{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Relations as Graphs - Network Analysis\n",
"\n",
"See also the slides that summarize a portion of this content.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## What is a graph?\n",
"\n",
"In mathematics, the word *graph* has two meanings.\n",
"\n",
" * **Meaning #1 (more common):** The graph of a function on the ordinary Cartesian plane of $x$ and $y$ axes.\n",
" * **Meaning #2 (less common):** A visualization of an interconnected network of objects.\n",
"\n",
"We're focused on the second meaning here. In such a network, the objects being connected are called *nodes* or *vertices,* and the connections are called *edges,* *arrows,* or *links.* While we call it a graph in mathematics, data scientists might refer to it instead as *network data.*\n",
"\n",
"Let's start with a small, pretend example. Let's say we spoke to five friends and asked them which of the others they'd turn to for advice about an important life decision. We could depict their answers with a visualization like the following.\n",
"\n",
"\n",
"\n",
"The five friends are the graph's *vertices,* and are drawn with ovals in the image. The connections among them are the graph's *edges,* representing the friends' answers to the question about advice. For instance, the arrow from Augustus to Cyrano says that Augustus would consult Cyrano when needing advice about an important life decision, but the absence of an arrow from Beatriz to Englebert means that she would not consult him.\n",
"\n",
"Now that we've seen a small (but pretend) example, let's consider some more realistic examples.\n",
"\n",
" * To prepare for class, you were asked to consider a spreadsheet recording shipping records between every two U.S. states in the year 1997. In that data, the vertices were the 50 states and the edges were the records of how much money (or weight) of goods were shipped.\n",
" * In this chapter, we'll look at a spreadsheet created by marine biologists recording the interaction among a community of dolphins living off Doubtful Sound in New Zealand. The vertices of that network are the dolphins and the edges represent social interactions among them. (The data comes from [Mark Newman's website](http://www-personal.umich.edu/~mejn/netdata/), which cites the biologists who collected it.)\n",
" * One of the largest examples of network data has as its vertices the collection of all pages on the internet, and edges are links between them. Google does linear algebra-based computations on this enormous graph regularly, to update their search engine to reflect the latest changes on the web.\n",
"\n",
"```{admonition} Big Picture - A graph depicts a binary relation of a set with itself\n",
"---\n",
"class: alert alert-primary\n",
"---\n",
"Notice that a graph is nothing but a picture representing a *binary relation,* a term we first defined in [the notes on Chapter 2](chapter-2-mathematical-foundations). In the case of a graph, the two sets involved in the relation are actually the same set, even though that's not a requirement for binary relations in general. In the examples above, we connected friends to friends for advice, and states to states with shipping information, and pages to pages with hyperlinks. In a graph, the relation connects the set of vertices to itself, not to some other set.\n",
"```\n",
"\n",
"The graph of five friends shown above is a *directed graph,* because the edges have arrowheads to indicate that they make sense in only one direction. While Augustus said he would seek advice from Cyrano, Cyrano did not say the same about Augustus.\n",
"\n",
"In an *undirected graph,* every connection goes in both directions. For instance, the relation recorded in the dolphin data is about spending time together. If dolphin A is spending time with dolphin B, then the reverse is obviously also true. So in the dolphin data, all connections go in both directions, and we can thus draw them without arrowheads; they are all \"two-way streets.\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Storing graphs in tables\n",
"\n",
"In our course, we store almost all of our data in tables, such as pandas DataFrames, CSV files, etc. How can a graph be represented in a table? There are two primary ways.\n",
"\n",
"First, we can use an *adjacency matrix,* which is a table that tells which pairs of vertices are adjacent. Its row headings are the vertices in the network, and the column headings are the same vertices again. Each entry says whether the row connects to the column. Here's the adjacency matrix for the five friends graph shown above.\n",
"\n",
"| | Augustus | Beatriz | Cyrano | Dauphine | Englebert |\n",
"|---------------|----------|---------|--------|----------|-----------|\n",
"| **Augustus** | False | False | True | False | False |\n",
"| **Beatriz** | False | False | True | False | False |\n",
"| **Cyrano** | False | True | False | False | True |\n",
"| **Dauphine** | False | False | True | False | False |\n",
"| **Englebert** | True | True | False | False | False |\n",
"\n",
"Order is important here. If we want to know whether Augustus $\\to$ Cyrano, we must look in the Augustus **row** and the Cyrano **column.** (This is not hard to remember, because the row headings are actually visually to the left of the column headings, which fits the \"row $\\to$ column\" orientation of the arrow.)\n",
"\n",
"Alternately, we could represent a relation the way we've discussed in [Chapter 2](chapter-2-mathematical-foundations). We can just store in a table the list of pairs that make up the relation. Each row in such a table represents an arrow in the graph. For the five friends, that table looks like the following.\n",
"\n",
"| From | To |\n",
"|-----------|-----------|\n",
"| Augustus | Cyrano |\n",
"| Beatriz | Cyrano |\n",
"| Cyrano | Beatriz |\n",
"| Cyrano | Englebert |\n",
"| Dauphine | Cyrano |\n",
"| Englebert | Augustus |\n",
"| Englebert | Beatriz |\n",
"\n",
"Or we could name the columns something more descriptive, such as \"Advice seeker\" and \"Advice giver.\" I chose \"From\" and \"To\" to show that a similar table could be used to store any directed graph data.\n",
"\n",
"We will call this kind of two-column table a *list of ordered pairs,* because the ordering of each pair of vertices often matters. An edge from Augustus to Cyrano does not mean the same thing as an edge from Cyrano to Augustus. We can also call it an *edge list,* because the connections in a graph are called edges.\n",
"\n",
"```{admonition} Big Picture - How pivoting/melting impacts graph data\n",
"---\n",
"class: alert alert-primary\n",
"---\n",
"These two ways to store the data are very related. If we just imagine a third column for this last table, \"From,\" \"To,\" and \"Connected (True/False),\" then the two tables could be converted from one to the other using pivot and melt from [Chapter 6 of the course notes](chapter-6-single-table-verbs). In that chapter, we learned that it is typically easier for a computer to process melted (tall) data, but easier for humans to read pivoted (wide) data. To make our computations easier, we will work with this second, two-column form.\n",
"```\n",
"\n",
"But storing network data as a table of edges does have one small disadvantage: It doesn't make it obvious what the complete set of vertices is. For instance, just given the second (tall) table shown above, we can't be sure how many friends there are. Is it just these five, or is there a sixth friend, or a seventh? Imagine another friend, Fatima, who has unusual opinions, so she wouldn't go to any of the friends for advice, nor would they go to her. She wouldn't show up in any of the edges, so we wouldn't see her in the data.\n",
"\n",
"Thus if we store a graph as an edge list, we will also need a separate list of the graph's vertices. That list will include every vertex mentioned in the edge list, and possibly some others."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Loading network data\n",
"\n",
"### Dolphin dataset\n",
"\n",
"I've included the dolphin community data with these course notes. You can download it here (as an Excel workbook). I'll explore it below to show you how it's structured.\n",
"\n",
"First, what sheets are stored in the workbook?"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"dict_keys(['ids_and_names', 'relationships'])"
]
},
"metadata": {},
"execution_count": 1
}
],
"source": [
"import pandas as pd\n",
"sheets = pd.read_excel( '_static/dolphins.xlsx', sheet_name=None )\n",
"sheets.keys()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are two sheets in the workbook, one called `\"ids_and_names\"` and one called `\"relationships\"`. Let's take a look at both."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" id name\n",
"0 0 Beak\n",
"1 1 Beescratch\n",
"2 2 Bumper\n",
"3 3 CCL\n",
"4 4 Cross"
],
"text/html": "
"
},
"metadata": {},
"execution_count": 3
}
],
"source": [
"df2 = sheets['relationships']\n",
"df2.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It seems as if the first sheet gives each dolphin, by name, a unique ID, while the second sheet shows the social connections of which dolphins spend time with which other ones. This is just how we discussed storing the data above; there is a list of vertices in the first table and a list of edges in the second table.\n",
"\n",
"But the data is not formatted conveniently. The second table would be more convenient if it included dolphin names instead of IDs. Let's use Python dictionaries and `replace()` to fix it."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" source target\n",
"0 Double CCL\n",
"1 Feather DN16\n",
"2 Feather DN21\n",
"3 Fish Beak\n",
"4 Fish Bumper"
],
"text/html": "
\n\n
\n \n
\n
\n
source
\n
target
\n
\n \n \n
\n
0
\n
Double
\n
CCL
\n
\n
\n
1
\n
Feather
\n
DN16
\n
\n
\n
2
\n
Feather
\n
DN21
\n
\n
\n
3
\n
Fish
\n
Beak
\n
\n
\n
4
\n
Fish
\n
Bumper
\n
\n \n
\n
"
},
"metadata": {},
"execution_count": 4
}
],
"source": [
"convert_id_to_name = dict( zip( df1.id, df1.name ) )\n",
"df2.replace( convert_id_to_name, inplace=True )\n",
"df2.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Python's NetworkX module\n",
"\n",
"The `networkx` module is pospular for working with network data in Python. You might already have it installed:\n",
"\n",
" * If you're using Deepnote, then when you attempt to import NetworkX using the code below, Deepnote will prompt you to install it first; just follow the prompts.\n",
" * If you're using Google Colab, NetworkX is pre-installed there.\n",
" * If you installed Python on your own computer through any of the methods described in [Chapter 3](chapter-3-jupyter) (including Anaconda or VSCode with Docker), that included NetworkX.\n",
" * If you have a non-Anaconda Python setup on your machine, you can install NetworkX with `pip install networkx`.\n",
"\n",
"The standard way to import NetworkX into your notebook or script is using the abbreviation `nx`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import networkx as nx"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This module lets us turn tables of data (like the edge list for dolphins we just saw) into Python `Graph` objects, which we can use for both computation and visualization. The first step in creating a `Graph` object is always the same; just call the `nx.Graph()` function and it will create a new, empty graph with no vertices and no edges."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"dolphins = nx.Graph()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will now add vertices and edges to that graph. Let's start with the vertices. Each NetworkX `Graph` object lets you add vertices with the function `add_nodes_from(your_list)`. We will use that function to add all the dolphin names to our graph. We can even check the size of the graph to be sure it worked."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"62"
]
},
"metadata": {},
"execution_count": 7
}
],
"source": [
"dolphins.add_nodes_from( df1.name ) # the column of all dolphin names\n",
"len( dolphins ) # how many nodes do we have now?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Similarly, we can add edges with the function `add_edges_from(your_list)`, but the list must be a list of ordered pairs. For instance, in our dolphin data case, we'd want it to be something like `[('Double','CCL'),('Feather','DN16'),('Feather','DN21'),...]` and so on. But we don't want to have to type out the entire dolphin relationships table as ordered pairs; it's too big!"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"159"
]
},
"metadata": {},
"execution_count": 8
}
],
"source": [
"len( df2 )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fortunately, we can use the same trick we do when creating a dictionary from two columns. Recall that `zip()` takes two columns and converts them into a list of pairs; we often used this to create a dictionary with the trick `dict(zip(df.col1,df.col2))`. We can use it with `list()` instead of `dict()` to create a list of the ordered pairs rather than a dictionary."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[('Double', 'CCL'),\n",
" ('Feather', 'DN16'),\n",
" ('Feather', 'DN21'),\n",
" ('Fish', 'Beak'),\n",
" ('Fish', 'Bumper'),\n",
" ('Gallatin', 'DN16'),\n",
" ('Gallatin', 'DN21'),\n",
" ('Gallatin', 'Feather'),\n",
" ('Grin', 'Beak'),\n",
" ('Grin', 'CCL')]"
]
},
"metadata": {},
"execution_count": 9
}
],
"source": [
"edges = list( zip( df2.source, df2.target ) ) # get the list of edges\n",
"edges[:10] # see if we did it right"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It looks like we did. Let's add these to the dolphin graph."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"dolphins.add_edges_from( edges )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We now have our dolphin data loaded into a NetworkX `Graph` object. This enables both computation and visualization, and we'll consider each of those in its own section, below."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Computations on graphs\n",
"\n",
"There are a great many computations that can be done on graphs; we will only scratch the surface here. You can learn more about graphs in MA267 at Bentley, and you can learn more about the capabilities of the NetworkX module through its documentation, [here](https://networkx.github.io/documentation/). But this section gives a few example computations that make sense for network data.\n",
"\n",
"We can ask how dense the network is, which is a measure of what proportion of its possible connections it actually has."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"0.08408249603384453"
]
},
"metadata": {},
"execution_count": 11
}
],
"source": [
"nx.density( dolphins )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Of all the possible social relationships among the dolphins (every possible pair that might hang out together), this network has only about 8.4% of those connections.\n",
"\n",
"The number of connections any one particular dolphin has is called the *degree* of that vertex. We can ask for a histogram of the degrees across the network."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[0, 9, 6, 6, 5, 8, 8, 7, 4, 4, 2, 2, 1]"
]
},
"metadata": {},
"execution_count": 12
}
],
"source": [
"nx.degree_histogram( dolphins )"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "",
"image/svg+xml": "\n\n\n\n",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"degrees = nx.degree_histogram( dolphins )\n",
"plt.bar( x=range(len(degrees)), height=degrees )\n",
"plt.xlabel( 'Number of friends, x' )\n",
"plt.ylabel( 'Number dolphins with x friends' )\n",
"plt.title( 'Degree histogram for dolphin network' )\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As you can see, no dolphin had zero friends, and thus we know that all dolphins appeared in some edge in the network.\n",
"\n",
"We see that some dolphins had many more social associations. If this were a network of humans, we might ask which people were the most influential in the social network. There are many ways to measure influence. One way is by a notion called \"betweenness,\" which considers all the paths through which information might flow in a network, and asks which vertices are on the largest proportion of those paths. This measure is called \"betweenness centrality\" and can be used to rank the vertices in a network by a measure of their importance.\n",
"\n",
"Although it doesn't make a lot of sense to measure this for dolphins (as opposed to humans), the code below illustrates how do to the computation."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"SN100 0.248237\n",
"Beescratch 0.213324\n",
"SN9 0.143150\n",
"SN4 0.138570\n",
"DN63 0.118239\n",
"dtype: float64"
]
},
"metadata": {},
"execution_count": 14
}
],
"source": [
"bc = nx.betweenness_centrality( dolphins ) # this is a big dictionary\n",
"bc = pd.Series( bc ) # now it's a pandas Series\n",
"bc.sort_values( ascending=False ).head() # let's see the top values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Although the particular numbers don't have units we can easily interpret, higher numbers are vertices that sit along a higher proportion of the network's pathways. There are many other ways to measure important nodes in a network; these are called centrality measures, and the full list of ways that NetworkX supports them appears [here](https://networkx.github.io/documentation/stable/reference/algorithms/centrality.html).\n",
"\n",
"```{admonition} Learning on Your Own - Centrality Measures\n",
"---\n",
"class: alert alert-danger\n",
"---\n",
"Choose 3 centrality measures from the documentation linked to in the previous paragraph. Write a brief report or slide deck for your classmates that provides the following information for each of the three measures you chose.\n",
"\n",
" 1. the purpose/intent behind the measure\n",
" 2. the formula for the measure\n",
" 3. the Python code for using that measure it on a NetworkX `Graph` object\n",
"```\n",
"\n",
"Let us turn now to how we can visualize the dolphin network."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Visualization of graphs\n",
"\n",
"### Drawing the dolphin network\n",
"\n",
"The NetworkX module has a small number of graph-drawing features, but they will be sufficient for our needs here. The simplest method is to just call `nx.draw( your_graph )`, but there are many options to help make it more attractive. The simplest form of the dolphin network looks like this."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "",
"image/svg+xml": "\n\n\n\n",
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"nx.draw( dolphins )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"While this shows us the general structure of the 62 dolphins involved, there's a lot it doesn't answer. But first, let's notice what we can from this picture.\n",
"\n",
"On one side of the graph, we see a dense cluster of about 20-30 dolphins who seem very social, and interact with one another more than most other dolphins in the network. There is a smaller cluster of about 10 or so on the other side that are also densely connected. Other than that, most dolphins have relatively few social connections. The dolphins in the center are an indirect social bridge between the two groups. But which dolphins are they? The vertices in the graph aren't labeled.\n",
"\n",
"The `nx.draw()` function takes many optional parameters, and you can see them all [here](https://networkx.github.io/documentation/stable/reference/generated/networkx.drawing.nx_pylab.draw_networkx.html). In this case, we might want to label the vertices with the name of the dolphin, and increase the size of the figure."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "",
"image/svg+xml": "\n\n\n\n",
"image/png": 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LkRp2j4jdc0iLfgwoMKvXHYV2RtpqUbsDz87toW/fvpQrV47Lly9TtWpVOnfurMEzzRlZ4y1J0kfr880XOXrr6Rsn7mRHoYBWzjas9qiZ94FJ0jvS1KqHUoa4uDi6d++Onp4ev/32W4HtXPI+mZubExsbi7e3N40bNwZg2rRpTJ8+Pct2WvrGWHX6BsPS1QEQQkXsqe3EntoOIuNiUse8KIVbj8KwVFUAkh/eIOnoMuIiHgMZ5Szfffcd33///Qdf+idrvCVJ+mh90bgsBjpv9yFsoKPNyMZl8zgiSXp3b9sNQqFQoFAoCsTt+A9ZaGgobm5ulClTht27d8uk+y3omNtiXLl5xroKKc9Junte/VyC/yFi/bahZ1sGuzG/YeMxH2XMEyL+mEF6YizpSXGE7/yBuIjHnDx5kujoaFxcXJg+fTq//PKLBs8qZ2TiLUnSR6uqvTmT3R0x1M3dR52hrhaT3R3fyxLNkpQTpUqVUifKL37tOHSS2V4BJKWp3ryTF+R2eyl7169fp169evTt25cVK1Z8VO0C85OudSms2o7FustkIKOLSerT+wCkRQZnbGNpj7ahCfq25UBLB5GWgjIuAmXMU0RaClraOtSqVQsLCwt1bf2tW7c0c0K5IP/FSJL0Ucu8vZ6T2/KoVBjq6zDZ3Unelpc+CO3ataNMmTLqn/fdjidZmbvaKZGuVNfGSm/v77//pk+fPvz888/07NlT0+EUaP9vFoVBicoYlHIhOegKsWd3Yd1xIvp2zsRfPsDzfzJWDFbGhIFKiZahKbqWdiBAy9AEVVI8zZo1o0yZMvz2228ANGjQQFOnlGPyN1GSpI+eR91SVLEzZ+WJQLxvR6AgY0W0TJnLEmuF3aZX1cJ41G2jsVgl6UWfffYZnTp1AjK6l7jOO05S8HVifDeTGhGElq4++iUqY9FkMDomlgAE/9gOAItmQ4m7uA8FUHzEOvU+nz1PwTgigoYNGxIQEMDMmTOZMmVKfp9agbJx40a++eYb/vjjD9zc3DQdzkfFrH4vkoOukBjgR1rDfhg7NyI94RkJVw+TGHAKhY4eBqVcMG/UHy3djAXQiveajkPQfq5fvcLly5cpW7Ysw4YNKxAXRHJypSRJn5SohBR2XQ4h4Ek8cclpmBro4ljUhG7V7Qi+c5O2bdsSEBCAmZmZpkOVPmGlSpUiODg4y4j3tZBY7heuRfC6MaBKx8ipAcrYcFIf30bXuiRFBy5Foa2jTrwVOvoYObqi0NHDsvUo9eNT1v3FgeVT8ff3l0n3GwghmDFjBp6ennh5eeHo6KjpkAq8y5cv023pEVRFK4Ii9xXPBX3iuxzxliTpk2JZSJ9hDctk/1z16ri7uzN79mzmz5+fz5FJ0sv279+f5edC1cJBpcS4cnOs2o5FpCsJWTGQtIhgkh9eU3eGACjcYhiFqrZ8aZ8rpozi2ZNgmXS/QWpqKsOGDePmzZucOXMGGxsbTYdUoKWnpzN//nwWL17MhDk/s+GhLklpb15a/r8K+sR3OblSkiTpBbNnz2b9+vUEBgZqOhRJYvfu3QghEEIwaON5lLEZC4foWtoBoNDWQcc8IyFUxoZnea2+nXO2+3z2JBhTU1M8PDzeY+QFW2xsLG3btiUqKgpvb2+ZdL+jBw8e0LhxY44cOcLFixeZOKTnJzvxXSbekiRJL7C1tWXChAl8/fXXmg5FkrIwNdBBxywjAUyLylgoSqQrUcZkJOM6ZkWybK/Q1s12P04N2xEXF0fLli0JDw/PdptPWUhICG5ublSoUIHdu3djbGys6ZAKLCEEGzdupHbt2nTq1Iljx45RokQJIGPuzWR3Jwx1tVEoXr8fhQIMdbU/ionvstREkiTpP8aOHYuzszPHjx+nadOmmg5HkgBwtDWlcI02JFw9zPMbxxHKVNLjwlElxqBrVQKDEpVztJ++Iydwt7Qlnp6etGnThhMnTmBiYvKeoy8Yrl69Srt27Rg7dizjx49H8aaMUHqlyMhIhg0bxp07dzh27BhVqlR5aZucTnxvUsGakY3LFuiR7kwy8ZYkSfoPAwMDfvrpJ8aNG8fly5c/+JXQpE9Dtxp2LP67DDY9ZxJzcgtJ9y+ipaOPkVNDLJoMfuUI93+5V7KlUpc1hIaG8vfff9OxY0cOHjyIvr7+ez6DD9uRI0fw8PBgxYoVdO/eXdPhFGiHDh3is88+o1evXmzduhUDA4NXblvFzpzVHjVfO/HdstDH829TdjWRJEnKhhCCxo0b07dvXz7//HNNhyNJAHy++SJHbz1944qV2Sno3SDep/Xr1/Pdd9+xa9euAtEL+kOVmJjIxIkT2bdvHxs3bpR3DLMha7wlSZKyoVAoWLJkCVOnTiU2NlbT4UgSAF80LouBztvdgSno3SDeByEEU6dOZfbs2fj4+Mik+x1cunSJGjVqEB0dzdWrV2XS/Qoy8ZYkSXqFatWq0a5dO2bNmqXpUCQJgKr25p9sN4i8lpqayoABAzh8+DBnzpyhQoUKmg6pQEpPT2fOnDm0adOG77//nm3btmFhYaHpsD5YstREkiTpNcLCwqhUqRJnz56lbFk5Wih9GLacDWK2VwDJyvTXlp0oFBkj3ZPdHQt8N4i8FBMTQ9euXTExMWHbtm0YGRlpOqQC6cGDB/Tr1w89PT02btyo7lgivZoc8ZYkSXoNW1tbvv76ayZMmKDpUCRJzaNuKXZ8XpfmFawRylT0dbJ23zDQ0UJfR4tWzjbs+LyuTLpf8PDhQxo0aEDFihX5448/ZNL9FoQQbNiwgdq1a9O5c2f+/vtvmXTnkBzxliRJeoPk5GScnZ1Zs2YNzZo103Q4kqR27Ngxvp02m89mr/nou0HkBX9/f9q3b89XX33F2LFjZbvAtxAZGcnnn39OYGAgW7ZsybZNoPRqsp2gJEnSG7zYXtDf31+2F5Q+GAcPHqRt80YMa1hG06F88A4ePEj//v1ZtWoV3bp103Q4BdLBgwcZMmQIvXv3Ztu2ba9tEyhlT5aaSJIk5UCXLl0oXLgwa9eu1XQokqR28OBB2rRpo+kwPnhr1qxh0KBB7N27VybdbyExMZEvvviC4cOHs2XLFhYsWCCT7rckS00kSZJyyN/fnzZt2nD79m3MzMw0HY70iQsODqZmzZo8ffoULS05jpYdIQRTpkxhx44dHDx4kHLlymk6pALn0qVL9O3blxo1arBixQrMzc01HVKBJn9TJUmScki2F5Q+JAcPHqR169Yy6X6FlJQU+vXrx/Hjxzlz5oxMunNJqVQye/Zs2rRpw7Rp09i6datMuvOArPGWJEnKhdmzZ1OxYkU+//xz+Ydc0qiDBw/Ss2dPTYfxQYqJiaFz585YWFhw/PhxDA0NNR1SgXL//n369euHgYEBly5dwt7eXtMhfTTkZbIkSVIu2NjY8PXXX/P1119rOhTpE5aSksKJEydo2bKlpkP54AQHB+Pq6oqLiws7d+6USXcuCCFYv349derUoVu3bhw9elQm3XlMJt6SJEm5NHbsWK5fv86xY8c0HYr0iTp58iTOzs5YWVlpOpQPyuXLl3F1deXzzz9n8eLFsgNRLkRERNClSxeWLl2Kt7c348aNk2VM74F8RyVJknJJX1+fn376ibFjx6JUKjUdjvQJkt1MXubl5UXr1q35+eefGTNmjKbDKVC8vLyoWrUq5cqV4/z581SqVEnTIX20ZFeT9ygyIYVdl0IICIsjLlmJqYEOjramdK8hFzWQpIJOCEGTJk3o3bs3w4YN03Q40ifG2dkZT09PatWqpelQPgi//vorP/zwA7t376Zu3bqaDqfASExMZMKECRw4cABPT08aN26s6ZA+ejLxfg+uPophxYlAfO5EAJCiVKmfM9DRQgCNK1gzslFZqtqbayZISZLe2ZUrV2jdujUBAQFytr+Ub4KCgqhduzZhYWGffCmASqViypQp7Nq1Cy8vL8qWLavpkAqMCxcu4OHhQa1atVi+fLn8DMsnMvHOY1vOBjHbK4BkZTqve2cVCjDQ0WayuyMedUvlW3ySJOWtoUOHYmZmxoIFCzQdivSJWLVqFWfOnGHTpk2aDkWjUlJSGDRoEMHBwezdu1fWu+eQUqlk7ty5/Pzzz/z888+yM04+k+0E81BG0n2LpDTVG7cVApLS0pntdQtAJt+SVEDNmjWLihUrMmzYMNleUMoXBw8epHfv3poOQ6OePXtG586dsbKy4u+//5adS3Lo3r179OvXD0NDQy5fvoydnZ2mQ/rkfNr3qHLh1KlTtG/fHktLSwwMDChTpgxffvklqampQEZ5yWyvgBwl3S9KSlMx2yuAayEx7yFqSZLeNxsbGyZOnMiECRM0HYr0CZBtBDNKbVxdXalZsya///67TLpzQAjBunXrqFu3Lt27d+fo0aMy6dYQmXjnwPbt22nUqBH79+/H3t6efv364eDgwOrVq0lMTARgxYlAkpXpAIj03HU5SFams/JEYJ7HLUlS/hgzZgw3btzg77//1nQo0kfO19eXSpUqYWlpqelQNOLixYu4uroyYsQIFixY8MnXuOdEZpvAZcuWyTaBHwBZavIGiYmJfPHFF6Snp+Ph4YGnp6f6H+y9e/cIDw/HwsICgMKtRhJ7ajs6hYtj22cuqeEPeOa9gdSwjKRav1gFLJp+hq5lxlVm3IW9xF/6C2V8FGv1Dbn+S1XWr11DhQoV2LZtG7NmzeLBgwcYGhpSoUIFfvrpJxo0aKCZN0KSpFfS19dnwYIFjBs3Dn9/f3R05Eer9H58ym0E9+/fz+DBg1mzZg0dO3bUdDgFgpeXF0OGDMHDw4Pt27ejry87qmmavOR5g1OnThEdHQ3AlClTslwllilTBj09PfXPMT6bMXCogX5xJ5QJ0TzdOonkB5fRL1YBPZsyJN27wNNt35KenEDas8c8O7YGVUoihSo3w6h0Ne7cC+LJkyckJSUxcOBAgoOD6du3L23btiUuLo579+7l+/lLkpQznTp1wsrKirVr12o6FOkj9qkm3qtWreLzzz9n//79MunOgefPnzNixAhGjhzJb7/9xvz582XS/YGQwzJvEB4erv6+ZMmSr93WqtMkDEtVBSD27C5UKc/RL1GZIt1/AODx+tGkhd8nMcAPA7uKAGgXKoxRhfroWpage8OquLlVJikpifT0dIoUKUKnTp1wdnbGwcGB9PT093SWkvQy2Yc+dxQKBYsXL6Z169b06tVLtuaS8tyDBw+Ijo6mevXqmg4l36hUKr799lv27NmDn58fDg4Omg7pg5fZJrB27dpcvXoVMzMzTYckvUCOeL9BkSJF1N8HBwe/dlsDO2f198rYjIRd19Je/VhmiYkyNhxdK3vMGvQlPSGa8B1TCV05kA1jO3Hr1i0KFSrEqlWrEELQvn17ypQpg729PSdPnszLU5OkbF19FMPnmy/iOu84i/++w54rjzkeEM6eK49Z8vcd6s87zrAtF7n6KEbToX5wXFxc6NChAzNnztR0KNJH6ODBg7Ru3fqTqc9NTk6mT58+nD59mtOnT8uk+w2USiUzZ86kbdu2zJw5k82bN8uk+wP0afz2voP69eura7hnzZqFSvVv15Lg4GDS0tLUPyt0dNXf65hlJOxpUSHqx5TRoernhCods/o9sB+zjeIj1mNatxuxYcEsXrwYgAEDBhAaGsrjx49ZunQpISEh8o+59N5tORtErzVnOXrrKSlKVZbFnwCS///YkX+e0mvNWbacDdJMoB+wmTNn4unpyZ07dzQdivSR+ZTKTKKjo2nRogVCCI4ePfrJTibNqXv37uHm5oavry/+/v706NFD0yHlq8iEFFb73GPsDn8Ge15g7A5/VvvcIyohRdOhvUQm3m9gbGzMzz//jJaWFlu2bKF69ep8/vnntGvXjvLly/P8+fPsX1exCQp9Y1IeXiN81wye7phK6tN7aBmbY1TBlfS4SEKWDyBi91xiz/1ByoPLAOrb0zY2NnTq1ImZM2eyc+fOLM9JUm41btwYhULBxo0bs30+KCgIhUJBv3qlSUp7/eJPkLUPfU6S74EDB6JQKJg2bVquYy9obGxs+Oabb2R7QSlPJScn4+Pj80m0Ebx//z7169enXr16/PbbbxgYGGg6pA+WEIK1a9dSt25devXqxeHDhylevLimw8o3BfEOrUy8c6Bv3754e3vj7u7Ow4cP8fT05NatWwwdOhQjI6NsX6NjYolt7zkYlK5GSsgtUsMCMSxTC9vec9E2NEGhb4R+0XKkhN4i4cphlPFRdO7WnSlTpgDQokULLl++zLp167h58yZt27Zl4cKF+Xna0gfq22+/RaFQMGDAAPVjI0eORKFQ4OLion7s119/RaFQ0LRp0zfu82G8wKJ2R0xqdlA/FrJyMME/tiM5+NorX/ffPvSZCbxCociyXcuWLRkzZgx169bN4VkWbKNHj+bmzZscPXpU06FIHwlfX18qV65M4cKFNR3Ke3XhwgUaNGjA6NGjmT9//idTVvM2wsPD6dSpEytWrODEiROMGTPmk3q/CuodWjm5MocaNmxIw4YNs31OCMHnmy9y9NbTLCOFerZlsOmZfXmItqGJetIlKhVVrRT8MaGtOmHJHOWWpP/KbCl56tQp9WOnT58G4Pr168TFxWFqaqp+3tXV9Y3zA7ZcicKs2dA3jnRnJ7MP/WqPmq/cpk+fPvTp0yf3Oy+gMtsLjh8/XrYXlPLEp1Bmsm/fPoYMGcK6deto3769psP5oB04cIChQ4fSv39/fv/990+uY0lBXin807k0es++aFwWAx3tt3qtno4Wt3f/TIsWLbh+/XoeRyZ9bOrXr49CoeDevXuEhYURHx/P9evXcXZ2RqVScfbsWYAsiXemBw8e0LRpU4yMjHB1dSU4OJjIhBT+Pn+DoLntCP6xHZAx2p0elzFB+Olv3xH8YzsSrmUsDpN49xxPPMfxcFF3QlYOIurvtRy78Qj/m7cpXbq0+liZI99BQUEvlZpMmzYNhUJB9+7d6dOnD8bGxjg7O3Ps2LH3/v7ll06dOmFtbc2aNWs0HYr0EfjYE+8VK1YwYsQIvLy8ZNL9Gs+fP2f48OF88cUXbN++nR9//LFAJ92lSpVS/63I7uv48eNMnz6dMmXKoK+vj6WlJRWrVufr2UvVSXfY1kkE/9iOhwu6okzIaP+sSk4g+MeMv2nKmKcAJMTF8sWwoRSxKYq+vj4lSpRgzJgxpKRk1IHfunWLOnXqYG5ujr6+PiVLlmTMmDEkJyfn6TnLxDuPVLU3Z7K7I4a6uXtLDXW1mNq+Ijd8D9ClSxeaN2/O8OHDs7QxlKQXWVhY4OTkBGQk12fPnkWlUqlrik+fPk1YWBj37t1DoVBkKe+YM2cORYsWxcrKitOnTzNlyhR2XQp56RiFqrRAoZexDLNRhfqY1OyArpU9SfcvEfHHTJQxTzEqVxdtQ1PiL+wh/OBKvB8kMGjQIPU+xowZw5gxYzA1NX3lufzxxx9ERUXRoEEDbt26RYcOHXj69GmevE+altlecNq0acTExGg6HKkAu3//PjExMVSrVk3ToeS5zM+u5cuX4+fnR82ar75z9qk7f/481apVIzExkatXr77yLnxBMnjwYPXfisx1Ubp27ap+7NKlS0ybNg2lUsmgQYNo1aoVoeFRJDz656V9CWUKcWdeXS3w7Nha4q79zfOUNLp3705cXBzLli1jzpw5AERFRaGjo0P37t3p0aMHERERLFu2jLlz5+bpOcvEOw951C3FZHcnDHW1+U+J60sUCjDU1WayuxMedUuho6PDyJEjCQgIwMjIiIoVK7JgwQL1lZgkvShzFPvUqVPqke0OHTpQvnz5LI9VrFgxy6Tczz//nK1btzJ9+nQA/P39CQiLI/U/tXHmDXqjZWACgEn1dhRu/jn6xSoQf+kvAPRsyqBlaIJesQoAxF07xv3oVKZOnarex5IlS1iyZMlra1JdXFw4fPgwhw8fxsXFhcTERHbt2vUub80HpWrVqnTs2FF2JJLeycfaRjA5OZlevXpx4cIFTp06leWOmfQvpVLJ9OnTad++PbNnz2bTpk0fTZvAqVOnqv9WGBpmDPaMGjVK/VhmmeSSJUtYvXo1y37dgM2Q1Zg3HpTN3hTEXzmEMj4y22MpY54AYFy3B0tXr2PIkCFAxtwkyCjjPHXqFGvWrGHz5s3q5x88eJCHZywT7zznUbcUOz6vSytnG/R1tDDQyfoWG+hooa+jRStnG3Z8XvelWiMLCwsWLVrEqVOn8PX1pWLFiuzevRvxNsW30kfrv4l3hQoVsLS0pEGDBpw9exZfX98s22XKHDHLTMYTEhKIS1bm+LiZ/emTg/yJv7iPBH+v/z8jePzo9X3us+Po6PjS9yEhL4/AF2SzZs2S7QWld/IxlplERUXRvHlztLW1OXLkyEc/afRt3b17V50QXr58me7du2s6pHxVtGhRAIYOHUq/fv348vsfSYt5irahyUvbGjk2gPQ0Yl8x6m1SswNo6RB9ajvuXXqwdu1aLC0tGTVqlHqb6Ohoxo4dS79+/Vi7di3m5uaMGDEiT89Jzvh5D6rYmbPaoyZRCSnsuhxCwJN44pLTMDXQxbGoCd2qv3nlv/Lly7Nv3z7+/vtvxo0bx7Jly1i8eHGWrhXSpyszofb390dfX1/ds7VBgwasX7+ezZs3Axn14C/KnOT3YtcRU4PsPwYU/x9de/GiT8esCGmRD7FoPgzTmv/WYabFhFGyrCPa2v/Oc1CpVG8coQsICHjpezs7u9e+pqApUqSIur3gvn37NB2OVMAkJyfj6+ur/p3+GNy7d482bdrQtWtXZs+e/dGN5OeFzDaB3377LVOnTmXUqFGf5Pv0/fffc/nyZS5evMiWLVsyHlRoYVa/J+ZufbNsq1/cEVXKcxKuHsbE5eULVf2i5dEv7kjKoxucP5rxWdytW7csCzPFxcWxdOlS9c+NGjWiRIkSeXpOMvF+jywL6TOsYZl32kfz5s3x9/dn3bp1tG7dmvbt2zNr1ixsbGzyKEqpICpbtiw2NjY8ffqUtLQ0dYKdmZA/e/Ysy8+v42hrip7Oyx/o2iZWKGPCiPXbSlLgOUxrd8akejuS7l0k5sQGUkJvodDRIy0iCFVSHPFll6JS1UNPT4/U1FT69OlDyZIlmTdv3iuPffXqVVq1agXAlStXMDIyomvXrrl+Pz50o0eP5pdffuHo0aO0aNFC0+FIBYiPjw9VqlRRL+RW0J07d45OnToxbdo0hg0bpulwPkjh4eEMHTqUhw8f4uPjQ8WKFTUdUr6Ki4vj+vXrhIaGEhoaSvv27SlZsiS3bt3ifmQiyeFBxJ7ajkmNdmgbZS25MXfrS9imy8Se2fHSfiP2/EjqkzuYNxpAh76fUejKdlauXIlCoeD3338HMiZ7CiGIiIjgm2++YcOGDQwcODBPW8N+epdPBZCOjg7Dhg3j9u3bmJubU7FiRX788cc8n2krFSwvjmZnfl++fHmKFMlYNbVIkSKUKfPmC79uNbIfYTZv0Acdi6KkhAYQf3Ef6c9jMCxTE+suk9EtUpqk+xdJvHMGFArManYg+qIX1apVw9raGiMjI3bs2MGKFStee+zu3btja2uLn58fjo6O7N69G1tb25y+BQVGZnvBcePGoVTmvLRHkj6mMpM9e/bQvn171q5dK5PuV9i/fz9Vq1bFycmJc+fOfVRJd1paGg8fPuTMmTPs2rWLpUuXMnHiRPr27UujRo2Ij48HMtrP9urVi8WLF7N7924SExNp3rw5P/74Ix0nLvn/3gQi7eU5cPrFKmBYphaJt/xePn7kQ/U2hU1N1BN5b93KaDOYeXwAa2tr9SBJXpcJyhHvAsTMzIyffvqJYcOGMXHiRJydnZk/fz5du3Z9acES6eP3559/Zvt4dl1BTpw4keXnTp06ZSkhaV67Eke/3Z+lj7dBySoUH/ZyKzyj8vUwKl9P/bNCAa2cbVjtUROlUsmZM2c4ePAgXl5ePHr0iN69e+Pu7s78+fPVFwXqYxgYsHHjRjw9PXNyygVax44dWbZsGWvWrMnzmkHp4+Xl5cX27ds1HcY7W7ZsGfPmzePgwYPUqFFD0+F8cJ4/f8748eM5cuQIO3bsKHAdS+Li4ggJCVGPUmf3FRUVRZEiRShevLj6y87OjipVqlC8eHE6duxIfHw8+/fvp3HjxkBGKcivv/6Kq6srdnZ2nD2RsWaFTuHiaJtaZxuLmVtfku5deOlxfTsnkh/4E31wGZcSrrHt3HHg37UxRo8ezT///EPlypVJSUlRlwZm3pXNKzLxLoDKli3Ln3/+ibe3d5b6b/lhJr2tLxqX5eTdSJLS0nP9WgMdbUY2Lgtk3J1xc3PDzc2NOXPmEBoaysGDB9mzZw9ffvkl5cuXx93dndDQ0Lw+hQ+eQqFgyZIltGjRgl69en00pQPS+3Pv3j3i4+ML9NyezHaBhw4d4vTp05QsWVLTIX1wzp07h4eHB/Xr1+fKlSsfVMeS9PR0nj59Smho6GsTayBLQl28eHGcnZ1p2bKl+mcbG5ss84D+K7sa9p49exIfH8+lS5c4cuQIZuYWFKpQH9NGA1454KhvWxbDsnVICjyX5XHLtuOI8d5AcvBVzh3+ExsbG7744gt+/PFHAOrVq8f58+f57bffUCgU2NvbM2bMGCZPnvy2b1+2FEK2yyjQ0tPT2bBhA99//z1t2rRh9uzZ6lnAkpQbuVkJLJOhrpa6JeabpKamcurUKby8vPD09CQiIgIHBwdmzZpFy5YtsbS0fIfoC45hw4ZhbGzMokWLNB2K9IFbvnw5ly5dYsOGDZoO5a0kJSXh4eFBdHQ0f/75p7zY/A+lUsmsWbNYtWoVK1asoFu3bvl6/OfPn7+UQP83uQ4PD8fS0vKlpPq/o9avW68hr2W3UnhOvXiHVlNk4v2RiIuLY86cOaxdu5Zx48Yxfvx4dU9MScqpjOQ7gGRl+ms/1BSKjJHuye6Ob738bnBwsLokJXMCkbu7O+7u7ri4uHy0M/jDw8OpWLEifn5+VKhQQdPhSB+wtm3bMmDAAHXXooIkIiKCjh07Urp0adavX1+gV1d8H+7evYuHhwfm5uZs2LCBYsWK5dm+VSoVERERrxydzkyuU1JSsiTP2SXVRYsWRVdXN89iywtXH8XQa83Zt7pDa6irzY7P61LFzjzvA8shmXh/ZO7fv88333zDhQsXmDdvHj169JD131KuXAuJYeWJQLxvR6AAkl9YXMdARwsBNKlgzcjGZfPswys5OZmTJ0/i5eXFwYMHiY2NpXXr1ri7u9OiRYssiwB9DBYsWICPjw9//fWXpkORPlBJSUnY2NgQHBxc4EaKAwMDadOmDT179mTmzJnyb9ALhBCsWbOGyZMnM3XqVL744otcDTIkJye/to46NDSUJ0+eYGpqmu3I9Is/W1hYFNj/N+/7Du37JBPvj5Svry9jx47F0NCQJUuWUKtWLU2HJBUw79KH/l3du3dPPRru5+eHi4uLejS8cuXKBfaPRaaUlBQqVarEihUraNmypabDkT5Ahw4dYvbs2eqV+wqKM2fO0KVLF2bMmMHQoUM1Hc4H5enTpwwZMoTQ0FC2bNmCs7Oz+jkhBNHR0a8s+cj8io+Pp1ixYq8s+ShevDjFihX7JO4wqO/QpqXzukQ2L+7Q5iWZeH/EVCoVmzZtYvLkyTRr1oy5c+dSvHhxTYclSbmSlJTEiRMn8PLywsvLi5SUFNq0aYO7uzvNmzfHxOTlFcwKgr179zJ58mSuXLmiXthIkjKNGTMGGxsbvvvuO02HkmN//vknw4cPx9PT86NpgZgXUlNT2bx5MxMnTqRhw4a4urry9OnTLMn148ePMTAweGXJR+aXlZXVR1uG9zauhcTwzabjBMRqo6+nly93aN+VTLw/AfHx8cybN4/Vq1czevRoJkyYgJGRkabDkqRcE0Jw9+5ddRJ+5swZateurU7EnZycCsxouBCC5s2b07VrV0aOHKnpcKQPTLly5di5c6dGO5pEJqSw61IIAWFxxCUrMTXQwdHWlO41Xr7rtWTJEhYsWMBff/1FtWrVNBRx/hJCEBsb+9pa6pCQEKKiolAoFFSoUAFHR8dXJtfy7/Lbadq0Kf2HjiSleDWN3KHNrQ8y8c7NL7uUc0FBQUyaNInTp08zd+5cevfuLa+cpQItISEBb29vdSKuUChwd3enTZs2NG3aFGNjY02H+FrXrl2jRYsWBAQEFLg6Xun9CQwMpGHDhoSGhmrkQvLqoxhWnAjE504EACnZjCI2rmDNyEZlqVTMhK+++oq///4bLy+vPF9eW1OUSuVLo9LZfWlpab2y5CM6OpoZM2bQsGFDfv7553zt/PGpePDgAbVq1SI0NLTAlNd8UIl3bn7Zq9qbaybIj8CpU6cYO3Ys2traLFmyhLp162o6JEl6Z0II/vnnH3Vt+IULF6hfv756NLxcuXIf5Gj48OHDMTQ0ZPHixZoORfpA/Pzzz/j7+7N+/fp8P3ZuOhvp62hh/egkusFn+fPPPwvMJOiEhITXttALDQ0lIiICKyur17bQK168eLalbmlpacyaNYvVq1ezcuVKunbtqoGz/DRMnz6dyMhIfv75Z02HkmMfTOKdn23MpIz67y1btvDdd9/RqFEjfvzxR+zt7TUdliTlmbi4OI4dO6YeDTc0NFRP0GzUqNEH025TtheU/svd3Z1BgwbRvXv3fD3ui50iIvcv5vmNY5i59sbcre8rX6OlUjK1fSUGNiiTj5FmT6VSER4e/sbe1Glpaa9toVe8eHFsbW3fqo3enTt38PDwoHDhwqxfvz5P2wRKWalUKsqWLcvOnTsL1AKCH0TiveVsEJ/36kBS8HUs3cdSqErzN77mQ2kLU9A9f/6c+fPns2LFCr744gsmTpz4wd+el6TcEkJw7do19Wj4lStXcHNzU5elODg4aDS+hQsX4u3tzf79+zUah6R5SUlJFClShEePHuV6BPn+/ftMmDABPz8/4uLisLKyUnfP0dbWpnTp0kDG78N//bc38vObJ0h5cgdDhxoYOrw+qcmP3shJSUmvLfkICQkhLCwMc3PzN/amNjc3z/O7X0IIfvnlF6ZMmcK0adP44osvPsg7bB+TEydOMHr0aK5evVqg3ut8TbxLlSpFcHDwy48PXU5s0HWUz55g7NwI/WI5G/X5EBqhfywePnzIt99+i4+PD3PnzqVv376y/lv6aD179oyjR49y8OBBDh48iLm5uXo03M3NLd9rBVNTU6lYsSLLly+nVatW+Xps6cNy8OBB5s6di6+vb65fW7VqVa5du0bTpk0pX748ISEh+Pr6cuDAAezs7F6beL+4GqBQpaPQevXS3v/1LqsBCiGIiop645Lkz58/z7aN3ovJddGiRTVS5/v06VM+++wzHj9+zNatW3Fycsr3GD5FAwcOpEqVKowfP17ToeSKRhLvdu3aUaZMxm2pY7eeElO+NdqFrHK9vw9h6c+PzdmzZxk7dizp6eksWbIEV1dXTYckSe+VSqXC399fvXjPzZs3ady4sXo0PL8mi+3du5fvvvuOq1evyvaCn7DRo0dTtGhRvv3221y9Ljo6GktLS8zNzYmOjlaPAKakpHDv3j0qVqz40msePHjAtGnT8PT0xKxaG1KePSH54Q1ses4g4fqxLKUmMSe3EnvqN4wquIK2Dkl3z6JjWgSLFsMwLOWCvo4W+4dUZcGc6Rw+fJioqCgqV67M2LFjKV68OKGhoezbt0+9QJZCoUBbWxuVSoWJickba6ktLS0/yFHNffv2MWzYMAYNGsS0adPQ09PTdEifhPj4eOzt7blz5w5FihTRdDi5I/JRyZIlBSB2794thBAiIj5ZlJ/iJUpO2i/07SsJQFi6jxU2vecIQOhalxIlJ+0XJSftFzZ95mY8ZlVClJy0X9h/tUuY1u0mdC2KCiMjI1GtWjX1fqV3k56eLrZu3Srs7e1Fz549RVBQkKZDkqR8ExERIbZu3So8PDyElZWVqFixovj666+Ft7e3SE1NfW/HValUolmzZmL58uXv7RjSh69MmTLiypUruX5damqqKFSokABE1apVxbhx48Tu3btFQkKCiIqKEoMGDRKAAMSYMWPEmDFjRFRUlBgwYID6cX37SsK4cnNhO3CJMK7UTADCzLW3KDlpvzBz7f3/7RTCoHQ1YVC6mgCEQldf2H25WZT+Zo8wL1pKAMLY2Fjo6+tnPK9QCBcXF9G5c2ehpaUldHV1RePGjUWLFi1E2bJlxa+//voe3sX3Lz4+XgwZMkSULl1anDx5UtPhfHLWr18vOnTooOkw3opGagnWrVvH2LFj6TFwOOFHfnnpef0SldE2tSYtIoi0yEcAPA/wA8C4UlMAoryWEXd2F1r6xlRu0JJHjx7RpUsXTpw4kW/n8bHS0tKiT58+BAQE4OzsTI0aNZg8eTLx8fGaDk2S3jsrKyv69OnD5s2bCQsLY926dRgaGjJx4kSsra3p2rUr69at4/Hjx3l6XIVCwaJFi5gxYwbPnj3L031LBcPdu3dJSkqiSpUquX6trq4u69atw8zMjKtXr7J48WI6d+5MmTJluHfvHlOnTlVvu2TJEpYsWULhwoXVj+nbV8K2749YtR2Lvm3ZVx5Hz8YBm54zsek5E90iDoi0FBIDTpEUdp+YJ0EYGhrSoUMH+vXrR7Vq1RBC0KpVKzZt2gRAkSJF+Oqrr1i9ejV3795l8ODBuT5XTTtz5gwuLi4olUquXLlCgwYNNB3SJ2fDhg0MHDhQ02G8FY0k3vv372fp0qV4/7GRmPN7X3peoVBgXLEJAM9v+SKEisTbp0ChhXHFJqQnxpJ4yxcUWugVcyRF24iKFSsihGD16tX5fTofLSMjI6ZOncrVq1cJCQnB0dGRDRs2oFKp3vxiSfoIaGtrU6dOHaZPn8758+e5ffs2HTt25OjRo1SqVIlq1arx3Xff4efnh1KpfOfjValShc6dOzNjxow8iF4qaA4ePEjr1q3fuqSiR48ehIWFcejQISZPnkyRIkV4+vQpM2fOzHZ7lUpFQkICAPrFHXN0DB1LO/X3uv//XhkfiTI2HMiYBPnbb7+xdu1a/P39gYy+5IUKFWLVqlUIIWjfvj1lypTB3t6ekydPvtW5akJaWhpTp06lU6dOzJ8/nw0bNsje3BoQGBhIQEAAbdu21XQob0Ujiffu3bsRQjBo43lKTsp+Fn+hys0AeB5wkpSHN1A9j8GgVFV0TCxRxj7N2EioiL+8nysHt+Hj4wNk/A+R8lbx4sXx9PRk9+7drF27llq1ar3VxB9JKuhsbGzo378/27dvJzw8nOXLl6NQKPjyyy8pUqQIPXv2xNPTk6dPn771MWbOnMmWLVsICAjIw8ilgsDLywt3d/e3em1aWhp+fn4YGBjQqlUrZs2apa4Tj42N5fbt2+pte/XqRbVq1TAxMeHgwYMAKLRz1jpPGRXy7zH//72OiRU6Zhl1tsWKFSM5ORkhBEIIEhMTWb58OQADBgxQL4++dOlSQkJCXnlR8KG5c+cOrq6uXLhwgStXrtClSxdNh/TJ8vT0pE+fPgW2nl6jM3hMDV59eN3CxdErVoHUx7eJObkV+LfMRMfMJmMjbR3svvCkhE48o2ubU69evQ9y8sXHonbt2vj5+fH777/Tv39/atWqxfz589Uz5SXpU6Kjo4Orqyuurq7Mnj2bx48fc+jQIf766y/GjBlDuXLl1Iv31KpVC23tnHWJsLa2ZtKkSUyYMEG2F/yEJCYmcurUKXbs2PFWr09OTsbNzY2SJUtSpEgRkpKS1Mn26dOnGT9+PFpaWqhUKoKDg6lSpQqHDx+mR48e+Pj4IFTpOTpOavgDnu74HoC08PsodPUxquCKkZkFRhWrcf+mP7Vq1aJ+/fqEhYXh4+PD4sWLGThwIDY2NjRu3JhixYpx/fp1gA9+0R3xQpvA6dOnM3LkSJlnaJBKpcLT05O//vpL06G8NY32i3O0NUVf59UhFPp/op0SchOFniFG5esBoG1khpGjG6QrebrpK8J9tzNu3DhKlSqFi4sLQ4YMYdOmTdm2LpTejUKhoGfPnty6dQsXFxdq1arFpEmTiIuL03RokqRRxYoVY/DgwezatYuIiAgWLFhASkoKQ4cOxdbWFg8PD7Zu3UpkZOQb9/Xll19y+/ZtDh8+nA+RSx+CEydOUL16dczMzF67XVpaGrdv32bv3r3MmzePQYMGUa9ePezt7dHX1ycyMpKrV68SEBCAlZUVo0aNIiEhgZs3b7Jw4UKsra05e/Ys27Zto0KFCty5cwcgx510jBxd0Ta2ICXkH3Qs7bDuMhntQhag0MLrr30MHz6cuLg4Nm7ciL+/P+7u7urVkVu0aMHly5dZt24dN2/epG3btixcuPDd3rj3KCwsjPbt27N27Vr8/Pxkb+4PwPHjx7G0tKRq1aqaDuWtaaSd4O7du+nUqRORCSm4zjtOilJF2NZJpDy6kWUBnfSkeEKW94N0JcaVm2PVdqx6X6rUJGJP7yDp9mm0EqMoXLgwtWvXplu3bsTExODr64uPjw8GBgY0bNiQRo0a0bBhww922eiC6smTJ0yePJmDBw8yc+ZMBg0alOORPUn6VDx69Ei9eI+3tzfOzs7qdoXVq1fPtmf+vn37mDRpEteuXZPtBT8BX375JcWLF2fSpEnAv+UhAQEBWb4ePHhA8eLFcXR0fOnLyir7trxCCC5dusTWrVvZvn07xYoVo2/fvvTq1Uu9smLLmbu4naCP4hXrN2S2EzSu1AyrduOyPPcxtvbdu3cvw4cP57PPPmPq1KkFtqzhY+Ph4UHt2rUZPXq0pkN5axpfufLFpv259aZfdiEEd+7cUSfhPj4+KJVKGjZsqP6qWLGiXCgmD1y6dIlx48YRFxfH4sWLadKkiaZDkqQPUkpKCn5+fuql7KOjo9UlKS1atMDCwgLI+Pxq0aIFnTt35osvvtBw1NL7oFKpCAkJ4datW/Tt25dmzZoRERFBQEAA8fHxVKhQ4aXkumzZshgYGORo/4GBgWzbto2tW7eiVCrp27cvffr0wdHx34mUaWlp9OzZk4PnblKs30+kK7IfOHld4v0xLWYXHx/PuHHj8Pb2ZtOmTXItiw9IbGwsJUuWJDAw8JUXmQWBxhPv/y5Tmxu5/WUXQhAcHIyPjw++vr74+voSHR2Nm5ubelS8atWqcnTpLQkh+OOPP/j6669xcXHhp59+omzZV7elkiQpYxGTzNFwX19fqlatqh4N19LSokWLFty6dStL6zepYElKSuLu3bsvjV7fuXMHc3NzSpQowbVr15g7dy5OTk44OjpSvHjxt7o7+/TpU3bs2MHWrVt58OABPXv2pG/fvtSpU+el/QUHB9OgQQMiIyPZs2cPEWYVmHngH1KUL6cFr0q8DXW1mOzuhEfdUrmO9X2KTEhh16UQAsLiiEtWYmqgg6OtKd1r2GFZKPvVLc+cOUO/fv1o1KgRS5YswcTEJJ+jll5nzZo1HDp0iD/++EPTobwTjSfeAFvOBjHb6xZJaTlvU5dXv+yhoaGcPHlSPSoeEhJC/fr11aUpNWvWlLeYcik5OZmlS5fy008/MWjQIKZMmfLGukVJkjISNB8fHw4ePMiBAwdISkrC1NSUMmXKsG3bNtm67AMmhFCPVv/368mTJzg4OKiT6syv8uXLY2pqytKlS7l+/Tpr1659q2PHx8ezZ88etm7dytmzZ2nfvj19+vShefPm6Opm361k+/btDBgwADs7O06dOoWtrS1CCOp6fE1UiUakK7ReeydaoQADHW0muzt+UEn31UcxrDgRiM+dCABSlP/mFQY6WgigcQVrRjYqS1V7cyBj1H/GjBmsWbOGVatW0blzZw1ELr1J/fr1+fbbb2nfvr2mQ3knH0TiDZnJdwDJynSN/rJHRETg5+enHhW/e/cutWvXVpem1K1bF0NDwzw/7scoLCyM77//nr/++ovp06fz2WefybsJkpQLd+/e5ffff2f69Ono6upSu3Zt3N3dcXd3x9nZWc5X0QClUsn9+/ezTbCBl5JrR0dHSpcu/drPvlatWjFs2LBctahLTU3l8OHDbNu2DS8vL9zc3Ojbty8dOnTA2Nj4tfEPHTqUzZs306NHDzZt2qSObdu2bcybN48Ne4/xq18Q3rcjUADJ2SSvTSpYM7Jx2Q+qvORt8ohaFil4eHhgZWXF+vXrKVq0aP4FLOXY7du3adSoEY8ePXrlxWRB8cEk3gDXQmJYeSLwg/plj4mJ4dSpU+rSlOvXr+Pi4qIuTalfv768HfUGV65cYdy4cURFRbFo0SKaN2+u6ZAkqUBZtGgRhw8f5ssvv1SPhqtUKnUS3rRpUwoVKqTpMD8qcXFx2SbX9+/ff+3kxtxeDCUmJmJjY0NoaOgb72ioVCpOnz7N1q1b2bVrFxUqVKBPnz706NEjRzWvoaGhNGnShKCgIFavXp1l1cioqCgqVarE3r17qV27dsZjCSnsuhxCwJN44pLTMDXQxbGoCd2qv7pcI7dOnDhBkyZNKFmyJEFBQW+9n7e5c66jUJHgu4mpfZrg5ORE06ZNMTMzIyYmJtvtBw4ciKenJ2PGjGHJkiVv3H9enZsE3377LWlpaSxYsEDTobyzD2r4sYqdOas9aubLL3tOmZub07ZtW/UKSc+fP+fMmTP4+voyZ84cLl26hJOTk7o0pUGDBrIW8z9cXFw4fvy4epa4s7MzCxYsoHz58poOTZIKhFGjRrF69Wp0dHRYsWIFy5cvJyAgAC8vL5YtW0bfvn2pW7euOhEvX768HA3PASEEISEh2SbYsbGxWSY39u7dG0dHR8qVK5fjyY054e3tTY0aNV6bdN+4cYNt27axbds2jI2N6du3L+fPn8/VGgr79++nR48eFCpUiCtXruDs7Jzl+QkTJtCjRw910g1gWUifYQ3L5P6k/uP+/ftMmDABPz8/4uLisLKyolKlSqxYseKd9w0Z5SWzvQJylXQDKIUWZo0H0aBDfaIDr+RJLFLeS09PZ9OmTR9Ne9UPKvHOlFe/7O+DsbExzZs3V4/aJicnc+HCBXx8fFi+fDkeHh6ULl06S+cUGxsbDUeteQqFgk6dOtGmTRt+/vlnXF1d6devH99//726i4MkSdnT09Nj4cKFjB8/nmbNmqGrq4uTkxNOTk589dVXxMfHc+zYMby8vFi0aBG6urrqJLxx48YYGRlp+hQ0Kjk5OdvJjbdv38bMzCzLqHWnTp3Ukxvzo+PVq1arfPToEb/99htbt24lKiqK3r17s2fPHqpWrZqriyqlUsm4ceP45ZdfqF+/Pn/99ddLd2mPHz/OsWPHuHnz5jufT3Y6d+7MtWvXaNq0KeXLlyckJARfX1+ePHmSJ/tfcSKQZGXuGzQApKoEK08E0ssuT0KR3oOjR49SrFgxKlWqpOlQ8oaQ8lRqaqo4d+6cmD9/vmjXrp0wNzcXFSpUEEOHDhVbtmwRDx8+1HSIH4SnT5+KYcOGiSJFiojly5eLtLQ0TYckSR80lUolmjdvLn7++ec3bnft2jXx448/ioYNGwoTExPRunVrsWzZMhEYGJhP0eY/lUolwsPDha+vr/j111/F+PHjhbu7u3BwcBD6+vrCyclJdO7cWXz77bfC09NTnD9/XsTGxmo85tKlS4tr164JIYSIjo4Wv/76q2jUqJEoXLiwGDJkiPD29hZKpfKt9v/48WNRpUoVoaenJ6ZNmyZUKtVL2yQmJoqyZcuKffv2vdO5vEpUVJQAhLm5eZbjJycni+fPnwtvb28BiJIlS4qFCxcKGxsbYW1tLebPn6/edsCAAQIQ/fr1E61btxYGBgaiRYsWIigoSLTt0EkodPWFXrEKotjwtaLkpP3CpvccAQht0yKi5KT9ouSk/ULfvpIAhKX7WFFy0n5hP3aHMHJ0Ewo9Q6FXpLSYMWeeAISZmZn6uCdPnhSVKlUSRkZGol+/fqJnz54CEGPGjFFvs3fvXlGrVi1hYmIiSpQoIcaPHy+eP38uhBBZzk16ez179hQrVqzQdBh5Ribe75lSqRT+/v5i6dKlomvXrsLa2lqUKlVKDBgwQKxbt07cvXs32w/DT8W1a9dEs2bNhLOzszh06JCmw5GkD9q1a9eEtbW1iIqKyvFrnj17Jnbu3CkGDRokbG1tRfny5cXYsWPF4cOHRVJS0nuM9v1IS0sTd+7cEfv27RPz588XgwcPFvXr1xeFCxcW5ubmol69emLQoEFi3rx5Yu/eveL27dsiNTVV02FnKyAgQBQrVkzs2LFDdOzYUZiamoquXbuKP//8UyQnJ7/Tvg8fPixMTExEoUKFxLFjx1653XfffSe6d+/+Tsd6ndTUVFGoUCEBiKpVq4px48aJ3bt3i4SEBCHEv8mpQqFQXxxl/nznzh0hxL+Jt0KhEN26dRPFihVTJ8kVqtcTetYlBSCMKzbOceJtXKlpxjYmVsK0agthYFwoS+L97NkzYW5uLgDRtGlT0bp1a6GlpZUl8T506JAAhJWVlfDw8BDVq1cXgBg4cGCWc5OJ99uLjo4WZmZmufrM+9DJxDufqVQq8c8//4jVq1eL3r17i2LFiolixYqJXr16iZUrV4qbN29+com4SqUS+/btE+XKlRPu7u7i1q1bmg5Jkj5YI0aMEKNHj36r16anp4vLly+LWbNmifr16wsTExPRvn17sXLlShEUFJTHkb6b2NhYcf78ebFp0ybx3XffiS5dughnZ2dhYGAgSpcuLdq0aSPGjRsnfvnlF+Hj4yOePn1aYD47lUqlOHr0qKhdu7bQ09MTzZo1E+vXrxcxMTF5su+JEycKfX194ezsLEJCQl657dWrV4WVlZV4/PjxOx/3dXbs2CHMzMwEoP6ysbER58+fVyen2tra4smTJ0IIIUqUKCEAsXPnTiHEv4l3s2bNhBBC/PDDDwIQtra2YvS2i8K66/cCELpWJXKUeJeYuFegrZMRR98fRclJ+0XjgROzJN6bN28WgChbtqz631VmYp2ZeLu7uwtAtGjRQowZM0aMGDFCfYHw39F86e2sXLlS9OjRQ9Nh5KkPssb7Y6ZQKNS1mcOGDUMIwYMHD9TtCxcsWEBcXBxubm7qCZtVqlT5qJdhVygUtG/fnlatWrFixQrc3Nzo06cPP/zwg5yoKkn/MX36dJydnRk+fDjW9g65WiRES0uLatWqUa1aNSZPnkx0dDRHjhzBy8uLH374AWtra/XiPQ0aNHjvaxgIIQgNDX2p9vrWrVvExMRkmdzYs2dP9eTGgtjSVfx/2fZt27axfft2ihYtSkJCAitXruSzzz7Lk2OEhYXRsWNHrl+/Tp8+fVi9evUr/x+mp6fz+eefM3v27PfeQq9Hjx506NABHx8fTp48yZo1a3j69CkzZ85k/PjxANja2mJrawtkNDV4+PAhCQkJWfbj5OSkfh6gbNmyxKeko6WX8e9BlZr86iDEvxMvVUlxkK4EQLdwRnG3nmXxLJuHhoYCUK5cOXVNffny5bl8+bJ6m8xOJUePHuXo0aP/HkoI7t+//4Z3RcqJjRs3Mm3aNE2Hkadk4q1hCoUCBwcHHBwcGDRoEJAxqSZzUZ/Vq1cTFhaGq6urerJmjRo1Cnwfy+zo6ekxbtw4+vXrx7Rp03B0dGTKlCmMGDHiozxfSXob1tbWDP56Oj2WHSXVqhzw30VCwlj8952XFgnJTuHChenVqxe9evVCpVJx6dIlvLy8+Pbbb7l9+zZNmzZVJ+LFixd/5X7eJDk5mcDAwGwnNxYqVCjL5Mb27dvj5OSEnZ1dvkxufN/u3bvH1q1b2bZtG2lpafTt25fjx49jb2+Pra0t3bt3z5PjHD9+nG7dupGcnMzq1avp37//a7dftWoVenp6DBkyJE+O/yppaWmcO3eOBg0a0KpVK1q1aoWVlRXjxo0jPj5evd2Lfc5fNXlUW1ub2NhYdc/0mzdvcu+v3aCftSOMQi+j64xITcr4b7qStOjH6ue1DE1BWwfSlaRFh6BtbE5qVGiWfWT+e7979y5CCBQKBXfu3MmyTalSpfjnn39YtmwZX375pfrx+/fv4+DgwIkTJ3L0HknZ++effwgJCaFly5aaDiVPycT7A2Rvb0+fPn3o06cPAOHh4Zw8eRIfHx+GDx/OvXv3qFu3rrqXeO3atfO0vZWmWVlZsXz5ckaMGMH48eNZuXIlixYtok2bNrJFmvTJ23I2iL0JpUk2VYLy5fZpmesfHPnnKb53InO82JiWlha1atWiVq1a/PDDD0RERHD48GG8vLz45ptvsLOzU3dKqVevXrYLwkRGRmbbmi8kJITSpUurk+sWLVrw5ZdfUqFCBfXo5cckPDw8y7LtPXr0YOPGjVmWbd+/fz81a9Z859VI09PTmTFjBgsXLsTU1BRvb2+qVq362tc8evSIadOmcfLkyfd+cZOSkoKbmxtOTk5Uq1YNIyMjdu/eDUCLFi1e+1qVSsWtW7e4e/cuAJs3b2bt2rXqTmEWFhaUsDHhn6i0LK/TtSiOQlcfVXI8kX8tJP15DKrEGPXzCi1tjB3deH7Tm8h9CzB2qMbTu6ez7KNt27aYmZkRGBhI8+bN0dPTw9/fP8s2o0aNwsvLi4kTJ3L69GkMDQ25du0aUVFRPHjw4K3eL+lfGzdupF+/fh/fHX+NFrpIbyU6Olrs27dPTJgwQdSuXVsYGxsLNzc3MWXKFHHkyBERHx+v6RDzjEqlEgcOHBAVKlQQrVq1Ejdu3NB0SJKkMZvPPBCmVZpn1KK69lbXr/73i//X0RYfvk44fu8lNp958E7HVSqV4tSpU2LKlCnC2dlZvf8ePXqI3r17C1dXV2FpaSnMzMxE3bp1xcCBA8WPP/4o9uzZIwICAj7YyY15KS4uTmzatEm0bt1amJmZib59+wovL69XnvuIESOydO54G2FhYcLNzU2YmpqK5s2bi+jo6De+RqVSiQ4dOohp06a907FzKi0tTYwbN064uLgIc3Nzoa+vL8qUKSO+//57kZaWlqUOOjY2Vhw5ckTY2toKQBgZGYnSpUuL0qVLC0D07t1bhISEiI4dOwpAGBgYiMkzfhTFPea+VNNt2W680C5UWGgZmYlC1doIvWIV/tPVZLswquCa0dXEuqSY8sOMl7qa+Pj4iIoVKwpDQ0PRs2dP0a1bt5e6muzevVvUqVNHmJqaCjMzM1GrVi2xePFiIYScXPku0tLShK2t7Uc55+uDWrlSejsJCQmcPn0aX19ffHx88Pf3p1KlSurSlAYNGhT4UaW0tDRWrVrFrFmz6N69O9OnT8/RSm2S9L6VKlWK4OBg9c+WlpbUqFGD2bNnU7Nmzde+Njcr2119FEOvNWd5tHsBz28cw8y1N+ZufbPdNvjHdgAUH74OHXMbDHW12fF53Vyt+BsfH8/t27dfGr2+e/cuqampQEb9a2hoKHZ2drRt25Zu3bpRp06dj2+E6hXS0tI4fPgwW7duzdWy7UIIHBwc+Ouvv966N/GJEyfo0aMHSUlJTJgwge+//z5Ho9d//PEHU6ZM4cqVK+jr5++CdC8SQnD79m3OnDmj/nrw4AHVq1enXr161KtXj7p162Jra4tSqeTgwYOsX78eb29vOnXqxODBg3FzcyMkJITWs//kuZkDvMXovUIBrZxtWO3x+t9VKX8dOHCAWbNmcebMGU2HkudkqclHoFChQrRs2VJdB5WUlMT58+fx9fVlyZIl9O7dm7Jly6pLU9zc3LC2ttZw1Lmjq6vL6NGj8fDwYPr06Tg5OfHdd9/xxRdfvPcJYJKUE+3ataN06dL4+Phw5MgRLly4QEBAAEWKFMmT/b/LIiHJynRWngh8KbkQr5jcGBAQQHR0NOXLl8fJyQlHR0e6d++Oo6Mjenp66lUP79y5Q1paGmfOnMHLy4sRI0YQGhpKy5YtcXd3p1WrVgXus+ZNMpdt37ZtGzt37qR8+fL07duXn3/+OceDAbdv30apVFKxYsW3Ov7s2bP56aef0NLSYufOnbRu3TpHr42JiWH06NHs2LEj35PuuLg4zp8/r06yz507h6mpqTrJ/vzzz6latWqW+Ty3bt1i0aJFbN68GQcHBwYPHsymTZswMTFBCMHmzZuZMGECfUZN4pBSh+RcrlwJYKCjzcjGZfPyVKU8sGHDBgYOHKjpMN4LOeL9CUhNTeXy5cvqzimnTp2iWLFi6q4pDRs2fKeJU5pw69YtJkyYwN27d1m4cCHt2rWT9d+SRmSOeO/evZtOnToRGRmpTjb37NnDtGnTuH//PomJiRQrVoyBAwcyffp09Wj3fwkhSExMZN68eezYsYPg4GAsCluS7tIVwyotidy/mOc3jmFSvR3KhCiS719Gx6IoVu3Go2fjAPw74l249Sjizv1BemIchRzrs3D8QMIfPeDMmTOcOHGC58+fAxkTm8uVK8fAgQOpVKkSjo6OPH78mGnTpuHv709SUhKVKlXi+PHjhIeHq5cqF0IQGBiIm5sb4eHhbNiwgaZNm3Lw4EEOHjzI8ePHcXR0pE2bNri7u1OjRo33VlMcmZCSqw4vuXXz5k31JMnMZdt79+6dq2XbMy1atIiAgAB+/fXXXL0uIiKC3r17c+3aNYoUKcJff/2Vq+OPGDECIQSrV6/Obci5IoTgzp07WUaz79+/T7Vq1bKMZmfXTSUuLo4dO3awfv16goOD6d+/PwMHDsTR0VG9TXh4OMOGDSMwMJDNmzfj4uLClrNBzPa6latl4w11tZjs7pSjORBS/omKisLBwYHg4OACf7c+O3LE+xOgp6dH3bp1qVu3Lt988w3p6elcvXoVX19fdu7cyZdffom5ubk6CW/UqBGlSpX6oBNZJycnDhw4wOHDhxk/fjxLly5l8eLFVK5cWdOhSZ8wlUqFj4+P+ucbN25gZWVF7dq1SUtLY8+ePcyYMQMnJydq1qxJ165d+eOPPzAxMWHw4MHq1w0dOpRt27ZhYWFB7969uXg7mJDoUF5sohd/+QCG5eqgY25DWkQQ0UdXY+sxP0s8MSe3YOhQk6R7F4i/epQf5sfTv10jnJ2dCQ0NpVKlShgZGXHgwAFu3ryJUqmkdevW3Lx5k6ZNm6onxpUrVw4fHx91iUmmR48e0axZM3XSndlJY+jQoQwdOpTU1FT8/Pzw8vJi4MCBREZG0qpVK9zd3WnZsmWetAu9+iiGFScC8bkTAbx9h5fsPHr0iO3bt7N161YiIyPfetn2/zp48CBffPFFrl5z8uRJevTogVKppG3btqxatSpXbRX9/PzYt2/fe1kWPiEhgfPnz3P69GnOnDnD2bNnMTExUSfZQ4YMoWrVqq+8O6lSqfD19WX9+vXs27ePZs2aMXnyZFq3bv3SJN7du3czcuRIBgwYwPbt29Uj95nJ82yvAJKV6bxuSFGhyBjpzunEYyl/bdu2jbZt236USTfIEW+Jf2eOZ9aI+/j4oKOjo07CGzZsSIUKFT7YRFypVPLrr78yffp0OnfuzIwZM/Ls9r4kvcl/a7wztW/fnj179nDo0CEuX75MVFQUfn5+XLx4kaFDh/Lrr79mW+P94oj55cuXqVatGmN3+LP70kMU2jrqEW/DMjUp0n0aycHXePrbdyh0DSjx1S7g3xFv6y5TMCpfl8Q7Z4n4cxaGJuYkxj0DUN/9ioiI4OrVqxw/fpwWLVpw5MgRRo0axYoVK+jQoQN79+4FMrpnKBQKHj58qB5lLV++PIGBgVmS7tcJCgpSj4afOHGCKlWqqEfDXVxccv0ZkzHKmbeJ1rNnz9i1axdbt27l+vXrdOnShb59++Lm5pYntesJCQkULVqUx48fY2Ji8sbtVSoV8+bNY/78+ahUKn766SeGDh2aq/cqJSWFatWqMWPGDLp16/Yu4SOE4O7du5w9e1Y9mh0YGIiLi0uW0exixYq9cV8PHz7E09OTjRs3YmxszODBg+nbt2+25UmZZTJnzpzB09OT+vXrZ7vPayExrDwRiPftCBT82+UHQKSloG9gQFPHIoxsXDZXcx6k/FOjRg1+/PHHN3a9KajkiLeElpYWFStWpGLFiupbkffu3VOXpsydO5fExET1iHjDhg2pXLnyB9NjV0dHh5EjR9K7d29mzpxJxYoV+eabb/jyyy81OnlI+rS0a9eOsmXLqidXtm7dmuHDh2dbThAREfHSY0IIYmJiOHToEJDRs3jTpk3MnDmT6xauKIo4Ztle16YMAFr6GZP4RNrLi4foWtln/NcyY5GQpPgYUlJSWLRoEd99990r48pshVa3bl31c9klnXfu3KFUqVK0b9/+peeyU6pUKUaMGMGIESNITk7G19cXLy8vevbsSUJCAm3atKFNmza0aNECMzOz1+4rN6UFQkBSWjqzvW4BvJR8Jycns3//frZu3aq+ABkzZgzu7u55/hni7e1NrVq1cpR0R0ZG4uHhwc2bN9Vt+GrXrp3rY86bN4+yZcvStWvXXL82ISGBCxcuqJPss2fPYmRkpE6yBw0ahIuLS47n2iQnJ7Nnzx42bNjAxYsX6dWrFzt27KBGjRqvvJg4evQon332Ge3bt+fKlSuvnbhaxc6c1R41iUpIYdflEAKexBOXnIapgS4X/t5DHycHRnq45/p9kPLHtWvXCA8Pp2nTppoO5f3J9z4qUoEUHBwsNm/eLIYOHSrKly8vLCwsRPv27cVPP/0kzp8/L9LS0jQdotrt27dF+/btRZkyZcSff/5ZYJaRlgqmkiVLCkDs3r37pecyl8neuHGjUCqVYuDAgQIQNWvWFD/99JPo3LlzxlLXurrCxMREmJiYCCcnJ3W7vs8++0yMHDlSVP58oSgxca8oOWm/MK7ULEs7waKDlqm3/287QesuU0TJSfuFdZcpAhCGJuZCCCGqVq0qADFjxgyhVCrFvHnzBCCqVq0qhBDiiy++EIDo2LGj+lzS09OFSqUSDx48UO+/f//+AhD169cXz58/f6f38e7du2LZsmWidevWwsjISFhZWQljY2Ohp6cnihcvLlq1aiUCAwOzHN+wXF31OVs0GyoAoW9fKUtrxcKtRwldqxICbR2hZVBIGDlUE1cfPRNKpVKMHDlSmJiYqJcsL1mypNiwYcM7ncebDB8+XPz0009v3M7Pz08UL15clCxZUjRp0kSEh4e/1fFu3bolLC0txcOHD9+4rUqlEnfv3hWbNm0SI0aMEC4uLsLY2FjUr19ffPXVV2LXrl2vXYL+dfu9ePGiGDlypLC0tBQtWrQQ27ZtE4mJia99XUJCghg5cqSws7MThw8fzvVx/+vXX38Vffr0eef9SO/PuHHjxOTJkzUdxnslE2/prTx58kT8/vvv4osvvhCVK1cWJiYmomXLlmL27Nni5MmTIjk5WdMhiqNHj4pKlSqJxo0bC39/f02HI32kMhPvP/74Qzx69Ej4+fmJrVu3itmzZ6sTb319faGtra1OGIsWLSrGjRsnvv/+ewEIhUIhPDw8xHfffSe2bdsmypQpo368dOnSorhjNWFWp3OuE28tY3NhXKWF0DLKiKNCvZYiLCxMtGzZUgCifPnyYuDAgcLc3DxL4n39+nWhr68vANGoUSMxdOhQ4ejoKJ49e5Yl8U1NTRXNm2f0FW/Tpk2e9euuVKlSRh/y4sWFiYmJMDAwELq6umL27Nni+vXr6uMDwnbgklcm3uaNBmS8j/pGwrhiE2FcubnQKWwn6n29XhQtWlQUKVJEVKxYUfTv3180bNgw4z3T0hJ3797Nk/P4L5VKJUqWLPna9QjS09PFvHnzhIWFhbC2thaTJk1664GN9PR04ebmJpYtW5bt8wkJCcLb21vMmTNHtG/fXlhbWws7OzvRvXt3sXjxYnH27Nl3+iwPDw8XixcvFlWqVBGlS5cW06dPF0FBQTl67alTp0TZsmVFv379ctSfPCeCgoKEtbW1SE9Pz5P9SXkrNTVVFClSRNy5c0fTobxXstREeiuZSx1nLnccHR2tXuZ+3LhxBAQEULNmTXVpSt26dV97e/B9aN68Of7+/qxbt47WrVvTvn17Zs2apV71TJJyIy0tjZCQEIKDgwkODiYoKIjg4GCePn0KQM+ePbGysqJkyZKUKlWKkiVLMnjwYHbu3ElERAQtW7akQoUKLFmyhNq1a7No0SKio6O5du0ahw4dYsuWLWhpadG+fXuGDx9OYGAgBw8eJDg4GMFDLJrXfUOELzN38yDu3B+I9DRMKjejStniODo6UqVKFXXXABsbG8aPH8/UqVPVr6tUqRInTpzg+++/x9/fnwsXLlC5cuWXygl0dXX5448/cHNz4+DBgwwaNIjNmze/03yQ6Ohobty4gbm5OY8ePQIySlr27dvHwYMHmbNw6QtbK4g9uZUi3X94aT+qlERiT28HbR2K9l+kLrcBCEPFn15Hqevybzs/IQQWFhbExsby8OFDypZ99xZz/+20IlKeo6rQDJsSZbLdPioqigEDBnDrVkZJzC+//ELnzp3f+vjr1q0jJSWFkSNHIoTg/v37WTqN3L59mypVqlCvXj369evHypUrsbOze/OOX0OpVHL48GE2bNjA33//TYcOHViyZAmNGjXKUXliSkoKP/zwAxs3bmTlypV06dLlneJ5UcmSJSlcuDBXrlyhevXqebZfKW94eXlRvnx5ypUrp+lQ3is5uVJ6L+Li4rIs6nP16lWqVKmiTsRdXV3fWMOZl2JjY5k1axYbNmxgwoQJjB07FgMDg3w7vvThS05O5uHDhy8l1pnfP336FBsbG3VS/WKCXbJkSUqUKPHGf1Px8fH4+flx/Phxjh8/zt27d6lfvz5NmzaladOmVKtWDZVKxZ9//snixYsJDw+nTp06eHt7Y9drOlGGdrzNB/aLi4QkJCTw559/4unpyZUrV+jZsycDBgygdu3aH8QE6rS0NAoXLkxCQgJVq1aladOmNGzYkBYtWmBsbMwPm48yo3/GmgVGjm4kBpzEdsAiUkJu8ezYGvTtK2Hb90eSHlwmfMdUtAsVRsfcltSn99Axs8GsQR8sKzVkXIvyDGtYhkOHDnHgwAGuXbuGr68vDRo04NixY++0PsDrOq1oCSW6unovdVo5c+YMPXv2xMzMjPT0dHbv3k2FChXeOoZ79+5Ro0YNBgwYQFBQEGfPnkVXV1ddm12vXj2qV6+eZzXsd+7cYcOGDWzatIkSJUowaNAg9fnk1JUrV+jfvz8ODg788ssv72WQZPTo0RQrVoxJkybl+b6ld9OpUyfat2/PZ599pulQ3iuZeEv5IjExkXPnzqknbF64cIHy5curO6c0aNAgX1aiDAwMZOLEiVy5coX58+fTtWvXDyLZkN6/hISEVybVwcHBREdHY2dn98rE2s7OLsviHjnpG52cnMyZM2fUifbVq1epVasWTZs2pUmTJtSuXVud4EVHR7NmzRqWL19OmTJlaNGiBbt27cLY2JglS5aga1OW7qtPkZr7NUJeuXLlw4cP2bx5Mxs3bkRbW5sBAwbQr1+/dx71fFe///47n3/+ObGxserHbGxs+Ouvv1h1NpwNozO6thQd/DNPPMdhULIqhqWrZ0m8n988QeRfCwDQsy2HTuFiJN46CYDtgEX0at2IxT1dmDZtGtOnTwfAwMCAqVOnMmnSpLf+XMhtp5Xv2jgSfvoP5s6di5mZGbVq1WLt2rUUKlQox8cUQvDgwYMso9lXr17FxsaGHj16qBNte3v7tzqnV4mPj+f3339nw4YNBAYG0q9fPwYNGqReYCmnlEol8+bNY8mSJSxcuJB+/fq9t8/l/fv3s2jRIo4fP/5e9i+9nfDwcMqXL8+jR49yNPG4IJOJt6QRKSkpXLx4EV9fX3x9fTl9+jT29vZZFvXJbnGFvOLt7c24ceMwNTVl8eLF1KhR470dS8ofMTEx6iQ6u8Q6MTGREiVKvDKxLlq0aI7axb2+b7QW6SoVxRQxKK8d4Jp3xpLgmSPa9evXf6n3ckBAAEuXLmX79u106NCBbt26sWnTJs6fP8/8+fPp0aMHCoWCM2fO0GXiYkwaDshV8p2TRUKEEOo2bTt37qRGjRoMHDiQzp07Y2RklPOD5aHk5GR8fHw4efIka9asITw8nPbt26Pf8DN2fd0JAPux23nms4kEfy+MnNxIvHXyhRFvf8J3fA+A3eitaBuZEb5zGkn3LmLWoC8dB32B5+B6QEbi988//9C+fXsePnzIli1b6Nu3b65jzu0iLpltH0s07MrzmyeYMmUKY8aMeWPSmZiYyMWLF7Mk2jo6OuoEW6VSsXr1am7cuJGrXt85IYTg5MmTbNiwgT179tCoUSMGDx5MmzZtslyY5tTt27cZMGAAhQoVYv369ZQoUSJP4/2vzHaOT548ydXFjZR3shu0iLh7lfTAU2zfuEbT4b13ssZb0gh9fX1cXV1xdXXl22+/RalUcuXKFXx9fdm2bRsjRozAysoqSy/xkiVL5tnxmzRpwqVLl9iwYQPt2rWjTZs2zJ49+70m+9LbE0IQERHx2hFrIUSWZLpUqVLUq1dP/b21tfU7j6K9aTQzs2dwsDBFr3JfFo3/gaGNXy4XEEJw9OhRlixZwqVLlxg+fDgXLlxg/fr1DBw4kHHjxrFp0yZ10nThwgU6duyIp6cnURZOed67WqFQUL9+ferXr8+SJUvYt28fGzduZNSoUXTp0oUBAwbg5uaWL3eH0tLSOHfuHA0aNKBVq1a0atUKKysrxo0bR3x8PFb6Wf9smdXvQcK1oyTe8svyuK5VCVBogXihj/P/3zAtPQO8du/CZExLSpcure5BbWNjw8OHD7lz5476Nffv32fChAn4+fkRFxeHlZUVlSpVYsWKFZQp82+t9tVHMcz2CsjVyomZlBWas2DCFwxsn/1KpkFBQVmS7Fu3blGpUiXq1atH7969WbZsGfb29igUCuLj46lYsSIbNmzI06Q7JCSETZs2sWHDBvT09Bg8eDA//vjjW5eDqFQqli9fzowZM5g+fTojRozIlxa1hQoVombNmvj4+NC2bdv3fjzpX68btEBphm7xTgzbcvGtFrsqSOSIt/RBUqlU3Lx5U10j7uvri76+fpYR8XLlyuVJIhAXF8ecOXNYu3Yt48aNY/z48Xk+SiS9nkql4smTJ69Mqh8+fIiBgcErR6tLlSqFubn5e00Mt5wNYpbXLZLfYUnqpKQktmzZwpIlS9DW1mbcuHH07NmTHTt2MHnyZFq0aMGcOXMoXry4eh9XrlyhVatWrFmzhg4dOgBvWCREmYK+ft4sEvL48WO2bt2Kp6cnSUlJ9O/fn/79+7/VMuk5lZCQgImJCU5OTlSrVk3dvzoqKorZs2cjHFyZ0rsxkDHirWVQiOgjq4m/vB9APeINELl/Ec9vHM9SaqLQ1afU0OV0qFSEFV92xsTEhMTERFJTU9WJuYGBAeXLl6d69eocPnyYJ0+eUK9ePapUqUJoaCi+vr4cOHCABg0aqOP+fPNFjt56+tqLof/KHPEuPnwd7VyrsNqjJklJSVlGs8+ePYtCochSm12jRo1XzicYO3YsMTExbNy4MZfv/MtSUlLYt28f69ev59y5c/To0YPBgwdTq1atd/pdCw4OZvDgwSQmJuLp6Un58uXfOdbcmDt3LmFhYSxduvTNG0t54n0sdlVQycRbKhDE/1dLy0zCfXx8SEtLy7KoT8WKFd9pxOT+/ft88803XLhwgXnz5qlv8UvvTqlUqjuCZJdYh4SEYG5unm1iXapUKUqUKPHOdX8vrjDp5+eHq6srkLEUd8OGDQHUK0hmblu0aFGOHTvGruPnWX0hmsee4zO2m5SR5D3/x4e483tIDX8AKiXGlZph1W5cluOqQm9geGkL927fQghB6dKlWbVqFc2bN8fPz4/mzZu/tBR727Zt2b9/Pzdu3KB58+YsX7482xUHs1sk5PLxv+hSvThjhg1+afu3JYTg0qVLeHp6sn37dpydnRkwYADdu3fP83pMpVLJxIkT8fb2JigoiKSkJOzs7OjTpw9Tp07l2u171KiUsZhQZuKtTIjm8eohCGVqlsRblZrMs+NrSbx9GpGehp5NGSwaD8SkpDNnvmnKZx49uXDhAhEREZiammJvb0/NmjWJi4vj4sWLPHz4EKVSiUKhwMTEhJSUFMqXL4+TkxPlypWjatWqpKam8uvadZw6fwlVWiq61iWx6T0bhZYO4TunkRoRhCopAYWuPgb2FSnccgQ6phkrM2Ym3oVbj8roPhMXDoCLiwuurq6ULVuWXbt2ce3aNZKTkylRogS9evVS16T/1/nz5+nQoQM3btx4pzkz/v7+bNiwgd9++40qVaowePDgPCk7EkKwceNGJk6cyFdffcXXX3+dJ6uB5tbly5fp06cPAQEB+X7sT8HGjRsZNGgQjRo14sSJEzkuwXp2YiMJV4+gSorDxNGVlRu2vDb5zm7l34JAJt5SgRUUFKSuEffx8SE6Oho3Nzd1eUrVqlXR0cl9NZWvry9jx47F0NCQJUuWUKtWrRy9LieT7T5WKSkp6o4g2SXWT548ydIR5L8Jtr29/Xu/y/Bi4t23b1+2bNmi/n7btm1ARuJ9+vRpqlatSmRkJAAmJiaUHTSfsPhUnmwYk7Hd/xPvZyc2kvzwOiIlkbSoRy8l3srYcEJ/HQaqdCqUL0dqaioPHjxgxIgRREZGcu7cORITE0lJSWHw4H8T5YoVK+Lm5kbTpk1ZsGABffr0yfF5btiwgUOHDrFjx453eLdeLTU1lQMHDuDp6cmJEydo3749AwYMoEmTJu89iRJCsHv3bsb+8Q9a9lUzSklyvRMV4tFVZrcpRZ8+fV57sR4fH4+trS2JiYlYWlqio6PDs2fPMDU1xdLSkrS0NO7fvw+Avp0zOoWLk/LwBkUHLkaho8+TjWPQsy2LQs+Q1NAAUp/ew6B0dWx6zgD+Tby1jM0xcqiBKugSifExjB8/noULF+Lh4cHWrVtp0aIFpUuX5t69e+jo6KhXN31RWloaNWvWZOLEiW9Vnx4VFcW2bdtYv3490dHRDBo0iAEDBuTZ3Y2wsDCGDRtGUFAQmzdvpkqVKnmy37ehUqmwsbHh4sWLeVrC+KnITKxf5dy5c2zbto2yZcvi1tGDXmvOkpSW/tp9pjy+Tdimr1Do6GFcuTn6RctjXaNVtpPCM8nEW5I07PHjx5w8eVI9Kv7o0SPq16+vLk+pWbNmjluEqVQqNm3axOTJk2nWrBlz587Ncvv/RW+abCfgpdZhBc3z589fSqZfTLCjoqKws7N7ZRnIfzuCaEJm4m1hYUFiYiIhISEIIbC3t0dHR4fnz5+jo6ODqakpycnJJCYmolAosLSyxnzwap6Hh/Bkw2jg38Q7U/TfvxJ/cd9LiXfm42Y123HPexch9wJwcXEBYPLkyXz33XfqDhAv/uEIDAykcePGzJo1i4EDB+bqPENCQnBxcSE8PPy918xGRESwbds2PD09iYiIoF+/fgwYMOCd2uC9SlBQEKNGjeL+/ft8/eNy5l9MfeMf8+zoaysYXDKWLcvmkJ6ezujRo6lcuTJKpZK0tLSX/uvn58fatWtJSkpS78PY2BhXV1euX7/OkydP0Lcti+3AJQAIVTooFCgUWqRFh5IUeJ70589Ifx7D8xvHQVuXEhP+QKHQUife1l2mYFS+LlWUd/hrwXisrKyIiIigZ8+e/P7778yZM4fWrVvj5OSErq5uthc48+bN4/jx4xw6dCjHd+rS09M5evQo69ev58iRI7Rt25bBgwfTpEmTPP23s2vXLkaNGsVnn33GDz/88E6tGvNKnz59aNq0KUOGDNF0KAXO+fPn1YMVkPH38tdffyUlJYXatWtz7tw59XM5LcFKuOFN1P6F6NtVxNZjHpC1DWp2ZOItSR+YyMhI9aI+vr6+3Llzh9q1a6tHxOvUqfPGUdb4+HjmzZvH6tWrGT16NBMmTMhyu/VjqVuLiYl55Wh1cHAwCQkJ6kT6v2UguekIokmZiffIkSNZuXIlDRo04N69ezx58oRSpUoRFBRE0aJFCQkJUS8u06NHD37//Xesmg1Gt4RLrhPvsK2TSHl0A9v242nXqDZei8YTGRlJamoq/v7+uLi4UKpUKUJDQzEwMMDAwAAXFxdu3rzJtGnT+Pzzz9/qXJ2cnNiyZctL3XqEECiVylcmme/y36CgIE6fPs2FCxewsLDAxcUFZ2dndHR03mm/KSkpPHnyhPDwcCwsLDA1NUWpVJLuUB/tGt1R6Ob8bpJQpqB1dS/6D8+hq6tLfHw8T548wdjYmDJlymBqaoquri46OjpZ/qtQKIiMjCQiIoKAgACSkpLUEyvv3btHycY9oG7/LMdKfnSDp9u+yzK5M5P92B1oGRirE+9in/+CbuHi1DRL4o9vMxYlS05O5v79+wwZMoRz586Rnp6Ovr4+X375JT/99FOW/d27d486depw/vx5HBwc3vg+BAYGsmHDBjw9PSlWrBiDBw+mV69emJub5/i9zIlnz54xatQoLly4wKZNm6hbN/eLQL0vnp6e7N+/n507d2o6lALv+++/Z9asWRQuXJjLly/j7e3NoEGDqN/AjcjG3xJ77wpPf/sObdMimLi0Iu7CXhTaOpjW6oRpnS4kXPubKK8lWfZp5tobc7e+pN0/j809LwLv3MbCwoJu3boxc+ZMjIyMCmziLbuaSB8tKysrOnfurF75LTY2llOnTuHr68t3333HtWvXcHFxUSfi9evXf6le1cTEhFmzZjFkyBBKly7NDz/8wOLFixk9ejTbzj/MceswISApLZ3ZXhkr0uVn8i2EIDIy8pWJdVBQECqV6qVR6jp16qgfK1KkSIGtd09MTOT06dPExMQAGav5GRsb888//2BgYICTkxNz5syhc+fO6OnpZRnp69mzJ3+fvkj0mT+wts39KG7684xjKrX1OXrhJj169GDDhg2kpqaycOFCSpUqRXJyMqVLl0ZfX5/g4GD+/vtv9PX18fHx4cSJE2+VsEZFRdGoUSP09PSyPJ6eno62tna2yWVe/NfJyYmKFSsSGhrKP//8w6FDhyhXrhw1atTA2dkZfX39bF/3qn3evHmThQsXUrp0adatW0epUqWyPL/3n2iW+YaQolS9dmEh9YVvx+p4/JR1JcTk5GR+/vln5s+fT8+ePfnhhx+wts6owX6xw0qmJUuWMG7cOOzt7alYsSIrVqxAOyGczLF3IVSAgsTbp0GoMHCogXXnb0mLCCZs01eZW2WJIS3yEbqFi5MalbFSp5WVFfr6+jg4OHDq1CmeP3/OP//8Q8eOHVmwYAGjR49W9+QWQjB8+HC++eab1ybdCQkJ7Nq1i/Xr13P79m08PDw4dOgQlSpVeu2/4bd1+PBhPvvsM7p06cKVK1c01pbyVVq0aMG4cePUvxPS2zl8+DBz5sxBoVCwadOmLKU7EfEpvPhXIz0ugue3fDF0qMHzW748816PTuHi6FrZY1CqGslB/mibWGJUwRX94o4k3b9E+O8ziDOzoFPHjvzzzz/qFX83bNiQ/yebR2TiLX0yzMzMcHd3x93dnVKlSvH8+XNOnTrFqVOnmDt3bpZtZ82axYgRIyhcuDCQMVo6ZswYHj9+jKenJ5sP+BBfZwipubzTnZSmYrZXAFXszN+p28SLVCoVYWFhrywDCQ4OxsDAIEtS7eDgQJMmTdSJtYWFRZ4m1vlV7y6EIDk5maSkJBITE0lMTFRPjDt79iyXLl3i7t272NvbqycwduzYkWfPnnH06FEAihcvzrx5Gbc2w8LCqF27No8fPwbIuA3t1AJVyO/qrhm5oW1sjjI6BJGWTJEylRDKjElykNE5Q1dXly+//BI9PT2eP3/O8uXL0dbWJiUlBQcHB5ycnN4qAT5x4gTr1q1j7969LyW4+XkB9ezZM3bs2IGnpydHjhyhb9++DBgwgMqVK7/2dVFRUXzzzTccOnSIJUuWvHKhq5HFi9PAyf6VHV4yS72aVLB+ZYcXAwMDvv76awYNGsSMGTNwcnLi66+/ZsyYMSiVStzc3F7qsAIZiVuHDh1Yu3Yt9y+ewDA8Cm2LYiSH3KRovwVoG2ccK/XxbaKP/kLKwxuvPt/Dy0m8c4ZDgWcBaNSoEVFRUUycOJHbt2/j6OiIUqkkMjISbW3tLP2nN2/eTGRkJOPGjXtpv0IITp8+zfr16/nzzz9xc3Nj/PjxuLu7v7dyj4SEBCZMmMDBgwfx9PSkWbNm7+U476pYsWIUL16cixcvUqdOHU2HUyCFhITg4eGBSqVi0qRJL7VnTExNR+fFloFaWtj0noO2kRlahqbEX9zL8xvHse78LcbOjUgO8kfHvCiFm2fc6QvfOQ2AwiUqYGlpSZ06dbh8+TKenp6sWLEiv04zz8nEW/okDR48mOjoaABWrVpFamoqnTt3RkdHh5CQEA4dOsS8efMoXbo0rq6uNGnShG+//RYbGxtUKhVt5+4hMk6F4i3qIJOV6aw8EfjKurX/UiqVhIaGqpPp+/fv8+jRI3VS/ejRI8zNzbMk1pUrV6Zdu3bqxDq/VgLLWu8uSFH+O7Knp/WYhUcCqFgYmhRJw0rrOYmJiVmS5jd9/9/HkpKS0NXVVS97nZ6eTnJyMgYGBlhaWmJjY0Pr1q0xMzPjzz//BDIuVOrUqYOPjw8KhYLBgwdz//59zp49i7m5OT///DNdunTh8ePHLFiwgAs6zqy7e/6lPtE5oVekNCmPbpDy5A6u/fozsrobS5cuxdjYmMWLF5OSkoKWlhapqak0btyYkSNHsmDBApKSkmjfvj21a9d+q/8PXbt25csvv8TAwECjI40WFhYMHz6c4cOHc/v2bTw9PXF3d8fa2pqBAwfSu3dv9egyZCSKnp6eTJo0iZ49e/LPP/9gamr62mNUsTNntUfNLB1e/vY9ReSTR3w7dijdqufsYs/Kyoply5YxatQoJk2ahKOjIzNnzmTs2LGcOHECLy8vdYeVkSNHMnHiRPVFzqTvJnPy7EXEkzvoWpcCbR1Mqrcj5fEdkoP8SXl0A7P6PYjyyr59nbmbB/Hn/kBboaKskxNhYWE4ODigra1Neno6Fy5cAMDBwYFp06ZhYWEBZNTYf/311xw4cCDLRPLHjx+re25raWkxePBgbt26ha2t7Rvfh3fh5+fHgAEDaNiwIdeuXcvVcvGa0KpVKw4fPiwT77egVCrp2bMnkZGRNGzYkFmzZr20TbpKZEkytY3M0DbK+Deha5mxOq4yPvLVx4jN6PLz8PpZll4/q35cCKGe1FwQyRpv6ZNnbm5ObGws3t7eNG7cWD2ytmDBAhYuXEhKSgqurq789ddfAHTp3Y+rpXqQGPGIKK+lpIUHYVCyMjpmtsRf3o9huboU6ToFgPjLB4g9sxOhTMW0ThfiL3uRHhdOse5TuLZ+CmYG2vz000+sXbuWx48fY2FhQfXq1SlcuDDBwcFcvXqV2NhYDA0NMTIyIiYmhjZt2tC+fXt1Ul2iRIkcdQRRqVRZRodzk/C+LvnN/D7FvjY6tXqAtu7rL0iECoVIp/SzyzioHmNkZKQ+v1d9/+JjBgYGPHz4kHPnzuHn54evry/FihVTrw7ZqFEj9Z2KF2XWeO/evZtOnTpx6dIlAGrUqMGePXvo3LnzS+0Ed+/eTZhFZWb8vJ4nf8xR7yuzxjvxzhkS75wl9ckd0qIeoWNeFH07Z/TtnTGp2gplzFNC1wwDlYoaTdyJe3Sbu3fvMnHiRObNm8eJEydo27Yt2tralCtXjtjYWO7du4ezszP+/v7vNCrp5ubGlClTaNWq1Vvv431IT0/H29ubjRs3sn//fho3bsyAAQNwcHBg9OjRJCYmsnr16ndaTXbkyJGsXbuWqKiot77o9PX15auvvkKhULBgwQJ1y8nsCCFoPftPAuL13upiPLtJZCqVigcPHuDv75/lKzU1lWrVqlGtWjXOnj2Lg4MD69evJz09nb/++ov169dz5swZunXrxqBBg6hbt+57v8uRnJzM999/z9atW1m1ahUdO3Z8r8fLK0eOHGHGjBn4+eX+ovpT99VXX7Fo0SJsbGzw9/fPsvjcunXrGDJkCIVLOWHS6yeSg6/x9LfvQEsbu1Gb0DYyI/rvNcRf3ItRBVesO3+rrvN+sR1o5kqzjQdOxHvDPPX+79+/j4ODg6zxlqSPzffff0/37t0xNDRk9erV6j9equJVUaalErFrJsqYJxntwnT0iPf3yvL65OBrRB9ZBSgwcm7I85vepP//6j5NqaTx4Ek88Fqj7qZhYWFBTEwMBw4coEOHDnTu3Blzc3P27dtHUlIS1tbWlC9fHisrKx49esSdO3dylTQnJyejr6//xiT3v9+bmJhgY2Pz2m3/Dkrhl/PhJCtzcB2v0EIotHhiW4/Bb1jKHDKSmnv37nH8+HGOHz+Ot7c3hQoVomnTpvTq1YtffvnlrUbycprYdathxyJHV3SLOJAWnnWUJfXpfZ7fOKb+WRnzBGXMEwBMqrZCx9yGIt2nEeO9gUvH96Ovr0/79u2ZPHkyAJaWlujr65Oens7NmzexsrKiX79+zJ49+51LAVq0aMHRo0c/uMRbW1ub5s2b07x5c+Li4ti6dStjxowhJCQENzc3VqxYQfXq1d/pGEWKFMHc3Jz79+9TtWrVt9pHw4YNOXfuHNu3b6dfv35Ur16defPmvbTYS0xMDEOGDOHi1fsU6jQFtHJfSmWgo83IxmWzPKalpUWZMmUoU6ZMlh7uYWFh+Pv7s3PnTi5fvsyDBw8wNDRECEGRIkVo1aoVe/fupVatWq9cZCcvXb58mf79+1OhQgWuXr2a5Q7Gh87NzU09uPGhj85/SLy8vFi0aBEA5cqVY8qUKYSFhREWFsaTJ0+IiooCMvro6yheKDURgqe/fYdeEQee3/IFwLhS01cex6R6O5LuXeTUtqX0Tn6IoaEh165dIyoqigcPHry/E3zPZOItSa+wfPnyLL2VM1mUcCT53E2UMU9Q6Bli0+dHtPQMCN81k6TAf9soPb95AgDjys2wajuW9MRYQpb3z5hXpdDmaUpGCzv19i98f+zYMZ49e6auNS5UqBDNmzfH2NgYIyMjdHV1MTU1zVUCbWBgkKsWYTldcGbvyStM7FcBZWw42oUKU2zYGrR09Ul9ev+lLiDKmKc8O76O5JCbqFISGbzcitODB7Lip9koFAp8fHwYM2YM9+7dIyUlBQMDAxQKBcbGxjRv3pzWrVszb968t+q9+7oRkU6dOvHizb//butkJkgZuOSl0Uxzt76Yu72+Z7JRaRc6t93O7Dal+fPPP9mxYwclSpSgRYsWXLlyhf79+7N48eI8H5Vs0aIFw4cPz9N95rXTp0+zYMEC6tevz5gxYzh8+DC9evXCyMiIAQMG4OHhkWUkLaesra0xNjYmMDDwrRNvyEh++/TpQ5cuXVi6dCn169dXL+RjZWXFqVOn6NWrFykpKVgXLkzS5T/Rq9c7V3M/9HUUTHZ3zPGcD1tbW6pUqUL//v0pVqwYKSkpjB07lurVq/P06VP8/f0ZNWoUd+/epWzZsurR8WrVquHi4pJnCaZSqWTu3Ln8/PPPLF68mD59+hS4CdiGhobUr1+f48ePqyfhS6+XkJDA77//rv7Zz8/vpTsGK1euZOTIkTg72BGp/W+aqW1ihXGlpsSd/QNtIzNManbAqNyry3wMy9SkWPcpFH1wBC8vLxQKBeXLl2fMmDF5f2L5SCbekvQKmYnmf8WnKElPyLii1zGxQksvY1RJ18o+S+Kt/P82mbVs2kZmaBuakv78GUCWRC+zxduLP9euXZtLly5x7949KlasSLt27TAzM3vpKz964q5atUr9fqxevTrLcytOBKp7NKQnRJPg74Vp7ez/iEUeWEzKoxvomNtiULIqSXfPsmrhXCrY21C0aFF+/fVX7ty5gxACGxsbHj9+jEqlYvHixdleBL1v8fHxfPXVV1y9GIB+m29Izflq8WqZo5mWluYMHTqUoUOHcu/ePVq0aEFKSgqenp7ExMTQs2dPmjdvnmf9zmvVqsXDhw95+vQpNjY2ebLPvPL48WPGjh3LpUuXWLFiBa1btwagXr16TJ06FT8/Pzw9PXF2dqZevXoMGDCAjh075ngE18rKCl1dXQIDA/MkXgMDA7755hsGDx7M9OnTcXR0pHr16ly6dAmVSkXhwoWxt7fnt9+WcCgwgdleASSlpr12gR+FArSFCu1rB+jybeM3xpCens6xY8dYv349u3fvxtbWlpUrV9K0adNsu3IkJydz8+ZNdYnK77//zrVr17CxscmSjFerVi3XFze3bt1iwIABWFhYcPnyZezs7HL1+g9Jy5YtOXLkiEy8s5Gens6tW7c4d+4c586d4+zZs9y7d4+qVasyduxY6tatS506dShZsuRLF10jRowAMvp473vhRqFZna6Y1en60rEKVWlOoSrNszymUED7Dh1Z7TEz2/gaN25MQayWlom3JL1C5oS9/zLSVaBdyBLImBiiSktBS1eftKiQLNvpZG7zLGPUOj0xlvSkOPXz9nZ2xOnpkZqayvbt27G3tyc2NpaYmBju37+Prq6uOhmPiIhg48aNxMbGvvSlq6ubJRE3NTXNNkH/79eL22WOLGfHwsKCXbt2/Y+9sw6LKm3j8D10SkgoiiCiIgqKYHevDRYqKHas3bXuurp2rt2Na2MXKnYTYicGSCrdMO/3Bx9nHcHGXO7rmgs4c+I9Z4aZ33ne5/k9LFiwACEEu3btwsDAgOjoaORCZBVSSp99MmIv7ULHoWmu+8qICcvaZ8M+aFlXJtJrGkn3LjBmwkQa169LixYtmDdvHuXKlUNJSYlWrVqxf//+b5K/d/bsWakjY+CpA+y7/eqD7SOz0VRVyhHNTExMpHv37jRs2JDly5cTGhrKzp07mTJlCl26dMHFxQVXV1fq1q37SZ1Xs1FRUaFu3bocP378kzoZfgkyMzNZunQpkydPpl+/fmzYsCFHfYKSkhK1a9emdu3aLFq0CC8vL1avXs2vv/5Ku3bt6Nat23vzlrPTHfJKeL++39GjR3Pp0iUuXbpEfHw8urq6uLq6MmXKFJSVlXE3MqK0iRYu45eiZV2ZzMxMMvlXgL/utNK/Tglmj9tGr1698PT0zPWcHj16xPr169mwYQMmJiY0atSIAgUKcOXKlXfeUGloaODo6KiQUpWZmcmDBw8kMT5//nz8/f1RUVHJIcatrKxyzJDJ5XIWLlzI1KlTmTJlCn379v3hotxv0rhxY5YuXfqth/FdEB4eLgnsy5cvc+3aNUxMTCSB3bt3b8qXL/9RwZ4Bda054n3yk8aTWwrWz0C+8M4nnw8gLu5fwXzwnzVo1+yKikFhMqJDCd8yDpUCxiQ/vKKwjXa5eiQEHiMh8Djy9FTSI58iddmRZ/L8tSrt7OYVhoaGxMbGUrVqVXbt2kVSUhLnzp2jVq1arF+/Pse4hBCShV5uojz78eTJE2JjY9+6nhAihzCPiMiqKLewsCAgIAAPDw80NDRITU2lWbNmeHl5EZ+chsZrEQctm5ok3T1LvN9BNC0dcoy3QGUXok+uIfr4ShJvnSL50TVU9EyYsPQfJnbOyvV7+PAhw4cPJyQkhEOHDlGkSBG6du2aY19fitTUVCZOnMimTZtYsWIFrVq1AsBKfhOlwL0I60b/b9rydsHxtoZJycnJtGrVCisrK5YvX46SkhJFihRhyJAhDBkyhKdPn7Jjxw7GjRvHs2fPaNu2La6urtSqVeuTOglm53l/D8L72rVr9OvXDx0dHc6cOUOZMmXeu42WlhZubm64ubnx/PlzNm/eTPfu3ZHL5Xh4eNClSxeKFSuWYztjY2NSU1N59OhRnp7Dzp07GTBgAGXKlEFNTQ1dXV2MjY05ceIEzZo1k/y+H1w6Ttnoi2wZO46uk5aSqWNKkeIlKaChik1hXQWnlVWrVlGrVi1mz57N6NGjgaybs127drFu3Tpu3bqFm5sbBw4coGzZslStWpUZM2Z80iyGsrIyNjY22NjY0KlTJyDrMyQ4OBh/f3/8/PzYvHkzI0aMIDY2lvLly0tC3MTEhBkzZiCXy7l06ZLUQOhHp1y5ciQnJ/Pw4UOsrX8+kfc2UlJS8PPzU4hmx8XFUblyZapUqcLIkSOpXLkyBQsW/KzjlDfXp0vVYkzb9HHb5Ra0+FnIF9755PMWIiMj8fb2xsvLSyGHbduc8fx69BXGbSdKribKWgXQsW9EwvWjyJSzUgU0itlh2Lg/sRd3kPLYjwJV2xJ/bR+ZCa+Qqagyb3BHSluOYMqUKfj4+BATE0NcXByamppS97/sfMz79+/j6+uLnZ2dQrQhO/9ZW1v7k3Jhs0lJSVEQ4nFxcXTq1Ink5GQqVqxISEgI58+fRy6Xo6urKwmahKQU9DL/Fd7aZWqRHvWUuMu7UTezyXEcDYvyqBpbkB4RJEW/NayciMj81/IuODiYv//+13atXr16X61gKyAggC5dulCyZEkCAwMxNjbm2bNnjBkzhnPnzlGvXj2CHuzGtv0wTn2kb3Rqaipt2rTB1NSUNWvW5CqkLSwsGDlyJCNHjuTRo0ds376dwYMHExUVRfv27XF1df0ol4pGjRoxdepUhBDfLDIZGxvLb7/9xo4dO5g1axZdunT5pLGYm5szbtw4xo4dy+XLl9mwYYOUt+zh4UHbtm3R1tYGsoR3YmJinkW8ExMTGTJkCD4+PpQoUYK7d+9ibGzM3r17sba2ZsuWLXTu3JlKlSoxc+ZMVq1axYABAyioo47W0wu0b9+eDh0q5bpvTU1N9uzZQ+XKlVFWVubevXvs3LmT6tWrM3DgQFq2bCn9zy9YsAAdHZ08TbuSyWSYm5tjbm4u3WRClpd6thhftmwZvr6+KCkpYWdnx/Tp06lYsSIODg7Y29tL1/1HRCaTSekmP6vwFkLw8OFDhWj27du3sbGxoWrVqjRr1ow///yTkiVLftIN/vuY+mtHylSs+lN0ec4L8u0E88nnNZ48eYKXlxe7d+/mxo0b/PLLL7i4uNC0aVMFP+E+m65x1P8xMvV/v3DCt00kJcgfvequ6NfuAoA8JREljax1MuKiCFnWA4ScOiOWknh6LbGxsQwZMoRu3bqhoaFBQEAAPj4++Pj4cPbsWUxMTChatCjKysqEhoby5MkTypYti5OTE46Ojjg5OVG2bNk8ywt+ndct9Z4/f87gwVmFkosWLaJo0aK4uLigU7AwBXuvInhpDzLjIjBuMwGRmUHU3plolalF0p2zQFZxpZBnErK0O5kJrzBqORLNklWI2jeH5IeXMa7YiC517ShSpAhFixbFzMwMFRUVJk2axNGjR+nVqxerVq3K83PMJiMjg9mzZzNv3jzmzp1Lly5dSEpKYubMmSxZsoRBgwbRs2dPHB0dOXnyJOXKlVPwjY5LSc81mplNWloa7dq1Q01Nja1bt350Csndu3fZtm0b27ZtIzExkQ4dOuDq6oqjo+M7RawQguLFi3P48OEPijDnJUIIduzYwbBhw2jWrBkzZsz47OjZm6SkpLB//342bNjA+fPncXZ2xsPDg2rVqqGtrY2ysjKxsbGf5e7h7+9Pp06dKFu2LAEBAcTFxVG/fn3Wrl2rIDiTk5NZsGABs2bNkqLthQsXplq1asyZM+etNSNhYWFs2rSJxYsXExISwtChQxk+fDhmZmYK6z19+hRHR0cuXLiQw1nlSxEaGkrv3r0lX/DixYsTGBioYG94+/ZtLCwscqSq5PVr/SXZsmUL27dvZ8+ePd96KHnCq1evuHLlihTNvnz5Mjo6OlSpUoUqVapQtWpVKlas+EE2tHlJYHDMW5tdyeTpqKmpv7PZ1c9CvvDO5z+NEIJbt26xe/duvLy8CAkJkaz8GjRo8NYv7OvPY6jXvjspL1+gVqgkaRGPSb5/EZmqBoV7LkZVP8veLmRZTzRLOKGkWYDEO2fIeBWCtnUlLvgcw66IHufPn2fevHmcOXOGXr16MXDgQKlQKSMjA19fX8lC7+LFi5QoUYIyZcpQoEAB4uLiCAwM5MmTJ5QrVw4nJyfpkd3x8HN4XXjXq1cPMzMzZDIZISEh+Pj44OLigq5RYQx7KQpvzZJVCV07KCu15v/J3xZjD2S5uizMSnkw67caVf1CxJz1JPb8P5jaODGiRwceP35MZGQkwcHBhISESMWV2faB2cK8SJEiCr9/ToOghw8f0rVrVzQ1NVm3bh1FixbF09OTcePGUadOHWbMmIG5uTlDhgwhPT39o/NB09PT6dixIxkZGezcufOzbpKEENy8eVMS4XK5HFdXV1xdXbG3t89VhPfu3Rs7Ozvpxulr8OjRIwYOHEhwcDDLly9/q+jMS8LCwvD09GTDhg3Ex8cTFhaGiYkJR44c+aSbDrlczt9//8306dPp06cPS5YsITMzkylTpjB48OC33vAMHjyYM2fOEBISwtixY1mwYAFnz57F0tJSWictLY2DBw+ybt06zp49S9u2benevTu3bt1i3rx5XL58WcF9RAhBy5YtqVq1Kr/99ttHn8unsH37dgYNGkTfvn357bff3prXm56ezp07dxTEeEBAAHp6ejnEuLm5+XeZEx4ZGUnJkiWJjIz8IkGML0l6ejqBgYEK0ezQ0FAcHR2l3OwqVap81oxoXvNm0EJDWbBj5Xz8di2jqLH+tx7eFydfeOfzn0Mul3PlyhVJbGd3rXRxcaFGjRofLFj7TJzD+iVzSY+LQllDF7VCJdCr5Y56oX+nKyO9ppHy7CbytGRUChhTwKYa0yf/Tp+G9gr7evToEQsXLmTTpk00bdqUYcOG4eSk2NkyLS2NK1eu4OPjw8mTJ7l69SrlypWjRo0amJmZkZGRwY0bN7h27RrBwcHY29srRMZtbGxydT94Gx/ScMbQtAhGvVfxaGE3SXhrlapG4t3zRO2ZLu0r204wZGVfMl6FoGpsibpZKRLvnEWkJePSdxS7l8+iQYMGZGRkYGNjQ3R0NPv27SM1NZX+/fvTqFEjQkJCJFH++k9VVVUFIZ7bTyMjI4UvfSEEK1asYOLEiUycOJGBAwdy+fJlhg4dCmRN61erVg3IcnGoXbs2d+7cwcjI6IOvYWZmJu7u7sTGxuLl5fXWgt1PQQiBv7+/JMI1NDQkEW5rayutt337djZt2iQ1gPqSpKamMmfOHObPn8/o0aMZNmzYVxcyQggCAgKoX78+CQkJlCxZkuHDh9O+ffsPttILDw+nW7duxMTE0KRJE+bMmYOGhgZeXl7UqlXrrdulp6dTrFgxfHx8EEJIXSU9PT3p1KkTt27dYt26dWzevBkbGxu6d+9Ou3btFFrADxw4kCdPnrB3717p/3X79u1MnjwZPz+/L+5i9PLlSwYOHIi/vz8bN278pO6pH9L8J/tRqlSpj/pc+lI4VKtN476/k6pZkLiUDApoqGBTqADtHT+s8+nXQAjB8+fPJYF9+fJlAgICKF68uEI029bW9ru4ph9DvXr1GDFiBC1atPjWQ/ni5AvvfP4TpKenc+rUKby8vNizZw8GBga4uLjQpk0bHBwcPjkKs/nSkzzNW4uJiWH16tUsWrQICwsLhg0bRqtWrd5qF3bx4kVJiAcEBODg4EC9evWoXLky6urqBAYGcu3aNXx9fQkNDaV8+fIKkfFSpUq9NafvTeH9OtnC27xYMTS7Ls8hvIUQhK4bIjWcyRbe6S+DiT61ntSQu8hTE1HRLUiBcnW5c2ANJnpaTJ48mU2bNhEcHIyamhqWlpZ4eHgwbNiwt75GQghiYmJyFeSv/0xMTMTMzIwiRYpgaGhIYGAgmZmZDB8+HAsLC9avX4+vry/Tp0/Hzc1N4bo0a9aMRo0aMWzYsLe/yG8gl8vp3r07L168YN++fV90WlcIwZUrV9i2bRvbt2/HwMBAEuEGBgaUKFGCqKioLyqCT58+Tb9+/bC2tmbRokUKEd5vQfXq1TE1NcXQ0JDo6GhOnjxJs2bN6NatGw0aNHirMDly5Ag9evSgW7duvHjxgl27dmFjY8O+ffveGzXcs2cPc+fO5ezZrBSr0NBQaYbq1atXaGpq0qdPH7p160bJkiVz3Ud6ejqNGjWievXqTJs2jejoaMqWLcuuXbukG8EvxaFDh+jduzcdOnRg2rRpef6ezW7+8/ojLCwMOzs7BTFerly5r9L8B7JmL5ecesjx26HIEGTy7/siu2ajbmljfq1jTXlz/a8ypmzi4+O5du2aQjRbCCEJ7CpVquDk5KSQBvmjMmfOHB4+fJjDrvZnJF945/PTkpSUxNGjR/Hy8uLAgQOULFmSNm3a4OLikqc5ku/KW3tXsd27yMjIYNeuXcybN4+oqCiGDh1K9+7dFSJjb5KYmMj58+elHPGbN29SuXJl6tWrR7169ShVqhQ3b96UhPi1a9eIjIzEwcFBITJubW39UQU2fTZdw/tO+DtvPN5Gbq2yvxTJycmEhISwceNG/v77b6pUqYKlpSVnz57lwYMHaGlpkZSUhLGxsUK0PDExkaNHj7J+/XosLS0pUqTIO18HyBLdffv25f79+xw+fBgtLa13rp+XyOVyLly4wNatW9m5cydmZmZEREQwb948OnTokOfHi4yMZNSoUZw4cYKFCxfi7Oz8XaQTtG7dGiMjIzQ1NVm8eDFRUVFs3bqV9evXExYWhru7Ox4eHlIaSmpqKuPGjWPnzp0sWrSIv/76i9u3b+Ph4cHff//9QTctzZs3x9XVFXd3d3x8fJg9ezbe3t60adMGCwsLtm3bRrVq1Zg+ffo7XUEiIyOpXLkyM2bM4Pjx46ipqbFkyZI8uzZvku1X7+3tzbp166hbt+4XO9abxMbGcv36dQUx/qHNf7p168aGDRv4448/mDRp0kcfO68DJ59Dtmf269HsR48eUaFCBYVodrFixb6L/6+85s6dOzRu3Jhnz579lOf3OvnCO5+fiujoaA4cOICXlxcnTpzAycmJNm3a0Lp16y/e5OH1vLUL1/wx0NHApV7lXIvtPhQhBBcvXmT+/Pn4+PjQvXt3Bg0alKuF2pvExcVx9uxZSYjfv3+fatWqUb9+ferVq4ejoyNxcXH4+flx7do16REdHU3FihUVIuNWVlZv/TC8/jyGjqsukZz+Ee36/o+mqhLb+lT7KoU0L1++ZMCAAVy/fp0NGzZw//59xo0bR61atZgxYwbFihUjIyOD8PBwKVL+7NkzpkyZgp2dHYC0XF1dPddc8+zC0EWLFnH37l2OHj36Wfnnn0tmZianT59m+PDh3L9/H3t7e1xdXWnfvv1n/z/I5XLWrl3L+PHj6dKlC5MmTfqm5/omvXr1QlNTkwcPHnDkyBGF527dusWGDRvYvHkzRYsW5ZdffmHPnj1SWoqLiwsJCQmsWrXqg60Ynz9/jp2dHQMGDMDT0xNDQ0McHR159uwZR48eBbKCAfPnz2fevHl4eHjw22+/YWhomOv+AgICqFu3Lurq6ty/f/+LtTQ/ffq0NAswb9687yJ6mt38p0mTJlL78dwoWrQowcHBnyS8s0T3p/jyl8kT8R0WFqZg5Xft2jUKFSqkEM22t7f/Kg3SvgeEEFhbW7N79+7P6jb7I5AvvPP54Xnx4gV79+5l9+7dXL58mfr16+Pi4kKLFi2+WWX93LlzCQ4OZv78+Xm2z6CgIBYtWsT69etp3Lgxw4cP/6j8y+joaE6fPi0J8adPn1KzZk3q1atH/fr1KV++PMrKykRFRUkR8eyf8fHxUkQ8+6elpaUkxj/lS0yWmU6JuACOLP7tswtB38fhw4fp3bs37du3x9nZmTFjxiCXy1mwYAHVq1d/63aLFi1i//79HD16VDpXIQTR0dG5prQEBwdz7do1YmJiUFZWfmfOeZEiRShcuPAXP3eAEydOMGHCBP7880+2bdvG3r17sbW1xdXVlXbt2lGoUKGP2t/Nmzfp168f6enprFixggoVKnyZgX8GY8eOJTU1lf3797/VVjA9PZ1Ro0ZJnup2dnb4+/tjaGjI8ePHKVeu3HuPk5SUhJeXFxMnTpRcQLp3746DgwNLlizh5s2bLFu2TGGbsLAwJk2axO7duxk3bhwDBgzIIbBSUlIoUaIE6enp3Lp1K88tNZOTk5kwYQLbtm1jxYoV32Vu7eTJk3n16hWQ1T03LS2NypWzmhJFREQQHh5OWloaJUqUoEOHDu9s/vM6nxcsUGZbn6ofFSxITk7G399fIZodFxcnRbKrVKmCg4PDR/8f/mwMHjyYQoUKMX78+G89lC9KvvDO54fkwYMHeHl54eXlxb1792jWrBkuLi788ssv34Wn7M6dO/H09MTLyyvP9x0XF8eaNWv4+++/KVKkCMOHD8fZ2fmji2kiIyM5ffq05JoSHh5O7dq1JSFetmxZ6csrIiJCEuHZgjw5OVkS4U5OTjzXsGTZpXBSM+TvnbYlMx3blLuk3T6BkZERmzZt+iICNCEhgZEjR3L48GFmzZrFvn37OH36NNOmTcPd3f2dX84vX76kTJky+Pj4ULZs2fceSwjB+PHjOXr0KCdOnEBdXZ2QkJB35p1HRkZiZGT01uh59rLPfU+npKRgbGzM8+fP0dfXJy0tjWPHjrFt2zYOHDiAg4MDrq6utG3b9p3Fo4mJiUyePJm1a9cyZcoUevfu/d0Wcc2dO5cnT56wcuVKEhIScqSKREdH06dPH+7fv8+WLVtYtWoVixcvRltbGzU1Nbp06YKHh0eu0TchBFevXmXt2rVs376dypUr4+vry4EDB6hSpYq03vjx49HS0nqrE8mtW7cYPXo09+7dY8aMGbRt21a6wfv999+5efMmtra2nD17luPHj0vnEJWQyk7fYO6GxX1SIeC1a9fo2rUrdnZ2LF269Iew/tPX1yc2NhYfHx8pFSY71aR58+Y8evSIBw8eoKSkhJqaGhUrVsTa2pp169YBWcXpqqqq0jZ6NTuhX9NNclbSsHJEWVOXpHsXUTUuhlGrUcRd2kXi7dOo6JlQsMVw1AtZI5PBk+lZNymLFi1i/vz5vHz5krZt27J48WI0NDR48OABy5YtY8uWLURFRSGEwNjYmNatW0vFuV27dsXCwoJu3bqxaNEiWrVqJY31v8rRo0eZPHky58+f/9ZD+aLkC+98fgiEEFy/fl1yIomKiqJ169a4uLhQr16972467urVq/Tt2xc/P78vdoyMjAz27NnDvHnzCA0NZciQIfTo0eOTp4pDQ0M5deqUVKwZGxtL3bp1JSFeunRphXST0NBQhcj41atXEQbmmNR1J1HfCmWZjHTx7/qv57u7VzSla4s6TJ06lY0bN6Kjo8OWLVvytPjv/Pnzkqdz0aJFWblyJb/++itjxox5b442ZEVfMjMzPzi3NjuCefLkyQ92PsnIyCAsLEwS4rmJ85CQEDQ0NN4bPTc0NHxnbmSTJk3o168fLi4uCsuTk5M5cuQI27Zt48iRI1SpUgVXV1dcXFwwMDCQ1jtw4AADBw6kRo0azJ0797uOzkUlpDJu5V4CnkQSGR1Pgzo1qFTSTBKmZ8+exd3dHRcXF/744w/at2/PmTNnGDFiBFOnTuXhw4ds3LiRjRs3YmhoiIeHB25ubggh2Lx5M2vXriUtLY3u3bvTtWtXbt++zbhx4yTnn2w8PDyoW7cu3bt3f+d4jx8/zogRI9DR0WHu3Lno6upSt25dAgICKFy4MM7Ozpibm9Nn7FSWnHrI6fuRAKTmUk/yrkLA9PR0/vrrL5YvX87ff/9Nx44dP/tafy3eJbxlMhmtW7fm/v373L59m6pVqzJlyhROnDjBjBkzgKxGRba2tsTEJfDowT30anRCv9a/whtkaFhVJCMmnIxXwcjUtVE1MEOmrExqyF3Ui9pSyH0WAE9nZAlvExMTGjZsyMGDB4mNjcXS0pK4uDiUlZWJjIxEW1ubmjVrEh4eTkBAAN26dWPdunWcOnWKevXqAVCkSBGaNWuGjY0Nw4cP/+rX9XsiJSUFU1NTHj169FHuUT8a+cI7n++WzMxMLly4IEW2lZSUJCeSqlWrfpEOW3lFZGQkNjY278xPzEsuXbrE/PnzOX78ON26dWPQoEGf7Srx/PlzKS3l5MmTpKWlSYWa9erVo0SJEjns+V68eIGvry/nrgZw6lkKIYmgpK5NStwrqpe1xLWyJXWrOmJmZsbVq1dp3rw5p06dYvTo0VJzmddvoj4lspeamsqkSZNYt24dnTp1YufOndSoUYOZM2diYWHxQed++/Zt6tSp88H2gdOmTWPTpk2cPn0aExOTDzrGhyKE4NWrV2+Nmmf/npKS8taoedGiRdmx7zCBCVrYVm/01muZmJjIwYMH2bZtG8ePH6dWrVo0btwYb29v7t27x9KlS2nYsGGenl9eku1Qcfp+JPJMOemvfbtlC1PTzCge7lvK6lkTsbe3p3r16kRGRrJjx44c6RZyuZzjx48zY8YMzp49i0wmo2bNmkyYMIH69etL7//27dvToEED+vXrp7B9gwYNGDt2LI0aNXrv2DMzM9m4cSO//fYbqampDB48mN9//x3ImuVy7DgUUcGFTJQ+uhBw0qRJ/PnnnxgaGlKlShVWr16do0HP9867hHezZs04ePAgPj4+1K9fH21tbRISEnjy5AnFixcHsma/AgMD6TJwNI/8zuUQ3ioGhTHrs5LEGyd4eWgBKKlgPtiTjLhIQtcORKaqQbERO4F/hXfhwoVJSEjAwsKCmzdvUqBAAe7du0fPnj05dOgQjRo1wtbWlrS0NJYtW4ZMJiMhIYErV65Qr149ZDIZ9+/f/2k7Zn4Kzs7OtGvXDnd39289lC9Gfsv4fL4rUlNTOXnyJF5eXuzdu5dChQrRpk0b9u7di52d3Q9T7WxkZERKSgrx8fFfpeCsatWqbNu2jWfPnrFo0SIcHR1p0KABw4YN+2QLMnNzc7p27UrXrl0RQhAUFCQJ8UmTJqGsrKwgxC0sLCThl916WghBcHAwtWrVoqBxfTauPMjgPtdQU1PDycmJSpUq0bJlS44cOcKoUaNo164dO3bs4G5E8jsie2HMP34/18heYGAgXbp0QU9Pj6JFi3Lu3Dm2bt360Q1cRowYwYQJEz5IdM+dO5d169Z9EdENWS2tCxYsSMGCBd9ZdJSYmJgjan7//n0OXLzBE63SpBqWR6gK7ge8kLZREs+ZfeQ2pXUzaFe2ALXLWtCyZUs6dOjAq1evGDRoECNHjkQmk/HLL7/w8uVLEhMTv4t0rjd5n0NFttvQM6GPrstELkaq0LZkSQoWLMidO3dy3Kjevn2bdevWsWnTJqytrfn777+RyWRs375dsmrs1q0bxYoVw9vbm9WrV+c4ZkhICEWKFHnnuF+37ezevTtxcXFMnTqVP/74g2nTphEaGsrBe7EoVWxHaub742RCQHJ6JlMP3QGgUyVzLly4AEDp0qU5ePDgD/M5+qE4ODgAWeIcsv4X3kRbW5tq1aqhqpX7jKCqYVFkMpnUaVhZWx8lDW2UUhIAEOkpObZZsWIFzZo14+HDh9jY2BAXF4eBgQFPnjwBwNvbG29vb2l9IQSPHz+W/jY1Nc0X3W/QokULDh48mC+888nnS5KQkMDhw4fx8vLi8OHDlC1bFhcXFy5evIiVldW3Ht4nIZPJsLCw4OnTpx9UoJVXFCtWjNmzZ/P777+zdu1a3NzcMDU1lZwaPjWPWiaTYWVlhZWVFT179kQIwYMHDzh58iSHDx+W0jdeF+LZnS7Nzc1xcnKiSZMmuLq6IoTg6dOnUnrKtWvXsLOzw9jYmMzMTGxb90XJsR0Zchm5yYxsAXXsdjhn7kcxoZkNnSqZM2fOHGbOnImNjQ2PHj1i2rRpdOnS5aNnRg4fPszjx4/59ddf37vuokWLWLJkCadPn/7mEURtbW1KlSqlYJW5+dITThy6S3pGJjIBb8otuSwrP/t2nApTzsfD4smEnt2Ompoa6enpaGtr4+zsTPHixYmIiGD27Nn06tWLhg0b4u7uTrNmzb562+nceF9xb0ZMOCHLewJZnvKpGYINN+Kxc+nPmbXTJM/o2NhYtm3bxtq1a3n27BkeHh6cPn2a0qVLS/vq378/T548YdOmTXTq1In4+HhKlChBQkJCjm6TwcHB7xXerxMSEsJff/3FrFmz6NGjB0IIytT4BZ3Wv5HBx72Pk9PlTDl4m0WTRxN27x4ApUqV+ulENyB9rr15bq/fIMbFxVGgQAEinuVeaIvSG7UKsvdfb7lcjrKyMnfv3gWyAi7q6upYWlpy+/ZtFi5cyKBBg6T1Hz9+jJWVFadOnQLI04ZaPwvNmjVj9OjRZGRkfJXC82/Bz3lW+Xz3REVFsX//fnbv3s3p06epXr06Li4uzJs377vOHf0YLCwspHbuXxtdXV2GDBnCwIED2bdvH/PmzWPUqFEMGjSIXr16fbY1mUwmk0Rev379EEJw+/ZtfHx82LVrF4MHD8bIyEiyLixcuDAPHjyQtrW0tMTS0pK2bdsybtw4KlasyODBg3mkZMa+Zypkyt8vDrIje1MO3mbW7NnE+x1CCEH9+vUJCgqiW7duBAUFfZTNWHp6OsOHD2fevHnvrRtYuXIlc+bM4fTp05ibm3/wMd5FdvTzbZw4cYKzZ8+yceNGgoOD0dHRwcrKin79+tGzZ5awrFu3LqdPn0ZNXYNi/VeTrqGPPCWB5wuy8nmL9FuDir4pyU8CiD23hbSwh4iMNNTNy2HpMYv6tmXw3bqAsWPHoqury+LFi/Hy8kJZWRkjIyMKFy7M0aNH2bdvH3K5HCUlJYQQkuDo1asXtWrVokiRIhQqVCjPiy8vX77MzJkzOX/+PNHR0ejpG5KkY4Z2haZolc7doUamroWuUyuFZUqqGsRbN+ZuRDLRjy6ydu1a9u/fT8OGDfn9999p3LjxW7/4LS0tmThxIhMmTKB48eKYmZlhZ2dHpUqV6NatG87OzqSlpSGTyT6q5mLw4MH069dPSo/Q1NSk7oDpnLv5mGif9aQG30ZkpKFqaoVB3W6om2XdEMjTUog9t4Wk+xfITIxBxaAwBSq7IGzrolOpDd0qlWHy5MnScRYtWsTgwYOxsrLCx8fng+xJf0SMjY0ly0F3d3c0NDR49ex+nu2/V69e7Nu3T+oK26VLFyCr++ihQ4cYPXo0Fy5cQFNTk8DAQF6+fElQUFCeHf9nxMzMDEtLSy5cuEDt2rW/9XC+CPnCO5+vxvPnz9mzZw+7d+/Gz8+PRo0a0bFjRzZt2iRNEf5MvE9EfQ2UlZVxcXHBxcWFq1evMn/+fKZOnUrXrl0ZMmSI9AX/uchkMsqWLUvZsmUZOHAgcrmcwMBAfHx82Lx5MwcOHJA8yXv16kWdOnUk/2I9PT127tzJL537ot92Eqh8XNlJaoYgpXgDymrJWfbXWMkp4FNYtmwZxYoVo1mzZu9cb/369UyZMoVTp07laYfGHj165LBPa9u2reS57evry6RJkyhWrJiUluDr68vFixcl4Z1NWmoK4We3Ydiob67HyngVgkhPRdXIgrSwrJuilAw5dzVt2eVzjfLm+pQoUYLIyEjatm1LUFAQfn5+dOzYkfv375OQkECtWrVISkoiPDycuLg47t69y/jx4ylXrhwvXrzg5cuXmJiYvLcw9EO7FO7YsYNOnTqRmZmJjY0NLVq0wOfmM6LvXofbp3IV3iIzA2VNXQwb9snxXHJ6Bs7jl6J3Yzs9evRg/vz5H1XUdeHCBbS1tdm3bx8pKSns2bOHDRs2MGDAAOrXr/9Wj+7cyC7qLFy4MIsXL84aO+D7LJbwf34jIzYcdfNyKGsWIOn+BcL/GU/hHotRNSjMy0MLSLp7DhUDM7RsapJ09ywvD8xDpqRMsH09kjP/tc1bv349Q4YM+elFdzZr1qyhT58+nDx5kmLFiqFrZkX8i8fv3/ADSElJYdOmTchkMurXr8/o0aMBaNq0KV5eXsyYMYNDhw5JgYohQ4bkyXF/dlq0aMGBAwd+WuGdX1yZzxflzp07UnFkUFAQLVq0wMXFhcaNG38XU9RfkhkzZvDy5Utmz579rYeiwPPnz1m8eDFr1qyhTp06DB8+nOrVq3/RKehChQoRHh5O165diYiI4Pz585QoUUJKS6lduzbtF3pzP0EdPqFoVsjlGCY/x61YEo6OjqxatYp//vnnoxprfKh9oKenJ6NHj+bkyZMKKQh5TW7FZK1atZJmil53J3n16pUk8rIj3iADZRWK9FuFkqpGjoh3NnFX9xJ9YhXq5uUo5DZD6iZqE3WOYcOG0aJFC/bv309CQgLGxsakpaXx4MGDHGlgR44coWnTpgAULFiQNm3a0LZtW0qVKqXg3JJbcaiurm4OC8U3xbmamhrFihXj1atX0g17TEomNWaeJCUtnfRXISipqEspJYZNfiX2/FZUDItg1GyoQqoJ/FsgZ9S4LwUenSAiPIzWrVuzdu3aD3ZJyrYbfNONIiQkhD/++IN//vmHwoULS7USud2kvesGXVNbF/0mAwjdPQMV/UKY9V2FTCYjYtdfJD+4RIFq7Sng1JrgRVn5sEX6r0VFz+Tf17SIDZbd52EdfJiD6xdRokQJnjx5goWFxU8rupOTk/Hz81Nos56QkICNjQ2xsbE8j4yhYPelUprVp5D93nn06BFxcXEcO3aMY8eOcfnyZRwcHGjUqBGNGzfGycnpu7Xb/J65fPkyPXr04NatW996KF+E/Ih3PnmKEIJr165JYjs+Ph5nZ2dmzpxJ7dq1f9qcrdywsLD4onaCn4q5uTkzZ85k4sSJrF+/Hg8PDwwNDRk+fDht27bNU0u/bLL36eLiQvPmzZk5c6bkm7xixQoyZSqY9l+HTEWJhMDjvDy0APWitqgVKknCjeMoqaqjX687OmWzLLhiL+8mIeAwmQmvEPJMVA2LklqzIw9l6Xh5/caVK1cA2LJlC7t375acAzZv3vzWZi+TJk2iQ4cO7xTdO3bsYOTIkRw/fvyLiu63UbhwYQB69+7N7t27qVatGs2aNVMQdOmZWXnO2ZHP2Is7MKjd5YOPIQT43Isk5tE1AJycnADQ0dHBxsaGgIAAAgMDJeG9ePFibt++zYkTJwAYNWoUv/76K9u3b2f8+PGEhITQtm1bOnbsSNu2bXPk3AshiIqKyiHIz507p1AsmpqaSmpqKpBVPDdx4kRCCpQhM9MQmZIyakbFyIgJl/Ybc3oTmqWqoqxtwLt4dXYL1nUa8SIkGE9PT+rVq5dj9iCbzMxM0tLSSE1NJTIykj179jBgwADu3LkjLU9LSyMtLQ1dXV0qV65M48aNOXnyJLNmzcLMzIxKlSpRpkwZZDIZaWlpREdHA0gdNNPS0iRHodT0dJJfhQGgYlhEujlWLViU5AeQERtBRmzWOctU1FHRM5Geh6znUzLkRMWnAVlCEbIiij+D6M6uNXm9Mc2dO3ewtbWlSpUqtGjRgubNm7Np0ybu3r3LsGHD6NOnDyP23MP7Tvg73WHexuvxCSUlJSpUqECFChUYPXo0SUlJnD17lmPHjtGrVy9CQkJo0KABjRs3plGjRnk6O/YzU6lSJaKioggKCsqzWdnvif+OCsrni5GRkcHZs2fx8vJiz549aGpq0qZNGzZs2ICTk9N3bfv3JfkeUk3ehY6ODgMHDqR///4cOHCA+fPnM3r0aAYNGkTv3r3zNP0nO+qTmJjIhAkTmD17NmZmZnTp0oV9+/YRFRVFwrW96FbtIG2TGnwbkZmOeuFSpDzx59WRJWhZV0FJXYuM2HBUjS3RKF4ReVIsSfcuELFvLuae3iz/ew5du3Zl06ZNPHz4EEtLS5SUlLh16xbVq1enbdu2UgdOBwcHtLW1uX37Ntu2beP27dtvPYe9e/cycOBAjh079kENdb4EEydOxM/Pj2vXrrF582Y2b96MkpISEydOlCL7kfFZ4lS9iA3y1EQSrh9Ft0LTjzySIOBeVi5qZmYmwcHBUiEZZLnHlClThszMTDZs2MC1a1ki3dTUFBMTE8LCwqhZsybVq1fn2bNnnDhxAg8PD+Lj46lZsya1atWiZMmSyOVy6ZGZmYlcLqdAgQLo6OhgbW2t8NzZs2fZvHkzAFpaWgQGBnLp2UVe3TwtjbpIvzXS70bOY9G0zHKBeV2Qv4lhkwHEGuihrX2alJQURo4cybRp03II6dTUVCmXXU1NTRpXx44dUVNTk5Zn//78+XMA/Pz8MDExoU2bNoSFhXHx4kV27txJ6dKlqVixInJ51o1SvXr1qFSpEmpqajx69AgfHx+UlJRR0cuanch49QIhBDKZjPRXIQCo6JlIz4uMVDJiI1DRM1F4HiA1IyvVpEGDBty9e5eFCxdSvHhxhg4d+pHvi2/Ly5cvuXLlihTNvnLlCgUKFJDarLu5ueHg4ICamhq7du1i1qxZJCYmMnr0aNzc3KSZjAF1rTn7IOqTOldqqLw9gq2lpUWTJk1o0qQJkNVV+fjx4xw7dozffvsNPT09SYTXq1fvk3su/OwoKSnRtGlTDh48yMCBA7/1cPKcfOH9E/K5Xc0+hJSUFLy9vfHy8mLfvn1YWlri4uLCkSNHpGjOf53s4srvHWVlZVq3bk3r1q3x8/Nj/vz5WFlZ4e7uzpAhQyhRokSeHevFixcsXboUyIpG16lTh7179+Ls7EzstQMKwltJQ5dCbjNBpsSzOW0Q6SmkvwpBvXBJDOp2J+neeTKiXyBTUkFZS4/MxGjOnbsArnWkm73sD+9sf1/IEjjXrl3D09OTmzdvYmVlRXR0NLVq1eLBgwdoaWmhpaWlMO5Dhw7Ru3dvDh069E5Lvy9N0aJFuXr1Kjdu3OD06dNs3bqV8+fPM3nyZAYOHIiRkRFJaf+KCf1aboRt9CP24raPOk5qhiAiKg6A+fPns3btWpSUlAgLy4q+Llu2DE9PT5SUlFBWVqZs2bIkJiby5MkTRo8ejb29PVpaWigpKUmP4sWLk5ycTGBgIN7e3sjlcszMzDA3N8fAwABlZWWUlZUVtnn97+zIMGS5QRQuXJiHGpAih6Tbp3Ocg0ZR2w86VzVTK0qXLoZdYgO2b99OnTp1mDt3roKIzv799Rm7ihUrMnPmzLd6dPfv359y5coxYMCAHM+Fh4ezZcsW1q1bR0JCll1d1apVadWqFefPn+fOnSwrwMyMDDRLVEJZz5SMmFDCt4xDWasAyfcvIlNRR8e+Ecra+miVrkHSvfOEb5uIepEyJN09B4BuxayUCPX/i8WiRYsyd+5catWqxfDhwzEyMvpubdvS0tKybq5ei2aHhYVRqVIlqlSpQv/+/Vm/fr1CMX5KSgrr169nzpw5mJqa8vvvv9OiRYscwZ/y5vpMaGbzTiec3NBUVcryR5/8YaFyMzMzKc0ou+7F29ubxYsX4+7uToUKFSQh7uTk9J+aEX4fzZs3Z+3atfnCO5/vm9ebR8CHex9/KLGxsRw6dIjdu3fj7e1NhQoVpM5vH9qY5L9EoUKFiI2NJTk5+YfJZ69YsSKbNm0iJCSEJUuWULVqVWrWrMmwYcOoVavWZ99QBQcHSx67ZcqUAcDGxgYgK20kM11aV9XIHJlKVoRKpqaBSE1CpCUjMtMJ2zSC9MicswnRr6IU/n7T3zc5OZkePXrQo0cPIOvLfcWKFUydOhVDQ0MGDRrE7du3sba2xsnJCScnJzIyMpgyZQr79++X0i6+FZcuXcLe3h47Ozvs7Oxwd3fHwMAAIQSJiYkYGRmRKf9XFKiblUazRCWS7pz76GPZ1WjIlWc3qV27NgcPHiQ+Ph5jY2NkMhnnzp3DzMwMNTU1KQqempqKiYkJcXFxzJ8/X+rMlxtCCG7cuMG2bdvYtm0bwcHBdOjQAVdX17f69SclJWFubs6rV69QVlZm3rx5xKw6zVE9q1yFt0zlw1KmZDJlLM1MEf9P49HX13/vzaafnx/R0dE0aNDgresEBwdLkc83MTU1ZciQITx58oQ7d+6QkZHBwIEDGTJkCGXKlJHetxrqamhqaWHaaSoxPmtJCb5NWkQ66ublMKjrgapBloVlwWZDUC5gRNL9SyTdPYuKfmEKVHJGu2xdNFSUMNL9N2e9fPny7Nq1i+bNm9O9e3cMDQ3fW0z8pcm2GM0W2JcuXeL69euUKFGCKlWqULduXcaMGUOZMmVyzZmOiYlh6dKlLFq0CCcnJ9avX0/NmjXfeczs5kLv8n7PJremRB/L62kpo0aNIikpiXPnznHs2DH69OlDcHAw9evXl4T4z5hi8TE0btyYHj16fLd9Az6HfOH9k/ChzSNe9z7+kA+Q8PBw9u7di5eXF+fPn6d27dq4uLiwdOlSjI2N8/gsfi6UlJQwNzfn6dOnkrj8UShSpAjTpk1jwoQJbNy4kV69elGgQAGGDRtGhw4dPjkPPCIiAm1tbRITE7l79y4mJibc+7/HsLKOITLl1/ar4KP7rxBLj3qeJbplSpj1WY6KfmFC1wwgPeoZ6iqKka23+ftKe5XJWLJkCWvXrpXER2pqKjdu3MDX15f9+/dz9OhRlJWV6d+/P46OjpIgt7Oz++o+vHPmzOHkyZPUqFGDokWLSi3KS5UqJeXsKispnqteLTeSH13Nsa+U57dIuH6M9JfPAEh/FUzUgfmoFiyKXrX2ODVux6Njmzh06JDkapKamkqHDh0oUaIEp06donPnztSuXRsDAwPOnj1LXFwcxsbGVKxY8Z3nIZPJsLe3x97enr/++gs/Pz+2bdtGy5Yt0dLSkhrUZN+cQdY0/pIlS3Bzc2PdunV4e3vzUq4JGp/XoEpdRQmbwrrc+YhtVq1aRc+ePd+ZRhcSEiK50UDWjcPVq1c5f/4858+f59y5cyQkJODi4kKTJk2oXLkyT58+ZePGjezduxdXV1dcOnXl92ugql8IY5fxbz2WkroWhg16Y9igd47nBLBh0WwKrlsoLWvUqBFpaWkfccZ5S3x8PFevXlWIZstkMqpWrUqVKlWYOnUqTk5O720+FhISwvz581m3bh0tWrTA29v7o+xb3ataYl9Un6WnHuJzLxIZ/35Xwr/dTuuVNubXutbYF9X/tBPOBS0tLRo3bkzjxo2Bf9NSvL29mThxIgUKFJCe/y+mpejp6VGpUiVOnDghNWT7WcgX3j8B72se8TpvdjXLTXwHBQVJxZE3btzgl19+oXv37mzfvv2rdGH8mcjO8/7RhHc22tra9O/fn759+3Lo0CHmzZvHmDFjGDhwIH369PkouzSA0NBQ+vfvz5w5c+jcuTO//PIL+/btA0DfqeUH7UNJs0CWKBdyok+sRqSnkv4qqxvjy+BHXL9+/YPHs3TpUiwtLSU3DshKY3ByciI1NZWJEydy9OhRqlevTmBgINeuXePKlSssW7aMBw8eUKZMGUmIOzo6Uq5cuQ92xPgUXF1diY+Px9fXl2PHjmFgYICLiwszZsyQbi601BQjguqFrNG0rkLyw8sKyzOiQ0m8eUL6W54YQ+LNE6ibl8O0liv2VoXo5e3NsGHDOHToEJqampLlHmRNo5cqVQpvb28pGt6+fXt+//33j/KJl8lkODo64ujoyMyZM7l8+TLbtm2jYcOGFCxYUBLh1tbWdOzYkQIFCtCzZ09CQ0ORyWQIDT00ildEy+bjupNmI4B2FYsyZfeHrZ+YmMi2bdsIDAx853rPnz/n+vXr/PPPP5w7d46bN29iZ2dHjRo16NGjBzExMbRr145hw4ZJ25QvX55WrVrx6tUrtm7dytypk4izbIpacSdkn1ArI5Nlica8SjH8FDIzM7l165ZCNDsoKAgHBweqVKmCu7s7ixYtwtzc/INn1O7cucPs2bPZs2cPHh4e+Pv7f3KxqH1RfZa7O/EyIZWdfsHcDY0nLiWdAhqq2BTWpV3FvEvRfBdvpqXcuHEDb29vlixZgru7O+XLl5eE+H8lLSW7i+XPJrzz7QR/IGrVqsW5c+cULNKuP4+h9Z8beLpmKCipUHTQRpQ1P+zOWFNVmW19qmJXRI+bN29KYjskJITWrVvj4uJCgwYN8rtrfQa9evWiUqVK9O2bu5fyj0hAQADz589n//79dOrUiSFDhih0S8wNc3NzgoODKVWqFDdu3GDWrFlSE5hixYrRqUs3PJPKkSaX/etq8n97O4Bn810RqYmYdpqGhoU98X4HiTn/DyIjDd0KTUl9cY/U5zep06AxTx7eIzY2lpiYGIYOHcr8+fMJCAiQpu+zP/KioqKwtbXl1KlT2Noq5gNfuXKFFi1asGnTpremCyQlJXH9+nV8fX25du0a165d4/Hjx5QrV04S4k5OTtja2n4Rp5i3EZWQSo2ZJxVSzT4WdRUlLoyp/00Fm1wu59y5c2zbto2dO3dKHVD379+Ps7MzSkpKrFq1CoOWo1G3rkzOvpwfgJDT0MaE1d2qfPAm69evZ+fOnRw4cEBhrHfv3pUi2efOnePx48c0bdqUmjVrUqNGDSpVqiTVDqxbt44lS5Zw6dKltwqoyMhI3NzciMjUJMaxGyh//A1d9md8XkZq30doaKiClZ+vry+FCxeWotlVqlTB3t7+k/4nLl68yMyZM7l48SIDBw5kwIABH33z/yOSnJzM2bNn8fb25tixYzx79kxKS2ncuPFPm5Zy7949GjRowPPnz3+qurF84f0DsWLFCvr160epUqWk6fk+m66xbdFfxF3di6Z1FUzaTfzg/ckAM3kkEbunkp6eLjVaqVGjRr73aB7x119/kZSUxLRp0771UPKc0NBQlixZwsqVK6latSrDhw+nTp06OT4gg4KCKFmyJJmZmejp6RETE5Pr/vpsuvZZFl9NbE1Z7u6EXC7nwoULbN68mZ07d2Jra4u7uzvt2rVT+JIeOHAgMpmMRYsWKezLz8+Ppk2bsmbNGlq0aPFR40hMTCQgIEAS4r6+vjx9+hQ7OzuFyHiZMmW+aMQqr67l90JycrJkoSiXy0lPT0dZWZkmTZowYtpC+u+490kOFUryDDgxn7VzJkle6e+jZs2aDB48mEKFCklpIxcvXkRfX18S2dkdPJ89e5Zj+4iICOzs7Dhy5Ih0M/gmFy9exNXVlUaNGuHr68tLA1tUKndAKH24WM0qBCzzyTnJH0JycjK+vr4K0ezExERJYFetWpVKlSp9ljgWQnDo0CFmzpzJ8+fPGTlyJN27d89RAP1fIjQ0VHJL8fb2RkdHRyEt5XM7E38vCCEoWbIkO3fufKsN7I9IvvD+gYiOjqZQoUKkpaXh6+tLsVJlqT7jOI//7kpmwiv0arqR/PgaGS+DkaenoKxZAK3S1TFo0AuZsmqukcSQpT3IiIvg5MmT7yyGyufT2LRpE0eOHMHT0/NbD+WLkZSUxKZNm1iwYAEaGhoMHz4cV1dX1NTUmDx5MnPnziUuLo6KFSty//59nj17hoFBTm/l689j6Ljq0icJqLdF9tLS0jh8+DCenp4cPXqUevXq4ebmhpWVFU2bNuXOnTsULFhQWj8wMJDGjRuzbNkyhQY1n0N8fDz+/v6SEL927RohISGUL19eIWe8dOnSeXbD+yWu5bciKCiIzp07k5SUREREBOnp6airq1OhQgUuXrxIuXLlKN28J2cTTBTyc9+HujJMbFEWvcgb9O/fn1atWjFz5sxc0+mymz7t27cPT09PVFRUpLSR7Mfr7hrnz59n5MiRXLx4Mce+OnfuTNGiRZk1a1aO54QQLFy4kKlTp9KsWTMOHjxInTp1ePLkCb/O/4fZ3o++SiFgbsjlch48eKAQzb57967kmZ0d0ba2ts6T6GR6ejpbt25l1qxZKCsrM2bMGNq3b/+fSLH4GLILlbOb+Fy8eBF7e3tJiFeqVOmHvmZDhw7F2NiYCRMmfOuh5Bk/7qvxH8TAwIBmzZqxZ88e/vnnH0q06Efyk0AyE14hU9dGrZA1KU8C0CpdA5SUSH50lXi/gyjrGqFXrX3uO/3/5+PPNI3zPfGjWAp+DlpaWvTt25fevXtz5MgR5s+fL+WB3717Fy0tLX755Rdmz56Ns7MzDx48oHLlyjn287kWX7kJRTU1NckqMS4ujt27d7N8+XLOnDmDo6Mj169fp06dOigrK3P79m2aNGnC33//nWeiG0BXV5fatWsrtD+OjY2VxPihQ4eYMmUKYWFhVKhQQSEyXqpUqU/ywf8S1/Jb8M8//9C/f3+0tbURQpCUlMSkSZMYNGgQKioqpKamcuzYMbZt28arx8lo1+yCUFbhXWknMhmoyATJF7ZQp+9MzKu2lOz17OzsWLFiBcWKFZPSRs6fP09UVBTVqlUjLi6O9u3bs2rVqndGXIODgylSpEiO5YcPH+bSpUvcuHEjx3Px8fH06tWLmzdvSkXZ06ZN488//+Ty5csUKVIEp+LGby0EJCMNZDKsNJP5rU1l6pW3/IgrnZNsz+xskX3lyhX09PSkaLa7uzsODg557tiUkJDA6tWrmTdvHtbW1syZM4fGjRvnf0e9hdcLlUeOHElycrLkltKvXz+ePXtGvXr1JCH+ZsfZ753mzZvz+++/5wvvfL4d7u7u7Nmzh61bt9LGsRMxN04BoG1TAy3rSiipaZIacpvMpFhUDYuQGf+SlKeBbxXe+fMdX5bvvYlOXqKkpESzZs1o1qwZgYGBLFiwgMOHD9OxY0eGDh1KsWLFKFmy5FuFN3ycxZeQy9FQU/7g6fQCBQrQrVs3jI2Nefr0KW3btmXkyJGEh4fTpEkTDh48yJw5c3B1df2Es/849PT0qFu3rkJ6Q3R0tNQcZ+/evUycOJGoqCgqVqyokDNeokSJDxLjH2uXRkYaVXWica/6sc128p74+Hjc3Nw4ceIEWlpapKenU79+febOnasgaNXV1WnZsiUtW7YkOTmZlTuPsP7KM15pFM6S3ir/5kUrkwnIaGRbmF/rWnPM4C7Nmzfn+PHj3Lt3j1KlSnHr1i2aNWuGtrY2TZs2pV69eowcORJbW1vS09MxNzdn/fr1701zeNPRBLLSkPr378+KFSty2KPdvHmTtm3bYmxsTHh4OBMnTqRu3bo0atSIAwcOSOf8rkLA0oV0MEt9jtc/e2lT91eqV69Ot27daNmyJRoaGu8cb1paGtevX1eIZkdERODk5ETVqlX59ddf2bBhA6ampu9/8T6RyMhIFi1axLJly6hTpw67du2iUqVKX+x4Pyuampo0atSIRo0aMXv2bMLCwqS0lD///BNtbW2ppX29evXytFHal6B27drcvn2byMjIn8ZJLT/V5AcjNTWVQoUKERMTQ5NRi/FeOAZ5aiKmnaeTGnKHmNMbc2yjamKFWY+FuaaaBC/pRmZ8FD4+Ph+c45jPh5ORkYG2tjbx8fFf1O3ieyUsLIxly5axfPlyKlWqhJ6eHtbW1vz555/v3C4wOIalpx5y/E44menpiNdtBjPSUFNXxyQzErOYm2xfNvuDx5OWloadnR3z58+X7AOPHTtG+/btUVVVxdTUFDc3Nzp37vxdtHd++fKlJMazH7GxsZIYzxbkVlZWb40IZl/L99mltS6pSdcWdTl58iR2dnZf5wRzYd++fbi7u5OWlkbJkiVJTU1l6dKlNGzY8IP38Twims6/LSQkQZAiV8JEXxdT9XS0wm+wctE8KZq9efNmIiMjcXBwoFatWtSoUQN7e3vmzZvHwYMHWbFihfQ+2b59O8uXL+fkyZPvPf6IESMoVKgQo0aNkpaNHDmSsLAwqftmNps3b2bw4MGYmZmhpaXFxo0bKViwIFWqVOGvv/6ic+fOH3ze2SQmJrJ7927Wr19PQEAAHTp0wMPDgypVsopInz59qmDll+2Z/XoB5Ns8s/OaoKAg5s6di6enJ+3bt2fkyJHvLdbO59MQQnDz5k0pLeXChQvY2dlJ0fDKlSt/l2kpbdq0wdnZma5du37roeQNIp8fjl69eglA6BUyF4BQLmAsio3ZL1RNimctr+Umio3eK/TrdhOAUDUpLizGHhBGzmMFINRMSwiLsQdE0SFbBErKAhCVK1cW48aNE9u3bxcPHjwQmZmZ3/o0fxosLS3Fw4cPv/UwvilJSUli1apVwszMTOjr64t169aJlJSU9243bOxE4TJ+iRi61V/0WH9FDN3qL5oMnS1adegsXr16JYyMjMSdO3c+eBzz588Xv/zyi/T3kydPhKWlpVi6dKmQy+Xi3Llzon///qJgwYKiZs2aYtmyZSIqKuqTzvlLERERIQ4fPiymTJkinJ2dRdGiRYWBgYFo2LChGDNmjNixY4cICgoScrlcYbuo+BSx/PRDhWu5/PRDERX/7+uwdu1aYWdnJ5KTkz97nJHxKWLZqYdiyFY/0X39FTFkq59YdkrxeArrR0aKWrVqCZlMJsqWLSsMDQ3FX3/99UHvk9wYNGiQmD9/vrh69aro2bOnMDY2FoBQUVER5cuXFxMnThTe3t6icePGolevXjmu14kTJ0Tx4sVF165dxcuXL0WjRo3Eli1bPuh8yw9aJlpP3y2d77Vr14SJiYmIiIiQ1k9OThZ9+vQRpqamwsDAQEyZMkWkp6eL1NRUUbt2bTFu3LhPOu83uXnzpujevbsoWLCg0NHREdra2sLExEQ4OzuL6dOnCx8fHxEfH58nx/oYAgICRKdOnYShoaEYM2aMePHixVcfw3+d5ORk4e3tLUaNGiXKly8v9PX1hbOzs1i6dOl39Z21evVq0aFDh289jDwjP+L9A3L69GmF6HSBau0xqONB+LaJpAT5o2JYBPUiZUi+fxF5aiKqJsUx67GI9FchvFjZDwCdis1IC31AWuh9AKZMmUJmZib+/v74+/sTExND+fLlqVChAg4ODjg4OGBra/ufjNp+LnXr1mXixInv7HL3X+H8+fP06NEDS0tLAgMD+fXXX+nXr99bpxBr1qzJpEmTFKKdqamp0jR6cnIyV65cYefOne89dlRUFGXKlOH06dPY2toSHBxMnTp1GDx4MEOGDFFYNy0tjaNHj+Lp6cnhw4epW7cubm5utGzZ8rvsQhoeHq5ga+jr60tqaqpC8aajo+N7vZKFELRt2xYrKyvmzJnzSWN5dwfdrAj76x10k5OTmTp1KrNmzUJXVxcdHR3s7e1ZuHDhR9ukpaSk4Ovry7lz51i4cCFxcXEYGRlRo0YN7OzsmDZtGnPnzmXHjh1cvnyZX375hVatWjFr1ixcXV0ZN26cwv4SEhIYP34827ZtIyUlhfDw8BxpGx9yvvKQm3SvbMb4fm5AVpTX2dmZly9foqenx+bNm3FwcEAIQd++fQkPD8fLy+uj8/uzPbNfj2Y/efKEChUqUKVKFQwNDblz5w4HDx7EyckJDw8P2rRp89UcQoQQnDp1ipkzZxIYGMjQoUPp27fvT+PC8aMTHh4upaUcO3YMLS0tKS2lfv363ywtJTQ0FFtbWyIiIr6qNeuXIl94/4AIIShevLiUO1y411LUjIqRFvWMlwfmkRb5FPXCpdAoXoHYs56S8AaIvbSTuMu7kamoomPXkMSbJ8mIi8yRavLy5UsCAgIICAiQxHhQUBA2NjYKYrx8+fL5TXXeQ7du3ahdu7bUpvy/TEREBDY2Nrx69YqbN2+yYMECdu3aRfv27Rk6dKiCn3ZycrKU8/pmTuyjR4+oVq0au3btolOnTuzevfuteePZDBgwAGVlZRYuXEhoaCh169alZ8+ejB49+p3bxcXF4eXlhaenJ1evXqV169a4u7tTr16979p288WLF5IY9/X15erVqwghFIS4k5MTZmZmCmI8KiqK8uXLs3nz5o92OnpfB91sZLIsr/AGBrFsnzaI+Ph4ihUrRmpqKosWLfrghhlRUVGSpd/58+e5fv06NjY21KhRg5MnTzJhwgQ6duwIZH1uFihQQHLViYyMZPfu3Wzbtg0/Pz/S09P59ddfmTp1ao4Ag4eHB3v37qVp06YsXLhQulH80PNFyNFQU+G3ZmXQj7qJu7s7crmcfv36MWXKFKlXwqJFi1i5ciUXLlz4oM/VFy9eKFj5+fr6UqRIEQU7Pzs7uxxiJTk5mX379rFhwwYuXrxImzZt8PDwoGbNmp9UzPs+MjMz2bNnDzNnziQuLo5Ro0bh7u6e3yPiO0YIwa1btyQRfv78eSktpVGjRlSpUuWrpqU4OTkxZ86cnyIlNl94/+B8Tb/epKQkbty4oSDGb968SZEiRRTEuIODwxctwvnR+OOPPwDem9f8X0AIgb6+Po8fP5Zs/CIiIli2bBnLli3DwcGB4cOH07BhQ06dOsX48eNztWQD2L17NyNGjGDIkCHs27ePEydO8DIxjZ2+wdwNiyMuJYMCGirYFCqAnXYCLs0acefOHeRyOXXr1qVTp0789ttvHzX+0NBQtm7diqenJy9evKBTp064ubnh4ODw3bsuCCEICQlRiIxfu3YNFRWVHJHx69ev06dPH65fv46Dg8M7C4Tr1KnD6dOnpb9l6lqoFjRHv2ZnNK0cpeUJN04Qd8WLjOhQlDR10SnfmAKVXUi+4Ena7ZO4uroSHBzMlStXSE1NpUGDBvz9999YWFhI479//76C0A4LC6Nq1aqSpV/lypXR0dEBwM7Ojs2bN1O+fHlpDA4ODqxatQonJ8XPvLCwMBYuXMjs2bPR0tKibdu2uLq6Ur9+fWQyGZaWluzevZvt27ezefNmFi5cSKp5ZaYd/jjXGGWRSYzPWjRDrrFt2zZq1Pi326a3tzddu3blwoULuUb6k5KS8PPzUyiAzPbMzs7Nrly5cq5Wne/ixYsXeHp6smHDBpKSkqTuiXnhfpGamsrGjRuZM2cOBgYGjBkzhtatW38RcZ/PlyUlJYXz589LQjwoKEhyS2nUqBElSpT4op+Bf/zxB6+S0inbomeOz/f2jl+nu2hekS+8f3C+tV9vRkYG9+7dUxDj/v7+aGho5BDj7yoA+5lZu3Ytp0+fZsOGDd96KN8FTk5OLF68mKpVqyosT0lJYcuWLVJLcisrK6ytrZk7d+5b9zV06FCCgoK4FZZAuQ4juBOT9f56c7o/NS2NElop/N62KoPcWtGqVSumTJnyWedx9+5dPD098fT0RF1dHTc3N9zc3H6oLnJCCJ4/f66QonLt2jU0NDRQU1NDV1cXe3t7tLS00NLSYtmyZaSlpdG2bVvJtSMqKgpPT09UDQqhYVWJtPDHpAbfQqaiTpGBG1DW0CHx7jmi9sxApq6Ntk0NUkPukh71DP263dCv1Jqp9QoyqldHXrx4QYsWLVBTU2P37t0UL16cvn37cuHCBS5cuIC2traCd3a5cuXeOutQqFAh/P39KVy4sLSsXbt2tGvXToqCv4m3tzedO3emZ8+e+Pj48PjxYxwdHXn48CF2dnacP3+e2NhY5MhQLWKLQeNfkcmUCFneEwDNklUxaZt1Mxd3dS/RJ1YpFLNDVtOexumXWDE/a1l2oW+tWrXYsWMHtWvXRi6Xc//+fSmane2ZXbZsWYVodl6KHSEEfn5+bNiwgX/++QdbW1s8PDxo164dBQp8WDfkbGJjY1m+fDl///03FSpUYMyYMdSuXfs/+fn/sxIeHs6JEyckIa6hoSGJ8Pr163/0DeC7uP48hqleV7kSnIi6uvp709e+d/KF909A1nTnp/j1fpmuZkIInj17lkOMx8bGUqFChRx54z9Dzta7OHnyJJMnT+bUqVPfeijfBZ06daJ58+a4u7vn+rwQghMnTtCxY0cyMzMZOnQo/fv3x8TEJMe6aWlpOLoOIbHUL8hRgndE0mSAyEyjouwJu2YMzVPBcunSJTZv3sz27dspVaoUbm5udOjQASMjozw5xtdECMGTJ0+4cOECgwcPpnDhwoSEhKCrq0toaCgZGRnMnDmTHj16YGRkxKRJk/jzzz8l0SkyM3g2rx1kZlCo61zUzUoT6TWdpHvn0avZGf2anUkLf0zousEoaehgPsSTMhmPOTJ3GCYmJnTr1k3qBimXy2natCkeHh7UqFEjh0Xf25DL5airq5OUlKTw+TJ27Fh0dXXf6Qm8Zs0apk+fzsWLF0lISKBFixY8ePCA9PR0ihYtiqOjI35Pogi+649Juz9Q0TWShDdAoW4LUC9k/VbhnRb+iPCNI1CSZQUupk2bxtq1a2natCkGBgZcunSJK1euoK+vrxDNdnBweK8tYF6RlpbGwYMH2bBhA6dOnaJFixZ4eHhQv379d6ZXhYaGsmDBAlavXk3Tpk0ZPXo09vb2X2XM+Xw7stNSslvanzt3jnLlyim4pXzq9/zHpK99icZRX4L8+Z6fAPeqlkxoVgZNVWXepyVksqxI95dsJSyTybCwsKB169ZMmjSJvXv38uzZMx4/fszvv/+Oubk53t7edOrUCT09PRwdHenZsyeLFy/m/PnzJCQkfJFxfSv+C010PoZsL++3IZPJqF27NqmpqRw9epQXL15QunRpqbnI62z3e0FauZbIlVQk0Z0QeJynM1oQ5jlWYV0BoKzGHXUbPC/nnbe6TCajWrVqLFmyhBcvXjB+/HjOnj2LtbU1LVu2ZOvWrSQlJeXZ8b40MpmM4sWL4+bmhre3NxEREQQEBODj4yPlPv/zzz+UKFECS0tL/tmxW9pWCEFa2EPIzECmoo6KgVnWPv/vp50e+RR5egqpYVmvvzwlgfTYSPyexwFZtSWpqakMHDhQajPu5OSEq6vrB4tuyPJE19XVzfFlb21tzcOHD9+5bc+ePenYsSOtWrVCCEFwcDDp6ekUKFCAPn368OB5GLLGIzEf5IlaoRJvXj1iz769S63ISCNq3xzUzctibmEJZE2hP3v2jNu3b5ORkcGAAQO4e/cuQUFBbN26laFDh1KtWrWvJrohq/GUi4sLe/bskXz3x44di6WlJePHj+fevXsK69+/f5/evXtTtmxZqY385s2b80X3fwSZTEa5cuUYNmwYhw8fJjIykr/++ovU1FQGDRqEsbExzs7OLF26lAcPHvCh8d5/g4rvqaEgqydJcnomUw/dYfOlJ59/Ul+Q/Ij3T8SH+vX+Wtf6u+lMl5SURGBgoEJ0/NatWxQtWjRHqkpuEc8fgbS0NHR1dUlMTPwuPVK/Nps2baJ///4kJia+dZ1Fixaxdu1a/Pz8gKx0huXLl7NkyRLs7e0ZNmwYhcpWodOqyznSrHLzq3+Tr9EWPT4+nj179rB582auXLlCq1atcHNzo379+j/U+2D69OkcO3aMEydOYGhoSGxsLD4+PtSuXZuHDx/SefBv+B7dobCNkro2Rs5j0CxeEYDUsIeEbx6DyEjNsX9T99nompdC7J/Mo5u+OZ7v3bs3K1eu/Kgx37lzBxcXF+7evauw3MfHh99//52zZ8++c3shBO7u7ly/fp0qVaqwfft2EhISKF++PEalKnJbFEGlWAWU1DTIiAmXIt5aNrVIunuWQh7zSA2+kyPi/cp7BYm3fCjsMY/EA9OJCQnCwsKCe/fu/RCFhjdu3GDDhg14enpiYWFBnTp1uH37NpcvX+bXX39l4MCBP+QsTz55x+tN45SVlTEyMqJixYo0btyY69evc+zYMdTU1KRo+NvSUr51Gu2X5Mf59M/nvbyrq5lNYV3aVfz+ChC0tLSoWrWqQr5vRkYGd+/elcT4zJkz8ff3R0tLK4cYL168+HefN6impoaxsTEhISFSodh/GWtra/T09OjVqxdArnnDT548UWixbmRkxG+//caoUaPYunUrY8aMIb5CJ+Rm5XhXe/C3kZKRydJTDz+4sPhT0NXVpUuXLnTp0oWwsDC2bdvGhAkTCA4OpmPHjri5ueHo6PhN3r9CCNLS0khJSSE5OVnh55vLihYtSnBwMG3btiU1NUs4r169mn379pGSkkJoTNYNlIp+IdTNy5H84BLylASSH1yRhLd6IWvM+iwn6e45MlMS0ChqS+TuaYiMVJS1CpAulGk1dhlVuM/t27cpVqwYZ86cYcuWLZ/Ure5tXe6sra159OhRjmshl8vJyMggPT2djIwMMjIymDJlCra2tpQoUYIpU6bw+++/c/36dbh+HQAlbX1M2v2Osua/Vnh61TuQ9OAiMWc9pXPPJjnIn3jfAxi1HoWKgRlKalm2lH369PkhRDdkFazOnj2bunXrMn78eBYvXiylA1WqVOm774KYz9ejRYsWFC9enKNHj3L48GFSUlI4efIkQghu377NsWPHWLNmDd27d8fW1lYS4lWqVEFVVZUlpx6SkvHxohvy5vM9PT39i6XB5ke88/khEELw9OnTHHnj8fHxOfLGy5Qp893ljdesWZNp06YpiMn/KlFRUVhbWxMdHY1MJkNfX1+KotatW5czZ87g7OxMamoqenp61KtXj9mzZ2Nm9v+0hf8LVaPGfYm5spfM5Hi0SlfHsFE/lFTVc414pzy/RcyZTaRHBCFTVUejeEUKNerF5T+d0VWTMWDAAPbv3090dDQmJiY4ODiwb98+hBBMmDCBTZs2ERERgYGBAeXLl2fLli2SK8vHcu/ePbZs2cLmzZtRUVGhQ4cOtG7dmsKFC+cqhN8miD/nuZSUFFRUVNDU1ERDQwMNDQ3p99eXqauro6amRnp6OocPH0Yul5Oenk6HDh2wsrJCRUWFDadu8fycl5TjnfLsBuFbxgEyCnf/GzVTK4Q8E2RK0muXEOjNy0N/o1zAhCL91yCTyShCFI3Ug8jIyCA2NpY1a9aQnJxMq1atMDU1VRDFuf3++rLIyEhevXqFmZlZjnUjIiLQ1dVVWKakpISKigoqKiqoqqqioqKCXC4nPj4eAAMDAwwNDUlNTSVWrwSxD3yRJ8WgaV0Zw4Z9pYi3+dCtRJ/eSIL/IbTK1CLpzlnpfRh1cAFJd86gYVH+/+/Jm4i0ZGxtbenduzdDhw791H+pr0JGRgbbtm1j1qxZCCEYPXo0rq6uJCQksG3bNjZs2MCTJ0/o3LkzHh4e+Wkm/1GyI95eXl44Ozuzf/9+WrVqReHChXnx4oX0GRAUFISlpSW//fYbU6dOpVy5cqipqXH79m1SUlJQM7ZE3bI8CQFHUSlgjFHLkSTdv0Cc736UNXQx/GWAdHMbvLQHmXER6NftRuItHzJiI9AqXgH/ozspaZH1vXHu3Dl+++03rl+/jqamJr/88guzZ8+mYMGCPHnyRCqKX7ZsGZMnT6Z06dL4+Ph8kWuUH/HO54cg29LL0tISZ2dnaXlUVJQkxo8ePcqMGTN4+vQptra2CmLc3t5eshn7FlhYWLzTku2/RMGCBZHJZERFReWISgYGBtKwYUPS09NxdnYmLCyMLVu2EBgYiJ+fn8INVfT5bWhYOZH86CqJgd4oqWtj2KBXjuOlRT4hfOsEZMqqaJaoRGbCKxJvHCc0LoIdrRxReXCK1atXU6ZMGZo2bcqLFy84c+YM169f58yZM0yfPh0TExPq1atHTEwMly9f5u+//0ZTU5OEhASSk5NJSkqSfr4udlNTU0lOTpaiy2lpaaSmppKWlkZaWhqZmZlMmzaNv/76C2VlZTQ0NNDW1kZNTQ0VFRWUlZWlh5KSEkpKSigrKyOTyXI8ssmOpcjlcoQQqKqqoqysjJaWFpmZmcjlcjIzMyXhmZGRQWJiIrGxsQoCVi6XKwhRFRUVKT3o9OnT+Pr6oqKiQpxKIYXrrVHMDg3LCqQ8CSD20k6MW48m/eVzIndPRd283P+j4ZcBGQb1uktjv+k5jWgdZTQ1NXnw4AHJyclSJCx7DK+P5V2/7969m0ePHjF58uQcz9euXZt169ZRoUIFaXlu9nadO3emWrVqNG7cmOrVqzN37lyaN2/O0G3+bFy1jOgTq5CnJefYTq96BxICvUm6c07xCSEQGWkkP7qqsPj27dsEBATk2M/3QlJSEmvWrGHu3LlYWFgwffp0mjZtKr1uBgYG9OvXj379+nHv3j02btxIixYtMDIywsPDg86dO3/SrEU+PzZr1qzh5MmTeHt7A9C2bdtc18tOu3N0dGT9+vUsXLiQIUOGkBb5FJmaJqoFzUkLe0DYP+NR1jFA3aw0KUH+vDz0N0UHKDqFxV7YhlbpGsjTUki8dxHXrj3wO32Emzdv0qBBA9TU1GjRogWhoaGsW7eOJ0+ecOLECYV9TJgwAWdnZwoVUvxcy0vyhXc+PzRGRkY0bNhQobNhYmKiQt74+vXruX37Nubm5jlSVb7WF0J+geW/yGQySpYsycOHD3Nc/+XLl5Oeno6enh5eXl6Sk8TNmzfx8fGhcePG0rqGTQaiVaoqSfcvEbn7LxJvnsxVeMf7H4bMDFRNS6CsrY+ytj6pL+6R9DSQcZOmEnNqPZCVF3z37l1JUDg6OkoiNiIigqNHj0r7/OuvvyTB9ro4zhZ3r4s9VVVVtLW10dfXR01NTYoiZ//MFsbh4eE8fvyYZ8+eYWZmRtmyZSlTpgyampofLDg/Rpy+73klJaUcgl5dXZ309HS2bt2KmZkZ48aNIzTgcY5rrle9IylPAki6e4702l1Q0tBBSUOHpDtnEfJM1ApZo1fdFa2SVbLeE/IM0jMFDx8+JDMzk0KFCvHrr78yadKkTyoqPHz4MGXKlKFMmTI5nrOxsSEiIiJHU6bXefnyJYcOHWLx4sWoqanx6tUrWrduTaNGjYhXLkDshSMAaFo65NhWRdcI3fJNiPc7oLDcqMUwjFoMA0AZOcpH/uJBwBXmz5//XUa7X758yeLFi1myZAk1atRg69atOSxA36R06dJMnTqVyZMn4+Pjw4YNG/jjjz+oW7cuHh4eNG/ePL/78X+EAwf+ff+rq6vj6Oj4jrX/Jdu6UqamgUnHv0h7cY/wf8YjUhMx7jIbFV0jns/vQGb8SzKTYlHW+jfVS7+WOwUqtZZck/zPHCUhIUFKZ8zuMWJqasqlS5fw8fHh3r17Cp8xO3bsoH79+nl0FXInX3jn89Ohra1NtWrVqFatmrQsPT1dIW98+vTpBAQEoK2tnUOMW1pa5nneraWlJVeuXMnTff7IZDubvP4aAdLNSbZgUlVVxcrKioiIiBwzBqpG5lk/C2blhcuT4xAZ6TmOlRkbDkDai3ukvVB0YyhdwpLZk88wdepUTp8+TUpKCgC1atVi/fr16OjoSC3Ds9MOKlWqxN69exX8ofOShIQE9uzZg6enJ6tWraJly5a4u7vToEGDb1qUKZPJCA0Nxc7Ojnnz5nHhwgVGjhzJguVraLjwoqK3brFyWIxVFJ6FPea/dd9qamrc87+M74XT7N27lwMHDnD06FE0NTVp3bo15cuX/6j/yYiIiFxFN3yYs8nmzZtp3rw5hoaGZGRkMGzYMLy8vDh69GjWjZJ2QXQdmlGgalsy46JybF+gegcSAo8hMtJy3b+KigpGOuq83dvn2/H06VPmzZvHpk2bcHFx4cyZM9jY2HzUPpSVlaWASHx8PDt37mTBggX06dOHjh074uHh8dn1DVEJqbk2y/rRmqn8rHh5edG6dWvOnTtHgwYN6NmzJ1paWtLza9asAbJukiHLQ79y5crSd4CKnglKquooafw7U61qWASZ0r92liItBV4T3v9+J5hLy0JCQqR9Znviv87Dhw8pV66c9PfrTa2+FPnCO5//BKqqqtjZ2WFnZ0eXLl2Af/PGs/PF161bx+DBg0lISMghxm1sbD4rb9zCwoLt27fn1en88LzNUtDS0hJAKjZLT0/n8eOsiOqbhanpUc9RNSxC+stgAJQ0CyBTyfkaKetldVHVreSsEBFPjwmjWl1HKlcuw5EjR8jIyODhw4cMHjwYb29vzp07h6urKytXrmTFihUEBQUxefJkNm7cyOrVq5k4ceLnX4hc0NHRwd3dHXd3d8LDw9m2bRu///47Hh4euLq64u7ujpOT01cvykxISGDRokUkJCTg4+ODv78/1tbWANQpZfxZHXTrlTbG3MQAc2dnnJ2dycjI4MKFC+zdu5e2bduSmZlJq1atcHZ2platWu/9X4yMjHxrPUWJEiUIDAx867ZCCFavXs2iRYuALJE8b9486bFu3Trsfl3EhafxIFNCRd80x02Gio4hxUbuzm33yMg63+VTzrzzHL42N27cYNasWRw6dIiePXty8+ZNqa7ic9DV1aV79+50796dx48fs2nTJlxdXdHQ0KBbt264u7t/1E3s9ecxLDn1kNP3I4E3m2WFMf/4/R+qmcqPgBCChIQEXr16pfCIjo7O8XdYWBgAvXr1ws3NTUqpE0Lw559/oqysTGZmJkFBQZQqVYr09Kxgia2tLX/99RenTp1i7NixIMuZ/vW66M6N9KjnaBavSPrL59KyIkWKSN8rw4cPV2jIFhQURPHixRVmo79GoXO+8M7nP8vreeMuLi7S8sjISCkyfvjwYaZNm8azZ8+wtbVVEOP29vbvnK5+ndctlvLJijq+PhWZTa9evVi2bBlnz56lU6dOPH36lIiICMqWLUvdunUV1n11dDFJDy+T/DBrJkG7XL1cj6VbvgkJAUeJv7aPjJiwLBeNl8GkBt/BptMD/vnnH2bOnImTkxM6OjrcuHEDAH19fS5cuEC3bt2oVq0ahoaGnD9/Xnrua2BqasrgwYMZPHgwDx48wNPTk86dOyOTyaROmdni90uRnp7O6tWrmTx5MvXr1+f69essWLCACRMmsHXrVmQyGQPqWnP2QdQnWX8pyTPpV1vRDzs7F7t27drMmTOHW7dusXfvXsaMGcPjx49p2rQpzs7ONGnSBF1d3Rz7jIiIeKv9qLW1NV5eXm8dz+XLl0lJSaFOnTo5nhs2bBg+Pj7smz4AU7fpfIrngoaqMr/W/bKv2YcihODs2bPMnDkTPz8/hgwZwqJFi77Y+9vKyoo//viD33//nXPnzrF+/XpsbW2pWrUqHh4etG7dGk1Nzbdu/75mKtkWusduh3PmftQP0Uzla5KRkUFMTMwHCeg3/9bQ0MDQ0FAqNH79UbBgQUqWLCl9RoaHh1OhQgVKlSrFjRs3OHfuHFpaWvj4+NCmTRvOnz/Ps2fP0NTUlD5vixQpQpUqVbhz5w7wKV5VEHN2M2kRQaQ8y9pnhVqN0dHRoU+fPqxatYq///6bx48fY2RkxJ07d7hw4QJy+Yc3Hswr8oV3Pvm8gbGxMY0aNaJRo0bSsoSEBG7cuCFFx9euXSvZnr0uxh0cHHL1sS1WrBjPnz9HLpfnWsj1X+NtEW9VVVXMzMwoXrw4hw4dQktLi44dOzJ79mzU1NSkVBAAvRqdiLu6B5GZjna5BujX7pLrsdRMrTDt+Bcx57aQ+vwWQp6Bip4phtXb065iUe6rlsbIyIhDhw4RHx9P4cKF+e2332jRogUPHz6kZMmSnDhxgpiYGIyMjOjXrx99+vT5YtfmbZQsWZJJkybxxx9/cPXqVTZv3kyNGjWkZjeurq556nUvhGD37t2MHz8ec3NzDh48SMWKWS4CM2bMwMnJCU9PT9zd3Slvrs+EZjYf3UFXQ0UJtduHmDthB2vWrMk1/ze7OUe5cuUkO8b9+/ezatUqevToQc2aNXF2dqZly5ZS5DQiIuKt9RvvSzVZvXo1vXr1yjGjkJaWxoQJEwgICMDe3BzduEAe6JRDrvThM2FZHYNtvrm/sFwuZ9++fcycOZOoqChGjRrFrl27vlqTHplMRq1atahVqxaLFi3Cy8uLtWvXMmDAANq1a4eHhwfVqlVTeA02X3pCn46tSH56g4LNhqJj3/Ct+xcCQk9upMuUf1jRrC1nD+78Gqf1VRBCkJycnEMc5yaY31yWmJiIvr6+JJjfFNHFixfH0dFRYZmBgQEGBgYfnJs/YsQIAE6cOMGJEyfQ19enZs2a/Pnnn5iYmLBo0SI8PDykVM/u3buzdu1aafu4uDjpPD8W/ZqdSbh5EnlSLNqlqrJtY9Z+y5cvz/Hjx5k0aRJnzpwhLS0NKyurrMj6NyDfTjCffD6R7Lzx1+0NAwIC0NHRySHGLSwsKFy4MH5+fnkyffuj8+rVK4oXL05MTIzCl+uSJUvw8/OT8v+yiY2NZfny5SxYsECayuw4dy+XIpX5lA8wmQya2Jp+UR/vr0FGRgbHjx9n8+bNHDhwgOrVq+Pm5oazs/MHz8bkxtmzZxk9ejTJycnMnDmTxo0b5xCi/v7+NGnShKtXr0ppQJ/S3rmNvQkdO3YkNTWVnTt35hrBfhuxsbEcOXKEPXv2cOTIEWxsbGjdujUzZ87k7t27mJqa5tgmIyMDbW1t4uLickwrx8fHU6xYMe7cuaPgavD48WM6duyIqakp69atQ0NDAxsbGzIsq6JRzQ2Zito734cyBBqqKt88ApuamoqnpyezZ89GR0eHMWPG4OLi8s428F+T4OBg7OzsiImJyfGcZe/FxD65QUZ0KNq2dVA3K/3OfcWc9ST2/D8UsG/I2YM7vvnNzpvI5XJiY2M/KOL85jLIcod6m4DOLSptYGBAgQIFvtvAT0REBHPmzGH16tV07tyZOHtXzj6J+6D0tWw7QdNO09CwsP/uP9/zI9755POJvJ433rVrVyDrLv3JkyeSEF+zZg3+/v4kJSWRmZnJ8OHDad68uZQ3/iN1MMxLDA0NUVFRITIyUiFKe+bMGZo1ayb9HRYWxt9//83KlStp2rQpR48epXz5LB/kUkphXEg3Qqb68Tl5qkp8N9P9n4OKigq//PILv/zyC4mJiezdu5fNmzczYMAAWrRogZubG40aNfrg99mdO3cYO3YsAQEB/PXXX7i5ub31i9rBwYERI0bg4eHBiRMnUFZWxr2qJfZF9T+6g+7u3bv59ddfqVu3LocOHcpVMOeGnp4erq6uuLq6kpaWxunTp/Hy8iImJobatWvTunVrWrduTdWqVSVxqaKigrm5OU+ePKF0aUXxtnXrVurWrasgurdt28agQYP47bffGDRoEDKZDB8fH1JSUoi+6EXfupWQ2zTI9XzJTEdZWZlGZQt/047BcXFxrFy5kgULFlC2bFmWLFlCvXr1vrvmY0WLFkVPT4+YmBhq1KhBXFwcDx48QMu6MhlqOhRwbPnR+8wU4os2y0pNTZVE8YdEobP/jo2NRUdH562C2czMjHLlyuUqqt+VjvOjERERwezZs1mzZg2dO3cmMDCQokWLcv15DFc/sXOlhsr3k86VG/kR73zy+QpERETQrl07ihQpghACf39/goODc80bf73y+2ematWqzJ07V6oiF0JQuHBhLl68iFwuZ86cOWzbtg03NzdGjBghFchIDXSMjBi6eBebbyV+VHqDmhIknN3IX92a0KNHjzw/r++BiIgItm/fzubNmwkKCsLV1RU3NzcqV66cq9h68eIFf/zxB3v27GHMmDEMHDjwg9IOMjMzqV+/Ps2bN2f06NEKz31sB10hhFS8euTIEUqWLPnJ525ra8vRo0fZs2cPe/fuJTw8nJYtW9K6dWsaNmyIi4sLgwYNonnz5grbVqlShT/++INmzZqRlJTEkCFDOH36NFu3bpXSbIKDg6lcuTKOjo5oaGhw+vRpdu7cSdmKVaTzjU1J54bvZTRTX7F7zmiMdL9OCsebhIeHSzeujRo1YvTo0Tg45LRA/J54swFLyMs46sw9Q4aQEeY5ltTnN6VUk+Qgf2JOrSf9VTAoKaOqXzjLprJ0dSnirWVTCxV1TTIfnqdQoUIsX75cwX4WchYPfoyATktL++CI8+t/6+np/WcDL6AouN3c3BgzZozUuTibrBm096evvR7xNrCuwIRmZb7r3P7/7queTz5fERMTE6pWrYqhoaGUV5aQkEBgYCD+/v74+vqyevVq7ty5g4WFRY5UlU/tkvg9k53nnS28s3O+x48fj7e3N/379+fu3bsKEXEhBNOmTWPlypUcPXqUUqVKYXHpCX8dvENyWgayd0yjvp7e4NTlT1q2bMnt27eZOXPmdzPVnleYmJgwcOBABg4cyMOHD9myZQtdu3ZFLpdLRZklS5YkLi6OWbNmsWzZMnr27Mn9+/cxMDD44OMoKyuzceNGnJycaNy4MRUqVJCeK6ijTt83iibfhUwm448//sDMzIzatWuzd+9eKleu/DGnDWR9oZuamuLo6IijoyNTpkzh8ePH7N27l7lz5+Lu7o6RkRFbtmyhatWq0v9WYGAgL168oEmTJty4cYOOHTtSsWJFfH19pfSX1NRU2rdvT6tWrdi/fz+3bt3i2rVrtG/fnjNnztC3dlYEfcaMGdy4uIujZ86gqfn1RffDhw+ZM2cO27dvp1OnTly5cgUrK6uvPo7PYc2aNZw6dYrA4FhePo9Gr37vHOu8PLSAzIRotG3rgJIy6ZFPSIt8ilbp6tI6SXfPoWlhj6aeMY8ePaJ169bUq1cv1+LBtwnm14sH31xHW1v7u5s5+J4JDw9n9uzZrF27Fjc3NynCnRvZ4vl96WtFf12r8Pn+PYtuyBfe+eTz1bCwsJAquCHLNq569epUr/7vl0R6ejp37tyRUlUOHDhAQEAABQoUyCHGixUr9kN/4FtbW/PgwQOEEJw+fZqBAwcSFxeHk5MTK1euzJHrK5fLGTFiBMePH+f8+fNSrrx7VUue+J1h+81YUgtaf3B6w+XLl2nXrh2tW7dmy5YtUuOGnw1ra2t+//13Jk6cyLVr1/D09KRWrVqoq6vz6tUrmjVrhr+/P8WKFfuk/VtYWDBv3jzc3Ny4du3aZ0+D9+7dm0KFCtG8eXM2btxI06ZNP2r73AorraysGDZsGMOGDePly5cMGjSIS5cuYWVlhYODA61btyYgIIDu3buzevVqfvvtN+bMmYOHh4fCfoYPH46xsTFnzpzh77//Rl9fn4YNGzJjxgyaNWvGxYsXuXTpEosXL+by5ctfPSXg2rVrzJw5k1OnTtGvX78cN64/Em+6HuUmvEVmJjIVNTRLVkHN2BIVQzPeVGeqRuYYd/wLs7g7XFo2mqSkJDp16oSlpaWCuM5v7PNlCQsLY/bs2axbtw53d3du3LhBkSJF3rvdp6avfc/kC+988vlKWFpa5mqh9zqqqqrY29tjb28vfenL5XKFvPFVq1bh7+9PSkpKDr/x0qVL/zDTlyVKlGD58uVUq1aN6OhoDA0NmT17NgMGDMixblpaGj169ODp06ecOXMmR1R23/rFTPv9d6rVrf/B6Q2GhoYcPXqUQYMGUaNGDfbv3y+ls/yMyGQyHB0defz4Mfv27aNgwYLY29tz9OhRYmNjcXd3x9nZGR0dnffv7A3c3d05cOAA48aNY8GCBZ891pYtW7Jv3z5cXFyYMWMG3bp1++Bt36wbeJOCBQvSqVMnYmJiuHnzJidOnGDnzp1s2rQJHR0dNDU1WbZsWY4W1xs3bsTb25t27doBii2wu3fvTlBQEA0bNiQsLIwDBw58kKjIC4QQeHt7M3PmTO7fv8/w4cNZt27dJ72O3xPZqSY9Nlzl5N2IXNcp+MsAon3WErVnBpDl5W/YqG9WBPz/qJlaIZPJKFGuIpf+v6xGjRo/9f/698TrgrtLly6f5A9vX1Sf5e5OH52+9r3yY3xD55PPT8Cnto1XUlLCysoKKysrhS/78PBwyW98//79TJ48mZCQEMqWLasgxu3s7L6rvPG0tDS2bNnCpBlzSTAuS+22nShjXJiTRw7wytSRlwmpCh+iiYmJtG3bFjU1NY4dO5Yjiujv709YWBhNmzZFWVn5o9IbVFVVWbZsGYsXL6ZatWrs2LGDmjVr5tm5fk/4+PgwevRoqUFMdlvkxMRE9u3bh6enJwMHDqRZs2a4ubnRuHHjD24aJZPJWLZsGeXLl6d58+YKVpyfSrVq1Th16hRNmzYlJCSE8ePHf9AMz7usBLPJthTU1NSkRYsW+Pr6oqamRpMmTTA3N2fChAkMGzaMVq1a0bp1awwMDBgxYgRr1qyhR48e+Pv75xjLwIEDmT9/PmXKlMHJ6cu7KWRkZLBz505mzZpFamoqo0ePplOnTj9d5LaAxttliqaVE1qlqpGZHEfK0xtE7ZlOzJlNCsIbWVYama7Gz3VdvnfCwsKYNWsW69ev/2TB/SYfm772vZIvvPPJ5ythYWHBs2fPEELkSYqIqakpTZo0oUmTJtKy+Ph4KW/86tWrrFy5krt372JpaakgxitUqPDV88YTEhJYvXo1c9fvpEDV9qi0mY52Whp+r1TgVSSy4lXwvB7N5usnpc5zRbUyad68OWXKlGHVqlW5RvNXrFhB7969PzlPWyaTMWjQIEqVKkWbNm2YNWvWR0VYv3du3LjBmDFjuHv3LlOnTsXV1VXBqURbW5tOnTrRqVMnIiMj2bFjB1OnTqV79+506NABd3d3qlSp8t73rKGhIevWraNbt24EBgZiaGj42WO3sbHh/PnzNGvWjBcvXrBw4cL3vs7vi3gDFC9enKdPn5KWlsb8+fOZOnUqw4YNY+bMmQDMmzePu3fvsmfPHiZMmICfnx9VqlRh9OjRjBo1CnNzc4X9paWl0b59e/r378/ly5cZPXo0c+bM+byTfwvJycmsW7eOuXPnUrhwYf7880+aN2/+3drEfQ7379/nsf85RGZRZCo5hXPousEo65mgUsCYzPgoAJTUc9poaqgoUcr0x54B+FF4XXB37do1zzqg/kzku5rkk89XpGDBgty9e/e9Ebm8JC0tTSFv3N/fn+vXr6Onp5cjb9zc3DzP88ajoqJYtGgRS5cuxbZVX8IKVyNNniMVUwGZDNSUZch9d9LGzpgZM2bkOq5s3+Vbt27lyYf7nTt3aNmyJW3atGH69Ok/dNHl8+fPmThxIocPH2b8+PH069fvo9ohP378mC1btrB582YyMjLo3Lkzbm5uOSz43mTYsGEEBwezffv2PHsvxcbG0qZNG/T19dm8efM7c6f79etH+fLl6d+//zv3WbRoUYoXL05ycjJPnz4lJCQkR7RYLpfTsmVLihQpQnJyMvv370cul1OtWjVat25Nq1atKFKkCH379iU8PFyyMqxevTqDBg3KNW3qU3n16hVLly5l8eLF0k1AdmHyz0R2gKJMmTK8fPmS9l16cFS9JulycriavPJeQfKjq2QmvAJlFdRMS2BYvxdqhUpIriba5RpQxHkEh/tWpIR5lk1kUFBQfqpJHhMaGsqsWbPYsGEDXbt2ZfTo0fmC+y3kC+988vmKVKxYkRUrVlCpUqVvOg65XE5QUJCCGPf39yctLS1H3nipUqU+KW/82bNnzJ07l02bNtGuXTtsWvRm1bWod1pDRR2YT+LNE+jV6IR+LTdUkDOptd1bq9RXrlzJ4cOH39kCPJv169fTvXt36tSpw6lTp9663suXL2nXrh26urp4enp+VEOX74Ho6GhmzJjB6tWr6devH6NHj0ZPT++T9yeEwM/PD09PT/755x+KFi2Km5sbHTt2VPC7ziYlJQUnJydGjx4t+dvnBampqXTr1o3g4GD27dv3VveVtm3b0qlTJykXOze8vb1p0aKFgsXn7Nmzc6w3efJkvL298fT0xNHRkRMnTlC8eHGOHj3K3r17OXToEDo6OqSkpLB3715pZuDx48fUrFmTlStX0qJFi8867+fPnzN//nzWr19P69atGTVqFLa2tp+1z+8NIQRXr15lzZo17Nixg2rVqtGzZ09atGiBmpoafTZdw/tO+Ac1U3mT772Zyo9OaGgoM2fOZOPGjXh4eDB69Gipg2w+ufPzzU3lk893TLZH7bdGSUmJEiVK0K5dO6ZOncqhQ4cIDQ1FS0uLkydPEh4ezt69e2ndujU6OjrIZDLU1dVZsWIFV65cITk5+a37vnXrFh4eHjg4OKCurs7NmzcZMHEWq669/Ci/bYAMlJh66C6BwTE5nhNCsHz5cvr27fuxp/9OChYsyNGjRylUqBA1atT4pLz8b0FKSgpz586ldOnSvHr1isDAQKZOnfpZohv+LcqcN28ewcHBTJs2jYCAAMqUKUOTJk3YuHEj8fHx0voaGhp4enoyYsSIPL126urqeHp6UrlyZWrVqsXz589zXS8iIuKtqSbp6emMGzeO7t2707BhQ6pVq8bGjRvp2bNnjnUPHz7MihUr2L59O6NGjaJXr17Y29ujq6tLu3bt2LRpE5s3byY+Pp5mzZrRsWNHrK2tGT58OM+fP2fHjh10794dX1/fTzrf27dv061bN8qXL49MJiMwMJB169b9VKI7KiqK+fPnY29vT+fOnSXnp4MHD9KmTRtpBmJAXWs0VD5t9ul7b6byoxIaGsrQoUMpW7YsSkpK3Lp1i/nz5+eL7g8gX3jnk89X5FMLLL8W2akVbdu2Zfv27Tx48IDdu3dLz12+fJm+fftSsGBBypYti7u7O3PnzuXkyZMcPXqU1q1b06BBA2xsbHj06BGzZs3CzMyMJacekpLx8R3IAFIyMll66mGO5deuXSM6OprGjRt/+gm/BTU1NVasWEHPnj2pXr0658+fz/Nj5BVyuZzNmzdjY2PD6dOnOXXqFKtWrfoirhrKyso0atSI9evXExISQo8ePdi5cydFixalU6dOHDhwgPT0dMqXL8+YMWPo0qULmZmf9rrnhpKSEnPnzqV79+7UqFGDmzdv5ljnbcWVT548oXbt2ly/fh0/Pz9q166Nt7c3JUuWxMbGRmHdoKAgunXrxrZt2/D19cXX15fff/9dYZ379+/TrVs39uzZw7p16wgKCmLXrl3o6ekxbNgwnJ2dKVeuHI0bN+bu3bsffI7nz5+nVatW1K9fn5IlS/Lo0SPmzp37Vq/jH43MzEyOHDlC+/btsba2xs/Pj0WLFnH//n3Gjx+f6/u2vLk+E5rZoKn6cZJFU1WJCc1sfgiLuR+FFy9eMGTIEElw3759m3nz5uUL7o9B5JNPPl+NBQsWiIEDB37rYbwVCwsLAQgvLy9pmY+PjwCEnp6eEEKITp06iSJFighVVVWhrq4uChYsKLS1tYVMJhMGBgaicePGwtHRUZiYmAhtbW1RqUpVUbTrLGEx9oCwGHtAmI/YKfRqdBIqhkWFHJrUFQABAABJREFUTEVNKOsWFIa/DBQWYw8I7XINso5Vo5OwGHtA6FZyFoBQL1xSPHoeJo4dOyYqVqwotLS0hKqqqjAzMxO7du2SxrpmzRphb28vtLW1hbW1tZg6dapIT08XQgixbt06AYg6dep81DU5fPiwMDY2FuvXr//cy5vnHD16VFSoUEFUqVJFnD59+puNIzIyUixdulTUqFFDGBkZif79+4uzZ8+KunXriunTp3+RY3p6egoTE5Mc521gYCCioqIUlu3cuVMYGxuLOXPmiMzMTGmZqamp2LBhg8K6SUlJwsHBQfz9998iLi5OFCtWTBw/flxhnejoaFG6dGmxcuXKt47vyZMnYuHChaJkyZJCSUlJ/PLLL2LNmjUiPDw8x7qZmZli3759okaNGsLKykosXbpUJCUlfdT1+N55/PixmDhxojA3NxeOjo5i6dKlIjo6+qP2selikLCZeFhYjjsgfZ7k9ig2ep8o/dshseli0Bc5l/8iISEhYvDgwcLAwEAMHz5chIaGfush/bDkC+988vmKeHl5iRYtWnzrYbyVbOHdokULMWTIEDFkyBDRtm1bBeFdvXp10bFjR9GwYUOhra0tAGFmZiZSU1PFvXv3ROnSpQUgDAwMhIaGhpApqwiZipow671cWIw9ILRs6whAKGnoCG27hkLTurIoULlNDuGtV7OzAIRaoZLCeuR2sfz0Q1GkSBGhrKwsXF1dhZqamrC3txd//vmnEEKI5cuXC0CYm5sLDw8PaRyTJk0SQny68BZCiFu3bgkrKysxevRokZGRkVeX+5Px8/MTDRs2FCVLlhQ7duwQcrn8Ww9J4vHjx+Kvv/4SZcqUEebm5kJLS0vs3LnzixzL29tbGBsbS/tPS0sTKioqkrhOSkoS/fr1E1ZWVuLKlSsK2x4+fFgoKyuLxMREaZlcLhfdunUTnTp1EnK5XAwZMkR4eHgobJeeni6aNGkiBg8e/EFjlMvlolevXqJs2bKibdu2Qk9PT9SoUUPMmjVL3Lx5U6xfv17Y2toKBwcHsXXrVulG8WcgOTlZbNmyRTRo0EAULFhQDB48WAQEBHzWPq8/jxZ9N10VpX47JKzHKwru0r8dEqV+OySchq0Qvcf+lUdn8d8mODhYDBo0KF9w5yH5wjuffL4i/v7+ws7O7lsP461kC+/cHnp6eiIpKUlMnTpVGBoaCnNzc9GyZUvp+ZCQEHHlyhUBCF1dXUm4FyxWSgCiQNV2ouhgT2n9wt3+/jdCNWqPgvBWMSwiiW7zoVuFxdgDYuhWfymK3rNnT9GkSRORmZkpCWFbW1sBiLZt24ohQ4YINzc3AQhTU1MhxOcJbyGyorp16tQRrVq1EvHx8Xl1yT+KoKAg4ebmJgoVKiSWLFki0tLSvsk4PgS5XC78/PxE06ZNhYqKiqhQoYKYO3euePHiRZ4ex8/PT5iZmYlFixaJFy9eSK/3rVu3RLly5UTHjh1FbGxsju3Gjx8vlJWVJZEuRNbNW7ly5URCQoK4fPmyMDU1FZGRkQrbDRs2TDRq1OijBHJGRoZo2bKl6N69u0hOTha7du0S1apVE0pKSkJLS0u4urqKixcvKozlR8bPz08MGDBAFCxYUDRq1Ehs3bpVJCcn5+kxouJTRO9524XjwIWix/orYuhWf7H89EMRFZ8inj9/LgwNDUVwcHCeHvO/RHBwsBg4cKAwMDAQI0aMEGFhYd96SD8N+cI7n3y+Iq9evRIFChT4riKUr/OuVBMNDQ1RsGBBoaysnKswDwgIENu3b3+rcNcqXV0U8piX9beySq5TxNnCO/thUL+X9FzV0etFly5dhImJyb/PGxiIdevWCSGE0NLSeuux4+PjP1t4CyFEamqq6NWrl7C3txdPnjz5vIv9EURFRYlhw4YJQ0ND8ccff4i4uLivduy8wNXVVTg7O4tu3boJfX190bBhQ7Fu3bpcBfGn8PjxY1GqVCnRo0cPUa5cObF69WphZGQkVq9enev/WkZGhihWrJiCOLt06ZIwNjYW9+7dE2lpaaJ8+fJi06ZNCtutWbNGlCxZUrx69eqjx5iQkCDs7e1FnTp1hJGRkWjfvr24cuWKuHTpkhg3bpywtbUVhQsXFn369BGHDh0SKSkpn3YxvhGvXr0SixcvFg4ODqJYsWLijz/++OL/I9OnTxejRo3K9bkxY8aIXr16fdHj/4y8LrhHjhyZL7i/APnFlfnk8xXR19dHCEFMTMy3HsoH8eLFC5YvXw5kFUX16tWLzMxM7OzsiImJITw8XFpXCCF545qZmZGSkoIQgiFb/TAfsQvDRv1R0TPNWjkzg7Twx/9uK1cswNMsVQ2ZmibRPmtJvJtV2KilkuU44ujoiKamJlZWVkRHR9OjRw+0tbVJT08HwNHRkW7dujFq1Chmz57N7NmzOXv2LEFBQUBWMeKnoqamxsqVK+nevTvVqlXj4sWLn7yvDyE5OZmZM2dSunRpkpOTuXXrFpMmTfrhLA6XLVuGr68vHTt25MWLF/Tp0wcvLy/Mzc1xdXVl3759pKWlffL+ixcvzvnz5zl37hwPHz5k/vz5nD59mp49e+bqJX78+HGMjIywsbHh4cOHREZG0r59e1atWkWpUqWYN28epqamuLm5SducO3eOsWPHvtPK8G08fvyYUaNG8ezZM3x9fRk7dizbt2+nUqVKVKlShWnTpnHr1i1Onz5NyZIlmTZtGqamprRv3x5PT0+io6M/+dp8SeRyOSdPnsTNzY3ixYtz5swZZsyYwePHj5k0aRIWFhZf9PghISFvLSIeM2YMe/bs4c6dO190DD8LwcHBDBw4EDs7OzQ0NLhz5w6zZ8/G1NT0Ww/t5+MbC/988vnPYWdnJ/z9/b/1MHIlO+K9ZMkS0atXL2FgYKCQ471lyxYp+u3h4SHKly8vRZX9/f1FZmamqFatmgCEnZ2d6Nu3ryhfo6FQ0tARBZsNfSPHW1do2zcSmqWqiQJV2ubI8TZxnSxQUhYoqwrTDn8K41odhbq6utDS0hIlSpQQ9erVE4CoWLGiiI+PF5MnT86KrGtpierVqwsHBwdhaGgoTExMRJMmTUSxYsUEIGQymdDR0RFWVlaiSpUqomXLlqJHjx5i7NixYu7cuWLTpk3iyJEjws/PTzx//vytkceDBw8KY2NjsXHjxjx/HTIyMsTatWtF0aJFRZs2bcTdu3fz/BhfmxMnTggzMzOF1I2oqCixfPlyUbNmTWFkZCT69esnzp49+0kpF1euXBHGxsZCS0tLNGr0P/buO67G9g/g+Oc0NBRllREhyQxlr6zHKHuFSPbeez6PzeOxN9l77z2KyI4UKaMUQiil3bl/f/TrPHoKjdPier9eXjjnvq/7e07J91z39/pezX5YDtSpUydp7dq1Uq9evaQNGzZIjRs3lqZMmSJJkiQ9e/ZMyp8/v/T8+XPF8b6+vpKhoaF09uzZVMV0//59qWvXrlL+/PmlKVOmSIGBgZKHh4dUsGBBycnJ6Yfnvnv3TnJ0dJTatGkj6erqSo0bN5ZWrFgh+fn5pSqGjODv7y/Nnj1bKlWqlFSpUiVp2bJlSRa0ZoZ27dpJBw4c+O7zf//9t9SuXbtMjCjn8ff3l4YOHSrp6+tL48ePT3bxr6BcIvEWhExmY2OTqJQjOylcuLCiRnvmzJlSUFBQoq4msbGxUt++fSVdXV2paNGi0t69exMl3pIkSe/fv5cGDRoklShRQtLQ0JCKGRlJuhWspCL91/7b1aSObXwdt6r6D7ua5G81Mj5Jz6UlnXNykdq3by/JZDJJRUVFkslkUq5cuaQ//vhDWrlypXTv3j1pw4YNkrm5uZQ7d24pf/78Uv369RXlAt+WmoSEhEg+Pj7SjRs3pKNHj0obN26U5s6dK40aNUrq3r271KxZM8nc3FwqUqSIpK6uLuXJk0cyMTGRateuLbVt21bq16+fNGXKFGnixIlSwYIFJVtbW+n+/fvSmzdv0lV3LZfLpZMnT0oVK1aU6tatK12/fl0ZX9ZsY+zYsVKHDh2SLf94+fKlNG/ePKl8+fKSsbGxNGXKFMnT0/OnY8bFxUmLFy+WChYsKPXu3VsaNmyY1KdPH8nS0jLZJOLdu3eSnp6eFBwcLM2aNUuqVauW1LRpUyk2NlaSy+VS06ZNpUWLFimODw0NlSpXriwtXbo0Ra9RLpdLFy9elJo1ayYVLVpUWrx4cZLSoIsXL0qFChWSHj9+nKIxw8LCpCNHjki9e/eWChQoIFWpUkX6888/JTc3t0wrW4uKipIOHDggtWzZUtLX15cGDRok3blzJ0vL5qpXry7duHHju89HRERIRkZGv9y/I2V49eqVNGTIEClfvnwi4c5kYudKQchkw4cPx8TEhJEjR2Z1KEB8icjly5dZsGABT58+ZezYsfTt2xcdHR2lXUNZO88tX76cmzdvsmfPHiRJ4uXLl7i4uCh+vX79mlq1alGvXj3q1atHzZo10dbWTlfs0v9Lgz58+MD79++T/B4QEMDly5eRJAkNDQ0+f/6Mrq4uBQsWpFChQj/9PX/+/KipqXHnzh0mTJhAYGAgCxYsoE2bNkrbcj27iIqKonr16owZM4bevXsne4wkSTx8+JBdu3axe/duRclHt27dkmxB/f79e3r37s3nz5/Zs2cPGzduREtLi6lTpzJz5kx2797NuXPnKF26tOKcxYsX4+npyZYtWxg9ejQbNmzAz8+PAgUKsGPHDpYsWcKdO3dQU1NDLpfTsWNH8uXLx6ZNm3749YiLi+Pw4cMsXLiQr1+/Mn78eHr06IGGhkayx2/dupVZs2bh6uqaqtv5sbGx3Lhxg2PHjnH06FHi4uJo27Ytbdu2pX79+qirq6d4rJTw9PTE0dGRnTt3Ur58efr27UvHjh3T/e9KGYoWLYqrqyvFixf/7jFbt27F0dGRq1ev/nL/ntLC39+f+fPns3fvXvr378+4ceOS7XsvZByReAtCJlu8eDGvX79m6dKlWRpHXFwcR48eZcGCBXz9+pWJEyfSrVs3xW5xyvTQPxjbjTeJiEn9Zipa6qrsG1CLSkXzUqFCBdasWYOVlVWyxwYFBXHjxg1FIv7w4UMqVqyoSMTr1q373V0N0yM6OprBgwdz7949jh49iq6uriIxTy5Z//b3T58+oaqqilwup2TJklSqVAkDA4PvJuv58uVTbHSUEz169IjGjRtz69YtSpUq9cNj4+LicHZ2ZteuXRw5coRq1arRo0cPOnTowL179+jVqxc9e/Zk1qxZqKur079/f6pXr86AAQMAWL9+PX/99RfHjx/H0tISSZIoV64cjo6OqOXWo+3o+WgXMcXqj5bkIo4TO9ay/a+hNKlbA4Dp06fj5OTExYsXv5tAR0ZGsm3bNhYvXkzBggWZOHEirVu3RkXl50uoZs6cydmzZ7ly5UqaEllJkvD09FQk4S9evKBly5a0a9eO5s2bp3ktwJcvX9i3bx+Ojo74+/tjb29Pnz59MDHJPjtAxsbGoqWlRXh4+A8/bMTFxWFubs78+fNp3bp1JkaYvSQk3Pv27aN///6MHTtWJNxZRCTegpDJDh48yO7duxU7Qma2qKgodu7cyaJFi9DX12fy5MkpThTSY+dNX+aefpKqbePjd54rh10tY65du0b//v158uRJimeuIiIiuHPnjiIRv3HjBgYGBopEvF69epiYmChlJkySJJYuXco///zDwYMHqV279g+Pf//+PbNnz2bPnj3079+fDh068PXr10SJeXLJ+pcvX9DX16dQoUIpmlHX09PL8K9tai1ZsoTDhw/j7Oyc4g8RkZGRnDx5kp07d3L27FlkMhmTJk1i8uTJig+L7dq1w97envbt2yvOO3r0KAMGDGDHjh1oa2vTb+Js6vWfxaUngaiqqhL3zQbOKlIc6urqWJUtiEn0C1bPmsDt27eT/bAWHBzM2rVrWbFiBRYWFkycOJF69eql6ntJkiTs7e0JCwvjwIED6f5A9fr1a44fP87Ro0dxdXWlXr16tGvXjtatW/90Z0FJkrh+/TqOjo4cPXqURo0a0adPH1q0aIGamlq64soIr1+/xtLSkrdv3/702JMnTzJx4kTc3d1z9IfWtHj16pUi4R4wYIBIuLMBkXgLQia7c+cOgwYN4t69e5l63dDQUNavX8/SpUupXLkykyZNokGDBpl6+zU++fYiMjbuh2UnMhloqqkytZUZdrWMAbCzs8PCwoLRo0en+fpxcXF4enoqEvFr164RHR2dKBGvUqVKum7Xnzp1CgcHB5YuXZqoK0aCr1+/snTpUpYtW0b37t2ZPn16qv4jjI2NJSgo6Iez6N/+HhYWRoECBb6bmP/3sbx582b494RcLqdZs2Y0adKEKVOmpPi8V69e0b17d9TV1WnVqhUnT57E09OTjh07Ymdnx4QJE1i8eDF169ZNdN7169fp2LEjhvU6EVamObESIPv+hxEZII+JYnAtAyZ1SjzW69evWbZsGZs3b8ba2prx48dTqVKl1Lz8RKKjo2nevDlVq1ZlyZIlaR7nv0JCQjh79izHjh3jzJkzmJmZKUpSzMzMFF/jwMBAtm3bxubNm1FRUaFv37707Nkz23ezuH37NkOGDOHu3bs/PVaSJKysrBQz97+DhIR7//79ioS7QIECWR2WgEi8BSHTvX//nnLlyvHx48dMu96KFStYt24df/zxBxMmTKBKlSqZcu3kuAcEs8bpGZeffiAyIgIV9X9v4WuqqSABjcoWZIiVCZWL6QHxJSQmJia8ePGCfPnyKTWeV69eJaoTf/nyJTVq1FAk4rVq1Ur1LXsPDw/atGlDt27dmD17NioqKsTGxrJ582b++usv6tevz9y5cxPVHmeU6OhogoKCUpSkf/jwgcjISAoUKJCi2fSCBQuiq6ubpkTd398fCwsLTp8+jaWl5U+PP3r0KAMHDmTMmDGMHz9eMYvv5+fHnj172LVrF15eXvTp04cRI0ZQoUIFAKysrHB2dqb9wInc1amOirpmimP89o6Ll5cXf//9N0eOHKFXr16MGTPmu7XFTk5ONGrUiBIlSuDr6/vT63z+/Jk6deowdOhQhg0bpng8KCyKg/cC8Ar8wpfIWPJoqmFmmIfOFsXIr5N86UtyoqOjcXZ25tixYxw7dgxtbW0qVKjA+/fv8fDwoGPHjvTt25fatWvnmDrow4cPs23bNo4dO5ai42/evEnnzp3x9vZGS0srg6PLOn5+fsyfP58DBw6IhDubyn73jwThF1ewYEEiIiIIDQ3N0H7ML1++5J9//mH37t3Y2tpy+/btn9bUZobKxfRYZ2fJ3UdedJqwmPa9h/ElMoY8muqYFdalU7WkScW2bdto3bq10pNugOLFi9O9e3e6d+8OxCdBrq6uXL9+nTlz5nDv3j3Kli1L3bp1Fcn4fxf5/VfFihW5desWHTp0oFOnTnTt2pU///wTQ0NDjh49SvXq1ZX+Or4nV65cFClS5KcxJ4iMjEySqCf82cfHJ0myHhsbm+IkvVChQuTOnRsAIyMjVqxYgZ2dHffv3/9ujXNkZCTjx49n7dq1xMXFUbZsWVRUVHj37h1WVlZ4eXnRsWNH3Nzc0NPTQ0NDg+bNm1OgQAF69OhB06ZNKVq6HM6RBVHTT3nSDRARI2fWSU92LJ/Lg8vHGTp0KD4+PuTPnz9V4/yMvr4+p0+fpm7dupQoUYLiVeqz2ukZzt4fAIiK/bc8S1MtkKUXvbEqW5AhDU0wN9L76fi5cuWiWbNmlChRgty5c7N582Zu376teE4mk/Hx40ciIyNzTFL6ox7eyalVqxY1atRg5cqVTJgwIQMjyxp+fn7MmzePgwcPMnDgQJ4+fSoS7mxKzHgLQhYoV64cBw4coGLFikof293dnUWLFnH27FkGDBjAyJEjs+Vt44sXLzJv3jwuX778w+MkScLMzAxHR0fq1auXSdH9Kyoqivv37yeaFc+bN2+i8hQzM7Nk66idnZ3p0qULX758Yd26dfTq1SvHzCimVHh4OB8+fPjuLPp//yyTyRKVuHh5eZEnTx569OiRJEn//Pkz9vb2lClThlu3buHv78+RI0eoU6cOjRo14vHjx7Rr1479+/cjl8vR1dUlKioKSZJwcnJSLMo07DyDr3qlkaWl1l0up4x2BMfG26R4AWRqZ7wT3L59m7bjFpOngT3RclJdjpWcr1+/cvDgQRwdHXn69Ck9e/akb9++lCtXDojf3CehLtzNzY0mTZrQtm1bbGxslP4BQ5kmTZqErq4uU6dOTfE5T58+pV69ejx9+jRDPsRnhW8T7kGDBjFmzJhs/XUTxIy3IGQJY2Nj/Pz8lJp4X7t2jQULFuDm5saoUaNYvXo1efPmVdr4yubr66vY6fJHnJycUFdXT1K3m1k0NDSoXbs2tWvXZvz48cjlcp4+fapIwhcuXEhwcHCiGXFdXV1mzpzJnTt3mD9/PkFBQUyZMgUzMzNq1qyZJa8jo2hra1OiRIkU7VIoSRJfv35NlJz7+voyffp0bty4gY6OjiJB9/X15fPnz2hoaBASEqLYJXXx4sU8ffqUoKAgqlWrRr9+/fDw8KBfv37ExMQwadIknJycuHfvHs+ePeOxlzc3N4wmf6tR6FRuStDJpXz1uIROlRbEhX4k0s8dNf3CFLAZQy6D+DtCkf6efDq/htjgQLRN6/BJiiP3n10ZOXIky5YtA+D48ePMmTMHLy8v9PX16dSpE7Nnz05Xmz1veSF06vciKgXNfyQJImLimHs6fmdGu1rG9O7dm23btjFjxgxatWrF5s2bOXDgAHXq1GH06NFYW1sn6VpUqlQpRo0axahRo/j48SOnTp3i6NGjjBgxgqpVqyrqwrPD3bJvvX79mqZNm6bqnLJly9KhQwcWLFjAokWLMiiyzOHr68u8efM4dOgQgwYNwtvbWyTcOYRIvAUhkwWFRRFn2ohV98I4FHQnzXWbEL9I7dSpUyxYsID3798zYcIEDh06hKZm6m6pZ4WUJt7r169n4MCB2WamWEVFhXLlylGuXDn69+8PwJs3b7h+/Trnzp3j77//JigoCGNjY2xtbTE0NKRDhw6UK1cOGxsbli9frihr+d3IZDJ0dHTQ0dGhZMmSiscrVqxIjx49ePDgAZqamgwZMoTIyEicnJwwNjbm/fv31K9fn8DAQO7cuUN0dDQlS5akTJkyLF++nPfv3+Pp6QnAokWL0NbWRl9fn0GDBuHl9zrZWMIenEWrTC3U9AyI+eDLpwvrMLRbhDwyjA8HZyGP+opG8UrEhQfz1fdhonPPnTtH27ZtKVCgAG3btuXx48csWbKET58+sWXLlu++/oQP3ACqqqoUKFCA2rVr888//xCqno+5p72Ikafu+zwiRs7c015ULqZHZGQkAGvXrmXXrl306dOHR48epbgkI3/+/PTq1YtevXoRERHBpUuXOHbsGAsWLMDAwECRhFtYWGT5v8fUlpokmDlzJpUqVWL48OEYGRllQGQZ6+XLl8ybN4/Dhw8zePBgkXDnQCLxFoRM8tA/WFG3GatdjrgIFZ54vQdSX7cZExPD3r17WbhwIRoaGkyaNIkOHTrkqFZZvr6+/PHHHz885v3795w9e5Z169ZlaCzpXcSmq6uLh4cHR44coXfv3gwfPhwfHx9cXFz4559/6Nq1KyVLlqRx48aMHDkSV1dXli9fnu3a/GUVKysrevToQZcuXQgICMDKyoq7d+8qZo/z5Mmj6KMdHR0NwIYNGxLNeFauXJlHjx7RtWtXZs2apZhVvzE8+XperdKWFOo4jUg/d97tmUL0uxcAhD+7gzzqK2p6hhh0m4dMJuPN5uHEvH+JXB5fa71ixQoAqlatSv78+alZsyb3799n27ZtrF69+qev18bGhpIlS3Lu3DmOHj1KSEgIJg6LiIxNfZ97gMiYOOwX7sLz/y1KE2a70/P9paWlhY2NDTY2Nqxbt45bt25x7NgxevToQXh4OG3atKFt27ZYWVllSO//nwkICEhT4l2kSBEGDRrEzJkz2bx5cwZEljFEwv3rEIm3IGSCpG30Ev+HGPn/xVPnH7/jqnfQd+s2w8PDcXR0ZPHixZiYmLB06VKaNm2a5bNPaZGSGe8tW7bQvn179PT0MiSGbz8MQeoXscXExLBx40Zmz55NkyZNuHfvnuI1GRsb06xZM8VxDx48wMXFha9fv7J+/XocHR2xsbHBysqKevXqUaFChRz1wUmZJEnCwMCAa9eu0bdvX9avX//dY8uUKYOPjw/t27fn3Llz1KlTB4h/jwEaNWqEqakppqamuLu7ExUdm+w46gbxHWVUNOIXe0ox8bPFcWHx3YbU8hVV/LtSz29EzPuXrFq1it27dxMaGgrAhQsXuHDhQqLXsW/fvp/+e+zbty/t2rXjxIkTtGnThsdPvHjt/YHY8C8EO28n4sV95JGh5CpojJ6VPZpG8SVpIbcOE/bgDHFhn5DkcajnK0beurbkNqvHF50StG7XgcMH9mFsbIyKigpjx45lyZIlWFpacuHChTT/O1JVVaVOnTrUqVOHhQsX4uXlxbFjx5g5cyZeXl60aNGCtm3b0rJly0wpb5MkKc0z3gATJkygTJkyeHh4ZMg6G2V6+fIlc+fO5ciRIwwZMgQfH59fpj79dyWmWwQhg/27ccyPe1dD4rrNnTd9FY9/+vSJWbNmUbJkSZycnDh48CCXLl2iWbNmOTLphp8n3nK5nA0bNjBw4MAMuf7Om77YbrzJhSfviIqVJ0q6If7DUFSsnPOP32G78Wair4ckSRw8eJAKFSpw9OhRTp8+zc6dO7/7etTV1alevTqjR4/m5MmTfPnyhRYtWnDr1i2uXbtGly5dyJ8/Py1btmTu3Lk4OzsTERGRIa87uwkKCqJNmzbs27ePEydOcPjwYZ4/f/7d4+fPn0+3bt0ICwujZcuWiu4cCTPhCTPjwcHBdOzYEZks+X90soQ+3v/596OqEz+LGPv5341ZYj4GADB8+HCePHmiqNPv3bs3q1atYsaMGQwePJjmzZuzdetWZsyYAcQvfCtUqBAVK1akUaNGfPgQ/wFv4sSJNGrUiMGDBwNQokpdJHkcHw7NIezBWdTyFETLpAbRH3x5v2+G4vqxIe9QL2hM7kpN0S5Ti5igVwSd+IfY4Heoq6nyJjRGEfNff/2llKQ7OWZmZkycOBFXV1eePHlC48aN2bFjB0ZGRjRv3pw1a9YQEBCgtOv9V0hICCoqKuTJkydN5+fNm5fJkyenqod8Znvx4gX9+vWjevXqFClSBB8fH2bPni2S7l+ASLwFIQ2MjY2RyWTIZDKuX7+uePzatWuKx42NjXnoH4xDi5p4zW5FwKpeyGOiAIh+9wK/BTb4LbBJNG7kKw8Cd03i6YL29GpQDtPyFXFwcMDExIRXr16xaNEiXr16Rf369SlcuDATJkwgNjb5Gb3sLCoqig8fPvywxd2lS5fQ1dXNkMWI6fkwdPXqVWrXrs3cuXNZtWoV58+fp2rVqqm6vqamJocOHWLo0KFcu3aN7du34+3tzcCBA/n8+TMTJ05U1P+OHz+eY8eOERQUlI5XnD05OztTtWpVzMzMcHFxoWXLlkydOpWePXt+9/taVVWVHTt2KLrFNG/enHv37ilmvCH+Q1uvXr2oUaMG8ujIVMWkbVIdFY3cxH5+w7s9U3m3bwYxH3yB+Br1ggULMnnyZAD27t2Li4sL/v7+3L59m6dPn+Ls7Mz27dsBKFGiBO7u7uzZs4dp06YpSme8vb1xcnLi9evXyGQyXgTHEPrah6iAx8hyaZHLsDSq2nlR1y+CFBtN2KOLAOhbOaBdphaqmjqo6uRHVTsvxMUQ9foJkbFyQsLj34M9e/bw559/ZkjS/V+Ghob079+fU6dO8ebNGwYMGICrqyvm5uZUr16dOXPm8OjRI5TZQC09s90JhgwZgru7O9euXVNSVMrx4sUL+vbtq0i4vb29mTVrlki4fyGi1EQQ0mnt2rWKjhv/rUVe7fSMhP9u4sI+EeZ2mjw12pOcSH8P3u2dBpIcrdLVUc2th6+/BxaRkTx69IjY2FjKli1LXFwcXbt25c6dO/z999+oqqoyf/78jHyJSufv70/RokV/uBW1shdVXr9+nQULFnDN5TpfQsNQ1c2PVilL9Jv0RaaqTrjPLULvHiMq8DnExaKatyC5y9ZDr4EdscHv8FrXl56zwahSbeZNGEb37t3TVUMrk8mYMGECZmZmWFtbs3LlSmxtbWnXrh0QX1Z0+/ZtXFxcWLt2Lb169aJIkSKJ2hiWKlUqR97xiIuLY/bs2axfv57NmzfTsmVLxXMjRozg1KlTzJ8/n+nTpyd7vqqqKrt27SI2NpbDhw/TrFkzvn79qng+odtIaGgo8q+fUxWbiqYOBTvN4NP5NUS98ULbtA7aJtUJ97nFnTt3ePfuHS1btuTIkSMsWLCA06dPI5PJMDU1ZeTIkUnGMzQ0xNDQEIDcuXMTFBTEkSNHaNu2Lbdv36Z+/fp8vHWCvFrxiZUUHUHo3eOJxoj9/AYpLobAHWOJ+eCX9P0MDwEgJi7+ro23tzcA3bt3z9Ck+790dHTo2LEjHTt2JCYmBhcXF44ePUrr1q1RVVVVLM6sW7duurahf/36NcWKFUtXrBoaGsyePZuJEydy/fr1LP939Pz5c+bOncvx4/H94p89e4a+vn6WxiRkDJF4C0I66Ovrc/DgQZYtW4YkSRw6dAh9fX0+f/6MXJLia4cVEz0yQm4eQqdqy2THCnbeDvJYRdszgFyqMlZNakJ+HQ1GjRpFVFQUw4YNY+XKlTx79owyZcqwcuVKpk6dio6OTua8aCX4WZnJ27dvuXTpktIWP+3duxc7Ozvi4uLIV7wMuUtUJzbkPaEPzqDXwI4vd48TfCW+G4VG0XKoFzAi5uNrQu+fRK+BXaKxrAbNxs6uiVLiAmjTpg2XLl2Kr/V9/Jg///wTFRUVtLW1sbKywsrKCohPVh89eoSLiwtnzpxhypQpyOXyRIm4ubl5uhKazBAQEECPHj1QU1Pj3r17Se56qKiosHXrVqpVq0aLFi0Umw39tx+2mpoahw4dUvzdxsaGDh06cP78efbt20fNmjV59+4dHu4PWXInjAuP3yEBBWxGU8BmtOK8XAalKDHpZKKxcxU0pkjfhEWSckK2jyCc+JKhhK3XR48ezc2bN5N9jVZWVj+d4ZXJZFhYWJA7d26Cg4MVj6vq5KPoIEdkaurxV4+JQooKJybIPz7plqlQZMA61PQK89ZxKDFBr/59b1/Fv0dFixblw4cPjB07lri4OAYPHqzYuCizqKur06hRIxo1asSyZctwd3fn6NGjjB49Gn9/f6ytrWnXrh3NmjVLdWxpXVj5X927d2fx4sUcPXqU9u2TnxDJaP9NuH18fETC/YvL3j+hBSGbs7e3Z9myZWzevBlJkoiKimLIkCEsXbqUr1FxfLsHnLZZPcK9rhF6/xRaxolLE+QxUUS99gIg3Ocmny5tQCWXNnpV/mB/0zIMtiqDm5sbgGJ7bRMTE/T09AgODubZs2dZug18av0s8d68eTOdOnVKcw3nt8LDwxk6dChxcXF0tu3Gg9I9iP5/84iYz2+RR4UT7LwDgDy1O6Pf0F5xbkyQf5Lxbrz8xMewqFS3fvyRypUrK3a6fPLkCdu2bUvSD1pVVZUqVapQpUoVhg0bhiRJ+Pn5KfqJb9y4kVevXlGzZk1FIl6zZs1s9YHs5MmT9OvXj+HDhzNp0qTvLiYtWrQoq1atUuxq+aPETJIkrly5wo0bN3ByckKSJLZs2YKmpibr1q3DzMyM/urvOe/uD2op677x8cwKUFGNX1QZ4EH4G1+KFCnC0aNHiYuLY+PGjVhbW2NqasqoUaOwtrZO1cJYR0dHLl26xNWrVwkODkamqkZus/pEeLsS9dqLt9tGo1HUjLivwUS9eoR+k/5oGlcBmQpIcj5f2oQUE0XMpzeKMTXVVKhsVobb/p7UrFkTTU1N9uzZw4QJE5gyZQqFCxfGzMwsyS9DQ8MMn+2VyWSYm5tjbm7OzJkz8fPz4/jx46xatYpevXphZWVFu3btsLGxoVChQj8dTxmlJhD/b2rBggWMHj2a1q1bZ+qH1mfPnjF37lxOnDjBsGHDRML9GxE13oKQDg0bNqR8+fJs2LCBDRs2UL58eRo0aADE3/b9dsFe7nL1US9QnC+3DiOPTrxwTh4ZBlL8sdGBz8htVg8pOoKP13azd8sGAMUGIt8mUgkJSWBgYMa9yAzwo8Q7IbFR1qLK69ev8+nTJwDKt3L4d1EdoK5fmIiX90EeCzIV8tbpmuhc9QJJ+/zKgIP3lb9wzMDAgEuXLqGlpUWDBg14/Tr5/tOKOP6/jsDOzo5169bh4eGBr68vI0eOJCIigpkzZ2JgYKBY1Hno0KEs+z6Jiopi9OjRDB06lIMHDzJ16tSfJqqdO3emZs2ajBs3Ltnnv3z5wqpVq6hQoQLDhw9HJpNRokQJZs+eTa9evdi4caOiz/qJbavQfXYeKTYqRfHmMixNVMBjvrjuQzP8PV27dsXZ2Rk9PT3y58/PpEmTePnyJf3792fOnDmULVuWlStXKrqdfE9CO8KTJ0+yatUqPD09MTIyYuHiZeTOb0jBjtPRqdoSeVQ4YY8uEf3uOZqlLdEoWha1PAXI12wgKrn1iPT3IJehCRpFzRRjS0CpgvE/GypVqsSuXbtwdHREkiQ0NTVZsWIFI0eOpESJEri5uTFz5kzMzc3R09OjZs2a2NvbM3/+fI4cOcKTJ08Ui1UzQokSJRg+fDgXL17Ez8+Prl27cvbsWUxNTalXrx6LFy/Gx8fnu+crK/EGaNGiBYULF/5h/3VlevbsGQ4ODtSqVQtjY2OePXvGn3/+KZLu34iY8RaEdBo0aBAjRowAYOXKlYrHk9xplsnIW7cbQccWEno/8a1tVe08itks/Sb9yG1WD7V8RQm+sgWfO1eA+MTs6dOnhIWFKc5L+HNCDWlO8aMe3ufPn6dAgQKKmf30ev/+veLPQegSFfsx0fPy/9fHqmjnQUX95xsPRcXK8Xr74wQrrTQ1Ndm2bRsLFy6kZs2aHDlyRFFqkRL58uVT9F4GiIyM5N69e7i4uLB161b69+9Pvnz5EpWnlC1bNkNnPH18fLC1taV48eK4ubmlapHYypUrMTc359SpU1hbWwPw+PFjVq9ezZ49e2jSpAlr1qyhYcOG5MqVCysrK0aPHs3Lly9xc3Ojffv2eHp6snLlSmQyGeO792D7o7Bv2nomT69OFwwbdPvhduzq6up069YNW1tbXF1dWbp0KX/++ScODg4MGzZM8cHy2bNnnDhxghMnThAcHIy1tbXia/RtnbLPjrtceCInf/Oh341Lt5o1utWskz4hyaljnJcts3ewZ9cOxcMODg44ODgkOrRVq1aJ/v7x40eePn2Kl5cXXl5ebNmyBS8vL169ekWJEiWSnSVXZpKor69Pjx496NGjB1FRUVy5coWjR4/SsGFD9PT0aNu2Le3ataN69eqKNRWvX7+mRYsWSrm+TCZj4cKFtG/fnh49eqRr59EfefbsGXPmzOHkyZMMHz6cZ8+eZWr9vZB9iBlvQUinXr16oa2tTe7cuenZs6fi8eRyGW2zeqgXNCb8iUuix2Wq6qjl+0+Hj/9nBlra8bPaCaUkCe3TfHx8CAkJIXfu3JiYmCjp1WSOH814JyyqVJZvb12/fZ10plpFO77vsDz8C/KYlHXA+BIZ8/OD0kgmkzFp0iRWrVpFq1at2LdvX5rH0tTUpG7dukycOJETJ04QFBTEsWPHqF27Ns7OzrRs2ZJChQrRrl07Fi9ezM2bN5U607lz507q1KlDnz59OHz4cKo7M+TNm5ft27fTv39/HB0dadSoEU2aNKFAgQI8evSIAwcOYGVlxdq1a4mLi2Pr1q3IZDI2b96MnZ0duXLlomfPnsTFxbFnzx4md67HvgG1aF7eAA01FTTVEv8XqIocFSmO5uUN2Deg1neT7m/JZDLq1KnDgQMHuH//PnK5HHNzc8qWLUvx4sWpX78+T548YdSoUbx9+5aTJ08yaNCgJIsDh1qZoKmWtj7uqkicWzqGw//fQCc18ufPr/gaLVq0iOPHj+Pt7U1ISAhHjhzB3t6evHnzcuXKFcWMuYGBAQ0bNmTgwIEsXbqUM2fO8PLlvxsMpZWGhgYtWrRg3bp1BAQEKL6effr0oVixYgwcOJAzZ87g7++f7sWV36pRowZ16tRh+fLlShszgY+PD/b29tSqVYtSpUrx7NkzZs6cKZLu35iY8RaEdMqbNy9Xr15V/DmBuqoKGv/5j12WMOt9NGkXkrw1O/Lx9HI+X9pE5Mv7hD+9AUCTNp0BGD16NOvWrWP9+vWEhIQoEvChQ4dmqzrelPD19U20ZXiCgIAArl69ys6dO5V2rTp16igWvD4+tQWp7iBFuUlsyHu0SlYDFVWQxxFyYz/6DXspzo359Br1fElvaefRVFdafN/Trl07SpYsSZs2bXjy5AkzZ85M98y0iooKFSpUoEKFCooPNwEBAVy/fh0XFxd27dqFj48PlpaWihnx2rVrp3pTlLCwMIYNG8bNmze5cOFCmtcfBAYG4uTkRGhoKBMmTGDVqlV07Ngx0U6Jd+7cYfr06RgYGKCrq0tsbCxbtmzhzJkz/P3334oZ8ubNmwNQuZge6+ws+RgWxcH7AXi9DeVLZAx5NNUpoB7F6rE9WTPPK1Udaz5//sy5c+c4ceIEZ8+epWTJkhQuXBgPDw+MjIywsrKiZcuWqKt///vG3EiPqa3M/t/mMuUJrJa6ClNbVaBUmyU4ODhw4MABVq5cSYECBVI8RnI0NDQoX7485cuXT/S4JEm8fftWMUP+5MkTTp8+jZeXFx8/fqRMmTJJZshNTU1TvYBSRUWFGjVqUKNGDebNm4ePjw/Hjh1j3rx5uLu789dff2Fra0urVq2UMgM/d+5c6tSpw4ABA5A0dNK1ky3EJ9xz5szh9OnTYoZbSEQmKbO5piD8JoyNjfHz8+PIkSOK9m8JElbIGxUvjlavdTxf0Zu4L+8p2GEq2qa14//j2jKSmPfxW1R/21Hhy+0jfLl7Anl4MGp6huSr3RHP3fMVP+wvXbrExIkTefToEfr6+tjZ2TF//vwf/oee3URFRZEnTx7Cw8OT1Pn+9ddfBAYGsnbtWqVec9euXfTq1Qu5XI6GQSnUDcsQF/aJCF83jIbvJNTtDMHO24CEribFiQ0OJPrdC4xG7SE2+B2v1/UFIJehCfqaKhQvmBcVFRUuXryYoR98AgMDad++PcWLF2fLli0Zdis8QUhICDdv3lQs2rxz5w4mJiaJylN+NNv44MEDbG1tqV27NitXrkz1eyNJEtevX2f16tWcPXuWLl260L9/f/r378+QIUMUddsQv/mOpaUlQ4YMYf/+/dy9e5eTJ08yZ84ctm/fToUKFRgwYECKtnFPYGZmxq5du7CwsPjhcd7e3pw8eZITJ05w7949GjZsqCghSag/jouL49SpUyxbtgxvb2+GDh3KgAEDfrjVd9JdbpMnk4GmmmqicpiIiAimTZvG7t27Wb16NR06dEjx61aG0NBQvL29FUl5wq9nz55RqFChRMl4uXLlMDMzw8DAIFUfKKOiotDR0WHt2rWcOHGCK1euUL16ddq1a0fbtm0pXrx4muPvNmwSftpl+agRX7qXeCdbFST44U62EP99MWfOHM6cOcOIESMYMWJEpuzmKeQcIvEWhAw0YMddLjx599NNWpIlyYl5eY9Ohp8ZN24cRkZJF/rlRD4+PrRo0SLJ7oSxsbGULFmSEydOZEiHlqtXrzJ77nwuX3VBHhOJmm4BtEpZoN+kX3wfb++bfLl7jOh3/+/jnacQuc3+7eOdkHj/1+7du+nQoYNix8SMEBkZSb9+/Xj69ClHjx5V2sKylIiOjsbNzU2RiLu4uJA7d+5EiXj58uWRyWSsWbOGP//8k6VLl2JnZ/fzwb/x9etXdu3axerVq4mIiGDo0KHY29srZgkfP35Mw4YNcXV1xcTEhHch4VgPm0Xuoqbo5jPg1fOnDOnelhPLp9C2RRNmzJhB4cKFuX//fqoSu/Hjx5M7d27+/PPPRI/Hxsbi4uKiSLbDwsIUiXaTJk1++oHowYMHLF++nKNHj9K1a1dGjRqFmZlZsse6BwSzxukZV55+QEb8LqoJEhLARmULMsTKhMrF9JKcf+PGDRwcHKhWrZpSZr/TKy4uDl9f3yQJuZeXFzExMcnWkZcuXTrZCQVfX1/q16+Pv398x6GvX79y4cIFjh07xsmTJylWrJgiCTc3N0/x137nTV/mnHpCRHQssh/c7UjuAw8kTrhHjhzJ8OHDRcItJEsk3oKQgR76B2O78SYRMXGpPldLXZXVHUw4vXMdmzdvpkOHDkyaNCnH1XP/14ULF1iwYAGXLl1K9PiJEyeYO3fud3sjK8Pp06cZstsNilWOX8yaSjIZNC9vwDo7S96+fcuhQ4fYv38/Hh4etG7dmi5dutCsWbNEpRDKIkkS8+fPZ+3atRw5ckRpi0/TEoe3t3eiRDwoKAgNDQ1UVVVZvHgx7du3R1Pz5wtVIT5hWbNmDTt27KBevXoMHTqUpk2bJlvqsXLlSrYev0y1nlO49CQQKS4OSfXf5ExDVUZkVBS5v/jy+vwWAtyvo6urm6rX5+zszNixY7l79y6fP3/m7NmznDhxgnPnzlGyZElat26NjY0N1apVS1PpT2BgIOvWrWPdunVUq1aNUaNG0axZs2THSq4cxqywLp2q/bzkIatnv1MqKCgo0eLOhF/+/v4YGxsnScg/f/7MX3/9lezPidjYWG7cuMGxY8c4duwYsbGxik176tev/907g//uZJvaEp9yVNePYs6cOZw9e1Yk3EKKiMRbEDJYen6oJ8yofPz4kRUrVrB69WqaNWvGlClTqFSpUgZFnLE2btzIzZs3cXR0TPS4jY0NHTt2TNKFQRkCAwMZNWoUd+7cYeKiNSx9KKX5w9C+AbWSzDK+fv2aQ4cOceDAATw9PWnbti1dunShSZMmSk/Cjxw5oiif6NKli1LHTgsXFxdsbW2pWrUqpUqVwtXVFU9PT6pUqaKYEa9Tp06i8oqEEozVq1fj5uZG3759GTRoECVKlPjhtba7vmTmkYdIKqo//OAkyeVoqKkwo3WFFC2Q/JaHhwc1atTA3NwcT09PrKysaN26NdbW1kk2+0mPyMhI9uzZw9KlS4mLi2PUqFHY2dmhpaX185NTIbvNfqdUVFQUz549S5KQP3r0CIBatWolScqLFy+u+MAmSRKenp5s2bKFzZs3ExISgkwmQ09Pj6pVq7J+/XpUVVUVa020ytSiUMdpAHy5c4zPlzaiYVQRwx4L4uN5/YTPztuJfvccmUwFrdLVyd+4D5EXljPCrh3Dhw/Hz8+PSZMmce3aNWJjYylVqhTr1q2jXr16WfAOCtmVSLwFIROkp27zW1++fGHdunUsXbqUGjVqMGXKFGrWrJlxgWeAqVOnoqmpmWg7cD8/P6pVq4a/v79Sa5jlcjmOjo5MnTqVvn37Mn36dLS1tZXyYeh7AgICFDPhXl5eiZJwZdXiu7m50a5dO8VryortruPi4pg/fz4rV65k06ZNtG7dWvFcWFiYYrt7FxcXbt68iZGRERYWFkRGRnL9+nWKFi3KsGHD6NKlS4pmxzPqa5awtXlCCUl4eDhaWlq0aNGCRYsWKT0R/q+EDYCWLVvGzZs3GTBgAEOGDFFqkp9TZr9TYsmSJXh6etK9e/ckSfnHjx8xNTVNlIzPmDEDHx8f6tati4qKCl5eXnz48IGaNWvSpk0bpk6dqhjbsPcyNAxNkiTeMcGBvN08HCk6Eu1y9ZFHfCHS9wGaparRfdpqHB1q4e3tjaWlJaGhoTRt2pTSpUvz9OlTBg4ciK2tbRa+Y0J2IxJvQcgk6a3b/FZERASOjo4sWrQIU1NTpk6dipWVVZYkYKnVo0cPWrRokaj14vTp0wkODk7UBz29njx5woABA4iOjmbjxo1Urlw50fPK+jD0I/7+/hw8eJD9+/fj4+NDu3bt6NKlC40aNUp3Eh4YGKjofLJ58+YMTxC/9ebNG3r27ElsbCy7du36aWu3GzduMHfuXC5fvoyhoSGhoaFoaGgkqhOvXLlyosW2L168YNy4cbi4uBDy5QvyXDqoFShBvj8GI5OpKGrufzZTyTtvCnodxtvTHVVVVWxsbJg5cyY3b97k5MmTnDt3jtKlSytKSKpWrcqePXvYu3cvx48fz5g38Dt8fHxYvnw5u3fvxtramlGjRv10kWdqXL9+HQcHBywsLHLU7Pe3xo4di4GBARMmTEjy3H8Xd7q7uyu+hsWLF1cs6CxatCifPn3i9kNPLp858f+zZWiVtqRQ55lJvo9C753k04V1aBSvhGH3+UiSnIDl3ZFHhlG873LuLxvIqMH92LlzJzNnzkyyPkAQviX6eAtCJkloY3ZjYmNGNzOlfZWiNDErRPsqRRndzJQbExuzzs7yp0k3gJaWFsOGDePZs2f06NGDQYMGUbduXU6ePEl2/yz93x7eMTExODo6Kq13d2RkJDNnzqR+/fp07dqVGzduJEm6AexqGf+wp7OmWnw7yNT0dP4vIyMjRo8ejaurK/fv36d8+fLMmDGDIkWK0L9/fy5cuEBsbGyaXqehoSFXrlxBJpPRsGFD3rx58/OTlODMmTNYWFjQoEEDLl++/N2kOyIigq1bt1K9enV69OhBw4YN8ff35+XLl3z48IFr165hbW3No0eP6NGjB/ny5aN58+bMnj2bK1eu0LZtW44cOUKlSpUoXdcGdYNSRL3xIi7sU+Lr+NwkKvBZsjHEBAfyatdU7t68Tr169ShQoAA7duygbNmy7N+/nyZNmuDh4cGdO3eYMWOGom67RYsWODk5ERERkey4GaVMmTKsWrWK58+fU7lyZdq3b0+DBg04fPgwcXGpL436r7p16/LgwQOKFClCpUqV0tT3O6v9aNdKXV1dLCws6NGjB7Nnz+bgwYOKrjq5c+dGU1OTkJAQPD09cXFxwf3zvx2Vtc3qEfH8DlFvvZMOrBZfLhYX8p64r8HEBL1S9PyPfveSg/cDFGtW7ty5Q/78+TE0NGT48OGEh4cr8+ULvwJJEIQcLzY2Vtq3b59kbm4uVa5cWdq7d68UGxub1WElq0iRItKrV68Ufz98+LBUt25dpYzt5OQklS1bVmrXrp3k7++f4vOCQiOldc7PpFF73aQ+W29Lo/a6Seucn0lBoZFKieu/Xr58Kf39999S9erVpQIFCkgDBgyQLl68KMXExKR6LLlcLs2ZM0cqVqyYdO/evQyINl5UVJQ0duxYqVixYpKTk9N3j3vx4oU0fvx4qUCBAlKLFi2kEydOpOh78cOHD9KxY8ek8ePHS5aWlhIgqaqqSoNHT5BKTz4hlZh0Uio+7ohkNPagVHSQo0T8LukSyCSt0tWlEpNOSvpN+kuApGFUUSox6aSUr9kgxd+LlTaTBg4cKOno6EiAdPfu3R/G06BBA+nkyZOpfp+UKSYmRtq3b59Uu3ZtydjYWFqyZIkUEhKilLFdXFykMmXKSLa2ttKHDx+UMmZmqFevnnTlypUUH79v3z4pb96833y/IBkYGEi3b9+WHFacVDxWuM9KCVU1SbOURZLvI6PR+yU1/SKJxkj4pdeglzRqr5ukrq4e/3c9Palfv35S0aJFJUAaOXJkhr0XQs4kEm9B+IXI5XLpxIkTUq1atSRTU1Np8+bNUnR0dFaHpRAZGSnlypUrUSLWvHlzafv27eka9+PHj1KfPn2kokWLSocPH05vmJnqxYsX0sKFCyULCwupUKFC0qBBg6TLly+n+oPTwYMHpQIFCkgHDhxQeozPnz+XqlevLtnY2CSbpMXFxUlnzpyRrK2tpfz580tjxoyRfHx80ny96OhoRYKc16CYpGvRWirYYapkNOagVGLSyUSJt7ZZfQmQDO2XJE28W46QAElNz0BaeOSW9OjRIylXrlwSIDk6Ov4whr///lsaNGhQml+Dst28eVOytbWV9PX1pZEjR0rPnz9P95hfv36VxowZIxkaGkqHDh1SQpQZr2TJkpK3t3eqzomIiJDOnj0rTZ06VSpUqJAESK1bt5Y6/X1U8X1kNGqvpFO1Vfz3VLn6ib6PSkw6KRmNPSjlazFMylO7s5TfZoykUbySBEj5WgyT+my9LRUpEp+YL1q0SJIkSdq/f78ESCVLlsyIt0HIwUSpiSD8QmQyGTY2Nty4cYN169axe/duTExMWLVqVabfNk/Oq1evKFasmKKW98WLF9y9e5dOnTqlaTxJkti9ezcVKlRAW1ubx48f0759e2WGnOFKlizJhAkTuHv3Lq6urhgbGzNu3DiKFi3KkCFDcHJySlGZQceOHTl37hxjxoxhzpw5yZYcBYVFsc75OaP2udFn2x1G7XNjnfNzPoZFfXfcffv2UbNmTXr06MHx48cT1QV//vyZJUuWULZsWSZPnky7du149eoV//zzT7raXqqrq+Po6EjevHkJeRdA6L0TfDg8l9fr+yUpBchbpwuoqhF8bVeScXKb1UNNvwixwe+Y2L4mlSpVIjo6Goivkf8RGxubbFW6VbNmTfbs2cPDhw/R1NSkRo0atG/fnqtXr6Y5Rm1tbf755x8OHjzIpEmT6NatG0FBQUqOXHkkSeLNmzcp7mOfsHBWU1OT5s2bM2fOHCZPngzE14PraiTevDv+e0md8CcuScaSqaiiW6UF+g3t0ShchqjXTwAZmiXMyaOpnqScLeFrktN2FRYyQVZm/YIgZLybN29Kbdq0kQwNDaUFCxYo7VZ1Wpw/f15q3Lix4u+TJk2SRo0alaaxXrx4ITVv3lyqVKmS5OrqqqwQsw0fHx9p3rx5UpUqVSRDQ0Np6NChkrOz809nwt+8eSPVqFFD6tatmxQeHi5JkiQ9ePVZ6r/9jmQ67bRkOu20YhavxKSTUtn/PzZgxx3pwavPinG+fv0q9evXTzIxMUlSlnH//n2pb9++kp6entS9e3fp+vXrklwuV/p78OXLF6lYy4FSnjpdJRVtPQmQtExqJJrxTulMZWWb3tL27dslKysrCZA2bNjww2vL5XLJxMREcnNzU/rrUoawsDBpzZo1kqmpqVS1alVp+/btUlRUVJrHywmz3x8+fJD09fVTfHxoaKgESOXKlZO6d+8u9evXT8qfP78ESHPnzpXm7HFK9H1UYtJJSbeajeKxb7+P1PIVlbTLN5RyV2wiqWjklgBJt5q1VHbaaWmd8zPp8uXLEiDp6+tL/fr1k4oVKyYB0uLFizPwHRFyIjHjLQi/uJo1a3Ls2DHOnz/Pw4cPKV26NDNnzuTjx4+ZHsu3Cyujo6PZsmVLqhdVxsTE8Pfff1O9enWsrKy4d+8etWrVyoBos5aJiQmTJ0/Gzc0NZ2dnChcuzPDhwzEyMmLEiBFcu3YNuTxpa73ChQvj5OSEJElYWVmx+pw7thtvcuHJO6Ji5Ym2wYb47jpRsXLOP36H7cab7Lzpy6NHj7C0tCQiIoL79+9jYWFBVFQUu3fvpk6dOrRp04aSJUvi5eXFrl27qFOnjlI76iTMVM6cOZN8xU3Rb9CTvLU7AyCPTnrnJiUzlY3tRlK9enVu3LiBTCajcePGP4wh4e7RyZMnlfOilCx37twMHjyYJ0+eMGfOHHbs2IGxsTFz5szhw4cPqR4vJ8x+BwQEpGrXVk1NTUaPHo2GhganT59mx44d6OnpMX36dCZMmEDLSoZJzslTpwsytaS993MVKEHki/t8feyMinYe9Kx6o99sIBLQqVoxGjVqxI4dOyhUqBA7duxAS0uLv//+m9GjR6fnJQu/INFOUBB+Mz4+PixatIhDhw7Rp08fxo4dS+HChTPl2t/28D5w4ACrV6/GyckpxeffuXOH/v37U6hQIdauXUvp0qUzLths6unTpxw4cID9+/fz8eNHOnXqRJcuXahdu3ai3R4lSaLHzLVcjzBEpvbjXQ4j/dx5t2cKqnkKYTx0E2FXt7Owvw29evUiICCA9evX888//xAZGUmXLl3YtWsXampqPxwzPcLCwtDV1UVdXZ2KdZvxPDiOsKeuyCO+oNegF7nLN1S0EzQatRcVTR0+nV9H6P34JPnbdoKvNwxEq7AJFYzy43XzMsHBwQwdOpRVq1b9NI5Lly4xZcoUbt26lWGvVZk8PDxYtmwZhw4dolOnTowcOZKKFSumepzw8HCmT5+e7fp+nzp1ipUrV3L27FmljTlgx10uPH5HWhKhb3eyFYSUEjPegvCbKVOmDBs3buThw4fExMRQoUIFBg8ezMuXLzP82t/OeK9fvz7Fs92hoaGMHDmS1q1bM27cOEXv5d+BsbExMpkMFRUVdHR0aN68Oe7u7mzcuJGLFy+SP39+Bg4cSPHixRWtC+VyOe4BIbhR6qdJ93/FSirktXIgNk8ROnbsiLm5OSEhIbRo0QKAcuXKZWjSDfD8+XM0NTUpVaoULx7cIPTRZVQ0cpO3ji15anVM9pwfzVR+fXGfe5dOUKBAARYuXMiKFStSFEf9+vXx9vbm3bt36Xo9maVixYps2rQJb29vSpQowR9//MEff/zB6dOnk7078j3Zdfb7R60E08qqUBTy2O+vcfgRTTVVhlilfS2D8HsSibcg/KaMjIxYvnw5Xl5e6OvrY2lpib29PU+ePMmwayYk3j4+Pri7u6doJu348eNUqFCBL1++4OnpiZ2dXY7YKEjZrK2t6dKlCxoaGhw4cIB69erh4eHBjBkz8PDw4Pz58+jp6dG3b1+MjY0ZvPIIkTFp6/0cFRPHvKP3aNasGX5+fqxcuZK8efMq+RUlLyQkhC5durB+/Xq8vLwI/vyZfltuUGzQRvQa2CFTUUVNz4ASk05SYtJJVDTjF6+p6eSj+LjDlJh08t/Nc4BCHafQf8NloqOj8fHxYcKECYnuDPxIrly5aNasGadOncqQ15pRChYsyLRp03j58iU9e/Zk2rRplC9fnrVr1/L169cUj/Nt3+/KlStz5MiRDIz6516/fv3TzZpS4+LFi4zq2Z6upupoqacuHYrfFdUsRfsuCMK3ROItCL+5QoUKMW/ePJ4/f46pqSlWVlZ06tSJ+/fvK2X8bztp+Je0ZvszFcZsPIOtfT80NL4/G/vmzRs6derEuHHj2Lp1K1u2bCF//vxKiSkn6tu3L5s3b8bT0xNbW1tiY2MZNGgQ4eHh+Pr6MnPmTNatW8fbt28pUMgA33cfFbfPA9b0wW+BDZF+7gCEuV/Eb4ENgbsmJblOyK1D+K+0w+/IYj58/oKuru53Y9q8eTPm5ubo6OhQpkwZ5s2bl+YNgSC+PKZ37940adKEXr16KR5vZayaZbOSrVu3zrZ13j+joaFBz549uXfvHhs2bOD8+fMYGxszadIkAgICUjRGwuz3gQMHmDhxYpbOfitzxvvgwYN0796dgwcPsqh/a6a2KoeWuio/+0wvk4GWuipTW5VL06ZagiASb0EQANDT02Pq1Km8ePGCunXr0rp1a1q2bImLS9IFaynx0D+YATvuUnfhZZZe9ObogzeoGJlzwTsYd6kYZzXqMXDnXR76Byc6Ty6Xs3btWszNzSlXrhzu7u4/XQj3O1FTU2PmzJkAfPr0iQsXLtC4cWMOHjyIqakpjRs3xu3eXQL3TCPm89tUjR0XGsRXj8tolbIg7mswM6dO4sSJE8keu379evr27cvnz5/p1KkTqqqqTJ06lblz56b5tS1cuJC3b9+ydOlSxWNv375ldK8O1M/9Hikmdcm3MmYlW7ZsyaVLl4iMjEzzGFlNJpPRoEEDjhw5wq1bt4iMjKRy5cp069aN27dvp2iM7DD7ndrFld+zYcMGRowYwfnz52nQoAGQeCdbNZmETB6T6Bxl7GQrCCASb0EQ/iN37tyMHj2aFy9e0L59e+zt7WnQoAHnzp1Lcb/gnTd9f9hJQ6amQXSclKiTBsQvDqtXrx47d+7EycmJ2bNno6mpqeyXmOOVKFFC8efg4GBevnxJiRIl2LhxIxMnTqRopdpIMVGEuZ9P3cAyGQbd5lGg9Vh0q9kAsH379mQPTaiTrlGjBnp6elhaxi8wW7t2bRpeUfxt/+XLl3Pw4EHFnZDQ0FCsra3p2LEjzo5zaVs8LtNnJQsUKEClSpVwdnZO1zjZRalSpVi2bBkvX76kRo0adO3alTp16nDgwIGf3q3I6tnv9M54S5LE/PnzWbBgAVevXqVKlSqJnq9cTI91dpZ01nCnssyf9lWK0sSsEO2rFGV0M1NuTGzMOjtLUV4ipEvGrpARBCHH0tDQYMCAAfTp04d9+/YxZswYtLS0mDJlCu3atftunezOm77MPf2EiJifL+aSJIiIiWPO6SccO3Ycp02zmT17NgMGDEhxHe6vQJIkvn79yufPnwkODk70+5cvXwBwdHTkyJEjBAcH8/r1a8W5/fv3B+JLc6ytrdHT0yNSTQ+A2JD337le8l8bVe28qGrH13Kr54+vpf1eSYKvry8Ahw4dSvT4u3fvCAsLS9XGIa9evcLOzo49e/YoanhjYmLo3LkzFSpU4MSJE4wbN46RIzrjHhDMGqdnXHn6ARnx7RATaKqpEBEZSb3S+kywqaK0BCmhrWDz5s2VMl52kDdvXkaPHs2IESM4duwYy5YtY9y4cQwfPpx+/fqhp6f33XMTZr+nT59O5cqVWb16daZsXJWexFsulzN+/HjOnz+Pi4sLRYoU+e6xXg/u0N3Wlq5dq6QxUkH4PpF4C4LwQ2pqavTo0YNu3bpx/Phx5s6dy/Tp06lbty4bN2787nklJqW8LjYyRs49eQn2nnelSdWc2SUgJiaGkJCQRElzcol0cr8HBwejoaGBnp4e+vr6iX5PmIUsVKgQ9evXJ0+ePKxevRqILw9asGABgwYNonjx4nh7eyOTyTCp0ZiPgFreQgCo5NIkjn97YMd88Ev2NcSFhxAXHoKqdl5iPsYn3N9bzGZsbMzjx485fvw4rVu3Vjz+8uXLVCXdUVFRdOrUibFjx9KoUSMg/oPIgAEDkCSJJ0+e0LlzZ0aOHAn8Oyv5MSyKg/cD8HobypfIGPJoqmNWWJeHR9aT/7UGlYtZpTiGn2ndujXW1tasWLHil1vYq6qqSocOHejQoQP37t1j2bJllCpVih49ejBixAjKlCmT7HkJs98dOnTAwcGB/fv3s3LlykQ7mypTREQEX79+TdP4sbGx9OvXD29vb65evYq+vv4Pj3/w4AELFy5Ma6iC8EMi8RYEIUVUVFRo164dbdu25cKFC0ycOJE8efJgaWlJ+fLlkclkrFm3nriYaHIVNk31+JKqGgc8g2lSNQOCT8n1fzDrnJLfIyIi0NPTSzZ5Tvjd2Ng42efy5s1LrlxJW+FBfIIbGhrK+/fvuXr1KtevX8fb2xs1NTU2bNhAq1atWLBgAc+fP6dRo0YUKFCA53euIFPTQKdyMwByGZQiJugVwVd3EOn7gNAHZ773JvBuzxRyFSrF1ydXAejZs2eyhw4bNowhQ4ZgZ2dH+/btkcvl3L17l0KFCqWqN/vIkSMxMjJi3Lhxisf+/PNP3N3d0dXVxcLCgtmzZyc5L7+OBgMbJG0p+SBPd9q2bctff/2ltLsmCd/fnp6eaeqLnVNYWFiwY8cO3rx5w5o1a6hbty41a9Zk9OjRNGrUKNkPHZk1+50w253aDz4RERHY2toSHR3NhQsXyJ079w+P//z5M0FBQZiY5MwJACH7E4m3IAipIpPJFP2BXVxcmDdvHocPH6ZMuYrExUSjoqlLwXaTiH7/ko9nVxH7MQB5TCSqWnnQLlsH/Sb9kKmqJ9q0RbdKc77cOcYmNXWKvBrPjCkT0xRbcrPO3/s9NbPO3ybOVapUSfZ5HR2dDJ0NPXXqFFpaWhQsWJAuXbowduxYatSoAcRv9DJhwgRcXFyIjIykTr36+Ju0Q0U//na6Xv2exAYHEv3el2gNbXSr2RB652iSa6jqFiB3xcZ8uXkIVe28TJ0wljZt2iQbz6BBg8iVKxcrV67k4MGDaGpqUr58efr165fi17RlyxacnJy4ffu24r3btGkTO3bsoHz58mhqarJmzZpUva9VqlRBT0+Pq1evYmVlleLzfiRhF8sTJ0780ol3giJFijBnzhymTJnCrl27GD58OGpqaowaNYpu3bolWXeRGbPfaVlYGRISQps2bShatCgHDhz47ofbbz148IDKlSv/VqVuQuYSO1cKgpBuq1evZtjw4SBBwU4z0DapToTvA0Jc9qCeryioqBDx/A5xoR/Ra2hP3tqdFYk3yFAvWPzfWVZ5HJs3b8bS0jLVJRspmXX+3u96enop+o85pxiw4y4XnrwjLT/hJbkc8/xwfELrnx+cRvfv36d58+Y4OztTvnx5AE6fPo2DgwONGjXiw4cPnD59+octJ7/nn3/+wcPDgy1btigt3vPnz/PXX39x/fp1pY2ZU0iSxIULF1i6dClubm4MGjSIwYMHY2BgkOTYhF0v9+zZo9TZ7127dnHixAn27t2bouPfvXtHixYtqFu3LitWrEhxIr106VKeP3+eop1NBSEtROItCEK6BAQEULVqVYKCgshTqxP6Vr0Vz0W+8iDq9WPiwkOIef+SSD93NI2rYmA7+9/EW0WVYsO2o6qdl08XNxJ69xiampqULl06UXKckgQ6o2edc5KH/sHYbrxJRBo20cmlCrFn/6ZJ1TIsXbo0VTXbKfHx40csLS1ZtGgRnTt3BuDu3bu0bNkSa2trPDw8uHLlyg97iP9IYGAg5cqVIyAg4KelBSkVFRWFgYEBPj4+FCxYUClj5kRPnjxh+fLl7Nu3j3bt2jFq1CjMzc2THHf9+nUcHBywsLBQyuz3okWLePfuHf/8889Pj/X19aVZs2b06NGDmTNnpupnQq9evWjQoEGq7twIQmqIUhNBENIsNjaWrl27EhQUhEHZqmg0+LceOMR1P8HOSVvRxYWHJPp7cp00qlSpgqurawZG/uszN9JjaiuzFHeYSRDf+7ocbSeeYNSoUVStWpUdO3ZQq1YtpcQVFxdHjx496NixoyLpfvHiBW3atKFNmza4uLjg4uKS5qQbwNDQkDp16nD48OHv1qinloaGBk2aNOHMmTOJNvf53ZQrV45169Yxd+5cNmzYgLW1NaampowaNQobGxvFzLKya79fv36dqI3m93h4eNCyZUsmTpzIsGHDUn0dNzc3xUJeQcgIoohJEIQ0mzhxIjdu3MDAwIDWoxYgU1FVPPf1yTUA8tbvQfEJx9BTzIQnvsmW0EkD+GknDSF17GoZp3lHPl1dXRwdHVm4cCHt2rXjr7/+SteulAlmzZpFZGQkCxbEb+v+8eNHWrZsSbNmzTh//jznz59Xyoyyvb39d3uQp1VCnbcA+fPnZ/Lkybx8+ZJ+/foxe/ZsypYty8qVKwkLCwOU2/c7JdvFu7q60rRpUxYuXJimpDsyMpJnz55RoUKFNMUoCCkhSk0EQUiT06dPY21tDUC9evVQNzDBzf8zcfL4HykxQa+I9H2AWr6iaBQtR4S3K/Kor6gXKkmRPiv/LTWRqaBewChRjfexY8e+u6hPSL2f9b6WgEZlCzLEyiTZ3tdv3rzBwcGBkJAQdu7cmeaODydPnmTw4MHcvXsXAwMDIiIiaNq0KYULF+batWtcvnxZaUlPZGQkRYsW5cGDBxgZGSllzHfv3lG2bFnev3//S60HUAZJkrhx4wbLli3jypUrODg4MGzYMMUsdXh4ONOmTWPv3r0pnv0OCovi4L0AvAK/cOaiE5bmFahfqTSdLYqRXydx7f+5c+ews7Nj+/bttGzZMk2v4e7du/Tp0wd3d/c0nS8IKSESb0EQ0uTPP//kr7/++u7zhfut4ePJJUR/8EOjsCmaJasQcm1XksRbNU8hdC2s+XLzEDJVNaZOGMtf06dk4iv5fXyv93WnakkTmf+Sy+WsXr2aWbNmsWDBAvr06ZOq2tlnz55Rp04djh49Sp06dYiLi6Nz586Ehoby4MEDjh8/Tu3atdP7EhMZOHAgxsbGTJ48WWlj1qpVi7lz59KkSROljfmr8fX1ZdWqVWzZsoXGjRszevRoateujUwmw8XFhT59+vyw9vuhfzCrnZ7h7P0BINHOtwkfFK3KFmRIQxPMjfTYt28fI0aM4PDhw9StWzfNcW/cuBEXFxe2bduW5jEE4WdE4i0IgtKkppPGt4l3sSGbQZIT63ufgRVUGDFiBHnz5s34gIVU8/T0pEePHpQsWZKNGzemaNFceHg4tWvXZsCAAQwdOhRJkhg5ciSurq68evWKbdu20aJFC6XHeuPGDfr06cOTJ0+Utuh27ty5fPjwgWXLlillvF9ZaGgoW7duZfny5eTPn59Ro0bRqVMnYmJivjv7Hb/zrReRsXE//Dkik4Gmmir1dd5zesUUzpw5Q6VKldIV79ChQzExMWH06NHpGkcQfkTUeAuCoDRDrUzQVFP9+YHJkcfSr44Rz549w8TEhFmzZhESEvLz84RMVaFCBW7duoWpqSnm5uacPXv2h8dLksTAgQOpXLkyQ4YMAWDJkiWcPXuWN2/esHTp0gxJugFq165NXFwcd+7cUdqYCXXeYs7q53R1dRk+fDhPnz5l6tSpbNiwgZIlS7JixQqmTZvG/v37E9V+xyfdT4iI+XHSDSBJEBETx/kPOoxbdyzdSTfEL6ysWjWLdvASfhtixlsQBKX69z/PH3fS+HbGu8zIrbQwjODKhllIkoSDgwNubm6cPn2aYcOGMXLkSPT09DLnBQgp5uTkhL29PW3atGHRokVoaWklOWbNmjWsX78eV1dXtLW12bt3L2PGjEFTU5PRo0czfPjwDI1x9uzZBAYGsnr1aqWMJ0kSJUqU4Ny5c5QrV04pY/7qjI2N8fPz++7zxYoVIyAgQPF3mYY26vmN0KvXHa1SFgAEnVzKV49LyZ5vNv0M4yrF0q9L8n3nt2zZQu/evX8YY1xcHHnz5iUgIED8rBEylEi8BUFQutTeLp7aygy7WsZIksTp06eZO3cuQUFBODg44OXlxalTpxg+fLhIwLOh4OBghgwZwoMHD9i1a1eiGUNXV1fatm3LjRs3MDExwdnZmY4dO1KoUCE6derErFmzMjw+X19fLC0tef36dZo240nOkCFDKFmyJOPHj1fKeL+6WbNm8enTJwDWrl1LdHQ01tbWBAUF4e7ujr6+Pm/evEFNzxCt0tWJfveCqABPZGoaFB22DVVNHb56OhH11lsxZvRbb6Jee6GmV5higzdSK380Bv7OiufDwsJwdHQE4Nq1a9SrV++HMT59+pQWLVrw8uXLDHgHBOFfIvEWBCFDpKeThiRJODs7M3fuXJ4+fUrv3r15+fIlZ86cYdiwYYwaNUok4NnM7t27GTVqFGPHjmXcuHEEBQVhaWnJ2rVrsbGxwdPTk0aNGlG0aFFq1aqV6q3g06NRo0YMGzaMjh07KmW806dPs2DBAq5evaqU8X4nenp6hISEcOXKFaysrIiMjKR9566cPXkcrTK1KNRxGlJcLK+WdIK4WAx7/YNGkbJJxnm7dRTRgc/QbzqAPJZt0FBT4cbExopFwitXrmTEiBFUrVqV+/fv/zSuvXv3sn//fg4fPqz01ywI3xIb6AiCkCEqF9NjnZ1lmjppyGQyrKyssLKy4vbt28ybN49bt27Rp08fnj9/jomJiUjAs5nu3btTt25d7O3tOXXqFNHR0Tg4OGBjY8ObN29o2bIlJUqUwNjYmFWrVmXqDqMJPb2VlXg3btwYW1tbPn36RL58+ZQy5u9KU1MT1fz/bowjSRLRgc8gLhaZmgZq+kWSnBPp70F04DNkGrnRqdQUABlw8H4AAxuURpIkVq5cCZDihZKivlvILGJxpSAIGSq/jgYDG5RmadcqONpXZ2nXKgxsUPqn7esS1KhRg6NHj3L+/Hlev37NmTNnsLW1xcfHBxMTE2bOnMnnz58z+FUIKVGiRAkuXbqETCbj/v37lClThi9fvtCyZUsMDAzQ09Nj586dqKqmcQFuGnXs2BFnZ2c+fPiglPE0NTVp1KgRZ86cUcp4v7ugsCgAInxu8mphawJ3jENFIzcFO05FVSvpDqahd44DoFO5GSoa2kD8HTWvt6FAfL94Hx8fDA0N6dq1a4piePDgAVWqVFHCqxGEHxOJtyAIOUKlSpXYtWsXN2/eJCoqijNnztCuXTu8vb0pU6YMM2bMEAl4NnD48GFevXrFuXPnmDdvHqampkD8XYzDhw8rrc46NXR1dWndujW7d+9W2pitW7fm5MmTShvvd5bQp1tNz5DclZqioqmDPOorET63kxwbG/yOcJ+bIFMhj0XixZRfImMAFK0ehwwZkqKNjiRJEjPeQqYRibcgCDmKiYkJGzduxN3dHR0dHc6dO0fz5s15+vSpIgFPWMglZK4nT54wZMgQDh48iJWVFRYWFsTExPD48WOmTJmCrm7S2cvMYm9vr9SNUaytrTl37hwxMTFKG/N3paEWn4qoFzSmgPUoCnaYCkDo/VNEv3uR6Ngv906AJEfbtBZqegaJnsujqc6jR4+4fPkympqaDBo0KEXXf/v2LZIkUbRoUSW8GkH4MZF4C4KQIxUrVoxly5bx9OlTjI2NuXTpEvXr1+fx48eUKVOG6dOniwQ8E3358oX27duzcOFCLCwsmDFjhqKFoKOjI0OHDmXChAlERUVlSXyNGjXiw4cPPHr0SCnjFS5cmNKlS3P9+nWljPc7K/CfsjPN4pXQNK4CSITcPKh4XB4dQZj7BQB0LdsmPkdNBbPCuorZ7h49elCwYMEUXd/NzY0qVapk6roD4fclEm9BEHK0ggULMnfuXJ49e4alpSXXrl2jevXqeHh4YGpqyrRp00QCnsEkSaJPnz40bNiQPn36sGHDBjZt2kRoaCjnzp2jV69ePHz4EB8fH2rWrImnp2emx6iqqoqdnR3bt29X2pg2Njai3EQJyhfJk+SxvHVsAQj3ciHm81sAwh5dRIr6Si5DEzSNKiQ6XgIaFddUlBONGjUqxdcXZSZCZhLtBAVB+KV8/fqVjRs3snjxYkqXLk3evHm5fv06gwcPZvTo0eTPnz+rQ/zlLF68mP3793Pt2jUuXLiAvb29oid7rVq1FMdJksSWLVuYOHEi06dPZ9iwYaioZN78j5eXF40bN+bVq1eoqaW/qdf9+/fp1q0bT58+VUJ0vy+5XE7zOYfw/qqJLA3fDzIZNC9vwDo7yzRdv1OnTnTs2JFu3bql6XxBSA0x4y0Iwi8ld+7cjBo1iufPn2NnZ4enpyelS5fm/v37mJqaMnXqVD5+/JjVYf4yrly5wuLFizl48CDu7u707NkTSZLYs2dPoqQb4hdY9unTh5s3b7Jnzx5atmzJmzdvMi1WMzMzjIyMuHjxolLGq1q1KmFhYXh7e//8YCFZ3t7eWFlZ8cllD5rqaet2o6mmyhArkzTHkFBqIgiZQSTegiD8kjQ0NOjfvz9Pnz5l1KhRvHr1iiJFinDnzh2RgCtJQEAA3bt3Z+fOncTExGBtbY2qqipr1qyhefPm3z2vdOnSXLt2jbp161KtWrVM3bREmYssZTIZ1tbWotwkDWJjY1m4cCF16tShU6dO3D5zgOk25dFST11aoqWuwtRWZkk24UqpkJAQ3r17p+i+IwgZTSTegiD80tTU1OjevTvu7u7Mnj2bz58/o6+vj6urK6ampkyZMoWgoKCsDjPHiYqKolOnTowYMYIqVarQrFkzAP766y9sbW1/er6amhozZszg2LFjTJw4kT59+hAaGprRYdO1a1fOnDlDSEiIUsYTbQVT78GDB9SsWZNLly5x584dRowYEV+DX8uYqa3KoaWuys/WOcpkoKWuytRW5bCrZZzmWB4+fEilSpUyvbe88PsSibcgCL8FFRUV2rVrx+3bt1m7di1yuRxtbW1cXFwoW7YskydPFgl4KowZM4bChQszYsQIWrZsSXh4OEOGDGHo0KGpGqdmzZq4ubmhpqZGlSpVuHHjRgZFHC9//vw0adKE/fv3K2W8Jk2acPfuXYKDg5Uy3q8sMjKSqVOn8scffzB8+HDOnTtHyZIlEx1jV8uYfQNq0by8ARpqKmiqJU5TNNVU0FBToXl5A/YNqJWupBtEmYmQ+UTiLQjCb0Umk9GsWTOcnJzYu3cvurq6qKmp4ezsjKmpqUjAU2D79u1cuHABR0dHunXrxqtXr+jQoQMzZ85M03g6Ojps2LCBJUuW0KFDB2bMmJGh/bETtpBXBm1tbRo0aMC5c+eUMt6v6vr161SpUoWnT5/i7u5O7969v9u+r3IxPdbZWXJjYmNGNzOlfZWiNDYrRIyPC31rGHJjYmPW2VmmubzkW6KjiZDZROItCMJvq27dupw6dYqzZ89StGhRZDIZly5dwtTUlEmTJilti/FfyYMHDxg7diyHDh1i2rRpuLq60rBhQ1auXJnuPsht27blwYMH3L17l7p162bYosWWLVvy9OlTnj9/rpTxRFvB7wsNDWX48OF07tyZuXPncvDgQQwNDVN0bn4dDQY2KM3SrlXYbF+diqH3MSOA/DrK2/30wYMHIvEWMpVIvAVB+O1VrVqVAwcOcP36dcqXL49cLuf8+fOULVuWiRMnigT8/z5//kzHjh1ZsWIFZ86cYe/evVSqVImdO3cqrUbW0NCQU6dO0bt3b+rWrcuGDRtQdtdbdXV1unXrprRZbxsbG86cOUNsbKxSxvtVnD17lkqVKvH161c8PDzo2LFjusaztLTk3r17Sooufp3C06dPqVixotLGFISfEYm3IAjC/5mZmbF161YePHhA7dq1kcvlnDlzBlNT098+AZfL5djZ2dG6dWsA5syZQ4kSJTh+/Di5cuVS6rVkMhlDhgzh6tWrrF+/nrZt2/L+/XulXiOh3EQul6d7rGLFimFkZMTNmzeVEFnO9/HjR+zt7Rk8eDAbNmxg8+bN5MuXL93jWlhYcPfuXSVEGC+h1aiWlpbSxhSEnxGJtyAIwn8YGxuzevVqnjx5QosWLZAkiePHj1OmTBkmTJig9CQwJ5gzZw5fvnzB2tqa/v37U6BAAS5cuICOjk6GXbNcuXK4urpSoUIFqlSpwqlTp5Q2dtWqVdHR0cHFxUUp47Vu3ZoTJ04oZaycSpIkDhw4QKVKldDX1+fRo0f88ccfShs/YcZbWXdARJmJkBVE4i0IgvAdhQsXZtGiRbx48YKuXbuioqLCkSNHfrsE/MyZM6xfv55Zs2bRsWNHcufOjbOzMwUKFMjwa+fKlYv58+ezd+9ehg4dypAhQwgPD0/3uDKZjF69eimtp/fvXuf95s0bxQLbQ4cOsWzZMqV/KDMyMiI2NlZpmy6JjiZCVhCJtyAIwk/ky5ePP//8Ez8/PwYMGICGhgYHDhygTJkyjB8//pdOwF+8eEHv3r1ZtWoVXbp0QUVFBWdnZ4yMjDI1jgYNGvDw4UNCQ0OpVq2aUmp97ezsOHz4sFISeUtLSz5+/MiLFy/SPVZOIkkSjo6OVKlShUqVKuHm5kbt2rUz5FoymQwLCwul1XmLjiZCVhCJtyAIQgrp6uoyfvx4/Pz8GD9+PLq6uuzduxcTExPGjh3Lu3fvsjpEpYqIiKBjx46MHj2a8ePHExERwfnz5zEzM8uSePLmzcuOHTv4888/admyJfPnzycuLi7N4xUuXJhatWpx5MiRdMemoqLy2+1i+eLFC5o2bcratWu5ePEis2bNQkNDeR1HkmNpaamUOm+5XI67u7uY8RYynUi8BUEQUklLS4shQ4bw8uVL5syZQ8GCBdm1a9cvlYBLksTgwYMxNTXl8OHDvHnzhsOHD1OjRo2sDg1bW1vu3bvHhQsXsLKywtfXN81jKbOnt42NzW9R5x0XF8fSpUupUaMGLVu25ObNm1SuXDlTrq2sGe/nz5+jr6+vlEWfgpAaIvEWBEFII3V1dezt7fH29mblypUUL16cbdu2Ubp0aUaPHk1gYGBWh5hmGzZs4N69e4SHh/Po0SM2b96s1IVy6WVkZMTFixdp164dNWrUYMeOHWladNe2bVvu3LnD69ev0x1Ts2bNuHnzJl++fEn3WNmVh4cHdevW5dixY9y8eZNx48ahpqaWaddX1gJLUWYiZBWReAuCIKSTqqoqnTt3xsPDg+3bt1OuXDm2bt1K6dKlGTlyZI5LwG/dusX06dOpWrUqFy5cYMGCBdja2mZ1WEmoqKgwduxYLly4wMKFC7G1teXTp0+pGkNLS4uOHTuyc+fOdMejo6ND3bp1uXDhQrrHym6io6P566+/aNSoEQ4ODly+fBkTE5NMj6NYsWLI5fJ0f1B68OCBKDMRsoRIvAVBEJREJpPRqlUrbt++zdGjR7GwsGDz5s2ULl2aESNG5IgE/P3793Tu3BkbGxv27dvHyJEjGTlyZFaH9UPm5ubcvXuXIkWKYG5uzqVLl1J1vr29Pdu2bVNKm7pfsa3g7du3FT203dzcGDhwICoqWZM+yGQypWykI2a8hawik5S9JZggCIKgcOfOHaZPn861a9eQJAkHBwemTZtG4cKFszq0JGJjY/njjz/Q09Pj5MmT2Nrasm3btnRvBZ+ZLly4gIODA127dmXu3Lloamr+9BxJkjAxMWHfvn1YWlqm6/p+fn5Ur16dt2/fKm03z6wSHh7O9OnT2bVrF8uWLaNr167Z4nth+vTpAMyePTvNYxgaGnL79m2KFy+urLAEIUXEjLcgCEIGql69OmfPnuXWrVu0aNGCzZs3U6pUKQYNGsTbt2+zOrxEpk2bRlhYGCdPnsTKyoqtW7dmi0QrNZo1a8bDhw/x8/OjRo0aPHr06KfnKLOnd4kSJRRJXU52+fJlKlWqRGBgIB4eHtja2mab74X0zngHBgYSHR2d6S0xBQFE4i0IgpApKlasyOHDh/Hw8KBjx45s3bqVkiVL0q9fv2yRgB8+fJjt27fz6NEjKlasyMmTJ7OsnCC98ufPz4EDBxg7diyNGzdm6dKlP90avlevXuzdu5fo6Oh0Xz8nb6YTHBxM//79sbe3Z/ny5ezatStTNkpKjYSyl7TesE8oM8kuHySE30vO/KkqCIKQQ5UuXZqdO3fy7NkzevXqxc6dOylZsiQODg5K25Evtby8vBgwYAChoaEULlyYa9eukStXriyJRVlkMhn29vbcunWLgwcP8scffxAQEPDd40uWLEn58uWVsi19Tm0reOzYMSpWrIiamhqenp7Y2NhkdUjJKlq0KCoqKj/8ev6IqO8WspJIvAVBELJAsWLF2LBhA/7+/gwcOJC9e/dSsmRJevbsmakJeFhYGO3bt0cul6OhocGdO3fInTt3pl0/o5UqVQpnZ2caNWqEhYUFBw4c+O6xyurpXbNmTd6+fYufn1+6x8oM79+/x9bWlvHjx7Nr1y7Wrl1Lnjx5sjqs70rYwTKtG+mIjiZCVhKJtyAIQhYqWLAgy5cvJzAwkDFjxnDo0CGMjY2xtbVVSm/pH5EkiT59+vD+/Xuio6Nxc3Mjf/78GXrNrKCmpsbUqVM5efIk06ZNw97ePtle2506deLKlSsEBQWl63qqqqq0atUq25ebSJLEjh07qFSpEiVKlODhw4c0bNgwq8NKkfTUeYsZbyEricRbEAQhG8ibNy/z588nKCiIGTNmcOrUKYyNjenYsWOaEvCgsCjWOT9n1D43+my7w6h9bqxzfs7HsCjFMUuXLuXcuXOEhYXh6ur6yy82q169Ovfv30dbWxtzc3NcXFwSPZ8nTx6sra3Zs2dPuq/VunXrbJ14v3r1ilatWrF48WJOnTrFwoUL0dLSyuqwUiytM96hoaG8efOGsmXLZkBUgvBzop2gIAhCNhQVFcWqVauYPXs2X79+pWXLlqxZs4ZixYr98LyH/sGsdnqGs/eH+HFi/11UqKmmggRYlS1I7TyhDLG1Jjo6mgsXLtCoUaOMfDnZzokTJxgwYAB9+vRh5syZipr28+fPM2XKlDSXMST48uULxYoV482bN+jo6CgjZKWQy+WsXbuWmTNnMnr0aCZMmIC6unpWh5Vqr1+/pkqVKrx//z5ViyRdXFwYM2ZMju86I+RcYsZbEAQhG9LQ0GDs2LEEBQWxYsUKbty4gbGxMS1btuTVq1fJnrPzpi+2G29y4ck7omLliZJugMj/P3be8x0zr35G1cyKnTt3/nZJN8TPSD948ICHDx9Sp04dvLy8AGjSpAlv377F09MzXePnyZOHmjVrcvHiRWWEqxRPnz6lYcOG7N69m2vXrjF16tQcmXQDFClSBDU1Nfz9/VN1nigzEbKaSLwFQRCyMTU1NQYPHsz79+9xdHTkwYMHlCxZkmbNmvHy5UvFcTtv+jL39BMiYuL42X1MCZCpa2DQfDCxxrUy9gVkYwYGBpw4cYJ+/fpRv3591q5di4qKCnZ2dkpZZJld2grGxMSwYMEC6tWrR9euXbl27RrlypXL6rDSJa0LLB88eCASbyFLicRbEAQhm3nx4gUdOnSgUKFCaGpqUqxYMVq1akW9evW4ceMGcrmcixcvUqpUKRo2bMjJG48YO3M+XrNbEbhrkmKcz05beb1hIH4LbPBbYEOYe+LZ11hUGPfX3xiVKImGhgZly5ZNsonMw4cPadSoEVpaWuTPn5/+/fsTGhqaKe9DZpDJZAwaNAgXFxccHR1p3bo11tbW7Ny5k7i4uHSNbWNjw6lTp37aQzwjubm5UaNGDa5cucKdO3cYNmxYju3P/l9pWWDp5uYmOpoIWerX+NcnCILwC2nfvj1HjhyhUqVKODg4ULVqVVxdXXn79m2Setbnz5/T5599xMQmTRKj3nijlqcQKlrJt4b7+tiZd2fXEPQ5hG7duvHhwwd69+7NuXPngPiFaM2aNcPJyQlra2uMjY3ZtGkTAwYMUP6LzmJly5bF1dWVKlWq0LVrV7S1tbl06VK6xixdujT6+vrp2mUxrSIiIpg8eTLNmzdn1KhRnD17FmNj40yPIyOldsY7OjoaLy8vKleunIFRCcKPicRbEAQhG/n06RPu7u7o6elx8eJF1q5dy4kTJ3j//j3VqlVLdKxMJqNCJXPymtUGWdIf54bd52FgOxtV3eRbBIbcPAiA/h+D+WfVev7++28A5s+fD4CjoyMfPnzAxsaGgwcP4uzsjKamJvv37+fFixfKfNnZgrq6OnPmzOHAgQN8/vyZoUOH8vXr13SNmRWb6bi4uFClShWePXuGu7s79vb2v+QujRYWFty7dy/FO1g+efIEY2NjtLW1MzgyQfg+kXgLgiBkI7q6uujo6BAcHEzVqlUZM2YMR48eJTY2NknC0LlzZ86fPU104LNUX0eSxxHzIX6DF63CZTh4PwBLS0sgvg4W4m/LA4rHdXR0MDMzQy6X4+7untaXmO3Vq1ePO3fu4Ofnh7m5OXfu3EnzWJnZVjA0NJRhw4bRtWtXFixYwIEDBzA0NMyUa2eFIkWKkCtXrhRvVCTKTITsQCTegiAI2Yi6ujqOjo7kzZuXhw8fsnTpUtq3b0/p0qWTJIBTp05FVU2d9047Un0defgXkOJrj6NVNfB6G6rYsTIkJITIyEjevXsHkKgdXsIxgYGBaXp9OUXJkiWxtramWbNm2NjYMGfOHGJjY1M9Tu3atfHz80vz9uYpdebMGSpWrEhERAQeHh60b98+Q6+XXaSmzlt0NBGyA5F4C4IgZDNdunQhMDCQs2fPMnXqVAoVKsS7d++YPXt2ouOKFy9OmQZtiHxxj6g3Xqm6hop2HkV5ihQdyZfIGMLCwoD4zXw0NTUxMDAAUDz+7Z9/5ZnUBPb29jx+/Jj79+/j7OxMw4YNU11io6amRsuWLTl16lSGxBgUFETPnj0ZOnQojo6OODo6oq+vnyHXyo5SU+ctOpoI2YFIvAVBELKRmJgYXFxc0NTUpHnz5syZM4fJkycDJNtNpG6n/qCqTvgTlyTP/YhMRRX1AsUBiHrrTR5NdcWMurm5OYDitnzCZiOhoaF4eXkhk8moVKlSml5fTtKqVSseP35MdHQ0586do3PnztSsWZOtW7emuK4YMqatoCRJ7N+/n0qVKlGgQAEePXpE06ZNlXqNnCClM95yuZwHDx6IUhMhy4mdKwVBELKRsLAwdHV1KVeuHFWrVkVbW5sjR47w8eNH5s6dS/fu3SlZsiQAnz9/Zu/Dj0weN5rgu/EL+DSMKmLYYwEAIa4HiPkYQMSzW8gjw9AoVh41vcLomP+BplEFvno6EXRiMaraeaneoAleNy8THBzM6dOnadmyJaGhoZQsWZKPHz/SoUMHXr58iZubG126dGHfvn1Z9h5lpuHDh1OgQAFmzpwJwKNHj+jRowempqasX7+e/PmTX7j6reDgYIoXL05gYKBSFva9efOGIUOG4OPjg6OjI7Vq/b692AMDAylfvjwfP3784QLS58+fY2VlleoNdwRB2cSMtyAIQjaiqanJ6NGj0dDQ4PTp0+zYsQM9PT2mT5/OhAkTkhzfyaIY+ep2RaaWK8lzES/u8dXjEvLI+PKQqIDHfPW4ROzntwDkrmCFftMBqOTS4t6lExQsWBBHR0datmwJxC/0vHDhAg0bNuT06dP4+vrSp08fNm7cmIHvQPZib2/P9u3bFTPclSpV4vbt2xgbG2Nubs758+d/Ooaenh4WFhZcvnw5XbFIksSmTZswNzfH3Nyc+/fv/9ZJN8SXPGlpaeHr6/vD40SZiZBdiBlvQRCEHG7AjrtcePLupztWJkcmg+blDVhnZ6n8wH4BkiRRsWJF1q9fT7169RI9d+nSJRwcHOjQoQPz589HS0vru+MsWbKEp0+fsn79+jTF8fz5c8XmRY6OjqIX9Tfatm2LnZ0dnTt3/u4x06ZNQ0VFhVmzZmViZIKQlJjxFgRByOGGWpmgqaaapnM11VQZYmWi5Ih+HTKZjF69eiXZ0ROgSZMmPHjwgLdv31K9enUePnz43XFsbGw4edGZdc7PGLXPjT7b7jBqnxvrnJ/zMSzqu+fFxcWxZMkSatasibW1Na6uriLp/o+Eft4/IjqaCNmFmPEWBEH4Bey86cvc00+IiEn59uRa6ipMbVUOu1rGGRfYL+D169dUqlSJ169fJzurLUkSu3btYsyYMUyYMIExY8Yk2pb9oX8wq52ecf5RALnU1Yn+5kukqaaCBFiVLciQhiaYG+kpnvPw8KBv375oa2uzceNGTEzEB6TknD59mqVLl3LhwoXvHlO0aFFcXFwU6yMEIauIxFsQBOEXEZ98exEZE8ePf7BLEBvDzLaVcKgnkrmUaN68Ob1796Zbt27fPcbX15devXqhpqbGtm3bMDIy+vdrEhv3w1IgmSz+7sPUVmZ0rlqY+fPns3r1aubNm0e/fv1+yZ0nleXdu3eUK1fuuwss379/T9myZfn06ZN4H4UsJ0pNBEEQfhF2tYzZN6AWJVSDUZHi0FRL/CNeU00FDTUVmlcwxNT/FE9PbsqiSHOehEWWP2JsbMyVK1f4448/sLCwYOSqQ/+/C/HjpBtAkiAiJo5ZJz2p1GEI9+/f58GDB/Tv318kiz9hYGBA7ty5efnyZbLPJ+xYKd5HITsQM96CIAi/ELlcjomJCRu27+G5vABeb0P5EhlDHk11zArr0qlaMfLraPD+/XvMzc05cOBAkkWDQlLh4eEULVoUT09P7t27x+LFi3FzcyMmJgYTExP69OnDyJEjFSUm+y7cZOL5t5BMt5mfUZdJHBxcF3Oj32cjnPRq164d3bt3p0uXLkmeW7hwIYGBgSxdujQLIhOExNSyOgBBEARBea5cuUKePHloUrcGTX8ww1eoUCHWr19Pr169ePjwIbq6upkYZc6jra1Nhw4dGDZsGEeOHAGgZcuW6Ovrc+TIEcaMGcPdu3fZtWsXAJcC1ZCp5fpJyU/yYpGx1vl5ijrNxMTEoK6unoar/FoSNtJJLvF2c3OjVatWWRCVICQlSk0EQRB+IRs3bkxxTXCbNm1o3Lgxo0ePzoTIcr7OnTtz7NgxAKZOncrp06fZtWsXhw8fBmD37t04OzuzfvM2to3pgN/iDvgvs+Xt9rFE+nsCIMnj+HLnGG82DeHV4o74r7Aj2GUPABEv3XizeQR+S7qw3r4WRsWLKzbuAdi6dSsymYx69eoxePBgdHV1mTt3bia/C9nTj7aOFx1NhOxEJN6CIAi/iKCgIM6ePUuPHj1SfM7SpUu5cuWKIqEUvk+SJOTy+JYk/fv3VzzeokULSpQoAcDx48cZOrA/MSHvyV3eCq3S1ZGiI4gNDgQg+NouPl/aSGzwO7TL1kGzeEViPgUAEBf6EVXtPOQu14A8lRrzKfgLs2bNYu/evYniuH79OpcvX6Z79+6UKlUqM156tmdhYcH9+/f5b/VsWFgY/v7+mJmZZVFkgpCYKDURBEH4RWzfvp02bdqgr5/y2mBdXV22bdtG586dqV27NoUKFcrACHO2T58+Kf5saGiY6LnChQvj5+fH58+fkcfFoaKTBy3TWqgXKI66niGSPA5Jkgi9dwKAAq3Hol22DgBSXCwAuSs1RjV3XqICnyOPCEW3YFHCQ0O4fPkytra2imvp6upy69Yt9PT0MvgV5xyFChVCV1eX58+fJ2q76O7uTvny5UU5jpBtiMRbEAThFyBJEhs3bmTDhg2pPrdevXr07t2b/v37c/ToUdH94TsKFCig+LO/v3+iBC8wMH5G29DQkNr2E7l1cD0fDsbvkqiqW4ACNmNQL1gCKToCgFxF/52BlanG/1f86dwawh6cVTwe+v/fP3z4kCiOChUqiKQ7GQl13t9+XcRW8UJ2I0pNBEEQfgE3btxAkqQ0dyj566+/8PPzY8uWLUqO7NdRu3ZtdHR0gPga7wQXLlzA19cXiO/3XbVJW4oN207RYdvRbzqAuNAgQm7sRUUrD7Jc8RvwRL95qjhfkscB8PXJNQDyW4+m+MTj6JWtCcRvENOwYUPF7pnh4eH4+/snKav43SVX553QSlAQsgsx4y0IgvALSM2iyuTkypWLnTt30qhRI6ysrETtcDLy5MnD/PnzGT58OPv37ycsLEzR1QSga9euNGzYkJY6eVApWgFZ7nzEfPAFQEVDB5lMhq5Fa7647ifoxGK0TesgSXJkMhkFWo9DNbcesVFfCb17nGhfNyJ947egb9SoEePHj1d8KHr16hU1atQgLCwMMzMzypUrR7ly5ShfvjzlypWjVKlSqKn9fv+9W1hYsGjRokSPubm54eDgkEURCUJSoo+3IAhCDhccHIyxsTE+Pj4ULFgwXWP9888/HD16FCcnJ1RVVZUU4a9l165d2Nvbo6mpSWxsLCYmJvTu3ZvRo0ejqqpKm/YdOXP5GrFfP6OirolG0XLkazYINT0DJHkcofdOEvbwHLHB75Dl0kK3mjV69boR6e/Bx7OriAt5j3bJqtj9UYP1q1fStm1bjh49ytatW3FwcKBhw4Y4OTnx+fNnnjx5kuTX27dvKV26tCIhT/hVtmzZZLe8/1V8+PCBMmXK8OnTJ1RUVIiJiSFv3ry8f/9ecadCELKaSLwFQRByuDVr1uDk5MT+/fvTPZZcLqdJkya0aNGCiRMnKiG6X1O3bt2oV68eQ4cOTfb5ATvucuHJu5/uWJkcmQyalzdIUR/v5ISHh+Pt7a1IxB8/fsyTJ094/vw5RYoUUcyMf/vrV6kZL1GiBBcvXqRMmTI8evSITp068fTp05+fKAiZRCTegiAIOZgkSVSrVo1FixbRrFkzpYzp5+eHpaUlFy9exNzcXClj/mrOnj3LjBkzuH37drLPP/QPxnbjTSJi4lI9tpa6KvsG1KJyMb10RplYTEwML168SDJD7uXlhY6OTpJkvFy5chQuXDhHLbZt06UHRet1QMOgFI+f+fIxMID+nVrR2SJ+x1ZByGoi8RYEQcjB7t27R6dOnXj+/Lliu3Jl2L59O4sXL+b27dtoamoqbdxfRWxsLMWLF+fSpUuUK1cu2WN23vRl7uknRMTIUzyulroKU1uVw66WsZIi/TlJkggICFDMjH/7KyYmJtmE3NjYOFuVIj30D2a10zMuPX4b329d9m9smmoqSIBV2YIMaWiCuZFelsUpCCLxFgRByMEGDRpEsWLFmDZtmlLHlSSJTp06UapUKf7++2+ljv2rGD9+PGpqasyfP/+7x8Qn315Exsb9sOxEJgNNNVWmtjLL1KT7Z4KCgpIk448fPyYoKIgyZcokWtRZrlw5ypQpg4ZG5s4s5/T3WPi9iMRbEAQhhwoLC6N48eI8evSIokWLKn38oKAgzM3N2b17Nw0bNlT6+Dmdh4cHLVq0wM/P74ezv+4BwaxxesaVpx+Ijo5CUvl3M5eE2dhGZQsyxMpE6eUlGSUsLAwvL68kSbmvry/FixdPdpZcV1dX6XHklLsKgpBAJN6CIAg51ObNmzl69CjHjx/PsGucOnWKoUOH4u7uTp48eTLsOjmVhYUFCxYsSFF9/cewKOrYjaFW8w6oaechj6Y6ZoV16VTt16k/jo6O5tmzZ4kWdT558gRvb2/y5cuXbEJesGDBNNWRFzEqztsAf8XfVbTykMuwNHoNeqFRuAx+C2wAKOywglwGidtjZlQdvSD8jEi8BUEQcqg6deowefJkWrdunaHXGTRoEFFRUWJznWSsWLGCO3fusGPHjhQdny9fPry9vRPtgvk7kMvl+Pn5Jdv+UCaTJUrEE0pXjIyMfrhuQbdgEcKC3qJVujpqeoZEvnpEzAdfVDR1KNJ/HQEr7YDkE+/0do4RhLQSibcgCEIO5OnpyR9//IGfn1+Gb5YSFhZGlSpV+Pvvv2nfvn2GXiunSegd7e/v/9NSitDQUAwMDPj69WuO6hSSkSRJ4t27d8km5CEhIZQtWzbJDLmJiQkhUXIKFytObMh7CnaYirZpbeLCQwhY0QOAgh2m8eHwHCD5xBtAQ02FGxMb/zJ3G4Sc4ffb2koQBOEXsHHjRhwcHDJlh0IdHR127NhB+/btqV27NoaGhhl+zZyiYMGCNGzYkIMHD/50h0R/f3+KFy8uku5vyGQyDA0NMTQ0pFGjRomeCwkJSVRHvmXLFp48eUJAQADFmjnw7byhJMmJfOWh+LuK9s/LomTAwfsBDGxQWmmvRxB+RiTegiAIOUxkZCS7du36bg/pjFC7dm369etHv379OHHihEgev2Fvb8/KlSt/mni/evUKIyOjTIoq58ubNy81a9akZs2aiR6PjIxk4FZXfK8eBuDD4bmJntcyqYFGUbOfjh8ZK8frbajyAhaEFFBe01dBEAQhUxw+fJiqVatSsmTJTL3ujBkzePv2LZs2bcrU62Z31tbWPHr0CF9f3x8e9+rVK4oXL545Qf3CNDU1UdX6dwt4rdLV0bVsS976dhTq/CcFO05HJktZevMlMiajwhSEZInEWxAEIYfZtGkT/fv3z/Tr5sqVix07djBlyhSeP3+e6dfPrjQ0NOjatetPF1gmlJoI6ZdH898b9jrmf5CvaX/06tqiVdoyVXdj8miq//wgQVAikXgLgiDkIM+ePcPDw4M2bdpkyfXLly/PtGnT6NmzJ7GxsVkSQ3Zkb2/P9u3b+VG/AjHjrTxmhnlIaX4ddHIJb7ePVfyK+fQaiO+hblZY+b3FBeFHROItCIKQg2zatIlevXpl+u6A3xo+fDja2tosWrQoy2LIbqpXr46amhqurq7fPUYk3spjXT4/pLAnW8wHX6LfPFX8kmKigPjTO1UrlnFBCkIyRDtBQRCEHCImJgYjIyOcnJwwM/v54rGM5O/vj4WFBefOnaNq1apZGkt2MX/+fHx9fVm/fn2yz5cuXZozZ85gamqayZH9OiRJ4uDBg4wbN458bScRnLt4SvPvREQfbyGriBlvQRCEHOLEiROYmppmedINYGRkxNKlS7GzsyMyMjKrw8kWevbsyYEDB4iIiEjynFwuJyAgQHQ1SQd3d3caNWrEnDlz2L59O1vHd0NTXTVNY2mqqTLEykTJEQrCz4nEWxAEIYfIqkWV39O9e3cqVqzIlClTsjqUbKFYsWJYWFhw/PjxJM+9f/+evHnzoqWllQWR5WwfP35k6NChNG3alK5du3Lv3j0aNmyIuZEeU1uZoaWeulRGS12Fqa3MxHbxQpYQibcgCEIO8OrVK27dukXHjh2zOhQFmUzG2rVr2b9/P5cvX87qcLKFhEWW/yXqu1MvLi6OtWvXUr58eWQyGV5eXgwePDjRplF2tYwZWrcIUkwUP1trKZOBlroqU1uVw66WcYbGLgjfIxJvQRCEHGDz5s1069YNbW3trA4lkXz58uHo6IiDgwPBwcFZHU6Wa9++PTdu3CAwMDDR4yLxTp2rV69iYWHBvn37uHDhAqtWrSJfvnzJHutxZC1NZR40r2CAhpoKmmqJUxtNNRU01FRoXt6AfQNqiaRbyFJicaUgCEI2FxcXR8mSJTlx4gTm5uZZHU6yhg4dypcvX37ay/p34ODgQMWKFRk7dqzisSVLluDn58fy5cuzMLLsz9/fn/Hjx+Pq6srff/9N586df9iX29vbm7p16/L06VPy5cvHx7AoDt4PwOttKF8iY8ijqY5ZYV06VStGfp2s6wQkCAnElvGCIAjZ3Llz5zA0NMy2STfAokWLqFatGgcOHKBz585ZHU6Wsre3Z8SIEYwZM0aRNIoZ7x+LiIhg8eLFLF++nKFDh7J58+YU3d2ZNm0aY8aMUcyG59fRYGCD0hkdriCkmSg1EQRByOay26LK5OTOnZsdO3YwbNgw3r59m9XhZKkGDRrw5csXHj58qHhM7FqZPEmSOHLkCOXLl+fhw4fcvXuXv/76K0VJ9927d3FxcWHEiBGZEKkgKIdIvAVBELKxwMBArly5gq2tbVaH8lM1atRg8ODB9OnT54c7OP7qVFRU6NmzJ9u2bVM8Jma8k3r8+DF//PEH06dPZ9OmTRw8eBBjY+MUnz958mRmzJhB7ty5My5IQVAykXgLgiBkY1u3bqVjx47o6uaMra2nTp1KUFAQ69aty+pQslSvXr3YvXs3MTExgEi8vxUcHMyoUaNo2LAhrVu3xs3NjSZNmqRqjIsXL+Ln50ffvn0zKEpByBgi8RYEQcim5HJ5jigz+Za6ujo7d+5kxowZeHt7Z3U4WaZMmTKYmJhw9uxZIiIiCA4OxsDAIKvDylJxcXFs2rQJMzMzIiIiePz4MSNGjEBdXT1V48jlciZNmsScOXNSfa4gZDWxuFIQBCGbcnJyQltbmxo1amR1KKlStmxZZs6cSc+ePbl+/Xqivsu/k4Se3mZmZhQtWhQVld93ruvGjRuMGDECTU1NTp8+TbVq1dI81qFDh5AkiU6dOikxQkHIHL/vTwFBEIRsLmG2+0ft1LKrIUOGkDdvXubPn5/VoWSZLl26cOHCBTw9PX/bMpM3b97Qs2dPunTpwpgxY7h27Vq6ku6YmBimTp3KggULfusPMkLOJb5rBUEQsqGPHz9y+vRpevTokdWhpImKigpbtmxh1apV3L17N6vDyRJ6eno0b96cw4cP/3aJd1RUFAsWLKBy5coYGRnh5eVF9+7d0/0hcvPmzRQvXpxmzZopKVJByFwi8RYEQciGduzYgY2NzXd368sJihYtyvLly+nZsyfh4eFZHU6WsLe358qVK79N4i1JEidPnqRChQq4urpy69Yt5s2bh46OTrrHDg8PZ9asWSxYsEAJkQpC1hCJtyAIQjYjSRIbN27MUYsqv8fW1paqVasyadKkrA4lS/zxxx98/Pjxt1gE+PTpU6ytrRk3bhyrVq3i2LFjlC6tvM1sli9fTt26dbG0tFTamIKQ2UTiLQiCkM24uroSGxtLgwYNsjoUpVi9ejVHjhzhwoULWR1KplNTU6NgwYI8efIkq0PJMF++fGH8+PHUrVuXpk2b4u7uTosWLZR6jU+fPrFkyRLmzJmj1HEFIbOJxFsQBCGb2bRpE/369cuRiyqTo6+vz+bNm+nTpw+fP3/O6nAynYqKCs7Ozsjl8qwORankcjnbtm3DzMyMT58+4enpyZgxY8iVK5fSr7VgwQI6dOiAqamp0scWhMwkk37n7cUEQRCymS9fvlCiRAm8vLx+ub7PI0aMICgoiN27d2d1KJlGkiR0dHQoXbo0S5cuTfVGMdnV7du3GT58ODKZjBUrVmRoy8uAgADMzc159OgRRYoUybDrCEJmEDPegiAI2cju3btp0qTJL5d0Q/yspZubG3v37s3qUDLNp0+fyJUrF3369GH79u1ZHU66BQYG0qdPH9q1a8eQIUO4ceNGhveZ//PPPxkwYIBIuoVfgki8BUEQspFfZVFlcrS1tdmxYwcjRozg9evXWR1Opnj16hVGRkZ069aNY8eOERYWltUhpUl0dDT//PMPFStWpECBAnh5eWFvb5/hvbS9vLw4duwYEyZMyNDrCEJmEYm3IAhCNnH//n0+fvz4S/cotrS0ZPjw4Tg4OPxyNc/JefXqFcWLF8fAwID69etz6NChrA4p1c6ePUvlypW5ePEi169fZ9GiReTJkydTrj116lTGjx+Pvr5+plxPEDKaSLwFQRCyiU2bNtG3b99ffke+yZMn8+XLF9asWZPVoWQ4f39/RQ/vhC3kc4pnz57Rpk0bhg8fzuLFizl9+jRly5bNtOvfunVLUUsuCL+KX/unuyAIQg7x9etX9u7di4ODQ1aHkuHU1NTYvn07f/75J15eXlkdToZKmPEGaN26NQ8ePODVq1dZHNWPhYWFMXnyZGrVqkXdunXx8PDAxsYmU7vsSJLEpEmTmDlzJlpaWpl2XUHIaCLxFgRByAYOHDhAnTp1KFasWFaHkilMTU2ZPXs2PXv2JCYmJqvDyTDfJt4aGhp06dKFHTt2ZHFUyZMkiV27dmFmZsbr169xd3dn4sSJaGhoZHos586d4+3bt/Tu3TvTry0IGUkk3sL/2LvruKqyLYDjv0s3iCCChQkiBiq2I7aCHYiiYo8d49jdMnaNOnZ3KxZ2Yjd2AIqUIiJw4cb7g8cdGVABgYu6v5/P+4jn7rPPOlfesNh3nbUFQcgBfuaHKr+kd+/eWFhY/NSboiQ9XJnEy8uLdevWkdM6+d64cYOaNWsyb948tm/fzvr169XWRUShUDBq1CimTZuGlpaWWmIQhKwiEm9BEAQ1u3//Pi9evMDNzU3doWQriUTC6tWrWbZsGX5+fuoOJ0t8XuMNULlyZSQSSY6537CwMHr16oWrqytdunTBz8+PatWqqTWmbdu2oaOjQ6tWrdQahyBkBZF4C4IgqNmqVavo2rXrL7m6Z21tzZIlS+jUqROfPn1SdziZKiEhgZCQkGQrxxKJRLXqrU4JCQksWLAABwcHDA0NefjwIT169EBTU1OtccXHxzN27Fhmzpz50+zcKgifEztXCoIgqJFUKiV//vxcvnyZokWLqjsctenUqRMmJiYsWbJE3aFkmlevXlGjRg0CAwOTHQ8ICMDJyYnXr1+jp6eX7XGdOHGCgQMHYmNjo0q+c4olS5Zw4MABjhw5ou5QBCFLiBVvQRAENdqzZw9ly5b9pZNugEWLFnHw4MGfKuH6/MHKzxUsWJBy5cpx4MCBbI3n5cuXtG7dmp49ezJt2jSOHTuWo5Lu6Ohopk6dyowZM9QdiiBkGZF4C4IgqNGv+FBlaszMzFizZg09evQgIiJC3eFkiv8+WPm57OzpHRMTw/jx46lYsSJOTk7cv3+fFi1a5LhSjvnz5+Pi4oKTk5O6QxGELCMSb0EQBDV59uwZd+/epUWLFuoOJUeoU6cO7u7u9OnTJ8d1/ciI/z5Y+blWrVpx7tw5QkJCsuz6SqWS7du3Y29vz5MnT7h58yZjx47NkX2xw8PDmT9/PlOmTFF3KIKQpUTiLQiCoCarVq2iU6dOaumTnFNNnz6d+/fvs3nzZnWH8t2+VGoCYGRkRPPmzbPsPu/cuUPt2rWZPn06GzduZMuWLV9cfc8Jpk+fTrt27ShWrJi6QxGELCUSb0EQBDVISEhg7dq19OjRQ92h5Ch6enps3LiRIUOGpHgo8UfztcQbyJLuJhEREfTr14/69evj4eHB9evX+e233zL1Gpnt1atXrFu3jnHjxqk7FEHIciLxFgRBUINDhw5RpEgRSpYsqe5QchwnJycGDx5Mly5dUCgU6g4nw76VeLu4uPDu3Ttu37793deSyWT8/ffflCxZEolEgr+/P71791Z7e8C0mDhxIn369CFv3rzqDkUQspxoJygIgqAGbm5uuLu74+Xlpe5QciSZTEatWrVwd3dn0KBB6g4nQ8zMzHj27Bm5c+f+4pgxY8YQGSendLOePHwbRVScDBM9LezzmtC2Qn5yG327DOnMmTMMHDgQc3NzFixYQJkyZTLzNrLU/fv3qVOnDo8fP8bU1FTd4QhClhOJtyAIQjYLDAykXLlyBAYGYmBgoO5wcqxnz55RpUoVzpw5k6Pa3qVFVFQU1tbWREdHf7F7yO3ASLwP3uLC8/fo6ekhlf27uq+npYEScLGzpG+tYpQtYJbi/MDAQIYNG8alS5eYPXs2bdq0yXGdSr6lefPm1KpViz/++EPdoQhCthClJoIgCNlszZo1eHh4iKT7G4oWLcr06dPp1KkT8fHx6g4nXZI6mnwpEd54+SUeKy5zKfATEi2dZEk3QJxMgVSm4NiDEDxWXGbj5Zeq12JjY5kyZQrlypXD3t4ef39/2rZt+8Ml3RcuXODWrVv07dtX3aEIQrYRibcgCEI2ksvlrFq1SjxUmUY9evTAxsaGyZMnqzuUdPlafffGyy+Z5uNPbIKcb33mrFRCbIKcaT7+bLj0kj179uDg4MDt27e5fv06EydO/CF/gVMqlYwcOZKJEyeqZfdOQVAXLXUHIAiC8Cs5fvw4lpaWYpOQNJJIJKxYsYJy5crh5uZG1apV1R3SF9na2vLq1SskEgk6Ojpoa2vj7u7O0KFDqVy5MgA2BQoSHBSIppE5Nr+vQENbl/iQ5wSvGQhAoZEHVfPFBdwj8txG4t8+AST0+Ccf+W3ysmrVKjQ1NWnRogXPnz8nISGB/Pnz07FjR8aPH/9DrHz7+Pjw7t07OnfurO5QBCFbiRVvQRCEbCR2qky/vHnzsnTpUjp16kR0dLS6w/kmNzc37Ozs0NXVZceOHdSoUYMdO3YA8DFOBoA8+h3RN32+OEdc4D1Cto5FGvQAvULlMCzlAppaODbpSp06dXjz5g3m5ua0b9+epk2b8uLFCyZOnMjatWuz4Q6/j1wuZ9SoUUyfPv2H6LoiCJlJJN6CIAjZJCQkhJMnT9K+fXt1h/LDadmyJTVr1uTPP/9Udyjf1L17d8qWLYu3tzceHh7IZDJ69+5NQOh74hLk/x8l4cPlXSgS4lKdI/LMelDIyN14IHnajCN3o/5Yd57DQ6UNEdFS2rdvz8mTJ1m+fDnbt2/H1dUVgBcvXmTTXWbc5s2bMTIyolmzZuoORRCynUi8BUEQssm6deto1aoVJiYm6g7lh7RgwQKOHj3KoUOH1B3KNwUEBFC4cGEmTJgAwLt375izYb/qdQP7GihiIvl4I+W9KBKkSF8/BCDmyWUC5rkTtKQLkec2gVLBzhtBADx9+pTBgwfTtm1bfHx8yJcvX44v3ZBKpYwfP56ZM2f+ECUxgpDZRI23IAhCNlAqlaxcuTLTdyr8lZiYmLB27Vo6dOjA7du3sbCwUHdIX5T0cGW+fPlUxx69DFI9TGlYsiYJ4a+I8tuNro19snMVcdGgTOxyEv/2KYb2NYh5eIEPF7agoWfEw9KJcwYFBbFgwQLVebVr18bS0jKL7+z7LF++HAcHhxy/m6YgZBWx4i0IgpANzpw5g46ODlWqVFF3KD+0WrVq0aFDB37//Xdy6jYUCoWC169fkz9/fl69eqU6rtT7bIMYiQTT6u1RxHzg442Dyc7XNDABSeKP51x1e5C78UBMqrkDEPPEj6i4BCBx50uFQkFgYCCNGzdm48aNOboU5+PHj0yfPp0ZM2aoOxRBUBuReAuCIGSDpIcqxcfr32/q1Kk8efKEDRs2qDuUVEVGRmJmZoaWlhaTJk0CwNzcnGKlyycbZ2BfA21LW2L8zyc7LtHURsvcJvmk//8lQ0NHDxM9bT5+/Jg4ViIhf/781KxZE4DHjx9nxS1lijlz5lC/fv0famdNQchsotREEAQhi717945Dhw6xaNEidYfyU9DV1WXDhg3Uq1ePWrVqUahQIXWHlMzq1auRy+WUKlWKx48fo6WlxbJly4jIY8Xnv3dJ/r/qHb435QqwaeXWRPgs4P2JlcS9uEHMo4sA5CpbD3trY1q0aIFMJsPe3p7379+zf39i/XjDhg2z5R7TKzQ0lEWLFnHt2jV1hyIIaiVWvAVBELLYxo0bcXNzw9zcXN2h/DTKli3LsGHD8PLyQqFQfPuEbHTx4kUiIyORSqW4u7tz4cIF2rZtS5sK+VOMNbCrhnaeIimOG5WpT6463UGiwaf7p9E0Mie32xCMStagTfn81KpVizdv3rB+/XqOHj2KnZ0dc+bMYdSoUdlxi+k2depUPD09KVy4sLpDEQS1kihzapGcIAjCT0CpVFKmTBkWLlxI7dq11R3OT0Uul1O7dm2aN2/O0KFD1R2Oypw5cwgKCmLevHkpXuu14RrH/UO+uWNlaiQSaOhgxbKOFTMhyuzz4sULKlasiL+/P3ny5FF3OIKgVmLFWxAEIQv5+fkRFxeHi4uLukP56WhqarJu3TpmzpzJvXv31B2Oyte2i+/nUgw9rYxtGqMlUdLXpdj3hKYW48ePZ8CAASLpFgRE4i0IgpClVqxYQY8ePcRDlVmkcOHCeHt707FjR6RSqbrDAb6eeJctYMYYV3v0tdP341dXU4L00hYObViaY7u5pObOnTscP348R30iIQjqJBJvQRCELBIVFcXu3bvp0qWLukP5qXXt2hVbW1smTpyo7lAACAwMpECBAl98vWMVW+pbRoMsnm/+OqZQoK+twbgmDlzeOIudO3fSrVs34uPjMzXmrDJq1ChGjRqFsbGxukMRhBxBJN6CIAhZZOvWrdSpUwcrKyt1h/JTk0gk/PPPP6xdu5bz589/+4Qs9rUVb4Dg4GC2Te3PzPpWNCxlha6WBnpayX8c62lpoKulgU74Q7oU/EDHKrbY2Nhw9uxZ3r17R4MGDXj37l1W38p3OXv2LA8ePKB3797qDkUQcgzxcKUgCEIWcXZ2ZvLkyTRu3FjdofwS9u/fz+DBg7l9+7baVlhjY2PJlSsXMTExaGikXNtSKpW0aNECR0dHpk2bBkBEtJSdN4J4GPyRqLgETPS0sbc2pk35/Ny7fpkuXbrw8OFDdHV1gcSHSkeMGMGBAwc4dOgQxYrlvLpvpVJJ9erV6dOnD506dVJ3OIKQY4jEWxAEIQvcunWL5s2b8/z5czQ1M/YwnZB+PXr0AGDlypVquf7jx49xdXXl6dOnqb6+ceNGvL29uXbtmiqR/pZmzZrh4uLCH3/8kez48uXLmTBhAjt27FBtoJNT7Nu3j3HjxnHz5k3x/S8InxGlJoIgCFlgxYoVdOvWTSQd2WzevHmcOnVKtaFMdvtamcmbN2/4448/WLduXZqTboCZM2cyc+ZM3r9/n+z477//zvr162ndunWO2sVTLpczevRoZsyYIb7/BeE/ROItCIKQyWJiYti6dSvdunVTdyi/HGNjY9atW8fvv/9OaGhotl//Sw9WKpVKfv/9d3r37k358uVTOfPLHBwcaN68OTNmpNzhskGDBpw6dYrx48czfvz4HNHxZP369Zibm+Pq6qruUAQhxxGJtyAIQibbuXMnVapU+WpnCyHr1KhRAy8vL3r16pXtieiXVrzXr19PQEAAY8eOzdC8kyZNYtWqVQQEBKR4rVSpUly+fJnjx4/j6elJXFxchq6RGeLi4pgwYQLe3t6ihaYgpEIk3oIgCJksqXe3oD6TJk3i5cuXrFmzJluvm1ri/fr1a4YNG8a6devQ0dHJ0Lw2Njb07duXcePGpfq6lZUVJ0+eRC6XU6dOHcLCwjJ0ne/1999/4+TkRLVq1dRyfUHI6UTiLQiCkIn8/f15+vQpTZo0UXcovzRdXV02btzIiBEjePHiRbZd97+Jt1KppGfPnvTr149y5cp919zDhg3j6NGj3Lp1K9XX9fX12bJlC3Xq1KFy5cr4+/t/1/XS68OHD8ycOZPp06dn63UF4UciEm9BEIRMtHLlSrp06YK2tra6Q/nlOTo6MnLkSDp37oxcLs+WawYGBiZLvNesWUNwcDCjR4/+7rlNTEwYN24cI0aM+OIYDQ0Npk6dyoQJE3BxccHX1/e7r5tWs2bNwtXVlVKlSmXbNQXhRyPaCQqCIGQSqVRKgQIFuHjxYo7srfwrUigU1KlTB1dXV4YPH56l11IqlRgaGhIaGoqRkRGBgYGUL18eX19fypYtmynXSEhIwMHBgSVLltCgQYOvjj1z5gzu7u5MnTqVnj17Zsr1v+Tt27eUKlWKGzduUKhQoSy9liD8yMSKtyAIQibZt28fjo6OIunOQTQ0NFi3bh2zZs3i9u3bWXqtiIgI9PT0MDIyUpWYDBw4MNOSbgBtbW1mzJjBiBEjUCgUXx1bq1Ytzp07x19//cXw4cO/Of57TJkyBS8vL5F0C8I3iMRbEAQhk6xYsSLLVxaF9CtUqBCzZ8+mU6dOWdrx4/P67lWrVhEWFsbIkSMz/TqtW7dGV1eXzZs3f3NsiRIluHz5Mn5+frRp04aYmJhMj+fp06ds27YtU8ppBOFnJxJvQRCETPD8+XNu3bpFy5Yt1R2KkIrOnTtTvHjxL3YFyQxJiXdAQACjRo1i3bp1WVLrL5FImDVrFmPGjEnTLxK5c+fm2LFjGBsbU6tWLYKDgzM1nnHjxjF48GAsLCwydV5B+BmJxFsQBCETrFq1io4dO6Knp6fuUIRUSCQSli9fzqZNmzhz5kyWXCNp85zu3bszZMgQHB0ds+Q6ADVr1sTJyYnFixenabyuri5r166lRYsWVKlSJdPKbm7cuMHp06cZPHhwpswnCD878XClIAjCd5LJZBQsWJDjx4+Ljg453KFDh+jXrx937tzBxMQkU+ceNmwYz549IzAwkEuXLqGlpZWp8//Xw4cPqVmzJo8ePcLc3DzN523bto0BAwawdu3a795dslGjRjRt2pR+/fp91zyC8KsQK96CIAjfycfHB1tbW5F0/wDc3Nxo2LAhgwYNyvS5/f398fX1Zd26dVmedAPY29vTqlWrdPfNbteuHfv27aN79+4sWrQow9c/deoUT548Ec81CEI6iBVvQRCE79S0aVNatWpF165d1R2KkAbR0dGUK1eOWbNmZVpNvkKhIFeuXHTo0IGlS5dmypxpERwcjKOjI9evX8fW1jZd57548QI3Nzfq1q3LvHnzUv1lITxays7rQTx8G0VUnAwTPS3s85rQpnw+3OrVYvDgwbRv3z6T7kYQfn4i8RYEQfgOQUFBlClThsDAQAwNDdUdjpBGly5domXLlty6dYu8efN+93xLly5l0KBBPHr0iMKFC2dChGk3YcIEnj9/zoYNG9J9bmRkJO7u7mhra7N161aMjY0BuB0YyZLTTznzOHHreans31aEeloayORyJMEP2D6pB04F017mIgi/OpF4C4IgfIcpU6bw5s2bbF3lFDLH2LFjuXXrFgcOHEAikWR4nufPn1OpUiWioqKIiYnJljKTz338+JESJUrg4+ODk5NTus9PSEigf//+XL58mQMHDnD2jYJpPg+Jk8n5WoYgAfS0NRnjak/HKrYZjl8QfiUi8RYEQcgghUJBkSJF2L17N+XLl1d3OEI6xcfHU6VKFfr06ZPhOuWknTGrVavGxo0bCQgIyOQo02bp0qXs2rWL48ePZ+iXCKVSydy5c5l38BoG1TsSL//6eFlkCK+XdQfAfpwPY1xLiuRbENJAPFwpCIKQQb6+vpibm4uk+welo6PDxo0bGT16NM+ePcvQHH///Tfx8fHUr19ftXmOOvTo0YPAwECOHTuWpvG2trZIJBL27t0LQGhoKEuW/cPr01t5vXM6SsXXM2+JrgHGFZthXLEZsQmJK+T5ChREIpFw+vTp77wbQfh5icRbEAQhg8ROlT8+BwcHxowZQ6dOnZDJZOk699mzZ0ycOJE1a9bw+vVrtSbeSVvJDx8+HLn8G8vV/xEaGkqdOnV48fQxBiWqYNFsOBINza+eo6lvjHm9XpjX6wVAnExOVFz63j9B+BWJxFsQBCEDQkND8fX1pUOHDuoORfhOAwcORF9fn7/++ivN5ygUCrp27cro0aOxs7NLtl28urRs2RJDQ0M2bdqU5nPCwsKoU6cODx48wLBEFSyaj0SiqcXbTSN5NbMJ70+v5e3GEQTMbs3bDcOQfQgFEktNXs1swquZTQAIXNKN6PDEHTFr166NRCJh7dq1mX6PgvCjE4m3IAhCBqxbt44WLVpgamqq7lCE76ShocHatWuZP38+N2/eTNM5ixYtQqFQqPqBBwYGqj3xTtpKfuzYscTGxqbpnEGDBnH//n1KV62NTetRSDSTPxga5bcbTRMLNAxMkL72J/Js6p1TjMrUR0NHH4DWrVszaNAgHBwcvu+GBOEnlL2PXguCIPxgUu9jbMyK9VtYuzxt23ULOV+BAgWYN28eHTt25Pr16+jp6X1x7JMnT5gyZQqXLl1CUzOxJCMgIOC7d4HMDNWrV6dixYosWrSI4cOHf3N8UoJerI47N+Qpy0uMnBqTu0Efou8cJ8JnAfEhqdfCm9VoT/Sd4xAfS//+/XFxcfmu+xCEn5VIvAVBEFLxtT7G2hqQ0Hg8a5/pYFggkrIFzNQUpZCZOnTowL59+xg9ejRz585NdYxcLqdr166MGzeO4sWLq47nhFKTJDNmzKBGjRp0796d3Llzf3Vs8eLFefLkCQfmDCV3m0no5S+Z7HUdqyIAaOgm9qhXxMdlTdCC8IsQpSaCIAj/sfHySzxWXOa4fwhSmSJZ0g2QoAA0tTnuH4LHistsvPxSLXEKmUsikbB06VK2b9/OyZMnUx2zcOFCNDQ0GDBgQLLjOSnxtrOzo02bNkybNu2bY2fMmEH79u2RxcUQumMC0jePkr0ukWgmffHNuSQaiSmFQqH4xkhB+HWJxFsQBOEzGy+/ZJqPP7EJX988BECphNgEOdN8/EXy/ZPInTs3K1eupGvXrkRGRiZ77dGjR0ybNo3Vq1ejofHvj88PHz6gUCgwMzPL3mC/YsKECaxbt44XL158dVxYWBiVKlUiVyF7lNIYQreNR/r2aYauqW1iCcD48eMZPHgwgYGBGZpHEH5mIvEWBOGX8fz5c1q1akWePHnQ09Mjf/78NGrUiGfPnvHy5UskEgmdqhbm1dbJqnOiru7j1cwmvN00UnUs9uVt3m4cTsC8dgTMacPzfwYwYvYK7gRFAvD+/Xv69u1LgQIF0NPTo1KlSpw5cya7b1fIoEaNGtGkSRMGDhyoOpZUYjJx4kSKFSuWbHzSg5Xfs/tlZsubNy8DBw5k7NixyY4nJCRw6tQp3r9/D8CoUaO4e/cuc2ZMwdCuGgrpJ0K3jiU+9OsJe2py/+ZJ4aJFuXTpEgsWLCAkJCRT7kUQfiZi50pBEH4ZZcuW5c6dO9SpU4cSJUoQFBTE2bNnOXToEPnz56dw4cKqsXm7zEc3bzGiru7j/YkV6BZwJK/nTBTxcQQt8kSZIEU3X0kkugbEPb8OEg08Zu1iy9AWuLq6cvjwYZycnHBycmLLli0oFAoePXpEoUKF1PgOCGn16dMnnJycmD59Om3atGH27NkcOnSIEydOJFvtBvDx8WHhwoUcOXJETdGmLjo6mhIlSrB+/XrevHnDwYMHOX78OMWLF8fNzQ03NzfKly+PhoYG0dHRNJi8g9cSC1XJSHpIJNDQwYplHStmwZ0Iws9DPFwpCMIv4d27d9y5cwczMzN8fX1Vq5NSqRS5XM7DF59/LC7hw7lN5Gk7IcU88k/vUSZIAcjTbjIaOvoELuiAIjaK87ce8jI4XJWA7dmzh0KFCmFsbMyCBQuYPXs2ixYtyvJ7Fb6foaEhGzZsoHnz5uTJk4eZM2dy5cqVFEk35Kz6bkjc/v3WrVscOnQIXV1dGjVqRLNmzWjatCkLFy4kb968ycYfOnSIfv364VS3Be9sGhInS3+Ntp6WJn1din17oCD84kTiLQjCL8HY2BgjIyMiIyNxcnKiTp06/Pbbb9SvXx9DQ0MO332rGmtgX4OYh+eQBj9OMY92Lmv0S1Ql9vElQreNR6JrgCI2Cr1CZTEoUIqD90PR1NREJpNx/fp1cufOzf379wG4fft2tt2v8P0qV65Mz549adasGdOmTaNIkSKpjssJifenT5/w9fXl0KFDHDp0CENDQ9zc3Fi+fDkDBgygZ8+eNG7cONk5wcHBDBw4kJs3b7Jy5Urq1av32TMOaU++9bU1GONqT5n8Zpl8V4Lw8xE13oIg/BK0tbVZtWoVpqam3L59m3nz5tGyZUuKFi3K1atXeRYWrRprWs0dNLWIPJf6DoBGpWqjoZ+4oUjc8+tIdPQxsKuGVKnBs4h4/vjjDyBxIxFjY2N8fX0BePv2barzCTmXvr4+CoXiq/Xb6kq8nz9/zqJFi2jUqBHW1tYsWrSIkiVLcurUKR4/fsy8efNo0KAB3t7eybaSVygULF26lDJlylCiRAnu3r1LvXr1AOhYxZYxriXR19b8ZiMTiQT0tTUZ41qSjlVss/huBeHnIFa8BUH4Zbi7u9OsWTPOnDnDuXPnWLFiBSEhIUyZMgXd37qrxmmZWGJUpgHRN33Q0DVINkd82CvC9sxAoqOHTc+lSHQNebt+KO+OLUXLNA9R9nlY5e1N/fr1OX/+PPr6ibv5jRw5EktLy2y9X+H7PHjwgHnz5rFnzx48PDyoX7++qnf35xsrXTd0Rh6Zh5gzz2hbIT+5jXSzJJ6EhAQuXrzIwYMHOXToEBEREbi5udGzZ0+2b9+OiYlJquc1b96c2bNns2HDBipWrEivXr2QSCScOnUKR0fHFOM7VrGlTH4z/j79lFOPwpBAsvITPS0NlEBtO0v6uhQTK92CkA4i8RYE4ZeQkJCAn58fNWrUoGHDhjRs2BALCwuGDBnCx48fsdBN/p9D02ruRN85Toz/+eTzRAQCSjT0jNHOXQAALVMr5FFhJIQHYqKnTXx8PPXq1aNevXrI5XIaNGgAoFpVFHI+mUyGl5cXU6dOpW7dukyYMIFOnTrx99ZDLDv3IvnGSubFuBQs52bYY+b5PsbFzpK+tYplysZK4eHhHD58WPVgZJEiRXBzc2PdunVUqFAh1Zrz/5JIJEydOpVmzZqhq6vLlClT6NWr11fPLZPfjGUdKxIRLWXnjSAeBn8kKi4BEz1t7K2NaVM+637BEISfmUi8BUH4JUilUmrWrEnJkiVxcnLCwMCAPXv2AFC/fn2UlkbJxmsZW2BctiEfbxxMdlw3b3HQ1EYeFUrI9glo6BggDbwHSDAuVAp7a2PGjRvH9evXKVq0KH5+fty+fZsCBQowaNCg7Lpd4TvNmjULMzMzevXqBUDfvn1Zf/E5bZdfQCHRTLXHe9Kq8LEHIZx9HM4YV/t0l2AolUpu376tqtW+f/8+devWxc3Njfnz52NtbZ3ue/H19aV3796YmJjQuXNnevfuneZzcxvp8vtvRdN9TUEQUidqvAVB+CXo6ekxZMgQdHV18fHxYcOGDZiZmTFu3DiGDx9O49J5U5xjUs0diZZOsmNaZlbkaT0W3Xwlkb5+SOzza+hYFcWi6VD08pekTfn8ODg48OzZM9auXUtgYCDt27fnwoULmJubZ9ftCt/h7t27zJ07l5UrV6pquzdfCSCqaD3kpJ50fy69Gyt9+vSJ/fv38/vvv1OwYEHatGlDWFgYkyZNIjQ0lN27d9O9e3dV0j1x4kQkEgldunT56rxhYWF06tSJHj16sGDBAk6ePMk///xDeHh4Wt4GQRCygOjjLQiC8H+9NlzjuH/INxOr1Ig+xtnD1taWV69eAaCpqYmFhQVVq1Zlzpw5X+w6kh4JCQlUqVKFPn360KNHDwBuB0biseIysQnydM+nr63Jtl5VUtRBv3z5kkOHDrF9+3bOnj0LwJw5c3Bzc6NEiRJffZhz4sSJTJo0CS8vL9auXZvidaVSydq1axk5ciSdOnVi0qRJGBoaAtCvXz+0tbWZP39+uu9FEITvJ0pNBEEQ/q+fSzHOPQnPUIIl+hhnryZNmlC4cGGOHj3K3r17+fDhAydPnvzueb29vbG0tKR7938ftl1y+ilxsvR/TyjlMuIk8Pfppyz2KMfFixc5dOgQBw8eJCwsDFdXV9zd3VWJd1I3nO/x6NEjevfuzcePHzly5AhOTk7JXh8/fjwODg4MHDgwU35REQQhfUSpiSAIwv+VLWDGGFd79LXT959G0cc4+3Xv3p2FCxcye/ZsAB4+fAhAREQEv//+O7a2thgbG1O9enXOnTunOi8mJoaRI0dSrFgxDA0NKV++PHv37gXgzp07zJo1i9evX2NkZISpqSllyjlxcP9e1acg0fdOErxmEAFz2xI434OII4sTj9/x5dXMJrzdOJyIo0sImNuWDxe3IQ15wZrhnujo6FCrVi3+/vtvHBwcCAgIYOLEifTv318Vm0QiQSKR8PLlS2QyGQsWLMDR0REDAwOsrKyYPHlysvcgNjaW7t27Y2RkRNGiRfHy8qJ69eq0aNECPz+/FEk3gJWVFYMHD2bMmDGZ9m8hCELaiRVvQRCEzyQ9DDfN5yFxMvlXy04kksSV7ow8RCd8n1WrVnHy5EmOHz8OJPZMVygUNG/enAsXLlCzZk2qV6/O/v37adCgAbdu3cLOzo7u3buzdetWypcvT7Vq1Th8+DCtWrXi2LFjDBs2DE1NTfz9/enQoQNaWlqcuHCV+NBX6BSrysdbR3h3ZDFINDAoURWJljYJ794ki0sa9AB5zAcMHWqhZZYXecwHNLS0qFivOU6F83Do0CF27txJhQoV6NWrF127dmXNmjUAqodvTUxMmDBhAtOnT0dfX5/WrVsjlUpVv1wk2bFjB3Xq1KFQoUI8ePCA4OBgHj16RIECBb763v3xxx+UKFGCq1ev4uzsnFn/JIIgpIFIvAVBEP7jW32MNVGgpaUl+hir0cGD/3ab0dXVpUKFCly/fp0LFy5gbGxM+fLlAShevDg3b95kzZo1DB06lK1bt6KhoUG1atXQ1NSkVKlSnDlzhsGDB1OwYEHevHmDnp4ezZo1o3Tp0hjfiGbvrdcAfLy2H4BctbthUqkFkFhO8jmJjj7WneegofdvlxyJhhbaiiAMDbWxs7Pj9evXnDx5kpEjRzJ+/HhV4p1Ud61UKlm4cCEAmzZtomXLlkBi/fnn7OzsKFSoEPfu3QMSV8CT+sZ/jaGhIRMnTmTYsGGcOnXqq/XkgiBkLpF4C4IgpOJLfYzDgwN59/wue+eOFH2M1WjPnj00b96cK1euULNmTbp3787MmTMB+PjxIwsWLEg2/unTp7x8+RJI3Llx8eLFyV5/9OgRR48e5erVqwwbNoy2bdsCoGtkinGdXhg61EL2ISTxWD471XkSzeQ/RrUtCiZLuj9c2k7kmfWEABc/GxcWFvbFewsPDyc6OnEn1SpVqvw7t7Y2kJiYQ+IDmnXr1sXPzw9bW1sAoqOjsbCw+OLcSbp27crcuXPx8fHBzc3tm+MFQcgcosZbEAThK5L6GM9rV45VXs54t3Ag6PhakXTnABKJhAoVKmBoaIhC8e8nEjY2NsTFxaFUKlEqlcTExLB48WJVcqqjo0NYWBhKpRKpVErp0qXx9vYmX758NG7cmCdPnhAeHs7OnTuRRn8g8uwGIHGjJADpm8eqaykVyR+6lGhqJ/v7J//E+vKqbfsgk8nw9vZOPO//ybOmpqZqbNI9WFhYYGSUmLz7+fmpXpfJZDx//pxNmzYBUKdOHRYvXoypqWm63zstLS28vb0ZMWKEait5QRCynki8BUEQ0qFEiRK8e/fuqyuWQtZbtWoVgwYNonbt2kRGRmJgYICXlxdVq1blzZs3ODs707t3b1q0aIGNjQ1HjhzB0tISd3d34uPjqVy5Mr1796ZcuXI8fvyYDx8+AODk5ISrqytjxoxh9erVAGj+fwXbuGIzAN6fWk3Y3pmEH5xL6PYJX41T09AMgOeXj9CjRw9mzJiR7HUrKyt0dBJ7xXfo0IERI0YgkUgYOHAgAJ6ennTu3BkPDw+cnZ2pVKmS6hcIS0vL73oPmzZtirm5OevWrfuueQRBSDuReAuCIKSDhoYGFSpU4Nq1a+oO5Zd28OBBFi5cyL1796hRowYHDhwgT5487Nu3j969exMVFcXatWu5efMmrq6uqpKNVatWMXLkSDQ0NFizZg2PHj2idu3aNG7cGIB69erx6NEj1q1bx/nz56le8zesmiQ+9GhcrhG5m/yBjqUtsc+uEfv0ClpmKTde+lyuuj3RyVuUd2+DePbsWYqWgTo6OqoWhtu2bWPJkiUATJo0iXnz5lG4cGG2b9/Orl27+PjxI1euXKFGjRqZ8h5KJBJmzZrF+PHjiYmJyZQ5BUH4OrGBjiAIQjqNGDECQ0NDxo8fr+5QhAySSqVUrFiRESNG0LFjx6+O/Z6NlUBJUZ1oQndPIy4uju7du+Pl5ZWmrd+joqIYPXo0u3btYu7cuXh4eGTJg5Du7u6UK1eO0aNHZ/rcgiAkJ1a8BUEQ0snZ2ZmrV6+qOwzhO0yZMoUiRYrg6en5zbH9XIqhq5mxH5cSuYw3vmtYtGgRGzdu5NmzZzg4ONCiRQsOHjyITCZLcY5SqWT37t04ODgglUq5f/8+7du3z7LuI9OnT2fu3LmifEoQsoFY8RYEQUinV69eUblyZYKDg0Urth/QtWvXcHNz4/bt2+TN+/VSEUjcdKdGl1G8t62N8j8PT36NvrYGoxuXRP/1Nf744w9+++03Zs2ahZGREdu3b2flypUEBgbStWtXunXrRuHChQkMDKRfv348efKE5cuX89tvv33PrabZgAEDkEgkqjaGgiBkDbHiLQiCkE4FCxZEoVAQFBSk7lCEdJJKpXh5eTFv3rw0Jd1SqZRWrVpRMP4VcZc2o6OZuHHS10gkoK+tyRjXknSqakubNm148OABBQoUoHTp0qxatQovLy8uXbrEkSNHiI6OxtnZGTs7O0qVKkW5cuW4detWtiXdAOPGjWPTpk08ffo0264pCL8ikXgLgiCkk0QiEeUmP6iJEydiZ2dH+/btvzk2ISGBdu3aYWBgQEhICEObV2Jn7+o0dLBCV0sDPa3kP0L1tDTQ1dKgoYMV23pVSbabqZGRETNmzOD8+fMcOnQIJycnzp49i6OjI507d6ZQoUJoaWnh6OjI0qVLGTlypGpjnOyQJ08e/vjjD7GVvCBkMVFqIgiCkAGTJk0iLi4uRXs4Iee6cuUKTZs25c6dO1hZWX11rFwux9PTk48fP1K6dGlu3bqFj48PGhqJyfbnGyvtPniYBrVrUrGYNW3K5/9mj3elUsnOnTsZPHgwpqamhIWF8ddff9GlSxckEgnPnz9nzZo1rFmzhgIFCtCjRw/atWun6u2dVWJiYihRogS7du2icuXKWXotQfhViRVvQRCEDBAr3j+WuLg4vLy8WLhw4TeTboVCQY8ePQgLC2PAgAFs2LCBdevWqZJuSL6xkvWTfXQrqcnvvxVN08ZKEokEAwMDtLS0kEgkKBQKoqKiVBvZFClShClTpvDy5UvGjh3LwYMHKVCgAD179sTPz4+sWi8zMDBg0qRJDB8+PMuuIQi/OpF4C4IgZICzszPXrl1LtmOikHNNmDABR0dH3N3dvzpOqVQyYMAAnjx5wsqVK+nRowdr1679arJuY2PDmzdv0hRHcHAw7u7uDBo0iJUrV3L//n3Onz/P/v37KV++POfOnVON1dLSws3NjT179vDgwQOKFi2Kp6cnZcqUYcGCBURERKTt5tPBy8uL8PBwDh48mOlzC4IgEm9BEIQMsbS0xMzMjCdPnqg7FOEbLl26xLp161iyZMlXu9AolUqGDx/OlStXOHDgAP3796djx47Ur1//q/NbW1t/M/FWKBQsW7aMMmXKULx4ce7evauat2TJkvj6+jJ27Fg6dOhA586defv2bYprjBw5kidPnrBo0SKuXr1K0aJFad++PSdOnMi0XwA/30o+tVaHgiB8H5F4C4IgZJAoN8n5YmNj6dq1K4sWLSJPnjxfHTtp0iSOHTvG0aNHWbt2LREREUyZMuWb1/jWive9e/eoWbMm69ev59SpU0ybNg19ff1kYyQSCe7u7jx48IC8efNSunRpFi5cmCL5lUgkuLi4sHHjRl68eEH16tX5448/KF68ONOnT0/zyvvXuLm5kSdPHtauXfvdcwmCkJxIvAVBEDJIJN4537hx4yhbtixt27b96jhvb2+2bt3K8ePHefHiBdOnT2fLli1oa3+7b/eXEu/Y2FhGjx5N7dq16dSpE+fPn8fR0fGrcxkbG/PXX39x5swZ9u7dS4UKFTh//nyqY3PlykX//v25desW27ZtIyAgAEdHR5o1a8b+/fszvGItkUj466+/mDBhAp8+fcrQHIIgpE4k3oIgCBkkEu+c7cKFC2zatIklS5Z8ddyiRYv4559/OHHiBPr6+nh4eLB48WIKFy6cpuuklnj7+vpSunRpnj59yp07d+jdu3eyhzO/xcHBgRMnTjB69Gg8PDzw8vIiJCQk1bESiYSKFSuybNkyAgMDadWqFX/99RcFCxZk9OjRGerNXalSJWrWrMm8efPSfa4gCF8mEm9BEIQMqlChArdv3yYhIUHdoQj/ERMTQ9euXVmyZAkWFhZfHLdq1Spmz57NiRMnyJcvH3379sXFxYV27dql+VqfJ95hYWF06tSJHj16MH/+fLZv3461tXWG7kEikdCuXTv8/f2xsrLC0dGRRYsWfXUl29DQkC5dunD+/HlOnDhBfHw81apVo06dOmzevJm4uLg0X3/atGnMnz+f0NDQDMUvCEJKIvEWBEHIIBMTEwoWLMj9+/fVHYrwH2PGjKFixYq0atXqi2M2b97M+PHjOX78OLa2tqxfv57r16+zYMGCdF0rKfFes2YNjo6O5MmTh3v37tGkSZPvvQ0gefnJnj17qFChAhcuXPjmeSVLlmT27NkEBQXRt29f1q9fT/78+Rk4cCB37tz55vlJXVQmT56cGbchCAJiAx1BEITv0rlzZ2rWrEnPnj3VHYrwf+fOnaNdu3bcvXuX3Llzpzpmz5499OnTB19fXxwdHXn8+DHVq1fn5MmTlC5dOl3Xe/jwIQ4ODpQrV46VK1dSvnz5zLiNVCmVSrZt28aff/5JvXr18Pb2/mZf8s+9evWK1atXs3r1aqytrenRowceHh6YmJikOj4sLIySJUty6dIlihcvnlm3IQi/LLHiLQiC8B0qVaok6rxzkE+fPtG1a1eWLl36xaT78OHD9O7dGx8fHxwdHZFKpXh4eDBp0qR0Jd1SqZTJkydTo0YNzMzM2Lp1a5Ym3ZBYfuLh4YG/vz8WFhY4OjqyePHiND9IWahQISZNmsTLly+ZNGkSR48epVChQnTr1o2LFy+m2DjH0tKSoUOHMnr06Ky4HUH45YjEWxAE4TuIByxzltGjR1O1alWaN2+e6usnT56kc+fO7N27V5Ukjxw5EltbW/r06ZPm65w7d45y5cpx7do1bty4gb29fbbWQhsbGzN79mxOnz7Nrl27cHZ25uLFi2k+X1NTk8aNG7Nr1y4ePnxIyZIl6dq1K46OjsybN4/w8HDV2EGDBnH58mUuX76cFbciCL8WpSAIgpBhsbGxSn19fWVMTIy6Q/nlnT59WmljY6OMiIhI9fULFy4oLSwslKdOnVIdO3jwoLJgwYJfPOe/3r17p+zRo4cyX758yp07dyoVCoVSqVQqW7durdy2bdt330NGKBQK5ebNm5U2NjbKLl26KENCQjI8z9mzZ5WdO3dWmpqaKt3d3ZXHjh1TyuVy5erVq5U1atRQ3a8gCBkjVrwFQRC+g56eHiVLluTWrVvqDuWXFh0dTdeuXVm2bBnm5uYpXr9+/TotWrRg48aNuLi4APDmzRu6d+/Oxo0bUz3nc0qlki1btuDg4ICuri7379+ndevWqp0w07NtfGaTSCS0b98ef39/zM3NKVWqFEuWLEEul6d7npo1a7Ju3TpevnyJi4sLI0eOpEiRIgQEBBAWFsb+/fuz6C4E4dcgEm9BEITv5OzszJUrV9Qdxi9t5MiR1KxZk6ZNm6Z47e7du7i5ubFixQoaNmwIgFwup2PHjvTt25eaNWt+de7nz5/TuHFjZsyYwZ49e1i8eDGmpqbJxqgz8U5iYmLCnDlzOHXqFDt27MDZ2ZlLly5laC4zMzP69OnD9evX2b17N6Ghobx+/RpPT0927twpWmgKQgaJxFsQBOE7iTpv9Tp58iR79+5l/vz5KV579OgRDRs2ZP78+cnqvmfMmIFCoWDMmDFfnDchIQFvb2+cnZ2pXbs2169fp0qVKqmOtbGxITg4+LvvJTM4Ojpy6tQp/vzzT9q0aUO3bt2+q/68fPnyLFmyhLdv36o25SlQoAAjRozg8ePHmRi5IPz8ROItCILwnUTirT4fP36ke/fu/PPPP+TKlSvZay9evKB+/fpMmzYNDw8P1fELFy6waNEiNm7ciKamZqrz+vn5UbFiRU6ePMnVq1cZMWLEV7ePzwkr3p+TSCR06NABf39/zMzMKFWqFH///Xe6y08+Z2hoyPr164mOjsbHxweA3377jVq1arFhwwZiYmIyK3xB+GmJxFsQBOE7OTg48Pr1ayIjI9Udyi9n+PDh1K5dG1dX12THg4KCqFu3LiNHjqRr166q4+/fv6dDhw6sXLmS/Pnzp5gvKiqK/v3706JFC0aMGMGRI0coUqTIN+OwtrbOUYl3EhMTE+bOncvJkyfZtm3bd5WfAFSsWBEXFxcOHjyIt7c3AQEBDBo0iC1btlCgQAH69evHzZs3M/EOBOHnIhJvQRCE76SlpUW5cuW4fv26ukP5pfj6+nLo0CHmzp2b7HhISAh169alb9++9O3bV3VcqVTSo0cPWrRokaIWXKlUsnv3bhwcHIiLi+P+/ft06NBB9fDkt+S0Fe//Kl26NKdPn2bo0KG0bt2a7t27ExYWlqG5pk2bxoIFCwgJCUFHR4dWrVrh4+PDrVu3sLKyokWLFlSoUIFly5bx4cOHTL4TQfixicRbEAQhE4hyk+wVFRVFjx49WLFiBWZmZqrjERER1KtXD09PT/78889k5yxfvpznz5/z119/JTseGBhIixYtGD16NJs3b2blypXf7HLyX2ZmZsTHxxMdHZ3he8pqEokET09P/P39MTExoVSpUixdujTd5SeFCxemc+fOTJo0KdnxAgUKMH78eJ4/f86MGTM4efIktra2dOnShfPnz6fYnEcQfkUi8RYEQcgEIvHOXsOGDaN+/fqqLiUAkZGRNGjQADc3N8aNG5ds/L179xg3bhxbt25FV1cXSOxssmDBApycnChfvjy3b9/mt99+y1A8EokkRz1g+TWmpqbMmzePEydOsGXLFipVqoSfn1+65hg7dizbt2/n0aNHKV7T1NSkQYMGbN++ncePH1OmTBl69epFyZIlmT17drZuNCQIOY1IvAVBEDKB2Do++xw7dowjR44wZ84c1bHo6GhcXV2pXr06M2bMSFYiEhMTQ7t27Zg1axZ2dnYA3Lx5kypVqrBnzx7Onz/PhAkTVAl5RuX0cpP/Kl26NGfOnGHIkCG0bNmSHj16pLn8JHfu3AwbNuybW8lbWlryxx9/cP/+fVavXs2DBw+ws7OjTZs2HDly5Lse9hSEH5FIvAVBEDJB0aJFiY6OJiQkRN2h/NQ+fPhAjx49WLlyJSYmJgDExsbSrFkzHBwcmD9/foq67CFDhlCuXDm8vLyIjo5m6NChNGzYkL59+3Lq1Cns7e0zJbYfLfGGxJX6jh074u/vj5GREaVKlWLZsmVpSogHDhzI1atX07RVvUQioVq1aqxevZpXr17RoEEDxo8fT+HChZk4cSKvXr3KjNsRhBxPJN6CIAiZQCKRULFiRbHqncWGDh1K48aNqV+/PgBSqZRWrVphbW3N8uXL0dBI/mNtx44dnDhxgqVLl+Lj44OjoyMhISHcu3ePrl27pvnhybT4UUpNUmNqasr8+fPx9fVl06ZNVK5c+ZubQunr6zNlyhSGDRuWrvptExMTevXqxZUrVzhw4ADv3r2jQoUKNGrUiJ07dxIfH/+9tyMIOZZEKZ52EARByBRjxoxBU1OTyZMnqzuUn9Lhw4fp06cPd+/exdjYmISEBNq1awfA9u3b0dLSSjb+5cuXVKpUiXXr1rFmzRquX7/OsmXLVEl7Zvvrr78IDQ1l9uzZWTJ/dlEqlWzcuJHhw4fTtGlTpk+fjoWFRapj5XI5Tk5OTJo0iZYtWxIeLWXn9SAevo0iKk6GiZ4W9nlNaFshP7mNvlzKExsby+7du1m5ciUPHjygU6dOdO/enZIlS2bVbQqCWogVb0EQhEwiHrDMOpGRkfTq1YtVq1ZhbGyMXC7Hy8uLuLg4tmzZkiLpTkhIwMPDg5o1a9K5c2eKFSvGvXv3sizphh+z1CQ1EomETp064e/vj76+Pg4ODixfvjzV8hNNTU3++usvhnsvoef6q1T3Psk838fsvfWGkw9D2XvrDfN9H1PN+yS/b7zG7cDIVK+pr6+Pp6cnp06d4vz582hra1OnTh1q1KjB2rVr+fTpUxbftSBkD7HiLQiCkElev35N2bJlCQsLy9QSBgG6du2Kvr4+f//9NwqFgl69evH8+XMOHTqEvr5+ivE9e/Zk586dlCxZkuXLl1O6dOksj/HkyZNMnjyZ06dPZ/m1stPt27fp168fUqmUJUuWUKlSpWSvb7j0kvF7bqHU1AK+/H0vkYCeliZjXO3pWMX2m9dNSEjAx8eHlStXcuHCBdq1a0ePHj0oX768+P+X8MMSK96CIAiZJF++fOjo6PDy5Ut1h/JTOXToEGfOnOGvv/5CqVQyaNAg/P392b9/f4qkOzY2Fk9PT1avXs2oUaM4f/58tiTd8POseP9X2bJlOXfuHAMGDKB58+b06tWL8PBwADZefsn0w/4oNbX5b9Id9Hc3Xs1sQtyrOwAolRCbIGeajz8bL7/85nW1tbVp3rw5Bw4c4O7du+TPn5+2bdtSvnx5lixZwvv37zP7VgUhy4nEWxAEIROJcpPM9f79e37//XdWr16NoaEhI0eO5NKlS/j4+GBkZJRs7IkTJyhVqhS7d+9m06ZNDB8+PMXDllkpKfHOaR8k29raqvqMx8bGAnDr1i0kEkmaV44lEgmdO3fG398fPT09SpUqxcRFa5jq409sgiJd8cQmKJjm85A7QZFpPidfvnyMGTOGp0+fMnv2bJYsWYKFhYXqHtasWZOuGARBXUTiLQiCkIlE4p25Bg8eTMuWLXFxcWHKlCn4+Phw9OhRTE1NVWPCwsLo3Lkz3bp1w9zcnMGDB+Ph4ZHtsRobGwPw8ePHbL92WgQHB7N06dLvmsPMzIyFCxdy9OhRtt55R5xUlqF54mRy/j79NN3nyeVy6tatS968efntt98wNDQEYNSoUXh7e/P27dsMxSMI2UUk3oIgCJlIJN6ZZ//+/Zw/f56ZM2cya9YsNm/ejK+vL7lz5wYSu2+sXbsWR0dHLCws6N27N9ra2mrrKpPTd6+USCR4e3sTExOT6msSiURVJjVx4kQkEgldunQBYO3atUgkEsqWLcsff/xB9Ro1eLF3AfGhL4g8u4GAee68Xtqd2Bc3UswdH/KMN6sHEDC3LaG7piKPjUKphFOPwjh07CQuLi7kypULGxsbunXrRkREBJDYlSYprmXLlmFjY0ODBg2AxHr6U6dOUaxYMSCxpv/p06eULFmSli1bcujQIWSyjP1SIAhZSSTegiAImahixYrcuHFD7Mj3nd69e0efPn1Ys2YNa9euZenSpfj6+mJlZQXA48ePqVOnDosWLcLHxwdPT0/mzZvH5s2b0dbWVlvc1tbWObbOu23btoSGhrJkyZIMz3H37l38/PywzF+E+PBA3m4ZzadHF9C1sUP2IYQInwUpzok8vxkdq6Jo6JsQ++Qy7w4vBiA+9CUtmjTi+vXrNGrUiBIlSrBmzRratm2bolxnzJgxNG7cmGrVqqUaV9GiRVmxYgUBAQG4ubkxZcoUbG1tGTduHC9evMjw/QpCZhOJtyAIQibKnTs3efLk4dGjR+oOJccLj5ay7MwzBm+7Sbd1Vxm87SbLzjwjIlrKwIEDadOmDc+ePcPb25sTJ06QP39+pFIpkydPplq1ajRr1gw/Pz9KlCiBh4cHixcvpnDhwmq9p5z8gGW7du1wcHBg1qxZREdHZ2gOQ0NDfH19qeg+AACl9BOWLUdj2WIUAPKPEchjPiQ7x6xmRyzcBpOn1RgAYh5fRBEfS/i1Q8gSEihVqhRWVlaUK1cOXV1dTp06leL/Pzt27GDVqlVMmzbtq/EZGxvTo0cPLl++zOHDh/n48SOVKlWifv36bNu2DalUmqH7FoTMovXtIYIgCEJ6JJWbODg4qDuUHOl2YCRLTj/lzOMwAKSyfx/O09N6y+yj/sg1HOhuX4CxY0dy6tQpChcuzLlz5/j9998pWrQoN27coGDBgiiVSvr06YOLiwvu7u7quiWVnJx4a2hoMGHCBNq1a8fixYu/OvZLn9jY2tqir69PgpaB6pi2eT4kGpqqvyvj48Dg3xp8bYsCiX/mLvDv/B8jkH8IAcDPzw8/P79k13n69CmOjo6qv1evXv1bt5dC6dKlmT9/PjNnzmTv3r2sWLGCAQMG0LFjR7p3706pUqXSPacgfC+x4i0IgpDJRJ33l228/BKPFZc57h+CVKZIlnQDxMkUyJQSlPnKsOK5IYMW7cTS0pKePXvSvn17pkyZwv79+ylYsCAA69ev58aNGyxYkLLEQR1ycuINieUmpUuXZvv27cmOGxgkJtJRUVEA3Lt3L9XzNTUTE2wj3X8T7c+T7tQkhAcm/hkR+O88xrnRNE0sG3J3dyc0NBSlUolSqeT58+c0adIk2Ry6ul/e9fJb9PT08PDwwNfXl8uXL2NgYECDBg2oVq0aq1evzvDqvyBkhEi8BUEQMpmzszNXrlxRdxg5RpcuXZBIJLTqMZhpPv7EJsj5dsc9CRItXVZci8CxRR90dHS4f/8+rVu3VrXAe/z4MX/++Sfbtm1TJY7qltMTb4lEwoQJE1LUUDs5OQHQv39/evbsyb59+746j21uwzRfM/LcRsIPzSd0d2KZiH6Jqmjo6GNatgESDU22b9+OjY0Nenp6mJqaUqRIERYtWsSFCxe+OOfMmTPp0qULAQEBAKxcuZIuXbpw/vz5r8ZSpEgRpk6dyqtXrxg9erTql7hevXpx5cqV724F+bXyKUEAkXgLgiBkuvLly3Pv3j3i4+PVHcp3S+oBvXfvXtWxwYMHJ+t4kVZnn4Snu+dzglKCYc1O/D5qWrIWglKpFA8PDyZPnpxtG+SkRU5PvAFatWpFuXLlkh1btGgRpUuX5tatWwQFBdG1a9evzlHPwSrN1zOr0YH4kGcoYj6gX6wyuRv1B8AwX3H2HTpC7dq1MTExQUtLCwsLC+rXr8+DBw9YuHChao7q1avTs2dP5s2bx9GjR9m3bx/r1q1TbaJz4cIF1q1bx9OnaWtRqKWlRZMmTdi7dy/379+nSJEidOjQgbJly7Jw4ULevXuX5vuDxPKpXhuuUd37JPN8H7P31htOPgxl7603zPd9TDXvk/y+8Rq3AyPTNa/w8xFbxguCIGSB0qVLs2bNGipWrKjuUL6Lra0tr169Ys+ePbRo0QJITLwXLFiAl5cXa9eu/eYcXbp0Yd26dZjWaI9ZDc90xyCRQEMHK5Z1/Pe9HDx4MAEBAezatStHbR/+5MkTGjdunOYE8EfWa8M1jvuHpOHTi5RS+zf9krCwMB48eJDif58+faJkyZI4ODgk+1+hQoUytHGSQqHg7NmzrFy5koMHD+Lq6kqPHj1wcXH56nwbL79kms9D4mRf/yRHIgE9LU3GuNrTsYptuuMTfg5ixVsQBCEL/Cp13qdPn0YikWBra8u0adOwsLAgX758zJkzRzUmLiHxQT1FzEdCd04mYHZrgtcOJj7kuWpM2P5ZBC3x4tWsFgTMbcvbzaOJD30JJG41vqq/GxKJhJkzZ1K0aFEWLlzIx48fiYyMVM3x999/U6BAASwsLPjrr79SXa3PakntBH+FNa1+LsXQ0/p6ffeX6Glp0telWJrGWlpaUqtWLfr06cOiRYs4ceIEwcHBvHz5krlz51KtWjXevHnDokWLqFWrFsbGxlSoUIFOnToxY8YM9u3bx5MnT77Z4lNDQwMXFxc2btzI8+fPqVq1KoMHD6Z48eJMnz491U8yEpPutJVPKZUQmyBnmo8/Gy+/TPF60vfr6dOn0/S+CD8mkXgLgiBkgV8l8U4SEBDA1q1bady4MaGhofz5558cOHAAgFcRiRu2fLzpg0RTCx2rwsS/fUrozkkoZYnlOPIPoegWcMSobEN0rIoiDbhD2L6ZKa4zadIk3rx5g7GxMb6+vsydOxdI/AWgX79+vH79mgYNGrBhwwYCAwNTnJ/VjIyM0NLS4sOHD98e/IMrW8CMHhXMUSaks35ZHk/e4AsUM9f5ruubm5snK0E5cuQIAQEBqh0669aty/v371mxYgUNGzbE2NiYsmXLqh7S3bVrF/7+/iQkJCSb19bWlty5czNjxgwuX77M1q1buX79Ovny5UMikbB//35kMhm3AyOZ5vMw1fKpyHObeDWzCeEH56V4LTZBwTSfh9wJivyu+xd+TCLxFgRByAK/WuKtqanJqVOn2LBhA/37J9bwrl+/HoAPsYmJjX6xSli2HI1Vh5loGJgh/xhB7MvbAFi0GIGujT0aOvroWNoCIIsIQvYxcRfDpNVEGxsbRo8ezeDBgwG4efMmABs3bgTAy8uLzZs3c/LkyQyVG2SGH6HOOzNERESw7E9PmuSToq+tybcqfiQS0NfWZEKz0uSLfUGtWrV4/fp1psdlYmJCpUqV6NKlC3/99RcHDx7k+fPnhIWFsWbNGtzc3IiNjWXDhg00b94cExMTSpUqRdu2bZkwYQKfPn0CIDg4mGXLluHs7My4ceNU83t7e1OoUCH6/b1f9WlOesXJ5Px9+ucvRxJSEn28BUEQskCZMmV49uwZnz59wtAw7R0gchp9fX2AZA+KJm1C8nknEUtLSywsLACwt7cHICgoCIAEeeKKYFI/Z4mmFlpmVsTHRCL/GE7Cu9cErx2MMj42xfUVMR/AOLfq70ZGRowePVr14F1SK7ikBK5kyZLJ4nn79u133X9GJCXeP3Mf9/j4eFq3bk2rVq3wHtKeO0GR/H36KacehSEhsS1kEj0tDZRAbTtL+roUo0x+M7pU34C3tzeVK1dmz549ODs7Z3nMhoaGlC9fnvLlyyc7HhcXx+PHj1W14zExMarXhg8fzqlTp1Q7pgIcP36cUxev4jF0KrEvb6OIi0bboiBmNTqgX6QCkec28eHCFgA+3TvBp3sn0C3gSF7Pmciiwok8u564gLv88ymSk1OKsGnjhmT3f/PmTf7880/8/f2pVasWmzZtIleuXFn87gjZRax4C4IgZAEdHR1Kly7NjRs31B3KdylatCgAly5dAhI3Vkna7KRYsX9rdMPCwggPDwfg4cOHAOTPnx8Abc3EHzVJ/ZyVchmyyMTNUzSNLYh9dg1lfCzalrYUGLyN/AM2fjGesWPHoqmpmeKBynz58gGJDzcChIeHq+LJbj/7irdSqaR3797kypWLGTNmAFAmvxnLOlbk4og6DKlfgpbl8lHXPg8ty+VjSP0SXBxRh2UdK1ImvxmQ2NZw5MiRLFmyBFdXV7Zs2aK2+9HT06NMmTKqLjmWlpYAtGnTBrlcjpmZGdra2qrx5ubmtG7rTvQdXzT1TTAoXiWxdGrHJOKCHqCbzx4dGzsgcdMg44rNMLCvjiIhjpAto/l07yQSLR1MStdBrm2Q4ntl7NixlCpVCj09PQ4fPqwqpxJ+DmLFWxAEIYsklZvUrFlT3aFkWM+ePTl06BDz58/nwoULvH//nqdPn2JsbEz79u1VW3srFApq165NuXLl2Lp1KwCdOnUCwFQ/MWmJfXqFsD3TkUe/QxETiaaROXqFyhAbn7jCKHv/hne+/xAf+jyVSBJrTZKSov/q1KkTq1atYs2aNcTExHD37l0UivS1LswsP3viPWvWLG7dusW5c+dSlPPkNtLl99+Kpnmu5s2bU7hwYZo3b86DBw+YNGmS2kqE/qt9+/Y8ePCAo0ePsnv3bpYtWwbAyZMnqV69OhIdfaw8vdHQ0UND34SP1/bx8cYhLJsNQ/r6IfFvHqFjXQLzer0A+PTwPLL3b9A0Mse66wI0tPVoVi4frq7Jd9CcOHEiw4YNY8KECUyePFlVTiX8HHLGd7cgCMJP6Geo827evDkbN26kfPnyPHz4kA8fPlC/fn1OnjyJtbW1alyBAgXo3LkzR44cwdLSEm9vb5o1awZAodyJJSnGTq4oZQnEh7xAx6oolm3Go6Gti4F9DYzKNAANTeJe3cK0atsUcUj4egFxrVq1WLJkCdbW1hw5cgRPT09VecD37HqYETY2NgQHB2frNbPLnj17WLRoEQcOHMi0EqoyZcrg5+fH6dOnadOmTY7ZSVJDQ4MJEyYQFhbG4sWLVceTSqi0jC3Q0NEDQDt34qc78g+hX5xP9iHxUx5ty0JoaCeeFxWXkGw1Hf7dzMjMzAwgx7wfQuYQK96CIAhZxNnZmSlTpqg7jO/m6emJp+e3+28PGzaMYcOGpTg+Y+pkLmvYo7QpgySV1UyJhia5XQeS23Wg6phhyd/+HaBQ0GXhAVZ4VVIdGjx4sOoBy8/j7Nu3L5CYHI0ePRqAEiVKfDP2zGRtbf3VXRd/VDdu3KBXr14cOXJEVdqTWfLkyYOvry99+vShRo0aqh0l1a1t27ZMnTqV7du3q47Z2toCIPsYjiIhDg1tPRLeJSbjmqZ5EgclfZ8r//3URcs08RfBhLBXKBKkaGjrYqKnjUwmQ0vr33Qs6euc1J9eyDxixVsQBCGL2NnZERoaSkREhLpDUZutW7fi4OBAwq1D6GlnrOezrrYmA+p+O3l2cnKif//+TJgwgbp166JQKHB1dVXVqWeXn7HU5PXr1zRv3pzly5dToUKFLLmGrq4uq1atwsvLiypVqnDx4sUsuU56SCQSJkyYkKwve8WKFbEtWRZlfCwhG0cQfmAOH68fBCQYO7kCoGWcWBIV+/w6744t49PDC+gXrYhWLhvk0e8IXjOIyKNLODSjF4cOHVLHrQlqIhJvQRCELKKpqUn58uW5du2aukPJdnFxcXh5eeHl5UWNGjV4fPk4Q2rbopSlr+eztkTJuCYOqofyvqZ8+fJs3boVb29vlEolf/75J5s3b87gHWTcz5Z4f/r0iWbNmtGvXz9atWqVpdeSSCQMGTKEVatW0aJFC9atW5el10uLVq1aUa5cOdXfNTQ08Dl0AJOy9ZHHfCDmyWV0rIpg2WYcegUS67UN7GugV7g8ygQpH28cRBpwBw1tPazaT8OwVG2UMilRd3whNgobGxs13ZmgDmLLeEEQhCw0bNgwTE1NGTt2rLpDyTaPHz/G1dWV169fM2rUKFUP5DZt2iAvXI0HevbEJyj+/Tg+NUoFGkoFk1qUpVNV2+wJPJPExMSQK1cu4uLifvhyAYVCQZs2bTA1NWX16tXZej8PHjygWbNmtGrVihkzZqCpmbFPTLJKrw3XOO4f8s0dK1MjkUBDByuWdayY+YEJOZpY8RYEQchCP8MDlumxfv16ypcvT1hYGPv27WP8+PFIJBLWrFnDkydP2Dq1H44hvhTRjUZXSwM9reQ/hvS0NNCSKJG8vsvm7s4/XNINif3NDQwMePfunbpD+W6jR48mIiKC5cuXZ/svEQ4ODvj5+XHt2jVatGhBVFRUtl7/W/q5FENPK2O/DOhpadLXpdi3Bwo/HbHiLQiCkIVevHhB9erVf6rSg9R8+vSJ3r17s3//fvLmzcuRI0coXLgwAE+fPqVq1aqcOnUKGxsbihYtypMnT5DoGbPzRhAPgz8SFZeAiZ42eXRlzBvYDp/d26hY8cddDSxVqhRbt26ldOnS6g4lw9asWcO0adO4fPmyanMkdUhISGDgwIGcO3eO/fv3U6RIEbXF8l8bL79kmo9/qtvGf4m+tgZjXEvSsYpt1gUm5Fiiq4kgCEIWsrW1JT4+ntevX2d6J4ic4s6dO7Rq1Yr379/TqFEj1qxZo9rVMiEhAU9PT8aNG4ejoyPz58/Hzc1Nlch93vM5ISGB3377jRGD+v7QSTf821LwR028z5w5w8iRIzlz5oxak24AbW1tli5dypIlS6hWrRrbtm2jVq1aao0pSVLyPM3nIXEy+VfLTiSSxJXuMa72Iun+hYlSE0EQhCwkkUh+2nITpVLJ8uXLqVmzJuHh4YwdO5atW7cm20p+ypQp5MqViwEDBqjG//7776nON378eMzMzBgyZEh23UKWsba2/mE/5Xj69Cnt2rVj8+bN2NvbqzsclX79+rFx40bc3d1ZsWKFusNR6VjFlm29qtDQweqL5VO6Who0dLBiW68qIun+xYkVb0EQhCxWqVIlrl69SosWLdQdSqb58OEDPXv25Pz58+jq6rJ161bq1KmTbMyFCxf4559/uHnzJhKJhDNnzqChoUGNGjVSzOfr68v69eu5efNmjtm58Hv8qJ1N3r9/T5MmTZg8eTJ169ZVdzgp1KtXj3PnztGsWTPu3bvHnDlzkvXAVpcy+c1Y1rEiEdFSdt4I4taLUA4eO0mbZm7YWxvTpnx+chtl70ZOQs704//XTRAEIYf72Va8r169Srly5bh16xZ58+bl6tWrKZLuDx8+0LFjR/755x/VDpfLli2jd+/eKR7SCw0NxcvLi3Xr1pEnT55su4+s9CMm3gkJCbRp0wZXV1d69eql7nC+qESJEly+fJmHDx/i5uZGZGSkukNSyW2ky++/FWVioyLE+y5kXrty/P5bUZF0Cyoi8RYEQchizs7OXLt2jR/9WXalUsncuXNp1KgRAFWrVuXChQsUKlQoxdgBAwbQoEED1bbxoaGhHDlyhE6dOiUbp1AoVP2+69Wrl/U3kU1+tMRbqVTSv39/DAwMmDVrlrrD+SYzMzMOHTpEyZIlqVKlCo8fP1Z3SCn86P9/F7KG+j+fEQRB+MlZWVlhZGTE06dPKV68uLrDyZDw8HC6dOnC06dP0dDQ4I8//qB///6ptpjbunUrfn5+3LhxQ3VszZo1tGzZEjMzs2Rj582bR2RkJJMmTcrqW8hWP1riPX/+fC5fvsz58+dzXL/sL9HS0mL+/PmsWLGCmjVrsmnTphzzy9uP3r9dyDpixVsQBCEb/MjlJufOnaNcuXJ8/PiRqKgodu7cyYABA1JNLgICAhg4cCCbN2/G0NAQSFzV/ueff+jdu3eysdeuXcPb25stW7agra2dLfeSXX6kxPvAgQPMnj2bAwcOYGxsrO5w0q1nz55s376djh07smTJErHSLORoIvEWBEHIBj9i4i2Xy5k6dSqtW7emcOHCxMbG4ufn98VWbnK5nM6dOzNkyBAqVKigOu7r64upqSnOzs6qY1FRUXh4eLBkyRJsbW2z+laynbW1NSEhISgUae/vrA63b9+me/fu7Nmzh4IFC6o7nAyrVasWFy9eZOnSpfTt25eEhAR1hyR+ARBSJRJvQRCEbPCjJd7BwcE0aNCA/fv3Y25uTvHixTl79iwFChT44jmzZ89GqVQyfPjwZMf/+1ClUqmkb9++1KlTh7Zt22bpfaiLrq4uRkZGREREqDuULwoODqZZs2YsXryYSpUqqTuc71akSBEuXrxIUFAQDRo0UOt7L0pNhC8RibcgCEI2qFChArdu3UImk6k7lG86duwYFSpUIG/evLx69YpBgwaxatUq9PT0vnjO9evXmTNnDhs2bEhWI/zmzRtOnz5N+/btVceS2gbOnz8/K29D7XJyuUlMTAzNmzenZ8+euLu7qzucTGNiYsLevXupVKkSlStXxt/fX90hCUIyIvEWBEHIBmZmZuTLl48HDx6oO5QvSkhIYNSoUXTt2pXGjRtz+vRpdu3aRZ8+fb66ghcTE4OnpycLFixIUa6watUq2rVrp6odfvToEX/++WeKjXZ+Rjk18U7qJFOiRAnGjBmj7nAynaamJt7e3owbN45atWpx+PBhtcQhSk2E1IiuJoIgCNkkqdykTJky6g4lhYCAANq3b4+BgQFOTk48ePCAK1eupGmb+6FDh+Ls7JxsVRtAJpOxYsUKDhw4AIBUKsXDw4PJkyf/sFupp0dOTbwnTJjAmzdvOHHixE9dEuHl5UXx4sVp06YNf/75J0OGDMm2+/2Z31fh+4gVb0EQhGySU+u89+3bh7OzM9WrV+f169fky5eP06dPpynp3r9/P0eOHGHx4sUpXjt8+DD58uWjbNmyAAwfPpzChQun6G7ys8qJiffGjRvZtGkTe/fu/Wrp0M+iWrVqXL58mfXr19O9e3ekUqm6QxJ+cSLxFgRByCZJW8fnFFKplIEDBzJ48GCGDRvG2rVrGTx4MMuXL0dX99s77b19+5ZevXqxYcMGTE1NU7ye9FAlJLas27dvH6tWrfplVgNzWuJ9/vx5/vjjDw4cOIClpaW6w8k2BQsW5Pz580RGRlKvXj1CQ0Oz5bqi1ERIjUi8BUEQskm5cuXw9/cnLi5O3aHw5MkTqlWrRmBgIO3atWP+/Pns27cvzVuFK5VKunbtSs+ePalRo0aK11++fImfnx/u7u68fv2anj17smnTJnLlypXZt5Jj2djYEBwcrO4wAHj+/Dlt27Zlw4YNlCpVSt3hZDsjIyN27tyJi4sLlStX5s6dO1l6vV/ll0sh/USNtyAIQjbR19fHzs6O27dvU7lyZbXFsXnzZgYNGsSIESM4d+4c58+f5+rVq1hbW6d5jsWLF/Pu3Tv6/TGCZWee8fBtFFFxMkz0tLDPa8LTYxvo2LEjOjo6eHp60r9/f6pXr56Fd5XzWFtb54gV7w8fPtCkSRPGjh1Lw4YN1R2O2mhoaDBlyhQcHByoW7cuK1eupHnz5uoOS/jFiMRbEAQhGzk7O3PlyhW1JN4xMTEMHDiQs2fPsnz5ckaPHk3dunXZsWMHOjo6aZ7n/v37TP17A/UG/kWtuecAkMr+3ShGT+stsfFlqV7CjCFT5iORSBg1alSm309OlxNKTWQyGe7u7tSrV49+/fqpNZacon379hQrVoyWLVvy4MEDRo4cmSUr1KLUREiNKDURBEHIRup6wPL+/fs4OzsjlUqZNGkSvXv3Zvjw4SxZsiRdSbdUKqX1yPmYtBzHxcBPSGWKZEk3QJxMgURLh0uBMez7VJhWI+Yn6+39q8ibNy8hISHI5XK1XF+pVDJo0CA0NDSYO3euWmLIqZydnfHz82P37t106tQp08u/RKmJ8CUi8RYEQchG2Z14K5VKVq5ciYuLC0OHDqVQoUKMGDGCgwcP0q1bt3TP127sYqQObiQoNfjWgp4SkGjp8vfFN2y8/DJD8f/IdHR0yJUrF2FhYWq5/uLFizlz5gxbt25FS0t8wP1f+fLl48yZM8hkMlxcXDK9Hl+seAupEYm3IAhCNipVqhQBAQFERUVl+bWioqLo0KEDCxYs4ODBg+zatYtz585x9erVL24R/vz5c1q1akWePHnQ09Mjf/78NGrUiGfPnjFj2Xr2zf6Tl3+1JHTX1H+vc3Ufr2Y24e2mkapj0tf+vN08ioB57jye5U6/Xj04d/dFsmstWbKEokWLoquri52dHevWrcuaN0KN1FVucvjwYWbMmMHBgwdT7TgjJDIwMGDLli24ublRuXJlbty4kSnzihVv4UtE4i0IgpCNtLW1KVu2LNevX8/S61y/fp0KFSpgamrK2rVr6dixI8WKFcPX1xcrK6svnteyZUv27NlD6dKl6dq1K05OTly6dImHDx+y6PBt1bjYJ5eRvn2a6hwJkW8J2TYeacA99ItURCdvMaLunsCzo6dqzNatW+nfvz8fP36kffv2hIWF0aVLF44ePZp5b0IOoI7E+969e3h5ebFz505sbW2z9do/IolEwrhx45g3bx4NGzZkx44d6g5J+ImJxFsQBCGbZWW5iVKpZMGCBTRu3Jhp06ZRr149GjVqxLhx41iwYAHa2tpfPPfdu3fcuXMHMzMzfH19Wbp0KQcOHCAkJIQlq9ajaWP/2WgJH85tSnWeuGfXUMbHolvQEcvmw8nTbjIaekYE3rnEiXOXAJg5cyYAS5cuZe3atcyaNQuAGTNmZM4bkUNkd0vBkJAQmjZtyvz586lWrVq2Xfdn0Lp1a44dO8aff/7JpEmTUCgU3z7pK0SpiZAaUfQlCIKQzZydndm3b1+mz/vu3Tu6du3KmzdvuHDhAqtXr2bLli0cOXKEChUqfPN8Y2NjjIyMiIyMxMnJiTp16vDbb78RHBzMM4UF2lr/Ju0G9jWIeXgOafDjlBNpJT6sKf8QivxTJPKYSBQJiQ+vrTt4hlpVnbl37x4AFStWTPbnrVu3vuctyHGyc8U7Li6OFi1a0LlzZzp06JAt1/zZODk54efnR8uWLbl//z5r167FwMAg3fOIUhPhS8SKtyAIQjbLih0sL1y4gJOTE0WLFuXAgQMMGDAAPz8/rl69mqakGxLLYFatWoWpqSm3b99m3rx5tGzZkn79+lG8ZGniP+teYlrNHTS1iExl1dvQvgZauWyQfQghaFFHglf1B7kMgGevXhMeHq7q9GFkZJR4jqEhkNhzOidsMJRZsquXt1KppFu3btja2jJx4sQsv97PLG/evJw6dQp9fX1q1qxJUFCQukMSfiIi8RYEQchmxYoVIzIyMlO6XSgUCmbMmEGrVq1YvHgxXbp0oXr16pQqVYpjx46le2twd3d33r59y5EjRxg5ciRaWloolUruHNmcbJyWiSVGZRoQ9/w60jcPk72moWuAdbeFmDfqj0nVtuRu8ge6BUsDINE3wcLCQtVeMDo6Otmfpqam6OnpZei9yImya8V78uTJPH/+nNWrV4vV1kygp6fH2rVradeuHZUrV8bPzy/dc4hSEyE1IvEWBEHIZhoaGlSsWPG7V71DQkJo1KgRPj4+XLt2jU+fPlG3bl2mTJnCnDlz0t1CLiEhgfPnz6Onp0fDhg3R1tamaNGiACjjY1OMT1z11ibG/3yK1yQamhiXa0SuWl7oWhdH+tofkFC8XBW0tLRU25ZfuXIFQPVelC1bNl0x53TZkXhv2bKFNWvWsHfvXvT19bP0Wr8SiUTC8OHDWbZsGU2bNmXTptSfafjSuYKQGlHjLQiCoAZJD1i6urpm6HxfX1+8vLzo1q0bY8aMYdy4cezcuZPjx49Trly5DM0plUqpWbMmJUuWJH/+/KokHMCqUFHeKmXJxmsZW2BctiEfbxxMMdebVf3RyVsMiYYWsU8ug1yGWcUmVHFyAGDEiBF4enrSr18/Dh06pKp5HzlyZIq5fmRZnXhfvnyZQYMG4evrS968ebPsOr+ypk2bcvLkSZo1a5a4a+vUqWhoiHVLIWPEd44gCIIaJG0dn14ymYyxY8fi5eXF+vXrGTx4ME2bNuXWrVtcu3Ytw0k3JH68PmTIELS0tPD19SU+Pp64uDh0dHSwNtRAUyPl7pMm1dyRaKXc+VLHohBxz2/w6cEZNAxMMHPpgmXD3rQpnx9A1V/cyMiIzZs3Y2lpyapVq2jcuHGG48+JrKysCA8PRyaTfXtwOr169YpWrVqxZs0aypQpk+nzC/9ydHTEz8+PCxcu0KpVK1Vp1H+FR0tZduYZo/c/wrDxUAZvu8myM8+IiJZmc8RCTiVRiiIkQRCEbBcYGEiFChUICQlJ88fSQUFBtG/fHn19fTZs2MCbN29o1aoV7u7uTJs27bt3JwwKCmL37t1MmzaNyMhIWrduTevWrWnUqBGGhob02nCN4/4h39yxMjUSCTR0sGJZx4rfFeOPyNramuvXr2NjY5Npc0ZFRVG9enV69OjBoEGDMm1e4evi4+Pp27cvV69eZf/+/RQqVAiA24GRLDn9lDOPE5/bkH72ILKelgZKwMXOkr61ilG2gJkaIhdyCrHiLQiCoAb58+dHQ0ODgICANI0/cOAAFStWxM3NjSNHjuDr60uDBg3w9vbG29s7w0n3ixcvmD17NlWqVKFs2bLs3r0bLS0t3rx5w+bNm2ndurWq40g/l2LoaaVc9U4LPS1N+roUy9C5P7rMLjeRyWR4eHhQo0YNBg4cmGnzCt+mo6PDihUr6NatG1WqVOH8+fNsvPwSjxWXOe4fglSmSJZ0A8T9/9ixByF4rLjMxssv1RO8kCOIGm9BEAQ1kEgkqjrvpFWz1MTHxzNixAh2797Nrl27qFy5MkOHDuXAgQOcPHmS0qVLp/vaDx8+ZNeuXezatYvXr1/TokULJk+eTNGiRalatSqHDx8md+7cKc4rW8CMLmWN+ftSCBJt3TRfT19bgzGu9pTJb5buWH8Gmd1S8M8//0Qmk7Fw4ULxEJ8aSCQSBg0ahL29PW1HL8SoRmcSlN/+d1AqITZBzjQffwA6VrHN4kiFnEgk3oIgCGriWLEq668Gc15+k6g4GSZ6WtjnNaFthfzkNtLl2bNneHh4YGNjw82bN5HL5dSvXx89PT2uXLmCubl5mq6jVCq5e/euKtl+//49rVq1Yu7cudSsWRNNTU3kcjl169ZlyJAhX+z7/eTJE+b3b4OyaA2Ma3khU0q+WnYikSSudI9xtf+lk4zMXPFeunQpR48e5dKlS1/dhVTIfLa2trx69QqA8+fPk9ehMia/yfnw8i4hmxIfCtY0yUP+vqu/Ok9sgoJpPg8pk9/sl/1l9FcmEm9BEIRsllQPelJaFrkygTu3/k3K9LTeMs/3McUM47m2bhpj+nRiwIAB3Lhxg1atWtGxY0cmT56s6oP9JUqlkuvXr7Nz50527dqFTCajdevWrFixgsqVK6foyjB79myUSiXDhw9Pdb7AwEDq16+PsbEx7Wrb0/b3Gvx9+imnHoUhIfHj9H/vIbGmtbadJX1div3yyUVmJd7Hjh1j0qRJXLhwATMzs+8PTMiwpUuXYtBwMPEKJR9vHk73+XEyOX+ffvpLPvPwqxMPVwqCIGSjjZdfMs3nIXEy+dcfUlQo0NXWYFyTUsgfneHPP/9k2bJltG7d+iunKLh06RK7du1i9+7d6Orqqh6QLF++/BfLEq5fv07jxo25du0aBQsWTPF6aGgov/32GxYWFpiamrJ//35V4h8RLWXnjSAeBn8kKi4BEz1t7K2NaVM+cdVegH/++YcrV66wcuXKDM/x4MEDXFxc2LVrFzVr1szE6IS0SlrxzpUrFzExMeTvtxapTEHQki5oaOuiiItG0yQPeTvM4PWy7gAUGpnYajP84Dw+3TuBafX2mNX0RPr2KR9OrEAzMgClQoGtrS39+vWjT58+6rxFIRuIFW9BEIRskph0+xOboPj2YA0NpHLoVLUwAEePHqVBgwYphslkMs6dO6dKtnPnzk3r1q05ePAgpUqV+mYNcExMDJ6enixYsCDVpDsyMpKGDRtiZ2fHgwcPOHjwYLLV9txGuvz+W9Fv388v7HtXvMPCwmjatCmzZ88WSXcO4OXlxfz58/lw6xgyhRLkCRiWd+Xj1X1pnuO97z9Igx7gVKshFYoX4OHDh1y/fj0LoxZyCtHVRBAEIZOMGjUKiUSCl5eX6ljfvn2RSCTYlSrNNJ+HxCYo+HjrCK9mNuHt5tFpnltu/O/mKPHx8Rw9epSePXtiY2PDsGHDyJcvH6dPn+bu3btMnDgRR0fHND14N3ToUJydnWnfvn2K1z59+oSbmxt2dnZcuHCBvXv3ihKHDLCxsSE4ODhD50qlUlq1aoWHhwedO3fO5MiEjKhVqxbm+YsQeeMI0beOoG1REL0CjumaQylP7OtuYV+FQYMGcfLkSZYvX54V4Qo5jEi8BUEQMkmNGjUAuHDhgurYxYsXAXji/4CYTx8BkAY9AEAvf8k0z73uwnP279+Pl5cX1tbWTJo0CXt7e/z8/Lh27RqjRo2iRIkS6Yr3wIEDHDlyhMWLF6d4TSqV0rJlSwoWLMjFixf5559/VNu8C+mT0RVvpVJJz549sbKyYsqUKVkQmZAR8fHxFKriiiwyGFnkW4yc0rDpkzL5p1y56vZA29KW4/9MpnTp0pibm7Nw4cIsiljISUSpiSAIQiapVq0aEomEZ8+e8fbtWwwNDbl79y529iV59NCfuNcP0S9cHmlQYjsx3fwOxIe9JPL0WqTBT0CpRK+AI7nq9kDLNE+yuY8fO8q+8euRoKRZs2asWbMGfX39DMf69u1bevbsyc6dOzE1NU32mkwmo3379hgZGfHmzRs6depEq1atMnytX52lpSXv3r0jISEhXZ1IZsyYgb+/P2fOnBFblGejhIQEAgMDefHiBS9evODly5e8ePGCt2/fAuDp6YlN86H/b6kpwahUHeIC7qjOl+joqb5WSGPQ0DUgPuxVsmvo5i2OTffFuJYwoV0RBQ0bNmTkyJEMGDDguzfCEnI28a8rCIKQSXLlykXJkiV58OABFy5cwMTEBIVCQaXmXjx6OBJpkD86loWRRQYDEnTyFOHNyj4o4uPQL+YMchkxjy8SHxGATddFSLT+TdI+XNxKZRdXnlw7w7Zt28iXLx9z5szJUJxKpZKuXbvSs2dP1Sp9EoVCQY8ePfj06RPFixcnLi6OyZMnf8/b8svT1NQkT548vH37lgIFCqTpnJ07d7Js2TL8/PwwMDDI4gh/LXK5nDdv3qRIrJO+fvv2LdbW1tja2lK4cGEKFy5Mw4YNOXnyJG/fvmXbtm2E5i7LDDMb4uVKNPQMk82vaWCKprEF8o/hhB+YjURLh4TQ58nGhO6cjAYK7jraE2GgRCqVkjt37m92KxJ+fCLxFgRByETVq1dPlngD6BerhJZ5PqSv/dG2tAVA27Ig0fdPooiLRjt3AbRMLAHQMDBFFhFEXMAd9Iv820/bvGF/Krm3ZvjvHWnRogXr16/PcOK9ZMkS3r17x/jx45MdVyqVDB48mKdPn9KlSxe8vb25evWqSAYyQVK5SVoS76tXr9K3b1+OHTuGtbV1NkT3c1EqlYSEhHwxsQ4MDMTCwkKVWNva2lKzZk06d+6Mra0tBQoUSPWTiaT/v2hoaNCmQn7m+RZHIkv9QencrgN5d/RvpIH30StSHv3iVYh9cln1ul7B0sTcP8WNkwe4+f/NtGbMmCE2RPoFiMRbEAQhE1WvXp0VK1aoEm87OzsStI3Qze9AzMPzaOdOTLx085VE9iEUgISIQBIiApPNk/D+Dfr8m3hrWxTg5ZsQDBwTVz/Dw8ORSqXo6qavZd/9+/eZNGkSFy9eTJFcjB8/nvPnzzNv3jzatGnDqVOnxMOUmSStdd6BgYG0aNGCFStWUK5cuawP7AekVCp59+5disQ66c9Xr15hZGSULLGuUKECbdq0wdbWlkKFCqGnp/ftC/3Hy5cvk/29VglLjvuHoFSCQYmqqtaBAPqFy5Ov95fbR5pVd6ddzwGij/cvSCTegiAImah69eoA3Lx5E11dXdzd3THS1UIvvwOf7hzn0/1TQGLiLY+JBMCgRDUsW/3b4UQe/R6JbvLygoTwQB7eeUfHmfNUx0qXLk3evHnJmzcv1tbWqX5taWmpWrGWSqV06NCBmTNnUrx48WTzz549mx07drB7924aN27MsmXLcHRMX6cG4cvSknhHR0fTtGlThgwZQvPmzbMpspwpKioq1dXqpD81NDRUZSC2traULFkSV1dXbG1tsbW1xcjIKMtj7OdSjHNPwolNkKf7XD0tTfq6FMuCqIScTiTegiAImahYsWJYWVkREhJCQkICjo6ObPbZga51YqKriIsGEh+slGjpEHVxOzGPLxKybRxaplbI3gcTF3iPfL3+QcPMSjXvu6NLKF6rLhH/33Wnb9++DBw4kODgYN6+fcvbt28JDg7m4cOHyf7+/v17LCwsyJs3L5GRkSgUCp4+fcrChQtVCfrp06dZuXIlp0+fplu3bnh6en51ox4h/b7VUlAul+Pp6YmzszNDhw7NxsjUIyYmhpcvX6aaWL948QKpVJossS5cuDAuLi6qr3PCJzFlC5gxxtU+7b35/09fW4Mxrva//I6uvyqReAuCIGSyatWqsWfPHgBmzpyJZ7feHNQqgoaBGYqYSDQMzNDOlVi7a+U5k8gz65EGP0Ea9ABNE0uMy7uhYWCSbM7ctToS/MgHqVSKl5cXs2bNwsDAADs7u6/GkpCQQFhYGHv37mX8+PGMGzeOjx8/8vjxY86ePcvdu3d59uwZ2tra2NnZoa2tTXx8PG3btv3iarqlpaXovJAO4dFSXuoX417Ee96su4qJnhb2eU1oW+Hf3T1HjBjBx48f2bFjx09R5yuVSgkICPjiinVkZCSFChVKllg7Ozurkm0LC4sf4n3oWMUWIE270UokiSvdY1ztVecJvx6xZbwgCEImk8vlTJ48mRUrVrB27VqKFy9O4+l7iDUvjiQDbeEkEmjoYJXhetCIiAjKlSvH6tWrqV+/vur4wYMH6d69O76+vty8eZOJEyeybds2YmNjVSvmn6+eJ30dERGBubn5V0tckr42Njb+IRKorHA7MJIlp59y5nEYCrmChM9+2uppaaAEXOwssXl/j02LpnP58mXMzc3VFm96yGQygoKCvphYh4aGki9fvmSdQT7/Om/evD9Vi8Q7QZH8ffoppx6FIQHiPnvoMunfuradJX1diomV7l+cSLwFQRAy0evXr/H09ERLS4vVq1ezbt06Zs6cibZVMSw9ppGgTH8Sqq+tybZeVTL0A1upVNK2bVsKFizI3LlzVcdPnz6Nu7s7Bw8eREtLi4YNG3Lq1Kk01XXLZDLCwsJSTcr/+7VCofhicv753/PkyZOuHtc53cbLL9O2CgooZFIG1SzAH82csy2+b1EoFAQHB6d4cDHp69evX5MnT54vJtb58uX7JT8ViYiWsvNGEA+DPxIVl4CJnjb21sa0Kf/vpxvCr00k3oIgCJnEx8eHbt26MWDAACpXrszvv/9OREQEZcqUYcuWLZwKTMhgPWjJDH80vXr1aubPn8+VK1dUnRyuXLlCkyZN2L59O6VKlcLZ2ZlZs2bRtm3bDF3ja6Kjo1Mk5Kkl6OHh4eTKleubCXrevHkxNTXN0avoiUl39v47p5dSqSQ8PPyLLfcCAgIwNTVNNbG2tbWlYMGC6e6oIwiCSLwFQRC+W3x8PKNHj2b79u0sWrSIHTt24OPjg0wmY8aMGfTt21eVKKZ5JTQT6kGfPn1K1apVk61k37t3j3r16rFy5UoaNWpEgwYNqKtRQV4AAFyESURBVFy5MjNmzMjQNTKLXC4nPDz8mwn627dvSUhI+GY3l7x582JlZYWOjk623odNgYIEBwVi2WoMBiWqfnVs9B1fInzmo1vAkbyeM7/rk43UREZGfjGxfvnyJbq6ul9MrG1tbcXGPYKQBX69z4EEQRAy0YsXL/Dw8MDS0pKBAwfSvXt3jIyMKFq0KJs3b07Rtq9jFVvK5Df7Yj2oFgo0tbS+ux40ISGBjh07Mm7cOFXS/fTpUxo2bMi8efNo0qQJf/zxBzo6OkydOjWjt59pNDU1sbKywsrK6ptjP336lGpy7ufnl+zvoaGhmJqapqkW3czMLFNW0T/GyTJ8bpxMzt+nn6a5lj86OjpFKcjnCbZcLk+WVBctWpR69eqpEmtTU9MMxyoIQsaIFW9BEAQSO0/svB7Ew7dRRMXJUu088V87d+6kb9++dOrUifPnzxMZGUlYWBhDhw5lxIgR36xxTaoHXbB2Bx9iEyhbsjgfAx+xd97I764HHT9+PFeuXOHw4cNIJBKCgoKoWbMmo0aNolevXmzcuJGJEydy5cqVH+aBvvRSKBSEh4d/sxb97du3xMXFYWVl9c0E3crK6oslFuHRUqzzF0T2IRTLVmPQL1aJqKt7ib5zHHlUGFomeTB2bo5xuUaq1e7PaZrkoejAtVwcUYfcRrrExcXx6tWrLybW0dHRyVap/7tybW5unqNLcgThVyQSb0EQfmmfd54AkKbSjcDFzpK+tYpRtoAZAHFxcfzxxx8cPnyYKlWqcOLECQoWLEhMTAybNm3CyckpXTFUrVqV4OBgVq5cSYcOHQgJCfmuhOnChQu0bt2amzdvYm1tTVhYGL/99hvdunVj2LBh3Lx5kwYNGnDy5ElKly6d4ev8TGJiYggJCfnmw6KhoaEYGxunWn/+WLMQayb1VyXe0jePiLq8Ey3z/Oja2BEXcAd5VBi53YagnTs/kWc3EvfyJprGuTGwq46GnjG5qrXF+MUZws9vJSIiggIFCnwxsbayshKJtSD8YESpiSAIv6xv1VsnlYAcexDC2cfhjHG1p6JZXOJulEZGxMfHExERgYaGBi4uLkydOjVDW1HLZDLMzMzQ0dHByMgIf39/HBwcMnRPUVFRdOrUieXLl2Ntbc2HDx9o2LAhrVu3ZtiwYYSHh9OyZUuWLFkiku7PGBgYqBLbr1EoFLx7947g4GBevXpFYGAggYGB3Lt3jxu6kn+/j5RKPt44BIBuPns0dA3QyVOY2KgwPt70wbrzHAwdahH38iZaZtaY1+uVeBpQumZDZs4Zgo2NjWrXUUEQfg4i8RYE4ZeUns4TSiXEJsiZtP8eUWfWYiGX8+HDBypUqMDdu3fZtm0btWrVynAscrmcXLlyER4ejouLC6dPn85w4t2/f3/q169P8+bNiYmJoUmTJtSoUYMpU6Ygk8lo164dHh4euLu7ZzjeH4FSqSQ2NpaYmBg+ffrEp0+fUv06rcf++3pMTAza2toYGBhgYGCAjo4OypolP7u+AmV8LACf7vomi032/ss7WALomZhToECBzH9TBEFQO5F4C4Lw07C1teXVq1dIJBIMDAywsLCgUqVKDB06lMqVKycbo2VkjvXvK9DQ1iU+5DnBawYCUGjkQQDen91A7NMryD6EAKBjWRizWp3Rq9qBstKrnN+3iZs3bxIdHY2LiwuQmOxlhEwmw9zcXJV4Hzx4kL59+6Z7nm3btuHn58eNGzeQSqW0atWKIkWKMH/+fCQSiarufNq0aRmKMzMpFApiY2MzPSFOOhYbG4uuri4GBgYYGhpiaGiY6tefH8uVKxf58+f/4riEhASCg4MJDAzk1atXPHnyhEePHvHs2TMsLCww0vj3318i0UCirYcyIQ7rbovRyWMLJH6PyD+EJg5K2kDmP983Jno/Tz9zQRCSE4m3IAg/HTc3NywtLblw4QI7duxgz549bN68OVmfaln0O6Jv+mBSqWWqc3y6dwoNXQMM7KoTH/wYadB9QndMxKbH35x7r8+fQ4eyePFiSpYsyfHjx78rXrlcjrm5OWFhYXTs2JE///wTpVKZrvrdgIAABgwYgI+PD7q6unh4eGBgYMCqVavQ0NBg8+bN7N27l6tXr6apfEEul381Mc5oQpz0dVxcHHp6el9MglP7Onfu3BQsWDBNSbS+vn6GyjSkUilPnz7l8ePH3L9/n0ePHvH48WMePXpEQkICdnZ2lChRAjs7O1q2bElkZCT379/H19eXj0EPkfD/JFoiwbi8G1F+uwjZNhaDYpVQxMchffMIvQKOWDQZgpaxBQDxIU+JOPo3OlZFsKzoir21cbrjFgThxyASb0EQfjrdu3enRYsWyGQyOnXqxNatW+nduzdubm4oVKuLEj5c3oWRU+NU57BoNgy9/ImlA4r4WIIWdUIZH0t88BPMHKrTsXtdBg0axK1bt9L9MOV/yWQycufOTXh4OIUKFUpTnbdcLlclsVFRUXh6etK6dWvev39Po0aNCA0NpV+/fixdupQnT56watUqWrduzZgxY9KUJEulUvT19dOUECf9aWVlleYkWl9fX21bhiuVSl6/fs2jR4+SJdaPHz/m9evXFCpUSJVgV6tWja5du1KiRAmsrKx4/vw5Pj4+HD58mFmzZlGuXDkaN27Mjh07yFfUHpt8/y8R0dDC7LdOaOgb8+nuCT7dP41ExwAdqyIYlqwJgG5BRwwcahH79ArRN33QL+qMzKkRrZ3yqeV9EQQh64nEWxCEn5aWlhYTJkxg69atvHv3jgsXLvBJKgfAwL4GMQ/P8fHGIfRtUybOSUk3AEolSkVif2ZN49xoSCTsvBHE778V/eK1ZTJZmleAw8PDuXr1Km/evCEmJgYNDQ06dOiAlZXVF8+Jj49XJbEJCQlIpVIADh48yKdPn6hduzaXL19GQ0ODXbt24erqSpkyZdKcROvr6//wHTOioqJUSfXnCfaTJ08wNjZWrVzb2dlRt25d7OzsKFy4cLKt6+Pi4jhz5gwzZ87Ex8eHjx8/0rhxY7p27crmzZsxMzNTjX3x4gXyT+8B0DLNg0RTC9MqbTCt0ibV+CQSDSybDfv37yhRvr5Ls4bTmDx5MnXr1v3h/w0EQUhOJN6CIPzUChUqpPo6NDSUBHniw5SGJWuSEP6KKL/d6NrYf/F8pUJOxKH5IJdhYF8jsS2cTMGyrQfYNdWH0NBQ1dj8+fOrEmOZTJbmMgqZTIaxsTFKpRInJyeUSiX37t1j8ODBXzxHT08PiUTC9evXady4MTdv3mT16tXs37+fu3fvYmZmhkwmo1GjRvz+++94e3tn2XusTgkJCbx48SJZYp30dVRUlCq5LlGiBE2bNmXo0KGUKFHiq5vHPH/+nMOHD3P48GHOnj1LmTJlaNy4Mdu2baNs2bKprtRPnjyZOXPmoFTI0c1bDG2L9D8cqaetxeYpvXh4oRD9+/cnT548TJ48WfUMgSAIPz6ReAuC8FN79eqV6us8efL8+xybRIJp9faE7/Pm442DqZ6rSIgjfO9MYp9dQ7+oMxZNhqpesy5YhEHNh/L69Wu6d+8OwKVLl1SJsa6ubppXK/fu3UuPHj2YOHEivXv35tWrVzg7O9OoUaOvzhETE4OnpycLFixg165dbNu2jbNnz6pWYUeOHImGhgbTp09PUxw5lVKpJCQkJFlJSFKC/erVK/Lly6dKsMuVK0e7du2ws7PDxsYmTeUscXFxnD17VpVsR0ZG0qhRIzp16sT69evTtMHQixcvMDAwoFGjRlRtP5DlN6LS1DEnib62BmNc7XEqaI5Twfa4u7uzZcsWevbsSYECBZg0aRI1a9ZM83yCIORMIvEWBOGnJZPJmDRpEgDm5uZUr16dz/NYA/saaF/cRoz/+RTnymM/ErZzEtLXDzF0rENu10FINP59WM+ucEEaNizHrVu3VMcy2gJOJpNhYWFBeHg4QJrrvIcOHUrFihX59OkTCxcu5Ny5c+TJkweALVu2sHv3bq5du/bD9IL+9OkTT548SbU8RFtbO9mDjUl110WLFs1Q7/SXL19y+PBhfHx8OHPmDKVLl6Zx48aqDZDSW3++Zs2aZH+3yPv1HvFJJIAiQUqPqvnpWMVWdVxTU5OOHTvi4eHBxo0b8fLyomjRokyePJmqVaumKzZBEHIOsXOlIAg/jaRWgU2aNFF1NXn8+DFaWlps3ryZhg0bks+2GNHvw7BsNQaDElX59PAC4XtnqOZIaif4dsMwpK/90dAzwrBUbZIydv0iFTCwLYuL6Xuk944RHR3NgQMHAPDy8gJg7dq16Yo7T548XL58mTJlyhAdHQ1Ax+590CxenVyFS6W6hf2BAwcYOHAg48ePZ+zYsZw+fZrixYsDcOvWLerXr4+vry9ly5b9rvc0s8nlcgICAlJ9sDEsLIyiRYuq6q4/LxPJnTv3d11XKpVy7tw5VbIdERFB48aNady4MQ0aNEjTqnZ63QmK5O/TTzn1KAwJ/27IBP/uilrbzhLL8FscWv83ly5d+uJ29AkJCaxbt46pU6dSsmRJJk2aRKVKlTI9ZkEQspZIvAVB+Gl83sdbX18fS0tLnJ2dqVSpElevXuXo0aMkyGTExsSoEm+lUknwmkEkhD4H/k28g/7uhjwqNMU1TKu3J3fNDuS7uphzJ46mGkd6/7Nqbm7O48ePyZ8/P2fvvWLlpUBO+r9FLpej1Pj3g8mkZK1KIROOzR/KkM6tmDNnDsePH6dMmTIAREREULFiRWbMmIGHh0e64shMERERKRLrpJ7XlpaWKRJrOzs7ChYsmKmr869evVKVjyRtStS4cWNcXV0pX758tnVViYiWsvNGEA+DPxIVl4CJnjb21sa0KZ/4S5RSqaR169YUKlSIefPmfXWu+Ph4Vq9ezbRp0yhXrhyTJk2ifPny2XIfgiB8P5F4C4Lw01EoFJw7d45Nmzaxa9cuHB0d8fT0pE2bNpibm9NrwzWO+4d8tQTgSyQSaOhgxbKOFYmOjub48ePs37+fgwcPYmNjQ7NmzWjWrBkVKlRIc2JnampKQEAAji36YFCjI/Fy5ddjUyrQUCqIvbiJPbP+oEqVKkBiyUrjxo0pV64cs2bNSv/NpVNSz+vUHmxM6nn9eWJtZ2dHsWLFMDQ0zJJ44uPjOX/+vKrdX1hYGA0bNlStaltYWGTJdTPDu3fvcHJy4u+//8bNze2b4+Pi4li5ciUzZsygUqVKTJw4Mcd9uiEIQkoi8RYE4aegVCq5c+cOmzZtYsuWLZibm+Pp6YmHhwcFCxZMNvZ2YCTtVlwiLh0PvyXR19ZkW68qlMlvluy4XC7n8uXL7N+/nwMHDhAZGUnTpk1p1qwZderUQV9f/4tzJj1Ama/XMrTM86tW263aT0evUJkvnqejAeObllLVBg8fPpybN29y+PBhtLS0VPO+ePECW1vbdN8rJL6vQUFBqdZdv3nzBltb2xQr13Z2duTJkydbWuEFBgaqykdOnTpFyZIlVSUkFStWVFuv8Iw4d+4cbdu25caNG9jY2KTpnNjYWP755x+8vb2pXr06EyZMwNHRMYsjFQQho8TDlYIg/NBevnzJ5s2b2bx5M9HR0XTo0IHDhw9/NfmIe/OIhCvb0CjbEoVG2v8zqKGQMbJhyRRJt5+fH97e3ly4cIH379+TO3duihQpglQqZdasWXTo0IE6derQrFkz3NzcVA9AprxA+rYKj1fANJ+HXNi+jGXzvDEyMuLly5doaSXe06BBgwAwMTH55lxRUVGprlwn9bz+PLGuX78+JUqUSNHzOjvEx8dz4cIFVbL99u1bGjZsSNu2bVmxYgWWlpbZGk9mqlmzJn369KFjx44cP348TWU3+vr6DBo0iJ49e7J06VLq1auHi4sLEyZMoGTJkt88XxCE7CVWvAVB+OGEh4ezY8cONm3axKNHj2jTpg2enp5Uq1btqyucCQkJTJkyhX/++YfFixcTl79i2jpPSEBXSwOTp8cpoRHKunXrVEnRjh07aN++PXK5HHt7e6pVq8bHjx/x8/PD2dmZnTt3EhERweHDh9m/fz/Hjh2jVKlSqpIUe3t7Vcz5eq9Cy8wqzSveSbEZ3trG/cMbaNq0Kfv37//q/Sf1vP5v/fXHjx8pXrx4qg82piVxz0pBQUGqWu2TJ09SokQJVa12xYoVf5iuLWkhl8upU6cODRs2ZPTo0ek+Pzo6miVLljBnzhwaNGjA+PHjKVGiRBZEKghCRojEWxCEH8KnT5/Yv38/mzZt4vz58zRu/L/27ju+xvN94PjnZMgUIYnECGrvEbVCxY5IjNqEUopKUu2vqrU3VbS0DfGlipIIVVtirzYEpWaCxkqEbNnrJOf5/ZGv0+YrdgbJ9X69vCTnPOd+rudE4sr93Pd1OeHq6kq3bt0oVarUc18fFBTE8OHDsbGx4aeffqJChQrAi1eecOtQk1oWBri4uGBra8vPP/9Meno6tra2xMXFMXjwYDZu3Kidbc7OzubGjRvUqlWLHj16cOXKFeLi4jA2NqZu3brUrl2bY8eOUcrMgttBl4CnJ94JZ7aTfNGf7OQ4FE02+uUqU6btYEzqtiP+d28SAjbnutY2bdrw9ddfaxuvdO7cmbCwMG7evAlA7dq1efToEQkJCTRt2pS1a9fSoEGDN6ZLolqt5tSpU9q12g8ePKBbt244OTnh6Oj49DsGxcT9+/dp3rw5O3bswN7e/pXGSEpK4scff2TZsmU4OzszY8YMatR4eqdVIUThkMRbCPHGUqvVHD58GG9vb/bu3UubNm1wdXWlT58+mJqavtAYGo2G77//noULF7Jw4UI++uijPBPM51WeeCw1NZUePXpQs2ZNBgwYQPfu3QEIDg6mbt0nO2BmZGTQvHlzmjdvjqmpKadPn+avv/7C0dERf39/ZvicZMGwDsDTE+/Yg15kJ8eha1oOTWoCqTdOgY4ulcasQh13n/jfvcl8eBNDQ0M0Gg36+vo0adKEU6dOAbBq1Sree+89nJycCA0NxcjIiAEDBrB3717i4uKYPn068+bNe9kvT74KDw9n//79+Pn5ceTIEWrVqqVdq92yZctiNav9Inbt2sWnn37KxYsXc7Wlf1kJCQl8//33/PDDD/Tp04fp06e/8np/IcTre3t2nQghSgRFUTh9+jQeHh5UqlSJuXPn0rp1a27evIm/vz/Dhg174aT73r17dO7cmd9++43AwEDGjBnz1FldC1MDxrWvwbJBTVk7ogXLBjVlXPsauZJuAGNjY/bu3cuNGzdytWF/nMxMnjwZlUql/WNgYMCOHTto0qQJJiYmNGrUCIDjx4+jKAqJOs+/lrIdPsS4Vmt0DU3RNbVA17gMZKvJCA/GqHpzjKo3B6BTp048fPiQ5ORkAgICtK93dHSkfv362mufM2cOGzZswMPDA4C//vrrhd7P/KRWqzl58iRTpkyhSZMmNG7cmEOHDtG7d29u3LjBuXPntM1iSlrSDdC7d2969uzJmDFjXro85b+VKVOGmTNn8vfff1OxYkXeffddxo0bR2hoaD5GK4R4UbK5UgjxRggODsbb2xsfHx8MDAxwdXXl9OnTr3R7XFEUNmzYwKRJk5g0aRITJ07M1+TN1NQUPz8/WrVqpX0sLCyMWrVq0a5dO8LCwvDx8QFyKlV07NiR7OzsXGNkZGSQlJREQpr62deSrSZi40TU0feeeC47NSHX51ZWVi/UCKZZs2YA2pnUx017CtqDBw/Yv38//v7+HD58mOrVq+Pk5ISXlxctW7bULtMROZYsWUKrVq1Ys2YNY8eOfa2xypYty9y5c/n000/59ttvadasGYMHD2bKlClUrlw5nyIWQjyPzHgLIYpMeHg4S5cuxc7Oji5dupCens62bdsICgpi+vTpr5R0R0VF0bdvX5YtW8aRI0f48ssvC2TGtHTp0hw9elSbLC5cuBBFUXBxcWHSpEna43777Teys7Pp3r07KSkpnDlzRvucoiiYlnp2bOqYsJykW6VDxXGrqfLVHvQtc5dH5L+bMzWaFyuP+Djmgl7TnZWVxR9//MHUqVNp1qwZDRs25MCBAzg7OxMcHMz58+eZP38+9vb2knTnwdDQEF9fX6ZOncq1a9fyZUwLCwsWLlzI9evXMTU1pUmTJnz66ac8fPgwX8YXQjybJN5CiEIVHx/P2rVr6dSpE40aNSI4OJilS5cSGhqqTcJfNSHctWsXTZs2pW7dupw9e1bbzbGg2NjYsGrVKiCnTXyzZs0YN24cU6ZM0R5jbW0N5JQc/OSTTxg6dKj2OS8vL075/frMc+gYmYFKBxQNj478RJTvdNRxD3IdY2Ses9nQ39+fTz75hN9++y1fru9VREREsH79egYOHEj58uWZMGECKpWKH3/8kaioKLZs2cLIkSOxsbEpshjfJvXq1eObb75h8ODBpKWl5du4VlZWfPPNNwQFBaGnp0fDhg35/PPPiYyMzLdzCCGeJIm3EKLApaen89tvv9G3b1+qVq2Kn58fHh4ePHjwQJuEv86sdGJiIqNGjeLzzz/n119/5euvv8bAwOD5L8wHo0ePxs/PDzMzM27cuMG6deu4cuUKjo6OrFmzBg8PD/r06UNGRgb79++nevXq2tcGBwczpkujZ46vZ2ZJua7j0DExJz3sKqVsamJQKfcmTtN679GpS1dSUlLw9PTk2LFjBXKtecnKyiIgIIDp06fTvHlz6tWrx759+3BycuLatWtcuHCBBQsW0K5dO5nVfkWjRo2iQYMGTJw4Md/Htra25ttvv+Xq1atkZ2dTv359vvzyS6Kjo/P9XEIIqWoihCgg2dnZHD9+HG9vb3bu3EmzZs1wdXWlb9++r1Wl4X+dOHGCkSNH4ujoyNKlS19442V+i42NpXPnzjg7OzN//nxUKhXh4eH4+/uzb98+jh49SoMGDXB2dqZHjx40bdoUlUrFX3/9hdOC7RjWaKldMvIy/t3CvrBERkZq12ofOnQIW1tbbV3t1q1bF3pTnZIgISGBZs2asXTpUvr27Vtg57l//z5ff/01vr6+jBs3jokTJ2JhYVFg5xOipJHEWwiRbxRF4cKFC3h7e+Pr60uFChVwdXVl0KBBVKpUKV/PlZ6ezrRp0/D19WXNmjX06NEjX8d/FREREbRt25ZKlSqRlJREaGgojo6O9OjRg+7du2Npaak9Vq1W8+OPPzJ//nw0ZW2xcV2Ury3s81N2djZnz57V1tW+desWnTt3xsnJie7du+f711bk7cyZM/Tq1Ytz585RpUqV57/gNYSGhrJw4UK2bduGm5sb//d//0fZsmUL9JxClASSeAshXtutW7e0FUnUajWurq4MHTo0z7rW+eHChQsMHz6cBg0a4OXlVaQzcnFxcRw4cIB9+/Zx4MABypcvT1RUFL1792bVqlV5Lq8ICAhg/PjxWFtbM3XqVEaMGMHCrSdZ4BdM2ksk30b6OkzrUY9hravl4xXliIqK4sCBA/j5+XHo0CEqVqxIjx49cHJywt7eXma1i8g333zDnj17OH78eKEs3blz5w4LFixg586dTJgwgU8//ZQyZcoU+HmFKK4k8RZCvJLIyEi2bNmCj48Pd+7cYdCgQQwdOpRWrVoVWLWMrKwsFi1axA8//MDy5csZMmRIoXdbVBSFK1eusG/fPvbt28fly5fp0KGDdgmJra0tERERdOjQgZEjRzJ58mTta2NiYvjqq6/Yv38/3333HQMHDuT27dt07dqV27dvsynwLtO3/wU6ejkbKp9CpQJDPV2m9aibb0l3dnY2586d07Zmv3nzJp06ddLO1kvJuTeDRqPB0dERe3t75syZU2jnvXXrFvPmzWPfvn189tlnTJgwgdKlSxfa+YUoLiTxFkK8sKSkJHbu3Im3tzeBgYH07NkTV1dXunTpUuCzbzdv3uSDDz6gdOnSrFu3rlATwZSUFI4cOcK+ffvw8/OjVKlSODs74+zsjIODA4aGhk+85sGDB3To0IGxY8fy+eef8/PPPzNt2jSGDh3KnDlzMDMz016Xs7Mzf//9NwBtew3ltkFNStdpjY5K9cwW9q+7vCQ6OpoDBw7g7+/PwYMHsbGx0a7Vtre3p1SpUq81vigYDx8+xM7ODl9fXxwcHAr13Ddv3mTu3LkcPHiQiRMn4u7uXmT7KoR4G0niLYR4pszMTA4cOIC3tzf+/v60b98eV1dXevXqhbGxcYGfX1EUvLy8mDVrFrNnz2b8+PHovMImxJd169Yt7az2qVOnaNmypTbZrl279gvNtIeHh9O6dWt0dXWpUKECXl5eNG3aFICY5Ay2nb/PmRthnDh1ll5OXalrY4bnxGFYlzFm6y4/Ri1Yw63oVFq064C5Uak8W9i/DI1Gw59//qldq339+nU6deqkbc1ua2v7SuOKwrd//37GjBnDxYsXi2SpVXBwMHPmzOH48eNMmjSJ8ePHF8rPAyHedpJ4CyGeoNFoCAgIwNvbm23btlGvXj1cXV0ZMGBAof4nHx4ezqhRo4iPj+eXX36hTp06BXauzMxMfv/9d22ynZiYSI8ePXB2dqZLly7aGeoXlZiYyMyZM/H29gZgxowZTJgwgUth8aw4HsKJmznl2jL+NaNtoKdDeno6lXUT6Fe3ND/Mnsi5c+ewsrJ65euKjY3Vzmrv37+f8uXLa9dqt2vXTma132JffPEFN2/eZNeuXYW+5Oqxq1evMmfOHAICAvjqq68YO3YsRkZGRRKLEG8DSbyFEFpXrlzB29ubzZs3Y2ZmhqurK4MHD6ZatWqFGoeiKPj6+vLpp5/yySefMGXKlAJZyvLw4UP8/Py05f7q1q2rndVu2rTpK82sK4rC1q1bmThxIo6OjnzzzTckJyfToUMHurnN5ffk8qRnZfPMn7yKBiVLzbiWVkwd+N5LnV+j0XD+/HntWu2goCA6dOigXatdtWrVl74m8WbKzMzE3t6eESNG8MknnxRpLJcuXWL27NmcO3eOyZMnM2bMmEKrpS/E20QSbyFKuNDQUHx8fPDx8SE+Pp6hQ4cydOjQAu/6+DSxsbG4ublx5coVNm7cSPPmzfNt7McbCB+v1b5z5w7dunXD2dmZ7t27v9bMMuSsf3V3dycyMhIvLy/atm2rfW753vMsO3EPld6zk5Hky4eJ9VuOgW1D3hm5+IWqlsTGxnLw4EH8/f05cOAAFhYW2rXa7dq1kwSoGAsJCaFNmzYcPnyYJk2aFHU4nD9/ntmzZ3Px4kWmTZvGqFGj5K6KEP8inSuFKIFiY2NZtWoV7du3x87Ojrt37+Lp6cndu3dZtGhRkSXd/v7+NGnShEqVKnH+/Pl8SbofPXqEr68vw4cPx8bGhjFjxqBWq1m+fDlRUVHa556WdFerVg2VSvXEn4sXL2qPSUtLY+bMmdjb2+Pk5MT58+dzJd2XwuL5z9noJ5Lu+ytHcW+RC+n3Lud57jS1hgV+17l8Pz7X449ntefPn4+9vT3vvPMOmzdvpk2bNpw5c4agoCC+/fZbOnfuLEl3MVezZk2WLVvGoEGDSElJKepwaN68OXv27OG3335j165d1K5dm59++gm1Wl3UoQnxRpD+vUKUEKmpqezZswdvb29OnjxJ9+7d+eKLL+jevXuRz0glJyfzxRdfsH//fjZu3EjHjh1feSxFUbh69ap2rfalS5dwcHDQdpR81aUWLi4u1KhRQ/v540Tdz8+PTz75hObNm3Px4sU8q62sOB5Celb2K503PSublcdD+Nq5hnZWe//+/Zibm9OjRw/mzJnDe++9l2dllX/LysqSlu3F1LBhwzh06BATJkxg7dq1RR0OAC1btsTf35/Tp08za9YsFi5cyMyZMxk2bJj8OxQlmyKEKLbUarWyf/9+Zfjw4Yq5ubnSrVs3ZcOGDUpiYmJRh6YVEBCg1KhRQxk5cqQSHx//SmMkJycru3fvVsaNG6fY2toq77zzjuLh4aH4+fkpqamprxVf1apVFUDZsWNHrsdDQ0OV9957TzE0NFRMTU2VChUqKB9++KESExOjKIqiZGZmKl26dFGsylsr6OgpKgMTxahmS6WS2zql6uS9iq5ZeQXI9ceix2eKRY/PFEAxqNxAMWvdX9ExMFF0TcspRqXNFWdnZ2XFihXKtWvXlK+++kqpUaOGYmxsrDRr1ixXfCNGjFAAZezYsUqXLl0UfX195dixY6/1Pog3W1JSklKrVi1l8+bNRR1Knk6ePKl07NhRqVmzprJx40YlKyurqEMSokjIGm8hihlFUTh79ize3t5s3bqVqlWratu2W1tbF8g5H5fGux6RSGJ6FmaGetS1MWNA86eXvsvMzGTWrFmsX78eLy8v+vTp81LnvH37tnZWOyAggBYtWmib2NStWzffqjxUq1aNe/fuaWe8NRoNf/31F1euXCE5ORkjIyNcXFx4+PAhJ06coGPHjhw5coTMzEyaN2+OaeXaXI/JJO3+dTIjb2H4jh3Wg+YS/8dmEs9uR8lMw7iOPbqlLTGp74A6JoxYv+WAilIVaqJjYEr63b8oZWhMdORDzMzMGDJkCL6+vtjZ2dGgQQP8/f2JjY3l6NGj2sY9GzZsAMDBwYHq1avj4eGBnZ1dvrwn4s104cIFHB0dOXPmDNWrVy/qcPJ07NgxZs2aRVRUFLNmzWLgwIHo6uoWdVhCFBq53yNEMXHjxg1t23ZdXV1cXV35448/qFmzZoGd81ml8Qz1Ilh2+CYd6ljh5lCTJrbm2ueuXLnC8OHDqVatGpcuXaJ8+fLPPVdmZiZ//PGHdmPko0ePcHJy4qOPPmLLli0F3sZ67969uT53dXXF29ubBg0aYG1tjbW1NYGBgRw7dowbN25Qt25dduzYweh5q1Di76JvVZXMyFukh15BUTSYtxtC8uVDZGemUdrOBcOqOevq1TFhAOgYmmLj+g2odAhd2pfM9FRu3rxJ1apV8fX1RUdHB3t7e3R1dWnQoAEnTpxg1apVdOjQQRtj+/btOX78eIG+L+LNYWdnx7Rp0xgyZAh//PEH+vr6RR3SEzp27EiHDh04cuQIM2fOZP78+cyePZt+/foVSn1+IYqaJN5CvMUePHiAr68vPj4+PHjwgMGDB+Pr60vz5s0LvK7vpsC7LPC7/tTSeI87Lh4MiuTkzRim9ajLkBa2fPfddyxevJglS5YwYsSIZ8YZERGhLfd35MgRateujbOzMxs3bsTOzq5Q/6Pu2LEjf//9N8uWLaNfv364uLgAcObMGc6cOZPrWG9vb9LT0/nuu+/QaDS5B8pWo2SkoTI0eeb59C1tUenlrL1XlTJEyUglOTmZu3fvAjkbLD09PXO9JiQkJNfn9vb2L3uZ4i336aefcujQIWbMmMGiRYuKOpw8qVQqunTpQufOnTlw4ACzZs1i3rx5zJkzhz59+hRZTXIhCoMk3kK8ZRISEti+fTve3t5cuHCBPn36sGjRIjp27Fhot2xzku5g0tSa5x6rKJCmzmbeviCWLv0W85grnDt3Ls/a4BqNJle5v1u3btG1a1d69erFypUrC2ypzNOkpqaSkJAA5LSN/+qrr7h+/ToTJkzgxo0bAJQtW5bs7GzS09OxtrbG3NycixcvcufOHTQaDZY1m2DUewbq6HtE/DLxvyPn/Kai+u8vDnmu+FP9+5eKfxKRx+9bqVKlCA8Px9LSEgC1Wk1ERESuIaSiScmjUqlYv349zZo1o3PnznTt2rWoQ3oqlUpF9+7dcXR0xM/Pj5kzZzJv3jxmz55Nz549JQEXxZIk3kK8BTIyMvDz88Pb25tDhw7RuXNnPv74Y5ydnfOtS9zjtcwqlQpjY2MsLS1p2bIlEydOpFWrVrmO0TMtR4Vxa9DRNyAz8jYP100AoOrknOUYKUEnSDy7k8yoO6DJwqRhZyxd/o/sWt1Y/91cqlUpS2xsLFOmTGHXrl3ExcVhYGCASqWiSpUqODs78+2332Jvb5/vt8szMzOJjIzU/omIiMj19+OPw8PDSUlJ0SbFWVlZ/PXXX1hbW1OzZk3Gjh3LtGnTSExMpHv37tjY2HD9+nVOnTrF5cuX+frrr5k6dSqpkXfJPLya1HtXnohFt7QlWfERJPzhTVrIGcxavp9nzCoep+o51VQGDhzI1q1badWqFV27diU2Npbff/+djz/+mNmzZ+fr+yXePlZWVvzyyy8MHz6cCxcuFPovrC9LpVJp92fs3r1bm4DPmTMHJycnScBFsSKJtxBvqOzsbE6ePIm3tzc7duygcePGuLq6smbNGsqWLVtg53V2dsbKyoqAgAB+/fVXduzYgY+PDwMGDNAek5UcR/Jffk9NFDOj7oCODvplK6CODfvnmlQ6eJ28xbj6OtoNiTo6OlSqVImyZcvy7rvvvlI5NLVaTVRU1DMT6cd/JyUlUb58eaytrbGxsdGuz65evTpt2rTB1NQUX19fHj16xPfff8/cuXO5d+8eM2bMeGIDaOvWrZk9ezanT58mMzOT6tWrM3nyZAA8PDw4e/Ys+/fvJ/XeFcrYDyTW7/tcrzdvN5TY/T+SEX6djPtBmDR4sTKKa9eupXr16mzbto3169dTrlw52rRpQ/fu3V/6vRPFU6dOnRg5ciQjRozAz8/vrVg/rVKp6N27Nz179mTHjh18+eWXzJ07l7lz59K1a1dJwEWxIFVNhHiDKIrCxYsX8fb2xtfXFysrK23b9rzqQ+enx7PZO3bsoE+fPmRlZTF8+HB8fX0pV64cYWFh1K1Xj7DQUECFjnEZKo3/iay4B0/MeD8Wd3g1SX/u1s54AyjZapJ/cScu8gGNGzcmICAAU1PTJ+LJysoiOjr6iUQ6r4Q6ISEBS0tLbSL974T6fx8rV65cnkmIoihs3ryZL774AhcXF77++mssLCxe+f08deoU8+fP5/Lly9T96FtuZZjyKj9sVSpwrG/NqmHvvnIsomRSq9U4ODjQt29fvvjii6IO56VpNBq2bdvG7NmzKVeuHHPmzKFTp06SgIu3msx4C/EGuH37trZte3p6OkOHDuXgwYPUr1+/yGLS09Nj1qxZ+Pr6EhcXR0BAACkZOU1gjOu2I/X67yRd2IdRtWYvNW4pfX0q1qhPXOQD0tPTsbW1JS0tDUtLS6pWrUpiYiIRERHEx8djYWHxRCJduXJlmjdvnusxCwuL11rffv36ddzc3IiLi2P79u20bt36lcZRFIXjx48zf/58bt++zeTJk9mxYwfXo9IYvCaQNPXLN9Ex1NPFrUPBVaYRxZe+vj4+Pj60bNkSBwcHWrRoUdQhvRQdHR0GDhxIv3792LJlC25ubtjY2DB37lwcHByKOjwhXokk3kIUkejoaLZs2YKPjw8hISEMHDiQn376iTZt2rwxMzr/7vIYFRWFOjtnM6VJvfdQx9wj8cx2DCrWfakx1RoIv3MHgL///ps6deqQnJzM/fv3MTQ05LfffsPGxgZLS8sC3yyamprKggULWL16NTNmzMDNze2VuuopisKBAweYP38+UVFRTJ06FVdXV+369Ca2BkzrUfeFN6Q+ZqSvw7QedWlc2fylYxICcu5krVixgiFDhnDhwgXMzMyKOqSXpqury9ChQxk4cCA+Pj6MHj2aqlWrMnfuXNq2bVvU4QnxUt78RV9CFCPJycl4e3vTo0cPatWqRWBgINOnTyc8PBxPT0/s7e3fmKQb4N69e9qPExISyHrc9lylokzbIWhSE0i6sPcpr366ClVzZnCdnJwIDg7mwoULANy6dYuyZctibW1d4En3nj17aNCgAbdv3+bSpUtMmDDhpZNujUbDzp07adGiBV988QUeHh4EBwczcuTIJzaFDmtdjWk96mGkr8vzvsQqFHQ0WUzrUY9hrau95JUJkduAAQPo1KkTbm5ueVfQeUvo6enxwQcfEBwcjKurK8OGDcPR0ZHAwMCiDk2IFyYz3kL816t0X3wRarWagwcP4u3tjZ+fH+3atWPYsGH8+uuvmJg8u5ZzYcjKyiI8PJyMjAwAfv31V/z9/blz5462PrVKpWLVqlVkZam1rzOu2w79U1tIDf7jpc9Z4Z063A48kOdzBf2e3Lt3jwkTJhAcHMzq1atfqdxadnY227ZtY8GCBejr6zN9+nR69+793A1sw1pXo3Flc1YeD+HYjWhU/FPvHMBQTwcFqGeu4dEf2xjWuvdLxyZEXpYvX06LFi345ZdfGDFiRFGH81r09fUZNWoUw4YNY/369QwaNIiGDRsyZ84c3n1X9kKIN5tsrhQl3rO7L+YkQnl1X3wWjUbD6dOn8fb25tdff6V27dq4uroyYMAArKysCuAqni45OZl79+4RGhqa598RERFYW1sTHR1NRkYGNWrUoHz58oSGhhIeHo6enp62qomFTWXiIsOx6jsN49ptSLkeQMzOr7Xnery5MvXmaVJvBpL58Cbq2DD0zCtgULk+Brb1sWruxNjW1swb1pnExEQGDx7MzZs3+fPPP3FxcWHPnj0F8j5kZmby3XffsXTpUj777DMmTZr00nWu1Wo1mzdvZuHChZQtW5YZM2a8crmz2OQMtl24z/WHSSSmqzEz1KduhdL0t6vMnetXGDduHOfPn3/pcYV4mitXrtCpUycCAgKoXbt2UYeTbzIyMvj5559ZsGABdnZ2zJkzh2bNXm7viRCFRWa8RYn2Kt0Xn3Xr/9q1a9q27SYmJri6unL27FneeeedAolfo9EQFRX1zMQ6PT2dqlWrUqVKFe3f3bt3135eqVIl9PX1tVVNbt++zcOHD7X1oidOnEjLli0BMDHQJe5f5zeuY49++eqoo27niisz8jYpV49oP8+Kf0hW/EMAlOZOjHBowHsHD/L555+zfft2ypUrx7hx4wqs097x48dxc3PjnXfe4ezZs1SvXv2lXp+RkcGGDRtYtGgR1apVY+XKlXTs2PG1lgVZmBowrn2NPJ9LsrQkJibmlccWIi+NGjVi7ty5DB48mNOnTxebBksGBgaMHz+eDz/8kDVr1uDs7Kwt9dm4ceOiDk+IXGTGW5RYL9N98bGczW65192GhYWxefNmfHx8iI2NZciQIbi6utK4cePXXq+dkZFBWFjYU5PqsLAwzMzMciXVVatWzfWxhYVFvq4bH7vxTw4FR+b5i8rzFHZpvMjISL744gtOnDjB999//9LtqNPS0vjpp59YvHgxDRs2ZPr06YWymSslJYXy5cuTkpJS4OcSJYuiKPTr148qVaqwfPnyog6nQKSlpbFq1SoWL17Me++9x6xZs2jQoEFRhyUEIIm3KEamTJnCokWL+OCDD9iwYQMAbm5ueHl50aRJEy5evAjA6tWrGTduHMbVmmA1eMFLn8dIX5c1g+sT9Md+fHx8uHLlCv369WPo0KG0b9/+hRtVKIpCfHz8M2er4+LiqFSp0hOJ9eO/bW1tMTY2fulreB2XwuJfuTSekb4uW8a2LvAqHdnZ2axatYrZs2czatQoZsyYkWet8KdJTk7Gy8uL7777jlatWjF9+vRCXTuqKArGxsbExsYW+tdXFH9xcXE0a9aMFStW4OLiUtThFJiUlBRWrlzJ0qVL6dy5MzNnzqRu3ZerwiREfpOlJqLYaNeuHQABAQHax06dOgXkrG1MTEzEzMxM+7z+S5bBeywtU83A2WtpRzCfffYZTk5Oed6yzc7O5sGDB09NqkNDQwGemKG2s7PTPmZjY1Pg1T1eVhNb8ze6NN65c+cYP348xsbGHDt2jIYNG77wa+Pj4/H09OSHH36gU6dOHDhwoEhuVatUKiz/u9ykSpUqhX5+UbyVK1eOTZs2MWDAAC5cuEDFihWLOqQCYWJiwqRJkxg/fjyenp60b9+e7t27M2PGDGrVqlXU4YkSSma8RbHx6NEjLCwsUBSFhw8fYmJigrm5OXXr1iUoKIgDBw7QrVs33qlRg7u3b2PVbwZJ5/eQGX0XTVoyKn0DDG0bUK7bePTMrIjZ+x0pV49SttNobWv0mH3LSblyGMvOo7jgs5S/An9n/vz5XL9+nezsbCwsLKhQoQKRkZE8fPgQS0vLp85WV6lSBXNz86J9017D89bHP6ZS5TSBed76+Nf16NEjpk2bxvbt21m8eDHDhw9/4WUlMTExLF++nFWrVuHs7MyUKVOKfGasWbNmrF27Fjs7uyKNQxRfc+fO5fjx4xw6dOiN+wW/ICQmJvLDDz/w/fff4+LiwowZM156v4cQr0vqeItio2zZstSrVw/ImfUODAxEo9FoWyWfOnWKiIgI7t6+DagwqFib7OQ4jN6xw7SpI/rmNqSFnCXW/0cATBp2AiAl+HcAlOws0v4OBJUOBrXsaew8gvfff58///yTcuXKUblyZcLCwoiIiMDf35/ExETCw8M5ffo0vr6+LF68GHd3d3r27Enjxo3f6qQbckrjbRnbGsf61hjo6WCol/vHiaGeDgZ6OjjWt2bL2NYFlnQrisLGjRupX78+iqIQFBTEBx988EJJd0REBJMmTaJ27dpER0dz9uxZNmzYUORJN4CVlZVssBQFatq0aWg0mgLb1PymMTMzY/r06fz9999UrVqVli1bMmbMmFz9CoQoaLLURBQrbdu2JSgoiICAAG2Htl69elG7dm0CAgJo1KgRAPpWVdA1KYtV32mkhZwlO+UR+lZVyYy8RXroFRRFg2HVxuiaWeWUxIuPQB0ThiY9GcN37NAzt6Fhner88aeGevXq0a1bNyBn1vXxUpLHvwQUZ40rm7Nq2LvPLI33OjXQn+fatWu4ubmRnJzMrl27tNVXnicsLIwlS5awadMmhg0bxqVLl7C1tS2wOF+FpaUl0dHRRR2GKMZ0dXXZtGkTzZs3p2PHjtjb2xd1SIXC3Nyc2bNnM2HCBL777jvs7OwYOHAgU6dOfeN+DojiRxJvUay0bduWNWvWaBPvOnXqYGFhQbt27di6dSv169cHwKBSPdLDrhLpMxWU/1mnnK1GyUhDx9AEkwYdSDz9K6nX/0Adk7Mm27RRZwBiHoYDEBwcTHBwcK4hQkJCCvhK3yzPKo1XEFJSUpg3bx5r165l9uzZfPzxxy90q/z27dssWrSIbdu2MXr0aIKCgrCxsSmEiF+epZQUFIWgcuXKrF69mqFDh3Lx4sW3/k7cyyhXrhzz58/ns88+49tvv6Vp06YMHTqUKVOmvPS694JqwCaKH1lqIoqVx6Xe/vrrLwIDA7Wft2vXjuTkZDZu3AjkJN6pN06BosGwenNsJ27D5oNv/zVSzqJl08fLTa4dJ/XvM6gMjDGq1RoAywqVAejbty+Komj/PHz4kNGjRxfG5ZY4iqKwc+dO6tevz/3797ly5Qru7u7PTbqvX7/OiBEjaNmyJdbW1ty8eZMlS5a8sUk3SOItCk/v3r3p2bMnY8aMeatbyr8qS0tLvv76a4KDgzE0NKRRo0Z89tlnREREPPe1l8LiGbvxT9p+c5Rlh2+y8+IDjl6PYufFByw/fBP7b44ybtOfXAqLL/gLEW8FSbxFsVKzZk2sra1Rq9UkJydrb50+TsAfPXoEQOmqDdE1MQcg88EN4g79h5jdS58YT9/CllIVaqGOvouSkYJxnbbo6BtgqKeDS98BmJubs337dhwdHRk3bhxdunTB1taWyMjIwrngEuTOnTv07NmTKVOmsH79ejZt2vTcxPny5csMGjSI9u3bU6tWLUJCQpg3bx6WlpaFFPWrkzXeojAtWbKEv//+mzVr1hR1KEWmfPnyLFmyhGvXrqFSqahfvz5ffPEFUVFReR6/KfAug9cEcig4kowsTa6ux5DTgC0jS8PBoEgGrwlkU+DdQrgK8aaTxFsUO/9ep/j449q1a1O+fHkArKzKU6pcBUrbuWBUqzVKtpqMsKuUsR+Y53imDTv/6+OcGXAF+Khbc06cOIGLiwsXL15k06ZNhIeH4+7u/lYkdm+LjIwMFixYQIsWLWjbti2XLl2iY8eOz3zNuXPn6NOnD46OjrRo0YLbt28zffr0t+o2uqzxFoXJ0NAQX19fpk2bxrVr14o6nCJlY2PDsmXLuHr1KhkZGdSrV4/Jkyfn+kX4nwZsz67qBKAokKbOZoFfsCTfQsoJipLpbeq+WJIdOXIEd3d3ateuzQ8//EC1atWeeXxAQADz5s3j2rVrfPnll3z00UcYGRkVTrD57NixY8yZM4fjx48XdSiiBPn555/57rvvOHfu3Fv7vZPfwsLC+Prrr9myZQvjx4/HcchYxm4JKpAmYo+rMd25c+e5P+/E20lmvEWJ5N6hJoZ6r1a31lBPF7cONfM5IvFvDx8+ZOjQoYwePZrFixeze/fup/4npCgKR44coWPHjgwfPpx+/foREhLCJ5988lYnDrLGWxSFDz/8kEaNGvH5558XdShFYs+ePTg4OGBmZoaRkRGNGjViy5Yt/Pjjj1y4cIGoqCiGzFtHmjrrlcZPz8pm5fGnb77/9NNP+fTTT7VVuUTxIzPeosT651bhy3ZfrFegjWBKsqysLLy8vJg7dy5jxoxh2rRpmJiY5Hmsoij4+/szf/584uLimDp1KkOGDEFfX7+Qoy4YERERNG3a9IU2eAmRnxISEmjWrBlLly6lb9++RR1OofHy8sLNzQ0AJycnypYty44dO0hLS2PgwIFs2bKFmOQM7BcdITP71VMnAz0dTn3VSaqdlFCSeIsS7U3rvliSnTlzhvHjx1OmTBlWrlz51DroGo2GnTt3Mn/+fNRqNdOnT6d///7FrvOeWq3G2NiYjIwMdHTk5qQoXGfOnKFXr16cO3eOKlWqFHU4BS4pKYlKlSqRlJTEtGnTmD9/PgD79+/HyckJyFn+1W/wMOIiw7EeshDDqo1JvnyYWL/lGNg2xMZ1EVnJccTs/AZ1bBiajBR0DEwwqm5Hua4fo2NoipKtJuHQKpTQ86QnJ1K+fHmaNWvG7t27AVlqUhJIHW9Rog1rXY3Glc1ZeTyEYzeiUZGzE/0xQz0dFKBjHSvcOtR86ro88eri4uKYMmUKe/bsYcmSJQwdOjTPrpPZ2dls3bqVBQsWYGhoyKxZs+jZs2exTUr19fUxMTEhISGBsmXLFnU4ooRp1aoVn3/+OUOHDuX48ePo6RXvdOHUqVMkJSUBMGbMGO3j3bt3p2rVqty7d4+DBw+izn72HVIlMw0lKxOjmi1R6ZUi/e5FUq4dR6VviEV3D5KvHiXh4gEsKtfAddAAHjx4wO+//16g1ybeLMX7O0mIF1DU3RdLKo1Gwy+//MLkyZPp378/QUFBeVYdUavVbNq0ia+//horKyuWLl2Ko6PjC7WEf9s9XuctibcoCpMmTeLIkSPMnTuXuXPnFnU4Berf+ykqVKiQ67kKFSpw7949YmNjn7shX79cJSy6e5B29y80qQnoW1Yh69ED0u9dzjkgO2dDplmlGri6ulK/fn1Zz13CSOItxH8VdvfFkuzKlSu4ubmRnp7Ovn37aN68+RPHZGRksG7dOhYtWkSNGjVYvXo1Dg4OJSLhfuxx4l2rVq2iDkWUQDo6Ovzyyy/Y2dnRqVMnOnToUNQhFZh/l4CNjIzM1Tr+8T4LGxsb/vfHj/I/nY9Tgk4Qs3vJE+NrUhMAMGnYifTQK4T9dZJ27dqhUqno0qULO3bseOp+FlG8FM97tEKIN1JycjKTJk2iU6dODB06lMDAwCeS7tTUVL7//ntq1KjBnj178PHx4ciRI3To0KFEJd2Q00RHanmLomRjY8PPP//M8OHDi3WVHXt7e0qXLg3klFR87NChQ9y9exeAnj17YmqakxxrMtMAUEffyzVOSnDOshHTJt2oMmkHlr2/Ah73QgaVji62/afwvf9FgoOD6dKlC4cOHWL79u0FdWniDSMz3kKIAqcoCtu3b+f//u//6NixI1evXsXa2jrXMUlJSaxcuZJly5Zhb2/Prl278pwJL0mkpKB4E3Tv3p1BgwYxatQodu3aVSx/AS5dujSLFi3C3d2d2bNnc+7cOczNzdmxYweQs+773XffpW2rd9l2N4T4kxtJv3uRpIv+ucZ53BE57fZ5Yg+sJP3Wn7meTwk6QcSZ3zge0o4r5mW4cuUKwFvV3Eu8HpnxFkIUqFu3btGjRw9mzpzJxo0b2bBhQ66k+9GjR8ydO5fq1atz6dIlDh8+zPbt20t80g2SeIs3x8KFC3n48CGenp5FHUqBcXNzY/fu3Tg4OHDy5Em8vb1JTU1l6tSprFq1CoAli76mfM1GZMVHkBl5i9J2LrnGKNN2CAZVGqNJSyIzIgSzNrk7IutbVKKchQVHDh5g7dq1lCpViunTp+PiknscUXxJOUEhRIFIT09n8eLF/PDDD3z55Zd89tlnlCpVSvt8dHQ0y5Yt4z//+Q+9evViypQp1K5duwgjfrPEJGfg8e1GHqSqqFm/MWaGetS1MWNAc9nsK4pGSEgIbdq04dChQzRt2rSowylwp0+fpmvXrtjY2HDixAkqVaoEwKWweAavCSyQzpWi+JPEWwiR7w4ePIiHhwcNGzZk+fLlueoAP3z4kKVLl7Ju3ToGDhzIV199xTvvvFOE0b5ZLoXFs+J4CCduRpOdnUWW8s+NycflLTvUscLNoSZNbM2LLE5RMnl7ezNv3jzOnz9fIjYD/v777xw5coQ6deowZMgQ7ePSgE28Kkm8hRD5Jjw8nM8//5xz587xww8/5Lp9GhoayuLFi/Hx8eGDDz7giy++oHLlykUY7ZtHGjqJt8HIkSPR0dHJtQmxJJLvV/EqZHOlEOK1ZWVl8eOPP7JgwQLGjx/PunXrMDY2BnJuTy9atIjt27czZswYgoODn9hYWZxVq1aNe/fuPfV5BwcHTpw4of1cZWCMvoUt5u2GYlT9n3XuSRf2kXR+L1kJUaj0SlGqQk1mRIwCXBjWuhpjxowhICCA0NBQDAwMaNWqFUuWLKFBgwYFeXmiBPL09MTOzo7NmzdrZ4FjkjPYdv4+1yMSSUzPKhFLo6QBm3gVMuMthHgtp06dYvz48VhZWbFixQrq1KkDQHBwMAsXLsTf3x93d3cmTJiAhYVFEUdb+ObOnUtcXBwAXl5eZGZm0q9fP+1sf0xMDN7e3uiXtcGwegsyI2+Tcf8aKj0DKnlsQNfQlPR7l4ncPBVUOhjXbo067gHq6LvomllR69Nf2DK2NU1sy9KqVSsaNWrE4cOHuXv3LpUqVSIkJARDQ8OifAtEMXThwgUcHR3ZsPc4O2+mceJmTtnLjDwSz5KwNEoasIkXJYm3EOKVxMbG8tVXX+Hv78+3337LoEGDUKlUXLx4kQULFnDixAk+++wz3N3dKVOmTFGH+0YwNzcnISGBY8eOaZuRzJ49mzlz5mBUqzXl+01Hyc4i9Lv+kJ2FzQffYlCxDkmXDhLn/wOlbGpSYeRyMqPv8nCtB6h0qDppO90bVeKD6pnY29sDcPfuXe26+fPnz2NnZ1dUlyyKsVELf+ZofFlUeqVkqYUQL0jKCQohXopGo2Ht2rXUr18fExMTgoKCGDx4MOfOnaNXr1706NGDNm3acPv2baZOnSpJ93OkZmZpP1YUhcyIEMjOQqVngF7ZigAY12qFXtmKZEbcInrHQmJ2LwVUlGkzAHT0OHYjmjqN/1mWkpmZCeR0Hvzf9tdC5IdNgXc5lV4BdJ+ddAMoCqSps1ngF8ymwLuFEp8QbypJvIUQL+zSpUu0a9eONWvWsH//fr7//nsuX75Mt27d6N+/P46Ojty6dYvPP/8cU1PTog73rRD0IBGAtL8DCf2mJxEbv0DHwASrftPQNcrppKdjVBqTBh1ApSL1xinU0XfRM7fBoEpjAFTAtgv3gZzuoCNHjgRg4sSJkniLF1KtWjVUKhUqlYqAgADt47///rv28WrVqgFQ0bYKw9u8Q8iyYWjUGQBkRt7m3iIX7i36Z0P1o5MbefDzJ4QuG0josoHcWTeJaau2cfl+PAAnTpygadOmmJmZYWRkRK1atZgzZw5yI14UZ5J4CyGeKykpic8//5yuXbsycuRIAgICiImJwcHBgZEjRzJw4EBCQkJwd3fHyMioqMN9q8Qk5yQueuY2mDTqgo6hKZqMFNL+Pqs9Jvmv/ST84UMpmxpU/nQz1sMWkxX/kOjf5pKdmkB6lobrD5OIiYmhU6dOnD59mjFjxvDNN98U1WWJt5iXl5f248eNY/4tKT3nLk12chzJf/k9dZyUq8dAUTCu0xY9Mysy7l8jbPNMluw4DcCDBw8oV64cQ4YMoWfPnty5c4fZs2ezfv36/L0gId4gkngLIZ5KURS2bt1KvXr1iI+P5+rVq1SsWJG2bdsyYcIExowZw40bN/joo49yNccRL+7xZjR9q2pYOn+GVd9pQE4Vk8zI2wCoY3Kqouhb2KJrVBoDm1qgo4eiziArMWdT24P7obRt25Zz584xefJkVq9eXSxbe4uCVbZsWbZt20ZMTAzR0dH89ttvlC1bVvt8THIG6drGMSoSAn9Do07PcyzLXpOoONoTyx6fYjN8KSp9Q5TMNI6cDCA2OYMhQ4Zw9OhR/vOf/7B161Z69OgBwJ07dwr6MoUoMlJOUAiRp7///hsPDw8ePHiAj48PUVFRdOvWDUVRmD59On379kVXV7eow3zrGejlnv8wrNIIw2pNSb97kYTAbVj1/hKDyvVJurCPlKCTAGTFR4AmCx0jM/Qtcqqj7FvwESmPoqlSpQppaWl89tlnAAwdOpSWLVsW6jWJt9eIESNYvnw5P//8M4qikJGRgZubG8uWLQNg2/n72mON67Yj9frvJF3Yh1G1Zk+MZVi53j+fKAqKJmemXL+0Jdsu3Gdc+xqEhITg6elJeHg4fn5+VKpUiQ8++KBgL1KIIiSJtxDF1KvW1U1LS2PRokWsWLGCr776ivLly/Pxxx9jamrKvHnzcHFxkZnUfGSZx9eijP1g0u9eJPX6H6jbD8ekvgPZyY9IvnSA1OsBqPRKYVitKeYOH6Cjb4ihng4pj3JmvkNDQ/n++++1YzVt2lQSb/HCHBwcOHjwIKtXr0ZRFOrXr0/79u21iff1iETtZkqTeu+hjrlH4pntGFSs+9QxFU02sfuWQ3YWxnXbobKuxfWHSQDcv38/17/Xjh07YmVlVWDXJ0RRk8RbiGLm3y3H4X/r6kaw7PDNp9bV9ff355NPPqFJkyZMnjyZ//znP9jY2LB8+XK6du0qCfdrio+Pf+Kx9Z5LaGvrlPvrVKUhVSfvzXWcWcs+mLXsk+e4ChCTlC71gkW++Pjjj5kwYQIAP/74Y67nEtP/qcKDSkWZtkOI2fUNSRdy/3t9TKNOJ2bnItJu/YlRjRZYukz87zhqADp06IBGoyE8PJyxY8eyadMmDA0NWbNmTQFcmRBFT9Z4C1GMbAq8y+A1gRwKjiQjS5MrmYOcrmoZWRoOBkUyeE2gtrRXWFgY/fv3x93dHUdHR/78808OHDjATz/9xO+//063bt0k6S4glqYGONS24lXfXpUqpzOeJN0iv3zwwQcYGxtjYmLC8OHDcz1nZph7vs64bjv0raqRGvzHE+NkpyUR5TudtFt/YtKwE1b9pqPS0//vOPokJeXMeqtUKipXrsx7770HwM2bNwvisoR4I0jiLUQh69ChAyqVKl937q9fvx6VSsXYwb1IU2e/UF3dhPBbfNS3K7p6elSpUoUHDx4QGhrKypUr+eqrrzh06BAODg7PHOf48eO5yoyJV+PeoSaGeq+2Xt5QTxe3DjXzOSJRkpUpU4aTJ09y4sSJJ+rw17Uxy/VLouq/s945911yi942l4zw6+gYmqJjYMKjo2uJO7ya7HsXqFuhNH369MHBwYFx48YxcOBA5syZA4Cjo2NBXp4QRUqWmgiRz6pVq8a9ezlVKHR0dChfvjydOnXiu+++w9ramv79+9O0aVPq16+fb+cMjUsFQKN58fq3j46vI+NhCAYV66BKfUS5cuUoX748Dx8+zNfYxPM1sTVnWo+6LPALJk2tef4L/stIX4dpPerSuLJ5wQUnSqTmzZvn+Xj/5pX55H8eM65jj3756qijbud6PCspFgBNejJJ5/doH9c3MqW/XWUiHRzYuHEjZ8+epVSpUtSpU4cRI0bwf//3f/l6LUK8SSTxFqKAuLi4YGtry44dO/Dx8UGj0bB582Y8PDzy/VxHr0e+9Guy4h4AUKb9MDq/1xYft44yc12EHrfSXuB3nfSsZ9+1kBbcIr/dvXv3qc/16dMnV1ObD3/cx6HgSO2/UZVKRcVRPzzxuspuPz/xmEoFjvWtsTA1YObMmcycOfO1YxfibSJLTYQoIKNHj2blypUsWrQIyOn6CE8uNRk5ciQqlYrx48fj5OSEsbEx7777LhcvXtSO9bhznKenJzVq1MDc3JzRo0eTlpZGTHIG1yOSnjh/etg1IrwnE7ZsEPc9PyBm33Ky03K6JN5fOYqs+IcARPnOYLN7J2L/28jl3x53szt+/Djwz5KWDh065HnNgYGBmJqaYmxszKFDh8jKymLJkiXUq1cPExMT6tevL5umnmFY62psGdsax/rWGOjpYPi/pQb1dDDQ08GxvjVbxraWpFsUCVkaJcSrkxlvIQpQZmYm58+fB6Bx48bPPPY///kPffv2pWnTppw+fRoXFxdCQkIwNDTUHjNv3jycnZ3Zu3cvP//8M+bm5tTq5fbkeaPvEuk7DZWuPkY1WpCdHEfKlcNkJURhPWQBpo27knh2O0pmGsZ17DEoY6VtOf6qLl26hJOTExqNhl27dtG1a1emTJnCokWLqFOnDgMGDODo0aOMHTuWUqVKMWLEiNc6X3HVuLI5q4a9S2xyBtsu3Of6wyQS09WYGepTt0Jp+ts9uxykEAVNlkYJ8eok8RaigLz//vvaj9u3b4+np+czj+/duzfbtm1DrVZTuXJlwsPDOXLkCM7OztpjVq9eTe/evdm1axd9+vThl19+wbXlMLKyc69LSPrLH7Kz0Leuga6JObom5mQ8uEFG6GWy4u5j3m4IyZcPkZ2ZRmk7FwyrNtbW1X0V8fHxdOvWjYyMDG3SrSiK9prt7e0xMzOjadOmhIWF4eXlJYn3c1iYGjCufY2iDkOIPMnSKCFejSTeQhQQFxcX1Go1Bw4c4OzZs9y4cQNLS8unHl+vXk6XN319fapXr05UVBT379/P85i6dXOaVcTExPAoKfWJsbITctZ8Zz64QeaDG7meUz96iL6F7ROveVxX91mys7PzfDwhIQGAli1b0r59e21sycnJAKxbty7X8SEhIc89lxDizTasdTUaVzZn5fEQjt2IRkVOydLHDPV0UMgpd+nWoabMdAuBJN5CFJjRo0fTp08fRo0axbp165gwYYJ22UlegoODAVCr1dy+nVMdoHLlyk8cU7t2ba5fvw6ApaUlZUsbPzGWbhlrAEq36EO5zh9pH1fHR6BvbpPn+c0M9Z94zMTEBIDExJy14VevXs3ztZUqVaJu3bocOXKEoUOHsnXrViwtLTExMSElJYXLly/TqFEjABRF0VZ9EUK83WRplBAvRxJvIQrYrFmz2LhxIxcuXODAgQNPPW737t3079+fBw8eEBUVRcWKFenUqVOuY8aNG8fu3bvZsyenNNewYcMwSI8DJfdMdOkmjiRfPEDSn7vJio9A19gMdex9Mu4HU3XyHv6XoZ4OdSuUfuLxZs2aERQUxPTp0zly5AirVq3KM3Y9PT22b99Ou3bt2L59O+PHj2f16tW4u7uzePFiunbtSs+ePUlOTiYwMBAHB4d8rWMuhChasjRKiBcjVU2EKGBVq1bVdn97XOEkL25ubmRkZHDx4kXs7OzYs2cPRkZGuY6ZO3cuJ0+eJCMjgzZt2nD06FF+WzoJHVXub+VS1tWxHjwfA9uGZIRdIyX4dzQZqZi16Z/nuRWgv13lJx6fP38+bdq04fbt21y4cOGZpRDNzMzw8/OjUqVKrFmzhqlTpzJ//ny++eYbypUrx6ZNmzh69Ch16tRh0KBBTx1HCCGEKK5UivK8HndCiII0cuRINmzYwKxZs5g9e3aexzxu137ixAl2797N+vXradOmDR4eHnTt2pWPvS/kqqv7Mh7X1V017N3XuAohhBBCPI/MeAvxhtNo/tms1KdPH3R0dDh37hx79uzB0dERHR0dqasrhBBCvAUk8RbiDRUfH8+yZcuoU6eO9rGAgAAWL17MO++8k+vYx3V1jfRf7lta6uoKIYQQhUeWmgjxhrl8+TIrVqxg69atODk54eHhQZs2bbTLTZ5lU+BdqasrhBBCvKGkqokQbwC1Ws3OnTvx9PQkJCSEjz/+mODgYGxs8i799zRSV1cIIYR4c8mMtxBFKCIigjVr1rBq1Spq1qyJh4cHffr0QV//yZraL0vq6gohhBBvFkm8hShkiqJw+vRpPD098ff3Z9CgQbi7u2sbzAghhBCieJLEW4hCkpaWxubNm/H09CQpKQl3d3dGjhyJubl5UYcmhBBCiEIgibcQBezOnTt4eXmxbt06WrVqhYeHB926dUNHR4oKCSGEECWJ/M8vRAHQaDQcOHCAnj170qJFCzQaDYGBgezdu5fu3btL0i2EEEKUQFLVRIh8lJCQwPr161mxYgXGxsZ88sknbNmyBWNj46IOTQghhBBFTBJvIfLB1atXWbFiBb6+vnTv3p1169Zhb2//QrW3hRBCCFEySOItxCtSq9Xs2rULT09Pbt68yccff0xQUBAVKlQo6tCEEEII8QaSxFuIlxQZGamtvV29enU8PDx4//3386X2thBCCCGKL0m8hXgBiqIQGBjIihUr2LdvHwMGDGDfvn00adKkqEMTQgghxFtCygkK8QxpaWn4+vri6elJfHw87u7ufPjhh5QtW7aoQxNCCCHEW0YSbyHycPfuXby8vPj5559p2bIlHh4eODo6ShlAIYQQQrwyySKE+C+NRsPBgwfp3bs37777LllZWZw+fZp9+/bh5OQkSbcQQgghXous8RYlXkJCAhs2bGDFihUYGhri4eGBj48PJiYmRR2aEEIIIYoRSbxFiXXt2jVWrFjB5s2bcXR0ZO3atbRt21ZqbwshhBCiQEjiLUqUrKwsdu3axYoVKwgODmbcuHFcu3aNihUrFnVoQgghhCjmJPEWJUJUVJS29na1atVwd3enb9++lCpVqqhDE0IIIUQJIYm3KLYUReHs2bN4enqyd+9e+vfvz549e2jatGlRhyaEEEKIEkjKCYpiJz09nS1btuDp6UlcXBxubm58+OGHlCtXrqhDE0IIIUQJJom3KDbu3bunrb3dvHlzPDw86N69O7q6ukUdmhBCCCGE1PEWbzdFUTh8+DB9+vTBzs6OzMxMAgIC8Pf3x9nZWZJuIYQQQrwxZI23eCslJibyyy+/4OnpSalSpfDw8MDb21tqbwshhBDijSWJt3irBAUFaWtvd+nShdWrV/Pee+9J7W0hhBBCvPEk8RZvvKysLPbs2YOnpydBQUGMHTuWK1euUKlSpaIOTQghhBDihUniLd5Y0dHR/PTTT3h5eWFra4uHhwf9+vWT2ttCCCGEeCtJ4i3eOI9rb+/Zs4e+ffuyc+dO7OzsijosIYQQQojXIuUExRshPT2drVu34unpSXR0NO7u7nz44YdYWFgUdWhCCCGEEPlCEm9RpEJDQ1m1ahU//fQTdnZ2eHh44OTkJGUAhRBCCFHsSB1vUegUReHIkSO8//77NGvWjNTUVP744w/279+Pi4uLJN1CCCGEKJZkxlsUmqSkJG3tbT09PTw8PHB1dcXU1LSoQxNCCCGEKHCyuVIUuODgYFasWIGPjw+dO3dm1apVtG/fXmpvCyGEEKJEkcRbFIisrCz27t2Lp6cnV69eZcyYMVy+fJnKlSsXdWhCCCGEEEVCEm+Rr6Kjo1m7di1eXl5UqlQJd3d3+vfvj4GBQVGHJoQQQghRpCTxLoFikjPYdv4+1yMSSUzPwsxQj7o2ZgxoXhkL01dLkM+dO4enpye7d+/m/fffZ/v27TRv3jyfIxdCCCGEeHvJ5soS5FJYPCuOh3DiZjQAGVka7XOGejooQIc6Vrg51KSJrflzx8vIyNDW3o6MjMTNzY3Ro0dL7W0hhBBCiDxI4l1CbAq8ywK/66RnZfOsr7hKBYZ6ukzrUZdhravleUxYWJi29nbTpk1xd3fH2dlZygAKIYQQQjyD1PEuAXKS7mDS1P8k3cmXD3NvkQsR3pNzHasokKbOZoFfMJsC7/7rcYVjx47Rr18/mjRpQnJyMidPnuTAgQP06tVLkm4hhBBCiOeQNd7F1Pr16/nwww+f+rzNB99S+t1e6JWtkOfzaWoNC/yuU7NcKS4c3smKFSsA8PDwYP369ZQuXbpA4hZCCCGEKK5kqUkxdfbsWXx8fDgSHMm9uFRQFJIu7odsNaUq1KbCiO+eP4iiQX3nPG2yr+Lh4YGDg4PU3hZCCCGEeEWSeBdjMckZtP3mKBlZGuJPbiTh1BZ0DEtT4cPvSb93mVi/5RjYNsTGdREASRf2kXD6V5SsTMxa9SXpgh/ZiVH84rOV4UMGFPHVCCGEEEK83WSNdzG27fx9ANJunyfh9K+ACguXz9ErU/6JY9PvXSbuoBfZSbEYvtOMlGvHyE6KAeDU7djCDFsIIYQQoliSxLsYux6RSEpcFDF7vgVFg1nrfhjXbJHnsSnXjgNg0qgzVr0mYT1kYU6JE+D+o7TCClkIIYQQotiSxLsYi09JJ2bXN2jSEjGwbYh5++FPPTYrOWdWW98ip6W7rnEZdI3MAEjLzCr4YIUQQgghijlJvIuxy9tXkhEejI6JOZa9v0Sl8/SSf3qmOU1vsh49ACA7NYHstEQAjEpJ8RshhBBCiNclGVUx5efnx1/7NgGgX7YiiYHbcj2vZ2aV63OThh1JvnyQ5MuH0agzUEff43HR78pljQonaCGEEEKIYkwS72Lq7Nmz2o8z7geRcT8o1/MWPT7L9blhlUaU6zaehNO/kn77Amat+5H0526yk+PoUK9iYYQshBBCCFGsSTnBYm7sxj85FBz5zDbxj2nSU9AxNAEgKzGGcK9RoGgICQmhRo0aBRypEEIIIUTxJjPexZx7h5r8/ncMaers5x77cN0EjGq8i46RGSnBJ0HR8F6nrpJ0CyGEEELkA9lcWcw1sTVnWo+6GOk//0tdyqYGKcG/kxC4DRUKPYaOYc/2XwshSiGEEEKI4k+WmpQQmwLvssDvOulZ2c9cdqJSgaGeLtN61GVY62qFFp8QQgghRHEniXcJcvl+PCuPh3DsRjQqID1Lo33OUE8HBehYxwq3DjVpXNm8qMIUQgghhCiWJPEugWKTM9h24T7XHyaRmK7GzFCfuhVK09+uMhamBkUdnhBCCCFEsSSJtxBCCCGEEIVANlcKIYQQQghRCCTxFkIIIYQQohBI4i2EEEIIIUQhkMRbCCGEEEKIQiCJtxBCCCGEEIVAEm8hhBBCCCEKgSTeQgghhBBCFAJJvIUQQgghhCgEkngLIYQQQghRCCTxFkIIIYQQohBI4i2EEEIIIUQhkMRbCCGEEEKIQiCJtxBCCCGEEIVAEm8hhBBCCCEKgSTeQgghhBBCFAJJvIUQQgghhCgEkngLIYQQQghRCCTxFkIIIYQQohBI4i2EEEIIIUQhkMRbCCGEEEKIQiCJtxBCCCGEEIVAEm8hhBBCCCEKgSTeQgghhBBCFAJJvIUQQgghhCgEkngLIYQQQghRCCTxFkIIIYQQohBI4i2EEEIIIUQhkMRbCCGEEEKIQiCJtxBCCCGEEIXg/wF5pJmEpLblOwAAAABJRU5ErkJggg==\n"
},
"metadata": {}
}
],
"source": [
"plt.figure( figsize=(10,10) ) # 10in x 10in\n",
"nx.draw( dolphins, with_labels=True, font_weight=\"bold\" )\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because it is often difficult to lay out a graph in an attractive way on a two-dimensional drawing, there is some random experimentation involved in most network drawing algorithms, including the one used by NetworkX. So we see that the layout of the vertices is not exactly the same. The two clusters of dolphins may not be laid out in the same locations or orientations in this graph and in the previous one. In fact, every time I run the code, it looks a little different!\n",
"\n",
"### Better drawing tools\n",
"\n",
"NetworkX emphasizes that there are much more powerful graph-drawing software packages available. For instance, you might download [Gephi](https://gephi.org/) or [Cytoscape](https://cytoscape.org/) if you need to make more aesthetically pleasing images from your network data. To export your network from Python to that software, use the following code.\n",
"\n",
"```python\n",
"nx.write_graphml( dolphins, 'dolphins.graphml' )\n",
"```\n",
"\n",
"You can then import the `dolphins.graphml` file into either of those other pieces of software to visualize it more conveniently. Similarly, if you have data exported from either of those pieces of software that you want to bring into Python for use with NetworkX, you can use the [`nx.read_graphml()` function](https://networkx.github.io/documentation/networkx-1.10/reference/generated/networkx.readwrite.graphml.read_graphml.html).\n",
"\n",
"```{admonition} Learning on Your Own - Gephi\n",
"---\n",
"class: alert alert-danger\n",
"---\n",
" 1. Obtain some large network data. One easy option is to use the shipping data that you prepared for class today.\n",
" 2. Export that network data in GraphML format, as described above.\n",
" 3. Download and install [Gephi](https://gephi.org/).\n",
" 4. Import the data into Gephi and try visualizing it.\n",
" 5. Create a tutorial with instructions and screenshots that teaches the process to your classmates.\n",
"```\n",
"\n",
"```{admonition} Learning on Your Own - Cytoscape\n",
"---\n",
"class: alert alert-danger\n",
"---\n",
"This exercise is the same as the previous one, but using [Cytoscape](https://cytoscape.org/) instead of Gephi.\n",
"```\n",
"\n",
"### Drawing larger networks\n",
"\n",
"The dolphin network was fairly small (62 vertices) and fairly sparse (most dolphins socializing with only a few others). But a larger or more dense network will be much harder to visualize, because there will be too many vertices or edges to draw in a way that a human can make sense of. We will see an example of this in class when we consider the shipping data mentioned at the start of this chapter. In that situation, we will find it useful to sort the connections in the network based on some information about them (like the amount shipped), and draw only the most important connections."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Directed draphs in NetworkX\n",
"\n",
"The beginning of this chapter distinguished directed graphs (like the friends network, where arrows went one way only) from undirected graphs (like the dolphins network, where each relationship was reciprocal). To work with a directed graph in NetworkX, there are a few changes to what we learned above.\n",
"\n",
"First, you create a directed graph not with `nx.Graph()` but with `nx.DiGraph()`."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"friends = nx.DiGraph()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"But we can add vertices and edges exactly the same way as we did with the dolphins."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"friends.add_nodes_from( [ 'Augustus', 'Beatriz', 'Cyrano', 'Dauphine', 'Englebert' ] )\n",
"friends.add_edges_from( [\n",
" ('Augustus', 'Cyrano'),\n",
" ('Beatriz', 'Cyrano'),\n",
" ('Cyrano', 'Beatriz'),\n",
" ('Cyrano', 'Englebert'),\n",
" ('Dauphine', 'Cyrano'),\n",
" ('Englebert', 'Augustus'),\n",
" ('Englebert', 'Beatriz')\n",
"] )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"However, some computations make sense only in the context of a directed graph. For instance, we can measure the *reciprocity* of a directed graph, which asks how many of its edges are two-directional. In the friends case, only the Beatriz$\\to$Cyrano connection is reciprocated (Cyrano$\\to$Beatriz); all the others are one-directional. So we expect a low proportion as the result."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"0.2857142857142857"
]
},
"metadata": {},
"execution_count": 19
}
],
"source": [
"nx.reciprocity( friends )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are seven edges in the network, and two of them are part of a reciprocated relationship, so the reciprocity is $\\frac27\\approx0.285714$.\n",
"\n",
"We can draw directed graphs using the same tools as we used for undirected graphs."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "",
"image/svg+xml": "\n\n\n\n",
"image/png": 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\n"
},
"metadata": {}
}
],
"source": [
"nx.draw( friends, with_labels=True, node_size=5000 )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you plan to use network data in your final project for this course and would like to learn more about the power of NetworkX, including both computations and visualizations, I recommend Chapter 8 of [this book](https://link.springer.com/book/10.1007/978-3-319-50017-1)."
]
}
],
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3",
"language": "Python"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}