering overview\n",
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"\n",
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"*Clustering* is the task of identifying similar instances and assigning them to *clusters*, or groups of similar instances.\n",
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"\n",
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"Consider the Iris dataset, which classifies each instance into one of three classes:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "43b2f3d8",
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"metadata": {
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"editable": true,
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"execution": {
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"iopub.execute_input": "2025-03-07T05:32:18.905064Z",
|
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"iopub.status.busy": "2025-03-07T05:32:18.904894Z",
|
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"iopub.status.idle": "2025-03-07T05:32:19.276111Z",
|
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"shell.execute_reply": "2025-03-07T05:32:19.275469Z"
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},
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"slideshow": {
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"slide_type": "skip"
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"%matplotlib inline\n",
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"import matplotlib\n",
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"import matplotlib.pyplot as plt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "a4916a09",
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"metadata": {
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"editable": true,
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"execution": {
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"iopub.execute_input": "2025-03-07T05:32:19.278360Z",
|
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"iopub.status.busy": "2025-03-07T05:32:19.278122Z",
|
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"iopub.status.idle": "2025-03-07T05:32:20.063169Z",
|
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"shell.execute_reply": "2025-03-07T05:32:20.062447Z"
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},
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array(['setosa', 'versicolor', 'virginica'], dtype='<U10')"
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]
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},
|
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"execution_count": 3,
|
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"metadata": {},
|
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"output_type": "execute_result"
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}
|
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],
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"source": [
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"from sklearn.datasets import load_iris\n",
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"\n",
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"data = load_iris()\n",
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"X = data.data\n",
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"y = data.target\n",
|
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"data.target_names"
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]
|
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},
|
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{
|
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"cell_type": "markdown",
|
|
"id": "b7e3dedd",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
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"slide_type": "subslide"
|
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},
|
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"tags": []
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},
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"source": [
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"Let's plot the petal width against the petal length, both with and without different markers for the classes:"
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]
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},
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{
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"cell_type": "code",
|
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"execution_count": 4,
|
|
"id": "010507ab",
|
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"metadata": {
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"editable": true,
|
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"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.065475Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.065147Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.220141Z",
|
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"shell.execute_reply": "2025-03-07T05:32:20.219437Z"
|
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},
|
|
"scrolled": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
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"tags": []
|
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},
|
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 900x350 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(9, 3.5))\n",
|
|
"\n",
|
|
"plt.subplot(121)\n",
|
|
"plt.plot(X[y==0, 2], X[y==0, 3], \"yo\", label=\"Iris setosa\")\n",
|
|
"plt.plot(X[y==1, 2], X[y==1, 3], \"bs\", label=\"Iris versicolor\")\n",
|
|
"plt.plot(X[y==2, 2], X[y==2, 3], \"g^\", label=\"Iris virginica\")\n",
|
|
"plt.xlabel(\"Petal length\", fontsize=14)\n",
|
|
"plt.ylabel(\"Petal width\", fontsize=14)\n",
|
|
"plt.legend(fontsize=12)\n",
|
|
"\n",
|
|
"plt.subplot(122)\n",
|
|
"plt.scatter(X[:, 2], X[:, 3], c=\"k\", marker=\".\")\n",
|
|
"plt.xlabel(\"Petal length\", fontsize=14)\n",
|
|
"plt.tick_params(labelleft=False)\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c34d799b",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"When the instances are plotted without different markers to differentiate the classes, as in the figure on the right, it is not obvious that the upper-right cluster is composed of two distinct sub-clusters."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ade9d090",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"There is no universal definition of what a cluster is. It depends on the context: different algorithms will capture different kinds of clusters.\n",
|
|
"\n",
|
|
"Some algorithms look for instances centered around a particular point, called a *centroid*. Others look for continuous regions of densely packed instances."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "dddd23bc-a156-4ae1-bd94-5da2129779d7",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### K-means clustering overview"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3c73d2a5-ec56-4ea6-a496-10f66084984f",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Cluster data into different subsets. \n",
|
|
"\n",
|
|
"First, let's consider how K-means represents clusters, then we'll consider the algorithm to find clusters.\n",
|
|
"\n",
|
|
"- Each cluster is defined by a centroid.\n",
|
|
"- Each data instance is allocated a cluster (equivalently, associated with a centroid)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "258dfb21",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Let's generate some blobs to use as a dataset, and run the K-Means algorithm for 1, 2, and 3 iterations to see how the centroids move around:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "52682b37-a58a-4647-9b52-2ec50a4ed106",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.222313Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.222127Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.308963Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.308289Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"from sklearn.cluster import KMeans\n",
|
|
"from sklearn.datasets import make_blobs\n",
|
|
"blob_centers = np.array([[ 0.2, 2.3], [-1.5 , 2.3], [-2.8, 1.8],\n",
|
|
" [-2.8, 2.8], [-2.8, 1.3]])\n",
|
|
"blob_std = np.array([0.4, 0.3, 0.1, 0.1, 0.1])\n",
|
|
"X, y = make_blobs(n_samples=2000, centers=blob_centers, cluster_std=blob_std,\n",
|
|
" random_state=7)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "0d70af36-80ec-460d-b2ef-6f47b656dde7",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Now let's plot them:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"id": "d6ea16db-a3a4-4c10-bc45-c4e312ce118f",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.311254Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.311003Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.452710Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.451956Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def plot_clusters(X, y=None):\n",
|
|
" plt.scatter(X[:, 0], X[:, 1], c=y, s=1)\n",
|
|
" plt.xlabel(\"$x_1$\")\n",
|
|
" plt.ylabel(\"$x_2$\", rotation=0)\n",
|
|
"\n",
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plot_clusters(X)\n",
|
|
"plt.gca().set_axisbelow(True)\n",
|
|
"plt.grid()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d8cb1420-daa7-4e6c-8439-780eb9ee4b20",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Cluster with Scikit-Learn K-means"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4b3bb454-6d2a-4d6c-823f-a6481ace87a8",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Must set number of clusters to consider."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"id": "9b1a11fe-7599-469f-ba66-8aec5bd5e464",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.455045Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.454858Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.516904Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.516260Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"k = 5\n",
|
|
"kmeans = KMeans(n_clusters=k, n_init=10, random_state=42)\n",
|
|
"y_pred = kmeans.fit_predict(X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "263eeb26-1ef1-408b-828e-027b12b5e65a",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Each instance assigned to one of the five clusters:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "473e5159-d2e4-460f-9369-8a4ddd660d64",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.520073Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.519823Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.526424Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.525803Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([0, 0, 4, ..., 3, 1, 0], dtype=int32)"
|
|
]
|
|
},
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"y_pred"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "f4ea4e83-42f4-438f-b05d-32d86e099b28",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"A *centroid* is estimated for each cluster (i.e., cluster centers). "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"id": "f166dd90-cb2a-4344-83d9-24428a788a16",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.528872Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.528668Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.535050Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.534458Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[-2.80214068, 1.55162671],\n",
|
|
" [ 0.08703534, 2.58438091],\n",
|
|
" [-1.46869323, 2.28214236],\n",
|
|
" [-2.79290307, 2.79641063],\n",
|
|
" [ 0.31332823, 1.96822352]])"
|
|
]
|
|
},
|
|
"execution_count": 9,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"kmeans.cluster_centers_"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "403c4770-d2c2-489c-a399-ebf9d88b8f63",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.538443Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.537552Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.543515Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.542928Z"
|
|
},
|
|
"scrolled": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def plot_centroids(centroids, weights=None, circle_color='w', cross_color='k'):\n",
|
|
" if weights is not None:\n",
|
|
" centroids = centroids[weights > weights.max() / 10]\n",
|
|
" plt.scatter(centroids[:, 0], centroids[:, 1],\n",
|
|
" marker='o', s=35, linewidths=8,\n",
|
|
" color=circle_color, zorder=10, alpha=0.9)\n",
|
|
" plt.scatter(centroids[:, 0], centroids[:, 1],\n",
|
|
" marker='x', s=2, linewidths=12,\n",
|
|
" color=cross_color, zorder=11, alpha=1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"id": "cc0d3c9d-01ba-4bf4-a619-b6aaa58ce4c1",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.546972Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.546031Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.698656Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.697966Z"
|
|
},
|
|
"scrolled": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plot_clusters(X)\n",
|
|
"plot_centroids(kmeans.cluster_centers_)\n",
|
|
"plt.gca().set_axisbelow(True)\n",
|
|
"plt.grid()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "85d52600-bd88-42a3-ab87-534bd5aaf799",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Predictions\n",
|
|
"\n",
|
|
"Can make predictions for new instances:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "4aaa517b-6e61-4420-a67a-eaa6f5b5e4a3",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.700640Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.700446Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.703441Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.702851Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": "skip"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"id": "7dd1bbaa-2397-4bd2-b498-1015bbb12d51",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.705280Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.705104Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.710360Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.709768Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([4, 4, 3, 3], dtype=int32)"
|
|
]
|
|
},
|
|
"execution_count": 13,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"X_new = np.array([[0, 2], [3, 2], [-3, 3], [-3, 2.5]])\n",
|
|
"kmeans.predict(X_new)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "475155e2-673a-4621-85de-c75110cba1eb",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Decision boundaries"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "e13f0010-97f7-4f01-9587-849b86d200ff",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Let's plot the model's decision boundaries. This gives us a _Voronoi diagram_:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"id": "9dd5caf8-5690-4205-bec6-273d580d4bdf",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.712259Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.712086Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:20.996132Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:20.995470Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def plot_data(X):\n",
|
|
" plt.plot(X[:, 0], X[:, 1], 'k.', markersize=2)\n",
|
|
"\n",
|
|
"def plot_decision_boundaries(clusterer, X, resolution=1000, show_centroids=True,\n",
|
|
" show_xlabels=True, show_ylabels=True):\n",
|
|
" mins = X.min(axis=0) - 0.1\n",
|
|
" maxs = X.max(axis=0) + 0.1\n",
|
|
" xx, yy = np.meshgrid(np.linspace(mins[0], maxs[0], resolution),\n",
|
|
" np.linspace(mins[1], maxs[1], resolution))\n",
|
|
" Z = clusterer.predict(np.c_[xx.ravel(), yy.ravel()])\n",
|
|
" Z = Z.reshape(xx.shape)\n",
|
|
"\n",
|
|
" plt.contourf(Z, extent=(mins[0], maxs[0], mins[1], maxs[1]),\n",
|
|
" cmap=\"Pastel2\")\n",
|
|
" plt.contour(Z, extent=(mins[0], maxs[0], mins[1], maxs[1]),\n",
|
|
" linewidths=1, colors='k')\n",
|
|
" plot_data(X)\n",
|
|
" if show_centroids:\n",
|
|
" plot_centroids(clusterer.cluster_centers_)\n",
|
|
"\n",
|
|
" if show_xlabels:\n",
|
|
" plt.xlabel(\"$x_1$\")\n",
|
|
" else:\n",
|
|
" plt.tick_params(labelbottom=False)\n",
|
|
" if show_ylabels:\n",
|
|
" plt.ylabel(\"$x_2$\", rotation=0)\n",
|
|
" else:\n",
|
|
" plt.tick_params(labelleft=False)\n",
|
|
"\n",
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plot_decision_boundaries(kmeans, X)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3c8361ca-5628-425d-a00b-1d5aee46f941",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Typically, each data instance is asigned to the cluster with the closest centroid (*hard clustering*)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "356ba5e6-5c23-44a9-9449-17997312fbf0",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Hard versus soft clustering"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d65afee3-559f-4da1-8c9a-99460188b91a",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"*Hard clustering* corresponds to selecting the closest cluster for each instance.\n",
|
|
"\n",
|
|
"Alternatively, with *soft clustering* compute a similarly score based on the confidence of being associated with each cluster. This is given by the (Euclidean) distance between a data instance and the cluster centroid."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "df56c34f-97b0-4816-aa1f-1c87a694eceb",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Can be computed by the `transform()` method:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"id": "0925b7bf-5559-4566-a5e3-b82d6d166ce8",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:20.998235Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:20.998053Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:21.002930Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:21.002348Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[2.84, 0.59, 1.5 , 2.9 , 0.31],\n",
|
|
" [5.82, 2.97, 4.48, 5.85, 2.69],\n",
|
|
" [1.46, 3.11, 1.69, 0.29, 3.47],\n",
|
|
" [0.97, 3.09, 1.55, 0.36, 3.36]])"
|
|
]
|
|
},
|
|
"execution_count": 15,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"kmeans.transform(X_new).round(2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "a98903e2-4bda-40a9-bf74-b316c08cf67b",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Can verify that this is indeed the Euclidian distance between each instance and each centroid:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"id": "ee7eef95-6760-4b40-9819-fe32350dd2a3",
|
|
"metadata": {
|
|
"editable": true,
|
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"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:21.004670Z",
|
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"iopub.status.busy": "2025-03-07T05:32:21.004503Z",
|
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"iopub.status.idle": "2025-03-07T05:32:21.008883Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:21.008283Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[2.84, 0.59, 1.5 , 2.9 , 0.31],\n",
|
|
" [5.82, 2.97, 4.48, 5.85, 2.69],\n",
|
|
" [1.46, 3.11, 1.69, 0.29, 3.47],\n",
|
|
" [0.97, 3.09, 1.55, 0.36, 3.36]])"
|
|
]
|
|
},
|
|
"execution_count": 16,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"np.linalg.norm(np.tile(X_new, (1, k)).reshape(-1, k, 2)\n",
|
|
" - kmeans.cluster_centers_, axis=2).round(2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d041388d-b3f4-45eb-870d-0dcd48199e4c",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### K-means algorithm"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "aee9b2d6-cfda-4a47-bac9-2170d42dd111",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"If know centroids..."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "eeff7cbf-ff59-4e55-b5d1-231d88e2e6dc",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "fragment"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"can cluster data instances by finding closest centroid."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "7c6b3a87-8436-48a0-8bd6-920a3032c198",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "fragment"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"If know clusters... "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ba85317f-d84b-4601-95cb-bee4366a5816",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "fragment"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"can compute centroid of data instances in cluster."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "679f6ba5-1f5a-40b4-8843-4435a7fc507c",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "fragment"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"K-means finds centroids and clusters iteratively following this approach."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d851e64a-7063-464b-8d4d-b54359f90cdf",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Algorithm\n",
|
|
"\n",
|
|
"Must set number of clusters to consider, $k$.\n",
|
|
"\n",
|
|
"Then run iterative algorithm to continually update estimates of centroids and cluster allocations.\n",
|
|
"\n",
|
|
"1. Randomly initialise centroids.\n",
|
|
"2. Label instances by closest centroid.\n",
|
|
"3. Calculate new centroid of each cluster by taking mean of instances in the cluster.\n",
|
|
"4. Repeat steps 2 to 3. "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "b2ab11e4-6d47-4bab-a4cb-de4c0f2f5358",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Algorithm visually\n",
|
|
"\n",
|
|
"Let's run K-Mean algorithm for 1, 2 and 3 iterations, to see how the centroids move."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "f313bf6e-4fd2-425e-8592-a2050f07590e",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:21.010924Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:21.010760Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:22.385407Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:22.384850Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
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",
|
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"text/plain": [
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"<Figure size 1000x800 with 6 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
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}
|
|
],
|
|
"source": [
|
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"starting_random_state = 6\n",
|
|
"kmeans_iter1 = KMeans(n_clusters=5, init=\"random\", n_init=1, max_iter=1,\n",
|
|
" random_state=starting_random_state)\n",
|
|
"kmeans_iter2 = KMeans(n_clusters=5, init=\"random\", n_init=1, max_iter=2,\n",
|
|
" random_state=starting_random_state)\n",
|
|
"kmeans_iter3 = KMeans(n_clusters=5, init=\"random\", n_init=1, max_iter=3,\n",
|
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" random_state=starting_random_state)\n",
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"kmeans_iter1.fit(X)\n",
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"kmeans_iter2.fit(X)\n",
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"kmeans_iter3.fit(X)\n",
|
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"\n",
|
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"plt.figure(figsize=(10, 8))\n",
|
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"\n",
|
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"plt.subplot(321)\n",
|
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"plot_data(X)\n",
|
|
"plot_centroids(kmeans_iter1.cluster_centers_, circle_color='r', cross_color='w')\n",
|
|
"plt.ylabel(\"$x_2$\", rotation=0)\n",
|
|
"plt.tick_params(labelbottom=False)\n",
|
|
"plt.title(\"Update the centroids (initially randomly)\")\n",
|
|
"\n",
|
|
"plt.subplot(322)\n",
|
|
"plot_decision_boundaries(kmeans_iter1, X, show_xlabels=False,\n",
|
|
" show_ylabels=False)\n",
|
|
"plt.title(\"Label the instances\")\n",
|
|
"\n",
|
|
"plt.subplot(323)\n",
|
|
"plot_decision_boundaries(kmeans_iter1, X, show_centroids=False,\n",
|
|
" show_xlabels=False)\n",
|
|
"plot_centroids(kmeans_iter2.cluster_centers_)\n",
|
|
"\n",
|
|
"plt.subplot(324)\n",
|
|
"plot_decision_boundaries(kmeans_iter2, X, show_xlabels=False,\n",
|
|
" show_ylabels=False)\n",
|
|
"\n",
|
|
"plt.subplot(325)\n",
|
|
"plot_decision_boundaries(kmeans_iter2, X, show_centroids=False)\n",
|
|
"plot_centroids(kmeans_iter3.cluster_centers_)\n",
|
|
"\n",
|
|
"plt.subplot(326)\n",
|
|
"plot_decision_boundaries(kmeans_iter3, X, show_ylabels=False)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "22b6d0c4-1524-4f57-917d-a2e5bb182684",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Convergence\n",
|
|
"\n",
|
|
"Convergence is guaranteed since mean squared distance between instances and their closest centroid can only go down at each step.\n",
|
|
"\n",
|
|
"Usually only a relatively small number of iterations are required."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "f97d2836-fa6d-44b6-9381-a79ff0c71d1a",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Variability\n",
|
|
"\n",
|
|
"While the algorithm is guaranteed to converge, it might not converge to the desired solution.\n",
|
|
"\n",
|
|
"Final clusters are highly dependent on initial random centroid selection."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"id": "9f229355-f37d-4759-8880-93da14aade52",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:22.387747Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:22.387288Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.117782Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.117092Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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GtWrVOB/aXnrpJXh4eOC3335D3bp1UaNGDbzwwgvo0qULVqxYgZKSEhw5coRJCGEu5l731atX0atXLzRt2hSffvopgoKC4Obmhp9++glLly41sMo4CnoeycnJvOm09WPZ9FOzazQaSCQS/Pzzz5zvl357W657XGnjR4wYgWPHjmHq1Klo2bIlvLy8oNFo0K9fP86/gyPXZb6xuY5bMh9bXWNubq6g2EJLIAKJQNDjpZdeAqB1PwC0AdIajQZXrlxBcHAwc979+/eRl5eHevXq8fZF75boFyvk2skV+lBDj/fPP/8YvHbp0iVUr179mU85SiA8C5B7lS5Xr15Fv379UKNGDfz0009Gk0fo07RpU1y/ft3gOO2WdeTIEdStW5dxEerSpQtKSkrw9ddf4/79+zrZ77iw1W73rl27UFJSgp07d+rs1uu7m3FB/31o6w4brr+ZJdBWEKVSaXZtpEaNGoGiKDRo0AAvvPCCVeZlrb9Lbm4ufvnlF8ydOxezZs1ijnO9t0Khv89Xr17VsQ7p/20CAgIgl8t5v2dSqdTAMuTMCPmbXL9+HaGhoTadB3GxIzyzHDp0iHMXg/b7pW9IL7/8MgAYVI7/9NNPAYAzowwNvSj89ttvzLGKigqsWbPG4FyFQmHUHYKmVq1aaNmyJTZs2KDzMHP+/Hns37+fmS+BQKgakHuVabKystCnTx9IpVLs27ePSRUslLCwMJw/f54zHXqXLl1w4sQJHDp0iBFI1atXR3BwMJNxjD7OBy0E9QWopdA79OzPR35+PtavX2+yLfvvw/57pqenM26b1qJNmzZo1KgRPvnkExQUFBi8/vDhQ5N9DB06FDKZDHPnzjX4PlAUZZBOWwjW+rtw/R0Aw++iGOjshV988YXRPmUyGfr06YMff/xRJ03//fv3sWXLFnTu3BlKpdLsedgbuVwOgP9vkp+fj6tXrwrKNmgJxIJEeGaZPHky1Go1hgwZgqZNm6K0tBTHjh3Dtm3bUL9+fYwfPx4AEBoainHjxmHNmjXIy8tDt27d8Mcff2DDhg0YPHgwevTowTtG8+bN0aFDB8TGxiInJwf+/v745ptvUF5ebnBumzZtsG3bNnzwwQdo27YtvLy8MHDgQM5+k5OT0b9/f4SFhWHChAlM6lwfHx+degGWkp+fj2XLlgEAU6siJSUFvr6+8PX1RUxMjNXGIhAI3JB7lWn69euHa9euYdq0aTh69CiOHj3KvFazZk2Eh4cbbf/qq69i/vz5+PXXX9GnTx+d17p06YKEhATcvn1bRwh17doVq1evRv369U2mxW7UqBF8fX2xatUqeHt7Q6FQoH379pyxLGLo06cP3NzcMHDgQLz99tsoKCjAl19+iRo1ajCWRWMsXLgQAwYMQOfOnfHmm28iJycHy5YtQ/PmzTmFjLlIpVKsXbsW/fv3R/PmzTF+/HjUrl0bd+7cwaFDh6BUKrFr1y6jfTRq1AgLFixAbGwsbty4gcGDB8Pb2xvXr1/H999/j//973/46KOPRM3LWn8XpVKJrl27YvHixSgrK0Pt2rWxf/9+TqukUFq2bImRI0dixYoVyM/PR8eOHfHLL78Y1BECgAULFiA9PR2dO3dGVFQUXFxcsHr1apSUlAiup+UseHp6olmzZti2bRteeOEF+Pv7o0WLFkyJgwMHDoCiKLz66qu2nYhNc+QRCE7Mzz//TL355ptU06ZNKS8vL8rNzY16/vnnqcmTJ1P379/XObesrIyaO3cu1aBBA8rV1ZUKCgqiYmNjqeLiYp3z9FNdUhRFXb16lerduzfl7u5O1axZk4qLi6PS09MNUucWFBRQo0aNonx9fXVSrHKlzqUoijpw4ADVqVMnytPTk1IqldTAgQOpCxcu6JxDpxN9+PChznG+lL760GNz/eNK80sgEKwPuVeZvlfx3acACEpTTFEUFRISQk2YMMHguEqlomQyGeXt7U2Vl5czxzdv3kwBoMaMGWPQhuv9/fHHH6lmzZpRLi4uOu9Tt27dqObNmxv0oZ/+mI+dO3dSISEhlIeHB1W/fn0qKSmJ+uqrrwSXZfjuu++o4OBgyt3dnWrWrBm1Y8cOzrFhQZpvmjNnzlBDhw6lqlWrRrm7u1P16tWjRowYQf3yyy/MOXyfBfZ8O3fuTCkUCkqhUFBNmzaloqOjqX/++Yc5R8x7yvd34cLY3P777z9qyJAhlK+vL+Xj40MNHz6cunv3rsH7JuazXlRURL377rtUtWrVKIVCQQ0cOJC6ffs2Zxrs06dPU3379qW8vLwouVxO9ejRgzp27BjnGPp/G745jRs3jlIoFLzvBw1fmm/9zwbXPYLrb3Ls2DGqTZs2lJubm8G1vvbaa1Tnzp1NzslSJBRForQJBAKBQCA822zatAnR0dG4deuWTsFRAoHgHGRlZaFBgwb45ptvbG5BIjFIBAKBQCAQnnlGjx6NunXrYvny5Y6eCoFA4OCzzz7Diy++aHv3OgDEgkQgEAgEAoFAIBAITyAWJAKBQCAQCAQCgUB4AhFIBAKBQCAQCAQCgfAEIpAIBAKBQCAQCAQC4QlEIBEIBAKBQCAQCATCE6psoViNRoO7d+/C29sbEonE0dMhEAiEZwaKovD48WM899xzkErJPhwbsjYRCASCYxCzNlVZgXT37l0EBQU5ehoEAoHwzHL79m3UqVPH0dNwKsjaRCAQCI5FyNpUZQWSt7c3AODmT6uhVHg6eDYEPpoMnowHufnYeu4Q2WkWwLZl67Bj1Ua4uLjgwIEDjp4OgcBJYWEhBgwYwNyHCU8ha5Pz03rkh7h+9yH8/f2xY8cOR0/nmaB79+4AgP9++RtSCXkWINiGx4UFaDKwraC1qcoKJNp1QanwhNJL7uDZELgoLCrGg9x8BDwXCC8fpaOnUyl4oVUIAKC8vBxeXl4Ong2BYBziQmYIWZucnxv3sgEAU6ZMIfdZOyKVSuHr7ePoaRCeAYSsTUSmExxG6s5DAIB24d0cPJPKQ6f+PRw9BQKBQKiyFBWXgKIoAED//v0dPBsCgeAoiEAiOIyvf/oNADAw8jUHz6RyQi/iBAKBQLAO0z/bBABwcamyDjYEAkEARCARHAJFUTh18So83FxRu1E9R0+nUrJv3z5HT4FAIBCqFOt+/AUA0LlzZwfPhEAgOBIikAgOYc+RUyiv0CCka5ijp1LpoHc28/LyHDsRAoFAqGIUl5YBAGbPnu3gmRAIBEdCBBLBISzf9jMAYMjbYxw8k0rIk9jCvXv3OnYeBAKBUIU4d+UG8zPJwEggPNsQgUSwOxRFIePcZcikUjRv18rR06l0dHv1ZQDAxYsXHTwTAoFAqDoMn/YJAKBatWoOngmBQHA0RCAR7E52ngqqwiIEvdCIpAE2g5d6dwJAkjTYirS0NLzyyitIS0tz9FQIBIIduXIrCwAQFxfn4JkQCLqs/W4Tgge1x9rvNjl6Ks8MRCAR7M6STTsBAN2HkBSq5uBfozoAQKPROHgmVZPU1FRkZWUhNTXV0VMhEAh24nGBmvm5WzdSeoLgXCzZkILbWXewZEOKo6fyzEAEEsHu7Dx8EgDQM+IVB8+kctLspZaOnkKVJjIyEoGBgYiMjHT0VAgEgp2Yu/pbACS9N8E5+XBcDIICa+PDcTGOnsozAxFIBLtSXFKKy7fuQenvC78A4udNcD4iIiKwe/duRERE2GwM4sZHIDgXK9O0ZRN69CDFuAnOx8RhY3Bx5wlMHGbbxFbEle8pRCAR7MovJ86Boii06NDa0VOpEmzYsMHRUyCYAXHjIxCcCzq995QpUxw8EwLBcRBXvqcQgUSwK8u/1ab3fnXiaAfPpHLjIfcEANy5c8fBMyGYA3HjIxCch1/+yGR+rlGjhgNnQiA4FuLK9xQikOzEqrR9aPDKO1j1xIz/rHL87D9wkUnRpNWLjp5KleDs2bOOnkKVxNYucPZw4yMQhEDWJiB64ToAJL03wfmxtQucvVz5KgNEINmJpNQfcOveQySl/uDoqTiMew9zoSoswnMN60Mmkzl6OpUaOsHF1atXRbUjsS/CIC5whGcFsjYB/966CwCYO3eug2fybEKvR6R0hWmIC5z9IALJTkyPHIy6tQIwPXKwo6fiMD7fuhsA0H3oyw6eSeXnlbHDzWpHHvyFQVzgCM8Kz/raVFFRAfqxvH379g6dy7MKvR4RgWQa4gJnP4hAshOTIvri+u6VmBTR19FTcRg7Dp4AALw8hrgVWYqLhxsA8QtKVXnwJy5wBIJ1eNbXpg+XrAcAyGQyUrjcQdDrUWV//+2RAY64wNkPIpAIdqG8vALX/rsPb18fKJTejp5OpadW3SCz2lWVB39iCSMQCNZgzfcHAABdu3Z18EyeXej1qLILJOL+VrUgAolgF/YeOwOKohDSqa2jp0KoAlQVS5izQ2LWCFWdktJyAEBCQoKDZ0Ko7BD3N/thD2sdEUgEu7AqbT8AYNCbI/HzpjS8GfYKft5EHrqsweeff+7oKdidqmIJc3aIpY5QlTl7+Trzs5ubG9kQIFgEcX+zH/aw1hGBRLALR85cgEwqRdM2Idi+IhUP79zD9hWpjp5WpcbLzxcAcOHCBVHtyEMAQSjEUkeoygz9cDEAoHr16gDIhoCjoSjK5lYBQtXAHtY6IpCsiJh6Es9S7Ykbdx6gQF2MesHPQyqVYnhUJAJq18LwqEhHT61S4+Ki/freu3dPVDvyEEAQCrHUVQ3I2sTN9XvZAIAPP/wQANkQcDQURZEYHoIg7GGtIwLJioipJ/Es1Z748vt0AECn/r0BAP3HROCr47vRn2Szs4guA7VZp+7evSuqHXkIIBCeLcjaZEhxSSnwJAtoeHg4ALIh4GgkEgmJ4SE4DUQgWQh7t01MPYlnqfZE2oHjAIBX3nzdwTOpWoydFm1WO/IQQCBUfcjaZJyPlm4AALi4uDh4JgQaiURCYngIToNdBNLKlSsREhICpVIJpVKJsLAw/Pzzz0bbbN++HU2bNoWHhwdefPFF/PTTT/aYqmjYu21i6knon1tV3RooisLV/7JQzccLci+Fo6dTtajcGVEJBIINIWuTcdb/eBAA0K1bNwfPhKDRaBw9BQLBALsIpDp16mDRokU4deoU/vzzT/Ts2ROvvvoq/v77b87zjx07hpEjR2LChAk4c+YMBg8ejMGDB+P8+fP2mK4orLXbVlXdGnb+ehIUBbwQRtJ7WxsPT0/mZ7LAEAgENmRtMk5xaRkAYPbs2Q6eCWHfPq349lZ6OXgmBMJT7CKQBg4ciJdffhmNGzfGCy+8gISEBHh5eSEjI4Pz/M8//xz9+vXD1KlTERwcjPnz56N169ZISXGuwL1VafuQlPoDpkcOtrgKeVV1a1i+bS8A4NUJox08EwJBC8niR6jK0BYfAIKtRsaoimtT5j9P03vL5XIHzoQAACUlJQCAFxsEO3gmjsUetX0IwrF7DFJFRQW++eYbFBYWIiwsjPOc48ePo3fv3jrH+vbti+PHj/P2W1JSApVKpfPP1lhzZ02MC0RlgaIo/PH3FcikUjRr19LR0xFNZarXtGjRIlBPAo6rArYUMSSLH8Ge2HttsrbFpyquTa9NXwIAqFatmoNnYh5kk8cx2FrA2KO2D0E4dhNI586dg5eXF9zd3TFp0iR8//33aNasGee5WVlZqFmzps6xmjVrIisri7f/hQsXwsfHh/kXFBRk8ZxN+V6zd9ZGxy2FW9sRaD9mGhq88g5Gxy3lbCvEn7uq+Hw/zM3H48IiBDVpBImk8gXMVIZ6TdWf035P/vjjDwfPxLrYUsRERkZCqVRCrVaTBwyCzbH32qRv8SFrkyFXbmufJeLj4x08E/MgmzyOwdYC5sNxMfBT+qJAXUisSE6A3QRSkyZN8Ndff+HEiRN45513MG7cONEFLo0RGxuL/Px85t/t27ct7tPUThx7Z217+nFUaDT488I13Lr3EN/s+52zrZDdvari85288UcAQM9hAxw8E/OoDPWavLy9AQBqtbpSilA+LE1FbmyHNSIiAnK5HCqVym4PGGTH99nF3muTvsWHrE265KsKmJ+7du3qwJmYDynV4BisUZzUmBVq4rAx8JIrkKvKs5sVibj18WM3geTm5obnn38ebdq0wcKFCxEaGorPP/+c89zAwEDcv39f59j9+/cRGBjI27+7uzuTJY/+Zyl8vtfsXbRVaftQvUckpFIppBIJXmrWEDKp9m2VSaXoGPKCzq5dx5AX4Kf0QkFhkSDLVGVm969/AgB6DHVugcTnSlcZ6jW17tUJAJCTk+PgmVhXBFiaitzUDqu9HzDIju+zi73WJn3rjrG1SSqR4HFhkY41qWPIC8yaJWbcysa8L78FUDnSe/PdU0mpBuFYUwBYozipKSuUNUSYNefzLOOwOkgajYYJzNMnLCwMv/zyi86x9PR03pglW8Hne83eRUtK/QG5qgKUlZejTmB1jH+1F3y85PBTemF4eBi2px/HrXsPmf+Pnb0Mb4UnclQFzC6c/sJWFXy+i0tKceV2FpT+vvCt7u/o6RilMrjS8TF+xruOngKDo0QA10OEKQFk7wcMsuNLsCZca4S+dYe9Nvl4K/Ag9zGGh4ehbq0AeLi7IVdVgG37jzFtjp29jAqNBsfOXmb6rIpr08rt2sLlvXr1cvBMTEM2VizHUQKAT5iZEkDWEGFisLcgq0zYRSDFxsbit99+w40bN3Du3DnExsbi8OHDGD1am9ls7NixiI2NZc5/7733sHfvXixZsgSXLl3CnDlz8OeffyImxjn+gOxdtOmRg+Gn9IK/0gvTIwcjKfUH5KgK4K3wxP7jmajQaCCRSNCqaX1IJBLce5iL7FwVcz5QNdwW9EnPyARFUQgJe0l0W3snR6gMrnSVAUeJAK6HCGfbYXW2+RCqHvrWHfbaJAGYDbrru1cybVxdZPBTeiE7V4V7D3MhkUh0LEhVcW0qKdOm937vvfdEt7W3qyzZWLEcRwkAPmFmbwFkCmebjzNhF4H04MEDjB07Fk2aNEGvXr1w8uRJ7Nu3D+Hh4QCAW7du4d69e8z5HTt2xJYtW7BmzRqEhoYiLS0NP/zwA1q0aGGP6ZqEvYs2KaIvsg+l4uGhVABAQWER/J6IH3ZOsWv/PQBFUSgrL4e6uAQUtIuP2CrnlYUV32rTew+cMIo5JlT42NuiUxlc6YSQl5fn0PEdJQLIQwSBYGjdYa9NfcJCddzn3N1cAQBl5RWQAFAXl6CsvBwURWF7+nHGYlTV1qYDGZnMzzVq1GB+Fip87G3RIRsrluMoAUAsM5UfuwikdevW4caNGygpKcGDBw9w4MABRhwBwOHDhw1uOMOHD8c///yDkpISnD9/Hi+//LI9pioIvkw+bOsRjVQiAUVRKC4tg1QigfSJD3ieqsCsKueVheNnL8NFJkOTVk9FrVDhQyw65lFRUeHoKdgMU0kXyEME4VnHWIY5tvsc/Tq9NuU+LoSriwvoFC8VGg1mLt8KoGq41LGJWvglAKB69eo6x4UKH7IZQ9CHz5WOWGYqPw6LQarM6Lsd0AtTx5AXmN022v/bw90NUokE6uISaCgKlEYDAIx1id6Zq6zpU7nmffdhDh6ri1D7+fqQyWTMcaHCp6pYdOwFnb3u/fffd+xEbAjxxScQjMPlDmdsbaLvzbRnA9vjoUBdbNBHVVibrv2nTe89b948nXOFCh+yGUPQhyQ5qLoQgSQQ9s2W9u2mM9F9vHwrbt17iP3HM5ndNto1wcPNFRpWAU/2IkTv2DV45R3MfNJHZfP15lqUP9+yBwDQfYiu1a8qCx9HFpUN7dweAHD37l27j20vyM4tgWCI/rpUt1YAkznV1NpkzOJcXlHB9F1V1qZylghs27atzrlVWfiQEgO2hbjSVV2IQBIIfbOduXwrklJ/QElpGXJUBZi8aC2KS7VBn/TNd1XaPiSl/oDpkYPRJyyUt08XFxem39wntRnuPcytVDt1XD7qO37JAAD0f2OYg2bFjS1FjCMz4bl7ugMAioqK7D62vTD1AEMeAgjPIlwbVDt//RO37j00uTa1Dm7A22+b4AZVbm36YMl6ANp115lqxtn63kWs77bFlCsdqTNUeSECSSD0zZbOBlRUUgoA0FAUiopLIJFI4C33gFvbEZi6dCOzaO0/rg0KlQCQe7jDT+kFuYc70++tew91xikrL8fUpRsrjUuDvo96WVk5rt99AG8/XyiU3g6enS62FDGOjJvq9fqrAIDS0lK7jy0GWz4IkIcAwrMIWwTQgkbo2nTtvwcAnq5Ncg93Rjj8eeEabnOsTTGL1laKdQkwXJvWfq8tHdKtWzdHTssAW9+7iPXdNLYUMcQFr/JCBJJA6Jvt/OiRqFsrAK/16Qi/J+lTKWj9uG9lZaNCo4G6+El9pycBsDVr1kTDhg3h7eOLvCe7cX5KL5SXl3OOVVRcUildGgBg77EzoCgKoZ3amj7ZzpgrYoRYnhzpPhjW27kWfD4hZMsHAUsfAogFilAZYYsAWiwJXZvc5F5o2LAhatSsCXVxCYpKSuHp7saIJNrqRCcWwpO+KuO6BAAlZdr1dv78+Q6eiS6W3LuE3LeqsvugWPiEkC1FjKUueMQC5TiIQBLI6LilcGs7AkdOX8D13SvxdeIUZB9KhZ/Si/P8sLAwTP94Lv766y+cPn0aR44ewenTp/FXZiaSl3yKps1fBPTM/OyFia6TVNkCZFdu185z4JsjHTwTQ8wVMZWpkKwjMtnpL9J8QsiWO5lCHwIcId5MjU0gWIKYtSksLAzLly/Hrn2/4NSpUzhyRLsuZWZmIiUlBaGtWoOiKJ02Etb/7DpJlWltOnn+afFbNzc3B87EEEsEDLGcG0dfXPAJIVvGEQnNZucI8WZq7GcdIpAEsj39OCo0GqZGBL0w9AkLhZQldIKCgrB582akpaVh8ODBTDpRjyc35erVq2Pw4MFIS0vDpk2bULduXcikUkgkErQJbgDZk906L4UnJkX0rXSF+n7PvASZVIqmrV+0y3hi44rMiUOiLU/BbUIclohBKOfOnbP7mPqLNJ8QssVOpljR4QjxZmpsAsESjK1N9MrEty5JJNp/7HVp8+bNCAoK0r4OoFXT+qhbKwC+Si9QFIVjZ7ViozKtTSNjlwLQrX1kS8Tel8zdPKHvW6GhoWTzhQN9ccEnhGyRklus6HCEeDM19rMOEUhGYC82w8PDIJNKMTw8TGdhOHb2MjQUBYlEgpYtW2Lfvn2oX78+PN3d4OMlZ/qig2XZ1K9fH3v37sWLISGgKAoPch/ji+kTIPdwx39Z2Rgdt7RSFeq7+l8WCtTFqBfcWMctw5aIte6YYw2iLU8XT511WkuSI4OO9cWFPV06jIkO+qEjPj6eeXiwp3jTh8QCEKyF0LWJAnTWJQBwdZExm3IUBegZjFC/fn3s27cPLVu2BAXgwrU7uL57JRZEj6y0a9P1u9p4qmnTptllPLGbIeZuntD3rczMTLL5woG+uLBnbSJjomPtd5sQ1LsFgnq3YASUPcWbPiQTHzdEIBmBvdh8nTgFpSe/xdeJUzA9cjD8lV54XFiEjiEvQCKRoE6dOtiyZQsyMjLQo0cPJC/5FKVlT2OM9N0WUlJS0KNHD2RkZGDLli0ICgrC9MjBmBTRFyWlZdA8qWhemQr1fbnjAACg8yvhJs60HmLjiixJpuDMBWwlTwTpwoUL7T62I33cjYkO+qEjPT2deXhw5FxJLADBWvCtTR1DXoBMKkXHkBe0AiYoSGddSklJQVl5BTSUxmBNArjXJTrpQ2Vdm4pLniav6d69u13GFLsZYunmCdl84caRxVqNiY4lG1KQq8pDriqPEVCOnCspasuNhOK6S1YBVCoVfHx8kPvrRihZlhwu2KlP2Tf70XFLsT39OIaHh6FL62b4ePlWUAAWRI9kFiiazZs3o379+ujRowfKyrTWotjYWMTEGH45UlJSmAdZV1dXHDp0CA/v30PE8NcwPDwMAJhxv06cYulbYTdeGByDq7ez8O3FI/BUGH/PCdZlyfszcXjHz3B3d8fvv//u6OnYlLS0NKSmpiIyMtKo2KDPCw0NRWZmpsnzCdajoKAA3bt3R35+PpRKpaOn41TYcm0CwKTllgDYZMG6dOTIb7h69RpiP3wPdx7kVNq1adKCVfjy+wNwcXFBRkaGo6dD4OCHH37AggUL0LlVe+xd/Z2jp2M2a7/bhCUbUvDhuBijYmPtd5swd2USAGD2O9OJMLEjqoLHeK5nsKC1iViQwO9LfezsZVRoNDh29jKSUn9AjqoAuaoCZsGiCQsLQ48ePdCgQQN89NFHzPGFCxdi+fLlkMvl8Pb2hlwux/Lly3V2+efO/hgd27ZGuw4d0bZdO2zbf0xnR5B2pRgdt9SpA2IpisK121mo5uvtFOLIFjWPHFkM1hQBz9UC4JgkDfaG7Y5izHc/IiICkZGROuLInokSSFIGgqWIXZskABPH2sGCdWna1Klo1yoUIyOGoHaDxqjQaCrt2rRx92EAQI8ePRw7kSfY4r5A7jXOAdutzlgM0sRhYzD7nenwkisA2D9JAknKIAwikMBd7FT/OO1W5/cku9ykiL54vW8nAMAbb7zBtImJiUFsbCzze2JiIlasWAG5XI4VK1YgMTGReS02NhaTJr3DpF5944034OnupuNfTi+Q29OPO3VA7M5fT4IC0CTMOdJ72yLznDl9ChFV1hBeL3Z8CQB4U8dXJdjuJKZ89/VfFyqujCG0HUnKQLAUsWvT/OiRTByr/roUHxfH/G5qXYqKjkbe40Koi0vwxujRAFBp1yY6vffHH3/s4JloscV9wZw+hdzHiPASB9utzlTiA/br+ueaK2CEtiNJGYRBBBIMC8pxHZ8U0RcPD6Ui+1AqJkX0xaq0fdh/PBOuLi7o3LmzTruYmBjEsRaj+Ph4VK9eHfHx8cyxuLg4xMTEoKikFPkFagBA586dMajbS5i5fCtu3XuImcu3Mgvh8PAwhwfEGkvrmrLtZwDAqxNH23tanNgiXkhMn7To2Zi83KSosoaYa9W5vdltKxvsWB5Tvvf6r4sRV3wIbUfiAgiWYs7aBAAebq7o0qWLTptoEesSABSVlEJVqEanJ+tbs4a18W7SOkYMVYa16czFq8zPcrnjPRsA29wXhPbJFjxC7mNkk0cc7FgeU4kP2K/rn2uugBHajiRlEIaLoyfgjLD9vgHo+IDTrxUUFiFHVYCaNWsyKVMBbcpUigKmTp0KhULBLD55eXnMOQkJCYiKioJardYZNyAgAJfv5urUnaAXQGeA7e7BnhNFUfjj/BW4yKRo1ralw+b386Y0bF+RalTAsM8RWw+p/5gIwW1o0ePlqzQpqoZHRZqctxgqKiogk8ms0pezExERYTSuSP91/d/pWCYx0OLKVDtTcyMQxCJ0bXL1VKBatWo6bSUQvy5RlHZdqlGjBs5cuoEKjQYyqZQZ09nXphEzlgDQXoOjEBszaU6spNB7DVvwCLmPCb3XEQyZOGyM0dgi/dfZP9MWKLECRmg7U3MjaCFJGjho8Mo7uHXvIerW0t5U6Z+v717JvOan9ELe40I0aNAAR44cAaB1QXBzdUF+gZrx7a5evbrOIuTr64vs7Gyo1WoUFBQwmYRov/H0zcugynnIGZjraPgChv/65xrajJqG519siqV7vrZ4HHNFzJthr+DhnXsIqK2Nx6F//ur4bqbPosJCFOSpmOO2whIhZi4D67YBAMyaNQsDBw50aOrvyoYlDycEQ0iSBn7ssTb5B9TEb7/9xrSj1yaNRGZyXXr8+DFzXCKRQKnwRL++fVDHxw3Hzl52unUJ4F+bZG203+UlS5agW7duFo9jzn3ilVdeQVZWFgIDA7F7926D3+k+1Wo1VCoVc9wWOOt9rqokabAFQhM/EIRBkjRYiL5/d91aAegY8gKq94hEdq4KfkovNKpTA6AoqAsLQT+HFpc+dZerqKhAUlKSziIEaHfskpKSUFFRoZNmtUKjgZfcA6P6hDlt+lS+eS3ZtAsAMCxqvFXGMdfljO0Cp+8OR/cJwCzXO7FxQnTtpP5jIuyW3IG2GpWVlVlNHDnaB93WcUI01ohNIhBsDVfs0ePCIoyOW4qCwiLIPdxRWFSMgoICSCRgipjTa5OQdYkNRVFQFarx5sAu+DpxilOuSwD32pSb/1ToWUMcAea5nBlz82X3CcAs1zsx9yv9UgPOcq/TaDSi2zg60YCt44RohCZ+IFgfYkESCL07BwB1awXgzv1HqHjypT5/7hyqV6/O/A4Ay5cv1wl89fX11VmU4uLiEB0drTNGXm4umpZcsniu9ua58Al4kJOPtMvH4ObhbnF/XNYXSy0yyTFxOLonHZ0HhGNqSqLpBnrQ1impTIpJ86abZdny8lXCU6GwmVVpSKMOKC8rQ926dbFjxw6r9Km/2wnYdxeSa3xbtGNfE/3AYsud3KoOsSDxY821iV6XZFIp4/5Gr0OZmZloVL8uCtTFzDFz1qWHDx9iUP9wXN+90qK52pv3Fq9Fyra9Vk3vzXXvs/R+GB8fj/T0dISHhyMhIUF0+549e0KlUkGpVOLgwYOi2tL3SaVSCblc7jDL0rBhw3Dz5k283n8o1s79QlCb4EHtcTvrDoICa+PizhMA7Gtt4RrfFu3Y10SLJbFjEp5CLEg2YHrkYPgpvSD3cMfjwiK0alofEmj9uu9evwIvuQdjSUpJSdFZhBISEpCdna1z80tMTERKim4g3X/X/nHqdKlcPC4swv2cfFR/LtAsccRlXWFbX2gsTWRw8dRZaCo0uHjqrFnth0dFQiqTQlOhMZiDKQsRbc0CYPXMemwGRI4AANy5c8dqfXIF/9ozcFdI8DHXLqjYoGUAghM/EAjOAm1RatW0PmRSKVo1rQ/5k/twxvHjAMCsTeauS0ePHkXHkBcq3dq05knh8j59+ohuy2dZ4Sr2bOn9MDMzExqNBpmZmWa150OIdYi+1wFwaDIGWqQnTZkjuA1XogF7ZmcTkuiAy+IjNEEC3RaA4MQPBOtCBNIT+LLg0McBIPtQKtzdXJGrKsCpC9cAiQQUgDmLPkF+gRoUBazQqycRFxfHBL5GRUXpZBFauHChzmI0d+EnTPa6yrIYrd+p3bHq0Le7wWtCXMuECh9Ls9JZ2r7/mAhMmjedsw++a6CvHwC+Or4bY6dGWz2zHpsXQpoBAKxpFOZ6ILCngOAaXx+uBxQh7Uy1BeAU7ieEZxtjaxMdd/Mg9zEqNBqcungdgDZ2KHXDBuQXqJFfoMayZSk661J8fLzgdWnz5s3Y+eufuHXvId5NWlcp1iUAKH2S3vvdd9/VOS5EOIgRPZbeDy1tHxUVhcDAQERFRekcN3YN+htDdB+O3hQSk1yInTGOxp4Cgmt8fbgEm5B2ptoCIK52doAIpCfwFeTTP05HdlB4+iB67NgxHDp0CNevX8fi5GSmbWxsLKKjo5nAV7VajejoaJ06SZ988gmuX7+OgwcP4tjx45AAyH9ciFv3HuLjSiCU6CJ8g996w+A1IeJHqHDhsiqJwdL2xvrguwb967fGHIxRq0FdAOb5c4tBqPgQi7n+8MYeMEz1aaytqYckW/vvO0t8AMGxCFmbpkcOhkwqBUVRUBeXgKIoHD9+nFmXPvnkE6ZdbGwsI46ErEsZGRlQF5dAAm2s7MfLtxot+eAMHMh4ao1hZ5kFhIkfMaLF0vuhrdqLubfZ6p5ub4SKD7GYG/tjTLCZ6tNYW1OWMlvHKj0rsVBEID1BSEE+AJgfPRJ+Si+D9vFxcahWrRpWr14NV1dXxMbGMvUk9KGLybq6umL16tXw9/fX2cHTUBRkUikeq4tx695DTF260WrXaU00Gg3+vnob7p4eqFGnlsHrQsSPrUWDPRIkiBVOtppT4ycWpMqKua4qxhZ3U30aa2vqIcnWroakBgkBELY2TYroyxSIZRMbGwt/f3+rrEs0xaVliFm0ltnEc0beSVwNAKhRo4bBa0LEjz0Eg603QMy5t5FNGW7Mdd0zJthM9WmsrSlLma1dDZ+VQrNEID1BSEE++vfsQ6k6C5G/0gvTRvfF229NQIcOHXDo0CHeRYgmJiYGhw4dQocOHTBhfCQePXwAAHBxcUHdWgH4YvoElD/JKFRUUmrNS7UaZy5dR2lZOZq0fpHzdWcQP8asWLYWT3zXb43CsKawtRXJFphT7NDUcUvcV0w9JNna1ZDEQhEAcWtTdb+nQcd1A6tDUl6McwfSEBYWJnpdGjVqFLLu3WMyYnp6uKNurQC4u7ky3hPOmuHp+h3tejp//nyD12wtfoSKDCEucPYWT2RThhtz442MvWaJO6ApS5mtXQ2flVgoIpDMJHnKWNStFYDX+3aCl8ITAPCcQoK+ffvixo0bgvq4fv06+vbtizd6hsLDzRUA4C33wPTIwUhK/QFtghtAJpXitT4dddo5i3vDF1v3AAD6jhzikPEtdeGzh1AROydrsXr1aov7sPduoiVxQ3zHrR1PxH5PbP2gVVXcXgj2g7Yqvd63EyCRYHrkYER0aoZXBrwsel3666+/4C33APXEoyF5ylhMjxwMCQC5hzv8lV5YED1Sp60zrE3l5eWMcGvdurXdxxcqMixx77UVlWFTxhHuXebGGxl7zdrxROz3xVauhjS27t9ZIALJTOjdu2NnLzN+4MfOXsbt27fxxhtvYNiwYfj+++/x8OFDnZo0Dx8+xPfff4/XXnsNkePGoVOzupgU0Rd9wkIhlUhQXFqGj5dvxa17D/Eg9zFKT36LrxOn6IzN55Nub/Yf1/p5twvv6pDxLXXhs4dQETsnS3GXewAA8vPzLe6LXqRXrFjhVG4XXIt4Wloa1Go1lEql0QeOxYsXW3Qd1nhwIW4sBFvBtS4BwLXrNwzWJalEwqxN9Lo0bNgwvDl+PO7euYPX+3bC/OiRkHu4Q0NROHL6ApJSf0COqgDV/ZR4eCjVwKrlDGtTzKJ1ALTeGI4oli1UZFji3msrKsOmjLPWBeKzqqz9bhMK1IXwU/oajSf6MHmmRddhDbc3Z3o/nQEikExA74iNjlvKuTPGLiT7uLAIUqn2Lc3IyEBMTAzavvQS5k75H7p27YpWrVqhZcuWmDx5MkZ2CdYRP8fOXobmSYBtcWkZp8+5/ph8r9uDnPzHeJCbj8B6deDh6WlWH5a6uDlD4gZnQ/IkjcjxJyl+LcFZUsDqw7WIr1ixAiqVinldX4RERkZCKpVCo9FYdB3WeHAhbiwEa2BsbWKvEavS9sHT3Q3A03WpZcuWCOvQHovi3kPr1q3RsmVLxMTE4MSJE/hs6nhmbZoU0RfFJaWgKArf7j9mcu1xhrVp4+5DAIAePXqY3YclmxjWEBmVQag4CrYQcaZYGD6rytyVSchV5THn6IuQD8fFQCaVoUJTYdF1WMPtzZneT2eACCQT0Dti29OPG80st+94JnJVBQaxH2Xl5Vi9bTeuXr2KBw+0ftFBNavp7LytStuHgsIi5nd3N1ejFcv5fNLtybb9vwMA2nTvaOJMfuzt4maPhA2OJmLyBADA3bt3Le/rySLtLClgxcCVpWnatGmcliehD0LWKpBbGdxYCM6PsbVpUkRfxlV75vKtUBeXGLS/ces2vkjdjvv37zPH2gQ3MFib6HgjD3c3k2uPM6xNJU/Se8+dO9fsPuy9iUGsysJhC5HKGAujL0ImDhuDJVMXGFyHGGuOtQrkVsb305YQgWQCekdseHgY6tYKAAXouBDQi1RJaZngPm9lZaN6j0gE9IjE6LileDdpHXJUBfBXeqFurQADv25n5KsftPWPLHFPM9fFzVyhYw9B5mgRVlZUDMD2tZBshbkPCvq1QLhEiKVFHs19aNK/Jlu8n+QB69nDFmvTnxeuIaBHJFal7cOqtH14N2kdKICJQXJ2fj9zgfnZzc3N7H7M2cSw5Dtoa0HmDPcHW8zBXrEwlriezX5nOoICa2P2O9MBcIsQrusQY80x1/Kjf122eD8rs9uehLLmk5QToVKp4OPjg9xfN0LpJbdav+zifJMi+jK/FxQWIUdVwNlGAuC1vp3w7+17+PPCNbi5ujBF7GRSKSo0GsikUnwxfYJDd9700b9WNh7tX4eriwzf/PO73f28R4b0QEGeCl6+Smw9e0hwu583pWH7ilQMj4q0mVvdm2Gv4OGdewioXQtfHd9tkzGMEdmuPx5laS2Vf/75p13GtJZlBdAmUsjKykJgYCCTXEEMLi4ujCtdeXm5yfPj4+ORnp6O8PBwJCQkGD03LS0NK1asQGlpKdzc3BAVFSXoei29JiHYYwwxFBQUoHv37sjPz4dSqTTd4BnC2damNs0a4sK1OzpWprq1AgBoBVdlWpsavTIJN+5lo0aNGvjpp5/sOqeePXtCpVJBqVTi4MGDotpa8x7KhTPcH4zNoVevXsjPz8d/v/wNX28fq41pLctK8KD2uJ11B0GBtZnECrZm/MwY7DiwC0N7D8T6BcaFz9rvNiHu83koKilGRPirJs+nscd1OeK9M4aq4DGe6xksaG0iFiSRcKVWvb57JeZHj0TdWgFYHvsWXu/bSUc0SKVSdGndDM8H1YJMKkVI47rwU3rBX+nF7P452wIE8Afcnjx/BWXl5WgQ2twhQbDmIjbmSN8a9POmNIwM6YGRIT14LUTDoyLh5atEUWGhQ6xIrz1xsbMn1tz9NGfnVqFQICgoCMHBwQgODkaTJk2Yn4OCgqBQKHjbZmZmQqPRIDMzk/ccmoiICMjlchQXF0OlUgm+3tDQUEilUoSGhgq9JNGIed+cYTeZYH3MWZt8lV4Y/2ovuLu5Qu7hzmSnmx45mLFQVaa16ea9bADAjBkzHDAr8xFrVdb/DqelpaFnz57o2bMn5/c6MjISSqUSarXaYd97R7gWWyumxhGuZxlnT6JCU4GMsydNnjtx2BiUlGpjBXcc2CWof1PJI6yFmPfO2axNRCAZQUzKUrbPd5fWzVD+53Ysj30LEokEFRoNJi9ai237j6FCo8GZSzewIHokvBSe6NK6Ga7vXgkADk+Pqg9fwO3Sr5+kTR43wiEuZWOnRiOgdi2MnRpt03H0XfK2r0hFQZ4KBXkqXje9/mMi4KlQGD3HlrDFn72Mw9Zc+IQ8KNAPB+np6ahfvz4aNmwIX19fuLi4AACKi4uRk5OD8vJy+Pr6omHDhqhfvz5cXV0tnjv9oMGXLY8LMSLMXMQ8YJEkEZUbsam0udYm/yfFznNVBZi6dCNyVQVQF5egup8S86NHMsKjMq1NJaVlTHrvrl272n0jQN/N15bof4dTU1OhUql4N27ozR0xGzvWxhGJJ6wlbIS6npl6wBcjAMTOfWjvgZBJZRjae6Cg85dsSEGuKg9ecoVNXRTFuO05W5IIIpCMICZlKe2vzT5/UkRf+Hprd681FAVPdzfIpFIMDw8z6FvoWPasM8EXcHvoz/MAgI4v97JqIVah51s7+xzfuPoxUrR1yMtXaRA3xe7DWGyVPQVlYmKizccAuBc+Wz6cpKamIjAwEMOGDdMJMKdRq9XQaDRQq9XMsfv376Nx48bw1Mu4KLZOUkREBA4ePIiDBw8KXuj50pI7yopDkkRUbsSuSw1eeYcpHUG3mc+Kcy0uKWU8GmghJXZtsnf9I661KTpRW/uN3gixViFWoedaWwAYG1f/O8y3ccPuw9T3vipalvUfzm1toTD1gC9GAIitk7R+QQryM24Kdq8zlpbcUVYcZ0sSQQSSEYSkLKUXhpnLtzKxROzz+4aFgnZoGNTtJSZ9aseQFyCRSJCdq8KqtH2C06M6us6EuqgYD3LyUSPoOUilUqsWYnVU4Vb2uGwBoy/E+o+JwNazh7D17CEDcbYxeTke3rmHjcnLjQo4/Wu0hWBSVvcDAPz3339W65ONkIXUVlaKtLQ0+Pv7Y+vWrTh69ChatmyJ5ORknXPkcjmkUimkUimys7OxYMECtGzZEnv27EGDBg3g6upqcA22tKpYmhzCHvMhVB6ErhXsTTsK0GkzKaIvXmrWEAAgk8mwIHokU9fInLXJ0esSAHy99ygAbSwQYL1CrI76rrLHNZXohW/jZsWKFUwtO1Pfe/3rrIyCydTDvS0tFLTLmtzDEwXqQs450AIgwK86fDrUw/iZhkJA/xpsNWc+y44jrTjOVoCWCCQjCElZSi8MEoDTX/vY2cuM2f/Y2cu6x5/UPZq5fKvg9KiOrjOx+rt0AEBY3+4ALC/EKtTywnW+JfCNa0qkCR2ffR79c3JMHIoKC3UsULYQhXQtpOvXr1utT/ZiKeSBwRpWCq4FOjU1FXFxcXj06BHefvttlJWVYebMmToiycPDA/7+/igvL0dKSgrmz5+PsrIyjBo1CtevX0ft2rUNrkF/vrZ+OCBWHIK5CF0rklJ/YDbtFkSPNGjzIPcxAG0pCrawMWdtcvS6BIBJfDRr1iwAlhdipe8BoaGhgs+1xv2Ca1wh91yhc2CfR/8cHx9vUGi7srjisgWFqYd7a1go+EQY7bJWVFKMXFUe5q5MMmhLC4DMf86jQlPBGS+kfw3sOdvDuuNsVhxHQrLYWYixTG8AMDpuKbbtPwZPdzckTxnLnLMqbR9iFq0FRVHwV3rh4aFUm83RmrQfMx1/XriKlYd2oE6jehb3Jzbrm9DzTWWs4+vHWu3Y5wHAwzv3IJVJoanQ6LS1RWa9H7/8GmvnfwrAepns2BmI6AWbvZDaIvsSV9ajP/74A0OGDAFFUVi2bBkWLlzInL9gwQJMnz4dEokEFEVh7ty5WLBggc7rU6dOBQCsW7cO8+bN05k3O5MU/XDgLFnhKhskix0/ZG2yPqcu/It2Y7SJGWxxzzN1DxB6rpBsdVx9WbMd+zxAWwSczvwpdkxrYUkWO3aWNLp4LP1wb40MdsbGY2dlowXao7wcqIuLIJFIsHRaIufYXccNwOmLmWgdHIrfNuzReY0r8x59rEBdiFxVntNkhKuMkCx2dsTU7hq9G1fdT/uHYBfyS5kxEXVrBej4gzszFEXhr3+uQ+HpYRVxBIivhST0fFOWGb5+9C1i+hYjoe3Y59E/dx4QbtDW2vFUABA+crDV+qJh77hGREQwIoJ24bDFLiPXLu+wYcPg7+8PhUKBmJgYxMbGMq/RliSpVIrk5GQdcTR79mxGHNH9GHN7IxYeQmVH6Nrk7uaKpNQfmPihyrg2vTZjCQCgRo0aVutTzD1A6LnmWt+FxHkKbcc+j/45PDxcUFtnhG3xoIvHLtmQgrkrk2ziKsZnYaGtQ4nvzYJMKgNFUbxjX79zU+d/rn64aiIBINYdO0IsSDaGvYtHu+PVrRXAZAeqTPz5979oP3YGQju3w4Itzj3/5Jg4HN2Tjs4DwjE1xfxkBY6ua2QOxUVFGN6kMwDg5MmTNknFTu9CKpVKyOVyq+8y8u1eBgcH62SrU6vVWL16NebMmcOc4+vri7y8POb3uLg4TJ48Gf7+/syx8vJyXLx4UdCYpl4jGEIsSPw429pE10mqrOsSAMjaaL+TS5cuRZcuXRw8G37E1F0zhTPUNrIW1qyDRFt4/JS+8JIrrG5BElJbSf8c/d+DerdArioPfkpf3D5w3uwxrVXn6VmCWJCcCPYunjP4aVvC51u1puB+o4c5eCamuXjqLDQVGlw8dVZUO32LUXCbEEhlUgS3CRE9ByF1kyyZGx8eepnabAG98xgVFcVYk8T63xvzmefaaXVxcWHEEfA01ig+Pl4nYx9bHCUmJmL69OmQy3UfRPX7AozvmLKDnc29JrFUxiBpQGtpzsjIcPQ0CCbQr5NUWdelnHwV87MziyPAspT/+rFD+jFDYoiPj0e7du0QHx8vuq2puTka2sIz+53pjDVJbMyOsVgfIUkM9K1A+m1mvzOdmaMQTCVU+DB5pslrtGb8krPVK7IVRCBZGf10p+zfhQbXOisHTpyFRAK0793V0VMxidBU2/qiQ981z1yhRfdlqm6S2P6sndDB3IWNLSbMDeY11o5OW0sXNkxLS8Pbb7+N4uJig3MlEglmzJgBX19fneO+vr6YPn06pFIpCgsLDdpKpda//VkzsLmyBEnTZGZm4r333kOnTp0qXaHOqg5XGm76GIBKvS7NWvkNABhseDgjxlzxuIq/8mXapOseyeVysyza6enp0Gg0SE9Pt+h6aGxxrzL3IZwtJszNyGas3YfjYuCn9GUy1QmZJ5dbXoG6EHNXJlkkMj4cFwOZVIYKTYXJa7Rmdjpnq1dkK4hAsjLm1jdydgrURXiQk4+A2rXg6u7m6OmIwpgI0hcdXLWPxMRIsTFWN0noXPX7EzsXUw+q1ljY+BZ9PvElJDuUfmHD1NRU3LhxQ6e2EQ1FUVi0aJGO5QjQWpIWLVqE8vJybVYuvbYajUbwNQotAqkv7CyhMsRB3bhxA7GxsejatSsmTJiA33//HW5ubng9orOjp0ZgwbUOVZW1ad33BwEA/fv3d/BMTMOO32RnkePKDmos06al94bw8HBIpVKEh4cLOt/URpot7lXWeAgXW+uHPt4hpC1vrM/EYWPgJVcgV5WHJRtSzLYo5arymD7MZeKwMVgydYGguCR9YWcJz0qmOxKDZGX0MwetStuHmcu3QgJtcT6uXTpT2Yacgc++3oUPP92AQW+OxFtzPnL0dERlmwOgE0fEbguA82euPm2Rcc7YvC2Jefpf11dx78Z/qFu3Lnbs2MF7ni1ja/h85I35zrPnA8Dg59OnT6NatWo6bZKTkzFz5kzmd/0YpPj4eERHR0OhUMDDwwMAdwySteDL+Gfp++sscVB//PEH1q9fj8zMTJSWlgLQujv26fkiZs94Da1bNoRKpYZPnTdIDBIHjlibuNaYqrI20fFH+/btM7g3OAJT31OuLHJc9wq+e6Ej4iNtHe/EFYNky/gavkx0fMf15wOA82cxMUl0GvDZ70y3W/yQLeKzKlsclJgYJLsIpIULF2LHjh24dOkSPD090bFjRyQlJaFJkya8bVJTUzF+/HidY+7u7pwuNlw4SyAsoM1cRydnoJM1sBcc9uvOGiTbeuRHyLx8A+uO70aNJ6LD2ohJrGBKSPCJIGPCp6iwEAV5Kt4+R4b0QEGeCl6+Smw9e8jomOYKKGuJsOheEbh15TqUSiUOHjxodj+WwLdwG1vQTYmnJk2aYOjQoYzQ0RdHCQkJmD59OhYvXoy4uDjmODvFN6C1Lt2+fduq18ue54oVK1BaWoqSkhJQFAWpVIpp06ZZ9ADjyKDsf/75B19++SUyMjKYe7C/nw86tG2ED2IGome3EJ1kIEQg8eOMa5Of0gveCk8DIeTsa9O+Y2fw8mRtsgNrpffmQkxyBVPfU6HCh32uWq2GSqXi7JMej+8eYw0BZWsRZs0kDUIwJ+mBUPHEJRKMtbUntDDLVeUBAOQenqjm62+RuHGWaxOK0yVp+PXXXxEdHY2MjAykp6ejrKwMffr0QWFhodF2SqUS9+7dY/7dvGmYErEywE7OwOXW4OzJGzQaDS5cuw13uafNxBEAHN2TDk2FBkf3mPaL5nM3o13Uzp84zRwzlUqbdrMDYDRuqTD/Medx2iXOGjFC1kr73WfkUADahzFLsCT4li/pgbkFHFNTU7FmzRrGVU5fHM2ZMwcxMTEoLy/H1KlTddJ8z5w5UyeRQ05OjujrEQrtHlhcXAx6/0mj0Vjsn29vl7u7d+9i9uzZ6NGjB0aPHo3Dhw9DKpVixJCO+PvE53h0cz32pM1Er+6hNsmUSLA99NojATjd7Zx9bYpauAYAULNmTZuOIyZmx5TL8ZkzZ5hjplJp0252AHj7VKvVkEgkBvcYejxrlGJwtpTfliYJ4Et6wHccMO5WZk6BWkckOqDdA2mKSopt5sZYFbCLQNq7dy8iIyPRvHlzhIaGIjU1Fbdu3cKpU6eMtpNIJAgMDGT+2fomaCtMZbJztuQN+gG9py9eQ1l5BZq2ftGm43YeEA6pTIrOA3T9ooVmbwOeip2je9IFixVabI2dGm0gTuixNyYvZx52W3cNMxiPtvqYG69kDDHXT/PqxFFWGdveiQJMiafr168jKysL//77L+bOncu8Nnv2bLz99tsAtPcNtVqNCRMmYPbs2cw5iYmJ+Pvvv7Fr1y5s2LDBptdBxyIplUr07dvXKsLGHg8p+fn5WLJkCfr27YtBgwZhz549KCkpQd/eLfH7/gQUZm3Gtg0foVlwkM3mQLAfpjLZOdPaxJVo4ubdhwCA+fPn23Rsrpgdrs0jY5YW+l6anp4u+J7KzhbKVQdp8eLFUKlUcHd3h1QqRWhoqMF4ALe4shRrZq6jN/JcXVwFne+IJAHmiicu97rgQe116jTZUyzRsUh+Sl9EhL9qsbgx9r5UdhwSg/Tvv/+icePGOHfuHFq0aMF5TmpqKiZOnIjatWtDo9GgdevWSExMRPPmzTnPLykpQUlJCfO7SqVCUFCQU7gxVDb03SrGzPwcW34+ghkrk9BpQG+7z4d2p/PyVcJTocDwqEhsTF7OuLu17hrGuOa1aN8a21ekIrhNCC6eOmuxqxo9trunB0qKtK5FbBc8sS5x5rjQ8bkTmuprYN02ACyrhWSOm5wlfQvp19XVFY0bN8aePXswatQozJ49GxMmTIBGo4FUKoW/vz9ycnKY31etWoXExESsXr0aHTt2RHh4OMrKyip97RBrUVxcjE2bNmHnzp24d09rSZXJZOjQtjGmvTcYA19uK/rzQ1zsnkLWJuugvy6VlZXDo8PrAGxX780YXLGGtCscLaaOHz8OAExyl9TUVISGhiIzM9NidzV6fEAbA1hcXKzjgif2Hi32fKGxpEL6eumllyCVSqHKuGXyXMC4S5s1YmK4+jC3X30XNP04oA4hbbHjwC5UaCoqjZtaZcbpXOzYaDQavP/+++jUqROvOAKAJk2a4KuvvsKPP/6IzZs3Q6PRoGPHjvjvv/84z1+4cCF8fHyYf0FBZIfTXPStXAcytCmuX+rV2SxrBmCeFYSGtswA4LQK0a55R3btZwTD1JREDI+KxPYVqRbVIKIz0ZUWax9wpDKpjoWIyyXO2LXSFqdVs5IEz4vPMiXUpU8/u5sY+KwW1rAscfUhpN+ysjJcv34dAwYMwF9//YWpU6dCLpdDKpUy9Y7Yv8fFxeHw4cPo0KEDxo0bh7KyMqfODGcPysvLsW3bNowYMQKdO3fG6tWrkZWVhecCa6Cavxe+SH4TR/cnYtCAdsR9zkLI2mQd9NeldxauBqBN7/3dd9+Zbc0w1xLCdqVjW2ukUinjjqdSqaBSqbBixQpGMLRq1Ur0HPnGZ3839a1EXPduY9cqtNYbe3xj7tBi1wcXF+GPo8asFtawLnH1YW6/+tYldp2miztP4EDGYVRoKiCRSKqkm5q1cIRLot0FUnR0NM6fP49vvvnG6HlhYWEYO3YsWrZsiW7dumHHjh0ICAjA6tWrOc+PjY1Ffn4+889WAdim4HIDqGyw3Soe5anwIDcfgfXqwN3Dw+w4G0vic2gRMnZqNCMU6J/HTo1Gw+ZNAWjTPbPHMGdMfXHTf0wEPBUKbaC9TIpJ86abtPwYG3d4VCSkMik0FRrB8+KLS7KVS58QQkNDDVw6xMK1wApNGV5UVIQrV64wbrd00VjgaXyRv78/k8zh9u3b6Nu3Ly5evGh1NzVnKpJoDI1Gg3379mHs2LHo2LEjkpOTce3aNTSsH4Tk+WNR9GArXF0pPMopwOKlPzh6ulUGsjZZB313v69/OgJAG+BvyYaNuW3ZAoTtCjdt2jQEBgYiPDycuf+oVCqdGkZix+O6x0RERMDb2xsA4ObmJui+Zk2XaXNjSW1Nh5C2kEll6BDS1uw+uFzmzI0jmjhsjE7BWj5x5+vtY1U3tapWzNURbpV2FUgxMTHYvXs3Dh06hDp16ohq6+rqilatWuHff//lfN3d3Z3x+af/OYKqUluC5pt9vwMA2vbU1jUx96HcGg/zbKHA/jn/US5zDtvCE9wmBFKZFMFtQnT6EWLhYYsXeu584ki/P2PX2n9MBCbNm24VYWMyocOT3UV2HI61sEZFeAAGC6wYi1VZWRlu3LiBa9euIS8vD+Xl5VCr1dBoNFCr1SgvL0deXh6uXbuG9evX486dOwgLC4O1sXeclhjKy8tx4sQJvP322+jYsSPi4+Nx4cIFBNaojhlThkB1ZzOunv0cH703GO7ubpjxwVDUCwrAjA+GOnrqVQayNtmG0rJyAMCsWbMseiC3xsM8+75F/5yQkKBTvFoqlSIyMtLo5hLfZgvfPcZUfTb9/oxdq9Bab0JwZFKHjLMnUaGpQMbZk6Lb0qICgIGI4RI2Qh/ajZ3Xu0N3yKQy9O7QXfR8zR2zMuKIZBB2iUGiKAqTJ0/G999/j8OHD6Nx48ai+6ioqEDz5s3x8ssv49NPPzV5vrPUQarsvDRqKs78cx2pJ35CtVrOmSQjOSYOR3bth5uHOybMnMIIBq7Ypf5jIoymCLdmjJCjmfLKG/j37EX4+Pjgl19+sWrflsQg8fmuG+uTTp0NaBdyvjH37t2LXbt2YeDAgejXr5/JMa2Bs9QnoqmoqMDu3buxbds2XLlyhUkuUs3PFxGD22F27AjUCvS36RxIDBI/ZG2ynF9PnUPP/2mTtNgyvbclsNP9u7m5Mfct+l6kVCohl8t17hvm3BuN4cjSAGJ46aWX4ObmgpyjNyzuy5IYJK6U1ULinTqEtEXG2ZO8Y5qbPtwSKlt9InvhdDFI0dHR2Lx5M7Zs2QJvb29kZWUhKysLRUVFzDljx45FbGws8/u8efOwf/9+XLt2DadPn8Ybb7yBmzdvYuLEifaYstk4U9Yfa3D+6i0oPN3hH1jD6HnmxBiZaiO0z4unzoKiKCj9/XREDW3JKSspxcM797AxebnOcdqCwx7HnDTbjnR1M4ZvgLZoIl86fb4sTELcxSzZIaR3MUNDQ3XGMmaJoVNnq1Qqo5aafv36Yfny5TriiD2m2F1iIe+HM6TApSgKv/32GyZMmICOHTti/vz5uHz5MoJqB2LiuN649OcyZN/8Cqs+n2RzcURwTqrS2jR+tvZeLiSzrVgXWCHnCzknNTUVKpUKvr6+OHjwIHN/oO9FpaWlBjE/+vcpY9Z2ITjS1c1c+FzDhLqMWZJVjbZSdAhpy4xlzBJDj5Vx9qRRa425GfCMYer9qMrZ5eyFXQTSypUrkZ+fj+7du6NWrVrMv23btjHn3Lp1i8mgBAC5ubl46623EBwcjJdffhkqlQrHjh1Ds2bN7DFlAoATZy+jrLwCDUJbmAzUNifex1QboX3yudLxoS+CzEmcYKw/a2FJYgsAeO29/wHQullxQQuSFStWMIu9PdzFaEGRmZmpM5apxdySxd5cEUO/H5999hnatWuH+Ph4wW2tGZvE11dmZiYmT56MTp064YMPPkBmZiaq+/vivXcGIPv6Bty8sBxfLotCkxdqWzwHAsFZuHUvG4DWvc4UYu9pQs4Xcg6d6l+tVhvEDkVGRupkNmS/xr5PiU2cYKo/a2HLuEu2IGGLAHu4jHEJHiECxhL3L3OFDP1+xH0+Dz4d6mH8TOFjWys+qarFOeljF4FEURTnP/aDzuHDh3VuNkuXLsXNmzdRUlKCrKws7Nmzx2rZXwjC+HzrHgDAgHHDTZ5rqnAr10O+KcuLUMvMxVNnoanQ4OKpszrHaeHj6u4GL18lMx/9udECS0ziBHtgaeHZpi25U+LT0IIDALPY23PHkT2WKRcSY+nGbZkggZ5jSUmJ4EKRNGIezExdB7uva9euITY2Fl27dsWECRNw/PhxuLu7Y+zI7rh2biWyrn6Jz5ImoFo1b8FzJRAqCyWlZaDjAtq3b2/yfK57mrHvm5B7oJBzjFm9U1NTtYl/pFKEhYXpzKUyJH2x5UYaW2ywRZE9Y1CEjmUsZsnW4oGeY1FJMSo0FdhxYJfgtkLFpqlrqGpxTvo4pA6SPXCUn3dVIrD3m3iYq8LOm3+anerXHvE5fHFD7OO02GDPgz03+hxajImNQ7IF5sRD6UPXQjp69CiTUUkfR9Y0ojFVU2Px4sXQaDQGr/fs2RMqlQpKpRIHDx40a+5CiI+PR3p6OsLDw5GQkGDyfCExU+z3h37g4IsVWL9+Pb766itQFIXiYm09Lg8PD7wcHoqZUyPQqmUjC6/QupAYJH7I2mQZb85ahg17foWrqytTZ0gs9orNEVJHTv+7z1VfiW7vLPGO1p4HXwySM9Q0MhYjFNS7BXJVefBT+uL2gfOCX7Mm42fGYMeBXRjaeyDWLzAtVNZ+twlzVyYBAGa/M91ozFSBuhC5qjze+KjKGOfkdDFIhMpHYVExHuaqULNubU5xJNT9y5QVyFI3MoDfxa3/mAhG+AS3CTGYB9s1j92HpZYba2FN170rV67wvmbKDUOov31WVhYWL14sKKZIH1M1Neiir47wpU9LS0NmZiamTZsmSBwBT+MP5HI57/vKfn+4rv/x48f44osv8PLLL2P58uUoKipCeXk5enV7Eb/smouiB1vw3dfTnU4cEQi2ZOt+bWbVPn36cL4u5H4lxAJkDUuOEBc3/bmwXfMA3dgjZ8mYaa+4S1PuZ0KsNHNXJuF21h1GFADiLB+OyJ4mlLXfbULG2ZNYMnWBIHEEaK89V5UHL7mC932l3x8ARq+9qsc5EYFEMGBV2j7U7f82AKBjvx6c53CJCC6xY+ohn6+fkSE9MDKkh1HhJERc0f1fPHXWYB5s1zx2X2xRJ0bAWUPsWRtrFPkU6m9PF0gUGlPERkhNjWnTphm8HhUVxewCCXmQMScxhTkPJWLddOjrf+WVV7BhwwYMGTIEPXr0wMaNG5GdnY12bZ7H9o0foST7GxzYNRc9u72o09eqdftQv/nbWLWucta4IRCEsGr7Pia9d1xcHOc5+t9XvhpCph7wub738fHxgmIRxdxT9Oei75rH7kvfLVmogKsMbnvmYK3ircYwJgJmvzOdKfrK9Zqf0hcABLnZcYk9W7i4iYmpoovZWiKAKnOcEhFIBAOSUn9A3mNt5rO+o4dxnsNlGRIqmoT0U5CnQkGeyqgVhz0e3zjGLFj0a8FtQrBqVhKT6Y62OG1fkYqNycsFW5Poc+lsec6AVCYDwP8wIQSh/vZ0gUT6PDoYmV7kzYXuZ8WKFejZs6fBg46Q7HY0XA89pgSQOQ8lQh7A6HPCw8Px/fffY+TIkejSpQuWLVuG//77D82Dg7By6f9Q/PAbnDi0GBGDO0Iq5b5lL/p0B27efohFn+4w+R4QCJWV+V9uZ352d3fnPEf/fsX3/Tb1Xea676WnpwuKRWSPyTWO0IQ0oaGhWLx4MZOoITU1FaGhoUhNTWUSOJi679Euys5gebI2Qh72uUSMfvFWSyhQF2LuyiSDfiYOGwMvuQK5qjxBAoZL7JgSQOzrt2aWP2tahipznBIRSAQDpo8bDABwc3VB7QZ1BbcTKprYcFmYhkdFwstXCS9fJaewoS1Mqpxc5hy+cfT7d5e6QC5zg7vUhXmNtiRJZVImJfiRXfvx8I42q6IzpvAWSp9RgwEAOTk5ZvfB9bDPtyurL4iEWF+MWXXi4+PxyiuvYMWKFVCpVJxCSIyliutcU+3Z128tFxe1Wo3Vq1dj4MCB6NWrFxISEnDlyhXUC3oO82eORMG9LTh/4nNMmtAPrq4uJvsjBV4JzwKlZWUAAG9v4QlI+L7fpr7LXPe98PBwSKVShIeHc7ZJS0tDz549kZeXB6VSqRNjxB6Hq28XFxe4ubnBxcVFJ9Mn7V5MpwXfv38/srKyAEDQfc/RLsq2hOtBXl8o0OcA0Dlu6sHdWLrxoN4tENS7BeauTEKuKo9XBImxVHGda6o9+/qdVYg4s4uiKYhAIhjQppk2pqFZ2Eu853AJEj6xI1Rg0FYgANh69hC2nj3E6ZpHW5hKiorhqVAwsUZ8bnF+bgq08AtC15rB6BLYFB1rvoC2yvpoWOAB5YNSTEuYhYDatTBp3nS4ursBANw83BFQuxbGTo0WHAc0dmo008ZR6F+7h6cnAP5U3+bC93Chf1yIeDFm1UlPT2ceBpRKJfPQwYb9sGFqV5jrwUSMP31oaCikUilCQ0NNnqtPWVkZtm3bhoiICHTt2hVffvklsrKyUKd2Nfj4yPHJgnGYPuUVrN1wABu3HhbV96QJfXHj79WYNMGwxg1xvyNUFXJUWs+GefPm8Z6jfz/h+36L2Vih7yutWrXCH3/8wRuLSMceFhcXM/GHbGuQ/r1JoVAgKCgIwcHBCA4ORr169VCzZk0899xzCAoKwqxZsxj3Yjc37drk7u6OwMBAREVFCbpvGXNRthf2dPHjEwr6x009uBvrhxZFAOCn9IWf0pezH7aAMadukRhLToeQtpBJZegQ0tbkuULQn6+5rnLGrsHZ3e+IQCIY8NnX2qw+/UYN4T1HqPChRRMAk/E5tIvaugVLdc7Vf+jnsjCxxRndz8GtP6KVf320qd4AgZ4+cHviblasLob6cQF8fXzxQu36iHnjTZz55zz8lD4AAHdPD7i6u4nKHvfzpjRsTF6OIp6irPZCX7h2elm701lRUWHVcfgeLvSPmxOkzD4WHh7OPAwcPHhQp+Ai16JrjoVHzOJN7+hmZmbytmUf02g0+PnnnzFmzBh06tQJycnJuHHjBp5vWA+fJIxD0YNvIJNKkZ+vxrLVPxl1lTNX6BD3O0JVIDs3n/m5S5cuvOcJFT70vQmA0e8/20WNXTOOz3VOfyOHHuf48eNMH66urqhfvz4aNmwIX19fuLhorcSFhYXQaDQAAF9fX0yYMAHnz5+Hj492bfLw8ICbmxsTtygUtVqNFStWOCwGyZ7JJfiEj/5xU+LDWD+0KJr9znTcPnAetw+cN5ni2xwLjxgBkXH2JCo0Fcg4e5K3rZj+9OfLN39LRI6zWr1oSJpvggGBvd9Edp4K313JgKubq1X6FJLue2RIDxTkqSCRSEBRFHOuqbb66bBHhvTA8/UbYsuWLSgqKUazF3XrAeU9zGEWITcPd3j5eOPqv//CBTK8/vrryMzM1BlfzPUBgJevElvPHjJ6vjVSeAvtl071/eeffxqc7yxpY82BK1WvOddjLK0u3SedsrtOnTq4dOkSk+6baw70MTc3N2g0GsZ6V/u5mhg3sjOmTxkCpfLpPWnVun1Y9OkOxj2O/lnfGlS/+du4efsh6gUF4MbfqwW/T+z+uSxMtoCk+eaHrE3m8c6CVVjz/QG4uLggIyPDav2aSvlNvy6VSuHl5QWVSqVTP85YqnD2/Yh2E27fvj02bdqEgoICNG+uuzY9evQI9COZl5cXPDw88O+//0Im012bxKQnp+cPQFA5BFusCab61E/zXRnTR7PhSg3Od00SFykgkwAVFKhyDW8/dMwUuz07xTcAnXTfXHMwlrJcH/358s1fTJ+mxrAHJM03wWyysnPxMFeFgDrPWU0cAboJEfgy1NEual0G9tGxTpmyVulbTd6bH4ctW7YgIyMDHdq1R3JSss75HoqnDyXlpWVITkpGqxdb4tixY9iyZQsaPf+8znh8CSD0M9+JyRhnLDbLkmx4xrIGclVud5a0sebAtVNsTvpZdj987n50/NOlS5d0LEjsthcuXMCUKVOQnZ0NACgtLYW7myvemdgXdy+vxX+XViJh9mgdcQTousdxucrRlqOO7ZuaFWdkzP2OQKgspO46DED7wG9N2C5wPXv2NEgEw3ZRi4qKYr7vYt2Ho6Ki0KZNG2zYsAFHjx5F+/btkZysuzYpFArmZ7VajeTkZLRs+XRtev7553XG5LN+62e+E7M2GVsTzHWVE3tfdnbLgim4rE9si5XUyw1u9Xzg2bwGPJrXgEfTAHg0rwHP5jXgVs8HUi83g3643pMdB3YxRWL1LUh8MU1+Sl8UqAtFJ3Pgi/cqUBfyuhiawtnThBOBRNDhk407AQBq1WOrpKtmxxXRCRH4MtTRD/dTUxJF1f/RF1DvjH8LRSXFePvtt1FWVoZZ8TMNRJJEIoFEIsHK1aswK34mysrK8PbbbyMvLw9bdnzLZLZLjonjFTPs4/3HRKDLwD6QyqRo3TVM9Jz5+hWLMXG1d+9eg2Ni/PCdDWvUb6L7ocVRaGgop7sf7TZDu/zRr3fo0AGtWrVCSkoKxo4diyNHjsDd3R1yuTbDVvVqXljx6duoFegv+Lr0XeloF7ljJy4RoUN4Zil9Yok9duyYVVzF6PsDACYhAlciGPZ9Rv9n/aQ0+rDvrxEREdi3bx/UajWzNs2cOdNAJNFr06pVqzBzpu7atGrVKh13OSGxoBEREejTpw+kUinCwkyvTcbWBEs21MSIq8oc2A/wP/hL3GS47ZIHlV8FSjwowEXvEdxFCpmvJ9wb+cO9oR/eGhnJiKMOIW0N3pOhvQdCJpVhaO+BglwIxWbW00ffnU5ITaXKDBFIBB1+OKw1kRbkP7ZKoVT9h30hGeroB3z6Z65U23xCwM9NgWoeXmj2YnN8PGc2c5wWSTKJFC4SKTw9PZGyPAXz5sxlzvl4zmy0atcGLwY3Q/mjx9BUaHB0Tzoz56LCQp3x9EUOu66SKYxZesQkttCHS1zJnsRecWGvgn/mYGlgr5jFnD43MzOTM4kDHf+UkJCAjRs34urVqwgPD8fgwYPx888/o6ysDC/3aYMThxah4N4mLEmIFGXtYYsi/ZghkqGO8Kyz99hp5ucHDx5YxeLNlVCGLxEMoHs/on/mSrXNzsDJditTKBTw9vZG8+bNMXv207WJFklSqRRS6ZO1KSUFc+c+XZtmz56NNm3aoFmzZmjWrBkj4ug5q9Vqo2nE9WMnjSGkJp05G2pi7sfOblkwJ+5GKneFxwvVkFesQoVGg0K18Xjla/dvw+OFath76hBuZ91BxtmTBu/J+gUpyM+4ifULUgS/Z2LFJ/taxSa6qOyQGCQCg7qoBMouo+EhVzACxtL4GLGxNhFNOqGkqBjunh5Q+vvh4Z17kEgkUPh4o3XXMJz+7ThzbkGeCgG1awEAE6O0Zs1qtGvZhoktSk5Kxqz4mUybxMRETJs2DUlJSTrF/uYlLMDU6VOfznvfPkQMGozOA8IxNSWRNw6KfX0AmBpIY6dGWzW2SChc7/fQxmEoKylFQEAAfv75Z7vPCbA8Nkiovz17PDpuKCoqyuSYpuZXUFCATZs2Yc+ePYw/v0QiQZewYMz4YAj6hbcWXZSXHRtEiyJaCAmNGXJEfJEQSAwSP/Ta1P7FxnAxsnkBAO1bNMaQXu3NHsvd1RWtmza0SsFoR9JgwCTcysqGUqmEXC63SnyMmHtSWloakpKSQFEUM4esrCxIJBK4u7vDzc0NYWFhyMzMhFqthkqlYgpn04KiUaNGGDBgABQKBTw8PJCcnIyZM02vTQsWLMDUqdq1qbi4GNu2bcNHH33E3NeExGKKvR/aAmPvt34Mkj0xJw5GbNyNxE0Gjxeq4cc9u/HaqNfw0Ucf4aMPP4Kvtw/n+UnJSZg9dw62bdmGbl274OWXX8bI3kONzs+a8TzsvmhRxBcHZY/5WBMxMUhEIBEYfjh0AsM+SkaXV8IxbcUih8xhUL2XQFEUJBIJ3lkwA6tmJUFTodERQoA2EYKnQsEIE1oUvP3K66hevToAwL+m9n99keTr64u8vDzm99lz5mDGzFideZRWlOO3+5eY3/WFEP0zbbERmlDCEWxb9hU2Jy+HTCbDiRPigii5sLbY4evPkmBhc8UVe8wuXbpgzZo1OHz4MPLztRm0JBIJXFxkKCsrF50sQR920gUxooivD0vmYm2IQOKHXpsqCxKJVmhZIrFq16wGfx/htYv0+eP8FQDAunXrzEqxbyn6iQ6ioqKwePFipr4Q+39aQIWGhiIzM5Nxw9u3bx+qV68OqVQKf3+ty62+SNJfm+bMmYPYWN21qby8HBcvXmR+Z9+zAK2lhhZpXMljzNlwsjXWEkjWFjt8/Ykdx72hH67dv40WLV9E2ZNaXvFxcZg32zBdfVJyEuJmagWyq6srzv91Dg1rBmF58hdGx7QkWYKxvsSIIlvNx5qIEUimKxASnhmWb9NaFwa/PdZhc+gysA+O7klH5wHhjAWELUzWLViK0uIStO4ahqkpiQDAuL0pFV54rk5tlBaXwM3jaZX1GTOmw0UiRVxcHADoLECJiYn4aPpUVFC62WPcZC5wk7qgVKP1e+8/JoKZDy2C2CKJnVCC/bszEFBbm3HJWnsh+v7tQmBnhxPaH+3nbw7GxjPG+vXrcf/+fSxevBiLFj3dJHi+YSCi/9cf0W/1x7qNv+hknTMXfVFkjgWI3QehcrF+RQzknu68rxeVlGLVun1Qqw2Tqwgl+5EK2TmPzW4PCigtK0dxaZn5fQD493YWcDvLoj4AICQkxOI+zIHOQgfoWmDouMXMzEz4+/vj0qVLCAsLY+ok0eKle/fuCAgIAADI5U83bKdPnw6plH9tmjp1KpNxlcbFxQUuLi5Mdkz2fZIWQUqlkjOW0px7YmWC7QIm9GGeLQCE9jdx2BjB/Uu93CD1dsfz3s9j7uw5jPhJSEyEQq7AjOkzAAkACliUtIh5HQDmzp6D559/HgBw6PwxnbnoizRj1yEWfVFkjgXImvNxFMSCRGDw6fIGSkrLsP3KcaNxK46ETgXOTqVNC5a2HTvgt99+BaCtdVRcqIaHQg4vhQIyiXbXjr0A+fr6IicnBxWUBuVUhUG7049vQV1RajAHc1J02yqttxBuXb6K6N4jAHCn+haLtdPAcrmD2DP1eFFREbZu3YqdO3fiv//+A6C1FHV4qTH+vZaFh49Uoqw81nZ7c1Y3OmMQCxI/9NqU/99mg4yGVZGSklKkH8yERmP+o8Zr45eiuLgEf/zxB6RS5wudpmsl0S51+lab9u3b47fffgOgdZNTq9WQy+VQKBSMRYlrbdJoNEwNO3a7mzdvorTUcG0y597pDKUeHGlBEtOfOf271fOBzNeT+Z1tIQK0QnjGjBlYtGgRI5QBIHFBAqZPnc78fu7UXxg49FVmbHOsPLZ+fyoDxMUORCCJ5cbdB2g0MAr1gxtj2b5v7Dq2KfHAfn1j8nIDgUS/PmFqDKa/GYPiQjUoigJFUZBKpahWozo+SUrWufnQJCYmIjo6GhoJ4CH3QO6DR4yL3znNQ8aCZOk1Odr1zlgtJGfDHFcQY4s812vl5eX48ccfsXbtWjx8+BCAVhQFv9AQ774TjonjekEmk/HGCdHubFzixdpub87qRmcMIpD4edYEkjUY/84ypH59CHPnzsWAAQPsNq4p8UC/zo47mjZtmk4NtdTUVMTExGDy5MlQq3XXpurVqyM5mXttSkhIwAcffMAIQrpGkkQiwYMHDxgLkqXX5Ayud46MQRKDOW5jRXVcUSHRQCFXQO6h/b7riyR918rEBQmYPHkyCtWFTDuqXIPivx8w5/DFCRmru2RttzdndaMzBqmDRBDNsm9+AgD0Hj7QrPaW1O4xldaazmK3MXk5Uytp7NRo5vX+YyIwPCoS65JT8N+tW4xLAl1wNmF+gs4C5Ovry/wcFxeHpKQkFBeqdcbMfpTNKY70r5Pvurmy95mbmc6a0P7Pzow5mZKMZUhiv3bw4EGMHz8eHTt2xMKFCxlx5OujQGHWFvx9Mhlvv9mHsaCyawhxZZPTzzgHWD/rHMliR3jWmRKjXZe+++470W0tyYZpKvMancWutLSUqZWk7yYcGRmJlJQU3OJamxL416b4+HgsWLDAYMzs7GxOcaR/nXzXzZW9r7KWerA3YrO2SVykqJBoDLLWzZg+g3HDBAxdK2dMn4FCdaFOO4mLVCctODtrHde8uOomWTvrXFXPYkcEEgEA8OPhPwAAfUeb9xBmSe0eLvHAJzxoMbR9RarOa/T4xzMytKlSvRSQSCRYtmwZ5s6Zw5yXkJCA7OxsnZtTYmIilq9YgZwn1iNIJMgp4U7BqX+dfNcd3CYEUpkUwW1CmHmLqe1kK2g/ekdi6oGFnWaWnTKXq4gjjf4izx6jV69ecHNzw4MHDzBt2jScO3cONQKq4cPJg7AkYRzqBQVg4Zw34PkkHkS/DhENV8FVLvFi7cKspNAr4VknpHl9uLq64MaNG6LbWlK7x9h9hY2bm5uOWx37dXr8jCdrk0LxdG2aY2JtSkhIwIIFC5Cdnc1YjwoKCgRdJ991h4aGQiqVMskuHF3q4fr169ofJI5/HDWVvpstSuhzx8+MQVDvFgjq3cKwnUwChVwBmVQKhVxbBFhdrIa6pAgzZszQEcSAViDPmKGNSdJvBwDb03/knB9Xim9TxWqtgbOnY7cUx38iCQ6nrKwc1+88gE81P3h4eppuwIFYCwlbAHGJB7bwGDs1Gl6+SqYdlyihx893KYdvgD885B5YuXoVFi5cyJzz8ayPERUdhaKiIkRFRemmUp0/HynLlml/oSjI6vgZvc7gNiF4M+wVBLcJ4ayRJKYmktD3yRLcPD0AgNNv3d6YU58oPT2ds4gjjf4iv3btWmRlZWHRokX4+uuvUVpaCm9vb7w5phduXViDe1dW45OESHww+VUD8cFlFaLRF09c4oVPYNHHR725lPN1AoHAT/26dZh7gBjEWkjYIkj/vqJ/74qKimLcdPgKt9Ljl5WVwd/fHx4eHli1Sm9t+vhjREVxr03z589HSorWCiCRSODnx7020eOEhobilVdeQWhoKGeNJDE1kYS+T5awZ88eAEDzBk0s6scacFldTJ2748Au5KryuIuvVlCQe8gR4B/AuNcVqgtRVlaGRYsW6ViOAK0ladGiRQAFg3YA8MWmVbzz0xd3XOKFTwCyxZ7Y+k5VGSKQCPjhkNZ61LKL+fU2xFpI2CKHSwSwBVf/MRHwVChQkKdi4nr0xRg9ftOe7fCouABX//0XCxMSmdfnJSxA1DtRUBeq8fjxYxQXF+P9D6bouDd88sknuH79Os5fvoS8Um4LEj3OxVNn8fDOPVw8dVZnblzztwRLLHNspFKty1h6erpF/VgDIQ8s9OIbGhqKwMBAhIeHQ6lUwsPDw2DBB7QZ+q5fv4558+ahZ8+eyM7OZl5rFdIA544vRd7t9Vi3PBpBdapzjkkLmI7tm8LfzwuPC4oMRAyfeDJW6FW/7bff/84rwAgEAjcjI9oBALZv3y6qnVgLCVvk6IsA/XtXREQE5HK5TuFW/XsbPX67du3w+PFj/Pvvv0hMfLo2LViwAFFRUVCrn65NU6YYrk03btzAvXv3UFjIvTbR42RmZjJFr9lzo7GWS50lljkuGtapb5V+LEGIyxgtJjqEtEVQYG0M7T0QfkpfyD08UaAu1BEXVLkGKNfNQqiQK/DJJ5/oiGB9t/9FSbplVtTFaly68g+ef64B/JS+BuMA/OLOWKFX/bY7DuwSLBCfBYhAImDtDwcAAK9Evma3MdkCgksE6Auu4VGRjKUGgIEYS46Jw6sN2iI5Jg4X8++gbsOG+HrbFri6ujJFYD0Ucsb9zjfAH+WlZYiOjkZsbCxcXV2xZs0ahLRrA+kLASYtN+z5GxNslrrUWUtovTX7AwBAbm6uRf1YAyEPLPTim5mZid27dyMhIQEHDx6Er6+vzoL/999/4/3330fnzp0xfPhw7Ny5E0VFRejTsyVq1tDWmsnJLUCL5vVMzosWMMdOXIK3lydycgsMRAxfPBBbFPGdQx8fMaSTyZgiPisUgfCsMmlCHwCwebFrtoDQFwFc967IyEjGUgPA4PX4+Hi0a9cO8fHxuHPnDho0aIAtW7RrE10EVi6XM+53/v7+KCszXJtatWoFmUxm0nLDnr8xwWapS11VjF0S4jJGi4mMsydxcecJrF+QgtsHzqOarz+nFamiQDdN/7Jlywxc/HNycnREc9zMeCQlJzG/F6oLcejwIWScPQkvuYJzHD5xxxZFfOfQx4f2HihYID4LViaSxY4A706jUFpWge+v/2G3MfkKrxoTFMYywb3aoC00FRpIZVJMmjcdF3/9E1u+3oxHj7LR6EkdAX3olN4ubq648s9lNGjcCJfLH0FVVmSVrHPJMXFMTSe6ZpOjuHr+Et5/eTQkEglOnjzJe54zpHw1No+0tDSsW7cOAQEBuHnzJrObqlAo0KRxTVy+chdubi5ImDUaAAwyzBlLmc1+jautMaydirsyZq5jQ7LY8UOy2JmP93NvoKysAkePHoVEYknpWn64Cq+auh8aywTXrl07aDQaSCQS1KxZE7GxsXjrrbdw/fp1psaNPnRKb1dXV1y+fBmNGjVCdnY2ioqKrJJ1Lj4+Hunp6QgPD9d5WHcEKSkpSE1NxbDeA7EhcSXvec6SUlps8dg9Jw+i29BwuLq64dNPlyCBJYTmzpmDj+M/BiRa9/f5CQt0xdOTVN/qYjXeGDUaPVp0BABR74O137fKmLmODUnzDSKQhHLtThYaD4rB8y8GY+mezXYblxYgXr5KeCoUOkIpuE0ILp46ywgmWkz5VPPDtb8vGQiOnzelMQVkuwzsw7i/tWz7EnYf2geFxoWpbQSA+dlD7sH0kV1cgEv5d1BcUcb0qT8Xen5CaxmxRduP1/lFiT14dO8+Itu/DMB4qm9nSPnKRXZ2NtauXYtffvmFsYK5u7ujT48XMTt2BNq0ep4RFQB4hYVY4WFK+NiqRpElYs0ZIAKJHyKQzKdj7xk4/sdlbN++HQ0aNLDJGOxiq3K5XEco0UVh2TXbVqxYgdLSUri5uekUkQW0Yuuzzz5DSUkJ3N3dUVxcjMDAQOzbtw+1a9eGq6srU9sIAPOzh8fTtenx48e4c+cOk4GUFnD0XPTnJARatEmlUvzxh/02RrkQKpAq64N58KD2WPhJEurXr48ePXowf0f9OkcPcx6iQqPBiuXLGRHl6uqK83+dQ8OaQSi5puv9YUr42EpQsvsFxIk1Z8Cmab63bt0KT09P3Lt3jzk2fvx4hISEID8/X/xsCQ5l+ba9AICug/tZ1I/YZAK06xgAxr2OdrU7uiedM1Pctb8vcSY+2L4iFSVFxaj+XCCmpiQyfXccHI4zOTcwavRofPfdd7hz+zaKC9XQaDQoLlSjtKIcWep8/Jl9HX/l3GDEEWAYa8Se38bk5YKutfOAcEhlUnQeEC7inbQN1WrVFHSePd0mTLmKFBQUYPny5RgwYAD69euHtLQ0PH78GN06NcO+72eh6MEW7Pw2Dm1aaXdhZ3wwFP5+XvD38+J1X2O7vwlxYzOWsEHI69ZAyBjEJY/wLDD+jV4AgG++EV6rT2wyAfoeCIBxr2Mni9HPFKdSqVBcXAy5XG4gUFJTU1FcXIyaNWvi/fffZ+6tZWVluHHjBkaNGoXvvvsOt2/fhlqtXZvUajXKy8uRl5eHa9eu4caNGzrlGfRjjdhzEnqt4eHhkEqlCA93/NokFHullLa2C9mH42KwbOnnqBdUD1+uWQNXV1cDcQQ8zVo3Y/oMzJk9B66urti4YSOeb9AQpf8ZJiYxlVBCTMIJcxEyRmV2yRNtQaIoCi1btkTXrl2xbNkyzJ49G1999RUyMjJQu3ZtW81TNPQuXVhIE7g8qWliLZrWfw6N6z1n1T7ZuLrI8Gr3tlAqbLe76OHmCk8Pdzw/KArX7zzAtgu/Qe6lMN2QB3Nd0rhc7bgsSBuTl6OspBSu7m5MDSR2u43JywEAY6dGG1h32GN4K7xw8Ntd6DliIDoP7cd7Ht0H1/yKCgtRkKdyWNFXc6GLxR4/fhyurq4Ong23taqkpARpaWn47rvvcOvWLQCAVCpFq5D6+HDyILw2rDNTOJEPoVYdU9akVev2IX7e1wBglsueJbDnRhepNTaGs7nkEQsSP8SCZD6PHxdBWXs0AgICBMcimWsV53K147Ig0RaiPn36oFWrVjouebSFCYCBdUl/DC8vL+zatQsDBw5Ev379eM/TL0LLnhMt5JzNA8AYQi1I9sJWliqp3BVFAVJcvnoFLZq30MlOp8/DnIf49+pV1KhRA3VKfaBR69YvXPvdJsxdqY1Rmv2OVmjpW3JsZUFivz90kVpjYzib5c/mLnZ0gN/HH3+MJUuW4MiRI2jevDlu376NMWPG4MGDB3BxccHHH3+M4cOHm30hlkAvQhLAqr7KmirkkajwVKCwqBBubi747l/LPrhc4sJS2H3S1hs6YcGqWUnQVGgYkcIWaMOjInVc7oTG/wgVeWKv1Zx4K1tAC6S+ffvaxe+cvYAfP34cgO5DAv36uHHjIJfLsWXLFly+fBn0LanJ8w3wzls9EDWxH1xdXQSPK1QsmBI3+v3YU4SIde2zlVAzFyKQ+CECyTJqNnoL2Y9ycfz4caagszGsHVep3x9bgKnVaqhUKiiVShw8eBCArkALDQ3F/v374e7ujvfff1/wfISKPLHXak68lbVxhECixUOHkLY4kHEYgFZo0PWNbOU21uudIZg85T307tULAf4BvOepi9XYn56OvMtZeK33qwav64sOe4oQsa59zhI7RmOXGKTWrVvj77//xv79+9GtWzcAwL1793D//n20bNkSWVlZaNOmDS5fvgyFwnzLhLnQi9Ddgxeh9PK2Wr8ajQYnz59BUXGR1frU5/rdm8jI5I8TsQYXrv6DHFUubt69DQD48cZJkzvz9kZf9OiLJTohA6BrQaJfB6AT/5McE4cju/bDzcMdE2ZOMWppAviFjFiBxL4OABYnfzCX0a16QfUoDx06dGDqatgSelFnw17gjxw5go0bN+Ls2bOoqKgAAATVroXxb3TB1PdexeZtv5n10G8t8WBtEWJNEeNsFiN9iEDihwgky3j19YXY+dNJrFy5Em3btrX7+PpihS0yVqxYoSOQ9C1IixcvhkajTfvMbm8sjgkQJmTMEYLsawHgEOuTIwRSUO8WyFXlQSKRMBtyQsWFJQ/8dNvkjxMxdNhQ5GnU0Eg0UMgVkHvIQZVroHlcgvJHRdAU8tcstLYIsaaIcTaLkT42F0h79+7F0KFDUVpaivPnz6Np06ac54WGhmL37t0ICgoSO4TF2EogVTXq9wlFdt4jhPXrgbg1nzh6OjrwCRH94/qWH/2kDbQFiU6aAABevkpsPXuId+yRIT1QkKfiPI9PuPGJJfZ8z5847bDMdm+07o387Fz4+Pjgl19+sfl4aWlpzAOBRCKBt7c3evfujfv37+PkyZNM0dqA6v54fVgHxH8UgZo1fRkh8bigCDm5BRaLAEvFhLWEjTVFjbNZjPQhAokfIpAsY/8vf6HvkHno3r07PvnE/muWMSFizLq0e/duxMfHG1iQ9DeS2NYnLnr27GlgpQKMCzc+wWTKym8PHCmQ5B6ecHdzB/DUgsQHLSIK1IXIVeVZRQAED2qPEk0ZXmjwPPauTDOomWQKawkba4oaZ7MY6WPTJA2nT5/GiBEjsG7dOvTq1Qsff/wx53mnTp1CRUWFQ8QRQTg/rdgGADix/1cHz8QQvlpC+seD24RAKpMiuE0I8/qEmVNQ/blAtGjfmmnHTpZQXFgkOrEEjakaTsau4+Kps5yJJsydixgmJcQCgN2SqURERGDatGnw9fVFrVq1UFBQgB07duD333+Hh4cbxrzeDf9mrsCDa2vxRfJE1KzpC+BpUgIAJusFCYGvLhGbVev2oVq9sahWb6zg4rC2mIdQJk3oixt/r3ZKcUQg2JIeXVtAIpHg1KlTDhnfWB0h/ddCQ0MhlUoRGhoKAEhISMD06dN1CoNGRkbqZK0rLS0VnViC7oedYEdIIVd2wgeVSsWZaMKcuTg7s9+ZjqDA2kh8bxZuHziP2wfOm3yYpxMSALBasogPx8XAXeqKiO4DecXR+Jkx8OlQD+NnGo5nrUQM1kyAIaSWVGVBlEC6ceMGBgwYgLi4OIwcORLz5s3Dd999h9OnT+ucl5OTg7Fjx2LNmjVWnSzB+jR7vilkMhk0Go1NRZIlAsBUWy7RwSVcpqYkMvFo5WVlWDUriVfcjJ0ajYDatZiEEOx5AE8L1Yot5Mp3vhChZSktO7WzWd9sKIrCyZMnERUVhSVLliAvLw93795FjYBq+HDyIJw+8gny/9uIjWveQ6MGgQbtaSGRMGs0k6DAkuxskyb0NdnPok93ICe3QHBxWDFZ4+hz6b4svR4C4VnG1dUFjRrWxOPHj1FUZLmruyUCwFTbzMxMaDQaZGZmMse4is+yBRMALF68mFfcREVFITAwEFFRUTpzAHSL1IrJSGrsXCFCq7JhzkM8LSJmvzOdsbJYmp1t4rAxTKIDvn52HNiFCk0FdhzYxTsnWtiIyRjHPlfIPJ5FBLvY5eTkoGPHjujevTtWrVrFHB8wYAAqKiqwd682XXRJSQnCw8Px1ltvYcwYxylI4mInnOgFH2HDzm/g7eeDLZn8pn1LsKTwqqm2prLPsS1QdPFWVzc3lBQVM3FMYmOJrB0/ZIskF/oUq4swvGlnAMZrIZnL5cuXsWbNGpw4cYJ5cPH388GwQW0xO/Y11H6umuC+7O1mp5+xzpRlRoy7HPtcABa72Tm7ex1AXOyMQVzsLOetySuwdsMBfPzxx3j1VcMgdjFYUvvNVFtj2ef0j9GxSoD2MyKVSjFt2jST7m62rl1n6+LhzpbFzhTWdrUz5d42fmYMdhzYhaG9B2L9AuOWIjGuctZO9ODsrnU0NnGx8/f3x6VLl3TEEQDs2bOHEUcURSEyMhI9e/Z0qDgiiOPzGYsAAI9z81FaXGKTMcRaWsS05XLFYx+jLT/JMXG4eOosJs2bjgkzpyCgdi3B4sjcaxBqOeNzJ7QmHnJPq/d59+5dzJkzBz169MCoUaNw+PBhSCQSRAwOw4U/Psejm+uxZlmUKHEECHOzE2PFMeXeNmlCXzy6uRGPbm4UJDrEuMuxz7WGNSrmoy9tXnuJQHBmPogeCADYuXOnxX1ZUvvNVFsudzz2Mdr6c+bMGcjlckRFRTEWIiHiyJL5C7WcGXMpfBYR4monxpJjyr1t/YIU5GfcNCmOhPRl7FyutmKuY+7KJNzOusOkH68KmJ3FjoujR4+ia9euCAkJYY5t2rQJL774orWGEAyxIImj2asdcOvef3gxrA0StzmXa6R+djn9mkemss/Rlh+pTKqTGtwe2MrqZK7FiU71feLECSZFrtgdwtzcXHz11VfYv38/Hj16BABwc3NDj67N8PG04ejUIdiMK9JFiJWkWr2xyMktgL+fFx7d3Ci6vbnjikFIf+ZYo2QyKVI+eYtYkCohxIJkHdyqvQapVIrff//dYXPQr0XEVSfJWPY52vojlUqh0WjsmkHOFpYnc6xNxixIzmiVEDInOgmEn9IXtw+cF9XWknGt3ZcYqxLfNTsbNk3SYIzOnTtDo9Hgr7/+Yv45Qhw5A5WtevCe5dpkDecyTps4UxjWTDrAjs/ZviIVBXkqFOSpmHgd/df1Y3loy0/nAeHw8lWiqLDQ4nkJvT5LLGfGsDRm6b333mN+FuJjXlRUhLVr12LQoEEIDw/H1q1bkZeXh04dmuLHrTNQkv0N9u6YhXN/3xJsDeHDGum0xVhZ2BYcayVkoBHSnznWKGcWRwTnRYy10tlp16YRSkpKcPnyZVHtrJl0gL53pqen6/xP30vZ91au+yxt/QkPD4dSqYRarbZ4XkKvzxLLGR/WjleyVhICwDrPZJaKFLFWFvacrfleCO1LjEWKTnxBF66tCjhX4ZsqhDU/zPagQZ16cHVxBSgKe7dY/nBo6gFejIBii4zhUZHw8lXCy1fJiA791+mf9ZMqTE1JhKdCoSOuxM6F7/r4+rCV65y5wqt2o3oAtDXLaPgWyvLycnz77bcYMWIEunbtilWrVuHevXsIbVEf61KiUfpoG47uT8SgAU+TP1giMOiHt/h5XwvqI2HWaNQLCkDfXq10HvoWfboDFRUayGRSQaKDPWdrZpoDhIkfMRnpSPY6giVYewPAkbw+TBtPaSwlNhemHuLFCCi2wGH/T99L2fdW+ufQ0FCmf9p9LSEhAXK5HCqVSmde5og5/evj68MWrnPWFl3WzK5myTMZLVRogWOqD1os9O7Q3SJRxp6zNd8LoX2JSWZRlbLX0VjVxc6ZcLSLnTOahk2xaO1nWLDmEyi8vfDN35ZltDPlAmZN1zO+sbjG4HLHKyosREGeymQSCJ9qfrj29yV0HhCOFu1bG63F5Ky802Mo/rt6EwqFAr/+avg3fvz4MX744Qekp6fj0qVLTFHD5xvWwv/Gh2Py2y/Dw8ONt39LrD+0+5i/nxe8vTwF96HvoiZ2Dnzni03cQHgKcbHjx5EudpUhwYdQ7j/IQ+Dzb6JBgwbYvn274Ham3MCs6XrGNRZf/1zueGq1GiqVinMu7PPPnDmD9PR0hIeHo1WrVkZrMTkb9krSYMkzGe1q5qf0hZdcIbgPfRc1sXPgO19M4gaCLg5zsSM8pTKq6WlvvgsAKHxcgJKiYov6MmU5EWMBMWXh4bNWcY3BnhfdDoCB1Yk9Fn3ev2cvQFOhwdE96QbXpz+WPeoamcOYqdrUsIWFhcyx0tJSbNy4EUOHDkWPHj3w+eef48KFCwisUR3TpwxB3u1NuPLXckx9b7BRcQToWjjEuvOw03uLsZLQ7Tq2b8qk0xbTns8qYyz1t7VclcT240wuUs40F4IwqpIFsmYNXygUCty8eVNUO1OWEzFWEFMWHmNudfr9s+dFtwPAnKs/Frvv9PR0aDQapKenG1yf/nhVsa6RENjPZGLd7fRTfAt9rqPbdQhpi+BB7QFAVHu+50hjqb+t5Uoopg9nCymx1nyIQLIBzvZhEYpUKkWdmrUBAAsmfmjVvi0RDLRA2Zi83KCPnzeloaiwUMfljkaoSGvdNcxgLK4YpudDmkEqk+oUnOUbyx51jfgw9l53fLk38/OuXbswcuRIdOrUCV988QVu376N4CZ18EXyBGRd+Qp3Lq/Corlj4OOjMGseptx59B+wxTy8sdvS7Y6duGRV96EZHwyFv58X/P28DFzkrOWqJLYfZ3KRcqa5EIRR1URt7+7NodFokJGRYXYfbMEgNskALVIWL15sIDjS0tKgVquhVCp1xJAQ1zZa1ISFPV2b9MUWW/iEh4dDKpUiPNxwbdIfz5F1jZxFnJlyt9N/hhOz4a1fX+jizhPIOHvSqiEXQ3sPhEwqw9DeAw1es0Z4h9g+nC2kxFrzIQLJBjjbh0UMP3yxGQCQecT4giNW8OgLBjECghYoAPDwzj2smpXEjEsnbfBUKETH+dCi5uKps8xcjMUwLd29CT9eP4mpKYlMH3zvg62SMwhB6Hs7d+5cXLlyBXVrB2JO7Gt4fPdrXDj5BSa/PQA1a/qaHMfUw5ap+BtzHrCNxSlZO37IWOpva40lth9rX6MlONNcCMKoaqJ24rheAIADBw4AsDxmR6x4iIyMZDLQrVixwsDCo1KpIJfLRcf50KImMzOTmY9+DBPwtDBsQkIC/vjjDyQkJDB98L0XtkjOIBR7iDMhG9SmYnDMeYYzFqdkzfghwHjqb2uMJbYPa1+fpVhrPnaJQVq4cCF27NiBS5cuwdPTEx07dkRSUhKaNGlitN327dvx8ccf48aNG2jcuDGSkpLw8ssvCxrTkTFI+n6j1ohHsmdMk3+nBigtK8NHn89HtyHc77fQmBs6fie4TQgunjrLxOwYi1Hie+3nTWlYNStJJ1W3NQqsiolh0m9jKn7JERh7/7avWI+Hd7SuG5Pffhmzpg9H9eo+Zo0jJj01F+bEQ5gbp+RI6Ovs2L4pjp24VCnmbCkkBokfZ4pBskZMkiPjmgoLi+FVaxRq1KiBn376SVS8jX6Kbr5U3FxtuAq/6scLWaPAqpgYJv3zaTHiTLFHXNdDxyDJPTyR+N4si59vLC14Cpj3vGVunJIjWfvdJiaj3ux3pjv9fK2BmBgkuwikfv364fXXX0fbtm1RXl6OuLg4nD9/HhcuXIBCwe2+c+zYMXTt2hULFy7EK6+8gi1btiApKQmnT59GixYtTI7pLEkaOoS0ZfxFLfnCWuNLL5SZXyTgs80r4amQ49uLRzjPESpMzEleIESYWCKIhGJsLHqOXr5KeCoUgoSfo6HnDAASiQSa/O8s6s8RD0ZWH1PiDsAFQDlA2aZIMrt2UUWFxkBQVqXAeRoikPhxdB0ktmD/9vvfOT+TYrB0o8RSajV+G1n3H+L333/Hrl27BIsSc5IXCBUntiyqamwc9vxokcRVk8mZir7SAgmAVZ5vHJUgqzIm5qKfKwHu974yXpMpnC5Jw969exEZGYnmzZsjNDQUqampuHXrFk6dOsXb5vPPP0e/fv0wdepUBAcHY/78+WjdujVSUpzXbY0rZz0tjmRSmV1NnpYwf3IcAKCoUI3CggLOc0zF99CuZ8FtQkS7mhlzT+s/JgLDoyKxfUWqqHgmc2KgjF0jnW6c/tkZYo9MMTwqEp5e2g0JmUxicX+OCPgWOqYx97/vf7qCTd/n4VFxW0DeA5B3efJ/T8A9FJD6C+pHKLQr2oghnThd0qqa2xPB+eCq9UWLI6Hp8PlwtKvlqwNaAQB++uknk/E9bLczc1zNjLWJiIhgRIlQFz9zXAKNXSPbDU9fDDky9kgIcg9PqzzfOCpBltBxjbkAiolft0as+4fjYuCn9IWf0pfzva/M4SLWwCFpvv/99180btwY586d47UG1a1bFx988AHef/995tjs2bPxww8/IDMz0+D8kpISlJQ83QFWqVQICgqyqwWJbeX5cFwMY0HKOHuy0inwVsO74srNa2j0YjA+27NZdHtTliNLLC3WtkqJxZh7nTNbkABgRsRE/P3HGXTq0ARH9y909HRsBueutsQTcG+O+zmuzINhzQAfFKpL8PhxEQDA29sTCrk7UJENlPyN+s3Gcrr0WdNtTqgFqTJZmogF6Sl8a5M9LUjs78OMD4ZWKZfPs+dvILTjB+jSpQuWLl1q9FxTViNLrSxirVLWTsHN5+7Hfs1ZLUi2TvPtLBjzBuJKC87nAsfl0geAsfiwf7Z1aEdlsjQ5nQWJjUajwfvvv49OnToZdZXLyspCzZo1dY7VrFmTSX2pz8KFC+Hj48P8CwoKsuq8hcC28tC7CesXpDBfAlrtV4Ysd+lrvgcAXD130az2ppIUWGJpMScBgpA2Qq1MXOnBaWirEwCnTPN9+98bAACF3MOxE+HAmhm2DHa1pT6AZyf8ez0fXgoPyGRSeCm070FBYTE0FAUNRaGgUJve/t/r+YBnJyQvfA/1ggIAQMfKw96Ft9T6I9QqRixNlRNnWJvY3wf687blqynM5gH9vauMWe6aBwdBKpXizJkzJs81ZTWy1Moi1iol9Hyhliau9OA0tOUJgFNkkqPhe6ZzFqz9vGbMG0j/tSUbUpCrykOuKs/AikOfC4Cx8rAtPtaw/gi1ilVVS5PdBVJ0dDTOnz+Pb775xqr9xsbGIj8/n/l3+/Ztq/bPhbFUkPqv0ZlN5q5MqhQfpup+1eDh5g4A2PGl+BuDKVc4S7K8mXLvM7eNUNFGz33s1GjePp3V1U6VmwcAWJY8wbET4YAWAPHzvjbrIY0r9fekCX21liOPtvhx589o1qI1li1bhpoBPlpLEQAvhQekEgmkEgm8FB5YlPQJmrVojR93/oze/d/Ec8/VRt9erXQElym3OWNzMxdHuzIRzMMRaxNfCn0ABp9DOiNk/LyvK6UIl8lkeL5hXRQUFCA3N9fouaZEgqUZ3oSk8DbnfKHCjZ5/VFQUb7/O5mp39OhRAMAQjpTVzgD7ec1cscSV+ptLdOi/xucCx7bYzH5nOiOq2AJLSFiGtcSfs2WxsxZ2dbGLiYnBjz/+iN9++w0NGjQweq5YFzt97JGkwZipNKh3C+Sq8uCn9MXsd6ZjyuI4UBTF/K5vNnXGysgpW7/EjKVz4eruhh1Xjotub023NmthzAUuOSYOR/eko/OAcJ1U3qb625i8HAAwdmo006ezutoNrNsGAECp7PcAJNaF7HFBEXJyCwQHfZts5/ES/r2ej2YtWqOsrAwAsDBxHmZM/8igr0VJnyA2bhYAwNXVFb/99iuuXr2G+NgpFgWgOzqQHbCvix5xsePHHkka+D5v7IQhKZ+8BQCI/mANNBQFfz8vJMwajfh5XwMAEmaNBgCd353VFW/uom2Yk7gNEydOxKRJk0yeb23XNmtgzAUuPj4e6enpCA8P10nlbQy+Ns7mate1a1etS2DGLUil9t2zF+Iaxj6HFktCk0nQbQvUhchV5fG2E+uiZq2kXfZM/sWHvd3znM7FjqIoxMTE4Pvvv8fBgwdNiiMACAsLwy+//KJzLD09Xadwmq0QqqqFquYlG1JA69DeHbozH4JcVR4jlOhkDmnpPyJ4UHuMnxnjcDe8mJFvQQIJykpKkf8oR3R7e9UCEpOAwZhl5+Kps9BUaHDx1FnB/dN1mAryVDp9mmPlsjVlpWUOGVforjS9y50wa7RRS4n+7jjdPwDDdlJ/QFYdzz/fCFM/eiqIYuNmYVHSJ4DEBZC4AhIXHXEEAPPmfowXWwSjd+9eWJpsWeFkZ7D+VEbrAEEXoZZIvs/bjA+GMtkUF326A4s+3QHNk7Wpb69WjADKyS1gLEo5uQXM7/Wbv41Rby51Oje8t8ZpC6SeOCHsIc8etYDEJmAwZtnJzMyERqMx2Bw2NkZ6ejo0Gg3S09N1jou1clVlhHjzsK06pp759J8d6f4B8LZb+90mfJg8E7ez7uDD5JmCnvmsZbFxBsuPM3tU2UUgRUdHY/PmzdiyZQu8vb2RlZWFrKwsFBUVMeeMHTsWsbGxzO/vvfce9u7diyVLluDSpUuYM2cO/vzzT8TE2P4PyfUH4xJN+i51Qb1bIKh3C6z9bhN6d+gOmVSG3h26I8CvOtMm4+xJAEBJaYnO/3RlZE93Dyb7nTN8aFo2fREAMG3YRNFtzYnH4RMjpkQKW/QYO5dPtP28KQ1FhYXw8lUavGZMVNHZ7LjaORtlpaUAAJnMvrt0Mz4YCn8/LzwuKBL0UGXMHQgwfNCnHwYTZo02jOVxfRrvMXnyZJ17TGzcLCxa9AkAGRYt0hVHtIVJIXdHzQAfDBkyXNC18j3AOiLjnz7OINIIlsElcrk+c+zP26g3l8LFLwKj3lyKSRP6YsSQTpDJpOjYvikCWDXQjp24hFXr9iEvr5A5Rn93/f28AMBqcXfWplagHzw83HHp0iVB55sTj8MnRviOcwkeY4KGS7TR54eGhnIKOmOiKjw8HFKpFOHh4Sav7VmFdmErUBcKEib0Mx8Azg1s/WdHWoDMfmc6r1vdkg0pqNBUAAAqNBWCnvnMydRn6hnWUTiDSOPDLi52Egl3SuH169czX/ju3bujfv36Ol/07du3Y+bMmUyh2MWLF9ulUCyXyc+YKZLeAaA/5H5KX6gKHjPpvTWUhrEgfTZdmzmMdrmTe3iimq+/QVFZZ8l+97iwALV6NAUA7Lz5J+/fUh+26xkAwcVU+dzy+OoO6Y81dmo0I2hoIWRpvSauYrcAnNKFzhirP16E3Ru2w83NBSXZ39p1bHNczPjarFq3T7jbj7wnIHEDACZbXcry5TouJ76+vsjLy2N+53S/o0oB9UHOIdiua/QDrCNd6ZwB4mLHjyUudlxuksa+J4s+3YHb/2VDQ1GMWx3bpS5fpUZFhQYAMDKiC5P6WyKRwM9XofP9cvaCx+17zMEfp87i22+/RcOGDTnPSUtLw4oVKwAAUVFRooqp8rnl0ceVSiXkcrlB3SF2IVr2ePp1isSMyXc9zlzviA9HutgB5rmZ8bUxJ1TCls98lrgHVlWc0sWO6x97N+Tw4cMGuyDDhw/HP//8g5KSEpw/f16wOLIULlXNVrlcZtQKTYV2UVH6AoDOjoCnuwckEgnkHp7M+RRFQSaVwd3NXWfHQT/7naNTJnorvOAl1+4erk/4XHA7tusZYJjtjQ8+Cw99HICBNaf/mAh4KhSMmxu7j43Jy/Hwzj0dscZlYTJVe+mr47tx8dRZZmxnTcJgjNNH/gAA9OkZavexzbFe8LWZNKEvvL08kZNbwLuLvWrdPrTt/jEKi57u/yjk7gis6YsF82djYeLTGDNdcZSIGTNmoFBdgvsP81GofpKeWeL2pKisIexdfWKlIdgSLksk+zPHVe/Iw9MNMpkUI4Z00nGpA4ARQzpp1ya5O/b9coZJf+/nqzD4fulnv3MmcQQAk97sAgDYsmUL7zmpqalQqVRQqVSMiBDqasd3Ln0cgI41h7ZSZWZmMsfZfaxYsQJZWVmMwAEMLUym5hcREQG5XM5cD32NzpSEwdkxx4LB1ybj7ElUaCoYTyF9jFlxhDzziU2qwLZoObOlxllxSB0ke2DLJA1cuerZFic6dz3tPufu5o4CdSHKyssg9/BE4nuzmPN/P3NCZ8fBGfPJb9/3I8Z/HA2Ziwt+uCZs54EveYGl8CU/4Dse0aQTSoqK4e7pgbR/fgdgfvII9hgADKxK/cdEOG1yBgB4vUV3FKoe43/j+2D156YDmYXiiPo8pnaz6zd/GzJXbxw79jtqBvjoNpa4ApDBz99fRxz5+voiNycHQAXuP8jWqZUEAFAfAahC6GPJ9Vem2kZiIBYkfmyZpIGr3hH7s7Vq3T58GJ+KoqISeHq649WX22Hbd0ehoSjI5e4IqKZkxL1+sgZn/5wWF5fCs8brqFatGvbt43bl5bK4WAs+yw3f8c6dO6O4uBgeHh5MJjdzkkfo989luXJmy5KtLEiOeJZijwkY1iGyNCmC2PbmvgfO+BxqLcRYkIhAMgO+Dw/bVEonXZBJZYw1ieaz6Qt5vzBCvwD2/gB7tw8CRVFY/st21G3M7b5gKywRHSNDeqAgTwUvXyW2nj1kcX80dMY7Vzc3lBQVM2LLGTP30dAZ7P76/ROEvmi9v6E1M7SJFQzG3IvWbTqKw78eZdJ5M0hcnsQcxRn0p7UgfYTCwkIUFBbDS+HxtL36EECVGLSxBGfIbmcLiEDix5YCie/7w95QoN3oADAJGwCtK/yKT//H6boHQPDn1JGiv3aTibiXlYsTJ07YxV3LEtHRs2dPqFQqKJVKHDx40OL+6PZsixS7WKwzZu4DbCeQrJ2hzRqZ5ix9brPXc58zZLezFU7nYlcV4Mtjz07OEPf5PNzOuoO09B91XOxcXVzh6uLK9DUlKRZdxw2AT4d6CPCrjqDA2ugQ0hZBvVvgUV4O5B6enEGD7DnYO/NHr/ZdAQCz3rC/eZbPnY3tKseXmGHs1GimZhGNNTLMHd2TDk2FBqXFJTquefbK3GcJ1hRHgHWD/9nuavrB51zB6Mbc8E4eng+Fp2HM3KJFi3TEka+vL/NzbFwcFi1aZDgxqtTq4gggiRMIlsNX/2vVun2oVm8sFIEjEf3BGibBAi2IAECplIMOK6UoCtEfrEHbbtPg4heBgOo+qBcUgI7tm+LhIxUkEgkCqvsYfAf5sko6IolDuzaNQVEUjh8XX5bCHPjc2diucnyJGaKiopiaRTSWZphjuxACusVi7ZG5z5mwtkuZsXpIXK5vXOM7Q1IEIRB3PC3EgiQQPkVN1zsCAAkAc97Mgj/+Y/pnoz8Wew500J29LEhFxUUI6NoYAPDjjZOcOz22ci/j65dtrQG0sUlSmRST5k23uXubOTWTHEmh6jFeb9EdgH1rIImFnYABgE5dI7OsLe6hgIv281GoLsHCRclISHj696JjjvRFU3x8HKKiop+62JXfA0pM118jaCEWJH6sbUHi+15UqzcWObkFzO8SCeDq4oLSsnIAQM2aNaFQKFBYWIj79+9z9k2pdjD9s2GPpT++Iy1IB389h14DZ6NLly5YunQpANvW/eHrm22tUavVBpYiW2FLF0Jb4egkDUKhQydo2HWNLLG4iLEKVWXLjr0gFiQbwKWo1363CXmP85nf+cSRq4srk6BBH8mTfgrUhZB7eDJZ4mRSGTqEtNXZlWDPwd47EZ4enkwCiiXvf8x5jq0SF/BZfNjWmuFRkZDKpNBUaOySOGFqSiJ+vH6yUogjAMh5kA0AcHGR2XwsekfZnHop7AQMgG5dI7OsLWW3mYQLiYmL9cTRPMyY8RGACsyY8REWJs5jXktISMSKFcvhpfBg+hFag4ZAsCdc34tV6/YhN083Xo6igDYvtcXy5cuRmZmJ06dP49ix33H69GlkZmZi+fLl6Ny5k06b+s3fRsf2TeHv5wUpvTY9SRFOfxf0x3dkSvue3V6EVCrFqVOnmGO2TFrAZ/FxlLUmIiICBw8exMGDByuFOLI3tKXHnDqTE4eNgZdcwWyIs58HzbW4sGsgCfEG4htHbPIGgjCIBUkAfIF3tMlVIpHA2Ns4vM9gbN//A+9rGWdPMrsCAX7VcfpiJloHh+JhbrZT7RacOHcKvSa8CheZDN9f/8PgdWtYkCzpw5kTJDiaFXGJ+Hnzd/D0dIP6/jc2HYveUabjG8TG14jdgTZ1/g8HNAioEYgePXqgrExbLJczlTegUyzW1dUVF86fxvMNlEDxKaeLF3LmBA/EgsSPNS1I7M8AAIN081KJBBqKQlBQEBYuXIgePXqY7PPQoUOIjY3Fo0cPoFaXMOLnw/hUFBeV4rVhnXHsxCWn+i6wCX5pMi5dvoPff/8d7u7uVrMgmduPsyZHcBbsaUGiLTB0bLjYZyuxMUCmzmfPZ8nUBWZveDuTZcnZEzwQC5KVmbsyCbez7mDuyiSDtIm0VcUYXOJIIpFgeJ/BOJBxWCfu6MylswCAzH/OO50faPsX20AqlaK8ogJnj/9p8Lq5sT3s+CFLrFDWiC0yNrfKzPG92gQVEYM62Hwsekd5xJBOZsXXiN2BNhXzUJDzJ2rWCMCmjalwdXXlFUcAMGO61pLk6uqKTRtTAYkbNm9cqXNdzhIv5MhYD4JzED/va9y8/RDx8742SDfv7+cFChRatmyJffv2oX79+oL6bNSoIX799RCaNmkGV1cXPC4oQvy8r6FWl0BDUUzWSGf6LrDp0bUFAGDnzp0ALIvrYccPmWuJsjSuSMjcCMKgn6mG9h5o1rOVWM8dU7Hi9HzEiiN9i5EzPSvaOz7elhCBJAA6XXdJaYmBmxsAo9YjLmiL0/b9PyBXlQd1cRGKSoqRq8qDi8wFMqkMQ3sPNFm12REM6z0QAJAUNcNqfbJFkdAkB/rCRYiQMUfssOf286Y0jAzpgZEhPSqdYCpWFwMAWrVsZPOxrF0vxZRrm6mHtTdGtMPzz/2H14YPxIXzp3nFEdPf9I9w4fxptGnzEoaPeA0z567TuS5nsdY480MqwT4Ul5Qx/7M/D/RntE6dIGzZsgUZGRno0aMHUlKMP7SkpKSga9duOHz4N2z++msEBtZCTm4B8vIKIZe7w9/Pi+mftlQ5m8tp9MT+AICff/7Z4r7Yokio25y+cBEiZMwRO+y5paWloWfPnujZsycRTEawdp1JU65tpoSLuaES+iLEmZI/OJNYsxQikATg7uau878pTFmV9AWVn9IXnu7aWAcvuQL5GTd1qjBbW5Fb4q+6ZvZnAADVo1yUl5dbZT5sUSTUCqRvaRJieTLHOsWeG7v4bWUqEAsAxWo1AKBXtxYOnol4TFlKhAiXVV9+i/+3d+fxTdTpH8A/k7RNk6bpQQvlKFhgVZQtl9iCgLAClUUOOVRcuVWu6ipQCoUFD1rAUnGXtoCiFEFBLafyYxUU5LBFBLGCoItctVxFaNMkPdJkfn+kM+RskzbJ5Hjerxcv2mQyeQjTzjzzfL/Pt/cj/cDqNXa9Z8c4BQoPbcCdP0s8NgHxtISNuF+w5G53VGvDLZctW4bbt29j2rRp0Gq1WLZsmc0kKTs7G8uWLYNWq8W0adNw+/ZtvLs2G2KxCHqWRXQzBf68/CG/f1dUMJ0xz+/BB9pCIpHgl19+aXI8xkmRvZUg80qTPZWnxlSnjGMzXwCXuEdD12b2JC6NuR7z5CTEk5K1pqIEyQ5LZqQiNqY1lsxI5X8g0v79BkITYqHSWC4cyU3is8fYwSNRvP80hvZLglgkRlzrdvwkQq59eGJ8T5e1q3RUYGAgFCGGOV0vJ41z6LW2KjiNGRpnXmmyp/LUmBbcxrGNnTkJ8nAF5OEKl7TxdsdwvvjOcS7btyMcuRCqr1Ji736Wv70dBcdOYdDgJ4DK7w1d6dga043YGsPjld8DVSegqrhj97/BkX8PNXsgzpK++B9oFxuNYEkgn6w8O2UVxGGj8WDnbhgwYADi4uIwd+7dqumyZcuQk5MDmUyG0NBQyGQy5OTkYNmyZfw2c+fOxQOd7sPjjw/CwtQXwTAMSv9U8sd6s3YTUPqnkq8oOUtTki7jn6tu8e1QW1uL8vLyhl8I2xWcxgyPM6802VN5akxTB+PYJk2aBIVCAYVC4fTGEP42lM+RhKW+RMXe/bhiSJrxe9sbBzV6sERNGhy0ftsmpP37DWiqKvnHggICUVOrdXhfDMNg1bwMZG3Mhkqjxh1lGT/8zrjxg7Pbejd1Et1fhvbAtVJDW9jPr5xoYOu7PHkRVU/gqs+n/M87eK7bQACe0+K7oYYH9jYgsKdxgnHr8PTF/+DXiFn+9na8vmgiJj47CECtxTpHDe27sQtpelqzB1egJg22uWKhWO54jo4Kww8/ngcA5OTkYOTIkfw2XIWIk56ejtTUVKxYsQILFy7kH1+wYAGSk5MRppBBpa7CF5/vxvMvTANg6GAXppDxXSYjI+QIlUud1iikKY1HjH+upk0ejLQ3PsLEiRPx0ksvNfhaT11E1RO4+rPxtDbf9TU8cGZLbm5fifE9UVh0nN+nPe/R0L6NnwdgVwMHT2r04ErUpMEFuOz6w91bTZIjANDqahv1g82yLF5ZsYBf/yg2pjU/1E4qCebbfifG9+QbRbz6VlqTM/ymlkBTp7zCf31wh/3jvIVeRLUx85asvbaxr2uIqz6fcyd/BgAEBQY4db9N0dD8GXvvJNszD2f529tx+44KoXKpxfCgJUs3Aqza6iKwDe3b+HlH5gPR3CHiTNwNgNI/lXxyBAB9+vQx2S45ORlpJmt9LURUVJRJcpSWlobkZMPd8HKlBjqdHgmJvfg239wiszKZBAzDoKpai8vFpZg5+100azehyVXRpgwbNf65mjz+bwCAb7/91q7XCrmIqrUKjSNVG3sWpbX3fa2hBWbvcqTa09AwOG5fhUXHTa7H7HmPhvZt/Ly9w/E8edieUKiCZMZW9m5tIVdn6t6pCw5t3GNzMTKuwgRYLiArhAWrXsfqLe9BHqbAlp8PCBqLvcwrNI5UbKwtSuvo64Sqmv0n5XXs+2Q3FKFSlJd81PALPEBTW1jban/M7csVLbI9ue22u1EFybbGVJDqO7asLeTaokULnDx50mI/MpkMubm5JkkRJz09HTNnzoRGYzpPLzBQjGjpCTw7eTk+3XEUTz35CN/mOzJCzidSADyqKhoROxHlShUKCgoQEOA5N4fMWavQOFK1Md4WQKNeJ2TVzNMqSPVxRgtrW5UjZ76HK+L2FVRBagJb2fucickQi6wvstlQUwZbi8Qa+/FcEWIHdkbav99AWUW5STKUGN+T30+EItwjMvz0fxoWi1WVK1Gptm/iu9AcnbdkXP0xX5TW3kqP0FUzADjyxX4AwHNP9xMsBmP2zMFpagMC4wqUtX25osEBtd0mrlLfsTV/9ih+gXFOSEiI1f2IxWKkpqYiPDzc5PHw8HCkpqZCLLY8x2m1Oox8Ngtb8g9Dp9Pzbb4jI+QAgKeefASREXKnz0dqqkcS7wXLsrhy5YrQodTLWoWmoaqNcfXHeFtHqj3+VhmyR0PzcJzRgMBW5ciZ72HrPX2h9bY7UYJkxlaZ8fnR45GVspQf9saN7QRgtVEDh2EYDO2XhMAAQ7ch7m/AMHepe6cuEIvEkEqC+ZbfLMtCLBJjyYxUnN19DIVFx3FHWYZm4ZEo3n/aI+4AiEQidIg1TPhf/Nwsl7+fMxoYmDeDaKg5hHHXO+NtHWkq4WgDClc0aqjV6QAAQ5N6OG2fjjJOiriLveS57zmlUYG1hEuIYWw0dI64Sn3H1vSpSch9+8W6YW9AYGAANDbOSTqdDitWrEBZWZnJ42VlZVixYgV0db8rDPu5mywVHDttEsv0qUkIlUtx+44K3x07hz8vf2jS4c4TjH/6UQDAxo0bXfo+TW1iYK0RREPNIYy73hlv60hTCUcbUPhqswbjpMh4zUtn75sjxFA2Gj7XOJQg1eEOZAAW2bvxc5XVVWBZFn/cuMpXjrRGDRoCAwJNKkaB4gBs37+b36ZWd7c1tlZXiwnDn0FWylKLeLh1kADPPbj35GwFAJw7UeTy93KkRbezkgwhqj9NWSjXFm2VYX7NXzq0cto+HWW+iKVYLIJOp3eo2mKra5y1u+tCtMCmttvE2bjjHIDVY4t7/tDRX6DRVINlAb1ej5pqNW7dumWxv5UrM02G1xlXkhYuXIjMzEwAAMsCMqkE0uAglJaW4ubNmxb78vQbAkMfN9wQ+v777136Po606HZWkiFE9aexC+V6OmdUV2x1jbO2byHaYPtS6213ogSpjvmBzB3kkxclY07mIv6uAjdlK0AcgOqaajAAxEbjZrW1WpMmDjW1Wuj0ev57rgkDYGjS8PqaFZiTucii8cP+woP81556cLeJaQ1JYBAAYOd7m136Xo4kK1ySsXbxCpe2zHZFtceVSdlfOjovQXK0VbX5IpbZK19wuHW3cSJknnDZe6FGLbaJN7GW/HPH8LNTViF57nu4XFyKrduO8M9LJIFof08Mjh49arKv7OxspKdn8N+np6fj1q1bSE9P5x/LyMjg10kqV2pQXa3FkSNHTPbDdYT09BsCcrkUrVo2R2lpKVQqlcvex5FkhUsy3nrrLZdVYlxV6fGWIXmOtqs2vgFtvKSLI/s1vn40/tqRm9vUZtvzUJOGOuaT2LimDGKRGDq9DmKRGAp5KO4oy0y+5jAAuA/SuEW3uXdSDW1WuRJudU01nxwZ7yNCEY7i/aet7MGzrP3kA8zNWozgECk+O3uk4ReY2bspH5/l5vGLxDpj272b8rF28QrodfomNUdoqMGCJzRgaMhvRWcw54kJAJzb4tuVrapt7buhxgtCx03uoiYNtjnSpMFacwbuGOaqsGKxCBJJIDSaaogYBnqWhYhhkJCYyF8km7f4TktLQ0pKCsRiMXQ6HTIzM5GRcTd54lp9A4ahWCd+OA5tbS1Y1tDa+8/LHzr7Y3GJyTNWI++jA/jPf/6D3r172/26/Px85OXl8QvEOmv7/Px8vPXWW9Dr9U1qjlBfgwVPab5gL2c3aXBVu2p7238DaFRDBH9psy00atLQCOZVGi7zHzVwGGJjWiMrZSl/d4H72phxOmSeHIlEIn7e0pzMRfhw91bIZSFYMiMV2tpai30wDIOBif1d8K90vmlPTQYAVKkrG9WswZEhZfZuO2T8GEx/I7XJlZiGqjme0IChIUVHfwAAKBQNNwpxhCuH1/ROuB9isQi9E+43qfgY37Fu6O61rUqRK+KmqhRxFWvHOXcMP/XkI2gXG43slS8gK30S2sVG4+nRfQzrcjEMCgoKcODAAVy8eBErV67kX79gwQLMmjULGo0GKpUKGo0Gs2bNQtqCBfw2K1euxMWLF/HNN98YusAFiiGVSiBiGCQ91s2tn0FTTBn/GABgy5YtDr3O0eFk9m4/ZswYzJs3r8mVmPqqOd5S6XEVV01JmDMxGRGKcKg0aouhdMbXjw2N+LFVKXJF3FSVahqqIDVBaEKsYVFXmCZI5mxVlOqrNHnTXYTOT/bGpZIreKBnV6zY9r5Dr3VFBYnctXxmKo5+sR8xLcJx7X8fCB2OXRq7ACtw9457haoSt++o3FIpoqqUJaog2eaKhWLNicNGQ8+yiI2NxZdffonCwkJMmzYNc+fO5StD1mRnZ2PlypVYt24dEhMTkZSUhOLiYr4yBXhWK++GaLW1kDYfB6lUioMHD9r9OldVkIil3r17o6amxivafDdmAVbAtMLEDcFzxzUeVaUsUQXJhdZv24TYgZ3RvN9fECAOAMMwGDN4JMYOHmnRapXDsixkwVK+TTj3S8A8OereqQsYhoEsWGr1LkJ9dwOEvFOwd81nAIBfjp9y+LWu7AhHgO/3HQIAPD36EYEjsV9jFmDlqjgL3/iIXxOmXWw0eifcb3d1h9tHz0fnISBiDJ6dssrheM33RVUl4i5r3/8SzdpNQEjMOIgDxBAxDFpESTB16iQkJibiwIEDFsmRcac6wLCY7IEDB5CYmIhnn30WxcXFEItF6N61g+HcJJNY/Cw2dKwL+bMQGBiAjnFtoVKprDaasMXRDm+Obk/uqqmpAQCb10+epDELsK7ftomfx84lScaVKHtw13f9Jg5FWGI7TF5kX5XJPEaqKDmGKkgOMl8wVhYsRbPwSCTG98T+woOorqlGbW0tamq1CAoIRE1d9zrjapEsWIrK6ioEiANMOuDJgqXQVFXazPbruxsg9J2CZo+0R7W2BjMz0jDkudFuf39PJXTV68kOCajV1uLXE6tx719aN/wCL8VVcSIj5AiVS/k5G45Ud8wX3BSLRai907iJzv5eVaIKkm2uqiCZH7/cz0LvhPtxougalix+DQP+9jeTG3PGlSHu+4PfHkTqvFRcKS4GYDh3SaVB0GiqrR7PDR3rQv8sLMvahrTXP8KkSZPqrZ75G0+pej300EOQSWW4+e1vgsXgSsbz2bNSlprMcbf3es38ulMsEqO88HKjY/HnihJVkFxk/bZNUGnUhrWQ6h7TVFWi+HoJ8vft4tcx4pIinV7Pt/zmqk2yYCkkQRKwLAu9UXc7wNBC3PyOhHHGX98dC6FbgadMfhkA8P6bbwvy/p7KFW27HVGrNcxxCwuzvnCkszX1bnFjX89VcdIX/8NkzoYjc464bR/q1hFisQhPPdn4qps7WyBTtcq/cf//vRPuh8joLvztOypcLi7FJ9uO4LffzuMfzz2HMaNHY8eOHSgtvZtIBQaKUVpaiqNHvsHMGVMxbtyz+OOPP/jnWZZFVWWNzSpp74T76z3WhW4HPm3yYADA8ePHBXl/T+WrbbutcUblpLH74K7NuOTI+DF7r9e47bl1M0cNHOZw/I1536by9ooVVZAcYJx9z5mYjFdW3J3UyiU+ZRXlFkPnAgMCUVurBQvD3bgxg0agsOg4EuN7orDoOKIjovDTr6cxauAwbFiabfM9PTnjZ1kWoQmxAICPf/4GoWFhAkfkGfZuyseHmTkAgAkpszBk/Bi3VpWGtTWsBeLMDnb1aerdYiHuNlvrFOZNhL5Dbw1VkGxzdgXJ+P9//uxRWP72dlz549bdEQsyCSora8CyLAIDA6Ctu2nSvHlzREc3g1qtwqVLhnlGT4/ug++OnUPvhPvx3bFziI4Kw49FF/DUk4/g4w9etfm+nnLcWcOyLGQt/gGdToeCggKhw/EY+fn5yM3NBQDMnDkTAASpKLmjguSM6yghrsXMuyt7G0+8fqUKkosYZ9/Pjx7PzzvikqM7yjK+aYMxbV1yBBh+WRcWHcecicn834c27kF54WWL5Mj8PT0ZwzB4oP19AIDU0c+77H1csfaQKw0ZPwbSkBCoypR8FcldVaXfis64dP/WOHq32Lz60Zi7zU2toFhba8abCH2HngjLfI2xS2fW4ZnRffhqkmEBWUPrb+M5Rzdv3sSZM2dx+bKhWqRnWXx37Bzmzx7F/33827dQeyffIjkyf19PxjAMHup2D7RaLX77zXUX4a5af8hVxowZA5lMBqVSiby8PJ+uKDXmOsq8+uHoPpxRPXHGIrZC8pbrV1soQWqAeStHrgvJ+m2b8Ei3BLRp0QoZ/1xssiYSYBgjGhvTGmKRGN07deGH2nENGOw98D11kVhrvn5/FwCg+LcLNrvzNZW7kgtnJmLm7cDd1R587ybDBX9khNyl72PM0cUjjZOTxlZymprgGLcV90aevmAncQ3uxgAAvnLE3STo98gDiG0TZbK9vm6onEwm4f9ERsjRw6wBg70/T9503M2Y+jgAYNMm1w31cUeC4ewkzLgluC+3B2/MdZTxNVpjKjnOSG4S43tCLBIjMb5no/chJG+6frWGEqQGmB/ktlZM5hIgAJAGS6HT61B8vQR6vQ7nLv4GSZAEAFBd17GFy6wT43vyCZi3j9cMDZHzn8PWf7/nkvdwV3JhLRFrbNJk3n3PXd34bl29DgBo0dxzhzsa34VubKLT1DvZ3x07B51Oj++Onat3O5rrQzyJ8c+L+c8O971522Q9y6KysgZarQ5VlTVIeqwbSm8ZhoVXVxvmznI/T8YdIL392B83ti8A4MwZ11XV3ZFgWEvCmpI0GXffo058poyrH41JdpxRPSksOg6dXofCItvz57z9utGTUYLUAOODnGvSEKEIt2jzyCU+YpEYGf9czLf0ZmFo5HBHWQYGgE6vQ9q/30DWxmwkxvfE9v2fo/h6CeZkLsLra1Z4dTkVAN6a/QYA4NPVrllzx13JhbVETOiGC476ucCwSOyQwd0FjsQ247vQjU10HL2T3dhhfd4+FI/4FuPj1rwKyj2Xk/UCxGLDaV7EMBCLRWBZFlptLfQsi635h1GhqgTDADqdHnMW5mH529vRO+F+fLrjKC4XlyJ57nt8+3xvPfYZhkFkRDiuXLnistEN7kgwrCVhvjw0TkjG1Y/GJDuNqZ40Zliftw/D82SUIDXA+CDP2piNO8oyyGUhFismjxo4jO8u8vzo8chKWYrAgEC0aNEC7du3R4sWLfh5SFznu+37P4dOrwMA/m9vHq8JAJNGjgPDMKjVanGz5LrQ4TSatUTMXdUrZ+G6JL6+4BmBI7GPu4bsCFWpIsSZjH9ezKugxs899eQjEItFeHp0H2SvfMFkyC0LQ7c7LmfQaKr5znc6neH3B/e3tx/7/fsaksfDhw8LHEnjWUvCfHlonKdw11AxoSpVxDpKkBpgrc228bA4bpv9hQehkIfikW4JEMmDMGDEYPxw4gecPHkShw8fxsmTJ/HTTz8hJycHvXr1gixYyidVgKHytGRGqleP1+Qkxj8EAEh7+kWBI3Eub1uolq1LkLg7yMTAPNHxxTkXxPcZV0KtDYsDgGenrMKnO46adKELld9dpoKB5e8HmUyCYGkQ/7W19vne6OVpfwcAfPrppwJH4lw0NM53mCc79iRM3j7Px5PRlVMDjA9Q7kAsLDpuMS/pjrIM8rBQtH34Pkg6RCL6npaIijJMkmUYBgp5KNq0boORI0ciPz8f765/D3lvrUFWylLExrTGqIHD+MmA3m736o8BADeulFis9UTcTyqVCB2CRzFPdNxVGfL2eRzEsxgn9twx/d2xcybJ/qc7jkKn0+PTHUcBgB8qFxAYALFYhGfG9EX2yhcgk939HVFdrUVW+iS0i41GVvokiwYQ3urRvp3BMAzOnz8vdCiEWGWe7LirOkTzmKyjBKkB1g7QOROTEaEIh0qj5itL/fr0xf59+9A+Ls7k9QzDoEWz5pAFyxAeGgamrvVqXFwcgu9thhfHT7GadHkzabAUYXJDf/nctAyBo/FPl341XAQwjHnTeWLO04f2EWKNtcTefC4SN7zOfNHjUHkw3757+tQkRDe7ux7IU08+YvIz4UvHbbvYKNy6dQtarVboUAhpkCcP7fMHlCA1wNoB+vzo8ZDLQnBHWYasjdl4Ydwk7Ni2HQUFBeiZ8DBWZK5AaIgcYpEIoSGmLZZDQ+TIzclB//79sWvPF5C0jwATJPa5caQblhoWR/3mk90CR+Kf3l38FgDP7mDnb2gOE3Ema4m9+Vykjz94FdkrX8B3x85h7ftfIn3xP/ghc8a4Y3PNqmkWax750nH7xOOGdsk7duwQOBJCPIevXX86CyVIjWR8QAW1UeC33/+HF158EVqtFmmLFuKtlZnQ6fWoqbtTpanSoPR2KbLefhvpGRnQarV4+tmncf7iBQS1UfjcONLBvQdAxDDQ6nT43yn3L1jqqdy10G11VRUAoNO9bVz6Pp7IfCibpwxtozlMxNWsJTPcsLqFb3yE6VOT0DvhfiTPfQ/PTlkFAA2uP+ZLx+2sFw3rIX3++ecCR+J5vG2hW29jbRibpwxt87XrT2ehBMkO1g5i7oBq2bY1/tQqce+992Hu3Ln882+++SZycnIgEotQy+qgB4v/rF6N115/jd/m9SWvoWPHjhCFSiAKCXLnP8kthj5qOKG+OXW2wJF4Dne1Cj//01kAQK+e9zW4rVAJhLPfl9ufeUtibohQ8tz3BE+SCHEm858h42SGe66qbn2jsjI11r7/JbbWdajbuu0IAP8a+nn/vW0QFBTk0nbf3soT24ULlUA4+33Xb9uEOZmLLIaxcUu7vL5mhVPehzgXJUh2qG98ZkVQDXR6PaprqvHSSy9hwYIF/HMZGRnIzc2FOECMnJwcZGTcnY+TsTQdqSmp/PcBzaTwNRvTcwEAd0pvQafTCRyNZ3BXq3B93ck//bV/NLCl9QskdyRNzr4w4/YHmLYknj97FMRiEXQ6vV9cBBL/Ud/PEHejADB0qtOzLJa/vR3Sug513N++NITOHp3ubQW1Wo3bt28LHYpH8cR24dauvdyRNDl7Tk7Wxmzo9DqIRWIaxuZFKEGyQ33jMxMTEwEALMsiQCzGSy+9hIULF/LPL1y4EFFRUUhLS+MfM0+OAEAU6nudxoICgxAV3gwAsHzGPIGjcY+GhtC5o1U4y7KAA3dHrV0gNSZ5sZVU2Xrc2Rdm3P7MWxJPn5qE7JUv+NVFIPEP9vwMaTTV6BbfHpERclSoKjHi7w/zHeoA3xpCZ4/xzzwKANi8ebPAkbhXQ0PoPLFduLVrL0eTl/oSKlvPOXtODre/rJSlJsPYlsxIRWxMayyZkVrPq4lQGNZH68xKpRJhYWG4+s1ZKOShLnkPJkAEfQc5lKoK/jGxSARJcDByc3NNEiVORkYG5qekgtVbfuyVZ24Ctb7VFvvM/84i4R+DIBYx2HnpB6HDcbkpvZ5Aack1RLduiQ8KvhAkhkq1Bk916gsAYJWNq5g0NC/BmnsenIbLxaVoFxuNS2fWNfi4UBrzbyOOUSo1CGvzHMrLy6FQKBp+gR/hzk27ts5HiCzYKfu8facCr2V8wg+nM7yPBrdu3z03BYhFqNXpESAWoW1sdKPep1ypxp0ydZPjbQjLso7c42m0Y8eOQSwWu/6NPMATTzyB69evIyYmBl98Icy5yZqHHnoIMqkMN7/9za7t12/bhKyN2ZgzMdmuOTOdhieg+HoJYmNa4+zuY3Y/526O/rtI4yhVFWj1t052nZsoQWoCRiJG8P3RKKsoR1V1FYIlwQgKDAQjFkEqlaJZs2YoKyvjtw8PDzeU9fUsWJ3lx151rhRste8NRQvr1Q46nQ6L1r+NhMGPCh2OS+3dlI/PcvMwduYkwRaUvfDLr/jn489CLBah9o77JtzaSjw8LSHxtITNFk/73BxBCZJt3LmJCK9NmzbYuXOn0GG4RX5+PvLy8jBp0iSPqhI5miA5qr7Ew5OSEk9K1hriSZ+bozwuQTp06BAyMzNx4sQJXLt2DTt27MDIkSNtbn/w4EEMGDDA4vFr164hJibGrvd0VwUp+MHmlo+LGCzPXGEyrI7jbxUkAEhOT0Heri0IDVfg46IDQofj85IHP4PL5/6H1q2a4Y9z7wkdjkvUlzw0lFh4S+LhLYmcNZQg2cadm2TyEKeuU9YyLhZdHulp9/YXzvyKX0+exn3dO6P9gw03cwEARiTGqGkTEBru3f+nezdv49foO3jwIORyeQOvIK7i6gTJ3RqbkHlT0uFNyZw5j0uQ9u7di6NHj6JHjx4YNWqU3QnSr7/+avIPaN68OUQi+6ZNuSNBAgDpg82BANOYVmSuQNqiu8PrwsPDTSpJCxcuxPx5qZAFy/jH2Fo9qs7cdFmcQtLpdAjr1Q4AsP18AQKDfK9jnyeZ1n8Url64jKnjH8P6nFlCh+MS9SUPrkgshEiqvCWRs4YSJNu4c9MnZ76FLFS4C3Pz4cCeUP12p2FtewAA5HI5Dh48KGwwfszXEiR3D+kTIrHypmTOnCMJkluaNAwZMgRLly7Fk08+6dDrmjdvjpiYGP6PvcmRO+lU1SbfmydHGRkZuHXrFtLT0/nH0tPTsXzFcpPX6StM9+NLxGIx2sa0BgAsmfCSwNH4vmsXrwAAOrS3r9rqjeqbnO6KrlxCtEL2t8nzxL069YiHSCxCpx7xANy3BIGnWLH9AwCASqXC1atXBY6G+Ir6Gjy4YkFWZ3fcs4e/rJvkeRmHka5du6Jly5YYNGgQjh49KnQ4VtX+Wcl//WbGUpPkaOHChXj5pZdRqanEzJkzTZo2pGdk4M2MpSi9XQpNlcZkP75o71rDXJifC04IHInv44rCC+aMFjgS16kveXBFYuFvrZCJ7zDvrMl9f2zft9Dr9Dh5qACA6RIE7lrQWkgPPNQForoGDfWNaCHEEfUlD65ILFyRdBEDj0yQWrZsibVr12Lbtm3Ytm0bYmNj0b9/f5w8edLma6qrq6FUKk3+uINeVQN9RTXOnz+P9Iy7VaKFaWmYOXMmypXlUFYoodFoMPvV2VhoNC8pPSMd53//HV/t2we9usYt8QqlXatYBAYEAiyL/35Ma9G4Sk21MJVIoRabdReq5pDGEurcxDGvDHHf11QZfldoq2swpdcTAMAvQeAv1aQPju0BAOj1evzwg+93WfU3Qi00607+Us0RgkcmSPfddx+mTZuGHj16oHfv3vjggw/Qu3dvrFq1yuZrli1bhrCwMP5PbGysy+Pkfvg+fDcPUVHNsG7dOgQGBuK1Ja9hfup8iEUiBEuC+b+rqqswc9YsLExLQ2BgID7c+CGaN2+Ost+uW92vr/1Qz51kuMOxYek7wgbiw0pLDMeSSOS8yd/2EGIIGiHewN3nJuPqz95N+ahUqyEPV/CLU3OVor7DBkMerkBNVbVFMmRrQWtfqyw1ax4Nebiho+D06dMFjoY4mxDDz4jvcHubb4ZhGmzSYE1KSgqOHDmCgoICq89XV1ej2ujuuVKpRGxsrEubNHAT7sQiMR7p3Rtr312H8rIyPNzjYYttS2+XQqc3dKhTyENx9Y+r6BjXHtUX7kCv0Vrdrzd2CKmPXq+HIrEtAGDzj/sR1ixC4Ih8z8/HTiJt7AuQBAWg6tanbntfb24oQJyPmjTcZevc5KomDVzzBXm4ApoKFfQ6vc112bhtRWIRpr+R2mBzBk9Y583ZKjUaPHW/Yd24mTNnYsqUKQJH5F9c2aTBm5sJENfwuCYNznDq1Cm0bNnS5vMSiQQKhcLkT2M4Ur2ZMzEZYpEYOr0OPxf9jMnjJyI8+O77aqo0/ByjEJmhpSvDMKhQq6Cv1qLqtz8tkiNuv744plQkEuGB9oZ2stSswTX+Pec1AECL5uFufV8agkaIdc46N9lbveGqPwCg1+khEotsVoI69YhHdOuW6DN0ED7MzMG4+AH17t9WZcmbSWUydOz6AAAgNzdX4Gj8y0cffQQACA6SuGT/NPyMNIVbEiSVSoVTp07h1KlTAICLFy/i1KlTuHLF0G1rwYIFmDBhAr/9O++8g127duH8+fM4ffo0XnnlFXzzzTeYNcv1LYsdKck+P3o8slKWIjamNZbMSMW4gaMw+O9JGDXqSax5by0uXLoInV6PCrUKao0at0pLsX37dowaNQq9+/cFW2N9UVhf/qHetdrwC/H3n88KHIlvqq6sAgDMemGIwJE4h6/PbSLEXvbOCxoyfgw+KPgCE1JmIbp1S0x/IxWAofozpddQDGvbA+++lonSkmt8g4Zj+76FqkwJVZkSH2bmNLhvX2sDvmr33RuiqampAkbiX86eNVwHjB40QuBIHOOr0yCIqQB3vMkPP/xgsvDr7NmzAQATJ05EXl4erl27xidLAFBTU4M5c+agpKQEMpkM8fHx2L9/v9XFY51tzsRkviRrDy6JydqYDZVGjTvKMhTvKcGuPZ8DAO7t8BfooEdFRQVu3ry7zlGEIhyTFyVj+/7PMWrgMGxYapqQ+WppuGV0DIKDJKiqqcah3V+i33CqODhT+a3bAIDISNet/eVOxnObqDpF/NnYmZP4dYrswSUxn+XmoVKthqrsbnOIWm0t5OEKqMsrTB7nZCan4ciefegzdBBSsjP4x315raS+w5NwePeX+Prrr8GyrFMX8SX1kwUHCx2CQ4xvpPvS9Rkx5ZYKUv/+/cGyrMWfvLw8AEBeXp7JQm3z5s3D+fPnUVlZiT///BMHDhxwS3IE2Fe9Mb97kPbvN1B8vQQqjRoRinB+uwhFOCrVGvz+++8myRHDMFgyIxXb938OnV6H7fs/t9ivL08ufHHsRADA6tSlAkfie7gphVMnPCZwJM5B7bUJMbCnemPeoGHNouUoLbkGbXUN5OF3h/bJwxWQhoTAfAoywzCYkDILR/bsg16nx5E9+0z2+2Fmjs92t5tnlAgOHDhQwEiIp/PVaRDElNfMQRKCccJSX/JSWW0Y1lSrq4VcFsK/vqyiHCqNGrJgqcW+j/54DKMGDoNYJEaX+zqj0/AEvL5mBb/fxPieEIvESIzv6Z5/rBulv/wvAECVWgO1SiVwNI3naR2darV357P5yt1PmttEiCXzRIj72ngY3me5eXwCFCgJgjTk7rlJVaZEWLMIi98TQcGGuSB9hg6CSCxC+wfvN0mMAENyValWe8zvPWdaumUNAKC8vBxareX8YG+Rn5+PJ554Avn5vvd/5Al8eRoEuYsSpHoYJ0Lc13MyFyExvqfJ3YMxg0ZALBJjzKARJgkNy7K4oyzjEyjjxz/7aif2Fx7EqIHD8NOvp1F8vQRlFeWIUIQjMb4nX10qLDruc+NdGYbBX9p1AAAsetp7W6t62lohpw5/DwAQi33nx5rmIBFiyTwRKi25hrWLV/BNF8bOnISxMydBHq6APFyBCSmz0KlHvMk+zhf9YlFBqq6swppFy3HyUAH6DB2EC2fOobTkGtTlFZCHK9C9Xy9oKlT8XCVPukHkDF0eeRioSxofffRRgaNpvLy8PFy/fp0fpUOcz9euy4gl37mScgGujJoY3xMqjRoAoNPrsL/woMndgw1Ls1FeeBkblmajsOi4xX4CxYapXgxgWCy1zh1lGfL37YJOb2jWwLIs5LIQFBYdh06vg1gk5udE+dpwu6/WbQMAnP/5rMVJ2lt4WkcnbpFYmdQ1HYGEQOsrEWKJS34q1Wp+uQS9To+zJ4r4YXhDxo/BlqID2FJ0AEPGj8HZE0VW98UwDDrGP8B/z7IsVGVKHNr9JfQ6Pf+YNCQEZ08U8Z3xAHjUDSJnWX90NwDDXOgff/xR4GgaZ9KkSYiJicGkSZOEDsVn+eJ1GTFFCVI9uDJqYdFx3FGWWR22tH7bJjTv9xfIH26DiN5xuH7rpsU2NbVawzA7hoG21rRszyUHsmApX5XiErNRA4fxw+18bbxrdGQU39pz53sfCRxN43haR6d1i98CAERH+UaDBoDmIDmKKm7+Ycj4MZCGhEBVpsSFM+cAwKKdd2ZyGoa3ewhPdkjAkx0S+CFy5oKCJSj+3wWrzzEMg37Dk0yqUlxbcAAmC9D6ihZtWkEqN6xP9eKLLwocTeOMGTMGX3zxBcaM8Yxzky+ieUiO8caKGyVIduB+EMYMGsG39OZkbcyGpqoSAKCt1VokQBxNVWW9lZKh/QxzLI7+eIzvXldYdBzF10tQWHTcJ8e7vj5rAQBgUyatPeEMlWpDlXPVMt9Z6NDaHCRbSQAlB1Rx8yfGyQrXztv4Zs2RPfvAsixqtbWo1dZavL5FixZo3749whVh/PIA5oKCJTh7oohPgrgOdmdPFEFVpoQ0JMRjbhA508Yf9gIw3MDctWuXwNEQT2RtHpKtJMAbkwNn88aKGyVIduB+EDYszeZ/ILgDPjG+p9UmDAAQG9Pa6uMMwyAwIBCBAYFgGAZjB4/kk6Ht+z/nDyJfv0Mxa9zzYMBAW12NirJyocNxKiEaOFSpDYl6cHBgA1t6N1tJACUHVHHzJ1wFOyU7g69kG//e4ao8gGGRbgDo1asXcnNzUVRUhJMnT+Lw4cM4efIkfvrpJ+Tk5KBv374AgIDAAMjDFQiUBFnMdeKSJE8aXuxsUpkMMbGG8/ebb74pcDTOQ80bXMtWEuCNyYGzeeP1LCVIjcQd8IVFx3Hz0P+sJkN/lt22+toAcQC0tVrIZSGoOFaMR7ol4M+y22AYBl3u68wfRP7QKaVrp78CAOaOmCRsIE4mRAMHrkI56G9d3faeQrCVBFByQF3//J3x752U7AxEt24JALj3gfuxefNm5OfnY8SIEWjWrJnJ66KiojBy5Ehs3boVmzdvRueuXTEhxbAwu0QajEq12qQBhKcNL3aFdYd38l8vX75cuECciJo3uJatJMAbkwNn88brWUqQHGBcJjU/4KMjoky2lQVL+aF3AEzWR+KG4ZUpyxA7sDNeX7OCH4JXeueWRZXKl8uyX6413Mm6evGK1zZrsMbdd1h1Oh3/ta+0+LbFVhJAyQHxV1zlyDiJAQy/hx5OTMD2T/Nxzz33GDY2+/0gC5WbfH/PPffg440f4ofPv4GqTAltTQ1UZUqTBhCetsSBK4hEIsT3TgBgqLz4wvmJmje4lq0kwBuTA0IJkkO4qtHra1bg9TUr+M52APDj2Z9Mtm0WHmnxevPLVhaGTnZ3lGUADB3ujO8w+ENZViaVQS4znKA3ZPxH4Gicx913WL/asgOAb7X4JoTYh6scnTxUgEq1Gh9m5mDvpnxEKMKQ98EGFBYWYsCAAcjOzgbqudDPzs7GgAEDUFhYiLwPNiA2NhZ6nR4SabDJzR5PW+LAVdK33p0fO3bsWAEjcQ5q3kCI/ehqqgHWqkbA3cQma2M2Ji9Khvkpp/h6icn3d5RlFtuY0+v1FvObrJVlfa2ytHqBYfjC7vc/FjgS71VdaahWRjdTCBwJIcTVzCs4XMUaMCwCy61T1CmiDW7fvo1p06ZBq9Vi2bJlhiTJiKbCsFh3dnY2li1bBq1Wi2nTpuH27dtYtmwZAEBbU2NSOTKvVFmLyVeMe8XQye7SpUtevXgsIcQxlCA1wLiKw5VJl8xIRYQiHLJgKVQaNT77amej9m0+FKrLfZ3RaXgCUrIWo/h6CXZ+s4d/bv22TYgd2JkfkudLlaWxSSPBMAx0tbUo/v1ik/fnqyfq+uTnbgQARISHCBwJIcTVzCs4XMV6QsosSKTBYBgG3f7aBQMGDEBcXBzmzp3Lv3bZsmXIycmBTCZDaGgoZDIZcnJy+GQIAObOnYu4uDgMGDAAiYmJaP/g/ZjS6wm8+1omSkuu4bu9XwMATh87iXHxAzAufgA+zMzxyarSs7On8V8nJTV++C41SCDEu1CC1ABrk+ueHz0exftPQxIk4YfHAYaERywSmywGC8BqlzuGYfgxzVwnu59+PY3i6yX8HCVtrRbF10swJ3MRXl+zwmQ4nq9N+HssoR8AYPE/ZjV5X/4y/MMYdxf4o/dfFTgSQoir2ZrjOGT8GCgiI8CyLJ555hn+8eTkZCxYsID/PiMjA7m5uZDJZMjNzUVGRgb/3IIFC5CcfPfcMu9fabhw5hxKS67x7cJrtbUoLbmGQ7u/5CtWAHy2s928XEPyqFQqoVQqG7UPapBAiHehBKkBXNUIAF/BWb9tE9Zv24SyCsvW1Dq9Dnq9nv+eAUyaNXC63R/Pfy2VBKOw6Dh0ep3JNrExrSEWifnHIxThiFCEY8mMVJ+b8Lc1830AwK2rN0w+v8bw9Ra01mjrLlykwUECR0IIcTWuYgSAr+BwFfNOPQznlj59+pi85uWXX8bChQv57xcuXIioqCiTx9LS0pD80kv890HBEtx7T3vodaa/k6Nbx0BUN9+RYRjIwxWYkDLLZzvb9X1iMBiRYcRHY6tI1CCBEO9CCZId1m/bhDmZi/gKzqtvpeHVt9IsutowDAOGYaCQh/KP2Zp3dLHkssn3XKVq7OCR/NA7lUaNrJSlfAe8JTNSUbz/tE8lRpxgSTAi6/6db7+yuEn78ocWtBbqjsW/dGwpcCCEEHf5MDPHZM7RuPgBOLT7S7Ro0QJRUaadVQOCAjEvNRXp6en8Y2VlZfzX6enpmDdvHoIkd2+yaKtr0Do2Fg90+Sv6DU/iz02Vag2mv5EKebgCIWGhmJAyy+d/377zfx8BALRaLc6fP+/w66lBAiHehRIkO2RtzIZOr+MTIJZlrbb81Ov1YFnWZNgdx3yYXXVNtcn3xovRhoeGAQBfoZLLQviGEL6MqyId/fxLgSPxLsYtvsVisYCREEKEwN9UqxvqFhISYtHOu6aqGgyA1NRUhIeHmzwXHh6O1NRUiMVi1NbcbUTAAgiWBWP1/32MlOwMhIQZbv6pyysAANKQEKjKlH4xnLn9A/dBJjd0XDUevkgI8U2UINmBq+6smpeBVfMyTJorMAxjMefIGvNhdsbfa2trEZbYDpMXGcZ9L5mRCrFIDJZlkbUx228WGevdLQEikQi1Oj1+LvxB6HC8xsdZawEAAdTimxC/MiFlFqJbt8SMpfMxIWUWf25Sq9WGmyVmSZJOp8OKFStMKkeAoZK0YsUK1NbWmg5xZlncvnEL/5m/lH8/kVgElmXxWW6e3w1n3nL6AP/1l1/SjTxCfBldUdnBeJGv50ePN5k/xLIs31ShsbS1Wuj0Onz21U7EDuyMoz8eg0IeynfJA+Bzc45sGTt4BABg+YxUgSPxHmW37wAAOrSPETgSQog7mQ8nDgqWAABu3LiBG9evW6x5lJmZaTLnyLiStHDhQmRmZlq8R2lpKXZt+gTj4gfg9LGTkIXKIZEGo1JtODf503BmkUiE6FjDMGbjz5EQ4nsoQWqEn3497ZT9iESWH/8dZRny9+3CHWUZqmtq/GJonbF1i1cBAJR/lqG2tlbgaLxDwV7DXU15SLDAkRBChPJZbh6qK6v4748cOWLyfHZ2tkm3uvT0dNy6dctkTlJGRobFOkncflRlShz+/CuoypTQ1tT4zdA6cx8c/YL/etq0afVsSQjxZpQg2cl4cdZRA4dZrGEEgG+mYC9b3dqkkmDExrTGqIHDTIbWGa+F5CuLxJoLCAhATLPmAIA3p1DLanuo69rOfrYpReBICCHuZrx4qzxcgYBAw5DvzZs389twi8By0tLSMHPmTGg0GsycORNpaWn8c+aLyX700Uf810HBEkS3bok+QweZDK3buynfopueL0t6dhQA4MSJEwJHQghxFUqQzBgnQsaMF4zdsDQbbVq0svr6IDvmI9nCtfHO+OdizJmYjMKi45gzMZkfWpe1MZvvpOfLVaV963cCAH48VCBsIF6Ca8Eb3UwhcCSEEFextQA2t+7b2RNF2FJ0ABHNDd3rCgoKcODAAVy8eBErV67kt1+wYAFmzZoFjUaDiooKaDQazJo1y2SdpJUrV+LixYv45ptvUFBQAHm4AvJwBRIGPQoA6JzQ3WRo3We5eXw3PX+oKiUvvzu8bsSIEQJGQghxFUqQzBgnQsbMGyXMmZiMCEU4jOtId5RlqDGbj2SeMFlbNJZTvP8038bbWhzce0Yown26YUNc67YIEAeA1bM4tJsmwtpLLrd9bBFCvJutBbDNGyWMnTkJ8nDDzZIFCxYgMjIS69atQ2BgoMUisMa4xWQDAwOxbt06REZGIi0tDQGBAdhSdABbig7g7IkimzFwSZS/NGyY/uZ8AEBJSUmjF48lhHguhrXWr9oHKJVKhIWF4eo3Z03WJWrI+m2b+M5xDTVF6DQ8AcXXS8DA9npHHAbAmMEjUVh0HMXXSyyelwVLMbRfEl81AmB3HL5o3ttLkLv1fYQoQrH19EGhw/FYLMtieLuHwDCAvny70OEQAgBQKjUIa/McysvLoVBQZdMYd2765My3kIXK7X7d3k35fOe4hpoiTOn1BEpLrgEAunbtio8//hi3b99GXFyc1e2DgiXQVteAZVlcvHgRkZGRmDRlMn766ScESoLQvV8vnD1RhE494nH2RJFdMfiD4e0eAsuykMlkOHTokNDheJ1Fixbhv//9L/753HSkv7xI6HCIH1CqKtDqb53sOjdRBcmMccc6Tr+JQyF/uA36TRxqsi1XVQq3MffIuP03C+CRbglWnwMMbb/z9+1C8fUSvL5mhdU4/MnyV5YAANTKClRqNAJH47nWLDTMK6D1jwjxbdYWwH71ifEY1rYHXn3C9DzBVZUk0mCcOnUKSUlJuHTpkvUdMwwCAgP5tf0uXryIpKQk/HLuLN+M4fDnX6G05BpOHirwq651Dcn4bD0AQKPR4MqVKwJH430KCwsBAM2bRTWwJSHuRwmSHU6e/cnkbw6XxCyx0ZI6c84bJt/Py1rMV4/MW4MzDIMAcQAAy0Vk/ZFIJEKHWMPdzn89O1PgaDxXyYXLAICEh/4icCS+ae37X+KeB6dh7fs01JN4nvNFv5j8zeGSqamLDI1uiouL8dxzz2H06NHYsWMHNNV3u92BZXHl4iXs2LEDo0ePxvjx41FcXIwqtYaf3+ijA02arPPDXREQaDhvjx49WuBovI+6rlX8S+NeFDgS72NrvjxxHkqQ7NC9UxeTv809P3o8xg4eCbFIzHey696pi8U8JvP5SQD4OUzhoWGQy0IAAJIgiXMC93L/l/sJAODXkz8LHInnunDmNwBAsKTxzUGIbcvf3o7LxaVY/jYNXySep2P8AyZ/mxsyfgz6DU+CSCyCPFyBwsJCvPNuLnr37YNu3bqhb9++6NatG7p27Yrk5GT+jj4A6Gp1AMB3bBWJRZiQMsvF/yLvk3f8vwAMSWRBATUWagxrS56Q+tmaL0+ch45KOxzauAeq7//AoY17bG6zYWk2ygsvo3j/abyTugyld24hOsK0bGzcBpxrtiANliJCEY4lM1KxZEYqYmNa26xI+ZvWLVpBEhgEANi5/mOBo/FMKmUFAODDd18WOBLfNH/2KLSLjcb82aMavQ+qQhFXWfXFJnx+5QRWfWH7LnJKdgZ2XTyOLUUHMDN9Acr/vIOwZhG4efMmLly4gNLSUnT4ayd+++jWMZCHKxAULIE8XIG+wwYjunVLTH8jlYbWWREWGcE3xXjppZcEjob4C/PGYY1BVaj6UYLkZOu3bcKrb6Wh+HoJfjxXZPLcHWUZ/zVXLdJUVaK6ppq/C+DP846sefMlw/ocH2XlChyJh6ob+tKqZTOBA/FN06cm4dKZdZg+NanR+3BHFYqSMFIfrkX4+0tXobTkGn7/+Sz/HMuyuH7lD/77SrUGmgoVqiuroKlQWbT0JpY2/nD35854MV5CXMUZ89TdUYXy5iSMEiQr6vsPNX7O2nZZG7P58dqB4gAwDIPAgECTduAMgMT4nvz3ldVV/EHqzQeTK8x4eioAoEpdidJrNwSOxrNUV1U1vBERnDOqUA2hoYC+z9Y6SNaeM/+eaxFeU2WY38qyLD93BgBUZXfbVGura/i5R3qdHp/l5tX73gQICgrCAw93BQBs304/g8Q7OKMK1RBvHgrotwkSl4hMXpRsNckx/g+dvCgZYYntMHlRsslzDa1VFCILAcuyiIlqbtLpjgWwv/AgP6RuzKAR/EHqzQeTKzAMgy73dQYAvDnpnwJH41lYvSERF4v99sfYKzijCtUQdyRhxPW4RCQzOc0iIbG2DlJmchpGxPXkK0Pcc+bbcl3t+g4bDFHd74uI5tGYmb6A/95YdOuW6Dc8iV9fydYaTOSuFfnv81+/+CI1HSCezx3dkt2RhLlKQMOb+CYuEbl68zp0eh2yNmbzBwmXqHD/odv3fw6dXoft+z9HVspSk+eMv+bIZSFWn399zQp+mF11TTWeHz3e6oFpbZ/+bOe/NyPu8a64ePZ/QofiUdYs4lp8U4Lk76ZPTXJpAkbcg0tE/rx+g6/ecEPbuETFeCHWI3v2Qa/To6aq2mKxWPNtAaBzQnd0TuhusZ7S+0tXobrSUJEOlAThg4IvrMbmL4vANtZjY57A1/lf4OTJk2BZlm9wQYi/snWd6w389sqKy2pHDRxmkd2aZ9WjBg6DWCTGqIHD6s2412/bhDmZi/i1jMwTqSUzUvlGDbY61fn7+kfWREdGQRYsBQD8dzMNX+D8dsrQ2vfvg7sLHAkhxBm4Sk+foYNMEh7A+jpIfYYOgkgsQt9hg/nnzBeU3bspH2sXr7BaAeK2DZQYmuHY6lRn7b2JpVfefp3/un///sIFQghpMob10QUOuNXKr35zFgp5qFP2uX7bJj7peX70eHQanoDi6yWIjWmNs7uP8d+LRWIo5KG4oyyDWCSGSCTi1z0aO3gkCouO8/sg9kl/920sW/82JNJg5P96VOhwPMLTDz4KTYUKE5/tj7y11MWOeA6lUoOwNs/ZtVq5v+HOTZ+c+RayULlT9mmcFHFVqOjWLfFBwReY0usJlJZcg0gswvQ3UvFhZg5UZUrIwxWoUmtQq62FSCRCs5YtTKpKpHF+/u4E0p4xDLE7evQoJBJatsOWXr16QavVQvX9Hw1vTIgTKFUVaPW3Tnadm/y2gtQY5vODuPlGKo3aUD2qq0plpSzFkhmpEIvE0Ol1JovCFhYdpwpRI6S9YFjwsLqyCqpyZQNb+wdNhQoAsCR1rMCREEKEZDxHaOzMSZCHK1CpVmPvpny+KmWtTXetthYAoNfrqULkJH/t3YMfWvfoo48KHA0hpLEoQXIAlwAlxvdEp+EJAAzzje4oy/g5TFzy8/zo8chKWYrYmNb8sDqRSMQPuaNudY5hGAYPdrgPADB/zPMCR+NZ4uJaCh2C01HbakLsxyVBnXrE88PoVGVKfg6TcfIzIWUWolu3xISUWfz6PdzfQP3d8oh93q+bw1VbW4sbN6j7qi+hazf/QUPsGsF4aJ1xQwdbVaGwxHbQ6XUQi8QoL7xssY+zu485NT5fxZVGAeDzKycEjkZYt2+WYuJDjwMAWKXvzcu658FpuFxcinax0bh0Zp3Q4RAH0RA721wxxI7DDaeThysgDQlpcMjciLie0Ov0EIlF2HXxuMk+uCF6pHGe7NgLtTU1YBgGx48fFzocj+SNQ+zo2s270RA7FzNuW9hQ04ZOwxPQ5b7OfJMHa/sg9lHIQ/lmDVv/s17gaITFdZySBPlmI0pqW02I47hK0oSUWfUOmeOqRO0fvB8isQh9hg6y2Ad1rGuaracPAjCsObV582ZhgyFOQ9du/oMqSE5g3ryB42iliTRsw86P8FJGKgICA7Hj90KhwxHMW8lpOLz7S0ilQdDc2Cp0OISYoAqSba6sIBkz72ZnzLhKZNwSnOYgOdeLfUfg2mVDdeSHH34QOBrP440VJOLdqILkZrYWdzW+00ALwDrH5JH/AMMwqNVqcevaTaHDEczpQsMQw2fH9hU4EkKIJ6pvcVfjKhEtAus66w7t5L9esmSJcIEQQhxGCZIT2Cq5Gg+/o7Ks8yTGPwQAmD9mqsCRCEejUgMAOraPETgSQognqm+onHHjBhpS5zoMw6DLIz0BAHv27IGPDtghxCdRguQEtLire+1e/TEA4EbxVej1eoGjEUa1phIAMGZEosCREEI8ES3u6hmWblnLfz1p0iThAiGEOMQtCdKhQ4cwbNgwtGrVCgzDYOfOnQ2+5uDBg+jevTskEgk6duyIvLw8l8fpSjTEznmkwVKEyQ1jR9csWi5wNMLq2KG10CEQQrwYDbFzvSemPAsAOHPmDKqrqwWOhhBiD7ckSGq1Gl26dEFOTo5d21+8eBFDhw7FgAEDcOrUKbzyyit4/vnn8eWX3rsmCg2xc671b/wbALB/y05hAxHAlV/PCx0CIcRH0BA715v22hz+68GDBwsYCSHEXm7pETxkyBAMGTLE7u3Xrl2LuLg4ZGVlAQA6deqEI0eOYNWqVUhKSnJVmC7FLR5LnGNIn0EQMQxqdTqc//ksOv61k9Ahuc2tG6UAAHmIROBICCHebsj4MTQMzw1e2/gfvDbxZajVapSVlSE8PFzokAgh9fDIOUgFBQUYOHCgyWNJSUkoKCiw+Zrq6moolUqTP8S3De1nuBP3xuR/ChyJe+3bugsAIBJ55I8vIcQInZsIAPQY8AgYEQMAePzxxwWOhhDSEI+8wrp+/TpatGhh8liLFi2gVCpRWVlp9TXLli1DWFgY/yc2NtYdoRIBbcxYAwC4c/NP1NbWChyN+5z89jsAwIuTBzWwJSFEaHRuIpw13+QDAGpra/H1118LHA0hpD4emSA1xoIFC1BeXs7/KS4uFjok4mJBgUGIimgGAFgxI1XgaNxHW6MFAPTp5T/DCgnxVnRuIpzW7e+BPDwMAJCa6j/nLEK8kUcmSDExMbhx44bJYzdu3IBCoYBUKrX6GolEAoVCYfKH+L7PV28BABzf963AkbiPtroGABD/YDuBIyGENITOTcTY5h/38V+vX79ewEgIIfXxyASpV69eFuXnffv2oVevXgJF5Jj12zah0/AErN+2SehQfN5f730AYpEYOj2L4/sPCx2OW8XdQ4vEEkLst3dTPqb0egJ7N+ULHYrfEovFaB3XFoChIRUhxDO5JUFSqVQ4deoUTp06BcDQxvvUqVO4cuUKAMMQhAkTJvDbT58+HRcuXMC8efNw7tw55Obm4tNPP8Wrr77qjnCbjNY8cq/nnngKAPD2q4sFjsT1zp4oEjoEQoiXojWPPMOag9v5r42vffyNP80dJt7HLQnSDz/8gG7duqFbt24AgNmzZ6Nbt25YvNhwQXvt2jU+WQKAuLg47NmzB/v27UOXLl2QlZWF9evXe02Lb1rzyL1Wp60AAKjKlajVagWOxrX+99NpAEB4mEzgSAgh3obWPPIMDMNg+JRnAAC//PKLwNEIQ61Wg2VZiAPEQodCiFUMy7Ks0EG4glKpRFhYGK5+cxYKeajQ4RAXu39YAv64UYK/9n4IGVvXCR2Oy7w59RV8v+8wmkcrcOP3PKHDIcQqpVKDsDbPoby8nObcmOHOTZ+c+RayULnQ4RABDWvbAwAQHR2NvXv3ChyNe6lUKvTv3x+RinBc2X9a6HCIn1CqKtDqb53sOjd55BwkQhz11bvbAAA/F5wQOBLX+vHQMQDA9Cm0jgYhhHizlzP/BQAoLS2l9bEI8TCUIBGf0LZlGwQFBgIsi/9+vL3hF3ipWq1hzPbYJ72jYQkhhBDrBj09EgxjWDz273//u8DREEKMUYJEfMbs8bMAAB8sfUfYQFyI1esBAHHtmgscCSGEkKbK3JUHAKiqqsKFCxeEDYYQwqMEifiMhdPmAAAqVWqoysoFjsa1QkKsrwdGCCHEe9zXtTMCggIBAOPGjRM4GkIIhxIk4jMYhkGn9vcCABY9O1PgaJzvp+++FzoEQgghTvZBwRcAAJ1Oh4MHDwobDCEEACVIxMd8kb0VAPD76XMCR+J8R7/YDwCIakZdwQghxFdEREchNDwMADB37lyBoyGEAECA0AG4Cte9vEKtEjgS4k7SYCkkgUGo1tZg08ocjJ42UeiQnObW9VsAAIVCCqVSI3A0hNimrDAcnz66ikSTcJ+JRqUWOBLiSd47sgvPdO4PANi8eTNGjhwpaDyuplYbjn+WZaFUVQgcDfEXXE5gz7nJZ9dB+uOPPxAbGyt0GIQQ4reKi4vRpk0bocPwKHRuIoQQYdlzbvLZBEmv1+Pq1asIDQ3l22g2llKpRGxsLIqLi2nRwwbQZ2U/+qzsR5+V/Tzhs2JZFhUVFWjVqhVEIhrJbYzOTcKgz8p+9FnZjz4r+3nCZ+XIuclnh9iJRCKn37lUKBT0A2An+qzsR5+V/eizsp/Qn1VYWJhg7+3J6NwkLPqs7Eeflf3os7Kf0J+VvecmurVHCCGEEEIIIXUoQSKEEEIIIYSQOpQg2UEikWDJkiWQSCRCh+Lx6LOyH31W9qPPyn70WfkP+r+2H31W9qPPyn70WdnP2z4rn23SQAghhBBCCCGOogoSIYQQQgghhNShBIkQQgghhBBC6lCCRAghhBBCCCF1KEEihBBCCCGEkDqUIDlo+PDhaNu2LYKDg9GyZUuMHz8eV69eFTosj3Pp0iVMnToVcXFxkEql6NChA5YsWYKamhqhQ/NI6enp6N27N2QyGcLDw4UOx+Pk5OTgnnvuQXBwMBISEvD9998LHZLHOXToEIYNG4ZWrVqBYRjs3LlT6JCIG9G5yT50bnIMnZtso/OSfbz13EQJkoMGDBiATz/9FL/++iu2bduG33//HWPGjBE6LI9z7tw56PV6rFu3DmfOnMGqVauwdu1apKWlCR2aR6qpqcHYsWMxY8YMoUPxOJ988glmz56NJUuW4OTJk+jSpQuSkpJw8+ZNoUPzKGq1Gl26dEFOTo7QoRAB0LnJPnRucgydm6yj85L9vPbcxJIm2bVrF8swDFtTUyN0KB7vrbfeYuPi4oQOw6Nt2LCBDQsLEzoMj/Lwww+zs2bN4r/X6XRsq1at2GXLlgkYlWcDwO7YsUPoMIiA6NxkPzo3NYzOTabovNQ43nRuogpSE9y+fRsfffQRevfujcDAQKHD8Xjl5eWIjIwUOgziRWpqanDixAkMHDiQf0wkEmHgwIEoKCgQMDJCPBedmxxD5ybiCDov+QdKkBohNTUVISEhaNasGa5cuYJdu3YJHZLHO3/+PFavXo1p06YJHQrxIrdu3YJOp0OLFi1MHm/RogWuX78uUFSEeCY6NzmOzk3EUXRe8g+UIAGYP38+GIap98+5c+f47VNSUvDjjz/iq6++glgsxoQJE8CyrID/Avdx9LMCgJKSEjz++OMYO3YsXnjhBYEid7/GfFaEEMKhc5P96NxkPzo3EdKwAKED8ARz5szBpEmT6t2mffv2/NdRUVGIiorCvffei06dOiE2NhaFhYXo1auXiyMVnqOf1dWrVzFgwAD07t0b7777rouj8yyOflbEUlRUFMRiMW7cuGHy+I0bNxATEyNQVIS4B52b7EfnJvvRualp6LzkHyhBAhAdHY3o6OhGvVav1wMAqqurnRmSx3LksyopKcGAAQPQo0cPbNiwASKRfxUsm3JcEYOgoCD06NEDX3/9NUaOHAnA8DP39ddfIzk5WdjgCHExOjfZj85N9qNzU9PQeck/UILkgGPHjuH48ePo06cPIiIi8Pvvv+Nf//oXOnTo4Bd36BxRUlKC/v37o127dli5ciVKS0v55+gOi6UrV67g9u3buHLlCnQ6HU6dOgUA6NixI+RyubDBCWz27NmYOHEiHnroITz88MN45513oFarMXnyZKFD8ygqlQrnz5/nv7948SJOnTqFyMhItG3bVsDIiKvRucl+dG5yDJ2brKPzkv289twkdBs9b1JUVMQOGDCAjYyMZCUSCXvPPfew06dPZ//44w+hQ/M4GzZsYAFY/UMsTZw40epndeDAAaFD8wirV69m27ZtywYFBbEPP/wwW1hYKHRIHufAgQNWj6GJEycKHRpxMTo32Y/OTY6hc5NtdF6yj7eemxiW9ZMZnIQQQgghhBDSAP8aeEsIIYQQQggh9aAEiRBCCCGEEELqUIJECCGEEEIIIXUoQSKEEEIIIYSQOpQgEUIIIYQQQkgdSpAIIYQQQgghpA4lSIQQQgghhBBShxIkQgghhBBCCKlDCRIhhBBCCCGE1KEEiRCBbdmyBVKpFNeuXeMfmzx5MuLj41FeXi5gZIQQQvwVnZuIP2NYlmWFDoIQf8ayLLp27Yp+/fph9erVWLJkCT744AMUFhaidevWQodHCCHED9G5ifizAKEDIMTfMQyD9PR0jBkzBjExMVi9ejUOHz7Mn4CefPJJHDx4EI899hjy8/MFjpYQQog/oHMT8WdUQSLEQ3Tv3h1nzpzBV199hUcffZR//ODBg6ioqMDGjRvpJEQIIcSt6NxE/BHNQSLEA/z3v//FuXPnoNPp0KJFC5Pn+vfvj9DQUIEiI4QQ4q/o3ET8FSVIhAjs5MmTeOqpp/D+++/jsccew7/+9S+hQyKEEOLn6NxE/BnNQSJEQJcuXcLQoUORlpaGcePGoX379ujVqxdOnjyJ7t27Cx0eIYQQP0TnJuLvqIJEiEBu376Nxx9/HCNGjMD8+fMBAAkJCRgyZAjS0tIEjo4QQog/onMTIVRBIkQwkZGROHfunMXje/bsESAaQgghhM5NhADUxY4Qjzdw4ED89NNPUKvViIyMxGeffYZevXoJHRYhhBA/Rucm4ssoQSKEEEIIIYSQOjQHiRBCCCGEEELqUIJECCGEEEIIIXUoQSKEEEIIIYSQOpQgEUIIIYQQQkgdSpAIIYQQQgghpA4lSIQQQgghhBBShxIkQgghhBBCCKlDCRIhhBBCCCGE1KEEiRBCCCGEEELqUIJECCGEEEIIIXUoQSKEEEIIIYSQOpQgEUIIIYQQQkid/weitJyOikoXhAAAAABJRU5ErkJggg==",
|
|
"text/plain": [
|
|
"<Figure size 1000x320 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def plot_clusterer_comparison(clusterer1, clusterer2, X, title1=None,\n",
|
|
" title2=None):\n",
|
|
" clusterer1.fit(X)\n",
|
|
" clusterer2.fit(X)\n",
|
|
"\n",
|
|
" plt.figure(figsize=(10, 3.2))\n",
|
|
"\n",
|
|
" plt.subplot(121)\n",
|
|
" plot_decision_boundaries(clusterer1, X)\n",
|
|
" if title1:\n",
|
|
" plt.title(title1)\n",
|
|
"\n",
|
|
" plt.subplot(122)\n",
|
|
" plot_decision_boundaries(clusterer2, X, show_ylabels=False)\n",
|
|
" if title2:\n",
|
|
" plt.title(title2)\n",
|
|
"\n",
|
|
"kmeans_rnd_init1 = KMeans(n_clusters=5, init=\"random\", n_init=1, random_state=2)\n",
|
|
"kmeans_rnd_init2 = KMeans(n_clusters=5, init=\"random\", n_init=1, random_state=9)\n",
|
|
"\n",
|
|
"plot_clusterer_comparison(kmeans_rnd_init1, kmeans_rnd_init2, X,\n",
|
|
" \"Solution 1\",\n",
|
|
" \"Solution 2 (with a different random init)\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "161b0c65-e0ae-474a-aedb-0f3a4d4c2c96",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Manual initialisation\n",
|
|
"\n",
|
|
"If have a rough idea of good clustering, can set manual initialisation."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"id": "111f75d2-01d6-4216-9b4c-95f433895eeb",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.119729Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.119556Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.128790Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.128193Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<style>#sk-container-id-1 {\n",
|
|
" /* Definition of color scheme common for light and dark mode */\n",
|
|
" --sklearn-color-text: #000;\n",
|
|
" --sklearn-color-text-muted: #666;\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: flex;\n",
|
|
" width: 100%;\n",
|
|
" margin-bottom: 0;\n",
|
|
" padding: 0.5em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" text-align: center;\n",
|
|
" align-items: start;\n",
|
|
" justify-content: space-between;\n",
|
|
" gap: 0.5em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-1 label.sk-toggleable__label .caption {\n",
|
|
" font-size: 0.6rem;\n",
|
|
" font-weight: lighter;\n",
|
|
" color: var(--sklearn-color-text-muted);\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: 0.5em;\n",
|
|
" text-align: center;\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>KMeans(init=array([[-3, 3],\n",
|
|
" [-3, 2],\n",
|
|
" [-3, 1],\n",
|
|
" [-1, 2],\n",
|
|
" [ 0, 2]]),\n",
|
|
" n_clusters=5, n_init=1, random_state=42)</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\"><div><div>KMeans</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.cluster.KMeans.html\">?<span>Documentation for KMeans</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>KMeans(init=array([[-3, 3],\n",
|
|
" [-3, 2],\n",
|
|
" [-3, 1],\n",
|
|
" [-1, 2],\n",
|
|
" [ 0, 2]]),\n",
|
|
" n_clusters=5, n_init=1, random_state=42)</pre></div> </div></div></div></div>"
|
|
],
|
|
"text/plain": [
|
|
"KMeans(init=array([[-3, 3],\n",
|
|
" [-3, 2],\n",
|
|
" [-3, 1],\n",
|
|
" [-1, 2],\n",
|
|
" [ 0, 2]]),\n",
|
|
" n_clusters=5, n_init=1, random_state=42)"
|
|
]
|
|
},
|
|
"execution_count": 19,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"good_init = np.array([[-3, 3], [-3, 2], [-3, 1], [-1, 2], [0, 2]])\n",
|
|
"kmeans = KMeans(n_clusters=5, init=good_init, n_init=1, random_state=42)\n",
|
|
"kmeans.fit(X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"id": "1102abdb-5e5e-4200-b147-4b989002ef71",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.130470Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.130290Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.415955Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.415286Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plot_decision_boundaries(kmeans, X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "8b289ad4-aacb-4ee7-a5ee-b6f77a5a60ae",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Performance measure\n",
|
|
"\n",
|
|
"In order to assess whether a set of clusters is good, need to have some measure of performance.\n",
|
|
"\n",
|
|
"Goodness can be estimated by *sum of squared distances between instances and their clustered centroid* (low good).\n",
|
|
"\n",
|
|
"Score given by negative of this qualtity (so high good)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"id": "b18c5ff7-0a7c-44f9-be65-ccbed864eca7",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.417941Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.417765Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.422662Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.422070Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"-211.59853725816828"
|
|
]
|
|
},
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"kmeans.score(X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "fbdd8b7f-86bd-4a66-bf74-7986609f996c",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Multiple initialisations\n",
|
|
"\n",
|
|
"Now have measure of performance, can run multiple times with different centroid initialisations and then select clustering with highest score.\n",
|
|
"\n",
|
|
"Controlled by `n_init` variable in Scikit-Learn."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "59c62d7b-1a33-43a9-a348-72190b6894fc",
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"metadata": {
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"editable": true,
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"execution": {
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"iopub.execute_input": "2025-03-07T05:32:23.424453Z",
|
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"iopub.status.busy": "2025-03-07T05:32:23.424262Z",
|
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"iopub.status.idle": "2025-03-07T05:32:23.437608Z",
|
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"shell.execute_reply": "2025-03-07T05:32:23.437018Z"
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},
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/html": [
|
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"<style>#sk-container-id-2 {\n",
|
|
" /* Definition of color scheme common for light and dark mode */\n",
|
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" --sklearn-color-text: #000;\n",
|
|
" --sklearn-color-text-muted: #666;\n",
|
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" --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: flex;\n",
|
|
" width: 100%;\n",
|
|
" margin-bottom: 0;\n",
|
|
" padding: 0.5em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" text-align: center;\n",
|
|
" align-items: start;\n",
|
|
" justify-content: space-between;\n",
|
|
" gap: 0.5em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-2 label.sk-toggleable__label .caption {\n",
|
|
" font-size: 0.6rem;\n",
|
|
" font-weight: lighter;\n",
|
|
" color: var(--sklearn-color-text-muted);\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: 0.5em;\n",
|
|
" text-align: center;\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>KMeans(init='random', n_clusters=5, n_init=10, random_state=2)</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\"><div><div>KMeans</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.cluster.KMeans.html\">?<span>Documentation for KMeans</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>KMeans(init='random', n_clusters=5, n_init=10, random_state=2)</pre></div> </div></div></div></div>"
|
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],
|
|
"text/plain": [
|
|
"KMeans(init='random', n_clusters=5, n_init=10, random_state=2)"
|
|
]
|
|
},
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"kmeans_rnd_10_inits = KMeans(n_clusters=5, init=\"random\", n_init=10,\n",
|
|
" random_state=2)\n",
|
|
"kmeans_rnd_10_inits.fit(X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4524c4c7-8f7c-49d9-943d-412a24ab77b1",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Recover good clusters."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"id": "eda66172-ee1c-439c-b602-c5a9de875e28",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.439340Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.439172Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.711937Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.711261Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plot_decision_boundaries(kmeans_rnd_10_inits, X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c842d05a-f644-4eaa-ad76-020ca86928cf",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Extensions\n",
|
|
"\n",
|
|
"- Acceleration\n",
|
|
"- Mini-batch\n",
|
|
"- Selecting number of clusters"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "7a63242f-1e3c-44c8-b2a9-6894639579b0",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### Limitations\n",
|
|
"\n",
|
|
"- Need to run several times with different initialisations\n",
|
|
"- Need to specify number of clusters\n",
|
|
"- Does not behave well when clusters have varying sizes, different densities, or non-spherical shapes."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5f0a0e6d-0d88-488e-b524-0d489ca7cbce",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "slide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"## Density estimation with Gaussian mixture models"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "a75ccc62-75ea-4731-a770-d435582217be",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Aim of density estimation is to estimate a *probability distribution* from which data were drawn. \n",
|
|
"\n",
|
|
"Can then generate new data instances (generative AI) and also perform probability density estimation."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5698c35f-e9dd-411e-a27c-7ad557863b14",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"A *Gaussian mixture model* (GMM) is a probabilistic model that assumes that the instances were generated from a mixture of a number of Gaussian distributions whose parameters are unknown."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d99d4e4d-7c89-4b0b-82a3-01a89421fa7c",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### Gaussian mixture model description"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "95422c17-1259-4fab-9ec3-61c9128272d2",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Instances generated from a Gaussian distribution form clusters that look like ellipsoids. Each cluster can have a different ellipoidal shape, size, density, and orientation."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "a15daff3-3eca-446e-b8a1-c21749f34d8e",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Scikit-Learn contains several GMM variants. In the simplist, the `GaussianMixture` class, you must know in advance the number of Gaussian distributions $k$."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "724d96ff-26bb-42dc-879a-9841813029c1",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"The dataset $\\mathbf{X}$ is assumed to have been generated through the following probabilistic process:\n",
|
|
"\n",
|
|
"- For each instance, a cluster is picked randomly from among $k$ clusters. The probability of choosing the $j^{\\text{th}}$ cluster is defined by the clusters weight, $\\phi^{(j)}$. The index of the cluster chosen for the $i^{\\text{th}}$ instance is noted $z^{(i)}$.\n",
|
|
"- If $z^{(i)}=j$, meaning the $i^{\\text{th}}$ instance has been assigned to the $j^{\\text{th}}$ cluster, the location $\\mathbf{x}^{(i)}$ of this instance is sampled randomly from the Gaussian distribution with mean $\\mathbf{\\mu}^{(j)}$ and covariance matrix ${\\sum}^{(j)}$. This is noted as:\n",
|
|
"\n",
|
|
"$$\\mathbf{x}^{(i)} \\sim \\mathcal{N} \\left( \\mathbf{\\mu}^{(j)}, {\\sum}^{(j)} \\right)$$"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "28acc2bd-d0f4-48f1-95f9-25ac4b28fea7",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Let's generate some random blobs to use as a dataset again."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 24,
|
|
"id": "684e1980-71eb-4748-a70c-f7cffcd914d5",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.714311Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.714134Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.719858Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.719306Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"X1, y1 = make_blobs(n_samples=1000, centers=((4, -4), (0, 0)), random_state=42)\n",
|
|
"X1 = X1.dot(np.array([[0.374, 0.95], [0.732, 0.598]]))\n",
|
|
"X2, y2 = make_blobs(n_samples=250, centers=1, random_state=42)\n",
|
|
"X2 = X2 + [6, -8]\n",
|
|
"X = np.r_[X1, X2]\n",
|
|
"y = np.r_[y1, y2]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"id": "29b9362a-9ae4-49d9-93b9-7483a6d8dbbc",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.721625Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.721457Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.823411Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.822731Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plt.plot(X[:, 0], X[:, 1], 'k.', markersize=2)\n",
|
|
"plt.xlabel(\"$x_1$\")\n",
|
|
"plt.ylabel(\"$x_2$\", rotation=0);"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5ef1235d-28d2-4fdd-834a-52d948f3111d",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### Training\n",
|
|
"\n",
|
|
"Let's train a Gaussian mixture model. \n",
|
|
"\n",
|
|
"The model is trainined by the *expectation-maximisation* (EM) algorithm. We won't go into technical details but has similarites with the K-means algorithm. It initialises clusters randomly, then repeats an *expectation* step (cf. assign instances to clusters) and a *maximisation* step (cf. updating clusters)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 26,
|
|
"id": "21208a04-d9ff-431d-ad74-843a079b2100",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.825362Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.825184Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.830771Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.830186Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"from sklearn.mixture import GaussianMixture"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 27,
|
|
"id": "effa4aaf-6129-4226-b59a-a97b8d32a4ef",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.832627Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.832316Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.902677Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.902140Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<style>#sk-container-id-3 {\n",
|
|
" /* Definition of color scheme common for light and dark mode */\n",
|
|
" --sklearn-color-text: #000;\n",
|
|
" --sklearn-color-text-muted: #666;\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-3 {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 pre {\n",
|
|
" padding: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 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-3 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-3 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-3 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-3 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-3 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-3 div.sk-parallel-item {\n",
|
|
" display: flex;\n",
|
|
" flex-direction: column;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
|
|
" align-self: flex-end;\n",
|
|
" width: 50%;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
|
|
" align-self: flex-start;\n",
|
|
" width: 50%;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
|
|
" width: 0;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Serial-specific style estimator block */\n",
|
|
"\n",
|
|
"#sk-container-id-3 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-3 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-3 label.sk-toggleable__label {\n",
|
|
" cursor: pointer;\n",
|
|
" display: flex;\n",
|
|
" width: 100%;\n",
|
|
" margin-bottom: 0;\n",
|
|
" padding: 0.5em;\n",
|
|
" box-sizing: border-box;\n",
|
|
" text-align: center;\n",
|
|
" align-items: start;\n",
|
|
" justify-content: space-between;\n",
|
|
" gap: 0.5em;\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 label.sk-toggleable__label .caption {\n",
|
|
" font-size: 0.6rem;\n",
|
|
" font-weight: lighter;\n",
|
|
" color: var(--sklearn-color-text-muted);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 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-3 label.sk-toggleable__label-arrow:hover:before {\n",
|
|
" color: var(--sklearn-color-text);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Toggleable content - dropdown */\n",
|
|
"\n",
|
|
"#sk-container-id-3 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-3 div.sk-toggleable__content.fitted {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 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-3 div.sk-toggleable__content.fitted pre {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 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-3 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-3 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-3 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-3 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-3 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-3 div.sk-label label.sk-toggleable__label,\n",
|
|
"#sk-container-id-3 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-3 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-3 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-3 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-3 div.sk-label-container {\n",
|
|
" text-align: center;\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* Estimator-specific */\n",
|
|
"#sk-container-id-3 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-3 div.sk-estimator.fitted {\n",
|
|
" /* fitted */\n",
|
|
" background-color: var(--sklearn-color-fitted-level-0);\n",
|
|
"}\n",
|
|
"\n",
|
|
"/* on hover */\n",
|
|
"#sk-container-id-3 div.sk-estimator:hover {\n",
|
|
" /* unfitted */\n",
|
|
" background-color: var(--sklearn-color-unfitted-level-2);\n",
|
|
"}\n",
|
|
"\n",
|
|
"#sk-container-id-3 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: 0.5em;\n",
|
|
" text-align: center;\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-3 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-3 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-3 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-3 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-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GaussianMixture(n_components=3, n_init=10, random_state=42)</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-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>GaussianMixture</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.mixture.GaussianMixture.html\">?<span>Documentation for GaussianMixture</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>GaussianMixture(n_components=3, n_init=10, random_state=42)</pre></div> </div></div></div></div>"
|
|
],
|
|
"text/plain": [
|
|
"GaussianMixture(n_components=3, n_init=10, random_state=42)"
|
|
]
|
|
},
|
|
"execution_count": 27,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"gm = GaussianMixture(n_components=3, n_init=10, random_state=42)\n",
|
|
"gm.fit(X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "91965fbb-57e5-4693-ae1f-76fb4a5099dc",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Let's look at the parameters of the GMM estimated:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"id": "b1397df2-f564-431d-8999-d0335f9b1bfc",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.904988Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.904805Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.909338Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.908881Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([0.40005972, 0.20961444, 0.39032584])"
|
|
]
|
|
},
|
|
"execution_count": 28,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"gm.weights_"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 29,
|
|
"id": "4e58e66f-59dd-4068-8fb2-4f52f9c43b7c",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.911681Z",
|
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"iopub.status.busy": "2025-03-07T05:32:23.911504Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.915938Z",
|
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"shell.execute_reply": "2025-03-07T05:32:23.915368Z"
|
|
},
|
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"slideshow": {
|
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"slide_type": ""
|
|
},
|
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"tags": []
|
|
},
|
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"outputs": [
|
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{
|
|
"data": {
|
|
"text/plain": [
|
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"array([[-1.40764129, 1.42712848],\n",
|
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" [ 3.39947665, 1.05931088],\n",
|
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" [ 0.05145113, 0.07534576]])"
|
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]
|
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},
|
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"execution_count": 29,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
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],
|
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"source": [
|
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"gm.means_"
|
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]
|
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},
|
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{
|
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"cell_type": "code",
|
|
"execution_count": 30,
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"id": "d3d1a385-4db6-49d6-aa12-0adc52725905",
|
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"metadata": {
|
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"editable": true,
|
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"execution": {
|
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"iopub.execute_input": "2025-03-07T05:32:23.918013Z",
|
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"iopub.status.busy": "2025-03-07T05:32:23.917721Z",
|
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"iopub.status.idle": "2025-03-07T05:32:23.922273Z",
|
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"shell.execute_reply": "2025-03-07T05:32:23.921776Z"
|
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},
|
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"scrolled": true,
|
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"slideshow": {
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"slide_type": ""
|
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},
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"tags": []
|
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},
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"outputs": [
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{
|
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"data": {
|
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"text/plain": [
|
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"array([[[ 0.63478217, 0.72970097],\n",
|
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" [ 0.72970097, 1.16094925]],\n",
|
|
"\n",
|
|
" [[ 1.14740131, -0.03271106],\n",
|
|
" [-0.03271106, 0.95498333]],\n",
|
|
"\n",
|
|
" [[ 0.68825143, 0.79617956],\n",
|
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" [ 0.79617956, 1.21242183]]])"
|
|
]
|
|
},
|
|
"execution_count": 30,
|
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"metadata": {},
|
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"output_type": "execute_result"
|
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}
|
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],
|
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"source": [
|
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"gm.covariances_"
|
|
]
|
|
},
|
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{
|
|
"cell_type": "markdown",
|
|
"id": "25d8790e-4879-416b-9255-b152fdbba228",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
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},
|
|
"tags": []
|
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},
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"source": [
|
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"### Predictions"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "806fbeb6-33d9-4c4b-85f4-a8d016832704",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"The model can be used to predict which cluster each instance belongs to (hard clustering) or to estimate probabilities that it came from each cluster. \n",
|
|
"\n",
|
|
"For this, just use `predict()` method or the `predict_proba()` method:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"id": "c1514c98-36c0-4c41-8e66-013b74f0ef7d",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.924979Z",
|
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"iopub.status.busy": "2025-03-07T05:32:23.924161Z",
|
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"iopub.status.idle": "2025-03-07T05:32:23.928952Z",
|
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"shell.execute_reply": "2025-03-07T05:32:23.928484Z"
|
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},
|
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"slideshow": {
|
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"slide_type": ""
|
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},
|
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"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([2, 2, 0, ..., 1, 1, 1])"
|
|
]
|
|
},
|
|
"execution_count": 31,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"gm.predict(X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"id": "043027db-4724-4eb2-af6a-fa520086dbe0",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.930889Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.930714Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.935904Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.935097Z"
|
|
},
|
|
"scrolled": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[0. , 0.023, 0.977],\n",
|
|
" [0.001, 0.016, 0.983],\n",
|
|
" [1. , 0. , 0. ],\n",
|
|
" ...,\n",
|
|
" [0. , 1. , 0. ],\n",
|
|
" [0. , 1. , 0. ],\n",
|
|
" [0. , 1. , 0. ]])"
|
|
]
|
|
},
|
|
"execution_count": 32,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"gm.predict_proba(X).round(3)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "83733bbf-e1a9-41a1-9dee-112c70e82593",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### Generative model"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "e024b7b9-e8a1-4b0a-b2d2-bf2a20e121fc",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"It is a generative model, so you can sample new instances from it (and get their labels)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"id": "ae6987db-a0c1-4dbe-ac1c-550b12d37764",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.937941Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.937765Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.944065Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.943632Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([[-2.32491052, 1.04752548],\n",
|
|
" [-1.16654983, 1.62795173],\n",
|
|
" [ 1.84860618, 2.07374016],\n",
|
|
" [ 3.98304484, 1.49869936],\n",
|
|
" [ 3.8163406 , 0.53038367],\n",
|
|
" [ 0.38079484, -0.56239369]])"
|
|
]
|
|
},
|
|
"execution_count": 33,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"X_new, y_new = gm.sample(6)\n",
|
|
"X_new"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"id": "d41f7c1f-6e4f-4f75-a0d3-970b5a6904b1",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.946209Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.946036Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.951024Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.950557Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([0, 0, 1, 1, 1, 2])"
|
|
]
|
|
},
|
|
"execution_count": 34,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"y_new"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "be0b4200-83f1-492f-9939-95cee8231fa6",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### Probability density estimation"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "298a478e-845a-41b7-a5f0-be616ae62184",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Can estimate the log of the _probability density function_ (PDF) at any location using the `score_samples()` method:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"id": "f63f5892-3af5-4a40-9b09-16a252ea7b70",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.953173Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.953002Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:23.959035Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:23.958565Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"array([-2.61, -3.57, -3.33, ..., -3.51, -4.4 , -3.81])"
|
|
]
|
|
},
|
|
"execution_count": 35,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"gm.score_samples(X).round(2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "22eeb02b-7f46-4441-973d-50b251e45906",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"A valid probability density must integrate to one over the parameters space. Let's check!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 36,
|
|
"id": "137358fd-658c-4a63-a50d-75a6b6cd616f",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:23.961456Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:23.961119Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:25.128194Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:25.127575Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"np.float64(0.9999999999225088)"
|
|
]
|
|
},
|
|
"execution_count": 36,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"resolution = 100\n",
|
|
"grid = np.arange(-10, 10, 1 / resolution)\n",
|
|
"xx, yy = np.meshgrid(grid, grid)\n",
|
|
"X_full = np.vstack([xx.ravel(), yy.ravel()]).T\n",
|
|
"\n",
|
|
"pdf = np.exp(gm.score_samples(X_full))\n",
|
|
"pdf_probas = pdf * (1 / resolution) ** 2\n",
|
|
"pdf_probas.sum()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1c159cf5-a9e1-4d04-bfd5-6784a15180ec",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"### Visualise"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "578a9285-d07e-4f08-8659-816353416937",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"Let's plot the resulting probability densities and decision boundaries for clustering (dashed lines)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 37,
|
|
"id": "fce7a3dc-9e32-4eb4-bb5f-7ebdb21ef90f",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:25.130371Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:25.130180Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:26.007076Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:26.006418Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"from matplotlib.colors import LogNorm\n",
|
|
"\n",
|
|
"def plot_gaussian_mixture(clusterer, X, resolution=1000, show_ylabels=True):\n",
|
|
" mins = X.min(axis=0) - 0.1\n",
|
|
" maxs = X.max(axis=0) + 0.1\n",
|
|
" xx, yy = np.meshgrid(np.linspace(mins[0], maxs[0], resolution),\n",
|
|
" np.linspace(mins[1], maxs[1], resolution))\n",
|
|
" Z = -clusterer.score_samples(np.c_[xx.ravel(), yy.ravel()])\n",
|
|
" Z = Z.reshape(xx.shape)\n",
|
|
"\n",
|
|
" plt.contourf(xx, yy, Z,\n",
|
|
" norm=LogNorm(vmin=1.0, vmax=30.0),\n",
|
|
" levels=np.logspace(0, 2, 12))\n",
|
|
" plt.contour(xx, yy, Z,\n",
|
|
" norm=LogNorm(vmin=1.0, vmax=30.0),\n",
|
|
" levels=np.logspace(0, 2, 12),\n",
|
|
" linewidths=1, colors='k')\n",
|
|
"\n",
|
|
" Z = clusterer.predict(np.c_[xx.ravel(), yy.ravel()])\n",
|
|
" Z = Z.reshape(xx.shape)\n",
|
|
" plt.contour(xx, yy, Z,\n",
|
|
" linewidths=2, colors='r', linestyles='dashed')\n",
|
|
" \n",
|
|
" plt.plot(X[:, 0], X[:, 1], 'k.', markersize=2)\n",
|
|
" plot_centroids(clusterer.means_, clusterer.weights_)\n",
|
|
"\n",
|
|
" plt.xlabel(\"$x_1$\")\n",
|
|
" if show_ylabels:\n",
|
|
" plt.ylabel(\"$x_2$\", rotation=0)\n",
|
|
" else:\n",
|
|
" plt.tick_params(labelleft=False)\n",
|
|
"\n",
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"plot_gaussian_mixture(gm, X)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "11feb53b-8b19-4390-8d09-8e5ecb565e97",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "slide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"## Anomaly detection with Gaussian mixture models"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3cf47de9-0cc0-4a7e-84a4-4a0f40acde21",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"GMMs can be used for *anomaly detection*.\n",
|
|
"\n",
|
|
"Instances located in low density regions can be considered anomalies. \n",
|
|
"\n",
|
|
"Must define what density threshold constitutes an anomaly."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"id": "12e7c124-913e-42a6-8e3a-23e586284b52",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:26.009077Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:26.008900Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:26.013481Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:26.012915Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"densities = gm.score_samples(X)\n",
|
|
"density_threshold = np.percentile(densities, 1) # Find threshold corresponding to 1% of instances\n",
|
|
"anomalies = X[densities < density_threshold]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"id": "009242db-3837-403f-ae46-8bcb40c50e9d",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2025-03-07T05:32:26.015220Z",
|
|
"iopub.status.busy": "2025-03-07T05:32:26.015054Z",
|
|
"iopub.status.idle": "2025-03-07T05:32:26.907039Z",
|
|
"shell.execute_reply": "2025-03-07T05:32:26.906342Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": "subslide"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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INN1SxHjUJqBfsBL9P0vpPff+FomfkzqcrBz39mke1Vs+mML+jtHNbo+I5+i8N4eIQj1LhnasSU4cuWI/BeH+F5RYPRuWIj0VW7NQ7N1N1voizFU2NAEKEvuG02ZAOEn9w9EGedczpDUhhgG0ECvWGrn0+jz69FDz4pdBaHzEB3dzkHRjEbqVltPG9y8Iq/n/rHQbT9xTSla6jVGPp9Hj6iSvCqg3lltY8uZu9s7PdpWjunOS1xWJFxxOilfsJ/eX9ZhyygjoFk/Yw7eec+kpkdrII8NwmmzYyqpRBjd/A4rbv/73NKF63ec3kZkUVvcOIq2W3akx7E49aUAiYcmwlBazx1tRhfkTPjYNxqYR6HBSdSCfii0ZlG3fz76nc0AC0WlBtB0UQbtBEYS28xfvhR5AFKtuZNlqIxNuyKP/RRpe+DIQtVoUqp5GorfTpUc+UmvtcacUdm+OxBHiusT/nmngjWfKCYuUcf2Pwwhv7z0iUBAEDizJY9GrO3A6BNo+PI7QkaledcNz2h0UL91L7m8bMOdVENinDf43XoMqyfuqJrRm5ME6ACxFVS0iVj+bNoir5mxF6XC1u7zlgymiUBUR+Q+JTIp/ajT+qdFw40Biyqop35yJfMdO1n99iH8/2kdAlA/thkSSPCSS2O7BXpcH0VoRxaqbWL7GJVQH9tHw/BdBqNTeIzTOW+x2unbO59Rv2pCq4OA/4SCRYDQ4ef3pcv6ZbWT8lT60f3A4Sh/vueyrS8wsenUnB5flkTwsEv/bJqEM8p6EpOMiNeeX9VgKKgkakIzulhtQxotLwp7geDKardJ4li09ZYCMD+4Yys0/r+e296+jIErXMnaIiLQClEG+hI/uDKM7E2i1U7krm/L1Rzi47ABbfklH7a+g3eAI2g+PIrFvOAq1mLtyrnjPU7sVs3Kda+lfFKrNi8Qpc1WwPmnZMv3jQCrHux74h/dbeezuUoryHVz6Sg+vqp0qCAJ75+ew5I2dSKQSkp++lJBBHVrarBoEh5PiZfvI/nkdlvwKggYkE3jHVJSxYoKNJ5FoXHVzHUbrWbZ0D20P5fP4B4u4/f3rcChcj4O5E3owd0KPZjm/iMj5glQpJ7BnIoE9ExGEERgOF1C29gj5G/ew++9sFBoZbQdG0H5EFG0HRniV06Q1IH5bTWTNRhPjr3Mt/T/3RaAoVJsRQSkh935/Yt7T41TCzt3RCGopgiAw+xcDb79QTkIbBTf8OpzghOZfUq2P6mIzC17ezuGVBaSMiUE7bSKKAJ+WNgtwdcgqXXWA7B/WYsopI6hfOwJvv0kUqc2E5D/B6LQ5PH6u9gdy+ea+nwH49+J3Abj8h9spjPCeEBkRkdaIRCLBNzkS3+RImDqQ2OxSStcconzDbuY+uhm5WkabAeGkjI6h7cBwFBpRip0N8RtqApu2m7nkujwu6qbm+f+JMaqexn+hgaR7yzgwKwxzmiv7suj+AAw9FBgGusRedZWTV58sZ9FfRq64TkvSfcORq7xj6eW4N3Xx6zuRKaS0f3YiugHJLW0W4LKtfGM6x75bgzGjCF2vJAKmTkGZIGYFtwgeLtLSZecxPn3kt5rXEsCqkFEYfn50LRIR8SY0scHEXNMXrulLVH4FJasOUrluJ3Me2YRCI6PdkEhSx8SQ1D9cjHGtB1GsniM791oYd20unTsqeemrIDQa8QLzJEk3F6Nb5urx3O76YnZvj4L/SiQdF6oH91p5/O5SSosdTHyzF8mjvUdoVZeYWfjyDg6tyCdlbAzaaZNQ+Gta2iwAKndlc+ybVVTty8U/LZbwx+9E1S6hpc26MHG4PKoSD3YQSj6QV0uoAjglEob9/WBNAw0RERHPoI7UETO5N0zuTWRuOaX/HqB4zU5mLNiA2l9Bx1HRpF4cS2zXYCRS8fd4HFGsngMHj1gZc3UuibEKXv0mGB+tKFQ9hbTaQeceecjMJ8YUFQLKdBvWdi7vqiAIzPnVwFvPl5PYVsH1v44gKM57kpT2Lcxh0Wuu2FRv8qYaMos5+vW/VGzKQNs2nNAHbkadmuxVVQguNJwWV6yqTO2Zhgpdt2fxyWN/1BpzSCUMnv8wgvhgFBFpVjTRgcRc2xeu7UtUZjEly/eRvmoX22dmERDlQ+rFsXS+JNarwthaClGsNpJjOTZGT84lOFDGmz8E4+cvClVPETirmsQHy08bLxujrhGqRoNr2X/BXCOXX6eljRct+xvLLSx8dScHFufSYVQ0frdMQqFr+dhUS5GeY9+voXjpHtSROoJvvxafnp3FYv5egNNgAkDu6/4i42m7jp0mVJ0SCYMWPCx6VEVEWhhtYijaaYMRpg6iam8OxUv3svW3/az78iDRaYF0vjSelNHRqC/Qtq+iWG0ExSV2Rl+di0wG7/0cQmCQd4ii85HkiQX4bredNn74m2CqhrsEX/ohG4/eUUJRgYMJr/ek/djY07ZvKQ6tzGf+C9sRHE6SnxxP0JCOLW0S9mozub9vJG/2FuRaFYHXTsR30EUeXXIWaRzOqmoA5G5OuPOtMvHZw7WX/u0yKYPnPyQKVRERL0IileDfORb/zrE47x5B2fojOP7dyKJXd7D0rV20Hx5F2sR4EnqFXlBhAqJYbSBV1U4unpJHpd7JFzNDCQ0XH/AewSHQJTUXmal2golDDbu2RiH4ur73+bMNvPJkOdFxcq77eTghid6xTGKusrH0zV3s+usYbQdFoLvrshavm+q0Oyict4Psn9bhtNjxGzME/9GDkWrEFoHehqNCD4Ay2L3XTGRhJUa1AqnTidrqwC6TiEJVRMTLkSrlhAzuAIM7EFhaTdHSveQv3cre+Tnoon3oMimBtAlx+IV5R/6DJxHFagOwWgUun5bH4Uwbn/8eSmyCZ+LJRECZbUeQ1BaqZReryfo0FACLWeCdF8uZ9bOBiy/3IeWR4V5T9iNrYzHzntuKWW+jzYNjCB3duUXjPwVBoHzDEbK+XIk5r4KwkZ2Qj7wUeaCY8e2t2EsrkKoVyP3Ubj3u4bYRjPzrAdRGK1NmbODrGwaKQlVEpBWhDPYlZnJvhKsuompfLpIVa1j71UFWfbafdoMi6HZlIkl9w85bb6t3POW9GKdTYOr9BazeYOajH0Jon3phxos0F9YEBXtWRdClZwES4OBPwTXZ/rnH7Dx6ZwkZh22MfbYraZcleEUykM3sYOVHe9n8UzpxPUMIefNy1OEtW6vSkF5E1hfLqdxxjIDuCehuufGCq5VatXID+vkr8B83FL8hfVranAZhLy5DHRHgluu616Z03nt6Fr9N6sHHdw4HwOyj5OsbBzX52CIiIi2DRCLBPzUGUq+m+1QLxcv2UbF4I7/ftQ5dtA/drkgkbWI82qDza+VMFKtn4fGXS/h9bjWvfRJMz77u9XaIgKzITsrIQjI/CqJ6kGspwxmq4OjLOsonaRB8XZfo6mUmnn2gDL8ACdd9P5SIjroWtPoEBfsr+PPJLVTkGEi4fSiRk3q26MzWWm4g+7vVFC7ajSYqkND7bkKd1sErRH1zo5+/AkdpBfr5K1qNWJVV5KGMCWryceRWO+8/PQuAq/7cRkZ8CPPHdWnycUVERLwHuVZF5KXdEMZ3JfxAPiz9l1Wf7WfVp/vpOCqaHlcnEZ3W9PuJNyCK1TPwyTcVvPNZBQ89p2PkxS2fxX2+EfirnsTHKwFoc0sJxk5KjvwSiqCWUna9KwbV4RD44j09X3+kZ9AINT2eG47GC7IhnXYn6789zOrP9xPa1p/On9yET3xIy9ljc5D/51ZyflqHRCYlcPJ4fIf0uaCTp/zHDa3xrLYWjEdLCB+T1qRjKC02Vox/r+a1zCkwZeZmUayKiJynSCQS/DpGQcdr6H6jiaKFu8hZsJk9/2QTmRpIrylt6DgqulU3HBDFaj38vbia+58pZso0X6692TuSd84bnAIdxhTgc9BeMySzgDrTjqA64QEsL3Pw1H2lbF5rYch9KfSdmuwV8TjlOQb+fmoLubvKiLqqD7HX90eqaDlRWL45g8zPlmHOq8B3cB8CJo5E5qttMXu8Bb8hfVqNRxXAUW3AVmbAJ+HcJz2nCtXjTP38piZYJiIi0lpQ+GuIvqo3UZf3onxTBpYFa/jryS0se3c3Pa5KotuVia0yREAUq3WwbZeZa+8oYMIYLfc/rWtpc84r5Lk2Ovcv4JQcKuy+EnZvjqxJ+ti3y8ojd5RgNglM/rw/ib3DWsDa2giCwK4/j7HkjV34BCpJfedaV+xQC2HOKyfz8+WUb0jHv0ssultvRBlzYcWlnk/YjuUD4JPUiGtdEOi2K5vtabHIbY46herFv92JVSne6kVELiQkMilBfdtC37YEHC0hf85W1n2zh3VfH6TTJXFcdH1br6mi0xDEO9gp5OTZmHBjHqntlTz0rg6pF3jyzgsEgcjXK4j8vPq0t0ov0XD0kxPepDm/VvPGs+UkpygZ+sZQ/CNaPgTDWGFhwYs7OLgsj7RL49DcPAmZT8vMTh1mG7m/byD3j00odD6E3DEFTc+WrTwg0nSsR3OQqhVoGhGz2mdzJu88PZPHnp3AGy/+edr7E3+8nYqg1vNAEhERcT8+8SG0uX80cTcPovCfHRz+exM7ZmXRbnAEvW9qR2y3YK9/fohi9SQMRicTb8xHJpXw8pfBaDStN77D20jrnIu8qrY7VQAOzA3F1M2VuGYxC7z5XDlzfzO4ulFNH45c2fIxl5kbivj76a3YLQ7aPzMB34HtW8QOQRAoW3eErM+XYS0z4DdqMP4XD0WqavkYXpGmIyvMwLddeKNCXYasPgjAy6/8ddp7Y2fcg97NzQVERERaLwp/DTHX9CXq8l6UrNxP+Zw1/DR1NdFpgfSZmkzykEivCLWrC1Gs/ofTKXDTfYUcyrDy1awwQsJaXiSdT9gDJLXEqjVcyp71USBz/TDyc+08dmcphw9YueTF7rSfEN9SptZgtzpY+eE+Nv14hIQ+oQTfdwWqkJbxUpnzysn4ZBkVmzPQ9UoiaPrtKMJbLqGrKQh2O7aCEuz5RdiKSrAXl+Eor8RRWY3TYMBpsiDY7CAISGRSJEoFUq0PMp0/8rBglDGRKJPiUMZHIZGdP7/Tqv15hAw9c6cziVNg0rzt+FZbABj2n1i1SSXIHQLHHzPjf75TFKoiIiJ1IlXKCRvVmdARnQjZnEH17JXMemAjIUl+9L05mZQxMV6XjCWK1f946d0yZv9TzTtfhpCcInqq3M2+ZeF0a++Kycv4LJDKcSc69GxeZ+bxu0tRayRM+W4IkSmBLWVmDSUZev58fAslGVXE3zaEyMt6tciM02m1k/v7RnJ+24AiUEvI3Teg6Zbi9Us2xxEEAXtBMZYjWVgysrFm5WDLLQSHAwCpjwZZaBDyIB3a8ARkPlqkKhUSuQIkUnA6cNqsOIwG7PpKzEdzMazfDnY7Eh8NPl07ou3fE1X7pFbzndSFvawCa0mVK6P3DGjMVm75fg0BVWYE4FMJvAU8Yndy13/b6LVKzNoL6x7mtDmwVRqxV5qwV5txGCw4jFYcFhuC1YHT7kBwOF0bSyRIpBKkChlSpRypRoFMo0Tup0bup0Hhr0Hur/FaD5OIiLuQSCUE9W5DUO826PbmYp69lL+f3srqz/bT9+ZkOl8a5xWrmwASQRCEs2/WutDr9QQEBFB+KAl/v7N/0bP/qebKW/K56+EApt0rdvdpKtJyOymjCzF2VJLxfWjNuO9KA9X9NfDfjE0QBH7+qpoPX6ugZ18VfV8ejk9gy2YpCoLA9hlZLH1nNwGRGmIevRxtm/AWsaViaxYZHy3GUqTHb9Qg/C8Z3iqW/O3FZZj2HsKy/wjmgxk4qwwgkaCIDscnNA5VRDSq8CiUoeHItY1vKyrY7ZjzsjEcOUDlwe3YC0tQxkcTcPkYNKnJHvhEnsewaSelX/xCz9/vRhl45koO4UV6XnhpLp0OFpAIHAXigUxgd0o0zz05nqKw8+s+5jBaMOWWY86rwJxXgaWwEkuRHmtJFdbSauxV5rp3lLi8SBK5DIlMChLAKSA4nDhtDgSbo+79pBKUgVqUIb4oQ/1RhfmjjghAFalD/d+/lqwAIiLiKQzpRVjmLOHAklz8wjT0vTmZrpPikas8c71bqm28038elZWV+PvXf9+64MXq3oMW+o7LZuxwLY9/pGvV3hlvIGCegTZ3lwGumNTthyJBdboD32Ry8tKj5Sz6y0ifm9ox5N4UpPKWXXYwVliY//x2Dq3Ip9uViSivn4hM3fytda1l1WR9sYKSFfvxT4tFe+WVKKJaRjA3BMHhwHI4C9PO/Zh27sdeWAJSKcrEGHyjkvGJb4MmNh6pyv1NNQRBwJhxiOL1i7AcycKnb3eCpkxEqmldpVnKfp6L/cB+un9321m3VVjtrLzkXQA+B14HHgduVCsYPfs+HK24tq7TaseYVYwhvRhjVjHGrBJM2aVYS04kZsp8VajDA1CF+WPVhCHT+SML8EXm54vUT4vUR4PUR4NErUKikJ/xni44nQg2O06jGcFkwmEw4qwy4NBX46jQ4yivRG4swVJUiaVQf0LcSiWowgPQxAShiXX984kLRhMXjEIMvxA5DzAeK8U2ezH7FmbjG6Km77T2dL0s3u2eVlGsNkCsVlQ66D02G41awqezQvHReleMRmtCYnKSfEUR2j22WuOGjnIOLqxdTin3mJ2Hby/hWKadMS/0JGV0y5V/Os7RzcX89eQW7BYHcfdfQnD/ds1ug+AUKJy/k6Nf/4tELsX/8vFo+3X3ygmUYLdj3p+OccsuTDv24aw2Igvww7dNKtp2HfBJTEambr6Ob4IgoN+5hcKFs5EH6Qh9cBrywJZtedsYSl55G992EbR9aOxZt1186btozfY637vjvWvZ3YLl1BqD0+7AmFlM9YF8qg8VUH2oAOPREnAKIAF1VCA+8SHYA2NQRIQhjwhFHhaMzLdlxKDgdOKo0GMvKsVeWIKtoBh5ZR6m7FLMBZUuuwF5gAafWJdwrfkXE4QqzF8MLRBpdZhyyrDNWsTeBdn4hWnof2t70ibEuy2m9bwRq6+//jpPPPEE06dP5/3332/QPg0Rq06nwMSb8lm7ycR3f4cTGy+G754rmi0mOlxewqm3YbsWdm+JRvA5cVFvXGPmibtL8QuQMuadQYS1a1lB4bQ7Wf35AdZ+dZC4HiGEPnAlqtDmT6IyZpWQ/v4iqvblEja6M4pxk7yusL/gdGI5chTjhu0Yt+zGaTAiDw/Bv10avh06o46KRSJt2QmfpbiQ7F+/QKKQE/7Encj8Gh9m0Nw4qo3kTn+Btg+PI2xUpzNuO++KDwnU117yvunj67n5l/UMWneEn666iM9uGeJBa88du8FC1d5c9HtzqNqbS/XBfJwWOxKZFJ/EEIhKQBkfjTIuCkV0RKsIeTmOYLNjK/wvaTC/CFteIZQWYM4pw2l1TSykSjnq6EDU0YFoogNRRwWijnKFFCiDfV1hCiIiXorxWCmWGQvZvzgXXbSWQXd2IGVsLFJZ0yZgDRWrXq3QNm/ezBdffEFaWtPaD9bF6x+WM3+pgfe/CRGFahOIebqMsB8Np42XXqLm6Ccn4lUFQeCnL6v48LVKeg9U0+el4WgCWvZhVJln5M8nNpO7u5y4GwcSPbl3sz8wnFY7Ob+sJ/ePjagjdIQ9ejvq9knNasPZsBeXUr12K4b123CUlCML0qHr1ge/1G6oIqK8yvOrCg0n7rq7OfrdB5R8/gthD93S4gL6bFgOZwLgnxZ7xu3mXf4hgafEZr56/2gOJ0fyxHOTGLliPwXh3hOr6jBZ0e/OoXLHUSp3ZWM4UghOAUWgFr/UaPwvHYWqTTyK+GikyuYPt3EnEoUcZUwEypiIWuOC04mjtAJbQRG2gmLsBSU4KvMpXrEfa7HeFSsFSBQyVKF+qMIDUEUEoA4PQBnm7xoL9UMZ4odUbOwg0oL4xAXj89AUulxWjOm3hfz11FbWf3uYIfem0HZwhMefA1579VdXVzNlyhS+/PJLXn75Zbcee9lqI8++Wcot9/kzYJjGrce+YBAEUvvlo8qrnaDglMPuzVE4gk54tM1mJy8/Vs6Cua741MH3pTZ5NtZUDizN5Z/nt6P2U9DpnWvxS4ludhsqd2WT/v5CLAWV+I0dSsDFw5AovOMnKdjsGLftoXrVJiwH0pGoVfh37Ir/JT3RxCU2WABWbF5H6ZplBA8Yjq5XPw9b7UIZFEzUxOvJ+eEzqlduxG9Y32Y577liOZiB8r8EnvpYOPF9/IzWWmNv3z2cf8Z1cb2QSFgyLMWTZp4VweGk+kghFVsyqdyaRdX+PASHE2WwL/5d4lD17Y8qORF5eIhXTXA8iUQqRR4ahDw0CE3nDjXjAbh+Y/aSMuzF//0rKUNmLMRwpJCytYex6021jqXQ+aAM8UMZ6ocy2NclYoNPeh3i22KNSkQuHLSJoWifuB7VxDwqf1zIjOkbiOkWzLAHUonpEuyx83rHk7EO7r77bi6++GJGjBhxVrFqsViwWCw1r/V6fb3b5hXYmXJnAcMH+nDrdO/xQrQ2gn6tPk2oVneSc+if2vGpBXl2Hrq1hMwjdia+0YuUMS0bT2czO1j69m62z8ikw6ho/O+4HLlv88VWgms59OiXKymcvxO/lGgCb5/qNQlU9uIyqlZuwLBmC85qA6p2iURMvAa/lC5IlY33hJeuWYa9spzSNcvqFaueELTapHZoB/Sk8s/FaPt1R6r23oe4M/MwAWfwqs674qPThOqb947kz/HdPG3aWbHpTVRsyaR8YzoV27KwV5qQ+SgJ6BKH7urxqFPaXVDitDFIFHIUkWEoImu31z0euOK0WF31h8sqsJdV4CirxF5eiWAuoWpfLqXFVadVQZD5KFGG+qH6T9SqQv1RhvihCvNHFeaHMtS/RZJGRc4//DpG4fvKVLRbMin9YQk/3LCK9iOiGDo9laA494dfeaVY/e2339i2bRubN29u0PavvfYaL7zwwlm3s9sFptxZgEIBj72nQ9bC3r1WyX8hzmWXa6kYryVleD7KQidZLwVQdkNt8b99k4VH7yxBpZZw3fdDCO+ga357T6IkQ8+cRzdTfqyapPtGEXhxl2Z/iJatP0LGh4txmKwETpmI75DeLb5MLQgC5r2HqVq+DvOuA0g0anRpvQjo0RdVaNNEdPCA4TVCtD4aImjPhfCeY8lYtw3Duq34DWser25jcRpNGDKKiKhHeCZkFaPTmxCgJib8hUfGsnhk52az8VRMOWWUrTtM+YZ09PtywSmgbROGz4A+qDu1R5UUh6QVVyTwFqQqJdKIUBQRofVu47TaXIL2v8oFjnKXoJWaizFmFlO+KQNbuaEm3ABAHuCDKtzfVVEhIgB1ZACqCJ3rv+EBSMW/nUgDkUgkBPZKQtfjNvyX7SXvhxX8b9JSelydxIDbOrg11M/rEqyys7Pp2bMnS5YsqYlVHTJkCF27dq03waouz2psbOxpCVbPvVnKqx+U8cVvoXTv3bzetNaO8rCF5KtKMFykJPOLEzdPRaYFZ5ACR0BtwTXr52reeLacrj1VDHhtONqglvNsCYLArj+Psfi1nfhH+RDz2BVoE+t/AHgCW4WRzE+XUrLyALqLkvC5cjLyIF2z2nAqTqsN4/pt6JeswZ5fhCI2kqBuA/Hv1P2cvKjnSmM9q43Z/tjcr3BU6ol4+l53metWTLsOUPzBt3T79hY00UH1bqc2Wpl93Wd8Om0w8y7u2nwG4vr9VB8qoGzNIcrWHcaUXYZUJSegWzyS5C6o0zoiDxRXqbwVwW53idjS/zy0peXYS8qRVxdhLtRjLdKfaJgglaAK83clgEUHookOQv1faS5VqFjNQOTMOCw28mdvoeD39UjlEgbe2ZHuVyaesXJAq60GMHfuXCZNmoTspDaKDocDiUSCVCrFYrHUeq8u6qoGsGKtkZFX5nLHg/7ccl/rKWnjDYS/X0n0e67QCgGo7qnkyM9hCOrTb1w2m8A7L1Qw48dqrrzel6Tpw1u0bZvVaGfhKzvYMy+bLhPjUU+dhEzTfEJMEARKVx4g49OlIEDAVZfi06dbiy6LOqqqqVq+nurl63EajGi6pRCSNhhNfJtWsVyb/t5L2CvLkQcE0uaBZ864beXOLRTM+YXod59GFtAyrXLPRMWshZjWb6Lnb3fV+u477s2hyk9NTtx/LXWdx8VE8/yWBKdA1f48SlcdoHTNIazFVcj9Nag6p6Dploo6pV2rytYXqR/B4XCFGBSXYS8uxVZUikKfhym3DHNeRU1tWalK7qorGxeMT0IIPvEh+CSGogoPEEWsSC2s5Qbsv89jx5yjBCf6MerRNBL7htW5bautBjB8+HB2795da2zq1Kl06NCBxx577KxCtS5KSh3ccE8BQ/ppmHq36AFoKPIiOx3GF6IscNaMSQCpyVmnUC0vc/DYnaXs3Gph7LNdaXd5YjNaezpFhyqZ/cgmqgpNtHvsYrTDU5v1/NbSajI+WkLZusMED2qPetJVyPxbrpSSvaQM/aJVGNZsASCga28C+wxCGRTSYjadCw0JLTiOT2JbACxHjuLT48xloVqE3CP4pdSuqHDvp0uZPHcbq/u0waaQ8fuknuzt5PlYb0EQqN6fR8m/ByhdfRBrSTWKIC2qLmnoenRClZyI5BzuvyLejUQmq0kCg7Y1474cr2ZQjq2gGFt+Mba8QiyFeZRvzsBR7VrNlKoV+CSEoE0KQ9vG9c8nMbRZnQIi3oUyUIvyjsl0GVlI2Vfz+PWOtSQPjWTEw53RxZxbSUavE6t+fn506lT7oaLVagkODj5tvCEIgsBtDxditgg8+q4Yp9pQdDOrSXqo/LRxc6KMg/MiThs/fMDKg9NKMJkErv7fQOK6t5wAEgSBHbOzWPLGLoLifen08U1oYj2XpVjX+UuW7SPzs2VIZFJC7rwOn54tE2NYtXIDlX8tRRakw3Y0F6mPhqB+wwi8aAAyH++q49pQdL36NTi2VeGvQ+qnxZZbAF4mVgWnk+pDBcROOfFZHnx/EZfP3wnAoA3pAGzqkegxserqAFZMycr9lKzcj6VQ7xKoXbug65WGqm18i8dUi7QcrmoGwchDg2tVM9AJAo4KPbbcAmw5BViz86nan0PRot2ukAKpBE1MEL7JEWjbheObHIm2bRgylZjcdSGhbROOz6s3o/n3APlfLeF/ly2l783t6Tu1XaPbt3qdWHU3X/2s58+FBt7+XzBhEef9x206gkC7y4vw21o7+1gA8qb7U/jg6SEUKxYZeeb+MmIT5Ez6chgBUS3XbtBisLHw5R3snZ9DtysSUN44qVlvkNbSatI/XEz5+iOEDO2IauKVLVbc35qdT8Xv8xCsNpz6asJGTyCge2+kSu/NjPcE8tAg7CWnT7xaGnthCU6TDW071+Tv5h9W1wjV42TEBTPveHkqN2LOr6BkxX6Kl+/DdKwUub8Gdbc0Am7o4vKgelCgSp1OEguKkZ4UgZYVHoJNLt6fWwsSiQR5YADywAA0ndrXjAs2O7a8QqzHcrFm5WLKPkrJvwdcoQRSCdqkUHw7ROHXIQq/lCjU0YGtIvRI5NyRSCSEDOlIYO825PyynrVfbmLPvGOMfqILSf0bnsDbKu4OK1euPKf90rNsPPhsMdOu9WfoaLFfc0Po3C0XRXntMGabv4TdO6LhFK+0IAh8+0kVn7xVyfCxGro9OwKlT8tdUkWHK5n98Caqi8wkPzEezdCOzXZuQRAoWbmfzI+Xurypd1+PT/eW8eRZs/Op/Gsppm17kGh9kMoUBA8ZTWDvgY06TlNKSrVEfdX6kPr54qw+vXFFS2PLKQBcdQsTMouZ9tP6Wu8faBvOtE9vdN/59CZKVx2geNk+qvbmIlUrCOrbFt+J41GnJnssgz8xr4iH5i5m4P7D+BnNSOG0bncjXnyAw9Gnr9i0GgSBPgcz2NA+CS5g8SVRyF1dyOKj4b/bTaDdgS23AEtmNtaMY+h3ZVE4bwfgak3rnxLtahLRORZtu3CxGsF5ikyjJH7aYEJHdqL8iz/57a51dBwVzaC7G/acbhVi9Vy587EiIsPl3PS09yVWeCsVw9WEzjxRjLr0Yg1HPz19Sd9sdvLiI+Us+svIgDs6cNHtHVo0yH7n3KMsenUHQfG+pH58E5qY+jOr3Y2twkj6h4spW3OI4MEdXLGpfs3vTbXlFVIxdwmmrbuRhwYRMeFqnDYrZWtXIJU2/gHQlJJSnipHdS4o7CqszuoWtaEubIUlyP3UxBss/Hz7t7Xeyw/zd4tQdVrtlG/KoHjZXso3piM4BXQ9Egm+9Wo03VI9miR1/5xFTJ+3nAshiGDInoN8//633HD/zfzbuf3Zd7iAkMhlJwTskD6Aq2SbJf0YliNZOHKOkP3jOpwWG1KVAr+UKPzTYgnoGodvciRShShezyd84oLRvDwV5fJ9HP3fEmY9WH9d/JM5r8Xqlh0Wvp4Zho/2QrhdnhsSsxNBJanxBmS/E0LI7GwECRz6OQRj39M7fBUXOnjo1hKOHLQx6a2L6Diq+bs/HcdmsrPo1Z3s+usYXS+LRzX1smZd9i9de5j09xeBIBByxxR8erm/NfDZqPh7KVXzVyJYbciCAwm/9CoCuvRCIpPVZM6fi2hsTCKTO/f1BN7o7HKUVdDVX8OMqV/WGndKYPJ3t57zcQVBoPpAPkVL9lD67wHsVWa0bcMJuGIc2ou6eqQqgsps4ZYla/hq9CAs/7VOrfDV1itUT167cUgkVGtOlBKUORz89uYXPHPNeA4knLkFrbcwbosrKXjc1t2iWG0AUh8Nms7t0XRuD4zG3+7AeiwXy6FMJMcOkDdjE9nfr0GqUuDfOYaA7vHouiXgkxgqVh44D5BIJIQOT0XXKwnj0RJKHvr1rPuc12L16pt96dLzworPawyBv1WR+FgFFcNVZHxzoqzEzm2ROAPrvjT277bywLQSJBKY8t0QIjrqmsna0ynNqmL2Q5uoyDHQ9pFx+IxsvmV3u8FC5idLKV66l8C+bfG58upmL43kqNBT+fcyqlduAECq9qHNnU8gOSn2rymisTGJTO7c193YZGYkUu/LTHYaTazPrR1LKwCD5z+MU9b4CbY5v4LiZXspXrYPc245yhA/fAb0wadvN5QeWmK/dvl6bl/0L/El5UiAGQN7UfSfWC3Wnfg9OIFyXx8Wd+3Igp5prOvQBpui9qTS12RmywMvoXA4kDkF/nr1U5L/95pH7G4qEqeT61duwN/o6iBVI1a37CY7xLWqo/dR8+OQPghigtpZkchlqJLiUCXFAYPxdTqxHs3Fsj8dsvaT/f0ajv5vJQqdDwHdEwjsmUhAjwSUga0zSVTEhcJfgzap7pJWp3Jei9Wb7xLLVNWJ1Unn3vkoylwlqQKWWeg4PI8D8yMRVJJ6heqSf4w892AZbTsoGP72cHxDW66xwv7Fufzz3DZ8w9SkfHBDsxb5r9x+lMNvz8dhsBA09Uq0/Xs0a5KA02hCv3AVVUtWI5HL0XbojCUvm+CBI2oJVfAu0dhSOKuNKCKbtwlEg5BIeCEigK49Exm66iB+BgvD5j3YKKFaVxxq8IBk/K++AlWHJI8kSumqqrn372XcuGIDCqez3u32xEbxzqUj+GVwH0p0Z5/IVWvUqGz2Gm+syuGk18EMNrdPcpPl7sPHYuPBuYsJNJhwAp9JJLwFPGK28NCcRUiBcq2GWX17YNCIDpPGIpFKUSXGokqMBYbgZ7NjOZKFee9hTIf3UbJ8HwC+7SPQ9UoiqE8btG0jRK/recx5LVaVKvHCPRXNTgsdLi2qleAgAWyhMlc4QB0IgsCXH+r54l09oy/1Ie2pESjULRNH5LA5Wf7eHjb/nE7H0dH433kFMp/meRg4LDaOfbOK/Dlb8e8Sh++11yIPCWyWc4OrE031yo1U/r0UwWoj8KKBBPUfjkxzeqiGyAkcFZWoO7ZpaTNqoTabkQX48bZUQvf7RjF/ZCoHOkQ1KF7BbrBQvv4IxSv3U7k1C0EQ0HVP8HgcatvsAn5590vC9NWnJUiByyusMZlB53ISHI0I5cMJIxt1jlvvuYGvP/6h5nW39KNeKVYNGhXjnpvOR1/8So/0o7wlCBwF3hIE7gK2tInnnjuuFYWqm5Ao5Kg7tkXdsS0wFl1lFaY9h5Ck7yR/zlZyflqHIkhLYO82BPVtS0C3eLFM1nnGeS1WRU5CEOg4sgD1YftpD5q8u30peLRu0XVyItWguzrS/bb2LVZqRF9oYs4jm8jfW07i3SPQXdp8naCqjxRy+I15mPMq0E2+BL8R/Zut/qQgCJi27qFi1gLsxWVoB/QkvNdYFP66Zjl/a8Zps+Eo1yMPab6EuzMhcTrZde/zzO7bnUc6tKFqyRoMGUUc6HjmuG9raTXlmzIoW3eYim1ZCDYHfinR6CaPx6dXmkebTXTOzObPVz5BVkezQwGwyOVsaRPPtPtuwKxu2mrL0m6pCJxeLcAbyQsO5OpHb2PnvS/wuNXK68DjgFGlZPKjt2MXs9o9hizAD9/+PaB/D3ymOLAcOYppxz70u/ZQtGAXUrUCXc9EggckE9i7DXKtOGlo7Yhi9QJAVmInrVc+klNW7JxS2L0hAkd43TPQkiIHD91WwuH9Nia9fREdR7ZcIlXmxiL+fGwzMqWM1Hem4NcxqlnOKzic5M7cTPb3q/GJDyH8mfs8Fv9XF5bMbCp+n4flcBbqzu2JufxmVOGRzXb+1o61tBgEAbmXhAFsfvBl/M0WblyxnhtXrKdIKiHhxbkkTR+Nf+cYpHIZTrsDS2ElhvQiqvblUbnjGMaMIpBK8E+JJuCysfj07Iw8SNcsNldoNbVqooJLpFZoNdx613Vs7tC27h3PkdYiVgG6ZGajtVq5A7jj+KDFStfMbLa0S2g5wy4gJDIZ6vZJqNsnIQgXY88vwrh9H9a9Ozj8+jwkCplr5WFge4L6txOFaytFFKvnObJSO2k985Gc4hQpHa/m6Ech9S47Htpn5f5pJTjsAtd+M5jI1OZb7j4ZwSmw/ttD/PvxPhIuCiPkoatQBDRPzVxzYSVH3vwH/Z4c/McMIWDiyNNiQj2FvbySytkLMazbhiImgpjrbkfbVswybiyWglwAlDEtL/D/fPFDQqtc9V6P/+oum34zsr/nse+x30EqQaqU47TYatLlVeH+yNu0JXjYUNSd2nu8JNpVqzby/K9/s7BbKg/edg0A2WEh7EiIoVtWDg6JhO+H9uWFay/1SIkFqdPZqkpdjdixH4CF3VJ55aqLefr3eYzesY8RO/aJYrUFkEgkKKLCCYgKh4uH4l9WgXHrHuy7t3Hk7flIPpCh65lIyJAOBPVpK7aEbUWIYvU8R6YXKJmsIfQ3V+1UAdj/VyjmLvUv161aZuLJe0qJT5Iz4t3h+Ie3TEykWW/l72e2cnhlATHX9iXi+v5IziFL+lwoXrGPjA+XINOqCHvkdtTNFDcn2GzoF61G/89yJEol4ZdcQUD3Pl7V8tKbCv6fDXPOUeSRoUg1LZcMCDD75Y/pejS31tjDN11OTqdkglIfwDczB1t2Hk6LFalahTwkEEV0RLNVmLh6xQZe/PUvVA4HAP0PpNd6/5Z7b0TmcFAY7NlJ6+vfzaz12qz07rjDpV1T2B8byZ+9u4JEwm333MCEjTvIber3JDYZcAvyIB3+IwfAyAH4lVVg3Lob246tHH5tnqspRr92hA5PQdc9odmeLSLnhihWz0NUByxYkuSglGFNVJD9RgjBs7JxqmDXjmhQ1P2jFASBn7+q5v1XKhgySkOP51uuI1XR4UpmPbgRU7mVDi9eRlAf9y411ofdYCHz4yUUL9tHyNCOqC+bjNTH82JdEARM2/dR/vs8HOUVBF40kOBBo7wyecqbCv6fDUNBBqo28S1qwztf/kaPzOxaY3/068GMgRcBLm+QKikWVVLz1xSdsnwtz/32T41IPU5YZRVh5XqKAl3JUiW65qms0j63oNbrP/t0a5bznitb2iXU9qBKJG6xWWwy4H5cwnUgjByIf3Epho07MWzdQsnyfSgCtYQM60jYyE4NLqUk0ryIYvV8wimQMiAfVa6D6t5KDv9xou/ujv31i1QAm03gzWfLmf2LgT43taPP9NQWKwOyd34281/YTmCclsSPbkId1TwhCFX7cjn0+jzsehPBt0zGp2/3ZjmvraCY8l/+xLz3MOpOycROvhVVaMN7JnuSuryo3lbwvz7s1VXYcgrwHzO4xWwYu2knV2zYXmvsj37deWTaVS1kkYsbl6zhqRnzTxOpAmBUKrj9rutqhGpzYlIqcQJSoEqlpNL3wqyjKTYZ8Czy0GACLhmGcPFQbEdzqV63jeKl28iftQVt23DCxnQmdGgKcr+WXZEROYEoVs8TVIcspIw8UZLKd6MVbA443qruDEK1qtLJY3eVsGWDhYuf70aXSQket7cuTi5L1eniWLS3X4FM7fllQMHhJOe3DWT/uBa/DpEE33878tBgj5/XabGin7cM/aLVyAIDiL76ZrTtU1us2kJd1OVFbS21Ww3pBwFQp7RrGQMEgc+/+KXW0KqUtjwybXLL2AO88NMcblix4bS4UJdIVXLfrVeztHtqS5gGwGM3XkaHnAL+99nPmLw8BMCdiE0GWgaJRIIyIYaghBiEq8Zh2n0Qx9Z1ZH66jKP/W0nwwGTCx3XBr1OMV92XL0REsdraEQTaXlWE/yZrrWEJoDpix9LxzOVTco7ZuX9qMaXFTq7+fADxvVoma7q61MychzeRu6uMxLuG4zehe7PcHCzFVRx+Y54rieriYQSMH45E5tmSM1Ur1lP55xIEhwPBaid44AiC+g9Fqmj+YP+zxZ+2Fi9qXehz9qCMj272zmLHkQgCT1w3kdd+mgu4PJbXP3hLi9hyHJNSVUuoCoBBpeTeW69mebeWE6nHORoRxtGIMDa1WcMHlw5raXOaDbHJQMsjkcvx6ZYK3VLxubKK6rVbqFq/geJl+9DEBRNxcVdCR6Yi9xW9rS2BRBDqKJ7XytHr9QQEBPDvnmh8/c7fWai8wEbnfgVIaq/kIQB7VoZjSzyz+Nm5xcKDt5bg6yfl4g+HEJzQMg/13F1lzHpwI4IgkPjk5fh3immW85auPUz6uwuQqhTobr62WZKo7MVl5D3zDtjsoJCTeOdjKIM878WtT5Smv/cS9spy5AGBtHngGY/b0Vw4bTaOvPMs/mMGETB+RIvasu6hVyj303Lxc9ObNVkmPr+Ix2ct4K67rq/xxiltdvbf9TQyp0C1Ssndd0zh37QOzWbTmVCbLSjtdvQX6NJ/VGl5TZOBROAoEA9kAlv/azKQ30zlykRcCE4nlgMZODatomzdYSRyGaHDU4iY0L1Zuyaez9gNFjZN+oDKykr8/esPPRI9q62UuIdKCZlpPG28YoCSjB/CQHbmh+Kiv4w8/3ApqV1UDH5zOD6BLTNb3z4rk0Wv7iQyNZDIxyejDPa8YHZa7WT9bwUFf20nqF87NJOvRebr2XJYgt3uyvKftwyJQo5UoSJ46JhmEapQf1KUt3lO3VVpwHDkAILZgk+Pzm607uyoLRYemrOYV6+6uEYg9nvnqWa1ISmngF/e/YqIyiokwDUrN/HLsD4AWBVyrr9/GjkhOo6Fe8/DNra4lFWPv4leo6bLxy+0tDktgthkwPuQSKWoU9pCSlvUE/VUr9pE+Zr1FM7fiX+XWCIn9iSoTxuxkkAzIIrVVkjQH9UE1yFU988JxdT9zEsUgiDwzcdVfPp2JeMm+dDpyRHIlc1/E7RbHSx+fRc7ZmXR7cpEVDddhlTheTuMx0o59OpfmLLLCJwyEe3QPh4PN7AcyaLs+9nYCooJ7D2IkCGjkaqad3JQnyj1tvhTd1UaqMjYiiImEkVU8yWqqSxWDtz1LADXr9yAWalgwBuPU91MZbPaZRfwcx3tUJ+c8U+NWAVYl9pCMbxn4KYla5ECOpOZV76fxVM3Xt7SJrUIYpMB70Wm8yfg0hH4jxuKceturGv+5eALc1BF6oia1IOw0Z3Fuq0eRBSrrZDKoRoqhhkJXG4BwNhGxsEFEQiqM8/ubFaBV54s4+8ZRgbe2YEut3dokaDx6mIzsx7aSMG+Cto8OAbNmLRmOW/R4j1kfLQEVZgf4U/dgzLWs12wnEYTFbMWUr1yA8rEGOJvfQB15IkuYM1Zr9TbRGl9uMPT6zAZMW7fh27SKDdadna2T3+xRiRqbHbUNjvVas9PSpKP5fPze18ReopIBXBIJHw3wvv/7jcvW1vz/1NWbbpgxarYZMD7kchlaHt3Rdu7Kz4Z2TjWLiXz8+Vk/7iWiEu6ETGxO8rACzOUxZOIYrUVIKlyEPdkuavjFOAIlZH5dQh+nfI4+pqOygln7wuur3Ty6B0l7Nhi4dJXetDpkjhPm10nOTtLmf3QJgBS3r62WdqmOkxWMj5aQvHSvYSO6oRq4mSkKs/OgI3b9lL+81ycJjNhYyeh69X/tML+3lCv9FTBfPy1JjYBU3ZWsxf+b4ioPpvI1+/eDk4n2mas0bll+gtobbZaY13ff9ajMarJx/L45d2vCKky1ClSfxrcm2evm+j1ReUjSsprJX1VNYPA91Y81mRAxCOokmIhaSpR48qpWrKGvLkbyZ25ibDRnYm+8iLUkbqWNvG8QRSrXk7wd1XEPVeBBLCFl5P39H83LamUXfsaloiUe8zO9P8y/id/PpC4HiGeM/gM7Jid9V98qo6Ix69GGXR2kd1UDJnFHHrpTywlVQRPm4ymn2drpzoqqyj7eS6mrXtQd+lI1LArUATU/aDxVLxoYzy2pauXYNdXUrJiARKZjOJl/+A0m6iqLAegZOVCfFPSkGs997dqrIf5TCJfEATKd69Dk9YBWTMVsv/n2fcIra4dljN92lVUeLg16oy3vkD3X6mj43i6Haon+PH9b2q9vu2eG1rIkpbHU00GRDyLPDiQwKvHEzB+OFXL11O6YjWF83cSOiyFmGv6oIltntyE8xlRrHorDicpQwtQHz2R6h/+ZfUJsdpA9uyw8MC0Eny0Uq75YViLZPw7bE6WvrWbrb9n0PXyBNQ3X+7x+FRBEChauIvMT5ahjgkk/JnpKCI8l1AiCAKGdduo+O1vkEmJvOJ6/FK7njHMoqFL8/V5P+sTd/WJObu+ElN2JqacY1jyc7AU5eMwunrVO4wGCv76HU7x/joM1aS/9SyKwGB8k1Pw73YR6oho3MnZPMynft4ziXxTdha27Hx0l491q4318fCs+XQ6pevS09deytx+Pdx+LpnDgeOksmpfjB7EY3MWA/8t9w/rx4vXjG81IhVAazKTnF9Ua2xjM7U2FhFxN1KtDwHjh+M3aiDVqzZRuXQFxcv2EjKkIzFT+uETJ4rWc0UUq16I33IjbaeWnra052ykc2v5QiNPTy+jfYqCoe+MQBvU/MtrhjILcx7ZRM6OUpLuG4XPJV09fk6HyUrGh4spXraP8LFpKC69CqkHC4zbS8sp+2E25j2H8OnTjahBlyHzcZ9X7VQxdzZxd1zMBfYdTPXBvRiOHMCQcQhbaTEA8oBA1FGxhLcfgDogDJVfMEqfAORqLRLpCTHksFmwGsoxleVTVZhB2d4dlG9cjTY5lfCxk1AEBrnl853Nw1y8fD5Ok5Hi5fNrBH59Ir9097/Iw0NQN0MS0eSVG7h3/r+1xj4eN4Qfh/d363nS0o/y/QffobLa6PzJCzWC9YuxQ7hm1SYWdu/EK5MvaVUi9TjffvBtrdf/dEvFKRa9F2nlSFVK/EcOwG9IH6rXbEa/aBk7bv2akCEdib2hP5po99w7LyREsepNOAQ6Ds9Hk3l6C8SySRqOvt+w5XtBEPj1m2refamC4eM0dHt2JAp182f8Fx6sZOb9G7CZHaS8cTX+nT3f+9yYVcLBl//EUqQn+NarUXlwCU0QBAyrNlH+xz9INSqir70F3+QUt5/nVDF3JnHnMJuQKBSoI6IoWToPwW5HERiMLiwZv85j8Q1PROnTsOVxmUKFRheBRhdBUFI34pwTKcvcQfaO+WR9/jZRV96Atm3Ta3Se1cMsnPLferBVlGPcuofAqy85LT7YE1y5bis2qRSF0wlAZmgwb7nRo9v1SBbffvAdgUZTzcT1lkWr+GLcUAAcMhkD33zCbedrCXofzqr1+u67rmsZQ0REPIBEIcdvaF98B/RyidaFS9k+7WvCRnUi9rr+qMKav6Vxa0UUq16C6qCVlFGFp3tTZbBnVTj2mIYlBDkcAu+8WMHv31XT56Z29JqeikTa/B6X/Utymff0VoIT/Wj75tXN8qMsWrqXjA8Wo4oIIPzp+1BEhnnsXPaScsq+n4l53xG0A3sR2X8iMrXGI+c6Vcyd+tppt2M4tA/9rq0YDu9DcDhQxyYQ3XUMurhU1AHu+R4kUhnBbXoQEJvC4U2/kPvr18Rcfzs+CW2bfOwzhTaEDh/XoNje8g2rkKhVaPv3bLI9DeG6B6dx6cadvPXDbMq1Goa8/qhbjtv9UCbffPQdOqP5tPvB6G17a8Rqa+fGJWtqvd6WEC22EhU5LzkhWntStWIDZQuXU7xsH5ETuhN9dR8U/p55dpxPiGLVSwj94fSyM8VXach+M7jBy3smk5On7itj9VITY57qSverEt1v6FkQnAKrPz/Ami8O0HF0NP53X4VM7dke306rncxPl7kC2kd2QjXJc9n+giBgWLOZ8t/mIdWoibnuNrd4F88FS2E+Fds2oN+1FafJiCoyhugeFxOU0AWlVuex88qVGtr3vZEDti/Jm/kjiXc/jkzTtJvtmUIbGhLb6zAaqNi+Hr8RA5B6MptcEOiUmc2epDjMajV/DLqI+OJS3pvQ9DJZPQ+l8/VHPxBQh0i1SyV8OmYI71w2usnn8RaWpbUHwNdsYfq8ZTxy8+QWtkgEoGrlBvTzV+A/bih+Q/qcfQeRBiNRKPAfNRDfgRdRtXgVBf/8S+GCXcRc04fIiT2QKkVJVh9iu1VvwW6n4/AiNFkOV7vUVeHY4hsuuMpKHNx/cwkZh22Mf6MPbQdFeM7WerAa7fz99FYOLs8j7qaBRF/t+YL75vwKDr40F9OxMnTXTsB34EUeO5e9XO/ypu4+iLZ/TyIHTvKYN7U+BLudqn07qdi8DlN2JjKtLyGJPQlp1wuNzvU3LzqwjoJdy4lIG0ZYB8+VnbIaKtk953UCew8gdMQlTTpWU2vOlqxYSNn6FUS98Tgyfw9VLhAEDtzxNBq7neun38yq/8SWO1j25Fu0KSypU6R+dPEw3p/YvDVjm5PYghKUdjvpMc1/zxI5ndxHX8NRWoEsWEd0Kw8z8XYc+moq/16K4d+NKEN8ib95MMFDWqb+eUshtlv1cmKfKEOVaePIb/912JHLOTg7lITpZa52qY1Yus9Kt3HfTcWYTQJXfz2YyJTmr8lXmWdkxvT1VOQY6fD8JIL6ej7BpWz9EQ6/9Q9yPw1hT9yNMs5zNVsNG3dQ/tNcUMg9Fpt6JuzVVVRsWUfF5nU4DFX4JLQlaegN6GJTkcpq/4wLdi3HaiinYNdyj4pVpTaAsOS+FG/dQMiQMUjkZ7+d1CdKG9u04OTj+HXuRtnm1fgO7u05oQrsvfsZNHY7AF989iN33nEdK7s03auutliJKq+sJVRtUikfXDKcjyaMaPLxvZFJa7cSWlHF/y4eQnZEy5TSE6kb/3FDazyrIp5F5u9L0JSJ+A3vj3neXA699jd+f20j8c7h+CaLk7eTEcVqMyPPsdFpaAFSqytfJOHOYoruDMCYpsQZrCDjp8a1h9yx2cKDt5QQHCpl4hcjCIjybI/7usjeXsqsBzag9JHT8b3r0SZ6tue44HBy7Ic15P66gaC+bfG59jqkPp7xcDqqjZT/NAfj5l349EojauiVbs30PxvWkiLK1q9Ev2MLSKWEJPUgLGVAjRe1LiLShtV4VptCQzy0wW16ULj3X4zHMtEmnX2C4q5GCCcfx26oApsN/zGDz/l4Z+O7d7/C13Ki6L+P1UZG5Dle54LARYcy2NS+DQBmlZIJT93N4ufeRwK8felwPnJDWIE7Eex27KUVOMoqcFToceircVYbcZrNCGYrgt0OTqcrZEkmQ6pSINFokGl9kOr8kAcGIA8JQhaso1tGNu9/8wdO4MfhfTFdwE0AvBG/IX3E5f9mRhERiuKWW1H0O0L1rDnsuvcHwsakET91EApd8z/TvRFRrDYj0c+VEfbdiW4zEiBwgZnsV8+tjMXSf4w880ApnbupGPTWCDT+zd+XeNefR5n/4nZiugYT/tjVKAI8+8OyVRg59NrfVO48RsDlY9COGeyxzG/TnkOUfTsDp9VG5OXX49+5+Ypzm/NyKF2zjOp9u5BpfYnqMpLQDv2Qq87+/YZ16EdYh34UHVjHrj9ePudwgIZ4aDVBkUhVasy5RxskVt3VCKGmPNdFAyhZsxjfIX081gTg+3e/Ysjew7XGJj90C8fCGlczUeJ08vp3M7ly7VakwMDXHiX7v2Mcionk07GD+XVAL7I9WA/4bAhOJ7a8ImzZeVhzCrDlFmDLL8ZRWg4nRYxJVEqkvlqkGjUStRKJXI5EKnFt4nBgt1hxmsw4qo0IRtOJE8jlHPrPOy0FNt3/Ip0+fhGJ/NyrlYgxliLnC+qUtqjaP4hq5UZK/1pI2ZpDxE0dSPjYLkhkrSSk0UN4nVj97LPP+Oyzz8jKygIgNTWVZ599lrFjm6fItyeQVjpI65GHtHY3RgQg44NAHIGNv1H//FUV771cwajxPnR5ZgRyZfOWpnI6BFZ8sIeN3x9ptkL/VQfyOfjSXJxWB2EP3oK6Y9Oz0OvCabVRMXMB1cvWok5pR9SYa1D46zxyrlMx5Ryl9N/FGA7vRxEYTHy/ywlu0xOpvPFJao0JB6jLixqRNozcrQtw2CwUHVhX5zEkEinK4FBsZSUNsqmxy/1nO07R4r/BKXhsyfLWBStOE6pL0jqwIaXhYS4Sp5O3vpnBZeu3cfIv5IP//cplT99T8/rNK8Y11dxG4zSasBzOwnIkC8uRo1izchCsrhuVLCQQRVQ4/slpKINDUeiCUegCkfsFIFU2fGLstFmx6yuxlZfS+dB+1JtW17yntdnJufc5lG3iUXdsgzqlHcr46EZNQPXzV+AorUA/f4UoVkVaPRKZDL/h/fC5KA3bgrlkfLiEokW7SZo+Gt+2jVt5PZ/wOrEaExPD66+/Trt27RAEge+//54JEyawfft2UlNTW9q8RhN/TwnBf5tqjQmANULK3nWR0MjZktMp8N7LFfzytas0VfcWKE1lMdj48/EtpK8pIOHOYWgm9vB4QHjh/J1kfLIUbZsw/KfdhDxI55HzWLPzKP3fr9iKyggbMxHdRQOapWanKfcYpSsWYjhyAGVIOImDriUosWutIv2NpTHhAHUJ27AO/WrGc7cuqDckQOajxWEy1nVYj2KrLKdi82r8xgz2SKxq18OZPD1zYa2xpWkduGX61AbtL3E6eeer35m0cQenXkECUKVRu8fQRiDY7ViOHMW85xDm/UewHs0FQUAW4IeybTwhg0ejjopDFRnttuRBqUKJMjgUZXAoc3/5utZ7dwwbS4hMTlXBYfT/rKBy9iKkWh/Uqe1Qd2qPplMysoAzd90TYyxFzkdkfr7IrrqO8O5ZVP06g133/EDUZT2Jvb4/Mk3zr6K2NK2iGkBQUBBvvfUW06ZNa9D2XlENQBBIHZiPKvv0Av9Hvg6iakTj4x4tZoFnHihlxUITIx/vQo/Jzd+WsDLPyB/3rUefbyTpiYkE9vKsDU6rnYyPl1C0cDfhl3RFecmVSBTun2MJTidVS9ZQMXshisgwosdfjyrMFRfa1Ez1M2EpzKNk+UKqD+5BGRJGTOooAhO6NItAPpn64lOPjztsFhxWI0ptIGlXPV1r3/1rv0YikRB9TcN+n+4iZ/HPmHYfIOq1x5Bq3Bv3GFNcxtrH36g1diw4kIFvPn7WfSUOB+999TsTNu2sU6TmBQZw5aO3kRvWPIlFjqpqTDv3Y9p5APPeQwgWK1J/X9Qd2+IXnoxPfBsUQSEen3Cm5h5j1pfv17x2AinPvVNTmk9wODDlHMWYfpCqY/trhLQiNhJ1SjvXEmnbBM+WJhMR8UIEuwP94lVU/b0URZCWNvePRtc9oaXNcgvnRTUAh8PBjBkzMBgM9O3bt97tLBYLFoul5rVer28O886Iz04r8lJXGarjjwBDJzmHZoQj+DReiFRWOHjo1lL27bRy2bu9SR7qucz3+sjZWcrM+zei1Mjo+N4N+MR79mFrKdJz8KW5GDKKCZp6BaoBvTxyHkeFntKv/8C87zCBfQcTMvxipCdlth9P5imcPwvALYLVVl5GyYoF6HdtQxEYROLAawhK6u52kdrQMlbH41zrGgfI3boAmdKnTi+t02pB7tu8nVjM+TkY1m8j8NoJbheqAF0yj2GWy5AAKrsDu1TCwDceO+t+vkYTmx5+Fa3FWmtcAHKDdFz56K3khXpepNrL9Zi27cG4dTeWQ5kAKJNiCe4/HG27jqjCo5p1QlSxeR1b/pnJ58Ad/43dd+WNtWpIS2QyfOKT8IlPIoSx2A3VGNMPUpm/H+OG7VQtWgUyKcq4aFRt4lAmxqKMi0IeHoJE1vwd+kREmguJXEbAuKH49OiM4fff2Pf4H4SNTSPhtqHItRfG5M0rxeru3bvp27cvZrMZX19f5syZQ0pK/aWCXnvtNV544YVmtLBuZKV2HEEykEgwdlGyc18MnbvnoigTSP8wkMoJ57ZUmZ9j594biykrdTL5y4HEdGlcYoc72Ds/m3nPbSMyNZDIJ6/xeCJV5a5jHHzpL6QqOeGP34UyIcYj5zHt3E/pNzNAJiXm+tvRtjm9dmbwgOEuoSoITc5idxgNlK5eSsWmNUg1PsT1vYyQdhedVn7KXbijjFXBruU1XtW6jmGv0qOO8Mzfpy4EQaBg5VzkEaH4DvZMXd1/LurKPxd1JaawlOl/L+WRaVc1qDnHZeu34zhpOwHICdZxxaO3UxDi2X7gToMR45bdGDbucAlUqQR1x7aEX3Ilvu1TkfueeTndk1SvXEgh8DouseoAlqZ2OeM+cq0v/mk98E/rgTBKwFpShCkrnarSdEw791O1dO1/G8pQhIUgDwtGHhKILDAAWYAfUj8tUh8NUrUKieq/JDCFHCTSEx4EARCcCA4Hgt0JDgeC3f7fPweCzQY2138Fm73We9j/29b5334OJzgFEJwguK5TwOWxlkhAKnFNEOQyJDIZEoXcZZNSgUSpdCWtqZVI1GqkPmqkGo0ree0CqrkpcmYU4SEE3HMXslWbKJk5j4otmbR9aOx542U9E14ZBmC1Wjl27BiVlZXMnDmTr776in///bdewVqXZzU2NrZZwwCCftST8HQlhTdoyX3pxENJkW3DoZXiDDq3mf+hfVbuvbEYlUrCJR8PJTiheR84gvBfR6rPD9D50ji0t13h0S4bgiBQ8Oc2sr5YgV+nGPym3ojMz/3xiILNTvmM+a4kqi4diR51DXJt/edpaiiAYLdTvmkNpauWIDidRKYOJTx1EDLFiVmxO4v5Hz+WNiwBQ1FWjUf0XI5/ql0nvw5N7s3WH58gbPSlBPYe2CSb6+PU775q707yZnxP6P03o+nsvsL8AH+98AG5IYHcefcNDdo+Pr+Ix2fO5667b6hpFaq02dl797MYVUpGPT+dwmDP1T0W7A5Mew5iWLsV06794HCi7tgWXdvu+HbsjEzjHWVvhv7vPRbkZfM4LrF651U3sSIlrUnHdBgNmAvysBYXYC0pwmwqxl5ajqNcj2C2nP0ATUEicVUw+E94IpO5cgckUlfW9skCUxBcwtXpBIcTwel0lfqyOxBs9jOfRypFqtUg9fVB5uuL1E+LLMAPmb8vMp0/skB/ZIEByIN0SDRqUdheQNhLyjH8+guVO44RMaE78dMGe7xbpCdo1WEASqWStm1dmd49evRg8+bNfPDBB3zxxRd1bq9SqVCpWsgVbnXSJS0Pmcml+cN+NKDdbuHwzAgEtQRb7LlfPJvWmHn49hLiEuWM/GAEvsHNm5BhtziY9+w29i3MIW7qIHyv7u3Rm6HTaif9g8UUL9mD38gBBFw5ziPLe7aCYko+/wVbfiFhYye5kqjO8rnONYtdEASqD+6lePFf2MpLCejeh4R2o1FoTp90uLOY//FjUURNjOmuP14+p+OfGiJwsp1+4YngdKAKjzxtv/oEfmOF/8k1Vf279KRw2Z+ou3R0u1Bd9Mw7dMgrIu1YHh2O5mJRKMiMCqtz2zbZBfzy3peEV7raJF+7YiM/D3eFKlkVcga88RiFgQFute9kbIUlVK/ahGHdVpz6ahSxkYQOvwT/Tt2Q+zVvSEZDWHvT3Sz/4h2SSouxSaVNFqrgSuzTJrWrs2Sa02rFYTTgMBtxWiwINlctWMHhcHlC+c9HI5EgkUhBKnV5O2v+yZHIFS7Pp1yOVCav+X+JTO62+5IgCAh2G4LNhtNqwWm14rSYcZpNOCxmHCYjTpMRh9GA3VCNzVyFpagUh74KZ5WhdjkxtQp5cCDy0CDkIYHI//M2KyJCkAUHNkvYR31lxMTyYu5HHhKI/913Il2+nqJZ86nclkW7J8aftxUDvFKsnorT6azlOfUWol4uJ/zL6lqdZyQCSK0Cgrppom7BXAPPP1xGr35q+r8+EqVP8/6pDKUWZj6wgcIDFSQ/fSkhg5reqedMWIqrOPjiHIyZJQTfMhlt3+4eOU/12q2U/zQHWZCO+Gn3o46M9sh5ACxFBRQtnIsx4xA+bdqTPOgmNIG1Rd3JXsrj2fvasIQm1UeFuisBuKtZwMnHqS46ChIJ6sjTwwDqawDQ2MYAJ9dmLV29FIe+irDJtzbpM5zKjYtW0yGvCHCtEC948UNGvvjAadu1yy7gl3e/JFRf+3f/xMz5NWIV8IhQFex2jNv3Ur1yI5YD6Uh9NPh36kFAt94evY7dgVWp5LZrb+GXbz7ipuvvOPsOTUSqVCJVKlHQ/N38GoNEIkGiUIJC2ehmI4LDgb1a7yoLVlmOvbIcW0U5ZnMJpj2HsBetc4UlAMjlKMJDUESFoYgKRxETgSI6AnlokFtFbH1lxMTyYqcgCPQ5mMGG9kkNCi+qD4lUit+I/qhT2qL//id23/cj8TcPJvKyns1eJcjTeJ1YfeKJJxg7dixxcXFUVVXxyy+/sHLlShYtWtTSpp1AEEjtm4cq33naW5nvB1I+qWnL1j/+T8/7r1Ry8eU+dHpiJDJF82aGl2To+eOe9djMDjq+NQW/Dqd7zdyJfm8OB1/8E4lcSthjd3okPtVptlD+81wM67ah7deDqMFXIPWQN95hNlG6cjHlG1ejCAyi7fCbCYhNQSKRnLakfrKXMu2qpwnr0O+cPaAnU1fCVH1JVE059sHNP6GOjEGqOuH1P+451cQmYILTGgA0tjHAca+2taSIzM/fwn/MYBTh7ktSSs7O58U/5tUa+2rkAI5En+gSpjWZWfbU20RUVnHqI8AhkfDNyP5us+dUHBV6qv7dSPW/G3FWVqFql0DkZVPw7ZiGVOHdy37ds47QOSeb7wcMJSc4lEGPvNjSJgGerfDRXEhkMhQBgSgCAtHEJpz2fvp7L2GvLEem9SV44AgsJUWYK/Mx7z+Cs9pVak6iUqKMjUIRF4UyPhplYgyKyLBzFrD1lRETy4vVZsieg3z//rfccP/N/OuGFSJFVDhBD09HOnshWf9bQcX2o7R7ZNx51f3K68RqUVERN9xwA/n5+QQEBJCWlsaiRYsYOXJkS5sGQNBv1cQ/Xo7klEhfS4SU/YvCcerO/St1OgXef7mCn7+upt+0ZNLuTWn2GKTMjUXMfmgT/uEakl6/HnW455YyAQoX7CLjo8X4dYjCb9pUj9TLtObkU/L5zzjKKomYdC0BXXq6/RzgWtKr2r2NokV/4bRaiO4+hvDUwbWSp05d6vekB7QpNCR+VnA6MaYfIqBn7Uodxz2nJqDNA8+ctt+5hFQIgkD+8pnIdAH4X+y+78XXaGLJ8+/XGssLDOCVq8cfPzEPzlnE9H9WnLavQyLhxyF9eG7KhCZ5R+rDkplN1ZI1GLfsQiKX49+5J4G9+tcZcuEN1CUAf/7uUwD+6NEbk0oNzVySrT7c1fbXmzl5UnjyZxQEAUd1FZbCPMwFeVgKcjHtPUT1ivUgCC4BmxiLKikOVdt4lG3ikfk2TPTU16pVbOFam3Fbdrv+u3W3W8QqgEQhJ3DyJahT2lL+7W/svOs7kp+8FP9OzZf86km8Tqx+/fXXZ9+oBYl/rPw0z0rOw/4U3ds0UWe1CDz/cBmL/zYy6oku9Ly6+Wuo7px7lAUvbSe+Vyihj17j0ZIYgsNJ5ufLKfhzm6t+6vgrkcjdezkKgoBhzRbKf56LPDyE+FseQBXqmXgeS3Ehhf/MxJSVjioiGqe+GplSc1qW/6lC1JMe0HPh1Lqqx0V1XeK1uigTh8mAb/vazTrc1VL1ZPS7tmLed4TQ+6ciVbrHm6iw29l77/O1xpwS6Pv2kzWv3/huJlev2XLavt8M78cL11zqdpEqOJ2uTPdFq7AczkIWEkToiPEEdLvIbUX6PcWpAvD+pfNq7pWr33uR5y+5knlpPVrUxuN44hr1NuqbFEokEuR+/sj9/NG2PRHe5TCbseTnYMo9iqE0i+q1W9DPd03SFNERqJITUbdPQtUhySNJr+czEqeT61duwN9oBk4Sq1t2k/1flRC9j5ofh/SpSdQ8VzSdO6B45gGqv/uBPQ//Svwtg4m6vFerT77zOrHq7RjSFPjucrUjtPvCgblhWNs1TdRVVzl55PYStm+2MPGti+g4snnjzwSnwL+f7mfdlwfpdkUCqpsvR9qEXt1nw6Y3cejlP9HvziHw+kmoPDDjdlqslP80x7XsP7AXUYMuR6pwf9cPp81K2epllK5ZjkIXSLtRt3F07Qxsxso6l/FbUog2hOOeX5nSB5nSp6bVal3JX2WZO5D761BHxdY6hrtaqh7HbqimaMmf+PRKQ9O5g9uSNXbe89xpY50+fL7W618GXVQjVgWgxE/LwNcexeTm7lOCzY5h3Vb0i1ZhLyxB1TaBqKtuwrdDp2ZvEHGunCwAZQ4Hd6xZXvOer9XKlvjmn4DXh7uv0fMBmVqNT2JbfBLbEoxrsm8rL8N0LAPT0QwM+w67vK+AIiYSdUpb1KntUCUnuW0Ceb7iY7Hx4NzFBBpMOIHPJBLeAh4xW3hoziKkQLlWw6y+PTC4oW60PDCAgPvuQpi9iKP/W0n1gXzaPjS2VXe+EsXqmbA5Cf9IT+GDupqhQzNC6JqaT+mVPmS/3vR6p6XFDu69sZjcbDtXfTaQ+J7N09XmOHaLg3nPbWPfghzibxmM+sqLPDoDMx4t4cBzs7FXWwh96FbU7d3/ALPlFVLy2U/YS8o9uuxvyDhM4bwZ2CvLiUwbRmTn4UjlCq9Yxj9XTrb9ZIF66mdyOuyUZm1H16Ovx8VU/pq54HQSeM2lgHuSNSav2IDSUTvm/Kthfdnw8GuMePkhCoNcKyU728RzJDyEoGojN9w/ld1JcU36LKfiNFuo/ncjVYtW4dBXo+mWQtQl19YZg+jtnCwAn5g3s9Z7xwKCKAjw7mQnkdpIJBKUQcEog4IJ6OpqyGLTV2DMPIIx4zCGzTupWrwaiUKOqkMbNGkd0KR1QO7hesKtEYNGxbjnpvPRF7/SI/0obwkCR4G3BIG7gC1t4rnnjmvdIlSPI5HJCLxyHKrEWMq++53d03+iw/OTUEe1zt+hV9ZZbSruaLca9HsV8Y9WAJD9YgAlN7q/HEx2lo27ry/GYhaY+MkQwpI9Gx96KsYKC7Me2EjennLaPDqekEHuLQV0KmUb0zn82t+owvzR3TENeaj7b2qGjTso+34WsiAdMZNuqmmZ6k4cJiNFi/5Cv2MTmvgkkrpfgUZ3/pULOVPcalnGdjL+/YmEux/zWGgFQPXh/eT+/CVBU6/A978OZu7wrAZWVCF3ONjy6GuAq/Xn8TvF6vZJXPfo7Sc2FgS3L/c7jSaqlq2laslanGYL2r7dCOs6AmVI3aWyWhOh+kpWv1u7SUv3x1/FqG7e0nsinkUQBKzFhRiOHEB/bC+Ww5ngcKKIiUDTLRWf7p1QxEa2+uVnd6Kw29l57wv8aLXyOvA4cL1KSdqHz2P35GpmXiHln32DvcpM+6cnENAt3mPnaiytus5qi2J10mlAPsrCE16X2Ocr3S5W9++2ct9Nxfj5S5nw3XB00Y0rW9JUynMM/H7XOkx6KylvXoNfiudCDwRBIG/WZo5+uZLAPm3RTrnB7S0yBbud8t//oXr5Onx6dyV6+GSkSvfH3Fbt20nhP7MR7Dbi+11BSHJvV53GZsSdzQPOxJlCFvIz16GJb+NRoeowmymY/wfq1HZo+5/wjrsjWaNc50dQZRUVGjU6k5mT/4J9DmUicTpPxI658WHrNBjRL1lD1dI1YHcQ0K0PQf2HomgBr6OnMuJ/+vbjWq/Tg0JFoXoeIpFIUIVFoAqLIKjfEBxmM8b0A1Rk76Zq2Tr0fy9DFhKET8/OaHuloYiPvuCFa5fMbLRWK3dwou0wFitdM7PZ0i7BY+dVRIUT8vh0qr77nn1PziDx7hFEXNLVY+fzBKJYPYmwTyuJfkN/WgKV082a53ix/4Q2Cka8PwJtUPM2NMjdVcaM+9aj9lPQ4d0b0UR77kHptNrJ+GgJRYt24z9uCL6TRrt92dheVkHJZz9hPZZH2LjL0fXq5/abor26isL5s6netxPf9p1I6noZSp8TnvCmCMj69q1vvK74UU8I2PqOaSjJwXQsg6grb3TLeeojf+0cnEYTQTdc7pa/Z2JeId9++B033HcT3378A20KS077revVKq549PYmJzmcitNoQr94tUukOpzoevQjqN9Qtxfwb4wA9URGvMpqJb68tNbY+HseO2cbRVoPMrUav9Su+KV2RRjpwJh5hKr9O6las4Wqhf8iDw/B56IuaPt2d2vpudbEiB37AVjYLZVXrrqYp3+fx+gd+xixY59HxSqAVOuD/x23oflnJhkfLsacV078LUNaTT1WUawC0jI7HS8pQpXrOO29/Nu15D/pvuXqJf8Yeeb+Unr2bZli/4dW5DH38S1EdAgg8qlrUQR4rg6brdLIwRfmUnUwn+Bpk9H2c3+hf/P+I5R88QsShZy4m+5BE+Pe5Q1BEKjau4Oif2aDBJIGX0dgYtfTxNPZuk+dSUzWt29943XFxLqz+9XZjpmTuRKFLgjfDp3ccp66MBzej2H1ZoJuuAx5SNMnU0qbnZXPvAvAqmfePU2kCsAvA3vx5E1XNPlcJ+M0W6hathb9wlVgs6Hr2Z+g/sOQ+3qmbXJjBOi5ZMSfTWh+/stXCFDz/c5O64HzFOF/IZSNutCRyGRo27ZH27Y94eMux5h5hPLMLVQtXYP+72Uok+LQ9u+B9qIuSH28u8qFO1naNYX9sZH82bsrSCTcds8NTNi4g1wPtmQ+GYlMhvLSyQRqY8j79S/MBZUkP36JR1uouwvvt9DD+C010m5a6Wnj1iApBxaHYw9131f0xw9VvPlsBWMm+JD2dPMX+9/yWwZL3thJ++FRBNw3GZnKcxmcxmOl7H9mFg6jlbCHb0PVNsGtxxcEgaqF/1IxayHqjm2IvvgG5Fr3llOxG6op/GcW1ft2IlEoiOoyiqCkbnVue7akqjOJyfr2rW+8ruX5M52/6MA6crcuACC6x9gGi9m6jmnWl1C1dwdhYyZ6pBUuuHq+5//zO+pOyWgHXdTk40kcDg7c8dSJ1ye9JwBLunTkjruuw+HG0mmCze6Krf1nOU6TGV33vgQPHOHxVqiNEaDnkhF/NqE5u0svjgUGM3n7RgCenXB1k2wUaf2cLFydQ6xUH9xL+cHNlP80l4rf/kbTozO+g3ujapdw3ocJbGmXUNuDKpHwZ5+6nymexG94f2RBOsq+/IV9j/9BhxcuQ+7n3aE6F3yCVfjbFUR/VFXzWgAKb/Ul72n3zXQEQeDLD/R88Z6eXte1YcRDnZvV9S44BVZ8sJcN3x0m8rKeJNw21KPnr9iaxcGX/0QV6ofuzmluzw51miyUfjsD09bdBA0YTsiwsW4PLag6sIfCv//AabUi2GyAgFIbSNpVT5/T8ZorzrSu8xzviAU0+DPUZ+/hHb9TfWg/Sfc/5ZFSYADZ87/HtOcQkS/cjzxI16RjSRwOMm97sk5P6qKuKdx513U43Si6BacTw/rtVM5djKO8Em3/HoT3HItC1zozcE+lIUv4coeDDW88zZOXXsXiTs3/IBZpHdj1lVTu3ELF7g3Yi0pRRIXhO6Qv2n7dkbq5NJxI3ViOHKX0429QBvuS8tqVKIM9s+JzJhqaYHXBi1WArknZSB3g0MDO3dHgRo+nwyHw1nMVzPixmiH3pdD35uRmnT3arQ7mPbuNfQtzSLh9GFGXeaaM03EK5m0n4+Ol6Hok4nvjjW6/6dgKSyj5+HvspRVETrwWv45pbj2+w2ymaOEc9Ds249s+FUt2DjZjJUgkxPW57JyEZkOFqjsE7XFhqtQG1nhGtWEJ6HMPAmf2rJ58/uOe4JPFrVlfwp7ZbxA6ajxBfQefk31nQ797G/mzfiL4tmvQ9u7apGMlZ+Ww+KWPTvOkLu+UzC333eRekSoImHcfpGLmAmy5BWh6dCK8z8UeTUDzJuR2O9FlJRz1QPWN45yPsa7n42dqLILTiTHrCKV712Davg+JQo62f0/8RvS/YGNbmxNbXiGlH3yJRC4l9Y3JqCN1zXp+sRpAHUjL7aSMKsTQSUnmt6E140df14FMQvnl7l1GtlkFnn2wlKX/mBj3XDe6Xpbg1uOfDbPeyqwHN5Kzs4zkpyZ4tDSV4HCS9eVK8mdvIWJCdxQXX+H2ZWLTzv2UfPkbsgA/j3SjMh7NoGDOLziMBhIGTCa4bS+Kg9Y3WUA2NJ60vu0aI2LrqpNKEXSb8lKj7KwrBODowYXIfX3RndJe1V3YKsopmD/TlYTRRKE6dOsuvvv059PGO3zyIma1exMarVk5lM+Yj+VAOqr2ScTdMt3tsdPejNTpZM3bz/Frj76sTE6hyE9HfpD7y9Kdj7Gunv5MDRHDZ9vG04JaIpWiTUpGm5SMbXAFlVvWU75pHdUr1qPp0hG/MYNQt0t0+3lFXCiiwgl55G7KPvyCPQ/+Qsobk/GJa3oNeXdzwYjV8HcriP7AtdyvWG4Gix1Uro9ffpX7Xd9Gg5NH7ihl6wYzk97uTfvhUW4/x5moKjTx293rqCow0fG1yfh3jj37TueIw2Tl0OvzKN+YTuC1E1AOd+8NTRAE9P+soHLuYjRpHYgee91ZW0825gYrOByUrFxE2eplaOIS6DDiDlR+rh/ruXacOllgNrRJQH3bNSZ56lR7G9Oc4OTzn3ocQ0k2VXu2Ez7+So8s/wtOJ7nzf0KqURF03cQmHUtptvDtKULVDqR+8oJbhaq9rIKKWQsxbtiOIiqM6GtvQduu43kfd3cqjy2ci85s4s61y7lz7XIOhoQz4ZQKAO7gfIx19fRnaogYPts2zTlJUPjrCBk2lqCBI9Dv3krp5pUUvf45yrbxBIwbijqtwwX3+2oO5CGBBD90N2UffM7eh38l9c2r8UnwLq/2eR8G4O900qlfAfLq2h/TkCLn4IJIj5y/otzB9KklZByyMfH9/iRcFHr2ndxIcbqe3+9aB0DSS9fgE++5i85aWsX+Z2Zjyi0j+Lbr0KR1OOs+jSnq7jRbKP3mD0xb9xA8eBTBg0c1KD41/b2XsFeWIw8IpM0Dz5zB/mLyZ/2EuSCX6K6jieg8DIlU2uQl+ZOX4xsT53ryeYGaZXxDUZbH413rQxAE9q34DIexmoQ7HvZIYlXpqiWUrFhI2CO3NamrWZ+9R/jt3S9PW/pv/+mLWFTuEapOswX9gpVULVqFRKMmdNAYArr19ljCmTdTVwOAHo+9gkFz4WR4uwN3ei9PPhbg9Z7VMyE4nRgO76d40xKs6cdQxEURMH44mq4praYNcWvCUWWg/MPPsZZWk/rmZLSJntcuYhgAEPqNng7vVp2WXGELlnJotmdiyYoK7Nx9XTHlZU4mfzWYyJTmTazI3lbCjPs24BehIe6FKahCPBcwbcgsZv/TM0EQCHvsLpSxDfMeN7Rdpr24jOKPf8BeXErU5Kn4dezcYNvO5rEQBAH9js0Uzp+N3M+fjuPuRRt6opVmU0tBnc2beqoYPv7aYbPgsBop2OXqq358Gf9cE7vcQcXR3ZiOphMz5VaPCDJTdhYlKxfhP25ok4Tq4B37+OGj708bb/fpS9hUTfcG1yRPzVqAw2AiqM9gggcOR6q6cJNBfvzuk1qvjwSFiUL1HDjuvSycPwugSaLwZE9omweeOeuxzlYV4lyqRrgLiVSKb/tUtMkpmLLSKdq4iJJPfkQRG4Vu0ijR0+pmZH5aAqffQfkHn7Pvsd9JffsarwkJOK/FavQpQlUAcp7yo/g2nUfOdyzTxl3XFSMIcNU3wwhOaN7MuoPL8pj7+Gai04KIeGoKcq3nmg1UbMnk4Mt/oo7UEXDnLcgDG94q1n/c0BrPan2YD6RT8tlPSDVq4qfd3+i2qWe6wTrMZgr/mUnV7m34d+1Fm06TkClqf1cNXbqvjzOFDxQdWMexDbNBEGrE8HFxLFP61CRHwYll/OaqJnAqhftWk71xLkil2CrK3X58h8lI7twfUSbGEDBhxLkdxOlky/0vEGow1xo2KBV0ef9ZtwhVS/pRyn/9C2tmDj49OxPRfwKKwPrjMi+ExJm0Y5kklJXUvP4cuNdhI3jzuvP2M3uK4AHDXUJVEJq83H4+hktIJBJ8EtuSkNgWY1Y6RevmU/zhdyjbxKG7YhzqZDGm1V3IfLUE3ncHZe99yr7HfqfTu9c2e9JVXZzXYQCVwHGnst1Pwq5tUaD0zNLBwb1W7rmhGP8AKZd8Ohz/CM8V26+LbTMyWfTqDtqPiEZ332SPFvktXLCL9A8WoeuZiO8NN7m9dWrVyg2U//InqnaJxF56EzIf97WiNedmkzfzBxyGauL7XkFwkqtRQXOKwZpSUhIJgQldMRRlnXWpv64s/8bY2pjPd/K2OVv+wWlzicCzhVQ0FkEQyP77W8wH0ol8bvq5Ff8XBLJuefy01ZNiPy0933+2yTY6KvRUzFqAYd02FHFRRAy/DJ/4s3t/GxqG0hi8TQDvevERlM4TjVRCFUpKbFa3XycXCt729/VmBEHAmH6IwtXzsB3NRdM1Bd2V41BENG/I3fmMo7KK0nc+QXA46fzetR4ra9XQMIALIugj6zUdu/bEeEyobt9s4dbJRUREyZj49ahmFaqCILD68/0sfHkH4eO7E/jgtR4TqoIgcOy71aS/t5DwcV3wu+UWtwpVwe6g7Ke5lP84B98hfYi/8g63CVVBECjfsIqjX3+ITONDyvgHa4Qq1F729zQRacNQagOJ63MZhqIsrIZyDEVZpF31dL1C8vg+J2f5N8bWxuxzfNv8HUtw2i1I5HKkGh+3e2oqNq3BtG0PwVOvOCehKnE4yKxDqGaGBDVZqAp2B/pFq8h76m1Muw4QfskVJN70YIOEKri8W/KAQLd+Zycv7zYXFZvXkf7eS1RsXldrvEt2Vi2h6gRko8a7/TNfSOh69WvQsn1zU9810JJIJBK0bduTeOMDRF5+HdbsfPKffZfyX//CaTS1tHnnBbIAP4Km345gd7LviRnYq8xn38mDnNdhAKY4KRl/heMM9NzHXLvCxCN3lNKpq5Ih745EpfVcV6hTcToEFr22k+0zMombOpDoq/t4LH7HaXOQ/t5CipfuRXfFWJRjBrv1XE6DkeLPfsZyKIPwS650a3kkh8lIwZ+/UX1gD+Gpg4jucTFSWe1roqnL/o3hbBn7dXlBm5LlD437fK5tlyEo5Sg0wSTc+QhShXuva3NuNkVL/sJ3eH98uje+bWu3QxnMeeOL04TqS5eN5quLm/Y3NO8/QtnPf2IvKEbXsx8hw8Yi0zRuAuqJOD93LO821ntXXyb4tz98Vmu7e666CV1KGrpe/c/ZNhHvpKHVAFrCMyyRSvHv3B3fDp0p37CK0tVLMGzcge7ysWj79xCTsJqIPDiQ4Om3Uvzmpxx4fjYpr13VYq1Zz+swgIY2BThXFv9t5On7SxkwVE3vV0YhVzVfNrDd4uDPJ7dwaEU+SdNHEz7GvcXxa53LYOHgi3PR78khaOpVTa6BeSq2gmKKP/wOZ7WR6CtuwiexrduObc7NJm/G9zjMJhL7XU1gvOf62Z9KXaJTEJxYqyuwGsopy9hB+dFdhCRfRFTX0TUC+lwrCbiT4gPrObp+JrE33olPYju3HtthMpL59TvI/LSEP3YnEkXjbn6djmTxz2ufnTY+/vE72NWEeoz2cj0Vf8zDuGknqrYJRAy/HHVk9DkfzxtpbHhCfQJkzmdvEVteio/VikmhpMdTr3vSbJEWpKEi1BOhL43Frq8kf91fGDdsR9k2nqDrL0MZ47lGFRcKliNZFL/zJYF925L8xHi3dsAUO1h5WKzO/qWaV58sZ9wkHzo/NRKpvPlmcJZqGzOmbyBvdxltn5xAUF/3iola5yquYv/TM7EU6wm+66YmZWvXhflAOsWf/IgswJfYK29FGeSeMluCIFCxZR3FC+eiCo+iXb8bUPmdvVC5O2NXj4tOudqP0PZ9qCpIx1iag9NuPW1bqVxJYEIXoruPoSJ731ltcIed9R3DWl3Onj/fwi+1KxETJp/TsetDcDrJ/usbzIcyiXzuvka34u2/cz+/fPhdrTGLXEbaB8+dcw1VweGgavl6KucuRqKQEzb8Uvy79PT6LONz8WS52/t1UcYhtsUlYZef14t0Xos3xbl6ky3GzCPkL56BvagU/zFDCBg/DImbV4cuNIxb91Dy2Y9EX92H+KmD3HZcsXSVB/nhcz0fvFbJ5Bt9Sbp/hFtnGWejutTM73etoyLXSIdXPVvs35hVwr4nZ4AEwh67G0WUe8t9Va/aRNlPc1C3b0PM+JuQNaHkzck3Sv8uPSj4ewZVu7eh69WfpI6XnrbsXx9NLVkFLqFsKMpC6RuI1VCB3VxF8YG1+Ea0ISluGFptOGp1IMUl+8nNXU94WBfkchXHcjdSmb2P9mPvJOyqpyk6sI5df7xcpyA9FzuLDqwjd+sCwNV2ta5jCILAkW0zkKrUhI669Jw+/5koW7sC0459hN53U6OF6oBdB/npFKHqAJK/ePWc7bFkHKPshznYcvLxHdybiN6XNHrJv6U4l2LtDQ1PqE94yBx2lDYrJrXrO9qUlHxuxou4BW/q6tWSJa5OxSexLYnTHqFszTJKFy7FuG0PwTdfhSrJc8/L8x2fHp3QXTGO3F/n4xMbTOiI1GY9vyhWG4EgCHz2tp6vP9bT/9b2JN3dvN1qKnIM/HrnWmwmBx3emoI2Kcxj56rclc2B52ejCvNHd9dtyAPrn/HUxZkK/wtOJxWzFlK18F98h/QhauDlTa7fefymXbJqMeWb12ArLyNx8JRaSVQnU1fx/cZ0m6oLu9VE6eHNFB9cj7myCKVWR1xMf0JDUvH3j0Eiqe1918aFkhB3YoYaHdWbLfu/IWPlT6RMfOiMgvRc7CzYtRyH1Vjr8556jJKDGzCmHyRmyq1NmjzUhSHjMCXL5+N/8VA0XTo2at8+e4/w8wff1BoTgJRPXjwnW5xGExWzFlL970YUcVGuFqnRrjq73uQhOhOeLFFUlwgKrtKz4r2XWJzSmSKtH3+n9WR/tPjwbyieuK7OxzJV7kIqlxMyZDR+HdPIW/Arha9+gv+4oQRcOgKJ/MJr4OEO/EYPQlF5jCPvLUQdE4RfB880VqoLUaw2EKdT4O3nK/j9+2qGPdiJPjd6bum9LooO6/ntzrUo1DKS377Bo3XPSlcf5NDr8/BPjcbvlmlINY0vel5f4X+nxUrpV79h2r6P0NETCOwzyC2CP3jAcEpWLMBpMiJVqki5eDqawPpjlU7Njj/+/2fKyK9v2Txv51IKdi9HcDhAcKKL70yH+EsI1CWeJlDPhELhQ8f48Wzb8T+qCjLqFJMn29DYeNaItGE1ntW6Wqqa9SUc2/IXAT36oG3XODF5NmyV5eTN/gF1xzYETBzV8B0FgVmvfkLPjOzax5NK6fjxC42uoSoIAsYtuyj/9W8Es4Ww0RPQ9epfa7LkTd6qluK4CNLEJpD+3ksEDxjOjkVzUTodXLJnBwBSAVGsNgJPXFfe5M30VlThkSRcP53SNcsoXbgY856DBN92jVjm6hyQSCSoL7sGbfYnHHxxDmmf3IgysIEVewSBbruy2Z4WC+fwzBdT5RqA3S7wwiNl/PFDNWOf6drsQjVnZyk/TV2FT5CKNm/f5FGhmv/XNg6+/CfBA5Lxv/P2cxKq4Cr8LwvW1Sr876isouitLzDvPUz01TcT1Nc9FQUEpxN7tR6H0YC2bQc6jbn/jEIVapeCOvn/T+X4UvxxkXiywDXrS8ha8zt52xbgtFmQSmQkJozAmH8Uk6mkTqGam7eRtRveYu++31m74S1y8zbWej/APw6ZUo2h+ChhHfqdJp7PVoLqZHtPJaxDP7pNeYluU146TZALTgdHNvyM3NePsFETzvjdNRanzUbO3G+RKBUE33ZtwzN0BYHMWx4/TahWatS0/fK1RgtVe0k5xR9+R+nnv6BqE0fiXY+7JkunePU9UXbKE7ijlFV9ZYmOl1EyZWdhryynauUi1HZ7rW3eGOPe6+R8p7VcV+cjEpmMkMGjiL95Ok6zhYIXP6R63daWNqtVIlHI8Z92E4JD4NCrfyM4nA3ar8/mTD5+5Dd6b8k8p/OKntWzYLMKPHVfKSsXm7j0tZ6kjm1eT0LG2kJmPbiRiBQdkc9c57GuVIIgkP3dGnJ+XY/fyAForrq4SWU//Ib0qeVRteUVUvT+t2C3E3fjPaijYhp8rDMtnznMJvJn/4zh0H6iu48lIm34aQK4IaWg6vOm5m5dgMNqJHfrgpo4z9D2fclaO4OSw5tQqLWEhqSir8ohIW4wWcdWYbFUkHVsFdFRvU873vH3C4srAeG07SQSCXK1L3aLsU7bz7b8X1foQEOSsfJ2LMGcl0PczfcgVbmxdq4gkLdqJtbsAsKfuBOZX8Nm4VK7nYzbnzqtNNWfvdK4744pjbPB6aRq2Voq5yxG6qMm6uqb8etQf1UIb/NW1Xf9n7oEfC7LzGfz9h0/xzuVtbuX3X3ljQhiWaBG4W3X1YWIOjqWxJsfIu/fmZR9/QeWgxkETpmIVCkmXzUGeWAAgbdMoeidL8n+YS1xUweedZ8hqw8CMHT1QTb2anyitihWz4DJ5OTR20vZssHMpHf7kDyk+eIzAPYtyuGvJ7eQ1C+c4EeuQabyzA9KcDhJf38RRYt2o7tyHP5jBrv1+OYD6RR//APyYB2xV96DIqBxBeDre6BaigvJ/e0bHIZq2o2cRkBM3UvX7kiaAghK6oa1upy8nYuRyVW0TRxNdNRFyGS1PXxZx1bVikU9mYS4QWQdW4XOP44K/bE6t3PaLJgrCtn1x8s4bBYcVmON7Wdq4wp1x7Ke7fNXFaSTv2spIUPGoIlNaOC30TAqt6zHsHozQVOvRJXQsAlKSuYx5r/8yWlC9X/D+/HKtY3z5lmz8yn7fibWrFxXzdThFyNTn9tqgSc5k9Cs7/o/VfycyzLz2WIedb36MX/nZrqfJFbtEgnLUjxXKk+k5Wgt8dpNQapSETNqCpWh7SicPxPrsTxC776+0QmfFzrqDq6QrpzfFuHfJRZd94Ra70ucApPmbce32gLAsONiddVB8iJ0AFT7qpgxNKVB5xPFaj0Yqp3cf3MJ+3ZZufyj/iT29lwyU11sn5XJgpd2kDo2Fr97rkLqoYBwh8XGoVf/pmJTBsHTJqPtV3dC0rliWL+N0m9nom6fRMylNyFT15+001APEkD1oX3kz/oJuV8AKeOmow6oP/6oKUlT/tHtKc/agco/mD2zXsdpsxAfPYC42IHI5aeLnuio3kRH9a5Z7k+IG1TLc3r8fXCFBGQdW1UzDnAsew02UxVVBek47VZkSp9aIQpn85LWJWbP9Plt5mrS1/yMJi6JoIHuXZ40Hs2gcOFsfIf1w3dAzwbt0/VQBn++8cVp469fOpLPJoxo8LkFm43Kv5ejX7gSRXgIcTff63Yh7k7OJDQbmkRzLsk2Z/P2+RsNdM85Wmus38MvnFPMmYj3cyHFawd0uwhVZDQ5M7+l4KWPCLnzOtQd2rS0Wa0K/7FDIPMAh9/8h65fTEURcKKSisZs5Zbv1xBQZUYAPpXAW8AjJit3fbcaCVDpp2Zev4bVVRfrrNZBZYWDe28sISvdxuUfDySma7AHrKyfDd8dYvl7e+kxOQnl1Ms9VhrLXm1m/7OzMRwuJPjO69B07uC2YwuCgH7+CipnL0LbvyfRw/7P3nmHR1Gtf/yzPb33RkLovQoCIkW6vWEDC4IFFOVexXrVq6igP73qvTbsBZQmohSl995CJ4SE9J5N3T7z+2PdZXezm+wmGwjI93l4ws6cOXNm5syc73nP+37fiS4j/i0kVdDpELR1DYpKi6JI+faNlK5bSUDHLrTvdw8yZctZyg799CpGTTUA4al96Rg5Eh9VsF0ZC+m0Jabbd72DTqdGpQph8MBnnNbtWCYvfzen0n8DRKQKH+RK33qk1KLdikRCaHIvaouzmqy1KooCJ7d/hTYvmzaP/gNFUIjHdbiCobKCrC/fRxEbRdSsh92Kvr33z628+fPvdtu0Cjn95j1PdVCA2+fWncmi7JslGIvLCR8ykvBrrkPSynVAW6tFa/+c5/A3nNcFXtehCzPuefgitujCoDnPo7U+S3dwKbe9qTDV1ZLz27foTp8l7L5bCBh61cVu0iUFk7qKotfeI6hbAh1fudnODS+6uIpX31xB9+P5pADngDZAJnCkSzyvvHAD+f6qS1Nn9a233mLZsmWcPHkSX19fBg0axNy5c+nYseMFOX95qYnpk0ooKjAxcf4wYjqHXJDzgpmIbf7fCXbMP0XC3VejfGBIi0lj6ctqOP7CYvSl1UT+Yyqq1DZeq1s0mahYsIKaTbsIv3Y04cPGNHgdltm81NevwQAEwWCg6LdFVKXtJ6bHSOL7jKXk1C6nElS2/7clcu6K6Rt1deTuW4lRU41EKiMxbhDtEsY6LWvrp2r5bV7mp94yvy2xtbgEWMqYjzfPHRP6jieq8+B6WqsxPUaQvWsZiCIVWYdAFBt0b3B2vZZtfuFx1GafIOHeqV4lqoJeT86yr5AoFEQ8di8SuaxBKTOAp5at5umVm+y21clldP50jvvn1epQL/uDmg07UKYkkDxtFqroC+u64w4shCB0wDX4xCehLyvGUKXGL6U9tWdOUH38MKIgIJHLkfn4Ig8ORRUVg29SCnUZp+2spy1JLPx1WjuiCvDP2+/z+nlaIyzfpKJVSwE8ur+XsnXyYvrVXiyiLPPzp83tj5C/dSnl3y7FWFJG8C1jrqRqdROykCBCJt1O6f++p2TtMaJGn48HKIoK4ol37mbNbR/ynNbA28BzgNZHwYx378Ikl0Gtzq3ztDqyunnzZqZPn07//v0xGo288MILjB49muPHj+Pv76ZEQhNRXGjksXtKqK4SuPOL4US280xbtDkQBZE/56ax/6eztJk6jPg7Wm52p8mr4PjzixCNJiKffdyrYv+CTk/Z5wvRpJ0k5saJBPepH2TkCNvlS1cfKWNNNXk/fY2uMNdOP9WVBJXt/11F0zsLQIrseDUVmYfI3r0c0WSkQ7sbiI+7qkEJKlvSaRtA1bH9DfWCrGyJ7eCBz9jtT0ocTPqZlQTFdSCq82Cn7bW0uTBtA3KfAOrKc/GPSnbZNmfXa9mmr60g7JrrvCpTJYoieWsXYCwoJvr5x5EFmi2irqTMAIYfPFaPqApAZw/E/rUnzlD2zVKEqmoiR91gjvJvRYONKIroiwupyzpDybrfEQ0GSv5c8ddeCfKgYOSBQcj8AlDhj0QmQTSa0NXWoM3LpmLHRnNRqRQEgbKt60AiaVFSZJRKORYTT5C2jtjKSmbcORltC65itCaEDxlpJqqi6PH9vaJ92jRcTJIvkcmIu/YOKpRRlKxagbGiivAHbr8geqyNTeQvBfj16UbkyC5kfrKe4D5tUEUEWvd1OVWAr9bAo8Cjlo1aA11OFXCkq/uB1q2OrK5Zs8bu9zfffENUVBT79+9n6FDvpfhyRH6OkUfvKcZohDu+HElYG/eXHZsLwSiw8tUDHPk9h9SnxhA9vmeLnas2o5jjLyxG5q8k/OnHkEd4FuzUEEzVtZR8+A2G3ALi73qIgA7uOU43NpvXFeWTu+BLRJORjmOnExCZZN1n0Q41GXQExXeEYupZVm3JaEMBSAWH11GVexJ1zjFC2/SgS+w4VKrGJyy2fqiAdSnfmSKALbF1dB+Qy8z+vEkDb7W7PmfX0ePOl0hb9Ab8lS3LFZxdb2THq8k7uBpFWAQRw51bi5uK8i3rqNubRsRj96FMirNuDxo/3PpBtsXitz7mqjP2PpEGqZR2n7tHVAWNDvWSVdRs2oWqY1vi7n4EZXjr0E80abXUnjlJbfpxas+cwlRbDVIZ8qBghNpaQtv0ILrrtfgERSCVNxw8adRrqC7IIPfEWnQFuQh6HUE9+1Fz8miLkSKdQsltj/6jRepu7bB8j5pCOt2xTv4dl9sbw8Um+RKJhLBBw5AHBlOwfAFCnYaIR+9tcaWAhibylxKUN96B9OC7ZH60lo6v3mJdTR286wwAmwe153/ThjHj840M3XGGITvPeERWW73P6pkzZ2jfvj1HjhyhWzfncjM6nQ6d7rwpuaqqisTERLd9VrMzDTx6TwlyOdz82XUEx124dItGvYlfn9tH+uYC2j1zPRHDvSvGbouqY7mceGkpPrEhhMyYZrV6eQPG0gqK3/8SobaOhLumWrMBNRc1p4+Tv+R7lGERdBz6EEr/kHplLH6cSv9Qp0L5tn6eSQNvrbdkXnxiO3kH1yAYDciVPnRqewOREeZUcs78US3Iy99NRuZaAFJTRtULnLKN+HcmY2XrszpowD/YdeRjFH7BdBg91em9OPjjy5j0dciUfvS+93W3XRpsIZiMHN/wCcbKCto8Mgt5gHkG7I3Bs/p4GvmLviH4plEE39hIMJQocmbqcygcvj5qPx96fvSaW+fTHDtN+TdLEWrriBx5AyH9rm62NbW598Gk1VBz8ijVxw5Te+YEiCKywCAi2/QlKL4D/lHJyOSe6cM6QltVytmDS6nLTDevXvT27iqM3Ghk4Zcf8vngEazt1surdV/O8KTvZLz/OsbKigb98y9UW66gPmrPnCRv0dco2yYR+eQDSD3UdPYEl4Nl1YK6fUco/eQHOv7rZsKHmFMxdz+WS0xRFWuHdzYHZooiozaeoDA6iCNdEzDW6tzyWW0962ROIAgCTz31FIMHD3ZJVMHs5xocHGz9l5jovhZqZrqBqXcW4+sr4dYvRl1QomrQGFny1G7ObC2kw8u3tChRrdh7luPPLcI/NYrQpx73KlHV5xZQ9NbHiEYTbR540mtEtWL3VvIWfol/Sju6XDfdKVEFe4F/W1j8Pf2jkq0viaOYvkFbQ1VBOiZdHaFtujGw95NERnS1RvNnZK6180e1RVb2FoxGDUajxm5/fNwABg98BnVVtstjwWxlValCSE4aSmnZCTQVBcR6oFjgLGlAY8g4thxdQQ5xEx+wElVovsC8Nj+XguU/4te/B0E3NGwZiSxXk/lwfaK6+Oo+bhFVQaOj/LullLz3JfKocFIefZbQqwZ7Zdm/KfdBNJmoOXWMvEXfkvHOKxQu/wlBp0GmMC+ZywQZCf2vJyiuQ7OJKoBPUASdr5lKcJ8BFK74mbrM9GbXaYuvv/uE7gW5zP11ITgkArgC1/Ck74QPGYnU1w9Bp6uXkMEWrpI2eLMtlzuacg/923Ui4d5H0GfmUPLB1wg6feMHNRGBwwYSP+/5S56oAvj27UbowFQyP16Hqc5sQDzSNYG1I7qcVxCRSFg7ootHVlVo5WR1+vTpHD16lJ9++qnBcs8//zyVlZXWfzk5OQ2Wt+D0cT1TJxYTEibjpvmjCYz2bi70hqCrNfDzjJ3k7C+l4+t3EHa1e/INTUHp5pOc/Ncygnu3aVZWKmfQns6k6O1PkQYGkHz/k15ZghUFgeI1yyle/QvRXa6h48AHkClcC9W7Im2W5f3a4iySBt5aj9BW5p7k2PJ3qSnMoFuXu+mVeDsKhXmyYvEtBayE0hZ5+bsxmXRIpQrkcl+neqm2ZNQRFqusyaRDEEXSc9cTGNeewBizdIqzTFTxfceh9A8lvu+4Ru6gc5Sc2knl/p1Ejb8N34Q2dh/x5mTXMVZVkrv4CxRx0YQ9eEeDwXSpeQXse+ateh+e/1w/gn8+PLHRc2mPn6Hglfep3XWI6Am302bi4yhCG9dHdHfA8uQ+6MtKKFn7Oxnv/Zu8hV9iKCshvvdYetz5El1HziC+73hkSj9MBp3TjGLNgUQqpV232/Bt05bCFYsQvUQqQ2pr6J9tzjDjZzCw/kP3/Yb/7vCk74T0H4RUqULQ1jVIKJtKOi+VbFlNJeOeoKn30K9NWxLvfQR9Vi4lH36DoDe0UAsvH0gkEnxvuR1jtZacBTu9W3drdQOYMWMGv/76K1u2bCElJcWjY92Rrjqepmf6fSXEJcoY+79R+IW0TGYoZ9BU6fn58R2UZVbT/vWJBHWNb7FzFa1OI+M/a4gY3gXfifd51WG87tBxyj79EWVqGxJvnuK22HpDS1SCXk/Bsh+oOXWMpAE3E9V5SJPb52qZXDAZyd23kuLjWwiK70j3xJvr+aY2tPwP7klTOcK2TlsyLJf7YjRq6XzDTGpLcyhM22BNBuDKtcFTVBed5dSaTwnpO5DoCbcB3lmKFPQ6zv34X0xVNcS8NANZiOtlnNTcQja88n697d8N7c/L99/e8Hl0erNv6oadZt/UsXejDHVfUs5by66iIFBz+jjqvdupyziF1MeXiJS+RLS/Cr/w+u9xYy4qzYWmooBjy98lqFd/6jLPNHvZ99hr/0BmMySs6tSdWXc92KS6rixFNwx37s/lfg9b2h0Cmn8P67IyyF3wOT6d2xHx+KQLEnR1qaNyxTqqVq6n1/wp+MY3HBfjrhtAqwuwEkWRJ554gl9++YVNmzZ5TFTdwZEDOqZPLiGlnYLRH47CJ6jl/FEcUVuu46dHt1NVpKHj2/cQ0KHhHPbNQf7SvWR9tpHo63uhvGmiV6Oja7bto/zbpfj27kLCuMlIPdCxLFm/CkFbR8n6VXYfD2NtDXkLvkBXXEi7kQ8RkuhegJYrOBPI11aWcHbT92jUhbRPHU9C/NVOI/0dg6Yc4Sg75Q5slQCSk4aa/V1FEZNoJKJ9f/wjEsnY8C362op6yQCaA111OWc2fYtvYjJRY2+2frx9E5PRQD3ri7sfd1EQyF3zA4bCEqKfe6xBovrCghU8sn673TYT0Oe9F1EHNxzEpk3PpPyrxZjUVUSNu4WQ/p4v+fsmJlNdpW5yYgCTVkPhrz9Tc/IoiAI+8UkkD7mLsJReDQZH2QYAFp/c0awMarawnYj5JrWl+ughRKOhWZHUd+3ZZkdUgSYTVbi0JZwuBNwJxLrcU7ReiKCqpt5D2+9g/B0PkPvTl5R/t4ywB29vMUnJywWBY69Fs2MX577YRKdXbvFKna2OrE6fPp0FCxbw66+/EhgYSGFhIQDBwcH4+jZ/mf7gHh1PPlBCx65KRrw/ClXAhcsJXFOi5cdp29BW6ukw9178U1omalkURXJ/2EHO99sJGj8M5c1jvfpyVf2xBfWilfgPvYr4YXd6ToIlDn8xL6nm/jgfQaej09jH8Y9w3+/YXZSfPUjWjsVIpXIUcj+kUnmDklQNwVkmKosV1vY34FRX1XL84dxlqHOOE993PFA/et/iY9tUkmMyaDm15SukSiVxd96PRCazkggNOLVmuEsyStatRHPwOBEzJttF/jtiyesf0j8rz25bnVJB50/eaLDtosGAetkfVK/dhjI1icSJ05rsZqLJyQJRNP/1AIZKNRW7tlC5fyeC3uyDJfcNpNvomW4dH9VpkNfS/drCts6IDgMoyM9p3rKvKPLqqmV2m3oPHk7G+6832SJ1saO7HeE4Cbti2TTjYl5jaybjtt/B1KdfJvamuylY9iPy8BCCbxp1sZvXqiFVKgi8eQJl83+i6lguQR76pzpDqyOrn3zyCQDDhg2z2/7111/zwAMPNKvuvTu0PPVQKd16KRn23miUfhfu8isL6lgwbRtGrYkO70zCN6Fl8hCLosi5+ZvIX7KX4FvHEjxheOMHeVB35S9/UrVyA2FDRhIxfHyTSHDkiPF2g5gmL5u8H79A6utLl3FPoAr0bsYwwWQkd+8Kik9sJyylF7X5mej0lXYi/q6W+13BNuK/qOQItlJVGZlrMRo1ZGSuRSZTudRVLS07RVnGfpKHTEThaw52srUGW5aQGyM5rtwdREHg9O4fMVZWkDTlSWqOpzVoUbXAHZKh3reTih0bCbnrevx6ubaAv/Tjr/WI6tmIUIbPfc7lMQD6c3mUffEThuIyIkZOIGzQsGatDHhCnNR7d1C65U8UwWFo87ORSGVIJFJCkrpSV5bvsbW7Oel+3alT7uOPaDSQ/MgsZH5N06L+eOGXdr/Lff04evRQsyyjrY2IOE7C3JmUXUrW4aaSzkvpGi8kHL8ZQT36YlBXULpiFfKYSPwH9Lq4DWzl8LuqJ9oNG8j+cgtd/+/uZhvMWh1ZbSkX2l1btcyaUkrvASqumTcKhe+Fu/SK3FoWTN0GQPt3JuMTG9Ii5xEFkbP/XUvR74cIvedGAkcO9mLdgjkr1cadRI66gbDBTSfBtoNYbfoJ8hZ9iyo6jk7XPITc5/xg64k0k6uy+tpKTq76L/qacqIiu9M18Xby5XusRNNWExXcJ67nxf/V1m2ugqycuQsYDHWcOLucoPiOhLfr7/Qc7pIcV5a7nL0rqD1zkoR7pqCKiiH3x/kNWlQtaIxk1KafoGjVUgJGXE3gda59ir957wuGH7OPVNfLpA0SVdFkMqfp/W09ivgYkqd6JwuVu8RJV5RP8Z+/IhoMmGqqCUnqhvrcEUSgujCT3ve+bi3rbv905o7SXNjWWZV/GjDrujojq42RGH+thhGnj9ttG/3kC4QfPdSqLKPNhSP5cGcC09qsww2hqaTTm9fobStta7P6hl0zkjpNIeVfL0YRE4myTcvFm1zqkEil+E0YT8mH31C5P4uQfs1z6WzVagDewo5NGp6eUkK/QSqGvjv6ghLVsqxqfnhwCzK5hHbzWpComgTOvLuKopWHCHvgdu8SVaOJsi8XUbNpF9E33NksomqLysP7yF34JX4p7ek8/BE7ogr1s1M1BGdlq4vOcvy3980aq0B5xRl27H4XwCotZUlvajLpGpSpcoQl0l8qNbuRyOW+VoKbmjIKlSqE1BTnS0WiKHI0/3cEo4HkwXe6nHG6K03lTLqr+Pg2io9vJWr8LdYMVd6IENYW5pG35Ft8unUg9K4bXLb9h3mf1SOqtUoF7T9/y2XdhsISit76hMpf1xE+eCQpk5+6YOlSdUUF5C36lqxP3kUiUyBT+pF41c3Ulea6PMaT/tmSsEzwXT2LxqKhe+Weo9z3/Lu3JaU9Nb5+hPQfZJ3UtHTEtit4M1rccj0WAuL4251jWivUe3cg6HVIffwafb8d76k3r9HbklkXQoLLkz4mkUiIHzERRXwMJf/7HlNNXYu163KAT49OBHSKJeeHHc02RF72ZHXLeg2zppZy9VAfBs8bjVx14SL5Ss9W8cOUrSgDFLSdez+qqJZJ3yoYTZx+6zdKN54gfOrdBFzj3FLXFIgGA6Wf/EDd3sPE3jaJkL7e0YIr37GJwl8WENyzH52uvt+p/qQr/VRncCxbfHIHp1d/gk9wFKnJo1GpQgDsyKiFcJqj8TUIghGQEBLUuE6sRUu1feq4esTUss/iEqDTqa3JAwAKCvdTkXWYNoPuQJ1zvJ5ElaX9zrY72+9IaivOHSV793JCr76W0P7nJy3NHZQMlWpyf56PPCaSiEfuQSKr/y7FFZdydspsrjl11m77lyOvposLH1VRFKnesJPC1z5AqNOQ9NATRIwYh8SDoL2G0NBgpC8tJuvz98n65B3qMtNpM/hOek18ld73vk50lyHE9BiBTOmHRGaelNg+D0/6pyMae76ewKQzD5hSXz+n19rYJGV7u06MevJ5RMxTt0cnPWK3/2JqdrZmvdALIbvkLsq2rUfQ1CFVqRp9v929p025Pm9KZnlCwJsDT/uYVKEg4eYHELU6yr9a1GKrwZcDJBIJvmPGUn08j6rD2c2qq9W5AXgT2zZoeOUf5Vwzwper5oxGprhw3Lw4vZIF07bjH66izRuTUIY2zZesMQh6I6fmrEC99yzhj96HX5+u3qtbp6f0v9+iS88ifqL76VMbgiiKlK5fSfm2DcT0GEl8z3ENWhbdXT49n/d+PeVnD1JTdJbIToPpGjmGgsJ9AISHtrdmlILzQVIW/1OTSYcgGP6yuNrDlZSVbR3bd73TqAtBTU0hpzJ+I6LDAMJSerr0S20sKMfV/pqSc5zd8gMBnbsTOeoGt+6dOzBpNeQs/hwkUqKefACpT32pt5S8Ijb9671627+7dgD/vudmp/UaK6oo/2Yx2qOnCRh+NbFX34hU6V0ZOWfLo4bKCso2/Unlob1YrOtyqZLIDvbPztIHnT2n5izvezPoSlddhtTHF5mPj9NrtU0davvbFrW+fjx7013sTW6H4OAb3Nxl4uYs5bbmZXhHkmPbzgu9dO3JfXK3bFPcCrzpp2wh4PLg0Ba9j03pY4qQMGJvvJu8hV9Ss2EngSNbt+X9YsKne0f82kaRt2gPwb3aNLmey5qsvvx0OcPH+NLv3xeWqBadVLPgke0ERfuS9MYkFMEtkxXLpDNw6rXlVB7OJmLG/fh27+S1uoU6DSUffIM+J5+Ee6bhl9L8pAWiIFC0cgmV+3eR0P9GYrpd64WWnkfB4fUY6tToa9V0bH8T8dHmNJQW/1J1FU41UR1JqzPfU1vZKWdk1Ha/5Xdy0lBSU0ZZ/280ajmcvhCfoEiSBpjlPFz5pTbmr+psv7ayhPQNX6KKjSf21nu8JlUmGo3k/Po1xvJKYp53LlF177rtvLlwRb3tb94yhs+ud34NdfuOUP7dMpDLSLh3qtVdwduwHYxMmjrKtq5HvXsrUpWKxP43gERC0dHNDVpIvR0k5c36qrT5qKLM7hKuBl5nxOPfy3/ihqMH6Pf8W5hkMn5zkba1uQSkOQE87hDtiwXbe+1IXC90wJInz8jdshd7onChzt/U/h3QsSshVw1BvXglPl3aoYiNaoHWXfqQSCT4jhxB2fyfqM0sabIKUqtNCtAcWJICjBjrw1VzxiCVXziiWnhCzYJp2whJ8Cfp9cnIA72XLcoWJo2ek68so/pEAREzHsCni/cyYJlq6ih5/0sMxWUk3jMN34Smz4YsEI1GCn5ZQPXxwyQPnkhEe/ddFdwJZNFVl3Hi948waqtJjB9E+3YTrPsaE/h3B43V4Uzw3zZhgCgKHMz6ierCDDpf/xQ+wd6VLTNoqjn+x0dIpDKSpjzR5KhwR4iiSO4fP1C3L42oWQ/j07FtvTL//eQHbth3xP44oNf7L6EOCqxXXtBoqViwgtod+/Ht0424kXci96+f/tebwRWC0Yh6zzbKtqxFNJmI6TqMmG7XWlOiXqoQRZFDS/5NcM++DVrSHe+ln1bDgbdfBGBpj7782aUnmzu5TmntLpw9s+Y+x6YKx1/I4Bzbc4F3Lat/B/msSxWCXk/ml+8i9fcj+vnHvKplfjlBNBopeuEtQgekkvrUGLt9l2xSAG+i5/MjLihRLThWwcJHthPWJoCEf09CHtByRPXES0uoOVNExMyHnBKIJtddVUPx/32BSV1F0qTH8YltfrSjoNeTv+gb6jLTSR1+P6Ftunt0fGNLpjUl2ZxZ9yUyhQ/9uj+Mn1+E3X5Hgf/QMH98fBRotQYqymvdakNjSQIc9ztaaDPPbUCdfZx21z3kdaJq0ms5uWk+gsFAm4cf8xpRBShdv5K6XQcJf+Qep/3sq3c/Z+SJDLtthYH+XDP3OfSq+n7IuvQsSr/4CaG6lpib7iKoV3+3AoOaOkiLokjN8TRK1v6GoVJNcN+BJKeOQuHnvv94xqYfqMg6RGhyL1KH3dekdniibOEJNBWFmGqq8Evp0GA5R+vROps0qrem7Ucvk3uFrLpyQ7DomjZFt7WpFrYLKcnkeH+9eb7LRVrqciTdUqWS2Al3k/P1f83uANc1PbC5etMuqlZtJGj8cAKHeSc2pLVAIpfjO+RqStZsos3UYcj9PXf1uqzJ6oUkqvlHyln42A4i2gYS/+qkJj0Md2Cs1XHipSXUZZYQ+dTDqNole61uk7qKonfnm4NcJk9HFeVZdi1nHyNBpyV3wZdo83NoN3IKwfEdPW5XQ0um6uxjnN30Pb7h8fRudw9KhXOi1qVrPNeN6kb37okEBMgxmnRIpTJKSkrYv+8o33z7FYX5Pg0SUncttJZ9FpcAudyXrHMbie87vtlZuRwhGA2c3P4VhooyEh+cgSLEe/q9FXu2Ub5tAyF3TsD/qp72O0WRA0++Snid1m7zoqv78MzDE+vVJRpNVP62jqqVG1GmJpF0z+MowxrW023uMqA2P4fiNcvRZGfi374LHYY/jG9ItMf1VGQdAlGkIusQxSfbNkg6XZHSlkgMAKDOPoJUqcI3OdXtY8Yf3kdY3flJmgR4d8yNXmlPQ8+sqaSrqcu0tm1pClFqLeTqYi7HN3QPPE2ycLmQbkf4JaUQcO0A1L/8gV+/7g1m8msIVas2YipTU7Vq42VHVgEChl5F5W/rKFl/nNgbe3t8/GVNVi8U8tLK+emx7US2CyLulZYlqsdfWIwmu4yIp6ehauu9LE/GcjXF785H1OtpM2k6ygjP/W8cP0YmTR25P3yOvrSYDqOmERjtns6a44DvKpCl5PQuzu1YQkhSN3om3oZMVj8bWVRUEFOmDqNX7/OuDHp9DSAiCEbCw0MZPeYaRo+5ho0bN/LF5xsoKCh1Skob8lt19He16LdmZm3AIGgJa9uHmO71yXbxyR3k7V8NQHzfcR4RGVEwcXrvj2hzz5Ew6VF8YlxnkfIU1ccPU7z6FwJHDSFojPmabGf+a7fsrUdUj8dGOiWqhqJSyub/hP5cHuHDxhA+ZKRTJQFHNJWkGGuqKV2/ksqDe1FGRtN+9LQmTZIs/dAvLIG68lxCk3s1OfCtJRIDiKJIafZBAjp1cz/dsSjyf78ssNv00oTbqfVpfnZAaPiZXWjSZdsWiyuBJ0TJW+SqOaT3YhPmhu6Bp0kWLrYPbEsiZsD1nN13BPXS1YRPqf8NdAdB44dbv6+XI2QhQYQNSKV4TVqTyOoVB4tmwkpU2we3rEW1Rsvx5xahySkjYpaXiWpZBcXzPkM0GEma9ESTiCrYy5YYa2vI+fYT9OWldBz9qEdENXvXsgb1K0VRJP/wOs5tX0xkx6vp3eZOp0S1Xbto3n7nLgIDtej1NQgmAwBymf0zkkrNA31ycjKffPYswaEVTvVWLVJXjQVgmWWqzK7gRlGPf0SiSz3VwrQNmPR1mPR1Hul1iqJA+uHF1Jw6Rtwd9+PXxnuuIHVZZ8hf9gN+/XsQcud531/LzN9nwa/0PWevP5oTHsK4N/7p0EaRmq17zZJUtXVmSaprR7tFVJsC0WSifOdmMj96i+oTR0gaeDPdx89qElGF88TTqK2h3wPvkjrsvkblqlztd1cz1xPUFGeiLysmqKf7/t/zlv5om+UYjUzOkgsYBHSxNEubIqnkLRmm5shvNVe6q7nyWg3dA8d9jd2vS0WztimQ+foROWwctTsOoM9yrc3cEAKHDSR+3vOXpVXVAmnfQdSeKaI2s8TjY69YVpuBvLRyFj66nagOZqIq863vo+cNGGu0HH9+Edp8NZGzHvFq1gxjaTlF73wOQJtJM1CENn0Z2WLJMNZUk/Ptx5hqa+g0+nH8wtwXdi9M2wCiCBKJU0IgiiK5e3+j6NhmUtqMJDlquFMSGBUVxAsv38SWLeuYMmUy//znP5kx4wnk8JcLgBxBMCGXqZDKFPznP+8wb97bzJ//FQsW/MjYseORSdwngLaZqmw1VaVyJe1GPIhUbk+mLVY7/6hkTHnmnPPuWt1EUSRnzwqqju8l9tZ7CejoPbkybWEeuT9/iap9CuFT7rQLGIgeMQj54lU8bxLsjvmlXzeeemyS3TZTTR3l3y1Fs/8o/kP6EXfNbUhVridyzbUg1WVlULRyKfqSIoL7XU1K+7H1kkx4CkdrqK3vqivS2RLZqlwhP3sHirAIt5U6EspLuPHoAbtt9zz0REs0rdXBUyu9Ny2azbEoNtca2VzrcEP3zZmf7qVCRFvCYh3cewBl+7egXrqGqH887JU6Lzf4du+IPNCH0g3H8Z/imRrQFbLaRFxIonrsuUXoCtREPD3N+0R13udIpBKS7puOIji0+XVWV5Hz7SeYtBo6jX7cqY9gQ8EmtgTBcZ8oCJzbsZjS9D10aHc9EomUHbvfJTlpKGp1FkUlR4iO7E7XLhOZMnUYRUW5TJkyGYPBwFtvvYVUKufxxx/D7AJgQqk0R6B/8MF7zJljTqM5depDbNu2h08+Xshbc8xSTLY6rEajxqkbgG2Alclk5MzZVYA55Zwz0pS3f7XZopqns0vh6Q7yD/5hzk414TaCevT16NiGoK8oI2fh58ijIoicPtlOlD+2uIydi1fhOC34eOxQ5t4xwW6b9mQGZV/8jKjTE3fH/QR2dfB3dYKmDqrGmmpK/lxBVdp+fBLa0PmGp/CPSHD7+IbgSDxtfVehaYFW3oKuppzqY4eJGnuT2xHIc3792e73/oQ2nIj33gqNt3Ghl8Btz+dN/8rmkLgLEZx2sV0NLgZawn9WIpMRNWQc+Yu/RZueiU/75qUXvRwhkctR9e5B6ZZTJD001GVwrTNccQNoAixL/xeUqLaERXXe50hk0mYTVcuHtGzrerK/+R+CTktnF0QVmpamUhRMZG5dQOmZvXTudDsJ8VfbLb0XlRwBRIpKjtClazy9erehbdtUZs9+0VrHnDmv8/HHH+Pv709wcAg+Pgo+/PA93njjVWuZ2bNfJCkpji5dw/DxOwGcX+I3GjXI5b5O3QAsMAkGijSnkUjlSBUqBKOx0SxFnmQzKjiygYLDa4m47nq77FTNhbGmmpyfPkOqUhI180GkvuetoC/89Bu7np9Xj6j2nzfbjqiKRhPqpWsofnc+8qhwkh95xi2iCp4vuYqCgHrvDjI/eova9JO0GXwnXa+b4TWi6uyZhCb3AonE/LcF4U5/KDyyEZmPL8EutFGdYd5112OyGRzua0VWVWfL1c6WwFsya5Tt+byZickTuLq+proDuLP03pqzhLUUWur5BnTujiI+hqrfL24K5tYMv77d0RWoqTtb7NFxV8iqh8g/WmENpop/5b6WI6q1Oo4/b2NRTfJe8IwdUb23+RZVy8eudONqRIOBTqMfb1CeqSG/P1siaxm0i05s4+zmH6jIPExcdF/OZq4jL3+31YfUrABg9hENDIjjulHnJXhmzpzFSy+9av09Z84b/O9/H+Pjo+LDD9/n9dfP73vppVeZOXPWX2lXYfyEgdbz8BdVk8lULpUABMHE4azF1BRn0WHMI8iVfi59UeP7jkPpH0p833Fuk/ei41vJ27eS8KGjCB/ivUAdk1ZL9uLPEbQ6omZNQRZ8Xhv1/c8W8MjabfWOGfj2sxSHn3cZMRSXUfT2J1T9sZmIEeNoM/FxFMEhbrfBE382bWE+2V9+SNHKJQR26Un3m2cT2WEAEon3PmfOnknqsPusvqsticb6g66mgtL03YRefa1H2b6OJSbz7YChiMC/x96M2Io0IS3fkKJVS61ELXzISKQ+fgh6nXVbSxIrWwJzsfwrXV1fS5Lni0XMLya8/Xwtk4zK/buIGDAS7dHT6HMLvFL35QafTm2R+aso33HGo+Mu66QA/9h+PaqA+oE3TUXB8QoWTNt+QeSpjj+/CG1eRQss/VdQNO8zG6Ia0uw6y7atp3TDaqRKFV0mPIVP0HmdU081Km1dBCyDtkSmAFGgW+e7OH1mZT3B/Q2bX8JCVlWqEI4fO0VQsC+CyYDRpEMuU/HRfz/gjTf+bT1PSEgIarXa+vull/7FzJnmACGjUYMgGCkpKWHAgGEMHvhMo7JVgmjicM4y1OeO0G7kgwQndHZbW9OdciUnd3Ju5xIkKhWRXrSqCgYD2Us/R38uj+jZj6JMPO9f/Psr79M9t9CuvEEq5ap3nqfcRp6lducByn9YjizQn7ibJnkliYTTtur1lG3+k/Idm1BGRJLS/3YCo70XWGYLb+miNqUeZ8fYblNrcqg9fZy2M19AqvJQy1kUQRDgryC31rIErN67g6JVS0EU7cT/HRMCtJb2thQu9+u7XGHbT9s++QIZ/30dn24dCX/g9ovdtFaJ2m+/QldUSY+PJl9JCuBtFJ1Us/CR7YQnB7QoUTXV6Tjx4hI0ueVEepuolqspeucvH9V7PbN8uayzppqqQ3uR+weaLapB9oL8Vj+/zIPsc4O02vkJigI5e39HFIz06HIvERGd0eur6wnuR0d2p6gkDalUQb8+NxIUbJbhMZp0gIjRpGP27Ofx9fXhxRdfALAjqnPmzGH69OkYzGIByOW+GI0aIiMjaZfaC2g4KYAoCqTl/UpFVhqpwycTnNC5/rU0gMbKlZzebSaqShWiTkf5tg1eIauiyUTuqu/QZ5wj8h8P2xHVjCmz630c/ujZmWlPPmD9LWh0lP/wC3W7DuJ3dR/irr0dmc958uTNgbf2bDpFvy3CWFVJXK/RxHQfjlTWcp8vbwVKNUVf1dm5LfUUHFqLQVtN1Nib3SKqgXU1fPjztzx+zxQ0Kh+QSKxEFVqP9qVtWlVbC5+jz+WlFMQD5slg+Y6NqPduJ7BrLxAEqo8dJrB7b4K69Ubm64c8MMj6LC+16/MUlzoZd9V+234qkckI6TWI8u3rCb1zAlI/78jCXU4QU7tTs3UJhioNEpl7KzxXyKobKE6vZMEj2wlN9CfhtRYkqho9J15aSl1WCRGzpqFM9o7/HYCxooridz4HUfReMNVf8lSCTkunUfWJKpj9/CyE1ZPgFFEQqCnOAsFEXEx/Tp35HZ2+yilp7NplIl0xa9vFxoVYt0ulMgTBiFQqQyaVMnv2bN55Z54dUQ0JCWH27NlotXoMBqPVGmux1BqMDfvVWIhq+dkDtB16r8fZuRpDafoezm1fTEi/QSijYynftsE6cDfnwy8KAnkbfkJz+ASRMybbBQOccUJUPx19DW9NvN76W5eVS9lnCzBVVhNzyz0E9+xX7xzNIUKWawsdcA360iIqD+zGt01bOg5/GJ/glsvB7e1MU97SV7XUI6rkKPxUhPS92q3jfv30PeKq1Bx4yzxJe+i+R9jZ7ryU18XQvnTVb50RtUuJvBlrqtGcy0CTew5dYT760iKM1VXW/erdW+3+b/tb6uOLMjwSVXQsPnGJ+Ca1RRkZ7TQA5VImfK1lctRUuGq/Yz8N7n0VZZv+oG5vGgHXNi3F9+UMny7tQYTKQ9mE9E126xiPyerChQt56KGHOHv2LLGxZkvMgw8+yP79+9m6dSvBwcGeVtmqUZJRxYKp2wiK8SXx35NbLoWq1sCJfy2jJqOIyKemokrxXpSuqbKa4nc/RzQaSZrkXpajxj6Iprpacr/7FFNdTYM+qmYr6n127gCNQRTNUf/lZw+iUPhRXHLEZRS+I7Rag/X/gmCy/jUJAnPnvm1HVMFsYZ07dx5PPvk0gB1RBaipcZ2OVRBNpOUupzzzEG2H3ktYW8+FjhtCafoesrYtIrjvQKLG34pEKrWzqDb1wy+KIiV//kbt7gOEPzwR356drfv2PvVvHB1n5t1wHf+7eZT5WEGg+s+tqJf9gTIxlsSJ01CGO3/2zSFClmsrWfsbUoWSNlffTkRHz/xSm0I8vZ1pylsW2qhOg5ArfTm7+Qfi751qp9TgCh0K8oirUgNYg+P2OWS6uhhk8FInLLbQl5dRfeQA1SfS0BXmASD19UM0GAiMTiWs5zhqy/JQZx0mstMgJBIZxSe3E9nxakKSumHU1WKoq0JfU462spiavBwqD+4FUUAWEEhA+84EdumJX9sOVn1ix/t3KZHXSz0xgLvtVwSF4NOlHbW7D10hq04gDwvBJy6EqiM5LUdW77rrLt5++23efPNNPvroI1555RXWrVvHrl27LjuiWpZVzYKp2wiI9CHpjcnIA1uGqAp6I6de+4WakwVEPD0FVTvv+fyZqmsp/r8vEDVakibPQBka7tbHraEBxaTVkvvjfIxVlXQa85hbKSwtpLUxiKLI6T8+p7ogHalUgcFQh1zuaw2k2rD5Jas8lTNUlNdSVakhKNgXuUxl9VmdN2+uXTCVrc/qiy++gFar58knZ1mPkUplFBcXE+hfP5rd7L+6GZl/AHUVBbS99j7CUszlvGWZO09UBxA94Tan8kRNzpm++U8qdm0m9N6b8B/4F8EWRU4/8iIqk8mu7NruHaxE1VRVQ9mXP6M9eprQQcOIHDG+QdLUVCJkqqtF5h+AsbICJBJiu40gspN7lkRbOCOejT2flsg05Q0Y9RrO7V9BQKduBLTv3Gh5iSCw4rP/s9v28ZCRGNzNdNWCuNQJiyiK1GWcpnznJuoyTiFRKAno2JW4DtcSGNuek79/iN5Yh1ZdRET7q4hoD20G3mI9PrbnSIpP7uDMui+d9kOTQUdNcRZV+acpP3eMyoN7kAUEEdJ3ICH9B9e7f62d/DuON62xje7Ck/aHtOtL4YqfMamrmpyC9XKGLDmV6mM5bpf3+MslkUiYM2cOt99+OzExMXz00Uds3bqV+Ph4cnJymDRpEsXFxcjlcl5++WXuuOMOT0/RKlCRU8OCqdvwDVaS9PokFEEt43ciGEycev1Xqo7kEjHzIa9qswl1Gorf+wJTdQ1Jk6ZbLWDufNxcDSiCXk/egi/QlxbTcfRj+Ia6L/jvDgqPbKC6IB0wZ5ZSKPytQU2WQKqikiPWZX9ngU9HjuQweEgHpDIFSpmCDz6wl6eaM+dNZs9+lrlz5/Lii2Zpq9dffxVRNKsHKP/KhpWZoXNqyc3K3oxOVwm6SiI6DiR3728YdbVEdRrkFctcyaldnNuxmOC+V7skqtA0Mlixawtlm/4g+JYxBI4wHztzyUqeXr2lnjTV8/fezIIRZpKoPX6G0i9+AkEg4b5p+LfrZC3nLcuOeu8OSjeuRjAakUilyFR+mHR1lJzaRWzP6zyuzxnxtDyfvP2r7UirLYntcedLTb6GxoKjmhpol3lqFYJeR9S4W1wcbY9/rVxq99sEfHjdBOeFLzDc6bet1VqoyT1H8R+/os3JQhWbQPKQuwhN7oFMcd41zNLv/KOSSVv0htPn2dB3QqZQERzfkeD4jiSI11NXlktp+h5Kd2yifPsGQvoPIfnRfyDz9QO8Q/5t7zfgtXtvGzjXWsl0S8GSrEVz+MQV66oTKFOTqNh1AJPO0Hhhmuizev3119OlSxf+/e9/8+eff9K1q/mhyOVy/vOf/9CrVy8KCwvp27cv48ePx9+/eZlkLjQqC+pYMG07Cl85yW9OQhnaMu0XTQLpb/+O+kAWETPux6dTauMHuQlBq6P4P19hKq0gcfJ0VJHnrZ/ufNycDSii0Uj+om/QFuTScfQjTdK0bGhALk3fQ97+VYSFdaSqKtvcjqAka9pTcyCVWfjfAlutVQuxXLf2KIOHdACoR1RffvlVnnzyabRaPdOnT0ej0VlVAizlZs6cZa0H7AlxdFRPUClAB5GdB1OZfdyO/PhHJUOx+9monN2f7J1LCek/2Lz074FocmOoPLCb4jXLCRx7LUETzPmn3/30R+7Ym1av7KC3niEvKgLRZKLy13VUrdqIT+dU4sfdhzzQbCWwDHCCXoegqWvWYFS+YxMlf5qTMEjkCrrdMht19rFmWTmdLcFbiITJoLMjC95a/ndWj7t1uypXVXCGyn07iBp3i1u+5nKjkbv377TbNvKpl5t4RRcHrc1aKBiNlK5fScXOLaiiY2k/eipBcR2dZ8/7q9+lLXrD6fMMD/LjqnF3c27/eiQx3eodbwuJRIJ/RCL+EYnE9xlH0fGtFO7fTNWhvUSOvYmgHn29Yq10lMzy1r0v27bempHwUrWkNxUyP39U7dqgOXrqCll1AlVKIggimqxSt8o3iayuWbOGkydPYjKZiI4+T4JiY2OtfqwxMTFERERQXl5+SZHV6mINC6ZuQyKBlDcnoQwLaJHziILImXdXUb4jnfDH7sO3W9PylzuDoDdQ8tG3GPKKSJz0GD4x9hqtTfm4iYJAwbIfqctMp/11DxMQldyktrkakM/tWkbJie1IpDIiwjpSW1uETqe2iv1nZW9h8MBnrBZVCyzpTU0mHXn5u4mPG8DxY3kcOniOoGAjc+fOsZZ96aVXefLJWTZ+rdK/5KqkVqI6d+4cbrjhJqoq5Rw/bvZBsxDijLN/cjpjJUgkdBw/ncDothSHxNiRH4ppsmWu8NhmcvesIHTgUCLH3ORVolp19CCFvy0iYNhAQm4fh0Qi4fVvl9YjqgIwcO5siiLCMJarKft8IbqMbCKGjyNsyAg7K69lgJP6+DVJp9FCdgM6dkO916LlKiGx3w0o/c67FFUXnvVa0JOFSNhOmqDpy/+Oky9n9bhbt7NyJoOWM5u/BZncHMlvA1fWx53v2BPTk5HRFIY0P6DyQsITa2FLW2GN1VXk/fQVusI8EvpfT3SXoW5lDbN9nj1SYxl3dWd6to8nJPD8Kp26WsPh9DxW7zxBWkbDupxylR/xvccQ1fFqzh5bQeEvC6g9c5KYG+6w6u029V44cy3wBrm0rbc1TDouNALiO1K+ezOiILidae7vAkVcNBKZlLrMErfKe6yzeuDAAYYNG8Znn33GN998Q1BQEIsXL65Xbv/+/dx///0cPXrUk+q9gqbqrNaW6fhhyhb0dSbaz5uET2xIi7RPFEXOfvAnRWvSCJ96N/5XuZflx626jSZKPv4e3YkzJNz7CH5tmq9DKYoiRb8tpvLgHlKHT25WxLszy2pdeQHHf33XWkalCiEkKImikiMEBsShN9Ral/mdLftv3/VOPe3VqKgg3n7nLrZsWceUKZOZPftFq8UUsNNglf7lKjB37hy+/PI7hg69juee+YniYnMkb17+bjLPbUKvrwZEFL5B9LzrlUavy12IokhB2nryD6wmbMgIIkZOcElULYORb2IympwstwaBmlPHyFv0NX5X9SL8oTuQSKXs/McbxKmr7coJQMoXb4NEgubwCcq+XIREqSDulsn4JdV3T2kuSch4798Y/woAUkREQZ2O2J7XWe+fxTKFRAKiiNI/tMGJQFOfgbvHOdMMtrSxsbY1FemHF1N5YBeAnf4o1NcgBeh17iw/ff1fuzq6vvwOJhu5qssNzu4DmPtnyfpVIAH/1I5uvy+WY8u2rSek3yAqD+5G0OvpMPwh/CM8C3yNDgtkxm1D6Nu58eP2n8jhv0u3UVRe3WhZgLKzB8jasRhVZDQJ901D5ufv8l5cwcVBXdYZcr75mJhXn7KTBrwCM0r+PY/AzvEUr0nzrs5qVlYWEyZM4IUXXuDuu++mbdu2XH311Rw4cIA+ffpYy5WXlzN58mTmz5/f9Ku4wNBU6Vn42Ha01QY6vNOyRDXr840UrTpM2IN3eJeoCoI1ACbh7ileIaoApRtWU3lgF8lDJjZbmsnWspW26A0iOw+i5MQOFH7BiHodICE5aehfS/+ilahaXAGsVs7MtVbSatlvq71aXFzFm6//yrPPj2bjxk20t/GxBHsNVqVMwRMznmDs2FHExCTy1JNv8PuqzwEID21PReVZjIIBucoPiUxGbM9RLq/LU4iiSN7+VRQe2UD48LGEDx3VoEXVYs2srlK75QdWm3GKvMXf4NurC+EP3o5EKuXUlNk4hgqW+vvR98NXEI1G1EvXUP3nVnx7diZ+zD3I/JyvjDRn+VGTl41gMmcKC03pRdtr760X6W/r+1dbnGW1OLoil+4utzuSTseMUa6Iq1Uz2EZ+rSUDsirOHaXywC4Cu/dBk51Zz9LlzPoYrKnDIJUiEUVkosjMOya5RVS9YZ28WH6mrqywZdvWI2jrAKg+dsgjv8nzWfnWIA8IpMvYGagCwz1qV4ekSN6YNp7iwly3yoeq9Hw061Ze+nwVp7MbtzaFt+2Db3AUp9bNJ+e7T0l6cPolH7x2ucEnLgmkUvRns6+QVSfwTQxHm1fuVlm3Lavl5eUMGjSIYcOG8emnn1q3T5gwAZPJxJo1awDQ6XSMGjWKqVOnMmnSpCY0v/nw1LKqqzGw8JHtVOTW0nHeffgl19cL9RZyvt9OzvfbCb33JmuAizcgiiIV3/9CzZY9xN0xmcAu3iHBFbu2ULxmOQn9byCm27Am1+NIMCwWKYlUhlzlR/8ej+LjE2Itb7GgKhX+VNeYl+NVqhArMTWZdBiNGjtrqjNk5y3k1VefY/jwESiV5106HC2ren0NGzas57XX5pKTk4tOp/6rpAQQkUhl9Jj4LxQ+3nMLEUWBjGPLUe/dTuToGwkbNKzRYzyxrNZlnSF3wXxUHVOJnDGJsNo6DsyaUy/H8gv33siPIwZjLC2n9LMF6M/lm7NkDRzqVVcEMCciKNu2nrJNf+ITG0/qgLvdUpNwltkMiYSkgbe6Fchkuy971zKrH12/B951WrczS6mn2diaA31tJcd++z98k1Lwa9fRqq/rLgn00WlRGI1U+7vXX9PffglBW4fUx4/2z73RpDa3Nqtecy2rxWt/QzQa6HLD0/iFeZbuOjoskI9m3crWTWt5+IHJzH7+RZ58+h8uy3/4/v8x9605fPHNd1wzbBRPvLfMbQtrXXk+J1f/F792nYi7Y7LX31lXaGxy0lqD5FoKrq737OdzUXVIIWySe8GRfyeol65Gs2c/htJq71lWw8LCOHnyZL3tK1eutP5fFEUeeOABRowYcdGIqqcwaIwsenInZedq6Pj23S1KVPOX7iXn++0E3zrWq0QVoHLZH9Rs3k3MTXd5jahWHT1I8ZrlRHcb1iyiCvWtXjE9RpC79zcEk4Eene61I6pwPmOUWQHADMvSv8UdwNFX1RlkkrZMmTKDm2+cyt13T6Rb9wSCQ/ysSgGV6jqOHslk4cKfWb5i/l+W2rZkZK5FEIwIggGJTEFCvwleJaqCYOLMwUVUpe0n+oY73BZ5d9eaqcnOJHfhFyhT2xDx+H1IZDIOzppTL+J//EvTOZaSRN3BY5R9tRipnw9JD85okZSp+ooyCpb9iDb3HLE9RhLbazRSaX2rnzPSadt/bAmnrRW1Ieu27fGWRBUWzV/H41xZSlOH3UfxybYUpm2g+OQOr+inOoMoCKTv+RGJXEb0jXdy7vP33Qp46ZKbzfH4RJBI0Kp80HqSu0Ti8LcJuFBWPU9IUlOJt1/b9ogGA/F9xnlMVAFm3DaE4sJcHn5gMgaDgTf+/SqAU8L64fv/Z93/8AOT2bprLzNuG8LL81e719awOFIG30XGxm+pPnaYoG69PG5vU9BYEFxrC5Jrabi6Xp+wOPT5RRexZa0X8ogwDGXuTcq8Krq3fft2fv75Z3r06MHy5csB+P777+ne3btZfbwFk0Fg6T/2UHhMTce37iKgfUyLnatoTRpZn20kaPwwgv+KxPYWqv7YQtWqjUSOvpHg3ld5pc7as+kULFtAUI9+JPS5vvEDGoHjcqlEKkMw6pHLfampySc4yLlPl60CgC0hjY8b4FQJwBEWcltSDB9+8AcAoaH++Pgq0GoMVFTU1vODFUQT5bIySk5uR6pQEZzQmaKjm5FIZV4hKILRwOk931OTfoLY2+8jqJt3kwlocs+Rs+BzlG3iiXzifqRKBenTnq/HQ167bSxHE+NR//y7edm/d1fiR99tlcTxJqrS9lO0cikyXz86jptOYLRriTZny/m2/ceWwNqSyoYsq44uBbYWWVs05s7hrstAc5B/+E80586SeP9jyP0D3CKBv3z8DsHaOv55671o5XKOx7epF5DVECJHjG820bxQGpotQZIcCbB63w5kvn5I5QqX8lOu0CM11uqjOvv5F61E9I1/vwoSCc8+OxuZVIJJEJk3b651v6V827ZmVZjuqbEcaSToyoLQ5B74d+hK6fqVBHbpcUGCeRrrl63dJcHbll9X16sMj6T20Jlm1385QhYWbJuDp0F4lawOGTIEQRC8WWWLQTAKLH9uL+f2ltDx37cT1DW+xc5VuuUUGf/5g+jre6G8eaxX667Zvh/1opWEDRnp1jKyO9AV5ZP/89f4JafSrtcdXl9WqivLJXvXMqRyJUajhlPpK1Crs5wK/dumUgV7GSlnvqquYLHEAqSmjLKS27z83ZxK/w2L4kBUZHcOZS2iOv8MIEEw6KjIOlzPiucKjQXrGPUaTm37Gm1eNvF3T3FL4N0TaPNzyFnwOYqEGCKffJCr0rNY/P6X9Zb+r3ljFmdVKkrnfYo+K5fIMTe1yLK/oNNStHIZVWn7COzeh9QetyJXNqxZ7MwP1JFEOiOVeftXY9LXkbd/tcvnVJV3CpO+rskSVbZtcyTV3kgIUZl3ioJD64gYPha/5HZA4yRw1LHDdC42k5oF33wMQKdX/s9leWe4lMTaW4IkORLcmlPHCEvqQdHRzR5Lmo27+vw7bbGkWgnra6/gq1Iwe/Zs5s6dyxuvnQ/UfP755+0sr+Ou7uw2WQVIbD+Sk6c/pC4zHf9U76nLuEJjfaa19ylvW35dXa8iJAyhshrRYESiuPhJOVoTPEmW0Crv3JYtW3jnnXfYv38/BQUF/PLLL9x8881eq18URFa9dpDTGwvo+K+bCemT7LW6HaHen0X6278RcW0nlDdN9CoZ0Bw+Qfk3S/C/pj8RI8Z7pc6yreso3bAaeWAwHQfdj1TmnS5iGdgL0tYjlcnxDY7GXxZKSYlZLcJW6L8h2FpTBw98ptH0q7bHGY0a6/8tx1kCuUBCbHRv9hz5DKO+DrmPP0ZtDUgkhCb3sgvwcec6nQ1uBk01JzfNx6AuJ2Hyo+iLCsh4/3Wvzey1Bbnk/PApipgIop56iNcWreShLbvrlRv+71mcKlVT9sVPSJQKkh6YgW9icrPPX689eTnkL/kOY20NKdfcTXi7fm4d506wmjNiKJjMkmSCUVfPGmZ5LjKlH0r/UJfPsjHC2ZDLQGMBXo3Vraup4OzWH/Fv15Gwa9wkWqLIR4u/tds0b+QEj6yqjmjtvoYtQZJsCW75ri0YyksxhSY3KYCuZ3t7w8eTT/8DJBIrMX3xhRd4Z948u9TPL7z4Ik/aqJU4q6cx+EcmIQ8KofbMqQtCVi8UvNkfbeu6UJZfiy61qbIaecSlJSHX0pAGuO9a1yqFv2pra+nZsyf/+9//vF63KIqsfecIab9l0+6ZCYRd3d7r57Cg+kQ+J1/9heA+yfjeNcmrSzO6M+co/fRHc8T2sDu9QoIFnZbSjX+AKGKsrqQs44AXWmpGTI8RKP1DUfoFYairpkfqnVRVnY+SDQyIIy9/N9t3vUNefn2CZUFIUBIg+etvw7Ctz1JeKlXYWWKTk4aiUoUQF9OP7PwdSGVyutzwFHG9x6D0DyVp4K2kDruPHne+5JZlxXKdjoObtqqU4398hLGmmqQHp+OXlFJPiLs50BbkkfP9J8ijw4l6ego7X3y3HlEVJNBn3mwO7D1MyQdfo0xJJOXhf3qdqIqiSPmOTZz78kNkvn50vWGW20TVXTguxwNI/8o8JgqmevsszyW+7zgrASk+ucOtel0hqtMgu37h6tk71p23fzVpi96wO79gNJC+/VskSiWxt97r9rdi9h+/2v2ulSv4yl2i6wLe7JeXCkL6DyL16ZcJ6T+Iih0bAajKO1nvGTeG8CA/Ox1VC559djZz3nzT+tuWqM55802ee8EckGbQVCMY9ACEBvoSFuS+S45EIkEVE4++9PLyj/Rmf3S0plqeeUtBvXcHBcsXAiDU1rXYeS5VyAL8iLiuq1tlW6Vlddy4cYwbN65F6t766Un2Lcig7ZOjiBzRpUXOAVCXVcqJl5bg3z6agAceRCL3ns6hoaCYkg+/QdkmgYTxk5A0U0PRPNtch1Tpg0QiQUTi9rK3u4jqNAiFTwAZG79FLvejQp1BctJQ6xK83lDrlg+quiobEP/6a4Yz7VWwt8JaoFD425WJje2HRqsmO2cLock9SB5yFzKFqslSVM6Oqy3N4fSGL5D6+NJmypMoQsMA7/l0WSyq8qhwomY9zLFn3iRIq7crIwJJ771E2fyf0J7IIGL4WMKGjPS6b5uxtobC5T9Rm36c6K7XEt93vMfWeUfBfkf5Klfi+/F9xzmVugL75+IqsxB4LzmAMzhmz8retQyAyI5Xk3F0GbqiApKmPOFSKswRYdVVPLhri9220TNf8KjdztDafQ1bGqGDhlOyZjnBCZ0aL+wAH5Vz9RmZVMLs2bPrWVRDQkKYPXs2Or0Rk1EHoojJqEOqUALg66I+Cxz7ncqoQmNSN3jMpQT13h0Ieh1SHz+n/dFTq+uF7ttl29ZjqjEHEAla3QU556UEiUKOz813wrpXGi3bKsmqp9DpdOh05ztCVVWV03J7fjzDtk9PkvTQUGKu925Qiy20RZUcf2ERyshAgh95GKlK6bW6jRVVFL//FbLgQBJvnWL9qDUH5tmmGoD2o6eiqy53e8B2Nxe6QVPNuR1LkMgUGI111mV8wM7vNCt7CyFBSWzf9Y4d+bQQ0pCgJNRV2FlHHUmpK59WR/9Wvb6Gw5mLqS46S0K/64nuNszOQu2NnO6VeSc5s+k7VJHRxN/zMHIbKSFv+HRp83PMRPUvi+qpp1/Hz2iyK1MUGEDPGZMo/fdHiEYjCZMexb+td1YUbAcLZVQMBUt/QDQYaHfdFEISmzYZtLVumgw6TPo69Jlq4PwEytmkwHGbYDKSf2gtJSd3ENlxIDHdRyCVKxokpE2dpLjjL2urMWyrZoAoUHlwDzE3341PnPui81vfe83u97HoOMoCg5u9bNrafQ1bGmEDh6LetQWZwlGNuHFoXeQ5Nwkic+fOtSOqYLawzp07lydmzkImV2Ey6pDJz8s4aBrJm+7oeqKlBpnvpZMxsjGUbVuPoKlDHhzqlWC6C923w4eMpGzLWozVlYgG4wU77+WIy4KsvvXWW7z22msNljnyWzbr5h0h7s6rSLhrYIu1xaCu48Tzi5HIZYROn4bUr+FgEk8gaLSUfPAVCCYSJ07zWtS2b2Iy1ZUVhKb0JjjebE1wNeA6EjN3c6Hn7F4OiLRNGkFu/m4rabRE69vCNuDJ1rdUp1OjrqKerqotKW3Ip9X2/xUVZzmavggR6Dj2UQJjUutda3Nzupem7yVrxyL8UzsRd8cka0pEb8ES9a+IiSBl2j2cePK1ehH/Tz54Oz/oDVTM+xxlSgIJN96PIijEa22wDBYl61ci6HT4Jrah/cD7UPo3/Rz+Ucnos9T4RyVTlXcKAIlMjsInoMEJlL5WTWXeKaoLzlBbmo2uqgxLqGn+oT/JP7yOwOi2+P4lReROGldPg6YEk6HR6HHb9ySkTXeyd/9K6IBrCO7Vv9H6Lbh/+0bmiyJvA88BjwK3PWoOzvm7SQa1BPzbd6b8ZBoJwo1O5dVcoayqDnW1pp4rwLx59sFUISEhVuL64gsvoNEZePKpWXbGh4pqDeVVDS8d2068BJMRbV42YYPs1WZauw9yQ7jUFQdC+g/Cv0Nnzr7/Om6HvV+BU1wWZPX5559n1qzzzulVVVUkJp63UJzeVMDvrxyg161t8J1ybYu1w6TRc+LlJRhrtEQ8O92jSLfGIBpNlH78A8bSCto88ASKYO84ateeTaf62GGiOg8haWDjosXO9FJd5UL3j0rm4I8vIwomBKOOzp1uJza6N20aiN4/H/CEnYZqQ5H/toRXrc6iqKTSpU+rIJrIOreJrHMbCYxJpe2196Lwc/6cYnqMMFvMDLoGdTUd74EoihQcXkv+wT8I7jOA6Am3N9tVwxF12ZnkLvwcRXwMqQ9P5Phzc+uVGfnCY+zauJu6nQcIGXANUaNuQCL37isfetUQSjeuQdBqiOk+gvg+Y5F4MLg7Q21xFogitcVZ1qV9V+TPUFdF2dmDlGcepK40BwCFfyjRIZ0IiBlCTW0RxcVHiI7qia9fOHnqwxQfN1vg9VlqO3eXxvRdG0o0YGmnZYm/sQlOVKdBBMV14PiqD/BLaUfk6Bs9ukfdCnJ5AjgHvA2se3imNaiqoQH8UiYuF7LtIf0God67ndLTuz22tB9Oz+PaPu2sv211VMHso2pRA3jxBbPbxhuvvQKiaKcGcDg9r9Fz2a4ElGceQtBpCejUza6Mq8nLpdAXLnXFAQDRZFZIau538e+Oy4KsqlQqVCrnVqtz+0r55Zk9dBgei+9U78swWSAYTZx6/VfqssuIeuYxFNHeSy4giiLl3y1Fe+osifdNQxXtnbRt+vJS8hd/i19KOxKvcm+wdCRmDS3Hpi16A5PebBmQSOXERPVyWqczOSpLhiqLddWZBdYZyirSAfGvv/bQaCs4krWUmuIsghM7oynPpyL7aIMWMHesq7b3QBBMnDm8hKpDe4gYPo6wodd5X/orM90s+J+SSIfJt3PouXl2+0Wgz3OPcuz75RiLSom99V6CevT1ahvAnDK1Ys82JAoFqcPuJyTROzJcjpqqjvddFEWq8k9TcnI76pwTSCQSghO6YJCXYTDWITWKdGh3XhvY9v/xsf05oJtPZVU2IYldqSvLazCavyGXAdvyliAcR39bVzDqNJze/CUyX39z1iGbyYxt5qXIEeOdDsbP3Hw3N5YUsaIon8dVKr6ySeLQ0AB+KVtdL2TbVdGxBPXqT+6BlQQndEIVEOb2sat3nrCSVUei+tIrr/HEzFno9EaemDkLjc5gtbg6Jg5YvfOE2+csOr6NnL2/ooiIqjc+NJSO9lLtC5cSRIPZRVHSiP/xFTSMy4KsukLRqUqWzNxJYp9wQp+6C4msZcQPREEk4701VB46R+TMKSjbeFezteq39dRu30/MLffgl+IdX0NBpyVv4VfIfP3oMHBSo7M+20HYMQ2lK8T0GEHOnhWIJgNtEq5xSdqcLd3bEtimQBCMdn6vhUWHOXV2BTKFLx3HPc6ZdV879TF0tK55EnBj1Gs4vfM76rIyiLnlHoJ7ejcCHqDm9HHyF3+DqkMKKfffRtqzb9crM/qu60n78Fuk/r4kPTQTnxjPM/A0BFEUqdy3k+I1v6CKiaf9oMc9Gswbgyu/UcFkpCxjH0VHt6CtLELhF4RcpiI5aRgymYIMziCX+zr1ebYgv2AvWp0akBCc0Il2Ix+07nNH39UWnpa3Xodg4vSu7zDWVNPm4Zn13Hlsc9q7JBJyOVumPME3i77lqTsnN3g+W7T2ZdOG0FjbvW0pjBpzE5qsDE5v+ZrO1z3eqD6wBWkZBew/kUOoSs/ct+ZYt7/0r1d58qlZaPXn/VCffGoWiKKVqM59aw7X33Qz5TqlRxqreftXgSAgaLX19rmavFzKfeFSgkljlkz0pkvg3xGtkqzW1NRw5sz5jA+ZmZkcOnSIsLAwkpIalyyyYOk/dhPWJpDo5+5Bqmy5S83+egsl644RPu1ufLq0a/wAD1C78wCVv64lYvg4K/lp7kdZFEUKli/EWFlB5wkzkasa9311J4DEEeFt+5B/YDUhqX1pG3udy3LOlvjdtaQ6IjVlFBmZazEaNX8R4E0UG7OpyDxEWNveJA28DbnK9UfD0brmbsCNrrqcU5u/wFhdReKkR/BL8W4/AKg+doj8ZT/i270jR3PyaetAVEWg55hrOPLzSny6dSBh/CSP/Zob61uCXk/RyiVUHd5HSP/BtO18o9e0eF3BZNRTemoXhUc2YtBUE5LUlc7JN3Dk2I9/Wd83IZOpMBo1qFQhqKuy7VQlbCc+5olRFUik6KrL7c7j7Fk35LNq6ypg+7shiKJIxtFl1GWdIXHSIygjouqVCR8y0mpZdSQSyz9+h71Jycy5/g60ShWP3jet8Rtog9a6bOrON62xtnvbUijz9SP+7ilkf/1fTm78jI5Dp6DwDXTr2P8u3cZHs27li2++4+EHJjP7+RedplqF85bUuW/N4YtvviMqJoHX31vmdjsLjmxAMJoj5iOuHQ145362FC4F9wNvwlRrVgOQBXkvXfffEa2SrO7bt4/hw887iVv8Ue+//36++eYbt+vxCVSQ8Oq9yPy8G9hii4Ll+8n7eTchE6/Hf0Avr9atPXWWsq+X4D+4L2FDz5O95n6Uy7etp+bEEVJHPIhvSLQ3m2w3uJv0GkwGHR3CGraO2hJT+6j/7HqR/I0R2Pi4AdZMVQAGQUdV3inaXnsfYW17W9sIIFP6Ed/XXiLNNrjHXdQUnyN901dIlSqSpjyJKtK79xRAfWAXRb8txu+qnpTsPYyfYO+sLwCB/XtQ98dWwoaMJGLEuCbJUjXUt/TlpeT//A36shJSht5DeKr3XQtsIZiMlJ7aRUHaOgzaWsJT+9IudDD+fpH1yoYEJVl9lUNCkuupQFjIq4WwGkWd0/vjTgChLTxNBFB4dCOV+3cRc9NdLldJXJGIB7ZvoFNxAR2KC1jbqQc54REUhIY3eh8vBXiDaLaEpVAVHUvi/Y+R+8N8jq3+gHbXTCIgsk2jxxWVV/PS56t4Y9p4tu7aa02h6gpPPv0Prr/pZqJiEnjp81UUlTeeL10UTOTuW0nRsc2EDx1FxIjz37KLvcTfECG92G270DBUqpGolEiuWFbrQTQa0a9yb2LWKpMCDBs2DFEU6/3zhKgCtHlpIopg70TMO0PZttNkfrKewNHXEDT6Gq/WbSgqpfR/36Nqn0z8cPvMV+FDRiIPDm3SR7k24xSl61cT2/M6Qtt0a/yAvxDfd5xVVB3Mg7CjsDnYDt7rKTq2hdjoPviogt0+T0bmWnQ6NUUlaVaC4UwvFeDY8Z/ZsPkljh3/2aGW80QuMLotXW95xkpULW006euseqq2sA3ucQdlZw9was3HKMMiSXp4ZosQ1bJtGyhasYiAawdQsP9IPaJ6NjwUn8RYNIdPEHfHZCKvm9Bk/VRXfasm/QTnPn8fwaCn84SZLUpURVGgLOMAR5fNJXvPcoLiO3J1/6eJkMRyKO0ba9KI1JRRqFQhpKaMstPfjY8bYKcEYZtIIj5uAEkJgzHpNfUsq2BeQbAI90PjQv/uJgIoTNtAeeYh8vatJOya6wjufZVH98RPp+W5tb8D5o/2Nz98hlS8fKKLLf3ONzGZjPdfR723fsKGxuBNkXf13h3WdvjEJtBm6lPIAwI5ufK/5O79HZOhcc3M09klPPHeMip07skLluuUPPHeMk5nlzRaVqMu4tj6jyk6vpWosTfbEVVo2hhhe83NRUNC/s0Zvy5F6MtLkUeGtVi8zKUMoaaO4lWH3SrbKi2r3oIy0r0lm6ag6lgup9/6jfChnfC7wzupTi0Qauso+eBrpIH+JN70YL0I7qYu3xgqKyhY+gN+qR2I6zXGo2OdpZm0FTZ3DEgJjG1H2Zm9JCYM9ridYM40pVD4u9RIBXOKVhApKkkjJD+ZuNirKCw+hIAASAhv15fkIXfV+0g05Ifqro+qKArkH/yTgsNrCerRj+gb70T613Py1jKXKAiUrPudih2biBlzDTl/bkPuQFCORYTRQ69HUgdJDz2JT0zz/KUd+5YoCJRvXU/pxjX4d+hM+373NOhG0VRYLJChyT2pLsqgrjSHkMSu9O40CX9/81J51mH7pBGOriKufJwdE0lkZW8CoLrgTL2yjmjMDaSx/Zb+FJrcncytCwjs3qcesXAHn//wud3vnOAw8sK8F8R5sWHpdxnvv+41q1tz3kNH658iJJSkh56gfPsGiraspSRzH3HdRhLRYQAyuWsyWlRezcvzV9M9NZZxV3ema2IIIQEqZHIVUoWSimoNh9PzWL3zhFs+qgZNNQVpGyg+ud3cpgen45uUUq9cU8YIb1o8G7JyXwz3g4vpeqCtKkARW9/d5wrAVF3jdtnLmqy2FDS55Zz81zICO8Xid7d306iKRhMln/yIUFNHm4fqB180FRW7t1L85wqkCiXtr7qnwTa78tOzbPePSv7LslA/05VVV3XPr6iCIlCrz3Io7Ru3lvDBbC1ztuTv7NjoyO4UlaQBZm3WrKKd6KpKkMoUxPcbT2z3+oTTk9zvrsqaDDrS9/9EzYk0IkaON2eCsiHE3vjoiyYTuesWUrfrIAm3jiFn2R/1ymyIjWRkSTmqlCQSbn7QLuGANyDotBT8spCak0eI7TWauF6jkEgaXzpvCgoOr8NQV0nRsU34hSfQu+fDhIbYD8LuypdZ4CyRRF7+boxGLSAhIKYtaYvesMt4ZZsFqzG9VHcQ1WkQgdFtObHmv/gmtSX2pvqTp8bQoSCXfjlZdtvGeiFTVWtEc5fybUlJc95DZ+2QyGSEDx1FUI++lG78g5w9K8hL+5PItv0Jb9cf39AYSk7tdPouHMko4EhGAWmL3iDEX0FYVDxJI6fZ6ai6eo9EUaS2NJuCvF1UpR1AIpcTMWw0oVcPQ6rwXoS5N90oWptvtCd9wZvEVhQE9DkFBHXt0Kx6LleY1I27u1hwhax6CH1FLcdfXIIi1J+gqVOQKLx7CysWrkB3+iyJkx5FGV7fN6+pKFm/CkwmpEqzuHpDcOWHZ9lu0aeUKf2QKVT1rJAFh9chmoyY6txLoWoLTwKrunaZSGBOAmfOrgJEdNVlyH0CMGprKDmxw46sWgYCS0akvP2rGyVYzu6Drqac01vNfptxEx8ksHP3esc196Mv6LTkrPga7cmz/Kt3N15zIKoi0Pua/hzeuhf/a/oTf+0dXtdP1ZeVkPfTVxgr1bQb+SAhSfVdRhzvqbt+m3bXKpgoPr4No7YWkBAd1ZMunW6zkmLHVLqWgClX0f62cJZIYvuueYiiCanCh9ric3b92VaCqqGUrB7dx1o1pzbMRx4UQtzEBzx/TqLIis/es9v0R8duiF5Ok9ta0FySY0tKmvMeNtQORUgYsbfcTcSwMVTs2Ubpob0UHduMMjwKY1UlgkFHQdp6p/3GYmn3CWxbT/Df9nsT1rY3tcVZVOadpiL/KAZ1OfKgEMKHjSak3yCvGTHcveZLHZ70BW9amPVlJYgaLcrkhGbVc7nCVK4GCW7lS7hCVj2ASWvg5CvLELQGwp96BKm/dz8Y1Rt2UrNpF9E33IFfsveiyWtOHUPU65ApfYnrNbrR8o5L4bYWVYqxWqIsfx2hDAzDUFdJSFAbwsM7NEuCyhVEUaCg8ADnCrYikUiRypXE/SVI72wZ3zIQyJR+KP1DGxRvd7xeS13VhWc5s/lbpEolSVOetEpCOc7EHT/6nszUjdVVZC/+HGNJGWNvG81ri1bbXzfg37srmm37iBx9I6FXX+t1X6jaM6fIX/IdMv8AOk+Y6TIIz/GeuuO3aXuva0qyObdjMZqKAhJiB5CSch3FxWns2P1/ViLqbLLj7gTImSU2KDCREl0lsd2HI1P5WZ+zxbJqgSeSZQAZm36gIusQocm9SB12HwBGXR0nN84HiYSE+6Yi8/HcfeL9Rd/a/RaAmXc96LzwFdiRkobIlzesZ4rQMKLG3EjkyPHUZpyi5uQRqo6bV3oMtWoO//o2qqgYAhQRKP1DqSvPQ519jPB2/fAPT6Cm5ByC0UB55kEqMtNQ+AUiUSgwYeTQjy8DIlKVD6IomJN6jLnJq6t4fyd4QsS9aWHWZJ8FiQRVqvsqRn8nGEsrUIQFYChr3B3gCll1E6Igkj5vJXWZpUQ++yjyCO/pSgJoT2ZQsXAFIQOuIaTv1c2uz/IxDul3NeU7NuHfoSudBj1oJTaNSfI4s6haiJvlOFckRFNu9r2qri2kR/dJTpdnLRH7qSmjPJKoEkWR8vLTnM5bi6aigLCUXsT3ux5VwPmMXo6uC3n7VyOYDNbo/8bE222vt8edLyGKojmf++5f8E1Mwb9DF/IWfmkd6Bqbibs7U9cVFZDz83wQBR4dM5SPnRHVpFi0x04TP/HBeplqmgtRFKnYtYWSP1fgn9qR9lfdR3nmQdL/nO+0nziK91vg2LccFRZMBh15B1ZTfHwbfuHx9Ov9GEGBZl9bRyLqjHA25A5gC0crvUkwoK7LITy1L7E9zeoa7iR6cAbHa6zIOgSiaP7LfZiMek5t/QpTTTWJD83wKMWt5d2NGTiUcSfS7PZdM+tf1kxVlxJaymfQNoGCf2pHNDlZdudwdV5vWs8kcjkBHbsS0LEr0TdOxFBWgib3HNqCXPQlRZQVHsZQpQbBnMmo6Ogmio5uqlePyaDBr00qyqgYfGIT8E1MJuf7zzBWVlBz8ijR4xrPMNiS+LtITnnTwlxdeAplcgJSXx+v1He5QVGdD3EhV8iqN3Hui02Ubz9NxIz7UXnZpG8sKaf04x/w6dSWKA/TLrqC5WNcun4VUpUP7freaWeBcyczkzMLo+1xrqxPviFR1JXluSQTWdlbMBo11v9b/ja2rFuhPkt64QZqijJRBUYg9w0kICbVjqg6whL5DyDzCajne2qJ+rbd7phvO+PoMioP7CbkqiFEjbmJsx++aTfQeSN/dW3GKfKWfIM8PIx57ZN5avlau/0ioAgPgcoakh54Ap847/ZBwWik6Hdz5q3obsNI6GtWFGion1gInUUZwpXck63CQlV+OlnbF2HUVNOu7VgSEq5GKjmfkMKRiDpzC2mqBm9e3i4Mmmpie45yWcZd/1vHawxN7mW1rAqCidO7v0dbmEfi/Y95rBBheXdrNv9pt/1gfBJlHpDe1oSWkiuyTaBQfewQiKLdOVydt6UE8SUSCcqIKJQRUQT36m/dLgoCFTs3U75rM8G9ryKwc08kUgkSuYLqk0dR79nmlAS2JuH+v5vkVHMhmkxoj6UTMPLKvXKFuuxSAjvHU3Ukt9GyV8iqGyhceYj8JXsJuesG/Hp18Wrdgk5PyX+/Q+rvS8L193sth3z4kJEUrVwCgFRS30/VnWVORwuj7Xb/qGSXg7oqMByJTOGSUCQnDbVaVs8LtTtf1hVFkfKKdDKKt1JTdBa/8ATaXfcw2TuXYtRU25EoZ0QjpscIOxki22uwkFhHImYhYfpaNcfX/w9dYT4xN91llRtyHECam79avW8HRauW4dOlHWey84jfuNNuf4G/HwkmEzKVisRJ01CEuCbnTYGxppr8Rd+gzcsh5Zq7CW93PvOWJ/3EogzheExMjxEUpK1HGRDK6T8+JTAmlfiI3uTk7UTm0E+aSkQbg15fQ2buJiI7DsQn2LUvuDNy7qpf2V6jeen/PkRRIP3Az9SeOUnC3VPwTWhck9MRlv6lGjyMXj36E1FbzdvLFzJl0iOeX3grQUuRLtsECraW1cbOe6H9MyVSKWGDhxM2eHi9feGDhxPusN3Wipn69Msen68lrKCtiThfCqg7dxahToOvlznD5QLRYESbW0H02B5ulb9CVhuBen8WZz9aS8yNvVGOGuLVukVRpPzrxRhLysyR/37+XqvbJyEJJBKzL2fv+jJVDWXfceWzaSnnGIBiqccymCv8gqkpykQURaf+lM4IieOyrslkoKj4MOdKdqGpKMAvIpF2Ix8kOLErEokEfW19EuWMaLhaznVFYi2oKjhDxtbvkcjkJD40A9/48z5HjZJPNwcK0WSiZO1vVOzaQsTQ/hRu2YvjVOVgRBh91FWo2rUh8aaHkPl6VzZKV1RA3sIvEQx6Oo59jACHZAjuZPCK6THCTFQdgpQs8AuNRSqVUVeWS4d21xMfN4Adu//PLb9TxwAr2222iSMaI7gnStaCROr0XXC8lqb2K1EUydm9gqoT+4m9/T7823du8FyuYNu/tECujw/3TXmySXW1FrQUOWzuRLG1orlWzJawgtpaq21/X4FzVB89iCwi1Ovp1y8XGPIKEU0CfinuBZJfIasNoC67jFOvLyekbwqK6+/wev3Vf2yhbm8acXfejyo61mv1CgYDBcsWoIqKpeuYmS7TYTYW9e9oUbVFQ76rQbHtKTq6CXVlVj35IXAe4Q1mwqrVVVJZlYNafRaA4ITOJA64mcCYVDvi64wseBIU44qEiaJI0bHN5O5biV+btsTeMblBSShnxNSdgcKk1ZD7+7doj58h5o4JFCxeWa/M/rBg+pVV4HdVT+JH3WPVcfUWak4fp2DJ9yhCw+k06vEG3Skagu3Ex/beC4KJgkNrKUhbh39EEr07TcbPz6wNarvc7+jDDOcnLw0FWBWVVAJio4S3vCKDsjP7aDP4jkaVMJrTr/IP/UHxia1ET7idoG69GyzbEJ5e+xtTt2/ksYkPstmJ2kRrwN/Ff/FioblWzJaygl5xBXAPgsFA1cnDBA4feCUZgAvosnJBKsE32T296Ctk1QUMlXWceHkpysggAu733vK8BdrjZ1AvWU3YkBEEdunp1brLNv2BobyEztc/3WDedleDsKvtjsuhjgQ3pseIv8qsR6by42DalyQnXkvbFHsfQVsCIogi585txGjUIohGzmVvxqxlAQq/INqPeriZd8MelmuQ+wRQV55rF71t0mtJP/AzNSfSCBs8nIgR4xt97s4+3o0NFPqyEnKWfIGpsoYpY67hCydEdX5iHNNy8gkdeC2Ro2/wehRwxe6tFK9Zjn/7LnS46l5kioZTEnuiTwugqy7j7OYfqC3NJaXNCNokXWvnm2o7Sdm+6516PsyO6VEtpNZiUS2r0CEIRqRSeYOBVtk52zmTuQZVUAQR7T3LGuXq2pyh8OhmCg6tJWLkhEaDexpCUlkxj2zfCMD//bKAO8JnkhkV06R2tyT+DqTlYhLy5lqEW8qifMUVwD1UHz+MWKfBf3C/xgv/TaHPOId/2yhkKve0gq+QVScQDCZO/Xs5pjq9WaLKy5F8xnI1pZ8twKdzOyJGjPdq3Zrcc5Tv2Eh8n3H4hTVsrXU1CLva7soSa1ve7B6gNkcsiyJZ2ZsorD5JfEhPVKogQIJC4YdOp8YkMZJ+5jdrPVK5kvB2/fEJiaLoyCa3ZYPATKZsl6Ib007V11YAWKO368rzSd/6HabaauImPkBgZ/f8aJx9vBsaKGrTT5C37HtkIYG8OrgP/1q92W6/CPTr25UD+48Rcd0Erw8KoiBQvGY56j3biO56LQn9rneLCLsTkGdB5rafKEvfi1zlT99e0wgOSqxXxta67ujDDDi1vG/f9Y5VN1UmU2E0alAo/Bu0qp7NXgeigGDUO01o0BDcDbYqObWL3L0rCBsygvBrzj+vphC6hV9+ZP1/gF7HyJPH+OIikdWGyNrfgbT8HQi5p/i7ZZ9qKsoPb0PVuR2K6Msny5y3YTybQdhA9yU6r5BVB4iiyNkP/6T6ZAFR/5zmdYkq0Wik9JMfkCjlxE/wbvYrwWik8Nef8YlNIKbbMKdlmpNtyJ3lUEsZ/6hkq5yPtqKQs5WliILRrqzJoEMiUyCaDMiUvvS+9w3rvujOnvkHF6ZtAFEEicSt9p23rPak9PRuzu1ehjI8ioRpT3uUjMHdj7coipRv20DphlX4dO/Iao2WYWu325UpCfQnpWNbavcfJebGiQT38W6gkaDTkb/0e2rTT5J09W0ePX93nr1gNJC9+xfK0vcCIEPulKiCvXV98MBnnEb8OyIkKImikkpCgpIICUluVL6quOQoglGPTOXXoAKAK7hD0Msy9nNuxxJCrhpCxMgJdgOrp4Tu2pNHCa+rtdv2xTXuT9i8jYbIWmvzBW1tAUXeao879VyKZM4TXGqTBk1OFvqz2UQ8cf/FbkqrhbG0HF1hJUE9nI8PznCFrDqgYNk+iv84QtiUO1G1S/Z6/RU/r0SfnU/SAzOanB7T1cepfNt69GXFdLnhaSRS58vXnkhWORJad5ZDLfvz9q9GIpUjmoyAiMI3kG63zqbk9C7yD/4BSIjvO87aJscEBJ6SaVean87aZ9lvMujISFtG1vZFBPcZQNS4W5AqXOf5bioEnZbcPxei2X+EoAkj+FhdwbC0k3Zlyvx8SEpORHvoOHF33E9gF/csu+7CWF1F7o/z0ZeX0n7UFILjOzVY3lGHtrF7q60sIWPjt+iqSomO6oW6MqtBIumuVqot1FXZgIi6KpuuXSY2aFHNPLeRzKx1+IXF0/nGp536jTXW11wlxzivrZpG5tafCOrVn6ixNyORSOwG1tSnX3Y6uDp7f5UGPb1/+opk4DngUeC9YWMvqqbqpWQ9bamAoqbW5a32uFPPpUbmPIW3+uGFIvUl+9Yij4nEt0fD39i/M7TH0kEqIbin+8kSrpBVG1TsPUvW/E0Ejr2WgEF9vV5/7d7D1GzYQdT425okaWOBs4+TrqSI8q3riOk2HL+wOJfHeiJF1FB2p8bSlFq1TW1SskrlCoqObsak16D0D7WLrLYgb/9qazpUT8iqO0TaFnXlBZzZ/h2GSjUxt9xDcE/v+xap9+6gdMufiFIRUasjYvokHq6o4t6VG+zK6aVSEuJj0J3KIOGuh/Fv19Gr7dAVF5L743wQBDqPm9Fg/7DAtg8A6GsrXKaozdq+mNLTuwAJyUn1fZSdoSGJKmcKAHBe8sxk0pGXv9vl8Tl5O8jMWgeAQVfrMsDBco2urstVcozCtA0o/UPI2PwDgV174hOXwNkP5rhtTXX2/v7+v3kMBc4BbwP3y+R8PqzxbHOewNPB+mJbT91tr3rvDgS9DqmPX6sh1t4iWO7U4+65LlULrLf64YUg9dr8HDSHTxA+ZeKVbGMNIeMIgZ3ikAf6YKzVuXXIFbL6FzS55Zx+8zdC+6cQcNtYr9dvKCyh/Jul+F3Vs0kvSkPLi6IoUrxqmTn/eCPLnbYDsCvi2RChtWpq7lxKdeFZa3CSLWxloSwZo8CcklJfW4FEpvDIH9WbEEWRklM7ydn7K8rwSNpMe9pj0XZ3UbpxNaa6WpBKiX3tKVbPX0jP7AK7MrkhQaSGhWDILSDh3kfwa9PWq20oXrOcil1bkAcG0WXcTNQ5xzmz7qtGLdCOfaAwbUO9FLWiYCJ3/6q/iCqASEHRIadk1RUBtd1nkaIymXQYjRqnCSMyMtdiNGrIyFzrlKyKokhGliWhgoSAqBS7hAXOrrGh1LvOygcndSVj4zcEdOhC7C332CWJcGVNtYXj+xtWU0WSupznMBPV54Br/vFqg3U0BZeaBc7d9pZtW4+gqUMeHNriS+7uwlsEy5163D3XxX7+3ibLntZ3IVYKirb/jjwmEr8B3g2avpwgGgyo92eRcPdAj467QlYBY62Ok/9ahjLMH//7Jnt9RiQaDJR+ugBZcCDxIyc2ScqioeXF6qOHqMtMp/2oqUjl7kXWgXsBU46I6TGC7J1LgfPBSY5wdby5PIiC0SVhju87zqOc7M7gioQbdXWcObiYmhNphPQbROSYG1tk2V80mShZv8pMVJUKwm4cRd7L7+H41E/ERNJTpcRUVErSfY/jE+++/05jUO/dQcnG1Qh/+UBKBClK/xC3A6Ucn2FUp0FkbPqBiqxD+EclU3BkI/kH1iAKJiIjulLxl9RYQ1nLXOmqOkpRyeW+qFQhjSaMcIa8/F1WP9X4PuMatNTbZuByp89FdRqET1AE6eu/xC+1I3G3T0Iik3k8CDqSi3nLfgTMS/+PAt9cNYQaPz+36vIEjbWztVne3Lmv6r07EHQ6pL7Nt6pebDLnCZryrC62W4e376+n9bX0SkFt+gm0x9KJmD7J6+pBlxM0x9IRtAbCBrX36Li/PVkVTQLpb/+GXl1L1AtPIvXzrug6mP1UDQXFtHl4JlKV+8oC7gRrCHodJX+uIKBTN4ITPPOR8USX1IKoToOoLjxrTS3pCWxTUlrgSJ48Xc53BmeErLowg4ztCxD0OuLuvN/rcmEWGKuryP3tW3RnzhFy5wTGxkWz4D9f1SOqX1zTj8czczGVq0mc9Dg+MY0vzXuCkvUrEbQakMlQ+gQS08Pcb9yVJXMGS9rUmsIMKrIOgygAEsJCU+ne9R6XbcnL343JpEMu93VKZi2k1JXIf0bmWgyGWrZsf4Pw0PbWMo4orzjD6YxVRHUZStKAm8zn/svC3xDc7XNVBWdIX/8Vvm1SibvjfiR/6d42dxB8ecKdrPj8XQJ15uWw//NSymVHNNbO1kbW3LmvlnSrzbWqwsUnc57A2bNyRmAdt13M5+rt+9uanpdoNFK4fjmqjm3x7d31YjenVUNyfC++bcLxa+OZUsLfnqxmf7eNij1niZz5UIvITNQdOErNxp1ETbgNnxjPMlm4E6xRvm0DxppqdNnZFIfuaFE/TwssqSUd4Uh4HH87O64phLkx2NYpCCbOrPuKqryTKEIjSH70Ca+nK7WgLjOdvF++RyKREPXMNB7KLeCt/3xVr9ykB+/g5z82Y6rVkDRpOiovShOJgkDJ2t8RtBqkChUJfScQ1Xmwdb+nsmS28I9KRp+pxqCtRuEbhKGuChDJyFzb4BL/qfTfABGVKsSpddTRfzUvfzfbd71jrS8rewtGowZBMKCuymbwwGfq1XE2az1Z5zYg9w1EfS4Ng6aa2uIsguI7Uluc5bR/eRLMV12YQfr6L/FNSiH+rgeRKtxfwWgMBeHhPHPLvby/5Dvun/woBi8nf3AXrWnwdxfebLMtmbuYVmZ3zu3sup0R2NY0AfE2Wb7Y5NsW5Ts2YiwuI+Kxe68kAWgAgk5P2Y504u/wXPP6b01Wy7adJm/hLkJuG4dvd+8GtYBZT7X86yX49ulGSD/PX6rGPsSGSjXlOzYhlSsw1FW5pYHpKTwZ0B0JjzsEyBuWVFd1aitLOL7uv2jzsgEQBVOLEFVRECjfup7STWtQdWxLxLS7eWXlRqaut5emEoG7p97F0t/XI9ZpaTNpOsqIKO+1w2Si8NefqEo7QOKAm4nuco3bxzY2aRBFkaq8E4CIRKpgUJ+nKCw6SFb2FgyGWpd+pGa/UxFz8JV7kf+OS//JSUNJz1iNIBgICaofParX15CVvQkAo7YGRBH9X7JpDWVhc9clorowg9PrvsA3oQ3xdz3UIq4jmzp1o/dL87xerydoTYO/u2ipNl9Mkmc5d8n6VS5Jq7PrdjZe+CYmU12lxjcx+UI0/W8JXUkRpVvWEjRmKMoE72WivByhOXgMQWMgcqTn1ue/LVmtO1dK+jsrCR/aEb9x13q9flEQKJv/ExIfJfGj7vJ4tuXO7Lps0xqkSiVxXUdSdHxriwQteSIG70h4bDVXLUEugNPgK2/ASqy7D0cikZK9bwXywCBCBw+n+uihFrEYGWuqyVv9A9rjZwi6fgTBN17HwSdfI1yjtSt3LiyYwS89QdE7nyFqdCRNnuGRnmtjEPQ68hd9S+3ZdNoOu4+wlF4eHd/QpEEwGTm3YzEmvRaZTEV4WAd27f2A5KShDB74DFu2v4EgGAAIDfPHx0eBVmugorzWTqLKHZ9TcC5rJfyl0WuWrzoPo0nHgfQfkMoVyBQqAqJTqS3Owj8q2WpRbUogoQV2RPXuKUiV3iGqPbIz+eKHz/mzSw9qlSo+HDGOWh/vuyB5C63Nn7WlcTGtzJZzC3qdxz6ZYCa7lt+anCwQRfPfywitpT+KJhP5qxYgDw8h6MbrLlo7LhUY9uwgqHsCPrEhHh/7tySrxlodJ1/7BZ/oYHwntozZvmr1JnTpWSTe/zgyX8+DJRqb2etLi6k8tJfE/jcS3XUo0d3MhLupOqVNHdAbSsFq+W3OanVeBskia9UUrdeGYCHWOft+QzQaCO47kKjRNyFVqYgadYNbdXiCuqwz5P/yPaIoEvn0Q/h27cC+J1+pR1TTkuIY/9RDZqKq1ZE0abpXiaqprpbcBV+gKy6kw6iHCYrr4LW6jbo6MjZ8Q3XRWRRyP9qmXFfP8nn7rU8wbEQHhl07kvCIcOuxVZUajhwZw7q1Rzl+LM/tczq6BbiyzgqCiUOZP6OtLKbTuMfxC09wWp+l/2XvWgacl0przKpv9lH90utEVW4ysegrc6aq2w+ZEyj83G8QZ1sxWW1Ny8kXAhfTymw5ty0hcxdWq+wGs1XWNzEZDVxSrh3uoLX0x7LNf6I/l0f0848hVXrPNehyhKGwhKrD2bR/dkKTjv/bkVVREDkzbyWGijqiXnwSqU/DOdGbAl1WLpW/riVs8Aj8klObVEdjM/vSTX8gDwwm0mGw9cQS6s5xrgZ0C5k0GXSY9HUNns+R8Fosq03VenWFoLgOlKbvAamU+LunENCxZRzdRUGgbMtayjb/iapDChHT7kYWEsQP8z4jstaeqC7t35OZd99A0Tufmy2qbhJVdy0HxqpKcn74DFN1NZ1GP4p/pPsiy41BV11O+tr5GLQ1KOX+6A01VotnVvYWrh5wK0/NGkzffh2Qy1RIZfYf66BgXwYP6cDgIR04dPAcX87fRHFxVaPndZS5sg3AsshZxcX2Jy3vF6oLztB+1MMuiSr8pWDhIhWvq0lRVf5pczBVUop56d9LRBXgqXUr7X4bJRLOtpB8mrdwKfqzXgx4W/4K7C2ljcFqldWZrbIaIPXpl5vVjtaI1tAfa8+mU7Z1HcE3XYeqbfO/u9WbdlG1aiNB44cTOMwzWadLATUbdyIP8iV8aNNcLv92ZDXv592U7zxDxBP3t0hAlaDTUzb/J5QJsUQMb7pea0Mze11JEdVHD5F09a1IZfaPsKkBS54eZyGTMqUfSv/QBo9zZnH1ZnsM2hrOpv1CdfohArr0JHrCbU3ODtYYjFWV5K76Ad2pswTdMJLgG0YikUrZ9Y85xKrtiVhxoD8z772J4nc+R6jTmH1U3bSoumM50JeXkvvdp4iCQKex0/EN8R7hqSvLJX3tF0jlSvr3eIQKdYYdgbx26I288PJN5OaeBkSMJh2YdE5JK0BQsJG337mLN1//lTNnihrUXXXUUrX8277rHatFt1xWSnnmIdoOm9SoJdnS35z1J2eTosq8U5zZ8BXykHD0pcVUHd7nNetNgKaOh3dustt2zaxXrJmqDBXlaHKz0JcUYaiqRDQakCoUyINCUMXE4ZfcrkkrNc3FpejP6ik8IZquyrYWeaamWGUvJVzs/mioUpO//HtUnVIJmuAd97uqVRsxlampWrXxsiOrgkZL3Y69xNzYB6myabTzb0VW1QfPkf3tVoKuH4Ffry4tc46lqzGVVZAw7R8tprVWvn0D8sAgItrXj6hrasCSp8e5m960qXC3PRVZaWTtWYooCMTeNomg7r293hYLak4fp2DFQiRyGVH/nIpPp1T6nDjDknfn4/ikf+3XnemTbqX43c8xVdeYLaoeBFM1ZjnQFReS892nSJUqOo96DFVAWDOuzB5V+emc2fA1PsFR9Gl/H0plAH5+EVZSGRUVxAsv38SWLeuYMmUy//znP5kx4wkspFXpQFY/+OA95s6dw5dffscLL9/Ec8/8xPZd9fVTLQTW4p/qCIuF1c83gpKTO2gz+E7Ckt2TIHPVnxwnReqc42Rs/Aa/th3RFeVjrFJ7dalx63uv2f3OCwqmUFNH1e4tVKWnYSwqBUAWGoQsNBiJUolYp8eYcRyhqgakUny6dySi+1D8Ujv8LSOPW8pf0RNi6Krs5SzPdDHQWnxTbSEYDOT+8jUSmYyIaXd7TZc9aPxwqlZtRNUumbxn37qsLKw1W/Yg6I3E3Nj08flvQ1Z1JdWcfvM3gnu1IeimxtNBNgXaE2eoWb+DqLE3t1hWJEOVmqq0AyT0HV/PqtqYn2dT/VmdoSWi+D2BQVNttqYeP0xAp25ET7gdeWBQi5xLMBopXbeSil2b8eneifApdyALDODmrXv44Jul9cpPmT6JPzulUvJ/X2CqqDTLU3nYHxqyHGjzcsj54TMUQSF0Gj4NhW9gk67LGSqy0sjY9B0SqYy44O4olfUt1FOmDqOoKJcpUyZjMBh46623kErlPP74Y8hl9m41H3zwHm+88ar5uCmT2bZtD1OmDuPgIfsgKluJK7ncF4XCv556QHzcAHS6arKyNyJT+iIKpmZfr20/rshKI2PzDwR06Ezc7ZOpPLjHq0Rhytb1+BoMdtu6RoVQ+fE8pP5++PbpSsjt41F1SEYW4F/veGNZBZrDJ6jZupfcHz5D1S6ZmOG3eDWZxKWAlvJX9IQYuirbWuSZvHWPLjZZbC2+qRaIokjeuoUYcguIeu4xZEHeW8ELHDaQwGEDyXv2rcvKwioajNSt30zEiC6oIpo+Vv0tyKpgNHF6zgqkChkBkye1SM5eQaOj7OslqDq2JeSqIV6v3wL13h1I5XIiO9TvxI35eTrme29Jy2hLQRRFys8eIGvnYkSjkaDeA4i58c4WszDpS4vJXfEdhrwiQiZeT+CoIUgkEmasWMszv66zbxswfdrd/NmlPcXvfYGxuIzESY+jivaenEndubPk/TgfZVQMnYY+jFzlvSXhktO7Obd9EQCiyUhO7g6SEgbblYmKrqRLV3MQ1bPPPsecOa8DMGfO60ilMp59djYSiYjRqOfdd9/jjTf+bT129uwXads2FcFkIDK6koxMswi+LRdaSm0AAJSKSURBVFEFCakpo5wqB2RmbbASVZNe41WptrKMA2RuXUhglx7E3novEpnMKVFo8uAtijyz3t5X9SYwB788cg9+vbsiUTT8OZaHhxI4YhABw69Ge/Q06iWrOffFfwgdMJSIkeNaRFKrNaKlrI2eEMMLsQzdHKLorXt0sclia7Msl65fRd3uQ0Q8ei+qZNd+8s2BxcIaNH54i9R/oVGzfR/68hri73RPDcYV/hZkNfurLdScKiDq2UeRBbaML6N6ySqEmlri7nu8RcgwmC18lft3EZHaH5myfiasxvw8bfc3NRDLm9ZZT6GrLifj4BLqMk4hUShAFKk7e7pFiKooilQd3EPRH78gCwki5sXpKNuYkzqse+Ed2v+1XGstD7T/+HV0Egkl//kKQ14RiZMewyfWs0QQDaE24zR5P32FT3winYZMQabwXnBg4bHN5O5ZgVSuQjDqcKWLeu3wVMxXC48//hgSicxqOX399Vfx8VEye/azzJ37vh1RfemlV5k5cxZglpu666472LZtszVgykJUO7a/wSVRzTy3nvg+45Cp/LyaSMJM0hcT1LMfMTdNbPD9bergfee+nXa/SyUSdj37CDEdUjxur0Qiwbd7R3y6tKN67TbUy/+k+twJEm6ejCrau5nQWiMutr9iS8AZMW0OUfTWPXKXLLaUBbY1PeuKXVso37aekDsn4Ne/R4udx2JhvRwgGozUrllHxLWd8EsKb/yABtBqyer//vc/3nnnHQoLC+nZsycfffQRV13ledaD8h3p5C/ZS8jE61G1a9MCLQXtyQxqNu0iavytKEOb90AaQu2po5jqaojsdLXT/Y0tzTvub8qA31SS2xyIgomi41vJO/QHMl8/4u+egrGqssVm3CZNHfkbFlG3Nw3/If0IvftGs2qEKLJn5qtEO0T8myQS2n02B5MgUvrfb9Fn5pBw7yP4xnsvMr/m9HHyf/4Gv5R2dLz6AaRy78mk5B9eR/6B1SQlDsVHFcK5HNe6qIMHn+97cpmKmTNnIZGYiSrAiy++wDvvzEOtVlvLvfDCi1aiasGQIebVBwshdhVsJYoimVnrycreSHyfccT2NGsZeqvvFR3fSs7u5YT0G0TU+FsbnWg2xdJjqqtlT/YRTgI+UimJgsBtrz+NT2zzXIUkMhlBY6/Ft0cnSj9bwLkv/kP0uNsI7tM8C8YVXHg4I6atwaroLlm82BbYlkblwT0Ur1lO4JihBI1xL7nJFZgVDvRlNSROGtx44UbQKsnqzz//zKxZs/j0008ZMGAA//nPfxgzZgynTp0iKsr9IBVdcRXp764ibFB7/Ee1zNK8oNNT/s0SVB1SmpSlyhNUHtqLT0IbfEOan56zMUkqV5bT5uSWbwpqSs6RuXcJuqICQgcMIWLEOKQqs1W5JT6KdVkZ5K/4AUGrJ/zRe/Dvbw7gkZhMnJ32Ao5U5vXbx/PFuGsRTSZKP1+I9uRZEu55GL82bb3WpuqTR8lf9C0B7TvTYcCker7KTYUoiuQfXEPB4XWkJF9HShvzslNCvH3Ak4VEhob5Ex0Vj9Eh6v+ZZ/6Jj4+CF198EcCOqM6ZM4cnnpiJTidYt8llKiIjoxg0cBI+qk4ATomxKIpknF1Ddu424vtNILa795JeiKJIweF15B9cQ+ig4USOut4tC70nlh5RFKlK20/x2l/JEAQG3XsTAUP6IZHLwYurL4q4aKJfnEHFgl8pXPEz1RVniRt6u1dTwrrCxfZpvJTQ0L1yRky9YVW8UM+nNRDrlkLl4X0UrviZgGsHEHLH+IvdnEsGQp2GmtXriBrdDd/E5hvxWiVZfe+995g6dSoPPvggAJ9++ikrV67kq6++4rnnnnO7njPvrkLu74PfXfe0mE9j5Yp1GCuqSJw4rcWW/8FsnanNOEXSVTe12Dmgcctpc3LLewKjro7MU6uo3L8LVWw8baY+1aKBJKLRSOmmPyjfvgFV+2TCH56IPPx8atbMaS/g2IOenXwrP187wKy7+vUSNIePE3/ng/i3dU+U352BpPr4YfKXfE9Ap+506H8vUql3FCaKT2wnd/8qBIOW1JQxtHGy5G8R/zf7k0Js3BikMgVKmQLBZECvr0EuUyGRKJk9ezbvvPOOHVENCQlh9uzn0OmMgM663VJHSspACvLVOIMoChwtXk1J7g6PU8dar9HFBEoURXL3/U7R0U1EDB9H2NDrvP59MFZVkrfuZ3qnnWSHUsGo157GENVyqy5SpYLwB25HldqG8h+Wcy63gISbH0QR7P30wra43C1q3kRD9+pSTxvbmpbrvYnKg3soXPEz/oP7EnrfzX9L9Y2momrVJgStgcTJ3jEUthy7aiL0ej379+/nuuvOpy6TSqVcd9117Ny50+kxOp2Oqqoqu38AtRnFhDx8H1L/ltEl1GfnU/3nViKuHe3VHO/OUHPqGAgioW5K9TQVMT1GNKqb6s3jik/uIG3RGxSf3AGYSUrp6d0cWf421UcPEjXu5hYnqvrSYrK+/4DynRsJvmU0Uc9MsxJViclExsPP1SOqj0ydaCaqokjFghXU7TpI7C33epSIwHYgsYV67w4y3n+dwhU/k7/4ewK79CQsqC1Hl7xFxqYf7O5XUyCKopWoyuU+TokqWJboJYBIVvYWtNrzkexGkw6zVJUWk0lg7ty5dkQVzBbWuXPnIgiCldwajRr0+hoEkwGtxj4y3gJBMHE49xdKTu2kzeA7GySqjv3HFo4BhWBO6HAmbQlFRzcRNfZmwq8d5fUBqOrIAc5+Og9pZg47gBS9gfeXrEah13v1PM4QcE1/Yp5/DFNlNVlfvEdd5pkWPV/4kJHIg0MvS4uat+HqXlned/Xepr/Tnp7zChpHxa4tFP76EwFDryLs/tta1Bh1ucFQXEb1uq3E3XFVsxQAbNHqLKulpaWYTCaio+39uaKjozl58qTTY9566y1ee+21etuDbxrllcwSziAKAuXfLUMRG0XYoJaP2qs5fQyfhDb1ZIq8ufzenLrclbJyPEfe/tWY9HXk7V+Nf3gCmQd/QZuXTWD3PkSNvrHF5KjATNoq9+2keO2vyEKDiX5hul2Ep0yvJ+Oxl+sR1ZkP3s6agX0AqFy2hpqNO4m+4U6CunmmIedq6cxCYisP7Cawex869LmLI0veQl9bgT5L7TQTkycoOPQngsHsdxse6toKHB83ALU6i6KSI4QEJVFRXktVpYagYF/kMhVGk7mOefPm8uabb1qPCwkJsRLXF198Aa1Wz6OPTgNEq4ZqYVE+FRW19VwNTCY9h7IWUZV/mrbXTiIspWeD/dK2/zjuc3RZEUxG0vctoPpEGjE3301wr/5Nun+uYNJqyN+4mLrdh/Dr34PcY+nWfTfsP8KeDil8d13zfbcagzI5gZh/PUnppwvI+f5TIkdOIHTQsBaxCl2uFrWWgKuMVC1p/bzyfDyHKIqUrl9F+bb1BI69lpDbx12xqHoAURTRLl+CItS/2QoAtmh1ZLUpeP7555k163wAR1VVFYmJiQQMdx6I5A3UbN6NPjOHxIeeaDHxfwtEQaAu8wwxnepbmLy5/H4hgqdcncNk1HHi9w9QRceS+OAMr/p8OoOxuoq8tT+hTTtp9kWaeD1S1Xnpn0dXrOW5X9fVI6qjXpnJ6SRzxHXV6k1UrdpE5OgbCenrefSmq4HEP7UDlQd2o4pLpEMfs+i0hXj5RyVTW5xlZ8EuPrnDmsI2vu84wEziBJMBqUxBfN9x57M4HdlI/qE/kct8MJq0qKuy650/L383GZlrbbaI1nK7du1j2PDeyGUq5DIf/vPBu7z11lvWknPmvMns2bOZO3cuL774AmAOvhIEE48//hhSqQxBMLF9+3YrUbUkB4iK7M6BMz+iKc+n3XVTCI43p+Vz1mcsBFYwObfOgv0EymTQcWrnt2iyMoi78wECO3dv+OF4CE1OFnnLv0eoqyN86l20T00idG+aXZmlg/p49ZwNQRYYQNSsKVT+8iclq3+jpuws8aPvQebje8HacCmipX08nRFT38RkqqvU+CYme/18V+AZBKORvHULqdt1kJA7J1wJpmoCNAePUbH7LB3/dTMyH+/5zbc6shoREYFMJqOoqMhue1FRETExzgOLVCoVKlV9GZ+WMtubqmpQL/sD/2v645fkufSMp9AVFyJoNQTEpNbb52g9ao51tKmpWpt6DsFoIDAmBXX2MSQyGZHjbiakz8AWJ//VJ45QuHIRSCVEPvkAvj072+1f99xc2peU1zuuw8evo/uL0NZs3o16yWrCh44ibNCwZrXHdoCU+QdQeXDvXxbV89lRbImX5RlbthembcCkrwMge9cyZApf62+TyWAleSUnd5K773eSk4ahUgXZifLbIit7C0ajBgCpVIFKFWIt9/n8Dxg2/GuMJh2ffPK5HVF94YUXmT79cbRaHU8++TS1tbW8+eYcwKzDKpHImDlzFnp9Dd999w1Z2SetWaniYvux99h8jNpaOox9jIDI8ysitn3Gcu0mgw6Tvg6Z0g+ZT0CDfdaoreXkli/QlxSRcN9U/FLaN+1BOYEoCJRv30jpxtUo2yYS/azZhWT7w/a+9S/fdQO1fheWKEpkMkJuH4cyNYmyLxeRlfN/xN98/98uiYAtGiOjLe3j6Ww1RZOTBaJo/utmO6/A+zDWVJO7/Gt0Wbl2wbVX4D6EOg1VP/9C6IBUwgZ77zsLrZCsKpVK+vbty/r167n55psBEASB9evXM2PGjIvbuL+gXroaCRAz8IYLcj5dQS4gwT/i/CBjS0p73PmSdXtzrKMXIitVVKdBRHYcSPnZQ6StmIuxupLQAdcQPmxMi+c8N2m1FGxdRu32ffj26kLY/bfVy0Cy9sV36xFVEWj3yesYlWaiWrc3jfLvfyFgxCDCrxnb7HZZBsjSjasxaTUEdu1Jhz53uZxsOT7jmB4j/loO14Bo1kCVKf2sltWYHiMozzzEuZ1LSYi/mpRkc0CRswh8MPuqnkpfAYBUKmfwwGfOnzvfhy1bttOmTRJz586xbn/++eeZPv1xamtrgTqUygBmPjkLURSshHbu3DnccMNNFBaoOXjwpHXpPygwkUMnvkcik9NpwhP4BEe6vFeWa5cp/aw+0g31WV1NBac2fo6pro7EBx7HJ857RM1YW0Pe6h/QHksnaNwwgm8ehUQm46NPfqwXDHAhlv9dwa93V5SvmN0Czn31odktYODQv6UPXmNktKWj2p2tpjg755XAtQsLbX4OuUu+QjSaiH52GqrUlpG5vNxhWP0LxlodbZ/wfixAqyOrALNmzeL++++nX79+XHXVVfznP/+htrbWqg5wMaHLzKF2+36ixt2C3L9lEgzUO2dJIYrQMDsReFek9EJYRz2FLbH2CYrkXNrv6ApyCejUjchJj7R4cBpAXdYZ8n9biFBTS9gDt+M/pJ/dyyQxmUh/9EUUgmh/nEJB50/fsP7WHD1N6fyf8LuqJ3FDbvXKCxk+ZCSlm9Zgqqs1R/33vRtJA1H/js/YMslwZVWvyj9N+tovCEvtQ/v48Y222UJinVle4+MG8OuyIl75dw8+++wzHnnkEf75z38yY8YT1jKWlKtSmYJZs55HJlMxd+4cvvzyO6KjE3j/3W1WAlxadpKjJ3/GJySa9tdNcZo61rav2157YxMrTUUhpzbMRyKVkjTlCZThrkmwp9DkZJG37FtEg5HIpx7Ct5vZ9zeupIwb99kv/4/915NwkX3e5JHhRD//GOqlayj5cwXVeSeIH3MP8qDgi9quC43GyOjF8PF0ds7W7BpwOVl9RVGk8sBuilYvQ5kYQ8Tjk5CHhVzsZl2S0Bw9Tcmqw7R9chSqKO/HmrRKsjpx4kRKSkr417/+RWFhIb169WLNmjX1gq4uNERRpGLhChTx0YT0bb4/rLsvvUFdgSIkzG6bK1J6IayjnsJCNnL2/opoNOITn3RB/FIBBIOe0g2rqdi1xSxJ9cw05JH291JiMjmVplrRpxtPTJ9k/a07m03p/77Dp0t7Ekbf6zXLlCI8EkGrJaBDFzpcdV+DRBVcP2Nn2+vK8zmz4RsCY9vTI+4mJJL6bXYMcgJ7wmrBefI6gBmP/4uP/vcqGzduJCUlxU531REzZ87ihhtuIjo6gTdf/5XiYrNax9HjP1FccgTf0Fg6jn3MaUau4pM7MBl0yJR+VoLqTv+uLsokfcOXyINCSLxvmtdImSiKqHdvpXjtCpQpiUQ8ei/y0PN1//jel3bld3RI4UQb72Qxq960y5qGsSkZbiRyOaETr8enawfKv1pE5qfziB53O4Hdev1tAkhaW8CRqzHAmWtAa8HlYvUVdFryNi6mbtdBAq4dQOjdNzaa8vgKnMNUU0fldz8T3LsN0RN6tcg5Wu060IwZMzh37hw6nY7du3czYMDFz8pStzcNfUY20SNu8YpfpSvpIkeYamvwkZituBapHoAed77U6oipIzQVhUgCzb56UpUvcXc+QNLDMy8IUdXkZZP51XtU7N1OyB3jzZJUDkR1yOETTonqyNeesiOqhvwiSv7zNcqkeBJveMBrfrWanCzyFn6Jb3IqHQZM9pqOKsCZdV9x/Nf/A4mUXil3uqzbNsjJ1XbHMtt2/MmYMWPIyspCLvNxSVQtqKqU89wzP3HmTBGCYOJI0UqKS44AYNJrXKaOtfjjyhQqt/t6xbkjnP7zU1TRcSQ9OMNrRFXQ68hd8705k82IQUQ/84gdUQX4dMxQbG3z9z4zzSvnBqhatRFTmZqqVRubVY9vtw7E/PtpfLq2p2Dp9+T8/jXGmmovtdIztKRs06UAV2NAa5acas1tcxea3HNkfvl/aA4eI3zqXYRNvvUKUW0iRFFEu+QnBL2Rdv9sfOWuqbjydNyEaDCiXroa3/9v76zj5KrO//8e35lZd9ckG924OwlJIFgKwbV4cSkF+msppYX2Sx2KtWhxAiGBCBGixF02tknWfXdkx+3+/lh2WddZSXLer9cmmTPn3vNMZvbO5z7nkVFD0af7J3C4o/FRkseNXF0rBvqi3WlXkrbsxlLyT62j5sgBVKFhxF55PcFZY3s8eQpqC/xXbV5L1db1qJPiiHvuYVTxzb3yco+HD//1XiOhKgFD//Uctga1eT1VBsr/9jaKsGCSrr4LuVrd7FwdpaEnJSAxmcIP3yIgPpHMKbf7rTMV1Ga/GwuOAuBzOeq35luiLskpNXlGIy9ravIMTp9di9frJCJsIEbzT+1R64554fnP2fGDh7kXD2f4iERCQn/6fzMZbRw5XMi6tUfIzi4CwO22ceDs59SU5CBXqpDJVcRmtf7572xYS/nxbeTv+IqgIVkEJKeT+8Zf/LJd6aqqoHDpu3gqqom490b0E1pOvvhs1iQu332IacdP87trL8fnx7jQ4Etn13tWu4siUE/kfTdhHTscw4fLOHvsT0RffCXBo8b3qpe1NS9db2419+W2dmvfAf3NA9yQtmzr7yECktdL1ZZ1VG1eizolnqhHf44qJrKvzTqnsW7eRfWWEwz6f1eiifJPTdWWEGK1g9R8vw1vtYmY6xp7Srrzy9nRC5JMocTn8wJ9E5PaGYFsqyqiIGc9NdmHUIaEEnPZ1YSMmlDbYrIXcJQUUbzyY9zFZYRcPofgS2cjUzYXyJOPnuKTv/23mUf1yqfubSRUvRYr5X9/GxRykq+9t9tJYPXJVJvXgNeHOiKKwdPuRKHsugBuiiT5OLv5I5DJQZKIiWq7TFNC/MT6bf8fdryM02nk9Nm1KH4UuB6PHaM5v1GiVcNjsrOL6sVoWJieAK0Kh92NwWBttI7FWsbBEx/hddlRBujxOCyo9YFtfqY6uu0vSRJF+1ZRemg9YROnEzX/Ss78849+2a60nDpG8dIPUQTqiPn1A6gT2m53/PNHbifQ5qQ61L8X7qBZk7q0/d8W+vEjCRg8AMOn31C67FMMx3cRN3cxmqjeCblqr9Zwb2w1+2utrnwXdEeU9jdhaNy9jbKVX4Ik9csQAUdpEcWrPsVdUELwwtmEXDYHmVLR7fCaCxlXQTHGT5cTs3AkkTMye3QtIVY7gM9mx7xiA4HTxzW7iPfGRVWhD8ThMPu1AUBnaE8gS5KEpewMZ/d8hauiFLlWR8xl1xAyanyvidT6O+Yta1HFRRP76wdRtxIr+Pv3lnDblt3NxjP//TyOgID6xz6ni4p/voevxkbK7Q/5ZTs5Ytocqjavxed2oQwKZvDMu1GoA9o/sBOcWvs25qLjJMRPJHPgFW3ObRqvWucx9XqdOJ1GAJRKbYslrlo6B0wEQ/PzllccIfvkl2iCIhg0/15MRSe6dNPV0u+Az+vh1P7PqDm8j6h5V9SXEutuZrckSVRvXU/l96sIGJFJ5N3XI2+h/FSAw8nvPl7Gr2/9GV6lEpdaTXU3vO+9jSJIT+Td12OfMgbDh1+T+8bLhE+aScSMi5Fr/PvZbEprYq03e837a63ejuXsb7GjVVvX11Yjkcn6VYiAz+2iavM6qrd9jyo2mphfN27+0jC8RojVjuOz2TG+9T7apHDS7u/591uI1Q5gXrMFyeUiemzzMkW9cVFVR0Zj2reT0vJKXFYD+Tu+AmgzA9yftObdknxeDHlHKD61EUdRPvy45SlXqwkd13MNGZriKC2ieMUnuItKCb50FiGXz2lZJEsShx/4DcHOxoXk7SolI/75HO4GTQEkj5fK1z/CXVRK8q0P+K1iQeDQLAw7NiNTKBh80b0oA/R+OW8dhrzDmItqO71VVp0gs52IlYaxqHXe0oT4iRzN/oyyitqsdoVC02qZq6LinZw49Q11LVnr5p0+uxaPx87ps2twOIzkFWwmLHUkqdOuq48/7crntc7LX/c7EJ42mpPb3sNecJa4a25p1EWsPa9VW54pn8tJ0ZqPse05TPDlcwi5Ym6rCXWHH34etdfL9T/sRQKmv/QrCqPDW5zbn9EOG0TA7x/DvHoThpUbMR3ZQ9SshQSPHNfrZa56cxvcX2v1psDui/Xao6E9/UE8A1hPHaN07Vd4qo2ELLyI4IWzm303+DO85kJB8vmwfvgBbrOdoS8uRq7ueSkpxGo7eC1WatZuJXTcNFTBoc2e76mLasMvUp/Tgddagz5hMC6bsVG7zb6IYfU4rFSc2knZqW14TAa0qRkk3HgXbmM11T9s6LWLp+Tx1HpTt65DFRtN7K8fQN3gjrnxZIncu55utu1frdcx+l/PNZkqUf3BVziyT5J4w91dKqLekhDyOR0UffQfvA47QxY8iFrn37JBDnMluVs+RRsej89qa9MbCrVC0+t1tug5/amzlazN89QmXEmtzvN4nOQVbCY0eQTps27pdjxkbNZFtUJVkig5uJbSnK14aswk3np/p5P2WvNMuQ3VFHz5Np6KKiJ/cQu6scNbPcdvP16G2lsboiP78acoMrQLr6x/IFOpCLl8LvopYzF+sZLSZZ9StX8zMbOuQJ/eemve1uhvW9U9SW/Hmfa3uNb+ZI+ruorSLV9j338UzeAMoh65A1Vsy6XreiK85nzH9PUazLvOMOSFawiID+uVNYVYbYeaNVtAkgif1rt1SxtnidbmF1vKzpI86WeNtk+7EsPalje2teckScJSnktJ4Q5qjh4AIGj4aMImTScg7ieBGDZhWhdfcedwFBdQvPIT3CXlBF86m5DLLmo15CC5tJxNv/5rM6F6Ojqci176VbP5pqVrsP6wh7if3YR+QNficJoKIcnjIfc//8BdWf5jvVn/BvX7vB7ObPgAZUAg44fcSVn5wfrM/da8onWdqjSa0GZzGiZdtXY8QGhwMmUVJmKiRjSaFxczhoLibfVNCmxVhX5J3Kn7TBYfWIPH40TpUZFy1yNd8ny35Jmync2h6Mv3kGsDiHn2AdSJrcenRhjN3Lm+cRb74l/eg3QeFNtXRoQRed9NOOdOxfDZCgo/eIOAYQOJmXpZpxor9LetasH5jddhp3rLOqp3bkYRFEjEvTeiG591wZRm6w2sO/ZjXrGBlLtmEjah56v61CHEahv4rDZq1m8jdOzUXmsAUEfTL9KKdd/iczkJjhtQv/1/6PM/NOtg1RHa8sY2fc5lNVF1Zi8VubtxVZajCg0nYvZ8QkZP7PX/E/gx/mjjGqq3b0SVEEvs/3sIdXJ8q/PHnDjN0v97q9n4n6+Yy2tXXtxsvGbDdswrvifq4ssIzhrbZTsbvn+Sz0fJsk9xV5YDUH16P4ljF3b53C1RuGcFdmMp40bdh1IZ0Gx7vyUaClJoHmfalkito9YDK2E05/94/CaUSi1WaynI5IQmD8VWVeyXdsB1qAIC8bodaGITSLjh513+HDb0BEmShHH3Nsq/W4pmUDqR992EIrDtZLpv//Bqo8fH4qPZNbh5S+RzGc2AVGKe/QX2fUcxLl1N3lt/RztmODETF6CJaf33ro7+tlUtOD/xeTwYd/9A1Q9rkVxugi+dTfCCmcg1nYsdF8lWbeM4eZbq974gat5w4hdP6NW1hVhtg5rvt4HX2+3e712h6ZZK8Mhx5L75V05ueZ+hFz/Qre3/tryxsVkXUXJwHYExaWRvfAPb2RxkSgWBg0cQfcnP0KUN6LM2jba8M5Ss/BRPlYGQKy8meMHMFjP968g8W9hMqHpkMqb86SnKIpvHFNr2H8Xw0TLCJk4nbEr34pcavn/la5ZTc3g/kQMnYi4+6fdKDqaiE5Rnb2ZgxqUEBdUKiKZCtCWaFv7viMAFmpW3ys3fTGhwcn3sqtNpqp0o+bBVFXeqHXBbYlaSJEqPbKBoz0qCho0k9qrrkau6n8gkeTwUb/kSy6adBM6ZSth1C9stsTb8bAHxBlOjscuee7TbtvRHZDIZurHD0Y4agnXHAUzL15G77y9oxw4nety8RjsrTemNMCnhsb1wkbxeTAd2U/nDd3gNZvTTxhFy5TzsB7Mp+c1fOy06RbJV67iLy6h+7T2ChiaQ8cj8XvdWC7HaCj6ni5p12wgZNRFloH9K0HTnAitXq0m4/ucUvPMq2WtfJWLgOKpO7elU/cmGIqDpFr/TXIGx8BhV5Udx281Un92PLnUAMVcsJmjoSBQBzbOge+q1NsXrcFC6YzmWjTtQZyQT9+CtLdZNbcijX63isRUbG43ZlAqGvPlii/OdOXlUvfkx2jHDiZp/pd9+EQ07t2DYtpGkCVcSM6ztGNKu4HHZyd36GZqQKPILf0AuVzZKlGqPhgK1IwK36TFTJ/2ShPiJbNn2InXhKkGxA7BVFwM0+3y2F7bSmpj1eT1kb3gdR0EuugGDibv6Zr/cNHmsFgqXvYvzdD7ht19N4PT2vQVyn48VTbyqr1w6C08bN07nAzKFAsntBp8P3aTRuE7nkbf3bwQMH0TUuIvRpqT3+BdY3XXF53Tic9haDC84H4Ts+fAaehLJ48F0aA+V29bhraxGNz6LkCsvRhVXGw7UVdGpGZCKzXAQzYDUHrL83MRTbaTqX/9BHRHI4OeuQq7q/WudEKutYN2+D5/VRtjkmX47Z3fjtzRRMST9/EGKP3uXkkPfE505meC45uneLXmnGmVRSxJBcQOwVuRRU3oGU0UOHpMBmUKJLm0AMQuvJnDwiHZFelsXVH/FqlmOH6H0uyX4bA7CbryCwNmT2xUpY4+faSZUJWhVqLrLKql45T3UqYkkLvCPCAKoOX6E8lVfEzNsZo8IVagtU+W2/eTha8krWlS8k9Nn1wKQkXZx/byGntHObP3XxamGBifj9brIrlyH221FplASP3o+cSNav4FqrwpAS2LW47ByYtv7OH5sPemqKPPLe+QoLaZwydtILjcxv7wHzcDUDh1313ebf0wp+9E+mYy/XH1Jt+05FzCv3IC32ojz1FniX3oK2+5DmFdtpOC9f6NOSyJi7CyChmT1WPOPuuuKXKtrtYvS+RAnez68hp7A53Ji2reTql0b8Fab0I4dTsiDt6JOims0r2GGf2e29p05ueCTav8WAOCtsWJ45S2QyRjy4mKUgT1bzq41hFhtAUmSqFm3Fe3oYajD/ZcI44/4LU1UDCn3Po5h2yYqt2+k/NhW1NFxhISnow2LxW4ooeL4dkCieP8aNEHheOwWdBHxuKwGkKT6sj8Amph4ggYPR5c+CF3aAOTq1jsdNaWtC2p3X6unxkzxxi+x7z1MwIhMwm9ehDKyedZh0wvRI0u/4/Fvv280xwcMfeV3La7jrbFQ8Y93kAfpSVp0J3JV221DO4qjqICSJf8jcGgWieMv6/J5yo9vo2jvKgASxl7SSOhZys5iLT/bYHbLGfl1iVRQV1LKAUj1hf9bSqJqXDuVRoK2Lk7VYDzDzsOv4bQYSJ60iKjBU7vtWWsqZu3GMk5ufBuf00HY5FnUZB9s9TPVGW9UzbHDlHz9EcroSKKeuhdlRMczWleNGU5yRRW3bNoFwJSXn+7wsec6DUWATKFAP2k0uomjcBw+gfm7zZQs+R/l4SGEjZ5GyBj/x7V3pDxST8XJ9qa3U8T6NsZTY8a4+wcMe3/AZ3egmzCS4Etntdqgo2GGf9FTL3XYyyrKWDXGZ7Nj/PebeMx2hv/tRjSRPdehqj1kkiRJ7U87tzCbzYSEhJD46vPItZ2/C7AfPUnF394mbNJMao4d6rdbMT63C8uJbKw5x3AU5uGqqgTJ1+JceYAWn9NRn50NoAwOJePx33Z5/Z64eEs+H6Z9Oyhf/y0ylZKw6y9HN2FkqyKo7kKkiAjFXm1E1eTTbNIGkPXq8y0e63O5KX/5LTyV1aTc8QjqsAi/vAa30UDef/+BKjScobPvR67sugA+9Pkfam8yALU+rD7+U5J8HFv+D2yG4vr3NHPgFS16Rht6VoEfhasMpTKg/t+ZAy8HaBQO4HQa0WhCAer/XdeC1eNxAj5U+jAGzbubmtLTfq/3ayo8xunNH6IMCSXhhjvbfX9O//0FPCYDypAwMh77TYtzJEmiess6Kr9fhXbsCCLuvLbTSRgACq+XPY/9gdcXzOStS2d1+vjzFVdBMTVrf8C68wAAuvFZRA6ZSkBS6jmfkd2Rz5fAf0iShKMon8ojm7HtPlSbOzF9PEEXT2/RcdEaImmqa/jsTkyvvYG9oJph/3c9+gz/1BpvisfqZNeif2IymQgODm51nhCrLVDx7w/wlFUhWZzn1MVJ8nqp3rYRw84thIyeQPCIMcjVGhQ6PXK1ul5capNSsRfk9jsR7iwrpnjtF7hy8tBPH0/oNZe2m5Fds3EH1m/W83ejmV80ee54fAzzX3i8xeMkn4/K1z/CceQEybc92KVaqnU0FO3BWWPIe/sVJJeToQseRqXt3p1oa57VylO7yd36KcmJ0yirONJuiak6mnpM65KilEptvce1TpS25Fk9m/s9Lrel/nxqfShZ1/6G/R/9Bq/LhkKtY/RNL3TrNUuSRNnRTRTu/hb9oCHEX31zhzoptXfz5HO5KFr7Mbbdhwi+Ym5t84hOhBNcdOAoWblF/OOqeZ16PRci3hor1i27sWzeiaeiGlV8DKEjJhGcNdav3tbe9HaKONLewed0Yj6yH8OhH3DlFaGIDCfooskETh/fYgc5gf/x2Z2YXn8TW24lQ/90LUGZce0f1EU6KlZFGEATvKYa7AeOET3/SmRyhd+3YnrygidTKIiYPoeI6S3b25+KNjfE53JStWkt1Ts2ooyOIPqpewnI7Fj9ttEDUlhvNDcb/9vlc/hnG6LC+MVK7PuPknDdHd0SqtA4HMJyKhuPycCQSx5qUah2tnRTSzGePp+X4gNrCE0ZwYDUSxiQ0X68ZEOROnXSLxs9V9detWFx/6bxq7ExozmTuw6X24JMriAobiAOY5nfKxv4PG5yDi7BfGgPuvRMnGUlmA/t69Dntq3Pt9tkpPCrt3GXlBN5/03oxmV1yq5gi5V3X/kACXjnoik41UqcAX0Tu3UuoAjSE3zpLIIWzMCRnYNl8y4q1n1Lxbpv0Y4cTNjA8egHDkXezXbMvRnb2V+vn+cDkiThKMjFdGAX5qP7kVxuAoZnEvXw7QSMyOyzCjQXIj6bHeNrb2HPr2LoSz0rVDuDEKtNsG7fB3I5wVljUWh1fr84dfTi2lOitr95BywnjlK65it85hpCLp9bW45K1bGP5fRDx/nwn+82G/9gxoQ2hWrNxh3UrNlC9CWLCBzceneijlIXX6aOiMJ66hgD596JNqzlWKqulhxrKHLlChUuSzWjMm9q97g6ker1OvF47M0SsBq2R1UqtWSkXdzMQ1tZdZzjud/itteQMG4hscNmIpM3TqBJGHtJp5tTNMVlNXFy67s4y0uI+9lNVKxf6RchYi/Mo/CLd5Ap5MQ884s26/K2xpd/egOoTara9dRLPHPrz1g6pet1eC8UZHI52uGD0A4fhLfGim3nASzb9lK87z3kOi1Bg7MIGj4GXWpGlwSJiO08t3FVV2I+vA9T9h48ZZUowkMJmj+DwGnjOhVHLvAP3hoLxlffxFlmZtifryVwUP8QqiDEajOs2/ehGz0Uhbbt7eeu0tGLa8X3K/HZbVR8v9KvorI1sdzbItZtqKZk01fYD2QTMHwQYU/ejSq6NiaxIzFGH778FtOPn2405gVG//3/YQpufevdfvgEho+WETpxOmETp/vltYSOn4JMraZ06cckTriCkMQhrc7tbMexOpHqdTvxumyUHvoeSZKQKZSYzHkEBrbeYQl+KjOlVGrrt/dbmtNSJyu7w8CxktUY848QHD+IQfPva7XzVntZ/m29ttisi9CGxZGz6X1kCgXJP3+IgPgkfE5nt4WI6eAeSr/5HHVqAlG/uAVFSOfDMpJLKxhUUl7/WOv2sHLciC7bdKGiCNITNHcqQXOn4i4uw7p9P5ZdBzHt24k8OJCgQVkEDcmqFa4drCYgvJ29h7++I9xGAzXZBzGd2o/rbAEyjRrd2OGE37wIzeB04UXtIzzVRgz/ehOPxcmwl69Hn94zMapdRYjVBriKSnEXlhI97dIeW6PDF1epyd9+ojWx3JbH159C1ufxYNi2gaqt65DrtUTedxPacSMaJV+0VyNv6fP/YEx+SaMxc4CGEf/+fZtruwpLqHzjIwJGZBI9/8puvY6GOIoKKFv+OcGjxhMz1L8lquo8sQq1DrU+jIDQaMxFJ4DGxfxbi1ntSNvUuqQpr9dJUfFOYmNGk1ewhbzCzSg1etJn3kxY2ii/J8jUvbaivavwepxoE1OIv/a2+pJp3REiks9HxbpvMWzbiH7qOMJvWdRhj31DZD4fW379l0ZjH00bh1Pd/WYEFzKq+BhCr15AyM/m4zpbiG33QSx7j2Dasw25TktA1mBCk0agyxiMQoRb9Au6GnIhSRKuynIsx49gPnMQ19lCUCrRDh9ExD03oB01tEtJjgL/4S4uo+pf/0EmlzH8bzegTWjeNKevEWK1AfY9h5FpNegGDO5rU4iac2mPbG+1JgDa8vj6Ky7MeuoYpeuW4qmsJmjuNEIun4tc27xUVlvlQ/738lvNhOrmzDRueeq+Ntf2mmqo+Od7KKPCSbr0Vr/dvXssNRR99i6a2HgGjLi6XUHXmTCA8uPb8LqdKNS6+uSqfR/++sdnZY2y9lvrOtWR2qkJ8RPrz3P67DrOFG3C47AQM2wGcSMvRqHqeDmzzhAzfCaF+1biddkIHT+V6AVX+aU+p9dhp3DFBziOnCT0ussIunhal4X2Jy837oAmAc/esbjbNgpqkclkaNKT0KQnEXrtQtx5Rdj2H8V+IJviHftBIUczMI3gpKHoB2Sijo4756sKnKt0JuTC5/FgzzuD9dQxas4cwVNehUytImB4JhFzp6EdOaRLyc8C/+M4eZbq195DHRHIkBcX92l5qrYQYrUBtv3ZaLOGdDvo3x/09vZWW+t1Ny7MVV1F6eal2A9koxmcQVQ7Haga1shryHt/+y8zmmz9u+TydoWqz+Wm4tX3wesl6Zq7kGv8I74kr5fiJR8geb0Mmnp7h0pUdSYMoPTQ93hdNtT6sHphqwzQ4fZ5GZR+SaN2qe11nYLGSVYNBawkSURGDKaodDcej43QhBEkjrus2ZZ/w237Ovua/rujoQBOi4GKgr3g8xF71Q2EjBrfoePaw1VVQcGS/+I1WYh69A60wzO7fC6F18vkk2cbjc38wxPdNVHQCjKZDHVqIurUREIXzcdTWY390HHsh05QuWk1FWu/QREShGbIAIJjMtGlDUAV2v88QOcrbX1HSJKEq7wU29lTmIuP4zx+GsnlRhEWTMCIwYRdfzmaIQOQq/1Tx1rgH6w7D1D97ucEDU1g8HNX9VnB/47Q96qsn+AxmHAXFBM5wb/ZzecDXRXOPpeTqi3rqd6+EUWQnoj7bkQ3LqvTnpEgq5Wtv/ozoXZno/FdGcksfvaBNo+VJInq95bgLigh6fYHUYX4L2i/Yt0K7HlnyVxwH2p9SLPn68SdPjoVa3lu/d8dFXVNha0kSXjsVtJT5tSLzY52nYK6hgB2Tp9dS0L8RAqLdnI2bz3yAA3OmmoCY9JIHLuQwJi0Fo9v6BUGWvx3R16XqegEZ7Z8hEytJvnO2vjUpnQl9MSac5yir/6HIjiQ2F8/gCo2qkPHtcauJ/7Y6PG6EYPIi+tfcVznM8rIcIIumkLQRVOQ3G4cJ8/iyM7BkX2K0p0HQJJQRIahTxiANiUNbVIa6sho4XntBSSfD2d5Kfb8M1jKT+E4eRaf2QJKJZoBKYRcPpeAEZmoEmPF+9EPkSQJ8zfrMS1bS9TcYWQ8tqBPWqh2BiFWf8Rx9BTIZOgzuu6JEdQiSRI1h/dRvuEbvDU2gufPIHjh7C7FJcWXV7LtmZdperl7+6Ip/P6m9uNOzd9+j23nAeIX34o2IbnT67dGTfYhDNs3kjjhCoJiM9pscevKNYIk1f/dlqhr6r1siOTz4vM4Uav03ba/svIYp86sQPJ5kXkdDJh7FyGJg9v8Ymkqnlv7d2tIko+SQ99TvG81uoxBxF99Mwpdy6+lM6EnkiRh2L6JirXfEDB8EJH33NDteowZxeVE1lgbjf3iF7d265yCriNTqdAOG4R22CAAvBYrzpNncZ44g/3EWcyH9oAkIdfrUKcno49IISAhmYD4JL930boQ8VgtOIoLcBTmYa3KxXk6D8nuBIUCdWoCgdPGEzAkA/WAVOE97ef4nC7sn32EadNxkm6bRuKNk8+JGwohVn/EeeI0qsS4Vr88BR3DXphH6fdLcZ3JRztmOGHXLkQZ1bWtumc/Wc69635oNv7gPdfzzcTR7R5v23MY09driJg1n6Bho7pkQ0u4qiooXfYpgUNH1idUNfU61nlUKadFz2prNDxPXQWAgl3La8XgiNnIFMr61qmdJTV5Nrn5G0Cp4NDRD1EHheNzu4gfNQ+X1cDhL/7YSGw3FeANRXhs1kX13bSAdj2qHqeNU7s/wXoqm4gZFxMxa36bccMdDT3xud0Ub/gM67Z9BC2YSejVC/wSj2wI1PLlpFEEuDzMP3CUp275GU7xJdxvUATq0Y0Zjm5Mbek5n92B83Q+rtN5OM/kY9i1GZ+t9vdEER6KOjkeXUgimth4NNFxqMIizvus867sTkiShMdkxFlWjLO0GKupAFdeEd6q2i568kAd6rRkghfMQjMgBXVakl+So0SXqU4gSUw6cYYdmenQSZHpqazG9J93sRcYyPzNlURMP3ecc0Ks/ogzJ4/A1NZLDgnaxm00ULr9G2w7D6BKiiP6l/cQMDijy+d77d8fsHDfUQDeAP4EPA385+VnqAwPbfd4V34xVW9/hm58FhEz/ddxyOd2U/zFByj0gQwcfW39HWlDr2Od4KS88Xhnt/4Ldi0HQPK6awXs4Q3oo1IosRwnUZrS5t1wXXxqStJ09PoYCmyHqM4/gM/rISxhONHDZmA3lNSKa5msxcSvurH8HV8BtYK0K3VirRX5nNryAT6Xk4Sb7iZwYPu/Zx0JPXGbjRQufQd3YSkRd1+PflL7NzAdpTo4iMfvvgGl243S48GhFZ1z+jNybUB9PVf4UXRVVOPKLcSVV4Q7v6i2r7yl1lsuU6tQxUUTEBKLOjIadUQ0qogo1OGRyM+TSg9t7U5IXi9uQxWuqoran4oy7DWluItKaz2mgEynrRX5Y4fXxhKnJaGMCu8RL1x7FWAEPzHryAne/8e73Proz9k0ouNi0370JIb/foxCq2bEP2/qd6Wp2kOIVcBrseEpr0I7LaVX1utvhfm7g9fhoHrreqp3bEKuCyD8tqvRTxvXLa/FV394lbFnC+of/wnIAx4OCyGuA0LVa7ZQ8cr7KOOiSbj4Rr9eXCvWfoOropQhCx9Gof4pGL2hwKvzqDYUru1t/de1VA1O+OniI1eo8HrdyBQqVAGBxGZdhFofRs66/3JKuZKMtItRKJp/sbrdNs7krsfttnLy9LcgSagDw4kdPovIQRNR60MBOLvpo3rbWkr8is26qFaoNghdaDqvrY5ckiRRcewH8ncvJyAugfjFD/gtIcaef5bCJe8iUyiIefp+1KmJfjlvsMXK7z7+hifvuhafXI5HpcKjEh7Vcw2ZTIYqOgJVdAT6CSOB2s+jz1SDq7AEd1EZ7uIyHCXlWHKy672wAPKQIJRR4Wi0EahCw1GFhKIM/vEnKBiFTt/vt019Tichoydg3P0DutQMqjatxW2qxmGvwlNRjbfaCD4fUCvclXHRqOKi0WYNQZ0YiyoxFkV4aK+9zrYqwAgac+mew7V/7z3cIbEq+XyYV3yPadlaQsemMfDpy1AFn3s330KsAu6iUgA0sQm9sl5vtgjsKSSvF+OebVRuXYPkdNXGpV4yq8VSVJ3h9J2/avahXBQfzStOF4EduJBJHg+Vr32I5PGQ9LM7/eolsRw/gnHXVpInLkIX0VwcNfSoNtwiby+esy7rH8CQe6BeHNZ1haoLHwAITRpC8sRFFOxeTnHZXgKjU9B59YCETWnHYarAZamuPbFMTlBMOvFjFhAYnYJM1vgGoqnXt6nYbLrtXzfWcF5rYtzjspOz/wss2QcJnTid6IsvR+anKhvGvdspW/kVmvQkIu+/uUuF/ltEkjjw6AvIJInZR45jCdAw74UnsIsakOcFMpkMRWgw2tDgRlUiJEnCZ7HiKavEXVaFp6JW0LmqqrEdPY3XYAapQcFrhQJFsB55cBCKID0qWSAKnR6FVociQIs8QItco0GuDkCuViNTqZGrVMiUKmQKBTKFsvZmXi6r/Z2UyUCSaktq+3xIPh/4vEheLz6PG8njQXK78Lmc+FwufE4HPocDr8OOz2HDa7PhkmrwWqz4zBa8phokp6veXPPBPcgD9SgjQlFEhqEbNwJlVDiq6EiUsZEoQoP7PCSitQowFwxtbO3LfD5u2biDYJsDaCBW9xymILL25t+sC+B/syYhNXkfvaYaLB9+iGl/Lkk3TyXxpinI5P37Rqs1hFgF3CXlIJejjuhe9nBHOZdbBEqShCX7IOWbVuCpqEY/ZSwhV12MsgMez/Y4e+evaHrJ/M/cqXx1wxV09DbC8PFynGfySb7tF6hCum9THR6zidJlnxGYOYyoIVNbnNOSd7IjnZ1isy6q96xqgiKwVReij06tP/bQ539oJAijh04jJHko1af3Ya0soMZjQCaToVToCUsZgS4igcDoVDRBEW2u2xHb2pvT0mu2VhaQs/V/eG1W4q+9jaChI1s9vjO7DJLHQ/HWr7Bs3EHgrEmE3eA/AQzw79c/QvGjKAm32gm32rGLONXzHplMhiIoEEVQIJoBqc2el7xevKYavAYTXmMNXpMZr6kGX40Fb40VV40BX1UhXqsdyWZHcnt6w2jk2gDkgTrkei3yQD2q6AjkGSkoQoJqf0KDUYSFoAgNFkX3+zltbe3rnG4e/3oNYVY7PuB1mYyXgV86nDyx9DvkgEGv5cvJY7E2cBbZj57E+N6n4JMY+tK1hI5J7c2X5HeEWAU8FdW1Wx5+KEjeEc7VFoHW0ycp3/ItrtxCAkYMJvKBW1An+qd3cM7dzzQTqrc+cAubfkyg6AiWTTuxbNpJzOXXok1uufxSV5B8PkqWfQoKBRljrqXixPYWt75bEnZtbZO3dNyhz/8AklTvSYWWBaEmMJy4kXObnasupKAzNU87Ym/DUIW6BgVNbZckibLszRTuWUFAbDyJt9yHOrxtwdzRXQZPjZnCZe/hzC0g/LarCZwxodOvrS1kPh+X7T3caOyS3z7c6QQGwfmHTKFAGR7a4RtyyePBZ3ciOZz4nC4klwvJ5UZye5A8HvB4f/Se+pAk6acuhTJ+9LjKaz2wSgUylRKZSoVMrUKmUSPTaJBrNbX/Fp/N84a2tvatWg2XPvcIr7z5CWNP5/GyJJEHvCxJ/ALYk5HCg/fdWC9UJbcH49LvqPluMyFjUhn41KWow8/9ihhCrFLrKleGBfe1Gf0We0EuZT+swHn8NOr0pG4nTzVEZ7Vx+JHfo5Qa95VdNXJop4SqMyeX6o+WETh7MqFj/budZNz9A7bTJxg4725UAYGdSjLqbEJSR7yzbQngriRAdeT4hqEKLZ3b7bCQs+czrKeyCZs8k6g5Czvk9ezILoO9IJeiL98DSSLml/eiGeCH2PIm226bnnm50dN70xLJTumdsCDB+YVMqUQRpISg3qksIzLpzz06u7VfHBHG9U/dw8GHnudpl6s+4dimUXPdU/fiUdY62lyFJZjf/wh7fhUpd88i/urx5+y2f1P6nVj94x//yIoVKzhw4ABqtRqj0djja/qsNpSyli8s52IylL9sdpQUUb5jJfaDx1DFxxD54K1oRw312x39Q0tW8sSqTc1qqE7/w5Pkx3U8JMNrNFP52odo0pOIn7rIL7ZB7f9j5eY1eK0WQsdPJSShtg1vZ7pQtTe3pfJQrZWOqqMtQdoR29oSu60d3zBUoelz5uKTnP7hE/B5SbjxLgIHDW3nf+Un6j6fVVvXN3pch3HPdspWfYU6LZGo+29GEeqfm8qG2274fKRUVjd6/tbH7wJqveo+qw3J4QS5HLlehzygZ9rPCgRdQWTSn3t0ZWt/5NkC9C4X9wH1PRudLkadLWB3ehI1323BtHwNAfFhZL1yC/qM1rtEnov0O7HqcrlYvHgxkydP5u233+6VNSWXG7mq5TZj52IyVHdtdpYVU7ZrNfa9R1BGRxBx9/XoJoz0axD+uy+/yUXHzzQak4DxLz9DRSfiXyWPh8rXPwKZjMQrbvdrDGPV1vV4a8wgk5OWubB+vCOxnh2d21J5qKbPNRWlbQnSjtjWFe9rS+f1eT0U719N6eGN6NIGELfoRpTBIZ2+WWrp8+pzuynevATrlt09Ep9a58m4bNcBrt22r9Fzv5s0mvyla5DyT2PPr8LnahyDqArVoR8YC6mD0Y4a2u1OWQJBV6jzqGoGpOIkV2TSn0N0dmsfYO6BYwCsHj2MP167kP/32bfMP5DNsK27WfP111hOlhJ/9XiSb5uGXN3vpF236Xev6Pnnnwfgvffe671F2/AUnovJUF212VFaRPnu77DvPYIiMpzw269BP2WM32N5j9z//whyuRuNeWQyBrz5R6Qf1+ro1pbh8xU4zxaQfPsDKIP8G8qhTUimxmQgZuh0FKqe8aa1VB6q4XMtidKOCNKueE+h40LWYSrn1PaPcJYVox88DGdJEZYTRwkdP6XTN0tNP69uk4HCr9/FVVBK+B3XEDhtfLvnaI/Wtt2u3Hmw0Twb8PyO/QTEhxI0PJGoOUPRxISg0GvA68NtsmEvMmA5XoJ5+RqMX6wkMDMW9aSp6CaOEoksAr/S1nWwzqPqJJeE/3umjywUdJWObu3XsW7UUI4lxbFs4iiQybj7vhuJ/8+n7N6+D01cKCP+diNBQ8/f0KV+J1a7gtPpxOn8qW+82Wzu1PFytQq35GjxuXMxGaqzNtuL8qnYvQb7gewfRerV6CePRab0f8LZiXufJcDjbTTmlUHGf15qdNPQka0t6479WNZvI/rSq9EmpfrVTrehGsupY0QNnkrShCu6fJ72EqxaKg/V8LmuxJ3Wna810dnWedsLI5AkicoTO8jfsxxlcAgpdz1C0WfvNRKnnb1Zavh5tZ45RfHSD5CpVMQ+47/6qa1tu13r9fIsEPrjvOmLxjL6slFok9pODAPwOt0Yd52hfM1hqj/4EvPSlehnTyNozhTkep1f7BZc2LR1HRS1Sc992tra3zMwtdHcPQNT68ecObmYP/6CgoIqEq6dSNLNU85Lb2pDzotX99JLL9V7ZLuCPDgQd0GJHy3q/0iShO1sDpV71uLIzkEZE0n4z69FP3FUj4jUiGoTe375YrOM/50DUrj2mV80m9/ehdhVVEr1+1+imzTa7zcTkiRRtvJLFFodieMu7da5WhKNbcWp+ovWRGdHxHNrtrjtNeTs+xzryWxCxk4iev6VyNWaZuK0Kzd4kiRR/cMGKtevIGBIBhH33IjCjwkqTbfdfi9JlAMvA9XAf4Cdo5IJuL/juxEKjYqI6ZlETM/EUWKk+Ks9lK/agGXtJvRzphM8bzpy3blXfLunEIlAnaet6+AFX5v0PKC1rf25B7KbiVUAr8WKZ/XXlK06RGBmHCP/fRv6jHOrE1VXkUlSkzTsHuDpp5/mz3/+c5tzjh07xuDBg+sfv/feezz66KMdSrBqybOalJRE4qvPI9e2HIvaENOKDZhXbWTgU38878uBSD4flmOHqdyzHtfZQlRJ8QQvnIVu7IgeKwwdZjJz4PE/Nhuf+7uHOZXU+W0Ln91J6R9eQaZQkHrbI8jV/t2ir8k+SPHn75Nx0R2EpXS8IkFLtCQO6+qmqvVhjZoHtDa/K2u0Rt3ayGQkT/pZh9cw5B0md8cXIJMRe8V1BGYO69BxHcHrcFC05iPs+44SfOlsQhbN67HPolRYwpDn/8kan4Qa+AXwYoCKq9/5OabIkG6f32WwUvzFLkq/2Y9MpSBw3iyC5k4T4QFA0VMv4a0yoogIFdvWAgEw7lQuCVWG+q19JIkrdx6gKCKskViVfD6sW3Zj/noVktdH8h3TiV04Cpmib5s5+AOP1cmuRf/EZDIRHNx6KF+veFafeOIJbr/99jbnpKend/n8Go0GjabrgkWdFIdkd+Curuy1xgC9jc/pxHRgF9V7NuGpqEYzOIOoR39OwPBBPSrQIw1G9jz5UmNbgIl/fpryyLBOn0+SJKo/+BKvwUTq3Y/7Xaj6XE7KVy9DP2hYt4UqtOypbOj1bCo0u5L81Jlj2oqRbQmP086Zo19jPriHwMHDiblsMcpAP3WMojaZr/Cr9/CaLUQ+eCu60f4TwQ3xOV2Ylq/DumYzKp/EMSATaitRONwkl9Vw2A9iVR2mJ/We2cRfM57CT3ZQtnwttg1bCbxkDoEzJiJTnRebWV1CbFsLBI1puLUPgEzGskmjG81x5uRiWfIV1lNlRM0dRsrds1CH9U5ZtP5Er1w5o6KiiIrqvyJQMyAF5HJsZ071mFjtqxJYbkM1ht1bMe7fgeR0oRs3goj7bkLjp1jAtgg117C3iVAFGP+XZ6gMC+3SOS0bd2DbdZC4a25FHdm57Q/j7m1UfL8SJIiac2mL70PVlvV4rRbSs67skn0doWkTgIZCUx+diivXiD46tdExXU2YamltaL8FLICp6ARnd3yOz+kg9srrCR413q83NqaDeyhb8QXK6Ehif/MQqphIv527IfbDxzF/8iVug41FQ+L57GgRCmqrT0jUCtZp23M4PMx/vxPq8EDSH5hL/NXjKfjwByo+/Qbb+o3oL52HfrL/kxbPBcS2tUDQcTyVBlyrvqZy43H0A2IY/vebCB52/iZQtUe/u83Pz8+nurqa/Px8vF4vBw4cAGDAgAEEBvZMFwa5TosmMx1jzr4eE5LtZUj7U8xKPh+2s6eoOrwF+8FjyLQBBM6YQNCcKSgjOu/N7Ao3rf+BFz9e3tguYNJLT3VZqLryijB8+i2BsycTPHxUp4+v2roen91W/++m/89uYzWGbRuJHTar3ValbdGZbfmmQtNantusgxV0PWGqJdqb73U5OHP8G0x7d6BLH0TsFdehCvXf58bndlOy9Sssm3ainzKGsJsX9cg2uddixbV8CRXrswkZk8qwP1/H2AO5KI4WAdTX9/3zwxdzNq1nblIDYkMY+OSlJFw7kYL3t1L17hJsa9ejv3QBuvFZfd6TXSAQ9C98NjvmlRupWbcFZVAAGY8vIHreiPOmuH9X6Xdi9be//S3vv/9+/ePRo2td4hs2bGDWrFk9tm7g9PFUvfUJjpIiAuL8f/fSXoa0P+q5eqwWzAd2Yzi4DU95FaqEWMJuvgr95DG9GjN3/J5n0XqbZvzLSG+S8d8ZfHYnlW9+jCo+mrgpV3XpHBHT5tR7Vlt6HyrWr0Su1XbIQ9kWDYVl3eOOJjS1VZS/o97T7mAqOsHZnV/gtduIWXgNIeMm+9Wb6qquonDZe7iLygi/9WfoZ0zokTAU24FsTB8twefyMODJS4i6eDgKn8Qz/1jbaN6ni8aw/LLRrZzFf+iSI8j8zZVYTpWS//5Wqt76BNt3a9FfMh/t2OFCtAoEFziS203N99uxrFqPz+Ul4doJJFw7EYVWxLtDLyVY9TZms5mQkJAOJ1gBSB4vJb/5K8qocJKvua/XE6266lmVfD5sp09QfWIHtv3ZIAPd2BEEzpqEZmBqi6+jp7JytTY7Rx76XbM7oNyocGa+9FQjodoZGyRJouq/n2Hff5TUe57okVANR0kReW/+lZQp1xCVOblb52roWa0Trg2TqbqSRNXSuWtKz2DIPUBY6igyZt3cLZs9Thtnj32Daf8udGkDa72pYeHdOmdTao4dpmT5JygCdUTefzPqHmhn6rM7cH2zhPLvDhM2MYOMR+ehjqiNsX3q76u5ctWh+rluGcz67im/29ARao4Vk//+Vkz7ctGlRqKdPw/duJ5LchQIBP0TyePFun0vlhVrcFVZiFmQRdItU+qvW+c7/SrB6lxAplQQdv3lVPzrPUzpOwgd2z3B0lk6W+7HUVqM+dBezNl78RrNqOJjCL3mEvSTx7Rb8qcn2vOFmi0cfOyFZuMbhg3k9h9bV3bVBuv2fdh27CfuZzf1WExx5YZVqMKjiBw4AeieoGzqLW3qEe1KElWdTQ2To1w2I0gShtwDQNfFqiHvMLm7vkJyu4i5fDEhYyb59WZN8nioWL8Cw/ZNaMcMI+KOxT1S0slx6iymdz/BbbbVbp3NH1H/OlROdyOhCnDNh/f73YaOEjQknmF/uhbz0SIKP/yBqjc/xrYyHO28uegn9Ez5OIFA0H+QvF5sOw9iXfUdjmIjETMzSb5tOtpE/zoJzheEWG2AduQQAmdOoGzVV6jCItGnD+xrkxrhqiynJvsgphP7cReVIg/UoRs/Ev3UsahTEzssMPydlTvmZC5L//x6s/Ftg1JbFKqdscFdVonhw6/RTxlLcNbYbtvakgfbUVSA9WQ2Co2OipM7u5yV3xKdrQYArQvl0kPfgyTVlo9q4lntCi6biTOHlmI5dhiZUkXEjIv9fpPmNlZTuPwDXHmFhF5/GUFzp/l910LyeDF9s672xmdIPMP+7zoC4kIbzVl1zSuNHp9OCacyqu89F8HDEhj60rXUHCum8JPtVL/9OdZvV6ObMxv9tHGi5JVAcJ4heb1Ydx7A9t1aHIUGwiYPIPM3V6LPiOlr0/o1IgygCZLHQ8Ur7+M8cYa4RTcRNHRkD1nZAVskCWdpEZbjRzCfPoy7sASZRo121FB0E0aiHT7Ir/3Su8JDX63myRUbGo35gKkvPklxTPe8oJLHS9mfXsNntZN25xPINZ17L1vi9N9fwGMyoAwJI+Ox3wBQ9Ok7WE5mg89Xv13fHc9qZ2ip5mprdVj9ZZMk+ag4sYPCfSuQKZVIkoTPZm30f+IPLMePULL8E2TaACLvuxFNerLfzl2Hp6IK83v/w3KylKRbppJ4/aRmtQeHHC/mPw9/SEOJPGPlE3j7offSeqacos92UrnpOMrAAHSzphJ00WQUQT2TXCoQCHoHye3Bum0v1rXf4ywxEjZ5AEk3TSFwUGxfm9andDQM4IISqx2Nk5Tcbqre/hzb7kMEzpxI7KTLUWh7p32i12bFdjYH6+njWM4ew2swI9MGoM0ajG7sCAJGZCJXq3rFlvb46xsfcc3uxlurDqWCzDf+2OVEqoYYv/oO8+qNJN/xENrElG6fD5p7Vl2V5Zx99U+Ep4/BUna2x8VpU9ryrOqjU7GW53bLpqbnt1UXc2bvEhyFeYSMmUjU3MuoOXrQr2XVfB4Pleu+xbBjM9pRQ4n4+eIeaT9q3XkA44dfogzRMejpywgaEt/ivJhSI9HlZl5/8lNkwC+fX8S2yf1r16Qp9R2xVh8GSSJqzlDkU+aiihfel/6I6M4laA2f3YFl006s6zfhNliJmJZJ4o2ThCf1R4RYbUGsdqaDiiRJWDbswPjlKpDLCR8/nZCxk1AFh/rVVrfZiKMwD3v+WSwlp3HnF4MkoYyLQjs8E23WEDSD0vpdDNsvl6zgwVWbG42ZNWpGvNY8brUrOE/lUvbnN4ictYCImRf75ZwtUbbiS2qyDzHy6v+HXNEzXuquekTb6nTV2XOo9KGEp46kLHsL6ogoYi5fjC6l6404WsNVXUnR8g9wFZQQuvhSguZO9fu2v8/pwrXsc8q/O0zk7CGkPzwPpb795hAvP/s5MgmefOlav9rTk7jNdspWHKBk2T7c1VZCxqSinjaLgBGZIhmrHyG6cwma4qk2UrN+G7bN2/G5PETNGUbCtRPQJnW9LOL5iEiwaoHOxGrKZDKCLpqMbuxwTCs2UL1lA1Wb16IZmEpQ0hC0SWloYuNRBLSfKCJJEj67DZehCndVBc7yUmzmItx5RXhNNQAoIsMIGJRG0EWTCRg6EGV4aHdfbo/x7Kffcu/aLY3GfMCIf//eL+f3OZxUvf0Z6oxkwqf1XKkmn9OB6eAeYofMaFOoNhWbnRWfTeNfO3q8P8pVxY6YTfH+7/B6HJSf2EbkRQsInzyrR8JHzIf3U7ricxTBgcQ++wvUPdB4wlVQguntD3CW19SXpGpNDEdUmHn676t56g+LkeQyfvniuSNS61AFa0m8YTLx10ygatNxir/ei+lf76GJC0U7bQr6aeNQBF543Wz6G6I7l6AO55l8vNu+p3LTcRRaNTGXjSLuqrFoIvs+Rv5c5oISq13poKIICSL8xisIXTQP255D2PYdpWrrOiSnCwB5oB5FWAhyvRalL6DW2yH58Chc+BwOfBYbXqMZyeX+6ZxhwagSYtFPG4c6NRF1WjLKsNbvKPoLKqeL/Y/9niCnu9F4XkQYM/7vab+tY/z8W7xmC0k33NejnX7MRw4guV1EDZrY5rymYrOzyVdNRWdHj+9ssf+m2I2lVJYdxuO0Epg5nOgFV/m9HBXUtqgt3vwl1q170E0cRfgtizodK94ekiRh2bQT02ffEJAYRta/b0WX3LqHQuaTWHbTG8iAGz/dwadXj8erOXcvd3KVgqi5w4icMxTL8RJKlu2j6uvvMC9bQ8SMTOTjZ6DOSOn1knuCWkR3rgsbye3BtucQzi2bsZwoISA+lLR7LyJ6/nAUOv+2BL9QOXev3r2MXBtA4PQJBE6fgOT14i4ux11UiqeiCq+xBp/VhtflBp8HZDJkqgBU4SG1YjYkCGV4CMrIcJQxkX7/Iu8NdDYb2Q89T9Ovwh2D0rjuV/f5bR374RNYNu0iZuE1qMN7pv1mHeaDe9ClD8JYeKxNT2fTFqid9Xh2tPB/Z2jLO+tx2ik+sIbyY1tRhYWTcONdBA4a2uW12sJRUkTRsg/wVhsJv/0a9NPG+X/b3+7A/sUnGDYdJ+ayUaTeOxuFpu247Vef/Lj+s3r/e1sIM9l49f6WG3KcS8hkMoKGxBM0JB7XvbMp/+4wZSsP4lz3OrrUSNSTJqOfPFp4WwWCXsBTUYVl0y5s23bhMdkIGZ3C4Od/RtiE9GaJnoLuIcRqF5ApFKiT4lAnxfnlfP09OP/nqzfx3Bcrm40/c9OVfHyR/5KRfDY71e8vIWDYQELG9WydW4/ZhD3/LKnTrqN4/3dtejqbtkDtrsezs8e3JExb8s5KPi+VJ3dReHAVPrebyIsuIWzyTORd2PJvr0mF5PNh2LmFivXfooqLIfa3D6OKi+70Ou3hyivC+N8PcBttDPr1FUTOHNzuMQqPl1FHiuofy4Cll4/yu219jTpMT+L1k0i4diKmfbmUrTpE9ZIVmL5cSfiUAchHTyFg2CAR2yoQ+BHJ48F+IBvPrh8w7stFodMQPW84sZeNEvGoPYgQq/2AnijS7y9uW7O5RaF6/eN3sn3YIL+uZfh8BT67k/h51/f4dqblZDbIZIQmD8Pndbfp6eytVqet0ZIwbWqTqegEeQe+wVVeQvDIcUTNWYgyOKTVc7YnRttq/+ux1FC0+iMcR04SdPE0Qq++BJnKv5eS+gTHz79BlxLJ0BcXExAf1qFjl1//WqPHmydmUJR4/n6JyOQyQselETouDZfBSuX6bMq+O4x907uowvUETBiHfvJo1In+ubkWCC5EXIUlWLfuwb5rLx6TnaCh8WQ8fgmRMwejCOgfFXrOZ4RY7Qf01+D8d/76H+Zk5zQa8wIX/+4RTie1XCaoq9iPnsS6ZTcxly1GFdIxUdIdrKePo01MQanRtevp7K4ntbu0JJbrbLJVl3Bsy3+w5hxHm5RG8t2Pok1ov55pW2IUIGLanHox2xDLyWxKvv0UgKhH70A7on1PZ2fx2ey12/6bTxB7xWhS75mNXN2xS9WlKw8SarY3Gnvu/13hdxv7K+owPfHXjCfu6nFYT5VSvvYolRt2UbN6E7r0KNRjxqGbMBJlRM//jgkE5zpeswXrzgO49+zCmlOGMkRL1JxhxCzIQpfas2FqgsYIsdoP6I/B+Ufu/TVBHk+jsWMJsSz4/WN+X8vndFH9wVdoBmcQMrbn/x8kScKed5bogW2v1VuNAdqjJbHsshjIPfUd5gN7UIVHEH/tbQQOyeqwR7o1MVpH0/a/PpeLkh3LsHy/nYCswUTcsRhFsP8L1Tfa9v9/VxI5I7PDx2rsLn79j+8ajT3/5CW42olvPR+RyWQEDoojcFAcqffMxrjnDBXrszEsX4txySqChiWgHDkW3dgRKEL7f3KnQNBb+BxO7Aey8R7chXHPWWRyGWETMki8aQphE9KRq/pXGckLBSFWBc048MBvmwnVz6eM5Zd39kzpH9PXa/CZaoi/4b5eyWb2mI14bRb0kUltzvNXy9WGdFcAux0WSg99T/nxH5BrAoi+5CpCx07udCmqpmK0LRwlhRQt/xBvZTVhN11J4OzJ/m+ZKklYNu7A+Fnnt/3r+Psznzd6bAzSsGbeCH+aeU4iVykInzyQ8MkD8dqcVG3LoXLjMYyffYvhk+UED09EMWIM2tHD+nXJPIGgp/A5XTgOn0A6uhvDztP4nB6ChiaQ9ou5RM4ajCq4/RKVgp5FiFVBIw489DvCHM5GY9+OHt5jQtWVV0TN2q1EzrkUdUT32rN2eM3KcgC0YS3H8DXsIEU5fo1V7aoA9jjtlB3dROmxzciA8OlzCJ880y8taFuiLqZVE5uANecYqvgfk6h6oINSw2z/zm7716F0exmZXdxobPEH/qtScb6g0GmInjuM6LnDcJvtVG/PoWrzCYyff4vh4+UEZsahGD4S3ehhPZIwJxD0F3x2J/Yjx+HYXgw7z+BzuNFnRJN481QiZw4mILb1mH9B7yPEqgAApcvFoUd+j97VuIbqgZR4Hnjwlh5ZU/L5qP7fV6jiYwifPKtH1mgJj8kIgLHgGGVHNjbzctYJSsrpcueo1uhsspbHaac8ezOlxzYjeb2ETphK+NSLUOp7tld85eY1eGvMeEwGgi+ZRchVF/dII4HG2/5XEDmjazGwPrmMJ5//GQEOF4+9vp7t49OxdaCr1YWMKlhLzPwRxMwfgcfiwLDjNFXbTmH8dj2mL1cTkBiGauhwtKOGoslI6Xdd9ASCzuI11WA/eAzp+H6M+/KQ3F70A2JIvGESETMy0Sb4vw61wD8IsSrg6o07+Ov/ljaroXr9Y3eyfbh/M/4bYtm8C9fZQpJ+/lCPFv9vitfpQKZSU3ZkY4teztYEZWe38Fua39FkLbfDQnn2FsqOb0XyeggdN6VWpAb1bHyhJEmY9u/Ea7eCXEbQ3GmEXnNJj6zz07Z/BEP+uBhtQteTfnwKOdsnD0Dmkzg6OJ7yuFD/GXsBoAwMIGruMKLmDsPrdGPal0f1jhwMO/dRs2YLCr2G0HGpSOlZaIcPEnGugnMCSZJw5xdjP3Qc7/HDWI6XgFxG8NAEUn4+g/ApAwkQ14pzAiFWL3Ce/HwFD323udGYBNz+0G09KlS9NVZMX65GP3UcuuS0HlunLVoTpa0JyqK9q/C6bBTtXdWlNqsdwWkxUHZ0ExWndgLUitQps3pcpAJ4aswUrfsMx8Fj6KeNI+z6y3ukgUXttv/HGDadIPby0aTe2/lt/zriigx8dM87rJ8+iD8+fTmSXCaEajdRaFSETx5A+OQBSD4Ja04p1TtOY9x9BsvmL0ACXXo0ikFD0A4biHpAKnL1hZfEJuifeC1WHNk5OI6cxHXsGO5qKwqdmpAxqQx4cjRhE9JRher62kxBJxFi9QLmhydfJNFgajQmAWlvvYjUw55O09LvkCSJ2MmX9+g6LaHQ6ZHcLiIGjOvRLP/ObPlbKwspzN1EzdEDyNUawifPRKYJwLhrK+rwyA4nQ0H7NVRbwnzkAGWrloBCTuRDt6Eb1TMdr/y17V/HOw9+gMbtZcH3x/jw+snkiXIyfkUm/6mqQPKt03AbbRj3nsW4Nxfjrj3UrN6ETKUgeFgCpA8hYHAG6pREETIg6DUktxtnTh6O7Bx8p49hOVkKEmhTIoi6aChh49MJGp4osvjPcYRYvUDZ+fgLxJosjcZ6S6i68ouxbN5F9PwrUQYG9ehaLVGXyGU3lBIY1X5N0joSxl7SrTarTZF8Xoz5Ryk+swV73hmUIWFEz7uCkNETkWs0nP77C23WQm2N9mqoNsRjtVCycQm23YfQjRtB2M2LUAT5v1WnJElYvt+O8Ytvu5zt35TJ208RbK1NBpQDrz/2EZcufcQP1gpaQxWqI2rOMKLmDEOSJGy5lZj25WI6kId59QZMX32HPEBF8PBEpORBaAaloUlN8nvTCMGFi+R24zxTgPPEGaTc49RkFyO5vShDdISOTiZm4ShCx6ahier97xZBzyGuIBcYcq+XU/c82+yN3zBkALc/eXePry9JEobPvkUZG0no+Kl+O29nvIkBsQnI1RpMhcc6JVb91RzAZTVSeXIn5ad34qkxoU1OI37xbQQOHt4odrelWqgdeZ3t1VCto+bYIUpXLQGvj4h7bkA/cVS3X1tL+Gx2bJ99jGHrSWKvHEPq3bO6vO1fh9Ll4S/PLW009s7NfVcL90JEJpOhT4tCnxZF/NXjkbw+LCdLMR0qwHwwH8uP4lWmUhA4KBZZ8kDUGcloMlJ6pEav4PzEa7HhOp2HMycPKf8UlhMlSG4vCr2G4BGJpNw5k5BRyehSo5DJe770oaBvEGL1AmJC9kk+/+vbzRKpbn/oNjb00LZvU+wHj+E8fpqEG+/ya1JVZ7yJMqWSoOGjKD26mcpTu4jLmtPjRf99HjfGwmwKj6zBVVEKcgUho8YTOn4qAXEJLR7TUi3UjrzO9mqoeqwWSjZ/hW3nAbSjhhJ+689QhPSMF8J5Jh/jfz/EY3WQ+duriJjmnzjoL257q9Fju1rJkqvH++Xcgq4hU8gJGhJP0JB4uG4ikteH9Uw55iOF1BwpombXHsyrNgKgiQ0haEg8npgMNGlJqJLikWvUffsCBH2O5PXiLirDeSYf15kCfPlnsBdUA6AK0xM0LIGUu2YSPCIJfVoUMoW8jy0W9BZCrJ7HSD4fntIK3GWVKK02Pn93STOhOuuFxzgbH9s79ni9GJesQjM4A/3AIX49d0e9iXWET5uLad9O3E6HX4v+N0TyeakpPU312QNU5x/C57DDjwJdGRhE7BWdr13b2dfZlJrsg5Su/hI8XiLuug7dpNHIZDJqNu6ob/nrj25qks9HzZotmL5ajX5gDMNevt5vdQtDjFaiqxqHsCz6+H6/nFvgP2QKOYEDYwkcGAuLxiFJEq6KGmqyi6g5VkzN8RKsW1chub0gl6FLiUQWn4w6JQFVcjzqxHjkWlF+7HxF8nhxl5bjyivGlVeIrCQX6+lyfE4PyGu99sEjk0m4YTLBQ+PRxIX2StMYQf9EiNXzDJ/Vhu3gMThxANOBPLwWJ8OBw03mScCtD9/ea0IVwLptL56SchIuv8kvF52mW+KdietUh0cQNGIMNYf3oQmJRPJ5kcm77+n1uh2Yi09hLDhKde5BJLcLuU5P6PipBGeNxZ57ultis7Ovsw6PpaY2NnXPYbSjhxF+81WNyg+ZV27AW2XEvHJDt8Wqt8aC9aOPMO4+Q/ziCSTfMR25HxNult/wWqPH/71pEjWiw0y/RyaToYkORhMdTOSs2ptVn8eL7WwFlpOlWE+WYskpxLjrQK2ABTRxoejTo/BEpKBOiEWVGIsyKrxXS90Juo+3xoK7sBRXYSnuwhIoK8CWW1n/PgckhhE4MJaIaZkEDo5DPyAGRYCoMCH4CSFWzwMkjwf7weP4DuzAsOs0ksdH4OA44heN4+dGG7/7Zn/j+cCAN/6AR9V7FwPJ7cG0fB268VkExLfd5rSjdGbrvyXir76Z6vgkKtYs58iaf5E0bD4hCYORyTu+teRx2rFW5mMpO4vRkIO9MA98PtSRMcjkMiRArlITNedSADRRMV2ytatIkoT50F7K13wNMhkR996IbnxWs5uF4Etn13tWu4PjWA6Gdz5G8voY8odrCJuQ3q3zNWXsnrMovVKjsfdume7XNQS9h1yp+Mn7urB2zOfxYs+rwnq6HOuZcmxnyrEd2YbZZANAplKgTQyHyDiUcdGoYqNQxUahjIlEHiA8sX2F5PPhNZprd/NKKnCXlCOvLsSWW4WnwXunS4lEnxFN9Nzh6DKi0WdEoxQNPATtIMTqOYy7tALLpp3Yd+7FY7KhHxRLyl2ziJyZiTo8kBU/+yehVlfjY4C4G65A34tCFcCyZRdeg5noCf4rMN/dLXGA8Mkz0SamUP7dMnLWvY1CH4QufSAhmnjUgWEoNTpkcgU+rwev24HHVoPTasDqrsRZXoLbUAWAQqtHm5JO9IJF6AcMRh0e0cjz2xe4jdUUr/scx5GT6CaOIuyGy1EEtZzYEjRrUrc8qpLXi2n5OswrvidkZDIDf7UQdYT/42ALksI5PDiOEcdLALjvrzcgiaSK8wq5UoH+RxHTEJfBij23EltuJbb8Suz5Vdg352A22urnqML1aBPC8AbHooyJQBkZjjIqHGVkOPIgvdhG7iaSx4vXYMRTUY2nohp3eRUqSwmOYgOOIkPtFj4gU8oJSAhHkxxB7OVJ6FKj0KVGok0IE3Gmgi4hkyRJan/auYXZbCYkJITEV5/vkaLmfYnk8WI/cBT39i2YDuSjDKrtPBO9IAt9Wm1JJrnHy8ZL/0rTjbKScD3x1dYeraPZos1uD8XP/BlNZgZJC3qmdWt3kSQJR1E+NdmHsOedxlleiuR2NZ8oV6AKCUUVHokmKhZNbDwBCcmoI6P7zReh5PNh3LWVig0rkeu0hN+yCO3I1mOEuxuv6qk0UPP+/6g5XkzyrdNIuG5ij34hBdY4WHHtK6yflsnvf31Fj60jODfw1DiwF1ZjLzLgKKrGUWTAXmzEWWLEU+OonyfXKNFEBaOODsaji0QRHooyNBhFWAiKsGAUIcHIA3Wd2lk5n5A8XrzmGrzGGrxGE16DCU917d8KSwXOMjOuagv4fpQMchmaqGAC4kMJSAhDGx9GQGIY2qQIAmJDhCgVtIvH4sCWV8mRxz7GZDIRHNx68xvhWT1H8BrNtV7UH3bgqrIQNCyBgb9aSMT0zEZlgORuD5sX/q1ZIlVFuJ7pt0+Hv69Gk9Hxck3+wPLDHrzGGqLHzuvVdRvSXsknmUyGNjEFbWIKUCtefQ47Z1/7P7w1ZpRBIaTe/yTyAG2//jJzlBZR8t1nuHKLCJw1idCrF7R7w9adeFXbnkMY/rcEhU7D8L/eQPCwxO6Y3yEsQQHMXPXLHl9HcG6gDAr4qQpBEzxWJ85SI44SE85yM84yE86KGrwVhdizj+E2WGvjouqQy1CF6lCH6VGF6XEpQ1EE6ZEH6ZHrdSj0OuR6HXJdADKdFrk2ALk2oN81QZDcHnx2R+2P1Y7PZsdntdX+WGx4a6z4aiyo3EZcBhtuoxWPyd7oHDKVAnVEIJqoIDSxIYRkJaOJCUYTE0JAXAjq6GC/xqILLhwkr4/yNYcpeW8D+oiOORT7lVjNzc3lhRde4Pvvv6e0tJT4+Hhuvvlmfv3rX6NWX3hlTSRJwpWTh3fHBqq2nESmVBA1dyixl49Gnx7dbP70LSd46YVlzYTqO9dP5O2fz6TyqU8JzkpqdSu4J5C8XmpWb0I3djiaqJheW7cpnY1vlclkKLQ6ImfMqxe5Cp3/i+X7C5/LRdWm76jevglVbBQxT9+HZkBqh47tSryqz+nC/c0XVK46RMT0TDIenY8yqGd2MRQeL+/c/z6bpwygIjKIbRPTqYz2T2UBwfmNUq9BmRGDPqPla4/P48VdbcVVZcFVbcVt+PFvow230YbSWIG7KA+32V7rpfW1vBEpUylQ6NQotGoUASrkASrkGhVyjRKnV4dMqfzxRwEKRa3XUS6vvfGVywAZ9Rdu6cc/fBKSzwc+H5LXC14vkufHH7cHjcKGz+XG53DjdXjwOVx47W68dld94lIzO5VylMFaVMFalCE6lKE6tCmRqMP1qEL1qCP0qCMCUUcEoQzWirqlAr9jOlRA5X9XUnbcxPCFSUy9O5M3r1rX7nH9SqweP34cn8/Hm2++yYABAzhy5Ah33303VquVv/zlL31tXq/hc7mx7TyAc+tmrDnlBMSHknL3LKLnDUcZ2LIgmLrlBH96YVmjMQmYt+RBbME67AVVmA7kE3Hndb3wCn7Cvu8onopqEhbd1qvrNqWr8a1dzb7vTSwnsyld8yVeYw0hV15M8IIZyJQd/9XubLyqK78Y09v/w1lhJuOx+UQvaJ6w5U/ev/dd0gqqGZBXCcDXOVm8/NiCHltPcOEgVyrqKxS0h+ST8NqceGoctT9WJ16rE6/Nidfqwutw4bW58DpqBaTP6cbn8qLxWfE5PEhuLz63F8njQ/L6kHw+JK/0owCWaBiQJ5PJkClkIJchk8uRKeXIFHLkKiUyVe3fcpUSZaAGeYAKhUaFXKtCEaCuFc06NQqdBmWgBmVgAIpADaqgAORadb8JVxJcWDiKDVg/XMGJdcXEDQvj1g9mkDgyAqfF3aHj+5VYXbBgAQsW/PQllJ6ezokTJ3j99dcvCLHqqaiiZsMO7Nt24bE4CJuQTvIdMwgdm9bmHe4rj/yPMcdKGo1ZtCouWfIQvh/bHBYv3YsqVIdu/IgefQ1NMa/dgiYz3W8VALrKuSA6O4vbbKRk01Lsew8TMHQA0Y/fhSomssfWk3w+atb9gOmrVeiSI8j6923okiN6bD2ArIN5pP1YFLyOd27xX+czgaCjyOQylIEBtQ6DuL62RiA4N3Cb7RR+tI2yb/ahjwjg8j+MZfjCpE577fuVWG0Jk8lEeHh4m3OcTidOp7P+sdls7mmz/Ibk8+E4fAL3js0Yd59BGRhA9PwRxF42qkO908fvOt1MqHplMH/ZY/WPXdUWyr87TPDCOch6sQqAK7cQ1+l84q+7o9fWvBCQvF4MO7dQuWk1Mo2aiLuvRzdxVI96TLxGM9aPP8K4N5e4n40j5eczut0ytSO88qvPGz3+ZNEYqiJFz2+BQCDoz3gdbkq+3kvZF9uRfBLT7xvChJszUGm79r3Rr8VqTk4Or7zySrte1Zdeeonnn3++l6zyD15TDZate3D8sB1nmQn9gBgyHltA5KwhHS6G/NsXlzN/4/FGY26FnDnLH200VvTFLuQqBUFzetezWLNhO4rwUAIzh/Xqur1Ne8lb/sSWd4bStUtwF5UROHsSoYvmI9f1bEF824FsjB98jkwhZ8iLiwkbl9aj69Vx24fbUDaIEfQCr97XN2XABAKBQNA+Po+X8u8OU/7xZmwGJ6OvSWPaPYPRR3Svlm6viNWnn36aP//5z23OOXbsGIMHD65/XFRUxIIFC1i8eDF33313m8c+88wzPP744/WPzWYzSUl9u+3cEpLPh/P4Gby7N1O97RQyuZyImYOJvexyAgfHddgzpq2x89UtbxBsaxzrYQwOYOGShxuNuaoslH1zgMD5M3tc1DTEZ3dg23WQ8Klz+iR7vjcFZHebE3QET42Zkm3LsW3fhzo9idjfPIQ6JaFH1qrD53ThXrGEyhUHCZuUwYDHL0EVquvRNesIMtu454OtjcaeeO4qbHlVOCvMeG0ukMlQBQWgiQ1BExMikkEEAoGgj5C8Pio3Hafy4w0YCqwMXZDIzAeGEJbkn4TuXhGrTzzxBLfffnubc9LTf+p0U1xczOzZs5kyZQpvvfVWu+fXaDRoNP23A4bHYMa6bQ+O7TtxlhjRJkeQctcsouYOQ9XJNpHDDuXz5pOfNsv43zB1IP/vuUXN5hd+sh2ZWkHwvN7t8mPbcxjJ7SFk1PheXbcOfwnIjohefzQnaI36Lf/N3yFTKgi/7Wr008b1+A2AM7cQ87sf4awwk/7wxcQs7Nkwg6Ysu+H1Ro/zVDJefXE5XrevxfmaIBWJo8LxZY0gfMpANFEiVEAgEAh6GsknUbX1BNWfbKDydA0DZ8bys79MJCbTvxVbekWsRkVFERUV1aG5RUVFzJ49m7Fjx/Luu+8i78c1LdtCcnuwH8zGu287ht1nkasUREzPJOaXlxI0LKFLX/wTd5zib79d2mz8Tw9fzDeXjW427igxUrbyIMFXzusVr2rD4vK23YfQDM5AFdJ+3G1P4C8B2RHR21PJW9acE5Su/wpPaSWBsyYRctU8FIE969mUfD7MqzZiXrYWXXoUI1+7DW1SzyZRNSWkwoymSemdyyZHM3tSNLGDQwmJ1xEQpELySdiMLgwFVkqOGsjfU0n+m+s5++91JI+LRD17AhHTM0WPcYFAIPAztSL1JIbPNlBxykza5GgW/m4MCVlt5xh1lX4Vs1pUVMSsWbNISUnhL3/5CxUVFfXPxcbG9qFlHUOSJFxn8rFu349jz348NQ4CM+NIf3AukbOHdqv/8b8f+ZBRx4qbjS96927KE1oWhPnvb0UZrCVoTu9kT9cXl//2e7xGMzGXL+6VdVvCXwKyJ72mreGqqqB0yzLsB7LRDEoj8t4bUSc1L3jubzwVVdT87yNqjhWTcN1Ekm6eilzVe0W/fS4PZasPUfj5VnKBIIWMMK/Euy+P54p5LTcbCAhWE54cSMbUGLgHHDVuTm4o5vDyfHJeXknhG2sJu3gksZePRtvK74lAIBAIOobk9VG1+QTVn2+k8nQNqROjWPDeDJJG96xTo1+J1bVr15KTk0NOTg6JiY2/nPpzV1h3cRnWXQdx7d2Lo9iIOjKQmEtHEjV3GLqU7pcSevuetxmcW9VozCODeV8/glPbsgC2ni6jckM2YTcvQq7pnYYKdcXlNQNSse0+RNDgzpfJ6o1Y086s0Zslr7wOO1Wb12LYuQVFSBAR992IblzHaph2p2WqJElYt+7G+NlyVCE6hv/lBoKH93wnqvr1fRIV32dT/r/vqSmzM3RBIn/8+SCiB3Z+GykgSEXWFSlkXZGCocDC/iW5HPz6ECVL9zBgWgzqS2YQMjZV1JoUCASCTuBze6n4PhvDF5upzreSPiWaS387msRRvbPzJpP6swrsImazmZCQEBJffb7dVpOtIklMOnGGHZnp0MIXm7u0Atuew7gP7sN2pgKFXkPEtEFEXjSUkKwk//RFliQ2XPIy6iZheivmDuPFpxa2eWj2s1/gKDUS9Ztf9norwPJ/vovkdJF6w4OdPvb031/AYzKgDAkj47Hf9Ih4bbpGXyN5vRj37qBy82okl4vgS2cRNH8mcnXHt6+LnnoJb5URRUQoCf/3TIeP85pqsH3xKYbtOUTPH0HqfRd1awegs5iPFlH5nxWUZhu5Ynwk7+WY+deKebj0/tu6dzu8ZK8qYPcnZyg/YSIyPYjgyycTNWeYCBEQCASCNvDaXZStOkTV0u3UlNkZNDuOKXdlEj/cPztVToubv079FpPJRHBw6805+pVntT8x68gJ3v/Hu9z66M/ZNCITSZJw5xVh238Uz5FD2HIrkQeoCJ+UQdIt0wgbn+b3upPrL/tbM6H6+RWj+OeD89o8zrg/D+Oes0Tef3OvC1XJ48F54gwR0y/u0vFNt917ItO+L7b2W0KSJKwnsynb+A2e0gr0U8YQsmg+yrDOexS70jLVtu8oxg+XADD4d4sInzKw0+t2FbfRhvPD5RxZnk/s0FBueW8Gb9+7FZXTx3VP7mLlE8OpGuCfAH1VgIKRi1LJuiqF/D2V7P7oNKdeWUPxuxuIuGQMsZeP7lAHI4FAILhQcBmslH69j8oVe3DZPAxdkMjkOwYRNaBvrpVCrLbCpXsOYwGi12ymev8RXEezcVVaUARqCJ+YQdJt0wkdl4pC43/PjMzr48ub3yCgSZLJ1/OGtStUJZ9E3n83EjgkHu3Y4X63rT1cZwuRnC70aYNandOWt7TptntPCMv+0M3KUVRA6eZlOE+cQTM4g8i7r+9WKarOtEz12ew4l31B5bqjhE8eQPqj81GH6bu8dmeQJInyNUco/u86JAkW/L9RjPpZKhOW5qJy1t6ZZW4rJ6h6D6995t+bCZlMRsr4KFLGR2EstLLn0zMc/HofxV/sZNDseJQLZhCclSRCBAQCwQWLLbcSVq/n8LcFyBWy2uvzLQMIieudsoWtIcTqj8h8Pm78fhvmonJyKqt49fhpbgHc2TlEBQUwISmcgdMGceiuWch6snOPz8eWS/7SrDTVB9eM4817Lmr38KpNx7GeKiP6V/f1yZeu83QeMo0aTWzrCUGd8ZY2FZa9WT+1J3BVV1K2/Vtsuw+hio8m6uHbCcga3GvvlSP7FMb3P8NrczLgyUuIunh4761dYqT69aXk7qhg2KVJzH1yBPoIDWqLm0UvHKifJwM239qzXt7QRD1znxzBjF8M4fC3+ez55AxVv/yUyIwggi+dRORF3UuIFAgEgnMFySdh3HMWx4rNnN1eTmBUANPvG8zoxWlog3sn56U9Lmix6rPZcZ4twJWThyLvBP86WIAVCAZSgEDgYeC5Ggey7GJMBdVcc/t0bD0kVh94dS03LN/fTKg+/+QlrJnXfrKSz+0l770thE3KIGBQ73QZaoortxB1cjwyRevhB93xlvZGAf6ewFNjpmrzWoz7tqMICiT89qvRTxnb5v+TP/E5nHhWL6X8m/2EjEom44lLCIjxbx281pB8EqXf7Kfw7Q1ow9Rc99qU2uz9H3lq/upG8y0hKo4sTO4V29Q6JWOvTWfM4jRyd1Ww99MznHptHYVvbyDsouHELhyFPiO6V2wRCASC3sRjdVKx7iimb3dQnWchdkgoV/xxLEPmJ6JQ9a+yoReEWJV8PrxVRtzFZbiKSlFV5WLJKcNRaABAGRRA0NB4Uq+fyNM7TnNdbiUDAQPwHvAccGhoAs89ezk2Xc94W15/4D2yTpU3G5+79GHs+o4liZWtPIiz1EjYfXf427wO4y4qQ58woM05XdmGr/OoapNSsUOfx5t2FK/NSvW2DRh2bQGlktBF8wmcM7VTyVPdxXHiDKb/fYa72kraA3OJvXx0r3V7cpQYqXzlK/L3VDLm2jRmPzoMTYPkqfGfn0Fr8TQ65q8r5/eKbQ2RyWSkTYwmbWI05jI7+5ec5eDS4xz89gAJWWEEXDyJyBmZKLT9w8sgEAgEXcWWV0np8v1Urz+M2+klc048C383msTREf02DOq8Fqs177yLq7IGR4kR6cf4T4VOjS49mtCxaQTeMJnAzDi0ieH1X97/uWUaV1/9L552uPkT8DTgCFDx4F+ux9sTyUqSxJor/4He0bh1qg+Y/+VDHRaqXruLwo+2EXXxcNSJfVOTVvL5cJdXoc6a3Oy57m7f13lU7dAvMvjbw+twYNixieqdG8HrI+jiaQTPn4Fc33txPz6nC9NXq6lZ/wNBQxMY+uLiXqs1KkkS5asPUfDmerSham58axqpE6OaTuKqPx5sNPTFC6NxBfZthn5wjJaZDwxl2j2DObWphP1Lcjn9t1UUvrmW0FnDiVkwAv3A2H57URcIBIKm+Fweqn84hX3NNgr2VqGP0DD+pgxGL04jOKb3WrF3lfNarMoUckLHpBIQF0pAYhja5Ag00cFtfskMPVGC1uHmPuC+ukGHm6EnSjg8zM+1JyWJzQteRtGkeJhTpeCiFU906lTFX+3BY3WimnOZHw3sHD6rDTwelCGhzZ7r7vZ9f8ngbw+f04Fh51aqd27E53QRNHsSwZfMQhHSu+0/HafOYv7gU1yVFlLvnk3corH+KafWAVzVFoz//pLTW8oYuSiFuU+OQNOCAL3xsZ2NHju1cg5ckdorNnYEhUrO4LkJDJ6bgLHQysGv8zi07DiHvj1A9KBgdHPGETV7KKrQvk08EAgEgtawF1RRtuoQhvUHsRtcJI+L5Mo/jWfw3Ph+t9XfFue1WB307OWdTpKYuiMHgE1TBvLve2bx4FsbmLEth2nbc/wqVlNPl/Lh/R80i0/9aNE4Xru//USqhrjNdoqX7CZw5iSUkX3XpcdntQOg0AU2e66jYrM1D2xfZPB3xhvsdTgw7qoTqU4Cp08geOHsLpWh6g6NvKlDEhjywtW92i61autJ8v+1ErlCxuJ/TWLgzLhW5w7dWNLo8Rvvz+xp87pMaKKemQ8OZfr9QzizrYyDX+dx6j8byP/PBgZMj0U2YxJhE9J7teOXQCAQtITX7qJqy0mc3++kYF8V2hAVIy5PZtTVqUSmn5tl+s5rsdoVtk4eQE56NGtnDwGZjGeeW8TFG45RGuO/Nzi+oJKP7v+g2fjlH91HdVTn1yn+YheS10fwws6JXH8juWpDGeTK5l60jorN/pRA1RFbvDYrhp1bqN69BcnlqhWpl85CGR7au8YCjuOnMX34Oe6q3vemeqxOHO8u5cTyfAZdFMclvxmNPrztG8X/d2ARALffs4Wy9CDKM0N7wdLuIVfIGDA9lgHTY7EZnBxdVcihZXmUPb8UbYiKkJnDiZozjMDBcSJMQCAQ9BqSJFGTXUT5d4cxbjmGy+ohZUIUV/5pHJkXxaPUnNs30kKsNuHwsEQOD2swIJOx9qKhfjt/Yn4ln971TqMxCZi35CFswZ2PG3EZrJR8vY/AOdNQBDf3aPYqP345S5KvnYmt05+2+9uyxWM2Ub1jE8a920CSCJwxgaAFM3vdkwrgsztxr/6K8m8PEDw8kaEvXoM2IbzX1jcfLaTwL19jM7hY+PwYsq5M7pRQe++t6T1oXc+hC9Mw/sYMxt+YQfkpM0e+zefoymOULt9PWJIe/YwsImcPRZfce55tgUBwYeEoMVKx/iiWjQcw5FsJidcx4eYBZF2RTGhi79TP7g2EWO1F0nNK+N8v/tdsfMEXD3ZJqEKtV1WmkBE0f0Z3zes2cm2tJ83ncHT5HH1VsL+lLf+WbHFWlFFx6Hus2/chU6kImjuVoLl9d6NgP3wC00df4Klx9Hqmv8/jpfDDbRR9up2ErHBueGsaYe1cHBVODz+/+we++MNYjMl9fHPlR6IHBnPRY8OZ9fAw8vdUcmRFPieW7abwo+1EZ4YQMG0UkTMyCYgL7WtTBQLBOY7bbKdq03FcW/ZSeKAatU5J5tx4Lv3taJLHRvbad0BvIsRqL/G/n/+H9B9LZdXho1aoWkO6lqDhMlgp/WY/gfNmogjs+yQPRUgwyGS4zYb2J/cz2trylyQJe+5pKg5swHHwGIqQIEKvmkfgzInIdX2TRem1WHF98yUV644SMiaVjEfnExDbe15de1E1pX/5ktLjRqbfN4Qpdw5Crmw/5OCJhWsJqXDw5OVrAfj62ZHsuS69p83tNeQKGakTo0idGMWCX4/i9NYyjq4uJOejreS/vYn44WGopowkYlpmr75fAoHg3MZjdWLYnoNv+x7Obi9HkiB9cjRXvDiOQbPjUOvObzl3fr+6fsLmef9H02gRm0bJxd883q3zFi/ZjUwhJ/jiad06j7+QqZQoo8JxlpW0P7mf0dKWv8/tpubIfqr2bcZdUIwqIZbwO65BP3E0MlXf/OpIkoRt10FMny1D8nrJeOISouf1XhequpJU+a+vIzA6gNven0H8iI6FHAxZV0hIRa3Xvc7aI/O63mK2v6PUKMicE0/mnHhcNg+nNpVw7LsiTr+3mby3NhI3LBTVxCwipg/q1bANgUBwbuC1uzDsPI1s515ytpTidflIHBXO3F9mMeTiBPQRF06XPSFWe5Agg5UV1/27mVAtjA3hug/u7da53WZ7rVf1omm9WruzPTQDUrHmn+prMzpNwy1/t9GAcc82jAd24LNYCRiRSeg1dxIwbGCfJs14qo3Yl3yOYedpwqcNIv3BuajDe28r3W2yYXr9S05/X8Kon6Uw95dZHb6bV9o93PzE7kZjKx8dhiPswrjYqnVKhl2SxLBLknBa3eRsLuX4umLOfPwD+e9sJmpAMJoJwwifOhD9gBiRnCUQXKB4rE4MO3KQ7drHmW1leJw+4oaFMvPBoQyZl0BIXP/5vu9NhFjtIWKLDXx5+3+ajX87Zygv/ar7tVBLvt4LkkTQvP7hVa1DO3II1m17cZaXoonum+YEXUHy+bCeOkZ19jbsh44jC1CjnzKOoIsmo4r9qZh9zcYdmFduIPjS2QTNmtRrtlk2bMe0dBVKnYbM5xYRMXVgr6xdh3HPWfL//g1el5er/zaRzDnxnTr+6t/sbfTYGSDnhzsG+dPEcwaNXlUvXN12D2e2lXPi+2JyvtlD4cfbCY7VopswmLBJAwjJSkLeQ+2dBQJB/8BVbaF6ew7sOUjuznJ8Hon4EWHM+MUQBs9NOK8SpbqKuAr2AI/+czWLVxxqNCYBK/wkVL12F6XL9qGbNhFFUP9KUtGOHII8OJCKwxtInHNDX5vTLq7qSswHdmM8vBOvwYwqOZ7wWxahmzgKeUBzr5955Qa8VUbMKzf0ilh1FRRj+eRzLCdKiLlsFCl3zux07eDu4HN5yHt7EyVL95I2KZrLXhhDUHTn4nQDy2xkrS1uNPbShoX+NPOcRaVV1ocKeN0+8vdVcmpDCac2naB0+X7UOiVpk6PxjMwibEJ6r3rSBQJBzyBJErbcSgw7TuPde5iiwwZkMkgaE8mcx0eQOSeO4NgL04PaGkKs+pkXfrOEi3aeaTTmkcuYufIJkPun5mX5d4fxWJ0Ez+t/JX9kKiXBl8zC+PkKHEOmExDv565ffsBrt1OTfRDj8d04T51FptWgnzAK/YwJaFLbtjf40tn1ntWexOd0YVq+jpo1m9EmhTP87zcS7O8Oau1gPVtB8ctfUp1nYe4vRzD+xozOZ5lKEr9asKbRUOHgYNzneTJAV1Co5KRNjCZtYjQX/yqLilNmTm0qJWdLKUV/Xw0SxA4JRTlqCKET0ggaHN9rdXQFAkH38Lk8mA7mY9h1Bvvu45iKbai0CtImR3PZ78cwYEYsutALIyyqK4hvDD9y71sbmgnV4xnR3Pn67X5bQ/L6KF66l8iZgzverUqSmHTiDDsy0+trofYkQRdNxrptH0XLPiD1tkdQ6Dq2hdGZjlGdxed0YjmZjfHMPuyHj4PXR8CQAUTcfT3a0cOQa9QdOk/QrEk97lG1HzqO+dOvcFVbSL51GvGLJ/RqZyTJJ1GydA8F72wiPCWQOz6ZRfTArmWuhxXakPsa9xN+88OeFfrnAzKZjOhBIUQPCmHq3ZnYDE7O/FBGztYyzq7cQ+En29EEqUidGIV72HBCx6aJ6gICQT9CkiQcxUaMe84iP3SYvN2VeBxeQuJ1ZEyPYeDMOFLGRZ7zxfp7CyFW/cQLzy/loh8aJxa5FHK/ClWA6h2ncZYYCb3z5g4fM+vICd7/x7vc+ujP2TQi06/2tIRMqSTy/psoe/Hf5H/2BkmL70EZGNTucf7uXuWxWrCezMaUdwjH0ZNIbg/qtERCr74E3fiRKMP6V9s5j8GEc/mXVG0+QcjoFIb+6Vq0Cb3bPtdZWUPVv5aQu6OC8TdnMPvhYd26mJpjAthw5yBmv30SgNc+mI7vHOpH3V/QhWkYflkywy9LxueVKDlq4My2Ms5sK6f41bVIXomwJD3qkQMJHZ1C8MhkVF2s3SwQCLqGx+LAdCAf475cnAdOYSy0IlfKSBodwYz7B5MxLZbIjCCRQNkFhFj1A68/8iFZxxrH5FWHaLn8i4f8vlbJ13sJGpqAJi2pw8dcuudw7d97D/eKWAVQxUQS/cTdlP/9bXLf/itxC29AP6DttbvbvUryenEUF2A9fYKa/GO4zhYAoE5PIuSqeejGjkAZ1f9KBEleLzXfb6Nm+RrkGhUDn76MyNlDev2CVrn5OPn/WoVSo+CGN6aSNjm62+f0qhWsf3AoY5bns+eqJIpGRvrB0gsbuUJGQlY4CVnhTL9vCA6zi7zdlZzdUU7ujlOc+PYAyCAmMwT5sIGEjEwmeERSr8Y6CwQXAl6nm5rsYkwH8pCOnKDkqAHJB2HJetKnRpM+JYaU8ZFo9M1bkAs6h0ySJKn9aecWZrOZkJAQJix9pEcv0NGlRr669S2aSopVFw3lD093P5GqKba8Sg7c/Q4R99yAfuKoVufJfD5u2biDYFttTcv7Vm4gyOnCHKDhzUtmAWDWBfC/WZOQ/BRH2xqeaiNVb3+O8/hpAoYPInL0RejSBiDzw7o+pxNHSQH2gjws5adxnjqL5HAi0wYQMGQA2qzBaLMGowhp36vbVzhP52H5bAnWM+XEXjaa5DumowwM6FUbPFYn9ne+4vA3BQy+OJ5LfjMabUjHwiLaPrEHlOJ+uLcxl9rI3VlB7q4K8nZXUlNmRyaHmMxQZEMGEDwiieDhCai62IxEILhQ8TrdWI4VYzpUgOzYCYoPGfC6fejC1KRMiCJtUjSpE6MITRDZ+x3FaXHz16nfYjKZCA5ufbdTiNUu8tSfv+HK9ceajS+bP4L/e+KSHlnzzL/XUbXpOLF//jWyNkSA3u7kh1+9RJjVjg94A/g/4CngPkAOGPRapv75Gazanve2SJKEfc9hTN+sx11UiiIsmMD0oWiT09HExKMOj0CubtkOyefDa7PiMRlxGapwVZXjqijDXlWEp7QCJAmZRo0mIwVNZjoBgzNQpyUiU/TvOCBvjRX36qWUrz6MfmAM6Q/PIygzrtftMB8uoOCvy7CbXMx7OosRlyd326OrcPt4duYKDHFajHFa9l+WwtEF/S/R7kJAkiSMhVbydleSv7f2x1xiByAiPQhFZhrBwxIJGpZAQHyo2J4UCBrgsTioyS7CfLgQ2YlTlBw14nX7CAhWkTw2kuTxkaROiCJqQLD43ekiQqz2oFh96LV1XP/1vmbji9+5i+LEntlm9rk87LnhNXTTJhF6TftiOL7KwCtvfsLY03mkAXlACnAW2JuRwoP33UhJeGiP2NoakiThysnDuvsQjuyTeEoq6p+TaTXItdrazlAyGZLHg+Rw4rPaocFHVB6oQxUXgyoxFnVKPOrUJFQJMX7x1PYGks+HZfMuar5ehSRJJN8+g9iFI3s9q9vn8lDwvx8o+nwnSaMjuPwPY/3mDXjwmvXEnTLXPz4zJpy3353pl3MLuo+pxEbB3koK9ldRsL+KytM1AOjC1CRkheNMH0TQ0HgCB8Wi0PrBwy4QnANIkoSjyEBNdjE12UV4T5yh8kwNSKCP0JA0NpKk0RGkjIusFaedrYwiaJGOilWxR9dJ/nfXf0nPr240JgGXfXo/xvCe226u+uEknhoH+mnj2p0r8/mYe/AYm4YPJCu3kKe9Xv4EPA24FQo2DR/ExQeyeyUMoJFdMhmagaloBqYC4LPZcReV4amsxmuqwWdzILndtXOVSmQBGuR6LYrgIJThISgiw1EEnrtbl87TeVi++BLrqTKi5g0n5c6ZqMN6f7vIeraCkr99ReVpM7MeGsqk2wchV/jnwqutdjQSqgAf/W2iX84t8A8hcTpCfkzWAnCYXRQdqqbwQDVFh6op/Xwb+VYPMjlEZgQjS08hMDOWwMw4dKlRvVqZQiDoKdwmG5YTpVhOlKA+m0Px4Wrsptrvn8j0IBJHhTPptoEkjo4gLEkvPKd9jBCrnWD9gv8jwNd47FhqJHe99fMeX7ti7VGChiY06qbUGjqnm8e/XkOY1d7sObXXyxPL1mLQa/ly8theCQNoDblO20i8doW+6CjVWbymGtzfLaP8u8PoB0Qz/O83ETwsodftkHwSxV/tpvDdzYQl67njo1nEDA716xq/mv9do8d7L03AEda7MbiCzhEQrCZjWiwZ02o7zvm8EpVnaig+XE3xEQPFR/I5u+4IkldCoZITPSgYX2oK+gExBA6MqRWwosuWoB/jNtux5pRhOVWGriCH0qMGjEU2ALQhKuKGhzPuxgwSRoQTPyKMgGCxo9DfEFeYDqAz21h9zas09Se8cfs0/nejf+uBtoTLYMW4L5ewm67q0HyrVsOlzz3CVy++RpzRzJ+oDQP4E7UxqyWhwSz69QN9KlT9RW93lOoMkufHLP9v1iBTyEl/+GJiLun9LX8AR6mJyn99Sf7eSibcPIBZDw31e32/WW9ko3I1vptb9rsxfl1D0PPIFTKiBwYTPTCYUT9LBcDt8FJ2wkjJESOlxwyUHjvL2VUHkXwgU8iITAuClER06dHo06PRpUWiChPeKEHvIkkSzlIT1jMV2M6Uoy08Q9kJE6biWmGq1imJGRLCoNlxxA0PI25YmPCaniMIsdoBVi9uLlTv+csNHM3qePmo7lC15QQymQzduBEdPqY4IoxH776eD/7+Nk97fgoDcCoVPHL39b0er9pT9FZHqc5iP3ICy5KvsRcZiLl0JMm3T++TupeSJFH+3WEK3lyHNkTNTf+ZRsr49r3znUVf5eDi1080Gnv31Ul4NeIScz6gClCQODKCxJER9WNuh5fykybKjpsoO2Gk/GQJxT+cwO3wAqANUxM9IBhnfDK6lEh0qZFokyNE/VeBX3AbbdjyKrHlVmLLrUBVVED5KTMuqwcAbaiamMwQBl8cT+zgUGKGhBKREihiTc9RxDdJG+jMNlZe928UTVLQll88rNeEKtSK1ZDRKSgCOxff6FHI0Xi83EetR7V20Iu3n2fKd4be6CjVGdylFTiWL8Ww8zTBWUkMevYK9Bndr1faFVwGK6bXvuT0plKyrkjm4l9loQnsmXp/T17auKVqVbyWnOm9X91A0HuoAhT19V7rkHwShgIr5adMVOSYKT9lpubgScq+3Y/krb2Q6iM0RKQF4YxNRJsUjjax9kcTHSzaxwoaIXl9OCtqsBdUYS+oxl5Qhbq0kMozNdgNLgDkShkRaUGEDAxmwIxYogeFEDMohMDoAOExPY84L8VqXYEDr83ZrfO8e8ub2L0SDSM/b331FkoSwsHavXN3FE+NA/OhAsKuuxyf3dGpY6fuOYwZWJs1mL8sms8vv1rN3MMnmLrnELsSY3vG4AsY07J11Hy/FXV4IBm/vITwyQORyWR4eumz0hDzoQJy//YNMrmMK/80lgE/Ckenxd0j69kdXhp+Ov/06UVIPbSWoH+jj9CQFhFN2qSfbtI8Li+GfCuVZy1U59VQlWfBmn2a/O8O4nPXXq/lShkhiXrCEnVYwxMIzIwlYsqgvnoZgj7AuPcs5iNF6KsLMRRYMRZaf/p8qGSEJweiTQ1k1M9SiUgLIiI1kLBEPYoWuuLVeVgF/RuntfZ7or3CVOdl6arCwkKSknrP8ykQCAQCgUAg6BoFBQUkJrZej/u8FKs+n4/i4mKCgkQP3v6A2WwmKSmJgoKCNuuoCc5NxPt7fiPe3/Mb8f6e3/T391eSJGpqaoiPj0feRinN8zIMQC6Xt6nQBX1DcHBwv/xlEfgH8f6e34j39/xGvL/nN/35/Q0JCWl3johmFwgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFfQ4Go2G5557Do3m3G9CIGiOeH/Pb8T7e34j3t/zm/Pl/T0vE6wEAoFAIBAIBOcHwrMqEAgEAoFAIOi3CLEqEAgEAoFAIOi3CLEqEAgEAoFAIOi3CLEqEAgEAoFAIOi3CLEq6FVyc3O58847SUtLQ6vVkpGRwXPPPYfL5epr0wRd5N///jepqakEBAQwceJEdu3a1dcmCfzASy+9xPjx4wkKCiI6OpqrrrqKEydO9LVZgh7gT3/6EzKZjEcffbSvTRH4iaKiIm6++WYiIiLQarWMGDGCPXv29LVZXUaIVUGvcvz4cXw+H2+++SZHjx7l73//O2+88QbPPvtsX5sm6AKfffYZjz/+OM899xz79u1j5MiRzJ8/n/Ly8r42TdBNNm3axAMPPMCOHTtYu3YtbrebefPmYbVa+9o0gR/ZvXs3b775JllZWX1tisBPGAwGpk6dikqlYtWqVWRnZ/PXv/6VsLCwvjaty4jSVYI+5+WXX+b111/nzJkzfW2KoJNMnDiR8ePH8+qrrwLg8/lISkrioYce4umnn+5j6wT+pKKigujoaDZt2sSMGTP62hyBH7BYLIwZM4bXXnuNP/zhD4waNYp//OMffW2WoJs8/fTT/PDDD2zZsqWvTfEbwrMq6HNMJhPh4eF9bYagk7hcLvbu3cvcuXPrx+RyOXPnzmX79u19aJmgJzCZTADid/U84oEHHmDhwoWNfocF5z7Lly9n3LhxLF68mOjoaEaPHs1//vOfvjarWwixKuhTcnJyeOWVV7j33nv72hRBJ6msrMTr9RITE9NoPCYmhtLS0j6yStAT+Hw+Hn30UaZOncrw4cP72hyBH/j000/Zt28fL730Ul+bIvAzZ86c4fXXX2fgwIF899133H///Tz88MO8//77fW1alxFiVeAXnn76aWQyWZs/x48fb3RMUVERCxYsYPHixdx99919ZLlAIGiPBx54gCNHjvDpp5/2tSkCP1BQUMAjjzzCRx99REBAQF+bI/AzPp+PMWPG8OKLLzJ69Gjuuece7r77bt54442+Nq3LKPvaAMH5wRNPPMHtt9/e5pz09PT6fxcXFzN79mymTJnCW2+91cPWCXqCyMhIFAoFZWVljcbLysqIjY3tI6sE/ubBBx/k22+/ZfPmzSQmJva1OQI/sHfvXsrLyxkzZkz9mNfrZfPmzbz66qs4nU4UCkUfWijoDnFxcQwdOrTR2JAhQ/jyyy/7yKLuI8SqwC9ERUURFRXVoblFRUXMnj2bsWPH8u677yKXCwf/uYharWbs2LGsX7+eq666Cqi9o1+/fj0PPvhg3xon6DaSJPHQQw+xdOlSNm7cSFpaWl+bJPATc+bM4fDhw43G7rjjDgYPHsyvfvUrIVTPcaZOndqszNzJkydJSUnpI4u6jxCrgl6lqKiIWbNmkZKSwl/+8hcqKirqnxPeuHOPxx9/nNtuu41x48YxYcIE/vGPf2C1Wrnjjjv62jRBN3nggQf4+OOPWbZsGUFBQfVxyCEhIWi12j62TtAdgoKCmsUe6/V6IiIiREzyecBjjz3GlClTePHFF7n22mvZtWsXb7311jm9iynEqqBXWbt2LTk5OeTk5DTbUhRV1M49rrvuOioqKvjtb39LaWkpo0aNYvXq1c2SrgTnHq+//joAs2bNajT+7rvvthvyIxAI+o7x48ezdOlSnnnmGX7/+9+TlpbGP/7xD2666aa+Nq3LiDqrAoFAIBAIBIJ+iwgWFAgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEAoFAIBD0W4RYFQgEgn7GJ598glarpaSkpH7sjjvuICsrC5PJ1IeWCQQCQe8j2q0KBAJBP0OSJEaNGsWMGTN45ZVXeO6553jnnXfYsWMHCQkJfW2eQCAQ9CrKvjZAIBAIBI2RyWT88Y9/5JprriE2NpZXXnmFLVu21AvVRYsWsXHjRubMmcOSJUv62FqBQCDoWYRnVSAQCPopY8aM4ejRo6xZs4aZM2fWj2/cuJGamhref/99IVYFAsF5j4hZFQgEgn7I6tWrOX78OF6vl5iYmEbPzZo1i6CgoD6yTCAQCHoXIVYFAoGgn7Fv3z6uvfZa3n77bebMmcNvfvObvjZJIBAI+gwRsyoQCAT9iNzcXBYuXMizzz7LDTfcQHp6OpMnT2bfvn2MGTOmr80TCASCXkd4VgUCgaCfUF1dzYIFC7jyyit5+umnAZg4cSKXXHIJzz77bB9bJxAIBH2D8KwKBAJBPyE8PJzjx483G1+xYkUfWCMQCAT9A1ENQCAQCM4x5s6dy8GDB7FarYSHh/PFF18wefLkvjZLIBAIegQhVgUCgUAgEAgE/RYRsyoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6LcIsSoQCAQCgUAg6Lf8f2aJpnupv2IZAAAAAElFTkSuQmCC",
|
|
"text/plain": [
|
|
"<Figure size 800x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.figure(figsize=(8, 4))\n",
|
|
"\n",
|
|
"plot_gaussian_mixture(gm, X)\n",
|
|
"plt.scatter(anomalies[:, 0], anomalies[:, 1], color='r', marker='*')\n",
|
|
"plt.ylim(top=5.1);"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"celltoolbar": "Slideshow",
|
|
"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": "3.11.11"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|