{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aragon Conviction Voting Model - Version 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Overview \n",
    "\n",
    "[Conviction Voting](https://medium.com/giveth/conviction-voting-a-novel-continuous-decision-making-alternative-to-governance-aa746cfb9475) is a novel decision making process where votes express their preference for which proposals they would like to see approved in a continuous rather than discrete way. The longer the community keeps a preference on an individual proposal, the “stronger” the proposal conviction becomes. In the conviction voting model, a graph structure is used to record the introduction and removal of participants, candidates, proposals, and their outcomes.\n",
    "\n",
    "## cadCAD Overview\n",
    "\n",
    "In the cadCAD simulation [methodology](https://community.cadcad.org/t/differential-specification-syntax-key/31), we operate on four layers: **Policies, Mechanisms, States**, and **Metrics**. Information flows do not have explicit feedback loop unless noted. **Policies** determine the inputs into the system dynamics, and can come from user input, observations from the exogenous environment, or algorithms. **Mechanisms** are functions that take the policy decisions and update the States to reflect the policy level changes. **States** are variables that represent the system quantities at the given point in time, and **Metrics** are computed from state variables to assess the health of the system. Metrics can often be thought of as KPIs, or Key Performance Indicators. \n",
    "\n",
    "At a more granular level, to setup a model, there are system conventions and configurations that must be [followed.](https://community.cadcad.org/t/introduction-to-simulation-configurations/34)\n",
    "\n",
    "The way to think of cadCAD modeling is analogous to machine learning pipelines which normally consist of multiple steps when training and running a deployed model. There is preprocessing, which includes segregating features between continuous and categorical, transforming or imputing data, and then instantiating, training, and running a machine learning model with specified hyperparameters. cadCAD modeling can be thought of in the same way as states, roughly translating into features, are fed into pipelines that have built-in logic to direct traffic between different mechanisms, such as scaling and imputation. Accuracy scores, ROC, etc. are analogous to the metrics that can be configured on a cadCAD model, specifying how well a given model is doing in meeting its objectives. The parameter sweeping capability of cadCAD can be thought of as a grid search, or way to find the optimal hyperparameters for a system by running through alternative scenarios. A/B style testing that cadCAD enables is used in the same way machine learning models are A/B tested, except out of the box, in providing a side by side comparison of muliple different models to compare and contrast performance. Utilizing the field of Systems Identification, dynamical systems models can be used to \"online learn\" by providing a feedback loop to generative system mechanisms. \n",
    "\n",
    "\n",
    "## Differential Specification\n",
    "![](images/Aragon_v1.png)\n",
    "\n",
    "## Schema of the states\n",
    "The model consists of a temporal in memory graph database called *network* containing nodes of type **Participant** and type **Proposal**. Participants will have *holdings* and Proposals will have *funds_required, status*(candidate or active), *conviction*. Edges in the network go from nodes of type Participant to nodes of type Proposal with the edges having the key *type*, of which all will be set to *support*. Edges from participant $i$ to proposal $j$ will have the following additional characteristics:\n",
    "* Each pairing (i,j) will have *affinity*, which determines how much $i$ likes or dislikes proposal $j$.\n",
    "* Each participant $i$, assigns its $tokens$ over the edges (i,j) for all $j$ such that the summation of all $j$ such that ```Sum_j = network.edges[(i,j)]['tokens'] = network.nodes[i]['holdings']```\n",
    "* Each pairing (i,j) will have *conviction* local to that edge whose update at each timestep is computed using the value of *tokens* at that edge.\n",
    "* Each proposal *j* will have a *conviction* which is equal to the sum of the conviction on its inbound edges: ```network.nodes[j]['conviction'] = Sum_i  network.edges[(i,j)]['conviction']```\n",
    "* The \"trigger function\" will check whether each proposal $j$ has met the criteria for passing; if a proposal passes its *status* changes from *candidate* to *active*, and an amount of funds equal to its *funds_required* will be decremented from *funds*.\n",
    "\n",
    "\n",
    "The other state variable in the model is *funds*, which is a numpy floating point. \n",
    "\n",
    "The system consists of 100 time steps without a parameter sweep or monte carlo.\n",
    "\n",
    "\n",
    "## Partial State Update Blocks\n",
    "\n",
    "Each partial state update block is kind of a like a phase in a phased based board game. Everyone decides what to do and it reconciles all decisions. One timestep is a full turn, with each block being a phase of a timestep or turn. We will walk through the individaul Partial State update blocks one by one below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "{\n",
    "# system.py: \n",
    "'policies': { \n",
    "    'random': driving_process\n",
    "},\n",
    "'variables': {\n",
    "    'network': update_network,\n",
    "    'funds':increment_funds,\n",
    "}\n",
    "```\n",
    "\n",
    "To simulate the arrival of participants and proposal into the system, we have a driving process to represent the arrival of individual agents. For simplification, we are using hyperparameters for supply and sentiment, 1,231,286.81 and 0.6 respectively. We use a random uniform distribution generator, over [0, 1), to calculate the number of new participants. We then use an expoential distribution to calculate the particpant's tokens by using a loc of 0.0 and a scale of expected holdings, which is calcutulaed by .1*supply/number of existing participants. We calcualte the number of new proposals by     \n",
    "```\n",
    "proposal_rate = 1/median_affinity * (1+total_funds_requested/funds)\n",
    "rv2 = np.random.rand()\n",
    "new_proposal = bool(rv2<1/proposal_rate)\n",
    "```\n",
    "The network state variable is updated to include the new participants and proposals, while the funds state variable is updated for the increase in system funds. \n",
    "[To see the partial state update code, click here](model/model/system.py)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "{\n",
    "  # participants.py   \n",
    "  'policies': {\n",
    "      'completion': check_progress \n",
    "    },\n",
    "    'variables': { \n",
    "        'network': complete_proposal\n",
    "    }\n",
    "},\n",
    "```\n",
    "\n",
    "In the next phase of the turn, [to see the logic code, click here](model/model/participants.py), the *check_progress* behavior checks for the completion of previously funded proposals. The code calculates the completion and failure rates as follows:\n",
    "\n",
    "```\n",
    "likelihood = 1.0/(base_completion_rate+np.log(grant_size))\n",
    "\n",
    "failure_rate = 1.0/(base_failure_rate+np.log(grant_size))\n",
    "if np.random.rand() < likelihood:\n",
    "    completed.append(j)\n",
    "elif np.random.rand() < failure_rate:\n",
    "    failed.append(j)\n",
    "```\n",
    "With the base_completion_rate being 100 and the base_failure_rate as 200. \n",
    "\n",
    "The mechanism then updates the respective *network* nodes. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "{\n",
    " # proposals.py\n",
    "  'policies': {\n",
    "      'release': trigger_function \n",
    "    },\n",
    "    'variables': { \n",
    "        'funds': decrement_funds, \n",
    "        'network': update_proposals \n",
    "    }\n",
    "},\n",
    " ```\n",
    " \n",
    "The [trigger release function](model/model/proposals.py) checks to see if each proposal passes or not. If a proposal passes, funds are decremented by the amount of the proposal, while the proposal's status is changed in the network object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "{ \n",
    "    # participants.py\n",
    "    'policies': { \n",
    "        'participants_act': participants_decisions\n",
    "    },\n",
    "    'variables': {\n",
    "        'network': update_tokens \n",
    "    }\n",
    "}\n",
    "```\n",
    "\n",
    "The Participants decide based on their affinity if which proposals they would like to support,[to see the logic code, click here](model/model/participants.py). Proposals that participants have high affinity for receive more support and pledged tokens than proposals with lower affinity and sentiment. We then update everyone's holdings and their conviction for each proposal.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model next steps\n",
    "\n",
    "The the model described above is a minimalist model, first iteration model that covers the core mechanisms of the Aragon Conviction Voting model. Below are next additional dynamics we can attend to enrich the model, and provide workstreams for subsequent iterations of this lab notebook.\n",
    "* Sentiment\n",
    "* Mixing of token holdings among participants\n",
    "* Departure of participants\n",
    "* Participants influencing each others opinions\n",
    "* Proposals which are good or no good together\n",
    "* Multiple proposal stages such as killed, failed and completed\n",
    "* Affects of outcomes on sentiment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configuration\n",
    "let's factor out into its own notebook where we review the config object and its partial state update blocks, with a slightly deeper dive on the trigger function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/aclarkdata/anaconda3/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
      "  import pandas.util.testing as tm\n"
     ]
    }
   ],
   "source": [
    "from model import economyconfig\n",
    "from model.model.conviction_helper_functions import * "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pull out configurations to illustrate\n",
    "sim_config,genesis_states,seeds,partial_state_update_blocks = economyconfig.get_configs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'N': 1,\n",
       " 'T': range(0, 100),\n",
       " 'M': [{}],\n",
       " 'subset_id': 0,\n",
       " 'subset_window': deque([0, None]),\n",
       " 'simulation_id': 0,\n",
       " 'run_id': 0}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'policies': {'random': <function model.model.system.driving_process(params, step, sL, s)>},\n",
       "  'variables': {'network': <function model.model.system.update_network(params, step, sL, s, _input)>,\n",
       "   'funds': <function model.model.system.increment_funds(params, step, sL, s, _input)>}},\n",
       " {'policies': {'completion': <function model.model.participants.check_progress(params, step, sL, s)>},\n",
       "  'variables': {'network': <function model.model.participants.complete_proposal(params, step, sL, s, _input)>}},\n",
       " {'policies': {'release': <function model.model.proposals.trigger_function(params, step, sL, s)>},\n",
       "  'variables': {'funds': <function model.model.proposals.decrement_funds(params, step, sL, s, _input)>,\n",
       "   'network': <function model.model.proposals.update_proposals(params, step, sL, s, _input)>}},\n",
       " {'policies': {'participants_act': <function model.model.participants.participants_decisions(params, step, sL, s)>},\n",
       "  'variables': {'network': <function model.model.participants.update_tokens(params, step, sL, s, _input)>}}]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "partial_state_update_blocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'network': <networkx.classes.digraph.DiGraph at 0x7f5a1abf4b10>,\n",
       " 'funds': 40781.42}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genesis_states"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore the network object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "network = genesis_states['network']\n",
    "# To explore our model prior to the simulation, we extract key components from our networkX object into lists.\n",
    "proposals = get_nodes_by_type(network, 'proposal')\n",
    "participants = get_nodes_by_type(network, 'participant')\n",
    "supporters = get_edges_by_type(network, 'support')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Exploring the State Data Structure\n",
    "\n",
    "A graph is a type of temporal data structure that evolves over time. A graph $\\mathcal{G}(\\mathcal{V},\\mathcal{E})$ consists of vertices or nodes, $\\mathcal{V} = \\{1...\\mathcal{V}\\}$ and is connected by edges  $\\mathcal{E} \\subseteq \\mathcal{V} \\times \\mathcal{V}$.\n",
    "\n",
    "See *Schema of the states* above for more details\n",
    "\n",
    "\n",
    "Let's explore!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'participant', 'holdings': 27108.81105195909}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sample a participant\n",
    "network.nodes[participants[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram of Participants Token Holdings')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's look at the distribution of participant holdings at the start of the sim\n",
    "plt.hist([ network.nodes[i]['holdings'] for i in participants])\n",
    "plt.title('Histogram of Participants Token Holdings')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'proposal',\n",
       " 'conviction': 0,\n",
       " 'status': 'candidate',\n",
       " 'age': 0,\n",
       " 'funds_requested': 24759.351195368352,\n",
       " 'trigger': inf}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#lets look at proposals\n",
    "network.nodes[proposals[0]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Proposals initially start without any conviction, and with the status of a candidate. If the proposal's amount of  conviction is greater than it's trigger, then the proposal moves to active and it's funds requested are granted. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All initial proposal start with 0 conviction and state 'candidate'we can simply examine the amounts of funds requested"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Proposals')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar( proposals, [ network.nodes[i]['funds_requested'] for i in proposals])\n",
    "plt.title('Histogram of Proposals Funds Requested')\n",
    "plt.xlabel('Proposals')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conviction is a concept that arises in the edges between participants and proposals in the initial conditions there are no votes yet so we can look at that later however, the voting choices are driven by underlying affinities which we can see now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 137.58, 'participant_id')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = len(participants)\n",
    "m = len(proposals)\n",
    "affinities = np.empty((n,m))\n",
    "for i_ind in range(n):\n",
    "    for j_ind in range(m):\n",
    "        i = participants[i_ind]\n",
    "        j = proposals[j_ind]\n",
    "        affinities[i_ind][j_ind] = network.edges[(i,j)]['affinity']\n",
    "\n",
    "dims = (20, 5)\n",
    "fig, ax = plt.subplots(figsize=dims)\n",
    "\n",
    "sns.heatmap(affinities.T,\n",
    "            xticklabels=participants,\n",
    "            yticklabels=proposals,\n",
    "            square=True,\n",
    "            cbar=True,\n",
    "            ax=ax)\n",
    "\n",
    "plt.title('affinities between participants and proposals')\n",
    "plt.ylabel('proposal_id')\n",
    "plt.xlabel('participant_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run simulation\n",
    "\n",
    "Now we will create the final system configuration, append the genesis states we created, and run our simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                  ___________    ____\n",
      "  ________ __ ___/ / ____/   |  / __ \\\n",
      " / ___/ __` / __  / /   / /| | / / / /\n",
      "/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /\n",
      "\\___/\\__,_/\\__,_/\\____/_/  |_/_____/\n",
      "by cadCAD\n",
      "\n",
      "Execution Mode: local_proc\n",
      "Configuration Count: 1\n",
      "Dimensions of the first simulation: (Timesteps, Params, Runs, Vars) = (100, 1, 1, 2)\n",
      "Execution Method: local_simulations\n",
      "SimIDs   : [0]\n",
      "SubsetIDs: [0]\n",
      "Ns       : [0]\n",
      "ExpIDs   : [0]\n",
      "Execution Mode: single_threaded\n",
      "Total execution time: 8.98s\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from model.model.conviction_helper_functions import *\n",
    "from model import run\n",
    "from cadCAD import configs\n",
    "pd.options.display.float_format = '{:.2f}'.format\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# Pass in configuration to run\n",
    "df = run.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After the simulation has run successfully, we perform some postprocessing to extract node and edge values from the network object and add as columns to the pandas dataframe. For the rdf, we take only the values at the last substep of each timestep in the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df,rdf = run.postprocessing(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "affinities_plot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f59f2e84490>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rdf.plot(x='timestep',y=['candidate_count','active_count','completed_count', 'killed_count', 'failed_count'])\n",
    "plt.title('Proposal Status')\n",
    "plt.ylabel('count of proposals')\n",
    "plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f59f2dbe350>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rdf.plot(x='timestep',y=['candidate_funds','active_funds','completed_funds', 'killed_funds', 'failed_funds'])\n",
    "plt.title('Proposal Status weighted by funds requested')\n",
    "plt.ylabel('Funds worth of proposals')\n",
    "plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "nets = rdf.network.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:563: MatplotlibDeprecationWarning: \n",
      "The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
      "  if not cb.iterable(width):\n",
      "/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:569: MatplotlibDeprecationWarning: \n",
      "The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
      "  and cb.iterable(edge_color) \\\n",
      "/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:579: MatplotlibDeprecationWarning: \n",
      "The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
      "  for c in edge_color]):\n",
      "/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:660: MatplotlibDeprecationWarning: \n",
      "The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
      "  if cb.iterable(node_size):  # many node sizes\n"
     ]
    },
    {
     "data": {
      "image/png": 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888+nubmZhoYGfvKTn/Cb3/yGadOmAXDxxRdz5ZVXUltbyzXXXMOZZ57JlClTmDhxIrNnz+bAAw+MbFcpxc0338ykSZM4/vjjSafT/OlPf+Kuu+6itbWV5uZmLrzwQi+69YYbbqC3t5fm5mbOOussPve5z414jkcccQQzZszgf/2v/8UFF1zARz7yEW/dIYccQiKRYJ999hmV2TSM2bNnc/7553PQQQfR1NTEyy+/zCGHHDLsPh/60IeYM2eOdy2j0NzczPjx42ltbeX000/npptuYtasWQD89Kc/5fLLL6eqqooFCxZsk9ow5FlfX88+++yD4zj84Ac/oLW1lbq6Ov76178WHfDD+wL86le/YsWKFbS2tnLiiSfy7W9/m6OPPnrU/SmG+vp6HnjgAa699lrq6+u5+uqreeCBBwLX64wzzuCss86iubmZwcFBrr/+egBmzpzJ7bffzle+8hUaGhq4//77uf/++ykpKWFoaIiLLrqIhoYGmpub6ejo4KqrrgLgmmuu4c4776Sqqoqzzz478IIUxmh/NzF2HJSM1g4SI8ZOiA996EOcdtppfOELX9jRXQF0OsNnP/tZ1qxZs6O78p7FkUceyWc/+9n3zD2L8d5DauRNYsTYOfH000/z3HPPce+99+7orsSIEeMdRGzqjBEjAvPmzePoo4/muuuuC0QmxogRY+wjNnXGiBEjRoydCrHiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxVi4osRI0aMGDsVYuKLESNGjBg7FWLiixEjRowYOxXGHvFlMju6BzFixIgRYwxjbBHfhg3Q2AA/+D4MDUA+C44DIju6ZzFixIgRY4wgtaM7sE0YPx4+fSocsD/kM/qfQSIJKgGJBKik+5kApXZcf2PEiBEjxnsOSmQMyiURGOwFcayFyiU/pdeLo/9FkaHZLkaMGDFi7HQYe8S3fDlMngylpdrUOdTvr0ukQPKAgmQakq6gFdHLHQecvEuIyiJB61OpmBRjxIgR432MseXje+45+MAH4P+cowlPBErHaZIDV+WJ+10gM6D/OTlNiiXlUF4F5dVQWgnpUk124kB2UKvIga36c6hfL8tlXbIcW+8HMWLEiBEjGmPLx7fLLvCJj8Oxn9RqL58FFOCSkjj6ez6jFxnV5+Q1AeKSYjKtFV4iDcnQMcRxA2ZcdZjPxGbTGDFixHgfYeyZOkGrr6E+TUw2VAIQV51ZhIjS/5IJy/+HJsBUenTkZfZznCJm0xAZJhL6mDEpxogRI8Z7CmPL1HnrrdDYCMcfD4kSbea0ycX47QAQTUDpcpeERJOdSvgEmc9oAh3YCgM9WhXmsr7J1IZyg2dSaUiXQWlFyGxaott18tpEOhA2mw7FZtMYMWLEeA9gbCm+mhrYuhXGjYM7b4ePf1yTTT6nSSyR1EosmdYiL5cFRG+TTGtfnziQKoVUiW5THHd/NycQ+3IobSr1TJzbaNoMm02NWhQpNJvawTUxYsSIEeNdw9jy8e2xBzz/vCaO6btoZQVolsM3fRqCS6Q0qeSyrq/OJZxcRiuwtEuA6VL9DzQ55bOu8sv76s+YNY0f0SPCYfIGVUKbV8PwzKYuGeZzuj+x2TRGjBgx3nWMLcXX1wcPPAB77gnTJruKDj93j4Tr2nMDUUQIKjh8U6idA5gq0SowESIpQ4JGDSZT+l8iGSQvW9kVpEkYQhyFmhOJTr1w3L6GyXC07caIESNGDA9ji/i+/nW49lqYMQOeeALG1/ppDYhWeKAVH2hCSJXp7/msn7qgXAWFhJLgcUklBcmkVl4mr08cVzm6fjoTHZpM+cQTJi6bEM1xC8ymo8gdNOc3rNnUItrYbBojRowYRTF2iC+TgbIyPdCXl+t6nZ//d4uUMpqoxNEDfzLlkxRoMlNos6JSWgiWlru+P3f/XIYChQiFhIV7TCfnkmDKJ8JiZBOICrUIzJhSI1MlRmHiDJtNbdK1zaZhBRojRowYOynGjo8vnYZp06C9XX+fMxtyQ/pvT3EZH19ek5JK6Fw9yetlHoEowNFqMZmCkgooKdP/TM6f2d4mJY/wLPIyx8vngQE/kCaVDqouj4TCiYMUpkrkc5aJUywFFxFkU6zdMNF6bbqVbQrMplZ7MWLEiPE+xthRfABLl8I118Ahh8AZpweJz5yGSmryiPLlebBz/Fwk07qyixn4TVpCPm/59Gx1l9Lt2HVB8y7BGgI2x4pSXKM1RQYiQ0NKcbRBNoH2LLNpwD8ZMptGmWNjxIgR432AsUN8HR0wezYMDuoB+sYb4bOfdX18rjIyA38+h0dspkpLzkR1uqSXTLvRmrmInD3LPGi2cRwdBKOU6zPMuSZVUwkmZD4U8aNJPbXp5g+aJPtwBGeAGEcbCBMiw+0JshnWbGr1LzabxogRYwxj7BDf3XfDF74Avb0AyAH7o/72KJ56y2XwEtO9vL28W9YMvV0y6Zok0dulSnQyulJ6eaYvRIIKEq4/0FaONoEYoihm4gTdpskVzGd9wjRkGfD7RaRMBEyco/X7RQXZWKpuW4JswmZTj2Qts2l4WqjYbBojRoz3KMaOj2/WLC+sX0pL4YMfQDLap6aMf8uQk/HpgR6ETfRmOL0hl9GqrLRCmy7Lq/V3U9cTAXHJLZnyo0bzWbfwtXtcEy2aG7LMrwk/jzCR1KSbTAHlPglmB30StNMpCtScU+j3C6u4sKIzCrOgFmkEieWtajXFgmxUAlJRfsRQWkc23FaysL2YEGPEiLEDMXYUH8Bvfws33AB77IFcdjGyeimypQPVNhPVNBmSKZQhIXALVEeYMoFIP59d0SU76JpM0QN1MuX6xXL+YO64ie1paz8TWJPPWbVErWPZRGWW2+0WM53aGDFCNGTmHK0JtVhuYjjIZjT+PzvpP8psGm4jLvYdI0aMfxHGjuID2LwZnn4aEglU1XjUnkcgA73IyqU4j/4/qKhCzTkIVdOAEjf5POEmnYtLRoYYUyWWUssCIcUGeMQkuKZUBUmznxXEkstooky5FWCSKXBnSvIUVd71E4ZJz/gnzbYmqMZMrJtM+srRmDhHEyEaIK4cZEcwoRoCSxRrN0SEjlVtJhwlGvAFpqL7VxDBGptNY8SI8a/B2FJ8TU06yGVcBfz+t3DYYXpwFEFyGdiwGuf1F6G3CzVrP9Quu6McK9AlkdJ/24NsSbk/0GeGIDcYPKY944MdPRpYT9AHmEhpAgyrmEAlmIj8P1txGcUYjkqNUnDb4vsLJMKHfIujMaFGtTlikE2E2TTKD1qgOC0VGybD2GwaI0aMt4mxRXxnnQX33AMVFfD801Bfp5ebhHQABNnSgbz+ItKxGjV1NmrmvigTdAKFZGKnMohApt8ycya1OPN8hm4QSz4HOC5pueRofHFRZdJss6AhKdssapRp2MxpTIamfqhRZV7uoksMNnFtDzFGEaLYJJYYPQFFqs+3EWQzKrNpPEdijBgxRoexRXzr1sEvfgEHHgiHHwbZAXeFVVbMkBAgg4PI6y8gKxajJs1Ezd4flS4Z5gDKz9GTPGQzfrsJt0anCQQB3++H+P5BM+Dmc9pkac8ZmEjqYxjl5RGwGegtZZmw8gXtkmie6TTr9zdM6mHCeieIMYrERhOFWixatGikaFh5DlPJZsQ5EsM+xCJ9iREjxk6FsUN8mzfryM5+tzbnwoVw8sk6AtOuw5lMA+KmLWgSkbyDrHgFee1ZmPpBEh/YG9KlqHSZbjuXLV6urAA2yRqlKXq5IcB0qT+4OnntCzNpDI6jN02mfTLFGsDtQTw8RZLt/zIwqjFMgqNVYO8EMYZNqFGBMVFpGcVMqEWDbMJVZ4oE2USmc1jXNDabxoixU2PsEN8f/gCnnqrn4wPk6A/Bb/8flJSjlEt0Im60Zd5XS7mMp7rEcZD2N5E3XkZNm4NqnQ6lFShDVHa5MvBNn4ZUzUDtuKQ6LExwihuYIvhBLkbFmWAW01cz95+Byf9z3P0Ed5C2CNdL03CP6fkzkz6xJl2lOdpZ5t8NYtwmE2oRk2Wkj9Iit2JBNgFSdArJ0OtHbDaNEWNnwNiJ6pw2TVdtASSZRNqaYPlzkEwiNY2oqvFQNg4c0bPzeeZAMISgEklU20xk0q7QsQpn8eMkdpmDpNJQWYcqq4CySiuXz0UiAY7Cm5/PRD7mrVSJZEqrPRNNms9pJWZmirBJyfTL5PohWhVmBnyyTJbo46bSQNonD2+uQHGjR0v1QA1BlZTPhSJUzblYKQ42aSmFR9YkC/P/YBif3SiJ0TbbBtoMq7PsyCbURAqSYbOnFF6DALmGzKapUt/0GRVtGjCbxnMkxojxfsHYUHxDQzB3Lrz2mv5bKT1Tw/88gOw+C9m8HjZvQDrXQrqUxOwDoboekklUqsT1y4WUm6uYpHsj0tOFmjAJ6VyHqm1EVdb65kxTlcWYUZXyZ3YHf51BSYVLVgTNnIb4vHQB5Q7MeX9Q99RbhIkzbJIT8FI0AqoxNEOEHRhjoiPt4Jlwwe1ipDhcZKfBO60Y3ykT6miCbArMpuH9RzKbFlGYMWLEeM9hbBDfHXfA//7feiJaGwceCH97VAeRqATi5GFoANmyAenbSqJpMuRzOsm9YSJUj0d59TqVjuRMpkAE6euC/h69/ZrlqNbpqLomfZxwFKiNgJ/PW+i3rZQeJHND2uxqilsbJZhI+QNxqgTSJXq9l9bgpj54UZD4xxPjWzT9cIlCJYKT5hpCCZNgyiTLJ4OqxyYr+3uYHKNIcbhB/90gxrdlQnU/o9qIDLIJJ+5bLyrDzpFovbDExb5jxHjPYGwQ31e/Cj/+ceHyigrYvFH/7ZmlEp45UhIpGOjRf29cjSx9EupbSOwyB6rGg0qgkik3lSGhCTAzAJkBZPVypP1NEtN2h6Y2XRHGK26NZcJEc48xN9rL7Q08peaqB+ODM3mF9jRIyRIoKfUHZ3N+ptSZyQE0E+aigkrGy/8L3VpvKiMz6FsDd9TEumF40ag2KdpkaRSrGoYUzd/vcvDNSPmFUESpWf2z0yi2JcjGu7b5QkKNzaYxYuxwjA3i+7//F84/v0DxyewPwtNPoExdyqgZ1e3tAfq6kfUrke6N2qw5ZbYeeLJZqKhx0x0EGRqA7CDO0iehYzVq5n6oSR9AYQ+aCTdvz5Vh6TI/pSE7qM2cNjxlRdC8WBTKJzebtMyMEYYIPb9gKKLTbJfL+hPw2uoOguomcFx7MB8FaXkX2SacCFI0n8VI0fY3Fov23F5iHM6E6vVvBKU4XJBN4HySweMDBakXbg3aAjIcjXk5RowY24yxQXy9vTqVoaNDExTglJby9w9/nEn/+VWm7rcnSeNXMwOPCF4unImKNKShFCRTSC4Lm9YhkkeNbwYEWb8SsoOo+laoqgMEhgZxFj+mCXDGXqjpe6IShoRC5KUUlIzTZCXip1uAHtCEoOIzQRi2f86UBCtIhrcCZGzlBpYpUrkFsd10ibB6CeQApgpNnR6h5nwFHWVetc2aRT+HM3mGzKoBArJMtmGCtAnBXIfwNXgniPHtmlDN7YpSmd71DJlNMdfYCs6JmiPRbB+bTWPE2C6MDeIDTXqHHw7LlunZ2O++G+f443li4e387cb/5rhvfYPZHzoUlUhByk0sN8ShXF+LIpjzZ+fcOQ4y1OcNOrL2DWTVK7ru59Q5UFmDZAZh6VPI2tdR0/dAfWBvbSotBmVmZMCt9YlFyBbpBUy0KT0TvCmj5jhuwexwgIyd+hChYKJKq3m+Kbcpb3DFjUq1yBJ0Ozm7xFra8htSqOLCJFNg8oz4HCkFIooUiwXjFJgrQ+TwThBjsXbs8nJh/55N1Ej0fkWDbCKIOMpsGs+RGCPGqDF2iA80oeXzyLhx8JPrUad8Cl+NCn0AACAASURBVFSC/u4e7r/i+7xw7/9w5v/9AbOOPEQPUV4Upks6JmjENvWZQBQvEtPRJcucvH55H+xH2t9ANq0jMXM/SKZwerfCpnWwYjFq9oGoKTNRqTLdhjiB3MERERjc7IhO5Saku2kNjqMntS0IkDHKLRUkLXMudm1QZRMD1qAf7quChDWo4hKUme4pqs5oGJEmz4hPbLNnkUCZKHVjm2qjSNFWwEVJMaRMt5cYAy8U22hCtWfqCM+jGBVkU6BOI+ZIDJhN42LfMWIYjC3iO+kk5A9/gJISeOKvMHkKKIVyB4G1S1/jnvMvpXfTZubd/EMm77kbsA2nZ0yjJgk+66ZOiIMkkpDNIL1dqHHVyMpXkPVvQSINA30k9jgEaidARbWuCyqi94/KpQN/UDK+N6MM7YCK6B3dTwkOuGZwtf199iwLJhk+b/n7TFRnIIgmwtSJsg4boSbtqjJ2FOk2+wSHIUlzzUYkyZDCKwjGiSDIyDYj2n0niLFA8Y3ChFrU/BoRZEOCwOTJtg/SNpsWq3oTI8ZOgLFFfI4DS5ZAWxtSkkQ6VqEqKmFcDcr1U0k+z3O/f5BfX3QF0w+ay6eu/S9qmxq1WrJNVSYIxRCCjFKhAaAQtyyabFyNrFkOG9fChDYScw6Cvq1IfSuJ8krdfqbfHyATSSDhqjVjDky6x1c6QMZEVnrkaZdTc314uOTs5QFGqUazizEFJv1r4A3Aw5k6xVeMeWu+QDNNkhlUvZQLS2F5x5BgH2wiCZg7hyHJgLobgSRH8j+OFP0ZldIRUKURhGbOwevj2yBGE/QUJsYC1Zco7EcgWCciyMaLNnVfYLxzDhX7DvsQY7NpjPcpxhbxLVoE8+bBscfCT3+KiED3RmTdmzB+Aqq6Xqu/VJqh/gH+ePWP+OvNt3D0V/6Do889h3RZeXCATiSC0xLlcy5JmcFa+W/JInrQ8PLurMR2lUBEkM0bkPbXdbRoXRPOsmehvJJE81SobXSHRtekZdf8LJgUV+l8PlO9xRBQ1prd3ZgnTa1PJ+/mAbppEHaAjJmMN8pXFVl+zSIPe2A3g7DjBgqFa4MWEKWZccIqzu2RS1jRGZI0xy5Ckt4AHkGStsKz2w6YQYuZV6NMq2GlF0GKBf7GsGqzvsN2EuMwijO8nzFXFyi/CKKLKvwdVpTxHIkx3kcYW8R3zDHw4IN6mO5cB+UVKKU0AW5Zj2xqh8Y2VE0jyg0C2bhiLb++8HLaF7/Cyd9fwO4f+5BeZyPh5vIZkjETy5rBJpkCUSCmRJlylZEEo0WtpHWnqwPl5JGNa5DXntNBIhOnk5i+B5RW6Nnio9RZMdhqzZCeRygOAT9dMqWVo23q9Px9LhF6s72H6oPaSfOOpSZtpViQ/gDeABkO5DDtmOOlQqZVGwHiijJ5hsgrkiSLKcqQCXRE/6Mhs2Im1WFIKUCK4faKkKJ3jSMU30jEWKDkQvsXmEOtfUy7UUE2Xgk7676Hydb2IcZVa2KMEYwt4nv0UeSsefDRj8BVC/TA75osVSKB5HLIxtXQuwXVNBWq6vRM7MCSh//KPV+/nIZdpnDK1fNp2nVakYMoK3jEMiUa/1kiZU1NlAAcf+ADvW1phWu+FGSgF3JDyMuPIT1boLIGVVGFmrY7dHUi6RJUbaM+B9DkYM8akR/y2wa3XaVJ1yO7sGIMnU9UkrSn3vJ690RaBw8VmDpDfsFwZKdd2zIQRWuTXwRRDuujU8EBtKj5M0xgoyHJKBVZhCRHE5xTTO0VqFRzm4qQom2qLZb8793nCBIqRoz29QubdaNMqEXVn7ttwGxqPXc22drtBUq6xYQY472BsUV8zz8Pt98Ou+0GZ56JDPXqyizZIU02pRX6R9a/VROgCKp1V1RFNeSz5AYHWHTTrfzxmh9z6L+fyccvOZ+yyko9s0M+IhJTJdzftfM2O5zUZAJIbggG+nCe+TM4eZ0PWN8MSuEseRxQJGbsBVW1oBKoknJN6uAH2uSz+s3aqALzlm36nS51iQt3PsAhf2AGPBOVh2LqjdDAG1KEdgqEiSY19T+9XMGcbtuL/rSCd2zlWWAKNIRmiIBCMowiyMCy0ZhAiyjKEUkyRNDeMcJkFvEZ5X+0Sc7ubxQpFgTjRJhSw8pvNMRo9nMijhk2iYaPEXYdGBNrOPUjNpvGeA9h7BDfihWw225IXx+qogIuvRQuvljX1nTLjJEd1GbK8mqkrBK1tRNZvwLKK1ET2lAlFYDQvXYdv738Kpb99TFO/O4C9j/9FJQXTOK2AXg/YsciD6P6zDx4Rg2mSj2VF0mibnuCQPcmnBf/BgO9qD0OQzVPgVwGWb8C6dmCamxDNbTqc+rrg7oJeuokN6AGx0xtlNTHDsxCgfYPmpkHxPEDZGw/kxf5aQJV3MfAnhXelFGzgy9s1TKcbzBKNZioTxM5K2gSNZVlEomIXEGLkAKkNcyygAm0CEEW8xVGtl1EURpfYaD9IooyfO2KkqMQTbS2OdS9rwEyN4rLtBGlGsPnOQIxeiZUfGLEUnY22amE9R4gQRI1/Tb31BOu1vHjORJj/Asxdojv97/XgS1mPr7DDoUHf48xoyh3UBEnD5lBGOqDZBoprYCtm2HLelRdC9Q1e7/PN/75DHeffznp8jJOvf77TN5vH73CcfTs7nlTP9PR6ksAJ+uThGfuM/P3JQKFr4PpDMpvy/0ufVuRV55Ctmwgsf9HoboOVVKu6aS7U7dTUqqLbq9Zjiqv1BVlxk/QRD0ilHd99MBl+dsMaRpyC1dxAf+N3ig04+8M1/QM+w9tReENmrbPKdzNRPC7N6i6cwkGVEEEWQX2tdWdRQzDLYNoMiy2LBD0Em6/iKKMPEYRU2uBQh2NeTVMjt4FCZJilL9RWQRmm82HI0bvXKzhI3JbS80GCM9YLWyViH/+dhBOmAxjs2mM7cTYIb72dvjgB5GBAUinkfO/DMcdjfR2w1A/VNej6iZA4yRUqRupmcvAYK9WU8kUdG+GwT5U02QYNx6lFE4+x2O33sV9C65h7+M/xnGXf4PK+vH4g0fo8pgfszHdBMjM2iZd7gafiFu2zJrc1szE7qZQSH8v8sZLyGAviT2P0IEvleP1trksYiJNB/pwVr0Cq1+DuibUhClaLaZLUYlkKNk9Gyp5piyVVcS8GTgHhc4JC711hyMDkyntH0xapjC7jqjxmYZLo3m+w6w/mJn1kdVQXNVk97uACKP+jvDdhZWP+RyJIG3SGZEgR/AZDqcoTR8DbYTJze5/BNEGTMURfscCcowg2XB0rznvwH7DEaN13hBs336+IvvhvjEFlKe13utXaFqo2GwaYxQYO8QH8PrrsHAh7LsvnHiCVnb5LJLPQ/cmpLsTujbqJPNpu6EaJyHdnah0GZSXw1AfkstpBZhKoybN1P4/oG9jJ/ddfiXP/eZejrnkPzns86eTSIaq7ZvBTUJBJcoyFW5LwnyAXBNIdgBZsVTPCt80GTJDUNeCSiS0enQrtQjoXMF1byAb12gy/8C+qOapui9llbqUmiHo7KCfh+eZL63ZJFJW6oTjaFVrTKp2RKA9AJmBLkrBgX/d7EhFs9wjOevaOjlfYYejP4vVGA0PiDZBhc2gtrobkSyHWQeFx4o6ToHfkEIyjPIZFlN9xRQlhNpJBNtRRmZZ92Ek/6MhIxVFSmFiVdbLkXXc8L2widEjNLtt/HbtvliPUNAcHPECYNbFZtMYI2BsEd9//if85CcwYQIsXgw1NXpQHBrQPwoT6JFMIdkMbN0CpaXgODiLH4f+ftSkXaC2URNJ/1aobkBN/IA7KwOseWkxd3/lAga6ujn1mm+z62EHg4nwNAOYZyq0phNC+WZOiJ6dAfAUj8kHNG+v4r8tSz6HdKxEVdVrMs9nUa3TtKorbBDJDiGb1sHmdS6hfwDEQQb7UVX1qHHVuu/Gb2fqfBrCMUi4aRBJ279mmzHzVm5eyh9MzHbGV+cV4TaVXFx4MxLkrcEWa1yOehTNoI61vRlI3Xth+jLczA4GkQRZ5Hv4b3P/CggxgrzCJlFjGRiJICODeqKOEaX8CJJDAbkRbCfguw1dr0hylOB+ph8BYsUn6nDyv7l/qOjjeP7ZhB8gE3kfwsRptWPO0X5WzP6x2TSGi7FFfC0tsH69nofv/t/BgQe4K2zlZL4H3+7FHZhl41rYuAbZ2oWqroWa8Zo4y6ugeRqJyloEeObu3/LbCy9nxqEHctIV32T8xBa3FidW8IsUHjuR9JPiRaxgGXe7ZMo1e5ofqTHv5fxt3Nqh4jjQtQESCZwl/0RVjUdNmaUVLC55mgHGq9UJ0r9VB8mUVejgn1XL9KBQ34qqb/EDZUZC1Nt5wE+kggTnbSe+YvQqvpjozyhzp1VCzSu+LXhzEJoEfDuU3hsMDYlGnoBFFhSqkgCRhLe398Eilgi1NxxZRqnM0ZhobbwTQT3mXAKPbNQ5DEOSdht+5wpJ0t43rAILniNLwZn9vOse8VJSQPoR1zpAfAAR5xQgRFVIhvEcie9rjC3iu+EGrfr23Qceuk+rORu2KdIMxiagw/bHuQ+3ZIdgSweydZOOxBQ92MrgEGpcNZnSKv7ws7v4+y2/4iNfO4cPffnfSYePOSySkHIVTy5rLZcg4Rn1FT6XkgqtvvI5ZKAHujtxnvkzauIM1K57o9Jps7F/bik3otON1JR8VvtA8zlk3VvI8uegbByqZRqqdRqUlqNsU2c+D7nBYFSq5z9J+INJlBowfRmRVJX7Rp/w/Y52EIY5ZtLMQqHcKEEr2tQE2CSt6ajMTBKI63e0zKkwDDFZg2ZY4YV9g0XJk+h19j0frbIcjYm0GEkHfs4RBBkV1FOgWgleN0LXJlKdhvuI36+Cl4aQeTXwKdbjY/fZ3IuwyXIY8g/f84LzItR2mEyh6OwXMSGOaYwt4rMh4vr4Mv4y83AWTBFjBk8Tou/65NKlfs1OwNm8Hta+pgflskpkSweseo2Orgy/WfgAHWs6OPnqb7HbcceinCyeiUjE9UlZ6QUFvq+wKn27py3ImuXIi39HTZyOmnMgqqSMQsJRflqAIdZcVivf7KCejLdjFfR1o2bsrX2KjqPrnqZK9DmZqFQzpZO5dsUiQI068+YfTBFITQBLxZmpdcyAa47hXrdiEaDFEI4g9EhUgqo0oCjCpFVwsSlKigUkFd4+rPbMZxHyNH0ImEgJqpPRkOWIZtkIssTsYp9LRKBPMVXpnZ997az2AmQbIldvvxDpDEf+9kGirnU4j9A7H+seBPo6AvnZ989WqLY6jIt9jymMLeLr7tYzsZ/2GTjqQ3qZ4+jB2cxEbkxwJlfMTBHkDSCWOgL9vaTMm15HHEcnv294CyqqdVm0ZAnSu5XFv7+fX/9wIRNa6vm3c+fRdOChqMZWHVUJhWZOU/rMIKzsEqZCTNbvX7JE9weKzO6gCU5EkJWvIq8+DW0fIDFrP0iVoAz5FkRuhs9bQ/I5HRC0pQPKKlAT2rQCHuhF1TToaFnbERd+k/bMRCblwDVTCr4/z8nrbcwEuebN2TZ3BqZYsiNAnaBJ1Dab2iZT+6XGC9Bw9w/MdqH8/RTW4GbWWdsUfKeQrCLXhY5jrse2qM2CAT187DChhfoSMPXh/1FAlk7EsYqQpSFi/zH027YJpkBluc+F2d/01Uak2o14IfB3sM7HeqajyCeKRMMoRoyBtkNkai8399e4Buxo09hs+p7D2CK+Bx7QBao/fDT8/tfbsKP9K01Yf4dPXXkPquRzyIaVsHUTjJ+gg0aSSbKJUhb99BYevu5GDj3xI3z0pCMpZQg1dQ6q7QOuaTIPZVXaFCmOW3Ul5w+0yRJ97Lxl/gyToqncIlKYVK8SeKkQoCfNff0l1Iw9UE1ToHyc9gN65GuKW7tE4KlA8aM6UyWgEsjQAPR1QbpE5w++/qJur3EyasIkSJegjOoTfJK1IwzDpreA6TDq9rh9sf069rl6UaXuOpMKYkjX5PqBT3RRJdZErPkJHX9GCq+iTYigCr4TQRJR6+xn6+2Sp30NsR7hqH6MklgL2rcJzj5W1AA9DEEXU5nm3nrPQ+gcTL9tE6i3IdaLlL1v6BoEnq3Q9t7mUcResFH0dYLg7zJwLiMNnaZ9i3Btf7id+hHjX4qxRXy5HNxxBxx0AExqKVzv5dg5+plLuiW/8m7SeUJpX5FSwcEwZ6YlCr/JJZChfmTDCk1m9RNRSQXZQbo6t/LbK3/E6489xYn/dSn7ffRw6OrQv6kJk6GkBOlcD5vX6/qcdc1aURV9yAO/7ODyZBJPQQHeSOgRoFsRpmM1zsa1JKbtplMhaupRpeP0Lk7O9zOG62yaY9tRnS5pSnYQMoOaXFcvAxRq5r6oxomgkqjyymB7Rr2Z4t1Rk+R6gS/ZoPnU9iM64qs4O2/LDEhRfqZRm5MjBi+vfdtXZW9bjKQovu12kedwZApvmzzDKEam20qe5sWl2PM9KnNwqP/u4uDtjLg29v4KdC3b8LFD5xCpwIptYx/PWmf22V54VhOLGGNCfFcxtojPhohlCjQDt6ldKaH0A6ssl8kFQ9xZDMr9aERxvNxADT0YipOH3s3aBFpeBU1TUU4eBrby+lMvcPelV1NeW8upP76GSXvsppsa7NcFpgF6u3Fefwk62zVpTJwG2axPhGZgB7c+Z8I139kBMaZL1iATGPDFe9uV7k4dqTquBln/FqppCmpcDdv+IzXt+seSoSGkczVs6dCl4Npm6tqouSxqfBOqtMIfrDxTmknbiPhhm21MqTTBDWoJBafYFWQMSdsVZIzKM2RqV5gR994GKtCYflgVbGy/o5nU1RvfIgbbAHERcX0j1N6whBpeHrHMM9dL8HAF/RqGPEci08Dxo8jTGpCLKTHvuhQ7niGqULsRXFTYdpG2ova3+1NgeShC1MX886aPkb7nYi+u2wPlP4thpRhjuzC2iK+zE845B848E475pF4m6ACXXMZXcCK+n8hxC1DbQQ/hh9Selgj0PplByzfo6PJnAJ1r9PRHtRNgfDMKwenv4e8L7+SBa29m308dz7FXXk5lfX2AnMWolP4epGMNVOlZGpw3XkZV1uoKLGUVoBQqmdb9UcqdI3DA/7GZqi82qSO+GlQJb3YI6evWx163AjauRU3bDTW+yScUx52INJX2TJ1eQWw7v09ZPzarxJmgoHeLzhccV41sakfa30SNq9G1RutadH5kYPALKTRzKwrMnMXg7RC8h97AZ/kYvTB2ZQ0Y7jHtWckDgS8KHT3qkmDYpxhlJgv4hAJsFCKb0LLA9m9zW/u6jJpQres1IiR0uYcjU2t5oF9FyLOYSTXw53CEF24fCtReoJ1RXLfAeRd7kXH/3pbgq3catm89YQXwxSpxVBhbxPf738OJJ8KRh8N9v3EXhgYg21cWJjtvcHXw3+ajfiX2G17hNpLNaPU30INqaIPqOhChd30791/5A55/8BGO/ea5HPLvZ5IsKfH7INYIopT+6uRgsB95aynStRHVPBU19YO6r4P9Ot2gbJyveDzFZ8y6lqnSRiLppigkdcmz7BDOC3+DwT4SM/eDpsl6yib7RSDC1OkpapOw7yXcu9fbzBgP2iyaHYL+HpwVS6D9TahpQDVOQk1o00RoEvy9iXKzVsWWkFlUxIoUtZVayicybxsTRAOBnCzwlZyX1pIIRv45JhfQqCn7fo+GjG2MQIzv9HrPN2r66qpB92vBS0IUgQxLtFFkEdGPqKCawDK3byELQhDD9Stqe1vpWb/bgmbDLyMR5+J9jEYBRuz3nhlG3efb+L2T7z2zqVKKigrf7fPpT3+a//7v/wbgzjvv5Pzzz6e0tJSFCxdy1FFHAfDGG29wxhln8Pe//52kKbCxPX0YU8SXy8Fdd8EBc6F1gj+w2eY/E7ziqjQ9k0LOD3YAvW0q7UVyBnPAwlD+Nkb5uIQhA31Ix0pQCVTzNFT5OESE1c88y90XXE6mv59Tr7qE6YcdDMkS90YPd7mVn1uYUKjxzYAgq5ZD90YY34hq2cWPIg3D81d5//nLRZBEAvq6cZ5dBJkB1PQ9UJNmaIVZLD/KvgZm+QgvBv5hHejejHSs0iq5twtqJ6AaWnWx7ZoGlD0zhK0Mwz49Zd1Xb943Q2J2+TOzjaXYzIwapv/GLCqOXm7mIUQFo0y9yXrd5ySf1c+J484u7yXch6+buU6h+/Kurw8TXhS2k3htxRZYUOR43urQOYT7ORqzceDZM89F9GFHPH7RazSMAgz0sxhG+o3vSCjLbJoqzHMdCY75zW0fiSqlWL58OTNmzAgsz+VyTJs2jSeffJJnn32Wiy66iMWLFwPwyU9+kssvv5wDDjggqslt78OYIj4bItocmR3wgyvsEkRe4jr4b/mJ4Js/aMWSSvs3M5fVUZTeAGwVTvaqrShvueRzsHWjrghTVYeauCsqXYqI8NQdd/O7Cy9n5iH7ceKlX6Nm8lQoKbN+UsoyVbrh/Artd0ylNVllBrTyEoGtW3BWLIV8jsRuB2nfWiKFqtYFrRXoQbqkXDcfiAa1Lh1ATxfO0n/C5g2oXfdB7bqXW+nFcVNAQi8B5jqYOqVJK2/R+OcC21tq2xQMyGVg0zqksx3ZtBYG+7QKrG/VptHKWv1y4BilYVSYdb3MR9HHVgIfgcESQm3aCk/5xyyWMB1IEYl4UYjqZ/AP96sa5bbhgV2F/hzFtgFFGFo97C/fuo4quKhgx+0l7nDHzLnZgUcF67cRRRXmKIis4J0vrKDfBzAv9fb8muHnpr9bfyZLoLT87R+qCPFt2LCBE044gSeeeILBwUHq6uro7+/n17/+NX/605+4+eab3/YxC/owpojvlVfgU5+Cs+bpfD7QD15uSA/ypiSWmXrHBDbkM/rTFGGO+tEl0v7sBuISUXYopBLdyENvrjrfrCqOowfz7k5U/USYMAWVSjPY08ND/3UNj/38Nj761S9w1LyTSFXVQFmlVopRPkfQbRszopkmyU3uFgUMDuj+lZThvPI09G1Fzdxb+/Bcs6Eqq9T7ZPqDydwoj6hk6xY9M8Ta11FTPoiatT+qxvVP5rN+KkTCIjl75Eml/bn/nJyOJsXxSdGuRZpIBk2jg33aZNyxWn86DqpxEjS26fkT3QLivlnUUu4FZlHHX190tvhhAmSg+GzzuITvtY2fnG+v8yJUk76CLHjWJLRoOJVmbyuBxW9/26gXg7exbQHeKbIfbbuhF5ptQoRKHZaMh0NIiQYbfJ/Aein0Fikoq0JUguXLobUVKitH2ZpStLS04DgOBx98MD/4wQ+YOnUqjuMwa9YsFi1axPPPP8+CBQtYtGgRhx12GI888gj19fXv3BmNKeK74Qb46ldhxnR44Rlrhbkxjj/4RBZ0fvchmUE9iA8NoBrbPBWzYfmb3PON+XS+tYpTvnMRsw/dT/e5rBLSZYxufr1hjpvPQWc70tWpTYgTJul0hPa3QET72Coqix5HBvuRN19G3loC9S0kdt0LVR+RMvKOwjdbiQgM9Ohi25va9WcqrU2i9S2ouhY93VSUySzUlr86pBjD4fdRP+ai6tDsh0+0kevs/ZRvGhrV/d2+Z2Dk5t/B9ov53PTK0LYFf0StLL5utMp0pDaLqb6izY6w/SjeAyK++N8jb8cI92jYdt89iIgrdi0hAHz90jJuuKmMmhpYtkzPGzAS/va3v3HggQfS39/PpZdeyqOPPsoLL7xAKpXikUce4ZJLLqG0tJQf/ehH3HbbbcyZM4dp06axYMECSkpKuPbaa9ltt92263zGFvG98QZcdRUccRj82wn+cju5GXdQcnJ+FRSjXowSdFzfT0lZMActOxj089lOeE+1uNGiYoJNXIWYTAZSI6SrA2lfrpXXhCmo0gpEHF7+wyL+3zfm0zpnFv/2vW/R2Fyn5wysqPFKqKl0mT5eLqPNufYAa7+tGr9VeCb4VImeqmmwR/cnn0VWLkNWLyex+8FQWaNNuhXV/liYTEO6FMlltAJc9iyUlpOYsRdM3EX7Ab1r60aCJt1yb/mcVt2BqjSWiVjEnfrInaA3lymMGg2UFXOJcOsmZOMaPfXSpnaoqNKBMo1tuuC2iRg1Zm27mLUdqeltY80qb/wcdgCM2UYp33pgBhc7p9Bu3z6+vY4EYKVJhFM5CvAu/wxH/TMfjghGue129aMYaW7DPu94+9u4gxBxntvRx1Fvti3HKKZQQ6Zd0L9Hs4c7YBja2HP/Cl5eWkJ5OTz+OOy11zZ0Acjn81RXV/PPf/6T3XffPbDuxRdf5Ctf+Qp/+ctfmDp1Kv/4xz9YvXo1F1xwAf/85z+37UAhjB3i+8c/4OMf1wN5LqdnY7/+RzrUH/w3bVOqzMlb5coS1kBGcNBNupGMZp2I7xvzyC7lm0nt/EDjLLbNp1YqgoijZ4JY/5aeXb2+FZUuI5vJ8OfrbuLPP7qJI84+g49e8GVK0gl9LqZiS7rMnUUBq/SZS3i2ac4gECmnvBke9LRNeiJbQSAzpGduqBqPtL+BdKxBzdgTVduo20iVaJJ2HFjzGs7SJ2GoX8/3N3mmG4xiR4Im/esXLh9niDJcps3URzXBInY0bpF8P3HyurTaxtVI5xqdR1jTgGqYhGqYqFNLku4LiT2RbTgAxgTQiJXOEChzhrXeCa63A2y8dcpaR0SEqF15xErliKw9ifVsFcF2E8f2/tzDJswR1hes/teplAKMymQbucPoFOX7GCKirUXu8yduoMuiRXm+9I0GjjgCbrzR/wmNFvl8npqaGh5//HH22GOPwPEOP/xwfvzjH9PS0sLee+9Ne3s7Q0NDjB8/nv7+/u06n7FDfNOnw5tv+t8rKuCvj+pXDCfvh90bIlL4b975jCaJpPWGHxWiHJ42xyn05QX8RXa0Y2TIs/b3SC6rB+vujdr/V9uAUgk2r13Hb795JW8++Sz/dtXl7HPiJ90UgoxWf6bNVCl+vczw7QqpwG2AADiOCIcgKgAAIABJREFUNit2roP6Jl2RZWgQWfsmpNN67sLMoC5dtmk9apc5Oh+wrGKbjjV6hEyR4eXup+RzsHk9srkd6VynI0bHm4jRibpqTSBgxW0vHC0KPiF5aS9WBRdDWIFIUjddwpjD7Ao49hyEdnRpOPrUU5eh5OTREkfUz9Z777EHbO9d3d+oGAGEUyO8j4jtwgeNajNK9YyKfEbpA9wWEjXnMVwqRaBb2zMshq73GIS+XIX3XdeIclVfZoBEXes2tbtkyRKy2Sy77747AwMDXHrppfzP//wPixcvJu3NNgM/+9nPWLx4MT/60Y/I5XI0Njby2GOPsWrVKi644AIv2vPtYuwQX3U19PQEv9/yc/joR0Jjvzkd9+3cfvDM27gJioBCRWLDDpFH9ICnk+/c9cpXBEaFGdNXRJuSGdLpD7kMqmkaalwVOHle+8eT3H3+ZVQ21HPKD7/LxDmz9MCeHdBtZwd0uyXl2uRoBmgTcOIpMDRhmgCf7BDRP7zwvnjKV3I5GOrTg3BmEHn9JWTNcp2wX1kLvVtg4xrU5FmoD+6vC1kbpefNO+ge0w6kSaR803I+pxVsIAfREJ4TDIIxLyB5y1TphWP7LyqSGYTOtYgJlBnsA9cs6vlaIdiWZxZNQdIkrzuFs0d4Zk3wzZdWsJBXj1J8gsRSiiLRii/wzFpq3Txb2xpcUowoigaWjGK70CFGHsetPiv3jwL+E3/bSEKylkd1IqrvBf0Pdcnj86gXhqgXyqhD2wr9nSTK9wYKyM5xkL6t0NcLdQ2QLiWhFI4b5JWoatABf9uARYsW8cUvfpE1a9Ywbtw4Dj74YL7//e+z6667ett0dnZy5JFH8vjjj1NdrQPc7rjjDs4//3zKysoC+X1vF2OH+E46CR56CIbcKMPKSnj5eZjQ6D+Q9lu9IaREWg9qdkSeIcDSCj8iEUIDMvimKqMGXHi5W+JHABo/lvHPGb+i7aNLJHUXezbpKYFKy1FNU1Gl5eQzGf72s9t46LvXsd+nP8WxCy6horZWP3xDfXqg7t+q+1M6TvsOC4IrLFVqZonw/ITgkTfgpSWEkS7V55DLemZkQWCgD1m3wvW3rdPbZjNQVYvadR/YZQ6JRNJPSgcCkZ02TKkwhZ9PF37J8KAs+4l1jyMHK59EZbAf2dyu0yc2rdNvq/XNfvpEeWXE/qaZkL3GPpZXag0/PSZg9kz6/TUkOKziU0FfoyFe28+YsI7p3pFQB4NEUUAgw62LWO59RFzfMOl4ZFOMkIxqNi83UUQIBUn34b4pIvo0XH8iEKFgij8DEWboov2IbGAU2+x4BIZ/EWSgF7ZshPJx2jLllv9TKqGNIt2dMK6KRGkVlL9bVp93H2OH+Hp64HOfg0cegaYmuOUWmLufW87LkJ1T6MuzJ1RFQcIdQJycbxItqfAJCywCdPx2kylf8QUS3b3Xdn9RIgmpMk24Jpgj55ZNcwdBQWlT3aY1Oqm7rgWVSNDbuZl7v301Lz7wJ46ffyEHnXUaiWQKxNGTyoqjCTCfhdJKTZ5AwBxbgHf2RygAPd04m9ph9Wu6ELc4UDkemqag6pt1NGapm2hvyNYocAkPXtbLRRQpetc1gT8FkpVn5AWmGJWWtCq8JHV/+7o1aW9crT/TJTplonGyVoYlZQTqeYaVJRAwf4cDVswgak98bFeX8XyDtuKzr8M23B+7cIN3Dd3P8HLvw1oXUEAUJ6ZIk6Y5lxGWhftV0FerTwWQUL/Cn1GEPAL5hQb4yOs9nM91OLIb9qXkvYWgqhPt89/coatENbWhysp1DEUypf35oF+0U64ZcmAAcDQxjmGMHeID+NOf4Ljj4ITj4fbbXfUmeHlUnnJwB9fw4Bjl1zHmKWO2wqRCiL/duwjJZZBOXdVETWiDmkYUsPK5F7n7/MvIZ7N8+gdXssvcvfUOrpoU0CbJwT79YLr1OVXKjb40pb4i4Zo6TdI84kV14ohrWrWSuD2145KU4+hBPV0KiZSms5WvIEseh/4eHaFqVObU2STadtV1SN3AGUArypwxxRrStl4iEindvnJ9tFk32MioabuSjjcXoAqqLMdq00spcGey2LoZ6VyrK8ps2QDlVaiGFlRdq/YVpnx/Q8G1M9cCgoNoeGYHRwiYPQsUn1tizasso6xnWTR5k9Qva6baDPhkaz0P7ywxDUegoSbsBZ5aCymjgEq3j60Kj+H9aX2PUqlFfcAR+9t9g8LfdCThEXEMe3sirud7EwGyc/LIlk4dHFZWCS2TNcG5EepeSUHQL9bbaMocKxhbxHfxxfD9q6G2FlaZQJfQ255n7jR+F0NwljnQq1BghaPnLRNdoAK6NdiaxGmjGI1CcfI+cZgBKTs0/CS0gJ18LX1btW8KUJNmoiprcRyHp355F7/75nxmf+hwTrziYqqbmwJRpEJCE8hQr1tRoULnv5UYgglPhuuSejFC90ydronUvHUHUkZCMAoLhWxejyx7BulYDW0fQNVOgN4uZGgANWGSzi/c0oFkhrR/sKp2pHCOIrDuS9jk6xGi+ybuBa9YUZxeYd+EJsItHTp1wo4YndCmp5iqa0YZX6WdIO+lRCj/OXKsFzBzHEfQz+H2KD7DJAk8f6Fpx1bA3iBunnnTtPs9PJiHTcfbQlY2YQznXwsTcMFxrbYDbVnqMHB53P3C5xLVn0jlWGSfcPs27OtalPBUkeX/eoh9vgO9yPo1+vfc3IaqbdDLTSGHZJpAfu/7mPAMxhbxdXfrmNnDD4e9diOgRGwlZyOZAmWVBbOjNJNpNxTf8i9lh3SlE9OuMXGakmX2wGXIwDanhv18ZiJYO3DDyy0LKjLP/7dxjc6xa52BKq1gYOtWHrriap647Vd87Otf4aj/fSbJUneWdquSiuSzWq0lS/SALI5Oi/Cuy7txqyN+7CqJDGxFlr+IrHwFNXE6auZ+upj31s36B1deiWxYpaNFS8p0zdCmyVBSinJzEQE/tzKQU+mbjL2Sczbx2FVUwpN+eiXWrHQGmzABcXKwaT2yaa2OGO3r1iqwrkX7CavrUFG5eEqhg6rwB1uPoJLBFyrJ6yAb8KdhUuBVqfFMrVZaiB1w4x3EeiaL3R+bUKzIWL/PllIqIBj8hTZZRRGJ3XYBodjHiCLZcFshc26UyjIvNZFEFib9UPvhc/dOudg2xQivqAz+l8JTde7vQDrWwKYOVEUlMmmaNuWDtrSIo60vXgCVe79Kxr3vCc9gbBFfGE5e+/hsMlOJwuLTtgkNCtVXOIpQRKuoTL8/YJkIQJu0wkE1BUj4+w6nskIQJ49sXg9dHVox1TWjEknWL3uDe74xn81r1nLqNQv44FGHunu45+YO7iLilnBLaOLN592I0JS/nTGrRZo6Byka/GIUrkFJhZ8vmB3yk/qNkh0aRFYsRd54CWobSXzwAGieikK/FEguo/0MG1Yh696CbEbPJF/XjPR26yjW6jqUMfdt90CjCKoj76ITyNuzFWEuo6vidK7WA8rQADRO9CNGx9Wg7LJlxs9o1zsMEC2W4huBtOxztasR2ebecAqOSDA1x2wfVkoFqilEWlGmSBVBAmHispVtVJtRKFCeEWQaICnrmFHkW6AWi20X0QcD7wUjSgGO5v69uxD7BaK3G1nzJmQGURMmIs2TfRVnrFmptBsVbvrtXlc3WG5nwtgivvZ2PS3RF8+Bz57uL7er7ReY5IxJzPZZGYxw6mZwsQeYACzCsRPg7QEugAQ6eMAiUfst3qq8QiKha1muXQ79W/UAW61raL744B/59YULaNtrN/7tu/NpmNJm+evQaQNJ7aOSoX790A/26mOVVWrThj3Y2dchVeoSYF4TvzfAhUxsUeeWNMq4kOQln0fWvIYsfwESCdSMvbTKC11TIaHnLOzZpN9SK2uRVcuQjWtRVXXQNgNVNd71Z5bo/jtZgsn8VtBJOHfTPCtm0ltTrT6QkmCmMbJ9hOZaoe/LpnZNhpvX6UegvkVXk6lvRXmOf+s5NIE5tuJz8m4frH566RTui5VK+v0KRMgWM6tZb/H2i55nDk0ECSHKDOiZhochoYIAG/fYnn+vGMFaRFiUzLDI0zqH0H0Ikp91XVRoO4/4QtvYiFKbUSov8CJhLYtUg+88xFyXfF7Ps9mxFsrGoSbvCtXj/b45ef3Sn0i46i7UvZ2U8AzGFvE9+igcdRSceALcfou70PoR2Q+4qdZiKnkgvvoSIF3ih5ErtCrKDgYHbC+Qwm3XcZPgU8bMGDKdGtIoSGdw9/fMVi45eogglXSZV+FEercgq5dpwpjQhiqrJJPJ8vAPb2TRj2/myC9+jo+edw4l5aGK6cb35ji68onkNQFmBjUBlpSzXTVCEynfBBw8sJ+M7c3mUAKptB4v2t/EefUp6Nmsq8ZMmaWr1Jj0B6XcFwBrhop8Vs9kv/JV6FiNap6Mmr6HWy4tB1XjUamUS4BmgI54Uy9AwYjgK7Wo/Dz72UomEZWEga06f7BjNXSu0abbhkm6GEB9iyZoQ6ZhEhkuEjes1uxgHtv0aYKylPIJFSySjVIm1j0qSkQQGPwNgRnzYsDsb+9f5OXSnKt3HYZTgyHCLNge/95AwO9d0F6BKhwhXaXo8ggifJf9eiLWdejtQt56VU8p1tACbbui0iW+mRPRVhdBT11mT/nldXfnJjyDsUV8AM8/D9OnQdo2VxrzFaG3P9zlxlzp+A5d8/ZoFJZtkgr7lWxfiynJZabpMQNkOM8vVarTGRyXAO0SaB4JEhykhjGdiAh0d+rgi8paPbCm0mxevZZff/NKVj77Ip+66nL2Ov4TrporrgYEtIl4sFf/CNwyaWo0pk5DTqZ9Q/b5nO8bBXdWiTDBu+fpmqJlS4cOhFm/AjVltp4fsHxc0WsQuB5DgzogRRzU+Ebo68FZtUz73tp2RY2fAElXFXrTJzk+MdgBTvYMD16Cu6XEA5VehKAajLhPPV3I5nV+xGhFNaphop55wkzG6yk+sfqQRCfI5/x1dt7gqMzl7jNpKst4s8wbRWkRsPebMZ03/khDHGFCKzhZfIKyFFp4f8zu5vnHsgxY+4RV3UiKMdyXcP89P99IxBfeDwrGkAJzZ8QL0ztEgOL5qx1kzRvQvkK/TE3ZFRpbUSph8a+4Y1Jep+i4lp7A9TLnFhOeh7FFfE8+CdddBwccAF/7mn44M4N4pZ88X0jK99eZ4tS2uSsKyjI3GfVlfDaBh9oQpKugDLGOSjjZZigD8QlRJdx8GXeACuexAZLPaf9f90ZUgzuQivDqX/7OPV+/nOqWFk65/mpaZ89yVexAYUK+S0Yi6FSBoQE3mrNET5hbWqGvaWaQggHHqxLzDj02KqEn9H39RWTlUj0D/Qfnomqb8KYRClwDqx+JpJ9SkcvomqS5DLL2LWTVK6iaRtTMffS2g4M6grR8XNAcW/Txt0xmtuIxSilQBNuYUN1nwixPJLVpyo4Y7XZnz6hr0eZRt3xdwbHt8mUFSfBuZK4952RC4c1wPpLvySZyr22rZJr9AhkmlEDKhk2IrhoKqDoneLyC87T2iSJA91LobSylGUV+UeQYRXxhEi8gOCJIcltIb9t/G2Jf454u5LWXkME+1PgJqF1mocZVm6vl98/UuU2mrEAVIq4BMeFFYOwQX08PtLRAXx9SUQHXXwdnnqnVjSN+GLn9sG8vws5tbzJWo2SMSshr02RJmb+Piea0fxABX6PbvnkzD+fUuYWuMYEqtmJMpvT0R+vfcp3Zk6GiGieX468/+yUPfe9HHPCZT3HMZd+gvLaGYJAPfn+s75LP6WPYZrlhp0tSwdSOYgrTI6lUMN0jN+Tm5rnXwXGQ7CCy4hUdCFM1nsTM/aBlF32Pczn3RcNSPyNA8m5h62wGVVsP/b04by4GlJtk36IDh8xbsnmZ8WZnt5PljZnc8Z8124/McH0yKizp9mmDnox34xro69IvLxPa9ItMZa0OlPFKnyn/vkeZKyH4smZeoEwEqR1UU9RcFzqHcIqEPTAHyNCyeBSoMPc4YZ9vwM8YQZoBs66y7jdB8osi0nC/wiRujm9vH1aBw5Fe2L/n3ZdthxirgePooJSVyyCVQrXNgInTAnmkYo5pAsiU0r/NRNS5WPfBBJ7FKMDYIb61a3Wh6qEhJJVCzv0/8KUv4JmskimtVsrKPROWSpZAeGoYpfTfqRJtprNTGfL27OvgvXlHmk/9yEVvoBTRMxOnLdIyNTfBey5N4EkgICdSiSp/EAunU7iQ3i6d/5cu1VGGpeVs7ejk3vnfY/EfF3H8/As58PRPkfAUhFg/cku9mWmJHIFMn1432Of+yMr1zAfm3O3BIZHSJC3iBsOY87ACeQpOy6gNc1FC5+TkkTWvI6+/AI6gdt0T1TbL74MhJTNVkklh8C6w+P1UeOkd4rgVebIZZN1byOrXoHsTVNboCXzHN6HqJsC46uIC3gy43pRFSt8Xb+YO/KoxZtAuIEu/dckMuBV81utAmcygDpJpmKh9hBXVKE99OSEitglyGNipN6atgOorFowF3m9AuYn0/5+9L4+T5KjO/CKzrq6+7567Z6SRNJLQAQgBNkYYmwVjY3k5hI3xrgHbYIwNCGGO1Y1tQEhgA+aQwQavOSQOG9/CHLsS96VrJNCMRtJcPdP3UV135ts/XrzIyKjM6urRAOpl4veTZqYqKzMyMiO+eO9973vSQv3cYmxYFwQtYIsdT+2PawE317KzwgMtVp8NcGnAJ5axC4Y2yCWAXmzDsE7LjkI+OiRWEfrhnaDleaiBYaide4Ch8dgmM5oaoZYOJJ7jvgNkLskGKqrMcqqlto0DfADwR3/EeXyTk8CXvgga6mM3Xb0CarDLjmoVoFGF6h3ivLDKKsKVeWYP9g5xVQE/a+aEIauYRVV2Vo5kmVloKZ4nBli7Yf1bieGJvFYYpoNArNm71DSXrBWw1n2mZh1YnOWY0tAE1ATvGB/+9nfx6ddcAVCIy268DpNPfILupyPjZk9gK2ZHjQq778pLfExXr2aEnkgT6wCQSvKmxRixIQNVNg9SCjj2MJdGWpxmIszOcxxVFWWBkDX+bRcmZY4hKGBlHjR/XFd7OMZV5IfYIlQjm5igki1EGyiRu3NdZ+2IKiaHz1qM3dQHzwdVSqDZI8DsYVb0AbRlyq5Rroph3ZuAkn3/MWCDBbju80AExMrTCjGWpWmas7jKe21/bxNf5PeeBa62dWRbga4b1BxjPcdY1QrrOq7Lc03gc6xSF/hi/+4U9FLeM9KxdG3Z0ZEDwL67+fitu6B2nGmxf51RFi9PEDCA2a5Mewzs+B1wysJbR9tYwFcqAZ//PPCEJwBnn80vVaPObjPbmvMyIM/nF6epXQPNOmhxBrQ0w5ZMNs/U86EJnsTNBvvVld4x5bSbb00yAaKJY9xhQWSByKIcWwAkXqPz6oIGopfY0+kI2iffbETVGYBWkLD6QI06x5FKiwz6Q1tAAL7595/EP771ejzu2c/Er1/9RvSNjeofdfboeacaAJUV7k/3AOcECXEkaCBVHs21ELOFKF2iJe+PEsabx4WWZjkOOPUQ1PYzoE67gKtbpF1T3GdSMJf09RItbBVz7VF1VYPgcQbExWlmwA6Nsa7q8AQwMBqlYtgLvjxXU2bI2ijZ6RHx0W29Z88DKY+r0s8eZTCcOczarCNbWAt1aII3AUljZoOegJU9xm3fa9fToczHLbEuk6Zh35KAk03QcawzIAK32DH6vK5L1QU/s/Fwzmt/7gJf0ialxcVpgzTFzxENQsLfoa06/dvVZdADd4GOHYLqG4DauQfYNBl5LezhkuuLjJ/OK465Mt0+AqcA71G0jQV8v/zLXOYXAPbeA2zeDDNxUkoBJTblRcSOahnUbAD5IlSeq7XTyjyXuFldZgAcGIMaGmeLLwx44fYzUJI7JhMlazFEiThmVluNjhECDQGGXRd1Sv9pTSpJuRCXaeCU/TG/iz9Cqpa5+kPYhBrbDlXsQ2VpBf/yF+/Btz75GfzKm16Pp//+S+H7FuDYCezNmgVk8X4RYEgk6OrVQF1kpmK94gDgOt1BQLRAGxecQ+6pVUAH7gUduAdqfAfUnouhRjZHQuCyiNrM03X3RVmMT9+yCo9x7t6crv/XP8LvxeA4/1ko8milAZHnIUpdcawzI2gNCzSceycAKwtxxmj3gK5Kv5XBWKlUxmnUHQ0Knor6YcYIrb9NBQfn/TWxQes0An4GgL3ofHJOs2mQ720LLgn8KDq3bfWJa9AGxBixxYteg3bWXiye2h7ooBSTU4IAdOwg8MPvszzf5p1Qk3ugBkcSH4ExIMNmVEw7V2h1ZSaNu7RcVyTWcaqtq20s4Nu9G9i/H+jqAr7yReBx5+ovlDOZ9CQyFRXsBHdNGYfSAJaNTzRNJDGDEgbsPi0tMZD0DvFieHQ/qLQIDIzDGxgFuvsia0zAQFIobL1M4yJaa9ef1Kzdp4lVWPEVgo5d5thNOD8FmnqQQX10O1ShC0fv+xFuueIqLE8dx2U3Xo8zL/n5+AKmf2/SOsx3Krqe7gKa2oLK5PVONaN1/1L6LgnnTYv0Y7vAbBeTn42ODzXxRkAC4NqGj2hFmK4eeLsvYEUY++LCuIVlfdjfybUyOcDL6lhhXa8x7a19JqnMghanWd1+4RifS1ySI5sYEP0sJ9gnWnwuMCP6PpZYT1EM0SJwGfLO3FEG5eU5BmNdhxB9w1DG/etaMs6zUT7YHW/F4Mx4Of10LaKkY6T/BD6vxO5cC1R+a8f2jOsa0TNy45JpVp8Lsi7wmQcYvUst38dAUP4uGwrw3ApDFlo4cD/owXugugegdp4JbD+DN9AJLVpTdNyOApNOlUgiOwV4P7a2sYDvO98B3vIW4JnPBF73mla1DptwEtv1OjtJEz/Q32VyUeI5wC+cYR06LiO9YyfJs6qWQaUFtoLCkOOIfcOAp0ClJdDiDFTYZPDpGeAqBcqLXnZ3URIw9jzEJNmkr4boYu9CBRAtkNLWJ4VN4Pgj7AId0JaJ5+POf/pP3PqmazD5xAvwgr+4EkNb0yopyy7XWZhBOik9F2mEBgFbuLlCpBHacjqfx5tCDYDW85N7Snwl5T71QqZjrkRgRZgffocL/J5+AdS23VqeTffT01qYNtGpwxhgovKLa6VBMUuvUoqIKgvHmThT7I2swuEJBiPb5ShVQwwQaBBoITJZlo0UWbbdq8rjIsLzU1pj9Ci7pgfHuSr96HYm8SS6/VwwVNHziLk6k6y8NDC1nmuMXGO5MGMuUP1cTV6rC4w2yFnPw5mXHQFfW6CT71Ssn5xbFwLTR0D3fxe0MAO1aRJq51nA+HYoL/Ftl97rTbUu1qyLPre4Ms0PnDGXltWklVOA96jbxgK+978fuOkm4HGPAz7+caC3N7Km5EUXQkqsfp5YC2JtkTOBO2ypEwW8mPsZk55AjWqUQkAEVFcRLs8Di8ehunos4s0iVLGXQTFfgCwmylJuMaoykq9odquyEFlglNKo2WD2Z3mFyx/1DqNRKeO293wIX/nrj+IX//iVeNYb/wTZbA4Ias6mwrLK+IP4tXxmx5IUoW3UgPIii94WugGoDuaqPqfeFBiXcFDX42j3w7UudM292SMIH/geMD8NtescqJ3nQuW73AshppQjaRZiwdpj3NI/4yezPkP0b0P84DgfAcDSHMfn5qbYKquusktycJwT7wdGmbDiUuWtXEAAEWCnsn8t8NCgTPUaX3f2CPehUdPSalugxrcC+W4GQjsmljQ3klyd9n3bx3UEgsraQDjWn00Qs+N+5nMVMbGBVqsvEfg6ILHYm2LxKlAIVMqggw+A9n6XeQGTZ0BNngXVN5R+n/Y3UtBZeSzAnuTKTBrbU4D3Y20bB/j27gUuuogLIeZywB/8HvCud8L46xOZa26zFtfYTh4AacUO+2WOLfiWFWC7oGI0erTG+exEcMMQzfCkqlfZgqnVQEszoNUltgQHx9lqBIFWFtjNmslwImtXHyuSwAOMVFgCaLTE6sA71/IyaPoRAIqrv3f1YPbhg/jsm6/Dobv24gU3vg3n//qvsousUbOszfU1Athiri5rspCux5fr0oQkkXJTaLUkov5G1g1Z99uuaUt7/52gI/uhtu+BOusiqL7BaMdtYohrnS/N0kG0sXK9DLZEnnsvns9gtDSjiTPHuIhvJsckK0mnEKswyQrzbaF0nXdomJlIngMaXKhWZktQgFApBsLRrawElM1Z1oZ9vgTLsx3Ayf2uBYLSTJqGPBcb/GxQtC1c17VpWY6hFRMkIJb+IOdx44hKl6cKQ2DuOOhH3wc9/COozZNQk2cZebCOwC4M2ANEoZEeTM2HbQt41ub3VDupbeMA3x13AM95DjM7lQJe9ALgozdH38dYXBoEfWH0hVauF6KFyi1LBESpDFJzTdxqoodoGJvoYAFIck06zQB3YOJapDzLLSJSaXVmNs5NAUrB23YmQARamgO6ehgUZVeoPK7H5/sOe5L7S1DA8hxo5iBQ7OeYUCaL+798Oz59xdUY2roZL3rnNZg483TEAN8AgLg69fgBnMMXU4jhY0nYao2qIQVBuxBV6ti1sSjsXb2dFB80NWszgMT1qLoKevAe0EN7geEJeLsv4IU+9nz86L4SVXrEmhC1lLTivrAsPq2RqnS/RJ4sIcZHwgBcnAUWp5lFurLA4Dc8wczNwXGg2A2VlLMXc/GLK9FyZSaNsVIwYuBzR4xFilyB45PjO3R8MhOdi2Q8ElydwBqbiCRvRMJn7Sw8s5F04oBCBDJjABjSSxLwmfHx9d4nBGpV4MiDCO/6OtBsQE2eBTV5JjC2FSrm6k+ew8aVWa/wu57JtndlxsbLGkNppwDvx942DvAFAXDppcB//ifQ1wd8+YvA6busA5Sza0zaeavIUnNSAZjgkImA06j4y2IIpL340fXXADm5lmGpZaJJHmi3qKjA5IvRrtnU9ONjSc4h6uvsm00QAAAgAElEQVT1KlPeyytQxR5WAMl38eeL03xcsY+rGmhLV4EQK380ug0Y246wGeIr7/0g/uMd78ZTXvJC/MqbX4uu3j59T21271K1PkgHBpJ78bORUECuqOMjjuXn+WwlKmgLUau8IOH5uc+BrwZh0VIYgB66F/TA94BcF7wzLgQmdiAmFWb+LtZlmybPRcG4eY113xJftn4ji3Msxme56oS00tB5mQvHQYszXBg3aDAI6vxCDI4xNT4RDFV0rRYFmGRXKSnFVenndOrEwnEutzS6BWp8kktDreFOb3ElWudvuznkH1kf+dFPRK1HPpP7aYnZp1l4FIU/hIFJIbA4D9p3N2jvt4HxrVCTZ3FuXU9/HJRSANt82qjzps/PJCeYu+0U4D0m2sYBPmnz8wx8GUuLs24xJmVHZ+SmVFzuKuY662CBk2YIDRqsJOZiFNBVVNNPFrag2VrxQSweY2EAsQlm79pNEvxagKp/L4QPgBP7KYz6t7qEcGEaaNbhbdoJNBsIl2Z0bLELmDvG7pmJncDABFamp/GPb7kO9/3XV/Ab170ZT7rsUq3+0kmzLCUZOxnPXJElJWurUXK8n+FYoPKSCTGx8yJ2r2aTEzQQZyM6Gx5PL3pHDiDc932gVuGE+O17dEJ8AlAZcMvxv02+YtpCruIyZ0JQkmedmjZgLdo2ocRKAKdyCVg4zqkMCzOs+VnoZhfp8ATn9fX0s4s6ye1vwMTaNLTEbmE+p5AixujsEWBlXlel364l8nqh2s6fNNAAWp5NJ6BoE2TcWF9s84Do/vX3FIYMUFMHEd7zDWDuGNTOPVCTZwKbT4PKZhPGxO6rA3ZBANRK/Hk2D2Tya2NVGmEFOAV4P4W28YDvG18DJrcDg0PWrjBMWOyA+KSydrzKY3eEKUukX/amdi/av7clzZLylmQXal9HrEez8AVWjlnKYmNOK8CMyIKIsd+s+0pzwdlanzFmqExgFblya2V2rwUN3kxUyxDxZ6pX8PA9+3DLX3wQfi6Hy268Htuf+HiAz6Ctsi7uh+iJmvtwqjikNBJLqbzMY1bsBTwfyhMXdSM+Ni27cXlGlhXVsrCipR+0MI1w3w+A2aNQp50Pdcbjuf6fpE20W5ClH57PoAj97hDSrapEi0+76Qy5wnUbKqv7cq9+BEzLbBVi7hhbhuUVJsuIVTg0zvckGym7tajd2GMK59+KtVznjzEQzk0xY3RoE4uKj2xmN2nsflUE5B23TixKfYxt9Uls1XJ/EoXAyhLowH2gO29nDVQBu+FxtvbdtIXYpinqi3Fl1srsPcnmtStzTbRzhtM53i5jdqr9RNvGA75//2dg9+k6ed1ujuvAWH2ZyGIy9fNUtEhJ3pod7DaWmlgQOobg6zifyFaluU4Tm7XggVotP5l0nhdZjoBmhZW5TzKxM/q3NjNuXY+xdTdrtDqJOPl95iDQMwgMjiEsl/CNj/5vfOE9H8V5P3cBnvdHv43eM8+NVG8aNV3hoQDk04StlWZq2pau9bgIGqRXI0CFAjIFqNCt0LDW7QkQynPLwZSlcoCNSousCHN4P9TmXZwO0T8E82z8DLszEbZRfkm4V9vjYJdDMuPvWqQO41jePRskY7FHfazFiqRGDdBqM7RwnF2kns8AOKyrQfQNoUWRyKQDuEBojydifaB6lQFw/hj/2axDjWwBJnYyWzWbt4DwZFh/TpPNgrCopTrG9BGE930HOLAXaseZwOQeqO2nQxW1yo9hRFt/t5mtelxML+pVBjxdvUT57Qku5rxp1h1wCvAeA23jAR+AWE6M/RK6SvqmYoPbUiai8riGHiGy4totcLIoKU/n3lmlXUR+qMWdJS7NBJKCu7hlpEYb+F4atQgck2IEMaJDMsDE71dFVqG0TA5QLOhMxw5w+aPhLcDACCpLK/jnt92E79z6j3ju5a/C037zefCyGSgtYYbKKujYQyAK4W09AwgaoEaDiTfiAvazUJm8TlOoJ/aMwpDHTpRygiZLhrmyVZLkLuSWZi3a2EC1eXZCoAiNPBTVa6B93wft+z4wOA5v94XsQkwbO5BJ2IekcazltpNYqHE5WhafWHe2lWRLgRkwbGMZym81kJECE2fmjrGbdHEGWJ5n60eIM0MTWnHG6rdNFEuMk7vXB5eWmj8OzB0FzR1hq310G1fX6B9pT/TotNlpB9KrRh109GHQ1/4dCJo6jeUsYHybZqla1qH0OQ3s7BBFtcTzTINURxB1CvA2TNtYwBeGwO23s07n6GgEbnXN5hPtS5MUbLvAToyWH7lXJG4gydAUt/xkErlqMGI92oLXiQtLJ7tdZ0eeycEwTe1Jly1EDE9hVJqJrnf3diypzXWpXgUdf4TZbhOTUMV+HLl3L2654hqU5hdx2V+9E2dc8jSTr2ScQ0EAChpQmSxIK5yo/hFmKFLIVkJ1la2EfJHHIcPgqPQ9kJeJ2KKVFe5QoQfw2sUCVXycMxazt2Hl6QGJwEhBE3RoH2jfnbzDP+siqK1ncKkgYca2BVXpg5AxLLHlmMVmj7necJnna72vLS5DleB+FzASyxCtVprECoMmFzRemOYY3vw0vx+D45xGM7KJGaVZi6ShFEytv0Q3MmKfE4ErEMxPcfrE/DEG182nMRh291lAmGYNUgvQMSMZHK+DvkajwakqOc2itEHN8x3gk3PGgY/EFVxd1ZusAnsaRGvVdqsnzRU3BcRtpwDvMdc2FvC95S3Ae94N9PYBD+1rb0HJrt5eDAzrizTlOB8tEEAkam3v3s0uXUULUgeAwc1xb9qf2xNJWfcRU24JW+OOtjByoD8Xq/CEJlbc1QlCizVGygNKi6DjD7NI8ug2IJvH9z//r/jsW96GXRc/Ac//8/+FwS2b0i7C18nmOTpoCD8E1KqgSgmqux+0ugSaPQI1vp2l4YIm66bC48WNiHfiSgHFfgZAP8/nkYK1bUAtsU+msKt2hUtOVxgAxx5BuO9OoLLCccAdZ+lcLt0kxUUUYTp5J0zBV0SLciKLUCxEm7CRQFqxz9lyPucYg11xK45qFS2/xvmFWJhml/XgGFuFo1uY4clHO+dNIhPJvfDxRKFmjE7xhmdxhosCbz6dz93VY507/g4ToPNrAZSWQEtznDzeN6Av3yr6nNSHRLADOP5dLWu1oRwLr3e6JJL9rBK+z+R4E3oK8B5zbWMB36teBfzd37FlcPSRqJSQ3WILn4pXVXf1DiXWlslHMTUAMVeq69ZRwr5LoGx3ktjr9tWupm0velldL1Cu3ai1utNsd5mJK2Wsha+DRRiIW8NScUGB798mxYQhu8wWjgH9o1AjW9Go1vAf73of/s/NH8Mvveb38Et//AfI5nP2RZx+KLaYFaIUDqsRwCzc6ioom4fKcSUHmj8OUAA1OMFWhArZeszkGTg9ny1H34/HlsxGIUTMKm5ZwOU5u331Oa3gge+Dpg9BTZ4NtetxLSVlnJPF37m2z0EfKxYfAW2T4O1cN6H2J7nNY5Ujgtb7slmSzvcEAKUVToXRVSqwuhTlFo5tgxoY4Qod7nXtjaZ9PRtoxeoUoszKAtcg3HIa1MAYgxCFwPIisDgLDAwDPf0MgLl8ejJ426ZgeJnNBnsQMlkzz4yMXIt15/5Jzuuc5NI8BXiP9baxgK9SAT79aeDiizmHzxAVdDPWmYBfEKmx2PT0E73lFkq4iiwzzYSMcgmh3YySVK0nlpBtAKcQbSeA6exgZaEJmhpIAgbwfLcmkpBVCd75XQwIOnSxaqCkRpUp7qtLUBO7gJEtmH3oYXzmdW/G0XvvwwvfeQ3Oe84v6d91SkqxXJTyb1k8rLJMvOcI2RpcmuFYUv8I0KginHoYWJrRJae2GJIFS5550aLpsnNNS1uwuW+0ugza/wPQwQegNu1kJmj/8Drd1R5M3bt2v/E8AJZ1KBu2JJATyzANNFuS3F3BbmVt6CjxGtRs6gR7zSCdn+ZjB8c51294gmOHks+ZOI5APE6pn2mzzvqmR/YD04f4fe4ZhNp+FtSmnW0IU501kusC2jMAFlDwM633mubWtBnZaX3xcwzapwDvMd82FvD9278B114LPPnJwI03RsokzTq/0IbW7hABUi002TkL6LTfqUYf6+t4+txJote62K0Jlosrrt3iKCQZZZ03bMbPbUAy4X7MoqbBVKzdMOl45x7buDpjepFWo0qJGaBEuvxRL/Z+8au45Y3XYHTnDrzwnddg/PSd8WvkuqIUi5iLD+njktRfaSKUXS/rtIgl3gCEIaha4XGX5P3SIsKZw8zUGxyHNzjGVmKg4365AlSiq9CxWOpV0MP3c2WI/mEmwoxuSbB+0PnmQkpWAe1Bzt3YtSSw682YvZlqcZEqx8K13q+0vzsxRCJiF6Ek2s8f59zCYi+nN4xthxoY1nUt5XxRM2C0ugKaPszv0CjnIlK9wu7W+SnQ7BQQNqG2nQE1toNzFdu6N63zyzXCJoT5mso4ljiouxzaG9O2gOeETU61x3TbOMBXLgNDQ0CtxmWJ3nMT8NKXINm1AseV49DDw1CnDeR1Lp+1CLjsQPmdFBclOy3CIiSsFVNylUFMbT6y8vX09eyJRBTJqIVhBKYG1BMA2471WHR3p0Nxa0Kan4uALqi3gF3891ocenkGdPwgx2rGtiEgD19+/0fwnze9Hz//P34Tz/nTP0ahp51r0D21YmFewBEAELJB+itLcj/lZR7Xrn6uWednmO4vpZSqFdDKLL9PxR6ovhGgvIxw7ghQr0INbWa3m+9HlnQmy8Ao1woC0JH9oH0/AJTHqRBbT2u/MNvvYDswNOIFlis8SaTauDW1dZ2k5CLHAfHNRgI703y3Vv5qS/UIDYZLs7p4rybQ1Mqc+D4xCYxsinQrfR9YmAFlcqyWku9KxRUqr7DCkMQI8wWobWcyMaqr2yjwRGAX8jOzqmes2wgzFh5czI6an9UW3inA22ht4wBfqQQMDwP1OgPfDW8Hfvd/pBxs7VZtcorExNxiqWLt2LtasdLakhZkp6itK2Nh6QUoqMUXhxhJZq3YzxrNLFqI+kChVWJJ/7tWZvCQxdHOH1y3q1MWbQsMvQyQ6wKFIej4Q8DcEY69DY5j+fgsPnflX+BH/+dr+O9veysuetGlJ+AFErdYwmLu+YDKaMunVSqNpExSo6IXqSInHisVbSAkCd3zubxSs6atxVVgeZafY88AVLGPyRnzR4FCL7zRLZxsX69FdfEeuhcoLUDtOg/qtHPXR5Tw5Llogk3ScxESi2yITMpKgqciKTZtf+a6OiWPz3znuErlPYshgeO+dBivBHCaw8EHgAN7gdICVyDJ5LiUz+adTKCRAr52/1PeSSJiopVUu5ifAgbGoLaczi5vE3tNs+7WanJPygE8q0+nAG/Dt40DfADwqU8B11zDVRo++AFtAATRIm+TWTzt4pMioHaMA1jbQgPiL7ZxH2qZLIROjE7H+YQoI5MuJnodZ5ZFi4/rhoK10CD+XeJn8hvX5ZVhd2wQOONgLYJyzkxOS3MpXc3cqpUnoJlIzY83atRAM4eBSonFjnuGcOCb38an33AVcsVuXPbeG7DtgvNalV7W1Zzrt4uRKg8k1eEry/wc8t2cF5i6MNrAmDECByTPMWhyJY3VZaiuHqB3kCXhpg4wUWNlkStqjG0Dtp8Fb2icF3zlsXViA8xa4gOmvFaYbPEJyJmNnQ102kJOivnZlltarp4Z01ZXZwR2cUuSAH7fFmZAxw8BSumivKNMJgE4t3BhRhOlprmafd8w1OZJJrn0DHA1Ers/SSQo6M2NkHAWjnMx3omdLMvXN8xW+poAqO+xnXUHJIvan2obsm0s4EtqEuNr1uPglkgRl4+8uLIGFAOoaHpGB8bjhmlu1XYWYQuZQj53WH8CnrpIZYyNKLX95BizqKEjMDLNdoF6GcR0R6X5WsoNWNvV6We5v0GgUyv09T0PVC6Bjj3E5JOxbaBsAV/72KfwhevehQsvfQ6ed+UV6BketE7nxcdJFhnJg3w01rH0F2Crrl7mOF8my2Wect38GgTW5gBI3xyZ3DpEm5ww4BSIMOTai3NTwOF9wMwRoLtPCz5vhtq0i4WzV+YBIrZSsppJ62e5aHGqJW69jzFAa+eaRHyzk5oWYYG9/EbOZ9zztlUXbTRIPCmry6BjB/nj/mFmfubTkr+j+6Nmk+sWSnWKxWmeixM7oCa2s8vZrllodHKjDaaAGwVNrTGq3aLVErD1DHjj24HuAX4fjcFqbTw6sQ49Pyr7dcra29Bt4wHfLZ8Ezj8P2L4dLUBk754NWYAiyShxbcnikNEpA/YOjigqpgqCSRCPLTpIdzGlLtBp32nrVOI49vGiBEOwdvtpwKv/yFj1AE3yvOWudUFN/t124ruuTqsfkrSvPB43O/9PYj6zR4DeQajxSZRXyvjna9+O7332C/jVt7wOT3v5S+H5ouvZSXPGUSxVKdTbYeNKETV2BQdNdoPmurjigX0t0XQFRZJlaz5nQMaLGjXQQ3tBD97FscadZ3NuXCYH+D5oYRq0PAPVPwbVN8xEkVoZ3tAmdts1NGkrk4s/onbgLPmFnrbSE8FQ3J7WczRsX328HOOk8BitV3lf544DzQaouxeqdxAqk0Fyc1ykbRpVV9lqXDjO1uHiDFDsAzZNwhvbylZ2B9YcNepsWUrqhFJQW89kAk6xh63wtToTW1dUtI74WS0UcQoEN1rbmMB3wXnA1q3xz1sULswX0YJtu5gS3YLWwk7Wfy3XcXfFYRQntIkNAqA28MQS4gPrO2nreBxCXAFagdjPIkq/0LJfLYw1isZDq1UYtRdbbk3IMba8Vtt+WvcKBQrqDH7Lc5z8PrwVR+69H59+7Z+iurSMy268Dqc/9Unx3/taMd8ppNs5QFpN1HaChmPR87WIAgbAWpmvmy+uIVMl9+dHuqkmHpzcKAxAh/eD9t8JhCHU7gtYEUaA1vNBpHjcPQVUSlxrsdjLyf0zh0CrS/AmdgL5IluMjRpUoRvo6uFKDbZLNOba1FYad0R/luAKta06iUWLVQZw3bowYAu1pNmz+SLQ09vGLSnXXoNV7I6X/EWHCIiI3ciLDIK0cBworwKbd7LgweAokC+ifQ08sjRGp1jKrbsPautujkvnnLSJmBs6xQKHBYIiPHGqPebbxgM+ABH7sq6pytbuVekioCYu1WC3CWAtAJb7Zq3Wwsb04uBmFho5Xmkr0qrtp+NC7V1nFP1WJpDk4TUdkkxLaaNOd9LW5LXdwuJeI2g3qyX91s6KEmuLwogJK9exGbX6ulSvgKYPAfUa1Ng2oLsf3/3MF/C5t/4Zdj/tKfiNt70Vg5vGovOLNdpOjcTLAAicOoAduH1bzuNxgn69rEsmaSuwq5eFiQ2BxnEJtpzLcoPGxkDfilLAzFGuDLE4A3XaeVCTZ3OifvxE/FulAFIgYVE266BajSXF/AxbMtMHObUgw6CtCt1c5infBZXNc3wxX4zYpmbzZwOdk/aiFMfPqmX9XrIWK4iYSWn6mzYe9jPo7P2MwE4/TzOPkWjZcd1CyypcmGYrecvp8HRe4VpWIZVXGAjnpkBLs8DIZnibTwP6hjjXL7bZkntqA4LKi9KZToHgY7ZtLOArlZjgcvHFwOMex5+ZGJ9WAWkbn7F2aJ7FwpSJYacymJ84uVN2XbXEXKiUlkSUEYABRYn20k8zeZQmpzSje0y7L5l0mSwfFlpVJuQ434dxnZqFlaJ+uRWuY5sFF9B087JRUnYqUCpTCYOWZkFH97FE1Og21AMP/37DX+H2j/w9nvXaV+IXX/1yZPMuECTcrz22qeQWxakRYRAn7KzRSHINa7rIaK4rYoSa+9bEF5ClctN5o6U5rgwx9RDUjj1QZz4RKt+VYJV2cC7PZw3LSglULXEMs15lObLqKv87m2MwLHSz5mm+CJUvcupMVtccrNf4PcvlGOgadb7H7j6YMjyJc2wdzwSIeWj4D9LvN0z1+vWSMomIq8ovTAML0/zn6hLHCsd3cMyx0I3kfD6t7LKywEn688eA8jLUBFuU6O5z3KIdbK4MCGbim+VT7afeNhbw/c7vALfewi/RoYeAgrXrBBBjntklicSqiam4hBZQOEUgjUZmAx2Bm4CY70c7Zwo5jhYDCD++aBgAXWORiC5kARVFwX03RUPibkI8aQuaurmszno5GiupW5hmebXtcsK9Ka2VOH+c0wP6hqGGN2P2kcO49U3X4diPHsSL3vMOnPsrz0pgf67TmuukeT67eSngcbKAhwj8HGurGhCKDB5pC5ltvUs82a3XKCWStNuYKiXQgbtBD9/PKiinPx5qaCzlPhViupypzZ4LHsfl6nWWgquuMKDXq6Bqmev4BQ0GvSBk9+rQGDCyhYE4xykIqsVL4lhy2jpt69bU1qE5i3l3lSaerBPt3Obk31EQAMtzcTDM5DjfcmQzl97KZPR1VTSmSrEHYIn1S2nuGEABC22PbGYXr1JrxwfNrXtRTPAUCP7U28YCvj/4A+Dv/x7IZoGH9wFiFbjB5VRrDxaQtTmGD0j42o/0Qe34nMQOvQwvEvaLHQaRzuaau2Av2h2S7qNRfNFNwJMIsSKmlNLnWNP0dbkXuV2X1Sn6oTZZxSQDyzhRxLxUygIo2x20dp+o2eD4X2mBE5L7x7D3tq/gljdejfHdp+GF77gKY6fttAcpfk5xDTerjrvTPt7tRwcxSnuDob0CJOVq6hVdNb4XKPQwIJjUFjsutI6mfM6FfOheLo3U1cOKMJsmO1xcLaAz7ktXp1T/k4jfyaV5ZlEqH9TTB9UzAIWAiSX1KguI11bZ3Rlq12+hm8Gw0M16pYUeTW5CSj+jGF8M7ORP3Vdl30PavbVrnSScy6G1CrtIJcl+ZQEY3QJv0yTQP2qlnlh9hQKFTSbKzOsST9k8A+HgmKmG0tGzUkorDmXjHqdT7SfWNhbw1evAv/wLcMEFwI7tkVSZDT7imvQzGjzIymGTXV0n1hXQHgg7AdKk8+mZ6YKj+ZriSeiArhohuYBtFlYJsoulETSjCg5ygZj8WFq8wmpyLSnnI5JqLgPVqKq0cTGLZBmIwSOISjpRtcyxqrAJNTaJZiaPL7/vb3Dbez6Ap73sJXjOG/8Y+e7iOkDFiTEluWilGUvXcoW2GeeIEVrh8c12sRVocjwp2sSIMHobi88dfwpD0NEDXBqpWYc6/XzWrZRNV4u4ePvVngAmpsxOgY4+BFpdhhrbBjW+DRgeQ1yg2fzC6q8CNQN2mdbKrIBTq7BLtVbmcQCAfBczY4u9QLGfq7/rqgd64KL5EgM795rraWLaWedu1xLIaUQBsLzAZKKFaY4Xeh7Ull1s3XX3mQ2nsp4jF/49Blo4BiotQXX3s7Zo35ABtDV7pFRUV/IUCP7E2sYCvv37gRtuAC65BPjN34zcPc26RR5Jm0jWLt5+2dxUBskJtBPTlYrcfVBasswizHREklnLKut0AbAWVpNjKMLEtiWmgTPULte2rk4V1a1TKjk2qHRah1iutsV4MprS5JLSPCfAd/VCbT4dS3OL+Nwbr8K+27+O5//ZW/GE5/9a5A5THscXoS1jd4xORhOXuXnuFogpn0GwvqoLl+oKEZkTqCAgY2rKXunhnz/GRJj541C7zoXa9TgujbQWjR8ALcxAQQFdRc6vyxagRiYYpNPIGfJ3W/Ra+gekbvCoqd+Z6ipvYqTcT7XELlTPZ2As9LBEWVcPA2M231rlIbFPbW60MzOrdZOaxnYFNHFmOrIKy8tQ/aPAph1QA6NGjDq2Na5Voqr09SrUwChLtRW60b6GpNXHTDbavJ4CwR9b21jAd/75oHvuYRfnN+8Adp/OL5N5gcXdIyormWhhFNekcU+CVxZfExTseJnk8q1BUY+sCPAL6+YEBs148VMZaldb0d1hm/nuPBqTR0eAcuMtHTR7Zy+gmZgGYcVF3YXOtgAzOVZB8Xyr4O0acaeWhP7Wz7j8kSYYDIxBDW/Cg9/8Hj59+VUo9Pfhsnddh63nnpVwXyktq+WlUvsn1qq18K+HIQuxAutsyTbrmlXZx1ZarPySgIpYn5258ai0yESYIw+yYPPux0MVI/1TUr5xi9P8DF9paAzGleguosadbgGbG8dN3KxZcweAqWVox+1EU1Yv9QRANestZBuqlRkcRUygUITqHmApuHyRXaqaHansTas5afthi7WYcpPMnQQwND5bFRsHJs6UGAwXZkDL8wCISTMjm4GevpiVR0RAZRU0d5R/E4Ycvx3ZxqGaTqxB2YyeAsGT3jYW8D3taaBvf5trl33jq8CmTZxHJQoimlyiBLwe1a5fJoWAqT6XicHphcuVkRJiSSwlIEDbdAZ78XfzAWVBldJCBiSS3LAqUqQhsIvX7Zur+LLu3DhZKCiyTtIswBYrQfFO2c9a95TwjPQYUqMBmnoQWF2EGtmCsGcQX/vbT+Kf33YjnvD8X8WvvfX16B4abP39ibR28VdR0pFNTMs9xhdSVofRjFDP08nxBYiYcvL1tbuYtLvYxL/0e6QBiqpl0IF7QQ/v5UT408+HGppAlH9Z12OcSVhYfQCOi9o8/zbeAGX1y9wzIssUiOZHYtxORb9Ncu1KzLFWZmCsVYHaqv57hTcs2QJXZujuBwq9UPkCs1E1ga3lXt13T/4tl29n9Zm5b837GMmNjyEKdTV7nVtYK0MV+4CJ7Rz3E9CWeywtsKLMyiJviCYm2XrU6SRtoc14qE6B4MloGwv45ua4EO1TngI8+WJQvQZUV3jSNOpR3KhQZJdTrhgF3pMsN3EXhoCxFFviG7JTtI6x4yEtFky75lg3xvLT53b7aCqrI+E7WZAAoywjLWupt4Sh1gp1iti6/WpxddbQAppAggWIOAC699RxS7EGAVBlBTT9CAAFNb4Dq6t1fOH6d+EH//RveN61b8XPvfx34IUNx91p9dtU1Vh/mkByVx2w417Gj8x6g9QAACAASURBVPEycY1QWbwLPcwqdC2+DmNUbFk2EU49Atz/bWab5rugznwiMLkH3rpIPPahfvz9l41MmOzqjFl3JhxgFQGObSQ6fR+c/uox4fzKKgNjXYNhrQyq8Wdocukp9A5AdQ9wuoYGf/HAKBPnlX7YoOakGklfXPBzrd0kEK/XDHuUSot81PAmqNGtWilGXy/UoDk/BaquQuWLLGdX7DHXTn0bJFne1gQ+1dbVNg7wEQG//ducx7dpE3DHHcCOHZE1JW4emSSNKi/e9Sr/Ps/JyMh38UuVtoOikEFUSCHykkIWJmf3C8DEAEViLBR3aUqhXHmlTTmipIm33rYe95y2DBWc/EE49QDTrFR9HuXxYp7J8nOorbLFEcsBlJ8oDayeTi2xQcrDWq5bImJa+sxhzikb3YrDe/fh02+4EvVKFS++8XrsuvgJ6xwPOdQD/Lx+Xq3KLvCy4KoJ6VZL9DkSv+O8wKpOE1FM8sl3QQmDVjZZTuoDeT6nG3geE0oOHwAGhrl2nZ/lY48eQLj/TqBWYUWY7WdxkdU1m8XylXGQzVLSPchfQp324Xn6mSIeclhznOzWBhQ7dGfy2PJcjwFjtcxuVaU4Zaa7n2PH+S4m3FhavcpdA6RvrtuzBfza3ycRaVFuXaqpUefrT2znmKHeWFMYQC2wVikFDZZ+G9tu2KKpQCi5pKdAcF1t4wDfd74DPOMZwOoqyPOA3/4t4APviyacWD8KMCokns8LB4U6b0kH3BtV3iEW+yKafrbAYChEkaT6ZzGA0rtGQwIIeRGQCSXN5ATWsWaek6v6IMxMk1RvAY5JaXAWKSHgKLQuYOICBawFfh0A0UmzLUATL3QX1ww4vpmWfkAcL83mtexbRLShMOC4ydIs1PBm0PA2fPfWz+Nzb74WZ13yc/iNa9+E/k0Ta9zTSbxnYxk5uXoSXw4bmr3KwE4SV5VySVlmQrJKiLZwAdboVCpKn5HqHr6fggUKNDfFADg7xSSYMy7oEACTzycTigB+VvWqniscEzcEmbbucnusrb+3i8t2ytC0ryEpHOYc+n9E2vVc5Y2D/CkSdfWqll0bhOru09ZiPtoAKhW5qMnZ7J7g0smi3EyaofIyn79/BGpsK2/MQaBmA2r+GDNNoYCRTewWte61ZYSMiHb2FAiu0TYO8P3wh8DjHw9UKqBcFnjpi0Gv/QNW/5B8Ip1sq4xry3bdaCtGXCcBB9sRBlqfsYstvUaNj83mGQwFgOxdngEXefmpzcS3mu0yFQvRjgNGB1quR1hWrV2NXR/nLj5ehhcmX5eAsfMIO3F1el4kbh0jX6S5IuV7G3ytPEDpk9z/o258TapXQDMH2coZ245q6OM/bngf7vjYJ/HfLn81fvFVL0Mmp8egrVYnGGSF/JJqyXUyTZJddWnfkzybGosFULUGzEwBhS6obbtZai+bYwshJlCgxzeNYVlaYiLM4X1Qm3dBnfkEqO6+DvpvnUP6Wq/ApNj4WbSyQTtpYlkmWHfrBrmEprzIMjPn1f+z47YmzheBFgkrXMcWqVG1Yo363rVeqhKPUTbuKToZbzWLcmsWadCEyhVYMaZ3APK+Y/4YW/+ZHNToFvZgnQLBE2obB/gA4H3vA971LuC884CPfxxUzLP7a3kOKC2xcO/yLINW/whU3zBU7zBXBnBV9z0/UlrxOHnY1M0D2EVSWuRj8qzcj1wXqzwIUK0nL9DsGmGB6IkMvbt4eNZHHbpJJbZJSGB1WiVXWgg57u4dUTyRyIolWs2wBBVbN9k8/9tUjUjqn0Ikvu1qcCLWX1pdYv3PTBZqbDumDx/HrVdcjZmHHsFlN1yLs3/p6Z2NSWsn0NHzibEhrVirlHcKA4fVCY7/ScyxXOK6dc061NAokPF1XmAxZgWeSP+pXgUduAd04B5gcBzenouBgRGo2DO0xlL+ElrEj5bF3bXarF/all/su5MJeM5zsT0csUZ6P2bPM5V8zRaWsVxHA2OdlXuoXtWkpQoDYxgweUV7j0xsUeoOPgpgpDBk+bSFaaBS4vscGIUaGgdlMswwXTiuvVf9THDKZs09xq4pVrq/dhrMz0rbWMBXqQCf+ATw1KcCe/bwCxvYrMlA04hXmG5cWgStLHBxykwWGNoENTEJJQK02Xxk5dhN639Ss64X9BpQXuYdYBjw4p3v4h1Xhl82lZTO4Kq2ADBEABMrdHakknwvi4jRgLQsL0nON4SYDh+hcXXa1sJJdnXGzmlZxSbXEJEr2I0B2osooGNrodNfp2XyTCKZPQw6/jDQOwQ1sgX33PZV3PrGa7H5nD14wU1/jtHJbTrem3SvPjjGeALx1XUs4OwyDLmQ7eIsF+sdGGMqvKbsU6A1QusVHsZCL3seWixqxK3XNqxUCpqggw9wZYhMFuqsJ/I8sF2rJk0lNHGn+F3ZgGcRYdy43los4ZMFeAbEkkDPuh93TNKYtW6fbbZn0vf6ukSkWahldp+KK1VvoJWf4QT4rh4GxkwuAtZ1AqMR5V6eY6uwqwdqaAJU6OZN+hKnsaBvmNc4y8I11xARimz+ZxoENxbwXXEF8N73Al0F4Mgj+kPLv29bUxbLkKA4kXZ5HrQ8yyrsYcCTf2y7JrM0eJed77IYd/r8ANg96YOUp91Tmq5eW9VU6wF+maCAXF4r+mtrR2qXtTDG9HmJ0JITaCu3hKHlrkxxxcl926ovpIFRrKvURclxdQqr040rtiwiFjHIVSdpyY+CtbiKNqOHWAWGR9koaLL82co81PAWNAq9+NL7/gb/9d6b8fTf+x08+/JXI1fsWv+J7disu3Cb5HYngd7LgLxMVPUdBHrkAVCtArV5EmpoHOkldHTeWFDnd6xR42eaK3ZYUTy5ERFw7BGOA5ZXoHZfCLX1dLYGCB0mWVv3eCLu38TPrY1Sy7Epn7kxPbelAV+a1ccHR79LPD7le9PNhE1HSCa1xbhPm3UQET//TI7rNBa743MeWBMYY6Lc1TK7QPtHQD39wMo8sLrIYgq6ZJN9XnNm0Sr+GasksbGA74MfBF7zGmDPWZzALk3ILfInAEOysCucx3z7xC6ElXlmVHX1AsVe0OwRUGkBystA9Q6x/FChWxwfLV0iSfSu13QttQy/ZES8+6OAgTFbAKvbOxPeTsxd0/2p4scJ8ChEtHL3+KTzSd5dksXo2a5OF2ht9qU+t68tXZAlIZfS/ExU86+h3UaygMUmvM6F9LO86Ddryfciyi2K4gVw6xXQ8YPsPhzbgcWlCj77lutx4JvfxfP/4ko8/jeeu8YC717Ldte1b8aqk1avsvBzjolPrWdZA0CUBwpCoLEaSYMVelkazM6NSxKudjY65ioUgmaPgg7cC8weBSbPhbf7/ITSSJ002Ri5Frvznpv8PsTfn44uIZtaGT3bHZnsto1AaC0wS2hpm0P7Jydp2TQWvgBjvcpuTqWtxUIPS8AZDWDrXUyI7RlR7pUF7mN3P1ucpUXedHX3Q/UO6NJmiJ/H15tmFwRrWmAgFi7a2G1jAR8AHDwIjI/zQiKFXk0StYomfywx1QEUuyyRKJhoSjGqq8ZCo/kp0MEfMkD2j0D1jQD9Om6YzcVjJSalQSvhCwgoxQtWSb+IeZ1jmOcXOcovdCex/Nt5PG6JpNRkdrfZVpicV63xmx9zsy1AUdpx3Z0tTcYmLfZonXp1geN/+SLU+A7s++b38OnXX4mekWFc9q7rsPnsM/TPVRSPowSrzpcyTwmg7udAQV2zdxvsPcjlOQaTyQO9/VAue9UWQGi5t5SFXO4p0Pmq9WrHVmDMlekkmNPqMujBu0EHfwS1aSfUnot4oe24Wf0Ur0Voz791gpyc094Qms/ca6a9v2SjfMo7JfOh3aYmCTTtPkhXfnzzh5oNK65YBoIABGICX64A1dVjWMHxe1FmyIwotzBYu7p5TSNit2ihC7ExUApKC+6Hq0vGM6HyPbrwMreVFY48fec7wMgI8NKXAuecs/Y93XnnnXj5y1+O+++/H3v27MFHPvIRXHDBBQCAT3ziE7j88suRz+fxt3/7t3jGM54BAHjwwQfx0pe+FLfffjv8kwDAGwv43vQm4MYbgbPOAr78ZWB4KEo9cKsYwAOkfpi9yNiMOBF1TipLZEmWsYbkIgPh8jy7EZoNYHAcasvpUP0j/OJlC1At+p/spqSm7l+jzvHCeoXPn80DxX5Ouvd8wM+xFqOt3GK7HhNp1JY70g5ii+qLxCpTJ6mKp1HY7tHURUZptRzt6nPrGCYtSpLfR451qvQ1paiwcaG6C6ZeWNcExui6LH92HLRwDOgfQdg3jjv+7lP41z+/CRe96FL86ltfh2J/X3sLwGkGSGxLvdngRSG1jlzaIt3u8xTQUEpbgeWIdVno0VagnE3/rtnQG4ownmAOwM7jo3oV9PD9oAfvAvqG4Z3zFE2EWUd7tAzNGFHFHpe1zumMT+wdTwM+c1Hrj3bXaQeC7vl+MksqyXtXqwD1Mq8xYcDzLFeAynVFifyx34VAaQlYXQYyGZCfg2rW+P3p7Y/CDwlN5bqBbBa33w4897m8VK6usjGYywEvfjHwN3+T7jmt1+vYvXs3Xvva1+IP//AP8aEPfQg33ngj9u3bB8/zsGvXLnzrW9/C9773PbzpTW/CvffeCwB47nOfi6uuugoXX3zxSRm7jQN8x45xwnq9Dspmgf/1ZuDy1wFK6/iZ7Q1ggA2AYd3Z1o678CY22x2iLQwiHfj3mfiyPMfFRJfngLAJNbKFY4ZVVrBXuQJQ7InygGzFD+VzPqLQ2esVBsV8kV0T4rrUgrWtTDwVvdASy3OD+K72ovsd0JpLJzErRa3FcZPidhIsV0pbyu0qoatIgDeJ7SiWaBjoWGWR/91OA1Sq3QdpblbF8mdBwPJnpXmokS0o1RS+cP27cNe/3oZfv/5/4Sn/8yXwmrWE6ygm0MhGqNngNAPpd7UKDI0ikeYvotNuc3UyzfFJBJX2C2nMCmxUo/xHR+i4UziiIAAd3seVIZSCOufJUOPb14grtgOnNYDAzE+A46jUatklGsEpm4KW5Yxif3S2aUJrH1qAuFMg/Om1SApO5y8KKGZzDHKZrFlDqNng9SzgY5QioHuQpeEAJl7p+52dzWLXud0olVqvWSwC11zDdIykdtttt+F3f/d3cfjwYfNObd++HR/+8Idx4YUX4tJLL8U3vvENVKtVDA0NoVwu4zOf+Qxuu+02fPjDHz5pY3Oi2a0/+dbNOw3U67xL6c4Bh3/EgeJsgS2mnBa2FYV8WUSFTBFjaq21M6PoN0Y5H5AKBUp5LKA8MKYPJy5Tsiwxw24gmwMdegDh0hy7EyS9otgHBYIKtPqFJNMDzAYzuVOa1VhaYqDN5HkHl9OVwGWhT6Nouwm3EmshAkgAyhmHlqRyy+WaNNEpbFPZPGERCupxucjYpXQfPQ2izcXWjYvbmjUA7SqrM3AqIqjx7aC+IdD0QXQT4bfe8VY87WUvwafecBX+74c+ihffeD12XnRh9EvZJDW0FF61AhS6gC6rCGmxJ+E+5QQpN5pmGSemjrRfXJUCSKz1TIHHo7rKv9MpOKlFc5PO5/tQO84CbT8TmD6EcN+doB98FeqsJ0HtOCPlXJ2AogMeym81C4zVRdZvnVPF/uJumhLvCAZMye5r0vGU8Ff3Wq47Oq399EFRKRWtFwnfc6pGVZfXajLTvas70hquls15BPSUUvjQR/WeOKGVy8A73wm8/vXJIcG9e/fivPPOi22kzjvvPOzduxfPetazMDc3h8OHD+MHP/gBzjnnHKysrOBtb3sbvvSlLz3a4Yi1jQN8vb3AbbcBN90E9aQnQb32coBCUKPCkkC1VWB1AeHMQWB1id17Xb0cryh0M70338P+atslmJLKEJXxUa2MTAAxINCKK6rQA/SPRi9ZGPC1gwZbqnNHEd57B7s6u/uZPDOymaWLsjko5UPli+z61P2ioKkVTHQCe2UFmDvKijS5gmGiws/womQKXCrrXjTxoyW2h+jfMVZnkCzIHGvWbwCr9JGc0z3ccqcGAS/QaVac5wOZLgAeu/OCRuT+jKVAaFaoQmvZJeN2U5HbOGQKOLbvYVLT1IPYOtGHN9z2GXz7M/+CD/7W7+PsZ/w8Lr36CvT25PndmT4CyuShxjdD9WQTOqurEyQudCmbK3HpkWulR5UOWixtZ6xIXKwiH5bJMptYE1RIqmWszDIw5rp0WkRnTSkFjG+HP74dtDgD2n8Xwvu+zoowp5/PqUCdNHGxy6bLFDR2XfYdAEXHFlanLsn1/mY9x/0UWyfjpBQU2gCjUghyBSgiEBGoUeck+2oVX/nyTlQq6adeXWUH3ZYtrd+VSiX09/fHPuvv78fKygo8z8MHPvABvOAFL0A+n8fNN9+Mq6++Gq95zWtw991347rrrkMul8ONN96Ic889d+17bNM2DvABwBlnAOeeCzz5yUYTU2ULQG+GdfgscKIw5KTTyipQWUZ4aB9QXmT1iTGrphaByQ+ZXHQdzwd8sRbtXCk/Eq0WV6TkMzXrvJj7Ge1+YwKDKU6a96E27wI27+L3srLCaRVzUwgP3APUa1CTe9hVKm7Irl4GaiFDQAE9Q6DeoSjFoVEDFqeBZgPUMwh09QA1MvFLZcDbTkoGmKGpIhepAKTkiBlgD6P+yG/I/Y1tSZIFUM4mQfoLaD3TKGcs1iTBHYgmMQUao7X1rfRxoocaMBOuNUeQdPyXooRj5QG9Q0DPANdPO3AXnvTUPXjcJ9+Nf//wJ3D9xf8Nz778Vbjk1a9AZvMk30UgMmzulNFJ/iElbHGJNyuy2JuYoMjiNSOyklIwBZNJPz9hAetrE7xovCS/U2s1KuNq5jFVfgbwiqBMni3WygpQXmIQzBahMpq9Gzb19fQGQrbyEhcMA6jeIagnPJNLIz14N8L//N/s/txzESvCEPF1fd/6eyaaO54fxcyjyZT415QPnK87hu/0jzsx2jo6fwdu6XaeYPfnJ9yP9NN2cnzS156nON80X2CJulweqncAPT3tzx4EQFdK1lBPTw+Wl5djny0vL6O3lwlVz3zmM/HMZz4TAHDXXXfhu9/9Lm644QZMTk7ijjvuwKFDh/CKV7wC3/zmN9vfwxpt48T4AOBlLwM+/nGeYLNTEYXbDWDbC6+J6VHk866ugqornIKQL0L1DQO5Aqi0wOa9n+Fk04KICAMmuVzAQhYo+3pGhFo3UeeQxcDE5qwK8TouRkGTLdfSIh/XNwzVN8KkjOV57lPPAFuK4puXWFkYMCM1aLDGoxT99HzOX2zUIh3RTJYXRUMosVilnuN+Eoaj5BkayrxeuMUN6RbzlWbn+AnTz+z4neNbjvVagcSQlPTzFjk0ub6JQer/CTHIBheAtRI14NOB+9mFnvE5/WF0G44dncOtf3otFg4fxWXvvBpn/eIvxBdbc/4QLW5YA9SIyFX2b+x+mnuyLSFrAwEAStdbkE1WU99PNmuV31LWb60NjpBXNOBSYGmE+rqWohSBtWPgxkLTfY59x5XH6aH7QAfuBnqG4J37FGY7G+KVbK7sZrk7bcv9UcXk7HMj5Zono1EcvNbVtxO6mvWPlPGx703mqa0x3GyCSG+EZJMpx9nN87WnSDPdM9mo1JtSnDTvZ6AoRFgtQ3X14POfJfzPPxpKjPEBwJOeBHzrW8nf3XbbbXjZy16GQ4cOGXfnjh078KEPfQjPfvazrdsm/MIv/ALe+973YtOmTbjwwgtx9OhR1Go1DA4OolwurzWMbdvGAr6//mvgT/4EOHM3cPuX+TOZqFKHzqQqaAahWdzlzZWXAGaxIUk5CAOzU6WFY1wJwPehiv0cl+vu5yKZsTQERAuX52uLSdxQLtMU8XQEm5Ridvm+ATUKAt6pA0DQAB17GPTID4FCgcG6fwRqYJwLeAob0tcvr/KiunAC+KVFJtLkCuz6KnSbY5Xr6mzWdOJ1yi5WXJ0ZrQCRqO/pHq/zhAA+1sq9azlWpNDslBV5hmYCExNg/Gwbcgs4kXz2GGhljvUPq6v8m+5enbTNoE+ri6Djj/AYjG7H3V+6A5/50+uw7fxz8fy3X4WR7Qm+mx9Ti9bW+EbiZCzlJrZT1+98Tgs3xOJ37cwUfUQYgI48yESYMIA672lcbNW1yGJMZP1u2KQW+5LyF4p9YP3emseJzQbdRzNahBMFOLL719JvRBs4sfoDdldTsx7pBRthc4D0b5VsGDyx/P1oI5vJRtXbM5oQt06GLcX6qz+raxnHbB4qkwXVKgh6xnHxkz3cdx9Qc8LrxSLwxS+yuFZSE1bn61//erzyla/EzTffjBtuuAH79u1DLhd53W6++Wbce++9+Mu//Es0m02Mjo7ia1/7Gg4ePIg3vOENhu15om1jAR8ATE1x0kgmkxDDgn6hRCnFslRsMARiL0jLDlxbT9Tk/Cyq6srLpQUWiaWQgbB/jF2meU5FUKKC4KZGSE5fOwV7e3Gw5c9MHKfOlqE+Hy3OMk1/eY5zBMcn4W3dzYzQQMcWswXtYorYlqwIEnB5HAlsF7pZeUb64Oc42d4lYdiVKNq6eKzFTca03UKVSBywnkfaBLaFyJ1SSARodzRFFoaMbxuFEi5/NAuaOQL0DKDZM4L/ev9H8KX3fwTPeOXv4lmvfxVyhULKr9vd29qfk0iBGU9BqFU1MlYuYIJ1F3t/2oxl0v0Gmg7fqGix9m4mhq1jzSQiYOYIK8IszUKd+1RO85Ec2VRiiA2ADgLGDrOtQBtQ1gK/dq7OpPGxgca9nrac7MLSQZPHT/I3tSufGvX4fWqwUkrpFKDIqlICWDZo+dk2qj4nryVuroJmJNWY4TJiXiYDCkNQvQY1MAbleVhZAV75SuBznwPyeXY0bdkC3Hwz8PSnt7/uD37wA7ziFa/AfffdZ/L4LrwwIpXNzs7ikksuwde//nX09THp7x/+4R9w+eWXo1AoxPL7TrRtLOC78krg7W8Hzj4b+MqXgX5N+w+allUHRG47ITXIiyolYhAHPeNWs91tlgtQJp8mU1DYBMrLoPIyuyfLy7zzGtnChJV6hcuKZHghUSaOJTs+bRUJkMgcbAGUpNbib+GFR0S6KyusCzi8mV26S7MAhdyv3sEWUgIBPCZCdxbwFhdpNq+JEZola/rQpp+xOGEHajI2jd8AlRVLTbuWip4xNSoa6MDqF6VlqOExTiQv9kMVe3hxT3rdfU26aUbC2RQ0Of63PAs1ug3zK0189s3X4pHv3YUXvP1KXPBrz47SaB6lyytpp32yrLv2zbx4fHlJrQmbDIC5rnUvwLQ8B9p3F2jqIa4NeNrj4vHzdn2JxXvFOwNniB1QcgAwNoom7iy5vhZgSbX6Zp2BSmp41ivsTpb3z7KmlG8DlAaumLWVY7e5J+Lij62ltQXoiHgsJJ6e74IK9MarexAqlwfV66DVOYAUvMHxlk3owgKwbx8wMADs3p2+R32stY0DfKurQH+/tmYKwNv/DPi9l+svE/0l6c12NcTiK9CgRxyfEXeCmfxkLVAq9pSJQl40KiWeq/kipzPMT4FWFphQ0d2nldz7GUhkd68U4nX67BhIQg5eLLk9QXLMz7C7pVICiCcxzR4FPXwvH983AjU4zoruhSL3zXJ1cjHfCi+AzQazZCvLPOGLvSzOrcueqFyB+xSr9J7SPJ/l2zxfS5HJzjjJraZg1FRgL24R8AtgUGkJOLSf72XzJG9isjmcDOigeoXVX+o1qLFt+NF378Mtb7gKfRNjuOxd12LTWbtP4Kwqsiq0PBW73u18TT4uVrpKmucnbAhOYKFNsaY5pUZ7BPwMg2A2nz6asdgeu6KpWubKEA/tBbacDm/PRZxqtFaX7H+EEWCRvIvmP21Z1Wv83hkdzJp5NxmQdFxb/m4sLo6TK4lnGQDL6UouCWsKtfRQBiCp94+JFttUEUXjBqXd2x6oXjWEr6RNCoVh5Gb9/6RtHOALAmBiApifZ9v6lk8Cv3iJdYCy3Jo2kFHElrObqZguwKYAEhq/PlYHiZkgkYnKGMUo9WIxZiPlE0PUCEFNzWQMQ1B5iYuoLs/pdIseqO4BYHCCAdG33KV2vCVorq2DaViD0JM9H91DUNfBbl5IaGUBmJtiC7G0CLVpF9SW0/mazTrv9HP52JgZ12GdleiNqHdXr44HStK5AM4Jui/bNp1PRAFocQ6YnwaGxzlVRSoKyOJkhLAl7trGNeZn+ZhmLeEYBeS6QCvzoKP7gGwe4eAm/N+P3Yp/e8df4skveSF+9S1vQKFnbfdnbMcdhry50u/pyVlSnLGOaXVGoNTp+DMZTFtBQTMlFmgdnxDbokYd9NC9wIF7OTxw9kW84apVQWETqtANKi3yBgoEqpah+oZAc1Og2aN8vkxOx6DjbkFD8pL/tJ6ksutlxsZGhijNXer+Jn4vsWa8FNZxj4EWBzqeryRpRrkuVoUKm6BqhYX0+4Y02e3/H1DrpG0c4AOAAweAj30MeMITgF/7NX6w4rIwcR5EFl2sqchyk0oFtkyX3RzJMvOZfW5xhwoTSs7hZXQCaMS4ZMmweDI5EViYdnWZaeZlVvFXw5uhhjZpF0SNJ3GhqCtpO7EcmeB2HGKdjVMrtFh3s8709O5+0PQh0PI8VKFoiDTIiD4pX1PijQB4DBp1VoQH2D2aL5raZBH5xjculnQXpseWoZ/heEOtzM+5XAK6ezigoKtkG4uz2UBMS9OweYUhmnEWsPVbSEQhFwudnwL6hrES5vCF62/Cvf/xJfz6NX+KJ7/khfC81gWEFyPt3g6aZgMVP1KDtJs7qVSCpfHjcaOZRVM8CZKWQCG/p7VVdvEFTXaUFHpY2H1pBmg0oAbH2L1eWdWlv3xQucTg5vmgh/cCj/wQIIJ63FOhxndE92GlobSOoIpSO1q+FRc5HCBz4nwxgg21jmlLuaKkY5T5Kt3y+8kupy1AV6vwugEFKhSjVJdmHVSrTalB7AAAIABJREFUcqij92cT7Oy2sYCvVAI+/GHgkkuAC86PJqdRZ7GaqWsnriIr7y6xAKrrrrB2f7JLtN05NkNUcrxkJ+1rlReTkyUxqyQFkgjMCODddWWF3Qu5AlDoBi1O8+JCZFylqtgH5AutItfmOh5bsO69JsXOlLIsVl2Ut1biY6plhMceAg4/wNcY3Qpvy+maDOMxicbPQPIKjWCzdvuiXmUQ7B2McuC8LJRb/86qV2gms9Stq5ah+oeZuLOu0jny3CyXspIJ3+lrr8dGSFMAqNng8kelRajxHXh4/1Hc8rq3AAp48U3XY8eF50Vnb9QiSbdHHbdrY0krn4FZ3sOgyRsRCjkPC56OS5eg8nmgZ5DdXvPHgWaD9Wa7+9k1X61A9fazsMLqMqhW5vSe7j4tf1VhNz2IPQuFHj3XlGPttzYiAuaOMRFm4TjU+b/A4tgdxUtlHtn3rwFNCfjFN5gtVpyZx21AL+37JEJN4sbkx9fI/h8Rb57rFR6/XBGUF71WYqu6XuWwS+8gxyh/hsHObhsL+K67jv8bGQEO/GidP7Z2fkBn1pENVvbENOQXByxNTpmKFkqZaIGOUUjag8smFYtIYhFWP5nmrF2w5WWEmnSBRpXLlgxt4rSGfBefP9sV7eiCIKL6xyjlekeclG7Bfs2YhUQAn2t5DrQ0AyotQXX3QW3axbvJlQUGpd5hduFK9yWXrq7rCWbybK1VSrwwZ3OaFZsBEILmZ4CD+4CBEWDTdqiCJQ+WsNib9JCgluySgtJxRU+7aOvJm5CWWoVrgyNVy6Dpg+w6GtmKb33+i/ina96Oc571DFx6zRXoHRsz12ix7pxz87/0ZsUGtzAAlVdYRSYITLoJaZ1YpRSntfSPAKtLoIVp3vH3DbEFBsXEp3qVzyGVF+pV7fXIxiqGr2dZpECLmdd0ekhXb1w0AQpA+jyjlQXQ/rtARx6E2vMkqMk9kWdjLQA0jNFo9FpAzQY+co4zx5wg6P2EAM+cXTZwVV2+yFMsQp0vWvm1xKIdjTqrSPUM/sxbdmltYwHfV78KPO95wH//DeCv/yrhABWlLniRBWEULeyX3cuw2yYpr84uKeQyDmOX0xNLEqkleN4uncFYIIgsEVnQNH0YChocda25IMGiVYpjKtVVUHnJyLapQje7Sv0saHWJ3ac6FqeskiIdNyOw7ViJVjIzahUTl6Sj+0FH9nM8Z2gCanQrq8l4HlSGc/OYPFPm57KyCJo/anIX1dAEl01RPosLCHDHJOM6eWVTjnNdoGlWeItrEYnno0wetDwLTB0AcgVUCgP4t3d9EN/61OfxnNf9Pp7+Oy+A3zcYPec8qwWZYsj9I6ClWbaoir3MCK6sQvUOMrAVijx+5j3xQZUSx2oyOfYmEAwJRp1w/DShyWZAkuGJkARkRhhCKo7ku/nZGY+J7WZMAP1qGfTQvUyE2XYmvDMfn6ov2dK/mPclBfjMJi/te3Mjyd+5VuSPEfBagW6VgQ7QOsTdkbCDxIorK1yRvdjLbMxTYLdm2zjARwS8+93ArbcCu3bx30dG4rE4O+bVwobUk9dMgBBRWaJszNUWI7XEyAGerkelJzKJKkua6zTFnZKk+xla5xOXpbD3RK7LkHEEcGWiyq6Wz8s1vGr8Wa7Akm3TB7kUSXcfF93tHWLdSj+jZdGsvEbN/mrR3jSLquVWlTgpot8QEbvEFo6B5o4B5WVO9dh6BlArI5w5AszPcPmbzZOcSC5J8BLPE0uwVmbLMJOLNEnXfFmssbclzoKUGGC2AFKZiNwiYy7WhxCCqqtGlJzKS7yr7urhnM+ZI6ClaTNcx6ZLuPXtH8Ty7AJe9I4rcebPXcSx30qJ+9TVbT1/sLUlceETaYmAl2Ahpwlnt2sxlRXLdWirxAiZRUTW6xV+l7p6dWxY+gOYd9YFwGYDdPAB0P47gf5heOc+ld/X9p2zAJCi52r6reL9T7P2EkHP2ezGxsG6/qMEQbL7Vi2xJibAFl2hmxPH7X4GTVB5BaCAQx6nwG7dbeMA3403AlddxfLf2Sywaydw910RUBnFECAGHBJXMjE+mRwdLgCx3WrLl62LQPqJIrZpLHUiOR3BSJqFjaienu0yBSIGqSHoqHjyu9x306oHWCsbNidVVnSV8kmo4U38e63SjmyO4zgxV9B67lcfRgRUK1zZfmEaqn+IrUAQ6NCPQKsrTIQY3QrVOwgoj4HYz7GiTqPK992ocR3EehXo6ddC3pq27mV1/cCmBjhLI1Lip+VlYOE4CzUPTbBltTzHlkXfEN9zrQpamgPyeZaLKy0yWad/jHfTSkU5oZksgzwUMx0p5CWwUWfFn8oKMLodd375m/jMm6/D5BMvwIvecTUGNk90NG7rb49+AY4LFNiLaJvzxkopRZYV14qrR+7lXDcv4m6eXkLfiUJg6mGE++4EKIR3wdPZndt2YU9w38dcnbJ5c76T+5Pvzfvugp59n3hUll8EdNp1qYvCqnxBqykxISUGds06E4wAVpDq7j8Vs3sUbeMA35OexKV+pRUKwD3fBzZvjh9nXkhp9s7fellbGGDK+QzW77x4TMEFLGENGlelHOe4OW0txugCVr+J/+mLG0u7moLASr5P6LPIHhkrNhPf+dqK+O4uOwx5l1kpwVST6OplQs3KAoNQsY/TLrq6ncVHJ/4LIIQBA4H0c+44qz0MT7AFl82zS4+IraS6ljhbnkM49RCweBzo7oc3eY4m9cyAVlcAX0H1DDK7tFbmGGetDNUzwCDmZdi6nD8G5ArwRrcChR7QwnGWJ+sfYZ1TW9CAKCIhaatV1XXytuMCNfcUNvlY/bzaLTlUWeH4HxQavWP44gf/Hl/54N/ima9+OZ71+lcjk01yO3toFxNbd/O8iI28rqasuJEGwRa1mJTf2XNCzyeTF1pbTbEC27hB56YQ7r8LWJyBuuDpUGPb1gBAuzsO8KVaewlgeBJUcczpAQfoVhjosnm2/LMFc08xsKtXeMOmPKieQZ6Hp8DupLSNA3wvehHw+c/rIqBg4Dt0gMXhTLOtKgt8XAtPwCGpLJEASbMRxfkkjtfSHAtIADCmedlwXKZWH0zVBT0p26mUtGsC6AqRZWsDqvQjFv90FikBbh0ronpFj0GTiRSzh9n68TNc3WJok64XyF5aPPxD4PB+qO4eqD1PBJQC1WtAxofyMkxoEdCoVTRTlQk6angL1OhWJmbMHuK0ha5uqPEdUH3DoKMPchJ5rgtqYpKBFPqetVKGIe9UVtgyzBa4AkM2x8dKcvhasUItbEAg7Rqk6B1JBDtxnyfEvpQPLB5nC7C7D/Nl4LNXvh2H7t6LF77japz3K7/c+SIOIO7OPAkWnl3lQs6dZMW4GzZ5b9uOpQuCYasVmO9x1GHS74lKS6AH7wYd3g917lOgtu7WieYd3CNg9Z8QB7gEMHTZxm1BLwGs5X/iYVldBihgoCv0sIfAeu4R2FnAqHxWW+rq5XzFU2B3UtvGAb6pKeDnf57/JOJ8vhe+IHL9CfljLZeE68oQkouSsixNRwJNJokGE0mQDwGmUJOzCLRrypp0NmvS3VVK3ALJ505lmnns5rQnipBDxF0qbmENtESkLR7Jr2sAlTKoVtaSZTmOIxS6QaUFI+OFRo2tw3EGQVqaYQunvMJxxYExeEObuEBweZljEp7P8cWu7hZWa2xa2/cRBKB6WTNaV0DHH2ERgGIvvJ3nMllmdYljHD2DUL7PIyKVCIImg2A2x/G1ZoPdSXnO/1PWNUnGWTY/pN+fXBdUCIDaCAi0aRQGPG5LM1CDE7j/rgdxyxVXYWjrZrz43W/D2K5J3YcUt/oJEVbWAYxC4pINXszF7Xoo3N+6YNHuupFrkcJAW4FlbQX2RZUi2gFgrQJ6+D7Qg/cAO8+Bd/p57VVlALRsThKtvYQ51Q707LimnEtbtlRa4vdHPBz5Yov0WwwcyytMTPMzOvbe10qSO9VOats4wAcAc3OczvC85wGXPD2KtwhIxSahY/0ZF6cV51tzYbCAysxZSpgs1r99H+yyAoxYtkM+MedLYonabk5pOk4XS0nQZB0SK89doJp1BpvSkgEAynUxzb13CCgtIjx+EFiY4pSIYh8wOGpKNLGQdZVz8+S8IXGF5moZtO9uUKOhq3XvhifqOGHAltv0I3zd3mF4Yzs4j49I6xnmoYJmPOE8abfdplEYAqUFUK3C8bdsDnTwh6CFmf/H3nuHSXJVZ+Pvreow3ZNng3YVNmlXEkISkjHIxE+AzY+f4fsINrZBYBNkjMHY/kjGJhkMJgojJBBCYGwRjJDIyJggYzDZgISVpV1t1KaZ2cmdq873x7nn3lPV1WFWK6Ox5z7PPrvbXX3rVrjnPec9icuxbdxiS6sFMMVBvoZGBRLyjYUZFrgja1j5ado6nYWSz0mTd0SeYRDACdGew9iSa56epkYNNLkfqFcRj23Av33qS/iX916BR138bDzt9a9EcbCcmkMUrxM0AkuvuiCqTgCTojYlMKwX1dnTOkqdA8oX2Kjw3wNDXCGmF5UctUD77+bOEGs2IHjIhcwSdPlNYp1uIr2X1R7qci2uCbBURlmc5bXnizDFQd5PYYpJkl/L75bm+N3NFVSg2apl9181Vhbwve1tHOBy0npgV0YenwY5Zy1pekNrsRYcQyl0bP1pbWClrTD5eZrqQJIqTKczSHdyDXxBAJLNlejwLueIQfUa04tL80yZtJh6NcM2RytfBE0e4Eoi9RowUGJqZGiMAaxY9msRv5YzYgMHrq5Wp/gowcJIWpLQzCTM/DFgdIJD7kOuTuOq7xsbFIFkwBABDJJLs0xB5gqcb2YCTsiv1zjnb3g8Gf4O8PMIAiWkM4YxtjRbAMQNG8BDLFSO7mNLcOJkmA2bgLlpUG2RfSXD456uqy3ZNIMSz7c4w/dqcJRBEMbXVW3YttPpnoLLHFRZYMUgzGMBJXzp7Zfhtm99F8/629fjkc9++vLoz+MZmRZeln9LRuDZja7H6XOkgaPtgLbvnBUoEaEDw8oKzB5EBBzeywnxJkBw3mM5WbtXIIxWRLMU2BQIkijMjRq/z/WatejKDHQdUoUc2MURB5Q1alyYYmh8Fex+iWNlAd/PfgY885nAc34XePMb4QHJbiIdbq1f5iyqUKcxpF+8rJJl8jsBDCLeDFnWVtQE1apc3LnGidok3SEGBmGG18CMrWVQmD4Emj0K1xmhNMj0yPAEW2F5VTTWCZJAWYQqd8sEfHxY8KCt8xKTNwFtggfgSMUj9wGH97EVdNoOmHUnAwVFJ4kfUZrLOprUWt5SB9WkzmGrw7iEfGOApVnER/cDc0fZeb9hK4N2ZINMXJk0vW6gs0BNXhvZ6jOgGBgog44dAe26mYNZtp4DM36SrUPJQE6RBdpGlanRfNHm19n+gfkBIJeD9PDrLLQMX2+WfxdWYM8eZdp2eAJ7dh/Fta99C8J8Hhdf9g6ccs5Zy7jePobOSe0UxMULg2dPBBzS55b7a/z19wTBTt9nvIfOCqxxx4zisK0+Y7oCGs0c4YT4+RkED3scsGZjf0pEm3tEAV2zzvmwlUWO9i2WmSrvQq86sIuanAbTanBqwvAE7+1VsPulj5UFfI0Gg9+WLcDGjUgGomTUftSg1uaMBxJ9t6ImC8hGlYMyoqZPHM8V2DIZGgVMCJo9wj6bmcOA4U4AsL4rMzjKVsVA2QWKALB5ehagXDskRacBHfIKyRep1knspKjdNjrGqND0FHCnBJDbpK0WXO5aum6i9LpLKxGu/2Bg11j3ZeSEgqbYV8Q3WlC6x+DX0WwwfVlbYt/i8Bq2PGcO87MfHGWL0Vb5N5LOAFiLOjtFhWD43jXr3iqPWqxwzE8DQ2Mw4yfZXLwpTryf2GB9v/YeRxHnT9Yq7OO0dSqdspVbTg81BcytJoPfwjHQ+Mn44VduxJff8l487GlPxrPe9lcojY70OWc/5zTKchNr3bSn1KTZjm75sfqdA5KWVOYyOvgxOwyKbeH4+hLvtdIQ94vsghu0NM+BMId2c2/AjVt7PBvbLUOnDSzNJnx0KJbQrRyb30cNThdqtdgaHBq3YKfepdXxSx8rB/iaTeDCC7n5ExHoW98ELngYC1hVn5DIttAI80xLVOaBhRmOlGo2eJOHoS9wPDzOgq9Y9gI/ksavLOgJBiYwHpgccNntboxNAM+xtaO14JayHLvl/mgL1Rje5AJUccRC3QkgmWOZ1oDh5HdqNHyqQhiC7tsNIIA5bTswcRLPKg1++8lPbFuDEhAED5gSNKELeGdF4qr2RdRqWIqRuMTV9H3A0hzTvRu28jG1JV5FaZgrmujVSDi/KBpZlxAWQGGO6VgDYP4Y4gN3A1FkUytKXEUllwNG11ma1FqSILYK6xWgVuV6lgNlXkCuCEMZNDagaEP733qVg4NaDVSLY7jh7z6G//jsF/G0N74Gj3vRcxAsuzGp6QFC9uUV4Nal9toswtQ7l2BYUnMmlDCg43vRKxI0NbwVWGUgLA0zFd3FF0iNGmj37aA9t8FsfxjM5oc46tRtQ4r5tNVFUGWemzcXS1wYXvyaHdZGcr8aNQa7OGYf+KCVJ1qBXR0PqrFygO/WW4Ff+zXuyweAXvz7oNe8nLWzms0PyhfYWWxzxlAeYR69YFv0RKpoc77IGl2Y9+2GHFDZnC1HDyHDmhABoDRhE7oGlWwFNX2UaBqo9NzymRZSWZF8rm5oANe/L6Gti69ObbhWkwtHRy1gaYGTyKMWsHYjWyxBkNRk3ZqS1vHyqLaUxQDA+ePE8pN+fEKZ6r9dBZmYLWVjoFMKAIBaLS7V1GqwZp0fAE3uZ2Aslti3N7aeb+vAIAJpO7SMyiUEsECs2SLNxnBprYUZmG3nsp+1UffdOSTnslbh96A0ZH2ILVvHMgeA2KeadT4iYGmWUzeKJRycrOK6v3w7Fo/N4HmXvxNbH/kryXu8XPqzK+Wo5hR/uABj4jf6neyifPVK8O5q+XW/NpcX6HyBtgJRBzOQogh04B7Qzl/ArDsV5ozzLVMBv5/SNKqmP9V9c2BXr4IWpjngqzzMynOhlN3tZXU86MbKAb75eWDzZtD8POfwfehymGf/Fn/XFnrtTDGkuXt3jKuQknpRxS8moKU3fRB6i04EgosS7cMySvsT09QhUTvdGbVskemWB9pOPhr5PAhBMQGH94EO7gZmjrIlt+UsYHTc5rQtQ3C6wtXqOtMRqEJJJXyJvayODsMBnrouoZ6N8cBoAg7wkdqfccTfNersW1k6xqkI4xuAOEI8NwUTx5zQXh4GTADXFcAle2fdE0VNAnzcwgxTpUNj3D/uvl2gyjyCjVu5cwUMUBgCohr/vLZk2yqNsmJWr9j+hUV7O5X1F8fAzBFOyh9dh5u/exM+9/q3Y9uFD8fvXvpWDK9d03WNfY/AKlCZfjw9p1F7J8Nf3iuI5XjegT4GyXtRr7I/WlmBbojFH7f4+KmDoJ2/AIplBA/9NaA83DMQxtGgtSWuy2oCWypsdBXsVuhYOcAHMM356U8D553HQS7dQEqCD1yxagGqfkBKj04CxbSDmESJwgJcOkLUHSe/Ee1aCQcXeFPwn+meg4nr074X4sAMp7GnVusCc4wVdikKTkqdOUuxA9W5TB/N8Q3j2ySJD5cif11xDJLOF7oLBcW2ZqEkZhNgQlBgvA+TiAHlyF6gWEKw8XTOUazMs7+1PGJLRvW51DDPQNXiYB1O5dgHM7oGZmIDaOoQF6Nev8kWqCZXbBoUAXNcNg2Doz7XssCVPKjV5OT3pTk0Byfw9as/i+989Bo8+f++DL/+Zy9FRsT88d9vFxEt+6ML1en2RIbylUmBZs3T7bPlD4pjoMl5gWRsQfRiCa5npkladDQ7Bdp5M6iyiOC8x7SVRHM+u6jFFYBAnIO6Cnb/LcbKAr6bbgJe9jLg6U8HXvVKCyxWACYCWVLJ4fzh8Z1TqBDt4E+nH4hPMV2yDPBVU1yHAfFj6RZG3YpdJxbj5za2G3nUYh/Dvp2gnbdwLczNZwFbzmIaV6xFd+7uFs2JoTqRDZAuGMb4NkUJaxxdlBLbjUIS/6XjRmGAfWnSBzCOOD8wFuo5z5fgfH2ho7gojpnKbFS58n2hBJq+j31to+sQrN/EFlkcLw8M7fvIbXuqnLpydD9o+hCCTWcBpWEWpqUhjmAFOIIxsFT1wgzfl+EJBvnqAnDsMECEqarB597yPhy87U489wPvxEOe8Fj+vRQ0v7/Rn0DyHc6asyfAoYMl2OtdWp7V6sCJYv5Py/Y+lLSIqMkpEYUi2qhMmaOyANp1C2jyAMxDHwWz7hS/BiVXTBDyu5ArtM2xOlbeWFnA9/SnA1/+Mm/KqUNMecrQ9RUTGzfKyJMznuYU/54Mir1fLmqibbMmju1E8agN7FINjPpN+vAMCtOE3m8kgKjBDoaT02tLHEwxOMph9lJ+LLACX4JrluuDSRxro1PTgJjTVKe1eqQju75XXakwZAtJZfGRWEJC99rgop44RIDrbCHPQCJkXaBS4N8d6/+TNjs0Nw206pxnWCiBpg5wy6A1GxmwCOwnNoFVbLKtba/UkE+vsEUC4j23wBRKMJvP5go3zSanuoQhg6G1AGlpjiNQKwvAwBBuv20frvvLt2Hd1s24+PJ3YvyUjR3u64mgGHtQnUDGeXqBWNb3PXx7AFvscQQDspHSccKnnbDabOAJ6hXeEwNDTPNnWHbUqAG7b+WSaDvO504iYdj+joU5F3i1OlbuWFnA98UvAhdfDDzpScBnPol2MFIWQdsw8O18Yk+TBcrPp9MjdMeHttBuNdoSzzsIP1lnGpTTdQGlzY+lUaRjNd23iymzDaex0Gza8P5CkdflanR2GsanOASm/XjX1UGVLms2kAwGub/+GmNpJ3hLPesYkBd/Tdtg1gJsv0ZXYj7X6UKlvBC8UiTNgePI+xFFITIBB87YuoswhhOYjx1m0Ft7Mnd1mJ/iHE2J+gwCGJNDorGszvs0PqWFrM8QIO6Cfng3aOYogtMfxt/XuCA3cnlO9Zg+CFTm0UKIb1/3DXzjw5/EY1/we3jaG16DXLHQ+R7dHyBMWPBdKEuhmPXn6UAnf2DXU7pvJTUmzCWVFiDTimubxzEjFVbOBoYYvKSObyJoLGJ/7e5bOaf09HOzW2EFOd6HqwC4IsfKAr477gA+/3ngzDOB37KBLTrZPA0i4u8BkAip79vPZ7yl4KjOOANkCMlGtEoLTtQS7WQ9Jmkjkutq1LhtTxxxz7piWWmhWnCoeaVsmuEIQheh2hG0Uv6bNiHVSch1+n8XTV5SGdIglD6DBLcEXknIFG+iKMCwxRWnQLpfSi1fZAu5UfW5kkKbCgjGVimS90qWGoTeym3WEU8dABpVLtOWH2BADHMwI2t95CGRt0Rd9ZvkFRIRUF3iajPD41wo/OC9nF5RKILmj3H6RaOOuRrhi++5Cnd97yf43be8Euc/+7f4mqLIUb3Z8BAAHbtByDufViQ1e9HtXVrOSCk7rtNIwIpPYCnrDnRlP4NkvdK4tdXgCHBbPcU9F/s3AcDkAcS7boEpDcE85BHZzXFXAXBFjpUDfLt3c1BLtcoU5+v/Evi/f66EuoS7owuwaQGjwcaoIBjZ6J00VfgNkgYusR6lWa0AnkQ6ttFCfi1E4E1eW+K0g4EyzOAwC7A0rddGjaprchSuNIdtZgSp6GtD+/W13TYb2p5ucRPmLWhYa6lRz66/2SPggYHeWoAiQAolFkxxy1J+6p71yk/T12QtNvYr1pQFuwx/Upj3VjDIp8VIlw9J2le0OQdbNGywE3GqxeI8gpO3Mm06P81+w8ERtg6DEI5S7jC4wW+NS7ENjwFLc4h3/YIjE8Mcdt15AJ99x5UoDJbwB1e8A+vOOIPX0KhypGnUgnQFWR6ABOqepynzDlRnJx+fenbum9jm0tWroDj23eXRn0XXaTgF0uXQkntGBuASd82azwuUvSb73+4tmp8C7bwFFDUQnN0hEnQVAFfUWDnA94lPcGDL4iIAgM5/GPDdG9sSlJ1GbmlMQ3F26TFJGch6USVZVqIJNdBJOa7lWpCuUgaDCBnD/ppmg53vB3aBFheA4VGYLQ/hcHtZi0SutrSvzvu6EqkVnRfgqV5H92qqU/x1iupsNdrvWyLyr8u5HK2m/XYFvlYCqFmzz8VaxSGnipiuYJS2KAIfLBOpDh3LHvad6VBejE+ZQWHrqFyxJkTJkSAIEbqBdI1oMgDniwAR4iN7YJo1mA3bgDgCVW09UZs3aHrQk0QEqleBw3uB2iKiWgU/vPZL+Monvo5fefJj8cy3vxHFk072uaRhjn3D0gE+jvmZ9OMzdWMZSkN6vbxoLuPXrHEUbqEEYQTub51SB3byTsWxp57bgrg4ipqrw9RsXqD4AttpdapWQPfeApo9ygA4tqY9J3MVAFfEWDnAd+utXLmlUgGVBoCLfxf0mpe5quiuooqAlqQ4CE0S5lnzHxjkii0SBm8Ma9rWQjKSgpCIFLUUZyfKB/DCyVjNPYDXNu2mJoLtRdbySc+tJm+Woq3950DWRh9GMRwd5bRoICF4XKAK3Lnc7xO+SmRYXvrzTlRnB+oSAFzdUPKpG+n1pT+RUnBBzlpEHai4RN+34xe2zqLvGTWbMdx7gC5Wa8ZviLzfWCxvihVQK0A0lh1o1JgtqFcRT+7nmq7jJ9ncsRBmdI29ljwM2q0vilpc/mx+GpVWDl95/0fx8xtuxLP+9Hm48PefCzO6FjR71DbvtWsL87YcmI0obTa52DmxotT+XITpyFB+Mqw/LhcXeSCStJIg59pndYa63s88+U7ZqkwuhSGw29f456h99VIlSZ6rCUCtOjMXrTpHhNp+jloho1YTtPcO0KE9XBFm/WntQLkKgA/qsXKADwD+9V+BD30IuOAC4LWvBfK24PHiDLcGqcyzr2dgGGZwFFQetS1wmt5GUBnLAAAgAElEQVSCa9kq/hKFlyswEBbLvDnrFduVoOk2pxFrSGhMu/Hdi97FgqT5Y6C9dwHVRaanTtnKG6swwBVHZCOKo72XcHetcazw1D6a9DrEWmzWk9aQMTyHO18fVCfQLuhcrUwbEdlsJNcj9wBIAphVOLrq9kL9Ra3MOZc3jtf3tJz5+5hbU9MicCUtI8fBGmwhymoDb0GGOa5K02zArN/EFYuada4eY0LrP+RzUKPK1V8addw3WcFn33wpqnPzeOGH3oWTzz2bE7Hnprj57/QhmMFRoDzEoFcs8fsifutWg/cGxRnRtKIU+nfIPetWk9NE4pijjvvsXN/PffUUqVVkJMo5FLBTlGqiFGDq36QVSg2CNnq6WWVlJLTVYYyAm/VJxsRNkvfdBXPyNphNZ9jiEGoEIVu0qwD4oBorC/je9Cbg7W8Htm8HfvDvQLnkX1hbYomaTaC2AKouArUFBoeBIaYOLY9vAEVBeVqUKPL0ngjqVoubstaXrCXZss1dWwxChRKXRrNls1w5o/kZYHaSX/iJDcDIOIzrcJAWxOr/Voi1JbC74J0UXSP/7ydYx9GtaKcrgzxTXo7qVEWnZY2O6uxBq5rABxNIcWciID/Ayb8A30sRsICd18AVUc6eGAlBqINbWvX+7kGH9ULWe0LHcqxUsSqtAiQ0sFhmLljL8O1pNfj/C8c4+X7NyaDKPKhWRbCGUxuosgAcOwjKFfDz792Cz7/53Tjzfz0Gv3vpW1EaGeaVtRoADFuCwxOguSkGp7F1oMoiR5NGTRX12mJLplYB8pZF4bPxemsVnlfKByYsoSwFpD+lxBMaliaNWzx/yP50Jl/s/e4IdoqWzixJpveh/4wi6RTR5GAY8T+6JREwfQjx7tu4huyOh7VHgkr9WRUYtTp+eWNlAd/EBDAzAwwOAp/5FPDEi/hzF44sNIxx0XLUrANLx2xNz0V+2csjMIPjwNC4q5LhhgO8DpGitvoJSZRfq8lWp1BVrSa3uCnZkOlGlQVQZd6X1BKLLAh58xbLTKnYItIIrZXpaKKm1/z7zb9LC/OOv+tFdWZODme5iD81jrj1kuQdRjZNwG70rlp+OhDCGF/XU7oqZAQEdV6b+l6CW4g6g2O3FBS3vhMEivKu9pVsbinvWDXtjcnRw4giZ+WQgW/lVJkH1StMbR47DDp2CMYEqEcG/3LNV/C9T30B//uNr8bjX3wxgjDFUNjnQEsLnCpTXeCGqSNrQYuzMOPrQY06f1evgGYn+TrCPBdolk7q7n72Av/OVLr7VAK0xAdtFUR/itQ91RR5JxDUgTZdrT91bwBbI7Rm8wIHlRVoj1mY4e7wQQBz1q/aPE91xCoAPijGygK+V7wC+MhHgLVrgZ//BBgZ8S+xK98Fb5GkBZrhMlBceHiRg0sMgNIIFyFuayipN6XRKh4LiMoiaP8u0K0/5mrupz8U5vRzOQHZHieJ8CTBBZLeYCkukrxBsSbzBa7sXhrm42uWeo1b3I5FgNOlTrAWy0ZvaOtnqn5fccw9zVo62tJayLLGvqjE1L1Q6QkEwzlSzRpbjvlCF0pLCZy2eZc7jK11aSlBHVHadV6xksmDLAIgrrdHrvazhhNBoUrBgk75jY4Sj3yeZ6ysQwl0ajYSealkl0gLs8DUflCzgcnd+/C59/0Djuw/ghde/jfYctET+bcZ+WpCXVKjBhMEoMU5G4FqmMocWQM6dhgmsAqGROHK/0tDtqt9Ohm8C41JAGDZglYTFIZchcjYdIYE0MFHZOtuHwngM+Bo3tS7py09B4Ia8JSCl/gbvJ9ddZgMK7BeAd17K6i6iOCsR3AwkQbJVQD8pY6VBXwAcPAgsGYNULQdF1yj1ZZ/uQG4gtJuE5AHxJiFvWt1IkBYXeTfDQyyxTYwZNvc2HJZtSVgZhI0yb4WbNwCM7EeKFqrMci7lkcAVEsi61/rWuUCzvLiB6KPtY8oajEIVhdYuMSKdh0oA+VRXneu4Lsf6LB75f8z6RSDTKpT9wAUgQIAtgkvkJxDwC4hbNSQNItu1tcDMSQSVyz4XhZeGuRzBZtbttyo0QzhnqCLKdOyaFu75P0B/t9CfyZ8R0qo62tsNfnZBQFoaYEDYOIWbvvZ3bjury/FhtM343nvfQOGt+4AzRyxDZCLNnF+lN8lSQmxz1jEBtUqMLk8aG4SdOd/8PWOrIEZWWvfRVtCrFVnpaw4ABQHbeBH4O8QEajVhJFmvxbMjFZoxZqT6xRgM3aWWCnBGviMUdWPMqy7Tv/u9WzsbWZfYN36ApMAR60maN9doGOHEWw/HxiZSNK/qwD4SxkrD/h+/nNgx+lAIedrUAoFmSVsZST8YVZ7TiSdW4d2vcKtYZZmuYN6HAOVJdD0UQ6COXkbzPpTgMER+LJJfUQLZpZTU1GfAFxFCl0Alyyl2shoqSM5Y4kyaxYMw8AH5ERNrvhRsS2c4tiWXipY/+SQDa+PfcSlMXYdOZiA1+telDhi4DUBb/TiICfZS13Q9DV3o/WyypqJ785YsIoa2b89UUPyLxNJ8H1acl1rZC7DGpRgnm4pFYl54Y81oacAe/2OrNIyNwmaPoSmCfDtz34L3/zQx/Ebf/Ji/PrLX4SwWES8OINgaAJU4T1gBkfZlzi8Bq45c8qqJwJbQXOToIVZ7lE3P83vwPAEzNg6B4YUtWCiJkgq2AyUuQi0pgbT6TN674ji4Ordpo7pBnzy+7T/T8zNBAgK+PV+lhRFzHxELWsF5t3TIoqBQ3sQH9oNc+oOmHWnrgLgL3GsLOCrVIAd24G/eA3w4hcAElWmq1/oxHKJfIzT0Y9GBbWEbnOIk5p23gLacwdbgDvOg1l/sg0zX+INPzBkqdFhT41qR7n46uI4qZ3r4453GHWtTssVwAg54CAsJMG1VU/kAJIICunAYC1TCgKYfJGpKYqBygIrAJLfBPB3Q2N8/Y5uEyFkc/HajCm7VtfWKWBaUoNkGwWaefH27xRAElQR8BMx0hafLQvXqvf5W1ljar1Au8XXUaAqOlkL7vSQyF0JjJI90OV+egurBRzdByzNYHahgS9cdg12/ujneMFV78UZ/+uxNpGbbHUaazU2atZXXQAtHIMZWw+qLnBkqNCwChBdCs/CNOL5GQbC+WleV3kYGF0PMzJuixXYvTowyFR/0UZDUgyTcGfINZukgtgJ+HQAWCc/nzybLBq0gw+y07OTWq9oWl9gcTB5T6YPI953F8yak2BO3ZGMBDU2YG4VAB/QsbKADwB+9jPgjB1A0Vb1cJpc6MEgEbFokNyFySFCAFHLhuPDJvQyNWRk3iBgwKhXgMocFw2uLfmGt0NjwOA4++D0cFRsM3n+tOXX02Iw6r8ZxzpNOO2fyJo2FUwCJPOOiEBR05bwsgImjhi/XWpIg6uT5Ivc2SDMcyDE0qz18YSeNi4P2+g/C9RSqcMqHpmkY5hn+pVa7fduOf47CcARy7nT6IPWyhzaMj3uBHp4pcBR9ssZ2gJUYGlSlnrUAjXrzFw0bSeDMMd+78n9QHUBu+6dwrVvei8G14zjRVdfhtEN6xQAAK5mZhx5QLRzI2ryfLUKzOAId6AocDdzl4yfL8D5DBdnORhkcZbBMGoCYyfBjK7lzhWhKgdXGmE/Wa7I+YX6OoHuFmAC+Ow7kQA4pbS6f2f5+pY/nC8wjhgAtRW4OAfacxtQLMNsOweJijoSlJWWJ6vjhIyVA3zVKvD85wNf+xqwcSNw3XWczycbLt2PzwKXswrlxbcCHBLksjDDFtKw7dYeqFydBJi0a30EAuo1mz6xwCHexRJv2gF26pu2nl1CdyIF0HbNoQSHqN+J1aYBQJLcExrwcTxKRfGQzKWLAgeSYJ6x+TVYWoAnSdSW6M5G3Ue+BoHKmWyCFueAyhxfUxhykFFpmP1AceyDgCRytK3LtrFlpgJVr1UBXt/3I8MyS16oDzxZxv1kQSrz6ucWeEHdEXBNao64/bv0EAuNYmsFWwANQ1C9BlMcyMjFUz+vLoKO7kMcRfj+v/wEX33PFXjci56L33ztnyFXTLXjccE2FmzkOcURKAhYiQwCzmM9uJMpwLDA5b5G11nWwHZOt4BEjQawyBQpzU8D81M8z/hJnLw/MAQTBvxehDmgPMr7TYFJohejtvCAlMWnAM4BYRcLsNe97zG8FVi3VmDZPQeq10B7bgeiFsyO85OJ/asA+ICMlQN8r3wlcOWVQK3G/5+YAPbsZF9WJo3otzYJMMwdQ7zrduDOn8KsPxU4/TyY08+BKQ8lz6ULX2uKKbDFnwNFM6oIUopjoL4Eqi5x6kSjBhRLvMEHBtmPoTVQNxR16QS3BcdOFFen9IRc0bcKArzFqcudiVIQa0Ep9864+TMtscS97UDntR2j1mY7jksenwuSkQCIBlvHFOY87dqoslWwOMPXPTBoy3oNARRzdKHkVeaKCcXBiO8kCJmqPpEBNeIjBlI5j8cz1/2x+OxdlnvQqDHo2VJkbEmkFTAgS4gTETA/DZo8gMUG4asfvhY3feXr+P0Pvw/nPPkidCopxq9P7O8BkbW0Y44GbVqmoFkD1SrMDojPeWCQi3gPT7DiU/A1M6nVcmCI+WkGxHrVguFaoFRmViZqMpiUhlkZk4pAaeozodD2Arv0e37/LUA+bcTMERGvWSJyoxZo/93A4izM9ocxqEugzCoAntCxcoDvMY8BfvAD918qFoHbfwGsX+8pAtHegoBBaOYo6MgB4PBe0NAYzClbYMZPAgoFG4WZ8xGPJvAJuhL917Zp9MjYQJJmID7DKLK06CywNMsbtlh2nZxRGuKXWoCn30aiWbSmzr9z5coI2akK1loFLMVb43WXRhhshBZsNpJWji6i3BFAjkcoBEhaRYF39LeanI4h0a4E2zJJqtEYXnu+yBZnZZ6DklpNFqjDE0y11SugWhWgiJPoCwOWdoMrd2ey+hamrytNlbUdpiICjeSTpbpGBMri6+Xjy7S0Q1YYpCZl1HIFlvmnVmlx0cyRVXZyXa4vOSiOOfpzbhIHDs7j2rdehqgV4Q+v+SDWbDqVj5FzCOBK0FQ3pUnWbJ8dmYDBsF7lijJVm/PaagBD4946LJY5VxAc/YmlOQuGM1zSrVYBJjbAjEx4BZNiBkJHkVplqC3HNeP/mek29w/w0oMkullo50LJ7+PDexFPH0Sw+SwuMJ4GQJfKtDqOZ6wc4PurvwLe/36gWuXahhPjiK96F2/OagXm1G3A+lNgikVQ1ISpV4HxdTBrNnB4tfStywSxDqMtEtN4UEhvDNHYFT3ofHsxCx6KI97cFZtM32ww+JWG2SLMF9lC0XRnImIzlYsn1qcIwR6BM+4bid60uVtMZFohKzRR+81Iz+Lrn4rQa9ZTEZi9KER1/3oODe6iqUtwC/kSdPp6RShT7LVq66clscjzBZiBYQbHyjwXG2g1mZIrj/BzEMpVlBsR7hINSnF2ZZ3lDInMpCjTcnQgo+lRqXcqAj2LSdDvvMt5lXuRcY/TFmCjxp0lahX89Hu34Atvuwy/8ozfxDPe/GrkS2VebyqgpX2+rHtin59zQcRe8YR0K6lx1aTqIldiqszxfRo/ieuYlm1HhSDgGqBL7DPEwjFu21RbAsbXc9PgYtkquwFQHmFLy+W72vzARFxANyvwxItMkq7xREChDNeSa+Yo6NBumPWbgImTvCvGGCBfWgXA4xwrB/jqdeDRjwZuvpkrt3z1q6DHPpZDhO/4KejWnwAzUywIFuaBwWGYLWfCbN4Bs2k7sOFUnxOkaUXAAohQQXYDJpznYo1B/V42gJqn29Agan9LrToL2xpvbkRNbi5bHmOLsFDiotmurVAnYFIAI8V/JZcwjvg8EoTg8vryLmpv+ZGmvQAtbQ2D/y80rIBkIuE8axpVaBvwQn/ZlVR6CKswDwrybPlKrl6ryRZ6qwUq2ACeOOagpoVjXJ1kZA0naNcqnC4SBJaqs5ViCFaAwRuLCLyy0sXic0AH4r6MzTrPLTS1CWGWS4kSGKiEzejTAiSArauj+1Gr1fEv//gVfP+fvoTnXPa3ePgzn5qkPwWUewULiUWsGRUdfCL+Q4qclUgCjg0LiLVFthCri+zvG1sHMzTO5QNzBU6ZWJwDLc4ACzNMk1YFDMcZDGH4eZXtc7ONkk0a7BL77oEBP0CsQFvOT5gMY4CledCBe4CRCZiTNrOiISzXKgAue6wc4LvmGuCP/5i7M4QhsO00xC97FgPctrNhtjwEOInBjQjctXzfLtDee0B77waOHQVO2QqzaTuD4bazYcbWKcBTg2K2xtIlyzTo6cTyBPVoNepEqL/e0Ehqkuq31GzYQBnrI4wjHygzMGTLq+loUAloUUAk1VSM4Q1Ur/LXlurpuDXS1eSjVkZx66xAi/Tox8rTh3fwz4Y2cCcRsJIx8kX4fD8NpEGPdXZdlNf4TQDXwV1ZY956VlZYHDsLBbm8C5ai+WNMdQ+NwQxN8M9qi0AU8TEWKMmmlRjrNySxSLN6MvZ1GdaCTI8E0ARewdCHAJ4VaNaBfIGDn+YmgemDODq1hOvf9REcO3AQf/RPH8VJ27egP0BIW4Ga5jbJ1CQXQBMj8Z674CkFiC3uO0j1CluH1QX+bJQDY0x5BCgMMLAszQGLs8D8MQb0WgUYXQszPM4++TD0/sK8lEmz1ZH+C8BPhrMCAbYCjS3BuP9uZodO3e5kiFkFwGWNlQN8f/InwAc/6P5LA0Vg952suQFIWBlamFqAoloNdOBeYN9OBsN99wClQZgtZ/KfTTuAk05OvjNu89m5NcBlRWPqoBJ9XLOuhHIHn0E6mTbI8SatLIAqNpmeyAKhLa9WFJ8A/65TNRU5k78mqPPq/3ehOtuqzljaT3wnktTeK/LRaKUg5ftyWracX4P6Moa2NsQnQsQWXSdhJf7LrJD37B90mMt+LtS3papdAJGwCYENyqoughamuID3yBoGz/kpThofWcOgWF3kqiZlK4gjO1fo8/ZMVopKr5GwAEOOxiRia9fR4GgDXW5/dAiYn8atN+/GdW95H3Y8/lH4nXf/NQYGy13uVTewCDhQDWqPpUHP7a0UhSvXogPO4ogjiZt1UL1mg84sIBaKwOhJCIa57yEFIbA0z8FTCzMMhvUqu0iGxrllWL7Iyqd0mhCK9AEGP74V5HNubacYohg4sIsVpdPOdO8CW7CrANhrrBzg+8pXgN/7PU5iLxaBxz8e+MoXkew3l7KoXHK6+BL8ZqEoAiYPgvbttH/uYar0lC0wm3bAbDqd/x4es3tRNhuQBCtNm5ISmllCyHgrz/lpMiq35PJJoGk27CausX9KNrAxvBlLw0yLUounKpa5mkoYdvAPipYvdFK3oJrj0GzTuVMyJJgojnvTnKGleSjilBEowO3XJ9j3uo06nJKfhzlbEAA2pSQF7OmegQlfUXI4+lJC21sNFlL2eRuprynCXqwaG5mJRg1UW7RCeJD9xQuzXBx6cIwjJVsNtm5yeb5vgaXyhHZFUpVwlp2+v1kpD235bjGoXgUd3Yfm0hJu/NyNuPGqT+C33/Em/NpzfstW++kH8FL3UilyifzBTNDTlqJmVFKgCPWexxGowSXGqF71UdjNGlvkI+s4BzHHBbpho4lp/hgfMzzOObsDZRipRVosWYo0pWQ+AINEwQSAYolvweQBYGkO5rQzVEWdVQDsNlYO8AHApz4FXH01cM45wDvfyb6+RE3JFEXSRrtZrVE2FsiXCLOJt7TnbmDPnaDddzJFWhpkenTTdpgtZzBdmiv6jSmafE+fU6/N3wdF6AJtAhZT1QX2N9WXbHHiHDA4BjM4BpSGubt1urVQp/n7pjozrrPNGtTzdivppUc/1l3KIpUWTkD3qiqB7YaRqO7S5V708k8lnlWH5xbkQSCfvJzLsy+QYrbUcwV4MbkMgM4AEvcvAclWg9+HXAHI5bgzSRxxdZVG1bcbCkOuvmItGWrUGbBEYZTOGl18qkwdzoOO7sXMzBK+cNknsPfmW/BH//RRnPLQM48DBFL3QweW6at1PlJ9jFtUUgZoRRPwVreah6IW76N6jYGxVgHVF1khGVnLLZuKZQadxRku+r1oizUMjfL9LA1zruSArUWq1nWiocdZgVHTdjLJgeamQdOHEJy8jS1TgCnQQskFIK0OHisL+N70JuAd7wA2nQb85IdAaQDtwrBz4robrudde+NYF0XZbHD1Eucr3MlAODPJVuHmM9gi3LwDZtB2UnB0p3Lau7ZCKhI04dgHOKAmCxySm51E65ZIUZ2KQTHTMzVbcLu2xOtRPkKuKpOyxNL+SXW+xDp0BJ58Jukb4otz/fXSwlzov5yKwrMO/ETAir0XmUPTwr2AqddQlpkEeQj9GqeKBIR5flYUJysFJdYFALYAgLxrLpAJfq5MakyBWUJps9/J+3l/qsLIjFGLcx4LNlCHYu56AHBeme38QUsLvPR8EbQ0Z2u5FkC1KgeOiAVlq7DABJD6n5g+iLvv3I/r3no5Npy5A8+74p0ojY5kX28va1BK/yUuIm3Npaw9oAvwye/TgWp2CE2qzkGtFlvSjSr32axXbOuxEifVl0eAVsQRpYszwOIcK2HlEaZJB0dY0SmWbQ6rcSLrRA2KY1styQD5AS5EcGQfgrWnAkN879kHOKBo2v/ZY2UB3/btwK5dwMAA8J0bgXMe2n6MEzYdaEknp5TG2FXgG++PMSGotgTafRdbhfvuAe2/l8Fl65kwW8+C2XIWA2MQ+sRxyaPq6INRmz+dgA6wQ7u26CO9XK6UFhrqGoIc+y0adaBqy6tV53nugUGmwsojTK31TIM4XqoTGdaVWmMiYCUjjy9X9FZaS6dIpIa0JYpTdG4n8M2ixJc77LMkex3cMWORq5CUh+GoyXyJIy918QDHOih69IT4idrZDRKfl6X3jEqW7k/0GVCiDJqdPmqyQtBq8Pz5ItfrLJYYGI7uR1Sr4ntf+Q5u+OAn8bTX/Ske/5IX8PtmkmDTfR3CcKTemwRwBe2TZAEfkFQstKKc+G0GKLp0IftdHNuIbO5ViEaV3wEYmMFh0OA4W86VRfYXVjjQxpSGgNG11jIssWWoUkvuLxyRKMWtJj+TKAIO7QZG13Cyv70HZhUAVxjwfeYzwMtfDjzuccBnPwPWPKMUlQe4F952VoeBirAkBXo96KyENSTzJgfFMTB5qIev8AyYkTE/p1ioYuWl/YLGeOtBhL7LlTLeqk37CCWvzSXk299HDZ66UWXttbrIGn5hwBfcLtuehJrqbNTQFoCSpRzk8vxxurNAulzU/R5poO8DrMWis1GXbDmpOVy3+8AKjVSxawnGIWL/Csg3HZZ2UFK9xQQ9gh063L+ExafPbZkBApItkQSEkvfUzSzRmKk0g3YxZ7ylC1K0NJKfw1hLGF1yAGUN/B5TdQE4ug+Lx2bw5Ss/i9v+7Qd4yTVXYMuFj2BmojBg38ES3/N8Ea7IteRdJiw2Vo6MVlbT1+huQpZVl7r36fucsBgzvssqYOF8hxGcb7ZR5WCkeoX98UQwuRyoPMbRuo0qW4aVBS5RVhoCxtZbZqacaP8kZzmeQXHMPkkTgMIccHgvV7kZ3+Cuy+QGXO/M/2ljZQFferjk7qbvPp2m8txQmrZofKm2RDyn/a3M2VayLPBCVIA3vax6A3RwN7DnHtDeu0B7bQSpzSk0p50OnLzZ9vrzkYwu8q9jVGYny7TPoeoYsk+j4sPv6xWmYwbsBiyWVZ3RtJViP3O9B02qd1+HoUuWNWrd2w2Z0AJKbK1mRc1qS/4BGSx4pBs54hjUrLGwyhdYQQhtQIpLddBRqqJ05ZUlmqIvE8EbncCw93BHxTE/TxOwnwk2zF3P4wJxyAFJP0E5fCI7j9C4OgfQVatJ5r4RxRwlObkf++49hM++40qUx8fwgqvfj6GJcb8yN7f1Uco5ZK1BwArb1EHbbsuWsstzhKPJ2XsdiJsjeSedAmZENtg717bPOoCffN52jzrsR5k/FkDkwhUMiEtcvk1dh4maXNSisgjELZjyKBffKA1xGoOUKTsOMHRWYBSBcnng2BHWrddthDz3/4kAuLKA77rrgOc9D3jiE4DPXWs/TGn3LsHX/qGoHcDEcS8dBHRpsjQ9qUEufT6trdsw47Z0hjhiOuTIfu7Wvm9Xyle4g1MpTtkKU7RNWsUn57oKRL6pbfpaO4Cva/8jAjnxmI0HQSv8KLJVZcQ/2Kgx+JWHnbM+u85ot6HpzQ6/6+Tby6SGU4JGUgZA2XSo8+Vaiyyr/qoJfc5gHDG1F8dML1cX+ZjysM+l6yvVYTlDv7+m/TnJ9amGwCTvtWU7qF7ldIhC0c14/MtJR2/KvwWsiX1JkvLQRxI8xRHo2GHQzBH8x7dvwhfefSWe9Io/xJNefgnCXNj1t4l5AFXyTPZ1i/1wcYurt8gzbjV5/cUBtqLyRc6ttIFsznLVtGtX8AN/517B41BWnCJl91yraZPwWfEkUTDzBZiYbGGERYBiLr03skbVMtVg3t8zJyl2H4SgJS6qb9ad7OYy+aK3OPWa/xsC4soCvmc8A/jSl/hBTB/2Xdj7GiZDsPS4dB1Rli6vJILBTZVOqcigUhUox7UqcO/toF23gfbvAg7uA8pDED+h2XomsHETjBTMFko07ZtIpAuEPsBGA7kEnWRG59kNa0Jb3Jcj+ahZ56LAFdt+qVln/6D0SiuU+FJztv+f0yxVwnk3UEtr3JnBHcc7egkh/5ycld1q+sCFYpm7SIRSA9YCfroDhgQXkbHXLS2yLCAEOYCsQM60vPoHT28dqRB/OVfyk+R16rqgoiwJ8Lt1ROo7iY7WOZUB2p6hSxmQvnhZFKhSDMEFGmjqAKqTR/G1T9yA//jCP+OSaz6M7Y/6VXQqfp09jNqbmr4k9belHuOW78lpwZJ0ik/Usj5YAxQKDiSNMEFhzivSiaiUdEL7/RzkZQs1a75MWwzGG2AAACAASURBVNRkoAIYDJs2DSMIYEbW2HJsJa/cAejlw3VWIMVsfS7MwKw9xae7WACMZydhCgXe6/l2WdtoAN/9LnD0KIddPPKRwKmnnpjb8UCPlQV8t9zC1Vue9Szgz/7Uv8zpqE0Azt+VdlC3JU6r4zW9IkDhPhPfR+g3gQBhTyHGG4bIwEVwuohCEarx8vIK04+tVwKzMRD6K2klaisqi7ph4UlxxM766hyXfYqa7BcsjzgnvXHnSc9rP88VGZjjyJYH63TPAqehJ4A7a+SLDDASPdv2Hqju5HEMEn9Ms+HLxJWGONJRV/QHOqzv/tDNy6M1HSNXXQKoydGVNnCmraSWjv50fkmJMA3gwMtRxp1TFPobMp9dZBxBSqm1KVlOobEAWFkAHd2Hw3vuw/WX/gNaUYRLPn4FRk5at7wlpCof2X/4NfkDe1otHiQFKNmq9CBp/8geC6yimCswSEqEuFYA+g7i6bYwxchI3dIGd3YgAtBqwsQtULMFU8j7pHupoeuuP3sNJHnCRMDsFNc2lhQhZe2ZgWG3P+bnOZvsQx/y4tIYrir5+McDf/M3wIUXHu8F/9eMlQN8U1PARRcB99zD3dCvvRb4zd/0tIZorZ18fOnvBBh1srgMR3mqGpmdqE4NrLpOpgJMkj5czmkPuI4SOrpPAM0YzgNrNkH7dwK77wLtkbzCsi27dqa3CtvoWLu2tuhB+GNkg3aN6kwLeWUptRg4mBrl8lsYGGK/hBTcPi6KpIu11lFYp55JYNgKo8iDh9Wi0agzdVks83tkbLFpA76G9PyhLUQdEwd4aIUhDBnMCTZfUvk4Q+tziuL2ZP2OFp+NxLQWKBp1prV0f7YTMpQl5vxe8v9AWXEqwEWozjYKVCxK8P/jllIOOw8iAuamEE/ux3/+6DZc/84r8aiLfwdPec3Lkcsvp/VOCtQy3+UM4Mv0FadZCP379PpjRa0q2lWBZuJcYYF9+rmCyxtuS8NYDlDqdAuhS+X8zTpMqwUyBmagxC2fyiPJru4ppkAKulMUAfPTMGPrgRz3vySLbmZwDJNTBo9+NLB/PwNd1iiXgY9+FHjOc7K/v/nmm/HiF78Yd9xxBx7ykIfgYx/7GM4//3wAwKc//Wm86lWvQrFYxMc//nE84QlPAADs2rULz3/+8/Hv//7vCMP+6fFOY+UA38UXs4+vaYVIuQTs3802tgzZcI6aAAusqNEuZEQrFi0NxgciiHMdgKOIAqs1G7gQcW/NtPsMiWIGhNoSH2ML4JqEwEFyXVlgHEeu5BkRbATpPbbs2k7rK1Q1SE8/B2ZsrQfeWKIzM8AP8MelqE60bF5eZiFkBTQ2NJqada6KvzjD102xDdse5OoWuTwDYWA3PUXJxrpZgCe5jgmKMQuM4eYhEcTNhlc2pI+Z9el0t+g6rOV+j06Wog0/EeusXuHrtk1jnXKkRxB6IIojnlrefckXFd+lsCKuVJwvUebvLVRhBwt6OpBjOdahi5oWRqO7kJLyZ83Jg/jWdTfiO5+4Hi/86Adw1kWPOQ76Ex2AS77vd75OAGjnSf+zhwglFzDXavvD6SIyn30/g9AyHoWkPzKxjOT/3f+cst3gdItmlf/dqMO0GqB8EWZwjEs9pv15CXaMmE51LgFC1Izwqxetwe23ezHcaZRKwI03Ao96VPLzRqOBHTt24M///M/xspe9DFdddRUuvfRS3HPPPQiCANu2bcOPf/xj/OxnP8PrXvc63HrrrQCApz71qXjTm96EC0+QKblygO/CC4Gf/MT/f2AAuPUm7sYOoF1HOpGX1UkQJj93/+oUlZlV4iwRMdaFqpTf69QHijmvcP+9wL5dDIj7diarzWzaDmw8jZ36mhrKKnDdherk35C1rE3yu0ROJK+TWs1ks1EDoDxqnfNlmERQQ5oWlRQEZASt2Ptn/WgU5PgYSdMAsdVZLPGxOVvkmWADIJQvDkYFv6QUH3km4jMlsiXLdIk5lS7TFjRjlSGXQqFGELIwlOCU6iJr1KVh1rLRYWQyGsZ/1vEZPtAjgxEhANLpJMir7amsTb13GjXQ0f04tm8fPn/5P2H2yBT+8JMfxtjJG06Qpav2GZ8R6GvmbiCYnv/E3H8ShTUBkhFcKTuxtIOQA+B0MY4ulrakW5jqIuJ6Dagv8tylYfYXDgw5OhNR5P9tx9e/GeDZzx/B4mJ/1/HEJzL46fGNb3wDL3zhC3HgwAEHqps2bcJHPvIRXHDBBXjGM56BH/7wh6jVapiYmEClUsH111+Pb3zjG/jIRz7S5x3sPXK9D3mQjGc+E7j1Vq7VmcsBp5wCnLaFv3O5fOplk0APR8XEyZw/rUkHlp4MrAYsfkAnyBQ9KOHr6rwJegpkNbWCZZFUMAwRXJCAsRGJhrzPLysYhk1MJHyP5NdjBsdgzjwfOOM8BkKXV7gLtH8n4h//K1uFp25jH+FpWzmvcHQcGkAT15lYA1xYNgNBTv2GMiJKeU4Thlz7cHiCN7I47BePAdV9nGDvqsoMtleV6ZLqwDI1BqI6YOxxxZIr2p0QZ21dG1IzdfteU95tNwWW0kqncCitOfE7Zdm1bL6grX5ihsYyRLASpOIHdikTxisx8ixMAEAKbaePkecXZv9frEYXuRkD0j6pE9Up76GjPZH8d2AACjhsn2IrSPPIsngBgikMwJy6A2vG1uOSv12Pu356Oz7wf56Lc///X8f/fsOrkS8WcP8GJf5yp3YfdgLBtKUo86Svg1J/H/8wonCFScq30wpJIl2bde+jpJhXYp+rCXMMkvkiUCwjUIyWpFvEs0e4WPfAMII1620xdH+e935grG/QA7hv+N69wObN/rPbbrsN5513XsKaP++883DbbbfhyU9+Mqanp3HgwAHcdNNNeOhDH4qFhQW87W1vw41pBL2fY+UA32tfyw/0+uuBrVuBK66wwQ/i3wMAn6eWTGyHt5RkBHnVckSNwBZ2bslvA+vHT85JIpiaNRf6j/JIMvpJNLem1MtUFBJF1noQisb+Roozi5WVSVfaH8QRgAh6ApMvAlvOgtl6Nv8+jkDzM6A9d3Jnih9/G/H1V1ur0JZcO+10pksHBj2wRTZJW3KrEpaiaM+KHo1joFltL+JMMQyM3XCDMPnN3DKpMg8sTHN3+un7OMlW+Qi54zYXh3Y+UoDXVVtiUVUocd/CXNH2LWyirbaoNAeWtadbTYkCEgbqe61A5VjzJVgaMUVxO4tPkveV5RPkQJDw+5b1w0Rs2RVLKhlbrUWUHKHrHXUY+fPZ++oCV1zKg12bS+XRxwR+XxjjzxXLGgIkWABReAAPlnJdmpnQ9zLx7yQD4JRK8XPrCkv6FgyNAoMPxVmj6/BX556O737pO3jD2Y/CxZe/C+c+5Ykqt/R4hzpfN5o9sai+P8w+zwM8TBAAQQFAUjnIWqFjGlot984aikFBwArYyBrETW6N5cjAVhNxZR4//o+1y1pXPg/86EdJ4FtcXMTo6GjiuNHRUSwsLCAIAlx55ZX47d/+bRSLRVx99dV485vfjFe84hX4z//8T7z1rW9FoVDApZdeinPOOWdZa0mPlQN8QQC87nVsIT3tN4GxQfYluWEYoGSTy0YXZ7MOsQexRRE3k/RRVr3MACwkcgGDXcR9v1xx2PyA7YwgVJg0fM0KNhEt3GpyIoRJUYeRSgTPymNzPkyTErb2GqImULMCzL64ppCHOeM84MyHASYAxQQc3c9+wv27EP/oX4GZo9Yq5AR7s2k7zPCoEsBot0rJ+qQ6BtXI+u33cQuoL/KGDAz3QBtbz4fVuQchLc4AU/tBYd5Xlw/znJQtCfCFMgIBiDaLTD1jss+5zXq0yoyE40cR6w+JOYxXOtJWnQak9NwuGCAGWjX2NQJMuWrLLiF0AWfpairbBcUYXrPcQ/eZWHx6fenP0la9PI4o9Rvtw0vRewmAPk6BLmBLgVfYOlBzxgTAxAbkRtbgCX+wFr960a/gS1d/Hl/92/fhJZ+8Cms2n3qcgVOdVk+pf1Lm11nn7O0pyrA0+1ld2/E9QDrTks0a9r3RFqUBEjzJ0iyi+WlWfMfXwhSHYPJFNBrLu+dxDFSryc+GhoYwPz+f+Gx+fh7Dw8MAgCc96Ul40pOeBAD4xS9+gZ/+9Kd4z3vegy1btuB73/se9u/fj0suuQQ/+tGPlrWW9Fg5Pj4AOHwY2LYNeONfAX/2iuR3bgMpalD+ry0Wl+vTy1lvnBAiZ6HZHCfLq7tamX2lM+jzK4tBa75pX1nHOVTQgQ7U6JnOAD9/IgHe+gr37QL23WNp0l2q2szpMKdt52ozuQI8HdZhnQmrJ8MHmPbvWC2UpBRYs24fY8z/l/Jq5RHXScDXKVUg5Wg4mVjdJ3ftlLxnAFzQkhP4KT9N+vd6/Sa0X1n6sFkHVRY4MKA8wtGt6XvlUg/EGguTFpkUIJegKwFnAyQKakctOIoy4EAWinUFI7nGDMFOVtFzSlTE55Hybi1r+eYLNsCqCeQs1V+v8TGFAS4/RjGXbqvV1L8rvIRiyTbmZXaF6hW26iXoK8yxclAe5solA7YDQi5nrVGuhUqH92DvLXfis+/6KLY88uF41t++Eflc4EufDZQ5CtYY35KpMMC/P7IPdMeP+XuhZ43xUZWyFwz8d+6PvZeB+r87Rubxx5j0d3qetn/rdQRKMc46hv/OnD/o8Bv9d+bcKUXacDBLXKnAFPJcf7RYAhZnYQZHcdL2NZic7B/8Rka4oc7TnuY/+8Y3voEXvehF2L9/v1MkNm/ejKuuugpPecpT/GtKhMc//vG4/PLLsXHjRlxwwQU4ePAg6vU6xsfHUalU+l5H1lhZwAcAR44AayVqMfIRlq4vH+AEbjoYwEVrKkHZ1lGBfXIkdRujyNOORnqmwQsULUSlzFYumc7gUy40xWZS2qV6oXIFW0JIRXZm+prcZPZvQlsZtjhiS7TVyc9lr9kETNdaqpNaDeC+e0F772Yg1BGklh41286GmVgPF03oantmaaVGNdEkYInrFXKHgJCr1UgFlXzRB+NQzGupzAOVeVBtyZZXKwGlEZ9MH7dUXVMVCRdb/1KzzgKWIr63eVumiWIWiPUKUK0wcEii/kCZ7191kStdLM0DhTwH6QxyR28sznJVkqn7GJDXnAwzto7XN38MNHMUmD/GrWvG1nGR4noVNHMENMVFGMzEBpiJDVy9Y/I+0LFDMIOjMOtOA8bWgKYPgw7v4ci8DZthTtrE5z2wk1sMbdgEc/I2YHYKdOBuEBGCU7YDExtAh/eApg/BjK6FOeV0biF0eB9QKPBvogh0dD8n62/YzDldU4f4WtadDMwdQ1xZQDC2FiiUQDNHWPkZW8vXF8fcpaC6xL0Ah8e5tU+rwbRlrcrvQmmQ8z/zXN2IGnUujdeoeQFMxOkbzQYf12q6vE8yAbAwjXjyAH58w7/jhis/hd96xxtxwTOeym9/OjpRGJ70W6gDsxLbrl+BTm26z3FbwQ/SQRFHmtL8NMzwOKdhmBxe9YZBXHEFJ673M4aGgMnJZOC9RHW+8pWvxEtf+lJcffXVeM973oN77rkHhYKnaq+++mrceuutuOyyy9BqtbBu3Tp8//vfx759+/DqV7/aRXse71hZwPexjwEf+AD347vySmCw7HtSZSWgd4qwMoGvOKK7IBDZIrPztnCurQcoM2VZE/J5mGfB7bR0TcORskqgQBZIlBMzAQd9yHlseyROx4ACFdHW7KUFgc1JCzy122gAjYrXci2NxkWEDRAyEJlimUPnw5y9dulUbbtBkD1PHINqFWDyEDB1FDR1BJg6woJqzTqY8bXAxBrQ6IQNwbeKRmmIyy0Nj8OMTPA9mp0EzRwFzU4CC7P+XuYKMOPrgLH1MBMncRrEzBHQ1EGu03jsCFy+5NAwMDTGbVcGykC1whZDrcJWCMD5ems2cGHeifXcfHR2EjQ3BcxPMygOjcGMrYMZX89Wx+IcaH6G+xzWlviz0bUwoxOsGCzNg+amQNOHgWYNZt2pvNbBMW/tLc3zOofGuORbYcB1AjetBr8rxQG+d0RsTUU2/y2X52cpFpn29xn7Jsrf8m5Lgrq974YUjShWpLynzsds/cWB3jNwyoZ6udv3z4kecm5XB7RzCgTFMTBzGJV99+KGj38Zd/3kZrzkk1dh/elblkd/9sgzVGc8ToD7L7hvJ2wY51JwCnNlzn9dZKV0927g7LPZsO81CgWuNfL+97d/d9NNN+GSSy7B7bff7vL4LrjgAvf91NQULrroIvzgBz/AyAi3VfrUpz6FV73qVRgYGEjk9x33Fa8Y4PvJT4AnPAGoVECFAvA7zwY+fIUHuRYHN5DkbzUbPlih1eIHWhzgmpN5G0CStw1l6xVQteKrqleXuHI64DelWIK2liOIeM7SIAcrlIdYyA2O8Pu+NOuaVdLCDAt4CZxwnSJUtGYQAiPj3D5kdB3n4g2Ns99r7pjNkZsFFmZsoIeyagVI8wUGGPsHQ2MsSCvzbLFU5lko1ys+aEMEaC7HSa7lYbZmSkP8ea3CVlZ1yYK4WNDgaNbZY8DkYdDRg8Dh/cD8LLBuI7DxVJj1J4PWrLMyxnApsKExYHiCS4IFSllxtRdj1xfOFwLwkbFeQQ9ct3oiAJU5jhhdmmMrYqDMxX6HxoCy9a211epUGx7Gl7DS5bmCkM9aXQRV59nqLw+7jg7G+RN1ekEGlS0RvVkRkHzA8e2LtqEsGU3362IGjsIDXDcGAVb9fwC+DJuK6kx3h0jkGt4PgS97QdbYDQBt+bNDt9yG6/7uGqzZthW/8563oFgu9Xkyk2kR2tlTbEynKYw7fEWAnMgKUdK7gX9lHkAAlIcSH7/5zcCllwJLS51/mssBJ58M3HwzMD5+YpZ+osfKAb5rrwUuuQQST0vnn4v4qndzxfzYa7jG+fNIPeic13YBNsisgDD5AmvkJUtvFUqsrhAxeAqYNqpAFHFyaU6FGevNLwIlZ+fMpZNPBfTQ/rmlSpmJtbSg5D+pgrxecKYoW+3zkuTXfqhORwsFPpjEXXunxrJ2SASqMdyoc2Ea8cwUsO8e4OBe0OQRBsPSIFeaOf1smC1nAhtO4+W74ByxZpAUzAQPGNpXq6nmtusJXHg2VRe4S32zwfSlVJUplDvLPP9EvIJj4IWECax/McPH6d4xGzyjW2E5BUXR1y75PJf0+0n6iFC2BLhqIAII2qoWxSkRyCKWoOl8r/oe+vkbf265Zu07zWRb0v/usRYHgMoH2unQ6gLiI/tw87d+gC9e9o942utfhUc8+/8g6Lu6hwbALoCnX5i+LMBfosUnxQu0cnucwUDpQQT89V8D73639SCkxMrwMKdWf/vbDH4P1rFygG9mhinOxUW24K65BnjG0/3m1x3OgSTQWWHAF2rYcmlUGFjKwxxmr18MKQwtJcva/HF2Hve5pd/yxSSgEVm60jr9dbRh1hDQlMot8vtW3Qs9TZfKWrWFIYESMNavaANyZM3yu8wAlYzNqu+jspRI5lD3168h8LO5vMJ7uIv9/p3JGqSb7Z+hUb+uTvdG7rlO5HWb2t7XtEJgQg5Oqlds65c5vi8DgxwoMzjGdGwQctpEo+rna7X4mQ4McdRu1EimyEgAiuthKBHECrw1GKSflXsPlkuhqd+kgpQAUjRn7C24NFhqa1SnLSSAMnWuZQ2liDnr83gAMPZ7pwMAEhEwP436gV345idvwM03/hAv/scPYuOZ2/tMf+hwnXI//Jk6791fBtAFCtwkJ/MEAVyvsWsXe50+8Qmu3ZnPAw9/OPAXf8GVJE9AVbEHdKwc4AMY/D7zGeARj+C7HLV8HzjZyIlcJH5xyQl5KxwCDkIxUk9RhLuAjERvyoZ1rYusZSICDkByg2sKKZVQn44I02XPOvkOs0YmCGeMNud+enMbfz29okmZ1ORAiGbNty3K5TmXrsR+LCNCNfVbAPB1THOgaoV7FO6+A7SbO9lzDdIdMFvOhNl2NqdW5PJWCWkwCOnyaSawlnzon4mkFiQiWJUwsH4t7kVofZmVeV5zoeQiR6UXYXcRkhKIcl6xVCX5W1tD2uJzeZxQwTiBUuIiz1bAJAO4nDJiUgrMcoAqdWyifmiKGpV3Bfr/UO/M8Qh9tW/QY54EAIZABzCjOAJNH8T07bfhc5d/GoWxcTz3/W9HcXBoeXiQADzya8g67gGnOY1Xrn4JAPffdaws4HvDG4D3vhdYtxa45SamJGW4FyKwCj+x1da0wR25PBDkbFQmeYF03MNufqch9zpWhC8AiPASi0B8fakqKE5LJ7SBk7YmEsnFMQvLfAmuNqNElWZerwibwNKz3BOQWg1gadZWbo/5vhXLdk7iKMBc0QtmncPIi1eBE2mqMmkhEgGYOsR5hXvvZlCUfoWbdvg6pGIV9qKYEkDX/j2B+LqEBs0X+TY0agyERJ4aHRxnChxAorejs/bs9btEdQVObc8vy8fXL13mFbmEspJ+j7QSKGkPcQuOgk0Ht7ixzHW45yfVYuL275YNiFlgqJfYJwA2aqDJ/bjz336Az/3dNXjiK/4Qj3res/ukP3tQn139evfH6hOAC3zKimZbVscJHSsL+J74RCaPczng3ruBNRP8uX1BGFOshdC00XOFIpcPA5LCJy0UxQ8oc2RRgZrWEgFH8JvdUZWqH14ccyJyOp1BDy0Ew3yypYjNDfPRoUEHwcK0ngA8JFijlSqhboQGixLrcS+BWNHNBk9vi1Bz2yGtmSd+1fm65Bo6HaupOqWQUL0OOrCbq83svdt2plA1SDefAZx2OgfJSDpF1EjW0rQBMBSEHN26NMPBS7kCB6jY4BmjgFKq1Cd8hCbw5dVKg8wUZF6LWGGwoK+BLlQpNoAriUewnexzAEKAWh5AHb2nwCrhW5Nn0GsLp5QBB4L6PQiUlaerDC1DQdRUfEd/X18Tqd/1AEDJO8wYtDSH1n278W/X3oAfffXf8MKPXoaTH3oWguOp/tLmU89ab18TrQLcg2CsLOC7+27g9a9nEvkFL3AvP0knARfkwpafSW9cp53a/0vPtwTVSHAdEeIWfARbD+FtIwwTVKYLKiEvFEzghWCcRZlCCce4/TyZFFfq930NURRsykSroYA7B9dfL7Eurd3LCHzOodBxbTRvaOfMJ4vgusa1Kd9sWsGQvmjTh20He9uv8NhR35lCrMLhMbZY+Qb6Z+3m5/tn5PvMW2NBIAhBZK3Zyjw35a3MM0iVx2AGOWrUBKGnv6XavvSmE3+hU5QosY5OVqkT/JpSTFh3kfffCQXmgl3En6x+3w8roRWbNqozZUW3pT10mfd+WYFdRh8AyH3mjmLu7tvwxQ9eixZCXHz5uzAwMtw/1nS0zrtdi0mCm3OXrALcg2GsLOADOCNyfBwUGC5ZVrE5d8UykC9ZZ7a1fgLZrJQKLDBJDdwEAGIOUcqkGxXgaMEuwkW07uO5ldqf0Ld/T/wwOS9U0r61XAHe/8Vh+iTz22RzalRZQQhDYGCYK6NYqpOtvpqfL2vTS2V4IAl6OhBFrqvbtSV8ch0PguuzZ8CpJdVFaxXu8s17S2WuMLNuA7DhVGDzWZx8PTAII123dTqDhHerZrWglvLBIvH8iWKb72i7QdQW+ffOIhzmYsAJmsx4MNVKjUTphjnA5Dw1LBYfANcuKEFRdhsZlLL2Lbvglizqs8ucbVSnsub6BbaOaQ/3Ewz7AcCoBZq6D7u//0Nc//5P4MLn/Q4e96KLEeaOo2pj2rdnQt+pfRXgVsRYWcB39dWgP/5j4Jyzga993qcN5Isw2unrcu90cng3DbvDyAKlNt8NJc+jj5ENnQYmAV6ZV4STCBOpSSmbR6qiuHJUQKagMAH/ztK21Gpw/t/SHOfutWzX9MFRvm8mSO3PDAHUD12ZtY70vdP3T987R9+q+UPV0Zqs7yzd9sdahWRCoFkFLc6BKrPAzDFgehI4uI/bNc10sgo7vQcaOGApZwFEu0YVzUkm4HtbmQMtznHxg/wAMDjCeYTFQVbG4ij1nnSj/4y6V3L/SL17ipLURahhPE3fNw2tqU+krLygj7k6MRX90pv6uBMBgJY+FsYgBUBUryA6vBc/vO4GfPdz38TzPvgenHb+Of3Rny5NIEzKgdWx4sbKAr6XvAT093/PtNnkQbZUgJSgVdadC/W1Tn6hh9JCL1dgsHEacexpyLYoRSBzozvQySctGOlyAPTQlO18jvc33BYkkvqCIgyVUz9qJeYimdsBfwr0jb+CtvUnRpbQStFfElUZKqpYgj/SqSUu7DrnLauW+D3Fn6T8fJ2EoBX4lBV0INdpbD1DqfMoVuF+RZGWh2C2nMl/tp7FwGhrXfqcSWVxSRNiuSdp2lINX/1HutOrOqNlLrFmXCCKncc1MA69kqALq4vfMCt3kBfpAVLud8JfnbLC+7HwhAWRyNjArqFfyrLNF43ux/czZ78jK41Df00ELM5iadcduOEj12J2robnffA9KI8Oo2v1Fymcvgp2K36sLOA7dozbET3xicBjHgMnhMRf1JVO07QOtdfolCH+PVcGDXYTmaSl1+bH0nRSp++VJZG2EnuOdj8LiebfqNkalku8xnwRpjTCgRgw8KHzWdaGFTYm9D5PF1CTCozRv0tbtdrScJ/bY3v6mIy3rLRwVQoE2b/RrLMF22oykIys4ZQK8VXq++78heIXA1OVRw6A9twN2nuXiiDdCrN5O8xp2/nvoVE4TSFBa2maPPSAE2cAWRCC4pir7yxZ/6CrMzpsCyaUYYKUINXBJ3p+IJlaQ1ESIN3r1IENgNxbRb26uTsoY1nPKm0JdvX3pZVFTXd2OccJBUDjlcnE1zEwcxT3/eRHuP4Dn8K5T30KLnrpH/SgPw0/v04BTqtjRYyVBXx6UJysY6mtKUdFKMtI+3X0hnVAlEHppC3JDlp+76FBS9F70pgzq0t3vuj60UngBLUaXgAaY2uBNuHSOPJFSVF/6QAAIABJREFUrr2pq7YIiOuAiUTgQmqdWVZUGsR6XquAPJIWdigdy5XAjTOsQ9syhUBcyHphmmuHloZsx4OCslyzhGQ3wWmfhQBXEIBqFdDencDeu0F77uII0vIQzJazwFbhmcDGTdaSbHkrSidldwUM48CXiFQyvQXC0jDTz9Knry2quMv1pJUM6ZeYoON7KVlCvSs6V8C3LZgp414mWAx0OZe+jl5U7wkSS7K2OFYyQe0FEKjVRDx1ADd94Z9x42f+Bc9+71ux5eEP605/rlp/K3qsLOD7wQ+A3/gN4Lm/B1z2PvWFSVpTCV9FevS7qWROeGDUVCTFvpWLdnan/XNx5Dtui0Bpu+UGTGPZCEkpnk0Eqi+xn65qabMgAAZHuT5ooegBIO1w72d09HumBFiWgiAFbSUNRAKIokaHKjpK6CSovMAfA2ItPOu5GcPWqzznhJWSokl1RRUdbCBAm4g+VXPaa6Q4Ao7eZ/MK71HVZrbCbD6D/2w5g32F2qJNtBnSvjixBtt9fBTb1Inaki8MXhpii31wBCgMwiBOUpY6qKoTbanfh7bglth/Dvj71un3rn8hss+ln3Pf9OYJBLeeQ+4VeYscSO5FY0CVBdT37cTXr/4MDh88xvTn+GjSPZCed9X6W5FjZQHfxz/O9TrPOxf4/nf85047BbyGalylEPa1WcETp4BKKM9Q0RvpkmWdfF4CDsYwWLlKMEalM6R6eEhdRvH/uag7Kwi1VZn2B9pjkr3oAi9DEhGpovWD/V3p79z1CNUZ2Jy9vD93S4o6q0o2Dig1WFD2WvuhOI3hjuytBoP7EqcLmMFRYHCMIySz/K3iN3T+LKXZC+WY1Vg4de420HRBJNYitH5Jqi6xJbj7TtCeO5kiLQ1aINwBs3m7rUEaZJxTrExVNzGdemCvg+LIpk5YizBqcMm0gUHfgslhBqnfin8wBeidgpJc6Trya9AA0e2+tfn7OhzXt3XX6bteQ727FNt7EHmFww1lmTsAjOC62aeOxPw0Jm/6KT5/+Sex7TGPxpP+5A8R5HOdAXDV+ltxY2UBXxwD3/wmcMEFwPr1yspQ+WCdLJ90IEpGWyJHn7Zs9wMHbIEXsiKE5VxOq+8mLPQ6FFAEAfvpJL2gbtsIhTkY6wdytJ4uccYTyaKT/w4LnLQv63K+OiWIOuYJdrl3xxXVSS7IJN0nkKKW669nKGbN2VK0Ju07bKNoO61FgVkiVQXeMtI0ZcIiVADoglc6UduGP54+zAEze++2eYWTwGnbYLacBbPV0qSDQyrHTwNx2uJJPU/JI4wJqC1YH+EcvyulYZs6McRl49L3AAYIdXCLAjaDDgpBSpGTgJmuygM6v0uZ15V13eljO4GjUvQoQiInV6JmHQAq4HMUdBqI1bPWSq/Qn3EMOnYYt9/wNXz9k/+Mp7/1ddj6yIcjDJW8SK9x1fpbMWNlAZ8eOkFcWyLGeJCSz7Rl1ZdW22M46ghe801sfFmDjYwTi4vIR162WkCjyhSXrbhiCkWO/iuUlEYec1Ro1ESSmlGWZd8+rgxh2+ab8pZldgqCFSJhLtXAl3xEZ6SS9gG3ZjKGQUD6FIZS2Fu06W7Pw3gw04Cl/ZVxpOhMRefpvCrt8+kInoGP5pQ0GQ2aUmPTBUzY1VeXGAD3MBDSvl1AedDWID0DZsuZwMbNHI2cpkcTa4zVvdZLM6AoSlaViWObojLCuZhBwAW1265NR36qexnHgG6XlHnrtYLXg+qU9WcfYP/udN/hgQwGriAF4P+t6Up379SxGgD1+60/0wDo3oc0ANqVNhto3rcb3/77f8KenQdx8RXvxuD4WGfjbtX6WxFjZQFfrQZc/FzgZX8EPOrX/OcmrYVR+0bOEn6UAoEgBYzpDZywRFRys8yTKyT9e0Rc1Lkyx8KqXuUmqaUhoDTCVl0YIrlFZLMCbeHrzieXEmzd0hKy6K609Ssglha+rgi4Tjmw69KBHV0AixvfRj7i0hYIT5RA0xallF3TFXVEMxdAE4tM3xM5LgvY3WLkHIGzqBxlKsJTW2e6Bqq6ouR9JDW3UfPm+NqP3gfafYcPmknXID3tdJjhUfXM7Xwd/YTJgBdqNpSPcIHncakTI5xD2DG4JWVJGX1sN6qzXxDM2Ifue1UFKMjxUqJIgWzsQVAxJPw5klYegI5UZxr4ugKgVW6yALCygNnbb8aXP/AJrD/3XPzGn78UYT5tbat7tGr9PajHygK+6WluTfTXbwSef7H6QgScWC8i3PLe6hKBlt4org2QeoXjyCeMu+oWCuiApHAwXnAwXrWAWhXU4KRxE+ZsZRlOLjdyfj06hnl3ABcnqOLkRg5C1ji1H7FRgxNwzgpKWRdO4844Vy+aNAE+tv1THHuLNghhBrhjuqsME7dsd3jlj2JuTd2HDMtVR9oadW9EODqfmfJ9iXUOqMCWWN27jHtugmRvFZnbCWRde1NZ3pkJ5HatQQCq1UAHdgF77vE1SMtDyle4A9hwKkzb+6AUM51Ur/x5ROBqO9UFziGsLvGxAoTlERuZKpR5B2ZA3+OuEaEZ7ID+ztG2ymoTX6e8A7p8n4AgwN+JoinHGaDNyksAaB8WX98ASG29dYgAzE1i543fwtf+4cv4/177Z9jx6Ed0Ln69av09aMfKAr70EGGXqInZxfrRwlt3IRYNsdVoz13TUYHa/6M2Fem1pOlBY+tCpgEzzAEQIRQrOUTWchzwGyZqcdh7QlhlWXMCwFCAJl8Z/1sNLHJOfZ/aUi9SvxUrMSw44UCtJkefzk+x8B1eYzuVF9my6xUIkSjWaxTe23M6C0xZVVkUoQBPxwom9vpE4Ooeb84PqAJEgv/X3rcGyVVcaX55q7qqu/qlVgsQBvQWCMRDAoTAMF5AYwgbD/ZMsGMPu4ztADvWxqy9w2wEnt0wYYfDu2uPPAzIJsBmWTMGz3rxhtez+KENFg8QBhbxsAzCIAn0wiCQkOhnVXdV5f7IPJkn8+atqm61HkXnFwFdqro3b2bee/PL75yTJwVs4BTv1xBhULlMrfFdGwI+PrVf4ZuQu7dr8+g25is8TW3gu/BUiFLJU3y8PdynapWwhFCTnvEhZRotj6r71qVNo129EM5kMTT5ErYfgirPU42UbYcmmWavQr1ch9K51QIkaNwTOvtKLmfvo2/mdD7T+0P+vykQXyYBkrk5QIC1Gmpv7cZvfvCP+P3vXsNf/P1/Qs/gAMKL36P6OxbRfsS3dStw8slAscAWmjMzEQ9jh1CEWNfb5XCV1MgMQ/CUDABlwkoSoDKuBpPRd9XgUuxSa+h6B4BSvw7QgBfd2cQ0SIRCJFmv2gHD1J8p24ZkYk6y1wueL2yCbb6Y30S2TtrBhBOipAwqRErS+rxo6QHfYYL1X+r7OiM0E6VIhEOmREZmmeRDpEaKj2W/B9xlDC2ZS7mqZL9RHfm9ItNwVjSpIQE22TDHwvQbAMixEcjd29W6wl3b1WeKIKVsMyeeomocJEPWJmZClgAwOQ6MDkGWh5Ui7ChoIuxX+UypLVkQ2u9J+w0Swfk5W+kdlHV330EANpF3HhCcBBM7uTRqj5s/NSFmmTyNCmyF+HTfGLLPUL88mCrxCHBiHKNbX8JDd9yLnkVLceXNN2abP6P6O6bQXsS3YQPwV38FLFsKbHrSfp8Vjah+tC8FD9DwAzryRT1Iwr58tDMAL9usyYNNTJvrgOgo2jIATXhlrUQJiR2IzYDP1VsTVeQoPKFmohLW30joKNpF7NC/16qMxEIDvWDvfjYxS0hVTmVcJbkuaMIvFK168Ad+nrLMUXP62KaEBjv48eAWR61JmMAT3x+WIi/YPnD8w765lKl9AR2kpJWnGRDd/nFJV6i0c7TEgEeo+m1McrbvaWAm83ldAm+/brPN7NLrCk9erBShJkNRKunrZSld2GuQWX5iXC+fGFZWhUJREWHPHJVnlPzZxmxM91hPyAQjOPrO36OQKz+emJuIzTFxcqLT99QxlWaZPNkEhEyejYiPK9XgXw88sMtb2C5HDmL344/hF/f8BP/iC5/F8kvWIhc0f0b1d6ygvYjvlluA224DerqBXa96P3pqiqs+CozwHecmGMU1ZcmJitqEtTKmfFTlUaCzW60rK/WpgBRu0gSyB+zMOgoWvMBJUIP2wdN1MllqGqlGX1UYkx2rp+9H881bnBSpPwDr96yMQ+YLel1Zn82XStGclCWG1J/EFBQaqYnE/uZEbLL1eSm15hERXzNn2sInPcJej4iNSKFeYwOdX2Vm0iNCB7Q6p7WiGYovNQGT9r57z6DTR4A9RqstWR6D3LEV0GnX5K5tOoJUL65fegZw/EnK/OY/W7zvmZqRItGmUb18ojwMFPVz392vMgOZtYc5awJ0lF8OkMKSPc8t24j0hGhCgszkSb/5hOj7+oLEx5/3RmSXRYD6WaZ60deyDvnOXmx64MfYvOllfHz919E9dwCJn44OiOrvGEB7EV+lAjz4ILB2LbBsmfquzsLjzQyeD1qBB9ibzSsTUFklFp4YB2o1peCKXTrcPmdNQOahZw9+apAUzKTHBrhMRcdeQEp0Tbtn+4vgabDmg2bWS+pfw6gIwC5qF+mlCQDkRBkY2g85vE+RWv9xKltMvqDC5YOqgvUvVz9mwA/541igiVmCQGTGBn1HmXr9T/fA+Likd491+3noeqOoRD84hhIBmIjPmn0W/D72/Y90PT4JSd0vYcme9y3vr7oEQkmqdTullMDbb6joUb2cwuQgXXQqxOIzIBafBtFZYqTkm9Y1gWnyUDtPMJN+ZUQtpu8eALr71RIcR/kxUyUPACIfnoQmS1KNNaQmf/QMct9eyuTZxO/XyNTpTySCarAJ6DmS3j0CIKuTKO/ahl9t+K/oOO4kZf4sZJg/CyWbMCLiiKK9iO+xx4BvfAO48ELgy7fAbPzJZ3OUC5KIw2T84AOlRDpDCuwDLFh6LONslzCZPITQ/hwyseiXwFeQUroLyOklNPvoSWYyYuVkgpUB2Lb6A5m/NIEv8vcVIJsgSBqka2xmrgci4fgHGWnSJrN8QHJUGVN/vgIj/5Zjemb3yYxRjKQ4oRllSMcwdZhJbLoOnNjIZEzt4uqymTmTT7QoiCWkbn3FR+03z5anTPk9Mt9JWw5kNhlSguxKBXLPq8COlyFf+72bg3TJCoilK4HBEyAo6lnAtsmYNK3PTkIoK4jxbY+rAJmeAaDUCyR5pQgpaMWYO8nH55Ge8IiR+pXIk/vkgySoy5Jw/X70TgSJD8gkvFb9fv49IQXMCbA8hrc2PYlffv/HWPupf43ll1yEXD5g/ozq76igfYhvYgIYGADGxoBSCbhzA3DNn+kfAzNoJ4JTz4grZRXmPTas/FSFojLZ9c5VmTC4aa1WVYRFLwaQTUpOQIaw5/M6MdJ1TYueSZCfQyrM+Byr4TqEyACw5Mxny9QO/dJKQC8qVzvYy3wBQmdYEdyx71wvZ0mRX48Tn5TW3+ZEMhLYd05Qi6cSuXnSNyWGFBc3nZKa4YFGfD1gytfLyvAVH8DObaL4uHmPVKgxZ1M/8HMTlWmFvuLmWK6QzWU887qfgcYncFKFEMC+N5VpdMfLkDtfBva/BZyyFGLxCohlZ0IsWArRUXDNjr5fmohQSk2EI4oIJ8tqyUTvXKCzB0gSTYTsHgRJT/eLSbFHijFv+49+N34//dz5vj66B0FTJ5s8BP19WWiBAOk5JXIHVP+MHMAL//OnePax5/Fn//lWdM+dGzZ/RvV3RNE+xDc+DvT3q13Su7qA9d8EPnldxsFCpwKbUIvGx4eV76LQpbKiFDqBzhJER6dj3oOUigAmK6YcZ2CBnkkSqU3bvwfXj8HNlUle1Y+HgU+W3QAWPis3mWFCgzi/vACQqOwp9ZqaAAzvVxOK3gGI3kG9zovUSE0pxMkJ2wdOtv4MdcqDRowfjBEZBw8i4ibP4CPJCTKxSo0PbhRAYogpg5yEcMvg99GpT+i+MmI1CgX2eoFF5u518/ZRcMg3MCmg6Empv+MEwPs1pVR9MhRe2+pMFZbVhr07XtE5SJkqXL4SYskZwMA85dPmpknfjCt04FNZK8Kxd/XGx/2KCIslQAhVjpkYeGZRkVgVbEye0v6bW18c/x4jvlTAiz6HT0pDhJep+qYAM0mDswRC1uuYfHMXHrnzXtR6BnHFv/uciv70+S+qvyOG9iE+APjhD4FbbwXWrAF+8AOgWFQP+GQFsjYJSAlZHlf70smajjbsMuZJ53Fy/EhsMA9a4zlpCf1QEwnU7IAEaFNjp+v458sZjKlSsPcuoAwbkSn3mdGxxhyUt+ZOqnW9pnw15RGIybI6pthlZpjC9EegPgQaiByTXWLroC7ECKDu1otfwxzPVZ9PkAJ27ZhkZdbhREc68wk2iDkRmcysK9k9c8yrfhkesfJ+TpGbd23ym9L3KR9viBADEaqcEMxfj8S4L4wHdAHNydD0p7YkULaZfW+qNYU6itSowqVnQJx6NsT7FqpEBNySYAJYGBHKuk6vNqLzjNaAngEdMdqlWk/Kjk9eHJMnI3siSt8a0IgEDfGxZ6Ch2dM3c/p/W4B57qWTBUZOTuDAC89j4933Y9Wf/0ss/6OLkOT9zE2I6u8IoL2I79VXge98B7j4YsirP6J8DLKu9mw7uFcN9qV+tXC6UIKADKizgCoyPhY2yIUUjV+GIPNUXWeAKbhmNX85A6kMwBsIG4C/5E6d0uZcqwR1qHp5BHL0oFqvlcurfimqrC42QMW/nlKGmf41TibczEl140rL3zoo4RMN7xwqn3Y79wnNmDfr7F55KtKP2jT+NFaYv+kqJ1q/Db5Pkk9GuDnTiT71J1ANFB8nUj8whiYanDQNqQh7fRMcIt1jaDB3FtP7x3hkCNg21Mnnp32Fu18Fdm5Nq8LTV0MsOhXom6PUnIT7nBsy03lGK4wIpVRuhu45QKFT5xiFaxblvj3n3/S7ZKRIbglGdqHlDkGzJ1d40yC7EHigEtsJQo4PY+svfoGnH34KV3/1b3T0Z+Kem8srAozq77CgvYjvtNMgt21Ti9c3PgS5+GRASuWn6yxB0MwRsAMXEYIJ3GCmRVm35gX+4GkVaXZhp/K4wjEbx/oDXBZoECXySvSsTrL96/TvfuYWGvxoQTm9SEZtqQFBkmkuRdjq2gKcrOq2L/K0pVIu/aKlBl5uQgy1mRGKY5r0/Hbc90W+wJS51ldTVC5Tn6TWKNCjUS5Pag8PEmEBTaqN1If6fjiZWzhRc1KVSJNigHBpgHUUHFNofv1DhGjqLO39SBFdYvuGm2Ad0vTITnpk6Kg4CR5AZVTh7u02BympwhWrIJafCXH8SToZN6sX3ad6TQdS1W3C7bF31XF98/Rmw0VtFuVmVVJ/TF366i9l9gTsLuzCfm4Y9KLLy1R/UwSf3GnSllKifuAtPH73vRjP9+CP/+1ntfnTe/+i+jssaC/iW7QIcudO5eP75T9BrLkgewDmLz6kHXDIp5YrqqwV3MQU8qfxmb0ToMCvA68eemZPM1GKWmum8HjUqAQbjNiLya8lyJdZAybG1CJkKVUGjlK/yiZDL3iNmb1CisRXRuY6uj2kKkOKj8+WuamTB4EE2+6TJPddeWRFkxZZs+Vn3XeHdDOIJWiu5P3hqU9ucnUUcEAt+uTmq2NnCQcL1vGJi57hlgmR9VVo+yU6B7C/Zyo/mf6dT/y4yZd8hXteBXZuc3exX3YWxMpzIU5eAnT36vWvwpoAJSPCWpUR4ZBKidc/qDblzetgK76InvyF5v6wf4eIz3EzBD63HOwyTYQIsF7D8LaX8PBd/4Azrr4ayy65EImfuD7JGx9pxMygfYjvjTeAq68Gnn8e6O0F7rsPuOoq9YBXKzpDBJlA2MDAHeSAJZVWHmwTMi3s+YnO8cnNRfTi5DqUUuMpuSbKauG5uS5s5gZDhmzQahZdJvTGrbWq2r9vTGXkF509amf2Yom1s64XvrNtmSgYI2X2I0LTl6Jq0MSBZr7cPOiQEy+zbvtFeATEox3JHMrNo1m+M+4LE4mN2DT3SNp7YgZ9UqbpPkyZFKkMk3askR+PVBMjKJ4azfcj8jb65wbVWd09P3Q9x7zahBB9PyNfcsDD8P3yHPKGNxnjZKjPN/0OrQr3Qu7Wu9jvfEXnIF0GcdYFEEtWQMw7AWbjXjIB62vIulTvjQmWGVJm+r556llP9O4e3LVgXBr6feXqD2DElvWZ3edMn98MgJ4PY4EB5EQZu/75ETz180fxof/w1+gZnBvV32FEexDfxASwciWwY4faxw5Qqu+hnwFr18A8lOZF1udROD+fP5noLo9keISfMcXVkFJ4IdBAzGePZJJ0rgt3IOZBDWaQy7EF5XYglbKuUkuNDqngnUInRFeP+mt8PI2IU7CBU8AJ3vD9CwRuknTMnE1MktQnXB0SuZgBm6knPsBToIuvQIOKy1OFTjvZ/TQ+Ia28/bb4/UT3JWRiDNWbf3b62TPzmrbUM0jRV6tcJfokpwd6xyyZwNkdPYsQzURHMjMmq4Oz8B+uOnXaRBMOT12GiFkIva7wNeUrNDtT9EKceb4ykZ64AOgqWWXH2iIpSIyIcHxYbe/VO6gW5YsEJj9syOxJzyRgf+OfgyTInqnDpQB5nwKojxzEpvvux9BkDpd+7nrkOvIuAUb1NyNoD+J75hngssuA4WH3+099EvjO39t/mxdODwxJzs2CwpUPKZJ80d2WSEq76Jy/HLm8euiktOWYgSakLBpBaH8DmSw1ceY6nBm0lBIYPQg5chCYGAOKJZU9pdCpXgZnlgtGfFRezv2eR5v56krov+oEpKIk6b8cH2hF+gWkcnnC5iDB0KWFW775t64PV4K+WdAcl9i6ZpFjqD0JkSOPqPQUqL/kQHjEZohAD9JkWguRo5TeOT7BhUixFj6PZ3rh/j5Oor5CpP5sSIhUD1Ym4F6Xq3tnDR57Hvy6c5eCvr6UAPbvVYm4dRQpDrwNLF0JcfZaJAuXAXMG1bPutUGSH55Mo+VRoHuOWpqjlwQIbiqW/D2pu/3hmDupT5FBgocB1Ne6j6WUKO95Db++6z4svfJKLLt4LUSSuObPqP4OCe1BfJs2AZdfHiC+vwS+u4GRjrSEljJPMZOPSPS2RHl7bL2uMtfzAdox8fDvtWISbCAhJDmgo4uRTp3toM7UpK9E9MBodjzwIVj2FD6jrtUAaJKnIJUsMuIzdz4YA7Y9KQJk/znRkL4io7+MTM0CckY0jvL11WTNI2SnA8KkIwCHyENkYZQmbxMnR490E97PrK9NkAo731F7rCw/VRsnjKmqRd+H6NzDDDJF4Fqc6Mw5AsqUX3fL9o/j7wE3hRqrRYC4uc/QPIecDBl562srX+FrwK5t1kTaNwCx+v1qgf3x77MJ0blFRPvnZXlMqcHKGNA3qCJG9ebQghOf4+cDIzn+mRHe4TB5+pB1NRnWz5+sVbH36Sfx1D/9X6y7+Sa98ztXfzmVSzWqvymjPYivUgHOOAPYudOmP+rqAjZuBC68QAWkyLpSZEYR5OxAa9KLCZd8GjadzV4NWWnzFx8c6OVJ8m50KI8MJfDQc+ZjUz67GjBRVqHeSaL8GKV+iHze1tX4oGr2JTTvITfLcLDvKULRSQgdiOQ0p/KBlgjK833RuY6fiEgS7kydqicB0MJ7IlNSHaFwfocgmwW3ZClI/pffV7iTAB61Oh1yTKk8Vq4fTeoHsRgSn4JazPLP8XNSvkH9XIQmCtxk6pFSmhDpvkq3HMec6tUtWG9/ogLTZ7JeV6pw93ZNhFuBg/uAM9cgWXk+xEmLgV6deIERqaxV7UbI4yNqHW3foAr66ijoR8WbiJrPTPUdbrXnwzzvjAArY/jd//gJDgxXcclnrlPBL/ydjepvymgP4gOA118Hrr1WmT0HBoDbvg186INsXBeAs5xBmw/84AjuYzKDc04FpeRYFGatql4W4w+gc1gZU3khvEFSAiop9tA7wOgBlfOwb1Cta2KLz21dKswfQDPsDLXBFRkNIgAb0P32c/XGjueBL4mwxE/9HFSWepDLChIx5xgJYa9n6kz3EOx3IkhWB9/XlDLnZvxNBek0IMiZJEdeTkg5krUiZUZlqgkSLatFR5Fz5cdImCZAjr+U2knKzp9M0K3LIESfxCmYhhMqXadehzFXm7IDZG/aXoMsj2tVuB1y1yuKDI8/Ccnq90MsXgEMHq8SaDO1LGt6K63yqFKEsq4CZbp6NWkImAhoehZT5HcESdA8z3XQXoqT+/bi8Xvuw4JLL8eSC851zZ9R/U0J7UN8AFAuA3/yEeCLNwKXXQrzAjk+ANgXO9eh/qOXr1Zlg2pdhUsXvKTStKSB2/v50gRnzR2Q+UKY/ef0MVLvtk0RqFJa/6PgSbHhnJMCOf0F87U1Um3ULj5g0uy8xiYG/kzcr0dDspSWpKgsx7yZsUTBrwtfapFJrGxgArvvPmFxReJfd6YJ0pR9iOTomzRDyjGoaOn8rHMDatGxFmSRIgU/sTaGjnOIlteBWUW4j48/iyaYCepzIwXotMVOcGWtqtcVvgq5a5syj44OQay+RAXNzD9FBc0Yk7OErE7obce0aTRJgN55EF3dNtMTPdNHWwEyVSqlxIEtm/H0T3+FS278NyjN6dPjh0ZUfy2hvYivUgE+/ufAjZ8DLrlEP/w0I2eDYhDsWK5aAB3ZVrWO/NSpbFBJaEE8bIQgJ0ieZxNQM83hdyCH9quQ7J45Ki9mVw/sxq21cN2DM3f2IvCXkSs86g9+DpXHZ/nNSJPP+lNk6RGN08UZZOn7Xf06OYu60bhefEbskJb32SfSTHL02jLTBEntmSo5psyKgrU7oByN8uJKk7erBbUYmqBwsjO+OyqXqWInQpcROz0X9Bxxny38uvlKD+n2Of3gk2Fd7WL/+g7tK9wGuWc7sPA0JGdfALFgGTBnLpDkQH4/WZ2U+7vtAAATwklEQVRQgTLlMWUaLRQgeuYCnSUzARApwjvCCpA9H7JWxcsPPYT9+0dw0V9+AoKbP6P6a4r2Ij4fUupEyjqptEhgNpxNKAqzrvNkspcjNSBzeKor9RsnG9iXjnYrANQMtDIKWSlDyJry/ZGD3R9kTESeNmPmCzrKNEEQIaXEB03uW8kyRQZJ0zvO8Q2y+lIUpK/IDOnUwv5Arvq46conSGcCwwkrpPC875DRZuc6GUSZmiA0IUff/DgTBMmJZDrkyNvP2+ZH1qaUX2Lvd9D8GjCfCv8azNxpVCJTSiGVaO6VhLM/pN+/vO5OIA17Vox/D/Z+svdd1mpqv8I92xUR7tqqmrGKgmZOBDoKEPQOU8RoeVSlRix0KiIs2HW6wnYEjhicNudQHT6Ip/7bD3HKxR/AKavOVGMM9Wuhy8nZG2HRnsQnpbvPHff/CGFfMD6A8pmnCQ7R6OjyljTUdfkTcJze5Feq1xXBUrmywf5+IpQcG3YGzInFUXf6dwoA8TO4OKZEdm5DlcRNWj4xhdQJ1TFLwYXAZvK8fr7ZsdlsNEVYHkGFVB+/vkNQDb5z7gkbpENE6RMcnduIHOmzvtWHTJB0r/h9aZUcQ2ZfXzmmzJe8f2D721eLfMJljs06LqMOzjHURCJE1h5498mcpy/MlwmZiS7rEzpybJj5CrdCvv2GIsGV50KctAjo7gNEooqYqKjJbHlURWl39kD09JvUgkdcW5k2qYQWIzu2Y9NPf4ELr/8UOnt7bJ1EDuiM6s9HexHf/v3A+ecB//FvgL/4uPubr6Ag9GxH6BeVMtBr4hJCz964ybOm/Hu1qi3XRBfCJUyhE0FPllWqsPERtc6uZ0CZM/1s+7Wq3QyWEwJdl8xADqlkqU89MDgmzgwF5kRPAo6J08nr6IEGQT9Vlu+38X1dPmE1M8+m6t/kM9CE3Pk16+k6BBUev1aSvnaIQPn1GpGjM+g2IUf/PkyXIB1y0W2cCjlm1cFRbPo6QVO8pxabHee0Qz8bwXrqa/pqz3/+HAJnk1lTH9Y2dl9kvQa89Qe1rnD3NmUqLfVAnHUBksUrgLnH2Qn0ZAUYH4WsjKh3u6tX5RjNF44sEVI/CAEpJXY++s/Yt/cgzr3moxBJYtVfR6eyOkUAaDfiGxoCrrwC+Pd/DXz4Q3Y2J+BGNzYzPziqxh+Q+XH6ZTQvmd7PbmwIcng/UB5TUZh9g0D3HAieAcUnOz4rZQ+rnV0z5eb7WTj4wNcomwp/wU07YdtL/UQDjX8NHsTC65jyOWHqs8lWyPFIkWZIOTYjUFOOT1wNCNRcqwE5OoraI13/s+RtCRBwM4IEPKINlREgR4f4/fOIXEITBQmr4AKE5/unM0mPrsnVHvstRIhcyZtr6vrz78wx9v7KsRHI3duB3dtV4Mz4KMSylRCnnQMxfwHQ0QEpEojJCjA+rNIIyroiwa7e8JZohwNsTKlPTuC5f/wxTjz/Apx4+mm6Obqfi91MHc9etBfx+ZBSmSMnK/bFoE0rc3lA5DT50F54WhFyguDISLckOckATrJm9UD7j3WIRPms3BtIADZIeuVxU5Szhg2uOTErOMHvLyqjVs02dYbIgQ/6zgANt94hBeoQgPf9VAn0aJOm0wdNTK9+P4UIIUSgfnsPxS/J/Yap/mtCkPyemXst3Tr45AikB9aUKubXgb3/qYlG6Hnk7Uf69yDx0Xme8gaafJekjpH1ulaF25QyfOctiP4BiDPOg1i4HOjuVXOSyYraFqwyrsaJUp9KseaMG4cBhgATjL31Jp7/2c9x3r+6FoUuZpKN6q8NiW/HDmD+CYCQ6cXh/MHl5EZmPUZmBrkOZfI0D7kqV44NAaPvqr/VSaBvLkTvPKCzS4U5pxZzM4jETaJsBhsgRSChfwfBycUfJH2SAZyBxknS7Zs5A4EqU0GwbXzQ99t5FAn0aJEmqaBWTK8psmxiejXt9e5Blro0/eX5JVP9xstrQJCmjrp/UvXwyDFklk/VWf8W8nkHSY8TO2+nbwJlFiGHLD3yS1lOvGfAczvI8VGlCndtg/zDLlX80tMhlp8FDB6vTp2sQJRHVNCMSFRGmWKX6YsZJ0LdXgmBN597BvvefAdnfuiD6lpR/bUZ8W3cCFx5JfCRDwP//QH3t9R2JYlNHG0yt7AZXIDw5NgQMLxfPZxJTs3SCl1AInTiXGaKhGBBLnCjMTMHXubs99N0mbI99aZONHUMDiw8pD3TR4j0bw7JeJ99BdrKMea7aeBYJ9AjTZoS9nlOXT+DQFMmUl4mN5GG+p0THCcXRo6mn/zB0m+7R5ApsiPy8AkP7Fqs//3n3T/OEC7vc++aod9M9QMuAuc7nxD185VBhrIuVQTprlfU2sLyGMTAPIjTVdCMTAQwUYEoj6rlTrm8Ta2mrzdjRKjvRb1Ww5b//XPMX30uBheeoi8jVK7iQudMXa1t0F7E98wzav3eDdcDf/tNmAeYiMSYUcAeSiA9S1Mw36S6QLCZkTc4mnVIsGv6/AGTz5KDoeS51n16VD+fLP1s+inSzCJfaqtPMvRbA5JtdozXf+rjNAi0kZJthmORQMHqcjhJk67N7zHgEZpHUH75KRWo/0eE4fRbA7+k+WwKCfQ/I0jAI1d2GxqSHjs4VBe/T3wzprlEQA061pxWxpXwOAMAcnxMq8KtkAf2Ax0dEEtXQixdAVnoUrlFyT+YLwDd/WzHF/dJmhZkHZBAZehdvPDL/4Nz/vRjyBU67DhX7JlV6q+9iM+HrAeWHUDvTJBXz2Btwq6RAyDpYa5OqswN1UmV3qirFyh2612j+UCoVR0t3OaLd4MvP4c38KXgDQzCGyCcwU//HvQRZpQzU2qsVcwUgWa1/0iq1GOFQP2+nWnSpGOo7FT7A0Tnl2uINzBC8/4L+SWpnc49EMjs25DS4/0TIrCguZP1u6lrSPl599Hvp+B3zSHrda0Kt0K+sRuQEuK4EyFWrILsm6O2HquUAUiIYpcKlGETg2m9yeyZ3v/y73Fg/0Esvfgi3QwBMYvUX3sR309+Anz5y8BFFwLfvcO9+/5OBwSRQObyQHUScvQg8O4+9XupD6K7H+gZgPB3NKjXFWFW9fZD5K+j37g51VdaraQP4wqOB67QTJWSSQv+ksMOIlQOfdnK9w6mSpQz9f000c4q9WgSKPVZiCAOhTQlEL6n1E6lLtJEx+oVtEpI+0dKXQ67R845HuFk1T01+Qwdww/JIMYpq7+pQ/kKXwX2bIccHwO6uiFOOwc4br4iwWoZgIDo7FYZZVj9p/SG6XstZR3bH3kEx5+zGr3zBlU5IgE63/vqr32IT0q1I0OlApRKwN13An/6Uf0jIwiz40ECyLrevXlEPSCd3RCFTqXw8kW7LZGUMPv11avpaztmyRbMibzOUiKYzUQIpNbUtVLmdMFvc8oUljEoms+BY98rhNsuKtXhrxB58TrNAIH65CalyzWmvBZJE2h8P7LqburiR4CyfkipPb9taOE4Xmzod/++0m8IfD8zcFThgX3KF7hgKXDSIptEP5dXRMj8g7pmLVxAtalaKWPrI4/i1Cs/iISy0uSLKvjmPYr2Ir7584G33wY6O4Gf/S/gA3+kXwwVni+1HRsTZbUQPUl06G7BPgg8YGRaTWcvUtbjlTJ7skGAVJwZDLxyfJNP6FpTPuYoomXCnSaxHquEe6yqVCJQDul9OFQCZdWDJHLwL+a32SPNUJtSyKoX2HseIL5GkxNTtB+tzd7XEAE6bTt8MKpw725FfvNOBE5eDOQSoFZVhNVZsgnyWyFCbYF6d8/rGBkawftWnm7OFcUe1KtVYGIUSbH0njGFtg/xAcDLLwN33glceCHwiU+oNXbk46uMQe7/g5oB9Q6q7CnaxOlMl33bfaMNXM1x/DMzTYYCV0gZQoTXM9l/BAaDGTzGQYsEav4c4jHHAlk3JdxDJNajSbghkCKbDslOR6U6BEoX9ggg1V8tECi/Fi+W//XrnDXR5GUHibcJ+QEBAoQt+xgYOo0q3PMq5OgIxJwB4ISTlVWsLiEKRaBY8iZIGU+SlJD1GvY8+yyOO+MsFEuK5OrVKnIdHZBSqv0Mj5VJ9SEg3/yQYwhvvAE88QRksQBcdYW6AcPvQI6PQHT3QcxfrPx1UDMYMgWYZNW0pVCuQy094OnKfKQWjbMF7GSepMTUWWm/jhZSL+QMk6wEADYg1N8DZJ0I9/jQMa2QdYpwp0igKfVzGAiXlFTifW94KMA4DrFS0VQHWnLBltM0U6lk+TB8yZWZroN/zVA/pEgvAylRRm32+xNe3wWWN/jK1C34iEIkCXDCSRAnnGRrQqrwwNuQxS7guBOA3j61RKtQUtlm2LNhH2sBkcvjlPPXoDY5iZ3/72ksXHM+krylidr4EHKlfvPvvXuB114DenqAlSvbhxPbS/GdeCLw5puQpRLkj+6FWHM+0N0HoXc+IMkOwAa7pPYNy7kPtuOfIAWnu0QI2K1VEpYaKWMQ5Mh8AkTwY8PZfLs8TYeCw03Wh+sYB0eYrPm1nGfWG8QlIzHJv+PtmiJBT5VwuSIU3r8d8Dqy78yfZoQnAn0pYVWqDJzGJxoN2tPwWO+8o0SEIRhVuHc3AAEMzAV65wCFLhXzkGN5hTkRSsnmQkJ/JSGKPdj6Wh433QT8+tfK81StAnPmAF/9KnD99Y3r8/zzz+P666/HSy+9hNNPPx333HMPVq1aBQB44IEHcPPNN6NYLOLee+/FZZddBgDYvn07rrvuOjz22GPI8fpOE+1FfGvWQL7wgro5m54GTl2uvqdNZinSkl4KngMTsKTGFwADcGahgJ0RO5DBj5kPeGa3TrGchhDOn8A/2NctELHzz2OgnJlq1yGV0wCRrNPqx1dW5t+azYLE06CuLRGuX0//XnLyS7Gqe82GwyFTxg4Xts8QSpDjo5Cv7wQq40oN9g1AdPUAHQXTf5XhYRR7e53zhBDY8hLw/nX9GBpKN71UAr74ReAb3whfd2JiAsuXL8eXvvQlfP7zn8ddd92F9evXY+vWrUiSBEuWLMFTTz2FZ555BrfccgteeOEFAMBVV12Fr3zlK1i7du2MtL+9iO/tt4ENG4APfABYt04R3kRZ78GnojjVzuc6fZnJasKzo8xguq4jgZki0FhO43IycRiI2PnnESb0kJlOcEWVRQoeo4VUE/8s/XJ8wjtEsk4xK5r0mbTHOH3Q4PlpeWjkfeMzf3vAqMKh/So4ZmAe0NmNgzt3YfzguxC5HDr6+tBz3HH4wJUDeGZzKbN7urqAZ58FVqxI/7Zx40Z8+tOfxp49e4yKXLBgAe6++26sXr0aH/vYx/DEE0+gXC5j7ty5GBsbw4MPPoiNGzfi7rvvnrH2to+Pr1IBPvxh4KWXgG9/G3joZ8D55+ofmUmlrpUfkVu+0Pryg2MRUx4AI6aFY42Ip1xOIAgD8PyvR7I+MzHB0JaX0LUzfeqc5KgqjJB8km1UH+fda6QIWy3z2EXQVygl5i5dCq6Ntm0TePGVbNIDgMlJ4Pbbge9+N/3biy++iLPPPtuQHgCcffbZePHFF3HFFVdg//792LNnD5577jmsXLkSw8PD+PrXv46HH354RtpJaB/ie/RRFdU5Oqr+/c2/BX6s83WSZdJJtiv1ovAaUEsXFxERoXG4TMEhTMfA1NK1pfeXnz/N66bKbrUuh3q9YwNyogx0FCAnJ4GRg8B4Gb/bvAAdHcD4ePZ51Srw9NPh30ZGRtDf3+9819/fj+HhYSRJgjvvvBPXXHMNisUivve97+HWW2/FTTfdhM2bN+NrX/saCoUC1q9fjzPPPPOQ2tY+xDd/vk4bBqBYBBYuBAqlo1uniIiIiGMRLRGvd4yJlFV/BMpAdRJJsRMozgcAlLZ0tHT5zozlfj09PRgaGnK+GxoaQq/2Ja5btw7r1q0DAPz2t7/Fpk2b8K1vfQuLFi3C448/jt27d+OGG27Ak08+2VI9stA+xHfWWcBttwF/93fAOecA/+WbaklCRERERMSMQ9Qq9h86j+clf6xMmY3Q3Q1ce234t5UrV2L9+vUqOlSr582bN+PGG290jpNS4gtf+ALuuOMO7Nu3D7VaDQsXLsT8+fOxefPmQ2kWAOAYWnzWAj7zGWDLFuBHP1ILRyIiIiIiDg+KPcqqVuo3GVt6eoDPflYFsGShowO47rrwb5deeilyuRxuv/12VCoVbNiwAQBw+eWXO8d9//vfx7nnnotVq1ZhcHAQ4+Pj2LJlCx555BEsWbLkkJvWXlGdERERERFHFZOTwEc/Cjz2GDAyYr/v6gIKBeDhh4Hzzss+/7nnnsMNN9yALVu2mHV8q1evNr/v27cPl156KX7zm9+gr68PAHD//ffj5ptvRmdnp7O+b7qIxBcRERERMSXU68CvfgWsX69iDnt6gE9+ErjhBmDevKNdu+aIxBcRERERMavQXj6+iIiIiIiIQ0QkvoiIiIiIWYVIfBERERERswqR+CIiIiIiZhUi8UVEREREzCpE4ouIiIiImFWIxBcRERERMasQiS8iIiIiYlYhEl9ERERExKxCJL6IiIiIiFmFSHwREREREbMKkfgiIiIiImYVIvFFRERERMwqROKLiIiIiJhViMQXERERETGrEIkvIiIiImJWIRJfRERERMSsQiS+iIiIiIhZhUh8ERERERGzCpH4IiIiIiJmFSLxRURERETMKkTii4iIiIiYVYjEFxERERExqxCJLyIiIiJiViESX0RERETErEIkvoiIiIiIWYX/D/HXKr5al5P9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "K = 3\n",
    "snap_plot(nets[K:K+1], size_scale = 1/300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7k+PVQ35Hpgk+9alP4Q1veAP++Z//Gf/0T/+E3XffPXWR90EHHYRvfvObOPTQQ/Hggw/i0ksvxfbbb4+9994bfX19OPDAA/H444+3Vee3v/1tLFq0CH19fbj66qsz1xF2dXXhzDPPxNy5czE4OIivfOUr+O53v4vXve51AIClS5fi4osvxsDAAC677DK8973vxcKFC7H11ltjp512wt57751arlIKX//61zF//nwcfvjhKBaL+OlPf4qbbroJQ0NDmDt3Lj75yU/a6NarrroKo6OjmDt3Lk4++WS8733va9nH/fffH9tvvz3e+ta34qyzzsLb3vY2e2zx4sUIggC77757W2ZTHzvttBPOPPNM7LPPPpgzZw4efvhhLF68uOk1b3nLW7DzzjvbsUzD3LlzMWPGDAwNDeH444/H1VdfjR133BEA8NWvfhWf/vSn0dvbiwsvvHBK2oYhz1mzZmH33XdHHMf40pe+hKGhIcycORO/+MUvMgW+fy0A3HjjjXj66acxNDSEd7/73fjsZz+LAw88sO32ZGHWrFm4/fbbcfnll2PWrFn4whe+gNtvv90ZrxNPPBEnn3wy5s6di8nJSVx55ZUAgB122AHXXXcdPvKRj2BwcBA/+MEP8IMf/AClUgmVSgXnnHMOBgcHMXfuXKxevRqf+9znAACXXXYZbrjhBvT29uKUU05xJkg+2n1vcrx6UNSuHSRHji0Qb3nLW3DcccfhAx/4wKvdFAC8nOGEE07Ac88992o35TWLJUuW4IQTTnjN3LMcrz0UWp+SI8eWiQceeAAPPvggbr311le7KTly5HgZkZs6c+RIwUknnYQDDzwQV1xxhROZmCNHjumP3NSZI0eOHDm2KOQaX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KKQE1+OHDly5NiikBNfjhw5cuTYopATX44cOXLk2KIw/Yjv2WeBKHq1W5EjR44cOaYpphfx/fGPwDbbAB/+EDAxAlQngagK1CMgjgGiV7uFOXLkyJHjNY7Cq92AKWH+fOCAJcCBbwHiCIjr/L1S4iTFn1UABEHyt/xtzsmRI0eOHFscFNE0VJPimDU+xOJLTWZE/DsI4RAcEUBGK6QUQswiyRw5cuTI8feE6aXxAcBXrwIOOgh43Xas8VUnAGgyMxRO5m/icygGggIQFvh3EABQmgjjhBRjcj8D7ZFjTpA5cuTIMW0wvYiPCHj0EWDHfwCG5iSk4+is+gPVtfYHTXghf44qQL3O3wcFIAw1GZZcAjOKsE+OFLOZ1dEgVSMh+mbW3LyaI0eOHK8JTE9TZ2WCCcxAmjMdaFKyfwMNJCUJTAVMkKHWDtsxdxrTKZEOsIndMnPzao4cOXK8pjC9iI8I+MlPgL32AmbMACpjHNFpoZjnUrukmMyARGMLQkGAPlHJMhVrcEGor9kMTY7I1RrTyDHVvJpFkjlB5siRI8fmYHoR37PPAtttB5x9FrD07IR4rHlT/zaanIUCAsUamUEQ6mtivj4sAYUimz0N4ojNonGUaHOmfJhqqbnvT34nr02DY15tQZJp5lVD0Ll5NUeOHDkyMb2IDwDuuB3YdRdgoB82oEUh3UyY2TVNloaMKBb8SUBYBAol/u37/SjW6wbr/JviRHMMhPlUnu9oc1nLK6ag0UnzKsXJGsa2zKspGqRpV44cOXJsAZh+xDcxAXR08ML12iR/Z4kGWoCLLjn+v5Rj9ntz2IaGwn4ZBIAKPVOnJg0iDqSxmqFeWxiEbvCM9SdmmTi9Y0B7mmQzrS61vqmYV32SzMkxR44c0x/Ti/ieegr4H9sDS88Bzl3KhGSWK/gw6/n872TAi0N8xARVLHO5REC9xj+xJia+CAnZCNMqPO3J1GVMpFMJnHE0ujSi9LS6LLNnu6bWdsixmXlVaru5eTVHjhyvcUyv5QwzZgD77QfstmuiZWUhTfhanyAEgRAATUxxBFQiPqdYAoodQKmTz4/rrGVGVU20QVKOCsXyBZVwK8XsWyQdPGOINGlQ4pcz6wsd02fA1zeD7UMKecUeUZoxSCMu25ZCunbnm1dNFGtcByhq07wq+pV1j3LkyJHjFcb00vgM4hiYHIVjttwcOF0n77PQClUgzJYhn1uPEm0wCBMt0RBAUEhMo9I8aogoFkEzjtaqbNVWa/XJydHo/GMtfINpWqMkrQbtboqm1mbm3Ny8miNHjtcAphfxPfss8M53AP/6IeADp7AANX4+C8+P1w7kEAQF1vYoBqJa4rOzZkVdhxXIlGh5NsLTEBGEoPc0O2PulG2gOAmaiev8Y0ykQQAg0KQozaCejxDwSCPL9NnELNnS1CrI0/Q/NUDHqxdI6muHHFuZV/PlHTly5NgMTC9T55NPAg8/Atx5J3DCMcn30oTZVP5lkKIUxsbcGRaBcnfiR6xV2MwpYQS00e6UAhC7fj0lCMuQmd8mSQ7WD1gUddS1ZliDXX8YhnxOGCak0rAcQpKin5LN9w820Sxt3zJMoKkBOjLDTZqWl6LhyXWV0k+aRo713LyaI0eOzcP00vgA4JFHgK3nASUtoAFNMpL82hBuad12IkDl9yGv8VOKCaheReLHoyQhttHY5BIHQzpyiYRpszFzmmucdYJ+W6S2aT4aAlPJ+j2Tnm3KyyJSSNEh0DSibKFZ+veilanV0VybmVq9ehvK3lzzqjTh5siR4+8V04v4brwROPVU4M1vBm65BahNaHOgEX76vzStxH7Xhik0KCYklrU0glK+b/isXOEbGDIImACL5WQhvS1XkKHRaqS50zej2jRpQtP0YQgibXF7GnGl9cm0L4soHY1PEk0aKfqapUeUqZpeC1Nrqg80hYibZc3Jzas5cmwRmF7E94//CKxYASqXgft+BbXDDoBZMtBSEPmER0jW/aWdHrCpUyk2c0pfoq/FyAXxNoAl9gSuJ1wb6hXEZHaPkD5ASFNl7AbOSA3P1GV9hVES/SqJr4HEpV9NtyeLGDOJM8MMmqY9pgbUIL2uZppls/Ia/IXIKFf8NrcTSC8nFvW0pTnmBJkjx2sN08vH97/+F+jjHwd2+Adg4TYgTS5KaeKJYzgE4MDnd5UIOHuKPCcGJkf0qQVe1lCvazOn1AqQmDodH54ww8V1PqfYwanRTARoHDOp1qtJ+ylqFPSyD3YpQT1dsEqflgrYvFpQybXSvGpMo6GIQG3QuHzyMgTsnQOPWLKI01/v12AKzdAe45Rjsr8NfsmA75s5Zs5N0xrlbhsNplZxL4ICEErt1LQZ4r7InTty82qOHK9FTC+NDwCqVaBYBE2OARObkhybSkFJE6QxKzpQibCS3/mkGBRcM6fjZ0sRUI7whluHJRKvHWHIbQ8L7oL5qMq/pWnOLpmQ2yiFSYWS0ByTnQdpgszURDRpmKTcSmaqaaLBpBFhKnF6x+34taNRphBEK7/k5kS8ZpW/OaZWt7CUcnxtNDev5sjxSmP6Ed/55wHveDvw+t1AQcDr+aoTrNmUOgAoKCiA6rBCHGDBkeb/ykJYZC2PiHeB8K9NGzaj0UiNjAA4ZtAMUuICEsFmz42TfpDR3OqJdivJsCCWSFhtpi5+Ii08hb/QBuBIU17sZauRfZbaUBaBSOJqoeHJctOCabIIbKqmWJJj2kSzdDRYr4wsv6TsT0N0q/htnpFU860eF/O8ZJZhtM8mJJmbV3PkaIrpZeoEgKF5wIwBgOpQ9TpQLIPCAjA5DoyPAEqByl1AEEAREpMe1acmDOo1YKIGQLGJkuKUPQCVR4iaaKwPT+ldIeqJ8AoKQKnMWioR++Giqt5eyRPsQQiQXjBPcULmSi9nMCRYiwCaEG0TglD6DVUJSVCMyLiiRJkFrYVa/1mcvbbQaihI2m5MuJlRoWgU0GnEIjfy9UmzKTE2M8WmEbMk6KJHlBD1eYQZp/XNLy/QmXdSyMhpX92toyENXZCY051n2Ix3mnlVXJubV3PkcDD9ND6Ahe/kGKRGQsZUWBnXa+8IKHcCYRHKaE1hAa21PiOopqAdpmp/vsks5ZwgBAplvU8guURI5O72IP1FhmDNMotCSZM7uUEtlqg8EjQCtEHYpg2HAq9DTBHcUjOUgTZZuUithicDUaixHU1Nlc00zCZaJ1FC+q00ygaibkOjhDc2TctuEfFqn0HKKNNfouERmiXtFJJsurwjN6/m2DLw0ojPajZ/Q/zsLmDX1wMDA3phuZu5hQAmv6jKAjiuA6UuICwwAbZrCiroXJ1xnctrOxuMpwUaorIEAm/zXKflcISeISegUag1EJbWEMOiIB592NHadJSnUomJNCwkGWXSTKQktFifOBUS8otTCDTN7CnNufZeqPRj9m+0JqlUU2lWpGobWqepm8z9SauzFUGnlJv27Emz71QiXmWQlh16b4KRZmqVwVk+aTfULfoQZJBjbl7NMY3wypk6XylSfPD3QLkI7Pb6pB4BBQDlLlChxISlAibByjioVGYNEASrxWTBJKQOtK8vrrumzlR4s3TbPvNdnestdyV7/UVVoDrpkSUSgWMjLYHElBUkyaSBJKjF+PFqdiTcPhpBFQriimocWSp9iSbaMwh04FBZ98WY+OruLvY2KtRrk93I12ielAhKo5UrQZgkiMMndUlEDYQJPSbCHOgcU26Zaf48a/7NILhmPkWzbZX5TlRpu9DUFOsFHNk6AjhZc3yYMlpFvKqQL7dmaVkGGsekwdQqxtGOSb1xjBoIMTev5nht4pUzdRri84u3msJmvgBEQGWC03c539v/bD1EpNfgVXixOBETTamDNcBmM/CXAy1NoIqJtaBNnZHevUGOkVwq4ZjIIIhHmzttdGjEJG00S1Oe9ffpMgNNqEq5QS0meCbNJMcVN/bDIXxPaAZBcn/84BknWtUkAffH0CNE57tWxyDalqFVNtM4zaTDTkZMPVPQOgE0ammetiTvq//etGOKTdNUHSgxHnEykUqLeJVj1QDZBv/5EOPlnG9+5+bVHK8NvDo+vmbE14oU163j7YmUYo0ulmZD5c2edZFxDFTHWdgWO7TJr8Ym0CCASpuJljqZTGpVzhCz2ZBtgg5YATJ9iFm3o5l5TEZiKMUz/FBHgSp4i9jFWj0jPOUieOmfM8LNbLJrTKWmHENYNjoUCWnKjDK2/SlE4mg8fn/TtKwUwexrd/5n+0z5JIXkuyyN0ydXv22ttFE3Ssa9b2lap+/rtOX6EaVmHIOknw6osZ4sUywgJjVm3AgJgaURbkq/Gx7dtPFrMtlM1bD9QC1vwpATZI7NwGsvuMUnPtm8ahV4/a7AmacDxx3bvAxPCyGABXd1goV7ocRaUUysASqVToBhB1AssDbW0tTZol8Gypg7tQ+yOukRuGmwuMbszgAtxKxp0QS7xMk2R4l9Da42YUhYCCHbpgwBYgW4SiIUJWE1aG8BoApMvEqSrNAknV0nxI85T5pIKRZCz9OQHCJJIy1vDBu0qymQp9TCnXK9etvRRv32ZGmclHJfZBlZZtmWfkHTJ4ix9NDMFNswlvo/ZyKW1ucWpOf3z5/o2LJTJgW5eTXHFPDaI75mIAJ+9CPg9TsD/f3J9820R+8cImKiqVdZ+wtCNoUGgfa7BVB/S/On1LKM0JfEbWb6JsDE+R7J32GR/XGGQMzGufWaEKBCiBmTYhxzkaFOoG32G0xNoK3HJRDah20SCV+j0PR8n1uDmdSHd77UTqUGaTRUf79DWUbq2EvtowlZpn4W5/ntBUSb5ff+Z3Fdgz8YyXdpBNqKHBrGTVSjvPL9OpoRnaMVyv7IdnttbyD5wL3GR5pm3TCGTc51JkS6LbK/qYSYm1e3VEwv4gN0FpOANbDquHj4pfYizm/ontI8orU/gHNyErFGZwI1OvugwgJQmbMdsEoAACAASURBVATqL0HT86EE4fjmzlYv3lTMoABsGL/170gfC/TkmVLaIQklTHyB5lzHTwc3y4s1fSo+px65plKzllH69AyJyyAdo7X4pi3zXVxPEbBSGPsE62k4Pik545hGVmkakgIUwSYW4IqnRp6ZAt+rP83UK063Zm2iRpLLNN+Kc1K1MZWU5ZBck3IbTJX+ZCSF/FpOKkQ7kkY0n4TYU30zuryPphxRpk+IuXn17xLTi/hWrAB22Rk48+PAZ86H1ZL8Wax5MM0DbbQG5+1RIFASVVkUyxfqtWT7oHIvVKHAyybqXkDNS0Ghg+u0/kexT5950fyX1gSJUOzIKxT0gviYtLmzlpCSc70mXelLkhGJxozq70phKrJaJhIh2xJCSMjlEkZQGjOpXagdiDZBnBu755pzZDCMswQjTlK7BdrniSDpV5rwzyQmuOemfdcwVuZ3BnGmEa9/vX1kvfLTTIpTMfWmkqf8zrwzft+kRmc+p2he5PXPeSe98rJMwQ2BNl577fV+GzPOTV2/q5Jfmc+yp0XaOgQZyixI1h+LnCBfw5hemVtKJV6/19ejhbPwi0nnPMSfVlMB/JdYAUChBAo0sU0MA8VOqEIZZITn5DCbR8MQyhEazZAyq/URTfKPQRCKjCcEN9OMLk+SmXlZCdz22iSfXygzqUqNy2pQgDV5WhMiwBlcSBNEiZeLmA14owpr13KCYZdUeD46aZqUawBloIvRJqVgs749fW5db7jrm6Wc6FCdeaYZYhGM498bK5zk8oM0zS9LKxRlSU0Uun2ktUFzzLU3euQUi+/EMfldO0JemiQdXyGJc0VTJHyS9YmoqVYWiP4rnl+YY0BiMRBfJR/E2ChBhA2mSzkGYhzS2uX7Tu04iOucMkTDGkgwjRDNO6rvm52zKjSOjdQc08ysOTm+GpheGp9BvQ5URj1h0y40IciH1Pj/olqS97N3FlRYAI0PsyA2GlmhxD7Al4Ig1GvXvFlo2q1ot65mt9E3P/GXiXCbkgknrR5Xk3aDNUSEqNQq5WzfNy1BX++sTzRaXCA0OW0yBYS2Fyf3ypKyKRONWqEk1YZAiCaCNs1M1uyYP16+VtJMu/GPebKV6/KJ1kdamyi9/Q3kltGuBuKF8xj4XO+U2VJrNuV7z6R5lvxxAKUkUDBkmjIRzazfPLd/Q0KyEwapOQoza25efdkRtD7lNYQoAi66EFi+nP1yxQ4xM5VIeUj8NWiOfOMyVFgAOnr5nPUrQSPrgHI3VM/MJBCmOgGqVVNf09R602AWc5d7uD5jVvV9IqJtTj+Ud9uCkMejqx/oFOXZ44YsAkEYxSTLS1jk9G7lHr6+3J2kQfMRFBLisTP6QOf4LNsAIeY4vY1TVNHmV2mCVeDHz2iIWtMzex/WJpIcpjafqGLhZiYokyPA2Eb+mRjh5S3GJG3LmuDvK2P8Y46b2boJKIqqfKw6oX8meSlLVBPp37wsMEbbsebUYrKmslDmtaPFDl4aU+wAip38U+rgz4Vycl6h5N4Taaa1EwgIIa1/7NIR7Uut1xJN14xDXfcjqvLf9ntpDZBLbsRzoqQvVkwkpNYutWKpVcJvr/88tyC9NJiJGvnnqMRMbv1yXpvkfbPn6slTqPtql+UIrc7+Td73cTL+9j6kyaMWMOXV5XM4zgn4J0bYEjW+iX9PjHC6xuqE3tKs5vm7X1t44okncPjhh2P27NmYOXMmDj74YDz++OP2+DXXXIMwDNHT02N/7rnnHgBAFEU45phjMDAwgLe//e0YHh62111yySX40pe+tNntml6mzlWrgIsu5pf47DMTkjCmNWtuS3kAMteKwXlglAJQ7ACFRSsEqdQJpV90KpS4rIkRUFFnglH+294GiFhrTYPjoxTnA0hd/xfX+UWxCJIk2DZpti7DagWy7JhfIuggHjPbLJRgNWSTicVoSQhgE3BLLUuFCZlKn541eQrTpyUNERyTFuhitb2ie75ZE2lNulEizG32GbPEwmiGUSKw/Gw1yphS5TrEOlBP0V7tPRL+1gbNT3/XcNy7uW1rioAryNO0QnmOf1w8V34ZDeeb85RzWqKlZ2iQfrsbhHHKeDRDmlUn1XUhG27anXE/nEvFREYmdLDXZU1mM8bFaaO8xxnFyDJSzekpZVKcuQzYluO7CKyL4SVojxMjOjah2PpcjY0bN+Kwww7DsmXL0NvbiwsvvBCHH344VqxYYc/ZZ5998Otf/7rh2u9973tQSmHt2rU4/vjj8fWvfx1nnXUWnnrqKdx2222p17SL6UV88+cDf/4zMLOPPztJes06MEOASDGTBI0PpDlPPrhhEaqzD1TuBSojQGUMFJaAYhlKBSAVAKWAZ1vVSVCpkzPBWOHS4oU2GpnZkSELsv1GwDj+GqFx2MwuBCAG6ml+I7DGpMRmuSbMHKJ8Mtd7/jFLSt5aQMd8Gmu/YCU5Lq81GrcxNtQj7SNpMeu3PstY+FTSLlHJC27yk6YGTegxNOU2bMNk+iWCZ6iuzWniuBPMIPyFTYWLSv0z4wtBNt4EyxHe8h7IYggcdepcIMqEN/TmOfE+y7paEbksP+saB1nkKyeAvubmnZuGNHLPnFSINm6O4pR6v5vdZ1l11tj5Y59WdFrBZnLr+yDTICZ0gYzKds3+8fA6BIUCqDoGVVNAZ589/uKLHHpRLjeWvtdee2Gvvfayn8844wxcfPHFWLduHWbNmtWsYXjqqaewZMkSFAoFHHDAAXjooYcAAB/96Edx+eWXo1DYfPqaXsQH8GB39PANqmpzmPRfKbGJbFBwH5DUyC5RLsAPnd6SSBVKQM9MUFc/MLoemBzRJFeEUiFIKSaxGpsnqNQJBGFrH6CJDi11afOpF9WZ2j6kCB8t0Ot17mupm8dFpixzTKd6DBqi8MTauGIxySNq1wIKc6OsX5qFgCQxQFjQpsuq8I9qwov1b2l6lbNRqeXJH6uZ+cE0cP17ZDTPIHmJrY+PkqUVcT1J1i0DdCS5Ux3WJ6kC2B3dlRhHo22Ckva19Ms00wSaPKNpkbpp1zXM7ZqV2UzK+wI544NPWEBr4pfE6x/Lqj/djpreRpVyWlNNWh/LPNzknqV21R+Ppicnx5T3udUlWeZNa8rPapI3WQW0e8BvEp+nwhBEBKV0KsjxTVBK4eR/7ceNNwK9vcDvfgcsWtSkrQB++ctfYu7cuQ7p/eEPf8Dg4CBmzpyJE088EUuXLkWhUMAuu+yCa6+9FieffDJ+/vOf481vfjNuueUWDA4OYvHixc0raoHpFdzywgvAttsC550DfPxjSB4MqbEJDcd85+d/NGj2cvrDohSv/TPbHpU6oXT9ZB6e6iRfV+4GgkDLg800KzRDStte0vWbW06r8hpPlJW1X2fLKDtRXrtlynKdCEtfoxN/t9W+FsiDFP5+0dZz2k4xbVyb+RpkTRwan7sUO0BGmcnZZlJPRBgdBWZsPYB6ndMNX3QRcM452cU899xzeOMb34jLLrsMxx7LmbeefPJJKKWwcOFCPProozj66KMt+RERli5dih/+8IfYe++98bnPfQ5vfetbceedd+KKK67Ar371K+yyyy644oorUCqVWvXC7dK0Ir56HfjS5cDbDwRet613MMtERMmMXe7H1ywitFBkf1I9Yq1FDBEBbuLrYplrJmICBJJdIUqdgFKNGqAJLjGBCG3Bs0lJIR3oDWQBNwK1WVlSazFlmwALkBv40HC58HVJX11YgNUqpdM9cRglZGKuNUEhgTY+yKABuwTCmGNk9GWKL9D8tsELQps0bZBlO5qk0QwDcV49SZ2mIDTDgluek7bNtM1omXGiPZrn0Klvc7TCtNOzTsow621uGS9XW7K0x6zzW1aVfm6mcJ+y9ifNjr4JMmXSbX/7JlRKvncm6fJYa9iz7Kul7CuWoIVJPetc533V7qGOLqhABLsRoT4+ge3eMBer1wQIAuCWW4C3vS29vWvWrMH++++P448/Huedd15mv2666SZ88YtfxO9///uGY5/4xCew3XbbYZtttsG///u/48c//jFOOeUUvOENb8Cpp56aWWYappepMwyBT5zNf5vMLT4kocnQ5zhms12WGUpeF9UA1NiR29Wvl0+MARTz41HqABV08MtEFVTuggoL7O+nOu8AH9c5KqtQ4iAYmImTSqLuCmXO2WlSqGXCI72kMNgAluoEl10o81o8Y4IjQYKm73INkvSjmK2YoJK9+sxBSxTmM8QLbnxvwk4iCUcSg/PGBjowZtK9Tt4faU6NI6DeSjDoPsaizlaom/OaTZ6gJ0IRbBBQalmaSLNg/adNIANR4DcrgygzNUljlbANaBT6vh/YEeDyXvvWFF9g82+S1hYZkCEnooTkO+d7YUI238XeMZtoQTzDRvhLs6tS7I5wltfI919+h5TjcD4rr+ysskj6jzPrRUP58t4qE5zjj4++P8rcjrRAPlM++e2A+ztLDvokTwSKY6iAzZxUmdAxDTHuvzfCf36/hF12AZYsSWkKgA0bNuBtb3sbDjvssKakZ/qdpos9/PDDuPfee3HppZfii1/8IvbYYw8opbDnnnvij3/8Y9My0zC9iO/pp4E3vAH4xMeBj3wEHNDiCbeGgBb9OQxFJJ8Rcp6A8Qe8NpG+MwMRB7mUu/Wu72O8CL7UAWUMoEEI6uhm0pwcBUqdIL1I3WqAZuE5F+q2xa2wxcCI9suNeZs91D6cSDbSAj5qPG6bI5YlpAbhxG5VPCiiDqPJiUTbJuLTbJtj7o8JT89a+G4jR+PkRVfSSS8Ca6yGVve0tCT6k5TW1OoiCtV0xgiRmESZdUihxDthCKElg2CCIKm/HoH0rhkqLCSTjXoNiGqgmlmCUPP6mUYUTb6XQtMKYbkUQTX/HqL9Vng2IRIAyj9X+mTTiMVpm/kM7xga6lJOAgLnYWsCsq9bK42RD8ljHtnLZ09/p5wJhPdeOe9EExKVYx5wn9peP+xbqNImO+Y85zkx38egKEoyWJU7AADxxDhQLDExRTWozm7MmV3CaadlN2V4eBgHH3wwFi9ejM9//vMNx3/0ox9h9913x5w5c7BixQpcdNFFOPLII71mEk477TRceeWVCIIA2267La666ipUq1X84he/wO67797euAhML+KLY2BigvNnxjU4Myf7sDS5Pghg8yra2aK5XMzSzRqqKIINiUqZhSgACIugTq39TY6Cil1Agff6UxQDYQgq9OgIUN4LkIIAKHVD1etANJGUZsyCpk3NzLE+zI7xdb3GjTxh16A1yu/IK6fMx6IKB+5Yc7Fyx4m0cdcSqkrMeCaSkKS51HsBiWCzxgDJsgi7HEFrjZFZ/6cSE6bNAxqx7zWq8f2iCGZXeRXqvQ4LJSaVqAbUqiBjqq5OcF26z6pYBkrlZOuq2iRQrYCiCt+7IODJTalDr8XTezzWWFOmqAqbSzYsQhV04nAFu9yCiU5xJqCwAFUuwWbtIR1MBHD7C+VEe/QFp9RU0jQXZ2bP37lPUsq9yDrmwCvX+S7lXP+jLdd/HmW9sj0k/m8s37oXnOtSyAmxpzmaHzT2xyHgxnFsICwVAqqQfAe0T1JThiRP0v8y7pNDzmIiKvtQj/i5jSIOYOnoggqLHNinFKhWBTatAXpngoigahWAuH9Bz4yWrb3lllvwwAMP4NFHH8U111xjv1++fDm22WYb3H333Tj55JMxOjqKOXPm4IQTTsC5557rlLFs2TLssssu2GOPPQAARxxxBL73ve9h9uzZ2HvvvfHBD35wKgPIQzCtfHxRxKFD2y4CervELAv6PlN2IIsPZ6aWIThKTGIwQS1p5iEDpVioVcf52rIOfjHtgtKKktnPTu9WHpa4XOnryxQ6bSCOQdVJAMQC2vSrXk9IK6pqv2CBx7Qe6UW8xWQMiICoAprkROCqo5uPR1W9RjAGxodBlUkmj2IZqrNbb/JbtG1hsplkcgpDFualDiaKygQTdRBwqrhiSSxFgfavxSAQ+xfMso16xELMrulrDL9uIH0FsDYjj0styJQRCpIQmqH00fl5GaV5zt/ZIFUAeeeYH6EgOMh6RU35gYKjqTWeiGyyEV+pDOKR7fKJxa9HAdTMcuGQrRbGzm85lgR3U2Q5XrK/3m9nQgDvb+96eCTVjgb4SiJtfCmZR9p+UPLRWTxvbpbSk0QWOjAuEYqqQK3Gfe7o5skev2G6PMXv5vA6oKMHqtwFqo5DdfSAOnpBq/8KVSpDzZzn+vymGaYX8b3rXaC77mTB+/sHgHlz4GoP4mWVviGlYP1MYSH53to7xMzPN7cALLir7B9UnT36+ji5NghYEIdaE6mMg+I6VFDgRNTmQSTi3ePDgv7R5xuzmVK6fVojNS9nPUrabeo2gpJiJhAFjjRNI35JAr75zUezmarzqBjhoU07MnOJUrDJvp2lEMolHCmQneUEpK81SxNUUiY3RLRBz7jNYnlzvJWAnpJgE/fPXk5uX5y1T/J8IcSlRmyfOyPcZfCLvodS25NkKUms1SRJmhyBhsldcqWvSVDyO5OUUr6zicQlOQm/bYOJNEhpF5Ln2zZdm/r8dzMVTcbFv97TLNMx1eclq1mC8N0Dug6lCc7rX8MEAMyEctIHEsFkBMSUWDYAqFIn0NnNk3F9f/iR1HXVI9Dwen6f+wYB7ctTpQ5O3yhIjv1905f0gOlGfP39wPAwqKsT9O+XAG/eF4ACyl1Q/VvpzU8D1jIsiSCZtZuMA0bAxEILApIXOYqS6yXhOG+imE2mDSFRYkor67V/RkAEIVDuYVt5ZZTLjapAUGBfj1OO/i+NkBxTqEq0rdpkYjJraF/y4GdDJSRkg1pEGVmz4pfbvGMnLaIum2GFACUErWm3JBcVsDZkM7IYoSAIx04CQldzNOf7Eaa2n0JLgyjbISnTJg+ZWpnotyRMkzRBqSS7iCUneU3G33YD4Ej0XWgITvLktN++NiUmTU5fEsJXymuH78tr6HdK+51JkinfGysHGYQn3xGnjizRt5lE5wTwKK+ZSdtJtkn2VWYpMhfb6GTzHFNyjiBtqk6yCwgxVLED6OxlU7u9x4ZYxQSuHoFGN3Hg3sBsvi6qguoRyyGdr/jvEdOL+C67DFi6lHdh/9EPgK6ul16mmbk76bViNkV29mgfUzXZu8/XnhrMJO7LTmbboyC0wS/2ZBUAYYl9fjVtMowqQKHc3gPX1q1r8RK/FLIyWoyZsYYiUCVrKYQUmuYFNynOzI709SgJ6JACwqlPt13mDDW7Qcg6XjKEsHV8pUbjEkSnydZGEjqaUpw+HrJfCkkd1t8ZiSCc0J2QWDNkhrk3s0tigkCAE0HoE6pPdI750O+L/U/0K42EmtwfvwxHu9e/zWe/bH98G7TDFsSYpSXa/piJiGxHel3k98+Mh3m+pYZtU/B5gVjmGZATFChQZZzzdcZ1lhXdfTqrlBJjICcqgBXzcR00pnPc9vRDdfVzvZPjbPAMQ6BrgDW9v2NMLzof18sXojpQ6OSghChtGUCasE+ZWQLJw2FfMk1mcZ0fDun/aShGCmN4GgB45muCX2qTwMQoL20olJgAKQaiSZjtjjgVWhdQq4Bqk0CxozkBypcrLHHdcdXWnToecsYnzzMvbqGUrAm0yxv8spCMkxwLu5xBJaZPUweJFxgQRVKSNDkNqVqDaEM9bdshQaxKJesmzTVC66EGH68kWkEuvlA1x2XWGEBrmGGy0S4gNEYxbtIsGkhS0X8XigDE+IHgbIvl+AyFhmitEVnkIp53E32qFGByr5p1jHaIKRkzv42OFmf+1O+AUrA+Qxl5neIbT2tiOv9kkaVHsGnm0FQNT1ckkzzLSY7gXP4udB8/v0RJbnbCok+S+WWN791eE/O9iKrJnMpoedVJ0PiojbBUXT1QXX1QPQPpkwvh6iDZnokxxCProYplqP5ZQO8AnzM+wtmmghCqo4f99FsApo/GF0WcDC6OQV1dwJcvA044DkD2BHTzoJKoQRnyLk2i8mW1s2UkLwjQKLCJWMhWxvlz7yBHTlXGkrVzZnZm/q/oQJlSZ/s29bCDBVi92riQvUFDbXXrlRBCvmDJQLMZtS+4jRZjdnQA4OzUbuuXcWuSxLXvyN/N3hl7uN8bIWPzeGpzt9wV3l9cbgUixHMgibKR1JQ1xxoB6i0vcMbMvw/eRKPBHwY4pi7rzzZlCd+bJUExGL6Vwr8npkyf2NJMkI4Gl/VcUErffQL1z8+ox3ZDTODkpMSfjEkfZENb5Th7vlBxzCU3XZ9J0mDXZJJLbo72JvpiUubZYVDJM1cdB41uBEU1KBVwPEFXHwd9mTL8e+SNn9TsUKuANq7ltvbP0vEJ3G8a28TaYhCyttjVl3If/n4xfYiPCNh+e9DKlXzvfvA9YI/dktmUMbPpm5d9CzOnky7CIoe161mXNXWaNWWOpuS1s1k3gGTX90KJ/ZNBKEx7SR/IzNYmx1gDEGnSXjLbp7ZTcTCO9COkXicFqVdOEPIOFkpxmL+vyRlTaFYb5JIGILm3gNgQF8nOC1K4pGqm+m/ruxM+FOuPEseN9mO6ZoMJjPbXxrPT4PsTffcTWlvhHHvPlCnDaHMZGksWOZk2GPOXox0q0VfRZqDx/tp65TUqIZKs47Y9YhyyyC9N4Pq+Ul8bl2Zmh9SCxnptPXLM3bFMIlHFs2nN7lFSjtzpQGtlSin3ztgJVpQ8x5LgoJiURjYkiSfKnVDd/SwPGsz7aZMMf7h0nVENtGktB9H1zmAzaKFk20QjGzia07gIemdO+0CVzcH0Ir73vx+47jpg/nzQXT8FZvawMNSZUWwQRkGHxRtSNLPwVJ9Tuwhgo+8cUxUahaGjWVlV0D0FxA99PQJKXYkjOmV5hSXLygSbSdI2ww1CNpNGlQzzbwoIInF/mlD1+uRcKASK0Yztpq/mNGHiMxoUkTapeZOH1Fm42x4lBa3R0kzINtVdAaUgzHMpHW+oS7TBHvIFdIAGPwyRyEqTQl7O2DV51SxRmefKaD3CTGiCdBp8cn4/fQ1M9MP8sqZS75mzp3lLP+T9Ib88OZY+mTkPUUqflHeOrk9uDSUnLqkTTdWYLSdVWyTddEFuhqCiWtIvqbHpPft8JdmpJ470ml9KnnWbbAFMRqMbgPFREIjNjd19rM3JKOwpEB2fnrSfRtaDxkagOrqgemYAHV3JxCSuM+F19epJdgT0zWZ/3haK6UN8d90FvPvdwOgoB4O88x1Q37kpMR9OjnNUZ0cPIM1MoCQDgYnQKyQJTRsXmvrCwoOcOWe9jP75aSh2AqUyaHKMd34I2L/nCnf3wSciDk+OqjYRdtM6fbMmUXJNHCHx6+gZfBQli8azVMpmfVWh3cBW1T1tz4xXagCC/ZAI98BoKpsxWbEalx5DudxB7vYAfY5PhNLUaQ8Jc2Z6pYI4PC3UEWhS+9CfpS+xnfIBT0CmmNTSNERpprV9F+X7RC7rVQF8DnMIOksb9fI7Jj5DoXmbsU4ja/meSWSZQaHfE3s9YCesUS3ZsSSN3JwlMY0jxDuOCA3QXisyCkU1NiOObuCw/7DAJNfdr9fMeUgd6+x3zPrt6jVgYoy1uzBkza2zB6pQ1LeDz6HhDUDvABNebRLonZ2YTrdgTJ/glnGRlzOOgZFhUHWchVpRZxsxZsHqOBNguds6bvnRCoFAP2RxHQgCTgullDaV8ousgCQTCuAuDzCC1JoDVaJVmlllVh8kodUmgBovDreamtnctlDksmx2GWFeNbt1m9RkpQ7hh2yy0aQvhMQu7Qrga0t6M9hyJ5dZnfCIJ02LkP2rp6d4M/WbvkvhIjVHEGxu0boUBkj6ZM63S020Jm42ovWbRgRQhMadeXyh72loTtCMp+3JtXGOIKekvmYgIGmQpyWae2gINxZEljUJMOdK+MsyADialtM3oZ0p6PWluj12fZ5Y0uKYDeHMGWyDyGh3YpIhzZGhcvst22HabEyYtm/6byL3LZMTmnot8Zk7W18pflfMtmEeWRNEjkhr5qwlkyRDlGFBv58A6nXQxDAwvB5Uq7AG1dnLRNe/PQJnAmQqEsFINulAC1Mj6fyndZ15aP2LPK49M6Bmb23NowQzOZ5k8u2ZCdU/yPKweyZUz8zmE9ctCNNH46vVgIMOAu67D9TZCfr+d4B/2JaPxTETQT3imVXPAGuAtUm+0V39yS4KAk7XoxqTTxAmvj0gMW0C7sySfGEizDEmbZXROqXp0+4+Lma6cqZd01sb6c1tk9k7CwapoRLF7EczG0gWO5OAmbQoxM156Fs9HlJohiETlmoipJMLG88JC7A7H9hF3Vl+xhZtkdqQ9a2RV2ZKG/xyGshCeefIa2RkpPmOEmHXjLzcwsTfsh9GYIty5Tmp/TDPq+izLHsqmmGzPpi67KJ72S5/sqTELRIaXYOFItZXyHck4qjuqMKfja9X7i5utDenj6ZeQ3BmAhzrMmtJW2yAk9jPM445J+/wetDECKACqI7uxGSZFX1tx0vICDtezUHaZ4e4Dlq/GlSd4KjOzj5ejK7rtObbyjgTXv9s7v/kOJs3O7eswJV2MH2IDwA++lHQ1VcDs2cDD/030NsDTIwAoxv4wewZ4MCK6iQTRLEMjKzndS+FAhADqneAd0SIiYWUISkAgOLZotGgCiKFlk4cDFOufIAd86dxeLfoi82tGfGMTN8GO7OrTuqAFr32z1kr5hZuX5CwyIShwkaHtSHP5AtYAWTgE4RzbQoaTG9GOwsAVWD5byM0m6BV+aZNUlCGYomCzBCTJqyTAt1jfh+MiRzw2iwFuCEiYz5Fohk5QrahM4lgdohFEmMbkwXbBVeYO0gjM78daX5HSdANlgOfmEzzPc1LjoHU5HyN3dG2RB3QE0CjudXrOp2eCGbSiQmUY5KX9Sak54g3qxHWLEFaTd5uqaXvQ3WCIyxH1gNxDNXRxQTX1Q+UyikuEjEGDtF52mwL2Pc/5kAUGlnHItOwgwAAIABJREFUWVd6BqDKnRzgJl0fAPsOJ0eB/kEek8o4y5aeAaRmcsoxzYhvzhxg9WpQVydw07eAvfdKHuCwAEyMMgmWO4Cemaw1aVCtCowPwyS3Vh3dQLkLVJ1kLamQ5KlUUHxtocgPYHVCmNGEGcSk57IzawXEdShQYzhzM6TcAtbmtBZb5IwsCp6wky9TUACZXc9VoHNqltqP2PI1QpNL1AaMpLfTFWjN4JmsfMEcFHTS55j9mJJ4U7WINmHJ3LTT0/gaNAJxbYqQtp8t2cn+GY1HBj7p/5zo0LR2ak1RQf8WRN+SFL1AlFQztLf8QZm+yPajcYzlhMb5zhuThkmQ+FuaJqUWatpg07Wp1ONKaoRyLMT7RXJ8jKk60kt6JGlq06dSAV+j/eY0NgwaXgNUq1ClMpNcdx/Q0QsVyM6nwJqBp050pr1kzKqTE6C1K1n29AxAlcucM1NolFZkj27kjC0DWsOrTHA//44zrrxcmF7E96Uvgc4+G/infwJ+chvQ1W01oOS9Z5Ufoxt5O6DeWWwL1xFMRKR3Uhjjh7OrD1ABRz3VKryepbMH1kxVr/NC8iBk0hTDxTJCaxn1Olil1EsTZJohsxu7RYAUp1M6ARrtTwUc8my1EiGsJbkVOkDQ5BHpjW6LHa0JcCrElUmAil/YgiQwMWHwBeiU2mMIR5uizAzdaKcyWCJNgLcDGzWJRqLJ6jNBk5Q87puz0iYsUlMx9TXRfG1dgqwlMaZdI8fC187ck2VHM87x4CjByfNIsjxZnxIEZ9uX1G/zcPo+4IamCl+ccSvUIzZ9AoLkFIxWziSnCbMecSKJ4bWg0Y1AscQLwjt72U1SKLUegzSinqopkYgTt5vtqVY/x6nCemewZlfuZGuP49rQ4zy8nq8ZmM3ywPji88CVtjF9iK9SARYvBh57jAX9XXeBdt2FTZ2kIzW109kkYqWoxtlXxjby8f5BoNyt31VtUpjU/rCuAW36pCTHZkd3YuqcGANNjvKyg+7+xEnugWURJZohoLXDgrv7gQqhyjrlWnW8qWmRAH6xqxUO5CmUtfzLmnWzULQJb+2O8B2pbXag9xVETByo4s+ks2b2thlZJiA0ag3SlFkoAQj0wvuo8Ty/rrYFjYjQNLk9G/xdbbwCTt+lYJfXppG1wzxCWCL5ruE+mqI8bS9VyMrzzd8ZWp/vn2xlEnVAKX9pxHFSppmASA1WtFf57bfmUb89fJ6b+ouSYB9p/laATRogfXj1Ovu9RtaDNq0BSGmfXC9PcDu6rKxI+pwyHtIvb/x0U+Q501eyiRMItGEVaHQTVE8/a3XFIgfHyOwrZoyIeHsgItDAVvwemwjvnpksS3I/XtuYPsT3s58B73oXMDICAKBD3wnccG0yE67X+EEgsKnT32JnYgwYW8/k0T+bZ3f6QaaYXxDE9SQ/Z1k7j+t1jh6V/o/KOKgyzgtOjVYnzDHO40e8e7GT3iosJpFhcT3xY0gyTTV/kibJOMnmYkihUOLo0KrZq1DUb+qpjAvi3IyXRMhv+4VDSirxf6ZljvEFS9uBMynnBmaHeErGVl6zOY+1XGBOPkFmlJdK/sa0KiP4JMl6/bLRiyq51pvEuPX77fHPb9b3bELzz5M6nDOZk8sQpM/Zugr8Kvw6GicIVlNUSHzscR2JlovMd8ySA8BJlsc2gUY3Mql1dGptTq+Zc8Yyg/RMPx0fs2jHVBHXeRIOAkaHEa97HqrczQvMw5An2EX3nUwILwZteJEj0wdmc59M7uCuGVBdvTnhbQamjyH42WeB0VEA+qF49q+gjWv4eTW7WHf2cODKxCiTWRzzu9TZA3R2A+VOXkg6vBbYsArUO0NvwQH26SmVRFXGsd1DDmFZL4iv8yL4zh7+kUKrWuF2lDs4mMbMwFTA+9CRfmnDIlAo6fc0SiLSDKFqzUwKSKsfKAWUu7ld1XGx6zuSvJoyQIUv0m6jAqizl88Z38S7x4eFRgJUerZJPmnJhujfZpZuyY+a7wDvCzyh/SYama7XmPKUd645JrO7yONpJtJAlt9E48tcN+iTji6TYrDJWjc01Y9n+pFC3IawrNYjiNKp0pChv5aOxPl+G8WYyLZ598D5pJ97+63RPKRp0VpVpgDvObBZUkzbpZYo/eLazyzXthKB303TH7OuLtQ+4kIRqn8QwcBWjW2w2qIcd9PvKPne1j2VTnqIYyY7qgNRBHrhSRAU1IytEMzZhuVAZ2+DC8ISXhyD1q9k0+vMedyFesQR2x29wMz5W/QC9JeK6aHxPfccsMMO7lq+zk7QuZ8E/vUDHNIf15kwzDIAIhbytar1c7E2YkwyMTC2gX2BXb1A7yCvf5kcY7NJsZT4q6KKXtdWAVGdw4NDLbhivYO4XpxK9RqUWSQfVfkBnxzl9pl8eMSmGtXRy+VUeUPWRJEShGpe6no98V0Y1Ca5f6UOJjFfE8iYqbLmOMltL3drctTC25JRgU2/MrilHaQ+Tp75rukMtZmmI/siNLNU7Weqj7XQuMw9crZjaqGt+uZHAM7O6k4ZKeQs65bnElxCbGh2kKKQUjIhSbvKtMlsYOovwnZMk14f0+5Jw9nJcbdZMZOPgpicibo8k7bVOM13cZ0nmIaAw6Ltp5Ln+QSaBsd8DCQBSS9BHBLxbix6/S2teho0OQY1MJstSAGY7FIWslvCq9dB657nDWD7B3l0zPrkUpnX4xWKDdfnmBqmB/Fdeinw6U8DVS8V19ZbA39azg+cIbrqBAt1qgM9s5KF7bVqsk6v3KWJQpDA2EYdSTWTX5rOHjYvRFUmLoBNhUGYaIfO0JHOfCK2jbFLDFi40IbVwPgmoG+Q1xoC/KAPrwWqFagZW3HbADh5O40QDkNNgAFsijAdeg2lgJ5Z/FIYopUBIQAsAZkWm3WDKtARlXofNfckJMEYCm3NgpWObHQiKDNPbq9MkkJSkrt/H+Aekxqf1apa+Phsed5kwJYrI0VjNJp0m7XfCGd/nZkkWO94UrHgTnGNFvQEJBqb7IPZjcIQjrMIP2v4HdWydfca+grYTEmW1E256ct9rPDX/neqVZnQCmXeS9Pcjmbt9S0QTjBNyr3MQrvnmbbWOdk5bVjNmlp3P0dbUszvVmcP+yCz+hzVQOueg+rqA/XO4kks1fldDvTeeCYHbo6XjOlh6hwZ0bnwXND4GG/uCj1bLJb5pxts6qxWWKMrljRZgR+yygSbEjp1ZhcdRUX1SG9FxEKb6hFQ5gWg5sEGxXyOJtAkbFjp3dbNR50JBQDAv9WseaBZ89jsSMRRpEEINWMOP9CVcdDGFznXXhACiJN+m1D/qGpJCnEdNL6Jly2EBWDTalBY4J2X63V2misdQUpI1p3xgPHncpeeGEzw3oBK+zfN3oBKmLuoDidUPwvWBJgBaYqVhJZm8rTX+BqVnJ1n/G1NaZ6mJv1ujqlJJdk+jN8wzc+XaRKVxKYgEqEKaa2FcuaEwNSRkvEkCLSZ0JhUKflRss9IxkuveVQ+WfrmVDkJaHF/ncus6ZjEhEBDa5FNg8BMVGYcJRMwvUG06ugCVNgQU+QW5E0+lSld3F95jp9P1U7qmpVr6hfkWo9YPigFTI6BVv4FFBagZs9HMLQdF9nZmxllaftfnQStf4EnwnO2Ze01jnmDaiLexcVMtHO8bJgeGt8DDwBLljimzjgMUX3X4Sgu+w8EQfrLZcAz4bpetB4AE8OJNgaw8De+CxMVVtF1Fcs6KKRsTRR214TxTQAUO6fTEke3QkETda1i6yObS1MTrdHIwFVxpnW4L4I2kdgdHqjORB/HoLjO7bbmopgJ2iTWLYqdFEwUXqHAM9DqBO/KXCzDEZREYm2dXsJhZuJBQS/MryUh5uYaH820Nf+8VnCEmyf8zUxfbjZsBHxT011We3SkaKwAePsMThUpPkkbyShzeDYI6+R81zTpaYjmV1Y/zbMk5w6ClF1NLhbao3LXqvpBXSnV2D7UI14gTsRZVgoFu7vKZgVdmbKtedfTntNMyw3Pi1Anm5AhmaUM9Qj0/J85yG1wiEkuqgEdnRyhmdEPOw6T46ANL0D1zQK6B5J3oTLG49M1oANX2lyHm2NKmB7EBwAXXABcdJG1n2PHHbHhxpvw6/+8BV0z+rDfScei2NmBoI0F27bL1QnWCPWeVCjrzW3Dop1lUWVcLwcAMLZJmy16E4KMYybAOAI6+oByx+b5xO3sXZqGuCRrwpLmmzgCKpPsn7Thz4qTX8dVXshvzLJAIkQBIay0ZiNfLrNXXaGQEKpZ3G/qjyJNjtq0G1V5jDp6kp0y6nXQ+DAH9nT2arJUvH9ZkAhLRzMxyzQiERGa9ngaAddMSG4Oodp0VVrb9gNoXjawYCXp73O0NzOLkEI8uTZRHj1it6CM/vvjRSl/IbnWaqaqYbzbITnSkysVR3qbLzOBIru+brPhkJV5NjPtoG6/klYKSDI0kzxdJsCTEaVg1wIan6hZK1soc7BJK8IbHwFtXA01MBuqu19ofhM8Ae7Q6wnzBeivKKYP8QFs548iUEcH8H++CvWeIwAA6599Hj/58tcwtm49/uXsj2HoH/9HxoLtxhmg1d4qE2zuU5xo1u4BV+6BCrWvz2wjNLyGtbWeft5h3QiIiWH2F3b08hqhrBc71EEz9ToQTTrtscKGjOkoXcDbFyaqMcGUOpK1PLUKaGIEKtABKqUOICxp+ZC8zFa4mgTcBc9Ua3xiJudpk2UQJP8w/iT7nTC1GvOQ0TSqk7z0oaM7CVaojPPO0GHIEbnFstZI9diZaDZrjoRIMq6b72tFptsNu0N468Ey4ZGQk0YN7jFzvvLyQlptE41E1aC5oQV5ew1uIHGttTj+Si6ZfB+YCIRJK6/xL48wzTMbVUGVSSCqsa/ZrK3V98YtJ2Uc0trhdFlcY4jppZoAG8Y4IT2CGCeoxBwr/YXtaLoAZ1kZXgs1Yw778Uzd1QrLnVIXZ2op5AvQ/xaYXsR30kmgm2/mHJ33/gIY2hoQjvL1z63ETy7/Kh772a/wns+dj53fdgDCgpfPrwV4m6NJNtWVO5kAzK7p5U4OeDGBKxtW8cyvZ6bOqmLMpGOcPq2ji7UgqHTCCEIgKIJ9eTW3fYaQzXmtXvCwxMsk/PRqE8McVh2GvHZIbAGTLPjVY2NMpYUSnxPXbeozQPE4lMqsEbctcNLIQTUKuSAEhWXwTgt6LKR5FqwlIIo48tbkTzSRulGNl7EAUJ3drHFUJ3gCZLaqimNekxlF7NfVKeka1qLZXS7A/pbU5yYR3g1HfTOa+Rx49dj5QfPy0wmQ3HPSSFApV3jbvniTKf23e0el+TON6MjuEUkgqKAACotMeGFKcgenD22+j3YC1YTgXy6Qdy+t9cVYRcxg8ITHRlA7BJyMq1NOrcq5RQul5HtjJSmUOLOUTIyf4xXH9CK+NWuASy4B3vEO0FvfAqx/gTWb/kFHGG94/gX8+PKv4IHvfB+HnPtx7HfysSh1dbYoXECbOwFoIavD2idGEyLo6NbLDGrAhhdZ8PbPBDr7EwKsTnJUlo7qyiTALDQxf2ZDv4Biu5sk8fUEv7JmKyPj8yoUnZmsKndxqrSoKtqgl1NUK+y70+sAZa0wAQ7t9k3+TtOAWpmuVIDELJlEM1rhbMqMhXlKrn2Kqom2WJ3gvK2hjvpVARNpZYyjiYslJtRyFz8btQqoNqnD63UgRqnDCkqCshG+iuLNM3+nwSMi8yXBBAyRd54gOWEabfAFKk+Q2yKMRgj2kUfV5HnUOXKVHyD0svk724GnPaY+T1n12f+SvurtylxyTsZQNRbg/OlowEYjNBG35hiIx7KgXSqetSLHK4/pRXzHH88aXxgCLz4HVSqx9rVpHWdq6B8EdCSjArBh5Qv46Ze+ht/edAve9P4TcPBZH0FXXzfafjHNDgqk1+fUJpMMKFW9R1/PDNYM6xEwsg4YGwZ6Z/LGkNr3RmZ2FxSYMFUA1aEXwNcmWvuRHALMNn+mXic/QpNxvaYTXxf0UMSg8RHWALv7+eR6xGuHNMErc70RNJPa76mDaJxtYcIQUEXejLatbXigl2YgPV3ZVIWC9PekEoWGjNIzl5pIQL1IWsVith9VWXuuc+JjNufpSUOtAqpMsDk8LOhI4S6dG3KEfcVBIUmyoBSTrU46oErav2w1M+VqiICdNLlC1HyTrUVZY5ynlcigHHuVzaepEtO0DGYJwqamzylBPp+2TaLYVte8FBAlKf0MSdl7re+3nsS1nKyayZYZB10Ol+KPtSFDr0wxkTCBPjkZvnKYXsR38cWgiy8G5mwFPPwHLWDNgxXzhpDrV7GtfOYcvaMBsPGFF/GTy7+K3970Xex93HvwL2edht6tBjerCXa4zKJSEAdsFApsUouqnD90bBNreX2ztSNfp0ar6gzqBW3WCzs4+7uzWDqzctfs58/mS1qgVsYTwkm5vTZFmwrENifi1TUBLbqfNDYC1dWTaJ1GKFDMvtFiiV9WuzegTiVmFvOaNGYt/CFZ7bUEJlNlWY2qCFDk7vaeikRIW9OuD53pp5nWmtn+tEAZqwWIEHoTGWk3OA2s5YAqnMhABQWeTIUFDpWfHAViJBmIqhOgSb5/ZqsaRDVQvQqFgO+HWTwPsJ9XaM8KAQt9mcXG7lAfJ+0PxFIC12mbOT5N4QTvCEJ4uQV8VkCU8dsZxJGdxHCAmGuxYF5s3rYGrVhYdRz/rinTmZSRIPqUCZ5eioKgwPIlj/B82TC9iO+qq4AvfhHYdVfQN/8vUKBkJ4Rih17nBKiR9by1R7EENTjf+t82vrAKP/3S1fh/N/4X9j72PTj44x9C/7w5XiUqSSht1hdlaC02qGVSE02hqAV/kbdAqoxzpFapA+jfigV/oDPFRxXYdU+1Ku/x1e7eWUZ4pmgFumGuQJEmINn2qMrt07u6K/MyqiDxPZrNQOXLXavyGNlF9JHdxYIJuDtJNm3MR1E1eYFNblIthFJn1E2jEnWwjL3OEyBasDglSH+h3rMQDQFQSsufgJfKqdhthxPUoCcADSnQpmBqk81raKspmxwfL+n7oAAmNB3gZE3XBV6qQnqtqiqW+P5Ojjm7hPNWPJt0knboHK5FfY+KHFVodzBXPF5mGYfxT7bTRbuAvU2N7uWEo8nrZ8RMxkzQDQAZfNVu0xKtO4mKdjRyXxuXk7606FLnK/2eWe1TwEwsw2J7vv8cqZg+xPfgg8Cb3gSMj4NKJeDE46Gu+t8smE3EZVThII9yJ0iFUGMbQetWAlBQWy3krOwgbHrhRfzky1fj/93wn3jjMf8TB5/5rxhII8BSh143RzoTeiWtZVYYcUhy1V0wXxnnbUTiiDXCvllcdlcf2/4r43rDzRqbUosdSVh/emXit5xBt2kaaSBAnfkljnlBvskbama/WVGcRgMzhyfH2d/V3csL9CvjUPWajdZUNogmTl5yEy1a7EgK1WSULiQ0TH8LJZ7B1/WGpdATETOTNkLarIkMvNl8k3FpCT8a0XyXpU2K8xOtQ2jwKsgc96mKtgbBW9PBQiIvLIFY+zCL9et1fsZrNYAikVhdH4v1FjpGWzUC3/hNlZ7UhHriFxY0eWrCDM1EQz6r2hj4cgpvEUyUrIcU2rapl4TGjSD9MU+zltg6krIaTND2k0d4rdrt1gJrcjZ/K6O1yxKVtiCZ3V9yE2k7mD7E98MfAscck+zOcNCBwC3fSWb+RqvRQRyoTbJgLHWxUF7/AhDXoWYNsf9NKWxatRo//fLXcN/1/4k3HnME3vbxD2HG0LyX1Ewi6C2EJpP0aEolPrOJEf6ue4B3WghLSVYWBRY+E2N6P67OjGUZXoVG2BdKvI6P6m6y6NRGyo/Egq06wSbY3llQxqdpNZz2XiaK4yQAKI44v6lZbtEzkGgmerGyrTuOkx014ogFsJyVexC6lXdAJVoFEZzNe7mFyd+ZfRKlZxKZEeSCvOwgwI6Z3ewUcO+V9Il6LZwKrCCOY52xRy8lMAFMgPXR2jY4o9dEs25yz5397Yxf0CNG3oInTu4vib/tHopktUwrvDVxGu1GBXqs5W4QntlPaY2OTLvjut7HUulgNW1+lx7KKRCES3hCw7P+PWdwGglvc8nIJ0Tn/mXcJ+MvtEtJchOpj+lDfJOTwN57A3/5C79037kOtN3WwOgmULUC1dnNqb/6ZujdDcAkUp0A6lVQoYNnrhs5AlPNGgL6ZkKpAMMvrsFPr7ga9377Zux19P/EwWd/BDOGhhKzWNs+jUSgcCRlpLdKIl7aoBRshviJUZ4Flzp5sXlcZxOU3aNvks2l5Q69C3QbBDiV5Q/mGvnR1Fuvil3f9RE/MKKdoo0JsDrBfSV9oFgCxoY5q0x3vyU30lGaKjaJsbW2EuhZrVkwbzQHE1VotJGW0PfH88m0baJs8qrYIw1mZUqI0GuJ+4U3i0955siEGNUqrK0VimzmjKqcLqtQsvd+6lqG04v0lpq+Cc3cXmbHcmrihKTPUxKiJdA6T6ZSj0fCj8kaJzdFW2tKZfaXAknQiCHRDDLwyTDRns0zk2SXIfc/O15OEVMRr+2So1+m8X03JcMg2Q4tN5FOI+IDgMsuA84+G9h1V+A3vwZKRTYtUh00PgJa9wKwbhX/DgtQO+8NNWsuC0yKOC+eiVIb2QBEVaiZQ0D/bCgFDL+4Bnf++//Bvd++GW846t04+JwzMXPhNrBmzMwACmp836VpK441AcZMdEEAlLqgCkVQtQJMshaL4bVcT2cva4RhQROgyRjTZwNlGhCKjVzr1Zdm/oxj1kYBNn+aQBZgyqYU+3gZU26h7M5CzWL7cheTPsWsIcbEm4b6fk/pHzUp5+T6QyfqsFWfhRYoM9i0E9BgogHTIisVAAS27crfQYKAJF8ppQhHNmlZoVuvM8FRzEkcTL91W18WEdaMBJ0AFF+wTp3sXhKsaVhZkzG/09piEusJoPHPxzy+ymigDnn621opfja15mknm3orMYc0GyJjFZqa0pthSiJYZRcuy3HiErLI0JhIS+mxAi8zrr32Wpx00v9n783jLCvKu/FvnXP3vr3OTM8+LLKjoICA4i4KzLgHwyc/YzRKfNEIQogB0Y8aI0SMSkAw6gAqBlTE1xjZh0XUNyBRwX3BjXWG6Z7e73qW5/fHU09VnXPP7b7dMy4t1Aem73Junao6Vc/+fJ83YOvWrTj11FP1kAnnnnsuLr/8cgDAqaeeig996ENskZuexl/+5V/iO9/5DrZs2YKrrroKvk5Hestb3oITTzwRr3nNa5Y0luXF+NatA7ZvB1UqwPX/BRxzdPc90KyBdu0ApndxEcq1e4OmdwHNOlR1APAUKGgDtVkgbEGNrGUG6HmY2TnODPCqL+LIv3g5Tjz77zGyQUygvWs9HWMSLTCOtO+QN6fyc47pSGulFGt0mCGdN9a01SH6BhOSZ7LpAyxBOb2mPySCODwGqw6bbJ5NV31fQPujnDbdiqDgBttIwd980QZPGJ9dSZeA0ikNQQBq15gpikYrgL1KARCGrCXeKOAoU0D7Z/NmnMqszTzbPcunk9AMnbm4sGtkWGFvLSMYiZzX5m8c8nB9D6Y2Xa/32J3WkyYI9GIS3SPNSbw3frso1O4Ez5oyjY+U9+difYdEGovTqZIOSWnRTJMosj5P8SXLfpR94nlQYq4VpCGz1+dhMBmfJ03UvbYUc0zHBbg9p+/p+RoMI98Z/DU7wdcXqyyALaJNTk7iWc96FnK5HM4880zD+D71qU/hYx/7GG6//XYopfCSl7wEZ5xxBk477TR8+MMfxsTEBP75n/8ZL3rRi3DWWWfh5JNPxt13343zzz8f119//aLG4Lblxfje/W7QhRcCGzcCd90KDA5amK15iYLiZONmg8PBJx9H/IvvcwXk0XW8Qes6OX14DdTwKJSXw+zYLmy7+JP4f5/7Ao58zctw4j++HSMb188zwN6lX2O+8X0tzYOjUMXvFQbA5HberH1DnBoRh2wijWMec98gANXdDKp9P4AQ6kUyQGjC324YpqP8nGHY5Bxi5V6f1VwJmWJGt4EyDNASqU5zTSKQpt3inMNKPzM38Z3mSxZwG9CRpC0bwZcrWBxS8R0lAk5SayC149wq992IqjD1LM2ts3drsmy32BLgKUbu8Hxdl1Fps6Uy1UdMf0s0Kc7bXDzOju/+SExQ9q6eL4nfrqVhAwsCng7HxG99x4u/nRZootDmK6b3hxM4I8wu605GiE2bbZ3XJFB7JghG/1gHYbFfU2ufgh+7RK2si3jK36SZocr4ha6aQYJgBUCpPFDp63kMp512Gg477DBce+21+Ou//mvD+J797GfjjW98I97ylrcAAK644gps3boV99xzD9761rfiVa96FU444QSce+65GBkZwdlnn43jjjsO11xzDfbdd9/eFyHVlhfjA4Bf/hLYay+goOG5Zsb5MHg+AzZrCCsFJCWdlNYjyCr02G9Bj/4GKOShVm9i5hK2uerx2v3g5fKYGxvHto9cjG9ffhWOePUWnPiPf48Vmzbs3jxyTKiJYh1SHusEec57M1pgFABTO1lTGl7NZtAw5CK6UcjvSzrHrtzP83bz+AAsmP7gNs/nsUVc0d1sDo2oz8DXThSmq/2Z//NQcQqCLdVMUEurwQdLoj9Fkk7HvWf5XiIdXSjSfn3a9hWFNiFcIiZdc6aYrnMFC3smuXXzRYBmHZe0Vpj+2l1DATX2C8ncLKVgYLAyNMIF22IJImXcp9ff2TfdBrP0MTmpIQZTtN1kVB1JzfBzlpEoH/CXDnhtcu1iSyMyGZ55153h7ek2r/9Tm8/JME99rg3T9A0D71nohe6rq7CVErniGL98bATvfz/wvOcBb31rdo/33nsv3va2t+Hee+/Fi170ogTjGxwcxK233opjjjkGAPDd734XL3zhCzE7O4vLLrsMv/vd7/CBD3wAxx9/PM477zz88pe/xMzMDN6ejQDSAAAgAElEQVT3vvctZik72vJifN/5Dge4vP7/Ay67BPYReGyCaMwB9Vn+vDrMDMHvzedDUcj+wcmdIAr5kEUhawuVQagV61CbnsNtH/80vnXl1TjiVVtwwj/+PVbutXGPTY9E8m43mLkVJL9OcT3A2V1M3AdHuZo7EUOitZvsHyuWrRBQKHVqJYb4q4TJpWMDuNcC9lrxr5mq70sPfrG30sxdIvAKJdYA7RX6b299G8ldawFUm+Yox3KVCajOQVTFMkwhXx0gAj/Pay5ERmrZLSLgJWEajWMm2J5nayh6qUT+pTC1BX+TYepKB6TsibanmKDxtTmmzLANatRY89LnAADvFaW0BuQvjXfL2OPI5pTOq+E5DG+ZBYUkzoOrhYoVBQCUYteG0kzT1/TBnDmtfTv+c3naz3hWFT/4UQ7lMnD33Rx+4bYoinDMMcfg0ksvxbHHHosXvOAFCcbn+z5+8pOf4KCDDgIAPPDAAzjggAMQxzFarRbOOOMM3HPPPdi8eTPe/va34xWveAXuvPNOnHPOOfjpT3+K5z3vefjgBz+46HVZXrUvRkaANauB/fcHTDQe9PPx2STYP8J5ffVZYOxhgGJQ35AOFumeoKr8HDC6AWqUNTkKI9DEY2zXnhkH1aZRbtTwilNeiBefchJu/8IN+NfnbMbTX3ESTnrn27Fy703YXROUSK1UKAMFsAZYmwLlS8zIhkZBAyuZ+Y09xP6/Ur+GQfMZ/kyituYm2JxS6jdMkCVoZQ+AHGKRlsW8ZyInddi2a97Jl0C5AmuVYRtUKOvcP/HDLM4co5TitBM/b310SnG/Aqlmogkleg1IE3eyHfJfiW7sH4ExKwKMtwnFKD/NOc7trAxoUzLB1M8V/MR2g2HKdJK/BK4oBRs6b0xbOqE/0NBmhRJjeAIc4JIwhzoacjqQROoiuhGo3X7jfmc+cxP8nd9kaXkpxdr0mRaa3PUmywgS7zufRuc4rbpgTcnQSSdRaLBxVbHMwU3Ks9HROjJTyeLLPHts9tZOHmIub61Drq9VAo80nXGvWU7N7ArPB+AnA6NS12U2PV8iGDRYEQYojrFysIlSqQoAGBjo/PknPvEJHHbYYTj22GMzu69Wq5iZmTHvZ2ZmUK1yPcNSqYRPf/rT5rvXvva1uOCCC3D11VcjjmPcddddeOlLX4qbb74ZJ554YvdFyGjLi/Htvz+wfQeMLb7dQOfBIvaP9I+AqsOsodRmgJ2/BaA0ExxkKbwrgVZQpQrUXocCSiFu1oHHHoCKQqBcQR8BL9/yDLzw6I248+b/xb8edxIOf9kJ2PyuMzUD7KH5eYt0IikEcncZV6HMTC9sMQP086zV9Q3z/+06m3qLGiC5UGbHc9AC+hSvUX0GmN0FKvezWZRiC89kJD59T+Xz7hbwZxICoRIHXikPVOxjRtWsMSPMS/BLDN2Jc5rIIcRdVtxlgGHApYmUsn5Fw2kAgkNEiXic6erfyoOVixRreM5YaGglFFYBcciaxdROLthbHQJiXdkB4DSUQllru21jHqWcjiiWnMV8kYNQACinaLGduwgXDgM3ZiozaD1ml6CnGF+C7joCSXIxk9qK0G9Zr/T1cdZncfKzhNDhzCuzpZlmarz6GvI89ne1Gxx0VihDCfi7aOJirvNzznBSGu0CzTVXKqVAng8gl5xeYrzWkmRN0PP0/gfQAjOtMgv+yBWEyPkrgpo+O0bA0r8zwqNnBUEiUB8D7VPQZGG4XsO1X1qFa/8bOOIIYJ99Oodw++2346677sKNN94IAJiYmMB9992H+++/H5deeikOPfRQ/OAHP8DRRx8NAPjBD36AQw89tKOfm2++GUSEE088EW9961tx1FFHQSmFo446Cj/84Q8XzfiWl6nz4YeBV78KeMvfAW94vX5wqVDxLo19em2umVefYUI1uJIJNgDXt9Ap7eqX7RZocgfn3ZX7+P8gwNwDP8cdW6/Bt269F4c9/2icdM47sOrwp89fTDJNENKbDsn3CZMglM4L1DJYpLE3CyVLoAsVDTWlmEDXpnVCfZmvazd1iLaX1OgW6Sth5Jcm+6008LWdgZrfvNZBFFVyvgKp5nk2DUKuFY1V+eazJBhzuv+MZq7T/4hJWcxpfp4BpqfHQX4OXv8wCxmtOggeVLEEAbQ2Qli+bH2OLgqNcw87Ns2NMnxIhrhnammU/bmdWIpH9XDEf1/EOxUQYoQWyb+LAkB5XNJIQaceRQaFZMH81flube4v2rjOE81QehOpKfoc7MkVyXwC3Z5LgjnZfEYT8GN89imN18XRFfeEWG4Er9U0Pd84srnFXi5RlYZmJqFIAaProEplzrsNQxZUdNFurzo877ynpqbQbFowjde85jU4+eST8eY3vxmDg4P45Cc/iYsvvhi33XYbJKrz9NNPx2mnnWZ+02w2ceyxx+L666/Hhg0b8OEPfxj3338/PvvZz+L444/HGWecgZNPPnnecaTb8mJ8N90EbN4MnPhS4LovpiRmh2EtcIi5Zl6dzaHtOtC/QmtDOjPI9GP+cX8MClqgqZ3AzC4OqClXoXI51CZnccell+Ouq7+Kpx15IE583RaMPvfFUKPrTWi9UukN2H35E9+4EriAXUPxBgR0uLs2dyqlC+u2GBotX+A5B6w5olDSdQLBZtOcrj5PxH67QgWIA1ugNnsRk28F+NrzgeoKKIMe45rn5ukOSGkqzrx1oI3BZE0wV6T2gbMfsjSDrO2uVCqIATCpJZ7PRIMAajeBxhzjXVYGOAKzWWdTb7lqgy6ikO/ra/SaMLDJw+aW3bQiZw6ZY/W7zMkDVGrt0ubJXgUCvSZLbh39KwbFFksNkcVqVc71MsYlRmaa20tfkjqkcUezGV6SMc8XuLIg8zIMS5iWBKOENhCrQwtzehbBU9IeTJCKMjJRx0CEnhjGpu8fxXyGI6l2olLIOB4QxaDaHGhqHKjNQVWrwJqNXLbMnVMcgZo1xO0WVLsNb9U6UKsJb+W6LivVvaV9fESEc845J5HHd+GFFyae/3vf+1709/fjne98JwBgenoar33ta01+3+c//3mT39drW16Mjwj49reBgw8CKsWknyqlMZgNleWvcAgxCci0IKn0j3A/xT4OilDKmlVTYNUUBqwBTo0xIawOQIFQm6nhziuuxTcuvxpPe/7ROPGUl2DV6hGoTftz5KhEGZYHtEbWYuJuDoGei4w1NWZA6AXZ+miSO+fnoOCB4oCvqk/z3KpDltmFbcvwyv38WUuDFRdK3LkQ/fmCO7ICO9LA1/IwugXTdNt+3eYaNA0DzNSoE9qT/Fr/TWwNh+BJioMuO6R0aoTqKpTo5GlJnPd81gxnJznhf2CEPw9DBykDrHlLSSjP1/mKSmuy6Rp5WfPKYmoZwt5iGVvX65W9Zy+MyO3HFSZcxpJmwGZvd/LzzLnNd3vpMwx0rmy+Q0jKJHfu2ia0Kidnz83tk7slBC4Zp7LmWWFiwsDSOXxOdGZi9vJcXSZIAKTupED6GeQacjBSnVJZYu6PWdCnyXHQxBj7UIdWAuv2gtIpVIm10YybmgxioUp92lcORJM7gKANf7RHl86faFtejG96mqszbN4MHHsMBAvSmr1SBwtI7ikXCNh8T+YzInCUZByzGVNMAYUSB564B9hpFIWgycc57aBvEBhYAQVCfXwcd3zmy/jGFV/AU094IU46/W8xOsTmMbWKq0agNsMSV6UfGLQ1/CDD7vXQR9oc4ueY4AKOhkHA3BQH6gyuBCpSc4+rlpuSSqTvGrXtIW3rGoSlvo7It8QaSvN8vY6z/LtixUZP2lllaucqV7REpts8EwwwxwJKVxHdrZPGe4OCJpTyOecvtVcWs95dxwbw2NotnfhfAOammKFWBoBSWQNq63tphsu+wqKtCp8G65brXeEobfEwf7zERz0xQul/vuvd+xvrg40MhFJJxpI+L65Gb9ZZQ3x19QWam5s+KDFvR8sSk7tO9u9kXE7iuZgJ00xJmA7BPh8DxC1pLiKEpi0Z5ERPJoVkAElNTsyPpsqHHp8gzpjUF9IABlKVIWfQZRQ8FsDMmAmIItDUOGhsOzA7BeTznKu8egP7ntO0K8Hs+HwgaIHgwxsY4VJYf4ZteTG+Sy4BzjyTvag//F7qS2Fg7qZcRN8p6Y2EqUouWLPOREnq12WY7+I4BiZ3cEX2cj8nwyugPr4Td15+Db5x5bU49CXPw0nnnInVBx4AajW4i3yBN9vvfgaam4ZauzczRt/r4ljPmJsOliGKbB5fu8Vjz3PJI6KYfX1TO4GBlZzyoTyY4rq+bysl5EraVKI1RwH/LvfbNXbKuBhp2y4GM1ApYVQowWgQEjCwu0wmlARw7l95fqeWAbBJMmhzhKUADKel7MTy5gGP5mXA6YCf+ccq/qwI1JgFoogjFonYVJrLs89W1hlkzaRRaEvQ6Pt2CB8d/kKHGbrXLlUrTF+b0NS0tqCUJtyBJdLSRxfzcma/QsQl5N7zLLPyfN6DjVlt6mdmRXqPqnxB+6jkfMoawNG2RAtzNDF3rVxXhDFHRtZsaieATtOk81cYpwjPBkJN5+GFbWZs0GMzDE2XhtKR1cqhZx2WkkYNtPMR0PhOBuCoVqHWbARWb4TK5ee11NhzwkyaatMs3LaaUKs28J78M27Lh/ERAR/7GPChDwFPPwy4ciswOJCU3vhCK8HJ4ZRSOxkmw0zi6/iSQBzhx0ElpAGlY50sX3KkrdgcToojYHInQ4+VqsDKdVD5IhrjO3Hnf3wWd17xRRxy/PNw0nvOxdpDDtL4moEuBUMcwfnQL5lAHvAMrQEojZvpEIwsDdR85tDDpjbTFjlHDgATj+lx1lCrw3YeokkBOoLRQpWRSPyCONNu8LUSwejm/bnjCaTqe1mbnshe50j+HEnqVGBfoBEUF2Bt1qCUfu65Iq+VZwlvxxPuag7NaHsy6MN5XgRozTzmsTZmQY0aI9IUK7y2yuO8Qiht0iYWkoQIK81g0vitWVpXmhlmmR0XMxW3fyIWsnxlmXQca/8SMTEXEyTIwvVFIaS8lIHYE20timDAyUVD9nzLfDyPn33Q5ilI5K+7pyQXzWiF2ixIsPeXChFGmHUYmHmvkVMMM3XWK62piSkydPxrUpbJz1l4NS/13BJ/HSang09ochy0/XfArjEQxVD9Q1Dr9wZG12omt0AQUILZae2uMQMoD+T58MIIWL1pt3yry6ktH8b3oQ8B//IvQL0OFAqs9f3vd/iwZZlG0qViAIcgk80hko0rh0x5nUElbjiwICHUZth8WO5j/56LGCN3iSNgaoyrwpcqUMNrgFIFjalJfOM/PoM7PvV5HPLCZ+Okd74daw45xGqSAIzZqDEHmpuBGhwGpsYRz0zAG93AvsjE/TIOJQ/CMqx2gw+kjsgC9Gdz08wUK4wBimIfENQ1OHKLfyMYmbKOLgNuzvHfMoc7g5hgKETOMJIBOZaBZ2vP6ZYgtPI3TezFv+hbDXD+TrswBZJAEcdctRSC0MU03v1yra21td+2UGTfTH0OqlLVz6XF/QkzkRJcwnB8Xd5HpczSGb6p5OmQc6TXIHa0HKVsXcpQ1z5USld6z/H9RTuTceloTaP9CROUz1yGY6rFk7O3YjuWtHaeqEbgfBZq1KU0ALWTEmHNmlbrsz4u2D6FQcg6RJqRmRqFob2PgD0r34KIdwmoSWuVBp1GfItBCzS2HfTQr4HZKZDnQ42shNqwD7ByLZSfW1ykKxFMErtSoFaNy54NjAC1WahiH9RIuhbpn39bPoxv9Wpg5077vloF/u+1wHHPnv93QkwMEbIQUR3mOQGgJbLmB7NzyWA9KgDwc5wP1Kqz5kQRUB4EqoMdQRcUx8D0OGhiOxP9VZug+kdQn57BNy75BO74xBU4+LlH46Sz34q1Tz00CQjtEHgSv8HcFOLf/hjK86H2e7r1R+YKDOgsDMAcYvMPk7tWi4lVsWJ9XVHIDEwStYOWdZL7Ppt6g5aGFsuxCcbJhTS+tzi2aRXthklFMBikkpIhwNcywJTjv/PZUKeWohSUp7UFnXBkoleDFhOjfA8MMHGvFJFNt/mYWAej88y4dqclCh3HMQsuzRprO+UqkMszaINOBVBxlJyHMBe31p34SWNJ5M6xtgyy2qXrVyJi0PCgxYS34AToiADjZTA1N3+xq4CTIby6a2nq9vlWCPVdK45Yd1K/d/1wWeZhMTtGOoI5EiFX/y+anKesliY17kwQSQpPVSwnrplZmV0O8cOBYqA+B3rsQdBDv2IM2lweanQtM7mRUZ2/uoQI1xSzQxRw4JXOk6SpcagVa7gk2BO0LR/GpyszmFbtA/77q8AxR8/7s6SmQDZnBYAtDZM6HNpfpjx9oLpVX3cl57DNGmBjBlA5rgtYHkgQdgIB07uYAeYK7MerDKNVr+HOy7bi9o9/Ggc955nYfOapzAAlebvb3OIYmHycg2OGR6GGVwFhCJrYwYjyK9ay3wPIZiqBRGDqBGwxzYRtPtSRxtIsV3VeFVhabNVYy80VOhggS79FUNi0UndjVmuSZftAAv19scwERYCvgxabbfKaCBPMs1nM8SeK7fxyeePn7K3JnWJYocG5e8I8SI4lYWmtg8mDgFBrVb5D7GX8UQiKAq4AQLGFZSv1s5m8NsXX5YsaBNyz+xCaCUrOlqD0iK9XNDPzXD1TCYH8nONHg2UeTgUQR0xMzid2GJn4zQg6rQFWs/R8/txllI721y24qsMiYIQ+nQjfbjqh/bDCnmhxIhAYxmZfKyibN5fpN+1krARYzZD43Me/+QVo+0PM+EolqLUboTbsCwythMotkcm58xGGJ9bduUme++BKqHYLVJuBWrtPMl3hCdqWD+O74grgjDPY1FkuA097GrDtJiDHBycxCSPt6PdRbImza1oAWcLdtbmml4WXiggaamyaCX7fkPahKZbEKeZr6tNsAvVzXBKpWEFrdhbfuPxq3P4fn8EBxz0Tm9/xJqw7eH82ceVL8xwKlqyJALRrxoxJOx4E7XgQavUGqDV7A+5cXc0pjrSJ0JrJ4OV1ikXM82jO8VykUG5zjrXd8oDRjFW6f8PwdRNnvtzT94AWJ7eSn3MO5DxELjFtIdjd/YLMADW+aM4RaHptHYQUVqp3JfnEtbpJsIcQUpfIyj4U02Fe10RrS8K+U2lC0HMAm89phDbAbHQxvWnzI81OMFiDlMHKF3W5JgEu0JqNWDdyhWQgjZmTy/gdE6B53vqv+Ldkb4mmKOtiQvOdPjMEGq7E4Jg+AbteMiZ3PQDWysQE63n2tbgopApKqP1wxuemE+VlnTMrVTiaaxbfBbTpk5ksjW0HPfAT0MROICbOj1u/N9SGfaAGR0xQzW7709LMDgpo1hDPTUFVB6HK/aDpcR7Dun0XIfj9+bflw/gA4KMfBb37PODphwNf/yqQz9kcrHzBagcA+A3nsXTdXg4DBJA8ZEtqSXmXiLjyQn2GvxtYwQcuV4QqlPjWk9tBOx8EoLgqfHUIrVodd33qc7jt45/GAc9+Jk46881Yf8DebIoqcaK0cjd7FgGWddGaHT3+INBuQW06kMv65AuMU+k4/0nMO77VLEzRWAVm5rMTDJItYc7tugbJ7mOC40teENkxGYguTbCk3Ey7ldQuBfosM/hl99pCDDApOEGHxft2PQErAInPlIgBAyKHsUi0nu9rv6/jVyaHkJNos7rfjkAbskEdkhhPSGrXLgNI+zyd3hhdpwG0mlxapt3URYEL7LuV2oWSbC0FdMU86po8AavFuAEh5oayHxepoZsXZJmeq4lKiocwNYDXOF2hA6QtCM4zA+yeosTdnPVOjr2bkGtqalIM1Gugxx4C/eZnbHVRHtTwSmD9XlDr94EaGNpzTM5dH41RagC944gBNTyftTsANL6dTZmrNjxhAlYW05YX4zvvPK7HNzgA/OqnNtBEO6y7P193M2dM1/UDKsUMJu/AUUlU4m40iolz24I2+8mE2BdKADxgdpwrx4M0AxxGq1bHN7d+Htsu/hT2f84x2Hz2aVi//yYea2kgefBFapfmEDGlIxwJ4Pu3m0CpDHroAaBVh9p0kK6tpbTJp8BFaOOQJWQp3+PnuJe5KcYIHVptq0RILlq+BMQhKAxZmhdQ6LRvjhzhQECI3cACP+cEDGWZl9xn6zLZebYzxezfjFrWrFYQ5BvRtvwEwkrStyj3gw6O6kYgHWZkisnqqEAxt0mQhYzcFdpcBqn7X3xRVenXHZ/ul2IG0W7V+f92Q+fDaqaeL3KwkzBuER4lAlP2gpjmXK04i7GoVCi+U1hW1oQo5r78vPXpyTpJbpyn97jR8jx7D3eNFvTXdnlmaXMlka6VGQMzk4gf+R3oVz8BZqcZ4GB0DbB2E9T6vaGqg5CCs3uc0RgBPQYZWgbW6Js1zhvWqQg0sQNqdCPUwIo9O4Y/s7a8GN/EBPDRjwIveTFwzDORRlKxrbvENu/1xpQiB8sHlK6cTKlIsd1oJAU1pTKzhvqiYgWqPgPa9RgH0YysBQ2sQLvewDe3XoXbLv40nvKso7D5nNOx4YC9magWNaivl+d0B4pZC3ETaF1i5JhyJL+Mdu0AdjzIaRerNzFhnJngA9w/DKk4gKBlSiUB0ADYE5wTWKpwRFocsybl5dgv6udNaaWu6y7DzBWZCDfnmPmEodaQC9aEBYfQSp+BhjPzPUdxUlZLCFps7i6WkubDoGXhxArFpIkvDdIsRDTNABOJ+eT8FjDFQ931X6Sv0m1JrTRjfxsGISZGHYWcZgikE/kDHeErfmCAc+KadSaoOpkZEYM4oFjhEkGyTm7Ep4lklGcUW6EMpH+j7HoZf54Wmgha6HAYW6ouYse8E9pcxqr2EohkrDP6NREwO4X4N78E/fR7OqK2D2r1eqh1e7E2V+mHJLUvtQ5gT83xK5Iw5lYdNDXGAtvgSihPceDK7DTUxgOYAT7ZFmzLi/HFMXDjjcBRRwGjqyy6AfXKkJKmyHlbwgwqJp1eSFYPTFcqM3geqNVkv5xSnCMYRaBSlec18RhrW8NrgMGVaDda+Nbln8e2iz+Npxx7JDaf+w5sOOQAay70fJPwvDg/Fv9DcQTMzYAoYogiBdD2B0GTO+Gt3xcYXMGRhO0GE7lSH2s+QZMJZd+Azk/KWYZDMTP2vMYDhcOQAJjwcFdbDQMdIk9aI9aaSthmZiKfRQJmnJzHvBMNA6sdy/Nt66reUoQ3t0DREmcfmFcdx6hT6+kyouzfx47Z2fOspigYl4DV9OX61B7NrC8Xy3r7hgkbfTkKAXgsQMD6WGMR1Fp1/ttuaGACbc7N5W0giNzT035iEe5yOQslJushVUJ0ikPHCpEZmbOU9mEnRQgldt0Fz2ky4lHjaHoe0Kiz5SMMOC3BfSZeXg/792w2lPQppUDOs6XJHTyu4dXsC6cYNPYoAAW18cA/+4TzPd2WF+O79VbghBOALScB135hET8U80APoeVK8SYXRiKHPnZQFuS6JbYOs48krguEUX2GmWCpjzf/9DgQtKBWrAUGViJotvDNyz+PW//9U9j3mCOw5dwzseGwQ2xVASgdrOKbVIJFjc/jQAxq1VnCB4C5adBjv4EaXAmMrAbNTTExK1agCmVboBbEWmioUVvy2iwWRWzqLVQ4/SJN5pQCV8kKrRlUMFKVp/MIweskjDdf4ucjhXjTJkmXCEYBTHI0kNLciBm45CwKzqhjmu1t4Rzt1X2VDspwzZiiFQmKSBTBJLWn79tNW8zQgswYdAoOcjlrQk0HigBJxik+RwP3FRvmJNBdFIXMCBtzmhG2dEK6skE08uyhGUauCKm6YD5Pr5F8qmAJvztPo+X11hLm7zjmYKpc3powy30wQNYpDb/zHovcD702Ef5cZgcC5mYQz4zD6xsADa7iu4cBB6xVh4B1+/5+Nc4/47a8GN/kJHDaaVyB/UUv6Pxegg4A9G7qnEdDk+hGHzqZ29Euu4Qxp1uHeSqtRZq+7Gj4UmKCPr2Tndd+nlMJgiZHgQ6uQtBs4VtXXo1bL/ok9j76CGx577nY9IzDQWGLf0sEtGa513zFajLGFOfkP0UaMDltGhPzrtGQwMTO84AgQPzQL6BGRqFWruU0BuUxyHNrTmuxU3y/vkF+H7Y5SrTczxqgSNtGutXrbKIayZokcwVrlhPfoOQahm1+X6wYAmlWtcP346528jOKQo5mDUPjzxLtmdLahBm7y0yVNQEmAlkISQVFmwRV70Q8OdB5mJ18J4yoI5qPeH5usIg7D1MKx2FInsdMSxBPiOxz03+JCCrWKTCtBlezaGsghHyJzcmFkpNeoSyeqVgJXJ9qYs34vKjOR2bWg2QtBK4vDIFiCVSTihp9jrabTGWaX6DoRkt6tQJl9R0nfJUkZzEMQOOP8phG1tic2Bq7QNToXiwAP9l2qy0vxnfNNcAHPgA885nA1q2M2iLVCXpqPjoQORbb0n5Axwya7YOh5HUAO8DzJT6AorFkhOSbRxNHXE5obprNkRI5OLyaGWA7xLevvBq3/vsnsfeRh2PzP52OTU89gMcgcGISWFMo2whM8a9I5CZpJlOqcI5YRkBPB/EnAloNxI/8CvB9eOufwv7KiR0AFOcWej4wPcYEc3AlE9AwYKJYlECfyAYrOX2LRmBKSYE4v9HL2bWlmLVUIJmHRmQCVboxwaQxzbGZCrOlWDPAYlJ7lDXT908Go2hiOu/RSmk47ti6/qQLs9NMgqLArgvBRueKv0+IvZhQXVg/wEZPShRpHMMAJKcDSLqNyzkXEnVIoQ6oCrRAJhpiXvyGBd4zIB3gIszQBgBZhkdmeqypa2252WBQ5kIR6B/SZaw8EyDl+oU7ZtAL8+qFCS7UlytIep7VKYk4KrM2w5U9TGAKsf+9NgO16aAndML5nm7Lh/FNTgJr1wKtFqhUAj74z8Bb/8+SAwW6N5V01Atsl8MsE34Zcj2pQS0AACAASURBVJKcXSm/2wFIL3cYsj8rDNmvUKzAhMxHOu9IkoaJdHrENKg+Z81LAyPA8BoEEfDtz34Bt37sE9j0jKdhy3lnYa9nHOYEuujftxu2Jl9WyoDxBUV8nv28nbXxzyWJiXxHrSYQNPiQUgx69NegZg3eXgfzms6M8+8GV8FU2g5auso5j1PlCsmxmJfEaxI0WRvPFx1fpqhOypH+wdqHp31RccjMX3IRZZ3T8HVSjgrQOY7NRMqCuee8EaQZAoI0x0/VGZeRJKCUILiqUws3sFluVK/TqSRp5wr8URg6QSjuOGUs8wXfqKTQmBX8w+yr85cdEZNaK2s3QOI3bOuSU6WKFjY4eZyU0sn6ev6FItBsMvyWn4eqaOFJrBiO+W9J9KFnAaQHJug+L33WSLTSVgM09gjvqRXrLIpSzOcGng+19yFPJpz/HtryYXwTE4ze0mqBSkXQ+94N9aa/SeYYiZluNyLnbFNArgDytVNe8rUM6jyYYIrp00S6xTB12nyNtC4JtFIc1vNt3pd7yDIOXLd5EAFoznFI8+wEj61/mH2AM9P49lVfwrZPX4ONhz8VW877B+z1jKdyb0Lw2g1GYPF8Njsqj4miQJTNE8zTs39FTKpBm32CjTmoFWtBc9OATrLF4Eo7rlgHqwQaeb+gk/bTQQ5ENsUkp0GcfcdEm9bERGAolnm+7SZfq3M/lQgvOqgDgA52sUSUJMk/Ci3cWirlwIwtzfCyBAvAsRKQRRRyzY1iqpTABQF1ln0uATkuk5bPPF/jenqJqM3Ms+Ey3zQ5SL83c1GJ8ZKMWZ655ALOqwExm0w837DNUb1zM2zeCzX0XBgDhSJjlpYqQC7PApJJs3G1bFfI2AM+sJ4YYbd1Y4HMmDLjGDT+CNBqQA2PGnALMc/SIw9wesLGA59MOP89tuXD+ADgc58D3vteNnV+9jMgj9hf1JgF1edAzZpGGakDQ6ugRjdB9Q8DkQZqzjlFKSlFrFwECPHfuS2OmclJOoBrHjTms7QJVZuH0hGWEqxhMBAtJFqCuHdtrvTP/haqzXA1iFYTKFeAoTUI/SL+31XX4paPfQIbDjsUW847E3sf+fTkvCm28GEFXbYnl4PyS5zvtgdSOGydujabK3MFoFAEbf8daOfD8PY+GKgOcWmUfAmqpBlUfYYZYakPCbMWkQ0CEeJuQLQJAJv0ukW2mvFEAWuOUm2CAFDMBMd9pkQm0Ikk4CMKdUXrQndYOZUqxpr2BYqfUoJb/JwTTKKsNi5jEKanfUEALFOMHQHM8R0ndnGCwcX2TbdISGNe7NLS8yNrDUgCZJt/7Ef6egpDqFCbp4slYGaSI4dzeRZUSmX+ZbthkvAZfqzN+7VYNnBfbNosaYHTCjEOa4YwyN1qC1pzHCuFvGi3EE9sZ3zdFeugcnm9LDpHcOdD8NbsA4w+cSok/DHb8mJ8p58O2roVGBoC7vtfoL9qzVvSSPuDatPA7C5QfQaqVIUaXs3EdtcOxjbsH4KqjmiAZ1gCI4nUUpbIz0MZv1GPTSTYDD+g+715bcxVGQxVtBHP0S5CTSzFJChErDLI5p/HfsVRobkC0D+MMFfB/1x7PW756GVY/9SDseW8M7HPUc/oHLag0ItZVWs3i5I8leK6gFHMjDMd0QhYX0+xAvg50MwuYGonB+0UiqDHfgOCgrdxf55XfZp9gcWyrGZyqaOWLvwqVd9Fo8ow46bn7I6v3bAIQFHQie/pEDaKYhZWopDvK+bDWDPoXMrnKIEhrjYqJlYJiBF0Ft+3of4GKNlhehoJJCkkUaJvm/QvGpWyzFaek/vMem1p36gERbnRm+6agpztrsdYnwNNjrFfrlQBqv1cnzCf5zVRMiarXXYqzRmm0qDJFoBiyQYleTlb4DeTGTom8j3RVBr83l1/R5YggB5/iP13ex3M0dJPtj9YW16Mb++9gQcfBJXLwNevA556iNbCKGk+FN9RGvE/DKCiiA9Ys4Z4Ygewazub1Fauhxoc5e8A/l2hwtI8kUa/b3eaNbIIicEr1KYyYYAmkktZQtYt3y6LYbgi+wLmXApanAg/M6GTzvMI/TL+56u34paLt2LdIQfiZeedhX2emWKAXg6kfOvXjAIH6HkeX0M3k55E/2VdFwU2fUB5fI8gYGk+aHKeUhRDbTwAqE2DKOIwbh2w464AxU7ifrHMDMvcq3cpnwTUWCoBNOZ4X0mh2HQL2nqtyJhAE+ZKTwi4o/VJcV4Zowsv5/F+IQ2qrLRwAMCmeci/0p+eozLrre+Z3psZDDKxNlnPMO2bM/0gkQJhd6hm/EEb1KhzgdSgzYxteAXPPeL0Csrl2FycOqdL1XgM0krab6iUqUSifN+AKnRqhovVCl0VOqXnma6UEQbI/U5rx8ov2PJOT2p6f7C2vBjf1VcDp58OPOtZwJeu1gfctsREXOQNcf53M33FEacK1KdB7SZUvsTRVcUKm7fqs0B9lglzqY8j0XxHE5jH9KHSREcYYp4hoRjPc9b6ZkSKJrIh3sqVUhfXKGxzhOX0uCkpFLZauPvrd+KWy67CmoP2x5bzzsK+xxyZGLfxVQJMJKKAzciex1UAxLyXJpZKASoPUAi1kIAgX8WRTh/II1Ftm4gZz9wEUOXnQQ/+HOirQo1u0gAGEVDps4RX/LE6z8/cLUP7S0rmHYOyyDEAzz2OGKhbfuzugSi0JmMHoKCzX0oyiw5mBlC7BeV7rLXo9AEissngcchINErZfWgELUdIEktG1nuipKaTNtmLwCDjE01OzLIdvkzWYGlyDDQxxliwff3aJ1fWJlmygp+swR+A2JOuLsEpFpohUszm8XyRzaoC0p3LA0qeKxmW2E0rTGjd5tlaoSyxu5w1z/hW75vik0zwD9CWD+NrtYBjjgF+/WsmArfcDBzxdE2cxSyIpHkQSJoYAetTcYMEZMOKH09HyJEOMFCimVEMmh7jEOOwDdW/gos4FisAYnQU/8xoBjXClS5dKVyPedHb3vM4V08pIOK6adbMAlDQ5pzAqTGuHl8oIZybwz3/9ybc/KlrsHq/fbHl3NPxlGcdbasHyPrZwTNhb8zyGpb72RScNed5GF12UyC/yBihIFvxXgqgal8uhtcyPR57lDX14VFd63An1Pqn2IChQANgF0rJqFSJ2gSQND2S3QsgG6yU9s+Zfst2nFLDUEyTQYv3UZ4r3htfYzfGm1ERIKFBpfe1EtOf/sz174mJ2o3ydEv+uJpipo8vuS9JGKrcR2lNWCpKiJaVzxtmbFJlpJtUgMmfgg+LTaXsLzTaoUS/iqk0p+sXZjBDAyGWYuamqK29Ef9NacZIf5/FBEUr/RNYrz+3tnwY37e/DZx0EjDH1b7pL14JfOLf+TsJBMgVk1BDKT+BNU04U+6mTRnpywkm0OY/G6zRAtWmQdO7oAoFqJXrOQG1PsuSZKXf+uEAltxrMyyx54uMq+f5MFiDaSadapkPKuvxCZESrcTxGVIUApOPMwPsGwAGRhDV67jn6utw03/8J1bvtw+2vO887Pfc4zRQdWdwiy2MWtOg21wMFSQBJbt/UE1EaKvO8xCG1qwxY+kf4Qg5Pw8VMVYnzewCZqcYb7RZZ00jCnjqsjcAAB5bC6jrqia1G1lTdz8ppUvf6Gtr0zzGUsUKCIHOMTW+R/5d4sg5TCfBeiSpXO7VizCUJqIk/cPuATfqUrA9RQjUsGikgaCp3eKh+TmgNss+1mIpobUmEF/SATwyCPHbSdCLe73M70+gmSLG7abVDCXRX0C7c0XWslUSzFxJ9KY8JadOYXJ2Cl0fZDcm6GnA9ieZ4B5ry4fxPfwwcNBBQL3OPr6z3wGc8TZYCRYwPjU3vcGFXJLIvSjiwD+BiJL0A8GZ9FPE26Qo6HtJ/+nDHoWIW3V42t9IYw9znk6lCjWyDmpolSWkng9V7OPDErZ0XbqUFiivXZ+Y3N8QGFioMpfJovv5ArT5Z2onaPJx1gBH1iIKAtxz1Zdw8yWXY9VeG7Dln/4e+73wBd2jFskpwhu2rYSqy8Qs/ogmhRKrEZFNXs+X+ItQa7QFrkbORVcLWriYgsqX+Rls/y2brQsFUMDrpwaGLSNwNTuXGGum0+scyB0nxWxWjsKkXzhf5ORs8fPlkpiqZr4Zq2Lf9DiibkQ0HQgmmmOryWb+QpGZXm0WqlzhvREF9vwIvJ5UQAfYTwfxYbkCph2Hktfu8DsED0eoWGrwzVJax5onmVMcaug8gWiLIxacCiW2OkjwjDAmneuqEoJ3t9aFEc7HBOV+TzLBJbflw/gA4M47gUsuAY44Ajj3XAAxELbZRyQmB5FiDf6lr/OYFEzVZyfk20THyT8p00TXJiYl6P6CJodmFzTIceSYl4IWaHYKmJtgktA/wsTYz7MjfmacI9yKZaA6xNiXQpAEbYOQDJTIcsArDyAFQafp5VhQHDEDnHgcKPdBrdyIqFDBPVdehZs+cilWrhvFln/4O+z//Ody/b55IiVN1XNZX0GF6WIOpeSP+a9ENxrwaUe4IOJcSAUH2cPXaRcx5zP2DzNzDJrst+0bYEI+NaZD3/P8LJSCWrGG+/f8xYF6SxONLyNXjKKI95ufY5NaY473ofJMMVi791JHMK0lZB3RhfZm8gP9n1gq2qB6jefc1w+anmJC3VeFKT3VTXNP+K3ZxMeFYyN7ZkTbAW/FhOlTxpM5XpX4k62RZ1hG0gJoL20BZpd4Lk5KizFlxjEoaBp4NrTqfP9CQVtACpx0n8vD7XhhM+98jDDNBH3NBAuLm/uTbZkxPgD49jeAvfYCVoz0dDmJ8GlKneiDKYDEbkkVx6+lnA1F4tcKA1s2RSntLwQfbBc1PwphCnr6OSsAi3YGBdKmJoZo0hpVqw4aexQ0uwvoH4G3Yi0HwEQRVF6S4R3GHAWWwYqGKy2OzL3M4RPTXcInpIkXEcOKTe5gLWp4NWKVw3e+9FXc9JFPYGTdarzs7X+N/Y87hssQFXSJH02cLKCzDxTKTBTCNhP/pk6UL/Y55jHAELEohKkSniVwpLcoEfcNaGYfAZ6O0GvVGR1meA0zmlBHjhbKFhYuaOrfwQniUcw0QWBfbZd7y2fu+IGEgt5xpIQoB20OZIKyUb3Fin1uC5kzezmqYtKW140aM7liCShVQNO7NJPr52hfY7bMZvzzEepuGiqQQbtd4UXMq7FUVyFYzE/VOR5XE0/0nnVv5TybrJE42mgGk0kg5Tg+y8xKF0BnqknYtkE0gc6D9XKcNpUvsfXEraSgFOZ/6hmM8EkmuNtt+TG+W24A9tsPWLtmt7vimWtHPUW80T0FU3UasAxE8pUAB3XelTQ7N+i82095bPbyPN1/oMfkaD6NGqg+wyax6hBoagwUBvCqQ7oEkCQL61SAXFEz9Sb7yJITnb/FEj0YMy7o5E4mjCPrEOeK+M4XvoKbP3IZhteswpa3vwEHHPVUYHAFg09LKRWJQpV7io+rULRBMVA6KEawNl0xO7YQYwLT5AItp31CwnijwKKWFMu8to05oD4FDK2xzFaCiNoNGDg6KatDMTA9wfBYQ6s416wxx8FLaYbUTXt111mnRLjRv+aaOGIfJOkIViKgPGBxRbsGC4n0RA6j1Uyu3QI1akxEq/08l2YDqlwFBoaSEaZuIIuzptoG0nWOXefqtJ4DV9IaILn/S3BanPwMcNB0NHNcyDIjA3YvcfcPUvmQst8yau0l5u1Eii80Y1NlpNXgoDNhlqU+NpWK4M2DMuPL7jdFZ7KYoIl3KC68Nk/QtvwYH2A3aNC0ByJ9SdaHicrOniN9suZDjg2f/BwnvgvMldzX4HaKlpUMPf59RayRmHEBdr5P7WQ/TN8A1Mp1GosyArUaHAJfrvaQeE4OUXCIQb6EGAoYf4T/9/PAirWI8iX875e+hpv+7eMYWrsaLzvrVBxwxMF8gPtHtAastEnPvY3zNNyo0FI/P4dmnYl+oWjHkaggESfNWQJobXyfkdWwRcMrayDuZo3fVwa1pqec9Iya9ZUUyoY5EBSDFuTyuuxOU+OaQo8RUMpL+iDjMAmdZVe4cw1knYl4HO2Gfh3bwrBhwAJPmvgaQAPF10vaRbsF9FWTqQYLmUMdc3+2TynJBLvOBbux77uRn27MXwg9uUzRZY6ypx3N0TBIOyc7F71+gAEhUHCuVSnGKPl3uwmFxnmnTbby6JxNKAWUquwu8fPWiuSMu3NVHEbYlQkW2Pz/JBM0bXkxvm3bQH/1V8CWzcAnL7Ob321uhedQEsmR1EbkuqANikOWuMQPqBSgfChJhBeiELSBqGWDGKQP0QjdKK/IOUhZkV1SmDMGS/1yfS/NHHweA0FpH0MNlC9Blfu0xjMLmtjB8E/Do1xYVoiyssj5ts/Mm4FiAmZ3AROP80EcWYuoVMV3r/0abrzwYgytXY3N/3Q6DnzmU5kYVPptiSB47PMQc68cSlMJopnU0jxmHGqeuolk+nEJQlpbIFv0tFRhJio1/Pwc52SWNLBxs8aMTeovFio2P1R8xI7GQVNjTJiqQ6CZSTZBl6v2enddIx1YlU8GHelF0EOnpCCnTa3sw9RCQb5gk/vzhaQQ0LFAqdQI5RSb1fOgmGHZuvo1MwhoFvC0zGOP0NPFMMCF+nD7MjSC15nE/x+FWrDyLSMzzDKlCYbiMtCFdkVYdEpL7YlGYipt1tlVICb4YoUFcDfh3hW20x0ZQSa9pkprgoWkW+QJ2JYX4zvlFNC11/Lr8Uct4RDJTiCKPGdDprUNqS7Qq19lEc3cyfUBhm0NYSX5QG6IOgej8BHrTuyzb+YwX0DjX2oGErb54AhRbTc51D9sQQ2NAspj0Oh8kZFQTD6joMrwe+Vo0zERB4/seoyvHV6DqNSP7133ddx44cUYWDWCLf/4Nhz43GPZvFcsW22rXE0Wdk1PxUClFcAm56g3qDSX0CXMn2xOJMAKFfmC9YdCMZOpTQEDukpEc06XsvE1uIAwqwzNiQjx7CS8Sj8jkEzshOof4v2VL9oQeFdwEhxLIgt2LmsuNeIix6xOxMn5GreUmjVN/HzW7oplOxcelN2AaaGGyN5bLSJpnFJoI+ZnfN/fmwKxmGAeQ+C7m2gTmnkYOIKwpBJZwUkwRFkQ0VXm/RwH6Qizc+tHJgeZemmZ6O4QGS76y+kVFAo2bYlRfTwB50/ev8sqJMcqaExPQCa4vBjfD3/IhWhf9Urg9LfBNXMm7e86ulCBCZHgIua16Wh36vEtoRHA9yetARAcPEZY/5QQKKfWW1dm4b4R/1XiswiQIIr0IY0CYw6iycdB0+NQ1UGolRv43mHAvsU4BEp9UIWKOVgUx0BtkjVAgE2gpX587yvX46YLL0Z15Qq87D3vxIHPfxYXJVUeM5XaNGuD5YEumoYHyhWBUKNqBC1brkhy4BLUl7oQH/naaoCsrTiakE4lgOex9tecA4ZW8+/aDbs+Ukmcn0SHFmVv5WhtAGj8MS4WOjfFMHnDo2y2dJ8dEWhmkrvrHwTabTajKsX+uiiAEmpbLMMkUIt2CmJiWOqz45N1FcErjqwQGAVW6MvlbQQ0YE20cYjEnjE4nE6/LhFPMF73M57fbpv9eyVN850R57kk8ES7XSvuEC2YJFiJsfbESJhaASRAM2RMGdqZ6ctlVEtgjhRLAn6d/YbCDAuiGXY+G/suY129vK1e8gRoy4vxnXce8OEPgw46CLjlRlAegOQeVfqdqtLaPOX7SxO0fB0o4sJBCWJHtvdwcU0SUpUHiiQx3jHXiaaolMWxFMQZA4Yc26TjsA2DdemEjitXuwRs4IyrIcnrdpO1wDgEKkNsMgVAM7tA02NAsQJvZK0JSiHlQdW5KjTiCGpkLeK+IXxXa4B9I8N42Xln4eAXPdfOu90ApnaylDm4AvBySEK62WYK3gYtjoQsVQ1W6KIIqmv+VB6bupQHU2evqCtS1Kf5s8qgTmBu8v6JQl0GR+rwMSFLCFod0RPgxPmZKajqADAzgfjRXzEq/+pNoIkxJlISdJJ+HvLMxAcYtGD9kBqg2g2yCDRAtwRNCMh4OkjC/Z24AORb13cIzTRFuFBeZ+qGfG8S4WHPi0ne9hzUGM8Gj8nnJhDKmW+PfsnEGqV9qokz5OsqGtl5pYnrxTJjNMEltgQzFObonG97ZxjGmE4TMq+zmGS32zqmUtEM80XtM5RYhDQzzGKCOVs9Jt3C0AKw99DGx8fxyle+Ej//+c8RRREOPvhgfOQjH8Fxxx0HADjttNPwn//5n+b6IAhQKBQwOzsLADjzzDPxuc99DgcddBC+/OUvY8OGDQCAa665Bvfccw8uueSSnsfituXD+GZmgBUrgDAEFfKg098EeuProPoGGQC3PKgj6BY7ncSR+YO0xJ3C0Ibz+76FgQJgAjnkwPs5TQiFKWpwW7lWCWSVrtAuqC1CIMK29i864dROIASfLw/I6zzCoMlmFrmuqSMdi1wolGYndFK2zxpg1AZWbQINrcX3v/xV3PDBD6MyNGgYoMlbiwJbQ3BwJaTCt02Uz2CCUcCBJoWSLlrbvexQ54I7zA8API9fKqVrLbZs6aNmwxJw8QsKcHW531lTq5F3HiGHEcYRKAi4dE4YMiJ/HEGtfwqbn+MIamRNkshkaZRRkABcTpuBiciW82k3tbWjZMyoLvPLXCJZp4w2f029NCEHkuTUWYssgSvN6KEvN8WBBTHHYRQS7BQEGuJOf660RUKEXsfHbrUqlbyfAJIvmBDOY9hNHbazpZliQlBLTpvH7zlzQfKvGWpylBQGphYoKcVCl5zb5E5DqietSXL9Q5reBeR0FGvfcE/TazabePDBB7H//vtDKYWvfe1reNOb3oSdO3cil8FA3/jGN8LzPFx55ZW49957cfbZZ+O2227De97zHjQaDVx66aWYnp7GC17wAtx1110YGBjoaRzp1jvr/mO3chkYHARNTAB+Dt5xxwP7Hpa6SA5Z1gHufMCdr/dMS/SYCIRxAm9kA/u+JbTmUDqjzXkJ4kCSdwhYaV9MM75jzhMfoxQl1dpjRwJ6h/8qZigy87VDKCoDUJUBPa0YKs8J4DQzzmkAxSowsQPq8Qdx5DH74xnXfwbf3/YtXPtP70N5cBAve9eZOOQlL+ACosNrmKA3a0BYA0p9IMnrKlYSTE0ppUssjXBOZasGeDleC11GqYMJukRchALnOUhlb+N7DXTOYbnCmkkcAZUBNoUGTTYDhS2gTawBRi1Qu81pJYDGq2TkGGGWFHL+pSrqe/s5qE0H8DB0CSRVGQCmxhDveBDe+v2A/iE2NRcrDo1Wuihynu/TrHFhU2MCZYKpJPBFl2/ioAxiy1zQYqGBACibl2ZWKZPp9eDHczUThwkmTITmGWTsu6zPiGDqYnpe5x4FnwkqFG0uokZTUS6TNX8JJj0i1tpdu6mBzAv823Yo3H9eTZ5MAEwWQ1XZ88p6n/hcpW/jrpxzc1dr1HPpeG66P6euqPJ9toih34r5ccxCXtjkaiwC1u15IJeGUgy05qBaMCZvAoDaJFQPzK9UKuHAAw8EAMRxDN/3MTk5iYmJCYyOjiaurdVq+MpXvoLrr78eAPDb3/4Wz3nOc1AsFvHiF7/YaHfvfve78c53vnPJTA9YThofADzwAPCZzwBHHgm85jU6dF0TrI62RE1OKWvq9ByzTtA2gNhGOnYPiGtGiCOLtWh8bPoQKQV4eTbPCmRa0DTJ1eRKf4DRLIzWQdYcY0xEgnRS0GDZQStpZpGACWMGSwax8LRlvTxNTKXortPSpqb01qEYFMWg2iRXgwjawOAKxK0Wvn/d13Dj5dehNNCPLee+A4duOcFoLUok9UD7rzRxR6nCpaGyfDJGWtfrLr4vBxOzWyPJOyT9TFziGgaW4IaBTVeZGWPBpVACxcQJ4cIwJSq1h9bVZxvzc6Px7czABleAxh5lvNehVXCDUoxJSxLxC5V5zfomBUJ8p/kSM3EJdc8g0rut2WSZ9Jz+u17fg8kzcf6c65Kaiuq4nrVzKxxm3yFNN5x+3DmlmaQ5K+5nlLo21b2rqQmvcRmoApImUDXvujgD1R2mUj7mMa8ay0XAtS0p50PlStrC0WV1CGj6w/iv/wIOPxw45JDuQzrssMPw85//HEEQ4NRTT8XWrVs7rrnqqqvw/ve/H7/+9a+hlMKPf/xjnHbaadi2bRve+973AgBOOeUUvOtd78K2bdsWXod52vJifABw4/XAoQcDqxZRuNE1o/TQyH0R6xyxUCe5K3D0Ydok6f5FpgCX7BuwqCGBxrr08xrOKqdNPfoQJJjg0oMGSO7pmlcE/1OwBgEtQeuAGU9BKcestoh7U7PGPsBGjZFg+odx/3X/jRs+/HEUCjls/j+n4KmveBkj1CjPKVCrHfRBi9FkSn1AdSihqSTuIzlQREBjhgl7QRetdTQbikKg2WQMSn29krVQirUoAAgDxOM74K0Y1fPQieAKXCJJIvskNDwKWYAp98HVcHaHeVDYNgEvtP1BoN2A2nQAqD7HGm5fv31+QVOnYpR7yN3UjDDU1oDGjM5T7DMoMns8F7WLOdS+VFnKVbILtx8J0oEjSGScb5J/Ay0w6jD+PTy730ubn8mmGCoIFqpQ/sIKY4bBKvs6YXJGkkGaa5gxUhgA7RZUX7VDLHjtX5Vw0+181n71K2Dt2u5zajab+OpXv4p2u403vOENHd+/+MUvxnOf+1y8//3vN59ddNFF+OxnP4uDDjoIl156KV75ylfiiiuuwLZt23Dddddh48aNuOyyyzA0NNTbwuq2/BjflVuBI48A9t+v8zs5QAC6aXodn7pBAuLPEtOYl5a2nFuZf7sdOCQPo4Fn0kEpXi7lPLb9/0EOpsP8DFExAQt5q+1KqoGYG93q8D0Sd2rWQROPAfVZqOHViAdW4v7rt+GGCy5CvljAln/4Oxz6gmcxIk2+yPmVux7hgJLh1SwYzLGJG4Or8W/GOQAAIABJREFUrAknQ+AgmUdjRlfjLrMQgTjpDzVz1gxekGvqNajB4SRogVIWfqpQYqbRnOPPwxajruSLGhFGo84Q9cSEem1EBNRnQfVZqMEVwC6do7l2b5jEbUnH6MIAE8zDdsx/W3VdFzLSVRj6bBXzPdkyI6q7azLkEnfx+6G75sy/cZiENj1nA633QPrmvWR5kU7AyheJvZAWTNz1IwCKQBHBK+QTtI2CAM9+8QDuvb+MYhG4/35AWzXnbQcffDC++MUv4vDDDzefPfTQQ9hnn33wwAMPYN9998383WWXXYaHH34Yr3/963HKKafgvvvuw4UXXoi5uTl86EMfWswyLEPGB8BGbbVsSLZ8lXWteR2nmI+kFDjipq7uoNxCohIhJrBi0q8JYaakSUI0APHheUmNSbmFSsW8sLsRozmn+nfY5j4T/oouLb3p/Zw2mYKDW1y0G2EqChYlRfyLJi+So0tVTEAcJG/VaoAmtnNqw9AoaHAVfnDDbbjhgouQKxax5d1n42knvDC5DkGLCXyxzBGmk49DDa7kfEQTmFLl4BEzJc2sSEOD6aK0VJ8DJndBjTrBJJJgLkgxrpnISzv/YTFCPQk0alkIMh2pirBt02h0yZ+laFEdxMkRNijS+74+w+koK9YCjTmusFAd5PmV+pBAmHFaYjzOd6aSva5VB8/ffW0wbRlJ3LNTCzRFbwEnQnTh/EPq6LMb1Jz76TIkf4k3vY5fa4Fu8IzzmihyfIZOnyaQy9l/uQKIYtDsDH47sQYf/FgVz38+8Ld/29tI9ttvP/zbv/0bXv3qV5vPzj//fNxyyy345je/mfmbxx9/HC996Utx99134+tf/zq+9rWv4ZprrsEtt9yCiy++GDfeeGOP66CntawY3803g/7mb4CXvgTY+knL9Iy5yrN5OOJbMzZ9r2eNKrEgYcjRihL8oHTkpZbquUORipUhnuYee9psNF9LMHm7URf1e7Px1YK/t6Hxsc19M+gS5ESr5pPMP2gxA5ydBIZWgQZH8cOb7sD1F1wEP5fDlvPOxGGbXwILpcXjMbNrt0CTO9ghP7iSUWvGHuEcwZXrdERrzvoxZqZAFDJD0JU04BdsPpy7IyT/0RFm0gSXRPCS/Ra2WaOPIzarDYzAlsLKsTalIdF6YRzkjsPRauf7JVFsod/mZhCPPQK1itdC9Q1pM6zbUoEr3UyFYZs12bZGEilUmBHmC5gXtivN7FLLnHVt0r+tetPu5PfmfmCTeNZY0q3ns7HnGWV35pVeKLKWCYkdiEODL2yiWE2RYs3uhf6JXz/Hwim5hZHNvfU9oogLVjdqGkYPoFIZKJWglKeVAZ8F2KAFf8UGRmaap91zzz0IwxBHH300oijCJZdcgg9+8IP4xS9+gXXr1pnrDjzwQJxzzjl405velNnP6173Opx88sl49atfjXvvvReve93rcN999+H888/H7OwsLr300t4WXrflxfhOOAG49VaWCB98AKiULZMTzcrL9eb/TbwgC7QM2D6zTFXiDDb/pswFe9w/gmyC4Uq3QmT3mFnKB0eNOabfXh3ryufow1hXqBCiFOuoOUkPILJFcWcngKFRxCs34UfX34wbzv8IlOdhy7vOwuFbjs8gsCxgEAB67EFQuwFv/b4M07brMaA0ALVqLYdfK49Bp5UCNWtA2OZISiI27RU5R0/maWaY8HN2SUQmssESkvgOAKTYP5sv2lQJgU0rVzVP7XxWWZrZUnyFpp+gxeWYCkVghlNP1KoNpoJ8phkzixyInzSOrCYoQN/lKqe/uHlyCf/RAlqaXGdK/2hmlxxAst/07xwhbd67Zayt/avQyYDmb/NrXqJhafD7WKctCZZs0NZ7h1wF1ZrxhZ4JzJ4AWev/uwoDRoiQ92LKBwD27VKrAdRrGihdm7YHhjV6kPb96r2rwgCoDkOV+hGNPwwEbahiBd6KdT3l8911110444wz8Jvf/Ab5fB5Pe9rT8C//8i943vOeZ665++67cfzxx2PHjh3o7+/v6OOOO+7ARz/6Udxwww3mM8nvO/DAA3HdddeZ/L5e2/JifHfeyfr0SScCH/s3ZPsLuHVsSmMe1RUD5OGagqTiHyTWBgol6ycx0GNhsk9gaYzOTZCXABc3iT0x9thqlGlHfuLeykYgxjFAi8D/7NZcjc7cb5FaZEeXjkZJxKH7YRuY2WXq6cXVYfxo27dww4WXAgrMAF/2UnvYY22WyTmmSHdNWjVgmks7odQHasywc75/hAlHbZrzEYfZXErtBlSpT5snU0zJpKGIFJ0xd9dP2qo7hVs10HBb55pV+rXlgGxwlIGL20MMT48jkV9IBApbUO0mqM21C9XACCPMDI2y1K5rG5rpzcMA+Wt+dpBK5UYbrBiT+7yoQ26AhhIB0uuihZLzW9kDNsBlSYFERN1Zm2sGFN9/ZBkXSeFlKUtmrAOAsS75vq26kMt1MrDdCSIS5uZqa26UchRyEntthhlc0Ob91j8EDI5oL0DA1izfB/JlqJzPxYibNahylc9DsZpkbnEMmt4J1b9yUUnsf4pteTG+738fePe7geOPB846S5f4aCcPqdHaoH2AWup0q6aLvrbQvjPBMo4JZl6tytEAe2lp5/JiTZN/yLZIM2jm793XQiScvmOKWQOc2glUh0F9Q/jRzbfjho9+ChRF2PyON+PwV78cXoWjJymOOOSawuy+wzYwN8VaXbGifW8FK0gQmWhamh4DgibUyFrue26CNUNJlgdgEqe7FeMVghTHQLtuEfel8sPctK6+UGQhSiJXhSACSyPigI3YTY/L6c+EqwctnbDNOaQ0uZMJXdjmdRsY1nyoS8kdYdQuI5R0FNEGoTjhv1gyCD2ZGi3mN2Wa/k1KhuPzg8fmUdecmj5/xt8rMG4Oco8kyMucmnWuhSkYnZ4OivFTjEvSiXo0XS+6uXRB/G/puRG4bNnMBFCbBbWaLLBV+jj9pX+In12kGbVUL8mX2R+ufEYnqs1A5XNA3xDXIC2Ulz1T66UtL8Z3yCHAz34GKpWAb90B7LORpU4JJCmUNJKIRvnfnT3Zk0bXI6Mzjno5ZPqfPRkxJ77HmLQwsEQ8Ui9n/ZdBsyN4KMkA0amNutc5gQndWsfqBS3Q9ASXLmrNAZVB0Ip1+PFt38T1F/w74jDC5nf+PZ7+ihPhFXRFDZHKJcjGJcpC7Fp1C/dWn2MGVCglCBczhjaoVef8uSjgwJFSH5srg4AJuaxBLqOyvBsoQvq+4q+TxPJmnU2E7aYuhJzjuRaZoS8mktKa/FJmxXkYaIIB5gsGCs7A5NVrvAYDIxxFOrCCv3cZ4UK+X6lB126yAJov8f8GD1Kl+FVKMJJ7iG9LzHDQQmzQhonUjdqsZZqafTn9G/1XCi6bII0UOEL6/m77fQmiieCSWCu/YvYkK2C1msD0OJvta3OWzvUPAcOrgAoHMCGOgZADwSwKlC58K373VgNUmwYohqoOM3pLLt8dnuzPuC0vxvfyl4PuuIMf/g+/C6xes0iJy8i+2V/LUni6LEyuYMxxHLyRwQS6RMcl75m6Tqoly2bTJY+6Hr4/xeaaWQDYeTpEO7U2BOgKBBFLlRpWjXY8AszNAuv3YmxLuT5sczX1qTGg3A8aXo2ffOMe3PCv/46w1cbm8/4BT3/lZngU2XuZ6vKSgO7ZNAbxNQqhmOZ+UakCyAhiEQ1KiHepj01dtTkGllYeqDbFwMDC1FSnj8oUIhXTZqFktSs/x0y+b1AHyoRa8IiSWKbp5TfPINUSPuj5Gxkw8LZhgAlBQPxRSrHpeGgVM8LqIH/mmOuSZIR0hKCT1K0jTq0ZOMeEt9xvc1mlWkDQ4p/lCw48X9HuOSPc6CknBNDdtJrsKQaYMJfGdnxEuiSY7s/zWKCamwSNbQdmJrUlIw9UqlBDq0BDKxhvU67XyDMUamuXp/jZGS1eW7bCNmh2ii0Z5SpQ6Wf3jf/EZHZuW16M7+qrgfe9D3jmM4Err2QfT1fklh7avFqdlriguH+KrCnJ3bhpP9syDI/ubMqah6RlbZOsYACdqkGzU2zuq/RDykHR9ARrUhWNi5nWBuMYFDR5ZZ3CmRRFwPRONoOW+0Eja/GTu+7BDRdchKDRxOZz34FnvHoLvJRpzgI5S2CN9gnGkdUIoojrDeaLQN8QX2uqQaT6ClpMpIt9MBU/FHicEhTQaoCIGD9W/Ic6oMVEB0vQgqd9vLmcZq5thkmTvuSvE8zQleEBSzeTJhhg0damNH40MutGjTpUscjm0cGVoPHHGEN1cAVH2OoaghSGjE5Uqui6mLGNMAzbPN+gaSDquD6iRpFxQa8XM6cOn2DWGV3UwnR+lhDm9B4wKT+WnhhoM9L7nIhNkrt2AI8/zCk6GnZODa3gVJihES2kydnQwlurxkwOsLEJfo6ZWC4Pc17jCDQ7CTRmWajoH2E/o6cRevLFJzSzc9vyYXy//S1w6KFAo8GmzrPOgHrPeQv8KMWIeg1IWWjD77G2gAa6mH5y+ew8vqU2MVUCDoNSmaoESQRkx3fu4U+9lnsQaaGCnBSEbK0ljiNgcicwuQMolkFDa/DTu3+AG87/KNq1Gja/60wcoRng/FNL+xsVE5jaNEdAFitMzHN5fp1uplJG3qKmiPYjeXNhmwu+Fkom2ADFMjNCT/uYlNb+pIKBFMb1dZqFBMi0azq3sos2o5I6T2L/uuWpxOwHaLgzDdKg6x9y4v8cm9w8X9d7c8yEadM1EYMf5/Kgh34B+uV9wOgGqHX7cuBQsbygRcbCZDW4L5D2De6BvMF0PtqS+3Hey37VDM2g/Yj7olkHpsZBOx4CpnfxHsjlgeoQ1MhK9r/19YPzKyl5tqKAI5Nda4BGVFLK00EyKYD5+gwzOxAHb5UqfK3nMxCFQCP+qcYO/JHa8mF8994LvOhFQK3G0tTr/gr4j49bu70+3Mp1AncwuhSjcYM13Pdi6vQL/JUkr++ppRKCliswUXGS4/9ozfiJgG6SstE2NPQXFNjn1W4DhQJo52NAbRZqzSagf9CJghWyrJJEUwNMC7OzeXvpewKQenrQxHJ6DJjYzgRyZA1+9u3v4foLLkJzroYt576DGaCAfy9qGciCOyuPI00LJSbGQvhdYANh1I1ZW9QzowaiibLU/VNjjiPplGKNqFxlLUD7VykKOG+qPs1aoKx7rgBqzrEkX9BmQeXZKFFBj/HzzGRzkq8Iq8HJuFPpOtZsGXOx27BtivJ2mIHlGbraFRFXnHj0N6BdOk9z9Sao9fsyAk+KESZKK3keAI/3jKRMCDh4sQrk8+iI+uztgbojtmNdbDfpPuMYNL4d+NWPQHPTvH+LZWBkFGpkFBhaye/1L8kNiiKw6bwxy+ZkQLtWhMnBPMOOqN9mHTQzxmkF5SrQv4IFKXmeTzK7ntryYXxRBLz85cAddwB9faA7tgGrh0FTOxnKqVXnMO3+YZauKgM6tDp1aLOCEbI2iGy8GAAEzmyhpfoTNnVKqLOML2G21U0pNrXkS3zV9Bh/Jrl37YAJW7nKvjg3nFyppMYhWiDAPgh7E3svoIOgmi7cMTrjS5gy4xiYmQDtepQP+8ha/Ox/7sP1F1yExswstpxzBo78i5cviQHyNGQeEYNulytAqd+pemGxPTk1JeJglrxmXvCgJMHXTUuRFgacW6iU9eGEbVDYhqqOgGrTrC3oz1EZALUaUKWKRvsJOTHdAVBYkNb1avUAbKRmGGgM2UKSCDtzyhRaogCY2AnatZ0Z4fQuZoRr92HGUOrTey47epSFkJZlhBSzAOLUJVx4Eg7jM0fAXYPk/uqwBgAW4F32g+87/F5BSdoD6T6k5qD0HXD0JEnwUK5gmJMSK4qOFk0i7RAnlU/tBNVnoHJFqKFVSX+fgCRIzMCTzK6ntnwYHwD8+Mecx/eXJwNvf5vWwiRS0uMggrlprhM3N8mhvo05oG8QamAEEKgrMQfwD/FHYVbKY1MTZVRBWGp/OR0A4OYcKkfb6maqBDK0WeLEW9GAnQOVuWJy+JWyJjTp100x0Rql6mC6Hie+myCQ3nO0iGJgZhcT11yeGeA9P8ANF1yE+tQ0Np9zBo46+RWLYoCJNRHhKI6A+owmXCWgNsOaVrECE53n5bhuYRxBFTlFgED8WjQupXQaQ94JVmjw54WyJsCAiBIUtqFyRdDsLqgyM16KQ6hyPwfXxDH7J7OiTN15LJEoJhig1gC5u3nu5TYtFFEYALu2g8YeBabGmRGOboBa/xQ2jZayK3HYcUQ2XaLdtGkqmiGrhHDhWHIyxpIAqwCsMNNuMVMKA2uR0b7hTOacnnvYAuamONUKYL9aoZysniE1Md3gIBkTAZid4PQagM2X/SPOb30rjD7J7Jbclhfje8tbgK1bOeF27FFrlssqzihEIwqB2SnQ3CQwO8lMsTbNm2ntPmyC0XBOCYQQAZEmWBSS/5+9N4+z5KiuhE9k5lvrvdq6W2oJIUAgb6wytrFYxfd5xiBWIyEWwbDYHmPGCGOBEBiwkOwBjPVhwB4GMGAzhhHLeDC2Wqi1ALYBI/ZBIAMSEpJ6r73ensudP+69EZH5lqrqhY8yHb+f1N1V72VGRkbEjXvuuecet6awhASyfQN+tG2TcUkr4mwMb8Qx15GjpSOg/Xcxwnef+8PsPNXS6l2iLPJQqL+henE5ygjUWuLNqD5jN3uj3/EhZiUCFPt/FEQNIuJNY3E/SyvN7ca/3fJt7Hnrn6O1sITzX/1y/NLTfx3B1BRsfT6bz0WW2GIPC4OBEDI8WrwB/7zf4XlDxDX7pmZyBX5tqaU04e/0e8Kc1Jp98lnrTcBpf0Yl3jB1RJU8A/BcTwYMebZXYOpNULfFBpkyPjNM7xC2JFfLnigtNmk8eVBh35VQ5pmQUhNYbsxbkvc5PCsZQuZ5knI8TD3CpUPAzvuwIZw/lQ2hXcvSB1FqIcAl0Mc9/n21ka9S7/XDzjtlj/Y7Xnkv4viZHHAmjdfI57GokXH3UR1hYyRpPV8zMje2vS5oYZ9lDpu5U5mckmWMlgRS/Nhng580dsfUtpfh+9rXgBe8ALjgWcDrL/N0Ff1Gw3C+D2kQ8YJrrYoxXOLclkodZvcDeMFpvtDUNEwoxU5V8eUnoRXhGIVfjDIF2ZDaxTXog7odgDKYao0hYIChMpAwxMTI6XUTNfaGN4Uh9Zj82hvtNU6AMn0DqLlaJZHREpYuX26D6ZkmoPY6EBhmUqYpCIbTIJYPASBQtYnvffuHuPbq92B9YQnnv/YS/PKFT0egyi++Coj3jOO2lqENFWCD1V4Bmjvsqdx4Xi+LfQt7UhWDABdnU+mtVFIIKM1vcvr5NOWCoHEs5atS5/10W0C/w6SJmI2jmdnJhJUkgWnOOiM7RvZqM++RtACyMjJHXMu+X4/QZNzFCjcVI5llnLO2eIDZj8uHgR27PUM4JV8dcS+VhOu1QUmfU0HIcDkrCOpQrkFVm4xCl6NHwPubyf9O56TPLRjTcr9RQ5yxfBktHgC1VmGiiCX1mnMs7K7X9j27sHzS2B3ntr0M31vewv899KHAP/4jMFV1RVb1MYZ0FYsTt/i4fKKkNGEcfn2JN5NqHWZmFy/u1goTD2p11q0rVZyXQ4CtfwVsfnKGZbd4ih7fKNZhob8jiSdpClpZAg7cDVpfgak3YO7/M0BzmmFLKYw7VH1b7zMKEptgBHKnVoKTdZreCZOlnFCbexaBcgLZDK3B8cDTNAE6LWbDTTVhq0BYtRPO/6NOiwu2+jGuUfHa1gp7gETA/Gn43tdvw7VveQfWDh3B+Zddgl9+7m8g3CQEap+XuCSLqVSG0ycSEfmtNx2JpKSf42fmDVDSKZIBe59Rga1n6+xFnvdH/G+Fj5WNqvluYcSs0HjARlG9x7LUNySSuGEEVOqg1UWOF9aaAu0VBQAmxwzZAPb4kCQGMPeu9Rr+c2mzFx5hPMS4EZHEcMUQLh0EZnfBnP4ANuhT01xFvNvm+Gu56qmuBI4gQyTC2lXpI+WBy6J3aN+zPINCqL4nWJhrY4sl62cHfdChu/idNGfZq4vKhdSN4KSx+zG17WP4Dh8GzjwT6PdB5TLwR28Afv8SAMgvLKtZ56C0jdRDRjfDnkO/y/lXQvemQ3eDVo7wPZtzQqaZZxKDvwH7DEn7Zz6mBZtTlriFpH2dFOvw75GmboONSkOeiyl+x/8uMKweE0SckA1weZoszRuvLANRxtcNQmEVmnxpIvkc+h2WVSqXmWyUpc6I6fMZwxTwJBYykmcAsDUVk3GNiFifc3E/92FuN77/ze/j2re8AysHDuH8yy7BrzzvWWMN4NDYjZPy8r+TpS4xvLMmZYIa3nW8g04QsL5oVGHDZthcWKp/MuBNXQ1LkZShSeYG4hFGzHgFMSOSZH4JMcQyTFOBebstUBLDTE0zeSkIeV7Hfacsg8Lm7s0J6wGmiUhesZHdFPlklKfoXz9NQL0OTL8HqtTYq9t/J4tvt1eZJHPG2TA7drNxAzGz2/dQlaUa95zHrXmDOSg3dcSVXL+KB9HC+8/F6QqfBdz6176lKR+WA8/YBZEUyj1p7H4cbfsYvrU1YPduzuOr1UB/8ibgogt4cy+VnehzLhDtG0IgHwucMLmMJHwq1d6r/Ue+cV1fQnb4XuDgD/mz0ztgZnYxLFNvSqzAi1HkhrrQB5995jEfCRAPp8On+ajEqiEDOc1HEZ96p6aZ+GAMyxYlveFFmKWypiVuoPCbxhxz/ZHNotsSb3eKvZgk5ppvpQqTALLMXasvxJRyjeOwFqokt5lsJnY3Ig54PDYDInDe0+J+rtIwfxq+/63v4x/f8udY2XcAT77sEjzq+RdYA2ihKc9IH00vSNmt7RUeq1pDjI7UgtQDDxFvzlEFVpNSx3bQ5WuI4SrOYzsvjXFxrEGPcx6zlI2uxirLVSGFlIbeC2k+ZjywsTxqrwFZCtOYZRHjSt156v7BxDeA1anxzEvyBKKJ2GM08vfVRTbC1TrQmJHpI0n+fuUVItjivIsHuDDv8iFmdN/ngZ4hlOfTOaVzvt8BBl2QCfleEht0npzviZrcfeUv8v8ibOvIdvCuMLKZQA40pZPG7sfcto/hA4CbbgKuugp49KOBK68EQBzYby+DOuucF9NZ51hHqQo0ZlheqSZGIQyZ+WWhQoEvjnrOCUwq0BStLwNLB/nUvLbEMYnTz4LZcbqUpknZgwlYRw8KdcR9xv11cRIBrTXQ6hKovQYztwtmbqdLMra3l777EEwSc5yju87XLddcake/4ypsRyWR9JLyJ/2OVBEIRMeykqdwW6mpcPjE6zV76vXTJY7SYDgY1Ydgj5MR7EgJowELU3//27djz1veicV77mUDeMFTENbdxnmsd8x56b2285DjnjNmcviwWpdByAYvEjRBc9wiJsmwIzGMZrg0jERYpm2gs8KetXpkIMBokVnx8PUQY9F0k++/QtlRGdRdgwkk9hv3mFWaJmJMM1eg1ybBy5pTeFvnnsLXOj6QkjzuYTwEZdS7N3b9EsD7wcIBfrdLh/gAuvt+XKexPi0PVmAcJzGrDCUxHzokDQoYhjDzXh25lB0YSdsZM1fGeMsARC2nkl/HJ9sJbdvL8H3wg8Bv/zbwi+cAn79pxAc8Q9Tv8Gmws85GoLPOC7TaYIrw7E5OAA0imEA31BGQqBHlilEkC/JPhVT4FfFGs74IWl/mmFS1BrPzPoASDtZWQIsHQYuHmdpdriA4+6EwZzxQytkIJbpc5dt0O/xnucaLrMXldewpvj7Np1cfcrTVlsHPOQTH+t6DfiXjml1JzJ6exBomGruR19zqmUJP2sUbFODB42kAuy3eJPsdYG43fnDrHdjz1ndh4Uf34PzXvhLnPv8CBMegVj8Ef/lNIeq4z95yfZpJOoGDNEnfX7/L7z1L+RCSJUC5LlDwaK+Y/ANIIkzUJAa6a2wQaw3Yzbs65byeNOZrhqHAcoE7BFlnyJv3uvn3u0C5yjlnpQrXfuuxILgpiUHxZsRIgWirADTi/U4yQlqkNfD7algfdPGgsEYPc+z+Pg/kivU17k/OwPvi2iCWpytXYePxBE8Bx4c9Kd+xEXHykc1/dhUlGFUH9GQ7rm17Gb6XvhT4m7/hBbl4gH/mkys8LN0uHG8SUZqwMeyyV0jddTZOzXmY+VNhGrOwsF+1yRAqIF5ZT/KnMs8T0gRtocMnAykwSfzdcoXFZLstvp/GVeIeTLnGLLvGHLB6BLS+wrlfU9PMRKtMOUUGfU5fgLnAsjRKgiDySuKMiRdaCFL/7dWTK3zeqMel4+udSmkUmcQETJ5Qxujxbj4MelSx21GXJE4kXzrAaMHcabj9u3eyAbzrbjzpslfg0RdfuCUD6GBSYMj8Fw4Rdgn2O65wbZqI0omXUkKSHhFELGOWkaun5hmL3EHEnz8GPN9Vck1Rgdo0K6MkA1dh3bJN1VMTiDCUdyvzhHpdmErVkWtKHnyqscc0ZiRG2a6qR1qqwPfAJnlKOSNHxNfOUifj5ZeMsl6i9zOdwHFfDOFB0PJhoFIVVOY0oFqzY2ivEfc5LzON2TOveN7guP4W4NBNeXL+NhwEQsQ5CYGeqLa9DN+hQ8Ab3wg8/enAk/6jo1RnCXKxPIUdyDsJe8bC5rJlCSiV3KRumyFCStkoNWb59NpeY+LBoM+5YUQ8F0tVVjCpNURPsQtKExdYFwIHtVZ5bU/PSXL9Kky9AZx2P5hShQ1pryUQVsQ5h4fuAh25lyGo5jzMjtOYxTYGfrHNf5WbWDA5+M2Ac80oA2ZPZcBGyC05IoPdFLwyL8TX8TdfewdrNCd4aOrBhWUmEm3GYObigBg6CGz62e2/pH/9DnsHnTWYuVNx+20/wrVvfTeO/PAuNoAveDbCCQYwZ3S0P97fc73LQbj6IzlApSm/k7jPnqAHL1sjmKUMY+p8iyojvaWckQVgY1xqwAY99gJKGcKwAAAgAElEQVTLVfZwsgRAAFJPLZMKA5UqbOHkqCxwpZHYocwHexgcES9LEyl1lTmJroHkN/ZFnoxoWEhZUzy0Jl6x9JQ+mS8aLmOw0WygeAAsHUK2eICrgEQlmFPuC7PzNI5pE4nCCvIJ9AZ8SBDBAX6NI+42ao5N7FBhDZc8xZyT7bi17WX4LrgA2LMHqNdBX/oCcMZp/PMRJA4kknun6vcwIoTbAwWiq1cTzL+zzif+QZehz6gE8vJomMhRZWLE6gLLRkUCS4RlPglWayLrVJIFPnA14kplVlL3T6+2r4kn7RXkWV1xH7S2CDp0N7ByiJ9p9/0RnHI/YHreLnCjJ1vV6ttADYbU40tT/nMDKNP22cJKToFk+Duhi0UWiwSPuqpPPMp3UH7ueyxF+Ehy0sjzLjeAQUdCjyOeg/pd0NIBYQ6egh9+7x5c+9Z34dDtd+L8y16Bc194Uc4AbmTwAMCMO5iMGiMihjkz0XJNBpwkn+arR1hDORCB51LNyfTpf6M8c4CrXmhdvjThQ54mg5uQYe4oAuozdoPfMGHdh0PVm1ONUyt2nbjSQ5W6d4AiNsaBcQn7CNhjHPR4zWqFAb+ArBj7rQha5w592i9FdFYXOFa/ssCGUGOE5aodg9y4qyCBpnSMW0tbMYLFOaFqQSfjgMelbR/D1+kADaaDU7UK/PEVwAuew4s1kXIxqq9ZnWIdwHLVxSkygrhjAGVCcoEYjMixGo14HqWKJ7uVgZYOc70sk8HM72IDunCA4dJ+i+9bn2YPbWaHeIJe0N7G2vRUqsQa72SuG53+qUQYUcineMDSXGtLnG8YhjBzu2FOPZNz+AZ9JgZU6jChpxVovORZ3xubeCo2yBXGzMFGY2CeY2oGCIXNmE0SBPdP9r6xzFxfR6SQkDHuQGJr523CIxj02ACuLwOzu3DnD/bj2re9Gwe/dzue/NpL8OgXXsQQaNHgkUJ4Q7y/4ecZAYXaX8k8JSVhEPHhKu4xJKneNBGvg1jqOmrBV40XFu+jxZtBEovr8Nhrqsagx0hErcFrQaA+VBvsAek89ubYxKfMHU5l7aUJaNBlb1bji6OuJd4vtVdBB+8E1leBao0Z1I1ZzuUUcshEyTPuiDsYa2FiwtgUFUpTYOUIaOkgaHWBD8Kn3Bdm133sHpHzBtWgl2vWUHqj5A+I16stGEEtFH2yvNAxte1j+IiAhz8cdOedvBBuvgHmYQ/Z+Hv+ydD/U39nDGxdLUhysdLINZagVd7LJQcnkQEMwRCxgchSoNsBtZZZCaYj8ZP502Dmd3NelJ6KyzUE5ZrEBvVEH0MUsd3z6gZuN0DdTGGNI8V9lmJLBnwint7BuXMrh0H9Nky5zp5CfZrro4ngtPU+fOPre6S6gXr5eUdVIuZEtiAEKGBDWcy1snRzOOPgGX1D/oYzwvgUvCSK+6Clg1ytYWYn7rzjAK5921/gwG3fx5MvewUe/Z+eMwSB5v37McbNv9cIT9T+nsT42UNI4CTOatMe4QIMzeu/SyLyEEkSvK9YMqoPKksW97nrCae0wBjOA9Q5WJ8eFoD3h8+/rrahaujSFAKFyRmL3LgVxoeSAUy35eLn3ZYQhJow0zuYzV2pS9UKOKGLqGSlCMert8h9RyGXvrrM6hITxk65L8yuM/he9hASc6ggldzASsOiJN5TFcZoAyOYQwxOpkIcS9s+hg8AWi3gL/6CyxP90i9ZwomFSQDnUW0CT8+dALtd9h7XV0Fxn9mRM/OsHiIT2miAXxljygSV2zl4ke9NWcabRq8laiQpTG2KFWFKZTZQWcKyaLVGnsZtO6n3Cye7WVHZ1uPLWktAa5X73uuCFu4F7b9DJKx2AbvOYGJNVGYDQJnL37Jldzx4LvOg0yByBtuPr1mIEc5rzcGOYmAmvhPfGz22Zj1cf26EkXgqI4yM/eIEowCA4h6TItYWgeY87rx9P/a8/b9h/799H09+zSvw6Bc9F5EawFEwbW7zsv8bax+L0CwlsYMxAR77fsehAyojpsbEAIjEmKRSZUEPAoVmvL4SIJt335Xk6neYOFVrSuWShI1upcb9sAdJGfNR4gOjxkH/rSQyKdA69jCih1mtdiCVMkjJK92WiNQvsjEMQk5tmt7BxBqFJP24tI7AFm0IC6QvsyFcW+J3s+s+7BFqkVgilzwPSDqRE3EYNoLeZJgYN5QWVUYcGE62SW17Gb73vAd45SuBBz0Q+MqX8sQLq4AwGgPnhSwFQYk4UB8PQO0We0JTTdgJV21wXM/XWoylPAq8IL5UFndJ4IHALYWbe4bBelO9Nu8/Gj9cXQCpNFqlxlDp1Myminna5yNvk/eMv4FATWnCEOmRe3jzjgesenHKfXkz6HdBUQWmMcf3VHKLXttemJDfzLO8Z+0ZTu6TQs2SB6ifV+i06IVTxnEeFZIeCwcaNsSZq2WYG4ccwcMfG98gY3gj0WcSCMx5j+7zNOiyHujqItCcw113HsaeP/1L7PvOv+HJr/49PObFz0VYKrnrjzOCI9+tpDGoEVGvQUklPnQOONhLDy99idOVpMpAGkteZoQc3C1GY8NisZkXC1QvsLPO9y1XQSCW36o1LQGLL19gmLorovg+XS1A8ox2yOt0RPyO/LmecsyQVJ5MYU/x7nIGURndvTZftzHLCky1Jt/LjItdb66xUPoyS6ytLwEIgF2nc4zQvicRJMhSfifVem4d2AOIP1Y5Az1qTMGHkZKEd062iW17Gb6//VvgxS8GfvERwE3Xu43DbqCADUsBEtuT3B4/3pbJphEGTDoptNxi9eNyulnmNlR43qYXx/NVUURNxnpUUZkZYQq19DqgRNhuYcQM0dVFrjPXbUn9uznWKaxPW1HgnDegVQCCyQnm9vmI2MtrLbMeYq/NBlcKhjr4tM4bw2ZjCibkGGmW5AySu3lxupFnNAtGUDd4PVRkGRtRmLzSDGUci9HTv+2Lv4EZd1jJQbvepqJzwzKA1eCNb5TGLKa8chhozOJHdx3Bnqv/O+79P9/Bky67BI990TAEqhclhVn1OYNAxKcFvlIIPgxccjmQ91rVQ/DGzvZXyFo2mdwYt8kS+HAhYtbqoU1M2FavLxlYA2U08VuYpzBgMowaQL+vQkTZjFnJGcBAKtXr+hvlLeo46Pv3D6VZIqEMPXwxfE/GMFu71xJkpg0asAQfG8R55gpoWtNRGESWy1tzhXlNAOw4jVmjmgsYD/gwAfC+oLJ9er/NQKFDMGgNefm/k81v28fwHToEPO5xwN13878/8hHgGU/nU14y4J9lKdCRSVwXckm/zxtKbUrEpQF/8uQenrxNCHCbybgA9UbNv55/XcDbtOE2bDM8qYmIcwFbK1JJYg0YdJnUMncK5/z1u6CS56n1e2CmY6E72ie/FRYzZSmf5pUgkWWgg3eCVhf4BD13KhvH6tT/fzE/z3MjjXV5MSOjxlIJLSoI7eemZcJo1byvoveZZSCosfE27lwfjGd7U2D5EBdGrk/j7rsXsefq9+Dub96KJ192CR7zoueIB1jwdgaysYchkKRSaVzs0rhnL3qMI2Fnb25rjl17hX8XRrbkD1mhdFGK0cOXNps76sXmjBGvpc8bNmWSEsHJ6ihV+ff1ppdkf3TNGsBBVxjSVWuktW08Cx2EaVOZLJFMEAmSZwwjUBDwGuquczii17JVMUxjXuKHU86z2qJBZNWgg54h3A0zv1sOd6lL+dCEdn8P2sgI5ta3YU/fg1VPNm7bx/A973nAJz8pidEAVSvAHf8GuvM2ZHd+n7UXz34Igvs9CJjZwfEy/yTol+kpKoCoWKxumOUKTFR1i0tzl5L+CI9li80aQ4UQ7S+cgbQG1xlDmz+XpezdJAPO4eq1QAg4dticZ2+x0wKyBKZcA9WbQn8nZxwmLlQ9VTsjTQr7pTFo+QjowA852XvHaQhOfxAwd4rdhI3UHuPNdITHd9Tjlv9L/sDC42ZyHqNvYNzGN9Jb0M8TwASjgDc///o6LmIIjG9EKQVMCDIAxTFDoCuHgVIVd3/3Dux594fwo9t+iCdf+jI89rdfgrDMSeCUpa7Sh/Z0MzGdoSbPJwLiAKyRpyyF0Tw0G89e15sJYUU8alsaKXHeiPWg5R65WLrMSY0FZkIg6bV5zWgenOS8brZq+vABjWDrJapwtlSsKMiwjxia4v1M4bN6SJB7kHiHWljYg5PJBJbtSh0uAQUQz/nmHMzUrBdrM7lpN/F5e5I72lrhNTq/G2ZuF18jGUhua4CiUPlEIzgUByzzezgOou//Htr2MXznngv867/af1K5BLru72Ae/kguFzSi5SBL+/fMeVliFF38x+ThMhto9ibVpk5OxcXl98G4k6umWgx6QDbIn9xJNyqvcoOmNgQhbIFOrz9E4NM9pUJ5ZyYiLR/mCV9vwkzv5BPrBEbeZhp7ol1WyV85AjIBzPQ8S7J111nRIwiBaSnjtJkxC0JRFUnd5lEYP3sAUOFwVbjJQT0eHDa0z3ne0tAvRe7OfhH59+3HSxOOl5qybOpaXkhiwLRyhL2U7jpQncI99y5jz//3Xtz1tW/hya/5PTz2pRd7McCUjTYh780oTG/76aDdYj4X6e8LBztjAoFUkR+jlDVdWY1FCt/auSWjkqaSU5daMkiRFeqieMaj9EvtyrjLMXUVeQCkYO/w3CN9LkDiwfmN3MYApZ6d0yxVA1h8t4VWhLf9+7krACMMKG8DxZg+2X3EGUTxDuM+ABHPb+6AqTddLvEm0CPqdzmPsLXK8PP8qcD0TknD6HMfShWBYB386/z8CUYwCBlO/SmPA24fw/eudwGvex3n85VKwIMeBHz9KxayGjJyRQJFsMn8M+shehugxmJ8w5SL942AHPy+AFuCGmxybOZvOKHg/XIK1ZiP1vGCARm41IvIg/YA/nx3HbRyBLRyiDe92VNgdpzOnqJ6eaUa51QZwww+XxR7w35nLAYQ99nYVeqgxf1SDSFlWbj50xh25m/A/jFxfDSnkODDbWZUvMd+xYwY/xEHEtt3+bkWN1bvxhhGGYh43rXWOJl6et7FfjxDNLShZxlo9Qh7yKUq7tm3jOve+UHc+ZWv48mXXYLHvfi5CMtlDDXfYfV/mBsrYuKGbwhHwZ8qNeZ/V583GfBGHQQMicV9l+do5w+5JHSVwgujsWvJzl+t1BD3OcUijKQYLLExrExZT9UiLhrHRKGvhfepwvBcZqhs0zXGlU6yrRjXza11+yGMmyfDz+rn3hZUjgAh1XSYTJMlfMCpVGGaO0TAO684NGpMKe4DS4dA66tAFMHM7gSac3L4i0XirJJb77nrjDwQGBHc+OlUhdk+ho8I+LM/A979btCDHwz81X8HZmf4dxrH8ZVPjjYuB/AC1erXAOCfMu0pkdyE96EwADmYUv89sulpzYNhNd6iuYSAeKQe7KLJ7wSOQ5G3ISpklWWOBGECwApxi8kh4thge4WNVZbCVCXVIgj4Z2nCp9Z6k1l7W2lp6p5Lx2BtEdnBu4DD93B+430exFJsyYANe20aoCRXWNh+36uSPvZku5VWvH6hnAyLOctmXak647IJlRt73TjmzoYRe0Nri1xMNSrj3v2r2POuD+CHX/46nnL5JXjsS57vPMDNdF+fwTd6mecp21ilQLOAgz+LcUKSeB2ljESYgN9JqeJpaiJ/j84aH7rKdXcoA2Q+Sw+NYX3cuM/Xz1LRI+WK8RSGMFGFIdGwJN5jcWRHngDcb3MGsDLsTU7y/nRkzLjPjvcCN2qu0op4iXqggnitcY/l8aSUlwlCoNZkNEY1TMd4iJTEbAjbq6wsM7uLDxKxyP1FpRy7Nvf9UYfFqJyTXvtpaNvH8AHAH/8x6E1vAk49Bfjet91JMQwBI/EDPan/OJtPYLE/y7zNNHRMQYUswzLLoq0eAa0t8MKf2bEJySNeUDaWo6froARMzTIBJe7n45GqXK813tSoForWArKo+h1AA+MEhkvXFniB1qeZXaplnuyzwp2iC/CgD41xl4kNy+oR0Ooin2JndgJTM/zvXpu9jukdbHh9tZijXJxE4FzK1UWY5jRvtr0ue3EK5RkDWlvm55qey8fxfM9glC6ob0iJPI8C8P9GIKkqvh+ISth3cB17/vyvcMe/fg3nX34JHvvi5yMqjzaAqtFJ8YBTcCz4YEBpynHtURul3YTz8b+hlsZ8uNODH7z5A/A89hWB0gTorPK8qnCFc6MEGQOGAC1jF/xe9ZAa93meaV1HGGaDliobHirGjk3RANrfjvHgRsX/Ju4fm/cEN+yrD52KJ0+a5tDr8DoEwUQVFq6vTuVJR957pjQBlo+wISyVYaZ3cj3MNHbv0ri+jz22BaErI/XvvG0vw/fNb4IuvBB47kUwr78cW5uE405vOiG2OKl1MzFAMd4y9DkL04nRCgyAwHp7utBcYnIw8pDrvB+FVNxCNf4JcVzVAu1L5i08Ij44+NWg9bMJl6ch2y/iSuYrR7joZ5rCnHIGM9KqU1LPrMyVLZIBctJjo+AWb8g5PtkXmJTp9XTwTtDhe4CpGQSnPYDLOcnzjVUMscnzwpDrSb5UrZ6n2BM5L9hvk7w5H0b3XoodH18EYINrcb6XGMAgxL6D67juXR/E7V/8Cs6//JV47Euf79IgfKUWjRHrAJr8EzgPdsRc9uaiJQIV3kuu6rvInnHqjBGZr1CMi5cwnWUMiyvzsuJVN/eZoCAYqBfYc8Vu+yKXVp3iZ6o2bAkje9jx4c7iu8/FuT2YVZRNJhpS8iegv4aOAU04hmah08wdnO1hdNBjZMYELEtYa/KhoXDQpCyFWVlgQ1iuw0zPujlZKhcILqPmqGFPXhGITgegAR9M/p14hdvL8L3rXcBb3wo87GHANdcA9arLfxlqRw9TwARCPoncYos96vZRQGzsCfCEptYagJShvUodxsKV5KjWFqaU4Lm+Jk/PMNcDu6kVIdEC9JXvkPuur7ai3qmFcl1f/Pw5ooxPpy0pcloqMbOt1uBF12uzkZqaZlEAW+R0ePNyUK++A89TTAZsbA/eBYBgdt2XSTSdNWTLC8D6MszUDMwuERLudznGWanzlSUGCgPHWCwa4iEjZfIGzo/tqkej39e+qoBB8eVPaEQEai0Di/sBAPsOtXHduz+E279wi3iAz+MYoPcOxhq6EZ7mSMhf3zfIkWeKBtBWfTdAuSqHssA9sx6aSKA1PcQMeiLVlbhqD6PYnER5I6V/9trOu4nKUqMw3NKY6rg6D5DF48eiKGPXMk3YPsidlwHkxvAEGIch6JQIlA64RmfcBxExClCpS01OT0A9yziZvrPOgvpTTV4TUalAchkxV8Iy30d/PjVb6BfbxUpF+DubaN/85jfxm7/5m7jtttvw8z//8/jABz6ARzziEQCAj370o7j00ktRqVTwoQ99CE984hMBAHfccQde+MIX4p//+Z8RHgdizvYxfPfcA/zMzwC9HqhcBi67FLj8MtjZpzi6hWWME6FNYlZpSQZASgzXhBEnZYehk+HKMefIJdDGA3dNJcqEJVcmBYBVJ4EaDsAuBsryRTJNKN8LoDGtkcoUgKRSJGCBbe1G4Dw07ZfSlSnjHKSkDyAbXpzavyGihDxzWJLyMPDq+hm32alEnAmdp8hfttenLHVyUmHEFSaO3Mub2vQOzkFszOQ9zDQFGa6+bY8ses9EkvMjJpdkR/YD6ysws1xHEdU66PDdDJNOzSDYdR+GMiFK+vpsOlb+v1FY6CMJM7KrF69l/072UxuVR8ottyTm91Uqc3mszhqTYCjD/v0r2PMXH8YPvvRVnP+6V+JxL7kYoQ+B2uvIuKvhLT7PpGYVd3TOjvD+FP4sVZwEl/9saSKJ9wNXmURJP3FfqhfEQLXpFFXsl410Xd6zijwnMZNhVLosCIDaDMN4Wz1wqnFN+ly5Yhwpx4eC/bH1D4h+073Aew478sb/ij9XYD1f91ntjdnCiyt23SE4pNq/vbZUumD1G1tH0EhlifVlzrusTnE9xbDkDjCjfUDpdQBMTSNNgT//c6ZdLCzwYzz96cDb3gY88IHj+zoYDHD22Wfj93//9/Hyl78c733ve3H11VfjBz/4AYIgwFlnnYUvf/nL+NrXvobLL78ct956KwDgKU95Ct70pjfhUY961NENUvF5tqfhK4F+73eA332p5LlIvpieivwJawy/3FpTmGQ19lI6a1KZveWMZcS0blOtu2rmPj4eD/i7vbYEpjsMpQGs9DA9zwzJJAatChy4usAbQa3Bk29qmlVY9FQr3iR114G1JSenFPeBxhzM3Ckws5wnR6tHQOusP2jKVfZo6tPsUam6fRIzpbq1ImVm+gCIk9un53kMOi1QrwVKhLxSqTnYRD2dvmiXdteAwQCo1bnfUzPsgfWYpGBULb5Sc8SiQY/70JF8sVqDY4NRiWXZVhe49llYgpk/hYuAphnHEg/+CFhbhpnbBXPG2Vx+qb3GK08rBQB8nzRxdeXUw0sGoCP7QPvvYC/wjLOBxiy/byFqBHbsfUJLwYCM2/AAPkRlKUy17raIoTigwIN2yyBH0Em4/I0pOUadlrohIs7nWj4IpAn2L3Txmb/8ML73+S8KCcYzgMdC4PL7bSFJgyG4G+LZD3rOiwv8A4+3zyvU25Uct8asS2YfdJ1WpUibjTJiRBmvs4EIUwx6fPisNbhvPgy6BSPoDODArpWJJJhJhLQhw5h588Xbeyj/tVxExT8Y6wdGgVSm8JchwzTZYCp0aktQ9Tv8nsploDwFUyozVK8ITaXOYvdRORcKyHWNgIteMos9e9jb0xYEQLMJfOUrwNlnj+7P3r178ZKXvAT33nuvHf8zzzwT73vf+3DOOefgmc98Jr70pS+h1+thfn4enU4Hn/zkJ7F37168733vG/+gW2zbx/ABDup8xCME6qyJfuDmKfcTGxGzN2FE+LXmlTWS+n5jhovnf+pKxygpY1ycJwiBoAyEhjF8VZ8ZglJJkncz9vrU20sTgXJit4GHocsPtIocqlKROojLwDFgKXOsuzRmT65Sc5JHavQJkiohFeaDkI2QCHFTd90xAOtNNvI6dhKjoHjAeUmimk+H7gHdezuwfAg49b4wpz+AIcx+V9TvpTDo/Gls/IOA6yH22jDlKsy0UMKN4eT69ppsbFU2tGuLyA7fw1DoztNhTr0fG8aDd4GWD8PsOoN/ZgI+UGQZk2yqUzxW3XWGcSt1mMYsaH2ZVXOac7x5UyaHgxbMFBMzqLXCBKN6k/slyc6mMcveb6/Nz1+uSg28Vd6E600+hFWqfJ0kBhb2gVrLMEQ4cGgN1/3VJ/Bvn/sCnvIHv4PHvvh5iJrTQJxwLMYYhptDKc2FjN9vlgoZpppLj6FkwIY3I6cYYlGJ0I5pjuigieph5A4g/u8tbCjGdG2R1WKqTTGCUt5o0GUPLCqLAsoIMo96gaqRq15Mqexy2GrTedi60Eb9lA2geJVFAzhqbZ/ImNYoz3Kkt+m7kMMwtveDER5l4Tv21iS3Szg0oApCavT6XT5gz50y9O3P/nOIp13YRLs9/EjGAE9+MnDttaMf+R3veAf27t2L6667zv7sqU99Kp74xCfiVa96FX7u534ON998M77xjW/gyiuvxM0334zHPe5xuOmmm7Bjx47RFz2Ktr0M3zXXgF7wAuC8JwB//782NylzEJe3KIs0aT+OBTgYQ2HK4jEsB2USJ3MnvPGb8oSEbT/mlqVSQsbBVJZtqd5TljqIZFzA3f+5QqP2dx6JwcYI9PkLY2NP/EE+fy8H64yASL1hAQzLxB25l2NXpRrMjlOBqWlgdZHJK+Uqi4IHoRhXDzJKE6n4RPz7QY893YV9/IlTzmSptixjD04OAkZhV3239n1rt/nQQHGfJc1KZa5ruP8OoNeGOfPnWIqt3wVlKQhAoJvAiKZSciaKrIGxyd3qeWcpw+m58ZXnTGKun1hRNQ3P20wGIMqY6m/AJXcW9gGDHg4cXMNn3vs/cds/fQlPff2r8NgXPRdhpczGTSS3fPiVkphTUZR8Exj+bFjKqbVQMuDPKbyppJRSxX0mjdnDT5iEhKjsKc8Yz7Bm7lmyjFVJeuv8uagiKMUM0F5h1CRi2N9U6pzm0OuwUQYsyYZaK04mrddyMHutyc8yNeMYnZqKEQ/cv/UwQMTvK02ALJGUnUo+nu8mMxefbq8OryWfpS3hD46DiiEOTP7zPmkG/p/w/g3r+du1lsdNi4stZ6yNzsscY6xwidy69b1Fbw8h4jXQbSFoaEyP7B/Pf1EZH/vfU+N8AJTLDH82m8O/u+qqq/Cd73wH11xzjf3ZxRdfjLPPPhtXXHEFbrrpJvzhH/4hKpUK3vnOd+LDH/4wHvzgB+Oss87ClVdeiXK5jKuvvhoPecgmStJNaNvL8P3Gb4A+9Sl+QUf2caxOS6b4pBD7lgNeVGEkMbmSeGUCjyZax804L8lo/C5ELhdPoaossadolmnKmNQhAXSEZf6seEc2jqPwkAaVtfitNjWwcn3HuJQgf1RCrhp3mrjYpD5fQbjZxuSUNq2xyajMv9dr+cLMqmmpJ0c1pDq2eq+oJJ5clwW2ybhKE6ooQTIOSR9EKRBVRNIsHH4OfUaFMLWqQBC638UDgYQXQUEAU59haLm9ynHEfgdmZid7gmWuvoFMjGNUduOdZSIDZSTWangTXjrAm/ncqUAQgo7cA+p1EOw8HZjZxR5eEnOMVT16fcZArpXTBtU80MSNscRhjPZH565uoPrMKhmmXhjAG/DKEaDfxcGFNq57z0dw22f/BU+9/JV47G++QEgwArv5iisAbC08/14Kb+o9cqWFPGKPhX7hfqe5aIBjeI7y/vRPJUq1VxgKTRP2AmuiaiLQOQCpo1d1605TJPQ5Bl2BQ8VT0UTsSp29dTUqOeKRcelP/oFP1hSlKR9Yde77UDcB1FlxGrb6fEUDU/xd7hr6szHfydN9cJUAACAASURBVP2Ou88GK2+cSPudO9j5BpRzdo3N3Q3FCDsD7dJSvH8Hxh7AjLDKs4xg0r7sSxmozByCX3vmLnzui/p+hlu9Dnzve8AZZwz/7h3veAduuOEG7Nmzx/7saU97Gs477zxceumluc9+61vfwite8Qp89rOfxf3vf3/8y7/8C+655x68+tWvxr96Kl5H07aX4fviF4Hf/V3g/POBq97MG4pCeWNbwXAB4z0nvwWR07bLUibG9NpSVofcRAKf0hxUkeVp7fIZUsMRiyJLuQpMzXE3Ug9G9U+cfhf9BeKrdNjHDJ2Wn1V7P5pXGzg2ZL/NJ3vAnbazjClcbYmNVursvQmBCJUphgXbK6xwUq3Zk+/kETdcNy7pOdFpA36/mtDuE5Hk5E6UgeIuL/QwEgHg/cDKYZidZ3D8MCq7KgSlPLuPdBzVw6GMY3OdFph52wTWlpAduBNIYwT3/RmgMSfFWQOGdQv6h3bU9aBkvfdMj+U8HrnT/+Yb9drsRXXXcWipj+ve+1F898bP42lv+AM85kUT8gD1WfV9+vE8A+ZPFeNeRf1Y/3qWANZlTy4qweQ8mwnPkCZsSLprPC7TOzh+R2JQbWpEw1YjyX0/yxwMqp+HEai4ygZ1ozhe8VmSPpBmtjxR4Y4CkijTOTeq7vejmhow/wPG/i9/HZKfTxy+cWjLiH8M3Ud/XvwZ/7vYTWqvMgcgjEB9zvF8zesr+IsPzmIwGN27RgNYXGTPr9j27t2Ll770pbjnnnvsu7nf/e6H9773vXjSk57k7kuExz/+8Xj3u9+N0047Deeccw7279+Pfr+Pubk5dPzg4lG07WP4jhwBHvIQjqZmGfCevwQufBY23NxtXMt4pzma/D2Bz3gDXAW113hzqzX490HAp6LAO+XqYvCotrmNxoNSBdRwnxoy3HnY4YTGGaDwSO4HwKAP6raBzhpUZgm1KVdl2m4M7rsEd2qEltQJzPjNcLNTz4egxLOnIizrJ2frwUBjaN0WC4835thrXBPItTEnBXlLLo7qv9NcFwSCGnSl4GgAzOxgEtHifiZQ7TyD43Oaa+XTrm0aRQCrb+lD7hsZixHzgPoibtxZw+GlPq573//Ed274HJ72hkvxmBdJPcAirG8N8ChyiPc5/54+47FoAJWQo3EzKUo7qtxX7j56yDMBxzM78p6CEGjO83XSFIg7fGgp1yyByi/LROoVxz2OSykLW2HqelO8R84h3KjZZ8kyEZwekZ5SQENRhCNP8Ho91uZs9qj1x+uAkoRZ3eUaIynVOkxYAnXbuKt1Jh7yEKDbHf52tQq87GXAO94x+t7K6vyDP/gDvOxlL8P73/9+vP3tb8cPfvADlD1L+f73vx+33nor3vnOdyJJEuzatQtf+MIXcPfdd+PVr361ZXsebds+hu+jHwV+53e4CjsAeuQvAp+/yf3em2ymuKFspRFNOLgVvTCMPExZg+eXdLEGr3AyHHciOwFNxZUt/BeGXD368D6uKReVgdmdwPypMM0ZCz0OL3zPE4DoRarXm/T5eUsVpx5vyTX+5ikkCv0djNCtA0wiKw15aBYeFIObpTCKAmi6CphhSYMuaGUBplJxEOnSQdD6CpNfdp7ORrXf4427Ws+rtxiTM/NIJEYkcDMtHQQtHoRpzsKccibDp72OsGGb7FFp7EubFSEP3J+2ALLGpEJ3sPJ/J+NOvTYziNtrOLzcxWfeew2+vfezePrrfx+PeenFCMsV52V6zzL0Tjf6mW8AR9WxVBjSBEwwmmTQFSEpGvO4z2kdnXVmGTfmXZwu7vL8rWlqRLGklniB/S5/tt+1TG1Up2yC/KYqRCjpKyNbcWGsNuxPqKGbaODSFJT0maXebcHooaUxK9VpOD2Kem2YIEC2uggzvRNBg2Ui//qvgZe/nLl1UjAHjQbw4AcDn/0sUKuN79c3vvEN/NZv/Ra++93v2jy+c845x/5+YWEB5513Hr74xS9ienoaAPCRj3wEl156KarVai6/72jb9jF8t9wCPPGJQKfDeXzPeAroLW/M12JT8kYg8ZWI41EcT4mASEgjkt9nYGzsgRQKJZJAesab48wumExYnQURWn9jcMZOEoN9IWX9nTYTCGNU4i/HBE1KC51SPXXXuaJ7EjM1ud5gceW1ZQDECaxSoUFjT1Y1xgjmn8XuWYoHCCJ26tyD57xWA7i8So0LKkSp8J8WlLX6lxJzsuQccrGuIHSKLFYzM9Q72UOGUfKG1tBLpUwOQfQLhfiRJtYDM2GJSxDFffbu+z2YWoPJEqsLyCQdJZg7lTfcZCAxuijHRsyd+bMU2coCDKU8h7IUtO92/tzpZ/FGOhgwWzSU+JmvAatzxL/6mL3VRxWo1wYEAj283MNn3v9xfPv6m/GMN74aj37R88ZCoPm5ucEmrp6ar8jiGYRcUrpVfpmc2zj6NsTeW2ed/6s1eFMWcg0bWMPwaFjKGTObf9jvOW3QNOE0iFKNvcDNlkhSA0hki+H+pBnAsQZOuQhadb4vIYGasGwrNRgoianKh5XCgSZbWwJayxw2KJD2bruNc/luuQXYsYP9kmc+0wm+/CS37WP4AODqqzlj8hd+AfjkJ4BywItd6M6keSoEhuQsYcW4jVhTDkBsfKpTXI0gKlmKuSVvlCowGeVzBfWUKvZAi4FYko3EoXJep22FDcxXRhkFe3lST+6zcMZWY0S+9JYmfCcDbzM1vOlHJVFPMR6Rho1YTr/T33Std6cenmFDoXE2Je8QOVabTeCHex7LMDPuZyCBGNUzDgrPLAm5epCwdRM9QxtWwEV3yTMg3phJP4kIplKHSRMA8hn1ytMECEOQz6RNU/5OyAcBai2Dlg/BhJHEDSvC9iObypDzyoreiD5/d53zGMtVmOmdoKUDoEEfwfxu3tyJYIJx4+VeCSxcyBsXpbFjag567AGuLeLISg+f+atP4P9cdxOe8abL8OgXPQdRqeTgf3uPLTbf6/fUhKwBVPILZawWkpvPW70VsffWXWdGZ32GDyaAxPd6vHFLtYOcEfR1QfuiKlPmlBHUpl1Zo41ikj8BBnCkgROyHvV7jGB014EkgSmVgPos0Jxl5EKdAkVWKnVm6P6Eeqsnum0vw/fQh/Ixo1QCbrqWDaAv5wU97XHAnfoS+I77tpqxKVWYnZQRnxptzTM4FlxUYsp9Wfz1QZeNqrIQdYNRRlSpAhOVGPJSbyPLkE8dkJYzamM2Ai8Gyc8jxtoYXnTdFujwPtDhe4Fuh+sRNudgduwG5nbJSY68a3n3Hvcz9wNRag9kfFxqBAFuw/QWvfE3UCPwYtLPp1VYo+5TvMe34UVO7vBi47XqJaZuAy6O6QRSje8tWU9QIVKFF9OUNw1VAQKYmNHzlEU666Aj94KiCMHOM0S3tA8EpSEyzdD9VRR60AMt7AdAMLvvz9cc9Dln0Ca6jx43uwEXYcNkAFo6CKwuYEEM4Lf23IRn/tFlOFcN4LE2H+UYIQVHqvwizNyj8f7ytyMe++46G8PmXJ4UkzDBysKTGmDQQ9qgxylEAwlQKRN0kzAoJ/ML4atclUc5fgZwpHGjjNNf4j4fnNaXOccuy9iLnZoVhmyD+6IsYiI50NdzYu8n23YzfA98IPDDHzKAvOdTwCMezj+3m4L/YWP/4PhOH2gtgzprDF0CvGlVpP5cuc6Jx8Zt0GQkpYESF6MKAp74cZ9zkLrrzrBGJauGbio1oVmXchPOnnwV6iQSceYun0hNwIa922Z4sttiL216ntmToarfB/nTbSC0/Ey8n2NpvgdKEKYXecbFjDco44yqvabzHO0BoPDZIYNkx148i0GP886CEFRtyOsXL1bvoQQLZdXahH4xxqNy/sbFM7VXcn3SA45Cs4H3HP0uaH2F3830PP97bZHjJtO7LNxqfKX93O14g6Zum6GlLAEduJO9plPPZMJRqQRTbWA0QWW475TEXINx5QgWVrq4/oN/h29eewOeecVrce4LLzp2A6jj6Ne/LMKfsUd+CQKYo/T+crfNMvYAO+t87eY8G4IkZs8OsFAoGzX9Xup0QTU1olzl70pS/IYGUD1aY2zqxUgDOOY6Iw1cEgNxj0sVddY5D1bjzQq/N+eAesMRdTIPuVEBi1LVyx892Ua17WX4br0V+JM/Ac47D/jP/9lV4R5TLJU30Dw8CMjfU1Es6Ld5ovU7vGCrUzD1GU64rjV5MbdXGMqMKgKfjoCxNA9P1C1IPZ4k5okZlThBt9pgo5fGIp3W4mB+r2uD8Kbe5GoCpfJIKvcxNUVfc56UGBcD2NyewBMk9r2JsQbPg71KNTmljhEQt0bVQZYUhCyr1GtZz9toTmCa5jbUIf1NfQ5l4ClByS8Npc/lQ7cmkFSEjSG/3P36HZZ7q0+7ryhkqknk2g+9VxACrVVk64swpSpXtOi2OOWj1nCM4ZF3lpt01pgsMzUN9NrIlo8gmD/Vyshp+o1DmQseYJqAlg8CK0ewuNzB9R/6O3zjH/biN656Hc69+Nlbqgc4uqveO/XFry38KeQXKXo7VCHiWG6dpcwK7azx/aZ38NyJhRQTloYEs50X2HFGMIjY+1MCDSbDoM4ABvlq8Pr74hesGk0X1Os6qcJ4wFqktQar/DRmQfVpnp8676yRy9z9ylWYsHzcxvGnpW0vwwewFs4vPgyYmc7/3J7eAwd3KkQlG4/xk1dR/Drx5mE1OCUoLpXE9T9TqmwyKC59GPSAThukQfpBjw1oowk0pvnkXmG6NeuAttggZ6nzIqOyGIFKzoPM98PYOmRW7T5XPmcSvOn9PAhBCIDOCn9nki6ijadNuOaosfH7Y42f/168RexV5M4Z4n6XTUK56tIGcrEPL5cSxJ67CWFyHrEa/aQAn6qxV0/R62cwfPBxD1Z4JjXWKgcWMrmKACk10xWUwYCO7APSAadElCvO46vUAAT54ZWYpU3tUDLWzA7Qkf1cT3B+t0ukLwgzc/22w6CVQ1hcauP6v/4UvvEP1+M3rno9zr34wuNkAEfH/3LC1yIJeKzw59Dt04SRmM4ar6HGnCunpKSbUi3nMVOWChnGW3+VKU7h2QQMOsoA+uNB68ugu74j5ZIqnB/amGUjNzXtpUXJ/yjjcdLcYwnVsAjESW/uWNv2MnydDvCzPwO89jXAS/6T/FAmLsCTRBNadaKUtCClTpTxj5vbWNNEo2ww/S4bpK4mbdfYEJZZc9Goikmvw/BkawWAgWlMM/Zebzg4oiQyT15yPPpdKIU/9zpUZWYg8IeqzaSxzVEy6kEqaceqhIRWZcX4yvub9Wp0dI03bgRrENhAeMM61NhU5YgYxsgziKGJJFaaJiAEMOU6J7BrEF5yr8gY57l7UKs97KiknJ/Dl+v7Jpo1WmzMycgzaNzPGAed2usGYKLM5q7Nc1RgWyUBWRhXNrMkZgq5MVzeaZXrqgWzpzAbsd+VRPyyS02wV5fKGEEAdNsM6zdmRQS9zVJvQcD9jkRmbfkwaPkgFpfa2Ps3n8LXP309nnXVH+JXL77g+BhATVXROWjhT1mrQn6B8ZjFx7FxjuCa5HJW86SYLGOjFrHSEHfPHYDZC+xz6KHWtEnxY58V4GvGfTa0KhXnfcYaWj8WqocBy2YWLdRyTYzcscPCJ1u+bS/D94lPcALJg38BeP3rQLWqm8CyaTCM4gXRN2jk/y8V41SusAKJMgL7XS4Xs3gItHyEvUIQZ2vOzPFpmwx7R815JpqUj66S9OY6rSfnxEl/geFCo3lLWcqbX6/lVPGjkos/FrxHALxB9jowzXmY6pRHbtm8V0eAeLpCLqKUF3ClLhCgby3l70XSjf5bmac2vid+n91MIws9w7vqyGZkw6dk0qfcwUMNfC7tmdwJXL05C6caB+/J7wnGed2qlEJkSTJGDbofr/G9JDkAkCrKtFeZ0NCYBVoryLrrCKZ3CJlmYElXxj6v9EMZx0Rcgb7C8WVqr8JM7+BNeG0RWD2CpcV1XP83f88G8E/egF993gUIS5sstDZ6QD0PeET6g8wVi2wcZ+8v15W4z6hLr8XQcm2a51esAs1Tbp4ZOMSm2+KQiDFcV7Iq5BkCcrAuYOeMFX9Xyb3imCQqp2dYsahUZSbmTzHT8sfZto/h+x//gyUBOh1QpQL8/M8iu/pygDKY3feH2X0WsxvHtrzHZz1ETebOqbp4TQkM+nPf49AmdGnqdyRvaGBL9ZjKFBvEQq7Rhq3YD5tTh8IJkAAEHM+IBGLpd+0Gn9vIU6lL2O84ODRLmZVaa7CKflRiA5jGTAJS7VLNifRJKMVYXUZweoD5Z7VxOR3TosHLUs5FpFSK2pZdTE6f0Rh7P1dx/tjjRM7Tz0DdjsRjqxscXFxfvAFhj8sAVufVGjNm8VovLdjgYKZsYGMcQ1jnaZbx2Mt4UHuVx2RqhlMl0gRmZof8PhhZx45UU9QErERTrvA4HLwLSGMsLa5j70f24Gufvh4X/Nc34lHPfdZxMIAT4M9cxYTjQ34Z3xWSvM01Nrq1aSHFcP4hlSqsvaukJzk4UHeN11aa8EGu3hyCQSl/I4faBJHUM3TNKIO6VDCMJ9sJb9vH8D3hCcA//ZP9J0UR6BtfBB5wNoJNLhB/g8OgD/R7TC5ZXQBWl1ifsSwqD81ZYHYnzAzLJ/Ees7mhoiyTvKGuGMM2f7dSZ0NYnwaa8w4i7Xc5YVw3M7uRe4bYKnbQMW8IdhyEFERByEYuiV3aROhVTlCot7PGRt0YNobVKS7/U63bDZ5KFZioBqOFcIfGnvLPMqp3+mPPoA09sV5rEyxRbpJ6QrG7BCAJ81KOaQRxaUtj6Ys9p4l4MN4nNRfTT8Ugyh9kCkSioWfWOWG8+2p8MssYQtSaf501hspKZWaW1ppMjEligZnzlc1J8xdBwL47QJ01LO8/gL1/8/f46o1fxoX/9Q/xqBc8B8GEFI2NB4wwlP6QI78oU7LikqmPy3y3/8t7oIlAjOuLLExQrbM3ONAYcs2mNRljxEPtyVoQT7E+w98ZB4PqAUjZ32EJcBnA4m3Wx3//ZDvubfsYvosvBj7+cauPQ5Uy6LavwUSh83aiktusdUFp3G99BdRa5aKmQchwZHOG42+afKwEmFDgQvU4NBi/qTQBM/JzlAycIex1HLxTqfPikhpt5lgNnCVjDMeehmN4Br4IFxuOEBSGDO/0WlJDL+S4ZLXGBiJlqS5LFlDJMD+NY9AHDboSdxSShZCDbAmYLHU5cWnCMFJtagubqu91eZ6njoMeHoreDiAM3IElf+QMnpHKCGPEz9VgUtwHtNadntrtdXxIt3gBebf+ZuynbPhGcTOs0yGUglx+qgmYLaseY7/DY12f5hqEMFzNIomHxoIoA60sAIv7sXzwMPZ+4BP46mf+GRdc/rv4lZe+mKtBBIGF8jaNaOj7yobhT0t+iXtSMX1z5BeHJnjGTQ9RWeLSV3QuqhHSNR6G/FlNUcoyjgeGkZNhq9ZhK24oXNld5/lLKXuOtWmbdzmqt5xKMXAoCnkGMCxZrdOT7cS27WP4vvc9TmCP5cR++eXAFW9ElvQ55627DqwvA+vLoLjHBjKWEi8lKVq6YzfnVh3LiXWzzW5quvhUq9JI/AcSQ+iDBh02NFodulqX2mQ1llvbsBmJnwWiMJPfsK1no4cBY6zQ71Ze/mY3NkIEyhKYROjhQcj5SWJM0e+CjIGpNiV1o+E2EiWqaLHTTUpLuZvrxpe5zQ/sEREBtLrAkHilvulnynmrgx5o0BVPoJA+sJXDSjGe6f9c547+LpMxUfjUN+6jrjHuXprsL7FGAvjdJANOlq/WJMWizwV5peYehRGvraUDWDmyiL1/ey2+8r+vw4Vvfg1+5bnPQqDejHqT1SnpbzB5fP34n2/goXBkj+eD5v4p0Sn3TL73JqWmopITmyhXHYqh5bh82Hls1zK3rxjDXp0hRoqisjNQxrjUqM6qLYTM8OnUxgYwKtuKL/ZzUcUm4J9sJ6ZtH8P3x38MXHmlNXx02m7gu98C/ej7XMW7J5Wx53YBs/O8CCHxom6LJ7AuylqD6cS1hhSyzBfvHG75+GCu6cFeNyu74SIPYdlLGQd3WKiFySeUppJT5MULjRGI1Eup2Cg+5PdWYzl+nTFfaFiJKGnC3l+pCjTm2OAOumO9nrH3G/K+Ajd8BSk0AsEkCdfGs0zUkoszdlu8mcQDppXXmkwsiEpiIA00WX2sgSTNpfPer5EY0pDoAQAETCZJY+c1KbwbOYadt0VjrGdX6IdtR7OhjYOF/aTxzRpEa3B0TMSoAgBl/PxZygawXAF6bUYspma5IG57BSsLK9j70evwlU99Bs9+2xX45Wc/HYESxIKAwwb1BhuPqWnum2ibDr2nEfE/+7Q++SUsDT+bb9RVPi8qO0MaTDZw3kgOj7MeZLJE9pE2z4F6060rSTGwh0pLhmnxz6ZmOXYeurSc3H2VoKY5wr4BLNeGmaEn23Fp28fwvfa1rNMprDpqNoBbv8rVBCLPcGXKsDMes1O8rGRgjSB1JT2h15YTmmcMmzvYE9Hv6+LTytTwIDRLuJBbbdIobablcwslyX7QtbmF1hhqbmFY5hN6vwXqrLNMkS06G7v+azFaLTx5FAsrZ+QykhglXLwpjNxhwK9SgTFeVnEjK97Hpnb0QekAMCE/X7nGn+qs82FBJKtMdUrqqoX8vuMYmNmFIJTDhlaAEOm4sYtA4MaRXt0oMlTxu0Xm6olu2p9iwVlAnhWw269vNIB8P61B5b+TCownMSgsAYv7QMuHsHLoCG788Kfxlb1fxLPf8gb80nOehSBi0QXLPDaGPaJyBWitMis1ia3k1xDJSeeQjp3Gn1NN0g+H42FbiM3m3pj/jjzC0Lh1QWnKNQQ1raTakIMrH1CtGlOW8t7SWeN1V29ybD8cDYNSmjiRDIFfjY6NGsCT7bi17WP47rgDeOQjbTVgXHkl6L+8DGh78ILE5cYvAONtVvzYlojiG8PuOm8StYbEnRrsKaq35S+IYyGbGK3CnjqIb4Nm8598rzBLeNHporGkCoF3FE7ZCHqaeF+/b4QhWr/+3IS8iNtr/C5qU5OTvo+lBWJcKRExa+lPEgus2uaNu1RhaLJaZ8PZl/yswHBcUg8I/Q5fZ2qG1VXUOG4VwsylN/wENAu7wzNoxsGeOQPuGepRsKIahoxAxrCs1sJ+rB48hBs+/Cnccu3ncdEVr8Ijn/8cJp1prqbGW/U6cY/fX7/D6zZNbKkh14eA35E61RmJFJnZNPllvJErMIuPYn5SEjvJwlKVDXsS81qr1N2hY9Bn9adBj+N/U7Py+w0MoE/sMoEzrCfbMbftY/gA4IorQG9+M3DWA4DP/C8gCu1JymkfToAli81Hqbx4A2lFhh5vntRruxicyBkZgUlRmxoq5bFhCyMgKPH9k82SZrxu+5tUllniTK4adRBJOoV4heXa5iDSMAKZiPs16OVP4JpMCzjPYYRotW1b2UzCEntnyQCbSgovNAvr+rqp9v4GCCNkaQK0VtigKYtOBchFLNpIGgriAZNzpAiqqdZtQVMmQ3BM1VhWKX5MXp3F1Y+tjSLEaPwwV7lhgviBwOYEsMe9uA+rBw/hxo9eh1v+fi+e/SevwyMvfAYCJT/pPaOSN4YQRqpUTiHIxl9y6i4qCC85lSx83eX3EUbwUx+GIEs/BqhzdOTh+NjGlcv/rLlwShCKVGHFKbmkiWiLiqxaY5ZjgeKJ+30iLZ3lQZ0GkHVd/8k5VG3Ttr0M39lnA7ffznl8N14LnPPIzXkwqjKCzEEvQ4nTAldKUVFdVACkwnMXNOjxxO22xDtcZ+y/XHXGsN5kL/E45ebYCtNWQSSQiuEcHKdM4phhCeaUM1m4ud8V6SWFSNvuVFr1INKo7CCpSbCd/C6Xq+RvjiBb0BJhCdhxBoIsYfjzRLYwAvX7QlgReSkolGp47PxTfv6h8vu4joHRGN/AKWkQXOmXNGbjWJ3id9FtsYEMQn7/ZdEp1TQFgey25mmrd+TFJTf9veNhFOGNm46hsd4XCXElZ/ClBBR11oHFfVg7cAA3fGQPbvn0jbjorW/AIy94hhvvzPOk1fPSEmK5HD8Zx1igRFW6KVXEQEoeqhrHccesoQOYP07j/n6UQ6f9VeNWrcPOIZuyILHA9gp7g/UGlxAqsovheYAihK29ZAZo/ccHof87a9vL8H3gA8Dv/R7wq78KXHetg2vGVez2c4YsdFMweMc4cRgqbeeNYbclUGmTldSr/KetSwZwPyLRmcwksdwvRqoC10nMM92PyxXpzpvwrCjLRBhX4NF+mzeWklSQKFWBag0mqnKMrDRMbrHxNhtzU7Zc6TjAmQH3gTLxgic8i/bDb3Jv6/lpLb4scwnEWsnBVj3fRG9zLFEvFhZGLi3CAMoq5DhjzONXmeLvtNfYI6iIRmNY8uo3RicOCj6GZkc38+akrieFLrNU4OYUgMCS4nFTpwUsH8DagQO48WM34JZPXY/n/Nmbcc7Tz0cQyjpUebhiXDIZCDMzYfiweDBTJqXG+3stj2XrDOfQePrxzuNs8EY1IuI11G3x9atTbvzKdfccnXXeN8KIqy+Uazkvj3VZE55rng6oAU4yQI+ybS/Dd+QI8O53A+c9AXjMua44rEAu0CKjQUHf7sc8KSwVW+jQpMYwiV15kfqMLGq4QrdZJhtmXYxcfkO0G74UTi0mIHPLQ73ke7NEDqI0RoSSOwKTyp+aW2j1SGv5TWdMflm+H2qcfWNxHMZVnz+JufSPCYD502AGHSE+VLzNOQSivDjz5oydbOCZxJK98bLXsJ6KHw8bzaS0468PoOogAOc0RiU+NLXXWGFlasbCfJSlXFxWK18Te13HczbnoEFFFFSmzkqnkduk04Q3aJVIs2okzogY+x2Aeh3Q4n6s79uHGz92PXuAb38zznn6kxCEIXIHGM/AkR+DTGJ5Jxlv/squVaayasgvxQAAIABJREFUFmONBxzy0NxC/6CrhiSHbJw4z29onImc/qcJhNgjDNRI5m2/w5yFNBGN36btvzWAavA9RMkAEv8rnTSAm2zby/C94AXANdewyv2heyUp1WOv+aVQhlreIExuhiemTqQslZyiyTqP7j7D9yCAT/0qdq3eYb9roVLUhVlanZL8PRJqeeaSrcd5B2GJ6wcmEq9SjUsT5jyySZ6FNdiWONOV03fZlkxCvemky/zYw/FovsyXN4bWi0sTWH3O4d7D3yRyP4ORxOMAgOh/jmubTjtQj8U3hPAOXOPm4bjbegcLWxBX5l+vw7mDYcTMwGTAEHYQMns1CEQ1JvSIJPn3kjdw5OZyFEm+a+C0VAkOauz3LEGFDXFkr2yzQDeRPkH9LhvAe+/FTR+/Hrf8/Y14zp9dgYc/9deHCWNFaNon1egBLo1hWappwmxJsD4mmYAPFfa7MhoEPuDBMARpNJ/vxHp+xUaUsQHsSyxexcDLwkJOE4ZB+x1ec1N5GDRXfcaTQTPGMMpwkgCzYdtehu/KK4GrrgJOOw249RtQqrWFmuzpDhiCA7fcjn4RWM9E4EDqyySXHCNTrjFzsDbN8ZL1ZWBtAdRZE8PYZuNebdp0BTTngFojJ8+W28xGPsJRGKaghMwEwMoh7kupwqfLQc95hwaF3MLa1gk+m2gEwFZd1+v3u6xNmWVMLGru4I1TjeXRwNc+QUfZhEOlkjbqbMEjVnhdNUZzfdL7wH12s7cBhAEMkSaLQXHPnfrTlKXKjGEjSRkXMzaGkQaRNTOBKBQlMfclks0ySdi7Uph4koBAMR1ibG6k95VBD7R4AK1778aNH7seX/2Hm3DR26/Aw57yH91hSt6h8Q1gkWGqf6cMpPHHTA4gWQrqd8Rbrno5rDLWWYbsnu9xTmKtAbPzDNY21ZjZjxF2pixzzFDLvg5FBFu9wBWrNoVSNT8WGocOfQMorNKRB8STDdhOhu/224FzzwV6osry1rcCL/ttYQGSE5JWPcQcwUBhkcAZxeMECeREoLVQpBZOtR6anCz1lr6sWC4tgJc6pakYGYFG1DtMEz4BVqekppjk8+l9ylxnzFA6vgjspGfR5/Cbv2HoViQQqU2nGHQZrtFcyGodMBGMOcqDg3olcd+9R4+pObwxFTyEUS3gKtygxPMot+aVbb6JYQN5MWizOfkx+33y/sy3sQceqzsasCFLUy50qySLbotLHlVqbBS7LfbihIVISZ+NRVTOJ8ZPtmWuL8W8RWPG9pXiPrB0AK27f4SbPrEXX/mHm3HR29+Mh53/aw4CnQjSeO+8yNyEGBQtBu0bC98bTxOG+9urQGuFUzMGPR6PnafDNHewTN8QknBiGtcRbDmURUsbaUy4tcws48acELm8g4KGfXwDqEV1T8KfQ237GL5nPAP4x390hqJUAvbdBUxNjf+OLgg1ivbvsqgt/Bc40ohOkqjsFgwRx1zivlfx3ThtwzTm02Zg8qVhJrUCBd4anVEeixhyhkqFmKIGsd9lI1iXorY1UabZZMKri5slvPCTPtCYB6Z3wsRdT3h5EkSaWY/QkmfSxNYtVM/QFNTp8/0wHAttrViZKjOluoeF8bRjJO8OHtQ49gZbgDCtJ7ZR2yQqYOOs2k9v7k24xkQDp3G4MOJLJAlX1AgE2u54Rq1Uzs2rXAVybX7h5qTPFeZLFQDEparKXpFj1ZlUokZxZvhx5SFvF/k+xH3Q0kG07r4TN338Bnz12s/iore/GQ990v/DBnDseI74ma9IpD/Wqu9hZMseObYvj2W2/w6gvcq1C6d38HP22ix/2FphJm+lxvHkmZ0Scz2xxpDSmNVvstSFKspVvq8W2a3WGQb1PdpUPHgP7jQnCTBDbfsYvsc+FvjCF9y/y2Xg+98Fdu3c+rV8goIawpxBjFipQiYSZQnXQVNMPSrncto2TVXXaxhIwmuNF+HifoZm6jMMcaohZqvE3/UqkeceJZN4QTEBP4ycJFutwX/3WKWk3rHdQAtFVj3DvKXlYjh/kJI+sLYE0orW/Q5U6NdU6qAK58UZH6LSw8io+x4NhGkPEhDCUwRAn/kENgtxBuzt5Qguw5AomRGeoJB4ONYXWUUQEgUeE4g4e7fNXl2lLiLichA4jhtzjnVJxO9I1W9KFabkZ5IbOeg6T0XlywDY+O2YPlEyAC0dQutHd+DmT9yAr+75HC760zfjIb/+xPEGcFTz17GsT6KMUSIVughDDGEGwr5Fd53jkb02kKZcI296Jz9b3GfPsM2HM1Ouif7vTonTnRhjyIpTwsKOypy/HFXY+2sv84eaO/LqLur5+/tGqWYFtH/a2/YxfB//OPCSl3AV9mqVUxr2fiYvPzWxyWaE4c/aAcjBpakzjjpEtk5YwUOcNJFGeBr2J3rKthtVAD8xdWu5X4HkDBkmPvTWh41hmriYYbXOkIkm/x+rwdugERHnQXbXmb49EJWUlMW7zdxuYNcZMEEJxi/RtGEr4GG2UvvRxngn4muwHqFfwWGTS2jIg9OE+zThjTPkxG4CgEwkqzRns7POHlytIad3r68/Dhgu948xyAT4IGYL7GYZG8FE3mcQOCF2ZYfa8RQjlSbA8kG0f/RD3PyJG/C1PZ/Hs9/+Zjz4PzxhawbQJuLrIZJcegHMZJUnfadEAj+uc37ioAsasG6rqTdB9SZMmgKdNamJmHGO5/zprBusCMfxPIDEfWGGGjGCol8qa4q1QT0UbMgAGmGNj0dffhra9jF8AHDddcBf/iVwzsOBV13CBrDYcrk6w81Cexmz5yiW2lqDARBp+Z0poD5jYx/ImC1m89rGxRGLhlAFd4tU+GLQ/nizI4vPLKxQaq8xJKnKF8osq9TEI6wDjRlg+hQEBsfgGfFYkBUMAJ9OBz2uygAwyaJcBbIUZuCVa6JsGCKdxFLzvbpJhKYwAhCBY3xbfa5NQpr+p4R4QHEfIJK6eCzNRVkKYwwojITQISSVQQ8mSySvUliJdk5Nhpu32s8tPQcgsKZCszi6OavGJ8cc9dZDJsYwHrAXvHAvOvvvxc0f+wy+tveLePaf/hF+4deeMMQCHdsHH9nx4U+tqVeqSMrLCKjWjwOHUpVd1jtpNYqOHCwHPRAIJiyBpqb5ar0OrzcAplyB2XG6sDMdCe9Y1jtJ+IVLJkHKspVdLFAIdHZNJImngCOH6krjp5YAs70M3/79wFlnAa99DfDaV2/qK3x6zpimHw9sThCVqhxzEsHbXGK5d0rccJPMCAyfCZus6CUCLiaoAfVBF2b2VJjmPH9v0D3O8JunWqJSUEGU94LU+0xVeV5KBmnOYRiJJFvDybOVqxt6oQRwLFLkvkypwmLRYcRjpfXQAqWRy3gLqYJi1jWkzpoj+ISRCE/XnCi3bhsnRLppgtcnRihXwQGATWAfMCHHRGWpIu/lwvk5kLohKWsVyMHNZiRLVE/ux8/A5Z7SJ2oVSwWN3aiPoi/+AdCDJPMf4WuqB9i5+07cfM0efP3GL+HZb3kDfv7/PQ9Gc3b96xQ9UTGuplC5wgrAa+kizYn1v6uPRRk4J1V+qH/674IyNojdjrCz2+z9BgHvNWHIqRY9LkptKnWY+dOAqSZ8ws3RGEObIzjo8xzSWqIt9kLRnHfi2ZoDbMM0AQtt/5RJoG0vw5emwAc/CPyHXwPuc7oIVsc29pB7kCR2hVCFum3KNQsNHDPMLQssN3w+iQGATaz3WVeAO+WrCO+GOYibaGEZKFdA68ugtQU2LI1ZF4ssivICzjMukEcIkhfWXQO1ltgj7rZ40dQaQG1aJMKaoOqUQ92yzFP28E7lPnHCbK0aBBFEDKDFXuGg59UtnIKpVNlTjUqTr7tpj894e7k3p9TLB8Zu1oWeA3HMlet7bY6v1hpMjMhkc7YCBMUlOMLw+t5Ljjm5QQ7dcK/y1wQBaebmoXetEx4J8o27HoDG3JSyFFg5jPZdd+CzH78eX7/xC3j2267Az533GI4TA7A5fgq16pjonNT1WDx4xJJPF5WwmaK39l45qJvsa+GmsVZieFTDDnGPD01BAAQRjKAChogPmXOnChMTOBpjaHMEE9E7jSrsnXbXOSm+XHMH+sCFOH7aGKDbx/D1+8DjHw98+9tAFIH2/ANwziNgJ19rGbS2yJ5DrcEsrEgKmRY3FsumM8ipv+eaqCtEJUcTj3t8AtXFpZu7f+r3T05W6aIkXiXyG5guGjUY9lS/tTiihW+HntH7ec7gHV0cT8s6UXuN6+R11vlnmjDcnAd2nsFJtCuHWLprbtcmma6aQA2XAjCGiUlZagkzNqUCyCvOVOqbzC1kQ8eeOgBNQRA4jEQb0laOl75QmjLrLu4xWUKV81WeLIxg6o3hYrXHo41kiQYAhg1HzpvTz49QNRrfv6IRNmP+fgzN9zR1DXh9y300S4HVI2jfdTs+97HP4Bs3fxkXvu2P8LOPP3dsDDC3PjTv12rNykEniZnRrBq9ow42m4FX/ecg7z9d+/KOWOqwywax1wIysoQ6k7H3aGCAqWnJMay5O29y3TLxrcWHWM1nbC3zM9ab/CGNteo8iMo5yTSf1f3vqW0fw/fpTwMXXwy0WgAAOu8JwDUfYq8uLDOcVqqykdOUBz8GV1z04wyKMTIRQl4xSU9SGGTyqhKKTxf2N2XAW1QYM0mNKCyErnozPCM4MY7oPERbsrLb4vhQuQbM7HSn2KIh1kW4xY2YABHKZk1RW0KmVOaYXb8jWqXrbAx6RahU6hxuBJXy4GHY8x2xwVq1fYAyEfL10ykGPU9+rQ7UZ0DVBsfQkoE7+WeZpKpIPmhUZoKCbgb6TpKBxEclBlcR9ADGOwgdL5JJ3v8e/TvfWIChtqH4cXHDMnafn3xfmvDvE7xdFOPgY7xAyjJgdQGdH92Oz338Onzzs7fgwre8CWc/7lc3R4KxhwZYI2eVi0BSIknzbeU7/Q7+b3vfHm5ZUd35q73P8z77iTwUECVCmiCtUSYPGJDRUREkDsmX+AUThM/JoERMo0ETYWRQZ2T6M4ojoZFhfAASMcqYgLaiKMhDRaDTQBjSiDTy7Ibu+zrvXfPHqlW1qnadc8/tvg1ce6/v6z7nnr137dq1q9av1ltPP0vrhwvQcryd3GT120x4AM8ONHDzB2YuN2Yo12m3bZZED6qX0VpLSwSG4yu8tGXzzT1KZk8Ai0rd1Bc1qdFU4uY1N1eukf8D/z26LNpuuw3s2EHuFuPjWDL4uHSA70c/At76VmB2FrqUAm97K/CFzzsXa6t6sIr54DfBEITXllNRJCaUwEzi1JThYRsCS2+cLb3bcVkTmFHbCawcgKYlVz2a/+YyLFzF2f4TtkGh6rAu6rK0CtuKbOXyUiABhOo4ZQzrAyRIltzSMvTsTuhnH4eenSL7xMQqKs5rmL0vQBJQ653bKP3V6gNI2poxcVBzO42qtEfJuuvjJuZwjICJn1XuLKPTcjjGq60HX9PZCVumkHClZtSkI0BlhHKjWicLQ70O1e1rTJuYQiNJsu1EmSLHdl5F+snu+za5dXheIqSAhS/BvMrSUCbvRXPTqdbFSzObBncu94cdwyLq1ueTPLOBQj8blNYZsHM75h7dgpu/+s+494c/w6n//Xy88ndfPzwAepl7DEi0m8Zr0ji/eBoHbXiAybHLgfAyoXeSGOmplgt/ApCXHkMp0fIvak93WhSbyTUje6awdFImEB6doDyv0hGsX+hIr0vq0MTwu+aMS4vGNviQ0gqV5jJdvfVW4OKLgW9/2+zfe8D++wMf/CDwrncRCL6YaekAn9bARz4CXHoplSf65jeBVcuGzJ8ZaY7bZAmx24Ero5OYXf0YTSqAJrkNXkfettdp0wzmWBrJ0LyJzKoPA5C8IBTcbxYEe64kUbdDar1OkyRb6TghbYZWytM+oHJGGel4o7UBeOMWzQVZS2U6t9t2AM9gbwGZkkBrpcg+UDUxQpl25zO4sz1UqCgRsdfRZ50AibO0cG5Oac9iCRig8Wg1aKesEuc9yXFkLNmVKlRncPY5YHo7OfT0usQ4jeclKiPEPMZX0CJPY0nA+9GelYYcD9Rubgg39aiUITeBrOLjTEIe6C0myC2yKjS0m/fJuqS1BqYIAH94zT/h3lvuxn/65N/iFb/zOqRDAWDmNpHcXteUPSoLdfWwtlR2LOMqK2b9aGvSAICENpX9wJHvZ8ZAeXZeBa17QLMB3ZwhjQVXc0nLUPVRqLFJVz5LtgfxxrttoGmS03caVDGmWrcAKGeGqo6hp0o44wzguusosixEj5ERYGwMuPlm4PDD42Nzzz334IwzzsADDzyAww8/HFdccQWOOuooAMDVV1+NdevWoVqt4sorr8Txxx8PANiyZQtOO+003HLLLcO9z3lo6QAfAHz0o9AXX0xB65vvoeDSIUkjMUAiYsSYCYjdFeUwrDhVV7sF6BBcjdckg64BLLNfDJgKne9UnzCOKEaPztlgYn229gF/sXl18QAHcLUJyqjRmDbONAmAzAXfCzuitqVlMvI027mNjlVGoJatBkaXB+PFnYdQz2qnHtGC2cVqq1kJl1W51GfrWt5qkPqlbQrgpikxnHKVkhWkVeeOnZYJ+Mtc5FPRGHZM5YNu24QFiHPKZO+FKTqrOy36brP69MjlO+saCbpss32gWjOVFCou9qxn6g12DbCXTWopXpTsrdnL6DWoFJ76FFqoz6V0rh0w6cyNe9al89MEUJStZTAL7q8S9TwqB2kABrbdD9z20AYgZgfsB4DTz6Lx6BbcfM23sOnWe3DqJz+Klx/92vkZprTJJaz+JFU4VfuogGs9LpbR1iactlqkDnRPSO0qgSqx1kjwJTsWMOdqG/vJleEzXkvdDtmpRyehRiZctQ9L5nnaTVoTKrGOLt4s0hrv+cByXH01gV4/UgpYvhzYtAk44AD/WLvdxqGHHopzzjkHZ511Fi677DKsX78eDz30EJIkwSGHHII777wTd911F8477zxs3rwZAHDiiSfi/PPPx9FHH71rAx32cUkB3xvfCH3TTcRcHn4QWDbpH/cmpXhlEkDE7kflrp2frKQ4jF1HB0ynLyi6T80SX69LjJylMGGX83b/Yd8HOK5oDutoNSmkIklpERjvLsWqD2aEnj0RFF/VnCXgqY3kbYU2A4nZlXLO0vlcpVUKnRh9SXuOjP1zM1RMtznrds1au5jD8RXA+GpSRc1NU1otbdI71U38ZYO823SSkv1zZIzAiStXhMxUAxoZbXbaDZMebg62+Cn/q9ahUrbtGCnbxIWy6suqtdMyqZ27vPNv0wvk95qmFrBtuqly1RW05TActjtV6vS91XD1ECtk32YVLaDdxgFwEi1ne9HaZYXhPLaspjPehgCElGjea6ASzG/Kdh8QhrpcqgMHAeDMDjQe/Tf88OpvYfMdm/COj/8tXv66tfOrQGP2P7Zv9wt92MPk1JtmHmU92PqdaYnWclq2jmTmKjtWHLyvm7M0r42mRY2vgKqPuHcO5MCf6f4HFF537CQajfn7WyqRyvOKK/zfN27ciNNPPx2PPfaY3cAfeOCB2LBhA9auXYtTTjkFt99+O5rNJlasWIG5uTlcd9112LhxIzZs2LCLo5enpQV8//ZvwAUXAG95C/Q730kvrzXnVBKW8XR81YhlQImzh3nMPrR3GEpKZpeVQDdnoaefo91XsBvaJbK2C6NaMXXabB9N3639S0p5/Gx9HVcIfOyrNRlCdHPOMkRVJpWm8q7neESz4zSZ/MFqG5MomhaZAUnAMQk5lfowBS+pt5doQPkB0qIdZa7T7JbN2WiaM8ToqyMmzGKMMmrUx5EsYmkWbSRczQV8W3M0N2SFilodyrqwD2jLfuHx7tGPQcq4/nNLmRRngHWQEMdy94/NawtyQrVunb8CUOM8kL0uNcNAz9qO1DiB9bp0XqlkpODMZKIxz2jb6ThNS7fj7EnsXMFzLy2blGecIccAt+45oFYCjAEXsiDs7TrLgLkpNLduwY+u/r/YfOd9eMfHP4KDX/NqUjMOfFnabQ7YialjNhbS+WUeAHy+4DGnXuUwL7P5pGT2ZiPG2h7dBebmyJ7d7VDIzcg4lAatca1Ja6F7eM8HVuD//MM4ukNal+p14KmnfHvfpz/9aWzcuBE33nij/e1tb3sbjj/+eHzgAx/AYYcdhu9///u4++67ceGFF+L73/8+jjnmGNx0001YuXLloo3V0irc1G5DP/YY8MyTlJKLFyc7EBgvPqQpVJIS02ZvRGbqnRYxL2Pv0knq7Ei8ayobPXepQrFsO6agqnXSmTPghQ4RC6GUgpt1lgHPPQXdnDaehxNCbeqkEECTQT20D3IYBWegr48BzRlk2x6n2Ltui8ofmVyDqj4WWYR8DxhmbpxbdjwFveMZcmgZnQAACgLOMqDTBdqB9yUX/zT1wDj0AZ2GS2OVpE5dyI49gPWSVGmF0q3NPEu5SzWpUnVtlAC33aTu1iegJvYBRiegSxWoxpTJobgT+omHgcYMslKZnGhGJiiDxehy8iplFXUYLgEQkCdG/cdSa5aZOnjjNBZQxEi6bQLDxgww8yvaWFRMtYzaGFAbo75Z7z0hBUP7cw4x5uhZV7yxVh7gsRZDzhdWq8fUjso4OYnf07L7O9yY6IzGIyxymgRJ0CWISG9DpACESUJuSOT3UpkYt/SOlGo92/3UPbPizZLpM4Og213QvBtbhtqrjsKbznsljn10C265+np886OfxDsu+hscuPa3oNLEDTP8oXHOZMYjvFyleduaI69OrmHIF3dapuI6/2Tmi7TDJ+JvT9VsJGb7zL4KWqkgbjhGJiFHrlK7IKdeNWuwXIaqrCJJNkmRdXtmmBNKpWfG4Os3jA4NegBdetNNwCmnuN9mZmYwOelr6iYnJzE9PY0kSXDppZfi1FNPRbVaxeWXX44LLrgAZ599NjZt2oQLL7wQlUoF69evxxFHHDF8RyK0tCS+d70L+stfJia7/QkAJiNJGglejqkBEZ6indMH28lCT0tW/bCnZ/B9Yfk0zX1l/5j6eWDFzrW/xVSntkFqkyVGqbqQKiqxZofuF6tPGIjDEAxznWNOQoVq1KN0G5YU4UsaEoyFqnTYkaZMFk3atMhcpToLEndTCSUVOhTsAuksczGF/E9rW6+QPkehFuQw8yIgC4DmvUAw8Bfjg4RqUCDHA/TcFJpbH8aPrvoG/vXn/w9/cNFHcMARv4m0NEACDNSfBB4dl/lFxZ1fPA3HIGe3hfxuP+Zh3XZeK9rL2Q2UAV8+5gGvQrZzO5KJFdCNGfLKHp2AKldQ23d/dDqxG8VpdBS45BJKscz06U9/Gt/97ndxww032N9OOukkHHfccVi3bp13/b333ouzzz4bP/jBD3DwwQfj1ltvxdatW3HuuefijjvuGL4jEVpawHfzzdB/8ifA20+G+twlLrA8VLVFwSi2+82THY5um1Q29XFjo2k7l3gJkCrxATEp0Y7a/K3YSA7AJlBuzFAJGZZI2INM9M+CkLAles/Y65KtbuY52mWWK+SROLGa7hmqfOU4KP/T3qvThp7dSfawZfvQLXtdUvVlXOketFHotFxmHABAAlWpWAYPlUJlJhdqu+lURp02Bb7PTbsdeqUONb4MmFxNkh87m0gglf23dijzXTjL5M5XBnTTlDzfGtPA7E7KsG8SD6M2QtloRidNkt9xIwX0nOpNStocQ5kJZx0GelEaR/d6UC1js2xy3UITW1gfp1RRlZp5XnY8UoCWO33BcD1JjueCJ57ImRz8vgjLXEquTk0wvw1XXs9zjxm51JxYFaU5x9ugaXFcPk/4W7iB0kA/O2BjBs2tW3DLV76BBzdtwSkXfhj7r3nVYCcYrUmTZEOLhPNLuQLvHbDqEeLn3L4yIsUpMT7+zYM2Yu80Mq62Xb5EjJUyn3Loej0X2pCkdn5OHrQvpqfjwxKj8XGy8f3hH7rfNm7ciHe/+93YunWrFRoOOuggXHbZZXjzm9/snkJrHHvssbjkkkuw3377Ye3atXj88cfRarWwfPlyzA3yrhmClhbwAcB99wEHHQSUYownDRbF8MTiv57aBlWuAStfSva8XtdkBskDiGZVkJQSrfTIBWlBO0R2N67UoCZXG3BQQKfl+6ZYpiCZAcjbq9umScgehAZ4lQygtSrEkHnCPYNpU0umKjPZc1xSt0VxeZw82BTFVBzAz9UqGDxZjdhtUyWGpglZUCbgtyI8I1mStNJEfudpbStyd2o/xLOxGphepDvXqo2CjYMsCcS5SpuzxvA/S6rwtEIp0Wqj0HVT/LdcNdlgZF8ZDGiMbdcCRyrrYNBpGHuh8WI1c4LshaMEwtaNXD7vrlJsPSwCEEpg8RxN4iCz8Pb9L8yXc72e715e/8xcCE9pzqL92MO45ctfx4Obf4E/uPDD2O+wQwfbAEP7HzsulWu+uhYgB6WsRxsaOUk8lWbwGf1NPK94ll3ROg0izQmt2y1ae+UqVHUM7/ijEr75zcheug/VasAjjwAveYn7jb06/+qv/gp/8Rd/gcsvvxwXX3wxHnroIVQqTkV++eWXY/PmzfjMZz6DbreL1atX48c//jEeffRRnHvuudbbc1dpaQHf174G/MkfU0mib38L1uAtnVPYE01KS1Bi1yy2NlCO+WtYLz1PuddPVTFMBQjJZK0qkOPqhDSRsHdg6iRI3vnrngMyEQBve2gdQpgZQzyf6DePD+9YGzOuwGhahs2YIm1PtliqgBm2U1kbl3H26LRNEdxxk0PTZDZhz8+oujaDt8hDWxjvlm1gu/lMObZPOiYJpxy+n9l0WKkvSeEcSjIBgHAbpyRFphQwu8P8M8H3nBatPka22NFlZPMrV+P2OQsAfDTz5405pjNtHGZmTdaZWbqmZoCwTvGN7LC0Zyjftl7o/aIqUQH+njYmWJu8ZlXi5npifue5wTF23A4f52Ty8i1IyVD6ATCGn6XeAAAgAElEQVQfCDcl/AitObQf+wVu/cp1eOi+X+LtF56Hlxz6isALVNlbhKBvY/+0Ns4vwh/gxUAy1pftp2KNW9Ka8v2WylCJ8ZIGcNttwJveBMzODnErBZx0EnD99fljd999N84880zcf//9No5v7dq19vi2bdtw3HHH4bbbbsPEBPkXXHXVVVi3bh1qtZoX37ertLSA77vfBd78H4GT3gZ85UuOWfazcYXqHkVxbXRJ5oLOTSyYkpcylcrEENkgLAEvUCfoLCPVXqft4sxUgr6xP+UadEpxd3p2BzFXE1gNc711CuGML/xPTFzFE7liCpF2O9AdI01w/BdTalKueTF1mrzxKiMkmSUpSUJT24Gdz0DPTUF3O9bZBGPLoUbHXUVogKQUG4ArANtbVGIMQgk0VFHxdx7jIP7PqrC8vKZmrPqq/OLkhIvIuQL4NTsuyDqH7aYB/AkCwpEJ8i5lJp0DAgPg1hnFgaFWRoXa65hQilnyXG01XA3F2li8mr29l99vu+HiDRGrJXtCLcxzqicSePMc41hEJc7jjQPHatpnUA6IPBCEe0dSzbYAWlSpZh47oG410PrVL3Drl7+GLQ9sxdsv/DBWH3JwfxugfH6lXNiQ0W7sefBTbu6zx2yYKH6h1G0jrOiiNXDCCQSArXjosaWREeDOOwHPB0Wqrl9gWlrAB1CuztFR2FJD0Uz78d2qlcSYiSYs4QWUpAQi7DbdnnPSh72FglVfQZNK0GZEL1vbXpRSqhCRNWcpaWzXFLesj5ONjO1WfH+ZwYXVu54DThqf5JxXFDB2iIQkltSlYdLWa02CEPIgoCj1lcey5Dk547290DF8K7XBSWTzTT8LigFjN8H5OQmR7a6sKk1MZprUxApK+6zWQmLQQupL/MB2DeRDLahPVKhUlHNidWmpYoCKwx3GyQ7L0j1Ln9K7Doo2IAlXXM9MkH+P1KKtBtlzOyaDUMXE9dXHjVdsye+j97IiG695aFFYlNSYWDtmOrxdcE9SPzWoWQO63UTrV4/gx1+6FlseehynfOw8rDzowMEAaNaj9ZzMOlT5fFelP5tTmOeNkNpeABCZmQHe+EYKTo+Z2UrGMfz66wkkX6y0tICv1wMu+hjw9pOB3zh06Ms0EuOs0vbzLe5GVzSDZ6/nVIPztGmBN0ZWenTSgVQRkjZPOPNwmEa347lL26wuWUY2Ot5lGUlI6Yx0+K0GVVmYfo6O1UfJ03FsGSXAHVtGbTFQDKP2YpBhsM26PmO3iZTFM4eL2KoitQAx6fLtvQS3CeDvcrStVKn8azz7FG+AAhWvlGS8a5STLqObDeOs0Gq4WMO5aQJGaKA+QZnxRyeA+iRlhTH9UtLWSQMKTzIUDh06I9ukbs26NHBJ4oVToFxBTlKyquFgbKQK0p0szlskkmBjnUReGCbu9SlUvwIOADsttB9/BLd+8Vo88vBTOPm/fggrXnoA0lIkGiym/uy4zC/UrHjWpOSe36rvh4sPfKGo3QauvBL41KeAJ5+ksAWtyRfwT/+U8nW+8pUvdC8H09ICvqeeAl5xCPDRvwHOfu+8p1ugYbVmSvkolVRXzkdCnWOT10Lbun6DwI7un1H84exOUhsCpE4cXw6sehnt0htT1L9SiWLemPHz/bkCNEt7sm+sYjTlVLKZHdC/vB9ozlBF6MaMkxBGJoCxScq6UqoYqZSB0UgZNnMLBNgonyFowHqDsY1AAoEEJCmxyqrWfL5c7NaWx0zYjqIAIfNbmrpdsMwYw2POgGtVdGVXTYHd0LMejTXgwK9UcjFrHB+XBeAH5MeDnRb6LCdr/zEqUs1SYqdJIDUyDlU3MYe1UeM0FDj+SFCUEhSMc5FJ6GBthe2mcZwxm5pq3YTg9JmwHsVAr99vu8hCwg2IZxvF88/4tZg/cqwtALbRfuIR/PiL1+KXjzyNt19wHpbtvy+SmASYU3/2XNkjaaNPycTwYgW5QaQ18OCDxJbrdWDNGlLGLQVaWsAHANu3UyI4pUi1yGVEBFnpSLodL0TCU4omY0pAhB1PQ+94mgI9J1a5YrYxdarWLiktlMuLJzNMpCXKmtA2qqtux6SsMl6gxolFsV3PMuKAAXqAY3aJ0gbG0opV2/mOFW6xCeZjA+XNNTKVlTWMy/ANo76U+TmlwTyw93jvIGyPwwECKdEBmvlPJdZBzj1jF9aBxeZgRfQdRV6aeH5hS2TnKaueLDk1ZThuDFASiG14Q5Y/z7w7UpXOUswhS4bNGWPTM/GGoxMkKZZKwRxmxsySIYS0oejWnYaTDJuz9Fy1UQLZ2mhcKozSsEC4i+SBoJOY3Fju/i0W3J9Q/c8A2O2g/cQjuO2L1+LRrdtx8vkfwuS++8RTofF7l84vgO/8AthiygU9P7S0gG/rVuC884CT3wac9Fb7s/cAWruEryI1GZTKlxEC4BZVoEqTgBHu+pkx8v00p/aC3wYDjFU3OhWZSgK1mlQ1hXYRrhk3txOYnaG4sFmjOqvWaVevNXkaHvAKygIDWBAcivlDmZCFKgFR1rNlV3QYomGlOLY5as/j1AcL+q44nRSPt5128/VNhEqw+pPfS+I2NSRw8bs19+F3YKVDAVixeoc5OySETVUkOpAqOra7QLzffuPrbTjkO3ZgRQwSZNObmzY1Dk3hXyiy542MU8xhfayPV6m4pxxfpUjN3W44qbBFuVepbuIE2QxzAPsCUOgg80KpRCUgB2EKuttB+8mtuP1L12DrY8/hpI9+CBP7rEKSRuyXvKlMEmeGKFWMc5p5JpMGbylKf3uM9pBDzNICvrPOgv77vwdqVeCZJwRD6hongA7Qy6C4Fp3VlZv/cnYiwRythGL+1hpARpOxXPN/Y9KaYl14F8eBzd2WqzgA7aoElCokAaZlqtVVn6AetBqA7lLsmykqS5UCyJtOcWLmSs2AkmEILcPA6mOUbFbBSXwheW7l4StfqLrKH0cdrS0YZMJJQmBMnN2jXLUeoTTEHZd/VZbTkSpSpWBd/DPzXrQAPpYOpaRr+y4+ZXYLTwKGGxMGLCnNWRDuuTlok3Knnt2X8j8FEtl84xsCllYUJ9aYJa/SuSkCxE7LZKPhAPwJk5ptuHeqNWi+tkwC49YctVmtAyOTZC8s+0nSn3fKqUSFWvz58hS0fUCOj+helwDwi9fg8Sd24m0fPRdjK1fmATCQIjWr3GXZI6CQ/p4HWlrAd/PN0KeeCpx8EnDZpcRoZnaQjaxC4JBz8x6CSDXao+rKU8+SKuglB1EcFQDdbkJvfxx47gno6edIohxbTpIVZ+ivjhADZ+cZKW0CguGZRdPtEMB1TDkdzm5SqVHmlHKV7E1Craqh3C5YlPwZvOz7qKisk0PE3mntfabfoXTkNW+AyHqWGmlJOJzYzC/WIajrQJGlRqsmTYSjCVc4MCEbw5CVqlgiUw6sACdB2/6xBCeusVIkg2Sgghs0zlJS8cIvIJxnhMpUKf98+RzzLk1jO2rOGrvhNDnSNGeImY6MQ40tI7thdcTOo/lIZ5nxIhX2QsDkPiWHnGiawOiYLDJ7idkFWeIeJG0vVj+kNiYCgJ2nHsPtX/oqnnhyCif+7bkYXb6sDwBmZkMD4gGpM2kooJD+9jAtLeC74QbgggugX/964IPvhX7ml5RHbp+DTAJhwEsb5ZEPALSh1z5TAtxEy3q2CKs2k1xx+9aeFXok+rt02363I5h9j9orGRteWjYu7KnrZWBk1wB0cxaq0zbqLVEXDNrZAbkCBRfW7XVIJWlbHvCqvYBrVu9KRi8kZvmcQ0kwdL1mFZ8t4WOSRSshHfHYi/pk5KSSOObAtck4g0xaAvuWeE4fMaCOkQZs8d5QUgxtdzJ0hMdCbgpC6dLeI/M3EJmGTZRtVcIlp5b1VN+Za89Tx8fHXuuMtAjNWWM3nKHNIZRxcFpG0mF1dCi1pnXNb81RPlJOv1auUBL02pitd+jAcA+AniQ7Vwz4wWwy0rJ/Tu79LzIIcvsy3i3rofv0r3D7F6/Bk9vmcOKHP4D6sgkkYQgHbyqTxDi/tAvp73mipQN87TYwMQG0WtC1KvTH/hrqjPeQ8X8BpAFaxO0WMRRbHDSzNcqIn2RGcquQF2aJmWugruDJb+KrdKtBuSCnd5CjQlpylRHGJoGxZSRRcpFVwBRgbXixXFqZ+DIu+lquApV+WUL44QYBG0t4u/G6pSej5/qunArTSKg2iS/XmctMwVb2HLVMIEikHWPkgANLVi2G6eEAJ2VbQBQAaUM9pAQrQMt7PjGmsiqGBdNgHD1pUcQQWhANnYuEuzozP6s2FeDIalOVOs2CSp0kHvabpZDIOJJbfZuktzkjHTamnap0dBnlS60au2EUDR1oWDf9ZsOEVMzR+qmPGRXpiCjcOiwp92yAe1abzSUR0hKr7oUHpszcwwnmw7GOPs9ugmEfO6DOMnSfeRx3fOkaPP1cA2/56/ejNj7uA6C41iYvAMgEYKW/1KU4LGhRaGkB3+Qk0GxC1+tQn78E+CPOftr/ETQ7n7SawMxz0O0m2QDZHtPrkW1j5jlS30yshFqxH7B8X7KtKWUKhTYof+XsFPTMcxQD1zBZNZLExb6NTBgX8pqfk9IjsZu3Cw8EpICL0RMZWpS8VjKHGEnJLXqeWOhsg5KelZLBeAHWOmjfjL0GtGfDEp8MambRWqk52jcp0fgbDM+uo8QnRM5UzpfIEjZLiz0GXel4U3ISpAFjlQRvSgfvKLw3A4/0gA3DHuR4WZWcsD1H72E2KZ5aVgAjt+U5EsXeeTjzIpuKXqAq5UD8Sp1CX8aWk0NNhfOUBu9LtMt1C61k2Jqjvo0tM44zQpqRISieyhLORu0BH+CBnQd88N8Hf+d2ebNivS5jQLcIkmAfO6DOMvS2P4E7vvxVPLOjhTefezaqY6N5ADTvTcNspEtBzHEh/S0aLR3gA4AbbwQ+9CHgmGOAv/s7ICMHCPsAhvloY5+gUAdjc0pLUBVjk+NJViqL2mHKqg81e4B2WtBtI7F025S6qWSSNPO1nNLM26kKJh+S9GZkFZsMdNXa7vYc4PkMxgeuxKj/Kk7N2WsbKStU+fJiVKIJyXjnI+XAma9hG12v54A6LdvYQwU4QAjvEdrVAEBmdgECaUnnpa1c/8ynBJkkgWbVoi3S2TVJDTqu4gZLjLn0cKTe9KWXkFEqJ+lZqVG5/sfyg0rJ0o5B4k+cUM1pp48AQi/vaxJsZPi6Yd+x2SyaAHwLhnPT1M7oBDC+glSlZj3Z7vI6MP3WLKW3m0ZFaiRDznVqEnIDIBuuBXwBfBYYEQc7/ttKvUIC9KRB3wvbqwW4J4h5jHL91DpDb/uTuPPLX8WzMz288Zz/gsroSAQATfgDO0xVKjT/gEL6WyRaWsD3jndAf+c7QLkE/PwnlPY76wIzU+Tin2WURqBUcbvl2hjZ0nixlMpBUU1tJCyjMusSI9fKVCxOhepMqkuU8Juzk1yClT0Iq7JUmhZBZcTk1VTQczuhH/8F2VpW7hfYSQDrLMISgDsgbzIECdAz/ffUd4Bh2oljnspIc+yIIou3etkliOEry7iCduV5C2DA3nVS0pL2Nm7PJgDXAlyGsPGx1AjAOqNYMO/6kmMiJEQLki6IfrAnZSAxSmkndCDi8/nDC7XoJxGb372UdkG4hudtKuZVtM+BNAfQJkFKh7M7STIZpZJSamyS5nWauiw0Mj9nljlXfq5o35yhdza+HBiZILOCtaezhCaeAUoAY0TdGZUAxbq1c9Ac40TXwzpPLZQidkCtNXrbn8RPrroWO+Y0Tjj7PaiMjvjrnjVVUDRe1uGskP4Wg5YW8K1YATz3HHS9Dv2V/w31e0eT7atsKiFrbUIB2gRkxu6gSyZ8AKDFunM7BaTPTVMQ77gx9o9O0uIdnYQqmSrsSWLCDKacJCCJA9Ml4ElbQ5/0Q/lhV/Ns4qQajIElaEN6DNoFl/kMMNesVBsaNQuHiXTNZsBIzDK90oKy34T3YoaYk/iU2yXL4rZeFfNBwClAXYIkpxmz9h/zfqKqybh6UEtw4vGRnqm9rvPmlcAoPDiVaC/fdX4HStyWgbGP44yneg2YJgJGb+sbija5FFUOxJWTUq2aWYK1tmOodUbOLtar1JgAaqNU03F0mSm1VIaNs5QFkbXx+u00yT7eNGBYGzVS4ahl8EoJEM1JedhFIIT73QJUJBB9dymiBtVao/fs0/jJVddiup3g+PeegXKt5gBQqj9ZlW+8xgvpb/do6QDf974HnHgi2fqUAv78z6E//7+AzhzQbSN7eivQmoPq9VzMm3EwUEoZu1vdqwcHwJ9kAKz3oAY0p9pSgqEyiUwsKmY4Z+mHVW8woMKTudeFzjIom1yYzogXX+1HSqjiRG5Jln5CNVmwoLRkwv1sTa4F+7/tqz0oJAkZbyeZrO2bkMTmlf6ElCPViLIiA0vCMebe18YZtC+dWqSdz4JtBBy9odDWlmyrHlhw7DqbLVQEGEVcY9/Nj9z0iLGXKmRPfRqMlSclCulJAkUm+hz2VfTPc7yBAF3xrjVAzlqNWUrNNjdFG840BZa9hFSlJmsM9ZgB3IwlezhKFWnXhBCNOFshrHkC/cEuekxK5sF3OXeg6R0tJkkVvtm0aK3R27ENP7v6HzDTTXHsfz4d5apwbpHSH7+bkgh9KKS/BdPSAL4dO4CXvYxSgxvSI3Xgf3wc2e8dCWz/FdDTrsL12HKKX2Lj/NgyKioZ2OCkX4kk4i2SsQdqTUHOy1PsZHNnGEDbuQ36mV8BK/eDOuCV5CzQ6xmHjHb+0iT1d/6iTdHTeYiZtKI0X6wGMwVjAU2ej+UqGdMrVdpZS+eWbhAWITcC/aTPXB/4GsEspSekHDsvbjBzEtowYCmBUjJ3K2VAgIUE5XnG0krugQQvn7+v5MjAqL34RgeKBmy07pMBx9kaVWiftUAn08SZ/7z0a4bR2rI1YpykHdJTiYs2Yll6bOgFBGDEwVZzgvXGrC8ddjvAsn0IDE19Q1pvARj2OuSJ3RYq0lKV1np91MXADXR6kRvUAeDH3zXgNmlw0vBiUWAH1Fqjt3M77rrmHzCHKn7/3aehVBEAZzescJlfWAOjUpKSC+lvKFoawHfnnVQBcWrK+zl70zHQ/+3DUMtWO6BjlSaTZUZsE4pkNQFgAUpKTfUJqHKFvDnndggQgl/1POf0QOdpQHhoJn6A6kCKAJvMWWhVqSzxsf7fLUyqCdaiBWJSjwEwJXpKwi41BNOX/VLyH0sVqftN2qZCiWlBaku+ZQTI5P3tDtpIkp46b0iJUj5LTjIetj0J7gYM5MZAgnef6zVLrQxCmQDFbtc54LCdmuMZZXUQOX+h/TGzTF279+GBYhKcr91GwXpSBoAYy85j55eUoCQgunlBlUIIyEg6nCYJb3wFMLnKk/AU5BzLqD5iu+U8SDstshOOTpprjIOVlAL7Al7wLsPfww1OuFnbHYoB4NSzuOur16Gd1vE77/pjpOWye7/mvWj29i2JvJ8yTKqgvrQ0gO/hh6miYaPhfiuVgHXrgAv+RkxqQ1oLphOopSJkB4AdAso1qLQEnXVdsVqz6IaJSyIPzRbtbis1qqYdu87agEC2dm2kgGFUnULysJKoVXNmbgwCw72SDNp2WNzPq/ul3OBIxh8Frj7jbCUTiPNE+16cVXDhgoBHti+B0jBKlnA0HEh6bYf9lE0y+DIowPU7p87t18egT+FGQbZhQcsHexJAMudoJMM22DvVJkVgcKw4O6NStNGxKlIBRqFdSRt1eRYBRfmO5CZMqkKlRJsoETYiQZU3b3IcTI3DtgnAZzCcmyITxuRqE3w/YsMTWMqzgfusIuVSTWPLKcie1YNS8usrBc5Doc11MeyCETtgb3oHfv7Vr6FTGcPR7zwVSakkNjjGXGHzEpvNj0rI9vdiqHn4IqWlAXwA8O53A9deS9UPSyVydPnJbcDqVcEkBizTYFIKRs+Xa9YyE8PMnBZJe9fPB3dWuuOCr9YILRYTB1ezm7nWjmmFkqi3Szd3sLp+/kkCAnKMUtnrbA8DikhS/hO5a6UDQM7zUKil5O9eOwIUPHtUeH6fPlvpUjJqBVseyba9AInSAzTZtmEYHLsYtaXF2graSUSOTsAHWpkA3QNE8d55bLyxC69111FKO2OXlqEbEhxZ81CSEqMARjmnpLTtSWrcD5GbVGok7PvOHBOXql4v6QBLrGYO2ncm5pTWRoPBzi+ckWYKUCVgudH4VEed5yODYbcLtKlEk27OkQakOmqkwroDi3mlwAHkzTUNl3lnFyliB+zN7MTd116H3sgkfvvUU6gUknhfWoPecbkCIKHbF9JfX1o6wKc1sGED8PGLgN/7XeATFwH7rILHNOedbA5ELFDZ3bsCtKh3pzVQm4Cq1mihthp5cJLq0eYceaXVR6GqI8FCsg8xxIMKhqeUYWba7PDbTm2ZlCnhdYmqcFsHGV6EHJsmVVmA+5zXZiYA1/tZMMOQMSrBNCxgQoBmzBEjAEzvtjGwDM6T53rHAyCxc4NBMpDSBoGk58gRkVb52TwJVW5KmJHHAA7w5m14rQxxyG1S5MZBbBbC0AgrMYq55HmkGlVqr01tWWmxar6LNG1aO3Wb3YgE70uCohKhE1aqzJxzGM8P/o2TDXBdxNBeGGgsdKdlq97bGodZDxhfSUkl6kLS4/XaMeEUnDFJgzy562MuhlbcdUHkaUUgNkK7SFYNaiTA2Snc87V/hJpYiaNOfguZXKQEmHWp53IDUEh/OVo6wAcAzSZw4luAc94PvOF4x9AW4FpvpTkhwRDbMMzDqDpRqUJxzFG0HUUB5+0W7bLC+lqeazqrgwSpxJYlYYZCLvPSpmPUntLBAbwoF/DaYgBlnUr6SXz8oGKnHrOj7Y6NMFS7SgCLqjdl32HHIt/fIfuVGw9jm7PjHEhaEiTDe4S2x9zmQPQP6A+U3K+YBBg+p6cOzoK+zAOOOVBN/DUgy1DZDDhtuo5VqKWK02AIxqok4MbejU1BFtqGZb9EP2W1D1blylJewb0oG80MgWGTCv9SvOEk1MRKykRTrrj3ZFWkZvPa61C6tZxUuAsk54rckO1KO3YdJOjNTePer/8jSitegiPe8kYoM/5Kqj9lIoxC+vNoaQGfJBP7kyvBI724BFEgaBsuKXICpRJfbciTZ8BtNeB2y8aN30vMmzOk26ucqtMsOCpMKZxPeh06xplPlFDDSHVmyMT4uT07jJS+pNQUSDgLBS2+V8icowm7A9CUO/uchDWMFKfy5+Wej0+X9j2peoqNSxYfkxwwyr/5XZt7yeskKIbg5kl/EaD0ns+843ATYL+HbUB8ijHMgWTk2r7gKAHZlI1C5iVdp5hPzoCTETiVK6a2Y0xiFI4yKpwr5l7hfLKSbLBx4D5YJ69QzUjPaO1/DQOGzRnatFaqVFyanWh4PHpdoDVLQNg2vgW1MZIKzSaXR2xosnPA2Fd3BQTtWAFQCr3mHDZ9/RuovuQAHPaGfw9Ou6d0Bht7WhIer4X0B2CpAV+WAZdvAI77fQpvGIJoDYvFryjDCP2egYtDRnd0aYVi/wDoHc9AP/ogUEqhDngFUKoKwBOMBArwMobQ4tahNBOSWACu8oJgDBIoLNCkEaaeOWYZMjtPSunDNKUkJTAix9gXBJ7MzIVjSAickqwHpHTWkQ44wiEmRrl+RaTMQd8NUyEVU5/n9f4O33fYbpJv246pHNsAJKNAKZmlBMoQsII+y754YyjHLPKs3jPICxB5fqH6D2syygw4acmFz1hgdBs65Y2ReCabli31+yNjXyUgZj06z3o9izbN/XSnbarez1KIRbtJ/RlfQcH31ToBPkDVURgMsy6QlMjrtFr31uFQUBbbZIXrYN7rzadS6LUa+JdvXI+R/Q/Eocf8jntWdjLibFVKQZWqBPJ7MS0t4Hv0UeAVhwAfOhf4yHlwix1woEL/2bgpEb/EfAes3jALWinBtACrxtFZBkxtg+62oUbGYCVFQCxU+KBk2tHMOGWJHQXYKuflKnmP2ms0gTBnBGHbHABP2oDY8eXu24+UYxI5NaM4ZrvCbQa7/hB8Y+AVc5LJST5Sepmn/8OAVfh8oQo1JuUO8x2Y/97R+4VjGAGzfsDWV6KEG3v7/iOSpTdmoR1R+e3k+hPON3lvOZbIXxM+Q+58GgO7AYwCYzcAxgr8AHrqc85DOgeKcm1mfigJq3GVyrdtnkPrzJRymjbFeZvU3MgEOdHURoEkJR7TbkC15ii7ExSlXBsZp76bcR8aCKUzkIrMqYHXGgBsN7H5G9dj7OBX4JDXvxZWHczPbfqlkoQqceyl0t/SAj4AuOce4Dd+A6jXbXYHu7gMaOgkhbWNKTZqG+LUUnJCBiOgwx8M2fPlhLTYa67hHZbWzoPO2CWUsNFZhsgZM6QdgLOHMJPISQ4Rx41QCpI7Qh0sfE8CBDxpKvrE4XiIRRlbnNzvUB0rn0GqZfvVNfRASAfPFB6D+zvcEORAMux/n2PeM+0KaCLSbgQgLMDJe8l7zqeK7SNRKm5DRfqY+e1Im7S3mdBuKGNaA+96+Qz93ocEZDFO5jzteb4yMLK90UiNSR9gFJsVZZ8d7ll5rrEKhnO7WjWqWQeyUomcku0mgWFjxqg/NTmWja0ARsYIDLsdW8SXJU41Mm4LAQ8lFcY0PMOAoLim12rhvm/9M5Yd+iq87Mg17hyWgpkH7qXS39ICviwDvvtd4IjfBJZP5HZwFvCMShNKSHlikfebQprv0W1Dz+yAqowCq/an3ZGR3jSDrU0GzIHFZQdyMpgYcDs5jynON+wxKUb+jfxi8EBGMh1xXQiazDQGSS6ebS7i3CLbt/3i/kb6FpX2+j2f7NOAY/2k16g6MQDR+Y7F7j1I4pQApAFO9p1/LwO+h88YHQt+1gBA+DMHVEEfQ4nSNhXMISAPlIg9v7aXxZ9H2PVkv8P3Y8+Fe6uCltEAAA8TSURBVF5zb22TkfNcDICR6/CVAmAM5qOybWr3rrwUeGKDmJk+JYlvrwQI6Kx0OEftlcrGo3SceFKnSfbFDjnKqXKVHGw4zdggMMxtdoYAQQmA7TYeuOHbWHnYYdj3sFe5d5J1hVSaUJzjXiT9LS3g+/rXgVNPBY75feCG68FSnS3aKoJy3RrOaGFwottIs6SyaEE//jCge1AvfRXU5Co61u0AbVPiiDOPqFTE49GuUEmmEDqXyCwanEi6VHKL2++M+TT2Rx04htjvcjHIp4o+oWhbAIG8pt9lSh6XEiaDp/htEBD1W6yeSpA/+wCkZIz9joXPNhR4yt8H9JnHIypxBoATk0bl/QdJnHCn5vZH3ngNCZpRwOzTbrS9yPh5bSj/OXMbm+CZYyrX2Pn2OTDgPNketal7Qo0agiMH5JcqVMklLfvPxI9rnwWi7zrQmJhz7LqmtaCznkncbVSlGfEpNbYMGJmAThLjRdpwUmF9zFZs4efuC4Q5lfY8a0tr9Lpt/OuNG7H6t34Lq19+MHgjbze/SkEJn4Zfd1pawLdlC3DyScCZZwDvO5vUIs1ZoNsw+SYrTq3JE0T1cVyBATy2K3DpIb4WgFLG85LJ7szCRSkXcgBIFhwG2b4A55QipSjAk9DClFKDnDzkjj+MCZMSm5T+bC045atbLbOXzyieYRjQ4nEKQWUowIyBUYSZyjb69mMAWM73LN5z7Ap4Cs7qXlS+n4OkUdvUIMBU8Xt4XweAd0xy7StlBOMVHauIY0wopQ6SrnVwjaeaj/UtNu/cOVpnxtHGBPpnmQNGfj0crsESXsBBrPFEKUAreFKi2X9DwYYhaQ3aPDemoRuzRjJVUPUJ6JEJaqs9J6TCGtkSmSfFpMLY5mQQCGqNrNfFgxu/h31f/Wos238/tzGQNsnqmCja++tJSwv4HnwQuOQS6H93NHDyW4DGTlJpVEegkhQuDqlHc8E4tEiyoGgKZNpgXW1q8QE0edKycUCpU5CoXOBeVWy2DTA4mRnvSSdC1emREh8xZhi7Jrg2/3T582Ig40lq8lzZrwHHcscHUF+pbhBgDjpvD4HTUOpTBV91udDnigCwbXeI/glsgOZz5HwJ+jOvJBbc0z73IJqnzb5jF7YxaCzEtQxGw4ydd4vQdq28D+RYnzJLV/vqU2tvFHb4kjBtRMbLvRbeEDAPgADEhDRKXOPQhDOp2iiBISfOMPGLqjpCSSvEGNs7D6sSNedl3R4e+t5N2O+1v43xVSsciDLgpRUqFPxrSksL+PbdF/rpp4FaDfjqF4Hj35CT0nz1n2Q8gJ5+FvrZJ6EqdaixcXrJadV8loFKjfTviZjMrBKQmVDoBv7ECj3ivM+IM0o/4gkcq50Wc+u37fF3ALkq3iHwmO/hMfsRHpPX9gNX82l/Us/DMXE8sAUtHEzlefP9HYzD0GreCKhFn6fPklxMVa/Wfl8suGAIYA/6EraZ04QEbYXPEwUg2a/w3SJy3QCQjQGg7WPs/txO/D1oDbP5FTwhM44y3AdOJm4TVHgt0B1ikm6SQiMDmg1K3N2l5PKqWoeujtJ9Oi0CvXLVhVKIMfB8C3LzUj4EkPU62PKDH+GA178e9fExG6bB71FVx6A7HdKqlasEvr8GtMjFpvYwTU1RZoJEAbNNI7WZAHCbIkmJxcku1Oy9qJEsX+0mQLcHdGe9W+ic1CO/CyYSfu+nehq48w3BRi6AEDjNv7SMvF0Nwb3dvYZJqr1LNAgU5wPMHBALxpSFxwZdNwiEzXcgz4jDd2rfVRjHKMcunBcq/5zg34L3mgNa4SiyqKpi5Sd8zj0D9xt0ngU70V8d9iU21uJ+sl/SZh2CqRuQ+OYk17ZsiNuSAKj8vstNXbjWwgQDOQk1bCt83qCHCkCa0KY5QrY2Y2YSibMDnGwgKUFLxxt5Tw3ahFdqQuhNoLptKstkEud798kyqFIZqNShrdOMTBpgzg3MI0mpgkP/wwnIej1s+eGP8LKjj0almlopUzenobMMSZKQY5+0Qy5hWloS3z/9E/DBDwLHHgv9mb8jVWe3Te64pQoATdUUWrMAFHS7Cf3c01Djy6FW7A9VNud4E40mvWa3ZuIKZnKGAeIDGJRXYDWwo8lPSYP08bLtHCOa7zg/m7xPP2Yp/4b4faF/L+Q+u3PfCJhHgVaMwbAS76Bj9mNIcLcU2fQsVOLNaTEUcp6i3u0j86AvCAdzyetH7D1xf+V7gb+s+klLQ29clP3q1Lni0XKAN+S42zbmC98J77H4pMO0cF5aMwJG375onlP0SSkFnXXJkabdotGsVMX4JRRXKPKPklSOfJIAA5BZt4tf3vkTvPR1r0MpFWEPyvg7KAU1Mmkve+op4Be/AMbGgDVrlg4mLi3g+8u/hL7sMmDlCuCH3wFW7UMqhW6ThAZZBVxrm65H2YrdLi+mrVJuPbLSXE07j6Ta0V4fiYmTqs2YM8rzODN0DiB392+I3wcwz0HHQ3Vd9O8BfbAUAGjIqKN/YwHguxvg7KkRBzBxARpubzUAHHb1WHg/2yGIG9sOiGN9mpGiXN/NQqQv0Y1Zvw1U2Occuva/T44i4x7tbz+SY/P8kPa8UQ0w8uNbD9Igp6x9JRpoNaDaLfqelux1ilPJMY+0z+WXXMuyHrb+/B4c+NuvBQB7TGsNVRnFQ4+UcfbZwM03k+Wp2wWWLQM+9jHgjDMGP9s999yDM844Aw888AAOP/xwXHHFFTjqqKMAAFdffTXWrVuHarWKK6+8EscffzwAYMuWLTjttNNwyy23IF0Ex5ulBXwrVwLPPgs9OgJc/UXg2GNEnI4h9lQMXmSewh2hZCLB3+F19kO2EWEq0cvn6VPfP/dEm4vU7qK1OT/ND+YQvy/070HtLuZ9I+3Q4CwMYBcqdQ91rjnHfoTvS4GkTQfaDkd0eKb/7CFZHIuALv+cu0z7B7y2AyDO3Xc+kF06RHk4ReYbuZHgDX6SGA9TkzGn0yKHPt6YJSlQqUCVaiQ02M0ljc/s9DRGx8e9+yqlcP8DwO+eMImpqfy+YWQEeP/7gU98It7vdruNQw89FOeccw7OOussXHbZZVi/fj0eeughJEmCQw45BHfeeSfuuusunHfeedi8eTMA4MQTT8T555+Po48+elHGb2kB38c+Rv9e9Srgpz+FLimKhXn2SWSP/wLJ/ocA+7wUfg08DjgVaZ+kxObtPBX8bCjm79zuGPAWVHRx9qGBw72H28z9uattBtcupK8DaU8Af3DtngD+3J8La9NbghIgFQRA8pyOgCiCvz2wDf+OAXe/c2S7u7BJ4LGIgo3wgPbWGh8Xv3MbOfVr0H50fKPo6Y9b5Kt3WdCECi8I8DraL++3PU82QTXHLkp1ua07CVOvsAFbJqpcgapQftJtj/wSKw8+CNDkL89araNPmMDPfl7tyyLqdeDnPwcOOyx/bOPGjTj99NPx2GOPWcHkwAMPxIYNG7B27VqccsopuP3229FsNrFixQrMzc3huuuuw8aNG7Fhw4ZFG5+l49zSbgM33gjUatBbtwJ3/AhYcxj001uh9nkZ0qOOpfN48fBLyXqA4ng+kSKLa32Fu96C9iwtFeBfSLsaQVP9bEgQzjuOcox0vjZDING8S5+nn7k/d2fPO/9mwgG6BFQprQ0jqQUAHqrG5XOEYO6BdXheeC73OxyTYFyVqWvogfJCgLpPu/1exaANVVQiF5QkQFLx+u7upwGdkba0Ngqpntcm1GvVyw8GV6unN5fgoS0Km+/vD3oA0OkAn/0s8PnP54/dd999OPLIIz1t3JFHHon77rsPb3rTm7B9+3Y89thjuPvuu7FmzRpMT0/joosuwk033dT/hrtASwf4brkFuO8+oNGg6fmp/wlc8xUkhx7lzpH2FM/DTKhSdM9NsrCubEEFvVho0STTXaRFUAQN71E8xL12vzuL0hB5Upp2cmAa/i0kYE/6nud6DcCqlM3POQnUHPfmhQhjsqDIgMxtit8BFw4G2HmkAHIYzDIw5OmsB91q4l/uKqFcBhqN/mPU7QI//Wn82MzMDCYnJ73fJicnMT09jSRJcOmll+LUU09FtVrF5ZdfjgsuuABnn302Nm3ahAsvvBCVSgXr16/HEUcc0b8DQ9DSAb599wXX6tLVKtRha4CJVYWkVlBBBT1v9KLkNgvapOTP9ezm/D3LoOe2kaBQGYFSKVCtob58uJRmtT55r8fGxjA1NeX9NjU1hXFjSzzhhBNwwgknAADuvfde/OxnP8PFF1+Mgw8+GLfeeiu2bt2KM888E3fcccdQ/ehHSwf41qwBPvc5YP16qFe/GvjEJ6nYZUEFFVRQQbtMfcG82yJ1aa9LRXirdRzzRlJlDqLRUeCd74wfW7NmDdavX0/eoUZo2bRpE9773vd652mt8b73vQ+XXHIJtm3bhl6vh4MOOgj77rsvNm3atLAHjNDSSsd9+unA5s3AVVdR4EhBBRVUUEF7hkaXEeBNroYyyavHxoD3vIccWPpRuQycdlr82HHHHYc0TfHZz34WrVYLn/vc5wAAb3jDG7zzvvCFL+A1r3kNjjrqKKxcuRKNRgP3338/fvCDH+CQQw7Z7UdbWl6dBRVUUEEFvaDU6QBvfzu5XczMuN/rdaBSAW66CXjta/tff/fdd+PMM8/E/fffb+P41q5da49v27YNxx13HG677TZMTFAC76uuugrr1q1DrVbz4vt2lQrgK6igggoqaEGUZcB3vgOsX0+1A8bGgD/7M+DMM4FVq17o3s1PBfAVVFBBBRW0V9HSsvEVVFBBBRVU0G5SAXwFFVRQQQXtVVQAX0EFFVRQQXsVFcBXUEEFFVTQXkUF8BVUUEEFFbRXUQF8BRVUUEEF7VVUAF9BBRVUUEF7FRXAV1BBBRVU0F5FBfAVVFBBBRW0V1EBfAUVVFBBBe1VVABfQQUVVFBBexUVwFdQQQUVVNBeRQXwFVRQQQUVtFdRAXwFFVRQQQXtVVQAX0EFFVRQQXsVFcBXUEEFFVTQXkUF8BVUUEEFFbRXUQF8BRVUUEEF7VVUAF9BBRVUUEF7FRXAV1BBBRVU0F5FBfAVVFBBBRW0V1EBfAUVVFBBBe1VVABfQQUVVFBBexUVwFdQQQUVVNBeRQXwFVRQQQUVtFdRAXwFFVRQQQXtVfT/ARsuss67GvdmAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "K = 56\n",
    "snap_plot(nets[K:K+1], size_scale = 1/300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.LineCollection at 0x7f59f0df5250>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mdO99Igohoo1E9InldSIR/biHbdQA1gLIApAI4D4iSuyy2goA7zFzKoCFAF515Q0IIYQQwjmu3LL3BoA8AMMtr48CeKKHbW4EUMLMJ5i5A8BmALO6rMMAfC3P/QCcdiEmIYQQQjjJlaQfyMzvATADADMbAZh62CYcQLnN6wpLma3nASwhogoAWwE8Zq8iInqYiPKJKL+mpsaFsIUQQggBuJb0m4loGJQzcxDRTQDq3RDDfQDeYOYIAHcCeJOILouLmTcwczozpwcFBblht0IIIcTg4krv/f8A8CGAkUT0FYAgAPN62KYSQKTN6whLma0fA8gEAGbeTUR6AIEAzroQmxBCCCF64Erv/QIimgJgFAACUMzMnT1s9i2AeCKKhZLsFwJY1GWdMgAZAN4gotEA9ACk/V4IIYRwM6eTPhHN6VKUQET1AL5nZrtn5cxsJKKlUDoAqgH8mZkPEdELAPKZ+UMA2QD+ZBnmlwE8wMx8JW9GCCGEEI650rz/YwA3A9hueX0rgH0AYonoBWZ+095Glnvut3Yp+7XN88MAJrkQhxBCCCGugCtJXwNgNDNXA8p9+wA2AZgA4F8A7CZ9IYQQQlwbXOm9H2lN+BZnLWXnAPR0bV8IIYQQ/cyVM/0dRPQxgL9ZXs+1lA0BcMHtkQkhhBDCrVxJ+r+Akuit1983Adhi6XR3RePyCyGEEKLvuHLLHgPItTyEEEIIcZ1x5Za9RlhG47NRDyAfQDYzn3BnYEIIIXrfvn37gjUazesAkuFaPy9x7TEDOGg0Gn+SlpZm91Z6V5r3/whl7Py/QhmcZyGAkQAKAPwZyi18QgghriMajeb10NDQ0UFBQedVKpWMkXIdM5vNVFNTk1hVVfU6gLvtrePKUd3dzLyemRuZuYGZNwCYzszvAvB3R8BCCCH6XHJQUFCDJPzrn0ql4qCgoHoorTb213GhvhYiupeIVJbHvQDaLMvkyyKEENcnlST8gcPyu3SY211J+osB3A/l/vxqy/MlROQJYOnVBCmEEEKI3udK7/0TAGY6WLzLPeEIIYQQ/1ZTU6MOCgoy9XccA0WPZ/pE9EvLz5eJaE3XR++HKIQQYrB69NFHL07PvmDBguj+jGUgcKZ5/4jlZz6UCXa6PoQQQoirkpub6xsTE5McFRWVvHz58lBrWUlJif65554LaWxsVJ08eVL/2GOPhU+bNm2kvTrUanWawWBIjI+PT8rKyhrR2NjY57cg1tbWql966aUg27LU1FSD9bmXl1dqX8dkq8cPhJk/IiI1gDHM/Jeujz6IUQghxABmNBrx5JNPRm3duvXo0aNHD23ZsiVg3759+uDgYOOCBQvqVq5cWf311197zZo16/zLL79c6eXlZbZXj4eHh7moqOjwsWPHDmm1Ws7JyQmyt15XZrMZJpN7riDU1dWpN27cGGxbtn///iK3VO4GTh0FMbMJMv2tEEKIXrBjx44h0dHR7YmJiR16vZ7nzJlzLjc3d2hBQYHn+PHjWwFgz549XpmZmQ0AoFare7zbYPLkyU0lJSUeAPDqq68GjBkzZrTBYEhctGhRtNFoRHFxsS4mJiZ59uzZMQkJCUnHjx/XvfLKK8MSEhISR40alXjPPffEOtoWAIqLi3UjRoxIWrhwYXRcXFzSpEmT4puamig7OzuivLzcw2AwJD7yyCMRgP2ze0f19jZXmj6+I6IPieh+IppjffRaZEIIIQaF8vJyXXh4eIf1dUREREdlZaUuKCjIuGHDhsCCggL9kSNHPMeNG9d25swZTWBgYLcZsrOzE3l5eb5jxoxpLSgo0Ofm5gbk5+cXFRUVHVapVLxu3bphAFBWVuaxdOnSmpKSkkMNDQ2qVatWhe3cufNocXHx4fXr15d1t61le/3jjz9+tqSk5JCfn59p06ZN/jk5ORWRkZHtRUVFh9evX19hL76e6u1NrozIpwdQB2CqTRkDeN+tEQkhhOgXT+cWRh6tavRyZ50JoT4t/z0vpfxKtl28eHH94sWL6wFg8+bNpwAgLCzMuGHDBrvJtL29XWUwGBIBYMKECY3Lli2rXb16deDBgwe9UlJSRgNAW1ubKjg42AigMSwsrCMjI6MZAPLy8nxnzpx5PiwszAgAISEhpo0bNwY42BYAEB4e3j5x4sRWAEhNTW0pLS31ANDU0/vatm2bT3f19iZXkv7rzPyVbQERSZO/EEKIqxIZGdlRWVmps76uqKi45MzfWdZr+rZlzEzz58+vW7t2baVteXFxsc5R34CetrXS6XQXLzOo1WpubW119pJ5t/X2JleS/ssAxjtRJoQQ4jp0pWfkV2vKlCnNpaWl+qKiIl1MTEzn+++/H/D222+7ZRK3zMzMhjlz5sQtX768Ojw83FhdXa2ur69Xd11v+vTpDfPmzYt79tlnq0JDQ03V1dVqR9smJCQ4PCDx8/MzNTc3d5v8r6Red+kx6RPRzQAmAggiov+wWeQL4LIPTgghhHCFVqtFTk5OWWZmZoLJZMKiRYtq09PT23resmdpaWltK1asqMzIyEgwm83QarW8Zs2asoiIiE7b9dLT09uys7PP3HLLLQaVSsXJycktW7ZsKbW3bXfJOTQ01JSWltYUHx+fNHXq1Hp71/UdxdQXSZ+Yu+8ESURToMyg9yiAdTaLGgF8xMzHei06B9LT0zk/P7+vdyuEENc1ItrHzOm2ZYWFhaUpKSm1/RWTcL/CwsLAlJSUGHvLejzTZ+adAHYS0RvMfMrRekT0MjM/duVhCiGEEKI3OX3LXncJ30I69QkhhBDXsD4folAIIYQQ/UOSvhBCCDFIuDPpkxvrEkIIIYSbOTO17puWn8t6WPV/3BKREEIIIXqFM2f6aUQ0HMBDRORPRAG2D+tKzPxGr0UphBBCiKvmzIh86wB8AWAEgH24tBmfLeVCCCGEuMb1eKbPzGuYeTSAPzPzCGaOtXlIwhdCCNHnampqZETYK+DKffo/I6IUIlpqeYx1ZjsiyiSiYiIqIaJnHKxzLxEdJqJDRPRXZ2MSQggxOD366KOR1ucLFiyI7s9YridOJ30iehzA2wCCLY+3iajbEfiISA1gLYAsAIkA7iOixC7rxAP4FYBJzJwE4AmX3oEQQojrWklJiXbChAkJI0eOTIqLi0tauXJlsHVZeHj4mISEhESDwZCYnJw8GgByc3N9S0pK9M8991xIY2Oj6uTJk/rHHnssfNq0aSPt1a9Wq9MMBkNifHx8UlZW1ojGxsY+v129trZW/dJLLwXZlqWmphqsz728vFL7Ig5X3vhPAExg5l8z868B3ATgpz1scyOAEmY+wcwdADYDmNVlnZ8CWMvM5wGAmc+6EJMQQojrnGXCnYrjx48f+vbbb49s3LgxeN++fXrr8p07dx4tKio6fPDgwSMAEBwcbFywYEHdypUrq7/++muvWbNmnX/55ZcrHU2Va51y99ixY4e0Wi3n5OQE2VuvK7PZDJPJ5Jb3WFdXp964cWOwbdn+/fuL3FK5C1xJ+gTA9t2b0PO9+eEAbKdqrLCU2UoAkEBEXxHRHiLKtLtzooeJKJ+I8mtqalwIWwghxLUsOjq6c/LkyS0A4O/vbx45cmRrWVmZztH6BQUFnuPHj28FgD179nhlZmY2AMqc9j3ta/LkyU0lJSUeAPDqq68GjBkzZrTBYEhctGhRtNFoRHFxsS4mJiZ59uzZMQkJCUnHjx/XvfLKK8MSEhISR40alXjPPffEWutytP2IESOSFi5cGB0XF5c0adKk+KamJsrOzo4oLy/3MBgMiY888kgE4Pjs3l697uJK0v9fAHuJ6Hkieh7AHgAb3RCDBkA8lJn87gPwJyIa2nUlZt7AzOnMnB4U5NRBmhBCiOtMcXGx7vDhw15TpkxpspZlZGTEJyUljV61alUgAAQFBRk3bNgQWFBQoD9y5IjnuHHj2s6cOaMJDAzsNjt2dnYiLy/Pd8yYMa0FBQX63NzcgPz8/KKioqLDKpWK161bNwwAysrKPJYuXVpTUlJyqKGhQbVq1aqwnTt3Hi0uLj68fv36MgDoYXv9448/frakpOSQn5+fadOmTf45OTkVkZGR7UVFRYftTbdr1V297uDMLXsAAGZeTUQ7AEy2FD3IzPuty4nI39pEb6MSQKTN6whLma0KAHuZuRPASSI6CuUg4FtnYxNCCOEGH/wiEmcPe7m1zuDEFtyztrznFYH6+nrVnDlzRr700kvlAQEBZgDYtWtXUWxsbGdlZaVm6tSpCUlJSW2LFy+uX7x4cT0AbN68+RQAhIWFGTds2GA3mba3t6sMBkMiAEyYMKFx2bJltatXrw48ePCgV0pKymgAaGtrUwUHBxsBNIaFhXVkZGQ0A0BeXp7vzJkzz4eFhRkBICQkxAQA27Zt83G0fXh4ePvEiRNbASA1NbWltLTUA0DTZYHZ0U29buF00gcAZi4AUOBg8RcAxncp+xZAPBHFQkn2CwEs6rLOB1DO8P+XiAKhNPefcCUuIYQQ17f29na66667Rs6fP//cj370owvW8tjY2E4ACA8PN951110Xdu/ePSQrK8upBGplvaZvW8bMNH/+/Lq1a9deciJaXFysc9Q3wNntdTrdxcsMarWaW1tbXblTzm697uJS0u/BZdf3mdlIREsB5AFQQ7nX/xARvQAgn5k/tCy7g4gOQ+kn8DQz17kxLiGEEM5w8ozc3cxmMxYuXBidkJDQ9vzzz1dbyxsaGlQmkwn+/v7mhoYG1fbt232fffbZ0+7YZ2ZmZsOcOXPili9fXh0eHm6srq5W19fXX3bv//Tp0xvmzZsX9+yzz1aFhoaaqqur1SEhISZnt7fy8/MzNTc395j8HdWbkJDQcbXvGXBv0rfbgYKZtwLY2qXs1zbPGcB/WB5CCCEGmc8++8z7gw8+GBYfH99qbYb/7W9/WzlmzJjW2bNnxwGAyWSiuXPn1s2bN6/BHftMS0trW7FiRWVGRkaC2WyGVqvlNWvWlEVERHTarpeent6WnZ195pZbbjGoVCpOTk5u2bJlS6mz21uFhoaa0tLSmuLj45OmTp1a7+i6vqN63ZX0Scm5bqiIqICZuzbv94r09HTOz8/vi10JIcSAQUT7mDndtqywsLA0JSWltr9iEu5XWFgYmJKSEmNvmUytK4QQQgwSLiV9IppMRA9angdZOuhZZbg1MiGEEEK4lSvD8P4GwP+DMmQuAGgBvGVdzszn3BuaEEIIIdzJlTP92QDuBtAMAMx8GoBPbwQlhBBCCPdzJel3WHraMwAQ0ZDeCUkIIYQQvcGVpP8eEa0HMJSIfgrgcwB/6p2whBBCCOFuTt2nT0QE4F0ABgANAEYB+DUzf9aLsQkhhBDCjZxK+szMRLSVmccAkEQvhBBCXIdcad4vIKIbei0SIYQQwkk1NTUOh7wVjrmS9CcA2E1Ex4noABF9T0QHeiswIYQQwpFHH3304gyuCxYsiO7PWK4nriT96QBGApgKYCaAGZafQgghxFUJDw8fk5CQkGgwGBKTk5NHW8tzc3N9Y2JikqOiopKXL18eai0rKSnRP/fccyGNjY2qkydP6h977LHwadOmjbRXt1qtTjMYDInx8fFJWVlZIxobG905Gq1Tamtr1S+99FKQbVlqaqrB+tzLyyu1L+JwZbq/U8x8CkArlNv2Lt6+J4QQQlytnTt3Hi0qKjp88ODBIwBgNBrx5JNPRm3duvXo0aNHD23ZsiVg3759+uDgYOOCBQvqVq5cWf311197zZo16/zLL79c6WhKXOvUuseOHTuk1Wo5JycnyN56XZnNZphMJre8t7q6OvXGjRuDbcv2799f5JbKXeDKiHx3E9ExACcB7ARQCuCTXopLDCAdbUYUflGO9ha7k08JIYRdO3bsGBIdHd2emJjYodfrec6cOedyc3OHFhQUeI4fP74VAPbs2eOVmZnZAChz1/dU5+TJk5tKSko8AODVV18NGDNmzGiDwZC4aNGiaKPRiOLiYl1MTEzy7NmzYxISEpKOHz+ue+WVV4YlJCQkjho1KvGee+65OPy8o+1HjBiRtHDhwui4uLikSZMmxTc1NVF2dnZEeXm5h8FgSHzkkUciAMdn9/bqdRdXptZdCeAmAJ8zcyoR3QZgidsiEQOSyWjGtg0HUX74HEjz5rQAACAASURBVGrKG3H7A4n9HZIQwoHnvnousuR8iZc764zzj2tZOWlluTPrZmRkxBMRHnzwwZqnnnqqtry8XBceHn5xStmIiIiOvXv3eicnJ7du2LAhMDg42HjkyBHPFStWnD1z5owmMDCw2+zY2dmJvLw83zvuuKOhoKBAn5ubG5Cfn1/k4eHBS5YsiVq3bt2wadOmNZaVlXls3LjxZEZGRml+fr5+1apVYbt37y4KCwszVldXqwGgh+31b7311omJEyeeuvPOO0ds2rTJPycnp2LGjBmeRUVFh7uL0VG9S5curXPmM+yJK0m/k5nriEhFRCpm3k5Ef3RHEGJgYjPjn5uOoPzwOQyPH4riPVUYNSEUkaMD+js0IcQ1ZteuXUWxsbGdlZWVmqlTpyYkJSW1OVp38eLF9YsXL64HgM2bN58CgLCwMOOGDRvszlHf3t6uMhgMiQAwYcKExmXLltWuXr068ODBg14pKSmjAaCtrU0VHBxsBNAYFhbWkZGR0QwAeXl5vjNnzjwfFhZmBICQkBATAGzbts3H0fbh4eHtEydObAWA1NTUltLSUg8ATc58Dt3U6xauJP0LROQN4F8A3iais7CMwy9EV8yMr7aU4Og31bjpnhFIyYjE5pXfYMdfi3HfczdCo5O7bYS41jh7Rt4bYmNjOwEgPDzceNddd13YvXv3kB/84AdNlZWVOus6FRUVl5z5O8t6Td+2jJlp/vz5dWvXrq20LS8uLtY56hvg7PY6ne7iZQa1Ws2tra2u9J+zW6+7uNKDcRaUTnxPAtgG4Dik975w4NTBOhR+UY4xt0Vg/PRoaLRq3LrYgIaaVny7tbS/wxNCXEMaGhpU58+fV1mfb9++3Xfs2LGtU6ZMaS4tLdUXFRXp2tra6P333w+YO3fuBXfsMzMzs+Hjjz/2r6ys1ABAdXW1+ujRo7qu602fPr3ho48+8q+qqlJb13Nleys/Pz9Tc3NzjznX1Xpd5fSZPjPbntX/xV0BiL7FZkZLQwcaz7WhpaEDne0mdLabYOwwwWQ0w2xi6PQaxIwNhF+Q5xXv57vPyuDt74FJ8+KgjOIMRIzyh2FiGL77tAyRBn9EGKSZXwgBVFRUaGbPnh0HACaTiebOnVs3b968BgDIyckpy8zMTDCZTFi0aFFtenq6w2Z/V6SlpbWtWLGiMiMjI8FsNkOr1fKaNWvKIiIiLulxnJ6e3padnX3mlltuMahUKk5OTm7ZsmVLqbPbW4WGhprS0tKa4uPjk6ZOnVq/fv16u5ciHNWbkJDgcguHPaRMnOfEikRzAPwBQDAAsjyYmX3dEYgr0tPTOT8/v693e11qrm9H+eFzqDpRj6qTDTh/phlmk3O/88BIb8SmBCEwwhsBYUPgG6iHSt1z49DZUw342+/zMXFuHFKnRV2yrK2pE++v2ocLZ1sxaW4cxk6NuHhQIIToXUS0j5nTbcsKCwtLU1JSavsrJuF+hYWFgSkpKTH2lrlyTf+/AMxk5iNuiUr0qpryRhR+UY5j31Zbzt7VCIn1RVRiJHwC9PAZpoeXrw46vQZavRpanRoqDUGlVqHpfBtO7K9Byb6z+Pbjkxfr1A/RYtpDiYhKGtbtvr/7rAw6vRpJk4dftkzvrcW8/5eOz984jF1/O4bq0gZMuS8BHl5at38GQgghLuVK0q+WhH/tYGbUljehprwRTefa0Hi+HS31HWhr6kBrUyca69qg8VAj6QfhSJw0HMOGDwGpnDuj9h3miXG3R2Hc7VHoaDPifFULzp9pxnefl+PjVwoxcW4cUjIi7Z6hN9S2oqSgBikZkdB52v966Tw1yHpkDAo+PYU9/3cCpQdqkTh5OFIylAMSIYQQvaPHpG9p1geAfCJ6F8AHANqty5n5/V6KTdjReK4NxXuqcPSbKpyvalEKCRjiq4OXnwc8vbUYGuqFMbdGIHFS2FWfQev0GoTE+CIkxhcjUoPwxRtH8FVuCepON+O2xaMua+4/8M8KEICxt0V0Wy+pCGmZMYhOHob9n5bhwPYKHNheAf9QL/gFecI/1AujJw7H0BC33jIshBCDmjNn+rY99FsA3GHzmgFI0u8DzIyDOyvx9ZYSGDvNGB4/FCkZkYgwBMDb3wNqTe8PJa3Ta5D5cDK++fgk8reWQqdX45Z7Ey4ub23qwKGvTiPuhmCnz9gDI3ww7aEk3HTPSBzedRq1FU24UN2CUwfrcHBnJTIeSMSIcU6NmCmEEKIHPSZ9Zn6wLwIRjjVfaMc/3zyCskPnEJkYgCn3jbqqnvVXg1SECXePQGe7CYVflMM/xAvJUyJQX9OKf6wthNloRuo01ye88gnQY8LdIy6+bqhrxbb1B/HJuu+RfmcMbpgRC5WTlyeEEELY5/Q1fSL6LwC/g3Kv/jYAYwE8ycxv9VJsAkpv99w/5KOtqRM/WJiA5Cnh10Rv94lz43DhbAv+9e4xdLSbsP/TMrCZcffj4xAY4X3V9fsO88Scp8fjX+8cRf7WUhz7thqJk4dj9MQwePq47ZZVIYQYVFzpyHcHM/+SiGZDmWxnDpTR+STp9xJmxva3itDS0IE5T6chJKbP7450SKUi3PHjJLz/3/uw+/3j8AvyxIylKW69Bq/RqnHb/QZEJQ3Dge3l2P3349j74QmEjfRDULQvgqN94D3UAxqdGmqNCmqtCmrLHQiePtpr4uBICCGuJa4kfeu6dwH4GzPXyx/V3nXk6zM48V0Nbp4z8ppK+FY6vQYzlqbg0JenkTI1EnpvLdhkAqndN8QuESEuLRhxacE4d7oZR74+jdMl9TiwvRxmo+PxBkJH+OGuX4yFfojcCiiEEFauJP2PiagISvP+z4goCIBbRkYSl7tQ3YIv3z2K8FH+SL09qucN+om3/7+vxbcUFODUkvuhHz0a3rfdBp/bM6A3GNy2r4DhQzBpXjwAZfa+c6eb0drUAWOHGaZOM0wm5WdrYye+3XoSH6wuwMzHx2GIn4fbYhBCXBtqamrUQUFB7pnsfhBxZRKAZwBMBJDOzJ1QevLPsi4nomnuD2/wYGacPdWA73dUYPvbRfjwf76DWqPC7Q+Mdvr++v5W//e/g/R6kFaL2rVrcfKe2Wg9cKBX9qXWqBAU5YOoxGEYMS4I8TeEwHBTGJJuCUf6nTGYsTQF9bVt+PuqAjTUtvZKDEKI/vPoo49GWp8vWLDA9d7Dg5RL93kx8zlmNlmeNzNzlc3iP7g1skGi8Vwb8reexNu/2YO//T4f/9p8FMf3nYXPMD0yH06Gt//1MVgNd3ai8dPP4DN1KmI2v4PYDz4AALQVF/dLPJGGAMxaNg5tzZ3462/3Yudfi1FfI8lfiGtRYWGhh8FgSLQ+vL29U1944YVgAAgPDx+TkJCQaDAYEpOTk0cDQG5urm9JSYn+ueeeC2lsbFSdPHlS/9hjj4VPmzZtpL361Wp1msFgSIyPj0/Kysoa0djY2Pv3OHdRW1urfumlly65/zg1NfViU6iXl1dqX8ThSvN+T+yejhJRJoD/AaAG8Dozv+RgvbkAcgHcwMwDfmB9ZsahL0/jy/eOwmxkDI8firTMaESODsCQoR7XXSe05j17Yaqvh29WJgDAI24koNWis6ys32IKHeGH+b+6AQXbSnH469M49GUlIhMDMDx+KMLihiIoygdameJXiH6XkpLSbp361mg0IjQ0NGXhwoUXZ9PbuXPnUet89gAQHBxsXLBgQd3y5ctr8vLyvGfNmnX+2WefPTtr1qxYe/XbTq179913x+bk5AQ9//zz1T3FZTabwcxQu6GfUl1dnXrjxo3BzzzzTI21bP/+/UVXXbGL3Jn0L+tVRURqAGsBTANQAeBbIvqQmQ93Wc8HwDIAe90YzzWro82IHW8X49i31YhKUu679w3sn/vu3aVh2ydQDRmCIZMnAwBIrYYuIgIdpaf6NS6/IE/cdv9o3DhzBAr/WY7SA7XYc+jExeWePlr4BCjzEKg1Kqg0KqjVBFITVCoCWR8EqNUq6Dw18PDSQK1VwdRpVvoTGE0wmRhmE4NNDGZW/jN0/R9BNkfGloM6uviPsr7RaIaxwwRjhxlsZjAD6DIpllqngtZDA62HGhqdChqtChqtGio1XXwQ0cXNiCy7I7I8VwIhsr5HQKVWQaUhqDUq+AV5Sj8I0W8+/PBD36ioqPbuZpUrKCjwHD9+fCsA7Nmzx2vGjBkNgDJ3fU/1T548uenAgQOeAPDqq68GvPbaayGdnZ00fvz45k2bNp06fvy4bvr06QmpqalN33///ZCtW7ce+/TTT33WrFkTQkQYPXp06wcffHCyu+2zsrLib7zxxqb8/HzvkJCQjry8vJLs7OyI8vJyD4PBkDhlypSG9evXV3h5eaW2tLTs7xqjvXo1Gveka3cmfXtuBFDCzCcAgIg2Q+kHcLjLeiuhXB54upfj6XftrUZs+a99uFDVjJvuGYHxd0RfN9fsHeGODjR+/gW8M6ZC5fHvZKGLjkZHP57p2xoy1AMT58Rh4pw4tDZ14ExJPc6dbkZjXSsaz7Wh6UI7TEZWphc2KgnXzPh3EjfzxeWOqFTKwYJtYr2IbY4BrNmYLz8u0GhV0OjU0GhVFw82rMnauqmpU5kOuaPNBFOn43iulFqjQsrtkUjLjIZO39t/IsS15PTyZyPbjx1z69jXHvHxLcNf/M9yZ9d/5513AubNm1dnW5aRkRFPRHjwwQdrnnrqqdqgoCDjhg0bAoODg41HjhzxXLFixdkzZ85oAgMDjY7qBYDOzk7k5eX53nHHHQ0FBQX63NzcgPz8/CIPDw9esmRJ1Lp164ZNmzatsayszGPjxo0nMzIySvPz8/WrVq0K2717d1FYWJixurpaDQA9bK9/6623TkycOPHUnXfeOWLTpk3+OTk5FTNmzPC0tjg44qjepUuX1nW3nbPc+T+61E5ZOADbX3YFgAm2KxDReACRzPwPInKY9InoYQAPA0BU1LXbm70nX28pwYWqZsx8bBwiEwfGfPLNe/bAXF8P38ysS8p10VFo3rsXzHxNXa7w9NZhxLigKxre19RpRnurEcYOk5Kcdcr4ACoV9ct7ZDPDZFJaHMyW1gaz6fIDAeXARfkJAGazcsRhNisHNNZtTZ1mFO+tQsG2Uyj6+gzSsqIRmxIkEyGJPtHW1kaff/653+rVqy/ONb9r166i2NjYzsrKSs3UqVMTkpKS2hYvXly/ePHiegDYvHnzKQAICwszbtiwwe4c9e3t7SqDwZAIABMmTGhctmxZ7erVqwMPHjzolZKSMtqyb1VwcLARQGNYWFhHRkZGMwDk5eX5zpw587z18kJISIgJALZt2+bjaPvw8PD2iRMntgJAampqS2lpqQeAJmc+g27qdQuXkj4RTQQQY7sdM2+y/JzjYLPu6lMBWA3ggZ7WZeYNADYAQHp6unMTwl9jyo+cw+Fdp5F6R9SASfgA0PDJNqh8fDBk8qRLyrVRUeDWVhhraqANDu6n6NxLrVXBS3vtjAhIKoJGpYZG676+CZGJAUi+NRxf/e0YvnxXeQQMH4L49GCMmxbl1n2Ja4srZ+S9ITc31y8xMbElMjLyYpKLjY3tBIDw8HDjXXfddWH37t1DsrKynEqgVrbX9K2YmebPn1+3du3aStvy4uJinZeXV49NaN1tr9PpLuYotVrNra2trtwpZ7ded3E6ECJ6E8AqAJMB3GB5pPewWSWASJvXEZYyKx8AyQB2EFEpgJsAfEhEPdV73eloM2L7m0UYGuKFG2fY7WtyXVKa9j+HT0YGVLpLk6EuSrmLpvNU/17XF64LjfXDnKfTcN9vJmDi3Dh4emux98OTeO/FfFSXNvR3eGKA2rx5c8C99957zvq6oaFBdf78eZX1+fbt233Hjh3rlttwMjMzGz7++GP/yspKDQBUV1erjx49etkR/fTp0xs++ugj/6qqKrV1PVe2t/Lz8zM1Nzf3mHNdrddVrpzppwNIZGZXzrK/BRBPRLFQkv1CAIusC5m5HkCg9TUR7QDw1EDsvb/n78fReL4Nc7LHQzOAeow37/0G5sZG+GROv2yZLlq5DNNRVgavG27o69DEVSIiBIQNQUDYEKROi8KpQ3XY/mYRtvzXPoydGoHEicMRMHxIf4cpBoiGhgbVrl27fP/yl79cPEuoqKjQzJ49Ow4ATCYTzZ07t27evHluOepMS0trW7FiRWVGRkaC2WyGVqvlNWvWlEVERHTarpeent6WnZ195pZbbjGoVCpOTk5u2bJlS6mz21uFhoaa0tLSmuLj45OmTp1av379eruXIhzV213HRleQszmciP4G4HFmPuPSDojuBPBHKLfs/ZmZ/5OIXgCQz8wfdll3B5xI+unp6Zyff/0cF1w424K3f70HY2+LwC0LEnre4DpSs+Zl1K5bh1H530LldWn/HzYaUTQuFcMeegjB//FkP0Uo3Km9pRO7cktQtPsMwMooiSNSgxCR4I+QWN8BdUA7EBHRPma+pCW1sLCwNCUlpba/YhLuV1hYGJiSkhJjb5krZ/qBAA4T0TcA2q2FzHx3dxsx81YAW7uU/drBure6EM9143jBWQDAuGnXbwdER1oPHYTHyJGXJXwAII0GuvDwa6YHv7h6Hl5aZPxwNG6aNQIn9tegZN9Z5G8tRf4/SqHSEIIifeAX7AnfQE/4+OstkyCpoNEptwL6BnlCre7zcVGEEBauJP3neyuIge54QQ1CYn0HXA9oZkbbwUPw/sEPHK6jjY5CR5lc0x9ohvh5YMytERhzawTaWzpxpqQep49dwNlTDTh97AKOfVPddXgBAMptjT7DlHER9N5a6IdoofFQQ6tTQa1VX5wl0fpTpSbo9BrEjg2EWisHC0JcLaeTPjPvJKIQKB34AOAbZj7bO2ENHPU1ragpa8TEOXH9HYrbGc+cgamuDvrkJIfr6KKi0Zq/75q7bU+4j4eXFjFjAxEz9mL3HJiMZrQ0dFycCKmj1YT6sy24UN2C+tpWtDZ2oqG2DWdPNcLYYUJnh6nbWRMTJoTg9gcS5TskxFVyOukT0b0A/hvADijDjrxMRE8zc24vxTYgHN+vHBeNHO/6PeHXutaDBwEAnmPGOFxHFxUFc0sLTHV10AQGOlxPDCxqjeqylq2wkX7dbmM2K2MMmI3K2APWsQMO7zqN/K2lCBs5FMk/CO/NsIUY8Fxp3n8Wyrj4ZwHAMrXu51DGyxcOHC+oQXC0z3U/zK49bQcPARoNPEaNcriOLka5ba+jrEySvovYbAa3tyuPzk6wyQQ2mkBaLVSeeqj0ekCrHTBnvyoVQaVSA9pLy2+cEYuzpxrw5XtHERztg+Bo3/4JUIgBwJWkr+rSnF8HF2fpG2wa6lpxtrQBN8+2O/HTda/t4PfQJyRcMvRuVzrL6Ikdp8rgNX58X4XmVswMY00NOk6WovPMaRirqmCsqYW5qQmm5iaYm5uVpGx5wMyAyQRms93x9wHYJGoCoIyKB5MJ5rY2mFtbwS0tSl09IQJptSAPDwRn/wf8Fy504zu/NpCKMO3BJLz74jfYtv4g5j2TDi/fa2eAJCGuJ64k/W1ElAfgHcvrBejSK19c6sR+ZTKlEakDr2mfmdF68BB8MzO7XU87fDigVqPjVGnfBOYmnWfOoP6jj9H81VdoLy6G6cKFS5arfH2h9vaGytsbKi8vkE4HlY8nSKMB1GplPgVS2cx2A5sx921/srKeyjLWvt4TKk9PqLw8QR56kIcOKg8PkFar1KtWgzuNMLe1gltbLx5oNO/Zi7P/vQo+06dD4+/fdx9UH9F7a5H50zH4e04B3nlhL25ZEI/49JAB08ohRF9xpSPf05bpb61jrW5g5r/3TlgDw/GCGgRGemNosFvnr7gmdJaXw9zQ0G0nPgAgnQ7a4cP7dYpdK3NHBzrLytB5+jQ6T5+B8VwdzE3Nypl6RwdIowY0GnQcP4GWb78FmOGROBret2dAnzAKHnEjoQkLgzY0FCrPa+tyTXtJCU7MvBt1f3odIb8cmPNWhcT6Yv6v0vHPN4vw2cbDOPbtWdxwVwyConwk+YtL1NTUqIOCgkz9Hce1yKWx95l5C4AtvRTLgNJ0vh1VJ+ox4e4R/R1Kr2j9/nsA3Xfis9JFRaHjVN8nfWZGW2Ehmv71L7R8m4/WwkJwx6WDWpFeD5W3t3ImbTSCTSao/f0RuPQX8Lv7bugiIx3Ufm3xiIuD39134/zbbyPgRz+CNmRgzHXQ1bBwb8z9ZRoKvyjHNx+eQOmBWvgG6jFyfDCGxw1FQPgQ+ATo5SBgkHv00Ucjt2zZUrpgwYLod999V+4ZttFj0ieiXcw8mYgacekVSgLAzCy9auw4WThwm/YBpRMf6XTwiOv5VkRddDTqDxy47LY9c2srOquqYLpwAeaGBpgaGsAmE0ilAkgFbWgIdCNGQB0Q4NIfcVNDAxr+8Q+c3/wu2ouLAZUK+sRE+C9aBH1SErThw6EdPhyaYcOUZD9ABD62FPVbt6J23WsI+81v+jucXqNSEVKnRWH0zWE4UViD4wVnUfh5OfZ/qhxYavVq+ATo4emjg5ePFjovLXQeamj1amh0aqg1yjgAao1ySUWlVmZIVKlIuSJjmTFRmdYYIOUf+AzTD8hWu2vF/PnzY7744gu/YcOGGY8dO3bIWp6bm+v71FNPRZnNZixZsqT2xRdfrOqpvKSkRJ+dnR128uRJ/WOPPRZeVFSk/+yzz4533adarU6Lj49vNZlMFBcX1/ree++V+vj4uH++6h7U1taqX3/99YBnnnmmxlqWmppq2L9/f5GXl1dqS0vLfnftq8ekz8yTLT993LXTweDEdzUYGuKFgLCBOTZ52/ffw2O0wamkqYuOgrmxER0nTqDpyy/R8Mkn6DxVdtl1ckdUfn7QBgdDHRAAdYA/1N4+yjVvLy+QRmM5SCB0nCpD64ED6Dhx4mLTfOgLv4VvVhbUPgP/66uLiMDQeXNx4W+5GPbQQ9dNK8WV0ntrkThpOBInDUdHqxF1lU2oO92Mc6eb0XyhHa2NHTh7qhHtrUZ0tplgMl793/KwkX4wTAxD3Phg6DzdOTO5eOihh2qXLVt29sEHH7w4I5nRaMSTTz4ZlZeXd3TEiBGdKSkpo+fOnXshJSWlzV55WlpaW3BwsHHBggV1aWlprQEBAaZnn3327KxZs+zOcmY7+97dd98dm5OTE/T8889XOxOv2WwGM0Otvvqhp+vq6tQbN24Mtk36+/fvL7rqiu1w5T79N5n5/p7KBNDW3InKoxeQOgCH3QUANpnQdvgw/GbPdmp9raUH/4kZMwFm6MeMgc/06dCGhUETGgJNQADUfn5Q+fgq19WZwSYTOitPo+PkCbSfPAljTQ1M586j/UgRzM3NMLe0wNzSAtth39T+/vAcOxa+d90J78mToR8zZtA18wY++jPUv/93nLjzLngkJECflAT9mGR4jh0Lj5EjlY6GA5DOU4OwuKEIixvqcB2TyQxThxkmo/KwjgNgNjGYGWazcheFctMFAwzlNQAwo+pkA458dQbb3yzCjreUGTODonwQmxKEuLSBeTmlL2VlZTUVFxdfclvGjh07hkRHR7cnJiZ2AMCcOXPO5ebmDj1//nyjvfK0tLSqgoICz/Hjx7fu2bPHa8aMGQ2AMr1tT/ufPHly04EDBzwB4NVXXw147bXXQjo7O2n8+PHNmzZtOqXRaFBcXKybPn16QmpqatP3338/ZOvWrcc+/fRTnzVr1oQQEUaPHt36wQcfnLS3/fHjx3VZWVnxN954Y1N+fr53SEhIR15eXom3tzdnZ2dHlJeXexgMhsQpU6Y0rF+/vsLeGb6juFzhytqX9NgiIg2ANJf2Nkic+r4WbGaMGDcwm/Y7SkthbmmBPjnZqfU9x42DZ2oqPMeOgd/cudAnODfpkMeIEcAtkx0uZ2bAbFYSv9k8oO5Zv1LakGBEb/oLGj/7DK2HDqFh2zZceO89AAB5eSHoF7/AsB8/1M9R9g+1WgW155XfZTw83h+p06JQdaIB5YfrUFPehIqi8zj6TTU02rGXjEgo3KO8vFwXHh5+sSNOREREx969e70dlQNAUFCQccOGDYFVVVXaFStWnD1z5owmMDDQ2N1+Ojs7kZeX53vHHXc0FBQU6HNzcwPy8/OLPDw8eMmSJVHr1q0btnTp0joAKCsr89i4cePJjIyM0vz8fP2qVavCdu/eXRQWFmasrq5WO9p+2rRpjWVlZfq33nrrxMSJE0/deeedIzZt2uT/85///FxOTk7FjBkzPK2tDvb0FJeznLmm/ysAywF4EpF1SkMC0AFggys7GyxOfFeLIUM9EBw9MJuU2w4pl9s8e+i5b6Xx90fMO391exxEBLihaW2g8UxJgWdKCgDlwKjz1Cm0fv89zr/7LmpeeQVD582F2q/70fGEfUSEsJF+F0cXNHaakPuHffj8L4ex4Nkbr/v5Nb7YdCTyXGWTWzsuBIR7t2T8cHS5O+vszuLFi+sXL15cb30dFhZm3LBhg91pbNvb21UGgyERACZMmNC4bNmy2tWrVwcePHjQKyUlZTQAtLW1qYKDg4029XVkZGQ0A0BeXp7vzJkzz4eFhRkBICQkxLRx48YAB9s3hoeHt0+cOLEVAFJTU1tKS0sdD3LSxbZt23y6i8tZzlzT/z2A3xPR75n5V67uYLDp7DCh7FAdRk8MU+7VHoDaT5wA1GrooqP7OxTRAyKCLiYGupgYeMTF4eTsObjw/t8x7MEH+ju0AUGjVSPzp8l478Vv8enrh3BPdqrMIuhGkZGRHZWVlReb/CsqKnTh4eEdjspdrd/2mr4VM9P8+fPr1q5dW2lvGy8vr247hzjavri4WKfT6S5eZlCr1dza2ur0l6WnuJzlSvP+N0Tkx8z1AEBEQwHcyswfXE0AA0354XMwdpoRO0B77QNAx8lS6CIiQDoZFe16oh89Gp5pacptfT+8HyStJG4xNMQLty4Zhc82Hsb2N4sQvtnvQQAAIABJREFUMcpfuUtAq4JardwdoFJbBl8iKHcLWO4aUFnvFFBZWq4IF8tA+PcyWF8DGg91rx1Y9OUZuTOmTJnSXFpaqi8qKtLFxMR0vv/++wFvv/32iZSUlDZ75e7YZ2ZmZsOcOXPili9fXh0eHm6srq5W19fXqxMSEi47qJg+fXrDvHnz4p599tmq0NBQU3V1tdrR9t3t08/Pz9Tc3NztL9WVuLrjStL/je1gPMx8gYh+A0CSvo0T39XAw0uD4fGOOxRd7zpKS6GLtdsZVlzjAu5fgsonnkTTzn/BZ+pt/R3OgJFwQyiqjjfg+x0VKN5T1av7ynp0zIDsLzRz5szYPXv2+Jw/f14TEhIy9plnnjn95JNP1ubk5JRlZmYmmEwmLFq0qDY9Pb0NAByVX620tLS2FStWVGZkZCSYzWZotVpes2ZNmb3kmp6e3padnX3mlltuMahUKk5OTm7ZsmVLqb3tIyIiHI6rHRoaakpLS2uKj49Pmjp1av369esvuxzhSlzdIbY36bW9FYkOMPPYLmXfM3PPo7O4WXp6Oufn5/f1bntkMpnxv0/vQsyYQNz+YGJ/h9Mr2Pz/t3ff8VGVacPHf/fU9B4gAUJCCAhEmgisDR8FBFGXVbHsWha7qyi2Z0V33dWHfV1dC669i1iWsgooiCLg2kFYilKCKfSEVNIz9X7/OANEIEAgk8nMXF/kw5wyc66TE+c6565e8oacQuIVV9D5/j8GOhzRStrlIn/UaOzZPcl4441Ah9NmtNa4S0txbN5M0+Y83HtKcFdU4qmowFNfj25sxNvUZMxn4BuEiZa++5o1BjXHx2PrlY09uxcRffsS/asRR5w4qqHGicvhwe3y4HHt6yHgxeM2egZ4vRqtQXuM116vF+0FtPa1STV6DXi92ujFoo11+0Zs1lqTOSDluMcLUEqt1loPbb5u3bp1WwcOHFh+XB8oOqR169alDBw4MPNw21rzpL9KKfUU8Lxv+TZg9QnGFlL2FNXgaHCTNTB0W/G6i4vRTU3ypB+klNVK4pVXUDb9GRwFBdizg3syKEdhIdUffED1Rx/j3nOge7UpPh5LcjKWpCSsaWmYIiJQEREomxVltoDZhFKHK009cCOgtcZTUYmjoICG777fP5qjvXdvooYPJ+qUIUQOHvKL0Q9lIiDR0bUm6U8G/gzM8i0vwUj8wqc43xhsJr136BbtO7ZuBcCWlRnIMMQJSJg4kfLnX2D3//6R6NNPx5bRnegzzwqaoXsdRUXULVtGzWef0bRuPZjNxJx1FtE33kjESX2w9+nT5oMxaY+Hpk2bqf/uW+q//Za9c+ZQNXMmAJYuXbBnZ2PL7omtRw8sySlYUpKxZmRg7RQcP1MRPloz4U49cL8fYwl6xQXVJHSOIjImdO/2nUVbAbBlZgY0DnH8LMnJdLrvXirffZeKN94AtxtrjwyyFy3q0I376r76itJ/PIFjyxYA7P360um++4i/6EIsqf6t41ZmM5G5/YnM7U/KjTeiXS6aNm2i4b//pWnjRpwFheydMxfd2HjgTWYzCZdNJPX227EkJ/s1PiGO1bH005+utZ6ilPqIQ2cHR2t9kV8iCzLaqykpqA7Zsfb3cRYVYYqO9vuXrPCvpGuuIemaa9BuN9ULPqL4gQeo++ILYs89N9ChHcK1ezd7Hv07tUuWYOvRg84PPkjsuecY0zYHiLJaiRwwgMgBB5o5aa8XT0UF7ooK3OUV1C1bRtWsWdQs+Iika68l9rwx2Hv3DvsBpERgHcuT/kzfv0/4M5BgV1XSgKPBvX/QjlDl3LoVW2amfHGFCGWxEH/RhZQ9+yyVb8/scEm/cf16tv1+Eni9pN51F0mTfo+pg3YVVSYTltTU/TfEMWecTuJVV1H61JOUv/AC5S+8gKVTJ6JGDMeek4M9Kwtbz57YuncP9MRPXq/Xq0wm07G16hYdmtfrVUCLYwkcy+A8+xrrJQMLtdaONootpBQXGPX5admhW58PxpN+5JAhgQ5DtCFlsZD42yspe/IpmvLyiOjTJ9AhAeDas4edt92OJTGRjBkzsHXrGuiQWs3eM4vuzz2Hq6SE+m++oe7rr2n47ntqFnx0YCerFVuPDGyZmZhj4zBFRWGOjyNqxAiihgxpj/kSfiorK+uXmppaLYk/uHm9XlVWVhYP/NTSPq35bboQeFop9SVGY77FWutWDwEYqooLqomMtRLfKTLQofiNt6kJV3Ex8VmZgQ5FtLFEX+O+ypkzSZ82LdDh4G1qYudtt+Otr6fHa68FZcJvztqlCwmXXELCJZcA4KmtxVlUhKOgEGdhgfGvb04LXd+Ap64OXngRc2IiMSNHEtGvH7aePbFn98TSpUublrS53e4bSkpKXispKckFZDjB4OYFfnK73Te0tENrGvJNUkpZgXHAlcDzSqklWusWPzycFBdU06VnfEgXezu3bQetpRFfCDInJBB/0UVUz59Pp3vuwZKY6Nfjaa3xVlfjrqzC29hg9KNvbEK7XeDxUD1/AU0bNtDt+eeI6HNsEzQFE3Ns7CFtAprz1tdT99XX1C5dSt3y5VTPOzAGWvqTTxA/fnybxXLKKaeUAtI2K0y0qtxIa+1SSn2C0aAvEpgAhH3Sb6hxUlPWSO6Zwf00cjTOoiIA7NJHPyQlXX0Ve2fPpvKNN0m5/TZM9mOeC+SIPLW11P3nS5o2bcSxOQ9HQQHu8nJwH7mgsNO99xB7zjltEkOwMUVHEzf2POLGnucbL6DCKA0oKiRq8OBAhyeC2DEnfaXUOOBy4GzgC+A14DK/RBVk9tfn9wr9RnyATLQTouw5OUSfdSYVr75KxZtvGo3Ncnph7dwZS2onzMlJmGNiMEVHY4qKQtlsKJsNc2LiYfvFOwoLqXrnXarnzcPb0ICyWrHl9CJ6+DAsnTpjTk7CkpRkfF5kJCoiEmW1oCwWTDEx2Lp3D8BPoeNRSmFJScGSkkL08GGBDkcEudY86V+DUZd/szTm+6XigmrMFhOp3UNzKt19nEVFWDp3xhQdHehQhJ90mz6duq++pmnDBpp++omGVatwl5WDq8Vhw8FiIXbUKBKvuIKI3Fxqlyyh+sMPaVi5EmW1Enf++SRccTmRubmBbqUuRNhrTZ3+lf4MJJgV51fTKTMWszW028A4thbJ8LshzhQVRdx5Y4g7b8z+ddrrxVNdjaeyEm99Pd66OqPBmdOJ1+nEsWkze+fNo3bxYjCZwOvF2iOD1ClTSJh4qQxM00yds45vd3/LpspNbKrcRHVTNTecfAPnZJwT0u2BRMfRmuL9i4HHgE6A8v3VWus4P8UWFFxOD+Xbaxk0OrSLIrXWOIu2Enf+uECHItqZMpmwJCa23LhvAqTeNYWaxYtx5G0hdvQoIgcPPmoSc3ldFFUXsad+D6UNpZQ1llHvqqfB1UCtq5bShlJK6ksobSjFoz0o3x/jP98f3zGav26+vP89BzYcdvvhPkehGNl9JA+NeOiEE/LGio3MzpvNoqJFNLobsSgL2QnZOL1OpnwxhZHdRjJ1+FS6xoR2uyAReK0p3n8cuFBrvak1B1BKjQWeAczAa1rrvx+0/W6MxoBuoAy4Tmu9rTXHCKSybbV4vZouId4/31NVhbemRhrxicMyRUSQMGHCUff7uepnPir4iHVl69hQsQGH55c1hRHmCKKsUURbo0mNTGVQp0F0iuqERRlfVRptzDrn++Nbuf91820HzyB6yD5aH/F9FY0VzN0yl37J/ZjYe+Jx/VwcHgfTvp/GvPx5RJgjGJc1jgm9JpCbkovNbMPldfHepvd4fu3zjP33WEzKhAnT/hubfRQKkzKhlOLxsx7n7O5nH1c8QrQm6e85joRvxpiVbzSwE/hBKbVAa72x2W5rgKFa6wal1K0YNxeXt+Y4gVS6rQaAzpmhXeCxr+W+FO+L1tJa883ub3h7w9t8V/wdVpOVvsl9uazPZeQm55Iek07nqM6kRKZgNXecOn+v9nLzkpv5xw//YHiX4WTEZbTq/aUNpdy1/C7Wl6/nhpNvYFLuJOJsv/yesJqsXNv/Wsb0GMP8gvk4Pc5Dblj23+BoIyYpDRAnorVT684C5gH7b8+11h8c4T3DgHytdSGAUupfwK+B/Ulfa7282f7fA1e1IqaAK9tRS3S8LeSn1HTkFwAy0Y5oHZfXxcPfPsz8gvmkRqZyx+A7mNh7IgkRHb9kzKRMTDt9GhcvuJipX01lxrgZWEzH9pW5oWIDk5dOps5Vx1NnP8XoHqOPuH9aTBq3DLylLcIW4oha0/IsDmgAxmCMznchcMFR3tMV2NFseadvXUuuBz453Aal1E1KqVVKqVVlZWXHHLS/lW2rJTUjtFvtA9Qu/RxLehrWbt0CHYoIEg2uBu5YdgfzC+Zz84Cb+fSST7lxwI1BkfD36RzdmT+P+DPry9fz95V/p7yx/KjvWVWyius/vR6rycrMcTOPmvCFaE+tGpHPn4Eopa4ChgIjWzj+K8ArAEOHDu0Q40O7HB6q9jTQ65TQnjPbXVlJ/TffknzdJJQptHsoiLZR7ajm1s9vZUPFBv7yq79wae9LAx3ScRubNZbvi79nVt4s5myZw6mdT2Vk95H0SexDr8ReJEUk7d/3611fM2X5FNJj0nll9Ct0ie4SwMiFOFRrWu93A54FTvet+gq4U2u98whv2wU0b9bezbfu4M8eBTwIjAymMQDKd9aBJuSf9Gs//RQ8HuIuOFrBjhCGJ1Y9wabKTUw/ezr/k/E/gQ7nhP31tL9ydb+rWbx1MYuLFvP4D4/v3xZriyU5IpnEiER+LP+RnIQcXhr90i9uBoToKFpTp/8m8B6wrxnrVb51Ryq7+gHIUUplYST7K4DfNt9BKTUYeBkYq7UubUU8AVe23WjEl5oR2o34qj9eiD2nF/beoTcGumh7mys3Mz9/Ptf2vzYkEv4+2QnZ3DboNv4w8A9UNFWwpWoLP1f9zM7anVQ5qtjbtJfRPUbzpxF/OqTBnhAdRWuSfqrW+s1my28ppaYc6Q1aa7dS6nbgU4wue29orTcopR4BVmmtFwD/AGKAOb6+sNu11kEx+UPZ9loiY61EJ4RuIz7Xrl00rl5N6pQ7ZfAQcVRaa5744Qni7fHcOODGQIfjF0opUiJTSIlM4bT00wIdjhCt0pqkX+Grd3/ft3wlUHG0N2mtFwGLDlr3ULPXo1oRQ4dStr2W1Iy4kE6G1YuMSxfXhrN6idD15c4vWVGygqnDpsrTrhAdUGtaZV2HMcFOCVAMXAr83g8xBQW300NlcQOpGTGBDsWvahYuInLgQJn8RByVy+viiVVPkBmXycQ+xzeYjRDCv1qT9B8BrtVap2qtO2HcBDzsn7A6vopd9WivDulGfI6ff8axebM04BPH5KOCj9has5W7T7kbq6njDLIjhDigNUl/gNa6at+C1roSCNuJnQ804gvdpF+7dCkAcWPPC3AkIhjMy59Hdny2DBErRAfWmqRvUkrtn3FDKZVE69oEhJSy7bXYoy3EJkUEOhS/aVizBluvbCypqYEORXRwO2t3sqZ0DRdkXxDSbVyECHatSdpPAt8ppeb4licCf2v7kIJD6fZaOmXEhuwXnPZ6aVq7jpjRQdvOUrSjRUVGg8/zs84PcCRCiCM55id9rfXbwMXAHt/fi7XWM/0VWEfmcXmp3F0f0kX7zq1b8VRXEzVoUKBDER2c1pqPCz9mSKchpMekBzocIcQRtKp43jc73saj7hjiKnbX4fXokB6Up3HNWgAiJemLo9hYuZGi6iKu/tXVgQ5FCHEUYVsnfyK2/lgBCrr0jA90KH7TuHYtprg4bD17BjqUoOD2uql31VPnqsPhceDyuHB5XXi0B4/Xg0d7AGNq1OZzuB+NUop9fw5eDwfmXDcpE/2S+xFhaf82JgsLF2I1WRnTY0y7H1sI0TqS9FtJa82WFSV07Z1ATKI90OH4TePatUQOGCAT7DSjtWZH7Q5+KPmBDRUb2F23m111uyhtKKXB3RDo8JiUO4m7T7m7XY/p8Xr4pOgTzux6JvH20L0JFiJUSNJvpdKttVSXNTJkbI9Ah9Iq2unEU1+PKToak+3IwwZ7amtx5OcTe5501QPIq8zjw/wP+Xzb5+xp2ANAnC2O7rHdyUnM4YyuZxBniyPWFku0NRq72Y7NbMNismAxWTApE2ZlxqSMGyiFOuRJ/XA0Gq31/pKBX2w7aP3D3z1MUXVRW572MVlRsoLyxnIuyJaxHIQIBpL0WylvZQlmi4nsIe0/na7WGvfu3biKi3GXV+AuL8dbX492ONAuJ9rpRLvcaLcbT20N7uISXHv24KmsRDuMyQsj+vcn699zj3icxvXrQeuwr8//audXPLf2OTZWbMRqsjKy20huSr+JoV2GkhWX1aF6bmTFZ1FcV9zux31307vE2+M5q9tZ7X5sIUTrSdJvBY/HS/6qPWQOSMYe6f8fndaaxrVrqVn0CU3r1+PIz8dbX3/YfZXVirJawWpFWSyYY2KwpKURPWwY5pRkzLGxNK5dR91//oO3oQFTVFSLx21cuxaUInLgAH+dWofm8Xp4fu3zvPrjq2TGZXL/sPu5oOcFHbr4Oi06jTWla9r1mBvKN/Dlzi+ZPHgydnPoVnUJEUok6bfCzk1VNNa66D2sS5t8nvZ6ce3ejbukBHd5Oe7yCrx1tXgbGvHU1lD/5Ve4du1C2e1EDhhA/IQJ2HNysHbvhiUlBUtyMqbYWCPhH0Pde81nn1H3xRc4CgqIPPnkFvdrXLsOe69szLGh2yVxH6011Y5qKh2VNLoaqXPV8eqPr7KieAUX51zM1GFTA9I4rrXSY9KpddZS56wjxtY+80G8tP4l4mxx/Pak3x59ZyFEhyBJvxXyVpRgj7LQIzf5uD+jaeNGqj9eSOP6dTg25+Gtqzt0J4sFU1QUkSefTMrk24kdNQpzzIl/kUf07g2AIy+vxaSvvV4a160j7rzQa4nd6G5kXdk61petZ33ZegqrCyltKMXhcfxiP7vZziOnPcJvcn4ToEhbLy06DYDi+mJybDl+P96mik18seMLbht0W7vdZAghTpwk/WPkbHJTtK6MPsO7YLa0rkW7drupmj2bvbPn4Ni8GWW1EtG/P/EXXYi9z0lYu3XFkpKKxVcMr47S0O54Wbt3R0VG0rRlS4v7OIuK8NbUhFR9fkl9Ce9tfo+5W+ZS66wFoGd8T/on9+fcjHPpHNWZpIgkoq3RRFmj6B7bnS7RbVOa015+kfQT/Z/0X1r3ErHWWH7X93d+P5YQou1I0j9G+atKcTu9rS7ad5eVseuee2lYuZKI/v3p/NCfiR8/HnN8+9cPK7MZe69eOLb83OI+jWtDZ1Ael9fF4ysfZ86WOWg0ozJGMaHXBAakDujQ9fPHY99IeLvrdvv9WHmVeSzbsYxbB95KrC30q4CECCWS9I+B9mrWLNlOSvcY0node7KoX7GSXffcg7eujrS/P0rChAl+jPLY2Pv0pm7pMrTWh7Q+11pTNWs2lvQ0bFlZAYqwbdQ6a7n7i7v5vvh7Lu9zOdflXhfSQ8SmRKZgMVkorvd/C/5Xf3yVGGuMPOULEYRk5JVjULS+nL17GhgypscxddPSWlPx+utsnzQJc1wcmbNndYiED0a9vqeqCk95+SHbaj//nKb160m97bagHpSnuK6Yaz65hlUlq5h2+jT+NOJPIZ3wwRiRr0tUF79329tRs4Ml25ZwWZ/LQq60RIhwIE/6R6G1Zs1n24hNjiB7yNGnmPXW17P7wT9Ru3gxsWPHkjZtGuaY6HaI9NjYe/cBoClvCzHNpszVHg9lzzyDrWdP4n/960CFd0LqnHXM3DiTGRtnoFC8OPpFRqSNCHRY7SY9Jp3d9f4t3p+xcQZmZeaqvlf59ThCCP+QpH8UxQXVlBTWcOblvTGZj/z069pTyo4brsdRUEin++4j6bpJHWoAFzCK9wEcW7YQc8bp+9dXL/gIZ34BXadPR1mC49ei1llLYXUh22u2k783nw9+/oC9jr2MyhjFnUPuJDM+M9Ahtqu06DS+2/2d3z6/orGCefnzuCj7IlKjjn4DLIToeILj2z2A1ny2nYhoK31PSzvifp69e9lxw/W4du0m47VXiT7ttHaKsHUsiYlYUlNx5OXtX+d1Oil/9lki+vcntgN31XN6nHy27TNWFq9kXdk6CqsL928zKRMj0kYwefBkclNyAxhl4KTHpFPWWIbL48Jqtrb557+3+T2cHifX9r+2zT9bCNE+JOkfQeXuerauL+fUC7Kw2s0t7udtaGDHzbfg3Lad7q+8QvSI4e0YZevZe/em6ecD3fb2zpqNa/duujzySIcrmQCobKpkVt4sZm2eRUVTBQn2BAakDuD8rPPpk9SHjLgMusV0w2b2T1fHYJEWnYZGU9JQQvfY7odsn7NlDhZlOa7xBxpcDfxr8784J+McsuKDu5GnEOFMkv4R5K/eg1KQe1bXFvfRTic7J99B448/0u2fz3T4hA9g79OHhnfeQbvdaKeT8pdfJurUU4k+veOVTqwsXsmU5VOoddVyZtczubrf1YxIG9Ehb04CLS3G11e/rviQpF/nrOOxlY/h8Diod9VzVb/W1cnP3TKXGmcNk3IntVm8Qoj2J0n/CHZsqqRTZhxRcS0/Qe75+2PUf/MNaX/7G7GjRrVjdMfP3jsH7XTi3LaN2mXL8JSXk/rPZzpcIl1UuIgHv3mQHrE9mHn2TLITsgMdUoeWHu3rq3+YxnxLty/F4XGQm5zLYz88ht1i5+JeF7N8x3Le3vg2mXGZPHL6I4f93GpHNa/8+ArD04YzMHWgX89BCOFfkvRb4GhwsaeohlPGZba4z95586h67z2SrruOhEsubr/gTlBEH6MFf8Pq1VS89jrRZ51J1JAhAY7K4PK6KNxbyJJtS3h5/csM7TyU6f8zXbqHHYN9owgerq/+wsKFdIvpxoxxM7hz+Z3833f/x+s/vs6uul1EmCNYW7qWWwfeur+0oLmX179MjaOG+4be5/dzEEL4lyT9FuzMq0Jr6N4v6bDbmzZupOQvfyVq+HA63X1XO0d3YmzZ2WA2U/bU03irq0m9886AxlPtqGZh4UIWFi1kU8UmXF4XAGMzx/K3M/4W9nX1x8pmtpEamXpIX/2yhjJWlKzghpNvwGa28fTZT3PPf+6hqqmKKadMoV9SP8Z/OJ75BfO5ZeAtv3jvtpptvL/5fX6T8xv6JPVpz9MJPs562PoN7N1m/K2vAGUCkwlMFuP1wX+jkuG0O8AsX8WifchvWgt2bKzEGmGmc1bcIdtcxcXsnHwH5sREuj71ZNB0cdvHZLNhy8rEmV9A7JgxRPbvH5A4yhvLeXLVk3y29TOcXid9k/pyVb+r6JvUlz5JfTrcnPXBIC067ZDi/U+KPsGrvYzvOR6ACEsEz5/7/C/2GdZlGPPz53PTgJswqQNdU59a9RQ2k43Jgyf7P/hgVlEA718J5b5eMWY7RKcCGrwe8LqN19oLXq9vvRtcDZCYCbnBU1IogltwZat2orVm+8ZKuvVJxHxQ3/zqjxdS8sgjaLebHm+9iSX5+GfcC6SI3n1wFhSSekdgvsy/3Pklf/7mz9S76rmk9yVcnHMxJyWdFJBYQklaTBqbKjb9Yt3CooX0S+5Hz/ieLb5vQq8JPPD1A6zes5pTu5wKGI0ol+1Yxh2D7yAlMsWvcQe1/KUwdxIoM1z+DnQbZiT8o41q6fXAc0Phu+ePLem7nbDhQ+h7Idii2iZ2EXaCd6xVP6oua6S2oonufQ8U7bsrKth1z73svvde7D170nPeh0QOGBDAKE9Myq230PXpp7D36tWux/V4PTy28jFuW3obyZHJzLpgFg8Mf0ASfhtJj06npL4Er/YCUFRdxMaKjYzPGn/E943qMYoYawzz8ucBxsyEU7+eSnp0Olf3u9rvcQelxr3w+cPw7qUQ1w1uWm4k5NjOR0/4ACYzDL8Vdq2CHStb3s9Ra9wY/HMQfHgTbJzfducgwo486R/Gjo2VgFGf762vp+Ktt6h8/Q28Tiepd95B8o03Bl2R/sHsOTnYc/w/BevBXl7/Mu9seocrT7qSe4beg91sb/cYQllaTBpOr5PKpkpSIlNYWLgQkzIxLmvcEd8XaYlkbNZYFhYuZPLgydz6+a3Uu+qZMXYGEZaIdoo+SDgbYOUr8PXT0LQXBlwB458Ee0zrP2vQb2H5NPjuOej+9qHbC5YbpQiNVdDjDLjwGegVHL2ERMcU3JnLT3ZsqiQuJQLzlv+Sf/9UPOXlxI4eTepdd2HvKQOTHK/vi7/npXUvcVH2RUwdNlXq6/0gLdpofb+7bjf1rnpm581meJfhxzRs7oReE5i7ZS6Xf3w5Nc4aXhz1ojTea87jhnXvwfJHoXY35IyBc/4EaSfQjdEeA6f8Hr59Fqq2QWKPA9s2zIMPboTkHPjdXOg29IRPQQi/F+8rpcYqpfKUUvlKqfsPs92ulJrl275CKZXp75iOxOPxsjOvis7Rdey89Q9YEhPp8f57dHv2n5LwT0BZQxl//PKPZMVn8eDwByXh+8m+pL+2dC03fXYTAPcPP+R/u8MakDKArPgsKpsqmXb6tLCarOiItIa8xfDS6bBgMsR3hUmfwO/mnFjC32fYzUZL/hUvG8teL6x603jCTx8CkxZKwhdtxq9P+kopM/A8MBrYCfyglFqgtd7YbLfrgSqtdS+l1BXAY8Dl/oyrJfV7HRSuLcPV5MG+6C0iBw6g+wsvYI47tAW/ODYNrga2VG1h+n+n0+hu5PUxrxNllUZI/rJvCuEnVz9JpCWS1897/YgN+JpTSvHomY9S3lDOyO4j/Rlm8Nj1X1jyEGz9CpKy4bK3oe9F0JY3rfFdod8EWPUGFCyFqq3gboJeo43jSaM90YaU1tp/H67Ur4C/aq3P8y1PBdBaP9psn099+3ynlLIAJUCqPkJgQ4cO1atWrTqh2F67dSpnGehzAAAIW0lEQVQ0HpiYxWOOxG1NAMDiqidhz195b7wDt1WeSI+XU8EeM2gFSsPdlXBuQ6CjCn0Tuxo/+2llcLIj0NEEL5PWdPXsoNoUz9yYq1gaNQ6P8s9zUlfXNm6unk61KZE9ljR2WjL4KvIcPOrQiZP6pcfxlwuPr5utUmq11lqKDcKYv+v0uwI7mi3vBA4enH7/Plprt1KqGkgGypvvpJS6CbgJICMj44QD80aAuaFk/7LV5cLm2IlW26mLLmbx+SYSVRS4T/hQYcuEYlijlQyXlQyXjUSvhV3SisTvJtbUkeKxkOSJkJ/3Cfo2ciQLo39Doynar8fZZe3BQylP+/UYQkAQNeTTWr8CvALGk/6Jft5NTz969J2ECEJSE992RgATAx2EEG3I3w35dgHNp/vq5lt32H18xfvxQIWf4xJCCCHCjr+T/g9AjlIqSyllA64AFhy0zwLgWt/rS4FlR6rPF0IIIcTx8Wvxvq+O/nbgU8AMvKG13qCUegRYpbVeALwOzFRK5QOVGDcGQgghhGhjfq/T11ovAhYdtO6hZq+bkGozIYQQwu9k7H0hhBAiTEjSF0IIIcKEJH0hhBAiTEjSF0IIIcKEX4fh9RelVBmw7TjfnsJBo/2FATnn8CDnHB5O5Jx7aK2PPuWiCFlBmfRPhFJqVbiNPS3nHB7knMNDOJ6zaDtSvC+EEEKECUn6QgghRJgIx6T/SqADCAA55/Ag5xwewvGcRRsJuzp9IYQQIlyF45O+EEIIEZYk6QshhBBhIqySvlJqrFIqTymVr5S6P9Dx+INSqrtSarlSaqNSaoNS6k7f+iSl1BKl1M++fxMDHWtbUkqZlVJrlFIf+5azlFIrfNd6lm9q55ChlEpQSs1VSm1WSm1SSv0qDK7xXb7f6Z+UUu8rpSJC7Torpd5QSpUqpX5qtu6w11UZ/uk79/VKqSGBi1wEi7BJ+kopM/A8MA7oB1yplOoX2Kj8wg3co7XuB4wAbvOd5/3AUq11DrDUtxxK7gQ2NVt+DHhaa90LqAKuD0hU/vMMsFhrfRIwEOPcQ/YaK6W6AncAQ7XWuRhTdV9B6F3nt4CxB61r6bqOA3J8f28CXmynGEUQC5ukDwwD8rXWhVprJ/Av4NcBjqnNaa2Ltdb/9b2uxUgGXTHOdYZvtxnAhMBE2PaUUt2A8cBrvmUFnAPM9e0SaucbD5wFvA6gtXZqrfcSwtfYxwJEKqUsQBRQTIhdZ631l0DlQatbuq6/Bt7Whu+BBKVUWvtEKoJVOCX9rsCOZss7fetCllIqExgMrAA6a62LfZtKgM4BCssfpgP/C3h9y8nAXq2127ccatc6CygD3vRVabymlIomhK+x1noX8ASwHSPZVwOrCe3rvE9L1zXsvtPEiQunpB9WlFIxwL+BKVrrmubbtNFPMyT6aiqlLgBKtdarAx1LO7IAQ4AXtdaDgXoOKsoPpWsM4KvH/jXGDU86EM2hxeAhL9Suq2h/4ZT0dwHdmy13860LOUopK0bCf1dr/YFv9Z59RX++f0sDFV8bOx24SCm1FaPK5hyM+u4EXzEwhN613gns1Fqv8C3PxbgJCNVrDDAKKNJal2mtXcAHGNc+lK/zPi1d17D5ThNtJ5yS/g9Ajq+1rw2jEdCCAMfU5nz12a8Dm7TWTzXbtAC41vf6WmB+e8fmD1rrqVrrblrrTIxrukxr/TtgOXCpb7eQOV8ArXUJsEMp1ce36lxgIyF6jX22AyOUUlG+3/F95xyy17mZlq7rAuAaXyv+EUB1s2oAIQ4rrEbkU0qdj1H/awbe0Fr/LcAhtTml1BnAV8CPHKjjfgCjXn82kIExLfFlWuuDGwwFNaXU2cC9WusLlFI9MZ78k4A1wFVaa0cg42tLSqlBGA0XbUAhMAnjJj5kr7FS6mHgcoweKmuAGzDqsEPmOiul3gfOxpg+dw/wF2Aeh7muvpuf5zCqORqASVrrVYGIWwSPsEr6QgghRDgLp+J9IYQQIqxJ0hdCCCHChCR9IYQQIkxI0hdCCCHChCR9IYQQIkxI0hdhyzdT3R98r9OVUnOP9p4TONYgX5dRIYQIGEn6IpwlAH8A0Frv1lpfepT9T8QgQJK+ECKgpJ++CFtKqX0zLeYBPwN9tda5SqnfY8xkFo0xbekTGIPgXA04gPN9g6NkY0zXnIoxOMqNWuvNSqmJGIOqeDAmhhkF5AORGMOkPgp8DDwL5AJW4K9a6/m+Y/8GiMcYeOYdrfXDfv5RCCHChOXouwgRsu4HcrXWg3wzEn7cbFsuxgyFERgJ+49a68FKqaeBazBGdnwFuEVr/bNSajjwAsbY/w8B52mtdymlErTWTqXUQxhzwd8OoJT6fxhDBl+nlEoAViqlPvcde5jv+A3AD0qphTLSmhCiLUjSF+Lwlmuta4FapVQ18JFv/Y/AAN8shqcBc4zRUAGw+/79BnhLKTUbY2KYwxmDMVHQvb7lCIxhVgGWaK0rAJRSHwBnAJL0hRAnTJK+EIfXfPx2b7NlL8b/NyaMudwHHfxGrfUtvif/8cBqpdQph/l8BVyitc77xUrjfQfXuUkdnBCiTUhDPhHOaoHY43mj1roGKPLV3+Ob6Wyg73W21nqF1vohoAxj+tODj/UpMNk3aQpKqcHNto1WSiUppSIx2hZ8czwxCiHEwSTpi7DlK0L/Rin1E/CP4/iI3wHXK6XWARswGgUC/EMp9aPvc78F1mFMAdtPKbVWKXU58H8YDfjWK6U2+Jb3WQn8G1gP/Fvq84UQbUVa7wvRgfha7+9v8CeEEG1JnvSFEEKIMCFP+kIIIUSYkCd9IYQQIkxI0hdCCCHChCR9IYQQIkxI0hdCCCHChCR9IYQQIkz8f7ti4JaFddjzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "quantile_plot('timestep','conviction_share_of_trigger', rdf, .25)\n",
    "plt.hlines(1,0,df.timestep.values[-1], linestyle='--')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "We have created a simplified conviction voting model that illustrates the state objects, and provides descriptions of how the model fits together. In subsequent notebooks, we will expand the model to introduce additional complexity to more fit real world implementations. "
   ]
  }
 ],
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