path: root/tutorial_full.ipynb

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   "source": [
    "## Tutorial\n",
    "\n",
    "This guide can help you start working with NetworkX.\n",
    "\n",
    "### Creating a graph\n",
    "\n",
    "Create an empty graph with no nodes and no edges."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "509e60e1",
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   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "G = nx.Graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f16129b",
   "metadata": {},
   "source": [
    "By definition, a `Graph` is a collection of nodes (vertices) along with\n",
    "identified pairs of nodes (called edges, links, etc).  In NetworkX, nodes can\n",
    "be any [hashable](https://docs.python.org/3/glossary.html#term-hashable) object e.g., a text string, an image, an XML object,\n",
    "another Graph, a customized node object, etc.\n",
    "\n",
    "# Nodes\n",
    "\n",
    "The graph `G` can be grown in several ways.  NetworkX includes many\n",
    "graph generator functions and\n",
    "facilities to read and write graphs in many formats.\n",
    "To get started though we’ll look at simple manipulations.  You can add one node\n",
    "at a time,"
   ]
  },
  {
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   "execution_count": 2,
   "id": "bd6562e0",
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    "execution": {
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   "outputs": [],
   "source": [
    "G.add_node(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d825f0d",
   "metadata": {},
   "source": [
    "or add nodes from any [iterable](https://docs.python.org/3/glossary.html#term-iterable) container, such as a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fbb02b73",
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "G.add_nodes_from([2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1329bd5",
   "metadata": {},
   "source": [
    "You can also add nodes along with node\n",
    "attributes if your container yields 2-tuples of the form\n",
    "`(node, node_attribute_dict)`:\n",
    "\n",
    "```\n",
    ">>> G.add_nodes_from([\n",
    "...     (4, {\"color\": \"red\"}),\n",
    "...     (5, {\"color\": \"green\"}),\n",
    "... ])\n",
    "```\n",
    "\n",
    "Node attributes are discussed further below.\n",
    "\n",
    "Nodes from one graph can be incorporated into another:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9f7ed036",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "H = nx.path_graph(10)\n",
    "G.add_nodes_from(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "352e5eb2",
   "metadata": {},
   "source": [
    "`G` now contains the nodes of `H` as nodes of `G`.\n",
    "In contrast, you could use the graph `H` as a node in `G`."
   ]
  },
  {
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   "execution_count": 5,
   "id": "70997bf3",
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   "outputs": [],
   "source": [
    "G.add_node(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6b38e18",
   "metadata": {},
   "source": [
    "The graph `G` now contains `H` as a node.  This flexibility is very powerful as\n",
    "it allows graphs of graphs, graphs of files, graphs of functions and much more.\n",
    "It is worth thinking about how to structure your application so that the nodes\n",
    "are useful entities.  Of course you can always use a unique identifier in `G`\n",
    "and have a separate dictionary keyed by identifier to the node information if\n",
    "you prefer.\n",
    "\n",
    "# Edges\n",
    "\n",
    "`G` can also be grown by adding one edge at a time,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9eea36b7",
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   "outputs": [],
   "source": [
    "G.add_edge(1, 2)\n",
    "e = (2, 3)\n",
    "G.add_edge(*e)  # unpack edge tuple*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b464b93d",
   "metadata": {},
   "source": [
    "by adding a list of edges,"
   ]
  },
  {
   "cell_type": "code",
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   "id": "34f152ab",
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    "execution": {
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   },
   "outputs": [],
   "source": [
    "G.add_edges_from([(1, 2), (1, 3)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f21d2b4",
   "metadata": {},
   "source": [
    "or by adding any ebunch of edges.  An *ebunch* is any iterable\n",
    "container of edge-tuples.  An edge-tuple can be a 2-tuple of nodes or a 3-tuple\n",
    "with 2 nodes followed by an edge attribute dictionary, e.g.,\n",
    "`(2, 3, {'weight': 3.1415})`.  Edge attributes are discussed further\n",
    "below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "043d9118",
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "G.add_edges_from(H.edges)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0e6b3d0",
   "metadata": {},
   "source": [
    "There are no complaints when adding existing nodes or edges. For example,\n",
    "after removing all nodes and edges,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a7803e90",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.321789Z",
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   },
   "outputs": [],
   "source": [
    "G.clear()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf6cae4",
   "metadata": {},
   "source": [
    "we add new nodes/edges and NetworkX quietly ignores any that are\n",
    "already present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7200f52c",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "G.add_edges_from([(1, 2), (1, 3)])\n",
    "G.add_node(1)\n",
    "G.add_edge(1, 2)\n",
    "G.add_node(\"spam\")        # adds node \"spam\"\n",
    "G.add_nodes_from(\"spam\")  # adds 4 nodes: 's', 'p', 'a', 'm'\n",
    "G.add_edge(3, 'm')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5b9201c",
   "metadata": {},
   "source": [
    "At this stage the graph `G` consists of 8 nodes and 3 edges, as can be seen by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a5ee0237",
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.number_of_nodes()\n",
    "G.number_of_edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f3096427",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "DG = nx.DiGraph()\n",
    "DG.add_edge(2, 1)   # adds the nodes in order 2, 1\n",
    "DG.add_edge(1, 3)\n",
    "DG.add_edge(2, 4)\n",
    "DG.add_edge(1, 2)\n",
    "assert list(DG.successors(2)) == [1, 4]\n",
    "assert list(DG.edges) == [(2, 1), (2, 4), (1, 3), (1, 2)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2250e7f",
   "metadata": {},
   "source": [
    "# Examining elements of a graph\n",
    "\n",
    "We can examine the nodes and edges. Four basic graph properties facilitate\n",
    "reporting: `G.nodes`, `G.edges`, `G.adj` and `G.degree`.  These\n",
    "are set-like views of the nodes, edges, neighbors (adjacencies), and degrees\n",
    "of nodes in a graph. They offer a continually updated read-only view into\n",
    "the graph structure. They are also dict-like in that you can look up node\n",
    "and edge data attributes via the views and iterate with data attributes\n",
    "using methods `.items()`, `.data()`.\n",
    "If you want a specific container type instead of a view, you can specify one.\n",
    "Here we use lists, though sets, dicts, tuples and other containers may be\n",
    "better in other contexts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "50bbc2f9",
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    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "list(G.nodes)\n",
    "list(G.edges)\n",
    "list(G.adj[1])  # or list(G.neighbors(1))\n",
    "G.degree[1]  # the number of edges incident to 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af406d27",
   "metadata": {},
   "source": [
    "One can specify to report the edges and degree from a subset of all nodes\n",
    "using an nbunch. An *nbunch* is any of: `None` (meaning all nodes),\n",
    "a node, or an iterable container of nodes that is not itself a node in the\n",
    "graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b9a24473",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.355518Z",
     "iopub.status.busy": "2023-02-26T01:59:52.355282Z",
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     "shell.execute_reply": "2023-02-26T01:59:52.359111Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DegreeView({2: 1, 3: 2})"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.edges([2, 'm'])\n",
    "G.degree([2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9277ad57",
   "metadata": {},
   "source": [
    "# Removing elements from a graph\n",
    "\n",
    "One can remove nodes and edges from the graph in a similar fashion to adding.\n",
    "Use methods\n",
    "`Graph.remove_node()`,\n",
    "`Graph.remove_nodes_from()`,\n",
    "`Graph.remove_edge()`\n",
    "and\n",
    "`Graph.remove_edges_from()`, e.g."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2e9d83af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.362428Z",
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     "shell.execute_reply": "2023-02-26T01:59:52.364859Z"
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   },
   "outputs": [],
   "source": [
    "G.remove_node(2)\n",
    "G.remove_nodes_from(\"spam\")\n",
    "list(G.nodes)\n",
    "G.remove_edge(1, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20eaa24a",
   "metadata": {},
   "source": [
    "# Using the graph constructors\n",
    "\n",
    "Graph objects do not have to be built up incrementally - data specifying\n",
    "graph structure can be passed directly to the constructors of the various\n",
    "graph classes.\n",
    "When creating a graph structure by instantiating one of the graph\n",
    "classes you can specify data in several formats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "086e518e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.367959Z",
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     "shell.execute_reply": "2023-02-26T01:59:52.627632Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 1), (0, 2), (1, 2)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.add_edge(1, 2)\n",
    "H = nx.DiGraph(G)  # create a DiGraph using the connections from G\n",
    "list(H.edges())\n",
    "edgelist = [(0, 1), (1, 2), (2, 3)]\n",
    "H = nx.Graph(edgelist)  # create a graph from an edge list\n",
    "list(H.edges())\n",
    "adjacency_dict = {0: (1, 2), 1: (0, 2), 2: (0, 1)}\n",
    "H = nx.Graph(adjacency_dict)  # create a Graph dict mapping nodes to nbrs\n",
    "list(H.edges())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "715a10d5",
   "metadata": {},
   "source": [
    "# What to use as nodes and edges\n",
    "\n",
    "You might notice that nodes and edges are not specified as NetworkX\n",
    "objects.  This leaves you free to use meaningful items as nodes and\n",
    "edges. The most common choices are numbers or strings, but a node can\n",
    "be any hashable object (except `None`), and an edge can be associated\n",
    "with any object `x` using `G.add_edge(n1, n2, object=x)`.\n",
    "\n",
    "As an example, `n1` and `n2` could be protein objects from the RCSB Protein\n",
    "Data Bank, and `x` could refer to an XML record of publications detailing\n",
    "experimental observations of their interaction.\n",
    "\n",
    "We have found this power quite useful, but its abuse\n",
    "can lead to surprising behavior unless one is familiar with Python.\n",
    "If in doubt, consider using `convert_node_labels_to_integers()` to obtain\n",
    "a more traditional graph with integer labels.\n",
    "\n",
    "# Accessing edges and neighbors\n",
    "\n",
    "In addition to the views `Graph.edges`, and `Graph.adj`,\n",
    "access to edges and neighbors is possible using subscript notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ef2ac6b1",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-02-26T01:59:52.637316Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'color': 'yellow'}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G = nx.Graph([(1, 2, {\"color\": \"yellow\"})])\n",
    "G[1]  # same as G.adj[1]\n",
    "G[1][2]\n",
    "G.edges[1, 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dc01db8",
   "metadata": {},
   "source": [
    "You can get/set the attributes of an edge using subscript notation\n",
    "if the edge already exists."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9a28c088",
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'color': 'red'}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.add_edge(1, 3)\n",
    "G[1][3]['color'] = \"blue\"\n",
    "G.edges[1, 2]['color'] = \"red\"\n",
    "G.edges[1, 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d9371d4",
   "metadata": {},
   "source": [
    "Fast examination of all (node, adjacency) pairs is achieved using\n",
    "`G.adjacency()`, or `G.adj.items()`.\n",
    "Note that for undirected graphs, adjacency iteration sees each edge twice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4a1ceee5",
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 2, 0.125)\n",
      "(2, 1, 0.125)\n",
      "(3, 4, 0.375)\n",
      "(4, 3, 0.375)\n"
     ]
    }
   ],
   "source": [
    "FG = nx.Graph()\n",
    "FG.add_weighted_edges_from([(1, 2, 0.125), (1, 3, 0.75), (2, 4, 1.2), (3, 4, 0.375)])\n",
    "for n, nbrs in FG.adj.items():\n",
    "   for nbr, eattr in nbrs.items():\n",
    "       wt = eattr['weight']\n",
    "       if wt < 0.5: print(f\"({n}, {nbr}, {wt:.3})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a85bf73b",
   "metadata": {},
   "source": [
    "Convenient access to all edges is achieved with the edges property."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a83a3c2c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.657586Z",
     "iopub.status.busy": "2023-02-26T01:59:52.657262Z",
     "iopub.status.idle": "2023-02-26T01:59:52.661858Z",
     "shell.execute_reply": "2023-02-26T01:59:52.661210Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 2, 0.125)\n",
      "(3, 4, 0.375)\n"
     ]
    }
   ],
   "source": [
    "for (u, v, wt) in FG.edges.data('weight'):\n",
    "    if wt < 0.5:\n",
    "        print(f\"({u}, {v}, {wt:.3})\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b485a1c1",
   "metadata": {},
   "source": [
    "# Adding attributes to graphs, nodes, and edges\n",
    "\n",
    "Attributes such as weights, labels, colors, or whatever Python object you like,\n",
    "can be attached to graphs, nodes, or edges.\n",
    "\n",
    "Each graph, node, and edge can hold key/value attribute pairs in an associated\n",
    "attribute dictionary (the keys must be hashable).  By default these are empty,\n",
    "but attributes can be added or changed using `add_edge`, `add_node` or direct\n",
    "manipulation of the attribute dictionaries named `G.graph`, `G.nodes`, and\n",
    "`G.edges` for a graph `G`.\n",
    "\n",
    "## Graph attributes\n",
    "\n",
    "Assign graph attributes when creating a new graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1937ca75",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.664478Z",
     "iopub.status.busy": "2023-02-26T01:59:52.663980Z",
     "iopub.status.idle": "2023-02-26T01:59:52.668249Z",
     "shell.execute_reply": "2023-02-26T01:59:52.667612Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'day': 'Friday'}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G = nx.Graph(day=\"Friday\")\n",
    "G.graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96061e33",
   "metadata": {},
   "source": [
    "Or you can modify attributes later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bdc65098",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.671346Z",
     "iopub.status.busy": "2023-02-26T01:59:52.670812Z",
     "iopub.status.idle": "2023-02-26T01:59:52.675091Z",
     "shell.execute_reply": "2023-02-26T01:59:52.674440Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'day': 'Monday'}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.graph['day'] = \"Monday\"\n",
    "G.graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "013ee034",
   "metadata": {},
   "source": [
    "# Node attributes\n",
    "\n",
    "Add node attributes using `add_node()`, `add_nodes_from()`, or `G.nodes`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5f30fb34",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.677560Z",
     "iopub.status.busy": "2023-02-26T01:59:52.677153Z",
     "iopub.status.idle": "2023-02-26T01:59:52.682171Z",
     "shell.execute_reply": "2023-02-26T01:59:52.681509Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeDataView({1: {'time': '5pm', 'room': 714}, 3: {'time': '2pm'}})"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.add_node(1, time='5pm')\n",
    "G.add_nodes_from([3], time='2pm')\n",
    "G.nodes[1]\n",
    "G.nodes[1]['room'] = 714\n",
    "G.nodes.data()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6cdd75a",
   "metadata": {},
   "source": [
    "Note that adding a node to `G.nodes` does not add it to the graph, use\n",
    "`G.add_node()` to add new nodes. Similarly for edges.\n",
    "\n",
    "# Edge Attributes\n",
    "\n",
    "Add/change edge attributes using `add_edge()`, `add_edges_from()`,\n",
    "or subscript notation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0d67c3ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.684960Z",
     "iopub.status.busy": "2023-02-26T01:59:52.684623Z",
     "iopub.status.idle": "2023-02-26T01:59:52.688859Z",
     "shell.execute_reply": "2023-02-26T01:59:52.688231Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edge(1, 2, weight=4.7 )\n",
    "G.add_edges_from([(3, 4), (4, 5)], color='red')\n",
    "G.add_edges_from([(1, 2, {'color': 'blue'}), (2, 3, {'weight': 8})])\n",
    "G[1][2]['weight'] = 4.7\n",
    "G.edges[3, 4]['weight'] = 4.2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96fa928f",
   "metadata": {},
   "source": [
    "The special attribute `weight` should be numeric as it is used by\n",
    "algorithms requiring weighted edges.\n",
    "\n",
    " Directed graphs\n",
    "\n",
    "The `DiGraph` class provides additional methods and properties specific\n",
    "to directed edges, e.g.,\n",
    "`DiGraph.out_edges`, `DiGraph.in_degree`,\n",
    "`DiGraph.predecessors`, `DiGraph.successors` etc.\n",
    "To allow algorithms to work with both classes easily, the directed versions of\n",
    "`neighbors` is equivalent to\n",
    "`successors` while `degree` reports the sum\n",
    "of `in_degree` and `out_degree` even though that may feel inconsistent at times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "83d74f74",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.691700Z",
     "iopub.status.busy": "2023-02-26T01:59:52.691271Z",
     "iopub.status.idle": "2023-02-26T01:59:52.696779Z",
     "shell.execute_reply": "2023-02-26T01:59:52.696133Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DG = nx.DiGraph()\n",
    "DG.add_weighted_edges_from([(1, 2, 0.5), (3, 1, 0.75)])\n",
    "DG.out_degree(1, weight='weight')\n",
    "DG.degree(1, weight='weight')\n",
    "list(DG.successors(1))\n",
    "list(DG.neighbors(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be22350a",
   "metadata": {},
   "source": [
    "Some algorithms work only for directed graphs and others are not well\n",
    "defined for directed graphs.  Indeed the tendency to lump directed\n",
    "and undirected graphs together is dangerous.  If you want to treat\n",
    "a directed graph as undirected for some measurement you should probably\n",
    "convert it using `Graph.to_undirected()` or with"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7f9d17cf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.699771Z",
     "iopub.status.busy": "2023-02-26T01:59:52.699353Z",
     "iopub.status.idle": "2023-02-26T01:59:52.702771Z",
     "shell.execute_reply": "2023-02-26T01:59:52.702136Z"
    }
   },
   "outputs": [],
   "source": [
    "H = nx.Graph(G)  # create an undirected graph H from a directed graph G"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "258a0a35",
   "metadata": {},
   "source": [
    "# Multigraphs\n",
    "\n",
    "NetworkX provides classes for graphs which allow multiple edges\n",
    "between any pair of nodes.  The `MultiGraph` and\n",
    "`MultiDiGraph`\n",
    "classes allow you to add the same edge twice, possibly with different\n",
    "edge data.  This can be powerful for some applications, but many\n",
    "algorithms are not well defined on such graphs.\n",
    "Where results are well defined,\n",
    "e.g., `MultiGraph.degree()` we provide the function.  Otherwise you\n",
    "should convert to a standard graph in a way that makes the measurement\n",
    "well defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b7d8bd66",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.705221Z",
     "iopub.status.busy": "2023-02-26T01:59:52.704881Z",
     "iopub.status.idle": "2023-02-26T01:59:52.711499Z",
     "shell.execute_reply": "2023-02-26T01:59:52.710832Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MG = nx.MultiGraph()\n",
    "MG.add_weighted_edges_from([(1, 2, 0.5), (1, 2, 0.75), (2, 3, 0.5)])\n",
    "dict(MG.degree(weight='weight'))\n",
    "GG = nx.Graph()\n",
    "for n, nbrs in MG.adjacency():\n",
    "   for nbr, edict in nbrs.items():\n",
    "       minvalue = min([d['weight'] for d in edict.values()])\n",
    "       GG.add_edge(n, nbr, weight = minvalue)\n",
    "\n",
    "nx.shortest_path(GG, 1, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8621f50",
   "metadata": {},
   "source": [
    "# Graph generators and graph operations\n",
    "\n",
    "In addition to constructing graphs node-by-node or edge-by-edge, they\n",
    "can also be generated by\n",
    "\n",
    "## 1. Applying classic graph operations, such as:\n",
    "\n",
    "## 2. Using a call to one of the classic small graphs, e.g.,\n",
    "\n",
    "## 3. Using a (constructive) generator for a classic graph, e.g.,\n",
    "\n",
    "like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3e5e0ff5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.714527Z",
     "iopub.status.busy": "2023-02-26T01:59:52.714013Z",
     "iopub.status.idle": "2023-02-26T01:59:52.718384Z",
     "shell.execute_reply": "2023-02-26T01:59:52.717741Z"
    }
   },
   "outputs": [],
   "source": [
    "K_5 = nx.complete_graph(5)\n",
    "K_3_5 = nx.complete_bipartite_graph(3, 5)\n",
    "barbell = nx.barbell_graph(10, 10)\n",
    "lollipop = nx.lollipop_graph(10, 20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3943038c",
   "metadata": {},
   "source": [
    "# 4. Using a stochastic graph generator, e.g,\n",
    "\n",
    "like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "439a61bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.720828Z",
     "iopub.status.busy": "2023-02-26T01:59:52.720487Z",
     "iopub.status.idle": "2023-02-26T01:59:52.735072Z",
     "shell.execute_reply": "2023-02-26T01:59:52.733943Z"
    }
   },
   "outputs": [],
   "source": [
    "er = nx.erdos_renyi_graph(100, 0.15)\n",
    "ws = nx.watts_strogatz_graph(30, 3, 0.1)\n",
    "ba = nx.barabasi_albert_graph(100, 5)\n",
    "red = nx.random_lobster(100, 0.9, 0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bc4b49a",
   "metadata": {},
   "source": [
    "# 5. Reading a graph stored in a file using common graph formats\n",
    "\n",
    "NetworkX supports many popular formats, such as edge lists, adjacency lists,\n",
    "GML, GraphML, LEDA and others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "740569d3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:52.737694Z",
     "iopub.status.busy": "2023-02-26T01:59:52.737345Z",
     "iopub.status.idle": "2023-02-26T01:59:53.058128Z",
     "shell.execute_reply": "2023-02-26T01:59:53.057088Z"
    }
   },
   "outputs": [],
   "source": [
    "nx.write_gml(red, \"path.to.file\")\n",
    "mygraph = nx.read_gml(\"path.to.file\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ecfcaf4",
   "metadata": {},
   "source": [
    "For details on graph formats see Reading and writing graphs\n",
    "and for graph generator functions see Graph generators\n",
    "\n",
    " Analyzing graphs\n",
    "\n",
    "The structure of `G` can be analyzed using various graph-theoretic\n",
    "functions such as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f8750762",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.061833Z",
     "iopub.status.busy": "2023-02-26T01:59:53.061350Z",
     "iopub.status.idle": "2023-02-26T01:59:53.067737Z",
     "shell.execute_reply": "2023-02-26T01:59:53.067050Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 0, 2: 0, 3: 0, 'spam': 0}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G = nx.Graph()\n",
    "G.add_edges_from([(1, 2), (1, 3)])\n",
    "G.add_node(\"spam\")       # adds node \"spam\"\n",
    "list(nx.connected_components(G))\n",
    "sorted(d for n, d in G.degree())\n",
    "nx.clustering(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77d7137b",
   "metadata": {},
   "source": [
    "Some functions with large output iterate over (node, value) 2-tuples.\n",
    "These are easily stored in a [dict](https://docs.python.org/3/library/stdtypes.html#dict) structure if you desire."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b96e8565",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.070685Z",
     "iopub.status.busy": "2023-02-26T01:59:53.070293Z",
     "iopub.status.idle": "2023-02-26T01:59:53.076571Z",
     "shell.execute_reply": "2023-02-26T01:59:53.075668Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{3: [3], 1: [3, 1], 2: [3, 1, 2]}"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sp = dict(nx.all_pairs_shortest_path(G))\n",
    "sp[3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13102485",
   "metadata": {},
   "source": [
    "See Algorithms for details on graph algorithms\n",
    "supported.\n",
    "\n",
    "# Drawing graphs\n",
    "\n",
    "NetworkX is not primarily a graph drawing package but basic drawing with\n",
    "Matplotlib as well as an interface to use the open source Graphviz software\n",
    "package are included.  These are part of the networkx.drawing\n",
    "module and will be imported if possible.\n",
    "\n",
    "First import Matplotlib’s plot interface (pylab works too)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "0d23c39c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.079488Z",
     "iopub.status.busy": "2023-02-26T01:59:53.078967Z",
     "iopub.status.idle": "2023-02-26T01:59:53.394606Z",
     "shell.execute_reply": "2023-02-26T01:59:53.393169Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cea4268",
   "metadata": {},
   "source": [
    "To test if the import of `nx_pylab` was successful draw `G`\n",
    "using one of"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "12db14b2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.398051Z",
     "iopub.status.busy": "2023-02-26T01:59:53.397540Z",
     "iopub.status.idle": "2023-02-26T01:59:53.633388Z",
     "shell.execute_reply": "2023-02-26T01:59:53.632795Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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zSMjOziZDhw4lAMjChQsZ652BgWLevn1LVFRUyPr16+U676pVqwiHwyERERFynbc0wsLCSK9evQgA0rx5cxIYGCjzcElthzEGZERqaioxMzMjXbp0kfkNc8OGDURDQ4MUFhbKdB4JYrGYrF+/nrDZbOLh4UFSU1PlMi8DQ21g3rx5RF9fX+41/gsLC4m9vT1xcnJSGCP/wYMHpHv37gQAcXBwICdPnmSMAhnBhAlkACEEEyZMgEAgwKFDh8DhcGQ6H4/HQ35+PqKiomQ6jwQWi4V58+bh2rVrePToEdq0aYOIiAi5zM3AUJPJyMjAnj17MG3atEp1MaUCFRUV7Nu3DxEREdi2bZtc55YGj8fD5cuXcefOHdSpUweDBg2Ck5MTzp49S/kOqtoOYwzIgJ07d+LcuXP4559/YGZmJvP5HB0dweVyZZ438D1dunRBeHg4TExM0L59exw4cECu8zMw1DR27tyJoqIizJo1i5b5XV1dMX36dCxZsgQJCQm0aCiN9u3b4/r167h58yb09fUxYMAAODs74+LFi4xRQBU0eyZqHI8fPyZqampk5syZcp3X0dGRjB07Vq5zSsjPzyfjxo0jAMj06dOJQCCgRQcDgzKTl5dHTExMyNSpU2nVkZmZSerXr0969+6tsD1K/v33X+Lm5kYAEBcXFxIcHKywWpUFxhigkNzcXNK8eXPSokULudffnjp1KmnWrJlc5/wasVhMdu/eTVRUVEj79u3Jhw8faNPCwKCM7Nixg7DZbIUoAX769GkCgAQGBtItRSpisZhcu3aNtG3blgAgbdu2JVevXmWMgirChAkoZO7cuXj9+jUCAgKgrq4u17l5PB5evHiBzMxMuc4rgcViYfLkybh16xZev34NR0dH3L17lxYtDAzKhlAoxPr16zFkyBBYWVnRLQcDBgyAl5cXZs6ciYyMDLrllAqLxYKHhwfu3r2L4OBgiEQieHp6omPHjggJCaFbntLBGAMUcfLkSezZswdbt25Fs2bN5D4/j8cDIQR8Pl/uc3+Nq6srwsPDYW1tjc6dO2PHjh1MTI+BoRxOnDiB169fY+HChXRLKWHbtm3Iy8vDokWL6JZSJiwWCz169MCDBw9w4cIF5Ofno0uXLnB3d8etW7folqc80O2aqAkkJCQQfX19MnjwYNpcVCKRiOjr65M///yTlvm/p7CwkMyaNYsAIGPGjGF6mTMwSEEsFpNWrVoRT09PuqX8wPbt2wkAcvv2bbqlVBixWEzOnj1LWrZsSQCQrl27kjt37tAtS+FhuhZWE6FQiC5duiAhIQGPHj2CgYEBbVq6d+8OVVVVnD9/njYN33P48GFMmjQJTZs2xalTp9CwYUO6JTEwKBRXrlxBjx49cOPGDXTp0oVuOd8gEong5uaGzMxMREZGQk1NjW5JFUYsFuPMmTNYvnw5nj59Ck9PT6xYsQKurq50S1NImDBBNfnrr79w9+5dHD16lFZDAJBdB8Pq4O3tjXv37iEjIwNt2rTB9evX6ZbEwKBQ+Pr6ok2bNnB3d6dbyg9wOBzs3bsXcXFx8PX1pVtOpWCz2Rg4cCAePXqEwMBAvHv3Dm3btkXv3r3x8OFDuuUpHjR7JpSaW7duETabTVauXEm3FEIIIRcuXCAAyKtXr+iW8gNpaWmke/fuhM1mE19fXybjl4GBEBIaGkoAkBMnTtAtpUx+/fVXoqqqSp4/f063lCojFArJsWPHiK2tLQFA+vbtqxCllxUFxhioImlpacTc3Jx07NhRYUp3pqSkEADk2LFjdEspFaFQSH777TcCgAwaNEju5VYZGBSNgQMHEmtra4VZQ6SRl5dHGjduTDp27Kj05YCFQiE5dOgQsba2JgCIl5cXefz4Md2yaIcJE1QBQggmTpyInJwcHD58WOblhiuKiYkJrKys5F6JsKJwOBz8+eefOHXqFK5evQoej4eYmBi6ZTEw0EJMTAxOnz6NBQsWKMwaIg0NDQ3s2bMHt27dwj///EO3nGrB4XDg7e2NZ8+eYf/+/Xj8+DFatmyJIUOGyK2kuyLCGANVYN++fTh16hT8/Pxgbm5Ot5xvkOQNKDJeXl4ICwsDIQQuLi44e/Ys3ZIYGOTO+vXrUa9ePfz00090S6kQXbt2xZgxYzB//nwkJyfTLafacLlcjBkzBi9evICfnx8ePnyIFi1aYPjw4Xj+/Dnd8uQP3a4JZSMqKoqoq6vTXjJUGps3byZqampKURI4MzOTeHl5EQBkyZIlCu8qZWCgivfv3xNVVVXi6+tLt5RKkZqaSoyMjMjw4cPplkI5AoGA7Nmzh5ibmxMWi0VGjRpFYmJi6JYlNxhjoBLk5eURBwcHYmdnp7D75u/fv08AED6fT7eUCiEWi8mqVasIi8UiPXv2JOnp6XRLYmCQOQsWLCC6urrk8+fPdEupNAcPHiQAyKVLl+iWIhMKCgrIzp07Sf369QmbzSY//fQTiYuLo1uWzGGMgUowffp0oq6uTp4+fUq3FKkUFBQQVVVVsn37drqlVIorV64QQ0NDYmVlxSTzMNRoMjIyiI6ODlm0aBHdUqqEWCwmHh4exNLSkuTk5NAtR2bk5+eTrVu3ElNTU8LhcMi4ceMUom+ErGByBirI2bNnsWPHDmzcuBH29vZ0y5GKmpoaWrVqhQcPHtAtpVJ4enri4cOH0NXVhaurK44ePUq3JAYGmbB7924UFhZi9uzZdEupEiwWC7t370ZycjKWLVtGtxyZoa6ujpkzZ+Lly5dYv349Ll26BFtbW0yaNEmh2jtTBt3WiDLw7t07YmhoSAYMGKAU++NnzpxJrK2t6ZZRJXJzc4m3tzcBQHx8fEhhYSHdkhgYKCM/P5/UrVuXTJo0iW4p1Wb16tWEzWaT8PBwuqXIhdzcXLJ+/XpiYmJCVFRUyJQpU0hiYiKlc+QUFJGo959JREI6iXr/meQUFFE6flkw5YjLQSQSwcPDA/Hx8Xj8+DEMDQ3pllQuR44cgbe3N9LS0pRC7/cQQrB9+3bMnTsX7du3x/Hjx1G3bl26ZTEwVJs9e/Zg6tSpiImJgbW1Nd1yqkVRURGcnJygqqqKBw8egMvl0i1JLuTk5GDHjh1Yt24dsrOzMWnSJPz6668wMzOr0nhxydk4EpqIkJgUJKbn4esbMguAhaEm3G3rYBTPAtZ1dSj5DKXBGAPl8Ndff+H3339HSEgIOnXqRLecChEfHw9ra2sEBwejR48edMupMrdv38aQIUPA5XJx8uRJ8Hg8uiUxMFQZkUgEW1tbODo6IjAwkG45lBAaGoq2bdtiw4YNmDNnDt1y5Ep2dja2bduG9evXIy8vD1OmTMGiRYtQr169Cl3/Nj0Pi08/xe34T+CwWRCJpd+KJcc7NDHGKi8HmBtqUvUxSmByBsrg3r17WLZsGZYsWaI0hgAANG7cGEZGRgpfb6A8OnTogIiICFhYWKBjx47Yt28f3ZIYGKrMyZMn8fLlS4VqU1xdeDwepk+fjiVLltTMOHoZ6OjoYPHixXj9+jV+++037N+/H1ZWVpg3bx5SUlLKvDaAnwiPTTdx71UaAJRpCHx9/N6rNHhsuokAfiI1H+IrGM+AFD5//oxWrVqhfv36uHnzptK5wHr16gUAuHTpEs1Kqo8k2Wr37t34+eefsX37dqXqnsbAQAhBmzZtYGBgUOOadWVlZaF58+Zo1aoVzp8/DxaLRbckWvj8+TM2bdqEzZs3QygUYsaMGViwYAGMjY2/OW97SBzWX42t9nzzPW0ww526UBNjDJQCIQQjRozA5cuX8fjxY1haWtItqdKsWLEC27ZtQ2pqao354/T398e0adPQsmVLnDhxolLVH3MFQrxJy0WhUAxVLhsNjbSgpaZcBh6D8nL9+nV069YN165dg4eHB91yKOfs2bMYMGAAjh8/jqFDh9Ith1bS09OxceNGbNmyBYQQzJo1C/PmzYORkREC+IlYdOrpD9cUprxBVugJCJLiIcrJACkqAFtNC6p1GkK7hSe07DqXOpfvQAcMc7agRDdjDJSCv78/JkyYgMDAQAwZMoRuOVVC0iM9Li4OTZo0oVsOZTx8+BADBw5EQUEBAgMD0blzZ6nnKkpiDgODh4cHMjIy8PDhwxpjnH/PoEGDcPfuXTx//pz2du6KwKdPn7BhwwZs3boVHA4HE2YvxCU4QiAU/3BuTlQI0i5skDqWfqefoNf2RyNLjcvG9TmdKMkhYIyB73jx4gWcnJwwcuRIpY5RZ2RkwNDQEIcOHYK3tzfdciglNTUVw4cPx82bN7Fu3Tr4+Ph8s8AqWmIOQ+0mPDwcbdq0qfFPze/fv0ezZs0wfPhw7N27l245CkNKSgrWrVuHw+8NoGpuDxb7x6ZU+S/5yIt9ADVze3C0DSAuyEE2/wwE718AADhaBmgw89AP13HYLLSzMsKhCdVPrmaMga8QCARwdXVFQUEBHj58CC0tLbolVQtbW1t4enpi27ZtdEuhHKFQiMWLF2PdunUYMWIE9u3bBy0tLQTwE7HsXDSEYlJuUs7XcNgscNksrOhnh+EUud0YGABg6NChiIiIQExMjMJ3J6wuO3fuxPTp03Hr1i106NCBbjkKQ1xyNrptvlWpawqTX+HjP7MAACwVdVjMOyH13OtzOqJJnep5N5ndBF+xaNEiPHv2DAEBAUpvCADK0cGwqnC5XKxduxbHjx/HuXPn0LZtW6w8EYpFp55CIBRXyhAAirN1BUIxFp16iu0hcTJSzVDbiIuLw8mTJ5WiTTEVTJkyBW3btsWkSZMgEAjolqMwHAlNBIddsfAQIWIIs9OQ/Si45D11Cwep53PYLBx+UP3dBYwx8H8uXryIzZs3Y/369WjZsiXdciiBx+Ph0aNHKCgooFuKzBg6dCgePHiA3Lot4R/+iZIx11+NxXEZbN1hqH2sX78eJiYmGDNmDN1S5AKbzcbevXsRHx+PNWvW0C1HYQiJSanQA8rHg/OQ6NsP73eMQU5kMAAWNBo7w6iX9NLVIjFBSGzZWxkrApNODeDjx48YO3Ys+vTpgxkzZtAthzJ4PB6Kiorw6NEjuLq60i1HZuiZWYHrOhKiIhEgJTlLmJmCzPuByH8dCVFOGtgqGuAa1IOmTdtSE3OWnotGu8bGTA4BQ5VJSkrCgQMHsGzZMqirq9MtR27Y29vjl19+wapVqzBs2DA0bdqUbkm0kiMQIjE9r2oXs1gAmwOUE81PTMtDrkBYrR1Std4zIBaLMXr0aKioqMDf379GZfq2aNECampqNTZUIGHx6acQiolUQ6Dg3TN88J+BnEeXIcpMBkRCiAuyUfgxDjmPr5V6jVBMsPj0j1uAGBgqypYtW6CqqoqpU6fSLUXuLFmyBBYWFpg0aRLE4h+z52sTCWm5qGjQ0qjHDNQduRpGfeZBrX4zgIiRH/cAKSdWlnkdAfAmLbdaOmu9Z2DdunX4999/ce3aNZiYmNAth1JUVVXh6OhYo42BuORs3I6XHh4QF+Tg05k1III8gMWGdqvu0GjkCBZXFcLPSShKe1fqdSIxwe34T4hPya52Yg5D7SMzMxM7d+7ElClToK+vT7ccuaOhoYE9e/aga9eu8Pf3x88//0y3JNooLGUroTRU6zQqea1p2xbvtowEERaiMCkORenvoWJYn5J5SqNWGwNhYWFYsmQJFi1ahK5du9ItRybweDycO3eObhkyQ5KYIy0el/34CkQ56QAAPbeR0G8/vMJjSxJzlvezo0QrQ+1hz549KCgogI+PD91SZI60gl5dunTBmDFjsGDBAvTp06fCNftrGqrc8h3w4iIB2CqlVVX94u0UF+RUe56yqLXGQFZWFkaMGAEnJyesWLGCbjkyw9XVFZs3b0ZqamqN83wA5Sfm5MeFffmBEHzwmw5hxkewNfWg1bwT9N1GgsVVLfVaSWLOcjDGAEPFKSgowKZNm/DTTz9VuZOdolPRgl7Tfl2JixcvYs6cOTh27BhdcmmloZEWWECZoYKkA3OgamYL9QbNwdE1gTgvE9kRF0GExTsyWFw1qBhJr7jK+v881aFWGgOEEEydOhWpqam4du0aVFRU6JYkMySd/kJDQ9GnTx+a1VBLRRJzitLelrzOvHOk5LUoKxVZD06gMPkl6gxdKTVXhIrEHIbaxaFDh5CcnIwFCxbQLYVyKlLQiwBISM/DodAE7L9P0GL2PpxYPwWjL10q6ZlSm9BS48LCUBMJZaxV4sIC5D65htwnpecwGXQZD7aa9GRmCyPNaq9RtTKB8NChQzh69Cj27NkDKysruuXIFEtLS9SpU6dG5g1UJDHna9caW10bRn3mwqjPXLDVtQEABa8jkR8n/f+GisQchtqDSCTCunXr4OXlBRsbG7rlUEpVO+29yVdFg8l7MG39YeTklO3qrqm429Yps86ALs8L6o1ag6NjDHBUAA4XHL260GzeCXVHrYGOY2+p13LYLLjb1Km2xlr3uBMXF4dp06Zh7NixGDFiBN1yZA6LxaqxxYcqkjDD4qqAFBW72rRb94K2fRcAxR6DrPtBAICCN4+gaSN962V1E3MYag9nzpxBXFwcDh8+TLcUSqlOpz2RmABsLsAbhWEr/HFx3SyK1Sk+o3gW2H//jdTjuk59oevUt0pji8QE3q7Vr5paqzwDhYWFGDFiBMzMzGpkiV5p8Hg8hIWF1bgtPhVJmOHofsmT4Op9sZ65ul9eiwvLDjVUNzGHoXZACIGvry/c3d3h4uJCtxzKCOAnUtJyFwCiuY2x9uQdSsZSJqzr6qBDE+MKVyGsKBw2Cx2aGFOy46lWeQZ+++03PHnyBA8ePIC2tjbdcuQGj8dDZmYmYmNja1QBkIok5qjXb46c/28fFGallrz/9euvDYbvoSIxh6F2EBISAj6fj8uXL9MthTLepudh2bnoUo8VJDxB8rHFUq/Vaz8C+h1GffsmIdgZ+glDOmahkYkulVIVnlVeDvDYdLPSpdLLgstmYZWX9FLFlaHWPPJcuXIF69evx5o1a+Do6Ei3HLni7OwMFotV40IFksScstBu6QnJ9pyciEvIiQop/hf5pe63lk07qddTkZjDUDvw9fVFq1at4OnpSbcUyigp6EUVLBYIWPhpW80xmCqKuaEmVlC8TXllPzvKqqTWilUuOTkZP/30E3r06FEr9v1+j56eHpo2bYrQ0NAaVyPd3bYODoUmSLW21eo3hS7PC1mhpyAuyP6hZ7iu62Co1mtc6rVUJeYw1HwiIyNx9epVHDt2rMZUMS2voNfXGHhMhmrdb5OxuVI8biwOF2+LuLgZGYNOrW2rrVOZGO5sgU85AkrCLgs8bTGMwg6rNd4YEIvFGDt2LFgsFvbv3w82u9Y4Q76hpiYRlpeYAwAG7uOhYmyJ7IgLKPpU3IBIxaQhdJz6QNvOXep1VCXmMNR8fH190ahRIwwePJhuKZRRXkGvr1E1sYS6ecWfeolYhDk7TiF836IaYzxVlBnu1jDWVqtWq/WV/ewoNQSAWmAMbN68GZcvX8aVK1dQt25duuXQhqurKw4fPoy8vDxoatac5juSxJx7r9LK/KPSdugKbYeKV5nksFloZ2XElCJmKJeXL18iKCgI27ZtA5dbc5bUinbaA4BP59dDlJ8FNlcNqqY20HUdBI2GraSez2JzkMwxRmBgIIYNG0aRYuVhuLMF2jc2LqnZQMQisNjSW1xLjLJ2VkZY5eUgkwZqNfoxOTw8HIsWLcL8+fNrVByvKvB4PAiFQkRERNAthXJWeTmAS3GWLpWJOQw1mw0bNsDIyAjjxo2jWwplVLbTnignvbgBmCAXBW8ikRLwO3KeXC/zGhUDU8yauwAZGRnVlauUmBtq4tAEHnojAkXPbsDSUAPfr2IsAJZGmhjNs8T1OR1xaAJPZp1Ua44Z+x3Z2dkYPnw4WrRogb/++otuObRjb28PTU1NhIaGws3NjW45lCJJzFl0iroug1Qm5jDUXJKTk+Hv74/ff/8dGhoadMuhjAp12mOzoWbRApq2baFiYAZxQQ6yws6gMCkOAEH6jX3QbOoGtqqU9s0sForU9LFw4ULs3buX4k+gHBBCcCXoAHp17oy/F3RBrkCIy3fDMdL7Jxw9fBA92jvJLYG5xnoGZs6ciaSkJBw7dgyqqqXXnq9NcLlcODk51ci8AaDY7Tbfk5qKb1Qn5jDUXLZu3QoVFRVMmzaNbimUUpFCW+rm9qg3chV0nfpCw8oJWs07oe7wP8BSK96KSwS5ELx/XuYY02fNxr59+3Dr1i1KdCsbjx49wsuXLzF06FAAxTukGumroPBjLBrpq8h1J1ONNAaOHj2KAwcOYOfOnbC2tqZbjsJQU5MIJcxwt8aagQ5Q47IrXdyDw2ZBjcuG70AHTHdvIiOFDDWJ7Oxs7Ny5E5MnT4aBgQHdciilqoW22OraUDH40pxJnJdZ5vnDBg9C27ZtMWnSJAgEgirNqcwEBQXB0NAQ7u7SE5nlRY0zBl69eoUpU6bA29sbo0ePpluOQsHj8ZCYmIikpCS6pciM4c4WuD6nE9pZGRW/Qcp+wpHYDO2sjHB9TifGI8BQYfbu3Yvc3FzMmTOHbimUIynoVRaCpPgf3hMX5KAo433Jz2wtfanXswA0MtHG3r178fLlS6xevbpqYpUUQgiCgoLg5eWlEM3yapQxUFRUhBEjRsDExAQ7duygW47C8XUHw5qMuaEmlnc2xod9U+FqVAhLI81SE3NIVjIai9/LPDGHoeYhEAiwceNGeHt7o379+nTLoZyKFPTKuPE3PvjPRFbYaeS/eYTcZzeRHPA7iKA48ZCtoQu1+s2kXi8p6GVvb4+FCxdi9erVeP687LBCTeLRo0eIj4/HkCFD6JYCoIYlEC5duhQRERG4e/cudHVrV6nLitCgQQOYmpoiNDQU/fv3p1uOTPnnn3+gUZQJ/+k9oampiVyBEG/SclEoFEOVy0ZDIy1MnTge0Q+i0WTNJLrlMigZR44cwYcPH2pkm2IJ5RX0AoCilNfI+NfvxwNsLox6zgRbRa3U674v6LVkyRIEBgZi8uTJ+O+//2pFPRhJiKBLly50SwFQgzwDN27cgK+vL/76668a1SSESmpyB8OvEYlE2L9/P0aOHFlSU0FLjQs7Mz20tjCAnZketNS48PDwQGRkJD59qliVNQYGoLiQ2dq1azFgwAA0ayb9yVfZGcWzKNMQMOgyHjpt+kPFpCHYGroAmwOOtiE0m3WE6U8boGnTVuq13xf0UldXx+7du3H79m34+ZViXNQwFC1EANQQz0BqaipGjx6Nrl27Yv78+XTLUWhcXV3x559/QiQSgcORXuRCmbly5Qrev3+PCRMmlHle165dQQjBv//+W5LNy8BQHmfPnkVMTAz2799PtxSZYl1XB25NjHA3/hNIKRkEaqY2UDOt/A4eaQW9unTpgrFjx+KXX35B3759Ua9evSprV3QeP36M+Ph4bN++nW4pJSi9Z4AQgnHjxqGoqAgHDx6sFe6l6sDj8ZCTk1OjY3P+/v5wcHCAk5NTmefVr18fzZo1w/XrZRdHYWCQIGlT3LFjR7i6utItR6ZkZGQg5cIWiIoKUXZv0MpRVkGv9evXg8vl1vgeMoGBgQoVIgBqgDGwbds2XLx4EQcOHICpqSndchSeNm3agM1m19hQQWpqKs6dO4cJEyZUqOa5h4cHYwwwVJhbt24hNDQUixYtoluKTHn06BHatGmDhzevYHRzdaDcvQUVp6yCXkZGRti8eTOOHz+OixcvUjanIqGIIQJAyY2BR48eYcGCBfDx8UGvXr3olqMUaGtrw87OrsYaA4cPHwaLxYK3t3eFzvfw8MDr16/x6tUrGStjqAmsWbMGLVq0QI8ePeiWIjMOHDiAtm3bQl9fH+Hh4fhrfC+5FvQaOXIkPD09MW3aNOTk5FAyryIhCREoyi4CCUprDOTm5mLEiBFo3rw51qxZQ7ccpaKmJhESQuDn54f+/fvDyMioQtd06tQJHA6H8Q4wlMvjx49x+fJl/PLLLzWy055AIMDUqVMxduxYjBw5Enfv3kWjRo0AyLegF4vFwq5du5Camoply5ZV6bMoMoq2i0CC0hoDPj4+SExMREBAANTUSt++wlA6PB4PUVFRNc7qDgsLQ3R0dLmJg1+jp6cHHo/HGAMM5bJ27Vo0bNiwRnbZe/v2LTp27Ah/f3/s27cPfn5+UFf/tqfA9wW9OOXYBBKjoSoFvaysrLB8+XJs3rwZ4eHhlfswCowkRDBgwACFChEASmoMBAYG4u+//8a2bdtga2tLtxylg8fjQSwW16g/MqA4cdDc3BweHh6Vus7DwwM3btyAWFx+PXaG2snr169x/PhxzJs3r0a1KQaA69evw9HREUlJSbh79y5+/vlnqedKOu1d8+kIj4ZqKEr/8MM5hBDocQqr3Wlvzpw5sLe3x8SJEyEUCit9vSLy+PFjxMXFKVyIAABAlIzXr18TPT09MmzYMCIWi+mWo5QIhUKira1NfH196ZZCGTk5OURHR4f8/vvvlb721q1bBAAJDw+XgTKGmsD06dOJsbExyc3NpVsKZYhEIrJq1SrCZrOJp6cnSU1NrdT1mzZtIurq6iQjO49Evf9MIhLSSdT7z8TVrRMZPnw4JRpDQ0MJi8UiGzZsoGQ8ulm8eDExMDAghYWFUs8JDw+nZT1SKs+AUCjEyJEjYWBggN27d9fIuF2uQIjoD5mITMxA9IdM5Aqot4g5HA6cnZ1rVN7AiRMnkJ2dXaWe8jweD1paWkyogKFUUlNT4e/vj5kzZ5YUsVJ2Pn/+DC8vLyxevBiLFy/GpUuXYGxsXKkx+Hw+WrVqBX1tjW8KevGcWoHP51Oi08XFBTNnzsTvv/+ON2/eUDImXRAF3UUgQan8XStXrkRYWBhu374NfX19uuVQRlxyNo6EJiIkJgWJ6Xnf7OhlAbAw1IS7bR2M4lnAuq6OtGEqBY/Hw8GDBykZSxHw9/dH165dSxKeKoOqqio6deqE69ev45dffpGBOgZlZtu2bWCz2Zg+fTrdUijh6dOnGDhwIFJTU3H+/Hn06dOnSuPw+Xz07Nnzh/ddXFywZcsWpKenw9DQsLpy8eeff+LUqVOYOnUqLl26pLQPgU+ePEFcXBy2bt1Kt5RSURrPwH///Yc///wTK1asQNu20stcKhNv0/Mw2i8U3TbfwqHQBCR8ZwgAxaU+EtLzcCg0Ad0238Jov1C8Tc+r9tw8Hg8fPnzAu3fvqj0W3cTFxeHWrVsYP358lcfw8PDA7du3UVBQQKEyBmUnJycH27dvx8SJEyu8Q0WROXLkSIknLDw8vMqGQEZGBuLi4uDs7PzDMcl7VHkHdHR0sGPHDly+fBnHjx+nZEw6CAwMhIGBAbp27Uq3lFJRCmMgLS0N3t7e6NSpU40p9hHAT4THppu49yoNAMqsAf718Xuv0uCx6SYC+InVmr8mdTD09/eHvr4+vLy8qjyGh4cHCgoKcPfuXQqVMSg7+/btQ3Z2NubOnUu3lGpRWFiImTNnwtvbG0OGDMG9e/fQuHHjKo/38OFDACjVGGjSpAn09fUpMwYAoF+/fhg0aBBmz56NjIwMysaVF4oeIgCUwBgghGDChAnIz8/H4cOHa0Q9/e0hcVh06ikEQnG5RsD3iMQEAqEYi049xfaQuCprMDU1hbm5udIbA0KhEAcOHMDIkSOhoaFR5XHs7e1Rp04dJm+AoYTCwkJs3LgRo0aNgrm5Od1yqsz79+/RuXNn7NmzB7t27cL+/furnfvA5/Ohp6cHa2vrH46xWCw4OztTagwAwNatW1FQUKCUoTxJiEAhdxH8H4U3Bnbt2oWzZ8/in3/+qRF9wwP4iVh/NZaSsdZfjcXxangIakLxocuXL+Pjx4+Vqi1QGiwWiylNzPANx44dw7t375Ty5iMhJCQEjo6OePv2LW7fvo0pU6ZQEnMPCwsrKW1eGs7OzggLCwMh1PU0MDMzg6+vL/7++2/cvHmTsnHlQVBQkEKHCAAFNwaePn2KuXPnYsaMGejXrx/dcqrN2/Q8LDsXXeqxgoQnSFjTR+q/z7ePlHrd0nPRVc4h4PF4ePjwoVLv4fX390erVq3g6OhY7bE8PDwQHh6O9PR0CpQxKDNisRi+vr7o27cvmjdvTrecSkMIwbp16+Dh4QF7e3tERESUhAapgM/nlxoikODs7IykpCS8f/+esjkBYNKkSWjXrh0mT54MgUBA6diyghCCwMBAhSw09DUKawzk5eVhxIgRsLGxwbp16+iWQwmLTz+FsJJhgfIQigkWn35apWt5PB7y8vIQHV26gaLoJCcn4/z589VKHPwaDw8PEEIQEhJCyXgMysuFCxfw/PlzLFy4kG4plSYrKwuDBw/GL7/8gl9++QVXrlyBiYkJZeO/f/8eHz58gIuLi9RzJMeoDhWw2Wzs3bsXr169wurVqykdW1ZIQgSK3iZdYbcWzps3D69evcLDhw9/KIupjMQlZ+N2/KcKnWvgMRmqda2+eY+rW/ofs0hMcDv+E+JTsn/oD14eTk5O4HA4CA0NRcuWLSt1rSJw6NAhcDgcjBo1ipLxzM3NYWtri+vXr2PQoEGUjMmgfBBCsGbNGri5uaF9+/Z0y6kU0dHRGDRoED5+/IjTp09jwIABlM8hucGX5RkwMzODmZkZwsLCqpXYWxp2dnZYuHAhVq1ahWHDhqFZs2aUjk81yhAiAGjwDFSkqM6pU6ewe/dubN68WSlddKVxJDSxwg0+VE0soW5u980/rl4dqedz2CwcflD53AFNTU20aNFCKfMGCCHw9/eHl5cXJXuZJTB5Awx37tzB/fv3lc4rcPz4cfB4PKioqODhw4cyMQSAYmPA1NS03BwuWSQRSvjtt9/QsGFDTJo0SaHLiBMF7kXwPXLxDFSmqI564Wf8/PPPGDRoECZOnCgPeXIhJCalwjsHPp1fD1F+FthcNaia2kDXdRA0GraSer5ITBASm4LlsKu0Lh6Ph1u3blX6Orp58OABnj9/ji1btlA6roeHB3bs2IE3b96gYcOGlI7NoBz4+vrCzs5OadqiFxUV4ZdffsHmzZsxcuRI7N27F1paWjKbLywsDM7OzuUmIrq4uGDt2rUQi8VSEw2rirq6Ovbs2YMuXbrAz89PYe8VT548QWxsLDZv3ky3lHKRqWegKkV1PP46C+26lti3b5/SVpr6nhyBEImVSPIT5aQDIiHEglwUvIlESsDvyHlS9tNqYlpelUoX83g8PH/+HFlZWZW+lk78/PxgaWlJueutc+fOYLPZuHHjBqXjMigHT58+xcWLF7Fw4ULKb2Cy4OPHj+jSpQu2b9+Obdu24fDhwzI1BAghePjwYZkhAgnOzs7IzMxEXFzVt0CXhbu7O8aNG4cFCxbg48ePMpmjugQFBUFfX1/hQwSADI2BqhbVKdA1h9rAP3ElPltW0uROQlruD0bQD7DZULNoAYNuk1Fn6AoY91sA1XqSPbwE6Tf2QVwovToeAfAmLbfS2ng8HgghMnPnyYKcnBwcP34c48aNo3zB1tfXh7OzM65du0bpuAzKwdq1a2FhYYHhw4fTLaVcbt++DUdHR7x69Qo3b97EjBkzZP4AFR8fj8+fP5eZPCihTZs2AKhPIvyadevWQVVVFT4+PjKbo6p8XWhIVVWVbjnlIhNjoDpFdVgcLorEqHZRHUUhPz8f8a/elHueurk96o1cBV2nvtCwcoJW806oO/wPsNSKrXwiyIXg/fMyxygUVj52ZmtrCz09PaXKGwgKCkJubi7Gjh0rk/GZlsa1k4SEBBw7dgxz585V6PguIQSbNm2Cu7s7bG1tERERgXbt2sll7rCwMABfbvRlYWBgAGtra5kaA0ZGRti0aRMCAwNx8eJFmc1TFZ4+fYrY2FiFLjT0NZTnDJRVVIcIi5AVdhq50SEo+pwEtoo61MztoNd+ONTqNfnh/PVXY2GirYZhzhZUy6SMrKwsJCQkICEhAW/evCl5Lfk5JSUFKnUawWz8tkqPzVbXhoqBGQqTio0icV5mmeercitv27HZbKXrYOjn5wcPDw9YWlrKZHwPDw/89ddfePLkCVq1aiWTORgUj40bN0JPTw8///wz3VKkkpOTgwkTJiAwMBDz58/H6tWrweXKb1MYn89H48aNK5y0Kyk+JEtGjhyJgwcPYtq0aYiOjoa2trZM56sogYGBShMiACg2BsoqqkPEIqQELUdBwuOS98SiIuTHPUD+q3DUGbKs1CS5peei0a6xMcwN5d86lBCC9PT0b27y39/wv66TraKiAgsLC1haWsLOzg69e/eGpaUl6ta3wJQbZecMCJLifzCIxAU5KMr4UrSDraUv9XoWgIZGVYsV8ng8/P333yCEKHyeRkxMDO7evYuAgACZzdG2bVtoaGjg+vXrjDFQS/j06RP+/vtvLFiwQKYx9+rw4sULDBw4EG/fvkVQUBAGDx4sdw18Pr9CIQIJzs7OOHXqFIqKimTmbWGxWNi1axfs7e2xdOlSbNy4USbzVIavdxEoQ4gAoNgYKKuoTnbExRJDQMXEEvpuo1CY/BKZ944DoiKkXdyM+pP3gcX99hdGUlTn0ATqqmdJEIvFSE5OLvWJXvI6N/dLHF5DQwMNGzaEpaUleDwehg4dWvKzpaUlTE1NpcawLSNDkFBGEmHGjb8hFuRC274LVOo0gjgvE1lhZ0AExdewNXShVl/6floLI01oqVXt6+TxePjrr7+QmJgos6dtqvD394eBgQH69+8vsznU1NTQsWNHXL9+HfPnz5fZPAyKw/bt20EIwYwZM+iWUionT57E2LFjYW5uDj6fj6ZNm8pdQ1FRESIiIiplhLi4uKCgoABRUVFo3bq1zLRZWVlhxYoVWLRoEUaOHFmhMIYskYQIlGEXgQTKjIHyiurkRAaXvDbqMRNq9ZtC07YdBB/jUPA6AqLsT8iLD4NW02+LfFSnqI5QKMT79++luvATExNRWFhYcr6enh4sLS3RsGFDdO3ateQmL7nhGxsbV/nJ2d22Dg6FJpSZQ1GU8hoZ//r9eIDNhVHPmWCrqJV6HYfNgruN9DoE5fF1B0NFNgaKiopw4MABeHt7y7wQlYeHB5YuXQqBQAA1tdL/3xlqBrm5udi2bRt+/vlnGBsb0y3nG4RCIX799VesX78eQ4cOhZ+fH21u8OjoaBQUFFRoJ4GEVq1agcPhICwsTKbGAAD4+PjgyJEjmDhxIvh8vlzDJ9+jTLsIJFD2vyUpqlPazU6Un42itLfFP7C5UDX90ulKrX4zFLyOAAAI3kX/YAwAX4rqLO/37T56gUCAxMREqS78d+/eQSQSlZxvYmJScoPv379/yWvJP319fQr+J0pnFM8C+++/kXrcoMt45EbfREHCY4hy0iEW5IKjqQc1c3vo8QZBtZ70dqMiMYG3a9XzKurUqYNGjRrhwYMHCl0yMzg4GMnJyZSVHy6Lbt26YcGCBbh//z46d+4s8/kY6MPPzw+ZmZmYN28e3VK+ITk5GcOHD8ft27exceNG+Pj40BrG4/P54HA4lbqpa2pqwt7eHnw+H5MnT5ahuuIw7b59+8Dj8bBlyxbavs+vexEoS4gAoNAYKKuojjAzueQ1R0MHLPaXNsQcLb0v531ORmmIxARn+XEouHfomxv+13tLWSwWzMzMSm7s7dq1+8aFb2FhQWss0LquDjo0Mca9V2ml/j+pmdpAzdSm0uMSsQiFb5/i0I4wLFy4sMqtSZWhg6Gfnx8cHR3lEsd3cHCAiYkJrl+/zhgDNZiioiJs2LABI0aMUCiv2L179zBkyBCIxWKEhISgQ4cOdEtCWFgY7OzsKr2Ouri44MGDBzJS9S3Ozs6YNWsWli5dioEDB6JRo0ZymfdrJCGCTZs2yX3u6kDJ1sLyiuqQoq/2x3O+tT9YbG7p531HehEXASdPIzk5Gba2tpg4cSL8/f1x48YNxMfHo6CgAO/evcPdu3dx9OhRrF69GpMnT0aPHj3QrFkzhUgKWuXlAG4FSxJXFHVVFQxtKMKaNWvQrFkznDhxokptQ3k8HiIiIlBUVESpPqpISkrCxYsXq92quKKw2Wx07dqVKU1cwwkICEBiYqLCtCkmhGD79u3o1KkTrKysEBERoRCGAFB+p0JpODs7Izo6+pv8K1nyxx9/wNDQENOmTaO0hXJFkYQIPDw85D53daDEGCivqA5L5Ut8l4i+vdkQsbDU834Yg8XCxZthCAkJwf79+7FixQqMGzcOXbp0QePGjZXCHWNuqIkV/SpfMrgsVvazw5ZVS/Hs2TO0bNkSQ4YMgYeHR6U7EfJ4PBQUFODJkyeU6qOKgwcPgsvlYsSIEXKb08PDA3w+/5sdIww1B0mb4t69e8PBwYFuOcjNzYW3tzdmzpyJmTNn4t9//4WpqSndsgAUd5GNioqq1E4CCS4uLhCLxYiMjJSBsh/R0dHBzp07cfnyZRw/flwuc0pQxl0EEigxBsordsPVq1vyWpyfDSL+EscX5XxZaLn6dVEWVSmqo2gMd7bAfM/KhwNKY4GnbUkNhsaNG+PcuXO4dOkS3r59i5YtW8LHxwefP3+u0FitW7eGioqKQoYKCCHw8/PDoEGDYGBgILd5PTw8IBaL8d9//8ltTgb5cenSJURHRytEQ6K4uDi4urri7NmzCAgIwMaNGxWq8FFkZCREIlGVPAN2dnbQ0NCQeb2Br+nbty8GDx6M2bNnIz09XW7zPn36FDExMUpTaOhrKDEGyit2w9HQgYqRefEPYhEKP34pSiT48KLktVqDsp+aq1JURxGZ4W6NNQMdoMZlg11+oeJv4LBZUOOy4TvQAdPdfyzU1LNnT0RFRWHVqlXw8/ODjY0N/Pz8yq2mp66ujpYtWyqkMXDv3j3ExsbKLUQgwdLSEk2aNGFCBTUUX19ftG3bFm5ubrTqOHv2LNq0aYOioiKEhoZi2LBhtOopDT6fD3V1ddjb21f6Wi6Xi9atW8u95PnWrVshEAjkGgJS1hABQJEx0NBIC+VFwrVb9yx5nRa8DXkx95Bx6xAKXhe7jjg6xtBsIt0FVZ2iOorIcGcLXPPpCHZqPACU295YcrydlRGuz+lUZlVGVVVV/PLLL4iJiUH37t3x888/w9XVtdwbvaImEfr5+aFRo0a0JPIxLY1rJvfu3cOdO3ewaNEi2jL0JdsGBwwYAA8Pj5IEPUVEsjWwqt4KFxcXuRsDpqamWLNmDfz8/HDz5k2Zz6fMIQKAImNAS40Li3IqBOo49oa6ZUsAQNGnRKSeXoWse/+P53BUYNTb54eCQ19TnaI6ikrcowd46TcHf7iqYjTPEpZGmj8YVSwAlkaaGM2zxPU5HXFoAq/C1RjNzMxw6NAh3LlzB0VFRXB1dcW4ceOQnFz6rg0ej4eYmBiFipFnZ2cjMDBQJk2JKoKHhwdiY2ORmJgo97kZZIevry+aN2+OPn360DJ/amoqevTogbVr12Lt2rU4ceIEdHV1adFSEaqaPCjB2dkZL1++RFpaGoWqymfSpElo164dJk+ejIIC6QnqVBAVFaW0IQKAwq2F5RXVYbE5qDNkObLCTiMn+l8IPycX9yZo0Bx6biNK7U0gobpFdRSVDRs2oEWLFvDu5wEWi4XlsEOuQIg3abkoFIqhymWjoZFWtY2g9u3b4+HDh9i3bx9+++03nDp1CsuXL8eMGTO+sfQlxYf4fD48PT2rNSdVBAYGIi8vT2ZNicrD3d0dLBYLN27cwLhx42jRwEAt0dHROHfuHP755x9aDMzQ0FAMHjwYhYWFuH79Otzd3eWuoTKkp6cjPj6+SsmDEiSGxMOHD9G9e3eqpJULm83G3r170bp1a6xevRorVqyQ2VzKHCIAKOxaOIpnUW6HQhZXBXrthqL+xN2wXHAa5j7HUGfw72UaAkD1i+ooIs+ePUNwcDDmzZv3jZtSS40LOzM9tLYwgJ2ZHmXeEA6HgylTpiA2Nhbe3t6YP38+WrZs+Y0L3NraGgYGBnLbE1wR/Pz84OnpCXNzc1rmNzQ0hJOTExMqqEGsW7cODRo0wMiRI+U6LyEEu3fvRocOHWBubo6IiAiFNwSA4hs4gGp5Bpo0aQJ9fX1aWqXb2dlh0aJFWL16NZ49eyaTOSSFhvr376+UIQKAQmNAUlSnvNh3ZeGwWejQxLjSpYgVnY0bN8LMzEzufdONjIywY8cOhIeHw9jYGN26dcOgQYPw5s0bsFgshcobeP78Oe7fvy/3xMHvkeQN0LFnmYFa3r59iyNHjmDu3LlyXbQl3q2pU6di8uTJ+O+//1C/fn3kCoSI/pCJyMQMRH/IRK5AWP5gcobP50NPTw9NmpT90FYWLBZLLh0MpbF48WI0atQIkyZNKjWZurrfg7KHCACKGxWt8nKAx6ab5XoIKgOXzcIqL/r3AFNJcnIyDh06hBUrVtBmRbZq1Qo3b95EQEAA5s+fj2bNmmHRokVwdHTEnj17FKKDob+/P4yMjNCvXz9adXTr1g1r1qxBVFSUQuxHZ6g6GzduhI6ODiZOnCi3OV++fIlBgwYhNjYWhw8fhotHP6y6HIeQmBQkpud9s5+IBcDCUBPutnUwimcB67r0PwRJ8gWqG1JxdnaGv78/LWuLuro69uzZA3d3d/z999+YNGkS4pKzcSQ0kZLvISgoCHp6eujWrZtMP4csoTRgJquiOnS0L5YlO3fuhIqKisxrdZcHi8XCiBEjEBMTAx8fH6xatQp///030tLS8PLlS1q1FRUV4eDBg/D29qa9UVC7du2grq7OhAqUnPT0dOzbtw/Tp0+XW7OfCxcuwMnJCbm5uTh74y4uFzRBt823cCg0AQnf3YAAgABISM/DodAEdNt8C6P9QvG2jOqu8iAsLKxaIQIJLi4uSEpKwvv378s/WQZ07twZ48ePx6I/1mHozluUfQ/KvotAAuXZM7IqqlNTyM/Px86dOzF+/Hi5FtApC21tbaxevRpRUVFo2bJ4x4eXl5fM4msV4eLFi0hJSaE9RAAUP1V06NAB165do1sKQzXYsWMHxGIxZs2aJfO5RCIRfv/9d/Tt2xedO3fGYr8LmHEpCfdeFWfTl+c9lRy/9yoNHptuIoBPz26W9+/f4+PHj5QYA5Ix6AoVAEC70fOhM3wtwhIzAVDzPURFReHFixdKHSIAZGAMAN8W1alsDkF5RXWUnYMHDyI9PR0+Pj50S/kBa2trXL16FaampiVVDOfOnYvMzEy5a/Hz80ObNm0Uxi3v4eGBmzdvftPymkF5yMvLw9atWzF+/HiYmJjIdK60tDT06tULq1atwqpVq9B15lqsCI6HQCiudAhVJCYQCMVYdOoptofEyUixdCQJf9XZSSDBzMwMZmZmtCQRAsD2kDj8ceVV8RZ2VuVufWV9DzUhRADIyBgAij0E1+d0QjsrIwDUFtVRVsRiMTZu3AgvLy9YWVnRLUcqXbp0gY2NDf744w/s3bsXNjY2+Oeff8qtYkgVHz58wKVLlxTCKyDBw8MDeXl5CrXTgqHi+Pv7IyMjQ+ZtbR8+fAgnJydERETgypUraOQxChuuU3MTX381Fsfl7CEICwuDqakp6tevT8l4dBQfAoAAfiLWX5VUvq1evsLX30NNCREAFCcQfo+5oSYOTeB9SdSITUFi2rfxGUIIGhprwd2mDrxdLWrcroGvuXjxImJjY7F//366pZQJj8dDUFAQbt++jdGjR2PBggUYP3489uzZg23btlHiMiyLgwcPQlVVVa5NicqjVatWMDQ0xPXr19GxY0e65TBUAqFQiA0bNmDYsGEybWn7999/Y/r06WjVqhVOnDgBaBlh+ibple+EmSnIvB+I/NeREOWkga2iAa5BPWjatIVe26GlXrP0XDTaNTaWWx5VdYsNfY+zszN8fX0hFovlVuPhbXoelp2T3ritKOMDMu8cQ0HCY4jyssDR1IWGVRvodRgJro5xqddIvofMD6/w4sULrF+/Xlby5YZcvg3rujpY3s8ON+e7I2p5d1yc6YbTU9vhlxYivN04BIeGNsbyfnY12hAAiosMubq6om3btnRLKRMej4fCwkI8fvwY9evXx9GjR3Hr1i0UFBTAxcUFEyZMQEpKikzmJoTA398fgwcPhp6enkzmqApMS2PlJTAwEG/evJFZjfr8/HxMmDABEydOxPjx43Hr1i2Ym5tj8emnEEoJCxS8e4YP/jOQ8+gyRJnJgEgIcUE2Cj/GIeex9NwUoZhg8emnMvkc3yMWi/Hw4UNKQgQSnJ2dkZWVhbg4+YU8yvoeCpNf4eN+H+RGh0CUkw6IhRDlpCPnyVUkHZgL4efSq7VKvofAwMAaESIA5GQMfM3XRXW8OjuDFBXQmlAiL8LDw3Hz5k2ZuympoFWrVlBTU/vGJd6hQwc8fPgQO3bswOnTp2FjY4MtW7agqKiojJEqz507dxAXF6dQIQIJkvrxdORQMFQNQgh8fX3Ro0ePkuRYKnn9+jXc3Nxw9OhR7N+/H7t27YKamhrikrNxO/5TqTkC4oIcfDqzBkSQB7DY0G7dEyYDf0OdoStg6DkVGo3bSJ1PJCa4Hf8J8SnZlH+W74mPj8fnz58p9Qy0aVP82eQVKijrewCA9Gt7ir8HAFotuqHO0BXQbtUDACDKSUf6td2lXif5Ho4H31TqQkNfQ2sbQFNTUzRo0IC2hBJ5smHDBjRq1AheXl50SykXVVVVtG7d+ofiQ1wuF9OmTUNcXBxGjBiBOXPmoHXr1vj3338pm9vPzw+NGzdGp06dKBuTKjw8PCASieTS9ISBGi5fvownT57IpE1xcHAwnJyckJGRgfv372PMmDElx46EJkrNk8p+fKX4KRSAnttIGHWfDk2bttCwcoKOY28Ydit7yzGHzcLhB7LPHZCsy5IbOBUYGBjA2tpabg+AZX0P4sJ8CN79f8cUhwuj7tOgYeUEQ8+pYKlqAADyXz6EMCu11OvZLCBVvymGDi09pKNs0N4T2MXFpcZ7BhITExEYGAgfHx9wOBy65VSIsioRGhkZYdeuXQgPD4e+vj66du2KIUOGVLuZT1ZWFoKCgjBu3DjaCx6VhpWVFRo1asSECpQIX19f8Hg8So1LsViMlStXonfv3mjXrh3Cw8PRqlWrb84JiUmR+jSaH/fVekcIPvhNR+L6gXi3cxwy/tsPIix7x4pITBASK5sw3deEhYWhSZMmMDQ0pHRcZ2dnuT0AlvU9iAV5wP8z2FhsLlgclf+/5pS8BggE71+Ufj0BtJq41IgQAaAAxoCzszPCw8MhEonoliIztm3bBh0dHYwfP55uKRWGx+Ph5cuX+PTpk9RzWrdujdu3b+Pw4cO4e/cumjZtipUrVyI/P79Kcx4/fhwFBQW0NSWqCExLY+XhwYMHuHnzJhYuXEiZcZmeno6+ffti+fLlWLlyJc6dO/dDvZAcgRCJZRQKKkp7W/I6884RFKUmgAgLIcpKRdaDE0g5+Ue5pa8T0/JkXrqY6uRBCS4uLoiMjJT5Nt3yvgeOlj5YaloAAFJUgOzIYIiLCpDz5DrE+Vkl54mkeAYAgKNXF0WE9tsoJdDeE9jFxQXZ2dmIiYlB8+bN6ZZDOVlZWdi7dy+mTp0qt6pnVCDpYBgWFoZevXpJPY/FYmHUqFHo168f/vrrL/z555/4559/sGnTJvTv379Si7Cfnx969OhB2TYmWdCtWzfs27cP79+/V2idDMVeAVtbW/Tv35+S8SIjIzFo0CBkZmYiODhYave9hLTcHyrafY24IKfkNVtdGwYekwAAGdf3QlyQg4LXkciPC4WmjavUMQiAy3fD0Uhfetv36iAUChEeHo62bdsiIiKC0rF1dXUhEAgQFBSEZs2aUTr217z+XFTm98Bic6Dbph8y7x4DAKRf2YH0Kzt+OI+IysiLYrHwJi0XdmaKk+xcVWg3BpycnAAUW6E10Rjw8/NDXl4eZs6cSbeUStGoUSMYGxsjNDS0TGNAgo6ODtasWYPx48fDx8cHXl5e8PT0xJYtW9C0adNyr4+OjkZoaGjxliwFRtLS+Pr169/EiBkUi+fPn+PMmTPw8/OjZAvb/v37MXXqVNjZ2eHff/9Fw4YNpZ5bKCy7HgeLqwJSJAAAaLfuBW37LgCKPQZZ94MAAAVvHpVpDADASO+fUPgxtsxzqsvGjRuxceNGmYzt7e0tk3ElqJrawHRM2dr13EaAiEXI5p8FERZ/JxxdE3C0DEr+b9n/9x5Io7zvW1mg3RjQ09ND06ZNwefza9ziKhQKsWXLFowYMULpniKr2sHQxsYGFy9exIULF+Dj4wMHBwfMnj0bS5cuha6urtTr/P39YWJigr59+1ZXukwxNjZG69atGWNAwVm3bh3MzMwwatSoao0jEAgwa9Ys7N27Fz///DO2bdsGdXX1Mq9R5ZZtfHB0TSBMewcA4OrVKXmfq/vltbiw/H4ERw8flJln4NSpU1i9ejVu3boFDQ0NyscfMWIEmjZtimXLllE+toTXn4sw75r0MCcAsFhsGHT6CXrthqIo7R3YKurgGpgi5fjvJeeoGJddAK+871tZoN0YAEBra0tZcvLkSSQkJGDu3Ll0S6kSPB4PmzZtqnSBEBaLhb59+6Jbt27YuHEj/vrrLxw+fBi+vr4YPXr0D2MVFhbi4MGD+Omnn5Rii46HhwcOHjyoEJ0dGX7k3bt3OHz4MFatWlWtJleJiYkYPHgwnjx5gr///rvC210bGmmBBUh1UavXb46c/xsDX2eqf/2ao1t2yWQWgB7tnaClJpslfNeuXXBwcED79u1lMn6nTp3w4MEDODo6ymR8ALAVCDH/2pUyQwUS2CrqUKtXXP5ekBSPgsSo4vc1dKFWX7pnk4Xi77smoBAmjYuLCx4/fgyBQEC3FMoghGDDhg3o0qXLD5nGyoKrqysyMjKqXCBEXV0dixcvxosXL9C5c2eMHTsW7du3x8OHD7857/z58/j06ZPSJFh6eHggKSmJ1kZODNLZvHkztLS0MGnSpCqPce3aNTg6OiIlJQV3796tVN0LLTUuLMqoEKjd0hOSkrg5EZeQExVS/C8y+MsYNu3KnMPCSFNmhgBAXadCabi4uCA6Ohq5ubkym6O87wEA8uL5SD21CjlPriP/dQSyQk8hJWAJQIpd/7q8gWBxpT+gyPp7kCcKYQw4OzujsLAQT548oVsKZdy5cwd8Pl8pigxJQ7IYVDZU8D3m5uYICAjAf//9h9zcXLi4uGDixIlITS1+EvL39wePx4OdHbXtr2WFm5sb1NTUmF0FCkhGRgb27NmDadOmlRmWkoZYLMaqVavQvXv3kp1OkrymyuBuW0fq/na1+k2hyyuuNyIuyEbahQ1Iu7AB4oLiQkK6roOhWq+x1LE5bBbcbepIPV5d8vLyEB0dLVNjwNnZGWKxmPLkxO8p63sAAIiFyIu9h7RLm5FyfCkyQvxLEjw1m7pB10V6XRhZfw/yRiGMgZYtW0JFRaVGFR/asGEDmjVrhh49etAtpcro6+ujadOm1TYGJHTq1AkRERHYunUrTpw4AWtra6xcuRKXL19WGq8AAGhoaKB9+/aMMaCA7Ny5E0VFRVVqU/z582cMGDAAv/32G5YuXYoLFy7AyMioSjpG8SzK7FBo4D4eRr3nQNXUGiwVNbBU1KBqZgujvvNg0HlsmWOLxATerrJr5BYZGQmRSERpGeLvsbOzg4aGhszX/PK+BxUjc2jatisOy3BUwFLThFqD5jDqPQfG/ReCxZZeF0bW34O8UQj/hrq6Olq0aIGwsDBMmzaNbjnVJi4uDufOncPevXvl1oxDVlQlibAsuFwuZsyYgeHDh+O3337DsmXLwGKxlC7B0sPDA6tWrUJRURFUVGSTxMVQOfLz87FlyxaMGzcOdevWrdS1T548wcCBA5GWloYLFy6gd+/e1dJiXVcHHZoY496rNKk3I22HrtB26FqpcTlsFtpZGcm0j0tYWBjU1dVl6qnjcrlwdHSUuTFQ3vegYtQAJl6LKz2uPL4HeaMwdyq6WlvKgs2bN8PExETmW2fkAY/Hw+PHj6tcSEgaxsbG2LVrFxo0aABjY2P06dMHw4YNw9u3b8u/WAHw8PBATk5OjUx8VVb279+PtLQ0zJ8/v1LXHT58GK6urtDR0UF4eHi1DQEJq7wcwC2ndXtl4bJZWOXlQOmY38Pn89G6dWuZG7nyShyn/HsgRC7fg7xRGGPA2dkZz58/R3a27BtwyJK0tDT8888/mD59erlbkJQBHo8HoVCIyMhIyse+desW3r17h6CgIBw8eBC3bt2Cra0t/vzzTxQUFFA+H5U4OjrCwMCACRUoCEKhEOvWrcOQIUPQuLH0ePvXFBYWYvr06Rg9ejSGDh2Ke/fuwcrKijJN5oaaWNGP2qfrlf3sZN6+mM/nyzREIMHZ2RmvXr1CWlqaTOeh/HtgseTyPcgbhTEGXFxcQAhBeHg43VKqxe7du0EIwdSpU+mWQgkODg5QV1enNFQgwd/fH9bW1ujYsSNGjx6NmJgYTJ8+HStWrEDz5s1x9uzZcsuy0gWHw0GXLl1w7Zr0drMM8uPEiRN4/fp1hRsSvXv3Dp06dcLff/+N3bt3459//pHJfvrhzhaY72lTvUH+/zcwppUBhjnLNkadnp6O+Ph4mSYPSpAYHN/vLpIFPax1ofricjVHKf4e5nRpLPPvgQ4Uxhho2rQptLS0lNrtKhAIsH37dowZMwYmJmXvE1YWVFRU4OTkRLkxkJmZiRMnTmD8+PEle/V1dXWxbt06PH36FDY2NhgwYAB69uyJmJgYSuemCg8PDzx48ABZWVnln8wgMyRtij09PdG6detyzw8JCYGjoyPev3+PO3fuYPLkyTKtFzHD3RprBjpAjcsuO7O9FDhsFtRUONB4chL7fxmBDx8+yEhlMZIbszyMgcaNG8PAwEDma75AIICXlxc+3TyC2W2Nq/w9QCSEdUYYZncrv6KqMqIwxgCHw4GTk5NS5w0cPXoUSUlJmDNnDt1SKIXqJEIAOHbsGAQCAX766acfjjVt2hTBwcE4c+YMYmNjYW9vjwULFijcTVfS0vjWrVt0S6nVXL16FY8ePSrXK0AIwdq1a+Hh4YGWLVsiIiJCLjc9oNhDcH1OJ7SzKt6dUN7NSHK8nZURrs/phOt7/4BYLEavXr1k+ncQFhYGfX19NGnSRGZzSGCxWGjTpo1M13yxWIxx48bh/v37OHfuHOb041Xpe2hRVw3v907BrN7UtXNWNBTGGACUu50xIQQbN25Enz59YGtrS7ccSnF1dcWbN2+QnJxM2Zj+/v7o1asXzMzMSj3OYrHQv39/PHv2DMuWLcOOHTtga2uLQ4cOQSxWjFrgjRs3hqWlJZM3IAdyBUJEf8hEZGIGoj9kftOxz9fXF23atIG7u7vU67OysjBo0CAsXLgQixYtwuXLl2FsbCwP6SWYG2ri0AQervl0xGieJSyNNPH9rYgFwNJIE6N5lrg+pyMOTeDB3FAT9evXR3BwMN68eYPBgwejqKiM5jnVgM/no02bNnLbBSVZ82UVDly8eDECAgJw+PBhuLm5Aaja99Ay/TY0ST48PT1lolMhIArE8ePHCQCSlJREt5RKc/nyZQKAhISE0C2FchISEggAcvbsWUrGe/LkCQFATp8+XSkNQ4cOJQBI27ZtSXh4OCVaqsuECROInZ0d3TJqJLFJWWTZ2SjSce2/pOGiC8Tyq38NF10gHdf+S6bsu0FUjMzJiRMnpI4TFRVFbGxsiK6uLmW/w1SRU1BEot5/JlsOnyUqdRqRlwnvyjw/JCSEqKqqkjFjxhCxWEypFrFYTOrVq0d+/fVXSsctizNnzhAAJDExkfKxt2/fTgCQTZs2lXuu5HuISEgnUe8/k5yCom+ON2/enIwePZpyjaURHh5OAMh9jVM4zwAApQwVbNiwAY6OjujUqRPdUijH3Nwc9erVoyxU4Ofnhzp16lRqC5eFhQWOHz+Of//9F9nZ2WjTpg0mT56MT5/KbkQiazw8PBAdHY2PHz/SqqMm8TY9D6P9QtFt8y0cCk1AQnreD/XlCYCE9DwEx+fCbOIunM6oj7el9K4PCAiAi4sL1NTUEB4ejn79+snlM1QULTUu7Mz00NbGFEUpr5GZllLm+Z07d8b+/ftx4MABypv8vH//HklJSXLZSSBBEqahes0/c+YMZs6ciTlz5sDHx6fc8yXfQ2sLA9iZ6X1TYjg6OhrPnj3DkCFDKNWoaCiUMWBpaQljY2OlMwaePHmCa9euYd68eTWycU1VOxiWhkAgwOHDh/HTTz9VaR+zu7s7IiMjsWXLFgQGBsLa2hrbt2+HUCgs/2IZ0KVLcfvZGzdu0DJ/TSOAnwiPTTdx71XxdrOyqscBAFjFS9j91+nw2HQTAfxEAEBRURF8fHwwYsQIDBw4EA8ePJBLHLyq1KtXDwCQlJRU7rkjRozA2rVr8ccff2Dfvn2UaZCsu/LKowAAMzMz1K9fn9I1//79+xgxYgQGDx6M9evXV3u8oKAg6Orq1uwQARTMGGCxWEqZN7Bp0yY0aNCgRluOPB4PfD6/2vH6c+fOIS0trVrlh7lcLmbOnInY2FgMHjwYs2bNgqOjI27evFktbVWhTp06aNmyJZM3QAHbQ+Kw6NRTCITi8o2A7xCJCQRCMRadeopVZyPg7u6OnTt3Yvv27Th48CA0NRV7T7ikYmJFPUzz58/HjBkzMHXqVFy8eJESDXw+v+TmLE+oLD4UGxuLvn37ok2bNjh48CAluQ9BQUHo169ftTpgKgMKZQwAxb8YfD5fYfeXf8/Hjx9x5MgRzJ49u0aXpeXxeMjKykLk02dSE7kqgr+/P9q2bYtmzZpVW5OJiQn27duH0NBQaGpqonPnzhgxYgTevXtX7bErg4eHB65fv640v7OKSAA/EeuvxlIy1t4HH5HArY+bN29i+vTpSuGtU1VVhbGxcYWNARaLhc2bN6Nv374YOnQoJXv1Zd2pUBrOzs54+PBhtR80UlJS0LNnT5iYmODs2bOUFH179uxZrQgRAArSm+BrXFxckJaWhtevX1NaDUxWbN++Herq6pg4cSLdUmRGXHI2rqcbwGzyPgwKeAMgoeQYC4CFoSbcbetgFM8C1nWl1+p++/Ytrly5QqlrEyheTO7du4dDhw5h4cKFsLW1xW+//Ya5c+fKpQqkh4cHNmzYgJiYGDRtWjP3IMuSt+l5WHYuWupxIixCVthp5EaHoOhzUnHveXM76LUfXtKD/tsLCDTdxqCBbUsZqqaeevXqVShMIIHD4eDo0aPo2rUrevfujfv371d5zRSLxXj48CEWLFhQpeurg4uLC7KyshAbG1vlv5/c3Fz06dMHeXl5uHHjBgwNDSnRVltCBICCegYA5UgizM3Nxa5du/Dzzz9DT0+PbjmU83Ui1/HIj1AxMAW+24QjSeQ6FJqAbptvYbRfaKmJXEBx7XhNTU0MHTqUcq1sNhtjxoxBTEwMpk6dimXLlsHe3h7nz5+X+RN7hw4doKqqylQjrCKLTz+FUEpYgIhFSAlajs+3DqIo7S0gKoK4IBv5cQ+QdGgB8t88+vEiFgtCUjyuMmFqalrpRFQNDQ2cO3cOenp66NGjR5UTauPj45GZmSnX5EEJbdoU792v6povFAoxfPhwPH/+HJcuXULDhg0p0xYYGIh+/frViNLy5aFwxoCJiQkaNmyoFHkD+/fvR1ZWFmbPnk23FMqpbCKX5Pi9V2nfJHJJEIvF+OeffzB06FDo6Miu05eenh7Wr1+PJ0+ewMrKCv369UPv3r0RG0uNC7o0tLS00K5dOyZvoArEJWfjdvwnqb9f2REXUZDwGACgYmIJE6/F0Gs3rPigqAhpFzeDCH/ccy8SE9yO/4T4FOXpdVIVYwAobvp1+fJlZGZmol+/flVqKiZZbyU3Znmir68Pa2vrKhkDhBBMnz4dwcHBOHHiRIUqUFaU2hQiABTQGAC+5A0oMiKRCJs2bcLgwYNhaWlJtxxKoSqRa3tIXMn7//33H16/fo0JEyZQLbdUmjVrhitXruD06dN4/vw57O3tsXDhQpk1wvLw8EBISAhtuxqUlSOhiWVWgcuJDC55bdRjJjRt20G/42ioN3IEAIiyPyEvvvQHBw6bhcMPEks9pohU1RgAACsrK1y4cAGPHz/GqFGjIBKJKnU9n89HkyZNYGBgUKX5q0tVE8dXr16NvXv3Yt++fejevTulmoKCgqCjo1MrQgSAghoDLi4uCA8PV+iF9dy5c3j58iXmzp1LtxRKoTKRa/3VWBz/v4fAz88Ptra2aNeuHSVjVwQWi4UBAwbg2bNnWLJkCbZu3QpbW1scOXKE8tCBh4cHsrOzFd6IVTRCYlKkGpyi/Ozi0AAAsLlQNbUuOaZW/0sCquBd6fkGIjFBSGzZ+/YVCUnOQFV/N52dnREYGIizZ8/Cx8enUuPIq1OhNJydnfHo0SMUFhZW+JqDBw/it99+w4oVKzBu3DjKNQUFBaF///61IkQAKKgx4OzsjLy8PDx//pxuKVLZsGED3NzcaP0DopqyErkKk14i47/9SDo0H++2/4SEtQPwdstIpAStQMHbKKljLj0XjajXH3Hy5MlvmhLJEw0NDSxduhQvXrxA+/bt4e3tjQ4dOlDaltnJyQl6enpMqKAS5AiESJSSXwIAwswv5a85GjpgsTlfftb6kqMj/Cy9THZiWl6ld7zQhampKfLz86vVe6B3797YtWsXtm/fjg0bNlTomqKiIkRGRtKyk0CCs7MzBAIBoqKkryVfc+3aNUyYMAETJkzA77//TrmeZ8+eITo6utaECAAFNQacnJzAZrMV9ikrNDQUd+/exbx58+iWQillJXJlPwpG1oMTELx/AVFOOiAWQpyfhfyXfCQfXYy8mHulXicUE8w4cBdCobDUpkTyxNLSEkFBQbh+/ToyMjLg5OSEqVOnUtJPncvlwt3dnTEGKkFCWu4PlQW/hhQVfPmB8+3GJxabW/p5348B4E1abhUVyhdTU1MAFa81II1JkyZhyZIlWLBgAQICAso9PyoqCgUFBbQaA61btwaHw6lQqODx48cYNGgQunXrhl27dsnkAaO2hQgABTUGtLW10axZM4VNIty4cSOaNGmCvn370i2FMspL5AIAjpYBdNsNQ52hK2DcbwG4hg2KDxAx0m/8Xeo1IjHBG4EGunqNKqmyRjddu3bFo0ePsHHjRhw9ehTW1tbYuXNntcNSHh4euH//PnJycihSWrMpFJa9r5yl8sU9S0TfJgkSsbDU86oyj6JAlTEAACtXrsRPP/2EMWPG4L///ivz3LCwMHA4HEqT7yqLhoYGHBwcyn0ATExMRK9evWBtbY3AwECZ1XaRFBqqLSECQEGNAaA4b0ARPQNv3rzBiRMnMGfOHHA4nPIvUBLKS+TSsnOH2ZR9MOg4GhpWTtBq3gkm/X8pOS7KSoEo93Op1xKxCHXdBlMtuVqoqKjAx8cHcXFx8PLywvTp09GmTRvcvn27ymN6eHigqKgIt2/fLrPLHkMxqtyylx+uXt2S1+L8bBDxl6Q4UU7Gl/P066IsyptHUahMSeLyYLFY2LdvHzp16oQBAwYgOlp6HQc+nw97e3vaqzSWt+ZnZGSgZ8+eUFVVxcWLF6GtrS0THZIQgSy2QCsyCvtX4uzsjCdPnqCgQLoLkA62bNkCfX19jB07lm4plFJWIhcAqJvbgf3dExjX8Nv2wyyV0st1stgcJBTK5g+3utSpUwd+fn4IDQ2FmpoaOnbsiJEjR+L9+/eVHoulZwrzAXMx/2YO7JdfQe9td+C16x56b7sD++VX0GldCJafi0ZcsvJsd5MlDY20fmgd+zUcDR2oGJkX/yAWofDjl8RWwYcXJa/VGthJHYP1/3mUAR0dHWhpaVHW9EpVVRUnTpxAw4YN0bNnT6m/03w+n9YQgQRnZ2dER0cjN/fHsI5AIICXlxeSkpJw+fJlmXoZa2OIAFBgY8DFxQVCoRCPHj2iW0oJnz9/xt9//42pU6fSbkVTSXmJXNL4Ok9ArYEd2KoaUs9NTFfsRC4XFxfcv38f/v7+uHHjBmxtbbFmzRoIBIJyr5UUZ/Lcchts287IZWlK7bJXkeJMtQUtNS4sDMv+O9Ju3bPkdVrwNuTF3EPGrUMoeF2c/MnRMYZmE+lJvBZGmt90oFN0qrO9sDR0dXVx6dIlAECvXr1+SE7Mzc1FVFSUQiRCOzs7QywWIyIi4pv3xWIxxo4diwcPHuDcuXOwtbWVqY7aGCIAFNgYcHBwgKqqqkLlDezbtw+FhYWYMWMG3VIopbxErtIQJMUj/dqe4h84KjDwKLscszIkcrHZbIwbNw6xsbElSVj29vZlNoL5vjiTpIueNMorzlTbcLetU2Z4SsexN9Qti8sKF31KROrpVci6d7z4IEcFRr19wOKWHjfmsFlwt6lDuWZZQrUxABR3BgwODkZiYiIGDRr0zfa9yMhIiMVihfAM2NnZQUND44dQwaJFi3D8+HEcOXIE7du3l6mG58+f17pdBBIU1hhQVVVF69atFSZvoKioCFu3bsWoUYqTCEcVlU2wKngbjeRji0EEuQCbA5N+C0qvEV/NeehCT08PGzduxJMnT2BpaYk+ffqgT58+iIuL++Y8WRRnqm2M4lmU+X/HYnNQZ8hy6Hf8CVyjBgBHBWx1HWg04aHe6HXQaNhK6rUiMYG3q4UMVMuOyvYnqCh2dnY4c+YMbt26hZ9//rmkBgGfz4eGhgbs7KSHWuQFl8uFo6PjNw+A27Ztw7p167B582YMGjRI5hokIQKqCxgpAwprDADUtrasLoGBgXj37h3mzJlDtxTKqUyCVf7rCKQELgUR5AEcFZgM+BWathUrJKQsiVwSmjdvjmvXruHkyZOIioqCvb09fv31V+Tk5MisOFNtw7quDjo0MS7TO8DiqkCv3VDUn7gblgtOw9znGOoM/r1MA5TDZqFDE2M0qSO70teyQBaeAQmdOnXCwYMHcejQoZK9+WFhYWjdurXCdFz9uvrs6dOnMXv2bMybNw+zZs2Sy/y1qRfB9yh0MM3Z2Rnbt2/H58+foa+vT5sOQgg2bNgAT09PODg40KZDVkgSucp7ts2LuYfUc2sBkRAsFXWYDFpS5pPZ1yhTItfXsFgsDBw4ED169MDatWvh6+uLg6cuQmPQKnzftAkABO9fIDP0JAo/xECUlwkWmwuuQT1oWrtClzcIbLXSY+RLz0WjXWNjmJcTQ6+JrPJygMemm5X2rpQFl83CKi/l+1uVpTEAAMOGDcO7d+8wf/58mJubg8/no0+fPjKbr7K4uLhg8+bNCA4OxsiRIzFkyBCsXbtWLnNLQgR//fWXXOZTNBT6UU2S1EJFr+7q8N9//yEyMrLGFRmSUJFErtwXd5B6Zg0gEgJgQc9tBFgcFRS8jS75V1rDGAnKlsj1PZqamli+fDmeP38Ow+7TUST8sfZ7QcITJB1ZiPzY+/8vzCQCEQpQlJqAzHvHkXz8d6klYoVionRd9qjC3FATK/pR66Ze2c9OKQ2revXqISMjo0KJq1Vl7ty5mDVrFqZNm4aXL18qRPKgBEnuwrBhw+Di4oIDBw6AzZbPbao2hwgABfcM2NjYQFdXF3w+Hx4eHrTp2LBhAxwcHNCtWzfaNMia1vVUkZiWAyIlAS4/ng8QScyf4HPIPz+cU3+KX6l7vpUxkUsaRRpGyNZqUOqWuKzw88D/98KrW7aALm8QhJ+TkX59LyAWovBDDAqTX5bq3v66y56yubapYLizBT7lCCgJvSzwtMUwZ+XKFZAgKTyUlJQkswZoLBYLGzduRHh4OO7evQtVVVWZzFMVtLW1wWazoa6ujjNnzsjVXR8UFIS+ffvWyhABoOCeATabjTZt2tCaN/DixQtcvHgRc+fOpaWuvqx58eIFRo8ejV3zRkk1BKqLMiZySaOs4kxE8GW3hI6zFzSsnKDj2AuqdRp9OUksvZucsnXZo5oZ7tZYM9ABalx2mTkEpcFhs6DGZcN3oAOmu5efzKqoUFmFsCw4HA66du0KDodT4iGgm5ycHPTp0wcqKipo0aKFXDsoPn/+HFFRUbWu0NDXKLRnACh2Gx0+fJi2+Tdt2oR69ephxIgRtGmQBU+fPsWff/6JoKAg1K9fHxuWLsQ9NQOEvvlcauzWuM8cGPepfPIkh81COyujGvO0W1ZxJjULBxQkPAEAZPNPg8XhQJiRhMKU1wAAFWMLqNZtLHVsSZe95aA/s5suhjtboH1jYyw+/RS34z+Bw2aVvdsABAQstKynji2jXJUyNPA18jIGAODRo0dwc3PDx48f0aNHD9y7dw8mJiYyn7c0hEIhhg0bhpiYGHh7e+PChQsghMjtAay2hwgABfcMAMV5A+/fv8eHDx/kPndqaioOHjyImTNnQk2t9Op6ykZERAS8vLzQokULhIWFYffu3YiPj8eMGTPgO6gVuJV8IisPZU3kKo3yijPp8QZDu4UnwGKjIOEJUo4vRfrVnYBYCC37Lqg7YhVYnLLtb2XqsicrzA01cWgCD9d8OmI0zxKWRpo/hGVYACyNNOHtYoHCM7/D6MkxpTcEAMDIyAhcLlcm2wu/hhCCsLAwtG/fHpcvX0ZWVhb69euHvDz5F8IihGDatGm4evUqTp48ib59+yI5ORnv3r2Tm4baHiIAlMQzABTvh+3fv79c5965cyfYbDamTJki13llwYMHD/DHH3/g0qVLsLa2xj///INRo0Z9s6VIksi16BR1iWzKmshVGuUWZ+JwwTWqD7a6NsT531Z6K3gdCYFtDDSteWXOISnOZGemV+Z5tQHrujpY3s8Oy2GHXIEQb9JyUSgUQ5XLRkMjrZKEVJ244fj999+xYsUKmJmZlTOqYsNms1G3bl2Zewbev3+PpKQkODs7o1GjRrh48SI6d+6MkSNH4uTJk3Ltu/LXX39h37592L9/Pzw9PUs+O5/Ph7m5ucznl4QI/vjjD5nPpcgovGegQYMGqFevntzzBvLz87Fjxw6MGzcOhoaGcp2bSm7duoVu3bqhbdu2eP36NY4cOYJnz55h7Nixpe4tHu5sgfmeNtWctfiWqcyJXKVRXtGkzDtH8TnkH4jzs6Dj1BfmcwJhOm4r2Fr6EOVmIPXMagg/J1d7ntqIlhoXdmZ6aG1hADszvW92pkyePBnq6urYvHkzfQIpRNbbCwGU7OWX7CRo06YNAgMDceHCBcyaNUvqrheq2b9/P37//Xf88ccfGDNmDIDiz1+/fn25rflBQUHQ1tZGjx495DKfoqLwxgCLxfqmEIW8OHz4MD59+gQfHx+5zksFhBDcuHEDnTt3RqdOnZCSkoKgoCBERUVh5MiR4HLLdghVJ5GLiEVQ43KUPpGrNMormpTz+ErJa712w8BW04RqXSto2vy/KJNIiPxX5W+TVbbiTHSjp6eHadOmYffu3fj8+TPdcqqNPIyBsLAwmJmZfeNJ6dWrF3bv3o2dO3di3bp1Mp0fAK5evYqJEydi4sSJ+O233745Js81v7b2IvgepVh1JK0t5WWtisVibNy4Ef3790eTJspzQyOEIDg4GO3bt4eHhwdycnJw5swZREZGYvDgwZXarzvc2QLX53RCOysjACjXKJAcN2Vn4fqcTjXKIyChvC57oq9CA+KiL902SWH+l/e/el0aylqciW5mz56NwsJC7N69m24p1UZWJYm/Rlqnwp9//hlLly7FwoULcfToUZnN/+jRIwwaNAienp7YuXPnD4mCLi4uePjwIcRi2XrJXrx4gaioqFrZi+B7lMIYcHZ2xufPnxEfHy+X+YKDg/HixQulKTJECMHZs2fh4uKCXr16AQAuXbpUkmdR1aIdFUnkAiFg56XBxaAA7/dNwaHxvBqTI/A95RVnUjX+si88PXgb8l8+RHb4BeS+uPPlnLpWZc6h7MWZ6KJevXoYM2YMNm/erHBtzyuLrD0DYrEYfD5farGh5cuXY+zYsRg7dixCQkIonz8hIQG9evVC06ZNcfz48VI9lc7OzsjKykJsLDUlv6UhCRHU5l0EEpTGGAAgtxjShg0b4OLiIvMOWdVFLBYjKCgIrVq1woABA6ClpYXr16/j7t276NmzJ2XbciSJXDfnuyNqeXdcnOmG01Pb4eJMNyxolISE7eOQdHEb2tlZwdrampI5FZWyuuzpdRhV0rWwIOExUoKWI/3abkBUXJlR3bIl1Bu2ljp2TSrORAfz589HSkoKDhw4QLeUamFqaork5GSIRNJrUlSHuLg4ZGVlSe1UyGKxsHfvXri7u2PAgAF4+pS6hOKMjAz07NkT6urquHDhArS1tUs9r02bNgAg81CBZBeBhob09uu1BaUwBgwNDdG4cWO5xJAiIyMREhKCefPmKWyRIaFQiCNHjsDe3h5Dhw5F3bp1cevWLfz333/o2rWrTHV/n8jVpWN7iMVi/Pfffxg/frzM5lUUyuqyp9nEBXVHrYGGtSs4WgYAmwOWihpU6jSCfsefUGfIsjK/m5pUnIkOrK2tMXjwYKxbt05mN1J5YGpqCpFIhE+fPslkfMk6KrnhloaKigpOnDgBKysr9OrVi5JtfgUFBRgwYABSUlJw+fJl1K37Y7VSCfr6+rCxsZHpA+CLFy/w9OnTWl1o6GuUxh8pyRuQNRs3boSlpSUGDhwo87kqS1FREQ4fPoxVq1YhPj4evXr1gr+/P1xdXWnT1LRpU2hoaEAkEmHw4MG06ZAXki57916llWoUqDdoDvUGzSs9bk0rzkQXCxcuRJs2bXDy5EmlXeQlLdKTkpLKvGFWlbCwMFhbW5db4U9HRweXLl2Cq6srevXqhdu3b0NPr2pbXsViMcaMGYOwsDDcuHEDNjbl71iSdRIhEyL4FqXwDADFvxgREREoKpLeDKe6vHv3DgEBAfDx8Sk3416eCAQC7NmzBzY2Nhg/fjzs7e3x8OFDXLx4kVZDAEBJgo+xsTG0tGpH4tsqLwemOJOC4uTkhK5du8LX11duCcdUI+sqhNKSB6VpuXz5Mt6+fYuBAweisLCwSnP+8ssvCAoKwtGjR9GuXcVanjs7O+PRo0dVnrM8mBDBtyiNMeDi4oKCggJER0fLbI5t27ZBS0sLEyZMkNkclSE/Px/bt29HkyZNMHXqVLi4uODx48c4ffo0nJyc6JYHALhx4wby8/ORlpYmU0NNkWC67Ck2ixYtQkREBG7cuEG3lCoh8QbIwhgoKipCZGRkpToVNmvWDOfOncOdO3cwfvz4ShtZW7ZswYYNG7B161Z4eXlV+DoXFxcIBAJKcxYkSEIEzC6CLyiNMdC6dWtwOByZxZCys7OxZ88eTJo0CTo69Lpqc3NzsXHjRlhZWWH27Nno3LkzoqOjcfz4cbRo0YJWbd/j5+cHKysrCAQCPHr0iG45coOa4kzF1LTiTHTTtWtXODo6Ys2aNXRLqRJqamowNDSUyfbCp0+fQiAQVNgzIKFDhw44fPgwjhw58kNNgLI4efIk5syZgwULFmDGjBmVmrNVq1bgcrkyCRUwhYZ+RGmMAU1NTdjb28sshuTv74/c3FzMnDlTJuNXhOzsbKxZswYNGzbEwoUL0atXL8TExODQoUNo1qwZbbqkkZaWhjNnzmDKlClQV1fH7du36ZYkV5gue4oJi8XCwoULcePGDYSHh9Mtp0rIanshn88Hh8NBq1atKn3tkCFDsHHjRqxevRq7du0q9/y7d+9i1KhRGDZsWJUMMw0NDTg4OMjMGGBCBN+iNMYAUBxDkoVnQCgUYvPmzRg6dKhcamF/z+fPn7Fy5UpYWlpi2bJlGDx4MOLi4uDn56fQRY+OHDkCQgjGjh0LHo+HO3fulH9RDeP74kykjBbFwJfiTO2sjGpscSZFYNCgQWjcuDF8fX3pllIlZGkMODg4QFOzaiGpOXPmwMfHBzNmzMC5c+eknvfixQv069cPrq6u2L9/f5VrnchizY+JiWFCBKWgVMaAi4sLoqOjkZubW/7JleD06dN48+aN3IsMpaWlYcmSJbC0tMTq1avh7e2Nly9fYteuXWjYsKFctVQWQgj8/PzQr18/mJiYoEOHDrhz547SJm1VB0lxpqkWn5ATcQnm+mpSu+yN5lni+pyOODSh5hZnUgQ4HA4WLFiAkydPIi4ujm45lUZWxkBYWFilQwTfs2HDBgwcOBDDhw9HaGjoD8eTkpLQs2dPmJqa4syZM9Xq+Ors7Ixnz55RuuYzIQIpECUiMjKSACC3b9+mbEyxWEx4PB7p3LkzZWOWR1JSElmwYAHR0tIimpqaZN68eeTjx49ym58K+Hw+AUAuXbpECCHk8uXLBACJiYmhWRl9DBkyhPB4PEIIITkFRSTq/WcSkZBOot5/JjkFRTSrq33k5+eTunXrkkmTJtEtpdIsWLCANG7cmNIxc3JyCJvNJnv37q32WPn5+cTNzY0YGxuTuLi4kvezs7OJo6MjMTMzIwkJCdWe5/HjxwQAuXXrVrXHkuDg4EBGjBhB2XhUEx4eTgCQ8PBwuc6rVJ4BOzs7aGhoUBpDun//PkJDQ+XiFfjw4QN8fHzQqFEj7N69G7NmzcKbN2+wfv36kr3FyoK/vz/q168PT09PAEDbtm3BZrNrZagAKA41Xbt2DT179gRQdpc9Bvmgrq6O2bNn48CBAzKv9U81Es8AodDTFhkZCbFYXKmdBNJQV1fH2bNnYWxsjB49eiA1NRVFRUUYMmQI4uLicOnSJVhYVD8E1rx5c2hoaFAWKmBCBNJRKmNARUUFrVu3pjSGtGHDBtja2pbU9JcFiYmJmD59Oho1aoQDBw7gl19+wZs3b7Bq1SqYmJjIbF5ZkZ+fj6NHj2Ls2LElfc91dXXRokWLWmsMPHjwAJ8/f2ZcjwrG1KlToaqqii1bttAtpVKYmpoiLy8P2dnZlI0ZFhYGDQ0N2NlRsy3W0NAQwcHByM3NRe/evTFx4kRcv34dp06dQsuWLSmZg8vlwtHRkbIHQCZEIB2lMgYAaqtSvXz5EqdPn8bcuXOrnOBSFq9evcLEiRPRpEkTHD9+HMuWLcObN2+wfPlyGBoaUj6fvDh58iQyMzMxbty4b953c3OrdTsKJFy+fBlGRkZllnhlkD/6+vqYMmUKdu7ciczMTLrlVBhZFB7i8/lo3bo1pQXVGjZsiIsXL+LRo0c4cOAA9u3bBw8PD8rGB6itPhsUFIQ+ffowuwhKQemMARcXF7x8+RJpaWnVHmvz5s0wNjbG6NGjKVD2hZiYGIwZMwY2NjY4f/48Vq1ahTdv3mDx4sVVLuepSPj7+6Nz585o3LjxN++7ubkhPj5e6VyyVBAcHIzu3buXeEoYFAcfHx8UFBRgz549dEupMF+XJKaKsLAwSkIE3/P48WMUFRWBxWIhLCyM8iRiZ2dnvHr1qtq9GmJiYvDkyROlLVMta5TOGJBkwj58+LBa46Snp8Pf3x/Tpk2jzEqMiorCiBEj0KxZM1y/fh0bN27E69evMX/+fKnduZSNly9fIiQkpNQqjW5ubgCK9xfXJpKTkxEREcG4HhUUMzMz/PTTT9i0aZPStDem2jOQlpaGV69eVXsnwfdcuXIFEydOxOTJk7Fv3z7s2rWL8u2cVK35TIigbJTOGGjSpAn09fUrnDeQKxAi+kMmIhMzEP0hE7kCIQBgz549EIlEmDZtWrU1RUZGYtCgQXBwcMC9e/ewY8cOvHz5ErNmzapx7qj9+/dDV1e31EZO9evXR6NGjWpd3sCVK1cAgGl4osAsWLAAycnJOHToEN1SKoSOjg40NTUpMwYkN1IqjYGIiAgMHjwYPXv2xPbt2zFhwgQsX74cv/76Kw4fPkzZPI0bN4aBgUG1QwVMiKBslC7FmcVilZs3EJecjSOhiQiJSUFieh6+dlqxAJgbaOB1aCq8xk5DnTpV7x8fFhaGP/74AxcuXICVlRX+/vtvjB49GqqqqlUeU5ERiUTYv38/Ro4cKbVoiZubW60zBoKDg+Hk5FSt3yUG2WJjYwMvLy+sW7cO48ePV/hwDovForTWQFhYGPT19SkrYvbmzRv07t0bzZo1Q0BAQEkewtKlS5GYmIjx48fD1NQUXbt2rfZckjW/OonjkhDBsmXLqq2npqJ0ngGgOG+gtNjU2/Q8jPYLRbfNt3AoNAEJ3xkCAEAAJGbkg23bGfcNumK0XyjepudVav47d+6ge/fu4PF4iIuLw8GDBxETE4MJEybUWEMAAK5evYp3796V2cjJzc0NkZGRyMnJkaMy+hCJRLh69WrJlkIGxWXhwoWIi4vDmTNn6JZSIerVq0dZzoCkUyGLVf1um+np6ejZsyc0NTVx4cKFb7qVslgs7N69G127dsXAgQPx5MmTas8HfEkcr2o+QlBQELS0tJi/0zJQSmPA2dkZycnJePfuXcl7AfxEeGy6iXuvihMLS+s1/zUsdvGTwb1XafDYdBMB/MQyzyeEICQkBO7u7ujQoQM+fPiAgIAAREdHY/To0QrV8lhW+Pv7w8HBocyOiW5ubhCJRHjw4IEcldEHn88vWRwZFBsXFxe4u7srTXtjqjwDhBDKkgcLCgrQv39/pKam4vLly6V6w1RUVBAUFIQmTZqgV69eePv2bbXndXFxQXJycpXHYnoRlI9SGgOSX2qJ22h7SBwWnXoKgVBcrhHwPSIxgUAoxqJTT7E95MeypYQQXLlyBR06dECXLl2QmZmJkydP4vHjxxg2bJjCuxupIjU1FWfPnsWECRPKfLpo2rQpDA0Na02o4PLly9DX15dJljYD9SxcuBB8Ph8hISF0SykXqoyBd+/eITk5udr5AmKxGKNHj8bDhw9x4cIFWFtbSz1XW1sbFy9ehIqKCnr27InPnz9Xa26J9qrkDcTGxuLJkydMoaFyUEpjwNTUFPXr1wefz0cAPxHrr8ZSMu76q7E4/n8PASEE58+fB4/HQ48ePVBUVITz588jPDwcAwcOlEldAkXm8OHDYLFY8Pb2LvM8NpuN9u3b1xpjIDg4GJ6enrXCM1QT8PT0RKtWrZSigRFVYQLJDbS6xsD8+fNx6tQpBAQEwNXVtdzz69Wrh+DgYHz48AFeXl4QCARVnvvrNb+yMCGCiqG0K5iLiwvuPn6B0yrRPxx7t3M8RFkpZV5fd8QqqFu2+OH9peeikRn3ELvW/YFHjx7Bzc0NV65cQbdu3SiJtykj5P9Nifr37w8jI6Nyz+/QoQNWrFiBoqIiqKioyEEhPaSmpoLP52PKlCl0S2GoIJL2xiNGjEBkZCRat25NtySpmJqaIi0tDYWFhdXKReLz+ahfvz7MzMyqPMamTZuwadMmbN++Hf3796/wdU2bNsW5c+fg4eGBcePG4fDhw1V+kJLkilWWwMBAZhdBBVDax1tnZ2e8NORBWMmwQAmc0u0gQWERfj8XDUNDQ4SEhODWrVvw9PSstYYAULyYREdHl5k4+DVubm7Izc3F48ePZayMXq5duwZCCLNvWckYPHgwGjVqpPDeAUmtgep6B6rbqTAoKAjz5s3DwoULMX369Epf7+bmhiNHjiAgIACLFy+usg5nZ2eEh4dDLBZX+BpJiIApNFQ+SmsMNGjeBqoWLUrNETDx+hV1R/l+88+w58yS4xxtQ6iZ2pQ+MJsDjUaO2HPsDDp37lyrjQAJfn5+MDc3r3CZUUdHR6irq9f4UEFwcDBatmxZsmgzKAdcLhfz589HUFAQXr58SbccqVBReEgsFuPhw4dVNgZu376N0aNHY8SIEVi1alWVdQwaNAibNm2Cr68vduzYUaUxnJ2dkZWVhdjYioeFmRBBxVFaY+BZkRGIWFTqMTVTa6ib233zryj5dclx7ZbdwZLiGQAADpuFww/K3l1QW8jLy8OxY8e+aUpUHmpqanBxcanRfQrEYjGuXLnCLDJKyrhx42BkZIQNGzbQLUUqVJQkjouLQ1ZWVpUSXJ8/f47+/fujXbt28Pf3r3ae1OzZszF37lzMnDmzSts7JX0/KhMqYAoNVRylNQbuvc4s2R5YHuLCAuRE/1v8A5sD7VZlu3VFYoKQ2LJzDmoLJ06cQHZ29g9NicpDUnxIGbZwVYWIiAikpqYyxoCSoqGhgdmzZ8Pf3x/Jycl0yykVExMTcDicankGJDfOyjbQ+vjxI3r27In69evj1KlTUFNTq7KGr1m3bh2GDBmCESNG4P79+5W6Vl9fHzY2NhVOIoyNjcXjx4+ZXQQVRCmNgRyBEImVKBSUGx0CIig+X9OmLbg65SfBJabllZQurs34+/uja9euaNSoUaWuc3NzQ0pKCuLj42WkjF4uX74MXV1dtG3blm4pDFVk2rRpUFFRwdatW+mWUipsNht169atljHA5/NhbW0NfX39Cl+TnZ2N3r17QygU4tKlS5W6tjzYbDYOHDgAZ2dn9O3bt1Iuf6ByXWuZEEHlUEpjICEt94fKgmWRHXGx5LWOY+8KXUMAvEnLrZywGkZ8fDxu3ryJ8ePHV/radu3agcVi1di8geDgYHh4eNTo3RI1HQMDA0yaNAk7d+5EdnY23XJKpbq1BipbbKioqAhDhgzBy5cvERwcDHNz8yrPLQ11dXWcOXMGderUQc+ePZGSUnEvrIuLCyIjI1FYWFjuuZIQgbTS6QzfopTGQKGw4tmkBW+jUZT6BgCgYmwBdQsHmcxTE/H394e+vj68vLwqfa2enh5atGhRI42B9PR0PHjwgNlFUAOYM2cOcnNzsXfvXrqllEp1ag0UFhbi0aNHFU4eJIRg8uTJ+Pfff3H69Gk4OFR8rawshoaGCA4ORl5eHvr06YPc3Io9eDk7O6OwsBBPnz4t87y4uDgmRFBJlNIYUOVWXHZ25KWS1zqOfWQ2T01DKBTiwIEDGDlyZJWTb2pq06Lr169DLBYzxkANoEGDBvD29sbGjRurVRRHVlTHMxAVFQWBQFBhY2DFihX4559/8M8//6BLly5VmrMyWFpa4tKlS3j+/DmGDx8OobD8sGyrVq3A5XLLDRUEBQVBU1OTCRFUAqW82zU00kJFNvyJcj8jL+YuAIClpgkte/cKz8H6/zy1lStXruDDhw8Vri1QGm5uboiNjVXYBK2qEhwcDDs7O5m4UBnkz4IFC/DhwwccOXKEbik/UB1jICwsDBwOp0KFlfz8/LBixQqsXr0ao0aNqtJ8VaF169Y4efIkLl++jOnTp5ebcKyhoQEHB4dydxRICg0xIYKKo5TGgJYaFxaG5X/JOY+vAKJia1PbrgvYqhV/wrUw0oSWmtIWaKw2fn5+aNWqFRwdHas8hpubGwDg7t27VMmiHUIILl++zDxx1CCaNWuGAQMGYO3atZUqaCMPTE1NkZycXCVdfD4fDg4O5Xr2goODMXnyZEydOhULFy6sqtQq4+npiX379mHv3r1YvXp1ueeX28L+/yECptBQ5VBKYwAA3G3rgMOW7h8gYhGyH10u+bmiiYNAcZ0Bd5va25s+JSUF58+fr1Li4Nc0aNAAlpaWNSpU8PjxYyQlJTHGQA1j4cKFiImJwdmzZ+mW8g316tWDUChEWlpapa+VtC0ui/DwcAwZMgS9e/fGtm3baCuyNnbsWKxcuRK//fYbDh48WOa5Li4uePbsmdQ26UyIoGoorTEwimdRZofC/Hg+RFmpAAB1yxZQMa64S1ckJvB2tai2RmXl0KFD4HA4lLgLa1reQHBwMLS0tNC+fXu6pTBQiKurKzp27Khw7Y2rWoUwNzcX0dHRZe4keP36NXr37g17e3scO3aM9g6sS5Yswc8//4wJEybg2rVrUs9zdnaGWCxGREREqceZXQRVQ2mNAeu6OujQxFiqd0DTxhWWiy7ActEF1B1R8TKaRCxCwZtIbPtrCVJTU6mSqzRImhJ5eXnB0NCw2uN16NABERERFc4WVnQuX76Mrl27UlaEhUFxWLRoEUJDQ3Hr1i26pZRQGWMgVyBE9IdMRCZm4PR/fBCOqlTPQFpaGnr27AkdHR2cP39eIW6cLBYLu3btgqenJwYNGiS1t0nz5s2hoaGBu2EPSz5v9IdM5AqEiIuLw6NHj5hdBFWARRTJDK4kb9Pz4LHpJgRFIoAi95Yal40BqlHYvf5PiMVizJ8/H3PnzoWOjg4l4ys6Dx48QNu2bXH16lV069at2uNFR0fD3t4eN27ckEuGsizJzMyEkZERtm3bhqlTp9Ith4FiCCFo1aoV6tevj0uXLpV/gRwoKCiAhoYG9u/fjzFjxvxwPC45G0dCExESk4LE9Lxv6q8QQmBppIkutnUximcB67rFa1h+fj48PDwQGxuL+/fvo0mTJnL6NBUjJycHnTt3xsePH3H//n1YWHzx0ko+76F/IyFS1/9m3WcB0GEJkBT5L67vXoYWlibyF08BERERcHJyQnh4eLVytiqL0noGAMDcUBMr+tlRZggAwMp+dvD9fQFevXqFyZMnY/Xq1WjcuDG2bdtWoUIXyo6fnx8sLS3RtWtXSsZr1qwZDAwMakSfghs3bkAkEjGxyBoKi8XCL7/8guDgYIXpuKmurg4DA4MfPANv0/Mw2i8U3TbfwqHQBCR8ZwgAxZ8nMT0fh0IT0G3zLYz2C8Wb1Gx4e3sjMjISFy5cUDhDAAC0tbVx8eJFqKmpoWfPnsjIyPjh84o0DH5Y9wmALKIGzZbd0W93GEb7heJtJSrV1naU2hgAgOHOFuhej5r9wQs8bTHMudgKNTIywvr16xEbG4s+ffrAx8cHTZs2xZEjRxQu45gqcnNzERAQgHHjxlW7KYkENpuN9u3b14i8geDgYDRt2hQNGzakWwqDjBg2bBgsLS2xdu1auqWU8P32wgB+Ijw23cS9V8VJhWXlTn19/N6rNHTZEIJrr4r/znk8nuxEV5O6desiODgYSUlJ8Ji8tFKfF6ziteveqzR4bLqJAD7TdK4iKL0xAACL+rVG2qWtUGGjzB0GpcFhs6DGZcN3oAOmu/9oJVtYWMDf3x9PnjyBg4MDvL294ejoiODgYIVKNKKCoKAg5ObmYuzYsZSO6+bmhvv371eoqIiiQghBcHAwU2iohiNpb3z8+HG8fv26/AvkwNfGwPaQOCw69RQCobj8m+J3iMQEIrBh2GMmEnWayUIqpdja2mLChkCkNe4BQZGoSp9XIBRj0amn2B4SJyOVNYcaYQw0bNgQau/D0Y/7GO2sipsQlWcUSI63szLC9TmdSjwC0rCzs8PZs2dx584d6OjooFevXnB3d0doaCg1H0IB8PPzg4eHBywtLSkd183NDbm5uQrjeq0K0dHReP/+PRMiqAWMHz8eBgYGCtPeWFKSOICfiPVXK9fY53skWwfXX43FcQV/Yg7gJyIwpqD4h2qGgpXh89JNjaiqw2Kx4OLiguf8O7i0YvGXpJrYFCSmfRtLY6G4oJC7TR14u1qgSZ3KJQa2b98et27dwqVLl7Bo0SK4urpi4MCB+Ouvv9C0aVNKP5c8iY2NxZ07dxAQEED52G3atIGamhru3LkDJycnyseXB8HBwdDQ0EDHjh3plsIgYzQ1NTFz5kysWbMGy5Ytg4kJvYlopqamePA0DsvORf9w7N3O8RBlld3op+6IVVC3bPHD+0vPRaNdY2OYV6CAm7x5m55X6ueVIHj/ApmhJ1H4IQaivEyw2FxwDepB09oVurxBYKv9+JkU+fMqAjXCMwB8qUpFCIF1XR0s72eHm/PdEbW8Oy7OdMPpqe1wcaYbopZ3x8357ljez67ShoAEFouF3r1749GjRzhw4ADCw8NhZ2eHiRMn4t27dxR/Mvng7+8PAwMD9O/fn/Kx1dTU4OLiotR5A5cvX4a7uzvU1dXplsIgB6ZPnw42m41t27bRLQWmpqbIs+8PYSXd5CVwSn/mE4oJFp8uu+EPXSw+/VTq5y1IeIKkIwuRH3sfopx0QCwCEQpQlJqAzHvHkXz891JDuIr8eRWBGmMMuLi44NOnT3jz5s0372upcWFnpofWFgawM9OjtMQwh8PBTz/9hJiYGGzYsAGnT5+GtbU1fvnlF6Snp1M2j6yRNCXy9vaW2c3Ozc0Nt2/fVso8i+zsbNy+fZvJF6hFGBkZYeLEidi+fbvUSnfygm1QH6oWLUuNmZt4/Yq6o3y/+WfYc2bJcY62IdRMbUodVyQmuB3/CfEpitW+OS45G7fjP0nNEcgKPw+IRQCKC8rVGboChp7TAHbx2l74IQaFyS9/uE5RP6+iUGOMAUlxjfK6WckCNTU1+Pj44NWrV1iwYAF27tyJxo0bw9fXF3l5ir+1RZK1W93yw2Xh5uaG5ORkvHz54x+pohMSEoKioiImX6CWMXfuXGRnZ2Pfvn206ogq0Af5/83ve9RMraFubvfNv6LkL4mP2i27gyXFMwAU504dfqBYsfQjoYlll5oXfClgpuPsBQ0rJ+g49oJqnUZfTpLy/6WIn1dRqDHGQJ06dWBpaVluNytZoquri5UrV+Lly5cYNWoUlixZAmtra+zbt0+hM+n9/Pzg6OiIVq1ayWyOtm3bgsViKWWoIDg4GE2aNFHIPdkMssPc3ByjRo3Cxo0baa0xEp0BsNgVKxUsLixATvS/xT+wOdBuVbY3SyQmCIktO+dA3oTEpJS5c0DNwqHkdTb/NPJfRyA74hIKU4qNIBVjC6jWbVzqtYr4eRWFGmMMAOV3s5IXdevWxfbt2/HixQt06tQJkyZNgr29PU6ePKlwbvKkpCRcuHChWq2KK4KBgQHs7e2VzhhgthTWbn75X3t3HhZV2f4B/DsLiyD7opiybwoiijMoDrFo6qtmLpkrlrknmbjhUmq+ZaD2qlj+Ml/3XdO0MsZQeFEDDERBERBEBEUEQZB1WGZ+fyCkyTLA7HN/rqvrsplzzvOMwjn3nHM/971yJR49eoTjx4/LZfxyQR3yy8T/IlGREgWRoOFupI7jYLD1TNrcJ6eoEhUCxfiyUi6oQ04bhYIMPN9HV7fhAIOJ6ofJKDi5DsV/7AKEddB19Ue3qZtavRuiSJ9XkahUMMDlcnHjxg3U1zd/i0jW7OzscOzYMSQmJsLa2hrvv/8+Bg0ahKioKHlPrcnhw4fBZrMxdepUqY+ljE2L0tPT8fDhQ3pEoKb69OmDd999F6GhoXIpNvawqOKNyoKtKUu80PRncTu1igBkFylG7xCxPi+LDbbJW2Bqd33jreoHNyHIS291d0X6vIpEpYIBDoeDiooKpKamynsqr+nfvz/4fD4iIxtu3/n7+2PkyJG4efOmXOfV2JRo4sSJMDIykvp43t7eSE9PV6oGUOHh4dDS0oKvr6+8p0LkJDg4GKmpqfjtt99kPnZNnfgBSHVuCmoLswE03CrXfuV2uiTHkSZx5lF67RhKovZDWPUCeh7volfQKVjMCgNT1xD1Fc9ReO4b1JU87fQ46kalggEPDw8wGAyFeFTQHD8/P8TFxeGnn37CgwcPMGDAAEybNk1uSXWxsbFIT0+X+iOCRjweDwCU6u4An8+Hj4+PQnR1I/IxZMgQ8Hg8hISEyPwxnyZb/FN02c2/myvpDRgjtXGkSZx5lCddbPqzgddkMLV0oNnNFjqOXg0v1tehKiuh0+OoG5X6G9HT00Pv3r3lmkTYFgaDgYkTJyIlJQU//vgjoqOj4ezsjMDAQDx92no0K2l79+6FjY2NzL719urVC5aWlkoTDFRWViI6OpryBQiCg4MRGxsr859daxNdiFN7r76iBJXpfwIAGFo60HX1a9c4Zl06MDkpEOfz1le9aPqzsLa66c+imqq/X3/lz//EeDkOeZ1KBQNAQ96Aot4ZeBWbzcbcuXORkZGBr776CkePHoWdnR3Wr1+PFy9etH2Adni1z3lj3++ysjKcPHlSok2JxKFMeQNRUVEQCASUL0AwatQouLi4IDQ0VKbj6mqxYSlGxbzypItAfUNSXFcXfzA1xb+61xbnoWc3M3h7e2PDhg24cuUKBALJNH9rL3E+r6bp3+XSi8N3oup+Aspu/IaKtL/PK5rdbFvc39JER6L1ZlSFygUDHA4HSUlJqK6ubntjBaCjo4Pg4GBkZWVh0aJF2Lx5M+zs7LB9+/ZO/UJmPC3Dhl9S4LMlCq4bLmL0zmsY/38xGL3zGlw3XMTbWyKhNXgGfMZOkeCnaRuPx0NiYiIqKhQ/gYfP58Pa2hpOTk7yngqRMyaTieDgYFy4cAG3b8u2ip2fkzkYraTViYT1KLvFb/p/cRMHgYZ19xO9emP79u0wNzdHWFgYfHx8YGRkhBEjRiA0NBTx8fEyTcr2czJvtc6Agff0ps6E1Q+TUHB6A4ojfgDqawEA2lb9oG3dv9l9WUwG/BzNJT9pFaBywQCXy0VdXZ3SNcUxMjJCaGgoMjIyMG7cOCxbtgxOTk44dOhQu34RxelzLgLwvJYNPY/RmHninkz7fvN4PNTV1Sn0o5xGjUsKGZ1skkJUw5QpU2BpaSnz9sbTPS0hauXmeVVmPOpfNCTlalu5QcO0l9jHrheKsPhf/fDJJ5/gzJkzePbsGRITE7Fx40awWCz8+9//BpfLhYmJCcaNG4ewsDCkpKRINXdiuqdlq3UGdOy56DY9BF0cBoGlawQwWWBoaEHD3AaGb8+E+aT1Lf7O1gtFmDGo9aZ06oohUrSF751UU1MDPT09bN26FZ9++mnbOyiotLQ0rF27FmfPnkXfvn3xzTffYNSoUa1emE7E52D9LymoE4ra1e6TxWSAzWTgy7EumNJG98bOEgqFMDExwdKlS/HFF19IdazOyMzMhIODA86fP4+xY8fKezpEQezYsQPLli3D/fv3Jd7dszX/Cr2Au0V1ra6fby8WkwEvWxMcnu3Z4ja1tbX466+/EBkZicjISMTExKCmpgbm5ubw9/fH0KFD4e/vDxsbG4kGzQF7ryMmq6jdbYtbI87nVQSJiYnw8PDAjRs3MGDAAJmNq3J3BjQ1NeHu7q4UeQOtcXZ2xpkzZxAXFwcTExOMGTMGPj4+iI2NbXb7zvY5l1XfbyaTiSFDhuDq1atSHaezwsPDoaGhAT+/9iViEdU2Z84cGBgY4D//+Y9Mx/3My7zFksQdxWYysGl868sPNTQ0MGTIEHzxxReIiorC8+fPERERgdmzZ+PBgweYP38+7OzsYGNjg9mzZ+Po0aPIy8vr9Nw2je8Ldhtt6NtLnM+rzlQuGAAa8gaU4Ta0ODw9PREZGYnw8HC8ePECXl5eGDduHO7evdu0jST6nDeSRd9vHo+H2NhYhS7RzOfz4e3tDT29jnW2JKpJV1cXn376Kf773//i2bNnMhvX3aEXnkfslugxN451aXc7Xx0dHQwbNgybNm1CXFwciouL8csvv2D8+PGIj4/HjBkz8NZbb6FPnz4IDAzE2bNnO9S0rZexDr4c69Lu/VrTkc+rTlQ2GEhPT0dpaam8pyIRDAYDI0eORGJiIo4ePYrk5GT07dsXH3/8Ma6n3G+173ft8zw8+/VbPPpuJh5uHodH381E0e9hqCtr+US27pcUqeYQ8Hg8lJeXIzk5WWpjdEZ1dTWioqJoFQFpVmBgIEQiEb777juZjWlmZobKO5fwtqFkzmkrhjthsgQeCRoYGODdd9/Ftm3bkJycjKdPn+LkyZPw9vbGxYsXMXHiRJiamsLDwwMrVqxAeHi42F0gp3AssXx48x0X20tSn1eVqWQwwOVyAQAJCa0XnlA2TCYT06ZNQ1paGnbs2IELFy5g3NcnUFPb/DfsmqdZeHJgCSpSol72/a5DfXkxypP/QP7BpS1W6ZJ23++BAwdCU1NTYZcYRkdHo6qqiuoLkGaZmppizpw52Llzp8xWxbBYLHTr1g22VfcQMqEvtNjMVjPumz0GkwEtNhOhE/pikZ90mm6Zm5vjgw8+wO7du5GRkYGHDx9i3759cHFxwbFjxzBq1CgYGRmBx+Nh3bp1iI6ObnXVVKCfg0J/XlWiksGAk5MT9PT0lD5voCWampoIDAzExdgkaFm5Q8Ro/p+xOGJ3U9MSXbd3YP7Bl01dzOrLixuW4zRD2n2/tbW1weFwFDYY4PP56NmzJ1xcJHubkqiOZcuWobS0FHv37pXZmN27d0d+fj6mcCxxKcgHXrYNTYjaukg2vu9la4JLQT4y/YZsaWmJjz76CIcOHcKjR4+QlpaGsLAwWFhYYNeuXfD19YWhoSHeeecdhISE4K+//nrj8aEyfV5lppKVF5hMJgYOHKgyeQMtOXenCCwmo9mEQWFNFQSPXuYVsNgwGfEJGCwNaFu7o+JuNEQ1Vai6n4C6F4Vg65u9sX9j3+8NEn5u18jb2xsHDx6ESCRSuKV7tKSQtMXKygpTp07Ft99+i4ULF0JDQ0PqY1pYWODJkycAGp6pH57tiYynZTh6PQdR9wqQU/T6MmIGGgrs+DmaY8YgS9ibyzf/hcFgwMnJCU5OTli4cCGEQiGSk5MRGRmJy5cv4+uvv8bq1auhr68PX19f+Pv7w9/fH66urkr5eZWNSgYDQEPewLFjx+Q9Dalqre+3UFAJvPxVYTDZYLA0Xv6ZBQZLAyJUARBB8Dit2WCgse/3BkgnGGis9Z6VlQU7u+Z7j8vDgwcPkJ6ejk2bNsl7KkTBrVy5EkeOHMGJEycQEBAg9fEsLCzeyLNx6KaHDWNdsAEuqBDUIbuoAjV1QmiymbA20VXoSntMJhPu7u5wd3fH0qVLUVtbi4SEBFy+fBmRkZEIDg6GQCCAmZlZU2AwdOhQrH+3DzYwlO/zKjqVfEwANOQNPHr0qCmSVjVt9f1m6RqCodVQf1tUW42ym+EQ1lajPPkShK/U9m4sVtIcafb99vJqaCqiaI8K+Hw+2Gw2hg4dKu+pEAXXt29fjB49WmbtjRsfE7REV4sNlx4G6G9pBJceBkp3YdTQ0MDgwYPx+eefIzIyEs+fP8elS5cwd+5cPHz4EJ988gns7e1hbW2NWbNm4efTJ2AoKlfaz6toVDYY4HA4AKCyeQNt9f1mMFnQH/h3sZzii98j99v3UfT79te2E70s4dkcafb9NjIygqurq8IFA+Hh4fDy8oKBgYG8p0KUQHBwMFJSUvD777+3vXEnWVhYID8/X+adE+WlS5cuGDp0KL7++mvExsaiuLgYv/76KyZOnIjExEQEBASgZ8+ecHZ2xqJFi3DmzBkUFRXJe9pKS2WDgV69eqFbt24qmzcgTj9uA95U6A/+AAy2VtNrLH0zaFr8vVyHqdV69y5p9v1WtKZFAoEAkZGRtKSQiI3H42Hw4MEyaWBkYWGB2tpatb3g6evrY8yYMfjPf/6DpKQkFBQU4NSpU/D19UVERATef/99mJmZoX///li+fDl+//13lJVJJwlaFalsMMBgMMDhcFT2zoA4/bgZDCaMfGai52dH0f2j7egx9we8teC/YGpqN22jYdp6pq00+37zeDykpaWhsLDlRxWydO3aNVRUVNCSQiI2BoOBVatW4dq1a4iJiZHqWBYWFgCgso8+28vMzAyTJk3CDz/8gHv37iEnJwf79++Hm5sbTpw4gdGjR8PY2Pi1CoqK3sCuQlCHByW10LRwxIOSWqk9pm2OyvUmeNW///1vbNu2DUVFRSqXGV4hqIPrhoutPipojiA/E/kHlwIiIZhd9NFz0QEw2JrNbssAcGfDCKk9i3v48CGsra1x7tw5vPfee1IZoz1WrFiBI0eOIC8vT+V+Xoj0CIVC9O3bF/b29jh//rzUxnnw4AFsbW3xxx9/4J133pHaOKpAJBIhMzOzKRkxMjISRUVF0NbWxpAhQ5qSET08PMBmyzfXoGmFRHoBcoqbWSFhrAM/J3NM97SEQzfprZBQ6YwLDoeD58+f4/79+7C3V62iE419vx+2kkRYmRmPiuQIdLHngqVnjNqCbJTGngJEDbf+9T0ntBgIANLv+21lZYVevXrh6tWrChEM0JJC0hFMJhMrVqzArFmzkJKSIrX6FHRnQHwMBgMODg5wcHDAggULIBQKcfv27abAICQkBGvXroWenh58fHyaGi65urqCyZTNDfPc4kqs+fk2rmY+a3GJuAjAw+JKHL7+EAdis+Ftb4pN4/tKpayyyj4mAP5OIlTVvIG2+n5DWIfKezEo+n07Ck6uw/OofRBWN5QC1XHmQZ87vsVdZdX3W1HyBnJzc5GSkkL5AqRDpk2bhp49e2LLli1SG0NbWxuGhoYUDHQAk8lEv379EBQUhF9//RVFRUWIjY3FqlWrUFlZiVWrVqFfv37o3r07Jk+e3FRBUVo3zk/E52DYtmjEZDXkf7TVXK7x/ZisIgzbFo0TUugfo9LBgImJCWxtbVU2b6Ctvt8aJr2g4+QFlr4ZwNIAQ0sHWj37wGR0EEzfCwaDyWpxX1n1/ebxeLhx4wYqK6XXC0EcfD4fTCaTbr+SDtHU1MTSpUtx9OhR5ObmSm2cVwsPkY7T0NDAoEGDsGbNGly+fBklJSWIjIzEvHnzkJubi0WLFsHR0RFWVlavVVCUBEXtMKvSOQMAMHXqVOTm5irEt09pUPa+38nJyejXrx+ioqLg6+sr9fFaMmHCBDx9+hR//vmn3OZAlFt5eTksLS3x4YcfYtu2bVIZw9/fH+bm5jhx4oRUjk8alJWV4cqVK02PFW7dugUAcHR0bMo38PX1hampabuOeyI+B6vOvtn3pSb/PirSrkKQewd1pQWor3wBppYOtHo4QX/QRGj3cm32eKET+kqs3LJK3xkAGh4VJCYmKnS73M5Q9r7fLi4uMDAwkGuwVltbi0uXLtEjAtIpXbt2xaJFi7Bnz54Ote0VB90ZkA09PT2MHj0a3377LW7evInCwkKcPn0aQ4cORWRkJCZNmgQzM7Om6okXLlzAixcvWj1mbnFlix1my26F40XcTxA8TmtqKieseoGq+/F4emwNKtObX6kiyQ6zKh8McLlcVFVVISWl5Ta/ykzZ+36zWCx4eXnJNRiIiYlBWVkZLSkknbZ48WIIhUJ8//33Ujk+BQPyYWpqivfffx+7du1Ceno6cnNzcejQIbi7u+P06dMYM2YMjI2NX6ug+M9ljGt+vo26Vu7gsnSNoO81GeYffAnTsSvANu7Z8IZIiOLL/212H0l2mFX5YKB///5gMpkqm0QINHT1WjrMAQA6nfAij77f3t7eiImJQX19vUzHbcTn82FmZoYBAwbIZXyiOszMzPDxxx8jLCxMKnkwFAwohp49eyIgIAAHDhxATk4OMjIy8P3338PS0hK7d+/G0KFDYWho2FRB8fQf13A181mLj3N1XfzQY8EeGL0dgC62HtDt4wOz91Y2vV//ogD1FSVv7CfJDrMqHwzo6urC1dVVZZMIG5XFnUZR+E5oshhK1/ebx+OhrKzsjSYsshIeHo4RI0bIbEkRUW3Lli3D8+fPsW/fPokfu3v37igvL0d5ebnEj006hsFgwN7eHvPnz8fJkyfx9OlTJCUlISQkBLq6uti8eTPmbzkMkbDlLzvavVzA1NB+7TW2cY/Xx9HQQnMaO8x2llqc/TgcjkrfGYiJicH69esRNJaLyGV+Stf3m8PhQFNTUy6PCvLy8pCUlET5AkRibGxsMHnyZHz77bcSz1VqrDXQWsMiIl9MJhNubm5YsmQJfvnlFxQVFcHBZ1yrq7ea82qegFZPFzA1uzS7XWOH2c5Si2CAy+Xizp07cl++Jg0lJSWYNm0aPD09sW7duqa+3xFL3kaApxWsTHTwz5CAAcDKRAcBnla4FPQ2Ds/2lFmOQHO0tbUxcOBAuQQDFy9eBIPBwPDhw2U+NlFdK1euRHZ2Nk6dOiXR41LhIeVTXQ8UVLSvx4sgPxPFEbsb/oelAaNhc1vdXhIdZlW6AmEjDoeD+vp63Lx5E0OGDJH3dCRGJBJh3rx5KCkpQXR09GtlNZWtzzmPx8ORI0cgEolkWgEwPDwcHA6n3UuECGlNv379MHLkSISGhmLq1KkS+5nu3r07ALozoEza6jD7T9W5KSj46UuIBJUAkwWzsSug1b31x7eNHWZdenS826pa3BlwdXWFtra2yuUN7Nu3D6dPn8aePXtgZWXV4nbK0Oecx+MhLy8P2dnZMhuzrq4OERER9IiASEVwcDCSk5PB5/MldkxDQ0NoaWnRnQEl0p7Or1UPElFwal1DIMDSgNm41dBx8pL4OM1Ri2BAQ0MD/fv3V6m8gdTUVCxevBhz587FpEmT5D2dTmu8YyPLRwXXr19HSUkJLSkkUuHj4wNPT0+JtjdmMBi0okDJiNv5tTI9BgU/bYSoVgCGhjbMJ62HjuMgiY/TErUIBgCoVDvj6upqTJ06FVZWVti+fbu8pyMRxsbGcHFxwdWrV2U2Znh4OIyNjZt6WBAiSQwGA8HBwYiOjkZcXJzEjkvBgHKxNtF9I2/rnyrSrqHwXAhQXweAAQPeVDBYGqjOTWn6T1RX2+L+jJfjdIbi3S+WEi6Xi7CwMBQXF8PY2Fje0+mU4OBgpKWl4fr169DRkV/in6TxeDxcuXJFZuPx+XwMHz4cLFb7snwJEdd7770HJycnhIaG4ueff5bIMbt37045A0pEnA6zVZnxTd1kARFKova/sc1bC/aCbdit2f0l0WFWre4MAEBCQoKcZ9I5v/76K8LCwrB161b069dP3tORKB6Ph9TUVDx79kzqYz19+hQ3btygfAEiVUwmEytXrsS5c+eQmpoqkWPSnQHl089c45WLvWRJqsOsyjcqaiQUCmFiYoJly5bh888/l/d0OiQvLw9ubm4YMmQIzp07J9Ose1nIzs6GjY0Nzp8/j7Fjx0p1rMOHD2PmzJnIz89Ht27NR9uESIJAIICtrS1GjBghkUJEX331FcLCwlBQ0Pm15US6MjIysHHjRpy6eBUWs6VTohoALgW9DXtzvU4dQ23uDDCZTAwcOFBp8wbq6+sxY8YMaGtrY9++fSoXCACAlZUV3nrrLZkkEYaHh2PAgAEUCBCp09LSQlBQEI4cOSKRNrgWFhYoLCxEbW3Lz5CJfN2/fx8fffQRnJ2dERkZiW0bVmKIrXG7q8O2hcVkwNvetNOBAKBGwQDQkDfw119/dbp+vzyEhobif//7H44cOQITExN5T0cqGAwGeDye1IOB+vp6XLx4kR4REJmZN28edHR0JJLw21hrgO4MKJ7s7GzMmTMHTk5OuHjxIrZt24b79+/jk08+QcjEfgrdYVatggEOh4P8/Hw8fvxY3lNpl9jYWKxbtw5r166Fr6+vvKcjVd7e3khISEBVVZXUxkhISEBxcTEtKSQyo6+vj0WLFmH37t14/vx5p45FVQgVT05ODubPnw8HBwf8+uuv2LJlC7KysrB48WJoazf0HFD0DrNqFQxwuVwAUKp6AyUlJZg6dSq4XC7Wr18v7+lIHY/HQ21trVT/jcLDw2FoaIhBg8Rfw0tIZy1evBi1tbXYtWtXp45DwYDiePToET755BPY29vj7Nmz+Oabb5CVlYWgoCB06fJmL4EpHEssH+4okbEl3WFWrYKBHj16oEePHkqTNyASibBgwQKUlJTg2LFjr5UbVlWurq7Q19eX6qMCPp+Pd955Ry3+Poni6NatG2bNmoUdO3Z06s6Xubk5mEwmBQNylJeXh8WLF8POzg4nT57Exo0b8eDBAyxfvhy6uq2v9w/0c0DIhL7QYjMVqsOsWgUDwN95A8pg//79OHnyJPbs2QNra2t5T0cmWCwWvLy8pBYMPHv2DH/99Rc9IiBysXz5chQVFeHAgQMdPgaLxYKZmRnVGpCD/Px8BAUFwc7ODocPH8a6devw4MEDrFq1Cl27dhX7OFM4lrgU5KNQHWbVLhjgcDhISEiAUCidNZ+SkpaWhk8//RRz5sxRiXLD7cHj8RATE4P6+pb7f3dUREQERCIRBQNELuzs7DBp0iRs2bKlU+2NqdaAbBUUFGD58uWwtbXF/v37sXr1amRnZ2Pt2rXQ19fv0DEVrcOs2tQZaHTp0iW88847SE1NhbOzs7yn06zq6moMGjQIAoEACQkJbd52UjXR0dHw9fXFrVu3JF5YaebMmUhKSkJSUpJEj0uIuG7evIkBAwbg+PHjmDJlSoeOMWrUKGhqauLcuXOSnRx5zbNnz7B161bs3LkTLBYLS5YsQVBQEIyMjKQynjw7zKrdnYGBAwcCgELnDaxatQqpqak4ceKE2gUCQMOjHA0NDYn3KRAKheDz+bSkkMhV//79MXz4cISGhnZ4mTOVJJau4uJirF27FjY2Nvjuu++wZMkSZGdnY+PGjVILBAD5dphVu2DA0NAQjo6OChsM/Pbbb9ixY4dKlhsWV5cuXTBw4ECJ5w3cvHkThYWF9IiAyF1wcDBu3bqFiIiIDu1Pjwmko6SkBOvXr4e1tTW2b9+ORYsWITs7G19//bXS97Rpi9oFA0BD3oAiJhHm5eVh1qxZGDNmDAIDA+U9Hbni8Xi4evWqRAtEhYeHQ09Pr6ldMiHy4ufnh4EDByIkJKRD+1tYWCA/P18pC6gpotLSUmzcuBHW1tbYsmUL5s2bhwcPHiAkJASmpqbynp5MqGUwwOVycevWLdTU1Mh7Kk3q6+sREBAATU1N7N+/XyXLDbcHj8dDXl4eHj58KLFj8vl8DBs2DBoaGhI7JiEd0djeOCoqqkN3KS0sLFBTU4Pi4mIpzE59lJWV4euvv4aNjQ02bdqEWbNmISsrC1u3boW5eeeb/ygTtQwGOBwOBAIBbt++Le+pNNm8eTOioqJw5MgRtYlEW+Pl5QUAEntU8Pz5c8TGxtIjAqIwxo8fDwcHB4SGhrZ738aSxJQ30DHl5eUIDQ2FjY0NNm7ciBkzZiArKwvbtm1r+rtVN2oZDLi7u4PNZitM3kBcXBy++OILrFmzBn5+fvKejkIwNTVF7969JRYMREREQCgUUjBAFAaLxcKKFStw9uxZpKent2tfqkLYMZWVldi6dStsbGzwxRdf4IMPPsD9+/cRFhaGHj16yHt6cqWWwUCXLl3Qt29fhcgbKC0tVatyw+3h7e0tsRUFfD4fffr0gaWl5It1ENJRAQEB6NatG7Zu3dqu/SgYaJ+qqips27YNtra2WL16NSZMmICMjAzs2rULPXv2lPf0FIJaBgNAQ96AvO8MiEQizJ8/H8XFxTh27Bg9y/4HHo+Hu3fvoqioqFPHEYlEtKSQKCRtbW0EBQXh0KFDyMvLE3u/Ll26wMDAgIKBNlRXV2Pnzp2ws7PDihUrMHr0aNy7dw+7d++GlZWVvKenUNQ2GOBwOLh79y7Ky8vlNocDBw7g5MmT+PHHH9Wm3HB78Hg8AEBMTEynjpOcnIwnT55QMEAU0vz586Gtrd3u9sZUa6BlAoEAu3btgr29PZYsWYLhw4cjPT0de/fuhY2Njbynp5DUNhjgcrkQCoVITEyUy/jp6ekIDAzE7NmzMXnyZLnMQdFZW1ujR48enc4bCA8Ph66ublNwQYgiMTAwwMKFC/HDDz+gpKRE7P2o1sCbampqsHv3bjg4OCAwMBB+fn5ITU3FgQMHYGdnJ+/pKTS1DQZ69+4NHR0dueQNCAQCTJkyBb169cKOHTtkPr6yYDAY4PF4EgkG/P39oaWlJaGZESJZn332GWpqavDDDz+IvQ8FA3+rra3F3r174ejoiIULF2LIkCFISUnB4cOH4egomZbBqk5tgwE2m40BAwbIJW9g1apVuHv3rtqWG24PHo+H+Pj4Drd8LS0tRUxMDK0iIArNwsICH374IbZv347q6mqx91H3YKCurg4HDhyAs7Mz5syZAy6Xi9u3b+P48ePo3bu3vKenVNQ2GADk0874woUL2L59O7Zs2QJ3d3eZjq2MeDweamtrOxy0Xb58GXV1dRQMEIW3fPlyFBQU4ODBg2Jtr845A/X19Thy5Ah69+6NWbNmwd3dHUlJSTh16hRcXFzkPT2lpNbBAIfDQXZ2NgoLC2Uy3pMnT/DRRx9h9OjR+PTTT2UyprJzc3ODnp5ehx8V8Pl8ODo6wtbWVsIzI0SyHBwcMHHiRGzdulWs9t0WFhZ48eIFKisrZTA7xVBfX4/jx4/DxcUFAQEB6NOnDxITE3HmzBm4ubnJe3pKTa2DAS6XC0A2HQyFQiECAgKgoaFB5YbbgcViwcvLq0PBgEgkQnh4OK0iIEojODgYmZmZOHv2bJvbqlOtAaFQiFOnTsHNzQ3Tpk2Dvb094uPjcf78efTv31/e01MJah0M2NjYwMTERCbBwObNmxEZGYkjR47AzMxM6uOpEh6Ph5iYGLG+Lb3q7t27ePToEQUDRGkMHDgQQ4cORUhISJtNiNShJLFQKMTZs2fRr18/TJ48Gb169UJcXBx+++23pnb0RDLUOhhgMBgy6WAYFxeHzz//HKtXr4a/v79Ux1JFPB4PpaWlSElJadd+4eHh0NbWxttvvy2lmREiecHBwUhMTMTly5db3U6V7wyIRCKcP38eHh4emDhxIrp3744///wTfD4fnp6e8p6eSlLrYABoyBuIj4+XWivQ0tJSTJs2DRwOBxs2bJDKGKqOy+WCzWa3+1FBeHg4/Pz80KVLFynNjBDJGzZsGAYMGNBmAyMjIyNoaWmpVDAgEonw22+/gcPhYNy4cTAyMsKVK1cQERHR1LyMSIfaBwNcLheFhYUSbZXbSCQSYcGCBSgqKqJyw52go6MDDw+PdvUpKC8vx9WrV2kVAVE6je2NL126hBs3brS6Xffu3VUiGGgsGe7p6Yl3330XOjo6iIyMRGRkJLy9veU9PbWg9sEAh8MBIJ0kwoMHD+LEiRP48ccfqQRmJzU2LRL3Dk5kZCRqa2spX4AopYkTJ8LOzq7NuwPKvrxQJBI1fev/17/+BQ0NDURERCA6Opo6uMqY2gcD3bp1g6WlpcTzBhrLDX/88cdUblgCeDweHj9+jJycHLG25/P5sLW1hb29vZRnRojkNbY3PnPmDDIzM1vcTpkLD0VFReHtt9/G8OHDm+4MXLt2DcOGDaPVVnKg9sEA8HfegKQIBAJMnToVPXv2RFhYmMSOq84anxeKkzfw6pJCOqkQZfXhhx/CzMys1fbGyhgMXLlyBb6+vvD390dVVRUuXLiA2NhYjBgxgn5f5YiCATTkDdy4caPdS9dasnr1aqSkpOD48eNUblhCzMzM4OzsLFYwkJ6ejuzsbHpEQJSatrY2PvvsMxw4cKDFRwHKFAz8+eefGDZsGHx8fFBaWorz588jPj4eo0aNoiBAAVAwgIY7A+Xl5UhLS+v0sX7//Xds27YNmzdvpmIYEiZu0yI+nw9NTU34+vpKf1KESNHChQuhqanZYkOz7t27o7CwEHV1dTKemfji4uIwYsQI8Hg8FBYW4uzZs0hMTMTYsWMpCFAgFAwA8PDwAIPB6PSjglfLDS9evFhCsyONeDwe7ty5g+Li4la3Cw8Ph4+PD92VIUrP0NAQCxYswK5du1BaWvrG+xYWFhCJRCgoKJDD7FrX+K1/8ODBePz4MU6fPo2bN29i/PjxFAQoIAoGAOjr68PZ2blTSYRCoRAzZ84Ei8WicsNS0rjEKCYmpsVtKisrER0dTUsKicpYsmQJqqursXv37jfeU8TCQ43f+rlcLh48eIATJ04gOTkZ77//PphMuuQoKvqXeYnL5XbqzsDWrVtx+fJlKjcsRTY2NrCwsGj1UcH//vc/CAQCyhcgKqNHjx4ICAjA9u3bIRAIXntPkYKBpKQkjB8/Hh4eHkhLS8ORI0dw584dTJ48mYIAJUD/Qi9xOBwkJSW98csmjuvXr2Pt2rVYtWoVhg4dKoXZEaChyEpbeQPh4eGwsrKCs7OzDGdGiHStWLEC+fn5OHz48Guvm5ubg8FgyLXWwJ07dzBp0iS4u7vj9u3bOHjwIO7evYvp06eDxWLJbV6kfSgYeInL5aK2thZJSUnt2q+0tBRTp06Fh4cHvvzySynNjjTi8XiIj49HdXV1s+/z+XyMHDmSHtMQleLk5ITx48dj8+bNr616YrPZMDMzk8udgdTUVEyZMgVubm5ISEjAvn37kJqaipkzZ4LNZst8PqRzKBh4yc3NDRoaGu3KGxCJRFi4cCGKiopw/PhxKjcsAzweDzU1NUhISHjjvczMTGRmZtIjAqKSgoODkZGRgXPnzr32uqyXF6anp2P69OlwcXFBbGwsdu/ejfT0dMyaNYvOgUqMgoGXtLS04O7u3q68gUOHDuH48eP44YcfqNywjLi5uaFr1664evUqKgR1SMkrxc2c50jJK8Uvv1+EhoYGdYYkKonL5cLPzw+hoaGvleWWVUnizMxMfPjhh+jTpw+uXLmCXbt24d69e5g7dy40NTWlPj6RLoZIWu36lNCiRYsQGRmJhFu3kV1UgZo6ITTZTFib6EJX6/XbXvfu3cOAAQPwwQcfYN++fXKasfrJeFqGSWvCUGFggzotA7z2wysSgS0owQy//pjuaQmHbnrymiYhUnHx4kWMHDkSkZGRTbX7Az6eg9TcZ9izd3+L56vOyMrKwldffYVDhw7B3Nwca9aswZw5c6CtrS2xMYj8UTDwUsbTMqw9wMefD0qhaWTx2kWGAcDSWAd+TuaY7mkJS0NNDB48GBUVFbhx4wa6du0qr2mrjdziSqz5+TauZj4DAyKI0HJOAIvJQL1QBG97U2wa3xe9jHVkOFNCpEckEmHAgAEwsHSG7+zPEZVegIfFFcArvw//PF91NCh++PAhvvrqKxw4cAAmJiZYvXo15s2bRy3BVZTaBwOvXmSYDEDYyt9G40XGXFiEO/vW4s8/fqEqgzJwIj4H639JQZ1QhPrW/oH+gcVkgM1k4MuxLpjCsZTiDAmRjdziSsz6vwhklrPFPl+1NyjOzc3Fpk2bsHfvXhgaGiI4OBgLFy6Ejg4F1apMrYOBjl5kRPV1YLOY+HpCP7rISNl3URnY+se9Th9n+XBHBPo5SGBGhMiHtIPix48f45tvvsGePXugp6eHlStXYtGiRVTJU02obTBAFxnFdyI+B6vO3pbY8UIn9MVkCt6IEpLm+erJkycICQnB7t27oaOjgxUrViAwMBB6epRzo07UMhigi4ziyy2uxLBt0RDUCV97vaYgGy+u/wRBfibqy59DVFsNppYuNM2t0dVtOHRdfFs8phabiUtBPpRDQJSKtM5XT58+xebNm7Fr1y5oa2tj6dKl+Oyzz6Cvry+xsYjyULtgoKWLTHMKTm9A1f2/17P3mPt/0DDp9cZ2dJGRvIC91xGTVfTG7dDyO1Eo+u3bFvcz9JkJg8EfNPsei8mAl60JDs/2lOhcCZGW1s5X9VVleHH9DASP01DzJAOiuobqqbquQ2E6JqjFY2qxGBhaE4eD338LNpuNoKAgLFmyBIaGhtL6GEQJqF2ZqDU/30adGM/bylOiXgsEWlMnFGHNz7fpIiMhGU/LcDXzWbPvsbp0Rdd+I6DVyxWsrkYQVpejLP4cBI8b2k+XJfzaYjBQLxThauYzZBaUwd6cboESxdfa+ar+RSFexP3U7mNW19bh3OOGOwFBQUEwNjbu7DSJClCrYKC1i8yr6itL8fzSHgAMgMUC6lvvFU4XGck6ej2nKRP6n7rYcdDFjvPaaxpGPfBkf0PLaGFNVavHZjEZOBKXgw1jXSQ3YUKkoM3zFYsNrV6u0HrLGfWVpahIjhDruAwmC5qW/fDhp2/D2JjOV6SBWlUgbLzItOX55T0QVr1AV/cRYOmKFzU3XmRI50WlF4iVLS0SCVFXVoSyW+FNr2lb9m11n3qhCFH3FK/3OyH/1Nb5StPUEt2nh8DI9yNoWbQviZnOV+Sf1OrOgDgXmaqsG6hI+R9YXY1h5DsLVVmJYh278SKzAfSNszPKBXXIKa5sc7snh5ahJi/9lVcY6GI3ECajPmtz35yiSlQI6iRapY0QSRM3KO4IOl+Rf1Kbs6E4FxlhTRWK+N8DAIyHfwKmdvvW10rqIiMSiSASiSAUCtv9X0f3U5TjFNZqQQSn9v+lMRgAkwWIkQ8rApBdVAGXHgbtH4cQGRA3KO4MCorJq9Tmp+BhUQXaukyURB9C/YsC6DjzoOM4qN1jiAC4DPKFqDi3UxdOVVvgwWAwwGAwwGQy2/yP1c0e2u9+3uYxTUYGQlhdjroXz1B+83cIHqeiKiMOBWVFsPhoW5v714ixmoQQeRHnfNVZFBSTV6lNMNDWyb+2KBdliRfA1O4K43fmd3ickaPGwJxV2eoFT9wLozT2l/W+jYGAuFLySjF657U2t9M0/7tLpI7TYDzaMQ2iuhrU5GegtvgxNIzfan1/tlqlyxAlI6tglYJi0khtgoG2Tv715c8BkRDC6nI82hnQ7DZ5exZCw9wGPT7e2eJxPl20kCLtTrA20QUDaPFbkbBWAKaGVjPv/B1wCKvLWx2D8XIcQhSVrIJVCopJI7UJBtq6yEgCXWQ6T1eLDUtjHTxs4Xlp/sEgaPZwgnbPPmDpm0FYWYqyxAtNBVcYbK1mC0O9ytJEh56TEoVG5ysia2pzRmzrIsM26gGjoXPfeL30z+NN3zT1B0+ChmnLZYfpIiMZfk7mOHz9YbOZ1MKaalQkR7S4ptrI/2MwtVquBMliMuDnaC6xuRIiDW2drwBAWFvdVBit5mlW0+t1LwpQkdbwqE3LwhFsg+Z/3ul8RV6lVj8JrV1k2Pqm0Oe898brL+LPAy+Dga6u/i1+66SLjORM97TEgdjsZt/T9xyPqsy/UPssF/WVpQBEYHU1gdZbztDr/y9o93Jt9dj1QhFmDKI+EkTxtXa+AgBhRSmenQt543VBzm0Ichp6GZiMWoKubsPe2IbOV+Sf1CoYaO0i01l0kZEch2568LY3bbY3gb7Hu9D3eLdDx23sTUBVIokyoPMVkSW1a1TUUgOczqAGOJLXnoZS4qKGUkTZ0PmKyIrapZJuGt8XbDFKErcHm8nApvGtl8El7dPLWAdfSrh/wMaxLhQIEKVC5ysiK2oXDNBFRnlM4Vhi+XBHiRxrxXAnTObQbVGiXOh8RWRF7YIBgC4yyiTQzwEhE/pCi80Uq8nUq1hMBrTYTIRO6ItFfvZSmiEh0kXnKyILapcz8KoT8TlY/0sK6oSidj2TYzEZYDMZ2DjWhX6xZCS3uBJrfr6Nq5nPWmxv3KjxfW97U2wa35e+BRGVQOcrIk1qHQwAdJFRNhlPy3D0eg6i7hUgp6jytaIsDDSsnfZzNMeMQZa0aoCoHDpfEWlR+2CgEV1klE+FoA7ZRRWoqRNCk82EtYkuFVEhaoHOV0TSKBhoBl1kCCHKgs5XRBIoGCCEEELUnFquJiCEEELI3ygYIIQQQtQcBQOEEEKImqNggBBCCFFzFAwQQgghao6CAUIIIUTNUTBACCGEqDkKBgghhBA1R8EAIYQQouYoGCCEEELUHAUDhBBCiJqjYIAQQghRcxQMEEIIIWqOggFCCCFEzVEwQAghhKg5CgYIIYQQNUfBACGEEKLmKBgghBBC1BwFA4QQQoiao2CAEEIIUXMUDBBCCCFqjoIBQgghRM1RMEAIIYSoOQoGCCGEEDVHwQAhhBCi5igYIIQQQtQcBQOEEEKImvt/jPg2O8y1UkQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = nx.petersen_graph()\n",
    "subax1 = plt.subplot(121)\n",
    "nx.draw(G, with_labels=True, font_weight='bold')\n",
    "subax2 = plt.subplot(122)\n",
    "nx.draw_shell(G, nlist=[range(5, 10), range(5)], with_labels=True, font_weight='bold')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d528e97f",
   "metadata": {},
   "source": [
    "when drawing to an interactive display.  Note that you may need to issue a\n",
    "Matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a261f16e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.636566Z",
     "iopub.status.busy": "2023-02-26T01:59:53.636122Z",
     "iopub.status.idle": "2023-02-26T01:59:53.639293Z",
     "shell.execute_reply": "2023-02-26T01:59:53.638784Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01288888",
   "metadata": {},
   "source": [
    "command if you are not using matplotlib in interactive mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "64936191",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.641819Z",
     "iopub.status.busy": "2023-02-26T01:59:53.641404Z",
     "iopub.status.idle": "2023-02-26T01:59:53.984715Z",
     "shell.execute_reply": "2023-02-26T01:59:53.983950Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options = {\n",
    "    'node_color': 'black',\n",
    "    'node_size': 100,\n",
    "    'width': 3,\n",
    "}\n",
    "subax1 = plt.subplot(221)\n",
    "nx.draw_random(G, **options)\n",
    "subax2 = plt.subplot(222)\n",
    "nx.draw_circular(G, **options)\n",
    "subax3 = plt.subplot(223)\n",
    "nx.draw_spectral(G, **options)\n",
    "subax4 = plt.subplot(224)\n",
    "nx.draw_shell(G, nlist=[range(5,10), range(5)], **options)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0091f94a",
   "metadata": {},
   "source": [
    "You can find additional options via `draw_networkx()` and\n",
    "layouts via the `layout module`.\n",
    "You can use multiple shells with `draw_shell()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "52b43d16",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:53.987815Z",
     "iopub.status.busy": "2023-02-26T01:59:53.987362Z",
     "iopub.status.idle": "2023-02-26T01:59:54.112065Z",
     "shell.execute_reply": "2023-02-26T01:59:54.111405Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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h5MiR8Pb2hqurqwYjVI+8vDzcuHGDV4v55s2bYh2rcuXKvOmKmjdvDiMjIzVHTAgRAyWUhGih5ORk9OrVC9euXeOVOzg44MyZM2jSpIlIkZH8UlJSsGPHDqxfvx7x8fEq923bti3mzp2L4cOH62x/Q8YYYmNjedMV3b9/v1jHsrS0lDeTd+rUCe3atYONjY2aIyaEaAIllIRomcTERLi7u+PmzZu88kqVKiE0NBQNGzYUJzCikkwmw7Fjx+Dr64vQ0FCV+zo6OmLWrFmYMWMGKlWqpKEIS09ycjLCwsLkCWZERARycnKKfBwDAwM0adKEV4sp5mTyhJDCo4SSEC3y9u1b9OzZE3fu3OGVV65cGWfPnkW9evVEiowUxZ07d+Dn54c///wT2dnZSvczMTHBqFGj4O3tjdatW2swwtKVk5OD69ev85rJExMTi3Ws6tWr86YratKkCQwNDdUcMSGkpCihJERLvH79Gm5uboLmw2rVqiE0NBQuLi4iRUaKKykpCdu3b8f69evx7Nkzlfu2b98ec+fOxbBhw2BsbKyhCDWDMYZHjx7xJl2Piooq1rGsra3Rrl07eS2mq6srrKys1BwxIaSoKKEkRAu8fPkSPXr0EHzJ1qhRA2fPnkXt2rVFioyog1QqxZEjR+Dr64sLFy6o3LdKlSqYPXs2pk+fDgcHBw1FqHkJCQnyZvKLFy8iMjISeXl5RT6OoaEhmjdvLq/F7NixI6pWrVoKERNCVKGEkhCRPX/+HD169BAs9+fk5ITQ0FDUqlVLnMBIqbh58yb8/Pywd+9elf0MTU1NMXbsWHh5eaFFixYajFAcWVlZiIyMlNdghoWFITk5uVjHqlWrFm+6okaNGsHAwEDNERNCPkUJJSEievr0Kbp3747Y2FheubOzM0JDQ2lAQhmWmJiIbdu2YcOGDXjx4oXKfTt37gxvb28MGTJEb6bZ4TgODx8+5K3qU9Ck8sqUK1cOHTp0kNdgtm3bFhYWFmqOmBD9RgklISKJj49H9+7dBVPNuLi44OzZs9Rspyfy8vIQGBgIX19fXLp0SeW+1atXx+zZszFt2jTY29trKELt8fr1a4SFhckH+ly/fh1SqbTIxzEyMkLLli15tZhlYbQ9IWKihJIQEcTExKBHjx54+vQpr7x+/foIDQ1F5cqVRYqMiOnatWvw8/PDvn37kJubq3Q/MzMzjBs3Dl5eXmjatKkGI9QumZmZiIiI4DWTv3v3rljHcnZ25k1XVL9+fWomJ6QIKKEkRMOio6PRvXt3QTNno0aNcObMGaopIXjz5g22bt2KTZs24dWrVyr37datG7y9vTFo0CC9n06H4zjcu3ePN11RQZPNK2NnZydvJu/UqRNat24NMzMz9QZMSBlCCSUhGvTw4UP06NFDkCQ0bdoUISEhZXpULym63Nxc+Pv7w9fXF+Hh4Sr3rVmzJjw9PTFlyhSUL19eQxFqvxcvXvCmK7p58yZkMlmRj2NiYoJWrVrJazE7dOhAn1dCPkEJJSEacu/ePbi5uQnWQW7evDlCQkL0sk8cKbyIiAj4+fnhwIEDKqfXsbCwwPjx4+Hl5YVGjRppMELdkJ6ejitXrshrMS9fvoz09PRiHatevXq8SdddXFwgkUjUHDEhuoESSkI04M6dO3Bzc0NCQgKvvFWrVjh16hTs7OxEiozomlevXmHLli3YtGkT3r59q3JfNzc3eHt7o3///nrfHK6MTCbDnTt35E3kFy9exPPnz4t1LAcHB3To0EFei9myZUuYmpqqOWJCtBMllISUsps3b6Jnz55ISkrilbu6uiI4OBi2trbiBEZ0Wk5ODv755x/4+Pjg2rVrKvetXbs2PD09MWnSJHq/FcLTp0950xXdvn0bxfmqNDU1RZs2bXjN5PTjkZRVlFASUoquXbsGd3d3pKSk8Mo7dOiAEydOwMbGRqTISFnBGEN4eDh8fX1x6NAhldPoWFpaYsKECfDy8kL9+vU1GKVue//+PcLDw+W1mOHh4cjMzCzWsRo2bMibrqh27drUTE7KBEooCSklERER6NWrl2Aak86dOyMoKAjW1tYiRUbKqhcvXmDz5s3YsmWLoHtFfr1794a3tzf69OlD0+MUUV5eHm7dusWrxSxoNL4ylSpV4iWYLVq0KHNruRP9QAklIaXg8uXL6NOnD96/f88r79atG44dOwZLS0uRIiP6IDs7G/v374evry9u3Lihct86derAy8sLEydOpBrzYmKMIT4+njdd0b1794rVTG5ubg5XV1d5ktm+fXuUK1euFKImRL0ooSREzS5evIi+ffsKRo727NkTR44coSXfiMYwxnDp0iX4+voiICBA5XQ5VlZWmDRpEry8vODi4qLBKMumlJQUXL58WV6LeeXKFWRnZxf5OBKJBI0bN+bVYtasWZOayYnWoYSSEDU6f/48+vfvj4yMDF55nz59EBAQAHNzc5EiI/ru6dOn2LRpE7Zu3Yrk5GSV+/br1w/e3t5wd3en5nA1yc3NxY0bN3i1mAWN0lemSpUqvFV9mjVrpjdrvBPtRQklIWpy5swZDBw4EFlZWbzy/v3749ChQ7TKBtEKWVlZ+Pvvv+Hr64vbt2+r3LdevXrw8vLChAkTYGVlpaEI9QNjDDExMfLk8tKlS3jw4EGxjmVpaYl27drJazHbtWtHfbSJxlFCSYganDp1CoMHDxY0aQ0ePBgHDhygueiIKBhjSEpKQnp6OqysrGBvby9vKmWM4cKFC/D19cXhw4fBcZzS49jY2GDKlCmYM2cOnJ2dNRW+3klKSkJYWJi8FvPq1asq13RXxsDAAE2bNuXVYlavXr0UIibk/1FCSUgJHT9+HMOGDUNOTg6vfNiwYdi3bx9MTExEiozoq9TUVOzevRt+fn6IiYmRlzs7O8trHD+djzI+Ph4bN27Etm3bkJqaqvS4EokEAwYMgLe3N9zc3KgfXynLycnBtWvXeLWY+eezLawaNWrwVvVp3LgxTXZP1IoSSkJK4OjRoxg+fLigFmHkyJH466+/aPoPonEnT56Eh4eHfJ7ETy/xHxNACwsL+Pv7o3fv3rz7ZmRkYO/evfD19cW9e/dUPk7Dhg3h7e2NcePG0awFGsIYQ1RUFG+6oujo6GIdy8bGBu3atZPXYrq6utLrSEqEEkpCiikwMBAjR44UTCQ9duxY7N69mzrJE407efIk+vfvD8aYyiZsAwMDSCQSBAUFCZJK4EPiEhoaCl9fXxw9elTl9De2traYOnUq5syZg1q1aqnjNEgRvH37FmFhYfJazGvXrqlc610ZQ0NDtGjRQl6L2bFjR1SpUqUUIiZlFSWUhBTDwYMHMWbMGME0LJ9//jl27NhBTUlE41JTU1GtWjVkZWWpTCY/MjAwgLm5OZ4/f65yOcbY2Fhs2LAB27dvF0zSn/94gwYNwty5c9G1a1dqDhdJVlYWrl69Kq/FvHTpkspuDKo4OTnxpitq2LAhjfonSlFCSUgR7du3D+PHjxckk5MnT8bWrVspmSSi8PHxwfz584s0mbZEIsG6devg7e1d4L7p6en4888/4evri4cPH6rct0mTJvD29sbYsWNp3lWRcRyHBw8e8KYrio2NLdaxbG1t0aFDB3kNZtu2bWkqNCJHCSUhRfDXX39hwoQJghqgGTNmYOPGjfTrnWjc+/fvERUVhQEDBhR5XkOJRILatWsjOjq60DWKHMchJCQEvr6+CAoKUrmvnZ0dpk2bhtmzZ6NGjRpFio2UnlevXvFqMK9fv65y0ntljI2N0bJlS14tZsWKFUshYqILKKEkpJB27tyJKVOmCGqA5syZAz8/P2riI6VGKpUiLi4OUVFRePToEaKiouS3169fl/j4CQkJqFChQpHvFx0djfXr12Pnzp1IS0tTup+hoSGGDh0Kb29vdOrUiT4rWiYjIwMRERHyWszLly8Llo0trDp16vCmK6pfvz693nqCEkpCCmHbtm2YPn26oHzu3LlYu3YtXTBJiTHGkJiYKE8UP00cY2JiijXQorBq1KiBkSNHYtiwYXB1dS1yTfv79+/l0xQVNOq4efPm8Pb2xpgxY2iyfy0lk8lw79493nRFT548Kdax7O3t5c3knTp1QqtWreh1L6MooSSkAJs2bcLs2bMF5V988QVWr15NySQpkuzsbDx+/JhXy/gxeUxJSRE7PFSuXBmDBw/GsGHD0K1btyJNfcVxHE6ePAlfX18EBwer3LdChQqYPn06Zs+ejapVq5Y0bFLKnj9/zpuu6NatW4Ua/JWfiYkJWrduLa/F7NChQ7Fqx4n2oYSSEBX8/PwUDlhYvHgxVq1aRckkUYgxhhcvXvCSxo+JY3x8fJEGzhSGRCKBoaGhYAqrkrK1tcWAAQMwdOhQ9O7du0jzFEZFRcHPzw+7du0SrG3/KSMjI3h4eMDb2xvt27enz5SOSEtLw5UrV+S1mOHh4UhPTy/WserXr8+bdL1OnTr0PtBBlFASosSaNWuwcOFCQfl3332H5cuX0wWPIC0tTWG/xkePHsknFlcne3t71K1bF/Xq1ePdnJ2dsXnz5iKP8i4Kc3Nz9O7dG0OHDsXAgQNRvnz5Qt3v3bt32LlzJ/z8/AocXdyqVSt4e3tj1KhRtFypjpFKpbh9+zavFvPFixfFOpaDgwNvoE/Lli1pxTEdQAklIQr88ssv+PrrrwXly5cvx/fffy9CREQsUqkU8fHxChPHV69eqf3xTExMUKdOHdSrV0+QPNrb2yu9X3HnoTx27BhCQkIQEBCABw8eFCpGIyMjdOvWDUOHDsWQIUMKNQG2TCbD8ePH4evri5CQEJX7VqxYETNnzsTMmTNRuXLlQsVEtAtjDE+fPuVNV3Tnzp1i/eAxMzND27Zt5bWYHTp0KPQPGqI5lFASks+qVavw7bffCsp//PFHLF68WISIiCYoGxDz+PHjUhkQU6VKFXmi+GniWLNmzWKvslTYlXKAD83kwcHB6NWrl7wsKioKgYGBCAgIwNWrVwv9uO3atcPQoUMxdOhQuLi4FLj//fv34efnhz179qisyTUyMsLIkSPh7e0NV1fXQsdDtNO7d+8QHh7OaybPysoq1rEaNWrEq8V0cnKiViORUUJJyP8wxrBixQosW7ZMsO3XX3/FF198ofmgiFrl5OQoHRCTnJys9seztLQU1DLWrVsXdevWhbW1tdofD1C9lvenbG1t8fLlS6UTUz9//hyHDx9GYGAgzp8/X+h5Chs3boyhQ4di2LBhaNasmcov+ZSUFOzYsQPr169HfHy8yuO2bdsWc+fOxfDhw6n5s4zIy8vDzZs3ebWYxZ0Gy9HRkTddUfPmzYs0oIyUHCWUhODDl+53332HVatWCbatXbsW8+bN03xQpFgYY3j58qVgQExUVBSePHlSrJGpqkgkEtSqVUvQr7Fu3bqoWrWqKLUmqamp2LNnD3x9fRETE6N0Px8fn0KtkpOUlISjR48iMDAQJ0+eRE5OTqHiqFWrlrzmskOHDkpXkZLJZDh69Ch8fX1x9uxZlcd0dHTErFmzMGPGDFSqVKlQcRDdwBhDXFwcb7qie/fuFetYFhYWcHV1ldditmvXDuXKlVN7vElJSUhPT4eVlRXs7e31upaUEkqi9xhj+Prrr7F69WrBNj8/P3h6eooQFSlIWloaHj16pHBAjKpRxcVlZ2ensF+js7Oz1s6rxxhDcnIy0tLSYG1tjTFjxuD06dPy7VWqVEFMTEyR4k9PT0dwcDACAwNx7NixQk+AXbFiRQwePBhDhw5Fjx49lA66uXPnDvz8/PDnn38iOztb6fFMTEwwevRoeHt7o1WrVoWOn+iW5ORkXL58WV6LefXqVZXvC2UkEgmaNGnCq8WsUaNGsRLA1NRU+byrn/5gc3Z2hpeXFyZMmABbW9siH1fXUUJJ9BpjDF988QXWrFkj2LZ582bMmDFDhKjIRzKZTOmAmJcvX6r98YyNjZUOiCkLc+VdunQJnTp14pVt3LgRs2bNKtbxcnNzERoaisDAQBw5cgRv3rwp1P1sbGzQv39/DB06FH379oWVlZVgn6SkJPzxxx/YsGEDnj17pvJ4HTp0gLe3N4YNG0bNnGVcbm4url+/zmsmT0hIKNaxqlWrxpuuqEmTJgX2X1bVpeRjcmphYQF/f3/07t27WHHpKkooid5ijGHevHnw9fXllUskEmzbtg1TpkwRKTLNE7vpJikpSWG/xsePHyM3N1ftj1e5cmWFA2Jq1apV7AExusLNzQ2hoaHyv6tXr47Hjx+XuF+iTCbD5cuXERgYiMDAQMTFxRXqfqampujVq5d8OqL8ibtUKsWRI0fg6+uLCxcuqDxWlSpVMHv2bEyfPh0ODg7FPheiOxhjePz4Ma+Z/OHDh8U6lpWVFdq1ayevxXR1deX1dS7soDcDAwNIJBIEBQXpVVJJCSXRSxzHwdPTE5s2beKVSyQS7Ny5ExMmTBApMs3SZNNNTk4OYmJiFCaOSUlJanmMT1lYWCgdEGNjY6P2x9MV586dQ/fu3Xll27Ztw9SpU9X2GIwx3L59GwEBAQgMDMSdO3cKdT9DQ0N06dJFPh1R9erVedtv3rwJPz8/7N27V2U/TlNTU4wdOxbe3t5o3rx5SU6F6KDExESEhYXJazEjIyOL9cPUwMAAzZs3lw/y8fLyQnZ2dpGm5Xr+/LneNH9TQkn0DsdxmDFjBv744w9euYGBAfbs2YPPPvtMpMg0qzSabj4OiMnfPB0VFYX4+PhSGRBTs2ZNwYCYevXqoUqVKkVek1ofMMbQtWtX/Pfff/IyJycnREVFlVpz8ePHj+U1l5cvXy70/dq0aSMf1FO/fn15eUJCArZt24aNGzcWOHl2586d4e3tjSFDhpT52meiWHZ2Nq5du8arxSyNWR3yk0gkWLduXaEGvpUFlFASvSKTyTB16lTs2rWLV25oaIi9e/di1KhR4gSmYSVtuklPT1c6IKa4y6+pUr58eYX9GuvUqaO1A2K0WUhICNzd3XllO3fuxMSJE0v9sV++fIkjR44gMDAQZ8+eLfRykQ0aNJAnl61atYJEIkFeXh4CAwPh4+ODsLAwlfevXr065syZg6lTp6qcIJ6UfRzHISoqireqz+PHj9X+OBKJBLVr10Z0dLRejP6mhJLoDZlMhkmTJuHPP//klRsZGWH//v3w8PAQKTLNKuqKKhKJBMbGxhg3bpx8gExxl1RTxdjYGM7OzkoHxOjDBVlTGGPo0KEDwsPD5WUuLi64f/++RmvxUlJScOzYMQQGBiI4OLjQk1zXqFEDQ4YMwdChQ9GpUycYGRkhMjISfn5+2L9/v8rmTTMzM4wbNw5eXl5o2rSpuk6F6Lg3b94gLCxMXot57dq1Qv/YKUhiYqJe/IihhJLoBalUivHjx2P//v28cmNjYxw8eBCDBw8WKTLN8/HxKdU1nwvi6Ogo6NdYr149ODk5UZOkBp04cQL9+vXjlf3111+idfnIzMzEyZMnERgYiKNHjyI1NbVQ96tQoQIGDRqEoUOHomfPnnj37h22bt2KjRs3FjhJdrdu3eDt7Y1BgwYpnSOT6KfMzExcvXoVly5dwunTp3Hu3LliHysuLg61atVSW2zaihJKUubl5eVh7NixOHToEK/cxMQE/v7+GDBggEiRaR5jDC4uLoiNjS3VhNLc3FzpgBh1Ty5MiocxhrZt2yIyMlJe1qBBA9y5c0f05CovLw/nz59HQEAADh8+XOg1062srNCvXz95cnn69Gn4+PjgypUrKu9Xs2ZNeHp6YsqUKbRGNBFITEws0awBVENJSBmQm5uL0aNHIzAwkFduamqKw4cPo0+fPiJFJo6SXhg/9XFATP7EsV69eqhatSoNiNEB//77r6B2/sCBAxg5cqRIEQlxHIeIiAj5GuOF7etmYmKCnj17YujQoahatSr27t2Lf/75R+W67BYWFhg/fjy8vb3RsGFDdZ0C0XHF/SFOfSgJKSNycnIwYsQIHD16lFduZmaGf//9VzAoQR/Ex8fDycmp2PdfuHAh2rVrJx8Qo2wdaKIbGGNo0aIFbt26JS9r3Lgxbt26pZU/CBhjuHfvnjy5vHnzZqHuZ2BggE6dOqFHjx5ITk7G/v378fbtW5X36dmzJ7y9vdGvXz/Ra2yJ+IrTVYhGeRNSBmRnZ8PDwwPHjx/nlVtYWODo0aPo0aOHSJGJKy4uDrVr1y72/fWl6Uaf+Pv7Y/jw4byygIAADB06VKSICi8uLg6HDx9GQEAALl26VOgv+2bNmqFOnTp48OAB7t+/r3Lf2rVrw9PTE5MmTdKb+QSJUFEHM9I8lISUAVlZWRgyZAhOnTrFK7e0tMTx48fRpUsXkSITD2MM/v7+8Pb2LnR/tE/pW9ONPuE4Dk2bNsW9e/fkZc2bN8f169d16rV+8+YN/v33XwQGBiIkJERl0/anqlWrBmtrazx69AgymUzpfpaWlpgwYQK8vLx4c2IS/fFxujWO41T+ePk43drx48fRq1cvDUYoMkZIGZKRkcF69OjBAPBu1tbW7OLFi2KHJ4rY2FjWr18/wXNSlJtEImE+Pj5inwopJfv37xe85v/++6/YYRVbamoq+/vvv9mIESOYpaVlod/nVlZWzMzMrMD9evfuzYKCgphMJhP7VImGBQcHM0NDQ6XXSYlEwiwtLdnJkyfFDlXjqIaSlBnp6ekYMGAAzp8/zyu3sbHByZMn0a5dO5EiE0dubi5+//13rFixAtnZ2cU+jj423egbmUyGRo0aISoqSl7Wpk0bXLlyRadqKRXJyspCSEgIAgMDceTIkUKvkGJoaKiyxhL4MHfnxyVK9Xk5T32SkpICBwcHhe+NWrVqYf78+ZgwYYJezmZBCSUpE9LS0tCvXz9cvHiRV25ra4tTp06hTZs2IkUmjgsXLmDmzJl48OCByv0kEgk13RAAH+agHD9+PK/sxIkTZWomBKlUiv/++0++DOTz58/Vclxra2tMmjQJnp6ecHFxUcsxiXbavXu30hWl3rx5g4oVK2o2IC1CCSXRee/evUOfPn14q34AgJ2dHU6fPo2WLVuKFJnmJSYm4ssvv8TOnTtV7le1alV8+eWXWLJkSYFreQcEBFAyqQekUikaNGjAm5anffv2uHTpks7XUirCGENkZKQ8uXz48KFajtuvXz94e3vD3d1dK0fKk5IZOHAgjh07pnDb27dv1TYtm04SrbGdEDVITk5mbdq0EfRlqVChArt586bY4WmMTCZj27dvZ3Z2dgX2/+rWrRt78+YNY4yxlJQU5uPjw5ydnXn7ODs7Mx8fH5aamirymRFN2rFjh+D9EhISInZYGnH//n22atUq1rp16xL1N/54q1+/PtuwYQNLS0sT+9SImrx7946ZmJgofc3fvn0rdoiiohpKorOSk5Ph7u6O69ev88orVqyIM2fOoHHjxiJFpll3797FrFmzBM39iixYsAC//PKLYIlDxhiSk5ORlpYGa2tr2NnZlclaKaJaXl4e6tati/j4eHlZly5dBP2Sy7qnT5/i8OHDCAwMxIULFwo1TYwyNjY2mDJlCjw9PUs0ZRcR399//61yaVJ9r6GkhJLopMTERPTs2ZM3ITPwYZ3o0NBQNGjQQKTINCcjIwMrV67E77//DqlUqnJfc3NzbN++HWPGjNFQdERXbdu2DdOnT+eVnTt3Dl27dhUpInElJCTg6NGjCAwMxOnTp5GTk1Os40gkEgwcOBDe3t7o0aOHyh9sjDEkJSUhPT0dVlZWsLe3px94WmDYsGGCVdc+RQklJZREx7x9+xY9e/bEnTt3eOVVqlRBaGgo6tWrJ1JkmnPs2DF4enriyZMnBe5bu3ZtBAYGomnTphqIjOi63Nxc1KlTB8+ePZOXubm5ISQkRMSotENaWhpOnDiBwMBABAUFIS0trVjHadiwIby9vTFu3DhYWlrKy1NTU7F79274+fkhJiZGXu7s7CwfTU4zLYgjPT0dDg4OKmfM0PeEkvpQEp3y6tUr1rBhQ0HflWrVqrHo6Gixwyt1z549Y0OHDi10P64+ffqwpKQkscMmOmbDhg2C99KlS5fEDkurZGdns6CgIDZ16lTm4OBQrH6Wtra27IsvvmBxcXEsODiYWVpayucy/HS/T+c3DA4OFvvU9dI///zDe00UzUVJfSgZ1VAS3fDy5Uv06NGDN1ceANSoUQNnz54t0/2TpFIp/Pz88P333yM9Pb1Q9/nmm2+wfPlyWoeYFFl2djZq167NW1WpT58+OHHihIhRaS+ZTIawsDAEBAQgMDCwUC0HihR2Gq+goCD07t27uOGSYhg9ejQOHDgg/7tr166CvsX6XkNJCSXRCc+fP0ePHj0QHR3NK3dyckJoaChq1aolTmAacOXKFcyYMUPQX1QZa2tr7NmzB0OGDCndwEiZ5uPjg3nz5vHKrly5grZt24oTkI5gjOHmzZsIDAxEQEAAb0lLdaCFBjQvKysLDg4OyMjIkJf9+uuvWLRoEW8/fU8oaZIsovWePHmCrl27CpJJZ2dnnD9/vswmkykpKZg1axbat29f6GSyfv36iIiIoGSSlNi0adNQqVIlXtnKlStFikZ3SCQStGjRAitWrMDdu3fx6NEj/PLLL3B1dVXL8TmOQ2ZmJvbs2aOW45GCnTp1ipdMGhgYoG/fviJGpJ0ooSRaLS4uDl27dkVsbCyvvG7dujh//jyqV68uUmSlhzGGvXv3on79+ti8ebPKJrBPDRs2DBEREahfv34pR0j0gYWFBb744gte2bFjx3Djxg2RItJNLi4u+PLLLxEeHo7nz59jw4YNcHNzK/Gk576+voW+NpCSOXToEO/vzp076/WKOMpQQkm0VkxMDLp27Sroj9SgQQOcO3cOVatWFSmy0vPo0SO4u7tj3LhxePv2rWC7oi8hiUSCH3/8EYcOHYK1tbUmwiR6YubMmahQoQKvjGopi69q1aqYPXs2QkJCkJCQgPXr1xfrOIwxxMTEFHpdclJ8OTk5OHr0KK9s+PDhIkWj3SihJFrp0aNH6Nq1K2/qEgBo1KgRzp49i8qVK4sUWenIzs7GsmXL0KRJE5w5c0aw3djYGAAEEyyXL18eJ06cwOLFi2meOqJ2VlZWWLhwIa8sMDAQt2/fFimissPOzg79+/cv0TGKO20RKbwzZ87g3bt3vLJhw4aJFI12o4SSaJ2HDx+iW7duePHiBa+8adOmOHv2rKBfl647ffo0mjRpguXLlyM3N1ewvWLFisjLyxOUN2vWDJGRkTTak5SqOXPmoHz58ryyVatWiRRN2WJlZVWi+1OLROnL39zdoUMHVKlSRaRotBsllESr3Lt3D127duVNVwIALVq0QGhoaJkaQff69WuMHTsWvXr1wuPHjwXbHR0d4ejoqLDpe+zYsQgLCyvTUyUR7WBtbY358+fzyg4ePIj79++LFFHZYW9vD2dn5yK3LkgkEjg7O8POzq6UIiPAh6VIjxw5wiuj5m7lKKEkWuP27dvo1q2bIIFq3bo1zpw5A3t7e5EiUy+ZTIZNmzahfv362Ldvn2C7oaEhBgwYgHfv3uH169eCbWvXrsVff/0FCwsLTYVM9JyXlxfKlSsn/5sxRrWUaiCRSODl5VWs+3p7e1M3l1J27tw5QT9Vau5WjhJKohVu3ryJHj16IDExkVfu6uqK06dPC5rcdNWNGzfQoUMHzJ49W9AvBwDatWuHzz77DMeOHUNWVhZvW8WKFXHmzBnMmzePvkiIRtna2sLb25tXtn//fjx69EikiMqOCRMmwMLCosijvgcMGFBKEZGP/P39eX+3adMGNWvWFCka7UcJJRHdtWvX0KNHDyQlJfHKO3TogFOnTpWJyXvT0tIwf/58tG7dGhEREYLttra2+O2332BmZqZwfrm2bdvi2rVr6Nq1qybCJURg3rx5vD5/HMfhxx9/FDGissHW1hb+/v6QSCSFTioZY5g+fTqkUmkpR6e/ZDIZAgMDeWUeHh4iRaMbKKEkorpy5Qrc3NyQkpLCK+/cuTOCg4NhY2MjUmTqwRiDv78/GjRogHXr1glGaQPA+PHjceDAAfj4+ODcuXOC7VOnTsWFCxdQrVo1DURMiGJ2dnaC5tm//vpLMEcsKbrevXsjKCgI5ubmkEgkghYIRS0SZ86cwZdffqmpEPXOxYsXBd2vKKFUjRJKIpqwsDC4u7sLmn67d++OEydO6PwIxri4OAwYMADDhw8XjFgHgHr16iE0NBTdu3fHoEGDBFMkmZiYYOvWrdi2bRtMTU01FTYhSs2fP5/Xd1cmk+Gnn34SMaKyo3fv3nj+/DnWrVsnGGxXu3ZtrFixQjCZ9tq1a2nFnFKSf3R3s2bNUKdOHZGi0RGMEBFcuHCBWVlZMQC8m7u7O8vIyBA7vBLJyclhP/74IzM3NxecHwBmamrKVqxYwd6/f89mzZqlcJ+qVauyy5cvi30qhAh88cUXvPeqkZERi4+PFzusMoXjOJaYmMji4uJYYmIi4ziOMcZYWFgYMzExEVxPIiIiRI64bJHJZKxKlSq853nlypW8fd6+fSu4br99+1akiLUDJZRE486ePcssLCwEH8Y+ffqwzMxMscMrkQsXLrCGDRsqTBIBsF69erHo6Gj24sUL1r59e4X7dO7cmb1+/VrsUyFEoVevXjEzMzPee3bWrFlih6U3tm/frvAH6KtXr8QOrcy4dOmS4Dl+8OABbx9KKIWoyZtoVEhICPr164fMzExeef/+/REYGAhzc3ORIiuZxMRETJ48GV26dFE4P5+joyP279+P4OBgvH79Gq1atcLly5cF+82dOxdnzpwpc5O3k7LD0dERM2bM4JVt374dz58/Fyki/TJ58mR4enryyl68eAEPDw/k5OSIFFXZkr+5u2HDhqhfv75I0egQsTNaoj+Cg4MFNRsA2ODBg1lOTo7Y4RWLTCZj27dvZ3Z2dgprGyUSCfP09GSpqamM4zi2fv16ZmRkJNjP3Nyc/fnnn2KfDiGF8uLFC2Zqasp7D3t5eYkdlt7Izc1l3bp1E1xHpk2bJm8eJ8XDcRyrUaMG73n9/vvvBftRDaUQJZREI4KCggR9fwAwDw8PlpubK3Z4xXL37l3WuXNnpc3bLVu2ZFevXmWMMZaZmckmTJigcL9atWqxGzduiHsyhBTR7Nmzee9jMzMz9vLlS7HD0htv375lNWvWFFxPNm7cKHZoOi0iIkLwnN66dUuwHyWUQtTkTUrdv//+iyFDhgjWqR41ahT27dsHY2NjkSIrnszMTCxevBjNmzfHf//9J9hubW0NHx8fREREoHXr1njy5Ak6deqE3bt3C/bt1asXIiMj0bx5cw1EToj6fPXVV7zPbnZ2Nn777TcRI9IvDg4OOHz4sKCbkLe3Ny5cuCBSVLov/2TmLi4uaNKkiUjR6BZKKEmpCggIgIeHB/Ly8njlY8eOxV9//aVzyWRQUBAaNWqEn3/+WeGkwiNGjMCDBw/g7e0NQ0NDnDlzBq1atcL169cF+3799dc4fvx4mVlSkuiXGjVqYNKkSbyyTZs2KVx7npSO5s2bY+fOnbwyqVSK4cOH4+nTpyJFpbsYY4L+kx4eHrQyWWGJXUVKyq4DBw4wQ0NDQbPAhAkTmFQqFTu8Inn27BkbNmyY0uZtJycndvz4cfn+HMex1atXMwMDA8G+VlZW7NChQyKeDSHqERsbK/iMf/XVV2KHpXe+/vprwXWmRYsWOj8Fm6bdvHlT8DxGRkYq3JeavIUooSSlYu/evQqTqSlTpjCZTCZ2eIWWl5fH1qxZo3DOTADM2NiYffPNN7wLd1paGhsxYoTC/evWrcvu3bsn4hkRol6TJk3ivcctLS1ZQkKC2GHpFalUyvr27Su43owZM4YG6RTBt99+K+jfruz5o4RSiBJKonZ79uxRmEzOmDFDp5LJ8PBw1rx5c6W1kl27dmX379/n3efRo0esUaNGCvcfNGgQS01NFelsCCkd0dHRgs/7N998I3ZYeiclJYXVrVtXcN1ZvXq12KHpjPr16/Oeu4ULFyrdlxJKIUooiVpt376dSSQSwQdtzpw5OvNLOSUlhc2aNUvheQBgFSpUYLt27RKcz9GjR1m5cuUE+0skErZy5UqdSqYJKYpx48bx3vM2NjYsOTlZ7LD0zoMHD5iNjQ3vtTAwMGAnTpwQOzStd+/ePcG1W9VqZZRQClFCSdRmy5YtChOwefPm6UQyyXEc27t3L6tUqZLSWsmpU6eyxMRE3v1kMhlbtmyZwv1tbW1ZUFCQSGdEiGY8ePBA8ANs2bJlYoell44ePSp4LcqVK8cePXokdmhabfny5bznrGrVqiorASihFKKEkqjFhg0bFCZUixYt0olkMioqirm5uSlNJBs3bswuXrwouF9qaiobOHCgwvs0adKERUdHi3A2hGje6NGjBT+m3r17J3ZYeumHH34QXI8aNGhAr4cKTZs25T1f3t7eKvenhFKIEkpSYj4+PgoTqsWLF2t9MpmVlcWWLl2qcNJ1AMzCwoKtXr1a4eTrd+/eZS4uLgrvN2rUKJaeni7CGREijjt37gg+B6tWrRI7LL3EcZzCgYGDBg2irjcKPHr0SPBcnT9/XuV9KKEUooSSlMhvv/2mMKH6/vvvtT6ZPH36tNKEEAAbOHAgi4+PV3jff/75h1laWgruY2BgwH777TetP3dCSoOHhwfv82Bvb8/S0tLEDksvpaenC2rdPl6bCd9PP/3Ee44qVapU4NR2lFAKUUJJii3/h/DjbcWKFWKHptKrV6/Y2LFjlSaS1apVY4GBgQqTwry8PPbll18qvF+FChXYmTNnRDgjQrTDjRs3BJ8LGmUsntjYWGZvby94Tfz9/cUOTau0atWK9/zMnDmzwPtQQilECSUplpUrVypMqn766SexQ1NKKpWyjRs3KhyJDYAZGhqyhQsXKq1RSUhIYD179lR439atW7MnT55o+IwI0T6DBg3ifTYcHBxogm0RnTlzRjD5vKWlJbt9+7bYoWmFuLg4wfU8JCSkwPtRQilECSUpEo7j2NKlSxUmVb/++qvY4Sl1/fp11rZtW6W1ku3atWM3b95Uev9r166xmjVrKrzvpEmTWFZWlgbPhhDtdfXqVcFnZM2aNWKHpdfWrVsneE1q167NkpKSxA5NdPm7bdnb27O8vLwC70cJpRAllKTQOI5jS5YsUZhUrV27VuzwFHr//j2bP3++wonWgQ8jUTdv3qyyo/ru3buZmZmZ4L7GxsZs48aN1F+SkHzyr9ri6OjIMjMzxQ5Lb3EcxyZOnCi4hvXs2bNQyVNZ1q5dO95zMmXKlELdjxJKIUooSaFwHMcWLVqkMClbv3692OEJcBzH/P39WdWqVZXWSo4bN469fv1a6TFyc3OZp6enwvtWrlyZXbp0SYNnRIjuCAsLE3xm/Pz8xA5Lr2VlZSlspVmwYIHYoYnm2bNnguejsJPAU0IpRAklKRDHcWz+/PkKE6stW7aIHZ5AbGws69+/v9JEsm7dugUOnnn16hXr1KmTwvt37NiRvXz5UkNnQ4hucnd3531uqlatyrKzs8UOS6+9ePGCOTo6Cq5pe/bsETs0UeSf8q5cuXIsJyenUPelhFLIAISowBjD3LlzsXbtWl65RCLB9u3bMX36dJEiE8rNzcXPP/+MRo0aISgoSLDd1NQUK1aswO3bt9GjRw+lx7l8+TJatWqFixcvCrbNmTMHoaGhqFy5slpjJ6Ss+e6773h/v3jxArt27RInGAIAqFKlCgICAmBiYsIrnzZtGq5evSpSVOLx9/fn/T148GDBc0OKQOyMlmgvmUzGZs6cKfgVJpFI2K5du8QOj+fChQusUaNGSmsl3d3dC1y1huM4tmnTJmZsbCy4v6mpqdadMyHarlu3brzPUY0aNQpdA0RKzx9//CG4xlWtWpW9evVK7NA05tWrV4IlKo8cOVLo+1MNpRAllEQhmUzGpk6dKvjAGBgYsL1794odnlxCQgKbPHmy0kTS0dGR7d+/v8CBM1lZWUqPU6NGDRYZGamhMyKk7AgNDRV8nv744w+xwyKMKewf3rFjR71J+Ddt2sQ7dysrqyLN1kEJpRAllERAKpUqHBFoaGjIDhw4IHZ4jLEPtYk7duxQOGnvx1rUOXPmsJSUlAKP9fTpU9amTRuFx3Fzc2MJCQmlf0KElEEcx7GOHTvyPlO1a9fW+5HF2iA3N1dQgwyATZs2TS9mrnBzc+Od9+jRo4t0f0oohSihJDx5eXls3Lhxgg+KkZERO3TokNjhMcY+rKHduXNnpbWSLVq0YBEREYU61tmzZ5mDg4PC4yxatIi++AgpoZMnTwo+W7t37xY7LMI+JEWK5tfduHGj2KGVqoSEBMFk70X9fqOEUogSSiKXl5fHRo8eLfiQGBsbs8OHD4sdHsvIyGBff/01MzIyUpgAWltbMx8fn0IlgRzHsTVr1gguKsCHVSS0pSaWEF3HcRxzdXXlfcbq1q1b4FrJRDNu3LjBzM3NBRUI58+fFzu0UpO/D6mFhUWRV3OihFKIRnkTAEBeXh5Gjx6N/fv388pNTEwQEBCAwYMHixTZB0FBQWjUqBF+/vlnSKVSwfYRI0bgwYMH8Pb2hpGRkcpjZWRk4LPPPsOCBQsgk8l42+rUqYPw8HCMHDlSrfEToi8YY0hMTER8fDwSExMBCEd8P3r0CP/8848Y4ZF8mjdvjp07d/LKpFIphg8fjqdPn4oUVek6dOgQ7+++ffvCwsJCpGjKDkooCXJzczFy5EjBFAqmpqY4cuQIBgwYIFJkwPPnz+Hh4YEBAwYgPj5esN3JyQlBQUH4559/ULVq1QKPFxMTgw4dOmDfvn2Cbf3798fVq1fRuHFjdYROiF5JTU2Fj48PXFxc4ODgACcnJzg4OMDFxQXR0dFo2rQpb/8ffvgBHMeJFC351KhRo/D111/zyhISEjB06FBkZmaKFFXpSElJwZkzZ3hlw4cPFymaMkbsKlIiruzsbDZw4EBB1b2ZmRk7ffq0aHHl5eWxtWvXMisrK4XN28bGxmzJkiVFaqY4fvw4s7W1VXi8pUuXqlx+kRCiXHBwMLO0tGQSiUQwFcvHMkXLlx48eFDs0Mn/SKVSwZKZANjYsWPL1CCd3bt3887P1NSUvX//vsjHoSZvIUoo9VhWVpbCC4iFhQULDQ0VLa4rV66w5s2bKx1006VLF3bv3j3efTiOYwkJCSwuLo4lJCTwLoAymYytXLlS8EUHgNnY2LCjR49q+hQJKTOCg4OZoaEhMzAwUPqZBaBwe9OmTemHnBZJSUlhdevWFbxOq1evFjs0tRk0aBDv3AYNGlSs41BCKUQJpZ7KyMgQLI2G/w1IEaszdkpKCps1a5bCxA8As7e3Z7t27eIliykpKWzdunXM2dmZt6+zszNbt24de/LkCRs8eLDC4zVs2JA9evRIlHMlpCxISUlhlpaWBSaTn9ZW5i8LDAwU+zTIJ+7fv8+sra0FPwaCg4PFDq3E3r9/z0xNTXnnVtwZByihFJIwxpjixnBSVmVkZGDQoEEIDQ3llVtbWyM4OBgdOnTQaDyMMezfvx/z58/HmzdvFO4zZcoU/PLLL7C3t5eXnTx5Eh4eHvI+Pp++lSUSCe/4+Q0fPhw7d+6ElZWVuk6DEJ3HGINMJoNUKuXd8vLyBGVSqRR79uzB77//rvAzVlgtW7ZEZGQk7zNLxHX06FEMHjyY97ra2tri6tWrqFOnjoiRlcz+/fsxZswY+d/GxsZ48+YNypcvX+RjJSQkoGLFiryyt2/fwsHBocRx6irVw2FJmZOeno7+/fvjwoULvHIbGxucOnUKrq6uGo0nOjoas2fPRkhIiMLtjRo1wubNm9GpUyde+cmTJ9G/f3+wD7Xsgvsp+4IzMDDATz/9hEWLFtEXGFFKUWKlLKnSxHZNPXb+WQ9Kg0Qi4X0+r1+/juPHj6N///6l/tikcAYOHIiVK1fi22+/lZelpqZi8ODBCA8Ph7W1tYjRFV/+0d09e/YsVjJJFKMaSj3y/v179OvXD5cuXeKV29ra4vTp02jdurXGYsnOzsYvv/yCn376CTk5OYLt5ubmWLZsGebPnw9jY2PettTUVFSrVg1ZWVlFGiVqa2uLf/75B+7u7iWOX1/kT6z0IanSVGJF/l/btm0RHh5OP/K0CGMMI0eOFCRhgwcPRkBAAAwMdGuSmIyMDDg4OCArK0te9scff2DKlCnFOh7VUApRDaWeePfuHfr06YPw8HBeuZ2dHUJCQtCiRQuNxRISEoLZs2cjOjpa4fYBAwbAz88PtWrVUrh99+7dyMzMLHIzm7e3d7GTyU8TK31JqiixIpoSERGB06dPo1evXmKHQv5HIpFg586diIqKwp07d+TlR44cwfLly7F8+XIRoyu64OBgXjJpaGgo+vzKZQ3VUOqBlJQU9OrVC5GRkbzyChUqICQkBM2aNdNIHK9fv8bChQvx999/K9xerVo1+Pr6YsiQIUprKhhjcHFxQWxsbJETSjMzMzRv3lxlQqUs6aLEihD1qlmzJp48eSL/u0OHDrh48SLVUmqZuLg4tG7dGsnJybxyf39/DBs2TKSoim7MmDG8hTvc3NyUdrUqDKqhFKKEsoxLSkqCu7s7bty4wSuvWLEizpw5o5FJvDmOw5YtW7B48WK8e/dOsN3Q0BBz587FsmXLCuybk5iYqNcfWKKdjIyMYGBgAENDQ0gkEnlS9LGP78cabplMplOTeVtbW6N8+fKws7ODvb097O3t4eDgAAcHB9jb2+OHH37A27dvi/TjTiKRoHbt2li8eDGmTp3K23bmzBn06NFD3adBSig0NBS9evXi/bC2tLREeHi4TiwEkZ2dDQcHB6Snp8vLNm3ahJkzZxb7mJRQClGTdxmWkJAAd3d33Lp1i1fu6OiI0NBQNGjQoNRjuHnzJmbOnIkrV64o3O7q6orNmzejefPmhTrepxcEol0MDAxgZGSk9GZsbMz7OyMjA48fPy7UsSUSCXr37g0nJ6dCH78o2w0NDZGTk4OMjAykpaXJb+/fv8f79+/x7t07pKamIiUlBampqUhOTkZycrK8CU0qFS4Hqk0MDAx4SWGFChXk/1dWZmdnBxMTE5XHlclkmD9/fpHj8fb2xueff46VK1fyailXrlxJCaUW6tGjB37//XfMmzdPXpaRkYHBgwfj6tWrsLOzEy+4Qjh16hTvu0MikWDIkCHiBVRGUQ1lGfX27Vu4ubnh7t27vPIqVaogNDQU9erVK9XHT0tLw9KlS+Hj46OwRsbW1hY///wzpk2bVqTO3bpQQ5k/sSpJoqOuY5T29o81dIVV1IFVBgYGMDc3x/Pnz2Fra6tyX6lUiuTkZCQmJiIpKYl3U1aWnJysM90aTE1NFSaEqhLFcuXKlcogipK+jlu2bBHUEp0/fx5dunRRe6ykZBhjmDRpEnbv3s0rd3d3x/Hjx2FkpL31UxMmTMCePXvkf3fp0gXnz58v0TGphlKIEsoy6NWrV3Bzc8ODBw945dWrV0doaGipziPGGENgYCC8vb3x4sULhft89tln+P3331GpUqViHb+4fSgdHBywatUqQXKkzmTL0NBQ50Y/isHHxwfz588vclPp559/jrZt26pMFBV1q9BWNjY2hUoIP/3bwsJCq/oZfjqFV0FJpUQiQXBwsHzwTU5ODurUqYPnz5/L9+nZsydOnz5dqjGT4snOzkbXrl0RERHBK1+wYAF+//13kaJSLTc3FxUrVuRdF3x8fODt7V2i41JCKUQJZRnz4sUL9OjRA48ePeKV16xZE2fPnoWTk1OpPXZ8fDy8vLxw7NgxhdtdXFywadMmuLm5lehxipuMrFu3rsQXEVJyJflRoK0+NikXpeawME3KukLVIgP5HTt2jDfn5Pr16+Hl5cXbJywsDO3bty+dYEmJvHjxAq1bt8br16955Xv27MH48eNFikq5EydOoF+/fryyZ8+eoVq1aiU6LiWUQpRQliHPnj1Djx49BP3SnJyccPbsWdSsWbNUHjcvLw9r1qzB8uXLedMyfGRqaoolS5bgyy+/hJmZWYkfrzSbS0np0/ZuC4qalAuqOSytJmVdkpqaij179sDX1xcxMTHycgMDA97ntGbNmrh37x4sLS0BfKj1ql27Nl69eiXfp2/fvjh+/LjmgidFcvnyZXTr1g25ubnyMlNTU1y8eFGj8xkXxtSpU7F9+3b53+3bt0dYWFiJj0sJpRAllGXEkydP0L17d8TFxfHK69Spg9DQUFSvXr1UHve///7DrFmzcO/ePYXbe/bsiY0bN8LFxUWtj1vYZjYDAwNIJBIcP36c5rjTEvHx8aVaU/6pT5uUC9OcrI1NyrqGMYbk5GSkpaXB2toa//77LyZPnszbZ9GiRVi9erX877Vr12LBggW8fa5evap1yQn5f9u3bxeM0q9WrRoiIyOL1Z2pNEilUjg6OiIpKUle9ttvv2HhwoUlPjYllEKUUJYBsbGx6NGjB2+0JADUrVsXoaGhqFq1qtofMzExEV999RV27NihcHulSpWwbt06jBo1qtS+nE+ePIlhw4bJm9k+9fExLSwsEBAQQMmkFilpDWXbtm3h6OhYYKJoZ2cnWGWJaB5jDN27d+cNgjA0NMS1a9fkc+BmZmbCyckJb9++le8zaNAgHDlyROPxksLz9PTEhg0beGUdO3ZEaGioVnTnOHPmDHr27Mkri4uLU7poRlFQQqkAIzotOjqaVa9enQHg3Ro0aMBevnyp9sfjOI7t3LmT2dvbCx4TAJNIJGz27NksJSVF7Y+tyL59+xTG4ezszHx8fFhqaqpG4iCFx3Ecc3Z2ZhKJROFrp+wmkUiYs7Mz4zhO7FMgRfTgwQNmYmLCez1dXV2ZVCqV77N69WrBa37jxg3xgiYFys3NZV27dhW8btOnTxc7NMYYYzNnzuTF1apVK7Ud++3bt4Lzfvv2rdqOr4v0u9OPjnv06BG6du2KZ8+e8cobN26Ms2fPonLlymp9vPv376Nbt26YNGkSrwnhoxYtWiA8PBwbNmzQWF/Fly9f8v5u1aoVEhMTER0dDW9vb5QrV04jcZDCk0gkgkEYheXt7U3N0Tqofv36+Prrr3llV65cwdatW+V/z5o1C/b29rx9fvjhB43ER4rH2NgYBw8eFPTP37p1KzZv3ixSVB/IZDIEBgbyyoYPHy5SNHpC7IyWFM/9+/eZo6Oj4BdS06ZN1f4rKSMjgy1evJgZGRkprDmysrJi69atY3l5eWp93MKYMWMGL5aJEydqPAZSdCkpKczS0rLQtZQGBgbM0tJSYzXfRP2ysrKYi4sL73W1sbHhtaSsWrVK8NrfuXNHxKhJYdy4cYOZm5vzXjcjIyN24cIF0WI6f/684L306NEjtR2faiiFqIZSB929exfdunUTTNvQokULhIaGqrUPx/Hjx9GoUSP89NNPClcD8fDwwMOHDzF37lxRJraNjo7m/V23bl2Nx0CKztbWFv7+/oWaNujjwKqAgAAapa/DzMzMBLVW79+/562+4unpKXiNqZZS+zVv3hw7d+7klUmlUgwfPlzQgqYp/v7+vL+bNm2q9sGhhI8SSh1z+/ZtdO/endd5HQBat26NM2fOCJqMiuv58+cYPnw4+vfvj/j4eMH2WrVqISgoCIcOHSqVQT+FlX++TUoodUdB01h9XBPb3NycRumXET169MDnn3/OK/vnn39w4sQJAB9G5X+aYH7c/vDhQ02FSIpp1KhR+Oqrr3hlb9++xZAhQxQOnCxNHMcJEkpq7tYAsatISeFdv36d2dnZCarZXV1d1dYUmJeXx9auXcusrKwUNj0aGRmxxYsXs4yMDLU8XklkZGQI4rt165bYYZFC8vLyUtnMTQOryqa3b98KrmO1atWSX1OSk5OZjY0Nb/u4ceNEjpoUhlQqZX379hV8lseOHavRwXRhYWGCGO7du6fWx6AmbyFKKHXE1atXma2treAN3LFjR/bu3Tu1PMaVK1dYixYtlH7Bd+7cmd29e1ctj6UOt27dEsSoDYkuKdj79++ZtbW14PVbsWIFi4uLY4mJiTSauwzbvn274LX/6quv5Nu//fZbQR9adfZ/I6UnJSWF1a1bV/D6/vrrrxqLYeHChbzHbtCggdofgxJKIUoodUB4eDgrV66c4M3bpUsXlpaWVuLjp6SksNmzZysdIGFvb8927typdV/wBw8e5MVZvXp1sUMihbRx40aF77WoqCixQyMawHEc69Kli6D14/bt24wxxhITEwWtJJMmTRI5alJY9+/fF/xgNDAwYMHBwaX+2BzHsZo1a/Ie+9tvv1X741BCKUR9KLVcWFgY3N3deQvbA0D37t1x/PhxWFlZFfvYjDHs27cP9evXx8aNGxUOkJg8eTKioqIwceJErZuuhfpP6ibGGNavXy8od3FxoddQT0gkEmzevJk38bxUKsX06dPBcRzs7e0xZ84c3n327NkjWAmMaKcGDRpg7969vO8MjuMwevRowdLA6nb9+nXBIh/Uf1IzKKHUYv/99x969+6NtLQ0Xrm7uzuOHTsmXwu3OKKjo9G7d2+MHTsWb968EWxv1KgRLly4gO3bt6ttoI+65U8oaQSfbjh37hzu378vKB8wYIAI0RCxNGjQQDA3ZXh4uHxuygULFsDCwkK+TSaT4aefftJojKT4Bg4ciJUrV/LKUlNTMXjwYMF3mjodOnSI97ezszOaNm1aao9H/h8llFrq7Nmz6NOnD9LT03nlffr0wb///su70BZFTk4OVqxYgSZNmuD06dOC7ebm5vj5559x/fp1dO7cuViPoSk0ZZBuUlQ7CXz4AiL6ZcmSJahTpw6v7Ouvv8br169RsWJFzJw5k7dt165dePr0qSZDJCWwZMkSQe3g/fv3MX78eHAcp/bHY4wJEsrhw4drXetamSVuiztR5PTp04JJYgGwAQMGsOzs7GIfNyQkRGFn6Y+3/v37s7i4OPWdSCmrUKECL/5jx46JHRIpwNOnT5mhoaHgvWdjY8Nyc3PFDo+I4PTp04L3w+jRoxljjL18+ZKZmZnxts2ePVvkiElRpKWlsSZNmghe46VLl6r9sRQN1IyIiFD74zBGfSgVoRpKLRMcHIwBAwYgKyuLVz5kyBD4+/vD1NS0yMd88+YNxo0bh549ewqaiQGgatWqCAgIwNGjR1GrVq3ihq5RycnJSExM5JVRk7f227JlC2QymaC8T58+vP50RH/07NkT48aN45Xt378fwcHBqFy5MqZNm8bb9scff+DFixeaDJGUgJWVFY4cOQI7Ozte+fLlywVLI5ZU/trJGjVqoHXr1mp9DKKC2Bkt+X/Hjh1jJiYmgl89Hh4exaq9kclkbNOmTQpHiANghoaGbMGCBez9+/elcDalKzw8XHAuVMOl3bKzs5mDg4PC9+Kff/4pdnhERG/evGHly5fnvSecnJxYRkYGe/bsmeC6OHfuXLFDJkUUEhIiaJ2wsrKSL63JcRxLSEhgcXFxLCEhoVizijRs2JB3/AULFqj7NOSohlKIEkotcfjwYWZsbCx4g44aNapYidLNmzeZq6ur0ubttm3bshs3bqj/RDTkzz//5J2Pi4uL2CGRAuR/zT7eDAwMWEJCgtjhEZH98ccfgvfG119/zRhjbNasWbxyMzMz9urVK5EjJkW1bt06wWtcs2ZN9uOPPzJnZ2deubOzM1u3bl2hF+24f/++4NiXLl0qtXOhhFKIEkotcOjQIWZkZCR4c3722WcsLy+vSMd6//49W7BggcJ+agBYuXLl2KZNm5hUKi2ls9GM7777TtD/k2i3du3aKXxPduzYUezQiBaQyWSsU6dOvPeGkZERu3PnDouPjxdcI7/44guxQyZFxHEcmzBhgsLrQP55kCUSCZNIJMzS0rJQ81euXLmSd/8qVaowmUxWaudCCaUQ9aEU2YEDBzBq1ChIpVJe+cSJE7F7924YGRkV6jiMMQQGBqJhw4ZYs2aNwn5qn332GR4+fIiZM2fC0NBQLfGLhaYM0i2RkZEIDw9XuI2mCyIAYGBggC1btgjmppwxYwaqV6+OiRMn8vbfuHEjEhISNBwlKYmP84+2bdtWsI3lmweZfajwQlZWFvr374+TJ0+qPHb+/pPDhg2DgQGlOJpEz7aI/v77b4wdO1aQ/E2dOhXbt28vdNIXHx+PQYMGYdiwYXj+/Llgu4uLC0JCQvDXX3/B0dFRLbGLjaYM0i0bNmxQuo2mCyIfNWzYEF9++SWvLCwsDH/88QcWL17MuyZmZmZizZo1mg6RlJCZmRl27txZ6Kl8OI4DYwweHh5ITU1VuM/jx49x69YtXhlNZq55lFCKZM+ePQrn4po5cya2bNlSqF9WeXl5+OWXX9CwYUMcO3ZMsN3ExATLli3D7du34ebmprbYxcYYo1VydEhSUhL27duncFutWrXQsGFDDUdEtNk333wDZ2dnXtlXX30FCwsLwWjw9evXIzk5WZPhETVQNAeyKhzHITMzE3v27FG43d/fn/d3xYoV0alTp2LHR4qHEkoR7NixAxMnThQkk56enti4cWOhksmLFy+iRYsW+PrrrwVTDAEfpuK4e/culi5dCjMzM7XFrg1ev34tmPCdmry11/bt25GTk6Nw24ABA2jSYcJjbm6OTZs28cpSU1OxYMECLFmyhHd9TE9Px7p16zQcISkJxhj8/PyKdV9fX1+FSwTnTyiHDh2q8926dBEllBq2ZcsWTJkyRfChmD9/Pnx9fQv8ck1KSsLUqVPRuXNn3Lt3T7C9UqVK+Pvvv3Hq1Kkym2Tlr500MzNDtWrVRIqGqCKTybBx40al26m5myji7u6OsWPH8sr27duH+Ph4jBkzhlfu4+OjtCmUaJ+kpCTExMQoTAxVYYwhJiZGUCP95MkTXL16lVdGzd3ioIRSgzZs2CBYSgwAFi1ahN9//11lMskYw65du1CvXj1s375dsF0ikWD27Nl4+PAhxowZU6ZrffL3n3RxcaHO11oqKCgIT548UbjN0tISXbt21XBERFesWbMGtra2vLJZs2Zh4cKFvOvb+/fvi13jRTQvf+tSUeVfBzx/7aSdnR1dV0RC38Ia4uPjA09PT0H5kiVL8Msvv6hMAO/fv49u3bph0qRJSEpKEmxv3rw5Ll++jA0bNgguwGUR9Z/UHaoG4/Tq1atYKz8R/VCpUiWsXr2aVxYbG4tDhw5hxIgRvPK1a9fi/fv3mgyPFENOTg727t1bomNYW1vz/s6fUA4ZMoRW3RIJJZQa8Ntvv2HevHmC8qVLl+KHH35QmkxmZmZiyZIlaNasGS5cuCDYbmVlhbVr1+Lq1atwdXVVd9hai6YM0g1RUVE4deqU0u00XRApyJQpU9CxY0de2erVqzF69GheWUpKisofL0RcHMdh3759aNCgAb799ttiHUMikcDZ2Zm3hOOLFy8QFhbG28/Dw6NEsZISEGf6S/3x448/KpzEdeXKlSrvFxQUxJycnJSudOPh4cGePXumobPQLg0aNOA9Fzt27BA7JKKAt7e30vcvAPb69WuxQyQ64O7du4JJzTt16sSGDBnCK6tQoQJLS0sTO1yST0hICGvVqpXKa0FhbhKJhPn4+PCO7efnJ1i4Izs7WyPnRRObC1ENZSlauXIllixZIij/6aeflP5Ke/HiBUaMGIH+/fsjLi5OsL1WrVo4duwYDh06pJcDUWQyGWJiYnhl1OStfdLT07Fr1y6l29u2bYtKlSppLiCisxo1aoRFixbxyi5evIgmTZrwyhITE7F582ZNhkZUuHXrFvr06YOePXvi2rVrJTqWgYEBLCws8Pnnn/PK809mPnDgQOpGIyaxM9qyiOM49v333yv8lfXbb78pvE9eXh5bt24ds7KyUng/IyMjtnjxYpaRkaHhs9EusbGxgufmzZs3YodF8tm0aZPK2oYVK1aIHSLRIRkZGax27dq895CtrS1zd3fnlVWqVEnvr5Fii4+PZ+PHjxcspfjprWPHjmzNmjXM0NBQ5X4AmIGBATM0NGQnT57kPc7r16+ZgYEBb9/Dhw9r7DyphlKIEko14ziOLV68WOEHY926dQrvc+XKFdaiRQulH6hOnTqxu3fvavhMtFNwcLCgiYPjOLHDIp/gOI41atRI5ZfEjRs3xA6T6Jj8n30ArHfv3oW+zpLSlZSUxBYuXMhMTU2Vfu7r16/PDh8+LL9mBwcHMxMTE6VN3B/X8s6fTDLG2ObNm3n7W1passzMTI2dLyWUQpRQqhHHceyLL75Q+OHYsGGDYP/U1FQ2Z84cpb/Q7O3t2Y4dO0p1gXtdk7/PTJs2bcQOieRz9uxZlclk1apV6UcAKZYxY8YI3k+tW7fm/V25cmWWlZUldqh6Iysri61evZrZ2toq/cxXrlyZbd26leXl5QnuP3bsWIX3cXZ2Zj4+Piw1NVXh4/bs2ZO3/6hRo0r7VHkooRSihFJNOI5j8+bNU/jB2LJli2Dfffv2MUdHR6UfwMmTJ7OEhASRzkZ7eXl58Z6nzz77TOyQSD7Dhw/nvUbm5ua8v2fMmCF2iERHvXr1SpC4VK1atVA/4Il6SaVStmvXLla9enWl32PW1tbshx9+YOnp6UqP07FjR959lixZwhITE1X+6ExMTGSGhoa8+x08eLA0TlMpSiiFKKFUA47jmKenp8Iq++3bt/P2jY6OFvT7+fTWsGFDduHCBZHORPvlb+JatmyZ2CGRTzx79kxwoc9fA3/06FGxwyQ6LH9TJwBWq1Yt3t/VqlXT2GhffcNxHDt+/Dhr0qSJ0u8xY2Nj5uXlVagEy8HBgXfff//9t8D7bN++XfCjVVXSWhoooRSiUd4lxHEcZs2ahfXr1/PKDQwMsGvXLkyePBnAhwldV6xYgcaNG+P06dOC45ibm+Onn37CjRs30LlzZ43ErotoUnPttmXLFshkMvnfpqamvCXWzM3N4ebmJkZopIyYNm0a2rdvzyt79uwZ7+/nz59j9+7dmgxLL0RGRsLNzQ39+vXDnTt3FO4zatQoPHjwAL6+vnBwcFB5vNTUVCQkJPDKCnNNzz+Zed++fWFpaVng/UgpEzuj1WUymYxNmTJF8CvFwMCA7d27V77fmTNnWN26dZX+muvXrx+LjY0V8Ux0Q3Z2tmBUX2RkpNhhkf/Jzs5mFStW5L0+derU4f09YMAAscMkZcDt27cFc1Pa2NgIai1zc3PFDrVMePz4MRs1apTS7zAArHv37iwiIqJIx42IiBB8d+bk5Ki8T0pKCjM2Nubd79PvW02hGkohqqEsJplMhsmTJwvW1TY0NMS+ffswduxYvHnzBuPHj4ebm5ugZg0AqlatCn9/fxw7dgxOTk6aCl1nxcbGguM4XhmtkqM9/P398fbtW17ZmzdveH/T6jhEHZo0aYIvvviCV5Z/6cX4+Hj89ddfmgyrzElISIC3tzcaNGiAAwcOKNynSZMmOH78OM6cOYM2bdoU6fj5vxednJxgYmKi8j7Hjh1DXl6e/G8TExO6rmgJSiiLQSqVYsKECYImFSMjIxw4cADDhw/Hli1bUL9+fYUXNAMDA8yfPx8PHjzAsGHDVK7jTf5f/otPpUqVYGNjI1I0JL/83T6aN2+OtLQ0Xhld+Im6fPfdd4If4oaGhry/V61aBalUqsmwyoSMjAz88MMPcHZ2hp+fHy+B+6h69erYtWsXbty4gb59+xbre6w4XZjyT2beq1cv+h7QEpRQFlFeXh7GjRsnWODe2NgYhw4dQp06ddCxY0fMnDkTqampgvu3bdsWkZGRWLNmjWCRe6JadHQ072/qP6k9rl+/jsuXL/PKqlevzvu7RYsWqFq1qibDImWYhYUFNm7cyCv7tP8uAMTExGD//v2aDEunSaVSbNu2DS4uLvjuu+8EPwgBwNbWFqtXr0ZUVBQmTJggSOKLIv81vaAWp7S0NAQHB/PKhg8fXuzHJ+pFCWUR5ObmYsyYMYKqfxMTE/z999+4cOECWrVqhfDwcMF9y5Urh40bNyIsLAwtWrTQVMhlCg3I0V4bNmzg/V21alVERUXxyqh2kqhbnz59MGrUKJX7/PDDD4JEk/AxxnDkyBE0adIE06dPx6tXrwT7mJiYYOHChYiJicGiRYtgbm5e4sct6jX9+PHjyMnJkf9tZGSEQYMGlTgOoh6UUBZSbm4uRo4cKRhdZmpqiq+//hrz58/HmjVrFF64xo4di4cPH2LWrFkl+jWn7/JffKj/pHZISkrC33//zSsbMWKE4PWihJKUhrVr16JcuXJKt0dFReHgwYMajEi3XL58GZ07d8aQIUPw8OFDwXaJRILx48fj0aNH+O2332BnZ6eWx2WMFTmhzN/c7ebmhvLly6slHlJylFAWQk5ODjw8PHDkyBFeuZmZGVq0aIEVK1bg+fPngvu5uLjg9OnT2Lt3LxwdHTUVbplFNZTaaceOHcjOzpb/bWxsLPjSqVSpElq3bq3p0IgeqFy5Mn7++WeV+/zwww+CAX36LioqCsOGDUOHDh1w6dIlhfv07t0bN27cwJ49e1CzZk21Pv6bN28ETeqqrumZmZk4fvw4r4yau7ULJZQFyMrKwpAhQ3Ds2DFeubGxMRhjCpu3TUxMsHTpUty+fRs9e/bUVKhlWnp6uqAZhhJK8clkMkE/thEjRuDcuXO8sv79+8PAgC43pHRMnz4d7dq1U7r93r17CAwM1GBE2uvVq1eYOXMmGjVqpPQ5admyJUJCQhAcHIxmzZqVShz5+0+ampoK+l1/Kjg4GJmZmfK/DQwMMHjw4FKJjRQPXeFVyMzMxKBBgwSdgA0MDJCXl8fry/GRm5sb7ty5g2XLlsHMzExToZZ5+S8+EokEzs7OIkVDPjpx4gTi4+N5ZRMnTsSFCxd4ZdTcTUqTgYEBtmzZorJL0cqVK3mT7OubtLQ0fP/996hTp45gAYKPnJyc8Pfff+Pq1aulvgBB/hanOnXqqPzRmb+7Wbdu3QqcOJ1oFiWUSmRkZGDAgAEICQkRbFPUdFKxYkXs3bsXp0+fppqzUpD/4lOjRg1K2LVA/qmCWrZsiZSUFN5ULSYmJnB3d9d0aETPNG3aFAsXLlS6/datWzh69KgGI9IOeXl52LBhA5ydnbFy5UpeLd9H9vb2WLduHR48eIAxY8ZopDWhKF2YcnJyBK+dh4dHqcRFik/vE0rGGBITExEfH4/ExEQwxpCWloa+ffvi7NmzBd5fIpFg1qxZePjwIcaOHUtzSpYS6j+pfR49eoSTJ0/yyubMmSPoHtK9e3dYWVlpMjSip77//nvUqlVL6fYVK1boTS0lYwz//PMPGjZsCE9PT8ESh8CHpVCXLFmCmJgYzJ07F6amphqLryjTwJ0+fZrX31IikWDo0KGlFhspHr1NKFNTU+Hj4wMXFxc4ODjAyckJDg4OcHZ2RtOmTfHff/8VeIzmzZvj8uXL2LhxI400K2U0B6X22bRpE+9vOzs7jBw5UtBxnpq7iaZYWloK+vR+6tq1a4IuTGXRuXPn4OrqilGjRuHx48eC7QYGBpg6dSqio6OxatUqlaPkS0tRZu3IP7q7Y8eOqFy5cqnERYpPLxPKkydPolq1apg/fz5iY2N52+Li4gR9wvKztLTEmjVrcPXqVbi6upZipOQjmjJIu6Snp2Pnzp28silTpuD27dtISkrilVNCSTSpb9++GDFihNLty5cvL7O1lHfv3sWAAQPQvXt3XL16VeE+AwcOxJ07d7Bt2zbRFhqQyWSCRFdZJUFubq5ghhUa3a2d9C6hPHnyJPr374+srCwwxop8YRk2bBgePHiA+fPnw8jIqJSiJPlRk7d22bt3L969eyf/+2PXj/zN3Y0bN1bZBElIaVi3bp3S5fiuXLmisG+8Lnv+/DkmT56MZs2aISgoSOE+rq6uuHDhAv799180bNhQwxHyPXv2TDCoVdk1/ezZs4JV54YNG1ZaoZES0KuEMjU1FR4eHmCMFXlOspo1a+Lo0aPw9/dXObUBUb+kpCSkpKTwyiihFA9jTDAYp3///nBychJ0nKfaSSKGKlWq4KefflK6vaz0pUxNTcXXX38NFxcX7Ny5U+H3mouLCw4dOiSfwFwb5O/CZG1tjYoVKyrcN39zt6urK30Haym9Sih3796NzMzMIieTPXv2xL179+jLUST5ayeNjIzUPskuKbz//vsPd+/e5ZV5enoiPj5eUE6fGSKWGTNmKO2SdPHiRZw/f17DEalPTk4O1qxZA2dnZ/zyyy+8hQU+qlSpEjZu3Ih79+7Bw8NDqwaMKmpxUhSfVCrF4cOHeWXU3K299CahZIzBz8+vyPeTSCSIi4uDhYVFKURFCiP/xcfZ2Zm6G4gof+2ki4sL3N3dBU1t9vb2KiebJqQ0GRoaqpybcsWKFRqOqOQ4jsNff/2FevXqYeHChUhOThbsY2lpiWXLluHx48eYNWsWjI2NRYhUtcJ2Ybpw4QISExN5ZTRdkPbSm4QyKSkJMTExRW7mYIwhJiZG4QeXaAb1n9QeL168QEBAAK9s9uzZMDAwEDR39+vXj9auJ6Jq1qwZ5s+fr3Db2bNncfHiRQ1HVHynT59Gq1atMH78eDx58kSw3dDQELNnz0ZMTAyWLl2q1VN1FXbWjvyTmbds2RJOTk6lFhcpGb1JKNPT00t0//xrjhLNoSmDtMfWrVt5K2xYWFhg4sSJSE9PF8zbSs3dRBssW7YMNWrUULht5cqVGo6m6G7cuIFevXqhV69euHnzpsJ9hg8fjvv372PDhg2oVKmSZgMshsLM2sFxnODHK9VOaje9SShL+mvN2tpaTZGQoqIpg7RDbm4utmzZwisbP348bG1tERISgtzcXHm5kZERevfurekQCRGwtLTEhg0bFG47deoUrly5ouGICic+Ph7jxo1Dy5Ytcfr0aYX7dOnSBeHh4Th48KDO/NDOzc1FXFwcr0xR7GFhYXj9+jWvjPpPaje9SSjt7e3h7Oxc5I7JH9eMtrOzK6XIiCocx1ENpZbw9/fHmzdveGVz5swBAEFzd5cuXUSZLJkQRQYMGKA0GdG2WsqkpCQsWLAA9erVw969exXu07BhQ/z777/yCcx1SWxsrGBgrKJKgvyju5s0aULXfi2nNwmlRCKBl5dXse7r7e2tVSPk9MnLly8Fa8/SRUUc+QfjdOnSBU2aNAHHcYIBOdTcTbSNj4+PwpamoKAgXLt2TYSI+LKysvDzzz/D2dkZa9eu5dX4f1SlShX88ccfuHXrFgYOHKiT30v5KwgqVqwIW1tbXhnHcYL+k9Tcrf30JqEEgAkTJsDCwqJIC98zxtCyZctSjIqokv/iY2FhgSpVqogUjf66ceMGwsLCeGWenp4APixnl7/mkhJKom2qVKmCH3/8UeG2H374QcPR/D+ZTIYdO3bAxcUFixcv5i0Y8JGNjQ1+/PFHREdHY8qUKTo9y0VhujBdvXoVz58/55VRc7f206uE0tbWFv7+/pBIJEVKKgcPHowbN26UYmREGUUXH138Va7r8vdBq1KlCoYMGQIAgtVx6tWrR/1ciVaaNWsW2rRpIyg/fPgwbt26pdFYGGMICgpCs2bNMGXKFLx48UKwj7GxMebNm4eYmBgsXry4TExfV5hZO/I3d9erV0/01X1IwfQqoQSA3r17IygoCObm5pBIJILkRFGykpycjB49eiAyMlJTYZL/oSmDxJecnCzoyzVjxgz5/Ha0Og7RFYaGhti6davCCoWVK1ciMTER8fHxSExMLNWVdK5cuYLu3btjwIABuHfvnsJ9xo4di6ioKKxduxYVKlQotVg0raA+8YwxQXP38OHDqSJBB+hdQgl8SCqfP3+OdevWoXbt2rxttWvXxurVq9GhQwdeeWpqKnr27Km1IwLLKhqQI74dO3bwVuIwNjbG9OnTAXyYlzJ/7T0llESbNW/eXOHclP7+/nBwcICTkxMcHBzg4uICHx8fwTrSJREdHY0RI0agXbt2SlfqcXNzw7Vr17B3794yOediQU3eN27cEIwCp/6TOoLpOY7jWGJiIouLi2OJiYmM4zjGGGPp6emse/fuDADvZm1tzS5duiRy1PqjXr16vOd/165dYoekV6RSKatduzbvNRgzZox8+5YtW3jbypUrx3Jzc0WMmJCCpaWlsapVqwqu75/eJBIJk0gkzNLSkgUHB5fo8d68ecPmzJnDjIyMlD5es2bNWHBwsPw7qCxKS0sTnPft27d5+yxZsoS3vXbt2lr5nLx9+1ZwLm/fvhU7LFHpZQ3lpyQSCezt7VGrVi3Y29vLq9UtLS1x7NgxuLu78/ZPS0tD79698d9//4kRrl6RSqWIiYnhlVENpWYFBwcjNjaWV/ZxqiBA2Nzdt29frVzqjZBPWVlZYdq0aSr3YYyBMYasrCz0798fJ0+eLPLjpKenY8WKFXB2dsaGDRsglUoF+9SoUQN79uzB9evX0bt37zLdtPv48WNBWZ06deT/Z4wJ+k9q2zrkRDm9TyhVsbCwwL///os+ffrwytPT09GnTx/ByiBEveLj4wUXYEooNSv/VEHNmzeXdwfJzMxESEgIbzs1dxNdkJqail9//bVQ+3IcB8YYPDw8Ct38nZeXh82bN6NOnTpYunSpwpXaypcvj99++w1RUVEYP358kQaK6qr8XZhq1KgBc3Nz+d/37t0TNInT6G7dUfbfwSVkZmaGw4cPC74oMzMz0b9/f8EXKlGf/Bef8uXLw97eXqRo9M/jx48RHBzMK/P09JTXFpw9e5bXt9LAwEDw44sQbbR7927B/LaqcByHzMxM7NmzR+V+jDEEBASgcePGmDVrlmA6LQAwNTXFl19+iZiYGCxcuBBmZmZFjl9XFdR/Mn/tZPXq1RWOyifaiRLKQjA1NYW/vz8GDx7MK8/KysKAAQMEX7pEPWiEt7g2btzI+7t8+fIYM2aM/O/80wV16NCBEn6i9Rhj8PPzK9Z9fX19lY7+vnjxIjp27AgPDw/BtQv40L1q4sSJiI6Oxi+//ILy5csXKwZdVtA1nZq7dRsllIVkYmKCgwcPCkab5eTkYPDgwYKVQkjJUUIpnoyMDOzYsYNXNnnyZPk8eIwxQUI5cOBAjcVHSHElJSUhJiamyNMCMcYQExOD5ORkXvmDBw8wZMgQdO7cGZcvX1Z43379+uHWrVvYuXMnqlevXuzYdZ2qWTsePnwomEKJmrt1CyWURWBsbIx9+/Zh1KhRvPLc3FwMHToUR44cESmysokSSvHs3buXt2KHRCLBrFmz5H/funVLsJIF9Z8kukBRf8aiSEtLA/BhWdjp06ejcePGSq/9bdq0QWhoKIKCgtCkSZMSPW5ZoOqann/uycqVK6N9+/YaiYuoByWURWRsbIy//voLn332Ga88Ly8Pw4cPF3woSPHl/zVLq69oBmNMsDJOv3794OzsLP87f+2kk5MTGjRooJH4CCkJKyurEh/j22+/RZ06dbBt2zZwHCfY7uzsjAMHDsgnMCcfaoaTkpJ4ZZ9e0/N/dw4bNkwvBiqVJbq7IKiIjIyMsHv3bvm/H0mlUowaNQp///03Ro4cKWKEui8rKwtPnz7llVENpWZcvHgRt2/f5pV9OlUQIJwuaODAgdTXieiErKwsWFhYFGlQDvD/U8y1bt1akBh9VKFCBXz//feYMWMGTExM1BFumZG/gsDIyAi1atUCAMTGxgoWSKDJzHUPpf/FZGhoiB07dmDKlCm8cplMhjFjxuDvv/8WKbKyQVEfJ6qh1Iz8UwU5Ozujd+/e8r/fvHmDiIgI3j7U3E20Hcdx2Lx5Mxo1alTkZBL4UHOfmJioMJm0sLDAt99+i5iYGHh5eVEyqUD+hLJ27dryOWvz1046ODigc+fOGouNqAfVUJaAgYEBtm7dCmNjY2zevFleznEcxo8fD6lUis8//1zECHVX/otP5cqV1dJURVR7+fIlAgICeGVz5szhNT0dP36ct93KygpdunTRSHyEFEdUVBSmTZum9gUpDA0NMWXKFCxbtgyVK1dW67HLGlVTBuUf3T106FAYGVF6omuohrKEDAwMsHHjRnh6evLKOY7DxIkTBSNlSeHQgBxxbN26lTeZvLm5OSZOnMjbJ39zd69evWBqaqqJ8AgpktzcXKxatQpNmzZVmkwWt6vGkCFDcPfuXWzZsoWSyUJQdk1/+vSpoMWDmrt1EyWUaiCRSODr64t58+bxyhljmDJlCrZu3SpOYDqMEkrNy83NxZYtW3hl48aNk8+XxxjDixcvBPOu0nRBRBtdvXoVrVu3xrfffovc3FzB9okTJ+Kff/6BhYUFJBJJoRPLDh064OLFiwgMDET9+vXVHXaZpWzKoPwtIuXLl6eBTDqKEko1kUgkWLNmDRYtWiTYNmPGDMGoWaIcY0wwHxkllKUvICAAr1+/5pXNmTMHqamp8PHxgYuLC6pVq4asrCzePh+XYiREG2RkZGDBggVo164d7ty5I9ju5OSEU6dOYefOnRgxYgSeP3+OH3/8EeXKlVN53Hr16iEwMFA+gTkpPMaY0kqC/M3dgwcPlvetJDqGEbXiOI4tWbKEARDc1q1bJ3Z4Wi0lJYWtW7eOOTs7C567KVOmsJSUFLFDLNM6derEe847d+7MgoODmaWlJZNIJEwikSh8X1taWrLg4GCxwyeEnTx5ktWqVUvh+9TAwIAtWLCApaeny/fPyspiv/76KytfvrzC+wBgjo6ObPPmzSwvL0/EM9NtL168EDyvT58+ZS9evBBcV44dOyZ2uIXy9u1bwTm9fftW7LBERQllKeA4ji1dulThxenXX38VOzytVFDiIpFIKHEpRTdu3BA854sXL2aGhobMwMBA6Zftxy9qQ0NDem2IaBITE9mECROUvkebNm3KIiIi5PtLpVK2e/duVqNGDaX3sbKyYitWrOAloKR4zp49y3tuzc3NmUwmY+vXr+eV29jYsOzsbLHDLRRKKIUooSxFK1asUHih+umnn8QOTasEBwdT4iKyqVOn8p7rSpUqMUtLywJfk09fG0tLS6pFJhrFcRzbt28fc3BwUPi+NDU1ZatWrWK5ubny/U+cOMGaNm2q9L1sZGTEPD092Zs3b0Q+u7Jj69atggSfMca6d+/OK//ss89EjrTwKKEUooSylP30008KL1orVqwQOzStkJKSQomLyJKTk5m5uTnvee7Tp4/SJm5lN4lEwnx8fMQ+HaInnj59ygYMGKD0/di5c2f28OFD+f6RkZGsR48eKt/DI0eOZNHR0SKeVdn0xRdf8J5nDw8P9vbtW8F1PyAgQOxQC40SSiEalFPKvv76a/z222+C8u+//x5Lly4VTN6tb3bv3o3MzEyFy5cpwnEcMjMzsWfPnlKOTH/s3LmTN9DG0NAQDx48KNaxfH199f49TUoXx3HYuHEjGjVqJFgCFABsbGywefNmnDt3DvXq1UNsbCzGjBmD1q1bIzQ0VOExu3XrhoiICBw4cAB16tQp7VPQO4oG5Bw+fJh33be0tESfPn00HRpRJ7EzWn2xbt06hb+IFy9ezDiOEzs8UXAcx5ydnYtVE+bs7Ky3z5s6yWQyVrt2bd7zO2TIkCK9HvlviYmJYp8WKaPu37/POnTooPS9N3jwYPb8+XPGGGMJCQls7ty5zNjYWOn+jRs3ZkFBQXQtKWUNGjTgPe87d+5kvXr1EtQO6xKqoRSiGkoNmTt3rmBJOwD46aef8NVXX+llrU5SUpLCJRYLwhhDTEwMkpOTSyky/REcHIzY2Fhe2dixY0t0zLS0tBLdn5D8cnNzsXLlSjRv3hxhYWGC7ZUqVcLBgwcRGBiI8uXL48cff4SzszN8fHyQl5cn2L9atWrYuXMnbt68iX79+tE69KVIJpPh8ePHvDJHR0dBbTFNZq77KKHUoDlz5ggmjgaAX3/9FQsWLNC7pDI9Pb1E96fEpeTyz4/arFkzdOvWrUTH3Lt3L1JTU0t0DEI+Cg8PR8uWLfH9998rnKB88uTJuH//PoYMGYLt27ejTp06+Oabb/D+/XvBvuXKlcMvv/yCR48eYeLEiTA0NNTEKei1J0+eCJL6R48e8VbkMjMzQ79+/TQdGlE3cStI9dP27dsVNvN6enrqVdNLQkICNa2KKDo6WvA+3Lp1a7G7Inx6MzExYZMnT2aRkZFinybRUWlpaWzu3LlK34e1a9dmISEhjOM4duTIEUGzav7344IFC+iaIYITJ07wXgtbW1vWr18/QTcbXUNN3kJUQymCyZMnY9euXTAw4D/969evx6xZswo9QEXX2dvbw9nZucjNTRKJBM7OzrCzsyulyPTDpk2beLXitra2GDt2LCQSCby8vEp07NzcXOzYsQOtW7dG27ZtsWvXLsEKO4QoExwcjMaNG8PHx0fQcmNgYIBFixbhzp07sLS0RJcuXTB48GCFA8kkEgnGjRuHqKgo/P7777C3t9fUKZD/yb/korOzM0JCQnhlw4cP12RIpLSIndHqs7179yqcLmfKlClMJpOJHZ5GrFu3jqanEUFGRgaztbXlPa8LFiyQby/qdE6Fudna2rIFCxawR48eiXjmRJslJCSwcePGKX0PNWvWjEVGRrKoqCg2bNgwle+3Xr16sRs3boh9SnrP09OT97p07NiR97exsTFLTU0VO8wioxpKIUooRXbgwAFmaGgoeGNOmDCBSaVSscMrdcVJXIyMjFhycrLYoeu0bdu2CZ7X/PPvFWXCeQMDA2ZnZ1fo19Dd3Z0FBATQcnaEMfZhxoe9e/eyChUqKHy/mJqasp9++ok9ffqUzZw5U+E18+OtRYsW7PTp02KfEvmf/KO583dN6N+/v9ghFgsllELU5C2ykSNH4sCBAzAyMuKV7969GxMmTOB1XC6LbG1t4e/vD4lEIugCoIxUKsXWrVtLObKyizEmmHGgb9++gvn3evfujaCgIJibm0MikQi6JnwsMzc3x4kTJ/DmzRvs2bMHtWvXLjCG06dPY9iwYahVqxZWrFiBly9flvzEiE56+vQpBgwYgM8++wyJiYmC7V27dsXly5eRlZWFBg0aYPPmzZDJZIL9atWqhb179yIyMhI9e/bUROikEPI3eecf8U2ju8sQsTNa8sHhw4cVzpc2atQo+bJhZVlBa3nnv0kkEhYUFCR22Drpv//+Ezyfqp7LlJQU5uPjw5ydnXn3cXZ2Zj4+PoLmKqlUyvbu3cvq169fpFrn4cOHs9DQUL0amKbPpFIp8/X1ZZaWlgrfE+XKlWMbN25k69evZxUrVlT63rGzs2Nr167VmTWg9Ul2drbK67mRkRFLSkoSO8xioRpKIUootcixY8eYiYmJ4E3q4eGhF0mlssRF1RdOVFSU2GHrnNGjR/Oex9q1axeqzy7HcSwxMZHFxcWxxMTEAhM/qVTK9u/fzxo1alToxBIAq1+/Plu3bh0tr1mG3b17l7Vv317pe2DIkCFsy5YtzMXFRek+ZmZmbPHixfQ+0WL37t1T+Vnv1auX2CEWGyWUQpRQapng4GBmamqq8AKbk5MjdngakT9xiYuLE6w1/Wny8e7dO7FD1hkvX75kRkZGvOfwt99+K9XHlMlk7ODBg6xJkyZFSizNzc3ZlClTaOqhMiQ7O5stXbpU6eo1jo6ObMWKFczV1VXp+8LAwIBNmTJFviIO0V6BgYGClqVP/96yZYvYIRYbJZRClFBqodOnTytMoAYMGKC3zTorVqxQ+gUzcOBAvRkVX1LLli0TJG2aanKSyWQsICCANW/evEiJJQDWtm1btnPnTpaZmamRWIn6hYWFsYYNGyp9jT08PFjv3r1Vvg8GDBjA7t69K/apkEJavXq1yh8Gb968ETvEYqOEUogSSi119uxZZmFhIXjD9unTRy+/VLOysgRrTn96+/bbb8UOUevl5uayypUr8563qVOnajyOjxNRt2rVqsiJZfny5WnqIR3z/v175uXlpbQvXc2aNVnfvn1VzibQtm1bdv78ebFPhRTR1KlTlb6m3bp1Ezu8EqGEUogSSi124cIFZmVlJXjT9uzZk2VkZIgdnsYdOXJEZbJx8OBBsUPUagcOHBA8Z2LO08dxHAsKCmJt27YtcmIJ0NRDuiAoKIhVr15daQ1Vu3btmJmZmdLX2MXFhR08eJAGaumoLl26KH1t169fL3Z4JUIJpRAllFru0qVLzNraWvDG7d69O0tPTxc7PI3iOI717dtX6QXKwsKC3bp1S+wwtVbnzp15z1fHjh3FDokx9uF1DQ4OVjlIQ9WtatWqbPny5ezly5dinwr5n7dv37KxY8eqfM3KlSundHvFihXZhg0b9GIwYlmWv0Xk09uLFy/EDq9EKKEUooRSB4SHhyu8+Hbp0oW9f/9e7PA0KioqSmmHfgDMycmJ1utV4NatW4Lnat++fWKHxcNxHDt9+jTr1KlTsRJLmnpIfBzHsT///JPZ29srfI2MjY1Z+fLllb6GlpaWbOnSpXp3XSuL3r9/r/R11pYfsyVBCaUQTWyuA1xdXRESEoLy5cvzyi9cuIA+ffrg/fv3IkWmeXXr1sXChQuVbo+Li8PIkSPL/ITwRbVhwwbe346Ojhg2bJhI0SgmkUjQs2dPXLhwAaGhoejatWuR7i+VSnHo0CH06NEDDRs2hK+vL1JTU0snWCLw5MkT9OvXD+PHj0dSUpJgu5WVFfLy8pCSkiLYZmhoiFmzZuHx48dYtmwZrK2tNREyKUX5JzT/FK3dXUaJndGSwrt+/brCX/6urq56NRdbWloaq1q1qsraqnnz5okdptZITk4WDPD6/vvvxQ6rUM6dO8d69OhRrBpL/K8bxJQpU9i1a9fEPpUySyqVsnXr1imdLzb/NFX5b8OGDWMPHz4U+zSImu3bt0/pa/7kyROxwysxqqEUohpKHdKiRQuEhoaiQoUKvPIrV67A3d1d4S//ssjKygq//fabyn3WrVuH3bt3aygi7bZr1y5kZmbK/zYyMsKMGTNEjKjwunbtijNnzuC///6Du7t7ke+fmZmJ7du3o1WrVnB1dcXu3buRlZVVCpHqp7t376Jjx46YN28eMjIyFO6jrLWgU6dOCAsLg7+/P+rVq1eaYRIRKKuhbNu2LWrUqKHhaIgmUEKpY5o2bYqzZ8+iYsWKvPLIyEi4ubkpbGoqi0aNGlVgk+iMGTMQERGhoYi0E8dxgubuYcOGoUqVKiJFVDydOnXCqVOnEBYWhj59+hTrGBEREZg4cSKqVq2KL774QrCmMCm8nJwcfP/992jZsiWuXLlSpPs2aNAAR44cwYULF9C+fftSipCI7dGjRwrLae3uMkzsKlJSPPfv32eOjo6CKvemTZvqTbX77du3maGhocrmtCpVquj16N8TJ04InpOyMJ/flStXWP/+/YvdFP7x5u7uzgIDA2nqoSK4ePFikdZp//SzuG3bNnqu9YSy6cAeP34sdmhqQU3eQpRQ6rCoqCiFfQkbNWrEXr9+LXZ4GuHt7V3gF1n79u31doWh/ElXkyZNytQI6MjISDZo0CCVr7+yCbU/vVWrVo2tWLFCr398FOTdu3dszpw5hXo+P71ZW1uzVatW6eXcufqK4zhma2sreC80b95c7NDUhhJKIUooddzjx48VThxcv359vfhyTElJYQ4ODrxzV7Rs5dSpU8tUIlUYMTExZWrtXFWuX7/Ohg0bpjKxKag2G/gwgGTEiBE09VA+R48eZdWqVStSImlsbMzmzp3LEhISxA6faJiiZAsA++GHH8QOTW0ooRSihLIMiI2NZTVr1hS8uevWrcueP38udnilbvv27YJzV/TreMOGDWKHqlFffPEF7/zLlStX5ifDv3XrFhsxYoTKWjRjY2NmampaYEJUv3595uPjo1czKOT35s0bNnr06CIlkgDYmDFjWExMjNjhEw1LSUlh69atUzoLx5UrV8QOUW0ooRSihLKMiI+PV7jWtbOzM3v69KnY4ZUqmUwm6K9jYWEhWNLNyMiInTt3TuxwNSIjI0MwgbQ+TaV09+5dNnr0aJWJpYmJicJ+yPlvFhYWbOrUqXo19RDHcWz37t3Mzs6uSIlkjx49WGRkpNjhExEEBwczS0tLJpFIlH7uLC0tWXBwsNihqgUllEKUUJYhz549Y3Xq1BG8yZ2cnFhcXJzY4ZWqiIgIwUWsY8eOgueiQoUKLD4+XuxwS90ff/whOPdHjx6JHZbG3b9/n3322WfMwMBAaRJkamrKGjZsqHJN6Y83V1dXtmvXLpaZmSn2qZWa2NhY1qtXryIlkk2bNmUnTpygbgJ6Kjg4mBkaGqr8nAEf1m83NDQsE0klJZRClFCWMS9evGB169YVvNFr1KhR5pugpk6dKjjvzz77TFDWokWLMj1AgOM41rx5c9459+nTR+ywRPXw4UP2+eefF5hYdurUSWFNf/6bnZ0dW7hwIYuOjhb71NRGKpWyNWvWCCbBV3WrXr062717N5NKpWKHT0SSkpLCLC0tC0wmP00qLS0tdb4rCSWUQpRQlkGvXr1iDRo0ELzZq1WrVqa+APN7+/atoO9k06ZNWZ8+fQTPxejRo8tsbcqlS5cE53v06FGxw9IK0dHRbNKkSSoH6JiYmLCBAweyfv36FbjKCwDWq1cvnZ966NatW6xNmzaFTiTLly/Pfv31V5aVlSV26ERk69atK/LIf4lEwnx8fMQOvUQooRSihLKMevPmDWvcuLHgDV+lSpUyvcyZn5+f4JxXr17N6tWrJyj/5ZdfxA63VIwZM4Z3nk5OTlSDlE9MTAybOnWqyoTR2NiYffbZZ2zevHkFLvX58Qebrk09lJWVxb755ptCJc4fa3EXLVrEkpOTxQ6daAGO45izs3OxEkpnZ2ed/lFPCaUQJZRlWEJCAmvWrJngTe/o6Mju3bsndnilIi8vjzVp0oR3vra2tiwsLIzZ2NgILmrHjx8XO2S1evnypSA5+PXXX8UOS2vFx8ezGTNmMGNjY6VffkZGRmzSpEls48aNzN3dvcAvS12ZeujChQsKf2gpSwAmTJhQJtZgJuqTkJBQpEQy/y0xMVHsUyg2SiiFKKEs45KSkljLli0Fb/yKFSuyO3fuiB1eqTh//rzgfKdOncqOHTsm+CVdrlw5FhUVJXbIarN8+XLe+ZmZmbGkpCSxw9J6T58+ZbNnz2YmJiZKv/wMDQ3ZxIkT2alTp9iCBQsEo+gV3Ro0aKB1Uw+9e/eOzZw5s9Bf+n369GG3bt0SO2yiheLi4kqUUOryYFFKKIUoodQDycnJCvtHVahQgd28eVPs8EpF/mZfiUTCIiIi2KpVqxR+6b97907skEssNzeXValShXdukydPFjssnfLs2TPm5eWlcp5KAwMDNm7cOHbz5k22c+dOpUvMfXrTlqmHjhw5UqjmewCsVatW7MyZM6LGS7Qb1VBSQvkpSij1RGpqKmvXrp3gA2BnZyf6l1xpeP78ObO0tOSda9u2bZlUKmUjRowQPA8DBw5kMplM7LBL5J9//hGcV1l8bTXh5cuXbN68eSqnEpJIJGzMmDHs3r17LDIykk2ZMkXhKk35b2JMPfT69Ws2cuTIQn3J165dm+3fv1/nPw+k9IWHhxdqBSpFnx3qQ1n2UEKpR969e6dwbkZbW1sWEREhdnhq9/PPPwvOdfv27Sw9PZ01bdpUsO27774TO+QS6dKlC+98OnToIHZIOu/Vq1ds4cKFKqfSkUgkbOTIkezOnTssOTmZrVu3rlB9EzUx9RDHcWzHjh0KV47Kf6tQoQLz8fFhOTk5pRYPKTv++OMPlV1ECkooaZR32UMJpZ5JS0tjXbt2FXwQbGxs2OXLl8UOT62ys7MFc3I6ODiwlJQUFhcXx+zt7QXPw6FDh8QOu1hu374tOJe9e/eKHVaZ8ebNG/bll18Kar3z3zw8PNitW7cYx3HszJkzbPjw4YWeeujw4cOFnnqI4ziWkJDA4uLiWEJCgsKanpiYGNajR48CH9vc3Jx98803ZaLbByl92dnZbMaMGcVKJAGah7Iso4RSD6Wnpyv8orG2tmYXL14UOzy1Cg4OFpynt7c3Y4yx0NBQQXONpaUlu337tshRF13+C3ylSpWopqkUJCQksMWLFzMrKyuVX5pDhgxh169fZ4x9WGxg+fLlapl66ONayc7Ozrz7OTs7s3Xr1rGUlBSWl5fHfvvttwJrjwwMDNi0adPYixcvNPkUEh32/PlzhV2nPn1PFfSeMzQ0ZCdPnhT7VEqMEkohSij1VEZGhsIpUCwtLdn58+fFDk+tBg8ezDtHQ0NDedLo4+MjeA6cnJx0qrN4SkqKoElW15vvtV1SUhL79ttvBVNR5b8NHDiQXb16lTH2YUqrgICAYk89pGqt5I9l5ubmrEaNGgUef/Dgwez+/ftiPoVEx1y4cIFVqlRJ4ftp3rx57NixYwW+Py0tLctEMskYJZSKUEKpx7Kysljfvn0FHwoLC4syNbozNjZWMGq3a9eujOM4xnEcmzhxouA5cHNz05mVT9auXStImJ8/fy52WHohOTmZLVu2rMA+iv369WPh4eHy+z169KhIUw/NnDmzUGslF3Rr3749+++//0R8xoiu4TiO+fr6Kuy6YW5uzutak5KSwnx8fBTWoPv4+LDU1FQRz0S9KKEUooRSz2VnZ7OBAwcKPhhmZmbs1KlTYoenNt9//73gHPfv388Y+5BYu7q6CrbPnz9f5KgLJpPJmIuLCy/u4cOHix2W3klNTWUrV64sMEHs3bs3u3Tpkvx+mZmZhZ56qCS3OnXqsICAAJ0eVUs0LyMjg40fP17he8rJyUnptHMcx7HExEQWFxfHEhMTy+T7jhJKIUooCcvJyWFDhgwRfDhMTU3ZiRMnxA5PLTIyMljNmjV551e1alWWlpbGGPvQz61y5cqC52D37t0iR66aoj6i586dEzssvfXu3Tv2448/Khzw9emtZ8+e7MKFC7z7FmXqocLe7Ozs2KZNm1hubq5IzwjRVXFxcax58+ZKfxjp+4IJlFAKUUJJGGMfJsUePny44ANiYmLCjh49KnZ4auHv7y84v8WLF8u3X758WTCQwdTUlF25ckXEqFUbMGAAL97GjRuXydoAXfP+/Xv2yy+/sAoVKqhM+Lp3787Onj3Lu29Rph5SdStfvjx7//69OE8A0WmnTp1idnZ2Ct9X33zzDZNKpWKHKDpKKIUooSRyeXl5bPTo0YIPibGxMQsMDBQ7vBLjOE4wIMLY2Ji39OL27dsF51+1alX26tUrESNXLDY2VtD5fdOmTWKHRT6Rnp7OfvvtN1axYkWVyV+XLl1YSEgI78cAx3EsICCgREmlLg0uI+LjOI79/PPPCvvqWltbs4CAALFD1BqUUApRQkl48vLy2Lhx4wQfFCMjI52do/FTDx48EHQu79u3L++L3NPTU3D+HTp0YNnZ2SJGLrRo0SJejDY2NvImfKJdMjIy2Nq1a5mjo6PKBLBjx47s5MmT8vejPq+VTDTr/fv3ClupALB69eqxBw8eiB2iVqGEUogSSiIglUoVjnw2NDSUD2TRZV988YXg3P7991/59tzcXNatWzfBPlOnTtWa5uSMjAzBAJC5c+eKHRYpQGZmJvP19RWsuZ7/1q5dO3b8+HGFX1pUQ0nULSoqijVs2FDhe2jIkCE06b0ClFAKUUJJFJLJZGzq1KmCD4yBgQH766+/xA6vRN69eycYgFO7dm2WlZUl3ychIUEwiAcA27Bhg4iR/z9FTfOfNt0T7ZaVlcU2bNjAqlWrpjIhbN26NXN0dBR0bSjoVhbWSiaaceTIEYXzqUokEvbDDz/Qmu5KUEIpRAklUUomk7FZs2YpvNDs2rVL7PBK5M8//xSc18qVK3n73LhxQzDi1sjISPSJ3zmOYy1atODF1atXL1FjIsWTnZ3NNm/eXKjJyIuaUOr6WsmkdMlkMoXTqQFgtra27Pjx42KHqNUooRSihJKoxHEc8/LyUviF9ccff4gdXrFxHMc6derEOydzc3MWHx/P22///v2Cc3dwcGBPnjwRKXLGwsLCBDF92mRPdE9OTg7btm0bq1WrVomTybKyVjIpPSkpKaxfv34K3z9NmzZljx8/FjtErUcJpRAllKRAHMex+fPnK7z4bN68Wezwiu3GjRuC0YyKJgVfvHix4LxbtGjBMjIyRIiasbFjx/JiqVWrFk3jUUbk5uayHTt2CFYaKUoyWVbWSial486dO0rfX2PGjGHp6elih6gTKKEUooSSFArHcezLL79UeBFav3692OEV2+zZswXnExISwttHKpUq/DU/evRojfdRe/36NTM2NubF8csvv2g0BlL68vLy2O7duwWrIKlq4i5rayUT9Ttw4ACzsLAQvH8MDQ3Z2rVrqc9tEVBCKUQJJSk0juPYN998o/ALbe3atWKHVyxJSUmCVU0aNGggWFkkNTWV1a1bV3Demk7mVq5cyXt8MzMzGslbhkmlUvbXX3+x+vXrq0wojY2N2fjx4+m9QBTKy8tTOLvFxy48+SfXJwWjhFKIEkpSJBzHsWXLlim8MP36669ih1csW7ZsEZzL77//LtjvwYMHgtGQEolEY8tT5ubmsqpVq/Ief9KkSRp5bCIuqVTK9u3bp3Rql483FxcXtnv3bpaXlyd2yERLJCQkMDc3N4XvlzZt2rCnT5+KHaJOooRSiBJKUiz5a8o+3n788UexQysyqVTKWrVqxTsPa2tr9vLlS8G+R48eFUzhUq5cOfbo0aNSj/PgwYOC5zsyMrLUH5doD5lMxv755x/WuHFjlYmls7Mz27FjB63hreciIyOVziAwZcoU3lRppGgooRSihJIU288//6zwQrV8+XKxQyuyy5cvC87j888/V7jvqlWrBPs2aNCg1Cf/zT/Zert27Ur18Yj2kslkzN/fnzVr1kxlYunk5MS2bdvGcnJyxA6ZaNjOnTuZqampwu4Rmzdvpv6SJUQJpRAllKREfv/9d4VfZN99953OXbAUrQ506dIlwX4cx7ERI0YI9h04cGCpTQJ8584dwePp+gTzpOQ4jmOHDx9mLVu2VJlY1qxZk23evFnrlg8l6peTk6NwsCEAVqVKFXb58mWxQywTKKEUooSSlJiPj4/Ci9fixYt1Kql8/fq1oI9kixYtFE7Jk56ezpo2baowkS4NM2fO5D1OxYoVKTkgchzHsWPHjrE2bdqoTCyrVavG1q9fT02dZdTLly9Zx44dFb72nTt3Zq9evRI7xDKDEkohSiiJWmzYsEHhReyLL77QqaRy7dq1gnPYtGmTwn1jY2MFI8QBMH9/f7XGlJqayiwtLXmP8c0336j1MUjZwHEcO3HiBGvXrp3KxLJKlSrM19eXZWZmih0yUZNLly4JlpT9ePPy8qL+tGpGCaUQJZREbRSNlgbA5s6dqzNJZW5urmAkrZ2dndLpWM6cOcMMDQ15+1taWrLbt2+rLab8NcCGhoY0MpOoxHEcO3XqlNLaqo83R0dHtnbtWtEm6Sclx3Ec27Bhg2B+WuDDtGJ79uwRO8QyiRJKIUooiVrt2LFDMAoaAJszZ06p9S9UtzNnzgjinzlzptL9FTX5Ozk5qWVOQJlMJpj/0sPDo8THJfqB4zh25swZ1qVLF5WJZaVKldhvv/1Gq6TomKysLIV9vz/2m7127ZrYIZZZlFAKUUJJ1G7Pnj2CJQ0BsBkzZuhMUpl/0I1EIlF6ceY4TuFF3c3NrcTzAZ48eVJw3NDQ0BIdk+inc+fOse7du6tMLCtUqMB+/vlnlpaWJna4pABPnjwRTHf28dazZ0+a5L6UUUIpRAklKRV///23wqRyypQpOpFUPnnyRLBEWfv27ZXGnpWVxdq2bSs43/nz55cojkGDBvGO17BhQ53pPkC004ULF1jPnj1VJpb29vZs1apVpT4VFimeM2fOsAoVKih87b766iuFAwmJelFCKUQJJSk1//zzj6B/IfBhfkdduOApmm9y9+7dSvd/8eIFc3R0LNJ9VImLixN0H9i4cWNxT4cQnkuXLrHevXurTCzLly/PVqxYwVJTU8UOl7APrSG//vqrwh/rlpaW7ODBg2KHqDcooRSihJKUKn9/f2ZkZCT44I0dO1brl4fLzs5mzs7Ogr5mqmptwsLCmImJCe8+pqamLCIiosiP/+WXX/KOY2NjQ02RRO3Cw8NZv379VCaW5cqVY0uXLmXJyclih6u30tPT2ahRoxS+Pi4uLuzevXtih6hXKKEUooSSlLojR44oHIE4cuRIrZ/K4tixY4K4FyxYoPI+27dvF9ynatWqRZoDLjMzk9nZ2fGO4eXlVdLTIUSpq1evsoEDB6pMLG1sbNi3337LkpKSxA5Xr0RHRytdbnPgwIFUgywCSiiFKKEkGhEUFKRwGTAPDw+tXxauf//+vJiNjIwKrA3w9PQUnGuHDh0KPRn5zp07Bfd/8OCBOk6HEJWuX7/Ohg4dqjKxtLKyYosXL2YJCQlih1vmBQUFMVtbW8FrIJFI2PLly3WiT3pZRAmlECWURGOCg4OZmZmZ4EM4ePBgrV71JTo6WtCM7ebmpnJwTG5urmDtbQBs2rRpBQ6q4ThOsJSeu7u7uk+LEJVu3rzJhg8frjKxtLS0ZF9++SV78+aN2OGWOTKZjK1YsULhNGzlypVjx44dEztEvUYJpRAllESjQkJCmLm5ueCD2L9/f61eDm7JkiWCmA8dOqTyPm/fvmU1a9YU3K+ggTWXL18W3Ofw4cPqPB1CCu3OnTts1KhRChObjzcLCwu2cOFCWtpPTVJTUwUzPHy8NWrUiD169EjsEPUeJZRClFASjTt79qxgKUEArE+fPlq7FFx6ejqrVq0aL97q1asXuMLIjRs3BAm0kZERO3/+vNL7jBs3jrd/jRo1dGJUPCnb7t27x8aOHatwhPHHm5mZGZs3bx57+fKl2OHqrHv37gkWM/h4GzlyJA3M0xKUUApRQklE8d9//zErKyvBB7Jnz55auwzcgQMHBPF+++23Bd5v//79gvs5ODiwJ0+eCPZ9/fq1oHn9559/Lo3TIaRYHj58yMaPH68ysTQ1NWVeXl7s+fPnYoerUw4ePKjwx7aBgQH79ddfaQ5aLUIJpRAllEQ0YWFhzNraWvCh7N69u1YuAcdxnGClEVNTU/b48eMC7/v1118LzrNFixYsIyODcRzHEhISWFxcHFu8eLHg+DTwgWijR48esYkTJyqca/bjzcTEhM2ePZvWni+AVCplX331lcLn0N7enoWEhIgdIsmHEkohSiiJqK5cucLKlSsn+GB27tyZvX//XuzwBO7evSv4Ah04cGCB95NKpaxv376C82zZsqVgrstPbxMmTCj9kyKkBGJiYtiUKVMUzjf78WZsbMxmzJjB4uPjxQ5X6yQmJjJ3d3eFz1urVq3oOdNSlFAKGYAQEbVt2xZnzpxB+fLleeX//fcf+vTpg/fv34sUmWKNGjWCl5cXr+zo0aM4fvy4yvsZGhri77//Rt26dXnl169fR0xMjNL7tWrVqvjBEqIBtWvXxh9//IHo6GhMnz4dxsbGgn3y8vKwZcsW1KlTB9OmTUNsbKwIkWqfGzduoHXr1jh9+rRg28SJE/Hff/+hZs2aIkRGSDGIndESwtiHwSv29vaCX3yurq4sJSVF7PB4UlNTWcWKFXlx1qlTp1BTHz148ECwRriqm6GhIQsODtbAWRGiHk+ePGGzZs0S9AXO/76eNGkSi46OFjtc0fz5558Kp1EzMjJiGzZsoP6SWo5qKIWohpJohebNm+Ps2bNwcHDglV+5cgXu7u5ITk4WKTKhcuXK4ZdffuGVPX78GGvXri3wvo6OjuA4rtCPxRiDh4cHUlNTixomIaKoUaMGNm7ciJiYGHh6esLU1FSwj0wmw86dO1G/fn1MmDABjx49EiFSceTl5WHu3LkYP348srOzedscHR1x7tw5zJ49GxKJRKQICSkeSiiJ1mjSpAnOnj2LSpUq8cojIyPh5uaGpKQkkSIT+vzzz9GuXTte2cqVK/H8+XOV99u9ezdycnIK/TgcxyEzMxN79uwpVpyEiKVatWrw8/NDbGws5s6dCzMzM8E+MpkMe/bsQYMGDTBu3Dg8ePBAhEg15/Xr13Bzc4Ovr69gW4cOHXDt2jV07NhRhMgIKTlKKIlWadSoEc6dO4fKlSvzym/evInu3bsjISFBpMj4DAwMsH79el4tQmZmJhYtWqT0Powx+Pn5FevxfH19wRgr1n0JEVOVKlWwbt06xMXFYcGCBTA3Nxfsw3Ec9u7di0aNGmHMmDG4d++eCJGWrvDwcLRq1Qr//fefYNvs/2vvzqOqLNf+gX/3Zp4ncSRCUEAJFREEsUw0h9R0k8cGXVH2asdWWuc0nerN3jx68uTK1M7JjvlqWh1Nk+2Eiq9jKQIGGDiAiOI8ME8Cstn374+zfH4+btA9shm+n7VcSy/2vp/LArm47ue57tdfx8GDB9GzZ08rZEZkHiwoqc0JDQ3F4cOH0atXL1k8NzcXI0eOxM2bN62UmVxkZCRmzZoli23cuBGHDh1q9vWlpaUoLCw0uDAUQqCwsLBNbfsTGap79+744osvUFRUhHfffRfOzs46rxFCYOPGjQgPD8e0adOQk5NjhUzNb9WqVXjiiSdw7do1WdzBwQFr167FP//5T9jb21spOyLzYEFJbVLfvn1x+PBhPPLII7L4qVOn8OSTT+L69etWykxu0aJFOk+oz507FxqNRue1NTU1Jl1r8+bNqK2tNWkNImvr2rUrPv/8cxQVFeEvf/kLXF1ddV4jhMDmzZsxcOBAJCQk4MSJE62fqBnU19dj1qxZeO2119DY2Cj72COPPIIjR47g5Zdftk5yRGbGgpLarKCgIBw+fBgBAQGyeF5eHp588klcvXrVOondo0uXLli4cKEsdvLkSXz99dc6r23uG6ch5syZA19fX6hUKqxfv54dS2rXfH198dlnn6GoqAgfffQR3Nzcmn2dWq1GREQEJk+ejMzMzFbO0niXL1/GiBEjsHr1ap2PxcfHIzMzE0OGDLFCZkSWoRC8MYvauEuXLmHkyJE6s+uCgoJw4MAB+Pv7Wymz/2hqasKQIUNkXRQPDw+cPXsWXbt2lWJCCPTt2xfnz583y/2QNjY2GDlyJFQqFaZMmcL7r6hdKy8vx/Lly7Fs2TJUVla2+LoJEyZg/vz5iI6ObsXsDHPo0CFMmzat2Xu+33nnHXz22WewtbW1QmZkLsXFxbJ/3wHg1q1bOpNKOhUrjSsiMsjly5dF3759deZ+BQQEiAsXLlg7PfHrr7/q5DZz5kyd1y1btkwoFAq951Aa8ismJkb8/e9/F2fPnrXCfwEi8ygvLxcLFiwQXl5eD/x8HzdunDh27Ji105XRarVi6dKlzR5H6ezsLDZu3GjtFMlMOIdSFwtKajeuXr0qQkJCdL6I/f39RWFhobXTEzNmzNDJLS0tTfaa8vJy4eLiIpRKpV5FolKpFPb29uKJJ5544JnJ9/8KCwsTH3/8scjKyuKAZGqXKisrxaJFi4S3t/cDP9efeuopceTIEWunK2pra8WLL77YbI5BQUEiJyfH2imSGbGg1MWCktqV69evi/79++t8Ifv5+Vm9M3ft2jXh6uoqy2vIkCGiqalJ9ro9e/YIGxubhxaVSqVS2NjYiJSUFCHEf878/e6778TkyZObPWGjpV8BAQHirbfeEr/88ovQaDTW+E9DZLSqqiqxePFi0aVLlwd+nsfHx4vDhw9bJcfCwkIxYMCAZvN6+umn29xpX2Q6FpS6WFBSu3Pz5k0RHh6u88Xco0cPkZeXZ9XclixZopPXt99+q/O6PXv2CBcXF6FQKHS2wO/GXFxcpGLyfjU1NeLnn38W06dPFx4eHnoXl127dhX/9V//JXbt2qXXUZFEbUV1dbVYsmSJzrGn9/8aMWKEOHDgQKt15nfv3t3i9vz8+fN1fqCkjoEFpS4WlNQuFRcXi0GDBul8QXfr1k2cOnXKank1NDTobMt36dJFlJWV6by2vLxcLF++XAQFBelsjy1fvlxUVFTofc09e/aI1157TXTr1k3v4tLNzU08//zzYtOmTaK6utrc/ymILKK2tlYsXbpUdO/e/YGf38OHDxf/93//Z7HCUqvVikWLFjV7T7S7u7vYtm2bRa5LbQMLSl0sKKndKi0tFYMHD9b5ovb19RW5ublWyyslJUUnpzfeeKPF12u1WlFSUiIuXLggSkpKTPoGqNFoxJEjR8Tbb78tAgMD9S4uHRwcxMSJE8WaNWtEcXGx0dcnai23b98Wy5cvFz179nzg53ZsbKzYs2ePWQvLyspKoVKpmr1ev379rL5TQpbHglIXxwZRu1ZeXo6xY8fi+PHjsriPjw/279+PgQMHWiWvhIQEqNVq6c9KpRJZWVmtmo8QAjk5OVCr1VCr1XqfOqJUKvHEE08gISEBU6ZM0RkuT9SW1NfX43//93+xePFiXLlypcXXDR06FPPnz8f48eNlR6beTwiB0tJS1NTUwNXVFT4+PrLX5+XlQaVSIS8vT+e9zz77LNauXdviTE3qODg2qBnWrWeJTFdRUSFiY2N1flr09vYWmZmZVsnpwoULOg/OPP7441Z94vrcuXNiyZIlYtiwYQaNLhoyZIhYtGiROHPmjNVyJ3qY+vp6sXLlSuHv7//Qz+ft27frfC2Wl5eLZcuWNXsLyrJly0R5eblQq9XCzc1NZ02lUik+++wzTlToRNih1MWCkjqEqqoqMXz4cJ0vcE9PT5GRkWGVnD799FOdfH788Uer5HK/a9euiZUrV4oxY8YIW1tbvYvL0NBQ8cEHH4iMjAx+86Q2qaGhQaxatUoEBAQ88HM5IiJCJCUliaamJr0ekrOzs2t2HW9v7xYfnqOOiwWlLm55U4dRU1ODSZMm4dChQ7K4u7s7UlJSEBMT06r51NXVoX///igqKpJiPXv2RF5eXpvaEisvL0dycjLUajX27NmD27dv6/W+Rx55BFOmTIFKpcLjjz/Okz+oTWlsbMT333+PRYsW6Zyyda/evXvj4sWLAACtVmvQNQYNGoSkpCT07t3bpFyp/Wluy/vmzZs6sU7F2hUtkTnV1taKUaNG6fzk6ObmZpXhx1u3btXJ5b333mv1PPRVW1sr1Gq1eOmllx56Usm9v3x8fMQrr7witm/fLurq6qz91yCSNDY2iu+++0706dNH789nfX7NmDFD1NbWWvuvR1ZQXl4uFi5cqPM5ERAQIN0e0RmxQ0kdTl1dHaZMmYK9e/fK4i4uLkhOTsaIESNaLRchBMaPH4+UlBQpZmdnh9zcXISEhLRaHsZobGzEL7/8gqSkJGzduhXXrl3T632urq4YP348VCoVJkyYAHd3dwtnSvRwGo0GGzduxMKFC5Gfn2/SWs8++yw2b978wId7qGNKSUnBs88+i9u3b+P+8unu54OzszO2bNmCsWPHWiNFq2FBSR1SfX09nn32WezatUsWd3Jyws6dOxEfH99queTn5yM8PByNjY1SbMyYMdizZ0+7+Yak1Wpx/PhxJCUlQa1Wo6CgQK/32dnZYfTo0VCpVJg8eXLn3g6iNqGpqQmbNm3CggULmn1S+2EUCgUCAwNRUFDQbr5+yTxSUlIwYcIECCEeeHuEUqmEQqFAcnJypyoqWVBSh9XQ0IBp06Zh+/btsrijoyO2b9+Op556qtVyef/99/H555/LYmq1GlOmTGm1HMxFCIHTp09LxWV2drZe71MoFBg+fDhUKhVUKhUCAgIsmyjRfaqqqnD27Fnk5+cjKysLS5cuNXqtkpIS+Pj4mDE7assqKirg5+eHuro6ve61VSqVcHJywpUrV+Dp6Wn5BNsAFpTUod25cwfPP/+8bCYkADg4OECtVmP8+PGtkkd1dTVCQ0Nl28YBAQE4ffo0nJycWiUHSykqKsLWrVuRlJSEI0eO6GwDtSQiIkIqLsPCwtjtIbPQaDS4cOEC8vPzpeLx7q8bN26Y7ToXLlzgD0WdxJ07d7BkyRJ8/PHHev/7Bvznh+hly5Zh3rx5Fsyu7WBBSR1eY2Mjpk+fjs2bN8vi9vb2+PnnnzFp0qRWyePf//43pk+fLov9z//8Dz755JNWuX5ruHXrFrZv346kpCTs378fd+7c0et9ffr0QUJCAlQqFaKjo6FUKi2cKbVnQgiUlJTIisW7xWNhYaHs9hJLYYeyfRBC4Pbt26ioqEBlZSUqKipkv28udv/v6+rqjLp2Z7s9ggUldQoajQYvvfQSNmzYIIvb2dlh06ZNrbL1LITAiBEj8Ouvv0oxR0dHnDlzpkN2OqqqqrBr1y6o1WokJyejtrZWr/f17NlTGkc0YsQI2NnZWThTaqvq6+tx7ty5ZgvH8vJyq+TU2YoEa2tqakJVVZVehV9LRaJGo7Hq36Gz/PDBgpI6jaamJrzyyiv4/vvvZXFbW1ts2LABU6dOtXgOOTk5iIiIkN2Do1KpkJSUZPFrW1N9fT327dsHtVqNbdu2obS0VK/3eXl5YeLEiUhISMCYMWPg7Oxs4UyptQkhcPXqVVnReLdwLCoqMmiLUR9KpRIBAQEICQnB7du3cfjwYYPe39m2MU3V0NBgUnewurra2n8Fk3WW2yNYUFKn0tTUhFmzZmHt2rWyuI2NDX788Uc899xzFs9h7ty5+Mc//iGLpaSkYMyYMRa/dlug0Whw5MgR6Yzxy5cv6/U+JycnjBs3DgkJCZg4cWKnudG9o6iurm72vsazZ8/qPUzfED4+PggODkZISIjsV1BQEBwcHADwQYuHEUKgpqbGoCLw/lh9fb21/xpWxw4lUQel1Wrxxz/+Ed9++60srlQqsW7dOsyYMcOi1y8vL0dwcDBKSkqkWEhICHJycmBvb2/Ra7c1QghkZmZCrVYjKSlJ7zEutra2GDlyJBISEjB58mT06NHDwpmSPjQaDYqKipotHK9fv27269nb26NPnz4ICQnRKR71/QZu6CiYXbt2tZsf/jQaDSorKw0uAu/9vaGnB7V1NjY20Gq1Zu98N6ez3R7BgpI6Ja1WizfeeAMrV66UxRUKBdauXYvExESLXn/16tWYNWuWLLZkyRK88847Fr1uW5eXlyd1Lo8fP67XexQKBWJiYqSHeoKCgiycJbX0QMy5c+cs8kBMz549pULx3sLx0UcfNcuRn/cOqwYgKzbuHVadlJTUasWkEAL19fUGbxHf+9qamppWybW1KJVKeHh4wNPTE56eni3+XqlU4vr16zh//jzOnDmDvLw8oz4vbWxsMGjQIMTFxaGyshLr16/nU94PwIKSOi0hBN566y2sWLFCFlcoFPj222/x6quvWuzaWq0WMTExsqLJ1dUV+fn56Nmzp8Wu255cvnwZW7duhVqtxuHDh/XulISHh0OlUiEhIQEDBgzoFJ0BS2hoaNB5IOZu8VhWVmb267m4uOh0GYODgxEcHAw3NzezX+9+FRUVWL9+PVasWIHCwkIpHhQUhHnz5iExMREeHh56r6fValFdXW1Sd1DfKQnthaOjY7NFoD5FooeHB1xdXXW+noUQKCgowJEjR3D06FEcPXrU6JOQXF1dERsbi+HDhyMuLg5Dhw6Fq6srAN4eoQ8WlNSpCSHwzjvvNDvgeOXKlfjjH/9osWunp6cjJiZGFps+fTp++OEHi12zvSopKcGOHTugVquxd+9eNDQ06PW+3r17S8VlbGwsxxHdRwiBa9eu6RSN+fn5uHjxotm3OxUKhfRAzP2FY69evdpE8S+EQFlZGUpLSyGEgFKp1Cn+9OkUVlVVtcq2amtyc3PTq/BrLubh4QFHR0eTc2hoaEBWVhaOHj2KI0eOIDU1FcXFxUat5efnJxWPw4cPR3h4OGxsbFp8fUe+PcIcWFBSpyeEwAcffIC///3vOh/76quv8MYbb1js2q+++irWrFkji/3yyy94/PHHLXbN9q66uhp79uyBWq3Gzp079X4KtFu3bpg8eTJUKhXi4+M71f2q1dXVOHv2bLMPxOg7zskQXl5eOkXj3QdizFFUPMzd2YOmjJqxxINC1mRra2tSd9Dd3f2BxZallJWVITU1VSogjx8/rvcPlPdSKBQYMGCAVEDGxcXB39/f4HXa4u0RbQULSiL85x+F+fPnY+HChTofW7p0Kf70pz9Z5Lq3bt1CcHAwKisrpdjAgQORmZlplX+825uGhgYcOHAAarUaW7du1btT4eHhgQkTJkClUmHcuHHStpahhBAoLS1FTU0NXF1d4ePjY7UuW1NTk/RAzP0Pxdx7QpO52NnZtfhATJcuXUxa+0GzB/UtEq09e9DcnJ2d9S4Cm4s5Ozu3iQ7wgwghcP78eal4PHr0KE6fPm3UWs7OzoiJiZG6jzExMXB3dzdLnua+PaKjYEFJdI8FCxY0e3LN559/jnfffdci11yxYgXefPNNWeyf//wnXn/9dYtcr6NqampCamqq9FBPUVGRXu9zdHTEmDFjoFKpMGnSJL2eDq6oqMC6devw1Vdf6XxDmTt3LhITEy1231RpaWmLD8RY4p67Hj16NPtATEBAQIsPxDQ0NJjUHayqqjL738OaFAoF3N3dDS4C790u7ogd9cbGRmRnZ8sKyJs3bxq1Vo8ePWTdx4EDB1r8UIS7t0dUV1fDzc0N3t7ebb5otyQWlET3WbRoEf77v/+72fiHH35o9utpNBpERETg5MmTUszLywtnz541udPTWQkhcOLECam4vPe/7YPY2NhgxIgRUKlUmDJlCvz8/HReo++W15YtWzB27Fij8m9oaEBhYWGzhaO+Q+EN4ezsLBWLwcHBePTRR9G9e3f4+PhIo2cM6Q52tNmDdnZ2et872FyR6Obmxvt3AVRWVuLYsWNS8Zienm7UsYYKhQJhYWFS9zEuLg4BAQGduphrC1hQEjXj888/x/vvv68T//TTTzF//nyzX+/w4cN48sknZbHZs2fjX//6l9mv1RkVFBRIxWVaWpre74uOjoZKpYJKpUJISIjBN+UnJye3WFTefSDm/vsa8/PzUVRUZJEHYry8vODl5QU3Nzc4OjpKM/nq6uqkeYWVlZVoamoy67WtzcXFxejuoKenJxwdHVmsGEgIgYsXL8q6jydPnjTqQSVHR0cMHTpU6j7GxsbCy8vLAlmTKVhQErXgyy+/xJ///Ged+Mcff4xPP/3U7N9gXnjhBWzcuFH6s0KhQEZGBoYMGWLW63R2V69exbZt26BWq3Hw4EG9i6eQkBCcP38eGo1Gr2+Kd8eG5OXl4datW80+ENPR5gRawr2zB43pDrq7u/M8+Fag0Wjw+++/S6N7jhw5YvS9u127dpV1HyMiIjrkln9Hw4KS6AG++uqrZofS/uUvf8Hf/vY3sxaVV65ckc4Xvmvo0KFITU3ldpmFlJWVYefOnVCr1UhJSTFq+40ezMHBwaTuYHOzB8n6qqurkZaWJnUf09LSjJ4Y0K9fP6n7OHz4cAQFBfH/eTvEgpLoIVauXNnsAzJvv/02lixZYtZ/+BYvXowPPvhAFlu7di1efvlls12DmldbW4uUlBSo1Wrs2LFD9uR9Z9bc7EF9u4Pmmj1I1nf58mVZ9zEnJ8eo2zLs7e0RFRUldR+HDRvWKc657gxYUBLp4dtvv8Vrr72ms9X55ptv4ssvvzRbUdnQ0IDw8HAUFBRIsa5du+Ls2bOdcgyFtdy5cweHDh2SxhHduHHD2ikZxcbGxuAt4vu3izm+qvNpamrCyZMnZafPXLp0yai1fHx8ZN3HyMhIODg4mDljagtYUBLp6bvvvsPMmTN1isrXX38dX331ldm2pXfv3o2nn35aFnvrrbfw5ZdfmmV9MoxWq4VarcbUqVNb/dpOTk4Gdwfv/X17mD1I1ldbW4v09HSp+5iWlmb06Ka+ffvKxveEhITwc7CTYEFJZIAffvgBiYmJOls9s2fPxsqVK81WVD7zzDPYsWOH9GcbGxucOHECjz32mFnWJ8OUlJTA19fX6PeHhoaia9euBnUHO+rsQbK+a9euSZ3Ho0ePIjs726gn++3s7BAZGSl1H4cNG4auXbtaIGNqD1hQEhlo48aNmDFjhs4/wDNnzsSqVavMskVYWFiIsLAw2RFjI0eOxP79+/nTvhUIIdC3b1+cP3/eoLEnCoUCgYGBKCgo4P83sgqtVovTp0/LxvdcuHDBqLU8PT2lzmNcXByioqLg5ORk5oypvWr+mAMiatHzzz8PGxsbvPjii7Lj3dasWYPGxkasXbvW5KIyKCgI7733Hv76179KsYMHD2Lz5s2YNm2aSWuT4RQKBebOnWvUEZzz5s1jMUmtpq6uDhkZGVL3MTU1FRUVFUatFRgYKBvf069fP06coBaxQ0lkJLVajeeeew6NjY2y+Isvvoh169a1eCydvm7fvo1+/frJbob38/NDXl4eXFxcTFqbDFdRUQE/Pz/U1dXp9XTr3TmUV65cgaeFjmEkunXrlqz7mJWVpfNvkj5sbGwwePBgWQeyR48eFsiYOioWlEQm2LFjB6ZOnapzhvK0adPwww8/mDxQecuWLToPg3z44YdYtGiRSeuScQw9KWfXrl0YM2ZMK2ZIHZkQAnl5ebLxPefOnTNqLXd3d8TGxkrdx+joaP6gSiZhQUlkot27d0OlUsnudwSAhIQEbNiwwaQHK4QQeOqpp7B//34pZm9vj1OnTqFPnz5Gr0vG0/cs76SkJBaTZJL6+npkZmZK3cfU1FSjz3J/9NFHZeN7wsLCOBKKzIoFJZEZ7N27F5MnT0Z9fb0s/swzz2DTpk0mzV07ffo0Bg4cKLtfc8KECdi5c6fRa5JpKioqsH79eqxYsQKFhYVSPCgoCPPmzUNiYiLnhpLBSkpKkJqaKnUff/vtN53dD30olUoMHDhQNr7Hz8/PAhkT/X8sKInMZP/+/Zg0aZLO8X1PP/00tmzZYtKJIW+//TaWLl0qi+3YsQMTJ040ek0ynRACZWVlqK6uhpubG7y9vfkADulFCIFz587Jhofn5eUZtZarqytiYmKk7uPQoUPh5uZm5oyJHowFJZEZHT58GBMmTNA503bs2LFQq9VGj9ioqqpCcHAwbt68KcWCgoJw8uRJHm1H1A7cuXMHWVlZsgdoiouLjVqrV69esu7jgAEDTH4IkMhULCiJzOzIkSMYP348ampqZPHRo0dj27ZtcHZ2Nmrd9evXIzExURZbuHAhPvroI6NzJSLLKC8vl7avjx49ioyMDJ1bYvShUCgQHh4uG9/j7+/PTji1OSwoiSzg2LFjGDdunM7xZU8++SR27NgBV1dXg9fUarV4/PHHkZqaKsWcnJyQl5cHf39/k3MmIuMIIXDhwgVZ9/HUqVNGreXk5CTbvo6JieH9uNQusKAkspCMjAyMHTtWZ6jw448/juTkZKPuccrOzkZkZKTsyeI//OEP2LRpk6npEpGeGhsbceLECdn4nhs3bhi1Vvfu3WXdx0GDBpk8bozIGlhQEllQVlYWRo8ejfLycll82LBh2L17N9zd3Q1ec86cOfjmm29ksX379mHUqFEm5UpEzausrERaWprUfUxPT5fGRhkqLCxMNr6nd+/e3L6mDoEFJZGF/f777xg1apTO/Ljo6GikpKQYfIpKaWkpgoODUVZWJsX69++PEydOsLNBZCIhBC5duiTrPubm5hp0hvtdjo6OiIqKkrqPsbGx8Pb2tkDWRNbHgpKoFeTm5mLUqFE6T3VGRkZi7969Bn+T+eabbzBnzhxZbOnSpUadNU3UmWk0GuTm5srG91y5csWotXx9fWXb14MHDzbpYAOi9oQFJVErOX36NOLj42WjfwBg0KBB2LdvH3x8fPReq6mpCVFRUcjOzpZi7u7uyM/PR/fu3c2WM1FHU11djfT0dKn7mJaWpjORQV+hoaGy7es+ffpw+5o6LRaURK0oLy8P8fHxuH79uiweHh6O/fv3w9fXV++1UlNTERcXJ4slJibiu+++M0eqRB3ClStXpM7j0aNHceLEiQeew94Se3t7DBkyROo+Dhs2DF26dLFAxkTtEwtKolZWUFCA+Ph4nW21sLAw7N+/H926ddN7rcTERKxfv14WS01NRWxsrFlyJWpPmpqacOrUKdn4nosXLxq1lre3t6z7GBkZyUMEiB6ABSWRFZw/fx4jR47EpUuXZPHQ0FAcOHAAPXr00GudGzduIDg4GNXV1VJs8ODByMjIgI2NjVlzJmpramtrkZGRIXUfU1NTdWa/6qtPnz6y02dCQkKgVCrNnDFRx8WCkshKioqKMHLkSBQVFcniffv2xYEDB+Dn56fXOkuXLsXbb78ti/3rX//C7NmzzZUqUZtw48YNWfcxOzsbGo3G4HVsbW0RGRkpdR+HDRtm0M4AEeliQUlkRZcuXUJ8fDwKCwtl8cDAQBw8eFCvE3AaGxsxcOBAnDlzRop5e3vj7NmzBj3oQ9SWaLVanDlzRja+5/z580at5eHhIXUe4+LiEBUVZfQRqETUPBaURFZ29epVjBw5EgUFBbJ4QEAADh48iICAgIeusX//fowePVoWmzNnDr7++mtzpkpkMXV1dTh+/Lhs+/r+AwH01bt3b9n4nv79+3P7msjCWFAStQHXr19HfHw88vLyZHF/f38cOHAAQUFBD13jD3/4A37++Wfpz0qlEr/99hsiIiLMni+RqYqLi2Xdx8zMTDQ2Nhq8jo2NDSIiImQdyJ49e1ogYyJ6EBaURG3EzZs3ER8fj9OnT8vivXr1wsGDB9G3b98Hvv/SpUsIDQ1FXV2dFIuLi8Ovv/7K2XhkVUII5Ofny8b3nD171qi13NzcEBsbK3Ufo6Oj4erqauaMichQLCiJ2pDi4mKMGjUKubm5sniPHj1w8OBBhISEPPD9CxcuxMcffyyLff/995gxY4bZcyVqSUNDAzIzM6XuY2pqKkpKSoxay9/fXza+57HHHuMEA6I2iAUlURtTUlKCp556CidOnJDFu3XrhgMHDqB///4tvre+vh5hYWGyhxe6d++O/Px8uLu7Wypl6uRKS0uRmpoqdR+PHz+OhoYGg9dRKpUYMGCAbHzPI488YoGMicjcWFAStUFlZWUYM2YMMjMzZXFfX1/s378f4eHhLb53x44deOaZZ2Sxd955B0uWLLFIrtS5CCFQWFgoO/v63gkDhnBxcUFMTIzUfRw6dCh/8CFqp1hQErVRFRUVGDt2LDIyMmRxHx8f7Nu3D4MGDWr2fUIITJw4Ebt27ZJitra2yMnJQb9+/SyZMnVAd+7cQXZ2tmz+461bt4xaq2fPnrLu48CBA2Fra2vmjInIGlhQErVhlZWVGD9+PI4dOyaLe3l5Yd++fRg8eHCz7ysoKMBjjz2GO3fuSLHRo0dj7969fECHHqiiokK2fZ2RkSF70EtfCoUCjz32mGx8z6OPPsrPP6IOigUlURtXXV2NCRMm4Ndff5XFPT09sXfvXkRFRTX7vg8//BCfffaZLLZlyxYkJCRYLFdqX4QQKCoqknUfT506BWO+LTg5OWHo0KFS9zE2Nhaenp7mT5qI2iQWlETtQG1tLSZOnIhDhw7J4u7u7tizZw9iY2N13lNTU4PQ0FBcvXpVivn7++PMmTM8JaST0mg0OHHihGz+4/Xr141aq1u3brLuY0REBOzs7MycMRG1FywoidqJ27dvY/Lkydi3b58s7urqit27d2P48OE67/npp5/w/PPPy2Lz58/Hp59+atFcqW2oqqpCWlqa1H1MT09HbW2tUWv1799fNr4nMDCQ29dEJGFBSdSO1NXVQaVSISUlRRZ3cXFBcnIyRowYIYsLIRAfHy/rbDo4OOD06dMIDAxsjZSpFV26dEk2PDwnJwdardbgdRwcHBAVFSV1H2NjY3kuPBE9EAtKonamvr4eU6dORXJysizu5OSEnTt3Ij4+XhbPzc1FREQEmpqapNjkyZOxdevW1kiXLKSpqQm5ubmy8T2XL182aq0uXbrIuo+DBw+Gg4ODmTMmoo6MBSVRO9TQ0IDnnnsO27Ztk8UdHR2xbds2jBkzRhZ/8803sWLFClls9+7dGDdunMVzJfOoqalBenq6dO9jWloaqqurjVorODhYNr4nODiY29dEZBIWlETt1J07d/DCCy8gKSlJFndwcEBSUhKefvppKVZRUYHg4GAUFxdLsb59+yI3N5edqDbq6tWrsu3rEydOyLrM+rKzs8OQIUOk7uOwYcPg6+trgYyJqDNjQUnUjjU2NmL69OnYvHmzLG5vb4+ff/4ZkyZNkmJr167FzJkzZa9bvHgx3n///VbJlVqm1Wpx6tQp2fieoqIio9by8vKSOo9xcXEYMmQInJyczJswEdF9WFAStXMajQaJiYn497//LYvb2dnhp59+gkqlAvCfomXYsGFIT0+XXuPi4oL8/Hz06tWrVXPu7G7fvo2MjAyp+5iamorKykqj1goKCpKN7wkNDYVSqTRzxkRED8aCkqgDaGpqwsyZM7F+/XpZ3NbWFhs2bMDUqVMBAMePH8fQoUNlg6tfeOEFnWKUzOvmzZuy7mNWVhY0Go3B69ja2mLw4MGyDmT37t0tkDERkWFYUBJ1EE1NTZg9ezbWrFkji9vY2OCHH36Q5lHOmjULq1evlr3m0KFDOiOHyDharRZ5eXmy4eGFhYVGreXh4YHY2Fip+xgdHc2h9ETUJrGgJOpAtFot5syZg1WrVsniSqUS69atw4wZM1BcXIzg4GBUVFRIHw8PD0dWVhZsbW1bOeP2r76+Hr/99pvUfUxNTUVZWZlRawUEBMjG94SFhXH7mojaBRaURB2MVqvF3Llz8fXXX8viCoUCa9aswcsvv4x//OMfmDt3ruzjK1as0ImRruLiYqSmpkrdx8zMTNy5c8fgdZRKJQYNGiQb38N7WYmovWJBSdQBCSHwpz/9CcuXL5fFFQoFVq1ahZdffhmRkZHIycmRPubp6Yn8/Hx07dq1tdNts4QQKCgokA0Pz8/PN2otV1dXxMbGSt3HoUOHwtXV1cwZExFZBwtKog5KCIF3330XX3zxhc7Hvv76a4SFhencN/nqq6/q3F/ZmTQ0NCArK0vqPqampspmdxrCz89P1n0MDw/nLQVE1GGxoCTqwIQQ+PDDD7F48WKdj61YsQJpaWmyJ7wVCgXS0tIQHR3dmmlaTVlZmbR9ffToUWRkZKChocHgdRQKBQYMGCAb3+Pv72+BjImI2iYWlEQdnBACn3zyCf7617/qfOyTTz7BF198gZqaGikWFRWFtLS0DvcwiBAC58+fl43vOX36tFFrOTs7IyYmRuo+xsTEwMPDw8wZExG1HywoiTqJBQsW4JNPPtGJjx8/Hrt375bFVq9ejVdffbW1UrOIxsZGZGdny8b33Lx506i1evToIdu+HjhwIOzs7MycMRFR+8WCkqgT+dvf/oaPPvpIJ+7j44PS0lLpz76+vsjPz4eXl1drpmeSyspKHDt2TOo+pqeno66uzuB1FAoFwsLCZON7AgICoFAoLJA1EVHHwIKSqJNZsmQJ3nvvvYe+bu7cuVixYkUrZGQ4IQQuXrwo6z6ePHkSxvxz5ujoiOjoaKkDGRsb264KaSKitoAFJVEn9OWXX+LPf/7zA1+jVCqRnZ2NAQMGtFJWLdNoNMjJyZGN77l69apRa3Xt2lXWfYyIiIC9vb2ZMyYi6lxYUBJ1Us0NN7/fE088gUOHDrX6dm91dTXS0tKk7mNaWhpqa2uNWis0NFTqPg4fPhxBQUHcviYiMjMWlESd2DfffIM5c+Y88DUbNmzAc889h9LSUtTU1MDV1RU+Pj5mLcquXLki6z7+/vvv0Gq1Bq9jb2+PqKgoqXgcNmwYfHx8zJYnERE1jwUlUSe3evVqzJ49u8X7D93d3eHj44MLFy5IsaCgIMydOxeJiYnw9PQ06HpNTU04efKkbHzPpUuXjMrdx8dHtn0dGRkJBwcHo9YiIiLjsaAkIqxbtw6vvPKK3g+13O1OOjs7Y8uWLRg7dmyLr62trUV6errUfTx27BiqqqqMyrNv376y8T0hISHcviYiagNYUBIRAODHH3/ESy+9ZNBWs1KphEKhQHJyslRUXr9+XdZ9zM7ORlNTk8H52NnZITIyUrZ9zXPGiYjaJhaURCT56aef8OKLLxpUVCoUCtjb22PKlCnIyMiQbY0bwtPTU+o8xsXFISoqCk5OTkatRURErYsFJRHJzJw5E2vXrrX4dQIDA2VnX/fr16/DHfdIRNRZ2Fo7ASJqO4QQ+OWXX8y+ro2NDQYPHizrQPbo0cPs1yEiIutgh5KIJCUlJfD19TV5HXd3d8TGxkrdx+joaLi4uJghQyIiaovYoSQiSU1NjUnvX7BgASZPnoywsDDY2NiYKSsiImrr2KEkIompHcqSkhIOEici6oR4BzwRSXx8fIw6mlChUCAoKAje3t4WyoyIiNoyFpREJFEoFA8937sl8+bN45BxIqJOilveRCRTUVEBPz8/1NXV6TWPUqlUwsnJCVeuXDH4GEYiIuoY2KEkIhlPT09s2bIFCoXioXMh756Uk5SUxGKSiKgTY0FJRDrGjh2L5ORkODk5QaFQ6Gxl3405OTlh165dGDNmjJUyJSKitoAFJRE1a+zYsbhy5QqWLVuGwMBA2ccCAwOxbNkyXL16lcUkERHxHkoiejghBMrKylBdXQ03Nzd4e3vzARwiIpKwoCQiIiIik3DLm4iIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITMKCkoiIiIhMwoKSiIiIiEzCgpKIiIiITPL/AJz2kaskR083AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "G = nx.dodecahedral_graph()\n",
    "shells = [[2, 3, 4, 5, 6], [8, 1, 0, 19, 18, 17, 16, 15, 14, 7], [9, 10, 11, 12, 13]]\n",
    "nx.draw_shell(G, nlist=shells, **options)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d883d5f7",
   "metadata": {},
   "source": [
    "To save drawings to a file, use, for example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6ce05699",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:54.115130Z",
     "iopub.status.busy": "2023-02-26T01:59:54.114723Z",
     "iopub.status.idle": "2023-02-26T01:59:54.335882Z",
     "shell.execute_reply": "2023-02-26T01:59:54.335264Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw(G)\n",
    "plt.savefig(\"path.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cb4ddfe",
   "metadata": {},
   "source": [
    "This function writes to the file `path.png` in the local directory. If Graphviz and\n",
    "PyGraphviz or pydot, are available on your system, you can also use\n",
    "`networkx.drawing.nx_agraph.graphviz_layout` or\n",
    "`networkx.drawing.nx_pydot.graphviz_layout` to get the node positions, or write\n",
    "the graph in dot format for further processing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4da90442",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-26T01:59:54.339196Z",
     "iopub.status.busy": "2023-02-26T01:59:54.338506Z",
     "iopub.status.idle": "2023-02-26T01:59:54.490351Z",
     "shell.execute_reply": "2023-02-26T01:59:54.489775Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from networkx.drawing.nx_pydot import write_dot\n",
    "pos = nx.nx_agraph.graphviz_layout(G)\n",
    "nx.draw(G, pos=pos)\n",
    "write_dot(G, 'file.dot')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "259ad362",
   "metadata": {},
   "source": [
    "See Drawing for additional details.\n",
    "\n",
    "# NX-Guides\n",
    "\n",
    "If you are interested in learning more about NetworkX, graph theory and network analysis\n",
    "then you should check out [nx-guides](https://networkx.org/nx-guides/index.html). There you can find tutorials,\n",
    "real-world applications and in-depth examinations of graphs and network algorithms.\n",
    "All the material is official and was developed and curated by the NetworkX community."
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}