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",
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   "id": "cef8525c",
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   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "G = nx.Graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c89a63e1",
   "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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   "id": "2d14bc17",
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   "outputs": [],
   "source": [
    "G.add_node(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86d31597",
   "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": "c94f91f4",
   "metadata": {
    "execution": {
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   },
   "outputs": [],
   "source": [
    "G.add_nodes_from([2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3bb8f77",
   "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": "02cbbc70",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "H = nx.path_graph(10)\n",
    "G.add_nodes_from(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb2c969c",
   "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": "ac9270c8",
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   "source": [
    "G.add_node(H)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13828256",
   "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": "a8284de6",
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   "source": [
    "G.add_edge(1, 2)\n",
    "e = (2, 3)\n",
    "G.add_edge(*e)  # unpack edge tuple*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5cffab",
   "metadata": {},
   "source": [
    "by adding a list of edges,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "434d2f22",
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    "execution": {
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     "shell.execute_reply": "2023-02-23T15:29:15.907461Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edges_from([(1, 2), (1, 3)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65f9fc56",
   "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": "54bfa016",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-02-23T15:29:15.914631Z"
    }
   },
   "outputs": [],
   "source": [
    "G.add_edges_from(H.edges)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "302b1072",
   "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": "191ec7af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:15.919100Z",
     "iopub.status.busy": "2023-02-23T15:29:15.918584Z",
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    }
   },
   "outputs": [],
   "source": [
    "G.clear()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bafe4169",
   "metadata": {},
   "source": [
    "we add new nodes/edges and NetworkX quietly ignores any that are\n",
    "already present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c0011fb9",
   "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": "acde4534",
   "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": "401d89be",
   "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": "5b28cc93",
   "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": "b66f2b7b",
   "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": "b44501af",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-02-23T15:29:15.962484Z"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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": "7b82fc28",
   "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": "8ca5a782",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:15.966483Z",
     "iopub.status.busy": "2023-02-23T15:29:15.966195Z",
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     "shell.execute_reply": "2023-02-23T15:29:15.973692Z"
    }
   },
   "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": "02b3e41c",
   "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": "a36cce3a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:15.978014Z",
     "iopub.status.busy": "2023-02-23T15:29:15.977569Z",
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     "shell.execute_reply": "2023-02-23T15:29:15.983120Z"
    }
   },
   "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": "1e28330a",
   "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": "9d0879b5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:15.988190Z",
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     "shell.execute_reply": "2023-02-23T15:29:16.333541Z"
    }
   },
   "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": "b6c57366",
   "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": "4b6b4cc9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.338419Z",
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     "shell.execute_reply": "2023-02-23T15:29:16.345502Z"
    }
   },
   "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": "4ef3c002",
   "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": "3af8cd3d",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-02-23T15:29:16.356822Z"
    }
   },
   "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": "a38aad14",
   "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": "78900827",
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    "execution": {
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     "shell.execute_reply": "2023-02-23T15:29:16.367886Z"
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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": "175a41b6",
   "metadata": {},
   "source": [
    "Convenient access to all edges is achieved with the edges property."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d0230f15",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.372031Z",
     "iopub.status.busy": "2023-02-23T15:29:16.371746Z",
     "iopub.status.idle": "2023-02-23T15:29:16.376487Z",
     "shell.execute_reply": "2023-02-23T15:29:16.375749Z"
    }
   },
   "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": "44de1952",
   "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": "303386dd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.379819Z",
     "iopub.status.busy": "2023-02-23T15:29:16.379537Z",
     "iopub.status.idle": "2023-02-23T15:29:16.387224Z",
     "shell.execute_reply": "2023-02-23T15:29:16.386306Z"
    }
   },
   "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": "b96ad4a8",
   "metadata": {},
   "source": [
    "Or you can modify attributes later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "55ece8fb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.390672Z",
     "iopub.status.busy": "2023-02-23T15:29:16.390390Z",
     "iopub.status.idle": "2023-02-23T15:29:16.397904Z",
     "shell.execute_reply": "2023-02-23T15:29:16.396982Z"
    }
   },
   "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": "d0ee2386",
   "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": "7490d9bc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.401446Z",
     "iopub.status.busy": "2023-02-23T15:29:16.401162Z",
     "iopub.status.idle": "2023-02-23T15:29:16.407975Z",
     "shell.execute_reply": "2023-02-23T15:29:16.407077Z"
    }
   },
   "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": "aa13f2c9",
   "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": "086fe04c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.411602Z",
     "iopub.status.busy": "2023-02-23T15:29:16.411311Z",
     "iopub.status.idle": "2023-02-23T15:29:16.416923Z",
     "shell.execute_reply": "2023-02-23T15:29:16.415993Z"
    }
   },
   "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": "d79874d3",
   "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": "14fab3bc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.420565Z",
     "iopub.status.busy": "2023-02-23T15:29:16.420048Z",
     "iopub.status.idle": "2023-02-23T15:29:16.430712Z",
     "shell.execute_reply": "2023-02-23T15:29:16.429747Z"
    }
   },
   "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": "c7dd6481",
   "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": "07fb35fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.434754Z",
     "iopub.status.busy": "2023-02-23T15:29:16.434184Z",
     "iopub.status.idle": "2023-02-23T15:29:16.439535Z",
     "shell.execute_reply": "2023-02-23T15:29:16.438635Z"
    }
   },
   "outputs": [],
   "source": [
    "H = nx.Graph(G)  # create an undirected graph H from a directed graph G"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cda3f7d",
   "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": "8d607698",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.443235Z",
     "iopub.status.busy": "2023-02-23T15:29:16.442734Z",
     "iopub.status.idle": "2023-02-23T15:29:16.451526Z",
     "shell.execute_reply": "2023-02-23T15:29:16.450641Z"
    }
   },
   "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": "1274128a",
   "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": "bf4e008d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.454896Z",
     "iopub.status.busy": "2023-02-23T15:29:16.454393Z",
     "iopub.status.idle": "2023-02-23T15:29:16.461601Z",
     "shell.execute_reply": "2023-02-23T15:29:16.460519Z"
    }
   },
   "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": "673279c6",
   "metadata": {},
   "source": [
    "# 4. Using a stochastic graph generator, e.g,\n",
    "\n",
    "like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "fd2feef4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.465145Z",
     "iopub.status.busy": "2023-02-23T15:29:16.464785Z",
     "iopub.status.idle": "2023-02-23T15:29:16.478097Z",
     "shell.execute_reply": "2023-02-23T15:29:16.475533Z"
    }
   },
   "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": "703ea6be",
   "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": "bb8090e6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.481897Z",
     "iopub.status.busy": "2023-02-23T15:29:16.481379Z",
     "iopub.status.idle": "2023-02-23T15:29:16.536664Z",
     "shell.execute_reply": "2023-02-23T15:29:16.534820Z"
    }
   },
   "outputs": [],
   "source": [
    "nx.write_gml(red, \"path.to.file\")\n",
    "mygraph = nx.read_gml(\"path.to.file\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "973a9b9f",
   "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": "26e8238c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.541031Z",
     "iopub.status.busy": "2023-02-23T15:29:16.540700Z",
     "iopub.status.idle": "2023-02-23T15:29:16.550387Z",
     "shell.execute_reply": "2023-02-23T15:29:16.549539Z"
    }
   },
   "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": "1def3479",
   "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": "58e06fa5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.553893Z",
     "iopub.status.busy": "2023-02-23T15:29:16.553608Z",
     "iopub.status.idle": "2023-02-23T15:29:16.562098Z",
     "shell.execute_reply": "2023-02-23T15:29:16.561243Z"
    }
   },
   "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": "14a94ada",
   "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": "07f88ce4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:16.565695Z",
     "iopub.status.busy": "2023-02-23T15:29:16.565381Z",
     "iopub.status.idle": "2023-02-23T15:29:17.065924Z",
     "shell.execute_reply": "2023-02-23T15:29:17.064831Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9234a34",
   "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": "43e21e1a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:17.070577Z",
     "iopub.status.busy": "2023-02-23T15:29:17.069507Z",
     "iopub.status.idle": "2023-02-23T15:29:17.446274Z",
     "shell.execute_reply": "2023-02-23T15:29:17.445345Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\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": "e7940816",
   "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": "bad8ba76",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:17.450067Z",
     "iopub.status.busy": "2023-02-23T15:29:17.449768Z",
     "iopub.status.idle": "2023-02-23T15:29:17.454467Z",
     "shell.execute_reply": "2023-02-23T15:29:17.453666Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b162725",
   "metadata": {},
   "source": [
    "command if you are not using matplotlib in interactive mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8a183e56",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:17.457938Z",
     "iopub.status.busy": "2023-02-23T15:29:17.457325Z",
     "iopub.status.idle": "2023-02-23T15:29:18.000610Z",
     "shell.execute_reply": "2023-02-23T15:29:17.999532Z"
    }
   },
   "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": "d91f5713",
   "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": "7635ed9d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:18.004939Z",
     "iopub.status.busy": "2023-02-23T15:29:18.004160Z",
     "iopub.status.idle": "2023-02-23T15:29:18.194154Z",
     "shell.execute_reply": "2023-02-23T15:29:18.193290Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\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": "22d018cc",
   "metadata": {},
   "source": [
    "To save drawings to a file, use, for example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "47c0c750",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:18.198557Z",
     "iopub.status.busy": "2023-02-23T15:29:18.198073Z",
     "iopub.status.idle": "2023-02-23T15:29:18.430655Z",
     "shell.execute_reply": "2023-02-23T15:29:18.429661Z"
    }
   },
   "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": "cc4da952",
   "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": "34997105",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-23T15:29:18.434588Z",
     "iopub.status.busy": "2023-02-23T15:29:18.434226Z",
     "iopub.status.idle": "2023-02-23T15:29:18.734147Z",
     "shell.execute_reply": "2023-02-23T15:29:18.733295Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rx9bW1tYV+rf+MzS/mhAqlEQFMAyDq1evwt/fH1evXoWZmRnmz5+PgQMHlvmx1o88zviMhXsvIuLZR2jo1f9qt0oO/t603MW0DgY7GtGjK6LwhEIhnJycUFBQgDt37kBDQ0Mm9xWLxXjy5EnpI+vY2FjcvXsXubl/b/ptamr61cijra2tTB/LS3p+9Zz29TGhu63ErkeItFGhJEpLLBbj3Llz8Pf3x+3bt9GiRQssWLAAvXv3lvjZxKNGjUJMTAwEt+/geVYuioRiaKhx0Vhfh07AIUonPj4e9vb28PHxwaJFiyR+fYZh8Pz5868eW9+5cwefPn0CADRp0uSr8mhnZ4fq1atLPEd5SWp+NSfhHLgPL+PGjRto0KCBBJIRIn1UKInSEQqFOHbsGJYvX46kpCS0a9cOCxYsQNeuXcGR0n5x5ubm6NChA517TFTGwoULERAQgHv37sHc3LzC12EYBq9fv/6qPMbGxiIrKwsA0LBhQ9jb25c+urazs4O+vr6kfgyJk8T8aofaYrRr1w7a2tq4fv06DAwMpJiYEMmgQkmURkFBAfbv34+VK1fi2bNn6NGjB+bPn4+2bdtK9b5ZWVmoVasWDh48iMGDB0v1XoTIi4KCAlhbW6N27dq4ceMGuNyyneaSkZHx1WPr2NhYZGRkAAAMDAy+mvNoZ2eHunXrSvPHkIp/zq8umT/9Pd+bX52amop27dpBX18f165dU7kN5YnioUJJFN6XL1+wfft2rFmzBm/fvkW/fv0wf/582NjYyOT+58+fh5ubG548eYJffvlFJvckRB7cuHED7du3x+bNmzFhwoT/fP39+/e4c+fOV+Xx1atXAAB9ff2vHlu3bNkS9evXl9pTBDY8zviMw9FpuJaSibSsvHLPr37w4AHat2+Phg0b4urVq6hRo4asohNSblQoicLKzs7Gpk2bsGHDBnz58gVDhgzB3LlzYWpqKtMcCxYswN69e/HmzRulejMkpCzGjRuHw4cPIzIyEpmZmV+tuH7+/DkAoHr16l+VR3t7ezRq1Eil/r3kFgorNL86ISEBLi4uMDExQWhoaJm3NiNE1qhQEoXz5s0brF27Ftu2bYNYLMaYMWMwc+ZMGBoaspKnQ4cO0NfXx8mTJ1m5PyGyVnJEYUxMDCIjIxEUFASRSATg7yMK7ezsviqPTZs2LfMjcfJfd+7cQadOnWBpaYmLFy9CR4fO9ibyhwolURhPnz7FqlWrsHfvXmhpaWHSpEmYNm3aD0+1kbbi4mJUr14dS5cuxcyZM1nLQYi05OXlffOIQoZhoKWlBVtbW+jp6eH8+fMICAjAtGnTJL6LAgEiIyPRtWtXtGrVCsHBwVLZT5OQyqBCSeTe/fv3S0+10dPTKz3VRh62CYmJiUGrVq0QGRkJR0dHtuMQUimFhYX/OaIwKSkJIpEIGhoa3zyiUE3t78e2/fr1w/Xr1/HgwQO5XoWtyG7cuIHu3bujQ4cOCAoKqvQJP4RIEhVKIrdu376N5cuX4/Tp0zA0NCw91UZbW35OjtiwYQPmzp2LT58+0Ys7USjFxcVISkr6zxGFxcXF4PF4sLS0/Ko8Nm/e/Id/x9++fQtzc3P06tUL+/btk90PomLCwsLg5uYGV1dX/PXXXxI5nIEQSaBCSeQKwzC4du0a/P39ceXKFZiampaeaiOrEznKo3///khPT8fNmzfZjkLId4lEIjx8+PCr8lhyRCGXy4W5uflXq62trKwq9Eh1z549GDlyJC5duoSuXbtK4SchwN87S3h4eMDDwwOHDx8uHSUmhE1UKIlcEIvFCA4Ohr+/P6Kjo2Fra4sFCxbAw8NDbudjMQyDhg0bYvDgwVi5ciXbcQgB8Pe/pdTU1K8eW8fFxZUeUWhmZvbVyKONjY3EjihkGAadO3fG06dPcf/+fVo8IkVBQUHo168fBg4ciH379tGiJ8I6+lhDWCUUCvHXX39h+fLluH//PpydnRESEoJu3brJ/ZYiaWlpePPmDVq3bs12FKKiGIbBs2fP/nNEYU5ODgDgl19+gb29Pdzd3WFvb48WLVpIde4xh8PBjh070Lx5cyxatAhr166V2r1UnYeHBw4dOoRBgwZBS0sL27dvl/vXTKLcqFASVhQWFpaeavP06VO4urpiy5YtcHZ2ZjtamQkEAgCgQklkgmEYvHr16j9HFGZnZwMADA0NYW9vj7lz56Jly5Zo0aIFK4tjmjZtCj8/P8ybNw9eXl5o1aqVzDOoCi8vLxQWFmLYsGHQ0tLChg0bqFQS1tAjbyJTX758wY4dO7BmzRqkp6ejb9++mD9/PmxtbdmOVm6TJ0/GpUuXkJKSwnYUlVPRTaIVydu3b7/aJDw2NhaZmZkAgLp16/7niEJ5Ou9ZKBTCwcEBxcXFiI2Nlcv5z8pk+/btGDduHGbPno2VK1dSqSSsUK5XYCK3srOzERgYiA0bNiAnJ6f0VBszMzO2o1VYREQE2rRpw3YMlVF6jN2jTKRlf+MYOz1tuJjVwSAHI5gY/PcYO3n2/v37/4w8vn79GgBQq1Yt2NvbY8yYMaUFUt6PKFRTU8Pu3bthb2+P1atXY+HChWxHUmpjx45FQUEBpk2bhipVqsDX15ftSEQF0Qglkar09HSsW7cOW7duhVAoxOjRozFr1iwYGRmxHa1Svnz5gurVq2Pbtm0YPXo023GU2svsPCwISsTN1PfgcTkQib//klXydWfjWvD3sIShnvxsMVXi48eP/znf+t9HFP5z9NHIyEiuy+OPzJ8/H2vXrkV8fDyaNWvGdhylt3LlSsybNw/+/v6YP38+23GIiqFCqWJk9ajw2bNnWL16Nfbs2QNNTU1MnDgR06ZNQ506dSR+LzZcuXIFnTt3xv3792FhYcF2HKV1NCYNi88mQShmflgk/43H5UCNy4GvuwW8WrL34eXz58+lRxSWlMfU1FQAQNWqVb95RKGilsdvyc/Ph7W1NQwMDHD9+nVaiSwDvr6+WLJkCdauXYvp06ezHYeoEHrkrQJk+agwOTkZK1aswJEjR1CzZk34+PhgwoQJqFGjRqWuK28EAgFq1KgBc3NztqMorcBrjxEQWrH5qaL/FdB5pxLx/kshJrmYSDjdf+Xl5eHevXtfjTw+fPgQDMOgSpUqsLW1RY8ePUrLo5mZmdIXrCpVqmDnzp3o0KEDduzYgXHjxrEdSen5+PigoKAAM2bMgKamJiZMmMB2JKIiaIRSicnyUWFMTAyWL1+OoKAgNGzYELNnz8aoUaPk6lQbSXJ1dQWHw8GFCxfYjqKUjsakYd6pRIldb6WnJQZIcKSysLAQCQkJXy2aSU5O/uqIwn8+tjY3N1fpzafHjBmDo0ePIjk5GQ0bNmQ7jtJjGAbTp0/Hhg0bsHv3bowYMYLtSEQFUKFUUrJ4VMgwDK5fvw5/f39cvnwZJiYmmDdvHgYPHqzUqzrFYjH09PQwe/ZsWmwgBS+z89B53XUUCsUSu6amGhdh09tXaE5lyRGF/3xsnZiYiOLiYqipqX3ziEJl/vtfER8/fgSfz4e9vT3OnDmjVI/15RXDMJgwYQK2b9+OQ4cOYeDAgWxHIkpOdT8yKzFpPypkGAbnz5+Hv78/IiMjYW1tjWPHjqFPnz5ye6qNJCUnJ+PTp0+0/6SULAhKhLAcH4LKQihmsCAoEQdHOvzw94lEIjx48OA/RxQWFhaCy+WWlqIRI0bA3t4e1tbW0NLSkmhWZVSjRg1s3rwZnp6eOH78OPr37892JKXH4XCwefNmFBQUYOjQodDU1ESfPn3YjkWUGBVKJXM0Jq3CZfLfAkJTULuqZumjQpFIhOPHj2P58uVISEhA69atcf78+dLHv6oiIiICPB6PNmyWgscZn3Ez9b3ErysSM7iZ+h6pmZ9hXOfvecJisRiPHz/+qjzevXsXeXl5AP7/iMLffvut9IhCOkqw4jw8PODp6YnJkyejc+fO0NPTYzuS0uNyudi1axcKCwvh5eWFU6dOoWfPnmzHIkqKHnkrEWk9Kjw/0QnhwSewcuVKpKamolu3bliwYAGcnZ1VqkiW8Pb2RlJSEmJjY9mOonSWnE3CwegX5ZqmUVY8DuCgX4QGbwWlRxR+/vwZwN+nu/zzsXWLFi1QrVo1iWdQdenp6TA3N4enpyf27NnDdhyVUVxcDC8vLwQHB+PcuXPo2rUr25GIEqJCqUSG7I6G4GmWRN+MOWAgepOMVwfnwdPTE/Pnz4ednZ3Erq+ITExM4Orqio0bN7IdRem0X30NL7LzpHb94uw3ULu47KvyaGdnR6NlMrRr1y6MHj0aly9fRufOndmOozKKiorg6emJK1euICQkBB06dGA7ElEyVCiVxOOMz+iy/obUrr/dvSG6OVlL7fqKIiMjA3Xr1sXRo0cxYMAAtuMolS+FQlguuQRpviBxANxf0k3pjmlUJAzDoFOnTnj+/Dnu37+vtDtByKOCggL07NkTkZGRCA0NpXngRKLoVVVJHI5O++nWQBXF43IQ+U4N3SR+ZcUTGRkJAEr9QswwDIRCIYqLi//zq6io6Jv/XRK/ssRVwOi2k+7PBuB5Vi4s6leX6n3I93E4HGzfvh1WVlbw8fFBQEAA25FUhpaWFs6cOQNXV1e4urriypUrsLe3ZzsWURJUKJXEtUeZUimTwN8LGq6lZGIJ6ESYiIgINGzYEIaGhl/9d4ZhIBKJvluWpFnEJH0PoVAo8f9v6urqP/2FWk0AB+kWSgAokuAcY1IxJiYmWLJkCRYsWAAvLy8qNTKkra2N4OBgdOvWDV27dsW1a9dgbU1Pn0jl0SNvJaDIjwrZLmHlvc/Lly/B5XJRtWrV/3xN0tTU1MpUxL71S0NDo8LfK+l78Hi8Mi3eSnrzCb9uuiXx/4//dn5yWxqhlANCoRCtWrWCSCRCbGzs3x8qiMx8/PgRnTt3xosXL3D9+nXw+Xy2IxEFR4VSCcjqjdjpUziqFGRJtOxJ+q8fj8eTWkHicrlYu3YtunXrBmdnZ6mWMDU1NZVbQZ9bKERzBf1gRCrm7t27aNWqFZYuXYr58+ezHUflZGVlwcXFBe/evcONGzdgYiL9I0qJ8qJCqQTi0j7AY6tA6vepcXsntPMzZT4SVtb7qKmpSfVsZIFAgDZt2iA2NlblV7pLi7RXeTfS18b1WS5Suz4pv7lz52LDhg1ISEiAqakp23FUTmZmJtq3b48vX77gxo0baNKkCduRiIKij+lKQENNeiXqnw4f3K/SjwoFAgG0tbVhZWXFdhSl5WJWR3r7UHI5cDGtI/HrkspZvHgxTp48idGjR+PatWtS/VBI/qtOnTq4cuUK2rdvj44dO+LGjRv/mSNOSFnQv1wl0FhfB9J+OMr5331UWUREBFq1akVzvaRokIORVBeXDXb88fn0RPa0tbWxc+dO3LhxA7t27WI7jkqqX78+rly5AoZh0LFjR6Snp7MdiSggKpRKQEdTDUZ60t3LzUhfW6XnnTEMU/rIm0iPiYEunI1rgceV7EckHpcDZ+NapccuEvni4uKCkSNHYvbs2Xj9+jXbcVSSkZERrl69ivz8fHTq1AmZmZlsRyIKhgqlknAxqyPxN+ES9KgQePr0KTIzM5V6/0l54e9hCTUJ/11W43Lg72Ep0WsSyVq9ejW0tbUxceJEiS/WI2Xzyy+/4OrVq8jOzkaXLl2QnZ3NdiSiQKhQKgl6VChdERERAAAnJyeWkyg/Qz1t+LpLds9TP3cLGEp5FJ9UTs2aNREYGIgzZ87g5MmTbMdRWaamprhy5QrevHmDbt264dOnT2xHIgqCCqWSoEeF0iUQCMDn81GzZk22o6gEr5ZGmNVVMit+Z3c1w4CWqv2BSFF4enqid+/emDRpEj58+MB2HJVlYWGBy5cvIzU1Fa6urvj8+TPbkYgCoEKpROhRofRERETQ/EkZm+RighWeltBU45b7gxKPy4GmGhcrPS0x0cVYSgmJpHE4HGzevBn5+fmYPXs223FUmo2NDUJDQ3H//n307NkTeXnS286LKAcqlEqEHhVKx8ePH5GUlETzJ1ng1dIIYdPbo/Uv+gDw02JZ8vXWv+gjbHp7GplUQPXr18fq1auxe/duXL16le04Kq1ly5YICQlBbGwsPDw8UFBQwHYkIsdoY3MlFHjtMQJCUyp9ndldzWh0B8ClS5fQvXt3PHr0iDZeZtHjjM84HJ2GaymZSMvK++pEHYZhYFhDE5359THY0Ujlp2goOrFYjI4dO+LVq1dISEiAtrZqf6hl27Vr19CjRw907twZJ0+ehIaGBtuRiByiQqmkjsakYfHZJBQWFQNcXpm/j8flQI3LgZ+7BY3u/I+Pjw+2bt2KzMxMlTsOUV7lFgrxPCsXRUIxMtJfo4dzS4ReOIfOnTuzHY1ISEpKCqysrDBlyhSsWrWK7Tgq79KlS3B3d0fPnj1x9OhRqKmp7jZy5NvokbeS8mpphDENM5D/Ih4APSqsDIFAgNatW1OZlCM6mmqwqF8dtkY10cXeHBpcBsnJyWzHIhJkamqKxYsXY82aNbh79y7bcVRet27dcPz4cZw5cwbe3t4QiURsRyJyhgqlkiouLsbmlX5wFsbj8rR2GOLQCI30tf9zog4Hf59vPMShEcKmt8PBkQ4qP2fyn4RCIaKiomhBjhzj8Xho1qwZFUolNGvWLFhaWmLkyJEoLi5mO47Kc3d3x5EjR3D06FGMHj0aYrGY7UhEjtCYtZI6dOgQnj17htOnT8PEQBdL3C2wBBZfPSrUUOOisb6OSp+A8zOJiYnIzc2lBTlyjs/nU6FUQurq6ti1axccHBywdu1azJ07l+1IKq9fv34oLCzE0KFDoaWlhc2bN9PTGwKACqVSKi4uxrJly+Dp6QkrK6uvvlbyqJCUjUAggLq6Ouzs7NiOQn6Az+fj0qVLYBiG3tyUjL29PWbMmIElS5bA09MTJiYmbEdSeYMHD0ZhYSFGjRoFLS0trFmzhv7dEXrkrYwOHz6Mp0+fwsfHh+0oCi8iIgJ2dnaoUqUK21HID/D5fGRnZ+Pdu3dsRyFS4Ovri/r162PMmDF0LKOcGDlyJAIDA7Fu3TosXLiQ/lwIFUplIxQKsWzZMnh4eMDa2prtOAqvZEEOkW98Ph8A6LG3ktLW1saOHTsQHh6O3bt3sx2H/M/EiROxZs0aLF++HMuWLWM7DmEZPfJWMocPH8aTJ09w4sQJtqMovNevX+PFixe0IEcBNG3aFOrq6khOTkaHDh3YjkOkoFOnThg+fDhmzZqFHj16oH79+mxHIgBmzJiB/Px8/P7779DS0qITjlQYjVAqkZLRyd69e8PGxobtOApPIBAAAJycnFhOQn5GXV0dpqamNEKp5AICAqClpYXJkyezHYX8w8KFC/H7779jzpw52LRpE9txCEtohFKJHDlyBKmpqfjrr7/YjqIUBAIBmjRpgnr16rEdhZQBrfRWfnp6eti0aRP69++PU6dOwdPTk+1I5H/8/PxQUFCAKVOmQFNTE2PGjGE7EpExGqFUEiWjk+7u7rC1tWU7jlKIiIigx90KhAqlaujbty/c3d0xceJEfPz4ke045H84HA5WrVqFSZMmYdy4cThw4ADbkYiMUaFUEn/++SceP36MxYsXsx1FKeTl5SEuLo4W5CgQPp+PjIwMZGVlsR2FSBGHw8GWLVuQl5eHOXPmsB2H/AOHw8GGDRswcuRIDB8+HMeOHWM7EpEhKpRKoGR0smfPnmjRogXbcZRCTEwMhEIhjVAqkJKV3g8ePGA5CZG2Bg0aYOXKldi5cyfCw8PZjkP+gcvlYtu2bRg4cCAGDRqE06dPsx2JyAgVSiVw9OhRpKSk0OikBAkEAujq6sLCwoLtKKSMTExMwOPx6LG3ihgzZgycnZ0xevRo5Ofnsx2H/AOPx8PevXvh6emJ/v3748KFC2xHIjJAhVLBiUQiLF26FG5ubnSaiwQJBAI4OjqCx+OxHYWUkaamJoyNjZGUlMR2FCIDXC4XO3fuRFpaGnx9fdmOQ/5FTU0Nhw8fRo8ePeDp6YkrV66wHYlIGRVKBUejk5InFoshEAjocbcCooU5qsXMzAw+Pj4ICAhAXFwc23HIv6irq+PYsWNwcXFBz549cfPmTbYjESmiQqnASkYnf/31V9jb27MdR2mkpKQgOzubFuQoICqUqmfOnDng8/kYNWoUhEIh23HIv2hqauLUqVNwdHREjx49EBUVxXYkIiVUKBXYX3/9hUePHtHopIRFRESAy+XCwcGB7SiknPh8Pt68eUPbyagQdXV17N69G/fu3cO6devYjkO+oUqVKjh37hysra3RvXt33L17l+1IRAqoUCookUgEPz8/9OjRAy1btmQ7jlIRCASwtLREtWrV2I5CyolWequmli1bYtq0afDx8UFqairbccg36Ojo4MKFCzAzM0PXrl2RmJjIdiQiYVQoFdTx48fx8OFDGp2UAoFAQI+7FZSZmRk4HA499lZBfn5+qFevHsaOHQuGYdiOQ76hWrVquHjxIgwNDdG5c2c8fPiQ7UhEgqhQKqCS0UlXV1e0atWK7ThKJSsrCw8fPqQFOQqqSpUq+OWXX6hQqiAdHR1s374dV69exd69e9mOQ76jZs2auHz5MmrXro1OnTrhyZMnbEciEkKFUgGdOHECDx48oNFJKYiMjAQAGqFUYLQwR3V16dIF3t7emDlzJtLT09mOQ76jVq1aCAsLQ9WqVdGxY0e8ePGC7UhEAqhQKhixWAw/Pz90796dFo1IQUREBOrVq4fGjRuzHYVUEBVK1bZmzRqoq6tjypQpbEchP1C3bl1cvXoVampq6NixI16/fs12JFJJVCgVzIkTJ5CcnEyjk1JSMn+Sw+GwHYVUEJ/PR1paGj5//sx2FMICfX19bNq0CSdOnKBj/+RcgwYNcPXqVRQXF6NTp07IyMhgOxKpBCqUCqRkdLJr165wdHRkO47SKS4uxu3bt+lxt4IrWelNE/5VV//+/eHm5oYJEybQFlJyrlGjRrh69SpycnLQuXNnvH//nu1IpIKoUCqQkydPIikpiUYnpSQuLg4FBQW0IEfBNWvWDADosbcK43A42Lp1K758+YJ58+axHYf8hLGxMa5cuYKMjAx07doVHz58YDsSqQAqlAqiZHSyS5cuNIImJQKBAFpaWrC1tWU7CqmEqlWrolGjRlQoVVzDhg2xYsUKbN++HdevX2c7DvkJc3NzhIWF4cWLF3B1dUVOTg7bkUg5UaFUEKdOncL9+/dpdFKKIiIi0LJlS2hoaLAdhVQSLcwhADBu3Di0adMGo0ePRkFBAdtxyE9YWVkhNDQUDx8+xK+//orc3Fy2I5FyoEKpAEpGJzt37kyPY6WEYRja0FyJUKEkAMDlcrFz5068ePECfn5+bMchZWBnZ4eLFy/i3r17cHd3R35+PtuRSBlRoVQAQUFBSExMpNFJKUpLS8ObN2+oUCoJPp+PZ8+eIS8vj+0ohGXm5ub4/fffsWrVKsTHx7Mdh5SBo6Mjzp8/j8jISPTp0weFhYVsRyJlwGHojCq5JhaLYWtri9q1ayMsLIztOErryJEjGDRoEN69e4datWqxHYdUUlRUFJycnHD37l2aE0tQVFQEOzs7aGpqIioqCmpqamxHImUQFhYGNzc3dO/eHcePH4e6ujrbkcgP0AilnDt9+jQSEhJodFLKBAIBTE1NqUwqCXNzcwC00pv8TUNDA7t27cLdu3exYcMGtuOQMurcuTNOnjyJCxcuYPDgwRAKhWxHIj9AhVKOlcyd7NixI5ydndmOo9QiIiJofqoSqV69Oho0aECFkpRycHDA1KlTsWjRIjx9+pTtOKSMfv31Vxw7dgwnT57EiBEjIBaL2Y5EvoMKpRw7e/Ys4uPjaXRSyj5//oyEhASaP6lkaGEO+belS5eiTp06GDt2LGi2l+Lw8PDAoUOHcPjwYYwbN47+7OQUFUo5xTAMfH194eLignbt2rEdR6ndvn0bYrGYRiiVDBVK8m9Vq1bF9u3bERYWhv3797Mdh5SDl5cX9uzZg507d2Lq1KlUKuUQzUyWU2fPnsW9e/cQHh7OdhSlFxERgZo1a8LMzIztKESC+Hw+Nm3ahMLCQmhqarIdh8iJbt26YciQIZgxYwZcXV1hYGDAdiRSRt7e3igoKMC4ceOgpaWFlStXgsPhsB2L/A+NUMqhktHJDh06oH379mzHUXoCgQBOTk7gcumfgzLh8/kQi8VISUlhOwqRM2vXrgWPx8OUKVPYjkLKaezYsVi/fj1Wr16NJUuWsB2H/AO9g8qhc+fOIS4ujuZOyoBIJEJkZCQ97lZCtNKbfE+tWrWwceNG/PXXXzh79izbcUg5TZ06FStXroSfnx/8/f3ZjkP+hx55yxmGYbBkyRK0b98eHTp0YDuO0ktOTkZOTg4tyFFC+vr6MDAwoEJJvsnLywuHDh3C+PHj0b59e1SvXp3tSKQc5syZg/z8fCxcuBBVqlTB9OnT2Y6k8qhQypng4GDExcXh6tWrbEdRCQKBADweD61atWI7CpECWphDvofD4WDr1q2wsLDA/PnzsWXLFrYjkXLy8fFBQUEBZsyYAU1NTUyYMIHtSCqNHnnLkZLRSWdnZxqdlJGIiAjY2tpCW1ub7ShECqhQkh8xMjLC8uXLsXXrVty8eZPtOKScOBwO/P39MW3aNEycOBF79uxhO5JKo0IpR86fP4+7d+9iyZIltHJNRgQCAT3uVmJ8Ph8pKSkoLi5mOwqRU+PHj4eTkxNGjx6NgoICtuOQcuJwOFi7di3GjRuHUaNG4ciRI2xHUllUKOVEycrutm3bwsXFhe04KiEjIwNPnjyhBTlKjM/nQygUIjU1le0oRE7xeDzs2rULT58+xbJly9iOQyqAw+Fg8+bN8Pb2xtChQ3HixIkyfV9uoRBJbz4hLu0Dkt58Qm4hHe1YGTSHUk5cuHABsbGxCAsLo9FJGREIBABAI5RKjM/nA/h78VXJqm9C/o3P52PhwoVYtmwZ+vfvDysrq6++nlsoxPOsXBQJxdBQ46Kxvg50NOntU55wuVzs2rULhYWF+O2336CpqYmePXv+5/c9zviMw9FpuPYoE2nZefjn9ugcAEZ62nAxq4NBDkYwMdCVWX5lwGFou3nWMQwDBwcHaGho4ObNm1QoZWT27Nn466+/8OLFC7ajEClhGAa1a9cuPcOZkO8pKipCixYtoK2tjcjISDx9n0fFQwEVFxfDy8sLwcHBOHfuHLp27QoAeJmdhwVBibiZ+h48Lgci8ferT8nXnY1rwd/DEoZ6NMe+LKhQyoELFy7g119/xeXLl9G5c2e246iM1q1bo1GjRvjzzz/ZjkKkqF27dmjQoAH9OZOfioyMRLsennCavAFpxTpUPBRUUVERPD09ceXKFYSEhOCtzi9YfDYJQjHzwz/Pf+NxOVDjcuDrbgGvlkZSTKwcqFCyjGEYODo6Qk1NDbdu3aLRSRkpKChA9erVERAQgMmTJ7Mdh0jRuHHjEBkZifj4eLajEDl3NCYNC07eg4gBOFxemb+Piof8KSgogLu7O+KKDKDj5FXp683qaopJLiYSSKa8aFEOyy5evIjbt29j8eLFVCZl6M6dOygqKqIFOSqAz+fj0aNHEAppwj35vsBrjzHvVCLEHF65yiQAiMQMCoVizDuViMBrj6WUkJSHlpYWBi/eIpEyCQABoSk4FpMmkWspKyqULCpZ2e3k5IQuXbqwHUelCAQC6Ojo/GfyPVE+fD4fhYWFePbsGdtRiJw6GpOGgFDJnPlOxUM+vMzOwx8XJVvufc4m4WV2nkSvqUyoULIoNDQU0dHRNDrJAoFAAAcHB6ip0UpNZffPld6E/NvL7DwsPpsk0WtS8WDfgqBECMsxX7IshGIGC4ISJXpNZUKFkiUlp+I4OjqWrkIjssEwDCIiImi7IBVRr149VK9enQol+SYqHsrnccZn3Ex9X64FOGUhEjO4mfoeqZmfJXpdZUGFkiWXL19GVFQUjU6y4MmTJ3j37h0VShXB4XDoCEbyTVQ8lNPh6DTwuNJ5X+VxOTgURVMavoUKJQtKRicdHBzQrVs3tuOonIiICACAk5MTy0mIrFChJN9CxUM5XXuUKfEPCSVEYgbXUjKlcm1FR4WSBWFhYYiMjKTRSZYIBAJYWFigRo0abEchMsLn8/HgwQOIxWK2oxA5QsVD+XwpFCJNyvNX07Ly6JjGb6BCKWMlo5MtW7ZE9+7d2Y6jkgQCAW0XpGL4fD7y8/PpVCRSioqHcnqRlQtpb67NAHielSvluygeKpQyduXKFQgEAixZsoRGJ1nw8eNHJCUl0fxJFUMrvcm/UfFQTkVC2TyFkNV9FAkVShkqGZ20t7eHq6sr23FUUlRUFBiGoUKpYgwNDVG1alUqlKQUFQ/lpKEmm1ojq/soEtqET4auXr2KiIgIBAcH0+gkSwQCAWrXrg1jY2O2oxAZ4nA4MDc3p0JJSlHxUE6N9XXAAaQ6+sz5333I1+hvuoyUnIpjb2+PHj16sB1HZZXsP0mFXvXQSm/yTyXFQ5qoeMiejqYajPS0pXoPI31t6GjSeNy/UaGUkWvXruHmzZu0sptFQqEQ0dHRtCBHRZUUSoaR9sw5ogioeCgvF7M6Ut0OysW0jlSureioUMpAyeiknZ0dfv31V7bjqKyEhATk5ubS/EkVxefz8eXLF7x69YrtKEROUPFQToMcjKS6HdRgRyOpXFvRUaGUgfDwcNy4cQM+Pj40OskigUAADQ0N2NnZsR2FsIBWepN/o+KhnEwMdOFsXEviHxZ4XA6cjWvBuI6uRK+rLKhQyoCvry9sbW3Rs2dPtqOoNIFAADs7O2hpabEdhbCgUaNGqFKlChVKUsrEQBcW+jwwYpFEr8uIhDBgPqBhNXWJXpeUnb+HJdQkXCjVuBz4e1hK9JrKhAqllIWHh+P69es0d1IOlCzIIaqJx+OhWbNmVCgJAKCoqAjz589H6B/DwWUku7WPGo+LxN3zYWNjA4FAINFrk7Ix1NOGr7uFRK/p524BQynPu1VkVCilzNfXFzY2NnB3d2c7ikp79eoV0tLSaEGOiqOV3gQAHj58CCcnJwQEBGDZvGn4o4+NRK/v72mN2OuXUKNGDbRt2xbTp09HXp50T+Uh/1X0IBwfrh+QyLVmdzXDgJY0heFHqFBK0fXr1xEeHk6jk3KgZJSARihVG630Vm0Mw2Dbtm1o0aIFcnNzERUVhblz52KgQ2PM6moqkXuUFA8+n4+IiAisXr0a27Ztg5WVFcLDwyVyD/Jzly9fxsiRI9GPr4vlHpbQVOOWe04lj8uBphoXKz0tMdGF9i7+GSqUUlQyOtmrVy+2o6g8gUCApk2bwsDAgO0ohEV8Ph8fP37E27dv2Y5CZCwzMxO9evXC+PHj4e3tjTt37ny1QG+SiwlWeEq2ePB4PMycORMJCQmoX78+XFxcMHHiRHz+/FliPxf5r3v37qFPnz7o0qULtm7dit9aGSFsenu0/kUfAH7651vy9da/6CNsensamSwjDkMf1aXixo0baN++PU6dOgUPDw+246i8Vq1aoVmzZjhwQDKPP4hiSklJgZmZGcLCwtCpUye24xAZCQkJwbBhw8AwDHbv3v3DBZIvs/OwICgRN1Pfg8fl/HAVeMnXnY1rwd/D8ofz68RiMbZs2YJ58+ZBX18fO3fuRNeuXSv1c5H/evHiBRwdHdGgQQOEh4ejatWqX339ccZnHI5Ow7WUTKRl5X19og7DoFEtHbiY1sFgRyNazV1OVCilpFOnTnj//j3i4uLA5dJAMJvy8vJQvXp1bNq0CePGjWM7DmGRUCiEjo4OAgICMHnyZLbjECnLz8/HnDlzEBgYCFdXV+zZswd169Yt0/f+qHhw8Pem5RUpHs+ePcPo0aNx5coVjBw5EgEBAahRo0a5fi7ybdnZ2WjTpg2KioogEAh++kQqt1CI51m5KBKKsWfXDhzbFYiM12k0Ra2CaAt/Kbh58yauXr2KkydPUpmUAzExMRAKhbQgh0BNTQ1mZma0MEcF3Lt3D4MGDcLTp08RGBiICRMmlKsomBjoYom7BZbA4qvioaHGRWN9nQqfgNOkSRNcvnwZu3btwsyZM3Hx4kVs376dDr2opIKCAvTq1Qvv3r0rU5kE/j4tyaJ+dQBApxZmCEx/hfT0dNSvX1/acZUStR0p8PX1haWlJXr37s12FIK/twuqVq1a6cbWRLXRSm/lJhaLERAQgFatWkFdXR137tzBxIkTKzXqVFI8bI1qwqJ+9Uofp8jhcDB69GgkJSXBysoKbm5uGDJkCLKysip1XVUlEokwePBg3LlzB8HBwTA1Lf8CKxsbGwB/fxAhFUOFUsJu3bqFK1euYPHixTQ6KScEAgGcnJzA4/HYjkLkABVK5fXq1St06dIFc+bMwdSpUxEdHS3XHyQNDQ1x/vx57Nu3D8HBwbCwsMCpU6fYjqVQGIbBjBkzEBQUhKNHj8LR0bFC12nUqBGqV6+OuLg4CSdUHdR4JMzX1xfNmzenhThyQiwWIzIykrYLIqUsLCzw/v17vHv3ju0oRIKOHz8OKysrPHr0CGFhYVi9ejU0NTXZjvVTHA4H3t7eSE5OhqOjI/r06YP+/fsjMzOT7WgKYe3atdi4cSMCAwMrtd8zh8OBjY0NjVBWAhVKCRIIBAgLC6PRSTny6NEjZGdnU6EkpehMb+WSk5ODYcOGoX///ujcuTMSEhLQsWNHtmOVW7169RAUFIQ///wTV69eBZ/Px59//kl7pv7A0aNHMWvWLMyfPx/jx4+v9PVsbW2pUFYCtR4JKhmd9PT0ZDsK+R+BQAAulwsHBwe2oxA5YWxsDDU1NSqUSkAgEMDGxgYnT57Evn37cOzYMejp6bEdq8I4HA68vLyQnJyMzp07Y+DAgfDw8EB6ejrb0eROeHg4vL29MWTIEPzxxx8SuaaNjQ1SU1Npn9AKokIpIZGRkQgNDcWiRYtodJJFuYVCJL35hLi0D0h68wnXBVGwsrKCri7tJ0b+pq6uDlNTUyqUCkwoFGLx4sVwdnZG3bp1ER8fD29vb6XZ7qVOnTo4evQoTp06haioKPD5fOzbt49GK/8nMTERvXv3Rrt27bBr1y6J/bmXLMxJSEiQyPVUDe1DKSHdu3fHy5cvkZiYSIVSxkr3i3uUibTs/25Uq83koX8bCwxyMIKJARVLAvTr1w/Z2dm4cuUK21FIOaWmpmLw4MGIjY2Fj48PFixYADU15d0BLzs7G9OmTcPBgwfRvXt37NixA4aGhmzHYs2rV6/g6OiI2rVr4/r166hWrZrErl1UVISqVati7dq1mDRpksSuqyqo+UhAVFQULl26BB8fHyqTMvQyOw9Ddkejy/obOBj9Ai/+XSYBgMNBHlcHB6NfoMv6GxiyOxovs/PYiEvkCK30VjwMw2DPnj2wsbHB+/fvcevWLfj4+Ch1mQQAPT09HDhwAMHBwUhMTISFhQV27NihkqOVHz9+hKurK3g8Hs6fPy/RMgkAGhoaaN68Oc2jrCBqPxLg6+sLPp+Pvn37sh1FZRyNSUPnddchePr3vm0/Oh7tn18XPM1C53XXcTQmTeoZifzi8/l4+/YtsrOz2Y5CyiArKwt9+/bFyJEjMWDAAMTFxVV4exhF9euvvyIpKQkDBgzA2LFj0blzZzx9+pTtWDJTWFgIDw8PvHr1ChcvXpTa5uO00rviqFBWUnR0NC5evIhFixbRPocyEnjtMeadSkShUPzTIvlvIjGDQqEY804lIvDaYyklJPKuZKX3gwcPWE5CfiYsLAxWVlYIDw/HyZMnsXv3bpWdE129enXs3LkToaGhePLkCSwtLbFp0yaIxWK2o0mVWCzGsGHDEBkZibNnz8Lc3Fxq97KxscH9+/dRXFwstXsoKyqUleTr6wtzc3P069eP7Sgq4WhMGgJCUyRyrYDQFByjkUqVZGpqCi6XS4+95VhBQQFmzJiBLl26gM/nIyEhgXbQ+J8uXbogMTERw4cPx5QpU9C+fXukpEjmdVEezZs3D8eOHcOhQ4fg7Ows1XvZ2NigsLAQjx49kup9lBEVykq4ffs2QkJCaHRSRl5m52Hx2SSJXtPnbBLNqVRBmpqaMDY2pkIpp+7fv49WrVph8+bNWLt2LS5duoQGDRqwHUuu6OrqIjAwEOHh4UhPT4e1tTUCAgIgEonYjiZRmzZtwurVq7Fu3TqZTCuztrYGADoxpwKoUFaCr68vmjVrhv79+7MdRSUsCEqEsJyPuH9GKGawIChRotckioEW5sgfsViMDRs2wN7eHmKxGDExMZg+fTotdvyB9u3bIyEhARMmTMCcOXPQunVrpfl7ffLkSUydOhUzZ87E1KlTZXLP6tWr45dffqF5lBVA/0orKCYmBhcuXKDRSRl5nPEZN1Pfl3vO5M+IxAxupr5HaiZtZKtqqFDKl/T0dPTo0QPTpk3D2LFjERMTAysrK7ZjKQRtbW2sWbMGERERyMnJga2tLfz9/RV6HuCtW7cwaNAgDBgwAKtWrZLpvWlhTsVQoawgX19fmJmZYcCAAWxHUQmHo9PA40pn02Iel4NDUTSXUtXw+Xy8evUKOTk5bEdReadPn4alpSXi4+Nx8eJFbNiwAVWqVGE7lsJxcnJCXFwcZsyYAR8fHzg4OCA+Pp7tWOX24MEDuLu7w8nJCfv27ZP5CHVJoVTFrZkqgwplBcTGxuL8+fM0OilD1x5lSnx0soRIzOBaSqZUrk3kF630Zl9ubi7GjBkDDw8PtG3bFgkJCejWrRvbsRSalpYWli9fjqioKAiFQtjb22Px4sUoKipiO1qZpKenw9XVFQ0aNEBQUBA0NTVlnsHGxgbZ2dl49eqVzO+tyKhQVoCvry9MTU3h5eXFdhSV8KVQiDQpL5xJy8pDbqFQqvcg8sXMzAwcDocee7MkJiYGtra2OHz4MHbs2IGgoCDUrl2b7VhKw97eHrGxsVi4cCH8/f1hZ2eH2NhYtmP9UE5ODnr06AGhUIgLFy6gRo0arOQoOYKRFuaUDxXKcrpz5w6Cg4NpdFKGXmTl/vcEHAljADzPypXyXYg80dbWRpMmTahQyphIJMIff/yB1q1bo3r16oiLi8Po0aOV5hxueaKhoYElS5YgNjYW6urqcHBwwLx581BQUMB2tP8oLi5G37598fTpU4SEhLB6vGTDhg2hr69P8yjLiQplOfn6+sLExIRGJ2WoSCibTXtldR8iP2hhjmw9f/4cHTp0gI+PD+bOnQuBQABTU1O2Yyk9a2trREdHY9myZVi3bh1sbGwgEAjYjlWKYRiMGjUK4eHhpfNp2cThcGhhTgVQoSyHu3fv4ty5c1i0aJHSnx8rTzTUZPPXVFb3IfKDCqXsHD58GNbW1nj58iXCw8OxbNkyqKursx1LZairq2P+/PmIi4tDjRo10LZtW0yfPh15eezvw7to0SIcOHAA+/fvh4uLC9txANBK74qgd9By8PPzg7GxMX777Te2o6iUxvo6kPbDMM7/7kNUC5/Px/Pnz5GbS9MdpOXjx48YOHAgBg8eDHd3d8THx0v9tBPyfXw+HxEREQgICMC2bdtKj7Vky/bt2/HHH39g1apVcvXeamNjg2fPnuHjx49sR1EYVCjLKC4uDmfOnMHvv/9Oo5MypqOpBiM9baneQ73wIy6cDZLLuUVEekpWej98+JDlJMrp+vXrsLa2xoULF/Dnn3/i4MGDqF69OtuxVB6Px8OMGTOQkJCA+vXrw8XFBRMnTsTnz7Ldj/fs2bOYMGECJk+ejFmzZsn03j9ja2sLAAq57RJbqFCWkZ+fH5o2bYpBgwaxHUUluZjVkdo+lBwwUHuXgv79+6NevXoYP348oqKiaA8yFdCsWTMAoMfeElZUVIT58+fDxcUFTZo0QUJCAs07l0MmJiYIDw/Hpk2bsH//fjRv3hyhoaEyuXdUVBS8vLzQu3dvrFu3Tu4WZZmZmUFTU5Mee5cDFcoyuHfvHk6fPk2jkywa5GAktX0oGXBwds0sPHz4EOPHj0dwcDCcnJxgbm6O5cuX015kSkxXVxdGRkZUKCXo4cOHcHJyQkBAAJYvX44rV67AyMiI7VjkO7hcLiZNmoTExESYmJigW7duGDVqlFQf9T5+/Bg9e/ZEixYtcOjQIbncMUVNTQ2WlpZUKMuBCmUZlIxODh48mO0oKsvEQBfOxrUkPkrJ43LgbFwLxnV0YWZmBn9/fzx//hyXL1+Gvb09li5dCiMjI3Tp0gWHDh2SiwnsRLJoYY5kMAyDbdu2oUWLFsjNzUVUVBTmzp0rl2WB/FeTJk1w+fJl7NixA3/99ReaN2+O8+fPS/w+GRkZ6N69O/T19XHmzBm5PhGJFuaUDxXKn4iPj0dQUBAWLlxIo5Ms8/ewhJqEC6UalwN/j6+3qODxeOjcuTMOHTqEt2/fYteuXSgqKsKQIUNQt25djBw5Ejdu3KBH4kqCCmXlZWZmolevXhg/fjy8vb1x9+5d2NnZsR2LlBOHw8Ho0aORlJQEKysruLm5YciQIcjKypLI9XNzc+Hm5oa8vDxcvHgR+vr6ErmutNjY2CApKUlhThliGxXKn/Dz88Mvv/xCo5NywFBPG77uFhK9pp+7BQx/sOCnWrVqGDFiBK5fv44nT55gxowZuHbtGtq3b4+mTZvC19cXz549k2gmIlt8Ph9Pnz5Ffn4+21EU0oULF2BpaYmoqCicPXsWW7duhba2dBfREekyNDTE+fPnsW/fPgQHB8PCwgKnTp2q1DWFQiH69++Phw8f4sKFC2jcuLFkwkqRra0tiouL6QNnGVGh/IGEhAScOnUKCxcupP3S5MT76LP4cP2ARK41u6sZBrQs+9yuX375BUuWLEFqaiquX78OFxcXBAQE4JdffkH79u2xZ88ema+SJJXH5/MhFouRkpLCdhSFkp+fj0mTJuHXX3+Fvb09EhMT0bNnT7ZjEQnhcDjw9vZGcnIyHB0d0adPH/Tv3x+ZmZnlvhbDMBg/fjxCQ0Nx8uTJ0hXU8s7S0hIcDocee5cRFcof8PPzQ5MmTTBkyBC2oxAAQUFBmDJlCkY6NsAKT0toqnHLPaeSx+VAU42LlZ6WmOhiXKEcXC4X7dq1w+7du/H27VscPHgQGhoaGDVqFAwMDDBkyBCEhYVBJBJV6PpEtszNzQEAcYnJSHrzCXFpH5D05hOd7f4D9+7dg52dHXbv3o3AwEAEBwfDwMCA7VhECurVq4egoCAcPXoU165dA5/Px59//lmuKT9Lly7Frl27sGvXLnTt2lWKaSVLV1cXxsbGVCjLiMOo+ESw3EIhnmflokgohoYaF431daCjqYbExERYWVlh165dGDlyJNsxVZ5AIECnTp3g7u6OP//8E1wuFy+z87AgKBE3U9+Dx+X8cBV4ydedjWvB38Pyh4+5K+rly5c4dOgQ9u/fj0ePHqFhw4YYMmQIvL29YWZmJvH7kcp7nPEZh6PTsPfSbXCq1Qb+sYU+B4CRnjZczOpgkIMRTAx0WcspL8RiMdasWYOFCxfCwsIChw8fLt3Lkyi/d+/eYfLkyTh27Bh69eqFrVu3ol69ej/8nj179mDkyJFYtmwZFi5cKKOkklMyKsvm5u+KQiULZcmbyLVHmUjLzsM//weUvInkP41FpuAUHsfeoMfdLHv06BFat26N5s2b49KlS9DS0vrq66V/nimZSMv6xp+nvjZcTOtgsKMRjOtIvxQwDIPo6Gjs378fR48excePH+Ho6Ahvb28MGDAANWvWlHoG8mPy9mFEEbx8+RLe3t4IDw/HzJkzsWzZMmhqarIdi7AgKCgI48ePR2FhIdatWwdvb+9v7iMZEhKCnj17YtSoUdi6davc7TVZFv7+/li1ahU+fPigkPllSaUKZXneRBixCBwuT+XfRNj29u1bODk5QUdHBzdv3vxpGfveiDNbCgoKcO7cOezbtw+XLl2Cmpoa3N3d4e3tjW7dutHOASw4GpOGxWeTIBQz5drblMflQI3Lga+7BbzKMfdWGfz1118YO3YsdHR0cODAAXTs2JHtSIRl2dnZmDZtGg4ePIju3btjx44dMDQ0LP16bGwsOnTogI4dO+LUqVMK+1oXEhKCHj164OnTp2jSpAnbceSayhRKehNRPJ8/f0b79u2RkZGByMhIhd8c+e3btzh8+DD279+PxMRE1K1bF4MGDYK3tzcsLS1/fgFSaYHXHiMgtPKLb2Z1NcUkFxMJJJJvOTk5mDx5Mg4cOIB+/fph27Zt0NPTYzsWkSPnz5/H2LFjkZOTg4CAAIwePRrPnj2Dk5MTGjdujKtXr0JHR4ftmBWWnp6O+vXr49SpU/Dw8GA7jlxTiUJJbyKKp7i4GD179oRAIMDNmzdhbW3NdiSJYRgG9+7dw759+3DkyBG8f/8etra2GDZsGH777TfUrl2b7YhK6WhMGuadSpTY9VZ6WpZrlwBFIxAIMHjwYLx79w6BgYEYOnQoPfIj3/Tp0yfMmjULu3btQtu2bfH69WvweDwIBAKFfz1jGAZ169bFuHHj4Ovry3Ycuab0q7yPxqRJpEwCQEBoCo7FpEnkWuT7GIbBmDFjcPXqVQQFBSlVmQT+3o7D1tYWGzZswOvXr3H69Gk0btwYs2bNQv369dG7d28EBQXRZroS9DI7D4vPJkn0mj5nk/AyW/lOTiouLoaPjw+cnZ1Rt25dxMfHf3eOHCEAUL16dezcuRNnz55FTEwMnj17ht9++03uNy4vCw6HQyfmlJFSF0p6E1FMixcvxr59+7B371506tSJ7ThSpaGhgV69euHUqVN48+YN1q5di1evXsHT0xP169fHlClTcOfOHTqVp5IWBCVCKOGz4IViBguCJDfiKQ9SU1Ph7OwMf39/LF68GDdu3MAvv/zCdiyiAEQiEfbs2QMej4e+ffti6dKlaN++vVLs72pra0uFsgyUulDSm4ji2bFjB5YuXYoVK1Zg0KBBbMeRqVq1amHy5MmIjY3F/fv3MWLECBw/fhz29vawtLTE6tWrkZ6eznZMhfM44zNupr4v19zpshCJGdxMfY/UTMXfzJ5hGOzevRs2NjZ4//49bt26BR8fH4VdSEFki2EYTJkyBefOncNff/2F48ePIzw8HOnp6bC2tkZAQIBC78trY2ODtLQ0iR1BqayUtlDSm4jiCQ4Oxvjx4zFx4kTMmTOH7TissrCwwKpVq/Dy5UtcuHABzZs3x6JFi9CwYUP06NEDx44dQ0FBAdsxFcLh6LRyb4BfVjwuB4eiFHsaTFZWFvr27YtRo0ZhwIABiIuLg6OjI9uxiAJZuXIltmzZgm3btuHXX38FALRv3x4JCQmYMGEC5syZg9atWyvsEYY2NjYAgPj4eHaDyDmlLZT0JqJYbt++jQEDBsDd3R0bNmyg+Vr/o6amBldXVxw9ehRv377F1q1b8fHjR3h5eaFu3boYO3YsIiMj6ZH4D1x7lCnxD5YlRGIG11LKfxSdvLh8+TKsrKwQHh6OkydPYvfu3dDVpQ3cSdkdPHgQ8+fPh4+PD0aNGvXV17S1tbFmzRpEREQgJycHtra28Pf3R3FxMUtpK8bExARVqlShx94/obSFkt5EFEdqairc3NxgbW2NI0eOgMfjsR1JLtWoUQNjxoyBQCDAo0ePMGnSJISEhKB169YwMzPDH3/8gbQ0+qDzT18KhUiT8pzntKw8hTumsaCgADNmzEDXrl3B5/ORkJAAT09PtmMRBRMWFoYRI0Zg+PDhWLJkyXd/n5OTE+Li4jBjxgz4+PjAwcFBoUb7eDwerKysqFD+hFIWSnoTURzv3r2Dq6sratasiXPnzqFKlSpsR1IIpqamWLZsGZ4/f44rV67A0dER/v7+aNy4MTp16oSDBw8iNzeX7Zise5GVC2mP3TIAnmcpzv/r+/fvo1WrVti8eTPWrl2LS5cuoUGDBmzHIgomPj4enp6e6Ny5M7Zv3/7Tp0paWlpYvnw5oqKiIBQKYW9vj8WLFyvMbha0MOfnlLJQ0puIYsjNzYWbmxs+f/6MixcvKsUWE7LG5XLRsWNHHDhwAG/fvsWePXsgFosxdOhQ1K1bF8OHD0d4eDjEYjHbUVlRJJTNzy2r+1SGWCzGhg0bYG9vD4ZhEBMTg+nTp4PLVcq3ASJFaWlp6NGjB0xMTHD8+PFyHU9sb2+P2NhYLFy4EP7+/rCzs0NsbKwU00qGjY0NkpOTae76DyjlKwm9icg/oVAILy8vJCUl4fz583SklQTo6upi2LBhuHbtGp49e4bZs2fjxo0bcHFxQdOmTbF48WI8efKE7ZgypaEmm5c4Wd2notLT09GjRw9MmzYN48aNQ0xMDKysrNiORRTQhw8f0L17d2hoaOD8+fOoWrVqua+hoaGBJUuWIDY2Furq6nBwcMC8efPkuqzZ2NhAJBIhKUmyWxEqE/l+FawgehORbwzDYOLEiQgJCcGJEydgZ2fHdiSl07hxY/j4+CA1NRU3b95E586dsW7dOhgbG8PZ2Rm7d+9GTk4O2zGlrrG+DqS9vIvzv/vIq9OnT8PS0hLx8fG4ePEi1q9fDy0tLbZjEQVUUFCAXr16ITMzExcvXkTdunUrdT1ra2tER0dj2bJlWLduHWxsbCAQCCSUVrIsLS3B5XLpsfcPKGUjojcR+fbHH39gx44d2LlzJ7p37852HKXG4XDQtm1b7Ny5s/QscW1tbYwePbr0LPHQ0FCF3iPuR3Q01WCkpy3VexjpaUNHU/72a8zNzcWYMWPg4eEBZ2dnJCYmolu3bmzHIgqqZCpNTEwMzp07BzMzM4lcV11dHfPnz0dcXBxq1KiBtm3bYvr06cjLk68DRLS1tWFqakqF8geUslDK5E1EXz7fROTdvn37sGjRIvj6+mL48OFsx1Ep2traGDhwIC5duoS0tDT4+Pjg7t276NatGxo1aoR58+bhwYMHbMeUOBezOlLbQowRi/Dk1jnMmTNHrvbYi4mJga2tLQ4fPoydO3fi1KlTqFWrFtuxiAKbOXMmTp48iT///BNOTk4Svz6fz0dERAQCAgKwbdu20u2s5AktzPkxpSyUgHTfRHhcDlxM60jl2sosNDQUo0ePxujRo7Fo0SK246i0hg0bYt68eUhOTkZ0dDR69eqFHTt2gM/nw8HBAVu2bEF2djbbMSVikIOR1LYQ43B56NJYE7t374aFhQVatWqFrVu34sOHD1K538+IRCL88ccfaN26NapXr464uDiMGjWK9nUllbJ27VqsX78eGzduRO/evaV2Hx6PhxkzZiAhIQH169eHi4sLJk6ciM+f5eMgkZIzvVV1kePPKG2hlOabiEjMYLCjkVSurazu3r2LPn36oFu3btiyZQu9wckJDodTuoVMeno6jh8/jjp16mDKlCmoV68e+vXrh+DgYIXbiPif6lflQr8oE4xIstt88bgcOBvXwt4Ny/HmzRucOHECBgYGmDx5MurVqwcvLy9cvHhRZtMJnj9/jg4dOsDHxwdz586FQCCAqampTO5NlNexY8cwc+ZMzJ07FxMnTpTJPU1MTBAeHo5NmzZh//79aN68OUJDQ2Vy7x+xsbHBly9f8PTpU7ajyCWlLZQmBrpwNq4l8VFKRiyCeQ3AuA6dJlFWz58/x6+//gpzc3McO3aMzgeWU5qamujbty/OnTuH169fY8WKFXj8+DF69uyJhg0bYsaMGQq1GTEA3LlzBy1atEDKEV+oq0l2w3w1Lgf+HpYA/v5/16dPH5w7dw4vX77EsmXLkJiYCFdXVxgZGWH+/Pl49OiRRO9fgmEYHDp0CNbW1nj58iXCw8OxbNmycm3lQsi3XL9+HUOHDsWgQYPg7+8v03tzuVxMmjQJiYmJMDExQbdu3TBq1Ch8/PhRpjn+qeQIRnrs/W1KWygBwN/DEmoSLpRcMAhbPhLDhg1TmkeC0pSVlYXu3btDR0cHwcHB0NGhhUyKwMDAANOnT8e9e/cQFxeHgQMH4tChQ7CxsYGtrS3Wr1+PzEz5PS1KJBJh5cqVcHR0hK6uLmLDL2GZh2S3yfFzt4DhN+Zq16tXD7NmzcL9+/dx+/Zt9OrVC9u2bUOzZs3QunVr7Ny5E58+fZJIho8fP2LgwIEYMmQI3N3dER8fD2dnZ4lcm6i2pKQk9O7dG87OztizZw9r+5U2adIEly9fxo4dO/DXX3+hefPmCA4OZiVLnTp1UL9+fSqU38FhlPwQ4KMxaZh3KlFi11vhaYn8+1cwffp0aGlpYevWrfDw8JDY9ZVJfn4+OnfujJSUFERGRsLY2JjtSKQSiouLcfHiRezbtw/nzp0DwzBwdXWFt7c33NzcoKmpyXZEAMDLly8xdOhQXL9+HXPnzoWvry80NDQAAIHXHiMgNKXS95jd1QwTXcr+97mgoABnzpzBvn37EBoaCk1NTXh6emLYsGHo2LFjhd6sr1+/jiFDhiAnJwfbtm2Dl5dXua9ByLe8fv0ajo6O0NPTw40bN1C9enW2IwH4+9/22LFjERISgsGDB2P9+vUyPxDj119/BYfDYa3UyjOlHqEEAK+WRpjVVTLziGZ3NYNXSyMMHz4cycnJaNWqFTw9PTFgwAC5Hq1hg0gkwqBBgxAXF4fg4GAqk0pAXV0dPXv2xMmTJ5Geno7169fj7du36Nu3L+rXr49JkyYhJiYGbH5GPX78OKysrJCamoqrV69i+fLlpWUSACa5mGCFpyU01bjlng7D43KgqcbFSk/LcpVJ4O9j5wYMGICQkJDSFfYxMTHo0qULGjdujEWLFpV50/mioiLMmzcPLi4u+OWXX5CQkEBlkkjMp0+f4OrqCg6Hg5CQELkpkwBgaGiI8+fPY9++fQgODoaFhQVOnTol0ww2NjaIi4uT6T0VhdKPUJY4GpOGxWeTIBQz5Vqsw+NyoMblwM/dAgNafr0Qh2EYHD16FJMnTwaHw8GmTZswYMAAlV9wwjAMpk6dis2bN+P06dPo2bMn25GIFCUnJ+PAgQM4ePAg3rx5A3NzcwwbNgyDBw9G/fr1ZZLh8+fPmDp1Kvbu3Yt+/fph+/btqFmz5nd//8vsPCwISsTN1PfgcTk/fE0o+bqzcS34e1h+8zF3RTAMg6ioKOzduxfHjh1DTk4OnJ2dMXz4cPTt2xe6uv+dp/3w4UMMGjQICQkJWLZsGWbNmgUeT7JzQ4nqKioqgqurK+7evYuIiAjw+Xy2I31Xeno6xo8fjzNnzqBfv34IDAxEnTrS333l+PHj6N+/PzIyMmRyP0WiMoUSkN6bSGZmJqZMmYJjx47B3d0dW7duldkbqTxavXo15syZg23btmHs2LFsxyEyIhKJEBYWhv379yMoKAhFRUXo0qULvL290bt3b1SpUkUq942OjsagQYPw9u1bBAYGwtvbu8wf6h5nfMbh6DRcS8lEWlYe/vmKwMHf+826mNbBYEcjqS7Ey8vLw+nTp7F3715cuXIFVapUQd++fTF8+HC0a9cOHA4H27Ztw8yZM2FkZITDhw/TCVNEosRiMYYMGYITJ07g8uXLaNeuHduRfophGPz111+YNGkSGIbBpk2b4OXlJdVBncePH8PU1BShoaHo0qWL1O6jkBgVlPI2h1l85j7TbvVVpvG8YKbRP3/NPce0W32VWXzmPvM4I6dc1z116hRjYGDAVK9endmzZw8jFoul9BPIr8OHDzMAmIULF7IdhbDo48ePzI4dO5g2bdowAJhq1aoxo0ePZm7duiWxfxdCoZBZunQpw+PxmFatWjGPHz+u1PW+FBQz919/ZO6+yGbuv/7IfCkolkjO8nrx4gWzdOlSpmnTpgwAxsjIiDE1NWUAMOPGjWNyc3NZyUWU25w5cxgAzLFjx9iOUm6ZmZnMgAEDGABMr169mDdv3kjtXiKRiKlatSqzatUqqd1DUalkofynf76JDBg3k7G2a1Wp62VlZTHe3t4MAKZr167M8+fPJZRU/l25coVRV1dnvL29VbJMk297/Pgxs2jRIqZRo0YMAMbY2Jjx8/Or1L+N58+fM23btmW4XC6zaNEipqioSIKJ5YNYLGZWrlzJaGlpMRwOhwHAuLi4MPv372e+fPnCdjyiRDZt2sQAYNauXct2lEopGdSpUaMGs3fvXqm9D7Vp04YZOHCgVK6tyFS+UP5TYGAgo66uzhQWFlb6WhcuXGAaNmzIVK1aldmyZQsjEokkkFB+xcfHM9WqVWO6du2qlG/upPJEIhFz9epVxtvbm9HR0SktSPv27WM+f/5c5uscOXKEqVatGtOoUSPm5s2bUkzMntzcXGbChAkMAKZHjx7MkydPmP379zMdOnRgADBVq1ZlRowYwdy8eZM+vJFKOXXqFMPhcJjp06ezHUUisrKymCFDhjAAmO7duzNpaWkSv8fEiRMZc3NziV9X0VGh/Idbt24xAJj4+HiJXO/Tp0/M2LFjGQBM+/btK/1ITl6lpaUxDRo0YGxsbJicnPJNEyCq6fPnz8z+/fsZFxcXBgCjo6PDDB06lLly5cp3P3x9/PiRGTx4MAOA+e2335gPHz7INrSM3L17lzE3N2e0tLSYwMDA/xTGp0+fMosXL2YaN25cOuK7bNkyqbxxEuUWERHBaGlpMf3791e6QY/g4GCmQYMGjK6uLrN9+3aJfvDauXMnw+VyafrJv1Ch/IecnBwGALN//36JXvfKlStMkyZNmCpVqjBr165lhEKhRK/Ppg8fPjAWFhZMo0aNpDpvhSiv58+fM0uXLmWMjY1L5wz+/vvvX30Au3XrFtO4cWNGV1eXOXToEItppUckEjErV65k1NXVGRsbGyYpKemnv//q1avM0KFDGW1tbYbD4TBdunRhDh8+zOTl5ckoNVFUDx8+ZPT09Jh27dox+fn5bMeRio8fPzKjRo1iADAdO3Zknjx5IpHrxsTEMACY6OhoiVxPWVCh/JemTZtKZej/y5cvzNSpUxkOh8M4OjoyycnJEr+HrBUUFDDt27dnatasqRQ/D2GXWCxmIiIimNGjRzPVqlVjADBOTk6Mm5sbw+VymdatWzNPnz5lO6ZUpKWlMR06dGA4HA4ze/ZspqCgoFzfn5OTw+zevZtp27Zt6SKoMWPGMAKBgB6Jk/9IT09nGjduzFhYWDDZ2dlsx5G60NBQplGjRoy2tjazcePGSo/G5ufnMzwej9m+fbuEEioHKpT/0qdPH6Zjx45Su/6tW7cYMzMzRkNDg/H391fY+YYikYgZMGAAo6mpydy6dYvtOETJ5OXlMevXr2eqV6/OAGDU1NSY/v37MyEhIUo1ws8wDHP06FGmRo0aTMOGDZmrV69W+nqPHz9mfv/9d8bQ0JABwJiZmTHLly9nXr9+LYG0RNHl5OQwtra2TP369VVqmkROTg4zceJEBgDTtm1b5tGjR5W6XvPmzZnx48dLKJ1yoEL5L35+foyenp5UP9Xn5+cz8+bNY7hcLmNra8vExcVJ7V7SMnPmTIbD4TAnT55kOwpRMmKxmNm/fz9TtWpVpkmTJsyZM2eYlStXMnw+nwHA1KtXj5kzZ85PHwlLi6S2F/r06RMzdOhQBgDTv39/iY8UCYVC5vLly8zAgQMZLS0thsvlMq6ursyxY8eU9hEn+bGioiKmW7dujK6ursTWCiia8PBwpmnTpoyWlhazevXqCn9AHTx4MNOqjbNcbDUmL1RqY/OyOHfuHNzd3ZGWlgZDQ0Op3is2NhYjRozAgwcPMH/+fCxcuFBuzkP+kQ0bNmDatGnYuHEjJk+ezHYcokQ+fPiA8ePH49ixY/D29sbGjRtRrVo1AH9vYnznzh3s378fR44cQXZ2Nuzt7eHt7Y3ffvtNqmf6lm6A/igTadnf2ABdTxsuZnUwyMEIJgY/3wBdIBBg8ODBeP/+PQIDAzFkyBCpbsb86dMnHDt2DPv27UNkZCRq1qyJ3377DcOGDYO9vb3Kn+6lChiGwYgRI3D48GGEhISgU6dObEdiTV5eHhYtWoR169ahZcuW2Lt3b5lPBSp5LQiKTsFHkfpX/3Yq8lqgTKhQ/svLly9hZGSEc+fOwc3NTer3Kyoqgr+/P/744w+YmZlhz549aNWqldTvW1EnTpxA//79MWvWLKxatYrtOESJXL9+HUOGDEFOTg62b9+OAQMGfPf3FhYW4vz589i/fz8uXLgADoeDnj17wtvbG66urlBXV5dIJkmfrlVcXIylS5fijz/+gKOjIw4dOoQmTZpIJGtZPXz4EPv378eBAwfw5s0bWFhYlB6VWbduXZlmIbLj4+ODpUuX4tChQxg0aBDbceRCZGQkRowYgadPn2Lx4sWYPXv2d1875OG4VnlHhfJfGIaBvr4+ZsyYgd9//11m901ISMCIESMQFxeHmTNnwtfXV2pH1VXUzZs30aVLF3h4eODw4cPgcrlsRyJKoLi4GEuWLMHy5cvh7OyMgwcPwsjIqMzfn5mZiT///BP79u3DvXv3ULt2bQwcOBDDhg2DjY1NhXMdjUnD4rNJEIqZH755/BuPy4EalwNfdwt4tfz/nyM1NRWDBw9GbGwsfHx8sGDBAqipqVU4X2WJRCJcvnwZe/fuxenTpyESieDq6orhw4fDzc0NGhoarGUjkrVjxw6MHTsWK1aswNy5c9mOI1cKCgrg6+uL1atXw8rKCnv37oW1tfVXv0fSrwXKigrlN3Ts2BF6eno4ceKETO8rFAqxZs0aLF68GEZGRtizZw/atm0r0wzf8+DBA7Rp0wY2NjYICQlRiEfzRP49fvwYAwcOxL179+Dn54c5c+aAx+NV+HoJCQnYv38/Dh8+jIyMDFhZWcHb2xuDBg2CgYFBma8TeO0xAkJTKpyjxKyuppjYwRh79uzB1KlTUbduXRw6dAiOjo6VvrYkZWdn4+jRo9i3bx9iYmKgr6+PQYMGYdiwYbC1tWU7HqmE4OBg9OrVC+PHj8emTZtoesN3/HMK2oIFC7Bw4UJoaGhI9LVgkouJBJLKLyqU3zBjxgycO3cOjx8/ZuX+Dx8+xIgRIxAVFYVJkybB398fVatWZSULALx58wZOTk6oVq0abt68iRo1arCWhSgHhmFKS1b9+vVx+PBhtGzZUmLXFwqFuHTpEvbt24ezZ8+Wjr55e3ujZ8+eP/xAdDQmDfNOJUosS6O3N3Fj30qMGDEC69evh66ufM+run//Pvbv34+DBw8iIyMD1tbWGDZsGAYNGoTatWuzHY+Uw+3bt+Hi4oJu3brh+PHjlfqwpgr+OQWtWbNmGOSzGdvufpbY9Vd6WmKAEo9UUqH8hv3792PYsGHIyclh7cVfJBIhMDAQ8+fPh4GBAXbt2sXKJOqcnBy0a9cOWVlZiIyMRMOGDWWegSiXrKwsjBkzBqdOncKoUaOwbt06qX5gys7OxrFjx7B//35ER0ejZs2a8PLygre3N1q1avXViM3L7Dx0XncdhUKxRO7NMAwgKsbvLRiM/s1TIteUFaFQiIsXL5aWcoZh4ObmhuHDh0t0niqRjtTUVDg5OcHU1BRhYWFyN4VKnsXHx2PohOn44DQJXDUNQEKjuppqXIRNb6+0cyppEtw3lMy7SkhIYC0Dj8fD1KlTkZiYiCZNmqBz584YM2YMPn36JLMMRUVF6NOnD54/f46QkBAqk6TSrly5AisrK4SHh+PkyZPYuXOn1Eff9fT0MH78eERFReHBgwcYO3Yszp49C0dHR/D5fKxYsQKvXr0CACwISoSwHHOkfobD4UBNXQM38hpI7JqyoqamBjc3N5w4cQJv3rzB2rVr8eLFC/Tq1QsNGzbEzJkzkZgouZFcIjmZmZno3r079PT0cPbsWSqT5WRtbY3mw/3BU5dcmQQAoZjBgiDl/TdDhfIbzM3Noa6ujvj4eLajoGnTpggLC8O2bdtw9OhRWFhY4Pz581K/L8MwGDVqFG7cuIHTp0+jefPmUr8nUV5FRUWYM2cOunTpgmbNmiEhIQGenrIfsWvWrBmWL1+OFy9eIDQ0FHZ2dvDz84ORkRHau3vhZur7ck26LwsRA9xMfY/UTMk9OpO1WrVqYfLkybh79y7u3buHgQMH4sCBA7CysoKdnR0CAwORlZXFdkwCIDc3F25ubvjy5QsuXrwo1e20lNXjjM+IeJIFBpKdbyoSMwr/WvAjVCi/QUNDA3w+H/fu3WM7CgCAy+Vi7NixuH//PiwtLeHm5oYhQ4ZI9QX8999/x8GDB7F//3506NBBavchyu/hw4dwdHTE+vXrsWrVKly+fBkNGrA7Ysfj8dClSxccOnQIb9++xc6dO5FV0xyMWCSd+3E5OBSVJpVry5q1tTXWrVuH169fIygoCIaGhpg+fTrq16+Pfv364fz58xAKhWzHVElCoRBeXl5ITk7G+fPnZb4llbI4HJ0GHlc6i5eU6bXg36hQfoeNjY3cFMoSRkZGuHDhAvbt24fg4GDw+XycPHlS4vfZtm0b/P39sXr1anh5eUn8+kQ1MAyDbdu2oUWLFsjPz0d0dDRmzZold9tNVatWDSNHjoR+83bgcKWzaEEkZnAtJVMq12aLhoYGevfujdOnT+P169dYsWIFHj16BDc3NxgaGmLOnDl48OAB2zFVBsMwmDhxIkJCQnDixAnY2dmxHUlhXXuUKfEnFSWU8bWghHy9sssRa2trJCYmyt0nbQ6HA29vbyQnJ6N169bo27cv+vXrh4yMDIlc/8yZM5g4cSKmTJmCmTNnSuSaRPW8e/eudKuSYcOG4c6dO3K9/cyXQiHSsvOkeo+0rDzkFsrX64mk1KlTB9OnT0d8fDzu3LmDvn37Yvfu3eDz+XBwcMC2bdvw4cMHtmMqtT/++AM7duzArl270L17d7bjKCx6Lag4KpTfYWNjg4KCAta2DvqZevXq4dSpUzh27BjCw8PB5/Nx+PBhVGbRflRUFH777Td4eHhg7dq1tF8ZqZDQ0FBYWVkhMjISZ86cwZYtW6CtLd+rGl9k5ULa210wAJ5n5Ur5LuzicDho0aIFNm3ahDdv3uDEiROoXbs2Jk6ciHr16uG3337DpUuXIBJJZ2qBqtq3bx8WLVoEPz8/DBs2jO04Co1eCyqOCuV3lOyULw8Lc76Hw+Ggf//+SE5ORrdu3TB48GC4u7vj9evX5b5WSkoK3NzcYGdnh0OHDtF+ZaTcCgoKMH36dHTr1g1WVlZISEiAu7s727HKpEhC2wTJy33kgaamJvr06YPg4GC8evUKS5cuRXx8PLp3745GjRphwYIFSEmp/IbRqu7SpUsYPXo0Ro8eLdPT3ZQVvRZUHBXK79DT04OhoaHczaP8ltq1a+PIkSM4ffo07ty5Az6fj927d5d5tDIjIwPdu3dH7dq1cebMGWhpaUk5MVE29+/fR6tWrbBlyxasX78eISEhqFevHtuxykxDTTYvhbK6j7ypV68eZs+ejaSkJERHR8Pd3R1bt26FmZkZ2rRpg127diEnJ4ftmArn7t276NOnD7p3744tW7bQUyUJoNeCilO+n0iC5HFhzo/06tULSUlJ6NOnD0aNGoWuXbvi+fPnP/yeL1++4Ndff0V+fj5CQkKgp6cnm7BEKTAMg8DAQNjb20MsFiMmJgZTp06Vu4U3P9NYX0fCG4T8F+d/91FlHA6n9INHeno6jh49Cl1dXYwZMwZ169bF4MGDceXKFYjFyjd6I2nPnj1Djx49wOfzcfToUVbPhVcm9FpQcYr1qi9jNjY2cv3I+1tq1qyJPXv24OLFi3j06BGaN2+OzZs3f/MFWigUYsCAAXj06BFCQkLQuHFj2QcmCisjIwNubm6YPHkyxowZg5iYGFhZWbEdq0J0NNVgJOXTK4z0taGjSW/6JbS0tDBgwABcvHgRaWlpWLRoEWJiYtC5c2c0adIEPj4+ePLkCdsx5VJWVhZcXV1RtWpVBAcHQ0dH+coJW+i1oOKoUP6AtbU13r59i7dv37Idpdy6deuG+/fvY+jQoZg0aRI6dOjw1QIjhmEwbtw4hIaG4tSpU6WnAxFSFufPn4elpSViY2Nx/vx5bNy4UeFP43AxqyPVvedcTOtI5drKoGHDhpg/fz4ePnyIiIgIdOvWDevXr4exsTHat2+PvXv34suXL2zHlAv5+flwd3dHVlYWLl68iDp16O+VpNFrQcVQofyBkpKlaKOUJapVq4YtW7bg2rVreP36NaysrLBmzRqIRCL4+flh9+7d2L17N7p06cJ2VKIg8vPzMWnSJLi5uaFVq1ZITExEjx492I4lEYMcjKS699xgRyOpXFuZcDgctG7dGjt27MDbt29x6NAhqKurY+TIkahbty6GDRuG69evq+wjcZFIhEGDBiEuLg7BwcEwNjZmO5JSoteCiqFC+QNNmjRB1apVFbZQlujQoQMSEhIwfvx4zJ49GyYmJliyZAn++OMPDB06lO14REHEx8fD3t4eu3fvxubNm3Hu3DmlGh0xMdCFs3EtiY9M8LgcOBvXgnEdXYleV9lpa2tj0KBBCAsLw7NnzzB37lzcvHkTHTp0gLGxMfz8/H46R1yZMAyDadOm4cyZM/jrr7/g4ODAdiSlRa8FFUOF8ge4XC6sra0VamHO9+jo6GDt2rVYvXo1nj17Bi6XC5FIhOLiYrajETknFouxbt06tGrVCmpqaoiNjcWECROUckWpv4cl1CT8JqLG5cDfw1Ki11Q1jRo1wqJFi5CamoobN26gQ4cOWLVqFZo0aYJOnTrh4MGDyM1Vvn39/mn16tUIDAzE1q1b4ebmxnYcpUevBeVHhfInFG2l94/ExsbCx8cHPXr0wJw5c+Dr64tWrVohLi6O7WhETr158wbdu3fHjBkzMGnSJNy+fRsWFhZsx5IaQz1t+LpL9ufzc7eAoZQn+asKDocDZ2dn7NmzB2/fvsW+ffsgFosxdOhQ1KtXD6NGjcKtW7cqdcCDPDpy5Ajmzp2L33//HWPGjGE7jkqg14Lyo0L5E9bW1nj06BHy8/PZjlIpT58+xa+//gpLS0scP34cy5cvx+3btyEWi9GyZUv8/vvvKCwsZDsmkSOnT5+GlZUV7t+/j9DQUKxZswaamppsx5I6r5ZGmNXVVCLXmt3VDANaKud8KbZVrVoV3t7euHbtGp48eYIZM2YgLCwMzs7OMDU1xR9//IGXL1+yHbPSrly5gmHDhsHb2xt+fn5sx1Ep9FpQPhxG2T7KSVhMTAxatWqF27dvo2XLlmzHqZD379+jdevWYBgGAoEAtWvXLv1aUVERVq5ciaVLl8LExAR79uyhuTkqLjc3FzNmzMCOHTvQq1cv7Nq1C7Vq1WI7lswdjUnD4rNJEIqZck3Q53E5UONy4OduofRvIPJGLBbj+vXr2Lt3L06cOIGCggJ07twZw4cPR+/evRVuJ4KEhAQ4OzvD0dERwcHBUFdXZzuSSip5LSgSisCUY5dKVXstoEL5E/n5+ahatSq2bduG0aNHsx2n3PLy8tCpUyc8ffoUAoEATZs2/ebvu3//PkaMGIE7d+5g+vTp8PPzk/vzl4nk3b17FwMHDkRaWhrWr1+P0aNHK+VcybJ6mZ2HBUGJuJn6Hjwu54fFsuTrzsa14O9hqdSPthRBTk4Ojh8/jn379uHWrVuoXr06vLy8MGzYMDg4OMj93+uXL1/C0dERBgYGuH79OnR1lXMhh6JIepGBbgv3Qs3Qkl4LvoMKZRnw+Xx07NgRgYGBbEcpF5FIhD59+uDy5csIDw//6QirUCjEunXrsGjRIhgaGmL37t1o166djNISNonFYgQEBOD333+HpaUlDh8+jGbNmrEdS248zviMw9FpuJaSibSsPPzzRZNhGDTW14GLWR0MdjRS2hWciuzx48fYv38/9u/fj1evXqFZs2YYNmwYhgwZgvr168skQ26hEM+zclEkFENDjYvG+jrf3dz648ePaNu2Lb58+YLIyEiFOsZUWS1duhT+/v64EpOE0Kf533wt4ODvTctdTFXztYAKZRmUjNjcunWL7ShlxjAMJk6ciB07duDs2bPl2ivw0aNHGDlyJCIiIjBx4kQsX76cPh0rsVevXmHo0KEIDw/HnDlz4OfnBw0NDbZjya1/FoOY6EiMG9QHT1Me0ElTCkAkEuHq1avYt28fTp06haKiInTr1g3Dhw+Hu7u7xOcIl34QeZSJtOxvlA89bbiY1cEgByOYGPz9GltYWIhu3bohMTERERER9MFODnz69AmNGzeGt7c31q9fX/rfy/MhQRVQoSyDVatWYenSpfj06ZPCnFG8YsUKzJ8/Hzt37sSoUaPK/f1isRibN2/GvHnzULt2bezcuZM2QFdCJ0+exOjRo6GtrY2DBw/CxcWF7UgK5cWLF2jcuDEuXLgAV1dXtuOQcvj48SP++usv7N27F1FRUahZsyYGDhyIYcOGwc7OrlKPxCs6VWJZLwvMmTgSZ8+eRVhYGNq0aVPhDERy/Pz8sHz5cjx9+pRGi39AMdoRy6ytrfHlyxc8e/aM7ShlcvDgQcyfPx8+Pj4VKpPA33twTp48Gffv30fTpk3RtWtXjBw5Eh8/fpRsWMKKL1++YOTIkejbty86duyIhIQEKpMVYGhoCB0dHSQnJ7MdhZRTjRo1MGbMGERGRuLBgwcYM2YMTp06hZYtW5aeKpaRkVHu6x6NSUPnddcheJoFAD9d0FXydcHTLLgEXMWFR59w5MgRKpNy4uPHj1i3bh3GjRtHZfInqFCWQckRjIqwH2VYWBhGjBiBESNGYMmSJZW+XpMmTRAWFoYdO3bg+PHjsLCwwLlz5yoflLDm9u3bsLW1xbFjx7Bnzx4cP34cenp6bMdSSFwuF82aNaNCqeCaNWuGFStWIC0tDRcuXACfz8eCBQvQoEEDuLu7IygoCEVFRT+9TuC1x5h3KhGFQnG5j+4TiRmIwIW+62S8rtG8oj8KkbANGzagoKAAc+bMYTuK3KNCWQYGBgYwMDCQ+yMY7927B09PT3Tu3Bnbtm2T2CpGDoeD0aNHIykpCTY2NnB3d8egQYPw/v17iVyfyIZIJMIff/yB1q1bQ09PD/fu3cPw4cPlfrWrvOPz+VQolYSamhpcXV1x7NgxpKenY+PGjUhPT4enpycaNGiAadOmfXdg4WhMGgJCUyp1/5J/iwGhKTgWk1apa5HKKxmdHD9+PI1OlgEVyjKS9xNzXrx4gR49esDU1BTHjx+Xyn5lhoaGCA4OxoEDBxASEgI+n4/jx49L/D5E8l68eAEXFxcsWrQI8+bNw61bt2BsbMx2LKXA5/Px4MEDpTudRdXp6elhwoQJiImJQWJiIry9vfHnn3/C1tYWNjY22LBhA969ewfg7zmTi88mSfT+PmeT8DI7T6LXJOWzfv16FBUV0ehkGVGhLCN5LpTZ2dlwdXWFlpYWzp8/j6pVq0rtXhwOB0OGDEFycjKcnZ3Rv39/9OnTB2/fvpXaPUnlHD16FNbW1njx4gXCw8OxbNky2iBZgszNzfHp0yekp6ezHYVISfPmzREQEIBXr17h3LlzaNq0KWbPno0GDRrA09MTo3ZchbCcj7h/RihmsCAoUaLXJGX38eNHrF+/HuPHj0fdunXZjqMQqFCWkbW1NV6+fIns7Gy2o3yloKAAvXv3RmZmJkJCQmBgYCCT+9atWxcnT57E8ePHcfPmTfD5fBw8eJBGaeRITk4Ohg4dit9++w2urq6Ij4+nfUWlgM/nAwA99lYB6urqcHNzw8mTJ/HmzRsEBATgybtcPPr045XcFSESM7iZ+h6pmZ8lel1SNjQ6WX5UKMuoZGGOPM2jFIvFGDp0KGJiYnDu3DmYmZnJPEPfvn2RnJyMHj16YOjQoXBzc8OrV69knoN8TSAQwMbGBqdPn8bBgwdx5MgR1KhRg+1YSqlJkybQ1NTEgwcP2I5CZKhWrVqYMmUKPGavBVdK05B5XA4ORdFcSln78OED1q1bhwkTJshskEYZUKEsI1NTU1SpUkWuHnvPnDkTJ0+exJ9//gknJyfWctSqVQuHDh3C2bNnce/ePVhYWGDnzp00WskCoVAIX19ftGvXDnXr1kV8fDwGDx5MC2+kSE1NDWZmZjRCqaKuPcqEhAcnS4nEDK6lZErn4uS71q9fj+LiYsyePZvtKAqFCmUZ8Xg8NG/eXG5GKNeuXYv169dj06ZN6N27N9txAAA9e/ZEUlIS+vXrhzFjxqBLly4Ks3enMnj69CnatWsHPz8/LFq0CDdu3ECTJk3YjqUSzM3NqVCqoC+FQqRJeeFMWlYecguFUr0H+X8fPnzA+vXraXSyAqhQloO8LMw5duwYZs6ciXnz5mHChAlsx/lKjRo1sGvXLoSGhiI1NRXNmzfHpk2bIBaL2Y6mtBiGwcGDB2FjY4O3b9/i5s2bWLx4MdTUVPcIMFmjrYNU04usXEj7OQwD4HlWrpTvQkqsW7cOxcXFNHeyAqhQloONjQ2Sk5PLtMGttISHh2Po0KEYPHgw/P39WcvxM126dEFiYiKGDx+OKVOmoF27dkhJqdwebeS/Pn78iIEDB2Lo0KHw8PDAvXv30Lp1a7ZjqRw+n4/379+XbiNDVEORUDYflGV1H1WXnZ2N9evXY+LEiahTpw7bcRQOFcpysLa2RnFxMWuT75OSktC7d284Oztj9+7dcj8vTldXF4GBgbh+/ToyMjJgbW2N1atXQyikxzeScPPmTVhbWyMkJAR//vkn9u/fj2rVqrEdSyWZm5sDAC3MUTEaarJ5C5XVfVTdunXrIBKJaO5kBdHf0nKwsrICwM4RjK9fv0b37t3RqFEjnDx5EhoaGjLPUFHt2rVDfHw8Jk2ahHnz5sHJyQmJibS/WkUVFxfj999/R4cOHdCoUSPEx8fDy8uL7VgqzcTEBDwejx57q5jG+jqQ9sd6zv/uQ6QrOzsbGzZsoNHJSqBCWQ66urpo2rSpzAvlp0+f4OrqCg6Hg5CQEFSvXl2m95cEbW1trF69GgKBAHl5ebCzs4Ofnx+r0wcUUWpqKtq0aYOVK1di6dKluHbtGho1asR2LJWnoaEBExMTGqFUMTqaajDS05bqPYz0taGjSfOhpW3t2rU0OllJVCjLycbGRqYrvYuKiuDp6YmXL1/i4sWLqF+/vszuLQ0ODg64e/cu5s6dCz8/P7Rs2RJ37txhO5bcYxgGe/fuhY2NDT58+ICIiAgsWLAAPB6P7Wjkf2ilt2pyMasDnpQ2ouRxOXAxpdEyacvKysKGDRswadIk1K5dm+04CosKZTmVrPSWxR6LYrEYw4cPx61bt3DmzJnSEzkUnaamJpYuXYqYmBhwuVw4ODhgwYIFKCgoYDuaXMrOzkb//v0xYsQIDBgwAHFxcWjVqhXbsci/0Epv1TTIwUjip+SUEIkZDHY0ksq1yf9bu3YtGIbBrFmz2I6i0KhQlpO1tTU+fPggk9Ng5s+fjyNHjuDQoUNKeWSera0tbt++DV9fX6xZswa2traIjIxkO5ZcuXbtGqysrHDlyhUcP34cu3fvlupZ7aTi+Hw+3rx5g0+fPrEdhciQiYEunI1rSXyUksflwNm4Fozr6Er0uuRrWVlZ2LhxI41OSgAVynIqOYJR2vMoAwMDsWrVKqxduxb9+vWT6r3YpK6ujoULF+Lu3buoVq0a2rRpgxkzZiAvT7qbBcu7oqIizJ07F506dYKpqSkSEhLQt29ftmORHyh5gkDzKFWPv4cl1CRcKNW4HPh7WEr0muS/1qxZQ6OTEkKFspwaNmwIPT09qRbKoKAgTJkyBdOnT8f06dOldh95YmFhAYFAgNWrV2Pr1q2wsrJCeHg427FY8ejRIzg5OWHdunVYuXIlwsLC0LBhQ7ZjkZ8wMzMDh8Ohx94qyFBPG77uFhK9pp+7BQylvOBH1b1//x6bNm3C5MmTUatWLbbjKDwqlOXE4XBgbW0ttYU5AoEAAwcORL9+/RAQECCVe8grHo+HmTNnIiEhAfXr14eLiwsmTJiAz58/sx1NJhiGwY4dO2Bra4vc3FxERUVh9uzZ4HLpn6kiqFKlCpo0aUKFUkV5tTTCrK6mErnW7K5mGNCS5k5K25o1awAAM2fOZDmJcqB3qgqQ1hGMjx49Qs+ePdGqVSvs379fZYuEiYkJwsPDERgYiAMHDqB58+a4dOkS27Gk6v379/Dw8MDYsWMxdOhQ3LlzBy1atGA7FiknPp9Pj7xV2CQXE6zwtISmGrfccyp5XA401bhY6WmJiS7GUkpIStDopOSpZmOpJGtrazx58gQ5OTkSu+bbt2/RvXt31KtXD6dPn4aWlpbErq2IuFwuJk6ciPv378PU1BTdu3fH8OHD8eHDB7ajSdzly5dhaWmJW7du4fTp09i2bRt0dGgjY0VEWwcRr5ZGCJveHq1/0QcA8H7SK0uKZ+tf9BE2vT2NTMpIQEAAOBwOjU5KEBXKCihZmCOp014+f/6MHj16oKioCBcuXEDNmjUlcl1l0LhxY4SGhmLXrl04deoU+Hw+zpw5w3YsiSgsLMTMmTPRtWtXWFlZITExEb169WI7FqkEPp+P58+fIzc3l+0ohEWGeto4ONIBl6e1g3M9oDj7zX9+DwdAI31tDHFohLDp7XBwpAPNmZSRd+/eITAwEFOmTIG+vj7bcZQGbb9fAebm5lBXV8e9e/fQpk2bSl2ruLgY/fr1Q2pqKm7evAkjI/p0+m8cDgcjR45E9+7dMW7cOPTu3RteXl7YuHGjwm7zkJSUhIEDB+Lhw4dYt24dpkyZorJTHJRJyUrvR48e0ZQFAhMDXTTMiITw9E48evEKL7LzUCQUQ0ONi8b6OnQCDksCAgLA5XIxY8YMtqMoFXoHqwANDQ3w+fxKz6NkGAZjxozB1atXERQUBGtra8kEVFINGjTA2bNncfjwYYSGhoLP5+PYsWMy2WReUhiGwebNm2Fvbw+hUIjbt29j2rRpVCaVhLm5OQDQY29SSiAQoHXr1qiqpQ6L+tVha1QTFvWrU5lkCY1OSg+9i1WQJI5gXLx4Mfbt24e9e/eiU6dOEkqm3DgcDgYOHIjk5GS4uLjAy8sLnp6eSE9PZzvaT2VmZqJnz56YNGkSRo0ahdjYWPoQoWR0dXXRsGFDKpQEACAUChEdHY3WrVuzHYX8T0BAAHg8nspsySdLVCgryMbGBomJiRAKhRX6/h07dmDp0qVYsWIFBg0aJOF0ys/AwAB//fUXTpw4AYFAAD6fj/3798vtaGVISAgsLS0RExOD8+fPY9OmTahSpQrbsYgU0BGMpERCQgLy8vKoUMqJzMxMGp2UIiqUFWRtbY2CggKkpKSU+3uDg4Mxfvx4TJw4EXPmzJFCOtXRp08fJCcno2fPnhg2bBh69OiBtLQ0tmOVys/Px5QpU9CjRw/Y29sjISEBPXr0YDsWkSLaOoiUEAgEUFdXh52dHdtRCP5/dJLmTkoHFcoKKnlUWd7H3rdv38aAAQPQq1cvbNiwARyOZI/rUkX6+vo4cOAAgoODkZiYiObNm2P79u0Qi8UVvmZuoRBJbz4hLu0Dkt58Qm5h+UeiExIS0LJlS+zYsQObNm1CcHAwDAwMKpyJKAZzc3OkpqaisLCQ7SiEZQKBAHZ2diq/DZw8yMzMxObNmzF16lTo6emxHUcp0azgCtLT04ORkRFi7iXAqn2PMq3cS01NhZubG6ytrXH48GHweDwZp1Zuv/76K5KSkjB79myMGzcOx44dw86dO9G0adMyff/jjM84HJ2Ga48ykZadh38+POcAMNLThotZHQxyMIKJge53ryMWi7Fp0ybMnTsXZmZmuHPnDiwsJHssG5FffD4fYrEYKSkpsLSks5hVmUAgQJ8+fdiOQQCsXr0aampqNHdSijiMvE46k2MlxeNIeDyKNKoB/xhl/F7xePfuHVq3bg0ulwuBQEDzN6QsLCwMo0ePRmZmJvz9/TFp0qTvFviX2XlYEJSIm6nvweNyIBJ//59EydedjWvB38PyP/vGpaenY/jw4bh06RKmT58Of39/Gp1QMVlZWahVqxaOHTuG/v37sx2HsOT169do2LAhTp48CU9PT7bjqLSMjAw0adIEs2bNgp+fH9txlBY98i6Hl9l5GLI7Gl3W38DB6Bco0qz+VZkEAAbAi+w8HIx+gS7rb2DI7mg8evUebm5u+Pz5My5evEhlUgY6d+6MxMREjBw5EtOnT0e7du3w8OHD//y+ozFp6LzuOgRPswDgh2Xyn18XPM1C53XXcTTm/+drnj17FlZWVoiPj8elS5ewdu1aKpMqSF9fHwYGBrQwR8UJBAIAgJOTE8tJyOrVq6Gurk6jk1JGhbKMKlM8um+KQCpjgPPnz6NJkyZSz0r+VrVqVWzcuBE3btzA+/fvYWNjgxUrVpSuzA+89hjzTiWiUCj+6Z/nv4nEDAqFYsw7lYi1l5Ixfvx49OrVC61bt0ZCQgK6du0qjR+JKAg6gpEIBAI0adIE9erVYzuKSnv79i22bNmCadOm0Sl0UkaFsgwqWzzEHB50O41FZE41KSUkP9K2bVvcu3cPU6dOxcKFC+Ho6IiAIAECQsu/Qv9bNoY/w7HYl9i2bRtOnz6tsKf3EMmhrYNIyYbmhF2rV6+GhoYGpk2bxnYUpUeF8ieOxqRVuniUrOQOCE3BsRj52dJGlVSpUgUrV65EVFQU8jhVsCniLQAJTR9mGNTqNgE9+g2hVfsEwN+FMiUlpcL71BLFlp+fj7t371KhZNnbt2+xdetWGp2UESqUP/AyOw+LzyZJ9Jo+Z5PwMjtPotckZdeyZUvYjlkFrroG/l5CJQEcDkQMsCAoUTLXIwrP3NwcxcXFePLkCdtRCAtiY2MhFAqpULJs1apVNDopQ1Qof2BBUCKE5XzE/TNCMUPFg0WPMz4j4mk2GEmVyf8RiRncTH2P1MzPEr0uUUx8Ph8AnemtqgQCAapWrYrmzZuzHUVllYxOTp8+HTVq1GA7jkqgQvkdjzM+42bq+3LPmfwZKh7sOhydBh5XOo+leVwODkXRlAby99GgNWvWpBNzVJRAIICDgwPU1GirZ7asXLkSmpqamDp1KttRVAYVyu+g4qGcrj3KlPiHhBIiMYNrKZlSuTZRLBwOhxbmqCiGYWhBDsvS09Oxbds2zJgxg0YnZYgK5XdQ8VA+XwqFSJPy/NW0rLwKHdNIlA9tHaSaUlNT8f79e7Rp04btKCpr5cqV0NLSotFJGaNC+Q1UPJTTi6xcSa3r/i4GwPOsXCnfhSgCPp+Phw8fVupMeaJ4BAIBOBwOHBwc2I6iktLT07F9+3bMmDED1atXZzuOSqFC+Q1UPJRTkVA2b+yyug+Rb3w+H/n5+Xjx4gXbUYgMRUREwMLCgh61smTFihXQ0tLClClT2I6icqhQfgMVD+WkoSabv+6yug+Rb+bm5gBopbeqofmT7Hnz5g2NTrKI3vm+gYqHcmqsryPhzYL+i/O/+xBiaGiIqlWrUqFUIR8/fkRSUhIVSpasWLEC2traNDrJEmo030DFQznpaKrBSE9bqvcw0teGjiZtFUL+Xultbm5OWwepkKioKACgQsmC169fY8eOHTQ6ySIqlN9AxUN5uZjVkep2UC6mdaRybaKYaOsg1SIQCFCrVi0YGxuzHUXlrFy5kkYnWUaF8juoeCinQQ5GUt0OarCjkVSuTRRTydZBDCPtZX5EHpTMn+RwpP2Mi/xTyejkzJkzUa1aNbbjqCwqlN9BxUM5mRjowtm4lsQ/LPC4HDgb14JxHV2JXpcoNj6fj8+fP+P169dsRyFSJhQKER0dTY+7WbBixQro6Ohg8uTJbEdRaVQov4OKh/Ly97CEmoT/XNW4HPh7WEr0mkTxlZzpTfMold/9+/fx5csX2tBcxl69ekWjk3KCCuUPUPFQToZ62vB1t5DoNf3cLWAo5Xm3RPE0btwYmpqaNI9SBQgEAqirq8POzo7tKCplxYoVqFq1Ko1OygEqlD8gjeKxxI1PxUMOeLU0wqyuphK51uyuZhjQkqYwkP/i8Xho1qwZFUoVEBERgRYtWqBKlSpsR1EZL1++xM6dOzFr1izo6tJTP7ZRofwJSRaPjzcOImyHHx3FJicmuZhghaclNNW45Z7awIhF4EGElZ6WmOhCKzrJ9/H5fHrkrQJoQ3PZW7FiBXR1dTFp0iS2oxBQoSyTyhQPHpcDTTUuVnpaInC8G/bu3YtJkybRqk854dXSCGHT26P1L/oA8NM/35KvN1TLxeud49FM44PUMxLFxufzkZSURP/mldibN2/w/PlzKpQy9PLlS+zatYtGJ+UIbYRYRl4tjdCmaS0sCErEzdT34HE5P1wFXvL11r/ow9/D8u/H3C0Ho6ioCCNHjoSGhgbWrVtH20vIAUM9bRwc6YDHGZ9xODoN11IykZaV99V57hz8vXeoi2kdDHY0glENTbQ48wdGjx6NyMhI8Hg8tuITOWdubo7s7Gy8e/cOderQdmHKKDIyEgBtaC5Ly5cvh66uLiZOnMh2FPI/VCjLoSLF49+ruUeMGIHCwkJMmDABWlpaWL58OZVKOWFioIsl7hZYAgvkFgrxPCsXRUIxNNS4aKyv85+N6Hfu3Ik2bdpg06ZNmDZtGjuhidwrWemdnJxMhVJJCQQCNGrUCPXr12c7ikpIS0vDrl27sHTpUhqdlCMchp7DVEpZise3bNiwAdOmTYOPjw98fX1lkJRIw5QpU7B7924kJSWhcePGbMchcqi4uBja2trYuHEjxo8fz3YcIgVOTk5o0qQJjhw5wnYUlTB+/HicOHECz549Q9WqVdmOQ/6HRigrSUdTDRb1y39u6NSpU1FYWIi5c+dCU1MTCxYskEI6Im1//PEHTp8+jXHjxiEkJIRGm8l/qKurw8TEhFZ6K6mCggLcuXMHgwYNYjuKSkhLS8Pu3buxbNkyKpNyhgoli+bMmYPCwkIsXLgQmpqamDlzJtuRSDnp6upiy5Yt6NmzJ44cOUJvKuSb6Exv5XXnzh0UFxfThuYy4u/vj+rVq2PChAlsRyH/Qqu8WbZo0SIsXLgQs2bNwqZNm9iOQyrAzc0NXl5emDp1Kt69e8d2HCKHaOsg5SUQCKCjowNLSzqwQtpevHiBPXv2YM6cOTQ6KYeoUMqBpUuXYtasWZgyZQp27NjBdhxSAevXr4dYLMaMGTPYjkLkkLm5OdLT0/HhA20zpWwEAgEcHBygpkYP/KSNRiflGxVKOcDhcLBq1SpMnjwZY8eOxb59+/6vvfuPq/le/AD+OqdfKkWlohSa0Emjkh+5rrXMjAdfbH4b5keM4dq4SDPWj82PDRdzLXdjiLlmlzt3s5Fhjlp+TSUS+mUrq9DvU6fz+f6xW3dnSDnn0+ec0+v5eOxRj1Wfzyu/ep33r4/UkaiRXF1d8eGHH2LPnj04duyY1HHIwPCZ3qZJEAScPXuWxwU1gd+PTtra2kodhx6BhdJAyGQybNq0CWFhYZg+fTp3CxqhqVOnIjQ0FLNnz0ZpaanUcciAdOnSBXK5nIXSxNy8eRO//vorC2UTiI6OhoODA0cnDRgLpQGRyWTYtm0bpk6diilTpuDgwYNSR6JGkMlk2L59O/Lz87Fy5Uqp45ABsba2hpeXFzfmmBilUgkA6Nu3r8RJTFtmZiY+/fRTjk4aOBZKAyOXy7Fjxw6MGzcOEyZMwJEjR6SORI3wzDPP4N1338WmTZuQlJQkdRwyID4+PiyUJkapVEKhUMDBwUHqKCYtOjoajo6OPMfVwLFQGiAzMzPs2rULI0eOxJgxY/DNN99IHYkaYdGiRejRowdmzpyJ6upqqeOQgeDRQaZHqVRyultkt2/fxs6dOzk6aQRYKA2Uubk54uLiMGTIEIwcORInTpyQOhI1kLm5OXbs2IHU1FSsX79e6jhkIBQKBbKzs7m+1kQ8ePAAKSkpLJQii4mJ4eikkWChNGAWFhY4cOAAnn/+eQwfPhynT5+WOhI1UEBAAN58802sXr0aN27ckDoOGQAfHx8AwLVr1yROQvqQmJgIQRB4oLmIakcnly5dChsbG6nj0BOwUBo4KysrfPHFF+jfvz+GDRuGc+fOSR2JGmjVqlVwd3fHrFmzoNFopI5DEuvWrRsAcNrbRCiVSjg5OcHb21vqKCYrOjoaTk5OmDNnjtRRqAFYKI2AtbU1/vWvfyEgIABDhgzhZg8jYWNjg+3bt+PUqVP45JNPpI5DErOzs4OnpyePDjIRtesnZTKZ1FFM0q1btzg6aWRYKI2Era0tvvrqK/j6+mLw4MG4fPmy1JGoAQYNGoRp06ZhyZIl+OWXX6SOQxLjxhzTUFNTg4SEBK6fFFF0dDTatGmD2bNnSx2FGoiF0ojY2dnh66+/RufOnTFo0CCkpKRIHYkaYP369bCwsMCCBQukjkIS49FBpiElJQUlJSUslCK5efMmdu3ahWXLlnF00oiwUBqZVq1a4dixY/Dw8EBoaCgX+BsBJycn/O1vf8PBgwdx+PBhqeOQhBQKBW7duoXKykqpo5AOlEolzM3N0atXL6mjmKTo6Gg4OztzdNLIsFAaIUdHR3z33XdwdnZGaGgoMjIypI5ETzBu3DgMGzYMc+fOxYMHD6SOQxJRKBTQaDRIT0+XOgrpQKlUwt/fn6NnIsjIyMBnn32GZcuWwdraWuo41AgslEaqTZs2OHHiBOzs7PD8888jMzNT6khUD5lMho8++gjFxcVYvny51HFIIrVHB3Ha27jxQHPxREdHw8XFBWFhYVJHoUZioTRirq6uOHHiBCwtLfH8888jJydH6khUD09PT8TExGDbtm04e/as1HFIAg4ODmjbti0LpRHLy8vDrVu3WChFkJGRgd27d3N00kixUBo5d3d3xMfHQxAEhIaGciexgZs7dy769OmDmTNnQqVSSR2HJKBQKHh0kBGrPQuYhVL/oqKi4OLiglmzZkkdhZ4CC6UJ8PT0RHx8PCoqKhAaGoq7d+9KHYkew8zMDDt27EBGRgZiYmKkjkMS4NFBxk2pVMLT0xPt27eXOopJycjIwJ49ezg6acRYKE1Ep06dEB8fj3v37mHQoEEoLCyUOhI9Rvfu3bF8+XK89957SE1NlToONTEfHx+kp6ejurpa6ij0FLh+UhyRkZFcO2nkWChNiLe3N06cOIG8vDy88MILuHfvntSR6DHCw8Ph5eWFmTNnoqamRuo41IQUCgXUajVPZzBCKpUK58+fZ6HUsxs3bmDPnj1Yvnw5WrRoIXUcekoslCZGoVDg+PHjyMrKwpAhQ1BcXCx1JHqEFi1aIDY2FgkJCdi2bZvUcagJKRQKAOA6SiN08eJFVFVVsVDqWWRkJNq2bcu1k0aOhdIEPfvss/juu++Qnp6OoUOHorS0VOpI9AgDBgzAnDlzsHz5cu7Qb0acnZ3h6OjIdZRG6OzZs7CxscGzzz4rdRSTkZ6ejr1793J00gSwUJqogIAAHDt2DFeuXMHw4cNRXl4udSR6hPfffx/29vaYO3cuBEGQOg41AZlMxo05RkqpVKJ3796wsLCQOorJiIyMRLt27TBz5kypo5COWChNWO/evfH1118jKSkJI0eO5OPeDFCrVq2wdetWfPXVVzhw4IDUcaiJ8Ogg4yMIAjfk6Nn169cRFxfH0UkTwUJp4vr374+vvvoKP/zwA1555RVUVVVJHYn+YOTIkXj55ZexYMECFBUVSR2HmoBCocC1a9e4IcuI3L59G/n5+SyUesTRSdPCQtkMPPfcczh8+DCOHz+OcePG8bgSA7R582aoVCosXrxY6ijUBHx8fFBZWclHphoRpVIJAOjXr5/ESUzDtWvXsG/fPoSHh8PKykrqOKQHLJTNxAsvvIAvvvgCR48exeTJk6FWq6WORL/Trl07rFu3Dp9++ilOnDghdRwSWe1Ob66jNB5KpRI+Pj5wdHSUOopJiIqKgpubG2bMmCF1FNITFspmZNiwYfj888/xxRdf4LXXXuN0m4GZMWMGBg4ciNmzZ3MTlYlzd3eHnZ0d11EaEa6f1B+OTpomFspmZtSoUYiLi0NcXBzCwsKg0WikjkT/JZfL8fHHHyM3NxerV6+WOg6JSCaTwcfHhyOURqK4uBjJyckslHoSGRkJd3d3TJ8+XeoopEfmUgegpjd27FhUVVVhypQpsLKywtatWyGTyaSORQC6dOmClStXYuXKlRg/fjz8/f2ljkQiUSgUfPSmkfjxxx+h0WhYKPUgLS0N+/btw0cffcTRSRPDEcpmavLkydixYwe2bduGRYsW8QxEA7JkyRIoFArMnDmTa11NWO3RQfy7Z/iUSiUcHR3RpUsXqaMYvcjISLRv3x6vvfaa1FFIz1gom7Hp06fjo48+wqZNm7Bs2TL+YDMQFhYW2LFjBy5duoSNGzdKHYdEolAoUFpaitzcXKmj0BOcPXsW/fr1g1zOH5m6uHr1Kvbv348VK1ZwdNIE8W9HM/f6669j48aNWLt2LVatWiV1HPqv3r17Y+HChVi5ciVu3boldRwSgY+PDwDu9DZ0NTU1SEhI4HS3HkRGRsLDw4OjkyaKhZKwcOFCrFmzBu+++y5iYmKkjkP/FRkZCRcXF8yePZujxyaoQ4cOsLa2ZqE0cFevXkVxcTELpY5SU1Px+eefY8WKFbC0tJQ6DomAm3IIAPDXv/4VKpWqbirirbfekjpSs9eyZUts27YNQ4cOxWeffYapU6dKHYn0yMzMDN26dePRQQZOqVTCzMwMQUFBUkcxeGUqNTILy1Cl1sDSXI6OTrawtfqtZtSOTk6bNk3akCQaFkqqExERgcrKSixevBiWlpaYP3++1JGavZdeegmTJk3Cm2++iZdeegkuLi5SRyI94tFBhk+pVMLf3x+2trZSRzFIN/JLsDcxGyev30V2UTl+P5ciA+DpaINnnc1w6MQ5bInm6KQpY6GkOjKZDFFRUVCpVFiwYAGsrKwQFhYmdaxmb8OGDfjmm2/wl7/8BXFxcVLHIT1SKBT4+uuvIQgCj+4yUEqlEkOHDpU6hsHJKSpH+JfJOJNRADO5DDWah5flCACyisqRVaiB28yPcErmiJeKyuHhaNP0gUl0XENJWmQyGdatW4f58+dj9uzZ2Llzp9SRmj1nZ2ds2LAB+/btw3/+8x+p45AeKRQK3C+twA8pmbiUfQ+pPz9AmYpHRRmKu3fvIiMjg+sn/2B/UjYGbTgF5a1CAHhkmdQi+61qJGTew6ANp7A/KVvsiCQBmcDV/vQIgiBgzpw5iI2NxZ49ezBx4kSpIzVrgiBgyJAhSEtLQ2pqKuzs7KSORDqonSY8lpKLn4urtUYna6cJQ7q6YFIfT3i78vdaKocPH8bIkSORnZ0NDw8PqeMYhC0nb2D9t+k6X2fx4C54I8RbD4nIULBQ0mNpNBrMmDEDu3fvxv79+/HKK69IHalZu337Nrp3746ZM2di06ZNUsehp9CQacJatR8f0LkNYkb5cZpQAkuXLkVcXBxycnKkjmIQ9idlY9mhZL1db81oP4wL8tTb9UhanPKmx5LL5dixYwfGjRuHCRMm4MiRI1JHatY6deqEyMhIbN68GQkJCVLHoUZq7DRh7ceVtwo5TSgRpVLJ6e7/yikqxztH9Puo0JVHUpFTVK7Xa5J0WCipXmZmZti1axdGjhyJMWPG4JtvvpE6UrO2YMECBAYGYtasWaiqqpI6DjXQlpM3sOxQMlRqzZPXm/1BjUaASq3BskPJ2HLyhkgJ6Y9UKhWSkpJYKP8r/MtkqBv5Z/dJ1BoB4V/qb8STpMVCSU9kbm6OuLg4DBkyBCNHjsSJEyekjtRsmZubY8eOHUhLS8PatWuljkMNsD8pWy9rzgBg/bfp+JwjlU3i0qVLUKlULJT4bc3vmYyCRr8YepIajYAzGQXIuFui1+uSNFgoqUEsLCxw4MABhISEYPjw4Th9+rTUkZqtHj16YMmSJYiMjMS1a9ekjkP14DSh8VIqlbC2tkbPnj2ljiK5vYnZMJOLc6yVmVyGPQl8kWQKWCipwaysrHDo0CEEBwdj2LBhOHfunNSRmq2VK1fC09MTYWFh0Gg0Usehx+A0ofFSKpXo3bs3LCwspI4iuZPX7+p9dLJWjUbAyfS7olybmhYLJTWKtbU1Dh8+DH9/fwwZMgRJSUlSR2qWrK2t8fHHH+PMmTOIjY2VOg49AqcJjZcgCDh79iynuwGUqtTIFnlEPLuwnOevmgAWSmo0W1tbHD16FL6+vhg8eDAuX74sdaRmKSQkBDNmzMBf//pX3LlzR+o49AecJjReWVlZyMvLM/lCKQgCqqqqUF5ejgcPHqCwsBD5+fnIzc1FZmYmbty4ge/Pp0DsswUFAJmFZSLfhcTGcyjpqT148ACDBg3C7du38f3336N79+5SR2p27t27Bx8fHwQHB+PQoUNSx6HfGbjuJLJEHNnp4GSDU4tDRLt+c7Znzx68+uqryMrKQqtWraBWq1FdXQ21Wq31fmP/n6Fco/b9hiyXsWzXBe2mfij6r/mXrwfD39NB9PuQePgsb3pqrVq1wrFjxxAaGorQ0FCcOnUK3bp1kzpWs+Lg4IDNmzdj7NixOHToEEaPHi11JELTThPaWjXdP+MajcZoypIun19btDp06KD3X0O5XA4LCwuYm5vXvf39+w35mLm5OaytrWFnZ6fTNRry/3LLgBVnSvX+6/BHluacMDV2HKEknRUUFOC5555DUVERTp8+jc6dO0sdqVkRBAEjR47Ejz/+iLS0NLRu3VrqSM1e6s8PMGzzD6Lf5yVcRkv1/SYrXGJuADMzM2tU0dFHWXrcdaOjo9GhQwe8/vrrT32NR33MzMwMcrlxFacylRrdVx0TddpbBiBl1YtN+uKI9I+FkvQiPz8fAwcORHl5OU6fPo2OHTtKHalZyc3NhUKhwIQJE7B9+3ap4zR7l7LvYdQ2pej3kR//ABbFd0QrXGKWtt9/zJCKVmlpKVq1aoXt27dj5syZUscxCFy+QQ3BlwOkF66urjhx4gQGDhyI559/HqdOnYKHh4fUsZqN9u3b4/3338e8efMwceJEDBw4UOpIzVpTTd/9+/CX8HVr1ST3ai4SExOh0WhMfkNOY/TtYIfsojII0P8mMzO5DCFdXPR+XWp6hvGSkEyCu7s74uPjodFoEBoail9++UXqSM3KnDlzEBwcjLCwMFRWVkodp9mpqKjAuXPn8Le//Q0xyxcBIk/+yAB0dLIV9R7NkVKpROvWrbkeHEBeXh6WLFmCv781SZQyCfx2DNbkvp6iXJuaFgsl6ZWnpyfi4+NRUVGB0NBQ3L3LA2ubilwuR2xsLG7fvo2oqCip45i06upqXLp0CbGxsQgLC4O/vz/s7e0RHByMJUuWIONaKmw04m7K8XSy4ZozESiVSvTr189gpuClkJOTg/nz56Njx474+OOPMX/qGPTpYK/3Y7DM5DIM6NwGnV3s9Hpdkkbz/RtDovHy8kJ8fDzu3buHQYMGobCwUOpIzYZCocCKFSuwZs0aXLlyReo4JkGj0eDatWvYvXs3FixYgH79+sHe3h4BAQGYM2cOEhMTERAQgM2bN+P8+fMoKSlBYmIixv7JV9RzKDlNqH8ajQbnzp1D//79pY4iiZs3b2LWrFl45plnEBcXh4iICGRlZSEqKgrrxwbCXM9/ns3lMsSM8tPrNUk63JRDorl69Sqee+45tG/fHidOnICDA88YawoqlQoBAQFo2bIllEolzMzMpI5kNARBQFZWFpKSkur+u3DhAkpKfnsqjbe3N4KCgur+8/f3h42NzSOvdSO/BC9sFO+Z98cX/ZkjO3qWmpqK7t27Iz4+HiEhzWeTyNWrV/Hee+8hLi4Ozs7OWLx4MebMmYOWLVtqfd7+pGwsO6S/x36uGe2HcUGc7jYVnC8h0SgUChw/fhwhISEYMmQIvvvuO9jb20sdy+RZWVkhNjYWf/rTn7BlyxYsXLhQ6kgGKy8vT6s8nj9/HgUFBQAADw8PBAUFITw8HEFBQQgMDGzUkUzernYY0LkNlLcK9fr4RTO5DMFeTiyTIqh9ARYUFCR1lCZx+fJlREdH44svvoC7uzs2bdqEGTNmwNra+pGfPz7IEwWlKqz/Nl3ney8Z3JVl0sRwhJJEd/HiRYSGhkKhUODYsWMPveolcbzxxhvYuXMnUlNTRTmg2djcu3cP58+f1yqPubm5AABnZ2etkcdevXrB1dVV53vmFJVj0IZTUKn1d36jlbkcxxcNhIfjo0dG6em99tpruHLlCi5cuCB1FFElJCQgOjoaX331Fby8vLB8+XJMmTIFlpaWDfr6/UnZeOdIKtQaoVEvlszkMpjLZXh3hC/LpAlioaQm8eOPP2LQoEEIDAzE0aNHHztNSPpTXFwMX19f+Pn54ejRo5DJxFnPZ4jKyspw8eLFuuKYlJSEjIwMAIC9vT169epVVxyDgoLg6ekp2q8PpwmNR9euXTF48GBs3rxZ6ih6JwgCTp8+jaioKBw/fhzdunXDihUrMH78eJibN36yMqeoHOFfJuNMRgHM5LJ6i2Xtxwd0boOYUX58MWSiWCipyZw9exYvvvgigoODceTIEbRo0ULqSCbv3//+N0aMGIG9e/di4sSJUscRhUqlwpUrV7RGH69evQqNRgNra2v4+/vXFcegoCB4e3s3+Q7eLSdv6G2acF4In0QlhoKCAjg7OyMuLg4TJkyQOo7eCIKAb7/9FlFRUfjhhx/Qo0cPREREYPTo0Xr5e3AjvwR7E7NxMv0usgvLtZ6oI8NvpxGEdHHB5L6eXKZh4lgoqUl9//33eOmllxAaGopDhw41eIqFnt64ceMQHx+PtLQ0tGnTRuo4OqmpqUFaWprWuscrV66gqqoK5ubm8PPz05q69vX1farRFzFwmtCw1b74yszMNIklIhqNBv/+978RFRWF8+fPo0+fPoiIiMCwYcNEG40vU6mRWViGKrUGluZydHSy5dFWzQgLJTW5b7/9FsOHD8fQoUNx4MABWFhYSB3JpOXn58PHxwfDhw/Hrl27pI7TYIIg4ObNm1rl8eLFiygvL4dMJkO3bt20ymOPHj0MftSb04SGa9myZdi9ezdyc3ONenlITU0NDh48iOjoaCQnJ2PgwIGIiIhAaGioUX9fZPhYKEkSR48exahRozBq1Cjs3bvXYEaRTNUnn3yCGTNm4NixYxg8eLDUcR4iCALu3Lnz0I7r+/fvAwA6deqkVR4DAgJgZ2e802ecJjQ8f/7zn+Hq6op//vOfUkd5KtXV1YiLi0NMTAzS09Px4osvYsWKFRgwYIDU0aiZYKEkyXz55ZcYM2YMJkyYgJ07d/K8RBEJgoBBgwbh1q1bSElJga2ttI/sKygoeKg85uXlAQDatWunVR4DAwONfqq+PpwmlF5VVRVatWqF9957D3/5y1+kjtMoKpUKO3fuxPvvv4/MzEz83//9H1asWNFsjj4iw8FCSZI6cOAAJkyYgGnTpiE2NrZZP+5MbBkZGfDz88O8efOwfv36JrtvcXExLly4oLXjOjMzEwDg4OCgdVRPUFAQ3N3dmywbEfDbKRR9+vRBYmIievfuLXWcBikvL0dsbCzWrl2LX375BWPHjkV4eDieffZZqaNRM8WXwSSpsWPHoqqqClOmTIGVlRW2bt3KdT4i6dy5M1atWoXw8HCMHz8evXr10vs9KioqcPnyZa0d19evX4cgCLC1tUVgYCBGjx5dVyK9vLz4+02SUyqVaNGiBXr27Cl1lCcqLi7Gtm3b8MEHH6CoqAiTJ0/G8uXL0bVrV6mjUTPHEUoyCLVr/BYuXIgNGzawZIikuroavXv3hiAISEpK0mlDVHV1NVJTU7WmrlNSUqBWq2FpaYmePXtqHdfTrVs3LmsggzR27Fjk5eXh9GnxHpWpq6KiImzevBmbNm1CWVkZXnvtNSxduhSdOnWSOhoRAI5QkoGYPn06VCoV5s6dCysrK7z//vsslSKwsLDAjh070Lt3b3z44YdYunRpg75Oo9EgPT1dqzxevnwZlZWVkMvl6N69O3r16oXZs2cjKCgIfn5+PBKKjIIgCDh79ixeffVVqaM80t27d7FhwwZs3boVarUaYWFhWLx4Mdq3by91NCItLJRkMF5//XWoVCosWrQILVq0wOrVq6WOZJICAwOxaNEirFq1CqNHj4a3t7fWxwVBQFZWllZ5vHDhAkpKSgAA3t7eCAoKwrhx4xAUFAR/f38++YiMVk5ODn7++WcEBwdLHUXLnTt3sH79emzfvh1mZmaYN28eFi1apJdHghKJgVPeZHDWrFmDZcuWITo6GuHh4VLHMUllZWXw8/NDx44dsXfv3oeecV1QUAAA8PDweGjHdevWraUNT6RH+/fvx4QJE3D37l04OztLHQe3b9/GmjVr8Omnn8LGxgYLFy7EggUL4OjoKHU0onpxhJIMztKlS6FSqbBixQpYWVnhrbfekjqSybh3715deXRzc8PJkyfh5uYGAHB2dkZQUBDmzZtXt+uaoyFk6s6ePQtvb2/Jy2R6ejpiYmKwZ88eODg4YPXq1Zg7dy7s7e0lzUXUUCyUZJDefvttqFQqLF68GJaWlpg/f77UkYxOWVkZLl68qDX6mJGRAQCwt7dHr1690L17d9y+fRsnT55Er169uG6Vmh2lUinpdHdycjKio6Nx4MABtGvXDuvXr8esWbMkPyuWqLFYKMkgyWQyREVFQaVSYcGCBbCyskJYWJjUsQyWSqVCcnKy1rrHq1evQqPRoEWLFvD398fQoUPrpq69vb0hl8tRWFgIHx8frFu3DgcOHJD62yBqUqWlpfjpp58wZ86cJr/3+fPnERUVhcOHD6Njx4746KOPMG3aNIN/fCjR47BQksGSyWRYt24dqqqqMHv2bFhaWmLatGlP/DpTf/JITU0N0tLStMrjlStXUFVVBXNzc/j5+SE4OBgLFy5EUFAQfH19H/toSycnJ2zcuBGTJk3CkSNHMGLEiCb+boikk5SUhJqamiYdofzhhx8QHR2Nb775Bt7e3vj0008xadIknY7wIjIEpvNTlkySTCbDpk2boFKpMH36dFhaWmLixIkPfV7ds5Gv30V20SOejexog5CuLpjUxxPersbzbGRBEHDz5k2t8njx4kWUl5dDJpOhW7duCAoKwtSpUxEUFIQePXo0eoRjwoQJ2LNnD+bOnYvnnnuOa7ao2VAqlWjVqhV8fHxEvY8gCIiPj0dkZCROnTqF7t27Y9++fRgzZgzPZiWTwV3eZBQ0Gg1mzJiB3bt3Y//+/XjllVcAADlF5Qj/MhlnMgpgJpehRvP4P861Hx/QuQ1iRvnBw9GwjroRBAF37tx56BnX9+/fBwB06tRJa8d1QEAA7Oz0U46zsrLg6+uLqVOnYuvWrXq5JpGhGzZsGDQaDb7++mtRri8IAo4ePYro6GgkJCQgMDAQERERGDFiBB8zSyaHhZKMRk1NDaZMmYIDBw7g4MGDqHDzxztHUqHWCPUWyT8yk8tgLpdh9QhfjA/yFDFx/QoKCrSKY1JSEvLy8gAA7dq1e+i4njZt2oiaZ9OmTVi0aBHOnDmD/v37i3ovIqlpNBq0adMGixYtwttvv633ax86dAjR0dG4fPky+vfvj4iICLz44ovc+EYmi4WSjIparcb48eMRn28J+z9N0vl6iwd3wRsh3k/+RB0VFxfjwoULWjuuMzMzAQAODg51xbH2UYXu7u6iZ/qj2rVkJSUluHTpEqysrJo8A5GYfr+++k5OFkaE9MN3X3+F0NBQvVxfrVZj//79iImJQVpaGkJDQxEREYGBAweySJLJY6Eko7Pn3C1EHEnT2/XWjPbDOD2OVFZUVOCnn37Smrq+fv06BEGAra0tAgMDtZ5x7eXlZTA/bJKTkxEQEICIiAi88847Usch0ll966sFQYCngzVCfdrqtL66qqoKn332Gd577z3cunULw4YNw4oVK9CvXz/9fBNERoCFkoxKTlE5Bm04BZVao7drWpnLcXzRwKdaU1ldXY3U1FSt8piSkgK1Wg1LS0v07NlTqzx269bN4BfhR0REYO3atbh8+TIUCoXUcYieSlOsr66oqMA//vEPrF27Frm5uXj55ZcRHh4Of39/fX0bREaDhZKMyqv/SITyVmGj1kw+iZlchmAvJ+ye0afez9NoNEhPT9cqj5cvX0ZlZSXkcjl8fX211j36+fnB0tJSbzmbSmVlJXr06IE2bdrgzJkz3DxARmd/Urao66tLS0vx97//HevXr8evv/6KiRMnYvny5XwBRs0aCyUZjRv5JXhh42nRrn980Z/R2eW3KS9BEJCVlaVVHi9cuICSkhIAgLe3t1Z57Nmzp0k92eL06dMYOHAgtm7dirlz50odh6jBtpy8gfXfput8nUetr75//z62bNmCDRs2oKSkBFOnTsXSpUvRuXNnne9HZOxYKMlorDqSit2JWXodnaxlJgP+5CqgQ+GPdRtnCgoKAAAeHh4P7bhu3bq13jMYmtmzZ2Pfvn1ITU2Fh4eH1HGInmh/UjaWHUrW2/Vq11cXFBRg48aN2Lx5M1QqFWbNmoUlS5bA01O6UyKIDA0LJRmNgetOIquoXLTrVxf9jOovVzy049rV1VW0exqy+/fvQ6FQoFevXjh8+LDBbBwiehQx1ldbmskQWqnEZ9s2QCaT4fXXX8ebb76Jdu3a6e0eRKaCT8oho1CqUiNbxDIJAJaObriefQctW/ARaADQunVrbNmyBS+//DIOHjyIMWPGSB2J6LHCv0yGWs+zF6pqNY78Yos333wTCxcuFP0sWCJjxtX2ZBSyCssg9lC6AIg6AmqMRo8ejVGjRuGNN95AUVGR1HGIHulGfgnOZBTofTmMTG4GC89nMXX+X1kmiZ6AhZKMQpUep7EM4T7GZMuWLaisrMSSJUukjkL0SHsTs2EmF2dJhplchj0J2aJcm8iUsFCSUbA0b5o/qk11H2Pi5uaGtWvX4pNPPkF8fLzUcYgecvL6XVE26wFAjUbAyfS7olybyJTwpycZhY5OthB9S4ggYH/sZhw/frzueCD6zaxZszBgwACEhYWhoqJC6jhEdZpifXV2YTnKVGpR70Fk7FgoySjYWpnD8ymeZNMYllUPsHXTh3jhhRfQunVr9OzZE/PmzcPevXtx+/ZtNOcDEeRyOWJjY5GTk4PVq1dLHYeoTlOtr84sLBP5LkTGjYWSjEZIVxdR10lNfK4nCgoKcPXqVXz88ccIDAxEfHw8Jk+eDC8vL7i5ueHll1/GBx98gHPnzkGlUomSxVB17doVb7/9NtavX4/Lly9LHYeaKUEQUFRUhCtXruDo0aP4/J9fNMl9ub6aqH48h5KMRlM+Kef3CgsLce7cOSiVSiiVSvz444+oqKiApaUlevXqheDgYPTv3x/9+vUz+TMrq6qqEBgYCCsrKyQkJMDcnCePkf4IgoD79+8jNzcXOTk5dW9//35ubi7Ky/83xd2iXWe4Tt0oeraj8/8EX7dWot+HyFixUJJRkfJZ3rWqq6vx008/1RVMpVKJnJwcAMAzzzyD4ODguv98fX1hZmamt6yGIDExEf369cO6devw1ltvSR2HjIQgCHjw4MFDZfGPpbGs7H9Ty3K5HG5ubmjfvj08PDzg4eFR937tWzuHNugReVzUaW8ZgJRVL8LWii+giB6HhZKMihhPw7Ayl+P4ooHw0GGNZk5ODs6dO4ezZ89CqVTi0qVLqKmpgZ2dHfr27VtXMPv27Qt7e3u9ZZfKwoULERsbi5SUFHh5eUkdhwxAcXHxI0cTf/+2tLS07vPlcjnatWv3UEH8/ftt27Zt0Ci42E/R6uBkg1OLQ0S7PpEpYKEkoyPW83r1qaysDOfPn9caxSwqKoJMJoOfn5/WKKaXl5fRPdawpKQE3bt3R9euXXHs2DGjy0+NU1JSUu8UdE5OjtbJCDKZDG3btn3sqGJtWbSw0M9TqVYdScXuxCxRjg4yk8vwap8OWDXCV+/XJjIlLJRklLacvIH136brfJ0lg7tiXkhnPSSqnyAISE9Ph1KprBvFTEtLAwC4uLjUlcv+/fsjICAALVq0ED2Trv7zn/9g2LBh2LVrF6ZMmfLQx8tUamQWlqFKrYGluRwdnWw5ZWiASktL6x1VzMnJQXFxcd3ny2QyuLq6PnZUsX379nBzc9NbWWwIqdZXE9H/sFCS0dqflI13jqRCrREaNTJhJpfBXC7DuyN89T4y2RhFRUVISEioG8FMTExEeXk5LC0tERgYqDWK2bZtW8ly1mfixIk4duwY0tLS4OLighv5JdibmI2T1+8iu6hca12bDICnow1CurpgUh9PeLvyB7TYysrK6i2Lubm5uH//vtbX/LEs/vGtm5sbLC0tpfmG6mEI66uJmjMWSjJqOUXlCP8yGWcyCmAml9X7w6T24wM6t0HMKD+d1kyKQa1W48qVK1qjmNnZvz3yrVOnTloF08/PzyA2+9y9exc+Pj54btjLsBk4wyR+H4xFeXn5E3dD37t3T+trXFxc6t3g4ubmBisrK4m+I90Y6vpqouaChZJMQt3IWPpdZBc+YmTMyQYhXVwwua+nUU1d5ebmah1ZdPHiRajVarRs2VJrs0+fPn3QunVrSTIu2LQf/8qxhLmFFRrzo7x2pHj1CF+Ml3Ck2BBVVFQ8cTd0UVGR1tc4Ozs/dlSxtiwaw1IKXRjD+moiU8VCSSbHlNfuVVRUPLTZp6CgADKZDL6+vlqjmJ07dxZ9s0zdWlZBAHS41+LBXfBGiLcekxmuysrKeqegc3JyUFhYqPU1Tk5O9a5ZbN++vcmXxYYytvXVRKaChZLIiAmCgBs3bmgVzNTUVAC/jVj9vmAGBgbC2tpab/fmaNDDVCoVcnNz690NXVBQoPU1jo6Ojx1VrC2L+vx9aw6MfX01kTFioSQyMffu3UNiYmJdwUxISEBZWRksLCwQEBCgVTLd3Nye6h7Ncb2aSqXCnTt36l23+Ouvv2p9jYODQ71rFt3d3WFrayvRd2TaTGl9NZExYKEkMnFqtRrJyclao5iZmZkAgA4dOtQdV1S72achB0mb2o7aqqoq/Pzzz/UezJ2fn6/1Na1bt673UG53d3e0bNmyyb8X0maq66uJDA0LJVEz9PPPP2tt9rlw4QKqq6tha2uLPn36aD3Zx8HBQetrje3Mv+rq6rqy+Lip6Pz8fPz+n0J7e/vHjirWTkPb2bF8GBtTXl9NJDUWSiJCZWUlLly4UHdckVKprJu+VSgUdSOYwcHB2HutCnsSsw3iqSTV1dX45Zdf6t0NnZeXp1UW7ezsnrjBxRQej0lE1JRYKInoIYIg4ObNm1rT5CkpKRAEAR6v/wPyVq6i3bv2uclqtfqxZbH2bV5eHjSa/63jbNmyZb0bXDw8PFgWiYhEwEJJRA3y4MEDfP/DOSz8QY3fVp+JRBCg3r8Qv+RkapVFGxubunL4uKnoVq1a8bniREQSYKEkogZL/fkBhm3+QfT7DDO7gmc9HLXKY+vWrVkWiYgMFFcjE1GDVenxmKD6zAybA39Phyd/IhERGQS51AGIyHhYmjfNPxlNdR8iItIP/qtNRA3W0clWzNWTAH5bndnRiYd9ExEZExZKImowWytzeIr8FBFPJxueDUhEZGRYKImoUUK6usBMLs44pZlchpAuLqJcm4iIxMNCSUSNMqmPpyiHmgNAjUbA5L6eolybiIjEw0JJRI3i7WqHAZ3b6H2U0kwuw4DObfg8ZSIiI8RCSUSNFjPKD+Z6LpTmchliRvnp9ZpERNQ0WCiJqNE8HG2wuoHP226od0f4wkPkDT9ERCQOFkoieirjgzyxeHAXvVxryeCuGBfEtZNERMaKj14kIp3sT8rGO0dSodYIjdqsYyaXwVwuw7sjfFkmiYiMHAslEeksp6gc4V8m40xGAczksnqLZe3HB3Rug5hRfpzmJiIyASyURKQ3N/JLsDcxGyfT7yK7sBy//8dFht8OLQ/p4oLJfT25m5uIyISwUBKRKMpUamQWlqFKrYGluRwdnWz5BBwiIhPFQklEREREOuEubyIiIiLSCQslEREREemEhZKIiIiIdMJCSUREREQ6YaEkIiIiIp2wUBIRERGRTlgoiYiIiEgnLJREREREpBMWSiIiIiLSCQslEREREemEhZKIiIiIdMJCSUREREQ6YaEkIiIiIp2wUBIRERGRTlgoiYiIiEgnLJREREREpBMWSiIiIiLSCQslEREREemEhZKIiIiIdMJCSUREREQ6YaEkIiIiIp2wUBIRERGRTlgoiYiIiEgnLJREREREpBMWSiIiIiLSCQslEREREemEhZKIiIiIdMJCSUREREQ6YaEkIiIiIp2wUBIRERGRTlgoiYiIiEgnLJREREREpBMWSiIiIiLSCQslEREREemEhZKIiIiIdMJCSUREREQ6YaEkIiIiIp38PzOPtRkAlW37AAAAAElFTkSuQmCC\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": "e4d99944",
   "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
}