teachopencadd/talktorials/T005_compound_clustering/talktorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# T005 · Compound clustering\n",
    "\n",
    "**Note:** This talktorial is a part of TeachOpenCADD, a platform that aims to teach domain-specific skills and to provide pipeline templates as starting points for research projects.\n",
    "\n",
    "Authors:\n",
    "\n",
    "- Gizem Spriewald, CADD Seminar, 2017, Charité/FU Berlin\n",
    "- Calvinna Caswara, CADD Seminar, 2018, Charité/FU Berlin\n",
    "- Jaime Rodríguez-Guerra, 2019-2020, [Volkamer lab](https://volkamerlab.org), Charité"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Talktorial T005__: This talktorial is part of the TeachOpenCADD pipeline described in the [first TeachOpenCADD paper](https://jcheminf.biomedcentral.com/articles/10.1186/s13321-019-0351-x), comprising of talktorials T001-T010."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aim of this talktorial\n",
    "\n",
    "<!-- TODO: The wording of this paragraph is confusing -->\n",
    "\n",
    "Similar compounds might bind to the same targets and show similar effects. \n",
    "Based on this similar property principle, compound similarity can be used to build chemical groups via clustering. \n",
    "From such a clustering, a diverse set of compounds can also be selected from a larger set of screening compounds for further experimental testing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Contents in _Theory_\n",
    "\n",
    "* Introduction to clustering and Jarvis-Patrick algorithm\n",
    "* Detailed explanation of Butina clustering\n",
    "* Picking diverse compounds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Contents in _Practical_\n",
    "\n",
    "* Clustering with the Butina algorithm\n",
    "* Visualizing the clusters\n",
    "* Picking the final list of compounds\n",
    "* Bonus: analysis of run times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### References\n",
    "\n",
    "* Butina, D. Unsupervised Data Base Clustering Based on Daylight’s Fingerprint and Tanimoto Similarity: A Fast and Automated Way To Cluster Small and Large Data Set. _J. Chem. Inf. Comput. Sci._ (1999)\n",
    "* Leach, Andrew R., Gillet, Valerie J. An Introduction to Chemoinformatics (2003)\n",
    "* [Jarvis-Patrick Clustering](http://www.improvedoutcomes.com/docs/WebSiteDocs/Clustering/Jarvis-Patrick_Clustering_Overview.htm)\n",
    "* [TDT Tutorial](https://github.com/sriniker/TDT-tutorial-2014/blob/master/TDT_challenge_tutorial.ipynb)\n",
    "* [RDKit clustering documentation](http://rdkit.org/docs/Cookbook.html#clustering-molecules)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Theory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introduction to clustering and Jarvis-Patrick algorithm\n",
    "\n",
    "[Clustering](https://en.wikipedia.org/wiki/Cluster_analysis) can be defined as _the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters)_.\n",
    "\n",
    "Compound clustering in pharmaceutical research is often based on chemical or structural similarity between compounds to find groups that share properties as well as to design a diverse and representative set for further analysis. \n",
    "\n",
    "General procedure: \n",
    "\n",
    "* Methods are based on clustering data by similarity between neighboring points. \n",
    "* In cheminformatics, compounds are often encoded as molecular fingerprints and similarity can be described by the Tanimoto similarity (see **Talktorial T004**).\n",
    "\n",
    "> Quick reminder:\n",
    "> \n",
    ">   * Fingerprints are binary vectors where each bit indicates the presence or absence of a particular substructural fragment within a molecule. \n",
    ">   * Similarity (or distance) matrix: The similarity between each pair of molecules represented by binary fingerprints is most frequently quantified using the Tanimoto coefficient, which measures the number of common features (bits). \n",
    ">   * The value of the Tanimoto coefficient ranges from zero (no similarity) to one (high similarity).\n",
    "\n",
    "There are a number of clustering algorithms available, with the [Jarvis-Patrick clustering](http://www.improvedoutcomes.com/docs/WebSiteDocs/Clustering/Jarvis-Patrick_Clustering_Overview.htm) being one of the most widely used algorithms in the pharmaceutical context.\n",
    "\n",
    "Jarvis-Patrick clustering algorithm is defined by two parameters $K$ and $K_{min}$:\n",
    "\n",
    "* Calculate the set of $K$ nearest neighbors for each molecule. \n",
    "* Two molecules cluster together if \n",
    "    * they are in each others list of nearest neighbors\n",
    "    * they have at least $K_{min}$ of their $K$ nearest neighbors in common.\n",
    "\n",
    "The Jarvis-Patrick clustering algorithm is deterministic and able to deal with large sets of molecules in a matter of a few hours. However, a downside lies in the fact that this method tends to produce large heterogeneous clusters (see _Butina clustering_, referenced above). \n",
    "\n",
    "More clustering algorithms can also be found in the [scikit-learn clustering module](http://scikit-learn.org/stable/modules/clustering.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Detailed explanation of Butina clustering\n",
    "\n",
    "Butina clustering ([*J. Chem. Inf. Model.* (1999), **39** (4), 747](https://pubs.acs.org/doi/abs/10.1021/ci9803381)) was developed to identify smaller but homogeneous clusters, with the prerequisite that (at least) the cluster centroid will be more similar than a given threshold to every other molecule in the cluster.\n",
    "\n",
    "These are the key steps in this clustering approach (see flowchart below):\n",
    "\n",
    "#### 1. Data preparation and compound encoding\n",
    "\n",
    "* To identify chemical similarities, the compounds in the input data (e.g. given as SMILES) will be encoded as molecular fingerprints, e.g., RDK5 fingerprint which is a subgraph-based fingerprint similar to the well known [Daylight Fingerprint](http://www.daylight.com/dayhtml/doc/theory/theory.finger.html) (which was used in the original publication).\n",
    "\n",
    "\n",
    "#### 2. Tanimoto similarity (or distance) matrix\n",
    "\n",
    "* The similarity between two fingerprints is calculated using the Tanimoto coefficient.\n",
    "* Matrix with Tanimoto similarities between all possible molecule/fingerprint pairs ($n*n$ similarity matrix with $n$=number of molecules, upper triangle matrix used only).\n",
    "* Equally, the distances matrix can be calculated ($1 - similarity$).\n",
    "\n",
    "#### 3. Clustering molecules: Centroids and exclusion spheres \n",
    "\n",
    "> Note: Molecules will be clustered together, if they have a maximum distance below a specified cut-off from the cluster centroid (if distance matrix is used) or if they have a minimum similarity above the specified cut-off (if similarity matrix is used).  \n",
    "\n",
    "* **Identification of potential cluster centroids**\n",
    "    * The cluster centroid is the molecule within a given cluster which has the largest number of neighbors.\n",
    "    * Annotate neighbors: For each molecule count all molecules with a Tanimoto distance below a given threshold.\n",
    "    * Sort the molecules by their number of neighbors in descending order, so that potential cluster centroids (i.e. the compounds with the largest number of neighbors) are placed at the top of the file.  \n",
    "\n",
    "* **Clustering based on the exclusion spheres**\n",
    "    * Starting with the first molecule (centroid) in the sorted list.\n",
    "        * All molecules with a Tanimoto index above or equal to the cut-off value used for clustering then become members of that cluster (in case of similarity).\n",
    "            * Each molecule that has been identified as a member of the given cluster is flagged and removed from further comparisons. Thus, flagged molecules cannot become either another cluster centroid or a member of another cluster. This process is like putting an exclusion sphere around the newly formed cluster.\n",
    "            * Once the first compound in the list has found all its neighbors, the first available (i.e. not flagged) compound at the top of the list becomes the new cluster centroid.\n",
    "        * The same process is repeated for all other unflagged molecules down the list.\n",
    "    * Molecules that have not been flagged by the end of the clustering process become singletons.\n",
    "        * Note that some molecules assigned as singletons can have neighbors at the given Tanimoto similarity index, but those neighbors have been excluded by a stronger cluster centroid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"800\"\n",
       "            height=\"500\"\n",
       "            src=\"images/butina_full.pdf\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f3ff4954af0>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import IFrame\n",
    "\n",
    "IFrame(\"images/butina_full.pdf\", width=800, height=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Figure 1:* Theoretical example of the Butina clustering algorithm, drawn by Calvinna Caswara."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Picking diverse compounds\n",
    "\n",
    "Finding representative sets of compounds is a concept often used in pharmaceutical industry.\n",
    "\n",
    "* Let's say, we applied a virtual screening campaign but only have a limited amount of resources to experimentally test a few compounds in a confirmatory assay.  \n",
    "* In order to obtain as much information as possible from this screen, we want to select a diverse set. Thus, we pick one representative of each chemical series in our list of potentially active compounds.\n",
    "\n",
    "Another scenario would be to select one series to gain information about the structure-activity relationship; i.e., how small structural changes in the molecule affect the _in vitro_ activity."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Practical"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clustering with the Butina algorithm\n",
    "\n",
    "Application is following the example of the [TDT tutorial notebook by S. Riniker and G. Landrum](https://github.com/sriniker/TDT-tutorial-2014/blob/master/TDT_challenge_tutorial.ipynb)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load data and calculate fingerprints\n",
    "In this part the data is prepared and fingerprints are calculated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "import random\n",
    "from pathlib import Path\n",
    "\n",
    "import pandas as pd\n",
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "from rdkit import Chem\n",
    "from rdkit import DataStructs\n",
    "from rdkit.ML.Cluster import Butina\n",
    "from rdkit.Chem import Draw\n",
    "from rdkit.Chem import rdFingerprintGenerator\n",
    "\n",
    "from teachopencadd.utils import seed_everything\n",
    "\n",
    "seed_everything()  # fix seed to get deterministic outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "HERE = Path(_dh[-1])\n",
    "DATA = HERE / \"data\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataframe shape: (4635, 10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>molecule_chembl_id</th>\n",
       "      <th>IC50</th>\n",
       "      <th>units</th>\n",
       "      <th>smiles</th>\n",
       "      <th>pIC50</th>\n",
       "      <th>molecular_weight</th>\n",
       "      <th>n_hba</th>\n",
       "      <th>n_hbd</th>\n",
       "      <th>logp</th>\n",
       "      <th>ro5_fulfilled</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHEMBL63786</td>\n",
       "      <td>0.003</td>\n",
       "      <td>nM</td>\n",
       "      <td>Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1</td>\n",
       "      <td>11.522879</td>\n",
       "      <td>349.021459</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5.2891</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHEMBL35820</td>\n",
       "      <td>0.006</td>\n",
       "      <td>nM</td>\n",
       "      <td>CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC</td>\n",
       "      <td>11.221849</td>\n",
       "      <td>387.058239</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>4.9333</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CHEMBL53711</td>\n",
       "      <td>0.006</td>\n",
       "      <td>nM</td>\n",
       "      <td>CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
       "      <td>11.221849</td>\n",
       "      <td>343.043258</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>3.5969</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHEMBL66031</td>\n",
       "      <td>0.008</td>\n",
       "      <td>nM</td>\n",
       "      <td>Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1</td>\n",
       "      <td>11.096910</td>\n",
       "      <td>339.011957</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4.0122</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHEMBL53753</td>\n",
       "      <td>0.008</td>\n",
       "      <td>nM</td>\n",
       "      <td>CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1</td>\n",
       "      <td>11.096910</td>\n",
       "      <td>329.027607</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3.5726</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  molecule_chembl_id   IC50 units                               smiles   \n",
       "0        CHEMBL63786  0.003    nM    Brc1cccc(Nc2ncnc3cc4ccccc4cc23)c1  \\\n",
       "1        CHEMBL35820  0.006    nM  CCOc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OCC   \n",
       "2        CHEMBL53711  0.006    nM   CN(C)c1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
       "3        CHEMBL66031  0.008    nM  Brc1cccc(Nc2ncnc3cc4[nH]cnc4cc23)c1   \n",
       "4        CHEMBL53753  0.008    nM      CNc1cc2c(Nc3cccc(Br)c3)ncnc2cn1   \n",
       "\n",
       "       pIC50  molecular_weight  n_hba  n_hbd    logp  ro5_fulfilled  \n",
       "0  11.522879        349.021459      3      1  5.2891           True  \n",
       "1  11.221849        387.058239      5      1  4.9333           True  \n",
       "2  11.221849        343.043258      5      1  3.5969           True  \n",
       "3  11.096910        339.011957      4      2  4.0122           True  \n",
       "4  11.096910        329.027607      5      2  3.5726           True  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load and have a look into data\n",
    "# Filtered data taken from **Talktorial T002**\n",
    "compound_df = pd.read_csv(\n",
    "    HERE / \"../T002_compound_adme/data/EGFR_compounds_lipinski.csv\",\n",
    "    index_col=0,\n",
    ")\n",
    "print(\"Dataframe shape:\", compound_df.shape)\n",
    "compound_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(<rdkit.Chem.rdchem.Mol at 0x7f3f837f2a60>, 'CHEMBL63786'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x7f3f837f2880>, 'CHEMBL35820'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x7f3f837f2520>, 'CHEMBL53711'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x7f3f837f23a0>, 'CHEMBL66031'),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x7f3f837f29a0>, 'CHEMBL53753')]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create molecules from SMILES and store in array\n",
    "compounds = []\n",
    "# .itertuples() returns a (index, column1, column2, ...) tuple per row\n",
    "# we don't need index so we use _ instead\n",
    "# note how we are slicing the dataframe to only the two columns we need now\n",
    "for _, chembl_id, smiles in compound_df[[\"molecule_chembl_id\", \"smiles\"]].itertuples():\n",
    "    compounds.append((Chem.MolFromSmiles(smiles), chembl_id))\n",
    "compounds[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of compounds converted: 4635\n",
      "Fingerprint length per compound: 2048\n"
     ]
    }
   ],
   "source": [
    "# Create fingerprints for all molecules\n",
    "rdkit_gen = rdFingerprintGenerator.GetRDKitFPGenerator(maxPath=5)\n",
    "fingerprints = [rdkit_gen.GetFingerprint(mol) for mol, idx in compounds]\n",
    "\n",
    "# How many compounds/fingerprints do we have?\n",
    "print(\"Number of compounds converted:\", len(fingerprints))\n",
    "print(\"Fingerprint length per compound:\", len(fingerprints[0]))\n",
    "# NBVAL_CHECK_OUTPUT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Tanimoto similarity and distance matrix\n",
    "Now that we generated fingerprints, we move on to the next step: The identification of potential cluster centroids.  For this, we define functions to calculate the Tanimoto similarity and distance matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def tanimoto_distance_matrix(fp_list):\n",
    "    \"\"\"Calculate distance matrix for fingerprint list\"\"\"\n",
    "    dissimilarity_matrix = []\n",
    "    # Notice how we are deliberately skipping the first and last items in the list\n",
    "    # because we don't need to compare them against themselves\n",
    "    for i in range(1, len(fp_list)):\n",
    "        # Compare the current fingerprint against all the previous ones in the list\n",
    "        similarities = DataStructs.BulkTanimotoSimilarity(fp_list[i], fp_list[:i])\n",
    "        # Since we need a distance matrix, calculate 1-x for every element in similarity matrix\n",
    "        dissimilarity_matrix.extend([1 - x for x in similarities])\n",
    "    return dissimilarity_matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "See also [[Rdkit-discuss] BulkTanimotoSimilarity](https://sourceforge.net/p/rdkit/mailman/rdkit-discuss/thread/663770d4-b809-c599-e379-31f57380a1d0%40gmail.com/#msg36335970)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tanimoto similarity: 0.73, distance: 0.27\n"
     ]
    }
   ],
   "source": [
    "# Example: Calculate single similarity of two fingerprints\n",
    "# NBVAL_CHECK_OUTPUT\n",
    "sim = DataStructs.TanimotoSimilarity(fingerprints[0], fingerprints[1])\n",
    "print(f\"Tanimoto similarity: {sim:.2f}, distance: {1-sim:.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.26996197718631176,\n",
       " 0.26538461538461533,\n",
       " 0.40866873065015474,\n",
       " 0.09345794392523366,\n",
       " 0.31182795698924726]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example: Calculate distance matrix (distance = 1-similarity)\n",
    "tanimoto_distance_matrix(fingerprints)[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elements in the triangular matrix (10739295) == tanimoto_distance_matrix(fingerprints) (10739295)\n"
     ]
    }
   ],
   "source": [
    "# Side note: That looked like a list and not a matrix.\n",
    "# But it is a triangular similarity matrix in the form of a list\n",
    "n = len(fingerprints)\n",
    "\n",
    "# Calculate number of elements in triangular matrix via n*(n-1)/2\n",
    "elem_triangular_matr = (n * (n - 1)) / 2\n",
    "print(\n",
    "    f\"Elements in the triangular matrix ({elem_triangular_matr:.0f}) ==\",\n",
    "    f\"tanimoto_distance_matrix(fingerprints) ({len(tanimoto_distance_matrix(fingerprints))})\",\n",
    ")\n",
    "# NBVAL_CHECK_OUTPUT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Clustering molecules: Centroids and exclusion spheres\n",
    "In this part, we cluster the molecules and look at the results."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define a clustering function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cluster_fingerprints(fingerprints, cutoff=0.2):\n",
    "    \"\"\"Cluster fingerprints\n",
    "    Parameters:\n",
    "        fingerprints\n",
    "        cutoff: threshold for the clustering\n",
    "    \"\"\"\n",
    "    # Calculate Tanimoto distance matrix\n",
    "    distance_matrix = tanimoto_distance_matrix(fingerprints)\n",
    "    # Now cluster the data with the implemented Butina algorithm:\n",
    "    clusters = Butina.ClusterData(distance_matrix, len(fingerprints), cutoff, isDistData=True)\n",
    "    clusters = sorted(clusters, key=len, reverse=True)\n",
    "    return clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cluster the molecules based on their fingerprint similarity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total # clusters:  727\n",
      "# clusters with only 1 compound:  339\n",
      "# clusters with >5 compounds:  164\n",
      "# clusters with >25 compounds:  30\n",
      "# clusters with >100 compounds:  4\n"
     ]
    }
   ],
   "source": [
    "# Run the clustering procedure for the dataset\n",
    "clusters = cluster_fingerprints(fingerprints, cutoff=0.3)\n",
    "\n",
    "# Give a short report about the numbers of clusters and their sizes\n",
    "num_clust_g1 = sum(1 for c in clusters if len(c) == 1)\n",
    "num_clust_g5 = sum(1 for c in clusters if len(c) > 5)\n",
    "num_clust_g25 = sum(1 for c in clusters if len(c) > 25)\n",
    "num_clust_g100 = sum(1 for c in clusters if len(c) > 100)\n",
    "\n",
    "print(\"total # clusters: \", len(clusters))\n",
    "print(\"# clusters with only 1 compound: \", num_clust_g1)\n",
    "print(\"# clusters with >5 compounds: \", num_clust_g5)\n",
    "print(\"# clusters with >25 compounds: \", num_clust_g25)\n",
    "print(\"# clusters with >100 compounds: \", num_clust_g100)\n",
    "# NBVAL_CHECK_OUTPUT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the size of the clusters\n",
    "fig, ax = plt.subplots(figsize=(15, 4))\n",
    "ax.set_xlabel(\"Cluster index\")\n",
    "ax.set_ylabel(\"Number of molecules\")\n",
    "ax.bar(range(1, len(clusters) + 1), [len(c) for c in clusters], lw=5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### How to pick a reasonable cutoff?\n",
    "Since the clustering result depends on the threshold chosen by the user, we will have a closer look on the choice of a cutoff."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for cutoff in numpy.arange(0.0, 1.0, 0.2):\n",
    "    clusters = cluster_fingerprints(fingerprints, cutoff=cutoff)\n",
    "    fig, ax = plt.subplots(figsize=(15, 4))\n",
    "    ax.set_title(f\"Threshold: {cutoff:3.1f}\")\n",
    "    ax.set_xlabel(\"Cluster index\")\n",
    "    ax.set_ylabel(\"Number of molecules\")\n",
    "    ax.bar(range(1, len(clusters) + 1), [len(c) for c in clusters], lw=5)\n",
    "    display(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the higher the threshold (distance cutoff), the more molecules are considered as similar and, therefore, clustered into less clusters.\n",
    "The lower the threshold, the more small clusters and \"singletons\" appear.\n",
    "\n",
    "> The smaller the distance value cut-off, the more similar the compounds are required to be to belong to one cluster.\n",
    "\n",
    "Looking at the plots above, we decided to choose a distance threshold of `0.2`. There are not many singletons and the cluster sizes don't have an extreme but smooth distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of clusters: 1128 from 4635 molecules at distance cut-off 0.20\n",
      "Number of molecules in largest cluster: 145\n",
      "Similarity between two random points in same cluster: 0.82\n",
      "Similarity between two random points in different cluster: 0.22\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cutoff = 0.2\n",
    "clusters = cluster_fingerprints(fingerprints, cutoff=cutoff)\n",
    "\n",
    "# Plot the size of the clusters - save plot\n",
    "fig, ax = plt.subplots(figsize=(15, 4))\n",
    "ax.set_xlabel(\"Cluster index\")\n",
    "ax.set_ylabel(\"# molecules\")\n",
    "ax.bar(range(1, len(clusters) + 1), [len(c) for c in clusters])\n",
    "ax.set_title(f\"Threshold: {cutoff:3.1f}\")\n",
    "fig.savefig(\n",
    "    DATA / f\"cluster_dist_cutoff_{cutoff:4.2f}.png\",\n",
    "    dpi=300,\n",
    "    bbox_inches=\"tight\",\n",
    "    transparent=True,\n",
    ")\n",
    "\n",
    "print(\n",
    "    f\"Number of clusters: {len(clusters)} from {len(compounds)} molecules at distance cut-off {cutoff:.2f}\"\n",
    ")\n",
    "print(\"Number of molecules in largest cluster:\", len(clusters[0]))\n",
    "print(\n",
    "    f\"Similarity between two random points in same cluster: {DataStructs.TanimotoSimilarity(fingerprints[clusters[0][0]], fingerprints[clusters[0][1]]):.2f}\"\n",
    ")\n",
    "print(\n",
    "    f\"Similarity between two random points in different cluster: {DataStructs.TanimotoSimilarity(fingerprints[clusters[0][0]], fingerprints[clusters[1][0]]):.2f}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing the clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 10 examples from largest cluster\n",
    "\n",
    "Now, let's have a closer look at the first 10 molecular structures of the first/largest clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ten molecules from largest cluster:\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Ten molecules from largest cluster:\")\n",
    "# Draw molecules\n",
    "Draw.MolsToGridImage(\n",
    "    [compounds[i][0] for i in clusters[0][:10]],\n",
    "    legends=[compounds[i][1] for i in clusters[0][:10]],\n",
    "    molsPerRow=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save molecules from largest cluster so other talktorials can use it\n",
    "sdf_path = str(DATA / \"molecule_set_largest_cluster.sdf\")\n",
    "sdf = Chem.SDWriter(sdf_path)\n",
    "for index in clusters[0]:\n",
    "    mol, label = compounds[index]\n",
    "    # Add label to metadata\n",
    "    mol.SetProp(\"_Name\", label)\n",
    "    sdf.write(mol)\n",
    "sdf.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 10 examples from second largest cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ten molecules from second largest cluster:\n"
     ]
    },
    {
     "data": {
      "image/png": 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z37x5Q6aiEKKiooqKiqo/x8LCgtSEtWLk5eXLy8vLysrkGG9gpDSE4GB4+bKO+s4PU1lZKR6TFB4eHhAQwOFw+Hx+SkpKQUHB9evX58yZ065dO+m4DEePwpo1YG4OpHWw9VFRUaGnpxcTE3PixAmiKsMIPXr0SEpKiouLo1LudZOXl9e9e/eSkpKIiAgdHR1Zu0NhBjc3WLYM1NQgPByYbcBJSYG+faGsDAIDYcgQJi23dCorKzt37pyfnx8fH6+lpSVrdygyQqaaNnVBRhuqqqrGxMQsWLCAw+G4ubnV54UikSgxMfHBgwcnTpwwNTUFACUlpdLSUmk7LEOEQiGLxSLVRLL2pU3z5584e/Z/dCEbR0lJCan7jIyMJOfwxYsXmXDww2RkII+HPB5mZkrvILKEKEPr6upWVlYyaJZosD548IBBm60S8vefNGmSrB2hMEZGRoap6RwtrWgpCaJ++y0C4LRpUjHe4khOTvb09LS3tx80aJCKioq6urpQKJS1UxSZ0UwD93v37nE4HDabfevWLbK1qqSkFBYW1ghTZJx765ZbLi4uBoB27drJ2pG2TmYmxsZiXBwDppYsWQIAjo6OLi4uADB9+nQGjH6cKVMQAH/9VaoHkQ25ublqamoAcPPmTWYtW1tbA8CpU6eYNdtqyMvLCw4O9vLy6tatGwBcv35d1h5RGIM03pibfyEl+5mZqKKCAPjwoZSO0KwRCARBQUGHDh2aO3dujb410sK3cuVKmqdrszTH0szExMT58+cLhcLt27erqqpu2rSJxWKdOnVKT0+v/kaioqL27t3bt2/flStX/v33366urlLt8JMtVFKmmaCmBmpqzJiysrI6c+bMhQsX/P39169ff/v27ezs7E6dOjFj/QOHgzt34N49WLVKSkeQGU5OTllZWePGjWNcPY1KuRPKy8uTk5Pf/ZeUlJTU1FTyhC5duigpKQ0aNEi2flKY4uHDhxcuXFBQUHBxkdaUUzU1WLcOduyALVvgyRMpHaR5IRAIQkJCnjx54u/vf//+/ZycHPFD6urqI0aMGDt27JgxY4RCobm5uaurq7y8PO0YaaPIeuVQk7KyMpIjnzRpUnJyMknVbNiwoaF2yBR3DQ2NvLw8VVVVAHj9+rU0HP4gxcUYGVn1fVwclpdL93Dv378HgO7du0v3MJQmRCAQdOnSBQACAgImTZoEACdOnJDe4fLz8eRJJLuvqamYlye9QzUpL1++5HA4LBbrxYsXjBs/ffo0ACxatIhxy82T8vLymJgYX1/fkydP/vDDD1ZWVqNGjeratevHbi7t2rXT09OzsLDo168fAIwcObKiokLWb6L1k5f376ZfTAwWFv77UGIivn1b9X1AQCPtl5SU9OnTBwD27t3beC/rQWEhqqsjAN66JdXjyJLCwkJfX19HR0czMzN5efnqHx8NDQ1LS0tnZ+eAgIAayfW7d++SZrZdu3bJynOKDGl2gfvy5csBQEtLKy0tjVT3jhkzpnGXe5Lg8fLy+uabbwDAzs6OcW8/xqtXqKBQFbt/9RUztRN18PbtWwDo16+fdA9DaVrs7OwAYP369W5ubgDw2WefSe9Y5eXI5eLly4iIe/ci00UlMsPX1xcAOBxOfHw848YfPnxILlCMW25uZGRkDBs27GPaXHw+v1+/fp9//rmNjc1PP/108eLF58+fp6enl5eXv337NjMzMycnh/Tv/u9//5P1W2n9PHiAP/xQ9b2dHf79978PHT6MvXphQQEioqlpI+1/9913AKCvr98Ey7BffkEANDDAVlbRXVRUtGbNmsGDB4snTwEAm80ePHjwmjVrPDw8kpOT67bg5eVFxKz279/fND5Tmg/NK3A/e/YsAMjLywcEBPzvf/8DgK5du6akpDTOGikOnjx5cmhoKAC0b9++qKiIWYc/xqtXOG8empujSCT1wF0gEOzYsQMA1NTUEhMTpXgkStPy9OlTANDU1MzJySHKg0lJSVI6Vnk5TpyI48djfn6rCtyzs7PJxoWurm5GRgazxkmRjKamJrNmmyHr1q0jsYWqqqqRkZGlpaWDg4Orq6uvr29sbKxAIMjJyQkICPD09HRycrKxsTEzM9PW1uZwOABw+PBhRHzx4gWZb3/lyhVZv5tWTt2Bu60tktWTqSm+f4++vvj33xgcjLGxmJKCOTkoENRlPDQ0lMfjsdnsp0+fSu0d/EtpKc6ciXfvNsGhmhSRSKSurg4AXC7XyMjI3t7e09MzOzu7QUbc3d3ZbDaLxZLqZiylGdKMAvegoCBSpe3m5ubh4QEAPB7Pz8+v0QZzc3PbtWvHYrGio6NHjx5NLDPocB28eoUbNuCuXXj2rBQDd5FIdPXqVTK8nWycKSsrOzs7C+q+9FJaCCKRiFRRP3z4cPbs2QDwyy+/SOlY5eU4dSr+8QeuXduqAndEzMvLGzp0KAAYGBjk5OQwaFkgEPB4PBaL1bpFqxBRX1+fnH4VFRVPnz69cOHC7t27ly9fbmZm1qdPHx6P98FMPJfL7dWr19GjR4kRUo+rrKwcKa4jpEiBBw9QTw8XLMAFC1BHp2bgfvUqzpuHr16hqSm6uCDAB77YbDQ2/qZr167a2toGBgZGRkYTJ06cMmWKpaUlKV5ds2ZNk72duDjs2RPT0xERHRwwNLTJjixdLl++/PjxYwkvHYcPH+Zw+OPGRUhTdYzS7GgugXt2djaJUVavXh0ZGamiogIAR44ckdAskeb47rvv3N3dAcDY2JgRbz8JCdzLynDcOJw9GyMi0MoKnzxh8hBPnjwhanSksmjfvn3i7ltDQ0NpVPRSmp4ffvgBAGxsbC5fvgwAw4YNY9B4djb+8guS4kkSuCPi3Ln41VetKnBHxIyMDLK+HTlyZGH1ml+J0dbWBoCoqCgGbTY3Hj16RCpuKyoq0tPTPxijfzATX1t8c86cOWQFVVJSIpP30haoO+N+9Sq+f49Tp+K4cejhgRMnopER6uujtjZ27YqqqshmIwD27z/ng/9oNTU1RUXFd+/epaamrlmzRrwqkx6xsWhsjEuWICLa22NQkLQP2MJwdn4PgHx+a+4EYJZr16717t1bQUHB0tJy9+7dt27d+mRhUnOjWQTuQqFwypQpJLDOzMwkt9gFCxZIbvnZs2cA0Llz59zc3I4dOwJAYGCg5GbrRiCoCtwR8e5d5HJx+/aqTMaECQyIW4WGhlpaWpLLaOfOnZ2cnMrKyshDPj4+pJaUzWbb2Njk5+dLejCKTAkPDydRUX5+PlF2ZypGLC9HU1MEwC1bqn4kgXtiIqqotLbAHRHfv39PPhoTJ05kMEE+ceJEALhz5w5TBj/G8+dVpck5ORgTI+2j/QdytXF0dCQ/mpiYWFpabty48dixY7dv346IiKj/37OwsFBXVxcAVqxYIS132zy1A/f37/HQIXzzpipwR8Sff8Y6tAwEAszJyU9JSYmNjQ0ODv777799fX1v3brl6ek5bNgwAPj222+9vb1JHF9AzkupERuLK1bg6tX44AEN3D+MgwMCoIJCG5XObBCpqamkeLIGHTp0GDNmjL29vbu7e0BAQLm0FUUko1kE7ps3bwYAdXX1xMREkpLR19cvLi5mxPiQIUMA4NKlS6RoftWqVYyY/RivXqGuLt6//+/y99AhTEhAJydUVa0K38eMQW9vbIQGa2QkWlkJu3QxJOfZTz/9VPuvVFxc7OjoSMpJNTU1PT09JX5PFFlCqhRu3rz51VdfAcD27dsltykS4eLFCICampiQgDt3Yloais+UW7eaOjRsGqKjo4ki8owZM5iaxESC2h07djBirQ6GDUPSXf/oEW7bJu2j/UtKSgqPx+NyuUz1V4SGhpIZwGfOnGHEIKUGiYn/7u4+eIBpaRgUhBUVaGeHgYFIFv4VFXj8eGOMh4aGstlseXn5xMREUoC6c+dOxlz/ECRwz85GU1NcvZoG7h9AJMJVqxAAVVTw5UtZe9OMKSkpGTlyJADo6enduXPH09PT0dHRwsKC9BtUh8fjDRw40Nra2tnZ2c/Pj9l9WsmRfeB+8+ZNNpvN4XD+/PPPn376iYSk0dHRTNk/duwYAEyYMCEiIoLFYikpKUkvQ/DqVVV0/kEBm8JCdHbGrl2rwndDQ/T0rG/4/v49rliBXC5J279xcHCou1o3JCSEnKAAYGFhkZCQ0Kg3RJE9e/bsIRtQd+7cAQAdHR3JbTo6IgAqKWFQEP7wAwLg0KGNWUm2OEJDQ8nO26JFiyQcPRgSEmJtbc3hcLS0tLhcro2NTWpqKlN+1mbCBFy6FF+8aOrA3dHREQAsLS0ZtPnbb78BgIKCQnBwMINmKXUQGYkHDzJjav78+QCwfPlyorncvn37rKwsZkxX4+DBqkHOJHBHRDc37NSJBu4fRiTCr79GAOzQQdI/kYUFnjyJiPj6NTo4MOJds0AoFJJWsd69e6enp4tEIjs7u19//fXZs2dFRUVxcXHXr1/fvn37zJkzSdl2ddhsto6Ozty5czdt2tQE5WGfRMaB+71790j2Ze/evffv3+dyuSwWy0vykfHVKCgoUFZWZrFYUVFR48aNAwBXV1cG7YuJjMQuXRAAZ83CzEycOBE/WGdeVITOzqipWRW+6+uju3tdjfzZ2ejggAoKCIBcLtrYYD3LsYRCoaurK+kWaNeunZOTE21abYkkJCSwWKx27drl5eWRPT4Jy70uXkQWCzkcvHED3dyqzqs//2TK3+bO8+fPlZWVAcDW1rZxFv7666+pU6cSbUQ5OTkjIyMin6KiovLjjz8ytVVYgwkTMDUVP/sM799vusC9srKSNCM+evSIWcuk+6h///60nK8J8PfHjRuRKcmxt2/f8ng8DocTHh4+efJkANi4cSMzpv/B0xMBsG9frKzE9++RiJWLRDh3LrbqdhKJqKzEGTMQADU0UJJM3YQJOHUqpqdjcDDa2zPnn6xZv349WWeSkT7v3r2rHppraGhYWFg4Ojp6e3unpKTk5+f7+fm5urra29uPGTOmhsS+zCv9ZBy4kwWQrq6uQCAgpe1bSMkto6xYsQIA1q9ff+HCBQAYPHgw44d4+xY1NBAAJ0/GtDQcOrSqJOZjlJWhqyt2714Vvuvpobs75uejt3fVE4KDMTkZnZywQwcEQBYLLS0bc81KSUkhg9mBNq22WMiW9O+//75mzRpo1DwyMU+exJJF4NGj+OgR8vkIgMeOMehsC+DBgwfkQrx58+YGvdDX13fMmDHk06SkpGRvb//+/XtEjIiIELedaGpqurq6MlWK4+eHFhZ46RJOmICIePgwWlk1XeB+6dIlABg4cCDjw9VLS0sNDQ0BYN68eQyarRBVlApbucJPIwgORl9fZFC/kdxS582bFxwcTCpnyAeBEfLzsVs3BMDjx9HVFceNw4gIpmy3csrLccoUnDcPHz2qSvAVFX2ieKa4GMPC8OZNPHQI163Dy5dxwgR88QIXL25VgTvZ5ePxePfu3SO/ycjIOHDgwOLFiwcPHlxbF6tr165Tpkz57rvvLl26FBkZWVpa+urVq9OnTw8ePJg8Ktu3I+PAffz48QAwadIkRIyPj1+3bp2E+9cfJCgoCAA6deqUn59Pipn+rt5pLzEJCailhQBoZoZZWWhiUpUt+GRqvKwMjx2rei0A/vADKijgtWuIiOvW4bZtVb+fPBklbKn18fHR0tKCf5pWpd1ORGGWw4cPA8AXX3zh7+9PQsPGfUwiIyM7duw4YsSPmzZVhodXlXV99x3j/rYAvL29ycXaycnpk08WCoXe3t6kLQ8A1NTUHB0da4suP3jwQPwcPT29u3cbL3ooFKKXF44YUXUFGDeuKnAXCNDICLdtw6aZQEq2KH/99VdpGH/79i3ZDzwm2cIxoTzBNtHW6p3V6azTPnk++9PoPBqpk5ycTKSWAwMDyZJ15cqVTBlfuRIB0NgYU1KqrlGXLjFlu/VTXIwCAU6fjjNnIiK+e1clyFNRgbGx6OeHnp7o5IQ2NmhmhtraVSJC4q9ly6ouNTo4hpUAACAASURBVDY2ePhwKwnc79y5Q4ZVfayvpry8PDAw8NSpU/b29uPGjSM6ENVRVFQcNWrUX3/9JRAIyKzogEZPHmYCGQfuiYmJHA5HTk6O8dkoNSA31PPnz2/YsIHU5zFlOTExtU+fCgAcPx4zM3H8eATAnj0boN1eUYG//YaDB2NQEFpZoakpFhbiunX44gVaWTHWJ16jafUyGZJJaQlkZGRwuVwej5eZmUnK7xpRupCVlUUmz5ubm6elCfr2RQCcM6e1jSSsP1euXOFwOCwWq47AtLy83N3dvX///uI0jKOjYx3VHSKRyNPTs0+fPmpq6kpKBaNGob9/w7yqqEB3dxw4sOo+2rkzOjpiTs6/Oj8REejnh59/jv+ovEiLsLAwFoulrKwsvWoWktGXk5NrdCalUlQ5PGJ4aEmoQCTwyvW6kXuDBu5NAyk8mDp1alRUFJfL5XK5jMjzP3+ObDby+RgWhvPmIUCV2hWlQUyfjg4OeOlSVeBubo4czoc1++XkUEcHp0zBVatw7158+LAqcM/ORl3d1hC4v3nzpkOHDgCwdevW+r8qOTnZ29vb0dHR0tJy4MCBpDCSDB2zt7cnFRxSc/nTyL451dzcHKQ5WYZw8uRJADAxMYmJiWGz2e3atcvNzZXcbFpamq6u7vDh5uPGlWZl4dSpCIDdu2NsbGOsxcfj11+jtzdu2IDr1qE0VnSvXr0aPnw4iUJmzZqVlpbG/DEoUoDUkrq6uh46dGj79u0N3ZguLS0l9TZGRkaZmZkLFpxq1w5HjsQ2rqbt5ubGYrFYLFbt0WyFhYXOzs6kwhsAtLW1nZ2d66l7WFZWduJESMeOVUVuVlb47l19XoXu7kgWVACopYXOzli7YF4kQl/fqj71Awfq9TYbx8qVKwHA7oON9szxzTffAEDPnj3r2eCYUZnxouiFR46HU5qTbaJtaEnowriF4kdpxr3JyMrKIhsmDx8+XLp0KTCh4Fxejnp6CIBbt+Lt2wiA7drV67NDqcH06ZiZiSYmGByMS5agpSUCoKoqGhmhpSU6OKCrK/r6YmzsB/rrxMJ758/jvn1N7DjDpKam9uzZEwDmzp0rSb1fdnb2vXv3yPQJIjKuqakpw6ZB2QfuRA62b9++jJdRVqeoqIhcZV6/fk2klyVvDU5PTyd1+cOGDcvIyJwxY+aYMWfV1TE8vJEGSeCOiF9+iebmUgncsVrTqpqaWibp26c0e86cOQMA48ePb8RrRSLRwoULAaBbt26JiYlffvklAJiZfUeGEbZxyDhPDocj3oPKzMx0dHQk4jOkJcbd3b0R1+jCQnR0rGor5/HQxgY/9gcvKEBn56omGXHHyweLYdLTccQI/OMPPHcO2WxksVA6nfZVPf0AEBYWJpUD/ENFRcWoUaMAwMLCovotIC8vLzg4+Nq1awcOHNjxdMcXMV8MCh+kGKQIgVD961beLZsEG/GraODelGzfvh0AxowZk5SUpKCgwGazgyQTNHF29u7Vq7x/f8zORm1tBEApJ/RaLdOnY2Eh3rqFlpa4ZAnm5DSmuO7BA/zsM2S0rLhJKSkpMTY2Jqcos8Otyd71gwcPGLTZIGQfuAsEAlJ+Le2/gq2trZaW1p9//unp6QkAXbp0+fHHHz08PAICAhqRfc/NzRXPUU9LS5s1axbZSQ8Pb7zepzhwj4vDdu2kFbgTkpKSHtJpDS2H/Px8OTk5Lpc7a9YsJyenO3fu1H+3hIxfbd++fVhYGCkVU1FRIZ31FPxnjgSfz9+zZ4+9vT3RuSKXe29vbwkTCgkJaG1dVUiqqoonT+LkyUh0I69dQ29v3LQJVVSqQvaRI/H69bp0OffsQQBUVER/fzx6tGo6vTSmnbu4uADAxIkTmTddi7i4OLJMMjU1/fLLL4cOHSpeNRFMT5mKI3XVYNUhEUNmx85en7T+cMbhhPKE4RHDBaKqZRUN3JuSwsJC0jPm4+NDxqRYWFg02trbt2/l5eUVFFQfP05dvx4BcPDgJurlaH2QwB0RZ82qqnGvP0IhXr2Kvr64aRMC4JdfSsNBqSMUCklURsQfmTW+ZcsWkKm2jOwDd/xn4c6svEBt8vPzSUvfxYsX+Xx+DX2fD47s/pipvLw8UnDSv3//pKSkBQsWAECHDh0k7FcoLsZHj6ouVf7+WKdQO6VtkZCQwOfzlZSUapy04mFvYWFhH+tY9fX1VVNTu3v3rriz3tfXt4n9b+bY2dmJ/6osFmvGjBnPnz9n0H5YGFpYIACePIm9eqG1NSKiiwu6uFTF9GQo2ycRiXD5cgTA9u0xMBB3765K5zM76VYkEpH5pswq89YmLCyMbPq5u7srKyuz2ezq3WB6enoWFhZ2dnbHbx/3yvUKKgnKFXwgw3I2++yEtxO+SfxmafxSGrg3MQcOHAAAfX399PR0skXTOOVQkUhkZmYGAF9//XVQUKq8PHI40k1dtW5u3kTSmZKc3OA2ufPnq+bMpKaiggKy2fjmjRRc/DgvXrzYsGFDVFSUJEmTdevWAUDHjh0Zab2oQUREBLn/iofWNzHNInAnw/n4fD7jC6PaREZGkpoZKysrBweHL7/80tDQsEY8VD0wGj58+Pz587ds2XLmzBl/f/+0tLTi4mITExNS3pOUlESEsVRUVBhRWty0CblcPHRIckuUVsWiRYsAYNq0aadOnbKzszMxMSGncXWUlZXHjh27Zs2a3377LSAgoPo1paCgQNxZL6U5Bi0aoVBobGysqKhobGwsveKQBw9QIMAJE9DeHu/eRRcXvHIF9+1rWIAiEFQ17XXujOHhVVkxBQV88oSxi6evry8A9OjRgylRy48xevRoeXn5R48ebd26FQCGDh3q4eHx/Pnzht4IRCjKE+QhohCF4uw7pQkoLS0lNcQXL14k/8SxY8c2ws7p06cBQE1NLTU1ddiwYTo68xwdaRln4/H2Ri63agO/oZSVVc2Z+eOPqoGsjbPTOMj+sPiOZmRkJB5fWv8RGaSnkcfj3b9/X0p+El3I69evS8l+3TSLwB0RZ8yYAfWTZpOEwsLCgQMHkqi9xkOpqamPHz92c3PbvHnzvHnzjIyMaksCEeTk5ACgV69eiYmJq1atAgAlJaUn4hnTkjFrFgJIZe+b0nIhYsl8Pj8mJkb8S5FIFBMTc/ny5c2bN5ubm4vbKMXweDwDA4PFixcfOHDAzc2NnM8N6qynSIMJEzAvD01McN8+vHKlMRaIWjMA9uiB8fG4ahWamj5TUVF5ydC485kzZwLAjz/+yIi1j0FUejt06JCbm6upqQkAjx8/luoRKdKABEn9+vXLzs4mlTN37txpkIWsrKzOnTsDwPnz50kKv2fPns1tyHzLYscOBMBGD/zYtw8B0MQE371DLhd5PIyPZ9S/j/Do0SMifNe5c+fadzQulzto0KBFixbt27fP19f3Y+3st2/fJqM83d3dpeeqk5MTSL9O5GM0l8D9jz/+AABtbW1p6LgTRCIRUZzV19cvKiqqz0tycnICAgI8PT2dnJxsbGzMzMy0tbXl5OTYbDbRHt67d6+CggKD1fkGBgjQgttBWh8FBQUhISE3btxwdnaePHnyzJkzX7161cQ+TJo0CeqhP5Wbm+vn5+fs7GxtbT1w4EAyzlMMm822srKSags4pT4QtbVz57Bfv0YG7ohYUoLjxuGAAUVGRpOTkpJJ83GnTp0kb11ITEzkcrl8Pl/aklNEiuTbb7+9ePEiAOjp6dGTsyUiHp7o6uq6b98+AJhATvF6Q0YEfvbZZ/Hx8WT3+8aNG1Lyto0wezYC4LlzjXx5URGqqSEA+vnhwoUI0BS6kDExMWT99u233yJiUVFR9TuakZERyZlWR0NDw8zMrHqxaFhYGElROUpZLjcxMZGMHpPJ7OfmErgLhUIiUH337l0pHWLv3r1k8yVCsjlsBw8eBAAdHR2yj5wgyXDh/yISoaIiAtDqdhlQXl4eGxvr6+vr6urq4OBgbW1N1mlEwLU6qqqqUhpr/0Fu375NEpP11MsTU1xc/Pz58+PHj69cuZJc8t5RZbVmgDiqmTCh8YE7IknbTyOZiIyMjDlz5gCAurp6o2s6i4uLw8LC5s6dC/9I+1VWVoY3WiSrTnJzc8kEn6ioqLFjxwLA8ePHpXEgShNA9Pg1NTWzsrJ27dqV05AbWGlpqYmJiYKCQkxMzPTp0wHA0tJSeq62EYgmjySreDL/0dwcw8ORzcZ27T4qisUI1ceMEAmvbt261YjLi4qKXr586erqamtrO3r06NoVzioqKkSyfeHChU2QBSAl02fPnpX2gWrTXAJ3RNy9ezcAfCmdHuYHDx6Q3ZOrV69KaKqioqJv374AcOrUKUZ8E5OcjACopsasVUpNgoKCrl69+ttvv23ZsmXhwoWjR4/W0NCAj6CgoDBw4EBzc/NvvvnG3t5eVVUVmFAsridCoXDIkCEAsE8yQd2RI0cCgJ+fH1OOUSQhLQ0vX8Y//5TUTmZmJqn9GzFiRFZW1pQpUwCgR48e8XVubFdUVJA1qru7e/W9RHFvaIcOHQ4ePJiXl2diYqKmppaYmCipo7XYv38/AEyZMiUkJAQA2rdvX89dUEozRCQSEY21/fsb0xksEolCQkKI2puKikpSUhLjHrYp8vORxUI5OYk0ebKyUEkJlZQKQkNTpk9HHZ2gffukNcC2vLx8/PjxADB06FByHcjPz68dl7dv337cuHF2dnanTp0KDAwsLy8Xj0mysLDQ1tYGgG7dunXu3LlpekaPHTsGAFNlMSGMhYgfC1mamLS0tJ49eyJiQkICKXlkitTUVCMjo9TU1C1btuzatUtygxcvXlywYEG3bt2io6MVFBQkN0h4/BhMTWHkSHj2jCmTlJrs2bNn69atIpGoxu95PF6PHj00NDQ0NTW1q9GrVy9xQIOIb968MTY2LikpOXXqFNnrlyqnT59eunSplpZWZGRkDR2kBmFlZeXh4XH27FmyK02RLX/8AebmMGkS3L0rqamUlBQTE5N379599tlnV65cmTFjxpMnT/r16+fn56emppaUlBQXFxcfHx/3D/Hx8SkpKbXPfwCQk5Pr1asXAERFRXXt2jUwMNDW1vbGjRvGxsaPHz8mtaeMgIi6urpv3769efPmzZs3T5w4sXbtWiKo32rJzYX166G0FEpLYeVKmDpV1g4xzJ07d6ZOnaqsrKynp6ekpKSoqMjn8zt06MDj8ZSVlRUUFOTl5VVUVLhcbocOHfh8vqKiYvXnAMCoUaNSUlJ+/fVX0jlGaTQkkBg2DP7+WyI7e/b8uX//gsmTP1+3btvIkXrt27dPSEioLYogIYi4ePHi8+fPd+vW7fnz5927dye/F4lE0dHRISEhQUFBwcHBISEhqamp1V/I4/EGDBhgaGhoaGg4ePBgIyOjgoICPT29wsLCqKgo8bhr6ZGTk6OhoSESiZKSkrp06SLtw/2Hpl8r1AHZ7WW2KaqiomLMmDEAMHHiRKYmXYkTDMwOfD11CgFw0SIGTVJqQpLrXbp0Wbx4saOj45kzZ/7666+EhIRPnhsZGRmff/752bNnL1y4AADy8vLSLnYXKzaca3St4j98//33ALBz505GHKNISHg4AmDfvsxYS0hIIOfJ559/npaWRuQOOnbsSOKh2nC53N69e3/22WdLly7duXPnuXPnnjx5kpycTDaXhUIh6akwNTXNyMggofy6deuY8RUREW/dugUAWlpaWVlZioqKLBZLGpJtzQtbW7x9GxGxtBTHjMEGlr01f0pKStq1a0cUIRsHn88fMWKE9Jrc2g4uLgiAy5dLaicpKYnP53M4nLdv35KMuDTkQ8gYDWVl5ZCQkLqfmZOTU0cT1969exHxq6++AoDt27cz7ucHMTc3B4AjR440zeHENK/AnciQ9ezZk8FZsqtXryY2mZ0SSrpp1dTUGGxN+OEHBEAp91S0aR4+fAgAXbt2JbOLG4SbmxsAKCkphYeHL1u2DAD69u2bl5cnDT8Je/bsAYDBgwdLfjM7ceIEAHzdlLJelI9TUoIsFvL5H5g33jiioqK6dOlibW1dWVn54MEDNptNaro+OJ7ikyKP6enpRNLh+++/f/HiBZ/PZ7FYVySpx/8v06ZNA4Cff/6Z9AtNmjSJKcvNEaEQKytx+PB/B2v98AMDZVLNjN9//x0ADAwMnjx54uvr6+Xl5enp6erqeuTIEScnp23btjk4OKxatWrZsmWWlpZffPGFmZnZyJEjjYyMtLW1e/TooaCgwGKx1q5dK+v30RpYuhQB8PBhBkyRO52Njc2ff/5JEl6NuHXWAZEB5XA4Nxs+iqJ6E5exsTFRfrxz5w65NTPoZB2cP38eAMaMGdM0hxPTvAJ3kUhENjhu3bpFfuPj4xMWFtbocbXkzyovL8+UUFp1PvvsMwDYtm0bUwa//nrdoEHLrlwJZMogpQZkS2f79u3Xrl379ddfG6o4tnjxYgDQ0dHJyMggWy4zZsyQUhNMZmYm6Y5nZFjS3bt3AeCzzz6T3BSFEbp2RQBksHo8Pj6enIqTJ08m91pJCj2fPn3K4/FYLNb169dJEYuysjIjefH4+HgOhyMnJ5eenq6jowOy00KWLllZ6OmJNjbYrRt6eOCIEf8G7ps2odTkpWXF1KlTAeDo0aONe/mNGzcAYPTo0cx61TYZOXL8gAGLnj6Nk9xUTEwM+bQmJSUNGzYMAIieHiP89ddfRDWh0adNbQQCAalakXAaZj0pKipSUlJisVhNLPzQvAJ3RPz5558BYPr06YiYl5cn3gcRp44cHR09PT0DAgIKCgrqNhUSEkKml//222/ScPXFixcsFktJSYkp3TQjIyMAYHZkI0UMmfPF5XKTkpJI2P377783yEJRUZF4DkB0dDQJrF1cXKThrb29PTDX+BIdHQ0AvXr1YsQaRXJGjUIAZFy4/MGDB9AoDaLaEKFiVVXVd+/ekRWvgYGB5Pm2DRs2AMCSJUtIDo/Z/VUZIxDgs2e4bRuOGFE1EZd8rV2LGzaghwciYn4+jhqFspCQkx5paWlEQrTR29pFRUVycnIcDic7O5tZ39oalZWV8vLyLBaLqVoAIjO1fv36K1euAEDv3r0ZmcsWERFBdgU3btwoubXqkDHYn1RPZgorKysA2LNnT9McjtDsAvfMzEzyAY6Pj09KSpo2bZqOjs7H+qI0NDTGjRu3dOnS3bt3X7p0KTAwUJxDzcnJ6dOnDwCsWLFCet4S+Sp7hjROSSAo+R2X8kG2bdsGAPPmzfPz8wOAxvWeR0VFkTrOEydO3Lhxg8Vi8Xg8psZviXn37h0ZF8BUGX15eTmHw+FyuRUV0p2FSaknCxYgADI7IUQoFJIVKSOlqCKRiExiGj58eFZWlq6uruSX05KSkk6dOgHAy5cvycWziW940iA1NfX06dPz5s3LGzny32BdXh4nT8aDB5GoDxcVob09WlmhpSX6+yMiXr+OrWXGEJFvnz17tiRGJk6cCACXLklLuqSNQGSa+vXrx5TB4OBgFoulqKiYnp5O8laS91xlZmYSaT4LCwvG1+1Pnz4FAE1NTalmBKKjo0lS39vbmxTn5ObmSu9wNWh2gTv+s8IbPXr08ePH7927FxcXJxQKSV8C0di2tLQ0MjJSVFSsHcqTblGhUEjKKA0NDZktyarB69evORwOn8+PjY2V0FRGRgZJlTHiGKUGFRUVpGz38ePH8+fPB4AtW7Y0zhSZFyMvLx8YGLh27VoA6NGjB7MdFOQjwGxJ+qhR0fLypRKfpxRm2LwZAZDZHip3d3cA6NatG1NzBnJycsh4DTs7u9DQULKBeebMmUYbJI0iI0aMSEhIIFdOaY95khICgSAgIMDR0dHIyEg86uH++PGorY02NujpiXVvCF+4gGw2jhnTOlLvBgYGkpc8kc122ocjIeQiwKwWvp2d3dmzZysrK48fPw4A6urqX3/9tYuLy6NHjxrR5VVaWjp69GgAMDIykpIILFkVMDgZswZZWVn9+/dXVFT09/dPSkpSVFRUU1MjqWQLCwsHBwciPC89LfnmGLhPnz6dZGXE8Hg8bW1tMzMzGxsbJycnT0/PsLCwioqKhISE+/fvu7q6btq0afbs2QYGBn/88QciOjo6AkDHjh2boPCI1D0vXrxYQjv+/v4kucWIV5QaiKczpqSk8Pl8Lpf7/v37RltbuXIlAPTp0yczM5NoFk2dOpUpPQRSgqWgoMDgbC9ENDFBgNZXW9tSOXlS1KVL8rp1b5kyWFpaqqWlJWFgXZuXL1+SOtTz58//9ttvAKCgoBAcHNw4a6RM1t3d/bvvvgOARS1TQsvW1ra6KJ6ioqKFhcWRI0fi678sjo+vmpFjZNTSFWaCgoIAoFOnTuXl5ZLYef36NQB07dqVDtCVhHXr1gHT0nyE3NzcUaNGsVisGkMJGxStikSiBQsWkLpN6S3aiVKNlKotKioqJkyYAABDhgzJzMwcNWoUAKipqdVWBldVVfVZvhzXrUN3dwwJ+YCufmoqurnhuXNVQzdfvPh3zJW3dx0+NLvAnchfyMnJ2dnZLVu2bPz48WJdzxrweLx+/fpNnTrVzs7OxcXl1q1bUVFRFRUV165d43A4bDb7NpHfkjLx8fGkqqHRNzMCWSg32WSftoZ4OuPOnTtB4jlfZWVlpCHhiy++SEhIIKvt3bt3M+IquSj88MMPjFgTs3gxAqB02j0oDebevXsAYGpqypRBMhnawMCAcUG9I0eOwD96SkuWLAGA/v37N6KC9vnz5+QOl5eXp66uDgDPnj1j1tWmYcWKFQCgra1tY2Pj7e3dSO2EhATs2xcB0NAQGd2va2JIpGhnZye5KaJqKuGdtI1DNDN8fHyYNZudnT1ixAiyvezh4XH06NEVK1YMGzas9nQRVVXVCRMmfPvtt+7u7iEhIRX/jVaJMLGKikpoaCizHlYnPDyceML4JCaRSERmoWhqaiYkJCxcuBAAtLS0UlNTBQJBbGyseCBU165dAeAtSZiRLz4fhw7FpUvRxQWfPcO4ODQxwTt38Pp1HD0ac3Jw/fqqOjpEHDWqDjeaV+AeFBREVi1ubm7Vf19SUhIaGurl5fXzzz/b2NhMnDhRS0tLPBanOmJpz127djWZ26SPkDTUNhpSgc2gRg1FTFhYGAAoKyvn5OSQdaDkm2jx8fEdO3YEgAMHDty7d4+sFe/evSuh2evXr4uDGwlN1cDREQGwsfVBFIaJjY0FADJyTnJycnLI2findHQGFy1aBACDBg3KysoyNDQEgHnz5jXUCAn6HRwczp49S/JV0nC1CYiLi2NmmmxqKg4ciAA4YACmpDBgsMmprKwkAcrff/8tubXly5d37drt6NE/JDfVZiHVCsxOn01JSRk0aBAA6Ojo1DjzKysrw8LCzp8/v3HjRjMzM5LDqg6fzx86dOjSpUsPHTpEonYejyf5jfKTkHEWN27cYNYsqeZQVlYOCgoSL0I+pkCflJRUdOcO/vgjWlpi377IYv0bxE+ahN9/j+L11YkTePhwiwzcs7OzST2lra1tfZ5fXl5OBneLC9/FmvwDBw5syjkOGRkZpGGxEU2KIpHo3bt33t7e5Dw7deqUNDxs49jY2ACAvb395cuXAWDAgAGM7MbevHmTxWJxuVw/Pz+yN9elS5fk5OTGWROJRImJiUQgjyjVZGVlZWRkSO4n4cwZBMCFC5myR5GIiooKDofD4XAkLDAgkKyn9OQ+CwsLBwwYAAALFy58+/YtKRT59ddfG2QkIyPjp59+iouLMzY2rp2daaNUi91LU1MlNFZaWurs7Ozk5BQfH8+Id5/Ex8eHXFEZsXb9ehEAMrcL1eYgg0qUlJQYzDTHxcURnQ89Pb363N2Sk5N9fX3FY5KqJ1g7dOgAACdPnmTKtzogoljz589n0KaHhweLxeJwODdu3CDtOg1bhBQU4JMneOQILl+Ohw7h4sUYFlb10N27+N13uH49fv45LliACxZgnz51WGougbtQKJwyZQoAGBsbS3LOFRUVRUVFMehYPSH58rFjx37ymbm5uaTL1t7evsYKVVNTU8LGfEpt8vLyyHTGiIgIMv6NwTln69evB4Du3bunpaWJ501+Ui0rJycnICDA29u7erO1kpISOQeUlZWLiorS0tIMDAwMDAxySPWbxPz1FwIgFUpuPpCS9JiYGAntxMXFkWq9wEApjoB4/fo1aU51c3MjHSNycnJv3rxpqJ2//vqL7GIz1UHb4snIwMGDT40dq62tHRcX1wgDsbGxrq6ulpaW4sp7ZWVlZnOuH4O00f/000+MWMvPRx4PeTyU5ly71klJSYmjo6O8vDzRWOzRo4erq6vk6cvw8HAi6kCkpRphoaCgwM/P78iRI0uWLOHxeGw2OyUlxd/ff8mSJffu3ZPQvTpITExksVjt2rVr6LSWj/H48WPS7XP48OFHjx4RqUOJVO23b8erV6u+P3wYT5xoeRn37Vu3AoC6urokLYMypLCwkFRtikdHEcrKygIDA93d3Tdu3Dh58mTyGaiBhobGpEmTrK2tSZnQvn37ZPUuWiVkfIyZmVl4eDjR3Wdw2G1lZaWJiQkATJw4MSUlRVNTEwC+//578mhBQUFISAgZYbN27drp06fr6+vXMRVcXV2d5CTmz5+flpZGBPhGjhzJyKUnMREBUENDcksUZjA1NQUmBmwRIWHJ++M/yYULFwBAXl7+1atXdnZ2W7du/aTgWk5OTmBg4NWrV/fv379mzRpzc3MejwdMq160dCqzs0nbbv1j9+LiYh8fnzVr1hABDQKLxerXrx+5j/Tv31/aN9O8vDwFBQU2m81M4RAi/tND7+XFlL02wa1bt7S1tckJMHXqVCLaCABGRkb3JZAjCAgIIIlFU1PTT47NqQ9EXvbgwYOk08za2lpym3VAGtskF69ExNjY2M6dOwPAunXrwsPDyerIwcFBIqOpqThuHP7+O54+jePHY1FRSwvc7SnfXgAAIABJREFUb94s0dEx691bSgWaTcMvv/wCALq6ul5eXrt27bK0tNTV1eVyuTWCMyUlJWNj4xUrVhw6dOjBgwfVV7FeXl5sNpvNZrfOUYKyQCQSkeKTa9eu2draQr0LsepPamoqqfLcuXPno0ePuFwui8UaMGBADWWk6rRv397Q0HDWrFnr1q07dOjQzZs3w8LCiDBWcHAwuSgsWbIkMTGxV69eZNUh+danUIh8PrJYSBOdzQRS8y3hxnFQUBCbzZaXl2+a6ggyAr1v3741ejDKyspqFC4aGRmRM7k2qqqqLbQtVXrk5eWNHDkSAHr27BkdHf2xp5HkuoWFRfWmwE6dOllaWrq6uiYlJVVWVubk5JA+Qi0tLcl1iuvA1dUVACZNmsSgzd27EQBXrmTQZGsmOTmZ9EoCgIGBwZMnT4RCoVAo9PT0JPcOcvsICgpqqOXHjx+TDRxzc3OmNLUvXboEACNGjIiJiSHa8FKSgyQcPXoUAKZNmyahHSL+SEylpaWRpfKXX37JQD12Xh5eu4Y+PlV35TdvULzB7udXx+uaQeAeHY0dOiCAsIVnmktLS7t06VIjn8rlcrW1tS0sLMjA17CwsA/+swsKCubMmePv7797924S3H+s3YHSIO7evUvuhTk5OeQyJI1m9rt373K5XKIDM2nSJA0NDfLfl5OTqyFjGhAQ8MkywadPn5IZBfb29tHR0cTazJkzJZxXV1yMFy/iw4dYXt5qBr+0bHbs2AESyweRsTWS5n7qTWlpKZnxpKGhYWdnN2/evBEjRpDNxg+irKysr68/ffr0tWvXOjs7X79+3dfXl6nqr1ZGUVERkQTp2rVrmLj4FbGoqMjX19fe3p7UVhHYbLaRkZGDg4Ovr29+fr6vr6+Dg4ORkRHZ7qvnMkBCiBLu2bNnGbQZGIgA2KMHgyZbJxUVuG/fAXKnUFZWPnDgQGZmpr29vbhrvKSkxMnJiWzhstlsS0vL+hdi3b9/n5Ruzp8/v6K2iGFjKS0tJVMmo6KiSKOLBxknLB0yMzPJrPR0scZiwykvLyefyqFDh2ZkZBDxx2HDhsm20k/WgXtJCQ4ZggA4Ywa2cPVWkUhEtG5Gjx69adOms2fPvnr1qp6JUtJIoa6uHh8fv3z5cpIsaaGjSZoVM2bMAIA9e/YcPnwYpNm9RyqVKyoqSLXMr7/+mipBq5mvry8pp9u5c2dISAjJXK5d6yzJR8TWFonWaHk5mpk13g6FKcinXk1NbdWqVa6uri9evGhoZuvmzZskgd2Ug+IjIyPF4l1i+Hx+9TWqu7u7r69vbGws1eRuEMXFxWQl1qVLlz/++MPZ2dnMzKz64PDOnTuT5HpKSkp4ePiBAwc+//zz6tn3cePGEVMfWwYwxbt370jSlKkaYoJIhBoaCIAN755oQ/z1Fw4ahOPH/wAAFhYW8fHx7u7uZP3M4/GqL9Wys7MdHBzI3YTP59vb239ywOeNGzfIGWVjY8O4yAeZe7Njxw5Swjpjxgxm7deADOI8evRo415eXfwxMTGRFCVKVYG+nsg6cP/qKwTA/v1bQTcKmaDUuEG7AoHAwsICAAYOHJienk4yGWPHmpSW0tte46k+nZGoWV25ckWqR/z9998BQE9PT3JTly9fJuHRoUNHnj17Zmy8pmNHkSRlPra2OH06+vrSwL1ZkJGR0atXL9LuKYbD4Yg36Ly9veu+PQgEAnJWHzhwoMncJjx8+HDSpEmrV68+f/78kydPGq2kRKlNcXExaXMnzQDkrCDJdT8/v8LCQpJ9FxdC1Mi+V8+PVl8GML7TSPQYlixZwqxZ/GfixC+/MG74A5SWlpqYmBgZGe3YsaMpjicxaWlobV2lK6ivX3z37r2oqCgzMzNyJpiYmLx+/br2qxISEqytrcngpI4dOzo5OX1s+MD58+dJfe+aNWukseq+ffs2AOjq6qanp3O5XD6f37ie13py7tw5qJ9qyAchJ7mysnJwcLCDgwNIX4G+nsg0cHdxQQBUUkIp5AOanlWrVgHAxo0bvby8HB0dG6oPUFBQQG7DU6ZMSU9PHzJk2JAh9ywtW/o+hCwRT2e8f/8+WVMxuOv3QciKy9XVlRFr7u7uHTpoGRjknzyJDx6gvDwC4ObNjbRma4svXqCJCebn08BdxoiHfhsaGvr4+Ozfv3/RokWDBg2q3RLTo0ePL774YuvWrVevXq1Rr3zy5EmS/mF8yAhFtmRkZJC+hWXLll29ejUvLy82NpZk30nqlKCmpibOvn/MlHgZ0LlzZwYHG4lEItINKUnv48e4eBG1tPDQIcYN1+TZs2dEAAAAWCzW9u3bm1JFuqEIhejujp06IQAqKKCjI2ZlVW7cuJEs8Lp06eLu7l53qP3y5UuyCQMAPXv2rC07c+zYMaLeKL3Su8rKyi5dugBAYGAgOTNPnDjB+FGuXLkyZcqUvLy8wsJCeXl5Fou1evXq33///c2bN/XPq168eJGIP3p7e586dQqaSoG+PsgucH/2DPl8BMBLl2TmA3OUl5eTZsSQkBCiOdgIRfa4uDiy27V+/frXr0XKygiATThIqjVQUlLy5s0bHx+fgwcPkqL2Z8+e/fzzzxwOR9o5leDgYABo3749gw03x48XAiCHg5cvo7c38ngIgE5ODbBQUYHu7nj+PNraYmQknjuHjo5oZoaxsdjwhqV6IRQKvb29VVVVFRUVW+hMe6lSY+i3UCjcsmWLp6dndHR0SUnJ33//feLECVtb29GjR5My0+q0b9/e1NR07dq1rq6upPnh4sWLsn5DFIa5desWAIwePRoRT506RarvCFwu18TEZPfu3QEBAfVMiJaVlU2fPh0AVFVVX7x4wYiHRNOze/fuAoFAIBA4Ojoy2Lfw/DmKhUCOH2fK6n8oLS11cHAgW5q6urozZswga+Zp06Y1kwaM4mIUD3goKMBXr9DYuGp0z8SJGBmJ3t6opYXDh5uz2Wxra+v65619fX0NDAzI6TRs2DDxLEJSucdisX6R8mbHmjVrAGDDhg1ECp3x+tXnz58TYaVTp075+flxuVyyVCDweLyBAwdaW1s7OzuTLayP2bl69Wq7du2OHTv28OFDUq7W0MkV0kN2gXtwMPbpg99+KzMHGOXq1askf5aQkECSJZ+sJPsgjx8/5vP5HTuqnTuXdvs2cjjIYmErvjWHh+PWrVXfOztj9QFW16+jhUXVhkPtKQrl5Rgdjb6+eOIEbtv2o5WV1ciRI6t/PkmKXVFRkeQpExISpF0HTAahr127llmzO3ciAPJ46OODV65UnRL1uYCUlaG7O/brhwDYrRuuWoWRkSgS4bRpaGaGs2Yhi4WWlvjuHWOulpeXnzp1isj4iPNYjKhxtSbIRpB4yzUiIkL851JWVjYyMhLfVEpKSpKTk8UztMVNz4QOHTro6urSIvLWx4YNGwBg8+bNiOjh4UHyqZaWlu7u7o0LK8vLy2fNmkUWfpLo+QiFwpcvX+7cubNnz54AsHDhQvynx7pPnz5MCSqcPImamkgqPv6p2GeS58+fk2liXC7XwcGBbFg9evSI3D769u3bHGohvvkGZ85ERKysxAkTsHfvqp5dLy+MicFp06qCeHPz2EbMrCWyM+JeZzMzs5UrVwIAh8NpgulI4qLinJwcIifK4MyBuLg48n9ctmxZbGwsyYROmzZt+/btM2fOrF5gRmCz2To6OnPnzv3pp59u375dozMtISEhPDycNPhKqCLALNIM3MVDGZKT0d0dETE3F7duRWtrPHIEKysxNxclE8poPhCB0l9++WXPnj3QqHngYs6du9KzZyyfj48e4S+/VO2LMZQoaXYEBeHq1VXfb9uG1behzp/H4cORXEbGjcNXr3D7dvzqKxw3Dnv0QDb73+HBOjqG4s+hnJxc//79J0+evHLlyiFDhgDA4MGDmVKzqoPc3Fwy5ikyMpJx45s2VZ0Gjx7h8ePIYiGbjXVM6c3Lw927UV296u+jp4fu7ujqiqQU+c0b3LEDv/22asdLXh43bcJGLTP/paioyNnZuUePHuS/0KtXr/3792/dupXcDDw9PSWy3oqoveWamJi4efNmc3Pz2kMeeDyegYHB4sWLDxw48ODBg9zc3NTU1Nu3b//0009EotjIyEi2b4ciDYyMjACAjKcpKChgJI4UCAQLFy4EAEVFRXGStZ5kZmZ6enra2NhUz/3Ly8tzudz9+/cnJiYShRB5eXlGpuGePIk//4xTpqBIxHDgXlFR4ejoKB6vXmP/4f3790RGU15e/vTp00weuOF88w3OmYM3bmBlJU6ciNevV12lnZ1RUREBsEMHdHbGhvfT/UtxcfH/2TvvsCiuLg6f3aVXAUEUkaKigoqCHQFRRFCwgsaCXezYYrBFTEwssZdE+aImKEqxYEURFBU7qBSlGYr0ogJS3WX3fH9cMm4WVIRdELzv4+OzOzN75s5y985vzj3n3M2bN5M6eAoKCjIyMv6NEv4gEAgMDAwAICwsbMKECUQ4icVycXFxjx49AMDOzi4vL4+4kBwcHIQLshUXFzMrYFpYWAgndhPU1NQsLCzc3d29vb19fHzI442zs/NXFUYlSeHOFJB//hznzkWBAIcNw/Bw5HLxwAFctUqCp25c3rx5Iysry+FwsrOzSZz65cuXG2Jw9WoEQHV1TErCBQuq181pnitTfYZnz3DQINy1C3ftQjs7UeHu5YVDhmB+PlpZ4ZEjH5Q6iR7R08MhQ3DmTNy92+/48ePh4eGZmZnCDsjCwkKyVvNC5uFAYuzZswfEXdKYQSDA+fMRAFVUMCICt2/HRYuw1mEkPx89PVFNrfpb6t0bvb0/Orinp6ObW/UjkLo6btuGH0lY+hTFxcV79+4llewBoEePHt7e3sxASbS7jIzM1atXv9h0iyM0tLx9ez0AOHLkSK0H5OXlBQcHb9++/bvvvuvatWvN4i36+vrjxo17+vRpWVkZCaSRXLE/SpNQVFREUurFXm+uqqqK1PRQUFD47KKVVVVVkZGR27Zts7CwEF613sDAwM3Nzd/f/6effiLbx4wZk5+fT+YbAcDNze09E+RRL/78E0+dwm3b8NgxtLLC7Gz86y9s+Po/UVFRvXr1Ik5WNze3Wr/eyspKUtWNXIikc6I+weLFGBGBgwdjUREOG4aI+Phx9fQpi4XTp2MDKhz+h7y8PCJ2Fy9eLB6LdWDdunXkGz5z5gwA9OnTp+E2uVwuCZo3NjbOz88fOnQoAPTu3fvTVY94PN7z58+9vb09PDwcHR3JKksimJqafiyXt6mQpHDv1w+fPcNnz/DsWZw7F1NT0dn5w94W5Csidf7t7e0jIiIAQEtLq4E/eD4fx4xBAOzaFfPz0cYGAbBv39q1WrPm2TN0dsbISIyMxHnzRIX7kSMYHo5z5qCVFT5/juvX45EjGBqKyclYxy84OjqahLuJt9iwCMwyT5JbOYvPx8mTEQBbt659yE5NRXd3VFColuwWFnjxYp0sR0RUdzAANDDAs2fD6hh9kZeX5+npSaYRAcDCwuLixYs1P7tq1SqiFe7cuVOnBrVQnj9HVVVs1y598+YDdfzI+/fvyU2FOIdIzWYAePLkCSISB+qvv/4qyVZTGpsLFy6AUFVH8VJVVTVr1izye6x1ucO8vLyAgABXV1fhxbPk5eVtbW23bdsWGRkpfPDly5fJz79Lly5xcXFeXl4kd9bGZnhOTn3uVVlZeOZMtXB//x5tbNDMDLdvr54YdHHBixfrM0nP5XK3bdtGkjg7dux4+/btTx/v5eVFYpotLS0bUtW3ISxejHFxeO4cenhUC/dXr1BREY2MsMFLLVeTkJAQEhKSnp6+fPlyANizZ4947NaBuLg44tsuLi4mXajhM9WkOoi2tnZqaip5QCU1HL/UTkpKyrlz5zZu3Ojo6CgtLd2jR4+4uLgGtk3sSFK49+qFO3bgjh34/fc4dy5GR+Ps2R/2iuMZ6yuBLHVx8uRJd3d3EFOUc0kJmpoiAA4fjnl52Lt3y1wFutZQmbdvsaqqWrgj4uzZ2L59/U9x+PBhMkH8QmKVga9duwYAHTp0qEcl0LrD5aKjI27ahCdOIFklMzsbb9zA2Fh0dUUpKQRANhsdHfHhwy82HhKCpqZoanob/puxVCspKSnu7u7kiYiR7B87WCAQECeWqqoqUZzfIDk5qKeHAOjiUv/H76qqqhcvXpw8eZJE5V6+fBkAunXrJs6GUpoaoqI8PT0lZF8gEJDsQBkZGeJo4PF4kZGRnp6e5ubmpGIgwdDQ0M3NLSAg4BM+y6SkJDLJrKysfPbs2SdPnujp6VlbP23X7sPa7XUkIAA1NFBWFjdtwlOnEBFv30YNDTx/Hq2sqgsgknQdD48vqPJeF0d7TSIjI0mMhI6Ozv3797/sSsQBEe6IOG5ctXBHxPv36+qxqgsrV64EgF27dv3www8AsH37drGZrgMkQfbixYvkSbKBHX7r1q3kCfPBgwebNm0CACUlpXqsF9tcaMRQmdJSHDCgOtkwJ+dDZ2zmvHz5kqxDUVhYSLIiRNwS9ebVK9TWRgDcsAH5fBQIkMWqjmzevbuF6PiEhA9lc37/He/fx5AQPHoUV6zAoCAk/uv8fBwypEFnIc/fXbp0edfwCdfacHJyAoCtTFKHxCCaz8qqeu7q8WNcsqTayy4tjbNmYXx8/Y1XVeHx4xeZMNZRo0bVXLclJibG1dWVVGBgs9mOjo6PHz+ug+WqSZMmAYCmpuZX6L2QNOXlOGBA9aSZGMMfuFxu69atQTKLAVOaClNTUwC4deuW5E4hEAiWLl0KANLS0gMHDhQuXqSkpDRmzJhDhw7VvZxxSUmJi4sLAEhJyf72W0FOTuGQIQiAMjJYx3VvsrNx9OhqXe7oiImJH5Z2ZgJEU1Lwp5+wU6cP0ZLDh+fs37+/oKDgY2a/1NEuQkFBAamCLyUlte2LKnmJg1OnkBT5/OcflNA6DSRLfuvWrRs2bACAzY1bwI5I7cmTJ5PVzTt16lRvU6dPn2az2Ww2++zZs35+fqSG44ULF8TY2q+NRhTuiHj8OI4cievX47Bh+OWp0F8npET/jBkzyCqG4nWAPXhQHeSHiAIB9uuHw4Yhl9tyhHut8PlirjZUWlpqbGxMhglx2kXEf5d5kpWVbci6yl/EsGG4aRMGBODjx7hqFa5eje7u+OVTgrVTVla2bds2sjA1WSg7LS0NEcPDwx0dHYlDTkZGxtXVNf5LnhK4XO6oUaMAoH379l+6xEGzhs/HceOqw5DE3kFILQiyyj2lBfDmzRtSlKwRYmqXLl2qqqpKftGGhobu7u4hISH1WxNAIBDs2LHDxuYBADo4YH4+enhU+8inTv3MwypxtAOgqirWZQGMyEh0d8fWrdHaegcAcDgcW1tbb29vEVd6dHQ0KU7AYrHc3NzqV6KXx+ORZXcAYNq0aY28yv2dO2hri5IrYkyky08//UTqAm3cuFFSZ6qNV69esVgsBQWFoqIikiJVj/I4iBgREUGWsdu5c2d4eDgJ1trfCKsANCmSFO5M4aqqqg+pJZWVmJraoFzorwlmHYrQ0NCJEydK1O0qEKCtLR49itu3t2ThzuPh9u34zz9iNpuYmEjS58W+3AMZ2V1dXcVr9hMMG4bl5Th4MN64Iakc77y8vMWLFxNnlYKCgpGREeOQW7VqVf2qd5WXl1tbWxPnyieWjGlhrFhRnfsrgWpDeOvWLRKjRYtCtgzOnTsHAEOHDpXcKY4cObJy5crY2FhS4Kh///7iWvj29u3qKeIOHfDxYzx/HlVUEAB79cL/Lh1WTW4ujh9f7T63t/+y6gsVFRgYGOLo6MisWaaurr5o0aIHDx4QRzsJUjc0NGz43IWvry9JL+ndu3eKGKvnfo7z5xEAx4yRlP3NmzcDwPr164nze82aNZI600cg6xX6+PiQGOMfmcrQdYYp/jh37tzk5GSSWrp8+XJJtParoklXTm3+hIeHkzA4UpGUxWJJzptIhLtAgMOH4/fft1jhfvIk/vorSqL2t6+vLwDIycmJMdK6srKSVIp9WI+48vpCoswuX0ZbW8kWZ0pKSnJxcWGxWK1bt27VqpWnp2cDl6cuLi7u06cPAHTv3l2iK11/JWRkoIoKktKukkAgEJBI3HtfGlBM+SohESw///yz5E5B1gcMDAycNm0aABw4UNdU6bqQmVkdFSYnh0ePYmxsdSGUmt6SgABs3fqDo73eD555eXl79+4lznUCUW9sNnvFihXiKgQcHx9PSr9raGjUmtQrCYKCkMxgSIjt27cDwOrVq3ft2gUAK1askNSZPsLBgwdJTGZSUtLt27e/tN4iU/xxxIgReXl5xLs0cuRIiWaafSVQ4d4g3NzcAMDDw+PIkSMggTXAhCHCHRGjolBFpcUKd4lCQgs6duxYVFQkFoPe3t7EEyMWa3WESQ8ZM6YxqqqOHDkSAMRSoRkRCwoKSNhSv379JJRy0LRcuoRMqb3DhzEmBk+fluDpyGI9S5YskeA5KI0FSfQMDw+XkP2Kigo5OTk2m/369WuyiFLNPJYGUlmJ7u7VfnQ3N8zPx4MH/3NAXt4HR/uIEWKL8YuLi/P09Gzfvr2Ojo6iomJYWJh47P5LYWGho6MjE0AoXuO1EhpavU6qhCAljJctW3bgwAFo3HKQhPz8fGlpaQ6HU48sUi6Xa2trCwDGxsZ5eXk2NjZQh+KPLQYq3OvP+/fvNTQ0SHIYiQEQl7ipFYEAGUfM7t0tdkkmiVJZWUkWN3FycqpjdIFAIMjKyrp79+6JEyc2b948e/ZsGxsbNzc3spcs2CHRv3tNmAmD/HxMSpL46UjNgV9++UVcBrOyskiAmY2NzddWH7fhrFiBJibVC1pZW0v8dE+ePCFeRl5LWczumyU/P59E/dYv0Lwu3Lx5k+ibpKQk0m0kFGT1558oK4sAOHfuh7q00dHo5/chov3oUfGf9/Xr11JSUjIyMpJwCggEAmZhikZY1O/OHQRAS0tJ2SdlrBcuXOjl5QUA8+bNk9SZPg5ZDZrFYhkbG7u4uHh6el68eDE3N/ezHyRPHW3btk1LS3N1dQWAdu3aZbTIxW5qQwoo9eXixYtv3rwxMzNTUVEJDw+Xl5cfP3685E536xYEBoKeHkyfDitWSO48LRlZWdmzZ8+amZldunRp7969K/77PRYWFqakpGRnZ+fk5KT8S2JiYmlpqYidgoICAHj69Onjx4/V1NRIyZRGw8ys+oWmJtS2XoSYIavcpaWlictgu3btwsLCLC0tw8LCxowZc+nSJRKQ2mJwc4P16+H33xvjXGZmZsbGxnFxcTdu3BgxYkRjnJIiGUg0toWFBUmwkwRhYWEAYGNjQ7IjhgwZIlz/UYzMnQtmZjBvHsyeDcOGgY8PjB8PPj7Qowe8ewcjRsCff8K/6yyLEw0Njf79+9+7d+/mzZtjxowRr3EWizVo0CAAkJGRkdzfiIEMilyupOyTS+ByuWT45UruTB/n0qVLDg4Ob968iYuLI8XdCbq6uqampr3+xdDQUKSjLlmyJCUlZfr06ceOHTtx4oSysnJQUFD79u0b/QqaBirc68+JEycAwNXV1cfHRyAQjB07ltTikNjp4NkzePlScmf4JtDT0/P29h49evQPP/zQt29fsnT8pEmTrl69WlJSUutHtLS0DAwM9PX1mf+Jw5ikpc6dO5dktbdUiHBPTU0Vo80OHTqEhIRYWVldv359ypQp/v7+NVcJbb5YW0NEBERENNLpJk6cuGnTJl9fXyrcmzWMqm6EU5w6dUrS5zIzg8hIyMqC0aPhwAEYPhwAoEsXuH8fzM1BMs8LAAD29vb37t0LDg4Wu3AHAPK9rV69Wng1WQkhaeHO6HVGwUvqTB/H3Nw8Pz+fx+MlJSU9+Zfo6OiMjIyMjAyyVAUAKCsrGxkZGRsbm/+LvLz8/v37/fz8Nm/ezOFwTp48Seqofis0tcu/ufLq1SsZGRkpKamcnBySGRMUFCS505WXo6oqAjSoUDeFgSzn2b59+/z8fEQkUyVycnKGhoa2trZubm7btm0LCAiIjIwsLi6uqKhITk4OCQnx8vLy8PBwcXExNzdnih9HR0c39dVIloSEBAAwNDQUu+XIyEgVFRVo9CQBibJiBUZFYXY22ts3RqgMIv7zzz8sFktZWbkRpu8pkqNr164A8ODBAwnZLysrk5WV5XA4hYWFZLmGL6roWj8yMnD6dLx8GVeswNWrGyPCk6xfrq+vL3bLpaWlSkpKLBYrudYqOeLm+XMEQBMTSdn38/MDgEmTJp05cwYAJkyYIKkzfSF8Pj8xMdHf33/t2rUODg4knEYYsqCpiYkJeXz6vY7rBbQgqMe9TlRVVaWnp7948eLJkydxcXEvXrxISEjQ0tJSVFTU1ta+ffv2+fPnhxOXgmQ4fx6Ki6F/f+jaVXIn+YbYtm3b48ePw8PDJ0+eHBwcfODAgSNHjsjJyaX+S1pa2uPHj9PS0lJTUwsLC2s1wmazPTw8yApwLRg9PT02m52RkcHn88XrFzc3N//rr78mTJgQHR1dVVXFVHZrAbRtC/b2cPYsAEBODjx/DpIbHjp27Ghubh4ZGXnlyhVnZ2dJnYYiSfLy8hITE5WUlEgSjiS4d+/e+/fv+/btm5ubm52d3bZt2y5dukjoXCKMGgXe3lBZ2RjnMjMz09LSSktLS0xMFO8FnjlzprS01MrKisy4ShpZ2RIrqzRNzTKAAZKwz3jcmzBUplbYbLaRkZGRkREpsQ0AhYWFRH0RARYbGxsbG0t22dnZLVq0qOka2zS0nDtlrSQlQVISODoCAJw5A/37f4irCwuDlBSYMwcAYOdO+P77/3wwMxOeP4eYGEhK4j150i8uLk6kW8vKyhYXF+fm5u7Zs2fFihUkPUJynDgBACDhk3xDSElJ+fr69u7d+8aNG3369CGSPS8vr9aDFRUVmSAZAnkt0ciorwc5OTltbe2xJMd2AAAgAElEQVTs7OysrCxSiUKMkPFXXV29EaaeG4eVK0FDAwBg6lSQloaMDDAwAGVlyMkBOTlJnXTy5MmRkZG+vr5UuDdTbt68iYiWlpZk8YSysjJSO1yMMHEy5IXkAtxrZccOMDGBDRskfiI2m21nZ+fj43P16lXxCvfjx48DAFmHuxGQln57505PPT09gDRJ2P9qhXtN1NTUBg8eTOJaAaC8vDw2NvbQoUNWVlaN9uf4umhql79kuXED16+vfr1kCUZGfti1fz/q6uKLF4iIVlYYH4+HD+OiRWhlhWpqH9ZVBsDWrU0AoG3btra2tu7u7t7e3pGRkZWVlWfPniUL7V5k0uYlQ14eSkmhtDR+fHVnSn04fPiwsPiWkZFhQmU8PT29vLxCQkKSk5Pp6jZkpQyxL8Oel5dHQmWIamlJcLmoro4sFqamopkZAki2fmt2djaHw5GTkysk5WwozYr09HRSl4ys37dnzx4DAwOxr/UzcOBAAAgKCnJxcQEJLEVXK+XlH8Jj7t/HN28a4Zzo4+MDAPb29mK0mZmZ2cg/sezsbCI8JGT/+vXrADB8+HBSa0iixawp4qXlC/cFCzA+HuPjcepUUeG+bx/a26NAgFZW+PPPImIdhw5Fd3f83//w8eOEjxUHJWuPKSsrx8TESO4qdu9GABw9WnJn+EYhZfjt7e3Dw8MzMzOpQP8YZK2Wv/76S7xmFyxYAABjJLc2YJMyeTIC4NatuGMHAqCkSz+TRMNGrkxKqTc8Hi88PNzDw8Pc3Jx4vlu3bj1ixIjS0lKySJl4tXtJSYm0tLSUlFRRURFZbPLly5fiMv61UVBQwGaz5eTkysrKxGXz119/BYDJkyeLy+Bnef36NQBoaGhIyD6pLGRtbX337l0AsLCwkNCJKGKnhUxPf4L4eDh9Gk6fhn/+Ed2lqwuWlnD8OACAlRXMmgW7dsH165CTAwUFcOMG7NsH8+ZB375dmExEEdavXz9t2rSSkpLRo0fn5+dL6BLCwoqBxsmIm+Li4pMnT7JYrD179gwePFhHR6cxJ46bF/r6+iDWipAAkJiYePToUQ6HQ+6ILY/JkwEAfH1hyhRgs+HSJSguFv9ZUlNTMzIyAGDy5MkAcPz4cUQU/2koYiI19e0ff/wxevToVq1aWVpabt++/cmTJ8rKyjY2NpWVlcHBwa6urkFBQQMHDkxNTbW2tn4ppjpid+/e5fF4ffr0ycjIyMvLa9euXadOncRi+SukdevW5ubmlZWVt2/fFpdNUkSuMQMzJB3B0oxCZSgitPAYdwAYPBh+/BEAoFZd/f33YG8P5eVgbQ3W1l9snMVi/fnnn8nJyQ8ePBg3btzNmzfFXt71xYsXly51NzOb7uTkLV7L3zh///13WVmZra1tV5rw+zkkURFyzZo1PB5v/vz5JiYmYjT79WBvDxoaEBMDb9+CpSXcvg0XLoB47/uFhYWjRo0qLi4ODQ0dOnSojIzMs2fPVFVVa5ZOE+dZKV9IRQXcuwehoRAaCkVFSsnJi8l2Q0NDR0dHJycnKysrGRmZp0+f2tnZBQYGVlZWXrp0ycXFJSwszMrKKjQ0tOG/EZEA92HDhjXQ4FeOvb19REREcHCwg4NDw609evQoISGhTZs2ZLXOxoEKd8rHaPkedxGuXoXdu6u97AAgIwOenpCbW3+DcnJygYGBHTp0yM/XWrWKJ5ZGCkMe9Pv0kZP8gg/fEIh46NAhAFi8eHFTt6UZQDzuYhTuDx8+vHDhgpKSkqenp7hsfm1IS8OECQAAvr4fvO9ihMfjTZw4MT4+Xk1NTUNDY9asWVwut6qqqqSk5MmTJydOnFi+fLmlpaWqqmqvXr1Wrtyydy/cugVFRaJ28vLg7t3q13fvQlUV3LtX/bakBP4t3kABAHj5EpYurX69dy8EB3/YdekS9O8PPB4AVJdDSEiAPXvA3h7U1WH4cNi+HZ48gcJCmdmzVx87diw7Ozs5OXnfvn22trZEOZmZmYWGhmpqal69etXZ2dnPz8/W1jY3N3fo0KGxDf4z1Fx6qYEGv3Ls7e0B4Nq1a2KxRtJSXV1dG7PyFaOnyRza2rVrg4KCxGjfwMDg2LFjW7ZsocK9+dHEoToSprISi4qqX799i1wuknXBV6zA4mIsLa3e1fCFcmNiktq2FQDgr7821JQwfD5fV1cXAMLDw8Vp95uH5OXo6urSheLrQkpKCvm6xGWQZLt6enqKy+DXSVgYAqCeHhYUoIaGwMoqKS8vX1zGSYZGzUW/CwsLw8PD9+7d6+rqamxsTCp4WlktZRJ42rZFR0f09MSAAHz+HK9dQxUVTEhARBw5EktKcODA6lNER+OCBeJqb0sgPh5nzap+vWULClclOHMGraxw+3ZERCsr3Lr1Q8YUm439+uGPP+L9+1hV9dlTxJMi61ZWVgUFBU5OTgCgpqb2+PHjeje7qKiIw+HIyMiUlJS0bt0aAMSe+fq1UVVVpa6uDgD//PNPA029f/+efGmNv2QHKTHE5XIfPXpEIjltbGwiIiLEe5b//e9/AKCionL//n3xWqZIiBYu3GvF1xfDwsRvNigIORxksdDPT2w2Q0NDAUBfX5/mTYoXsqjer+J9zGq58Hg8KSkpNptdWVnZcGsBAQEAoKWl9e7du4Zb+5rh87F9ewTABw9w9OjxAHDw4EGxWP75558BQEFB4dGjRxs3bgQAZWXlqKiomkeWlpbev3//77/j3Nywb1+Ul/9PFj4A/vknLlqEjo4oEFDh/hni49HUFDdswA0b0MZGVLgfPIj29piailZWePcutm6NLi7o5YVZWV92loSEBB0dHQCwsLAoKCgYO3YsALRq1erhw4f1a/alS5cAYPDgwVFRUQDQoUOH+tlpXpAq4A1fnefs2bMA0KtXL7G06ovQ0tLicDjLli17/fq1l5eXlpYWALBYLBcXl4Y/kCBiWloauRWSarwsFmvChAmJiYkNt0yRKN+ccP/tNxw/Ho8ckZRxAJSXxy91jnC53JiYmFOnTq1Zs8bR0bFnz55k+4wZMwBg48aN4m/rNww3Pd3VxERGRiY3N7ep29JsINEyDa9EweVyO3fuDACHDh0SS8O+ctatq7C0jPvxR5+TJ0+CmEo3+PkFslgsDodz8eJFX19f5nVdPsvj4fPn6OOD33+Pw4ahri5evYrbtuHPP6OPT7VwNzbGqVNx6lQcNYoK9/8QH4/OzpicjMnJuHp1LcI9JgZdXNDKCgUC5PPrf6LU1FSSWGJubp6Tk0OWdlZVVa2fT/TZs2cLFiw4ePDgnj17AGDmzJn1b1nz4dixYwAwusHl2Ii03b17t1ha9UUQAUAm1ry8vAoKCn744Qc5OTkAkJGRWb58+evX9fSkcLncvXv3KisrA4CiouK6det+/fVX8lZKSsrNzS0nJ0e810IRI9+ccJc0bm4IgO3afSb8Ji0NL1/GrVtx6dLNPXv2JEFmwmRkZJSVlZEfUgKZxqaIi3XrEODNkiVN3Y7mBKk2eP369Qba2b9/PwB06dKFxG62eMgC7FpaWkVFRWS99NTU1IYYDA9HbW1+z56L9+3bd/v2bZIN3xBHfnAwbtuGlZVobY1WVtTj/ilqDZVJTcXy8mrhjoirVqG6uhjO9erVq44dOwJA7969c3NzSUlWRUXFGzdu1NvmiBEjAMDb21sM7fvqycnJYbFYioqKDZknfP36tYyMjJSUVFMJ2QcPHjALD3Xp0iUgICA9Pd3NzY3D4ZiY9FdWFnh6Ynn5l9m8ffs2k+7s6OiYnp5Otufn57u7u5M4fkVFRQ8Pj+LiYvFfEqXBUOEuZrhctLFBADQz+xBDj4jp6fjHH7hgAQ4ejKqqH+aprawWMY/Ujo6OHh4e3t7ez58/r6ioIDPgA5m7KEUsvH+PbdogANJ4vi9h1qxZAODl5dUQI+/evSM1pM+fPy+uhn39kOUbr1+//t1338G/i+zUj6Qk1NBAAFy+nB8fj3Z28dLSCqtWrWpI84hwR8Rr15DFqkW4V1Xh0aN49GhDTtJCePUKmb/eiRN47x6GheGZM7hoEd65gxcuICK+e4dOTuI5XXp6OpmeMjY2zszMJP5XBQWFkJCQL7Lz9u3bgIAAsu4SAMTGxoqnfV89pqamABAaGlpvC8TRMGrUKDG2qh5cvHiRKd85YMCAO3fuREVFzZwZRVSEri7+9VedZnhycnDp0j0kXN7IyKjWjvTixQuSWQEAI0d6e3khTQT72qDCXfwUFGDHjmhoiML5P8HB/4kr1dJCW1tcvhxPnUqIiIgoKyt7+/YtSSlzc3OzsLAgFdyUlZV/+eWXpruUlsiJEwiATRGw2KwhQdVr165tiJF169aRZ9FvKmeDVM6ZNWvWhQsXAIAJhPtS3rxBIyMEwJEjMScHDQ0RABcuzOY3JCYDMSMDmdh4Pz/kcqsFKDnj3btYWIhZWbhjB/7rmKP8h6oqXLlSUsZzc3O7d+8OAF27ds3MzFy0aBEAyMrK1iUy6vnz59u2bbO1tSU5joShQ4dKqq1fHx4eHgCwevXqelsgi2H5+/uLsVX1g8vlenl5EcdH//5jHR0xKQlDQ6sXZgbAbt0wIOCjH+fz0dsbNTSwZ89iBQVFT0/PT09E3L5929JyhLZ2FbH8LXlamgFUuEuEpCQsKMDt25E80Obm4rZtOGcO7tmDoaGYl4dFRXj3Lh4+jIsW4YwZ19XU1ERCZdhstqGhoZOTU/mXToNRPs2AAQggqSyHlstvv/1GQj6uX79eUFBQDwtZWVkKCgoAcO/ePbE372uGrKGjoqJSXFysoaFRP5fn+/fVU3m9e2NBAQ4ahABobv6faT3JwePhypWfr4jyDVJZiVu3YlqaBE+Rl5fXs2dP4iJNT09fuHAhABgYGLx//77mwQUFBQEBAW5ubqQ0DYHD4Zibm3t6el65cuWbema+ceMGyes9fvz4tWvXbty4ERkZGRsbm5ycnJeX9/bt209/G3FxcSS14Ou5CxcXF69bt87EJA4ApaVxyRLMzcUTJ1BPr1q+1/oM+egRmptXHzBqFKakvK7j6S5exE6dqj84YADeuSPOa6HUGyrcJcjo0WhlhWVlmJyMM2diYCCuWYOjRn34jZF/nTrFksHFwsLCzc1t79694eHhJSUlTd38lsizZwiArVo1kt5pQQQFBZHKA0xkl62trbu7O4nsqovTd/bs2QDg4uLSCK392jA3NweAM2fOLFmyZOzYsTExMV/0cYEAXV2rk2fS03HKFARAfX1snLDbN29w5ky8fh3pmFSTwED87Tf86y/JnuXt27d9+/YFAH19/eTk5I0bN8bHxzN7q6qqIiMjiXNduNC4vr6+m5tbQEBAEVMU+RujrKzss5XXpaSk1NTU2rVrZ2ho2KtXr759+9ra2o4aNcrFxYU8Zk+ePLmpr0OUzEx0c0MpKQRARUX08MDXr9HLC7W08O7d/xxZWIju7sjhIADq6GA9shu4XPTyqg4vBUDi6U9NxcJCRMSqKvznHywv/zAW5eRgWVmDr5DySahwlyCjR6OvL3p4VAt34jAj/+Tl0dwcZ83CXbswNLSKZnA3ErNnIwA2LCb4m+XIkSMjRoywsLBQUlISufmpqKhYWVm5u7sfO3bs6dOnNX2BcXFxUlJS0tLSSUlJTdL4pmXnzp0AMGHChPp9vLQUhw5FZWWMjsY1axAAVVTwC8V//cnPx5AQDAnBb1X+fRUUFhb2798fADp06EBKAebl5QUEBLi6upKC5QQ5OTlbW9tt27ZFRkY2dZO/CiIiIoyMjMaOHWtnZ2djY2Nubm5iYmJoaKipqdmqVatPa3oy9X3s2LGmvojaiY9HF5dqRaGpiXv3YkQEPntWvTcsDP/+GzU1kfjm16xpkLequBjXrUMFBQRANTWcOhXHjUNEfPsWx4zBBw8+ePp/+AHpqjOShoWIn+27lPoxZgycOgWurjB7Npw9C5aWkJ4OPXpAjx7QsSNwOE3dvm+NwkJo3x4qKiAhAYyMmro1zZvs7Own/xIXF0dWaGKQkpIyMjIi90hjY+MBAwZMmzbt+vXrS5cuJcle3xrZ2dkdOnQAAA8PD2tr6969e2tqan6RBS4X4uLg6VOYMwekpeHKFRg+XDJtpXytFBcXOzg4PHjwQEZGRltbOyMjg7l9GxkZ2dvbOzg4WFtbk/woSh3hcrllZWXl5eXv378vLi7m8Xjv3r2rrKysqKgICwubNGmStbV1U7fxU9y6BT/8ABERIC0NK1eCvz88fQpqamBtDR06gI8PWFnBH3/Av1VkGkRWFnh6gp4eJCcDiwVjx4KVFcyaBWvWwOnTsGsXAICHBzg5wb+FcCgSgQp3CUKEe34+uLhAjx7w119N3aBvnPfvwc8PYmNh586mbkpLIy8vLyoq6tmzZ1FRUVFRUS9fvhQIBCLHyMnJpaenf6lgbTEMHjw4Njb23bt35K2Ojk6vf+nd29zQ0IDF+ryRrVth/Xr480+YM0eyraV8nZSVlXXr1i0jIwMAFBQUBg0aZGtrO3r06G7dujV10yhNBiL4+0NyMsjKwtu3UFgIhw6BtTUEBEBoKEyZAnUZW76ImTNhzRqYNw98fWHJElizBmbNAjMzAICoKPDyosJdsnwm/IvScAwMYMwY+K9HkiIxSkpg9Wo4fBgAIDAQ+Hxwdobz58HHB+TkQEcHtmxp6ia2QNq0aTNixAhSJRoAuFzuy5cvGZf8o0ePAGDGjBnfrGoHgJCQkL1792ZnZ0dFRUVHR2dlZWVlZV25cgUAunUzz8yM7NkTTEzA2BjMzcHcHIjb9NUrmDkTLl0CJSXYtg0mTYKRI8HUtImvhdJUKCoqRkVFnTt3rqysbOHChTUXAKF8g7BY8N13AAA7d8LgweDnBw8fAgC0aQNTp0rqpIqKsHIlbNtW/XbkyA8ed4qkocJdgpw8CQoKAADr1kFlZVO35huBz4f09OrXRUVQVQWpqfDHH3D5MsjIwL59sH8/fP99kzax5SMjI2NiYmJiYjJ9+nQAqKysLCoq0tbWbup2NSXy8vJr164lrxExOTmZmaBgs3vGx8O9e3DvXvXB0tJgbAy9eoGLC7x+DZs2wc6dkJEBFRVUtX/rqKurz507t6lbQfl6+e03mD4dGiGWYtw4+Pvv2t35b9/CpUsweDB07CjxZnyDUOEuQZgUPg4HFBWbtCnfFOnp8McfAAAPH4KlJdy5A2PGAHFNTZ0Krq5UuDcycnJy37hqF4HFYnXq1KlTp07MmjiFhfDiBTx5Uv0vMRGioyE6GsaOBUtLyMyE6OimbTKFQmkeaGuDoyPs2yfBU4wcCSoqAAB790J4OOjogK1t9a6hQ0FXF/75B5ycwNMTDhyQYDO+Wahwp7Q4lJWr3ZJZWdVbaCIH5etGTQ0GD/4QGFpWBjExEBUFnTrB9euwYwfMnUt9VxQK5VM4OVXr6cWLJVt/YeLE6hcGBmBgAACgq1u9hcRL6ulBTg5Qd42EYH/+EAqleaGmBhYWYGEBZI1oS0u4cgWqqgAATp+GoUObtnUUymdRVISBA2HhQiBLXurqwrBhcOlSUzeLQqF8xXTpAm3bAgBwOGBv35QtiY+Hgwdh4cKmbEMLhgp3SsuCwwFmyUAVFVBVBUNDmDkTJk6EKVMgMRHc3Zu0fRTKF8DhVOfJrFgB2tq0hiyFQmkGZGeDnh4EBzd1O1ootBwkhUKhUCgUCoXSDKAedwqFQqFQKBQKpRlAhTuFQqFQKBQKhdIMoMKdQqFQKBQKhUJpBlDhTqFQKBQKhUKhNAOocKdQKBQKhUKhUJoBVLhTKBQKhUKhUCjNACrcKRQKhUKhUCiUZgAV7hQKhUKhUCgUSjOACncKhUKhUCgUCqUZQIU7hUKhUCgUCoXSDKDCnUKhUCgUCoVCaQZQ4U6hUCgUCoVCoTQDqHCnUCgUCoVCoVCaAVS4UygUCoVCoVAozQAq3CkUCoVCoVAolGYAFe4UCoVCoVAoFEozgAp3CoVCoVAoFAqlGUCFO4VCoVAoFAqF0gygwp1CoVAoFAqFQmkGUOFOoVAoFAqFQqE0A6hwp1AoFAqFQqFQmgFUuFMoFAqFQqFQKM0AKtwpFAqFQqFQKJRmABXuFAqFQqFQKBRKM4AKdwqFQqFQKBQKpRlAhTuFQqFQKBQKhdIMoMKdQqFQKBQKhUJpBlDhTqFQKBQKhUKhNAOocKdQKBQKhUKhUJoBVLhTKBQKhUKhUCjNACrcKRQKhUKhUCiUZgAV7hQKhUKhUCgUSjOACncKhUKhUCgUCqUZQIU7hUKhUCgUCoXSDKDCnUKhUCgUCoVCaQZQ4U6hUCgUCoVCoTQDqHCnUCgUCoVCoVCaAVS4UygUCoVCoVAozQAq3CkUCoVCoVAolGYAFe4UCoVCoVAoFEozgAp3CoVCoVAoFAqlGUCFO4VCoVAoFAqF0gyQapKzvnv37uzZs9HR0Vwut2PHjt99952Ojg4AnDx5sry8fN68ecIHP3369MqVK0uWLFFTUwsICEhMTBSxtmbNGmlpaQDw8fHJysqaPHlyhw4dhA+4cOFCQkKCk5OTsbExAMTExFy9epXskpeX79Spk52dnZSUFAAUFRUdOHDAycmpV69etbb82bNnly9fHjduXPfu3ZmN5eXlp0+ffvbsmaysbL9+/caPH89isZi9T548OX/+fGFhoZ6e3tSpU9u1a8fsQsQLFy7cvn2bz+ebm5tPnjxZRkaG7Nq/f39FRYXI2Xv16jVixAgAKCwsPHHiRGJiooqKyrhx4/r16yd8WHFxsY+PT1xcnKKi4qhRo6ytrWu9lpZHSUnJ2bNno6KiuFyuoaHhpEmTdHV1AcDPz6+oqGjBggXCB0dHR1+8eHHhwoWtW7c+e/ZsXFyciLXVq1fLycmRj7969WrixIkGBgbCB1y+fPnFixcODg49e/YEgLi4uEuXLpFd8vLyhoaGI0aMID2zpKRk7969I0eONDc3r7XlMTExFy5cEOl4lZWVZ86cefLkibS0tLm5uYuLC5tdy5P21atXY2JiZGRkVqxYIbw9Pj7+7NmzdnZ2It2DwOfz9+/fz+VymU5FePnyZUBAQHZ2dps2bcaMGWNqakq2BwUFxcbGihhRUlJavHhxrVfUwsjOzg4MDHz58iWLxerRo8fEiROVlJQAYM+ePd26dbO3txc++OrVq4mJicuXLweAAwcOlJaWCu/V1NScO3cuef3bb78BwMqVK8n4w3Do0KF3797Nnz+/VatW8O+fmPl49+7dmb/p8+fPL126NH/+fHV19ZrNRsTg4OCYmJi5c+cKH5Cfn+/n55ecnKylpWVnZ9e3b99ar5o0o2vXrmPGjBG2GRoa+vTp09mzZ2tqagofn5WVdfr06ZSUFGVl5UGDBjk4OLDZ7Nu3bz98+LCmcQ8PD/KCy+UGBgZGRkbyeDxjY+OJEyeSq/4WKC4uPnPmTGxsLI/HI7dCcoM4fvw4n8+fNWuW8MERERHXrl1bvny5srLyyZMnU1JSRKz9+OOP5MWxY8cKCgpmzJihra0tfEBAQEBqauqECRM6depEDN68eZPsUlRUNDIysrW1JYNMdnb20aNHJ02aZGRkVGvL7927d/PmzSlTpnTs2FH4cvz8/F68eKGsrGxpaSnyu2A4depURkZGmzZtZs6cKbz9/v37N27cmDx5Mmke4ejRo69fv2bestns1atXM29v3rwZFhZWWFhoYGDg6uqqpaUlbDA3N/f48ePdunVzcnKqtSUtkqKiosDAwOfPn/N4vM6dO0+aNIl8LcePH+dwOFOnThU++PHjxzdu3Fi+fLm8vLyvr29aWprwXhaLtWbNGvL6r7/+ys/PnzlzZps2bYSPIT95plM9efIkNDSU7FJVVe3cubONjQ3pVPn5+UePHh03blzXrl1rbfnTp0+Dg4MnTJgg3OuIvoqOjlZUVCSjSq2fDQwMTEpKUlVVFb7RZ2Vl+fn5paent23bdtSoUT169BD+SGVlZWBg4JMnT/h8vomJycSJE1VUVJi9iYmJ58+fz8jIaN269bBhwywtLcl2gUBw9erV+/fvc7lcExOTKVOmMLKt8cBG59atW61bt5aSkho4cKCdnV3r1q0VFRXPnj2LiLa2tr169RI5/vDhwwDwzz//IOLo0aPl5OR6/Zfy8nJypKGhIQB4enoKf5zP57dt2xYAdu3aRbYcPXoUALp3725ubt6lSxc2m92xY8f09HRETE5OBoAjR46ItEEgEISEhDg6OhJFvnv3bmZXSkpKp06dlJSUHBwcBg0aBAAjRozg8Xhk79q1a9ls9qBBg0aPHq2pqSkvL3/nzh2mYc7OzgBgYWFha2srJSXVv3//0tJSsnfo0KHmQvTu3RsAli1bhojx8fHt2rVTVFQcNmyYnp4ei8USbk9mZqa+vr6CgsKoUaOIoFy7dm09/1TNivDwcC0tLaZfaWlpycvL+/v7I+LIkSONjY1Fjj927BgAxMXFIaKLi4usrKxIvyouLiZHduvWDQDWrFkj/HGBQECeD7ds2UK2nDx5EgCMjY3Nzc27du3KZrP19fVTUlIQMTMzEwB+//33WpvN9CvGFCKmp6d37dpVUVHR3t5+8ODBLBbLxsamsrJS5OMpKSmKiopqampKSkrCNl1cXDgcDgCsX7++1q9r9+7dcnJy8vLyCxYsYDYGBARISUn17Nlz1qxZ/fv3Z7PZTJs3bdpk/l+UlZUNDAw+8tdoUfz555/y8vLy8vKWlpaWlpZycnK6urrPnz9HRFVVVTc3N5Hj58yZo66uTl63adNGTU2tuxDjxo0ju/Ly8sggfO3aNeGPJycnk/5w//59smXu3Lnk4c3MzIyMZiNHjuRyuYjo7e0NAAkJCSJteP/+vbe3N+NfiIyMZHZdv35dWVm5bdu2Dg4OnTp1YrPZv/zyS82rPnHiBIfDUVZWnjhxorBN5uZ379494eN9fHzk5eVVVVVtbGysrIVzLMgAACAASURBVKzU1NTIoHrgwAGRnqOhoSErK0s+lZKSYmRkJCUl1bt3bwcHhzZt2vzxxx91+7M0e27cuKGhoSEtLT1o0KDhw4draGgoKSmdP38eES0tLQcMGCBy/L59+wAgMzMTEW1tbRUUFESGLObI1q1bA8COHTuEP15ZWamqqgoA//vf/8iWXbt2AYCpqam5uXnnzp1ZLJaJiUlBQQEiPnr0CABIY4Th8/kXL14kdzoAOHnyJLPr2bNnbdu2VVdXd3R0NDMzA4Bp06bVvOrw8HA2m62mpmZmZiZs08LCgtg8ceKE8PFt27Zt164d03ns7OyYXUuXLmWxWMOHD585c6a+vr6SkhLTzxMTE93d3eXl5QHAwcHhc3+KlkNwcLC6ujqRE0OGDFFVVW3VqlVISAgi9u/f38rKSuT4HTt2AEB+fj4i2tjYKCgoCA9WPXv2ZI4k6n/nzp3CH3///j3xCDCdivTSnj17mpubE1dXjx49iP2oqCgAIDdlYfh8PtFXpAP8+eefzK7ExEQDAwNlZWV7e3vSqVxcXPh8vogF4rpq1aqV8C3pzJkzcnJyHTp0cHBw0NPTk5KSEr4FJyYmduzYUVpa2szMzN7eXktL6+jRo8zeLVu2SElJaWlp2draDhgwoEOHDkSblZaWDhs2jMPhWFpaDh06VFpamvnJNCaNLdyzs7PV1NQ6d+788uVLsqWiomLx4sWXLl3Cugl3ExOTWi1XVVVJS0srKCh06dJFePuNGzcAQEFBYcmSJWQLEe5MA54+fSovL0+GmI8J9/Ly8j59+qxevfrKlSsiwn3ZsmVdunTJyckhb4kL7fTp04iYkpKioqISHBxMdhUWFurq6lpYWJC3J06cAADmlhkUFAQAGzdurPXqzp8/DwAPHz5ERCsrK3V1dfKF8Hi8SZMmSUtLE4GIiBMnTpSXl3/w4AEiCgSCRYsWsVisx48f12q2xZCbm6uhoWFoaMgomMrKSnd398DAQKybcO/UqVOtlgUCgYKCgoKCgoGBgUAgYLaHh4cDgKKi4rx588gWItyJnkPE2NhYJSUlFxcX/Lhwf//+fb9+/VauXBkcHCwi3D08PAwNDTMyMsjbAwcOAMDx48dFLIwYMcLExGTp0qWMcOfz+YMHD3Z3d79x44aUlFStwj0tLU1JSWnz5s1t2rQRFu76+vr9+vVjhkUnJydFRUXmKVSY4uJiVVXVDRs21PqltSTu3LnDZrOHDRv2+vVrsiUnJ8fFxSU6OhrrJtxnz55dq2WijRQUFGbNmiW8fcuWLQoKCsKqaO7cuW3atGEO+N///gcAhw8fxo8L94cPH/bp0+eXX34hIxIjaAQCQa9evcaOHUseAnk8nqOjI4fDYUYwQkFBgZaW1rJly7p168YI96dPn5qbm//888979uwREe4xMTHS0tLjxo0rKysjW2o+ZBJ4PF6HDh3Id1JVVdW7d++2bdsy7efxeFVVVbV+sIWRkZGhqqrapUuX5ORksqW8vHzhwoVBQUFYN+Het2/fWi2XlJSQoalPnz7C2wMDA9lstry8POPKIcKd6dh3796VkpJaunQpfly45+Xl9e7de/369b6+viLCfeLEif379y8qKiJvyQRgeHi48McrKyuNjY0dHBycnJwY4V5QUEBs+vn5iQh3Ho/H4XD27t1b8zLJzdrDw4O8fffunba2NqPRp0+fPmPGjHPnzpmamn47wj01NVVJScnY2JjRA+/evZs1axYRIXUR7jV7HaG0tJTFYikoKIj0uosXL7JYLDk5OaZTkV6am5tL3t65c0daWnrx4sX4ceFeWFjYs2fP1atX+/v7iwj3OXPmdO/ePS8vj7xdv359TU8Hn88fNGhQ//79p06dygh3Mus+c+ZMMp5UVlYOHjxYXl6e6G/iLNfV1SU6imxhbnxk5nzZsmXMvY8ZzY4dO6asrMwMpyR242PeMcnR2MJ948aNNX/MDA0R7mSKZ8mSJQDw9OlTZvu8efNMTU0tLS0dHR3JFhHhjoh9+vTp3bs3fly4MxQWFooId0R8+/Yt85pM6jGdmPGgE+zs7HR1dcnrYcOGtW7dmrjNCP369dPT06v1vMTVh4jFxcUAQMZWwosXL5jn4KKiImlpaWE/R1ZWFofDIT+bFszmzZsB4ObNm7XubYhwz8nJYfoVeRwiLF68mMwsDx8+nGwREe6IaGFhQc77CY87gYRFCQt3/G+/IuPm8uXLhQ/4+++/2Wz23bt3V61aJexxZ/iYcLezszMyMqqsrBQW7nw+n8PhzJw5kznM09NTeAgWZvv27bKystnZ2R+7ohbDqFGjFBUVyY2tJg0R7kSmLF68WEVFpaKigtneo0ePuXPnysrK/vrrr2SLiHCvrKxksVjEE/Ex4c5w4cIFEY97ZWVlSUkJ8/bMmTMAwPgXCFOmTGnbtm1RUZGwcGe4du2aiHCfNWuWnJxcVlbWx5rB4OPjAwDksYfc9r4dF7swa9euZXwxNWmIcCdRVWTISkpKYrZPmjTJ0tLS1NR08uTJZIuIcEfEjh07Dh06FD8u3BkSEhJEhDufz2dUO9OM/fv3C39q/fr1CgoKKSkpwsKdISkpSUS4k5EzICCgZgPCwsJEfBmDBw+uKQ/69ev37Qh38rD07NmzWvc2RLg/f/6cDFYinWry5MmDBg3q1asX06lEhDsidunShZz3Y8KdIT09XUS4CwSCN2/eMG9TU1Nr3ih3794tJSUVFRU1ffp0YY97aWmp8Ljq5eXFjISBgYEAcOzYsVqbYWlp2bZtW+HPCiP8e0HE9u3bN34Ha+zk1Js3b7Zp02bw4MFit0yE+9SpU3V0dMhzGwDweLxz5845OzsbGBiQP3lNXr16lZCQQKJK6oeamhrzms/nAwAT466oqMjsSkxMfPDgARNPHB8fb2VlRWKgCcOGDXv16lVZWZmI/cjIyPDw8FWrVgFAZWWliNmuXbvKysqSeMfk5GQejzds2DBmb7t27YyNjePj4+t9dc2CmzdvqqurDxkyROyWSb9ycXExNDRk+pVAIDh37hyJev9Yv8rMzHzx4oUY+xUiCudOvH79evXq1XPnzmWmmOvI33//HRIScujQIVlZWeHtbDa7X79+Z86cOXv2LABwudzz588PGjRIJKIRAHg83sGDB6dOnUrCNlowfD7/1q1b1tbWIsHcYiE1NVVaWnr58uUlJSVkygUAEhISYmNjJ06c2KFDB5F4U4bQ0FBEFE6z+SJkZWVJgD4BEZn/CVevXj116tTBgwdJZEVduHHjxoABA9q1a1dcXBwTE/Pu3buPHblv3z57e3vyuyDToRMmTODxeHFxcUSlfSPcvHlTR0enf//+YrdMus28efPU1dWZIau8vPzy5cvkVvixfhUfH5+enl7vIYvNZgt3GJFbIQDExsb+9ttvP//8s0iy0CfIzc0FAE1NzdjY2IiICOGbY48ePeTl5X/99VeiKVNSUiIjI8eOHVu/xrcMbt682bFjx49l6DUEcpubN28eSTUkG8vLyy9duvTpTvXy5cu0tLR6D1YsFks4OafmYPXq1auNGzeuXr2aScdiUFRUJFlqNT9LUjvGjx/P4/FevHiRnZ3NHFZRUfHgwYNRo0bJycm9fv06NjZWJNtQQ0ND+K1AIKjfpTWExk5OTU9P19fX/8QBaWlpJPKbQUQYpaamCmdburq6kkwvcljHjh3Hjx/v6+u7detWFosVEhLy5s2bCRMm+Pv7EznC4O7urqSkVFpaeufOnSFDhuzevbvBFwcAcPnyZQCwtbUV3rhs2bLExMRbt25NmzZt//79AFBVVZWXlyeie4hCysrKEskH2rFjR+fOnUl6jaamZqdOnc6cOfPDDz8QYXf27FkWi5WVlQUA5M4nkpDUpk0b8iDbgklPTyfh/h87IDMzU6RfvXr1SvhtVlaWcL+aPHkyyXEh/crQ0HD8+PEnT57cuXMnh8MJCwvLyclxdnYOCgry9vYWCARM2uiqVatUVFRKS0vv3r07cOBA8uduOKRfDR8+nNmyZMkSNpu9bdu2L7Lz+vXrH374YdasWUOHDq2519vb28HBwdnZuWvXrqqqqsrKyiK/GoK/v39GRsayZcu+8CKaH2/fvi0rK/u0zrhx48Z3330nvCUiIkL47bVr14QHhF9++WXAgAEAkJaWpqur26lTp969e/v7+5MEUF9fXw0NDRsbG319feGhr7i4eOLEiQDw5s2b8PDwFStWMBmuDeTKlStKSkqkSQBQVla2ePFiBweH8ePH19FCVVUVSckYNWrU1atXEVFOTs7Dw2PTpk0iR968eTMiIiIkJIS8JRkaBw8e3LlzJ7k72tnZ+fj4SOIx6WsjPT2dJGV9jKSkJJEh659//hF+m5CQIDxkubm5kbzD1NRUFovVqVMnJyenU6dObdiwAQAuXrxYXl4+bty4tLQ0kVzhOXPmyMjIFBcX37lzZ+zYsWT2suFcvnyZxJiRtwKBYP78+V27dnV3d6+7EaKoRo4cSWKolJSUtmzZsnTpUgDQ0NDw8/ObPHlyz549ra2tk5OT586d+9NPP4ml8c2U9PT0j9U/IMTHx4sMViLVPuLj44UHq3nz5k2aNAn+fRokncrf35+ErFy5cqWsrGz8+PEZGRkPHjwQtjNv3jw5ObmysrJbt245ODhs2bKlodcGAP/eB4Vdk/Pnz9fQ0CDt+TRXrlzR1NQkz6UpKSmtWrXatm3b3r17iTN05MiRJ06cUFdXf/XqVVVVVXl5+YABA8i8k6qq6q5du+bMmVPT5rNnz7Kzs1euXCmWq6s7je1x5/P5ws9ANeFwOK3+C8kvYZCXlzcTginSkpaWpqioqKmp6ezsnJ6eTsYmf3//7t27d+vWTV9fv6ysrKCggLGjqqqqpqamoqLSrl27hw8fMh6vhlBQULBx48bhw4fb2NgIb9fQ0DAwMNDX1w8ODo6MjAQAHo/H5/OF3e0AQDygpBsxpKWlnTt3bsWKFUQaslisP/74Iysrq3PnzkOHDtXX19+wYQMjWLlcLgCImJWRkXn//n3Dr+5r5rP9is1mi/QrEkbMICsrK9yvSJkjAEhLS5ORkWnXrp2zs3NOTg4Jbff39+/cubOpqam+vj6XyxV+XldRUVFTU1NVVW3Xrl1ERARJXWggRUVFGzZsGDp0KJNQHxQU5O/vv3v3bmGvfF1YsmSJQCD4mNy/f/9+Xl7e999/36tXr5iYmKdPn5JwDhF2797NOE1bNjweDwA+O2TJ/ReSFszQqlWrbkIw3u60tDTySODs7HzhwgXiTTx9+vS4ceOkpKQ+5sRSVFRUUVG5du0acTQ2kEePHp08eXLdunWMr9TDwyMvL+/333+vuxGiuW/fvt23b9+oqKjk5ORp06b99NNPNTvPrl27evTowdx3KyoqysrKnj17duXKlczMzOPHj9++fXv+/PkNv66vn88OWVJSUp8eshQUFISHLGZmLC0tTVtbW0FBwdnZOT4+nvQTf3//gQMH6urq6uvr5+XllZeXM3bIrVBVVVVbW/vOnTtMnZmGkJycvHPnztmzZ5PMfgDYu3fvo0ePvLy8RG5Pn8be3v7q1asvX77k8XhZWVkjRoxYtmwZefAjxT0UFBR+/vlnRMzKyjp//vzdu3cb3vjmC4/H++x9UGSwEqlnJS8vLzxYMd7ltLS0Nm3aKCoqOjs7x8bGkgBdf3///v376+npGRgYiHQqgoyMjKam5qNHj+7cudPwq8vLy9uyZcuECROYeSpvb+/g4OCDBw8KxyDUytWrVy9fvvzLL7+QCjAVFRVFRUWJiYnXrl3LzMw8duxYSEgIiS4jo1lQUNCUKVMSEhJevHhhYWHh5uZGRLwwVVVVy5Yt09XVXbhwYcOv7sto5NAcU1NTQ0PDj+1tSIz7jBkzyC5SRmbZsmUkiX7Tpk2IeOvWLQB49OgR1ohx5/P5rq6uMjIyGRkZ9YtxJxQVFZFOTGop1KSqqsrCwkJHR4dkPKipqU2dOlX4AOItEI7oQsRly5apq6uLxMonJydv3br1hx9+OHHixJs3b1gs1vz58xGRDFt+fn7CB/fp04fJiG2p9OnTp3379h/b25AYdzc3N7JLIBDo6ektWLCAy+VqaGisW7cOEYmbgVQKEolxFwgEc+bMkZKSSk5Orl+MO6GkpMTS0lJHR4fJNyouLiZZzm//ZfHixYqKim/fvhVOmcAaMe4XL14EgL179zIf1NTUnDVrVmFhISLGx8dzOBwmPfrt27cTJkyAGpkDpNQXKVPQ4qmoqGCz2TWDvBkaEuNuZGQ0d+5c/De1xs/P7+nTpwBAnNZbtmyRlpYmmVUiMe7v3r0zMTExMjLCesW4M7x48aJNmza2trZM6tXDhw/ZbLZw4Yi6xLgLBAJ5eXkmSxsRuVyuurr6mDFjhD+VkJDAZrO9vb2ZLdOnT2/VqpXwMXPmzOFwOEyGawvG2NiY/AVrpSEx7uPGjRs4cCAivn//Xk1NbcOGDcXFxfLy8uS2RQaB+Ph4rBHjXlVV5eTkpKSk9Pbt23rEuDNkZ2d37dq1R48ezL0sOTlZUVFx+vTpzMhDnvzfvn0rnItcM8ZdhNLSUikpKZKHQ4TBrVu3yK4XL14YGxurqamR0Yzhm4pxNzAwqKmgGBoS4z5+/Hiyi8iqH3/88d27d/Ly8mSsEO5UIjHuPB5v9OjRioqKr1+/rkeMO8ObN2/MzMw6duzIJFYVFBRoampOmjSJOUYkxp3h8ePHrVq1Gj9+PNPZJk2aJDyiIuLUqVOlpaW5XG5GRgYAbN++ndlF4rVWrlwpfDyfz58xY4aCgsLHMjYlSmN73Pv27fvq1SuS8CdeUlNTifuKzWaPGzfO39//8uXLxcXFZLaR7KrVg8Vms52cnLhcbs1K3nUnJSVlyJAhWVlZoaGhpHZ4TTgczqhRo7KyskjP0NfXj46OFj4gJiZGRUVFOKKrqKjo6NGjixYtEnmgNDQ0XLNmzfbt26dNm0YyUUhdZz09PQAQNltZWZmUlES2t2D69u2bnZ1NvljxwvQrFos1fvz4M2fOXL169c2bN5/tVywWa8yYMVVVVcQ5UT/S09NtbGxevnwZGhrKBGwEBARkZGTcu3dP/V9+//33srIydXV1UvXoY5B4sOXLlzMfLCgo+Ouvv0iPJesJMEGiampqJM6HJIExiDhNWzZycnLdu3ePiIhAoahKsYCITNygoaGhqampv7+/v79/q1atSBSTgYEBj8cTnsxhUFZWtrOzS0pKqpkPU3fCwsKGDBliZGR0/vx5Jtvht99+EwgE33//Petf4uPjAwICWCwWmc2rFRaL1a5dO+HYM2lpaQ0NDZFI9507d2prawvP1Ovo6BQVFRUVFTFbtLW1+Xx+Q66rudC3b9/U1FThSWBxwQxZMjIyjo6Ovr6+gYGBlZWVJPaJ7Ko1M4fD4Tg5OZWWlorE5HwR0dHRlpaWJE6VuZd5eXmVlZUdP36cGXmuXbsWExOjrq5ec2GWT6CoqKiqqkoqNNy8eVNNTY0JFjI2Nl67dm1hYaHIXfWbok+fPomJieT7ES9paWlksJKVlXV0dDx16tT58+crKirGjRsHn+xUUlJSY8eOLSsrI09l9ePly5fW1tZv3rwJDQ1lAoyPHDlSUFDg7+/PDFbHjx8ncWL37t1jPnvx4sXhw4dbWFj4+voyc6E6Ojr5+fnCUwTa2to8Hq+iokJbW5vD4QiPZqR8OSnWRHj37p2zs3NAQEBgYKAkMjY/S2ML99mzZwsEgtWrV4vcCBt+X2Q6FgA4Ozvn5uZ6eHh07drVxMQEAHR0dKSlpT+WR0j8psKLPnwRQUFBffv2VVBQePz4sbARPp9/6NAh4RteXFyclJQUGc6cnJyeP3/O9LDc3NygoKDRo0cLWz58+DCPx1u0aNHHTs3n87ds2aKqqkoG5fbt2/fu3fvUqVNMJztz5sy7d+9EzLY8SEG977//XiRTROz96vXr1ytXrjQ0NCSV9bW0tBQUFCTUr27dukWKMz58+FB4xYoxY8ZE/pdp06YpKChERkZ+Oj338OHDIh9UV1efMGECmcds3749AAg/vr58+RIAhAOOExISgoODibCr30U1O2bPnp2amkrKcYqRnJycyspKpmu5uLiQlNCxY8eSydxP3AsR8dGjR9ra2p+dIK4VRNy3b9+IESNGjBgRHBwsbGTjxo0h/6VDhw7W1tYhISEiU+oiWFlZ3bp1i3nMiIuLS05OJr8RQn5+vo+Pz9KlS4UXKyFrmpw6dYq85fP5V65c0dXVJWXIWzazZ8/m8XiNcCtMTk7evHlz3759ifuG7PrEkMVisYTXVPoiTp48aWFhYWRkdO/ePeGk9qVLl4qMPJaWll27do2MjPx0oH9aWpqw4+PBgwdv3rwhYdw6OjrFxcXCT7bkeeNb6DwfY/bs2RUVFXUJ+P5SPtapyJ/vE4MVAJDZm3p3qsuXL/fr169Vq1YPHz78P3tnHhfz/v3xMzPNFO2pFJUaIdllT2UpQnbZ43LJnuVG1m+4aNzrulmKsqZry3ojW/ZkLYUQ2hctlNBeM+f3x3vu/LqFW81nTJP38+GP0syZU/OZ9+f1Pu+zVKyQHDduXKXFysHBwcDAIDQ0lKg+RNy8efPIkSPHjRt35syZSisPIpKWpgBQVlZ26dIlc3NzDQ0NJSWlXr16nT59WlKTeuHCBdK4lnz76tWrnj17Pnr06ObNmwMGDKjdLyUl37s4tWfPnsuWLdu8eXNKSsqkSZO0tbUTExNPnDixatUqsnX7T969e1epemb69On6+vrp6emSkKStra2+vn58fDzpPgkAHA7H2Ni4YmTU39+/UaNGQqHwyZMnJ0+eHDVqFJ/PJ71Zzp8/X3E56Nat28CBA2/cuPHw4UPyXl6/fr20tJQMFPTy8lq9erWWlpajo+OhQ4fIU5o0aeLi4hITE+Pu7h4YGDhr1iwNDY2rV68ePnx45syZJJ104cKFBw4cGDFihKenp4qKyp9//snlciUOA0BZWZmPj0/V3h2PHj06fvx4586ds7Kyzpw5c/fu3cDAQMmswd9++83R0XHAgAFz585NS0vbtGlTz549KxU51T+6du26atWqDRs2pKWlubi4NGrUKDEx8eTJk+7u7qSk7z/Jzc2tdF1NnTrVyMgoJSVFcl2RJNH4+HjJMDkWi9WsWbOK19W+ffsaN24sEomePXsWFBQ0ZMiQ1q1bk9JhEqqXPLJz585DhgwJCwu7e/dueXk5AJCW4ebm5qNHj966deuyZcvU1NSGDx8uyRXW19efNm2anp5epeq9xo0bs9lsSVnSgwcPSG6YSCS6e/fu5s2bTUxMJkyY0KpVq0q/NZfL1dPTI0tSnz59mjdv7ubmlpub26lTp4SEhP/9739GRkYTJ06UPP7333+vFDSt95ApE4sWLXrw4MGgQYMaNGjw7NmzI0eOXL16tdKE5q/x9OlTLy+viv+zYsUKSdEz+R9nZ+fVq1enpqY6OzuT/5Ec5tja2gJAUVERad/+4cOHy5cv3717lzRoJ/j7+1fUK2Q24dmzZ7Ozs0kAkgwItLa2btGixcSJE0+dOtWtWzcbGxsyTQIAOnTo0L179y92ZiDpNOTbc+fOZWRkkN3d33//HRMT06NHj/bt23t4eJw4caJv374kT/S3337T0dGpOMp3586dbDa70lTsgQMH9u7de8mSJaQi/6+//oqOjj548OCPsC20tbVdsmTJ1q1bk5KSJk6cqKWllZCQEBQUtH79eskkmm/z9u3bSkvWrFmzuFxuXl6eZMkaOHCghoZGfHy8ZJykmpqarq5uxYDi9u3bGzZsWF5e/ujRo+Dg4OnTp0si5UFBQZKRvQDQp08fGxubkJCQmJgYclZw7ty51NRUKysre3t7Nze3HTt2NG3a1MbGhlyrANCyZcuRI0caGRmRuIAELS2tgoICyZJFBjOTZsrnz59PT0/v1KnTgAED3N3dL168OGPGDHJA4e3tbW5uTlKKJ0+evGvXLkdHx5UrVxoZGd25c+e3334bMmQIEW1JSUmko05GRsbHjx9J+1oyzLge4+joOHPmTB8fn7i4uHHjxmlra79+/frYsWNbtmz5YjeCqrx9+7bSYjVz5kwul5ubmytZrBwdHTU0NN68eSNZgkh5YcX7YGBgoIaGRkFBwb17906ePDl58mR9fX2SanH27FmSHEiwtra2tbUNCwt7+fIlSUW+ffu2SCRq1aqVnZ2dp6fnr7/+2rRp0/Hjx5OEHABo2rTpkCFDzMzMKrUNCAwMjIuLI4tVfn7+6NGjr1y50rdvXysrqwMHDpDHkFVu6NCh3bp1W7BgQVJSkrm5+cGDB1+8eCHR8WvXrh0wYEDfvn2nT5+em5srEAhatWrl4uJCnHdxcSkvL1+9enV0dDRJ/uFwOF8sXZUd31u4A4BAILCystq9e/fq1atLSkpIRId0CzIxMak4cpagra1tYWFBdkvGxsavX7+WRGgIw4YNQ8RmzZpJ6mBIO+qTJ09WFKw9e/YkNZrq6up8Pp+0yyCj6bdu3Uqi2jwez8LCIjY2liTwSawNHDjwwYMHe/bsAQA+n//ixYsXL14MHjx4+PDh169fJ7vAgwcPSp7SsWNHFxeXDh063L9/39PT093d/dOnT6amphs3bnR3dyeP0dHRuX379ooVKzZu3CgUCrt27XrkyJEWLVpIjISGhvJ4vKprTU5Ozr179wICApSUlLp27Xrjxg3JMF4AsLe3DwkJ2bhx46JFi0ha4caNGytVy9VLfv31106dOvn6+q5Zs6a4uLhZs2akaTEAGBsbV/0LaGlpkU6aAGBkZKSvr1/puho0aJCKikrTpk0tLS3J/7BYrKlTpx45ckSirgCgR48e5FBFTU2Nz+eTlGIVFRU+n//bb7+RxrdcLtfCwiIuLq7iGXR5efmQIUMiIiLITY7P579+/fr169f9+/cfPXr06QkOsgAAIABJREFU9evXSYRMshsEgNatW1eagk7Q0dGpGIqIjo4mNk1NTZOTk/39/Xv06DFhwoSqT2zWrJlE8KmqqoaHh3t5ee3YsSMlJUVbW9vBwWHDhg2S+qRPnz7dv39/2bJlcpjwLD+UlJRCQkJ27Nhx+PDhs2fPcrncZs2akTFnANC8efOq7TIbN24sCS/x+fx3796RggoJy5cvJzdCyY2HzATIyMiQ5CDp6elZWlqSbBNdXV1dXd3NmzfDP8vX8ePHyY5UQ0PD3NxccksjdOzY0cLC4tChQ0S18/l8ck/y9PTU19ePiori8/nv378nBgmzZs36YmtC8tGQfHvkyJGHDx8Sm6QB/MqVK9u3b9+qVasbN26sWrVqzZo1XC7Xzs5OIBBItFp5efnly5cXLlxYqZMam80+d+7cqlWrAgIC8vLy2rZte/LkSVJZ8SPwxx9/dO3a1c/Pb+XKlWVlZcbGxn379iV3MVNTU1IYXREdHR0LCwtS3GliYpKWllZpyRo3bpxIJOLz+ZIturKysouLy8WLFyv+Va2trUkESktLi8/nk876ZPny9fUlm6sGDRpYWFg8fvyY1F0QdHV1bWxsbty4Qdpg8/n8hw8fPnz4cMqUKfb29jdv3iTabu/evZKnDBgw4IshuUqfmps3b5I7Mp/Pf/To0aNHjyZPnjxgwICAgIBt27adPHmSpNlMnjx5zZo1ZF/RuXPne/fubdiwYenSpe/evTMyMlqyZIkk2JyWlkbWQC6XW1ZW5u/vr6GhUe+FOwD4+fn17Nlz7969bm5uIpHI1NSUtKgCAGNj46pLt7a2trm5OTlPMzIySk1NrbRYjRkzptJFpaKiMnny5EuXLlW8qHr16kX6amhqavL5/F27dpFHmpmZeXt7E32lrKxsbm5O3l/JE1VUVGxtba9cuUIuZj6fHx4eHh4e7uzsbGdnd+XKFbJIVuz7Z21tPWTIkKq/u56eniRROSMjIy4ujs/nJycnV1zoPDw8OnTowOFwLl68uGLFiv3793/8+LF9+/Znzpwhfb0AoF+/fufPn//111+XLFmiqak5evRoLy8v0lTg+vXrZD2s+Ffi8XjfWbizGM/dpFAoFAqFQqFQKIzzvXPcKRQKhUKhUCgUSi2gwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKRQGgwp1CoVAoFAqFQlEAqHCnUCgUCoVCoVAUACrcKRQKhUKhUCgUBYAKdwqFQqFQKBQKpQolJbBsGbi4wOjRcOYMAMDChfD+vfinkyZ9f4+ocKdQKJUJDw+3t7dfunSpvB2h/FiUlpa+fftW3l5QFAlfX99OnTpdunRJ3o5Q6inbt0OzZhAYCEePgo8PJCZCWhqUlYl/mpT0/T2iwp1CoVSGxWJdu3YtJCRE3o5QfiDCwsI0NDQmT54sb0coikRGRkZ0dPTVq1fl7QilnnLtGkycCADA48Hw4RAWBgBw8CD4+ICPDyB+f4+ocK+fiESiT58+ydsLiqLSrVs3TU3Nly9fpqWlydsXyo+ChYVFSUnJw4cPy8vL5e0LRWHo378/AFDhTpEhEnWOCCwWAEDbttCpE3TqJP72+0KFez0kJiaGw+FYW1vL2xGKoqKkpGRnZwcA165dk7cvlB8FPT09Pp9fUFDw4sULeftCURh69eqlqqr69OnTzMxMefsiW+Lj43Nzc+XtxY9Hv35w4gQAQHk5hIRA794AAF26QK9e0KuXXDyiwr0eoqysDAAlJSXydoSiwJA4FhXulO9Jjx49AODBgwfydoSiMPB4PBsbG0S8ceOGvH2RIS4uLi1bttTV1W3evPnQoUPXrl177ty5er9XqRO4ucGLFzBhAowdCzNngpkZNGkCSkrinxobf3+PlP77IRRFg8fjARXuFOmwt7cHgNDQUERkyeM0kPID0r179yNHjjx48GDmzJny9oWiMPTv3//SpUvXrl2bMGGCvH2RCRkZGSdOnBCJRGw2OyEhISEh4fz58+RHRkZGHf+hU6dOZmZmdLlmmPXroV8/cHICDkf8Pzt2/P9Pjx37/h5R4V4PIRH30tJSeTtCUWAsLS2NjIzS0tJevHjRpk0bebtD+SHo3r07ANy/f1/ejlAUCUmUQd6OyApPT8+SkpLhw4efOHHi9evXkZGRkZGRL168ePz4cVpaWlpamkTHq6urt2/fvk2bNpaWllZWVlZWVg0aNJCv84pNbCwIBKCqCmlpoKkpb2/EsFAeJbEUmZKbm9uoUSNtbW2aD0eRhqlTpx46dMjb23vhwoXy9oXyQ1BaWqqpqVlaWpqbm6tZZ26TlDoOIhoaGmZlZb1+/bpFixbydodhYmNj27VrBwBPnz5t3bp1xR+JRKK4uLjo6OioqKjo6Ojo6OhKyTNcLrdNmzbq6uqjR4+my3htcHODHTtg9mzYtUvervw/NMe9HkIj7hRGoGnulO8Mj8fr2LGjSCR69OiRvH2hKAwsFqtv375QT3vLLFu2rLy83NXVtZJqBwA2m92yZcuxY8d6eXldvHgxIyMjNzc3LCzM29vbxcXF0tJSJBJFR0eHhYUtXrz47NmzcvFfgcnPh0OHAADmzJG3K/+CCvd6CM1xpzCCvb09i8W6efNmmWTYBIUiY2h9KqUW1Ncow+3bt8+dO6emprZmzZrqPF5bW7t3794LFy48dOjQ8+fP8/LywsPDmzRpgohxcXGy9ra+ERgIHz+CrS20by9vV/4FFe71EC6Xy2azy8vLRSKRvH2hKDBNmjRp3br158+fHz58KG9fKD8KJM2dCndKjXBwcACAa9euCYVCefvCGIi4fPlyAFi2bJmBgUEtLKipqfXq1Wvq1KkAUFhYyLB/9R6SHjNvnrz9qAwV7vUTEnSn2TIUKSFVX/XyAJpSNyERd1qfSqkRzZo1Mzc3z8vLe/z4sbx9YYzjx4/fu3fP0NBwyZIl0tgxMzMDgKSkJGbc+kG4dQuePQNDQxg5Ut6uVIYK9/oJbeVOYYT6egBNqbOYmpoaGBi8e/cuISFB3r5QFIl6FmUoLS0l6THr1q1TVVWVxhQR7omJicx49mPw4fhxAICZM4HLlbcvlaHCvX5C09wpjNC3b18ul3vv3r1Pnz7J25c6zfTp4i/evwcPD7m6ovh069YNaNCdUkPqmXD39fWNi4uzsLCYNm2alKZMTU2BCveakJGR0Xjv3unt2pW7usrbly9AhXv9hDaWoTCCurp6165dy8vLw8LC5O1LnSY2VvxFWRnEx8vVFcWHprlTakH//v05HE54eHg9SOb++PHjxo0bAeD3339XUpJ23k6zZs04HE5aWhptM1BN/Pz8ysrK8i0slJo2lbcvX4AK9/oJjbhTmILEsWi2zLdBhAMH4MABIOerFGmgjWUotUBLS6tz584lJSV37tyRty/S4uXl9f79e1tbWycnJ+mtcbncJk2aCIXC1NRU6a3Ve8rLy/fu3QsA8+peWSqBCvf6CY24U5iCpLnXmwNoGcFigbExGBtDkybydkXx6dq1K4fDiYqKKi4ulrcvFEWifkQZ0tPTd+zYwWKxBAIBUzZpfWr1OX36dHp6uqWlpa2trbx9+TJUuNdPaMSdwhQ9evRQU1OLiYnJyMiQty91Gnt7sLcHGxt5+6H4qKurW1palpaWRkdHy9sX2ZKbC76+4q9DQ4GeMUhJ/YgyrFq1qrCwcNy4cT179mTKJq1PrT4+Pj4AsGDBAhaLJW9fvoxCCvecnJwHDx7Ugzw22UEj7hSm4PF4tra2iHj69Gl5+1J30dMTf8HhQKNGcnWlXkDS3Ot9fWpBAdy6Jf765UugskpKrK2tGzRoEB0dnZycLG9fasnTp08DAwN5PN6vv/7KoFlan1pNnj9/HhYWpq6uPnHiRHn78lWkLXr4/uzfv3/evHnkCFVFRUW7Ak2aNDE0NKz0ra6uLgk//1DQdpAUpkDEoqIiAwOD+fPnb9261d7e3t7efuDAgRoaGvJ2rQ4xYgRER0PHjsBiwcCB8vZG8enevfvevXuvXLmycOHCOhv3YoTcXHGgPTkZ9PXl7Y2CU1JSoqmpyeFwmjdv3rFjR7JY2dnZceteR7+vsXTpUpFING/ePHNzcwbN0oj7tykpKUlKSkpMTBQIBIj4008/1eUbnIIJ98LCwvXr1xcXF/N4PCUlpcLCwoyMjP88wdfS0tLX12/UqJGGhkZaWtrBgwe7dOnyfRyWF3QAE4UREHHx4sU3btzgcrmqqqoJCQn+/v7+/v48Hq9Xr14ODg4ODg5WVlZstkKe3THIiRNw9ChcuAC5uXDpEowaJW+HFJyEhARtbe3Lly83btzY0dHR2dnZ0dFRgeRX9cnJ+X/h3rWrvL1RZPLy8gYMGJCZmamtrQ0AkZGRkZGRmzdv1tHR6devH1msiH6ts9y4cePKlStaWlqrVq1i1jLNcZfw4cOHhCokJydLZu5qaWm1aNFCvk5+GxYiytuHGjB//nwfH5/WrVvfv39fQ0OjqKjoQwUyMjLevn1b6dv3799XaoHE4XDevn2rX6+DG0OGDLlw4UJISMjgwYPl7QtFUUHERYsWbd++ncfjnTx5cvDgwdHR0VevXr169eqtW7ckHys1NbU+ffoMHTq07t8XZcfgwTB0KBQXw+DB8Mcf4O8vb4cUFkR0d3ffunUrm83W1dXNzs4m/9+oUaNhw4aNGjXK3t5eRUVFvk4yRWoquLuLOxFt3w76+jB+vLx9Ukzy8vIGDhz48OFDU1PTGzdu6Orq3r9/nyxWkZGRkofx+XwShu/fv7+Ojo4cHa6KUCjU1dXNy8vz8vJavnw5s8ZTU1NNTEwMDQ3fvn3LrOW6iUgkyszMTPwHEk1PTExMS0srLy+v+ngul2tiYmJqalpQUHD//n1tbe3IyMi6eztDxSE0NJTFYvF4vOjo6KNHjxYWFlbziTk5ObGxseHh4YGBgbq6ugCwefNmmboqXz58+EBO2WbMmFFSUiJvdygKiUgkcnNzAwAejxccHFzpp58/fw4NDfXw8LCysqq4nvD5fFdX16CgoNzcXLm4LS8GDcKiIuzfH69dw5kz5e2NwlJWVjZ9+nRy1R07dgwRY2JiPD09LS0tJddYw4YNnZycAgICPn78KG9/pSUlBceOFX+9bRsePSpXbxSWDx8+kKFdpqamiYmJlX769u3bgIAAZ2fnikqdw+FYWVl5eHiEhoYWFxfLw+vKlJeXczgcAAgICGDcuFAo5PF4LBaroKCAceN1jfnz539N8bLZbCMjIxsbmylTpnh6eh44cODmzZtJSUmlpaWpqakJCQkikWjkyJEA0KFDh+qLzO+Mwgj3vLw8ExMTAPDy8jp37hz5s5aXl9fISHFx8aVLlwCgcePG3/ktWbwYJ08Wf21nJ6tXEYlEhw4daty4MQCoq6sDQPPmzY8dOyYSiWT1kpT6iEgkWrBgwddUeyXi4+P9/Py+cV+sx7vHjx9x6VI8fhwHDcKSEoyMRGtrKtxrSUFBATkhVFNTu3TpUqWfxsfHe3t7W1tbS1LelZWV7e3tvb29MzMz5eKw9JSW4u7dSJbnBw+wiuak/DcfPnzo2rUrALRo0SI1NfUbjxQKhREREQKBwN7enpSBSbaC9vb2AoEgIiJCvvdK0kZGVVX1zp07jBtv3rw5ALx8+ZJxy3UKyQGLhoaGlZWVs7Ozh4eHt7d3UFBQREREfn5+bm5uREREUFCQQCBwc3Nzdna2srJSVVUFgBEjRiDihw8f+Hw+AMybN0/ev82XURjhTip8e/bsmZmZaWBgAABbt26t/tNFItGyZct0dXXT09NJgruPj4/svK3K4sXo4IBXryLKTLi/fv3awcGBXLI2NjZ79uxp3749+bZLly7Xrl2TyatS6h0iES5bthUAVFRULl68WP0nfu2++PTpU9l5Ky9EIjxwAA0MEABNTNDREcn2ZP58nDkTt23DXbvk7aJCkZuba21tTaIqkZGR33hkcnKyt7e3vb29ZKIkh8Oxtrb29vb+tm6rg+TnY8OG6O+PiLhhA1bZrVD+g5wcUY8efYhqT0tLq/4TCwoKJGeGkq1g06ZNZedqdRCJRDNnzgQATU3NiIgIZo2TJvcXLlxg1mxdgxwUEwn+9OnT06dPb926dcGCBU5OTm3atCEC/YsYGBhMmTKFGImOjm7QoAEABAYGyvW3+TKKIdxJHzpVVdXXr187OzsDQO/evYVCYY2MkCe6u7ufPHkSAExMTEpLS2XkcFUWL8Zbt9DWFouLmRfuhYWFnp6eRCrp6Oj4+fmRsIFQKAwKCiJ9oADA3t4+KiqK4deuq4SGhv71119JSUnydkTBEIlw/nzU1xdaWIw8d+5cre18/vz5/PnzCxcutLOzq38HPhER2KsXAiAAdu2K9+5hRoY4blpUhOHhyOEgAK5ejfXuV5cJyck4cuQuAODz+W/evKnmszIzM/38/AYOHCjpG8ZisXr06LF58+b379/L1GGmyM/HIUPQ3h6zs6lwrzEfPmDXrmhl9b5t2641Uu2VSE9PP3jw4OTJk93d3Rl0r3aUl5ePHz8eAPT09J4/f86gZbIl8PX1ZdBmXaOgoEBSmoyIbdu2rSrQVVRUSKmDq6urQCAgkfhPnz5VMuXr60tO/168eCGPX+VbKIBwz8rKIoWku3btOnToEDkBqYUgi46OZrFYqqqq2dnZbdq0Adlkkn2NxYsxOhoPHcJNm9DODk+dwlmz8MkTBixfupRGpDmbzZ49e3bV3OKCggKBQKClpUUe4+zsnJCQwMAL11XKysoEAgHpc6KlpRUTEyNvjxQGkQjnzEEAbNAAr1yhkvMLZGSgqyuy2QiATZpgQMCXpXlAAHK5CIBTpuB3jA8oJDExaGSEDRrgyJGCt2/f1sLChw8fgoKCXFxcSH4gi8VKTk5m3E9ZkJ+Pw4ZheDj+9BMV7jXj/Xvs1AkBsGVLTE+vWRSvjlNaWjpkyBByAsDgzXrTpk0AsHTpUqYMfo3Xr1Ei0Jg+NvgPdu/eTQK75FsSaF+wYMHWrVvPnDkTFRWVl5dXfWsuLi4A0LZt27pWGKAAwp1cwQ4ODqmpqWQvtX///tqZGjRoEACsXbv24MGDAGBhYVHTsH2tIcJdJEInJ7S1xd69xeG63r3x8GGsXQ5wWhq6uCCbjW3aTO/YsePdu3e/8eCcnBwPDw/SjYHH47m5uX348KGWv0wd5tGjRyRBiNQxk23ef2ZpKyjZ2Zifj4goFGJGhrTWRCKcNw8BUFkZz5+X3rv6RmkpenujhgYCIJeLbm5YJUbzL0JDxQ+2t0fFr6IUM2IEhocjIt65gwcPMmDwwQPU1UUAtLPDmtxSv0xBQcGpU6dWrVrFgGey5++/8dMnHDYMEXHGDBw6tD4L96Qk8Rb382cGPg65udili0S1S+9dnaOwsNDOzg4AmjdvXrvdbFX27t1LpBQj1r7BL7+glZU4YCG7ir4vQu7+Rxmq8s7Pzydl8RMnTmTEIFPUdeHu5+dH4qbJycmOjo4AMIysc7Xi7t27JJkkJyeHRKlPnz7NoLdfJDMT37zBXbswPh4RMSYGFy/G16/RwwMbNRLLd3199PCoQWVSaSkKBKiqigCoqYl+frnVrNNNTk52dXUl0WgdHR2BQFBUVFTLX6yOUVhY6OHhQary+Xx+aGhoUVER2TGzWCwPD4/vtkn7bkybhs7OiIh5eTh0qFSmJKq9QQMMDWXEu3pFaChaWoo/rU5OGBdXrWc9eoSNGyMAdumCCls/+S969kQHBywtxZAQFAiktXbuHDZsiAA4fDjW1f4NMiExEQcORADculUs3N+9w0aNMDgYBwyonx9AAwPcuxcR8ehRlDJZo96rdsLHjx9JPV7btm2lTP3Kysry9PTU0NDQ0dFhsVj29vaPHz9mys+q/PILLlmCpHXf9xTut2/fJqnqDLZDiI2NJed4e8nlWzeo08I9ISGB/MmOHTu2fft2ANDV1ZWygYCNjQ0AbNmyZefOnQDQqVMnmSbgFhZi9+6oq4sPH37hp0VFGBAgPu8DQDYb7e0xKAi/LcJv38a2bf9fQ6Sk1NiriIiIfv36kXwvY2NjPz+/mvbnqWvcvn27VatWJBfI1dU1Ozt7165dIpFIJBJJ0macnZ3zSYC6vjBtGk6ejCEh0gp3kQjnzqWqXUxhIR48KI4OPnyI4eE4ZIj449a6NV65UjNrcXFobo4A2K1bZvWzt+ss/frhvn34229i4R4djVlZtTR16JA4m+inn7CsjFEv6zBCIXp7i2Muurp4+DBK2odEROC6dQiASkro7S1XL2VAnz7o4IDv3kkr3HNz0cqq/qt2wrt370hab7du3aomYVeH+Pj42bNnS+YetG/fXlNTk9wof/rpp5RaqIdq8MsvGBmJAwZgUtJ3Fe7jxo0DgDVr1jBr9siRIyQz/ttF89+TuivchUIhOSqaMGFCXFycmpoaAJw4cUJKsxcuXCB7sg8fPhgaGgLAlZreiquNSIQTJiAAmppiejp+o61LRAS6umKDBmJ90Lw5CgT47h0i4rVrSCLFqakYG4uurshiIQCam0t7rhoaGtqpUyfyeW7Tpk1QUJBU5uREXl6em5sbkebt2rV78OBBWFiYhYUFAOzZs4c85sKFCyTFv3379vUpv3/aNHz+HG1s8O1bHDoUt29HZ2dcswaPHsWoKKz+UcqdO8hmY8OG4q5HPzhZWaimJs4DWbkS//wTAVBLCwWCWqa0ZWWhrW1Bu3Y9GjVqFE4STRSWfv1QJEIHB/T3R4EALSwQAA0N0ckJPT0xOBhzcqplZ+tW8Tr2v//J2OO6xOvXaGcnXuSdnb+w5xGJUCAQV1BMmlSvTiH69cPwcJw2TSzcJ0/GadNw82YMDsa4uP+IVVVkzRoEQAsLZCh/pK6TlZVFYlLW1tY1Cjw9e/bMxcWFdF5is9lOTk4PHjxAWSbNxsejmxsuWIC//IKPH+PTpzhhwvcT7hkZGTweT0lJSRatpUhdr7m5eY1S5GWHTIS7CEXPCp9JaWTz5s0A0KRJk6ysrO7duwPATz/9xIh7ZGTM7t27BQIBAPTt25cRs1VZvhwBUEMDnz7FRYuQxcLff//W47Oz0csLTU3FK3uDBvjnn6iqin5+iIg7d+LGjchmY4MG6OmJjIyMEAqFBw8eJA3ySfbb69evGbD7vTh//ryxsTEAcLlcDw+P7OzsWbNmkd5e7dq1e1jhmOP169etW7cGgEaNGtWbzpjTpmFyMgYF4aJFOHQoDhsmvnIk/wwN0d4e3dzQzw9DQ/+VrTFokLhfYVQUrlqFAQHf2lj+UGRlobMz9uuHOTm4ciWGheHOnbWPKxPy8/NJrY6qqup5RS4g6NcPETEqCs3McNMm7NsX1dX/dcmx2di6NU6Zgjt24P37/79Mpabi9OninY+fHx47hioq+McfcvtFvjMkuVFZWfypPHXqWw8OChKH5Hv2rD/ylFw506fjwoW4cyeqqPzrsuFykc9HJyf08MCAAIyIQEk14OfPqKeHsbGIiL//jteu4YoVDJT0KBDJycnkHj1gwIDqzIqKjIx0dnYm90Eul+vi4lK1L0p8fPy4cePIY3R1df38TkmTXfL4MY4dK95wNmyI8+cjycRZsgStrRHxexTor1u3DgDGjBkjC+NFRUWdO3cmqdrS5Gic/mN+kNfMw2snvwiX6i7AmHB/W/p2SuKUsQljXRJdUkpSBr0ZJI2158+fq6iosFiskJAQ8n4YGRkxNYsxKCiIpEHn5OSQaldZDDvYv1+8Hl25gnv2iL+ujjYSCjE0FJ2dkcPBs2exb190cMCsLNy5E48d+/9ceQYpKSnx8/PT09Pj8XjxjFuXDZmZmSR/HQB69er1/PnzkJCQiiK+6gL38ePHYcOGAYCSkpJA+vzcOgAR7ojo5IRDh+KzZxgYiCtX4qhRaGEhzkOoKuX79UMfH+zbFwcPxowMfPQIlyyR929Sl8jKwgkT8OZNdHUVC3dGKC8vd3V1BQAOh+NH9uI15MOHD8+ePbtw4cKSJUt+/fXXz58/M+NZTZBUGP3yizido7wcY2LwwAGcOxe7dUMer7Igs7LC2bMxJAT5fNy0CRHR1RVfvkRFa7leex4/fmxj42RgUM5ioYtLtQ4lnjxBMzNx56L792Xvouwhwj07Gxs3Rh8fvHEDd+9GNzd0cEBj4y+sVBwOmpvjsGF4+TJ264ZDh6JIhOvX1zhXrX7w6tUrMldx1KhR38hrDQsLc3JyIrdFVVVVNze3byfDPHr0qG/fviwWq127cBMT9PPDmhaChYWhk5P49IzHQxcXjI3Fe/fE+QKfPuHff6NAgP371+AEuBbdZBvnAAAgAElEQVSUlZUZGRkBwI0bN2T0EnFxcSTLyFuKPLaAVc7lpSXCslL/RY5F+R+zkl6+CA8pLqhxEhRjwn1k/Miwz2GImFSSlFuWO+jNoHxhfrGoNmHh0tJSEhSfM2fO48ePeTwem81mMEoqFApJpfBff/21evVqABgqZWVfFW7dEt/AfH3x0iVUUkIWC2vafDI+HsvKsH9/vHsXp04VC3fZkZOToyjdV4KCgnR1dQGgYcOGAoEgOzubSCIA6Nmz5zf6P5aXl3t4eJAww8yZMxV6omd+Ph49iuSQMy7uCy0+ysowPh6Dg1EgQFdXtLZGNTXxTXHxYuzXDyMicNIkKtwrQ4Q7Ik6Zgo6OjAl3AjnlAwAPD48vPqCwsDA+Pj40NDQgIEAgELi6ujo5OVlZWZFcr4rw+XwmPfsvhEIcOxbPnv2Ph5WVYUwMBgSgmxtaWYn72QPgmTM4bx4OHowJCWLh/iNQUFCwePFiUjE/fLjvrVs1eG52tjivxtr63PfsXCwLcnPFQ6YQMSQE792r/IDiYoyJwaAg9PREZ2e0shKfTgDg2bM4YgRu3IiHDv24wh0Ro6OjSZxx6tSplYK+QqEwODiYjI8ljdTc3Nwyqn0qcfHiQ0nlfbduePNmtZ4VGvr/syzU1NDN7QtbcZEIs7LQ0FBcgC67UhYSjW3durVMSxaDg4NZLBaXy61mqLekKD8r6eWrB1fuB++9tOd/Mbf/DljlfPu499/bloSd2JERH+O3cEDM7b/LSmq8p2FMuHd80VHydZGwaNCbQbOSZ0EkqEer82P43WO7D4kbMiVxypLUJZsyNu3P3n/27Nk7d+68fPnyHdmaVWDFihXktvTu3bt27doBwKJFi5jyk7Bv3z7yNmdnZ6upqbFYLAaLrF++fG1ungmAS5fi8+eoqSlVKmf//oiIM2bgpEmyFe4KQWJi4sCBA8ny5OjomJSUFBQUpKenJxHx1amyPXr0aMOGDUmovvqrW11j+XJs1gwvX67BU0QiTEjACxfwyRNxAGzuXPztNyrc/4VEuGdmopYWw8IdEXft2kWU3KhRo7Zv375ixQoXF5c+ffq0bNmSzOr7Gurq6paWlgMHDrSxsSGpq7u+43TWAwcQAI2N8cMHfFbtRMjPn/HWLdyyBZ8+xfnzMSYGR478UYT7rVu3WrZsSY743NzcalEZX1qKy5ZlqKtrAMDixYvLFLOGVyTCTp3Qzq5mfRRKSvDZMwwKwpQUHDECi4vRxgbd3X9c4Y6Id+/eJYM/3dzcyP+UlJQEBASQmi4AaNy4saenZy3ysIVCDAjAJk3EQtze/qtDZoRCDA4W1weTAmtPzy8fIpWX4/Tp6OmJz56JG+hNmlTjiH41IfWQPj4+MrFegcWLFwOAsbFxReFaXFwcGxt78eLFXbt2bd284YRglv/iQb9NarvWybDiv7N/LgpY5Zz6MiLu8c39y4anxT6+6Le6dm7IULj/nPQz7zEPIqHqP8Mow4o3JDabra+vb2lpaWNj07dvXzabzeFwwsPDlyxZAgAWFhaFTBfplJaWNmvWDADOnj27aNEiAJhA7tVSk52dzefzmzZtNnNmXFpaVqtW+QA4cWLtBygS4f7uHerp/dDCXSQS+fn5kS5DWlpafn5+aWlpI0aMIJeQnZ1djbLzo6KiyAXQtGnTh1/s+PNNUlJSQkNDd+7cOW/evJ49ezZs2HDw4MHf87b67p04t/j+ffTwwEOHalDdRSDCPTcXW7Sgwv1fEMWAiOXleOECJiTgtGno5MTkS/z99988Ho+c7VZCMtXPxcXFw8PDz88vODg4IiIiNze3qKjozZs3JNhz4sQJ8uDo6GgmPfsKnz+Lb+pHjuCmTcjhiHu9VZ/nz3H+fETEpUuxZct6Ltzz8vJcXV3JyV779u1rscJUxM/Pj4yksLW1zc7OrtFzS0tLY2Njz5w5IxAIpk2bZmZmpqur+53ng548Kc75ycnB8eO/EG7/Np8+4YgRiIhXrqCW1g8t3BExNDSUjEifN2/e77//LllDzMzMvL29pVRK+fm4fr34zqKkhLNm4dKl4thQUhJu3Yq+vuIMLgA0McFt2/Abg4nCw1FJSdzz9MEDsdk5c6Rx8Ms8f/6cxWKpq6t/lP28jNLS0l69epGw7+TJk62trZs0aUI+6QRDPR2JUt8wynTnHNu/PCeF+K4IP+2b+DScpMqIRKJ9S4cmP7svf+E+In7E3fy7iChEYaGwUJLj/rH845viN/fy753LO3fw/cEtmVs80jwWv1w8bNgwa2vrVq1a6ejoVLp1GRsbW1tbI6KPj4+GhoaUq97X2LZtGwB069YtNTWVx+NxOBzp6zKLiorIm2plZZWdnd2lSxcLi85OTunSFJJKKtnu3Klu9+j6x6dPnyTXyfjx48mo84oivhYHZO/evevTpw9RPwe/PkumtLQ0Pj4+ODiY5C1YW1uT163KL7/8It1vWQOWLEEAHDYMY2KQzUZl5Rp3BZXcu4OC8DvGbRWGT59QXR0bNsTCQmzYEFkslK6TciXjn8hV5Ozs/OuvvwYEBFy9evXly5cFBQXFxcXx8fFhYWFBQUECgcDNzc3Z2dna2prP55PWSSwWi9RvkPQwS0vL7zDVb+VKBMAePTAjQzxVqqZtQyXCvaAAmzWrz8L93Llz5AxQRUVl06ZNjOzn79y5Y2BgAADNmzd/9vXzjry8vIiIiKCgIE9PT2dnZysrqy+e4bDZ7JvVzIeQGqEQ27dHANy1C7dsEc80qBGFhf9/Xu3ujnWmI5/cOHnyJFkKCB07djx27BiDDZ3fv0cPD+TxcPx4dHBAe3ssKMCYGJw9W9w5o3lz9PauVs56YCCy2chioZ8fhoeLS66Zzp/AOXPmkJ0Mw3b/TVZW1suXLxExNTVVTU2tSZMmkreAy+U2b968f//+M2bM2LBhw9ObZ1JfRnzO+ULj8vM+HsE73E/+Njvy8uH3afHhp2vZGJUx4Z5amjo+Yfz4hPFj4scklyT/nPRz9Z9bXl6emZkZExNz69atLVu2sFgsVVVVchIhu+Y7RUVFZCm8evXqjBkzAGDmzJnSGBSJRJMnTyZB3JSUlJEjR5J9cJZ0DSni41FdHW1tpbGh8GzevFlZWVlJSenUqVOvXr2ytrYmHxhnZ2dp+vqXlJSQtx4A3NzcysvL379/HxYWtmfPHnd3dycnJ3Nzc5LVUAk9PT1bW9uZM2du2bLlwoULK1asUFJSYrFYx48fZ/C3/hpv34qlZFQUjh6NALhgQW3sCIW4ciWOHSur40tFp2VLBMDHj8Vzji9eZMwyiRr06dMHEc+fP+/q6jpkyJB27dpVjWJURFlZ2czMzMbGhkxjKSoq6tChg/QL13+SkiK+3u7cwWnTEABHjaqlqdhYPHYMnz9n1L86hp2dHYfDMTMzq9rKQxrS0tJIErOamtrp06dFIlFiYuKlS5e8vb1nz57dt29fcjurqtHNzMwcHR0XL17s5+d34cKF0aNHA0CjRo2+T2PcI0cQAJs1w9xc1NdHALxwoTZ23rzBhQtx3Tqm/VNMZs2a1ahRIz09vQsXLsgoqzs2FpOT0cEBz5xBDw+MicG5c/HkSTx1qmb3Cx8fcbOpo0fx/HlxywRvb8amtn/69ElDQwMAvrGhZYTVq1ezWKwNGzbcvHkTALS1tfft23fz5s3k5OTvPwanLvZxJxNS165dK+sX2rRpEwA4OjrGxcUpKSkpKSlt27bt0qVLkZGRKSkpNY1jkTpXdXX1J0+e/PLLLwCgqan5jULJanL/vrhk5EeGTERr2bIlIj558oTL5RoYGJw8eZIR4zt37uRyueSOWPXOp6Sk1KJFi6FDhy5dunTv3r3h4eE5OTl5eXkPHjw4ePDg8uXLSf/7rVu3EgtPnz5lxKtvMH8+AuCYMfj0KbLZqKKCaWm1NEXyH6o/sveHwsVFXF/u7o4AyNSCJBQKmzdvDgBnz55FxPXr11dS54aGhlZWVs7Ozm5ubgKBICgoKCwsLD4+vurtISYmhlRrHD58mBnnvsTYsQiALi74+DGy2cjjYa3PJkmH3I0bGfWvjjFmzBgAmDt3rlAofPTo0alvt36sCQUFBePHjwcADofzxVB6w4YNO3XqNH78+HXr1h0/fjw6OrqoqCgtLe3q1as+Pj7z589/+fKlUCgknUk7duwo67Oa8nJxp/99+3DTJnGDy9oRFYUAaGnJqH+U/8LBAYVCHDkST5zAuXNraWTjRnGDqZAQPHUKraxy1dQMt27dyoiHO3bsAFk29SaUlJSQrj537txxdnYGAE9PT5m+4repi8L91q1bAKCjo1O7UWHVJy8vb+XKlaQ80dzcnDQTrIiKioqhoaGlpaW1tbWTk5Orq6unp6e3t3dAQABJPE1PTy8tLUXEo0ePslgsDodz7ty5vXv3AgCXy73KxDyb8+cRAAcPlt6SAlNWVkZ21WS2wtmzZ5maGUHw9/fncDjKysrKysqWlpbOzs4eHh4BAQERERGFhYW5ublhYWF+fn5ubm729vZ8Pr9iTtvEiROJkenTpwOAqalp1XprBklORmVlZLPxyRN0ckIAlCZDp18/hmPJ9YmdOxEAp07FEycQAAdJ1eH2/zlz5gwAmJmZESH++PHjXbt2nTt3Ljo6uhZXzu7du8mO8dWrV8z492/u3kUWCxs0wORktLVFAPxKO5xqsWMHAtReASgEN27cAIAOHTokJSUBgJaWFoMBOZFINGDAAFKhqK2tbWVl5eLiIhAIgoOD4+PjSZ5Vxbw+smxKOHToECLm5ua2aNGi4tolI0hBs7k55uSgjg4C1H7EW2EhstnI5X6PjuAUCUS4x8dju3ZSfWw9PFBLS9S585wbN27s2bOXxWKx2WxyNUpJ27ZtAYCpKN7XOHz4MPlQv337lsvlKikppdU6WsYEdVG4I2Lv3r0BYMuWLd/n5Q4ePEjCFSNHjhwwYEDHjh2NjIy+3eGhIjo6OiTu5evre+fOHdLwYf/+/Yz4Rta+qVMZMabADB06FABk1BZt3rx5AODq6oqIT548OX78+Lp168aPH9+pUyfyzn4tsrV27drL/zR2KSoq6tatGwDY29vLrlDV1RUBcMIEfPQIWSxUVZVqNtDcuQiAf/7JnH/1iIgI8YzGlBQEQB2d2peYV4Q0QNi2bRsDthARccKECQDQpUsXxtubCoVCR8dRPXse8/QU/f33S2XlYn19lKYA7MwZcW1GPaakpERVVZXFYmVkZJibmwMAg2VaIpGI2Dx9+nRRUdHdu3f37du3bNmyYcOGtWjRgtx6KqGrq9u7d+8ZM2b8/vvvkuydly9fkqbUv397KKAUlJYin48AeOgQrl2LANi7t1QGSYK1bPanlC9DhDsirlsnlXAXiXDZsm0AoK6u/vDhw+3btwMAh8Op9bx2Unv2+++/A0CTJk1I/FR2x92kdtHf39/T0xMAxo4dK6MXqiZ1VLiHhIQAgIGBQZFMu/YjImJqaippj1p1/1dYWJienh4TE0Nqxby9vT09Pd3c3FxcXEhzZUNDQ5Jloaurq6WlRWrLJk2atHLlSqbc+/13aaOq9QNvb28AmDJlCuOWi4qKyAVAGnSYmZlVuvNVjGwFBQXFxMQIv5Ll9/btW1KzIqO+DfHx8S1atOnd++irVzhrlo+eXuaKFVIZ3LYNAXD2bIb8q1+Ulopzu3NysGlTZkTD06dPAUBDQ4PBBgh5eXnkol26dClTNgkkomFsbJyTk2tmZmZi0jwwMFEag48eIQB27syQf3UVku155MiR2bNnA8AmMneKCa5fvw4ARkZG5eXlL1++rCrTDQ0N7e3tXV1dvb29Q0ND33598urZs2fZbDabzb5Qu6zz/8Lf39/KaqCj4+Ps7JyBA315vJLbt6Uy6OiIAPj33wz5R6kepaV47hweOCCtHZFIRA6ltbS0oqKi/ve//wEAj8f7z8svNzeXlFyTcyRy6C3ZoxobG9vb2yPiokWLWCyWLGbRREdHE7fz8vKaNm0KALdqNJFBBtRR4Y6IZAbT7t27ZfoqQqGwX79+ADB8+PDaWRCJRFlZWcTbFStWkP9hsF7EwwMB0MuLKXuKSkxMDNlbM16LQ07BunbtSr6dNWvWyJEjly9ffuDAgfv379c0Jyc8PJz0bjsg/VJXhalTpwLATz/9FBYWBgAGBoY5OVKdHF++jADYpw9TDtY3SFnqpUu4cOFdK6uVhw+fltLglClTQAYNiB4+fMjj8Vgs1rlz55iy+fnzZ7ILPXz48MaNGwGgQ4cOUmZ9ZGQgAOrrM+VjHYUEAn/++WfStbM/6enLBJMmTYJ/8mtLS0u7d+8+adKkDRs2nDhx4tmzZ1XHRX8bEj7U1tZ+8+YNUx4SSkpKTE1NAeD48eMrV64EAGdnFyltLlqEADXuQ0qRkuJicZKS9Alf5eXlpAJEX18/NjbW3d2dHF/fvn0bETMzM+/fv3/06NFNmza5uro6ODi0aNGC3EyrwuFwTExMOnfuTDafly9fJh86LS0txqe/kw4WixcvPnbsGABYWlrKdMxTdai7wv348eMAwOfzZdoe+88//wQAPT09aZqTIOKjR484HA6Px3vOdMeEn39GANyzh1mrCgnZ7DL+FyY7Nwa3iL6+vgCgoqLCbCfT169fKykpcbnc+Ph40shS+gLu5GQEQAMDRhysh/zyC7LZKBAUbN68GQDmSpednZWVpaKiwuFwGL+14D8zWfX09NLT0xkxSPRWjx49MjIySKp0aE17QFZBJEJlZWSxZDv/XO5ERUUBgImJSW5uLofDUVFRYWQUSV5eXsOGDVksFlPXj0gkIkKqdevWzPbAJiWDbdu2zcrKIp1P79W0f3sVdu1CAJw+nREHKTWA9DBISmLAVElJCTmPMjY2TkxMJDF4TU3NL6akSg6RevbsOXHixJUrV+7Zsyc0NDQuLq70n1oHUtyvo6OTmJg4atQoEl9gcPLPhw8fSObbq1evbGxs4PuOvfsadVe4C4XCVq1aAcBff/0lo5d4+fIlSWRnpPCfnIra2NgwuxsbPlw8MJzi4uICAN7e3gzaTEhIYLPZDRo0YLbalfTYNjExkbIZaEVIKrOrq+vVq1dJaEF6n0UiVFNDAMzNZcTH+sbZs+EaGsaDBg0iFfNWVlbSWFuzZg0AjBkzhin3KiISiZycnACgT58+0ldDpqSkEI14586dadOmAcCoWveA/DckU7l+j6QQiUSkB8Xr16+7dOkCAFeYmBvk4+MDAA4ODtKbkvD582dS3jdixAim7lxFRUUkyHLmzBnSYM2JiQFmN24gAPbqJb0lSs2wtkYAZKr1f0FBQe/evTt37pydnZ2fn6+urq6vr09OfiwtLUmiF8lKjYiI+M8OJUKhkOwEevTokZWVxefzpY+wVOSPP/4AgIEDB8bExHy3MU//Sd0V7oi4b98+Egz4WkqxNJSVlZFSwp9/rkHL+W+Ql5dnaGgIX8qVl4aJE3f27r3n7t1kBm0qKMeP37Kx2ePiksqgTdLEk/HU+dLSUltbWwCwtrZmpGQwJiaGzWbzeLzExESy72cqcXbMmDQ7uwcPHyYyYq2ekZKSQsI5+fn55Lij1h30iouLJQ3FmHVSQlZWFlmCNkrdcJG0PHNxcXn8+DG58KSfT0ewsxMZGpaHhX1mxFqdhfRt9PX1Xb58OQB4SNOL5x86d+4MAMeYHqCdkJDQqFEjAPj1118ZMbhlyxayy3379i3Z/jFy9piZKezVK9nRUdpjH0pNmTwZARhIc5eQm5tLRvSQk8w2bdpIE4TKyckheVm//PJLdHQ0icYyIsNEIlHLli0BIDg4eNasWQCwoHYzU5imTgv30tJSMpeeNDxmFpLeZ2pqyuD+KSAggORv5TIXwCTXTWxsLFMGFZf0dGSxUF2dsY5gQqHQxMQEAGQxRzAzM5PMo55PJkZKBxmbsmDBggsXLgCArq4uU81SJ06cCLLJyK8fkNjhq1evOnXqBAC3a1tht2fPHulj9v/J9evXORyOkpJSLbYHnz59ev78+eXLl1etWsVisRo0aJCcnEzOjhgseyWKVnbnqHUE8naPHj06NDSUkff9yZMnZA8pi4YNV65c4XA4bDZb+tq+/Px8EkC9cOHCggULGDyrQUTSRYDBY0xKdVizBgGQ8cblubm5ZOScpDNbrbl//z4p8jl16tSuXbsAQE1NTfqs2osXL5KT8w8fPpCML+kn8zBCnRbu+M+IwW5Mzx+KjIzkcrlsNvvGjRsMmhWJRCRhes6cOUzZJFf2ewbnrSsylpYIgEyFLIkI5vP5Mqo1iYyMJLt/f3//WhtJSUnx9/dns9kqKippaWnz588HRpu4rVu3DgCWL1/OlMF6BsmbDAgIIIO1a/2Xb9++Pch4UhKBhHiNjY2/uGgUFhbGx8eHhoYGBASQLg2SBlmV8krbtWsnFAqFQuH+/fsZnGC9dOlSABAIBEwZrJtImrjn5+c3aNCAzWZLOd6BiGDZBfy8vLwAQF1dvdbSpLS0NDY2liQ09urVq7S01MLCgs1mM9ikr0ePHlAHenr8aOzbhwDIeEe3xYsXA3Ozk8gMRC0trbi4ONIDoE2bNvn5+dLYJMmHAoGACFEGq8ylpK4L96KiIjLJmZFhRhKbbdq0ARn0dkDEV69eKSsrs9ls6WtxELG8vJzNZnM4HFkkCykibm5MzrAkhVkMNmuryqFDhwCAy+VWJ1JLetNWnJ9CdvkA0KRJk5YtW5JC7WvXrjE48pBUgY8YMYIpg/UMSVkq6Y1Yuwz1K1eukDeR8VbrVSkrKyNdh+3s7Hx9fVevXj1lypT+/ftbWFh8owIMABo2bNi6dev+/fuPGDGCjPhZvHgx4+6Rvq515MRZpkiauNvb2wNArVtWI2JJSYmuri4AREVFMehhRUQiETkMadmyZXXyFvLy8kiTPk9PT2dnZysrKxUVFXIhqaqqLly4kLgtfTC1Ij/99BPIvtccpRLXryMA2tgwaTMxMZEopcjISEYMikQici7dvn37d+/eWVpaAsCECRNqbTApKYmMZczMzLSwsACA06el7SrGFHVduCMi6UTG4F5n4cKFANC6dWsGS48rQiJenTt3lr5ELDMzEwD09PQYcawe8PffjK0g79+/V1ZWVlJSYqoLx9dwc3MDAAMDg0qz1t69excWFrZnzx53d/chQ4Y0b96cw+FUlVN6enrdu3cnkmv8+PEMTmEkkCN4CwsLZs3WGyRlqampqfv27Xv58mUtjAwePBgAvGTc1bWoqIh0x0pMTGzQoEGlIDpBRUWFz+dbW1uT8cDe3t6kCCw9Pb3iudONGzeIDmM8NH7y5EkAGDlyJLNm6yCSJu4kmD1r1qxamzp69CjIPs+qsLCQ9DUeOHBgxXVGJBIlJiZeunTpzz//nD17dt++fUk0rRJsNtvMzKxDhw7k63379jHuIflLymI/SfkGiYmorZ1jY/OEQZuk1wKz1WWfPn0iHU1mzZoVGxtLwl57atuSb9myZcRDku1mbGws0w6HNUIBhPvHjx+1tLQAIDw8nPzPtWvXHj58mJSUVItzkGvXrrHZbCUlJWZb9VWkoKCAzEPZsWOHlKZI83JLS0tGHKsHfPqEXC4qKUk1vpFATtYYaXfwbcrKyvr27QsA7dq18/LymjFjhrW1NakGq4SSklKLFi2GDRu2bNmyffv2hYeH5+TkECORkZEkv9PZ2ZnZ5aOoqIjD4XC53FI6TPxLFBQUSFmW+urVKzab3bBhQ1knvO3du1dZWdnLyys1NVVJSYnD4bi4uKxbt+7AgQNXrlx5/vz55881KAk9e/Ysh8NhsVh79+5l0Mn79+9DhbEJ9RhJE/dHjx4BQPPmzWttisTsfX19GXTviyQlJenp6QHAmDFj1q5dS6ZHf3GIuGR69Lp1644fPx4dHS1JvidNllksFuON886cOQMAgwYNYtYs5duUlZUpKSmx2eyaDgr4GlFRUST5M4mRHpMVePLkCblcAwICyHZXRUWlFkH94uJiUqrx4MGDESNGAMCGDRuYdVUaFEC44z8dhSUzkpSVlSsGkAwNDS0tLa2trZ2cnFxdXT09Pb29vQMCAoKDg8PCwuLj4yXH03l5eaTalany+a9Bkqc1NDSkjObevHkTAGxtbZlyrB7QqxcC4Pnz0tohOcdnZNxok4js7OxsPT29ShFQZWVlS0tLZ2dnT09PEvX89hFQREQE0e5jx45lVruTFlq1iyX/CDRv3hwA2rRpM3z48Llz565fv37//v0hISFPnjypzvwHkhw/W/bzacklfeTIERIrmjRpkpQGd+/eDQAcDoeRhrmEtLQ0ADD4AWYHSJq45+fnk0SXhISEWthJTEwkLWsZ7HlQFcmScu3aNQ6HQxyWoK2tbW1tTfr0BQcHx8fHfzt7k4RFGNfuZFismZkZgzYp1YG0bWFqUFf//v2BoVZLVfH39wcAVVXVmJgYUltvbm5e0yqdwMBAAOjSpUtKSoqSkhKPx5Ny1A+zKIZwf//+PemB//Tp0+LiYkdHRysrKxMTk2+nbEqYOnUqsUMGT1pZWX2H4OKwYcNAuhQrRNy+fTswWpVfD/jf/xAApTwsJWG/xo0by/RKSE5O1tXVdXd3FwqFxsbGADBixAhfX99r167VbkcnI+0+aNAgqEsJfHWKw4cPs1isSjqmEtra2lZWVpLAgZ+fX3BwMMk/kaxdL168kKmfly9fBoCmTZvm5eWR85wHDx5Ib5ZMJm/QoEGt2+lUory8nDQG+A7p/nJH0sSdlNPUrkidvAWTJ09m3L2K7Nmzp1WrVseOHXvx4gWJiLm7ux88ePDBgwe1K02WaHcGU9JLS0t5PB6bzWawyIdSHcihMSPjCM6dO0fWTMl5MuMQpdeyZct3796R7K9hw4bVqAVFcXFxYGBgSEgIiRpLHwRhFsUQ7vhPonDPnj2PHz9+/fr1p0+fvn37tqSkpLCwMKilgSoAACAASURBVCUl5fHjx5cuXfrrr7+2bdu2Zs2aOXPmjB492s7Ork2bNgYGBmRjd/bsWQBo2LDh92mtmJycTAq8alRWKxQKY2Ji/Pz8XFxcSKfCZs2amZmZyTTWUseRRHZEIhSJ8Plz3LcPU6Vr5j5z5kxgtMndF1m7di0ATJw4kYxMMjU1lb7I+O7du2SMJSPaXSQSBQcHGxgYGBoatm7dWtbiUuG4fv06Od9bu3ZteHj4qVOntm/fvnLlyqlTpw4YMKBNmzZfTHmqiJKSEgDY2NggYmpq6rRp06RsdPA1yO7Ly8uLjOnp3bs3U5bJ2qupqRkdHS29tejoaJJ7eunSJemt1XEkTdx3796toqKyfv36mloQCoXklJjZBmhV6d69OwAEBgaSkUnSZORLIMNrmNLunz9/FggEysrKhoaGkydPrgtzcH4cyIhTPz8/Ke2Ul5eTgV9bt25lxLEvUlhYSGotxo8fHxcXp6mpCbWqaZb0Nr17964s/Kw1CiPcr127pqamxuPxKt0XJaky9vb2Li4ubm5uklSZ0NDQmJiY9PT08vLy+Ph4Mv1E+rzz6kMqaVq0aPHtzrslJSV37tzx8vIaMmQIucIkNG7cmCgDGxubHzPGkJeHkoTGAwfQ3x83bEA7OySb59rlEOXn5xPtK1OdKhKJSArK1atXSSHOunXrGLEs0e7jxo2rtXYXiUQnT54kaygAEIMqKipeXl51pwRHvjx9+pRU1yxbtuwbDysuLk5PT4+IiAgODvbz8/P09KzYY5EM2+Pz+QUFBSRq9dNPPzHuqiSN/t27d6QBwsmTJ5kyLhQKyTymJk2aJCYm1tpOWFiYk5MTi8UiIXwVFZUdO3bIqBNrHUHSxD0/P792vRAuXboEAGZmZjL9Q5EUFE1NzY8fP5LCU6ZqwIh2Z7PZBw8erLWRz58/e3l5STbJZDNsYmJy4cIFRpyk/Cfr168HgBUrVkhph8w3MDU1ZSpd/mu8evWK3NR27959+vTpIUOG/GeJUWFh4YsXL0JCQnx8fNzd3UePHk0uuSZNmsjU1VqgGMK9tLSUTD9p27btmDFj+vTp07ZtWwMDAy6X++1wF4GMlgAAa2vr73mfKCsrI1mnVVPq8/Pzw8LCBAKBvb19pdIfQ0NDZ2dnb2/viIgIkUiUkpJC0svs7e1lMXqjjvNF4T54MJL5LbUT7gcOHCAXA2NefglyzzY1Nc3JySGNnBksxLl79y4JW9ZOu4eGhpIDRHL/8/b2zsrKcnV1JaKqffv2ERERTLmqoKSmppL5WePHj5fmnCQ3N5csAjNmzHj9+jV51wIDAxl0Ff9pYDJnzhxyDN2sWTNmd18lJSUODg4AYG5uXtPxN8XFxfv376+4RXRzc5s2bRr5dsCAARkZGQy6WqcoKioin/2rV6/WbjYk2TJJPwr325CO2nPmzDl16hS5zzJonAxSrZ12Lygo8Pb2ljSxsba2vnr1akxMDDkfAABnZ2cpG+RTqgPJ+R4/frw0RgoLC0nK6NGjR5ly7BscO3YMAJSVlSvdzkjb5bCwsKCgINJ52d7ens/nE5VYVT3K9HCgdiiGcF+1ahWJOlSdFllYWJienh4TE0NGinh7e3t6erq5uTk7O1tbW1taWhoaGpIuezo6Ovfv3//Ont++fZvMIIyPj//48WNoaKiHh4e1tXWlowM+n+/i4uLn51cpoJWZmfnnn3++efOG1DUOHz78R4uG5uWhiQnOmoWzZmGfPmLhfvEi2tpibi7a2qKXFzZsiAYG2KIFWllh//44YgS6uODcubh+vb9AIPDx8QkMDDx79uy1a9ciIiLevHlDpniQbmUFBQUySnMnTZHXr1+/Y8cOABg4cCCz9sPDw4kKrFGPyNDQUJJ3CwDGxsbe3t5kN/j48eOoqKhbt261aNECAJSUlDw8PGQdFKmzvH//nsSt+/btK/0fISYmhlTjHD58eO/evQCgpqbGYMJebm6uJI2eVH398ccfTBmX8PHjx86dOwNA165dq9md5uPHj97e3mT/AwAGBgaenp4k66+goOD06dMkoKWvrx8SEsK4w3UE0qRFgqamppGRUevWrbt162Zvbz9mzJjp06cvXLhw9erVmzdv9vPzO3r06Pnz52/fvh0VFRUZGUl6Xaf8H3tnHldz9sbx595btz3tC0JZ2khEpJBkaWFIWcsyY7LNZBeGKQyTGZLBmMZathZCdi1S1oSSUkypUNoX2u6t+/z+OP2uOxVD3dvmvF/98b3f5Zzz7Z57zuec85znycpCRCGGwRKkurqaFPLBgwfEb6mPj49ws+Brdz8/v88vla+vL39Dv5mZGT+q6/nz5/Py8nx9fWVlZQFAXV29OT7yKZ/DrVu3AGDIkCHNSWTLli0AMGDAgBaLS0McA8jIyMyePXvOnDkjRozo1q1bo26XAYDNZvfu3Xvs2LGurq6//vrrqVOnrl+/npaW1jJF/SLagXCPi4sjm5maHC+Ny+UmJCS0lrc7EsSrU6dOZDqTICYmNmTIkJUrV54/f/5jKzhcLpcEitq8efOTJ09IJ+fs7PxVBWMqKcGxY7GsDMvKcP/+OuEeEYFhYfjjjzhiBK5bhwCN/2lpjWj09yktLS0hIVFaWvrq1atBgwb98MMPQi92YWGhpKQkk8nMzMwki0WBgYFCz+WLtHtYWJipqSn5D6ipqXl5efEXcKqrq/v27UvEemFhoZubG5l7GDx46N27HdmSoVEqKnDu3CgAMDY2FpYdra+vL9Hrqamps2bNAgATExNh7c4kJnm2traJiYnEMkdECi8vL69Pnz4AMHr06E+PZ9LT093c3MgmHwDo37+/n58fvwXOysrS1NT08vLKyMgYOXIkADAYDDc3tw45UIyLi1NTU1NSUiIL91+KlJSUsbExIl65ckVZWfnChQtCLyHxrN+vX7/Xr1+zWCw2m52Xlyf0XH7//XcAYLFY/6ndiWTv3Lkz+Q8MGTKEL9kR8dmzZ5KSkmpqan5+fi9evCD1BwAWL97Ultx+dDRevHhBpK2zs/OOHTvCw8O/dGtpXl4e+QkIMZjmf1JVVdWoXwHiToDEsvD19Q0LC0tLSxN6jBTR0daFe3l5Oekq2m9I9pSUFAUFBSkpKWlpaXNzc3d399DQ0M9cNg0JCSH2fL///vv9+/eJSlu2bG2Htgv9F42aykREICI6O6OxMSLiu3eYnY0pKfjgAYaF4ZkzePQo7tmDv/22z93dfeHChbNmzZowYYKlpaWJiYmOjg7ZbrJx48aHDx8SO6Umx2j4GMQd0Pjx40l4I2VlZRGJklu3bpFaMXfu3I+N6GJiYvjdm6qqqpeXVz1z24qKimXLlhGxrq+vf+fOnTt37ujr6w8f/heTia6u+CXuv9s3NTX4zTcIgJMmPc7OzhZiymSfw6BBgwoLC0mbtmLFiuYny+Vyyerz9evXyQYyErRSRKSlpRG7hRkzZjRa3+Li4lxcXEirBQDm5uahoaH1DBTJ/CsA2Nvb5+TkbNmyhdw/bdr11FTRlb1NUFxcnJmZ+fTp07t3716/fj0oKOjgwYPe3t6bNm1atWqVq6vr1KlTbWxszM3NjYyMunXrJiUlReIuk0CEcnJySUlJwi0S2da8e/dukoWTk5Nw0+fD1+7+/v6N3kAkO3+JxsjIKCgoqF7lSU9PJ3tFAMDBwSE7O9vX11dFRVVHJ1lBAX198evpHFuM2tpaBweHhpYkmpqa9vb27u7ufn5+T58+/bQd8pIlS6BFAqfUIyUlxcXFZfLkyQcPHgwPD09LS+sAEUvaunBfvHgxABgYGLRf824S9H748OFNm2Dz8/NjMpkMBsPX1/fWrVu9eun36PFclF1z26K8HPlxDyIj63R5YiIi4ps3TXQKGR4eLiYmxmAwAgMDybdDukahFRrR2NgYAIKDg0lrJVIt9QntHhMTw+/kVFRUvLy8PrHF+e7duyRMNIPBcHV1LSgoWL+eJyaGANizJ0ZGiu4N2hA//IAAqKyMQndqX1JSQuKyrV69+sGDB2w2m8FgnD9/vpnJnjx5EgAMDQ1zc3PJIs8///wjlAJ/jISEBLJnd8mSJfyTtbW1oaGh5ubmpLKx2WwXF5dE8kNtjHp2Mnfv3p08eTMAysqiCAJutmNWr15NRv5paWnTpk0DAF1d3aaZyzeK4Cx7r169QMTefn777bdGtTuHw/Hz8yO7+cn0f0PJzofH4/n5+SkpKQGAgoKCr69vZma5jU3dQquNDWZlie4NvkaIo6FOnTqdPHnS19d34cKFQ4cO5a+n8VFQULC0tFy2bNnRo0fj4+MF9XFaWhqbzWaxWJ9oEyifT5sW7iWRkX2UldlstlDckLUWpLXds2fP7du3mxa/YO/evQDAZDJPnjx55UoNm40A+OWOxSgfIL4OZGVlExMTf/zxRwDQ0NB4/fq1UBKPi4sjfW1JSQlxuy7qCszX7vPmzSPa/datW8TcmZTEw8Pjc6w+qqqqfvrpJ7LnW1dXLyKiOiEBBw1CAGQw0MUFReZ4t02weTMCoJQU3rolkvRjY2OJXg8NDSWzj6qqqs2M0UZ26R04cID4Hp00aZKwSvsJbty4ISkpCQDE4MrPz49sCSC9u5ub2+f8lF69emVpaQn/t5PJz69yda3TXg4OHbymfT61tbXE7tzY2LigoIBsMxg3bpywlvWJ2fG0adNu3LgBAF27dhW1wQBfu5Mt2kSykzEDGYJ+QrIL8urVKzs7O/KUs/MPGRkYFIQqKgiA0tLo5YVfk0mpCCF+YMTFxYmJy19//XXo0KGHDx9WVFQ8e/bs1KlT7u7uY8eOJevYgrDZ7IEDB3777bd//PEH+aXPnz+/td+mg9CGhXtREXbtWquufrUFHTgKHS6XS2an0tPTia1zVFRUE9LZtm0bACgrq1y6VBoSgmQe9PffhV7erwji16JHjx45OTlkWnro0KFCMWghy0TLli07ceIEtFR095iYGLJVy87Ojt+fKSkpeXh4fKnF85MnTwYNGmRpuZmI9dxc9PJCCQkEQE1NPHsWS0vrOkUuF5vk464tcuwYMhjIYqHwgoQ2gpeXF9Hrr1+/njBhAgCMHDmyyVKJ7BhTVVUtLi4mFixNa16aQFBQEFkJJLUOAHr16rVv374v8lpbU1Pzyy+/iImJsVgsB4f7KSkYFISKimSDCjZ1T1NHo6ioiOjaWbNmZWRkkI2kGzZsaH7KPB6PRAW+fv26s7MzAPz888/NT/Y/4Wv3H3/8keyGJ+vqfn5+X/pbCAoKUldX79fvNhHr2dno4lI3/DM3x+Rk5M9XVFTgV+bZQQhcvXqVrE7zPQJ16dKFfF9iYmIGBgYuLi4kmG5eXl5RUVFMTIyPj4+Li4uBgYGgaY28vLyEhEQzJykofNqwcJ85EwFw2DBsPzsGGhIZGQkAffv2ffPmDenkmiwNPTy26uvHSUpieDj6+yOTiQwGNjsewtdLZWXl4MGDAcDa2jo3N5es0s6ePbv5yfJn2a2srKBJcR+axo0bN6SlpckGIDk5OXd39yYvqXO53F9/5UhKIgB26YIXLmBSEg4digA4dCj27183aLxxAz08hPgGrcalS3WDYVHPEvB4PHt7ewCwtLTMyckhO/Aauov9TEg8zo0bNxIPpwMGDBBuaT/N1q1b1dTUWCyWiYlJEyQXn7t37zo47AVAGRk8eBAzMtDCAgGQxUJ3d2z/9qhC4NmzZ+R3vXPnTkFLv2YmGxERAQBaWlqFhYXS0tIMBkPUdlZ8Nm3aBADE3EJPT6859Sc3t2Lq1DqxPnw4Pn+OZ86ghgYC4MqVKC6OZL1zzRq8e1eYr9Dhefr0KQkswx/O1dbWenl5TZs2TVdXt6HJu46OjoODw+bNm0NDQ7OyssrKymJiYvbs2ePs7EzMsb7mOJLCpa0K95AQJA358+etXZRmQYzD1q5du3//fgCYMmVKc1JbsaJuHTA6GvfuRQBkMvHkSWEV9qvjzZs3xN3Y6tWr4+PjSS+yb9++5qR5/PhxADA1NU1PT2cymVJSUkI0SP1PXF1dAcDCwkIomb54gZaWdT2ikxPm5OCuXZiUhFZWOGECZmZ2HOFOZumEMYn53+Tm5pJat3Xr1qioKBaLxWKxIr98D0FGRoaYmJi4uPjr16/JnorP97UnFEg84GZ6iCOUlaGgnUxuLv70E7JYqKWFc+fiTz8hIubnY7OH1e2Yc+fOMRgMFot1+fJlb29vYun35MmT5qQ5c+ZMAPD09Pzzzz/JFIawSvs5kB01P/30k1CMcy5cwK5dEQAlJdHDA9++xfXrMSMDx43DceOwtpYK9y/jzRu0tp4BADNnzmzUcun9+/d37tz5888/v//++8GDBxPbOUGUlZWtra1PnDiBiNbW1gBw8ODBFn+PjkmbFO65uaimhgDYUlOVokNXVxcASMhAADh8+HBzUuPxcP58BMBOnTAuDrdtQwCUkMBXr4RV3q+O27dvE5/6R44cOX36NIPBEBcXb050cWJ14+vru2HDBqFM4X8RJMT6tm3bXrx4ERMT0/zQNrW16OODMjIIgGpqdduCrazwyROcMqWtC/fqaly1qu44IgLPnftwKTUVp06tm8399VfMzsbjx1vOH0VkZCSLxRITE7t169b69euJbfF/Bvarx5o1awDA2dmZLOupqam18A5+srF75syZd+/edXNzCwkJaWaCgnYyUVEYFYW3buGsWTh2LCYmYl4eNm/eo92zceNGYv/2zz//EA9CPXr0aHL4oZKSEmlpaRIYjoRjO9myk0AkKP3jx4/v3r1779695ocGLyrCefOQwahbGORw8M0bdHHBnTvxr7+ocP8C3r3DgQNRQqJqzpytn2kjQOLTh4aGenh42Nvbk0D1APDbb78h4qFDhwBg9OjRIi7410KbFO52dgiAY8a0d8dO//zzD2lny8rKSBPZfCFVU4PTpiEAqqpiUhJu3IinTuGuXXjnDiLimzd44oQQSv5VsW/fPgCQlJR88OAB34dDenp6E5Liz7IXFhZ269atJW2OCcS8fu/evUuXLgUAYYV8e/kSx4zB/v3rlK6VFSLiihXo7t6mhXtFRV1REfHEiX+ZwTx4gLq6uH07IqKzM2ZmtnTZyBBLS0srNzeXOGOxt7f/orjORUVF27dvj4+PnzhxYnPsbZoMsddftWqVj48P/NvJTJNJS6uzyGKxkLh7njULY2Nx3DjMzf3ahTuPx5syZQoA6Ovr5+bmkrAM1tbWTYvKR3wejBkz5smTJwCgoKBQ0bIbVoiTpbS0NGLmLqyQZFFR2KsXrl6NiHXCnctFS0ucP58K98+itrbOJa6ODjbHoX9mZub58+eJ8VVpaSnxeSUsDxBfOY2EeG1l/v4bLl0CBQU4fBgEIha1R0JDQwHA1tb25s2bFRUVgwcP5odubjIsFvj7g60t5OfDxImwcSNMnw6XL8PPPwOHA8XFcOuWMIr+NbF48eLvv/++qqpqypQpK1assLW1LSwsdHBwqKio+NKkDh8+zOPxnJycYmNjs7KydHR0RoxoPAiUiCgrKwMAeXl5/oFQku3RA65dg7AwEBf/cNLTE06fFkryIiQ/H0JCICQEHjyof+mbbyAqCjIzW6NYAFu2bBk2bNirV68WLVp04sQJRUXFy5cvx8bGfn4KioqKa9asYTKZFy9elJCQ+P7770VX2kbJyckBAE1NTf5B89PU0YGYGPDwgMGDgf/T0dICS0vw929+8u0bBoNx5MgRQ0PDZ8+eLVy48OzZs507dw4PD1+3bl0TUjt8+DAAfPfddySar7OzMwlq0WLw26h3796B8BqrkSPh8WPYtOnDGTEx2LIFTpwQSvIdn2XL4Px5UFaGK1fg32F/v4xu3bpNnDiR7H6Wl5e3sbHh8XjBwcFCK+hXTNsT7mZm0L8//PUX/D8KQ/vl0qVLAGBnZ8c/EEqybDacPg12duDr+0FIzZ0Lv/0mlOS/Rvbt2zd8+PCsrCwnJ6fDhw/36tUrPj6e2It/EXJycurq6t9++y1ZGZw/fz6jZQefpC+Uk5MTbl8IAAzGh0acVGQ5OfjzTzAxEVYOogIREBs5z2DAb7/BqlUtXiAAABATEwsICFBSUgoJCbl8+bK/v39YWBjx7fgxqqurX758GRMTc/Lkyd9//33p0qUODg6DBw/m8XijR4/mr023GNnZ2SAg3PmhLpuJmBh4ekJMzL9GiStWQEiIUJJv38jJyYWEhCgoKJw9e/bo0aPBwcFsNnvHjh1Hjx79onQqKyt79+7duXNnW1tbEgqA2N60JKSNkpOTE+4sAwDIygIZg0hLA4ljYWEBv/wCLf4TaX/s3g179gCbDcHB0KePMFMmEehOnTolzES/Wlphln/v3g8r02RBq7ISPT1x5kxcuBCzsjqGH4HS0lIScaCwsLB79+4A8OjRIxHlNWYM1tSgjQ1euICLFokokw5OTk4Oidj3448/Cvpw+NJ0OBxOfn6+hISEmJhYy3u/Iu5yIyIixo4dC6KMpeLkhOPHYxuPMf5pUxl3d0TElStRW7sVTGUIJNq8pKQkv3Goqqp68+ZNXFxcUFCQj4+Pu7u7k5OTubm5jo4Oi8VqtA2XkZG5du1ayxfewsICAKKiosjOMxFVtm3b6ny6R0Xhpk2iyKH9ce3aNRaLxWQyL1y4QPaVSkpKxsbGfmk61dXVAQEBADBw4EBRlPMTkPVMCQkJLpcLACwW64vsxD6fjAwcORJdXUWRdkfj0iVksZDBwGPHhJ94ZWUl8VHzvJ17HGkLtIZw//575EfPMjNDRPzhhzrT7NRUNDNr1/4f+QQFBQGApaXl48ePAUBTU1NEDRMijhmDtbWYlIQDB1Lh3nQePnxIFosPHDgQEhLCYDDExMQSEhI+P4XXr1+Hh4cTbwmtshGHxGd58ODB0KFDAeAO2fogAlRVEQBzc0WUvHCorEQ7u7rjwED86y988gS9vPDHH/HxY/T0REQsK0Nd3dbc3r1gwQIiXPT09FRUVD4xySIuLt69e3dzc/Pp06evWLHCx8fn9OnTp0+fbi3vyMSD6vPnz0mFb6aHk0+wdCkuW4bUlZwgW7duBQA5ObmkpCRiJdWrV6/Pj+XO5XJTU1NPnjxJwozs2rVLpKVtyNu3bwFAVVW1sLAQABQVFUWUUWwsAqCJiYiS7zjweGhqigAous0ys2fPBoDNNHhksxFr8lR9s7hzB968AQDgcgEA7t2DPXsAAPr0gV69IDUVDAxap2DCg28ec/HiRQCYMGGCqK0mDAzA2hrevRNpJh2ZgQMH+vr6zp49+4cffrh586anp6esrKyRkVGjN3O53FevXiUlJSUnJ6enpyclJSUmJpI1XwI//HtLIiIb98YyAgAQWfLCQVISLl6sO546te6gXz9YuRKMjcHYGABATg5SUlqneITt27cHBASUlpampKQAAJvNVlZW7ty5s46OjqampuBB9+7dPzbp3irwTdv5NjMiyujgQSgvh82bRZR8u2TdunVPnjwJDAx0cHCIiYkpKChYsWKFuKB1kQClpaX//PMPaaZIe5WcnFxZWUmuiomJffPNNy1YdoAGLRUJ/CyajADafEvVWqSkwM2bsGABAMDhw3D5Mvj7w/LlospuxowZ/v7+J0+eJP6RKE2mlYR7YSEQr588Xv1LUlLw/wal/cLj8a5evQoA9vb2JEKnsAzcG+Xbb+HOHTAzg61bgcMRXT4dHxcXl9jY2L17906aNCkuLo4fJa6wsDA1NfXZs2epqakpKSnPnj3LyMioqamp97iKioqenp6YmJiNjQ3x1tfCtIxwr66G6mpgs6GB6952wPnzYGXV2oUQoFOnTm/fvj169Kiurq6BgUHLm6o3jeLi4srKSnl5eRaLVVJSQsYbosiotBTKy0FWFkQm7dolZKPqixcvHj165OLicunSJTKoQ8SsrCzSTKWkpJBWiwyx6j3eo0cPXV3dkpISb29v4uClJaFTDG2BtDTYsAEMDcHCAgIDwcVFhKodAKytrdXV1VNSUuLj40noCUrTaCXhPmEC9O0LAPDXXwAAmprw4gX07g01NfDkCejptU6phMf9+/dJME5lZeXY2FhJScnRo0eLLru1ayEzEx4+hIEDQayVvtIOg7e3d2Ji4s2bNw0NDceOHfv27duUlJT8/Px6t7FYrF69eunp6enp6enq6urr6+vp6YlIu3w+LdMdkr6wPQqpGzfg0iUYNAg4HGCzW7s0/0dSUnLhwoWtXYovg8yyd+7cmX8gohXF7GwAACFtfO1QSElJBQcHm5qaXrt2TUtLy9LSMjU1NTU1tby8vOGdurq6urq6enp6+vr65LiFfcjUgwr3NsKiRbBxI1y/3hJ5iYmJTZky5c8//zx16hQV7s2hNVQeg/HBzyM52LEDli0DTU14/Rrc3UFGphVKJVSInczEiRMvXbrE4/GsrKxkRPZSCQmQmQmamjBggIhy+LoQFxc/c+ZM165dS0tL+b6rJCQkevbsaWhoqKOjY2BgYGhoqK+vLy0t3bpFrQeHw6mqqhITE5OUlHz//j2DwZCVlRVFRu23Lxw1qs7LBKWZ1BPuorOTIcJdZMm3b3R0dPbv3z9t2rScnBy+vw5FRUV+M0UO9PT02pSRFVDh3mZQUAAXF9i1q4WymzFjBhHuv/76K5PZ9rwathNaQ7j7+n44vn0bAKBPH7h0CSoqoI0poSZD7Nrt7Ox8fX1BxHYyxIp3woT27vW+DaGsrBwXF7d9+3ZVVVUbGxs9Pb2u7cE5Kb8LfP/+PY/Hk5OTE1FvTftCioh8QTaEWHnQGfeP4eTkJCsru2/fvjFjxgwdOlRXV5fsN23jUOHedpg3D2xsIDe3JfIyNzfv0aNHRkbG7du3hw8f3hJZdkTakl1FR1Htr169evLkiays7NChQx0dHQHA1tZWdNldugTwf9faFGFhaGjo394ivvB9t9O+kCJq+HqdP/Uuooyoqcx/5Y2A4AAAIABJREFUYmNjY2Nj09ql+DJarLEi3hrao11fi8FgwO+/w8CBAAAVFXDlCjg4iGoekMFgTJs2bfv27adOnaLCvcnQpQohU1VV5ePjg4jjxo0rKyszMzMbPHhwjx49RJRdfj7ExoKERNvab0dpFVpsEovDyRg58l7fvq3qjYXSqogibOpHMgKgpjIdDhGFTW2IpOTDkSMfampmiSj9do2FBcyaBQCgpwd79kBFBQwaBI6OcOeOCDMlkZgCAwM51JNGU6HCXQi8f/8+PDzc09NzzJgxioqK3t7eXbt2LSws1NTUvHLlyr1790SX9eXLUFsLo0eDaIyZKe2JFhPueXm3b940Kymh/vm+XhpuThVRRkxm4tChb7p1KxFR+pRWgR82lX8goozS0nxu3hzEYt0UUfrtmk6d6qLJTp0KixZBSAjY2wMAiDS8af/+/fv27VtUVBQeHi7CbDo0VLg3kdxcuHChYOnSpQMHDlRQUBgzZsymTZvCw8M5HI6urm5+fn5UVNSqVasAQKQ7MKidDIVPC5qNijZ9StuHb+Mu6s2pDx4suXevq6pqvIjSp7QKtLFqUxAJceoUzJgBABAUBA18HQuT6dOnA8ApkY4POjRfr3BPS4PQ0Lrjs2chI+PDpeho+PvvuuOdOz+cz86G4GBYuhQGDQJNTZg7V2nPnr2PHz9mMBgmJiZubm5BQUH5+fkpKSkXL16UkJDw9vb29PQU3StwudzS0rMDBpRQ4U4B2hdSWhC+jbuoN6eKekaf0irQxqpN4egIEhIQGQnq6mBgAPn5IIrZ8Orq6vv37wPAjBkzGAxGSEhIcXGx8LP5CmhLm1NbluxsuH0bJk4EAIiJAU1N4BuiJyfD1q0wdCgYGcGFC2BoCP7+EB1dF+yVICsLJiZMa2vfIUN6m5qa1vOJa21tHRAQ4OTktGnTJmlpaRHF4omOjr5+3cHIyKh79wRRpE9pX7RYXyjq1W1KGwcR+abtxGu4KG3cRTswoLQKVLi3KRQUYPx4OH8egoNh2jTw8IBTp2D8eGFmgYjz588PCgry8/ObNm2ahoZGbW2tqqqqrq6uiYmJoaGhgYGBmZmZioqKMHPtoHy9wh0AioogNRUAoOGob+VKWL0arlwBAEhOrjP5kpcHU1OwtgZzczA1JQFc5n8s8UmTJh05cmTOnDlr166Vl5cXRYAV4i3enlilUb56+F3UiBEjjh07Jrot0bQv/MpJTU2tqqqSk5OTkZHJzMysqKgQUUyDkpKSiooKWVlZEUUkoLQW/DbEzc3NxsZmyJAhIs2IzjL8JzNmwPnzcOoUnDgBnp5w9iz89RcIMUiXp6fn8ePH5eTk9PT0fvrpp5ycHFlZWURMTk5OTk4m9zAYDG1tbROTQUZGp4yNmcbGUM8PMyKcPQuTJwODAc+fg6wsFBSAjk7dHr/bt8HcXGgFbst8vaYyAJCSAoGBEBhYJ98F6dwZrK3h8GEAgIkTYf9+SEqCkhIICwN3d7Cw+Kywi87Oznv37gWAJUuWnD4t/M0xfG/xQk+Z0u5ISEjw8/OTkpKKiYnR0NBwdna2sLAQYvqRkZFWVlbp6elAhftXzIsXL/gbeyoqKmbPnv3+/XvRRSIjdjJdunQRUfqUlgcRz5w5Ex8fz2azIyMjzc3N582b1717d2Glz+FwfH197e3teTwe0Mbqs5kwAWRl4f594PFgyBDU1S0ICxPaxpKAgIAtW7awWKzjx48/fvz4119/FRcXDwkJKS0tjYuL8/Pzc3NzMzc3l5KSSk9Pf/To6caNzAkTQEsLFBXBwgKWLgV/f3j4EKqqYObMOmF24QI8eAB790JmZl0uq1cLq7xtHvxaiY7GNWvqjpcvx7t3P1zavx8DA5HDQSsrNDFpbka7du0aPHiTjAwGBTU3KUFSUlIAQFlZuaamRpjpUtobiYmJU6ZMIQHnycRk9+7dr127Jqz0b968OXLkSNJcLF68GBEnT54MAKdPnxZWFpS2T0REhK2tLalmTCbT1NRUUlISAPr06RMXFyfEjGJiYpycnDw9PRExLCwMACwtLYWYPqW14PF4586d69+/P2lMiNuG0aNHp6enCyV9Dodz8OBB/krjhQsXEJHU0vLycqFk0bFxdkYA/OUX9PHZCwCTJ08WSrLR0dESEhIAsHfv3qioKDabDQB//vlnwzu5XG5iYmJwcMyKFWhlhUpKCPCvvz/+QCsrtLbG/HzcsQPPncPvv8enT+seNzMTSnnbAVS4I/5fuF+7ht7eePRonXAn96irCyGvjRt5ACghgdevNzGFtLQ0Pz8/V1dXAwODR48eIeKOHTsAYPbs2UIoH6V9kpyc7OLiQsKjSkhIuLq6RkZGmpqakn7LycmpoKCgOenfuXOHb4ilpKTk4eGRn59P5vXl5eUDAgKE9SKUNguHwwkKCuJbMkhKSrq4uDx79gwRnz17ZmxsDABiYmIeHh61tbXNyYjL5QYEBAwePJhkpKWlVVNTQ4KgzZw5U0hvQ2k1wsLCBL9cHx+fEydOqKmpAYCUlJSXl1dzZqBqa2uDgoJ69+5N0jcwMPDz83v79u3GjRvFxMQUFRWF+CIdmMuXa4YMyXFw+Cs7O5vFYklISBQXFzczzdTUDCUlJQBYsWJFcnKyoqIiAKxdu/YzH8/IwHPn0NMTJ03CHj0wOhrHjMFbt3DevA/C3d4eZ83CWbOwb99mFrbd8PUK96oq5NfJoiKsrkYuFxFx+XIsLcX37+suvXolnOxWrUIAlJbGmzc/6/6aGoyPf7V7925HR0cNDQ3BRZI//vgDEUeNGgUAgWSEQfnKeP48fdasWWTKSlJS0s3NLTs7m1yqra319fWVkZEBAHV19eDg4Cakf+8ezpjxPalvCgoKmzdvLiwsPHz4sLa2NjnZr1+/6upqob4TpW1RVoY+PmhiUi0uLg0AampqHh4e9YaCVVVV7u7upB5aWVm9fv26CRm9e/fO19e3T58+pGqpqqq6u7tnZ2fHxMTo6OhISEhQ4d6uuXo1nD+b0Llz5z179lRVVZFLRUVFrq6u5JKZmVlycvKXJl5TgydPvtfV1SWJ6Ovrnzp1Ki8vb926dWT5kcFgzJs3T9jv1DHhcrlkKBUfH29lZQUAhw8fbk6CBQWop4cjRgTb2dm9ffu2V69eAODo6NjkQX5NDY4Zg4j47bc4dSqdcacgImJQEIaHiyRlHg9dXREA5eXxwYPG7+FyMS4OfXzQyQmVlNDE5CpfrKurq9vb23t5ecXExJSVlZ0/f57FYomLizd/QExpX7x8ia6u2L9/KQCw2WxXV9dG1dLz589HjBhBKs+MGXNzcz83/YQEdHJCBgMtLA7Jysq6u7sXFBQEBQXxdZW+vr6fnx810OrAZGTg8uUoJ1e3PO3kdOLw4cN8sdWQS5cukf6+Sxedixe/YDj3+jWuWYPjx3uQqqWnp+fr61tSUnLo0CFDQ0O+1EtISBDGa1FampgYtLRES8twMh7z8vKqqKhoeNuFCxfINgZJScldu06RGbT/pLYWg4JQTw8BcOhQR21tbV9f3+LiYi8vr06dOpHKY21t/eBj3S2lMRYtWgQA7u7uBw4cAIAxRCY3icpKHDYMAXDwYMzP5zg4FKqrDzAzM2u0DnwmfOGel4fKyo0L9ytX0Nsby8qanEk7gAr3D+zahd98g76+okq/thZnzEAAVFH5UNUI27bhyJEoJfUvc66+fcvmzJlz8ODB1NTUd+/ehYWFeXh4WFtbE6M9aWlpc3NzUZWV0vZIT8d581BMDAGQzcb1649lZWV94n4ej+fr6ysnJ2dpGaOg8N8V+9EjnDgRGQwEQDk53LiRm59fGBgYyp/N0tXVPXHiRDMtIigtTEHBh/XDjIx/XcrNRWL6W1ODb98iIj56hC4udXUMAM3NMTQUebz/ziU3N9fOzm7kyMcA6OKC/2lRHB+PLi7IZiMAqqnljB5tHRoaWlRU5OPjw9+KqqGh4eHhUVRU9MXvTGltIiPRwqKuFvXqVbNz565PW5mXlJS4ubmJibH79SszMvro3BaBSHZDw7r0e/bEEycKCwo4np6b+JLdxsYmNjZWyG/1FRAdHQ0A3bp1KywslJCQYDKZb968aUI6PB7OmoUA2KULZmWhgwMZX1Xlfv4c0keSvXix7jgmBjMyMCbmg+nE+fOIiMnJ+OgRHjnSnHzaOlS4tygcDtrbIwCamPyrO7S0rGuDdHTQxQV9ffHlS8zNxTNncO3azQMHDiR2zAQmk9m/f//p06e/JZ0tpaOTlYVubighgQAoLo4uLvjPP5/7bGZmlp1dLalddnaNm34lJuLkyXWSXUYG3d0xLw9DQ9HYGIcPPwAAPXr08PX15X7mVBilLbFlC166VHc8bNi/Ls2ciTNmICLm5qKjI1pb17VCbDbOno3x8V+WEY/H27mTR2pp376YmNj4bTExaG9fV9mYTLS3x7t38cUL9PA4Quy7AGDAgAHHjx/ncDhf+rKUVuf2bRw9uq4iKSujhweWln7uszdvZuro1LVyP/2Eja7xnD2LRkZ16ffogYcOYXExenmhoiIOHeoAAObm5lFRUUJ8o68KHo9HdvfGxMRMnDgRAHbv3t2EdNaurbMvSEjAlSvrjj/WJgidnTu/oItsj1Dh3tJUVuKcOfj8OU6fjsRe9MIF/OMPPH8eCwrwzRsMCkI3NzQxqevbzMymku1f/OCshYWFrf0SlOZy9ChGRtYdz5nzr0seHrhnDyJiaSkuX46LF9dNTIqJ4dy5mJbWlOyCglBZua719PHBepPmBw/WbcBwc8PsbDx9Gvv2resae/fmHD16gkr29sunhfvs2Xj1KubmopMTzpmD8vLo5oafXMj5DxITsV8/BEBJSfTxqT9bv317Xb2Sl8flyzEjA+Pi6ub49fXjGAyGtbV1aGgo73Mm+SktxXff1W0AKyvDH37416UxY/DRI0TEK1dw//4PYz8lJdy6tSnmChUV6O6OLBaZqseGCnzKFARALS308cGCAvz117qWDQBnzEiJiYlp2jtS+JB4kYsXLw4ICDAzM2uC97BDh+pGX9ev44EDdcciMkKuB4+HGzbggQP4/z1fHRMq3FuHmhrU0sLvv0dE3LkTDx/GWbOwa9d/mcrIyKC1Nfr4xN64cYN6s+pgbN+OZ8/WHdfbUjNnDg4bhi9fYlERfvMNTpiATCY6OWFqarNyfPsWHR3rqpaFxb9S43LR0xNzcjAsDE1M6u7p1g19fBqf9KK0I7ZsQUtLnDkTZ85ETc1/XZo5E58/x+HDMTMTnZwwJwffvRNCjhUV6OZWV4vGjsWcnA+XXr/Gbt3QwwPz8/H0aTQzq7tNQgLnz8fkZOG4BaQIl5EjkWxELy5GW9t/XRo0CMeNw9paPHECfXxQSQnl5NDdHZu59+rOHTQwQABkMNDV9V/VMikJ9+3D4mL08UENjQ82XS2jC78GHj9+DAAqKipNXvJavx4B8MABvHoVxcSQwcCjR4Vbxo9SU4NhYRgWhkJyMdpG+aojp7YuenoAALduAQBIS0NQEHC5ICcHQ4bUBWcdPBgkJABgcKsWkyIqwsOhoAAAIC+v/iVPT1ixAg4dAgDYsQN++62utjQHdXUIDobgYPjxR7h1C2bMABYL1q+HSZPg5k1ABHt7ePgQAEBLC9avh2+//awoY5S2z+rVYGsLAI2EFZSXh8WLYccOAIB/O69qOlJSsHs3DB8Orq5w/TosWADS0rB7N6ipQWIiHD0KL16AhUVd2LtOnWDOHFizBrp0AQBt4ZSAImyOHAEWCyor65/v1Ans7OCvv0BBASQl4exZMDICBYXmZmdmBo8ewZYt8Ntv8PffwGbD+fPw4AGoq4O/P3TvDnp6kJsLAGBuDps2wejRzc2RwsfY2NjQ0DApKWnSpEnffvvtgAEDtLW1SQCHz2TrVvjmG5CRAXNzqKmBn3+GOXNEV95/wWKBtXUL5dWKfNWRU1udbdtgwwaorQVJSThxAp4+hdLSD8FZJSRau3wUUaKhAT17Qs+eIClZ/5K+PvTuDaGhAAB9+ghBtfNxcoKkJHBxgT17QFIS9u6F9++BywVxcSgvBzU18PKC589h4UKq2jss//wDx45BeXndx+nT4cUL4efi6AgJCWBnB97ecPcuuLsDALx4AY8ewcKFkJoKOjrg4wPZ2bB7N9DQqG0cHR3o2RO0GxtYLV4MwcGQnw8AMGKEEFQ7QUICfvkFYmNh4kRwdYWuXWHNGgCAykro3BkKC2HIEAgNhVu3qGoXPuPHj5eQkLh8+bKjo2PPnj0VFRVHjhy5dOnSI0eOxMfHczi1/5mCqSm8fQuIMGsWeHqKvsRfGXTGvTVRUYGZM8HHB379FZycWrs0lJalb18YNQoAgB+Nu7r6w2jt55/B2hrU1YWfr7Iy+PsDAIiLw/Ll4OEBY8YAkwlnz0KPHo2MIijtmmHDPshiZ2cAgFevwNQUdu+GCROAbAf94w+IjRV+1lpacPEiAEDPniAjA5GRAADdu8OKFWBhARMnApNOHLUTRo4ENhtKSmD/fgAAROBy68b2LBZs2wZTp8KGDcLP19gYzp+H9HTo2xfYbIiIAADo3h0ePABjY+FnRyHs2LGjT58+L1++jI+Pj4+Pf/v2bXR0NHE4w2AwlJWL1NQUTEzA0BAMDMDMDFRU6h60s4NNm2DQIIiMhPx8uH8ftLXhSybrKZ8FFe6tzPz5cORIaxeC0uLIy4O0dN0xMVE4dAjy8qBbN1BVBTExkJEBd3e4ckW0xbCzgyNHIDkZAIQ5r09pO1hZfThetAgAYNQouHIFjIzg/1FxoXdv+H/QSVGxZQt88w1MmgQAdZY5lPaCunqd9mIyQU0NOBzYsQOysmDdOtDUBAAwMwNHxw8TECJiyxaYNAkMDACAqnaRww+MBQBv374lCv7x48dv3hTevatQUFDXawAAgwHa2jBgALi4QEEB/PQTXL4MxcWQl0f7FFHBQMTWLgOFQgEAyMmBEydg1aoWym70aIiIgMxMsLCAxYth3boWypfSuly4AG/ewOzZH4aOoobUtKNHwcsLfvkFHB1bKF+K6DhyBAYNgn79WiKv9HTw8oK//wZ/f1i+HCIiqHBvTd6/h9RUSEqChw/h4UN4/BgqKgAAduyAK1dgyhTgcqFLF3jzBtzcWrusHRS6VEmhtAmKiuDvv2HhwpbLkcRC7d4dVq+umzmjfA0UFwOTCXFxLZ3vnDlC2/9KaV0ePYKKihZS7QAgIQHdugEAuLjA2LEtN+CkNIqsLJiYwOzZsHs33LoFpaXw5An4+8OECQAArq5w/nzd1mGKiKAz7hRKm2DZMujVCwwN6wzfKRQKpQ2Snw9r1oCZGYweDT17tnZpKG0Ja2sID4cHD8DREVaupDPuooLauFMobQIfn9YuAYVCofwXqqp0XxalcWRlAQAGD4ZvvqF+DkQInXGnUCgUCoVCoVDaAdTGnUKhUCgUCoVCaQdQ4U6hUCgUCoVCobQDqHCnUCgUCoVCoVDaAVS4UygUCoVCoVAo7QAq3CkUCoVCoVAolHYAFe4UCoVCoVAoFEo7gAp3CoVCoVAoFAqlHUCFO4VCoVAoFAqF0g6gwp1CoVAoFAqFQmkHUOFOoVAoFAqFQqG0A6hwp1AoFAqFQqFQ2gFUuFMoFAqFQqFQKO0AKtwpFAqFQqFQKJR2ABXuFAqFQqFQKBRKO4AKdwqFQqFQKBQKpR1AhTuFQqFQKBQKhdIOoMKdQqFQKBQKhUJpB1DhTqFQKBQKhUKhtAOocKdQKBQKhUKhUNoBVLhTKBQKhUKhUCjtACrcKRQKhUKhUCiUdgAV7hQKhUKhUCgUSjuACncKhUKhUCgUCqUdQIU7hUKhUCgUCoXSDqDCnUKhUCgUCoVCaQdQ4U6hUCgUCoVCobQDqHCnUCgUCoVCoVDaAVS4UygUCoVCoVAo7QAq3CkUCoVCoVAolHYAFe4UCoVCoVAoFEo7gAp3CoVCoVAoFAqlHUCFO4VCoVAoFAqF0g6gwp1CoVAoFAqFQmkHUOFOoVAoFAqFQqG0A6hwp1AoFAqFQqFQ2gFUuFMoFAqFQqFQKO0AKtwpFAqFQqFQKJR2ABXuFAqFQqFQKBRKO4AKdwqFQqFQKBQKpR1AhTuFQqFQKBQKhdIOoMKdQqFQKBQKhUJpB1DhTqFQKBQKhUKhtAPEWj5LRIyMjLxx40Z+fr6ysvL48eNHjBgBAElJSSEhIQsWLFBTU+PfzOPxtm7dOmLEiJEjR7548SIgIKBeauPGjTM1NQWAp0+fXrp0ycDAYMKECYI3ZGRkBAYGamlpzZw5k5zZsWNHbW0tADCZTA0NjVGjRnXt2pVcOnXqVHl5+fz58xsteVlZmZ+fn5yc3Ny5cwXPx8XFXbx4MT8/X0dHZ+bMmZqamg2fzc3NPXr0KADY2dn17duXf76iouL48eNcLnfJkiWNZhoVFXX//n0AWLlypZhY3ffF4XBOnTr15MkTAOjfv/+MGTPExcUbPkv+JwAwd+5cdXX1RtPvMJB6FR0dnZeXp66ubmtrSypGQkLC5cuXFy5cqKioyL+5urra29vb0tLSzMzs2bNn586dq5eara1t//79AeDRo0dhYWHGxsbjxo0TvOHFixchISE9e/Z0dHQEAB6P9/vvv5NLbDa7c+fOo0aN4tfk48ePMxiMWbNmNVry0tLSY8eOqampTZ06VfB8bGzslStXioqKevfuPXPmTCUlpYbPvnr16uTJkwDg4ODQu3dvcrKmpubChQv3799HxP79+0+dOpVfcwAgNTX1zJkzubm53bp1c3R07N69O/9STU3N2bNn79y5w2KxLC0t7ezsGAxGw0xTU1PJf8zZ2blLly6NvlRHIjs7OyQk5J9//mEwGEZGRk5OTrKysgDg4+Ojq6trY2MjePPVq1dTUlKWLVsGAPv27SsrKxO8qqSktGDBAnLs7e3N5XKXLVsmISEheM+BAweKioq+++47FRUVAIiIiIiLiyOXVFRU9PX1hw0bRj6+ePHi9OnTc+fObbTNgf+3Hi4uLp07d+afLCkpCQgISElJUVJSGjVq1PDhwxt91t/fPycnp2vXroL1Ni0tLTg4mJx3cHDo2bNnwwerqqr27NnD4/HMzc0tLCxAoBEThMFgrFmzhhxzOJxz5849ePCAy+Xq6+tPmzZNQUGh0VJ1JAoLC8+ePZucnFxbW6urqztt2jRlZWUAOHTokJycXL3W4Pbt29HR0atWrRIXFz927Njr168Fr4qLi69atYoc16s/fAICAjIzM6dOnaqtrQ0AsbGxN27cIJcUFBR69+5taWnJZDIB4O3bt0eOHJkyZUqfPn0aLXlcXFxYWJiTk1OvXr34J8vLy4ODg588eSIjI2Nubj5+/PhGnw0JCXnx4oWCggL/hwAAb968CQgIyMrK0tTUtLOz69evH//ShQsXkpOTBVMgr3br1q3bt283TH/NmjX1Wq0///zz3bt3+vr6EydObLRIHQxEvHbtWnR0dGFhoZqamp2d3dChQwHg4cOHly9fdnNz69SpE//m8vJyb2/vMWPGDB06NCEhITQ0tF5qkydPJorl/v37UVFRgwYNGj16tOANycnJFy5c0NPT++abbwCgsrLyjz/+IJfExMQ0NTXHjh3Lr4q+vr6Kior16jafvLw8f3//Xr16TZo0SfB1IiMjIyIi3r9/r6ur6+LiIi8v3/DZZ8+ekcILNneVlZWnT59++PAhm802NjZ2dHRks9n8Rx4/fnz27NmioqJu3brNnDmT6EAOh7Nr166G6Y8cOZL8GwEgMTHx/Pnzr1+/VlVVHTduHGnlWhRsWYqLi62srACgd+/eY8eOJb/P2bNn19TUnDhxAgDi4+MF76+urgaADRs2ICL5Vvr06WMswMmTJ8mdXl5eAKCpqVlTUyOYwvr16wFAV1eXf0ZCQkJdXd3ExKR///6dOnVis9l//vknuTR+/PgBAwY0LHZ2draHhwdRftra2oKXVq5cCQADBgyYMGGCkpJSp06dbt682TCFqVOnksePHj1KzuTm5np4eJAKLScn1+i/Kzc3V0VFhTxYWVlJTpaVlRkZGcnKyk6fPn369OkyMjIDBgx4//59vWc5HE6/fv3Is48ePWo0/Q5DYWHhyJEjAUBHR8fa2pr0N4sWLeLxeAcOHACA58+fC95fXFwMANu2bUPEU6dOkQrZV4AzZ86QOzdu3AgAPXv2rJcjUWaDBg0iHzkcDql+JiYmhoaGMjIy0tLSx48fJ1fNzc1HjBjRsNgvX750d3cnGqV///6ClxYtWgQAAwcOHDt2rLy8vKqqaqNfoo2NDXn83Llz/H/F0KFD2Wz2qFGjRo4cyWQyBw8eXFZWRq56e3szmUw9PT0bGxs1NTUZGZnQ0FByqby83NzcnMFgDBkyxMDAAABmzJjB4/Hq5VhTUzNkyBCS6a1btz7xpXQMDhw4ICkpKS0tPXz48OHDh0tKSmppaSUlJSGioqLi/Pnz693//fffKygokOOuXbsqKCgI1it7e3tyiS/oz549K/j4q1eviHiKiIggZ5YtW8ZkMk1MTExMTEiHNGrUKNIakOETGaEJwuFwgoKC+N3MtWvX+Jfu3bunoqKioqJiY2NDvuVly5Y1fOvw8HAGg6GgoDB8+HD+yf3797NYrN69e9vY2GhoaEhJSQUFBTV8dv369aR6eHh4kDN//PGHyb9RUlKSkpIiV9PT03V1dcXExAYMGEBS3rdv30e/j47C+fPnSe9jZmZmaWkpJyenrKwcHR2NiP369Rs3bly9+zdt2gQA7969Q0QzMzMZGRnBejV48GD+nUSW7d27V/Dx8vJyMtr08/MjZ3777TcAMDY2NjEx6dGjBzkuLCxExAcPHgBASEhIvTLU1taGhoZaW1uTenXkyBH+pZSUlO7du8vJyZE+FACmTZvWsPVISEgQFxdXUFAQbFGDg4MlJSW7desoxpnNAAAgAElEQVRmY2PTvXt3MTExwQowbtw4BQUFwcpDCrl///56lUpFRUVcXLy2tlYwx6NHj7JYLDk5uenTp//3t9L+ycvLIwN7PT29sWPHkt846Qr37dsHABkZGYL3v337FgB27NiBiIcPHwYAAwMDQYl1+fJlcufy5ctJJamX43fffQcA/A6uoKAAALp27WpiYtKvXz9ZWVkZGZng4GBy1dDQcOLEiQ2L/fz5czc3N2lpaQCwsrLin+dyuVOmTGEymcOGDbOxsZGRkencuXO93pzcNnDgQKJ27t69S05mZmbq6urKyMiMHz/ewsKCwWCMGDGiurqaXPXw8GAymUOHDp04caK6urqkpCRpcsvLy+vVK0NDQwDw9vYmD65fv57JZHbp0sXW1nbYsGF9+vSpqqr6ou+o+bS0cHd0dGSxWHzxiohnz5794YcfOBzOZwp3/rdSj4ULF5JvPSoqSvB8r169pKWlJSUl+b9nCQmJlStXkuOKigpbW1txcfGioiL8uHD38PCYMmWKn5/fN998IyjcU1JSJCUlDx06RD7m5OSoqKiYmZnVe/zixYsA4OvrKyjcfXx87O3tDxw4MGfOnI8J9xkzZnTr1u2nn34SFO5kOEuaeEQksyb1mmlE3Lx5s7S0tLe399cg3CdOnCgmJubv788/c+zYMTc3Ny6X+5nC/cmTJ42m7OzsTOqV4P+wtra2S5cu0tLSysrK5AwR7nylUlZWNnLkSGlpafKtfUy4L1u2bMqUKf7+/qNHjxYU7nFxceLi4qdOnSIf09LSZGVlbW1t6z1+7NgxJpO5Z88eQeHu7e2toqKSnJxMPpK3I+1ybm6uvLy8p6cn/5+gra2to6NDPpIhLj8dsoBw+vTpepl6e3uz2WwfH5+vQbjfvHmTyWRaW1sXFBSQM9nZ2Y6OjgkJCfh5wt3Z2bnRlBMSEgBAWlq6np7w9vYm9e3gwYPkzLJly2RkZPg3kAUW8oV+TLinpqYaGxv//PPP+/fvryfcx4wZY2lpSfQfj8ebM2cOADx9+lTw8fLy8p49e06dOtXKyoov3EtKSpSUlNzd3YkaKysr09fX19TUbPhe4uLiJF/+z6EeHA5HS0uL/OtqamoGDhyooaHx7NkzcpXL5dabfOl4pKSkSElJDRgwICsri5wpLi52dnYmndfnCHdLS8tGUy4sLCT1ysLCQvB8UFAQi8Vis9n8nz8R7sXFxeRjZGQki8Uio7iPCffCwkIjI6M1a9aQVkVQuM+dO9fIyCg/P598XLt2LQCEhYUJPl5bW2tmZmZhYTFz5ky+cOdwONra2nPnziVfelVVlYWFhbS0dHl5Obmhb9++33777Sf/nYiINTU1Ojo6s2fPFjyZn5+vqqq6fPlyXV3dr0S4jxs3js1mC46ojx8/vnr16pqams8U7i9evGg05cmTJ5Omif9TRUQOh6OkpCQtLa2lpUXOEOG+c+dO8rG0tNTU1FRBQYEIsI8J9++//97FxSU4OHjw4MGCwv3atWuSkpLh4eHk45MnT9hstouLS73Ht2/fLiEhQWbK+RJx9erVPXv2fP36NflI+iwym/bq1atOnTpdunSJX0htbW3B0a8gPj4+4uLi5KdKmt8NGzbw9SSHw2n0KZHSosL9+fPnDAbD1dW10avNFO7jxo2zsrIyMDBYtGgR/2RsbCwA/PDDDwDw5s0bclJQuCPiwYMH+cl+TLjzmT17dr0Zd6L4BW+QlpYWHPSXlpaS/jstLU1QuPNZsWJFo8L98uXLAHD+/Plt27YJCncyx09mHRCxpKQEANzd3QWfJSOK7du3nz17tsML98TERABwc3Nr9Gozhbu5ufmECRO6d+++Zs0a/smoqCgAINZNpaWl2EC44/+bCSKJPibc+UyaNKnejDtfKRImTpyooaFR7wY1NbVFixY9fPhQUHDXe5bH48nKys6cOZN8LCoqEqycq1ev5nfeRkZGgpWfw+GoqqpOmTJFMNOMjAxZWdmNGzdeu3btaxDutra2srKyfDlSj+YId6K5lyxZIi0tTdQYwdTUlKwFb9y4kZypJ9x5PB6bzZ47dy5+XLjzuXXrVj3hzuVyS0pK+B+jo6MB4NixY4JPrVy5Ul5e/vXr14LCHRGLi4sFJbWHh4dgu4qINTU1gwYNMjU1ramp+YRw9/f3ZzAYZNXi6tWrAPA1TLELsmDBAiaTmZqa2ujV5gh3YlW1ZMkSBoMhKNEmT55sZWWlp6c3b948cqaecEdEbW1ta2tr/Lhw55Oenl5PuNfW1gp2hf/88w8AbN++XfCpHTt2sNnspKQkZ2dnwRn39+/f83s3RPzrr78A4OHDh+SjsrIyEQCfhpjRPn78WPDktGnTtLS0ysrKvhLh/ujRIwBYtWpVo1ebKdyNjY2nTp2qpqYm+Lu+cOECACxevJjJZJLJ7HrCHRE3b94MAJmZmfhx4c5n+PDhgsIdG0isYcOG9e3bV/BMenq6jIzM5s2biWQSlIiCz5aWlgIAX/vVM1Kwt7dXV1dvWJ6ampqePXvym/EBAwbo6OhwudxPvEIL0KKbU2/cuIGIDg4Ookj85cuX2trajo6OwcHBpNsAAGLdTgyqMjIyGj6FiGFhYVJSUnz74C9F0HIaAEjHJmhjt2bNmvLy8p07d35Rsu/evVuwYIGDg0NDs7whQ4YAwKJFi4hkJ1Mpgpb9PB5v/vz5vXr1ImtbHZ7IyEgAEFG9ysjI0NHRcXBwIPPf5GRgYGCfPn3s7e3hI/WKx+NFRETIy8sLWpB/EcTaVTDBeje4ubkxmcytW7f+57P8YgOAoqIiscRomGxFRYWcnBz/o7i4uIGBARlt8lmwYIGGhgaZm+/w1NbW3rx5c+TIkfVshYVCRkYGg8FYsWJFVVUVWZEDgJcvXz548MDR0bFHjx4vX75s9MHo6GgOhyO4T+aLEBMTE7RwJRVAsIbEx8fv3r1727ZtDXcvKCgosFises8KsmvXrvj4eF9fX8E61pBdu3bxDXXIj3fKlClcLjc5Obme6XZHJSIiom/fvh+zIG8OpDlatGiRjIzM6dOnycl3795dvXrV0dFRW1v7Y/UqJSXl9evXTa5XTCZTsCskNUqwXmVkZHh6eq5evZp874LIyMhISko2+iyHwykqKtLQ0EhLS3v06BHRXo2ya9cua2trY2Nj/pnLly8HBgb+8ccfgs1ax4b8miZPniyKxDMyMnr16jV58mTBrYaBgYHE6p3H47169arhUzU1NREREWpqahoaGk3Lt57EIhsU+SCiq6trly5d+BtmPvYsaa/42kxGRoZ/KS0tLSYmptFdGWfOnElLS1uxYgUAFBcXx8fHT5gwQUxMLDs7OyEhobKysmkv1UxadHNqVlYWAJCdMR9j1apVgv2K4C+fsHjxYv7vUFlZOSQkhNyWlZWlra09ceLEzZs3R0REkBmL06dPOzk5kR1UL1++5G/qunDhQlZWVk1NTVJSUllZWUhISD2t0zSqqqrCw8Otra35lSM6Ovrvv//29fVVU1N7//795ye1bt26kpKS3bt3N7zk6Oi4fPnyXbt2Xbx4ccyYMTdu3AgMDDQ3N+ffsH///jt37sTExDS6Y7Xj8Tn1avny5cTEk8Dlcuvd4Orqyv8ld+7c2d/fHwCqq6tzcnJ69Ohhamq6a9euu3fvDhs2rLa29syZM66uriTHjIwMIyMj8mBwcDDZapaYmFhZWRkSEiKYaZMpKyuLiYkh4wTClStXTp48GRAQoKio+LGemBAVFVVeXl5vOxEBEa9cuTJo0CBikTx06NDTp08/ffqUdN4JCQlZWVmCldbPz+/atWthYWGCvWwHpqCgoLy8/NP1KjIycvr06YJn+BtJCaRB4H/09PQkO5kyMjI0NDR0dHTMzMwCAwNJIgEBAbKysmPHjj106JDggLC6uprMPhQXF0dHRy9cuPDHH38UwhsCXLp0SVxcnOwPAYCamppvv/12wIABCxcu/JxnDQwM+PvAiDJbuXIlsYL92FPh4eGPHz/esWMH+Zieni4tLb1v374dO3aQXnDs2LHHjx9XVVVt7ru1YV69evWxvZuEhISEevUqKSmp3g2C9WrJkiVErr18+ZLFYvXp08fW1jYwMJAsz547d666unrSpEmJiYlXrlwRTGfevHni4uLv37+PioqaNGkSmRxtPmQsKtjsLFiwQEVFZd26df/57KVLl1RVVUmjmpOTg4ju7u5k2VxCQmLJkiW///57vZFhdHT0/fv3BV+trKxs4cKFtra2gtscOzyf0xUuWrSIWLwQiFGDILNmzeK38Do6OkeOHAGA4uLikpISbW3tUaNG+fr6xsfHGxsbV1VVXbhwYd26dSTHly9f8ner+/v737t3j8PhxMfHi4mJnT9/XnBXaJN58+bNo0ePSGUgHDp0KCIiIjw8vN4W/4aQOin4qwGAlStXJicnR0VFTZ06laxI1GPXrl1WVlZk28bLly8RsaioyMjIiKzzd+rUaffu3cTgsCVpUeFOJsI//f+Vk5MT9CfQcFJHV1eXP3Tjby7Oycmpqqrq0aNHv3799PX1AwMDx40bd+fOnczMTEdHR01NTUlJScGOUFJSUlFRkcPhdO3aNSYmxs/Pb8SIEYK1uWn8/PPPRUVF/EnQ6urqhQsXmpqakt0bn8+9e/f279+/a9cuvrsbQfLy8qKjowcPHjx+/PiAgICysrI9e/ZYWFgQvzHZ2dkbNmxwdXXlj1I6PESFS0lJfeIeCQkJQbnZcEZQW1ubP3jji4bMzEwej6etrW1mZtatW7fAwMBhw4ZFRETk5eURfyxMJrOhbmaxWGpqarGxsQEBAcOHD29+g7V27drKykpimQAA5eXlS5YsGTdu3LRp0z79YHV19cqVKw0MDFxcXBpe3bNnT3JyMjF6AYAtW7ZERkaampoOGzasoKDg9evXgr+IgoKC1atXOzs712v4OjCkvfr0KIXFYtW7QXBOGgA6deqkr6/P/8ifdCArhADg6Oi4du3akpISBQWFwMDAiRMnSkpKamtrEwuoekhJSSkoKBDtS1bemkNSUtK+fft++OGHbt26kTPbt29PTEyMjY2t9xYNOXjw4KNHj/hrBWTeS0VFhWzm/gQ7d+40MjIaNWoU+VhZWVlRUfH48eNLly716dPnxo0b8+fPd3V1JTZ+HRJE5HK5n65XTCaz3g2CjqEAQFpaWrBe8V1OZWRkdO3aVVxc3MnJycnJ6cWLF7179w4MDBwxYoSmpqa2tvbr16+5XG69OR02m62ionLnzp3bt29/ekTxObx582br1q1Tp04dNGgQOXPkyJHr169fvHhRcJqzUS5fvnzp0iVfX19Swm7duoWFhXXu3FlXV7e0tHTr1q3e3t5aWlrENwCfnTt36unpCTr+cnd3LywsbFSKdWA+R2LJy8sLTidVVVXVu8HQ0JA/ecp3V0XkU48ePYi3tMDAQLJvtbS0dMqUKaTrFJRY0tLSioqK1dXVWlpasbGx/v7+gwYNqleHm4Cbm5usrCx/+Pf27ds1a9bMnTuXuDz5BMXFxRs3brSysqrnHU5RUVFbWzsjIyM8PDw2NpbfLhFiYmLu3btHXPMBAJlZuHr16i+//DJmzJjq6uqlS5d+9913xsbGxAddy9GSdjlkluVjdrHNsXEnppy3b99GxA0bNsjLy1dWVv74449dunQhW6n69OnDt0atZ+MeExMDAGTLThNs3Pn89ddfDAbDx8eHf2b9+vUsFismJqaoqKioqIjYnxHXVIIP1rNxr6qq0tfXNzQ0zM/PJw/+/PPP8P/BCSJOmDChc+fOxLQaEYOCgqSlpfneKuzt7ZWUlNLT08mzx48fB4CoqKiKiopPvFe7hswS8W0i69EcG3ciakmdXLp0qYaGBpmS7N27N7mhc+fO/2vv3IOauNo/fjaAcg8gFATCZY0SjRa5OHYULFBgRogiBCgUtJBiKzcZldsU6kAr4B2L1LZYgaBgUWmtKDCCkdIREPBWKyCgBiPKXYiiiIb8/nimZ/YNan2R16n+9vNXstmzyW7O7nnOc77P80A410SNO4j/MjMz5ZPSuGN2795NEMT+/fvxlqioKDU1tY6ODng7UeMOjI2NeXt76+joPDfC4fjx49OmTYuLi6Nu7O/v37NnT0xMzN69e+/evWtjY7NgwQL46OOPP9bV1e3p6aFemXdb4/7o0SMGg/ESaezraNytra2DgoLkcrlEIiEIIi8vr7W1Ff2dZCYzM5MgCBD+KmjcR0ZG7O3tWSyWTCabhMYd09nZCfFYOOPQ9evXVVVVqc9GBY07pry8XFVVNTIyEm+BSKHS0lJ4Cw6XiRr3lpYWgiCokvqQkBAmk0ndJywsjMFgTEyT9S7x3nvvLV269EWfvo7G3dPTEz4aGRnR0NDYsmXL4ODgtGnT9u7dK5fLjx49ihC6efOmfILGfWxsbPny5dra2kNDQ5PQuGP6+/sXLlw4e/ZscJbL5fK+vj59ff3AwEC8j4LGHXP+/Hkmk8nn8xUyw2DGx8fnzJljZ2dH3djW1sZgMHCKCLlcXltby2AwcBoQuVz+/0TjDs4dCJ2fyOto3EtKShBCMOisXbvWzMxsfHzc39/f1tYWdtDR0UlKSpI/T+N+5MgRhBAMYZPQuGPi4uKUlZWpIx2fz2cyme3t7WDtwBedPn0aRzYDUql06dKlpqam4DKfiEwmc3JyMjQ0VMgP4+XlZWVlhXtjW1sb+s9EIHAjvEoMxtTyRjXuixYtgmFmyo8MUz3wYPH5fKlUWl5eXlJS4uvrC6qVl2j7HBwc9PX1L1++POlvHx8fT0lJiYiISEtLi4mJwdt37dolk8kcHR319PT09PRsbW0RQhERES9XY5eVlbW0tFy7ds3AwAAagmE6c+bMgwcPIoREIpGLiwtebfDz81u5ciWES16/fv3kyZODg4MkSULb4OBghJCTk1NycvKkT/BfDvh1IBB5aoE+A7nSfH19u7u7q6qqjh8/Drnb4aPnatwRQp6enqqqqjBbmxwymSwxMXHTpk2ZmZm4tsCjR4/27dv3+PFjNptNEARBEHZ2dgihVatWUZPjDgwMeHp6VlVVlZWVwTIfle+//97f3z8sLGzbtm3U7TNmzIiJidmzZw/MDVpbW+GelUgkxcXF9+/fNzQ0hC8Fv4WDg0NERMSkT/BfjpqaGpfLbWxslL9Y+DFpxGIx9CtTU9PFixcXFxeDTgYuLHgHnqsZVVdXX758uUQi6evrm/S3NzU1OTg4aGtrV1RU4EWArKys0dHRXbt2EX8jEon++OMPgiA6Oztx27y8PG9v78DAQJytGSEEMTwrVqyAhrCilZqaqhA7tGPHDmNjY2pHNTExGR4ehok0YGRkND4+PjIyMumz+/djb29/9erVR48eTfmRb926Bf0K+klxcXFJScmzZ89g0MHqvokNVVRUvLy8pFIpxJVOjra2tmXLlg0NDVVVVeGF8ZycnP7+/sOHD+N+dejQoRs3bhAEUVdXh9ueOHHCzc3N0dGxqKjoRTESBEGYmJhAcBcG8mjhOi0IoW3bto2Pj2/cuBF/4/Xr13/++WeCIHD82zvJ/9TEUlJSYrFYCCE+n3/79u2zZ8+eOnWKz+fDDi8Jy1m5ciVBEK9jYo2Ojn722WeZmZkFBQWQLR5+UklJyfDw8OzZs8HagQeLu7t7QkICbtvZ2ens7Hzz5s2qqiq4NSbCYDA8PT17enqot0Z7e3tpaWlsbCzujSALpJ4mdPIHDx5M+tQmxxuVyjg4OMyZM2fHjh3+/v5UEYj8P6M5J4FYLFZVVYWLCNP9uLi4u3fv4l5laWl5+vTp57Zta2sbGBiYdHCqVCr99NNPKyoqcnNzFaROtbW11CG/q6vLy8srJSWF+oiZiJOTk4JMNj8/Pzs7u7a2Fn6kqalpa2srvmhyubyjowPi58zMzBTaVldXx8bGFhYWQpWrdxJXV1czM7OMjAwfHx9q9a7XRywWQ25+hNCSJUuMjY2jo6MHBwdxvyJJErRuE/nzzz9HR0epBUr+K/r7+z/55JO6urojR47geQJCaPr06VjcArS3t0dERKSmpuKYpEuXLvH5fCUlpbq6OshBixkdHY2KisrPz09LS6M+3Saya9eux48fQ5fW19evrKykfnrhwoXExMQ9e/YorDy+YwgEgg0bNmRnZ0+Vphy4f//+8PAwHkX8/PwSEhJaW1t5PB4ovrBm9LnPpfr6em1t7Ul39YKCgnXr1n300UeHDh2iBhRFRkYqCILj4uJkMtnu3btBhvfkyZP4+Pi9e/fGx8enp6dTrauffvqJaobK5XJ3d/fVq1dTtfK9vb1FRUWpqalU8RiUfyoqKoIcTTKZ7NSpU6ampu+2xl0gEJSVlaWkpIDbewqBEkvw2tfXNyAgYPv27fDsQpR+pSAJAOrr6wmCIElSIST9FSktLV2zZs2CBQtEIhG13l9AQADUwsNs3bq1paVFKBRCoKpcLt++ffuXX34ZFhaWnZ1NlfGMjIxcuXIFyz57enouXrzo5uaGdxgcHDx48GBiYiJVWZSSkkKVQSOEQkND2Wx2UlLSP2rA3mrc3d1ZLFZaWpqXlxf1+TAlJpaxsTHcuS4uLnp6ep9//vnIyAgem17iG62vr5fL5ZM2sSQSiZ+fX0dHR0VFBTVqYubMmQrWTm1t7fr16/Py8vBuZ8+eDQgIMDU1rauroyaKGB8f//HHHwUCAZYVNTc3MxgMaqxjZmamvr4+tfychoaGvb39sWPH0tPT4VLAmif4zt4kb9RwZzAYQqHQ3d3d3t4+PDycy+UODg5CqpmJJVFfRF5eHtWGsLGx4fF4t27dMjc3x13T19c3IyPDyMgIh2xaWFhIJBKZTAb3bUNDA/gaBwYGDh48qKWltXbtWtizu7v7m2++wccnCCI5OfnBgwf79u1DCP3111/Dw8PQNjIy8s6dOx4eHrdu3QoICOju7sb+S6goCS52DAQ4W1hYQA9+9uwZuKkaGxvHxsagLdSEU+gHMOWwsbGBZ5NAIEhISAgMDAwNDVVWVhYKhU1NTfDz1NTUFNqC027u3LnPlcu/G6ioqOTn53t6etrZ2UVFRXE4nL6+vjNnzqirqx84cOAVD3LgwAHqYLNo0SJXV1csREYIMRgMHx+f7OxsS0tL/M9aWFhQS81duHAhJydHJpN1dnbm5eXp6enhuZxEIsnIyMB7qqqqbtiw4f79+7B4LRaLBwYGcnJyEEICgeDatWsrVqy4c+cOzBNgO0LIz89PV1dXQWUO8lZra2soZ3bo0KG1a9eqqKgkJyefO3cOiguqq6sHBwd3dXXxeLzLly+D7gUf1s3NzdLSUiqVJiYmLlmy5MmTJ9XV1YWFheHh4TDfU1NTU/hS0ELY29tzOJxXvMJvI1FRUaWlpTExMfX19R4eHqqqqlevXi0qKhKJRK94Q127do36vyOE4uPjYYQjSRK2+Pn5xcbGisVinHtKwTP67Nkz+LOGhoZEIlFlZeXmzZvx404oFJ45cwYfH4r+lpeXSyQSsMDKysrEYrGdnZ2trW1YWFhubu68efN4PF5xcTE0sbKy+vDDD+fOnUuVTSOE9PT0nj59Cn99b28vj8drbGz09vYmSRK0MQghZ2fn2bNnK0TUgMOCJEnq9qysLCUlJYW61O7u7suWLdu0aVNXV5eVlVVhYeGlS5fy8vJe0874l8Pn84OCgnbs2NHS0uLr66utrd3a2nr48OH9+/e/YujC7du3FfpVeHj42NjYyMgI7lcrVqzQ0NBob2/HViy4Iahuxfz8fHV19YcPH547d+7XX38VCAQ4Eccvv/wC8i3A0dHRwcGhpqamtbUV5BC///772NjY3LlzHR0dv/rqq7S0NBaLFRAQ8Ntvv0ETU1NTDw8PkiTxTwKEQqFYLIZ+9fDhQx8fn8rKShcXFzs7OwiFRAgtXrzY2tp6586dW7ZsCQoKcnV1HRoaysrKkv8tCAFAt6AQS03NLQNoaGgYGRm98/E5MBTyeDxbW9vw8HArK6v+/v7KykpdXV18w/4j3333HbVK99KlS11cXKhDoYqKyqpVq3Jzc62trXFmJAsLi/r6etxKJBJB7Nm9e/eEQqGxsXFgYCB81NbWRjWxdHR0oqOj79y5A2JpiUSipKS0bds2ZWXlTZs21dTU+Pj4DA4Orlu3rqmpCVvq0dHR6urqCtZOb28vQojD4cDKwM6dOxMTE7W0tLy8vLCFaWhoGBIS0tLSEhcXl5+fHx4ezmQyz549KxQK16xZgxOIDQ4OFhQUxMfHK8TOff311zwez9nZefXq1d3d3Tt37ly4cKGfn98rXtup4o0a7gihDz74oKmpKSMjIzc3d2BgwMDAYN68eWA0M5lMDoejEJFDEASHwwHvi5aWFofDgcTDmLGxMR6P9/TpU+rzzs/PDxI1YJ8Ql8tlsVi9vb0QoNPV1ZWTkwPlr/h8/vr168GYNjMzE4vFkGMfYDAYycnJDx8+xFaOjo4OvA4NDb148SK4KBoaGqhSDTc3t4nJ1FRUVEiSxAvTeDBGCJmYmMBrb2/vibnndHV1SZLEI1l8fLy5uXlWVlZQUNDjx4+5XG5hYeGLvPgaGhokSf5jwPXbjrOz8/nz59PT07/99tv+/n4jI6P58+fDk4LJZLLZbIUIUSUlJTabDY8nLS0tNpuNA1AAmUzm6uoqk8lg8REICAgoKysLDQ3F/8X8+fP19fWlUqm6ujpJks3Nzc3NzQRBGBsb+/r6bty4EWb5LBarp6cHFISAtrb2hg0b+vv78WRv2rRp8Hr16tX19fUqKiqWlpYnT57E8X9wmgq5sRBC06dPJ0kSR31BLBf6u+AXYGBgEBwc3NzcLJVKSZJsbGwEGStgbm4ON8XNmzePHTv25MkTLpe7f/9+gUDwogsO5/vOp5dRVlYuKyvLysoqLCyEqAAzMzN/f3848VmzZlEne4ChoSFOrWBpaXnv3qfaMGcAAAKySURBVD3q/44Qio2NHRgYoFozLBbL09Ozo6MDxwVqaWnZ2NjACuyMGTNMTEygb2hqapIkWVBQABI4TU1NNputsJY4a9Ysa2vrY8eOgXyOJMnS0lKYfixcuLC6upokydHRUaqv19fXFyeWoQKFqOE1rEySJHnlyhWoHoXP97m+NJIkqX316dOnp0+fjomJodoECCGCIE6cOJGUlFRQUDA0NDR//vyjR49Sl5jeVQoKChwdHfPy8sCqNjMzc3d3h1hAc3PzicspM2bMYLPZMKKxWKy+vj6FfhUcHDw0NESSJLal1NXVAwMDRSIRVZy5ZMkSiLHT0dEhSRLKt6mqqpIkmZ2d/cUXX8BbNptdX19PNcU0NTUdHBzKy8tBSUySZE1NTU1NTUBAgKOjY2VlJRh21MTHjo6OHh4eE8/dwMAATCuE0N27d2/cuEGSpFgspir3EhISrK2tk5OTDQ0NhUJhSUmJhoaGk5NTSkoKdhbIZLKKiorIyMh/TNjKYrGmdjH2X4uLi0tDQ8PWrVt/+OEHEDdyuVxYItbV1eVwOApxycrKyhwOBzzNOjo6HA4HSitgNDQ0XFxcxsfHcagxQigwMLC6upoqMXj//fdPnDgxNjampKREkmRLS0tLS4uysjKLxRIIBBs3boTrT5Jke3s71cQyMTGJjo6+d+8emEAMBkMul+fk5EAs4rlz55hMJpPJVFhnDgsLm5hNRGFUEolEMP4KhUK8D5fLDQkJ4XK5DQ0NmzdvjouLg8XP1NRUakLJkpISExMTqF9OZfny5aWlpenp6UlJSZqamiEhIVu2bHnz4yDxv5Bv0tDQ0NDQ0NDQ0NBMLW80OJWGhoaGhoaGhoaGZnLQhjsNDQ0NDQ0NDQ3NWwBtuNPQ0NDQ0NDQ0NC8BdCGOw0NDQ0NDQ0NDc1bwP8Bj1u0S6xAsEoAAAGIelRYdHJka2l0UEtMIHJka2l0IDIwMjIuMDkuMQAAeJx7v2/tPQYg4GWAAEYgFgFiMSBuYGRjSACJMUNoZjif3UEDxIfTbBCaBUFngMUZsTEgSjgYwAKMmDIwmh2qgglhC1QlurXcQGczMgHdBWQnsLBmMLGyKbCxZzCxcyRwcGYwcXIlcHErcPEAxXkTePkymPj4FfgEEgQEM5gEhRKEhDOYhJkTeNgShHkTRJhZmVlYeYXZ2Dk4uXjY2PgEBIWEecV/QUMGDETcL2Q5TAz2dQBxuPLSHdYevWUPYk/KnOOg+TETzN66TMjBf2MDmH2irdC+4fUVMFu159Tek1tEwWyOE6f2v3P3BrOzgzgPrLjODTaTLynjQKGNJJi99ODEAzLms8FqHk+pP/B0odk+EJs/eu4BJrF1+0Fsh1aFAzblx8DiZtel7HszbMHivzh220r2ch4Asdemb9zvaCAFZh/kbbd/LhMMZv8XUnLYX+kEZrd+cHKY1HsBrPeNI6vDre1fwWaKAQDCl2SbzHVD9wAAAf56VFh0TU9MIHJka2l0IDIwMjIuMDkuMQAAeJx9VFuO2zAM/M8pdIEa4kMU+blJFkVRrAO0296h/70/OrSRlRYQalmMRY0oPoa5lHx+3L//+Vs+Hr5fLqXU/7wRUX5LrfXyVvKjXF+/ftvL7f3l+tTcHr/295+Fa2HGGYzP2Jf3x9tTQ+VWZDPzMMYHV2dupW71eMZJPnFkNajQ1vHTfIET4HRz73ixHSQutsBp2QtvHKS4jrDdlGiBa8DBjIqaAGcmKn2BM9z7BerwSPXWXHvUBbAnkHKfObDfQ6utPPQE8kbarDX4St6qrEKOBCI3gssTKPCWdAGkmkjdWlN3RzRMbBQrJJ02IxA3Z2DUXRqvoFweaTSoC+JAaGK16ipHJGdIrTqJpFXxbryKCf7foLaqrpbILuF9abQdSPBB2M6EBS9LRIZapn/eoh9QxalYsY06oGBFa1R7JoLDTZaZyjIhJGEYSyRqZL5iEhK9g8JVW2AFP4xDeEURrodNtAJiyeBBpaBVml73+6duOvvr+tjvo79y8GgjLIqMbsmljqbI0Qb3sSg2KE6YfRBZMX3QVTFjkFIxaeaepiCaOEaH4IlKemhkYozmvTrxQlNQm+pPh7Cpznpo+lROTUE+lU1TUEzl0RQ8l0EP8aGghMhIAfOJGP5lQeb05/r514jvyz9HNANF9FLpAAAAAQp6VFh0U01JTEVTIHJka2l0IDIwMjIuMDkuMQAAeJwlUDtuxTAMu0rHBHAM/S0h49vbQ3jPCXr4UqlhwAJNipQ+n+NzPvzs49qycY6fcwvuPr7PZz9b+Ov30BmRFUOnUIqOGwAH1eC5qDjGbTNzZQ2axZoKRKYUm4JC5MbjxpepRSMRajbuiyZVFhFD52mrgHFX8KC5yijQ6ZLJ5qjwplML4a+QAlE0RfPLprtlJxKWkJdTBb8BF16pLi+reOkacNFArre5U7I2TXOFZCcNsvyXLq1cqzEMquLQdpwSe7NqOmIAMioYYFh35gFzqQzrNbiKvQhpRvbuyLy0M4SUSnOwVfa2ww6Kc5y/f8gaVFDDBmwtAAABxXpUWHRyZGtpdFBLTDEgcmRraXQgMjAyMi4wOS4xAAB4nHu/b+09BiDgZYAARiAWB2IpIG5gZGfIANLMjExsDhogBgubA1iAmRGJAZOB0OwQmhlGszEkgI2A0ExMOGk0/XALEAJQBXjcBBHggKpg5GZgVGBkymBiYk5gZslgYmFVYGXLYGJjT2DnYODgZODkYuDiZuDmYWDnTeDly2Di40/gF8hgEhBMEBRSEBQGahBJEBHNYBIVUxBlTBBmTeDhYBDmTRBhYWMUFWFhZmJlYxXmZWfl5ODh5mLj4xcQFOYVl2OEhCEYiCt5nzqg9dxvP4gzdd2sA/tV5cDsMvWOA7vEXexB7IuihgfUbpaA2a+uvt0/r7toH4h9tW/vvj3idntBbLceDfv29RPBeq+8Y3BonfkPrCZbKdSh+95ssLj496kOp1cJg9m9D7c56E25CmY3XZ7vsO6v3QEQ+1hQokOChi6Y/anmpf3y6bVge12ijB0cdTgcQOwLC4Udnh9PArNdzULtTeeWgNmzHovsu3dNG8z+6HJ+v84aWzD7UuBmu4KyRWBzTH5KHzAoOA+218+o+sCzC8/BbDeFCQculvuA7RUDAJiGd5lfHZegAAACQXpUWHRNT0wxIHJka2l0IDIwMjIuMDkuMQAAeJx9VFuO2zAM/M8pdIEYfIkSPzfJoiiKTYA27R36v/dHhwoSawGhdkTI8pgSZ4Y5lLx+Xn78/SyvSy6HQyn0n19ElD9KRIePkpNyev/2/VrO97fTc+V8+329/yqiRRzf4P6KfbvfPp4rXK7l6JsKe5NypK1TF66FNhrX/q2Uczna1lU7cyKdW3NdIPWBlGqdG943r9HbAmgJFLz3qPk+qpv2BbAmkLdeO8XYW9S78wLpiaRNGwmeMCNzo1ggGypHEbVrUCZn1OUrYAdQNmKrrWVGiya+Yiiwt26qJOAdGQUEySojQ6NiG0owHqTX5l1WKcH0udStcSXVzOkOEpZIGTkjrKIKsBrdRFfysI5zViHPgsA/1dqX50yBQLvgmJ76BNVYbl4HRx2kd8OEpTVaycOpj2yKrSvnIUytLoEPebpKrwFgF6H11v2hOORRtIaAVYt1NZFeB4UcAheBIVdfMiSpD0xUUY+BAPEQXaUUfjjY4DeoksnBKq8KktE/uoUYJBpuZqZl/6Bxb9lA0DyM8iMOtNIK+n69fGnnR4OfbtfL3uB5y97F0Kfo3qqWY2/IvOvedozhe28ZRtsbyDD63iaMEXszcI7Z8zwCT97mEWTyMI+gk1ctM9tkScvAdfJePsJak8ksA7fJTZaB+2QbHiEme1iuyGwDkAGRJ7ktg8ikaj5Cskk8GyuvhTwxUr2OJ0krCnvtLP5A7FWmrLOI+fz8h8f88A8tdyeacYFHgQAAASh6VFh0U01JTEVTMSByZGtpdCAyMDIyLjA5LjEAAHicJVE5ksMwDPvKlsmMzOEtclKmzz5CvV+Qxy+kdWMLIkAA/ixZaz2upff9eNsbjz2X3etej89zKQ5Lfn++jyvJVHKOi6m4VGK8LqcyK9lYypxpB9Pw0sE0M7omIMVndgLqSLcCJFRR3JuplpUCjMkmq22MPZ3bxwvCUYY5IcEmqCmxeNSe8p6a8GFkdohCChtw4QRNP8ZiZimGgqYEn6FMLN9D3R5IpNTl4EMolLM2Mjmixws+1cW29ebo2PsLu2ooic7jxzhnDHDdPLblMi2QDVz9DwbH1g1OluO986e0bqTTdm8IH9D1gQzZ6qc2RyEne8LWVjLCFVzs/kQ4T99IhapwJ+34Gc/vH2ymYIivvHDgAAABxnpUWHRyZGtpdFBLTDIgcmRraXQgMjAyMi4wOS4xAAB4nHu/b+09BiDgZYAARiAWB2IpIG5gZGfIANLMjExsDhogBgs7hGZmcwBLMDMiBCAKcNNQDUgMiIwggwLIXhiXA2olI4YVcKsYEsAqIDQTEy6am4FRgZEpg4mJOYGZJYOJhTWBlS2DiY09gZ1DgYMzg4mTK4GLO4OJm4eBmzeBl0+Blz+DiV0gg0lAMEFQiEFImEFYhEFElEFUjIGNMYGfI0FMiEGQNUGEhY2RjZWFmYmNk4ubl5+DVYCdjVWQVVhITFREXI4REoJgIP7R5by9zhrbAyDOrMcidveuaYPZrmah+03nloDZFxYKH3h+PAnMdokyPuCowwFmf6p5uX/59Nr9IPalwM37CsoWgdlX+/ba7RG3swWxX119az+vu8gOxL4oauigdrMErKZMvcNhl7gLmD113SyH/apy9iC2kvcpB63nfmC2n1G1w7MLz8FsN4UJDhfLfRxAbJOf0g4GBech4j0a+9vXTwSzr7xjONA68x/Yrmyl0APd92aDxcW/Tz1wepUwmN37cNsBvSlXweymy/MPrPtrBzbzWFDigQQNXTBbDAD7ynU0HGfLpgAAAj96VFh0TU9MMiByZGtpdCAyMDIyLjA5LjEAAHicfVRbbhsxDPz3KXQBC+JDFPkZ20FRFLGB1u0dCuSz90eHaziroEJ3I0KSZ/maYQ4ln++Xb7//lI+HL4dDKe0/fxFRfklr7fBWclNOr1++Xsv5/nJ63pxvP6/3H4WlsOEbvJ+xL/fb2/OGyrVQNQoOKkeuYWIipdW2PfunXM64Je2CBAA01/BYAAUej626sHcgpTpzi75AKlzCkzQbnRLZVRS7f5E9fXL1xuKaO+Ix2gpp6ZMQUwnFI4+I1pfRRyJblQ6nmt+wBcuqIt9KlwFgy5/VtK1wARxCd2+RqbGY2ypHAkWF6zCLPrYcu6n4CklAauWuThtyWA8fKyRvSBdxyphGY9iKR5Jyfi9WhckGA+DNmVYNouRHarCG9iyMqK1d9nJD7N4kFPxXCqS7BNpWuKKVnh6Nm9GyQ+MhIusugWMllGWrnpM/pNGgzJGN0Rhsy3KSHohMpDGkAb7RIl755OTnqJC4QUUA9GHOK5+c/Bx7HYTiJSsy0L9E8sNnoJcoBIPmyutBk0eeHc1BRdBJ6305aa/Xy6dZfkz36Xa97NOdL+8zrFiyT6rm2scx377PHA7F9sFSrLFPj2L5PiKEFfskKBbNitc0RJOyNQ3xpGDajExS1e1GJ0nSZvqkPd1ubBKZZj5jEpOmIZ9EQ5uJSRyUhmcRUBqmiWxKwzyRmkdQNpGXfdkR2VJk9BEIMqJE7aE580UyNtM6k5jn57937A9/AXdpJ1UYZoRmAAABJnpUWHRTTUlMRVMyIHJka2l0IDIwMjIuMDkuMQAAeJwdkTmOxDAMBL+yoQ3YAu8DE04++wilC79gHr8tOTCMEtlFyp/Jz3ymTJ7Hjdecx/vvnMfvOfl8HnnzGw//fA8ewS193TI6NPR60WBz7Y2iDB+vm0aplIPpKBEGkqEU6Yu4qflGRaK1GlkyQRjVxnohoJu8fWepo8wunEq02FJqAl00yMKogdDpRQ0kGhUwysiIjp3lYfC8bIhbyUIZ3pULlWox+oIz1z4xVDgSpKiEMYIOWDELHMwUq8lJYdXBbbVdhokaFSG05DCEly7CiM+9LeGiCrnWKbFW06G69sBikMN9G64wbI3jGSWryEcydCs7sOMu6jbPC7+gTHQHObwFkuS49vP7D5AJYC3mr/drAAAB1XpUWHRyZGtpdFBLTDMgcmRraXQgMjAyMi4wOS4xAAB4nHu/b+09BiDgZYAARiCWAGJpIG5gZGNIAIkxczBoAGlmJjYHMM3C5pABopkZEQIQmh1CM8NoiAHMUIOYmHDSaPrhFiAEoAoYwBKM2JyC5ia4Um6grxiZFJiYM5iYWRJYWBVY2TKY2NgT2DkYODgZOLkYuLgZuHkY2HkTePkymPj4E/gFMpgEBBMEhRQEhTOYWEQymEREE0TFMpjExBXEmBKEWRN4OBiEeRNEWNiYxERFWJhZ2ViFedlZOTl4uLnY+PgFBIV5xbUYIaEJBhLz754/UO/Jbg/ieK5ZeCBhVT6Y/a+37oBhzsO9IHagttKB7Wkz7EDs6oO79ncvsd8PYpcK1O0Jal+3D8TefX2KfXTBIrD4Rgsph9mX74HF2X1LHKz0SsDib3kWObTv+go288nB4w76Wm1g8XDN7Q65mrIHQOwFRu0O1nmSYHalAoNDsUAj2D2ZQcYOf/cKOoDYr6axOXxclwZmf1wqZa+clQVmW7V77Is3kQSzj7y+sX/iexkwW/sMg/21tg6wOWs+vtwf+p0HbH5zdOCBXn51MJtbuPuAuvEJsHuSXHYemJH8B8wWAwC70HbtAiXiFwAAAlF6VFh0TU9MMyByZGtpdCAyMDIyLjA5LjEAAHicfVVbbhsxDPz3KXSBCCTF52dsB0VRxAbatHfof++PkmskUgqhuxYhaWcpaTizPrW6vl+//f7TPi66nk6twX9+EdF+DQA4vbbqtPPLl6+3dnl7Pr/PXO4/b28/GnEjy3fy/ox9fru/vs9gu7Qn7RziwA26kLNKduC45qvU7u1JOgiRYz6PoRhjAxyVcfQwY7T2BB0RwGCD5EJSlzE8am0KU4kNUAqInSUgR5nS2PXY7r9ILWROowgciw8GN90grd0adlTywZWcNEB2KT2B1BnC8FibhxD4Bhi59uiORoAFDBk+dufOPJeWVCqD+YOhCN+RjlUe7cTE6LVLYM8t75B05DQaFlqssojKrj5YBeJOxFFkUh9hY4+sAlFOYzglWQA+cEcRysGRJxAkO2RGhDugHhkRKBSTrCwi045LrPJAPYeQAirZHuiPimMKOAF1muG0ZSgyZVKowRq1SxbCLZKqPmkFGJgny3OrKm49gQ9hOpm6F5cEJLGTG9HDFmRIeNCuCIN2bNLhIE7pKphUfkml6I7PfP9WrjQPCStoqjQHG+jL7frJ+I9Pwfl+u85PQd00DZ+DNqatudr0bt0yHYrZdNqQs9n0Gmfz6SjMFtM3WG21Bx4BFxvgEWiROx5hLLLmysyLerkCyiLTGqYKFz1yBbRFeFwBfVEYHiEWJXHN0KqYJCP1sCiDKxAtAuAKNJY6YwXipZxcMxNSO87kHxsmrc2MSR7ZAzHPXYVey1rj93+H7J/+AjSTMjzp1cbKAAABL3pUWHRTTUlMRVMzIHJka2l0IDIwMjIuMDkuMQAAeJwlkTtuxDAMRK+S0gvIBP8fuNx+cwj1PsEePqTjSnoYcTjj9++mvY9z830fb3n3J68t97738Xlt7sve9Pn5HqeDluVCME51W9dpgMY8qMSppJFARSivE4EIMRoxmEhWq7jCrRoRqBXKqELTUZshIJmh11BRzPB1EZBztpCAvbBNGRQraEQqxpjrEkiKx7JMWnz1Xt4D/peoyn7mwMqzFwFqko8oWFrTA80mjgKzdogmUiGPFyJVrn6DKTQgGywGjmCeOyGXL4HOoO2Mc8CyIc4hTy7q2rqlGSvJT3wv9ZmjxsTzzFCIbJzcnR5NckwZbYbsT7UcxDTECWUGaRflXXKrrRP7808ie6Mm3VLUen3/AJpkYwPy4165AAABzXpUWHRyZGtpdFBLTDQgcmRraXQgMjAyMi4wOS4xAAB4nHu/b+09BiDgZYAARiCWAGJpIG5gZGNIAIkxQ2hmOJ/dQQPEh9NsEJoFQWeAxRmRGBgyEAEOBrAAIyMJemA0O1QvE8IdUJXoDuMGeoyRCehyIDuBhTWDiZVNgY09g4mdI4GDM4OJkyuBizuDiZtHgZs3gZcvg4mPP4FfAKhKMEFQKINJSFhBSCRBRDSDSVQsQUw8g0mcOUGALUFcMIGfM0GEhZWZhVVQnI2dg5NfgI2Ni5uXj5+TTUhEVExcUFyLERKmYCCRsCz7wEnVKgcQ5/vE5gM/tOTA7FzXTQec/rCD2ROsXA/s2LvBHsQW4zqzXy/sJJjtNqd4/+KtcXYgdsdJVvu8qcV7QextXU32MQf37Aexz82Td9hj8gDM9lSNc7jGJgtmx9nPc5j2NhnMnt2018HgSi3YnND1bxxKzN7tAbHlZ651ML9/BWzXqRs1DtODfoDZAUF2Dt1OvmD2jo/77ZeJdIHZupuZDvD98Aeb+Tqb4YDEd+EDIHbiaoP9Lb8cwew9qUEH9r9xBbMzgicfCH4pDmZzlk858OtAPFivw5ewA0+C9oP9IgYAh4B+evEIuQEAAAJGelRYdE1PTDQgcmRraXQgMjAyMi4wOS4xAAB4nH1VW45bIQz9zyrYwCA/Mf6cJKOqqiaR2mn30P/Zv2qTZCAS6iVY1+gA9vHxzaHk8/P84+9n+XrofDiUAv/5uXv5wwBweC/5Uo5v375fyunj9fhYOV1/Xz5+FZJCFntiPGNfP67vjxUsp/LCtXWC8Lg6dNVWoMJ45lZKoFRE1NYLVTFk4w2QE6hVDdw0gEhiRhuglEteDR1b5ISVO5jDBqgJxKouoD2AauSyO7Hl1VBdsUGGRmiyPdECCFWJGrTcAXF28w2wBxAroPe4OWIQk6a4AXoAg5QIsQ2gZQy7EzHqEzwHfUDj7obMfcc4Zm2kuiixJrI7sMgOmcXR6kToI2+x3nd5I5drscreJAjKxMmD9B1SxpFCkRIGBa0xtB3nqCMfVzCmAAYDQNu726DIjc0yiQ5objugDdLFXZsk+9ZNdQfM6rxQBSHsg8uOxPt0/A6Fpt3yjRF9L3RIuUVdHELrQ6EMjrsACG8Spm6iPqBOalvovX9CmM44AjBuuA2A89SAsmu4mZZFufoOKrf2Ze0tBRoIZ9nS/3Y5PzX+7VNwvF7O81OQg2bDh1N4tnW6Mps3h84WDae02YgY02a7Scw+m0pi+mwdiYlrh0gaxKUTJA3Songchhdpy1iRRcKSBnXRarohxUWUkgZtUZ9k/H1RmaRBX8SEaWjVjIwVXKQhaYgWBUga4qXQkoZkqacM87UwIrZJJbUbYsZHdk/hqdRrYdN//D/E++EfpJYy63VN7bQAAAEuelRYdFNNSUxFUzQgcmRraXQgMjAyMi4wOS4xAAB4nCWQO24EMQxDr5JyBvAK+svClNsnh3C/J8jhQzud8UyREt/v631/5LOu19K1lq11/dznoTfI9X1/1mepfP1eL6OcyjaMmmfkeF5OIhI1lLzECiQoinsTUa9NjHhKDSGbXA0gFO2cIFHaDsLUIQlnJpVyiJhCNSHCH0OeE1ZCLD3BBHGeMR7kwqo2KTjIeGxvAifMpZhB/Ti1h/pGs9kciUGtKr3zvOYcT5F1Hglrc+20IFe4Y81Mwyaw7uAyAGSy7vQuw43wZak+G3p37NO2x25IiX0n7XBROwWAcQaYkol0ngayGVWOXZdx6ylOJ848qDXq9I2W2s5kWeo/so5zMNRs80xazPwvr81R2rh//wCYBWVC9/dIQwAAAZt6VFh0cmRraXRQS0w1IHJka2l0IDIwMjIuMDkuMQAAeJx7v2/tPQYg4GWAAEYgFgVicSBuYGRjSACJMUNoZjif3UEDxIfTbBCaBUFngMUZkRgQGUEGBZAJMC4HA1ieEVMhjGaHqmBC2AVViW45N9DxjExA1wHZCSysGUysbAps7BlM7BwJHJwZTJxcDJzcCdw8Cty8QCm+BD7+DCZ+AQV+wQRBoQwmIeEEYZEMJhHmBF62BBG+BBFmVmYWVj4RNnYOTm5eNjZ+QSFhET5xNkZIEIGB6KXGAodD3BEOIE7uzyKHA+of7EHsSysWO1wvnQJmX5RQdHj6shvMFrsxwd6s8iqYvXOJgt17QXYwmydo9f72RFUwO/bp3/2xzAxgMxmWxR1wns4OZl9p7zqwlSEJrKY2cdcBNY0GMJvhWPaB3LCP+8BqxCceONZ8az+IvV6I58C5X2Jg9pMlBfb1BQ5gtlgGs/1+FZ4DIPYWtqL9DU1KYDbn2aP2c88HgtnmTg4OdwqtwezsidEOVZf2gfW+bpF0+P7pLNguMQB+C2iVl2Ic5QAAAhF6VFh0TU9MNSByZGtpdCAyMDIyLjA5LjEAAHicfVTbihsxDH3PV/gHMuhmS3rcJEtZyk6gTfsPhT72/6nkIWsvmJ2Jhe05lmSdo5xKPj9u3//8Kx8P3U6nUuCLn7uX3wwAp/eSk3J5/fa2l+vj5fLcud5/7Y+fhbAQx5l4P2NfHvf35w6Wa+FNqzpJTDhmaAU26M84SQfOm6gU3EwbIS9wHLi6IQpXCxxWN2kLnJS90FZRUSKJDZxB6wJXAxduOBxl3NY0Ii9wLeJChGummX4lbagLnAbujBuziWB8b9IAfQG0A+jGNQJSfidYZegJ5E3UzBKIaA1WoRESKRuTg2XswButiojByt9yrpuRCPT6ABKtoiMd4ZuxNyhniESQ29Irl3vGryxRzbycQpR/xQ5Keo27mDXpXqu5NllBa6+8R57YEqlJ6vL+B0cVObg+vLvKMlMN1s/ptEaqCa3shMv7WxdIlcoEWQhSI1+G9y5hAIFgPnw6BQErn+FoD6SkJCHrJA7qy67I9qGN3ZStFx8oKFsgX/fbp747OvFy32+jE/Ol0XCxKDz6Kpcy2iffOrokFqWNZsAYOjQvMWwoW2L40K/EwFmm2A1OcpS+Q5PqsBuexCV9RyYNSWZSJ6VIGmyTIrAbnZiXvmMTwZIGfSJS0tBMmKQhnIiRbj42KA/JKArxgRj5JUUzIbl+/q3G/PQfgUMOPdgFf9EAAAEWelRYdFNNSUxFUzUgcmRraXQgMjAyMi4wOS4xAAB4nB2QOW7FMAxEr5LSBmSC+wKX7n8OoTbwCf7hQwlQITwOh0M+z/GcL73zuCbPOY/n75zH7zm53zw+5zvfyfTzPQTCongISH943A3KNQZBhjON24BIxRuQVdq4GYyCtAGWYI67K9K1Bu4RPm5sqWfkQDAOpxj3RSCSqo1cHak2qhTzwYCIa9QloJGZTYjSF1EQLlxOmZwsjQySdY9H2kDAU8rHhd1O4rL7TJSaEQQGdeyrTTNdl8yyon8dtLRddmusrWIxIxGMsRsqWnYtnWm7NDOplZXA1IRHT+dIWYdDVNQlKe6wi2j72Mqga4e+nFTGTqDIa4nz+w8e8lf5yH6L5QAAAbJ6VFh0cmRraXRQS0w2IHJka2l0IDIwMjIuMDkuMQAAeJx7v2/tPQYg4GWAAEYgFgNiSSBuYGRjSACJMUNoZjif3UEDxIfTbBCaBUFngMUZkRgQGXYHC7BJzLiVYBGA6mUASzAyIayFqkR3BzfQH4xMQIcC2QksrBlMrGwKbOwZTOwcCRycGUycXAlc3AncPBlMPLwJvHxAaf4EfoEMJgFBBQGhBCHhDCZhkQQR0QwmUeYEPrYEUf4EXs4EERZWZhZWflE2dg5OXj42Vi5OXh5uNgEhYRFRfnEhRkjQgYHYHkNfB93NZQ4gzrubqQ4LX0uC2XucFzokPmIAs6deUXRYE7XGHsRWFGuz/37sFJid67HLLoG/3g7EjlPo3x/J3m8DYi/xubJf4f6G/SB2/3+PA+9bzoHZIQubDvy3fbIPxFbr33TgV9UuMNv+8b4DkR+6wGYyTpl2QF7vM5jdtibpQLV4CZjteZn5QM/G6WD2Jr5t9l2BAWAzP85dbc/2QfgAiP09yNq6KcIezN5tpuagl+wBZt+/Vu2w6ZcMmL2gvcHBpqYErLd2uYFD3j4usBvEAD72cldKrO9+AAACH3pUWHRNT0w2IHJka2l0IDIwMjIuMDkuMQAAeJx9lFuOWyEMht+zCjYQ5CvYj5NkVFXVJFKbdg997/5VmzQDkVDPCRZwPsDGv3Mo+Xy/fPv9p3w+dDkcSoH//Ny9/GIAOHyU7JTT+5ev13K+v52eM+fbz+v9RyEqpLEm3lf27X77eM5gOReuBA0bRsdUmrUCFcYzV9Lg1FGoFaoCCtA3HAenFdgVLThANtxxUq7xWclazGJlabrlNDisIF01OTVB33EtzoXKjY0lOiQORhuuB3fEihhuaX7HLg02oD3Apqbm2YtADHxDepJcMe7EbaxBFt4djpCo1HANXcoRqoh20x2KEfhRq3b3PlBuEqt2aOYmUG9KkpcEmcVdTMiP8zuoth6kuZtsj5dHUCrYLbdyZTHekZpkZFq9d4w90RRhJyHMHGEVIibOiAy5i+zIPkgW6Npzc0ZU2vppcU05TZGmJN3CjZ1A4uqG4ryD48gXI+guIoKhdWdxh9xTQqaAOzKTFOnEFveZEXmolLZk5ohqb0CP2JFVfKeR9+vlpUAfJXu6XS+zZPOlWZkxKDwLMIcy6yxfneUUg9Jm1WC0PotDotksAYnmU+cSDVc1SxrERbSSBmnRpqRBXjQoaVAWrUka1EVTkr61RTqSBvsiERzGFinImPEl5ZKG1tRKGsIlhZKGaEmVDPM5MTzWeU0kD2L6R/ovhJc0rknL8fM/OvqHv7ifG/3U3PaDAAABInpUWHRTTUlMRVM2IHJka2l0IDIwMjIuMDkuMQAAeJwdkDtuxDAMRK+S0gvIBH8jkXC5TapcIEil3ifYw4d0JemJHM7w/T7er1vufZxb9972e3//9bn1VeD4ed373ipfn8NIecocRgGfOS4jpLgNJWewjAvEltACLBY6LiVozCFkPotfQuwLKIDwejPZtDAfTOrJ3XIKiYREIZblyPmwiUCOulj91ajTSJxnkylWJq7TqQSkipjcsQLFQFiZq5lN799mWWa8THAHeToXA6tIZIY/6nBZbSJhHi1foZCriyQg0mFc1bS1Q2y5NzLnVa6UTARPQmYNdMaCGVmivZZcXE4rhAmjV5nmmV3jtbJxVRiZmC2eAKt015qszzwxeOp4ff4BP7xcrQgMtGUAAAG/elRYdHJka2l0UEtMNyByZGtpdCAyMDIyLjA5LjEAAHice79v7T0GIOBlgABGIBYHYikgbmBkY0gAiTFDaGY4n91BA8SH02wQmgVBZ4DFGZEYqCrYGcASjEwIoyzAAsxYzCCgFa4S3TncQO8wMgHdC2QnsLBmMLGyKbCxZzCxcyRwcGYwcXIlcHErcPFkMPHwJvDyJfDxA1UIJAgIZjAJCikICicIi2QwiYgmiIplMIkxJ/CzJYgJJPBxJoiwsDKzsAqIsbFzcPLxs7FycfLx8rAJCouIigmIyzFCAhEMxFNmZDnwVhU4gDh/ftc57F4lBGZfMV3rsO/aK3sQ+/l7c4du0yVg9sLHm+03uZwGs+N8Ne31zSfZgdiCGSH7Hxz9aQtiO9Vt32+rumA/iF2rY31gldhWMHvPl+IDr4yD9oHYZ/esPLCpL2kviG2y8eSBJZHTwGpmvtt8QL9rC9h86cquAzHLuMDume/ve0C2eipYvO3I7f3dOavA7FnHrtrvFQkG65085ZA9n5fIARC7z1/GbvkeazB7mpm+Q0iMD5j9ObbZYfdLFTC7VKvDYcfJLrDeeRlODsmaoWC3iQEAHi13vM6nG4AAAAI5elRYdE1PTDcgcmRraXQgMjAyMi4wOS4xAAB4nH1UW64bIQz9n1WwgSA/sfm8Sa6qqroTqU27h/53/6pNmjtEQoVgAXPANuc4W8n2/frt95/y2ei6baXAf3699/KLAWD7KDkp5/cvX/dyub+dnzuX28/9/qMQF2pxJvor9u1++3juYLkUrq2pKsbE1ER6gQqjHSdp4LoL5qJSx2a4wHHgtAqSExasztLMFzgpe1zjJoAWuIC7ywKngcMqoByfsao78ArXwi9EHshsMSFXNVvgLHAnqE7dkOM7EnZdJewJDM/MKpgzUkRuC2RPJNVOoh3GGRTTVZAICeXqiI6UcRAo2epSTGJOWhkkQk0oqHIcWkAp3ujUAhpvOEJFk4YrdiLlPW9tRB5uM1QIglbIJOgklcnIQ0gVWxNYJqWPpAisu8adoQwnWCHb400NW+dEMqPw0nvShLUZYKh48CUaRxZIH0glwKAxaGA0WHvvkVEQrtTEBmHM7EutwxCnsRlYpoadcemdkiWpGCxGIHGnWrO24pOSJAkRKcZzxiOAC/mKI+JRasDWwufQiOPyzvf9+lLLj+o+3/brUd3Z6SjiWBQ+ajWXcpRkdj0qLxalHQWGMeyoI4nhR7VIjH6UhMTAWfiSBnHSNw5Dk4xl7PCkVkmDMqlS0qBO6stlaGtSmWS0NolJ0qBPosFh+iQOyR2aRSBpCCeyJQ3RRKqkIZ7Ik2E+N0bE08ORPhBHfNT+pfBC7Exjrp9/8DHf/gLF9icc9lba0QAAASx6VFh0U01JTEVTNyByZGtpdCAyMDIyLjA5LjEAAHicHZE7bsQwDESvktIGtAT/lOBym1S5QJBKvU+wh8/QnfxEjebJ7/fxPm+59/Hauve2ffyc9+/9/YelnmD9ve+t8vU5jDIjYhhVlMe4jNZ0saGkS7LGFeSiU4fQNM85LqVZzg2AJ4CQc9gEiDnZxsUIFbMajJGIQsqLaeoqBDOJyooFhoNm4QMLDREHUlrq2Ow98UKhl9EUmTIQoRxaCRZk7NaII0yk0xKs++ColKc8Y6mNOoy9aziZlk7oSaY/6cq1egS20OxWJbkMxEzc2y+LRcfj4GHRKJQlB/qaFB4DzhKauKMVzGz1Q5VVobiRLGs9J4GB9kxU9rs4zEOe0jwdxfAD2ArVHt2JluP8/AMgmGC4DsmFJAAAAbJ6VFh0cmRraXRQS0w4IHJka2l0IDIwMjIuMDkuMQAAeJx7v2/tPQYg4GWAAEYgFgNiSSBuYGRjSACJMUNoZjif3UEDxIfTbBCaBUFngMUZkRi4ZNgdLMBmM2NRgmoqOwNYgpEJYS3cDFR3cAP9wcgEdCiQncDCmsHEyqbAxp7BxM6RwMGZwcTJlcDFncHEzZPAw5vAyweU5k/gF8hgEhBUEBBKEBLOYBIWSRARzWASZU7gY0sQ5U/g5UwQYWFlZmHlF2Vj5+Dk5WNj5eLk5eFmExASFhHlFxdihAQdGIjtMfR10N1c5gDivLuZ6rDwtSSYvcd5oUPiIwYwe+oVRYc1UWvsQWxFsTb778dOgdm5HrvsEvjr7UDsOIX+/ZHs/TYg9hKfK/sV7m/YD2L3//c48L7lHJgdsrDpwH/bJ/tAbLX+TQd+Ve0Cs+0f7zsQ+aELbCbjlGkH5PU+g9lta5IOVIuXgNmel5kP9GycDmZv4ttm3xUYADbz49zV9mwfhA+A2N+DrK2bIuzB7N1mag56yR5g9v1r1Q6bfsmA2QvaGxxsakrAemuXGzjk7eMCu0EMAEHrclcwe4SIAAACIHpUWHRNT0w4IHJka2l0IDIwMjIuMDkuMQAAeJx9lFuOWyEMht+zCjYQ5CvYj5NkVFXVJFKbdg997/5VmzQDkVDPCRZwPsDGv3Mo+Xy/fPv9p3w+dDkcSoH//Ny9/GIAOHyU7JTT+5ev13K+v52eM+fbz+v9RyEqpLEm3lf27X77eM5gOReuBA0bRsdUmrUCFcYzV9Lg1FGoFaoCCtA3HAenFdgVLThANtxxUq7xWclazGJlabrlNDisIF01OTVB33EtzoXKjY0lOiQORhuuB3fEihhuaX7HLg02oD3Apqbm2YtADHxDepJcMe7EbaxBFt4djpCo1HANXcoRqoh20x2aiTlq1e7eB8pNYtUOpQfqTUnykiCzuIsJOW4zzu+g2nqQ5m6yPV4eQalgt9zKlcV4R2qSkWn13jH2RFOEnYQwc4RViJg4IzLkLrIj+yBZoGvPzRlRaeunRUQ5TZGmJN3CjZ1A4uqG4ryD48gXI+guIoKhdWdxh9xTQqaAOxJjz0gntrjPjMhDpbQlM0dUewN6xI6s4juNvF8vLwX6KNnT7XqZJZsvzcqMQeFZgDmUWWf56iynGJQ2qwaj9VkcEs1mCUg0nzqXaLiqWdIgLqKVNEiLNiUN8qJBSYOyaE3SoC6akvStLdKRNNgXieAwtkhBxowvKZc0tKZW0hAuKZQ0REuqZJjPieGxzmsieRDTP9J/IbykcU1ajp//0dE//AW0+Bv9pORJrAAAASJ6VFh0U01JTEVTOCByZGtpdCAyMDIyLjA5LjEAAHicHZA7bsQwDESvktILyAR/I5FwuU2qXCBIpd4n2MOHdCXpiRzO8P0+3q9b7n2cW/fetvfv/f1Xp74KHD+ve99b5etzGClPmcMo4DPHZYQUt6HkDJZxgdgSWoDFQselBI05hMxn8UuIfQEFEF5vJpsW5oNJPblbTiGRkCjEshw5HzYRyFEXq78adRqJ82wyxcrEdTqVgFQRkztWoBgIK3M1s+n92yzLjJcJ7iBP52JgFYnM8EcdLqtNJMyj5SsUcnWRBEQ6jKuatnaILfdG5rzKlZKJ4EnIrIHOWDAjS7TXkovLaYUwYfQq0zyza7xWNq4KIxOzxRNgle5ak/WZJwZPHa/PPz/4XK3w1e3cAAABxnpUWHRyZGtpdFBLTDkgcmRraXQgMjAyMi4wOS4xAAB4nHu/b+09BiDgZYAARiAWB2IpIG5gZGfIANLMjExsDhogBgs7hGZmcwBLMDMiBCAKcNNQDUgMiIwygwLIXhiXA2olI4YVcKsYEsAqIDQTEy6am4FRgZEpg4mJOYGZJYOJhTWBlS2DiY09gZ1DgYMzg4mTK4GLO4OJm4eBmzeBl0+Blz+DiV0gg0lAMEFQiEFImEFYhEFElEFUjIGNMYGfI0FMiEGQNUGEhY2RjZWFmYmNk4ubl5+DVYCdjVWQVVhITFREXI4REoJgIP7R5by9zhrbAyDOrMcidveuaYPZrmah+03nloDZFxYKH3h+PAnMdokyPuCowwFmf6p5uX/59Nr9IPalwM37CsoWgdlX+/ba7RG3swWxX119az+vu8gOxL4oauigdrMErKZMvcNhl7gLmD113SyH/apy9iC2kvcpB63nfmC2n1G1w7MLz8FsN4UJDhfLfRxAbJOf0g4GBech4j0a+9vXTwSzr7xjONA68x/Yrmyl0APd92aDxcW/Tz1wepUwmN37cNsBvSlXweymy/MPrPtrBzbzWFDigQQNXTBbDAAep3VGY+xQ6wAAAj16VFh0TU9MOSByZGtpdCAyMDIyLjA5LjEAAHicfVRbbhsxDPz3KXQBC+JT4mdsB0VRxAZat3fob9D7o8M1nFVQobsRIcmzfM0wh5LP98u333/Kx8OXw6GU9p+/iCi/pLV2eCu5KafXL1+v5Xx/OT1vzref1/uPwlLY8Q3ez9iX++3teUPlWqg6BQeVI9dwcZHSatue/VMuZ9ySmiABAH1ojFgABR6PrQ7hYUBKHcwtbIFUuIQnad6NEmkqit2/SEufXEdjGZo74t7bCunpkxBTCcUjj4hmy+g9ka2KwanmN+zBsqpobKVLB7Dlz+raVrgADqFttMjUWHz4KkcCRYVrdw/rW47mKmOFJCC1sumgDdndYvQVkjfkEBmUMZ169xWPJOX0XrwKk3cGYLTBtGoQJT9SgzXUsjCitnZp5YbY1iQU/FcKpLsE+la4opUjPTo3p2WH+kNEbkMCx0ooy1c9p/GQRoMyezZGo7Mvy0l6IDKRxpAG+EaLeOWTk5+jQuIOFQFg3QevfHLyc7TaCcVLVuSgf4nkh89AL1EIBm0orwdNHnkamoOKoJNmtpy01+vl0yw/pvt0u1726c6X9xlWLNknVXPt45iv7TOHQ/F9sBSr79OjWGMfEcKKfRIUi2bFaxqiSdmahnhSMG1GJqnqdqOTJGkzNmlPtxufRKaZT5/EpGloTKKhzcQkDkrDswgoDdNENqVhnkjNIyibyMu+7IhsKTL6CAQZUaL20Jz5IhmfaZ1JzPPz3zv2h7+KHidayktrygAAASZ6VFh0U01JTEVTOSByZGtpdCAyMDIyLjA5LjEAAHicHZE5bsQwDEWvktIGbIH7gukyfXII9S5Sz+HzJReG8UT+R8o/k5/5TJk8jxuvOY/vv3Mev+fk83nkzW88/PU5eAS39HXL6NDQ60WDzbU3ijJ8vG4apVIOpqNEGEiGUqQv4qbmGxWJ1mpkyQRhVBvrhYBu8vadpY4yu3Aq0WJLqQl00SALowZCpxc1kGhUwCgjIzp2lofB87IhbiULZXhXLlSqxegLzlz7xFDhSJCiEsYIOmDFLHAwU6wmJ4VVB7fVdhkmalSE0JLDEF66CCM+97aEiyrkWqfEWk2H6toDi0EO9224wrA1jmeUrCIfydCt7MCOu6jbPC/8gjLRHeTwFkiS49rPzz+YvmAySFb7XAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Ten molecules from second largest cluster:\")\n",
    "# Draw molecules\n",
    "Draw.MolsToGridImage(\n",
    "    [compounds[i][0] for i in clusters[1][:10]],\n",
    "    legends=[compounds[i][1] for i in clusters[1][:10]],\n",
    "    molsPerRow=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first ten molecules in the respective clusters look indeed similar to each other and many share a common scaffold (visually detected). \n",
    "\n",
    "See **Talktorial T006** for more information on how to calculate the maximum common substructure (MCS) of a set of molecules."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Examples from first 10 clusters\n",
    "\n",
    "For comparison, we have a look at the cluster centers of the first 10 clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ten molecules from first 10 clusters:\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Ten molecules from first 10 clusters:\")\n",
    "# Draw molecules\n",
    "Draw.MolsToGridImage(\n",
    "    [compounds[clusters[i][0]][0] for i in range(10)],\n",
    "    legends=[compounds[clusters[i][0]][1] for i in range(10)],\n",
    "    molsPerRow=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save cluster centers from first 3 clusters as SVG file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate image\n",
    "img = Draw.MolsToGridImage(\n",
    "    [compounds[clusters[i][0]][0] for i in range(0, 3)],\n",
    "    legends=[f\"Cluster {i}\" for i in range(1, 4)],\n",
    "    subImgSize=(200, 200),\n",
    "    useSVG=True,\n",
    ")\n",
    "\n",
    "# Patch RAW svg data: convert non-transparent to transparent background and set font size\n",
    "molsvg = img.data.replace(\"opacity:1.0\", \"opacity:0.0\").replace(\"12px\", \"20px\")\n",
    "\n",
    "# Save altered SVG data to file\n",
    "with open(DATA / \"cluster_representatives.svg\", \"w\") as f:\n",
    "    f.write(molsvg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While still some similarity is visible, clearly, the centroids from the different clusters look more dissimilar then the compounds within one cluster."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Intra-cluster Tanimoto similarities\n",
    "\n",
    "We can also have a look at the intra-cluster Tanimoto similarities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def intra_tanimoto(fps_clusters):\n",
    "    \"\"\"Function to compute Tanimoto similarity for all pairs of fingerprints in each cluster\"\"\"\n",
    "    intra_similarity = []\n",
    "    # Calculate intra similarity per cluster\n",
    "    for cluster in fps_clusters:\n",
    "        # Tanimoto distance matrix function converted to similarity matrix (1-distance)\n",
    "        intra_similarity.append([1 - x for x in tanimoto_distance_matrix(cluster)])\n",
    "    return intra_similarity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Recompute fingerprints for 10 first clusters\n",
    "mol_fps_per_cluster = []\n",
    "for cluster in clusters[:10]:\n",
    "    mol_fps_per_cluster.append([rdkit_gen.GetFingerprint(compounds[i][0]) for i in cluster])\n",
    "\n",
    "# Compute intra-cluster similarity\n",
    "intra_sim = intra_tanimoto(mol_fps_per_cluster)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Violin plot with intra-cluster similarity\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 5))\n",
    "indices = list(range(10))\n",
    "ax.set_xlabel(\"Cluster index\")\n",
    "ax.set_ylabel(\"Similarity\")\n",
    "ax.set_xticks(indices)\n",
    "ax.set_xticklabels(indices)\n",
    "ax.set_yticks(numpy.arange(0.6, 1.0, 0.1))\n",
    "ax.set_title(\"Intra-cluster Tanimoto similarity\", fontsize=13)\n",
    "r = ax.violinplot(intra_sim, indices, showmeans=True, showmedians=True, showextrema=False)\n",
    "r[\"cmeans\"].set_color(\"red\")\n",
    "# mean=red, median=blue"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Picking the final list of compounds\n",
    "\n",
    "In the following, we are going to pick a final list of **max. 1000 compounds** as a **diverse** subset. \n",
    "\n",
    "For this, we take the cluster centroid from each cluster (i.e. the first molecule of each cluster) and then for each cluster (starting with the largest one) we take the 10 molecules (or 50% if less than 10 molecules are left in the cluster) that are most similar to the centroid, until we have selected max. 1000 compounds. Thus, we have representatives of each cluster. \n",
    "\n",
    "Aim of this compound picking is to ensure the diversity for a smaller set of compounds which are proposed for testing in a confirmatory assay. \n",
    "\n",
    "> Picking procedure was adapted from [TDT tutorial notebook by S. Riniker and G. Landrum](https://github.com/sriniker/TDT-tutorial-2014/blob/master/TDT_challenge_tutorial.ipynb). \n",
    "\n",
    "As described there: the idea behind this approach is to ensure diversity (representatives of each cluster) while getting some SAR (structure-activity relationship) from the results of the confirmatory assay (groups of quite similar molecules from larger clusters retained)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get cluster centers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of cluster centers: 1128\n"
     ]
    }
   ],
   "source": [
    "# Get the cluster center of each cluster (first molecule in each cluster)\n",
    "cluster_centers = [compounds[c[0]] for c in clusters]\n",
    "# How many cluster centers/clusters do we have?\n",
    "print(\"Number of cluster centers:\", len(cluster_centers))\n",
    "# NBVAL_CHECK_OUTPUT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sort clusters by size and molecules in each cluster by similarity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort the molecules within a cluster based on their similarity\n",
    "# to the cluster center and sort the clusters based on their size\n",
    "sorted_clusters = []\n",
    "for cluster in clusters:\n",
    "    if len(cluster) <= 1:\n",
    "        continue  # Singletons\n",
    "    # else:\n",
    "    # Compute fingerprints for each cluster element\n",
    "    sorted_fingerprints = [rdkit_gen.GetFingerprint(compounds[i][0]) for i in cluster]\n",
    "    # Similarity of all cluster members to the cluster center\n",
    "    similarities = DataStructs.BulkTanimotoSimilarity(\n",
    "        sorted_fingerprints[0], sorted_fingerprints[1:]\n",
    "    )\n",
    "    # Add index of the molecule to its similarity (centroid excluded!)\n",
    "    similarities = list(zip(similarities, cluster[1:]))\n",
    "    # Sort in descending order by similarity\n",
    "    similarities.sort(reverse=True)\n",
    "    # Save cluster size and index of molecules in clusters_sort\n",
    "    sorted_clusters.append((len(similarities), [i for _, i in similarities]))\n",
    "    # Sort in descending order by cluster size\n",
    "    sorted_clusters.sort(reverse=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pick a maximum of 1000 compounds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# Selected molecules: 1128\n"
     ]
    }
   ],
   "source": [
    "# Count selected molecules, pick cluster centers first\n",
    "selected_molecules = cluster_centers.copy()\n",
    "# Take 10 molecules (or a maximum of 50%) of each cluster starting with the largest one\n",
    "index = 0\n",
    "pending = 1000 - len(selected_molecules)\n",
    "while pending > 0 and index < len(sorted_clusters):\n",
    "    # Take indices of sorted clusters\n",
    "    tmp_cluster = sorted_clusters[index][1]\n",
    "    # If the first cluster is > 10 big then take exactly 10 compounds\n",
    "    if sorted_clusters[index][0] > 10:\n",
    "        num_compounds = 10\n",
    "    # If smaller, take half of the molecules\n",
    "    else:\n",
    "        num_compounds = int(0.5 * len(tmp_cluster)) + 1\n",
    "    if num_compounds > pending:\n",
    "        num_compounds = pending\n",
    "    # Write picked molecules and their structures into list of lists called picked_fps\n",
    "    selected_molecules += [compounds[i] for i in tmp_cluster[:num_compounds]]\n",
    "    index += 1\n",
    "    pending = 1000 - len(selected_molecules)\n",
    "print(\"# Selected molecules:\", len(selected_molecules))\n",
    "# NBVAL_CHECK_OUTPUT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This set of diverse molecules could now be used for experimental testing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bonus: analysis of run times\n",
    "\n",
    "At the end of the talktorial, we can play with the size of the dataset and see how the Butina clustering run time changes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reuse old dataset\n",
    "sampled_mols = compounds.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that you can try out larger datasets, but data sizes larger than 10000 data points already start to consume quite some memory and time (that's why we stopped there). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper function for time computation\n",
    "def measure_runtime(sampled_mols):\n",
    "    start_time = time.time()\n",
    "    sampled_fingerprints = [rdkit_gen.GetFingerprint(m) for m, idx in sampled_mols]\n",
    "    # Run the clustering with the dataset\n",
    "    sampled_clusters = cluster_fingerprints(sampled_fingerprints, cutoff=0.3)\n",
    "    return time.time() - start_time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4635"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sampled_mols)\n",
    "# NBVAL_CHECK_OUTPUT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset size 100, time 0.07 seconds\n",
      "Dataset size 500, time 0.37 seconds\n",
      "Dataset size 1000, time 0.71 seconds\n",
      "Dataset size 2000, time 1.79 seconds\n",
      "Dataset size 4000, time 6.54 seconds\n"
     ]
    }
   ],
   "source": [
    "sample_sizes = [100, 500, 1000, 2000, 4000]\n",
    "runtimes = []\n",
    "# Take random samples with replacement\n",
    "for size in sample_sizes:\n",
    "    time_taken = measure_runtime(random.sample(sampled_mols, size))\n",
    "    print(f\"Dataset size {size}, time {time_taken:4.2f} seconds\")\n",
    "    runtimes.append(time_taken)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.set_title(\"Runtime measurement of Butina Clustering with different dataset sizes\")\n",
    "ax.set_xlabel(\"# Molecules in data set\")\n",
    "ax.set_ylabel(\"Runtime in seconds\")\n",
    "ax.plot(sample_sizes, runtimes, \"g^\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how the runtime is not exactly proportional to the sample size! It grows faster!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Discussion\n",
    "\n",
    "We have introduced the Butina algorithm to cluster a compound dataset and discussed how to pick a reasonable clustering threshold. The clustering was rationalized by looking at example compounds from different clusters and by checking intra-cluster similarities. Finally, the clusters were used to pick a divers subset of compounds."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quiz\n",
    "* Why is clustering of molecules important?\n",
    "* Which algorithms can you use to cluster a set of molecules and what is the general idea behind the algorithm?\n",
    "* Do you know other clustering algorithms?"
   ]
  }
 ],
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   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "pygments_lexer": "ipython3",
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