{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Classification" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "remove-cell" ] }, "source": [ "Think Bayes, Second Edition\n", "\n", "Copyright 2020 Allen B. Downey\n", "\n", "License: [Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "# If we're running on Colab, install empiricaldist\n", "# https://pypi.org/project/empiricaldist/\n", "\n", "import sys\n", "IN_COLAB = 'google.colab' in sys.modules\n", "\n", "if IN_COLAB:\n", " !pip install empiricaldist" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "# Get utils.py\n", "\n", "from os.path import basename, exists\n", "\n", "def download(url):\n", " filename = basename(url)\n", " if not exists(filename):\n", " from urllib.request import urlretrieve\n", " local, _ = urlretrieve(url, filename)\n", " print('Downloaded ' + local)\n", " \n", "download('https://github.com/AllenDowney/ThinkBayes2/raw/master/soln/utils.py')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "from utils import set_pyplot_params\n", "\n", "set_pyplot_params()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "from utils import Or70, Pu50, Gr30\n", "\n", "color_list3 = [Or70, Pu50, Gr30]" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from cycler import cycler\n", "\n", "marker_cycle = cycler(marker=['s', 'o', '^'])\n", "color_cycle = cycler(color=color_list3)\n", "line_cycle = cycler(linestyle=['-', '--', ':'])\n", "\n", "plt.rcParams['axes.prop_cycle'] = (color_cycle + \n", " marker_cycle + \n", " line_cycle)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Classification might be the most well-known application of Bayesian methods, made famous in the 1990s as the basis of the first generation of [spam filters](https://en.wikipedia.org/wiki/Naive_Bayes_spam_filtering).\n", "\n", "In this chapter, I'll demonstrate Bayesian classification using data collected and made available by Dr. Kristen Gorman at the Palmer Long-Term Ecological Research Station in Antarctica (see Gorman, Williams, and Fraser, [\"Ecological Sexual Dimorphism and Environmental Variability within a Community of Antarctic Penguins (Genus *Pygoscelis*)\"](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0090081), March 2014).\n", "We'll use this data to classify penguins by species." ] }, { "cell_type": "markdown", "metadata": { "tags": [ "remove-cell" ] }, "source": [ "The following cell downloads the raw data." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "# Load the data files from \n", "# https://github.com/allisonhorst/palmerpenguins\n", "# With gratitude to Allison Horst (@allison_horst)\n", "\n", "download('https://github.com/allisonhorst/palmerpenguins/raw/main/inst/extdata/penguins_raw.csv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Penguin Data\n", "\n", "I'll use Pandas to load the data into a `DataFrame`." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(342, 17)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "\n", "df = pd.read_csv('penguins_raw.csv').dropna(subset=['Body Mass (g)'])\n", "df.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The dataset contains one row for each penguin and one column for each variable." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/html": [ "
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studyNameSample NumberSpeciesRegionIslandStageIndividual IDClutch CompletionDate EggCulmen Length (mm)Culmen Depth (mm)Flipper Length (mm)Body Mass (g)SexDelta 15 N (o/oo)Delta 13 C (o/oo)Comments
0PAL07081Adelie Penguin (Pygoscelis adeliae)AnversTorgersenAdult, 1 Egg StageN1A1Yes2007-11-1139.118.7181.03750.0MALENaNNaNNot enough blood for isotopes.
1PAL07082Adelie Penguin (Pygoscelis adeliae)AnversTorgersenAdult, 1 Egg StageN1A2Yes2007-11-1139.517.4186.03800.0FEMALE8.94956-24.69454NaN
2PAL07083Adelie Penguin (Pygoscelis adeliae)AnversTorgersenAdult, 1 Egg StageN2A1Yes2007-11-1640.318.0195.03250.0FEMALE8.36821-25.33302NaN
4PAL07085Adelie Penguin (Pygoscelis adeliae)AnversTorgersenAdult, 1 Egg StageN3A1Yes2007-11-1636.719.3193.03450.0FEMALE8.76651-25.32426NaN
5PAL07086Adelie Penguin (Pygoscelis adeliae)AnversTorgersenAdult, 1 Egg StageN3A2Yes2007-11-1639.320.6190.03650.0MALE8.66496-25.29805NaN
\n", "
" ], "text/plain": [ " studyName Sample Number Species Region \\\n", "0 PAL0708 1 Adelie Penguin (Pygoscelis adeliae) Anvers \n", "1 PAL0708 2 Adelie Penguin (Pygoscelis adeliae) Anvers \n", "2 PAL0708 3 Adelie Penguin (Pygoscelis adeliae) Anvers \n", "4 PAL0708 5 Adelie Penguin (Pygoscelis adeliae) Anvers \n", "5 PAL0708 6 Adelie Penguin (Pygoscelis adeliae) Anvers \n", "\n", " Island Stage Individual ID Clutch Completion Date Egg \\\n", "0 Torgersen Adult, 1 Egg Stage N1A1 Yes 2007-11-11 \n", "1 Torgersen Adult, 1 Egg Stage N1A2 Yes 2007-11-11 \n", "2 Torgersen Adult, 1 Egg Stage N2A1 Yes 2007-11-16 \n", "4 Torgersen Adult, 1 Egg Stage N3A1 Yes 2007-11-16 \n", "5 Torgersen Adult, 1 Egg Stage N3A2 Yes 2007-11-16 \n", "\n", " Culmen Length (mm) Culmen Depth (mm) Flipper Length (mm) Body Mass (g) \\\n", "0 39.1 18.7 181.0 3750.0 \n", "1 39.5 17.4 186.0 3800.0 \n", "2 40.3 18.0 195.0 3250.0 \n", "4 36.7 19.3 193.0 3450.0 \n", "5 39.3 20.6 190.0 3650.0 \n", "\n", " Sex Delta 15 N (o/oo) Delta 13 C (o/oo) \\\n", "0 MALE NaN NaN \n", "1 FEMALE 8.94956 -24.69454 \n", "2 FEMALE 8.36821 -25.33302 \n", "4 FEMALE 8.76651 -25.32426 \n", "5 MALE 8.66496 -25.29805 \n", "\n", " Comments \n", "0 Not enough blood for isotopes. \n", "1 NaN \n", "2 NaN \n", "4 NaN \n", "5 NaN " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "remove-cell" ] }, "source": [ "For convenience, I'll create a new column called `Species2` that contains a shorter version of the species names." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "tags": [ "remove-cell" ] }, "outputs": [], "source": [ "def shorten(species):\n", " return species.split()[0]\n", "\n", "df['Species2'] = df['Species'].apply(shorten)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Three species of penguins are represented in the dataset: Adélie, Chinstrap and Gentoo." ] }, { "cell_type": "markdown", "metadata": { "tags": [ "remove-cell" ] }, "source": [ "These species are shown in this illustration (by Allison Horst, available under the [CC-BY](https://creativecommons.org/licenses/by/2.0/) license):\n", "\n", "\"Drawing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The measurements we'll use are:\n", "\n", "* Body Mass in grams (g).\n", "\n", "* Flipper Length in millimeters (mm).\n", "\n", "* Culmen Length in millimeters. \n", "\n", "* Culmen Depth in millimeters.\n", "\n", "If you are not familiar with the word \"culmen\", it refers to the [top margin of the beak](https://en.wikipedia.org/wiki/Bird_measurement#Culmen)." ] }, { "cell_type": "markdown", "metadata": { "tags": [ "remove-cell" ] }, "source": [ "The culmen is shown in the following illustration (also by Allison Horst):\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These measurements will be most useful for classification if there are substantial differences between species and small variation within species. To see whether that is true, and to what degree, I'll plot cumulative distribution functions (CDFs) of each measurement for each species. \n", "\n", "The following function takes the `DataFrame` and a column name.\n", "It returns a dictionary that maps from each species name to a `Cdf` of the values in the column named `colname`." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "def make_cdf_map(df, colname, by='Species2'):\n", " \"\"\"Make a CDF for each species.\"\"\"\n", " cdf_map = {}\n", " grouped = df.groupby(by)[colname]\n", " for species, group in grouped:\n", " cdf_map[species] = Cdf.from_seq(group, name=species)\n", " return cdf_map" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "The following function plots a `Cdf` of the values in the given column for each species: " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "from empiricaldist import Cdf\n", "from utils import decorate\n", "\n", "def plot_cdfs(df, colname, by='Species2'):\n", " \"\"\"Make a CDF for each species.\n", " \n", " df: DataFrame\n", " colname: string column name\n", " by: string column name\n", "\n", " returns: dictionary from species name to Cdf\n", " \"\"\"\n", " cdf_map = make_cdf_map(df, colname, by)\n", " \n", " for species, cdf in cdf_map.items():\n", " cdf.plot(label=species, marker='')\n", " \n", " decorate(xlabel=colname,\n", " ylabel='CDF')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here's what the distributions look like for culmen length." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "colname = 'Culmen Length (mm)'\n", "plot_cdfs(df, colname)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It looks like we can use culmen length to identify Adélie penguins, but the distributions for the other two species almost entirely overlap.\n", "\n", "Here are the distributions for flipper length." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "colname = 'Flipper Length (mm)'\n", "plot_cdfs(df, colname)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using flipper length, we can distinguish Gentoo penguins from the other two species. So with just these two features, it seems like we should be able to classify penguins with some accuracy.\n", "\n", "All of these CDFs show the sigmoid shape characteristic of the normal distribution; I will take advantage of that observation in the next section." ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "Here are the distributions for culmen depth." ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "colname = 'Culmen Depth (mm)'\n", "plot_cdfs(df, colname)" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "And here are the distributions of body mass." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "colname = 'Body Mass (g)'\n", "plot_cdfs(df, colname)" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "Culmen depth and body mass distinguish Gentoo penguins from the other two species, but these features might not add a lot of additional information, beyond what we get from flipper length and culmen length." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Normal Models\n", "\n", "Let's use these features to classify penguins. We'll proceed in the usual Bayesian way:\n", "\n", "1. Define a prior distribution with the three possible species and a prior probability for each,\n", "\n", "2. Compute the likelihood of the data for each hypothetical species, and then\n", "\n", "3. Compute the posterior probability of each hypothesis.\n", "\n", "To compute the likelihood of the data under each hypothesis, I'll use the data to estimate the parameters of a normal distribution for each species.\n", "\n", "The following function takes a `DataFrame` and a column name; it returns a dictionary that maps from each species name to a `norm` object.\n", "\n", "`norm` is defined in SciPy; it represents a normal distribution with a given mean and standard deviation." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "from scipy.stats import norm\n", "\n", "def make_norm_map(df, colname, by='Species2'):\n", " \"\"\"Make a map from species to norm object.\"\"\"\n", " norm_map = {}\n", " grouped = df.groupby(by)[colname]\n", " for species, group in grouped:\n", " mean = group.mean()\n", " std = group.std()\n", " norm_map[species] = norm(mean, std)\n", " return norm_map" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For example, here's the dictionary of `norm` objects for flipper length:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "dict_keys(['Adelie', 'Chinstrap', 'Gentoo'])" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "flipper_map = make_norm_map(df, 'Flipper Length (mm)')\n", "flipper_map.keys()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now suppose we measure a penguin and find that its flipper is 193 cm. What is the probability of that measurement under each hypothesis?\n", "\n", "The `norm` object provides `pdf`, which computes the probability density function (PDF) of the normal distribution. We can use it to compute the likelihood of the observed data in a given distribution." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.054732511875530694" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = 193\n", "flipper_map['Adelie'].pdf(data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The result is a probability density, so we can't interpret it as a probability. But it is proportional to the likelihood of the data, so we can use it to update the prior.\n", "\n", "Here's how we compute the likelihood of the data in each distribution." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[0.054732511875530694, 0.051721356158881626, 5.866045366199098e-05]" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hypos = flipper_map.keys()\n", "likelihood = [flipper_map[hypo].pdf(data) for hypo in hypos]\n", "likelihood" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we're ready to do the update." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## The Update\n", "\n", "As usual I'll use a `Pmf` to represent the prior distribution. For simplicity, let's assume that the three species are equally likely." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
probs
Adelie0.333333
Chinstrap0.333333
Gentoo0.333333
\n", "
" ], "text/plain": [ "Adelie 0.333333\n", "Chinstrap 0.333333\n", "Gentoo 0.333333\n", "dtype: float64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from empiricaldist import Pmf\n", "\n", "prior = Pmf(1/3, hypos)\n", "prior" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can do the update in the usual way." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
probs
Adelie0.513860
Chinstrap0.485589
Gentoo0.000551
\n", "
" ], "text/plain": [ "Adelie 0.513860\n", "Chinstrap 0.485589\n", "Gentoo 0.000551\n", "dtype: float64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "posterior = prior * likelihood\n", "posterior.normalize()\n", "posterior" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A penguin with a 193 mm flipper is unlikely to be a Gentoo, but might be either an Adélie or Chinstrap (assuming that the three species were equally likely before the measurement). \n", "\n", "The following function encapsulates the steps we just ran.\n", "It takes a `Pmf` representing the prior distribution, the observed data, and a map from each hypothesis to the distribution of the feature." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "def update_penguin(prior, data, norm_map):\n", " \"\"\"Update hypothetical species.\"\"\"\n", " hypos = prior.qs\n", " likelihood = [norm_map[hypo].pdf(data) for hypo in hypos]\n", " posterior = prior * likelihood\n", " posterior.normalize()\n", " return posterior" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The return value is the posterior distribution.\n", "\n", "Here's the previous example again, using `update_penguin`:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
probs
Adelie0.513860
Chinstrap0.485589
Gentoo0.000551
\n", "
" ], "text/plain": [ "Adelie 0.513860\n", "Chinstrap 0.485589\n", "Gentoo 0.000551\n", "dtype: float64" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "posterior1 = update_penguin(prior, 193, flipper_map)\n", "posterior1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we saw in the CDFs, flipper length does not distinguish strongly between Adélie and Chinstrap penguins.\n", "\n", "But culmen length *can* make this distinction, so let's use it to do a second round of classification.\n", "First we estimate distributions of culmen length for each species like this:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "culmen_map = make_norm_map(df, 'Culmen Length (mm)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now suppose we see a penguin with culmen length 48 mm.\n", "We can use this data to update the prior." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
probs
Adelie0.001557
Chinstrap0.474658
Gentoo0.523785
\n", "
" ], "text/plain": [ "Adelie 0.001557\n", "Chinstrap 0.474658\n", "Gentoo 0.523785\n", "dtype: float64" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "posterior2 = update_penguin(prior, 48, culmen_map)\n", "posterior2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A penguin with culmen length 48 mm is about equally likely to be a Chinstrap or Gentoo.\n", "\n", "Using one feature at a time, we can often rule out one species or another, but we generally can't identify species with confidence.\n", "We can do better using multiple features." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Naive Bayesian Classification\n", "\n", "To make it easier to do multiple updates, I'll use the following function, which takes a prior `Pmf`, a sequence of measurements and a corresponding sequence of dictionaries containing estimated distributions." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "def update_naive(prior, data_seq, norm_maps):\n", " \"\"\"Naive Bayesian classifier\n", " \n", " prior: Pmf\n", " data_seq: sequence of measurements\n", " norm_maps: sequence of maps from species to distribution\n", " \n", " returns: Pmf representing the posterior distribution\n", " \"\"\"\n", " posterior = prior.copy()\n", " for data, norm_map in zip(data_seq, norm_maps):\n", " posterior = update_penguin(posterior, data, norm_map)\n", " return posterior" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It performs a series of updates, using one variable at a time, and returns the posterior `Pmf`.\n", "\n", "To test it, I'll use the same features we looked at in the previous section: culmen length and flipper length." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "colnames = ['Flipper Length (mm)', 'Culmen Length (mm)']\n", "norm_maps = [flipper_map, culmen_map]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now suppose we find a penguin with flipper length 193 mm and culmen length 48.\n", "Here's the update:" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
probs
Adelie0.003455
Chinstrap0.995299
Gentoo0.001246
\n", "
" ], "text/plain": [ "Adelie 0.003455\n", "Chinstrap 0.995299\n", "Gentoo 0.001246\n", "dtype: float64" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_seq = 193, 48\n", "posterior = update_naive(prior, data_seq, norm_maps)\n", "posterior" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is almost certain to be a Chinstrap." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Chinstrap'" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "posterior.max_prob()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can loop through the dataset and classify each penguin with these two features." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "df['Classification'] = \"None\"\n", "\n", "for i, row in df.iterrows():\n", " data_seq = row[colnames]\n", " posterior = update_naive(prior, data_seq, norm_maps)\n", " df.loc[i, 'Classification'] = posterior.max_prob()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This loop adds a column called `Classification` to the `DataFrame`; it contains the species with the maximum posterior probability for each penguin.\n", "\n", "So let's see how many we got right." ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "342" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(df)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "342" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "valid = df['Classification'].notna()\n", "valid.sum()" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "324" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "same = df['Species2'] == df['Classification']\n", "same.sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are 344 penguins in the dataset, but two of them are missing measurements, so we have 342 valid cases.\n", "Of those, 324 are classified correctly, which is almost 95%." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9473684210526315" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "same.sum() / valid.sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following function encapsulates these steps." ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "def accuracy(df):\n", " \"\"\"Compute the accuracy of classification.\"\"\"\n", " valid = df['Classification'].notna()\n", " same = df['Species2'] == df['Classification']\n", " return same.sum() / valid.sum()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The classifier we used in this section is called \"naive\" because it ignores correlations between the features. To see why that matters, I'll make a less naive classifier: one that takes into account the joint distribution of the features." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Joint Distributions\n", "\n", "I'll start by making a scatter plot of the data." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "\n", "def scatterplot(df, var1, var2):\n", " \"\"\"Make a scatter plot.\"\"\"\n", " grouped = df.groupby('Species2')\n", " for species, group in grouped:\n", " plt.plot(group[var1], group[var2],\n", " label=species, ls=\"None\", alpha=0.3)\n", " \n", " decorate(xlabel=var1, ylabel=var2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here's a scatter plot of culmen length and flipper length for the three species." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "var1 = 'Flipper Length (mm)'\n", "var2 = 'Culmen Length (mm)'\n", "scatterplot(df, var1, var2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Within each species, the joint distribution of these measurements forms an oval shape, at least roughly. The orientation of the ovals is along a diagonal, which indicates that there is a correlation between culmen length and flipper length.\n", "\n", "If we ignore these correlations, we are assuming that the features are independent. To see what that looks like, I'll make a joint distribution for each species assuming independence.\n", "\n", "The following function makes a discrete `Pmf` that approximates a normal distribution." ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [], "source": [ "def make_pmf_norm(dist, sigmas=3, n=101):\n", " \"\"\"Make a Pmf approximation to a normal distribution.\"\"\"\n", " mean, std = dist.mean(), dist.std()\n", " low = mean - sigmas * std\n", " high = mean + sigmas * std\n", " qs = np.linspace(low, high, n)\n", " ps = dist.pdf(qs)\n", " pmf = Pmf(ps, qs)\n", " pmf.normalize()\n", " return pmf" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can use it, along with `make_joint`, to make a joint distribution of culmen length and flipper length for each species." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [], "source": [ "from utils import make_joint\n", "\n", "joint_map = {}\n", "for species in hypos:\n", " pmf1 = make_pmf_norm(flipper_map[species])\n", " pmf2 = make_pmf_norm(culmen_map[species])\n", " joint_map[species] = make_joint(pmf1, pmf2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following figure compares a scatter plot of the data to the contours of the joint distributions, assuming independence." ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from utils import plot_contour\n", "\n", "scatterplot(df, var1, var2)\n", "for species in hypos:\n", " plot_contour(joint_map[species], alpha=0.5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The contours of a joint normal distribution form ellipses.\n", "In this example, because the features are uncorrelated, the ellipses are aligned with the axes.\n", "But they are not well aligned with the data.\n", "\n", "We can make a better model of the data, and use it to compute better likelihoods, with a multivariate normal distribution." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Multivariate Normal Distribution\n", "\n", "As we have seen, a univariate normal distribution is characterized by its mean and standard deviation.\n", "\n", "A multivariate normal distribution is characterized by the means of the features and the **covariance matrix**, which contains **variances**, which quantify the spread of the features, and the **covariances**, which quantify the relationships among them.\n", "\n", "We can use the data to estimate the means and covariance matrix for the population of penguins.\n", "First I'll select the columns we want." ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "features = df[[var1, var2]]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And compute the means." ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Flipper Length (mm) 200.915205\n", "Culmen Length (mm) 43.921930\n", "dtype: float64" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "mean = features.mean()\n", "mean" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also compute the covariance matrix:" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Flipper Length (mm)Culmen Length (mm)
Flipper Length (mm)197.73179250.375765
Culmen Length (mm)50.37576529.807054
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" ], "text/plain": [ " Flipper Length (mm) Culmen Length (mm)\n", "Flipper Length (mm) 197.731792 50.375765\n", "Culmen Length (mm) 50.375765 29.807054" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cov = features.cov()\n", "cov" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The result is a `DataFrame` with one row and one column for each feature. The elements on the diagonal are the variances; the elements off the diagonal are covariances.\n", "\n", "By themselves, variances and covariances are hard to interpret. We can use them to compute standard deviations and correlation coefficients, which are easier to interpret, but the details of that calculation are not important right now.\n", "\n", "Instead, we'll pass the covariance matrix to `multivariate_normal`, which is a SciPy function that creates an object that represents a multivariate normal distribution.\n", "\n", "As arguments it takes a sequence of means and a covariance matrix: " ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [], "source": [ "from scipy.stats import multivariate_normal\n", "\n", "multinorm = multivariate_normal(mean, cov)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following function makes a `multivariate_normal` object for each species." ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [], "source": [ "def make_multinorm_map(df, colnames):\n", " \"\"\"Make a map from each species to a multivariate normal.\"\"\"\n", " multinorm_map = {}\n", " grouped = df.groupby('Species2')\n", " for species, group in grouped:\n", " features = group[colnames]\n", " mean = features.mean()\n", " cov = features.cov()\n", " multinorm_map[species] = multivariate_normal(mean, cov)\n", " return multinorm_map" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here's how we make this map for the first two features, flipper length and culmen length." ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [], "source": [ "multinorm_map = make_multinorm_map(df, [var1, var2])" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "## Visualizing a Multivariate Normal Distribution\n", "\n", "This section uses some NumPy magic to generate contour plots for multivariate normal distributions. If that's interesting for you, great! Otherwise, feel free to skip to the results. In the next section we'll do the actual classification, which turns out to be easier than the visualization.\n", "\n", "I'll start by making a contour map for the distribution of features among Adélie penguins. \n", "Here are the univariate distributions for the two features we'll use and the multivariate distribution we just computed." ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "norm1 = flipper_map['Adelie']\n", "norm2 = culmen_map['Adelie']\n", "multinorm = multinorm_map['Adelie']" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "I'll make a discrete `Pmf` approximation for each of the univariate distributions." ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "pmf1 = make_pmf_norm(norm1)\n", "pmf2 = make_pmf_norm(norm2)" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "And use them to make a mesh grid that contains all pairs of values." ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "(101, 101)" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X, Y = np.meshgrid(pmf1.qs, pmf2.qs)\n", "X.shape" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "The mesh is represented by two arrays: the first contains the quantities from `pmf1` along the `x` axis; the second contains the quantities from `pmf2` along the `y` axis.\n", "\n", "In order to evaluate the multivariate distribution for each pair of values, we have to \"stack\" the arrays." ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "(101, 101, 2)" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pos = np.dstack((X, Y))\n", "pos.shape" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "The result is a 3-D array that you can think of as a 2-D array of pairs. When we pass this array to `multinorm.pdf`, it evaluates the probability density function of the distribution for each pair of values." ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "(101, 101)" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "densities = multinorm.pdf(pos)\n", "densities.shape" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "The result is an array of probability densities. If we put them in a `DataFrame` and normalize them, the result is a discrete approximation of the joint distribution of the two features." ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "15.87134363991382" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from utils import normalize\n", "\n", "joint = pd.DataFrame(densities, columns=pmf1.qs, index=pmf2.qs)\n", "normalize(joint)" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "Here's what the result looks like." ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_contour(joint)\n", "decorate(xlabel=var1,\n", " ylabel=var2)" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "The contours of a multivariate normal distribution are still ellipses, but now that we have taken into account the correlation between the features, the ellipses are no longer aligned with the axes.\n", "\n", "The following function encapsulate the steps we just did." ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "def make_joint(norm1, norm2, multinorm):\n", " \"\"\"Make a joint distribution.\n", " \n", " norm1: `norm` object representing the distribution of the first feature\n", " norm2: `norm` object representing the distribution of the second feature\n", " multinorm: `multivariate_normal` object representing the joint distribution\n", " \"\"\"\n", " pmf1 = make_pmf_norm(norm1)\n", " pmf2 = make_pmf_norm(norm2)\n", " X, Y = np.meshgrid(pmf1.qs, pmf2.qs)\n", " pos = np.dstack((X, Y))\n", " densities = multinorm.pdf(pos)\n", " joint = pd.DataFrame(densities, columns=pmf1.qs, index=pmf2.qs)\n", " return joint" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following figure shows a scatter plot of the data along with the contours of the multivariate normal distribution for each species." ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "image/png": 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3o1Jt7dKnUqlcXoataal67LZoKIZn2ot72seC08OVv7uJLMlYyszUtVfT1NNAdXPlc5stEIRSEzNn11ZQ8UQpiIydIDzb4tEEc+MLzI0vMD/pJuRZrJo3WAxUNpRRXldGeZ2DsloHemPh36plWd7SuaqpRIq5CTezY/O4hmaJBKLoTTqauhto6W2kurlSjAQThC3iDnq5OdbHobY9z3RBxaYVTwiCIKRTaeYnPcyOzTM3No9/PgiArdJKbWsV+1/sobKxApPNWPQAJxRM4HIGCPhipDMSGrUSe5mR+iY7VtvmfKPX6rU07a6naXc98psy3hkfkw+mmeybZuj6KNZyC7sOt9F+oKUogawgCLlbGjmmU2uem4IKkbETBCFvIW+YqcEZXMOzLDg9SFkJo9VAbVs1tW3V1LRWYbSUtrggFEwweH+OWDyD1aZDo1GRTmcJBZMYDWq6ems2LbhbiSzLLDg9DN0YY7JvCoVCQdv+ZnpP7xb78QRhEyy1RZGkLEql6plugyIydoIgFJUsy3hci5mo6cEZQt4wKrWKmtYqDr++n7r2aqzllk1bcpRlGZczQCyeoaLyi0ygTqemolKFxx3D5Qxg6a3esmVQhUJBdXMl1c2VHHljPyM3x+m/PMTIrXHa97fQe2Y31jLL+gcSBGFDnteRYyKwEwRhRZIkseD0MPlgmqkBF7FQHINZT0NXHYdf30dtWzVqzda8hcSiaQK+GFab7qnATaFQYLXpCPhixKJpTGbtlpzjowwmPXvPdLP7eAfDN8bouzDI6O0JOo+0ceCVXnQGsUQrCMW02sixPU2dz2zWLlcisBMEYZksy7inPEz0TTPZN0U8ksBkM9K4u57mngaqmiq2RbVnJpMlnZGwaFauntVoVIQzSTKZ7Caf2do0Wg09J7voOtrB4LUR7nzygIm+aQ6d20vHwVZRZCEIRbKUrWsorwEW+9vNBTzPRdZOBHaCIBD2Rxi7M8nonQki/igGi4GW3kZaepuoqC/bdgGHWq1Co1aSTmfR6Z5+G0uns2jUStTbdGKESq2i52QXrXubuPH+XS79+DrDN8d54atHsFfatvr0BOGZ9mS2bsnzkrUTgZ0gPKdSyTTOB9OM3J5gYdKNWqumZU8jbV9t3vYtOowmDfYyIwvzESoqVY+dqyzLhIJJqqrNGE2aLTzL9RnMBk7/7HE6D7dx8cfX+bv/7wcc+ZkDdB5u29bXXxC2s+d95JgI7AThObK01Dpya4KJvimy6Sw1bVWc/vpxGnfXodFu70BoiUKhoL7JTiSUwOOOPV0Va9RQ32R/ZoKjqqZK3v5/vMaNn97hyt/eYGHSzfG3D6PVPRv/HoKwXYiRY6LdiSA8F9KpNOP3nAxeHcE/H8TsMNF+oIWOAy2YbKatPr0N2w597Ipt/L6Ty39zA4NFzyvfPi0qZwUhTztx5Fg+sZEI7ARhBwt6QgxcHWHsziSZVIb6zlp2H+ugtm3r2oAU21ZPnijFuQQ9IT7+/gVSiRTnvnOWshpHCc5WEIRnhQjsBOE5JssyrpE5Bq4MMzMyh96kY9fhNnYdasNsf3azc9tdsbOHiViSD//0U8K+CK/80hmqGivW/yFBEHYkEdgJwnMom8kyfs9J38VBgu4QZbUOuk/somVPI6ptWh26U5RqCkYqmeaj732Ob9bPy986RW1rdQnOXhCE7U4EdoLwHEklUgxeG2XgyjDxSIKGzlr2nNpNVVPFjllu3c5kWWbg/vzDCl3jUxW6HneMqmozuzc4BSOTzvDxDy7gmfbxxq+9JJZlt5GdMmBe2P7ESDFBeA4kYkkeXBpi8OoIUlaibX8zPSc7sVWIL0SbqdRTMNQaNS/9wgu89z8/4aPvfc6bv/EqJquxWKcvFOB5HDAvbH8isBOEZ0w8Eqfv4hCD10ZQKBR0HmlnzwudGMyGrT6159JmTMHQaDW88u3TvPPfP+Sj733Oz/y9l5+Z1jQ71VIT3DKz7bloeis8O0RgJwjPiFg4Tt+FAYZujKFUKuk52Un3iU70xmerbH892axEMpUhmUqTzkik01kymSxZaWnXiIwsg0qlRL30R6NCr9Wg12tQqza3N9VmTcEwWgy88ktneOe/f8i1d27zwlePFnQ8oTDP64B5YfsTgZ0gbHPxaIL7n/UzdH0MlVpJ76nd7D7e8cwOjk+lMwRDcQLhOJFokmgsSTiaJBZLEk+mSaYyBR1fq1FjNGixmPXYzHqsFj12q5FyhwmtpvhveZs5BcNRZePYWwe5+MNr1HXU0LKnseBjCvl7ngfMC9ufCOwEYZtKJdP0Xxqi7+IgCoWC3jO76T6+C60+/31aW0GSZILhGF5/DF8gijcQJRCKEYt/0TjUoNNgNukxGbWU1TowGLTotWr0eg06rRqtRoVKtZgRUyqVKBSgYDFwykoSmYxEJpslk5FIJNPEE2niyfRisBhJMDXrJzycQHpYI2azGKhwmKmpslJfY8diKryJ8WZPwWjf34JreI7Lf3uDqqYKjBaxBL/ZnucB88L2JwI7Qdhmspksg9dGuPtpP9l0lq5jHfSe3r3tl1zjiRTznjBub5gFbxiPL0omu7ivzGLSU2Y30dlajc1iwG41YLMY0KyyLy0XGlSQwyVZCjA9vigefwS3N8LYlAdZlrFZDNRX22ltLKe60rrh4Mtq09PVW7Pcxy6cSaJRK6mqNhd9CoZCoeDE24f44f/nXW5+cJfTP3u8aMcW1ve8D5gXtj8R2AnCNiHLMpMPprn5wV2iwRi7DrWx78WebZuRSaYyzC4EmZ0PMusO4g8uDts2GXRUlps51NtIZZkZh92ETrt1bzVKpQKHzYTDZmJXa9Vj5+6aC+Cc8fFgZBaLSU9bUwXtzZU4bPlXnVptesx7qvC6YyQSafR6DeWVxpLMo9QZdBx8tZfLf3ODziPtonnxJnreB8wL258I7ARhG3BPe7n27m08014aOmt55dunsVfatvq0HiPLMl5/lOlZP675AAueMJIsYzUbqK2ysm93AzWVVsym7Z1ZBNBp1bQ0lNPSUI4sy8y7Q4xMehgYneNO/zQNNQ72dddTk0cWb6XJE56F0s2t7TjYytD1Ma6/e5s3f+NV0bNwEzxrA+YlSSIejhMJxIiFYsSjSRKRBIloknQyTSqZJpPKkM1IyJKELC++zlVqFSq1ErVGjVavQW/WozfpMFoMWMstWMvN6E168ZzbpkSDYkHYQtFQjJsf3GP87iSOGjtHXt9Pbdv2mS6QzUrMuUNMurw4XX6i8SRajZqaSisVdjNV5RbsVuOWzmctpkxWYnLay70BF95AlKpyCwd6GmmoXXuPXKkmT6xndmye9797nnPfOUtde03Rjy88bTsOmM+kMwQWgvjngwQ9YUKeEEFPmEggiix98RGv0qgwmBaDNI1eg1anQaPToFIrQaFAqXy4fzUjkc1kyaSzpBKp5WAwEU2yFDJodBrK6xxUNpZT2VBOVVPFM7P/91kkJk8IwjaXzWTpuzjIvc/60WjVHHx1L+0HWrbJt3yZ2YUg41MeJqa9JFMZLCY9TfVlNNU5MGi1zE2HijYTdTuSZRnXXIA7/dPMuUPUV9s5frAFh+3pWbulnjyx3nm+898/RKVR8cb/9nJRjy1sT9lsFv98EK/Lh8flwzvjJ+gJIUsyCoUCs8OErcKCpdyCtcyMyW7CbDditBrR6gqrzM5msoT9EULeCEF3CI/Lh3vKQyKaRKFUUN1cSUNXHc09DaKJdpGJwE4QtrHpoRmuvXubaDDG7uO72PdiT8FvuIWSZRmPL8LIpJtxp4d4Mo3VbKCtqYKWhnLK7IsBy1ZlpraKLMs4XT6u3pkkEk3Q21XPwd7Gx3rlRSMp7t6YRm/UrNjHLpnMkIil2Xe4YUOTJ9Yz2T/N+f91kbd+6xwVdWVFP76wtVLJNAtOz+KfSTfeGT/ZTBaFUoGj2k5FfRlltXbKauzYq2yoS9DSZy2yLBP2R5gdW2B6cIbZsXlkSaZ+Vw3dJzqpaa3aEdn8rSZGignCNhT2R7j27m2mB2eobavmlW+f3vLxX7F4iuHxBUYmFgiE4xj0WjpaqmhtLKeizPxU9snlDBCLZx7LTOl0aioqVXjcMVzOAJYSZKa2ikKhoLmhnPpaB/cGXNx5MI1rzs/LL3Rhe1jUshmTJ9bS2FWH0Wpg5Oa4COyeUY/OnC23OPC4fMyOzjM7No972ossyehNOqqbKzl4bu9iMFdj3/QgbiUKhQJrmQVrmYWuI+2kEikmH0wzcGWY9797HlullT2numjb17wtViSeB1v/rBCEHS6bzdJ/eZg7n/ShM2h58edP0tTdsGXBjyzLzMwHGRidw+nyoVQqaa4v4/jBVuqq7cv7bJ5U6pmo25lapeTgnkaa6sr4+NIgP/rpHU4fbaetqXLTJk+sRqlU0nGwlf7Lwxx+fZ8YNfYMuj3Yx0fnLzCunsCRtpGMJdHqNdS0VnHsrUPUtlZheeKL1nal1WvZdaiNjoOtzE+6eXBpiIs/vEb/5WFOvH2YygbRCqbURGAnCCXkcXm59OPrBBZC7D6xiwMv79myD95kMs3Q+AL9I3OEowkcNiPHD7bS3lyZUzuSrc5MbQflDhNfeW0fF6+P8fGlIQLBOAf2NGza5InVtB9o4e75B0wPzdLa21SyxxGKJ+yPMDXgou/WEJ9duoIkSYyWO3nr3MvsOdBJRUP5M53hUigU1LRUUdNShXvay9Wf3OTd//ERnUfbOfzavm2RbdypxJUVhBJIp9Lc/ug+A1dGcNTYeeu3zlFe69iSc/EHYzwYnmVkwo0sy7Q2lvPiiV1UlVvyygBsdWZqu9Bq1Lx4YhcOu5HrdydJpjP0tNVu2uSJlVgcZhw1dhHYbXPRUIzJvikm7k/hcflQqVX4NUFsBxwcONzNeMCFolVJVVPlVp9qUVU2lPPmb7zKwNURbn14j4VJNy/+/AtYyy1bfWo7kgjsBKHI5iYWuPija8TDCQ69to/uE7s2/Zv3Um+2u4MzTM34MBq07Ouup6utGqNhY8ukj85ELa9QkkplyWZkVGoFWq1qUzJT24VCoWB/dwM6jZoLN0ZBhp49tcxMBUs+eWI1DZ21DF4b3TY91IRF8WgC54Npxu85WXB6UKqU1O+q5czPnUBfreOHN96nS9+G1qSlhp07vUKpVNJzopPa1irO//kl3vkfH/HqL52mon5n/Z7bgQjsBKFI0qk0N9+/y+C1UaqaKzn3y2c3/RvpUhXnnX4Xbl8Yu9XI2WO7aGuqQKUq7MN+aSaqey5M/715Hq2nVyigutZa8szUdrO7owYUcOH6KCaTjr29dcSiaTKZLGq1alP7+9XvquXep/345gKiiGKLZbNZpodmGbk5zszoHAB17TWc+tljNHbVLfd7++Tepedu5qyj2s6bv/EKP/of7/GH/+8/4pu/9TY9e7u2+rR2FBHYCUIRLDjdfP7XV4lHEhx76yBdRzs2NcCRZZmJaS+3+6bxBaPUVFp5/UzPuo11N0Sx+HjptIQkyygVCjQaJbA1nZNkWd6yYApgd3sN0ViK63cnsVsMNNVvTVBVXutAqVLimfbmHNht9bXbafwLQUZujTN+d5JENElFfRnH3jxIU08DBtPjWdvneeaszqCj/IUy3AM+/vq/v0P1P6va8FaVRyuKd+r1ypcI7AShANlMljuf9NF3YZCKhjLOfecs1rLNy9ItBXS3+qbwB2PUV9v50qFeaqqKP45sqd1JIp7BatcT9CeXAwKrXUcinsm53UlGkkhkMmQliawskZXlxVFGCiVqpRKVUolWpUKrWnu/3kpjvLaiWfKh3kYCoRifXB7iq6/vX26FsplUahVlNXbc0z52H1v//tvl2j3r0qk0E/enGL45jmfai96ko3VvEx2H2nCs8Tp8nmfOuoNehhYm6Hqtg6mPXPzkTz7gF/6fX9tQP88+5xBXh2+jU2t27PXKlwjsBGGDAu4gn/3/rhB0hzj4ai89L3Rt2t4mWZaZng1w474Trz9CfbWdU0faqS5hX7xYNM2sK0g4GCcrgcmsQaXSkc1KhAJJVEqYdSlpai1DoVPgjcXwJ+KEkklCySThZIJoOk08kyGdza1yVqNSYdZqMGm02HR6KoxGyo1GKowmMrHsY82SLQ8LFhbmI0RCiU1tlqxQKDh7bBc//OkdLlwb5c2X96wa3JYyS1ZW68A95Vn3fk82mt7Ka/esCvnCDF4dYfT2BOlkhtr2al78+ZM0dNWhWucLybM2c7bY+pxDRBNxuupbCR+J47wxw6UfX+fsz53I67WwlPUsM9t2fJYzHyKwE4Q8ybLM0I0xrr93G5PNyJu/8eqmVrzOe0JcuzPJvCdEdYWVL71cmgzdk9LpDF5PDCkrY7MvDgCXZZmMSiJqSDMdDBF1zXHvtgdZvfjmrFQoMGu1WHU6HAYDDTYbBrUGvVqNXq1Go1ShVCpQKRQoFQoykkRWkklLWVLZLNF0imgqTSSVwh2LMuj1kJEkQCbpz6BPqOisLseq1qFUKra0WbJGo+KFw228e76P4fEFOleY+VvqLJm13MzonQlkWV4zsHzeGk0XiyzLuEbmGLgyzMzIHDqjjs4j7XQeacdsf3rc3GqUSiVvHDi77szZnRjUPbkE3dRYiys2y4ObgzR21dG2rznnYz0aIA66xnd0ljMfIrAThDwk40ku/fg6zn4XnUfaOfLG/k3rxxQKx7l2d5KJaS/ldhNvnO2hvmbzihXSKYlkPIXCpMSZCuHNxPBlEiSkDAAqpQJ9SkWXrZL2unLKjQbsegPKIp6fJMsEEnGmPEEuuMfxqxJ87naiUCio1Ztpt5RRb7RsWbPk+ho7HS1VXL0zQVN9GfpHlpY2I0tmLbeQTWeJhWKYVphrC893o+mNSqfSjN6eYODKCCFvmLJaBy989SgtvY0bfv0bdHoMuucvK7oUjD1WMFLtQQ7DzQ/u0tRdn9M1fTJAfB72JuZKBHaCkCP3tJdP/+IS6VSGF3/hBZq7GzblcZOpDLf7pugfmUOv03D22C46Wiqf+lAu1RJfOptlKhSkb2Geq4o54uE0er0Gu1pPvdaCQ63HptSRCmVQmBWcaGjA7ijNAHClQkGZwYjKoiBorKKs3EhcSjMTCzMeDfDZwiR6lZo2k4OqjHFLmiUf29/MxJSXB0OzHNq72FNus7JkJtvidY+FE6sGdqLRdO7i0QSDV0cYuDpCOpmmqbuBF756hMrGCpHN3IC1CkY8TX68d/wMXhtlzwvrV8muGCDu8IriXInAThDWIcsyDy4NcfODu1TUl3H2506s+qFZ7McdHl/g+t1J0hmJAz0N9HbVrdgAuNhLfMlMhvGAn2GfF2cwQDorYVCo6XCUoYkqscoabHoDKpWSbFYiFk6hUispKzei2YQM5qPNkk06Lbus5eyylhNIJRgN++gPuLmXltC4tZw0N6FTb95bnUGvZXd7NX3Ds+zpqkOnVW9alkxn1AGQiCZWvY9oNL2+kC9M34VBxu5MggI6D7fRc7JzU173O9laBSMJVRJDtYb+y0Pr9v58niuKcyECO2FHKlb2KpVIceGH15gacLHnVBcHXuldd2N0MXj8ES7dGGPBG6a9qZKj+5sxPfzQflKxlvgyksS438+A181kIEBGkqg1mzle30ir3YFDr2fQuIBzwg+yRCSSRsqmUaqU2Ox6UCipqbdtSoPiR5slPzrGy67Vc6isluq0Cbcuzj3/PIMhD2ebW+mu2Lxu/nt319M/Osfg2Dz7dtdvWpZMZ1wMCpOx1fdurXbtYPNGoG1X/oUg9z/rZ+L+FHqTjv0v9bDrcBs6w8qvPSF3uRSMmNvMRK/FmBmdp2FX7arHep4rinMhAjthxylW9so/H+CT/3WRZCzJy986RWNXfQnPelE6neXGfScPhmdxWI3rFkYUusQnyzIL0SgPPAsMejwkMhmqzWZONjayq6wc6xN7gOqb7ERCCaKxNDaHEaVSgSTJJBIZTCbtpjUoXmqWvNoYL4fZwIk9LSj0Cj6fmuS9kWGmg0FeamlFswmBudGgpaW+nOHxBfY+zLJuRpZMpVKhVCnJrhEgrnftNmME2nbjnfVz79MHOPtdmGxGjr55gI6DrWKeaRHlUjCiVWv5YOo8o7cnVg3sngwQw/EoU+4ZGivrsBhMO76iOBfiWSvsKMXKXo3fm+Tij69jLbdw7jtnsTjMJT93p8vHpZtjJJIZju5rpmdX7brTIja6xJfOZhn0eri3MM98JIJZq6W3qpruikrKjavvj7Pa9HT11iwHzonUYkBSXWPZ9P5nS+cyPelnYS5MMpVFp1VRVWOhodmxfC5vdnTSbLPz8cQYc9EIb3V0rvk7Fkt7cyWjTje+QIwyu3HTsmQKpYJsVlrzPk/+O27FCLTtwOPycvf8A6aHZrGUmTn5lSO07W/elKx8PrJZiWg8RTSWJBJLkkxmSCTTJFMZMpksWUlGkh72glQpUauUqNVK9DoNJqMOk0GL1azHYtZvacCeS8FIU08D/ZeGVg3MngwQP3twjWA0RE9DB2d6jgI7t6I4VyKwE3aMYmxQlySJG+/fpf/SEG37mznx9uGSf2uPJ1JcujnO+JSHxloHJw+3YTE9/ea30vJyvkt8oWSC23Nz9LnnSWWzNNscfKVrNy12R87Vq1abHvOeKrzuGInEYiFFeaXxsTfSTZ1ooFj8X4ql/1jhYXoqq6gymfnJ8CD/q+8eX9vdTZ2ldD3/AOqqbeh1GsanPJQ7mjctS6ZSKZGl9aeAWG16LL3Vz+XkCf9CkNsf3WdqwIWt0srprx+npbdxy4MBWZYJhuN4fFH8wRiBUIxAKE44mkB+ZIafRq1Cr9Og1arRqhdbBikffglMpjLEMhKZbJZYIk088UWGTKtRU243UVFmpq7aRm2VreBRg8VW21rFnY/78M36V50juxQguoNepryz1JVVMeWdJZVJP9d765aIwE7YMQrdoJ6MJ/n0Ly8zN77A0TcPsvtYaceCybLM+JSHSzfHAXjpRCdtTStX2622vOwoN+a0xOdPJbg4MsWw14tWpaK3qpp9VTXY9PlnZlY6F8/CF0vdmzXR4NHsrM2hXw6U3PNRoqHkU9nZCqORX9izlx8PDfCjwX5+rqeXSmPpNsOrVEpqq2zMLSzuJ9qsLFk2Iy1/yK9HoVA8Vy1NQt4wtz++z2TfNCa7cc2AbjNGVSWTaea9YebdYRa8IXyBGKn0Yvsgs1GH3Wqkqc6BzWrAYtJjMmoxG3V5LdlnsxKxRIpgKI7XH8XjjzDm9HBv0IVWo6apvoxdLZXUVtm2RVBfXl+GSqNiwelZNbBbIvrYrUwEdsKOUcgG9aAnxMffv0AiluTcL5+ldoXmssUUT6S4eGOMiWkvLQ3lnDzUhtGw8gfsWsvL4WAcrU5NKJhccYlvzO1nVhMhMzaLTW/gxeYWuiur1h3VtZr1lrrrmuzMPMyalnKiwUazszq1mq907uYv+/v40UA/3+zp3VBwm6vaKiuXb44vBtgaVcmzZLIsk81kUam3VxZmq8XCce6ef8DwzTEMZj3H3z5E+4GWNZdcSzGqKpPJMu8J45oLMDMfwBeMIcsyRoOWqnIL+7rrqXCYqXCY0G1gvNZKVColFpMei0lPw8NG6rIs4w/GmJjyMj7lYWRigapyC/t7GmisdWxpgKdSqbCWWwh5I2veT/SxW50I7IQdY6Mb1GfH5jn/5xcxWAy89ZuvlnzW69SMn8+uDiMDL5/soq2pYtX75hLAmM0qDAb1Y0t8rnCI6/MzBOUEnU1VnO1ooaOsvKBmweudi3shSt/tWXR6NRVVppJONCgkO6tTq/laVzd/8eA+PxkZ4ud7elGVaAmuptKKJMt4/BFqHxbBlDJLlnmY7RGb/helkmkeXByk7+IgKrWKQ+f2sftYB6p1Ml7FHFUVi6dwzvhwzviZmQ+QzUoYDVrqqu3s6ayjutKKxfT087iUFAoFZXYTZXYTB3sbmZ4NcKd/mvc/66fcbuL00Q4qykq/r3g11nILQc/TlbOPEn3sVide/cKOsZE2DsM3x7j8tzeoaa3ixW+eRKsv3bJUJpPl6p0J+kfmaKx1cPpox6pZuiW5BDCJWJrWXRX4vTHG573cCc7jzcSptVl4u+cg+xprivKhsd656PVqXJN+2ruebp5c7IkGhbYPMWm1vNnRyf/qu8cV1zQvNDYVdD6rsZoXJ28Ew/HlwK6Ultqc6E3Pd3uObDbL8I0x7p5/QDqZofvELnpP78759V3oEl8okmBi2su404Nz1s1cwM3e9lYO9zbRUGvHbjVui2VPWHxtNtY5aKxzMLcQ5MNLffz7P/0bvnT2ICf3d23JeZpsRvxzgVVvF33s1iYCO2HHyKeNgyzL3ProPvc/66fzSDvH3jpY0o3TvkCUjy8NEY4meOFwG7vbcwu2cg1gUqosY7ogD7Q+yuvNvN3Qw566qqL+Tuudi1KpIJ2WUChX/r2KOdGgGO1Dqs1mTjQ0cmnaSZvdgUWhK/ryqEqlxGLWEwzFCz5WLpYaEz+vgZ0sy0wPzXDjp3cJ+yK0H2hh/0s9eTUW3ugSXyyeYmzKw+iEG48/glqloqHWTmU9eDUL1DS3sHd36VsmFaKmykZNM1wZn+edT++Qiis5daQdzSqv+VLR6jWkEqu3RRF97NYmAjthR8llg3o2m+Xij64zfneSw6/vp+dkZ8m+lcqyzND4ApdujmEzG/jqa/tx2HJvtbFeABNNpuiPu7k2PIfNqOet3Z10V1YVtOQqSdKKFa/rnYskyWg0q1dkFnOiQbGa7B6pq+fO9Cx/dfk+B7XVJSn2sJj0RGLJgo+Ti+jDANJgMWzK420n/vkA1396h9nReWrbqnnx50/iqLbnfZx8lvgyWYnJaS8jE25m5gPL2a+9u+tprHUQiAX4y0vXqbTbn4lMkjvoZWhujK5OB6FAjP6xaSLRJD/z8h7Um1g9q9FpSCczK96WS6Nj0cdOEHaYtTaop5Jpzv/5ReYn3Jz5uRO09pZmCQ4WA5mLN0YZmXTT1VbDiYMteQc1qwUwsiwzGvZxcXoKnUnDWy1dHKqtK7j5rmsqQN/tWdzzYdJpCY1GSWW1hT0HaqlrsK0ZTCUSGSqrLSQTGWSrzOL/SChQgkxxe7U9mp1diKLTq1EoFciSTDKRwZhjs+RIKIkjpOWCe57dzeVU2cxFL/bQadWPtZwopYg/ilqrRr/KlJInbWpbmhJJxpPc/ug+Q9fHsJSZeflbp2jorNvQ75HrEp/XH2VobJ6RSTepdIbqCisnDrXS2liB/pGih2etavOx802NU1ehxDMX4eL1Uc6UuEvAU1Z5qFwaHYs+doKwA620QT0eTfDRn31GyBvh1V8+Q21r6SpfA6EYH14YJBpL8tKJTtqbNzbOaqXl5bCU4rJ7itlQhHabg68f20tdZeE92VxTAS58NEokmsJRZkCrVZNKZZieWsx+nnqlfflc3O4oeiukNDHC6Qj+WBjZnMbQqMDnD3M7mEKjV6BSKslKEslkFp1Jjc/sYN5twag2YlKZKNOWUa4rR6vMP9iz2vTUNdnpuz3L9KT/sUC0Y3flugHZUjFIOUYqbUbGEgFqLJaiF3totSr8wZWzD8UW8UewOEw5ne9mtaUpFVmWGbk1zs0P7iFlJQ69to/dxzsKai681hKfPxziw2u3MFPNvDf0cCZwDZ1tVdhWyJA+a1WbK53vTGSaI7uPc7dvgTK7id6uuqK1gVnrOFJ27WxbLo2On2cisBOeC9FQjPe/e550Is0bv/YSZTWOkj2Wc8bH+cvDGPUavnxuX15LrytZWl6emPByacrJUNiHXavja7u6OdhZX5QPYUmS6Ls9SySaorbOsvymqlZr0evVzMyEuHp3kN2nbYSb3Djdc4TiUaSkjFqpwmGzUV9RTrnFRtom419IEA9myGZBpVJgtmkprzahMUI8GyeWieFL+hgKD4MCHBo7Vfoqmo1NmNS57YcKBRPMOANo9WrauyofG2824wxgserXvDZLxSB2u56OeDl3vHPs0VWi06rQ6dRFK/ZQKZVI0tqTIIrFvxDCWrF+kF+sCS1bxTvr58rf3sDj8tG6r5nDr+3DWODy82pLfOmUhNedxutREtDM8uKBal49tZumujKUq+wnhWevanO1843KHvZ21XP97iRNdY6itYFZ6ziZdAb1Ju/r20lEYCfseCFfmA+++ymyLPPGr72Mtbw07UxkWebOg2lu9k3RVFfG2eMdaIvUdsIvJ7guzRIwpnmlro3DtfVUVZuLttzgdcdwz4dxlBmWj5lWpAipfITVfgJtfqbTKZLztTSW1XC0fQ/6jBkTZsxaEyaz9osskR3kmtyW+KKZKO6kB3fSzXhknMHwEDW6atrMbVTpnq6uXfJo65XKqsczVBarnFO2bakYRJXKovLKeDxRbgVdVGvNmM1aHOVG0hmp4GIPGWATlrBkWSYwH6C+Y/e69yt0QstWSSXT3Pn4PgNXRrBVWnnj116meoPZ8Cc9ucTnC8ToH57H6fVTb1Rw9kw5vZ0NVFfY1z3WVlRtFpJJW+98v3a0g/EpDR9cus+8VHgbmPXaySSiyee2AKgYRGAn7GgBd5D3//g8Gr2G175zNq/quHxkMlnOXxlmYtrLwT2NHNzTWJQPxWQmw+fOSa5PuTAm1RxSVaHzqxkPe/B7YkVbNksk0osVrToJt2aGkNpLVBVGISswSRaqMw0k5tWc3HuQ5or138hz7dVmUpswqU20mJrJSBmm4y7GouNc9FzCqrFytOwwVs3TGahCp4zAYmFKNp3FORdGykrYtDpCmhRNOhXBQJxwOEl5ubHgYg9ZljcjriMajJFKpHFUr91WpRjXbrPJsoxzwMXVn9wilUhx8Nxeuk/sKvpMV71Wh8+f4N6AC9d8AItJz+kjnexqrUKnzf3jciuqNgvJpK13voMzIxze28Ef//gjtBVRDuxqL2jP4Hp7DxORBPoVxioKuRGBnbBj+ecDvP/d8xjMes79yosYSvRGEYun+ODzAfzBGOdO7aa5oTjfxF3hED8dHcEfjtGctFCjMGOzfjE6q1jLZpIsEVL58FSOMWuIoNGosGTtNCY6sGQcqNEQi6XQkMJoKN23aLVSTYupmWZjE96UlzuBu3y8cJ4uXQ+16rrHMn+Ptl6RZUgmM2SzEiqVEp1OnVNrFYNRTTotEQomqK2zUJkw4s8kFn9/q47ZmTBWqx6DsbC3yVQ6W7TM7VrcUx5gcSTTWgrtAbjZosEoV35yi+nBGRq66jj+1sGif0GTZZlJl487D6bx+COU2028dKKT1saKNZdbV7IVVZuFNFTO9Xy76mSCiQA1qcVrv9HsYy57D8P+KGW19pyPKTxOBHbCjuSb8/P+dz/FaDXw2q+8mHOVYL78wSg//bQfSZb50iu9RenWnpUkLrumuD7josZkZo+pkXgyXfRls0Q2wXh0gvHoBAk5gcGuRD1dQ4e9CY3yi0yNJEn4fXEaGu2UVxa2XzAXCoWCCl0Fh3TH+XT2Cj+NfoYjU0Uruygvs1DfZF9uvRIKJAiHk0TDyeXAzmTRYbHo1m2tEo9lUGuU2Kw6wqEURo2GqWyIZCpDIpbBZtWj1iiJxzIFZa4SifRjlZKlsuD0YK2wrPsFphg9ADeDJEkMXB3h9kf30eg0vPgLL9C0uz6n53muy5KyLDMx7eV23zS+YJTaShs/8+Ie6qo3Pje1FFWb6/0+hVTfPnm+npCfOxP97G/ppsLqWD7fy4M30ZmzxCJKZFne8J7B9fYeyrJMyBumdW/pOhbsdCKwE3Yc35yfn/7xeSwOE+e+cxZdibJMM/MBPrwwiMWk47Uz3ZiKEDyGkkneGR5kPhrlZEMT3dZK7t90FXXZLJQOMxIZZSo2hUKhoMnYSIuxhSgyF1yjLMzEcZSxXBXr98Uxm3XsOVC7/GFU6jYZoWCCkT439ngTBquFSf0wE9l+MvPdREIJOvdUo9Wp6b83h0arwmTWolJpyGYlAr4Y7rkw3Xtr1mytkslkUWtUNLaW4/fFCAWSJJIZgqoEVQ4LjjIjiUS64MxVPJmmwlH68Uzzkx6qGlcfT7ekWD0ASyngDnLxR9fxunx0Hm3n4Kt70eYRHK+3LCnLMk6Xj5v3p/AFo9RV2/nSoV5qijQdZL2qzXQ2y3wkQiiZJJxKEkmliKZTpLNZ0pJEOptFoVCgUSpRKZXcGb3P9eEbvOH38bNHX6HKZEb98LWYT/XtagHio+d7a6yPvqkhysw22mubH3uM9sZKxocThMNprFZt3lm7XPYeGmQ9mVQGW0VpRzvuZCKwE3aUxeXXT7E4TLz2Ky+WbETYmNPDp1eGqam08sqprqIstY35ffx0dASNSsU3e3qptVgIBuJFWzYLpcMMhgeZjrvQK/V0W3fTYmpG+zA7Z2+EU6+0L/exC6YTaDRKGhrt7DlQS32jffE4JW6T8fTmfhMW2cQ9xS1i5fMovDW4pgLI8mIj5CfjycX/Xj/IXMpcabRKGprs6Mo0DM36qaq20mC1kUplyGYKy1zJskw4kqC1sbTtLaKhGIGFIHvPdq9733wmtGy2bDZL34VB7p5/gNlh4o1fe4mqpvyKI9ZalpRlmenZADfvO/H4I4sB3eG91BShXdBqkpkMc5EIc5Ew89EI3nicUDLBw6cvGpUSs1aLSaNFo1JhUGuw6XRIskxGkvFHg9x2DrOQzPC3g/0EVWZsRjP1FiuNNhuzs6M5V9+uF/Cudu2W9uA1VVjISBE8vjAqrSHvPYO57D1sUTYAUF5Xus4FO50I7IQdw78Q5P3vnsdkM3LuO2dLFtT1Dc1y5fY47U0VnD7agarAjuySLHNp2sk1l4s2h4PX2zvQqxezE8VYNoukI/SHB5iOuzCoDByw76fZ2IRS8fR51zfaqa23rjh5AnJvk1FIRm+lzf02hYNmZRuT0hi7rBYWZmVApq2zgnAwQSSSQsqmUaqU2OwGLDY9qWRmOZO50vk8mbkyG7RoNCqUGgVQnMxVPJEmlc6s2OesmGZG5lAoFNS25dabMZcJLZvNvxDkwl9fxT8fYM+p3ex/sQfVBoLq1ZYl3d4w1+9OMrMQpLrCylsv95Zkfm8qm8UVDjEVDOIMBvDGY8gy6NQqakwWOhxllBkMlBuN2HR69Gr1mq+NH15+DwJODtjKmAtOUq/YS29DN1PBIB+ODHJ3cohak5HKZIoy3eJ73kqZtFz24a107c7uOb68By8YDyMp0yz4wmgtaSD3PYO57uVz+zyYbEYM5udvekqxiMBO2BEWW5o8LJQo0fKrLMvcfjDNzftOejvrOHagBYBoJLXhJclkJsM7I0NMBgOcbmrmcO3jHfMLWTZLSWkGQgOMRcfRK3UcsO2n2bRyQPcopVJJZfXTS4e5tsmQG23MTAU3nNFbbXN/g6KZkCLAhGqI2lQPCpRUVJmx2fWLxRMZGZVagU6nRpbB542RyWTXzDA+mrkyWBZ/LpZM44nEipK5CoQWsxKlDuymh2Ypry/Lay/pWhNaNpMkSfRdGOTOJ31Yyy28+RuvUlG3dgHIalZalrw9OkxgXoPXm8RhM/LamW4aax3r/p75tA8JJZOM+32M+f1Mh4NkJRmzVkuTzcah2jpqzGYcekPe19Yd9HK+7wp6jZZKWzmhWITbwzd5a/9JDtfW80HSz4IqS1qGz2bmqdRp2W0zoVshk7bePry1lnQf3YP3mW6MZDLDuTOdyz+by57BXPcefvTHn1FZ4gz3TicCO+GZFwvH+eBPPkWj03CuRIUSsixz/a6TuwPTHO5t4sCexoKXJH3xGH8zNEA8neFrXT002+1P3Wcjy2aSLDEZc/Ig1I8kS3Rbd9NhbkelKGwzfC5tMuZcQbzuKFlJ3nDj29WylAqFghZlB9fSl4jp/ZRJVcv30esfD2xTqQwatZJ4LM3UuG/NDONS5mrOHSIeT5MxZKmqK07myu2LoFGrShrYpZJpZkbmOPBKb94/m2tbmlIJecN8/tdX8bp87DnVxf6X9mwoS7fk0Y35mYyEbwHuDwSJVk/w86+fpb25Mucq1/WWLcPJJMM+L0NeD3ORCEqFggarlTNNLTTZbBsK5J50of86k+4ZWqoXlydryqqYmJ/mQv91vnLsNSKJKO0OG7Is40kpGI9GmI9G6LToH8ukecP+dffhLV07i97EzbH7tFc3E03ElwPApT14DosFdzqCzZT/8vV6ew+T8STeGT+dR9rzPrbwhbwCu3/xL/4Fv//7v//Y33V1dTEwMABAIpHgd37nd/jBD35AMpnkjTfe4D/9p/9EdXXpRjcJz7dkPMkHf/IpUlbi9V99qSQtTWRZ5vKtcR4Mz3L8YCu9nXUFd+6fDAT4ycggJo2WX+zdi12/+gd/PstmgVSQ24Hb+FMBGo2N7LF1Y1DlF1Sstoy6XpsMtVqJxxPFatPT8EiwmW8F71pZSiMm9DErsXIPXco2PO7YqpnMyioTPm903Qzj7t5qdvdWY/MZqbk3y57OOrpqK4qSufL4IlQ4zHm3zMiHa3iWbCZLc09DyR6j2GRZZujGGNffu43RYuCNv/dyToUfa1nKOFXbypmdjeF0RshmJTrbyzE54tjLVDn/O6y2bJnKZhnxeXngXsAVDqFUKGi1O/iZjl202h3o1MXLlTyarTPpFl/DJp0BvUbL+b4rnOo+8lQGLJpK8cHEOHPRKMdbWuipWix4Wq8S9dFsndPjYmhmHI1KTVNF/VMBoFazWFRVCrNjC8iyTG27iBkKkfezcM+ePXzwwQdfHOCRJ/Jv//Zv83d/93f8xV/8BTabjf/j//g/+PrXv86FCxeKc7aC8IhMOsPH379APJLgZ/7ey5jtxW8+LMsyl2+O82BkllOH29ndUVNw5/5+9wLvj43SZLPxZkdnTh8G6y2bSbLEYHiIwfAQFrWZs5VnKNflv5y1VhZyvf1+0UiKVCKDrfnpTEU+FbzrZSmbjM14rGNY7SpiEfWqmcyyChPjw56cK4pVOiU6vQaHtfBMCyw+d+bdITpz3Pe2UZN9U5TXOUry/C+FeDTBpR9dY3poll2H2zjyxn402sIrcPucQ8wtBMmGJaLRDBWVOhobTWh1KiYWXHm15ehzDrEQ8LBYhCPz+fA9LGUNDHq9pLNZGm02XmvroN1Rtu7rd6MTIS70X2d8fpr68moSqeTy3zvMNsYfZu2+duKNxzJgNhP8sr2c90aHuTAzS5XVgS4eWQ7agtEwo/OTtFc3P5a1WypqUCmUjM450ao0jM45qbCUPbWkK8tyyb6oTD6YpqzWgcmae1ulYs2u3UnyDuzUajU1NTVP/X0wGOR//I//wfe+9z1eeeUVAP7n//yfdHd3c/nyZU6cOFH42QrCQ7Isc+Gvr+Kd9fP6r76ELYf5mBt5jCu3JxaDuiPt7G5ffN5vtHO/LMtcn3Vxwemkt6qKV1rbUeYRQKy2bBZIBbnhv0k4E6bL0kmXpXPdfXQrWS8L2bmnes39fsFAAq1eg8ms23DT4CVrZSlrGmv5NDpNShelq7du1UymLMt5VRQHkwkAbPriLOV7A1HiyTT1NfaiHG8lyXiS6aFZDp3bW7LHKBZ30MuH5y8QvxvFpDPyyrdP09BZV5RjR2NJrt+ZZmFKicGYoKFNh9EsE81EiWbyawq8lL1KpFL0exfQWaoZHhjgWJuSY02t9FRWYs1jAP1GJkJIksQ95xAoIJ5KEn8ksANAAfenhvjKsdee+n2UCgWvt3UQTaV4d2SYRmViuRK1zznMoGuMTCbLnqZdBKNh7k0OEopHsJks9E+P4I+EqLZXMB/w0D89Qmd922PXLpPNoi6wYGwlmXQG1/Ase8+sX9n9qGLNrt1J8g7shoeHqaurQ6/Xc/LkSf7gD/6ApqYmbty4QTqd5ty5c8v33b17N01NTVy6dEkEdkJRXf/pHZz9Ll78hReoLNKkh0ct7qmbpG9ohhcOty0HdbCxzv2yLHN+coLbc7OcaGjkeH1DwVkhWZYZjYzSF+rHrDbzUuWL2LUbq/LLJQs5MxWkrtG2aibNZNai0SgJBzfeNPhRa2UprSkr/lSA9rK2Ve8TjaTyqigOJhPo1Cp0quIsp7lmA2jUKqpKNJsYwNnvQpZkWnq3dzPXbCbLj7//Uy5+eJ0Dh3r4xX/wtaJUPcqyzODYPNfvTlKuq+OlrxyivWXlaRG5NgW+Od7P3QU34+EkGY0NORmnXq+m16zmRENjXudXyESIrrq25SXYlTRWrB4Uq5RK3mjfxXfv3OK2fx6byYLTM8vI3AQKpYKRuQksRjM2k4VwIspr+04zF1ggnkzQ3dCB1WgmFIsQScR4ff9p6su/6GGZSmXRrPLeV4ipwRkyqcxjWwrWy8a5g16ujtxlLrDA1ZG7JZnB+yzK6x3s+PHj/NEf/RFdXV3Mzs7y+7//+5w5c4b79+8zNzeHVqvF/sQG8Orqaubm5lY9ZjKZJJn84ttIKPR0GbQgPGrg6jD9l4Y49tZBmnbXl+Qx7g64uDvg4vjBVro7ah+7Ld8WJJIs8+HYKA88C7zS2sa+6qcz3vlKSSlu+G8xF5+jw9xOj607p+KI1fbP5ZqFbGotWzWTVtdoY2TAXVDT4CetlqW0qM3EsrE175NvRbEnFqOsCBvelzhnfNRV2wtuh7OW4Zvj1LZXYyxx1W0hQr4wP/mTD7lz4wEtJxpR9WiJZGMYKOycfYEoF6+PMe8NsauliqP7mzEU0OIomEjw0egAf913n1Aigy6bZF+ZA49/HoOsZ3BmjL3NXXkFDhudCKFUKvny0VcLml5h0enYX1PLTSnLN7q7uTp0i1Q6RUdtMyOzk/Q0dHCm5yg6jQ69VsfUyCySLFNbVgWASW9k0DXOlGeW9tqW5eNGokmsluLvZR67M0llYznWR74IrZeN63MOMT4/RSgeRpKmSjKD91mUV2D35ptvLv//+/bt4/jx4zQ3N/Pnf/7nGAwbe5H+wR/8wVMFGYKwmumhGa69c5vuE7vYfWxXSR5jKQNwsKeR3hWWivIJGCRZ5r3RYYa9Xl5v30V3RX7NVh+1FJR5Ez7uRG+h0MicLD9OjSG3QHGt/XP5LFva7IYVs2SP2mjT4FypFCqy8tpLuvlWFM+Gw7Q7NtZm40mRaJIFb5gXj3euf+cN8s768Ux7eekXT5XsMQo10TfFpR9fZzo4Q9VLVezf213Q8HiATFbi7oNp7vRPYzXrC+5H54vHuD7jYsDjweVxoU9HUSTcmHV65GwSg1bPbMCDUqnK67zzmQixkvUqSHNxoKaWW3Mz3F+YZ8o7S0tVAya9kZaqBqa8s6QyaWwma04TIZbOORRNUFdT3P5/8WiCmdE5jr15cPnv1st2LmXrEqkEFr2JRCohsnYPFfRV0m6309nZycjICDU1NaRSKQKBwGP3mZ+fX3FP3pLf+73fIxgMLv+Zmpoq5JSEHcw/H+DTv7xMQ1cdh1/fX5LHmJz2cuH6KN0dNRzsXXnZZSlgMBoWN+4nkxkkSSaZzOBxf9H/TAbeGR5i2OvlzY7OgoK6UDDBwP15Prl5k7/uf4+FqSj1nh6MKXvOPz94f46F+Qh6o4ayciN6o4aF+QiD9+eIx9LLWciVPJmFXMqS2ewGTGbtctYvlczQ1lmBzW4gmcwSCSdJJheDwbbO8uWmwYXKJbCDL/bqVVWbScTS+LwxErE0VdVmuvZUL1cUR1MpQskktZbiLJtOTHtRKZU0lrB7/tD1UYxWAw2dtevfeZNlM1mu/N0NPv2LS1jqTRhOmWlpe9iy42Gw4A568z7uvCfEj356h7sDLvb3NPDVNw6sGNS5g17eu/Xpmo8RSMR5Z2SIP7l7G2cwyKnGJo6VWTBlo4RjISRZIhKPIckSgWiISCK6vNcsF0vZOptp8TllM1mW24dsFrNWS7PNzqWJtc9lqXhCrVIx61vgYv9NZn0Lj02EAIjFU8QTKRy24s6MHr09gVKppHnPF++5S9evqbJ+xeu2lK1TKBRU2spRKBSMz09t6vXdrgraTBKJRBgdHeU73/kOhw8fRqPR8OGHH/KNb3wDgMHBQZxOJydPrv4NR6fTodOVZpansHMk40k+/sEFLGVmTn/9WF4DtHO14A3z8eUhmuvLOHGwbc0lufVakFisOt4bHWHU7+Ptzi7aCsgELQZ1s4ylxvGZpmlU19GU2UVoIcNgeG7d1iq57J/zeaPYHAbcC9ENzw9d2ntYVm5ct2lwrlZbOs7K2Zz78uXSiHcyGEChgHpL4UU4siwzMrFAQ60DnbY0rULj0QRjdybZe7a7JK+FQoT9ET79i0v454Mcf/swM9p5EmOpx4KKfIfHZzJZbtxz0jc8S4XDzFdf34fDtnoV8FpLeOFkkquuafrcCxg1Gl5qaWNPZRVqpZJKDUwuTC3vM1uytN/sUOuenK53PhmwUjMoZIYW5ni17vEvlkvn0t3Q8dhEiCHXGCNzkyTSCTrr2x4rPPH4IgBUlhVv36gsywxdH6V5T8NyD9L1sp2PZuscFjsAdrMNfzggsnbkGdj97u/+Ll/+8pdpbm5mZmaGf/7P/zkqlYpvfetb2Gw2fv3Xf51/8k/+CWVlZVitVv7hP/yHnDx5UhROCAWRJIlP//IyqUSa13/1paK0RnhSKBzng8/6qbCbefFEZ07l/KsFDAAfTYwx6HXzZkdnQUGdLMtMTfoYSPcTt/poU3XQqGhBoVZg0Glz6g2Xy/65oC9O664KouHkhueHPrn3cLWmwbkWT6y1dBzPJtCrcl+mWq8R77jfT43JjElbeLNerz+KNxDl0N7SFTQMXh1BoVTQdXR7NXKdHprh87+6gtag5c3feBXJKPHRpUsFBTgL3jCfXRkmHEtydF8zezrr1nx9rraEl8xkuDbj4vbcLBqVktNNzeytqkaj+uL5ODbnJJVJPxbUAViNZnyRIKNzkzRWrl/Jm8tM1M3aCxYMzBNNJUjJMOtbYHxhitaqRqxGM8FomP7pkeV+eJ6Qn3gyQX15NUqFitf3n6HC6ljezzfvCWHQazEZi9fU2jU8S8Qf5fTXjy//3WPNkkf7aK9peqxZcp9ziOGZcdKZDCqFkkQqiUqhJJ3JMDxT2FL/TpBXYDc9Pc23vvUtvF4vlZWVnD59msuXL1NZufhN4N//+3+PUqnkG9/4xmMNigWhELc+vMfc+ALnfvlsSXp1JVMZ3v+sH61Wzbkzu/Mq5V8pYPjcOcm9+Xleb++gs7ywpqvhSIIboevEjCF2q/ZQpfxiW0OuveFyreI1GDUFzQ8tZPzZk9ZrveKvD1FvL05/uHQ2y0TAT29ZNcFAvODRWoNj8xgNWhpqSrMMm06lGbg6wq5DrSUZnbcRsixz55M+7p5/QENXHad/9hhavZZP7l3acICTzUrcfriXrsJh5quv7c5pCbDPOcR8wINCAbIM9yYHKa9q5bJriowkcbi2jkO1dU/1n8t1lmmxZqLm0nqlUJIkkUjF0Wt0eKNh5hYmGZlzkkglH8vG6TRaDDo9t8b6kGSZrvr2h4UTM7TXNi8fb3o2QH1NYWP2nnT/wiAVDeXL3Q0ea5bsdjE0O4ZGpaKpsn45wzjpmSGSiKLT6Ig8+rxSq4kkoji9s5tyfbervAK7H/zgB2vertfr+cM//EP+8A//sKCTEoQlzgEXfRcGOfz6/pwHnOdDkmTOXxkmlkjzldf2odcVlg28MzfL9RkXLza30FNZVdCxMlKGK/6r+GU/hzSHKVc+ndnIpTdcPlW8JrN2w/NDNzL+bCXrLR3Pu0PM+Dz0VBSneObu1ByzcyE6w3buTLryHg33qEQyzciEm33d9SVr4jp0fYx0Mk3PydIVZuQjGU/y+V9dXR5rtvdMNwqFoqAAJxCKcf7yML5AlIN7Gtnf3ZDT9VwKClLpNJOeacocDXz/wX3a/HGONjZzoqEJs1a7YhuNXGeZrhQsZKQMoUyYUDpEKB2mvMWMoV5JUkohyRIKhQIlSlQKJUaVkTJ9Ge6Uh3JtGWpl6SZ7KpVK3th/Gpd8gxPVFdyQ0tSVVaNSqnh9/2kqrGXLv9N6y5+xeApfMMq+7uJ1IliY8rAw6ealXzy1/Dp/tFnyyMNmySNzTiqsZcsZxhpbBV117TRVPr2/1OmepcZW8dwGdSBmxQrbWMgX5uIPr9LUXV+yD7Eb95xMz/p5/Ux3wfM8R31ePpkc51BtHQdrC2u8mpEyXPJeJpgNsFveizljgxUSbk8WNazk0UxaeYWKVCq73F9Oq1U9lUkrZH5oPuPPVrPe0rHCmiQeT2HMFF6ZFwom+OTuCLqkiopa03Igms9s20cNjMwhI7O7RCORspksDy4N0b6/BdMae8w2S8Ad5OPvXyAZT/HKL52m/pHWQBsJlJb60l25NYHJqOXtV/dSmUcfwKVs3UIkRFTrYCGSpFqO0GNSc66t47H7rbQHL9dK1JSUxpv04k568CS9BNJBQAYUmNUmDCo9ZUYHOqUOpUKJLMtISGSkDJFMlIn4JCOxEbRKLe3mVlpNrehVpcm+GnR6dBods343kiyzu6F9xTYm640dG5/yLs7DLWLD7bvnH2CrtNLYtfh++eiXgf7pEQLRp5slB6IhJGSqHRUkM08XYlU7KoinkyJjJwjbTTab5bO/vIzOqOOFrx4taup/yfiUh7sD0xzb30JDbWHLZu5olHdHh+lwlHOmqXn9H1iDJEtc9l0lkA7yUu0p3JFMQcubS5k093yY/ntzyJK8NCkJhVJBdZ01p0xarnIpVljLekvHUXUQZUKNTi6sFYQsywyMzjMdDfNyY8tyNjPf2baPnveDkTk6mqsK6qe2luGbYyQiCXpP7y7J8fPhHHDx+V9dwWw38dZvvop1hQ31+bTsSCbTfH59lIlpL11tNRw/0JJXI1x30Evf9AiueJrxtAqH0YIj5qFRpWPGM4U76F3eeL+RpsHRTIzZ+CyziTk8SR8yEgaVgUpdBa3mZmwaG1a1JacMnCzLhDJhxqMTDIVHuOW+SzKQ5c32V6mxF5bpf1I8nSaWjOEMuahboxhhvWKPcaeH+loHugJXNZa4p73MjMxx9psnl19fS18GZnzzqzRLPkN9+eJYx0J6/O10IrATtqVbH97HNxfgzd94FW0JPiRD4TifXxultbGC3q7CsmvxdJq/GRrAoTfwentHQQGSLMvc8N/Em/TyQsVJKnQVaJsSBS9vLh784f9duu/Sj0jySvcuSCFZv7WWjmVZZj4zS4WiEo2msLevWDTNDZcLq0FHi/nxwD6f2bZLBkbnSSbT7NtdnDFZT0qn0tz7tJ+2/c2PNXHdbLIsc++zfm5/dJ/mngZe+NpRAvEQ7936dMPzOhe8YT65NEQyleGVF7pobcx/b+pnQ/c4P7OAJxajQqOgQZUkqVOzEHKjUikf23ifa9PglJTGFXcxGXXiS/lRKpRU6irYb++lSl+JSWVa97W30rKvQqHAprFywL6PbksXf3Xv77jjvkNKmeQ3Dnwn54rvXMTSaRaCXioyyVUrk9cr9rg++IB5r7KofRk/f+cKrsQ8hrrHA3+DTs+UZ2aVZslf7PkrtMffTiYCO2HbmR6e5cHFQY68sZ+KuuI0jH1UJivx0cVB9DoNp4+2FxSISbLMT0aGyEgSb3fufqzCbiP6Qg+Yjrs46jhCpW7xw63Q5c2lPWuyQkH33urFpdiHbUi0WhVeTzyvzFSprVWEEZD9hJIxeq3785pgsZJIIslo1M+hmjrUK3y7z2e2bSaT5e6Ai/bmSqwlmgIxcGWEZDzF/pf2FO2Yq7WTWU0mneHSj68zfs/J/pf2sO/FHgCu337A5wPXkNIKfubo6ZyfR7Is0zc0y7U7E1SUmXnz5T1YTPl9YKeyWS44J3jfOUU6ncQUXaDc7iCeXFym80dCWA1mgvEI8373uk2DZVnGn/IzFp3AFZ8hK0tU66s4WnaEGn0VGmV+z7v1pieEIhECczGaaWYyOM2nrou83HAmr8dYy6h7Fl/Yz6G6xzOBq7U7eZLNZGF4wo1dXUdzfXHej+cn3dy71U+sPUX/9AjVji9asWynVjHPKhHYCdtKPJrg4g+v0tBZS/eJ0uyru3ZngkA4zpdf3Ye2wKzPpWknrlCIr3f3YC2wH+NkdJLh8Ah77b00GB/foFzI8uaje9aUSiV6/eNBTL6ZqVJbqwhjODqORWdid3NzwUFov9+NUqmgRb/yXr1c9i8uWcrW7X9kzmUxxSNx7n8+QOeR9qJVhq/VTmalLwvxSJyPf3AR/1yAs988ScueRkLBBPf6x/no6g3SWfjo8g2sUgV7u1vX/cKRTGX4/NoIE9Ne9nbVc3hvU97j16aCQT4YHyWWTvGVnv08GExgaW0BFMttPUBe7EHX1kv/9Miq+8jO9B5jOuZiNDpOIBXApDax29pFk6EBg3pjwXouy75fZBDbiMzHuDV/l1ZHEy2mwrZ0LLk1NYoym0arVq+YjXu03clKspLE3/y0n12tVUWZESvLMuf/5hJhdZzm3Q1PXZft1CrmWSUCO2HbkGWZK397A1mGk185UpLs0fSsnwfDsxw/2Eq5o7APSGcwwPUZFycbmmiwFraR35fycztwlxZTMx3mlXuTbXR5M9d2J/k0Di61lbKUkjpJ2hrkeN1hbPbCsmLxdJo+/wL7q2tJRyRkg7zh9izJZJrbD6bobKsuuABnNbc+vI9CqWD/Sz1FOd567WSeLBrxLwT5+Hufk81KvPFrL1FRX758jGvDfWQUaTrqmhldmOTaQB/arGHNwhNfIMqHFwZJJNOcO7Wb5ob8MjDpbJYLU05uz81Sb7Xys7u7uT18m3Q2g9Vo5oFzmJG5CTRKFT1Nu/BFgtwYuctswP1UJqjKXsbVuVu4zXOoNEqq9dWcLD9Otb4KpaKwfVrrLfs+mZ1qNTczGZjk8vw1GlsbCl6SzWazuMIhKo3GNSuTl9qdrGR4YoFMRmJ3e+EzrgEmH0wz8GAYyz4LzVUNj12X7dQq5lkmAjth25i478TZ7+LFnz+JwVz8D8h4IsWnV0doqHGwZ1dhY5hi6TTvjQ7TaLVxtK6w8v9kNslV3zVsGhv77HsLOtZK8ml3sp08maXsjz+gTnbQU9Wx/g+v4/qMCxQKzvV24BzwFrR/8e6AC0mSObhn5RF0hfLN+Rm9PcHRNw8UpW9dLpNIHl2anx2b5/yfX8RkM/LGt09jspmWjzHj8+DLzFFtr1gsxLFX4EvOMePzYHbqV1zeH3O6+ezqKFaznq++ti/vpev5SIT3RocJJZO82NzCgZpaZFleDgimPLMMz02gUigZnpvAYjRjM1nocw6hUKqWM0ESEgFFAL/Ghzflpyrg4Bu9b2PRFGf/Yi6zYleqRFXNapnxz7NQ66Y2xznQqwmmktRVNPB6awvNNvuK91mr0ECWZe72u2isKyvKGLF0Ks35H18kYU3Ts7sNePq6bLTljPAFEdgJ20I8muDqO7dp6W2kuac0H5CXbo4jyzJnjhVe4PDR+CiSLPN6+66Cj3U7cJesnOVY2ZGibppeUszGwZttKUsZzUSZj87QZeksuO9XIBHn9vwsR+saqC63YOjVbHj/YiAUo29oln3d9RgNxV/GlmWZq+/cxlJuZtfhtqIcM5dJJEtL87MjLi79+Dq1bdWc/eZJtA8rIpeOMZ+cIZ5OUm1bbO9i0ZvxRnzMJ2eo8pU9trwvSTLX705yb9BFe1Mlp4+25/VlQpJlrs+4uDw9RYXRyLd691FuNC6f91JA8NmDayTSKXbVNjM8O0l3Qwendh/h/buf4w378UWDRFVhguogkiKLKWumVW7Dka7ApCpeC5n12oestpeswVrLYGiQId8otfWLP7tSAUYuJgIB9Bot3dX1G9r/63T5CIRinDpSnAknDy4O4XTNYD5uXbWQI59KamFlIrATtoWrP7kFwNE3D5bk+JPTXsanPLx0orPgD+Bhn5cRn4+3dnViLnAE1XTcxUx8hmPlRzGqiztYe0mxGgdvpfvBB+iU2lWXqfNxfnICo0bL4Ye9Bje6f1GWZS7dHMdo0LJvd/Gatj5q7O4kC5NuXvuVF1E98cG80Q/7J5fmfVE/D2aG6KnrpMzkQKNREUonuPtpH8NXh+k41MrxLx167PEzmSzusI8pv5Ny8+Mb6svNZUz5ndTo68hkFjPjyVSGTy4N4ZoPcPxAK3s6a/N6vkVTKd4bHWYqFORwbT0nGxpRPZG1Mej0RBJRpryztFY1YNIbaa1qYMo7S0bK8PbhV5iOuRiIDBLJ6Diq30unqQOTejGYK2YmKJcCgLX2kqXDWUYWxnmx/hQAF/qv81dXfko8GedrJ97I+TwGPG6a7fYNBXWyLHPz/hR1VTZqKgufoRz2R7jy4U2kepnWxsdXTERhRHGJwE7YcpP900z2TXHm505gyLMiLhfJVIaLN8dorCujramwEV/xdJqPJ8bYVVZe8LiweDbOncBdGoz11BtK0yJjSTEaB28Vd9LNTHyGw2WHCs7Wjfl9jPv9fGlX12MfdhvZvzg+5WFmPsDrZ3pKsoydSqS4+f5dWnobV5y6sl615WqeXJofWRjnnusBWrWGY60Oksk049eHyIRCHH19H/te7HkqCFOrVUwFnARiEWxGK/FU/IvblCoCsQhTASdq9T6CD+cwxxJp3jjbQ32eDW4nAwHeGx1GoYCf3d1D0ypLikvXZKUs2fXJO1jrDMwnFqg0VHDWdgq7Nr/zyMd6BQD3JgcJxSOr7iUz6QxEU3EkScIb9nO+7wresI/zfVc41X0kp+DHHYuyEI1yvH5jBT3jUx58wShvv1qc7SHX3r2NPxFEs0eHWqUqWmHERr/g7GQisBO2VCqZ5upPbtHQVUdLifYo3bzvJJ3OcupwW8FZqYtTTiRZ5qWW1px/ZrWWEn3BBygVSvbb9xV0TrkqtHHwVkhLaW76b1OuK6fRUFjFaTKT4aPxMVrsdjrKCmvbkEymuXxrgpaGchrrSjMT9vp7d8iksxx+ff9Tt220yS48vjSvNIYY80xgM1gY80zQ6mjkwfsjxH0BvvRrL9K1yhKc3qBC1mbQSDpC8dAXvREBZBmNpANtBn84wieXhzHoNHzltX15FZfIsswV1zRXXFM0We283t6BaY0M+UpZMkmWUJfJfOa7yGHLPk7WHKNWX1PS53wuBQDhRJTX9p0mI2VWPMbN4G1khYxSqeRC/3Um3TM0ltcy6Z7hQv/1nLJ29xfmMWo0tNjzf35msxI370/RWOuguqLwbN1k/zRTAy4qD1eStKeLWhix0S84O5kI7IQtdff8A1KJFMfePFiSN1uPP0L/yBxH9jVjMha28XwuEua+e56XmlvX/IB51GotJYy1MlOJaQ46DqBVbl6LkUIaB2+F+8E+UlKK0xUvFPz8+Mw5QSqb5ZXWwnoXAly5PUE2K3HyUHH2vT3JNTLLyK1xTn7lCCbr00v0+TTZfdKjS/MXhm4TjsVor2pmeGacv/nTn1KJgy//5st0HVn9d1OpVHzz5dd5cG+aWDyLxapdXt4Ph1IY29UY7QY++HyQ6goLr7zQldfEgkQmzbsjI0wG/ZxsaOJoXf26/2ZPZsmiRFlQzpNRZVAFtTjC5dS1FlY09aRcZs56Qj7uTPSzv6WbCuviFwqdRodeu8b7URRsaivuoJfzfVfQa3RU2soJxaI5Ze3i6TQP3Ascqql7ask6F/2jc4QiCV55oSvvn31SIpbkyt/eoKm7geNfO0Q6+/QYsCX5LocX8gVnJxOlJcKWCbiD9F8eYu+Z7qL15nqULMtcujGG3WoouApWlmXOT4xTYTSxtzq3SrWldhAL8xH0Rg1l5Ub0Rg3z82E+GbqMLmukyViaLOVOMBefYyI6Sa91z/I+qI2aCPi5v7DAmeaWVfsNuoNe3rv1Ke6gd81jTc34GZ5Y4PiBlpIUTKSSaS7/zQ1q26rpOPh0Zni1asv1zvtRVpue8iYt/uwCVo2VgDdG8mYUv2eBl3/1GD1H1w9YqyvtHD7cQVtTNRpJRzqqRCPpaG2sQmPUcX9olvbmSl4/24NOp8n5+rqjUb5//x5zkTBf7ermWH3DukHdo1kyT9TPSGqUkewIqWQGW6ScOk0d4UQMSZJyvka5WMoW9TmHHvt7g06PzWTFZrJyb3KQH179gHuTg8t/t1ZQJ8sykUwEs8a8nK2redjAt8ZRuZy1W8u9hXlkGfbX5P++l0imuXV/iq62asqK8L587d3bSJLM8S8dwqg3LF+Dlf6sGeyuYOkLTlNlPdFE/Kl/h+eVyNgJW+bm+3cx2YzsKcK3wpWMT3lZ8IZ586U9eTc+fdKo38dsJMI3uvegzCHbs1ZLCU1FCl84QEdgF4qm7bsMupWimSjX/TepMdQU3Kg1mkrx09ERWux2eitXn8OZy5JOPJHis2uLLXN2tRZ3pueSGz+9QzKe4sSXD68Y0KxXbZkrZ2ASS5maOkMtg+8NU242Y3ipgpg1kvMxnlzeVyqV3B5wMjSxwJG9zezr/iLTlsv1HfF5eW90GIfewDe6e7DmWB25PGM0Nsud0D2qZSvd5i4a9F88frHbZOSSLVrKuOWzPy6UCZOW0mQT0nK2zqRfXMI26Q3oNbo1j5XMZLg5O0NPZRVGTf6V7tfuTAJwqLfwL53OARfjdyc59bPHMBa5x2Mu7WSeVyJjJ2wJ18gs00OzHDq3D1UJNp5nshLX707SWFdGXbW9oGNJsszFKSfNNjuNttwaEa/VUmJGdlKms6EIGIhFV1+WeF5lpAxXfNfQKjUcdhS2RC/LMj8dHUGhYM3WNE9+SK+UVZJlmc+vjRalZc5qXCOzDN8Y4/Dr+7E4zKue52rVlrlm7ZZ/X42NsQ9HUcoy+362m5b2xryzf0vL+yazlst3xhiZcHP22C7293yRaVvv+sqyzFXXNH87NEir3cE3e3pzDuoAsnKW4fgId6J3qTSW86WGN+it6MFutm04G7SeXLJFK+2PW89MfBa1QsPA6BjjC9M4zDYS6eTyH4fZxvjC9KrHujk7Q0aSNtRfc3YhyND4PMcOtGAocEb30hJsQ2ctbfuKM0XjUUvX/9G2KSJrt0gEdsKmkySJ6+/dobqlkuYSjWAaGpsnEktydF9T4cfyevDF45xszP0b7FJLiSdH8ETlCH7JS5O6hUxG3lbTHjabLMtEIymCgTjRSApZlpFlmRv+W0QyEY6XHyt4/+G1GRfOUIA32netmb3I5UN6YHQO54yPM0c7SrIEG48muPij69S2V9O5Ss+6pX1kS1WFS38erSrMRZ9zCM+cj7H3xglGQkR2JwjK4byPsySZyvDu+QfMzAc5d7r7qWzmWtc3I0m8NzrCxSknJxoaebOjM6/2HJFMhE8WPmMsOs5eWy+nK14oWeugJbkshz+5P24p07ZS0Ly0TL0Q8OCKz1Ctq+SBcxhkSKQT+MKB5T+JdALkxWv65NJyJJXi5tws+2tqsOQ54jCTlbh4Y4zqciudBWajZVnmyt/dJJvJcuLLxZ8iVKwvODuVWIoVNt3o7QmC7hCnv/5aSbIemazE3f7FgewOW2F7RGRZ5sbsDC12OzXm3DvSrzbtYUGaRaPQYs2Uk1Jnt920h82yUlGJzWEgWD7DHDMcLzuGTVPYmLYxv49L006O1zeu2SIjlyUdjy/ClVsT9HTU0lSkQeiPkmWZiz+8hpSVeOGrR1d8XWxk3NJKm/slSWJ2xo3/og+lWklqT5Zxr5OMJktnfVve1YnxRIr3zj8gEkvy1st7qCx//HWy1vW1mmz8zdAAc5EIb+7qpCvPFkKu+Aw3fLfRqbS8VHkWu7aw50yuclkOX8rWtVQtfnmtcVQy8TDT9mRV69IydUqZIF0eZ4+lm1118xh1qweojZVPt0i6MDWJWqnYULbudt8U4UiCV17fV/D78sit8eUWVsVeggUxT3Y9IrATNlUmneHOJ3209DZSXluaNhHD4/PEEin2dxfeNHY6FMIdjXKmO78ZnStNe5BlCbc8TzlVRELpbTvtodRWm1N63zvIQnSSF1tPUGcorNjFF4/x7sgwbY6ydft4rfchnUxl+OjiIA6bkaMHWgo6r9X0Xx7CNTzLK790ZsUqWHi62nIlT+4jW2lfW8gbRr6V5lj3Afa+vZv3HnxOY30dKqWK1/efpsJalvN+tEg0yXvn+0ims3zpld4Vv0itdn2vjT3Aq7IQTaX42e4e6i25t9WQZIm+YD/DkRHqDXUcchxAo9yc11IuzYeBnPfHPbpMfdtznz22XdQYqvnK0XN5/Vu7wiH63W7OtbWjV+d3LdzeMHcHXBza01jwl+GgJ8TVd26x63Abrb2Fr5g8ScyTXZ8I7IRNNXRjjHgkwYGXe0ty/OzDbF1bYwX2VT4g83FrboYKo5FGa36ZgJWmPcTUYWKZOFVh6zMx7aEUVisq8Wnm8VunKQ/Vo3bbkKvlDV+beDrN3wwNYNZqeb1t7b1w631I9zTu4s49N8lUhp95aQ/qAotwVuKZ8XHzg3t0n+ykYZ3q7XzGLa20uV+b1vD+H5/HYjNz7lde5MrYLSRZZndDO4OucaY8s7TXtuR0/FAkwbuf9AHw9iu9K858Xe36WswO/nLgAQdauvnlA0coM+T+Wk1Jaa56r+NOethn66XdXHh/ynzkki0KREOML0xTX1ZDIp1cvs+j++OWsnZLgW9zXS3joTGyARlFiyKvf+uMJPHR+Bg1ZjN71igQWkk6neXTK8OU203s6y5sa0w2k+XTv7yMyWbk6M8cKOhYq9nIF5znjQjshE2TzWZ5cHGQ1r1NWMuLM2j7SRPTXiKxJK8VIVsXTaWYCAR4saV1Qx8cT057mJbnQKOkpbKGhuaybT3toVRWKiqZkaYYyw5Rp2yk3tS6PKd0I/320tksPx4aIJHJ8At79qJTr/0Wt96H9N+cv4YiaeO1091YzSWYihJP8umfX6Ksxs6hInX4X/Jkr7vr9+4QuRJFZ9Rx7ldeJJKJbriqMBSO884nfSiVSt58aQ9m08r7uVa6vsFUhjuBCJlUkl16ZV5BXTgd4bL3KkkpyamKE1TpK3P+2WLIJVsUiIa4OzmwvD8ukU48fqeH++O+cuw1vGH/8r/BAgvYdTbccwHcQW9elZ3XXNP443G+tTf/ZdQrt8eJxFJ89fV9KJWFBcjX37tNyBPmzd94BbWmdOGFmCe7NhHYCZtm7M4k8XCC3tO7S3J8WZa5PzhDfbW9KP2XBrxuFAroKt946fyj7SAiPifVqha66/Kbk7mTPDmndFqaZCI7Qr2ymRZlO7IWIuHUhopKpIcVsJ5YlK/v3oNdv/benvU+pOWknsFJD99+o7ck0yVkWebCD6+RSqZ5/X97qajV4U9myhwqK+9/91MO7erl7V85h8Gk58q9WxtqmxIMx/nJx/fRqlW8+XLvqoUkK13fYDpLfyiBUa3kSKWDVDqe85KZJ+nlsvcqOqWOFyvPYNE8XTVcarlkizQqDclMGrN+9fegpf1xS8F3WZmVkBykSdfIgjeQ1x6xhWiEazMujtU3UGnM731vYtrL4Ng8p460F7zCMdE3xeC1UY6/fZiymtJssxFyIwI7YVNIksT9zwdo3F2HvbI0G5zdvggef4TXz+S3H241gx4PbfayvPerPGmpHUQyFKPRXPjUg2fZUlFJKpVhTjPJtDRJo7KFJuXicloqlUGjVuZdVCLLMh+PjzHi9/Llzt3UWtbPCK/1Ie3xRfng80EOH61kf4kqt++ef4BraJaXv3266A26H93XloqmmPlkhrScpfJMJQazIad9YitljELhOO983IdWo+bNl/asWR385PV1hUO8MzrKa40mfqatHY1KlfOS2Wx8jiu+65RrHbSr27l4/+aWzQbNJVuUy/64pWxdtb2cGVwYFAbs2FHa1TlnTlPZLO+ODFNuNOZdMBGKJPjs6ggtDeV0rTCLOB/++QAXfniVlt7GVSu6hc3z/C5CC5tqasBF2BcpWbYOFlucmI26vIeMryScTLIQjdJe4EzRJRkpQ1pKl7wNw3pWajGymYwmDVaHjruxu0xJk7SqdtGsan9YXCITCiYXR67lUVQiyzKfOSe5tzDPa20dtDly/zd7dELA0h+FrOXKjSnqK8t55eTukgTizgEXdz7pY//Le9bdV5evR4O2dCJN/0+GkGWZg1/tZSwwhTvo3VDblFAkwTuf9KFWK9cN6pYsXd9gRuIj5zTt5ZX8wt6DVFgdOfeWm4w6uey9Rq2+mhcqTjA0Pb7itIcnr0EuUy5KZaXn1ZMTFpb+DULqAJF0BHuyjFgynlfLmU8nxwmnkrzZsSuv0WGZrMTHFwfRadWcPlpYT8ZUIsX5P7+EtdzCya8Uv7WJkD+RsRNKTpZl+i4OUd1SSUV9ab5hp9NZxpweejvrCt4nAjAe8KNUKGix2ws/OSCRXdxnY1AVv/Q/V6vNra1vsm/afr+klGTaNkg86qcuuIsKSx2SRiadzhIKJvMuKpFlmcvTU9ycneHlllZ68tw4/qREMs37nz5Aq1Vz7szukrSjCbiDXPjrqzT3NLD3THfRj78UMFg1Ju7+XR+paJrON9vR2/QsLPi4NzlIKB7Jq6owFk/x7iN76vLp4zcVDPLjwQEarDbe7uxCnUcAMhoZ407gHi2mZg7Y9+EN+bk2cpc5v4drI3dXzWpt98HwS8vUBrMWV2YGS8ZGPJMizmKWL5fKzkGvh/sLC7za1p7XPkWAyzfH8QdjvH1uLzrtxsOApe0EiWiCt37rHBrt81flvx2JwE4oOY/Lh2fayyvfPl2yx5ia9ZHOZOko0pinqWCQGrO54GXYJWl5ccKERrE1L7nVWowszEeIhBJ09daUPLjzpfxc9V5F0sp8addrRGZlFmYjpFIZtFo1VbVmGpocOZ+HLMtcmHJyfcbF6abmDc3FfFQ6neX9z/pJpDJ8+dW96PMYWp+reDTBR9/7HKPVwMlV+tUVYilgsOhN3Hunn4Q3QdNrTcQ1KeLRFDaThXAiymv7TpORMqse59El0mQyzbvn+5Akmbdf7cVkzL3x7Uw4xI+HBqi3WPMO6sYi49wJ3KPD3M5e2x4UCgV9ziHG5qcIxcOMzUsr7kV7FgbDK5VKXt33Ah+7z9OuqOcFx3FUise/RKy1TO2JxfhgbJSuioo1x+StZGB0jsGxOU4f7aBihekm+bj10X2mB2d4+VunsJaVpiBOyJ8I7ISSG7o+itluoq6jpmSPMT7lpbLMUrTKxdlImK6K/JqlrkX1MKDLysUdQp6LtebWVlSq8LhjuJwBLL3VJVlGkWWZseg494N92DQ2jpcfJR1REJH9gMziYrAMeawKy7LMp5MT3Jqb5cXmFg7WPt2sNR/ZrMSHFwbwB2O89fLKrTsKlUln+OQHF8ims7z+qy+hLUHgqFQqeW3fac7/xUX0JhV7f6GH6cw8+1u6qbAubmjXaXQ5j9dKp7P89LN+4ok0X3qld9Xq15UaIbujUX402E+VybSBoG6C24G7jwV17qCXayN3iacSWPQm4qnEilm7J6uBN9qsdqXfqZiGEyPIKpkXq05h0eQeFCUzGf5ueACrTserrfnt2V3whrl8c5zujpqC99WN35vk/mf9HH59Pw2dhb3+hOISe+yEkkrGk0zcn2LX4baS9RVKp7NMzwZoaSzOm284mSSSSlGXx6SJ9Sx9G8/Iq2dJSmWtubUKhQKrTbfcYqTYUlKKq77r3A3co9XUwtnK06QjCgbvz+FeiGJzGKhvsGFzGHAvRBm8P0comFjzmJIs89HEGLfmZnm5ta3goE6SZD69OsycO8S507upKCt+teXSkpVvLsDL3zpV9GKJRx/n/scDeCf8vP7tl4jpE/RNDTHlmcl7Zmo2K/HRxUECoThvvNizZtXkhf7r/NmnP1qeXxpMJPjh4APsegNf6dyd14iwqdg0twN3aTe3LQd1wHK2TqlQUmkrR6lQMjY/9dhetFxGfeVqaTm3FLNHxyLjTEQn2W/fl1dQJ8ky74wME0uneXtXF9o8rms4muCDzweoKDNz/EDrRk572cKUh4s/uk77gRZ6TnYWdCyh+ERgJ5TURN80UlaivUQd+wFm3UEy2SxNRWpJ4Y0v9tuqNBXvw1en1KJQKIhlYuvfuchWm1u7RKNRkc5IRZ9bO59Y4KP5j/Ek3RwvP8o++14UKB7LHup0apRKxcPsoZFYPIPLGVi1qCOdzfJ3w4P0LSzwWls7+6sLywJLksxn10aYmPLy0slO6qrtBR1vNTc/uIvzwTSnv368ZPtMAfouDDB4dYRjbx1CX6N/bEkyn+BGlmUu3hhjZj7AKy90rblktzQT1Rv2cb7vCk7PHD8cfIBWpeKrXd3r9hJ81Hxigeu+WzQZG9ln610O6h7N1tlNixMq7CbrctZu6Xcr1mD4J5dzi1mEsZBwcydwn3ZzGy2m/CYzfDY5gTMY4K2OLhyG3LPKyVSG9z/rR61S8uqpLlQFNNqOBKJ88oMLlNc5OPH2YVEssQ2JwE4oqfF7TmraqkoyL3CJazaAxaTHVqTHCCYSqJQKzDlmNnKhVqqxqC3404GiHTPnx35kbu1K0unshlqMrCYlpbnpv81FzyXMGguvVL9MnWExq1ZI9jCRSfNXAw9wBgO83dnFnqrClpJkWebC9VFGJ928eGIXLQ2lCbgGrg7Td2GQw2/sp7nAzv5rGbs7yc0P7rHvxR66jrQvBzlNlfV5Bze3H0wzND7P6WMd61aZL81EbSyvZcI9w3+6+DGpbJavdfVg1OS+3BxIBbnivUa1vopDjv2PPT/6nEMMz0yQyWZRqZQk0klUKiWZbJbhmQn6nEOPZeuC0TA3x+4TjIY3lLUr5NqtJZQOc9V3nUpdBXtte3L+OXfQy3/99B0uTI7yYnMLzXkUdWWzEp9cGiIaS/H62W4M+vwbfy9JJVJ8/P3PUWvUvPgLLxS196JQPCKwE0omGoyyMOmmbV9zSR/HNR+gvqZ447mCySRWnQ5lkb+JlmvL8CQ9W9JixF5mJBRMPvXYG20xspqZ+CwfzX+EK+7igH0/p8pPPlYJvNHsYTCR4M/77hNIxPn67j15tTRZiSQtBnXDEwucPbaLtqbSTDCY7J/m2ju36T7ZSc+J0i1ZLUx5uPTjxaWx/S/tKWhJcnTSzc37Tg71NrGrZe2N+UvZOr1GR4W1nJjWzl3XBKdqa7Dpc9/vmsgmuOS9AhkFAWcMb8i/fJskSTg9M4QTETQqFe6gjwdTI7iDPjQqFeFEhCnPDPcmB5dbuAy6xuibHGbQNZZX+5Cl36lYy7mPimfiXPBcQq/Sc6z8CEpF7h+/H/Tf5t2RASxyKq8ioaUvL7MLQV55oaugJsTZTJaPf3CBaDDGy98+jcEkJj9sVyKwE0pmst+FUqWkcXfh471WE0+kCIbj1FblPkB8PYlMGkORqmEfVW+sI5qJspB0F/3Ya1maW2s0qPG4YySTGSRJJpnM4HHHijK3NpKOcMlzmSveq1g1Nl6teplWc8tTx9xI9nA6FOQHfXeRZJmf79mbU/PhtUiSzGdXhxkaX+DMsQ46WkoT1M2MzvHZX16meU8DR17fX5LHgJWXxja6JDnvCfHZtRE6Wqo4kENj5qVsXY2jkoU0KA12CM0yNPkg5/PPylkue68iI6MPmrgxcu+x81QqlVTbKuiqa+dMz1GqrGVoVWqqrGWc6TlKV107lday5RYuTs8sI3MTKJQKRuYmcHpmH2sfsp5iLec+KplN8rnnEgCnyk+gVeb+/nLPNck7o8M0mE2o4t68Asxb96cYnljg9NH1M69rkWWZiz+6hmfaxyvfPo2jqjRN5oXiEFWxQslM9k1R11GTV/WfLMvEomkymSxqtQqjSbP2EHdfBICKIpbap7MSGmXxlxgqtBXYtXaGIyNU64vTliVXT86tDWeSaNRKqqrNBfWxS0lpBsODjEXGH2YijlKnX31k2lL2cGE+QkWl6rH7LWUPq6rNy9nDO/NznJ8Yp8Fq5a1dnQW3n8lmJT65PITT5eOlE520NRWv8vlR7mkvH//gArVt1Zz62WMl24eUSqYXl8a0XyyNbXSqRDSW5MPPB6gsM3PqyPrVlo9m6zJqA/NJaDRqiMQUnO+7wqnuIzlVk94L9BFIh9ij6+GDmYtPtSmRJIl4Okm1owJPOMCUdxatRsuUd5YKWznVjgqS2cxyC5fPHlwjlU7RUdvMyOwkPQ0dnOk5mtOUi41eu7WkpBQXPJdJSSnOVp7GoM59y8hCNMJ3b11FK2d5paWdkYfLzrlU+T4YnuXWgymO7Gsu6MuLLMtcf+82E/enOPvNE1SVKLstFI8I7ISSiIXjuKe8nPrZYzn/zEYa6Hq8EQw6DZZV2jBsRFqSUBWhyfGTFAoFu8wdXPNdZz6x8Fhwl29AuxGPzq0t9HEyUobx6ATDkREycoYuSycd5nbUyrXfUpayh5FQAo97ca+d5mFPvUcbFGdlmU/GR7m/sMCBmlrONrcUvDSeTmf58MIAc+4Qr57aTVN9caaKPMk35+fDP/uM8loHL/78SVR5VC7mQ5ZlLvz1VSKBGD/z668sL40tNSh2mKxEE18U6zy6JPlkYJB5WAGrUil55YUu1Dlsrr/Qf53xhWkqHbWMxzOYlDJWWUJjtjG+MM2F/ut87cQbax5jJj7LWHScA/Z9OMfnVmxT8uhosrWCNr1WhzvoZco7S0tVAya9kZaqBqa8s6QyaWym9bP6G7l2a0lJKT73XCKWjXGm8oW85tt6YjH+9PZ1whE/p+tqUSkUOQeYIxNuLt0co7ezjn0Frpjc+6yf/svDHP/SIZp7Ggs6lrA5RGAnlIRreBaFQkFDZ277QTbaQDcQjuOwGYsaBGmUSlLZ4laILqk31DGpr+SG/yavVL2EXqXf1IkQS3NrNyojZZiITjAUGSElpWgyNtFt7cprosZ62UNJJ/PnfffwxeO81tZecJEELC7Z//TTfkKRBK+f7S5Z9at/PsD73/0Ui8PEK98+jVpTurfY2x9/0Rx2aWlsqUFxPlMlAC7fHMMbiPKll3tz2lwvSRL3nYPIMkylQSZGBXH8yYd3kBeDpK8ce23VLFk8m+Cm/za1hlrMGQv9rgtP7WtbCmAMOj2RRHTdoO3RGblLv+9cwJNTQLbRa7eaZDbJBe9lYpkYpytewKbJffnSH4/zw4EHBMN+WrSgViq4OXaf9urm5WXh1X4fp8vHZ1eH6Wyt5tiBp7dD5GPw2gi3P7rP/pf30HW0Y8PHETaXCOyEkpgZmaOioQydYf1MWiENdEPhOJXlxe14rlWpCKeSJcmiKRQKjjgO89HCJ1z33aBXc5DhvoUtnQiRi2Q2yXh0grHo+HJA12XZhUm9sZYwq2UPh31ePhgaxajR8At79hal5UwokuCnnz4glc7y5st7Cu62vxr/QpCf/vF5TDYj575zFm0B1YfrmR6a4d6n/Rw6t/ex5rCPZrdW8+SS5NDYPINj85w9tiuv19KuujYWshrcqSx7LFqMT2T5GitX7y8oyzK3/XdQKJQcsu/n0oOb6wZk6wVthS6jbuTarSaWiS0vv56uOIldm3tQ54vH+Kv+B6RSCcqkMOVllTg9LoZmxtGo1DRV1K/6+0zN+Pno4iBN9WU5LaevZezuJFd/covuE7vYd7Znw8cRNp8I7ISik2WZ2bF5unOsAsynBcaT2aZQJEF7c3H3fOg1avwLcQbuz5cki6ZT6ThSdpjP3Rf4YPozHPEmaiptmzIRIt9gNZAKMh4dxxmbQqFQ0GRsZJe5Y8MB3aMezR6mslk+Gh/j3sI8neXlvNranlf/s9UseMN88Fk/Go2at1/dW7TJJE/yLwR5/48/wWg18NqvnM3pC81GhbxhPv+rKzTurmfPqd1P3W7Q6THocvs9fYEol26O09VWza48xvEplUp6Ow4zIZv4xcYm9lQ+/RpcKwiajs8wm5jjePlRQpHIugEZsHyfB84R3rv9KW8cOEt9efXyfYqxjJrPtVtNKB3mgucSChScrTyd1/KrNxbjrwb60KnUNOjgdjxKTKVmdM6JVqVhdM5JhaVsxd/HNRfgw4sD1NfYeelEZ0Ezs6cGXVz44VXaD7Rw5I0DolfdM0YEdkLRBRaCpBJpqnPcsLvUAsOyRguMcCb5VAuMxZ/LFtSXaSW6jIrxaS+ddgdldkNJsmiVugoOGA7zTuw8QWsQE3uxYl++fb2AdiNyXfJNSSmmYy4mY04CqQB6lZ7d1i5ajM3oVMUPWGbDYd4bHSaaTvFqWzu9lVVF+SAZc3r49OowFQ4zr57qKvrzZIlvzs/73/30YVD3YkmDukw6wyf/6yJ6s55TXyts1mwmk+Xji4NYzXpOHMxvEkE0leJz1xQ91bWcbG7L6zzSUpq7gXvUG+qoN9TxycildQMyYPk+H975nHvOQdQKJX/vtZ8nGA1zb2KAUCJatGXUXD05dsyd9HDFew29Ss+pipMYVLm/TyxEI/xwoB+jRsPXurr54PZ5bCYL/dMj+CMhqu0VzAc89E+P0Fnf9tjv45oL8P7n/dRV2Xj5hcIaEM+MzvHpX1ymaXc9J74sGhA/i0RgJxTdgtODQqmgIsfN6Y+2wNDpnn5KrtZAN55cbGKrX+FnNkqWZZK+NOm0hMamXD6fUmTRylTldCb2s6Af5172Js3KNuoUjSgfjh97MqAtZGl4vT2MbT3lxHRBZuIzzCXmkZGp1ldzvPwYNfrqvHpu5SorSVxxTXNtZppqk5mvdnXn1U1/NbIsc7ffxfV7k7Q3VXL6WEdOxQAb4Z318/53z2NxmDj3ndJm6gCu/uQWYX+Et37zXMFLvVfvTBCOJfnqa/vzbk79ycQ4ChR5zyoFGImMkZYz7LXtyWlfWyAaQkLGZrJwfeQegzNj6DVaBmfGuD5yj/baZsLJ2HJV7GpyXUbNx9LYMZ1aQ3NbLbf996jUlXOs/AhaZe7/Pq5QiB8N9lNmMPDVrm4MGg1vHDjLjG+OeDJBd0MHVqOZUCxCJBHj9f2nqS+vRalU4pzx8dGFQeqqbbxyandBz/XZsXk+/v4FatuqOP314yUbAymUlgjshKJzT3spq7HnvHE83xYYS1KpxYBHpy3e0zgWTUNEwmBQ40nGqdB/seRY7CyaWq3CpDbSld3HnMbJSGqYcWmCamUdTdomFGn1ckBbSIHFSnsYZVkmo02QKvcxGpzlzniMsiojZVoHPdZuGo0N6PPINuRrLhLmg7FRfPE4J+obOVrfUJSG0JlMls+vjTLqdHOwp5GDvY0lyzgsON18+GefY6uwlHxPHSzueRq5Nc4LXz1acB8xp8tH/8gcLxxuI0Oc925dz3nY/bDXy7DPy1u7OvOaLAGLezWHw6O0mVowqheb5eayr02WZVKZFL/zR/8v9Dodexo76ZsaIhAL8e0zX1muit1MS3v6HGYrF+evMmWoZm95D/vsvXl9ERrz+/jJ8BC1Fgtv7+pa3oJg0OmZ8swiyTK1ZYvL5Ca9kUHXOFOeWdprW5ic9vLxpSEaah28fLKzoEzd3MQCH33/c2paq3jx58VUiWeZCOyEovPPBajIYzxTri0wnvyAXpqioChia5JMJouchVqjBVc8xG7b4/t+NpJFW+0+SwHt1IQflVyOI6bGp51jwDDMiHYEq+SgvaqRQNKCayBCPJ7dUIFFLJrG6wshWxO4ZC8RKURQ9pOWUygVSgxGC6ZII6fa91JpsxftWq4kmclweXqK2/OzVBpN/GLvXqpMxSlmCEcTfPj5AP9/9v4zOK4EP+9Gf+eczrkbOYMgCBCBcTgzDJM4w9mZzdKuJCs4ybItV9kuWfIHlarsuiWXq+y6X17XteT76sp+fW+9trSWrNWutGF2JwcOhzmCJHLO3egcT7ofmsAQRHejATQwJOf8qmZ3Bt04fTqhn/6H54nGM5w91b1rHnUAsyPzfPC/PqW6KcDZX3thS16N2yEeTnDxx9fYd7htx7nLmazMJ5dHaG0McHB/PT+8+HO+f/HnpLPpTe1JsorCh5Pj7A8EOBDYmp/bcjTET0bexewT6Ko/sPbzcufaro3e4cbYXZoC9ZhNZpoC9dwYu8udySHO9J7Y0rncmx7h+xff4jvPv0lPy/a2PQemhohlE9gbRFZiKxxI7ONo5+EtHeP20iLvjY+y3x/gzc4uTA9VyDZbBnEK1dy5u0xbcxUvP39gR6JufmyR9/78E2pbqnnFiAp74jGEnUFFURWVyHKMrhP7t/R72zHQXRN2VE7YrbaF60UXt+KLZFUFq/T52+ThtnA5VbTNruPx2YispEgkc/gDdto5QDraykx2hrg3zqx5gtHJIXIq1AeqiAsOrNiwmq1I1RKLoQzaRIYDB2tRdBVFl5E1mayWI6kkSaopgvEIE+IidtGMpEm4cFMnNOATA7gFL4IoshJPYdF3r+Kh6zrjkTDvT4yTUWRebG3naH1DxWLbZhcifPDZEGaTxDfPHSLg2/lyRzEm707z8V9dpHF/HS/98qldtTQBUFWVj//3Z1gdFp7/2rEdVyAvXBtD03XOnNhPMLbChwMXCcVXyjIVvjQ3Q1ZVeLlt6zYatyfvc2P5NsekfmzbmNX8849/QDKXZn9DPqKwxlvFfGSZP//4BxuE3aOzb4/ys+sf8N6tT3FabNsSdsvRENfn75CrSiBho9vcRXAhxnI0VFbVU9d1LsxMc2l2hiP19fT68rODD59vqWWQyakI88PXeP35ZzhzYv+OFiVmR+b54HufUtdeY4i6pwRD2BlUlHg4ga7p+LbRKtqqge5qpa6cmKByWctVnc+3hkYTYXq9+SWQh9vCiqIyNLBY0qYEKDnX1tVXRyySwRtw4PXbSCRkUskcoiTR4+8EQaQqYWM5HSJrTyALacJ6kKyeQdPz91lxa4wlNCZmPVgsn/9BNokmnCYnTslJs70JSfcR0Pz4zB6ER9pE2ZxScIaxUoRSKT6anGAyGqHd5+PVfX14drh5uIqm6dy8N8P1gen84PipLqy7WD27f2mYyz+9QXt/C6d/4dldMx9+mJvvDxCaD/PV33p1x+3eyZkQY1NBXjnZhcNu4ec385FgLVUNTC7PlTQVDqfT3FiY5/mmli0/f8vRENcWbmO1moksJssWQKucv3uFz4Zu0uBbv5DV4Kvhs6GbnL97ZZ24e3j27dFN2HvTI1wcvkmV28/F4Zvcmx7ZkrjTdI13xj9kVpyhzdJME82YHWYGw+Nlbd7Kqso746MMBoO80NrGMw2NfHjns3XnW2z2UNd1lhdkossS3ftNnH5m3463Xz/8iws07q8z2q9PEYawM6go8QcRX+7A9tprWzHQXZ2tyxXIHd3uosHDbeFA0s7AyhIHXAE0RV9rCze2eJmbjpb03ZuZDINAyeuMDYdIJ7PU1ruwWCSyWQVV0ZFMAlariVxOJRxMYdHdtHgb1/6A67qOgoyKiipqrCSS9HrqCfhcmAQTZtG8bsZH13XuLy+ytJiAmo1t4mIzjDslqyhcnJ3hxsI8bquVb3Z10+EPVGzmLZ3J8cFnw8wvRTna08zRvpYdfciVQtd1rr93hzsf36PnVBcnvnJkT7YFl6aDDJwf5Oir/VQ3ba31+SiyrPLZ9XFaGvx0tFaviwSr8VYRSyVLVu0uzEzhMFs43lDcn64YA1NDhLUwDc46clF1ywkOf/7xD4ilE1R7AixFQsTScTx2N1azhVg6sa5qt9rCfDSabJWfXf+AeCbFsX29XB+/y8+uf1C2sEsqSd6b/Yjbkbu0WJpp4/PKZTl+eYlcjh8N3SeUTvG1A110VVUXPd9HZw81TefKrWkILvHam40809++oy8W47cn+eSvL9HS3ciLv3RyT76kGOwNhrAzqCjxcBLJJGHfJb+wh1kVdtmcvO7nO01yWG0LqyPwv0cGuDE7T5e7aq0tLEnipr57SwtxQMDrtxW9zkowia7reHx2BEHAZlsvrMxmCU3XEQRh3cawIAiYsWAmL548kkjA5sdpKiyItzvDuF0UTePW4gKX52ZQNI2TzS0cb2hcNz+0U+YWI3x4cRhd03njpd4dBZxvhqqqfPa3Vxm9McEzXzlC3+nuXbuth1FkhU9/cJmqRj99Z7Z3mw+3JMfGYmSyCieP5+1Jzt/LV+vaa5sBqPfXMFEkCmwpmWAoFOJcx/4tP4/L0RADs8NYXBIevJh91qICqFALNZfLMR8J4bG7CMZWiKeTxDMpEukUbrsTj93FQnSFXC6HxWJZMzJ+NJoMHqrWuXyMLkxS5fKVVbXTdZ3J1BS3IneYCs1hi7ipq6ojlU2vXWczv7zFRIK/HboPwC/19FPnyn/5HZgaYikSBARAX/v9h2cPFVXjw8+GmJ6N8erpXg7ur9/Sc/AoQ1dHufija3QcaePUt04Y269PGYawe4zZi/zQSpOOp3F47HtynmaThMVsIpH6/FvtdqPJHsXjtfH88TYWrSnGI2H299VS43MiCALRSHpT371sTkV48O/FroMO4iOi7WFkWcXhMGN3WolFM1vaGC50f7Y6w7hVNF1nMLjMpzPTJHM5+mpqeb65BZelctuiqqpx7c4UtwfnaKjx8PKDluJukU1n+fAvLrA0FeTF7z7PvkNtu3Zbj3LzgwGS0RSv/Oq5bX/wrrYk5YzO0rSZE4fb8Lhs66p1TlveYsZps2MzWwtW7S7OzuC32+itKd/E+OFziMhRLGYzbtxYndaiMV+FWqgWi4X/1z/+fxBORAknIvz8xieomookSnzl6Av4XT6q3QEsFsuGhYNHq2ir1Tq/08TsyhKt1Q3EM6mSVbukkuRG5BaLmSVa7S3IsohkC23JL+/u8hLvjY9R7XDwja6Da++J1fPNyTkmgrO0F0iVyGRl3vnkPsFwgnMVyDi+88k9rr1zm+7nOnnuqzuf2TR4/DCE3WPKXuaHVpJMMovNuTe2A4Ig4HXbicby35p3Ek1W7Phf6T7A/7h9g08Xp/i2rwcoz3fPapGA0qLN7jBjd5qJRbMlRVtji5ehgcWi1bbGBhtkE+jF7ohkRjDb8HhtuPpqCS2nyGRkbDYzVTWOHX9b13SdwVCQy7MzrKTTdAYCnD7YQ8Du2NFxHyUcTfHhZ0NEYmlOHG6jv6tx11qvALGVOO/92Sdkklle//svU1fhhJNSBGdD3P10iKOv9uOr2Z61yZodh9PDh5eH6Gs6SN+BfHbz+XtXGF+aoSlQT0bOrv2O3+Vl/JGqXTid5s78LNVijlBsZUuzcavn4PU6SQpxLOQFTaG2ZakWalNVPU1V9Xxw+wKSJGEySeh63guxv+3zamap2LE6X81atW45FsJusRKKh6nxVBWs2mm6xkhijHux+1hEC6eqnqfBXk+fK1N27JiiaXw4Oc7txUX6a2t5pb1jXcVztVq3kozhtjlZScawmC1rojcaT/Pzj+4hywpfO9tP7Q7iE3Vd59o7txg4P8jhl3s58kqfIeqeUgxh9xhSqarTF0Fe2O3duXk9diKx/MbYTqLJimE3mznX0ckP79/jyvwszzY2r/Pdq6qWyOVUVFVDkkQsFikvyOrdIMDyYnJHom1VyBertjU22HDOfYKS2lg9WLvvDg9SzzniKTZ8WQgubf/LgqppDIWCXJqbIZzOsM/v5yv7O6l3VTa7V9d1BobnuXJrErfTxjfOHdq1vNdVFiaW+PAvLmC1W/jaP34NT4XziEuhKirnf3CZQINv2y1Y+Fzk1NgbWAmP4zokI0kimqZxZ2oQdMjIGTJyZv0v6vnf/dZzryOKItcW5ogmwuQSswz4fFuajVvd7LS7JJAhpeW/hBVqW5ZqocLD1S2ZyeAMbdXN6wTgZvYgn9y7RDgRw2G1E0sl8Ts9hJMxbGYbqWx6XdUumA1xK3KHiByl09VBr+cgJvFzf7ly7Fli2Qw/GR5iOZXkXMd++mvr1l3+cLUuK+doqqpjNrRITs5xb3aUGkcD128tYrea+ca5wzuKw9M0jYs/vsbw1TFOvHmU3jLjHg2eTAxh95hR6arTXiPnFFy+ylZqSlHtdzE+FURR1G1Hk23GPp+f55qaOT81hdNsobemlqZWH8uLce7dXkDX9NXxGARRoK7RQ3ObH4BkLLtt0faw4Cq2MUw2gZKKIZitYCrwh1/JoKdixFYSDI0kKvJlIaso3Fle5Pr8PIlcjg6/nzf3d63NDFWSaDzNx5dGWAzG6D3QwLOH23Zte3eVwSujXPrJNeraanj5V07teprEo9y9MEQsFOcbv/36tqupq6KhzlvF+FCCxloPS5lZlqMhqtx+DjR24LAWf5+21OQXJHKqyrWZKYRsjGq3b9PlgId5eLMzmF1CEzTCuc+/gDzctgzFwyVbqJAXfouRIOFkFLfNSTiZb++uCsBS9iDheJS7M2PYrVamlmcxSSaiqTiKqjC1PEtLTQNLsTCxbJz7iUFm0rP4LD5eqX2RgMW/5cd/ZCXE22MjWCUTv9zbX/DLzsDUEHOhReYjQewWGxk5i91iYz4SJBkVmR++yKn+Pl493b2jTW9FVvjof3/G7PA8p3/hWTqPbi0+zuDJwxB2jxm7UXXaSzRF3dOV+YZaD6qmsRSK43U6thVNVg6nmltIyzLvjI1ikSRqJSdrvc/V52n16dLyF+xUtBV6/h99ztfaryYbgmVjHJcO6Lkss7NxUml1R18WIpk0N2enGVhaQNF1DgYCHNvXSrXdDujomfha23enaJrOwNAcV+9M4bRb+drZfhp2mLawGaqqcuWtGwxeHuXg8wd45iuH93xTMBFJcuuju/Sc7MJf59v2cVarX1bNSzKZ5PCRGubjs2si6FvPniurnTiyvMRseIkaFFprWgtW0oohiuLaZufN2G2SSpLTgZMFb6dUC/WVQ6fWVeuycpamqnpmQwvkZJl7s6P0NHeWjCbzu7187ZmzSILIwPQQHXUta5eNLU7T29pJx4Fm3gt+iFk084z/GK2OraeWKJrGx1MT3FxY4ECginMd+9eSJB5mVfQmMkkiyRhWs4VEOoWuw+KsQkKXaT1q4twLBzHvwCcxk8ry3p99Qngxwtlfe4HmB614g6cbQ9g9ZuxW1WmvUBUVcZdyOQvh9zqwWc3MLkRpOOzdVjRZOQiCwNl9HWRVhZ8MD9KYc1GNnZ5DdflW7AObEotFIhRMrwmlnYi2Rym0TFMO6SxEkhk83nxFLZOR19mqlPqyoOk6E5EwtxYXmFgJYlkZp8+scdhlxhWZhchtHk7nXG377kTchcJJzl8ZJRhO0HuggROHWne9SpeKp/noLy8QnF3h5DefoeuZrRlsV4qrP7+JxWbh8Mu92z7Gw9W60fsJ/AErHo8FXVpfBVttJ5Yy8708PY6cjtFWl58vLMfS42FW25Ye2U0um8Pr9BQ932It1L7WLgamhpgNLbIYXc5Xt3L56tZidBlRFLk3M7JpNFksneRHV97lYNN+vM58BU3TNZKWBAPKXUjKHKnup8vdiVks77318GOHycZbo8NEMxnO7uvgcG3xL0qiKOY3lRem1nJgZVljZCiO5EkRqNP55XOndiTqVmdEc+kcb/zDV3Zsl2Pw5GAIu8eMcgbzd9NMdqcIogh60TH+yt+eINDWVMX4dJATh1t31dZDFATe7Ozi/eExfnr9Pi1uLy/qbRtsSh4VSlvx5itGsWWaxloTmzW+ZVVAUTTknMrSfJxEIoemaoiSiMtlwV/lQFa0dV8WQqkUd4NLDAaDJHI56l0uXm9tYR/TWKy2km1fVBm2IexkWeX6wDQDQ3N4PXa+/mo/ddUbhUClWZpa5sO/uACCwFf+4SvUtuxeFFkp5scXmbw7w5lffG5HEWWrLUk9YyUaT9Pc7iWZSRW14yhm5ptVFG7OTOJAXRNCj1bSysVn9jKWmCCn5bCI698LD7dQ51eWGF+cYV9dMx6Hi2gyzu3JQWLpBMlMknAiRp2vmsSDVms4EcNjdxFNJ7CaLSVn366PDazdTiwTJypECAthNEmFuEh1spa+/T1l36fVc784dJ2pRJqM1YPfZufv9B+ixrF58snYwhQ5RcbjcJFIyAwP5c3djxypZiWzxOjC5FpLfKssTQd5/8/PY7VbePO3XsUT2LsZUYMvHkPYPWY8PJhf6arTXiBKIqpauSSIctjfVs3g2AKLwTj1NZ5dtfUQBYETtY2suOPcVYP8dG6Y56uaaXR8/odztaoqp1Popmzxg5XZtiy1TBMPqezXwGt/UNHL6CgqmCRw2PKvHbOko6Q0pibCaKqGw2lBksyoqkY0kiYez1JV5SCjqYzNzzEYCrKQSGAzmeiurqa3upY6lws9E0eZEUq2fZFL3N8i6LrO1OwKn10fJ5NVOH6olf6uxh1lX5Z7u/cuDnP15zepaanm5V8+id218X7tBZqmcfmnN6hpqaLj8PYtVVZbfB6Hi5H7YUw2IZ9YkswvLTxqx1FqE/Xm7CRLsRVeri9eSSt3Q7bOll8cmEvP0+78/P49mrAwNDvGyMIkGTlDV1MHXqebeCbJ0fbeddWtVWKpBIlMiuMd/SXnEVdvx+W0M5GdJC7F0AUdp+rCp/gxSWbSmdwGm5JSLEdDXJsaZl63MTQ1zt85dpqvHuwvy+dv3fM0EWJuOovdIdK234YqpYvappTDxMA05//6ElVNAV75O6exOfZ2RtTgi8cQdo8Ze20mW2kkk4haIAliN6mv8eB22hgcXaC+xrPlaLKtYjJJNDs9NFo8XIvP8/7iOPV2F0d89VTbHMiyiklQEcc/RtHiRY9TTtty02WauTBzSRGsGgtRhXBcQ1VBksDvFmnw6TgtIKsasWiGhkb32geFKEpILpG788soAtwYDGKSRFq9Pl5t6qDJ6cZmMe/ql4hILMVn18aZXYzQ0uDn5PGOHW3/lUsuk+PTH15m6t4sPae6OH7u0BfqvD9yfZzIUpSv//brO3qdrs61zSysQPA+Z88coLFu/Wziw3YcpTZRPxsfBDWH22rZsIxQyoi3EHbJRr2tjrux+9Tb6rBJtnXnm1NyBGNh0tkMTVV1iILEV468SLXHj9Vs5bPBa2vVrYfxOFysJKKMzk/QUl14fkzXdVbkMNXtbjK1Lmpw02p/jn2Ofdilz19rDz8um6HpOn9z+yqXgjGa/FXU5GK41WTZ5s2iKPJq/xnOXxkBQjz/Ug3PHG5Z92VmK+ezej9vfXSXm+8PsO9QK6e//awREfYlxRB2jyF7YSa7W1jtFrLp4nMuu4EgCPR3N/LZ9XGO9bXgcdu3PbNWzofqw1XVs7XtzKbj3I4s8bP5ERrtbmoUB711Hmy5OIKl9LbqZm3LzZZp3B4zi9MC4WQOTdBxOcBsAVmF5SDEIzLNfjBJAl6PlUg0Q86mEdLSLOQShDMZJItAm8nHy43ttLi9BGcTRBZSDCiJdf6J7gp+8c/mFG4MTHN3eB6nw8rrL/TQ0ujfky8swbkVPvrLC+TSOV7+O6dp62ne9dsshSIr3PzgLvsOtVLVsPUNzEexW23MziWoCfg4uK+56GO6Wq1zWGxcG7tDjbtqrRJX5fYzF49R7XCUZcRbak5vlWP+I7y39CGXVq7wQvXptdi71Tm862MDxNMJVlfMp4Nz7G9oK5qbWuxcVsmoGaZSM0ylponJMVwmFyeqj9HqbMVS5gxdIYKpFD+8e5P3J8bo8vs5VldFMm3bUppGOJrkvU+HSCSzfOXFQ3S278wjUZEVLvzNFcZvT3HkbB+HX+p9bL/8G+w+hrB7TNntqtNuYXPaCM6u7Pntdu2r5cbdGW7dn+WFZzfPfdyJAfTDVdVQME2t18kb9fsZi4W5tjjPpBBhORklksnSFXASMG+MFSu3bbnZMo3JYmElbcWl5GiqVhB0QAEL4LfBUkznBhbmHXEiHoWZSIxMTMaMSK3JSW91LQdqq1BzGrWCk4l7waKWKF2drk3n+TZDVTXujS5wY2AaTdM53t9KX3cjpj1YuFltvV57+xb+Oi+v//2Xce+yH1453L80QjaV5eir/RU5XiYrMzET4plDrSX/XqxW63JKlqG5ccwtJiwmKwNTQ7zcf5L66maO1dVxtK6OYGyFmxP3ONLeQ7Unn3zwaOWv0Jzew9glG88HTvDx8qdcC9/gmP8IkpB/XW+WwLDZYsTquWTUDAuZRebSCyxmlhAEgUZbPYe8fdRaa3b091NWVS7PzXJ1fpal0Dz7bQInGvIt5lKzhw8/Ni/3n2RofInPro3jdln51uuH8Xt39q5KxdN88L3zhJeivPTLp2jva9n8lwyeagxh9xhTiaH7vcbuspGOpze/YoUxmSQOH2zi0s0JDnbWlzSwrYQB9KNVVVnRqDU5+DsH+zFXm5mIzXP97iCX0mE81jQtdgvNdiuNNjPuLbRHNlumSWV0cvY6/J1+FKdIVM4SlbOE5SyhXJqQkCaTVTGno7T4vLzU3oZPtOEWLZhMElariVxOIa3KLC/GS/snzsbp1D93ddkKuq4zPh3i6u0p4skMXftqOd7fuqtxYA+TTqQ5/4PLzI0s0HPyAMfPHX4s2lRyTmbg/CCdx/ZVTGROTIfQdb1kFejhat3owiRum5Pp4AKHWru5NzvK/sYOEESafAG8Tg/XxwYYmB4m4PKxv6G94LEKzek9SrW1imcCR7kWvslSdpn9rg72Ods3TWAoZgqsaAoruTCz6TmWIkus5CIPbifAYV8fLY7mDcsa22EiEuaDiXHiuSydHjdiaARv9fp4tc3SNO5MjhBdshAMZujuqOPksX07XoJbngnxwf/6FEGAN37zLNWNO4sbM3g6MISdQUXxVLlIJzLksvKONvu2Q09nPcPjS5y/PMo3zx0uGDdVSQPoUlXVzoCVMyu3mBUcTMswFs9yLZRCFMBpEQlIOlV6Fv/8PC5XGofZjNNswSyJSIKISRQRBQEsYPGYmV+K4wlYyWkaWU0hoyqkFJmphQgrYprRZIpcPG88IgoCXrONaoeXLm89QlKnweshlZSp9joKLuR4vDbSyewm/okJ0iZwWjKF48uUzxMMVtvcsqywGIpzb3SeUCRJS4Ofcy904/duvjVYKWaG5/n0B5cAePU3XnysvLyGr46Ry+S2lTBRrP05NhWkodaL3VZc0KxuoiYzKZajoTWD7fnwEk6bg+sTg4AJu8m8qXDbLDHiUVodLfjNPoYTo9yL3efa0g3GlmZJCHEyeoYmbz1zoaW1BIa+1i78bi9ZLUdGzRBTYkRzMSJylIgcQdM1LKKFGms1z/jbqbPVYZMqMzcQzWT4cHKcsXCYFq+Xb3Uf5NbITeKpBFUu76azh6uPTYOriY8vjxHyjvH3vvEKHa07j6cbvjbGxR9fo7opwMu/cuoLW/wxePwwhJ1BRXE/iF6KheJ7/u1RkkTOPLufH717m7vD8/R3b7QKqLQBdKmqqlkUqNLM5BJmLAkbLYpGHDk/C2TLsqiqjC8uklkMlryNbFYhFEsghzSsNglRFNE1HVEWcFnM1Ptc1NldVDudeM1WXGYL0oP5pWxWIaPJtLT5mR5fKbqQU1PnYmw4g7mUf6IGisWNLseLtpEFh4dYQmV2aIGxiSBDk4vEUxmaGvy8fOYAB/ZvPUR+u8g5mWtv32Lw8iiNnfWc+YVnH6sPP0VWuPPJffYfbd9Wta5Q+zOVzrEQjPHCieI+fKsza6IoMrIwQSKTZCURJeDyMrIwwbGOflZScXSTD4tJYmB0oKhwKzWnV2pj1m12c9x/lF7PQb5/+8cspZeJmKOYGk2EpEVEh8KMMk1cjfBnowlaaj8X48FYmKGpCc50nOBQQy81tmo8Jk9Fx1SyisLV+Tmuzc9hM5n42oEuDgSq0HW97Hm/UDzMwPQIStzBrfEVqr1ufE1p3N6djR2oisrlt24wdGWUrhP7efarR5Ekqaw5R4MvB4awM6go3mo3giAQXoh8IW2B2io3fQcauHJrkuqAi/qa9T5oe2kAHUvB8LJGRtFwOwQ8DolqRSKe0rEpJg7U6ASOHkW1OEnJOVKyjKJpyJqGqmlouo4kCIiiSDqRIzSfJBPLIWgCDrMJf5WTxhYvc9PRvD2Oo3A1rrbORV2DG4fTUnQhR5LEzf0TrVasvS9jshX/AI3GFT79bIZ74wtkZJmAz0l/dxMWwURkIUWsOrMnyz9L00HO//UlUvE0z33tGN3Pdj5286mjNybIpnL0v3Bwy79brIo2uxABoKWx+BLG6iaqSZQIxyM4rHYa/LWIokitp4re5k6OHDjGX92/z1IkVDLqq9ScXjkbsxbBgiPrRly0Eg/J1FS5UU0aomAmmUjh9oOr2stx31HsJjs2ycr/de0vuH5liOZcM7/Y9Y0tP3al0HSdO0uLfDYzTU5VOd7QyInGJiwPNqYFQSh73u/i3TvcvRPFbfbR1uqiucXJ0NzElj0AHyYZS/HhX1xgZT7MqW+d4MDxjrXLyplzNPhyYAg7g4pitpjx1XpYngmt+6Ozl5w43EYonOS98/f55uuHcTs/FxJ7ZQCt6zpzKyKZtEzAl/9AQAOLCAGnzkpEZm5FxK/rmEQRj9WGp1SwuA/0psJbvIIglGWPU6p1rOt6Wf6JTq+7oEDSNJ3J2RA/f/ces/MRmuq9HG9voTbgXjv+XuQcq4rKzQ8GGDg/SFVTgNd+40U8VY+fOaumaQx8Okhrb3NR89hSFZhi7c+ZhTDVflfJNixAIpNkOjSPKAiks1kQdNAFREFgOjRPb3veqHdgZrRo1Fdfa1fJOb1yfO4KJTCssupR95WOl2lx5avv96ZH+PjuFWRF4aO7l3nj2Cv0tGy+LLUZuq4zGl7h0+kpVtJpempqONXcise6saVbbN5vFU3T+ejKXX7y/j08LheH+6twu/NjKdvxAFxlfmyRj//qMySTxJv/6Oy6JImtzDkaPP3sqCb8H//jf0QQBP7Vv/pXaz975ZVX1j5sVv/5Z//sn+30PA2eIKqbqwjO7P1m7CqSJPLqmW5MJom3P75HJiuvXbZqVRKLZtEfSchYFTC+gGPH3m2pLERzDpwWBeQ0ei619g9yGqdFIZpzkNqCn+9q29frs68lWsDnixy1dS4yKZmVUIpMSqa2zkV3X926ClmxY6xu+jrsJoLLKbJZBU3TyWYVgsupov6JiqJyf2SB7791nZ99cJdsWubFE528cLyTuirPuuM/3ObeDZZnQvzoT97m7oUhjr7az5v/6OxjKeoA5kYWSIST9J3uKnqd1QrMwNTQup8/GsG1KhaWIkHml2IbfOuKHXs1gD6ZTTO1PEcym2Y+EmQutMjY3DjpXJo7cxNFo77O37tCNBlnPrxEPJXAbXcRTyWYDy+tzZqVw8MJDA/jcbjIKTKjC5NrP/vZ9Q+YDy8jiALz4WV+dv2Dsm6jGPqDyLzvDdzmR0ODuCwWfv3QYd7Yf6CgqNuMcDTFj9+7zTsXbmP3yBw+4ichh/n03jXmV5bWzeFt5RxvfjjAO//3R/jrfXz9t1/fEA+2KvRba5pIZtJbOr7B08e2K3aXL1/mT/7kTzh8+PCGy/7JP/kn/Lt/9+/W/tvh2KlJgsGTRH17DcNXx0jGUjg9X8xzb7Oaef3FHn76/h1++v4Ab77Si91m2TMDaBUzWvUBbD5LwSUOm6aTjuRQqcyCSSXscbbin5hMZbk/usjg6AKZnEJbU4BjB1uYHY8SqHIUvN3dyjlWZIUb7w9w78IQVY1+vv7br+Ov3VzcfJEMXh6lqtFfNL+zVAVm9UP80SrateF7pDMiNYHS83oPB9AvRoJr3nHhRARFVfA6XCSzKbKpOIuJBL1VVRuWBMKJGKHYChazlZGFCaxmK4lMCpPJtDanV05ywlY86gZnx/jo7mVMkoTdbEPTtG1X7XRdZzIa4dLsDHPxOA1uN9/t6aPFu73Xjapq3L4/y427MzgdFjoPOkmqfqLpeME0jXJTJdLJDJ98/yILY0scfrmXQy/1bPidYkLfqNp9edmWsEskEvzGb/wGf/qnf8q///f/fsPlDoeD+vr6HZ+cwZNJY2c9gigwMzRPd4kh7t3G73Xw1bN9/PT9AX7y/gBvvNSLy2ndEwNok0nCbLWiCGaslo1vMyWrYLYKFc38rYQ9zmbt2sVgnHsj80xMh5AkkQPttfR2NeB120kmcixNx/c053h2ZJ6LP75GOp7h2LlD9J7q2nIE016TjCaZG1ng5DefKXqdYq3WRz/EV6n3VXNjZBRnrpmaTaqUD7c/RUFkMRKkIVDL/MoSdb5qmqrqOdrew73wRWTJwkoiukGo+10eqtx+7CYrOTlHrbea8aVpju3rYykapLe5k3NHXlj3XBRqLT+cPFGM1Zm11Wqd0+bA63SjaOpa1a5cYafrOuORMJdmZ1hIJKh3ufhW90H2+bZvjr0civPJ5VEisRSHDjZxtK8FWenbNE1js9fpwsQSH//VRXRN47W/+yKN+wt/phYT+juZ5TN4stmWsPvn//yf8/Wvf51z584VFHb/83/+T/7H//gf1NfX881vfpN/+2//bdGqXTabJZv9vB8Vi2381mbwZGG1W6ltrWZmcO4LFXYAfq+Tr73az88/usffvHOLs6e6aKj17roB9JOc+fuoQMxmZYYnlxkcXSQSS+F123nu6D4622vWida9vM/pZIYrb91g/PYU9ftqOfd3X3ps266PMn57CtEk0lbESLZUBWbVpsTv9Gyooq1EE2S1MHbb5o/v2MIUK4kokVQMrzP/uHmdbiKpGHarnfHFaX792Vf484FbnNy3j/3+jYtQsXSSH115l/baZqaWZ5kKzuK2OWivbWY6NE88ncBm+bydWWy4f7OZNcjP1q1W65zW/GeJ0+ogK2fLqtopmsb94DLX5udYSadpdLv5xYO9tHq9237PZ3MKV29Pcn90kYDPyTdfP7zmn2mSPk/T0HSd7qb9DM6Or6VplELTNG5/dI9bH96lrr2GF77zPA534W3uUkLfqNp9edmysPve977HtWvXuHz5csHLf/3Xf522tjYaGxu5desWv//7v8/g4CDf//73C17/P/yH/8Af/uEfbvU0DB5z2vtbufTja19oO3YVn8fBN147xAcXhvjpBwMc72vhSG/zrhpAP+mZv5qmM78UZWRiifGZELqm09Zcxclj+2isK/xhuBf3WdM0hq+Ocf3d2wiiyJlffI6Ow22P7eP4KLquM3pzkpbuxqI+j8UqMLcn7hPLJIu2Lc2CDSQFXddLPh6r7c9kJkk4EaPOV03igUgMJ2J47C6i6QTNPj+d1bUMRmIca9r4GF8fGyCajCMJIiMLU1gkMyMLU1R7Ahv83HY63P+z6x8wE1zAYjajaQqpjLL2eM4EF4pW7RK5HHeWFrm9tEBKlunwB3itYz+NrsJLQOWg6zpjU0Eu3phAUVSeO9pOb2fDhpGL7bRIk9EkH//VRZanQxx+pZdDL25svT5MKaG/1Txfg6eHLQm76elpfud3foe3334bm63wN6x/+k//6dq/Hzp0iIaGBl577TVGR0fZv39j9eYP/uAP+L3f+721/47FYrS0GJEoTzr7+lu48rMbjN2c5NCLPV/06eCwW3jzlT5uDExzbWCa2cUILzzbibfIN+FK8KRl/uq6TiiSZHwqyMjkMql0Dp/bzrG+Fg6015aVErGb93l5JsTFH19jZT5M5/F9HD93GJujggG2e0B4MUJ0OcYzXzlS8PJSFZjB+XG+/sxZvI6TBX/3A2kEk8m0aYsv34rtL7mJeryjH1EUebaxie/fu8vA8hL9tXVr13t4Nu7ezAiRZF4gLkaC3JsZoaupY90c2VZNjB9GURTGl2bRdA1VU4mmEmuXqZqKpmtMLs2iKAomkylvQh6PcWtxgZGVFSRR5GB1NcfqGwjYd/YlMxxNcuHqOPPLUdoffNFxFnkNbrVFOjEwzWd/ewWz1cwbv/kKtZuYGG83Q9fg6WdLwu7q1assLS1x/PjxtZ+pqspHH33EH/3RH5HNZpGk9fMzzz//PAAjIyMFhZ3VasW6je0jg8cbi81Ce18Lw1fH6DvT/Vj8YRFFgeOHWqmv9fDJ5VH++q0b9HU1cqS3CYt5d5x/noTM33A0xfhUkLHpINF4GpvVTEdLNZ3tNVQHXFs+10rf53QizfV37zByfZxAg5+v/uPXqGl+MttLk3dnsNgtNHQUNmrerAIztjBVVBBZTBZsZbRhAcYWJotuoq4koozOT9BS3UCr18eh2jo+nBwnYLfT6M77Qq7Oxs2tLJLOZtYE4ppFyZEXaaqqRxTFHQ/3m0wmXjt0GrvZRnP1xjmzmeACL/QcJ62q3Ftc4O7yEpFMhoDdzktt7fRU12A17ez9nc0p3BiY5u7wPG6XjTde6qW5obhX4FZapLlMjstv3WD0xgRtfS2c+uYzWDaxq4GtzScafLnY0qv9tdde4/bt2+t+9pu/+ZscPHiQ3//9398g6gBu3LgBQEPD4xPjY7A39Jw8wOiNCSbuTNNxuPRcyV7SWOfjO28e5db9WW7fn2N4fJHDPc10d9QVTV7YCY9b5q+m6SyF4kzPrTA5u0I0nsZiNq1VIBpqvUjSzj4MKnGfVUXl3sVhbn90D0EUeP7rxznwTMcT/UE1eXeG1oNNBf9W7rQCo6gapgLH3entvNTWTiid4m8G7/PNroM0efLizm61MR2cQ9N1GgJ5oeq0OTbMkm2lclVowULTNDR02uqaNpyrrOnYvLVcWF5h5PoVzJJEZ6CKYzUB5hcnabK3FhR15aY0aJrO0Ngi1+5MISsaxw+10tfViGmT90e5LdLFyWXO//Ulsukcp3/hWfYfad/SF6By5hMNvnxsSdi53W76+/vX/czpdFJVVUV/fz+jo6P82Z/9GV/72teoqqri1q1b/O7v/i4vvfRSQVsUg6ebQL2fpgMN3PnkPvsOtT5WVSqTSeJ4fyvdHXVcuzPN5ZsT3Lg7TW9nAz0H6jc1eH3SSKVzzC5E8v8sRshkZexWM61NAZ470k5jvW/TD6u9Qtd1pu7Pcu3tWyQiSbqf7eTIK71Y7U92ZT8eThALxjl+rvDfwp1WYERRQNO0Tc9jq7djliS+3d3D3w7d56/uDXC6pZVnGhoJxlY2rUoBWxruL7Rg8ej5JnI5JqNRJqNRZuIxHLpOmy9AX109BwJVWE0mPrh9gcsjN7GZLQUrnOWkNMwuRLh0Y4KVaJLO9lpOHGot2nZ9mHKEczge4/Jb17l/cYSa1mq+8g9fweXbu/xkg6ebivafLBYL77zzDv/pP/0nkskkLS0tfPe73+Xf/Jt/U8mbMXiCOPTiQd76v95n/PbUY1W1W8XpsPLic50c62vhztActwfnuHV/luYGPx2t1bQ2+itqz7FXZLMyC8sx5pdjzC9GWYkmEQSBKp+T7o46Whr91ATcBT32vkiWZ0Jc/flNlqaCNHbWc/bXzuCrebw96cplbnQRQRSoby8+O7WTCozFbCIrl+cRuNXbsZpMfKenj0+np/hkapLRlRBiKkQkEStZlQLKHu4vtmChaBrBTJapWISpaJTFRAJREGh0u3m9s5sDgSqcls+/iG22qLHZ5cFwgis3J5ldjFBX7eFb5w4XtZDZjoVLaC7M9Z/eZjA6+sRY9Bg8WexY2H3wwQdr/97S0sKHH36400MaPEXUttbQ1tvM1bdv0VxiE/CLxuW0cvLYPo71NjM8uczYZJD3LwxiMZtobfTTVO+nsc5b1gLBXqOqGtF4muWVBMuhOEuhOJFYGl3XcTttNNR6OXSwiaZ672NbiYytxLnx3h0m7kzjr/Ny7u+9VNS360llYXyJ6qZAWfNT28FmNROOpja/4jYRBYEXWtto9/n4aHKC96dn0BUT6VAIn1nCJgprVXmv000kGUNDL7vlOzA1RCKdor2hjRvT4/zFjUvU1bSwkEigaBoOs5lmj5ej9Q3s8/mwmUpvFRdb1Ch2eSye5vrANCOTy/jcds6dOUhrU6Bkp2ErFi6qonLro7vc+eQ+gXofr/7qi4+9kbbBk4mRFWuw65x44wg/+KO3uP3RXZ55vfA24OOC1Wqmv6uR/q5GovE0oxPLTM2tMDK5DECVz0l9rZdqv4sqvxOv275nVS9d10mmckRiKSLxNOFIilAkSSSWQlU1BEEg4HVQV+3hUHcT9bWedTm5jyPJWIrbH91j+NoYNqeN099+lo4jbU9lBSM0u0Jrb/OuHd/nsTM2FUTT9F19TTZ7vPxa/2GO19VxY2GOqVgMWdexWSw0uN0EbHY8VivVTjd2kwlNU5CEfA6tomnImoasqaRkBVmHawvzTK8s8/bdO6iCmfG5ZTKqmfnZKc55azjd0kqLx0u1o3CiycNstqhR6PKb48OkVmwsLqaxWs2cObGfrn11mz6GW7FwWZoOcuFvrhBfSXDklT76znQXnLM0MKgEhrAz2HWcXieHXuzh5gcDtPY0PzEbjV63neOHWjl+qJVUOsfcYpTZxQjTc2EGhuYAMJskPG47HpcNr9uO22nFbrNgt5mxWfOpEyaTuImvmI6iqsiySiarkMnKpDMy6UyORDJLIpUlkcwSS2RQ1HyrTZJEfB4HVT4nne01VPmcVPtdO1r+0OUMqCVyXCUzgrkyQjGdzHD300HuXxxBMkscP3eY7mf3Y9ql7eQvmnQiTSKSpLppo9FvpajyO1FUlWg8jd9b2tZjp8+1IAgcrK3nYG09WUVhNh5jKhplJhZlNhRCVjef9VvFIkkshubQVZmDdTW4TCa8FjOTC5M0SjLHGxrLPtZmixoPX57NqAQXdO4MRYnVjPALZ0/T01lf9uhFORYuck7mxnt3uH9xJB9390/P4a/zlX1/DAy2w9P5V9TgsaPvTDczg3N88v2LfP23X39sW7LFcNgtdLbX0PlgPiqbUwiFEwTDSWLxDLF4mqVgnGQ6W/D3TZKUF3gP/lsnX4FTVX1NrD2KxWzC6bDgctqoq3HT2V6Dz+PA67HjclgrWpXR5QzqvXfQU8WTXwSHB6nn3I7EXTqRZuDTIQYvjyAIAn1nuuk93f3EvR62SngxCkCgwbdrt1HldyGJIrOLkZLCrtLPtdVkosMfoONBOoWu66RkmUg2Q1ZRUDQNRdNQdR2zKGKRJMyihN1sxm2xEEtG+d8XhjnQ2IDX+bn9SoO/Zku2KJtZjNT58sfz2/2MjERZXEwjSQJd+6tw+DLUN9jKFnXlWLjMDM9z6cfXSCczHH/9MD0nDzyVlWiDxw9D2BnsCZIk8cJ3n+dH/+fbXPzRVV74zvOP1ZbsVrFaTDTW+Wh85Nu3qmr5iltWJpORyWQVVE1DUTQURV2fCiDkBV8+P1XEbDJhs5qw2czYrea9XdpQZfRUDMFsBVOBD3MlkxcCqgzbEHapeJqBTwcZujKKKIr0nuqi91TXE7/pWi7RYBxREiu6+fjo4L7VYqKp3sfEVIj+rhJVrl1+rgVBwGmxrFtoKEWl0hM2O84PP32PhfksouzCZBKob7BTV2dFMolMLM1uyTS5VGXwufajXH7rBpMD0zR01HHu77+EJ/BkxN0ZPB0Yws5gz/AE3Jz61gk+/t+f4al2c+Tlvi/6lCqOJIk4HdaybBEeS0w2BMvGNA4dQC5cjSxFIpJk4Px9Rq5PIJlE+k5303PywJdG0K0SC8VxB1wVrdgUGtzvaK3mg8+GiMbTm6eqVPi53g6VSk8odhxd10kmNEKLErPzUao8bgL1OoFqE5IkE8vKkN1aSkOxymCdp4rz719hdGUMt9PFC995/rGzeTL4cmAIO4M9ZV9/K/GVBDfeu4PL52T/kfYv+pQMdoHwYoS7F4YYuzWJxWbh8Mu9dD+7f9c2Qh930vE0zk3m3rZCscH9tuYqHHYLV29P8erp7ord3m5RqfSER4+jahpTM2HujyxCJsXRFju/eraOfa0BpCLHKjeloVBlMBVKMfXpLHOTC9S84Ofb//jNL92XF4PHB0PYGew5h17sIRFOcuFvrmBzWmnqNFJJngZ0XWdhfIk75+8zP7qIw2Pn+LnDdJ3owGx5umfoNiOdyOAOuDa/YpkMTA2xGAkiCKDrrLURTZLIiUNtfHRpmIXlBuprPBW7zd2iUukJdqsNTRUYHF3k/tgi6UyO5no/L5zopqneV5HK2aOVQTWrsnwrSHgojNVnpfvrB6g7WIf5KZ8ZNXi8MYSdwZ4jCALPf+M4mVSW9//8PC/+0knaenbPBsJgd1FkhfHbU9y/OEx4MUqgwc+L332e1t5mw9LhAdl0juoKtedXq3U5WWYyOENbdfO6ql1new33Rhb46OIw33r9MLanXGRoms7cYoTBsUWmZlcwmST2t1XT01mP31vZNIfVymBWzjJ+c4pbV+7iUBv52j88y4FnO5Ak0chnNfjCMYSdwReCJEm8/CunOP/Xl/joLy6s5SQaPDnEwwmGr44xdHUMOSPT1NXAiTeOUr+v1pgregRN1Xacv7vKarUunIzitjkJJ6NYzOa1qp0gCJw93cXfvH2L984P8sbLvRW77ceJWCLDyPgSwxNLJFJZ/F4HJ4/vY39bDZZdtM2JLyW48tYNgrMrdBxu55nXD+PYbJ7RwGAPMYSdwReGJEm88J3nMVlMnP/rS6TjafrOHDREwReJkskPzxf4OeTbrbPD8wxeGmFuZAGTxUTnsXa6n+t8rDf/dF0nlZRRFBWTScLhNO/p60zXdMQKiKuHq3VZOUtTVT2zoQVysryuaud22njtdDdvfXiXT66M8sKJ/RvF3SbP9eNINiszPh1iZGKZxVAMs0mio7WGro5aagKusp/TQlFgm5GMJrn2zm3Gb0/hr/fxxm+epa6teDycgcEXhSHsDL5QRFHk1DdP4HDbufbObYKzK5z+9rNf2iH7LwzJjODw5G0uCmxEJhMyY1My4+ffIxnPEWjwc/Kbz9De3/LYz8/FohlmpyJEVlLIiobZJOILOGhq9eHx7k0yhyAKqEp5Oa6lGJgaYja0yGJ0GbvFRiaXxW6xsRhdXovlWt2Qra/18sKznXxyeYRYPM3ZU924nNZNn2vI+9ghVfZ53Y6Ygrxn5NTsCuMzIeYWIui6TlO9j5ef76KtKbAtU+5iUWCFyGVlBs7f5+6FISxW85bTUbZ7vw0Mtosh7Ay+cARB4OjZfgINfj79wSV+9Cdv89Ivn6K6cfdc+g3WI5htSD3n1qURyDmFmaEFRm9NMT++jMlqp/1QEwee6aB6kwzNx4VYNMPgnQVSaQWP14rbLCHLKkuLCRKxDN399Xsi7iw2C3JW2dExVgf3k5kk4USMOl81iQdbmeFEDI/dtcGyo7O9Bo/bxvufDvLDt2/y8vMHaG7wb3iuN1DBlJFVtiKm4skM03NhpufCzC9FUTWNumoPJ4600dFSvaPM5nKjwFRVZfjqGLc+vIucVeg5eYD+F3u2bKa9lfttYFAJDGFn8NjQerAJ/2+/zsf/+zN++l/f5fDLvfSfOYi0l0a9jxmqopJJZZGzMnJWQckpyDkFVVHRVA1VUdG1fENN1/P/L4gikiQiiAIms4TJYsJkNmG2mrDaLVjsFkxm0wZhJpht6CYrS1NBRm9MMDEwjZJTqG2t5vR3ztDW1/zYV+ceRtd1ZqcipNIK1TWf54xarSaqaySCyylmpyK4++t2XaRa7RayqZ15w4miyPGOfsYWpuhp7sTj+HzLNpZKkMikON7Rv6GSVFvl5ttfOcJHF4f52Ud3aW+u4khPM9V72DrfTEwpispiMM7sQoTZhQgr0SSSKFJX4+HZI+20Nwcq5g25WRSYrutM3p3hk59cZHhsnJMvHeelr5/C6dm6Xc1W8mQNDCqFIewMHivcfhdv/KOz3PzgLrc+vMv4rSme/erRLVuifNEzVZuhaRqpWJr48grJcIxkLE0qliadyJBOZEkns2RTWRQVBLH021QQhXX3Tdf0NZFXDMkkYXfZsLls2F1WFFkjvhInvBBBUVSqG/30ne6m40gbbv/nAmIv82R3SiopE1lJ4fFaN4pYQcDjtRJZSZFKyjhdu9v6d/mdhObCOz7O2MIkOUXG43ARSyUYX5pmX20LHoeLlUSU0fkJWqo/f6883AZ8/cUeRiaWuXlvhh++fZPmej/93Y001HorGk9XiEfF1M2x+/Q09LG4HGMxGGMxFEdVNRx2C411Po70NtPc4Kv4EsRmUWDzY4tce+cWobkwMXsC7ZiAvd+xLVEH5eXJGhhUGkPYGTx2SJLE8dcOse9QK5d+co13/8fHtBxs4sQbR9aJjGI8DjNVq2TTWaLBOLFgnMhyjFgwRmwlQSKcRJVz6Mtj6HIWmz0vPu12Ex6HiVq7hNUnYfN5sfeewup2Ybaa89U3iwnJJCGZRERRLChYNU1D13QUOV/lU2QVOSuTTefIpXOkk1nmx5eYGZxlfnSR2EoCXdVwB9z4aj0kY2nGb0+xshDBX+cl0OAnUG3HOnse0vGi97cSebKVQlFUZEXDXWQGy2yWiCtZlArMvm2Gp8rN+O2p9ZFyW+RRD7Ub43e5OX6XlX1Rju7rLZie8Ggb8MC+Wva31TAxE+Tm3Vne+nAAm9VMW1MVrY1+aqpc2Cs436rrOtOLi1y6N4ikuRgcjBAMmfmrgdv0NqcJeD35FuuhNprqvfg8jl39AlYsCuzTi1ewz1tZGF+iurmKE989yoezl6jXtpZX+zDl5MkaGOwGhrAzeGzx13r5yj94hYmBaa787CY/+M8/Zf+RdvpfPFh0A/OLmqnSdZ14OEFoLkx4IUJ4MUp4MUIqlgYe5Gf6HHirPTR11uMOuHA5BWzTWVx+FyZbgYqAkkGXs5j2VyPYttY2E0URxHxlbtUBX1VUFieXWZoOMXVvlnQ8jcNl5+VfOU17Xwu1bdXk0jniKwkiyzGiyzEiyzEGL4+STWXRlSyW8DA19U6qGzzU1jsJVNs+37ZUs2jxENI2M0YrjcmUz+GVZRWrdeOfOllWH+T07n6r31/nRckpRIMxfDXebR3j4XSFYGyF2xODeB0eJEHiK0deoNoTWOehVqwNKIoCHa017GupJhROMj4dZGJmhcGxBQCcdivVARdetx2nw4LTbsFht2AyiUiShOnB861qGpqmoyj5fORsLp+NnExliSezJFNZovE0g9MTzIXj1HpNOF0i9XUeTO4MHd0Wvvb8s3tWSS8UBZZYTpK6EuediY85/cwzvPKrZ2jpbuTDO5/tuNJWKk/WqNoZ7CaGsDN4rBEEgX39rTR3NTB8dYyB84OM3pig/VAr/We68df51q67lzNVuaxMcCbE8nSIpekgobkwuXQ+zsjpdeCv89JxpB1/rQdvjQdPlRvTI20lPRNHiVsRbI5dy+xMRpPMjS4yOzzP3OgiSk7B6XXQ1ttMe18zNS3V6x4Lu8uO3WWntvVzGwdd10nF0wRHxlj8mysEF1e4NaihKjomk0BdnYXGegsNNQIut4guZ7YsRHcDh9OML+BgaTFBdY20vl2t68SiWWrrXDicuz83WNNShSiJLIwvbVvYwecpDe/fvsBCZJl9dc0sRJa5PTnIL5x8Y911N2sDCoJAdcBFdcDFicNtxJNZgisJQuEEwQeCL5XOoWpa2ecniSIOuwW304rXbcftkZjJpDl1oIHaKu/ac1CdFJiKTBGMrexZ9erhKLDFqWUWbi4Sm4lj81rxnvBS/2odrQebKlJpK5Yna1TtDPYCQ9gZPBGYLWZ6T3XTdWI/I9fHufPJfcZvTVLbWk3Xif209jSRzWq7NlOVTqRZnAzmK15TQSKLUXRdx2K3UNtSRc/JA1Q3BQg0+LE7v7hqVTadZXEyyPzYYr7FGoojCAJVTQEOvdhDc1cDvlrvloStIAg4PQ7sHQHqD4pg9aKZHITDMgsLWebns1y5lUWTc/idCm2Wu7Q/exh/XWVinLaLIAg0tfpIxDIEl/OvC/ODCm4smsXhMNPUujfnaLaYqW6uYn5siYPPHdjRsZajIT4cuIjNbKXGW0UsleTDgYuc6TmxJha2Kk4EQcDjsuFx2eho/VyM6LpOOiOTzsgoqoqiaKiqBkJexImigEkSsVrN2KwmzKb1AvqD2xfAksblCpDKptd+bpIkosn4nlWvNE0jnIxhSkjc+OwOyfkUVq+F6mer8bS5EUSBWCaJpmkVqbQVypOFvb/fBl9ODGFn8ERhMps4+NwBDjzTwczgHIOXR/nk+xex2MxUtdaQVEx09BWOJ9vKTJUiKyxMLK8JpMhSFAB3wEVtazUHn+ukpqUKb7XnCxUvmVSW5ekgS1NBFsaXWJnP+3y5/E4a99dz7LV+6vfVlhVIvtlihL5aPZTMmKw2aupt1NS7OXQU5JzG7GSImdEQg1cnuHN1EU+1m86j7ew73Lbt4fOd4vHa6O6vX5u5jCtZzCaR2jrXns9ctvY0ce3tW6STmR2J//P3rjC5PEd7bf51Xu+vYWJphvP3rqxV7SrVBhQEAceDVuxWeXQm8FEKzQTuBrquMze6iHhTxzNlp7Wln95f7aK5u2Hde9dqthKKh3dcaXtc7rfBlxdD2Bk8kUiSRFtvC229LcRW4ozemGDo2gQjA3OMXb5P4/4GqlurqWqqWhM1m81UxUJxZobnmRtZYHFiGVVRcXjsNO6v59CLB6lrr/1Co4NURSW8GCE0FyY0F2ZpOkgsmF9ksLvt1O+rpfvZTur31eLyrc/I3FS0aSrayCd509pi19FV0AqLYrNFpLXFRmuVHfH111gKS4zdnOTmB3e5/u4dGvbXcfC5TpoONOy5EPZ4bbj7677wLemOw21ce/sW47cm6T3Vva1jPFytc9ryr0WnzY7NbF2r2gGPRRvw4ZnAYmwnV7Vcw19VVRm/PcW9C0OEF6PUtFTxtX/wWsnX4GeD13Zcadut+21gUC6GsDN44vEE3Bx79RBHXunj8ocj3LsyTnQ5wuzgDADuag+BxgCYbXT0NmJ35F/2uq6zPBNi+v4s04NzxIJxREmkrr2GY6/109hZ/4VU5HRdJ5NSiCzFWZkNEZ28SiScI7ocQ1M1BFHAV+ulvr2Wwy/1UtNShcvnLHqeupxBvfdOSdGGyQy5FILVBaYC1SQlgxZdBH3zeStJEmnqbKCps4FcVmZyYJqhK6O892ef4PI7OfhcJ53HO7Zs9LoTBEHYdUuTzbA5rLT2NHH/4gjdz3UiSVtf2jh/7wrjSzM0BerJPDR/6Xd5GX9QtfM5PWviZH5laZ0lyl63AVdnAivJZoa/2XSW4Wvj3PtsmHQ8TXNXA89+9Rh1bTUl38uVrLTtxv02MCgXQ9gZPDWIokjP8VZEi4VUWsFi0oktRViaXGL8zgxKJsvKyAQ3fnIBVdZIRJIIgoCvxs2+B2He9ftq98SENy/eskSX0yTTGeIpSESzRCNZouEMuawCmoIk6FQdSVLdXEfXMx1UNfrx1/m2ZtqsyuipGILZWly0paKgyWB2UuijT9d0dFXJX6bK6EqBpY4CFUGL1cyB4x10HttHcHaF+xeHufbObW59eJeek130nDzwpYqPO/RSLz/6f/+c4atjW5610zSNO1ODoENGzpCRH8l01eH25CB9bV1r4mRodoyRhSkyuSxdTR1PfBuwlOFvNBjj/sVhRm5MoGs6+w610nemu+xlFaPSZvC0YAg7g6eKR2eq7FV+9tcG6Dwmk1gIMnFrnOWpCJqmYXPYsDjMCKLI5MA086MLOL0OnF4HNqcNm9OKzWnFYrdgfuAfZ7aYECUR4cHgOIIAuo6q5n3jNFVDzj3wjssp5DI5sukc2VSObCpLOpEhFU+TjmdQcln05Xl0OYvFIuLyWPB4LTR0O/D6LHh9VjwN1Zj7XquML5zJVnT7VleDsDSMLk4imDYKW12R0eU0SJa8gMulNl5HlfPnWSBjVBAEapqrqGmu4vjrKe5+OsidT+5z77Mhek9303uqa8PW8NOIv9ZLx5E2bn5wl/b+VmxbTFM40NiBw5qfV0xkksyEFmiuqsdly7feW2oaeePISyiaQjC2QjqboTFQhyQWtkR50nh00/fOxCD7rW0MXhphfmwRu8tG/5mDdJ3owO7a+tiEUWkzeBp4+v+SGnzp8HhtOHtrGL4zz/D1CZbHFxBRcLodHH21n7a+FmqaqxAEgVxWJhaMkYikSESSJCNJktEUkaUomVSWTDKLktt+xqdklrA5rFgdVqwOC06fk9rWauxuOw63DafzLC6PBWux4fS9SnLQVJAz4HCApcCig55EyMoINR0Idi+YNgoS4UEVb7PzdXocPPvmMfrOHOTOJ/e59eFdhq6Mcuy1Q3QcbnusEkJ2g2OvHWJmaJ5Pf3CJs7/2Qtn3VxRFvvXsubWK0sd3L5OVcxzv6OfF3meBfEXJZsk/N9fHBtB0nYPN+xmcHWc6OM/+hvZduU/lUO5sXKnfX50dzKVkhGmNH731Np3+Nto7W3jhO8/T1tv8pY4gNDAAQ9gZPGUossLl9+5x4ae3mRtbBEEg0FxD59F2Tn6lh5a2wLrrW6xmqpuqqG4qPYS9WoGTcwqamjdmRdfRNB1RFNYqeKIkrlX2TBbTk1cZkcwIBUSbruRA19Fji7AyXfz3nQF0TS3Yzn0Uh9vOc189xsHnO7n+zm3O//Ulhq+OcfKbz+zI6+1xx+G2c+YXn+O9//kxdy8M0Xe6/EWK1YrScjTEdGiexkAt06F5coq8Tiw9jqkHm83GbcadiUGWxoKkwgnCU1EEUUD0m2g+18RXX3ttF87YwODJxBB2Bo99rmo5RJajDF8d4/pH9xm9t4jZ7aL7TC917fWouk54Jc2FD8YRXxVpavFt6diSJCHZpbIsQ55mBEFA9zYhuqtAKvBYqNn8HJ64tYqJJ+Dm5V85zfz4Ihd/dI0f/Z9vc/jlXvrOdG9rweBJoPlAA31nurn2zi28NR6aD2wtC3kz8+HHLfWg1GzcZsRCca58cpO//dE7SLKAuUGk/XQLVfsDJJU0M5lFlqMhw/DXwOABhrD7kvM45apuFVVVmb4/x+DlERYnlrHYzWB30X6qjvau2nXVMpvNxPxcnIEb8zQ0efakkraZxcietVm3wiaLEYJkQrD7Cs/q5dKQjm77phv21fGNf/Y6tz68y80PBpi+P8uL3z2Jp+qLT7HYDY69dohYKMGH/+tTXvrlk7R0N5X1e5tV4x7H1IPNhOijpBNpJu/OMH57iuXpEDOReaRaid5nD+Coyo8KZPWcYfhrYFAAQ9h9ifmiclV3SiaVZejKKIOXR0nH09S2VvPid5/HHvDx7k8HcbgsG4SbKIr4A3aWF+OEllPU1Ll29RzLsRgRHB6knnN7J+6UTD6mrMDPESUw29A3W4zYYjVuq5jMJo6fO0xrTxOffP8SP/7/vMOpb52gva9lV2/3i0AURV76pZN8/Fef8cH/+pRT3zxB57F9m/7eZtW4xy31oNy2cCaVZereDJN3Z1gYWwIBmjrrOfOLz3EzcZ/FeJAsCtlHrEie9E1fA4NKYwi7p5RNDWlFE7NT0T3JVa0U0WCMe58NM3pzAnToONLGwec61/JipyfDyLKGxVL4ZW2xmIjKGTKZElW0SlGGxYieiuWfo90WdpIZweHJ316R7FnRFUCXehBt3qLVOD0VQtcfVOYKoOfSeWFYAaqbqvjaPz3HZ397hY/+8gLB2RWOnzv01H1wSyaJl375FBd/fI1Pf3iZ5ZkQz755tOiG8GbVuJ7mzscu9aCUEH2+4xizQ/NM3ZthdmQBdKhrr+H5bxyntad5bWu4MVtv2JAYGJSJIeyeQsqpFqVFN+FEFx6vo+K5qpUmOLfCnY/vMX1/DpvTSv8LB+l+tnODVYTNZsZsFsnlFEymjeecyymYzSI2294Z4z5qMaLrOjlFJ5FRSESTyBNBMlqUdFYmm1OQZZVcTkFWVFQtv6ShaTq6nq+1rT5XJpOISZIwSSIWiwmrxYTNasJmNeN0WHDYrbgcVpwOC4LZhtj5QsFK3Np5aRra0EcIYmERL4hC3hZlaRithCUKgo4uZxBsO2+fWqxmXvzuSaqbq7j6s5vEQnFe/O7ze+IzuJeIosjJbzxDVaOfyz+9weLEMs9/4zgN++o2XHezaty9mZHHyovtUSGq6zrplTTijM5PP3qP+7YhnFYHNS1VPPvmUdp6mwvalBg2JAYG5WMIu6eRMqpFuUgCRVYwmwu31raSq7pbLE4uc+uju8yPLuIOuDj5zWfoONxW1M6gqsZBTZ2bmekINtv6jVRN0wivpGlu8VFVs/Pc0s0qorl0klBcJRrJEFdkoimVeFohnlaRFQ1dVUDJIIYnsDoc2K1mrFYzFrOE3W7GY7IjSQKSKCJJIgIP/OZ0HV0HRVVRVQ1F0cjJCuFoimxOIZ3JIT/0nEmSiMduwhMbxitlCbgkql0iDssjH+wWG1js+WpckaqeYHGAkgN7cUsUsvHSc4Vl8vDj23O0AY9L5KPvX+bn/zXCq796Epvb9fjNJ+4AQRDoemY/ta3VfPaja7z9//uQ9v4Wjr7ajyeQF8nlJiNYzZbHRgQNTA2xEo4gKDpzc/NEp2PIKRnRJJJ15PAe9fILX39zR9m5BgYG6zGE3dNMCUNas5TFpIvIsorVuvFlsFmu6m6h6zoLE0vc+vAuixPL+Ou8vPhLJ2nrbd60yiCKIn1HG4ispJifi+MP2LFYTORyCuGVNC6Xlb6jDTuuVjxaEU3nNEJJjWBCZSWhsZJUScgCqDKCRcXpsOKxm6jxWOiok3DZJBySjENL4Hr2OCZH5aw9dF0nJ6uk0lkSyRzRRJpIcIXwfIr5jEBmXgA07BaRep+Zeq+ZepeGR09j6v9KSbGkxYNok9cqdq5F70OBinMd8NrxDO++NcjP/583OfedPhzH3nyqxB2Ar8bLG//wFUZvTnD93Tv88D+/RXN3Iz0nD1DXVvOFZq+WSy4rszwdZGF8iU8/uMzi1BIL+gJWjwVnoxNfkx9HrR1REnEEnMU9HA0MDLaFIey+pNit4PPYWF7JUl0jrWvH6rpOLJqlts6Fw7l3ba+lqWWuv3eHxYllAg1+XvnVM7R0N25pxq+pxceZV/czcGOe5cU4UTmD2SzS3OKj72jDlq1OHkXXdSKRGLNjQZZTIksJgVg6XyGzmkWqXBba6zR8Uhqfw4K/thqzfWN1S8+BnhaRKtwSEwQB64PWrN/rpAU/eqsbRbwFNg8p3UowliMUl1mI5Lg0kUWVZRxijjZ9gdb2JhrrfJikjeclyJnyFiwKJE9siSIV56oWL69/x8M7P7zPO98f4I0DL2LzP13CDvLPYefRfbT3tTB6c5L7F4f5+f/3A/x1XjqOtNPa04TbX7nln534y2maRjQYJzgTIji7QnB2hchiFF3XsTmtPNt3hKqv+qnfV4vTt/F9YMzGGRhUHkPYfUkRBGhqcpNMJwgup/B4rZgfbMXGolkcDjNNrb49WZxYWQhz/d07zA7P46/3cfbXztDctTVB9zBNLT4amjyEllNkMjI2m5mqGse2P0ASySwzC2Hml6LML8VIJxLoi1kCPifNdU5qvRZqPGZctrxA1nNptNgiggCC9HgsnkBeMLisEi6bnfbafCVXVjQWg3FmFsLMLcUZnL6H2STR3lzFgX211Nd41p4HwWxDbDiYz5MttmCRieaFWSZe+CS2YvFSoOIcaLBz7tsHefv7d3j/Ly7yld9646lNGjCZTXSf2E/XMx0sjC8xeHmEG+/d4erPb+Kr9dKwv47alipqWqpxuLcenwXl+8utZhvHgnEiyzEiixFC8xHCixFUWUUQBLw1HqqbAhx8rpO6thrcAddjs3hlYPBlwhB2X2I8Xivd/a41H7u4ksVsEqmtc+2Jj10ikuT6e3cYvzWJp8rNi790kva+lop8GIiiuG1LE03TWQrGmJoLM7MQJhxNIQgC1X4XB9prqfc2EJiZw+ou7Oe2jlIWI48BZpNIU8BCo92GdKSfaM7ExEyI4fElhieWcDttdO2rpXt/HTYA0YxgsRcWdmoOfWkE5fZbRcVbJSxe/FV2Xnm9mfeuRzj/g0u8+N2TT7WAEASBho46GjrqyGVl5kcXmB6cY+ruDPcuDAHg9Drw1njwVLnxVLnW5R1bHVYkk1jQ7PnOxCCxWIL9NS0MTo5z/tPLHGnpzWcax9IkI0kSkSTxcJJcOt8CFkQBT5WbQIOftt5mAg0+qpsCT91Si4HBk4oh7L7keLw23P11e5o8kcvkHgTAD2OxmTn5zWfoPLbvC23JKKrG7HyYydkVpufDZLIyDruF5no/R3tbaKrzYrXmP7j0TBxlYZPHR5TA6kSXs8WXERyenbctK4ggCPi9DvxeB0d7m1kMxhmZWOLmvVlu3Juhs9FNT1bDW0zLqvm8WcFszefJPkoFLV5q6hy88O3jfPw3t/HV3uPwS707Ot6TgsVqpq23hbbevK9fMpZaa4PGQgnmxxYZujKKpmobflcQhbXqpq7pJDJJ7kwMYTWZiVkiZHNZ3lUWmG9ZwON04/DYcfmc+Ot9tBxswlvtxlvjwe13PbVVUgODpwFD2D3NlFktEgRhTyxNdF1n9MYE1965hZxT6DvTTd+Z7i/sm76qaswuRhifDjE1u0JOVvB7HXR31NHaFKBmB60kQTIjdb9cujIlfS4US13ni1gQEASB+hoP9TUenj3cxr2RBQbuTXB/KsmBBo2j+304rY98uK8mVkjWoks7xUTudmjraSISUbj5/gB1bTXUtdVU7NhPCk6PA2evY03oQX7uLZvKkknm/8mmcyiygqpoqA82pgVB4PrYHfx+PzWBALOxBQ407CeUjXGgdz+vHX/hqa6CGhg8zRjC7mmkDEPava4WBWdDXPrJdYKzK+w71Mrx1w/j9OzcdmSr6LpOKJJkeHyJ8akg6ayMz+Ogr6uBjtZqfBU8J8FsK+nntpfpFLoqQzpS2Fz4QcZrMaxWM0f7WujrCHD3vQVujqwwupCmt9HC4WYL5tU5QjWbr8TtcjrFKrqc4dDzLSwMT/HR//qQb/3TV7E87FH4OEa27QGiKGJ32Qv6wa2yHA0RDSfpauhgKjjLdGQBj+imtaWJ4eVJjsR6jexVA4MnFEPYPYUIZhtSz7nHIqc0m85y/d07DF8dw1fn5c1/dJba1r2vrGRzCqOTywyOLrISTWK3WdjfVkNney0B30aT5rLY6fzcHqVT6JqKvjKFnlwpfiVnAF1TKfUomO1ODn/lmxx8KcPtoQXuDC0ytWzmzPE2Gms96Jk4uiAhFDCH3hYlHl9dlVEHPwQlx8kOmR99f4zL/3WS519oWLvanke2PUGsGh1LgsjowhQWyczowhTV7oCRvWpg8IRjCLunFMFs2/2oqhLous7EnSkuv3UDVdE48eZRup/dv+dzdMFwgnvDC4xNBdE0jdamACcOt9FU70MskrKwKWVWRHVNhRJtVl1+IABL+A1WonUpiBJiVStUd4DJuvEKShZ0BaGMSptgtmE12zjxjI+urjY+uTzKWxcm6O6o57meKoRKVIHLeXytDsglEawuXDVejr8Alz6epr1XpL7JvSaK9cwmhslfwqrew0bH92ZGCCdi1PmqWYwEuTczQldTh5G9amDwBGMIO4OKk4wm+exH15gdnqett5kTbx7d07arpulMzIS4OzzPYjCGy2HlSE8TXR11OCpghlpORVTXVLSRT0q2WTGZQatsSkPRywFMpWbfirdii+Fx2/nq2T4GRxe5dHOChfklXnGp+LbnvLFGWY+vnEEdeHtNFHcdbWZiPMHVi0t87Vdq8pXHbAJ18ANQih/ny1jVE0WRN46+xNzKAulshp7mTjwOF7FUgkQmxVeOvEBT1c6NvA0MDL4YDGFnUDF0XWfo6hjX3r6F2Wri7K+doaW7ac9uX5ZVBscXGRicI5HK0lDj5bUzB2ltDGy/OleETSuimfimbVYtFWWn8+nlzOnpAuizA0XbpLqSQxDYVsarIAgc7KynvtbDux/c5Ee3UrzUa6J1Y8zplixetlpxFgSB46dbeOuv7jExFGJfhxM0FT0dR3R4d7XV/SRit9qYDs6j6ToNgVoAnDYHg7PjTAfn2d/Q/sWeoIGBwbYxhJ1BRUhGk3z6wyvMjy1y4JkOnnn9MBbb3kQFZXMKA0Nz3B2eR5ZVOlqr6e9uosrv3JPbL4am68R1M3FFJK6oJBSVhKqRVjXS2QypVAZFByUcQhZN6Pr6iTKzrmJWMlhMd7DbXTjNZhxmCy6LBZ/Nht9mx4OMuNmcXmwRPZtCcAbyea+Pous7znj1eRx849xhPvzBOO/djnEylaW7fuPzv5tLOzX1Llo7/Ny6Mkdbe+fn84K73Op+Elk1Jq73Va/7eb2vuqRRsYGBweOPIewMSqKlIgXjo1bRzXYmR2Nc+sk1TBYT5/7eSzTur9+Tc1sVdAND82iaTldHLf3djbg3CRTftHWpqaXnzVaFyUPHSORyLKdSLKVSBNNpVpJxVuYSaCZ5be7MIYm4TBJ2ScRjlqixSphRsNhEzBYLDxcVdR1kOYOcE1C9XrKimZQsMxePkcjlyCgPWqdKFk8wSZ1LoM5pod5mps5qRnxQClwnFSUzQoEZO71E9uhWsDqcnPulX+TC1VEuji2jO5vpP/DIa2GXZ9r6n2ngJ395l+nxKK21u3YzG9jsNfW4zfKtLk/4nR6Smc/f3yZJMpYnDAyecAxhZ1AULRVBfvc/Q5FtylxO59JdiRnpCB3PdPPcV49itRcYzq8wsqwyMDTH7cE5NE3n4P46Dh1sKmt+brPWpa7K6CtT+WUDsXBlSTNbWc5pzCWSzOdUFnIqSTUvoayiQLVZpMFqocctUeXx4nU4cUkSpoeUm55Lo4ajsDSOnhRALPBW1BQEyYS5/hcQ3es3idOyTDiTZiUaYiExzpKiMboSR9V1rKJIq8NCm8PKPpPOXkasixY7p0/2YXVOcenuDGa7m4OdeyP0AapqndQ1url/e5nW1zx7cpt7aVtTCR5enggnN56z1+k2licMDJ5gDGFnUJxcKi/qTHZ4pJW1vJzj00+C5LI5XvwXvXScPrHrp6OqGsPjS1wbmCaXUzjYWc/hMgXd5wfZxGIkHcnbglR3rEtPiMgqk+kc08kk0/Ewsg4mi406u42DTjN1FhO1VhNuSURQs+jpKLouItotCObSbzPhof8tF7vZjN1spsEs0O2zIdi9aGYbS1mZyVSWyVSWd5aiiJpCm6rQpZppV2QEpUDrcQct2EIIgsAzh1qRZZUL18ZwOqy0NPorehtrFLBE6Tro4eOfjRCNWPF4N/mioZXItYXyKm17ZFtTKVaXJ3IlKrVWs9UQdQYGTyiGsDPYHIsd8cFQva7r3L0b5+aNJAGPjddesODvbSz565VoU03Phbl4Y5xYIsP+thqO97eUbLnqul46Jq3Y3NUDA19dsrCoSYwlM4wls4RlBVEQqDeZOOY00WqTqAvUYbJunFnTcwIQzVf/ChkCP3Q7Qt0BBEdV0XPRc8myqzySINBgs9Bgs3Ay4CahqAyFo9xbjvMTxYsjJnI0l+WwVcXysI5UlbzgqODsmyAIPH9sH4lUlvcvDPLNc4fweys481jCEqWpFiwmGJ1UOXa0eEtdV3No8/fRVbUy2bZP0Cyf3WrDbv3iRaaBgUHlMYSdQdlksyoXPl1hZiZNf7+H/m4RMRMu+Ts7bVNFYiku3Zhgej5MY52Ps6e6N12KiEUzzE5FiKykkBUNs0nEF3DQ1OrDXaKAo+s6i1mFwayV0fk4SSmHXRLZ57ByuspNi92CWcmixbIIAiVNjXVVRl8aRmOkcEtXk9F1HaH+AILFXlAQAKBuf/7NZZI45rVzVHSw5K7ijuLgUlbnuiBw2GXlmNuKVRRAzoCaqXibUBQFXjnZxd++e4v3Ph3i268fxlShjNFSligmoH3xBrNj8xwT5eJGx9nUnmXbVoonbZZvqyxHQ1wbG+B4R5+xvGFgsE0MYWdQFisrOT76KIic03jlbA3NzXa0Ui2sVbbZppJllRt3p7kzOIfTYeXcmYO0NgU2TYiIRTMM3lkglVbweK24zRKyrLK0mCARy9DV6eLRGltCUbkXT3MvniacTGBTzHTZzXRVV9Fg+3wRASgsEEqgl/itikZxbpLSUBWZ5GUEnsHMjZyJq2ETtwQ4Zc3RI2YRTaZt2Z1shtkscfZUFz98+xZXbk9x8ti+ih27lCVK66H9DN+cJpa14hWyhStmqxFoZscTUWl70mb5tsPA1BCXhm9gNZmN5Q0Dg21iCDuDTZmcynDxagSPx8xrr9Xidm/jZbOFNtX0XJgL18ZIZXIc62uh/2ATJmnzeR9d15mdipBKK1TXfB4TZrWaqK6RCC6nmJ2N06kDus5kMsOtWIrJVBZJENjvtPGyw0lDNoHJb0csMbunqzJs0mYVN2uzpkJFFzTKpqyUBg8IIoKu4xbhRZvCMYvKhayZ99NWhiWBVx0qu1Uf8XudnDjUxqWbE3S211Dtd+3SLX1O/b5aJLOFZUsPVUdbC16n4hFou80TNsu3VVYtWAIur2G5YmCwAwxhZ1AUXde5OZDhzkiOfZ1+Tp4KYDJtFFi6nC06gK5n4mWnK6QzOT67Ps7YVJCmOh9vvtyLx11+jEEqKRNejuK259uLj1aw3HaNpaUEITXHMGGiukiN1cwr1V66XDaskoiWWEHbpJKmqzIsDaOLkwimjcJMV2TQclB7ALFUmzVrRi+jBLiWHFEEsfOFkvYsupxBV3MIFufauXiBN4GedI73FsN8T87yRiJNV2ULdmv0dNYzOLbIZ9fG+dqLnQhaiaSLCrQTTWYTVY1+ludi9JwufqcqEoG21zxBs3xbYWBqiGQmTXfTPgZnxw3LFQODbWIIO4OCKLLCJz+8wfj9HEePeOg9ZEFQkqz7PM6l0VUVdeQ8mlC4oqbLGfSlYcR9zyFQXKRNzIb59PYCAC8/38X+tupN266PIqdT5GYHcVjSqI+cTlrTGMzmuJ1WqHLn6K9y8rrPSb3VlL8dNYuukm/PASjZwosPSgY0NT+XZrWgF7IpQc5frqnlnXiJNiqaXJFYLEEyF5zla7fY+XWriXfnl/jJ6ChRXeREQ9OWH/vNkCSRk8f28dZ7N5k6/1Oa7MXFaqXaiTUt1Uzdm9nRMbZEqefRoCSPGiYbRskGBtvHEHZPKTsZsk4nM3zwvfOEpiO8eLaelkAK0oWXJASHF5QMgsNfuD2E/uBcCoucrKLx2VCaidFR2toaOP1Mx7bzXE2ihklJIIsiVlu+EpPSNO7mMozlcmiKxj5Evt0UoNaqgp6CzPoJOF1VwBkAXUFPRwvfZ6cP3eJERy9YedLR849tKZNjAFFCsDjQ5SIzYAAWJ3o2iWhz7Vr7zSqKvOm3caWukfNTUyRyOV5p21dxcddY56XGb+f26ArNx4q8XirYTvTVerj7aRI5J2O27GJlrpx2+C4mbjwNrFbrmqvynodep5uFSNCo2hkYbAND2D2F7GTIOh5O8M7//RFyVubNf/ImAf/XSydPaBra0Eeb2ocUYimS44NbEbJphZe+uo/OrrYdiQm7WcGTnWI5bMfpULinw4ief5H3CBBISzQ5MtT1fwXJ6Stxn0onT+hyBlWVwezc2fycaEbqfqVkZerRsPsNl0NF2m+CIHCqsRG3y8d746MAnG3v2PFxH72NQ131vHP3GqG0RHXV7rYTvdV5g+JYKEFVQwkfvR1W2kpt6K7xhG+r7iZGvJmBQWUxhN3TyDaHrEPzYd77nx9jtpr56j9+DffqkLvDV/Sm9EwcrZxzeqi1qes6t6fTXB9PUu2EN4868bVV7bhCJGgKNbYwV2QrAzkLVpNGn0lgny6SyZmxW9I02sOIklRy+7OssxALtzbXWJ2feyAadF1HQUNFR0d/8HMFqyRhsboqXh3bgLaJp54mo8sZ+j0O9MZ63pucxCfqHK19KJerAuKktcGH3Swyspilepc/q53e/P5zKpYqLOwqWGkrtaFrUBoj3szAoLIYwu5pZgtVnoWJJd7/8/N4q92c/fUXsG+St1o2opT/wHuQxpCRNT4eyjAXUelvtnC0xYLJ5d1xm0rXde6Hw3ysWYg4cxzRLDTJdiRFQBOhxqPQYE/j1iqTi1ro9jMoxPQ0MS1GUoqSMomk5GVysoaMumEpQzBbEYLvI4gmTKIJm2jDaXLiNDlxm1wELH7c+s4Fny5nHhjxKkWjyxAEEC2ATg8QSmb54PIQ3io7Lbb871Ri9k0UBfbVmBhfyvLcQR1R3D1Ba3NaEUSBVLxw5e2JrbQ9RbN8RryZgUHlMYRdBXlSzUNnR+b54HufUttazSu/erqi80iCyYJQfxCp73VWMhLvXhhB9mi8eW4fTXUPTGF3+LgEUyneGx9ldnmOdlHlF705fA6ZdE5F1gTMoo7doqFnFSjeVd4SChpRPcmKEmNFTxHR02T1/LydpKk4BBVXwzHqLR6sohWzaMYimpEQEQQxXxWUTCiihKIryJpMRs2QUJMsZZeYSE6g6RomTcWrzVCbTdKk12AX1j83ei6d39Itg1LRZbquoWdjiK5qMNk4Y9MJEuPdpMqve91YtVzFZt9aAybuLmmsJGSqPYXnKTfbBC7nNSOKImarGTlTXMw/UZW2p3CWz4g3MzCoPIawqxBPqnno1P1ZPvrLCzTur+PlXzmNVKFkgIcRJDPjyzKf3JzC63HxtTPdJePAykVWVS7NzXB1bg6fzcYv7t9Hw8JbINkRBHBY1zeJV6scpexZgKKiIaEkWMgsshCfYIlJdFnEpFoJCHbaBRcerHgFGw5dBXKYqk9u2/BX0RQicoRgZIzF6McMSDPcESWqVIlmxUyLbEZEyFurCHpJc2HBbEOoP7jO7uRh9FwaLRnKW388qPJKwLkGC/9zJsincYWzXlvFZt9q3BJmSWduJVdQ2OmqjDr4IZT4sC/3vWS2mFDkMreTH3Oe2ArjJhjxZgYGlcUQdpXiCTQPnRle4KMf3KSlu5EXvvs8krQDUVekPaTLaW5MZbk1Okbn/ibOnNhfkVipuXiMd8ZGiWYzPN/UzDONTYixBWTIPxdFwu43s2eB9aIhqaSYSc8wk5ohJscRBZFqk5c+WwtVGRW3akFcq4LpQHrtGDupnJhEE9XWagLWHPuiIJucLDgkZk0yN205hq0KXTkbTYqOuFmlmOJ2J2uXZzaeq8ds4qTfzSehGMccEgVCt7aFJArUuHSWVhLojY+8FlbtZDKxfMzXDt9LoiSiqWVNgT4RPFEVRgMDgy+EHQm7//gf/yN/8Ad/wO/8zu/wn/7TfwIgk8nwr//1v+Z73/se2WyWN954g//yX/4LdXV1lTjfx58nxDx0fibBR3cu03SwbWeirkR7SNV0zo9kGIuIPPtKG0cO7dxCQ9U0Ppud5srcLPVOF7/ef4QqR35IXpPMD+b5lMKbvKoCJgvkkggPWo4bUDLIqQgziXGmlCCh7AqSKNFgq6fHc5Baay0m0YQeeG5vKicP7pNJh5acREtOIiaq3LdkuW6NMyzqHMpYadyl9lu/x8HVSIKr0RSvlo7oLY8HrxefdYnplQR6gX0Owe7OP38VeC/pml7h7DYDAwODx5ttC7vLly/zJ3/yJxw+fHjdz3/3d3+XH//4x/zlX/4lXq+Xf/Ev/gXf+c53OH/+/I5P1mCLFKmiLc2E+PCdWRpOnuGlXzq5o0pdsfZQTlZ578IIS+Ykr36jk/0dTdu+jVUimTQ/HRkmmEpyqrmVE41N63Jc11qOkgkk68ZzVbNomcS6luPDpPQcY1qUSRZQY1ZqnU08EzhOo60B0yNLB3tVORHMNsSGg+usVfzAKSCsp7mTm+GiGqM/N0eXvnVT580wiwLHfE4uLIc5bTex0zCw1ddLlXmOwWuTCIePIz0yP7Vm8VIBVFVDKiOOzsDAwOBpYVvCLpFI8Bu/8Rv86Z/+Kf/+3//7tZ9Ho1H+23/7b/zZn/0Zr776KgD//b//d3p6evjss884efJkZc7aoDQlqmgrwQzv/WSS6iZ/xWbqHhU5mazMzy7cJZZQefO1o9T5rduaaXuYoVCQd8ZGcZjN/ErvIepcBSSGZEZ0Vz1o0xWazxIQXYEN1by4lmFYXWZGiyBpKi246ax6EbervuQ57RlFrFUC2HkBG/cyEwzEB4kJMsd8RzeI0J3S7bJzfinMaFrhSAWOJ5htOLw+dNM8OcGOw7Z7Wa25dA7LNg2vDQwMDJ5EtvUJ8M//+T/n61//OufOnVsn7K5evYosy5w7d27tZwcPHqS1tZULFy4Ywm6PKFZFi4eTfPD+R/j7n+XVv/8yZkflw9hT6Rw//WCAbE7ha2f7CbikHS2VaLrO+alJrs7P0VVVzWv7OrCaCr9syxkuf7galNCz3FcWmdUiWAUzvaZ62nAgyXFMpkr0HXcfQRDoIUDAd5RrqSHSoc94ofo0YqEZwnJsMgpcxwk0WWAkLVdE2AHYrfnWcTojbztpZDMUWUFVVCy2J2dL1MDAwGCnbFnYfe973+PatWtcvnx5w2ULCwtYLBZ8Pt+6n9fV1bGwsFDweNlslmz286pSLFZcABiUz6NVtGw6y3t/9QkWp4vX/uFrWB0bW5U7ZVXU5WSFr7/aj9dtzxsYx0NF26OoWbR4CKnAIHxGkfnp8DDTsSgvt7VztL5h01ZjOS3SHCrD2iLjuThWwcRhUxOtoh9JENHVdGHx8wh7aW2jy2l0XUOQNw6k6XIGlCxNtgbs9io+CX7KrehtjvoekmDl2GQ4fYCQNysucJ0Wk85VxYwmmqjE3vSqfYWm7d5iQyqWf7wcnuIZxQYGBgZPG1sSdtPT0/zO7/wOb7/9NjZbZT60/sN/+A/84R/+YUWO9VjwGJqHqqrK+9/7lGwqx1d/61VsuyDq0pnPRd3XzuZFHeSFh75wH10XEEwbKyfF7Dpi2Qw/uH+PlCzzCwd7aPX60FIR9BLxZlgciKVSMnSdidQ0t5lG16x0WxrZL9VgKrEhW/A4cgbl9k8hVTg/FwCHH+ng2ZLRZOWIPy0VRb3/PsgZKOTlpWlgtiH1vUFVoJnDvkPcCN+kylJFi6MZKN8mQ5czRePjGuMJPpuYIazoVFegwLZ6VzS9hIze4XspEUkC4PI9GdVXAwMDg0qwJWF39epVlpaWOH78+NrPVFXlo48+4o/+6I/42c9+Ri6XIxKJrKvaLS4uUl9feF7pD/7gD/i93/u9tf+OxWK0tLRs8W48Bjym5qG6rnPxx9cIzoT4yj94GU/V9nzVSpHNKfzso3tkc59X6tZQ5bwosbrB4ihwgknIxteJjuVUkh/ev4dJFPk7fYfw2+1oqQjyu/8ZkivFT8QZwPzavywo7hJKguvhGywn52jGSY9ej11zgZZdLx7KEA16Jo42fmnzJIdcBkrU/8ryYlPlvJ+bIBXOntUfXP7g8dvnbGcps8xAdIAGW/3avN1mlUxdzqCNfFK0Ze5TNfQVhUiih2pHgedxiyhKvlJnKrS4U6H3UjQYRzJJa9FiBgYGBl8GtiTsXnvtNW7fvr3uZ7/5m7/JwYMH+f3f/31aWlowm828++67fPe73wVgcHCQqakpTp0qnPVntVqxWitfQdprKmkeWsk23/1LI4xcG+f0LzxLbWtNWb+zFRRF5e2P75FIZtZV6jYgmRFMG59n/RET2tlYjB8O3sNns/Ht7h6clgfloVwK4svokgXMBW5DTiPEl/PXe0jY6brOWHKcgdhdrKKVM9WnCKxcgVQYPZMsfK4Of2nR8ECsClY3gnVjNUjPJtFTK+jpCKKndkdebILZiuCtB5sX0bZxJlLLJCATzfsnPqDf28s7i+8xkhjloKe7+P145D6V8mF0yGlEJUQiU5nojtwD02CLZaOwq9R7KbIUxVPtNlILDAwMvlRsSdi53W76+/vX/czpdFJVVbX289/6rd/i937v9wgEAng8Hv7lv/yXnDp16kuxOFEJC4xKJlgsTQe58rMb9Jw8QOfRfTs6r0Lous6HF4cJhZN89WwfgR22vGZjMX4weJd6l5tvHOhetyShy1m02EJ+Q7SAsNPlNLomoz9U4clpMtfC15hPL9Dh2kefpxdJVVDQKdUBFMqasqM8sVoBLzZBlMBkKXhbgimXz+N9CKfJSZujlYnkBN3urq1ZoBQ5XwCrKJBVK5PikHoQ82UrEl9XifdSaC5MoN63o2MYGBgYPGlUPHni//g//g9EUeS73/3uOoNigzKpUIJFOpnho7+8QHVTgOOvHy56vZ1w5dYkk7MrvHa6m9odtnhnE0n+Zn6aBpebb3YdxPxoi06TQZHBZi8splQ5X63T8lWeSC7CpZXL5DSZk1XP02DPjwLouTTkMoiOEqkGuczmqQaaiq7kCiZc6Eoun57wBdLsaGI8OcFKboUqa1VFjllJh7x4IoPdZsFsrnyEHYCckwkvRug60bErxzcwMDB4XNmxsPvggw/W/bfNZuOP//iP+eM//uOdHvrLzQ4qPbquc/6vL6GpGi/98qmdRYUVYXhiiVv3Z3n+6D7amssQDiVivpZUkb8Zn6C+urGwqHsYUSrcJn2oajWXnuNK+Bpuk4sz1adxFrIu2cnju1o9TITQilQPUTaP+dpNqixVWEQzS9nligk7Va+cuIvG03hcu2fwvDwdQtd0alurd+02DAwMDB5HjKzYp5B7F4eZG1ngtb/7Ik5P5QfHg+EE56+McqC9lr6uhtJXfhCJtVZRe4SIrPAj2Yvf7thc1JXBeHae2ysRmuyNHPcdq7hZL5CvCspZsJqh2EatnAX9i8soFQQBl9lNUsnPEW42t6nLGdDkfEWzAEo2RVZVcJgrs/wTXEnS3OCryLEKMTuygMNjx1vt2bXbMDAwMHgcMYTdU0Z4Kcq1t2/Rc6qLps7Soms7SxrZnMJ75wfxexycPrG/LF85seEgCCZ4pIWa1XR+Mh/Gatb4dncPlh2KuhGXiaH0KAfqnuWQt7/i8Vqr6EoWMjHIZdBNBRI1lCwo2fzWbKXIpSkoE4sIMQCn5CClpsqa29QF0Gfvogsigmmjn0ksJ6Mn7TiEnYvVTFYmlkhTE9id7Xdd15kdnqdxf/2uvQYMDAwMHlcMYfcUoWkaF354GXfAxfHXDpW87naWNHRd59Oro2RzCl8924epnAxOyYzg2hjzpes6Pw9lSGnwK20NOGxlVhbVXEEvuxGbzD27mV5bC327KOqAByqIvIecVkC8rZnu6jv3NbQ4wBnI27woRUScM1DQSkYQHqyBlDG3qUUXIZdEsHoKWrisaCqoClUVmImbW4wC0FC7O9W0yHKMWDDOia9UKifDwMDA4MnBEHZPEXc/HSQ0F+bN33p18wzYbSxpjEwuMzYV5OypLtzO8uajillXXJibY1qb51udnVQH8nNQpfJkdaS8zUkus8EiZcIhcs8u0ZUS6XH37HqVRrA6wVWV39AtUN3SlVxexNq8aKkoEC18HKdvUy820eHD/Nq/LGocDBQ1ZtZ1HeHhqbhSc4WitPY8CwXE6rIqYjNJuMoV4CWYXYjg8zhw7oJRNsDkwDQWm5mG/XW7cnwDAwODxxlD2D2ubLHSE1uJc/ODu/Sc6qKmnGUGHmySSpaCA/G6pucvf0AyleWza+N0ttfSsUU/vEetK2ZjMS4vhzjZtp99dc1lVQ9BAHctgi7n27oPWDZpDLgVOjI6XZJjnZ9bSXZQSRPMVnDXIdhcCNYCebvZBHo6iiCZEYRS1inlCVDR4VvnzVcuKTWNXSpTgEtmqDuA4KgqKP7mZpZp0HKIRaxQykVVNSZnQ3R3FDYs3ym6rjN6Y4LW3uZdWRoyMDAweNwxhN3jxjZc91fTJewuG0de6S3rZrYS9YXVxfmrY5hMIiePtm/rbq2SVRTeGh2m0e3h2aZ85FVZrcJEEMFkAsxrrcKkqHHVlaZasdErS0jlDPZXINVAl7OQXM6LtwKWKLqcATmDno0j+ptK2KqkN7dV2QEJJUGNtfytUEEyI1jsG4RdVtOYVwRecu48S2x+KUo2p7CvtTKbuo+yMLFEMpqi81jlfRsNDAwMngQMYfeYsR3X/ZmhOeZHFzn7a2cwPzB83XQLMpMoO+pranaF6bkVzp05iNW6s63IT6YnySoKb/T2Iz7aMi3RKhQkM+JDFSVN17mhTWBH43mxHZOcAzm5qWlzRVINVrdiLSJaoc1XXfl8gULTi1ZEVz33doO4HCerZvGbfTs+1lgyg4ZOu23nfy5GJpbxuu1U7VJ+6/DVMTxV7rKr1gYGBgZPG4awewzZiuu+qqpc/fktGvbX0dzVCJS3GIGuomtqvkpTIj1BUTQu3pigpcFPa1Ng63fmIWbjMW4vLnK2fR+e7cTIiZ9XlIaUBWKovGjej0V0oAtpdDW3+THYeaqBrmmQTeX/MRV4jBUZNAVtaRw9sVJ0Dk8Q8s+VYKt8fu98ZgFJlKi2VkMu/cBupvDyhf7g8kKVW4B78TTNNjNu085mFzNZmYmZEM8cat2VOchUPM3k3Rme+coRYxvWwMDgS4sh7J5wRq5PEF9J8PKvnPr8w6yc1mZsqSyftXvjIZKpLG+83LujD0td1/lwYpx6l4tDdTubr4prGYbVZbqlWvzi1of5d5rFK4giWB35ZY5C1c5cCjJxkNOgF94yRc/mr7cLJsa6rjOdmqHOWotJNKGttt1VBcQC4k2T0dHR6w4gPDJ7GJZVZhIpXvPt3L9ucHQRBNjf5Cm5KLOVLOR1x788gmSS6NzhuICBgYHBk4wh7J5g5JzMrQ/v0n6oFX+db+MVSm1BrlIiESKrws3hJQ5278fr3tnQ/GAoyFIyyS/3FWjBbpEBdR6bYKZT2toSB1Qoi1c05z35RBNiAYNiTTTlxVwqlK8ilpltWymCuRAxOcYh7/pcZ/2h/92AICJYPfnzeeicrocz2DWFAxYTgsO76RZvMRRVY2B4ns5mH5bxD1EqkIX8MLlMjsFLIxx4pgOLbeezgAYGBgZPKoawe4IZvDxKNpXl6Nm+rf+yKJZMhNBVmYGIC90vcqS3eUfnqek6n81M0+H30+TemXfZip5iQY9zwtSKVCz1oRQVyOLNb8XWgMUFtgJbsZkEROcgFQbRVFa2bSUZig/jMbvXFifWTKLNzsJCP5cGOYnUt15MxXM5Bu/c4bmDDdgaGrZdSQMYGlskk5Xp31+NPnp9x1nIj3L/0giKrNJ7qmtb52dgYGDwtGAIuycURVa4++kg+4+24/YXEBeb8OgywqNkU0kGp0P0HmjEYd9ZBWRkJUQkk+GrnZt86JZhQTIqL+KSRBoVC7qaLnidsthhVizxZZCihcWHnIFMdK3VXcrwpNIsZpZYyizxXNWz61vnYuGN11V0NYdgtq2b97s0N4LFaudoS8eDjeTtIcsqNwam6Wyrweu2ocCOHv9HyaSyDJwfpOvE/l2J0DMwMDB4kjCE3RPK6I0JsqkcfWe6t38Q0YwgFm6LDi/JqLpIX2ft9o//gOvzc7R4vdS5igjQMixIcPhJ6znm5DkOqdVAbINg2sympGJocr6iZLKgF6oaCoCmgiCBpiIUaHXrmpo/10Izb9s9LV3jTnSAKmuARtsmGb6bEEylGFhe4qXWdqw7EHUAtwdnyckqx/pbgMpXKO98ch9d1zn0Uk/Fj21gYGDwpGEIuycQXde5d3GY1p4mPIFtblSKEoLFsWGmavX492eS7Gvy4HDtzJYimEoxn0jwja7iArRcC5Kl5DhSVKK95jVMhRYSdtAqXIcml07B0DQwmUEHocACiq4DJgs4Agi+JoQC7Vohk4BMtHxD5TK4Hx8krsR5pealHS+6vDs+it9m3/GiSyKZ5fb9Ofq6GnA7beiZygq7eDjB/YvDHHqxB3uZaSgGBgYGTzOGsHsCWRhfIhaMc+qbJ0pfsVRrUzQjdb9SUAjNLcVIjg3R+1L/joXSveASdrOJfT7/jo4DsCivUONswuLY+bGKoas5tPn76Kpa9L7rupYXbVYXFGgnCrk0emolXxEtIrAEQcjHeFWIYDbIYHyIHvdBfBbfjo51e2mR+XicX+rtwyRuY47xIS7dnMBslnY8p1mMa+/cxuqw0nvamK0zMDAwAEPYPZEMXxvDW+OhtrVIqsAO0xVGpkJ4XDZqq7Y+u/cooysrdAaqkEoIhHI2VXW7m1BAoc93qOTtbWrMLG8yi6eqIGcQzFYEu3fj5UoGLboAqRX0+DJ6IXGmqSCI4G0AVSmc86oq+fm8CrSOU0qKSytXqLJU0eU+UPyKZcwwRjJpPp6apL+2lmZPgfu/CQ8//pNzYcbH53jp2X2Y1TS6WsbjvwXmRheYHJjmzC8+t2bMbWBgYPBlxxB2Txi5TI7p+3MceaW4r1w5rU1dU9FGPtkgplRNZ+JqgoP1FrT7IYQt2k48TCSTJpLJ8GJrW+krlrGpmkivoKp23ObiW7VlGTObLHkz3qIi54EQlqxFh/t1VQVFAcmUb7luOEYuL9yq2xC99SBtbLcKahZdVXZcEVU0hc9WLiEJEs8Hni1ov1Ku0FcFiZ8OD+M0m3mpbeuRXA8//llZ55PrSZrcIm2hOZSVB6/VTR//8oSfIitc/PE16tpr6Di8yevLwMDA4EuEIeyeMCYGptFUjY4j7SWvt2m6QiZeUEwtrOTIIbOv3rEt24mHmY7FEATKr/yU2JRMyxEAnKYSW4/lWJlkEwjWwrOF+WNk8/e3VJtUV/P/mN2I1o1VTS2bACWCaPcAAhRMxBAQ3VU7qtipusrFlUsklSQv1byAtYCAhPJnGD+cnWc5meRX+vqxSNtoEz94/DFZ+GxcRpWsnO7zI1ofHKucx5/ylmBuvD9AMpri1V9/wUiZMDAwMHiIJ17Y7TRF4EljcmCGuvYaHDs0DF7jETE1H5dxOq34vQ7IlKh8lcFyMknA7tjxViWA+qC+IwllCI5NrDSKzRYC6Jk4uiAVjAEreP1iFwgijih9DwAAR89JREFUUscppOoS1aQyX5uFXuOqrnIxcp1gboVTVc/jNZcWz5sJ/YGlRW4szPPqvg7qXTuLOBsOwkRI5eyhapwPvU7LefyBTR+Xpekg9y4McezcIbzVO/NFNDAwMHjaeKKFXUVSBJ4gsuksCxNLPPe147t2G3MrWZoCVgRB2LH/2nIqSY2jUmHvlXODe9SvbcPlm1XRBCmfLLGJlYlgde44B7bQa1xG4zKLrJDheeoJRG+g91Rv+zU+G4vx3sQYh2rrOLzDLdiVpMrFkSRdjW7aawt/+djs8S+FnJP59IeXqWr0G2bEBgYGBgV4ooVdJVIEVnkSKn9zo4vomk5z1+YeZdtZIpAVjUhSobelMmIskcvRso0B/ELYMIGmkE6FsBWpTlVyML8UgmRCd1WB3V88eSKbqIyViSqjxUMIkgkkKxld4TMWSKFwkhaqNQktHkLaZst8OZXkb4bu0ej28Er71ufqHiabU3jvfhqP3cHzXZV53h/lys9ukoymOPvbryPucGPXwMDA4GnkyRZ2q+zQxf5JqfzN/f/bu/P4uOp64eOfMzNn1iSTvdnTNN330kIpZSlSShERhEe8iAteRBSQy/WCXtwAryjPRZ5HkcV7fSp4FRVQWURoKdAWge5NS9e0TZNu2beZZPaZ83v+SBuaZpJMmqRZ+n2/XtFmzpmz/HLIfPNbvt+DtaRmu/vMrq8iQaI730D5WnveyWpHO62cVVNbBKUUmSk6dNQHSEi8IFIphS/QjlOloiLBAbeb01AYjVV46ttJpofVuhZ98Ep09TK5X8Wi0N4MIX/PlSeM8KDUgVWRIKp2H0pptFpNbHZ0rLBdHHCSYvgxohHQVEcb97MXrDUY4NV9e3Hb7Hxq0pReVy73xTAUazcdIhyOcdVsHXMsiIqddi/hQEcptTNUtfsoB7YeYtGnF8gQrBBC9GBsBHYDNYg9f0Op/kgj+ZMS6K0LtmFUbu5YmRmvsoERQaEwZZaA/nHvXKsnAEaUFEsEFQ4mFCT1FBQbShGtbkcLVBFrzegzKFaxCARaO+qWni4WQo9ESFKKRluUwng9dtEght/DgOfRJ7KC1OZAGRHQ7D1XnohGBifIjEVQkQBVSXb2uKK4DTsLwkk4LCfmGipfR7v5W1A9tW+c3ubWYIA/79mNbjZx3ZRpA5oHqZRiQ9khqmtbuDz9GK66oxhN3Z87NYAg1NPo5cNXN1M8o5CJ8wbWsyiEEGOZBHanGsT6lYMt0B6grbmdrMKMvneORTp6jWzJaLbuw6oq5EO1N6Dq9mM0VnXMFwNaa3UcXjOqopyYEe0YcuzrQ7iHoFhTCvQImkXvMyhWRgzVfATla+75PLZkcrPcHNaCzNFtmE8LqDp61zwd3wwglUYiK0hjLccxdq/uyHmnxVtZO3jlwkJGmG2uKNXOMBNVGtNjSZjMH0evRtiP8tYS3f02Jmdq3GOc3tvcGgzwl7170M0mbpw2E5d1YLWAd5VXs/dgLRfNyiFvrx9woOJVBuHEc9nPXrtIOMK6F9fjTHFw0XULZBWsEEL0QgK7UaKpphWAzPz0BObPnczFpqNZus/zUtGO9BtKdXQunfzfYETDpSs0zuCD87Sg2KQUFouViMkKxEv38THNZMaUUQSZEyDO9RINocLtFCg4SBtVRjOl5jjJmU1msLkGnEqjrxWkpqQMtMzxHaXF4h0rFkEzmeKWEuuP44FqtrduImIxWBBwUaDHCbANA6KRXhMqnxpY17W382r5XuwWC5+ZOp2kAQZ1+w/VsWlHFXOmFTClxEnkoB2lFJrRfShfodB0O8owei3ZdmoPo1KKD1/ZTHurj6u/eoUkIhZCiD5IYDdKtNZ7sFgtuFzmvpPwqhjKiPUanmkmM1r2REzu3M6ALBry4ADMk9wd86HCvjOeG6dpGi6LifaYAYl8Fpt0NIc7fo9pOACxEMkKijU3+6N1FJnS0E9LfaKZdcxTLhtQKo1EaLodc/4M0F09X2/kzNsuEAvwUetOqgM15Ohupnut2B3W3tuxl4TKJ4PcI55W/ra/nEyHg09PmYZDH1iQVHm0kfe3VDBlQg7zZxVBqB1T7tRe20UFWzEObcCI9hzsn9rD+NG6PRzec4wl/7SYtOyhWZAhhBBjydgI7AaYxX408DR4Sc1KQTOifc4HNLz1EKc4/ek0swXN6uj8EI7gx2kzffyhHDexbuKSLWY8kSgM4rTEKaYsjnOEHdHjzLcUdhuWG0gqjX4x6V3a7nTqDNouakQ50H6QA+0HsWgWzk9fQG4Iomplx5B3nNQqiQ5r7mxoYG11HUXuVD45afKZJSA+xeFjTazbcICSwgwumj/h4/Q4fbVL0AtBb0fvYh/zWQ/trWPH2t3MuXwGRVPzB3S9Qghxrhjdgd0Aa6KOJu2tPpLSTpkv19t8wDOk0TE8O1jG2XTKW4OQPHjF7h2azjxzAZujR0g1HEw0Zw3asQdbn+lXTjyXRjTEkcBx9voOEDGilDqLmeSagNWkYygP6PaOxSXxas6qaMdq4B5WtMaU4r3WILujh5mdX8xlxeMHtPoVOoK6dz8sp7ggg0svmITJ1L+hexWLgKHi9igrQ4ERofZwIx++upXSueOZfen0AV2vEEKcS0Z1YJdoqaSEh8RGSM9fvDl0vqYWMrLyOuYmJbrasp+9PJoGxiAGdjk2K1tjMTzhKOm9zKnqV/65aJA87ExUKewKHUWZQpRq6WixYVjc0tvzYkSIla/tWB3b09t1K0fwUhGpJ0CUfJKYRhpO9gP7OxLOWPSOIXOLPe78QxX0YETCaObuc+XaojFW1nqo9UX4xIxiZhdOOMMb/dihIw2s23CA4oIMLls4CbO5n0GiEUHVHcAwVcWt7qGiYVo9UdYeM5M9voALr50viyWEEKIfRnVgBwnURE3ECOr56yl9SKCiHEvycaI796DqD2AquQCNHsqKmUwdvTyRHvKGGdET9VC7fijbdBOBcN9DuHHFCXIKLQbmWJgDx44yX1vZc4B9sjB8b8c3mdGsH9cYnYYNhY1d2hG8qoXZZGBxpp6d3tkEnhesLlTIh8me1G3IMaAiHI7WUxmqJYxBvjWTyZZcUrTT2icaxAi2dwxbRsNxh8Y1TUOzu7rVtq3yBVnd4MEUM7gh00lh1sB7NvcerGH9tkpKi7O45PyJPffU9RrwxlDhIJrLiWbtno+xzRtlzZoWXPOtLPncRZgHOGQshBDnmlEf2A2GQe/5G4g46UMMQxFROvYUN5puPtGjF+vxEJpux1R8HlovPWFKt6PFIl0+hO2mKM2BcMfk/0R7KXsJcnSgRDcob7Mw3+pAs8dJKhsNogKejjHk3gICk96txugcID1QTZl3Fz5LMnPT5pB2Fn5GiTwvKhIktnt155C5oRSNqp0jsRaqlQeTFiVfOSlVySTrBT0Oq2vmUK8LQjpr22KgwgEihmJ9q4/t3gDjHVaWZthxDDCfnlKKbbuOsn3PUWZMzmPh3PHxe9ESCXjtKaCZ4q7Y9vmivPteG7qusfSm87HaB7ZiVwghzkUS2J0wKD1/g+mUOXQq0pEXzeJwgDmBYSmTjmX6lb0nBDZiGAff7/IhnKSFaWsLEfObMGlawqlBegtyZjVU89cN73BM2SnuaU6gqR0FGN66nk+UlIlmT+52T0X2KSS5stnaso21zRsoCOYzLXkqSfrAUo30JZHnRaFoVQGOR1s4brQSVFGSNRszLLkUYsdsNCaUULnXBSFmHVNyBsrvpc7nZ3VLEG/U4BK3jTkuhWZEBtTbHI0ZvL/pIBVHGlgwu5jZU/N7HBpNJOA12hpRh7d2e93vj/L26noAPnGJE7trEMqxCSHEOUgCu1Hg5Ly3Lp+n0VD8Kg0netr6LHQPaKd9CGfmeVGB/fgnziA12ZFwL2VvQU5xZi45NiubWv0UpaTEDQpULIKqr0AFep6HpyWlo2Ysi3s96dY0rsi+nCP+o+xrK+ft+ncpcBRQ7Cokw5qBKV51iF4MpG5wxIjQGGqipq2Sao4Qilmwaw7yTakUmFJJ1RwdK0hjAc5w0LsLTbcTm3w5G48doayujqwiJ7eMH0+G45Qg+gx7m/2BMO9+UE5jazuXL5rChKI4uQPjXE9vAa92cq7lKfM/A4EYb7/dRCxmsPSyZFx6nEUiQgghEiKB3ShwMhRSio65VLodYqGOIcx4+yfYQ3P6h3DmODuafpjGdkjLGpyUIZqmsTDFymueCOXtQaYmx5kXGA1DoK1jqDZemoxwAIJtHatCe6iuYNJMjHcVU+gsoNJXxaH2Qxz1H8VmtpHnyCXblk2GNR2bufeeoP7UDcZiwxfz4Yl4aQo10RRuojXSMazswkw+SeSYx5GpZ2AaogUAh1qaWVtViT8S4aKSiczPzR+Uc9U3tfHuB+UYSvHJy2eSnTFIKWTM+onnNwphPz5fjHfWeohGFUs/4SbJoUCzj4mV7EIIMRwksBsFzJaOHqdo1ECzWNFypmKecWWvw3Nn0kNjs+mkp7qormtlUkn2QC65i2K7hSlRjXWNXgocVpIsPUyItzowxbknAyAap3cyDrNmZmJSKaWuCbREWjjur6Y6WENlexUASXoSaXoaSRYXLosLl8WJVbOim3QsJgtaNEzM70Gz2DAsNiLEiBAjjEFARfDHfPj8DQQabHgJEz1RYcFpcZJhzWC8azxZ1kxcMUX0mBdNcw14VWe8VcMtwSD/OHaMytZWilLTuWHadFLtPSym6c+5lKL8UB0btlWSmZbEJxZPwekYvLlumm5Hy5mKZnXRHjTx9ocHIS2Fqz41kWS3bcCJsYUQ4lwngd0oYDJp6LqJSLhjwYRm1jvmmw1BIt78cansr6wjFjP6n8qiF5emJ/GHunberGvlM7npWPqZ+yxRpw6jpqGTZi9mpr0YfyxAU7iFppgXb8xHXaiOcJxVpioawtAq0TQb3Uo9aGDVFE6iJJsd5DrH49ZTcOtu7OaugYiKnRhyTCSFTh9pU6J7VncuhAkYis1tUT7yR0kyayxP1pngyEA3T0mofXoTjkRZv/UQBw83MLU0hwvnlQzqM3CSZtZpaQ7y7lvH0XUzSz9Viiu5I3jUTJr01gkhxABIYDdSnfZhb7dCwOuD6NBOKp9QlMlH+45RXeehMC9t0I7rUGE+me7g5ToPb9fEWJaZ1NGTNYg5AnsbRrUCuUDeKeWqwkYYfzRAREWIGBGiKkos2IZR24JmSsJksWPVzOh0fNk1HUskjIp4sLjn9B5YJ5JCx5UKaCdKkPWwitRkxThSRthQ7IjaKQvrKOB8a4Q51ih6SxTltaAmXzKgXq7GlnbWrt+PPxDmsoWTmTh+iBI/m3XqWjTW/u0AKSlWLr8qF7slgAp83CM7VpKKCyHEcJDAbqTpISCw61F8za2oiGtIP/jSU52kuZ3sr6wbnMDOrIPVjuFrZRzwCXuMVc3t2EMeLk62dCwk0B2AQkXDcRMqq2gYzeg5vUunOKliujilXBW6HavJitXadZhRmdqIkoxmcqOZz7yyR6IpdE5ed08CrXVs37+dMpVC1GxlZhLMdyicpo4AX4V8EGpLuLTY6QxDsXt/NVt3HiHV7eS6ZXNwx5sHOUiq9tXx/iaNnAUXcdn/ugDdGudX0NlKLSSEEGOQBHYjTE8BQdqxMppqPVjmLhm0D76eVn9OK3Kzvuwwnuk5pCTZByG/n9a5oneK00xI6bznjRAwFFek6phiUZS3DvytGHqcYCoSQBmRjuTEieit3FqixxgECafQibOPPxJhe20N26uqCEVsTHNpXODWST4t3Y2Knnk9X29bgH9sPkhdYxszJuUyf3YxliEYeoWOuXs7/7GX7e/uonTuBC68dr4kHxZCiCEggd0IFC8gSM0fR2V5A8rqwjTAWp/Q+7Dl+JhiS5OP7auOc9FkJ4R7Hi7VThnajCsWgaAXzLbOklizbeC0h3mr2Y+v1eBKsxdHNAwmHaXiJAExjI7SXANMtDsaNPh9fFRby76mBkBjRnoasxztJDl1TInkMOzBqUG8Uop9hxrYvOsYDpvO8kXjyc1JRxuioC4WjbHh9a1UbK9izuUzmH3pdCkTJoQQQ0QCu1EiPTeNWCSGp8FL2rjUgR+wl2FLHZhdDJsPtDIlNUhmVlpCQ5vxqEgQo2YfStGlNugE4NMxjTc9Jv4UDXOZJZUJKhS3WoZSBticoHcvQTVkzmLd4KhhcKilmY/qajnm9ZJktXJ+XgGzssdh8zUQ2TmwAr6nBvHNvhjrK4I0tMWYkmNlfr4N6/EqYi19BOhnyN8WYO0LH9JS28rFNyxkwuziQT2+EEKIriSwGyUy89PRTBp1hxsGJ7A7qYdhy6lFivKjHjYfjrA8x4bpTIc2YxGIBNFsyd1qg+Zb4Z80H2s8Ed50z2Gy280lmSkkndZzpCJBVDSIyenu7931X4J1g5UR68it19tx+giSGvw+9tTXs6+pgUAkSl5yMp+cNJnStHTMJ3plByOJMbEI4TYPH9UodlfHSHHauXpBMjmpJ+b4JRCgn4mGY02sfeFDAK76yhIy8zMG7dhCCCHik8BulLDoFrIKMqg5VM/UCyYN+fnMJo0Lxuu8tSdEeXWQaSUD7C2LUxsUwKWHucbazIE0G+/HrDzfHGWe28UctwvHiQBPhQM9JmM+nRH0QMgfN6hSkSCo3odzE6oDe2o5tp6O08MQdWswwP6mJsqbGmny+3HqOtMzs5melU2Gs5c2PqVSw+mv90YpxaGjzWzY5iOEjbkT05hZlITllGHdwZ57qJRi/5YKNq/cTkZeGpfddBHOIVyQIYQQ4mMS2I0iBZNz2bFuD9FIFIs+9D+6/FQzU3MsbKrwkZOVTFrS0KzE1TSYbDcxIS2Nzb4Y21p9lHl8zExxMs/twpXgcWKeeoyyVzvmBMabw6UUWO3Epi3D0lu5tb4WPQTbEl59qyw2Gvw+DrW0UNHSTIPPh242MyEtjcWFRRS7Uzt75+I6WakhEkDFot23Gyd62eKskm5saWfDtkrqahspSDJz/rQ03O6hraEbCUfY8LetVO48wpQLJrLgqjmySEIIIc4iCexGkcKp+Wx7eyfHD9ZSPK3grJxzQZFO/UET7+xs4VPzM7Fbh2aCPYDNZOKSDBfzU11sb/XzkdfH9lYfxVaNyZYIkwyDXmsgRAIQDYHJAuY4j3Ys2rE9klgViz71MIzdHjM44m+nuqqKo/4Q7eEwNouZ8alpnJ+XT0lqGnqCwY5mT8ZUcj7K19rzPq7ULjn1vO1BynYd4eDhBtLcTpZfMpns6ho0x9AGWE01LfzjzxvwtwW45H9dSMnMoiE9nxBCiO4ksBtF3JkpZOanU1FWedYCO4tZ44qZbv7+kY93PmrmqnkZXYbxEpbIUOKJBQsOYFGyhfNcyZS3h9jnbWeVN8Tasq1MSMug2O2mOCUFpx6nB9GWBLZkNFv3nikVaodQG5o+CCWyjEjHELFStEYNakIRaoIRakJRmoNBiIXJTvUzOWMcJalp5CUn994z1wNNt2OZ9cmEUs4EgmF27D3OvoO12GwWFs8vZfKEcWjhdiJHIx01d+NQ4QDqDPPgQcfQ694N+9n29k5Ss9186o4rSRms2rJCCCH6RQK7UaZ0Xgmb/r4Nn8eHy53oIGUvElj9maxHuGKag5U7PKzZXseSGSkdJcESWSF6WtH3bmJRsDrRXKkdeepOmetlBWbpMCvDSovmYr+vlqqDh9h7orRahm4ix2om22pmnG4iJerFHGyDaEfQ1U0kALFQ/ADzFD3l9wtEo7QEgzS1NFBfcYD6mEaT0gkrDU1TpJkUueYY8whTqCtSJ30WU/LAKzj0NTQcCIbZtaeKPQdqMZk05s0oZPqkXHS9o4fOiARRtftQSkOzdA+GVTQCmkJFgv0uU+fz+vnw1c3UVNQxbdFkzrtiFuaeagELIYQYchLYjTITZhdR9s5O9mw4wPlXzT3zAyWw+hNnGhoKFQ6SqcOSUo01+9p4Z5ufy6c60M1an1UwOou+my0duexO3x4LoWJRLNOv7HUVaWYkSNru1VzoTsOnWTkSCFMdjFAXjrKnPYYyQiifj2RTMakmMymaBacWw0kMJwZWDHSTQo/EsAUC6KGOoFQpiBgGUSNGJGYQDPnwHfgQv68Nv6Fojym8MYO2qCJknAiBVZRkTytZJoNiM2RpUbK1CHZNQQRULAQqhgq2wyAEdj3xB8LsKq9m78FaNA1mTM5l5pQ87LbTfh4nViZjcaBM8f6TP7G9H712Simqdh1h49+3YdYtLP3ipeSV5gzshoQQQgyYBHajjG7VmbyglH0bDzD70mnYHGdWO/ZMSl6NB66a4eXt9Qd52+vgikUTcbqcvaf1MOuYkjNOLCaIVyVBw5ScgWZPTiyHmsVOktXBdIeL6SdeChsGDe3tNBxvpNVoo1VLpVaz48dEABNKnRg61lLBEsZUcRRTY5yFCADREKquCbtFx6FbSdZN5DrMTDKbSNXNpGlRkrzHMNceBWsqJlsSHZn/Pg6mVEh1JGUeooTKrV4/u8qrOVjVgNlsYuaUPGZMzu0e0J10otdUKYVmdL9vhepo+wTL1AXaA2x6o4zDe44xfmYhC68574yfQyHEwMViMSKRsZ/AfSzTdX3QFppJYDcKTVs4kX0bD7Dr/X3Mv3LOGR/nTEpe5Rclc02Sm9Xv7+W19yq4YvFUsjN6PkZ/AkjVS144FSdx8UlWk4k8u06WHTAagDCauWMo1lAQwEQEjXDMTyTmRyvKxZI3vfP9FpMJ3WRGN5uwRoOYth/GbEuKX5Ys3NG71/l9z3c1qJRSVNd52H2ghmM1LdhtOvNmFjK1NAdbvHqrp9B0O6bcqaC7erinAER8fQbWSikqdx5h05tlmEwal352EeNnFA7ovoZaT8PqnaQurRjFlFLU1tbS2to63JciBkFqaio5OTkDrswjgd0o5EhyMOOiKex6fx9Tzp9IUuogzLXrh8z0JK67cg7vflDOG+/uYv6sImZMzsNkiv8w9hVA9lberJPFiopFSOhxj4RRpo75fBrQmR0uEgAVQnc5sLhT477VaGsnUleO0dt8tKAXNBMYMbQ48/WUEesIVk0DTw8TCkepONzA3gM1tLYFSHe7WLyglNLirP7VdTXpaFZH3MAOQMXtTf1YW0s7G/++jeqDtZTMKuL8q+dhd47sXrpEnqs+S+IJMYKdDOqys7NxOp1Sqm+UUkrh9/upr68HIDc3d0DHk8BulJq2aDL7tx5i0xvbuPzmi8/6f9BOh5WrL5/B1p1H2PzRYQ4fa2bx+aWkuc8gkXEv5c2AjgUeAU/f3WMWe0fZsVgEQr7u2w2jY3tvCwROzkezJYM1zr0oX8c+SZloKTlo9u6rb7VgOwQ7Eir31gvZU2+RUorG5nb2VdRx6EgjhmFQlJ/O4gWljMtKOas/61gsxp4P9/PRuj3YXTY+8fmLKZicd9bOPyCJPFdDUHFDiLMhFot1BnUZGVLVZbRzODr+6K6vryc7O3tAw7IS2I1SVpvOwmvOY+2fPqBq1xFKZp39Gpxms4kL5o6nKD+d9zcf5NW3djB7aj6zpuZ3rsjslx7ywnXEc31XnjA7UlCzr0GzOXquPBGLYU4Z1/e19FApQ0V779nq3O9EdQpD67kdTu8t8vlDHDzcwMGqBlq9fpKcNuZMy2fyhHE4HQNM0WL0sFKYE0OxceYD1hyqY+Mb22hrbmfahZOZs2Q6unVoklQPqd6eq0GsuCHE2XRyTp2zt4o1YlQ5+bOMRCIS2J2riqbmUzyjkI1vlJFdlDk46U/OQE5WCtcvm8OOvcf5qPw4+w7VMW9GAZNLxmHuz3BhIvpIz2JyJKE53HF7aLRosCOlykApA9oaUMF2DEv3gEtFwxALo3wtmNLye+0tCvr9HG5opfJoIzUNXswmE8X56SycO568cak9Dm/363IjQYyafR2VK+KtijWiaGZLZ7qTtpZ2tr61gyN7j5NdnMVln100uPWJhRCDRoZfx47B+llKYDfKXfip83j9V6v5x182suzWJZjOIAnuYLBYzMyfVcTkCdmU7TrK+m2V7NxXzcwpeUwuycYy0NxmJjOa1dkt192pNFcqoJ1YDNDDPn2kZ+nUZ0JlDZSBirPKFGXQORkwTm+RLxjjSF2AwzV+6g59BBYrudluLl5QyvjCDKxDVC5OO+V/4wmHIuzZtJO96/djc1q55MaFjJ9ZJB8cQggxikhgN8rZHDYuuXEhq55by9bVHw0st90gSHbZuXThJGZNzWPHnuNsLKtk264jTJmQw5QJ2aScaTF4k455ypI+U6uoSDB+IuSTrH2nZ0G3d1RiiHMcFYt0zKvTHaBb0eIEiSoWOTGfr2MoVylFY1uE400hjjaGaPSG0Ywo2U64cE4hJaWFOOyDUA2jB525BK3xV8VGAz4O7qph96/fJ2qYmX7RZGZePHV0DrsKIcakhx56iFdeeYXt27cntH9VVRUlJSWUlZUxd+5c1q5dy+WXX05LSwupqalDeq3DTQK7MSC7KIsFV81l85tlJKe5mHrBpOG+JNLcLpYsmsx5s4rYe6CGfRW1fLTvGOMyU5g4PouSwsw+03T0l4oEMQ6+3+cqSK2XVZCJpAZR/qYTx8qIu48R8uNtaaKuUaO2xku110MobKBbTOSl25hemEp+ssIabcNSmo02hEFd532Zu6+KVUpxuKKF7R8coa3Jw8Qr5zJv+fm4UmTOjhDnguFOB7R+/Xouvvhili9fzt///vchOw/ARRddRE1NDW63e0jPMxJIYDdGTFs4ifaWdja/uR1Hkp3i6SMjv1hKkp2F80qYP6uIw8ebOVjVwIdbD7FhWyW52W4K89IoSNdxQK/z51QsQqx8HfS2eMFiRYV8mOxJA1sFadLRekrdYtI6egYVnYGSYShafFHqPWHqPWHqmgK0eaKYNI2MjBhT8pLIT7eR5bZiPnFcFQ6gesiRPNSUUhw/7GHHxuM0N/rJy3dw8SUlZF9xHpp9DAZ1CZTNE+JcMxLSAa1YsYJvfvObrFixgurqavLyhm7FvdVqJSfn3KiOI4HdGDJ/2RwC7UHe+/MGLrvJRNHU/OG+pE4Wi5nS4ixKi7Pw+UMcPt7M4ePNbCyrZH00QpIvSrY9QI7bQnaymWS71mVul2ZzQtiHZuslaDuZEmUgqyD7KLUWMxSeqJPmVh/N9e00BXw0t0WJxgxMJo2MZJ3iTBvjcm3kpJiwpaX1mDsuUYP1V7VSiuNVrezcXE1jvY9xecks+8xUsjMtHW031iRQNi/hOZdCjDXDnA6ovb2dF154gS1btlBbW8tzzz3Hd7/73c7tjz76KP/3//5f/H4/N910E1lZ3csz/r//9/94/PHHqaysZPz48dxzzz3ceeedcc8Xbyj2/fff54EHHmDLli1kZmbymc98hp/+9Ke4XMOzEHGwSGA3hphMJi6+YSFKwboXP+TSzy6ieFrBcF9WNy6njemTcpk+KZdQOEpNvYea6hxq6ls45AlAG1h1MxmpTjJSnbiT7bgdGq4jH+Bw2jANICVKXzTdDlM+QaDdT7s/jLc9iLc9hKc9iKet499GNIKqbybZpZGZ6qCwQCcrRScz2YLFrJ0YrjXQzOY+e4t6q6gBH6dNGchf1Uopjla1sWt3Lc0tEbJzk7ji2snkFnbkxOspDcpol2jVE0lOLM5pw5QO6MUXX2Tq1KlMmTKFL3zhC9x777088MADaJrGiy++yEMPPcRTTz3FxRdfzO9+9zueeOIJJkyY0Pn+559/nh/+8Ic8+eSTzJs3j7KyMm6//XZcLhdf/vKX+zx/RUUFy5cv58c//jG/+c1vaGho4O677+buu+/m2WefHbL7Phv6Fdg988wzPPPMM1RVVQEwY8YMfvjDH3L11VcDsGTJEtatW9flPXfccQe/+tWvBudqRZ86grsLeP+v8N6L67ngmvOYsqB0uC+rRzarhfEFGYwv6EiwGQxFaGxup7G5naZWH4frfbRXtaIiIYzadnRbDJerHZfNjNNmxq6bsOombISxhKKYNQ09GsZsM6Hx8fJxw1BEw2FigSjqSBNRk49QJEo4HCMUjhAIRgiGIvj8YfzBMEp1hGOappHktJGcZCe/wM1MtxO3OUDSpnfROZE+JAQ0dHxFAYwoaBrmwnm9ruLF6iB24B8Q7iW4G8DwciwWo2rXUXat2U7zrmPkFKSw9JPFjMtL6miXyImgcwwPSSZcNk8IcVatWLGCL3zhCwAsX74cj8fDunXrWLJkCT//+c+57bbbuO222wD48Y9/zNtvv00w+PHvqgcffJDHH3+cG264AYCSkhL27NnDf/3XfyUU2P30pz/llltu4d577wVg0qRJPPHEE1x22WU888wz2O2j9/dGvwK7goICHn30USZNmoRSit/+9rdcd911lJWVMWPGDABuv/12fvSjH3W+R5Innn1ms5lLblzIZpeNja9vxdvUxvwrZw9bKpT+sNt0CnLTKMhN63wtGjPwNjbStPkIPpz4YxZ8oRgef5T6iEEoYhAKhVGhcMfcN5sHzdy98oSKRSEaxNRSiabbsOpmrLoFu03HbtdJczvJG5dKkstGktOGy2klyWXvVrrLaGsgYgZi0GP6EJMZ0+RLMDl7nqirIkFiu1cnVnGjH39Vh0MRDm47xL6NB2lv9ZFfmskFN80kMyUGGBD0dutFlCFJIcTZUl5ezqZNm3j55ZcBsFgsfO5zn2PFihUsWbKEvXv38vWvf73LexYtWsSaNWsA8Pl8VFRUcNttt3H77bd37hONRhNeHLFjxw4++ugjnn/++c7XlFIYhkFlZSXTpk0b6G0Om34Fdtdee22X7x955BGeeeYZNmzY0BnYOZ3Oc2aC4khmMpm44Op5pGQks2XldlrrPFx840IcrtH3V4jFbCLN7SA5U0dzOHtciRrxxIjEQLnSMSx2VGf0ojBpGlo0iCnkxX7ePHSX+4zzs/WVPkSFA6iwD5PTjdZb+bLOGxxYxY2T2lt97N14gIPbKolFY4yfWcjlNy8mbVzqsK9+E0KIk1asWEE0Gu2yWEIphc1m48knn+zz/e3t7QD8+te/ZuHChV22JVqxob29nTvuuIN77rmn27aioqKEjjFSnfEcu1gsxksvvYTP52PRokWdrz///PP8/ve/Jycnh2uvvZYf/OAHvfbahUIhQqGPexy83l4KwYt+0TSNaQsnkZqdwj/+vIHXf7Wai2+4gNySBEpqjTKapqGbNSwmMFkiEDchcgSlTFgs5gEn3Y2XPqSLWGKlxwZKKcXxo+1UlG+guqoV3a4z5YKJTL1gIs5TcgbKkKQQYiSIRqP8z//8D48//jjLli3rsu3666/nj3/8I9OmTWPjxo186Utf6ty2YcOGzn+PGzeOvLw8Dh06xC233HJG13HeeeexZ88eJk6ceGY3MoL1O7DbuXMnixYtIhgMkpSUxMsvv8z06dMB+PznP09xcTF5eXl89NFHfOc736G8vJy//vWvPR7vpz/9KQ8//PCZ34HoU27JOD719WX84y8bePt/3mPqwonM/cTM0ZmAtrfFCIlUpxgjQ44BX4SKfQ0c2FlDW5OXzLm5XHjtfEpmFWEZosoVQogx6CynA3r99ddpaWnhtttu6zZseuONN7JixQruu+8+br31VhYsWMDixYt5/vnn2b17d5fFEw8//DD33HMPbreb5cuXEwqF2LJlCy0tLXzrW9/q8zq+853vcOGFF3L33Xfz1a9+FZfLxZ49e1i9enVCvYYjWb8/AaZMmcL27dvxeDz8+c9/5stf/jLr1q1j+vTpfO1rX+vcb9asWeTm5nLFFVdQUVFBaWn8CfwPPPBAlx+C1+ulsHBk5GAbS5zJDq780mXs23iAsnd2cbS8mkXXLiB3wijpvUskdUVSBqaJF6OZeumKT2DIsa9hy75Wsg4Vw1DUHPVQsbeRo4da0UwaxSUuFi9OZ9yVl2FypAzLdZ1KhnyFGCWGKR3QihUrWLp0ady5cDfeeCP/+Z//ybRp0/jBD37At7/9bYLBIDfeeCPf+MY3WLVqVee+X/3qV3E6nTz22GPcf//9uFwuZs2a1bkYoi+zZ89m3bp1fO973+OSSy5BKUVpaSmf+9znButWh42mlIobrCdq6dKllJaW8l//9V/dtvl8PpKSkli5ciVXXXVVQsfzer243W48Hg8pKcP/QTUWeZvbWP/aFuqqGiieXsB5V84mOS1puC+rT4kEDcCAAotEknZ2rlRNyux5jl3Ag2Xutb3OsVPBNqLb/4bmcPd8nLY6mptCVB2LUXnIR9AfITXdwcRpGZRMSsNmiaIioT7PdTaMhISnQpwrgsEglZWVlJSUnPEKTvlDbGTp7Wfan9howGM2hmF0mSN3qpM13XJzcwd6GjGIUtKTWfblJVTuPMLW1R/x6pMrmbpwEjMvnordaRvuy+tRX/PEBiWwSCRp58mVqoM1hBHnOO1tIar21VG5r55Wr4HNqlEy0c2EiVmkZdg65ggqHyoygoaXhznhqRCif2Tu7djUr8DugQce4Oqrr6aoqIi2tjb+8Ic/sHbtWlatWkVFRQV/+MMf+OQnP0lGRgYfffQR//qv/8qll17K7Nmzh+r6xRnSNI0Js4spnJrHnvX72f1BOfu3VDDtwklMu3DyoAZ4Z+2vwsEMLHpbqWpqH5y5fKcNhbR5wxyp9HKkso2mxiAWi4nCydnM/+IV5E3MxWzuIV3NSPurepgSngohhOhnYFdfX8+XvvSlzkK6s2fPZtWqVVx55ZUcPXqUt99+m5///Of4fD4KCwu58cYb+f73vz9U1y4GgW7VmXPZDCYvKGXPh+XsWb+fPev3M+m8CUw5vxR35sCGw4dleG6oAwuTjnnKkt6vN5Fgy2KjNXUBx2qPcrS8huY6DxY9k/xZM5g5JY+CyTnoDsfICtqEEEKMaP0K7FasWNHjtsLCwm5VJ8To4XDZmX/lHGYsnsq+jQfYv6WCfRsPkFs6jqkXTCR/Uu6ZJTgeo8Nzmm4/ozlt4VCEmkN1VB+spfpgLT6PH6tdJ39SLrM+MY/8STmjc7WyEEKIEUHyIogu7E4bcy+fyaxLplG1+yj7Nh5gzR8/wJFkp2R2MaVzikkbl9r/A5+jw3OGYdBU3dIRzFXU0XC0EWUoUjKTKZyaT+GUPLKLMxNOqimEEEL0RgI7EZfZYqZ0zngmzC6mubaViu1VVGyvYs+H5bizUiialk/h1HwyctMGnOx3LIlFYzRVN1N/pJG6w400HG0kHIyg23RySrI5f/lc8ifl9msVsqxcE0IIkSgJ7ESvNE0jIzeNjNw05i+bTfXBWg7vOUb55gp2vrcXZ4qDvIk55JXmkDshG5vjzBZd9Jkb7mwHLwmseFVK4ff6aaxuoeFoEw1HG2mqbsGIGVisFrIKM5h+0RRySrLJzE8/o6HsUZlC5CwnPBVCCPExCexEwsxmM4VT8imckk8sFqP+cCPH9ldTXVHHwW2VaJpGWk4qWYUZZBdlklWQgdPWd5pEFYsQK18H0Z7LcPUreBlIYNFD0k7DULR5wrQ0h2j1m/Hs30RzXTtBX8c+LreTrMIMxs8sIqswg/Sc1DObk3i60TRHcZgSngohhPiYBHbijJjNZnInjOusXOHz+Kg5VE/d4QaqD9ZSvukgADYruENHSM/LIC3bjTvdQUqqHd16ypwyIwZBL5rDPbDgZYCBhVKKUETDm3we3mAL3mYf3qY2PA1teFt8GDELYMHpTiI9z8rkBaVk5KWRnpuGK6XnesiDYhTMUdR0O+ZpS2XYWAghhpEEdmJQuNwuJs4rYeK8EgAC7QGaqltoOlxN/fpKDu9vYM/2uo/3T7LiSraS5NJw6mGcLgvOLDvOVCt2h47NZsZsMaFpWsLBS0+BhVKKSChKKBAmFDIIVbUQaAsQaA8SaAvg8/jxefy0t/qJhD5+ryPZgTszmZzJRUzJTCY1201qtntEJ3EebpLwVAgxGDRN4+WXX+b666+Pu33t2rVcfvnltLS0kJqaelavbaSTwE4MCUeSg4LJDvJL0omNq0X5vUTCMTyeMJ7mEG1tYdq9ETxNEar9MYLtQdB9XXrTzGYTVpsZixbDrEJYt7+H2e7EZDZhMpnQTBqcqIinFBgxg1g0RiwaIxqJEQ1HiYQiRMJRlNF9cNbusuFIsuNyO8kuyqRktoukVBcpGUkkpydJ2hEhxDlBKYXfFyEajWGxmHG69CFfFFdbW8sjjzzC3//+d44fP052djZz587l3nvv5Yorrujz/RdddFFnTt3B8NBDD/HKK690VswazSSwE0Pq1F40C+AAck7bR0WChD96ixBOghEzoWCUUDBGOBQlHIoRCQSI+tow0pNQZhtGzMAwFEop0DQ0TcOkgW6zYDKbMFvMmC1mdJsF3aajWy1YHVbsTlvH/7ts2F02STEihDjneT1Bjh9ppbXZTyRqoFtMpKY7yS9KJcU9NL3vVVVVLF68mNTUVB577DFmzZpFJBJh1apV3HXXXezbt6/PY1itVnJyTv80GXqRSARdH9l/9EtgJ4ZcIsNzZrOGy2ElKd48snAAFfBgmXvesBe6F0KIscLrCVK+qxZ/IEqK20aybiYSiVFf1067N8iUmTlDEtzdeeedaJrGpk2bcLlcna/PmDGDf/7nf+78vrGxkc985jOsWrWK/Px8Hn/8cT796U8D3Ydin3vuOe69915eeOEF7r33Xo4ePcrFF1/Ms88+21mvfu3atXz7299m9+7d6LrOjBkz+MMf/sCaNWt4+OGHATp7Kp999lluvfVWNE3j6aef5s033+Sdd97h/vvv5wc/+AFf+9rXePfdd6mtraWoqIg777yTf/mXf+m89ltvvZXW1lbmzZvHk08+SSgU4vOf/zxPPPEEVqt10Nv0VBLYCXEGznpuOUkhIoQYREopjh9pxR+Ikpnl7AxobDYLmVlmGhv8HD/SSvLMcYM6LNvc3MzKlSt55JFHugR1J506X+7hhx/mP//zP3nsscf45S9/yS233MLhw4dJT0+Pe2y/38/PfvYzfve732EymfjCF77Afffdx/PPP080GuX666/n9ttv549//CPhcJhNmzahaRqf+9zn2LVrFytXruTtt98G6DLE+9BDD/Hoo4/y85//HIvFgmEYFBQU8NJLL5GRkcGHH37I1772NXJzc7nppps63/fOO+9gt9tZu3YtVVVVfOUrXyEjI4NHHnlkkFozPgnsxMgxSoKXs5pbTlKICCGGgN8XobXZT4rb1i1w0zSNFLeN1mY/fl8EV9Lg9TAdPHgQpRRTp07tc99bb72Vm2++GYCf/OQnPPHEE2zatInly5fH3T8SifCrX/2K0tJSAO6++25+9KMfAeD1evF4PHzqU5/q3D5t2rTO9yYlJWGxWOIO737+85/nK1/5SpfXTvbwAZSUlLB+/XpefPHFLoGd1WrlN7/5DU6nkxkzZvCjH/2I+++/n//4j/8YnHRYPZDATgy/0Ra8nMXccpJCRAgxFKLRGJGoQbIef66xrptpi4aIRmODel6l+s5tetLs2bM7/+1yuUhJSaG+vr7H/Z1OZ2fQBpCbm9u5f3p6OrfeeitXXXUVV155JUuXLuWmm27qHKbtzYIFC7q99tRTT/Gb3/yGI0eOEAgECIfDzJ07t8s+c+bMwen8OBXWokWLaG9v5+jRoxQXF/d53jMlgZ0YdqM2eDlLueUkhYgQYrBZLGZ0i4lIJIbN1j0UiERi6BYTFsvgLjKbNGkSmqYltEDi9EUKmqZhGEa/9j81kHz22We55557WLlyJS+88ALf//73Wb16NRdeeGGv13H6kPGf/vQn7rvvPh5//HEWLVpEcnIyjz32GBs3buzzns6GoesLFKIfNN2OZk/u+UsCGyGEGDROl05quhOvJ9StF00phdcTIjXdidM1uCMl6enpXHXVVTz11FP4fL5u21tbWwf1fKebN28eDzzwAB9++CEzZ87kD3/4A9AxbBqLJdY7+cEHH3DRRRdx5513Mm/ePCZOnEhFRUW3/Xbs2EEgEOj8fsOGDSQlJVFYWDg4N9MDCeyEEEKIc4ymaeQXpeJ0WGhs8BMKRTEMRSgUpbHBj9Opk1+UOiT57J566ilisRgXXHABf/nLXzhw4AB79+7liSeeYNGiRYN+PoDKykoeeOAB1q9fz+HDh3nrrbc4cOBA5zy78ePHU1lZyfbt22lsbCQU6nnUZdKkSWzZsoVVq1axf/9+fvCDH7B58+Zu+4XDYW677Tb27NnDG2+8wYMPPsjdd989pPPrQIZiR6SzvuJSCCHEOSfFbWfKzJzOPHZt0RC6xUT2uKQhzWM3YcIEtm3bxiOPPMK//du/UVNTQ1ZWFvPnz+eZZ54ZknM6nU727dvHb3/7W5qamsjNzeWuu+7ijjvuAODGG2/kr3/9K5dffjmtra2d6U7iueOOOygrK+Nzn/scmqZx8803c+edd/Lmm2922e+KK65g0qRJXHrppYRCIW6++WYeeuihIbm/U2mqPzMZzwKv14vb7cbj8ZCSkjLcl3PWndUVl+KMqGAb0e1/Q3O448+x68y7d63k3RNCDIlgMEhlZSUlJSXY7QP7LBiOyhNj3ck8dq+88krC7+ntZ9qf2Eh67Eaas7jiUgzQKEnPIoQQvdE0bVBTmojhJYHdSHWWVlyKMzDa0rMIIYQ4Z0hgJ0Q/jdr0LEIIIc6K5557btjOLYGdEGdAcssJIYQYiSTdiRBCCCHEGCGBnRBCCCHEGCFDsSOVrLgUQgghRD9JYDfSyIpLIYQQQpwhCexGGFlxKYQQQogzJYHdCCQrLoUQQghxJmTxhBBCCCHOqtraWv7lX/6FiRMnYrfbGTduHIsXL+aZZ57B7/cP2nmWLFnCvffeO2jHGw2kx04IIYQ4xzV4mth2aDfnTZhBljtjSM916NAhFi9eTGpqKj/5yU+YNWsWNpuNnTt38t///d/k5+fz6U9/ekivYSyTHjtxzlGRICrY1vNXRFYeCyHOLbuP7GfTge3sPrJ/yM915513YrFY2LJlCzfddBPTpk1jwoQJXHfddfz973/n2muvBaC1tZWvfvWrZGVlkZKSwic+8Ql27NjReZyHHnqIuXPn8rvf/Y7x48fjdrv5p3/6J9ra2gC49dZbWbduHb/4xS/QNA1N06iqqgJg3bp1XHDBBdhsNnJzc/n3f/93otFo57FDoRD33HMP2dnZ2O12Lr74YjZv3jzkbTMYJLAT5xQVCRLb+zbR7X/r8Su2920J7oQQ54wGTxN7j1eQnuRm7/EKGjxNQ3aupqYm3nrrLe666y5cLlfcfTRNA+Czn/0s9fX1vPnmm2zdupXzzjuPK664gubm5s59KyoqeOWVV3j99dd5/fXXWbduHY8++igAv/jFL1i0aBG33347NTU11NTUUFhYyPHjx/nkJz/J+eefz44dO3jmmWdYsWIFP/7xjzuP++1vf5u//OUv/Pa3v2Xbtm1MnDiRq666qsu5RyoJ7MS5JRZB+b1oug3N4e7+pds6Us30tipZCCHGkN1H9uMLBijKyscXDAxpr93BgwdRSjFlypQur2dmZpKUlERSUhLf+c53eP/999m0aRMvvfQSCxYsYNKkSfzsZz8jNTWVP//5z53vMwyD5557jpkzZ3LJJZfwxS9+kXfeeQcAt9uN1WrF6XSSk5NDTk4OZrOZp59+msLCQp588kmmTp3K9ddfz8MPP8zjjz+OYRj4fD6eeeYZHnvsMa6++mqmT5/Or3/9axwOBytWrBiythksMsdOnJssdjSro9vLCnrMHyiEEGPNyd66nNRMAHJSM9l7vIIZRZOHfK7dqTZt2oRhGNxyyy2EQiF27NhBe3s7GRldryEQCFBRUdH5/fjx40lOTu78Pjc3l/r6+l7PtXfvXhYtWtTZMwiwePFi2tvbOXbsGK2trUQiERYvXty5Xdd1LrjgAvbu3TvQWx1yEtgJIYQQ56iTvXUFGTkAuF3J1LY2svvIfpbMWjTo55s4cSKaplFeXt7l9QkTJgDgcHT8wd3e3k5ubi5r167tdozU1NTOf+t612T9mqZhGMbgXvQoI0OxQgghxDno9N66k0722g3FXLuMjAyuvPJKnnzySXw+X4/7nXfeedTW1mKxWJg4cWKXr8zMzB7fdzqr1UosFuvy2rRp01i/fj1KfVy484MPPiA5OZmCggJKS0uxWq188MEHndsjkQibN29m+vTp/bjb4SGBnRBCCHEO2n1kPx5fGxazGV/Q3/llMZvx+NqGbK7d008/TTQaZcGCBbzwwgvs3buX8vJyfv/737Nv3z7MZjNLly5l0aJFXH/99bz11ltUVVXx4Ycf8r3vfY8tW7YkfK7x48ezceNGqqqqaGxsxDAM7rzzTo4ePco3v/lN9u3bx6uvvsqDDz7It771LUwmEy6Xi2984xvcf//9rFy5kj179nD77bfj9/u57bbbhqRNBpMMxQohhBDnGMMwaPW34XYl0+LzdtvudiXjCbRjGAYm0+D2AZWWllJWVsZPfvITHnjgAY4dO4bNZmP69Oncd9993HnnnWiaxhtvvMH3vvc9vvKVr9DQ0EBOTg6XXnop48aNS/hc9913H1/+8peZPn06gUCAyspKxo8fzxtvvMH999/PnDlzSE9P57bbbuP73/9+5/seffRRDMPgi1/8Im1tbSxYsIBVq1aRlpY2qG0xFDR1al/kCOD1enG73Xg8HlJSUob7csQYo4JtRLf/DU23gSVO2bZoEBUJYZl7LZo9uft2IYQYAYLBIJWVlZSUlGC3n1kJykAoSDga7nG7Tbdht9rO9BJFP/X2M+1PbCQ9duLcYtbRnCkdKU16WP2qOVPArMfdJoQQY4XDZsdhk7rkY40EduKcoul2zNOW9p6nzqyj6fLLTgghxOgjgZ0452i6HSRwE0IIMQbJqlghhBBCiDFCAjshhBBCiDFCAjshhBBilDrXqyyMJYP1s5Q5dkIIIcQoY7VaMZlMVFdXk5WVhdVq7VL7VIweSinC4TANDQ2YTCasVuuAjieBnRBCCDHKmEwmSkpKqKmpobq6ergvRwwCp9NJUVHRgBNCS2AnhBBCjEJWq5WioiKi0Wi3eqhidDGbzVgslkHpdZXATgghhBilNE1D13V0XZKqiw6yeEIIIYQQYoyQwE4IIYQQYoyQwE4IIYQQYowYcXPslFIAeL3eYb4SIYQQQojhdzImOhkj9WbEBXZtbW0AFBYWDvOVCCGEEEKMHG1tbbjd7l730VQi4d9ZZBgG1dXVJCcnS7LFQeL1eiksLOTo0aOkpKQM9+WMOdK+Q0vad2hJ+w4tad+hda60r1KKtrY28vLy+sxzN+J67EwmEwUFBcN9GWNSSkrKmH7wh5u079CS9h1a0r5DS9p3aJ0L7dtXT91JsnhCCCGEEGKMkMBOCCGEEGKMkMDuHGCz2XjwwQex2WzDfSljkrTv0JL2HVrSvkNL2ndoSft2N+IWTwghhBBCiDMjPXZCCCGEEGOEBHZCCCGEEGOEBHZCCCGEEGOEBHZCCCGEEGOEBHaj2Hvvvce1115LXl4emqbxyiuvdNne3t7O3XffTUFBAQ6Hg+nTp/OrX/2qyz7BYJC77rqLjIwMkpKSuPHGG6mrqzuLdzEy9dW2dXV13HrrreTl5eF0Olm+fDkHDhzoso+0bc9++tOfcv7555OcnEx2djbXX3895eXlXfZJpP2OHDnCNddcg9PpJDs7m/vvv59oNHo2b2VESqR9//u//5slS5aQkpKCpmm0trZ2O05zczO33HILKSkppKamctttt9He3n6W7mLk6qt9m5ub+eY3v8mUKVNwOBwUFRVxzz334PF4uhxHnt/4Enl+77jjDkpLS3E4HGRlZXHdddexb9++Lvucq+0rgd0o5vP5mDNnDk899VTc7d/61rdYuXIlv//979m7dy/33nsvd999N6+99lrnPv/6r//K3/72N1566SXWrVtHdXU1N9xww9m6hRGrt7ZVSnH99ddz6NAhXn31VcrKyiguLmbp0qX4fL7O/aRte7Zu3TruuusuNmzYwOrVq4lEIixbtqxf7ReLxbjmmmsIh8N8+OGH/Pa3v+W5557jhz/84XDc0oiSSPv6/X6WL1/Od7/73R6Pc8stt7B7925Wr17N66+/znvvvcfXvva1s3ELI1pf7VtdXU11dTU/+9nP2LVrF8899xwrV67ktttu6zyGPL89S+T5nT9/Ps8++yx79+5l1apVKKVYtmwZsVgMOMfbV4kxAVAvv/xyl9dmzJihfvSjH3V57bzzzlPf+973lFJKtba2Kl3X1UsvvdS5fe/evQpQ69evH/JrHi1Ob9vy8nIFqF27dnW+FovFVFZWlvr1r3+tlJK27a/6+noFqHXr1imlEmu/N954Q5lMJlVbW9u5zzPPPKNSUlJUKBQ6uzcwwp3evqdas2aNAlRLS0uX1/fs2aMAtXnz5s7X3nzzTaVpmjp+/PhQX/Ko0lv7nvTiiy8qq9W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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scatterplot(df, var1, var2)\n", "\n", "for species in hypos:\n", " norm1 = flipper_map[species]\n", " norm2 = culmen_map[species]\n", " multinorm = multinorm_map[species]\n", " joint = make_joint(norm1, norm2, multinorm)\n", " plot_contour(joint, alpha=0.5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Because the multivariate normal distribution takes into account the correlations between features, it is a better model for the data. And there is less overlap in the contours of the three distributions, which suggests that they should yield better classifications." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A Less Naive Classifier\n", "\n", "In a previous section we used `update_penguin` to update a prior `Pmf` based on observed data and a collection of `norm` objects that model the distribution of observations under each hypothesis. Here it is again:" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [], "source": [ "def update_penguin(prior, data, norm_map):\n", " \"\"\"Update hypothetical species.\"\"\"\n", " hypos = prior.qs\n", " likelihood = [norm_map[hypo].pdf(data) for hypo in hypos]\n", " posterior = prior * likelihood\n", " posterior.normalize()\n", " return posterior" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Last time we used this function, the values in `norm_map` were `norm` objects, but it also works if they are `multivariate_normal` objects.\n", "\n", "We can use it to classify a penguin with flipper length 193 and culmen length 48:" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Adelie0.002740
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" ], "text/plain": [ "Adelie 0.002740\n", "Chinstrap 0.997257\n", "Gentoo 0.000003\n", "dtype: float64" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data = 193, 48\n", "update_penguin(prior, data, multinorm_map)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A penguin with those measurements is almost certainly a Chinstrap.\n", "\n", "Now let's see if this classifier does any better than the naive Bayesian classifier.\n", "I'll apply it to each penguin in the dataset:" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [], "source": [ "df['Classification'] = \"None\"\n", "\n", "for i, row in df.iterrows():\n", " data = row[colnames]\n", " posterior = update_penguin(prior, data, multinorm_map)\n", " df.loc[i, 'Classification'] = posterior.idxmax()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And compute the accuracy:" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9532163742690059" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "accuracy(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It turns out to be only a little better: the accuracy is 95.3%, compared to 94.7% for the naive Bayesian classifier." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Summary\n", "\n", "In this chapter, we implemented a naive Bayesian classifier, which is \"naive\" in the sense that it assumes that the features it uses for classification are independent.\n", "\n", "To see how bad that assumption is, we also implemented a classifier that uses a multivariate normal distribution to model the joint distribution of the features, which includes their dependencies.\n", "\n", "In this example, the non-naive classifier is only marginally better.\n", "In one way, that's disappointing. After all that work, it would have been nice to see a bigger improvement.\n", "But in another way, it's good news. In general, a naive Bayesian classifier is easier to implement and requires less computation. If it works nearly as well as a more complex algorithm, it might be a good choice for practical purposes.\n", "\n", "Speaking of practical purposes, you might have noticed that this example isn't very useful. If we want to identify the species of a penguin, there are easier ways than measuring its flippers and beak.\n", "\n", "But there *are* scientific uses for this type of classification. One of them is the subject of the research paper we started with: [sexual dimorphism](https://en.wikipedia.org/wiki/Sexual_dimorphism), that is, differences in shape between male and female animals.\n", "\n", "In some species, like angler fish, males and females look very different. In other species, like mockingbirds, they are difficult to tell apart.\n", "And dimorphism is worth studying because it provides insight into social behavior, sexual selection, and evolution. \n", "\n", "One way to quantify the degree of sexual dimorphism in a species is to use a classification algorithm like the one in this chapter. If you can find a set of features that makes it possible to classify individuals by sex with high accuracy, that's evidence of high dimorphism.\n", "\n", "As an exercise, you can use the dataset from this chapter to classify penguins by sex and see which of the three species is the most dimorphic." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Exercises" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise:** In my example I used culmen length and flipper length because they seemed to provide the most power to distinguish the three species. But maybe we can do better by using more features.\n", "\n", "Make a naive Bayesian classifier that uses all four measurements in the dataset: culmen length and depth, flipper length, and body mass.\n", "Is it more accurate than the model with two features?" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# Here are the norm maps for the other two features\n", "\n", "depth_map = make_norm_map(df, 'Culmen Depth (mm)')\n", "mass_map = make_norm_map(df, 'Body Mass (g)')" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# And here are sequences for the features and the norm maps\n", "\n", "colnames4 = ['Culmen Length (mm)', 'Flipper Length (mm)', \n", " 'Culmen Depth (mm)', 'Body Mass (g)']\n", "norm_maps4 = [culmen_map, flipper_map, \n", " depth_map, mass_map]" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9678362573099415" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "\n", "# Now let's classify and compute accuracy.\n", "\n", "# We can do a little better with all four features,\n", "# almost 97% accuracy\n", "\n", "df['Classification'] = \"None\"\n", "\n", "for i, row in df.iterrows():\n", " data_seq = row[colnames4]\n", " posterior = update_naive(prior, data_seq, norm_maps4)\n", " df.loc[i, 'Classification'] = posterior.max_prob()\n", "\n", "accuracy(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Exercise:** One of the reasons the penguin dataset was collected was to quantify sexual dimorphism in different penguin species, that is, physical differences between male and female penguins. One way to quantify dimorphism is to use measurements to classify penguins by sex. If a species is more dimorphic, we expect to be able to classify them more accurately.\n", "\n", "As an exercise, pick a species and use a Bayesian classifier (naive or not) to classify the penguins by sex. Which features are most useful? What accuracy can you achieve?" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "Note: One Gentoo penguin has an invalid value for `Sex`. I used the following code to select one species and filter out invalid data." ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "gentoo = (df['Species2'] == 'Gentoo')\n", "subset = df[gentoo].copy()" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "Sex\n", "MALE 61\n", "FEMALE 58\n", "Name: count, dtype: int64" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "subset['Sex'].value_counts()" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [ { "data": { "text/plain": [ "342" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "valid = df['Sex'] != '.'\n", "valid.sum()" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "tags": [ "hide-cell" ] }, "outputs": [], "source": [ "subset = df[valid & gentoo].copy()" ] }, { "cell_type": "markdown", "metadata": { "tags": [ "hide-cell" ] }, "source": [ "OK, you can finish it off from here." ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Solution\n", "\n", "# Here are the feature distributions grouped by sex\n", "\n", "plot_cdfs(subset, 'Culmen Length (mm)', by='Sex')" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Solution\n", "\n", "plot_cdfs(subset, 'Culmen Depth (mm)', by='Sex')" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Solution\n", "\n", "plot_cdfs(subset, 'Flipper Length (mm)', by='Sex')" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Solution\n", "\n", "plot_cdfs(subset, 'Body Mass (g)', by='Sex')" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# Here are the norm maps for the features, grouped by sex\n", "\n", "culmen_map = make_norm_map(subset, 'Culmen Length (mm)', by='Sex')\n", "flipper_map = make_norm_map(subset, 'Flipper Length (mm)', by='Sex')\n", "depth_map = make_norm_map(subset, 'Culmen Depth (mm)', by='Sex')\n", "mass_map = make_norm_map(subset, 'Body Mass (g)', by='Sex')" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# And here are the sequences we need for `update_naive`\n", "\n", "norm_maps4 = [culmen_map, flipper_map, depth_map, mass_map]\n", "colnames4 = ['Culmen Length (mm)', 'Flipper Length (mm)', \n", " 'Culmen Depth (mm)', 'Body Mass (g)']" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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probs
FEMALE0.5
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" ], "text/plain": [ "FEMALE 0.5\n", "MALE 0.5\n", "dtype: float64" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "\n", "# Here's the prior\n", "\n", "hypos = culmen_map.keys()\n", "prior = Pmf(1/2, hypos)\n", "prior" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# And the update\n", "\n", "subset['Classification'] = \"None\"\n", "\n", "for i, row in subset.iterrows():\n", " data_seq = row[colnames4]\n", " posterior = update_naive(prior, data_seq, norm_maps4)\n", " subset.loc[i, 'Classification'] = posterior.max_prob()" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# This function computes accuracy\n", "\n", "def accuracy_sex(df):\n", " \"\"\"Compute the accuracy of classification.\n", " \n", " Compares columns Classification and Sex\n", " \n", " df: DataFrame\n", " \"\"\"\n", " valid = df['Classification'].notna()\n", " same = df['Sex'] == df['Classification']\n", " return same.sum() / valid.sum()" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9186991869918699" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "\n", "# Using these features we can classify Gentoo penguins by\n", "# sex with almost 92% accuracy\n", "\n", "accuracy_sex(subset)" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# Here's the whole process in a function so we can\n", "# classify the other species\n", "\n", "def classify_by_sex(subset):\n", " \"\"\"Run the whole classification process.\n", " \n", " subset: DataFrame\n", " \"\"\"\n", " culmen_map = make_norm_map(subset, 'Culmen Length (mm)', by='Sex')\n", " flipper_map = make_norm_map(subset, 'Flipper Length (mm)', by='Sex')\n", " depth_map = make_norm_map(subset, 'Culmen Depth (mm)', by='Sex')\n", " mass_map = make_norm_map(subset, 'Body Mass (g)', by='Sex')\n", "\n", " norm_maps4 = [culmen_map, flipper_map, depth_map, mass_map]\n", "\n", " hypos = culmen_map.keys()\n", " prior = Pmf(1/2, hypos)\n", "\n", " subset['Classification'] = \"None\"\n", "\n", " for i, row in subset.iterrows():\n", " data_seq = row[colnames4]\n", " posterior = update_naive(prior, data_seq, norm_maps4)\n", " subset.loc[i, 'Classification'] = posterior.max_prob()\n", " \n", " return accuracy_sex(subset)" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.8807947019867549" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "\n", "# Here's the subset of Adelie penguins\n", "\n", "# The accuracy is about 88%\n", "\n", "adelie = df['Species2']=='Adelie'\n", "subset = df[adelie].copy()\n", "classify_by_sex(subset)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9264705882352942" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "\n", "# And for Chinstrap, accuracy is about 92%\n", "\n", "chinstrap = df['Species2']=='Chinstrap'\n", "subset = df[chinstrap].copy()\n", "classify_by_sex(subset)" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": [ "# Solution\n", "\n", "# It looks like Gentoo and Chinstrap penguins are about equally\n", "# dimorphic, Adelie penguins a little less so.\n", "\n", "# All of these results are consistent with what's in the paper." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "celltoolbar": "Tags", "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 4 }