{
"cells": [
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"#hide\n",
"%load_ext autoreload\n",
"%autoreload 2\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"# How to normalize spectrograms\n",
"> Scaling spectrograms for neural networks. \n",
"\n",
"- toc: true \n",
"- badges: true\n",
"- comments: true\n",
"- categories: [spectrogram_normalizations]\n",
"- image: images/violin_spec.png"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"# Introduction \n",
"\n",
"Spectrograms are often used as images to train deep neural networks for audio tasks. By treating spectrograms as images, we can borrow from the many powerful ideas in image recognition with deep learning. A spectrogram, however, is fundamentally different than natural images as we will see below. That brings up the central question of this post: how should spectrograms be normalized during training? \n",
"\n",
"This post assumes some familiarity with deep learning and signal processing concepts like the FFT. It is also a light introduction to the [fastaudio](https://github.com/fastaudio/fastaudio) library."
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"# Transforming audio into two dimensions"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"Image classification is a challenging task that was previously done with expert, handcrafted features. Now, features are automatically learned from labeled data instead. The success of these learned features has completely shifted the paradigm of Computer Vision. We would ideally like to apply these same, proven techniques on audio tasks. \n",
"\n",
"However, audio is treated like a one dimensional signal in most Machine Learning applications. That means raw audio is unusable with 2-D Convolutional Neural Networks (CNNs), which are the workhorses of modern image recognition. If we could somehow represent audio in two dimensions, like an image, then we could leverage the successful approaches in image classification. \n",
"\n",
"Thankfully there are many ways of transforming audio into two dimensions. The most popular one is turning audio into a [spectrogram](https://ccrma.stanford.edu/~jos/mdft/Spectrograms.html). As an example, the image below shows the spectrogram of this [violin recording](https://upload.wikimedia.org/wikipedia/commons/d/d1/Violin_for_spectrogram.ogg) taken from Wikipedia.\n",
"![The spectrogram of a violin recording](violin_spec.png \"Spectrogram of a violing recording.\") \n",
"\n",
"The spectrogram is a 2-D signal representation in time and frequency, so we can use it with 2-D CNNs! But first it is crucial to preprocess and normalize the spectrograms. Neural networks have a much easier time learning when their inputs are normalized. \n",
"\n",
"For natural images, normalization uses an estimated mean ($\\mu$) and standard deviation ($\\sigma$) as follows: \n",
"- Subtract $\\mu$ from the image values to give them a mean of $0$. \n",
"- Divide the image values by $\\sigma$ to give them a variance of $1$. \n",
"\n",
"In math terms, if $x$ is our image then $x_{\\text{norm}}$ is: $$x_{\\text{norm}} = \\frac{(x - \\mu)}{\\sigma}$$ \n",
"\n",
"Since spectrograms are fundamentally different than natural images, we should reevaluate if this same normalization makes sense."
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"# Why spectrograms are not images and how to normalize them"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"Now we can describe what makes spectrograms different from natural images. We start with a high-level overview of images and their normalization, then do the same for spectrograms. A quick recap of how spectrograms are computed will further show how different they are from images. This recap naturally leads to a specific normalization for spectrogram features. Finally, we talk about Transfer Learning and why we avoid it in this post.\n",
"\n",
" \n",
"In an image, both axes (height and width) are in the spatial domain and at the same scale. Images are stored as integers in the range of `[0, 255]`. To normalize them we first divide all pixels by 255, the max possible value, to map them into the range `[0, 1]`. Then, we find the statistics that approximately center the data with a mean of $0$ and a variance of $1$. The three RGB channels in a color image are normalized separately. If an image is greyscale then we normalize its single channel instead.\n",
"\n",
"The axes in a spectrogram are from different domains than the axes in an image. In a spectrogram, the horizontal axis represents time and the vertical axis represents frequency. Each of these quantities has its own scale. The frequency dimension is determined by the size of the FFT window. The time dimension is set by the total length of the signal, the size of the FFT window, and the hop size of the window. You can check the documentation of the [torch.stft](https://pytorch.org/docs/stable/generated/torch.stft.html) function for a breakdown of how each axis is determined.\n",
"\n",
"To be more specific, a spectrogram is actually the log of the power spectrum. Below we give a quick recap of how the spectrogram is computed to show how much it differs from images.\n",
"\n",
"If $\\text{x}$ is our input audio then the STFT returns the spectrum:\n",
"$$\\text{spectrum} = \\text{STFT(x)}$$\n",
"We are more interested in the energy or power of the signal, so we take the absolute value of the STFT and square it: \n",
"$$\\text{power_spectrum} = |\\text{STFT(x)}|^2$$ \n",
"We cannot use the power spectrum as a feature because it has a few strong peaks and many small values. You can check this other [fantastic post](https://danielsdiscoveries.wordpress.com/2017/09/29/spectrogram-input-normalisation-for-neural-networks/) on spectrogram normalization to learn why this is a problem. \n",
"Taking the log of the power spectrum spreads out the values and makes them better features. This becomes the spectrogram:\n",
"$$\\text{spectrogram} = log(|\\text{STFT(x)}|^2)$$\n",
"The range of the log function is $-\\infty$ to $+\\infty$ which is clearly different than the integers from 0 to 255 in an image. \n",
"\n",
"A spectrogram transformation can also be thought of as a very simple [\"channelizer\"](https://en.wikipedia.org/wiki/Channelizer) in Digital Signal Processing (DSP) terms. That is a fancy way of saying that it splits the continuous frequency spectrum of a signal into discrete bins, or channels. For example, consider taking a spectrogram with 512 bins from a signal sampled at 16 kHz. This spectrogram will have 512 channels where each channel has a \"bandwidth\" of $$16 \\ \\text{kHz} \\ \\ / \\ \\ 512 \\ \\text{bins} = 31.25 \\ \\text{Hz per bin}$$ \n",
"\n",
"[Spectrogram channels](https://en.wikipedia.org/wiki/Communication_channel) are very different from the image channels we are used to. So it raises the question: should we normalize the entire spectrogram \"image\" with a single, global value? Or should we normalize each spectrogram channel just like the channels in an image? In the rest of this post, we compare global and channel-based spectrogram normalizations on a real-world dataset to find which is better. "
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true,
"hidden": true
},
"source": [
"## A quick note on Transfer Learning"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"We also have to talk about Transfer Learning in the context of normalization. In Transfer Learning, it is best-practice to normalize the new dataset with the statistics from the old dataset. This makes sure that the new network inputs are at the same scale as the original inputs. Since most pretrained vision models were trained on ImageNet, we normalize any new inputs with ImageNet statistics. \n",
"However, we avoid Transfer Learning in this post and instead train an 18-layer xResNet from scratch. The reason is that pretrained image models operate at a completely different scale than spectrograms. And the main goal here is to learn our own scalings instead!"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"# Downloading a sample dataset\n",
"\n",
"\n",
"To keep things practical, we will apply these spectrogram normalization techniques to a [sound classification challenge](https://github.com/fastaudio/Audio-Competition) hosted by fastaudio. [fastaudio](https://github.com/fastaudio/fastaudio) is a community extension of the [fastai](https://github.com/fastai/fastai/tree/master/fastai) library to make audio tasks with neural networks more accessible. \n",
"The challenge here is to classify sounds in the [ESC-50 dataset](https://github.com/karolpiczak/ESC-50), where\n",
"ESC-50 stands for \"Environment Sound Classification with 50 classes\". This dataset has many different types of sounds which show how varied audio spectrograms can be.\n",
"\n",
"Many of the lines below are based on the fastaudio [baseline results notebook](https://github.com/fastaudio/Audio-Competition/blob/master/ESC-50-baseline-1Fold.ipynb)."
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true,
"hidden": true
},
"source": [
"## The ESC-50 dataset"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The first step is to download the data. ESC-50 is already included in fastaudio so we can grab it with `untar_data`."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"from fastai.vision.all import *\n",
"from fastaudio.core.all import *\n",
"from fastaudio.augment.all import *\n",
"\n",
"# already in fastaudio, can download with fastai's `untar_data`\n",
"path = untar_data(URLs.ESC50)"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The downloaded audio files are inside the aptly named `audio` folder. Below we use the `ls` method, a fastai addition to python's `pathlib.Path`, to check the contents of this folder."
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
"text/plain": [
"(#2000) [Path('/home/titan2/2A/cck/fastai/data/master/audio/3-68630-A-40.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/5-260433-A-39.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/5-188796-A-45.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/1-57318-A-13.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/4-141365-A-18.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/1-9886-A-49.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/3-71964-C-4.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/5-201172-A-46.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/3-253084-E-2.wav'),Path('/home/titan2/2A/cck/fastai/data/master/audio/1-91359-A-11.wav')...]"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wavs = (path/\"audio\").ls()\n",
"wavs"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The output of `ls` shows 2,000 audio files. But the filenames are not very descriptive, so how do we know what is actually in each one? \n",
"Thankfully, as with many datasets, the download includes a table with more information about the data (aka metadata)."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"hidden": true
},
"outputs": [
{
"data": {
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" filename fold target category esc10 src_file take\n",
"0 1-100032-A-0.wav 1 0 dog True 100032 A\n",
"1 1-100038-A-14.wav 1 14 chirping_birds False 100038 A\n",
"2 1-100210-A-36.wav 1 36 vacuum_cleaner False 100210 A\n",
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},
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],
"source": [
"# read the audio metadata and show the first few rows\n",
"df = pd.read_csv(path/\"meta\"/\"esc50.csv\")\n",
"df.head()"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The key info from this table are in the `filename` and `category` columns. \n",
"`filename` gives the name of a file inside of the `audio` folder. \n",
"`category` tells us which class a file belongs to."
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The last file in the data directory will be our working example for normalization. We can index into the metadata table above using this file's `name` to learn more about it."
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"hidden": true
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"source": [
"# pick the row where \"filename\" matches the file's \"name\".\n",
"df.loc[df.filename == wavs[-1].name]"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"This is a recording of crickets! \n",
"We can load this file with the `AudioTensor` class in fastaudio. Its `create` function reads the audio samples straight into a `torch.Tensor`."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"# create an AudioTensor from a file path\n",
"sample = AudioTensor.create(wavs[-1])"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"An `AudioTensor` can plot and even play the audio with its `show` method."
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"hidden": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Audio shape [channels, samples]: torch.Size([1, 220500])\n"
]
},
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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"print(f'Audio shape [channels, samples]: {sample.shape}')\n",
"sample.show();"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"Each \"burst\" in the plot above is a cricket chirp. There are three full chirps and the early starts of a fourth chirp."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Normalizing an audio waveform\n",
"\n",
"The first step is normalizing the audio waveform itself. We give it a mean of zero and unit variance in the usual way: "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$$\\text{norm_audio} = \\frac{\\text{audio} - mean(\\text{audio})}{std(\\text{audio})} $$"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"# normalize the waveform\n",
"norm_sample = (sample - sample.mean()) / sample.std()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's check if the mean is roughly $0$ and the variance is roughly $1$:"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Original audio mean: -1.781299215508625e-05\n",
"Normalized audio mean: 2.876160698495056e-10\n"
]
}
],
"source": [
"# checking the mean\n",
"print(f'Original audio mean: {sample.mean()}')\n",
"print(f'Normalized audio mean: {norm_sample.mean()}')"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Original audio standard dev: 0.008586421608924866\n",
"Normalized audio standard dev: 1.0\n"
]
}
],
"source": [
"# checking the standard deviation\n",
"print(f'Original audio standard dev: {sample.var()}')\n",
"print(f'Normalized audio standard dev: {norm_sample.var()}')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Success! The waveform is normalized."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For convenience later on, we define the `AudioNormalize` transform to normalize waveforms in a fastai training loop."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"class AudioNormalize(Transform):\n",
" \"Normalizes a single `AudioTensor`.\"\n",
" def encodes(self, x:AudioTensor): return (x-x.mean()) / x.std()"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Audio mean after transform: 2.876160698495056e-10\n",
"Audio standard dev after transform: 1.0\n"
]
}
],
"source": [
"# checking if the Transform normalized the waveform\n",
"wav_norm = AudioNormalize()\n",
"norm_sample = wav_norm(sample)\n",
"print(f'Audio mean after transform: {norm_sample.mean()}')\n",
"print(f'Audio standard dev after transform: {norm_sample.var()}')"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"# Extracting spectrograms from audio"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The next step is to extract a spectrogram from the normalized audio. We can do this with the `AudioToSpec` class in fastaudio. This class takes an `AudioTensor` as input and, as we might expect, returns an `AudioSpectrogram`."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"# create a fastaudio Transform to convert audio into spectrograms\n",
"cfg = AudioConfig.BasicSpectrogram() # with default torchaudio parameters\n",
"audio2spec = AudioToSpec.from_cfg(cfg)\n",
"\n",
"# extract the spectrogram\n",
"spec = audio2spec(norm_sample)"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The `show` method of the `AudioSpectrogram` is a great, quick way to plot the spectrogram."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"hidden": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Spectrogram shape [channels, bins, time_steps]: torch.Size([1, 201, 1103])\n"
]
},
{
"data": {
"image/png": 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OSA+MH/Xox47GYh3pqCwTiJ7XI5YO3dQhFIJ+5IbFT1iG1zxf0YBABNlWUayYeflOh+vgemD8uEf1pGEWFRWjJz2/K+c1a/YyhJLZUxh5QAj9uI6Oqx/TQY1OeH1jDhTLgGwTkW8UnWVeKRPMlwH1YYbyUtEsPHzD7MMFYHQS0S0KhJIOodnLsLlZoLzomXXlhIXUApZ+xCXmeiBbB0JYJecIM2fFwd84RvSMvLNNGObl6EmPbkqDHr2gPOtRfPkB6sMMy5fH2B56dCMGDNVZh6yOBiMB2VbhW1DJtxDen1XA9s4UvlOUF3RioeQ6WN+p0I+dBTAZfMdjl8BAIGZC5y28P9Ggr+osYHPksffFJWLpMP/iJbJasbmeobjosfrwApsbBaZv1ehHDvMvraA5g4h82SPbRs65qcPs9S3qowyuYwYUCkE3EWyv0cEXlwHSA6GywESBwjLVmHEuqgDnH58gZlzL20OPdsGMJxZ0vqHiPSpWzGD7EVGEkAukV7QzOrHnNVjkz57p8X4bHzgHI0HhW6bmxJppfPuRQDMMaXe2DuimHvlaMf7KKYpVhG+VEWhl+HVUxJzf201ZY/GtYnuUwQXF+GED9cD5J2fI6gRNMbLOakVx0aE5quDbCN/svr/e8yiWESEnTBQKpu6+08HZNUcV2hkjx5gTAhg9aYk1GwSRIr3RacTszWaor4wfduhLOkjfMgMon9RwHT9DI2w4fu7QHpYIpQNE4IKi3eO5unZXp0gZiChQnrYDZOd6Gs7Z6zW6CSG7fBUsWzDs24HHcNJQNSzqEIVLVHRTz9oYgH6coT7IrC6lqB7XkIghYo1+932NGRYVXsNu4gYYZ/Sohu8iylNCPDw3zonttQy+URSXPUIOqwdF9CWhGNfGXV3FjKMK0I0E5XFj88ENtbtQ8T628wwxZ00tlAZJjRyWnzhAeRGxuZlhfStHzATTN7doZ3Ru1Vng7yw86k/dfcoR0xFBWFdJMBfhK6A6pSPm3AW21zhZo9XUJNV9gtK5bSPyLTMqQoY0xvmKGUA3z1Asg8G2OmRJrlecvTpD9bjG9oUp2plDdRaYdXf8vuVLIzrlg5L3Vblmopchg9vcLDF+2DK7f1zD9YDvbB51vFZZw3UhQx1FUR/QQdT7HpM3N4BaNu85/1zLNd3OLHN8BwQZM8LTovyN8aPu+ajX2WAJyj3T4/023n9n9C4jZoSAqrMwRG8AF1v0gsUXqKTeTVlEzVcB5z98De2MBqq46CFROQkNVgolDVe2jegmNM6hcGgOCjqADITKDHqKnpHj5mYB1+xw93rfW0EWmL5VA2AtaPr6CjFPRX46mtHXzuF6OjtYVNYuMkbgW0W2JQySrwmxdXNGgekaqLO6khfCXLOCmPRlDwn8XfWCbN2jmTu0M0G2iSjPuiG6C5VjbeRBC98q8mWP8rRDfVQMxqsfCeAFl69U6C0rafdoOINF+xJp0CBCR2yFbXVWmPVAs8gIIy1ISCiPG0AEzX5JskOvLCx7ga8V9SHhuGwT0I/EHAPrHL5VbG6NsLpTDDBU+WSD8iIMzibVnyRlAFaPiZmg3cssQ+D8kKAIlUN5EbG+OxqyNDFDBwUm91tmGfa52d98G8VlpGM96+DruIvKL3tsbo+GrE8CC/+pRpbuX7aJFiQp1ncr5Js41Iz6SgBHAkQ7Y12mG/E8EnGkOm4gkfMpGXvpGWRsjzK43jLNdcDsa2u4XlGctQA477N1QLPHmlVWK5qDcghM0jF2Y5qYdJ/beUYYNxdk24gwcvCdkVpyQbvIWePZdAgF52i+4f2FBQqiPH7XA/UhJ7Xr6PSXH54g36T6UOQasUyMx8bjSEFiyqDUcd6EUhBLx+v3HEdQeabH+2184ByMCqzwHoaCfl/t6jHHn95DdcbojYVyRuvSMyJc3yamXR9mKM8Js5TnHcrzwNS6VszeaIZIKV9HTO4zDKuOW0IzdSo8ClxHg5cKne3UYfywx/p2BRe4kM8/MWMtYauY3mvQVw7NnTmyLfF938GMEG+nBAwYdl86FsMnDvmKi217fWc81KCZdsGsa3stR77l8blOcfFKicUvLuEbFpU3NwtIVFTHBLCr84CYO0zu1ehmGS5fYYSaott8RQearxX7v7hBfZgZrOHgAhd0P3JoFxma/RzlSYt63w/3I5SsS4WSNaXpW8xYYumHGlC2oWPfXOe9yVe8LwAAx0XrW0a0MWPdQxQoljviw/kn5zTids+6qR+ID+r4nYuv1ci2ZvBLQXEZLAuE1bWUDLKY6mEYDGM/9ujHZKBBFevvuw31rLM0+zmKixbVacD4UY/l3WLIdPrKwdecI66jgXYd64TdxCGro2XVLJaz5uYwf71GO3MoLloUy0jnuuI16UcO9WHGOotYBj9mdjp9c41QCiYPW8v2FfVBhvULE97P4zVCIRg9aqC5w+RBi27EIKBd+MERhmpHPCkvAtlmNa8PsMsK2xnnTralsyxPmAFevMr7kWCsbuKGDDwUhkTY+i2WhFlTAJB+N7Ho8nXE7M0a/UiGon8oBfufv0R13GLvS1vWhAoSMOp9v6s7Pg+bY538z/J4v4333xm92zDmVjclXJGwcigXU1bTyE/ebkixzUmBjDlTbNdhSJ9D5dDse9T7OdqZHyZ2u8iQbxTNwqG86FEfEZroR56RYsbfVc+sI8EgxWW0Ar8zlhcdQlqU1eMa3YSZSLNHqGj2i2cI5gw1w8CkaWcyQDgAnY5v40Atnd5vkTWK+Ws1mj3PxdfRqJUXAdXjLSZ/8y34Drj4+IxGcuoRcmaA49fOMHrSsUZR99heL40txmg0Wwe43uisGZ16u8fMppsSqshXAZMHnf12RPWkYS2g5P+TwY9+BwWt71QW6WZW/yGrKKuB0THhN82N4up37KHyPGDxC+dWiN/V3AB+PtWRAFgBnoGHCwBE0M4zrO6WQ21CPYkBidiRDJw3gwYYA04V0u8osd3EIea7WhfnhWD10ogMsMqxUH3aw3fMEtZ3ChJMHtZop4J8HQb6bzujg9z70pb3ObL2tL5dQgKwenFE+NBo65M3N3S+yuwLIgPU6bcR21tj5OuIzY2CTmATrPDPTO3iU4eozgMuXxkhW/VAJBMz1Xmqkx6+JYNw/rUNWX1zPwQLzcKyqTEL96OTgPy8xvjtjWX11UCxzxodCvWp3tNO3Q6KPdvtSxfsnlenvTldzp9swwwlFqyPhoIoQFYr6htjrO+UpHx3EbPXNshXHaqT/uuIGs9jRHXP9Hi/jfffGb3LSEa3m7CmIIZFF6uIfBPha0JK/SynIYAxpzoYnBKMqcX6wORBO9Rh9n9hafCXI1SWCfqROR4hjdc3jKDUM4JWL4he0E2dRV9cqC5YgbkjZTbmgm6Wo9n3KM8C1KjVy08coDIowHU7w+56i/49MHuzGeAvOlTSpruRQ7vHg/ctMPvSOUaPGpTHDZqDCpc/+uLQT5Go1b5V9GPB5kP7dKoCdIuCdNugAySXXzbwTYK9dMhqsm3E6LgdYImU9UkEtjfpPHynQwZSLFkvCzmvixgzrFl49pNkguIioFgGNIsM7cyjr5wZUd6XkAs21zOsPrLA+FHLTMJhqGmJORHfKMbHzDD7UoYsqjztWecwdltxGRA97LiZWfpGUSx7tFPCK+owZB8AoJmgPGmsD4rZhwTS2bMtz5eOpbXMUpBf9ggjN7D22n1jD86z4T6KAo3VxOZfWg0UdYmM8tUBo8ftwDbcvDCGryOqU1KlE7znO/7rLAhxrWL6Zg3XBRTLiHbh0eyR9t1O6SCb/RztIkN1HlCeG50/JyOy2cvQLgpUD1aslymGQMnXJFek+7p+eYbmsEJ5GQZCQbZVkkUyGcgQzdyhOg+YvdUglILttRyuAyZvbaFGex7dWyK/7NHO/bB225lDqDxEmcWV54Fz5qKjcyyZ4XfzgsHEwtP5PqehwFUG80Ea89dqlKc9s4WSTKS+cgiFgzrB5EFnUEocjAdgxcCMTmbx1S360mFzo4Bv6TBi4ZnxlMT1R8e76G3ydk3nMeKjuOTi6SsWgQFgcm9rTC72L7heUT7aDjjz6m6O8jxge43NoO2chiwUhJAkKjY3MoQCmFhdRHoagupJg/qwQGrILM47FkEbwmwxA86+bx+rFyqcvjohcycXFOc0MKnfpa+ELLwJnV8yGoDRvZW1n8uPTA0nV6PuKspzZjztnP1FMU+FdUU3dWjmDuVpPzTqFcvIPqFNtKIsI/x+RAPUWdG8nXtIp+imvA6uYw1h+lbNhr0I7H/uAu3UYXutMKozmXyAFbmXrMltjgiNQYDqNMB1vKbMCt1QbJ+/2Q6MNzK1gPogR3ERBtIBVNEuMoSKDbiXHx4PzgMgGy9f8xoysyVk1o/Z63P5SmnNlLAGTAYh0epGfcWsM98oLj48ImGkjuhHxiCsHIpVRPHW6S4bzATtnrcs0g3XKxEqsm1ANxZUZx3Wtytsr5eEjk579kcJBobfQI6xYCHbKla3c2YenaLZz3Dx6gJ9xddcB0zf7ngdAWbpCoMJUxMsHQXrSA7d2GH8qCfsuCUBZntUIOTWk6TA2atjtBOHfBVQ357BtWGo4WVrwtPSRfgGQFBsr2XI1j1OPznG5I01NBfM3qjRzj1Wd0vs/aWvDPfoeQyFoFP/TI/32/jAORhRsHPdOrSjZxSVFmA/FuSX3VC3kKiDwaEjIVMolB5Zw/Q7X/aMeic58pUxzUYO/dgNxcjmoADA/hlYVFUsA3zLOks3Eiw/NCY84IH17YL9GAVhOdKTxSiXjJ5dtyueSuCCHZ0y8qr3Gd3FHMwW/M6YtDMSEHojBpCJxkgxseUA/kaoGEHHwiFfB2uY7BALGfpTUuFXgqKde+QrZoLpwQ5wYHtUDNcm+l2ndjv3A5ssX/cGR2ZQv8sUUwScben0Y0FK9vReQ3p35Qa1hX7Ez2xvsN9mcr+FVmQ0JQpyMkBPs4XKszAU5atTg48M3gqlDIXtbBOxulOgG5PWmm8jqpMek7e2CNYPI8p71o9YPO4nzPZ8qwOlvDhnnSPkAl+ngjRhyG7M3673PcqzHtHmZ1azVyMZad/GoY9IM9azimUcshcVoLu9NzgX16nVUGpAaLShCYYUdNMM4+OAzfWcAVZD59NPPPyWGenkQc8+MJt72TrYNefxNXNmRBIMgt7oQFK5fKkwggLrMglaGz9oBwYgHTkbIvuRtRNYPWtyv8Xir90bSDUkWZgaQMU53u4VKM97rumMkGN9yBpjLHgN1nfovLd3xsg2hPwAYPyww/n/5CNEOJ7TUAWCumd6vN/Ge3ZGIvKCiPw3IvIF28P5f2vPH4jIXxSRL9u/+0995hvuGS0iPywiP2+v/Tu2HwFMGfRP2vN/VUReftcDC7seln7syF7JuFi6sTWn3aqQbeOQufiGi9K3EVkdUV+v0C4y9KWD9Czgju+t4WsaAham+XPt1AxkrygveogSRso3av0n/UAvlqiozo3VYjWH7Y3S4BZGgdITi+4r2RVP22i9CTJQVQn/wLImBzhCO24HWw9Nk8UyDNTO1OXtzDiEapcl+Tpi8naDZsEsqbyMaKcO9bUSmu2M8PSNNTONiWfXtcdAEQ4lcXoInW1qfIy5oLwgnBS9DA2QNJ5WozmLqI7bQcojSaX0Fdl9+TqSCWQd9wkWqo9ybG/SgKT6jzoGDMUFM6m+ZOF7+uZ2UC1IRpOU3NRbEgmdKqmuzX7GJsvc0cBX/E32+fTWsEpVhaGf6c/9NWPTEfIaus0nDrFwgwwL6xmK9e18gPuS4YyZkQwmbAQeHfPvZuEH+DfbRIzub7G9UfHaClAfMOiJuTfiSEQsZEdvzwW+JoMwdcBHC6yDza36MBtgzZgJ8vMt1DGrSU2q2apHec56jG9JMkj3c/wkoLq/Hs6T9UMZ+nCSCkFnAVq78HA9sD30aPYznP3YC/x9BbJNIptENjAHQl6+DhBVNiU3hHnZH0TmHh21wjUR3TQDhDWdzc18YNk9v/FsTZZXjZbf2ugB/O9V9ZMAfhTAP2P7Qv9uAH9JVT8K4C/Z/99tz+h/D8BPghLTH7XXAeB3AjhT1Y+A24T+6+92UC5QhylFd6mbe/yoR75RzF9vSGG0FNx1itGjBtV5wPq6OZWYekUAzYDxgy1WL02wMcc0e6NGZ5FXvmEkF0YO3cRjdBKtIMwJnF806Ece5XlEcR7YV2BNna7b1WuauRskRfJlGCAeSmyQ/TJ92LO7GcD20A3Ni0mqJjnJ8pxNdvkqRboyKBgkeCKaU3AtI+zoBfVRjm6Rw3eKYqlfR911HRljWR1x8bEpAH6epADLji4CihWbOxP1l7AjBiezvV6iWEU2qz5qMH4Shvf2FXslfMcaCUSwvltRvmbmMXrC7GfykM5m/qVL+IYGJRWLfafY+9J2cIbJeKUsNRXb631rShUyCPMNo9/6sGD0ncQNhLpZoWDkDGF20Fdkh/mW1+rgLz9AN/Wo9z36/+mnmRE3kWoBMdX3Iuo9h6xRHP78ijUPAfKVYvpWPWRfoXLY+9IazT5rMcVpg+K8RXEZMDrujTTBe7n88GRounW9YmQ1pnaRIRaCZo9svNT/VB23aPbygTrej+n4+xEVC8qLgL60/qZL3s/65mTQ1Vv8lTfJ/Bp5UsWbiFAwmy8uI6rTiG7qcPnJOXyn2P/rj5FvDNJ8fYvJww7FZRhYfyk77ytTPfA7duLkjRU2N0uDeAlXtlOHYPNk/CQMSgnZhkX/7bV8aBeYvb5BLB3qPTpR1waUlyz2jx4336q9+yWH4iqDee5DVR+o6t+0v5cAvgBu0fmbAPwRe9sfAfCb7e/fhG+wZ7SI3AIwV9W/opR+/qPv+Ez6rj8N4Nen7OaXPC7vTCrCLITVJLopC3v9eEeRhTKVbw4LTkCjnDZzj/GjdpA26ebUMVIPlGcdli9WyDeMrqdvbtndLTAevwxCe7OvrhFGORd5p8g27Nxm1zOdXDLyKdNgZKmDPEyKNPOLFt2IToh9AxhgEUhq8Nz14/Rj2dGjhf0KVCLAAF1lNbOH8qKn4sEmIr/orNEt9anQQSS6cTM32RDLriDMdBZf2Q6wVnFJerQzqikLrTL0ABVLdudvbpfYHvG+ZLWazhg76J0JLjKDS82ohLU0ExSXPS4/Pkez8OacWMtxbcTqhWro06GcjkFXqwjpaVidiYo2e5wrEujcuzFrG4nuTvFKGrGUPa5eGtGBbCMJGQ5Yft8Nyut07NeJnkKjR3/5MRlTNbNBiQwm1ndGrHnY/V6+VKFdeOuoV4QqG2SONHeWDUVkm0B5lVzQ7Hur2WDoA0qwUr4OgOpQJ8sM/trcKIf+r2af/T6i1AnbHhXw5lwTdEUKMenR1XGH5mO3ED0G+ZhoDExf60BLVseApS8FaFtbl4Ltzcp6ynaZLTM7rhnfWmZ3zv6b9YtTrrmLHtVJS6FZ4W8lNQW/DQavMnsJOZUaqtMOqxfGdjxkkjaHBdbXGdNub1Tfirl713FV5H8Ph0FXPwjgrwK4oaoPADohANftbb/UntF37O93Pv91n1HVHsAFgMNv8Ps/mfa4bvu14dmU63AdKcJJ7yuaBlQoxfo03NA4Vp2z6JyvI7uyzWD2Y1MzDsD6FmGP6pwTe313xO5ni8CTcmwohN34CzbzNQuP5pA03vXdykQ4d0q6vsNAg20OcogCe79wMTiudr9Avg4YP+xRnjTINjRi1XFrhngnurjL3NwAzaWIvB85Kh2r4fuBdQGJAIKivlayn+eyH6RcyjNmDMWKrCbfAZtr3npFohXxWcSNhaA6bhgxG7XUdRHlRWDPwiqiuOgGeAsG4yVjldV0gJO3aZhGjxpTRwZWd0tAWQgGkrYZBiOnTljvEcquZHUc+nV4nnRy+SqQxWSsu5iLGWXWp1I2kArN6TOhEgSjtXdjQX3IOTJ5a8t6njIbWt9kPW59u8Lye46Ge1yd9mYIGan3FSEj37HeJkaI0Iz6Wd3IIMDrFbPOzGF7vUA/EkzuN5i+WTMQMUcfStKt/bZHO/MD2yxfhoHt5nrTKauj1b/wdUKq2+s5pm9TCaKde3QTYQ9NRygyrZehLlnRmfhOAdP8I5mA1377iZtDA7F6GRQaUpNmVlNeKaFH0QOrWxmyTTQY1ZCGOqC4aOEN5p28zUbcFAwkrTHfKpp9FvNz6yMrlqbsbcFmP83fxaJ9a0PxbJuNfbsbjn03jvfcwYjIFMB/DOB/p6qX3+yt3+A5/SbPf7PPfP0Tqn9QVT+tqp8uZYTF5y/IxU/MHTPA3hSHgV1U3M0yo2XK0Kg1vr8ZcPbxMbn5SWImmJhfYj9N39wMtM5E1Z2+1ZKWey0byAah4GeTQkB1QgNeXAbEgnh7Xwr8lsagPO+wemVmmYKanDyhonavwOhxg2IZqL+UehUsywCoIptZ93h9lGP8iAZ7/KgbMq7tgWevztwj28ahUN3u5WjnZLZ1Y8HmRo5mQQgl0XCLJZ1sO2ffR3PAiHt8v0F9VA5yMSo7QcXOBCy310uUl2FQYd5eyzF6bKytmlnG8qUCrlN085xd4UaFDgVrF+vbJdWyrQk1ZoSusm1EKBhMpB6SYNLwqfF0fYsK0O0iQ5FEFC3DAEyWpmMxujphdpeo3CyKU7V5dNxjdH+L+no5UJpT3UsdUJ2QrSi9YnvoUVx06EY8lnRc1Tn1yfqxmNMnbbqdC6YPCSMWFx1Wd/JBSXn0uId6wfLl0dAXM3+jNUFSQTfNh/pjKAXbG/lQX0GCkyqSUMZvb1GetCgtUGhnDttrOeZvtph/dQMAGD3uMX7cDdldKBy21/Nd57xaJh0V07dbUvkrh/IyYnOd88J1MHqzRyi4nqhMwKbe6pR1x2IVMXlI3bjyLFigRAry5vZoqM0tX6wIrRpTLqkAJKXpRHWv9x00Y+AzflAjX5EhGYpvYqm+xaEAOs2e6fF+G++pgxGRHHQuf0JV/xN7+pHBXrB/H9vzv9Se0ffs73c+/3WfEZEMwALA6Tc7ppg5bF6e2b4XjHyTijFFEgGoKdzmGHpcsk2w5jfALRv4hgq97dQNzXWp8NgcZKSHXvRYvTAGhMyx+WtbzH/xgrWMpIPk2ZyYYI1uwmwoMauCFcLzZaAI54QU03aewfU6SOOHikXm8rxnxrDI2Y1euUEJePjXms16ew2qaBYZ+hIonmwMRpPBfSeKcsyB0eOGwpkzN9Qmsq1i/KjH5nqO2Rs1jQmpM8g2uwbGfuywfLnC6GGNfmxqx8bwibYHSrYO1kdCZpF6OtftNcKQ0VhlxVKRr3oeR2Smk28U5WUcBEJFsYuMe8X2RmUSQLA9TQT1wa4JMO3JU51HVMedkTtghWdFvqHRGz/skCc2W24SOqcNurFj1mDbA9QHHt1eiZg72xrCWGUtz7t844R7+2SEi7YGT8XUxCnA6M1LhMqbUCiG/o+ksVYfFYi5s2K60elLh831HMG2f6iOO8SMPVh7X7ikUKmxsHo77+KcdF7XM+PZHjGo2BhVOTlpEk5Y6F+9NGLgMnKo93Mjp3CepD6c1FTcVxStBOhw9v/64yHzLC7jwPACWHMcv7kcMldf9xg93O6UCKoUiJBs0E0dli+PB825mBmRBGl/Iwz7+VRncVAWT71W+ZoswO2NakA38s3zLfKHZ3y838Z7ySITAH8YwBdU9d966qU/A+B32N+/A8B/9tTzf9ue0QajLUXkR+07f/s7PpO+6x8F8F/ru2zRqZ46U4k9lq/49vKix/jtLY2SOYN8HVFcBArtjT3yZYfytMf25QXqwwLSK8YPW0zfWA8CguUFRRFHb69RHxVQj4E1tblVodsfDdlGttVBMNM3tj/H4wa+1mGDqNGjms5rSWPbzN2goRYKpv99STZaftEOVOa+ohIA5UR2hAEYnh7zJL/CGkiKjpubE+RbNim6jg6pHzmDTdjsR60nDBkWBQeZ7XTzHOVlRHnWQ63wWiwDuhH1p9QBm9vVUEdq9qhs0E7dwPjyDTWv1rcLyvFsA7rJjulUHTPbSrpVxaWpEKfAoBCsr/tByNLXrIUkKGv/c+cAdqw6Z6KnxbIfaLLRCtPpfX3Fbn/XRHSzjH0VbaRadeGwemHM4vk8x+hJT2Vny5KLS6PumSOs92w/lVEBX1NKx6dueituh5xBwOUn9ghZWk2tvAiUSompD8WZvhfvU6IhJziv2fdo9zI61k5x8Yk596ux3qSUefezfGguJMtOBhi1Nw2zfBV4721TMwAYPWYWljVxEFnlQktzBEbHJ5yKyL1l6pf2LfMHVcEj62GuU5RnPfp5hdHba+TriPpaiVh429YCA7060cdHTzpmux2vXXXao3qyZd1wFQd9OcBqMka6yTa8/9mG5IluagSeSnbw53MYig9uJ/97mZP9XQD+FwB+XkQ+a8/9ywB+H4A/JSK/E8CbAH4LgHfbM/qfBvBTAEYA/oI9ADqwPyYiXwEzl9/2rkclwPKFHMUlDR8pl2RZba/l6Esga4iPR6PmJtbY8uURZd1nGRddlcHNPUJZYvHlDbI3HqP92C10kxKbuxN2sqtgdZuNhe3c4+JDFARM9ZR+RMNNuXHF5YdG1hVO9tfZJyYYnQZsb49QnRF3Hj/koo5TzwbEicPFKyUmD/qh6BxKwkb12A1d9mnvldFpxOomxSCrbUQ3cugnhPSKsxr1jRFm93tsD03WxiI639hmaG/XiL6EC3QsszdqrF6s4DepOU4gkf0caXuBxIbLaqpMn3xqjPKSDjwx57bXMmNdRWxul0NtKua8NuNHDVZ3S7R7OVwX0c48DZ5BLtHgsfogw/TtDvVRjsm9GtsbJTY3MhRLHn+/qHjs+94iaJ5bO8usIXC3f0u25dYJaVM4zLx18ZMskfaFkciaVxjR6C8+f4FyNiO0Ns/QjQnpUPrfhFGvTYffqc55byl2qchqamKJKlwfkTWC7cSjLwX5VgdF4mzNwnZ5wX6k5rBEvefQjT33tjHYV4JidNxjW+SolhHNnPBwVjOr6gw6TbT06b2OjlQpfBoKR5FSY9al+7q5SaZcKNwAF7vealKlMxjy69+vzogqrVoja85+nEyQrQM2N8hUjHdLg9eAbjwymjUz/ugJ8zJLcpi92aA+YCPy5nqG+nBm8z2iuCTk5zr2I2U1t2hIStDbo5x74Bx5jB/2pLJPn6+xfz9mJ88y3ksW2c+oqqjq96nqD9jjz6vqiar+elX9qP17+tRnfq+qflhVP66qf+Gp539WVT9lr/2ulKWoaq2qv0VVP6Kqv1ZVv/auxyXEx7M6DjsjhpJGMdtGlJdKGmZgXaA8I55dXsah2S8VhSl3wqa8za0K6x96YagAqZeh0B0tGqU8CY1pgklS57aaXlf0LFy3Uzd8NuSE74ZMp3SDhEgyNC6Y/HmemiZl6Ixmz4cOkVwz97YnyK6wm69oiPzZBvmyh2sjDaowcyAcl7E5c78YpGPUC5qDYqC55ksWqsVUbIfMCamxlY461V2Ks9bOn4QAdYLirDU2F4vBxXlPwkEXkTZU6yZu2NOmPsxQnBHbrw+ouqw54b92L0dx0SPb8Pgmbzeojwqsb3jbHuEpyHDs0CwMJnu4Zad7IcZUipY9dfAdmwnzZRiuX4JmABr1zcszpG14VahwXR5zU6/xA+q/bW4Ug0xLcdZynxyDgZo9P2iatXPS44EkU5P2J+I8486eZJJ1RiuGEMrKV2GAqOqDfIAfXU95GtdTp41U/WYQkUyBF8Bie9Lk851i8rCz79/V0BJhYvFFlllTdkGavlImx7O3pbwkHZiBg4l1WqEfxopMO75m22h7/zB7y9dqvUnMtJLqwfpWgeq4HbZa9tbLlBomuT14HFS/0zFGz60R8mWAigzKGwliex5DVT6wGcz774yeYYhStbWd0ZiFgpFqO3XIbBOv7SGN8OYmm9x8HXZNlY+aoQgfSvYScEteh/xsi8l94vEpaOHeFEzvqzPu3Fcs41OUZR32fxmdBqxerIxuGQe9KTaeEZroSxZry9OWe9LXEeNHPJ5mQew85jQM3BGQlNnRcQ8oF2u23emDAVzIosDye45QHxaoD5jczl5jIdc1cShQ13veRBtloG6nLaWbg2yQhknbBwdr5CuWiuqUNaLJwx7q6JyKizAo5QJA9zRcM3XoZiz8bm8x8+BvyteJaRZfvIe0lXF12puoIQal5qSkvLlZmDwPjfPkfjvAfQwyeF22d8a7onxnsJapTafdNlOfR2cwUjcxqfqc0jBJjyzfEvppD0huaPeLIQDoxg7VcY/8bGtNmoTe1NmukbVak2aP0WkY6iD5mvuZDDuOClBcdMP8ZtEc6GbZcF1jBowf9tgeOuz9jcfYXiPRoa/YXEuKMrgnS2CU781xSL/7TVKs+Z3Oalliv3H6fQtmq5mx/tbM3Lc3KmQbkmJIU8Ygj592JG322DSaerKSarL0PB+/tde2RBXKy0iHazpk67sV+tLtHOcFiSTd1CPbBKvRCHfnXEWMHnO7gu3NCvUhJW54LQkzP6/BIv93RipGRP4fIvJFEfmciPynIrL31GvfsJH9m3zXj4vIf25/f0ZEnojIZ61x/k+LyPjdvuMD52AkmPjdmLTZy1dGpENuwiA3kW0V/Ri4fMljc51smtNPlFjfdLh8MUO7yFE9XBshwBSIbX+Zfl5ifasw2MK2Mt6wk3/+1Q31ts5oXIvLgPKCMuX5ZWeyImTrZJuI5iAbmDKpE7m8CBjfp2R9kkJJx90brZPFbTqlVABv9v0giKkCTN/Y9aWw7sDJTcdhzK5O0RyVqI577nFuDjOULB5zB0XWT5YvkGww7BTq2IuSsHFu7Ca20yFhDACmhsx7kdhqsRCy4WZuKNymXS5VKImTqL0q3Plx82teMaejtnNnHPpsOuv5GT/sBiWDp+sF3EKY12f0pIdYnYTd+BHlOdlhaY+XtD8JFZcpbNpbtJ7k4avHG6PiAgi77DFUDtmqJ43dIMtmL8P2xbmJhLZgF74i5Bj2iUnCovBkUtUH3JSuPG3Z4LqJWN/hfOgrss/Ky6TmsNtOe3ODOnYXP3Ad3YSOoh/TEfiOGWM/zYbskSKsGNSbJTKLHz2seb6dop3K0EeWaOd9KYOQ5uhxNzDnLl/0hPBMxywUDpNfeLyrAe5xv5hEL4cIuin7qropAw2/tUw20dx7EkiSTlp12u16wACMnrTcnuAaN3PLNiTMtAv+P5SUpfENt7dIlPbnaHWee6OlGf+f+gYv/UUAn1LV7wPwJQC/x97/zRrZn3X8SUOivgdAC+C3vtsHPnAOBsL0t5tmqE4D1jeNLSWknlImn93T1Yki21jxtAUmjyKyDbOEkx/cGxZdKIX1mkZZyJ84dCP2oKQtdOujDKuXR5SaN6XX+sDDbxmBbW6WmN5rKRViMEGxpJPJNhHzL61Iue0V6xdG1HxaOOtQdgNLJqujQWDA7K0Gs59/guqcRmpzPR92+bv42Bh9iaH42ZtMTr6JGD3qbItkwcmrGZYv5ENkmYgC22sZRm9SKZcsLUaRrseg0ba+VaBYcWfJ0ZMOzZ5gc10AY3VRa4pTML9kZuN6RTP3aOa7vgVgt4UCYHupqxW6p9wKOtWLoNxGd3stw8h2JkyZQn2YDYXnbEvH382zYbfRbEtjz73ZTfJkGzF9fT1IvbuWRfTVLW+OK2L/CysGCpFGUXpFt1+h2acHa/c8ocW5R7PwCJXH5ppHs2AGOf/i2aCFl5r/Ys56w9knct5bpQTK5hqdZ3XGDK85LBBKSsRQkZmO/OST2cDec7Yr5OhJNxxnPxYsvtaappdCjcLcj+gAu4kb4CVmwQwYINz8bXOrGq7l6ITB2cXLxZA1Zg1Zd5TgJ41dvaCb8P10VJTRWb96nbL91ks0fkAlhOnbPcpTNjQn5exQGEvzcoc0FBc9lSk2DCqypZFdrPl5fbukPp5JPrWLDNmGgchAWZ7TkaagybUKSc1h3+Zgkf870wejqv+V9QQCwP+IHQP3N+EbNLK/8/Mi8hOWAf0MgH/kG/2GMXYnAM7e7Xg+kA4mVA71voNvIopLRnftjLTQrCZdMt8o2nnqQmYT4fqWQ9qwCrCtd5/0XGQPtyY1DvRjoJsRnlj84pIOTE3SxXaKjBmdE4UXYVRZbg6WWEL1nu1TMvFoD0prWEyUVR5jeUF5lGZBzL4vycaa3KtRH+RYf+II2SZg+sZ20AIrljuKbSrYZhsa1Xbq0Bzk2F7L0CwE+cr2Lp9wx0OAkabrFfXtCTurzwLKC9am9n5hhe0BZeChQG6wTT/xyFdAvqZRCIWg3mPGkjrSB5ZbyXpUX1ntyYxvfVQMG6lpttNny02gM2UkmompMHQoT1qE0pQFzAGoFYhTdK+O8GOxipQZOWIAkOoC2ztEAobtiSP7lvqKUfLlR6YYP6wHR1AfkmXmWkJ2+ZoOIZoRTIGqN6h0+8Lcvt8cgsFs+ZqOMG0PETNgcr/D9lpGlqBi2K1yOHcHTB70KC6BycMW2YY7UvpGUVy0tskZHUOC+74+g+Xe9aHAAOOlTLCdZYNO3PzzJ0NH//JuhvKkQWACNWQOEgmTAubMJ3y+M8ZgsxC0c6pVpG2ToRgajkPBnVB9q8gvOY/SluF95eBbZpiuj6jOA/w2wnXA5Uem6KYybF2gzoQx12yoLs96u7fMfn1DKDrb6tdp5j3P8S108h+lpnB7/OS38bP/S+wIUb9UI/swRKQC8IcA/EMAfh2Am+/4vt9qhK23ARwA+LPvdgAfPAcDw4xt46tiTTgqiVRWJz37Lg4c+hGN3fKFHOPH3QA1tFNBuxBsr7GoXFwGtHsl8hUNzPRt49cve5x8H3ejdL1i/tqWPQsmqS6mgZU2g0oMl2JJh0fDb3phuRsoyuubfrdHhqkhJ6ZWO2O63+7lGD9suDmWE2zujHZFfy8DDTpfh6G7uhtTPr887xjNVsD8zZ4EB6NTS2CWEzPB8oWcRiM5E9O+2hlQxfZ6icnbLdY3KHo5eRjMmFOmPhSC/Z87Q7OfDXTYpMJbLAnB4CnmeXKuhe0/kho2U9c/ZX9Iw+3mBeprJWEyg3pYH8IQAcdsJz2zusXspZthgLSS9hXAQr8zqC5f01mqY89Pt2BzaxKGbPcLLP7WCcYPGqxuZbh4hbUpX0djtCmmbzcswlt9TqLuMsm1Il8rZvcYjI4fstG0PswGBeRBJNNEOVe3ORc21zNUpxH1AXuhugmFXVcv0FFOHvQGu+6af6MH9n76a8jXVK9oF4JQWj+LkTSSgrMLwNkPHXEurCO6KaDeDdtWZLZNszMF8Oqkp6CqjW4kBk2ZmrkpHCeacergT71R1WmHMMmQNdzHxjcUdxWDSevDAusbGdo9wpxJcJTbGbBPa30zG/YaEtVBromit35AFbqJmPzQ8+uD+RY7+Y9TU7g9/uDT32Wivp8F8P8G8ButJvLZd9ZUROT/CLJx/0R66hse2tePTwB4TVW/bESqP/6O1/+kqv4A6Hh+HsC/+G7n/v5rHX2XETNgfYMGZXvAnRB1zw8S8GcfL9CNaTzyFRAqIGsUJ59keFadB6xvZIguFXpJQ67OgHYOlGcKqQhLnH6yQnPAfWLUAetbY8xfD7j4kAciqaAxt73mpymbAC4+TGM4fx2Iud8thhlf3x4BoyeK5Yse5blic12weC3i+NXMqMAO5XnAxUdGkMCIenskGB3r0J+QryNWtz2ZYSNBdRrQzgXlheL4U6X1XCg2Rx7b64JsDZSXiu0RYYr6uqJ6AkweAhcfZlPf6BhY3XEoLoHLVwo0e4CvgfWtktM7WtF+AsQzDA7h7Pv2sbkuOPhCh5PvyTG9z2xxdEKJHUqOcNE/+qEMo2Nge5SjPGcfzeXLDvka6EeAKEUVt9c8xg8CYpZhdVcgQTB/M2L5osO1n2tw8j0lZm8FnH/IM5I9UWxuAsvCIV9RPy1lYvW+M2q5YHPd9N5WdHTrmw7j44jzVzLIyxl8A4yOAy5e9ljfuEattSYpeAuWL+Y2DwX1XoXyMmJ1x8E37E/KatieOzAigsfmuqAbV3TwSih3eq/D8qUc07d7bD+S2e6NwOoOId/yXLC5CUzfVEghWHy1xuMfGmH8RHH+oRzztyI2hw7jxxHrGw7T+xHnP/4hjB+1WL5QopsC0hPSKpaK9U0KtbZTMh5n9wJWNzNsbgHVMfccKlY61Mb6UhCP2AhZ38rZH1Yxe1IniLnC11xDMQfOP5LDtUA3JVU6XzGYiQWwuVYOu1imLShYm/MoL3WQetkeuqHJk0EHM8B+xP8v73J9rG6VJg0lGD9iYFWslbDlPs93c81Bn6N0S3xOsbyq/gjAGgyAz6jqZ975HhH5HQD+QQC//qm+wF+qkf1v+4lnOAYVkT8L4J8F205+yfGBczCEWghPIAJoOKlFBc3CdoKsAM04OUMBxEPB9D51yM4+nCFraOwHRV0PbDN+Z7OwTmYlVKYCNHNGfTEHzj7KSL4fA49/sMDoRFFcKto5sL0hQNxBGO3MoA8Bmj2guARGpwHr24zGsi0NVRjZohrB+nwcLl9h3SjmQGlI6fq6IJaC6T1mDs0+ML0PtDOgOmW2RgNBR9POmWWpB5p9Qk/tHCjPAURBuwfka0F5TsbP8ffm6KZAN6Ej7Mdm9FMUrMTcAeDyRYe0LQFrAsDx9+foJsBKnDHdAs4+RgKAb4Dzj5isR5YcLR1rMIfuOgy6V+0M6BZUbQ4VUJwBFx+i87j/YyV8DZx+whsEuruPdNDA4x/MkG2AblLYNgbA5gYdQdrsjZAb0M2YdSXjtr7tka2B7TXAtTIEB5RS4VxoI9BPgWaf94kNokDsOfe6GechVFBc8P7na5jKNdDs5SiWwPGnMut9svlmdqw+BPJLBkAqwOb6iFT4e1QOKJYRp590KC5kp+AdFMsXSlRnrGF1M6C4IKTZzRhM0OkBFy9l6Ka8L+0c0EeCyxcFe19VnH7S79aG43zG647QZ80MeHnXWf1jJ5xZ1VyLSci02ed5lRf8LokMrtTz+VgAYSyoD4wUUAJ+a8zCkq+3cwAgGQBGUkgswHZmkFsL5Btgc9NqSo8aZHWO81/zfByMKtDF7wxYJCI/AeBfAvD3qOrmqZf+DID/QET+LQC3YY3s7/j4FwG8IiIfVtWvAvjHvslP/RiAr77b8XzgHAxguLsHNAd6EwJsZ1zYqhhS/XbBiRw8sLrlBsdRT/g9MQekt82aKgzGKi1C31htZQSg4fPJYANAPwE2JnUf7PMwGCtbmz6ZLZRY0Fgn+nM3ETR7wN6XA1Yv+EH+H7DvygD3FINos6BD6ko6rvlbPSRmxtbZGfkkCbO9ZnumbE0wsgB0zb+bvXQhaciahaBY8vOidh17DHUmVbsW5iwHKRGLXlMzXSgtgjdDuT2iw3HG1ou5XdeW1wIAttc8fM3n+wkMzsrQjym4ySZTGuxY8HzoSO14A68XqbyMnJt9GI2WBipUvCaxMHWDDFYns0BilJR+d9+XYKVYJCII/y8K9E9JEEFpDEMFwGDOWNjr9t3dnP8PFQal67RBW6h295xbJ1jmbVG+6566t7nVdzLu80IYEAhjsgebPYGvsVPYngLZJsGqJAYk+STxu2PKNoRrY2FB0VM6XgmKS8rXYQarrbGGFUpez3xp52LsvlDZebrd+9LcSeebtg0HMLAhw2inQJGCM/at2fxTHm95zvkSil1gEQue6+qFCpcvC+Cej2Q/IbLvWDXi9wMoAfxFE5b/H1X1f/Mujew8TtXaaj5/TkSOAfwMgE899ZbfKiI/BpZW7gH4zLsdzAfOwVCSYqe0y30tgHofGD8AVi9yEo/vc1KPTggLjY+5R/nDHx0hX/G7UiQUSgyildzUiA+AE7ibcjJnGy706gmG6K85BFZ3mc6HEqjOgfULCgmCbsaF1y4Uo8fMHo6/36E4Ay4/JKiOgQe/zmF0H7j/9wjyc6AfK6oTwfghsHwZUK+4fEVQnQCrFxSjh4KLT0Rsr5OuevpJvvfRr2ER/smvUUzeEFQnLMKKEgJpF8D1v1nj4Y9UjERbMCI0B92NeazVGT+nQgO9k1nHAGOp8Pq4ziLtDf+VSIcO8Lse/zDPcXtTMQo0XMUFcP5xxeJLguamvfZQsLmrmL4hWL3ACL3dV6xU0E8VxYUVl0eKfCNYTSKOfg54/GnB+D4zseVdZhLtnmL0SLC5pYgbQX1dsfcF/r88kcHgigKIzIarCwsuWqAvgdkbinYm6Ec8t/KcBe7RcUB13OLhj7ArPdtgoADnWxIP+pHg8G/1OPtYhuLSNrtLWxk8Vch3Pax/i8/1Y86flK3GnMa2uAA2t+lYJQBPvt/DtcDDv1NQnAOnrwLTN4EnP8T39hOFr3eZs2+B84/wvJ/8sKJ6IpyPDwX9mGsp28CUkIGzV4HxPWBzRzG5J1i9pBjfF1x8RDB7k/f47FVg+gaPtZ0Ds7cjVjcJnVYnFgC0tk4tgEvwGOtGuwbikFN5oy95rdNrhPgYnBSXinqf9cXqRNHsCdopMHrELNNv0oZ6nKPLF5l1Pi8WGfD8O/lV9acB/PQ3eP4j3+QzvxfA732X7/0vwFrMO5//KVBN5VsaH8giv2920Ey24WLMajoBZiA6RKXNHguNzUKwerFCcWlwTA8US4uKux3MkgxHN2Hk1ZljSeqs6oDxcRwa4YZtjc1YZxsMjWWuo/PLtoQZRo/5+WLJ7wol3wsHILJOUlyKLXg6F6igH7MPJe194zeU8yguADglA8xxQUsrlqUQJqtO2e0+eaBAVDLBVoScJAJ3/tsNj7vh/5sFDY2L1gcUdk6lndIg5mug3aMBpNgovy9Fp66hUfY1s498KYMh81sgW+32B3GdDLBVtgF8Y42jS0qKZBuxhj0A0a5ZEKzuOLhOeH7bXXbia8H8DaYf6bcJ1ciQBbRzsqLg6AjZ3EkmXr4hDTffKPopv6Ob0rmEyuHsEyP0UwxBSurLIS2axf125lGdGj17kbrhMQQh5fnufs3eCqgPd5mKa3l8iShRXrBRUSKvneuA8WMdAgPX7xSPJQKu2e32qQJsr2PISCQanLQSQsibneE//7Bl+L3ARd4H1wHZevd9ANcElGuttczs7OMO9XXO7W5i98nWTspwfL3LTNK9VFtvZIlxzpP9xveMjnkNt0diitisu0A59/qxZdt+FxwWlzrYiOc1vpM05e+28YHLYGBwTMyB8pQTPk1g9VyEgyFurZ7Q8P3bIxrxvqJDKi8j6iNGvmIQzuiYbKAkFqg5kJ3xu0ZPGI36OtFX+dvFEuhGwPghJ/nkbf6OBB7X7DW+r50y6os5UB4T2pjcE3RToDwRTB8ouhEXf7OXHFdi2gDVY07gxVcYYasH8ksxUU8uvNnr1ijpaRiLSzJ72rHg7OMjtDNej80dZln3f92Yxm6p6GZ0CC4AIUEiFR2GqHX758D4cUS7cEMmo84ynEs6VN8qIMD0LWBzC7bnOjB5m/dm8UbA5shDLugkF1/t0I8Jp1WmzZ15YPZmZOG34LWWwKyiPGHxenKPBA5fy1AjW3zV5PaPd4tdM0KWrjPD66xvyAHjJ+w6X932Q4aR9nHpJxROlMAIf31DBhhP1IKOaMVsL2iO+P3Zegd59RXQWL0nlBj2/+kmVgtZePRTRXUqvM4WNJUXMOUJwehJKlwLSiq5YPSQcFf1BBg/Djua/hoDI5EGGSjOeQ2qJ5wjfst5GMpdzSpBe5N7wPQB96bJtoqbfy3g8oVsyERcAMqHMlwD3wLtvskvWf0x7a3kOiAaDDja7M4/M+jZd3QUvgaqs4hmwSwoOF6DzXVh8KW7uVhcKrqpMKNTILMsCY7fk9WK0ROx2s3zGt9RiOy7anzgzlodJ3m2xgA7pBpIec7+ir1foHFZ32b03c6firws6mnnLFSneRMzYO+r7PpOUV15oahOuAj3f1FRnkeMHwGr2x79hPDK5pZic4M4/Og0YvFai+JScfkhYP8rAdd+9hz5VjF/vcPoRDF7k9H19GHE6DEwvR/hG2D6tmJ1R6wYrMiXjL6zjaA8Fdz6K82gPCCRRqGdWzYxExx8MQyMnlBYJAlgc1OwucXz6yfAtc92VF/uBeoU67vMxpYvM6uoj3ZsqPUtRv2hIsTWHJE5VO87TN+mUQkVUKx4/ovXSB2ePOhw/jFBfWS1pzGwvgXM7nWYPujRThktTx4EzN/s0ex7TB4yeygvFMWSmcXyRYd2AcxfD2jmGDZau/3fb8l4ewG4fMmhvFDc/B8uCIk+pswMIgDHrLG32sD8Te6IOLsXKVDqyZq7fNHzeikd5uYGu/tTHa6vgOPv5bEkWEl6HktzxOscRry+0gPru7yO7QJoDpl9+kaHOl19YBndGkN21c6Ba5/rUF6auKjVTdoZv+fyFUFzAJx/QlEfCCaPSMcePyHjbvFaHMgl+1/uqXK8BGKpaA4VzYFiczswa1uZaOmTiBt/fYNuCszeDsjWwOhUsXzBmfSL4Mn3ZWj3gOYAw1qZvxGHGpVvmDVmW7IcZ28p5m8ETO9HVKeKwuDsdr6bu30FY44ZS2wMbI8cLl/hd3ZT3q/ykjXKwy/0mDxSNPvA9lCwPSIsl+DO2b2IdsbPUM4potl/vnYnQp7p8X4bH0wH0wKL13vM3u7hrDCqDjj/GOGW5cvGjBFbAFuyrMTYLe1iF7GNHynqIwBKYxNMM6wfs05y8RHCEfW+kKI7Zi9IcWFpuNcBQlrdcjh9tcD2SABHHn99Y2IdzoyKXZ+gAhnol0lwsDwn9NTMGZG3+3EojC9fYJPi+Al3YsxXiuIiQSmCds6pkJpEY07jJYEOZ3ud12R9KyPxoFLEijzjbsr30xnTSRe2FXG+fKq4uhZsr/E+nH9UsL3Jmkfae2d112N9m+KOruV9kgCEMY1fO/e4eClDvuamYfU+NdHqfYfNNS7O+pB9RX1FAzx+xP4NCncaxLVH1WzNdZAXufzojEXqPc/sLjXMThnpdjMyrUanOsiLJOfXzQxOWzNb7CZAfQ2IVcTyZR2icrLmbDvrbAeJbm8AtRngfrTrvAcIB25vsE73dAYVCzpIwLJuBc4+Toxx/qaiXezIATE3skhpxzfl9Xc9cPGK2+mAtbzXzcIjbVI3+5rAdYIwiUC+6x9JvVcn3zuGb4DtoTMDzWvazekw+zGPjYabvVTtlDuTVqc2dzJjf5mqxPbQD9puKWNOjMhsS+fbLDj/t9eZedRHO/211AgLc2KXL2ZY3eE6KQyabOakv29vKk4+RYZbc0hG2/qmYwD6nAZZZP6ZHu+38YFzMDCc9+LlDGcfyYZiZrZl7SXmQJhEi9K+3uCWF4riMkFhNBybm6xxxNwiLTNOqbCtuSKUXADrG4J8A5x93DOSXQMxU2iuA8RWHyYnKFi+4HD+sRznH86wuuXRLgTLu7xl65tsjlvfYgE4FIJ63/Do2qA/p0YDNbhvSpgvlMDmhlE7PZ9fviAD+wyw2lTBz/maDiWUjJ7VIj2AGH4YKWKhg2Hsx9Ty0oyQV8LUE3usPgT6kSLmCkQM0WKwWtTFK1zgEgnFSGQhupmz+fXsYx7jJ+wSX95xvD/lDn9XIQU4WNaZOtJTfezJD5DaW5wJygvOh/VNB0Tg7KNuYE1RP21nuDbXqUCwPRJ0Y2aP3ZQwkyivDXeQJDyG3jboMlZcdcyaUT82ZtQ41RgU/ViRGGUpukcErn0uDAw23xg0JjTO/VgxvUdotV2Qmr18UdDOWDdSz5sk/Y5UUZyLqRfsapGh5PeSZcZemlDSgW2vWSDUC8qHGdmENmdcRyhWhQFUviQVvJvy8BMZgewuNhtna2D1gqA6oyQLM1xCorFghhELo/sXRBsom8Q1kplK8sDSNLiQGbYOMkKhZCC4ucE+p27CILGbAJMHfG0IEkbY0c+ndFztAhD3fIr8V1smf4CG9DSa5YWit4JidcJ0e/a6DMW97Q0d0uY0aZt9wfo2I+PqNLDHIwDFhSn72mSvD7kA8xWw+KJjJtCzObGbMBpL8MX0NY/qsQy8/upkx3RrDhjZppR/e0QjUCwpxpk1PE6A2ReFNYHVXWYys696tPtxYDeFig5l9TIdZT/dUbJHx2acrf/HG8kgXykWrylmX9sxqGLBbKQ4dcgvHIozGYrDk3s0NJtbvGbrW4xkXWs1iTJF+wJ4xfihYHKfhfYEIXUzRpP1NWD1Es9v+Qpw/klSYfsJqa7rW5y+KkYk8Dzvbmp02oyf297A0Jzn7TrHgrCU9LtIf/SEr6djT4betQYV7RvDqTem0ohQ1frujhLbzngdqkeC4swhlsq6Walo9gi5pSJzClgn9wSa21zrWPPoR8wEn3y/RzdVzhmj4UoAVrcF5Rnn4+qFROrg3NzcoNEe6PgZz7N6zNpeGDPw8Btmpd2Uc83XwPqOYvKQc3/8wOjcFVAdOzTXw67wnwMn3+uQL41GLhj6XEhbBo4+Z3v9tEDMqfeVoK4k0V9c0MFub1q254DDn98O6ynR09u5Uaj3BOUZhlro6JE1RS9JPgDoQGJh86Lc0bvrI5gILL93e533afyAv1Edg7ToMc8nhudnHq8gsg/KcLsJ24+Z1feVIOQsoo8fRVSPHeAZMXUTHaCLaIu4uGQa73orpE6s+c1gDjGGVmq+UzHces1FMnmkOPx8QLvgIVUn/Lc85WIvlvY750A/ZURcnUVkNTC9r1jdJrW4vFD4LRfc6PGOotqPeczbmwrXko46f7MdsjJfs8u7m9JRhQJwLaG66mQHGaaMpVlQNmb8CIBwMZenwPy1FK0bNj5hNrL35Q6hUlSn7DeIlqHlSxnYPq4F/JpZw/ZIcPDFiLS+2ExJxxLzyHqPgOd6brBlq7YNcWJ/8biTAR893jkQxB301M6B/MLgs/sYeplS1OpaY7UtLVM4MWhmLUPWFsx5NfvM+vwWtu01vo7VFIsUfWPow9he27H/+gmLzN0UgyFVYcOf5pxTo8e7a8I/MPQadTM6ItcB5Zmgmz8d3VO9ACBDz5kjzbbMjqtToDpXVMc87uqEdYniQoYm0naBoYlXBUBP6HVyn3MtQWqwgCj1fRUrZgvNHlUdYsE5B2OTVScY5I66CckXrhGEirurPvnB0XCtJw/Ny1vwlphwaR2nNddPgNnrSiTCgpisZhBWnlO0Nr/AkFEmSnM/5fVKpILOmIKa6XPMYD64LLIPnoNJRqKgUUrd2KnJ6+IVh/pIIT0jcdeRhQNwUiaGGYTQBKmwO9ZNom6mxq/oaZCzDRddavw6eZWsnebQCrVW3ykudgXN4tIWJoDlHYfqCYatYntrsKtOADjSVfsx//aNWBQpLKDWQL2fo7g0Su0xMHtT4Tqj9NaUoM+2ZO2o4eyug+mlcRHWh2awQXLC5Svs9E8sr8Q+Gr29hN+KFXDN2PVkiY2e6GCUF19R5Ft+5vIlh9ETMwpr0otHjwDXOCMrJEkSYHqPvTb5OkGBux6JROIYoD7rE0lwkDPKbih355UgUujOYZHmau8PO9pqdcqMsLxUTK1QDMd72s6A2ZsB87dIvIgl6xGkNZNNllSEi+WOWqwZoavUA+SbXaYdM342dagnyJD3D/CtYPzYaPIxvd8YeRfsyfF2PlBmxM7OMZRUqEjU+/VNh/IcWLzWw2/NadRAP40II0V54lCemNL4ecTeV+IAYaVzgTMKN6hcUJ3qAEd2FsxMHj0F+9U8tvEDgd+6AapL+8E0CxI6Zm+GoTE0QZcpO0tw3fo2r3HId1lmXxG+A5iVp9/tq6fqmYKhCTg1OVePdgHF8xhXG459UEbcYfX5ymAK2UX/iQGWrbmofbPrzO8swlfHmsfoCcn4+QqDpEWKuJLkTIJfemNlJUHMVJjtJ3HoSh+dKhav9whl0tVKuD2QdpVMe270I2B7INj7Wo/yguKCxSWNzvxrJBb0kzg4o1CRctwb/XVznZmPb3j87SztAGk0bmfRouH3mRmwkLqqsatTVKekImcbGrXHf8cBv7smpJVfYsiemgVrR+xWl4FZ1C4YPYaSDmT2pqI5IJ22OAfGjzFkOO1Uhg7yFNkn7arUS6HCY0lU6P0vB7LLVuwDybY7eDCdY74yNYEtML3P3RMXX+2G73Y9UB84U5MGNtcIEXkLKthgG7G67WxTNIVEGTIWv2WwMb7PeecbXm8os8OhJ8b6eSTS8ccMqM6sN6iFzQ/B7A1FeYpBjDPbCKHNlpmu3xKyGzK9fnetUi8Pt5w2CrE5iXbmeZ8NNpTA+9TNud0ze5CibRJniMAMVJOIPLboU8Ymwzpo9yzTHTmjJXM++ZrfM7m3cwztnNluO+P1Wd5lQDY6iaiv7e5X6ifKNolGzv4jv9kRHGKx66tJmQqzf0JsooB0O6QhX+Hr1Ai+3aEq6NU90+P9Nj5wfTACTrL5W+yRSAa3nXFiMUqXIdJUb5BIzs9tD4DpPf7/9HsI8eRrcyLKBV2dsPiZipDqAbVmttPvAaoTWoS04NsDRbYVrG4JNtcyjB4To24XjPy99cOEUvDg78hRndJ4hooMGV9j0F0qT9mc5xtg8qYjFOCB0eMOp68WQwf46Imi2ZcdAcBqGL7GsIlTa53owQNQw9ot4pZASCMWhE18baoHh2T+uABcfJRZoHrCddUTKgSoIwU5s+zF9RjOobjY6ZVVx4SUNosIv3GY3gOmbylWL1g2oOzSTwVdvwV8z+ueNYrzj+2yhtNP0EAhAtvrgsk9y17y3T1KXeD5UnH+YW/01xztgtdw/BCDwnAoSeZwLSAGoUoPPPn+fLg+09esr0OB+RsB5x9m0eXyw7uMKjEDx48CupEnBTwCesYaVBKxbOYA5oLxYypLtDNm191slz1mWx5nVrPY7xpO+HaPTj5lGCliX9/k7o7NgoFTb42v3OeGn5VIJ+9bfn83BVQE3TQb9PG4QR2vyfwtOthQAPVslxGkRtZQKVa3BOMnVCXPNoCsdsoWkwcR9T6p481CMDpRrG9yjsmWDZ3Arpk0v8SgQ0YiBs+7OWKgpSJDfak6BS5fAY4+p1jelaE3JnqTmAkM8poFg6/UO/08xvsR/nqW8f5zme8yKCcObI4oXJgi/FQ/SI1/uUFV/ViHrt/mEOhnissPqzXH7QzT5IF1W3e7vgmAkzrVVPK1shBpjV/lCaBlJNurtV4IqxVsbsiQubQLWwgF0O0xa2IWhSGNb40q200MMniqp0UiUJw2Q9EXwga84oJwWzPfdeKn8y9W/OJ8qQOclCK78tyiviCDvloYkZadmuTmrwcyqWJiYYnpgT0tdc9rop71hGRwU3E9dZtL3DVCbq7z+o2esGEuMdeSplkqdm8PZIDznmYW9WNrINyzyNYi1ZQ9deNdFJ1fcg64zrSrxjv9qm4MEyjdFbU1wYvGQmsOMNB927kb2IX5CoNWVoLFLl/2CFYH2l63zLdQrO8YDLSwrC9jlpL6ktJ3BKO6b6/voNmYMuFo8zRnppkUKAAGVKlOUizJwkqw13A/DCJs9nYwaOqh4nbivF7b62QPjh8r4DDohOUre9+WxxtGwMWHGBh0cwxipRLZQ+R6OshY2H2MnNftjJ/NLzFkoLHA4DSTnluCvep9GTTvIMDmeoJj+by6r2+0DhXnV4Lfnte4qsF8gEbqGu+mbKRMjKKkSEuZFcXkMaEszdXUWZVUy9oid6Pgpgi9toVw8cquQzrVd5IBXd0RFsrVKJS3APSUgU+NjQn+ag64ZW473zmTfgQg0MB25hCT4QC44BOTLDk539I4nL86RXGBQeYm5qRYuy5tTUBnU1yqaWTRQDd7gvoacfRuvNNTg+7YcKmZMtFSY0koSZ1CcxqFMIq210cylAlmYnNoKE2yxeCW7XUaOjo8xeQeIaLknLrxTi8rWPQqKeMs6eh9s+vAT7WX1NWvmW2tYE23SXAyluylCTkDCokstD8tLZ/kVthTE9EuSBse8PtTHk8/1mHObQ95rftyR+pINYBQmvG2a5nqPgAj/lQ3k2DOx6L98tSowsZuCyMATsmOOjHNuxnfEws6nfqGYn2bRrdbpIyHc3xzg6oQSQcM4G/FksSDJMSa2H4hB+Aw0JJhDn55l/UkEj8U2xvs1g9W90jwWFI4zpd2XVseVzvDIIXjW7YEpOsx9KYZFb8+opNMytzZBjv2nGXkszd1EKJNZJTRE0JpcBiOi7tx8jeed0vKB9XBfOAgskQRDSXQzciyivmumrfJFH7rsLwDNHsKv3Fo9xXZkv0eabQLk1QfE75JEWU/DRjf81i9ZJThl3RYmMWZ4PJlGs5uFuFaQXnCmZy0tZo9YHsronzisLmjCOOIyRsem7sKvxEU50LZj+t0dOs7xKqLi12El6Li+mgX5edLZhehsmhvxIVYX+c5HX4W2NwhhhIq04kqgcacV7YB1ncVUNOY2hh7bhahspOrv/xIRHniBudFxp6iOHOkTG/Z1NYtIkLlEAsdIsztrYjinNe7emQwYkvW0/o20M/5fD9hHWP9All03Sxi8iaLwd2EzmPvSxQ1bA4VkhoFFXCN7fF+xmjVd7um2uYwoDj3WL1AAkS+omNfvmS02DEzWEBwuVB409mKObB8iZDL+FHa04RQ6/JDEaOHjrUE8N43h4BmiiSmla2A7W07vk4A4Tllawf1vD7NPo+lWHJe6jXAb3jvtzcjfC0IInAtr/vFJ6IRVQSbFwJG9/zQw9JPFP2MdQfXCep9QmCpd6a4YEOs33KOH/5CxP2/h9BlthWEQi3g2hXCyzNBt1D4htc825gcTC+kXHsdAiL1rOeMHwjqQ+DikwHSk37XHCr1yzLg7FVFdSy4/ChrKsnBLz+kKM7t/lR8T8o0mz2rxTScBxcfVfhW0M0jZB+ACmKmOP0U2TrtPtf46uWI+ZcdLj8a4bdiauSpIenbNTnvT+fxLOMDl8EAFqmMuXB9g51A4ppdy0lPSyKdit+YBLkaPdN6PlKHcrbmgmHnOb8rlE/1vGTUuwqjHSEgQUyJIpnSdN8C2aVDN6fWl+uo6JutuEg0Y6MamU6MFENpcuclu/eTtIdrhXRLpXEk5GdRpOfxIjJDcAHIlnSUxTkdSKhsh863ZOhIT1lLOhffyACrxBFlclKDI+IOuurmCi0UkwcmnvmWG65fcSmojmXYO8VvBGEMNAuYXIxFoBtne9lw/5xE+66OCT9tb+oAWZ59nPdMOgGcYvyWg/QC31jNZkrn2icYKQC+Zld7cSGY3CecFHNei3ZhjXy1OewLOkffyNCIG3Nmxd0MO3iuEXjLipO8C/eYF1SPBaHUYW75jaPT2AD50jHjKnWoscRCh458OnQdRFYlCOIo8vvsWvktm4DzUz8QMmavJXiITjR61noAmDKDfV9PiA8AHv8Q71VyirFUnlctFLdsud10WiepH6W0eZSvkuPj87Ega275CueT3zgqOOc8R9dTa4/riPMIwutPx6HoZlQrKC52GmyibOjsx+ZIrf8l+rRWhffPoFdfy7BXkWvpLF3N8youBBqfn1O46oP5gIzEg08Lpd2LzEJqOpNsLdazwQXsjH1THbM4382B1AsCAH7rmHpbRzskSYcIYmmKwIqBptvu0wgWZzQg+YV9T70zTPkaQ6dytnRDqg+vgyNr93e1CnXcZgDgMafCdsKZy1MrgjoauiSZktSDAUJ7ABf/5haj7DSo1ksjAbFiuvUbqJD9Q1acfUem1l2vdm5WD+llaAgN1a7ID2VU7lo2AsZ8B3PEnMbMBasxmCRMGGEQLe2mRoW1gr9min6iAwwnvaC+oZi+JUNtIVR0oPU1c0qlUYWtC79ZEEICdplq6q1goZvGML+UQeF32AMmt56TDcVEO2vYTQy10SOrE+Ts7QEYzIwfscekOaDOGSIgLVlgsVDAK7IVhr4RwHpp1m6419lW0M12jmf0UIZaI0DSBASonjgSRUYMtOoj3jf1/BsOQzNqGPHeTN6yjDPsemzKMx7b+UfdQHpobY52U8LI6szRC+fR/Gu8xt0s6fbR+SSNu1AA21ucx+1etNqaIhjt269ZdGFWqQNDjuKuXHeJUOBroVJGL8gvmblKJ0Bk9u03zL7H90kGyNc8r1R/eh5DFeije6bH+228/87oXQaNcxx49+WJQ/XQmRMQkxmJuPi4Dos2YdmhwCBh0hwa6+WeSclUlEspTxzCSK0gbkaukSGyV7frsi5PLIqeKJp9PqIxogAaJNYZGOVmS4eYx6FLOeHOxTkXWnMUUT30KI95HmGsCKOI1Us67J00eiioD43GPOUx+1qGyBAA0jYC0pnUyUgRq4iY69BQ14/51uJCcPYpZk0Qtf3kU0bIxSvGoCtPnHVt69Bp7xtGrpP7slNpjjuHm20F03uMtPt5MH00QbsXbb8UHke7YN9Eec5jyldp22HdBQDWVFk9oQaaRIHrzSl6QqaiQHnMfWRSg2gYKfILh2wrX9cT49pdJpt6S/qRWv8UjV63IAxTXAjCmPWR5gCDtHw/47WobA+aYqkozmgkY0Fos5sRCszPHdp96pONnvA6J1JIKOiIQ0GnFUYKzRSbuzro78VC0e4Hy1rpBEePmHV0k11fVHMUUR+pqS9ElCeC8duEJkcPBdM36SyS7H55wky8PCXUJwrU1yOawzhscVCe0kn4hpBjyiabozgQACSAQdSCAV+2YX0yQYept4pBwm4ere/qoMZdWn0rWrNpt4hDMKCejsvXAt8KylM37AvVLnb1zGxNB/hct0z+gNZgPnAOBp4LUB0jzG5Ko55qIOoZNULNQZRKrL8hDFSeYRD8Ky64SF3gAp686dDNiDdLZLo9fsQmslT7cY0AkUYjpeblCRdSakgsLvi+2es8RgTbkKxSZCvPYr8QhkuaUtUxnVh7GLG9TehmdF/gOodQRWOoKdYvRaoUGP2UzZ3EzVPGAafDZlahSk6Hk7+b0UB287jT/vI0bip0Ks6K6wAGRQDAonyDIJODgxnwhM/nF4LDzzMjCSO+njYjy1ZuaOrzte3PkpoUOzGdMwoodnNFs8douzql82yOFN2C4qSu5+eAREwwSFGYHU7fFNuSN8LVO3mStIMkT2hHomiOIuprkUZtYhvFzWGQlaK+FpFf8P4mGDJBjq6lgSvOBKffY9CeMd98y0wndaerJ9lke32XEfmGNZB8SemVa59l/SUZZWDHGnM9IaDyFLvtEx7wN7K12B5C7KkBmKGLki0nwUQ8DW5TY281BzTwm1sKt6V0UNp5M5Q8vm7OOVRc8F5WT+z6B8H0Hq9luwcgmsROxjodhHM5ZjzGJONSnvL4Ro925wPHrJMZKnXPsqXtfXTmCIs/1Rjaj4lgpDWdyBf9hDDt89pw7EqL7D0YIvLvi8hjEflbTz33r4rI2yLyWXv8A0+99ntE5Csi8osi8hueev6HReTn7bV/R2wfUBEpReRP2vN/VURefpbjStTifoxBADEUhGISbJZtZLcfiD3Xj4jpbq9jiMrbvR2t2G9liI4ADDpm9QGGPovRY4tsAxCLyO8yiEidIr+0Y8yZRa1vJyhJhobQZAyH7nlPOKqbMCpEJM4s0WCataA48+gnEdmG35NfcJuBzlg0lLcRSGcCmCWVkol5G9S3Id7OepHVbGoaAQli+6vv4IVuZvh6DcAlqIwZRrqufkuYw29lYNtpBpx/mBCGqxkpd3Ma6SSlkjK30UODWuZ0tGlztuo4ZRTcUqA6I0TC62NOU2WgeXczRsz9RAfDuHqRTrM4ddSFO2T020/NsZacL6kjPCk8kInHeUHWXipqWIRsvT6LrwWDPmXInAq7//2Y2RUczxmyq6MNm3rZtW0OIpo9MrS6maI6Ax7+qAw0+pjrTnjV00lPHgDLVxRwjOrXL7C2pI6vjx4x80ykllACatdfesqrpCwzVKytJSh5ZNk+wPuaNmRLtca0TxE3HGMgsb5jFGZjbiXtMOkExQlNVHnG6xAzAJEZKEDnps5YYRWPKb+Q3XbKhkykbbed1eAIIxrxZcRgsj7g9eqmZCs+z6Eqz/R4v433MoP5KQA/8Q2e/7dV9Qfs8ecBQEReBfDbAHyPfebfFZFEFPz3APwkgI/aI33n7wRwZluE/tsA/vVnOiqh0Y2F7RCZq2G2guZGgNgOid0UyC9ZfJx/mdhzGKl1DItBOMSFN7ci+2WqaLRS4r6aU/F2c4fGuj7kguynO4ZQKppnW8HmbkBzGC1DMpimVOuwp5Esznka3Yz/h2Ndpz0IGN+zguvSorP9gH4a0c2JNeeXQHHu0C0iz8eK8aNHdGgJKiuP3QB3hYq/40y6JNFFsxWVjfNLB7+h+nG2FoRxtDoTDT+hQR3qEs2eFb7NIDUHRv+2786XGDah6ucB3Swi5hH5ktF1exCGXp3Lj8VdP8OEUGA3o8PtpxHdYY9YKS5fFAQjIGQbMfXe3S6fADOVbENjn3prwiiiXaTtCJT9Shs31MhcK+hniu3tANcIRm+TKQfl/UqG2Fnm1k8YVbcL4MkP+oFsUlzQYWyvA90iMKMNvJ719Yj8gk4uTCKP1/G6NodxyDCaA9LAz16NqE6snqE8xtZqe8U5A4jly2ReZQax5UvKCZERp6gPzbGZw+ymtuncXkS7z7nezRTtAWno0jFLlF6wucnrNHnDAULiRbtQOiLPgMR1RmppZFB8bvdsh1XBoF6dNMYkmOJ2SOKYDDSqxwKobRvw/cyI1WjHmilp5go7dt3dewtuuqkiP3dDxpYCFdcKNrefD4Msjasi/3MeqvrfATh9xrf/JgD/kao2qvoagK8A+LUicgvAXFX/iqoqgD8K4Dc/9Zk/Yn//aQC/PmU333SkjCWD9QNYR++I6Xi0fo2YWwGxFqzuWqSWAZu7EWES0S0Mzz8x5lMSF7SCJGAF2kUY9jhPaX5+QQggFVJTZJqKoIm5Vlww/R8/BOBZUE4MmVRjiDn3ive1G6C8UKbagyPcBxD2ss9KL9j7ApV+s7WgvgaUp6wdJZ2uNFybnBiNud+CWUBJZzt+QCOUiuWIMuDdSY7ddbwu3TxCc9Yo2PvChZ2tGElKoMOpr9lC78Qco0e7pyjOHeB316p67AaDoJkiZopYRCy+oihOGZ9ozhqIRBlguck9h1Apz8myDxXumBlzRT+LthEdvzfpmUlPgxgzYPqGDIQKBNYL8g0NW7tn99GMqt841i0Sw84ZdJYxcu7MEfVjhau5AyczTMuSxjr0+sQ8spDtgdFDGsd8KcjWDtVjzsH6GlmE/TSauKiin+6YZ/00Dg236q1uETlHYkWosJ8oJvfT3LHemKWDszrl+L4Mtaf8krRmzQxmtfoMyQD8imwj1gtlzmqu3MG1Jzuym0f2WwEmIaPD7/qtZc2tMCAZR0zuy9B/EyodNteDMFh4GhXIl4Qfk07gQFnveW79yHpkejqefsqA7HnZe9WrGsx3cvwuEfmcQWj79twdAG899Z579twd+/udz3/dZ1S1B3AB4Cnu026IyE+KyM+KyM/GyzUn6AOgOQoIFfHqbOUgjQNsW90wisYSYgHfNYSeYrGL7MM0YnOb2UhvjJjEsoE5HXXKPoCckXqsGBkldlO+IhShnsYl7XQYRorinMXbzQ2gfOKGzaa8RWLtwmCCQ8Xh5wDITuQQSJRPwfi+9emMkiSLYn2XCzGUumMtETkaIkHNMOzZok7RTRSbu4z0i3OjWKeFKhj2e0lFWG9F8WCOLBls9aQ0h3FEN6cDCIUVVhPjSAEY9BZzHRolEXbEh/paHHSsijNvEbvDyad4bG7jabCt2ysV5OtrVjOahp0yQhWHDbwQeJzFOesB3VQH0Ul1vD6J5JCtBfmlQ7tnnxc6hH4SByebr5JUvBjUxzmSmSxPgtYot89ImhvS8d4BnG/FuWN2nNGIT982JYZDkjXq6+ZEChIyUg8Nm13puKtj20AswUSN1VdignLV5jCwfCWinyRjDbR7YaDit3vMRJOzChXPyW8YuHSztBeQDIwuXi/HRt5pwPoOAyW1jAxgltWPeX4xY+azeJ29KXDmwCLVwNMayZfstUlbjKsww9aCO2I21+KQxajVYPsEkUULQhaEK/MlgCKinwU8Q7j6jEMQonumx7f9SyIHIvIXReTL9u/+M3zmp0TkH7W/f9rKFJ8VkS+IyE9+O8fznXYw/x6ADwP4AQAPAPyb9vw3upX6TZ7/Zp/5259U/YOq+mlV/bQfs2V++YrCtQ6udeinEf00GgTFmkN56oBMsfpI4OR+KjLKl7ZVcsTQN6MWBZcn7GAvzxmZ5cc5Zm8Ixm874uErN+xI2M8C1q/0zCRWu2iR/TGKy1d7YxPRmfTWHEkNMKudWJT4+NfQoCw/2WH54QA4a0I86JkRmMEZdpD0AAJZVOqA9nrPaHrOTClbOsAp9r7ILCq/9CguBfmFQz/l93RzxdmrkVBhFXfUYoOP8iXQXA/INoL2eo8wiXCNoN1XIPC7XCuDJMzA9skYvWqm1oWu6BcB9RGdeTenNRRjgKXNy1KHeBxFDJ39ThHm/SDlki9Z+NYMQMdjUK+o7psXsizWtYyQm1s98nWqaRGi8htCKNmWLKUw4fv7eYDbuqEeg2hGeAz0M/tsK+j2uaNpcxhRHjuEMVl4xYUMEFt9nc62m1nBPTKocA0dTD9VnHwvocCYcb+eWMSh5uM6fibVcHTaQ71icycg5jTcYRwHuJT7F/GaJjYhs02HOAkMmswBwhGq7I46IPKYE6U8jCPZbgckWUzfMjXmkg3Mo0eC+kiBjnBqN1U6nZUDvKK+EZAvBWEakK3orE5eZQCXMlrNGKhVjwWbOxHtAe9FcxhQH5HJ6XrA1Q4XH2HUVJzTeZXHguoJ4UHXsiYYSsXoMddAP+W68FsHfT41frNBz7cGIyI/LiI/9Q1e+t0A/pKqfhTAX7L/f6vjn1DVHwDwdwH410Xkly39+R11MKr6SFWDqkYAfwjAr7WX7gF44am33gVw356/+w2e/7rPiEgGYIFngeSUhkudWhSe0vIdE0mF0R2s0Jg6/fNLB1QRobDPBKM1z3Zc/eaIhradsd4RKzJ+0jbLCfKI4wD4tCmUbTN8QSbQwOZqaYAB1mja/WC/C8RxQBgxslPD5dUB4hUYBWAUKId+6QfHKIGOMl+6ActnXYlsHullaGoMFTOqob8mMyc3jwhVNIounZhrCdGl33E9M5DNCxGIdKZ+6QnxZMbQUeLx/TSwEa8HtDCDVuoA5XUzRfWEmWW+dIOzT5TWWLBTO8F7/aIfIuuhOVB20XY/sfqCU7i1tyxDUF8P6CdW0+hkcGoA4ZxYGLOtipSCgdHWLx1p6L3BeUtG7K7m0uoOe/QjOtR+GhAt6yNl3Rpia4f8wrK2THf3uNBBxTjBp6n+kArY6hXII9Z3+NnEAotlHMRas5UDth5asCDvNw5hag5v7dCb42wO47AeQqXwgzMnFJqfelNxICFE/I7KP3lTBuYZ+4oiylPB+at0FCgiYhWxuW3H6I2+b2SCkGj+TzzPN9UxPeuXqQlYvQ6ZYD/FsGaD9XmN36bDm9zne8OcAWJ9tMtgtjcIE25vB6xe5tpd36Ej6idqSIA8twxG8R2FyJ4uHfwR7EoKwxCO3y8ivyAifw7A9V/iu6YA1gDCL/dgvqMOxmoqafzDABLD7M8A+G3GDHsFLOb/NVV9AGApIj9q9ZXfDuA/e+ozv8P+/kcB/NdWp/mmg81g7OrmfiA6dFAnI5KvZIhK2b3PJq32KDAaLHY/k1hd+lTm4QLQ7wU2cc76QZNq9MANzZfqFX7pBz2mfqyob/eorwWUp2K6Xra9bUY6pRaK9gYzAakJAVA8UWiYiggNTAXcOTVeCO/xNmdrGqZuP5hEiyCWxL/hgDgJ0MKMqbPmPoPAXC8DZFY98qaF5QaITDOFFhGZQR6aAXEUUJx5qNsZ6AEqzCnh4jo3dNKrMJp0RteOZbSNr2iEu0VgD9PbPJ+YK/q9QBjq3LGhzuohcRzMEQmkdghjq68JabPSWgOewXlaROg0ENY0QwzHSNt1dCClMZrWd8zwHfR0WNYIGaxxN+1zEkeR1yU3aFSAfr9Hdu7R7UVkK2+srEBywlwBy8oS1NjNA8KE0FR7QDIB4UjWSzipLSjpWL+BB7JLD9cImqOA9lqPbOXg17xf1RNLsZwijPmb/SxQ9cH2ENIR5VvU0TlefiSi2w/Y3oqoj2xtrDOqN0Rg+eE4YA5s3mRzK+cTgDIC1pypNq/6aRzmv2acD1TYEBSnHtUT0vfjmMSCfsb7Ux7TmTfXecwp6/Vrh+VHeN/PP77L2hPRpXosqK+R9RitXpjYhWke9PMAv3SsdT6vDEb5Xc/yAHCU4Hx7fKsQ1Q2zm7B/v5Hz+IcBfBzA9wL4XwP4O9/x+p8Qkc8B+EUA/5qq/rIdzHumRSYi/yGAHwcv2D0A/wqAHxeRHwCn4usA/ikAUNXPi8ifAvALAHoA/8xTJ/VPg4y0EYC/YA8A+MMA/piIfAXMXH7bMx2YV2R31+jqDF1wQOPQX+/gqh4aBc11a7BqPRePU2wWAq4cw4HnPeCAYtyibz1y0yxSBWLv4LIIiQ6hcxAA/s4GANAq4KIDbkZkUYBxT6e0zhAOesBHuCyiXgh0myFOIlzJ/V/EAdrRwIlTaOTiaz+6hXiFByDCY/c+QhY1ujqD8woNAg0O9ULgyx4uCjAHsiyibz00CnweEXtBbDzCQWDoocb6KgN8FoHOIcsiugP2CAhtHdptBl9EOAXiXoNMgNA5lGUAFg1yATQK+pZZjBQBzq5PXvVDp7MDEHtCBeIUThQxGnQQKN2RHbaorwtC4+HyiNg79B/tAFFI7yBO0c465D4ijnt4HxGDgwiQiULHgqb1zGCyiHCNn/MZnXP/Sg9vx6+dg5906GcOIormOghVTYFi3EFVEOe83u2mQFZ1iL2DzyP6Gw4uAi6LiJVDlvM4IAox0kG0JkK0HnHawxcRWOaIez1cZql043mcH+kYECxa1tCjQDcZ/Lzlfd8TeAAaBN4Busf7js7DlwFx2sH5iFyA+gdbuGjXeE+hrYf2JAxo7dGNIvyoh77UAw0/H1oPXwSE2sMVAaHJIEWA94pQOhSjDt2+R14ExMjoX0ThokCnDmg85FaNGAjd+dxINQuBc4BGQJsMWvUInYf2Av1oC60zrrtZC/QO/V6L3s7TOVurwSFMeM1SxOyziBgFZRYRJg4aBdsjhVdB2DN1jfR5BSRTZAB8HtBVGTQ6YJU/k0l5lvEtMMSOVfXTv9SLIvJXAZRgdnEgIp+1l/4lVf0vn/E3/m4A/6HZ2Psi8l+/4/V/QlV/VkSuAfjLIvJfqOobz3oCT4/3zMGo6j/2DZ7+w9/k/b8XwO/9Bs//LIBPfYPnawC/5ZdzbH1aUBsaPHQCVIBuMhZxbPKLV2jal3vL92oOSK5wZzn6PCA2GVQDnFf4LCAkLFWYcmsv6J2HOEXs7PfKnSGFAsgVqB2QWZqsQHbhEaaC6ACXBfs+MAuIjB7hFZpFIBDjdV4RbeEhgk4jCmLr+bleEMQTDssiujYfelSSc4Fw8Yoo0Bje3Xo4HxE7D59HOoQ6I0QiNFDRnF7sHd8bHEKvX9espqscmtFpx9ZDg6CrS8iYzl2E34HaI6Zi/6SnIYBAth7ZXkQIDtEpYud4DC4itB7a+eH7+y63Ai6vpwFP0M7Dn2XoF6xJaMf7EDuH2Hp+nxl3aR1iVxB+DDwWrDLCpIFOJ/b8Nx0DAMTgeH+DgzggrnNgQueDKMCohwZB7D20JSTnWod+1kNaB+1z9GWEKxhjaXCIGjkXxbJUIcTGtbBrCozqAFUIhA4tCo8rAtHRASfDqlEQAXNyhCGrhx719YBYkPUhWURonc09m9NRgK3jfKoCEATtNh+2GGY9AXQc9jcUPI4tiRdhHOBnnV0vXiu0DkEz1ta8otvkPFcAsckAzywp2rXXFHxAoZ2jY8si1AKN2DsGGB0djC8i+nUGqT0w76CNh+QBsc44b7IIVQ+cFdBxQGbH9+0OtSL/c/ku1R8BWIMB8BlV/cw73vJIRG6p6gNDjB7/kof17r/1RET+JoAfAfDd5WC+a4cC8bKAXxkODRBhVMCtPGIZ4S9zo1R6Yr6GS7vaIeQR2HrEUYCuzUBf5AiZQmdAbDz0IocWTPklU+hlPmiAoXWIywyxivArj3wpqG/18B0jWmkc/PUt+nVGx9E6hH4XZWHr4TYO8ajlcTQ0ilh7xDmj6tA7OoOyR2gyoHOsN1xrUH6lQv1KA3lSYvREsPlEw8zIMUsCADQOYowp6QmbBB/pVDOrbfRMcXTjIZOezskK79obKcJlwDjQeBWRlGknkIcV8jYxsgLGP1+h3QO6vQAtrAs9CHTRoXirRPtiA3+cs+G1dwidR2w9/GWGuNcxM/IKjYCoIG49ncQ6Y+1l0fPcesJl8XqD4l6F9khQPMnQ3ex4Hk6BaY/x5ypsvq+GNDn0qIGuLYpe0fjp1iEgJ5xVBvTLinUvpfOXkwxaRaAX6HkOzHvkXx0NtOWwbwFI7ZGtHMKMAU1+kqHbZ0FdPJ0wosBtHcpjFs5JIHGob/VUiW6ynakwOEsbD4wCtCVRw11mnH8O0CpAVx6oSATB0ubwKABwaA4j4MGAqhdCh14hnSPC1QnVsxcd4jbD3l8v0U2BzYsBOg5otzmdKIAQBa7sETY5oTDTIwsT25V1k9HhLTNg1sMvHbKN1WCcYvK6s54mwmbdQUAsItA63usgcBEI0wBpHdf0YQ9ZeQSn0NahDTKcY0CAs7Urlzl8I+j3CJciOmhLR6STYFnWLxsZ+tvNzvOC2959pNLB77N//7Nv8J7/DsA/JSJ/FITQ/l4A/8E73yQiYwA/CODf+OUezK8ETflXdqggu7Qid0nWjwRhduFghVzWZRCsON0TGpMA+LVH+YgLX4Jg9EZOwbzWIRqEBQeUjzIWjGsz3uOeRXurNVApN6K5HiANt5DFrBu2vwWIVUsEpHaEf5aZcVqZ3kubfo9F09h6RtWdgzvPEDY5tBOrI/Az7R4/T9KAQnsHf5lxATRk8vg16zvsXzHcfJkj2wjcwxKxNqNmdF46Fjfg2SpsLnQ1YSYLMlnjkR3NOhV7tzfZU+M3vF6uZx1kkIsJguKS391flNBNBrf2ZN5tPNySEbr0Dlixiq69FZbte7B1yE8yFssz4vJw7HmRPEArwoIui1h9vIPLuBGcmnMGsCNlFMxo3MYzo/GW7VmGkq2FQYuz2ktDGnO24fVySw/UhOnCPLB25nYF6/IxszvpHKZfYQxY3w6IeSQsuh9JqbcMzJ3mcOc5tHXwpzn8itCv3zhk57xX1SM/BDl+9dSyz6xh19aDeoXmVuyf9rwfBTNol9nkNfhUInDxakBzZA4qEHZDw7kqK4/YMWOR2vGzUSCFUfXTdQUAWzvNrR5hylrT6pVIrbJovSnLp5hdalRkhyHj4frVQdFCWgd/XAyKHVjS0botr/2uxihc45FQrNt4+KVHmfffrrXZreXvXCf/7wPw94nIlwH8ffb/d47/FMCXAfw8yOz9b9/x+p8w6O1vAPgpVf0bv9yD+cBlMCyqspHKn+YsLM4j/EmO8X3B8uMKlD1kXSK/9OgOevilR5gFLL4sOPn0LqqRVlDfDiiO/cD8ktrBdY6EAKToCNBLRnFxxMg2P83QzbmQogd01sOdFTRq98Zwwj4OKNlHbuu48LYOsYoQe292niHs98xqxuYPNp7vT3vVzAJ6B8BgrdGXSmxeIaYvjUMcR0jrINMOepmj3wuM7OfGjrM9cprrPfzKm86at2NRBJiwpRVLQ6UIsx6zX8yxzs2BZw5SRH7vggVviXT2/SRi+5GA/O0CEshq8muH4DzJAKsMmxd7+DUJA/lJvmvqc0aLPmeW6GuBO/dU6rWamWxpyNL+JuGsoJLCvIP0GSafrXD5iZ5O8LxAvvToO4fRY4dtyQBBR4Hfk0dU9zN0exFxxIhYgyJOArLTDGER0C4iYc/Wwa8F0dQQuhmNWnHsB8HQbj8ADTOF9kDhV56sqdMMYaRYf6JlBijguUpEtvTo93sa0YzNqwDnC/db0YE27zqBjiN36DzN0O9R3cBd5OwHmZgz2XhoGTF67FFfh/V2CaonDtuSZiJeFFRw6HnffA3Ud3s2KRvEpgCy8wzdYccAqLUAo2CR39UO7mFBtuI4oHqjIPmkd1h+mCQMV9Nx7H3B4ezXdOjLiPkXMyw/RGeTn3l0pvKAcUD2JCdpYC9ADB1A4yxAiXAG9fqGDan9hPsTbT/UQbZuCEKkJSMyFop42GFbP58aDAv4z8V5PPWd+tMAfvobPH8C4Ne/y2cVwO/6JV778W//6HbjA5fBpA7m1AfQG0wmgWJ9CAJtPfpZQHezpQHOFSgDpc4dO8YhNLzFsScLC4Bc5CbTH+E2DigDyhOH8okfKM0weZdQsg8nTMLQgeyMXRZzRZwGMmemgVGmRcQAGGE6hescO7Abakf5lQO2DsWFQ3/Qo3yYkRa78hjdt8heqHQrXpFdeGSXFkU6Rv2uZSE6jBVakloKr+wSz9jH4rZ0fGHCHgzpbF8TY9PFKkJqj9WHwtBs6VoB8ghfA6NHpBuHSdxRso3plraqDdVOqsO1xvTpAGkdwigiTAO7yT2Ps3rMBdwbrbY4d2w4zPi6jgLFNS0D5LUUxAmpqq7qh/4P1wLTr/ph24AwCbsoWSnhAwDV/WxoEpRARwLb1sBtPNV/WxkcX5gGTF7zw86aYUz2k/SMnCeveZ63mtZZEYesGq0DTMBy9BgoHmeoHlqmY+zF/MJh/Dadldg1iyXn9OYWGW3SsE8rjgK6/TAwIl3tMHorp5BqYj4q50p2totDY6mYvca+lPp24Hx+2nZaVu02nPMIvG5u4wdDn7J3gAoRm7sRq1fITBNTZdBccfY9O8e1fCUOn+0nvC7VEwfUXJ/9PEDzSLWBjtmLdDIwKF3L93WLiH7Ro7kWGYgljTrlHkWa855o/3wdwlUn/wdl2D10LaMp5JysxYW9oEB2voNEinPbVfAiR7swWMqiRCgdRXni2Hzp2TQ20C6XGeprcbcTZhGhBYvyolSElZ4LQgMb9aDsDE84tpaM9hOtmBRPAUYRcb+j7EVFamYiDLTXWMDuZ4S5REn11SgoLhy/s2Hm0E8jsktGjOOvFKZ4bGynjI5IbJGi8egXAdKRgpx6JhCFzmgU6BCtgROjwD3YS1u0UbC9FVAf6qAHxoY6j9FbGam+0x0VF6kzvCBpgQ2p5ogyxeY2j016QajouMR2L2xu9ijOPGG3LFpHuQDTQKOTCBaBx67G8IIn9Xt7g/0XEsl6k9Yx+rY+GVc79jxldNqIMhTd4zgiWwsO/xazK79x6I54T9afbNHuW4PjiPUWnfCYQgVkSyNaVAwisMzgLz2DEMvalq9EtEeB8FDr6OR79nBs7ia4jZlpXPS8F5ld25YOyW2SJyfkF6uI+hazG/RcF65jUDT/mq0dg0NXLzPTQMleLr8yEkDqwakI5RVnds1sl03XkBreHfTcA2bjh85/LkqqN6emW9eJ7d1i80HA4EYwXC8IhnPyF9nQjCodmyWTlE4cB8QxAwVxhizk0XquOL9Wr4QBEpbGkUn2nMa3QFN+X40PnoNRWJe61QQyRXbuUV+nUGVxSrirekSGTzfb3fVsK1xMRaRzmvYI04jtCx0jPse+BYwCF+c0oDrmApLDZligMu8QxhHbD7dwWyoJiGMvxuSeQ3Oj5+LNI7KLbGcMlFhxduEJC2z88J3hoEdYBKAj7OUMTmJDnok9tg7tnRYyJltJAiGt/mYLv7ZrMA8on/iBkp2ypvpIuSjLiHDUDY2ZKJgdSB7hlx7VI2+SKgqsMuvK12E3xCFCLCOyCw+38QijiO0LPbvrxc4zY9NdHO0goOLMoT/qoWU0gxqhkwCZdmiuBYQC0HmP8sTBz1s0N8xg1h7ZOeG27FGOWFrmtMqQXbI2Mf5yQUda8lhioaSOVxHaemZp0zDIlfR77C2RnllQapLM1o47ks4iTj5FRxgqZhF+mQFrXpPskvMIEahez6nndjugnweEWRhqARB+vp9EZKfZ0CfjrA8EEWw4HUXEgw5hEuDXrElBgew4Y2HcMXOLpQ7yO37lgGlgD0hJ+DJWZAn6S48wYW1qfRfwK8411wKj++ynwZpzM5YK9AK/pMNIgXg/pvEOkzAoUmDcExUwNerugI2x3MyONamhBoRdP1B54pAaSCnnr0O/TT+lw9OcmWIseT26gx7xoENzGOBWHpIrwixAVh79XiCM6SzDLRSYBPZeGcqQF8+nBqMQxOie6fF+G++/M3q34ahwHGY9jaSYBAwAeCoQq1fUNwMjeWU0mDa5AmDNljQ8rnaQTFGeCqoHxqTKCOFAKH0RDXrxZxkhgOigubGxbC8VNB5+7bF+wdg9ahmWcjMq6encsjV3DuxnAfmZH7ILWXuD0ixy7Gj4igtBnPfILz3yc6OJ5tH2VhHsf94B6wzZSoZGxG5hRj0KWW9jMxCTQDq1Y01GcxpO6Ryw9QgTwiYxYySqVeCOn/aAClzVU0/LirPjtwiboGRD4ZAJ9DLI9GsW4VqH5iVKBIsZqbSrokZep/p2D+0FzSEpw37jdp3p8zDoYSVnlyTc2ZwJlMc72roogIzsrvEb2dDECTAS90vPc1DsAoBcqeBcsr4QDnuTtZfBaOZLZpDNzR6zzxWcRxmhOM15nlLT0aWGz+QAusOemYVBZXB8XfPkQCzbVIvqO6FEjYNR8ekI44jzOFSkV+enGZtRK94Ht2aQII6RfBLalBXPOV+B0jNVMK0zhVac8zFX6qcJHbRrBYd/Pd9lKZKCDDZoSusQ93pkG2arKHcNm+qZdSW1aLd10CKivtNxfudWBwu8PmIyOXtfcJbVG718FHnOW08WXMbsXCOG6yVBAMu24vj5scfS0Gd8vN/GB8/BCICcBeDimAyx1KqhGcUhZd5RvuPMIx61jHhzxfgei9raEw8vH2YDXru9EVHfDMN+34mx4xoHjCJCzQIrHEgfBRgNm3pzkbKGKVllMMw4TCI2L4XBKPQLRq35uR/qR9h4MtNWnjLlqdtfqE4Mp8PmZNKz56PbDwjTHuefpJNwLWhcaoc47+k8th5ImY45Etc6aMv6gmusBhRBQ1nsjEPqmeBunDrAGNp5Onen6PYC6muK4swDWxIQUoHXNQ5xrxscOPXKFNiQmg0AOmXGhjXxfsmYpakD0DPKxTggP/cDY8k1Asl5P+N+h1gp8uMMq5cpRY/WAeZQYT0521sMOrJLg+sAhIMe/X6PMI6IY9Kr84csCocJ76HkAf0RsyGx+RAzhb/MII3D+tNbQIX3a9bTUUeTJPIRKJgVFucmxJp6XUbB4FTWThI8hGUOTAN3Hy1MfbqMKB976u5lhPRQMWvJlw7akchSnnieW+egsx6+BR2sN6Vxu3ZhElFf260l18kAkYnVWDa3I+JeR2PugdMf7pGfGkszpBqRI4MO7PNqrgV0Bz2ZcJfsNRJjpcVZoAOb9yYkK6wNmtPPL9wgcwQAyxcBdLxm+TF7abJLrvUE3WLNupIa7OZXzPrjKEIyhV+651cT0e8oi+y7anzwHIzVKQArCAMmCkgjEOc9dJ0zxT7qkT0sGFnNeqw/xMXrNw7jtyn3kbSxMO1JAd24oQvbnefEx1fs2UgGBAD8MoM7LeDXHuGgQ3u3JWTXpb1k4i6iA4AqkP4a6Qi72y1ft+Ikirg7jkjoCrVDXDCqd50MRklXOY3XuId0Fh0veP6Ux6HzlSADHBgnAdmFJ77eOCvqG1vKAf4igwRB+cQjzHv0NzpkF9zoTAvCFeoV2XEGyVj0Lc4IrwzabivPzdIU7N84J3Qky4wSP6cFMO3hl5QoQW2R6ijQKCudXtLEwiiyiz0zCGkS0B4auy+CzXl5RLcXKNJ46Xg+AjaqHud0OBmdTbcf4NdUtXYXGZ+3xkVxJn+zZSYqgWoM2ZPc4B8as3DNmveKiNgQokNhXftW1G+PApw1++L/z96fxtq2Ztdh2Jhft9ba7Wnuuc27r62GRbIkiqJEWorkDoZj+Y+lAHJAQ4gVQAIDh05k+I9l/8gfw4GNAE7sRFIgJIZlAxYj2HFMBLIVR0KQQKJt0hZFsihW86peve62p93NWutr82N8e53LJ1bVK/IWKdZ7Czi45+5zzt6r/eacY44xpgKGh4G9pFCDb89kRN9o4MjzFj6KwDKQpl3A/pzjOR3PaCCZrx0ryZ1BntMuSG1YBfujjLKKJI/UfiNK3c85ezdpkXH0K5qVZK9hn1mEo4R4EtlLHIW6JwByYyebo4P+xdY+pwQG8UNPMkcFd/6CjsoUuA8t8nFggrOtiWBlx0GYOBzgwvF+nKa0FgWEV0f+ngbCaSAzb03IuQjoKlDIqjugEenMIy1ZvZWgkO55pPgSl8dPaAnzyQswqE3b4ZY+yawu80FQ4KKVgKNfMohL2srrZ5Zmf11E1rR817vKwzfE+dWo2IMpguaJQV4HlC6he6KQVnUwfcfGeZ4lQgqmVkRBTV5NqiP2m2ZcZIrJVLdbAF2a/JtyR3PG3Q95NixbWs3onSI0MEu3Wa8taB9rTkqsD6k29dg2t3oE0oIJhZgNK7W8THVUL1lkpa37IKC2ZMaKp6g6Y2VQFGUex4nFo7caYivhYaeroWiezAtZBZWpItA7Nfl3uQtFCK+heLJ9xiqE1SA1Jf5uVccfh9vEQWeIyqSvHiZLmgolFdTKiNmtjIpzXyohoDQ8N4dFqzR5on6Pd4nVI1C4ieqAIIUzavKa50Nm8VZgW3tZ5rGbvOhkS/o79lUYCs4tQXUpUNd2gmsmg8nDIqR5rkqs+p7aY5FEVwAUNtZLJUiEdab40hQuxnWUdhGgrCPhz5rN5zZTH6QKe32HTRVcfyFDP7WEqNoymXMWy/OFsbovBzLCcOQhma7e42mm3c+VBnaazMF6P/oj3reqkjbG+3RqRqnjxHvF81SoRcOogHkNMo7UfzUKE7oDVAjSn9My0uU6MXmDsO8STiJFpQD0U8fqWRe453QUNS9VaPlpBfOJ2SZLi9rkoxV5XWgPT3CXcfVjAVIx23TmObclcKRsdsR1c1MpjS6zmWoKytMG/lVPEeNWY/cZZq1FF8BkZr9thlSfMfZcCAtJoGBP7XQNeoSI0ORbeGZBdXxRQLzn+bD1GqqNSHszORSUKAxclYHTvxqJWY8C7DVCbyYGUeoyRZHLWCsajvRdvs1zojfmdtFNhD7Es9GOTAv8g6ivtBmzDwhvpFVk5VPNIyXQyBCWmbG90Zg9AReLLtLAc0MNSDGVUnonwT/07CFlwf7znotPBsRl9iBMQfvIAIMmRXdLPrrUxb2sA89pFKhzN1GDS5t5DhcR+zciG9dXrDY57Iz/0jlYIMsAdHGCQUuTJ7w/nEaMd6rFi6LNkNnzXGFjgAVhNYm4ZbVZBtGSBfrcYDzN3M9BI7uqC3GJ0xZbQnhpTu2VvaaPXLgfpvtWkrCXpUk1b57qiX1WIl0BDvs79SYKeyEY6BhQDKnpckG9ivTU18CyD5dbVnT5OEBfc4WWKKz+Dm4JHeE1UUw8ZKzsxUIdGhbso6mBti9YRFK067gEsaX2SzJyU01KK4svr2rzvYABaGPgLjXSWUBaZtomVVq/HNwDFok9NlXQPDGTQ4feKCaDD0bCuIVTRTEqjE9nL2W9KQAtmz7G1/fb9skLMFmQLx3KMqJ9VMvhJY3y8r2RWpaNgb6k99E0C2Nn2HCOCv6H++nhLI4eRuaZZZZbsX4xeXoYxHLRkVEBe9qbqHML9AcabcXnTwIXSwA48SgZt9DXXiOdeb7XXk9ZNXZUHRfLBUE1hIwghYrpyN5JdjUbN4fhYkLPppFsONTMVl3aqXeUX+2x+WJgz+LY86EsANo60GpZezWDRrwTkc5CdYk22P6wp0ZjVIhrKvjlmrDHQUcinhXB5jM8Duz44Ocm3y4AO1YHdh4oSpxH9oYGBcwJ/4nNgGHjHKoAx35inqXAjBiDhrnfA4uIfOpR7g9U3wuqtxezcX3kkdasNtOdgPFBmH4nzxJKzyBmbjTEsRptvunINDMF6myEer8FbKGbggPyiWdQTiQH+LsR0rAhjsJqSUaFtKYupZgC99RAH3s2o3d2GiMMy/vKvz7C32Pi0qw5ZUvbjPn7Va90ZZCWiXCWywwaha7Jcm0ZZKqVzIFWrwaF/vUAe26hbzTyMrFfNksIpwEYFPS1QVkHVjxJJh1NMQV6GdhPs0yI6AvHKirPUx3ZwAoYieSRtIqVIg4+UysKXpvFCAQFvTFw5xp5nhCPIp2lry2r/SzAMqIsIrItsB86VulSkNeViVmDp9iM8VXen+NpJfAIkB+MGM8S5HmDfG9EPmKCpTcaau1fzppTA+HH+vo+2z55AQZgZmXYlD9YSqS9pQ+RcKRxWiTYDxtmmmNtaCsqrdNYK51685ZIOEffGOTTwObxqAlvBIX26w3kwhGyyrjl9O/Zo1AXduLiiye8VSIfADH8OVSBaSPU42aymiHjRqhN8WSB5YNjcVTVjgQTDCVewcwisArAsvZqqifWQRNitwL7nOSFtLeTSho9G9Mw9Hgqy8h9nEeyvCrM1jwnPXr+a67OpslwT82kkSgHlpgQgsu2UFG/4mKp93zP3OXpvLZPNVIgw6dU3QqA2usCT2YBZu+wL1IitSoYFc1Iq14kbB01HnuDNBjCOI5UcKn9oYMxI6rgUWoju3liKKKswT0uEjNvAcZ7te9wbYAPWwbCwzC0ex7Ymak5nWZMQkRIugCqZUrV0+gtjzmsMx2dE6uOuK79AcUxCSWQbaa3GmE0JIUkwe419lCoHRKYJ5ZV3QGKPCQGXlOPNbD67d43yKsI3VKZn+b1HO9r/8OzApEEPhM7ijwPbgKSBKk3tzNbdoQdRVURsi7UB91oSKSXmOo1K8xRQV1Y6HNT59Zk9j8c9US3c5CEbg660t51JmHGk74ejhNiC5TE8yaqkAhStWSHfcIsVYcNoRXQqAhnJ6H1jmPwN+7lepF9qoP5JGwHhtelq5gzIQM1KCApNBdqGjqUmjKpkUtlJOVZgtwwi0XLxqjaaeRVRD4KEJ0nT6buXQuYguFNj3JKy49iy9TMyx2HQuU1szZU9lTzuBoGZuEiCvouxYF9jUmHg1I9tCpUk5jNy42ZdBAHCmtZpNpQFSidoWy6FW56BffMQJ9bxHlBWNXZKDvNIVmDmeAroFI6D2K1XtOdtgarOKf2YfdZVm6IAn9WXYFNgX1mWRWOpMWWWgWIKpOPGTaGTdhzg/aRQZgX5I2jULBJMDMK9UphhYQtP388LmRy+Toh0RSUUmG0ZWSAqOdGRoWyjsBOk90HkPE1GBpjpgovehIz/J00QTx6HlhpVLEmjSRJGU7LxCBZqeBQNWisI8wioLjMQXeZU05LwbQISpJp5LZkYTVdqfIyIwNRMhDm9QaasTLMnrY97ZdbpEWceld0heDvIbCfNrH8FDVfKlT1ugJka+jAjHrfVIo6TO21FEzsurSM0HMmU6IYHJv3LG2YukgXg33tg4SDAWolkSiOSCiqAL3ic2QK0j1fmWNA3DOx8acvCGMNmX9lFXjv7Qypy7WfhVnVPZXKlhw1xLFSUybBXfJ6KJd47Uf2dYoqUz9Pbw3yqGGvFXQNji9l+7TJ/wnZqjJdeeLphweL7BlDmOXugIM5o7lhg764CuO0vDlpK1JuF5gdsy+Rwn7IjUGcA6ph8JBzVzNBgWrI6tFHI7HxDOitqWr1F+xrRoX0vCVN+uEA0ZlivcRy+uRvN5Nx4EGjMames8Aej5h9w7KSUBxwVnYW5bxBvmRTU1yCHHn4o4y4TkhtZcbtNVk8plJsE/HvqamawYdS8ZyWsxEAmPnOExvcsbLgZpGjouuQLLXTFEjG2sR91kxGocdfqovyhmK42YegsBOAfWahHjdIvaEIcEvXaiwiSQVHCeEVQkLhoedCJkD7dccsuU6ZlDUXet1Q7W8XHvrDBrLVmP+ahbo2zLB3mvqcNUkfUtloh6rCPHYM6KaK81oK+vKKvZw4I0wWj6gfKnW98sdcpPc/6MkudNX5uItwVwrmmote81xBlgF5kVByhXJ39CGTynbLc/YLyonHeFoTopb9rO49Q3JJoXByaoafW4jN8K97JkUZGO+wMa9dQlny/YvNOPp7lvdwqs7gDeFIdRh10Wuoxw3Mjcb45gisAvKNoxXTOtVRAfxbtdMIRyTYAAAWCegqkWUVIdcW6s7Iz6s0YmQ6I6heAb2axkPAlgoFozLUFFmbqwhdnS3MPPK5UwV5a6ljmyWOiqijIFQVymqXoLe85/XWILw5wPuXZdX48Rr8nzb5vx+2TIFd6qpCe+0ZPDTI3Z8GQwEQ6k4kUfMCBWZNJnHR7Q0x8iazkpglujKbgnLiqYquC34RQB154sxRYXglIPUG5orMrnziaVlzUanANk19EcwTcqxQ3IkHkiB3CRc/RsaaalJlvglt7WeJvYakMHxhYJ9iY5DuEINm76gKJ1Fhqy6xSa5rlrqMmH3ZMYDsNWBYrekbBk91RRz8sKCVK8f5GosAuTHIfXVczoAI9TwycpE8uBvn48AGq8vsz3QZ5z8RgBlpw0UXnP94RPOeQ7EZ7Tn3zT6pzKaWppwAkO942AsD+8jxOg2ECEsSQqFRiK/XAWwAEDcO/iwi9pYOAYuE/mHtu3myoaDKLcRY3XjLnhBiPErQNvFc1H5YWkdWSVXjlE1hEK8QkgRCraU6P+fmNmAVrxnoVwnqbMTwmTpKIQpE5aqap88bkkBdWujK+FOmjuE+GF/ajOFVUrpRqNspAi6oi6oDObAWe8179ygy0AtQ6kjk6y9Qw3VgHhYFOkgDyDsLs1FIdwN1VpFwG9rqZKFrlVct9tMqothKLEhg/7BjT01URlkHpCvHqr1OaD1spfrA5VFPiQIUbWl0F+HPyMqELsg1CYo7w9ea2i9a3DL2DokZCQUU5uZqyJkWkeMgzKcVzG91++QFGOEiVRwZL5PfUEu7Ew5TqmVzwaRRGO/WrGirkA+T7hJQrhxEAfY5m+PYGsgsQhlaZJS9Ida7JgxTMuC+2UBsgXniEF8ZJyhMVGaWFZnVo0uTmh9FIDoT3jrYhQwKzTcd51aUykgCmTvKJg5yKuwzSCI8Ig2PU1xCUQX6mePrikaAE224APvXErUCiwjTRChLNXyp7DBUYaRq2Hw/nD/l6wja2kfKo5681YAXepl7LqiwdTTAwWp9ULfqdADDgwj7zGL3IwObvXOK4Uoig0rqdMrDeFwMZOGJFx7vMnDhLSBEuTNQbfp1PleyrcOndE0Gqt0OesP+Q4VxxCWgzbTTMQVxMAyaB8KG0H/scH1gmYgUASHDWURepgoX1apqS12P3rOyRpfq+ITqvOAVq4StAjQFkkBlE6LCfQW0269BI48MQmkZ2YNxdOLGnZHuEZ49Kuw00oID39QN4aFSoVYUsF9x0OSk2tsydCSAufWUgyWtWe24gMd15LU8+Jr1ilU6qu2MLRzcFhTcc1PnCwHFZQ7Mc5nHv4xAFCzeUVAnIyQStpMuTlDnJDi1GaLzNEdn/SVWaqaNJIcApNRHxZk5VU+EQcO0AWarJ6sl5DpY7WVsh97jx/j6fts+VoARkX9URPRHXvux780ufe83WQSK4QZisAd7irK1E2wDAdQicPHM/BsUTHYjuovUtBTAPapWGFImAR8+bLlQ1wzVtAHlokHz2FKTkNjwnYZD5TrV75Atv9JDHXj4dX66fbdls/Q4kLZsChkwL9yX6YzNStEF8rSp0xb5N2IztEvsEwEQBaQzz4xRsYITk1HOxslNNj4YK42W0xmxjCjrSIhEF+SjgHzRMAs1pDrTOZksNmUTWXKVqWbmtPnAMpJ2q9kDSosEPYs4CA51F9F+wOvh1iPiA899N5nBuvZo4BUnUnrNLH0dmCw8GIBjD9cFQipNgukqnberDfrq2KxrMzePGs05zTHTij5Wh+teVK0me0KZ4/0IdWUo2nMZ+nhEeThQe5PBfsGJh3QcDKZHEjd0cxB6CsWPXeZ9lBmY0rL6nQXen6XJSEvaz4RXRqBNCA8qQy9WM0jHRVXZDLceGWR6zUW1sAekTJ60S2Kojtc7zt5Rezod5Jqg6KrDkg3JGVIHmcmO1xymYLwXoGdh6rOoReDCXQO52EzSRc8hXnkdkY/9dNxmPRLCvLL08RMQJswCv2lYwZd6bRYRmy9wn9TKQzWJjfyo6D125Qjr1t6nVCnA5q1apaTaw+kVBayezMLZO7yWpU74jA9GBr55ZWG+MI31Jaw6H/Pr+2v7uBXM3wDwt0Tk3guv/V++B/vz27KVK8esTRcuIACnPtaGv8wDzCxCv9sRr3WZ88+PPOTOCLUMSJcV220z/J3IxUQRSy5RId3xXMCEWW+4aVBWAf6ITrOq5QKrdxSdlb2hPkaA0mTErQWetsDdgdldIpsmeU2FeWbFotae7Ki9ppZhVDCLgPy0RXaVUXXuCJOpgnTtUIJG882GxplthHq/Y6AdOEq6bC2Dw0DGlWjuT37WMKvdaZp3RoE+t6xkgkCeN7dWLYNCCcJRt3vSwdFwlnvRBUpnMtoU7XnsuSG9tyOGLgoY3xzhznqEgdoU9ZU59y+ywRtO6qKjqcU5MNXQkw1WkoLfuyq4LDxPXV3A60x5tIlsrQo9haPMYVm1cpSnDbPqln0ltAn2katwX4Kac9Z9unZIfb1+y0iL+x1nu5d1oKdWrxE3jur5QbFnMYs0l1wFBuFQF8Nq+4MscE8ttUu9YR9QCtwzQ0PWV4ZJ3W6/1iG/N+N90GYmF7og3fVIFw0hsIuGpAhdkBYkIpR1ZC8yCWSoVjwbi7ImaaXsDLr7O+pZvIK6NjDziOQ14isj3DcbwmigjQ0uHTBq7D8fGNCqTqtEkibG04S4txyUVofhoZIxVBvJJhNWM+l5y4DZZpTnDdLeoPlKe8uuO4owW43wgD238rxBiRTmliZDP3F8vj2993LdT+iC/Wupepgp4P1uGh53GJkd/a/LqX+Li87H/Po+2z5ugPkygP8dgP+PiPyP6mu/a8OtOhlJkVwFlN4wU2uoIIcwa0peI73RQzfstxRDbDcPhrPVF5Halqo7kQqp6QpBIanK5JLbOe8DBYYTJLHTWH+FzcaiKpMnCNzzCssozhU3V7XnsaBXUzrz7IkoQltmzv5NWcWpYsrzNNnX5HWEvjbIV67anReMb7ApHwc79UoAVO0Jx8fmdYQ71wwcLrOR6hLU2iPtq6jywUC7kyTEsLPQlLGq5GndK3Wss6EVziIhR43kK5U1geNwHw7Qjot1jgI34zjkA8PMn93SyrGo1U6XkLeWkF8UZqhdQr527BnEysS7dKz0KmyHUbFiBIAby2RgTgZWWVVd0NbA7MhqKlUAi0EjHFc24aFHIGTIiaoq8o1BvD9ClgGmDdzP6qwg1QKoWNK95dqyekhC9h8w/S7q/JOwSmifC3sJVXEfHnhkU4OrFGhHT7tcNSjuQ1sp6wK5YSUoOsPsFNSxn1hd4/26ujsmPnqs7DlToCwTq2ksgwBlnliNHBhpWSZnCWkS7JIaJBlU1SqxL1Jq9aoHmVhtZkcRajwLdVEHR36fsRqS6gsHgH29jvsY57xPyyIxILYcGIgiKEdEHfxJ7btYwlNoqhbLJrinZhq3IZFwbHaFHoSGaIJ4gWleounlpwHm226llPL/BPDPAfg/ici/jN+tp6Pwocwz0m/VPHBBScLeh3BRR6qwy42FeUJNR9laNO/b6ciNJftEhCW2qjYkAL2qSlTQz+1UtqPSR808stq5M+Li9/N7ycKBY6uI8R51IWzeZgrMVpGL18HlOHL2SdpbQgBd5EhbsPkqhq4Dh7kueVFJCDZDNQluFiZ33fhgnOzagRfo2V7Bn9J/TRRtXpQmrRgAiQKDQVwl5NPAbHDtYVfsKxVTKAw9HqHaSAy9ZqmHVSl3GemE0JW2eaqSRHOxLs8bzsqp4kdzTWNCqc4LJQpkHpF7w/5HrXBkEaBdJt4vAE48zLyKVzeGlczGEMJbewBlYh/ZGSFI2EyhZa5wkdDwEYnEihIrdp6onVBXFu4bLaeTXlkoXWBtom/XnQFiCfH5s8BM2VbY6qRCXqcj1MlIarXJk8rfXWiMJ6gBmhoYBAV/nKBUIQRZr1tpaLcf3hgYVFyCOhtIpzeZMBAIgxVdoFsmIdLR5SHdCYT15oFWKU2CW3nsLzved6rArcYKmRK69cfs8SlNgowsAsph7s6BGCAFxibkeyMDbpsQ3hxQTkc23et4h0NPRG4MIb69pjNCAdpHrCzDHVZG2GuUlp5q6TQAvYZpIoxL0Cceau1Ja64EGTnygAD+NY9mNUKfsoLUswiceGibkG8cdV6uoHXhpa05nwotv/0mAFBK+SqAfxTAPwbgR75XO/U93Qob+7qllXoeDcVgJkPWAbhyE61XTIY9HusNXYBZpDIawvnehc7EyhTYNsI6+mGhAPKgn+AJEaAEDWUJqbgmoGkDTEOqbh4M4aM7ZGCJLmRhLQO0zWiPBrRHA5StosxEWxHYQs2ByeiWI0QBbu7hjgc0ixF6FtAtR9iGlY3o2mvZWPhNA4AVl2kjxGWM9wPUhg8tbIFaehIhbCZp4cwjjgZp1BQnNgliE9rHGuaJhV14NLOAFDTUkip0XDpSMJ83yEHDtpEU6QsHJDpW23mAPebCR0V3Qr5oMN40sK/smYFbBmj9xg7mM1tmmQ8GmFlEubZoT3peo72ZaLBxa+mjloW9mNpHklXgcZ/1yNcOZWcn+yC98hAp0OcWasGxv6LYM1GWWbA6GSGqoFmN0+IFULEfPtfDzALyKiINGuNgUUyGtZGfLwVmHtmDEABnI5lo545an71h8lEE2GvolUf5wg7xnkdpEwN11W6oUUGpAjsLSF5BXtvDHI1YnO5hmsS+SBKkUUO3ZIi5WUDeWBjLwOFa9mnKjWUlfm2YeJkC35PMEr3G/GQPe7cns7K6WePKEVatzMB25pmcgfR889oO89XAAGIKYtBo557Q5M7UfmA1mY0a+sTDzKoVz7GHthlYRmhXR4v/4A7u4Q5mFnmf39tz9IPhOdDHI++9F3qMbu5hZ+w/AuBzJYC/bCFS4LoAbVj1l0yIXPX0HPTh5U2U/1Ro+W22Usrvf+H7XSnlfwrgM9+zvfpebqqwfyKV5RNr5ZEF5cZCTke0vziDWzCjiSOdkJE5Slk09RMwBWEw1GIUPoQFFL1h0JUVwmopnTcQR/696IIQNIadQxgIzUmUibWi7/b8dx6ArUEcNfzecsDjSMaSauhgW1ThIpoU/GiRa0Ydvca448IegkYYDNq33fQA6bWn1mDQE9MMwHScclgwE3sTal/hLF3QfKNhL2dOFbWyGcNnPIdw7RxyVUdrS8sC2qzU2ywJ/HVDS/ljj1KA/HBA9BopKoS+Vod7TQjyyiIFLmAUY1YBYZFp3wEAi4QwGKz/rqM9ySpAP2IAhRQozcUt+coS0gVxbxCftxTeLT2TgZGQkt+6iaGl1h76kjqpPNLOPcfq/FAEzXtuajqj1PlCnlRuMwtV7JepqdjzvkgXrjaegXzjEPeW4kiwunVLX6uDF+7bOnOmZJmgXElACJrXyVMVHwc76TfyjhooZfLEUlJCCO1wzv1oCOfOCCnlGZmLaWOBGwt14WCbiJg0wnlL/UjdcscKRzZ0UOh3DROvyMZ+CnraFzf3SNeOATeRnKAUDVdz0DjAAjkpwn3XDmnk8xa2DmnOfY6eCU70fC5opVQQer5erhzGreM5jkK/vbpwH3qLKMD8awapPhspKsiNZbVfNXHlxmLWviSrGGASTn/Hr+9iE5E/JSK/VL/+joj8vhd+9sdE5Msi8jUR+fMf8/229d83RaQXkV8Ukb9X3/sL39XO1e3bhmgR+T/i20Nh/+vfzIf+jm4VNy6ZfQpRQHna0FVVKMzbfi6gAabKA6aQBDAqZKVJCxZAPXeQBwNKBsq1hQegbigCzNXnK3tHXczOwF4YpDcSUtQoo4a55pAuCQK1s2TEfN5PkADmCSVoyE5jyAL7gaMJ5QtMHWRBftYQ5tsahGXFrwWk7V5bmI3G8Janz1gGiuNxo9KK49ZCshCGM4WixCbywa+ZPXYaWGaMr3vIpYO7VvBnXExL4HwO2WnEpnqKzQJx/oav5y4zi95amMdsvIbTwAXFZsS94c91ndtiE3JH8sOBJVeigt/Vpm2ToZ40iOsIvTVIS8HN5zLcUwuIRVglmBuNuGYwoVtx7aWFmoEXQdG0zXerEePOotgE976DP03UrWSBUmzcy6bCcBV2DM9blAcRpjbZMWikeq7KOiI/62oPoSBsHKSrXmYayNeO+/dgJOOrI5SWRmpClMlIuiANBvnmwOaiviUXQlXpbkDZOEhDCnKa08U61HlCUoASLbAKKEHBdAEhaGBrkFqeVLG07M/HZMvJQFKLdBGlEWQAKVZ7pFmdc/O45SiEtWdwO1Chb+hTBlX7Hu83NI60mXY2Up+/LXsgKbIfKNcGZRmRLhyKK1BdhD4dEXcGyPqWNry1SJUJl4JC+6HB8Eq8pZs3CVgGyLUlrXxPV+R40LWBTDXVK+ze4rVQg0JWZDmWTGZec6kwPEhIL5E2/FIJabfbNwD846WUSxH5ZwH8ZQD/SGX8/gUA/zSA9wH8vIj8bCnlV7+L9367lPKjACAi/wsA/waAP/3d7uB3qmB+AcB/X7/+uRe+P3z97tsEfFifNRCb4T6wnKVhClRQSJeEyPxFi/C8hb6szcUDq6jXiNcNjSyPIsqjluwhDcg5M1/JFU81BeamCsPaBH8WkLeWzd1KU3ZnPadV9gL/SkB83lJQee2Itfs6ZyMpquQPTc/ArBW9nlT8ZqeAUdOiRhfi2IrutQfrdxUx9Zb0uYV6Xg0yc21mV2ucvCNT7aCHUIOCPG9gnjjgxCN+tq8aIUIRCAo49jy+JiNeNZBAF+LiMvQskBhgM9IrA/KrPe1QriwXclWQbxzsjSZsuGEgOdjN4MLVYFdqliyIR4T2cDYwoK4i0ps9UlOgjjzPVyEpoHmHlZfe0ihTBjod2wtmuH5DUkDaW9r9F/pwLb5qgHsD3PuO+p7TkRDqwaLfCyviKr4sQVFP0WvOZ/EkTDRPaGFTKokCukw+ZcgUTZaG2XjsLeLOEga7qJqrWWKg3lhgp5ksbHmu2rcbuiQENrzRVsHh7NbeRkytBG4cadSljnA+GEP2LzCmAq+1urJkRN5Y3osZkEHBbsjqylsLubaYfdnRuuXugJIEzTcdHzTFy4VRo1xbIMitaHNBCDFdNZBIDY7uaVkkFWXQN/R/g+HwtOappj6qNt/H+xH2knRs1d+SMMpBpNnWJv3BHFU49rscUcwrVTx8eH5yUNAP9xzffTCdfRnbx23wf5dBqJTyd0opl/W//w2AV+v3PwHga6WUr5dSPICfAfDHP/r3IvKWiPyciPy8iPyb3+ajVgAuv83Pv+X2bQNMKeWvHL4AXL74//rat9xE5D8Qkaci8isvvHYiIv+1iHy1/nv8ws/+9VrOfVlE/pkXXv8DIvLL9Wf/vgjzWRFpROT/Vl//b0XkzY991JX1gyKcYgg2j/MxS2J1bdlgzYLUshE7OQe7TLpqYRMcdd6H3lDLIQMfkoPnE8e+xvqf24xI9QroEkJv4G6E2phqLY69JnurcAFTnn9XpGaG9U7UW7oop0UCdhp2y0Vx+IznwnTkWbE0eRKlxaMqyhRqZvJRFZ7Vxj1ni4CEhy3ZYUWBBp4NRynnkcwuHBbaw/1yaOynag4ZhfYeLk/Eg4PGInvNXoKjVU6pmiFJIAtpThKCqYajOPYMqBBgFSAD3YuxM6SSV2W7CJDWsRIfyPJTo8J4j6JXNdT5KQKaVh5X+G1jXhCggs7Kg2A4Y7UYV7cTFmVT/cxiNd6sjgjuieU5XlYISxcg0QbIH6Xp8qd5hntygCOF5/HQ9K9Qja5D6nJD5tRhoJa51igtZ/8cGGXjHbp6q0uaoiJWur0wsCjDnp5USBjHHuLyJMIE+Dwc/zcNqwHFMd5pkaiRWQSaVFZTy+FNT01MFpR5wnCXwSx7ulIMD8lMi0ekXUug592BEtw+5nXk/ZKn+TFpnskmDBruQpNxFgUIHGkdZ9XDrOq80OaJodg+raOmD3T16l9WbJ202uTJGUCqUS1Xv3I7vTUpum97aoNeXg/mYzb4f2tN/j8D4L+s3z8E8N4LP3u/vvbR7d8D8JdKKT8O4PFHfvbZCpG9DeBfBfDv/mZ26rtR8n+3Rd5/COCPfeS1Pw/gb5ZSPg/gb9b/Q0R+GMBPAvhi/Zu/+IKw8y8B+CkAn69fh/f8M2DQ+xyA/z2Af+dj7VXkTZvbagqp2RgOJ7cTKYEXgowpUFu6Eh+sNYqvSv+EKajEYy6cuie7B1WNnDoOd8LhoXCZhnrV+h+XDv6IDzRc7cdokGYJQHlBeLVqTvYK7QcHFwEuBBAuTKXNiB1xcWUTLWUEXBQdB00VS9sTHEY21zk4sqFlzcEBuByGbrlC7P8Fv7NsC5RLSDfU3hyGlZUuATcW+sag/VAjrApV2LW/JaPifkWO6TVPHadXeho7No8tMCqENUf8Zq9J9z0me6wUYRWlMmxb58FrCjVLpCJejYLypCWkVu1UABBT14Q5c1Pg75HxlpsC6ehQUKrjrjLUhqhBITugaNAl2HLgWtxVs85qzKm3lXptCuyWp/UwabQEBSjQGLJnBn14iuJn++n/MuMQOySpgV6Qq2G33ismKIlWNxyeVhMCKVTI78jo0nuZpmyWTJIAysGiRuj91ebaxGczW6qljuiCy99f1e5tRqjUYTWw6ojrCFw59n8Kbt286wTKaaSzqay2sXqVuTyZgdJBXGG4l6DOLdoPLCtIxeF6nKYKYEeHhzTPNONsMvavZJS63stA2Bg9IWZcOAx38+0CfRBKXzKpEc/roc8t4bsapMohodMF9lpDXRvkG0cR8Cq+vJHJwHdTwdwRkV944eunvtNbi8g/Ca6H/9rhpW+xBx/d/giAv1q//48/8rO3Syk/Wkr5LIB/BYTfvuvtuwkw39VWSvn/Arj4yMt/HMCh8vkrAP7EC6//TCllLKV8A8DXAPyEiDwAsCql/FwppQD4jz7yN4f3+k8B/FOH6ubbbapWzeZGU+RVrSbEZWLTq8RhYsd+8nlKq0iH3/pQLb9kOV63FhOHefX2mWX2XYWA8IqWGrrQnyqwOa2GW+8vlujgpMeRcy/02kONarK1P+DG8SQirJnl6tORg6WKULDmEsI6kbJ7Q4bW1FwXoH1GKvP8bQvM4hRoD/Y3aZUm23MZuLoVQ5U5DoPLwN+V581EQ06ngbTaUU16B3+aIQHAQA2PPmc1Zb7eEeqqjgfxbmB27hX1GJqBYHxQq4rTcRI3Ln65QVnS7TjsLXsFV44z5x8bwnNNQTmlkt0ejVNzV0rFwJcR+Tiwx5UFcjJCPSW7Tbwik+vKIZxGeslZDmLr3rfMgkFLIKlwkgocPSAKsJca+1c56z4e1UmeQcFdaLin9b6oBIpiCS+hZ8Zv3mux/rJC+w2O51YXvL/iOiKtaxVxQ1iweWwYlEfFmSq2IJ6wEgkPR4p1x5qIzBIrWZNhrzXsB45zjgDkqDmu4HTkv4YVdFlFwCvM3iFE6q5JXJAspF8PdDrIurKeKuxX6ngAAOy9HWyLBt4XUpMXSSC9fZHgjzhVUu90HWUh00TL9hkHveV11RHN6vRXkwk9AvVzKzvMFj7bhyB9mLezMRxUt2cwMnVAmn1uCVtuDfS1RjiNhAozaB3z1KKx8TstJx9/yx/zC3heSvmDL3xNC7uI/HStKn5RRF6pr/0IKHr/46WU8/qr7wN47YVPfxXAh99izz5O4fCzIHP4u96+bYARkY2I3IjIDYAfOXx/eP038Xn3SimPAKD+e7e+/q1Kuof1+4++/uv+ppQSAVwDOP0Wx/FTh4wgDDvizjUjzQdBYF8Dzp7luXnikGYZR79suEiOzLQxKoQly3WAvRAVhEORGsJuUkB7kGuNuMgTbVbtmNWFswCJgtixNF+9LZzxYTlTJlY8X6pVvN5pZFOqmLHQD60OEoMUKvb3hkFpb1gNCYV8dkObEL/mAjAel8msEJn9lrjIJDEc7OylwGyrM0BfRXd9HdwlgAqAe8ahW4f3OmT9eq/gLthgVoOCiqzC8mEO+g1db8MqsblsM1QQLtyDqtMy2TDPVdxYgsL+1TwNV5ON4QjhAmCr4U+ZVR+qQr1XCFcNITjPRZjjd8EGfOIclXzj4K6Er5nCCZKOIsGSaw9to5EaJhHl0FOoxIfccN/hObhMomD+Lo8htxnLv29gb9gDK8JKSu/UtNgexkynWcb2zYLxTq7eXoCKDNpFFeie1Zne1mqxySSlRHq+wVcYKnKSZNHl1k3BFKgLh7DigiuJMBt6ThnNG/Zk8sBgJ7UvMx6zChrPai8iCrA1U69DMuhW4EgfV71C93VHnVF9H9Vr+qcJ0Dyh0WduCiu8OuJYb8jawmG0dr2u/pjP6CEX775h+ZlXvN8kHYKscAR1Hd6mEuFnuSZcqLwgHBEmbZ9oaA/2aVRBWNbrp3htEAUq8n1zU14eRFbwUiCyUspfqFXFj5ZSPhSR1wH83wH8z0opX3nhV38ewOdrj8WB6NDP/gZv+bfrzwDgT32bj/6jAN7+mEf767ZvewZLKcvfzJv+JrZvVdJ9u1Lv45aBqFnAXwaA5rXXiqpZ16F6gS6QvYK7EqQWiEuqrZGB7WsFxaBi0hzSlfWhhwMaEXpBnBGHds8MTC9ITa3U6wIupcDsFSmubS3NK+y2e8hFyFwY5KbAPbFI8wx9o+GugeEMgAb0tiqTdYF60kAPAn9SzQ+Lgt0A+dqgaGDUBtoLJFXqdJex/rsOfg2Mpu7zMsE8s0htQftcwa8LLTa0JvzT86FPJsFsVK12gPGU+243bLTrawPl2a+yG0FYAtkC3QcKKgH7+wXmmlCIP01onmrEBRfFvMgwe0FynJZpNgq+TlfEyCz6ECDMRsHsgbDkjHrd83qFk0hKrRdk0Vh9RWHzFgNCe2k5blgV2HMH3QPZaizeAy5/mC4C9qYOfvMCdc3PSzsG7NRlLvA7DbsVKA/EFa+/2XIhwmGuzq8LDECcE2JToyB1tKIpFQrrHmmMx8zk7RODuKy3riroHin4I8BsNPLIqZ/2hoEpNXQ/lsgApXoGcz0Ag+WIYL3jyGndK/YQk8BsOKgrzgpmjxR6x0C++rLG/kGBvbYcg52A8X5m5XJpEWf0SHPXPCblAXnMoFQESAcY0hWEBffNXjEAZVsr88j7sHmqEbuCxXuC/i4TlbAopIrfMEFLLWCvFFJbF/2eLM7xToa7qvfjnkHJXSqEoww9CKIXdI8F+1duqyUAaJ8L9q/yuLJlYmivNJQHxo4BVyLJHrkpaJ/wsyUB9s2Xp+T/HrHI/jdgUv0XK3gTa9UTqxj+b4CpyH9QSvnSb/D3fw7AfyIifw7Af/aRn31WRH4RXKk8gD/7m9nBl6ck+njbExF5UEp5VOGvp/X1b1XSvY9bZsSLr7/4N++LiAGwxj8Iyf0Dm2Qway1CRpUFIILmHIACBgM07ytO5hONxfvAcMobzl0b+CMGnOZCIXY1Kx2B1ADLLxsGFsMHsWigewpIUUgWGE8AsxPYG8H8w4L+jiA3guRY8didII+0z2ieK4zHBXEumH8gSI6Lqfb8rEM2fSADqABkx/1UAeieKOgeiAuge5uOyf1ZhYsiYPZAtgr2RuCuaL8x+0DQXAM3nwHsDtCDQHtAooEZCjZvCIrh4q48z13z2NZFG2jO2bcwO0BfCOICaJ8Di/cEfl1/55mG3dA23q8LuicMjH7N7HE8KZi9y0w9zgWmB7IV2Gtg91pB8fU8GSAuCnQv6N4zaC+AsABSqzEecx85XRF47f+d8P4/rpFaZrTuGvBLXovsuDgXXSeXBsDuBKnXyAZILc+n6QVhXmAgWP+axv4BYG+AsBK4AdAjv8ICmH3Ixfj0VxOe/phGcyFQge/njwuWb2uMp0D3VDB6Eg66x4LluwXXn9Foz2twEsJwdivQI+BX3BcVeWyLD4Crz/O+DUsOEJs9AravM1EIq4LmuYbZA37NY5g94n00+1DBr3gvSbV9UR5TRTScZbhrhfn7QGoUkwoAs8fA7pV6rEtez9kjYPMG73W/ZiKiR96L3TMBoOHX9Rm6EdhdgR9lOu8pC9rngB4FsasJxA6AErTnGnHGcw3wZ4uv10ANQI8KdgdIZKW5epvPWm6A1AiyBWYf1BHjClg+FYzHvC9VUJg/Ktg+5H7FOZMSiSRO6Jfdg3nJWynlz+JbLPyllL8O4K9/h7//BoA//MJL/3Z9/R0A3cvYx+9ZD+ZbbD+LWy71nwbwX7zw+k9WZthbYDP/v6sw2kZE/lDtr/yLH/mbw3v9SQB/q/Zpvu0mhVmm3WKqkVRdHPozwG74cGsPjp0FH6r2AhO9c/3VAhWA418rsBtB+wyYfcjMXRIfDkk1yBhg/U5EXHCxk8yH+uYzrGL8Ed9L1WpDRaB9Bi6O1Yuqv8uFLlvuX/eEiysE1T6f76kiEFZlqp6KZvaZDf9WCisQKH7uYYFFDTrD3YKbt3guAD7M+3tAnAE3b7Kp7Y94ToriObIbBrY44+cCwOwppvpyuAPEjsctiQ92nHNR14MgzgB/xONLDV+TispIBuIhm9xjMkbU+/o57zML1yM/pwinPaaOx2433M8P/igX8eainuMEpBnPXdZAnBdkw2scF5zOmF9IvbJBHVUscFdMFHTPY7Rbfq88ExGzZyBAAS6+oLnoroD+LjP1IjV4KJ6X5gI4iCY3ryooz+udLa+D6XluSq14w5J/H+dAf8Zz1VwwoB7Omdny3tIDK56wrPeCZaCBAM0Vr1+c8WdF83O4T6w8VeA+jMe8Xs153TeHyX8szgr294H5B4AZ+B4AjzksC8bjigIIP2s8Lti9ImQ8Bn41F/z82N1e90OACktwDpBlsgThe+fKdSmK1/5QISRb7/XA+8kfFfgl96XomizG2+PYvC7IDa9xcvW8D5Xy/+n2W96+Z2dRRP4qgJ8D8AUReV9E/gwYIf9pEfkqKAI6RMwvAfhrAH4VwH8F4KdLKYf69F8Cm1hfA3HAAxXv/wrgVES+BtLoPpZatQjgrjAthqnhw7p9nTfXcFYQFoU3cZvRnwHb14D9/UPlULB/wMzo8od44/Z3+fCowMUy15s8zvkwXL9hMJyR7hyWBWlGeG08rWOC9e0Dlhwz9dRUkpHi/Pc44wMSZ8D2DUI+ZgekZYbygD9ONeNmwFl/vSCsGODGUxpjhkVBWAOHyZlmD8SuYLhbiE0DHOh1gynjOlRnuSmIy4LUFIRlYYCr5zMb/vwwY37zOs/F/AN+ZqkLK0rNwj0z/UM/Z/4BWUTZAsmVKZiGdUaaFfh1we6VGrgjMNzjsbcXnP8y3CH0kxu+T2o59jm1PB9pRnr1cFqQHRcZv+L5DeuMbLiojceEdOKMP2vPCUPpkUGkf5ARZ7xO2fG4JdbF/i6mwFgqmzo1wHjEYzwEez0Imsvb+y8u+N6p4ffjCSZWlRS+d3aYrptkwK84Cjks6v52mK7l5k1eHz3w/ZtLngPJmCr22AFXXyhQI+CP8pTItM/q/Tav5qLrgu3rPEdhAexfLfVYbpMJybwu2zcKF+iW96OKgLsWhAV7hN2zmmQU7v9wh+dvuJvpply3OLu95+KMScK4BsKKyQMTLwaf2AHNNe+nbOr9vQJSB/T3+YxkWwi9dQW6ZwI2rVERCGsek1/Xa1ITs/Yp6HrwkrYD0eQ7fX2/bd8ziKyU8i98ix/9U9/i9/8tAP/Wb/D6LwD4Pb/B6wOAf/673jHhw4BM+KcokJ1iGTyUZ8MwLkBBnPAhNlsGlaL5UEhkwx0FCJY3OQqZVWEpaC6YfWUHbN4ku6rI7TyZvC6wN4rGkoVQ0OLdgssvktbaPbbYz/iwo+6fuQH6e3UfFRdLAPAnBegyYkcowB9nXHxRIawS3AWFaPZ9h7DmInBgvw13iUEDQH+fbslxzkDWXLF6SfWhdjcC32SoBDbDtSDvuIAc4AqzrxWaYzUYlkD7TOCPef78ScH8m4Ld62XS9rgtF7tsC/KS7++P+XdpkWCuTBVM0oBQDdQbjVljuM/rmFuyiVKr6KF2LUinAWnv2PBuM6RqhuL89lZITYHZqan/UhQDiqQa3FpBcRnj3UroiAJ/VNBcsvIKywKV5LbK0AwQuc2IXk1Bt1iOPw5LVo03nyEhQY/8zPG0oDmvi3GboVKFCFvuY3MpCAvep4cKHIULcXYCu6sVnC3ISoAaLKEK+sOAjbqwt8+p7aHdTGUxPnZkdC3piC2J2qs8T4hJ1z4iGYvuRki4kNpDcwygaZmwe5XamPG01JHiJBlAF1z/QIYaBWYrTHhqbwpgT8/sajXvWSVu3uI5D0tCaXGeb/uWmbCpikB/5zbgqCi8fxXPr9kpBqvah2JlW+CPCUmbzHOatbCXs+f9HxY8ZSv9ksSWBd+1Dcz3y/bb3YP5Hd9UOEAzBaFmXAeoTO/VBIvlpsBdK4wnvMniUSQ9dR5hnllWKW1G94GpsAwzJKBmfKvbCqQ09T0WuVJVmaH6O4nDohouKOMpg5raa+wfHjLLymqZJXh1y1CCFI4CBh8u9GwGq1QfGlcDkwEwaoRlpdVqYvHxOEPtFFX+gYLBuOSDuX2DD8NhcmIxBf1rnAcvWSr0wsYrClDaDHOlWZ0tuFhnDeSO+9I8r7TeUbD5AWpIzLUgtsD+dWqGzKVBPIlwH7DP1d/LfG2d0Dw21AVpIOuM+dcNhjt1aNal4XH3HHk7+4bhzPudRrzvObtmUJNgMdsCe63gTxKb+4sqpLWkV6tBIa7YUM4GSEsGFr0no0uSsLp1ZJ3tO0FpE/ROIzpm/maj4M840Ct11BSNdzIpxUueT73TGF8NDHy6oH/IRa95Tg1I7jL7cPcT2udko/UPOOZaXxtCug8ouPSnwhHEtsA9JskjLvh5aiSLLrcZ7kJj99kAtdMwl4b3xDXPsd4pXruR1y6dBjTvuYkgcRAlXv0gdULZAum+pz3RiqMnUst7DgUcez1wyqvecrBZuO8hT121KFIYz3g+wzIjzgjrxXVEnGvqy7ygKMUqrsswN3o6n7mp2iYNiKeHmowK9loTIdAFKgLR3j77w8NAIk1Lq/+85/PsNV0Z4jKR0OEJvab0EgGe78Pq5ONsnzigMbXAeCcx664K6tKQapkrE6g0GaVLiB2HYR2mTKqqY4kzZlqqjRhPM9KMD104iVNmZnakrpaDgrgu4qyFManlYTK6J3UMbKxTLheJ0x4zb/Q8TzBXtAWRDPL1Lfcdqdq0txRbiieBoWiymQAAUhDnVPznJsOvWYHFZQZmVK7bc7K8issU6jUZ4SiheV6x/Yrp51W8zb5rUqZ6RYiq5eKSOwZUDsICxnsJ/jRT4d5wURzuJv4+eB7i3QC4jOEsT7qK3BRAFc6BUaiiTMKYh5HX3IECiWTsDfcY7FFp3dBkG6nayC4K8PdoDxKOqgC1uWVp5Rnt35kk1OumWWFpL4AqiCv+nRrVbb/IMwipgX2e9rFGc879U1WUiTZPAtm8ipVmLDBbzUAwSxjv00lYCrB/nRYow1nBeKfOCzKHCqs6DiRS5Es1ywxL7quq+pPcZqDqV/wdak1yx+TlAF2WQyJSMAl+6RCQpqrebHh+zF4QTuhEjlEBipCcZEyiSonCUQYGKPOE1BWEY1ZAuWUQL7rwZ4tY0QCKOkvVQkkB0GXkhl8ysnKlpVN9FgsDazGFE1ZBtCHbfDt8TlfK/aGCUNynw6jsEhUHCpoMdImBrdR7/SU2+T+pENknLsCgjsrNTYa7VPWBULQrWUWOXg112JEC7DWdX3/dkKLMDHYSMlbMVmwdZ1xhte6x4tTJK1tnY4Dz2PMtPIAi2L/Khy+tIhfOkdoTGCr8D/M+iimIaw46K0JbmFLnliBzETO9AEJ7mqKAcJSoYD9Qf02hHT+qHqLU953TUkN0mcp5vVPYvZHY8JRCOnC1xkkz0kMBoH2spiqNc+iryC7J1OzXO4XDPBEp4DU4VI8KFO0pwhoH/yxa3EilAWdajdRqM1vOf8+ucIja9PtAWUQ6B9xwvsh4h+e3rOLkUVVUXVirt5Vf3yrJJVZqtOWALmSq6P06T+ep1KogV7Fr6irZYs7KdDzJvK6KDec8TzxGobNDScz6DxBlmtfBdvX8cgFk8EuLhFSrVuw1RbFtnmBGv6YdvuoVB6bVoDHNwinA8a9y8Zbax0kLikhVoO4kNww6qa3Xf9DT0Li0Sqx0RyYCYgn3yqhgbgjLxqM6X6ZO4tRbDXvDAI9ZAppEpbytfmCuTOp+0wuUZwUuuQaPg2uzIdxmN4Q/9U19/z3f+zB2u1h6CeYu0wsORBJKvVfpGsHPKPW+zPWc8ZmWaX/CUUJ2eHnzYMBr8LK9yH43bJ+4AGN2HBCFLBhPKGxUI28++8jVBi1v6uZc4CtEFlaELVSdkw5VoC45yrbYjOEuaKg3KqRjqvP7+xmypW9Vbqvi3CvklrPsJQP6KfUb9txwQU7gQvuUtX2xBerKsHmvqyXHk5beaU3mXBZPU0nV02qltBl6Y7gY1wUFlj0WKsGpMpcCYNTVNaBWPHWaod5T3a9GRaHaFdXz3ddcxZRrY36WsH8tTZl8WkW6GNiMfESHXve8ukYX0PNrVLCPLfSWi7e90vQH6zXiOkE8Fy7YfKvzuKa3WbaFo4pDhbtuFKuXLBRImoL2GxzHkOZc4DnVszoKXxio53S4Poj/SuQ1PUyDLJY9HdVrZHvLKJIMNOca0muoPRMGtWNlSYo2M38JgtmHqpo3klIrUarQlpY39oLMNruR6l3G+0mC4sySA8WlTvCUJLA3DKR6oyloLEDznDR17KgjUaNCWnJIXVxHNE814BUufoTnUm/0ZOsimb0WfaNhNgruORHz+TuaqvIkFJPuNNwlA5vcGJqFZt6b4TQCipY5aqd5zRvea2HNEQvuAwv93DK4RKHdTZ3g2Ty28GeRz1Gt9lNT0JxrqA17Ou45A5P7wE5O4v5uZOWyoyt5sbV6CoJ4HGEuDJNFsLcazgLvt6ZW+ZmVJX9BaJUEwtEHjdvgX8DXfqvbpwHmk7HFGRfSgzJfCtA8I3Yba/8AmrCPPypTRjt5P0UQ5kgCs+PNLEKY6uB9hb3m/+tmt8JGaVfgaj8CI6uPeBxRBFh+E/QpqypnAMyoipCEsGAP4pDRSV0AXvwcqcp8kZoxL+Jk8VE0s1N/wuqADKX6faxWMoct197RAapIUtlCisy3gskaRG+rO27iMbLyYzBUdb7MwY5GAqd2mg17XWZP5XWc12rI0cqjOJpeyoZVY1lwMYHhAiUj4UcVhWyxRUZccUUujnAPBYeaEIpl5i9VtAhd0DypDgAZ1eqHi62YDHtZVe0BaM6F5ymyIT/BQQIUS2hN7xTGMwZjNdI9YbjzwmqhWWWVqSqi7irbDL8qwJwLrt2yajk4JkhdMNXIc9tc8L3shvBQXKdKvz38TZkWVek1JCoytJpb2LHYMrkNZ5cR1nUiZFem39k/ZCKFQrFt7jLh4sNMGk1mHodzEQVwV8JqIvD6+6MM3XPWkD/OrOQK78uDqzGA2pTnZFOWXgBmiYmSqqr8RMQgztlbPPQlZeRnxxVNNCUIcpcm54zcVFLEyAQsrRNnNAU1JUl5xh5gXGaOS5YK+a4SjH45QsuPC499CpF9n2ztc8VKpdwyg1Jb4agELjpc2zmHvuL77pmlMG+voAdy+SVyumRub3Ffd62qoJM3cpyXiUgw3g8MVtXqQnfM3ravA/qZ5SLgSL+FV9Q0mAIYQjnIXAzjkjt5gHXMM8uRt+vqM1ZhLrOl7YmMzIJPf7Fiz4a9HQBIXZ7oxN271T6+LgB6kFv4y5NBZrZqqizaZ+w9TL4KQpjssGgDoCWHx+S5lmbsrzQXt+aiwwO6Oscj7r+/FzB7n00C2ZppyNYB2mKFQDbdoZo4QGQHiq4k3C7UtYc2f5eWNv6EgeQAR80+0NO5TLWX1FxQlAjFylHqayoI7EY4+TCSQaUGWu2YjUy2MXGVkGZlgkP1ts4IMqTdAnR+Lp77ZHYAEv24iq2GlQAW75KduHuNY639CUdBT7Y6Bwip9uwkVC2R3DKiDos3TSVr86Ueu7viuZx6Gg2V/MUx8JfaMLfXtae0Z9WLUWP19u0SonoF98SgeddNcDL2hsSTg9Fq9WM7JDRqZCKgd4pV285wLEH9/QMNulSfu2IZuNyVqtZD/Fu9U0zkKhStPQ8nt/UYag/uYL+jqhO6KMA+szxntSfLi1XwnZ0Nv4vtezBw7HfD9okMMNlyoURV4eeGvZO0ogGfu9AwN5x7wSxXpoBzqASkALu36vhaQ4bWwTU4taW6Kme0z0hFtjcV6w18AJqntTH7rEVu2QNJHfskequrbkEQF/W1J44mjpeVkTUouCuNfOqha8aleg1zZeCeGv7enpYvaqeha0Z68XtpQVJcJtQzEttOC/Zy+vsMJqmhJ5c/IkNK77lo6Z6v2Y2CvVHUlthSvdhIHiimwD030yKnAmm9xfL/khiwN5+psBRum+R0KGAltH8tTz5T4hW6d/mealQIc8BdVubfIqF9xApFDYrsqnk1OyyAecoBVNllxEXtF9Q+2aHhvH81sRF96dA9kspKw9QoLopVQn8/QXnBeMoGeFEcm5BnGWZH3UlYJ84Qqr26uE7sAdQsNXWZGf6ejXO90WieKeqRei6AzVMD99RCBcFwBxNBIazydFzFsC+CLPDHtPPJhlYryhOSyw0HeinPe4dkDg4ZK3UaZOwK4lEixBbZbxxPObzNH5F8ojz7THlOgkNuMtrHGtdfjCgNSRvIpPuGdUb7lIjA7F3OqLHXakqOUCi41AOrsFxZb7r63umeYwzcJZlp1D0xqdM7jdQV+OPaB7MkXWTH49AVwh7vVMdrBbLKDs9Bz0QgO/ZnzHMGQJx4zsqJMvnovczt0wrmk7IVTLDSYSxuc15PQxDYjYI/i8iWLBpUHYPeKfYHkuBgs15q8z27XPUObESnhkaaKFTOq5pJp1nmgp5oV3Kw58gdFy24XBuwbKznjg6yuc1kXAng75JEkFsK1JTl37hzDXstSMtEdb0tVT9Tm88dRYsSMS3qBzomIh98GfkQw1Rn2jpvRPekhYYVm7vQrEriIk/nIHX812zJhgqrzIW1GkHy2Gs1llHZVtWkEDw/pC/rajJZmUaV3YRMHYMaBfP3qHfo75fJ22t4JWLxDdKRDxXXYcZNPGZV1JyTSn3Y8iwhLwjZlDpYzV4rMtHmiWK+VSZjT+EFIWWZXuOMEt4T/jRj8xk2qouADekahNIsk2mnCePpkfod2IK0juhfi6yERlZIcUF2YtFVrGpvoTm9V8izDIkV8kvgALNlbdTPWLFJqZm/LZOLgfa47TdlmdhnvAd4nv1ZJYjcicCCjsL+LJLSXV2zoQv61wKaR2aC6A4izCK16rCFfcjx1jNsGu7lDoSC6kIg/P1imaRIrCashoSVuMiwN2TA5Qr5IfK+BA6Bm1WOvtGcEFr7ihOzzRSkFQkTek9dVWqreDMdEkBCuGmWX6rQ8tMezCdlK1xwisvQ1wZhSZolXqA5HspxVV1q7abe7G0iM0YB/lU/zeUwOzXZyCDTU6vYWuW8wQfO3+GQMgkAdMH2zTw5GcvhKjRkKYnnw4os7BWNZAdJUBBTkFYR9krDrwpKndHiX/XM6hQx9IOgE6gLoynI68BAs0ycIFmbsXp3O3AsnYapmV7qmOiwTojzypiqVujNOZlpEPZ+iuIIhHASJzZUUcTcc1sZYHWBjCdxmv+RFonncKMR15EuydU8VCIxdfYCBP4kobiCmx/mWN7ckngxe1cDtmD7VqYuog7WksR+2gG+G0+4AKte30IhAJvokbBUmnHRE0+BaDnxJG90ZJ7pngHzwGyzW1LLUS9/qSQBgEp2qAqj9gqlIxmiGCYhpclklmUBKjPLn0WktgYXwUQ4ObD3UGHJwz6WNk9PcbFVo+IK4n0/eYwdXAX8aeIwsMhAf2jqH8gc8TjeQlHdYUBarTpq5X2ouFCP8RCw7TWp6lBMAvavVUafK1MVerjmxZE6fRChxgUnS+aGQS+cpCpirv5wfZ1y6jBR3w+MwmILRNcejirIhr29kgif8rwUztyZU3cGjVtK/SxVJh+DvVTa/0utJj5m9fJpBfP9sB2kIVk4pdFl5LsjH/bKudcbg7RMSKvIKuKLW45ZHTXGszTNoBAvnL3uAHdBFo5EIXsJ1bakQgriSd8tFrBXFR5rM/SxJ0tslqFdIpRgCj/HULuie87gUEvPmSCPLMLDEbjHZkN2BbolVKGaxAepPsBpRlZZqUOozEbDLOkLoyvrLC3r77yAQes9+wW0/gewICSUVxHNuw7jnQxZB8jJiLSIVK8fxZo5FqDNaJ4YmEsDtfZAFM5nD0Im10gnBOUSME9IrwxAEVqXrAPFi3sFtBwrnU4j1q9eI68iTu/fIC0iuvs7oAD7tyJUyyFRzdkedqNg7gwoTcbqlRuoRUDzTHMezCoyMILZLWzG0evXzJxtFUMeJaCri3yg5Xy3GniMxxFpXgNmEgz3EqdtKi5W5kYDLkOdjehfo8bjwLiTkfCNfW5roM6Vqizs82Rm0Iemf2m5P+6K0xrzjPdC/4DXqRwFmKs6TKzNaI8HVh/zxJHSawZkvfbwr3mOCe41MGdzPpxGBmMB5P7A63zMwOSWvlLWATkdOZa46qrKKwMrwvWIfBogwuCFZUCxvJ9wZwRmCc3ZHvFORHd3B1kGpNMA+9yiRIGsPYfludpgN5lzmeq01LwOyMeh6nQKxnscPoeWCZIETsSEzmRhRgbq8axSvitCUQyFnbzotVo95swlcRn+LAJJAYb7fhhE19lPacq/1e2TF2BA/B+R2aXeK5SsIL2G7ipbqTbBZVSwzy1i0HDfbICOkwVFM7sHwKl4hR5HcUGYZf51QxpzFyfrcL1jFpwtmTuwGWIT8GGLvGCTOHmSD+yF4bhfl2AuDeE2ADnWB+JunaEuQB4MyiIhDaSJlkprLZGMKKm9IffUsnq7G2BsQslkwJXDVExTuACpAtiMtOKUx7jge4jKDJKHIDtPUJpz4A8NY70hjRajngZbuSvcEgAALtynEekug3sJevq5uIyyrpWeKYhLTq1MiRSk0VMZHiLHJec6iKooNmRLUPB7S73KwM9XiiOex9c9MCrOO7EU1U3jioGa6ReUdZhg0OIy9LlBPAuIUZPiqgoJATvSf81GoWwtqceViquaiFyp8GpgoCjzGnwyq1Z3wVk1EzGhSdTnuMxrWzCRBcY3RizeqUyojr2kA+U5LZhQFK8QRgM9C1BXZoKiZB5IaRbAzT3kyJMqfxyw+IqZpo6mOsI6jxoyiwh7uqOaJ47X+NCHOszVSUIIaa+56M8T1KXjaIArDVFAyfwd88zy/F05iKmJCIBy7dB+w/G4Bu6z6DyxNMVkPme6QJY1mA6a81yqNsnMOUIjPOAEVyTCa+XA6BTq3DBwICB6w2CkqiATYHB3CW7GAHnYUn55y+NBf/Sdvr7ftk9egKmQhO7ZC4kncVIkZ6+5yCmOIVYjrVTwtOUkyQOr5YmbxGL6xiC7jHQcYa/UNMd9ahJ27EPE+/4W89YF6sqiRIV05skC2soED4QTPjSia9ACoK74cCjDZnwxpQrGCgdO3XBImTKkmMqoJkEZ2sRsVReY5wYx6Gn4GQBCRjvNffJcBGEK9RYNF/3DPHvxUhk4GXHHaZXiuajoUSDXFrNvsiILq8yG+2AmbQl0AUzmQmIqlblOiMReo4Q69MorYJ5QvEYaNUoSBppMe/cSFHKq7LUiSDcW5oqjlidGVBRcnc/r6FwuXHmWJgpuORuBqOADCQKiCLdAcb8kCamtSRC95vC1vcb+lcRAVOrguQIUx+pGD4LsNcrOEIKpUGWp95q90nDX1YPOyxToSgaw52fqvZpYTUUXyLXF/kFB8y7N55RXE9236ALVVOrvoxY5kVYMr2rmLkxMrg38847XFwB6jf0rBYgKstVAX5v+RVByFYJeW2pWbgwXdVMpxZ73jh9YNegLBiNOWKXYNAUG3GHnEE4i4qinKvoA9UEKhgc8v/ra8LO3TISwiCg9k6bD5NXlO7T0n/RgkYkPinDstSq3lWAS6EvDZ3RH4XRzxUMPJ5HPRpeBrcHRL1mULEiR+6xG0qt3o/terkSfiO2TF2AEQJNYFXjFzN5wJrdsDScgdhlyZQmXjYJ8WNB3XCjjXc/55qognwQytHSGP6u9io5ltnm3BYRzVtS1gdzwgdE3lXG1rToRnWkRAnBxWwSojeZo4qrIN1uBPhpRnjdQLhFaunR1qh9QVnGiFqdVhNnoSQODPYNGSWyKplFzcqMlHq08CG0VQF8Y6J1C875lI7kA2OnJ/aC0mcOuIh/atEi0OxlodlnajP3Dumg6LoDN+5bMuKEubnVKpeq56KhBoRThQlAFc4eplhgUzKOG3ll9nbY4WkiTEJ90kBoIyGziYn7A8vWg4OYB+Y4HLqtAtOqKoIBS3y9lxfPwtEEeNQPRccDsGwbSVaZgVMz2Z9Qj6WcOpd4f7lxPCUW8w/HFEPakUABzYUheqNVLnBekM8/z9oi2xNlrNE/JAjxY0aBX6B5TP5PmGeNJNaKstGf13KH90CLXzysCrP6HBrP3q/jyhUmJpc2Y3d9ysbYZ7qlhkDKHqpGQoWojR3A3CeV0xPzrerqO3SNeP31ugZa9w7KiPVKpOhQkQVkFYG+m67H8skHZ10mU1xQvSqQQVQIr7nwUmbysmHDBEyqGgAnZ4waXP5IQ10QFDkSO5DXUlUG5aCCrSoCpmrS4qvZLTZl6k8WSHSfnDXtrCti8USjy3TiEO2STogDdp0r+3/L2yQswmtiD3jEDSm0BBmaUs/fY64CwcY+KQRfHKXjmusI5dRGCYQ8hHUe+VlAXIOK8uSnAqLD5gVhH5lamjAH0sacnUgF0NQCEAhAEac+HsHl9AwBw9/bwdxK0IXZcsiAPBs25grvXA7ME0/HByLFm+bMMNAyialDALNLKxhXCMbUc11vSqu0jjg9Odz2yIw1UjVTH06ySizJsJQmYwqAElvbDnWqNUhfvXMfoQmgymI/4sLr33VR15WqNk5YR2lYvOEjVJxRCkrpAfW6L3Bbow/z1yDHQZRGnhQbgue2OBpR1hF14mjwmgcjB26rCjjtm9O54oMguaMg80HXXVlgxKuxfT2hmgaJSgNd8VxvjHVXn2Rb4u3GabHmA1pCpWC9thQRXiSxDVV0cFCdiTpBsVBjvJMR77EtMuqnTgvk3672laC3Pc8vFfngYWH3ZjHwccPMDCftXEnRfRyx7BdPx3A97B7S8P/0bIyBAM/esGpeBnnQd7ZJECkpvMNyr4uAC9A/IcjNvbSE2IXkFVauXQy8NlZUmi0AISoDtFz3UMrCPV/3Kuvfp2pBbkiLE1r7lzvKe7dWtB+Cg6ARxECB3iXR/mye7pjxLTAJcve+qgzKaTCacZpUpnqhEbm51a7khC1RcZYk62jvFlwWRfdrk/wRtBdVplY3Vw5ZWEbs36CslsboMLwP1IVIQ7geOUt4RTlNXtC6RmmFNLrIHFbtLE1VZtXFSDONAQ3ZsTJtZQHk4sJopJB/oGReErqHVStsENkKFC2/ZMIMfHiSIECJRio1JN+ffllVg41QX5BkXPNMGYJawXvZ8eDVtV3KXEV8b0L8eYJo4NbClmjGGdV3E28QAbJkhloPQD2B23zEjhuNCnRZcdKRCNWZPevGh50IGFfsMOQpw7HmBauBSV8yUG8vGddN6KJdgXELqa0bcMfOVUQGzBGsSlE2YdePE5ip7U3sjpF2nV0aURULbhNsMPxAOlCvLyi9x0c1ZoJYedhagHFlgequmEcl5nm7FnkWqnTwDjRyo55bXQQ7eWVIIQylayRddIdXDeQkH6I9q/yLULkHdzvvJq8hK2xzuPd7PxRaaRLqqmk8Ca+kFVopAP3HV7aHCXUnRMsawWm1shL8bUAoX5zTPGB8E3mNrj3gceT2uSemSBz3yKjIhAKAawrvKsNpdrnroNqFpA/uVlYjSP2Cw17MA1UX2DmPVedVjBsD7tzIByfiqPaCOvTp1XbVReyIQEAZwqHIbpHSuwR3VVqZMRBQI2HsMArmx0z2eTcHM+Ze77nxawXwCtihov+740N7oiZkjSSbaqATSKvPNLQZbkvy6BmCptNK0sSihYuhgJtp8aFE2dtKRyLMGdulRbMHslS1hmbcX6GYe8aqBayLKOmB5vCfUEzXyOuLyYg7VJGw3LUQXjHuLduZRXIZpIqAKxk2DHBWzcFXgdxbdSQ/7YcPPNhmze1uoJiGet9Au4eK9Iz5cFw7zezuoLsJ2EXbpkZ52sMcjNSK2NkKTABvLBWxvgFFBX9ZGchF0HyigZsuoxqEYKkwjFepCtaYBCGvNIvRWw93tCUmNGm4WoGyGmwXo5xZyb4DojN22ge4iht4h3ziEnUV7NEAMf9fc76GOPJCBfe+QR42b6xlp3yN1GvpkZAU4aNgmohTg+tmCsGEUtOsBqkloHu6Qjz26kx64oKdZjhrpwxmaLqAcBTLCDsanUSCDpn5IF5IrdMH6S4RT9TML/ajB4isWGDTcU0tYrFLPm3OyyPIs8Z5KB18ssBoWYP8DHnGdqHc59gzqe81F8dqQepsE5nED0QVuOaLogva0B7qEsbeEpi4cGWC9hmno+ZaCAtqEdNVAomDzZAEzjyjXtRdSk4WSFXs5NqMf6nOhCmadB3oN2xLiNU2CeeqgNSuOm6sZmtZj7C3mp3tAgNV6D3XkITcW+dqh3LD3l9tKr6/zaOTGoMwp6j0svs0TA/3cAjsDfWFoOmvplrD4ugL2tX8n1VX6ysC+22L1q5Y9zfse829oVnd7DXPM+whzMkbRk0Aw+0C/1Cb/pwHmk7JpNhbDGemP87eZ3XIxZoXQfchmNuKtDYo46lCyO2g82MOQgRmgKDATqvNE1FCZXF1EPg2Ife0bRA2xnMA4job29ZWZkzIxaHVl6JgcNLTJyDeOWVgWOJvgVh5h47iw7DSUpkOsbSN0k6B1Rng4oiRBs/Dotw0X10WENgl6TbpzWUZolWEbLg62whTORWaR9ZiggMU3+fCqZQDaRCaQJftm97nICiZKbbyC9NFMqOlwblEb0xBgfbyHftAjJ0FzjzOQc1IwNmHRjSivDEgjg6aqsKU2Ge4Oh+6EwSAPBq0LsPa2f1WykKo9aFaCBVjc2cPahDhqSBfhn3Wk4VbmIASE0XRBzgLdJPRXLcz9HnHUmK165DWZZNqSnIAgwLYy1eqcnRcrs5vPkR2W1iRYbD9PiyB/NyDcCdQlNRwLoAa5DVamjhtYMIEoTaYhqWdPqeTKPFsG2A2/1y3p3/Es8DzpjLIK8INBsxyR9hb2lT3KIsG2kZXIqKFPRuQrB+1IEca9gfCQztAnHu1yRLMe0M49tEsw9f4KvUXpElwXIMJ9NTpDNxH+vEW85+F7C3s8QpmMlNUL/yZstx1cSy2aGmiXLyOh3TxPk7izzBMwcCDcQXw53osolk38VMc/mI1COgsIa0w+a9gZYEahsj9KHBXtFTAq7D4bke4EsjqTYrDVBc16pA2Oydh/LkCrl0PrEnzKIvvkbIVlt5lFZFew/Xxkv6VNU0NxOKvisJaqXzGZXkao1NHaxylVq0AMPLG3oejim2cMSLaNEJ1xevcG7dzDX7bTnJKuDcCooFSBunTYX3coRTjvpRATDpcNqbhBc3BY1IRt2sruqRl2iZU2nQWxsq1KYCYsigunSEGsrCypNObdroXfOfgnHbynjUhMpCOrKBBLBfX291AfYWxiYDUVZkg8d8pUTPsAL1kKU8VxEVCmQmUKwLFHzoK2CQgbB6N5rkoBxusGWmqFUJlYyZOSG7bMjEskg0xMhg8GpQhSb9AsPNLOsr8xj0iDwfxXG1iTMGwb2C6i7Cwwj2SF1fOlTIazEak2onMVtJYC5KAJgyr+X+k8CTlRoa2jXxOEO4E9q0B/uTxPULXasAsPswhMUhKDSEnUcEikBYtExX5BryFrD9cFqIvKGltSZ2Ov6aklSWDaiPFu5LnVZFI164GVoxSo2v9IsTIkk7AZfvC7unQ89iOPNBo0RyPp60kQrhpom5CSghLSwZXOyFEhPW95bwqQoua9UoB+55Cr8Fg53g+iao8jKcTe8t72Gqk3vB89HQno9spRCsollJEWMaXCYcUUqDvj5EMnAdQTnfN6+TvsZfYPOfdGXVuKpB17ggeRb6nnROYRpg2ws4AcNMLOEnZNCuVsJBOxi4QJX9Ka873swYjIj4tIEpE/+cJrf0xEviwiXxORjzVOXkS29d83RaQXkV8Ukb8nIn9HRL7wm9m3T2CAqT2OA8WzV1TZAxCVoStjLBwfAg4A1IZp1YzAV1X2QAGcBNIaRWU0z8jeUoOCzANmnUfuDQZv0bhAKuWo4O706FxAe6fH8WLPAVTCGTPKJmiboW01eAwCtaFOISZFzYAUqLNxmp0CVeA/mCP1hvB9oCU+ITTNh39vkEcDO+Pnape48LiE9v4eOSgor+A/mJOkUCu6OKPtep4lpKihLfscDCR1MRF6cqGpDLJIzYnShRBiIQxGSq5gDAb9YOlSkAXurEfXBsxOemQIg0pHvU5JCtZFqCbWCjCjmXuYWcD+fIZxsDDzgK6pi7gUlAzoNmL3gwxm6tIiJ8Hs3ha2iwyINVOez0Ze/yzwvYV2rLTiQFhwHA2K11CK1cGk66kuwBd/oLoXKFB3ct4wqEdFIaVQjwNUdpxXaJ4aVivHkT52s1qFuQzbRvjeIp960nTB/kP/WoSuUJQcqmrD45VFwKLjccRUK9/BINw0U4/OvrFF4xh4mwuFxWIgrb1WrqWwl6XmAf6mQU4KIWgYzUy/XDQUUyZBKUC6qMnBjYVtI/JgoGe3gRqFyc/Un5ECBEKo4dFssmASX/UvXqEEXl/MOPgLywh15GFcJJRVgHQWAMu+IUbSsbE1JDrM0vSFAohnwB/eYnUiM5qqlsz7DoNCuxoRR10DrMLyZM+A+hIHjn2vIDIR0QD+HQB/4yOv/QUA/yyAHwbwL4jID3+Xb/12KeVHSym/D8BfAfBvfPd790kMMJo8/jQYNk5PPNkj1xa4dEijhrnfM0vXBd3dHWZfcUjzhOZOD33iAUs3W33iaYVyHNC80yCFOja2ScDZgDunG6S/dYLmeMB+06CzcRJzdq3HGDX6yxZXuw7dUV8b9Oz9hGfUNKDJxMRPPbo3b+D3FrN1z+z0wqFZj4BXZFideMxP9mhcgF2NCA/YFC9eQZ430KtA1bONGHauBkWKJa1hExj3BgZIl+Du7ZE3Fuk0UANkCuLOIA4GIkB7NJDRFjTSxiKdeagmofuAi4q51zNIAhMZQR70aOYe47Zh8Kmso+Vs4O8o0oa1zWhWI0pU0A2zy8VyQCnA/KhHqPugZwHGcQEdRvbDupZEB/X1GXQXcfPeCmkZES9bzBuPMBhoU7PlncHmhpWjuTSwbcRiTmgHGdAu8XgzkBIXJQo0wT5Wk+FOBrTLkeMRVCGWP7CnJKdcvMJVA0AYIJoE/4qHW3iYuYc86BkUk2B2vIffOuhnDs3cwz7YI48Guo3Q84DUG7SnPayNTBBqf2uxHNCPFrII8DuLUtg3nJ3uoXRBGAwaGzF6A7vwsL//ajrf+cbBP+8AAOvXrpEGw+pMZ4Stwzg44MOW/R+v0dX+l6wDbi7mMPd6jOcdF/hrx4FkzxtCkXM2yt3cI3gDdzKQ9l0TKjzs6bqQBO1TVh2mC7ALz2TlyiKPGkaTHCC28D2r2NJe6gmeVo7VNVyGOx4IJ65JWHCzAH23R9MFnJxtYFxE3Fm4kwH9RYeSFV45uobojNYGVvq/O3ow/ysA/xmApy+89hMAvlZK+XopxQP4GQB//KN/KCJvicjPicjPi8i/+W0+YwXg8jezc5+8ACMFzWqEW3jk1/sJe1d3RpQ1bVDCzlL1bbj4jb93D9Uk+L1F8gruQwYc40iH1V3E8EqAMpkiSQFcG5EhuPkh9jlK0OiDwWI5sG+xb9APDs3RiFwE42Dh9xZuFnD02jVFYMCUTWubyN6JCiEY9k1mCSeLPe3mZyO0TZg3HloVxJ1Dt+aDe3T/BvKgx2LRQ1SBVgXYGMJdNbt0NmK+GtiruTugbC3CyDHKsjUoSeBmPFYA7OVUkZuojOa0J4buNfrX43TuUoXpclRTVp+immbnNKsRIWjMncd20yIlhf3gUAqw6gaoK4v1ag+8PUeIGvG8RWMj2hkrE9dSxOdc5Puc7mFNwnLVQ31hw4rDFu53x2ti2wijE+4cb1FMwWJJy53mC9fIScEqZr9u4bGYD2gXHkcPb4AiSN+cU/u09mQI1t5OSsyEs9fQWzP1ikqFKvXKo1mMyDsL7TLc0iMnQRwscuTQM8lVPV7o/5Wi4v7rAuNYzR3Ei/2u4f239CiFFaH/6grt3JMsoQrW9zZYdiNcE6BdQsoKjYtQqqBzAdeXcyznPPbZvS1SUNCK52p9soXWGc0ji9QbxCOec7cesewGkkIOjX1DJp173/G4pWD55jXU2qOxhHuPFj2Mi/DPO6i7AxfTNmM+G1GKQNkM/4MMALlSj20XqdEJtcptIqt7ndHc3QMQpDf7Cb7kCeczHgYD7RLUheNzORrEnUOMCmMw6JqAZjWicRF6FjBf90hFoekCnp8veU7sy2ORfRcQ2R0R+YUXvn7qW76nyEMA/xMA/+eP/OghgPde+P/79bWPbv8egL9USvlxAI8/8rPPVojsbQD/KoB/97s64Lp98gJMqgtcAUyFoFwXkKsq2L81AIoz6vOg0W9aWMvs/vDw+tdGSGWSJk/Mm9CAhXtGiMWahG3foDka0F91wF5j8JYwi8tIXsPvHVoX4HsL10S4WUCKGj5ojpeNCmnUmM9GxJ3D4Kl6dy5CAKgm4WI7g7vTI9ceRSoK274BdMGspX2Grs3vEDVKVthcd8CCAWI+G6GbSOgtKeLRlpTU4vVEfdUu0QHggK2DUMwhQwVAFfWNgVmPKIl9ktQbBnCboav1h3Os5JSwktMmw0eDbu7RX7YM+gJksKJKWRBf5Xk0p8zUASDuLFRtxJbCKmm/abEfHG6uZjA6c/HTrA6Uzbi84qJqTcKmb2DmATEp3FzMEWow3HuHrh5XrllszoJ05YCHA7DXyElguoAc2WeLnkEGe032mypQUqhMB5CuGgZkmyEqswL7+hzoNZQu1R5GCG8W1OSHx9QuRvievSX9+Q2b8lng9xYiXODHyxb54cAqVAh3KVWwGx3G3iJetghBQ6kMv3OIWbFqKqRha1WQrx0uni+Qrx36wSF4g/hWD5gMu/BIidculco+A7A8ZkAXlzHeDwxgmtfEthGb6459swJoldGe7eu9wuCcMu8RFPYKU1JTEhJHzd7doDAOFsOWPamUFbomwM09XMNKSKo7g2lJ1RddYV2XYW3ilNCe773fNLyH6vlVJuN4vsf5dg4/GORRY7YYEbJ+eevOx69gnpdS/uALX3/527zr/wHAv1ZK+ehktN8I2/uN6qM/AuCv1u//44/87ACRfRbAvwLg2+3Ht9w+cQFGTGY/oFpWuCbSw8klekoZPtDhTkR7PEBZBouDwC4GDdcF2pVftVCWvlfaUO8QHo5II/sLjY1kZvUKsvYIo8HoDVlflVEzc4FZWxb48xYA0O8ayP0B2iU0yxE3lzPCeAK4sx4hagxbh7y1DCIgvt2sR1w8WyJ9Yw4397i6maFsLa6uZtAmY3/ToVsOOL2zgZt5DL3D5qZD0wQM3sKahNlRD79zyFGhO+qxPtuSdVbtQ3JSuHO6Qc6COGrEoNHOPWLQKKNGWSSUTHGfdXGazqk0ewXtasSwdxCVMWwblCIIo8GT5yvst6Rza8XG9eXVHCIcXWs7VovxvMWwd9h/uIBbenhvkL3GOFrE8xYogmHngEsH7w1aF2FmrCoPFdv+vz3FzfUMIWjEXR1NXW11ktcYBothsPA7h5QFwRsMo8XsPrN8WYTaXyA7yveWkBpQmV7AuHNkpB2PFBF2iVDTzjApUQVhTUZfjgK19lBLjxhZOR/saYZ9pQRvzeQhd0hqTJPYK/jlFexqRFMFlX5nEQaDfrQIQcO1EWrpoVTBzTtHgCq4eLZEyQrXGzK6xmCgj2ln1NzdI0WyE9uZB/YGsbdkJ0aNy4s5VuseRifsewcfDLrFiPZ4YHXRBfhgMFbYbRwsNj2vWwiEtrpaNYagcXS2ZcJWdV663uvKFPZEFYOPqjKBFBWuL2cMQhVC1acjUk/Ch9EJOSjgG3NgHtFftehOCMWJZrIVv75gQtI7xN5iOzYMbkGjWY8YBkuG3MvYysthkYnIT9eq4hdF5BUAfxDAz4jIOwD+JIC/KCJ/AqxYXnvhT18F8OG33rvvuP0sgH/sY/zeP7B98gKMFJRHHbHnxMVIKqSEJkObhFwE7WmPFBWNEr1h07sIclBIUcPNqLh2LtaMkRmbKGZOShf0g8M4GuhTNl9zYKM47Cy65YAcNZYNs2ljqntyUFC6IF069gnqQ2fbyJu+7rftItrTHqNn9heTgt9Z9ivuefidY+VlM3LUk3nhsGfvJUWNbubJFsq0aukHi7Fmdst1Dz9a9IODddSNQDBBbOlpN0EZuYoVxeRK+y1QumC4aUgZrb/vn8zgRwNXoRVkYLttYSzps8YlrBbMwpXOyEFhuexhdEb4cAZRBc29PVbrPVCFknE8NJQpjMReExq5OxAmkYzlsifBoEJ04Yf66bESm8nicwld46FM4jV9r8P8iJ+dzht0NZCjUOtB6BJIezKzZp1H+mCG8oCLmNKs9Epm5Ws/dIh7mksqU6clzhMZfVWsmq8d4p7XsBQBLhz0Nzv4wcDd7aF15pfNXNCbAGcSxjdHVou1R6RdhusCxkdz+KcdKwwFJiPH7F9gr1GiQOuM4dGc0F9lxh2qKFP7ckUXuIWHNZUUYhlovGewHDYNk4b6jPXXrELd0yqGfaEysZbBI2UFEUyBEMAUHFK9pm1Xz/mSkJ/UL2MT8lg96jLfM/UGbuUJ5yVyxrXHpFeaKqPq51deGSZ2G1SBVhnLjo7SKSk0TUBn/uGyiiml/IVaVfxoKeXDUspbpZQ3SylvAvhPAfwvSyn/DwA/D+DztcfiAPwkGCQ+uv3t+jMA+FPf5qP/KIC3P85hfnT7xAWYUgT5iI2/nNhMRhHITlNZbxJCb1DADBVCfYieRcSgSYU9b1gB7Q0zxJo5hsGgREU8+aZBuGwQR1MfBCrplRRi6prU5yM3YAwGOSs2gAtwst4CpqBriK+vj/foGg9jE8bramiYhYGpwkBGZ8xWA06PtrW/UeAHg9lxzx7JcsTZnRu4LiDEStEt1LzEoOE3DkoXLOYDkKqhZKWYFlTWkipI5w2u9y1w5GGaiBw0ojcUV3oF1xA2AkB9xqioFymAOh5Rzum9lSoVFMBEodYVWumvW4w7h/XJDj5o9lxe3UJJQRgNFg1ntCjFEQdiqZPBpcPq4Q3Sntln8ewpAICZRThDB+j1ao+SFU5WZAs1NqIk/m6uMBleHab7BbOEzka0jjoQpQn3NW1gg7lSg+X+MGmS8tZi3DbIlw4pK8RXBzahrw20TZjNRjpU68zMO/NzZGMIK1ZnZ/fD18hbC60yjCadWlTG/tEC200LHwlbGpewmI0THJUixxPonucJUmg/XwB9rcnMmgcKItceJz/0nD2PoOBHg7bzE8xmFgFt9eXKjzukUWMcDfsnQWF9ukUJ7Bfd3HSs7jct0ud6rI93QBE4FzFfDyj12pfqdpBHjfHxDACZdiEYKJOQo6D/5pJQYnUciDv2q/zeYnbSw80CciIaobvIxKDX8M87iM4In2PPcXFnj/Cc6MChn7VYDgjP2okWvXQjUlFwc4/ypMWqMvJe1vbbaRVTSokA/mWQWfb3Afy1UsqXfoNf/XMAflpEfh7A+iM/O/Rg/h6A/y2AP/ub2Rfzm/mj381bKYJ2VWmpL1zRfOynnytT2KcB0K0GKsi3lurzJnChzAr6aIRS1JZkX+mVINziViMOflKh9iHChtUDsuDucoMxGDgdkSKpyfPFiHnj8eTZCmoeEJOGf3eB4STAtKQ8xy6iaT1yVuhcwM2+RfAGTUvIq2to67Fa9bj65honZ9f44KZF1wRi51EBJkFUZp9o1+LB6TWeXrGxeX0xR7MesL8h/CcqIwZasuegYXaKjWipQUez6jMmITYJ4zeXkHsDlBR4r6BXYWKS+YsW9l6PcU8osmkCcmbmfW+9wftfuo8Hv+caN7MWq8WAy4s55LxB+/kL9I/n+PwPfYCvP7kDqwgtrbsBIkA/WjiTsHENRApmx3vESKijsx57b5Ej9UGLRY9Ug33MCnk0WDQjLhQhk9m6x7zxeL53CJEUXdVGXO46qBoEx+uWPR9V0KwHaJWx2zdIXmF90uP6YkFNh02QExIGCPck6NrbGX0VaVpCtt1iRIwaQWf2oh7NoY49ts/mMGsPP1okm8gQiwrtvT2iNwijgXEJYTBwiz1GxQW5bQPUrGCDGaulIli4kaLCt3aTvmXWeoSgSQ0PmgJUKVi0Hs/Ol5gtRpTHLdTnewyjRV4mLI969lYWA6TXfGZcQl/hvOW6Z9KUBE4nlMIRCyio0HSBv3Hsw7W0sdEmwe8cdWGLQFHxqzvkryyRXu+RvKIQUgr6iw6yGAnjGfazStDoswCLSH+1LHS3qBWJOR0Qe4vl8R6jN5i5gNUPPEVMGru5g1YZKQvurjd4CmDd9vDpJfdgvodbKeV//pH//3UAf/07/M03APzhF176t+vr7wDoXsZ+/Y5UMCLyjoj8co2Qv1BfOxGR/1pEvlr/PX7h9//1Khj6soj8My+8/gfq+3xNRP59EfmOxHURig5zJjxgTKLob+aRg8bYW7gmkCcfNPrrlk3EGVk0pQhMk9hf+IANTNHVdh4MLsYlpKD58Os04b5iM3LNmkLWCL3B034BaxP6yxapZvJ55INTCscb60rDvbmaTTDXsHO42nXIRUi5jAxyzz9cT5CAuTNg5930YMeksJiPFGt+OMP1xRxpTwGc7wlTrI73GLcNitcoz5tKSea8EDcLKK+zRyNSEM5bNF1AeDwjlJIFuEsmmtYZ+rmDNlxgjabg8qCc1hUqUSrD/NIcIWnYV3d4crNktprYPM/HnuQGBTzbLYAi2Hg6E/TeYt9zcWhtgFp69mz2btKr7HyD3a7lojdYbLd8buJgoSXDPrYYgkW3GNHZAHdwM+iYHcek0XZkQx1IABgV3NJDt4SQUlasyFzG6C10U+noWRC3JHaUAkJMReAPwcUUqK/P4Dq6BExEEhuhAl0NpGE/QRsGEVVHCkdvkCO1RYf72ic9NeJ31y1C1NQrFcC6iMt+hjhqnK22CJWafr3psJiPuLyaw7qIWceFe4xsdPc7h3I2ktkHwC4YgGwbKcA8IQusnfmpL7XbskqNe4ubvkXaGygphLKqaFYsCQamQo1d66GbBHvM98PIyjU8JGW8qRDdYdvfdPU5FZJqFn4iCkRvqPtpIqyLGDYNE8KG3n2+t1Pw2HuLfrA4389RisCqhNYRaVi8LBbZx4XHvsdB6Hdi+52EyP7JiiX+wfr/Pw/gb5ZSPg/gb9b/owqEfhLAFwH8MbCRdUgt/hKAnwLw+fr1xz7OB/vzjqygpBCjRhxN7cUQ305Zoak3fLuiwvmwxaiRaiBKZ8wslSrIlcZp5gF+byf8uHXsy5AKK9B3e9gmotFUCh/mfjfrEa2L2A7NpCI2OrN5eenYM1mMDEBRoZ17zFqP1gUcz3s0jnBTe0xsWalMCmyWCZJbdQN2+wb+vQXkQY/V8R5yoK/OPaLX8MHAzTzcMwN1l0K85Ok1lQJV2CVSOKnWPEZ7f49+27A6etZC6YyYFMqDAX7voH5lgZg0bBegTUL0DK79zhHC+rEb3PQttMo4nveEAoPBYjbeLixtQoga2iRYlZG/PseiGbGoIsnLzQyL5TBRl50lfbm1/MwQNVarHrPZCKMz90UVhIcjZpaLZkwanQ242rKBPJ+NaB0nNgIg3Bk1zMlQZ9EUhN5guGrpYB0U+ouu9hk4lK45GhCjIuurBhZdiSYlA+GE1Z/fO1qwFAa1fBwQRs5IkWcN/N5xUQ8K9pj3RDv3mB311Yeu9hfBf92cNi5t5xGinhZnuXDYDA3un9wgVCsiqxLKeYPhvEM/kiI+cwH93mG17nF8vGOlM1CB3w8OOSkMIxXwrlr1LFf91EuzJsEtmJCJ5n7lzFkz6pJBmGxBsrh07V2uFj3FxgsSBZAIrykp6PcOfjRQvULx1bnivMGs8xNzzX29RdxxP1OkULRUl2vXBAwj+5hOJ+w94UulCq6vZnQlAPuZMSvE8nKWR8FvL0T2D9P2D1MP5o+DilHUf//EC6//TCllrCXd1wD8hIg8ALAqpfxcKaUA+I9e+JtvuZUssCcDwsbRGqKKsJRhVhZ6gzAYZqWDRn/BZnYeNULQCBfEclVt5E6NyEGh3zbIz1oAgt3TOaTi3iULNlcz6CZOFOOrvoObBXz1w7sYrlssZiNiUticz6dpgDdXMyidodYei0WP++ub6YEVobBwu23x+PERYlJwC4976w1WR3tcX84xX7NJPV8NuPmVU3z47AjhqsHxD5xTNxI1jEt4fj2HkoKj9Z7MqqCR3ugpOnVkhYkUNK2HnQeaH0aFXPH6Wedh20iq9WtbhJHnsO08RGf4H+jRNVzEx6sWJSisjvZkYNXM/WyxxTiwMmocHXuNyhgfz2iuKEDruOjmIrCf26AUwX5wGPZsju92LUxdaLbbDstVDx8N/GWLRTuiHy02lzPs6wLpkyYDSWUsWo+5G3G+mcMYVoy5Lj6HBdp1YTI1BYD8rGUiMKczxHJdBbpSEEcDt/CYdX7qX4Wew95QXoBnZxG78xmAAnVuSRUPJCq0Mw/sNJo3yfqLH8yqa0LB7MF26lk0LfcrJgUBMPQOfmcx9iRtjIPD5mqGVAT21R2sSTjfzFnFq4xn75xg9toGahFwVAP8+WaOtvO4Op9ju29w9XxBs88aSNvO43hByvFR22P/bA6nE1aLHvG9OX32wKoNCjhbbVGKYHW8Qz7xSNe8pgd3hP3gELYVQh7UFKRQBFoV9NctmjZQ/3XsoQaF/qaFfbDHGAyiNzBNQvdjF3ArMubinsw3u/RomoB+U3un4Pm/OF8gBI22Cfjcw6cYB4eFZVDch5c7bOzTAPPbuxUA/y8R+e9fEBLdK6U8AoD67936+rcSDT2s33/09X9gE5GfOgiXym7LBnm96Q5Mn1wZNUgUvWlFF9nV3fr7z0mDNccDqaqK3kwhsMFbdIF+4qZ56O1pj7yzuNx1mM+ZZVvLZrzWGa+vr1Cy4IcePoZdeMycx/WzBbqjHmlgtt3MPdomVLhMMDPsw6gnDZlPis3dbjWg37QwOqH3FmMweHDvCv3eoTHM/srrXDhOHl5DS0F/1eH1k0uK+UxG/2iOi3eOaDFSM2I3q7btG0MLFVXYSC1UpIsuyFcM1GEw8KPBshtgLC31Y9LIPfUtpbBiFF3QrQfse8JvpdKAT7s9jtY7vLa4okblpsPlZgZZh5qhZ+z6Bu3MY9M3CEHjuO3JDtpZdOsBrmHWbk3C2fEGTiccd3vIjALLRTe+IACloFPe7bAPDqkIWh0ZxIImTBRITw49mU5aZ5TzBmHj2Ojf3/q/lRd0IQcWnN86+KARnnboZp79lkT3hPZvL6BMxvxXG5hFAHqDfEIF+XjdEP6q9v+LdqT26IxssfGqxTiSSh0Gg/1lR3uZYJg05UPSxM9br/YQlfH66oqTGvuGfbAaoMzpQMisiZhZj8VsxBfuPsXQO6yO9zhZ7jFb81yvVj0b5FFjf6C2m4DZ2Q5DsBi8hXtji7B16FqPVTfg5A77jY0LmLnA4WTzSBfwKsDtr1o0qxHXG0KYOQnJCaqgH3h9VWV7qepN5uYe5auL6TlvbMR+cMDbcwzPO5IqFC1/QjBw8wp99wbX+xZHJzv43mIYLVodkWpVdHimX+r2KUT227r9kVLKj4FeOT8tIt+OY/2tREMfV0yEUspfPgiXzHpG4eJoYCtco3VG2RtSLW2CbiMWLQ0HnY1o20C79C7B2gR1aWumpenSWxfkdDdAdxGL0z0fnC6iawJGb6itqdjwOBo4FaF1xlHTTxTY43sbOBvx5mvPcHU+x731BncWW7x25xLWJCysR+cCzr74DMuWQevueoPh/QXOzq7RNQF351scz3usGjLKxlgNHJ81OFtvMXMeDxY3WN3ZYmYCXMNqYf5wi9VrNzhZ7OkenATjVcsAdDpCrixShRVtR/bRYjlAHXlsHi1hmkgTQ1AAmBKDdHPMxWgYLdldNmE9G2AMzUEXsxFxz/ORskIuXPiVLjhe7jFbjFgsBtg24g88fA+Ni/ixV97HK6fX2MdqiSLAvdUGEFLitwAAYIxJREFU/bNZ7aNEnM220KrgpNnj+HiHza7FqqG1zf31DR7cu8KyG/DKjz3CDxw9w+XlHOf9HD7wGp2styhZcLzY487pBl84e4aTxR66V3Arj671iPc8cGOhDe18xmCgVPUGU+Aws0TzSu/p/mxcQvQG2zfZgxh+X8/e1WHssRTYpcdsOWJ8PEOxhI/CwEpFmQw9J223aQJcx3tOqwzv2S/Tlve1q75jWjKUzZgZwo1H8x5vPDhHzoJXTy9hbcLZeovGRjyY32DmPFZuQDfjfdlZD2cT7h5t0NnAoNJ6vHl0CaMTPtissbuYwZqE08UO44dz3HuFweyo7bEfHO7Md/Qtk4L5yZ7HHFkhliwws0ifu+rCnbzGvm9+nZA3pYoSJEFOTAjjqwPGnUMaNMXGvUF+a0+n5MsG85bUc10/u2k9Fmc73Fnu2LubezQu4ivPzshazBrHyz0r35fd5P80wPz2bKWUD+u/TwH856B3zpMKe6H+e/DW+Vaioffr9x99/dtuKbF/gCK4vphPaml3WmmpSSGdN3j2fImSBefPl9hddpBFgJ0HDDuH5jXaaMg8Yhyp/O2OethKV1ZSWO5v7STqXHYD4tbi4fIaJSv83C99HgBwMc7wcH2NvXf4Q/ffwcwFvLU6x9HpDg9mG9ztdjhpe/zgyVO8uznCj975AD5pfP7oGfpdg8+vn8G+ssfvufMIJ90e5/0cDxY3eLZb4MfvvQuRgj/44F3I6YgfOn4CqxLOhxnuLTfYBod/4o2vwpqEP/LwG5i5gN9z+girboRxCe1JD9eQFqvOxonymwKZXz5qLBYD0EUkT9ZWTIo6i0pxPWgnGhcBzfktT56t8CP3HwFF8Mb6EqIKvnxxF589PscvPX6A3//K+9A24QvHT7G77PDFs8f4fa98iK9enuGN9SW+fn2KufV4/+oIf/iNd3D34SXeWF7i7uuXuDfb4vKSkN9b63O8c3OCHzp9gvW8x6vza5ze2eDV+TX6YPGZowvc67Z4++YU/8hn3sHVrsOPP3wXy/mAHzx5iqPFHp9Zn2PRjHj/Zo2jpkd6hcFx3ztWcUce8UnH4JoEOSv0m4bkBlC9vlgNEzSTooZxEdllxFoJrVY9VJMwXw+kzQMYBsvAbjKu9+2tnU0bsFz21AAlPZErYtS4f3JDRt7xBvnK4bOn53jw8BKrdsCPvPohfuXZffzg2VM8v57jrdU51ssen12dAwC+ePwYR7MeQ7K4N9vi8X6JP/zwHcSk8PriCkoKPrs6h1YZnzs6xxfvPMaQDH74zhPkIvijX/wqQtR4bXGF9VtX+OLpI7xxdInz/Ryr2YBcBHdmOzy7WuAPPHgfRyc7HN3dwF+0CIOBcRHpwtHm55UNIKTIp6gRh5okFeq/cMkEZOxpstktRrhl1emMTPrmqwHzVzcYKnQ27NwEHzaWycz5u8f4oXtPcPNsjp94+C60Knj34hido1X/51fPvuNa9rG2jwmPfQqRvYRNROYisjx8D+B/DOBXQCHQn66/9qcB/Bf1+58F8JMi0ojIW2Az/7+rMNpGRP5QZY/9iy/8zbf+fFWZS21Au/BTD2XWUnTYrQbMH245vGvLxur6znYS6q2P92QCnXewDRdWUydQ+msuLGMw9Dm6u4dIwdnRFj948hTHD24wJIMHd65w+toVfu/9R1AoWBiPlAV9IjPscb+CVhlfvjjDTWjwq0/u4WKc4fk14YDLizluQgvXBXz1+gxGJ3zp/AEAYDM0aHXA5eUcu9hgs2vhs4Eo4O2bUxiVEZPGSdNjHxxi0Vg1A/pErcV7uyO0JkDpPLnzrhYD8rOG1VwT0M7YT3H1WEUVmmmqjJwVVg82k917YyOaJsKahNXxnr2VJmFmRiyXPW58g2Y1ImXBwlRGkiaD6+mwwOp0h3duTnDlW1id4LOe4MKUFCumpPHhfoVUBG9fnqIUwdP9ArFafXQ6YO8dtrHB5eUcV75DP1r8/ed3MST22+bGY9g5DIkwzz4Rg//q5RmOmoHwoE44PtmRGLKnR5dtIiTQofvsaFvpx1LJB6QB7/cNrE2YHe+xXu3Zh5lHSBKEWu11MzoYUOCYsV72mM9GnJ5t0DWB3nWVbp6zwvF8T8GtjViueixmI16Z36BtAz63fo77nz3HPlrkInj7aw8Qs8LN1QwLM6JrA/axQcoK39icIASNL13ex9KO9bwpPN/Nf91zk4vgcU8q+y+8+xqGZHGxn6HVAXPnYSRjPevhk8F+cPjK1V3EomB1wmePnuO9yyO0OuJktUcsamJyumcG62P2cpr77AE6GzFbjMiRlYybB/Sb6kHnAuRkRKqjMA42TkYnbLYt7rxyjcYF7K5J5HE2YTkb4LqAWesnR4k3VxdYP7yGkQxdIdR7iw1ECo6bHjd9i0f9R6Uhv4XtE1rB/E7oYO4B+M8ro9gA+E9KKf9VFfv8NRH5MwDeBfDPA0Ap5Usi8tcA/CqACOCnX/De+ZcA/IcgZ/u/rF/ffivgDJGsUJAx9I50xwLE3k6L4S5wxspBzSyqwN80WM6o8ZB5QHvo4RRBv2no5L9zWJ3sMHiLrglYNQN8MhjqAv721x7gs597xP4EBEMymBn2Ov5/b38W8/mIt5/dIdasCq6GDrPW41e/+hBmHvHN3TGaWcBXnp1h3Dk8CmsYm3C16+CTJrW5mvb9/Yt7SFHjf/jwVWib8MHlEUqWyeDw+WaOvxvZtvr5qzWUyuiDxcx5jM87HL/Rww+EEuXOiF3foHEBIdDJOFfvLAhQ7jA4WJPQj5bCzcowUlKgJSMrwegZkD7crxGixtvv3MeDhxe43M4wJAokrzytbR7drBCTwm5k4O2agD5YDN7gjVVG8Aa//PQBlCr45vOTyf9LpEzB2CeND/ZrNDbim9fHKFnwpfcYjGPQ+Go4g7MRYzJwXcAvPX6AcdPgl8MDxKBx7/QGj7YrhKyQi0xUck5N5LHnRYIuDHRHix5PbhqkTHPQ602Hk/UWQ6jHdjWbZtBkl6Er3XccDdbLHnGwaNY0yjQ6T0aW2mT8/9v782Bbs7O8E/ytb572fMY75s1ZSiEJEEhCTBKTwICxy4SxKZeNsR0uy27joQpXtbvLFRTVVY5ytU0D5SBsNzjshqBtbCjaBjOYUSChIaXUlMrhZuadzrjHb55W//F+dyuVZEo34V4lmXc/ETvuPWcPa+19vr3Wet/3eZ/HDEviVCRNJmEiGlutgeeVlI25ToHljdBwD67uCJkirDiIJSLPG6GjP3a4h2lolrmH49RcuzYm2Y7XopHLecCNfh/frbi8GpMVNtebAZ4tdcDHbuyLVEztsspdloFH3Zh85PoZmmdCTu/VJKUw0tpItMPajjX5/mcvCjV/6mNeyljFnpBv3Jpy5ZLdVBBIbJwtEaS1/Yost4nCgnbhiLKBIYoCVW7hBaWkqxvZSGkhuxHiXFhgoLGsRvqfrBajW8mVgidmW0SRfEeXhYfXsTHj04B0YL+8le1z4LVoJnYr+IJvMFrrp4E3vcjvT4Gve4nn/CDwgy/y+w8Ab3h540N2HOBtZZ0WlXTa153netsqktTFWFg45xKU0sRPD2FU4UU5p5dHODtCpUxSl8kgYR77ImCJQleKvLApZx7WdkPlmhwvIg6mfWnAHOfMsoCisniuHVK1Jknpslr6DIYp86MeVlhiW0LL7HnStzLZX5IVNjeWfTy3oqxMeoOMJBHfDmVoVrEw3D55soNtyabTlCalEll2y2qoGpM4c3lSTWhqqXe0H+vjf8kUgMUyoPDFaXOVu5h2y+owwuyLTlZ+NJDIDEhjF51YhLsJTSdVMp8HWE7DcDtmfhKRl/b6ZLaa+yhTKNuXT2R85TQsM49WK56ej8lil+e8IfncQw2l+JwWcorNS4k26srkyfkEwxTDNNNuKI/9z9giI+kVQ2lWiSeabK2inTtoW6NcYYTVHYMoK2yup30sqyHPHLEDqMRDx1Ca09/epXggp24M4sSTz3JYrEUZrUFBvXCZNhGjUUJ/Sw4YdWWiG8Uy8yhih6AvUiROF/EWpUlbG1hmQ1J41IFBOMiITwLacSaNl8ceqlX0nzBoTVi9qQRDc302wPdKFse9NU34IOvRtoonZltMTyLCgdS/bkrRBP2cx6fb8julUarlZNoTv52wYv7sAGc3Y+DnGJbmNAtZpR7zRUivl2EozXQZ4jjS41PUNk/PxyilubYaMFsF0sM0rvHMllXsYZotT8/H5KXN9bhPnAmtOElcgklKWUh3fhAVNB8e4LwhJktcHL+if2bJauFjudIDZHs1ceLiTE169+TEmUt56GMMSyKvYB4H8j0apcSJS2O1xLGPdXO+udhxBF7Js6sRRSl11+3JisMs4mQV0vdzrq/6DHdWBLdRKua1mP66FfxRoil/QWCZLV53KgLobycEA9F58vxSCuXDFV/2ZU8QeEIxdc7HBP2MqrRQg4oqtxhuxdKvUYsqsuNWeFEh3i1aYfZLqspikfr4nsi89AcZZSLFcttqKBsTz6o5WYQEkXQpUxprXSnPl5NpXtpMj3uijpu6DL0Mv+P0m1bL/niB75b0ohzXrfDsmiSRlJUxs7HtBt8ryVauFDATm9PLIyyrFdbR62PSzKHv5SKjomFnd4FlSrHY30ppjzzcziLANESyZDBMMaJq3bQKsDWOOTueU9Um4TCjF+S4HSV6Z2cJSFd3L8jF6EtLzSrwSuZxIIrSrcFgO2arH+N5FXTCmlorPKdiMpAFXHS5GgZBxt69p5zdmgNilWA5NbYhpIxm5qJbxf59J0zOLKAzFru4e0peSKR55XSEbTWMhslah8uLSq4fDSkezEVOX4HrVlhWg+9VhFHBZJCgtWLvwpReX4RIi7ITXbQbDEsi3Mn2SpSZtahF3DOZsrO3kFRQK7TttjWITwKUI59lP8oIzsTYeymrt2as3lTi93P8qKBMbWnqDISZtZwHPHljZ63ife7MVKKZaxF1bLNIfdKVx/x6n/w4IE8dSW8qDfozY6HhYNbn9WdviCSQhjDMKUqhhw96GY5dM+kn9KKc6SLCt2vyymLST3DcCvtUepzOb80I/JK0dNiOYhYrn0Hn+9PvZ2QLj+EgwXIaAqektWFvtJT6nyPXse3VwuL0aoZRypnJAvsNC3y7YquX0D+/xHIbitqiXLig4Cv2L/Omc9fZ3V4yHCQohMH5+rM3OHf2lNnTI5pWGKDbkxWO1UWRscsy8ygbE7+jyd8WbBot7x5opOCed2KQqxs9PKfuWE9dEbs12PMWXBzM6Hni1xJ5pXig2A16ZeNZosKc5Q6DcSw1HLPFcSuGkdRemsog8grKyhK3ycbACSoWJxF9L8cxG3y7ZNSTHLRvV4R7MX7nddK2Bkkuhc9wKCkB161IK4d7B1Pu2ZZ+lpHb9bs4skGeLkJstybyCpzzMYbRMg5STEd0t5ygwt1L1xuDfiJiEGaEtnTN56mzZtAYVkvglfQvzaXDeW5hdY2UfS/HchtxlSwszo7nBHbJG4YH9LxCbo7I33iuSLMEUcEoSrGNliwXP/gkcfGsGt8rJarKHIkSVEvolgy2YkajRKjJfsbIT9npregHOdv9WAQpW4Vviatjz8/ZHawwjZaisFA9qRu9aXKNvpuLMymysU16iTQadv0WBppBIAKkdScX5PgVe/tzitIiXYp6Qlmb9P2c+qZ/i9KsFj5Gl9osZh7DKKOpDM6O5t21B6bdUh75vH5wQFGba9/30C0ZhSnBOFs30WaFTd8XfbEwKjC9mmzlMY5Szu7PaFuF61aETkHQk8OBzD9bCzV6Z2PCScowzAj7OSqoGZxdcHHvlDKz8cOScJh1m7d4xYx7KfdGJ0RewbiX0vMKJr2E7TDm9KCPb9c0HWlhb7JYf7eU0tLgulXT1iahLRL/PU8ahF23JinESqGqTXb2FlK/sRoabTD4kmOuHY8wzZbAqXCsrubnVfSjTLxlEDry2XDJThAzCaUJ1LYaRvtLLu6e8lBwwH3hMY5V49sVD+0c0fdz8kYUBYLzK05XIUF3gAOwVEt/lPDGvRs4Zid4a/7RErt8NeKu22AUmqGfsbezkIa2YYGpxLmvrE3O9+eETsFJGTFxEwaeNAkCsggHBeaopOfmRFHOIMxYnEZorUSe32owDY3vVexvL5jFnYxKv8azK+7bOZE+G9WyzKRRLylE2j0pxR9mGGRrAchRmJHG7jpVZpktb9l5joGT0XcKJlFC3Rp4Vs0y89gKEhynpkzl1Nq2oghQtSZ7kwU9p+DMaCGRQD/BMDRv/OoncO2aZeHhdMrGoVOyE0mUNpuFBI74pkSXFhSVnNBDu2TSS9auibtBjG9XGKrlYn9Gz83x7YqBl+FZNZMgWS8SniU1LMPQbI1iUbP1RDXBdWr2e0vyWnLggVPh2xVNabIq3XXNqm4NzkULitpi1aXZzC7ZbaqWvLbZGiSc2Znj2DWuURPaJWE/xwtLikZO8HEuasl1Y3B8ICQH367ZHsaMxzH3b50ICcGT3ov9wVIorpak1zxf9M4u7p8KswsY7sljdraXQkhoDYob0sS5d68wt871F5SVxRt3r3daWOKqGHglae6w04tZ5S7DMGOnt8K0Ws7uT4mcggeHR9i2GM4dLPv0/YK8tDg57VE2JtNMFnGtFencJ3QkQo56Ob4tn4NpN7x++xDXlq76gZcJi8vN8bvFtWxMHLPmnbtPENkl+2dnZJUlygmukEDS0pZDhCXRlNOXz2lVuez0VoROwfW51MHesHOA6TSMwpR57HP1aETPL0hyhzh3eduly9y3dcLpMuTGR/dkY7LrdS3q9cMD7hueMrAznO5g4Jii7mAaLX2noNUGW3ZM1cgmdzMSqRqTnl0wCtNOXkjqgz2nwDYb9vtLHowO2YtWjPx0TRL5w685GxbZXYO1DERjcHZrzmSQcDqP2Nmf8/rdQ+4JTyWyMCuO84hF7rPXW/GWnedkke6t6PUyAqtiv7+k7+VcOHdCVZsslgFKaRapR1FaXD8csj9c0LaKs2emJIWDpVouXToksCpev3tI1Zqkcx/Hrvninat4Vo1jim3vhbF8mYOoIKss3rx/DYAryYissTnOQnyr4qmTLaZxQOQV63TT1mS1btqLVx5ZZWMbDatSdKIGfs4y87gwmnHGW/DF42vcPzjBMRuKlcvpKqRorK6xrWUaB6xWPlkum6BtNSwLj3v6U1ynpkwcPvDceWZZwJOrbVqtWOQ+p2nIYdzDsWqe+PQZXEt6NqrWxHckvbZMRd7dNFoGQc7XnnuSsZvy9t3LPDK5wT39Kff1TzmzO8cxGx595hwXezPqxuDyYsxD4yO8LrLznYq8sjlNQg5OB+xHSy70Zlhmy3sPLvHkyRZ7/WUXRTUczXtrVYSysjh3/oS4kML1IvWIM5ejJGIcpNwzmOHacip+ZOeQpHSJuo0/6Kitb967xlYvYa+3om4MPLtimgfYRsNDb7hCqxU9N+dqOuLKYsilrVN6Vs4bx9fX0YwoWXe05sag7+acpiEXJ1InGzo5dStCnK4ph5rDkz7pyuPs3oytMCHJ5FCy1Y8JhhmXn9vBsytCt+Ro2uM0Cxn3U07ygDdtX+OewQxDabaimGkW8Gw65kt3rvCOvcsAXM2H1K3Ui8ZBShRKdHpT5XnspTzQP+HgeMDecMnecMlzV7Z42+QZ3rXzaR7cPmbkp/TsnDefv4ahNI/sH7A7WTIJEi6MZ9w7kc/CMRsubk05/6br0kNVWlIbrC0ePTmHZ1YcFxGBVfDc0Xi92Q+9jKM04mevv5H3zS/hmjVPXN/h8nzM2EvJa5tF6XGpN+WdF58gdArO9ha8fXyZd+08zn29E47LHnHlrBlytwuq1bd0e63hrttglILnjiYsM4+qMVmkHn5QYpsNeWNxUkacDRa89+o95I1F1RpcmQ2ZlQFNYzDLAgyl+chT56lbg3n+GdFRzy/JPzSmrqV4rBuDHT/h0vYpTWvgOTUnWch+uKTv5F3kUXXyInCSR51oocXssEdcusSJ0DOz3OG51Yi+n3OShbz3iXvJSpsrsyE9P6dpDcZeyjOnYxyzYZV54lXvSlf9MvY4WkVYqmVZeOSVjWU2DJ2MaRXw6dU2Ty62aLRisrMUxlPqk2cOVqck4HWaT3UjjZPHy4hl6Um0ZbZ4XkVeWzwzG/P0Ysz5/hzPllpR0xqooCar7LX+mmMJbXXSS/CtimUuemQNiivxkOfSMfMyYFoEXE/75LUlC6or9ZWzgwXL1OPyYiIaU0pYUau5+P1EkdCgj7KI0ClZJD6RXxDZQgl+5voW24MY360oVy6BJ4oDVWuu/U4AfKdix4u5nvTx7Ipl4TFyUg6P+1g3O/Ybk+M44iiLcMwaz5R00CwRevkq81jkPsXSJa0cPnL9DJbZMs99Pnh0fk2JvXywhWM2THoJtTZw7JqkcpifRKSVRNlPziccZD0ss+WpqzvMj3riPqohq+y1SvLAy9buj+Eow+l6c7ZG8To1tCw8Wm1wmgWsCg/LaLGNlmvJgCeW22St0JF/4+n7+fiVfZaZR1K6LBf++jUGXsY0D5iVogdnKonG+pOET8e7HJU9prlI8p8WIc8sRrRasSxdIkdYk3Hp8vTphKxx6NvC1MxrUQoI3ZI6FoWKvLY4KUKeXYy4mgzRJy5x7tKihHFpl9Ta4IMfv8SzNyb0+xnbYYxjSs2zrC1CqyBrbJ65sUVcOVzOJizqgLK1+MR8l2uzoWQjjBcaRf4BcRfXYO5CuX4Y9FNWiUdaSiNkshAp9qyyOUlCxkGK71bcWPbX8huP3jhLqxVp5tCLcvy+UH2n04hFJ4ZpWZ0HRXcCdcKyy+XWXI4DfLdkFgecixZcT/pM44BJT4qcae5wYPRICpHc94c581TUmuvO/yUunK7eIEXh4+M+TlBxvBwQ9DPKVthBWSUFcNUqKgWm2VImHro1yH2b6VGPwVYMwLL0uLoc4Ns1B09P2Lv3lKRwyBYeaSsmYpUSjxLdKemadktWSZPgQSK9EerYRYcFy4WP61ekuUMa2hho6tqQdGCrWK18bKP5TO7bbMkyb/23cc2aw7xPXLjEhYtvV1y7Meahizc4uT7APjejF+ZcXo070yrNKneFNFFbeJZI2TSN+JMcxxFZ7jDqpdSlSWo6lKFJXLic2Z2TVbJwGV5N5BYsMo/FLIRW/n5NbZBXNstK5li1JtPTiHPRYu1JT6tYrHy0VjwVe5zZnhNXIuRZVPIVq56JmN8DVlCRlA6BL/WuOHOxzIbL8zEAYShWvWYrEV2aOcRPDTEUHLgDTLvh7GjOs6djiVZ7OdnVHqN7Z6wSj9PjHvW4E21sDYrawrcrFiuf1lcsM5e+X7BYBkyGMfNlwJPWFqvclWvbzWURX4SYViv1iNYQq4jGIF55LEuTwVbMMpeC+F5vxdGqx1WQ+drumpxymEV8erpFXtqEXsmzx2PG/ZQbpwMMQ9OPxPxtGgsD7WOne5yJlpSNySzxMY1WnrslZIrZYW9NOJjPAxiLmOcy95hfHaDPSypteGZJXtikuYPVa7GUGAbGucNh3sdSLduTFc8dTZimAfeOprRa6nhlamMNWxyjvm3rzmsx/XUrUFrfXe/cvXhe3/9D34tptGsxSafrRWhqgyjMWVzv42+Lp8jNhksKAxwReezvCOvKtFqaSjqzQYrG2coTYzFTUyYOTiCCh75dUTYmae5Q1yY7wxUnq5D9wZLDZY9BkHM86xF2fvFVbXbpjD7KkHFGI6FNm0pzfNpDJ9ZagaAX5EynEduTFavMpchsXL9aS9NYVks/yIlzaSAsS4vtYUxSOMSxJ6q6dk1ZWhidmGaZiow9QLr0CPoSKenObtq1a1YHEc4kp74WoMeit9UUJl5UUj4boc5kor/VWRa4ntQjmsshwYMLkkRSdobZMuql5JXNau7jhBW+W66lW7LEIerlZLlDL8zXhdjpUvxObro9WmazXsxWiUcYSAorXbmi0muL2dRyFjLeWgFQVGKrsFr57G8tOJj2Mc127YLY62csZyH9kbDXqtwSynlQUSxdjI72XF4LUVuiglBfC+jdOxfKuyE0cZAm32QadLL3rDv8na7AflPlu2kMmtQGqxUZntIUum7sMNheUZRih9zWBroxcAKx5NalyXBnJden2VLkNvtbC649vc099x/wzBN7jC/Mibt5VZ1ZXFtYBKMUy2xZXuvj7qSEXoljNhxNe+yMV5SNubZhrlYO++ckhau1InAqDm4McfvCcLM9cXq1rYb4NODMuakclBDbCN0d1gxT1B7S2MX1JfWaZg7N0gGnJRhklKX0AVWd1I4yNEXsMhjHxIls/G1liMW4W1M3Qh9vOn215rmQwcNTEcVshKXZNgaDfkqcueta5+FJXxTRTdmMvvmeT/KP3vzTH3ye4vsfCOHWef36b/tbt/TYD/z43/lDj/dHCXddigxDk9yISFIXXRprGqRptGuFYaMngodtY4i7ZaOgUVhBhbJayo8MaaZupznVCmU0diie6WHYjTwvtwgHIqVudPWFJJPFNAwK6Y1YuZKauxYxT3xcr5TFtzXWTXYgFMsgKogzl6o2Obw6QlcGzjhfNxaeHvXZGq9otCI7DPGCkiK3SWNZSHp+ziL1qGtz7XkSOcV64VOGlh6TU0+MnwCdiBJvWVqdgrN4zQPUpSkK0bFJ2yjYLkRpN7MwnZb8IKD1OnfHUjSm2tJcb+TqQkqauuIhUhn4ntRO+p1tbS/I15YFdSfgqLWimok6QdXKpdtUnRWyFgdOxxQa9WwaYts1i46xpAwNqWjG2ZYIkrZaSZHeqXCtBt0ojuY9olC85XWraHNJlw3GMUVlUaY26shF1wauU4ugohI7BEZCR28qk3ZYs1pK+tSyGqrSokht8tTBH4pnjudWhEFBk1vUtSneK1o2b92InL9YNICupIlWN6KyLRuDWjul+l5Jm5u4A9l8qxsB2dwHLcVtFVW0KLEa0PJZtlp1zMgWw6uFRWdonG25buvGYLoK1moXceoKozIs8Ee5+BG1Its/jQP6k4T9wRLDlveGhmGQ0d9KsM1mvbk4phygrM4S3HMqol5OkUo02WSdTH9UksXiCrt+r1ZDVVgYc7FGbnJL+pUsEbVMrkfy/Vu60nhraNpdidiSa5EYrXWbepy6okVotGSVxWiUMI7kujwzWGBw+7ojN0X+uwVKo3qVmDnlYvdbJrKItlqRpw5tbon3SW6Kf7rdYm/lWJ3nvHpkhTkqUYDvVThBJSrB9y7XXuyG9ZmLM05djuY98li8y/PCJvIKhlsxp2mIvZ9S5taaHjufhqwSb72BZStXJFfsmuVBj/5OTH+SANAPcly7pj9OMA0tjWx7MZFX0lbS0V9XJo02OikXMVUKg4JpFhAnssibRktVWPTPLWUzNVu0KVd9tZSGyraVjfamU6BaWrS7sklZToNht1Aa2E6NOSmkZ8ZuRQqmNnCuiUx+MxMl5Wbu0NaisJxmItV//WiI0VGu49gT2mslXjh9P8fdytgaSE49KRx6/YymNjo7AFhmHuksYHd7SZ46nN+Twrjj1excmkodCY0VSErMdWrGfoptNjx84YCmNmhbgyK38YOS/XOzTqRR0nlBL6f1WozEXGtjGVYrZmRdZ38zdeSgsXSoFy5tK+rbtiePLTKbMrPXG5Mxt8UVdeEINVpDm9ioroembRUYWhZkv7N3thpxGHXrtc+9OywoFp7I8u8L9b0tLCGXOA1xIZI1fS/HcYQcYNvSxLgzlmguK2yayiQKc0K3pJx6pHN/zXTUWuHbIrtSFhar05C90ZIydqgbg7Dz1nGtml6YUzWyUVWNbNSRWxI64qJZ5hZ1LYSbpjMOazrvHGdbBFfVsbvOIshnIerfelISnwbirGrK98SYWxA2YolhtRhmu7ZZaCoD/JbsKFy3E9yUy01OQuLEYxl72IYocRu3e7Xf1GDuEnSn0tZpcHZTObl3UuvltRDdqzGDCuNyQNVraW1hUVVzl8oVG9yy87ooc4u8cnGiEsPU0iRni8Ol41cETsk7zl7m0ZOzrDIXZba0uUkwSnhkfMDHp3t8/f7jfGh2nr6TcyMRDbLt8zFHccROID70QzfDMlouBDM+HJzlfDTno//+dbhfMWc3XPHMbMy941Pq1qDnSlSz5SVrdo1jNpykIedHc5LKYeDIY9Jaiu8jP8VQorUVWBWf1grPrkg9F7dzDbRdSSPaoTC/msJict+U+SKUlFFmYfZLrGFBeSXq+m9EPSCLXZxnXXg4ltO43XL/+SOuzobsDlZkpc09gxmfnm6xt71Aa8WDg2NRAVaaoZexKjzeNLnGrBcwclIuxxPeNLnGx2YiFeNZNX6Qci5ccGUwZDeIhUEWTHlveYmv2LvMB04ucM9oSq0NXj85JK0dcjfjof4Rl5MJD0RHJJVDWVs4do1ttDwwPOYojwisiqM04mjew9sVzax05XZd+WodCZYHAeEVg3wMvTMr4mf71LWkZKrYQlka53myJquFj3UmxTBbWkfMx5pP9rFsjb5QUqQ2UT9nVZjksStumqO8u5g1dWdS1mrFl569wsedPbEnBvxhxjhK2QliIZSYNTfSHl++9Ry/lD0ICJtwFKbsBjEfOjnPg+cOsVRL1BXL9x5ZcXk+xrcr3rh7nafmWwBMgoRLwyl1a3AhmOGaNff1TvjI6VnOb81wzIZZFnC+P6ftKSzVkvsW+/6Sy/GYwJdoPc9tFtcGENSyIXg1rWtQd46q1rl0nbqtc5sitdErG3srpzVFObpYuFiDAr2bY2pF8fgAdiXqWl3rYU1ydGVItD0SqZuv2n+aX792H0ltcO7iCe/YeZr3Hl/i/sEJv33lEt927jEi8+bn/IeEvnulYu7CCAZUK9pitt1IyicXaXPttvKJaEW1W4Hdrk8VKqgx3Rq0KNrqRonMx5GNa9fit56YcorXIlWiFAztlNApeHjniN2tJZfuOSJwSh4Jr9N3c3btBfvBkq8aPcFuEDNwcqyuJ+Sh3iFfNL7Ol42f5WwwZ8+VxXfLSbjwLc9wYTjjfDjjwnDGA71jdvwVXz5+lof7h3z18NPYpqTCksrhXG/BmWDBA4NjzgYL7u8d891n388Xbd1g7GUcLIWlFZglW1G3EbTSfHjz9K67jnrTaqEwSDKXZmWjjl1wG6kHXJXUWJHaVCciq0JtoB9KxGBKaQY7MX1HIpKRK+ymrxk/zv3jU/7apV/jvuEJlmq4r39K0Vi8fnDII5Mb2KrBUJo9Z8mOF/N1w09wqTdlEiS8ffcykV3y5GKLs9GC88GMe0Jpuvvi7Wv0rZy9UE7pfbug1gYPRodYRst595S8tnjQOyArJd1zrrdY04b3/BUPREc8MjqgH0knuzgxivaZ69biH2FoCGviB4XeWjcGzlkpTreVgSoMDEssgrVGNN0MLQ6fhUXbGEJW2K6pxjX1ykEntqQSFeLM2Kkto4DGAENSpJFfsOctMQzNJJT+pjPDBUnpSBrKrPnmrcdEVcBecWEwJ81c7uufMI0DPvjERR4+f4ChNGeDBe8af5JlR2l/YHRC3Ric5CKA+c1nPsGlaMrD0QGeWXN/cEhkl0zshJOF9ISdD+dcGkx5fe8GF4Ipbx5c4Www55FIKMrDQOR4DENj9MQaw/UrHEtqZMrQMCqpC5MskcjLOrTxwhKCRvx4LLkelCWRimm2KKOl3i3RtRLlCU8+L1UZGHsZyhBK+razInAq9icLtvyEB/0DLvZmfEnvWc6N5rzOu8ae9Zkm0j/kkrNJkd0tUIZeS4/kmQOtQvnP81tvRMEVqwW/QS8c2sJEdwXftuok0pe2vE7Ukhe2SJl0zoVtYVLNXeaJz2HRx7Nq8sYidAou9U8pKouvDD/NxXDGl/mX2XcXnLVnvK53A8+q+Y7dR+k5Bd82+DC1Nnln9ElmZcC39x/lW88+hmvWfOXkKdLa5iv7T2AZLW+NnsQ1ar5j+CFco+a8c8o37X2SoZvz9XuP45k1X9Z/hlYb/OWdX+eo6PGIe41db8Wnjnf4Lx94P2fCJV8zelz0t+YR5omkrZrCJM9tyqmH7dVMeglmX7rzt8/NsM4nmE6LF5To/RwVVYwnMYRySu9vxSI544raQdMaHGchVWuy7y8Yuhlf5l9m5KS80b3GjrsiqV3OeTPeMLrBN48+gmvU/KWt36RuTf7E4ENcCk64YE3Z9VYM3ZwH/EOGTsY/euinmRYBf3L4e9StyTeEjwsttXV4U/8qkV3ycO+Ap+ZbfHXvU2y7Md8SfYKv3/4UPTPjOy9+mIuTKW8bP03kFHzr5CO0WvFdo/cxtCXtZJliI92UwtorCovqSkQ76wQ+eyVNaZLdCCkzmzq28XsFql/heDX1lVDqXaVJr5/hBaVcVy3EK4/B/hJ3WHDu4ol8loOYoJejLDHBc52aXpDjDXJ6gwzfE3vhD5+eo20VF6I5o0iiudAp+a/23svISXmH/zRvmlzDUzVfNXmSLzl3lW8YfYL7Jqf8wFf8O5aFxw/e8+8YOwlv85/mS8dXmLgJD/cO2AoTvm77carW4K3hkywqn+8avZ8vHTzL2Iz58tFlArPkLz7yXnaDmK8ZfArHqPn2wYc5KSO+ufdRXKNmaKa8ZfQcA0csDHyvRLeK85MZk15C6EpX/mSQsDVZMRiluH6F69TUe+KrgxLCSNMYFJkNKLLEoUwd6ky+l4YrdR7lNNQLF27q8TniZbNsfDyrYrfLEqwany0nZs+as+PH9IycK9X49i08Wt/a7eWuZ0p9rVLqUaXUx5VSv/68379bKfW4UupJpdTfu8XXirt/71FKZd3rfkQp9V6l1EMve3LchRuMYWjscc5wmIqKcq2I+lJ07e3FmIHY3970/HYWBhigFl2xP5HcMZGcRJ0d0TGzvVpcLU2p05i9CkNpvmn8Mfp2wT+4+HNseSn/8Ox/4k9efJSJUfANo49xxsp5e/QEAH97/GEuhaf85cENvmP3Ud7iNnzN4FO8za35tq2PEKqGb+19lL6Z8XfHn+Ab9z7Jd0UzHuod8l+EK97Se4Z7rIpv6H+MRhv8jdFHcYyG/2byKIFV8FcH1/iKwZM8YDV81/b7yLXN92//Fm/Zv8J7hh9jYGf8xf4h33v+twnDnK/+qsd4aHLM1z/ySaIw5098+QfZHsR81e5TvPO+J3jb3jM8PD5i3Ev5s4/8HsMw48888gEePn/AO888yTtf9ynedu5ZHpocc3HvlLfuPcckSvjO+z7Mjzz4k3zjuU/xd3Z/hbPBglKb/MXt32De+vyF8W8zdhL+/tbHOe/NeLdf8sXRc+yZmq8ZP86eqXmdd51l6/H3t99L1L23tw+f4stdg/9i70N8qQNv7z9JpRV/cfJbuKri+ycfY8dd8T9sP8a3nP04X+eXvGPwBCaa13tXWTQB7xl9gtcPDvi+0Sf54tFVvjNa8PXjT3DeavgL4/dy72CKb1c8eP6QnZ0FozCTyG2rwByXeEFJP8o4uz/l0sM3OL83RVmaN+9fYzRK+IZ7HufCF13nG+95nLO7M96695x446Qmf+YNH+DC7pRvvfBx3nHhab529wm+6eFP8Kbt6zy0fQxa8ae/6IPYVsO7z36Sd93zab79nsd48+413n7mGf7WpV8mdEv+7v4v8uDwmP/t3C+wE8S805tyKTimxODPT36bXFv87fETPNK7zndFM7a8mO/uTfmei+/lIVvxiH+VBsX3Td6Lb1T81+P3YamWvz1+gq/ce5qv80v+5PYH6amGrwk/RaUtvrX3UU6qiL89+hQPRod8d2/K24dPca9V8xd2fovzVsOfHf8ulTb5+9sf5nw443X7h2xHMWf3ZkS2pLQcq8ZUYltQNia20ZDHLllhr9l0NAZlakvhvxHV6rY2AQ2FgdaI/XnHOjNSEyMzKU98hlFKVth8y+BRAP7RhX+HZ1Z8a+9j3OOdkmuHd48fY9pEvGf46du27tyJCEYpNQR+FPh2rfUjdAr0SikT+BHE0PH1wJ9RSr3+ZU75Ka31m7XWb0Is7P/7l/l84C7cYEA0kxYrn7K0CC/blLVJmdlrlVlahenXkJnUUYvfy9EDoV0S1bSVXMy6EipkqxWO1aAdLRFMZUqh22w5a83o2TmeqhnYGddrg4GZ8dvZRc5aMz5U7LJnLnmi2GXaVnxkdoZn6hVp6/I7hUOhbd5fGKwaj19KHsShJW5cbjQZn4r3+VSVYCjNY2XG5XybX0rPERoFT5c7TNuKy4sxx01J3tg8VcdMm5BfzbbwVMX70vtYtS2fnO6y0BVZ95i0dVgtfEyluZH2yBobpSCpXbLK5qlkm0Xpcy0dMi0C8triuIw4POlzNR+xLDyeWG0zLUKuJgOmhc/hsse1dMBzz21zOZU8/pVsxLRxeV14g4/kF+gZJY/l57BVy5Orba7WCb969CCPlRk3qiG/me3wodVF/kNykTPWjI/l51npmrGT8FQds2h8fieHpHX53cJi1Xj8YvwIDi3XiwE3mgzfLHmuFoLEh8ua963u5VfT+xmbKU/muxw3JR+b73PY5DwR7/DxKuXZYotfSs+xah2emG2R1xZJ5XB82qNqTEy7XXvV55mDgSbvnERdUyjsdWuyWPkcFT2ePZjwTDLmxsmQy/GYp+djBucWXC8GPHsw4clkh6OsxydW+xzmfa4kQ+k3ykwOix6Llc8z2YTTIuLJZIeTIuS0DNkzF+wEMSYa16i5XhtEVsEHSp+qtfjF+BF6RslR2edGk/Dx1RmeqGJMpXmqjjmue/xWHtI3c/7j6o3kWnNShuRaczaYc7lOqbTJh8uaK9WYX88uERgVq9bDQai9N5qMT8e7PFHF3CiH/HK6T2gU/Gp6Bls1zJuAkzZnVXmktS3d9anPp452mCUBz13dkl6jRcTy8pDjwwHKbClWkq7ThYkVloSDXIRSTx3KREgVht1iDkqMVAgXbWEKC3RS0EQ1+A2L1BdXTyNjWXistMkb+1e5XkekrcOT+S4TK+aT+RkOm9tXg7lDRf4/C/yM1vo5WBs4ghg4Pqm1flprXQI/BfzxFz5ZKXVJKfU7SqnfU0r9wOcYpw/MXvbsuAuL/G2raJ4JMWpFeyklva/C0QqmDuaFgnzhYXjSLZ7nFm1fitum02Bc9rFftyBdCvfeG2eoj/Qotlqs8yuUKb0jKI1GvL2Pmh5FY/FocZ5KG/zvB9/Iw9ENPpmcoT/M+aFn38X3XfxlfunodSxqUQn40dOvJm1sTqqIkZ3wM/O3YKuG4zJiaKb8p6sP8/hqF8do+MeHX4+hWn58+g7mlc9h2ecr+jY/9dxbiM967EdL/snJ11C2Fv/Po3fxe4cXeNvuiNeF1/l0usvPqi/CsWp+cvFmPj3f4YfMdxI3khZ8Nh5x9dqEeMtlFXt8QJ1nsfL5SHyGKCyYH/XY2Z8zPw35HX0P7dLhfVcvYhgt14+G6MbAiwqcTkvqRtxH2Q0fO93jN/sPMHJSfm7xxWzZMY/GFzhjz/g/D9/I7rkFN+I+3/nY93DvcMpPzt/Ksvb4t8lb2PeWvG91L16/4tdOHyQwCqZlyP90/ZvxzZLT6kupWoOjss/ITvh0ssc555TLywn/1/ZbcYyaf3j49RhK8/+dfRkTO+FXpq+jt5VzOdnih/VXYyjN91/54+S1xU/Pv4zDos/lbMJhNEBrRN16GtFmosllmi210rSlpGQcq+HB4REfPTkjCg69gsdPt/G8ivd9+hLhMOPJky2a0mSe+ThWwyLx+Y2n70dXBk/OJ5we9+iPUhaHPex+QT/KMQqD37x8H9vDmN/6+ANs7S/WemN9P+daPcQxGt6b3UvW2PzI0buotcFvxQ+xay/4cHyBZ7wRSe3y3175NuLK4Z9P30HW2PzQ0Ts5KUNOqx4Te8VBMeDXs0v87pOX+NXx/axqjx+fvo1ZGfDPj7+KvpXzqWQfT1X83I03sn1+xQdPz/Oe1Xey5SX8q/lbef/0IsdRxNv7T/GbiwcpBya/Pb2fo7LP1WRAVjkcPDfGCCuUAUUm6a80c6hTUS6ni1JuHu9Vo6hzC9+raCsT50JCuXSFqmyL0GjT9VwZbiMFdkNjeCJSa/Q0VW3yRLnL2d6Cn1+9EYD/uHwjY0sONK/zr/FEssNjwTZwcFvWnZdR5N9SSn3geT//mNb6x17isQ8CtlLq14Ae8E+01v8SOAtced7jrgJvfZHn/xPg/9Ba/0ul1HtecN99SqlHu9cNXuL5nxd3XaNl8MAZfe7/8V+LqyAIRdduaSqhyzqOMFYCv1z3PZhOI82FgOWI94gxEFqs7cgGVJ740IJ2W1RlYI9z6fcwNO2Rx9nXHXKyjKgqk3E/Ic5FmmQ2C9nfXnC8jBhHKUenPfl5ETHupXhWRdFYa9WBopJicFOJ4dX+1oIbxwPO7MyZxgGeU5PmUjsZRynXntli+9yM2Spga5BwdNqjPxDxyXnis9WPySobx2w4XYb0wpz5MqCtRPm5LsXOtq5Mkao3RQW5yi3Cfk790QHV/WKQZbu12NIeBGi3xR0W0jRaSXqif3bJ8qCHvyVKCVkhsiZ9P8fpvGrmsc8wyjidR0RRhmtJX0tSiKr0fBGyvzWnbkwOjgac3ZuJi6ddc3RjyP7ZKUVt0Xdzam2Qlg6W0TLvZGIWK5+98ZKD0wGTYczpPGIyjDk67nPhzCmuWZPVNtePhtheTd8XSfrt0Yq0FNbdzUh3FGYsM5eqEgp32/29laGJQvFiceyG+bU+uC1er6DIbHRsg9cw3IqZ3ehj98VlsqxNoXM79boPqm5ErUBrRVnY7E3k2tBarWs4RWXhOWKhXNUmkV+wjD2MzgfGMhvSlcf21pKi7gQ+uybUpjWITwP2z86YrgIm/YRZHIgkf5jw3PGY/cmCo0VPaO5aMQozsk6hYORnXJ8PGIYZs1Ug/jh2w7iXMkt8RqFcG0khjZ+Gkp6l+WmIFwlduckt+uNk/X3zQlEFn14ZYhSKdlhhebXQp3s5xWND7DcsSBYetl9TzV3CnYSisGhKk6ifi09SYRKOxMcmiV0sV3qUbjb1njy+xfCB6Vofz1Cag3lfIiND87ce+RX+6sO/8YdufIzG5/Wbvu77bumx7/03f/eWx1NK/TDwFsRHywd+B/hjiN/WN2mt/1L3uD8HfLnW+m+84PmnwJ7WulJK9YHrWutIKXUP8PNa6zd0j/vTwPdord99S2/iebjrIhgQAUHXE8vdYu4R7a6oLJN06qN6mia1MaOc8sBDBZL39UKhjNaFibuTSte0ls5s3RrgNV3THegWbLumPuhh7mXorYKr1yb4/ZzALzk+HtAfJcyXgUQ9tckwzEhLm7YxmCXiIZNV0sOglCaORTOt7+fEuUtdiOHYMvNQBhwteniOSLTYljT/5bWFPSyYLkMMQzNLfPoDkf2fxgFVbjEzA9pWMctEuXjR+kRhTlHaOHa97noO/FLeq1bi5Kk0WoN6ZIVRG9SFRdna7G4tOQhclCEsNENJXUr1KvLSxogqMdLqrGudTun59DhiOBQ5l0XqiUmUVuRdp3iaibyK7dRMY+ne395acjjrEfglR8d9zKDiZBHRVAZFaJHnttCpt5eUqc00dnDCUthyQUHZmNSpfAZBT3o2bmJrHFPUIsjZFCZZJdYMltXguyVZ4ZDX0iDZNgbN0ibYScg7hYe8tGlqQ5hihUFrSte8F5TkGgxLmm+VqUX1oTZlkzBNmsYAs6UoLcqZx/DMUuRRGsXJSmwfLLsBTJrWoLwWUm1JQyZA7RhrGrDnCKNtHKUcLzuXz2shg3vnlJWJ59QUkVxrdWlysogI/EL86Y8mhGHO6SoUdltpUWUWlV+Ql9LLA+A5FavMpUptdnYXnM4jDo/76FaRdgrjdSfdM58HuH6FrkVnLY8lvSVqCi3FyqboGiTNgdRlzG6DNQ5d6OVU9+RQmfRHqfTYuKIuwDMhel/st3Wr6I1T0sxZ/02rXDZX26ulpr4lG7FptdSVKcoHc4+ts3NRLNC3R01Z0l9/+IN8F2X85e7Hb0EikxOtdQIkSqnfQDaXq8D55z31HHD9c8zu8+HngP/3H2TOd10NpqkNDOOmFIqDsmXRHAQ5ymlx3Rp3kEsDoisLALVBVVq0pSlyJ3ZNu7LRJy6mIeG46dXrjue2kYVFuy3NDR/XqwgGYnJW1SYUn1FzNrsFtmzM9byUElvnqjZZnYYsnxvguDV5bjNbify/6TSUVWdn3KkJLE9lIYhX3lpSfxil1ImN7popy6oTclxJk2JRiBSL61fYXs2ol64lTJLUxbZrHKeW02VlUXRjVrmFaYjMh2W1mMcOg6H44PQnCW5UUMXOWgrG8WVTcj3pXje7Jrgklvvb0lynewylKTN7LWBpWw1NZpFmjniqGJo8t0kKh73xkrKyGIyEmhsGBW1tknRpzKCfsUo8YVv1c5pnQ9nYu79FOE6pCxG2FP2rgLoxmQQJSon5Vn+ciFpyZ6oWudJMOD8V+X2Uxh4VstlUomwgEvgiARNcWKHslqYUGrLt1dhOTdMaGG5NORVVhyx3KAqJhuKVzN8Z5+SFLWwpjQhWXvUpjgNMW4Qg3bMJ7cqmKUycLsoMHCGZaK3IS5u4cPEcoQHrqMGzammgzB3q3CbvIuR+lBF/aiSyKolIq4BcO1uDGC+SqLttDEy7Ic26eWc2GJqj4z5tIwu8YQvDMslc0qnPauWvG03dfkEcSwRiOQ0KMaIzxwVtY1AUFvqGh+NWNIVFFObUA5GBeX4Tc1FIhqFMHNpzGU5Q0bYGliO0ZX0gagquL60FZvd9X2Ye/UEqTZtaEfglytAEk5STGwPSuU/aurdt3bkdRX6t9Y90hfc3a62vAz8LfJVSylJK3UxjfRL4PeCBrsbiAN+FbBIvxG939wF89+cY+iuBp17WG+5w120wdFRi09AYVoPlV8QrkR7xo0JOWkaLZbVMdpY4bo3h1egW6axe2XKR9yraQDznm8agOXVJVx50YpBag9GrsM6muE69lmdRSktDotmyyDwCvxRr2S5Ed4MKz6nIFh5taxCOU/buP1lP37YbXKeSiKGwcC3p5D63P8VwZcExTE0+94jcQlJLUUkVi1Bm+5EB4yDFiUQksG1Egt13K1xbUjOLWUBdmgR+ieeIgoBuFXXXwJeXFuNJTF7Y64UwuH8hP3fpKq0VwSjFcWUhlZSORXoaYBoyxuK5geiCLXysoKIoLfqDlCKzGY0SLKsR10YlzLwolLSjY8t7blqDujFxHfFvsW3xnHHCEi8U2RbLbClTB6OzAtD74vqZZg6hK66jZ3bn6Nbg9OqQplXMEl+MxIBemIsWWmWjEQ23phWtKyeoyGJXpE2AMnUgMRn0MsrKwvck4gzdksE4IejnJIkHCvKFt+6M16ZG15LyMgxNOZWo9GaXfVVa2E/6tKWYnHE2J9iNGfXE16Tn59ijAsNpyFNn7dMSupLmTW5ElJXJaulTlBbhWA4CRuccSQuhV2JYLabSWPfGZInDYCf+rK+O0W32Z3bmVJktUa0pGmF+WEqd0pI+sME4wTBbBqF4zPS3E5rSxDDlMGNZDW1uYZhSN2m1osotURjwRGVbbxfiKmu0JKmLyk2y7npDiYZcvXJAaZywxHKbdcTc1Aazwx7toBLNwNbA8sTAzLaatSOoa9cUc5eyNqlyMduzwkq+H7crgoE7UuTXWn8S+AXgo8D7gX+mtf6Y1roG/jrwi8iG89Na64+/yEv8TeA9SqnfAwYvuO++mzRl4H8G/tLLm53grqvBuPee1ef+5/fQ62VkhU2x8MDUqIVF/9Jc5Fa6xrabKGMHt1fg2vXaalVrcYNsO+HHuhT5FMetyFYutIr+JKFpjS5yEC0qy5WN5matx+8k4n2nEh+ZEx9/O6XnF9StwWwWYpiSjtoaxWgNi9THMhscW+oTptLME3+t1ZStXJywWjfgZYVN2xoYhkQNZWXR8wuRFOmaCfPaoihFOXpnuOLq9TGm22BaLeXSxR9KBJZnzjrHvkg9sqXH/v6M01VIXZpc2JlyuOzhuxVJ7tDUkq4JulTNKnfXNYymNrDthu1+zCzpvHQOe0Tb0g9xdNzHsFqiKCdwKqrWIM2dtUabRiLSeuYxOLtY/+2UoakraZ7NE2ctvIiW9KhuFY4rGnRl4uD1Cjy3YvnEiP4DQpaZX++DpXH6hcgGLW28rYy6FqkS02ipKot+lHUCkLJYNrWxnh/AsJ9yetwDLdpaVW5JU67VSr3qpmhj7IsVws1FuLsuitzGchqJmrVaC5eCHFbK0sLqrgOtFenMxxvmnZunjW4Uo1FCmjsUuU2vJ+6VN+23m663y+/lZCsXw2rXtYogkBraYuWLQnVpYro1bWXAzEFNCmyvllSZRsQtPTG7Y2kzuDhfi3J6XkX18QHeF83IC3ut8DCexKwS2WwNQxP4JfPTiME4JssdaTBtFdWRT3huRXIjon92uf6Mk8TFDyRzUBQWYVAQxz6eL/00i5nYcN/0Grp+dYyqFSqs8YJS0rUzF3NQMujWhLKQaPDPfcnv8j+98d//oWswvdF5/eav/Zu39Njf+vf/zUbs8tUMpaBOLOLEpe5Oc+QG0UVJtcjCJ94adWlSxrIAaa1YTkOqSk72dWlKBOHUWGbTifGJkKJa2Ex2l9hWQ1FYeLacnHoDsdDthaIfNuknkkOuTRxLoofBmSW+W5FXIuUeRAVhKH06p4uQorYYhtlaE8pAEzoF4yjF76xj+6OUprP77TkFWeKKbXKUshPFDLvC63qh72ol2/2YpjaxVMs9Z0+IunkGo5S9wRLPqRkNE0yzZeJLSurc2VNuHIzw3ZLRUEQNB4GoEYzCjDq3MQxxS8wqC9euGQQZozCTgquh8a2KplXi/bGVEDgldWtw6ewxk2HMMMiwzAZTicVx2yph6RUWdWajooo0c1ksA7YHcuoOfLHrjfo55WFAUwkVva0M2i4qcJ1aKLCpeNTYFyQq8+0KZ5zj9GWBDYICPEm51F3HPUidzbNqquozpcw6t2lyi6YQPa/TgwGm06JrRS/I2d1aAuC7XcqtO981U7E/GI9jTEucGuvapNcTOXuJtkQgUimN61RkK49elK8VF5rWwAplMVWdYGbbpUSb1sBx5Rq7qdpsmC1tZTAYxzh2TTjIRZC0UVhOjWGIFbVtN7ieRCiBLxufsZNLSjXMpAM/qNArqcmYdosalN1YbVcvAh6KJd3ZiDeSMiRN6To17fVgfU36PakBuk5NXZi0rcLZS8Wyuy9RWdF9V21XIuxkKaoRuhPwrBuD1coXFW+tSI9CTpchdlQS7CQ4fsU4SgmDAmtY0HTyT00rWnpur7iNNZhbMxvbGI69BmAYGiuqiMICwxSP+t5ezChMceya6TSiyeXCCkNJNeQH4tuiunztTQkRw2zx7ArPqdHdSVApjR5W67SQbTdkpSxgnl3j+tValdaxJCIKvFIcJ60G1/qMyZGhtOTYrZqtQUxTSuTkdWKDttmwzDzyWuoR4yAldKW46zg1zZM92YQ6SXTbaKhbQ/xeSlvk0pWkC0FshnfGS06TEKU0e70VO70VnlNjGS2RKy6Gji0/Z6nodpluLYZOlUVaOTStIittmlYRDjJ2oxWOIZ3VrVYMfdlsol5Oz5NIre8X2DcjrMZkNg1FX8yphNlV2WRdLcE0W4qFRxTlDLdiXL+ibQzCMKeszbUtcy8UNlHv/JKmMhhPYnSrpAO+l1GUlthXOw2O2ZDPPEK/IOvM2Nb1Nq0wXVkYh+ME265JpgGDQFxBbVt6nqrCYjiJccIS3f2tglGKMlq8kagcW2YjFgqlML/cXkGauahBRZnZ2EZLeeKTHUmdo20Nyq4H5KaN9k2VaWMmC7ptN6SpqHt7XkXklSSHIf1BhuVL5Bj5Bfmpv/Y3MgwR2pTTvVwDnlOhViKN71hCWFkuAoxuw6pTC9NsccOSXiTMv6yyyKa+pO7CmnGU4vklUV/UsJOTkPJaiGUKZbiqzbW3zHCYkpfiXeRciEGxVtQIvBLPFiqy51XUhYltiFpEXZlyeOuIAaZqhdFYmWS5Q12Z5FOf/a25XCNhJk3UZot6OhRb61atFbhNq8V067VFRc/PRR37duLO9MH8kcddt8EADHoZVW1i2/XaD2KZe+LDPllhBRXjXkrTKvx+zoWHDskqm63xirPjOdNpxGCYYlktjTaYXhni9gomO0vqxoTEInRKps8MKQt7fRIsupNkFMjGdfVoRF1+NpEvsEumxz3R6YpS6tZYOxGe258SuiWncUjdGMxTcUisG4NBkJGU4mteNwatVmy/+ZAnDraZDGMityQpXWaZpKJAbAPiwmGe+ExPI5LSxTVr9vpLqtbkYNXj8sEWi5VP1Zhkpc2y8Cgri8Okh+tVJIXD2a255LIri+uP7+A7FX0/p9EG909OmGUBh0kPz6lZXB7yzPGEwKmYhAk9N+fKdERWWZwuReuq5xW4QcWNVZ+ytnjy6g5ay+LaNAbZ3GewvWISJhSlJSd7RyjFIFIuodstYoMU02y5cOaUujHY2VniuSLYaZotg62YaiVMo60zCznBGo3Izpstvl0JMeOaz6Wt007RQ/HwfdfXcyoKm61+TK+X0TQGe6Mlo32JYMdRyt5YUjpZJYV03yvFQsEp2O7H7I8XKKXZnqxICodwP6Z/Zsmgn5IXNt4gJykcHKcWd0pf6MW9+2aETknglHh+ye5ghedUTIKEnQuS6tsaJPQ6W2dvktG0itUsWNsYVIUlCsqtEpLFUEgCRWVhKL2WsM+e7uP2C/GZMVqyQjTSitJmsCsab+axQ9aRQGxLNm13mBNcWMlG2cnxl7XJauGTlxaBVzJ/dsD+cMEgyBhGGYHXmYhlHv1xIhv7UL6PVWXhedWaaOJ1FtnJ0mM4EPFa16uw+wWHs37HunTWytXtpU7upzvImIYm9EqG/RRTafyo4Pikv1ZXv13YaJHdJTCNljh1haWiFYMgwzJbVrEUD+exT+CXVK1B5JVkJwGuWVOUFmnpUGsDLxAjJgDLaHG2MponethGS57b+LsJSengH5iYdtOls2ra1qBtFJMgoe/l9PsZ+sDD7LqwDKWptZhizRIphrtWzSzxsU15nbIRL/a6o9SGo4wWxdGixzwOCF3pIdjux8JSMjVx7pCUDo1WXQqoJvJkk3PMBsMQxWjbbLg2HXJlOuLGyRDfrgnDAsepqbXBIvUxVct2PyavhX02DDJmSUDTGlzaOoVRKV/40sFULVeWQ04XIU3X02Hvp5Qrh9OlaJEdLPtrcoFt12SFwyL1CbyStlVM44CoL6f/LHfwnUqiAgXPHY+lCKw0vluxSH2UEhLC0alYCjtmw/wkEiVoqxGRyVpOuoFXsnp6yPmLJ+yGK9555kkeGJ2wzDw8sxYByXDFdj8muH9B3y64Zzhjux8T2eW6h2fQy7BUS5q5eLZEr5MgYS9c0XMKXLPGd0t2I1mI48QjSx3SysE2GgZOzmgk6UXHrvGcSvqdOql+x65JYnGiHHgZ9wxErfhMf0lcOIROyU5vRWjLpvr41V1GfsputJIerdpkNZNIxHNqhltxl1ZriXo5rlMTOBWLo2h9+BDjNmGRFZWFczHGshrcTuZferzE5M0wNPM4QJ1L5fM+Dem7ufRwLV2arpfHsFuK2CX0SvrDFM+R/hN/P+Ekjii7PihTaVZzSZkVlbWmxQMEfkHolixmgbA6tWyYpiPfx2GYfZbBW1bZmIamev+IsGP/mUZLFotb6m60ku/YPFz36AzHCaNeevsWHQ20+tZurzHcdRsM0NGBociFRVI3Umy+mb4InIrTp8c4Vk1vNyatpEBqWw1H8x6uU1M2pjBSTDmtuQ8vqFqD7WFMzy+YHfZw3zrFcypCtyQtJZKJwgLHaBi50uw4fHAqKavCZjYLO+Vd6YlYpOJ77rsVzz67zTztDKy6hrX9/pJk4ZOXNsMwY9JP1vL8AHllsTeUnL+hRNI+8Eo8qyKrbEZ+ht8V37dGMa1WnB3POT+eMe5qGUUphACtFTuDFTthTM8uyAubSSSSKzu9FYFdMnZTRiP5nWdJmirNxWL65NqQnldwZrjAHRRrr5AzgwWhWzJfBus0zVYU49sVPa8rsLeK43mEZTU4Vs1uf4VtNIz7CZ5VszdeEjolZwaigHwz5WegOTrtYbqSHjToTrGt0HF7TsHkgVO2/YR7wlMiMyeuHRyrIakc5ssAx5A0Zt/PmRa+yJtUNleWQ/JKDh2RWzDLfM6O5+yEsZhvOQUtiry2WOYekVuyLDwip2B/siAMC+aJT1y41NogdEqOl9Gaqr07WBE6JW63uA6HsuAN3RzHqOm5uUS3ZkNaSQTmmTVZ7rAzWVG3BsvCw7MrTufR2i/oZm3Cj8QLZ3WjxyRIKGoLM6ix/ZpJlHTvuaDs6ktKaTynxrMrssJhd7RiayDRRZK67I6W3Ld7Ih49wwy7M36LJimjKMWza6IoxwnF3dUy5fBUdhtp35e6i2FoiSwcYQAqpIUkzR0abdDzpH+pLeWAlRU2plezPYypG7GeCF2pE1lWszb5c982lQObK2m8i/unWKqlbEyKWggaAGVmEzolkyD5I88iezXgVb/BvFzVUK0VW/2YneGK0TDBNaVjuR/khHbJVj8mdAr6FxYSUTQGq9yV7l8/pUzkxGgozcgXmmjTGEyihJ5TdB338Ib7rxInLpbZcvr+3XVvQuiUHKcRj37q4rozen+wZByl7G7JidTrFQy9jDRzJJVntOyfnTEMMs72Fvh2JXbBacC5M6cMg890S4d2iWNJM6JtNbhmzVZPFv2bjXa1FkFA16oZuZmkk1qDeeKTlA5HcUTkFhye9Lm4NWWVSc1okfqsKlcWzsThNA7xrIq9YIVltDx64yyW0XKxPyN0CrbChFHULYx7SynKmg1nhgtMpem5+Vrk8J6dU+4ZTel5BdemQxyzxjFrokjmtz2MGQQ5dWOSVQ4XBnNmq4BV7hLasmkexj1csyZ0S87tzohzl92tJftbc5aFh2lodoKYyJMU07Lw2AoT6tbgU8tdfvlABGP7fk7PKTi/NeOjh2ekzlDZVI3JaRoy8lO2AyEEjPxUaltdRDnNpQv+KI146niLa7MhpiGNlIEtm4xvVTy4dUzkF/hOxbLwuH46wDIbksSTCKuUKHC3v+JMXw4JPTfn4wd7PDnb4iQJuTIdsRPGnEwjrs2G3Ij76+j76my4vua3RjGuVXNmsCDNHMYD+Swds8HbFi+gvLQYDlLOjuacxiG6VRwcDjCMlukypOcXuFaNYwmjraxNQqfAMFrOjufYRoNn1niOjHOcRJJutJquHsk6hXk468nGWNrs9ZeMwoyyNukHcr9nSSPkdhRz39aJqFe3Bq4ltbihlzHYjnndvdcZBDkXtqf4dsl+f8lxElG3BvvjBXuDJdnMYxIm7EYrktKh7+f03ZyqNSkai6o1mc1CBj1hSW6N5fCS1xbmbcxZbVJkr0L8QVRDhTVlSH7XFfvYRS4pqKK2WKQ+RWOtufk38/n9KOfq6YizZ6brIn9WORwvI2HkoNcnScdqSGtbGgpVy/ZbD5jNQlyzZuyllI1JuJVQ1tLQd5KEZJXIpqSZyzAUg63tYSwpGC9j4GX03Zy0tskqm2Qq3eyWajuKqjDYksrBUkLJTDJ3XTu5aSpmqpYbpwMit+TJg22uLIc4VsPAE3OqorYY+RmL3EcZmkXuC404DihKi4N5n1kWoCuDUZhymobkjc1xErHbF8vmuHZ46uoOq1IsC0KnpG5MVrlL0VgkpYNtNlhGy7J0mfgJy9zDMmQhubR9ytGqh9VFIzfTggMvIykc/C49tT2M8eyaw7gnciWenJw9q6JqTAKvlPRmZckJuFUsS5dV5uHbFYtlJ9SZRiSVwzLzSCqHyCmIu7/lzYbJuDsJT08jik7sUnWR0jL3hJBhl+t0aFmbDALpAfHtEqdbaE+XIUVjUbfSbJuVNrYhXvKRVzIZSjG60QZDLyOrHHFaLS1O05AysTm6PhRHUaUpW5PdLTmgKKXZ7y3lVN+Zzc2SgJGfMg7kb2taLb5TCc3dknRXVtvS0V9Z3JgP1k6XNAajMMO25bE3a06rWYBltixzcbustcE0DTjJQhyzYVnI55FWchi7SSxxTfFTcpwa2xRCy01SSF4JUSXwSkKnYHcidcAbcZ+8lOzBjWtj+m7O4bJH3cgB4XjWI7AkCo9LOQhNrw6Ypz6L3McdFBzHEc9NR2KHrjSzLKCsxSrZtyr6gxTfrjg4GpCWDofLHmVj3V7L5LuURfZql4pZq4YCKKVuqoZ+4nM96aauVVK6lN3Jc5769LyC1WlIUVrsjZYcLXrUtYFnV9SNwe5ouXYPTHOH6VHA9sUpp/OIorEobqoxAweL/poODKJh9tzRmK2RpH+KUk5PTSvGZHVj0Cg4N5mxyH1m05DxJObwuM/FfTHeAskpe1aN4dbC1Or81ZtWETgV1+cDJj3ROgN49mBCEBVEbkE/EB/1YT9lnvpSO+gWouvzwbq4q0JNVoiCct6lSBy7llz71QFNkDHcWdG0Bot5wDVLyBLSDyIWueNJzI2TIa5XMk+FZZSWwgQDOJr3UCPNwbTPpZ1T5nGAa0vkVTayEMSli2W01I1F2akTj8KUsrE4zkKSwlmfkm2roWpN5rkv/U2xw97ugqIRQcrtYYxr1ly+siPMM1McFBstdr2OpclLm6uxx7mdGYeLHlVh4XRmYrpV8jcdJ5wmIVku72Oe+5w+O8Ia5yxKadh9voaYa9edW2hNo4W9dRqHJKUUnudxgDOUdFLoFMSFS+QWHEz7WEZLXlnktUXbGmKjbWjsfrmmHl+ZjhiGWfcYhWvW6xRhUrrYViOLbiZF/VGYcbyM1gcnx66JC5flwscLSqrSoh/kpLmD0ytYZsKsiwsX22hQSsQ7F6lHuvChkghfKUhKB6ejk0duwZUbY9ygIj8OsMc5V2dDmlpSy3lls0i9NRkkdEtJjamWpHTJa1GyaFvpBWpzi8H2iqqVg0OcuaxyV3TptLH+DidHISqsWZ5EBKMUq7s2IlfeS1bZzOcBO5MVWivi0mW5CBj5GV5YCiGiFZLM7ZWKuT0v9WrDq7rRUin1p4B3v0DU7a1a67/+gsf9FeCvdD++AfjYF3Sin40t4OTzPmoz/mt5DpvxXz3jX9Rab/9hBuv3z+m3vPWvf/4HAv/5l/+711Sj5as9gnkxHuHv2zE7uesfA1BKfeCV/ANuxn9lx/+jMIfN+Hfh+Le5rebVglf7BvNyVEM32GCDDV4RqFdxpugPg1d1kZ9bVw3dYIMNNnhlcKsU5dfgHvSqjmC01rVS6qZqqAn8i5dQDX0+Xsod7guFzfivPF7pOWzGv6vGf20yxG4Fr+oi/wYbbLDBH3X0e2f1l3/xX7ulx/7Kb/79TZF/gw022GCDW4QGtSnyb7DBBhtscEdwl2aKXu1F/peFlysrc6fHUkp9beca93Gl1K/fxrH/hVLqSCn1ov0+SqnvVkp9tLu9Vyn1pts19suYw0Ap9X8qpT7Svf/vuY1jn1dK/Wel1Ce7135Jtyel1JcppZqup+qOQSnlKaXe/7z3+z/+URjvTl2D3WubSqkPK6V+/kXuu+PX4C3M4Y5dg78Pd2mR/67ZYP4gsjJ3ciyl1BD4UeDbtdaPAN95G6fw48C7P8f9l4Gv0Vq/EfgB7kzR8/PN4T3AJ7TWbwK+FvhHHRPwdqAG/o7W+nXA2xBb2N/3t+7+Tv8rQhK50yiAd3Xv983Au5VSb3slx7vD1yCIJe8nX+K+L8Q1+PnmcCevwc+Cattbur3WcNdsMDxPVkZrXQI3ZWVeqbH+LPAzWuvnALTWR7drcK31bwDTz3H/e7XWs+7H30X6h24rPt8ckPNaTymlgKh7bH2bxr6htf5Q9/8VssCcfZGH/g3g3wK37bP/HHPSWuubJvd2d7tjZ9ZbHO+OXYNKqXPAHwP+2UvM745fg59vDtzBa/D3jdLe4u01hrtpgzkLXHnez1d58UXnCzXWg8BIKfVrSqkPKqX+qzs0l8+H7wX+4ysw7g8Dr0MaYx8D/qbW+rZ/xZRS9wBfDLzvBb8/C/wJ4J/e7jE/x1xMpdSjyIb2S1rr932ep9zp8e7kNfiPgf+WW1s279Q1+Pnm8IW5BtEofWu31xrupg3mlmRlvoBjWcCXIiesbwL+b0qpB+/QfF4USql3Il/u7/9Cjtvhm4BHgTNICueHlVL92zmAUipCIpTv01ovX3D3Pwa+X2vd/L4n3iForRut9ZuR0/qXK6Xe8AqPd0euQaXUtwJHWusP3sJj78g1eItzuOPX4Bpihfr5by8Dn6uG9AepNyul4u7fe5RSWVeb+0hXI3voZU2uw920wXwhZWVuZayrwC9orROt9QnwG8AdKXS+GJRSb0RSB39ca336hRr3efgeJD2jtdZPIjn5h2/XiyulbGRz+dda6595kYe8BfgppdQzwJ8CflQp9R23a/zPBa31HPg1PneN6gsx3p26Bt8BfHv32f4U8C6l1L964YPu8DV4K3O4o9fgZ+EObDC8RA3pNtWbn9Jav7l77Z8A/vuXOzm4uzaYL6SszK2M9bPAVymlLKVUALyVly5G3lYopS4APwP8Oa31p78QY74IngO+rpvPLvAQ8PTteOEup/7PgU9qrf/3F3uM1vqS1voerfU9wL8B/prW+t/fjvFfYk7bXVEdpZQPfD3wqVd4vDtyDWqt/zut9bnus/0u4Fe11v/lC+Z3R6/BW5kDd/Aa/OzJcKdqMC9VQ7qlenO3Pv2OUur3lFI/8DnG6QOzz3H/S+Ku6YP5A8rK3NaxlFJ/tbv/n2qtP6mU+gXgo8il9c+01rfFRkAp9ZPIiWZLKXUV+B+QIi9a638K/N+BCXJqB6hvd/fwLczhB4AfV0o9hqQUv787Rd8OvAP4c8BjXQ0C5AR24Xnjf6GxD/xEd7o0gJ/WWv8+6uydHu8LdQ2+GJ4/Nl+Aa/AW5nAnr8HPHvfWGWJbSqkPPO/nH+vU4F8MP4wcXK8DPeBPa63brr74whrwW1/k+f8E+D+01v9SKfWeF9x3X/fd6QE3Dx8vGxupmA022GCDO4hBsK/ffv/33tJjf/GxH7xlqRglvVvvAP42cB/wS0iK85uAb9Kf7ZP15Vrrv/GC558Ce1rrqqs9XddaRx0x5ue11m/oHvenge/RWr/slO7dlCLbYIMNNvjCQ3NbajBKqfd0hfdHlVJneOka0supN99KhPFzwFffwuN+HzYbzAYbbLDBncZtqMForX+kK7y/WWt9nZeuId1qvfm3u/sAvvtzDP2VwFOf/03+ftw1NZgNNthgg1cKd6jH5SVrSLdYb/6bwP9HiZTSv33BfTdrMAoogb/0B5ngZoPZYIMNNrjTuAMbTBfFfONL3PcfgP/weZ5/GXj78371v3S/fwbwb8ccNxvMBhtssMGdhNbQvAZ1YG4BmxrMBq9JKKUmzyuIHiilrnX/j5VSP/pKz2+Duwx3ptHyjzw2EcwGr0l0neFvBlBK/QMg1lr/b6/knDa4i/Ea3DxuBZsIZoO7Ckr8T36++/8/UEr9hFLqPymlnlFK/Uml1D9USj2mlPqFTm4GpdSXKqV+XYkg5C8qpfZf2XexwasKGmj1rd1eY9hsMBvc7bgPEXv848C/Av6z1vqLgAz4Y90m8/8C/pTW+kuBfwH84Cs12Q1ejdCg21u7vcawSZFtcLfjP3adzI8hlM5f6H7/GHAP0lvwBuCXOkkTE7jxCsxzg1crNHdtkX+zwWxwt6MA6DScKv0Z7aQW+X4o4ONa67e/1AtssMHnxaYGs8EGG7wIHge2lVJvB7EBUEo98grPaYNXGzYssg022OCF0FqXnajgDymlBsh35h8Dd0SJe4PXIl6bm8etYKOmvMEGG2xwBzGwd/RXbH3nLT32Fw5+9JbVlF8N2EQwG2ywwQZ3GnfpQX6zwWywwQYb3FHcvVIxmw1mgw022OBOQoN+Dfa43Ao2G8wGG2ywwZ3Ga7BL/1aw2WA22GCDDe40NjWYDTbYYIMNbju0hnaTIttggw022OBOYBPBbLDBBhtscPuh0U3zSk/iFcFmg9lggw02uJO4Kdd/F2KzwWywwQYb3GncpTTljdjlBhtssMEdhAZ0q2/p9nKglHpYKfU7SqlCKfV3X3Dfu5VSjyulnlRK/b3n/X6slPolpdQT3b+jWxjnxzs9PpRSv9a97qNKqU8qpf7K53ruZoPZYIMNNriT0HfMcGwK/F+Az7ICV0qZwI8A3wy8HvgzSqnXd3f/PeBXtNYPAL/S/fxy8d1a6zcD7wD+V6WU81IP3GwwG2ywwQZ3GLppbun2sl5T6yOt9e8B1Qvu+nLgSa3101rrEvgpxLGV7t+f6P7/E8B3vPB1leCHlVKfUEr9/4Cdl5hCBCTAS058U4PZYIMNNriDWDH7xV/W/2brFh/uKaU+8Lyff0xr/WMvc8izwJXn/XwVeGv3/12t9Q0ArfUNpdSLbR5/AnFy/SJgF/gEYhV+E/9aKVUADwDfp7XebDAbbLDBBq8EtNbv/gIPqV5sGi/j+V8N/GS3cVxXSv3qC+7/bq31B5RS28B7lVK/oLV+9sVeaJMi22CDDTZ4FUAp9Z6uuP6oUurM53joVeD8834+B1zv/n+olNrvXm8fOHqJ1/i8G5LW+hj4EJ+Jjn4fNhvMBhtssMGrAFrrH9Fav7m7Xf8cD/094AGl1KWuAP9dwM919/0c8Oe7//954Gdf5Pm/AXyXUsrsNqF3vtggSqkA+GLgqZeayCZFtsEGG2zwKoRSag/4ANAHWqXU9wGv11ovlVJ/HfhFwAT+hdb6psX3/wL8tFLqe4HngBez2vx3wLuAx4BPA7/+gvv/tVIqA1zgx7XWH3zJOW4skzfYYIMNNrgT2KTINthggw02uCPYbDAbbLDBBhvcEWw2mA022GCDDe4INhvMBhtssMEGdwSbDWaDDTbYYIM7gs0Gs8EGG2ywwR3BZoPZYIMNNtjgjuD/D+AHJfOiFjTQAAAAAElFTkSuQmCC\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"print(f'Spectrogram shape [channels, bins, time_steps]: {spec.shape}')\n",
"spec.show();"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"The colorbar on the right showing the power in the signal is especially helpful since `matplotlib` always scales the values in a plot to the same color range. Without this colorbar, it is impossible to know or even guess the specific values in a spectrogram plot."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Finding spectrogram normalization stats"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To get the normalization stats, we have to step through the training set and find the mean and standard deviation of each mini-batch. Then we average all the mini-batch statistics to get a single pair of ($\\mu,\\sigma)$ normalization statistics. Note that normalization statistics must alway come from the training set. This is a crucial place to avoid data leakage. \n",
"\n",
"One small detail: if your training dataset is large enough it is not necessary to go through the whole set. Sampling 10% to 20% of the dataset can be enough for accurate statistics. However, since ESC-50 is small we find ($\\mu,\\sigma)$ from the whole set. \n",
"\n",
"To accumulate these statistics over mini-batches we can borrow and slightly refactor a class from this [very helpful post](http://notmatthancock.github.io/2017/03/23/simple-batch-stat-updates.html). The `StatsRecorder` class below tracks the mean and standard deviation across mini-batches."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"class StatsRecorder:\n",
" def __init__(self, red_dims=(0,2,3)):\n",
" \"\"\"Accumulates normalization statistics across mini-batches.\n",
" ref: http://notmatthancock.github.io/2017/03/23/simple-batch-stat-updates.html\n",
" \"\"\"\n",
" self.red_dims = red_dims # which mini-batch dimensions to average over\n",
" self.nobservations = 0 # running number of observations\n",
"\n",
" def update(self, data):\n",
" \"\"\"\n",
" data: ndarray, shape (nobservations, ndimensions)\n",
" \"\"\"\n",
" # initialize stats and dimensions on first batch\n",
" if self.nobservations == 0:\n",
" self.mean = data.mean(dim=self.red_dims, keepdim=True)\n",
" self.std = data.std (dim=self.red_dims,keepdim=True)\n",
" self.nobservations = data.shape[0]\n",
" self.ndimensions = data.shape[1]\n",
" else:\n",
" if data.shape[1] != self.ndimensions:\n",
" raise ValueError('Data dims do not match previous observations.')\n",
" \n",
" # find mean of new mini batch\n",
" newmean = data.mean(dim=self.red_dims, keepdim=True)\n",
" newstd = data.std(dim=self.red_dims, keepdim=True)\n",
" \n",
" # update number of observations\n",
" m = self.nobservations * 1.0\n",
" n = data.shape[0]\n",
"\n",
" # update running statistics\n",
" tmp = self.mean\n",
" self.mean = m/(m+n)*tmp + n/(m+n)*newmean\n",
" self.std = m/(m+n)*self.std**2 + n/(m+n)*newstd**2 +\\\n",
" m*n/(m+n)**2 * (tmp - newmean)**2\n",
" self.std = torch.sqrt(self.std)\n",
" \n",
" # update total number of seen samples\n",
" self.nobservations += n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By default `StatsRecorder` averages over the image channel dimensions (grayscale or RGB). The `red_dims` argument might look familiar from normalization code in other Computer Vision tasks (also the `Normalize` in fastai). \n",
"To average over spectrogram channels instead we only need to pass a different `red_dims`. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Building the dataset loader"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The setup below follows the fastaudio ESC-50 baseline to step through the training dataset. \n",
"It is worth mentioning that the files in ESC-50 are sampled 44.1 kHz, but fastaudio will resample them to 16 kHz by default. Downsampling like this risks throwing away some information. But, keeping the higher sampling rate almost triples the \"width\" (aka time) of the spectrogram. This larger image will take up more memory in the GPU and limits our batch size and architecture choices. We keep this downsampling since it gives the spectrograms a very reasonable shape of `[201, 401]`, compared with the much larger shape of `[201, 1103]` if we don't downsample."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
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sM5ssN/CcgqpWSR710E4SzkZrPrqcQAeH0y13/A1/5fEdXLeg52SMrJSvf3iG08vQ1BbfKjDUmrgwiTKLlydznoV90txgEsSoSkuYW7hGiaHWbHMbQ21ICoOpH3HoRPzlp3epMg2/nzFyE663AW0nKDYm/YMIVenYRjZvHF/zZDNg5CY8nY0wzIovH10QlhYtgvevJ9ydrNCUlveeHXAwCdkkNqra4hjyWmwRrFYer51dY6k1H62HlJVG383YphZ1rXI4CNmktlywNAqOVaLQsdp66EaNaVQYasN8EdAbJDhGxWwV4PsZhtqwSWwmQUxZq6xCFzpBszHonW4Zu4m8zncTwjqzqWoVzyoJU4s8NEHp8PsZQnSYWs0qdHnt6IYP//x9ytcy2lpBNRoOhyF5rVE3CmM3YR57BHbOwMz45jfvcvTSglXscNCLUEXL1aZHfu3w+heeUTYqz5YD2lZwOAzpdve/onS3C480NygTnZOjNTdrH9uqiNYOh4cbykZlvXLpMo3ekTzetwrWic3AzbheBTRbg+AoIo4tuUjUGwy9xtRqVKXDN3Pef3TEvTszHp9PMNyS9/++f+nJ3/jQ/N3RfiYGRf/DwOcZwz4FfnznniGQvcTeRrrh/9bdPr8V+P/sHv9R4LcIIUwhxH0kieUv79Kh0a6liwD+kY8d84nQjQbPLHi6HvDOfEpe69hmxf3xElOt6Zk5rlHi2zlhZqKaDU2n0Dcz0szgJvQZ+QmvfuEZrx/d8NF6SFIaXK8ChIDlPKCKDc6CDaZWI4S8EdLKoKhVDKtGFR2H0y1DL+XwcENWaWhmw3Xky1V3JyhKjapVWMUOSWGwzhxsvaJtBYODCNussJ2ScO0glI44ssgzg/hXZIhehW2VhO8PAJgOIpzdCl2UCk8XQxaJi6E2uHrJuBezWbrEhYlrlByNtwR2TpybjKyU4MfnTIcRs9hjMoroOqgalSiyGXopp2dLmkbBtCu4tnCtkldOb3CMiuA4xDRq7n/pnOnRhjg3cL2Ck195Tl3KQaerFPJaZ+ik6FYtI0QBy62Lo5fkhc578wlhbFPWGocPlvSMHFOrsa2SslGpapW2E9wZftuOT1MbTL1mdG+NrjUc96WH8zJ20bWGs/GaqRPTdgLDqGXE2grWmYOuNXhWgabKKLBu5eD4ztUB89jDtwoQcrV/2t+gnSYcDkIMtcHxCvxeRlIYhJWJ5+UM3JRtKhcur9+/5P5whWNULCKXbW4znweU5y6LTP5dXp3OaDvBPPRQRIeh1nSdwFAbotykKDUe34x5fz3BsQsMp8KzCh5fjjkZbLDNkt40Zrv0qBuFYZBwk/ic9TZYWs3ReINp1KwKh/OwR1hYNJVK1arEpcnhdMuZv2Hai6gbhbJRCTOLO8GGg3HI4+WQslHp2TkjP+HqeoBnyclxHnrkpU7bCcpCJ8lM5k+GmFaJZVaUlSYjpFKhrDS6TvDa8TVfHF8B0HczLK2S96suo8B7L1+TZiaLxKVsNOpW4XzZx9ZrylKj6WSmxB1kmE9Moq1NeCnvyZcO57QIjv6Oc44nG3qDBNcp2KQ2y4VPmpk8XQxvI7iPViM6U0ZwTa2gKw1JaaKqLSKoeLQYcbUNePVghmHUnD+aYKg1ll6zedYjXLlkhc7ITwgGKVFuousNp/0NL9+9xtIqAjNH0TowW+LYJnrc4+JiiGuWbFKbV45m2JMUU6s5na6ZDiIMXV4DfTsjzEzaTnB6tuBi1eeLD85vsymfJWSNT/vE7UXD51nj+1ngPwf+KlLKoCCjsd8N/BohxPtIp+7fvdv/LaSb/beAP80v1nP8r5BWOB8g28b8qU/7fEW0WFpN38lQlZbAzNF3qSBHq9gWFjehT9monPS3OE5BnJnUnUI/SOk5ORM7oag1vvno9DYqOR5tUZWW+6cz7t+94Rvvn3F1PSCNLNKVzey6hxBwd7QiK3WaVqbc2k6wXbsAqErHyEqZODG63rAJHUy9pm0VoshGiI40M2hbwXrjYhkVbi8nCDK6RuFovJGrZrvCtwq000SmfnbpxyfbAQ9fvcS2ShxD3sBRaZKWOtNpSFWrrGKHReQyWwUUlUZcGWxTC0OrbycByy5ZhQ7jQcw6keclREe6tmmCmpGTcB35uEZB1wmqWiUwCqKfmaAqHYZec7npcTZZoakthl+SlAZXmx6BlxE4OZvEpq0U1pmNbZUy+lFb5kufrNLYlhZlo9K2Cp5Z0HaCVe7gaBVVpfLR9YSy1gjMnDgzEX9iePv7BXbOoRuxTFxuEh9TrUlWDvV/NeF0tGZgpwzslLJRWS09nj0d8wtPj9nkNv0g5c5gja40eLaM9t5+dMxxf8s2s3j34oCJF2PpNSM34WLbA6Bn5HhWwTz1yGuNqDIpG5WmVnCMkodnM4KHG64+HBOmFs/CPp4hJ14ATZFpyYkTy3R2Kxj1YxTREW4cytQgLXWODjZ88OiQoZPSdYKHd27oOsE6cjgLNrz16IR1JruznPhyIVDVclKznJK80slrDVOtOY97PP3gANus2C48DnoRX3t0ymzpI0RH38xkJBc7HB2umc0CFKUju3Hx7ALfKqhjHdcuwJWDdv3fDvHtgvnGo38gvbSrVmGeepStxvyDESNHRl+eWaBrDare0CKoS5kODsyc623AF0+u8M2cYZCiKy2nozWBndO8mkCt4B7GbGKbdeZQtwqL2CPKTQy1wdJrjntb3CDntcMbml36fBU7NI2C0FtmSxmlna/7dB0kW5vBMEFRWgK7oGxVpn6MNcrIa51V6KAUCi/fvcazC2Zrn3DjcLe/JotNskrnOgzQ1YbzZR/PyxiOI3w/Qz3IMPySwMpxjJJl6tJzcmyjIswt6kZh5CYyFd6opJHFR2+dUNYaAz9llTtYZvU3MCJ/b/yg1fg+12/Udd2/3HXda13XfaHrun94x9hcdl33d3Vd9/Lu39XH9v9dXdc97Lru1a7r/tTHnv+53Xs87Lrut30/Gr4OQVbpWFqFY8gLZb7x2OY268LGNwrKQicrDKLCou0EPSdjlTrou/pPWus8vhyj2xWK6PCNgomdsF67dJ0gKU3u350xmoSQavQPIsygoKxUzjd9Rm5CnJuUjUZSGHSlgqnXGGpD3SpEpclhEDIdRFS1rGNZdskycjkchnKV3MjJr21ldNjVgrLWZJpFdPSMnMNByPa8x/V1H1VpKUoNTy858CPi3OSwF2Kqtax/NOptaq+uVBynoMo0DLWha2XdQVfkKriqNGxLfvciNihrjbLS6E1iRCN4shhiao1c8dcq+Y3DprAwvrIm2tgkmYkiOuaxh6nW2GaJrVcMvJS6UWSkZ5U4fsFpsMW3CnpGTvnMw7RlmkwRHct5gKXL82gqOSiGpYlQOnpBSl5pLBOXsZ8Q/eqEdeYgBFyeD0kqg1fGczn5tAp2P6P5e1bMIp+81plFPp5Z0hskjA5Dgl5K38rQlZab2KfrBNvQIbzy6Y9j8lqn6wRH4y1VqxKmFpZWkxc6QnQYqkyVq0qLp5e0nWCzdTgYRFwt+hhqQ17oBKchutawedLDUBqiSx/HKKkalbJRSWsdy6g5HW048bdyknIqNKsiKwyWkcvB8QZPL0liU6bNIwtdb7iMA/rjmOubHkWlcRH1yGpdZgqeBLd1tjQ36Jky4u9UuVgYHYSyBqu3BL2MplUISwtXL2lbhTCz0KyaPDQxpylVLc93dLwlzkx0qyZdOpQ/KiejST/m0I9Ilw7rtcty6zLLXMzjhPcuDygqjbCwcM2SnpNxvQ7wA5nKvYoCjvtbwlJGPZvYpmdldJ1gsfVoa4XeJKIoNBy7xNFlJBouXIpSp29nWHpF0Wi3Nd3pUE7CUz8mTwxOjmTmINo4eHaBqdeQyXukblRsvaSo5TkOvJSs0hECzDsRUSEnKsOoOTlckzcahl2xSh1UtSWtDF49nLFdeoSxhWcWdK1CsZbjzeLDEXFuyHNDZoxs49uT2uOnU+jg+NUZi7fHZKXO2E5Ic+MzGZ+/c7zcszpfALSt4NHjKddhgKHVJJVB1wjSUpekhlalF6RMgpikMGQRH8FpsMXWSwIzp2xU+sOEgZ+S5Abz2OOr791F0VrWmc3yrTHP5kOixOLlVy/ICgPXKskSkzuDNefLPj0nZxG5vDaZcXS6xrMKwszkMg64XPeoWpXZKqDvZqhKx8BN0bWG61XAw/ECv5fRJHJQHfkJIldYfX1CvkuxRJXJwMy49/I1/XFM1ag0jcIs9bjc9hh7MbPII8wtbL1CVVry1CBJTe5MVnLAGaQ8XQ84HmyZhx7XNz2SwuBouKUoNQZ2iqK3LFYeeSjrG8FRhGVWFLXKk5sRPSfHOZKRSRxbiFCnqiQJwTIqLtc9enaOIjo2iaybPScZmXrN21+7C8BN4tMOSqa9CM+UaSo6CKycdeLQ7yVEuSknm5WNqdXEsUW0tVGVlmGQyvRTkPDjr3+Eq5c7opAma0FGTd2olKXG+ZMxxe55zyzxzIKenfPh+ZRtahFnJlfbAKG0KP7ut6s1AjtntvFZxQ6OVTJLPEZBQpKazDOXNDbJa4280VgnDgejkMubPm+cXBEWFqYhyUyuWfLqm+d86+kR7lHMOnF4/MEh89gjKU2aVlC1KpvC4sgPGXgpx6MtjiUniazUeef6gOkoIikNDidbfLvAVGsGdsrR4UZGya3gxN3y8GhOcH/DvdGKq3kPXWtYZC4DN2VwFKJpDWNHZg98L0dXGg56EYroeOfqQEZ0gOsU+MOUl8YL6kahqlUMtWHoyS5N/UOZ9gbYJDY3sY/RK3j99BpVbckqg4GX8uU755wONuiKjMDS0uDueEWaGVxuere16LGVcr7uY1sl88TjahtI0plVs33aw3MLbL3i0eMpWa1z9+4cxyqJS1OmOWOXJLGYpR6q0qJrDSfelv4wYbbxOT1YM5nIqLhuVE4ezCkqDdssWcTyGMcouVkElJWcBCZBTJSbqEpHz8nxjIKqUem5GQCWVuMZBY/XQ+wgp9uVMxS1xRmlJKXJa196iq41XDweywW31pCVOo+eTRnYKdOjDbSCvNboJgXHvS11+/kN2W2nfOL2ouHF+0Y7CNFxcLJh4sUkpUHbCQ7GIY5RsUltVqmDEB2X70yJI4tTf8upv2WeuXz06IBl6vL4akyaGfhmThGbNI2C5lQ4dsl25dF/Y8lkEGFbJbPYo1zKyeVgHHIVBShqR5iZFDOHeebSdgJTrakqjaGdomkNs61PnWi3UROAbxUcDkNaZPE8mMakoc3Vssfk/gr15QjfzVlGLlWjsshc8lrnyJfF8/uTJUkhU6Wa0pKd+4SZxfznD2QUpXY4dskycVlsXaLI5sFwyZPrEV88umI4jgFISoNJL2aZuggBrldgeDJqy0udviOJKeNBzHzh41kydXP/cIF/d3tbTzPUhrPRmrySK1bfLnDskpPBhiw3WN0EHL9xg6uXDOwUBJhqzSzyb4k/T+ZDoo1NVsjPPd/0cccJYWYx6Cd0hYzoilqlrlTCzOSrzyQn6jzu8epkzrPFgM3SxTVLNK1BGC2OXXJ+MWKd2MSFydMPp9heQdNKsoZnF9hWxcFIRkJ5oZOWBqejNY5VcuSFLJ8OKGqNs/Ga603AycGasZPw/rMDDoOQ2dqnaxTWhS2vt9imTAzJTBUtXpAD4Bglb77+lJdHC64fjzC1hmUka7KPFiPSUsfVy1vSS2DnWKZMo+eVzrEX0uyiuWeLAaZa8/hyTPpOn+vUZ5PZjN2EuDQZDWLJLlUaBmZGFFsEdkFW6wzMjCQ1aTqF+/4KS63p+RnrtUvTKHhmiWuWRJWJaUiGYlIYTJ2YMjLIcoO6UTgebBGi48gPKSODtNYBOPJC1rHD27Mpj2/GLENZAjD1GkutGQYpVa4R5hZfGF/x9atjAMpKo9llOk6na9p3fEb316SZga42vPLwirQ0ePruAeuVS1rqVLWKbxWoWsOxF0pGLh0KHZ5ZEHgZZa1RtSrLpwO2f3FKXBjUlYqt1xh6zbPlgKLS8IOMwC4Y92ImdsLISxjY6Y5xCgMr49gPCS8Crp8MuY58AjuXCy6rRAgkk/TrAYt3x3y0GGGoDegtQ0dmQebzADvIWaYucW5wcrLasUgl+/Q87KGIz77G1+4jvhcDbafQdXC56d3S50215ub9sUxJ7Va3x6/N8IOMdWGTNxrz0MMbpxy4EV2pUl86bHKb6XTL3dGK+9MlQnQEg0TWIK76RJHNwM54+PIVq1jWVapapYwNek7O9N6KAztmYKdcbnoM/JRnqwF1o1JkOqpdU+wo2GEmGYqzjU/dKvStjCQ2Uc2a6SDCNqpbyr1p1FhatUu/dBhKQ15rFDsGW5HrPFsNCO5tUETH4EtzdLVhMojkd7BzdL3hcLTl3dn0ljG6mvtM/YimVSS7NHLo2l0KaSvTl7Yp03hHfoilV6hGwzpyyAudReIShTaa2jL0UuLcZGyldB0sMhffzNlcBuS1ThkZKGaNqcoIYZ052F7BJrNl9Ks2dI2Q0o1Eo20VLt6fcNzbchBE9J2M5cJHDwriwkAIMIyaIjeY9GMCIycwczTR0jYKD89mrCOHItOhUNgsPIaTiDS00JSWw7sr8tTANks2K/c2Mlv/xQOi2JKRt5OwTFzKSmNT2FgTOWglpXkb9SSVgWbW5LVOz8+YTLcUlYZ5kqDqDW4vwzVKlplLXugkG5tN7GBpNTeph9orKXZEniizqGspIYlKk3XkUNcqcWGQxCbLrZw4BkbK1I2ZJx6now1Fo2G5Jd1ZLgkcnSQXeUaBZxaMvRghOtaFTEkK0bFOHNaFzcEg5MgL2ZQ2T8IdeWokiRdXb0/pWRnbXUr3OeFoXdiYvQJVbSkLnapVOeqFAFj9XBLGgoR55qKqraz7mhWK2tJUKo5R8uFyBMDD4zkvDxbkjY6iyL/dJIhlSr4TxIVJdSenqmXq+8iJeLYa0LQCfZJzON0iBGSRRdUqOHZJvGNSP5fvdJ0gL3Wur/pyMjFa2i9HbJ/2sKyKAzdiaKc4doltVGiqlJUcuhEKcjxpWgVbr9jmNmmt885sytGDBQ9fvsLUGnS14agXUlUa6VM5EbZfjPEfrhHITIYVFNyEsk7oBDmK0rFdOwR2wXzrYagNRwcb6lahZ+ecfYzY9ZmOmfsa3//woSsNaSlz4QdeRFyYFI2Gcxbd3qjXkU/TymLyJrXZ5pK9eNyTaQ+7nyEOcupG4cgLGVsJy9RlYGdYek3TKZyeLmnXslYSFRaHvZDr6z6mXnP/bCZJInrFIncoakkHTwqDPDbpuxldrfD66TXHQYhtVuhaQ17qHA+2nK/7LBOXg3HIqJewjh1mWx+A7VyyAJ/8wjFRYqGrDYGe45kFea2Trh2OJxtenswxNZmGmi8CslLn+vGIJLFYJw73RiuWkYttlpIin/gcHm7QlJa80FmGLi8dzDGsmqOTNbpfEuUmZaVxvQr4aDHiehOgai1C6VB31P2zwxX5t/qUjUoSm8wyl76dERcGT+bDW2o3raDfT2U67YNjwtQim7loasts6/P0YoTdzzkYhaiDEkOv8U8jLrc9zpcDskoSPQIvx7cKrB05p2uhqDWexX2+9d4pYWXy+omUd0z7EbZb4h/EDCcRplYzmkSS5BI7DIcxti6Zuse9raxh/apr+kFK0ypSb7XTJs42kv174EeMnISr8wHnlyOKSsN1ClSl5SyQKUdDa7DMipGfkKwcVCFTfKMgwQ5k9PYs7HOzDhj1YzYznzIxqGs5cLtmSVoaTPsRnlNgqA1tKc+lKDX+3Nff4GLbY+QkJKWMwGyzwrJL6k6Sg6pGZZU6XKz6XP+FU8LCwtYq5msfVWmxjYrzRxMWocdVHJA3Gl8YXXHkhTsdIRy/ccPj5XCnw5QMWcuo2GYWjlWSJwaTgUy/Pp6NePdrdyRZxZa/R5SbPBgueX08w7elHOjB4Zx14kjph5mTVgaenvMzH9xn4GYEXsbFos82tW/JHYreEkcWtlXy8xcnjPyEO70NhlGjqw1xYmJ6BWMn4fXRDXWr4OglmtpgqxVhZtF1MJxGklTUz7g3WjG5v2LqR3zjyQlPlkPyQicuTJbXMtoKS5OPtkMAns2HLEKP2dLnJvYpU8kruNrKEsvAzJhFPnfGKyYvL7leBXh2QVHq6FpDWhk4VimzIH6BupNJPDiZM7BTjgdbskqjv6ttJqXBk+XwMx8vu05Qdeonbi8aXtiJr2pVRl7C6wc3xKUJyHpDYOecDTZ0ncAxZN1mmbgc+JEUjHaCeeKxLmyO+1u+fHZBz85ZZC7vrycEZk5UmixWkrARZhbGNOMbj09uhbmWX7ANHWaRJEesE0eyHUuTm4s+p/0NP/byI5pOYPoFF5FkBLY7Jlvfzag7hZfGCzyrYJPYhKkFwP3xkp6TI/SW9cpFHOQcDbfyhogH6ErD9azH0Ymc0OpO4SzYsEltppOQ5drDPYw5HG2pKpWrSJIdBnbG9TbgetbjwI0wlIaj/pZRkLDJbepaYZtaDIOUo0CmjDy3oLh2KLYm+dqiLtWd6Frw5MmE0x89Z+wk/NiDx0xtuWi409twPJILi21qYQ0zosSibhXMfsFhL0TtlSSF1LedHq+Y9iKpM9ObWyq3sZuYqlolMKXkQRMt68TG0itstyTNDUy1Rg8Knq4GbAr79vpwzZKxJyOItNSZujGBlWObJXmpM994nB2tbg0J8lpDV1qKtcX1VtZ6llcBZWhI2UGjcRkGCLWTzMfLPkWpM7ETvvbuHRaxx9hOsLSaTWJzeLwmr3Uso8LQZErN0GsWaw/bKjG0mv404vBgQxUbpJnBMnRJc4Os0m+/x8O7N6hqK9OKlRTyX6z7GFrDR6uRTK/rNevEYR56OHpJlFn03IxWB9coebbuczja4uolN5d97j24kYQoTaYe/+tvvoGmtHhmQVlJJqgiOs6CDW0rcOwChY6BnRFYOULpiHKTrkMuEE4T+m7GfO1T1hpTL5Zs3ValZ0kd3k3ko2sND4dLAkPWEq+zAASynvrhkDoyKDZS4jFyEoZBQr+fEp4HvHl0LYlBrcrEi8lKHU1r+fLRJfPEI60NAqOgamVm5S9d3qNpBenWJowtokxG61ktU9nLxOXscEXfzTgbrjnxtwwPQjyjYJG4bLauFJQrLYGTE/Qyqlrly/fPKRuNsS/rh483AxSlpWg0Zk+GjHuJlPbsrsHZKiBKLObvj8gzg5GbUNcqRaORVAbny/5thJrXOvd6a37o6LvKmP+m0AFNp3zi9qLhxftGO6hKyzpxeLQe3gphs2t3VwfSuL7pcehGkgVZaRg7lxNblzWsnpHLwSwOMNWadWJzFmxQlZbVB0MUTTp4uGYJAoJ+iq40aEpL382YDKQuyjMKmlawzB2aVsEdpbdsP1uvOOhFuEbJh7MxB17ExbrPxIm5WQeUrco6djjsSWLD2XDNxbYnB8VhgqJ19PyME3fL2Ekw1RpPL7l/MsfRS+zdyrhsVAauTMHZbsnUj3D0knJuy1XxzuXDMmXKst3pyEC6sKSljmHU9N2MTWKzSF3qHemlf3fL9GiDO0qx7JJw5VLWKu4wRVNaAr1gU9rElcHmgwGWWt8uMGxTuokIpcPTZT1tmbh0rUwVX817XM77csDe1duKUmPqR/iGTKkFdo6hNLfp3kkQU9Qax70t015E35SpI9us6JsZlionTH3HGJ2tfNpWYZnKayP6YEBg5/heTlyYhIVFz85ZrTwWWxejV5CHJm2rYPakxi/aSt3eoR9xeLSRQuljWd96PqHnhZysDK3GNivCzJT6v7WUlYQbR9bczJpw7VA3KnWjkpY65rWO5xYcDkK653+T3CApDNLKwDQqJnbC5O6K+/0V450o3DVLRk5CUe1S35lOVJooiqwpHf3KCymaN0suroYEesHZnQV1p1A0GtvUQhEdD+9dkzcarl7i2gWn7pZJEPN02ycKbZle1hoeX0yIC5PTgzV9JyPNTJpLh7GfsNx4HI039KxM1q8KkyfbAe+/f4yhNwR2znbt8N5iwlUcsIhcyWS1KwZ+yvGrM8x+jtC620jJ3Im89XGOpVac+FuuwoC6U1gsfQy9ZpbJNPA7sylprWOoNT0j58FwKd183JLAk4vNdWIz20p2bZYbZKUua+U7Cc2BF0l2bKnTFCrL1KWtFepd7dc1ZTrV0Ut5LzoFptbgW7Jm7B9F5LUkU702ndGzMnpBSuBJmcOoH3O57tHfpct9veB4tJWuMnRYWoUmWkZm/JmPlx37iO+FgK40/NjxE+pG4dTbsty6HD1cyFTfNqA/StgUFhdfO+LOcM089VCFXC13neDDxZhlJAfDZeqiKh0XUY957KEdZihKx4fnU469kGkvQggoGo3rMODIC2laQWDnJJVBUeiYak3fysif+jzeDuTK1E4Ic4t56HEy3PBs3ccyKpLKoFqbXEc+ValxuelRNwpPlkPJApsPKEoNVWtwjJKvnkvDm3niAWCoDYEho84P52MU0eHqpXTcaBRWqcOHlxN6Z1s0rSVNZUSc5gaKKr+nochV/WmwJS8lFb5sVDy7YBvZ9HsJj94+pt3ZXfWcnCwxGU4iToOtZKjVOm/NDvhoMWJsJbz5w48JK5Oy1igqjbNgg2/nNJXKPPWw9Ypo6XI02WIaNZ6f43mS+DF25Eq5LHSeLQe4eom3c0N5spG/xyqVUY1r7kg2vlTK/NDxJWfBhvdupqxy5zZSTyuDl49nt+SIvpkxenXBNrXYrqVLzyaRrMCDcUh37vDKwQzVanCskkkvRmQqJ4drSVLRS+73lmxT6bpS5DpPtgN8J8d1Ci6jgKcfTdlsHDnpiw4nyOk5OcNRzGrhY2gNX7x/QZiZvDKek39jwA//ne8CYGsVxcImSSwss8LQG9axw9BJuUplCjws5e+rKh1ZpXG+7nNnsOal8YKDcYhrlLLuWkrGqq40rEKXk6MV37g+4vxyhKnWOHrJ2Jf3iKeXOFrF5bbH1I15FA1laeAyoNtF+avYIRgkHHgRutLI2pRRQwvXyx66UbOKHTSl5Uem53im1M2++soFaWYw2/h0reC1yYyJE3Pc37JKHRSlpWfJSUnXG968f8HLowXz0GMeejKF6mU8i/u8u3PzMdWaoJ9yt7/G00s0peXOcM0H1xOS0qRsVbkQLVSGfsrqqdRS2mbFYS/k2A/58smFJHTtyFWBmXOx7REXJobW4A9SZtc97h4uWT3p49s5Iyfh6f/vDnFpyoV2oVM+tw5sFU77G5pG1hjzRl6vVa1i6xWBl3Pib5n0Ylyj5PxyyDtXB/SMnKMgJDByqlbladTnT//Mlz+XMbNB+cTtRcOL9412qFqVvzo7Zeil5I3Gl04vuRessPQKxyrJCkkbbiYl7z89ZDbr8bC/YOilpKWOZUqHjIf9BQM7ZezFfGF0xVlvw8lww+uHN0zG4W1dKAxtNokkZFwnPodeJMW4jYrvyZrFMnF5+YeeodDx3nzCedhj4sacDDbMIp/7wxW61khPwH7BoR/xyvENxdJm+f4IOjmp6YaMWhy7RFcahn4qo55CZ556fPgzd5lnLoZZcdzfsswdLrc9Bq6sYUShjWHVpJnJ3dEKVW94/MEhx33pMiNEx1vzQ5apy7vzCXWp0aQaaW6w2Tg0NzarpYdzElFWUiO1DF3aQtozffMvvkQc27h6Sd1IgsMid/lgMSYuTVyjwLVKPlqNZM3GLuVqe+Nj96WbR1VLl5byq4PbKD3NDITSUkYmeaNJEbBWYek1da1iapL4sEmkzOG9zYSwNIlrg0frIa8d3nCzCFgkLse9Lc5Oo/UjZ+csI5dvPT1CUyXdvdsabDeSqPRguGRgp5gPQt6fTeg6iFOToZXSv7ehZ+S4eskqt9mUNpYhHTuOJxs2z3psti7ROwOaTiE4jBgNYlTRke30WI5est64KHpDtLV56/yIsZ/wjWcnDL8y4zzuYWk1H83GnD6Y0wtS0szA1ivqWuHpfMgqdlCVjmXqMl/6t1G1qdfktcb78wnL0GWdODx7Oubypi8p+ZlFz8+4eDTmqBdydLjm2WqAo1U7kbvOMpfCcCE6rqJAepR2Av8w5tUHl3Sd4CCIsPSarNJZpi51pfJguOT0S1ccjTcYu6zCk9WAdzZTmlaRNnaRT5VrlEub1+9dcRnL1PvFqo9nlpz0t2wym/xRcOtt+mgzpAxNDnqSpJVkJm/0b/jlx8+YuLH0ZxUQVwbPwv6tF+8XTq5ICoPHyyF3/TVuL8fQan7shz64HTceX0woW5W/8sE9XKPgwI24DgPeeXoo0+lKS7iQDO3hNMJQG3pnW9LS4HzTp309AeCDmwl9N+PhYMnVpsdsHrBMXUauZIImlYFtyJp+WWvyev3jL5FVOo+eTDk9XvHK0YwPlyPON5KVe3E1YOrEKIPiMx8vO/ZyhhcCys6/T9bXJKvvWdxn7CbkpUbPyXH7GdNpCJmKcW5Qthqa2jDx5KrLNcqdjZRM+2WNfrtSs9SawMrx9ALPKjkYhXhWIZ1JrvuscoepG7MMXbYbRwpd9ZpF6lI2KpMgZujImkK5E9imtY6tV8SFyaQf884Hx7z95AhjmNPaLb6bo6syFWmbFU2jEBfmrQmwZxckhcHxVy7RlYaRn1A0GnWjMnITVKWlb+Ry4FVbaYGlSOLLvZeuefRkiqVVrFaeNHMWHdkzH9fNOTpdy9qiAp3V0sU6mirTuqvYQdMapkcbxqMI45UtZ5MVbSd4dTpjlTpElUnXCcZ2IlfNakOampQLm7YVHPe39L0U05CDS1FoeFZB96UIU6+5CX30XY1veBBK4XYpGabLrcu4F9PszK7bTjBbBTh6yTa36RsZX5xe8d58gmHVmFrDInV5thxQdwqrwuZksMF0Kopao2fnqKOC8TDidLBhXdhEpSmj3lRH0yVJJSpNWePSKjaFTV7rXEUBAGFhycmoLyMG9xVpbeeassamqw1C6WhbybT0/QzbKaEVuG6Bq5d0Ldh6SVbphJmMyid2wpEX3rr0qFqLpjcM3EzWZtUGP8jIKw1F6fCtgstNj7ujFT03o+dk2P0c06l49mTM/fGSIy/EGmc8nQ2Zb6Qsx9MLilq9NRXXlBZLl1mLoZXSczKaVhCXJnFmyt+n0rhc9+g6sGwZJdo71nFZaXiWFMEXlcbYTigbqf9jY+AexkSliaOXfOvZEUM/pW9mxKVJi2Dw2pKRn1B3Cputw/AgvDV1bhqF97YTFNHydCXr3NtH0izAUBtWscNHN2PSWr+dPDXRMvKSnVVcyypz8I2C6XTLxbbH4cGGZeLy4XLEyEsYjyK2iU3dKqh2LcXmuiwl9OycZGtTNwquU9C3MqrYoKg1PlyPGAcxqt4S7Zyh2k6giZbzmwGrpcc2tcgqHf9Xz/DMgqOTNYvQw9gZzluGHBNsv+AqDgh62Wc+Xu5TnS8IBB1FrfFguATgJpNpwLefHFEUOsutS57rUvR8tmH4y2aUjUpRyXRl2wnu+msuk4C+kdE3c65TH0ereDhc8rO/8JCkNLlOJRsuzCyqVlpfmZ6s4Vlqza95+A6DgVwFPqc+a6p0aqhbhfOrIcvIlRZQlSQuJIXBfONhDXJOj1ZoasO9BzdEqcXTD6eUoYlvFIRzlzCTxsaP10NcQ6b/FDqqVuXieoAiOr4wuqJn5pJtlvrMZz36jjRP/oUnx8zXPqZW88ZLF7QIDLviqL9lNffpPdjgmpJssU0t+r2EwzsrhndkLWuT2Bh6TZ4ZzB8NqVoVVemYRZJ1eh37WLpkt3W/4PO19+5w7IesE5tXjm+Y3l0hdrqk54y2uDQ5Hm1xjVKKg62C08GGl8YLbKtEFS1ff3SKpja8dX6EY8vJIUoteo5MHd47WMhBsROktcHjcMjpYINrF3QdHLoRQulQhNyutgF1LaOaTSpJMJrach0GrGKHi7cPcN2CySSk3gnzny0GaGrLk3DAbOMTmDnbjYOly1Tq1I957fiaplDZzj1JjNh6FBfubQeBspA1n6wwSG5cJtMtd/pr8lrjh++dExcmD/tLBm7Gg+mCn//Gfd65PGTaj7hZSyF3YOeEmSSLZKX0Qo1ji/v9FeVO16iITqbQPprgWCUdoLk1710ecJ349N2M44kk0ih+haVWvDG+4fw9Kea/igNGToKrlzzdDIhyk4Mgoqyl6ft643LS28pMiSnry3/l8R3efe+ErNB5dTqjbhWqSsU2JHtViI44N3nw5gVdBzfrAEerCHopR17Is20fU62JUotjL0RXGykT0Rup9wTCzOJouJW6RaXmsBdStSrGcUJW68xmAarS8oWTKx7PRwy9lINeRNmqlLXGcX/Ls7hPVujUncLNRZ+mlXXtaGtj7DxE15HD0E9JcwPXLei7GZc3feaJhypa7pwseGUy58SXLOCH965Jc4NXh3NGVoq6cziKcpOPHh9QNBqjQcz9kznlhUuaGWx2WtLrmz4ng42c+NSWzdaVPsJuhqHVFOXn453ZID5xe9HwAk98Mh311vkRmmhZRC6K6JiMQ45GW3p+huvICCneraYNteFOb8PATbG0irCyCIyCn/ngPnUrC/6K6CT78jCiZ2VklXHrXtF18Nqda944uOHqpk9a65Stxmrm31KndaW5pSV7esloHDHwZOoqKQxWK4+ek/Pq4Yy2UfCNgrpW8Q1J+/YPY6ZHG2aRx9HpmraR5xXYOQe2dPlfpQ7LyKVrFbJK5yoNCEuTWeTz7FuHTA+2LCJpsNu1gmZr8P7llECXKZShl9J0Cv4gxdIkNXydSO3bc7KLEB1jP8E0KsKtg+flqMOScGsTzjyEkFq2wMpZRw5prTP88Rteun8tSQZawzpzdulh6YHYtFJXdehG2FrFwMqoW4XZ2qdq5Kqz6wSBldNVCucXIw5GUiemKw1lKmuputoQ5hZVo5JkMi1aNSrXYcDQTgkzi7yRUb+p1mS1LqORWtq19Z2Mw9GWrhN4VkFgFyjTXHqIXvcRlxbbhYeidMSpyezxEMOQ7kCGXRGmUt92E/pYmpS1KImKp5coakvXq2WrrPcC2kiXrZVKdafd0wiMHENtKBv11iO2aRXpvWnJlkFNq+zaMEmD7nuDldRwlhpPZ0NpdZfbpKWB7+W8940zHj+bYI4zKWt46nEyWdM2MiV6/cGYotKw+tITtm5V2k7h1TfPqWvJvlxnMnJ3TSnGtjT5PUC25vK0krPeBiE6osRiPIjpHcm/j6FI03jLkp6UhtpgaTVvHNzwdDGUUge1Ja4Mhk7Ko80QTZUdVPpuhrYjqw3MDN/NbxnT0UbWdZtcI6ottrlNmFsc97dcLPrcOVli7VxkqlRnsXVR6PC1gjN/Q9XKxa5nldKOza1lxLpLzSqikyJ/P5X2ZZmUISii4+xodUucU0XLtpDXFYCl1oyDmE1pschcPKegrlRZXrg7lyn3lc86c7BOYxxbGuY/n0STUroAnQUbXju+pmdl3CxlNiGLrM98vOw6QdVqn7i9aHhhJ760MCTNe7LhOvMZ+wllre0czy3C2OLAj9DUloeTBfONx8+9fY+01neTlBw4toXF4XTLtrSYbXzeX4xZZC5HgUy3rRObxVJquQy1YbMTst45XvJ4OeRnL+9iBQXH/e2t2LaoNNLSYF3Y6EorSSelymEQ8trZtUzNLEdUK4ukMhgFCavc4WSwIdrat84NhlYz7sW37NRVYbOMXO7210yCGN2u2Gwc6k7h8eUYVW2ZvLxkNgtkWxY3w/JK7r98xf3DBe+vx/R2gu+RlWLotWyrkjiEC/fWP7OoNCytJswt8lK2JYpjizvTJUEvQw+k5+HlrM8icfnyyQWWWvPD43OppdQqslzn+rovmaKpfdtLzbML8lrjvfMDfv7DO+SlxkuHc+axx1vnR4zchKQ00Zwaw5OyB1WVPRcVTQ6Uq9hhdtWXqateRFIZ1K3CwJVM03ujFc9WA2bzAEutOf9gyia2OT1YS33nZkf6iBx0tWGbWrx2dIOuNDy8d435MOToeE3fS1GUDmuaMvUj1olza4llajWOVfJoM6TpFKzTmJ//xn1ss6I3lKzL+qigdxxy9cEYz8tvvVKvU5933zklrgwU0fHRdsgylAs3d5jSrg1u5gH3DhYc9kKOnIiolE4rZWpgOyW6Xe+i75amUfDvbdGvDYZeKg2PX11yvQ5khLtxsI4SVluPppY9E3/u8oz312PqVk6u88TD0iqaVuHE3/LqcC7Tm7XGiSsnt0Xu8Gg1xFRrpn25MAwfSbLYedzD1UusnYTo+umQoZViKDUnQ9m+x7ULmk6REduuvLBNbMpG5SLqMXBTylaSQaJnMiuj7Cbe3igmLC0mrjSKaDoFz5UTiRCypn7vdM6kL/1W54XHVx+fkVc6cW4SphZ3+2ssu2TqywVk9zwDkNvMLvs0ncLdwyXrDwfyvo/c284o68yhalWiwiLMLVa5ZOY+R90oNEuTaT+irDXuHi7p9eXCsiw1ug7mi4Aos3jyZMLEkefwzk8/uCXo3D1YooiOH3749DMfL6VJtfjE7UXDCzvxqVqDrjVc/sIhSWUQFyazlc+zlexTNunHGIq8acLC4nAY8oWXz1lnDorScb7sS6q02tC35OA89NNbWnzdKtykHp5d8KMPJXu0RbCMXN59cgTAGwc3VLXKwEtlayCzZGSnfOXoGV8+vCCvdHpWxkEQ8cP3zmURv9Yw9ZqmUfhlX/xIfq6VMg+lf+NkHN7KKMJcpoA+XI0kAaTROAikCW/TKtTXksSySCXxRFcaFmsPw61Yrj10RbbF6TohI6Ra5a3zIxapy89/eMZ4R4UvaxXDL0lXNp5ZMHBlx4uBndI2CtHjHqrWUjZSX9Xt6jg/dPeCL08veX89ZmzF3OQBPSPn0XqIY5cyEhIddaMw2/hkpY5jlFwnviTyOCVfPJCi82RrcTzZsEodbhYBJxPZgkhTWzZzj/nWw/NyZheSDNOfynTWkRNx5m2YuDGXv3CIQsfQTHk4WTAaRzzd9pncXVGuLPJdmtl3pFbz5emcMLfQtYaPdo4iHzw6JFm4t4zX/s6b8XLTI891DoIIdddpQaHjwIt4rTcj21qcvDSn6yDdSRmE2snB0WnIvznAtCo0teHJ9QhsadmWVRrrtUvgZSxDV+oWz0IGw4RnKznofvXJGUlpYGsVp8dLHgyXUo+4Y88+b7t09MsvKWppjwdQpgb9fopmSs2m4xT0fCmUvjda0bSCvpnzyliKqZ8tBpLIlDn83JM7xIVJYOa8s5zQXNlcrPoYesPjmzHz0OPRbMTdN64Y+QmK6LgMA1ZLj0M34vVXz/nGe2dcpz62XuEYJVFi8fT9A27WAV2HNHXetSFaRw7L2JULgsIkuCO7pDSpjMB8q2BbWswTD08vuV4HbK8CNKVlE0p7wqpV8QyZ5QF4+WSGaxQ0jcLD8YJfeHqMbxW0yI4qql2jKy3LWcDoKOT8ZsD1NmDy8pKxn1DkBne/dMFN5JPmBuvdJN23MwIzl7/Zus/ljUyfamPp22to0qg+K3RmS1m73p73ePXONWWuMTiI2JYWUWHh/9CSulMwlIbLTQ9z1xvxs0aH9IX9pO1Fwws78TW7Ls1Hb97c0qj7vZSXJ3MpHNYq0lpntfBvu1u/dzNFUxs2C4/Aywl3XRs8rZStbkpJPtkUNk2rYKo1i4s+ZauyiaVOr4wNLK+QbhiZy2FPMj/LRmXopKS1zgfbMZvCpqhVrkJ5c17GAautJ7uvqy2vHsy4ST3u9tdylWuWzJY+eaXTdIJV6KIqLZvCkqQDM6NuVNl+qNapGpXDV6VZr2uUaG7NsR9iOyVdKziabMlrSdapWnmzumbJ3YMlVa2i2zIFGM9disRA0xoUq6FspH7P1UvOlwM0raHrVTh2QVmrPFsN8P2MZGPjaQWuVuAapUz55jaP10N8S7ay6TpxS8w5GMgJPcwsNqGD4VT4bs5VKltHBQM5+ftWwUsnsnfxc20iuUrbCtmC5s6Ss+GacOPIZq5KzaPtSPpTvrrg6WaAJlrefucUS6tJUpOhk+JME1yjoG4UAlO69VxEPTYrl3DtYug128RGMRtUp2IeerQ7gomhS7cYy6okc9OSEgzXkD0Eo9rE7uXEuwF3FCTcHa5xPDnoqlaD/qaUcNh6TVtoKLqM1ADaWmEb2Uz7EdWlI3VkrcA2SwKj4HiyQVNbFqnLKnZ4upWMyDgzGfvJrkNJyc3WJ/zmiKQwyAodvy9/v64VhIVFtHbICp2JGzNLPKKP+vzct+7LZreNRlOq3GxlPfjOdMnISW4ZlNpJyslwQ5obnEzW0l+yVag7aReY1xpRaKMaDY/XQ6ZWjDXI0ZSWp+sBXSc4HmwZ3tkw7UfklY6vF7hOwcBNaSqFB8Mlxji7/V3SUkfzKsK1w8hKWcYuqmi5SXwmvZj+sSTA9PyMgZtxNe/dpszD0iSrdSxNpjSXmUtXKcw3HrZW3S6Gz/wNh4cb8l3n9sDJiXODbWYhlJZZ5HMUhJSJ7NrQNAqBIT1PL7Y9jnohjl8w8WIGvmx3drnsSYbuYIPn59KOzmhJKgPTrtgsPLaZbMeVFTqPt4PbDimz2CPdlWY+8zHzc5QzCCH+z0KId4QQ3xBC/JdCiP7HXvudQogPhBDvCiF+7ffxXr9aCPHHd49/UggxF0J8TQjxlhDiPxdCOJ/2Hi/sxIciCQNCdAzcDHfnBrEubK5u+mxzG01pcQLZLft5n68jJ8LpZbetWza5TViZxLHNq6M5Za3dOnU8Ww547eUL3ro6pG2kJdSd0wWmIb37TFX2o1NFx9PZiFXqUDYqy8jlrQ9PeWm4xLcKlqnL2E6YDkNsrfp237nY4a1nR2Q7c9/7RwvphXnVoyllOujRN07JK9n3Las08lLuq6sNU0emfXSlwXVz6lYSIY6GW6pGxdDk5HZxNWQWe7ctX543fq0alZceXmG50obqYCwHkqfrgXQpER0HQYTtFzhGhW1IbZprlBwdrfnZZ3f5xupYph4zD0ureWm02LnaSzeLwMp5MF7KiHZjS7F1ZFDEBlFisUntWxKJqdeUtSbPedHn4nrAyEl4+Oolnluw3LosI5dF4nI43eKbOV+9Or0lQmhqS1mrnCc97j28oWpUTLOW9c2deN61SvJaJ3p/wPajPofTLarRUP7lIbreIJYGg0FCU6m8O5tKYtPGYeLFpJHJ0/PxLbmoZ+YkpcmHm7GsBakth35EmMkefVlicDZcS9cUUxp0H7gRwThmPIh58/AaW6/RrJq2kfXa4UsrDvuyDVVVq3ywHEsLuUbl1Jf+pVNPpr/vjVayO0Hi3v7mzWlOGpmcDTbkhc565TLtR/StjNfvX6KpLXFpoistr3/5CUav4CbxKSqNoJ8y9hPqVrp5fPj0gKzS0ZWGthHchDvbM63isB9yMlmTltI9Jy91fvjeOaejDYdBSN5I15ony6Ek+dSqvNdii3Vi41myD14UW5zPBnKC6JSdsbmOY1RsVx6q3tAfJSwylwfDJYul9LhNSgPPlIzWKLFknW4grdyef5YqWh4vh4yChLTUef3BJb/y3iPKRuVOsOHynanU3DYqxo7JqyotPUfa4zl2SZYYPFqMeP3eFYc7R6Off3xKWWvkhZSDJDOXqlVpOgVdbfDcgr6Xktf6bVuj+3dnLEIPzyoYTiJ8qyCwco77Wyyt5vF6iOFWFKXO0XD7mQ+XHYK6Uz9x+36xm5R+/3d56c8BX+i67kvAe8Dv3O3/BvBbgDeBnwD+HSHEX2+I+Ye7rvty13VvAiXwmz/tgBd24nveu+3iRqZn+mbONnQ4vxpiPjZvuzB7VsnX3rvDzSIg2XnwWYaMBK43AaroON/0aSqFX7g5lIJUTbrj21ZJUhkcDkKaSuH8coirl2xupI6qb+Y8nCw48kJcNyctpUnuwEv52954D020HLshPSsjKk1OvS1RIQvX52EP1yyxnJLZxsfUGvJa53S0xvBLXr97hWcUKEcpli7dKMZuwmEQ8mwp031fe+cuHz49YJPb6FrDtpS1y2dXQ0ZOQlbqcqDWG+lYohesM1tGLbaUTiSliWlUdKnG9XWfrNRl251Sx7ZKnlyNKHKdxdZjnTgMvZSbtU9W6TSNwuWsLxuc5jZvv3MqI8xa1g1XscPFui9X/K3A8KRo+uhshW7X9NxMsk+1VvppupICf7XscWeyojdIWaYu68zBUBua0Ng1y5U+nU8WQ+4PV7x3Nb0VWRfXDjehLxvkBhs0teHveOl9OYEtXUytJikM7v7QBfpRyvVNH9/PcH7FAsco0U5kD7rp8NukmtE4kvU0o0HRG9mnb2szSz2ySuPmsk+RGISxzdPVANusWCQuCLgOAy5nfXS1keSjsM8PH1wwchLeW0xkJ/ejG9pCZjBWK8kiHN7Z0OwWMp5Z0nWCx5sBFyu5qIsrg7El2cSKIu3EjnohQunoGqmLNIya4Sjm8p0pH11OuIqC22bDmtrwdDPgtcMbfFM2So22NnFhMP9jZ1yvA3SnIoxt4tykXksHmLLQOd/0efJoSphbrNcuT5ZDikLjq2/dJywk+zmtdYpSx9Rrkkc9NrEjO0JUKmeDDXf8DVFh8dLhnJePZ9ztr3mykt9PEjEUNKuiWFsM7BRVaVlkLscH0mc2sKS2EmQ2YWSnqKLD1Gt6To5Cx6OnU2lTVkkm7NuPj5jlHlll8GgzZPzSklXokuSy1noYyK4S69hh/peOmHgxbS376y0Sl7GVchiEjAYxIzvh5ekcXWlQA9mAeb2W+r/NUrrJJKVBnhmoSscqdRh4qfR0VRs0IWUkYS7HA9csZe9Kq6T5HFoTdR2yu/0nbH/z79/92a7r6t1/fwY43T3+jcAf2vVqfYRsNv6j33m8EOIndhHjTwN/73f7DCGEBrjAp7p4v7ATn6a2NKGOorWyvpd6IDqINepXUopK4/2nhzh6yf27M75w51JKG+yUphVS52aVuEbByEuky30nuNtbs5z70kg6CLl4+4DrTcB0EmL7BZpoEVrHKnQwlJqoNPnms2OZQrNzaVqtVXz16pRVYVN3Cseu9EW8yTxWkXQWOQ7kwJpGlmyzs9P6aEqLbZVItz+Y9GPOgo1cHReWZEc20lezdxBxdLQmSmS7pKZVaFrBYJhwvpEG0qYvI2HtNCGsTMZuIlNblcbNf3dMVmk4RsXLr1xyerKU9SKjoS410sykqxW6hSnPadfpPvCk/ZSidPhBRs/KcPQSY5hzHfk4ViltmERHXStYRoVQOoqN7F4933goakuUWahC1suand5tc97jbLymbDQ2T3oceSEHnuwZNzzZUldS+L7+cCCF0a1KP0gx1ZoiNhje29C2CuVSppI0tWVVuFwve/hD2UkiCm0srcZ3c1SzZjOTrihDJ5XmB7nB1cWQDrnAWp73SUoD06yxXVlbEwokhcHmxkdzK6aTEMeWkfw2knIJISB+It1PskonWTmkuUFYycHO0Gtph9XIhsSbt0cEvZSqVaWP5nOv2chleRWQZiaOXWLpFVmt8yQaMPIS6ce5GDCLfMaDmMPDDU+uRhwGIYuLPr0HG7pW0HUw9WLKWsPWKiy9YltaZLXO+UwuTlSlo/8/veRkuEFVW+prW2ovB7lsK2RLE2ihdqyvfdQd6/RwGDI9W2PrFWWtoe1IQHmhwyRH33mv3jta4GgVcSUbtIaFRbxL32exydlozYODBQCmWSOMhrgwuVr1dr+ptKNrWoV3nxzx6nTG+fkIQ6npWRlFpRHnBsd+yOHRhriQk9oycQkGKWUjDeyT1KRvy/qta5U0rfTwFaLDtQu0L2252gb4/QzNqxACPtiMbieqDxZjlplLWhmcjddsnvXotjp9K0OzajaxQ9/KaEt5vWpqS1FrO29fm6Q0WPzMIUWtkZQGmtrQNAoDO71NmX+W6BDUrfqJGzAWQvzcx7af+pv4uP8F8LzR+Anw7GOvne+eu4UQwgL+feDXA38bcPgd7/ebhRBfAy6AIfDHPu0EXtiJr2kVrHHGpB/L/nG1hq439O9sUdWWKtd4+c41jy/GPHo85em2L3ucGQWeWfLm4TWq0vLog0M2qc3LkznjIOZZ2KcrVQ77IZ5W0nuwwbGkHRjANz86BaXj4cGC99YTdKXh/uGCwJZm02llcBP6HAQRdavwwXLMdepL55VSp+9lZLXOJpeRV3+Y8OrJDdnKJjBzHv2VM+mgEQc8WQxJCoN35lMezUfMPhxJV40rm3TpkO1WqseDLcvI5dTb3lpFeZb0ETS0hjbWEYrUFT6ejeTqeeVj/fCK7bm0S3v/6QHnjyasYwfbKkF0nAw3OP2M4L7U9G0vZKdvTWl5cDLHdYrb5rNFo/H64Q2q0jF2ZE8+26xoa4XVB0MpjegXqKLFMGqOeiGmUclB3qh42F9gqjXGWJppR7mJdShTmO//7F0ZDT0aYJqVrFW+cYVQ5eeqQjqa0H570nnztWd8sBiTlzpvXx/QZBpJbGLpFScHaxQ6lrMA38s5PZMNVx8vhxx4EXfG0grNMiref3ZA/ziUE6Ulm75GqcXJZI2idHzh5XOGQUJSGBhqg2cXqO/IHoiq3qAdZty7M0NTWiaHGwCehn3eeXbIJnRklmLd55WHV7z2lce0zyUq1wOiSLJhHatEdWr6Xkpg5eSVzjaTC6XLZQ/PKHjlaEaSmGxim21qoZkNUWFh9GTHBDpBmplEhXXLGp5dDFjGLq5e8vBoznQakuYGvl7gaBWK0tL1KjYrlzePr0lLeb05RsXDe9dYg5z70yVNK7hZB+SVxs3ax9BqrhOfV8Zz7oxXnB6sZYspL+PJ9ejWGxO4nYjSyuDu0VLa97UKi6se8cJhMgmJc5Mfv/OYZeTiGwWBmZOUBndOFjzd9hkdhDyNBsxiD1XpuDtcE5YmmtrQs3M5PhQ6E0+6vtStwhtH11xuZXsiQ23YrqTWzrFk7dS3CtJQcgDOJiuaTnDsheSVjmuUBHZOz8pkf8Rf8wT3KMaYZrz9+Bhdb9D1mscfHaBatfQezQ2qWuXx5RhDa2Sfyx+/JtraBFbOs6djbKOSjOYdeeozHzO/t45v0XXdVz62/Z6PHyuE+Nnd5PN7gd+wq7l97TtrdkKIfwGogf/4+VPf5VS+s+Hga8Cjruve77quA/7gd7z+h7uu+zJyQvwm8Ns/7bu+sBMfwFF/i6Y2VI2KpUmT5cDKEW97aEbDk+WQk6M1zjBjcyPd4b91c0BcyFTHcuHz8iuX+FbBdewT5Sb3+ytEJZhtfX7uozsooqNvZdwZrjGNmunBli/eu+Cj2Zh7vTWL2OOOt2Zgp3Iftebl8YKqVbna9Bi5CZZa8yzsk5bSD7NuVBZbKbjfftSn7QSihU1uM/ziAluvb7WHeanz0mjBm0fXvPzmOUWt8uqPPOGNV875ytlTdEWyBF8aL5hnLk9nIzkR1Rp1q1DWKsFhxEvjBU2rcDgMWV736PVTotBGH+VS09fPUFzZUqduFNpK4fGzCWlooyod6ZXHyYM5qmhRlZaPfuGEvNDJSl1KGPSSd2ZTVuc9Hi1Gsg6TG5werBk8XLP+bw+xzRJTr1EUmW7rOkFZaxhqw7cWB4hd+tq3ZY3FNCren024/8ufsYxc+vckyaNnyQH0znTFXW+NIjpWC5/XH1zy4GDB2XDNo9UQ26zIEoOmVpkcbjg9WLNNba4WUoNpeCVJahJmFo5R0XNybmLZygq1lWQNvSXcyslEVWT/wb6bcfG1I8KtLbV9mmT0ampLGNuoX9py90AyL8e9mLCwmC98qlbFMiuWNwFvnF1xOAwZ9mKqSuWjmzEXkVyEbELpi+ntuqSHsUW/l2JoDU8vxnJiU1uW1z26TlC30uR40E8YBQkjP+HBVAr8B75kHJ8eLxn4ssZ4swh49t/c4fTugokXcx35LFPJZA0cWWvLG02ye82G6SRkXdhs3h9y2t+wDF1Zt/YTPjifks5dHkwXmFqN8oHL1arHqSebPj83LX/2V05ZrD08X3ZCAWQK0k65upG2Y3Un5QWP3j2iP42YHm+IMgvfLnh/M+HuaMVVFPDOs0OiWLZb0tRWMigrHd8qKBuVqRWTVZIF2zPkJPnSwZy0Mm6lTo/WQ1SlZepHzDcer9+74vXDG7pO8GC8xNIqFK1l4KY8nQ0Z2pK4NnDT23LBc2ea6s/dJbnyaGoVwympKpXALhidyhZK4cyjSHWiaw865JigV+iKdPfJStlVvm4VHvYXvNRffuZj5fcR8X3v47vux3aTzz8O/NFdze3LXdf9mef7CCF+K/D3AP/gbgIDGeGdfeytToHv1n7iU7vv7t7zjwF/+6ft+8JOfG0n8PRS9kUzCi5nffJaw9cLvK8sUJSOh5MFji57YXnjlLLa9RsLQgIzR1Fb2b8sdjC0BluvWeU2wWmIqrbolpyA1pms3YQf9vHNXNaxcg1HlZ0QNqXD1Pq2o3paS9GyqspJIm80skLeNGkuO3O7TkHPymidhrg0caYJaW5gaNJ7salUzkZrylCa7qa19EiMQhtNfHtFGBYWL53MqHeF9a4FXWvYbGVarWslmaVsVQZWRlmr9CbRrR2TZVZkhU507mNYNVWjkmcGit5iBgX9UUzbCfyTiLgwqFqpVbTPJK3fM2X6d2hmVLmGMZSNNHtWxiSIZe1j5ZK9nrM973H+0QRTr3lyM7oVEW9TW05AhcV0GNK3JUNv6sUcDkI0RUbwtl6R5QZxacregEpLi+DE39IfxVyG0hnEUBrpCGMW3DlYoX4kJ++BmeFY5a2o27FKpv2INJORTJwbt6Qcyysx7QpVbxDXFg9GS6LcZJNKWyvrpZDxMObx5ZihlcpOCjvhvxDImo6d3UY0h9MtZaWyedzn9HSJpckmp9vUps50VLVlfSNF26NeIpm8jkzFNZVK0wqqRkWzKumjaRSodo1pyoilRdC3stvWWW0n8M2cMLWYrQLiwmST2Lw7m0rLs/vSfcjVS5yd96hrFGxTi6LWWCQulzd9+kHKYu3x7O1DxGHGe5cH8J7Hib+VZg2tApZ0XGkRFIcVB4NQ2uGV0i3FNwqCLy4Jgoz7gxUPgqXs45jLDMx0EjIwM9aJg6E32IcJvlWwCl2qUts1cDZlGnnjcHKwplnIVPahG7EMXTYbaUk2cWPyRmdkJ8wTj3rHwg0L+Tsk7/alNKfSOApCssqgrWQHhnVhs42kfV1YWOhWzfUqoC1UNKVlbKUc2DH1bsILjIKriyEXqz7OYUxTKjKzsjFvG/iahkzX2l5Bp3WoZiPrtDsnqDaUv1vTKkSJxeNwiKHUfB74PHV8QoifAP454Dd0XZd+7KU/CvwWIYQphLgPvAz85e84/B3gvhDi4e7///Pv8VG/Cvjw087nhZ34NKXl3ZspaWncDv5FqfHO1QGLyx5H/S3vPDtkm8v+bb5VYBsVWWTx/vVE5vx72S1zsW9KT8pVKmULx70tZ6M1Ta3IASzTef3LT4gKi76Rc+d4ybO4T9FofLAc89++8zKr1OHZXDIol6GLqcvVbl7rDL2UiZ3wy0+f0rQK9/srmk7h/j1J3a9rmV5tWtlZ/nC0ZZm6nJ4t2OS27CG4cvH8nKfbPrPE48PNWK52a52pFXOx6WE5JQM3RQgIHNk7Lc5l9Pi1x6f07YxXhgtmvzDF9QpGbsLQS1FHBXlssnhvxKgf07ViV+czKEqpFSsrjfMPp1StQllK39Nl4nK+7FN3Cr/8/lMeThcsEpeb0EcTLaroGI5ixsMIdVAwOVtzt7emSTWaXff3k4FcGceZyTa12GQ2L5/MeDQboYqW802f4TBmtgoIPNk66XiyAeBZ3Ofr58e3pIGwNFlm7m3t5OnNkP6PzHGNgg+WY9mSqp/y5GpEuLWJcpPAy5mHHgM3uz2HstAoMp0q15i8Ob8l7WhqQ5RYnPY36L93yOt3r0hrmUY79KVNGsD2SZ9VKkk50TsDri4HeFZJ/548b9ktXHDYD+mPYxBg9goCJ8c3JaX+YtHnYt1Ht+RA+COTZ2hau2s+XNMLUsnerDVmicd1KBsRj6yU9x8dscqcW/1eGNp4dsE4iGVfvLs3DK2URytpgJ1WhuxskOnMY08yptWOKLUwzJre/Q09P+NsskJ/c4uhShH/cBxBI7C1ijQ38EbyOv/W/IChk3K57d3S9nWl4VtXhzyL+5SVxiuTOe/MJTFpXdiMvIS7vTVfOrxCER2q1nJnumSxlY2L81rnRx88wVRr3NOIx5djHq2G0g+2kinMZ2t5LQ7NlIeDJcvUlUzhSqdr4eyHL3nj4Abfzpkn0kfz+GAjDQ+2PpouG1xHiUURmwgBQpctys7jHlepj6Y2WFrFu7MpvUkka7utguFUMqU/zohymbJsW8G9k4XscDKJuTddcjpa33Z7f/2NZyxn0nf2dCQ5G+dJ7zMfL7uOz1vH928BPvDndinQf09+bvcW8EeAbwF/Gvgnuq5rfvG5dTnwU8Cf2JFbnnzHe//m3Xt+A/hh4F/9tJN58bxodmg7acMz9SMuVn10pcU0pIv/9HjD0Mq4diR55XobyIG7UXn93iWXYYBnlmxSm8tND9cqURU5oESVeatrut4EHO2aqtpuwVsfnnL/7g3zTOqJnjdwPAxCFKWVxIBeIlN4kcnLJxecxz2iXLJMx3bCX/z6K2A3zIxSpu/cjMXWZeCn3Gx9vnR4xWUSyN5+Rskqdng4Wt6a3wZWzpETcZN6pJXBgRvxwXJM7spJs6kVuYp3pAmxgNvmuz9y/xmr3OarP/cSR1+8wdIqHl2Ncb2COtFRjAb3Xshi5eMHmezYvg3oOZIB6lkFx69sSSuDwMtpWkG4dHH6GfNMpsoWkStbGAnwjYJZ5HEQRCSlKZ32C0NOiIm82e5NpFtFurU5OlrvOjWobHNbWs6VpuzaIDqOxhuKnTnzzTq4FZIfj6R8Y7n2UEeyr1lWaZSVTr+f4hoFmiLTVrOtJN8oWofr5twfrPjau3dwRynrXSNjGdVWsr1PIV1UFK2jbQTHx1s+XMuJNf/H1rAzq1YU2TS3jA2C6Zb6KCHcOMSqhXKWctSPZY3KyfGNgg9nY6ltO7pGQUavaW6wiW0pGTAr0huPwweSOfhsMeBnru/xxd31cTnr89LJDENpeLbucxBIA+upE8s63CBlG9nSEq9RGA9iqTncDcizSBJ68tSQzWDjgNfvXTHXPO4NVtJH08loOgVDbbD1klXqMLETaZmXO7d9FO+cLbDUmoNAdrtf5o6UHmQuYlf/zc89ssDi9GTJ09mQ/9GDj2SU6mTSRSd1cIyKt9cHOHYpa3KBdGExjBrHkOStjzZDxq4UzB9Otxy6EU+MGs+UsqGT/pa81vC0gm/dHPCV42f8lYs7fPHwiq9uHVxduu3oivQDbTsXQ60JnJwjL2SRucy33i0ZR1VbNK1hm9usYodpL5LC+dOWqtRQ1ZZkY6PZFa5TSJan0uLumLirhU+4dqATnJ4sWWcOcWpiGjVdJ7ha9Dk5XvFoNsKxpZ7YUD97QXmHuDU2+Jt6n677C8Bf+C7Pv/Q9jvldwO/6lPf908ha33c+//uB3//Xd5afc8QnhOjvBIXvCCHeFkL8CiHEUAjx54QQ7+/+HXxs/+8qZBRC/DIhxDd3r/0/hBCf+hcSAnS9ptylHWcr/9Zzbz7r8Xg7wNBr4kJGO8uNh6a2XIYB4eM+WSWd3Ic7ivGhI6M+U63xjYJ56FFsTFy9JCws6kYlGMe3q6OykZ2qba3i8Vy6fvhmTt/KUEWLYtVsSgtHlzdxb+cW4h/GkKtcPBoz2omP60LDNioCe1dfqTXSUme28UnXDtvS4ib22SxdDuyYWeZKN4xdw9tka/EkHFBE0vw52k0y4cahbQUjP6GqVeJKpiq1k1QODnpJvy8ZsHSgmY2MjoOMwM53v7OkvquiZZvYLFOXxdaTBIPUBEVKRmZbn/PZgCwxpQlwZjBPPYZeSmBIgoUQUBRSVO/d31JWGlEhv9vR0VpqnrSaQz+Sdc/dVdAPUnRNMvlmF1K+0tQKVamhaw1PHk1lSrFUWSc281jWT9tOsJr5lI1GWFgUlTQtLkqNyUA64JStiigVqkrD0Bvms55Mqc6d3fcw0e0a0yoJeimPrsYMR9JuajkLbr0m21bQczIUXbrNdK3AcCpMu6JtpBnC0EsZOwlJZdBzM8a9mHVhy4a2jUI2dyhCuUiqG4XDe0uWkWQOqpoUvD9vtjocxqSVsbP6yjh0pK3ds1CyeW2zwnMLns6G9N2MKJOdzW29vhV1Rxt7J0QXGG6FQsfJeMM89UgzQzJibwLma58n1yO5gMpcksRim1k0u9riOnFQdtZfcWmyzSwuo4CL8xEjVy4EvbuSxRwXJm2lElYWq8IhMOV9Ee76I5apIRsgu9mtftGzpAbS0ioMrcHRKopK1pVnqUdeyntxvXJlu6VG4zINSNeSVf286wMdbEuLotQoao157BFYOVllsNzuapy7xsauWVImhjSXj+X9dHe04szbSBN3O0U3ZBeHyVR6AwPMYw9Db4hzk1XkcHK0oj+SspMwk+5JCFCUljC2aCKZHlc1OVmWlcbma5O/sQH5e6AD6k75xO1Fw+f9jf5N4E93Xfca8EPA28DvAP5813UvA39+9/9PEzL+u8hQ9+Xd9hOf9sF1oZHOXPqmpAzfma5IS1kjG04iDt2IoZNS1BqOVXI8kcxEVeno3IbVYtfYc0epv059/ru//BrzxON8I3uZnd1d8Gzdp9m11Xnukr/JJR35o5sxm8zGsQvu9DZ88M3T20jtdCpJF08W0n5obCey/YqbovUKTu7L+uPTmyGOL3VHfTvjg+VYtj8xS758csGrDy5R6Ehzg+k0JKxMHp1P+XAm2aqPd/ZGs7cn0MGRE7EIZdshvydTtMvIZeCm3xYTh3JyWmQuEzfGNkvsQY5h1JK5p3ScfzglLCwso+b8csTjyzFNo1CUGoEnTacdu+T+6YwwtdDUhldPbjg7XLGJbfqerG9llc43nx5jqjUvHcw5Gm15uu2TZgZpJtN9fUv6q6alQd2ofHA9QREdXQezWQ/XkNomRXR4kwTXLDkab2kK6X96dm/OsRfiDjLGfkLTKAydFFOvGR2EhJnFzSKgbGRa50uHV0S5/A1uYh9jmnEy3NC2gq4RXF0PULyKxVZaiZXznZOP1vD66TWeWfDoaozpS2NxRy/JIoupG9NGBstImhY/x3QovTaXocu7Hx3f1ndulgGb1CarDA79iPsvXTM6DBk6KYe+nMiqnc/jJIgpSo15+u1mxOdPRwSmdIz5+vUxWaWj/mfD231GTkK7kYSOLJZRxvUHY27WPqraMppE+EHGycGak8GGR6shT5+NMbSaKpI1y94k4nC0RdnVxTa5zWvH12S5pOCrioyKvv7hGWWlEpg5jiHp/0cnK55+7YSbtU/yUY+u2g1HjeAmkVrQvN4lpSKdvNJwgoxV6uAaBUlqEiUWUWayTF0ev3O0k71oDHddzMtaTozn6z6a2bDMHdaZw9PVgJfuX/PhZgzAN86PGQwSzj+a4NsF4dJF33VUuP5gjOsUfO3nH/BoIdsMzec9FL0hufQw7Iq6kQ2rV4U0Xt/msmvJS+MFninLAGUlzeTXNz5pZmDumvNmhc70QC70Bm5KmRhMPckJGJ5sUXYd28PMYuilHP3od+N+/M1j34/vM4AQIkCya34fQNd1Zdd1G6Rg8T/c7fYfAr9p9/i7ChmFEEdA0HXdX9qxdv7Ax4755M/XW7R+wVvvnGH3cx49nsqBudKIU5PH6yHrTKZP1u+MuFr0pa4qM0Ht6I9iRn5ya62V1zqTl5fkhS572wnpFn/UkyvVnilp+0dBSNfBkR/y4GCBqcuUxbOwz8Erktn2+GLC03cOefvtM85GaxDSUea+L93eh4EUgb///jH9fkr9rR55rXO57d06469jhw83I64jn2eLAYrScnMu7bhMr8AyK47PViSxydHhBv+lNfq1wU3q0baCaS8iL6WMYeQnXFwPJOkltXn94YU0AGhlLeRef03g5GhqQ75rgGqMM5ZzH88soAPbK+gHOwusTsi2Srp0rnGsElXpUOgYWSmTXkyUmWxDR5IIJlsOHEmSaVqF7dMek10d0TVKacMWm+S59NJ8TvzxrYI3710Q5hZhaN/qm9axwzqxOTzccOyE0louk81no9wkv3KxtFp6se6alE5H0rA8MHNmmSubydrSuqyMDR5fTKhqlQf3bvD7KbZbouy+kzooKK5celZGUhk8eTLB83MMTabLPrqYcHK04tFKLkKO+1tZg3Myek5OXmusVh62VRKMYzS15SzY8MWzS7LcYLF1SSqD621AUWmcb/oUtew4oRk129SWv10t61hPbkZc3fTpH0Syf2OrSD9Lo2D961Li3GDqxtK9ZFDSdzKpd01M9KmUAHlmQZRa1I3CPPR4thggBNi9XJKAhvL319SWq0VPLnLGS3Sl4a1HJ5yN1ggBy9Al3KWpXbPk7XdPKRv1lig0emOBbVX8sh99H9EIjvyQl+9fYeslrl4SFyZjJ+HwJck6NnTZY+/D8yl0Ak1rMPSaphOcvDLjZh6wKWySwmCRuKhKR9moHPe3nAxlKlxTWo56kmCT7yLDZiG1rvdfusbRSxSjYbX0OH9/yqtfeEbTKpy9fo2h1zJdudDRzAbzIMV3czS15X5f3r+mUUnylid7DD56IhnJRS4N8KdHG0xTRqXZlaz1zxc+RSpZ0IcHG9776AjXKcgKHVcvWeYO9wYrVKUl27kzfZboOrGP+D4jPADmwH8ghPh5IcTvFUK4wEHXdVcAu3+nu/0/Sch4snv8nc//NRBC/NRzgSVRxOEw5OjekvvjJZpb7yyHOsrYuO3KXLUK+t0YsXOxt80SobbYesVi6zGypc3RPPQoapWj/vbWPd4xSoodqaHtJKvOUmvCrUNSGdK8tjQ4CkJco8TfTY7BIME+jjl5MJe1iL5sLLrIXZpWISkM6q2JsGsp4H4lZrF1SWNZX7S0muLSJUoshOA29eKMUhmxZTpdJ8gqnaCXcfXBmHDj0P+hObZeUeUai0jWV9pcOoIIpbs1M15n0tv06lxmoetW9t3bXgWM+jFZpdM2AhHqrBMHp5ehaw1xJqMkQ21oStnKpsqlHGHkJiwz6Vzh6LLPnu9nRLsu54+2w52UQ2F4b8NsFWBaO2apVtM1gibTpHZsR9E/vxpK4X5k01aKTMt1kMcGYz/h5f6c86THs+WAxdYjq3VJuLi/ZpPbkjXXCcZeTJjJFGJea7uIQtZYfavA9AsMt6TvZlStdO6pG4XjgazvtrWCfybtqp4tBuierMWUtcoHHx0yHMVEuUnPyQmOpVmBqda3NeCmUXA86V8qRCejgx1TF6BtlNuOIa5Z0jQKT65HNJ3gqBdiGZXs3ODmtJ2grRXuHS/Yzn3e++joVrP5vB6mqS1lo6KKDlWXNad+L6UpVarYwNFLJnbCtBdh6LLdU9cJAjun72aUrUp+7lE3sv9kEGS3EU/TKRhuyTJ16TsZtiXdh/qW7P84OV2j78Trz7sXWHpFWJnQwk3sM088mk65ZRPWrSIb8iYGbSvYpjbKwkB/W2oybb3m0I1ISlmPzGt5T27X0s+2rFSeLQeS6arITMHlpsf7jw+x9Jqi0SCouJz3KRsN35AmDcNRjNIryWodRXRUjSr9eBuN6Rdm3B2tbq9PgMfbAWll4JklT1cDnsyHhIWFP0rIC122pOpkFgnAd3LMw5QsN6QRRKtg6jUDO+X4dHVrPxgWFqZaU3cKTy9G5NVnP/GBTP1/0vai4fOc+DTgR4B/t+u6HwYSdmnNT8AnCRm/H4GjfLLrfs9zgaXwZfeBODe5DANeOb6hbQWGVvP6g0vu9tc7JlkrV+BmzWl/w8DOODtc0XWCO+MVs8TD1Gtenc5wjIon3zxBiI515iCEpNpXlcY3H8u5+Otv3eNH7j/j/BtH5IXO6qJ3q5dbpi6G0vDm5Jp0LTsxOFp1606SVDIN5hgl1ijDdCpeGc4xjRrPLbAcaXo8e3tC59UM/JSRk/CF4yvu9WQrom9dHHEwDnllPMczC0ZOwr1Xr/GCnP8/e38WK+16pudh1zfPNVetWuM/738P5CbZbLIltVtDGooM27AUIDAMOLFykAgw4sQnQRAfB3Yc5CRIjBgwfGAHMWIYRgILNmTHkCzZmlpN9ia55/3Pa655+uYxB0/tRapNstndZGJv9wsU/n/VmqrWWvW+3/M8933dHSdhGvmYrhwojlVwcragrDSORmtcQ0Je49xgOmuh+wXPVwM+uTgkX9hgV6SFzvZ5F9/L7q6ARYEmhm7HEkyUG6ScL7swsSXxwBRqSV5rrBOH25sOVaWiGqKAW30wJK90ahQ0pebheIau1aIgLAypWnsxm4VPy0m53ba4fzRnEXv02iH3j+ekuUG8dTgcrzk/H/J8M+B83qMXxDwczQnMjDC1OPS3XF/2yAuN6W2bMBN25Wbus4g8ok+7dyIEmSsZdDzhmJaVRprr1JXKLPTJK41uNxIG6KrD2XCJqjU4Rikihn6Ms1cNh6mFpZe8mvVZJbJpL7YefS+i5aTsUoskk3zHl9MBt9svEWJiQZHYHoU80zkYbFmtPF69GXG8r2T/ieOXvDe4RbdKlrHLkwc3dA92d3i+qlY47YrX8dXNgOm0TV0prGPh1tpeDvtw3g9enmKoFbudgxtk+F7KJra5nbZ5fjskuL+RVm8nZhfadD2xSuhqjevkxIlcXG4mAYftLevUYRW6zBeievQtoaFMX0ts08Wqw/HjGWFi0XViAiNjlQjbdhb6vPrskH43JAxtma0/2uD9qTlNo9B1YmaxvN4PBmKyP+2tUNRGgmrbW75+dMPVri1w+tykSHTeeXhNWuisYwfTLTgbLbl6MeTDT8/IdxZ5oVMl8v4vhVItJ2UZujI/DP091UXF1gvOWmt6dsx855HNXMlK1Etso6AsNMq1xSiQFma8dVitPLqe5AsODzY8ObvF0kreLLsCPNCru7SV19M+LyYDRqMt+Q86P2cb/aOtBrnA+Fm3r9r6VT6jS+CyaZrf2b/9HyEH4WTfvmT/7/QnPv6nGRkv+THX7Sfv/wPXq6vhXWtwGol4JckN5pHHi33MjLLHFXXchKtNm7gwOb8YsPhgRMeSFkacm1xsO5SVyr2vX2GoFUM3xNAqHLNA1yvGow2+mXH4YM6Pro6ouwVPRjO+8c4b3sxEaXYcSIXwO6/uc3o2R1MaPro8QldrUQduA8adrVz1+TFlqTJNBFyb5RIns9042Pe3aAs5nEyt4s2my8WuQ17q+wOj4vs/eMjltbTWbjctxq0tm9ThfnuFZ0vFVddSfS0+GHF50+Ni2WX2ss9xe8PTs1tsW4DZmlHRPtoyHGzpexGH7072bSKDlpXSNArrN23yPSR7s09C73oJ3bcXd0kHaaFjqhWbyGF4sEFVa2gky2zwbZHPx6nJbNrmYtm9S18YeiE3Vz1hZB5s7iwd51Nhjo48EXLQgNeWwM7+eEPLSvnm8RX3WjJPfTnvU5Yau8Li8HhFy8kYjaWCbxkZ5GKQ9t9dMd0FvDWc0bETTg+X2EZBlJnc3nQkqPfGIdo4+FaOb2X4ToYCvJkI+cbUSwZBRHzts4kdrp4PGfghZ+01T0Yzuo6g3DStZp06QmLZOuLJq1S6gTx3382oMsFabUOHODX51r1LdE02+c5oxyL2aDkpF1GXq7DNt08v8aycdeKw/aKLb2UkuYFvZXTMlEedBaP+jvHBGtjj4AqZdXcGIS9vh7T2yQ39Tki0doQ6Y+d0exFvH06ki+GKRcSyCuY7jyg3edqdcuDvuDdYUlQaql0yjzzi3KDrx7hBRlWrzDY+Z+01qM0eeiDQAsHWmUSFydAN8a0c2yh5+t4l69Cl24m4d39GUWosXvZEvLTssth4KIpkVL49mhLmFm+dTMgKnSi3KGtJuEhLg1Gw496hKCgfdJc86C457a1YJQ6Pnl7zp99/Rme0o+WkuL0ESy8pSok0ykpRoGaVTl2rbLYuVa1wu2lxE7ZIKx1NrQkOBRLuGhJw6/spWjvn9eUQ25RMxm43YvJMLDSWUTKLfLapzSCI2K5cRsGOtDSY7zzujxY0tYpnZvza//DTX2T7+0OtL1Wdf1Lx/TFX0zS3wIWiKE/3d/024tX468Bf3d/3V4H/eP//n2pk3LdDd4qi/Km9mvNf/InP+ZlLUaTqcIxcMswsQQiNvJDVzqWuVcpcBud9LyItZfi82rkMDzaUJymT2Ofmqodr5mIuDl3SUto+r1c9fDNjOmuJaq9RePbJsUTtFCpBL2ZgR0xjiTgaWBEvFn10tWbU23Ez73Dob3HdjHifOv1lttuXbS1VFan3wImEh6jVOF5OfO2j3Rd+6OuFbP55pbFNLOLCJM5NGqtmNJL5YxYbTEOfyWWXcJ8Yn5WieNTVmtY35nzn0RscK8c72bFKXDqmHIxFrVFsLSy9ompUwsxisZM26zpyiHLrLiPO2CPQDlo7ksIgKXS2oSNS9WzftmsU2l5CWhj4Vo5piyz85mbfVi01hqMN5t7jmGVCmBkdrskS+Rp5pdHeexCLSuP5fECzt6+MW1uOhmtsvURVpHqJS4NpJCGrTSNg6WXochxs2MZC7s9rjeHpiqPWlo4tVo1tbrFKXLbpPp7KzvC6Iq83TyJMT4KINUWsBq6d08wtylKyD1eRi9bP2E59OmcbfCPnOmzxatkjq0Q1W1UqYWSh6hXK1KLKNBEcraWyXU4DhqMNUWRjmiXJ1GMSCxC8Yye09zDxtpny6T94eFelduwEyyhBFU+raZR0rJRnqwEvNz2mS4l7KueSN6iq0mL1zJwq09htHeahj2dm2EEmRvpape9GuHqxj2SSalTXaur987gIZf4IsNgJiFtRwN23YztuwnQV8GQ046PbMe2jLZraYOjyHI5OlwR7JeckCrD1gsCSZJEi0WlZKavIpch1hg8X+2grlV4rwtRLPCPnh+fH2HqBrtT4TsYutbjYdui3I9kP9qxTx8jv/kaqWmW3E5HSOhdMmKmVWGbJ4vMBfT+621uc092eKqQJwECBeOVw+0YuNPO9rzUtRexT5jqK0mBZBW47oefKRUVVqwT3Nth6QZhZhJGoVNexg+XnzCOPqlY4aO+4Xrdpt2SU8ZOAil/aav5E1fnLXP8r4N/fGwu/CfzrwL8B/EVFUZ4Bf3H/9h9kZPyXEAbcc8SV/zf4A5aqNBx3NoIY6i0YuzsuF10+en5CEZqYRkkzsZlvfCbb4G5Od9xbCyy2lhmZ5hYsdh7fObqQDXoiJP04tFCVhqdnt7Lx2An2OGYT24z6O3Zrh7//5gEdO6EoNW6TgG8dXrFIXGy94O2jWzaZzf3ukuk64HbTIspMppuAoR9yHGzotyKmm4DzTYf1wqMohJrSf7Ci7Uq1UBTSYisrlUEQEWYmQy/E68fMnvdZxB6nh0u6ToLbj3m9kDy85aRFz4l5s+ySFzrbwuKotaWspOr5nR89lgDQyEWxKtahw3IeCC2j0GR2Y8qmdNpbEX3RYeiHmEbJ+aQnlBmtwjRLTt+9xTJLwp0kU/fcWNBbsUNZqhhqTasXcRsGDNqhePm0mutZh3vDJdNdIGkYnngPl5OWpHx3d2LvWNvMLrsUscHLj46ZbX2J44k9fuf5feLSQKXh68c36Hoth3Wi83zZJw0tZrM2n04O2CY2n18ecLNp4RiSyXY7acvhlAltI7AzJtuAqlJpaoW6Vpnu5O3NzuH4nQlvjye8uBxRVipfO77hm2+/wTEKyfeLHNI3LdaRwyz2ORssGbQjmlrhya+dMx6veXQypWnkIuHRvQmz2w7j/oai1DAHCVeTrsz1aISbaeRcbDo8/VOvWCUu69xmGvkcuCGdJ0ueX41wjIJF6uJbGeuty9FwjWMUnLwlYId77dXd3+I7D67RTfFl9uwEVZUDJCuk6/D916f7uVvBNrbJC52T/kqM/qG0i9eJQ+CmdLsRQy/ENyWv8ctkgYtNh7abiqVmX1UsU5eeHTPZBXhmLgQcrWSX2cxCn7PjBYtIFMiWnVOjoO49jVmpc/F6yJtll1Fvx8COWaYubVusN0+6czwzI8wsJqsWbxY9Lr5/zAfPz3ix7BOYGZ4nM9Y3yy6XHx6SV3IhcPL1GwCKSiP+R2Lb2KXW/iJXY770efvRNXono6xVjvobjvwteSU0oU47+sf4mufTPklqsn7d4bi94eX1kLpWKBOD7dolsDPOeit6bsy3RxdsU5tvHl6xeim5fPPM++Puy/+N1fAnM75f2mqa5gf7mdv7TdP8laZpVk3TLJqm+e2maZ7s/13+xMf/a03TPGqa5mnTNH/jJ+7/XtM0X9u/71/+Cc7bz1xlpfL8csR05/PRmyOuojb9VoTTSbFaGU/6c/TjiDIXr17HTXgwWFDUGnkhQaAtK6UdJIzbW/7rv/ce/VbE1+9f8eKDU755/5JXcwk4LSoNVy9ouem+Mqs4OVry5x48Z506OGbBm3mPv/fJE97cyHwnrcQnlNcagZdi6DIPGLRCbrctPrw+ZOztsK0CSxfa/agj/f6eE6Nr4utR1YajjrRQJcFc5ndpbPLu+28wNaHXT7YSlXTY3rKOHd57dElWCQ2+2KsBz1ddHg/mXF/0sIcxp/0V0dpB1WpUtcH0csa9LcNOiKULMqtuFJ69GWM/3t5lD+pWJeT9wiCcuyS5UDmenkzQ1JpZJMbmotAY97bc3nYkl3Dl37VOW1ZKU0m0U3jeuvMNDrwIs5Vxs2kBcD3roDkl6A3tfkjTKvHsHM/KadsJ/YEkN+iaoOFcO+c0WOMGGZulj+nmuK2Enh9z0l3T2WfOfXF9wMgL6fSFTZoXmlhVIkeik3ob9L3c3TZFMGT9yGWx87jatRkNtzzsL7jctQkLk2XokuY6ycyl7hSc7bFtt1uxURwdrHkxGRBlQkg5Gy0ZezteTwacnc2Y/e6Ybxxe8/XDG7rdiPXG4+Wiz+VWKB6HrS1ppfOoIzSSx50F3392D9fMuTcWtaWhVgIQCMQDd3nRx1Ar3h5N+dGbY2axz6iz49PPTij2SRnXYQvbLDnwd3S9mBeXI5r9RhhmJoNWKIkVhSlQ5kolzQxm8xZ5ISKTl7dDlonLbCIH/5fpClFmcjDc3sXe3E7b8jsyJcGh70ZcbITTuV0JYSUMJaPxQW+JZ+Zslj6emdP3IpxeQryzqWqFN9suZ4FEFNl6wafzERfzLmFqMersMPSKol/y9YeXotqudE46axGH5TqH700AJFW91ElyydYb/ZZkFqpqw4PBgk47QtVrlrFLsxeeTTYBKo2krmglu9gmMDMe9JaSDeqlOHbO2du37HKL8XBDFFs8vX9DqxPLAVuY2HrJD+YnxInJD26O+bPf/YRN6nD7H9z/I+/JP2sJq/NPZnxfiaWZ1b7lKTMOzxSZfx6ahIVJPnNoNqJM1BRJQB65IVWlopuVYJGUmqLWePrtN3eE/WaUEZcG+blPmO3jU3KL42DDbufQNlMmqxZXcZvpsoWqNJz2V7SHOx6fTKn3V7IdN2GTSuoCSMvIM3LqWqGqBHJ7GEiC+73xAksTDNUuk1boJrbR9QrfkI1eUxsWW4+bbYtuNyKtdKYzkcAnoUWRStp6HFqcr7t339Pe8xyHfsgmt2kNI9KNzXQXMDrYcHKwEgVoJW2lpNDJK43bVYt56KM7BdGVJJKr+8wzTa3vZiS+lbEOXdapw/nVAE0R1Wx54WGoFWQqVzc9UEBXak66a7p2Qq8fkpY6zskOSxOKfZRbnPZWNLVYJkyrxHFzVLsURuKVyfKyTZIbdwrYTerQs2Oh/Kcml6EcFtZrkzwxsM2S2Sogq3TCxBJQgS3KxKpS75IkilJUiJvERmWPsttjzMajDeafWeLaOauXXSbXHZn3KA3zyKMsNKoP2wTjECvICHOLliFKzig1sfWCe8MlR+0Nq8jhdtNilngoai2p519bcx3JfX03wrQKHKu4M/knpcGLz49w9Zx77RWuLi3Km7kcHKrSEBcmj/oLTK1i4EUMDiXkdBoLtH2xlUpCaxU8eHQrF02pRZIZd/B0N0jRTbEUlHuOrabUzFYBri4Q88PeRsYMZoGm1VSZRpobDA/2ySiVJlVNd0VgpSzmAeuLNqpRM488Dn25GLpcdbD3diCUhs3fHfH0eEL8aZdlKt/XaycUlaQaBE6KojRsIof56sd/j8vYpe9FHPUl5R4gzQzMIGeVSeitqjRMI58ol2inpDDwzQx7//HLjc9sJQfa/e5SgA+5haY0+F7GbN6iyjQ+Ox+T3bqUjYqtFdxsWhx1NkS5ySKRQGBLL8lyg9nWZ7Jq3bWG57FHGNkkuUGYmbxZdn+8Z70IUJVaLrz+ufNfyX4pquiffvuqra/swaepNYN2RJbp3O8u6bnxj5lzKtzuAsYPF4weLolDi2XssokdfnRxTL8V4TsZrycDPFPQQuvU4bC15WLbQZlZfP76kGaYSX8/N9H39oh2S1os+VYG9N88uyTYJ3F3nUQI8DPxZX25GWeVfmem9/fQ7NOBCDI+eXbMgS9m5ctVh6EXcjtps00sTL3CNkt++OxMWmcrMd2HO5vFpIWtlQRt8RO9c++Gg8GWy/M+3W4khvXXQ47aG+JUHquiNMy3PrZRMDpc0/Viktxgm9p0vARNrylqlc3SI8lMso3E+Khaw9nTCenaZhPb7NYuB8GO20UbyyxJ9l/bNXK8doKmNly8HvLOt19j6yXeQcSj0wknoxU9K+Z2K0KBKLG42rVRFNjlFtEnPW4u9ib7pU2Va/SDiDzXqXNN2kV+TTAOabsJvpGzSy0Wa5+oMJnHHqc9IcBkmU7rOzNsL6fvRmh6xWIn/r0vA3ujzMS3hSpz1lrj2xnH3TWuWTALBXAcWCmenTNdttDUmvXWRRslHBytBWZtFAy8CN9LSQ9FJNH1EiYfjLnYCTj9oC1z1Ytll21mC8nFLMTz2Ak5661Q1ZrrSUcS6Zdd4qXDob/lrLfiONiQ5AbDe0t+ODsiLg3+1g/f5RuH1/TaIZd/95S4MAUunXhEmXkHPU5L8bG9e3hLmWnMdx6Hg/WdIORhb8G7BxN0tWYVOXcqRIEXSHdh4EXoZnlHjVFpSCKLbSwRR14nwTaFqhLOZU4+cCJeL3qUtcqT0wmt4y2Bn2LpFR9dH6JZFW8NZxhaRV5pPDmdYHx3xfmqS+/9GdNli9fXA2yzYHrTYdDfMfAifu3hBaraMOiGrHObLy4P2O0cXn98BIhQarHzuD9c4Ng5N/OOmOr1goEbsYocbKNkufCZRT5ZoZOWOl87uebx4ZSundAx5TWVlxrLrSsXb6mG6RW8fXYLKlzt2vxwesQ7o6kcdKXOLhW83pdLURoOexuWswDXEXVovy0Ahq6T8N5oIvN2N2H8jQkvtgNG7R09K/mV7Jm/Skj1f9vWV/bgA2mlPBgt2BUWt7tAEo/3IgtFkfdrak3QSvbqsQKUhrTUxehqlkS5KUKF0MXWRJpc+RXj8ZomFkhz3414eTtklng86iwYOBEnZws2ic06sykqTeZ3O59V5KBaFavEIS4NDjwxGaelgWvmbHOL6Uw20U1uc3C8ZpXIZpEnBrZW8uBkRjT3MA0xYfcORFgy6m0FddULuX86Y2BHjALxN+lKzWTRojveEacmeanTHoV3HqWbZZttZpNGQoNXlYZ1LG3aOBG6R7a1hNLfTrHNAq8fUzUqo7ZUZJpdkkYmrW5EXJjUlVRcjpFT7eX+RalR1CrffPsNHz0/kZw8RICx/M+P2BY2qlqTFDodT4Qkhi5mYvOtDd3DLW/mPcx+iuUWXE86dIOY3nAniswHG9LMoGslbDKbw5ZE+/SdmI6dMNkFrEOXci4kmFFbWqFFJoxP2yi5+vSAotDEM1dL5T1LxGhc1Jp4MR2JBFKVBt/KaCb2/u+qwXMzwlQoM2khsUxhZDM4XssFhFpz8K1b0lLnMNjiGTmOUdDUCoZWoWo1bSfFVCuyUpcLGDuj1w/31JMGzS2pUcgrjbTURRX4qkecSLSVN4h4ue6Jif67U2nn5dLa3q0EOh14KcvYZZ04dMyE47FAkGdbn8BKeacv7b66UQhzi2xjE2YmDzpLslJnMWtRFDov56JkffXZIZu9P1LVGtKJK/PmPZdyl1pYbRGblLXK++MbyVbMbLYrybvbJRZVoTLs7niz6aIoDeu1y7M3Yw5bW7JMZxvb9DshllvgmTmKKcKrVeKySFw0rabrxDx7doRuVhhWyfgfQF7qvLwdEjgpzy9H2EYpaR9mir7v+HS9hK4TQ6qxnAUUhUYYWehqzSQM2OYWl1GbXW7Rc2McW6KPnHOdtptgayXDe0umsxbbtSvxW4VJYGd4Vs6gHbHceqSRzLG3qc14vJZ0jVK7u4BdxjKrdU0x8heVxja1uZ52+IefPvyl75VNwz6o+qffvmrrq/eM9qtuFGyjYJfZdC0RmNh6yZPhjHYvZD3371LArb0BteMkvH04oe9GvDWYcdjeMpu1qFFItxavVj2qWuXwdMkydLFudPqtCF2tqXKVQ3dHXBqEhcntssXD7pJF7LGIPAZ+yL3eCscqGA52UsVkNl/MhpK2vPFkhpQ4jEcbdtlebVhp0trSSvwgZZuLqObhw1vyQqdnx+wiWzK8dNkItrHN62dj3uy6vLoZoGs155sOv/HgNYfBlgeDhWCnSo2Lmx6qWlOsxLd0ciizky/N5H03ouMnZJnOyYkAo+93l9zrrFD+YZskM7hdtnj2eoznZxyPVwS2bG6aIaKfotYY9wXpdtpbMfJCNpnNu4+vCKyUUbDj9aLH6T/zmstdm66T7BV2cqWpKg3DgSjpotgCBdpuwmFnw3A/w0tznbabMvRD7g8XYj9pZNMJU6kcvwxYrWuFR+9co2sVUW4yCQOG/R11rZCVGuOnMxy7oO9GdJ0YlYa2mXL16QFhZjHb+oSpRV7pJPuIqW995znGvsugqY2wPfWS+RcihjDNkoEbkRQ6y9BlHTtkuc4kDKSKsWO+eXzF5UeHvD++YbIJ2BYWvpUxiQIWO4+WJR6ywMmwHfFL6vvopazQUVoFllky3QU86i+Y3nTueJbbxKKuVRZbD9WoJI7LzHDNgpEXcpvsU+b9mO8enxPlFt+7OsU3MlpGysgNOTxeoms1n81GtO1E6EatiLKQKtY8EIuGbwqOrXdvLQHJF115jdQqvSBm6Ieklc73L07oBxF9J+L4cEk+lzT3B4dzYavWcgGmGTWjgw1lrdJrxZhGyfRlj+Pumig3efv09i5maRb6GHpFx0zpHW949/CW+/0l/l+7ZJdajPsboszk9HBJ04jy1FRLrqMWV58eAPBm0ePb773i0dmEpwdTukHM7/3eI+LUFEtRZmPrYj8oK5XJosXBn7+i4yQS/BxspZMw2PH5dCSz0mmHxdrn5kpGDMfjFXmhE8UWjpETT3xGwY5+EPH20S0tJ+V6IwD7pDD45uCKrw9uGPRC/mBS8R9l/Ymd4SuzqkZl6IYsUpdBENGzY652bSy9wnALOl4iCsDQvZsHTPdemuk+3WB8sMHSSr7+6JKWk+4NsAbvHEw4/M0rDK3i0zeHHP2nBi83PTa5zfW6zVuHUz66PsTUKtpuwtWyg67UDNyIoRvyqLvANXIUYLUWwUFZqcxmInbYxDbb1ObA3/HZxVjEA27CKnGZhT7zUF50u0KG9avEpWWKNcK2Ckb3l0y2AZpR76uSnL//0RNGdoivy6Z50NpxdLDG0CsePL5lFOwIM4vrhczATrtrrjZtFhsPw6jucsZeLaXdWHxHImy6QYzbSUgzQz7/sxHbyxZPx1Mu1x0CM6OoNPJKu0vQ1tQalUbamuu2hKiuuqxW4gcL9lDftDDu2qS+nUmeWa4xve6wzWzadkJS6Jx216wjh21qM9knC1S1qFLLUsMxcq7WbVpOyv3RgtttS8QtWkVRasye90k2NruthMqC2CZeTiURO610tIOEXWRTlepdmgYgIbuzEUmhs4ocfCujCE0WoUfnscxHh62Qm33qx1lvRZqYFM8DTE0q2rg0uIkD3vu1V/ze+Snp0sFURZh02lrz1nB21zJOC51H/QVJYbBJHdapyO/b3ZiHvQVvDWaUjcrgcIOqNiynAY5VcNpbMWiHdDrS9t/lFkf+lo6V0DIyLl4PGTgR88xjGbp0vYTbOODVrsc6E+h0y5Jq/3LR5V57RbTHxFW1wJ7zSpSfxj4Roe0lWDfS8v3S33joic1m0Jaf3zpzmH5vzPDeko6dsMvk777jJuSlTsePmc0DtqlA3ZtGwTsOefnRMXFq8mI6wLcyXt4OcU1JUolLg6EXin2nVskq4WD6ZkaWmhR7LuvT0VTsC1ZK68FaDsXeitsoIMotns8H7BKb2ql4MBDvn62X2HtLh6o2nI2WGFrFOnFYZzYX2w4tN0VTGkyjJEos3r93xePDKaNDiW868raM21sMo+Rm3cY9CLH1EkOr2OQ2T9ozul5MuX/NTNKA2yRg+rJH72D7S98rG/6k4vtKrLoQ02/ZqMS5pC2nlc5q5VE1CorSSFtJach3JpN5i2Xsstz4KArcLto0jcwKy1oVX9Gqxfm8R1mphIUpLazMoj/YEf1P13RsoXs4VsGreZ9+K+K0teb2gzGPRnM+fHHCzbbFLPaZxCL7VpSGKpKqwbNydLu8syb4lsijg5YcAqoiMGpFadjOPPLM4HrRpqg0hl5IWatMZ627SJWqUrGtgmXochaseP/pOV+shxJ8uw8BjXKTOBG/2u22xTv9CeOevLC+FM0YRkWys+5+FrZZijgokgSLL+0HHV++Z9MpUFoF08hHU2t0pSawUjYLSWPwjZyelZBWAu1tQCKN2hvODpa07PQuLfvL1IXzaQ/HLPD+pggxRkdrVBrC3CIMHfJKQ9dqwtRit3VwjAJbL8gyEQ5sM5t4Iwq9WegTLV3avZDpKiBaOegHCapVUecamtoQhRaz0KcbxFy+GXCzaaHrNY6do5w7YpzedNmlFq9+5wzXlIsJxyo4cELMlrS2kkxSNAxVnDlVrWKqFXWlUAY1s7XP6jbg9WTA7VKUqoeDNf4wIi7l0FcRL2JS6PhOdme9iQtJKvDNjKuVkHBMteKDF6cS2uvJZnp8LMLprNIZezuyfdXpmTlhYTJNfPGzOeKdXKcOtlkwWwX0LFHuXq0kZNnUhPnZDWQ+begVxh57Nlm0GHs7ylolDeVwmd12yLv1HuJdcruW5/hm1iMpdPFEaiXmuxv5/Rr5XVju0BF/atWoHI9XeGZ+h4yLQ4ujt6f0/BjDqLhdtjgertglMt9epu6+DWxwteoAMovPSp12K8bSSoZeKLPLzOF620JR4KSzpqwl4mvohrTdVKKH/IIX+5m/qYlHdLtxSCIZYWSVzlGwpag1Dv0tgZXKa7BWOe2tCAvzH4M+pPtEkCSy6HgJj/oLdrnFfOdx+WrIPPUl/SO0CNyUT28PcPWC9752/qupwBr2Xtiffvuqra/swaeZAgG+2bV40Fny7HrEi5shiirRIh1fTNTp1sLvx2hGzSZ2MC25Mg3+rnMnhpnuAopa47i35v3jax70lswjD9fI5ZByIwZexCpxubzo0zRwr7+k68Q8X/Zpf23B5bqD0xb1ZpSZkiq+J+L/2juvReY/a9MNYg6CHbONT14J0iwMJd3g/Kq/jwGqMYKcw8GaYScUgYnSsMltxiPZQJaxi65LjJCiNJzvuqwyR5ibuX2HW4tTk0E7ZOiFkrMWdij3bc6PbsfklSbG7FJlFUmszHojCs12T4z1jlWQ5gbTK4l6sr2ct04mMmuyxCS8iD3G4zV1o6ArNS83Pa5WHbaJjWfn3Ew6rBOH11dDtqktM0gnJUpNDvwdQSAb8PbPijF7etVlvgyoapVRb3sHcLbMkuODFdNlC1sv+c7ZOX/m3it6TszoYENgpaSZwaP7t3SdhLPhkvHhmoPuFkVtMDwh7VtOgbpPce8ebslzncBJ6XsR93798g4kneYGJ79+RY3C233JxqtR6HgJ02mbZg9SfvF6TGuvOpxEAePhhvGDBb4nytfDwZpxb8sXs6FcZVcq69RhGzrMEo+kNNi97JBkBsnG5pPzQ7K9DeXF9ZCWKyrKSeLz9QdXcpioFaZe4hpyKA8dASoM/ZCH/QWekXO7C0hKg++9OSNoJXz85ghDq9htHXw/ISxNwszCtXN2mVTCb2765JVGvt/kPSdjsfP49r0LrkNJc+8Pd8S5wYN7E4zDmKubLtObDr6TcRF2GPe2YneoNbZ7P+smsdkVFr6Zcb7qEpcGfTdis3WZb322mU3PjtmGEiy9TWwRUBklp4OVANYPJrQHggWz9ZKi0jjurnnzZoimSFhtkhm8fnnAsy+OWGc2npET2BlPezPSUuag15c9Vpmg9VSlEc9oJOrbeeij77UBnY5Yi1QagTOYKXktfsVtZpPnQivaZTZJYfCwt+D1iwM2uc1y0uLx8ZQoM/liNiQwM9LExOhkfHR+hG9m3Bsv0BSxMl3vWsSlwWlr/UvfLxukQ/azbl+19dV7RvvVNAq3yxZFqfF7r06x7IKD/pYq0bH1krTQ2cQ2QS8WH9baoufHjNtbUVf+lRtJjDYzbFOy7dLSYJFI/p2lV9xsWrw3vOWzF0dEuUXbTnj70TWuWZCUBpfrDgNPfGADPyRwMg6CHaNgx1F7w7fuX2Lrpfi4/C3v3L/GMQsBX2cyv1tlDv1OyGzrc3y4uvPd1ZXKMhTfmKbU3O4CvP0GlxYGVaMKWqtR73xxN/MOZamR5AbryCErdEbtHWEqw3tXLzDUirTU6bgJ2a1LmFisXnaxWhnxyiVMLYJAJPxRbFFVKvObNo6Vc+/BVKTyLQk1HQc7Rm4oA///g41nZnTshGerAWEiGWZpKuDos6MFjlkwGm2oGpXZIuB60RZTfm7hGCVZoaPpFS0nxeqKOdo2CibzFmksuXdpZuDoBYeDNeerLv/ozT1+9/pUqlczY5va/Oa9l6JqzC1efXEocOnzATQK1bVLsrFJJh7rN21RqYY2jl2w+f6Q81mPtBT814evTjD1ijc3fapa5SpqoakN12GL+dLnwcmUJ0NhjvbHG24WbQZORJhKe3AdOYSRjaI0NI3C1aSL72RYWollyrx20A65XHSYb306j1dkmYHmlAwHkibh6gX11uRBe8lxsKFrJXz8vQc0jcIPP7pPVas8++yYnhOzSFwGTiRe1Vrjetui6yRcPhvx+HBKVugcj1dcL9o8PJph6ZW00O2U09aazT8acr7s0u2JKf3VvM+usIgSi34Q8dl8RJwbOGZBmMjM2NYFDk+jcHi8EnxaYXAz76CqDbvUomMn2HpJGNmEmcXL6YBxa8uL2YBZ5GOYJVUlbVZVaXjv6JYwF0VxVai4Zn5HhVmlDuNgR15qkgbiygze68WctdfYesHD/oKvv32ONZAOTV5pPAiWvFz3aBqFU3/N4HDDJnagUO9wdd94IrNP0yj59OURZ+01UWruyU8GLTNlk9v4Rs7VskOYWhSxwW0UcODteHPT50dvjvnGu28YOpGEVkc++T4QuqxVzkZLbKugqRQWscc6dUhyg+tZh7d6M3wj5/l88CvYMf9kxveVWJpa0w4kNaD5UvZeafj9+K4339pfwSeZQftwS9+JOPE20srMLBwr52bbEnl2aRDs/XaLnceBt6PrJdSNyr17M/r75Om80rA0QSf1vUgqQ1OQRE0j7cqi1mQDMWOqWmGReHw+GUnEjVKTlzq2K4eYqjS07JSy0LhdtCWPq7XF88Rj5DsZaWmI6s+K7wQhAH07pmWl9ANBstlOTrG0qVF4NJzjOxm3yxZ5Kf6jZSbBo5u1S5SbtE63eHZO79GSItNBaQi3ttDkG4WDrmwwfj8myUxuVy2SwsDSSsbujqgwMfc4sNf/SoOu1uxyC0OtuN9f8ngwZ9iRduPNso2hCiHG2Vsk6lLFNzNalgCSx/6OUUesHf0gIkpFcet4OYPejqpRSCMTVy+4eDOQj2tHjILwTtiiqQ3TJOBq2RF49NGObWzjdOR3qx3JvHJ0f4m10IgnvkTI5Dr5ccHj8Uw+TqkZjYSm0uwrtDCzRLKeGwKRTsTPlWaCuRt2pLWmqYLIqhsF/XOXeGsLmquVyP0o9NxY0FWawMjH7S1RatJrRVhWQZiadOwE38hon2yYpy4f34zFsP1gi6FVeIehoNkeze7mXC+Xfa5uuuwym821WALapxuS0tjDxhuqXOPFJ8ckuYGpiz1hl1u0vzu7w+qtE4e2K8HMX3bCRoGItvJSx7MloQLEXE8qApttKi3Ydium68VsX3ckHHbvZdvt0WxpaeA7mYRAt7dUhXoHfggLk5vbrszwB1vi3KRjpfTtmMDMMNWKODeJS8nzG9gRLSdjndlklc46c7gNAzxb1LTn0z7fvznhfnuFpZdMUx/HKPDtDGoJPN7OJcMwzg0ZaZQqLTPl3YMJVSPe1rg08YycuDTw3AzbKH6cMQh0exGmI7PBtNR5fT348TilVIkLk9eXQ7pezHv3ryVqqpKD93Cw4Spso6s1afxjS8Qvc9W18jNvX7Wl///7AfyqVt1IPM7A33IYbLlcS2CsoVe8WfQIHAFQXy46nPTXFLXGs9mQfOJgjWPStc3gUEDHN+s2I2/O57cjdL3m6Wgqc7/U4pL2ndQ4sDPe3Pbxg5Sn/Rlvll3abspi5/FoKEq1F5MBZabzrYcXvAm79NwYWyvv7AvNfv747sGE2yhgHcs8iUYhCBJptcSiEgWIcmFn5juTfCx+wGXsUlYq17sWHUeqIFVpGAU75kpDYGa8XvQYtiQD78DfUXZlIz6f9jCsUhSElcQTqUrDvfFCNsVG8tkeD+a8WPQx9QpVFYpMWui07JSrVedu/nndKISZSOezUr+LolklLpvY5qy3whyUzLY+r6d9bFs2hnePBRN1Gwb736fCddii2V+Bdh3hFka5hW0WbBObPDH4009e8oObYzoHO9qOcB3bdsIice/+Nja5zUlffJKGXjHwQ8LMIjc1otgi3tkCGfjWkrc7Kz6dHKCqDeOjFb6Rs923/GyjQPUaFpXKuLWlrFXG7o6bSOZYmlrzat4HBYmwKnRerXtEocVgHJIWOul7Ifc7G9apQ2BnXF706T+I2KY2qtpw7G94sxMlYNtNWWw8bFvasbZWEpcSg2NqFW0v4ZPJAff7SyZhQMdNuF22WOwkVHW3cXh0Ikz4tp2wGkhUUNMoXNz0aHdjksKg24vQB3JB0LUSXi77JKnB0/EUVWn48ON7PHn7iutN+w5WsNh5tNyUvJCYqC/FSS9mA3wnY3RvSVmrVLVCy8h4lfYxtYruwxUX247YVoyKwEmZ3XboejFprnPob5lGPkErQVHg809OePLOFd9+/EZ+lplchC0Sl6LW7ryx7w4nvNz07pTb232HYeBE/OjzM5RMxRglpLlOrx0SphazxKNrJ8SlQWBmRIXJk6dXhLnFcLzmhy9OcdvixX386IZ/dH6Pw94Gz8i5WbaJA4Mwt8hLjeNgQ1SYvP/0nJ4VE5YWmlLztfEtP/o7TzDe2aCZEtTbDUKKWuNm1sbrSEtfV2s6tnyv5Y+GfOfPfsqrTZ+4LHl4NOP1L3m//JJ1+9+X9ZWt+HS1YhPbzBOPSRhw1N7QdlN8K0dVazaRqPd8TyqmulF452DC+NGCrpfQH28x1JrzaZ9+EDGLfR6MFhSFxmfTEZvcpufGzDY+aaFz2lqzilweHM73YZcVT4eS/F1XCrs98Pikv8bxhfzy7JNjdKXmetciyk0uLyUxwtLEDNyzY5LYZH3RBqUhikVw4Zk51+s2011A25YN5ttvvaFpwNULZjNBfJ20NsSFyfxHMt8wtYq81LiYd/nawS2zragaN6nD8xeHDOyYJ0dTSQRoVAZeRFZq3E7bnE8kuDfKTXp+fDfH+DJXbb7yUdWGKBfJ982iLYG1mtgmqlrh9YsDdK1il9hUjSIJEY3C5bSLawt+rSikYk4rXbBus7bkE+bSNssKnc3a5fW1tHtub8Ub+HCwwLBKvn95SnIrBIy81NG0mnivhlSUhradMN/6LGOXeeSR5jqLyMPURd2p6zUPjmfUtSLxPaseHU9QXFFm8qOrI6LMZLtXObZtSWdfJw7L2OWL1ZBdbrHLLQJTDO/jzpYws9gmNpuVi2bUdzPJfhDJwTELMLWS7sGOeeSxS2y6TsxnyxGLncfFrCfVgVaTJpI3uExdns0HnAUrtplUxCfdNdvMZrX0RPTUCfn6+IY4tuj1Q3wj52FvIdW4Xt29Xn7t4QWnrTWeme8B1DWWWZDXGm03oUwNFonH+abDk7f3QcWVSllpxBuHItfpOjF1rXL/YE7fjWi7KeU+WaJqFJy9mb9rRnx9fCPBxrkIXFp2yqi9k9zKfsT1tINv5+S1xiZ2pAJeeFgHwvK82rWJU5M0Nkl2AmefbQQq8GrZ4+Wmx5EvIq0ot4i3NmfBGgBFazAPYo578nbLlq5IlJusM5tnVyPSUmeyEczfdBWwiRzun8x4MphjaSW2JnD1ulF4Phny1sGUz54fYagVR8GWdeagqTWf3hzw+WpEvG+PT2Kf9//cM6papUwMuo7EVhWVRh0aDP2Q61mHTycSXrvauZRBxcezMdNFwBeXB6TlryaPr6qVn3n7qq2v7MFX1SpFoROmluSn7a9mksIgTX4swY5iC1MvWYUu17sWti5ikDCR0FfTkrnXfOVT1irDToipC90/LgR5FdgZz2ZDOm7CizcH+E5GXEqr5ePbMZYlFc1y7nO9anPQEuVb63QrrbDCwNZLHpxN71pdKg2mVlHvDNxxSJVplLlGEkvCd8tJcc1836KqWGc2s9sOZa3y4GQmSfOFtAKpFTn09knUVSIHs6I0LLcumlpzeLokLg0GdoRr5hhqxaNgQXvPyERB/H2FzuWFiBt6fszQC4XZmcqB9OVVYxkZ2LqIbHxbKpJgHHL5ckjXj1lMpCqaRx5HwzWmVnHcW+O7GRezHsvElcq8E5OEFmWs45sZ97tLWu0Y1ZCWj+4ISmwSBvhuRr5wsA/2Sr+9MME3M7aZzF7msVQmPTdmu3GxzVKM63rBIJDw1dtNi14Q36W0b2Ib18nQtBrXkVidJDNYx46ArPeA8S+fu2fmwlPd4+62qU3HTlBAomXcDN/OaPab6i6zMb2CtDQEzlxpWGZxx34ctkJOh0scs6DjJ3TaEetY8u1Mo6KsNWZbEVyYe5XkcLDj0N+yTSwARr0tp601i1RM1U2jsLsMiDYOZaVyse1gayXnn41p2SnzjVwULWIJR9btgttpm7pW6VkJYS6Cl3Xk4LYTUBquNwL0vlhKIGuYWnS7EWedlVhXFm1moc+z7ZDrqMVk1aKuVVY7qdZUGry9klhRYZdYdy3Vlpmh2yVZaBHubPElNgqaUaPbJYf+llFH2uu6VqMpDfmeu5sUOq1uzA9vjmiZKW435sloxuuXB5ISH3t4Rs70qsvT9pR3Tm6pGpXHgzkXyy7j3hbHzuk7MWml07ZSOlZCx0/EIxwZErZ8uOVyIa/BopL8Tccu2MQ2eaXx6tMj4ebGPqZe4baTO0BCWatYA6nwdLOiH0TymvFS0KQzoeo13W4keL9fwfoTZNlXYDUo2L/jET9rY+gVSWkw3/isN0Km17Saw/aWQTvk2JNsuLQweH0xZJvYjDtbYWFq9R1N43zaJ7BE3mwaksk3Hm0k1aG75nbZojMMMbWKj/7hQ7aZjedkEixrFnjtlLaXsMvlCvXb4wuiQrBYAEWtEVgp69hhnTl8MjlA78hGSyYtQlWrMfycTeSwDuWg6fmxfL2nr3H1Qlo+bky2T5M++fUrPn95xOVCjMR2K+MfPn9AGpsM2pLoAPD87zzgg5tj2maKrZV8b3rKIvQYDra0WkIcccyCrz2+5GLepapV5rHH2Nvx9OE1TbS3i7zysNpCwgfxufXcWKrQhzOaRsFqiVXD0sVSYuuCAVuedzgdLtGUhn4QUTcKX7t3jdtN+PzNmLg0OGltGHZC7h/O8VxJja8bheNgg9lPMI2SfhDRHsjvwtZKHKPgk6tDRl7IoS8V2NFozepFl6aBi0VXZrm5Qc+P0faGa8cseGs4493BhONgQ5bLhUa0dHl3OBFp+kLa0eLzLAkzi6Q0eL3q8ebNkDCycIwC184ZDjf4llTUDwYLbLtg+aMh/SCSn5MtwPQwdNjlFuvYIcwsXr06EN7j2pcKqhLfXJbrvNl272bYplZxMe/SdWJcPaflZLzc9ATHppXEucnHr4/JS43RwyVPzm4ZBBGrncuLdR+lk+PoBWeDJZZR3ll+vnVyhTo38aycZSYhuq6ZC0dyH++1u/Wx937B21mbx/05Kg2f345Y7VyqRCdJTVpmxmQVEHgpLTdF1Rpu1y2mO59PL8c4Rs79gzkdLyHO5QDdZDYn/TXHh0s6nRjfzilSnbqW2WlcCq3HUCvSXIhI58suw5ZkIHpWzqPBnA+nhzhWweW2jdVPeHs4pdoH9T5+dMNHq0Mut23m/+URi8Rj2AopKo2j1pa4NFglLjdhC1MtGbohy9Tl0b2JfH8nlvSPwiQrBTxx0lnztYNbrtdtDp/M7qwBXS/mXm/F68sh1+s2DzpLDto7PDND1yrRGeTy+nny1jUnwYZHe7j3tx+/+ZXsl79KcYuiKD1FUf4LRVGe7f/t/gKf8+8qivI/3v//byuK8rmiKD9QFOVTRVH+2h/n8XxlDz5VqTF/ew7HMsu7mXcwjBLDKrn+eCzG0lyo+ee7LtHCpe0mDA82jIIdQ0eiYvpexCZ1eO/olnF/w8gR6X/LFoXZl/LnM3+FbRdEscXNiwHWY8l1c4yCtJCqUFUaPDNntRIKx3XcxtELLE0SHeLcJNm3Ma5eDKkqlYPujoeDBYpbMujtaAcJnpsJMSPT6FgJQ0eoLbdRwKfzkVR7uVwRv1z2xfvk57x/LAPzlpty/2hOtyskkZ4ropjySUKWmtyELaaRj7JHc81mYg3YpjaLtc808nk6nhJYKYZa89HtmC8uDugcb3G8jKpVcdTZSPBvanI+7fFm0SMvNZLCYOiGDIKItp3gGjmbREgYo2AHjrTf0j2VJtrKPK0sNXS75NXFiI9fH2HrhSQ3fNFFVWvyQuNq10bTaqJY/FBdR+Yll7s2h65YIl7N+0yiAEWRdIH3v/WK7cYlX9qsEoeqkVnn7HfHTJcB853Hs9mQD65PuNiIMbnrJAwON3x4e8jzmxH9kzUjP5RA11Jned7h8mJA20146+EN3UDin5LMQFNFwbm8bPNq1kfXKhq1YboUj+gsFpWf58nPtuWkWHqJ1U0ZezuqQgzFLTelqDQBejsxeSUBu7dRgO/JfGqZuZJtF8uF3DJzeKc/4em9m7vYn7KWjkPLl8DVdke+1tiV14Br5Fye97mOWozelZDjbG9S94ycoRdS5Rq+l2INEhSl4XrdxrBKPpkcEKYWB90ddanSGe0wzRJdqXkynlHu28f9IBK8nVmiqPDqcsTAjnGNnHFLcHxxYbLLLa4nHfpuhKo0fO3sGsOouHndv7Na+EYuSuXC5PFgTloYfD4ZEWUCiW45KT0nRtsnzZe1SpbrPPu9M15PBndmbe83Z9SNBDX33YioEMLP9FzA0ddxm10hFybr1GEWScWdp5K9lxc6aWlwvW3x0WTMsBWy2HpsZgG7VF6bn74+pD/a0g8irsMW042AvrPUZDZrMdv6dJ2YslbZ5kLg+fXRBX0z+ik73h9zNb+cik9RlD+vKMq/+1Pe9b8D/mbTNE+Av7l/+w+7/oWmab4J/Cbwf1QU5Y+s8vnKHnwALSvlbLRg+byHpktSQ8+PMU4l2TmvREY833moVkXfjlntXNlQC1NI8nsvX1mr9OyYvNLJKp1NYguOKBOT8XUsg/66UsGWjLCoEA9UHFvoSn3n43p0NCOvNDpmyizyWSXO3ePNS52yUvEOBQf15Wp35MUaJhbbjUtW6igzi7JR+Xw2RN3TTTYzn5adMnAiksIgywRC/M3jK2aJh67W3GutKGqNgRsJo1Qv0dSGw8GaIJDNa/Gsz2LakiDeVvqPXfXNLrvUKFyuOgLZjkx6/ZDtxiHPdbwDUbhuE5t7gyWOm2Po0moFWO0rhkXksdtf1a4Sl0Xk0R9tWUQe25XHLPbp9CI+fHmCbRVUhcaD0ymdfiQetCjAfbwhSYWxuFz4lKWGbRd4+7y2ppGfa9sUyXyWGEwXIi/PC51F6nIw2DK+t8TSK3xLUrazcYFplXfJ4IGTEu5sylrUhWFi4TkZqlazmAeUtSoBvbFN53SDYojxPswtAf3WKq794/lZ72SDbRWEoUPVqmhubWyroG0n7BKbB90ls7VPXmloas29/pJp5DMaytzKNqSFtk4crjdtFpMWxV5R3HViPCPn81eHTEOJgIpyk1nkM0895rEnkO1KZRm77BILlUbCidWKZeySVgbT2Gfs7Di9N8c3MzwzIzAzAkPA3S0jExtMkNFzpUre3gQkoXUXoZXMXMLMxPGEqBKtHZaZtIi3CzmIwtSimjp0nRjDLLH3M/AXzw4FMFHohKlJy0oJ2gnn/9UZgSVdCc/JOLy/oG0nhIXMl7tWIs8rt6gahWE7JAxt4twgzk0hrGxcMYiXBoZRUXdKqkTn5rrL+raFrtVUjYKrF9haKbmUSsPTp1fklU7PitGUGtsspDNgFJS1im5VLCIPxxKAgmsWJFvxCvaCmNYgRFMbtonN4XhNnJpc3XY58rd0/Zhp5AuOrhYvqKnJ72O6C1hEHpvC4ZP1wa9kv2xq5WfefgnrLwP/3v7//x7wV37/Byiy/k1FUT5RFOU/BUY/42v5QARUP+P9f+D6yh58RaHzZtLn1ReHvPX+Bb6b8e5wwjJ0abspu9Ri4EUUr3yy0OT+0ZyLbQffy5jGPs+uR3zt4JakMJhcd3i56LPLLfL9PGXkhwRuSvHGx9YLLlYdTltrDgdrjk8W3G+vKCqNrhPz1tEERWkYuSFJYfJq2ievdJ6tBgy9kCQzCfZ8Q0OrqGuVo/aGbSKm12nks575rCOHItUxnYL1xkU/jTDVivdGQs+fRT7tYch0JxuxinieZpHPZdimqlU+f3nETRwwWbWYxx6XbwZ8djFmuZODylArWlbK4K0F4/EatxtjmyWemRGnJlWu4g4jJmHAYXsrFg1NEsg7nZim3icfOCkPewvOl125so+EFWnrcsUfZia7rcNiKuiwqlZIM4OeEwveyipZh3JAkotq8pv3L6V6VStuQpnHmkZJvxXdzXsGbTHid52YTWLL77jWeLHt03ciDLuk1U54NhuSbG2mG0kiV5QG2yi4nHRZXLdpD0P6QcT9rlBPOk6CaZdUtSLRU25KnJqSVaiL8rUqZIb6oLPkYCiWgpvbDj0nJp2K0tbUSy5ueiSZhI6O+xvG95Z0ny6wjYI3i96ewB/Rb0dsQ4c4N3l5O2SxnzPXtcyAHasQ0Hawwwxyxt6Orp3g6gWb1MHrik/Nt2Se+E5/IuQdveTt4ZTAzog/7GEaJYsvBiwv21SNCFZaRsLY2/Fq16NtSgL6IvZYxJIscnndZ5Z45JVGdO1zMe9S1yonD2eMhltuly2GrZDD+wuxOOQSyvr0/g1Xqw43szbvPLxmHTlCSXm8EGW0k/L18Y0oGzsZdaNQ5Pq+mjbYXrQ4+7PnvLwd8oOrY9ZbF3c/u71ZCzy6bFRGfkhW6XTshFXk4Lg57wym+FbGNrGpSxXlE6nSPCtH93Jag5BH9yY8fnRzB6eoG4XLbVtmy1Z6F122zh1e3wxYfSaA7jAzuVx1cPdZkF0nvguI7gzE86ipNdEzsdHkhcysTaOk1w/50dUR28RGUxuJGLMrjoMNrxc92k5K1xMKTFiYfK178yvZM/8AcstAUZTv/cTtD9tqPGia5ka+T3PDTz/U/kfAU+DrwP8C+DO/7/1fhpp/DvzvfyKo/A+9vrIHn2mWPDmacvJ4yvWmjalVfHB5LLR6R+Yos9Dn3e++ot2LGNgxcWpyr71itvEZdEPmqSsp1acLfDtjnTrMEw/XzlkmspF1316wjF08K+f1WhBW69jhBxfHWFpJzxZ6TNMobHOLKDO5N5QX0XrjEuYWT4azu8G+oVZoWs1yL7+39JLNzsHwCkFS2SVFpmNaklO2yiTl4fPPj+m7Ec0eI/VsOrxjTNa1cneoBf2ITewI87JSUZ2Se+MF74wnbBces3mLV58fso4c+o58vaEXcrmQ1G+3lQqV4qM+r96MiHOToCVhvWmuo2o1ji1BommloyoNbw1nvHdyg6GLoOZ61WZz3aLXC2kqBSdIWW49Or4oVOfP+1RLi46f0HcjsEV5Gpfih7OMktPWWg74SmUVutzcdNH0iqQwyGvtLvUhrzTCzOJyIRluo/aO/O/1cO2c46Ml/SBi+apLUhjMdx62m9MahRy3N6SlPP5+EInRONXZblyaSiEtdEko92M8L+PNrMdbRxOi3OTVusc7vds7gsnttsXZkwnbjYujFxyPVzJ7OlrIlb+/5ay1ZhM5Eg218/hgesJ8KQntfTfiu/df43g5UWoSOBlvbvqs37R5azDj9WRAce1yGwWoSsPHL072pngY+iGWVvKkO2edO2SVzjaxebHqcz3pUD+M2aw86l4OplzAhAuXf3DxgB+cnwAQlwYdK92LlyAwM1rdCEsvaZkZWi9j3NtSVSrTTUBa6BJWrJV31VDHF6tEUhp0/Zij0VpA1I1Cnussty7LrcfbvSm/d3HCbRTwYLSgbhTeP71i2Arp2TEP3r7B1Qt8P+HhaI5lFVyuOqg0HHfXvP58zD1vyS6z0dSaXWYzCCKO2hs+Xw6l8vJjxqMN2UnBF9cHzOYSC2Tp5Z3Ptm4UBl7EF7MhR8GWZ7MhF987oaw0Xiz7IhAqVY6+fktViwK6LDQ2a4E8vJmJXejLddpbSTrFw620MP2YFzdDBl5EnJqcDZacdVfcXPTYJRaHgzXT2OegtWO2FaRcOBd4xt/44P1f+n7ZNCK8+lk3YL4PFf/y9m//5OcrivI7iqL8APh3gH92P4v7gaIof+kP8TD+LPD/bJqmaprmGvhbv+/9/0LTNO8DZ8D/RlGUe3/U5/uVPfgAJqH009tuQmClDDshRSmIpK6VEMUW55sOaW6wLYTIYGslriNt0Ktlh9vl3pRtlJhaxfWkw3LhY+slcWJh7HP4tol4v9pOStMgyeIbAU77VsbloiPQ69aWl9dDeQydSPBM667kzxUmUW5iGSLG+JL/WIQmxcymCE08J6OZWxh6hWmWBGbGF5MR7719IfQIJ+XQ3+I6OVfXPV7N+sSJSfIm4NgXIU7LSfGdjM3cp9uN7ozGil6jGTXt0w3a/nl92bLVdRm457mOAhhPtmhOiW0W+7aQehfa6dsS/DvZBZhGSdmonG86bEOZw6jq/hLSjXhwb0qeGdAorCOHZ+cHBPc3qG2JifKNnNFwy3TW4nYXYOtyqE5j/+7nc9pbMTrYkMcyHy0qjSQzyHLhNG5WLp6bYWiVHDR/8YJHnQXXn43YxDbte2vyQuO90YRBEEl6/L7lfBO26FoJ3j7J3HZztGubzSS4a0P6dkbLT4V440hL9Tzs4luZQLA/6JDkBjQQ5hY3izZRbjLdBOwuWrxcCfT7qLshS0Vcs906WE6Brta8vB2S13uuaS2HbrcXMX60ICxMjocrBo8XLHYezxYDDD+/Y7/OQjFefzI7YJ06dxaPLwUdtl3Q6sT0Bzs0u8K1c1qDiHF7i+2I93Cb2XdhyLvEZpm6bBcSeHy5bXN/tOB61qGuVPKtBK26Ri6JDI1ELX2pCJ7vPFahKzmJsUdVqnSDmCI0GXZC5plHFQu71jdyaXvn1l1bsmpUVpmDpjZ7/6sg/Fp2Kib2B+LP7DpiZj9tCSZvk0orNS11JvMWQzekaeBstCBoJySp2DuWicv5+RBXL+RQ34dM143Ce3/mBX0n4kF3KWG6XanC0kwuDDqtmKZWyHId18mZbgJGnsATwtyiaRSSyKKu5GeiKHCzaWHoFa9uBqwSF/dcx7VzDtxQIq4MsfkERobTTbm87PP+019VEO0fndXZNM1v7Odv/3PgrzdN88397T/ff8hEUZRDgP2/05/1pX6B7zUDfg/4jT/4kf309ZU9+MpKZfOysz+IJOwVoOWmJIXBy2WfXivird6ctivBmrpWM0/lqvY42PBguMBzM7pOzC6VeUG3FzHo77i67uE60p4c+SHDVsjj/pzF/+cIxyq4mbcZtEJWmUNVq5z019xMZCY26AnKK80NTrw1Az+k68TcblqY+zmTzBRg4ES0hyHOYQRaw+KiQ+vBmqKUTXceeQReyjpzSApJbt4VFt8aXaJZFc1zH9MsOXnvlo9mYx7357hGTstKMYMc38rI95WZ42ccDtYoCphGycefn5LmOpc3PalsrJxxT2YRbTcVpecenH056bKLbDRNzMxVrXAQ7Ej2nremUegGsWDHtBqzJ/PNi1mPYXeHZecMWyG/9fQ5fS/inZNbzi8Hd3Ezo+EW19zHTDlSPYjXLeFq3WY6beHtWaivvxhjmwWBk/JoMOe33/6cJ925KP4+FGrJ752fcvzOhKLQcfeBqs9WgzuY8sW8y+PegrTQZY5l5MxDH9/OcN5eMzheo6kNN4s2R/4WXa25WokloKhVprsATanJSp1v/aVPOQq2tDoxt18M0Y2K1cqjrhXMg5i2I3FTt5sW7xzfcuCGPBjPpUuQ2XheyutNlzAVtmtVqwKa3rk8+/yYvBRwwFFng2sWd7PhTeQQJyY3mxa7pcs6cqgahV1ok5cag77M4XStZuztZB5+2UZVa7JK52FvgWfmEiOVSwVlGvL9hwcbLL3EMQtenB8QBAm9dkjQj5hddrndtnh+M7oTRrStlCiyOO2u+R/c/4KH3SWnrTW9Vkxa6Ny7NyMpdNapQ+9gi2MIyOBJfy5hrHusmWfkWFrJgS/sSnt/gagqDa/WPVQa/rPP3uXTl0csYmnFfgm+7lgpulrz4HDOF7Mhp2dzNqnDg+6Sk/6KpBBbghlk7AqLaSxQ9bzS+cbhNT96fcwi8YR+s+wwCoRHalsy3+s5Mb/x+DWBl/KkP+fJcMblts0ukkBee5+5qOs1Fzc9LDuXscubNrpZye/nGyH32yvWmY2llTybiXVJVRoOOxu+/dYbnrZ+1pnxx1k/e773S5rx/XXgr+7//1eB//infMx/BfzziqJo+8PxL/zUR6ooLvAt4MUf9cF8ZQ8+TW3w722llVKKl6ppFPEGzX3i2GKX2Hx4e4im1uSVJhljlpjcB3Z053eahT4DL6JjJ3eKzuMjmf1sEwnVnG7EVOv9hRlpbjDohkw3ATcLma0deluent2KH0mTasqzctLKoLc3oQ9akuqsKTVvDUT6fLVr0/ci+oFklgFCxnBSdluHgRdxr71i4EQc+lt2z7pEuckH0xOG3R3qWzse9AQArCjwatXj2bMjLL2k4yXMd5IQoSs1bVfCVQ/8HZZecfJgRrx1UDYGs61PVupcvB5yfdnjdtK5qxrqRkE3Kzw3I4sNOl7CQWvH9abN1w9vUJSGg2BHUUuCgmvm4rlKTVw3I8pMTEPM9T+aHfL6esCnV2O8TsLVro2rF1SNInaUyOHzj04luPXjgNcvD8gyg+Fwy0lnzYG/48k7V3tBhHX39/C7z+4LtqwBz8wwzFLav/uN3LdzDoMteanhGjlH/Q0/uDjmuL3h45sxcSGztC/hAOutSxhbHPY3qDTklcY3Dq9FWao0nHUk1DXNdT5fjni57GPpFY1Vk80dRv0dxY2LbRVMNgEvJwP6QcQmt+UQ3LaoPg+Ic4PtStrq26nPuLWl74vXUtNq2sdSnaelIZFU+7icvhvRC2JOByt8O+dbT6RK2EU2uiGq26NA4Nu6WnMTttikDv1TUai2rJRZ7BPlJseu0En0vcr0dtLB1CvxQqY2hiuQ8i+RZ+4wwjYLeu2QXWST5AZxacDUJipMPl0fyHMMAzaxTRRbd/PYnh3TdyPWkUPLSPm9V6d0nfgut/DT14eUtcrNrkXLTqnZtyRfHKIpNWN/xzsnt+iuwOavwxZJKZ7L54uBsE0bSVDZpRbLacDrdZfOPnlitva5N1gy33loao2hVtx+eMDFrkOrEwttqLPisLfh+YvDu4umvNaIC5NJ7KMpDbdRgL3P+Wz5CVfXPRYrn/FoQ1Fo9PohZaVhaBX+2ZZ8afNoIBjBRSLCm5dXQx4MFvTs+I6l2zIS/l9/57u/mk2z+Tm3P/76N4C/qCjKM+Av7t/+/ev/DTwDPgT+LeDv/L73//v7dur3gX+3aZrv/1EfzC908CmK8luKomi/775f+6N+0/9frLJS0bSaMLPISp3t1pEYFL2i1YvotUO6fkzXF/n28rm0m26jQCKL1IrpLqDrxaiq5MZVtUpSGjLgz03ud2RTqRrBIs1XPptYru7C1CRwU44Haw68HctMEtxdPefE3/CDDx5SNQp5rfPB9x5JKyc3GXkh57OevDjNgtPWmoEtZmjXyDF7KYoC69Bl0BPD7izx+Hw6Qldrvv0bz4gSiyzXsfWCo86GGuXuBWrpJcOTFQM7umthqErDi3Wfx+35HYndMzMMteLByZTxWzMcS4b9+lrD7qSoKwPzJ3xeAHFi0pQqu0SqF8uQmJuy0lgmYpQ3tIr77RWLnUeZS/tu3NpiahW6VrO+baFoDZ12THQZ3EVLbXYOh70Nx901o0cLJvMWh3/mCnKVKpG5FXCnHD3prjGNkmXq4qgFQTcGoPPtGWEmreKs0KlrlXXoMHQF32YZJRfLLklu0FQKSWHQ9hImq0CEEG1R5lpWQZHqWFrJ7z67L1FQZoxvZSKMaKTqAyhKDd8W3+L4bIkaFMw3Hu6ZhOuWr3xoZA6rKg27zOatwYyzP3WBooDXlk35wYMJm327chM7xEuHNDcoKk1a8rnBdCdRUFebNtvEoqg1ptMWq9QhSwxQfoymCvcp7FWjsA1tdpFNmhu4esGpt0ZRGu63V2xyhxfTATfbFm0zJejEmJps6kMv5K2DKW8NZ6xCV+Z+ToZjSMBtMbPx9qAF+54oUheRwJc1tSHbWYx7Us27urTVB3aEYxVMU5/7h1LxdZ2Yx/05pitJJPXflNerodZsM5vB0QbLKJknHh+/OaJMjX3qvCGwaj+iKDXi0uBqKZaIcbCj1Zd/p7FP34kYtCOBtevVHVji3e+84tDfkuaGtIB1uVgaHa9YRw670GYSCuXl0Nuy2+PRylr9sWraLnG8nG0iz3d+1aHMNQIjYxTs6BxvuY2ExNR3Yi7mYnOLCpOyEVGLqVW83vXQDpNf/obZ/HJUnU3T/O2maf5nP+X+RdM0v900zZP9v8uf8jFN0zT/ctM07zZN81f2t/9o/74/3zTN03379J2maf71P87T/UUrvv8c+FuKovykjvbf+UU+cV+2fqAoyn+yf/tnGhkVRflXFUV5vjcq/qWfuP/biqJ8uH/f/0VR/uAM4qYUcHCSGXz38Jyz0ZIwsiW6Ri/lMNgbhhe3be69e8MqcZmuRfG4K+TKrtgnoI9bkrUV5ZKrpSoNX8yG3GutWIQeT4YzTkYrbFM4ig96S5LMIC91rvdX02WtMk18fCPFOpIKMixMnHs7uVI2c5apy1uHUy53ba7mHVw957P5iF1usUxcilRg064j6rSL2x7LUEQb17sWk8TnvfEt4/aWdercKTxHbkhdK6x2LmN/R1lrWEaJbZYERka1T7u++uEhF6sOq8Tlet3m1eUQWy84a685bG85+7Urfu3oksHTOQM34uq6JyKPICafiZIwSwzxXqUml9s2cS6zN1OrWIQeaaULXUOv7uYvh/4WWy/whxEH/S2WXnL4ZIZjFpIQ4Kd7uK9BXmkMeiFdO0EfJpycLDho70T0YOSsE/FV7bYOIzckq3UGfsjICclKjdm8JfMTOxehRXcDQMsQr+Vxd83Ai/jTj16xiDxGXsi3Tq642co85kvGZ9BOeHk9xA4yPDPnH97co2sldO2EqDA56ayJFq5Qdoyc3T6J4enxhJYvyfOeldN+Z8n9gzn3u0vBtZU6n8+G4pUzc9x9Dt3FrEeSGyxDl28cXqN7JQrC3fS9lJaTctDaMVmImOpeb8V86+O1U7JKx/MzvnV0xXF3zTKWaKlDf8v99opxb8v7x9e4Zs4ms/kvn7/F7azNx9MDXm+6PBgusPQS38hJUoOWKQf5szdjPjk/ZJmKGMsxxZKxiR2Wqcvxk5kAwXUh0VS1SstJaVkp91orxuO1jAL8DVc7UWW+3vaIUpNN6jCwYx51ROTy0dUhjp3zejKAv7DizbyHptYU+xgtz8hZ7DzuH80ZDjdCRKlUOWhjh0eDOdPQx3czFrFEPfXcmHA/Q4wKk74TsclsfCvnwNvRs6TaOt92sIySpDBJS30fCGyQpQbtIGH9TA7i56sBydwlL3XmiYehVvKYRgtGwQ7fzpmu5YLo3sGCTW5TNwoPOss7LvAk9um0YoYDaUV/GR312XREmFn8mXuvfpGt94+wlJ9z+2qtX/Tg+xz4PwF/W1GULyWmv+hP418BPv2Jt3+qkVFRlHeBfx54D/gngf/bT1SZ/xbw14An+9s/+Qd/W0k/vt9fsspdlrFLvx1x0N7hmIVkddUaNQpmkPG4PZfqqh3y/vE157sOV7s2PVsg0lWtsk1s1huJAVpOWtSNwjx1KUqNL2ZDFqEnL5jWDlOriG98nP08zTHEV3a7bfGj+RGqWrOIPTapQ3Tr4xs5l89HTJctXs0F4GvbBd+7OCPc2WhKw2Lawm+lFKXGbithocP+jj9/9px7/kpUnIXBp9MRY3cnc60vqTWJR9MoPDqYM4kCXm16TFYt1huXvNbYriWFvv/unHdGEi9kmwXHhyuu122udm2u123Op30+XRzQdyOS0qAzCKkalaJW0bq5bGrthL4ncyZdq8UvthTbx0lnzetVj6LU6PgJ68hhOm3xZtOV8NRgJ+GwmXmXI1fVCof+ViwDtSrKV7Xm1bpHGZlM1wFXHxwS75mrnpmz3TjYbs6bTZdP1gfklc6L9YDNZZsnpxN2W0ndnq6CO0D57z6/T2BkXC07rFMHdd/jKRuVZeYw9EPW04DpRjauL1Wq3zoSko2hVyxSlx+8PuFm3uF82eXB/eldpJXnZkxXAS+mAzSlFgvKKmD9vMtgH0H1ZtFjPffxbZlbnQUrdK3G1kt8PxFhSqHxYt1n3N/w3vj2rrJwjZzbTYtRT2KvANLQwrNkLtb1hLHasxM2c59034KMS4Njb8tnsxGb2JE5mp3j+hlPBnPJ+QsDmWnGAePelkUqmLFHZxN6/ZD5zmPc3pKXOp+/kagnW5d2Y78VsUxcAidjvvGZb+Xv/SYOJDVElxzBotREBFNpDIKIR505YWmyLSxevjqg04opSo3DgZBYhu2Q2cZnsfZ53FswskO+cXjN4/acrNT5tdEl749v8O2MvhfRs2Kh/ngh65nPdBOQVfpdUsbNpsXHr455fT24Y87+vc8fcbVrE5gZ7w1v8cyMWexjaSW+neH7KYubFve+fsUydBl4EeMzAXLfLtrcbloUuczQV4mLqZe8PZ5wen9G1ahYmhyml9s2qtIIAL/S6DmxgAlKnZPWhraZ0vEEKv53Pn76C269f8hV/5zbV2z9ogdf0zTNfwL8s8C/qSjKv8wv0PlVFOUE+Kf5x6vDn2Vk/MvAf9A0TdY0zSvgOfDd/ZCz1TTNP2iapgH+7/wU8+N/Y6mQ5gafvTgiLfU7Jl7dKKxjh11qieS+1Bl3t+wKaZXdvBow2f9hg5D8P3p2wjqV4NhOO2I2a6E5Ylaf7gK0fYJBYGfMNpLGfBsFOOOI6U4k5iNHvGYCfVXJMoN77RWryOH4oUTdmINEJPlLB9/MSGITx85pKhVNrekMQlpOSh6a6FaFY5RUjUJSGQRGeieNj+YedaNyGbZJM0E5dazkDo2WV5qQL45uuHew4Hbb4t7hghpJnQao9i3K2dYni0yJS9qT7NPM4GYnSe9NA8srMVB32hGLnUffjbhadvj6+IYwtchSk6aWys7WSmyjoCxVktygqlQenU45DLYM9tlpnZa0JVWloWoUahRezAcS+5PIbHab2GxedRgfrST1/TglKcXzeLno8OBwjm9LAnrbTLnfWlLVCqP7S7JKp90ROLDvpSxDlzw2aPdCPn5zRFVKPuJ13KLrxbi6tNdcvWB8tMLbi5pWa49+N+QmajHshIy8EM/I+drZNb12iG9nrBLn7hBYv+5w2N9gGBWbyGEa+lS5SufxipfrHqvIpUh0FL0Wib1ecBtL2O7NlSR5OEZBU3MHAM8rTSpdM2OdONzvLyVKaA9Q9toJu0S8betYYn3KPZ3EMqSC83WBQbtmTl0pxKWBbZaEM4/Lncyobb1kupDMx2bflv3SrtCyUoatkPb+Au9wvCJ52cLUKsLMEprN0qdqFGyroB9EvF71CAxRXa5Th8CQn2laGGxDZ59SbtyloR8cr9lFAgafbgImixazjc9Rd8PxUOapYWmhqxWr3OVRb0FSGdhaccdqXeeOXEAYOe88vKYfCPEosNI9KqymP9qi35oUpcarZY8//dZLVjt3L7ZRhUqjVYycEFsvOG2vOTlb8PL1AU2j8HLep6oVXDNHUSXJZdwXNXW8j/PKa404Nzl/fsCLL45I/5MRWSmz1tfrroCxQ/Fszpc+u0LyMu+3lsw3Pt9665ePLJNZnvKzb1+x9YsefApA0zTPgN9C/Ba/iJnk/wz8b/nHrxl+lpHxGLj4iY+73N93vP//77//v/kgFeWvfWmwrHYRgZ3x9qNrBrZI1B90lgydiNP2muP2Po17z/j7aDomLEy+8/UXZIWOoVX7VAGVzoFQ47vdiKpWMV0JwDTNkvvdJR0vwTJL3undMmyLf8nWC+73hXc4C30+WwyZ/Ef3SM8DkszgdLDi2XxA10s4C1a8XvV4MFzw3uEtiiZznpPRiu3SI+jEbBOb42CDb2ZollRj8x+OeNhe8mrb59l2SNtN+PD7D3F6CVdRS3IBnYxyH9G0CqUdtZ4LjmyRuqhKIyG5pqg7l6nLIhEG6Je4qEcnU2aTNqPujrd7Uw47G+paYezuRJn6YEZnGDK/6tDxEhaxx73Bkknic7+7pEo1xqMNbVsQYrNXPXxPZhtloVHUGuv9oVg3Cm/3pjzpz+lZCUlm8LC95OloKirJ1CCduIQLl7ffP0fXxNbh+ynn131adorvZXdKzN86e0lcGrzZdXHMgkedOUluUJQaUWFi7au2w4M1ll4xHIiM/9W6h6lVaErNi2UfXa358NUJN5dd1luX7drlO/fPedydE+UmQzekZUgWHMDbvSnKfp5mapUIFd65ZrHzpOXlZhSlBqlcjJ2117hmzqC/w3Zz3CBjmbpcLrqYeomiNcxDn8XW42i0xjUkoeP5fMDrVU+qJE/QWudXfbkAWHcY+iHj9pa+LdXSF9cHvFz28boi1JpEAfPUvavgukEsCme15rvvvmS98bi66bHYeuhWxfmqyzax5WD4nTNWiSPVrlrxbD7gei0qV+UoIdmnne92DuPhhs3OQdNq8lLj7cGUaeTj6gUPOktqFJLUQFNrHo7mTCNflKy5JbYYvaQXyAXRqL3jZLSSVIzUoW2KmjetdF5t+nzwRnyAeaXzd58/4vnViLJS8Y2M7784Iy7lQD3xN5x4G8aOgMlts5BD970lHTchvvGJSxPbKlinDh9OxgSOmOrLWuNy0eV83ZXkj1TlyXDG++MbztprskLnpL/m8+kI38yIcovj7pqkMGgZGcfBhnfeuWB8f8HqWzJTDHML1yw48EQN/fJqyIPDOZNNQFwaTBOfh6O5CIV+Baupf/btq7Z+oYOvaZpv/cT/o6Zp/jng4c/7HEVR/hlg+odQ3vy0y4rm59z/0x7nv/2lwVJrCWLIVCu+WA/xLZnffPlHs0pcMSVXmkTPuAlH7pbrfZbaq2mftwYz7reWpLkkDXT26kvHzml3I6KNzWc3B5wFa2y9ZJl55KVG10448rZ3j8s1C3wrh39yyb2vXXPQ3nEvWPHOaEqUmVxFIiFXlYZZ4vH04TWztc/ltIvp5ThmQbSRANm80rA+FItEcy/m9aZ7Z9RNCoO6VRI4Kd5+Y6xqlVXi/tgsXGn0hjuWocsmsUlLg5cvx5T7CrGqVS6/fyzG8MTF0Cui3KIzDLmdtblNAvEsuQltI6Es5OJgddPircdC4viSpbhJbF6verz38Eq4nPvK6Z2vXdzF34x6O64XbQBer7tC58htvpgPiUsDx5LKxtVzEcuUKngVo8M1kzBgE0uVE+5saBR2mc2T7pzP34x5qz1jYIZ0rJSulXD58Zh6H7d00lmzTW2yUqPrCSX/ONgwf96XWZm/42rTxtZLDoIdLSMTwPQgRjcqTg+XbAuL37s+obNngs5T906IUDaqqGy3jnwdLxfVZCBV7S6ycawCxZPYJoCBF6EoEOwryttli1Fnx4Eb8vWHl3JBZkgVZaoVPV98ZNFGZmF1oxAYGaYrf6tfms2rRjxwvp3Ra4cYesW4tWUee0SZzKxv1y0co2CX2Bz5W/JKY5Z4KGrNe/evMIySni/ghzi2KAqN6iSlrDQcW2armtqINSi30I2KJDdQ1Ybm1mYT27T8lPVCfIWTxKfjJExieQ1eb1vUpaios1JnvfFYfyIpIH0v2lNNavLYwFCrO5WpZ+Z8MRuyTIWZeeDt6HYizoI1Q3tHtxvheBlHrS1tI5HIqUZhmbh8/+KE55sB28KWNvXLHlUpW6Jr5BiDlFer3p2Fo+2mHAcbHrfnzFOXwEuxDcmCfOdrF5SNSl5r9M2IqlE5n/R4MpzRs2Li3EBXa4kmSuRnUDcKs1WAZpdC9dH2OZipC5/7PDyesUrcu/gu38jlbz51fsEt9Q+5/ntU8f3cIFpFUf6v/PyW5v/657zvNxEH/z8F2EBLUZT/B3sjY9M0N7/PyHgJnP7E558A1/v7T37K/T93mUbFYuuxTWyqSqUoNPp7dWSNwju9W+apz4tFn7pWGfUWfDg/5BvDaz5ajHl0MBcWpCFzq+t1G9cWYO06lZbJ209mvNpIRMhxsOE6bBGmFrFr3AGsN7v9H2mj8HA8o2fJ4fnJ4oCOk3DWWaGrNY9ac340PxJ/nVrxzdMr0lLSoltWykwNmEceNQr+b81Y/miI8XjHw84SXa047F1xlbTJ2yvySuPD18d86+GFDPgblZ4VizE6s/Et8SZW+1TuozPJZ7P1AlOreO8v/IjzsMsqcTkMRCRT1wrD/o6kNLhYih5p5ojJVlUarK748vpBxJtZT+J3vJS2m7BMBSt1vu7S88UT+aC7ZJU53L7poWQqg8MJz6MByz2cOsul+hx7O7a5zSQKOA42JAODk2Aj87HEo9A1LtcdADSrxNRLnq0GPDmb8IP5MY86c0y14vPZkG//+nMR1ig1t/uvp6s1P3x1wjv3bvjB6xOO3p5KOzx1uNcRM7RKwzJzmL3p0T7Z8N2jN1zHbYmWcoQZOYv9O37k2NkyT4W28Vfe+yE/WB5TNSpRbhLvxVFForNYd/BGES0nRVdqyn2+n6lWuIZJZJp30ORl6vJ0NOXFos/T3oyX6554MBc277x9yfdenXFvvGCZm3zr+Ipl5vB0OOODT+5jdDLqcxfz4U4qln27Pc0N+n5EXJjQSLr4o8GcT64O8byUXW4x7IQSmdVb8snFIb/+4JyOlbDOHNJS5yTY8Hwx4DYMeNhb8MMXp2iHtdglvC2mWnLZ7jANJdW83QvpOAmq0nC57nC/uySvNTRVwo5dvaBG4S+99QnlY40Xu77YNIySVeTw3Udv+OD6mGxl89Zj2QbqSszuy9jl83BE4KR8cHXMuLvlXnvF5bbNza7F51cHVJHBd999ieo1/BPjlyxzj7C0yAud977+hlnsc6+1Iq10Wr50HCxd+KfZPiX+89WI6bTN4XhFx04YO1t+9z98n0d/+QWmWvEq7OGaOatlF/1ezVXU5ruH53y8HMsIY5/coSgNvp/Qc2M6VspN2OJy4VGsLO7/xhW7zMY18x9HfdUqLTvl4vZXE0uk/HJsC/+dWH9Qxfc9xDPxfWS+9/3fd/uZq2maf7VpmpOmae4jopW/1TTN/4SfbWT864h50VIU5QEiYvlH+3boTlGUP7VXc/6L/HTz4+/7/gpFpvP2cErLTfFcaUNtcgENv9r2sbUS3875jZM3fDEf8qi7AKC39w25Ri7S8t5McuxqlXXqcORvKSqNZeYIjzEOWKYyl8sSqSi/mA95dTVE02sej2c8HM9I9kKCeepyvy1ziUXiscocXu/EfLvNbH70xSkf/M5jbL0Uo7EV3Sm85jey4d77zoUgohKPi7DDf3HxFv/g+08JCxPfyOj1RZ6/zmTG9F9//oSqVrjfXpGXOvG+KlGVhjg3OL8c0LFkTva9m7O7kNbtHv3UcRPutVYEZsa3ji75xuE1338t1ylFpVGVKr6VYesFLT/l7aNbAGZbn5urHovY492DCQMnwrMkGeBRa04wDmlaJboqHrDHA4le8d0MU/vxrOpea8WPLo4JE4tV5vDB6xMMVRSW97tL7o0XEk+Tm9h6ialWPO1OCQvhq9pmyWz/s34+H6AoSDtt3cXy5Er68fGU+60lqtJwcyuH+zzx5GdUmPTO1ux2Dj+cHTOyw7tkg9sw4Pa6e6d0/HhxKLT92OeTzVhk9YVwSF0zR1NqRqMtJw9maGrNdBXwvfNTnl0coCoNF5sOr6+GVI3KLrX2UvaSDz89o+tJdTn2dyJ5V2CdOjQ7g5tNi+XG58PJmHXiEBYmveMNZ4Mlx9+84WFf/r59K+PQ294pIhc7D0VtcIySZ9MhnXZEx03oOTEdO+H5ss/FpsPj46kAt1GEM6lVfPz3H5FlotL94asT/sK7n+GbGa8/PmKZufyXP3iXYh+XtAxdztprOmYqFbQf0rNirjdtlpdt0lKqoteLHh+tDnkV9ihqjU1sE1hSXf7u6zPaboLqlNxuW+SlRstPmEQBll5x3F1zFGxpewlX8w4vVz0edpbsdg7vHN9itDJu4oCWkfF8N7ybIz4YLLjYdGgaeLHu88VseFflaWpDx0y52Ug3yDYKvv7gkvutJYvY4x9d3+PRX36Brtb84OqYr3VusLQS91RSIvJSp9ofXmNnJ8pfL+ZRb8G7gwktM2Od2awih7/46DP+3Dc/wzEKPDPj8rpHVavMQv8uIeXt09s/aPv7w69Ggfrn3L5i6+cefE3T/Htf3oDVT769v++Psn6qkbFpmo+B/xD4BPjPgP/lT0BI/yVEIPMccev/jT/om9SNwlsnE2nZLAJ2W4ebvVAARKkXlwa2UfDJ4oD3D64xVcFrTfaClJaZCcW/0sVEXamMvR23YcAusXh+Kf3760WbgR0zsCOenkzwjZzH/TlnRwvabsLn52PKWuVr3Rs+/QcPqRuF37s4wdXFzzXZBLy6HKEocNZa8/5bFxy8NyUtdXaJTV7/WJAwOpQh/ypxKTON+R5JddTacvzWlKgw2eY2p6015l79WDcKlp8JmX6Pn7K0kmUo7eCz9pp2P8TXBTWWlxrhF10cq2AZunhGTtdKeL3pMgkD5qlHXmvUpYpllWKR6G3pWgkvXx1Iy6yw2M59FMBqp+zCL2NjBAM1i32mScB27mH6OYtU2qquXvBi0afrxBS1JjaO1GVbWGLI33ss+91Qgle18k5KP1v7LGcBjzpznu0TK+aJJ7l0VnrnjTrqbJhO28S5iWsW5LHBchZwuepgqmJspxJ7x2zrk1YiX7f0klYroWWlPN8MiHKLk86at3ozvvHk/K7FmRY6662LpZVkpc4yllbzs4sDykoTxurO5fKmx0EgUT3tIIFGEel6avLgZErbThi3pO043QUcP5gzcCLmqcsqczgdrHjvqYzFzYF0Euq5qDjvt1cSq7PHuqk01Chs9z7TZeZKFRW6BG6Kta+oAI78LavIpWfJIZsXOmluMA196kbhxUyM4JvY5t53LlA1SXY4OVzyYjtgFvk4p5Ikb93qlI0q4AI7Z5dbTBKfmzigbaX8/VcPedyfg11j71vh9/tLzr84oG4UblctPCvn1c1AWruxjmMWgn9706LnyuyybSccBxtsraTcC9nePbolzQ1+9/WZHOZWwrAjCDFdrchrjYtdh1nsY2sl25uA1U48g19i42Zrn6EboqsVf+rkDbpSy8+yUXi1EfB014uZJx7XYYu3DqZEpYATxq0tL26GeGbGOt9DCAqbtNJZxw43oRykB/aO6U6g75O0RdkIEHzkRLR7Eh1m6SWvN9273+WvZP1qDez/rVo/t9X5+9Yf+ek3TfO3gb+9//8C+O2f8XH/GvCv/ZT7vwd87Q/zPVWl4YvLA+4fzrGcgmQpMu0wl/mIaVZ8dnPA6WCFYxZME59VItaEs86KXWHx8c2Y496asDClVRVZfLI7pNcL+ebhFfPUYxIG/NNPPqZoNJ5th7TMjFni4ewJEZraYLriYbpJ2pz++iXf6Z/TMjNer7v81oMXdIyE/+zVO2xiwXF1TMle+8GrE5GKpy59N2Ia+myWHuODDbO1T9MoPOwtSCupzHwzo2fF1I3KtrCwtZJFKGisrpewSy1aZkZcmHhGTpqYdPv7z9+4xD0JOv3G2RVxf0lUmKxWHm8WPQy9oqoVktBis3VpajFWV5XK2UCgwGFh8rUnl8SloJ/sdsq9L79O5LJMHVTFpm/HfHorlgh9raN0Uk79NQ+Cmuu4xdcPbrmKWvTt+K7iuwlbdB2JvhnYMSMn5B++eMDXzq55uQsw9Ir7owXr1OGj2ZjfPHvJedjl7e6EulFpWymn919xEXaY7gLuH8+w9JJl7NLtRQz3TEUQoo45lg30nYMJz+YDngzmd3FKhra/HtPg2e2QRwcin78XrHC0nJ4V8/e+9zZlX9BiAFFs8fTslmdXIzw/wzBKykzjctWh2ZNWksCgrDRGHfEkfno1xnHF1tByJH/v08kBllHS9yJeXY44PpT4onvDJb6R89rsUu3ntevIQVUb6lqhKES4MmpLzt6rdU+UirXCwI3YZrbk/hklq0wUzL+zekBTKbz18Oau/XvirHluDEgrnW8dXvGD22M0taZtJ3fwgzgRQYhvZZz99rN958FmGcrm7xjlfuab8937ryWf7+yWI3fLbRLwbvuWX/vNCy7TLvZeXd2yU3wjZ/iWhAs7pwX2/VJA6Hv2q6lK9JVv5PzawSWXUYevjW/5/rN77GIberAKXVpuSl7pnC+7HLa3XMy7Eip9b0lgpbh6QVyYaHrN/eGCD1+e8N6DK87XXTxLTOgPeksetBd8vhzhW5kcjkrNZSjz6lXiYmoVv/nwJWWj7g9JeZzrxJHMzFdteAqmXmLoFWWj3oHB3zqacBm2sfSK6a0kWag0fDEZ8Vn4q4kl+iraFn7W+sMcfP+dWrpaoeo1N+s2h50NTXtLVJiCpPIKZomHbQvNZOhEhIXkfRluxccvTnhwb8Kj0ZyrTZun/RlxafDeyY2ETVYaP5ocUdcKR50N53GPF8s+rlnw7HxMpx/S78S8mAz4xsk1p8GasDTvBtQ/XB8LocKL+K9ePKHdivHtjNlFl1d1H9sqKEqNo4M173VvWeQeF1uBaf/pt17yg5tjTLOks6+AZpHPNrQpWhrL2EVTGw68HdPE4+3hlOuwRcdO8MxMZhd7HNVvPHjNPJVW3sOjGYvEpdOOSSv9jpbxjXtXXO3apIUOKNw/mhNmlpjgG5WkkBZb0yiYesksFoTbob8lS4y7hPbJqoWqNPSshC+WAwyj4sV/fZ/RdyZ3c7wPX57wT339Q1a5y6G7wzdS5qmPqVXS6qolhDWtdCZRgB+kXO3a/Onj11SNwqfLMWFiMWyFzFOfKLcoa40fTI552Fvwo9kh3xlfsIxdahRWicvy/8vef8bImqZpetj1eRveps88vs4p39V+Znp2huNWs5wVsBQpECIJiZJ+UAIJAgIlChAgCJAICBAkShShlSclkiIgCrsCdjm7w53d9qaqyx9/TnoXPr74vAv9eKNimsvpHqNuSqyZD0hUVsTJzIjMiPd9n+e57+ueu3QaC+5Uhnzz4ga6LH6WLC1FBFXocrM1FtlvWsp1UmE0dylPbH7rr/yYg+qYp7Muca5yFVV4dtFlrzfm5v1zscE2JuhKwXufHFB2JCrViLKU6VUXnOdCcNRwIiF8MIUR3lBzMXO1xHxZkUt6ts8wcshTF1UpWKQG/d6MiW+j6zmX8yrtSoClCUWxl5g0XSF42XSF0OpkXidIdVpmyF5tKhLFVaGmvYgNwbcNLN7aOsfaFIv/ZwBzd+WpPIvq3O9ci8o4M6laMZuuxziyuZ5XsIxs7c98OewhH1xxPGzy2tYl9V7Mk2GHG40Jtpryct6ibka8HLUw9WzN0/3m5U1hZ8i19XOfJZYQTMUWO9UZ08jGC8X83rETzqZ1Qld4P59N29TMiP3KhKuoilFJuNcdILPkV/eecRo0cLWY7caMi1mN+5tXKziCyl414vmsRdsOMFsZA9/l7v4l+erga2oZe80pjy/6QvizeSXAEUtXtKV9C3cjwTUSblZHPJt32LAXDGcu7+yeMkks+u6CEgl/Gw5qY1SpZKLZdK3Fej2KC5XdypRTv06zK4RWTTvkVk+Ic17+vBfMz+wMf0Gun9nqlCRpIUmSJ0mSB7z+2eef3f6f02P8c13lUsKxE7q1BcVSiDiWS4nhdQ0/10ULsBShoO+9f5PqykeUFCpv3TkmKxXhkdIzsYmuFKFpIfw9m7U593vXBKlBmGvs1GZcXdfQnXSd7LzZmmMq2ZqML1pzBXkpKBO2mglQrSkG3HIlY689IXgmOJgT30aWSlw1WVcZ50EN10xITgU7U5cLbD3lwaYw11bNWGS+eXU2HQ9Tydh25wwCl7YZskiNdWjtk0mXl9dtvMTEVHKu5lWiRFuLLA5HLcJcWz8+U89JC5FAME0stuw5QaoT+QY1O+ZyVGcemlhaJiKEPI0gEh4k20rWwp6mHVIxE/KKQJiNY5vzRY3trTGHfgtZWvLjkx3C3BCQXk2oLmVpSZSpzBMTS0vZrU/Zqsx54bWYpTZXJ00aToQXmXz8YpvBWBjNN2tzwhWl49G0h6nlXE0F4qvTWHB10eDporNO5Y5WRvi6HlNZgY3LpUTX9PFDA0UpsW/P+XC8xXdPDxgvHMYjQdfoNhd4iWgn5oUsSCTzBpW+z9m0ThTrIs1BT0TQcaJyeSZaWJOHbTSl4GQilLoHTeHbulkds21NOXnZxbJTGk7EzLOxtJTN+hxTzwmnNidPeyhyiaOlWFqGJC0JEp0w17jwqywic82RfDFp8fyqI8KZjYBbLQFr79R8Xs6a6HLBtjvn9KRN1/I5ngt/2YlXZ5aa/Oh8VwTVOguGkUD4JQuDjiPoOP26R63jMw4dXCfheN4QPFw75iqoEOY6V8Mas9jiXneAoRZosiD53KqPCVJjHcxsKhmDWYUw07nbGOClBvNQUHAaFREntt2YUTci5rHFZOwyDhwUacnz6866ip2lFlU15mTWIMwNFonYOCexzSAQBnpZKolTcWADSDOVrim8rXu98dp606r79JseYa7RdoK1j7dSEeIkLzYJc4OLYR0/12lWA2SpJMx00lKh6/gocsmpX8fLBMM0LdX1Aed8XiMvFQ4qEywtw9TEwctU8vUh5Od9SeVP//i8XX/SjK+yXC6rqw/1Jz6vLJfL6n9eD/LPcxWr6qBjBYx9B0PJ2XbnSJpINMhK8SbMSoUvvvWcmh4RpDoNIyIvZSw1Yxw6ZKXMeVAjzDWC1ODTh7t0K2K+pEolHdvn+VVHtGE6Hq1KQMMSPf+OFfDe+c46xPLSr/Js3CYpVJ5fiRnUG/0L3myes+PM+Bv33ycrFO68c0zNiYh8g/OwziB20eSC/daEINWFGvSBqD4vw4rgPZYyzRVkW5MLglgnLxXCXOflSnmaL2UuPu4TZYJXaOsp9WqIoeTMU5N+zeOdzVNMJScpVL6++3LNvjyfiADNrFB4/vE2qlRyuBDf950bJ2SljKrnKHLJxLe5mleR6+INOoocylLmR8/3UOUCVS4JU43bb5wSZxrzyMTzTa4mVapawst5C9eN+MGzA0wj47unB6K6zDUxy3Tna4k+QLEUVeBvv/0RW5U5TTtEUksajYDn8/YaMedqKaaaEWcqNSdiszZHV3PeunMsAk9zRfAr9YSsUHjvWIh3Pv7OLcJcY5Za1JwIQ8/wBi5tK2C7MWOjPhfhq7MqilwSJQIYfa87ECkHNWG3uNEac7s7xNZSno/bRAuTg/4IqZB4MWhz4wunyCuBT9sMKZHYbU/4eLTB00WXan/BbmOKraW4juB3Hg+bVI0YlBJ7w0eTC9pmsD4o9CoLkdxu+2SZQpDoeJGo1G71h2hqsZ4hO3qCqye0nYBHZ31OFnW2d8ZiplVKgkm7AnK3q77AgcXCFtO0Q/r9GQC3mmMsVcRVvda+xFRzWnbA0+suE18odc8XNZjoTHyb5+M2g8s6J6MmjiZsLluV+XrzeTbtYJnib/fdo4P178gyMsFZrfqYSr7uDJhOylZtzg8u9rjRHdFyAqJUw9USvjs84Lf2HnMeVHmzfc4Xtk+JcxVHT9lvTPjex7e51RrxevuC5Qpm/a0f3+PSqzIOHBw9ZTCtMBwJM//L6zZns/paMf5a+1Kg1xYWH11toGoFo8BBkZeMYodFbIjW/ypvs2FEpKXwsn7/aJ+0EOb2vfqUSWLxnRc3uJpUeaV5zTw1USWx7vzl9f/d9blNZ5DlJaFvcOFXCWZCffnZQhmmOqdXTXrOAk0umCQW11GFYinzctLieNagbQZ8beOQV1tXNIyIwaKCqhS8cv+Uip7wYtDmZFFnmljrk1+xFFVa3YhpmiHPxoK4//B0g7YpNkTHSJn4NopScurVOfXrfPvyBo9nXf7w4jYlEmezOpaesbspGIWXiypD36WqJWhyyYvLDkePRaqEIpUocsk8NZklQkBSN2Lu9655/2KLuFBpWiHblTkn8zq33z6hRCKbGtT0mN3qjEVqsOOKts8stTiZi2DPp7Mu7sovZVtiM+g5C+69cUKQ6rw46eHoAj31Vuec3eaUhhNxrzugVQm4uTHkZnuEruR8efOYfm9OXips2h5bNcFSHD5v0a8suNkb8WDzCi8zuDxss12ds7UxIQgNilxeL+SPXm7y7vkOX2kfcXzV4sqv0LECppHNeVhnEltCgdny2XQ93mmf0jV9Lua1VWSQwL11HZ/DYYuxL8QvZ9M63sgReXmLKg0z4vbmgNvVIX/9t77P0+suR7MGqlLSdgK6W0KVa6/aijUzolsTcVNb9Tl9Ryj6FLkkzDVsN+HZsMNVUKFpRAQTG90Rv9tK3+dub8DxuEmQ6Zx6dZ7PWlwuqqirv3Gci45FWigMAxdJAlUqudsfcPSkz+6WUGwOFi4Pxz1mgUVWKBwOWsgsGYQuv3vnE0w9o2rFnF02GYUOlpZx6teZrAzsdT2mbQT85t1HuKsDwLee3GarJugjwzPhtVwuJbarc/zEYLc242TSoGUJwPNn4pLp1OHZrMMssISHsRrwav+Kh9c97jYGvPrmERs1j9A3sOoRWaRxNG4yjBzef7GDIi3Zqc6YeDYd16eqJ9zojdbdlyDWqTlCbBTmGi8molugazmDwCVJVZ4c97HVjO3qnEkigoA/nm1wv37NdVzhMqjSdxYsVp2br772jA+e7BLmBnuVKW90ztm9c02caHRcUaVttWe8vn9OWii8s3vKdn227sq8d7mNoeb0W3N2m1O+sH1KVirEucrZtM7iqEZNjwlTjeWPaxzPGlQ1ATa/v3nFdVDhdmNEVRft9td2L9hqzxjFAjlYInEZVn4ha6ZUSj/14/N2fW43vqKUaTZFvMobN0+p6zHXQQXNEBL5ZSY2uaPrNkfXbcJcQ5FKtuszlkuJmhZxGdXQ5IKLRRXXFAZ4U8nFCS1RVyZhEXt0vqiR5Qqv94UQAEQSQt2IqFQjHCWlrkd0bZ/XeldsNuY0rJC8UPgMuT2Zi8qu5QQokohEyZcCtL1cwumijqWl7PXGWJv+muZf0ZI1vSIv/6gS2mlOyUt5bRwfHjWxV0GurZ0Zh5Mm49imaYVU1IStxgxXS+hXFqIFuXD46OkOL4ZtLC1ncFnnOhBS8LRQWGYyYSa8aePEoaonpKu5lSqJGBV1FWj7eNbF0gQa6yqqoMsFrpZS2ZuvBQwPL/vMYovX7h+LtHTbxzJTeo0FQaLTs3z2d4a0KwGXcY0vHpyIDWzWZPGHXYahi58Y2FpK2xYRP4OkwpNpF3n1OKaBSLWIC1H1JU+rHHlN0lTlYG/A1bBGsJpTJrnKx5NNholLu+YznzpcXgmu5nAgRAymkrMIzPXvIS0ULuY1xpGNLhcYSs4iM7jfuaZmi1ZvXKhIgUJZSJiKEKrYK66ltfpbmWrObOKsF21bzehWFgIqsKLDmKpQtDb3Z5xeNlGVUswLlXKVIpBxszcizoSv1MtNXm9fUDcjJHnJdmWOpgi+qyKXa8VzWqrkS4VFYnJ9XseqCH9iXihY7ZDlCvt35tVQpJJpIoz5ulLwydmmQG35Lre2Bow9hzQWJKSaGa05nJ+O+6LqA2xXjBlqTR9dLbA0wYg9qE2QWaLrwu4S5uJ56HJBnGtkiVA9Xy6qwtKxlIhyjTe6F7TtAElesrUxpURg2I7HTc5nNZ5ddHlvuI2+MsIfTZtocklVT4gLjY3t6er3oAg/JksURbBVvViIsy4W1bWYp65HhIVOXY+52RqvA4/91MBRhfdXkwuKUqZ/d4ip5lStmFd/+ymLubCdPD/vChGQbxHmGldhZT3zbBhiBlyUMp9e9dfv9Z/r9bMUnZ9DVefnduOTVwGpTUOAeYeRaJv0Gx5RrLG/M6RqxTRrPvdWw+392hRdLni9d8E8s/jweIt5alEiMZy5zCOTq0AIGHptD1vNeKd9wr3mgN/ZfshXN49IV7NBgKxUeDFqs1H1cNSEth5Q1QSFoWbEbNpiTHq3MWDL8bizec35tM7xZYs418RcUCrZb00w9ZyeI4bftirmNx3XZ9P2uFMdcMMV5t8w15hGNtPYwtVErmC5lHDVhMrWgku/Sm1FoHnQvcZQcup6TFKquFrKdz+9BSA8ZXLJ2/eORTusUDBrMX6s82zaZr8+5c6ti3XC9YtJi2fjtggtTQQRZhzb+JkugNk1wSP1M50g03ky6DKKHG63RqhyyfG4ScURKQafQYAv/apIxlZyoljnOnJxtJS2FXDq1znza5RI9NwF5jdGHNTGFEsxP/USE0dLCXONlhXgGimz1KTlBNStiDjXqFsRX/6VR8xCC0UtOR02eXP/jDxVMJV8BSrI+M7RAWGqYVdiut05759vcXf/kg+e7HI0b9CshPiJjmsk1I2Iuh0Jf6cvoqxaZsh15IqkcEMYwyt7c1xHKHvzpcwHl5tEc1Gxv9a+pGrENFv+WvKeL2XOpnU2XA9VKek4wkfYtgJu1sf8xr3H4ve7IrH0bNGOr2pilriIDb53eoCfiTSAeztXPB+3iTMxt55HwkcWFyofXG5yHopUjYP9AXVHGM6DROe3Dx5xParyaveKmW9TtyJaZsg0sHl43WOnMyEuVG61RMjrnd6Aej3E1ZN198BUM2Yze40QjAKdTtVHkZfcaI6p6xGunvB81hKsTTPlYl7jyeEGXmKuD5CbnRlf2DrFVHO+1jvi7f4ZrzcvSEuVo3ETx0xFa/66g6kI5aSmFlSrEeNRhWfTNoPApShkrq5rXPpVHg+6ZKXMyaLO+xfbTBMLSVqSZco6EHcYOdyoT4gzDT/T+f7zA7zUYJaaXPmiGnPNhEVs8Gja4+W5mB93awvhyYscpoHNLDW5sTXkfFHjzvY1+VJmqzljnppkpUKUajwZdBnHNg8v+2SlzM32iB1n+gtZM/9yxvc5uBSppFUJ+PBqE10uGPouG66HpWb0GqK14UXCnG6qYj4gS0sxBE8sjrwm1VrEmV9juZRorsDJmlJw0B9xdSwy8x57Pd692GGcOWRLmeN5A1UuueGO2ah46FqOrWZ88/ImPx5vExZCbNAxfWapha7mvHe5LYbquUrVjrmxNURTCjZdbxU+mdBzFytxjcrpvE7VSsQGWWg89bo8XXRQV9iz61GVa6+yOrE6vBi3mCQ29zvXbLgCVfVZi7KqJ0wSi49HGzwbdnjnlSNeDtp88eYxjpEyCF0RnWNGyHLJ7fZIBIMGIn/sw7NNkSF3VKPjiqTua08EqI48oaz0M4P3B9v0bbFxf6F1Sre2wNZSbEXMAfdaE/wft5hGNlGmcnTRBmC7NeX1xgWqWnDyuM+nT3Y4W9S4VRvxoHElhASJSRAZTBKb+UKo/7bdOU0jZMMSWX+6kpMVCkPfXac8JIXK9w8PuNEcY+oZr25fCKuLlfF41KVqCmHLV/eOsLScXlWoaBWlFOKP3TF9d4GlpcSpRkVL8FITU80wFSHZl6Qlfqaz5cwZew5RpnNyLRB5srSkYYkIn/u9a+4eXOKnBh+PNjif10Q0TygOW15i0quJSrVtBZhKzvG8wYtxi4ugymlYZ68+FUzWwGIU2zw76QlKUesaW894pXfNKLbxU4O0UNiuz0QiQHNI2wlwzZSHl30cM0WVBLTgTk1g+/xMx1+YXER1funWC04WdfY7Y9pmIDifmcJuc0qQ6gBrJXC+FBBrUxEAgRNPpNTf3Bxy6tV5Omnz1v4Zg3mFvdXB088M6npM3Yz41uPbOHrC/c419Y5P31lwuGgyT0w0ueDppMPN+ogPp5t873SfabqKRzIy/MhgqzLnRneEraYspjYNKyLNFF7bP2f+sk7fXfBa/5K3bp4SZyq2KTyfeSGsLA1D/J36TQ8/1jm+bGEoOU8mHZH+rmbc372ka/m4Wso8sNhxZ6SFwk5tJtYMM2fsOZxdNokzVQTmVj10ueDFaY+qGXO1qKxe+zqaLLB0k7lL1Y5ZLiVe3bxkdFFDVwqu41+QvOIvK77/4l8lEudXDVwzXbVp5LVSz4uE8rBbWTCKHQ5nzbWptWWG68WlbkYkuYqlZXRsnxuNCVmhMAoc9Fa8Vsb1qgs+HG8RFxpblTleauDl4mT9hf4pXmpQ0ROaZsimOWfLnhMV2tqM/dn8qqoLlNjxUFBcPmN3XoYVLhdVFolJVijU7QhVKbDcRMTMGOF6YblaVNCtjKYbcjIVNJFedcHLcUsYiaVS8BtXAp5Tr05RyuxUZ/RrHqpU4tjC9uBF4jksl3D4dIPb7RGnXp0w0xlOBUIt8wxmc5sbrwr5/mcRL2mmstWY0bICroMKaaZwFVbYtD283GTLmXMyauLnBtehUKhab05E+Gl9yvbGBFUR7dByKfP25hm3H5wh2fnKIG+yWBmFdSUXCsZMR1FKqnqMlxniuagJn172aZshFT1ZJ2lkq7ZekcqcenVuNsfocsEngz73e9ds1uZYaoYuF8xSQb+x1YyrC2Hsf3i+wWBWYRi6pIVKw4l4fNHnOhDwg0UqHlvTjBgGLo4qUudrpmh9W2pGGOvUjBj/uCpQekuJbXdOlGjEqcat9ohoJlp4VSNmzxV4uwu/ysm8DkDDEdX7y1ELgN3ajK36HC822d6c8MlVHy81CRIBL9ivTIhzFV0puPSqazwXiNQOkUgvERdigR4mLhU1YR5bvLp7wSSx+MHZHpdXdap6wuG8xchz6dYXjEOHtFA4GohZm2OkPDnc4Gxc5+FlX6SEmBGHE/F+q5kRm1WPU6+OoWfEhcp7Rzu0TaEsNZWcbm/O6aghKj8jQV2NABS5XEeLPZ50USSRhFAuZfE+tgMMTaRXpIXCLLWoNMRr4JXuQGxYbxxzNG0yiu2V2V8kyRdLma7jY6siUPigMiFMRbLCZm/Gy4vOmtvrZUIl7aUmdT2kVQ24Citi81y1QndaU7ZbUyq1iPBRg8OTrqBAJRb7W0NOr5psV+d4K6VqUqj03AWqLlBp5xdN8fzbIaaSrWEWP89LWv5lxfe5uFSppNYIGU1dzoMq240ZkxVE+Nd2nuJoKS9Oezw97bFXm3LhVZklFp9cbDAKHOFtmtVoWCHaSon46WWfJFdpWBF7rQm9yoK3d87YcDy+0j2iayyo6qJKiAshif50vCGMxS96xIXKf3Jym+OggZ8Zwoumpby9eUZNi3BXdP/b/SF7FZHeUDNiLsc1bjbGfxQWO2ywXEpIkpgXXYRVdLmgYUQsFha92kJQKlyfC18IJKKBIEsMIyFosLUUV0sJEp2kUKnrEQfVMbPUJIxXVWnVZ7mUqFsRtW3BtZxOHfJCBmmJoRbsHQzY7k55ed7BMVL82GC7MaP9E0o7Z7X56krBs1mHQVTh/YttTCMT7dDEYBpZ7NYE7PvpsCNadVLJJLZ5f7IlSBmDFq/vnbPlCDHRe2dCdXmzOuZed0CY6hx0xnw8EHlw717ukJcKNSdCV3I2LI+WE3C5qKJISwwlp9+bUxQy7z/fFc99YfBk2EGVSvxUxPl8crLJhutxOq9z98YFfmjw+s45qlowCyw0uWCnMiMPVTq2T1YIUPnpqEGci0Xsw+Emaa5y7VfYrYkgWF3L+fDFDr/1tQ/QFYHgcjWR8P6gf4WrpRzsXbNTmXE2q/PNT+6I4N6FxY2GkLlHmUhg327MeHQpjM3lSnhyPa1yqz3i8WUP10y4mNVwlZQw1sUByBTtxA8f7dFeefuWS4l+ZbEyg6uMY+F5fLN9hiwteXndZqsx45X9S2wlZasiRC8VPWERmBhqwW5nQsMKaVsBqp1R5jKNisgbtNWMhhNR1RL6lvg5caZSMRMuvCrfuP0ML7MIU30dFv3lvWOqquCZHs0bHFQmHFQm65GCvrL6VPWYl7MmaaHixSY3mmPSUrQoHz7dJoq1NaTg4VC8H++0hyyXEvMVmq/lCgXoi1Gbl3NxmDhcCOXsdmPG0BOp8JpScDmpcTgUeLPjWYNJ4jD9Xk8A5JcSVU2Ig0wlZxw49Kse7TcGVJohV/PqOsJsmYs5fN2JuLyui9k9S1xLIPA63Tmnfp2KmfBi1iYtlX98ufv5XH+BINWf240vKVQWvpCLv94UMFtJWnIyr/P3ju7RNEJu716JqBWvzr3WkIcf7nGrN2Q+dsmXMm9sXAiyvyl8a3U34nZjxDQSKrWu5bNpzXgxa7PITZJS5fm0zc3KiHwpc6cxxNQyponF733xxzSNiKYb4mopcaGysTIWf+/xTR7Neryct7jhjnDVlEeTHq65EsQ0FjwadPEik8G4Qq0qANN5IXOzMqJrCbpLz1rw2s4FG/aCcSQsG4aS8+ykz807F8I39MEmUaZhKjmqJN7ol1cNXngtrqIqSa5SsyO6lk9Nj8lWFVy/suAqqPBb9x5yoz7hVn9Iyw6YBjZFKWNXhECh4YRczquMFw6zRAzqo0xfVW6S+H6IXDZTyzgf1fEDA0VecuqJN/12Y8bRXMS9THybHXfG02mHvc6ES7/KJBGCgDxVuPSrXEcVXk6FtWIUOizmFm0zEOb9WMwBPx31uY4rnI0bLHyTYimhywWmmnG/c02zI2gp0tCgaiWczBqYasaLQZtXdy+IC5Wd2gxXSzH0nI9Ot4g8E8cS3Etdyal1fOJCZei7nHk18kjjKqiwaQv7RZIruEbCybxOsZTpuD7bW2OOgyYv5y226zO+dXiTL2yciVbhCpX33tEOVSumvTnn5XUbWV5yvqhxedwSfFRNCGI6dZ9ZYtI0xBxqvzNmGLrstKcocsmdzpBJZtOrLqjrEWku/GQbe2MGkcMnZ5ts1ueoUina6UZMRUuw5IwgNxiErsgdtAJ0ueCD6y1eTFvkqcKjRzvsd8b0nAWHjzY5m9WFYtGNaTd9KkZMkOqocsmm42GrKyKNJpLjDSVns+px6LU49epUrVhkPiqi9fnJrC8CcrWc87DGd04PiHOR56jIJePAIS9FNNOzaZu+uxCb9lLC0jLu3T7HtlIu/Sq6LOLEXC0VsHJ3TlYq6ErOnjul7QRsNWaYasY0soWyVhZirVd612SlQl6KWLLNxpyqFbNRFe/l/i+dE2Y6g4XLjz65gaYUXAUV5kOXK6/KVmVOywkwjYw00nD1hC/ePhLdmkGNWiMgzVRhZanO0JWCJFdZxAZ3GwPBzdWjX8ia+ZcV3+fgKgqJelWgrYZxhRePN1nEhjB9azlpqTIMXHbbEyp6wsNhj6996TGumrK1OVm3P00lw1UTjo8Ec8/PdCQJdqozvNTkb334JrcbQ154LbTVK2SxanP6mUHDiFCkUmCztIi9ypTzhVCWtQwhdnlw45y2GbJbmREUBi/nTcxVe1WWStpWQNMNRTxJIVOUEuVSolP1uYxqqFJJ317wwhMtpjO/JhLflxKaUvCb9x9ytzZgw16w//YZJ4Mmw9AVGWiphqwVVPQEV0259ipYerZS9snreKIkV9HkgsuoRr4UJ1SAqhUTZZqYWag5fmKw15zSdMWJfxrZFKXEMBTBmvOFxaNPdzioT4QvTF6S+WIupMkFNTtikZiCem8vqNkxjioM2Zu2x+3GkJdXHeqGSHpPC4UX4xY1KybJVBRpiWblzFJLCHKUjLyQaVghHz7fIb8SYoXZ3GES22y5cxE8vAJbb79+yXAmzMxBamDoInnh2q+s4QP+wsS2xUa/CE3yUuHFrE1Rylx5VapWzHjmIqkiNueF12Y2E4BmPzGYTx06jhCfGErOo+MNvEh4tAwjx1KEwvPpsMM8NXlr/4w3Wuc0rRDHTjD0nIoRs5SX9Cyfse8wiyx2KzP69oJjr4EqlcJbavtkpbKudD5LJxklDqoiXq+GkhOkBqaVcuVVKZFwDJGEHuYafWNOiUTfWWCqGT/60W2h/q16mGrOspDYv3XFLLL49GyDV147EV0BEKi9QY1x6BDGOi8mLXQlp66FWEpKWqoYSs7NirDuGGq+bkf33IVIz/hkX6h11YzLUZ1ZbHGjNSbKNGq2aBt7MxtTyWgbAfOpEFUtlxIvHm2yXEo8v+qIdraaU9Ming07pKVC31nw3ec3GK5S4Qexy+WiyigQrMwoU5nHFtPI5mxRo65HbDkexVImy5UVKACaRrju0NhaSuQbVDcWXI5q3KhN2NyeEPgrmIGeUBQyupUxDFzeO9qhZsR0Ox79yoKqHSOz5MSrE2Q6wbM6qlJyFoiUdkf9xRjY/3LG9zm4JBm+0Dnj02Gfp5M23YMJiiyUkLae8fC6R89d0LcXIjW7e8mjcY8w17hRFZ6oj642OPXrfDru8xtvPCTKdJ6P2lhaJkgYqcHGpoAB71cmfDLr4xoJeSkk/WGuMU9MlkuJk1DQOfJSwdJSbm+KNKa6FrFlz/l00KOixcxTi/3aFC820ZWCUezy8HyDkSdEGfubI3SlYHDcJM1VvNUsqaYJyfOLSQsvEl8bZYJAkpQqn0w3iAuVONfY642Jc5Vh5GBoObqRs2XP6Zsem/U5B5UJtpJyOq3zaucKQ805HTYZLFxRYYUuH51tcjJtiGpPFxSanuWvW1+LWLBCbS1dSdRTppHNV/eO6B5MeDrq0HMX3OoNMWoJtp6yWfE4fyQ8aM9f9hnFDkUp8ePBNmmuMklsVKnk9Z1zXDWhZQsJfbfis+PORKvKDpCkJRdelYcXfeJCI81EuvUX7xzx6ptHWKZIMTcUQaK5mIpU7R8932MWWhSpQre2oFxKtJyA2/UhsrTkg8NtYa7uTVnMLJGVaKQczRtkpUyxWuzzQubu1jW/88qnfKP7nIqW8MWDE4E/a4y5uyvo+i++v8fJqEmtERCFOp+cbHKjOeZ7F/u0rYD91oSziyYfnm3yZN5lEtlUzARJWnLlVdnYnnIZijigG/UJP/jxba7CCo6erFWlk9imbkR4scmpV+fJtEuQ6pzPa7h6QpyrDBYu73RP6Lg+LTcgzlV2KzMh309Mvj2+SVxouGpCiYS2HeClJq6WslOZ0et4ZKVC310gKyVtI6BXXazCX1OcWoSjp/RrHlmu8HLeIigM8qXCsSdeQ7//4QO8xBQqVLnkjdY5srSkrkc8uH9C2wk4cEbc2hjQtX3ypYyh5tR0IZzpdjzypcwocXjz4Iy0EPFWN1+5QFdzbCtlGDm0zJDvnN9goz5HRhCWXt87Z1lKjCKHaWSzU50RhAYfXW2QZirXwyqeb+LoohNzsqhjqRmb9TmjwCHJFfxMdAou/SpxrrG/OcLUcspM4cwXr6/d3oS+s2CemphaRre+wFRz2k2fi0WVmS9mybK05Nmgw3ZlTpxp7L91xqbrUdXF376t+z//BfMvZ3yfj0tTCv7h8S3yQsbWMw5qgp6SrIQr240ZqlRyvGjgaimj2GGrMqdtBjybdUT6eiGz484A0eePMlW0Z1anuhJRUXWNBVeRIDvMY4uGHqxtBa0VWPnj924wTW0qWszN6piqljBNbaJS46PxJgfNCY9nXdEqixyqZkxdD6nqMZ3Ggq2GsA1I0pLxzOXmnQtmvkXdiAkLndOgIYbsU5v9hgBD+4HAMs1Si4OKiNtx9WQtqulZPslKhHIe1nh/ssUstng06eHnBjuNGed+DUPJ2e2OUZWS6ay27QABAABJREFUB61LthyPW/0hqlJwuz5k4ttc+FWO5g3OFzUmoY2qCN9VxwrEAlQdoysFcaGhq8K3Vy4lZJbsNEVUUl7KtG+N0bWcV2+fiRinVGdyVsNZPe6LUMT9XIRigZl4NppSMElsHnSueHrZJRmIn1/mMraS8ss7LzkctJgkFk0jZL8x4as3D1mkBiUSraqwfNzeveaV9oCt/pTzDzdo2YGwGlxvCXHJxphJLFIX/sorT7jbG9CvLJgHIhj4Qf+K7fqMvrsgLRT+ziev8u++/2XaZsB7p9s4esKpV+dw2GIeW/S/cMkv7b/gTnPEg+1LqrWQpiHUw/lSFukGbkqtIuaFulJwORTet37VE5ttKfP4qkdaKmzdGXA8FMnxuvxHvrlJbLNXm9KyA4JEp+8sUFe+tGkkWp+HfovjqxYHlQkvX/Y59sTrqW0HHLhj3v/RLT4abtAyQ3q1Bc9HbfJS5kcv9ihKCT/R6VkLHmxe8Xze5uy9LZZLiQ9PtoQRu3nBK/Vrmm5I1/YJcp3n8zb6qsKrdgKmvs2HF5u0zJAXizZ1PWIUO9SNCFdN+ebVLY7HTbzU4GxWZzhzaZsBwIpN6/LV5iFpIdqW14FI3PATg37V42oiXjtxonE1FykI+86YR1c90rnB9aiKucLtvbF9QdMNsc2UG1tD8rFJz/JZRIJpqq88tq6RIElCxTr2HJRVvJYql1yfNWh1PLzI5OSszSI1GIbuKgBZZRrYDKeVldhKoVkJiXINVSkwjWxtPRoFDrpSUNdD7tevMeXsF7No/pwqPkmS/llJkj5afXxXkqQ3fuK+35Yk6YkkSc8lSfrv/ym/n7/6774kSZEkSR9IkvTh6nvf/bM9OnF9bje+spR4beOSnYYwpMeF6JtHmSZSslNDzGuUHD8TAo9hKGZ7upqjKgW2lYoqY2UetfWMaCjafp8ZWR0t5SKqMw4ddmqiJ/9iITBZe7UpMktePNzilbeO8HMdVSpICtFGLJfS2tj9mRXh4fkGJ4/7nDzpcRHWOF6IWVOca9iamItsd6cMFhVsK8VVE4GRKgWVXlIE1cLRUu72B8jSkg8f7vHhcBNbTbn0qkwjW6CrMgNVKXnxcIsDd0xFT9itzhhc13g5bfLsvEucaySrStHWM57OhNH2cNhiPnJ5Mu3yoHstEsX1TEi13QVJpnLlVwQ9X1oS5DqDyzr5UmYa2Jh6xum0ziIzRGU7dXk26ODoKf7C5PFFH0MRs5jtG0NxOImcVeKFYB7qSk6zGnLlVbn2Kzwa96i4MQd3Luk7C17fO+fUr3PoN9nrTDib1pkk9soEndN1fCaxhR8bzEPBUjWVTHjy7kw5mTYwlBzXTKgZMT3bJ8qEv9LLrLVna7Mx56A+wUuFDP/JdVfYHoyCrY0pJ36dZjXEi038WKdT87G0lLPDDrPU5sPLTWG+D0ziQqPt+gSZzludc97ZOmXT9bDMjN3KjFZDJKgHqfi9Nc2Qe/1rALq2T7smNqqjaRM/Neg7wjv24cttslLB1DKugsq6FdmwQuzVLMu0U/zcYO9gsFJAR9T1mPdH27z1xec0rIhwxTHdbYqQ3u2NCYaWY2k548Th5aSFphRkrYz43KXMZGS55PGsxzCurIOWz4MarzUuqWgJWamQ5YqIftJz6npE0wipaRHHoz9SOFeMmFd61+hKQVHIbLcE0WSaWCxSg64lKqEb7hhTzdmqzNmoCTuLqeQ0KiGXz9tkscgPfHbe5SKq06oGqG5Gr+0xCy1enHV5/2hbtGTNiDDT2bg5wssM4QM0hRczWR2EP0sQ0TTx7+um6L70tqc0rZDg0kV3UvzIIM5UklQlL2SWS5CVkmDlvZSkJXmhUNETNqoe89AUWgVPpIKkpcozr817091fyJopLX/6x5/xOgS+sVwuXwf+J8DfBJAkSQH+LeB3gPvAf1WSpPt/xu/9YrlcvrlcLt8A/q/Av/5nfnR8jtMZdKVAlUqCTMfREz4526TfmhNEBrkV0ncWvH+xxRe2TokLjSIRG95nc7kg1VGkJU8vetzaGFDVRDDq9qtzfvTBTe4+OKOqxYDJp4MeX946pqP7HKptznzhM6trEQUSr71+RLkUKDJztdHaq9ii27Uh5VImX8qYSs7G3oJyV+LxqMuOM8OSMy7iGtehy8W0hiSLvDKj6vHspEfaEq2UO/UhV1GFX73zlBdem2lkr43quzcH3KyOOPRapJlK0/aomUtGoThJ6v1wTVu59Kvsbw9pmBEfBULN+GLSQlVKkkwlyxWGnstWc4bnmNhayvvfvgP7wUpuXxDmglTydCLia/bcqUhc2JpgKhnLJWxX5nw822Rn45y8VPi9Vz7iLGwwSSy2e1N6ls/poo5qluSFwvGsQd2OGIeiMo9ldeXPK+g5BddBhZlv4f4nLodfFdFNaaHwpd4x+VKhWEps2h5hoaPLOYeeyFKLc437nWuez1qkhYKXmaSZSji2uX/njB17hiyVnAYNwqVGyw5wtZRn4/aaFCKzxFUTPr3qk9XnPNi4Eibu/pAkV/ETg+FVHUkrqNQEYutsVmf3xoDDWZOD9lhkJBoZ50GVmh5zwx3z+4f3qDuianPNhPdOt1FVAVe/3R0yiW2eDTrstKbUjZjrVQr8w1kfZSUi+fhqg7oT8caNMz54vIfqZmy0Z0IcVcp4iUnfXnDm1cgyhXFk0zAipggg+r3agG/0R3x/uM877VMMKWOa23z38oBXWtdUKzFPpl0aVsiTYYedxoyqlnDnjSFNLeA7gxtcPO6y++aMdw93qdZC5ic1Nm6NOAqabNliftgwIvxMzHoNWXQEfjzc4ZX+NYeLJl/pHGOrCa6S4uUm929c8Xde3hcbopVQsQN+cLzHJ3af1zuXvFa74EXQYcedkS9lHDVlmlgc3LsUWLWlzN7mlG+fHdB0Q3791hOeeW2BGkw1YVovFaJMI0o0AT9PBADhxbMNbt+5EFVbZLMITPJUwbCE59bPdGaJRbGUyAoFu+8T+QZuNUaWl2zW5xwPmzSrIXbFFwrzUZtp5NBuLjib1SlKifu9az462+S13Ys1aHwemhSV4BezaP6cZnnL5fK7P/G/3we2V59/CXi+XC5fAkiS9B8Av4fIYF1fqyDyfw+xP/3HP+NHVYE/l5v/c7vxFUuJ61DMxXZdMYe7nNX48vYxPzzfXb1ZYo68JnfqQ0pL4nDaxItFJt7Ms+nUfd7ZO6GixTydd8TmddbC2hAG4quowiQUraKPRptsuh51PVrPJwZJBVtNyJcyj0/7vLp7wVUgTr1VLeb7J/tIUped1pSsVAQBIxZc0bbrCwyYFgs82FJipzXldNzgaNykasWoZk6Y62y6HrJUcrMi0struqDDmKoguVf1mEOvRZDqxL5OpZMwDAWKabxweGPjgifzLl0rWAsMprHFrf6QD0+2qFQiDDVnw/U4mjZ5vXfBKBZiBT8y2P7C+brdOI4cOrawUSyeN2i+HvLjwTZf6R8xjmzSUuVma0y4SjI48ppI0pKKJrx3u+4UQ855POvRsX0WqcE0EAbvqhbzYbzJpV/F1lPOp3UkaUmvumAwrLK9McH7qxlOKWNpKY6+5Dys83zURteEavBk2iCOdLpNjyKT8UKTd9qn9PtzBkmFU7/OjdaYrZ2XfPvsgKqWsGkJK0ySi0DQs2md/daERSoOSa6W8MPzXb68fYwqF/zwYo/N2pzDQYtGJWS3NqPr+Hx6tIXvmwS2MLY3VmkVsrSkb4vA43ko7BFXcZUvbJ0ySy3GoSNM4O2Mw+d9Kn2fT55t8xtvPMTpJJxFDd779ACnG+CrAsRwuyUYqXe7Is1gmlgcHFwTZjrz0MJfmLhGgiItOfXrGGpBtzsmzHSejdoo8pJXu5cA/P3zu9TNiO8N9tdew6/0j/je5b4wxjev+cHZHq/0rlGlknwp873zffYbE27VRij3S77QOOELjROmmc2o46JKJSd+nfNljRejNgdtkaVY0RM+Gm+ufZaPB10UueQfpLd50LriJGlwOG3ScgLalYBNx+N0UcdWM+72B8xTk1GySlYoFDbNiH94dkvMamtDfny9jewEdC2fqND4jb0nHAUtpqmNqeY8H7W52RkJNGGhCFtLZNC1fZ6P2xhOTn9vwiSyqVoxNT1eZQtmq9QJTZBXCoUo0eg6Pt2Kz8LIqJsi2HeRmDSrIY6eMPJdLvMqNTtGr4rRQ82OaBgRLyYtbvQE2ahj+gwCF9dMiVLt579gLv/EWV5bkqR3f+L//+Zyufybf4rv/N/gj4LDt4DTn7jvDPjyH/M1/yvg314ul/+OJEn/0j92301Jkj4AKoD9U77+T7w+t63OYhX9c3Ih6Ca6UnCzPWKWClWfoyekmcp44fCDsz02rDl3W0PKUmLXneE6MS0roKZFZKUiaPNSyc29a17tXeFnOpNQLIafsRX9TOfDwSYfjLYx5BxVFjOtR0cbvHNwwoblCQqMERIWOvc3rmhVBafxYlzjKqgQ55qYD3gV0kKIZEwlpyhlgtRAVQuWpUSQ6Oh6ziB08VKDMDeYZxaPZj1GkcOOO6NveTwftdkwPXbcGU07xKnFVPWYRWygqwX5iUhTP5+IuBkvNNfJ7bpc0Gt5RLHOLBDotoYT0tbFxq8qJe2KmIO5WsrhpEnNFBvBcinx1pees+l4vNK65sWivUawhavnuFMRUTKqVPLds33h01o0uY6roi2n5GhKQa+2EC1dSVQ784UlhCmJiqHnDBYu3Y7HIja42RxzqzXifFoHBCKtZseoSrlumSEtGc1dZr6FYyU89ro8XXQJc9FyejbsUCLxRv+CY6/BUSDad4aa07X/SFjgaCmuluBnBpv1Oe9dblNVY+51BnQtn73OBF0teO/jG3StBQ/2z2k3fBSpJM1UjucNFKnk2Q/2iAuNqhGzWZszDhy8TGQJ1vWI5VKErKpyid6MaTghip3z7vUOTxddnk9aVHo+VSumasYoUsknV33SVZvZTwyKUuZyLgzrWa7QbIpKY8P1cLQURS7JSxlNLtioeZgreHWJRNMKWSQmfUfQdnQl58WiTZxqbLtzvvmD+9QdUbF5mcH5osaN5phPP94TeY8suYjrTDOb98Y7fO/FAZpcYKsZg8AljVUGgStagblGxxaA8Ru1CUUu03RF9JClZFQ18bccB6vNrVSoGDEfX2yQliLZ4GTaYJLYPB12mGUWb/bOkaQlcaGtsgAzytXstlzKXCyqnPk1Xgza7DanzGKLE08ksxtqTjwV9Jx+1RPBxZaYw04DQYlJC5VnA2Fqt9WMi2GdvJS52RIiuYtpDUdPmcXCx1gsJcarIOmaHbEsJWaBJcRoSCSZyihyRFSZJAQ409Tm9fYFNTNCV4tfzKL5s2d8o+Vy+c5PfPyJm54kSX8FsfH9a5/d9FN+6j9+fR3491ef/7v/2H2ftTpvAv8Kqzbqn/X63G58SBBkOl++dcSLmcBfxYXKR0dbVK2E86lIQMgThboT8R8/fMAH51u0nIBJYhOnGp883+YyqnIVVchLka2WlQqfXPcJM53t6hzHEIpGW0vZdWeYWk6Q6Hzz8iZ+ZnDq15FkQWDJljKqUvB02hE+tFLmrfYZbdOn6sbcqI15vXWBq6aEnkVaKnw03OAiqCJJS7zIIBjbVJyYdkWceBW5pGlEPBp10eWc42vRwjtZNHg27/DO5imP5j0OF00O3DHLJbx/ucVuY0rX9jEPhKfKWhFufnXvmVBjqhkPL/qMPQfLTGlVAp5ddajoCS/9FovU4EZzTN9ZcL9+zTS2OGhOmMcWg8gVi7Sc82za4bs/Er5JU825DoVsPMo0ZqmJKpfrqvl8IeTas8TEi0wugqowbEcm33pym2fzDh3X52v7hzSNCMcRCsDlUqJhhUgSfHC0zTi2ud0ZUjdi5rFFx/a50xgKturGCa4TIysle+0JdxpDwkxnFlsczRpkhSJ8YYnDZVBlw/X4+HwDLzYpSlmAzlUhHvFTg3O/xvNxm3ls8YWNMz6ZbeBnOu+d74i5j1zw5defcxVVCXMNTREb2F5rIuwhsxoHXzwVnMiTPlUt4ZX2AFPJMZWM731wB0MTsVEg5ol77pSbGwK1p0olXddH13Iuj1tiMzYSYXUJK3x8voEiCzHTve6A00WdneZ0/bXzxBTtWmlJWqi0rFBYa2ozNLngcNHkelGhtmJUDhYVPh5siBlWbYEqF1QPZivrzZJrv8LocRtXS9i9d8WLUVuwbhOXk7Ap5ledOe8Pt1hkBjfqE+5uX6Otvt9w5rJli8SQtFR4sHlFywzZqM/5dNpnELs8aF3xtc1Dura/VkH2Gx7nsxoH9QmOIeAM7Ypguk4Sm6ou1NYAbdNHlQu6lQUfTzdIC4W8kHlr65ysUKgaMYq0ZGOFDLx362KdVLFR9Xh6IVJJ6rag0HiRyc3uiKKU8TKhsg5jnYcXfZ5edklDnaxQ0JWCo2kTU81p1nyGvsvFQMwYX+mJQOaqEVMsZXYrs9XBKkWXCz6+3KCj+3Qtn3faJ7+I5fLPreqUJOlfWglOPpAkaXN12+vA/wH4veVyOV790zNg5ye+dBu4+Cnf9k/TeP3bwK/8Kf7df+b63G58srQkzETq+WBQw10JQxrNAFMVG56tpdTrIWGqsdWfcqcnLAaT2Ga7MeNXHjwlzDXqK8n0+LTO2HdouiGvNS+p6yFpITLc+taCSWKL9kptznTq4K3ifnY2Jsxii6uoymBWwfMtolyIbNJS5ZPRBrae8smwT7bKltvamHC9qNB1feqGgB5HpxUkTQhtRguH08smO65Qe6pKiSaVfPngiHTluTOUnEHsCjl7JBbOXlV447zE5MSrc9Cc4KUmXddnukq57pseaanw9s4Zd3sDGlZETY95beuSrukT5hpHpx0AbCWlroXcb1yJuUYpcTppsFzCKBan8v37F8jSkp3KjMNDQRexNJFuPU9M6naErhSEkc62I5II+lWPthWIKJeFxYP9c6JMW/vMVLkgyVTRXnaidbrBOwcnXHzcZ8cRwqKtylxk7KkCw6ZJJbeaY17tXzEOHcyVZ65tBSjykrYVsFmfc+mLbD0vNXhl45qylKitUuybdigS0/WEip5g6gIanpbCNtE2A/ZaEzYdjy+1j9FlscmMA0egqiIBEFeVEkPP1uDmzd5sjQ/7zHdX255jrDijXcunZYVMEptJZLNVmfPp+/tU9YS2HbC1PyIvZV4e9tiwF4Jk0x3zauuSy3l1HeCbrToJINTPJ6dtYXG4amArKdehy8PrHq6WcjoWlKCsELPd+NM6O7UZQaZjqRmz1GK7OhfkH3fMTnXG3uvnxIWGpWYsEd2Xui7myGmh8EbrnO3KHEcTvNhFKpiaMkve3DlnkZtUVireuh7hrYRotpZS1cToIMgNbFVU3BfzGqOFQ5qK0Nq96hRTydbK689+nw09ZN8ZY8jCy1cuJaaRRdsJqJoxg89A9taCB61LjucNPj7fEArOVQcpL2WaNZF76OoJjiECkbumT8/2efRkm17LwzQyZHlJrRJhugltSyhqi0KmbkRYeiawg07KPDR5MugyCFyqerIm0cxTE13OOV3U6VR9fjQWopani+7Pf8H8GcKWP0ncslwu/61VFfbmcrm8kCRpF/iPgP/acrl8+hP/9EfAbUmSDiRJ0oF/BrF5/ePXd1b3AfyzP+NH/xLw4k/5DP9T1+d2xqdIJXvVKV5m8GD/XLQDM51XWtd8Ourzhf1TPr7a4Ks7h+SlQlMP+OFwj213jpcJo/uzWYcvdk748XibW7UR+zcFQd1SM8apw1VQYRGIVOszahyedlkWEnu1KQcbI8JM5yqsUNNjGkbEqVcnTxW+cfsZjyZ9KitLQ38FoF5g8IPzPe52RFjpeOFwszLiybyLJhdsvXLN2UWTqhmz057xnR/f5cmky/iiRmPD4/c/fMDB/oCes6Bt+lyENZFFF1Y5aEwIckNEBxUqca6yXZmLVlim0zYDDuctfv/pfVw3Yrc2o0SiqsfEhco4cqgY4vOsVJA0oUKNC43rpEpcaHRtwTc81oQ3KysUYTdoFBwvGvRsn1974yFHqwDbrutzOmmQRBrLXOa1G2d0DB9LSfne5T5f3Tiivh1xFVWYpyavtq4Ic51B5DKLLJYrpmTX9pnGFnVTAIXLdsp1XOXhdQ9dLYhijTjXGEyqlJsSZ16NzapHx/F5PO0RZRrTQGQk5kuZbFUZ3KyMeXewQ2lG+L7JTm3GpV/lZn3MmV9bt7YcXaiDH426bNXm+JkwW5/6dV7M2lRWNpq6HTGYV8hSdW0qT1bzmsvvbJHfDalvRBx7De42Bpz4dbar87WI59m0w+2GgDtrsoCam7sC/H0xr1EuJaqNmK/cf8nLWRPXEIzNwAywDJEbOL6s0t6cs+l6bFgef/DsLkhCBX2wNeTDwSaStOSdzVOezcTh5jN+ZFHIFPviOV/6VeJMKI0PqmPOgjqy5NI1fZ6P2hRVmT13ytyxsLVU+ClLBS82KasSu/aUHw13RaakXGIrKb6qc+FXqZuRQLGVCmd5jaYdMoltTDUTgqlUwzIywkjHNDJuNMfkpYwqlzS1ENUQM9JZZFG3xOOdJMIjd7HYwtFTNhxRzbWbI/xcZxw63KyPGEQuHww28Z80aD0YcbM34tFlj3YtoGsFHE6aHDQnANSNiGu/IvyOmcmnl33eun+04rqmPJG6tOxgrXDeqc0YBO563chThW5rweV5g97mDIBxbLOIDdS6ONid+kLoUjFE5TdLLJ5fd34xi+bPz6/3PwJawP9WEplr+ao9mkuS9N8Bfh9QgP/Tcrn89I/5+n8Z+PckSfqXgf/nP3bfZzM+CUiBf/HP8wCl5fJzaMsH7Nuby83/5n+P/tuXbNgLPr7a4Df2nzDLLGapiF95ftbFdFJutUc8H7XZbsyo6yLUcpaIIM+8lLlZH3PsNXD0hLoRYyrZWsIcFwJL1bV9Pniyy5deOUSVCx6Ne9xsjPEznbcaZ3x7cENgpayAT6/6fHXnkKoa83TRJc5VbldHLHKDtFR5eN0T0UV2TJypvNG94NhvrFOe3zveQdULujVhG7jTHPLDkz1a1YCilOi7C46mTdquwEsJk7CEowsySxzqGFZGv+ZxOa+y35qgyyKoV1cKFqkAPIeZTpyphJFOrSKqMlPNOB01MIyclhus23nqakYkS0vqRsxVUCFIdZJUXcfB5IXMl/snPPPaFEvhQVPkkj13KipTPeb98y2+vveSuNAIc30dcVQxYqJcYzCr8MbmBbPUZBi4tOyAuhGvKxihtIXn8zZ9Z8HJvM43Nl9wGLTYNOf8Jye3ud0ecelXOahNuOUM+OFkj6wQcvpiKVPTY6aJRccKOF/UyEuZOFUJ5xbd3pyaGfHiosNubyKCbWNDyM9jITtvWcE6h/CGO+IkbBLnKldBRcx1zIhx4NByAq7mVe51B3xyscF+Z0zTiJgkFnU9pqGHBIXOKHaoagkvZi2hBG6MiAtVJCYkBpIEiixk8Y6R8qXOMUmpchw0WaQGZ+ctHhycA7DIDFpmSJhrAru1Uj/nS5mXo9bapnAxr1G1Yu7UB5wFda4XFb6ycUyJxHVUYRQ53KiJDtZVKIDlt5oCjLDnTnixaGOuoqV2qjOejdt8bfOQRW4yWyWgRJnGG51z3r3cxTUT7tSHDGKXphHipaZoeeYmV2GFuiFYnV5msGPPuI4rjGOblhniaglXoQCkb7lz4kLjteo5H863qWoxXmYyjS1aVsjjYZevbx2SrMhE3/7kNlolperGZLlCt7IgzHTGnkOzIrpBTTvk6GWPB3dPRZ6kV6UoJYpSZrsx4/CyjeWkLJcQLkyq9ZDbrRFPRx1cU8y7P7sWsYGpZ8gsmXgOO+0pR6cdtrfHpLnKXnVKQw/5h0e3uNkVFXzbDFYboIihug4q/Oh3/mfvLZfLd35e66W1sbO88S/8qz/1/of/xr/6c/15/7++fmGtTkmSdiRJ+kNJkh5JkvTpavdGkqSmJEl/X5KkZ6v/Nn7ia/4HK2PjE0mSfusnbv+CJEkfr+77NyVJ+hOpqcslNF8XAFo/1zH0jKu4iqUIg2qY6SwLmX5NKDHrK8r9ZwBYTS54p3vCVkUQTfaqU87GDWaJSd/0cJSUU7+OLov4oKoWYzcjcapNTe42h0xii0loY8oCtZQVCg+ve3xx6wRlpfo0lZzjq5aQzPt1dDmnX/PYboi5yVu9c0okvNjEVlO8zKBVF16us4sm46lLuZS41RvSsgJ+aeMl5VIiL2SqesIsFfi0ph2yV5nyzuYpy1LidmdIywrZbswwlVz4toxYhMd+hl6LDEwt525/gPkTKCnHFriqk/M2lprhainnsxqHJ12aRsThrEmQ6jh6yv3eNTebY9JMRZGXPJ13RObgUYc4Vzk5a+Nl5iq0tqDf8FBWlaQuF4wDh4lvM/Bdzi5aFLnCDx/e4HwFEF8kAvU1CF3h1VxKXEUVtt05AK6RME5tvNSgoy/Ya06pajE36yMaesA0twWX1IgZBw6DeYWmEdIyQ8axaCe27IBuxUfWCqJU43pR4YsHJ5yNhap0rz5FlYRxea86Jch06npEXKgkpUpVi/jk+TZppgp1ppqTZCrnkzpxqKPLBXd6A7ad2ZrAky9lLqMqfmZwNG5yNG+wU52xU51hqyKzsG2GBIkujPaFjKqUzAKLUepyGdWw1YxFbODUIxFYa4TcqQ3xUhG0u+tOGQUOHz/f4XJRxTJE2/UzE/144aBJ4m++VZsTFDoyInmibkZCDMSSk1GTfmUhfIxGRF4q2GrGhjXnleY1upzTtEM0ScDbZWm5DiwGeGfjBE0paOoBMoJMMk9N5pnFqV9HlUvSQuEyFAHGSakyT0w2bIE0myQ2QWpgaRmjWHg9n/g9OobPTXvI8bxBywpp6QE3mmPOQxEw3dRC7t8+p+rGbLge99oD6kbMfnVCsxLSsgKadsiOO2Nrf0TdENXjfmNCnivkmUKca/zyrRfcaI7Za07Z3RwTxTofnW+ymAsR1iI2VrABiX7Vo+8skCTY7UyEnWRjhbILTa4jl9OwTs2JeHQkYOuTxCbNVfqrPM5f2PUXCFn2C6v4JEnaADaWy+WPJUmqAO8Bfx34F4DJcrn8N1bO/cZyufzXVkbGfx/h9dgE/gC4s1wuC0mSfogof78P/B3g31wul3/3P/NDf+Jy7/SXd/6X/6JgBfouNxqCv6nIJfOFRR6rSPKSL9085uVMDKg363NOPtjiza88x88EwX7LnmPIOc/9Nm0jIC3V9QL7mR9o05zzo+EuNTPifu2K7w8EcupWZchFVKdrLCiQeHewiywtebtziiYVPF90mCUWaa6wXxNziVO/zv3GFcO4wkVQZb864ePBBqYmFI5RJrxkgJgHyPm6MurZPieLOpuuSC9oGwHfeXmDL+6fCMXbKpldlpYMApdNV2Ce8lKma/n86HSXraYw/GcrjmG5lFaVrcrFvMYvb7/gMqoJLqIe8NjrMossqmZM04h4Nm2zUfHWfkVXE6io+/Vr6lrIadRgFDvraJVNx8NLTV5OWgSeyT/xymPqWsQ/urjJZsVjHNs4K+6oqeSkpcLRuEmvtuD0sslv3HvMod9kHlv0nAVPhx1kacmrvSsej7qEocE7eyc8m7bZqsz/U6+RF+MWe82pYFJmOqaa0bcXnPp1kalWqowjG0PN6VsL0lIhLwX/89vPb/Lq7gWuljCIBI1DkZcUpcS9pgAHTBKbeWqiSEKle7cz5MWkxVZtTpRpDH0XU8/Yr00Jcw1XTXk5bwr1pJphKplAhWkxRwshipjF1ur+lONFg7OXHQ5uXVE3Yh4PuvRrHm0zxMsMDkdC6PRq74rLsIKfGLzSuua98x22GjOOr1tsd6e0zHBNIslLoXIEYQe41RzT0gOezjtMIwvXEMKku80BXioOLMPIIV/KNIyIjx/t0tyeUzViBguXJNbZ6Uw4uW7yhf1Tjr2GUCau2nZFKbNTmTGKbQaLCruNKVGm0TAjdu0JPxjsM5o73O0PBPDb9ZjENudXDQ62hiLlQiloOwF5KdTFLSMgKsRrXZfzdcv/2axDkIi5/zd2nnMdVzGVjEdjgS+8XFRZLmE+dtnfHuJoKUGmc3zV4tbWgJNJg4YTsYgNtuuztbDm2q/g6ClnJy3sZsSbG+cczltMFjY3uyMRlyUJEVbHClYiIRdTFxFQu7UZw5UHMysU8qVId9h258Sr5JTDRRNNLriY1ZDlJQ//+v/451vx9XeWN/+5n17xffo//8uK7091LZfLy+Vy+ePV5wvgEcLH8XsIxz2r//711ee/B/wHy+UyWS6Xh8Bz4EurDbS6XC6/txS79L/zE1/zUy9DKei5C25Xh1iaABC/0bngC50zZGXJ7d1r9jdFikLTDvnaziF1I+b+Fw95NOhyNqvTtRZ8NN7ksdfl0dEGV1FlZT5Pma8qqY6x4OG8h6oUNI2Qq7i6zuoaJBXypUxSqvzdhw/4au+Qji38Q3/v6B6T2Ga3MqVuRew5E66iCjUj5tGsR8dccD0VCrqKKdiLb7fOeK19ufYCDSOHTwYbVLWYX+09E5VfbcS2JRZzVS5wHCEGECG2Yq4UZDpNK2QUORxPGqtNymCnNaWqC5KGIpdMYouroMJ1UOFk0sDSM757ecD7nxwQF5pIPlhK3GkOCVIDV4vXiexxodK3FnQMn4PKhGdem+8ODxjFDq6W8kr9mk3H4+VctO82a3O+fucFxVLiMGixuwrxPHvRFYubXOBqIsXbMjIMJefe7hWHvsht6zkiceD3bn7Mve6A98+2+PLmMb9792NsNeGf3P0YXSmEf3ElmjhoTlasygq7FbER/PhiG0MRr5dxZPOVzhGb9px3L3e4Cits21Pahs+v333Cxy+2GUTuOs19w/X4QlfYlLzM5JXq1SrPUOJ2W7StlqsNvKInvNq94k5jyMm8zihwOF3U19SPh8OeoPsgceI32HQ8cQhbtQ+fTUV00t275+hKwfsvdmi6IWmh8sPHB4xCh6/uHHGnMyQtFX6z/5i92pQw13lj44Kb1TGNerDOT3w87qw2WpWqGWPpGa93LvEznWeeEL+0nYBtd85OdUZeKgQrw/m1VxGm98Tii6++5Ne2ntEwI764ecqX9o9IChW3EvPe8Q6aUvDs0RZH0yabjkfLCpClJePAYbcxxVVT7tSGxIXKLLPZqcz4G/c+WKuC950J+9UJX7/zgrRQ6bo+jp7yRv2cbWfGVVDh/eGWmGMXGvkqlmgQu6SFwmJm0XID3h9t46UGjyddJtdVZqsZcdsJ6HTnDH2XceQgrYgqz477uFbCK80r7rSHHLhj/NRg057TcxdMA4s3756QJhqHcwFDaFXFAfV82MBbxR4BIglCE5mBYSQ8lo6+iiCyAtFiv2rwyaAvBEGlQkVL6Fo+/8TeU6JA//Muyz/7+gtU8f3nouqUJGkfeAv4AdBbLpeXIDZH4DOJ0h9nbtxafZz9Mbf/cT/nvyVJ0ruSJL2bzULiXFRmPWeBqWQMYpdh4vLGxgUXc9EKuvBFlt0Lr01dF6xEXSuo22LzUuRSkO+3xhyPmlz6VcqljCKVdMwFP7zeY9uZ07N9uoZI6JZZoisFXmrS0EPOwxqNZsAkdVaVgEO/5jGcubx3tkNVF+24bWfG3co1dSNGkwp+7cYzWo6ALjfNkE9mAtycFKpIRGfJrdaInrnAWPH7mrpYSJqrllO/6nE0b3DtV9h0PB6f9Nly5uJ0rCe81ruiaYhN8GxaF5WsllJZefF2KzPuNga82rtiw/WomjGv3T+mXEoiSmWVY2iqGXmpsGF5pIWyVt89nAnup6nmvNU8p6onnHk1xolo0XZtn3EkNsNTv46fmVz4VSareVl102O/Nl1nHA4jh+lllaYR8fSyS1VPuPJFIOz3T/Z5suihywWvbV2K035Up6oK2r2pCPXlPDHxMpOmIRiiNVu0JdsNn7KQaRoRlpIyCW2CXPjpTD2jaUa89NsEucFlWGV7e4y6YjOGK3uKq6bUtWh9yGiZIQfV8ZpKcqs1WnvyBpHDLLWYhxZNOxSKy1Jh157iGCntVetPlUvCXGD1JqFNVsqYmngutpqx50zZ3RqjyQVd2+fNOyc0rZC40OiZomr3C4N5YorHZIjEhnvNAU0zxM90mna49v15sUmcaaSliEWqGzG7tdla9PPx6aZof7pz0fGoz3kxbrFhL7gMKwwTVySPqDE1LeKd9ineWZW93hhJWrJ9e0AU6LhazOm8zsNhj4qZUNcjMUZQE9pGgLNS4nq5SWU1u72Ia/iZwSwRRv9npz3u1Ia0tQWbxly0TC0xw/zgZJtB7HKzLg4dB/UJuiOwetuu4PKaas7dG0JRP/RdTEW0Zd/ZOGU0F2SjRiPg7v4lXcdnltqMY/G68GNDHADnNeFnLWV+4/YjokzFDw0MJedsVscwUzE7T0wxvzUiXCMhKVS2mjOA1cExFUKb2Oart1+iqQVpqTCIXPRVPJMslXzx4OdvZ4C/hFT/XC9JklyEMudfWS6X3s/6p3/Mbcufcft/9sbl8m9+ZrBUa+JFO0wqgnoQu8QrEPIsNamYyVqs4Wc6aa5ytfLs3W0OaZohhpzTNEPqVrSmbNxtDng+a7FcSjyc9gljnX/4yV2uggpnUUNQ4Q2x6d6qDIkKjUVmsOF6fPv5Tep6xJNBF1PN+Wt3PuF2d4jMkkFU4aPRJs/8LoezJn94dhtHTbhbG6xxTtvOnD13gheZ4kRpCdJLUqgcRy1ezFqMUpdBUqFl+KtU+ZK/uv2QL/VO6BoL7u1eocsFu+6MvrWgosX88HyX0UIkNZwvalx5guovTL8qT2cdLsMKriaieFS5xM907tWE/eNoKvxZYaHz0XiTqi5oJ6pU8lbznFli0jaCdYV4rzlg05rR1gPqekRWynipsRLJFOxWZqtWX85ObUbL8Dn16sSFSssM+Y03P2WSWDh2wgcn22xX52y4Hm9vn+FqCQfOiFerF/zgeo9h5PBw3uf//MFX+fHFNsulxNHLHraachFWeTrvrE3CB7UJv3v7E64jl2FS4aAx4R+c3iZfytxrDjBX8+HLqMqZVyNM9bXM3Vy1vQ+DFi/9Fq/UrvnW9U1MJefxtMcocFDlknFscx26PB2JaKUde0a/7hHlGhezGj3L5+miw0FtQlKqjFbEGFPJOAtq3G0NebV1haWKjfjMq3HoN5kGNu+0T+kYPvPEXCsZZUkk0j/y+mhKwSwx+ebpTWGlKVSeXAv2at9e8N7xDjv2jHloseF6HHsNwfUsZXQ5p2MFPB53eGP3nOezFi9mbc68GkeDFhs1j2fTNmeHHf7Rj1/hw+Emo9Th48km70+2eOXBqXg9SiXz0OIL+6co0hJbz3i1e0nX9vlksMG3Lm8wSCoiKikXXr6/88lrvDsQUv7rVbxVXKhczqu8cXDG43mX70xu8cFsm691Dnm1fknbDHh1+4I9Z4qjptyuDgH4rYPHzGOLo3mD59M2t2qjtXVktzFlHDkEmY4h5/zywQtcLeXV1hXPLrpUtWQNVo8LjYYT8nDUo+WIyi4tFRa5ya9uPUfTCnq2z732AFUpqZsRNTOivkpmN5Qca8XgtVRhwdiwPN5pnKBIJYPI5XZjRN9asGn/UX6hl5sczps/c839c10/q9r7y4rvz3ZJkqQhNr3/+3K5/I9WN1+v2pefzQEHq9t/mrnxjD9ivf3k7T/z+gyOnJcy89TCVPL1RrBITGpmRM/08BKTq3mVOFe5XAjYcUWL2XcmfDzZxFZFDpyXGvz12x8RFxrjUYW9ypSkUPmV3Rf8k29+yK3aiJYeYKup4EEqBR9MtpgkNluOsA38ziufYikpX94+5pY74vmiw5Y958yvsedOaFqC1NCyA/bqU87CBqdBg3lqsl+ZcLho8szrcNCYrC0Jv9Z7yrujHTSpxFBz0XorNE6DhgAOOxO+OzogKVUmqUNdjzjx63ww2OQ7L0RiRKfqc6cz5Csbx2y4HjU74kudY6JMnD792CBMdT4ebKBIJe9/fEC5lPjO+QENJ8TQcj4+3OLZuM1BbcylX+XhvE9Y6MwyCz8Rp9/DWRNXTVDlgu9dH/D3ju7yvdN9HD0lKVRGgUNcaOvZYL4UKtHLqMZr7UtUqUSVSq4jQd3vuD6dxoKWIYJRZank2bRDVGg89Xv8+uZT7jeueLV+ya/fe8Iv77ykZkYc3LzixxfbHFQmvNG44PiwKyp9Oec7VzfYcWfEq8int/tnDCKXc7/GuS8M9s9HbRqWwLhV9YRpZLPrTmkaIRd+lVdq13w43WS3MqVl+OxWZrzauRIZc5Yvvs6Kef/Tfd4bbtOzfCw142s7h1wEVRHi6jWoajFNU/ycvBTYuhKhJA4yHVPJuN+6RpVLvr71ktOwgaWk3Ktfk5YK1VXGYloIEsiXmse8Ur/mbmdIXGj0TY9+w2PT8TjymlSrES8WLb64fSLmpK1LrgY1qnrMKBb2na9vHq5zFd9sn3GrMcJ14lWQa8GDu6e09qaUSOzZE2wtZRrYtI2ARWKy5c4xtYyLoMoiM+k5C7rGgqoW83rvgp3qDJklj2ddDhdNNu05f/XVj3m7c8q2OycvFM68Gn17gSKXfPhyh5oe46oJQabzo/Eu74+3aeoBPXOBLJV8Mt4gKkTF/f5ki5v1McVSpmrGvH+9tUYCns9rXI+qq9zJKt87PeC9J/v4ucHXb7xElQs+PtnE0VLSUiFKNb6+eUjP9nmreUbTiNDlnKu4xq/tPGMQCSpSywm4XFQ5nTQEd3XlKb5aVGis3vOfHVL+4PIuu+6MIDUYxTaOmlDRYtKVivfQa/F25/RPWP3+7JfEzxVS/f/31y9S1SkB/0fg0XK5/F/8xF1/G/jnV5//88Df+onb/xlJkowVpPQ28MNVO3QhSdJXVt/zn/uJr/mplyqvZPlySUMPGUYOQ98FYDhz8VODcinTtgPudQei3x7r3G6MsOSMk7DB260znq8k5GmhEhU6s8Tk9179kA1zztd7hxhyToHEtjllzxrzfN7mwBG+oru1Abpc8P137/J81F6r2Eaxw7cub+BqCYacM5y5TFN7bbK9X7vGVHJahs/RtCmI8V5bmJIznVHkcH7WYhi6JKXKtjvn4bzHO+1T9twpw8jhtfoFh7Mmf/DiLtPI5vlc0Gu6xoJtZ07TDnlr/4xxZHNy2maaWJyHNYahi6VmZEuFV5pX7FWmpLnC1/uH/I2DD9ivTKjvzNl0PAwt52pSFQrSRshWbc6HV5s8aF2KVmcp46gJv771lANrRMMKKZE49FqM5g692gJDy5FZcrM65vXOJfcrl5x5NSaJJUzIqlAapivfmywtOZnXsQxxIGlYIe9e7/Bs2mYQuZhaxsO5mI0Ycs4n0w029DkPnAvqWkjbDNh25vzm/pN1rtmdWxe89Fp8+9lNdDXng6stNmwhEmkbPrNY4No+S/Uw9Jx79WveaZ8K1F1jIEAEw/56jvOZ1eUzWkhNi1asUoVn510G0wpvPTiioidr32i5lIW5uz7jl/oveW+8TV7K1PWYT677bDgek1gskGGqk65SPvJS5jISIPOruEa+FHOtR4MulysBxy/3XlBTIzSpwFbTVdByiZ8YhLlO1/bpOP7a53k8b/DCa/Hr957wYtamqifr5zWJbbZbM+patEIAQs/ycfSEcSS4or+y8YKKEnO/dsW9zoC6FtFbiaV+aeMl/dWGF66oMc/n7bVi9LOKqKbHXEVVpqmNq6YcOCNeaV6xXEpYSsav7Lzgy7cPMZWctuET59p6Rj1JHZJS5YfXe6v0g5JtSwh5anrEr209o22G7NRmItVEWuKNHfY3RgL4HVTo1zz2dwekhcLzeZsXszaOm3AyE7zQYinzzOsgSyUfTrZWfwtFtDO1kE3HWwtg4kSkxX8WO5YVChVTbNafHa6HibC7jGKHV5pXxCsxWlWNeTETIdMbjseLRfvPuBr/6a6/SBvfL1LV+UvAt4CP+SNr5L+OmPP9h8AucAL8U8vlcrL6mv8h8F8HckRr9O+ubn8H+L8AFgJ4+t9d/gkPvP1Ke/nX/p2/xqYx5yKprdPRj4MGe86Uuhby/nQbUxEDcwAvN4VPJxTzsLxU2LRmzDILS8mICjH3GEQutpoxT0zeap3xwWSLN5vndHWPTxZbvJy3eNC84um8w54rTr8yIkvu9cYFj73eGn78tx+/zk5ngqOJOYAsLRlHNh0rEIttKWOrIh7ptfoln8771PUIPzMIc41dd8qzeYfXmxekpcppUOf5VYdfufGcA2vMh94229YUTS6pKhHfGt1cK/gA8pW4YduZM0stRpFD2wpIS4VR6KwVhiUSt11RnAe5QV0L8XKTk7ApkGdKxjgRtJq7tQHvj7ZFirrl8Wze4dXGJa8651SUmGFe4ThqM1rNPF/OW7ir4f5yKfFG85xyKXMSiqrnIqxyszJmnDrEuWAudK0F3zs94LX+pWgBZQYH7hhXSdg3R4yyCo/8PpUV43OcuBx7Dd5snwvm51LmNBRpGR8eb7HZndEwIh7UBJj5P/j2V+jemFAzIwa+mLHcqE/Ys8dkS4WzVbDwRVDl7dYZF3GNjrHgD17c5aAr/HiH8yYPWpdsGnNOoiaPJ12K1e99ctjgt7/ygUi9jys8m3XWEUEHzpjvDfbZr07YMD26msfLqI2rprw33qZthoxim5NBi/tbIm3AVhNaeogqFRwGbdJSIS0U2mYgeJnSkhvuiLOosRJl+Tyc9daevjcaFxRLiZOwyU1nyDB1xWxUWnIUiMNf0wgYxS5XfoXpwubLe8ciFiiyiTOVg8aEi0WV3dqMlh4wTh3SQmGaWGw5HoPI4XZ1RFKqfLF6yHVWIylVPpxt8fyyy1+98yk/Hm8L0YvhU1/RVf7h5W3GD9v80i99iiYXjBOhCvYzncPjHm/cPmHXnjLJbME81SI0qWSeWWxaMz6ZbfDL7Re8P99h25rx3et9Xm1d4agJP7reZTwTB+J6TTBBHSvh1dYVh4smLTPEVDI+GWzwazsCQnIUtBiELruVGX6m8+i8j24IduztTZHkMktNLuY17nUG5KXM2aLGrfqY80AoZit6wiI11n7geWjRr3q4mkhXF9FNVe7VB3w43OQrvWMsJaVExs91/nfv/N9+ripLu7ezvP1P/3RV50f/68+XqvNza2Cv3estf+V//19BVwpuuwMOgzaPRl06rk9RygI1peQMI4eLaY2v7h4JRmchsFMXXpVXO1e8mLW52xhQVWPOojqHsyavtK6paRGnQYNblSFnUYNtS6QK1NSIbX3C3x6+uZbs+5nO640LXvptqlrMrjXByy0GSYU9e0xU6GRLmajQeTjusVnxcLUER0n5/Y8e8Oadk7U44sVZF0UreXtXtDv2nAlJofLuaEfYE1Y/U2TOFUwSi761wM8NPjrb5NUtsVF0DKEuve0MOItFi+yzx+8qMe/O9+mZC174bU68OmGsc2OVqvCZUfsr/SOmqc2jcY/f3H7MH17cZrc2o6pFxIXGD4/3+K3bj4gKjVlq0zICglxny5ozTFy8TACxr0NXZLitbAV3G8IO8KOLHboVn4qerPMGn43bPFi1DWtaxDhxCXONu9UBXmYyTFyqWiyoJ86cm86Qi7jOu4Mdkc9meYxTh5YekJQqV1EFVSpZrBiLAL/cecE/vL5Ne6U4VKVy7e9MV2rGDXuBvorPiQtNGKudGY6S4OUmlpJx6LdE6nzvkJNQtHmfz9u81rzgw/HWmjVZ1yPahs/zRYdJbJMVCi1bwMsf/Z3bvPG7j9aJ57qcYyg5SaGyb4/xcpOkVFnkJp8M+6SZyv3eNQ095NhvcK86EHM+NebhYoMDZ8xx0GSSWHQtn7Ye8O5oh7RQGB81qO3MhQpazflK+whXSdDknHluUy4lvFwIZKJC42jR5Bvd5zzxe5RLmffPt7jdFQxRMRcsOPNr3GtcC5ybVPLxaIPX2pc8mvToOcKH56UGL887/Ordp+tDgpeZPB+3+aduvs+n3iYPqheEhY5fGDya9dh25pz6dYJUJysV3uqe8el4g2IpjOWWlvFa8xJVLjj0WwAsUoP79WsMOScqNaKfqMg/a6+npfDa3mqP6FoLLCVjx5xwETfwcpN3L3eo2xH71Qnf/vgOBwfXVFaYsYYeUlFjvj/Yp2v7uKuZ4OG8xd3GgKezztoLe79+BcBp0OBk1qBbWRCkBlGmsln1cNWUuFDZcUTqTksLeBm22bcENOB/+sb/6+e78XV3lnd+xsb34f/m87XxfW5ZnXGq0rMWTGILhZIfPD3gdmtE1xJMPVlach25LFKDzcZcKMlMAYGdRjZv9854Nu0Qphp+bjDLLML8jzx0hpyzZc+xFKEMnWU2Xm6iSQUXWZ2roCLUg6nBpu0R5AZb9own0y7ZUmGS2bQMn67u4eUmHd2nY/j8+tZTXq+dM1u1S96+e8wNVwzgdaXgG3ef0W/NGcW2YBUqMVGpcas24u3aCXcr17xSvVoLEjZtj1HicOLV+fWbT4VKLHT55slN6lrEOBN8wqu4xr45oljK+IXJTWeIjBBjbFfmVCzx5n61fsXvbD/ENQRuLS40Oo7PeVzH0VPSQuHEb1BRE3baIofPkHO2rRnz1OIyqPL7x/dIS4UNay4INUZM1/JpmBFvts/JlzJPZx1utsbCd7kCNOelTMsJCHOdihozTlyRkhHbJIXKPLOYxtY6kiktVeTVZP4r/SPypcxx0CDOVRa5gaMm3Kte07UWzEKLnuUjs+R50BWtP9NnuOI3ulrClj0TwqVMhLE+nPT4eLTBp4MeQaYzT0VnYJbaTFOxUfzqxjPeH28ziQUxaNudU1Vj6ma02swTzoIaZ2GDUeTwSuOahhXiJSaT2KL2K9fEhcbT6y5nfm21URd4mck4E+08Q86pqDGvdq5EkkGu8Z3TAyFCKnS83CRbKrx/tI2f63xy3V9DsOWVv8zSMnbvXDOfilipm9URmlRQUWJsOUWTClwloaP74u9pzth2hC+yXMqocsGv7j+naYTcc6/YsAT671ZtRFWNuetcs21OeaNzTlWNebtzKiq2WZNZbPG79z9h05iTLDUcNaFpCLP5OHXpm0ITp0kFVTVm0/FISwHULpYyLVsoSKNUY9P18OaCOfvMa3MdV0kLhYdPt/EiE3XFsLVk4d9rGb7Iz6wMMRXhnUw8EfL74+ttNKngKqkxyyzyFWQ+KxQmiU1ve0qQ6gKIsWpL1tSI15qXmIo4FKWlylZljpeZ+LEQcDWMiMuohiHn6EqBuxLaHdTGtJ2AO5UBfq7TNELeH21z7De5TGrILLGVlK7+szSCf/7rL5Kq83Nb8TXudZf/7f/wV/h0vgHAjiMWYVPJOPEboqUYOrzdPRO5dKkAFlfUmGdeh9vVIR9PNgF4rXnBeVinbYo3vbwCEj+a9rC1lFfrl3z78gZVU7SG/NQQc7dhj//S/qdcJ1V+dLHDr+y8wFIyfjTaZcNe0DEXDOMKaalwPG8wmzhYbsKdzhBdLtYtzs/wUJ+dTnfsKe+Nt7lbG/DN05s86IoTfraUuYqq3KkMCAqDd693uN0QLMIDd4zCkpd+i3lqoskFrzcuOApaa8zXZ1VHmGuiuhq1OWhOxCEhEGnjX++/ZJBUqKzaYK6S8GTRo2cKz+NOZUbHXPCD6z3uNQeEuahUt60ZPxrucrM+EoP6XMdVUz4d9LjbGYrYF2dBWig0jZAPB5v80zd+zGHUJilUns/buHrCl5rHPFxsUNdDvvnyFjd6I9pmgKOmjBOHnukxzyxu2CNOoiaOmjBfYeqaRsiONeU8qvNkKjiK5VLCTw0xczFidt0peamsCSOmIgKDDSXnjn3N87DLPzq5ua4IWnrIOLV5f7DNRsVbR8tockFVT9iw5swzC13O8TPhvXyrdcb3B/u80TrHVVP+8OIWN2qi3d5Z2Q8uI4FK+2LzmGIpo0kFmpzz965eQZXLtaG/bQbr9l/LCEgKlZ65wMtMDDmnroU89Xu8e7zLvc0rHtQuGaYuo1hI9/umyHJ8f7KNJgsmaJQJgPo0sPmd/UecRzXKpcymNeMsbBDmGhu2R1RoqFLJh8NNWnZA2xTEl745572xEJ10rQUnfoODyoRtc8oTv0dbD7CUlFlmr6EGj8Y9qmbMhr1YdynqWkRUanz75Abd2oKWGa5b6baS8Q/ObzO5rvLFu4ec+TW23blIXTAWfOvyJkmmUrVi2lYgOihqyiIzeTLp8KB9RVML+XtHd7nVFgfLSWxzozrGy0zqerTuvviZEKv1LTH++Ox+PzfWbePPOg0fjza42xxwsmiQ5gqbFY9pYjGYV2i4IftV8XceRC4vTnv8tVc/oq6F+IXBR9NNwkxnvzpZqXjr1PUYVS746HqTO+0h29aMG9aQf/X+3/+5V3x3/8ZPr/g++Lf/suL7L8TlqAlBbqxxXMO4QtdYEBciCy7MdN7onPPNo5v0DI9dW8xThkmF3+1/QrmU+Xr35brdteNM8TKLHw93+P1nr9DUAr7UOebAnfDU6/KV3jH3a9fcrIz4Rv85tprypc1jDoM2u9aEr20fschN8lKhYwXMUpM/PL7NgSM8Rr+5/Zi/cu8J/8TeU/adMR1TkELKpcSN2ph3z3c482uEucb7ky2yUuE0aPBa74ph5Kyk7y53KgMmqcO2OUWTC64jl6qW8HDax8tNfqn9HEvNqOoJn8w21r8rPzc4Cxs8qF0SZjob1pwvbJwJ43up8Bubj3nQuuSl30aXc6pqTF/3OA5b5KVMUOhYWsosNbGVjC/3jrntDPhS4xBbTbmKq9ysj3g2FVl3s9jiOnL52vYRh7MmTTNcK3EPF00OGhOeBj2O/cY6q06Wlkxzm7oeEuYGr25dUtUTzoMaf/j8jlDxLgVZ5VvDm6sZkcyWNefAHVPTIppqQFjo7FWntI2AN+rnxLk4lW87cz4dbzBLLV6rnjOIHMJcx1ETXngt/tHoNudhjY2ax1VQ4SKs8YcXtzjxG9xtDjGVnA3Ho2WKWR3Ah2NhpnYVIc6orbii77RPiQodVSr4q9sP15WHJhUscpNTr86WPecqqXIUtrhKq3xzdBsvMblfE8KHW5Wh2NjmHTqGz2VYxctMslLGUlJe+i0UqaSixdzbvOLN+hnD1MXLLDYsb2V5KUXHwRKb5me4Olla8o2d5zTUgL7pUdMiTsImqlxwvqgRFRrfPzxAlkre6Z2yaXv0TVHBP5z3ebVxKWADSsauK9p1jxYbnCwaQulbGESFxvvTbUaxw4P2FUEqRCi3q0PqWsRJ2GCeWry1eca92kAgyCpjgtzg/ckWr7UveeP2CV4mVMO2mvLD4z2u4hrzhcWr3Sv6zoK4UHHUlKfzDrqcs/BNKmrMIKnw5sYFz4Yd6npE1RDz5Eu/SlWNhU3GmnO/ds0tdyRm6H59bX+YJSY90xOzUkPkUu5UBXbOXYlsqlosqjw3ZOrbOGoqxESWT7O94Cqu8vvnr3AVV1HlkgfNK0axs0b2paXCLWfIL2+/YN8ZUyBxmdZ+/gvm8i9Wxfe5TWeIC42o1HhQvcCQMx4uNnm+6NA2A5qGMKq7Ssor/WuGqRhuX8dVWkZAvBStsAN7yJcaR5zGDfqGx6Hf4mZ9xG9sPqare4SlTqgYbJozbDmlQMLPTVw1plfx+Pb0Fi+mLVwtJi1V8lLhD47v8ObGOa6a8JXWEZpU8HbjlLa2YMuYolASLzXKVfRKmGts2XP+y7c+QpMKTqImR9NtNLUgTHW+3j+kpkUEhc6+M6GhCf/hPLdQlZItZ05aqpRIfLn2kj8c3+ONxgU7xpijWKjDRolLz/SoaxG2nNK1fapqjCaVVOoxDTWkrYn2sCHn9A3RaglLnZoWUdMiklLlclbjN/af8O5oh1/rPSVbKmhSwW82PyVbKjyONrm7fc2ToMd+dUJNE97Iv7L1jLxUaOk+canx//j4C9y+M8TPzHU1N0tNzJW3q2d4vMgsngy6/O7NT/EznVsbAz442ebN3TN0OceLTapqhF8Y3DAHjLIKw7RCU/XX89jjsIUh53Qdn7uVa174HVq2qA6GaYU3m+e4SkJbW9A3PP7fp6+iySWWlnKjNmHTmvGYHgfumHypcB1V2HGnPPKEAAlguzVDlQveG+/wy50XQugQNdZg6NOogaOkJKW69o5W1Jg3OudEhUZFEyf+vu7xrOzQdxYMkgqKLAQ6k8zmTm1IUOjcqgwJCoNJ6vDjq23e2Tjl/dkOHdOnbQbU1AgvtxjFLtlSJi80dtwpPxjs8+XukQAnJxb3G1coLFHlAk0qaKiikvt02ue15gVppvBG5YxPK33KpYylJNyxr/ne9AZfahwSFgamnGEpAmpwyx7ywXyHWSroJSUSt60BoaGv36vlUuK3tx7x/fE+X6m/5O8N7vNm/Yyw1FnkJh+NN/ntrYfILDmLG9yuDjn0WyS5yv3GFQ01ZMuY8trrZ/yHx1/ga/uHAjkX20SpRtsMaBhilvrmzjl71piO7pOUKge3R7xunxKWOn/r+k3aZsjH0w1+tfeMbw1vEmY6fUdQiBwtxUsNtq0ZRdngOBACmGlqc9sdcCnVqKoxrpbiNsa8e7FDqxLg6gm3tkZMU3sFdFe4u+qI3KyPaOsi9NpSMm5WRgS5sQaKK1JJR/e5TGrsmhO+Nzn4xSyan8/m3x97fW43PkPOmacWN+0BtixiYx7ULvFyk3vumE8WW/SNOVGpoUkld+1L9qwxtpzyB8NXWKQGr1ehoQbMVYvvjG5gqxl33Ws2tBnv+7tMU4dRLEIuVankR5/e4K+8+ZAeMuOlQkMP+cbmdC12OE9Ezt975zt8YeuUpFT5B4M7BKmwUbx3vMMX90/W/M8De8QXq4d8a3qHRW6sF4h/6sb7/N2L+0SZxllU527lmjKV+EfnN/mrew/5eL5J1/R5p31KXQs5CltUNBVdynm7fsxF3GCUVQhyg+9d7PPlzWO+d7lPlOh8YeuUU6/OIHS5OGuytzfkTm2IrYg5D4iT+3XorrmDrzUukaUS2/z/sPff8ZZkZ30v/F2Vdu28z94nx855enLWKIxyQphggQEjLphrX8D2tY0Nfh1w4JprYxsn7ItBJshYgCSjnEB5cuqens7h9OmT086h8nr/WHV2t4bpmR5pknrq15/69NkVn6patZ78PB5VP8ON5UW+vr6LA8VVTBHyeG+QvZlldthruJHJzYVLfHH1AANWVyX4BzZNT/lfVpwCt2yfp+2r33UvTTew2FdY41htjIlMnV5ocVvpIrbu48dBFIYWcWBimUuNEm8Yu4A1pISEI6sTbIzkqLoZ9uTX+J2L9/KDU0+x6A6giYjHa9PMZKusunluKCyqiE2nRNXPcGRlgjdNnaMdpphOVSnZKsrwzsE5moHyO46mW1TMDgvOAAXLwZc6I+kWXzm7h/fvO4YvdTacAhutLM+kxjlYXCZCI6c7zHYHqXtpJuw6vtQ5mFuiFdqUzB5n28O8tXKSdmjTCm0iBDcPqAJGJ5uj3FqZp+6nyeoeM+lNNvwcvdDkhtwCF3pDfHDnk5zvDmHr6jsAJaj0IpNbBy7RCNL0QpPZnqphOmB2Ses+MNQ3FZ9ojfHYxjSmFrKzsImlB/RCix/ceZTj7XHuGr3IfGeAIKXxxcZ+bD2g5mdZdopkDZezzSEurlXYM7bGRKaBratSc9N2lW5k4UQmdxYv8HR7ipqXYdUrsLe4xsnOGG8ZOk0jyDCRqvGUO80bRi/whcUDbC9u4kVxTtt6hXfvPMGlbpkvPHYLP3r/t9hur/NzO7/GHy7dwb7CqvIhF3vUvAwlq0dKC6hYHT45fyNT+ToDVpflXoGM5tEOU6pBtNSYydfY9HIcHljiq4u7sbSQr1/aSTnX5d6RWaVVm6rVUxRXOPr8pf3sKW+wSoEBSzFDzzXZObFJFKdgDKZUQNOam8eLVH5lxjS/TZMcSPXYX1jhRHWEejdNwXQ4Ux/i/tEzLDgDTGXqL/l8udWI9vWC65bxbfRyFK0eK64yC2xPbzDbGySUgm9s7ObO8kXOdEZI6x4Prm6jWbE5uj7O9lKVvYU1TjZGaMeT21y3wqHSMl9f2sVYusFsd5CC4TCT2WQ8Xado9DjamOS+w6fZnt7EjQwQqibfcLrFPflz1MMMT67dxzsmT3GotMyw1WSuV+He4QvMdStYWsAH9j9NJAUbXo4Vp8CGlyVV8PsaXcnqUvcyfG7xIEOZNmPlJmndY743QN1N85bJszxRnWJnfoNVp8D5ZoU3DF+gZPbIGi4PN3eSNxzqfppPP3MD7zhwknfPnKDqZ7l/8iyDZptPXLqRH972JDPWJo8Nb2fDzZHVXT6/fIADpVXmOgPcW7mAoY3wwKld/MjNj7HsqGr3d4zM8dW53dwxcYmc6bHQK+FLlWP2+MYUNw8usM3exBSqe/mA0aViqo99QSsxaLZZ6pXQkExmaqrcmOlSSbX580u7mRqos9wrUnPTMKBy45Z6JeabJcbyTYbtNoHU2HAVo8sYPu+cOcXxxijvHT7GRpBnV3GDzyzdAMBIpk3PN3Ejg/3ZFc51h2kFKabSNXqhRcZSPiHT6tAI07xv9BlW/QJH6xNoSMYyTdpBilPtUbqByS2leb65vpN7hmb5gQNH6YYmu9NrrBoFZtMVJjJ1nqhOcaC4yuMbuzHj9JWUphrNjpk1YIAz3RFuKCzyB3N3Yuoh9wypNjpbjUgvrVXIbVPFsd80dI4NP0dOVx3G/2ThFm4uL/K5xYNM5BsMpRRjXvUKmCLksZUpGIVBq40pQua6FfblVjjfGeLYxhhp0+f+0TOMmA2KA13yFYev1fZyvlkhZ6rI34zu8qbSaT67cRiAs7Uh3jlxkidrU/hSJ0LQC1WUZKXYoeebaEjVhUN6ZHSXb27upuHa7CpuYMS5hYvdIk3X5s0jZ/n4/M0UUg4z2Rq7s2v4kc7hyhJZw2WpV2J7bpOd+Q1MLeLG4gK5u118qfPFjUOqZmy2TsXsMGB2qfkZVsM8bVKYIuTW/EUKpvoORlJNtmfW2fTzPLC6nYPlFUIpWOoWOTi0hC91Prj9CT45fyN/efdTfH1tF5tehgcu7WD74Oa3dUy4f/IsRaPHgjNAVncpZXsUdvboBiksLaDmZfClRsnsMWh1eKY+yr3DF/o+zr3ldUbtBqeaI4xZde4cmSOjK5P5nolVnmmNM5xq9YWulxriOo33eC5ctz6+lOlT8zJ0QhWm/kxrnJLZY3t6k4zhk9J8Ze7qlBnPNRlKtdlbVi1M6n6aHblNupHFidY4tu7TCmwqmQ5pXbU+mbKrLDtFjlQnGDab3FaaYyJdpx2mWPUK2JrPUKrNiltkJSjSCDPcP3EWnYiql2XJGWDKrjGd2mQqU2OuPcCam2ebvcmh/CKWHqiQ9J5qWTRh19me3uxX1LD0kE1P0XFbYY53DJ/AjQz2FdYYTzXYnVtjX0lpuxfaFY5Vx5m0VeDGmpNjbLTObLtM1c8y2yqjC4kvVQWLI41plvwSbqSCSjQhCUI1od1bucCKp3KR7t57HlOEKmS7VSalBewa3OhXXNGEZDzVoJzqcEN5mcVuiRDBojfADeVlTrTGuNit4EYGXmRgClWybE9ulQFD+fyeWpqg4ad5z/aTDNttDhcXuXFgCTcyWHdUEfBuz6JguhQMh2G7zWCqjaFFjNrNfnScrfkMm03Suk/ectle2CRvOtw/coZIavhSBQ5dbJZZdEr0IpObhxYZsVsUDEeZvCIVIWmIqO/Dyxmu6mKQ26AdppjINuiFJk3fZspWgQx53eGtY6dp+TYFyyWlB9w7dEHVeLQ7PNMcJ6UFHOtOcaw1oTpuhBY3VhbxQ13RbjU5PLDEaKZFuajqwvqRziWnTNXLoouIrOEShDq+1DhUWebIpUm+dGY/T9an2JddZtBocXhomVP1YRZ7Jep+BksLMLWQwVRbddiwu8o37KuAlilrk5sL84xnmzihwbhdJ685dCOLtm9xy8A8P739ASatKjeUVMqOISJMLWR3fl21dUp3WXXyHC4uqiIDwuftgycophzKZod1N69M6Omm6vTu5fnQzEMUTJes4bI9ta7aCMUpKONplTzfCVJsehkymsebBk5ze+4C3cDkcG4RP9L59PwhnqhN8+j6DJqQFMwey26RE91xle/YKvOVlT10wxTDZpMPzTxEOjbR7ius4kudI40pan6WQxWV37mnuE7F6vLenccpmC6T6RrjdoP9+WU+e+4ga16e5W6BFaeIIUJKZo/T1SGc0CRjeDxwaQefPHGYhV6Jnm9xujXCWi/H9lKVS60SK06Rgumy4efJ6D6jVp2mb7Phq+LqphZxMPeChatePF5nPr7rNqqzsn9ITv36X+dtk2eY7VQ4vjLKrRPzHMovcqQxzcH8EhldDbBA6mx6GSKpsT2zwReX9nPH0BznWkOUUsq8NZWu9U19phay4hbYlVlj0R2g6qnSRBtOlpsHFjjbHlY93zLrZHQXU4QseyUA6n6anOGhEfHnS3vYM7DeNyuB6sBctBxG0kqSnLRr/Mn5m5ks1bm7MsvRxiQrHaW5jNgtQikU80HDDQ3OtIYYj9MsvMhg0q5R1Hv4UuejF2/l3ZMnaAaqT9h8d4CM4fL48jTjxQblVJe84TLXGWCjm2U42+bG0iKB1BmIg0K+vLSP7cUqw6kWVT/DA0f38LZbjjNtV/nq2m7Gs82+7262XaGcUia0stlh2GqS0TwuuRV0Ii50B/s5fWuOCsKZbZS5e2QWgE8eu4mfuPnh/ju1NZ8Vt0iI6FdmSWkBbmSwzd7k8eYMTmhSsVTKyflWBUsPGbbbjNkNTBGy7uXYm1nlwdpO9uRWeXhzmyo75qTZU1wnpQU0A5uRVJNhq8kfzt6OLiLG800OFZQGsJV0XPczaCJiR3qDzy0fxNRDBu1Ov1C5E5psz6q0AFea1P00DS/NifURpgdq7MmvqYk81aAZKnPkVEolyC+6AwwYXY42J/m+oSPMuYMUjS7zbgUN1bF8zcvHPsg2Od1h2StRNLrYwievO5zpjdIOU/hSZ9RqUgsy5HSXI/XJuFanzpuGzrHkFtmVWaMbpuhGFqtuniDSSes+37i0kzdOn+dsc5Cy3eP4yii3T1ziXGOQ6XwdW/eZtGucaI2RM1xuLMxT87M8XpuOy8CFPLU6wc/u/hZneyN0whR7MquECE60xrkhv8iyV6QTpDC0kF5oMmnXGTEbdKMUGU19P0+0thEhWOwW+62yZnI11p0c5VSHitVl3c2xM7OOLiJW3CIVq83ZzjBZ3eOb8zv4hQNfY8PPo4uIDT/HQ6vbuXP4Iku9EgNWl4LpMNcpc0tpjhOtcfKmQ0oLWHEKzGSqPLIxw3C6w4DVIZA6lhYwYHTJ6B5zvQoRgnUnx978Ko9tTjOZVU1xQVWSMkTEkdUJ3jlziqZvc75VYTTT4mKzTM5SOX8qmtunHVjcXZ7l0/OHMPSor/kfq49TSvX4w7t++yWNsswOTskD7/+/r7r98d/9u0lU5/cCdBHhegZpzWNfboW9w2vMtQb4s9V9DKdaPFab4WhzCp2IUatOTve41C7hRzplu0vF7DCWabLUUfb6jO5xsVfh4c1tLDklAqlztDlF1cuy4ajovyDSON/Zau9iUguUNFrSu5SNDiOxxjFq1Vn3ctw6tMDe3CrdyKJgOqx1c9wxeAlDi8gbDrOtMktOibdNn6ZguhxvjmNpIYPpDu1Y2gU43xnifFsFqhworpDTPZ5cn6IXmtT8DMtekTW/wG3D85xqj/L1xZ0sxj31nNDkh3c81Wd6KS3gB0af4vDgklqnOyw7BZ5uTpLRPcZyKry76mc4kFvmHbc8gx/p+FLnUGmFvOGw6hT67WDqrprsjzfGeKy+nTW/gE7EpV6ZExsjzHcHWOgUMeLoQylVTuFSr8Tde87zaHWGTT/Lpy8dYt4ZYMUpsOnmKMUBNSrMP8KRBkWzx7itGqYudoscHljqN1Xtxf7R8VSDapAlZzosOAP9snJCSM63KlzslBmKC3zbwueu0YvcOqw6b59ojbHqFniqNslct8Jyr8CqU6ARpBnJtFnvKKl8K9VjwOoqszfQDU3GUg2KVo9bRhdUN/HA5kR9lE0/y6hVp2K28KXOhd4Ql7plNv0sQ6kWJ3vjuJGhgi/O3MBct8KSUyKj++xJr5DSfB5rblNpCn4eR5qs+kVCNKbsat9c1gmUqc/SQ2Y3KoxnFDNc7hVxI5NNP8vZ9jBnG0Ok9ICs4TJabHKsOsZmJ0tG99g+uEnJ7GEbPrONMiu9PI9WZ6g5abzI4ExnlFWvwHimwUS6wVCqzV1jczzS2KES7X2bx+rbON8dxtBCLjoVLnZUkNEXTh2g6mZ5ujHBE60ZnmjMcMmt8KerNzFktZQPs7ikAoMijVAK5puqo4chQjacLO0wxeP1Gap+hpSm0pPG7Tr3TV3oM72Pz93EdKrK3SOzfObMISYzNTqhRU53VB/D7hB5U+WJmiJkJlNlxFRVVcbTdQBWe3l0JBd7FRpBmnU3hxsaeJHOupdjW76q8jYzNRbaRUbtJlU3w4GhVXK6Q4SgYLlMpWvcPXyRfYVV7ijPATCZUW3FakGG+pEh9g2scsfgJZqBzS0D8+zNrr4sc2ai8V0HGD1Yln/9j+5j08sxZLVYin19U3aNr63v5q7KRRacEiWzx3SqykVHmdxm0pv82eo+7qpcZNBUtRy7kcWKW+Rip8yg3WbDyfG2oZP4UudYa5I92VXOdEYwtZAbcgvkNYe83uPB1m7eX3qKzzVuIpSC23OzzLpDDBotTnTHmbKr5DWHapjFFCFTZpWVoMio0aATpZh1h9BFREbzONkZZXt6k0tOmU5g9SfYO/KzlPQO1TDHo80dLPcKjKRbjFhNTC0kpfnU/Cx70ivUwwzdMMUlp8zOjAo0acQVZNK6j4bkrsJ5fnf+bvYV1zjTGMLUQ35o7Emeak8znmqQ1x0aYRoNyRN15XMasVu0ghT7cys8UZ/mzZUz5PUe60GejOZRC7LcnJnDkzp/uHIXQ6k2i90iXqQzmm4RSI1Bq8OFdoV7KhfohhYPb25jPNOkbKl2ThGC4VSLotHjZGuM/fll/Ejn62u7mMnXOF8fZHdpnbTuM27XOd0e4a3lk4wYDR5o7+HW7CwPtnYzbDWp+VnmuqqaR9HsUbY6HG+MkTF8pjI11t0cgdR4b+VpZt0hTKEm6OVekW3ZTZZ6JaYyNZq+TSe0KJtdzrUH2ZXb4ERjhHePHgegEWT6pb/aYYp1J8+Q3WLUanK0OcnO7DpPVKdoOjbvmDjFidYYTS/FO0dOEiL44vIBhJAM2l3qns2h0nK/XNYN5SXOtwaZzNYZSbWY7QyyPbtBLzTphClWe3kGbTV+ndDk/YNHeai5i3G7xpHGdD8/MW86fb/r8c44fqT3y9ntzq5xvDlOJaXOUzJ7DJotSnqXTpTiwdouvLgx7+HCAvNOuZ/orgnJoNnCFCG+1HmyOUPVzfC+4afZCPKkNB83Mvniyn6mcnXqrnIvjKYaDBothowm836Fk50x0rqPLiSzHeWPbAbpfsTpoKl8lWWjjS916mGGPzh/B2+eOMe51hCGFpExPDacLPcNnqdstDnbG2EiVe9ryV9d3c33jR+jqHfpRilW/QKLvVJ/LknrPoYWktGVJjaeavQFkU+dvoHhgRZ/afIo846qf3quNcRUthZHQDf6z+BEa5yja+MM5dqUUz26gYmlh5Ssbr/RcMbwsbSAmwvzfH1jd7+E2WKngCYkaUPVr/3TN/zmS6vxVabkofdeXeN79A+uL43vumV8lf1D8qc/+maKRo9D6QU+W72RmfQma16eG7PzVMNsfzC+oXSWEFWzcsErM2i2ONqcYl9uhRPtMVUns7jE+c4Qi60i75o4QUZTAzKnO3yztptIauRNh7Tmc2PuEk5k8uWNA/zAyJPMukP4kc6qV2DEatIM0uzPLrHh56kFGXbaa1x0hzBEyMnmKDeX5umGFmNWg98+cw8/vvtRzneH2Zdd5str+1W1EavV/3BVn7+Im3OXONUbY83N9yMFH1jZwRvHzlPQ1aSlPvoaa16BlBZwqaek9tW2SlC/Z0yFge/MrLHiFsnpLt3IQheSSjyRgaqioROx6hf762Z7FWbSVdqhzYDRwZc6j1S38f6Rp6nobfJ6j1BqzHmDPNLYwW3Fi+Q1h1Zkc9EZZKlXYld2jROtMQ7kl/GlzrKjBJbpdFVpnGYdR5rK/9Ka4vbCRSIp8KXBRUcV8h22miw5A+zNLHPRHWLCqvF0e4K7CheU4BFrVm5kcr6j8gojKdiR2cCVJjvsNZ5szZDVXYatFifaY7T9FDeX5snpDmc6o5StDo9tTuMEJvePnuFQeoFWZFMPM8z1BtGE8uXeVryITsTT7SneWz7KCWecj5y9g5/d+y3aoc2p9ig/PvwgGpKVoEhWcwnReKS9iztz52iFaT67cZjpTJWi0WPNy9PybcpWh4lUnQu9QUZTTSatKq0wzYy1zpI/0P8Olr0S06lNulFKBcEYDue7wzS8NG8qn8aXBstekW+s7GIk2+L+wVP88fyt7B9Y7TPPqptlW3azXxrNCw1mslU+dvQWhocb3D0yi6lFaET9COatgtiNIM1sZ7DP8Gd7FW4vXATgoqP8x6tunvFUg3aY6r8/PzKYtJSP9LMbh9mdW6NsdFh0S/hSp+XbXGhWuKG8xK7MGk81p7m3dI6n25O8pXiKj63dxk3FeRpBmm32Bu1Q+cmagc1t+Yucc0YA5Xr4+qVd/NTeh3miMcNwqkXdTzOdrvZr/EYIGl6at1VOsOyXGDA6rHkFLnQHyRoe29MbtEKbo/UJNrtZ7h6ZZcDssuAMcENugccb20jrPsdro0zna8xkqjxVm+SO8hznOkPcVbrAsldizKqz5hUYtppcdAbJaB6uNJntVHhj+Qw6EV9cP8jh4uJLXrIsV5mSh959dcb3yP+8vhjfdRvVKVC9qx5c305mwuN8q0LDTzNgdfiTlVuZyaqKJBGCr1T389TSBNsHN5nJ1pjrlimavX7gxi2leS50Bxm3G9xWuoiO5Ex3hGm7Siu0GbRUr7lpu8r57lC/TNabK2dohTY1P8PFTkX11EpJbs7NseyXAJV2YYqQCatGSvM5qw3jRCaDZptlr8gtowt8aWU/pZSDn1ENXnuhCgXXRMSI2ez38NubWWXYUuXRVt0CC50iByvLqqN5pkozVCHsF3pDyuylhWQNl0gWeO+UyrWbTm3yyZUb2ZNZZW9mhVqQxZUmR2vjGFpErZfhjaPnAHhsc5qbyov9otuWFvCRE7ezd3SNjOEzajcxRMTHl27m1rJK2B63a9gi4E0Dp/nk6k3cPjCnfC5uTvXoi7XsWpAho/t0Qwsv1BmzdTb8HE5k8nhtmncNH1cpK7FvLJIaKS2g6mdpBTbL3QLjdo12YPG/lm/jjWPnWfDKnG8PkSl4fGz2JtWGyW7wVG2yX+N0wOrSCNPckFtg3q0oE25+kSVngPOdIUpmjyMbE8wUagyn28y3lV+tHmYo6V1Swqec66CLiJO9cXyp88cLtzKdrzHvlan5WQ4MKfP2XK9CSg/YDPPktR4Vo80JZ4JTnTEeWtzG1F4VYKUhGbMahAgeWZ3B0kN2FWHDy3Fz4RJzvUEGjRafXDrMHYNzfG15N++ZPM721Dqh1VSMIlRly+adsqpAwzAhGl/Z2Mv9g6d5+/gplt0iy16J2wYvMWCqupMrToH7KmcB+M2n3sT79x9joacY6/9xywO0wxRz3QozmU3WvRxeZLDqFGJzccTpxjC7CxtsujnWHdUn8oIzzKhVp+6rtjsA616emfQmTmRyqj3GpF3j0+s38sbyWXbn1sjrqrpQwXBY93IYWsiu4gZTdo1jrUmans03a7upuhlm0kqYaYU27TCFG5ls+DmWnSIH8iowJKN5zKQ2OMMob5k5S0rz2ZVdi324Ee0wxVovzz2VC6x5ebJplyGjyapfpB3aNIM0QaTz1PoE2VGXKbvKGyrnoaKEwjW/QFZ3yWouad3nm/M7uHdqFjc0ON4Y44bSMnndYTjVQidivqdqgWZ0nzVPpVfstNdY8Mq8pXyKcbNGiMag3eab6ztfnknzOlWCngvXrcaX3zsqf+J/vY2JVJ0jjSneVD7N2d4Iw5aS9rcK3/qRTs5wGDfrHO9O4EYGJxqjDNpxxYrYtKaqUmi4kcGQpZLNfalzujvKgcwS1SDH8dY4xTh1YKe9xgP1Xdw3cJbT3VF2pNc51x3h3QNHqWgdnnC20Q5tQgR6zCgHjRarQYEVt8g2e5PT3RECqbMvu8yQ0eKR1g6CSOdwbp5HGjtU3z8t4K7SBWzhs+oX2Z9eZMGrkNKUKasRZph3BjiUXaQbpWgEaVa9ArfnZzFFyDcbuxlPNdhur1MNcoyZNT6zcRO27rMvt8xHL9zK3WMXyRkeB9KLLPslUprPhp+n7qdxI4NdmXXOdEZ4cmWSXz7wBf732i0cLCyp+4k1QlvzuehUWOyW6AYmJcvBCQ0OFxd5vDbNHeU5FbzhlHlic4rbBy/1W7oczCzSiVKc647Qi0z2ZFY51ppgZ3adp+pTGFrU9xGGcdDLTHqTXalVdCI6UQpLhKwHeZ5uT1G2OmQ0j9leBT0ORIkQDFptvr6yi+l8nVFb5bY9Ut3Gnvwaad3nbHuYcbvBkqN8kk5o8FdGH+Gp7gyPbMzwg+NP8dm1GyiYLntyq3xq7hAf2vkIi94A890BdmXXaIcpTjRGGU23yBpKiNmTXcWJTNphCl1I3LjreEoLmO+WmMqoJPiWbzORrveDT5q+zeHiIr3IYtXJM5hqM2Co1k8A3VBFDQ7ZbQwRsiO9gS91Hq/PkDNcHprbxt0zqjj7u4ef4X8v38T2fJWS2WO3vUI3SlE22tTDDMteiYPpBRb8cj8KNpQaGd3tWw+2NLd1L0/Ny/SLR5zvDnNP4RyPt7dxS26Oepih5iuBKqc7fXN73nAoGA7TKRW9fLo7ytuKx3nGmcQWQayxpUnrHuc7Q+zLrTBgdtjw88x2BhlP13Ejg5P1EXKmx+HiIk/Wp9ie22S5V+TugQsMGi26kcWIqb7nJX+AQaNJK0pz0RmkaKgiDhedCrvTqzTCDGtenic2p7i1Ms+F9iATmTrjqQZfWd3DfcPnGTEbPN2ewo0M9mRXebi6nR25DTphiqc3xrlt+BLrTp7t2Q1SWsDTjQn25lf5xsoubhpcIJA6x6ujvHP8JP/rzK3cMzXLeKrBpp9luVfkzZUznOyMoYmIxW6JY7MTzP3kL7+0Gl95St7wzr991e0Pf/TvvejrCSFuBx4GPiil/Fi87l3AfwB04LellL92DedpSylzQohtwEngNCr1sAP8lJTy9IuhC65jxjdxsCT/3sfuYEdqjYxw+VprP6YW4kc6RaPHoNFiwSsrc5pb5L7iGWbdIRpBmqVeiQ8MPcWTnW2cbQ3x42MPccYZwxSq2emF3hADRpdNP8uUXWPRLWGKkBuz88y6Q+xPL+FEKprrVG+Mg5nFvv9hzSuwzd7gzzf3c/fAeWq+cshXzA61IMNTm5N8YPxpJq1NIqkxZDT539XbyBou870BBi1VVaUZ2BQMh7yuQsszmseF3iA70ht0I1URo+ZnmLKrPFTbyc7sOm5ksCO9ji91MprHml9gzKzTCDNkNJdlT5mR9qWX6UYWvlR+jA0/x0J3gFtKc5zvDrM9vcEee5lZd5gxs8aH5+/lvWPP9M85bW3ycHMnpxrD/cnirvIFMppHI8iw5BZ598AxOlGKL1YPcUthjscb2yiZPXZlVrGFz1PtaQKps9gtcktpnou9CmndJ5Sif/9brWcsLWBbrHHMpDcZMlo80NjFfcWzVMMsGc3jSGuacbuOKULOdEY4mFtixtpAExEnexMATFpV/mj5Nj449jhZzeWZ3iSTVpXPrB2m5qZ50/A5JlI1Nvw8I2aDZb/EmpfnltwcZ3qjmCJkX3qJBb+MjqQRpMkZDkca08xk1GQ+ndrkSGuaVSfPD4w8yZHONMNWk0mzSoRGNciR0nwuuRWKRpdnWhNsS29yoTtI1c1w88ACpghZdVWfupuK84yYDT67fpgfHnkcUwT40uCh5i7uyJ/HlSbnnBFsTWnPw7EGaAtVRPlkZ4yZ9CZPNyfZk1tl0qr2v4utdlyRFKw4RfbkVvtM9kB+ifPdYVq+Tdu32OxleePoOap+FjcuPZfSAspWh6+v7GJPSUXM7smuMNcbxJcaM+lN7syc58+bB1WN2zDFmpvnTHWI759+GoBdqVU2wxwHU4uc9UZY8gZY8Qp4kUFWd5lI1QE40x1h081yb/kcNV+5MRadEjcXLgHQDm1yukNZ7/BUe4Zn6qO8Y/QkGc3rp2ec7o5RMrsUjS4XekPcnT/HsNHEFCGONLGFzwVvmPUgz7hZV9ppb4yi0WPa2uRoZ4pIapTMLgtOie3pzf784oYGWUP5PgcMVZszpyttdzq1yYJXph2m6AQpzjSGuGNwjkWnxGK7yI3lRd5ZOkY9zPL5zRvwIoM/vuf/e8kZ3+G3/+2rbn/oj18c4xNC6MCXAQf4sJTyY/G6M8DbUQ3GHwN+VEp54gXOdSXj+4yU8lC8/v8E7pFS/uTzHf9cuG5NnSEai94AI2aDzUj5NhpBhrzusOYXWPZUxfUhq03DS7PqF3Eikyc2p9hTXEcnYltqnZzusB4U+PCxe/gnt36GOXeQlBYwaCpnekrzuS13kSGjiSUCTvQmqAZZQjSWvRJn28O0wxQHMkssugNsszfQididUzl2JbvLsc4k41aNEbOBPigJUT4rnYgL3jBvLJ4ikhp1P81oqsGnFg5zY2WRc50hZjJV9qeXONMbJYhLhJ3tDHMov0jVy3JDdoHbShc51R7DCU1yukszSBPGZaOWfZUwflvmAjtSa5x2xlWRZRH2Q8r/bHUvbxo+x1yvwqDVJqN5faaY1VzuGZylEWToihSz3UHaoa3MsOk2a26edw6pYI9v1naTNTzyhkMztLE1n52ZdUYNlX6hiQhf6kyZm9yWv8iqX+RgdomTHZXqMWi1lfkOjQfquxiy66R1j93pVYaMFnUro7QUvc1IqsWHL93DgZLqCrArs6YCfQKVetKNLL5QO8SkXecLC/u5a2QOW/OZydZYDZSpadKqMmQ0uam0wJn2CNvtdcq6eu/PdCY51x7k+0eOUNbbZHTVKaOgO4xTRyPq+xEP5pdY9/L0IrMf5Xm4uPhtwRkLfhmAx+vbeGP5DCNmkw0/x6OXZtgYzvKB0aM0wjSP17cxYjfJGi4ls0tG8zjnjFAwHZ7uTlE2OrRCmwttFax1ODdP0ejSDVPM9wbohRZp3SOje6Q0n6zhMtsbJGOo0myrfpFVt0ArSDGTqZLXHTZ8ZYZedZVmFyFwI5N92WVKepdTvXGMUsh0apMbMvPMusMca04wna9yrjNExvRI6x5vKZ6KzYg2Gc1j0S1xVh/t+yAHzRZuZPADM0dUw1zN4xPrt1I0e0yZm4wYqhvEZxYO8dd3fINLXqUv9OUNh5ZvsxKnDR1vjMa5lTbd0GK+N8Cu7Hp/fjg8sEQ3THHAXqKkdalHGRqhipKOpMbja9P8aPlhbC2gHqYJpcaU2cIWPit6kYre4aI/yA2ZBSIEjjSpmB3WvTx53eHW/Nzld9Ed5I7irOqQ0ZymYnZ4dH2G2wbneWx9msMVZX51IwMzjjA2RciN+QUm7DpjVoOS1qWkdTG0kLn2ZR/uS4mXOHrzF4CPA7dfse4O4JyU8gKAEOKjwAeAb2N8cSPyP0Txpy88zzUKQO07Ie661fiGD1TkL3/8Vs72hpnvDHD/4GlW/UJfik1pAccbY7xv+Gmeak+zP7vcz5FadQvcXphlwSujo5JxQ6lxrjNE0ewxZLXZ9LO8oXCWr9X3cW/xLJ0oRUnv8pX6fm7Jz/W1py1fQj3MYIqQkt6lFar2RVnN5c/rByhbHaZTm4wadQB8aeBJlbjsS4N/+cy7+dCeR3AiFdShi4hGkGbQbFMLVNucbal1zjvDZDSPU+1Rtmc3MWIfpRsZ1P0MB3NLPNWc4q7SBWpBlnZoc7wxiqWFTGRUpYtICnKGw5nOCE5osj+30s93BJVLV/MzuJHBYrdEw7PZnq+y4aiu7/O9AfZmVznfHaLupRlLN/pNgC91B5QJKEgRIRixmhypT2IbgWqDJCRuZKjIxCBF3Uszla3RCVIMpdo04zJmoHyjupB8/Bt3sOfwPAXTZb5V4s7hi3TCFIOWKg1VNHqcaI8xZjcJpeDNhVOsB3laYZqLToWlXolKqk0kNVpBigFL1cvM6S7nOkPsyGzwpcV9dFyLcq7LPUOz/WT3E41ReoHJ/HKZN+89QzfORduW3uwH4jza2k4vtHhP+WkueEPMdoeYSW8SSo0HNneoGppmj/OtQW4oLXOyMcL+4irH6mPMZGv93oE1L8NCu8ibRs+R1x2ebk5i6z5lq8OY1aAV2nxq7hDfN/MMp1qj7Muv8HRjgoyhgrCc0ORQYYlmYLPiFFX0YW2Q8XwTTUh25jb6ZdS2ujpkdI+M5jFm1ijpXZ5xJslrDmd7I31tZSJV40hrmvuKp3mys42d9hqtyO73r+sGFgcLS8z1ytxXPNsPZKp6WcpWR3Us9zOsdPM0HZsfnnmK7am1foCOTkRedwilRlZzqYcZykabapDjK9X93FS8xJDR4mh7ms+f288/v+XTLPklLvSGGLZaLDgD9EKTtK4KWjiBqlu72s5z2/A8hhZSMVVifE53+++2aHSp+Vku9cqk9IDZVplBWzGeSAqWOwXeOabm6xW3SC+0uCl/iSOtaQwtVDU5RcRgqq3M0oFN3VMts7aihx9en8GM8/YOFpeZ7Qxye+kiZ7ojtHwbW/c5sTnCocFlqm6W6UyNIavFJ+Zu5Oj7/uVLq/ENTMkb3/q3rrr9wY//4hywccWq35JS/tZz7SuEmEAxrvuB30FpaR8TQvwQ8C4p5c/E+/0EcKeU8uefdfyngI9JKX9fCPFzwP/7HKbOPJCJj7/0Yu/3umV8EwdL8s0f/mGans0PjT7Bfzz3Fn56x4Os+QWWnBI35S+x7JXYnlqnFdn89pl7OTS8zK3FOR6q7eQdleO0IpvdqVW+WD9EJ0jxzvIznHNG+iH9Rb1HSvP7H2de67EaFOlEKb5V3c3tpYv9j/TzKwf40NRDzLpD3JqZZT0o8Hh7G8u9Iu8fOkpJ77AeFHiwsYtbCnMMGS3OOSM0wzR35s6x5A/QDm3WvDyjqQZlvcOsO8R0apN2qEoYHW1NMpWusctepRqoHKT/8Nj9/NhNj7LgDDBmK4l5w8txV+E8T7ZnGLZahFKjF6lOAU9Up3jPyHFMEVANVPHu461xpjI1CnqPWpDhnvxZVv0itub3/WNf3jzIpVaJe0dm+8nuvtT503OH+RsHvklGc1n1i5zvDgFwZG2cW0YW+tF8o6kGQ4ZK2t8SEmpBFj/SWXKLfOviTv7ZzZ/mSGe6z1R0EXGmN8pEqsaX1g5wQ2mJVTfPm0unqQY5Hqzt5IbCIhGCmp/BlzrvLj1NPcyw4Jf52NzNvH3iNPvTS3QiFQRxsjPGTww+wHxQwYlUi6GHmztxQ4M7ixdwpElG8zjdHWXDy/HeytN8sXqoz4C+vLaPmVyNx1ameN/0cU61R/FCnZ8a/xZDeouz3iimCFj2B1jzCyp3LzLYay8z75f5zNIN3Dd8nl5kkdY8DqUXMEXAv73wjn6nkJ25DVadPDuz6zSCdD8IYsPLcXR9nEODqut7N7I40RhluVngp3c/yMcXb+aOwUt0Q5Mpu0o3VHl9m36WXmj1v52S2WXRKQH0ixFMpOrUgiy5mAltaZFPNabYmdtg3c2pyjGRznKvQM50mW+XmMnXOFUd5tahBQqm08891YVKndkyXT5TG+NHJh/nv525j/fMnGDZKbI9o/pDRlKw7uU52xzkvWPPcLw9zky6yqaXI0RwS26OY51JBswuTqTez4KjGKcvNfZnV1QEd3uMu4vnuegOkdMdVtwCO9IbrPkFjjdGecvgGRbdEtvsTS65ZR5a3c4PTT/J8fY4Q1abZmBTMVWxb1/qfGNjFyXLIZAa3z/0JOfdEYq6el63pC9y3htWRbYjm0aghEU3MtCRpPSAitnifHeYstnBFCHNIE0zsBmzG2Q0L9aATcbNGhe8IWwRsOgNsC+9xF/b+62XnPHddP/VGd8Dn/jFa76eEOJPgH8rpXxYCPG7XGZ8Pwy881mM7w4p5S886/hNYFRK6QshCsDSVUydH0T5+N71Yu/3uk1g14TkQkPVRzzWneINoyoAZNhUZqIho8mJ1hiONDnenuBn9jzAobwyRxZMNbBnrA1W/CJz7TJlS4XnD5otJi0lsW+hpHdZ8Mp9H82aV+DYyhit0GbWGeJcd5jbK5c454xwOH2JCI2d1hpTdpWduQ1akU0nSrHsl7i9MEs7tDnjjLLu5VWyq9QYMlrsSq1yY3aeGWuzn3ZR0VXVjm5kcUdxlkGzxbhZY8yssdde4pfv/DzTqU1uys+T1524G4DLV2v7SMUdxMtGh4Leo2h0Gc+orhIbQR5bU4nPbd+iHVj9hPz1QJUs25LCM5rH/eWTfGjmIW7MzDFtbVA0emyzN3jb9tMMGk3OO8Ns+krK9yKdW0YWKMWT6u70KrtSqqC1hqSsdyjpqsno11Z3sz29yZu2n+trvGc7w2wEeapBjoyuNJqJTIMRs8nB3BL1MMMlt8z2rCoj5keq2sqmm+Prrf3MusOcao9xz8hFHlxXle59qbPoDTBp17jgD/N0dwpTBLRClYCfj3sW6khGjToTqTr3ls4xYdT4meGvM2Y1cCKT7TkVgv/u6ZPUAqVh5EyXZ3pTXPCHOdqZwhIqB82PNGp+lvPdIea8QXQkxZTDw5vb6IYmX1jYz2lnjJWgxJ7SGtOZGrtza8x1yozYLcbMOg+tbmfZK3GyOcozm2PsKauuFhd7SpsdzzQoZ7qc645wx+AljtWVr/pEa5y6n+GR6jYeWt1OK0jhRsoPZYqQe0vneMvAKb61uIOK2UETEbdkL7LHVhaAdmhjagG3lea4J3eGII6qLZgON5UWVB3V9RKRFNw+fEmZpO0VtscdxC0tYMkb4HRnhIrZ4caBJbqRxd6KcjMArLgF/nT2MK402ZNd4fCAqpxzU34eDdn3WddjE+XZzjBuZPB7x++k5mVI66q26LnuMGtenqqb4aHGTlLCZ83LY4qI4+1xKmaLO8sXyekOu9OrnO0NM2B0ec/Ecf6/Z+5j0q6zzVYRpEroqjHbG2SllafppyiYSuDd8usDPNbbjimC2IphMtsZZKe9xu70Gjfn5khrHt1Q1fAcMDvkDNWFYyilXAnjVk1Vp7HWKekdxs06Kc2noPf66UMvJbaKVH8nCexCiJ8TQhyJl3HgNuCjQoiLwA8BvymE+H6UX2/qikMngavVX7sWjexTwBuvYb+/SPP1qvGNHCjLf/+p3TiRSTXMMmNt0I1U+aa85uBJnd9fvJufmfwWS/4Aeb1HJ0qhE2FrPkW9yzZzE4uQxbDIv77wLv7y5BN9E+bB9ALn3RGGTeXb+2Z9Dx8ceoTP1G7iJysPYIuAtTBHSe+xHubwpYETmcrMFikfx7uyJ+hIg80wywl3glvsi9SjDLbwqegddCQeOkedKTpRirzmUImj7L5UPYghIj449AgmIbqI2AxztMI0tubzreZu7s6f4zMbN/Evpz7FemhTjzJUtA5DusNikOWR3k4aQYY7suf58PJ9/MTogwDkNYd6lGHaqNKMbLoyRSgF60GBcbNGPczw+4t3c+/gBRacAc41BvnRycf4rQtv4Od2fp1WZNMObd6Rf4ZuZFGPMnSiFE5k0opsolhoWPUL7LJXqYcZ9qaWGTVUqydP6pxwJxg1GtTDDM90JjmUXSCjuURoPNTcyeHcAlPmJt9s7SWnu4yYKlG4GmbJaw6jZoNRXWm4mpCcckdZDYrssNZoRSoFwhQhTmRiaz6mCJRZW4SsBkVGjAbfbO3lYGYRW/h905sjDSbNKgXdwYlMPKljiZCnujO8o3CMj1Vv530DR6hoHR7rbWfEVDTMeYPKDxlm+jTYwuOcO0rZaLPqFxk0WuxOrbDoD1DSuzjS5FMbN7Mts8mYVedIS5nkt0LuF90B7smfpRrkONUbY8xqMGMpa5QKwKjhSEv5lK1VnnRm+PPqfm4tzjFlVvnI8l0YWsRbKyeZsTZ4ujfNmFmnpHewNZ9OlKIbm/A3gxzbrHVaUZrNIMdT7RnePXCUVpjmnDvCx+du4ud3fY2S3uHRzk7VsSC1SV53WPJLHLCX0GKfdVlv40qTUGrMukPcnJnDFIH6/oTEiUxGzTq28ClpPU55Y6oFlt4lkhrnXCVAPtzeRTtMsc3e5Jb0RUb1NouhqlxT0ZQWdcSZVsXJUys83N5FSgu4I3seXUT40mAxfq/Z2CLhS51aoCrpRFIjo7l8vbqX20sXWfaKDJptQqnRDNMcSC9yrDvJTnuNA/YijjQxCVkPC3y5dqAf7Xx7YZZVv8jFboUxu0FOd6kFGW7KXqIa5Hi8OcM7ysf5s+oBDE3V9/z60i5+cOYIodTI6w4P13dwf/kkt6TneLC7i7+9/89fUo0vX5qUN7356hrftz7597+j6z1L4zNQwS1vBRZRwS1/RUp5/FnHfAr4YynlR4QQfwP4N1fR+N4O/Dsp5Q0vmq7rlfFNHSrKJ7+U4xOtXdyenu2nDABktJA/btzC9xWOsBQUGNWViW1ED2lEMKhr2ELnK70i99hVujLEkSpE3JeCkiY55pWY9yt8IHeB9RAmdZ2FMKQjTephmtPuGHdmLqAT8XBvJ3oc7HB7epaM5jMflLjgDnPAXmRI71CNpdaS1sMWISthjhmjRVbTeNipUNAcNCKymscxd5J70hdZD222GQ6bkcaULpgLwBQROpKVMNdPsq+GGcq66tBui4BxPeC3ardxZ1bl45X1LvUwTVZz8aVBWe/y9c4e3pQ9Qz20idDoSIv1oMANqQW+0tnPDfY8X20d4NbsLAWtx7xfYcbcwBIha2GePeYal4IBLBFgi4CPVW/n5twcFaONKQJKWpfFQE06w3oLT+pMGE0WgwJdmeLO1Bpf701wX3qR416RUaPFephlSO+wEuQ57Y7xgfxJ5oM0R5wZbrLnGNIdqnFR8l2mz0ea+7g9fYF6lGE9KDDnDjJpVdmXWmI9LLDiF/u9D29JX6QZJ6Dfl55jPUpx1hvhW83d3JKb44bUAt/s7uH+7EmycUTkWphhyujwpDvKSWeCnyo9ST0SmELymdYhLvSG2JVZ5a70ef6wehc/XnmIUd2lGwkmDZP10KMRGdgiJK/BgJaiEbl80xnjsLVMRpM4UpAXsBrqDOkhGtCSUI8sdhgBSyF0I5O9ZsDXnQoZ4TKst+lIE1sEbIZZCppDiOCIM8MNqXmymsdKWKAeZslrPYb1FithkQPWGhf8Eo60GNKbHHFmmDI3qehqsv9k41ae2JzkF2a+wrxf4V3ZE2xGSqACmNAb5LWAi0GBzzVu4pbsRdaDPKNGg5tSi4QIbBFxzBthyqgyH5RphjZ3pS/x5c5ebk/P8vnmYe7MniMjPIb1LoO6EpIakbr3B51pbOHhSIvd1ioXvCHGjRotaTOhN1gLVRFsW1Pj7lPNmziUXuBGa5VGZNCRJiXNJSMiTvgVnulNsSu1QjXMcbw7wX3505x0Jhg0WtyenmVUD8gIna4MaUVwMShxzJlid2qV35x/M/9w5nMA3Gj1WAojJnWdtgzQgLxmshD4aALO+mVG9SZDuk8r0tCRLIZ5Pl2/mVuyF/t1SW+yFzjmTnB/ep65IEVJcynrgouByWFT4xtOijtTHYoT8y8547v5jVdnfN/89HfP+OLf7wF+A5XO8GEp5a8+xzFXBrd8HPhHV0ln8ICfl1I+8mLpum6jOnOaQz3Kck/mPEtBgbWgwB5rlcWgxKjR4C055ZjeYdaJJKSExBQ6k4ZONfKYCzRs4fPJ9rY4yERnh7lGV1pgNMgIj1BqfLq9ndvTF6lGPmf9ETyp87G12zmYX+LfLb2DW4tzcUBLmlVfmQjvzFxgM1Ba4KfrN3NDZoFRs04o1TW/2d3NHy/eyl+b/ib6VrfnMENWc1kJNfJaj/kgrwJqNJe//Phf43/e+jv4UqcjBaHUYkl5lAveUL802ZjV4JOLh/lLk0eoBRmOOaqNzJDRoqh3mfMHyWsOa2EeTUj+rH2Aot6lFdmU9C6rflGZFzWPLzQOc1fufF+TKerd/oRTkD02owwXvOF+M9rPnDxEe4/Fm0unyWs9FqMBnu5Osz+9xFqYpxFmOO2OUTY6qi1MaFDW22xGGqNGi5VYUy5pPVaCIv97+SZGzAa+NGiEaR7p7uKezFnqUZpT7jgdOc+iO0Akd+FIAzcyMUXIV2v76BYtnulMkNICdqdXOd0bRRMRG36eZbdIK0pzsjNOxWpT8zIc707w59X9vLV8kvP+EKN6g9PeGONmjdO+hSlCNvwcDzsjVPQOx90JdqVWGDdrzPtlPtW4mRWnyCPdHexNLRMhaMouWaHRjFL82sr9/PDQYwzpLU64u3mqPU0rn+5rXjoRec0hDAVDuo8tYEL3aEWSR3q7GDdrHPMcHu9sJ687FPUupgjJ6z1O9iaYtKp8duMwB/IqTaWsqwT7WXeISauqStlFKcpam4c6u7k3e4b1sKCq/Jg1Huzu5kb7EstOgW35Kkv+ADoRZ/xBdBH1tauONCGCvObypvxJSlqXKWNTRUZGKYbiJHSNiLPeCI40cSKTjzVvwo1MlswSu+xVPr55O4dz8/jS4GxvmDcUzpLVXGzhYQuPlaBEVlPBNTusdXypcbQ7TSV7kk/VbqFitVlyVHeR+wdO8lB7F820jSVClvwBJq3NvpC3PaW0b+VTa9OK0uxKreJJnfmgzCkvxahRZ96vsM3cYNEvc6w1SSQ13jp0mnqUoay1OealqEcZHnNydCIlfB1MLbIZltlmbpIXTl9gGtEFJjplvU09f5p/debdvH/qGW7OXCQrQvZZy9hC55vdPbw9e4KVULISFIAmw3qbh9z8yzJnipdBB5JSfuhZvz8HfO4FjpkF7r5i1a/F6y8C6ZeCrutW45s4WJLv/r3v5/a8isLzpUFGc9kI8tSCLFOpTRbdAc62h7mxuMCA0WHcrNEK0+hCmbzyWo/T7hjH2+PoQmJpAVN2lUhqfG7pID8980C/zuZQnBe4K7XCM70pltwic50yw3ab+wdO0olS2MKnGmaJpEZR77Lsq6LY06lNQjR0or4pcStvMKO7nOqM8c6BY3yjsY+3FE/gS4ML3hC/e+ou/ust/5MvNW/g1uws1SDHrDtERvMoGl1KepdzzghvyZ9gJSjF5rQmw4bqoB6i9UuItSKbQ/YCT3S3c3Nmjk6UYj3I0whUUEjZ6DBoNHmotYuGn+YtA6cIpUY3SjFiNvrn1oVkytikJVXAzeOdHey1l9U1Qpu35E/gS50/2byDD5Sf5Out/Yxa9X4EbFlvc7Q7w4RVoxGm+9GAQ0aTJX+gX64srznsTq0w71fYZy1zxFF1Q5XZMuScM8KbcqdoRjbDeou1ME+ERllr46Nz0RuiYrR5pjdJLchyQ2aeJb+Ejoz9qqJflODtleOcc0YYMZs0wjS3ZmZ5xpnEj4MV3pg/xUVviAWvzKVemZvy8xzvjPOegaOqSEBrL28unOSEM8EOa40L3jBTZrXv1z2cvsRJZ0L5jtxh7sye46I3RDXMMmS00JBsBMrf++nVw7xx8CyNIMO9uTN8ePk+fmTkURxpMmQ0OeuOciC1yMert5EzPOY6Zf7S8JP4Uo8Flyx53SGnO9jC79Njaz6jRp16mMWTOqtBkTvT5+lKi2POFGtegdOtEd5cOUNR73LeGWa7vc6MucFRZ7pfHaVo9Lgje54TzgRTZpWPrt7B+4eOMusOMWbVGTKatMI0eb2HLXymjRqLYZEHWnt4Y/4UZ93RfpWS9aCAJQIWvDLd0GI6tUkjzHCqPcqI3WK+O8BdpQs83pzhBwcf5+neNDdn5miGNo0ww0hs7n7S2UZJ71INcpzujvDGoir/tVXM+8b0HI93d/Dfn3wDe6dXeM+IMtHvSq3yWHsHRaOHE5k8WZviB0ef5MHmLt4zcJQL3jA6kozmctYZJSV8XGliiJAxq87p7ig6kneUjvGPT36AH5g5StHo8mhjOzfmlen+vDOshK/uKLvTq4RoPFjbxXi63i+11gpt3po/TjXM4UmdJzvb+I2b/+il1fiKk/KWe//mVbd/4/P/IClZ9mrgxWb8GyJkT2aVA6lFTntjFEWXVpTm6eYkb68c50Z7notmhfvyp3miu50oDtQ444zFfo4uq4GqWn8wt8SI0UAXsl/66d7hCzzc3Mnh3DzjZo1nelOMmA2G9BY3Zi6xP62zc2idzzRvwhQht6dn+XpnL3nNwdZ8nFgLG7aatCKbKbPKvF+mHmb4QvUGymaXgtEjQnBP4RzDeosfrTzEeligpDexNZ8P7XsYR5oUjS4TRo2nu9O8t3AES4T9XMC81lMTbmotToWQDOltOpHFNzr72G8vshHkcSKTepjh7qyqW/qV+k1sT29QNLp8bvUQbx8+iStN3ll6BoDNIMd6mOWduWfIioDBzCLVKMJEUtIMfHpUQ8lUsc5Zb4i99jIXvUHymosTGfzE4IP8Wesgm16GO3MqcGWPtUo9SnNL9iK2UB3f35o7TkXv0YosLBEwZTT4TOtwv3LIbmuFh3s7iaTGjek5vtXeyyWnzMHsZU0yq7kM6y2+2d3D7ekuF7xhWmGaapjlycY0bxg4RydKsTe1zBOd7Wz4Ofall/nkxk4+OP44S57q0Thm1TnWnOgX/t4Kf//45u28tXSCcqbd98WVTaWtPd7ZQS+0CKXG1zf2sHdimRGjoaJmwzKH05cY1ls4qTUOW8vstNaoRxlusi+xEhb7Cem6iJgyN5mYrOFJneGMyin7xcnP902So3qTjpnirDfKD5Yf59HuTm4fvsCUuckRZ4ZPLh7mnWMqafszKzfwnpHjTBsNdBHRitIM6W3qYRZfGrwzd5yVIM9KoISBPekV9qRXONUbp2uoQCe3N86UucmUWeWZ3iS3ZC9ytDtDJ0qxw1rjq40DvLlymqfaM9ycm+O8M0xFVyXpLBGyzawSScE2o0a28AxP9rZxyJ7ngjfMgldme2qdL24e4n2DR5h1hxkyWsxYGwwaLS65Fe4ZOKd8f6YSUM92hsnpDjPWBpZQgV/1KMPu1ApZ4anyX8VTbIY5Jczpbe7OnKUrLQ6lF/ixGx9Fi/tSNoIME9kapcIztCIlxL0xd4p5v8J9xTNc8IYZN+vMukOMmA3Smscue5XZOGL04foOvn/wqb5f+id3PEIjTKscV2S/5ujd+XOc6o1zT/4crchmzh3kh4YfQyeiHmYp622GjSbTRoNRo4UjDbKay2+8HHPs9akDPSe+JxhfnPH/X7gi418I8anny/gP0djwc8wHFRY8lRz8WHWGqWyNM71RPGlwya2ows2dYQwRoYmIx+szHCqYPNjchSFUjs8zrXGm0jX2pZfjMmVj3Ji7hGcbRFLw1cYB9maW6UbK3GGKAE/qlDWfstFmSG+SFT4z1garfpED5iLH3Ck23ByDZpsVP6/a64iQ471JxuwmdT8NARytjTOVq9MoZDjbG+bG7Dy25fFoewcAv7fyBu4bOIMvDc51hrgjm2E1KPZTEc51VW/AT67cyAfHH8cWPuthjmaUpqh3mfcrHEwvsOoXWfYH2Gmt8VhvB+8ZOMoTne0MGi325Nf7oe/f3NjDnuwqa55qmnvKG+v7XIZ0ZYqJCKhHJvUozXpQiDU1FcZ9yh3lUqz96UQMWW0+snw3bd/ibSOnONMZYVdmnVBqXHLKTNtV9trLdKIUrchmM8yzPw4kOOuNsi+1FDftdPnz5kEyusd8p8QNuQW+WLuBstnhgcYuxlMNTC3kke5OLjoVnlyf4nBliZzh8rGFm7mhvMQDwS4m7DqASmUprPN4axuz7QqDdoeLziC7c2s8uLmTXfl11WnbcEnrHg+2dnGuNcSbBs+y3CtQtlR6yi57lbLR5onudt49/AzPOJOc6YzwyOIMH9rzCA+099AMbHQk3XyKapDjolPhttwsjTDDE60ZJXD5Nu8bPMKCX2bSrPItZw853WGHpXpCPtbcxsHcEm6kzIdbGsSvHHsfv3Dga5zujnL/6BlMLSBE8L7RY5zujvJvO2/n1vxFFrwyz2iTquNIc4LGQIZHG9vYlV2n7mfYlVnFjVSJscfrM3QDk16gohi3ipcf700yatV5orOdSatKM7Ap6212ZeCbjd2ktIDPbN7IY4vT/OCuI3y4+QZ+cuwBlvwBjrSnuSU/x6PdnTxa20Y3MGkWbe4qXaAVpXmkuo2bJy/yaGcnY1YdV5o0ggxfXN6Pbfjcmb/ATEWZMD9dvYlOYDGcavHI2jZ+bsdXOeqX2fBz1IIsA0aHot7leG+SapjjSGuKw7nFfjH2pmNzY3aeR7q7MGONsxeaDFstBoxOLPQ4nHNGWHAGGDRa9CKLVmjjRCaPVWe4vTzHkj+AKQJOd8f65tdJ+3K+9TZ7k/PuiHJRRCkebe6gbHU42Zvgd5++i8Fym1uG5jmUXWQlKPXrwW7l+77UENHrh/N9T5g6hRB3A78ipXxn/PuXAaSU/+pqx6R3jcuxf/7z/NXDj/BnK3tp9mxG8i3OLQ5TLKku0+pckE85uKHBSrVAUE9x+6ELLHUKrNXzZNIuedtlcXWAiZEahojImh4Xa2U6iznuvFkFiFyolylnuth6QDnV4e0DJ2iFNmedUTa9DCOpFou9EhPpOrbms+nl+jUfl7t5ipbDqZUR7pq+yPHNUdrdFFOVGoYW0fEt8pbLZjfLxslB7rz7FFU3Q8708EKdlpcibaqu0QtdFTDSDizWOjkGMx3WOzn8QMc0QiqZDkGk8e5RJTNoIuJUZ4xNN8vO3Aanm8Nsy6pJK2u4bLo5ji6Po+sRk6U6Xqi6tM+tVJgZ3SRCcKC0wniqQS3IfFs1kmqQ5VxniMVOkbzpMpWtMWXXeLi6naV2gc31PLunV8mZHs8sjeFv2mzfs4wXGuQsl+VmgULaYSjdoRuY2HrAppNhIttkw1EBFbMrgwyXW4xkW1hayPG1EXK2x1ShThBpzNbKZFMeja7NQFY1Fe56JikjRBMSXYvoeBa5lIsXGDS6NuMlFYm5VC9iGWqcaFpE3nYZSPWouWkWlstk8g7dpRzpsQ7plI/rG4wWmtSdNKPZFrvy6wyYqh/gI9VtzGSrnG4Mk4lby1xsDNBxLWbKNc6vDZLPOuwrr5HVPZZ7BSw9xAkM6m6a9UaOYD5LZZ/KbUsZAW0nxa7KBpqQLLULlO0uJ56eobyzSsnuMZ2rcak9wGKtxM7BDY7PTpAp9tg7tE4kBTVXJVS7vsHacolU0cXQQ4oZh7VaHk2TZDMuzqNl8net4wZKTi5lephayPZ8leVugdlqmfdsP0nTt+mFJkvdAsPpNlPpGgOmik5+rL6NGwqqdF8zsPsl5+Y6A+wrrPL4xjSTuQajtmr5kzNUJZyU5jPXq2CKiDU3z4DVoWT2eGRjhoyh0m0MLWI6UyOlB7ihwbn2ID3fxNRD5jbKTFVqXFgaYny4jhMYNNtpshmXiXyDlU6ekt3Dj1RhiEG7S9VNM18dYKpcY7ObZSLfYL2bY3uxSjcw6QYmLdemaPeo99IYekQhpczjLdfGMgK8wMA2fJzARNcidC2i55nkUi5L9SLBbI7MbjXOvEBHAKWsSu/p+eo5j+ZbLDcLmEZIzzWZKddYbBT5wLZj/MvDf/rSmjoLk/K2u37hqtu/9uVfuq5Mnd8rjO9aM/5/FvjZ+Och4JlXlNAXxiDfXv3gtYLXIl0JTdeO1yJdr0Wa4LVJ13dC04yUcuilIqBQmJS33f7zV93+1a+8tEWxX218T5g6IS43/+34Cxw7LqHzWwBCiMdfay/qtUgTvDbpSmi6drwW6Xot0gSvTbpeKzSJ7wEl6KXC9wrjezEZ/wkSJEiQ4MVASngd+fi+V0qWPQbsFkJsF0JYwI+gytUkSJAgQYKXAEJefbne8D2h8UkpAyHEzwNf5HLG//EXOOw5K4e/yngt0gSvTboSmq4dr0W6Xos0wWuTrlefJgkivA453FXwPRHckiBBggQJXj4UchPyzhv/xlW3/9mD/zgJbkmQIEGCBNcXXk95fAnjS5AgQYIEKsDldYLvleCWa4YQ4l1CiNNCiHNCiF96rdIghHhz3L/quBDi668ATR8WQqwJIZ4zt1EI8WNCiKfj5UEhxI2vAZqKQohPCyGOxs/pp14BmqaEEF8VQpyMr3nVkvVCiNuFEGGcZ/qKQghhCyEeveLZ/LPXKg2v9FiPr6kLIZ4SQnzmOba94mP9Gmh6xcf6t11fSkR49eV6w3XF+K4obfZu4ADwo0KIA681GoQQJeA3ge+TUh4EfvgVIO13gefrVDwLvElKeRj4F7wyDvcXounngBNSyhuBNwP/No7qfTkRAH9XSrkfuAv4uecaQ/F7/n9RAVevBlzg/vjZ3AS8Swhx12uNhldprAP8LVQLm+fCqzHWX4imV2OsfzukvPpyneG6YnzAHcA5KeUFKaUHfBT4wGuQhr8CfEJKeQlASrn2chMlpfwGUH2e7Q9KKbcKCT6MypV8VWlCFSnICyEEkIv3DV5mmpallE/Gf7dQE9XEc+z6C6heYS/7u3suSIV2/NOMl1d0hrpGGl7xsS6EmATeC/z2c21/Ncb6C9HEqzDW/8LVQ3n15TrD9cb4JoD5K34v8NyT1qtNwx5gQAjxNSHEE0KIv/qKUXdt+Gng8682EcB/BvajihUcA/6WlDJ6pS4eN768GXjkWesngL8E/LdXipbnQmw6O4Jivl/+ThpyvgI0vBpj/TeAvw9cy1h5pcb6b/D8NL2qYx1ic+dVlusN1xvju6bSZq8BGgzgVpQE+E7gHwsh9rzchF0LhBBvQU0G/+DVpgX1bI4A4yhT2n8WQhReiQsLIXIoje5vSymbz9r8G8A/kFKGrwQtV4OUMpRS3oTSWO4QQhx6DdLwio51IcT7gDUp5RPXsO8rMtavkaZXbawrSIiiqy/XGa43xvdaKG12LTQsAF+QUnaklBvAN4BXxMH+fBBCHEaZYj4gpdx8tekBfgplJpNSynMo38y+l/uiQggTxfT+p5TyE8+xy23AR4UQF4EfAn5TCPH9LzddV4OUsg58jef3l75aNLzSY/1e4Pvid/NR4H4hxEeevdMrPNavhaZXZaz3IUl8fN/DeC2UNrsWGj4J3CeEMIQQGeBOru70fkUghJgGPgH8hJTyzKtJyxW4BLwVQAgxAuwFLrycF4x9LL8DnJRS/rvn2kdKuV1KuU1KuQ34GPB/SSn/9OWk69kQQgzFgSMIIdLA24BTr0EaXtGxLqX8ZSnlZPxufgT4ipTyx59F9ys61q+FJl6Fsf5svJ6iOq+rPL7vsLTZK0KDEOKvx9v/m5TypBDiC8DTKJv/b0spX9YWSkKI/4WKFhsUQiwA/xQVjICU8r8B/wSooLQXgODlrtRwDTT9C+B3hRDHUCbkfxBrDS8n7gV+AjgW+64A/iEwfQVdrwWMAb8XR5dqwB9LKf9CmPyrQcOrPdafC1fSxKsw1q+BpldjrH87rkPN7mpISpYlSJAgwescRXtU3jP9k1fd/oWz//pFlSwTQrwZ5Qs3gQ0p5Zvi9e8C/gNKKfhtKeWvXcO52lLKXBxsdhI4jRIOOsBPSSlPXytdW7iuNL4ECRIkSPAd4iVSgq7I3XyXlPKSEGI4Xr+V4/x2lO/3MSHEp6SUJ17E6c/HwVQIIf5PlDXm6hz7KkgYX4IECRIkeClNnVfL3eznOAMIIbZynL+N8QkhtgN/iOJPX3ie6xSA2vNsvyoSxpcgQYIEr3dICeHzZucMCiEev+L3b0kpr1bxZg9gCiG+BuSB/yCl/H2eO8f5zuc4/j8A/1VK+ftCiJ971radse89D2wFS71oJIwvQYIECRK8kMa38SJ8fFu5m28F0sBDQoiHufY863uBH4z//gNUacAtXGnq/CCq3NyLTuNJGF+CBAkSvN4hgfA7S1SPtbK/Fv98D0qT25BSdoCOEGIrd/PF5Flfi931U8D/+E5ovt7y+BIkeEkghKgI1VHgiBBiRQixGP/dFkL85qtNX4IELzm+wwR2KeV/kVLeFC9LXD1381rzrB+ItwH82PNc+g3A+Rd3kwqJxpcgwXMgruZxE4AQ4leAtpTy119NmhIkeNnwwj6+F3Gqq+duXmOe9d8C/lColmAff9a2LR+fADzgZ74TGhPGlyDBi0Ccn/T3pJTvixnidlQi9x7g76BaGb0bWATeL6X0hRC3Av8OVXV/A/iQlHL5lac+QYLnwUuY0y2l/DfAv3mO9Z8DPvcCx84Cd1+x6tfi9RdRPsPvGompM0GC7w47UQWYPwB8BPiqlPIGoAe8N677+Z+AH5JS3gp8GPjVV4vYBAmeG1L5+K62XGdINL4ECb47fD7W6o6hzDdbeUfHgG2omouHgC/H5bF0INH2Ery2IOEV7oL0qiJhfAkSfHdwAaSUkRDCl5drAEao70sAx6WUd1/tBAkSvCZwHWp2V0Ni6kyQ4OXFaWBICHE3qJZHQoiDrzJNCRJ8O+Trqx9fovElSPAyQkrpCSF+CPiPQogi6pv7DeAV7RqSIMELQb5EUZ3fC0i6MyRIkCDB6xxFvSLvst971e1f6v7Bi+rO8FpHovElSJAgwesdkpcsj+97AQnjS5AgQYLXOSQgo9eP9S9hfAkSJEjweoeUiY8vQYIECRK8fhCXGBt8nl02pJQvugvCaxUJ40uQIEGCBK8rJHl8CRIkSJDgdYWE8SVIkCBBgtcVEsaXIEGCBAleV0gYX4IECRIkeF0hYXwJEiRIkOB1hYTxJUiQIEGC1xUSxpcgQYIECV5XSBhfggQJEiR4XSFhfAkSJEiQ4HWFhPElSJAgQYLXFRLGlyBBggQJXldIGF+CBAkSJHhdIWF8CRIkSJDgdYWE8SVIkCBBgtcVEsaXIEGCBAleV0gYX4IECRIkeF0hYXwJEiRIkOB1hYTxJUiQIEGC1xUSxpfgexJCiA8JIb71PNs/L4T4ye/i/N/V8ddw/m1CCCmEMK6y/R8KIX77pTpfggQJLiP5SBJcl5BSvvvVPP67hZTy/3k1r58gwfWMRONL8LrD97pW9L1Of4IErzYSxpfgNQ8hxJQQ4hNCiHUhxKYQ4j9fse3XhRA1IcSsEOLdV6z/mhDiZ+K/PySEeEAI8e+FEFXgV65Y95+EEA0hxCkhxFuf5/hvPc+1tgshviGEaAkh/kwI8V+EEB+5xtv7P4QQS0KIZSHE373inL+ydY4rzJg/LYS4BHxFCKHH9GwIIS4A733WM/uQEOJCTNOsEOLHXswzT5DgekbC+BK8piGE0IHPAHPANmAC+Gi8+U7gNDAI/Gvgd4QQ4iqnuhO4AAwDv/qsdYPAPwU+IYQoP8/xV7vWHwKPAhXgV4CfeBG3+BZgN/AO4JeEEG97nn3fBOwH3gn8NeB9wM3AbcAPbe0khMgC/xF4t5QyD9wDHHkRNCVIcF0jYXwJXuu4AxgHflFK2ZFSOlLKraCWOSnlf5dShsDvAWPAyFXOsySl/E9SykBK2YvXrQG/IaX0pZR/hGJs773K8c95LSHENHA78E+klF5M26dexP39s/i+jgH/A/jR59n3V+J9e8Bfjmmfl1JWgX/1rH0j4JAQIi2lXJZSHn8RNCVIcF0jYXwJXuuYQjGd4Dm2rWz9IaXsxn/mrnKe+edYtyillFf8nkMx2efC1a41DlSvWHe1a10NV+77fNd/9r7jz3HsFn0d4IPAXweWhRCfFULsexE0JUhwXSNhfAle65gHpl+CgA75HOsmnmUanQaWXuR5l4GyECJzxbqpF3H8lfu+0PWvvIfl5zj28o5SflFK+XaUZnoK+O8vgqYECa5rJIwvwWsdj6Im+V8TQmSFELYQ4t6X6NzDwN8UQphCiB9G+c8+92JOIKWcAx5HBcxYQoi7gfe/iFP8YyFERghxEPgp4I+u8bg/jmmfFEIMAL+0tUEIMSKE+L7Y1+cCbSB8ETQlSHBdIwmLTvCahpQyFEK8HxWscQml9fwh8ORLcPpHUIElG8Aq8ENSys3v4Dw/BvwusIli1H8E6Nd47NeBcygh9NellF+6xuP+O7AHOAo0gV8H7o+3acDfBf4A9byOAP/XNZ43QYLrHuLbXRwJErw+IIT4EPAzUso3vAzn/iPglJTyn77U506QIMF3j8TUmSDBdwkhxO1CiJ1CCE0I8S7gA8CfvspkJUiQ4CpIGF+CBN89RoGvoXxp/xH4G1LKp4QQPyaEaD/HkqQWJEjwKiIxdSZIkCBBgtcVEo0vQYIECRK8rpBEdSZIkCDB6xzvfEtWblavnvHyxNPuF6WU73oFSXpZkTC+BAkSJHidY6Ma8sgXJ6+63Rw7P/gKkvOyIzF1Jnhd4cquB68lXNkNIkGCVxoSiS/Dqy7XGxLGl+C6gxDirwghHo8jKJfjbuoveb7eKwkhxP8thFiJWyh9WAiRerVpSnB9IXqef9cbEsaX4LqCEOLvAL8B/D+oTg3TwG+icuu+JyGEeCeqJNlbUa2ZdgD/7NWkKcH1BaXxRVddrjckjC/BdQMhRBH458DPSSk/Ebfw8aWUn5ZS/uIVu1pCiN+Pm7QeF0LcdsU5fkkIcT7edkII8Zeu2PZCDWm/JoT4F3GD25YQ4ktCiMErtt8lhHhQCFEXQhwVQrz5Gm/tJ4HfkVIel1LWgH8BfOg7eUYJEjwXJBAir7pcb0gYX4LrCXcDNvC/X2C/70M1sy2heuf95yu2nQfuA4ooreojQoixK7a/UPPbv4IqNj0MWMDfAxBCTACfBf4lUI7Xf1wIMXQN93UQVZNzC0dRvQAr13BsggQvCAmJxpcgwfcoKsDGVXr3XYlvSSk/FzeV/QPgxq0NUso/kVIuSSmjuDntWVQz3C28UPPb/yGlPBM3i/1j4KZ4/Y8Dn4uvG0kpv4zq6vCea7ivHNC44vfW3/lrODZBgmtC9DzL9YaE8SW4nrAJDF5D776VK/7uAvbWMUKIvyqEOBKbI+vAIZR29xeOvUrz22efe2vbDPDDW+eNz/0GFON8IbSBwhW/t/5uXcOxCRK8IKSUeM+zXG9IGF+C6wkPAQ7w/d/JwUKIGVS7n58HKlLKEvAMIJ7vuGvEPPAHUsrSFUtWSvlr13Dsca7QSuO/V7/DFkoJEvwFSBKNL0GC70lIKRvAPwH+ixDi++MGr6YQ4t1CiH99DafIouaAdQAhxE+hNL6XAh8B3i+EeKcQQo8b6r5ZCHH1rOHL+H3gp4UQB+Kms/8I1f8vQYKXBBKBL6++XG9IGF+C6wpSyn8H/B0Uc1hHaVo/zzW0CZJSngD+LUpzXAVuAB54ieiaR6VU/MMr6PpFruEblFJ+ARVI81VgLl6SXn8JXlKEiKsu1xuS7gwJEiRI8DrHwcOW/MPPjFx1+00zC09IKW+76g7fY0hqdSZIkCDB6xwqj+/60+yuhpfV1BmXWTouhHhGCPG/Yr9GWQjxZSHE2fj/gSv2/2UhxDkhxOm4WsXW+luFEMfibf/xWXlTCRIkSJDgu4BEEKJddbne8LLdUZyw+zeB26SUhwAd+BFU6aU/l1LuBv48/o0Q4kC8/SDwLuA3hRB6fLr/CvwssDterpv2GAkSJEjwakMlsGtXXa43vNx3ZADpOEcqAyyhHPy/F2//PS6Hnn8A+KiU0pVSzgLngDviqhkFKeVDUjkkf5/vMFw9QYIECRI8FwSh1K66XG942Xx8UspFIcSvA5eAHvAlKeWXhBAjUsrleJ9lIcRwfMgE8PAVp1iI1/nx389e/xcghPhZlGaIMK1bzRF1as0HBEgNRKSWyAQRcjlDS4LUQfMgTIEWwJVRvEJe3kd3IbTV8boHofnt65HqvKmlLs5EBgCzC342vibx/1q8q4xpC0EaoDsQxPuKUG3bGntGT/0f2t9+75qv6DV6EhFJgozWP+fWdj/37ddCXD4ODSJdPRstUP+HKUhVQ9yyrp5bCJGhjtdd9beQ8XpLnUtEEFqXn7fRVf+HafVcNF89KxGp66XqEX5OQ4p4vbxMb6THz8ON7z9SryuK99O9+JlGYHYgsNW96J6iQcTvSwSXn+sW/SKKz6nF44PL9wPqPFpwed/IVGMjsi6/E6Q6L8Tv3vr2+9saP5qv9pNCPRezLfEKAhGC4arzRMbl62yNH92FIK2eYZgGsxURZLQ+rVt0SwOMriRIC5V0Ja64b1M9m9BSNEfx72Crt4MGmhtfV8TPjMvvz2yrbZF5xT1tzYNbcXFCrd96dv33ZKh9DEe9M7jiHcfjUOrqb91T19Cd+P/4uxLR5bEldbBqAX7eIDLifezLdKXqIaGlE6bj9+ar+xdB/G378X3GtH/bGIr30R11zq19zbZ6B1tzA7q6Fy1Ux0QmWM2IIK0RptTxaJefje5KgoxAamo86a7Ez6p3L/X4mYfq3XpFrX98aMXP6oo5pj9VaeAuLmxIKa+l3N01QQI++gvud73gZWN8se/uA8B2oA78iRDix5/vkOdYJ59n/V9cKeVvAb8FkB6bkjM/83fU4LTUIM1fktT3CNJr0JmQ5BYEfk5NmPlLUDsg0R2B1CWl09CeEAQZxWzKJyPqO7X+x+EV4w+nB1EK9K4aqGEa7E1oT0lylwTOoPoo02vQ2ilJbahzan48qRiKPqOjPrggA7l5aO6UZBaFmlgldKcijLbGwElJaEFjl8DeUB+BM6zoNrqXGZzRVcyzeE7SHRYYPWjukphNoRi7r65nti8zvyCrPu4goyYrqYHVgO6YJLug6JYaeAMSe1UgIsiuSFozAs0FvwBmE4Ic+DmJCARWQz2rIBchIrDqaoJAqsnDbIGfV8c5gxIRiT6T1R1wByXZ+fg9pSFVU/eXWVEjo7lDorsCex2cIYgsSaoq+kzKz0LprKS+W6jnbamxElrqvW4xp8iMGbeMmWaknqHuqe3uwGXGZ9WgN6qO93Pq+lvM1WjTn/iMXnycr56p1VD0GD31OzJg9JGQxjY1WYPa1h2T6D1BdhnKx7vMvTuDFsTvaYtZAPYGOIOK3lRVrfOL6tml19RzVzenaPJzl4UAqav3IySYDTWGNE+ocZFW4ynISqy6UIxBXhaiIgOkKTE6ov97S6B0yxGaL7A3BL2RCKum4Zcichc13IHLDHtLcHKHIvSuhu6qc1v1mM44a1pIcAckZkugO/EYa6mxkF5Tz1OLmVaQhoEzEY2dSujbEmBFqN5HkAV7TY37re80SKtxp7sifrYSzRVYTXAqUDwHnQkIsurbkRr4ecnYgxGrd+joPTWOpabOlVsA3ZF0R9T3kqqr+9z6tsyOGhN9IUyPGWJPjd8t4VFqENrqGesOeKX4nRbUMWf/0d+Ze6458DuFlOK61OyuhpfzTt8GzEop16WUPvAJ4B5gdavob/z/Wrz/AjB1xfGTKNPoQvz3s9c/L6SA8gn19RhtsFrQ3KE+bGcQEODllbSbXosZzpzabtUE7QnRl3JFCGu3arhliVeUBFk1eQRp9TcojS7IABLcImi+6A/SwqwEDUYfkBg9NdAjS9ERWWrQ+wX1wZvteFK0JH5efUxBBiJTQgStaUFnQqAFijl5RXWvYUp9UH5O0esMKmYidfXRdMdAdwR+XhKmpWK2XUWv7irmndpUtI0/GChGLtT5rbpA6lA+GcaTpqI3yIJTEYSWmjgBvIGYcYRCiSyammD0nkBz1URpdOi/Fz+r3oHuqWdmtiHMROgupNfVcV5RHROlJIW5SDHjUbCaklRNYMeTvAjAbIq+BO/l1TG9imLAQVpJ615BEllSPbc0WM0taVy971RNMaAwrZ5nb0hNQl5RkqpCd1z2tTEE5C7FWkLM/ANbTVBhrF34WfWss0sShJpotUCNu40bdNJVSelcRJhS5xShYkitabj4/jRmW50nMmPG4YG9Dr3hWAtqge5DqIwLiFDREOlqbAWx0KC7xONbfSBBPiK0JWHm8gQsIiASBBlJZEqlJVoSsxlrM7GVIFUVfQZsthUTBiXYoEm6EyFmUyPISQgFzZ0RUoeZz3eVgNCjP/uk19Q5jQ64FRh9xFOMqRp/l5fUuPEL6n68gqK1tV3R7hfU2I9MaG7T1POKtX2rrq7hlST5WcVcnBGJn5c4FfWsUjWB2YT8bDx5aJeFtda2LcYk1HgoStKrgtakTmRJ0uvgFdVYSlXVmKvvFf177A2rsSE19b1kViOCrESEar3uqDEWpUBqEntTjT8tgPxFQZiWSmBsKoEoVb8sFLyU2NL4rra8VBBC/D0hhHxW15LnDGp8nnO8WQjxmfjvDwkh1uMyg8eFEB8TQmRe6BwvJ+O7BNwVV88QqF5iJ1HV8H8y3ucngU/Gf38K+BEhREoIsR0VxPJobBZtxS1dBPBXrzjmqhASVu8QuEMR7qAksNVHs2VKQaqBt8VwOmNqQiuel4qpZS+bXHKLUkn/rsBsxRO6pC8lihC6I2pwmi0lAdobSsLXXGjuVJPx+s0aoa0mfCnUvqF92ay6ZZrTfNC7Gul19eFrIWTmlbnRKyjGUjoj8fKAAHtTmU40L9bYspBZVsyvMxZrP7EZyWwJjLbAqtM3t2i+OqdbVvQs323glmPzYC82rZRg86BOaEH+giCzHE+EsblICiUJqw9aMQipSXILkiADIhKgqcktyCrJ2hmSSrOMzZmgaMrMK9Nna5uaVHU31khcQW2PRnpTYnbAywuMjnpvQsZmVT02DdqQXoXUhqA7KXEHYjNuLFGbbUFkKSYbZNW76o1KwpSaYPzct5t1UxuK/taOCBEpRppZBs0T1PdLpKEmJTNmohAzJDdmojY0dgpKZ5VGmptXTNDPKyvE2q1aX2syOvG1DaVxuWXZN13m5tXE6AwprXfL3NmZkGgeDJyUuJUIv6CEqt6o7Nec2tJYtVDdr97VEIHS1tOr6lmaTfU+U1WB5ittQ3eFGqdezFRz6jmZLQgykt5YRHNfiDsY4o37EAky8zpeJVRm3FSEVdcwW7B2awYRKnpFCHpHozek7tsZVuNm6Q0WZizcINXY090rTP+GjJmGINKVxmp21HM3euq4rX07EzLW5gWdSbXOaAmshiC01dgMU/EcMAlEglRVCWupTQ2zCaWzUf+bt2pCCblZyCwqrc5sKkbXG5E4g1u28lgTDmHwWKi0OF3SGVHa6JbbYcuitKVsefnLZn3NA80VeCW1PlUTSrgtvBy51y+Njy9mSr97lW1TwNtRvGFr3fMFNV4r/khKeZOU8iDgAR98oQNeNsYnpXwE+BjwJHAsvtZvAb8GvF0IcRb1EH4t3v84qpr9CeALqJ5qWz3v/wbw26iAl/PA56+FBhEBUmB01QANYwldahKjp0xqek9pRFsahzOgJnWpS2XHD8EpKwa3ZZrws0pjSG2qwZtZiTWrgmKkYSqeyIXaFplKw9qaEHVfaSJBJmYeXDa1aV6sxemSziREdsxM0soEtWWa7A4prS+9rjQIqauJKFVXE2dnUh1HpGgzY2YbpNU+bkXiFySaD3ZVmSG3mMcWMxOBuq5XUlKn7qoJJjKVFuOVlGYRphQj0TzxbUZosyNo7BTKT9UDs6EYtNUE3RMYHWV2tjegNRM/J0OdP8gp2sIUDD/uYdUUs5G60nqN+L0BpOpqAgzTlzX0IEvffEjM8MzWltlb0Wm2YlNnpM5ldC9b1VOb6nmHKTU5hRklNIhQ9E2XW5J8dk5ps51JiVdU6+0NpWX7OfU8zYYaD91hZZJuT6kxiSA2KV5mYlv+W80T8VgSfZO9O6CYnhFrNSJUZnbdVQLZ5g2KRrMJ+YtgdNSz0ny1rxYoQcGP+zpsCV+g7kXb8n0KEL66vtKKYubiq3OGMS26K5RftaOhORpG1iPMhco0GgikKSEdEeTUu3UHLo8xpHpOqXqsFXcUg03V1fPWXUVv3wzciYWWlnoeRi82TdtK69r6lkSgGNeWZipiTXZr/Bq9WFuXom++lTr4xQg0JSSFprpn3YfGNg17Xb2n0FZMKMioMRNal4XkwaOgBUpYkMblsbhxWFfvqSfUc4+F3PIJSW4hFtBqSjgUMv52ZWwmDyEyZN/nroi9ltnvxUFFdepXXV4i/Hvg7/Ptd/CcQY3PPlAI8S4hxCkhxLeAH3iuk8dBlFmg9kKEvKwJ7FLKf8pfLK3korS/59r/V4FffY71j/MiayYqE42S0IzulslOfWDSktgLSnrSvdihnVJMqj2tJHKpXWYUWxOD7tFnEJLLAQ+NXUr69/PqHI2dSkpFgD8O6WWB7sUfSjyRmE1BqgadKakka1cxp9BW0nhoKSnSbIo+MzBbom//D2J/jTLxqfO7ZbU+Mun7X4Js7EcrXHamd0clZluQWVV+jOoBrX9eP68mm1RVnc/egMgUfb9MaKt9ojiYJ7KgeF6yeRj0riC7CI09MePpB5hI9TA16E7Ivk9R9wS9QWXmUUxJ9M28I49JansVg5p/u4mIlH/UL0hEAEFaXA7Yic2+bkmSWRa0t0ek1pU/dotxmK1Y44vfd5BRk2N6VVNChaXuJ70GnUlBfiGiN6rkQquhmD/E5uJCRBAJ9J6aOPMLEX5RQwaiP0Ft+YDVRK1MwEFGIsLYTxQLHSIQSoAKY3OxBDTILqj9umOyz9SkFvuJ2or5KWat3q3mqQk5s6IYrleKGbMOXlbGgTXKF2o2BN1xSW5e+aBFoDTD9IogNKFwQWmjga1Mz25Fnac9Lvvm6vQadKaVQLc1dqQhiVbSkA0JY9OdiATCVFFR7lCE1tPQfEivKcGtO6bG/+TXPDYOWX0tO0zFQVIos26YUv7LIBthNuN3aythyegKUlVlioxM9b7aM7EVJaQfdLPl142seLyZl7/77mjsMrDV+XLLkto+QZhSpk2/EGuLXcWQcvPQ2BuRaasINS2A1owaZ0ZPWYB0Lw7sMdT7tmqC0rmIxg7l09w4rMa30VUmVLOlvvVUVblZ0mvQzimBPLOinktnUr5Mpk7xQvl6g0KIx6/4/VtxTMU1QQjxfcCilPLos9KwrxbUeOWxNqp4/P0oxvhHzzr9B4UQW51OzgCffiF6rltvpojAXlUDKbTVZGr0lCSWndNwKkoK94pqoGYX1WQiQjVIzfaW5CZJrwGRmjC3/FNWU01GfkFNVr0RxVTre5TZS+pqck2vKgm7O662h7Yy8SEUY9F7gsKcJLN62dQodSX1bkXU5RZl3/cX2peZijMi8QYipKl8TtlFpQlofmx+3IpkS8VBNLpiQlvarltQH9eWyU3EkWoqSAEGTku6o3EAj6k++NBSAR2hLdF7is7mjCCzJCjMStpTW45+SZiJlOk3UJO4VYfSSWVm0j1lYtsyNfUjB6V65rU9moo2NBR9RkcQ5BTztzcEVktpzSJQxzjDEboTCzMdTZkXrcs+MS1Qzw2hgpy0QAUteLHmk6qBX4pwKuo9N2c0UlV1nFdQk6K9JihcgNSGhr0uYt+opHpAI9LVs3crEUYnNpHHBp0t7cXoir6PzGwpS0RmVfmypKl8e7oryCwInLISnjLLylQNilGbcRDElond7CjaI1MF8YRmbEZvXjahpVfVdbfM8IarzGZ+TjEJdzDCijUjLYDWNkFvSGkfzqBi2G4JglJIlJL4xYhUXRLmAjJLgsyShtQl0pSE2RBhKGtCekWHSEDNUtaEpobZUe9KBZVA5Zia+Kv7LbySCpZyKrGWEyqtVfeUUJBZBrOhXQ6ysRTzBiidDfsChdWMA5Ocy8LalishMmDgdHTZ125Cd1y9AwCjrRHY0B5TY9ZsKl99dklZeXpjyscc2spU7JUgzMhYCFWmzva2CKOrviU/G/u4HYFXUmPFK8YBaB31PpTpX80x0lA+aKOtYgUGn47QAvXteSU1RsrHXvr5Uml8xlUXVJ/L265Yvo3pCSEeEUIcQVnmvi/2uR2Ji7JngP8fqoD8s3EtwYv7UPEiZ+OUto88a/sfSSlvAkZR1sVffKH7vW4Zn9TiEOmUMiNZNaE+3rSMGYzsB6gQ0bf/mx0lyWeX4mAVlIPa6BIHJqjJSIRquwhEf5ArU6FQpjQUA1EalOibSSPrsmSpmKOkuU0ok2EmUsEXecV4tqLbnLJiEiK4HOQRpiVSUxK4NJRJrjeqoiCNzmWn/lYIO2LLfCn6JjK/AO0p9QyMjooSRcTpAgHUd4t+0ILZhvyc7GuTuqN8ZIGtPtbQUua7reg/IZWkuhU5GmRkHKmmnmVkyn40HijTJsTmOF/0zX5aoBiO2VaS/1YIed/vJZUJKr2oKUm+oyJ0t8zNV743r6job09e1ui3tFtpKIaJdplJ+vnLgoARm6laM5dTM/zcVkCPEjzs2MAiDaUhdiYUs9G7cbDJln1FqPNqnmJuvSG1zV6PGe0A/fQYrxBr8O1Y2BmIA56yigF1xmVfC2hNC0WDUDR0x9QzdstqnVdU13JL9J91pCuTaqoWB5IsRuobiX1JUUoidUmYkWhdHXtNjbfmDqG0uQB6YyrimHRIet5UwTFFZdcXAUTpCL0rCPLyckRob8sMqO49sxqRqsHmYfUdGD2B4UBre6w9b6UgxSbLMC1BU6blVBVqe3TMprqvLQ3eHYyIYkFgC6EN1f1aP9WiMBtHDw+o7UojlFhxQNGWf84pK1O+CJVmqfmXA8GkJknFAUNb2q/69tXz7zO52BWQXlUC45YmGqUkVlV9T0Z83fyiJMhBY3ucvhJblzRfPaOXGhJBKK++vODxUt4ZM5+fAT4V+9xuklJ+EdiJiu4/KoS4iApQfFIIMcrVgxr/IokvTINEaXtvfKF9r1vGRyyt6k4cst2JtbtuPJlLgTMk0T2hpO1IMSMRKtNddxgGTqmUBCL1MaWqkFmF5q4w9hkqKVBIZdJAqglc9+L8qw79/K1UVQ14q37Zr6DyuyT2hvoIrE0lEftFFUxjdJXk7mfj0P92nN/ng70usGoauiuwNjU1kfqKaaTqyoRpdGErT0uLA1AyK+pabkXG0rCMgz2gPaMYaJRSJiwiZeZyB6NY8lfnNlvEE6nEK9FPWTDbcXCEK8guqECgIKM0Q90V9EYlvSHFBKx6HHSTUkEZeldpUFJX0bVbTM3PK1pCK9Z0DLUYHdEXHMKUpDemNHOrcTm6dcs/FNrqHUWW7GuWUov9KuFlX5wKdpD9aEhEbC1ISRXBm5EEWWWiHDgdktpUE4LmCLyixC2C0VKTaj+C1gZ3kL6GEaa2AlfUBG5X1br+/WYlXikiMiVuRUX5hSlJdyoiis3kuhOb3doaRlf0J/cwrWjQPBUQo3kCP6do13tK+PKKkt5oRG80IrMmQYPSKWVinvlsA7eoYXaUyU5z1UQtdUmYjYjKHu1tEelFnSAfoTd0vAH1LQW5CNE0cCYC8AV606A3FhLZEr2j4015INTzIxR0J6RKeZHqW9k8qNGeUmZGvadhb8bPSajxm9pQvmIRqbELkFrXMDpQ36/eq1dUboXesHq+Vl1pV5ElVTBPbLkIsip4KUwrQQbUNqOtKW2rI+gNqejXpTdpyNg3mV5Vz8MvyH7+6Pz9OlZdozd8OXjMqmn9carSFCTOSITVVO/YK6l0p+ySGlMI2Y8CdYbV32t3KMGmO6UsCFvBeFIHq/HCjOhFT5fyBTW+7+Lc8piUclhKuU1KuQ3F7G6RUq5wlaDGZ53iFLBdCLEz/v2jz3O5N6DiQJ4X1y/jQ2k9oa0m2/aMklyFvDwppjZjP1GWOARa4FZiDSyrNBg/F0f11ZS07OfAbMYfvqMCNGSsJUWWxGirQSkNSZBWjECZRNWiEoiV9BhkJGZDo7E7NiluJRJHirlF5laOkbLtyzhKzGwrU9+W+VAa4JVlbPKSNHcoLcQty36Aypa0TBzMYbYEzpDK/E1tKg0oPyuIYp/GVmi/CCC9olE8G+czxeZWzVPniiylMWdW1ATuDKqAm+6o0nqshopKi0w1kW75ZraCGDILikF4lVBpH37sQzTBqajcKbgcyKI0QiVEmLG52Yj9LCoiUz27fmJwW40BpIrSi+wIESrtShpbmqhi/pllcZlhZa6IEu2oCEdi0xdAZ1SH2K9VPKcmxe64mpDDlCS01L1v+XRVZKd6H2aLeD9oTyptyi9GdKYkVlOQqiqGZjXUZB+lJPkLGs5QiF1Tx1l1lY6gonVV3hmRimBFQOGCiCNEBama8lWBEkBSmxqaL9i4WdKZCdm8KcLPwdqdRWWVMKA3qpzZUgPN1xh4WkfUTewNjd5oRJgL+9o6W4EshiQz1AErIqr4KrCF2N/cNohMFaWqiihsuRNiLUlX0clBRgkWjd0qvSOzSj/3UglsESIQZOdiv6euhNnQVu+8sy1SApWhNHKjq8y6QQZ6Y7Gm6Qu8SqgEnVxEaF02GadqyrqAgO5kpMYS6tvsjikLS35WaWdWI44sNZQ1Jb2maPXz6ls0m3EecFtg1jWciro3txwp4aSg3nFmQVMMOa2+EaMt0LsaRksjN6vRG1PvVO+pZz14bCvm76WEIHqe5eXCCwQ1bu3joAqTfDYObpl71mk+GJtVnwZuBv7FC133+mV8cRh6elX0B+jWR221rrD/x0ENgU3fxxWm1YS2VU0kspQ0mZ+P12lqgKr8OyWJR2ac79RS50hV1YfpDahzbeVWEcUfZEdpZ5GlJjaEpDsR4edVMEOwVU0i9lEanTh0O/b79YbUPfo5RaPUVGK7FJBe4XLaRRw1WJiNfSWVWGvSYtNsR/kA/Xzs4/Qv5w4Gcf6ZMyTpjqkAHiOeFFI1ZYLcyunrDV8OANnK/RKB8ldYDfUMrKZavxVx19itzLNmOzYPxybgrQos0ozvTYcgF6K7lwNQmjtj7UEq36buxAn9utJSo5SkN6py72ScRiF19d6c4Qh3MDY/piRDR9R72YqyFZHoh6KrABp52SxlqX16I8pXRajC5M2OYirlExJpKROhikJVB7oDakzYm8o6EKSVpq+7yqIgPEFkqkk4tMAbiLhc3URFLGqehlOOg0hiIXxre2jTTyoPMxH1fSqSMsgo7UYJXxHptdj6sBxrqz0NLOWT8nKxDzkjFfMy1BiLzIjajQHSkPhZidXQ0Lo6qaoSEiJbhfuLvI/rxupnT1cJ8oGIo2oFVlWnNxohUxFmS4sjZpWmHqYlXkHRuRW8EZlqLNib6ptlK+IU9Q2kV+lX0NnKv5RC7W/0FCMNbTWeC7NKwEltXjb5S4F6V6Z6n0FWjWGvpK6l91QQjdFW43iLLqd8OdBFGoq5+nklvFo19d26pcs0Kb91fC09jtS0JO4gcbUldV4RKTNvGDN/EcVRwRDHBCgGuH7jS5dXtwUJeNK46nLN55Hya1LKD73APtuklBtX/P5VKeVOKeVeKeVzRuxLKb8gpdwnpXyDlPKXpJTvi9f/rpRyKDarHpZSvkdKufZc57gS1y/jA5p7QnrDKrhEha8rs1BzV9QvvwVxAMlC7HeLKyYQKa0psOmXOWpuFwS5rRw1NUkMHNfw8xF+MULvaXFkpRqgW9pb7qKIy2Mpyd5sCpzhOJgkUg57zRN909WWxCl1FfyylXeYaqi8pDAl++auLY2icC4266QkqYa6jtFRzJn/P3t/FqNblmaHYWtPZ/rnmONOeW9mZdaQ1d3FZnMWm6TatBqyTAqGAdIwYBJ+IGzYhp8Mk/CjQUOGniwIoiHTMClYgGQIECzREC2aMm2KYDenru5iVeU83Snm+Mcz7sEPa58T2c3KqiI7E6Cv6gCBe2/ciH84/zl7f9/61gBCOvV+GCzFXMrFtjnwsAU34t79ozn0mH4Y2W73/SAFcIbzoiCBbMlzqkoO7X1K1mVQAdtHIc4yBA5+i5tqiJRsXQo0exHmVWGYicguVs4Vu810CeQv+N67ceCiv8+53u3bJDXYqUN6GzuxHee0rt90btnJ6h07CkpEgPv/bzswE+laIrF6IrgYmUhaaO5gtvQ2ygkcPwPZcXG0OYugfuPqN2vO4yTSa14LsiX1v59xVkf8WdUISBsG8o/ZCWSXKmoQA8yGXUDQQHausPp6GDZCVbEwUqWEG3nqLBc8N+kNOxpVSnYPFUlasmMnuX1AKUM3AULqUbwQyJ5rlA8ctl/vsPo9LVQtoDYKuiK0BxMw+kgDiqiDV/zd+shHUgthUABQygONBBygV1ygu8c15UEd3ysA7H3fR/mOGGaQsiMh7c7Wjz+7/EZAeRyLzw8l9r8XUN33KE8iaSsWcjQ6kGjm3Ijqg4D8nDKF228KjJ5KmF0YpkVmIzD6SMEVHt3E09ggyoraPRLKgg6oTzhzlF2U0Sw8qvsO5SkLKZfzMzE7Fo/JOmpE07tCyY490iuJvXc8pu/3rNQ4mz8kW7UnwUw/pGtOz2pFlEVAclNN1l/mKskjQMCHL/561Y5XduMLggtG0Jxv6IqdT5C0aqqPPa2+IiyyeQ2AJH6uagGzFTj8x7w4s6u42BVkM/bibghgdw/ILiVUfce+gycTrKf7r952w+/2UFqP0ydLVn/sHLkZ9mJzXWJw11ANsH6DEEl6I7B75Lj4KnY+m8dhWDBv32ZF61Jg98hHqC6Ktg07jtHznvhz99qbeewUncDtt1jByo6bx/oth93DCBVPA87/oGdnFX0UJx+JKH/gbC+7JFV+/Ro3BniBep+bWJC9hZcYNErw0dJrQkbg9jVP6cSeY3Xed057AXpD9qa50SgfOmwfhYH+HjQ70frUkTl46FE8lyQEpQFP/6SGcFxYuikLlG6MAWIDWOEffC9uEGMyDFXDRbpdeHQLBzdhl9MediSyPCSrcf2Y867mwGPyCT+THhJupyywhOe1uHyLhJneVIGuOuxUvOHss39PPTRYndL5Q9XsFFQpCSlKvs7qmPO4oEPUq5EI1Yvi977POVJ2BYhWoj4KqN9oMPpMkZjSSroEBRB+TjygiUYgZRfq7teDVMFsJIQOgBcInUR7nSN7qRAyD7tn6f6yM/CFQ33sYFYCaqVw8fvEYCjgEo4d7MTDxtFC8VLGjYedX3HGz6Y+Ai5/kUSkbhrQzcLQQfX3mB1xBq5qMXwuPvNo9oDVm0QWkluSoZr9iEYs5W8rcOD5p2yp0bSjOzRDVdQs2lEYvFrtKGD30A2ygx6d6UZxhivYea5fkwORxuXstG3BNamd8r4tjyP5q+N8XcURgVlFR5jyK1gv8dXN+P5lPF7ZjQ/gxagqXjTthBdOz6jz5g627A2Be6Pa/qK7eVsMtO/8TNxplTLOP7y5m8sJK2CnngPuLQYjY1d4Vmy+h6RCfA7cGWanEY7bxnnXnAtbfRRg1ly060PqnfrfgeDvqVYMsGXv+oG4kfgk3L03Fzu9OGcibV8MjLd2wcfsJoTLBhg04awS4DkYPeOiIq2I8pAAhOiKEQiLUreEwSexn02SkSd+m8k1ody4qR2EwVEFuBMu2zE3fAgukPRlJLEIga9HeLIHfeZJfgh3TFGXAaPPKB/wqadbjAoQfSdb0E6rnQVqxnLg5pucd3odyS1RMxZMwOQ9DdFyVqZ2dNQJOlDwnQdu5pbifZ9wA+tnYNUBF1tVsRjxkQGqt5wNduMwMFZ7GFxv7zrmIAlpEt4G5u/yeYUDsgsJO+L1VjzntZRfsJNu9nlNXX8H8JlnBzy28BowmcXuGy0hyZ2CG3u4ccT1dIBIHMLEIp00cNPI1vQimi1ESNYLiI1Gsl+hPnUQKmoHjYe5vYPmejTEbAS6GYubXoTOAocFWDsLA5FHdgLlPUSXHT90XiSQsKCBiJrXhGhOM8egFxWdGJiWo2fxdRT9+eR91Ut/+ObivTANcPmdaK6f1/uEBWeQlFsIxyJONnShcSlfK8cmLJr0jht5j9DIXpupqWdVdZwHB0R2Z9z4JV9XX+zILo45vvRDwP2Yr1fteGU3PhE4x6AJdGRajsl0K14I6I1C0BFeubpboLsJF81uAiAQQvJJ7MIageRWUYRbszLuF62gA4pnrEI/nwSQ3EqMP1aEAq8Vja0bgW7icfRPLLoJkNxI5OcSyRqYfsAKs53dzQbVTg4wEATFxtmZGiyVfEaizSiabgORALMUyM8kO6kxO71kKdAuAmceCoMXIEX+AcULXuSTj8TgcsLFV8KOgc3jgPKeZ8Wb3S3oXrOrcDk1UrrkMN7E6jS7vGMf5hdAdewH4ojeCczeFzBrgebAIciA/CWtnY7/nsT4E4nJJ2JwwBGeiwVkgF4pVMfc4EQrMPpUESLeEeoLmYPZkNjQ7Hl2IhkhTkjaTJkVrbt6C7du3JMJ2OHprYSugcUPgeRSoZ0Bo6cyblw8f+mVhHTAw/9Xh/ylGqA7gOe9l3f0zjuqAe++uAn0sHYW4VlVUuCdrCiezs4UZMtOKL1kt9HOPW7fZpednxG2lp2EqiU2b7nBtstnHn5EJrLfa4HcojngexQBsI2CXBpUr3WADIAMmL6rkD8jYhJKDbnWaEsDtdUIa4PkUpOJOmuhbjgLCJmHUh5i0mtRAsTIwr1WcTNRNDsXlp+zrGVMnqAvKIszWr8REo9+mlFDe/BP+Lv5eSS1bAWyc44H8pckkmSXip9L7tHsO0Dx2pVtnKVGxAKCz5VdERbOLwhhqoZM2PSaz5UsFeeTtwLNQRi6VL2l6UNfFDZ7YZjxj54D408lmn3+X3nPw0ebtV7ilJ+zm+RjhGF+PfsgDJ65tiCxrNcTupwb5+gnOhX/8x/s+L5y55Z/aY5XduMLgkxAs2P1m13z+6oGbZlUnJkIdindGJi+Tw1ffsHF35sQN5BoidTwe+mSm5LsuLnYUZQAmLs5YrL5nGP+GMjOo3bIi8huk1g91tRq7fnB1qs6vpvdwd2x3FRFAXcQNO3tJQ/VSUByrcjEO6SYtp/1ALwxt7Ebs/H/ZCtw821EDaLA4t2od9KEcZPV50TS8VyNnrFCDxqYvcsWUwTehL0Y26WAWbEDqg95o3cjQod2xAKE8xRuAqz4uZmtv0bZg7BkvNaHrKqvvgNsH3tsHgckt2Rvks3IzW70AoP1nAjA7iE3TtkSHhWN5IzXc4aaPTdwhaclWRpd+TWLH9kJlKcYOr124TjDi+dx85h/L84wVO96y42214Q+/+UE9ZFHds6NSJUSzfzOZb865rXU7Hu0cxJ2ENiRmS3hLgCDHrKZs6ORg26URVh2JTD6TKJ4LlAfBOwe0g9T78gK1GsVmbtAdqGgNgqQAaGNAkbweeXDEsFGn1Dt4WcW6CQ2TzyqBw5C8hz63CMfNxDHNfIzhW7iiZhsDNx+B5VbyhtaDXGdcNNTAfI8hd9Q22duNNbfaWH3LPIXCnbkUd+30LtoalCRmNPO4hy05uy1l1Ws3uD9tnmTQ8CgQDPsTUzmiOzddh5YnDYSo89YoKTXvC9Xb4WBbDP7UESHGTqtyMjQ1BU33V6Y3heFPdnJrO8SRJrFnUH37D0JW9DRpTyJZJrbOG/tRJTeMCGivE9UQNWATz26MdePZsYRgR0FeqJGCYctAtoFN9YeKv1S18sg4IP8wq9X7Xj13lF/RNjOa7KoqiMumACGLjCJ0KeqYyd1xAu7vBeQ3JJV2DusCCcG8TjnMnHuJO6cIbIbRCEwJRTBUPTdezr2N0uQQDv3aBZczEKET3b3+H2fxLggC7gRZzp2REf50XOyyhBhxaDDQMlP1oAbW6iG0KOMFGvVsgrtrZD6TkQ17G5uviEjM05EKAcDZKsqgfycN7Ss2UXVhwAC4aPdfcKAs49C1P/x5ib0hMFIwKVR3O9J9pCtQHbBBWH0HNF1I8JehYcf0yXEZT56VYrB/9Dr6H1a3RFIhsghQShQBLLoZCMJV8kAn/VM3fgZRrgxKBY+Jgr/SQoBEOfD3rDSH70A2gOH9df4WbksxFkcDY9lR+MDs5bx/Us+Z4S220UYCi69460XFAZtYG9H5pIIu0t27qqhTnD8FAM02E7oclLeCxH65ON6zcKlh+u7iUd96KJ9l4CwfG1ubCETh67S3BBPawTL60A1AmHWQdbsirFoASvQthrKOFRPOqiKm2FIIqMzwoOuUczeCwLBsXtFEFBbhW7PAo2E3CpCr5WArCJqoXmvyDYKtqO+tNenNgc0JpeOz0PSioNZK9QHGBIUfAIUL+42pnYa78cTDzuhs4K0QPEiGgdEWN0nRGpcwQ0dKpBlm4eBjNTLlnp4/vPXpN6ya9cVO99kJeAjeUX4mDQSmeXNPoZ4KZcAUBjiuNppHKckd167XrMgzC45E949vINfv6zjZx3fq3QobhbVYZwxdYRD2ilJAapmt9W7cyBSoYXlxWnWIjL9otyg9yqM7DqzEWgWAXbskF5Rj9ebQ/c+ktuHgqbYEfITsdpUNbvQ6YdcOPvOwqy4UPOiJwXcj9ywQdeHXCjTWy4og3eoBvbesZj/phlo1+2M3qO2oJVYdcr3GgTIihwFZJd3Ny8Eb7hmwY2gnd1lyDULburTT6JJdxoweoFhHnjzrbvNyWUBo88EkrgZ9TEy3rCCbk4s50Nzzr82j3hj3xF8BEQtITqB7JzxLz7OWrwB9EbFuQo1US4L2D7i4jP5UGH6Hm9U0XEj1xvFxIirmG8ogfmHkRBiopFxuDMZT2/pZJKe68EIuRsHZv+VkgSNNrKATRjmTv3r602yAV5D0w9pxp0s+fyjZ5wFqpKQpRv7aGkVySyGxVJ95IaFE15g/TrPY0/fv/55FmL5SwmzUiTe7Fls3nBwM4vdQ4f0RgJjBzdxcGlAsl8hGbWAAI4P1nh0/xpvPjrHvcMlzLjF/HALO7cInQQOa6gLg9Aq7D++hdIe47yBMA7dQQcx7iAaCbHScMsE7rDDIEcoFfStRnPgoNcSbuwgK8VNP2oUzY7dUHmfxd7mMeFrl3JT7GdtnP8Buwce1bHH9B2FzeOIDnTRCUhxMxMOQ1yUm7IzpL5WIn9JicXhPwnYPAl3G5WOTM/Ax3QZPxu9I/HLTsiSFoHSHxvlRS4PaBcOLmHRu3ndo50C+lajOvGc+Wa8p8oTykmYdUjGs4r6Q3Ojoun6ndF2f9hxGNamZi9g/l4Y9JFf7vHfrAT2V+8dxUM1rNzNVgwkB4AdVLLmDKCbsmsYuq6ojzMbCoJpYssLr+8meglEt3AQlkJhVXG2ZzachyHCiqNnXMgmn5Dq7HJ2Baz4BZbf8Lj5ucikjKQVEbuB6tSTcaqA5ELTwSLOhvzYoVkEjD/jbKnvOp7/ccVoFSBqA/l+VU0IKbuIXYaOzi5bVpAksXAu5nJ6eSarWDHPudjKFqiO6AwCQRnD9kFAu+fh0jB0qJOP7/xRb78VSSMLdqx6R7KHueaC6E0YBvp27hhdc6OGRcePHXwCHPxjMTi8AICdOi5I48iwa8Xg5L95kxIWW5CYIDt2D7JhRBXTDCQ29wVcxlSK3QM/pGd7wxlmdYCBaEJ7uzAI4W0RUB/yvKqd5GvoO8cRhtlaesPrpTwBdvdIEspfcLEj01hAbwREe0ecstEzVVqeZ2njDKi9g8B7FxpV0SWkD7fNX0rkzzVkI5GcG+RnCs2eRzZuoLaKpJbSwDYK+ydrGOWwqjK8/9kJqs6gyFs0rYbQHjIjQcUddFAFIYIs6XBzNUYoNWG65xmQ+2GDwkYDtSIs+lwNNnBBAPkzjexcQC81CxwdO1vHTrSb0ipN1hJmyxl4u+DPScv5qmq4Udb70fXmUkaYmJ/z9jHhwvrEIaiA5Eqj2efr6xYO1UMLO3VYP+JcsIuEkR7y1nGzTVa8X1TdF6MiwpJiCN21EQbNXyrsHgSs36S1mZ06jJ4DyYqws9mI2LVzU+2jjKpjyqIGizMLLL4vhoI7u5DILtjl6fLu8778w5bWel/y8bOO7xU5XEp/zvSGG4tseyafiN6IkQ0mw8DS6qNH7oyTw2AGzNmKp5bGA2orUR8G7E4RiQyEQrIzwndFtE7qH2N3j9BG78ZOUbocXCt8FC33xdXos7t8Njv1dIgfsxtDR03R+k3efDLSsFUt4DPq8vIX3GBlzVw/4TjPyC8irBgZdboC6mP+DudKPWvyc0xXQRgQiJZpVsCNPKYfCXalazGwDOt9diwUI4dIGAmDi4WqaCCNIJAs5VAo9J9Zz4ILEhA1tWy33yQLY0jVrqMpdPT87IkRquJCm19wbiJbyXSOrRjkI72bSTeJ0F9/3iLU1TuB0LicC95A2/c8p2bXU9w97NTBThy9VieOaRiRwFLGzDlX9AkLnA/3MHI3ppg/u6CuS3QCosPwPuHvuvLeHB3gZpqfsaDrJmEoCpr9gDYarNuJR3XigEmHpjKEQnPihL5VcF5ACY/Vp3McHq6QaYsi6aCVh7pIIGSAtxJQAXZrME1rjNMWo1kNtVaQkw72uB0Yn2orEXIHZA6ipUkAr8vYuSFqKWVgUROZvt3U4+HforYymJ6lCSBqPEXUTm4fsDhM1jEaS/daUCZsQCBCvYQg7czBrCPCUgsk1yQc6aUaDCfMVmDzxJP5Le/kTr0Hq82pA2wXPkac3YnW01u+KRoeROLSikVQb3/X+3X2a0jQFMcHGZm1cz5mMJzlbR7x3/08t5tGl6RYVNlxgNpoTD7+8lmWP9PxvSpHIC29vBciUxBIloqMzgpIbhXGTwVT1y0Xs/KUi3+65MKTn9OeqHghsP89oHimhpigwWk/6n762VY7A7q5w+b1OPtw1Jz1zhE+6Sn2ZEEWz7hh2pmD6NhpdVOHZp8XfLJiV9onOgQTUDwj/CdrMjRpnMsNIL2MM5LYGeiSTv/pNTe+zRt8/vRKIsioB1tLjD4TA4mGIvB+9oghmUEEElXSGyB/IVGe8obkDAIDK9IsZeyy+FomH7PqN1tET1QMWrbe3Du5Jtzj9zpq/TThJhpye5gbzRlmTrd6V3g0C24KsqO1VzcF4IHNE7JOyRKNOXAHAWYpB/cemkdLNAcudvSR9NASQq6PwgArplec8yGySX10lIHhuddbekuOP6AtV3UcFzcT0B5bpFfxmluRlt/OIumnIgu32ScrNlnzcVVN5uLsPYnxp9yk6fwSM+HinLmnuicrge2bHdJbEY3BA8LUAmMLaTyClYTLS4V8UgONwoPpCjdlgeL+BntFCSEClrscSnnM375GklpI7aESB1VYzNMayzLHJGugnuzgrYTYavhKY7AOu9EIHQuE9EZSygOe22afm0e6jOzcrN+wBT77VW5Ko6f8v+wKmL6rkNxKtDOP8WfcPBbvsEjzOs6CUyIRdfTulK2IhDM6y+xec7w39u3QrQdDyJDzz4DZ+xIhypKCog5Wl7QRA2jinizloOGsj9xADpIdPxvZclZJ8lcY0mDuUKO+eKbERARg/zdISLPjAFWyq7NTT73njMzO3kidcLeArFnEVcdfwXIZftbxvRIHsf6AbkGcX3ZciKqTMAjE6326fdixh97yZoLnopSsCEfs7vPnbr8u4FPOAPvBdNAcfENwA0uX/Lve3onCRy+5yG4ei2G2181iNTgN2D0Kw+Ypo75OOJoE2ywu5jIM0TKiFcNz98G2wcSNoibDtA9wdSmF8b2tk6pZ/faC6ZAEVEe9VyTJKL0BdW/GSwslD5cTtqxOo/5J82f0VnJh24uJERGSTZacWzZ7HuUxoquFZxVu+Zpl29P4+6w6QEiPItppBUXv05723RM7epKS7DchHQb3DbPjwgfJSj29EsgvCeuqlh2GHUehdMv5n1kTMpQdSH5oCTdVh7HjsJFh2OvBokQAnRhkE904+okGAZd7NPtcBGFJQ28W4U5ekMTi4YLnuDdMoChdDBBzn6bADZFIhGzFQMrq9WB9QGm9z+KnWzjAsRv3VkIoj3xeQ8w6pImFmrWYpxWOxlscTHY4yrbYz0oUWYtx2sB5ifq8wN50B6U8tHGwXqJIWmzqFO1lDiECwqyDSDz0OQXqkOBz5o7JBI2I1nVi0MrZIs46o84vaMBsJMyGXqf5S3ZM1RE74mQlUZ4SKtzd48bYHPrY6fdELDHA0UEH3PuvOcPsWctip+AmDqKRcCMHP3JMh4+ENp9Fq8CKCFFvJO7GJEX164lsBGQnh04zWXPjHb3gaGH0KZEIOwrIz8gh6O/rdh7iWITXcnnMdcfnTKVwKQ3OOd+902z2YchmzeLJawxi+i/7+FnH9wocQXNupEoJ2dLOKz9jIjQtrMJQMWYXCt0kehSCF3V1wgW4OIvJzKKXBoTol0ndXm+71C64UKXXYJkW6OW4fcTuqZv5Qb8E8KKm1yWrWbNUSFbRsDcJgygdnjdwdRIH/hKoTh3mP4w3VpRHCPs5l/4sdnKlwORDGRmhDM8Mqs/2C0iu7xxNujE34W7csy/jzX0tqSeMc0m9FUNkEh1ogKN/yAUnveFCl18Bez+gsDm9kbBjmiD3SRl2FDD/pwpec1DfjQlLuwTAbYLqhEQUO3esiCtCfs2CnZGJ2io79qR7W4GQxs0wQoWyZtdRPraklqvoddi/pp5afkn41qV0ySBTM0LeEx+zCWNqQxqiHovEGNlKdPuWxJ2Em+rk00h8WkmiCh+pgTLfW7/ZMSUdmyfRyWfqhqQL34vT4zzZTj2q4zD4lrqC57I3CW/3ydhMLg3yM14faqMgtop3d60Q1gb1mrujcxJKO9w0BV4b3+K02ECKgEJzgHqzLVBWCRCATZUhBIHD2RalNbi6nmCa15CzOGytFORSR9E8LeRmP9AQKrJ7J264dlzGz6c3iQgyMKdRBTRHlvM8E1A+cGj3WKy5iRus44Sj9nPyIU9Oz4btI7B8wsJLOIFP/3VDxmgjKEmpBPRKYf5OXO4iZO2Pm0GA3xtW7x4Sfq5OPfRGIr1meG//+cv6jjFa7/Pa3T7gZ1sfEAFStUB5z2H1dY/sOuYctn1qBGU70lLjK1qSmsjmZrGg6jtbv97Eu0/w0BWGkOkvdb3Ez+QMr8QhHJC91JxBLblIVkecDzWHJEf0obN9ByctA1LdiJqozdcc1l+Lw/Gp4xwo4cXuDSEqO4pV9oTMzfqIQ+u9HwCLH0ikV7SZ6m9eYQXGn/Bm6IMlScTgXMzlAWorB/2OrsEucidiejgv+npBT830Nho0X3DmpMvo27ngYq0rDI4vm8cku7TTKM6O0TV0NOEcrptzY26OHMkoKZC/UOzsTEC75wbBOvPJgJe/jKhTYmW6uw+c/36ec7Oh7q9PB9g9pKv/5gnnXr3B8efNiYMCyocO6RmZRKMX1GLqUkC23PBdRqPjbsIFQzQysl4D2kPLpOw9j+JTjWDYzfqEHYUtwjCvgYgLq8eQWpCsORceWJcx1geBUJ1sBJJLdorjDzXqe5ahuyuJ1dcpv6BLv0d5Lwrcb2hKYItI+FAx6SEQgucbp2ejHQeG4t6LRIbAjrVdEMJVbZRGSF7P3YznYPd2Ax8LABEAudSQow7msIaIkGdmSFQ5ydeonMFFNYIPAhPdwAeB1/ZuMRnVOP3aFbpOIc9avLycAQCKSYOyNUgzPoYsFcRRA4wJ0+ulwurbHdCQPQkbIc+JAzTZz93cR/biXdFYfKp5D2Ye0w8UZ24mIHtBTJPkKKB4cbdcyVbAjR2aY0c9ZCURph3aAwtVCnQzRz1udEvSb2xR/soGMrPUGE47+IYFFApH1MXT2afZI5IhO4HdY1ri9bpdCG5S7TxGKLVx4zUYHJhoii5h1pIQfJzD9nFY7SJa7GUBxXM5/E4Qd/e3T+LakjBsGoKGBb2Y/8s+SG6RX/j1qh2v3jvqD8HqEujndXKAO0UnhioRiJV18blIoVhQiUhRN2uyDBH4vWRDuGb6kRispHzqMf0kuqBUQDsV0GXMulvKAbaQnUB1Qsy+h76CoX2WbO8Wf294wTdz0uWTFYbwzuxSMSTXE2KTTbwBHQkP6zc5sIeijKEn2ITYpfiUMKnouKHaCYkIsgXGHymei7W829THuJNX3KrBds0VHtsnjl6YCY2b23lAF6HIfr7pUuDk1wPszEE2coDrhAPF0SmrbAh2Sj7zkPH7PZRXnbAzLZ6T5IPe1abhnDa5lUC00WIn5OELh/IRN/K6p5fnXDRVLQbPUJ+EYfPT0c8UnucN4g7apbm4R34V9Zxzj+ooIHuuodcS6XU0OLihrjBZSiRrFiSEQjmX7KUQ7cKjm7GY8HERB+g41F+DrgjRqovdDB09oh1YIMM3pISipfHQKwU/txAtXU2EChgVDaQKENpjnDa4t1jBCA/rueF+tN7HbVvAOQmJgHvjNU5GG2jD15MVLZZ1js4q1C1dWnTq4KYWwQPSOGCvhV1QG4icHp3QAfWx4+dSKsiOEhVdkq3YM31lG+81Rz9XGTVzfRYjED1cx0BxHgZ5kPBAMJ7X/dxCZxayf+7MY/MNepaFJMAHgSzpEKyEmTe8l2sZPWADkhtJFGUncf//05HM5QHZkGXaO6joCpHkdGc5R79dD5d5yPpuDemmZDyPnwpCrbHbTZa8ptMlXXkgABg/CPDn7/IBCO9z7tjb+mXXn0ts+FKPn3V8r8TRu2kExQUzSAxmtge/IQbzYL0TMWKEMF17wN2S1RXnS+NP7wbn6TXFxNLS2Fo2UbzcSlz8PhIptq+R7bk7oatGcxTxmAgXjj/l62LKdryJok9hUOzKejhD1VykN29Z1Adc7Js9T4hLc9FsTix29+MmbiK5xHAx6aacI/iUUI43fpjDpTH1efKBgtmSOahrfr/btzHnjBtWP+9r91hd+4Q+osKxk1E7iWR1RwnvuxQ79rAjYPWYhAO9i+LwwKw1plIILH/eRhlEANzd3Gb6EUXy8EB+Qbq3ariQUm9Fp4tueidQh+empscdWXwJPTx7QkSQGCyqinNeL7MPgPKRRXPo0Ox7vt+po8i+osyjjzVavxEhUYUhZb6bec4/LV0/2hk/j2bfc+HNiSK4GZ1GhBOYvicxf4cuK9MfaiRXCsKxy5Ax0sfrALNWpOdHJqFw7Ewg2XXJKnYuFxlZsqWCP21Qv11BG4e6MbA7jemsxK5NMUkazE2Jb05e4sFohWla48noCuOswVG+wflugk9XC0zzGs5LHE222MtLeCcwzhu0H0/QbROojAQY3ygEJ/Hzbz1FPm4w399BLhoAwP5rtxCjDn7RAR6wcwuXhMF9pDlysHEhT24U2rmHnQS4qR1s5FzmeS2OPM7/UNQ8zgKQeBSfGEw/lIAT8C8KqGcZ7JxWZcIKBOOB3GF/ssO3Ds7x+OElDmZbFJMG+emOzF4ZUD3qsPo6PUqf/opGfeTRzT3NuCNjGILxRKOnnDm2M64h1T2P2bsk6KQ3IhK9eA26Ka3iZMWQaVULVA9thGXjBjnxQCehKroZLd8Ug3xGVTL6dPKzX79+N9v/UtfL8LOO79U44vzXRzF4O+PiCZCo0ptR95lj6W1cdL0YLlrZAn7ksPxGGGyy6hOSPHoTaBFwl9WWE9PvtX9Bxy6vFZh8oKKIm5CjcFzYmW8XhgTt9IpmtyoGZvaLbXqmBwcI6n4EJh9xfikiG9GsxaABc7kfcvf0mrBceiUHJmKfDG1HHuPnHs2eR3XCsNndGx3UhnorCGDvN7h56B09LYOMFlojVqPCkSjSe5QiUDtnp/SIbGecc/ZiY5tzhlrvYYi+kTv6mQKEnLt9C9kJLL9OI26A8gDZ8TxRoiKGc+oNUxt6YoywAq7SsMctF8GWcKu0nLFVx1yE1k+4eW0fcnEafRrF705ArRXqI+opZ++xM5GtwPGvIaZkyCFFPruUsXsRw5/NviOUeaXYbSYYuho7c9g+phclBKOc7CiKk+NsV1Zy6KYBRuV4Q8gQOiC5EXBjO7CFe99QEYDgBXyn0FznqJYZ8kUN6xSsl3jn7Bi/dvUYtTc4qyawXuKmG8F5LgdGOWjpsa4y7FYZOq9QdgnGowabXYbRm0sk0wbBC8gPqNQPnUBp2Q0ur8cIQQCJx9Foi8XeDlk0uBadhBtH9uPYUTua3HXdANmdySUlGCq6/bQzQsnptRp+DrWCS3hN0VM2kkUuCJEHFSATB6E8lPR4uZvicjvG5XKM3TrDJG/gM4/gBXRhIQ/ZCbqxBw4bJLeEK7sJsHkjmj9oGmLYgvIXO+K6sHvQGxLwevAp0Z38mR6KIBqne2QvNNJrgXqfxWhyyxirnkBlx1xjVMnPPrkV6BZxPGMFHvxXXwHWCfys4/uyDiHEXAjxnwgh3hFC/FAI8YeEEHtCiL8lhHg//rn43M//JSHEB0KId4UQ/9rnvv97hRDfi//37wghfuJ0V3hW9LKScUFmZS5djOV5SvafinP6fjMhGSaSO3rIMwDppeSNldLI2RYRNo109qAovi3vOcIWaRiezywl6qMoDUhYyY1exG5P8LF1jYHlGCTZp2YdEwISwinwglFBER6tDgFfOORPdSSu8Pvt7G7+pndyCKl1ORdTzg2iML0RuPxOFIxHmytzaYZ5pKwFlt/g+1z8kA4YyUqQgaboXMGZRmSNtmTp5Wd8HhEtqMp7DqNn7DD7dHdvSM5gfFP034yzDtg7R30KuPu5qB90iz0JRXYADDf6dgaGqM47wm4tIarZuxKYdMNmHSQGcbTLPQ5+i6LnPm+weMnOW9acKTaLKMVIAy7+ACv5du6HrEYXzbOzSzG4+KO/pmIxoCue/2R1x84t7zkkSxHd/alVg79DIdoFOxezItvJzh1ky+7ZJ4SK+9mTjIbhwgpgq4GdAlIHoQOslXBOQoiA48UaT8/2cNWOcbae4qOzQ5xXE2Smw4tyhm2TwHqJ5uUIoZNIlEVtNUIA2jLB+nbETe8iRXPSIXgBVVg0TqNpDITy8JWGLjpkyqKsEz63F0DmOJ/LPfRSk3hS815wRQAkZ93dzMHs6HST3EokSxnhQyIPPuX7TNbA6mtAmFrC+ApoD6lDSaYtpA6QKuBiNUHZJTDaIU0t5ns7GOUgJh2SooO7SeAqDTHukF4qeMugXLKiI0En97Shy310TuJcUlgxmKd7jQEGhSDzU9WUO+we8b17xfeRXUcLv5ydY89sBngd2ThvDwqDiYYde1y/nf2LLcg/5ggQsEF+4derdnzV7+j/AOBvhhC+AeAXAPwQwF8E8LdDCG8C+Nvx3xBCfAvAnwXwNoBfBfDvCSF6AclfAaPn34xfv/qTnlh4wm/C0j2BAuUwOLRsH98leNsisJuI/ojU+UlIy8E7wI7RrBXMrUJ5Gu66nYjDUwwdu42GwmmvIxSa9xBcpFjvBDavsdtqIjMMiN3QiJtL79ohW86Ido/ZeQhPw+vkJmr5SoVmL2D9ZpQTyDjDquhMYhcWZsdk8N6HsN9MTBSeE44kHNhDrUFgEH73j3f1e3kOm0POLtJrSYNsQ+hq98DHQFCP6sSTmCEDoAJgAlZfd8zJK+42ZtFGJ5OS79lOXYS46Ijf27mZTdzYUxJ4mn3OtXpLKADoTlq0ex6ookPNNcWIsqbmEDsNn3h0U4/20MJnHpOPee5vvqWw9z26m6Q3dAeBi5tWZPQ2+7QXCxKQW4UQ0+T7662b0E+yXcT5ciTtVDHItNknPDl6ye4gyACzYip5N2H1D0VihRt5NKdddOWPejh1N5fqbbZ6SFTWEn7RQcQCATpAzDqoywRoJGyjIaXH1csZNnWKX3zyFE93c3z76CWKokFpDZTwKHSH1eUEq3UBFA7FXoVdmyIEgbbTgBMophW8j3MrGaBHJIqkysItUyR5Bz1pIVXA880Mp/MV7HmO6ckGwrAowYidqkvDwOgk+1HCRYlQF4saveU9q1rKhpJbavySW37OduYgbw3HAypA1BJwEt1FDtdK2FKj3Rko6bHdpSg/m2CRl3j+fA9SBRjjILyAutWQFykTWrY6eoWSD9Db3+39kJ11OyN8LbdMSclfChx8N3psxk3KrFmodrPIOI7QrSIKjHqfXTsQU2Hi2pTexFFFHAO0Cw/Yfn7Nuf2XfQT8TM7wpRxCiCmAXwbwfwaAEEIbQlgC+NMA/nr8sb8O4N+Mf//TAP6jEEITQvgYwAcAfr8Q4hTANITw90MIAcB/8Lnf+eLnd1GftxNRvC7ivwl5jZ4K2JllVxbhKa+BvX8KmBUhxd5Sy84tkjWrOGGZjuBTD9lwkXeRhKEqAbNW1C8ZPr+IRr3dQcdNsqC9EinRYohMahdR+yUogDcbESUDxK58xkW+nZLy3b1WQ9VimAX6xCN/KWCWcpABCEfCgM2YHp/cMv6o3yiqh5aBpaUYcgldEhBS5t91c0/NVBoGGNinAaKlz2J96tDNfEwQJ4HIjgFIno+eqKPXEsXHmrBsJ4asN29IAOkh1aACROpYgCR8bjsmsac6Je1cr1RkvNJNJSQhykfEYLIsO4lgYwL5mt8Lko+ZnXHRlJWE3ijc/Dw7yPrIY/sAw3l2BRM0KCindjA/Y+Xesw4n77EIkq3gjDFlUjgiwQkyDCnzzaGjjrMSWH0tarJyDzvx0TdWYP6OhF7G6KpKIj0z6CZA8YyvY/yJRBjHluBzUi5dxpzCjsbIds+yY94YuKMWcAKhlRAC2D9ZIwSB968PsKpzfLzah5QeH352jNuqwEU5xmivxGhUY3a4gfMSl1cTNJ1GXSbYP1nB2qi3SD2EJlSYThtcbCaQkxYhCLhWod0kMMph3WQwpyWqOgFuE2BjIG8TCstnDvkLQor5GeUN3gQkV0y96KYB1SnnzOXjbvBA7cbcKO2I59tnHnkMq1WVJKO1FRArg+TCQGcWFzdTpKnF8VtXWNU5ZgdbzKYlql2CMCVTtYdMe39Xv9/Ba4YDy1pi+TWBw38UCVkv1cBm7qbA+gnDbLs5iSx6x3VIx0zN5Fpi9l7kCDSUnrRzQqLZlRjIdMJxI1RlhJ7XhHgBIL1WA0r1pR5BwHr1hV+v2vFVdnyvA7gE8H8RQvyGEOKvCiFGAI5DCC8BIP55FH/+PoCnn/v9Z/F79+Pff+f3/5lDCPEXhBD/SAjxj7p6Fy9CP2jqZCMHZtXuQYDoJOzEDRWYCEB5QhH49tEdExJe0A5q7tEeOIzOuFDrCkDSi6n5GN3cIVmRXRmSPhGadPsg2UnWpw5u6qJAm9Wd1/x5Wh8pdOOA4mVkeUa3e71j7hpUQHBkYyLwpqR7DOdfAOdpsuHGJ+2dKNfm7Cj2vwfACYw/pjsIVBjS3SlCZsfGWQUG66g+YiUIPr7ZcM7V7FFn51J2eOktH0utObujXRlfp7nhghF0FHBHeDkkHthodj6Wi0CylGjmrLj7OVB2BXjjqcGyJBrAgxtNGk3HWwF31MFOSWpBiCzTA4/m0JE9mvK5+8TyvuPvC6Ug2c27lO+7OI+dFig23rxOyKtPh09uyb5TLeenjMbp8XJ20L1OsJuEoTCgrs+jPKXQv1/88zPOi6rTmMa9x5/vTYrNluel16QWnxq+f0W6PgKAnQZSD1kqVLsE1kmsX04gZcCuSbDc5fBeQhqHzSbH9WaELOnQWYWmNXCWzNDd2RizeYlpWrPba/k7vuWi6J3E5raAdxKTokboJCZ7JZ6/XGBbpZgVFbrLDGHEAkB0gNgqiMIOTOjqhMLvYCjDGT+Nc9VGAJ93PolcsXYvZixGA4f1mx4oaCHnZhb+oIU4aGAf1rC1gVQeRdJCK4f1NkOqHZbv70FqMmLdYUtYs8+YTD3TJOIcWVqaKJhdQP6cI5TsMlrUNby3zIYSE5dRO2snfrAqbBcBq7eoX+x9dLMrvsduFJNUahqa98L3PgHEZWFgQvcd5Jd5cKwsvvDrd3sIIf7tOPL6LSHEfyqEmH/u/37kiOvHPNYfF0L8jfj3Py+EuBRCfFcI8f04Wit+0mN8lRufBvCLAP5KCOH3ANghwppfcPyosxt+zPf/2W+G8O+HEH4phPBLajKK9lN3LvpmIyI9WFDL00V4MrDKGn/GPLRmj9W7iQuV2ij4nIslAnDxiySVbF/zUGs1xBrN3g9AYVEfe7iFJZvNEMIKcfDe7HOgDyegd0zMFpaVnLlVAxwLRfgwveZH1EOCdkz399BJiqRXvOn0Vg1WSaKNurwN55i26MkP0ZGiCLj6PeyAIIH1G6xe8xd0yhe97+g1hg3DxwVfNVyce5FxT8rRWy4WquFmV556lPc93IQzkPbQwY14w3ZzFx0pAtzEwk6okVRrHYk9ZIvO3qVGTbo+sJbUcsK13KwhufjptYJoJZIrHd1VBLKPE0LNhb8zfW4F0kvF2WIMew2JH4hP2QtN0kKBIbuwvEc94s3bJML0afAwHt0IQGAIcLPnoVqB6vV2KDzcmBuvuVXopuyue3/Q5EKz22vitVAEVA9s1J7KGP8Uw2gnAW7kMf6hGUyKd69xEzEbFkHJGlArheRZ7KwApJcKIQDquIIyHrtdhmS/xnpFe7Kj2YaidE1kochalHWCapWh3qRI0w46cQjao2oMPj3fh3xvhL2DLfzGIJm08DcptHZIRi2yUYvlukA2r7HbpdDnCbpa4+p6Qgu1jQKOakLGqUcoNbZPHMqvtXBjH0cKEtWJx+5+YJSRjISsrRru1aAZGySsQP48OscvWqgrQ11e4iBEgPo0R1gZSONgWwUXJJpO497+CterEfLHawQv4TuJJO8Gc/egAzCyQMsOv3rQxXvH4+L3SjQHLIzLB1HCM+X1XJ1QayfjBtUXT7P3ec0ksVBqjyxGHzGeqdn3hLYXGAocn3LzD7HYc1mMVso56viyjwDAevmFXz/tETelv/Yj/utvAfh2COHnAbwH4C/Fn/9xI66f9viPQwjfCSG8DaAF8Gd+0i98lRvfMwDPQgi/Hv/9n4Ab4XmELxH/vPjcz38evX4A4EX8/oMf8f2f6mAnwXlIs+8YB1Jzg0hvJI7+ARe/5tgOc7egwyBTYORPgF5q+CQyJLfUWhUvCBu6sUf7qMH6DQF5nXBhlAEqISyV3CqoHZl9UD3jknq3ELPl2jkjS0bPIqOxov+j2RAqIWPMoz61sAsLCMJn3ZQRSj7jTVY8kxCBN0dzGGHVuHGYmCdo1qwlFt812L7mGYQ5iXT93j6tE9i+Tt0dhbUxoiX7nAPKlYTZcoOwU8LIyRKwe3bo4IpPFewk6ssMFxVZS/gZI2z0jSbDderg91s6wFwTSlz+nIVPSaBpTi3s3MIWwO4RQ2mTa8WMQCtgJw7JjYpsu4CQ+WFOkl5ozlAilNQ75biRR3tkoVca0nLjGlxFOv6Z3gAHvyFQnZA8I2KKejd30Leac1MVsHkSU87HHuraoNu3tCa76PPpyBAWjpU+ReecT9Eejn/qpR66yt7tRXZAElm55b07xqBeq2gnRyh8/YaHO+iYRhIA5A7NnodoJbpNAmMs/BUdXPJRi7JK8Nr4FlVn8NrhDZTyWOQlTmZryNTh8YNLWKfgnYAed3j94BomtcA3t9hWKbKXGuGTAnKvQXmbI0s7ZGkHbRy6RmMx3+HwFy4wnVXwjQIqjbDXwtUaKIh4oJVchVoJc6ti5hzvi6CA9MwMBuNmw4T67JrXkN4ouKmNhtcCvlFwC26U5rMMQgXYhzXSkxKvHV/ja/cvYsfnsW1S+E5it87gaibQt6UhC3y/4TigjKaggt20H9EKLr0BCUieyQ29/CgYRKNqcTeDDCTubJ4EFM8ETMnOPz3TcAXo/1rSwaVHAoIAiucS1bGnFtOxEDJruiAV5z+y7v9dH1/ljC+E8F+GEHohxq/hbk3/kSOu3/n7QohfjR3jfw3gv/ejnkMIoQGMANz+pNfzlW18IYQzAE+FEF+P3/oVAD8A8J8B+HPxe38OwP89/v0/A/BnhRCpEOIJSGL5BxEO3Qgh/mBkc/6PPvc7X/z84m7GdvCPBcySFk71YWTzRYf/i993Ry7xCau83uhXNpQIEP6icBYyoNkP2L7VoXxAv7/8mYI+S9Du0wfQ7XfIJg1soxEyx0U0Eh2QeAp5m16GwPy9YLh4bZ4EjD7WkJY+ot2EN4oI7HLUNtLtY7aZqvjaZU29T7NPmzH+H8krfe5cN+Zr6Cacj2wf3HWUbsS0BniB0VNCdLKRg2yj1/7lF9y4hSfjsNm/05fpEtwsd4qQaeJRHwdMPpJ0SQkkp/R0ewjAHXQI8w4it9DnCVQpsXtiOd8IYoAvgwDQSXQHHUX3+Z2LDMC5nkvDkMwOQ82h3bPo8+t6AlJQd0GiasMuW3TsuoQjFNyL410GeBXlLQ2LpPI+Ieb8HEM+I8wdAUWXUYNnqAVTNYsZtEwl8LlHeimR3gKylNFGTwzho6oi3OWygPGnRCHaOTczN7WYvcuZH8BF04495C5eF1vN97vfQK4M3YhKCWEC2lYjJB552iJLONO6akbY7DIc5VvMRhUS5fDx0yMEJ1B2CYIX6NYplPJonUKzyiBEQLtNYL+5g79fw5Uao70SqbYoqwRKeoSrFEoEXNxMIUWAuTZQsxYmtxAyADsFc6OBscX8e4qf7Z5FN74bL/QQXzdG1IzSP3f9Nd4r/NwkIf+MBBVUvPa7OAaQKsA7iYOsxLZNcbsrcFRsUTUGvua50pek5iZFB5E6+FoP8zXkHqoCqvu8rs2G9oHB3EmQEKHLXubTLhxTGyKrWpf8TLePPep9DBmfXa/Pk2GYcataxOQIXq/dpP87olRJYHf65ZNNfgpW50E/Ropff+F38XT/YwD/Rfz7F424hkMIkQH4PwH47wL4owBOfsfj/RkhxHcBPAewB+A//0kv4Ktmdf4vAPyHQojfAvAdAP87AP8WgD8phHgfwJ+M/0YI4fsA/m/g5vg3AfzPQghxko//KYC/ClYDH+LupP3YI70kA2759Uhs2XCmZ8cBft6hm1FDQw8+bkRo2JkUzyl1sAWAEYfwbt/CHnVc1ANYtQqgerNBt28RtIesFEzRYZQ3gBP0Lfz2Fli0XHx3CqoUcRZF+nqylFBbGa2s6OXXHjh2eMduoNH7ghutudEoXsYIlAnQHnZk/gWg2+9Qnzr6hl5FyrVmB2PHbtgEZEyCqO9bEnI6djx6K7B7SFJJ7xuYXfNGa2ecT+UvVCQNhcGCSZXMNQSiSPeBAzoyDbe/VKFdBM4qMxJ3hAD8vCM0tdMIOwN71EFGN5eeBRtkQHpmoHaK89SohXJjwptZlJkERSgwjxUyKoWQeKRnZjh/fUp5N3Xwc8vNvvB3rNCJR3McyTWKzvnNfsDtz/lYeHBRCyO6kWy+SSFyeisgdwrZM8NOVzJ/Ln9JlmgfJCp8tKRbUYqwe0SI1434GYfUs1NMA5bf4v/V+8DkU0B03Pzypwabx9EzNBqIo+8QzR2k79eEOl3sMuEB1ykmoVuFEAT2JiU+ud7D/nQHHySmWY1nyzmCFQhe4PzFHMZYiMRDKY+nNwskkwbeSei8g73NaIJtPJyX0MrDvihgtEMYO9QdJRBKeIzfvkGatXBWwpwlCAmJPagUNo8DkET0wwD5GWe+AIuu+bshpsrHiLEuZkdG6FzWEuZlEsXmAmLN7iwEAW8FXMdl7uWLBb5z8hxSBOyNSxzcX0KoAPn6Dn5m0SwziJWBXGpeE7mDMA67N7ph5gYRXVryiChYgexKUjrVEZJOrxXqgzBIL5gcQoSpOXTIbnh9uamLMglufLQ+o9Xg+nWOD+zIoz5iXmQ3DkMh/qUf4Sd2fFf9GCl+/fuf/3UhxK/HzeevAvhTceb23d85sxNC/G8AWAD/Yf+tH/1qftvxDQAfhxDejwTH/+vv+P//OITwHXBD/B6A/9VPerv6J/3A7+YIIXwXwC/9iP/6lS/4+b8M4C//iO//IwDf/ud57j7LjoQNIAhCgLLlwqjPEwaFprQby18o1IeE5FRDtlg3iTZmMsBc8WZQjUDzjQrCSYilQcjogShqCYwcsguBvbfXKNsEjx9eYt1kuL0dweQW7TymVRchskW4sDeHnjOgGR07do89kivGlviM1GmzFUifauweBC7cRg7aMLfVkNEGS601dIwWavbvqPBMGJA0mT618ImEy8hS7E2VdUkdXC/Ilx1Nt8t7scINwO4NN2gBAf6snTqIWrJDLFzPS4GatrCbBB6AUGRBbh9zs5dLfWfAO+OGJJRH+6BB6CS8YWgpoKBqIAgBn4r4+Qi0R9FhZ0oGoB2xAm+npJlnLxSq1wj12gzstLcqQr0KzrLDQoSRBtMBEHYGyFKtDwid6o1Ee8wFUMT3nbzU6OYe5SOH0UcKdsx5XE8iciPCjAgC0x9qwqGFAxIP6+7ud2Epu0mudJRnACgc9MsEk6cBN98CTaoljayzc4HyNQ99Q7eQIHgNo7BAo9A+qYFKw08tWb0FyVCzgxKrZYLFqEJrFXZNgtf3r/Hh1QHenF9iWed4vLjBmemwqTI0pUF5W0CPWrStRpp2hD6thKsVkDnARUlBq6EkZQmr2xHyeQWtPPzWQO0FXC9z+E6RXXqvgb5IyO5NPYr3FXaJHHSzIcZ+hSgFuvpFspNGn0nUR3EckQQkl5rEqQkLkeP/r8bFr7TATkOmDul7GapHHYQOeLad4dHDK5Q2wXVdYFOnmBcVrq1Ee5Nx00wcQkrBe/G9HOU9jZB5OhVNLVy0WzNxjWj3eJ3YMfW0QVIPm6x4vbaHnOeLyDr1tYJsJLYPSZyRpYq6P254ozOa6ffm2908agRzj27PoXiqaNSefPlQZz/j+xf+/RD+AMAZH4A/H0L487/zZ4QQfw7AvwHgV+IGBnzxiOtHvcSf9BqCEOI/Bxuuf+vH/eyrp0yMB51ZKGYtTwK6mRs8JGWLgfDQTgP0WkULL3Z//SKKOOvBTv/2qJBaI7SEqJB4CH1HPS4fWzyZ3OBfvf8+Xpvc4vZmhLBMYJ8XkIaVsJtYdoK5G2A2swE3UcGbpJtRr0ZqPBfT3QMyL2UTN57IVkxuSXDo/T+DZG7cYPoseT7Sq1gttuwuZSvi/A4xPw44/A0PEattXYHC+yjXABjkaZbxslGBg3ZPy7X0VgClAgQZja7SSGYNkqIFArB5nYSG+tTBp+wq27kHfKTGy4D8/ZSL1rm+015Glx1V0vWji476faq9y5gazwUm0PKsBZILg24Ud6qo54SIOipPEb7oi4eCptd91y2sQHUcu95tJBjVhAzTWY0wchEG5We0e+QjvT7EDMEQnXcC7MJi/QYty5ARxBBesBttJWAJ6/UyliDj7AtAOyHt3ce5c3pNN/8+tb2bOfjcAyag3zmCk5BbhexTA6EY7QMAnVUQ8xgt5BQ2yxynxRqTvIaHwKPpEq1XmGY1spS+lvm8gtYeo6KBkgHtZY40a4EgkH6aIHlhIDML10lIEdmkTsA5CeskJsdbaOWgtIeQHiKhT5eLMg7IgO1jXnM6mnfXhxwP+CRg9BnTyFUZN4Wph6pJYnIjfj7JDWHeiz/Aawg6IHQS9QMLIQGIgFWZ4enLPbx3dYj9rERmLJQgaxOJhyosxL9GY4oAAPx7SURBVMpAGU8S0DdahHlHYwQJiA1n0e2UZLX6xLGIiuGzaq0plcppgtDNPJA6JkwkzKbsppQ5pLe8h0dPOXcPE4v8TGL7poWNXV2yjPl7OwG1kdCR8ONyj+ziqyC3fLVBtEKIXwXwvwbwp0II5ef+60eOuH7Hr78D4IkQ4o347//Bj3mqfwVEBX/s8cpufBD0ARSO2qbsUkV92p1f4+4RF6nxU8JO9T2L5KZfUKhfq4+o6bn3dynybg+7O6F6R+o/EOAOOwQrIAoLKQIkPFJp8e3XXkDtN5AnFV3t46Kqcks5w4Y+jPs/sJA7BVWR8RkE0xekJSnHjv3drMpHI18dZQoJN/A+CLabO7jPVYXpjUQ7DWgO2GWq6KdpZ25IIed8MODFH+Mm0jNYXcEFKigmhZN6H0NmvUD5tQ7JlYbPPJoDj/SS7Eo3tUg/S9AtU7TnBWdOVjBFYcfuOIwdQuYweVchdBLBCyZOvJ+hPrUIBw1c4VE97IZAWoAuLOm5JqNSBLgJ5QA8J9zoyvse3dTBFT4ahZNVKSxQH9H+yWy4+TULbhrdhOw6xOiq7JLv1x10hLKTgGAFmnUKmRGSxNhC79dAQsNpl4fBgcNNHSABc6WRXUg0Rw5yabD4hwnMFS3hZE0ShPCcxTX7Dse/LpA90/CaBB94IFkxILU5iIGuVzHoVYAwsBd0qrGC2rreIFp5tA9aCBPgvYSQAesXU9StwWxvh/NqgosXc3z37D5+eH6Mm7LA1W6ERV4iWAnnJbpW0+/TSUzvr1FejCBXGrYIaB828DcppPJ4+oMTiEgGcVZhV6ZoOo1NnSJ8PEKomDEkl4bX1tgBNf1J3cxB74gezN5TqE9oZOCyON8U7AThOPPu9uwgRemiZEU4Af0s47xvw2QKdALYGFRbknomWYN1m2JbJwhBYH5/TZPtEAtfJ2BbBXVtSG6pFcLYDiQ3N7U0Udjw/mhOLHof3t5gIbtkQgp2Gmqtom0hERfZCjQL3mMu5/xOXyToJkBySSsznwDJhoiBLShj8LHjJ9T61SyZLsgv/PoSjn8XwATA34oQ6P8R+IkjLsSfqUEDk/9HJLd8+jse+8/Ex/wtAL8HwP/2J72YV3bjE44eicHQkaQ+JCPLZazAk5WEWdHvcncfgA5kWn3OvV+0gp6UU4ern1PQWwW10RCFhbk2TGwoFZJnKUJH55HprMRNU+DAbDE1NbZdgm/cO0OSWDS1QTpuGIh5k0K0EnbqkF4rPP8ThK1c4ZHcRtNhxDwuF8kSSZRGmAB/0sAvuiHq5OTXIiwSLZR0RUKFL2gwTUd4/r6uON/TKwVfOLQLdhNBBuRnCs2+G5IEuLEDCHQgURUtmyAYnyS2Ct0JRdJmSfmBcFx8IYB0v4KYtYTHRg5hxtkaKgWxUxBWYv0tGhL7RiF/bcOFDkCoNNILNeiqoAOyM4XlL7WD0TSCuCOIOIH59xWSWzUQhyDjfDTqEX3Cx+kmHnUMNHVZwOL7fIxBk7dix4eJRfIsgejIvEMAso8T+JsUbmKRRhITMm6yZIJKuMMO5prft2POatmdSNy+7egTW7hho/ZJnDVK4PatSPyZOow/0DHAlWbnXhPqqh6ShNUjDbIR8EuSg8LGIEwsC7SNQWglJt9NUG9TwuNriRAEVrcjvHt+hIN7K2byZS2UDMiNxadn+zi4v4RtFdKshe0UZkWN1fkEatrBjR3cYccZmRWQ2uPk65fQqYO8MTCJRZp2GOcNxin1cXLUQaUO6bVgcacDkHKNk5VE9dCieKqwu38XKlsfRilOTBiZvafQHDuojUJ32lIYvmQkUX5O5jM2FK/7VkGOO4gA5OMG+bjB+XsHSJTD8XSDXZsgNx0m0wreSZjfs2R0U0F2sZq1EGMWq66IhafuZ8Vxfi5oHiA73qPmSsOOgM3rZB5DkEAWBO9TO2YxK1zU1WZxQwscLRQv+adNef36vQ71Ef2GZScZQzX5CqDOnzzj+ykfJ/ydHwVzhhC+FkJ4GGUH3wkh/E8+939/OYTwRgjh6yGEH8nfCCH8zRDCN0II/0oI4S+GEP6N+P2/FkI4jI/58yGEfz2EcPGjHuPzxyu78cETFsk/M1BbVpWyJSW4lxK4PGATnfbhaSLczRzswrLDAiGl5Eqhvm/ZccgA9TyDnTkSJjKH9l6LdEHjWK08Prg6wEfVAa7bAh99dIJlk6N9dwYhAGclsGhpSxYASIbAAjG5veRN4hN2MC7pB+gxSknzbgulhljrGFnj8fKXOc/LX/C9dtMYteM4UzO7WNEmgSnoEQ5UGwVh+XdhxcB+lA21gKOnkVkZuyBhxRAhA7AKJrzJAT6/yZle81qLZpVB6oDQKgjjUbzDclWVkqbZqYOIpBW10Sg3KfyiI3u1i8G9McEbwGAz53LOu4QHfOGRnZOdufo6H4v+oXzvvTONcGKYX6qGsxM3pk5w+U0P5I7dE6Jko2CxZKd+mDCYa0PKeeZgrgxsG7uCuChJK8jiuzSMpPmnCQlC5zRXVg2A0Dt1SPjCDYxX0dEdhJ8zAAHsHrJQ0aUYdJfZZYSx4+cBAH7igIwdazCeHqVjS4aqCli/3SFE263p2zdcaG8S5FkLiQDnBVLNuWltNbyTaDsN3ypUO3ZLQkS4uWURoDILXyuE/QZCAFVnkKctcFKjKQ28l6gag12bAA9qpHkHVytU97nZpS8NZt9NSL6qJPJnmqG/oyjCt2JIJQgmQO+A9RsexdNYDHWESgEgdHJIohcuWu3dGoQgIPYaVNsUTWNw+OY1EumwbVJ0XqF1CutlAf0yhZQ8b+OsQfJgh9GoRvASqBVz/BYtZOIgS8UNFsDh36eTUNBkmtqJR/mQUo0+voufO8+9bGjF140D2j0ml/RxU90oDKzWnnuAmtZ4uiT7RTWCSRdf+iHgvPzCr1ftePXeUTxE4EbS7vkBnvDzDu29DrKkv56710AeNNAPdwjaozvshrmdqiRGT+PMb0zWZxg7+ImDf1ghaA83cUhfGkz2SrhOITk3WK5GqF6O8HS3wK89e4wHr13h+UeHEK/v4C9TeCfhW4Vu4dgxZg7+oI0ekm5gAcr2Dmr0hacpds6FTxzXhAyr3otUQm8kimcSzX7A6FOB7JxkCVkpQAW0M1aScALlQ2rSmn12Kaqme0SyFL8t6yu5lejGnA32dkrjz+6S1PskckQGpqoJ0brIHlWpBZSHdwLpvIZKHcqvt1zAAdSH/DP7OAHGFn6vhW8VghMIh03M3BOA4pxRNBLTD8Vg/tyn2WdndOlncgLfSzDsFJIldZc+YYEgGzIwXebpqXqtmKV3JYGGXalaRYnDVsGcG1b7mRukJ3Zh2WlawFUaMlLokyXf/+4bLWQn4A9aVMcsqmR0Hinv8T3vHnoUz6jv9AkYXZTRyaM+YFGWXGiYtUS7H+eCrUR6obB7QMeaoAB71MLPOiQvDfKPDdSigfACxSca+pKvvafrIwj4WuP2doR2m0CcVGg7jbozZGQ6ibOzOVa3BWAldtsU2GqkeQd/m+Dl2YLXIASQe4hPCow+MlDPKXEoqwSJcjwnOkApj3qXoGoM0qxFtc7IvlQBcq9Be6+DzTBA1NXX2gjnC76XhkxbX/C+6FmUuycd7IQwPVoyJcfvm7jRBISppdNKS3aqUAG+1hCfFri6HeOjm32UbYLtLsVqkyNsDMSTHVa3IyDx2NYp2lojMxb5pEZxuEOwEmFrYD7I6Y3qeI9e/T7KHRbf52tLLyXgMMSODfmOgYVYetvLFQiz25zkHGGBg98CqqO+qCOiMvpIAZYbZRBAe/RVbHrx8gjiC79eteOV3fjo8+eBENmBLs7jVCQsNKwSpfKcyVWKbg8JGWIu9ygfUJTdk0DkRgGaTLXxBwYidbBvVNhcjwDBhda1CvnpDlp6zEcVXlzMkexX6G4yLhoBUBlnBv4+NwN5k9Dm65piZ+byBWRXEe6MzLCeOSk+zQEwEoV5ZXSCaPa5uW3edKhOSXV3I4fp+3JIEhAB3Pzuc+OVMZS3G9OfdPSc589Ec1yf0nRZV0yhWH+NlbibuM95cSrABM7BJhbphUbycQalPKaLEr5RKPIWruE5VpkF7lesgmuFbhTIkO1IjZeVgjxLCXfFK5SFh8XqzQB5zYW8n7XWJ9wYzAa4+jn6bsKKgfjSLAAEAbPuc/UiRhWNnmkvxcRv0XCWll7KwcQgueQm8nntmAhAc8T5jk8DRKTiTz+QUClt8OR1Ajd16PYtqmMK3AEgZG4oKmQlUb/WQi+Zct9OqdXySYgkJSBoP8g7uhmr/r57FRtN+7qxR/V6C9cqqGmL8hsthe2Fgx07CBWgig6QAcW4gcotXGmGDavpNNq/eQhTdAhOQuUW3klABzSlYSLEjeHMrJYw4xbBBJT3WDA2a7q3qAjbhQDsVhlnc0GgaQxlEgoMi90YjN412D2i7tVNHL1GUxY75eOOLktrEkfMLZmUuhTInhvOmOPMW1YSu8eOHb4AklGLduHhHtRER7yAmTawJy1+4dFzHIy3SI2F1p4d3cgRiQkCOu/QVAbqsxxVa1De5nxPAnRTetywu8spoUHMo9y8FollmpCk3hJZcnlMUd8nQlQ+pFzm4Le4FriRR/6S8+er72DI2kuWMY5pDiDC22FiMfrIwLz48od8IQDOiy/8etWOV3fjk9HaRwS4zJP51caBcyWw+xYNOrvrDM3z0TDb6ZlxMtLQu7mDPW1ipcv/N1cau2+2dG+INwQCFyuTd6g2GWqn0TqF0MaAysOSMFGl4S1Pu18ldLEIIDkiYvd95dpN+ZTCMU0BoC4LPYQ56Ui4UACswOgFBheL4RABy7e54FIHJId5BENf2TnJjjmB69fDkEye3BJ2lS3jg5IldVRmB5hrjfyMkJcIADq6UUAyQqmde4QgyCTUHiEAwVJfpoyHq/k5BM2ondO/y9etjIfPHVQlICpFevi1glnRhFqXhAl7iYFwYlgUmwPCsdJykwMIH/YbdHtoo5E4889gRUx/F7ED9rSpisSi6UdisBjrrwuzispxT+ipN8bGTiFIYPWLLYJnWLDPWHjNvh8F0Z1E8UKSBdxgsN7qUxxcxmRxJtAzpscl1G26EeFcb6i1ZOoH56gydZh8wHlmUkSzZempNwxcQNEo+E6hmFWoqwR2k0AYB6MdXK3RbBOsvm3RbRP0IZOLv58CqePs9UzAj9j1opNcKPc7hNxBdBL6RqPrNKpOQ48sgqPOIitatGtikCpC8zrChdUJ562QRFlkpaKJOs2vvY6s1cwjvRbY/z6vU9XEAGkbIfmclnO95rarNcLIwWSWTFIB+JcF7p/e4Lee3ocLEqs1E+d1YjGaVZCKc2djHPw6QfLNFZQiY9s6SVjV8j3pnWQBwNMEVwQ0x27wEg0yuiB1YtDXppeKxWIn0M4Dbr/OKDK9VsOcvr8nXebR7JEQEyQLH+EBuTKoD8Iwhvmyj6/Sq/NftuOV3fgQgOprbWQn8iJF7oDcoX1ER2mZOOTHO8ijGtlxCZU46AvSs73x8DpA7ST0WYLspeaNdmtYxXYCQnm465QLuuXCUOQNposdVnWOSdJgdrhBnrasng8biITzi8E+qyNZZPyDhK9x0sHvt+z+NPVB+Tm7F9lEiPF+jfxcAFvNxd9yZrZ5nYPzPpMtCECYALPkTKTvXBnxEwaRsN5y0bQTbpCq6W25PLqFQ3PkkJ0ptAuyXW3G81veo56qu9dCTDt0b1SAB+pf2iHMLOxZjvoZ7WI26xyqsJDTlpRzGdA+bDl/7QRe/Ao3XLc2kKnjXK3gQidbSg7Ulnq96iT6iUragMkOZDtGw+r+5/VWDgGtsp+F9UkTgp2XnXps3+xoyl0TRm0ekdywfoN2aa4IsEftcP4wsiTdNJFYUkkgp/g8/yCBKw09PWuJ4lOF9TctGbTcB2mPtaDpuU8C5NJQdD4is1htyfLs56x2zFxJO6YVW3NMYgkCIV0hA6ojIB03aNcp/GUG3CaQG4Vsr0JISUYKnUR5OYLSjjOr2wTrVcGNJ2blCcPN0ncS61+uWNSBvqDQAeKU37PXGYLtJRmUs0jlYZ2CSSxCp4BKoVrmmB9t4FoFf8D7zj0rIE4ruCmLjGzcQqYOYWo5HzMB2GqK0GNSQvnA4+wPKgq5J0B7bKF2TCIRvbH7QcdCc5lArhhFhGUCW2qE/QaX6zFO9ldIlcW3H7zAYlIiTztoFUmEhcU4a2D2ayjpcXs+ARqJtjEo9kuulqUaDOmDDhD7DVQloHYS3ZzOTUQKPMafCuiNih08MHlPD/KcPoxZtSy4+vgxn4Dn2XJD9VmAMCxwzIrpHmH65Uewh5/N+F6hQ7BqItXcc7gvA0IrIW/YeVTnI3grUa9T2F2Cbs/CLxOuUCMLt2cJm8483NgNsyK91GSw9fTx6GCxejHF+hlbtU+eH8I6hbbTyLMWuCSrLsk7YEwfTFlTo9NOATdxQKWBtUFz6IaK3iUAjEeyFtC3GjLO7FA4tA9b2LmFO2xJdJl4iHFHaCQKtIPk/M3OHWHReSC1uqO5stckjYTUc3ge7ZhEy9leeqnQTSK7LvdDAkSylCRSlIphpMZzUazjTGnRciEwDuEmxXRawd+kaHcJsKFy16d0vFA7wocwAepFxg6plTBrbmr1foz46Si1cAWJRgj8bITnhs6Km2kcyYobA93wA+epkQBS3+sgWgkTNWDJFSUB6soAXkSYiuffHzeAjOSF4xaoFHVaJoa+qgB1TS+I6lGkvgsWF9UpZ4m9jKW3GguCdlbZhRzmQUIA6ZmOP8ek9d5yzk4dQ3wzC7Uh4QKaLYdfJ2hOLJqzAvm8QpjYYXFsVlncmGNRM23hbBS+jx18rZB+nPLxrET6YYZk3CJsOJdD9OlMbqjPdKWhMfRLhfTcMMYqidmSmxRdp+CDgLrWlK0oj+UncwzRUSrA79HDTzQ0fqi3CVypgTp2zyKgeKGQXFL+4HIWOnZCNmw38UDHTm/2fRohdAsHYTzUhlZ+fuSgEna9QgDjaY0s6WCkw/ufnKC0BtZLdFZR5iEAVHdJE6O0hVAB6X6F0ahG1ymoeYPiKTs0vWUx6btoeDEnMxmWpujjTxR29zijL17yWihPed/0etJ+dJbcSuSXGDIqERniQYDyqogqtHt+kDV9FUcIX/z1qh2v7sYXRazVmw3MlWbluNTMAqskOzonMXuwQpp3SCYtoP3goiE8kH6WADUlB0GAN27KFGZXeHTbBGYtoFIXoR1AjjvsvbbE+eUU0jhkSYfEWKxvR2RjlRrNLqEH5ryjoe2KsJasuAkmKy6UYWYhjMfuax30rUZ14tDtd7BbA/daBWE8QoRfEAj9BOMhbhIUzyVkKSFXhJe6qUd6oTD5VAwxLt3EY/NmTIXeayEsq87pBxIujw7xO4n6lBBheiOAmKdnH9Zwb1SQpYpkFYHuOkNoJbBVZJLmFtm8hlQee2/cYJS0wMRiutghOapgnke24HENO7fQM86euj2Lbu6QvWCX+XmNlE85L+mhwSD5ucALVI8sN/xo3VXeZ7RSH7IrVoaJ6qWEsBKzdxX9XFuJ9shS/mEC9AXnt2LakWV5lUKlDjAR2owQaVBRqD+iJ6isqW0UtUQ4bAapgd7JwV0lWQPCcobqco/qQZz3TQIh0mMK0nuHEATEQFI+j6sJe8JGZm20+lJFh/RaoVplQKV47T3akN0pAJU4yNwieIEsJ4lEZpZQ3lsV9YC5RfeNErZRwMhhd12wkNkkUDWQThtAeYRph/qtGragfrUnfok1CzzbKJjXtwj3aoxm1DjKawPsFNRew2uy42YcMg9sIwlLcJYrrMTuCU3MZSRwSUuYWXgWr2ZFpGD7mDNWvVaQ1wmJaiZA5BbhZQZ1rTHZ3yExFrsyxU1Z4OfeeIZtm2JbptheFWg6DSEDiqMdltsCrlGoOgNTdJgVNVJtKce5SVG+ZtGddLDzqOc7N6gedlArbsCqJPxeHQXYqYNZSlTHvH59jB2r71GbmV1S29keWay/YQdTClrbeSQr6jb1jYbZSBpezCiv+bKPEADv5Rd+vWrHq/eOPnfkTw1QaXQL6qX0ky2S4xLYa4Hc42R/hW8fnuHtkzPMRxXUeYLRyZYQxkFDer4OGL+v2T1ljovk/ZYQkBXovlah+Ic0qZTGYzyp4YNAUnRYzHe4vpxgsyYZJTQKSDlLkCt6VKY3gvBO9FvsFhyCy1IBW97MhP4coMDvi4AktUOXyXAyifRSQaZugC79PjsuvYni532H1dddNFAOMROPXZx+kQ6pBsufs8wHTAl1qlLSAefUI8T5kzxPEc4yLko7BXltIMYdZMYNI5s2mBQ1fvEeoxSdl3h+tsDewQbrswn8R2OIt7ZA4eAahXTawJYG/jJljl0Md20PObNSTT9f4QbfB1aJ0DPoeP589E9FnP/YPcJp03fYSTH/MGD2A4Xlz3cIMSUCxkONOs437zUQMkAoxibhqEZ4mSPERUlvFJBbqK2Cn0fYKVBSoJc0JMjezegO1Aha0VWRKLJAXNAIi9G1hXM9tSODT9bUQ7bHHfzIUax+2pDgJAAx6YCxpS/nWQI16uAqDby9QTGvIGct1Gc5mjoyKI9q+E4iOJoEKOmRFh1Mapmpd5lSb7g1cMsUQgLSOJgJMb0+OaAtSUAyuUXYGjJva8YMmXOD5P4OuzKF7xT8OxP4DVPPzbyBfrRDcq1gN8kghdHnCXV2jp9L9lzDJ7TvU2sK5GXHLki2FK0HFTD+SA3kHz+18BP62vqRQ3ubxbxKScLMvRrbdYbr8ymSxOK1+S2uqhGsk2ivcxzcW3Em6AWqbQr5zghCeSTK4XRvBQCc1YfoEJN5oGaXLmuyvoUVMYPTD5Ifn9Kcopv7QYMYoi/r7J8SHeimXEPURkG0AsVL3qdMKFFo9gnfu6lDc8wuWS417Feg4wO+2nSGf9mOV3fjC3ToCJq6JrVV6BpNCGFlIIxDoixqZ7BuU2Smg359C+ckxKTjQqED9K1GcxAw+lgBW8I3wQmk55oO8p3C5gmH4AAZbG2nkCUdbpcjJEVHSrXkBiWMA7IYyWI86sPA7k+BHV4r7iq/GVl4wXP2hIKJ6cILTIsa6aRBL6qFDqjvdQilRnuvRflmi9BJqLUi21KCXXDi6a3pOFMSlsJzV3iyFWsJtWP6NTpGxSTXEmqrMPlYQkS7syAJ2QQdKAVQ3CgQANwmqJYZ2k5j26X4I48/xmuzWxSTGou8RLKoKQnxnJMCgG0puxD7zSA9cTm79BAZoygssquYktDGLEXPRTOoQNZrSR1jdhXT09eUJmyeMDqmmzAXcfWWZ9Gw1Xy81EEbBzFvoRKHsNPAeTZ8rm7sBiF9fgGEVg22diqnBR1EgH9UASOHdkZ2ok8DkEW7soTuNu2Mjyl0zOeLmjwSUTBs4iJu6M0hoXR9qyF2CjKyUYUh21Mn1EImmrCe72iPFTyQzBqoeI6DFQhOoqoTjHKaTfvbFGHWkdGsAmU6awMhQMh6xwSF5hGlJjJz6CoDvZHwlaZBREtdmwCYSGJ5niGAVFtI5ZEaSxmKYqElr5M7whj4nns9a59an13EhIaCjkuISMz2a2SCCg/6azrCzbJUkKWCmjA5We0ipLsxyGc1QhC4qQvcbgsstwWOXrtB1RgEK2HPckjjgbc3kMYPgm4pKOgPO432XpyrRouzPqMSIjKLI/oQNOfnrqDZBP1XPY3oNxr1Ptj5d5RF9JtkfeQHvWk7Z5HpC09bRBMLsSIWul/FkvkzqPMVOLyAqrlQ07bMYzRq4DrCOOImwccfnOD96wPcVAUkGF9irYRvFDesCUkJdu5Qf6eil2MjMHnH0G39IkbBzFqgVvCtwvpqBOsUcmORZh3aXUKrJpCdFyqN0Cr67cWIHOGiQDte0GKfLNKw03Ajx7iUUQdl6HUpxx0uni7weP8GOrNIxi2guHGFqKsTmiQat2fpFDPyMDca5sogueIGnj/V0CuF5sj9Nv1iH4+Sn8uBOGKnDuVJgI6sRl2x2w0qoP5adJHZGAgZEGYd0lmD9cUYt00OKTwOsy1mRY3nt3NIGaC0hzHsWtUF2a2jaQ2/SqBvNeAkkqOKc08PyK2CWBpUx3Q0mb1Ppxk55WzTrCj0ZXZZ9CQ9rvm+As9xc48dnTAe2emOHeSWEhL9UY5mmSGsDLyVUNMOyaMtZ3sNu2xREHpev82FNUQ43VsJudbcnBIHoT3c7E7uEeJClrwggUk1hJvlrYEd7NbIZkyW/Kz8zAJb+kOGKQsge9IizDro93MET+q9vdegWaXQqcWD+RKH4y2ycYvZoxWyokVXGjhHDVofXfTW8QVu39vni0uivyUAc24gaoXsoIK3gnmS0fg6REp72HE2q7ecbcvEEeqfWHgvsLe/hdopyMMGcqtweTmFktQIujdKJJOGhd6igziuoRMH7LXo9iy783Ek16QBzR4T2aED2n0/kETSCwV9nsAdtfCVJtSq2U3J0xK25PUTZICPyQzOSRjtcFRsMS1qtJsEmSGUKROHyeMV3G2K8IMJRgUZ35OEf16tqO+DCtBnCSOkbHQFGsUcxbWCXtHzN6Scw8laxMKb6EkfO9XNPcp7AXbPEoYu5SA9avdJjgkTCzXpmPiypPuO3BDe9emXvxMFiJ9Bna/EEQkDKNwwB9q8nMA7Dpb9osPkZAvrJIz02LUJpPJwrWLG19MR1JVBdkYSgVsbyA5oTzts36IVWH1qIW8NfKO4CUb/SikC1lWK4+kGs/3tIIDt9i2hHQ9UDyxUnA+FlCJ7WGqKwk06mBAL49GWZKe5SuPgdIXRqMHX33qOm7LA108uUGRkSqpSUiieWXomlhSDY9EOKQx27GEf1LATh2afcwhVSgbffmrQHbCqTW/p/2kLhvGqrSIMowLa4w7taYTXCi5U2Om4YHIwr5VDuqhxXGxx04zwzvIID8YrnMzWaEoDYyycJ/SGBzWSSYvdizF9G0ceqCT8x6OBju8zRkjpHSB3CtuHhL9wkdE+qyAD12wE6mMHOwpwZYyXGTn4BY0LIAPSSYNqmbF6f1RBzFsEBcx/SyM/3SGsDVyjoJRHNmoBSfF8v0HACwjDLluPO7Jr15TOiB+MIc9TINrRhVk3ZCg2xzRIkC3Nvn3umJA+5lxPWAG9AyUVO8WMvwCg0lCJh1AeYmnQPOiglxq2YqGhC4tukyCRDkY5KOXRtCQYmaJD+r0CyUEMbmwkPr7Zg5tYdtkdYXmlPcLrO86XIiSKFxmk8Sg+ZuGWzhrIcQc0dCsRxiN4AVtq+oQKYL3NII5rMkfvlxAqoDwb42S2xsneGu1thr3HS+TTGq406KKcJ3thkD2LGrXYVemYJylLRajYCxTPBTMoZYB5nkIVhKtlFVMQnORrkQFmI+kLOrJozws4L/D9sxNc3YzxjTde4LNnBzi7mHFsEATUooF9vcKuTHFvsh7SCkZFg9nBFibvWHwIoHddMtcG5lrDHrVwuUd7aKFj8kgwdKdJrhSEjlZ2WaBGtBWQW8W5YEMYNH3Jz8xN6DXqL1OSe8YsopIbFvHZmfpKlszwY75etePV3fhC1EMlzLwS445EgJVhJbvRqGqDLLHoIqurazSClyRrnJBwUZ9aitoNBcrJ88hYdIId3H4DoSNFPnfQ4w5p0sF7iZuyQFmlqKuEsFoAfKeQ7NVkt5nAINReQxg3q8lH9I1UpYS8TsgynHUUBVcMBZ2aBm/tXWKeVphnFb716CXUox26hvExoid9iACdcoZoT7iIh7WB7CTyFwIYOZg1ocP6noXaaDz6Lz26CSGY3jIKgcxPlweojDotvdRMsDAOIfHwnkSfbNRinLW4N1/hMN0gUzTu9hCYJA1Ojlaotim08jQLaBWECEiPS4SE5ImQedgDhsjmZzLCjED1RgsfyTpB0xkDXkBYarvsKGDvNxX0VqD41DBTTXq+5oQ+ot7JyMTl+REyoNujAUBiLNSihdhopMYydnFaEzLzgtqw1AGlQvY8pnoFge5JDb3SaB61cGmIsLYHHOUmwguoDbuTbhrgjsiYbA4dw1NjPmN9ECmhvTVdJNCIOJcLE4vRu4YbQuIgZICrNMykxbZLcF2OMM1rFhiNQZJYqN+/RFdriANC485LjPZoQm0Oa8jPQWdh0hdNGnbG81+dsisMXkCnDqKwdBSq6cclWol81LKzqw2yrIOUAd5KFGPKA8amxfVmhNnpGtbRFqxYlMiKFvIiRX2vQ3PgkF+A16kJsDktvNIbFkM+YadUPnCD25CPGjvZ8Dpwu2hTttZoDy1w2CBYCbnXwHuJdp1iPmco7d7hBtmoRf1yhPXVCFlG79HgBGqncVMVaJ3C6tM5yirlJl3TB1asiJzYmWNcFRBRGyDIALPl/dzNPNJbRBIaAMM5oJ33ZJboQBR/FgHUScY0DjXqOEcvFaqHHcK0Q7v4CnR8gdf3F329aseru/HFDyv7fk4WZ6MQAiAbCaUdzCF9+LT02MtLTNIaSntM5iUWxxvKDqYt5LjjRrHhHKM57RAkuwuXe4hrUsHtlKQV10qsbsZIjKV4WwQO+yu6gqCRUL85htpw3uiTAHOtobaxO8sddvcCq/7DhgSCSkEZpmw7JzFKWqy7FK8XzBd7Mr3GxW6MPGsxmVYoL0YoigYoOPvxTsKclhArdmjpFc2pd685mOcJqkcdQ2BrwkNP/1tqyKRr+0yw1A/zBW85jLczEjuS1GK0V6ItE9itwShvcP5sgaeXe7htRyg0IaMfnB/j3fMjvPxkH+Npje11ATNtcHhIEkHXaCT7NReyz81u6kOyNNuZH1iVEIjCZpIv7MKiOSYrc/snt2gX0RCgJcznWgbZ+sKhu87YvQUBt2aHkR5UcN/aYZy2eHR0jTDr0FmFR3u3sJakhuAluoqzXRQW9ls7+KsUKCgLCCd11HkGyE5yfllLuKkbtF/5S3o1YsugWtHRQxaVhNlGR5aVhhhRpyZU4DXwyQj1yxFk6lA+8DAPtzApC5C94zXsdQaAHdf59RSN00gSi3KTYrvJ4GsN3ynM7q3x7ZMzOC+RTRq8dXwBox2SxGI8io4uVgEjCz3i7DJMCaf/4gMSlXTCDnp8UEIaZs5ZJyEE0yt25yNUywwms9gtcywmJVqv8HvvP8VeUeKP3f8QnVeoqwSJscjeWLODHjus3+w/dz8kclQPWbQgcC49eko5SXNq6fZTS/jTBnJKBxyso7NPLYe1wN+kaJ+NgEbij5x8jG2TYL3N8GjvFqMHG8jEodykSNMOOnF47+kxlAgokhanb15Ca4diUkPNG+h5w5nkhJKaPvhYdJQb2blDfRg4ry8c48RK+v2KRqJ85JBcatraJQH5S3ZwshFIr5g3qdcK/rShzCOSqoRhQfJVQJ0AfmZZ9kocKgCFRfn1ZoC5hA4QpzXaXQL3osDDwxvUnca2TZkgrR12uxSbbQa/M7BxtpEcVcOgWm01uylgsKDSS4X8GW27hAwUwkefwvYqh7qghEJaAaRMU/a5R/GUptl2zkTw9NxAXRu4iQeshPwsZ4Dr+wquVkju79BVBn/o6BO8WM3wdy/eQOsU/vEZcxxneQ3nJdSsxWZZANojxA2/vckg9htkkwbN43bwwWyPOwgT/RzjBS46MtOEiy4VHoxLikxPbDTElL8nlUd9laPcZMBGI1uQRPD662f41v2XOMlWGKsWs6SGVh5vHl1idm892CC5VkFJnjffSTS3GcYHjOuSOTdWv2CnqmoxmDKn14QWqxMWM6KjowgAuI/pxNMtHKHlSYd01DKHcEuyC5YJhPZQkw5+w4iarjRYljnmaY1fePIMB+MtPr3eoxVXwZw5qX3UgirYRjNYVkTLsh2ZjmqvhZ9ahB2tvkQjaWo+sSgfeJSvWQrR9yIzsXCDubUrWGgEKxFOOX/ytYKdOUwfrQjLjRzCDyawncJib4flBwskhxW09Li3v4JJLW63BTeVUQudxNfvgV2ZorSGDlw96SWSOJbXI/hOwltuzK5WLBhqBSED3rk+hLN0bYGV6LqogXx9g71xierZBOmUcKhMHdrKQJ8nWO5yfPDyCB8uD/DN+Tn+iw++if1ih7xoUVYpmiZaCooAOW8hOgl1mcCsaOI9fk8PhguyVNh9s0F6SZnG5B2D/KVC2DJ70O1bohCHDeY/JJIjEp47fa+EmHT4ZLcH7yVmkwrvPz/C7mzM669R0MqjvczpGRuAw3yHi9sJqqsC/jdnCGc5z0mE4NWakpPkVtE8IhJz6NoSkD81hGzjmhEMuQFeg9d0JdDsc3YuHJ1f3H4HO/Ywn5BcJaYdwmlN7WsA8qPdl75cBgDeiy/8etWOV3fjc9G93d69xWBF1PYYBBlQWwOjHfF96ZGnHcZjpiyI3BLesQzYVCPGk8ADcq3hDjqM3zU00H1YoTql64uJoZy7OoFQAeZWMT27hzM90C48kkuF6l6AnbCTQ0NIjLljHKS7+zX8xmDznQYycYRaSgUXBBajEvt5idfGNziebLBXlKg7g90yh9KeGWNrQ1bfpzmZpEGg3iXAVpFdCtLj5VVCI+fIPgyaG/P4syioleCNGzstVQuYTzIAAn5rovclABXQ1RqJcnh+M8dVNcI/vn6ILrCznhUVbJDIjcU0bzA92EGogLNP9/h7RYfx4Q5KxgXZSSQXJI3IWL3LaUt25B69Ers9C7/fIagQtU4edo+RPEIFMhG1R1sZILIsZSW5gfeXRm7RrFLk0xrzooL1EtsugQsSqbG09SoNVG6hE0K5xX7J4iRhxp7OORsdfTeD/DhH8BhE76qMJCvjBxo8PGHMkHqSZjpqv5Ilafh9xptQAXpERqt1Em2jkc1qQusAdnUCHDbIsxbbNkWqLASAekVWrXPcqLxlYeCdRNUZpEmH3fMxdl0CpTz9ZhsStKTx7LBUGETdzTZFEueHtjRIZwyrFRKoywRXqzGy+1sAQJpTKpEVLcJrJfbGJfbn/L/n5RxvHF9hWeeoKz53t00I9+6inZ9nAQAwDaPZB9RWw2wFskvOk+sjitV3jzzqI4/ieAv1YYFk0iCYALvTWP7hmobZxqOJ5yLJOzxdz7G5KVA1BqNxAzVrAQHkzwyclzh8fEO3mSBRO43JuIYcd6ifNJRbfJYN7FufBsidQrvnkF0xoghWDLZi009IaBE+SpGcgN7Sk1O0UQIR/Xalo40db8wQHaKIWAQfi9DcDdmCX+oRMOiBf+TXK3a8uhsfALXSZNu1Mf6lsEz+nlnIoxq11diUGSn2yuH2wwW08qyEb9kFCMPODQDUpIM4rTkTW2lsv84FN3hBk+bDDt3LArPFDs02gTaONkZTEll8EhiQ2Ql0cy6CvY4OKYNMfcKuEk4QjktJsHCVhm80sqMSM13hXz1+D98Yn+HvvXiCyhqcbSbITIf9ozXadQptHPJ7W3TbBN1xx028VZxvgpvK6KmEvtLw+y3qQ6ZgNw86+CiKXr/J1+/GDm7G9yB3Cv6koXtLpaDnDfS4g7pKcPLkGscHa6zKDCEIWCfx3z55BwDweHSNRVph1yU4LJjKLaXnQpc5+EajOyuwW+XoLDtteW0oVvfR9R6AeJlFxxJAxBBTVCStdFGmoUcdZCuQPjNQmYVbMi9RWDF0A0gdVEINoZAB+bwmSUgEnO8mmKc1Xvyje9htU7SdRrEo2TmXBvWGCMH9B9fIRi1tvMDiYPsWI616/8revNxnZOdNPiKpZXa8gR85JLMGJrfAgwo+9ZwpewBNpOKfZ3A1F8xqm8J3dBmSr5XMeNymCI6eqABwXY6glIceteg6Bft0BNdxM5MjSmterqZoWoPi3hafPDvEepUDncDkeEuGonEQViIfNxAjS2JJI7Eqc7RlgmTcomsYTgsROBMEUGQtjHFIE2onneNndrvLcVhs8c29MxxnG7z7gwcAgCxv6YfZSECBc62bBGl00TEbRMII77Nu5lHe4/UQ7UShSt7b5TpHc9LBfTqCHhONwG0CmVnIpznjo57maDYpnsxv8M3XX+B4ukFZJfBOwLyfo3rQoesUbtYj5MZCS48PLw6wyEuYlIUwMo/2YYMwJ6lGeMDNLJIbWtNVpx7CU3YhHbA7FnSNSihpEB6o7tMw3s14L9q5xeRjiW7qmXG45kjC5kRlgvaQKlACZCXST76CjQ9A8F/89aodr+7GJ5mW7HMa4sILjP9+jpB5ZAtWgp1VkCLgxXqKdz47wfTJEutthjxrmaRctAgxhdmkFrbUcNcpmkMHnwTopWYVXzJwVO4URdOOXUazSgfBq9vvyODLKLRlqjm7D7WVEGsNvSVFPxw0hKbAXLemIgwZnEC9TfGbqwf4jeVDvLM9AQCUbQLrFJyXKOsEe8drmu0GAbHjpuBrjeQ52YrCCaBU2P1CzbQCK+kuokJMoAiD4Nqs1OBTGhRdSHCTsEItJdxFDikD3MTh7OWckGGEwI5GrPJ/8/o+KmfwcHSL/azEqs1wsZygrFIoQ9nF0ekS8qCBSm3094zVryBVvLpH7ZZdWIgtNXQidlVBk7QCSecP1yimIkwD3HWK9ILCfuEEO18PIH6WiIQV+8EEq02Oh+Ml7k9WKFSLt//IhzjYo7az3GQYjRpMFyWSUQutHM6/e4ym5jlNUwszbUhcijo7e68BsqjvkgFu7LB5g5l/q8sxzLVGt03Q3mRIf6uAcAKjTzRZjKMO5oMcXgeG+koAtwnz2SLcWGQtRrMK2ahFnna4XI+x2WWoygR51sEYB3FaM2g1zvhCJ2E7haY0sE4heZ7QNHrSYXM+5izqJoeaceMUfTKB4ep3//SGJDAn0F7lGI94L7WbBMt1gd0qg3MSSnpeF7cpDiY73NQF/sGL13DZjDG5v8Fqk8N7gd1tjuy4hBh1ZLoWDvatEvqwQn0c4W3jUTwjtInI1PY6QO8EVM2uOBm1ZN4+LGmCYDiaSFKL8KjiNXHQQWiPH5wfo7YaLpC9KlVAeHtL2U9ktHZe4up2jCztcL6ecNblBVAx0UUZTwnT1MJcGhLVtopM4wAaRNQS1b3eqi4gvVIYfUabOpd75E81wsRC7hTWbzqMP4kSpyklJD6LCEFJyNntDGeKb2++ggXzi+d7P5vx/f/TEQTtxxrS+IUHqkPAXBpGkHQSuxvOQQDePNttjuAl6tYAmUfXRZFy6tBsUsbpaJo+6xVtubCLzD5HzN8dt9hejjhX2WioG32XP3e/AwwveDt1wNgS8oiOIoLOXxAywO4MgzvzAJNZFPukhqfjBh8v95BIh0x1SLVD3Wpo5eA8DXW19Khrg7ZklA4q+graCYfjYew4WG8UiTobHTcR2qiJwpJen1u4NKCNAbNmLVh9J9T8CUcWYFdr2lIlDlWnkWcdjhdrXFcjfG99H4VpYYPCy2qGQre42oyQJhaLSQmlHfb2tihMi8mkQpJYBm9mFv6kgdmr6Xf4TAElF+LphxLSAWbTC9ejz2YpIeto31ZQcoIg0BxR2O3GjvC3APRGIuRu0E7akwZae1zVI0wN4e4XmykaqzAbVUiKDqO0Rd2YYTYmX99BaTIeP8+M7OOOsNWQt0QLhBOk2UfTgOTcsDPcKvpVHhCqLR9xRiUkmJrRciEOViAkTAU30wZ2maKzCm2r0TYGdWswH1Uo8gbzWQkhAqxVCB5YX4/ijI8LmO8kfK1hW4XuERmrvpPID0qEcZxbJxZSURIS9hsk4xbtdYbaapJYOgW1aFA1CcYHJaYHOySJJfkiCM7KPhsDMuB6M0JjNX7++AXGusHu4xmM4fU63d/Bx03FFT5KOKiTGz27m+kGSX2caAWgqdtsDh2aY4fgBdptAhQO3TZBmEepTerRNpqeowEQW27YqbHYNinOllMiKZcpfLx/tXHwW4PNLoPvFDqrkCVkugrJeZv5MGfqQ2GhrgzsnoWqBdzC3lnZRb2dzzxn5DvqZXePPMr7vXsS6Dcr6Aa0u0/bOqH8YBwuXH8OAg3uWzkgUF/q8TNW5z97CCH+qBBC/Y7v/eJX85K+rIOdQMg8k83XCu2xRXfQwT8vYK41kmmD7YdzrC4nFLoKUsObXYJ8UtO5QgRqqDTZkcF4dPdaZu9N3eCmgoYQljIeekLIx88s7Nxi+gMzmB+jZQ5bSDxnGoYQT7dwZFKqgHCVQu4UuvenkA6wDT0Y1bVGWxnUjcFlNcKL3RTbOkGWWGx3XJSyvMXl1YQX7CqhHlAHJAcVwj47ELliTI6+1fRKRIwzsoIdxc7whrtMmQ8mAdFINPuOXon9Ii8AuYobf6mgU4ftNod1EtsmRW5a1E7jtiqQxKCxzzYLeC+RJx1WJTP7rJN4fjPH6WSNcdZwRlIayPMUXcU0jOrEQ8bE7fKYm5h7o+Q5jQJvlzEbTp8lfO1bFYuJAPGU9moqt+z29yzMFWcnk1GNx/evUN3kuC5HuKpHKF2CdZVBScownJW42RS0rjIWSZyRau0QtgabVQ53nqNZ0XJt7zej/nNi4UYO2QtNIXypYGfxmlEBx78uqOPb69DeI40fQUA8zcjKPSHLFV5g/mAF19I+Kz8ssb4ax/mdwO75GKsyQ9MarLcZ1mcT6vRAD05/mXFD3XBmqooOvlOQFymclZDGo7osIDOLg/tLpMai3SX0YvUS3gvISYfrsxmyokUybTAZ18jTFturAifTNYqsBQrORNeXI4iTGpOTLdKkQ1kn8EFi2eY4/dY52lZjf7JjsXad0Qkn9RAbDbc28J3C9pcqFOcAGoXyLXZ0IfOAE5h+RFITMkKfiOL8dNbAZBYqs0imDZT2qHYpzMsEWLRAo/D24RkAoN0ZHJ0ukT3YwpYGYRTn6BFKPzleYj6qULcazSYFBGAyi+bIAZ8WJDo9qJnIXpBBLGKB4kYOyVIguVKwexZ6JyAnLULGBHlIsCBbmchYRTQylzS5+Byi4ZMAsTZQFwwaVudfwcbHJfO/MUK+n7bj+38C+K+EEMef+95f/Wl+UQihhBC/IYT4G/Hfe0KIvyWEeD/+ufjcz/4lIcQHQoh3hRD/2ue+/3uFEN+L//fvCCF+ihJE0IXihYY96uCmDmraIpm2cFMLXQJZ0tG38XCDk+MVhAiY7O9IWpCBVZ0OcNGRpPcYFCtNj0YBINCrMn+uYK41w1Zl4MylowP9+lv0I1Q7enXamUNyYWgOPaJrimippVMb5roFEyCe7GCWEn7Lxd+fNgg7jaYy+OSdU8zTGtO8wX6xw6PDG6xuC0gRUEwapFmHycckcQgnYFvFDs8LuKkdAjIBklrMhs+ZP2XoZ3qhYLZ0yuhZnXrD7kTfaiQXGi73CPstYZ+RgxQBrpNoKoPNNsPL5QzbLoGWHkY4bLsEe1mJ0/kKdccMuKY23AizFp/eLHC7Ke5mXA8qVuqdiAUM2Y7+SUWyyCcFREPoqe9mVNzsfLR70lsSS9y9GCC6TmCuDPStho82UFVj8PGnRxgd7JAoh1Wb4f3rA2RJh5vLCVPF1wnSxEJrh9XLKZbXY7iPR6hWGeS0HeKl1EZD3yux+hMV9XcVpR/tnJ01RnawMht9qHH2xxzQCRTvJ8BOQxgHb+iRip1CUTSMlpo2aFpN8lStUT8fA5WEO8+RFh1G97dQ0qP7aEzWoWbgrE4c/AXF+mKtOZfaaITrFHIZz8FnOcwHOfS8gV8nWK5G2O3i71hBp5Xn9KMVW4Xy+QTtNsHyeozV7QjZosZHZ4e4+WAPQgbcnk3YxSSWc0AAR7MNPtvMse24aE/GNarOoH5/ys9Me1q/HTRkR681Be4j2s6hjG5HqQdaiZtf8PB7LRBNCdR+g3xaY1LUmI9L+FahWaboblOM/0mG7jTqSVKHi2qMbZ3i9GSJ6+UYzklC4cZRp5g4CBFwuRzjajWGdXx+X6vYWdJI3d2kCOcZ/IKFMESAn9kBuamPHNqH9H21RYD+JAeMR7PPzD5kdK1R0w7hcQm/6KBmLeSIM8owsfyZCT1K3djDNZqs76/i+ArJLT9u3f8xv/PXhBD//fj3vxP3he8KIX4ohPgLv5vX89NufO8C+LcB/B0hxB/uX9dP+bv/SwA//Ny//yKAvx1CeBPA347/hhDiWwD+LIC3AfwqgH/vc13mXwHwFwC8Gb9+9ad6ZskgT8T4n+AFjYYTD5cA62UBTKnXqjqN6bhGaxU7IkmvwezjBHKrSMKIDLfRU/p1yh1nJsEE1IeMBJI3Bu55gXaTkL0XBGSluJE5QJ8lGH9ICJWOMpwHMNCSz5nc0g/TdRLtno8xJaRbq1mLsDbAtEPtNDLNWeC6yVBMGjSdhtG8cTc/39JZJIusxI0ehPSyjl6d8d/Vmy0gAuwI6OZ0u+nGAXpDey2fhOH12Ylj/JETCKWGqzSE9KjXKdKPU4izDN5KZGmHZ9cLHBZb/ObNfazqHN/75D5uyoIejtpDPsuw26ZY3xZwXqLIW6T3dwjaQ31YDKkXsBSnC8VCRFYSdhHlDk5G5xQQcna9xIHCZ7Pm53X097hI2qMW/rRBHwDbvTNDsaiQGIfr9Yiz0ipB22mcnt7i5dkcatqiswppYllAFS3wsAJqBVdr0s6tgF+0dNoRMTki8YACO7+pZXqFoDdrdZ/2cwBDVPVWRh9OFkyQwG6XAo2E6xSsVexIGklz7YIdeNdq1FUC5yXmb19DnqWYHmyxuynQbhNmOp5JhDkNuUPG+Vd6yc26Wzg0DzrIPm3iNmF6QsOUCaH5ufflprQC+ZRwsFQezSpjBp8KwG3CEUPNOV9Xa6xuR7hcj9FYjXWT4exmCikCmlYDD2omeYy6wSRARRnLIOgX/DzLJx3Zzw0hblT0dzWXhjPHVuPmeox1ldHAXZGMsv5Wx42rUUieprguR4RiHe/ntkwIY14xNiy0Cs2ONnpJQocbtYgbpwpQFwlUQZ2lN56ksUqyaA1g3NUlMxl7uzdh+ZkjrgVh3iEZRRNw6emc00qIz3L4RhPubCX0yxShI4yvdpKdbfHl5/EB+FI6PiHEHxdC/LUf8V8/ct3/5zz+hyGE7wD4IwD+90KIf+HW96fd+EII4W8A+FMA/l0hxP8cP8XpEEI8APDfwW/vDv80gL8e//7XAfybn/v+fxRCaEIIHwP4AMDvF0KcApiGEP5+CCEA+A8+9zs/7iVDbxTsxA+myrjI0G0TyJsE7YMW870dkqJDucqxuh1BCY/T2RrjN5Z8hK1B980SPvVQiUNxuoUQwPbnGsia9lgUIHN4jXnLheKkRog2W8JzQVOlgJ06WoYVgNkBPucMSjYc3AsrYOeWju5JgPkwB+ak70tNpqDdGWBskY8bbNoUZZfA+mi7ts6gpMeuTNF1Giq1nBVOGurXVEBoFIQJzJWLh9pxB5alIgR4q2DHJAc198io83O6qUzfl8jPFD0K91rAeDK/goDKHLpJgHq0Qz5qIEXAo4MbzNMK98crHI82mMwqJMqhdQpv3LtE8uYafpVg/3CDgwh9AcD4oIR7o4RMHbAg2ciNo7g5jckGAtxYauqizEox601wVhlil94cUSdy+SdaEp0axU5or4M0jlluIpDdCODtvTP80ScfwgeBX9h/jp978hzfOD3HtKhhJMXe7TaBW6bIjkqiARuNxfcUsg9T6LMUbplSaxiTumXikEz+f+z9eZCtW5rehf3WWt+8551znvmcO9a9NVdXdanVE5oHSxZgwGAQBkxYIQUowg4DDgcmwoHd/gdMAIZoYwsJiUFGUkgYiRZIakmtnqqqu2u6t+54zj1Tjjtzj9+81vIf73eyLq2qW92lugq44ovIOHn23rlz753ft4b3fZ7fU18JV67ez3ksIOrdFm0liDfYKaScnFpsHhBviWq0mSWyu+3Ke0HW4Lcq+v0CfxpjtGOxSrF7ok7d2Z+jAkc0rMlflNtYBYTnnWrwExvxa3aAbfug1/kSEWjCqJb+zmXE8PlL2k3A8M4cc5hT1zI4e/++0ndmUduVBCaPGok1ArJBSRo3vLJ1zGd3HvOT997ixnDOpw6ecGPngvErM5l4FEKDeZJIWbJrI3jDt5FzXVYigSii9UAwcG4TYnPBBzaP+qhGBFw46d/7xBGehTRDJ5UJp4iMJc0ESt6uImzXr44GFTpwxAM5hweDgiStxe8at0KRqQ12rya6MOhS0+7XV1B1XaluhyZJITo3tJNWiDSBZF3iFHUeyWLjrR7+rb4AFQ5LgvOA4HEiz9ulk9iew05biV+6DL/38PebPT78Ht93G/evDiXHv6eUek0p9V8Du9/lufrABrDf5f7veQS/wccpAO/9W0qpHwX+BPCJ38DP/T+A/wMweN9te977o+75jpRSz97cNeAX3/e4x91tTff9r7/9736Rsv39FwHMdCzy30YL/SCxkq6wCkhOFYUJmOse6aBiZ3eBQ1G1AWcnI7b2lrL72BNVYh7I6i8vAsnsm4f4xFEeOJQX42dyYrBLQ7iE/E6Lzlp807H3UuEzRmcB9W5DuScpCSrsVnW5ok3F2+NHYoBVTYezWocES0PbKui1mNARxbLiu1hnDNMK6zWN04wmG+anA0Y7axYnA5SRhny1jmDUEpyGIkzBg1bowKJPYvGNlQa3JSGrLvaSM1iE1Nst/fsGUxpWdzyLz0oUTf+tkPVz0nzXtagl7SyGzFGfZLCfM19ErHNZYW9lGzZ1zO5gxapKuD5ccLQe4pxmemvOcp1y2crOzDtNb1RglxJbox+l6Fs5tjIExzHtpO2Mws9S5h126NGzEH0ZUu1LyKx4IuXzNGchbr+SgT1yNBuh8uvjiPC5Fc5poqTFGMc3ZgcAVGcZP8vzbA/XPHqwQzwpqWcJ6U4uk05iqcsAHVusVVx+oUUtAkmuuDC0qYhaVK1Qm5gmdQSlwj9NUF2Yqu8L5Dg+DmjvFGgF7mmGseBGDb7blfi14NdcY4h6Ne2THukkpwkceRGj9wuKTUzWr+hlFXUTiGrzmTo4srhWEWyXNAOxy9hWMzhckb81EvvBTiPlz2cJ314JMg+o6oDrN2dERnLtdicrLtcZdRVgsoYwsLh+TdsY1G5FGLXYsPOOFhHbgw1fOzvghek5t3oXnBQDEiOvbbFK2R5tuNykZFnFOh/KiJMHRHNNedigVxINFp8asXxUmqBS2NDhRy3ppKTKQ2gMwbXNlQCpWMWQB+hW0Y4selRz8d5YElicltW7EuZqv1+wWqaC/UsFPZgXsdB61gFoMP0as5tjvjKg3PXUNyvUMkTPQglp7jkJ/S0FiwcKtTYE8+CqteAHrXB9rcIWBnujQi1CVCQ7a2+QEOIOY2cKjRuIGtleK4nfST5ozP3+jw/eymwrpb78vv//tPf+p38Tz/7dxv33H38IeBH4OLAHvAb8f953/59RSlVI1e+Pe++/74nvN7Tj895/+n3fb7z3/xhw94N+Rin1+4FT7/1XfoOv5TstK/wH3P6dXudPe+8/573/nOn1cZWRE6ov+XDeeNR+ITX2WHZRadyQ1xGhdjStIRrULNcp8/dGVFVIYBx60BD1a4JuEAmXWgzuVtF7R/o2VjYLlK8WRNOOOq87urwXjuQVakghIhFE5FLfkLJbM20BSRlvJ62km8eOtm+l4W41QWipnvQo1jFhIH/3ug1EdGFkV1E3Il5RkZWyURFI6KgDHzoRS5Qa5hHtuL0yplMYzNqQnChsDM3IEiwNmxuO5fNdREo3mWxuCjj3ij7vZGIO5oZwJcbvILLUeUQStDw43cJ5xbxMmaS50EOUJ0tqNmVEmtTESYNvDOOtNeOsIBhVEo8z7Mz2i5B2JJFOKvCiAOzA0To3wo+MHNFZKH2zJ6bzQXVG4y5DkU4pGV4Khq4uQuoqEExiYwiMJQka9LAmClsWeYoKHdU8FpFPEQrvUzvcOiTosuuUlp6iT614slInfdzMSnBpJLxX3XaTYZferlpFvdvCWYJ+nOC3K+yOGOKV7eTkz5ioVpEmNab4dlZavYixJylZv8JaTWAc+6MlWVQLoUU7KUVaTRy3DEYFOraYwLFZx1cxWCjZjQRZg0mswKdbsZVcn8wZxiVFE9HvVWyqb1eZtPYsz3tYK2pR3e0EvVeiIF0LEScylgeLCUflkNoZLqoel0VKs4yxTonXDvBDea0m11T7reySK4VZaaodS9j5I+3AouYhSotnUIcOAoG6N43g/ZT2JCdiDYhmBtdoop0CHXjKVUxTBbSbEH+SXFkWXBFQ5SFNa0T4EziGN5ZEOwW21VSrmOrjBbbfkg4q/LBFHRYMDleQtvhGhECCxQPdyI7t2bUTnIUCLldiYqeQFA6s/G7bE5FbfBRCKKhA70AXhvBBIkG2H8Ih/sPv/AWcPxtbu6//3qSnlPolpdSvIdW9P9D14n7t/VqN38DxY8B/5r233vunwF//dff/U977TwA3gf+9UurW9/teP3DHp5T6d/ngdcC/9AH3/QjyAfxeIAGGSqk/DZwopQ66Wf8AOO0e/xi48b6fvw487W6//h1u/+DDiD/N9yxGe5EAZ5aDrQWffv41lm3C188PKKqQuJMrT/s5Z7+0T/TxBb1bC/IyYnkkjXq7TIjvLWmWMf1Pz1jnMXUesLnbolYBd/71L/Hmv/1ZWEa4aUm7iSCxbO76jj4hK9D4pDNldz6g3sOA/IYowIohUAmx3a8NbFe4KpDIGhzZewHlKy1qq2Jva8Xx0wmLWjO9MacfV5yvehJDE1rUXglPU+klDkTJ6AdO0sEjfyUGUa2G1KFXEu5pE0e11e0yQo9rvQTbIhWtKhBJNf0WtQhh2EIF+iJC7Re0u+pKHLA12FBnJXkd8onrT1nWMdO4wKGYOyGLGCOlpyRsqRqZoL2Hs2Uf/WaP+mZNuFWKAX+7wuUBqtZEF4Zm4IhWWkqZfQFH63GN33awiNncbq+EEy6D4H6KeV58ecY4bK8RFZ1VIhpqDOmgJFCOR2dTBoOC9TrlhcMTHj7zJ46hWsSE/RqtPVs35szOhqhFIL3EFzaYJ5mEjw5bOAulXzduRMUbO1zUDTJblfRDx8Lc3Pslz9GPe/QsFvViLQrDphRpftqrWZcBq2WKO6yoz3qEFwH9Fxc0jaEX11ivmKY5Txcjskgm7tUyRR/FsNWyedqHzBKkDfUyEv5j6GlTR5w2uLjFnqQCqw4d/Y9dMj/vs6oSkqC56ostL3roUDL8AKJBTXOeQM/S5CEmtthliBk22MRSNwFJ2GK04xd+4WXGL1zgvKKoIuJxyeUqQxvH5v4IJjVqGV71wH3scOgrRKDNFAwkGYXtCgU0RUjUEzV1/bBPm3RVntJQ7lricUkdRKhFSG01Qa9GhzAe5cx9hsrk/Atii9ViIQoDy2hLoNrTLOfxfEyYWJatptcr2ZBQPeozfe6SdR6T5zFqGaLGNW4lpCDVKmwiSDKbSdvFBVLdIbP4bufnYqkAEHiicUlTBjRDodlITqJ8DtWBJR5V33P4+00ff4/qTe/9F0B6fMA/673/Z3/dQ77buP+dXsn3+l1nSqlfAb4AvPf9vN7vteP7MvCV7usPvO/7Z18f9OL+Ne/9de/9bUS08te99/8r4C8Bf7h72B8G/mL3/V8C/gmlVKyUuoNsZ3+52x6vlFI/3Kk5/5n3/cx3PxTE45JkXMpK+jJkurPi09MnLNuE12Z7XJwPuLs1IzKW49MR2+mG53/sPknUEGpLtYgxwwbdbzC3NuTHfXShmc+zK++aqkXc8sZ/+KkOgyVUesGbKZTudnKTGm+6mJ9ayWT55xyb20LAL/csZhmgMgmNdeNuB5DIalKNGppPboiThl6/4uRsyNb+goM758RBS2MNSsF4e02vX9GuIhlkJ43sRrqLUDeCzlKDbkdRi+DHRV2S9KWsjtUzalbQxRDtNrSp9AFNrlGLUMgjTyIIhEphq06VWAQsTgZYJ/DioCs7LcuEB4sJsyJjXgqhpRfVfGL/iIulKFKTtObmaM61yRz7XMFgnNOsI6rLBHcRi1jHQzNw+L7FRl4m2rWBQQvnMc2zlO9OZWfOI7GHTC31LKX/C9J7cqeJCBpKAVj3RoXsWlD0+9JX299a8ObTPYpNxO54Rb9DrTXriGouJadsWOAjT329ppnH2L6Vv7/22L1alHuRvepNmbLr6SqhfpjLALMxHP2Y+CO98ZiVJtgv2L87oz8o2dlZYK1muL1hMtkwGBeEwwp/KycwliytiYKWm8M5J6sBn9l/zGKTkkUNz107JX5uSTwqJZ09tsRxiwo9vVGB6jeoyFFfJphv9fB9y2Cag4e8lHSQJGgIjaUfi7q0Ny7QgVCOnFP0sopwuyRMGwaTHNtoVE/wfYNRwe5oxaqIaa1m+6VzsqhmnBTsDNfc2r5geyQcWr8l/TWXCdtU9VpRPQ7F6K0CB+NaHhN7/KyjmFSaphQPoRu1ZPvrK8VnsFUKeFt7zF4BjZJMyNCxziVxPklrqkWCcwqbhwzTkshYqjZgt7fm6WJEL66lL9gToZP3gFPM35xSXybYRqO3K3xjBEOYdZUKL8Gz8YVweemEbb5RovzuuLi63xBciL/Sr0JJZEksqlOHm4VBRY72ce97Dn+/+UPJYvi7ff29H99t3H//8beQOcB0k+NPfsdXqlQGfBp45/t9MR848Xnv/+SzL+Dy/f/vbvt+jp8CfodS6i3gd3T/x3v/TeDPInXd/wb4o++r4f4RZAv9NvJm/8r3/jUerb2UiXZK3KilrAO0cvSCiucm5+zuLkiClq1sw97Okm+d7rKdbEjDri+yNoRRi1Li1yKTOBS3CUX2HHT+m1jk9MnTQOr7ABsjUSSdIsvbDlLtuxq/gvv/JEJIAQg8028g+KntVsqOhSLoUgp8R7+v64A8j3GVoW4CamvEIG6FOrHXX9GLa+JJCanDxGLqJbYkpxLlQi0lIPfswuxUr6pTRAIc/ELbTR6IhWEeEOQSTmsHVtLiFdRTe2W/MHGLd/qqzGq9YnE0pLXCPLw7vmC/v2IUl/Siml5aUbdGkq6NF1N7r2BVx1zvLdiZrEijhnRcEI0q6LVSUs2shM5uDLoVJqsfyALCDTpxRlcCNVmDjX2naBRz8eKzFc6JRcLFDjNsmO6uKMuQNKm53GS8tHXGzdGcujXc3J1x7/CMNGi4fHeC1l1afeAwykt/cKuQHWeXt4gXEAGbAL8Qv6AKHfGxeLR2vqyuFIAu9PI6ci0Ziv1W+m3GCX1HefI6Iokb6taw2iSsFilNh8Ur6xDnlOyYlWenv6Z2AV+48R5b6aZ7ju40i+yVECbq1VIuV5D0K8zS0Dxf4D3kRSTRRJUh6NXEgZTXjHIUq1hwaFVwFSpsrZYd5DO1ppe/S5i0rOYpRjkGaYXRHu+haEJOlgP6UcWiTMnrkOTdCL+RvrjedIQhwF5ERL0aP2rledchrpaJzI8lSohAdmnP8GnFOhbKSys9Y5Qg+wAIPbZLTnlGJTHaQSsGdmUVl6uM3d5aKD5Bg/OKvd6KXlSRRRK5pRSwW+IiaUlED2MxzhtPci6kJZc6XOjJr1n2fllyA3WDEIiswmxVsigeyZgT5Aq3jIhmBvIAs+y8tpnF9hxR2gUkfxjHh+vj+47j/q87/gLwFvB1RMn/N3/d/X+mK6d+BfiPfxNttL/r+I2KW+Dv4e17738W+Nnu+xnw277L4/5N4N/8Drd/GXj1N/M7lYK6CkizGmdlFbc7WNM3FWf1gF98+w4//Nx98jbi7ZMdelnFZw4fMwxKji+GHG4tePFTDyma8Kov9cQa2muWKLbUG6HBB/vFlXWhPGwJj2LUnQ2qEMq9DyV3Ty0DgSMbjzkPMbWi1qK0fLaiO//RRnYfqQCmbebQVjLQ6iogTWqc02jtiEaWdRnzqb0Tfu7te/y2F9/gST4S6LB2jHsFS+Vp6oDJ3gprNauXIenVtMsYE0g/zJdiHKYRgnw98USXmoe/u0MtBZ5g0yVIRJrmdi30l1oTDGrcOsFMKuxCIomUBr9Vk2Y1Gs/02oKiCrmRzRmGJY/yCa8MnvL6ep86DQiU46JKxR8F7PTWTOOC3EaUbSArcCeT/nBrw/JcaCBmXIFXNAMxzkdxQ7GO0RchbtqQTgqKZSKxQ8Puc00kTcJ3KQ6DvbUYzxcRTVZJJI1x9NKSQFsio+nHFZGR1cA7J9scvnjKqozZvz1jWcSsy4hylkpVoNBE+w3FMsJHDn0ey4CmPWHcUjtFdaPGnIfMfkcJZzFBobHXSxGRHJb4dUg6lKDc8jKhvEgZ7q5pGsPmqI8Zixq3NyzZHPWJAkteRDy3fY5Wnr1kSWIaDpIlgbK8vdhmN1uzWaSYuKXfK2luWopSEkr08xXeKqzV0ldsJNHAGMfghuwytXYkpuXxakReRsT9mjgUdqXzCmcVeWOIxxVhYNksEymDKhj0Si7OxlzkGZO0IG8idntr5lWKjxXrOqZsAvzPTmh+qLgitejdEruI0IH0SpX24GRhaIa1TA7nhurA45RHhVbOodyQ7m9kYnbSX7eVQV+E6N2K9jKBrMWWBtO3bI/WnLy+i7pXML22YF3EsogB+mHNL33rLl98+W0+s/+Y07IvySPjCx6uxoxHG4E1aATbttsSnIWSJt9D+tCWqxLme79fE6w0+t4atYnI3g7JX3JiUUgtzhuasSym6922I7cgY8YiQO2XaC29yR/40e1e/56f5n1j/a+7/buO++97jAf+2He57yf+nl/c+46PLrIM8OcSAhtFEia7k0qcx8u9I37Px77J0WbIuonE8OoUgXKkpuaVw2PZheCZlynjpGBRpmRd3p1SIjTRgaPJQ6Fb9FvCC0libgoxdwMip7bimdMWoqWUNZ7J7wdvm24H6GVADj1qHhIuJZ3dtXLxRkfCViyrkOU8Y77OGPcKbmczftdLr3EnFbXcuooZxwUH/SXOKdp1yHzWI42ab38wlcE5gWDHF1pg3oWU33zoRU3aYd50La/3GT4pjGVnhfbYMoBpfZV1pxpNNKhkkK8D9vsrLi963JxeshOt6JuSrVhWq5G2tE7Tei0DlBOUlFaexDRsRRvuTWYcDJdUc7nQve88XtpfAQaSQYUJrFBHAifA4F5NsRQDdjQpCeKW3u7mCtAt3irN8qwn8v5pyWqe0baGy3mPsgnJ26gz3Bf0w5rDbEEvqyiakLZjUeZnPYpNzGBvjd2EpEcySQcLg04sar8QYo/V1HmIX4Ty2cdeqB+IcMcVIkaytVyOTR2gul7q9rU5VR1cMTNto0nSWlI4JhVR2GIrQ+0Mx+sBmzYm0i1/8+k9TqoByyKhdVqqG0mD94ppX2KfXGZZ5wLwrpeRABu0JxpI2oP3Esw7Px0wDEuSoCX6m0Om/ZxhKpadUVbQyypBpNWGfB0TxC2u0QRRS1GJArq1hqfzEVHQkgQtr0yO2euvJLzWaqrfsqbXK/FWX1U5SK3Yd7THWaH2qEBwbqpV1DekhB9nYmExZ0Iccl5hT0Rt5huNiS2uL4QdWiW9aQVJ3JDXIThYLVMuL3rUXUSV6Xbbz985YjdeMQhLpnHOneGMJ5shu9maXlRTVBFR3KCXwRWcQlWaeiwAAmpN9qSLMbKKtueklNkobApB0lxN9lFWy/eJE8xiF76MUwQbha015TomzN53Lf8Aj2fg7+/09VE7PnDiU0qtlFJLpdQS+MSz75/d/vfpNX5fh/eI/DmpKTYxOztLItNyVg/4q2cvc1IOOV4MyYKGi2WPMBDyyJNyzM3skqIJcUhc0ZOLMRfnfeqfn7LJY9rGEJ50+XWdmVitAtpJS/Q0ukoC0FW3eu1yxFQLxfWWdmRph1K6yK95MdeGIrunFYl7s99gNoY47QzOqScMLON+znCcc3P7gtoazuo+L/eOOAjnbIUbXtk6xqG4rFLSpGa0t+L2tXNWRQyFoZylkLbYyxhXBJTXGsJ1J/W2iCCg18oKdNxgM0cztqRPjGCXvtnvaA4QP4yuwMlsRExwNUAvIx4uxuztLNk0EX/n7C4az7V4ztrG3EwveHX4lMzUDKOKa9dnhIHlRm/Oskk4q/p89fEhj+dj+ts5o17BepWQZRXZoMRZMXXXlRQtzEhy5/BQn6eQG1HiBlbM31bjzmMx/3uwpWG4s0GPa3pZRTYs2BmtGY9yDvpLvvrwGvvpip+cfovENAyDkpujOVkkQOh5npLtbBgMC6KwZXKwpP7htcRc3cqFs1obzO2NCGFOYtSoIdqW3YRtDH5aowbyd26vl6hFKCKIypD0axn4rSaOZEGgBzU3D2esz3pMd1Zo7bm46HP72jlP5iNOn455bzXBKE9tDcsm5YXtM4ZRyenpUNieTcDT07GEFu+tJR0hcsTjCr8M8VbTVAF5ETM/GdCLag6vX/C3vvECZ8s+7h+aU7UBp/MBcdRiu6A5W0uPOe1VojAdlrSNIZ9lBL2GzWkP22p6YU3ZBlzWGZ8cP+GF0Rk3JnO2Bhs23SSMQloJ2ksgcSP9u2cEEVvKYtHMQuFxPurTH5Qkzy9Jrq1FnRm7K1WsvYwk+bwW5bHviRAKIDAOO2zpD2QiR3tZ4JxnPN0MSUzLed1n0aQ4r3lzvotWnrfOt9nUEYGx1HWAKaSn7AMnFYZ+eyUKy5+r0cOacCnWJbeIUIGnui18WG/kfSotnkUahYocvid+VeWhvVugQ4cyTuACH8qg+QFfH7Hje/X4Bt77YfcVvO/7gfd++PfrRX5fR6MhtmxmmWCuUCzrhF5Qcat3wdsXW+yPlrwz22J/uuSwv+SiytB4jssh1wcLTtYDxklBWxsG4wL1+QV7kxX9Xkn08gITWNmhKVHwmUFDvd1KUK1C0EKBlDp94CUxuqNjqFY8aHZgiWfC7lO1hlah59InACie9mmOMtK7S6o64Hw2YHl/TGQs46QgVI438n1KH5K7iO14za3eBWnQsNtfExjHw9Mpg7RisL9mdLBEGY+ZVOikxawC2hfybwtdnKyI1TLg8L8OZbAAyh1HPXZUW45gbsRD9/IavVOKQnXYSeDrgDhsMQvDaplineJ82Ucpz1ubXf5fX/5RChuR6Ia1jRmEJZG2hNpya3TJNy/2qa3h7dk2k0FOFtVslgmNM/QHJauLjHyVELyVSkZZZNHaM+iXHUgY6LXEeznGOKLQkvZEBRcfbkj3N0TbBeOdNUUZsjVZozugc2MN1imWdcwX7jzgIFnwtfUNRmHBg80Wd/vnjCIRPQTGUjwesMllNzpOCsJABsHpcEMcNejgmaxfPHLqPKY+S4XocRFJ39Z4ESClrRifD0t8q7BvDDBpi/eKvIiY9nPuHZ5xrbfg1p1TWqvZHa/wS1mgBcYx3lvhUHzzYp+boznX00t24jWtk4m0PkkZpCVx2lA1ApuOwpbRZEM/rVBWkY1EtOLf7aFzw9HFiNPLAbuHcwJjr5LWTRffZZ1ivU4lOmsZksYS19NaoR3tXb8kjhsGe2vGQ1Gb/tD0PX5y61u8nD5lO1rTD2u20w139865e/cYZyUYdzjKcaWoGtUilN70MhC6Ua/Gbjf4VhHfXGGd4ubkklFWYlvN9PqCdFiieo2AwbssRNUFCdNvWa8SKW0Oa6om6JI3GjZ5TLqdc7boE2jHo/WY3XjFjewSox2XG2G2rouYJGpJEhF/Ke0xaac2RdGOrez+FyHqKMEraLfbTnGu0BcRxWWCGjViiG81LrVE5+Kz9J4O2i39YlcKZzX5RvqhDJn/IO34fjM9vv/RHSaVZncQOIZxifMKozyFjfjM3mPOyz6n9Cnb4IoheF70mK16vLJ/zHyeYZT0hKo6IAwtRjuKKsI2BruUFafPA2g01iPy7SIge6LJr7mrVSoOKXf0HNlTxepFiSbSS2FzDt40bG56wqWmnlqhYkyln6YGjQgC5ineQ3JtQ6Ac/bjmq5eHfHLylAfl9tX7DpVjGFb8ysMbvHB4IqxJp7rUcy2lyFxKcGxVImLx4AMRFfhYQj6Pfxi56Po15ii+Ehs8u8itlQigsCevr5dVrDeJlALvbIjDlvPZgBdunPDebMp+tuJHXnqb87pHoC0XtajTHiwmvDA947Toc72/INBih5hmOW8f7dIblqxWKb1eyWCas35vSLUnPZB6HTGcSnitswJfjmMp6cVRK97M0FJ0/rskExvCehMLU9WJOm/QK7lYZuyM1wyjioerCYFyfGzwlNN6yGfHD/nVxQ1u9S94ZXTEJNywvpnQD0qOqxHfWu7xmf3HnFc9KeF2KR+BcVIyjFry3KD6DTaRsp1vNe4ilhiovqfOXAcBF7l7UxmCgSOKWoZxSW0N6yZmUSRkUUMW1lx//pTZWioW/bgiNi1FHaKV53Ex4XgzIAkaylXM6OaCspHw5aoJKOtQRC6dlSQ51dhrGlsFxM+vyMKWugkIQ0cUWKKgYLbq4b2irkKcVySRiHBGWUmRxmg8cb/GaEfdRAziktm8z2iYc3nZ44v37rNoUzJds7YJBkfeiqDFecVFnmE6tajRXlTN2kPSYh6lqDsbmjwUoc8qJj4JqdIWN4+4TCvKVoa0QDuKRSI9y1KT3lhRGS+9vcTizmNoFc2upFO0laExAf1+SRY1RJ2Yp7QBT84m/Pju2/zyxS1iI59VnYcEcXuVg/hsx6aNo+2sK2ZS43Lp47tJi58HeC+iOR943KSGRuM7Fbj3ChpNe6cgfT2lfLEUwETn/9VJi7uMyF/8NnXpB3b8gHp8/2M5PrITn4qc4LpGlaRRDzbcG8745fObXG4yPnfw8ErttlzLCurmcE6Ubq4GmVv7M44XQ16++5S6y7t78GQbXwsIOdkuqKsA1500KnC0ufRjyp0ORDtoMScRdugkr2tuWL3YXtX127HFOqivy8qu0QE+lCyz/pdSyh+RcNBnqctmbajjkIeLMXkRszdZclwOyYKap/mQ4+WQ57bOebwc0e8XvPFkj+GwYL2JaZYx0ai6ovZTalGeVppo8Sy+SVFPPHa3FlpFaqWc6RTNngg16FIcbKOJTgLqXSN5bssUWwZkaU1xlpEeLkneSFjvxZQnGfPtlFu9CwDeXu0wjIT3uN9f8fpsj1FS8N5ywu84/Bb7N5Zs2hh9KH1WgPUqoT8oUR7CqXidJtMNy3VC1AGk29awPdjwozvvEGrLcTVk08as25h5lRAZy5uP9oizhkFaMl9nDHols9Mhw+mG3WzNZZVeTcADXXLsR+Qu4no65w9MfoXb4YKnbZ+pkV7Z39QvMAlz/ubpcyRBy34qO6+yDblcS/TVZpMI5zGytK0mfBJT77SCXAs85VGPYKegXcQCMHghRzUa5xU3p5eUbXAF0G6tgbDldN1nlJbE4bcNze9+5Qaf+eJbPFhMhOjTGsowIH4YMb2Rs5+t+NWn17m9dSFlvG6h1zQG92KJX8Z4p2gbQy+pKWsFTtNYw6qImfRzNlUkLYRHA6rEkWwVnM37TLfWnF8MiN9KKF8oMInl/tE2UdKyWMkOPdItmzZmoVNyF/E4n6Dx1M5wmC2JjOV806Nxol5VxhOElrY2gvy6SBhdW7A4Ggq+7PkN/jhFW0XZBmzymIOtBUfnY+kHp6BGnvyshxlIEG+7kfN693DOxbInPepW0x9uyKKG04sBYdyyN1qxqmN2Jit+cXabeZFyfbhgkJWslac6T6m3HdUyRi9Cohtr2lZDZeg9NGxMCKOG4DSi1QZnIJgHEoSdWExHTdJRiysDwl5NfG1FayV/ktrg90vipKV+0kPvlkR7Beq1/oczaH4Ed3bf7fjITnzeKpJxiVaeeFTy5GgKwDAuCQeW0oacbvo4p8jSiiRoOVoPOegveeeXb7L/6WOKJiRLau6fbwEw6ecMJznjrGBZJhRViFuFcjLv1wLGbRVm1IALhR2Zdz2Ly4B22gIS7FpPOjNr6NGVxuouTTqW1GWOE4pd6Z3ggcsIs1tiC8kSLEoBCVdNQO0M3zq+zvXxnN3BinGU86vnN7h5OCMwjjRsiIzltAxpT1LBeA0aDv8anHxBZOPNqKOMRF6sAsuQcLcQb9WoxW1ZNJBk9ZUvL4saLrdSMu0YppXE4gBFKXmG+4MVb76U8eTdHaLdgnmZkgUD+kHFedHjjdNdPn5wRGQsWVRzuhowzgq+fHmTdS0iHecVyyJhM0/JRgVNa9h76YzaGnqTLtvvV3q0n19RXqSowPHDLzzgZjzj5xfP8dsn3+TL6zu8Nd9hWcQ8v33Oc9dPefd4B5cqdscr5nnKcLohLyJmaUaoRQTzq6fX2YnWpKahsCG9oCL3Mf/e2Y/z9mqH37P7DQ7DS06aEW9vdhjHJad5n7eOd5gMcmaXfVwVwKjEzmKivfyqV+UiAZOrrMU8Seg/hHk/JDqTxIS2FxAPKsZJwbfePmSyvyING7bTDU+rEWURdbaDmLRLjn/03jbJnTXvLqbcHM5593JKFLa0VrPzxSNOlgOezkdo5VmUKW/P+8RxgzGOOGooyoi2MbJrKUNm6yEqcowmG+mZe8XJbIjNA3RiCfYL0kRIQd4qFquU6XTN/GWH8ookrYUeoyAJG56cTbi/3CIOWi7rjLwNeTifMOnl1G3A08WIMLDkpdgimkI+q6oIxDrQJRqUdcju3zGc/FYrlpCtCu8Vq3XCeJizLBKmozUXC4ltUsZDLMivaCCiHWc1Z8dj4lEpauTAo7VjVcZXk95sLTSaca/g4cWENBYDf2s1zmr0oKHaROh5KOXqwAo2rdZsXqpJHkQUNxqaLeGM+tDTjsX0b57GtHtisQneSVEfWxFHDVUdCvVof02+SHGtpi5CmNZidWoD1ODDmaE+iiXN73Z8dFWd3ao1DCzlZcK1gwtCbZnGOY8vx9QuIK9FwbVcZDiviIIW5xWjV2ecXA6JjGV2PCJLarKk5nKdsclj1lWM91CtIzGc3ywIn0aEx5EMao0mPVU0U6Hnm+rbIZs2cZLD1SgRtHRILQAXdAX1VuF3K5qB7ALNe2nHdBQPG9oThmKkna8zZmXGC9tnXMsWXBYZp8WAm4czFkXCxdtT1pXI7nVo8X3ZHfhFyJPfKRfis8iWZ3gt1SqyI7m4UWLFcI3BVQHWaelvrBOKruSTryQLML8UsnyzjEF5SWFIG9LdDUnUME4Knq6HpKZmvklxVvHm+Q5vzbYpmpDNZUrRhEzjnGFcclFm3D/fomkNOrJMegXWiaJyvsw4WQzoxTWbey1tHRBeBNy+ccZutORxPeWl/hEvxcc8n57w6tYRv/fO67w6fIpWnp987k2+sCfQh8PRgq2ehMpqJaGyTzZDfvv1N/lU7yFf7L/N3fSMgSl5UG+zG61443iX//LJZ2h8wN88fY5AOUob0FjDZJATGMdkskGFlnIpkx4K/EaSBNpJi8oE6+auF6x/bIOJJcaGWznD6Ya2MRgtTNdNHktqRBvSnif0eiVuHjEZ5CKACaSPVa1jFt/YYhiWpGHLcp0ySkuqJmDaz4nDln5SSWm41eSXGZuLjKKKrqKr2jIkHZQyYRSGflyzLsW7p5Rk3mkjfrzAOMrTjLRXY8uAiwuZTMNICDxlE5KEDUY5pqM1j2djxlHJsom525+x1dug8SyLGOcUdWOusGA6cASpRPSojYHSYM5Dkqjh9IcdJmtIE/HxDUc5tgqom0CADk4qEntbS7TxRJn0XN2jTM5PIB0XJFGDajTZGxGtNWwuMppKjPBhYImjBqU8r+4fM5/12DQRk7QQ2L1xpP0Kt1WjL0Tt63Oh7ehFQD304vesNcGmox9ZCRVutwVPiFN4A7bVLC56lKcZeRGJbWkuPNlnX67VcBGh9ssPacz8gK+P2PGRnfhU6HBnwt8b7614cjzh0dmU1kmZ7/58KqtYYDTO8V4xz1PuX04ZxiKUOD4dEY9KZsdDEbAA7SZkPs/IC4HfutpgS0O93WIT8Rqps5j1HYvqy2qv3m7pPZS+zjNOo+sCYL0W35zyQF/M4PQs6jQWAHZt8Pc2mLTFBJZ0VJINS4pNxOa0x83tC8k1awMebcZ8bvcRtTM8fLLFYtYnPMiZX/ToxbWE7eZGqC09C7HDLExHkvA0ew3pwxDVKOqRxy4iWAeignNKzODv9Gm/NMbNIxbnfQmt1Z71N6YEvQZK3dFVFGkkq+C067k9WYww2vHWcodpP0cpWB0NKOuQJGiZ7q6Ig5ZeULMdbxgnBUY7doZr3DKisUaILk6zP11SzVLxnA1lFe9vFtwZzgD4Yv8tXk0eM7cp02BDZQO2whWXbcY0zilsSKgsn9l6zDgq2U037I1WaDx5E3G+7JPbkPvVDj+7fInzZkDflFy2Pb6xOqSXVVzrL3jUTPnk5CnTaMMs7zGb90mjhvkmZblO8atQFL/dIkz1GnTSys6jEaGIq40EoR4lRGlDOxcO6+5kRaAdvVHJwXQBwNm6z8Fz5wySiuyxQXcG+k0lf6t0UJK+uCBvI3pRxc1tKS0v8pTLTUb7ixMpI5YxQWRJx2JYb8qAKGmJ+jUmbqW0XhiCccU8T+knFXf3ztmdik2m1yslTaFbjHkPg0lOf1BSdSn1adygOzHI0/mI2WWfe3vnAHx8fMROtOL3H36dO8MZz2+fszdcYbQnjhv29+eoY0lTGY5zhrfn7Ny8gOsFi8se4VZJry8AhDAUX+Jouma7v2a3J9mE+7sLzhd9bBeRZRtzxX3VxtG2Buc04VZJ/oLQWHYP5gwGBY8e7JCGDctFxiIXS8jNazP5e6FIRiVBIM+xs70kuLmhOM/QgwbSLrJoKvl6yopH1gceYocuDCqywtC9DGmmlnaWECQtwUpjL2LKcynv69hKSkRkCdNWuK/5D75Q90HClo/iTvAjW+oEGcw374ywo5a9wzlZWJO3ITenlzivOLN9GXzXCb5XipzaKZrWiNdmHVJWhmRSssoFT6Uji5tH2MRhKk10ZPABVDdqUJ0RtWfFbDuPUKEIRTY3HXoupnQVyqTXf91Q7BmqbZmEgpNQOI6tEVBtLFl8bRGiuz5HXcWMvhpS/XABieWd166RHGy4MJbTiyHnox6Xlz2m22uKKqSfVJxXAYuv7KDGgnvyK5H0q2GDv1bCRUy00FSJozywTH/FcPHDDdGTkOZOiTrrcspWhvDemroOoDSoVYDelUVCu9vgVxF60OBahVoGnPQHNGUg/rrasL21YhIX5G2I7VK97zx/xKaOmeci3ImM5RuzA17dOuJGNhfLxrpPtrfm9HRI1GvIkpqDwRJ15wzrNB87PKZ2hi9u3eez2X1uhxfMbUJOxMolhKrlXu+MX5nf4guTd/nV5ibvzLf5xflt9qdLdrM1x+sBrdX0opof33+b15f7fO3ikGynYRSIof6NfJ/P9R8wi/r8c8/9Aj9/+RxvbvY5TOY8Lcdo5TnYnlO3AVlSU9YhvZsLNl+fYq6JEMKVAWZlsPslJrHEUUsbS0zS1uElp5cDku2CcVKwqhJqa7g5uaR1moff2mfr7gWzZU/oNJ9Z03Sfo1IKM5Uy9GYd8140IQkb0qDh8eWYrcGG+SZl/OMnrMsYrcVPtjXcSA8yj4mjhsWsDwr6X4/YfEpsI2FgaZzhosgo65C2CljVhrRfMX8yhERSGOq2qxIAgbHMToYMpjlFGdIsu97lgea8zAi05WdOXuL6eM798y20lonSeUUvFsuD3y/p92oWZ33MMmD7pXP6vRKfKcoqZHXS59rtcxorZvX5IhOKTtgy74RKSdyQhA1VG2A6ha/92gizvaHYxKwuBTyutypsq5lvUrQSDJ73islEyDcnmwFGOx6fT7i1N2N7uOZ0MUBpz+nRWOhG2yU86KFuFtR7jaQvrEJ6T3Q38RlUKx5fVwk5xoVeFsSVpp0l0HfoUU2UtFRFiDaeahULb9ZJmHV840Mit/wDJG75yO74vFMSADpqiYcVZSPhsiebAYtOLLG86JGvRd1XlBGDfkmcNFRlSBBZzKTCZFJGsw961MuY9PVEBh0vKd/VjqPNPHgxmfpWS2mgNOKLc4pwLZ6+5FRjNgZlxI+zfN7R9j261OiZJA+YXGFTh1lrVGhFIFNp3CbErSJ00jL/eINtNGm/wmxV9FIxVodRSxpK6aesAwLjRFVoRSnqUotfROhRlwvWSEoBgaeeWnQsyQezH2qFcr8lHipdKzGzlxLjYosAtQpIjwT2rDvTc7bVlfNWIeFBTi+pcWtJMuAyonHm6u8zSXMOthYE2kkpTIvJubaGQVxS2JCjYsjZuk9RRhgtIbT1JqQX1bx5tEugHEY73pltUbUB28GKC9vnV8qb/Bv3/wBLl2LRPG0m3M+36Yclb272+cbZvvRyXst48nRK6zR5HbIsxDZR2JBrmUxg1isOwjn3klNuJzNKH/Iwn3BUjznJ+6Sm5rQe8OXTG1ysJEx3U0mIbbGJyIsIe7PAvTZAfbOP6TWwJ+kdWVaxO1iJeKMynF4MieOGttXMy5SykXXp+aZH0Ybs3puxLuR8bSvD1mAjCzIFxXGPXq8U5a6C03elxF21gZyuHfpstuqRFxHLecZgWHC5SVnOpfwnmYoSlru+a4neSYjiVtS7VrPaJJSF0FRQIrjyWgDlYWAlFeEiIQwtVS1m/aYVWICyCjOtuCwylqUsIu9OZySmRWtH1SW1F3lE2YTMZ31R4CqxIPhtycaLA8s4K0jihnQ7p2wDdrI1WVRza2/G9fGcNGyw85i8FgXrM6+h7jB21c2aug7ETlJpyfxzCvN2RvuwJ7YY48nrEOvEy7vXWzGMpcRY24DH73w7VUd1aL+g44faQv5uqhQww+alWoKGNzKx+NBLOkbHlzWDRsTfHui1uE0IXxtc+U2jnnhUbW1gp6LMv+/81Q88/kHa8X1kJz4A1SjMIqA5zlhe9mQAqUO8h8eXY0zSEiaSsBxHLfOLHnUt5cv6PJVIlTLAWYU/KME4qomgvMxGAihdavGHJen9kDbzhJeG+FFEdCEp66rfyGrPiJHV9mTySV9PuhKIF57fpEH1WtydAgJJO/etRoVCdjcD4fy5RUQ4qMEqinWM6vpdZRVSXIriT3ehnlHYcnoxRIcdk7PRYuw9i+ViazXqLJYJLXKE9xPCYYXJGilxxrIztYclNnW0uzXVWYbaGOJrG/KXK9rGYFsjLFPAt5rsYE09k8Et2S4kbmjYUtUBJ5sB55ser715Ha08RRtyvuqxWshK+/KixzQuOM4HjCPxxkVRy3qZ4J1if2+B0Y67e+ecLAfsZWvuTC/IG/EGPh8dMzVr/qHdN3naTPi55Qv8Z+/9EKdln3eW23z94oDd/pokaog+d4mJLZeVLISqdcTpfMBpJfGRW9mGv3N8l5VLaLzh1fQRa5uwqBK+Pj/kIs/4+eM7/PzRHdKwQWsZLKsmoBfXBLElCETMELy6oL5X0u+XfPr2Y5QSIMFhtqQuQgbDgvFog9Gew60Ff+Te3+J/+8Lf5oe2HgIQKMcoKYjDlihsid5Ipe9WBthWM7y+pKxCNheZoMKurxglBceLIdcmc05f22F7sBEyTkdweWZn8E4z3l+yvMxoN6HsdkJPdaum3ETkeUwUdqrZXIQmrgjwjSEel7itmvU6wRcBqlGUq5i6Coh3cuoqwK5Cou1CBDBLeX1fPz2gH1aUNuDe1oyDrQWbImY8ykmjRozaTlNW4onb2V6xyBMuVxnrKuaVnWPSuOGwv+R37r7Gx8YnAIyjgl5Yk+zkbDaJVCOsZnHWZ9CVZ3uTotuZeuF/9lp8q7FpF27bxQmtFrIouJj1ef1kj5P1AG8Vs1WPaKugPu2UqpMSNWgoLlJc5K4S5H3sIJaefHu3oLwmrQ+QwN121MJa7DR+1Ahb90y4uuW1FlcZTNrSVGKDiNIGP5MS9Q/88EJq+m5fH7Xjo1vqbJXkeuUGM66Fm+kVq1mP/DLAJg41EkWbd3I7jcJ6sSX4TEJcg35NvRCxhrKye6sDrlLXVasx76XUQ7lo2szR9rrYlIsI1xiCNVS7cvY8w4CVrxT4WXwV/+Iqgz6NRVEceXxqJdak61216xA1lotGay+0FONpvSJI5H3oxLIqYyaDnNPTEbmO0UGXFqEgWGm80JOE/qA9wY0N9UkqLEAP6t0ebr/+9pKoMHjf7dSMl1TsleSVkQe47sIuzgZCvtce6zTRtGTx2hTlFO1+jQrEV1WVIf485vDFM9ZVfJXekPYrEc7kARdVyqaOyWNZ2W5Oe4wOlsxPBsyWPfS3egSfWMguwxqerEb0opr/4J0f44d2H7IfLzmtB7TOcFlnHPSXzEoRMJ3MhiyzmmFaovEUxnE6H6C1R4cO+yTjjd4ulxc9dOh49doR7xY71C7gMLzkS/PbPL0c8fL+CcO05ORyyHN7Z6IQfn3AYrfFa8+5VfhHGU0sg2hBgh+0lHXIk5UoK6sm4I3LXW4ezjieD7EPekR3V+ykG/7axctE2jKNNlcex6ZTFJZ5hLtTE2vZzWM8y+MBxJb0vZDqecvquE+7o2nqgHdeu0Z2Z8njb+4THObsj9ZsHg+wkSWJpCS3WqVEWUNTiR3Hd4B3XxlM2rBcpwz7BblVkgKvOgFHLikEzglD0y4jzCzEpoYyDgj7NcGkpL5I0H0RvZydD/BO83fm94h7Nb2k5uJUFhvVkx7hYU6YSIRREjWQVqzLqINcO24PL/jn9v42/6H7Se71zkhUw8u9I17pP+G0HpK3h/zYzXcItOWt5Q6VDQgPxHwPUGwi3Dok2ipxVtGWoVQ79i3eajYnPWg00X5OtYjRkSS11MuYwddDNj8kW6BoVzi95LJz6+9s2Fym2CIQUlMjwrXsqaY4cGgNPnKiqm61ZGNGHo4Tghba3Qa71WDOI9xuRfQwoVJiXm9bLT3hYSPj0YdxfAR3dt/t+Ejv+OgmGToBgfdKhAWX0g95BufVxkkOnAZlHPooxrea6M2U9iSVGnxuxMvW7yJ4UklHJpOAV7TsMEks4VIsCMmJENrz6+6KikLowQh70Ie+SxxXEjqpkLBXpEyicwNG1Heq1uiO9djWclEBsApoz1Ks7dRfHs7e2mI0XeOLQAI2a40e1d9GpQ3bb1MmugndbdU0Q0+4REq5TkDfpJbkxKAb+ZxwSgJVy85vGHcxK7GUPOMHcbdCVfgQ9N21lHa1pzcpSNIa5RSLXKgZg6Rik8fUtSQLkDgaK4kN6yZC40m3cxYXPeJxJcnar6xoWsNmk6CVZz7rczof8JOHb3M3Pee4GlLYkL/18B7fOt8lC2pRtlaxSPE7pNflKiPsPHDOKREqDVsuZv2uDyqfcagss6rHo2aLvA15ef+EN892OF/2acqAJ4sRSdBS36ihFnGPbeQcCJea6FITrmSh0e9sH67L96taQ90G1CcpNvH0k4rr6SXLOuGrZ4fMm5TWGSobXJWK3SZEhRKc/CxZXZUaXxvqLveR1JJfptjKSFCy0wzvzYmjlk0dEV2KUd064auawFGvBBnmFhGuNpjQoQspc6ZJTVGFqKylPU4x6wA3rTGVAiPZksY4glGF263wkcMsA5p1RFMFmGFN8E5K/bCPPo0Jkoa4V1PnIWnYEGSN9M97lnoZY1vNZpaJvD8Q4PVs0cNoxyQS/+QwLIi1/P3+1sXz/Ntf+u0AvHa0z6qNOSmHbCcbijpkU8SSuO4h7dWYUU31bALxSEm+4+ISOei32Ac9VK1RM4E3BL2a1SdqBoMCPGglJVJlFeFjWcRRa4LTED9shQ8aO/JDsS4pqwjmwsVFSVVGGY/uoonwYsOyA4urDdW+RHBRiqIVpKKiPowdH/9g7fg+uhOf8QIEnjT4kwSlYP1wSBBZihutDOJeSW5dFeCWETpthbHYF0BwM/RMvyYnrMss8ZmhnbboWsJcfejxlZG07b7FpQ6sRrVAHpDfblGxpf+ehkktVBQreWH6MryaUNU8xIUSSUIkESQo6R3oWYSrDNGFwQ3bLmZF4UcNutdA5NCTiqoL4qzrgGCjyYuY6CyQmCElPR5JWvckkxLfauKkoTzOSK6vCdMW22+ptqWor0e1DGiNpty3uMThFhHxQ/mcVKNQjSTCgxDkmyqgHju8FQD2nU88xnvFtb1LxqOcJGroxTXJrSX5UiatJ0cTbu/O2B5tyC9Tptsryjbk9GTE08WIi2WPLKmZbq+Z9nN6aUVgHIOs5MbOBSebAa/cfsJL+ycEytI3JZUL2ItX3Jhe8tL2Kcf5gNlTSRbo0qRZf3kbWxuaJqAuQqzVsA7YPZiDVYxuLJiOxMz+c8d3+fToEa9vDhjHBesm4vpkTl0GjKfCmDxb9iXVHtmR+3mE3W5obpVUNxraOwVRr+HifEDbGvppRVMGFFXEKCkwWxWDG0saZ3iYi+c0DRserifid3u4w7JIKPOIoAsirbvEclcbia5BLDG+MUx+Maa/leOtQi8DysuEUMtO8Ox8SNsXBXL+cECdiyfUzASJxTPY0LMg1Vyk+lUZ4YoAtV0Jeu8iEhGW1ZhRTb2OZEFnNWYVYActZhmgT2LcaUJ1KAO526toLxLqIiR5M2FdRYTdeTR4PSTo1ZgOwZbEDaeno6vdWtUEPJ+e8hcuP8tz2RmjQCbBz43f44997m+QmZrfce9bfPNsn1mR8c58m6grw2828RVCLgwtJmnRRnbkEg+mZLHT8Wb1TUH5pcfdwsJJFNVqJf668jgjmAe4zNJsdyXJwOMS2TqpVNLjlVPYVGLA2oHFFNJbxDj0PKDtW5otiVxKnoTCvC01Zm2Ij0KSI0N4aQgvAkl82Hx0C3V/v46P7sTnlYhGLkNc7CE3mN2C+iKRSa0MpHTQ+ZHIWlxpKC4T4jNDMC2x2zXnnxe/lS4M1dR9u9E+qHF7FeOvy8muepIaQKWpDhqRLocePYtYfaLC5wHxueTe6cjiBsLxA6Hku8RRjxxUsmIEiC86o3PgaQfiZdIWTIdHcq3kv9lcvGFNGaDf7uFui7G42pXVsAqklEpHZgEIs4a94YrbLx4TBpZBr2Tv2pzpy+dQCmeR0qC6nD6cqECbkZTXwoWBrKW+kF6e0nBt75Lf+vnX2d5acThecLbu87kbD7nRn7PTW/OFvfe4OZpzb2vGK7efUj/qs7WzYlPHbKqI3QOBQANMd1asjvvYyrAuYubzjItVxux4RP36iFe3jvn45IiXp8e8PDrhZCPJBH/u6afZi1ec133Wdcy6jahswHB3Tb0JSbYKijKkmjpcGdDMEqZba3pZxc2Xjjl9Opadt9NEgWVZJnx65wkO1e0UA6ZxwTtPd1DGMz/vE4RSCiOVsq9tNARe+JCNJh0Xgt0CfKNoK8MwLtGhI0tqijakl1Vo7fj07mO+8fSA002fYVzyiclT+mHFy/ee0ItrhqOCZhXRH5TEcYs/TgiyFjoPqLIKHbdcfq6hLASGHF3fEA5qzt6bku7kZIMSv10R9hqUBx1YdODQt3LZTWgvWC0npXYdtxSbWCbCSuPmkfhBFVKuswo7j6CWnjjrADdq6d0P5dzercgedxmQ0wZXyrmjTmOKfQt/dSoBwMuI9QsttjZXApn5rM/WzpLAOOK44ZM7T/ny8hZ/+/E9AD6WPOFGNOO/ePczfHN9yNv5Dq/2nvB7b71G3kRM0pyiCdkerrm+eynG+CagPMtQxlMtYoKskUWlB2opKVJqbNcTLz9ZEF3bECc1YdpK1aLLAGzHrSRGpC2ulqDcZ8/lrb7KvHQ9C4EnWGtZRKZO4r0CDxqpNoUWFwHLEFKHG1iasaO8V9NMLO24lUizyYeDLPufdnwfhcPLLsQljt67wp/0TstqalphQofZGCi1lBk9mEygzc1I+IjpoCIel5gunNInVoyklcjPlfIsP18KcLqRrD2s6niLHgoNu6IE84GnGcku0TVSEgFQ2xUq9Ni+JVhrMbZHnuGbhuLAwqDB111id7cCb8tQIlaswrWSi4fv4lleWKO0Iy8iVOSwWw1RryHs16JeM562Dhj0Sj45fcLHJ0cM05I0bDg9GgvtIvCYyMnuE9CV/F7zJOlQa50MeyPAYH0RQau4M7jgIFkwX2fcf2+XH7/2jkwWLqBqA746u8aj5fhKTLL1wjmXc1HRlVXIYpOyyFPmm5StbMMrLz3i3o1TkqjBrYQqoiIL9zas25jKBbzSf8q16JKfOHiLW+k5w6jiou6xqFOO3t2mdZrYtCzPe6hFSNtqgsChxjVmJSXjvIzYbBJOFwN6WzmjrbVE2zjNjx68S6obFm2KwROZlnmdXAWYDiY55Txha39JNijR4xpnJZhWKU80kF24CZxMHIEnzhoC7TjYWvD85JzZusc0y3FOMw7FV7fbWxNpy3a45lZ2wSzvUTQB86dD0kkpcURWE6wVJugIJl3/yJYBFBJfZCJLUwfymrYLmrcHFJuYbFChtGf7hRlBZAkCOedBke1scAOLWoT0HyjcOiTrV0Rpg26UVANKSRtJnoSo2BLOjaSEpzIJew/58/XVObR5tQIN0ZOI4FIWnW7aoCc1y8+XtLWR5IrYos5j4rBl0s+5c/2UYVxitOP57XOsV/yBrV/jd936Fr+9/00+Fs4Y65z/5JN/gn91/2f4kdHbbJk1ry/3+dT2E2prJDU9aEQsU0Q064hkJxeObyaByt4Jho/Aowvh57oqkB1qq2i6snA1jynzCBN2VZlGjOY6dKhlcNVuQCEg6n6DixzZe0K3aXsOdiqxNHVBtSQW5cDnAc1YFh6UGrU2oqg2HWC712J7DqU/pJnIf8DXR+z4SE984UKL+vFALAO2lv+72qAeJZKcbLyUfTZCJ7GDFnYq8mVKfplSn6a0swS/VXWePKHF16ep0ExK2UlSa1nhp2L2Vk6x/RVNcD8VOHWtCZcKHzjMeSSepkx6j8FxRDgLaA8qXM/ixi3L57s6ftcH8KEnWMtgG/crmYBKLUQKLQSIugyo5gneSWQPVoQ6zoqwp7+zYbK3wlnFQX/JfrwgNi3Pj87Y1BFb+wt2p0viUYU/jQWcO2qwOzUudehnSMiuP5k9NEQnAW7ckGwVnFc9HhUTtkdr0nGJRTGvUs6KHg8e7lK30tM6mo1Y1AlRYBkMCi7WGXd3z3nl4JiXtk/59OFjsqDh4+OnTOOCw+ESEkua1dzYv2AyyLk/n+JQ5Dbmm5tDPtUT9eO9/jmVC2i9ZnR9wVuP9tjUMTiF3i1pi5DiIiVKGymDB5727QFh1DLuFaKGNRZrNaOk4MFmSuUCYt3yX331k4zCgmFU8YlbT4jjhtVFxrgz3m/Oe3JudekFzmrqdYR3ijSu8U6jQysYMdeVRZWX3ESv2eptmAQ5n77+hOPNgNIGvJ3vkOiGQVwySCoIHXUZMDsZUpcBQQG2NaTjUnYqPUn29rFj87TP7nRJv1+gjRPhSiul581Jj7Y2JGFDnUdoLTDtIGlkok5b4nPN4rM12e6GzWlPiCZbHeVnWGN7jvKwkVL97QLft9jSoHoNqpC+VDysJC29NGLWHjiJ7zoLiQcVQWiJswbXijp4NN3gRi3zecZs2btaYGjtuds/5xP9J9wIZ1Q24OvVdb5a7/E31h9j5jLuhRn/aP8BO8GSP7j7axQ25LNbj/mhnYdM44LT+YDf+cLrJKMSD+yM1wRRSxi2qMChhzV6ZXCpUHDIDUGvxXegimoZE48rmdQeZ1KuBMnNbDR+0BJcBGKRqDXBIhAV5spQ7DtULEksrjaoZYByEJ8GJMOK6EwSGcK5Qdca3QVDu0iS402vIbyfgOOKPPODPBT/047vo3EoqA6EUOIy2bGZ04hsLMrDZtriY0d8EuA62T6l9CZcLd6ZsF/jI090adCBLOO8ltJEemxkoPGq42l2cT6lNMhVpTn/jMcFXEWplDtiXrdb0uvwqRVItIdmIhPmcHsjKdIHkhWnlAhgVKuoty26VlTriHA/v1qJ1YuYsF9jHqakjwNRlQXuqsTWrCPaVUTTGOazPsNRzjTO+ZX5LZZNQu0C0rDhY9OTK2rN9gszskFJlDVcP7xARZbmZontWxHnxJ72M2vqGzVh1lAVIW8d7/ClhzdprWaYlbw+3+N4M8B5xcv3nhCHLWnY0ssq8joiMi2jtOTz1x6SBQ2BcmRBzS986x5vz7Z5UozJgprLImN/f87+cIlRDusVkbEUNmRtZRD42flLVC7krOozr1MibVktU24fnnO5SRntrQhDSzYqMLmmnCfoyJLs5Yw+fi4EEmDSE8bmMCt5MJtykC55a7nNG6s97tw64dFGoMrvLSbSY6uFm3p6OaC3vbkyATeNgbXwNv0sZvXWhN4vpQSxJQws9x/vEpuWiyrlhZ0zemHNXrbmrc0uX3rnFgBvP97l5x7c4yuXNznMlmjluXbtgl6/IhlWuE1I++k13snvi4cVaikClPRRiK40R8cT8iKmzUPxp72w5snJRC4RBce/dIiJW5zTlPeHtJuIdh5jS0O5a4U6Y43EZXV9cdcKtg7j6d0PYVIL+Nk49DLAr0NMoQiW8jmrDmxu+y1+1BD0G4nqcrIgKy5SBuMc72F5fyyc3aymbQzzMmVZJYyTgp8Yfou78Sn/3epVnstO+PLqNn/+/LP8t8cv8RcvP8P/+fQT/Jfr22zpnHfKXa6lc27EM37x5Ba1M3zi2lN+5hc+xdZgw+F4QdGENI8lTBjAbkJh5yZWsv4ymcgB2AiwoT6TBa/tOXSlSB+brj+IJLTsNjKqKo9NHf33NLoRmMb7DeLeeNIjTbXXUOUhze0S+i31dotLnOiqjKS1kBvsJsQ+Jwn1H5a45R+kHd9HtkuqI8twe8PqMpOGc2Yxg4b8MmPypZDVLZEPN0NPsNK0mUePa2zg0asAPaioNzFmY6ivSTJycBSBAjtxFHtOjJ2xlf7dqaG6UaPnIeFKUd8t5UJwgQhhjEcBvddiin35v1kbXOqE5tIoVOooyhDlkZ5HGWBmASqSUmjyJKQ8EO9hUwWoYUMa1+ipyJ2DF1Z4QBUh7jQhe+6C4rRHODc0Ow3OKQ72LxknBc/3TgG4XwiAu7aG1DRsJxuqUUAvrDE64/hsxMU6I0gkG86GHt+oq8BZZRxhKGKhaiP8wk0V0Ytrns5H3N2e8fbJDsF0Tho0tNqS1yGbMuLaYMFzgzNWbcJxMRAwdVKQjkoCYzkt+2yaCOsU83XGKorZ6UvQ6LKI0WPPG6s9LquUO4MLTusB91dT6jagF4kApPWa5nEPc1M+m/y4D4kjmAfYHVnwmI7P2ThNbQ3jcc6qEIrPMCx5dXzM2ka0TnOjd0moLA7FSdynGITMzgbs7i4p6pCd/TlnD6cMpxvmzyYID+yVLEYBughYK1E1nq4GXB/PWdYx/bBGK4dDMZ5ueGFyRrL9lJ97cI8saGi95uHjbUZba3pxzdLFRJOS+jxlcLgiz8XTp6YVcdqQ3xAUHa0Y19UqwI2g8Qo/j2DY4B3Yezm2MkRRix2I5xDtMbHFbsTLWS9jKWkbSb3nMkJtVTjjya9bFKALg1MCdaAzdJtc0TiFii1+E1w9xgIM7VXW3nB3TVUHbE/WrFMJjo5CS9ta5qcDDq5dcGtwyc8uXwKgsCGPywlHhUSCPni4y2WRkkUNL01GrGxK4w2vL/fZ9GLOHk0YPl8yy3vsPDdjVcaUdZ/6JCUoNU55fBkQT0vapxluFWI7sZC+DOU9ZZb+1yI2tx3OaEhb2kCTnH879V1l4gckks/Ah57NTVF0ooCNobreEB5FeA35DYvSwm8lsVAYoq1ShEaho60MzMQqofDioUycZBP+oA//0dzZfbfjIzvxxYGYnvf351xuUsrLBKUd0aBi8aMt7iJGrwzBSokM3csKOOzXtG1MeZqBAzeV/pk+jWkPKimZXUSw1aG/SsnWqrasKDZTR5V2wjivOigthAuDzRybj9VEvZqmCHDLEELxERKLwMCepKitCt7sYxKP3WmIH0Yifhk7VFfqUI2CnmWQVHxi54g3LndJQkE++YHiNBpQNwHDwyUcSqRPmggo+rLIeFxOSE3Nm/NdPrf9kKK6RuM1Xzs5ZH+45PFyxOFwye6tNV+9f5203xEjSk26l+O8kvRpH1JVIe0mBKeItyqi0HKx6JNlleyapgtCY9lONszrlBujOb9v7+v80uIuby53eetsh48fHDGMKiG3pNVVpt3J5ZDmLGF0c8HiokcW1UTG0h9UvLvc4vM779FmhrvpGaUP+Ng44EunN9HK80N3HvLW5TZqr8RoT76MOsK/Q40r/DqiqQPOqz6ulQigOGwZZYUQcLrJ8DC55J18l35Y8YcmX+FmsODXqmusXML9cofZbo9NG/Oti12mWc74xYJZ3iNKpE/lX8jJ65A26yT6TrG1s+LmUCa9QDvO8j7P7Z0BMDoo+IOTX+Hj0ZyvbG3zdrWPRXHjU5cUNuJby116UcU7bx2wdeuS2ekQ3yqUBn0RUEYx0X6BfZLJ+biIZRPS2Ur2njvn5HyIfpzC7Q3QKUQ7AY4OrdggMouKuvMyMBJ/5KEOQymNBR6T1cJ0jZ1cOxfSB7Y9hzdCKnKtEiLJsx3PKiTYKVDv9NAvrlie9dg9nEtvc7DmTMF8Jti9tYLZqsd09wF/4Vc/w6dfeI+vPbpGv19Q1dKzzSY585MBo9tnfPXsGr/89BafP3yP9+YTvvHeIdPrCx6cygLPdQnvOnDoWtPu1vhSTPn1mbBfVatwqZW+f6VwCVAZVp+oYRN0i1iFWQasn5dsSl9raPVVgoRSHaVlq6VJApnY8oDs7ZBmgIhiKo1XXvx+GHDQnqToWtFsN4CnviZ92jYP0BsjSRTl/7B9fEqpfwr4V7r/roE/4r3/anff7wb+HcAA/5H3/qd+A8+39t73lVK3gdeBN+iWEsD/2nv/xm/2NX5kS51VK6vJy01KtY5FGVmE0qdYhTBopFw3dFAYKAy2CGgrCZWlJ/JiNgGsAryG+L0YNoHU9DsDudcS3qqsov922AXOfttv4yJHuNTSvA7lAmkrQ/gwIbo0V5654CSi3YRS119G1BNLfCEXTz12EmsybjDDjlY/FLrFszSBTRURm5bLTUbdCuHeGEcSiocLBdv9NR8fPeWLe/d5oXfMbrTii7sPGAYld6YXmC6RG+DmaE5iJK1iOBbJOJcRvcM1xUVKvRTvHZvgihSjvJTcfHcBbfU2PLd9jsZ3z6VZVglZIBN06zXjuODO9oxvHO/zdD2ktAFlI9lzZRsSBJZkP2e1SsEp8lp2gI+Op2ynGzZtzGuLPRY2pXEBby13WKxSCYK1AVUTSC9ukQpqqytrOytCDNd2Pd+F4K3q1tBaI69rcCE0maaHxuO85mdXL5Npz9fyG9wIZ2Sm5sXshEBbDgdL3vjmdYo2ZK+/Igpbwi6t/RnNRbWadFCxKWL2kiXHyyHvHu/QOM0oKNi0MbeTGbeDOX0VkLuYF5OnZLqmbyoCbWmsYRhVkjIeNgwmufSkak07FrWlbaTEpgstfarYXaV419aIKXqnoS1DTOQIQ4veGOJ+RRBbUJ7wWADkUdSCVVR1QBxJlqRrDcNfjWg3AdGZIT4OpK+cWqK5htRKWXynhKyFRl9dJ2SWtgxo+05IQE5xsehzejTmdNWXyKXasCkjbKsJjCVUlju3TpiVGUEkAbnt2wM57xTSewOa1gjr04Zs9Tbs7SyZzzN4JJQVHTritBE7QyHWheRJiC4kUszHDj9sr9TPzX63KK67XWyl0LnBnIXS944twUkk/T7lIXKYkwgVOMJjsSKpWmNii9lo8tstzcgKqNoDxhPPNPGpEYC9VVLmLAwmtujIYhtRVvvQ4xaReJM/hOMH2OO7D/y49/4TwP8F+GkApZQB/n3g9wAfA/6XSqmP/Saf+x3v/ae8958E/iTwf/xNvzo+xB2fUuoG8KeAfWQ6+Gnv/b+jlJoC/wVwG3gA/GPe+8vuZ/414J9HqiH/kvf+Z7rbPwv8x0AK/GXgX/bef+D6xDUG12iqZSYXnlPoRUhwfYM9ibE8U32K7YCgS0t3CkI5eYNcUU8cPnHYxKOslH5U0PEDN7JKDrpcvfzQdenlAclDw+Zui+pZXN4RUwInq7wyZu+XWx7/Nk2QNvhz4XQ+O3St8NOaYq9Ti2ZSEjGhE/zTtJQE9U3A08eH/Pbf9wbnkx55K4P32YMp0W4BQNkEtFZzuDPnx3ff5vO9d9jSG/765mWei0/YhDFbwZqzus+TfMynd54QKMuqTXi0HnNncMFlKnFB9Y6EnurdNVUjRvDp7QtO70/xoUfFjiBwZFFDMHI8eLTDy3efEgctrz05wNYysJ5+ZZ+jzw0ompDFKkVrT51H5FHDsBNxOK84X/WkfGc8aVaz3vTYHPW5/bGHjNOCg3RB6w2/a+91Xt/sX31+w37J/Xf2iSaiFlTGo88j3JYQZFxpcBgGY4n06ScVi15KFtUMk5LIyN+itCFxF5z65mIHh+KVwVP+bye/jX90+iU+Hq2xPGDjYspewGvukOsvnNILa5ZVwjTLRWQTlaTThnee7jA4WHF7IokJO9Gaf+PV/4pfWj/H/c0Wu+GS42rIF7J3qNH86dU9roWXGBwLm/LN1SH3F1OioOWs6OG84LOKVczWzoq8jCQhoFbYdYgbiHiLIiDaKqk3EeOvhKx/IsZ1qmA9rFHvpZQHFWpaU61ECKQ2huZaDZUhHeUURY87d2a88XAfRpK+sXxZJoh26HAGWTAWhmb47UvTdn8/ao3vd+rTWqN6VhTNgD+PYSBxR1Fosa5lfG3DfNEjiFq2BxsqF/DkckwSNXLuK3DbDYHVohw+Szn2UK9illbRiyruv7NPb3eDn8WEd9dU65ikL7aRfJkQBNJ3q/ZaWRB5MBcheibDYjO1JEeG8rYkabDu7AeTGtvKew0eJleeW9+3qEWAzRzZtxLaDPpvhhT7Hb9zYNG5wY0aXIcz1MZT3q4Z/UpEPQaU5GHqZxSchUEdVII/W8nrimcfwsT3A+zlee9//n3//UXgevf954G3vffvAiil/nPgDwKvvf/nlVJ3gP8UmZ/+mw/4VUPg8vt5jR9mqbMF/nfe+19RSg2Aryil/lvgnwX+mvf+p5RS/yrwrwL/Sjfz/xPAK8Ah8N8ppV7w3lvgPwD+ReRD/MvA7wb+ygf9cmUF9UO/wW8CovOA+nolfquhJbyURGd9EWGDboVXdDuw2OIPG6pGDOeqMERLYfmpQLx8+jjGRR5GDc20lcmz0ITnIe1OQ91Bd30rCs92LF5AP2jxwJOfCCUKaBmjpi0UnbCmo8JQillVNQozabCVwZ3HqHFN+7DH9MULLjZj+q9e8LQa8drDA567fioJ4HdnV/lmVRNQLRJ+/Llf40d6b9Jg+MXiHrmN+W8uXyVvY37L5G0AXhye8iif8If3f46fmX+cVw8EAVX3DaUV+oV1klMWBlaSz4OWrduXkpy96LM9XHN0PsZZxf/pt/z/OAwvaXzA/DDjr1++zLqN0ftH9MOSX3x8G9dqdraXLEOhcxwth2jt6UU11ToWU/4qYlMLG5VJzdFaYqKG0YC8DRkEJV87P2R2PGKwtRG25KSkvkyIpiVNEbD/yilJ0PDkcsyd6yecbfpkUc0oKtlNV1wMejxdDdlN17TOcF5mlDbgzYuXGaUl94bnHBdDHpZTBkHJH//6P84PH7zHDw/f4Wdmr3Irm/HucovGSlRQEjQ8upjw/M4ZmybiycWY/qCkrEPeONll0CvZTsa8m2/z6uAJ1yaX/O3L57mbnbPxEQ/KbW6EM75RXmegS0am4OFqzGd2HnF/vcX9n7vF+LNnhIkln2XMHk4ga9H9Br8xqF6LnwuQXGlPnYf4RjH/ZEvoFdu/aDj7oiSNuMOK4GkMdzZYIHiUCF+2DmmHlsUqBQ3vnm6T9GqJ57rfJztSLF9qhTM7D/GKb3vMFhGm1EQXinLf4hOLmXcG754VZfAiwKeWsNDoQOxB86dDiBzVUQ/6LW0eMNk95a8+eIlrkzmLMiXtV5Ko3m8woaWqA3zkqOYJKnT0pzllG3Ln3jHvffUaPnZUiwTvECD2O0P0QSnWgrwTr6ReuJ5DEcKpXgNFQLXlSN+NKO40eOVwzyxLS6kCtQOHS2UHl9yPaHqe9FSz/piQoeqJRlddj68Rtq8MDIhgTnmCk4jFp5pvD16Vxm4kHNcdVPjaoJMWmyhM2lJOvt8h+YOPD6nH98/z7bH6GvDoffc9Br7wHX7m3wH+A+/9n1JK/dFfd989pdSvAQMg+y4//z2PD23i894fAUfd9yul1OvIG/+DwE90D/uTwM8i9eA/CPzn3vsKuK+Uehv4vFLqATD03v8CgFLqTwH/c77HxIcXX0wwD2hHFt0girdJjZpFtH3Bb7nYyYpUgRo0xG8nlHuyRVWhY/DVhNWLVlSXSD6WW4XYaYteGdn1eQQv1pWPMI6251CRg1Ljok7IMm6g0oSzAJvJTtF2J5tPHDZu0YmIBXyrwSh4ZkdoNAxbcBp9UJKXEeFWyeIyo9iJ+MTtJ/TDisYaGmfYG644WQ6IAstwf86d5IxHzRYvxU85bwa8mj4mMxV3ozNC1fJXNx/jldERpZVT4h+efAWN443ggAebLRLT8MmDp5Q24Gg9JAkbJmnO+UY8aGUb0hQhTGA82rAuYqZmzb1Adjdh5LkbnvJWvc9/ff4J9uIV//C9r/K0GjEMSr4xPyALGs7yPoGx9MKa3qigtRqTWMKopdKeMGlRyvPC5Ixr6UJUnE3KOCkY3hLP5IWWVAp6pewaYotWntuDC5Kg5UY2ZzdZM40E2lw5ec+f3nnCW8tttpOcaVIwiXI+MXnKaTXgG+cHGO2505e8v4Phki+f3uArZ9f57M5jvjq/xpP72yTbBUsSsi4V/Wg9ZLVJaDYhbW3Y2VpRW8N+b8X1ZM6yTVi3CY1uOc4HDIKKn12+zCTcsLIJryaPedpMeC0/pB9VPNpM2DQRza0S7+Fi0UcFDkI5503gqActqpWMR5sHKI2U1EYV9SqmKUJWt8XqghV1snuGoasN0SWsX5DUcFULuYXEUi8jKQ+vIkgd9UgUjT5yMKlRlxF2KL1ELOCguPEMouCvMiiDiwA7stBvURvpfWsEEu6NF99sFWJ7MNyWv9G0n2O9Zl3EYhcZNHgPbWWIkpZkXGJbzWhQSHSS1XijsKOu2hNZwi5qyFSKFsSzN2gEGZhKdmCbttTLGB062lI+NxuBXgTYvsVcBviDEtdVNpVVV2i7ZuAxuWJzQyZUpWD8TcPlp1p6b0Tk14W/qyOLD7vreh1BT8YJXXYTpPZQdyVPZVDjGncZEe8WtE96pEcfUqnzg3d820qpL7/v/z/tvf/pD3w+pX4Smfh+67ObvsPDvtNv/RHgH+m+/0+A//v77nvHe/+p7vn/caSM+rs/8JV/h+Pvi7ila0p+GvglYK+bFPHeHymlnuV7XEN2dM+Ox91tTff9r7/9O/2efxHZGWImE1mRHVQEcUuzzsQc7hSm0NisxVyEuGkjO71ei7ea4lpLOAtwlcYNW1afrKWceRzR7jS4ixj6Lb5Vz853uYBWimanJX4SUt+qoNcy+GpEM4DyVoOKLOoyIlxowiXkA097UMM6QFca3fE97UCjB2KlqBYxYdxemdRt1dkmtKN5t08yU/CZDW8vtolMy8lmQNkGXB4NCfoNSVrjvOLmaM7PnL/KRZVKGoCThOl+UPJuvcP9fIffvvMtfv7yHs4r/szpF/lY/4jr0QW1D/j85D6LNmPepPy3b7/E73juW2zamIsq43C4ZF6mJEHD8zeP2U42jMICrTx/4fyz/H+9pnYBHxsc8XL6lIXN+MzoIa+tDyitBOieqz6NM+QtHD2ZkE0KjuoRQWhJ/8aA+ecrUIYobag2EQureBSO+cbpAYejRaf81FRtcNUX2pusGMcFGo/RntP5gCyseW825Uk0YpBUXMQZx5sB0zRnVSW8drRPU4Qc9YUJ+qn9J5yVfY7WQxabVAJPbcimjTnPpdS4eHfCm52C9Pa9E1qvudxkAOwM15wt+2jjGO9IPqL1ihenZ7x1uc1rwQHrJmJRptTWSO8yGPM3Tp6/Erp8fPSUt9a77MRrFmXKIBYwdpQ11NbgjxLMYSFJIrWhyYXjqS8iUTJnLa7R6IuIujAisujGGt9qVGrRiwDdctW3rrYQUUrqUKVm+Gshi0/X8lyVnKdoqG5XsiBrFF4Z1KhFLQJMoeVa6VuyQUn97gA7lVQTH3nsXi1CEKeIdguasivh9aXUGsSWeruGPGB51uNx2LAsBBrQ1gZtnPRmSwGr24cp7Y2SMG6ZnQ2IsobZu9usb69QgcNEDrsMqStDYxXmbvFtwEUtO77mQV92e5HYddp1yO7PG86+4PABuFGLKsSq5OYikvKpRV2GmFzTe6hZvVpj40AEa1pEMqvfWqBWIfnzjUxoTvqj5jSknbbSVikDUdROatxZjOtZUR2PO5pMZVCpIwgs9aRhM/pND8Hf+/B8r6T1c+/9577THd2u7H/T/ff3eu+fKqU+AfxHwO/x3s+6+x4DN973o9eBpx/wir7X8ZeAP/EbeNzfdXzoE59Sqg/8OeCPe++Xz9RO3+mh3+E2/wG3/903ygrkpwHiu9e9ihzhk5jmUMHQSr18EdJstQIS7mTHJBZf627nJ5FALnXotZGyTKMxpcKuA4K9gnopVBSnIJgHknaQOZRV1DeFahHOAlYvCqvPXAaEi5DyQAgNm+daYWyeR9hRizMeVT1rYDuSb6a0PdA3S9pFTDCqhDrjFdHjiHpXY66XJK9ssEVM0YRkYc2d0Yx5nTJMShZFQl7EDPsFsyIjDlrefueA1fWEP3Tz1xiZgtvRGW9V+9xKZ/x3Zy+RBC2vjI745uKAv3L0MXbSDf+zna9yI5mxcil/a/ECv+v514l1y1Hx37/6jhdDivOM4s4Z3yz2aa1mb7ji/qNdfuj5B/zc2V3+q+JVtrIN13sLShvy5vkOzisGSUXjNJeXPUzaEgaWchNRlQHVZwRmXJ1lZAcr6NVXFI394ZLzvEdrNZNU0tpf3jrh0XrMokjIwprd3looKf0lrdPc2rpgVSUkQcP9iynTfs6bbx/Kyh1BcEVhy1ZvwzvzbeablLbV9LKKQVJR2pC8jXhuPOMrj64T7BWcrvqEgaXfBahu5ikb7bnIA3r7a8LAkgQtW9mGT0+fMDQF/+julwB4KTrhLyw+w3a4onIhjTd8cXqfygX8taMXYQR7yZJfPL7NK9vHXFQZ437Obm/No8UYt13DLEZXmvBajms1+kmCTaUk52cCIrB9K7szawQ9N/Co2BIcxbQDSzPpEhdy2YH5jrjiQ8/iM9IbVUcJKvTSy1obSRRJZXB2lSF6GGETqXqotSG6Jqnk9BzJAwlZtqnHakHtBaGlvkgI5gH1Xi2m7omAq6HrPxpPFFhub13w5uM90l5FvkzwXe8WoL0h3tNqGWPWhlpB7+6yY5lKGKyqNDgvopvSCKv2NKA+aARPlglIHqPxDuLjkOUdObfbfrcjqzU2FTWoi4RjGy0VLlSUX9jAZYwpFW0iAHjXGExoaXWAyg2ETqLMxkJg0bGFS9nlqsBjVyG+Zwl6DTZwoknYaFzg0bdyygdDousbAbX/gA/Fdx5ofyOH9/7fR0Qr8lxK3QT+PPBPe+/ffN9DvwQ83/XwniCtrX/yOzzl3+nu+9PAP/UBv/q3Au98P6/5Q1V1KqVCZNL7M977P9/dfKKUOujuPwBOu9u/22rgMd9ujr7/9u9xeKEcDBxRVqNKTTtpBQtmFW3X3DepqDdVpa8IK16LGu6ZaktVmmpHQmHtUdq9NzlZTakExTTvPspKVoXNXoPKpP9h+5Z6KgNRtW0xSyNN7EDUkHhRk7meECOaAdSHtXAPu/JVm8v39cRihjXec5ViXlQhP7r9Di/2TxhHBVtJzktbZ2yP1rwwOeNoMSTSluRIglVDZXlYbfGo3uJGOONmdM4f2Psq93pntF56VHUbECjH/WqHV6IzDI7Luse1eA5A3oacbvokpqUfVdRVyO6NS8lCC1ui0HK+7rO1u2TdSo/LWs1lkTGvheayXiYExuK6bDhXG0wgF3U26HYTXf1l9Jq5yuTbnqw5mQ1prKGoQupGDPhFE3bqS0UcWCJtyYKGLKjpBxW1M0Raft+jiwlKweM3d+nvbCBrMeOKbFIQGEc/rNnrrSjmCbY2BMaxKmNGoUCql01MHLcS1bNIWVz0iEyLxhMPKrJBSTgtKcuQSZozSgp+y/Z99qM5l23GJ6IjboczngtCvth7i9xFhKplZHIcikm4EX5ptOTRZkIaNuRtRG0Ns8s+gXZs8ljOj2mN360EEO0V7cBhchmoVasInp1vxkPf4p3GjVpM6DrZvJT1e++EV1g8lbVEJ50M3yP0kFzJOboWhXF8HKCUJ/tGIiDmzNNOWsnzi6SvSCQe1fJ2Q9v34o+rJQEiCKykPfQcwUkkisrGXF2+OnD4I6kmRNqije98kV10mBVVpp9HAm2ILS6WXt1Ofy1Eli4xwg9bdK0ITiJoNKpW1GN5L+HCyHu2SkDuyHVW7bVX0UJ4RKXab/HbFWrYQKMod60wdoHoVIQtKvD4WYxaBtTrCBU60hMJvHWxRwcWM61E8ekQa1KpIXboyBKEgovzGpqRpZ20OCsCOtsa2jeG33v4+z6OH6Cq818HtoD/p1Lq156VSL33LfDHgJ9BbAl/1nv/ze/w8/8y8EeVUl8Cfv3+9l73nF8F/q/Av/CbfnV8uKpOBfy/gde99//W++76S8AfBn6q+/cvvu/2/1Qp9W8h4pbngV/23lul1Eop9cNIqfSfAf7d38ArEBi0gjqPCNea8MaKIomFm9hKjI82DqvEvJ58M6U4kGY1oYNWY54koDzNlgwATmvh810GuESSy0ktbRtKySfyBCsjPp3O4O0Tj++JpNtbJTEyRpr8g9dDyh1P25dVtrmUHWl4HNEc1lBJSrqOLGoW4zJJYlbKs7jMRGKd1axtzL3klIPJnIXN0Mrx8iBhbRMmt3MMntu/74LChXxrc8C97JSfXzzHOMx5Pj2h8QG/enmd03WfLx48AODRSsgpTwY9pmbNj0/f4C8ef5Kf2HmTV8fwOJqQmIavPT7k7v4Z7zzdYe/GirIJWD4akh1Kee/1d2+SHq6JQpGhv368RxhaoqyhqkMWF33GW2u29pbMzoY0swTVb6TcNnK0jREm6iwiuVNw8mTMaHfNe8db7GytWJcRr98/ZHdvwdfPD7g3mXE9veQvfuOTjCYbbo8vOc37aOV5/HCLdFKyM1xTNCFFrdlcZOikJUkaNhcZOzfXHK8lHy4dl1grvaW72zPe20zRynO0GrI57bF77xi96zk7G3L/vT30IsD1LOG4QhvHtemS+092+MJzD6hcwDfXh/zQ8AF/p7jLp5KH3G8t7zXXuWx6PK1GfPXsGj+yf58ZfX7k2rskSqACqybmeDMQP+R0zePVCFsFUBhUUuJnKYxryefrtbQeATLkAey2qGUkk16j0IklfjehfqHtZPhArclfrkjeialfKPDzSEr23YLLB576WiMTztBDaaj2W8xZQv5qiT6LpVxXGtQ6wA1afGVQrf529STw6EogzcHSsAl6YsMYtLiJCF7UIiQ+LCkuUvwsg4OScVxyVvTo9wsWj0Yyqd/MaYpQYpmWXQzWOiS8NDQe5mUqxBlPlxjRcTFBkhbGDcHTWCAWxqNGQlNK3kloXsqhp3BnsaReBF56dk5Klc+EPMTCs1XrgLYyBAHCMVXg+pKK4ZXHt5r8tsQu6Z74Q9t5TDCqiSaFUH6sJngnpblTUj/pSfpFrXEjK77IUibJ+Ospbfb9j8sfePzgVJ3/At9lQvLe/2VEoPhBP38f+OL7bvqp7vYHiLL/7/n4MEudPwL808DXOxUOiOfip4A/q5T654GHwP8CwHv/TaXUn0WkrS3wRztFJ8Af4dt2hr/C9xK2IL4b13aqTOOpd1rq8x4qcNh1KKotD+5Rhoo8rqeEQjFoMLMY27MiSLlR4FYhqtZiiwi8eP5GshPUpUaNa/TNBlsEqDzAhV7SzluFHjQEjxOaAzG/klrMXkG7iFFOsX61En+Z1SIH366g1QQv5jTzFBqFe7ePvllgp9ITpNV47TGJ4L+WD0f82fVn+ey9h3xy+JhZ0+OvPniJKBTaSmAcW9mGflhzVvTQyvOjozdJBi2lD1jYjONqRKAdk7TgG5cHnC377I1W/OrJNX6q/L1clBn/yI1fZVGm/InXvsjueMXj+zsQOq5fn/HoYgInCa+ZfeK46cJJNVURMry5YL1Ovq109aK41cpT5hHKOIoqpDrN0MMalyKT4kZk61HUUhPAXslynmEyCXSdTtecHo+IBjVB2nB+0Wc8zol0y2k14EdfeJuvnR1wmveZLXskcUM0rCkuUp6sI6KsIbq5plzHKAWtlSSFs2X/ysxujBMVYx3wzum25DdqT1sZRgdLHp5uobRjNN0wSksePt1ia3vFfJnRbGIe1VPCpOUbp/u8HW1xcdHnU599xJeWt/nV9S1+bPQtboQzLto+mam5dfOCWS2Cned7p6xcwjAoCbXl6WxEFEkpODKW8daaxTyTisDg/9/enwdblmXnfdhvn33mc6d335xDZVZXdXU10A12CyBBEKREilYYImVRtmlLlkxbClO0LdIBhewwLYXHYDDCCtsMyJYohkKmKImmGAqJIUEKChYpE6QtgiTQAAh0N7ob3TXm9OY7nXkP/mOdfFVoVFZXFSqrqrPuF3ErK999792d956z115rfev7esLYEn8lpflyhTPi2KE3IaxC1IE4hMQXIcpEtLsOLkWRhdxeVyq6ucOV4g6gFiJH5ntNei+iPTSiN5pYnBLbHJc4Au1xMyPlQCvalY+zJ10F2D1RicEo7MQSpBbjxBszfDMlKqF8vhdN2li0SMOFxo4dedbRWc2jK2H7+thhM4s9l0F5v2sJWoUfeYK8p9MRyig2gwyZa0QTU2VWmNK9wu13BKHDjMSH04VyCKbRNMeG5Js55qVaxNrHPc4q4nsR/Qsy4+jyXvRwO5n/DdcBZiYlV2+0MFQji5sATonTRSCHB289aMTxJfA090YEB42MO0yG8nLi0BOxU2NQ0gmznt4qXBzQDySuDxVb5ZYPB977/x9PLhv//if8zJ8G/vQ7fP0XgC+8r9cPBzUFJRfO4wFfvJKLv9NSV88dPnKEmcH4YRj7sEGtIrJHiuYIoouQbt8Qxk4YZ2+MaPfESkhvNO4sIbpZ0ivwsSM9iWjudDLg7hRBjyi/Kzkx9usYXWmhet/0uAyhSCs5neIGg9zUwDLFjCwsY1TRyw3kIJ81tHVEWabEhxWm17y6mPMr928wG8nA+WaTkect1ikerWQEwLqAPO540M/oXciDVioJpUkYhR2vnO+SRIZJ1rCflTy8nPImM2Z5zbfKI4q4pUoillUm84QnGesmkb5c7giVp3o4Ij2s6JqQKJHftVrkYBVh3qO1p92IbNfk51Paf3BNs4khs6iHKRyIw4EuA0zo6LoQs45J5zVaO0ynxctOR+JrOOoItMeeJFz2GuanMsCclHR9SNvJIHbTRfSVBN/gKqbzimzSoAKH7QL8yQg3McTjliDwlFVCmoorefidjPzLl+jAcfH6Dmrc87hdbTtN99U5y99xCSZgtckIXs3hbk2c9FQXOelBz7pMwcM3qyP+xlc/j857bn/xkueTU9ZW7J1+8eo2Z9UIgFkks5hfXRzRO82t3QUnqzHrdYYK/LUXonltBPMe02rMTYdyInDMRgxR0V4yt8jRT+x1CVR5cJHHeYRkEQ19rkhB7AiPalES2W3pXzSoi4HY5UUv0qVyL/mLhGDe4nSAW8sweHDQYK8SdK0kIxsb8HLPeatg3Iu9loVmb2gbJBbbBdgqIjhqwQa0bcSjzfjar0/p4ecThxpbmRMsHARCVAkyg++03EceildCmn0vWpsOsSjbhKi5jF348wSm/bWHJInDpvKZkgmbuO81/djLYD9gFsn12BOJpZ8o4tdT/EslfR3gTEA66uhfSbD7vcwGKw8bjXch4XGF1iIa0OUW32qpTiXBtTKMvYpRey10GkIne0ZuaPaDD9yL+96b5tP6xZ88PLPKLSABS9lBPHr9Voz3g1da9CAmOZWegu0ClEJMN8vHotIed57Q7xqU9thG3M+7mQwGq8jh5j0+8lKuKEWZvbnTSaAtQ1wj+nyqU3KKtlJq8nstzYGTG+gxJbpXwnYb2Guu07jdjmBH7F1U4InmDSr01IsMFYCtpY8AUDYxfRlxuSrEWBVYL3KM1bR9SFklVG+I2sVffuWH+fmrO/zi2W1+fSXD2fc2U4q0Y55XFHHHq4s5hzsrgsCzqDL+2s/9EI2JhmAS0l6lBEZhBsd0cgOvFVLqcaJ0YW3AppVeVDppRRrqIiUuOpSC1QuO4BfH0OprYhGI8ojdMahBCDyoA3E7qGKKUctkWtHUMcndNaO8pStjXvohGRF6zFp9WE340vF9iqzFdEPJzoh25Oyzl6RDgBtNGtJRhzqqRXbrzQLnFGna07ahsEu/NAS904lkpa3m6mRMGBuCyNF/oWR5byqHFcA+VxPFYh1U7JUEgWx0+3tr7lczinlFmvZ8ZXmH/2rxA4x1g1aO28UV46RhJ6v4pcub/Oy9F5klw5hGldMNmpbjUUPfhuSjFnWrkiys0/iJwdYyH0cwBAkn11jyhpQ7g15U/83MiIB7H0hJsgmxEzFKDbNe/Oi0x1ahsJk9eKsIEyNVisBfm9KKDY9IdsULyYZ87Oie6/CpI3kzBgf6XKTtgsjJgWHXSllvEYniT2oJMsN4Ko4ndpFwfjGmXGaUlzlR0ZPMWnGPyHshiIwM1EJYwcvoQRhZ3Cai/3Ip9+qNmvRciY9gYTGbCL3X4EeW4EL6cKoNoNSYo1ZKyKGjGQTexWdRFJHCRSglyyEbY9LTHho5VDnQZzHd6yPc8HvcY0LQpBft03VMu0hp21D6+ya4tkwjkyF3lPRVo1FHcBGTPogke7WK7OvpU9kvlX/y41nDsxv4FPR7PekDCXj6oB6owYEYwFYh7m5N+1yH3oREDxLS1yMZO9CeoNTiojDr5IJUEuhsFcLO4OW2DvFdQFAH2FUsnnWlbNTpN1Pi/VqYmA8iYYdWmqAK8JuI0S+lBFZINGodkkwbVG4gdG+pr5dC3VaBR5UaV0b0FylR3qMii3o9w3vwTuF6jek143lF8ErOuGiufbvKZYY1gZTJblS0RtMbzVk14oXZOfevZvzSw5tMkobeyEHA+ICmCzldjtmUCWWVEN2oePjVQ+pFCt8YSeY8NdRVTLVJCK4izMgS7TYS9Gp57xcXhWwGbYg1AaowQmqxAfEioNn3hAs5OOhaNA/1GxnBKoR8UPvYbTGdHjRVPZsyRYfCwKzbCKUds7jhx1/+NqFynFYj3lzOME4T4DneW2BtQDJtuXl0RW80XRNSPhxR1bGU1yKL1o7xZ6/ozjPKVcqt3QVJbGi7iM9ML5nvr8W/7ipk53CN6TV5JhlnMJFhcdNpnNG09wvMmwXtQMDZHZWs64RXr+Z4D0lkiAND60LebOY0LuLvndzh+fElo6hjN634wsFDHm4mFFFH00ZEkeXkvhCFbBWSRAYzrD0adeAUYS7O5zy21wm8mAbPHbSBsBQLOVSoeJi5sxCeybxecqkwi0T64LEczoIdCXDKKfpVgus1JA63iFHjHk5TlJIeV3u3BatIZ8312E9zsydoBuJYbPHnCVFmIBAjZjuWsQtqmSVcPRyDVWQHJXE+uJk4+exNp6Uf9uoI3wdE9wYTYMDXIeq4pjvL8NrTrWNcKB6Y5ec7CTJWDj9B4PEO6UFeSYk03G1QgSc50dIvdYp42pLc3pCkHdzPxD7MDL33y1gyZS19TwIPt2rs1ODrUDLTWQdNgB80TYOFZMWSxfXiCbgKZZh+I6L2+38vIH4YYR/kuHlHe1sG4n3sab5YP50t88Mjt3zi8ewGPiMZR3OnF/PVJkQVBjXuZV6nU7KhbkJc6Oknlvq5Hiphh3ntCa4iUVdwwh7TkR0c2xV2boQEE3jQnvgsxE96MYqMLPUL3TDv5OXiqbXo+LUSHDd3ZNbHJZ6gU5guFLHqSkw6vVcERuGslH7w0pQnk4ARJhZz1JHOGpJJKw7pypNGPShYbTLyrJPjWqUJAtHhHGUty3tS3rzc5Hz9/JAotByMNzxYThmlLSerMVdlTrXKaBeJMMqGG93tyCm7OzREew3puBW/ua+luMijd1v6RUI3UMvtUnpp9kCGcN06wpchTS1ZanNTjDqTS0XQDlqTlUY3wEFD+h35GR058lFLOm6xTjYv02mWV4X0MvuAMLAcpyu+ebnPJGlYrzIaGxJqx/lqxHxSMi4a1k2C1rJZ6VmHXSSSOdeRzM8MQ8TZqOWilHGJg+mao3RF2cR0Vcz+F87QgQiM90YEnHXk0NqRFS3ZuJFS1WHD7rTkcLImC3vytGOW11SPRoySFofC+YBvrA542EzZVAkvFw/57x/8PP/k0c8TKM/vPf518rDn9u6VZI7jjqPJSjJrr8Q0WIFp5OBmqlDmUz1EeS/9Y6ek7BkL41NfRlKqa8T/jZHBjC20mvrQDfN+oksZVFpKipOecNrKYbKW8hz54OjgIToRZi5lSBBbujoiez2SjdMj9l+BzMEF/VCwyw06M8TjDp3I/aRii17LTGEcGbo6kvJk5OnqCFuFtEeG9EyyJeD6HvVKZNJ84ohPI6KLEMYG32vCtJcybCX+gH0Tivn0Tkt6IqQb22n8Mqa92xLlPTq19E1InnZkSU94dyNZ5SIifj2Bg4YolmuW1JKOOinVxpZgJGIW3gTSR43c9fvgCisiAw9TGa+IJGsms5Abzr/sSc4Rf1CEKKMGhqxbxh/+fum/x+MZw7Mb+PQQsJpABswvYrwNREk9kaDDo1S0N6cd8UEtJ9HQ44xIY3HUSNmzDwiuYvm69uLO8LhviASvbtdCLadsFNBouk1MkFjMZ2v8UMLo9sWLTO226IMavQ5wh62MVyiEdNOIIowLPclriWR3ZmClNRrbBXTLhPA0wvRSfg1iS79KOL2/Q38sWoKrN6YEFzGTmyvsw4yuD7m6KiC19L2USL0X25oHiylNG3GxLujaiM1ZQRBZokvJ2kZjsUuZ7JYo5UWBPhDquAo8zZEbbhKFXmniSSuEB6/oTnIpb+2IqWkw7sVf7DJGhTJbVX6+I7hRySxjZmnuSvbkEmA4ANRlTLNOqKuYOBXBgelOSagdd2+fMQ4bfu70LpO0oTYRSdZzXheUbUxzntH0ERePphgbsHx1RpL02MsYEstor5KAlYh9U7JX0zYRvdHUjwpuFkvu1TNC7RjPKuo+pDcat4qJI0P/SzO6dYzWjuoqxxiNd4rZrKLuIlor2qZF3LGoMubPLYgCy2Wb84uPbrFuU756ccQffPFrfDY5IVCOn128zO3sCoBJ1FB2CfNRRZ51nG5GFPMKHThsLZm0qIXITCgbmXPrSyG50AcEi/C6nGzHVnrekSOshimudNiYMyFbRVmP8uALK/J550IY6T9bE11pyfZWIW4ToQz0N2WQX4174m9m6PspzQ0hiT2G2+mgsNgdQ1+HsIqkJHmaSUYzOESYmYFUCFK+CqUsOQRLvQ5RkaP+bTXhqMe/UKJKjV6GhONh5tAqzO0Gd7OR/mboMG1IdKPCT3sRzF5I+dBsItov1lAYgtBTvBkQFz39eSqGzJXcNxePpvRtiE4s488s8J8rsU1I9/oIvdvijaJ/bYR3Qs5ygycjgZdAOBZheV0F1wP0PvJvtWG0lx3ZKtjpWH+xJ7wKhdk970heFwNrOZR8uFBsM75nAwrC5XCaTS3RRqHPI5JfEzas3mtwczkBeqckSD0uC3npV4SvZkTnEcmjELfT4TaRiB3nlnTcipP642DlQa9l83F1iCp69EVE+Iac6FQXEN/eSG9xJRmdPc3wNxrURYKKHWFiZHzisetDH9B9psG1GrcnfUM97aAWpppNPbYNsZWctIPUkAzlpTC2EEsPcvVojNvpqTcJ3iqSSUu3jgliy2adsl5lMqc0KOGbMqTYK6Xkc6mwdcjm9Qn+IpF5u1YcK7qzjObeiCgxUsaKpXTkNbKp2aHvN+nRqcEtYqpFhj9P0HlPfFiL8K72eDMY+iaiheqdvK55vkbPO+k3ucFRfiWmurPdDQejDdYFNCbiq1fHdEZzvi64d7rD7riks5q6iQlnLVWVEBYd1SojPQ0wRguNXUFdxhir0YGjGrJRFXg+d3DK0WcucD7gUTmmXKVs1lLWazqZU1uvMvqXxSGhXqZglIgcnCasNinrZcamSXjlfJemF3KN84pAeRZNRmc0u1lJgOe55JL/5OLL/HsPfhf/1XdeYmVSfubNz/Pt5R5p2FN1cljxXnqrXS9lcltFBNNOGJm5HL68k89aOYQFXEnmR+qkL5dZ6SdnwlRGe4gd06/LZ2JOMmzuiE4icSOYi+2Q6wO6wx49b/EjIXj4CIKLWH7HVUxzaOn3euLdGjvvCdKhF+eUMEiHz5jQE+20qKmQTfRATglSK4Fp8LmzrRBjWEW4WY9ahwTa4R2YJiQ6rojubLCXCa7RMrIwlNpJrQQgr+AbIzlY7kmQDlIp+bqzBLzCLmLKH2zpLlMhMPWSSbo2JCw6GX+6SFiejenriHxH2J+mFNd6u9ehIo/pQoKLSPrzm1BcFd7MiDKDPejQpbiq20IOtdG8Idur8J1c5yxi8u9E2N0evdJEqcHr4VBSaZ4KthnfMwAnnmAAVCHdzGFTR3WnJ7wM3/LlOqrlRBhAEIhyhe8DoiGYmZHDZF7Kj8FQrkmt9IRKdW3Bo0Y9duRgJH0Vb0XlwWZSCvWhpylj9FmMi2Xo9vEFFbSK8CTC1IOMkZGBejcR01kVO/RZLOUqD+EqID4N8TNZo9JyavQD/R8FgfLEOw1R1hNsRLFGx/aaZ/tYWSIrOnwVisBv4GnbiORRhHNS3mx+m7i4s9PhZ4My/kBmCCYd2UlAV0fXg7jeK9yuUOAfO174Xn5XuAmIRx0uc7h1TKgtTHpYhzL+sYyJC+lTPVb0D7QbpNoQAsCA8Ui0KlNt0IEjDg2dCXGIiPZ4XNNbTRF3HO6s8C4gTnpspwkiS/tyjekkK4uLQVjZIwPSSP/NO8WbqxmLMuPV5ZzLjQxQeatYXIzwTpFOG9K8u2ZYUklJW0UONzOEoWM2L6mbiHadcPqmKAzvZBUPllPSsMd7Rec0TR+xtimbPqUyEXhFaRImacP9B3NO1yOWqxzrFJtNynwk7MAkknKhrYaB80aTnmh0NGiWJg7VB6I362UjV49ZjIg6CxbZdE1AX4COLUGn0EVPt2fwx40Msc9ETUVpjw6dXP+tzOgReAlGhQUturbdJpZrcxnJgW0gkejIwTqCTDI/PehoujYUfduh/FeXsTi6n8dCgMkswVWEn/aYKhJlmuGiNl04uJ8D8w4Gwk8QWfk3elGO8QphqCr5zEktLhcdTR96gtARXoUEJ8k12UpfhHJ/1hGMDfoqJH4jJtRStgSkBNlqwBPFhvFrSiTeMqkkmaloxj7WRgVQkcft9nTLhLYWublo1AlJKZZ+qNkxdOsEk8s+QvYUUjAPyvknPp41PLuBDwlGbqfHR07KGzud2ALdbPCbCJTHXKbXliSm1XJThJ7+PCXoJM0PjEJFIvFEALt/K8GtY5qbPfF4oEXbANUrwlToy8nrQx0+8MSvJ3LDLyPs2BK9uBbJsoNGSCnHLfa4lX7cYDCL8uQ7Ffb1ArWIsHvSr3OrGP9cTXdbDCrZyIk/6KQE0pUSIJuznG4T05+luJnBpU7mguzQTzxPxGfQQzR4mdk2xLaa/k5D87DA24DgtYxgGUlAqDWsQ3QipAQ1OHB7p+j2ZXZPR7KBANIHuook6zhP6Hcs/aMclVhU0VOtMlhF6HknAr2BF4Zqo5l+RaScTBWhU2FOMpRV472artfcmiyZxTXzrCLRhjzqWK4zeqPZbDKWVcpVmXO6HKNDS3UlJ+540D+dTGuxejKaybSmqyKsU/SbmM1ayDPTtCYIHGfnY7xXHOyvmO9tKKa1jIfYAGsD2XSBYEdmCoPIMd1f0zUh1S/NiWNDPq05uH1FqB3eKyZZw7LJmI8qlk3G77n1HS76ghvZgnWb8ruef4Wfe+Muz48vee7WOXfmVxztLkljQ/L1jEWZXZORdCS6nGFiIDO4L26wFwnlVYY3Snzy9moY9CaDSmZcYSB+aVFvUdrTfaESD7hblZBWYidlO+Vl7KMX1mdXRgSlhtDjU0twVMt10gUErWJnp5RD4LRHOYWetegHibQaHBLELiVYmEpGToSFqggL8RWMvpMR79W4gxY7MtcjJGoZESzFEy/Kerp1DMqjZ8IcDkIhhc3/rrQoosnQH97rUEaYruFhjWtDgkUk7GHt0XlP8msZpnCiQmOVBNCjljDr5bO9iDETS3enpfr1KTo1qMhDYYh3GoLQ0fea+h/ckH9b2h2PX7NZpsN4g4xSxHkHyOu6VYw+j/Bv5IQnEXxhLQowgSdIDHZi0HnP7BefggM7W1bnswHtZeOORHElLno5EY8MtoxEkzHvhT68DIXpdRmLAS0QNAHNCy1Bq7B3hEWlAo8a9Vz87u66x+VsQFp0QsioA5JEJJva51tRnz9s6PYsxawmOqrQk57+22PGhxvsKibKe5FmWkVgAyn/DSrtTRXjDsWLKwgd2bSBzEgvxKrrUlHfhOg7pTDQ8g5d9FJ+1dLPVLEV1uR+i1qHxElPemsjVjGBp9/E11Tu8FEiQXwmqjH2To06bIRxOdCxdejIDkp5z4wifJhQ7FbC5DzJRGUmtlJS221xTno3yawhvlGSFB1RZlCB9Fe9QwxLB3EAMsviS71sfkNmMR7XYBVRIhmCsZo3Fjv83Xt3aG1IbzUPlxPsScY0F8KBNQFtHxKFFudkrXna0VYR+aRhcVngHehQrG0eY+94yXOHl9zavWKe1ozSjtvHl5hWc3o2oTeaF3fP+cHjRxzM1gSBZ3e2Ic56ZtOKUdESJYZNmeJsQPalSwma4w3N0Bu8KAte3jnhH7rxbX7i5tf5/PyEm8mC//K1l/mbD14UP7n1nIPZmr/5jZdItOE7Z3us6lSG/X+gptnElFcZq6uc7lx6ZOYqRccO04qqv5Cr1DA+4uUQtw5xicP3YsYLwPBnkBj8o4zgPCb4doHLLDoxBLEl3WmgEeawORuMfecdwVqj2gDba4JHCeFOg4s8Fw+mEsi8Qs1b7DLGHHUShL+ViSbl2KCXWioQy5jJweb6Hkz3K9rbHe1C3BJUo6/XG98ocVPpQdo+kJ1skDMLzyLseYrvNavfV+I7CazNSU70IJGDcOTxrxQEqcHvt+gdYaIq7enHnslzS8KiJ9hvYC0kN9NEYrZ7KOMlvg/gVk2YWPRphO9kDMFWkbzXylO91OKupAQcrjVoRzxtJcvMJDjr81gy3dziDlvsfo857GgvMvmeTUj4SiYOFzag2X06W+a2x/csQHmCyOL6AJ0bTKtJTiJ8H0jGEXkhBDRalNetwkVe1FMGHU3fabwWWr5OxA7He0WY9dczUknaUV1lxJcaf6eiXGYkWS89BRuIislwSnVO4azC3Wxoe+mBmZMM1wcy4+O4pvsro3BlhKtDSCXwea+IMnNNn1b3U8Kdhjg1YtgaW7pz6deFiZS1onE3lF2F0q28aHxGoShoKDWUFHdaeQ8S8RwUaxi5POw6Iph0mCokPpOb37pAyrAOzFEr8lDKE7QyWqEC6dt5J7RtPzGoQN5za4bXH/4dtoqEOBQPPdZBlcZexgRXEd0mZnlZMJ5XWBOwv7cGD+Umwfaah5dTqj6mqyOi44qqE3am7TWm1ddZEamTIOwVxmjivGc0bugqcXeg0TSd+A5Ok4ajfM1Xvv0c46Rh1aRwkqIjR5F0GBdQmYiTqzHGBKRRT1eLsW4UWNpNjF1JOdtYYdWebUY0XUSRdOJmHhhGumUnLPnB0QPWNuXlg1OKuOONszkPTmfsJDXzvbV8DsPrOK+wZUQ2buVw02l8KOX1YNJJ1j1kPY/LeUEg167b6WV2b9SjTIBdxJirdBBYEMalCz0cNnQ3O7CKODak2VAOdorOaOKjSpjHoRDFwlIyQXcomqGEnuQkFMZpLeMdGAlMSdHRvijBQ2cGuyskqGAi70s86oSwY6X0mkxlfEBNO2EJ39ngbDDYMUmvMBm1hLER14ZbtRzQMhn1SB4JyzSYdvQzuS/CdYCZSwbp6lCEn7UjTXtM4Wi6CNtqGZwfxh70aYQ3gWhsxm5wWgiu3SWUBx24a8Fz81gWcdYRbDRmbIkeJNfD9TrvadeJEO2MIn4zHu4JcddQ+aAVOjK0N3oh93hF//nq6eyZn6Ie30diS/SxwCmhYHcBLjeiChF7UZfv5cIzJkJPOjhNcTsdQRXjCilTBYc16n4uvQGQniAIGaCMZR5w1glBog3obnZoAKuoLzOyw4rmJKe6P0Z5kcMybSiBdtjsg5EExSi2IoH1tYj6xzoheYwGpYpe4XuFqVPUvKE/S2FkSMctjfLoN3OaiZVm/tRAbrFVhM8MYdpjGgnaFk8xbWjOY7p1TBfE6LOIVR8Q79WYewXBofTN/CrGTQb/tDIiHA9Cxn1Av2vwmwgbB+jTmPTFFc4FNJtEJNqMwi9D3AyUVYSjDqPk391cZtLQr0IZ06hDoZbnVrwSd1tcG5CPG6wL6GwC+y20mnjUs77KifKeRZlxtLPCecXp3zkm//Ili00mRq+tlGXj0GKjAF4t6A5EmSOb16yXGWEiQbhIOy4vRkRZT9+IS3m7Sbh5fAnAosuY72147ZduSdnvqJFyq/J87bWbQ89UDkBnqxGsQ4rbFWdnU/RZxOhzVyzvT6lWY8Z3lqzOR0Sjjp2s4vRyzP1qxl//zucItGea1+jA8+jhDJ1admcbAuX51e/cYvdwxZuXO0SRpTUh7Tqh2CupHo1IDyp8Ae0qkUMDMtYCyAhKF6BSR3OaX2dSutS4LiDcbTDnqZCHFrGURIeAEacGGzmCcUu9SmVAPPSo3Ig7Ri3D1Ix7/KRHHRqy0NK1Ee48IVoH9BMnG/peLT3ksZHroE+vxeGD+ynh8yXdZUq002JtQPT1HF4QApbSHvt6gS+csEX3auorcYnAQfZKjPoHlrRthF3G6EmPqcSuaPgP5oWa4I2M4MUNXSaHPfOcEQlB5DrtTnKIHeWDEWSOdiGEs+ZRfh3I7MRKRSK10jdchiT3U5q7nVgtOSXvVW5kjzAKlVo51BVyGNEvrXFdKCMOsVSb3LwnCC2m0OhAyufqoCEIwOYWbxXRSPYFdZ5gd57CfumfzczuSXh2M76hbBFMO0BhlzH2QE6tQSyOySDMN6+9BLvjiuAiIh0Gku3YEh1V16QHbwK58DtRWjdViHkgG4pOLXY5jDloT3u/kD7YrMMHnnYjg66kVgZWH6td9IHME2pP97vXWCNSZfG4FeX4nVbUKVJLt0xIjip0YmmriGTUYfe7a/8vnRgZHJ7XqLNEhHAfJtg2JMoM5Spl9wfOKXZqgmFEQoWO7lGOOqplWH6YYXNXsQzzG4U7T3is7q8yg15LtuQST9vENGVMmIqShX2ulnm+c5kTM8uE+I0EOumzhJGVslYTCnuzkMFrnzhsGTE5XlOtUtHt3G8HJQ4xcVUr6UmO84ZHiwn3HuziXipZrTL6JmR9mWP7gLqJaVohIsSfW6JiSzRpae8X14zI9mHB6mtzwgcJ1ki20lUR41+JuX9vl2+eHnB/OeXqqsDMRBO1KMSn7+R8IgPHgG01QehEh3RkWC8zoqwnen5DVSek+xV+LNWCH/+BX+dLN+8DMJnUfPP04C3B8Srj4hcPmOyWjMc11iuuykwGrr2iKWP6LmR1VaBTI5Y7iaOtIpqrVGbqEG1KHTjCWErxQSplOHKDWkQEocNp0PMWsxARZjscfoJKk89rXK/pu5BuFUtA7QKCaUey08jnfiVjKPG8QYeWfNJgOk29TuBBipq3uM9UouoyKAhFk5Y466VF0ArZyXYBLoZR3ko2/qbojjbHluBKgh6hI9pI8MRDV0VMDzZSXVhE1M/3VMsMsxE3gyg2qFqjMiOBMLakv5rR7xrcYxPYPiArWuJTGWWI5g16tyXbq2SsKTFyz9UaMoefihqOyo0QhQbrsGC/pdmXVgrDfpKORWvXO+mdp4XYlCUnIT7wNCc5zghpKAidtBFqLVWP3Y4oksNB+FjEwkuLxbtAyGuB59ZPf/isTsW2x/dMQA1+Yq7TMo9UGBkONwquYtS8RafCmoyOK1HcaCKCoeXRVZF86IEXgWqv0BfRNQssyCR4RYsAtRpkziIRk41GEmCz+xrXaKL95pqckRYd/mEKWjYnArEdihODMQHuKka/ltGtE/y0p18k6IcJ8agjugyJQ4t/JBuiDoZ5q6JH77YDU3U47eeWeN6I2a2DvoxgFbGuEzlVJzKwHITSB7yWSTtLhjdQRjp87MQyyQQEmbxfHDYksSG+ks0rTIz0Ph47STQBdt6jVhHReSgn/8JgLlIpp61i6av2wTUdXeWGcNyxWafSqymkB+g6ca5XgbhZ2E5T1lLixA2ail7IRWhPMWrpm1Ak0zbi2wcQfr3AT4V4pJSHkcHdasSWxyNWNcsI+7uXclJXnrqJrweklYK2C2VmMnToMsAZxXxvQ5IYIQ4NIwSm1TTLlG4dkyY9dAHjtOW8KVj1CedlQddrupOMJO8lOzUB5rmGJDQsFzmrTUYa9+S7FW0fEj5I8Ccpyagd2JQi8uw6LQ7rjwkdsR186MBtIvm8BiJSchGQpD0+taSp2GapejjEOCmpWTuULK2SzV97ma3zwnRFAVoOWV0ZiZ+eHkYT6pD4+bWUJZUcnmi0WOm0Uk5Mi45wr0HHUr53Oz2bKgGrsKm4kosFkEGtQ6LU0HxGMkEWUvrebFKyUUvQKVRkB3kxmatVyhMd1MIAVmAbTfVyh4rdwBrVhIUh1I7++YZw3F3rtxojkmQqkIPu6NdD8RXMO1Qnpf143JJkPdWxI05kJCeZtOhJj05E+UeVmnAZ0l+mmKGE3x4a0SOtArwNcL2WkaZamLhKe3TkqNYpPhQhBDuY5KYTmfP1w6Hlwe95Otv2ltX5DMC7ofncBvR1hF9HhPOGyV6Jn8pMWZwaAiVK+yA3s7pbUV3l0r/KDe0ypbixIRs32L2e6a2l9PiAW/+pJv7SgvGdpZRDQoc9yeT1ArA/tJEsyAwbzoOMvgvxB8Ogb+DRsaU9z2jKmMmoITsu6SeO+eEKWi0egMfD3N1nNqwXGeMXrojHHc4FYqI5bM46tgSxlYAIUlqJrfRCuoDkuKTeJCRxT3ueCdGnDklmDWYTyaZwVKPHPRT2WhXGK8QLrRdngig1klG9VEvgjazQtlOLji3hcyXFTk18o6Q76NGHNVHREx/UdKtEbvTjWjZWrwiuhAFrm/B6Vi/QIsxLq6HUcD+TzNApkrhHh1I6ilIRTdaJlcB+ISzYKLKoaUd/r0ApT/fSMLYyZBvpeMgmE0tWdGAk88+SHj3uCbUjTXqyScN0f0NVx/SN2N8czVfsfekUv4mo24hqnTD6zALMIJAwfB6j3YqqiUl2a+5964BvvnrMK6d7VF0syjWZY5w1RKFsmGFsObu3w83DK2wfsClT2jqS5z+75uDlM9ql6DS64ZCUzRqKufR83DqCqxizTOAbI+J5I2o7hy1hbOk/X9H3muxeRLVJJFhNRNw6SQwHR0s5FE3k+szHrZRKI0eYWNbLTIb0Zy37M7m2GZRrHhO/2lqyyiyVw5iedsSJKCLVm4Q4MpizTBiYkSN8GNO3MuSdHFW4+1JBCa9C1Fxk6nTkZOOPnfjdKWjrCLNjyEYtyUFFmMmsaFPFQnbBE9QB6UQGy3UipdWo6PEeyjIljAeLr1ACrnPqrcOjCTA/tmbnhSu6TYyet/LZeoVH5oCrq0z6yL2WgK085TLDpU5K45nFlMLqRCG9y72eZNyiYxHYpg+ED6BlFEQtI5JZi/vq5Fp1qe9l5k9nBsY96ujpuDN8mnp8z2zgUwHiDj0QS0gtpgnZrFNheoaeZpPQtSFqyLrsKqa/SCnmFX0TMp1V6LzHWLHX8X3A8mwsChCp4f5/RwKgdQHBqJcLd1cuajXrZC5wGaFDR302zIANWWSc9zIsXknJKv3OYKPiFT61lE0sLEcFwan0b9plIoP12jHKWtKkF8+uPiDNRPTZO0W1SlGFoasiOQBYyVizZFCKB/S0Ixl1qI2mK0UzUGdGNrZQApizAVo7dN6jAkcyaSVorhP6KhLKe2ypTwqK+ZA1D3qcfhiIj8byPjzWsFSRBOcibwlCL2XZo5ooMYO5qAQPW0Xo3DD9ugbN9TxVnPcsL0ZCKBg+22ggwgDED4TgYm3AaNLgUqHi2zokPahI9mohHwHB/RTXhDSNbKqkjsWyQAWONOqpm4h6nYquZ/UbZaKcVwTT7pqkU9UxQWKEKRx4olFHtUmkn/TqSD7LAHbGlYgTA9QByyqTzxroNzFB0fPm63vs7JTEsUEFsLgsaK4k4I13SwnA64igDYTZuZKhcj3ppTTvFO2R2On0jWTWfS1MQ2cC6ltDlotktraKMH9/StOHQsYC0ryjXA29tEGFKM57CSRWfs4Pc4P1WoKoN4G8tycpbR/KPbWIqS5y4t2aOOuF1BV67DKmW8WEnxXtUzYh7UYczClD/I2GJOvJihbbaIpXIykzDoSrMBZZQaWgu19g2hB3mhJnvYwoXMRi5NqFcr/FBneWYDpNnBhxXahkttXbYe1JL9JmkYXQ0awTmmE2MI4NpgvpTzOaRUoYWXYO16TZ0Hu7iKVvH1nCcQevFeSTGn0VSutkJO9rMasJlJfZ1FoLeeiwIsp6cWw4rsjTjv4Feb/iwxo3iDdEqXAVdPjhK7cAKPvkx7OGZ5fc0gRMZxVlnDAuGha/PidaKdQProkjQ5sYksiwejhmfmtJ2cTEO1LCi0LLpg+uFfqrdYJrQmZHK8pKnLe9h2zWUbcxptOkeUddygYwHtUUSUfdhwR3VtSbhMnxWuSv1inT+YblxYgu8CRTKc0VP3rO5eXoWg/UWaGaz6cbyrkMyiahYV2nXF6M8JuI8Y01+kZFGHh6o9kZVzCGxWZQp9GOKLSkkaE1miiwHB0tOP+VfcIXhDzBvGN3vqE3mrJKuHPnjLKLKWvRs9SBI5kaFhcFBmjrnMmNFUp5Vsscv4oobmwoVynjaU0UWlablLaJOZivqPsIawPWCyGKXF0VuGVME1uKQkgs7SZhvLuh1Y5mCDDTwzXeKzY/Bmlsrj/WvguZ768pmxgFBIGjvMzZubOkN5r+SGN7jQ4tvdHkB6Voezp1bYRbL1PG8wr14prQCxlptF/SG804b7h4ZU4ZG+JYBtCT2DA/vqQzGofiYl2QJT27sw2LTY53imIkWdIka7hQBX0/lEQDh7lVo4GDnTV1HzEZCas3KFrKTcKNg4WQY3rFaK+hTUMuzsZMdoQ5mWbCRl1WKdO8oRwUeNRxw/50g/UBq01KlvaszgqSXRm/6ZtQ5hS9lPuDx1Y4j1L0nRbTauLUYGJLX/SYMsX2AcWkoa6kJx1oR7bTUVYJ5n5Ocnsjh6suYn5zyeX5WNilb0Nyd029FAJLMO0kOLiAIpUWgN0JCENHs0rYm2zYtAntDSvlzJc6Yo+U0iND1cRk04b6ZSnrB/MWu4hxo57JXsl6mUlf2inxuew1+U5Femi4PJkwGtX4QrJSnzrG44b1pRxCo6KnyFuqMGZ3XNKaEDWv6Do52AbaUZcJxbSmaSKStEPfbqm+PaWNYnTgJIvNeqKJCLyH2lIkHcsXnCgB3ZHrL9AOcz9n9+UzTi8nhFmPAXRqSJOe5ekIZUUqLwosxahlfZkTjzrycUtTy/WeJP31PfJh41ns5T0Jz2zgU6mlamKiaBhD2G2xx5Y4cNRNTJZ2LE9H6HHP5fkI32nCccf6wVio3pFjdVGQTRui1NA2Ics3puh5d91DaaoY/UaGultT3R9T3FqTDK/XDXJSADvzkjBw4oU3qWm74WQYW7rTjPHNNWWdkI9aMUOdV6wvc3RqOb2/Qzjqice1MPrqiGzUEk5r0shQVQmRlk1i04iclTUaU4ao0DM6WLKqUqwNqNUwIL4vJ1uzich2Gs4fTsVpvNWcLMc0lxlBZshHLU0rgev4aEFnNRePppTfmmHHlmSvxmhPObD+ukJjnUK9UmCOOk6vxMXcVhHptGG5zshHLXXgSRNxou6/NoW5ZR1nJGmHuogZPS/GtSrwwjacgI4c/WXK7NaStg9pT3N87FBGEe+0VI2MDjweGYkTR1tHkk0o6dms7k/QOy3FzuDrZ2WsIj6UQ0lXxixMwHMvP+Lh5ZRuHTPd31BWCctXZgT77XXGXl3k7ByvsL30fsoqIY4Np4sxWouBqveK1al46432Sx6+toue9HAvxd9opGxmAx6czXC9Jt6VzdPZgMlOxebbM9LnV5QnhbAtE8s68HLI8grbB5xfjmVmLJRDjoqlP+S9DEkXRUMbh/RteC1TF9/dkESG0gQ4r0SNREGU9dhGU5cxWdFRLjKsChgXDeNRwxqoH4wI92s2w+FKaemrVYuM8byibiLMVcr05pLNJuNgLqMYp5djKoRxas5TwqOK/cPl9SFimjecLwsJiOc56Y0VF6/viADEvCF8M6W/2TKZ1PhxLXJxwGRWEcw9VRPjhky0qWO5Ny9DNpms01nF5GhNEhrKREQXAu1ouxBnFQ8f7Uj2NW6lB6ykzw8yohBFVqTx6hCXD//mZSY6m8eGNO6ZZPKZPjqZko1b2iZiPK6p25gkMZRjy+nlhDxviULLZSMZ9maTEp1HuNs1OnB0VhOFVqQF7xe4QyGeNRcZetKhHj0FW6JBueXTgme21AnQLhLMIFs13anIUlELMY8yjA2EnDKUp4LUyED5bkM+bonfTK5FqKPIEjSBNOVDSxRJNmCrSJzVgXC/pqljrFNcnE6wTlGfFLIZKc+6Tug66XPkaUead9eO0m0fUl+KCkffhJSbhCCxhLGh2Cux64jVUkSmw1gEptfLjM5qwtjQlDHrVUYcWZoqJs9bmdELHVUndkBZ2hFFdvBMgzQVl4UolO9Lk55s3GJ6fS0qXC4z6elFlkWZEWsLdSD6gdOONBbPtjjr0ZOBpOEC9EtrYXFGljCyItobGWynMYOdjohjg3uxvDb8rMuE7M6aspQSpO000W6DW8c499acl3Pi5KBCLzOPypMl3XXpM3iYCKlFvXUtKCW2QVFk2ZzndL2wKas6FluiNmLyy3KSXlSZlBkjCSB9KRJZOrIioVZFpHMpWSVZT7NIsU0olYRlgjGa6hszeW+dMBqbZthEQ4vN5OdcK8QJUVAZBL+VZPtVHRMY2CnE2ioZt6hAZggfu1Po2Mp7HznMIuHyQnQo48iIy0Tg6fqQ5kr6WUFi8b2mu1/InNqVuGjERcd0LrNx3ilUgPQgnSIZiFqrVSblubFkwWnWiSsB8r3BYNIaBB5Sy6ZMsauIZZVyuc6JEyHOtHVEfFCTJr1ky15hh/K7uUzp2pB4ryYJjTBNxz1p0sv8HXKw0YEXmTbt2KzTa9nAODZkqZQUdeSwuxLIZ9OSQHuMDSjbWNRQlJhEe68ItCcuOrJZjTWaMBSmpl/GwowNhKWdJT0MQcc76RP7oYS/LlMe3JuzqhPC9K0KxWMJvLYNoQswm4imjVgscma7JToQNSZ7q8E2IW0T03bSO45DC/MO/0YupKqil5niO+VvfXN8J2x7fN//cE4RTzqmec3p//cG3ktZbLJTMrqzolqnYucD5Jk4AeAUadJTnhR0N2RDautIdC9vlCSJIYoszaui3qESEaueTeVCnE1LNpuMZNyyvCrQO61kAtpSb0R6KMl7Lk/HWCen7cdKFDvHK2EB5h3H+0uiROxYrAvI9ioOdqVEG2hHlgrJY7nISeOe48MFIKavad6xXoiKx2jcUC5FeqvtQzbnOdm8Zn9/SRr37MxLjBW36EB5Qu2k93ajIh+16MTgvKJrJGCfnE8obm5g6CsqhfQO047xWMqcadzTbBKIJZg2i5Qbty9RA5mh3SRM9kvKTcLidMx8Ukk5J+1ElWWQxvIO4qxnXDTMbi3xVrE725CnHU0VE94s0YlhMq3oLlM2AwtyVLTYQ/ncD+ZruioSTVCE4esRfcTHtkijosH2Gu9g9aVW9DGrhM1ZQVp0rE5HqE0ITjRATRVBpUnjYbbxKxMZA5jKHF64DCnyln7XsKlkOHlUtLizFIaZ0MlzS7ouJN+pybNOSsSZEdsb7QZyBiJjB8xvL8Qy6V4uMmWt9DfHIyE59GXE7OYKrOLouUuS0DLJGtw6ojnNSQZJuiTr2T9aEBw0jPMGMktYdELOcMLQVYHHGRFmiCcth9M1i4UELqxULNKkJwot9SIVslEqQdw6RVdHTHc3JIkchkLthDAzHBh15NifbvBeSvGTvMFYLTqomUUpCLVlWWUDjV+xuiqY3Frx/K0zVle5CH+vJJMbTySjCoZMb3VWiIj2Kmb/cElU9FycTnBWMc0bui4ku7UWE2ejaTZvaeZeK/64gCQ2+NRyvL9kvc4Ij2ravzNn9+VzKAzJqGVW1ET7jejCtiE6NbRNjKkjgr83wa1iOWAYIVTpMmD3xlIOi6mh6zVVJUoyk2lFMm1Js476KqUpY4LAkeYd/kZDlBg4SYnHHeprow99v1T+yYzOZzETfGYDn2oCsrQjDi3xD1+xWubCButDdoqKg/0V7TqRLMUGZEUnDfjIkO1XgwanKDOsH46xJqC8kqwsvC0Dt0nRMc4aFsuCyaghGO4gawKykZAA7CLhfDkSpYbAiUVfbKX0VEopznSaphVNy+pkxKOLqczzPUpI455ZUXNVZmw26XBCDtjfX5EV7fWJMs07yaZcwM3jK8LUCJHAKforUYtIpi3NJmZZZUSBI4t6RmlLHBlWX92lLBOS0BBoT/drUwBMp9nd2ZAWEpDLZQaxsPzaLuTm8SWbTSaalU6xKVOC0DLdkxKhzgynlxNAyk1R1lO+MhXtR6O4WufowLGpE9plQhIb1BvZtYjyYpmzuBihI0fTy0l4OhMijQ4dSWjJ9isYxg904JjuSL+m7mV+8fF7FMSW5jITok4qm/LyqnhL6QbY31mzOy3ZOV5hTEA47khvbojHHbujkvG8gkgcGRbfmlO91BG0iraJWSxzDr5wyuJ8hM4M46Jh7+aCtgvJb69Jpw2mlxK4O03pe82mTDA2IPhGwWrIsEHIVvPdDYsq4/JixGjcEN7d0J1l7O1siN9MSEMhXKhNKKVeoO5DNk2M9TJrmh9t6C5SQi3M0cUmx7aivBNcRSSJIYws3cDMRHuC0FOtUsybBYsqE6/CNkTnPdX98bW8W3wSXZdYg1iqDeNpTazttZJPHL31+/n5KVFkePDNA5wL6NqQi2WBtQHdSSbjRbGhWqdEoRUS17ghGbX0RvNgMUXHjsmoYTKtWG9SlvenMobjFTp0qNAz2akIUsumSeTAuwwJtGfTJNhODwLsUir2nWaUt3SrRJwgBjJSFFqynYbLTc5oVGNNQP3ZjmWZMZ7WKOB8WdBX0fU15J0SMplR1F+s0dMON0gLpnmHmRoWy5zRuLnOXN1g2GusHKbKZYbOxR5peTYWR5XBPSa8XWI6TfEjF09nz/yQ5/iUUr9dKWWVUn/4bV/7CaXUN5VS31ZK/W/e4+/ZDH/eVUrVSqlfVkr9faXU31ZKfe6DrO2ZDXw+dTRtxLpJRHD4vmgcFmlH2cUshszM2IAs7um6kHEhPZbH5chiOImror9WXbEmEMX53BCHlt7poXmvqLpYrHTKmCQ2OKOJd2sZPB+JykscipKDt4rxrJbMNBFCTbuJRQPTIeSWO5JBbppETuXriG4lJdOLxYhJ1tL1IZ3VNFVMEEjJb9PG8JqUWXVqr8uBWos+aRIZ6j7kfF1w+nAmaifP1US/nlF1QtvvDqSsEkaWso3p3hjRmBBKTVT0hKGlusi5/y0Zwq6biLoRQeA074i16GNOJjWmClleFm99OApRvpm212UqZyX77Y3G324Ixj1F2onqRRsQRYa6iajOCunH1RE6cDQDWQUgTXqqJmZ5X4L2ep2RpR3t62O6TTwwRWUmsF6n0oP1whRN4574TclqW6OpahkLGBWN9GxPMlZNirEByZ6QR1zkUUthIOrIosOhb5j3hLHl8ttzylpKn+UqpVklcCp/RseV9I06jVIw+ZEzilFLFvXDfKNiXUrAChPD+sGY7n6BGvVsmphuLp+L7QOi44puJYSXuo2FnFUlpDPJCJO9mqaKpZS+SAhCR6ylDGttQP8ol/7UJiLOe4qiIcqMHPCGPnU4yP8x7mnujyirhPDlFcFQbnTD2AHAxdWIUEuJv+kiGde5zChf6CmSjuioulaXsYuEcdbgU5kV7ZqQyawi1FI9qCq59r0Xhup0UuG8Eum3vGV8vCZ4IyPUlv4qIcx6yipBXYh1lTnLUAdvlYmDR/J6+TDOojw0XUg6bTi/HEnPc2ZoOgn29SqlqhNsGRHnHUlsKEsJkoH20AYS/FODr8LrkrLrNVFspH96kmKdtFaK4bCaZ53oyKYyU1ieFjI32smWbKoQ6oD0O4mY+3ZykHeXclB6GvgwtTqVUhr4V4H/93d97d8A/lHgB4D/gVLqB97nr/6O9/5L3vvfBvy7wL/y/lf3DAe+JDLMRjWrBxOO95eY4xYFxNqyqeVmalcJ1VVG04fc2r2iN5o0MqRFRxb1Qjs2gbiwA8999gS84tatC24eXlGWCWWVMMtr1qtMiA+xJd+pcE4xnW9Qgef49qWw+4Z5waPDJaOJbKh51uG8Yn0y4uhwKQFzEzGbVqSDjc56kRFFltnNFd7BwWxNnBjSUAgiXR+SZDIesXp1Rqwt8UtLqk3CeFzz4s1TslR6iuZBzihtySJhte4dL+nqiNm0pLkl5bvJtCLMDcc3rq6ZoeMXr/BeMb29BKBrI6JJS3QgpdPDnTV5JjqRXReiFEzH4qKwe7TCm4DxpKavI/Y+d8781hLvhN1njCbQnvGkFofyaYmtQ5wXCvf4cEN1MsLUEUfPXcr4wVA+y+OeqOhJh96OUuLe4L0IWlsXkN5dMdvfsHtjibtKmM0qIRnVon6zP9lIX/GzJUHohmwFnvvMKcZqmjpGz+WauDFbitUPMsuV3V5fC2cfzNY4ZIB9f7Jh54Urmo0Msd+9cU4+q7Fjw3Rvwyhvae6NmO5U9EazLDOcV5wtRuwcrhkXDWFoWS1yYesWBj/rRas1EEWi9YUcJvqHOd4xCC1AElrSRMgW1YORZLnak6cd85tLbh1ecX41ghuNEHFur9k0CeQiRDDJGvr6LQeAgxsLuiri6GDJeFbjp9Lb7TrpwyaZfAbWyPhLmEjJ8nBHSEPhrEUX4mSyruWQsllL3/HWC6ecPZqR79TcPrrEGdE1Xa8zyjrh5RuPOJqLPJ2OHJuhdZAlPetlJpqnL4tjRXFYyqHSKbI7Qqo5evGc+XRDoD0XqwK719OaEGMDZrslRI5qlcls3mDjVOxWVMuM3dkGNbQWjm9fkmcdndEURUugvJSLU8fezoZpUTO9scJa0ZINs54ia7l184L07or+XkE86ggCuZ+WC6l0dKX0r7O9Su7R1PDZG6dks4bkqGL3xx9RzCtufeYMHXjUrCP8q09Bs8wDzj/58f7xvwD+Y+D0bV/7HcC3vfeveO874C8Df+i7f1Ap9bxS6ueUUj+vlPpT7/IaE+Dqgyzu+ybwvd8UWSmou4j8cMPFuuDujXOOpiumac0Xjh6R5R3TvQ137pyRRobGROwWJYtNxs6oojVCVghfydjfWZMUHQGe+XRDqBzLKuOF4zPyrOV8XbCzU+K94sWbp9yZX9F0ETuZZAbjRE7eNw4XZLGIDO8UFbNcNuhQWz772Qc8Op1SNTHHdy/ojR5KmrLZ7E02ZFFPPq95dDmh7zXT4feO0pbn9y7o+pDJ8wsuVwVpbLh9dMluXnJWjhglHXUVM3vxiqoTg89omAcKE0MaGo5vXpHHHfO84vb+pZAohjLhpkzRSoaH7+5f8OLxKUfzFS8fnTBJG3Tg2Mkqbu9dcWN3ybpOWH5jznxUEWvLS595SBB4klHLosw4Hq2YTUvytCMeRkiUgqurgqqJKeaVlPJazfrNCcl+xfHxFY9Op2jtmM43rFcZjQk5ni/RgaMsE5paqOnTvGZ/sqGpY7KkpxqIRzdfOmWa1tycLdmbr0njnkQbZtOS/dmGo/mK3mhmRc3rr++TRIbjvSXz6eY3XF9RajiaryiSjq4W9f7GhPK5z6Xnm0U9N4/lQPVwOWGStbz0mYeSeRnN0efOWC1FVHx3UkqZdlwzSoSl6lxAmFiKuCMtOnb31sxHlYxVLGOSacN8d8PeCxfsHK0Jd2W8oe4iklAEmOPDmunhmuPdJZsy4eLRhN7KLJsOLeXDEc4pdsclt25c4s4SLjc56ahlPqqY5A2bJiHOey5WBQfjNdOdkp2dkiJvifOe/cmG2ahib2dDFEimVl7m9Fbo/dGQLd7avaK+Snl+/wJngqE6kfD5F+4zSlvGUUsxranbiCTt6e4V3F9P6QbGbRQZ5uOKy1XOLK15+blHpEnPwXhN20swO9xbcetA9sJbuwt6F3CxGLE7lvUmk5ZQO/bGJXUbcff2GS/cPmGnqLm1e3V9T+4fLMnins/cPGOctuxmJfvFBh049kYbjmdL1mVKMa1Jo55llbHZZLx0fIpxAbd2F6w2Gas65c78itmLVySxYXlVkISGm4dykJzvrTFGszsumWQNh/srjAtoloPfYuCYj8R2a5rW3Dm6IPxDZx/Glvqb98x3z/j2lFK/8LbHH3vi71HqJvDfBv7cdz11E3jzbX+/N3ztu/GvAf+m9/63A4++67kXhlLnd4B/Cfgz7+sfOeD7IvB9kBTZeSWK60CzSXi4nHC2GfHNV27w6mJOkXTkA0FhUWZcrAt6p/nc4SmbJqFuI66uCpIvCo0f4P7lDIeitZKNAPRGY7qQsk7o2ohNl3B/OaVbJVzVQrhYtymjtGNRZbSPnQKAZZ3SdsJwrPqYW8dCAnn42i5ZLBnn2dlUTomBBCnvFfuzjcwfmYg4MiyrlMaE1A9GZENPZb/Y0JmQRZMxSloWVSblt/MRedxLv3H4NzgbcFVmsklcjVi1KZG2bIa+kVKI6ozTTNKGk/WYVZtycjUh1pY3L3aou4iT1Zhlk133SnZ/4JxlJezTTZfQD6XeaV6z7hMuzsaEgaNpIspFRqA8OrJCqOlCFmUm2fbIYHrNskrJxw1Z2kkmMajUnC7H0g8aiVLJ6eWEUDk6Ewp1PJBZvJ2spu4jVm2K89JfrGphgFZNTNnGPPy1A5LI0PQhkz0ZQ9m0MetaylWrJsU5RVsOQ+dOc7S/RA3jKlFoyaKeNOx5eDalt5q9iTAmH726y6KWubOqSuisRmnPbFQziltWj8Tzr+ri63nS3UnJRVnggXHccrnOaTeJmJs+/vxQUpptIjojGdvlqiCNenbHJcvTEZ0JpZ+XG1Z1Sp52jPIWNe5l5nDQC/Whx/7KlCTuudzklG3MNG9EBUg7nFcsTsdcXRXiMnGWc+90h6qLWVUpZ+cTKWNqz+nphPpNGbcYz2rqPkb1AZsuQWlPFhmWVzmd1SKHBpTLlEB5ofPf3rB8dcbF1UjstgJP2caYNqTsYupeGJKXVU7bikbp5SbnjQe7bM4K3jiZ03QRbhGzaRICJco8V5cFZScHIuOlL173IY2JuCozxlmLQ7GoMhZNxqLKOC1HnKzH0pu0IXUvmbxzije+dShthchyshljbEDVx/S1lP/vLWZo5aSiVHQkWvrveSotgb4JWdUpp8sx58uCqzonLDpWdcrFpqDqYu5dzXi0nGB8QBH/xrnJDw3eP/kB5977H3nb4996l9/0U8Cf9N5/9+i7eofvfad08seB/2D4/3//u557XOp8AfgXgXdbxxPx/TLHd50iAyilHqfIX3/SDxgbUFYJe9MNe+OSadxwUo6Z3aqJteHu+JJXV7tUfczBdC3D3MAbyxnPza749s8+zw/+vlfIw55feOM2cWw4ni9oTISxAZOsIQ5kWPX5+SXLLmUct4TKcZBvYEcU/s/rglHckoc932r3uTuT0+jryx32ipIyMtweLzipRxRRRzh1TA9OuWozdOC4cWfJssmwXs4ofa85XxZ8+dZ9zuqCF+cXbPqYR+sxX/7SKwDcmVzROc1r5VzYm6NaxgwCB1NYVhkv7Z3xi6/cxnWaH3jxPvcWM46KNTdGK5Zdyv3FlCzpZfA47lgdNsTaUnYxz+9cclKO6S9SVvtSNlZKFGyMDXjzjT0+c/eEh4spB9M1nZFNqWkidqclJw9mHN5YMNsthYjRaeJ7MeGhE1amDbi7f8Z5LaLSV2WGAqp1ynM3LmQTDy3NMK82K2rqwedub75mlEgpqohbTh9NqfOIO/uX9E4Ta8ujkxl+T/oss7xm1aZ0rSibZHeEPXu1KEjSnmWV0lWieRkoT+c0d3cveQ1xZM8SOUQczVecr0YcTNfsJDW/fr5HMZIeZqINt3aveNPv0FlNucg4OFwyTWvWZUoedazblOM7F9cHkk0rZrjpQEC6WIv0WjDI3B3tSsnZecXJuZTzox35fMouJoosD75yAzOxqNyy2GSMC8nMJ5mQKRZlxt58TRb3TOOGN75xBJFj+jvORPAgtNyYLuVAEjjKLubVe/sU80p0LV2AKsSD0Fi5vnYORT5tevOcZZ3SjUP2xiX3TnfYLUqyw5JHF1M+c+OMVZOyt7vm/tVMKhZOc3y0AGCW1jiviPfOGUUtb25mFFFHZzW7Rcmj5YQkMoShJYsMt46WvHo5Z5I1ZNM1J8sxd3cv+fajfW599pSz1QjrhBh2dLDE2ICrdc7q2zs8/0P3mGYNnQm5vbNg0yWkgePBeop3Ac8dXLBppaVxsSnIo44wcNwed5zUI/qipuoieqO5+s4Ok+cX1F1EMa0p743J77wVqPK0o7UhSWTYtAlxKP33spQScKAd7d/cxf8DFU0j0ntWK3aKmjSUQH1Rvq1f/mHBf3B3BqXUHwf++eGvfwD4EeAvK3EN3gP+gFLKIBne7bf96C3gwZNX9D3x08C/84HW7P0Hqt9+pBhYQT/hvf+jw9//CPCj3vs/8V3f98eAxyn4F4CvfqQL/d7YA84/7kW8Az6J69qu6b3jk7iuT+Ka4JO5rg+ypjve+/0PawGTyS3/Iz/6J574/N/46//yV7z3P/J+f69S6i8A/7n3/j9SSoXAt4DfD9wHfh74p733X/uun/lp4D/03v9FpdT/HPi/eO9HSqm7w+/6wvB9/wjwZ7z3X3y/6/p+yfjeU4o8pN//FoBS6hc+yAf1NPFJXBN8Mte1XdN7xydxXZ/ENcEnc12fmDU9ZT8+771RSv0JhOmpgT//3UFvwE8Cf0kp9ZMIQebteEEp9ctITOiAP/pB1vL9EvjeT4q8xRZbbLHF+8FTkizz3v+z3/X3vwr81e/xM68CP/a2L/2fh6+/BmQfxrq+L8gtSEr82YHmGgP/FFLf3WKLLbbY4reMdyG2fB+0w94vvi8yvveRIr8dH4jt85TxSVwTfDLXtV3Te8cncV2fxDXBJ3Ndn4g1PYvSZE/C9wW5ZYsttthii6eHyeim/9Ev/QtPfP6v/9f/2w9Ebvmk4vsi49tiiy222OIp41OU8W0D3xZbbLHFFqhPUfXv+4Xc8p7xQdS/P441KKV+7yC98zWl1N/8CNb055VSp0qpd5xtVEr9M0qpXxkef1sp9ds+AWuaKqX+s0GJ/WtKqX/uI1jTbaXU31BK/drwmj/5Lt/7m9TnPyoopVKl1N9723vzf/qkruGjvtaH19RKqV9SSv3n7/DcR36tv4c1feTX+m+AB6x/8uMZwzMV+D4k9e+nvgal1Az4s8A/7r3/QeC/9xEs7S8AP/Euz78K/EPe+x8C/hQfTcP9e63pjwNfH5TYfy/wfxtYvU8TBvhfeu8/D/xO4I+/0zX0TurzHzFa4B8e3psvAT+hlPqdn7Q1fEzXOsgs2K894bmP41r/Xmv6OK71ayi8ePI94fGs4ZkKfLxH9e9PwBr+aeCveO/fAPDen/KU4b3/W8Dluzz/t733j5XO/w4yK/mxrgk5h46VaB+Nhu817/L9H8aaHnrvf3H4/zWyUb2TkO47qc9/ZPCCx8rZ0fD4SHeo97iGj/xaV0rdAv4g8G+/0/Mfx7X+vdbEx3Ct/yY49+THM4ZnLfC9V/Xvj3sNLwE7SqmfVUp9RSn1P/rIVvfe8D8B/ouPexHAvw58HhEr+FXgJ733H9ldOEgkfRn4u9/19Sepz3+kGEpnv4wE37/mvf+73+NHPo41fBzX+k8B/2vemxbJR3Wt/xTvvqaP9VoXW6J3eTxjeNYC33tV//641xACP4ycAP+bwP9OKfXS017Ye4FS6vchm8Gf/LjXgrw3vwzcQEpp/7pSavJRvLBSaoRkdP+i9371XU//FO+sPv+RwntvvfdfQjKW36GU+sIncA0f6bWulPrHgFPv/Vfew/d+JNf6e1zTx3atP4Zy7omPZw3PWuD7JEibvZc13AN+xntfeu/Pgb8FfCQN9neDUuqHkFLMH/LeX3zc6wH+OaRM5r3330Z6My8/7RdVSkVI0Pt/ee//yjt8y2P1+deAPwz8WaXUP/G01/UkeO8XwM/y7v3Sj2sNH/W1/uPAPz58Nn8Z+IeVUn/xu7/pI77W38uaPpZr/S18upRbnrXA90mQNnsva/hPgd+jlAqVUjnwozy56f2RQCn1HPBXgD/ivf/Wx7mWt+ENRMkdpdQh8Dnglaf5gkOP5f8J/Jr3/h1NLr33z3vv73rv7wL/EfAveO//k6e5ru+GUmp/II6glMqA/wbwjU/gGj7Sa917/y97728Nn80/Bfx/vPf/w+9a90d6rb+XNfExXOu/cZF8qlidz9Qc3weUNvtI1qCU+p8Nz/857/2vKaV+BvgVpIL+b3vvn6qFklLqP0DYYntKqXvA/wEhI+C9/3PA/x7YRbIXAPO0lRrew5r+FPAXlFK/ipSQ/+SQNTxN/DjwR4BfHXpXAP8K8Nzb1vVJwDHw7w7s0gCxcflNNPmPYw0f97X+Tnj7mvgYrvX3sKaP41r/jet5BjO7J2ErWbbFFlts8SnHND32v+vO//iJz//Mt/7VrWTZFltsscUWzxKezV7ek7ANfFtsscUWWzyT83pPwjbwbbHFFlt82uHZilRvscUWW2zxaYIH97GOpX6k2Aa+LbbYYotPOz5lGd+zNse3xRYfCpRSu4OjwC8rpR4ppe4P/79RSv3Zj3t9W2zxoeND1Op8kiOH+gDuOUqpzfDnXaVUPfzevz84a3zufS+Obca3xRbviEHN40sASqn/I7Dx3v9fP841bbHF08OHx+p8myPHT3jv31BKHQxff+xc848gij4/r5T6ae/919/Hr//OIJGHUup/iszYPnkO4wnYBr4ttngfUEr9XuB/5b3/x4aA+DwyyP0S8C8hVkb/KHAf+G9573ul1A8DfwZR3T8H/lnv/cOPfvVbbPEEeMB+aD2+JzlyXDvXACilHjvX/IbAp5R6HvhLSHz6mXd5nQlw9S7PPxHbUucWW/zW8AIiwPyHgL8I/A3v/ReBGviDg+7n/wP4w977Hwb+PPCnP67FbrHFE/HuWp17SqlfeNvjj73Lb3qSI8d7dc/514B/03v/24FH3/XcC0Op8zvIQfMdZQW/F7YZ3xZb/NbwXwxZ3a8iEnWPT6i/CtxFNBe/APy1QR5LA9tsb4tPGPz3Irecvw/llseOHL8fyICfU0r9Hd67e86PA//d4f//fcTw+THeXur8JxET4fctzr4NfFts8VtDC+C9d0qp3r+lAeiQ+0sBX/Pe/9jHtcAttvie8OA/YKlTKfXHgX9++OsfQDK5c+99CZRKqceOHO/HPee9NBx/Gvh3Psiat6XOLbZ4uvgmsK+U+jEQyyOl1A9+zGvaYovfjA9oS+S9/ze8918aHg94siPHe3XP+a+H5wD+mXd56d8NfOf9/SMF24xviy2eIrz3nVLqDwP/d6XUFLnnfgr4SF1DttjiXeH9h0ZueTdHjvfonvOTwF9SSv0k4ov5drwwuKYooAP+6AdZ49adYYstttjiU46p3vO/M/uDT3z+vyz/va07wxZbbLHFFs8QvAe7FaneYostttji0wS/DXxbbLHFFlt8SuC9/8Cszu9HbAPfFltsscUW+E+RSPWW3LLFFlts8SnHwMLce5dvOffev+9B8U8qtoFviy222GKLTxW2A+xbbLHFFlt8qrANfFtsscUWW3yqsA18W2yxxRZbfKqwDXxbbLHFFlt8qrANfFtsscUWW3yq8P8HuftgvO6rCr4AAAAASUVORK5CYII=\n",
"text/plain": [
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"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def CrossValidationSplitter(col='fold', fold=1):\n",
" \"Split `items` (supposed to be a dataframe) by fold in `col`\"\n",
" def _inner(o):\n",
" assert isinstance(o, pd.DataFrame), \"ColSplitter only works when your items are a pandas DataFrame\"\n",
" col_values = o.iloc[:,col] if isinstance(col, int) else o[col]\n",
" valid_idx = (col_values == fold).values.astype('bool')\n",
" return IndexSplitter(mask2idxs(valid_idx))(o)\n",
" return _inner\n",
"\n",
"auds = DataBlock(blocks=(AudioBlock, CategoryBlock), \n",
" get_x=ColReader(\"filename\", pref=path/\"audio\"), \n",
" splitter=CrossValidationSplitter(fold=1),\n",
" item_tfms = [AudioNormalize],\n",
" batch_tfms = [audio2spec],\n",
" get_y=ColReader(\"category\"))\n",
"dbunch = auds.dataloaders(df, bs=64)\n",
"dbunch.show_batch(figsize=(7,7))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Calculating the statistics"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next we make two recorders: one for global statistics and the other for channel-based statistics. Then we step through the training dataset to find both sets of stats."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"# create recorders\n",
"global_stats = StatsRecorder()\n",
"channel_stats = StatsRecorder(red_dims=(0,1,3))\n",
"\n",
"# step through the training dataset\n",
"with torch.no_grad():\n",
" for idx,(x,y) in enumerate(iter(dbunch.train)):\n",
" # update normalization statistics\n",
" global_stats.update(x)\n",
" channel_stats.update(x)\n",
" \n",
"# parse out both sets of stats\n",
"global_mean,global_std = global_stats.mean,global_stats.std\n",
"channel_mean,channel_std = channel_stats.mean,channel_stats.std"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can check the shape of the statistics to make sure they are correct. For the global statistics, we expect a shape of: `[1,1,1,1]`. With spectrogram channel normalizations, we expect one value per spectrogram bin for a shape of `[1,1,201,1]`."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape of global mean: torch.Size([1, 1, 1, 1])\n",
"Shape of global standard dev: torch.Size([1, 1, 1, 1])\n"
]
}
],
"source": [
"print(f'Shape of global mean: {global_mean.shape}')\n",
"print(f'Shape of global standard dev: {global_std.shape}')"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape of channel mean: torch.Size([1, 1, 201, 1])\n",
"Shape of channel standard dev: torch.Size([1, 1, 201, 1])\n"
]
}
],
"source": [
"print(f'Shape of channel mean: {channel_mean.shape}')\n",
"print(f'Shape of channel standard dev: {channel_std.shape}')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Training with normalizations"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now for the moment of truth. We train with the two different spectrogram normalizations and measure their impact. For this we again follow the fastaudio baseline and train each type of normalization for 20 epochs. The final score is the averaged accuracy of five runs."
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"epochs = 20\n",
"num_runs = 5"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"## `Transforms` to normalize mini-batches"
]
},
{
"cell_type": "markdown",
"metadata": {
"hidden": true
},
"source": [
"We need to extend the fastai `Normalize` class in order to use the spectrogram normalization statistics. The reason is type dispatch. fastai normalization uses ImageNet statistics due to the focus on transfer learning with color images. But this ImageNet normalization is only applied on RGB images of the `TensorImage` class, while `AudioSpectrogram` subclasses the different `TensorImageBase`. The solution is to define `encodes` and `decodes` for `TensorImageBase` instead."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"class SpecNormalize(Normalize):\n",
" \"Normalize/denorm batch of `TensorImage`\"\n",
" def encodes(self, x:TensorImageBase): return (x-self.mean) / self.std\n",
" def decodes(self, x:TensorImageBase):\n",
" f = to_cpu if x.device.type=='cpu' else noop\n",
" return (x*f(self.std) + f(self.mean))"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"# make global and channel normalizers\n",
"GlobalSpecNorm = SpecNormalize(global_mean, global_std, axes=(0,2,3))\n",
"ChannelSpecNorm = SpecNormalize(channel_mean, channel_std, axes=(0,1,3))"
]
},
{
"cell_type": "markdown",
"metadata": {
"heading_collapsed": true
},
"source": [
"## Training helpers \n",
"\n",
"To avoid repeating ourselves, the helper functions below build the dataloaders and run the training loops. \n",
"The `get_dls` function makes it clear which normalization is being applied. The `train_loops` function repeats training runs a given number of times."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"hidden": true
},
"outputs": [],
"source": [
"def get_dls(bs=64, item_tfms=[], batch_tfms=[]):\n",
" \"Get dataloaders with given `bs` and batch/item tfms.\"\n",
" auds = DataBlock(blocks=(AudioBlock, CategoryBlock), \n",
" get_x=ColReader(\"filename\", pref=path/\"audio\"), \n",
" splitter=CrossValidationSplitter(fold=1),\n",
" item_tfms=item_tfms, # for waveform normalization\n",
" batch_tfms=batch_tfms, # for spectrogram normalization\n",
" get_y=ColReader(\"category\"))\n",
" dls = auds.dataloaders(df, bs=bs)\n",
" return dls\n",
"\n",
"def make_xresnet_grayscale(model, n_in=1):\n",
" \"Modifies xresnet `model` for single-channel images.\" \n",
" model[0][0].in_channels = n_in\n",
" # sum weights to reduce dimension\n",
" model[0][0].weight = torch.nn.parameter.Parameter(model[0][0].weight.mean(1, keepdim=True))\n",
"\n",
"def train_loops(dls, name, num_runs=num_runs, epochs=epochs, num_cls=50):\n",
" \"Runs `num_runs` training loops with `dls` for given `epochs`.\"\n",
" accuracies = []\n",
" for i in range(num_runs):\n",
" # make new grayscale xresnet\n",
" model = xresnet18(pretrained=False, n_out=num_cls)\n",
" make_xresnet_grayscale(model, n_in=1)\n",
" # get learner for this run\n",
" learn = Learner(dls, model, metrics=[accuracy])\n",
" # train network and track accuracy\n",
" learn.fit_one_cycle(epochs)\n",
" accuracies.append(learn.recorder.values[-1][-1])\n",
" print(f'Average accuracy for \"{name}\": {sum(accuracies) / num_runs}')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Baseline performance \n",
"\n",
"Before getting carried away with normalization, we have to first set a baseline without normalizations. This allows us to evaluate the impact of normalization later on, else there is no way to know if normalization helps at all."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
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""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Average accuracy for \"Channel Norm\": 0.7144999861717224\n"
]
}
],
"source": [
"# get data with waveform and channel normalization\n",
"dls = get_dls(item_tfms=[AudioNormalize],\n",
" batch_tfms=[audio2spec, ChannelSpecNorm])\n",
"# run training loops\n",
"train_loops(dls, name='Channel Norm')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Discussion"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The results are: \n",
"\n",
"| Normalization | Average Accuracy |\n",
"| :---: | :---: |\n",
"| None | .7110 |\n",
"| Global | **.7315** |\n",
"| Channel | .7144 |\n",
"\n",
"\n",
"I ran the cells above several times to make sure these patterns held. Overall, there is a gain from global normalization. Channel-based normalization shows a smaller benefit. While these increases in performance are a good starting point, there are several explanations for this that point us towards other approaches.\n",
"\n",
"For starters, the spectrograms in ESC-50 are very different both within and across classes. In other words the activity in each spectrogram channel changes a lot from sample to sample. A global statistic likely fares better under these unpredictable conditions. If all the audio came from a similar source, like speech, then the per-channel normalization might fare better. \n",
"\n",
"We also process the entire five second files at once, which is a large analysis window by audio standards. This large window means that each sample looks exactly the same in every epoch. If we used a smaller analysis window, say 2 seconds, we could randomly \"crop\" many spectrogram regions from a single example as a kind of data augmentation. The risk here is grabbing a silent region without any information but still giving it a class label (though an energy threshold can prevent this). Cropping with a smaller analysis window is one way to expose the networks to more samples and variability. \n",
"\n",
"Using the entire waveform at once also means that the waveform statistics need to model a very long-term relationship. Going back to the cricket recording example: we would not expect good normalization statistics for the chirps to be the same as good statistics for the pauses in between chirps. To counter this it is possible to do a \"short-time\" normalization. Here we pick a sliding window, often much smaller than the whole waveform, and only normalize the data inside as it steps through the waveform. This \"short-time\" normalization can be applied with or without the global waveform normalization. \n",
"\n",
"Furthermore, the spectrogram is a high-dimensional feature with 201 frequency bins. It is common in audio tasks to reduce this dimension by combining nearby bins. This is done with something called \"filterbanks\" which usually operate at the Mel frequency scale. [This tutorial](http://practicalcryptography.com/miscellaneous/machine-learning/guide-mel-frequency-cepstral-coefficients-mfccs/) is one of my favorites and gives an incredibly clear description of Mel frequency and the filterbank process. There are other options such as [Gammatone filterbanks](https://www.mathworks.com/help/audio/ref/gammatonefilterbank-system-object.html) as well. While this might seem like an expert handcrafted feature, there is good reason for using filterbanks in audio tasks. If we feed in a raw spectrogram, the early convolutional layers tend to learn something like a filterbank anyway! So directly feeding a filterbank into the network lets it focus on more complicated relationships. As a bonus, the channel-based normalization discussed here also works on filterbank features.\n",
"\n",
"We are also training a powerful 18-layer model from scratch with only 1600 images. While deep learning can handle datasets this small, it is usually only through Transfer Learning. But, we stayed away from Transfer Learning because pretrained networks are tightly coupled to their original dataset's normalization statistics. And the main idea here was to learn our own spectrogram scalings. It is possible that a smaller, simpler network will perform better. Looking at the training logs above, it seems the validation loss was still decreasing. So we'd still have to train for longer to check if the network is actually overfitting and a simpler model is needed. \n",
"\n",
"Lastly, there is no data augmentation even though it is almost de facto when training CNNs. It is possible to use image augmentations (flips, rotations, etc) even though they do not technically make sense on a spectrogram. It might be better to use augmentations directly inspired by signal processing like [`SpecAugment`](https://arxiv.org/abs/1904.08779). By the way, `SpecAugment` is already included in fastaudio! Along with many other waveform and spectrogram [augmentations](https://github.com/fastaudio/fastaudio/tree/master/src/fastaudio/augment). \n",
"\n",
"To recap, there are many good reasons why normalization only helped a little on the ESC-50 dataset. The points above described some possible next steps to increase performance.\n"
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"In this post we saw how spectrograms are fundamentally different than natural images. We then explored two ways of normalizing spectrograms when training neural networks: global normalization and channel-based normalization. \n",
"\n",
"Next we implemented these two normalization techniques and tested them against an unnormalized baseline on the ESC-50 dataset. Both normalizations showed a gain in performance, with global normalization outperforming channel-based normalization. We then offered some next steps that could further boost performance. \n",
"\n",
"In the end, the choice of spectrogram normalization will depend on how the system is used. For example, if the system will be deployed in an environment similar to the training environment, then normalizing by spectrogram channels makes more sense. This is because the training statistics will be a good match for the similar patterns and distributions in the deployed environment. However, it is critical to monitor the system in this environment and update the statistics as needed to avoid shifting out of domain. \n",
"\n",
"If the system will instead be used in a completely different environment, of which you have no knowledge, then the global statistics could be a better fit. While not as technically sound, the model will (hopefully) be less surprised by radically new activity across the channels. \n",
"\n",
"To recap, there is no one universally correct way to normalize spectrograms for every audio task. Like many aspects of deep learning, the final choice will be experimental and based on the specifics of both the problem and domain. \n",
"\n",
"I hope this post gave you an idea of how to normalize spectrograms. Even moreso, I hope that it gave you new ideas to try out. The ESC-50 is a great playground for any new ideas. Happy experimenting!"
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