{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Conformational analysis of CXCL12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "In this tutorial, we demonstrate how to use the HTMD code for doing conformational analysis.\n",
    "\n",
    "To analyze, one needs MD trajectories first, which can be generated with HTMD. Here, we already provide the trajectories (data) to analyze. You can download the data from [here](http://pub.htmd.org/tutorials/cxcl12-conformational-analysis/cxcl12_filtered.tar.gz). (**Warning: 2.6 GB filesize**)\n",
    "\n",
    "Alternatively, you can download the dataset using `wget`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "assert os.system('wget -rcN -np -nH -q --cut-dirs=2 -R index.html* http://pub.htmd.org/tutorials/cxcl12-conformational-analysis/cxcl12_filtered/') == 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Getting started"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we import the modules we are going to need for the tutorial:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-12 11:17:00,407 - numexpr.utils - INFO - Note: NumExpr detected 32 cores but \"NUMEXPR_MAX_THREADS\" not set, so enforcing safe limit of 8.\n",
      "2024-06-12 11:17:00,408 - numexpr.utils - INFO - NumExpr defaulting to 8 threads.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Please cite HTMD: Doerr et al.(2016)JCTC,12,1845. https://dx.doi.org/10.1021/acs.jctc.6b00049\n",
      "HTMD Documentation at: https://software.acellera.com/htmd/\n",
      "\n",
      "You are on the latest HTMD version (2.3.28+11.g37253b25b.dirty).\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from htmd.ui import *\n",
    "from matplotlib import pylab as plt\n",
    "from moleculekit.config import config\n",
    "\n",
    "config(viewer='webgl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Introduction to CXCL12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "CXCL12 is a chemokine involved in...\n",
    "\n",
    "*  many types of cancer \n",
    "*  inflammatory diseases \n",
    "*  early development events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "![system](img/system-protein2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Sampling major conformational states"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "There are many different metrics to assess the overall conformational changes of a protein. From them all, phi and psi angles of the protein backbone (dihedrals) have been the most successful descriptors in \"blindly\" capturing the major protein conformations.\n",
    "\n",
    "In this section we will project our trajectories on the backbone dihedrals and, we will reduce the dimensionality by using tICA and then we will build a Markov Model to asses the major protein conformations in equilibrium."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "![conformations](img/conformations.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Load the trajectories into a simlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Creating simlist: 100%|████████████████████████████████████████████████████████████████████| 289/289 [00:01<00:00, 175.70it/s]\n"
     ]
    }
   ],
   "source": [
    "fsims = simlist(glob('./cxcl12_filtered/*/'), './cxcl12_filtered/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Calculate metrics: protein backbone dihedrals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CXCL12 has a very flexible C-terminus loop as well as a transiently disorderable N-terminal alfa helix. In this study we are not interested in them but in the core of the chemokine. For this reason, we will select residues from 10 to 54. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Projecting trajectories:  54%|█████████████████████████████████▍                            | 156/289 [00:37<00:30,  4.30it/s]xtc_read(): XTC file is corrupt\n",
      "2024-06-12 11:17:42,406 - htmd.projections.metric - WARNING - Error while projecting simulation id: 156. \"negative dimensions are not allowed\"\n",
      "Projecting trajectories: 100%|██████████████████████████████████████████████████████████████| 289/289 [01:08<00:00,  4.20it/s]\n",
      "2024-06-12 11:18:13,682 - htmd.projections.metric - WARNING - Multiple framesteps [0.0, 0.1] ns were read from the simulations. Taking the statistical mode: 0.1ns. If it looks wrong, you can modify it by manually setting the MetricData.fstep property.\n"
     ]
    }
   ],
   "source": [
    "metr = Metric(fsims)\n",
    "metr.set(MetricDihedral(protsel='protein and resid 10 to 54', sincos=True))\n",
    "data = metr.project()\n",
    "data.fstep = 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plotTrajSizes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-12 11:18:13,772 - htmd.metricdata - INFO - Dropped 1 trajectories from 288 resulting in 287\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([145])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dropTraj()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "##  Dimensionality reduction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "tica = TICA(data, 20)\n",
    "dataTica = tica.project(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-12 11:18:16,315 - htmd.metricdata - INFO - Mergesmall removed 0 clusters. Original ncluster 200, new ncluster 200.\n"
     ]
    }
   ],
   "source": [
    "dataTica.cluster(MiniBatchKMeans(n_clusters=200), mergesmall=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## MSM analysis and visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Estimating Timescales: 100%|██████████████████████████████████████████████████████████████████| 20/20 [00:15<00:00,  1.29it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = Model(dataTica)\n",
    "model.plotTimescales(lags=list(range(1,100,5)), units=\"ns\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Build Markov Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-12 11:18:33,788 - htmd.model - INFO - 99.7% of the data was used\n",
      "2024-06-12 11:18:33,803 - htmd.model - INFO - Number of trajectories that visited each macrostate:\n",
      "2024-06-12 11:18:33,804 - htmd.model - INFO - [ 10   5 287  30  15 111  11  12]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.markovModel(60, 8, units=\"ns\")\n",
    "eqDist = model.eqDistribution()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "We can now visualize representatives for each of the equilibrium species"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Getting state Molecules: 100%|██████████████████████████████████████████████████████████████████| 8/8 [00:00<00:00, 27.15it/s]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9106d3771cf0432c97dde5fd6bfc5669",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0213bd63bfe64eeeaede3d17311943c0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Checkbox(value=True, description='macro 0'), Checkbox(value=True, description='macro 1'), Check…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "088b2ab46e9846a8a4d35b56a6eb1c65",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.numsamples=1\n",
    "model.viewStates(protein=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Statistics: What are the major differences between the states X and Y?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\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>type</th>\n",
       "      <th>atomIndexes</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[253, 255, 262, 264]</td>\n",
       "      <td>Sine of angle of (SER 16 N A A) (SER 16 CA A A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[253, 255, 262, 264]</td>\n",
       "      <td>Cosine of angle of (SER 16 N A A) (SER 16 CA A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[262, 264, 266, 279]</td>\n",
       "      <td>Sine of angle of (SER 16 C A A) (HSD 17 N A A)...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[371, 373, 391, 393]</td>\n",
       "      <td>Sine of angle of (LYS 24 N A A) (LYS 24 CA A A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[371, 373, 391, 393]</td>\n",
       "      <td>Cosine of angle of (LYS 24 N A A) (LYS 24 CA A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[391, 393, 395, 408]</td>\n",
       "      <td>Sine of angle of (LYS 24 C A A) (HSD 25 N A A)...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[391, 393, 395, 408]</td>\n",
       "      <td>Cosine of angle of (LYS 24 C A A) (HSD 25 N A ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[393, 395, 408, 410]</td>\n",
       "      <td>Cosine of angle of (HSD 25 N A A) (HSD 25 CA A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[517, 521, 529, 531]</td>\n",
       "      <td>Sine of angle of (PRO 32 N A A) (PRO 32 CA A A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[517, 521, 529, 531]</td>\n",
       "      <td>Cosine of angle of (PRO 32 N A A) (PRO 32 CA A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[529, 531, 533, 543]</td>\n",
       "      <td>Sine of angle of (PRO 32 C A A) (ASN 33 N A A)...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[711, 713, 723, 725]</td>\n",
       "      <td>Sine of angle of (ASN 44 N A A) (ASN 44 CA A A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[711, 713, 723, 725]</td>\n",
       "      <td>Cosine of angle of (ASN 44 N A A) (ASN 44 CA A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>dihedral</td>\n",
       "      <td>[723, 725, 727, 737]</td>\n",
       "      <td>Sine of angle of (ASN 44 C A A) (ASN 45 N A A)...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         type           atomIndexes  \\\n",
       "24   dihedral  [253, 255, 262, 264]   \n",
       "25   dihedral  [253, 255, 262, 264]   \n",
       "26   dihedral  [262, 264, 266, 279]   \n",
       "56   dihedral  [371, 373, 391, 393]   \n",
       "57   dihedral  [371, 373, 391, 393]   \n",
       "58   dihedral  [391, 393, 395, 408]   \n",
       "59   dihedral  [391, 393, 395, 408]   \n",
       "61   dihedral  [393, 395, 408, 410]   \n",
       "88   dihedral  [517, 521, 529, 531]   \n",
       "89   dihedral  [517, 521, 529, 531]   \n",
       "90   dihedral  [529, 531, 533, 543]   \n",
       "136  dihedral  [711, 713, 723, 725]   \n",
       "137  dihedral  [711, 713, 723, 725]   \n",
       "138  dihedral  [723, 725, 727, 737]   \n",
       "\n",
       "                                           description  \n",
       "24   Sine of angle of (SER 16 N A A) (SER 16 CA A A...  \n",
       "25   Cosine of angle of (SER 16 N A A) (SER 16 CA A...  \n",
       "26   Sine of angle of (SER 16 C A A) (HSD 17 N A A)...  \n",
       "56   Sine of angle of (LYS 24 N A A) (LYS 24 CA A A...  \n",
       "57   Cosine of angle of (LYS 24 N A A) (LYS 24 CA A...  \n",
       "58   Sine of angle of (LYS 24 C A A) (HSD 25 N A A)...  \n",
       "59   Cosine of angle of (LYS 24 C A A) (HSD 25 N A ...  \n",
       "61   Cosine of angle of (HSD 25 N A A) (HSD 25 CA A...  \n",
       "88   Sine of angle of (PRO 32 N A A) (PRO 32 CA A A...  \n",
       "89   Cosine of angle of (PRO 32 N A A) (PRO 32 CA A...  \n",
       "90   Sine of angle of (PRO 32 C A A) (ASN 33 N A A)...  \n",
       "136  Sine of angle of (ASN 44 N A A) (ASN 44 CA A A...  \n",
       "137  Cosine of angle of (ASN 44 N A A) (ASN 44 CA A...  \n",
       "138  Sine of angle of (ASN 44 C A A) (ASN 45 N A A)...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "means = getStateStatistic(model, data, range(model.macronum))\n",
    "plt.figure()\n",
    "plt.bar(range(len(means[0])), means[-1] - means[-2])\n",
    "idx = np.where(np.abs(means[-1] - means[-2]) > 0.6)[0]\n",
    "data.map.iloc[idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c35cd5b6c9974aaca0b52aabd2df925e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# we can visualize which residues are different between states\n",
    "filtered = Molecule('./cxcl12_filtered/filtered.pdb')\n",
    "filtered.view(sel='protein',style='NewCartoon',hold=True)\n",
    "filtered.view(sel='resid 16 17 24 25 32 33 44 45',style='Licorice')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Mapping back: Which trajectory originated the state X?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 7,  8, 42, 51]),)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(model.macro_ofmicro == 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[array([[ 166, 1371],\n",
      "       [ 234,  806],\n",
      "       [ 149, 1108],\n",
      "       [  80,  666],\n",
      "       [ 265,  812],\n",
      "       [  87, 1404],\n",
      "       [ 243,  370],\n",
      "       [ 157, 1808],\n",
      "       [ 204, 1231],\n",
      "       [ 166, 1656]])]\n"
     ]
    }
   ],
   "source": [
    "_,rel = model.sampleStates(10, 10, statetype='micro')\n",
    "print(rel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "simid = 234\n",
      "parent = None\n",
      "input = []\n",
      "trajectory = ['./cxcl12_filtered/9x11/9x11-GERARD_VERYLONG_CXCL12_confAna-0-1-RND0109_9.filtered.xtc']\n",
      "molfile = ['./cxcl12_filtered/filtered.pdb', './cxcl12_filtered/filtered.psf']\n",
      "numframes = [None]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(model.data.simlist[232])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Studying a defined reaction coordinate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Revising the literature related to CXCL12, we find a paper published by Andrea Bernini et al. (2014), where they describe the opening of a pocket in CXCL12 located between the 2nd and 3rd beta sheet (see figure). To try to capture this phenomenon in our simulations, we will project our trajectories along the 2nd and 3rd beta-sheet distance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "![openclose_struc](img/openclose_struc.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "_Figure taken from Bernini et al., 2014, 1844(3):561-6. DOI:10.1016/j.bbapap.2013.12.012._"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "The first selection corresponds to beta-sheet 2 carbons alpha, the second one to beta-sheet 3 CA.\n",
    "We specify `metric='contacts'` to create contact maps instead of proper distances. This means: create an interatom matrix and with 1's if the distance is below cutoff and 0's otherwise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Projecting trajectories:  54%|█████████████████████████████████▍                            | 156/289 [00:21<00:20,  6.51it/s]xtc_read(): XTC file is corrupt\n",
      "Projecting trajectories: 100%|██████████████████████████████████████████████████████████████| 289/289 [00:40<00:00,  7.22it/s]\n",
      "2024-06-12 11:21:01,367 - htmd.projections.metric - WARNING - Multiple framesteps [0.0, 0.1] ns were read from the simulations. Taking the statistical mode: 0.1ns. If it looks wrong, you can modify it by manually setting the MetricData.fstep property.\n"
     ]
    }
   ],
   "source": [
    "metr = Metric(fsims)\n",
    "metr.set(MetricDistance('resid 38 to 42 and noh', 'resid 22 to 28 and noh', periodic=None, metric='contacts'))\n",
    "data3 = metr.project()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## tICA projection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Dimensionality reduction along the slow process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "tica3 = TICA(data3, 20)\n",
    "dataTica3 = tica3.project(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-12 11:22:33,667 - htmd.metricdata - INFO - Mergesmall removed 0 clusters. Original ncluster 200, new ncluster 200.\n"
     ]
    }
   ],
   "source": [
    "dataTica3.cluster(MiniBatchKMeans(n_clusters=200), mergesmall=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Plot timescales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Estimating Timescales: 100%|██████████████████████████████████████████████████████████████████| 20/20 [00:01<00:00, 16.92it/s]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model3 = Model(dataTica3)\n",
    "model3.plotTimescales(lags=list(range(1,100,5)), units=\"ns\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Build a Markov Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "We want to pick a lagtime where the timescales are converged (timescale is flat). 600 is the lagtime we want to use (600 frames is equivalent to 60ns). 4 is the number of macrostates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-06-12 11:22:35,487 - htmd.model - INFO - 100.0% of the data was used\n",
      "2024-06-12 11:22:35,504 - htmd.model - INFO - Number of trajectories that visited each macrostate:\n",
      "2024-06-12 11:22:35,504 - htmd.model - INFO - [  4   3  19 289]\n",
      "2024-06-12 11:22:35,505 - htmd.model - INFO - Take care! Macro 1 has been visited only in 3 trajectories (1.0% of total):\n",
      "2024-06-12 11:22:35,505 - htmd.model - INFO - \n",
      "simid = 59\n",
      "parent = None\n",
      "input = []\n",
      "trajectory = ['./cxcl12_filtered/3x9/3x9-GERARD_VERYLONG_CXCL12_confAna-0-1-RND1251_9.filtered.xtc']\n",
      "molfile = ['./cxcl12_filtered/filtered.pdb', './cxcl12_filtered/filtered.psf']\n",
      "numframes = [None]\n",
      "\n",
      "2024-06-12 11:22:35,505 - htmd.model - INFO - \n",
      "simid = 277\n",
      "parent = None\n",
      "input = []\n",
      "trajectory = ['./cxcl12_filtered/10x23/10x23-GERARD_VERYLONG_CXCL12_confAna-0-1-RND9861_9.filtered.xtc']\n",
      "molfile = ['./cxcl12_filtered/filtered.pdb', './cxcl12_filtered/filtered.psf']\n",
      "numframes = [None]\n",
      "\n",
      "2024-06-12 11:22:35,506 - htmd.model - INFO - \n",
      "simid = 280\n",
      "parent = None\n",
      "input = []\n",
      "trajectory = ['./cxcl12_filtered/10x27/10x27-GERARD_VERYLONG_CXCL12_confAna-0-1-RND0101_9.filtered.xtc']\n",
      "molfile = ['./cxcl12_filtered/filtered.pdb', './cxcl12_filtered/filtered.psf']\n",
      "numframes = [None]\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model3.markovModel(60, 4, units=\"ns\")\n",
    "eqDist = model3.eqDistribution(plot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Visualize states"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Getting state Molecules: 100%|██████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 32.17it/s]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "086676b5b3864a2397686998375d8965",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Checkbox(value=True, description='macro 0'), Checkbox(value=True, description='macro 1'), Check…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "26fc2aa6f7c1422ab01577cad09aa08b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model3.viewStates(protein=True, numsamples=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Analyse Open Conformation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Did you see any macrostate where the pocket is open? What is the equilibrium population probability? Let's try to find the trajectory that produced the state..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "# Map back the trajectory/ies that originated the macro. Substitute 1 for the macro that showed the pocket opening.\n",
    "# This function is giving you the microclusters that are inside a given macrocluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 17,  23,  59, 114, 148]),)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(model3.macro_ofmicro ==1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[array([[  35, 1927],\n",
      "       [ 180, 1529],\n",
      "       [ 283,  255],\n",
      "       [  34, 1400],\n",
      "       [  67, 1430]])]\n"
     ]
    }
   ],
   "source": [
    "# substitute 48 for the micro number from the previous step\n",
    "# This function gives you trajectory-frame pairs that visited a given micro\n",
    "_, rel = model3.sampleStates(48, 5, statetype='micro')\n",
    "print(rel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "simid = 277\n",
      "parent = None\n",
      "input = []\n",
      "trajectory = ['./cxcl12_filtered/10x23/10x23-GERARD_VERYLONG_CXCL12_confAna-0-1-RND9861_9.filtered.xtc']\n",
      "molfile = ['./cxcl12_filtered/filtered.pdb', './cxcl12_filtered/filtered.psf']\n",
      "numframes = [None]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(model3.data.simlist[277])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Calculate RMSD of the site of interest for a selected trajectory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Creating simlist: 100%|████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 173.87it/s]\n"
     ]
    }
   ],
   "source": [
    "simus = simlist(glob('./cxcl12_filtered/10x23/'), './cxcl12_filtered/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Projecting trajectories: 100%|██████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00,  2.58it/s]\n",
      "2024-06-12 11:22:50,859 - htmd.projections.metric - INFO - Frame step 0.1ns was read from the trajectories. If it looks wrong, redefine it by manually setting the MetricData.fstep property.\n"
     ]
    }
   ],
   "source": [
    "refmol = Molecule('./cxcl12_filtered/filtered.pdb')\n",
    "metr = Metric(simus)\n",
    "metr.set(MetricRmsd(refmol, 'resid 38 to 42 or resid 22 to 28 and noh'))\n",
    "rmsd = metr.project()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Do you see the pocket opening at 50ns?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAioAAAGwCAYAAACHJU4LAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAACL2ElEQVR4nO2dd3wU5dbHf7PpPYSWQEIooSd0qVJElCqgXsULUiwoigW7iAjY8Oq1XBXR14KCIqAUC4qi9N57CxJ6QmgppGf3ef8Iu5mZnbo7m53dnO/ng2anPHNmZ3ae35xznvNwjDEGgiAIgiAIE2LxtgEEQRAEQRBykFAhCIIgCMK0kFAhCIIgCMK0kFAhCIIgCMK0kFAhCIIgCMK0kFAhCIIgCMK0kFAhCIIgCMK0BHrbAHew2Ww4f/48oqKiwHGct80hCIIgCEIDjDHk5+ejXr16sFiUfSY+LVTOnz+PpKQkb5tBEARBEIQLnDlzBomJiYrb+LRQiYqKAlBxotHR0V62hiAIgiAILeTl5SEpKcnRjyvh00LFHu6Jjo4moUIQBEEQPoaWtA1KpiUIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIgiAIwrSQUCEIL8IYQ3GZ1dtmEARBmBYSKgThRR6etxMtpq7AuZwib5tCEARhSkioEIQX+fPQBQDAou1nvGwJQRCEOSGhQhAmgOO8bQFBEIQ5IaFCECbAQkqFIAhCEhIqBGECLKRTCIIgJCGhQhAmgCOPCkEQhCQkVAjCBFDohyAIQhoSKgRhAij0QxAEIQ0JFYIwAeRRIQiCkIaECkGYgKrUKacvF+LAudyqOyBBEIQbBHrbAIIgqjaZttc7qwEAW1+6GXWjQ6vsuARBEK5AHhWCMAHeyFHJuFRQpcc7cfEacgpLq/SYBEH4PiRUCMIEeCNHhbGqO1bGpQL0fXctOr/5d9UdlCAIv4CECkGYAH8f9bPu2EUAQGm5zcuWEATha5BQIQgT4O8F3/KKyrxtAkEQPgoJFYIwAf4+PDmXhApBEC5CQoUgvITNVpkk4u+hnxIK+RAE4SIkVAjCS1gZX6hUvVKpykP6ucOIIAgPQkKFILyEledRgRc68qoc9UMQBOEqJFQIwkvwhYK/56gQBEG4CgkVgvASwtCPFw0hCIIwMSRUCMJLWG3ezVEhCILwBUioEISX4I/6odLyBEEQ0pBQIfwaQcKqyeCHfqb/cqhKjsm8lEFL/iKCIFyFhArht8zbfBJp0//AzlNXq/S4Z64U4qsNGSgsLVfczuYFEcXXKQzmFXEEQRB2SKgQfsvUnw6isNSKpxbuqdLjDv5wPV799RDe/O2w4nZWGh9MEAShCgkVwu+p6onw8oorPCkbj19W3M4bYSmSRgRB+BokVAi/p9RqzvLt3nCoeCtHhSAIwlVIqBB+T0mZ1dsmSFKdPCr+Pjs0QRCeg4QK4fd4y6OScakAY7/ahmIZoeSNHBXBIcm5QhCED0BChfB7yqze65HXHruIxbvOSq7zyqgfUicEQfgYXhUq06dPB8dxgn/x8fHeNIkgDKeoVJtH5cyVwqowhyAIwqfwukeldevWyMzMdPzbv3+/t00iCENZsuuc5HJxjsrtn2zyuC2US0sQhK8R6HUDAgM1e1FKSkpQUlLi+JyXl+cpswjCMA5lSt+nNlHqzKVrJZLbEQRBVGe87lFJT09HvXr10KhRI9xzzz04ceKE7LYzZ85ETEyM419SUlIVWkoQxnLVC/P7CDwqNBCHIAgfwKtCpUuXLpg7dy7++OMPfP7558jKykL37t1x+bJ0oazJkycjNzfX8e/MmTNVbDFBGMeYr7ZV+TEFybRVGAai0ckEQbiKV0M/AwcOdPydlpaGbt26oUmTJvjmm2/w9NNPO20fEhKCkJCQqjSR8FEyLhV42wQB5VYbAgMq3wv2nc3xih2Uo0IQhK/h9dAPn4iICKSlpSE9Pd3bphA+zpUCc+V7FIvK+A/9eKP0diYtTmckVB2XIAg9mEqolJSU4PDhw0hISPC2KYSPY7a+UGt13Fd/PeRRO8zwtZjt2hAEYW68KlSeffZZrF27FhkZGdi6dSv+9a9/IS8vD2PHjvWmWQRhOGKPihzzt572qB2HZUYgVSWkUwiC0INXc1TOnj2Lf//737h06RJq166Nrl27YsuWLUhOTvamWYQfYLbOsNwkEyPe9elmb5twPfRD2bUEQWjDq0JlwYIF3jw84ceYLbxgNnuAqhVzHE+YmPCrIAjCxJgqR4UgjMJsCZs2k9kDVMxD5A1M+FUQBGFiSKgQRBWgtW+2VGFE5P/WyRdX9CQ0MSJBEHogoUIQVYBWDw9XDSqjkUeFIAg9kFAh/BKz9YVaO2f/lykEQRD6IKFCEFWATatQ8aBSWXM023ON64A8KgRB6IGECuGXmK0z1JpMy3nQp/Lz3vMea1sNvgCjHBWCIPRAQoXwS8zWGWoO/Yh0ipH1VzwpgvRgNhFJEIS5IaFC+CVm6wxdGZ78zKK9aPfqSlzMN2beIrPk6Zrs0hAEYXJIqBB+iVVrUojJKOV5UBbvOotrJeVYuN2Ysvre1Cn8Y5utxg1BEOaGhArhl1hN1hlq9ahIbRZgMeZnSh4VgiB8ERIqhF9iM5lHxR3dFBRgEoVhECbTkARBmBwSKoRfYrbQj54clY3HLwk+BxhUrtabybQCb465Lg1BECaHhArhl5hMp+iy5/kf9wk+Bwb4W+jHZBeHIAhTQ0KF8EvMNwmgdnuuFJQKPgca5VExi1Ax26UhCMLUkFAh/BLzhX60byvWJUaFfsxSoN9cV4YgCLNDQoXwS8zmUdFjTkhQgEBo+Z9HxVzXhiAIc0NChfBLzOdRqbTnWkm50/q7OiY6/g4JtKCMV0/FsBwVQ1pxH3NdGYIgzA4JFcIveXnZAW+bIIDvRDh7tVCwbt4DndEhuYbjs5NQMSz04z34508OFYIg9EBChfA7yq02FJZavW2GAH64QzxMmAMnyEsJDrSgzFq5vWHDk72od5jgb1IqhDakvI9E9YOECuF3mLEb5EeipHQHX7yEBAYIPCpG4c06KkyoVAhClbdXHEHqtD+w6sgFb5tCeBkSKoTfIQ4ttE2M8Y4hPPheBE7k2uA4Ycn/kEALSssrhYo/hEr45+8Hp0NUAZ+s+QcA8Oovh7xsCeFtSKgQfoc4tBAaFOAlSyrhe1TEIRgOQElZZagqJMiCct4ORo2S8Wroh3JUCIJwERIqhN9hxo5QmKMigoNAmFg4ThD6Mep0LCYZn0w5KgRB6IGECuH3mKFbZAKPinMy7e3t6wu29bfQDx9/Ox+CIDwLCRXC73DqCE3QMfK9COJkWo4DakaG4IMR7QBU1IDhe1SqsnhdcZnVIzNP8z1KJrgchA9x8nIhLl0r8bYZhBchoUL4HeLQghlCDTbeIB7n4ckVBAZU/GVjTDA82Sjr1SI/VwpK0WLqCoz8YotBR6xEMOiHGZ9/Q7hP+oV87Dp91dtmSDJpwR5vm0B4ERIqhN8h7vvM0BfyvSJiwWBfE8DxhUqlsnl7xRFsSL/ktg1qw5P/PJgFANhy4orbxxLDvwZ20fbi4n3o++5aFJms5k115Zb31+GOTzYhO6/Y26Y4seG4+/c/4buQUCH8DhPoEie02MQ5hAoEQuXs1SLc++VWD1lWiSdnHeB7texDsRdsP4OMSwVYvj/TcwcmdHP6SqH6RgRRhZBQIfwOcTjBDMJFGO6Q3saeu2K1MY/MVaQW+qmqXBjxuZltAsnqzvt/HfO2CQQhgIQK4Xc45dKaoCMU1BGRkU72UvmMMY+Eq6R0SlXliwhCP06xOY8dltAI/9pvPH7Zi5YQhDMkVAi/w4z9oJKDxC4g7HVOrMwz6b9SHhX+XCqeDf1UUm4Ve7zMcIWqNyabbJwgBJBQIfwPEz50BSXk5UI/1z0qNptnvBvi+i3iZZ4MwSh5VEzg8Kr2eCLUaDTbMoxP8iZ8AxIqhN9jho7QJgj9SGPPUbF5yqOist4TfdWBc7n4dd958M+63Cb2qBDexkx5Qkw06s3O3Z9t9oI1hBkI9LYBBGE0znVUvI/dQ/LHwSzkFJYK113/P394skfyRVSUiieOOeSjDU7LxG/ve8/k4K6OiQgMoPcmb+FpobJw+2n8tj8L797dFrUiQwBUDIcvLLViOK8qMwCMn7sTe87keNQewrcgoUL4Hc6Vab0vVZbvy0T7pBp4eN5O2W3sYRirzTPJtGpU1Vu1+DgLtp9BaFAApg9tXSXHJ5zxdOjnhcX7AQB/HryAkV0awGpjeOj6b6Fbk5qoGx3q2Pavwxc8agvhe9ArDOF3mLCCPmpHhajWp6gc9eMZm6UKvvFFg5a+6rH5u9D7ndXILy5z2Q5xMi0AfL3ppMvtEe5jc460eISXlu5HwxeXo8lLvzmWXRV5GAlCDAkVwu8ww3BkO6FBFT8xBqCkXLkCq6OOiqeGJ0uEfgTDplWOufXEZfy6LxOnLhfiu62nXbbDTPkQRAWeTaRWbtsuko5dyMff5E0hJKDQD+F3mCnyYx9yzBhDSbnyayvHy1Gpss5cqb6JiGV7zjv+didUIE6mJbyP1YP3m9q9YmMMRaVW3Pr+Oo/ZQPg25FEh/A7nOire6xgrhYp2j4onQj82G8PsNf84L9dV8M2Y4nCemJ2ZcA9PXhM1YVpuYzhzlcr2E/KQUCH8DqdRP171qFT838aYZG4GUDkYh+OJGqPDV78fyJJczj9KVekHX6jZUd3wpEdFTahYbdo9iMv3ZZpy0kTCs5BQIfwPE/WDFl6CrEVlsp1Kj4rxJ3AxX/rhLkym1X5cd0yk0I/58NQlsdkYlu0+p7gNY9rntpo4fxcG/G+9EaYRPgTlqBB+h5lyVAJ4MyLLYV9lH5VjY1Vns7BibNUcc8Pxi8grcn3UEGE8ngr9LN51Fi8vO6C4jd7h+FcKaJRQdYOECuF3mGmuH0c4R0OmjN3hwmB8Mq1U+XwASL+Qj9pRFQW49Hhy3LHu2y2nAbg+aogwHk+F4zYcv6Tp2DQSjFCCQj+E3+Gco+LNZFq7DepvrZwjn6XqPCojv9jq+Futs9IzlJnwLTwlFLQ0a2WMJkUkFCGhQvgdZupE+cOT1ToD/gghqS0ZYzialY/Xfz2Eqx5wf6slVAqEipkSgQi3cVeorDiQhXXHLjot19IqeVQINSj0Q/gdZnrk2avN2ph6DgjHS6aV8gKN/nKbw5WemVuMWaM6GGqrVWZUkuz2NoZdp68irX4MSq02hAcF0Hw9PorEHICayc4vxoRvK8rhZ8wcJAgzavFmemxuK8JvIKFC+B3ih543n4H2Z/b5nCJVj4XDowJpscWP9+8/l2uQhZXwR+MwxmTzWirWAx+tSscHf6WjS6M4bM24grT6Mfjl8RsNt4vwPO54NHIKKxOjrTaGwACeUNGwv9XmnlAitHHofB5WH83Ggz0bISQwwNvm6IKECuF3mKngm92jsuPUVTStGym5jf2xzq+5ovaGqTLS2aXthcXfnPcRf48f/JUOANiacQWAZ8QTUTW4k0zLv03KbQz8PlCLp8So0M/eMzn4ac95TLqlKaJDg9xuz98Y9GHlsO6JN6V40RL9kFAh/B4zlNAHgF/3ZkpuU2ne9TCRhuGaenQKYwyv/HRQdTu+R8XGGCwKRyFHvX9h1KgfV9pxZcoIm405ahTZGTZrI4CKCtBv3J6m2w5/ZfXRbBSWVFbFPpSZ50VrXIMCyoTfYaZwtx7Ph2OEEIwVAgfOaXsw8Uclfb4+A3kKMyQXlZZLLi8nH75PUi6aPtnVnBFxMb+9Z9S9bHrrqADAeoVhz8cu5OtrzI9hjOG+Odsxcf4ux7JAi053rAkgoUL4Pd7ULYJqtCrPB2EJfW3baqFYZY4hO2W8ZNr/rDiC6T/Le2E+X58huXz+NqqP4ouUlrue18XfVOxROZdTpLq/Kx6VfAURvf3kVWz6R71+iy+SnVeM77aeQqHMi4IYqa81gIQKQXifqq6jYrMxXLpWIrkugCco1B4P/BL6ank1+kI/2razit6qV4jmB9LSzu7TORqtIsxEmcgTplXcAsLcJrFnRgurj2TrrqOidi+O/Hyr8gY+yt2fbcaUpQdUq/3akfqayKNCECagqivTPrFgNzq9/hc2pDu/xQkcKipeEH4JfdUHtweeNeLRyaXl+jsdX3xb8ySMMUxZuh9fb5T2QBnBgm2nMfLzLch1cVqCM1cKncIl+cXa3tgBoRdF7FEJD1YfXbJsz3lVj0pUiDCd0kTR3Srl5OWKWaaX7FKeP8mO1EtagMX3un3fs5ggVHD6aXr4qfbrvook2dlrjzs9GPR03PwS+t5ItBF7VFyZPDAogIQKny0nruC7racx/ZdDbrdVXGbF7tNXnSocv7hkPzb9cxlfrD+hu03GGHq+vRqvLz8sWJ5bVIa9Z3I0hRj44kQ8Q3hUqLbxGmpVm//373aCz4wxjxQ99DekvlZf9KjQqB/C7/BW8Sip3BJXhIpNpjKtYFtddmn7PowY+cE/36NZlNR4rUS7Z0KNB7/ZgQ3HL2HqkFZ44MZGTusLS7WHa+yUyiQ/z9t8CvO2nEK7pFgsm9hDsY1yBY9KrcgQXMiTDovyUbr1Pr23I4JEhQRn/HLIMTnhtpduRp3oUNVjVEekQsiu3CfehjwqhN8h/mlWlWxhzPnBryfp1VLpUlF1qOg5J63bGnHMY1nXHH//Z8URjUf2X4x8ebUX/Ju3+aTk+kAXvFly4b15W04BAPacyVFtQ+BREXnl7Ksa1gxXbEMp9NOhQawwKR3CGZT/++dRVRurK1Jf6+JdZz02W7anIKFC+B1OOSpV5GHZfOIyWkxdIVhmEeSoKO9f6VFRL/hm1gfNtpNXcOB64bfiMt97czMa/jU36j6UayXYhekLXMlDEsMP95y+UihYZ79Po1QKsBUoeJ7CggOchAqfojIaEq+XMheSnr0JCRXCD2EKn6oWpQes3LYM6sm0auX4PYHWIaQbr7/5lxjQCfo6HC9IZ1RRNTnE4REtyIV+9MA/r/u/3iFYZ79nHunTBC0TomXbeHrRXtl14cGBiiFUxhjOiAQSUYHcT5bzRDa+ByGhQvgs6RfykVvoPNLBTAXf+G/Rao8G+3obUy/6r+eFyKjvQ+tIAzvkURF6VFxJTtaDS0LFADEpFs2ZuZW1U+xCpWZEMH5/sqdL7QdYOCidGmNAz7dXu9S2vyP3JPG12c9JqBA+ycHzubjl/XXoOvNvp3VOOSo6fpPZ+cUY8dlm/LRHX6csh56+iV/wbf7WU4rb6qlX4Y2HUnGZFQfP+16pbqPh5yiJa5UYjSsjrgwRKqJ70T5M2mpj+OdiAQA4lbvXyubJfQEo53r5Wqdblcg9+8z0MqcFEiqET7Lm6EUAQJHEW7s7kxK+veIotmZcwZML9rhjHs8WfqKhtB21IoMBCN++7Q/4Tsk1JPcxe6X6MV9tE3x+6440PHNLMy9Z4xmy84tVh8jy+2fx0F2jcWXYqTg8p3eyS8D5vMKCKmqnLN9fObeVq0nFCTFhAISFE8X4WqdblRgx2aMZIKFC+CRKiYnOlWm1t6tUmlsKtTdSvjaRKqL12vBUpNSJAiCdzxIdJp2EKH6LBSqGws5e8w9OX66M13+39RTWHruoaKM9x0Dpa9KbCLrt+ozKdm5uWReP9U3BX0/30tWOWSksLUfnN/5G+9dWKt+LvFVGJTDy2+TnhwQakKNiFxl6EOfe2O3Lzit2LNOTqyWFco6KW037NXJfja99Z6YRKjNnzgTHcZg0aZK3TSF8AKWQivOoH+3tBuqs2rjqyAXF9WpvNKO7Jjv+lnoWyz2fpbwzr/1yCP9ZccQxnfuh83mYsvQAPlurXAhsfXqFkFEy1Yj0Co7jHKLM1znPm8NGKUmWn7/hCY8KPwToSlVgsdB2RaiI70Wps3RXqCjt7i9eA08gG/rxsXCZKYTK9u3b8X//939o06aNt00hfASlh5M7w5P11qIoVel89Iz0kMrEl3vAS7W76UTFaBt7kbELvDdaJSo7K2Gb/EO72xm42U+ZDoFXQ+G7sSlUbTXaDlfCK2KhEmqIR8X5PD3qUXGrZT/HT3JUdFWmZYxh7dq1WL9+PU6ePInCwkLUrl0b7du3R79+/ZCUlKTbgGvXrmHUqFH4/PPP8frrrytuW1JSgpKSyiqHeXmUrFddUaojIn5b0DOUV+9bqZoI0vNA4CReG+TskRIqrj587ImK4iYrKu0ycBzn9tBaP9MpgjtMKaLD9zZ4onYF/7q4MuTUWajof3cV3xtSt4q708tQjopryI/68S003T5FRUV48803kZSUhIEDB2L58uXIyclBQEAAjh8/jmnTpqFRo0YYNGgQtmzZosuAiRMnYvDgwejXr5/qtjNnzkRMTIzjnyvCiPAP9IR+9HSyRs+DoccTIXVkudEShgqV6/+XstW+yH2PivL3WiNcuSCYmVESwvzr9E/2NdntXGHX6au4fK0ymdcVp4U4R8WVIc7O9yK7bk+lQa54VO7skFi5v+Lv0te63apDftSPb31nmjwqzZo1Q5cuXfDpp5+if//+CApyfqicOnUK8+fPx4gRI/Dyyy9j/Pjxqu0uWLAAu3btwvbt2zUZO3nyZDz99NOOz3l5eSRWqil6Ok49QsXomUXPXNVeiErqYS4b+tFy/jr7BqkmbYzBAs7tHBU1Uzz92MwvLsPmfy6jd/PaCAnUH94QI5fQKoa/7qF5O3HyrcFuHxsANh2/hJFfbBUs0zNdgx2xR8UVoeKUoyLlUdFoW8bMQQCAE5cK0LBmhKb9My4VaGrbH7F7PGXXV6EtnkTTXfn777/jxx9/xJAhQyRFCgAkJydj8uTJSE9PR58+fVTbPHPmDJ588kl8++23CA3VNqFUSEgIoqOjBf+I6olSRy1epafQll6PippeKNZR3lvqeSNnjgd0iqT4++NgRbJwoZuT66n1U1YPD919eN5OPDRvJ2b+Zsz8Q3yXulIY0hPVaBkY1kiM5HLFFygWKq7MFyQegSadTFvx/4Gp8bLtxIYHgeM4cByHJrUjBWFPpdCPfSh/dSOnsBQ3/mc13lguPzO33AudrwkYTUIlNTVVc4PBwcFo2rSp6nY7d+5EdnY2OnbsiMDAQAQGBmLt2rX48MMPERgYCKuVqloS8ujxXOqZF0fvg9rI7Hmpt8aQQNc9PFrfsJU2mzh/F/KLy3Df19q8nrLHUOlGPT0lwKZ/LgMAFm4/Y0h7WpNpPV02n48roZ8ScejHBY+iJo/KddExa2QHvHl7mmQ7ORJVpiv3122W3/PQvJ04l1OEz9dnyG5TbQu+rVixAhs2bHB8njVrFtq1a4eRI0fi6tWrmtu5+eabsX//fuzZs8fxr1OnThg1ahT27NmDgAD33bOE/6KnjoqnPCozfjmIpxbKz1FiBHqSe12NO/MnQ5SiSGeV2QKpaeTVPCpV1KEbJSz535WiR6UKewRXDmWMR0U8PPl6jgpvmf1vi4VDQqw2Dzofd0cN+SPiWkVSyN7v/i5UnnvuOcdom/379+OZZ57BoEGDcOLECUH+iBpRUVFITU0V/IuIiEDNmjV1eXCI6olSZVb7A9vex5eU2/DJmuOO0t5K6MlRmbPxpOZttSD1MNaTd+Dus8eoCcw+/DvduQ2VJnytFga/c1YUI1V4Wq4cqlz0Q3KlFotcwTc5XBEdrtjlj+gelVVd66hkZGSgVatWAIDFixdjyJAhePPNN/HJJ5/g999/N9xAgpBCsY7K9f/zK3W+veIoXl52QLVdvkdFT8jICKSe3+48nrXua++rPCkW+Lbc0b6+hA2+9eDke+mUbOd/p72a1Tbs+FLX1hWPmtjb6KlkWv4iVzQHyZQK9F5iuc197L1AXx0VoCIHpbCwYiTDX3/9hTFjxgAA4uLi3K5rsmbNGrf2J6oPymXLK9YFWjjwZ2JZczRbtV2+67vMZkOIpepCkNIeFe3763n4dG4U53Ad25Mh5fY3QsDwPUONakU4rbfxarb4AnxxolQeRVhvxZje4cyVImw76ez219v6zN8O47N1wqrFUqHP4jKrYiE4udCPYBlvUZv6sfoMFVE/NgzneJWBqxO6hYp/RH70e1RuvPFGPP3003jttdewbds2DB5cMdzu2LFjSExMVNmbIIxBcdTP9f+LH7paZq/l71NmwEiUtkmxmreV6qJdKeIFALmFZbIiJyTQgnHdGzo+29+I5b5SI7wdcmexZfLNjr99yamiNfQjmOvHwJkkd5/OkTiYvjbEIgWQ9qj8fVhe4O8/m4t0UX0YSY8Kb2FMeBAm9G6iw1IhtaJCXN7X19H70iBb8M3HXCq6hcrHH3+MwMBA/Pjjj5g9ezbq169w4/7+++8YMGCA4QYShBRaCr6JJ2nTMqU9v7BUmcL2Wn/oTWpFoG+LOpq2lQz9cMDiR7qp7ltcZkUWr2R+21f/lN322we7IK1+jONzuZUht7AMF6+VSG5viFDhnRu/tbDgyjf1cg9UbgWA47yO1Kjns1Vj6IffURgpVKQwwvMllUwr19ll5xXjto834Je954XbX99cOAWDcN9YvQX+OMk/qx16r7DcrelbMsWF0E+DBg3w66+/Oi1///33DTGIILSgLBQqQz98tPS3fA+GUseitU+wMYYa4cGatuU4DmO6JWPu5lM8e4COyXGq+/6fxNuxfHIskBQXjpoRwbhcUIpyG1MUNoaEfmS6F2FOkPP6cqsNz/24Dx2SawgmcNRDv/fWurSfEvy8DK3zTukZfeYKRrQuNSmn3LU7eVm6mKFd2PDP3Z1h9hX7VwraYDfb8mW0/hbLrTb8Z8URJNd0DrMC2p9fhaXlyCsqR3yM/pFaRqJbqNjJzs5GdnY2bKKnC00sSFQFinkBdo+KC1l7/AeBuLy44Bia2wOCRGbUjQ7BhTxp78WYbg0FQkXsFZLjuER5djkb7W+6bZNisepItuqbvuEeFV5z/NEcUiGUPw9dwNLd57B09zmXhQofo6TC/K2V16hAoRge/3hGhBKVMMJbFCThUZELIcrdF3Y7+PdVQ1Fekt5fZkxYEKYOaQULB2w8fknn3v6D1mv8486zyvVVNP4Sur+1CjmFZVj//E1IigvXdnAPoFuo7Ny5E2PHjsXhw4cdb7Ucx1VOXkaF2ogqQO7N4lxOEf53fXis1k6eD99To9SxaH2zsTHmlCSrVGVTrK20vj1K5RaUlCn/Fu2HUhMqnhwNxP9upDq+/GL1IeXewF6xFwBu/2STfGl83ncnHgpsNEYMOZW63xgDXvv1ENolxeK2tvV4y2WEyvX/22fxHtvNWWC6YukDNzYCUFm8j5DnfK7KzOkaL4C9CN+G45fw784N3LTKdXQ/ye+77z40a9YMmzZtwokTJ5CRkSH4P0FUBXIv+ffP2Y716RVvXK7UXuC3q5TToif0I/amBygU1RLbHKxRbEm9CT80b6fM1hXb2kfYqL3pG9G/CnNUKo8XoDIc3N1RQOI2qzq/gX90j4d+DGh+uMTQ8VVHsvHlhgw8/v1uwXK5JGK7gMkvrhAqkaEuO+4lubuTtvndBv1vPbZLjI6qDii9DAHVIEclIyMDS5YsQUpKiifsIQhNyL3lH72Q7/jblU5JmFMg30Nr9TIMSktwegNUe4jwccejIof98Pb/V0noh3c1+F8dX5dJdXzuViQVtyl3JvnFZVi25zwGtI5HbZVRJXqGGTONwtcI5KxatvscakYGo2dT9ToujSWGjst5tWRDP479rguVEOfEWXeuar+WdXBLq7pYeeiC4naHMvNw16ebDZsI0pdQe0fTK2q9ncCs26Ny8803Y+9ez5YNJwg1+ELh9k824p0/nCebc6WPE5ZGd8k0AQNaxzv9yOUS3ADnt24ljwrf9a6n9Ll9yysFFVVm3vpd+N0l1ggTfPbkqB+O4xwPVSkBwD99V+qQaLX9paUHMHXZAYz+cqvqtno8I/z7yVOjmuxIhWIyLhVg0sI9GP3lNtX9f338RoQHO7+7hgdL11CRnfDu+uLC0gqhEhHivP8NjdQTxOXgOA4t46Nc3r86YFFRKr5WmVa3R+WLL77A2LFjceDAAaSmpjrNpjx06FDDjCMIOfh9xe7TOdh9OgfP9W8h2MaVt3H+w16pPoZWj0qAhXOy45E+TVC/RhgGtHaeSbZcFIZR8qjYGGDXJ1pDREBlOGXnqauS618fnopxcyonIbxaWCq5nVEEWDjYrEzVo1JqtSFUZwE+J1Ehc9n+OJAFADiSlS+9AQ89wk3gofNCMu2FPGGuQnZ+Mb7dchr33CAMnzzcuzFSeUPW+YTxxEtpuc1xT8rrrgpD7N+9VAi2Q4Ma+GFCN9z16Wa5RggRakUu+WFStUefbo+Kl10quoXKpk2bsGHDBsly+ZRMS1QVWt6uXREq/Ga1DjtVgu8xsBMeHCA7g2x0mPAnqSxUGAKu+0dcmUxODvH39v5fx9xuk9+i2GMTYOFQZmWSHfm+s7mOv0utNsUKqVJYJdqcszEDdaJCMbhNQuV2Op7cUttO//kgpg9t7bRcOOqn6j0q4mv52He7se3kFfwqqn2i9FsJ433nRaVWxz0p953Zf0P236hcqPOGhkKvyvB29SS3k6LMl6oDGoTSKVttTPAMUHv26f32XC08aRS6Qz9PPPEERo8ejczMTNhsNsE/EilEVaHFoyH1W/3novMwXrl2lcSQnpEw4oRQpR99QoywE1fylNzy3los230OgL68F7UtxWeWLTOUWg/87+DODol4pE8TfHN/ZwCVtkt9p19uqBxi6UqOhzjcUmq1YcYvhzBx/i7HskPn83R5SaTEz9ebTkpuywShn6qvoyK+Leyl909cKhAs54vptc/1wStDWjk+BwVWrizijSSTHfVzfbFdyKiFIezo+XrMNDdUcZkVD83dge+3nfbocZTOWXxvqeeoOLd1PDsfr/16CJekCj962aOiW6hcvnwZTz31FOrWresJewhCE1p0gtSIkRm/HFLch/97V644qh3x242apnh1WOWbuZJH5eTlQkxauEeHJdqObxV17kaU2+YfMsDC4YUBLdD7+iR99o5MrfNxRaho6dBeXrZfV5uu5pp4I/TD/96VhDf/Hk2uGYG2SdJhIP65yzmI7PeLVcWjIkaP+Pe0d0oP87eexp+HLmDyEn33kV6Uvh/+unM5RXjzN+ecPT5STQ36cAO+3JCB534wXw6qbqFyxx13YPXq1Z6whSA0o8VVL/VWUVqu7PXTmqMiXjW0rbzbWu8oaX5Co9bRPFsytA/DVHPjijtUI7pXpb7KnsNgf9j+cTALDV9cjr7vrhFsp6UjyyksxWlexVQlL0ZRacW9oPftXO3ee3HxPtw3ZxsYY8JRP1abR+dYUfOoKNktFvWCr0RGvMsm04rWay0ToOer8bTo00NWnkrNEoNQupf51+UVDbPES2F/EdjLC7eaBd05Ks2aNcPkyZOxYcMGpKWlOSXTPvHEE4YZRxByaHngS8Vp1R5w/Iev0iHEx+c44K070vCixFuV2PWt9oLJ1yZaSo9vP3nFMROyFtQ9KsJzy1QrHqXpmAq1Yzi7R6Xi88PX67+cuCgMT2jpyNq9uhIAsOnFvqgXG6aYCNzylRXY+XI/3SEZNWGzYPsZABWJueLRFeJcAiPZffoqgEaipcoF9eyItYTcd61l6gDGgNyiMmw8XjEsX2voR89IFE+PoNKD1PQVnkDp+vG/jpwi9SKJSr8lqcvl7eHJLo36iYyMxNq1a7F2rXAODY7jSKgQVYLUb/aj6xVp7Uj94MQu492nr+LrTSfx4sAWSIgJ0x76Ea2ycJzskEuxGWqJbvz1Wuqo6BEpgLr48XQuhRh7vY19Z3PQXGHYqZ7QwN4zOagXG4YxKsNyP/w7Xb9HRbHDEHmjRJuW2xgC9eUDa+bXfZn4eKRwmXBiQG2hH0AoxPl7aZmMkYHhMV4OkNbQT1r9WE3bAUBpuXk8KlWFUuiOL9y0fNt2UXjyUgFeWrofY3mzqXtfljjjUsE3gvA2Ug/Jd1eKRqdIPCDFVVhv/2QTACArtxgLH+4meJgrucqz84UJZxzkBYhTMq2qR0WfUFmfflF1Gz4pdSIV11f126p9TqXnftyHuxSqjurRE/ZNLxcoD62+VmLVPUWAklDhhwE4zjkcU1Kuf+SSO/BvNSW7xeEZuS35Hkm55kZ+LqxFo3XkvL1EvhbM5FGpKpTmHtMSCg8NsqC4rKIN++Z9/rsGgHBaAvvziS9W3a0Q7S5uTUNZEYOtfsqW8D5aOhcpj4rcA25rxhWnnAK5N5i84jL0/2CdYJnUMGQ5O9RyRPhvoFrqo2w5oc+jovbQMVP8n48eQfHod7uwQ0P5dI7T70GS237Licvo/tYqx2cLxznZfDG/avIZ7PCvtVLfLr4l5L5qQY6Kxu9NS5mAnk1r6ZoV2YgqvwUl5Xj0u534dd959Y1FXC0oxZGsPLdt0MMfB7Nk12nRbaFBAYgKqfBNaLlyZuraXRIqc+fORVpaGsLCwhAWFoY2bdpg3rx5RttGELKUaHhQST0glR5wv+zLFAhvuedw+gXnIc4cJ/9A1jvqx6LTo2I0VR360Yrel6IxX6lXY+Wgv+Kt3PZzNgq9zRaOc3rYn8+pYqHC+1vprVsp9MM/3zJej6in6KEaet/YJYfQ6uSzdSfw2/4sPDZ/t+w2x7PzMXnJflwVeeY6v/kXBnyw/npekOdhjOGVnw7KrrcKvB/S23CO/wArD2XJetjsuwva1GGrJ9Ad+nnvvfcwdepUPPbYY+jRowcYY9i4cSMmTJiAS5cu4amnnvKEnQQhQMsblXSOivzD9de951E3OtTxWe6HLDU0koP8A8LZo6KM3hwVozGrUNFrVmGpel0njgMuXxN2Qs//uBdv/6ut7D5y34/YU5YlkYTszWG1upJp+fvxw6H8HBWNQkVLMq3ekXFq8zFp4WK+utjp916F5/T7bacFcwbZnyMjPtvith1aKFKZCV2L2OY4zjFv05u/HZH11tqfP56cNV0vup+CH330EWbPno3//Oc/GDp0KIYNG4a3334bn3zyCT788ENP2EgQTmjxqEi9pSm9lQcFWoQF32S2lQqNWDjnUvlydugZ9aOnNL5RNKwZXuXH1ILeB6eW727RjrPILyl3WqaE7Juo6Lre++VWp/utqguVabmfASmPCq8Nns2Pz9+N8zlF19vTZoOWZFq9VaSnDmmFYToq2Urj/rVQyhsxEnvCuRx88SwXWhYvnS5TU8qeZ2WmNCDdT8HMzEx0797daXn37t2RmZlpiFEEoUaJSj0UAMjTMEyPT3CARdOoH0mPio7Qj5pPxdselRtTalX5MbWg98EZ5MYw4P0KtSTk7gup6y/etKrfUvnHV/KUicU0f6gwf7+svGI88X1FqERryExL6EevRyUhJgz/u6c9ujepqW9HHlKXotxqw7dbTqlWsK5q1J5lgntSLvSj4zsuKhUmmXt7rh/dT8GUlBQsWrTIafnChQvRtGlTQ4wiCDW0hH6kJphTerQGBXCiHBU9QkU+mVb8I9fzo/eGR6WqM/zv71Ex2qN1vWjF7VYeuqC43rm2jevncdvHG2TX2Tvu+rHC6Q4uFziHEsTiwNUXcC1hCinkck3EKNVREe92/HonrjVEqMVb4uq1mnmH9JxZWhDWTKr4+5vNp/DysgO4+d21crt5hQKVMOag/63HnwrJthVo/44Hf7TeVKEf3TkqM2bMwIgRI7Bu3Tr06NEDHMdhw4YN+PvvvyUFDEF4Ai2hHymUfntBARaBCJEN/Ug8oDlO/mGrN0eF/3Zk96hwnLmy8LVyZ4dEtFCojQIAqfUrBEpcRLDidu//dQxP9pN/GRJ/P9dKlN3lrmK/L8TeLqnRV2JxoGfyQz5nrxaqbySB1rpAYjHRrG7lNROfg/2zeKoFOTQl02pqyZnkmhEY2y0Z32w+hSFtEvDrPu1eff6l6PDaSix6uBu266xJVFWUqyjcUqsND83biZNvDZb9LvV4rU5cLBB4MH3Oo3LnnXdi27ZtqFWrFpYtW4YlS5agVq1a2LZtG26//XZP2EgQTmh1O08Z1BJ1oysT75SqXwY5hX6kt5NLppX3qAhXqL1hlksIFT2TDpqJaUNbYXyvxorb2L8Pd4WYqyJAL/YcJS0dsFjU6h1h5C7iukCyCd+ic4mPCUVMWJBjPz72T1o9Klqcgq7MdG5nxrBUHH51AFLrx0iuz7hUgL7/XYMFokkD+dZfLSzD1J8OCL6v139VnhesKjEiwV3vVywI/fjS7MllZWW47777EBsbi2+//RY7d+7Erl278O2336J9+/aespEgnND6sx3fqzE2vNC3cj+FHYPFybQ2ht/3Z2Lu5pNYn37R8aCTGjmklEyrd3gy/8038HoHorUMeVVzY0otTBnUEklxYZLrtVht/z5sjLlVm0LsATNiZIjScQI1XBOx18HVZFqtoZEc0ZQB4vtZrhWpasXNr3tVnOrRXG9SahZpKbSFfjQ1JUtYcIDsd3vTf9fgxKUCp+ktxPeL1cYEy77gzdztbfTcN+euJzuL0Ss2qkr4a0GXUAkKCsLSpUs9ZQtBaEZPTQ3+g1JprwCLsO6FlTE88t0uvPLTQYz+chteXLIf936x1YVkWtG2apMC8jP4r7dplEelca0IQ9qx07p+NMb3aizbaWnpYPkelQe+3uGyLeJIhKt5HWrYr4+WDtgpR8XDD/92r67EnjM5js/i+1mOJrWdqxXbT+/kZWHYSb9HxfhRP1Lo9laJNi+zMt1D4KsKrcPai8usOHtVRqi44VHRMw+TJ9Ad+rn99tuxbNkyD5hCENrR87PhPyeV+gkOwh9nkUQC24bjl/DG8sMSx+DAyfya9HtUnB9KWmegVeL9EW2xaEI3t9uRQm6Yphar7d9Puc3mlrioquQ/+/XRMrmg+E1YT2f69+ELeODr7bh0rUTXu/BXPE+AIPRjY7LCsXaks/dJ7j61t6n1Lb8qPCoAEKuS4yRGbL3VxtwePr7x+CXFCrKuwrerbnQIZgxtLbmd0uggvV+xsAqxzp0NRncybUpKCl577TVs2rQJHTt2RESE8A2NJiUkqgI9fZLw4Sy/4ydr/hF8lpuFVC5JU76OirJ9YqTrtOhrQ4rb2ye634gMJWUyQkWD3fZz237yqls2VJWr2q7JtIhHccenx8YHvqnwLr2x/LBo0jhl+EfgH16ps4kMde4K5O5nu1Ap09h7aZkB3AiPyohOSdh16iqW7j6naXuxV7ZcFPpxhVFfVMxztGXyzYiPCVXZWjs/7aks8x8fHSrpAQOA//55VLYNvSOrCkoqX9S8PQLIpdmTY2NjsXPnTuzcuVOwjmZPJqoKV+eY0rNbbqHyhHZ8LIpz/ejzqLRNinVaZoRHxRNEBlc8QkpkPSrGDk09dD4PrWSGMbMqeuuze1S0hOPc8ajYyc4vVh31ITiGzBB7JZEUEeI8UaKceLA3ozVHJUhDNq0Rt3dwoAXvj2iH3aevOoWr7Kw+mo2bmtcB4Dzs2mqzGdYhn88tMkyonL5ciJ/3VgoVjuNknyFqxQr1UMB7IfN2ugrNnkz4JK7+cPTsJq5YqoQ4R6V/67q4o0OiY51wW+WncrO6UVjyaHdBOf/+reOxYPsZNK4VgROXCjTb5Ul6pNTE/ddnvJWra6PHo6KFVUcuyAoVn/CouCBUGAOmLD2gYwf+vqLQj8wuIYHOQkXu2pWU2/DHwSycz5XOhRCjpWihkbV7lNq6b852Ryl88QSl5TZmWIijWKXkvR4uXhNOxRBgkRcqSujdhy9UvO1R0Z2j8uqrr6Kw0FmtFhUV4dVXXzXEKIJQoyp+NnpmEeYgfBA8178F+reOByDhUdHQXocGNQQFxV65rRXevD0NCx7qqtkmowkOsODJmyvrmHz3YFdEhOh+13FCj9vf3s8zxvDkgt2Y+fth3jpj7wo574e9g3Mt9KPfjk3/XMbRC87FC+2IPXD8xMcdvHCajTFdw1yVOvyH5+3Eb/u15WJoESpGhH7saGkpr7jMyf4TFwuw+cRlQ2wwUqiIz8jCuTZcWO9X/CpveLa3k4x1C5UZM2bg2jXn8sKFhYWYMWOGIUYRhBquh3607yd+41LCYuEEDw/+Q8Fp1I8Lz+Tw4ECM7NIAdaL1u5PjIoIxoXcTp+V67bizY33UiZYe8hsbHiS5XEsHZNHxFLJ3/Eey8vHTnvP4bO0JxzU1ukbJjlPCnBn7G6bdhgALh6Z1pHMF7Gipo2KzMeTqnO6BzytDWgo+22/xMqtNkHd1VKJSsxJ6b1M53aZFqERKhJ5cRoPhv+93fboXLfdZUalxcUjn54eLHhWdV5Rf2dvnPCqMSWeO7927F3FxcYYYRRBquPqz0bOf1jdGoOLZyH/DrhFeOQJBb8E3o1n//E14cWALp+V67eA4TvZh9+0DXdClURzevD1NtI+2drViFyX852ZRmRWMMcNDP3d/thnHrnsyvlh/Aq2n/YGf9pxzCJVAC4cvxnbC0Lbyk+OJbZKycdzX29F2xp84nq1PSNgR54A4ckhEHerB8/pq1OgJyd3fo5HsW7eWaSCkknldRYvZAXrU8XWOZ+dj0fYzmpKI1Twq4no3Sjg/P1yr5OvOY8fVF0Oj0Hy1atSogbi4OHAch2bNmiEuLs7xLyYmBrfccgvuvvtuT9pKEA5c/d00r6tczt1VOI5DgIXDdw92wVfjOgnKwbsS+jESuWG0emuzWDj5h11q/RgsfLgbOjWsIViuZ3iyGKnRIvbOkH9Ot7y3DmO+2qaY/xER7PzGLucF4jPs440AgNevD0l/ZtFegUcluWYEPvy3fLFLccKplI3rjl0EACzcfkbVHinEHgt76Ef8GwkN0tc56xGyQYHy22oRKlGh6tfCSFyZsLLfe+vw/OJ9WLxTfVSR0uPp2y2n0O7Vlfhs7T8KW1UiFowVOSr67XfnBcmIyrjuoFnGfvDBB2CM4f7778eMGTMQExPjWBccHIyGDRuiWzfP1GggCDF6CxA917853vnjqOp8Mq5ifwb0kJh52OnNtIqVSpDM22OAhQNEL37tG8TKtmPh1J3H4rd7d5Ik1z53E+JjQtHwxeWOZXYXND9/6FxOEc7lFElWDLazd9qtSJnyu2BZnagQ5BQqh1yKyqyC0usBFs7hFTG6hL6r1Ydjw4T3tF2giH8jUgmzSui5dCEKYkTpvOIignGloBT9WtbRY5oiWu45d0bR7Tjl3nxALy+rSIye+fsRPCwRkhUj/tVxkB9hqNyO62iZBNaTaBYqY8eOBQA0atQIPXr0QGCgca46gtCLXo+Kfd4ST8ValR4Czh6VqlUqWjvANc/2QUKsfA5MRcEw5TbEZeW1HFmu85Yy2y4SpCp1Kg3hDZToSLW+YfJLrwdaOIFHRQ1xnpNSeMru4Tp7tRCFKrPl8hHrUPvXKf5a9d77ekSmliHIUqx5rg8uXytFIwMrJqtZfdenm9A2Mdbl9rWM3DIyVCI1+7pL+t+Nx46rk8Aahe67KyoqCocPV2ba//TTTxg+fDheeukllJZqj7sRhDvofQwYNfGdWvuSGJBMWxU0rBWh+Nb93dbTqiIrJEjsUVE/rlwHKtVR8hNFxeh9mMpNYqdEgIVzeG605DmsOXpR8FksyvjnYRc+N/5nNW59f512m5y+p+vJxaLvVe9IFC0hG8e2Mgmz/+7cQHG/6NAgQ0UKoH7PbT951a15fLJyi9U3MhDx+VTcJy6M+nHDBmNHMelHt1B5+OGHcezYMQDAiRMnMGLECISHh+OHH37A888/b7iBBCGF3jcW+4997bGLyhu6iNLD0ds5KnLwzWqZIKxNwh+GLNxJuc06UaGoxyt0peWtXO4NVcphYe/opUr2l5QrP0z5ZcfbN4hFqkw9FiXKrAyF10f/8PNetIxsAZw9Kv/9o7KSqIXjXKqzIvbsOEI/oqbmbj6lq12t5wTIe1SkcoM8jac9llsz1EM/Wq/iWJXcKsD5OlpcHPWj5AH8SCHPCvBBj8qxY8fQrl07AMAPP/yA3r17Y/78+fj666+xePFio+0jCEn0Ps/tv9GSchs+/Dsds1Yf11XtUw2lDllqeKEZ4D8Ab24hzBF46pZmLrf7+u2puraX86hIeansHgipfJRjF5zLJgDA09fPhZ8v0rlRnEt5CkVlVlwrvS5UeDVkejSpqWl/qw3ILy7DqcsVRfu+5L3ZB1g4l95cxaE9++ged8MPWmaHthMkI2q8kYNpip+XxvNee+wiNv9TWbvlakEpvtyQgUvXKue8chYqrr3s1IyQn008ijfqavkTNzqtV3sJ8DS6E00YY7Bdj7v+9ddfGDJkCAAgKSkJly5dMtY6gpDgn4vXNL15Lnq4Mrmb/5b13soKj2B0mHEjDfTlqJiDuIhgx5TwWudt8YTtcnrR/r21TYzB3rO5ACqrBZdJvOFN5uWS2LmjfX08cd07xE8ItFrlJ+hT41qxs1D5711t0fH1v1T3tTGG7m+tQn5xOf5+prdAPAVYOF25KQAwpluyU+gnK6/4+rF0NeWEnsn12iZKh9G8Peuut9Bz3vzf3hMLdmN9+iX8svc8lk3sAcBZyHMc59IIns6N4mQL2iXFhWNMt2REhgSidT3na1ksM5dXVaHbo9KpUye8/vrrmDdvHtauXYvBgyvKEWdkZKBu3bqGG0gQYl795ZD6RgDSeDkIUr/rdIVqn3pRenBIJcOZgS/GdnL8LTcySIwnvEGyOSrXTXqwZ2PHsryi60JFozeMH2rh7xMZGujycM3TVyoqc/OLlNWUmH1Y0h4bQ/51ofPY/N2CdRZOv0flXx0TZT1D7npU8oq1TSHx2vBUtJFJTvX2HDFVgWSIUsd583dfn17xsr/nTA6vLWFjAS6Gfh69SXmE0avDUvH8gIp6S8/1by5Y53Ohnw8++AC7du3CY489hilTpiAlJQUA8OOPP6J79+6GG0gQrsL/MSslZhp9LDHiDlFqBIpR/LtzA80u+5YJ0XhlSCu0TYrFeJ4YUMITcyOqhX74a6+VlOHStRJM/+Wgprb5OUn2yeiACvHj6mXIuD7Xknj6gMf7pqjuy/cEHs4UFmALsEC3R8Wi8HYtFwozmpua15Zd50rCsrtUtTiSEoqu5BrJIW7KYnEtD0cpUT4uXDjEXXxO/+rouZnXtaA79NOmTRvs3+/sYn3nnXcQEFD1iVMEIYdSGXvAWLe0ntBPqI4kRb00rBmOw68NwHsrj2H2GvWCUvff2MgxsaAaX47thLxi10u9yyH3ULd/T/xrV25lePaHvbiQVyK5j5jwoMpnUlpiDFY+1Qt1Y0IRGRKIAakJeGFxxbNszbN9cCSrQjgEB1rwxPd7cE1mUsorBRWjGyNFQuXpW5rho1XHFe1RejNlDCgs1T4RJlBxb8l5VB74ZruutlwlUMIbt2JST+w4eRV3tK9fJTbwqarJKe1U/L6Fx8zMLcI/F6+hSW3lKRbsMMZk7zexZ4yDax4VAHiibwo+WfOPIOT49C3NUENUX0rcfO9m8mK0KjCsGEpoqDFTWhOEUfAFgtQP28hEP6VaJfxjBwdY3PaoxIQFKc4NExRgMXzeGwBIrhmOA+f0lWHXgpxQsX9P8bz5jUqtNuwSzcGjhDgPqSmvMnFMWBCOvT4QQQEVlT4b8obJKnmO7F6PiGDh45PjONSPDXPk/UiRp3DdZv5+RLIarxIWi7yter0zYuKjQx35LkpIVT5uER+NFvH6R1UZgSfufSWkhOKs1f9g1up/sOPlfqilEhbkOA6Pzd+N5RLzD53LKXII48rtXbf16Vub48l+zdDkpd8cy56QGOFntoid7iemvZS++F/NmjVRv3599O7dG3PmzPGErQShC07wt2dDP0rwn2N6y5hL8eME9QrQdV2YvFCNAItF29w9Ot3SYSpDWNN4iZpWG9N13dRyaoIDLZLbaBkRJDVztNScSkDlCJp8mbdmO3pzASryFZwrlR44l6urHSmUpgbg42qxN09R1R4VpakoTlwsUN2fAyRFypWCUvR4axUemrdTsLxn01pulcMPsHA49vpA/OfONGx44SbJbcyWW6T7DnvllVdgsVgwePBgzJgxA9OnT8fgwYNhsVgwceJENGvWDI888gg+//xzT9hLEJrVvppHxcj3BsV6b7yVap2yFkKD5NuwH2pU1wa4t2sDfMlLmHUXT01M1r91vOL6kMAAzHugM4CKwlN6rHDVZi1CJVziWt4mM0Ghvb11Btfxsd9bYnuHfLTB7ba1FGKLDQ9CtIETChqBkfkhWnB16gM7322Vrm8jlez/1h1puKtjktsJ+cGBFoy4oQESa4RLrjfbaC3dd9iGDRvw+uuvY8KECYLln332Gf78808sXrwYbdq0wYcffojx48cbZihB2NHq2q3KZFqlKp58wRSmIDKMJCQwAK8PT1PfUAc2pm3Uj96HnJY3cns+SHGZTVV8dG4Uh23Xi3K5eo21nKfcZI+zRnbAxPm7hNtaOGjLqtGHvY+UypNwFy2VaVvGR5umLpAdM4R+7Ijv1SW7zjpt88fBC5L7StUKuud6pV+tX3lokMWlocU+71H5448/0K9fP6flN998M/744w8AwKBBg3DixAn3rSMIERvSL2HDcW31evgPUMlkWgN/jEq5BcLQj/tCRekNzpMPmISYUCTEVE0u2sguwtLr9u+tpNyqmls07bZWbh9fy8zSch3U4DYJqB8bpmlbd7G3q6c4m1aUZkS20yBO+o3cm0iFfh7urW1UmyvoCcM8vWiv5m2f+1F+Wy1ljyJDAnVNg2BmdJ9FXFwcfvnlF6flv/zyC+Li4gAABQUFiIqKctqGINzl/q9dG8ng6bLaSuXG+Q8yI4SK0pl4Kj6/ZfLNiAgJxA0N4zBlUEt8Nc64kJIU4o4+6Lr3oszKVCfX43toXHVhaxEWSmJGvMpTQ9Lt95a74QcpxJ6u2aM6YOoQoQjk3/cvD24JAHikj/qMwJ5EqsTO6K7JqvuN7aa+jRT8KrJGkqkwp5DUFBJiZo3q4JH7whvoDv1MnToVjzzyCFavXo3OnTuD4zhs27YNv/32Gz799FMAwMqVK9G7d2/DjSUIV/WG1O/1p73n3LOFh9JbPr/TMiL0o/QGZ5VwFxtBPM+TMr6X595O7YjP0T4BoM3GVBNO+fu6GgXQIlSUOgGxh8MTHg+g8t7yhMdGLFQGpiWgoKQcr/1aWXBx0z+V3s0HezbGwLQEwVxP3kBKyGrxeng6hGVkjleJSmHA9DcGIijA4nLSrafy0VxFt8wfP3481q5di4iICCxZsgQ//vgjwsPDsXbtWjzwwAMAgGeeeQYLFy403FiCcPVRIvV7NbIstFKlVIvBybRKVPWIh6rC7r1QGzUDCDttqZE5WhDXSJFCSXyIRYynhIr9XLWEqvjc0b6+oHKzHIPTEgSfI0IC8QZvLifxb6h+bJjXc1akkmm1dNhSydHuwrfEyOquah4Vu8h09bYbkKqc4F7VuOSP7NGjB77//nvs2rULu3fvxvfff09VaYkqwdVnoKf771KFh5DRHhWlcEZVj3iQokGc+mgRMT2b1hJ8viCq3xEgk7gqhYUDPh7ZHs3rRuHdu9rotgUAPrinnYbjKAiVKqpG7Erop1ZkMN4b0c7lfKNmdc0d1pdKptXy9Yzs0sCjOR0FGkS2VsKDnYV0vERJAleHjqfUicL4ntoKQVYFLr1u2Gw2HD9+HNnZ2Y4JCu306tXLEMMIQgpXc0083X8rPRD4nVaIAXVUlMRIuQmESkqdSHwxphNqR2mb/wYAvhp3A7Jyi9Hz7dUAgCJRsTI9HgMLx2FIm3oY0kZ6qLAWmtWNwt2dErFoh/MoDYdNCr2f2F65EULuYj+MHo+N3W4td0p0mHMXYfa0B7FX8ZE+TTR5eaLDgrBoQjcMn7XRI3a5W4CPT4cGsU7LHr85BVOWHhAs+2RUB4yfuxNTBkvX91HihQEt0Lh2JLo21jYzuCfRLVS2bNmCkSNH4tSpU86lfTkOVqt3p4Mm/BtXPSpqCZju0LlhHO7qJD8XhrgyrbsonUpVD82Uo18rfROUBgVYkMQbQSLubPTkYBiVr6HWjtJ68X2qddJHvdgFkZ6Q4n09tL8pP3Nrc6RfuOYYFgsIczlS6mgrEV+ViIX8fT0aahJXwQEWw0N0S3adBQegS+OaKNA5PYISUsLr1lbxmLL0gGAm6/YNamD7lJtdCscFBljw784N1DesAnQLlQkTJqBTp05Yvnw5EhISvB6PJKoXriaHaZ1tVy9xEcFYpFIpVlh4zv3fi9k9KkbgNGOsF4RKw5rKISyle1HsYfOUR8Vug5acGjv2CSi1aPdakSH48RFhWJ9/JlOHtNR83KpCfO+EBweiTEN+SFCABa3rGVv2f9GOs1i04yxOvjXY0NCPFLWjQnBgRn+nucT8oY/WLfPT09Px5ptvomXLloiNjUVMTIzgH0F4Eq0/uf6thW/0chN+uYsWe/gdmhF9qFJIxQw5KkYg9gzpER9GPZfH9WiI9hIudjtKb99v/0uYG+PpHBWtQqV9g1jed+navcLfS20eG28g/g2EBQVoesEJsFRMRzBjaGuP2FVQYmy0oWvjOKdlkSGBHp2d3VvoPqMuXbrg+HHlGUIJwmNo6ITu6piIT+/tKFiWX2ycUDn51mBd2/P7MyPe9pVGspRrqQTlA4j1li6PikFKJSQwAJMHynsMlBJYWyYI38yDXLzuQ2VK8lfaUPF/raOb+B22q9FQfsjfU4Xs3EHq3tETedM6T9YYnXVX9M6MrcY393fGfT0aGtqmWdEd+nn88cfxzDPPICsrC2lpaQgKEs5O2qaNa1n2BGEUESGBTu5OcXKmK/RIqYnPRgsLnWmapI+3kdLoICO4V0NhK19AnKPiSrKoERQp1KvwdDiqbnSI6v1lFx5aCwka8c3whYAZhQqfUV3051jcqjG/6q6OSWgQF44ujWrito/V51aSKonvDiGBAejRpBbmbDxpaLtmRLdQufPOOwEA999/v2MZx3FgjFEyLeFRTly8pskzEiSRDzC6WzI+Xu2eJ3DG0FQJF7uWQlKVf69P11b+3xU2T+6LhJgw9Q19AHGivp7cJCNj8koCV4/nRm+Hfm/XBnjgxsb48O90xe3s34tWISfwqOiyqBJ+aMXsQsVuqZ6IqMXCYXzPRvh8fYbidhxXUeROK57wdt7QqCL84+0ie55Gt1DJyFC+eAThCQpLy9H33bWatpVyydeNDsWoLg3w3dbTLtvg6kOZ3zl4KqkSAGqEB3us7apGnGfgqYJpanRIjpVdpyecoPfesU8oyddC8x7ojMU7z2LZnvNONmhun7eZq9VH+cmqgR4azWQU9nPkF3MLCwpweMrGdW+IvOIytBKF6h67qSn2n8vF7e3r44XF+922w2ZjKPdA1eiYsCDsnXar38zpI4duoZKcLO1atlqt+OWXX2TXE4Q75BVpj++K54mx42rxIztSb9BaXqr5fYgnO1yzv93qQTxIS9ecJQb2B3Wi5N9U9XTSStdGaYZbft0gqZLoej0qAQZ4VPj6xuy3nN3WoAALNk/uC8YqwmTbMq6g1GrDgNbxkvN0xYQHYcFDFaP5jBAqZTabx0bkxYQFqW/k47gtw44cOYLnn38e9erVw913322ETQThhFQ4R4oBreMxrG19yXV6OvJZIzs4LZPql7S0yO9sPPkGalQSqRlw5W2/Z9Na6N2stmSRMqPg1w3R00krXZvbRIXpOibXkDxGUADndMPZhYrWe9sIjx7fo2L2oa/82yghJgz1YsMQFxGMAanxGNq2nuJkomrU4Y2+e/qWZkisEYZNL/aV3NZqY35TOsAbuHSVCgoK8NVXX6FHjx5o3bo1du3ahTfeeAPnz59X35nH7Nmz0aZNG0RHRyM6OhrdunXD77//7opJhJ+j9hMf37MR1j9/Ez4d3REx4dJvGHqEitRcF1L7a3lO8x/sQYHGPNj5RZ3s+MtMqYBrcxbNe6ALvrm/s8c6z9jwIMy8I83xWc9x5O69v57ujQ48YQJUVBO1w/egBAVYnCoz25vV6lHhexVdLYXvS/2tJwo9Lnm0O+be3xl1eKODnri5KTa80Bf1ZLy55TaGcpGb0CzF1HwBXa8emzdvxhdffIFFixahadOmGDVqFLZu3YoPP/wQrVq1Um9ARGJiIt566y2kpKQAAL755hsMGzYMu3fvRuvWnhnLTvgmcg+cXs1qIyE6FFMGq99/ehIypToWydCPBp8K/03KKI/KN/d3RrtXVxrSlhkxY2dotTHZsKIackIlpU4k9p7JcXyuFRksGB7Lv+UCLRYnYWwXS1prZ/DtmNSvKTgOGJiaoLCHM56s8mw0RlhaOyoEF/NLHJ87NKihsLU0h87nYeWhC4Jlfp5WYiiahUqrVq1QWFiIkSNHYuvWrQ5h8uKLL7p88Ntuu03w+Y033sDs2bOxZcsWSaFSUlKCkpLKGyYvL8/lYxO+xeHMfMnlc+/vrLkNdx8Mrnos+ImhWkNYasT6UeKsFGpTAXwwoh1+3nseq45ke9wWe0fVMbkG6sWG4ev7bkBUqL68ACVvHj8cI86j4nttggPlZbF2j0rlduHBgYp1YuRIquE7I8uM+L2teqY30qb/6VYb9/zfFqdl/hSq9TSaH93Hjx9Hr169cNNNN6FlS+PLJlutVixYsAAFBQXo1k26JPnMmTMFVXCTkpIMt4MwJ2O/2uZ2G+4+GFxNpuUPS3R1CoDqhlSFXX6BreHt6+OrcTdUiS2f3tsBY7sl48N/twcA9GleR5BHogUlIcG/J8R1PywqHhU7WsOaAQZ49FLqROGTUR2w+BHlqSPMwKR+zdxuIyo0CHERxr8Y6A1RDkpzDkdXFzTftRkZGWjevDkeeeQRJCYm4tlnn8Xu3bvdjgfv378fkZGRCAkJwYQJE7B06VLZMNLkyZORm5vr+HfmzBm3jk1UL/R6RObe3xlJcZVvj1L7a2nRU2Xtb28vnTTsyzzVrxmCAyx4WWIOGT0T7xlJx+Q4zBiWimidXhQ+SvceX2SIJwzke1iCAi2yJeu1elQa11Kev0grg9IS0DHZuYS72dBaZVYNV4dyKyEWl1MGOd/zcRHB+PmxHnhtWGu8/a+2htvgK2gWKvXr18eUKVNw/PhxzJs3D1lZWejRowfKy8vx9ddf49ixYy4Z0Lx5c+zZswdbtmzBI488grFjx+LQoUOS24aEhDgSb+3/CEIrej0qvZrVxhvDK5MnXR1azM9RMfJx997dbQVCymiaX0+2vKl5bY8dQ8yT/Zri0Kv90bqetnnDBqfpy6/wFlo9KuJRKPyKs0EBHB69KUWyjXyFuaxeGNAC8x/sgnHdG+KRPk20mkzw8MSrhlioJEqE1AItHNokxmJ0t4a6Jp70N1zyA/bt2xfffvstMjMz8fHHH2PVqlVo0aKFS+Xzg4ODkZKSgk6dOmHmzJlo27Yt/ve//7liFkEoIn6rnTpEPQE3KrTy4SA96kddvHRI4oUJDHzicRzn0SJv8x7ojJcHt8T7I9p57BhS6JlUzZMF9IxEKTTDXycWNMH8/BWLBZEhgY4QFJ+jWZU5XPwQWVr9GDzSpwm6p9TC9KGtNZfaJ4R4In9Y/OiQ8hj6U20kd3ArYBkTE4NHH30UO3bswK5du9CnTx+3DWKMCRJmCcIoxD/6sd2S8dqw1nhhQAvZffhJq67ml8gNlzYCT+a81IkOxYM9G5smcbdb45pOy3zlQa6YTMtbJxa+fHEdpFDzI7eozPH3q8NSHX8rzf5MaMcToR/xS4ZUdVnfuLs9j2EDpNq1a4cPP/xQ1z4vvfQS1q9fj5MnT2L//v2YMmUK1qxZg1GjRhllFkE4EId+AgMsGN2tIVrEy9eTaFgzHIPTEnBHh/qSxaH06gRmsBPZVzpqI+jdrDbm3HcDNvKKajWpHamwh3lQCjsq5q9wzt4WqU4zqUa45P5h5EExhKduqUjKvbtTomFtju3WUPA5MMCC9c/fhF8fv9GwY/gLmoJeAwYMwCuvvILu3bsrbpefn49PPvkEkZGRmDhxomq7Fy5cwOjRo5GZmYmYmBi0adMGK1aswC233KLNeoLQgVyHoNRRcByHWaOcq9S6itEvZtVpiCPHcbipeR3Bsgd7NkJOYSlualFHZi9zIL7HUutHY2KfinwTfoVTpf2UpoCYMaw1IkICMfp62KdWZAguXStBf4nChdUFI38a47o3RO9mtdGwpnoysoXTVgcoLDgAqfWjceBcRZmNwAAOSXHhqM/b2eyVf6sKTULlrrvuwt13342oqCgMHToUnTp1Qr169RAaGoqrV6/i0KFD2LBhA3777TcMGTIE77zzjqaDf/nll24ZTxB6kEtnEHf2ekbTePs5Up08KlKEBAZoKvbnbcS5J78+3tPxd8uEaEwd0goJEjPg8vezX2upUFzd6FC8e3flqJC/n+mNzNwitIivvgMOjAyLchyHxhq9d8GB8nM3iflkZEf0emc1gEp7/anCtFFoEioPPPAARo8ejR9//BELFy7E559/jpycHAAVF7BVq1bo378/du7ciebNm3vSXoJwGblOnV9a4osxnXBzS/W384d7NcZn605gqpc7yWf7N8OdszcLEigJ86FWv+SBGxtJLq8hUb+jV9NaGNe9odOMv3xiwoKqxWR1SnjL2xgcoF2o8Ef6FJVaPWWSz6N5vFNwcDBGjhyJkSNHAgByc3NRVFSEmjVrIiioev8gCN9A7k2F/0CLjwnV5G6dPKglHr0pRXdnYHRKXsfkOOyffmu1HrroC7haFbl1PWcxwnEcpg+lKUbU8OD8n4oEBwYA0Dbbu8XC4bn+zbHvbA5uaOhcRLCknMQLoHOuHz726rAE4SvIvWEFSLjXteDKG6snRg/oLedOVD2uVoRtXS8G749oizpRxhQuq054z6Oi77gTZWrjAEBekTbB4+/QtEiE6blSUCq5XGo4nxJ8ETKue0PH3xYXhQpBaIXfaSqNMpPi9vaJ6JFSy2iT/B5v5XrIeWRdKZxYatUWQvJ3SKgQpmfqTwckl+sd6stPQgzhDTXmdyKefrbJlUAn/Bu+pv72wS7eM6Qa4a2XjntukJ6D7tn+zfH8AMrhdAUSKoTp+fvwBcnleqMo/FEVnECcSP9tJF+O7YRezWoLinER1Qf+/VadhpR7E299z4/1TcGWyTc7LQ+0WKiujYtQBh5heuQy6PVme/DL4fNftvjpA54SKje3rIubW9b1SNuE+eF3UDSDdtXgzdBPvMRQ8wALp3kOK0KIbqHCGMPOnTtx8uRJcByHRo0aoX379lSYhqhy9Cam8gtm8TsLV5NpCUIrfJHMkR+7SjCb5yrQwqFzozj87552aKQyi3WzupE4duEaIrw0Y7jZ0CVUVq9ejQceeACnTp1ydBJ2sfLVV1+hV69eHjGSqL4YWVuAL1T4zzBBjgoJFcIDCCa3NFkH6q+Y7aXDbs+wduoFJT8f0wnv/nkMD/du7GmzfALN2v748eMYMmQIGjZsiCVLluDw4cM4dOgQfvjhByQmJmLQoEE4ceKEJ20lqiF5xWWy6/SGfoJ4wwZtPG8MX5yY7NlG+An8JGoK/VQN3qqjIoeel6DkmhH48N/tKVR0Hc0elQ8++ABdu3bF33//LVjeokUL3H777ejXrx/ef/99fPTRR4YbSVRPdp++ikIFj8pAnfOY8D0q5bz5NAIo0ZHwAGFBASgqq7h/+bcV3WJVg9l+y+ayxrfQrDnXrFmDSZMmSa7jOA6TJk3C6tWrjbKLqOZk5hbh9k82YdQXWyXXp9WPwVt3ttHVZiDfo8IXKrw3Hcq1Iozi2we7oEntCMy9v7NghBp5VKoGb4dxZ4iqB9Nldx3NQuX06dNIS0uTXZ+amopTp04ZYhRBZFwqUFw/sksDROusyBpkkfaoCPJVKPZDGETH5Br4+5k+6NWstiBMSbdY1eBtj8rY7g2x4+V+XrXBX9AsVK5du4bw8HDZ9eHh4SgsLDTEKIJQS0BxpRI9/w3LKjMPO3UihKchj4pnefbWZgCA14Z7v2YRf5qNGhKzXhPa0DXq59ChQ8jKypJcd+nSJUMMIggt2NycM0foUaFRP4RnEYR+6B7zKI/1bYrxvRojJND7Q3uDAizYPLkvrDaGUCr25jK6hMrNN98sWbuC4zgwxii+TxiHyq3k7uR+VqucR4XuYYLwdcwgUuwkxIR52wSfR7NQycjI8KQdBCFELfTjZvNWntAhaUJ4Gk/Mmk0Q1QXNQiU5OdmTdhCELgLdLJLAz1Hhu2S9nYBHEARBCNEsVK5cuYLCwkIkJiY6lh08eBD//e9/UVBQgOHDh2PkyJEeMZKohkjohRrhQbhaWFEAjj/U2BX4OSpxEcGYMqglggI4hFHJasIDUF4KQbiO5tfSiRMn4r333nN8zs7ORs+ePbF9+3aUlJRg3LhxmDdvnkeMJKohIk95/dgw7Jp6i+NzoJsPfqtNONHh+F6NMa5HI7faJAg52ifFon2DWNzRXr18OkEQQjR7VLZs2YI5c+Y4Ps+dOxdxcXHYs2cPAgMD8d///hezZs3C6NGjPWIoUb2xWISjcwIDjAv9EISnCQywYOmjPbxtBkH4JJqf9llZWWjUqPKNc9WqVbj99tsRGFihdYYOHYr09HTjLSSqJyKHiXg0jvseFRIqBEEQvoBmoRIdHY2cnBzH523btqFr166OzxzHoaSkxFDjiGqMSEeIk1zdrSBbTkKFIAjCJ9AsVDp37owPP/wQNpsNP/74I/Lz89G3b1/H+mPHjiEpKckjRhKEOBmxYc0It9ojjwpBEIRvoDlH5bXXXkO/fv3w7bffory8HC+99BJq1KjhWL9gwQL07t3bI0YS1RCRw8TuUflxQjdk5RWjeXyUW82XyxR8IwiCIMyFZqHSrl07HD58GJs2bUJ8fDy6dOkiWH/PPfegVatWhhtIVFNEOsIe+enUMM6Q5q1UgIsgCMIn0FVCv3bt2hg2bJjkusGDBxtiEEFIYfSsxu0bxBraHkEQBOEZNAuVuXPnatpuzJgxLhtDEHIYJVT+fqY3/jp0AWO6NTSkPYIgCMKzaBYq48aNQ2RkJAIDA2XnreA4joQK4RGMmvCySe1INOkdaUhbBEEQhOfRLFRatmyJCxcu4N5778X999+PNm3aeNIughDgZsV8giAIwkfRPDz54MGDWL58OYqKitCrVy906tQJs2fPRl5eniftIwgAxueoEARBEL6BrjrkXbp0wWeffYbMzEw88cQTWLRoERISEjBq1Cgq9kYYiji4KK5MSxAEQVQPXJowJSwsDGPGjMGMGTPQuXNnLFiwAIWFhUbbRlRjxGlQJFQIgiCqJ7qFyrlz5/Dmm2+iadOmuOeee3DDDTfg4MGDguJvBOEuNpFSodAPQRBE9URzMu2iRYswZ84crF27Fv3798e7776LwYMHIyAgwJP2EdUUp9APCRWCIIhqiWahcs8996BBgwZ46qmnULduXZw8eRKzZs1y2u6JJ54w1ECieiL2qJBOIQiCqJ5oFioNGjQAx3GYP3++7DYcx5FQIQxBXKtHPHsyQRAEUT3QLFROnjzpQTMIQojNJvxMoR+CIIjqiUujfuQ4d+6ckc0R1Rhxjgp5VAiCIKonhgiVrKwsPP7440hJSTGiOYJwzlExVFITBEEQvoLmx39OTg5GjRqF2rVro169evjwww9hs9nwyiuvoHHjxtiyZQu++uorT9pKVCPeWH5Y8JnqqBAEQVRPNOeovPTSS1i3bh3Gjh2LFStW4KmnnsKKFStQXFyM33//Hb179/aknUQ14/QVYQFBqqNCEARRPdEsVJYvX445c+agX79+ePTRR5GSkoJmzZrhgw8+8KB5BFEBeVQIgiCqJ5pDP+fPn0erVq0AAI0bN0ZoaCgefPBBjxlGEHxIqBAEQVRPNAsVm82GoKAgx+eAgABERER4xCiCEFNYWu5tEwiCIAgvoDn0wxjDuHHjEBISAgAoLi7GhAkTnMTKkiVLjLWQIACczynytgkEQRCEF9AsVMaOHSv4fO+99xpuDEHIYRVPp0wQBEFUCzQLlTlz5njSDoJQxGpT34YgCILwP6iMFuETWMU19QmCIIhqAQkVwiew2ij0QxAEUR0hoUL4BKRTCIIgqickVAifoF5sqLdNIAiCILwACRXClNSJChF8fvP2NC9ZQhAEQXgTEiqEKRHPnpxUI9xLlhAEQRDehIQK4TKl5TZk5RZ7pG1xToqFJiUkCIKolpBQIVyizGpDs5d/R9eZf+PAuVzD2xd7VAiCIIjqCQkVwiUW7Tjj+PvHnWcNb99Gw3wIgiAIkFAhXOQCL+RTUm41tO2CknKQQ4UgCIIAdJTQJwg+AZZKjVtcZlzV2E/X/oO3fj9iWHsEQRCEb0MeFcIlAnh3TnGZcR4VEikEQRAEHxIqhEvwPSqU+EoQBEF4ChIqhEvwPSqBFrqNCIIgCM/g1R5m5syZuOGGGxAVFYU6depg+PDhOHr0qDdNIjTC96gEUI0TgiAIwkN4VaisXbsWEydOxJYtW7By5UqUl5fj1ltvRUFBgTfN8htOXLyGh+buwL6zOYa3HcDTJoEkVAiCIAgP4dVRPytWrBB8njNnDurUqYOdO3eiV69eTtuXlJSgpKTE8TkvL8/jNpqdzf9cRu2oEKTUiXRa9+A3O3DiUgHWHL2IY28MNPS4AbzYD1WNJQiCIDyFqZILcnMrKpzGxcVJrp85cyZiYmIc/5KSkqrSPNNxPDsf//58C/q9t1Zy/YlLFZ6pUqtxw4ft8KUJ5dISBEEQnsI0QoUxhqeffho33ngjUlNTJbeZPHkycnNzHf/OnDkjuV114XBmvteOzfGUCjlUCIIgCE9hmoJvjz32GPbt24cNGzbIbhMSEoKQkJAqtMrceNORERlSeevERQTjeHY+QoMCkKhzluNNxy/h2IV8jO3eEBxHiocgCIIQYgqh8vjjj+Pnn3/GunXrkJiY6G1zfJqD53ORcakAQ9rUEywvLrMiNCjAsOPwa6dcLihFv/fWAQBOvjVYVzsjv9gKACgpt+GhXo0Ns48gCILwD7wqVBhjePzxx7F06VKsWbMGjRo18qY5PgeTSA4Z/GGFRyo2LFiwvMxqM1ao8NJeTl8pdKmNvw5dcPw98/cjkgnBBEEQRPXGq0Jl4sSJmD9/Pn766SdERUUhKysLABATE4OwsDBvmmZqyq02FJRYBUmsjDFB6GTN0WzBPjaD82kF1Wh5f9psTPMooAfn7hB8/mXveadtxnZLRrcmNV2ykSAIgvB9vCpUZs+eDQDo06ePYPmcOXMwbty4qjfIR7hz9ibsPZuLKYNaOpZ1f2sVHuaFTr7YkCHYp9xgpSI30sfKGCxwLddEanTStNta0/BngiCIaozXQz+EPh79bif2nq0Yxr322EXH8szcYkz/5ZDsflaDv2u+R4XxXCpWG4OrEaaiUufJDUmkEARBVG9MMzyZUIcxht/2Zzk+147SPgLK+NBP5d98DWS1uS6Iyt3YlyAIgvBPSKh4iB92nMFKXrKoEYidInpG8xoZ+im32vDS0v0yx3FdbLgjcgiCIAj/xBTDk/2NM1cK8dyP+wDoH66rhLgbL7Nq79iN9KjwQ04AsOPUVd5xSKgQBEEQxkEeFQ9wpaDUI+2Kc3pKypxzOuQwMkdFSSC541Gh0A9BEAQhhoSKB+CHZIxMGBa3VFyu3U1iNdClohRycscrspPnmSEIgiAIgISKxzEynCHWPMV6PCrGz0sofRwayUUQBEEYCAkVD2NkNIOJfCr6hIpxhlgUXCpWHXkzBEEQBKEGCRUPwPEKntmMDP2ImpKqOyKHkUJFabAReVQIgiAIIyGh4mE8Gvop904yrXKOivYYU3Ag3X4EQRCEMtRTeAB+R26kQHAO/ehJpq0aoaJn5M6g1HgDrCEIgiD8GRIqHsaduiJixJrnYn6J4PNjN6WgY3INyX2NDf0o5KjoOA4FiQiCIAg1qOCbhzE09KOyfkjbBNSvESY5zNfQYmpKHhUdybRqzqa/nu6tuS2CIAjCPyGPigfgd8CGjvpR6dmVRuMYm9Qr39aVQu3F7tQsalwrQnNbBEEQhH9CQsUD8EWBoQJBZX1VCRWlmiwXcos1t6NmE82cTBAEQZBQ8QD8DtjQ0I9K7qxSv67HjPziMuw8dVXWc6J0Tocy87QfiJJUCIIgCBVIqHgAjwkVlZ7dwnGyeR96SvnfOXsT7py9Cb/sy5Rcr+QJ2XFSexl8pXaevqWZ5nYIgiAI/4WEigewCXJUPDfqR0yAgktFjxnHLlwDACzddVZS4CgNQb50rUR2nR6bnri5qeZ2CIIgCP+FhIoH4HtRjC2hr4xSfRNXBFNRmRV3fboZ//6/LQLBojTkukzHpEJ2D9HLg1sKlvdsWkunpQRBEIS/QsOTPQBfFPyTfQ2NDBq94s6oH/uuxWVWbDlxGV0b10RoUIBie1tOXHH8nV9SjujQIADK4awyHcOT7c2EBwtvw6AA0s8EQRBEBdQjeAC+nnh+8T7j2lVZH2DhZPNYfj+QhScX7MaUpQcwbs52TF6y32mbqwWlGPvVNsn9+V6U/OIyp/Wfj+kEACgt1+FRud4kDe4hCIIg5CChopM9Z3LwwNfbcTw7X3YbvschR0ddETXUwjdih8pT/ZohOrTCW7F411n8tOc8Fu86CwBYuvuc0/6/7s/E2mMXZY5d+feJSwVO60ODKm6lUqvN4fkpt9ow7acD+H2/c1Lutowr+OfiNUm7SbcQBEEQdkio6CA7vxjDZ23E30eyMfpLZ8/Dpn8u4d0/jwq8CiGByuEVXai4VMShnyf7NUXz+CjtzSsIoSW7zuLg+VwAQG5RhUclISbUsT4uItjx92frTlzf5xy+2XwKj3y3S9DWmSuFuPuzzci4LniUSvITBEEQ1RsSKjr4v7UnHH9n5hbjsmiEy8jPt+KjVcfx897zjmV2TwNQETLZ9M8lQRhl+b5MzNtyClcL1D0vqsm0AKKu55E4lill2Org9eWHMfjDDQCAkuuTIfI9PElx4Y6/3/r9CMqsNmTKFH87dblQZCNVoSUIgiCkIaGig8siMfHuymOOv/neiCu87Ya1q+/4++7PtmDk51sxd/NJAMDeMzmYOH8Xpi47gN7vrFY9vv0QgTJJHQwVMxIPaZOAGUNbA9AXRtEyMMhqYygptwIQ5qNEiBJiS8ttsqEqvngDKsTUwoe7OT7f3LKuVpMJgiAIP4eEihvM33rakVhaVGZ1LK/BC4PwR9Ycvl61demeCo/L0QuVeS55xeWqx7MnynIcMO22VpLbBAZY8PHIDhjbvSEA5ZFATu1rUCrv/HEUJdcFCn9rcQ2XknKboL2Nxy85/haXxrdwQO2oEGyf0g9fjOmEe25I0mwzQRAE4d+QUNGBVJ+fdT28YQ+HAMDfhy84/i5XqCuiZ6ZhoNLjwXEc7uvRyMmzIuVpsShcYfEwYy3WfLr2HxSWWlW3Kym3ooC33agvtjr+Fp+3/XutHRWCfq3q0hw/BEEQhAOqo6KRXaevYsku55Ey9hyQUp4g4XfkUlVcOcc67UN5gcqcEPv+W166GWevFmHN0WzYbAyx4cFO+yh5VC7kFaNudCj2nLmK1vViNNux50yO6jYlZTZ8uSFDsOyjv9Px+M1NnYrCUTItQRAEIQcJFY3c8ckmyeUWDsgrLsOMXw5Kri+32XD2aiESYsIcy+zawXWPSsX/a0WGoFZkCNolxepqx073t1Y5/h7QOh6dG8W5ZI8UJRL1VN5deQyP39xUIOoA5Yq6BEEQRPWGhIqbWDgO7/5xFL/tz5Jc/8veTHy75TQGpcU7lrnqUancX3vPrjVHZcXBLFh1ltmvFRnsGKosZsnus5LLL18rQVm5WKiQUiEIgiCkIaHiJtdKynE4S774m70jlxIyesrNA84eFS3oSfdYeeiC+kY8Xh7SCl9tyMC/OzdwWvcZbyg3n1Krzem8KSWFIAiCkIOEipsM+WgDOjfUFzKxexCkwiNKbLg+ckZPv+5Jb0VibBjmPdBF1z5WG3PyJFGOCkEQBCEHjfoxgG0nr6hvxMPeLX+5Xuh1OJ9TpLjfS0sr5ucp0DDqxo4nvRWuVN1lzHk+IIr8EARBEHKQUNGAeJSKUTSpEyn4fMt7aw0/hic9KiFB+m8fq41h0z+XBctIpxAEQRBykFDRQE6hdMKoO9hsDPvO5gqW6fGUaMWTIiAkUP/tk1tU5jQhYnG58edNEARB+AckVDRgtEeF44DTVwrVN+ShpWqsFHoq0+pFHPqRSqoVc+yCc+KxlgJyBEEQRPWEhIoGxEmvrtYtscOBcyo5r4ZU4TgtKFWmdZdgkUflzdtTVfcRF4EDgCISKgRBEIQMNOpHAyWi0ISr3g0+ckKlpNwq8FSUlttw5+xNKChVnwtICk+OqBGfA8dxCArgFIddX8wvcVpGHhWCIAhCDvKoaIA/j8+2l27WXRjNCc55nh07P+wQFkpbczQb+8/l4sTFApcOtXx/pkv7uQp/EkYppIZkuyrCCIIgCP+HhIoG7J1r41oRqBMdChcLyjrgUDlvj5irBaWCz3KCxhtoiVZFBFc66aTqy4iHJgNASu1Ip2UEQRAEAZBQ0YQ99GPPyZATGXqQyzmJDBVG48wjU4CEmDCEqgxJDg+p9Kgk1wx3Wi+e5+eVIa1wR4dEYwwkCIIg/A4SKhqwh35Croc13PVycFzF8GQpTl8pxMT5u7Dz1FUAyhP/VTUWC1AzIkRxG35+TZnVhvqxYbLbxoYH4f4bG+lOLCYIgiCqDyRUNGCv8xFikEeFAyeb5zJn40ks35eJO2dXzNbMTORT4cCpTqQYFVLpESqzMfy7c5Lstm/f2cYw2wiCIAj/hISKCgfO5eKx+bsB8IWK++1q9coY6VHZ9tLNqtuseqY3AKB2lLPnhFNIArbz5h1plR8YML5XYzzXv7nTdl+N64RbW8c7LScIgiAIPiRUVHj2h72Ov+1hDXc9KmVWG/acydG0rZH+lNpRITjy2gDsm34rlj9xo+Q2jWtHYvuUflj//E1O6yyc8tBjAEjhTQvAwBASGICJN6WgSe0IwXax4cEunAFBEARR3aA6KirwPQj2uW3czVHZceoqdlzPQalKOI5DaFAAQoMC0LpeDFolRONQZp5j/fB29QBIe1Mq9td37vwo0YlLwuHVQZ6sREcQBEH4DdRbqMD3nthDP3yHyoM3NsLvT/bEtNtaoU5UCEZ3TQYApNaPdvvY53OKcDQrT31DFwkMECaxBqiIhwqPivax2fz8GrETihJoCYIgCC2QR0UGxhhmrT6Of3iF1uyhH75X4eUhrQAALROiMa57QwDA2O4NwRjDLe+vc8uGCd/udJq40EjEYiFQ9PnbB7rg7NVCvLhkP4CK+i+6PCoKm6ol5RIEQRAEQB4VWVYdycZ//zwmWGb3qMh5SziOA8dxSKkT6TQPjisYIVLsEwU+c0szp3ViYRIg8rDc2LQW7uFNNGjhOF1zDilNNUDz+xAEQRBaII+KDBfynOekseeovHVnG8xafRz33CA/W3BggDk04OvDUzG2ezKa141yWjcwNQHbT1bmyoQGKpe/75BcA0clZj+WQynnuK2bEzsSBEEQ1QMSKjJIVWC1h35qRYZg2m2tFfcPMiAHo0FcOE5fKXSrjQALhxbx0h6gsd0bol5sGLZmXMaaoxfx6E1NJLf76+le+HVfJh64sRG+33Za87HldMrsUR1U5wQiCIIgCICEiixhEh1piI5wjhHJonIixShvRICFw4DUeAxIjce02+S3S6kThUn9Kjwy3z7QBU8u2I2Z/HopMsiFfsKCSaQQBEEQ2iChIgPHOQsNPULFU6Gf14anYmRn+ZCTp7mxaS3seLmf5PcjRi6dJdgkYTGCIAjC/FCPIYPUqJQQHeGKoADPDL+NDQvy+tBeLSIFEIZ+BrdJcPxtRKIxQRAEUT2gHkMGqXohVR36kcKiUSR4kzHdKmrJTOrX1LHs3i7Jjr8pP4UgCILQCgkVGaRKxesRKvzKq//qmIhmdSMVttaOL0RNXh2WioMz+qNDgxqOZfzkZMpRIQiCILTiA92edzhwzrmGSYjK8F0+Fp5HhTF5L0LNiGA0rhUhuU6yXR/wqABARIgw/Yl//lKJygRBEAQhBQkVCa4WlGLu5lNOy0MkhixrgYEhIlg6b7lL4zj8/UxvbJmsPrMx4Lul54N4riASKgRBEIRWSKhIcPZqkeRyPaEfMa8NT5VMsO3epBY4jkN8TKimdiw+KlT4qbUU+iEIgiC0QkJFgpyiUsnlekI/AhiQUicSe6fdKljcMbmGo8Q9UFEILSo0EO+PaCvblDtiyZvUja4UYr56DgRBEETVQ3VUJLhSICdUXOtg7TMwB4kyYe/qmCgI5QxMS0D/1vGwWDg8tXCvZFsxYUEu2eBtokKDsPrZPggK4DQPbyYIgiAIerWVIKVOJCZKlJOXKquvB7FQkQqB2EM7cqOEokN9U6gAQKNaEUisEe5tMwiCIAgfgoSKBK3rxeC5/i2clrsa+uEPdL7nhiTH34PSEpw3VqFGRLBLNhAEQRCEL+JVobJu3TrcdtttqFevHjiOw7Jly7xpjiquVlTlT3nzbP/m6No4Dh+MaOfkYdFCZAhF6wiCIIjqg1eFSkFBAdq2bYuPP/7Ym2Zoxogk0FqRIVjwUDcMb19fcTsOznkcHRrEun18giAIgvAlvPp6PnDgQAwcOFDz9iUlJSgpKXF8zsvL84RZshgR+tG+j/NeCbFhLh2fIAiCIHwVn8pRmTlzJmJiYhz/kpKS1HcyENdDP65IFWdua1PPkHYIgiAIwlfwKaEyefJk5ObmOv6dOXOmSo/valVYV2RKu6RYx9+T+jXFwNR43NKqrkvHJwiCIAhfxacyM0NCQhASEuJtM/TjglKZMrgVakaGYFi7emgRH228TQRBEAThA/iUUPE1akeF4GJ+CW5trd8TEhMWhBcGOA+RJgiCIIjqBAkVjfyrY6Luff6Y1AtHMvPQrUlND1hEEARBEP6PV4XKtWvXcPz4ccfnjIwM7NmzB3FxcWjQoIHCnlVDp+Qa2HHqKgDgv3fJz78jR1xEMLqn1DLaLIIgCIKoNnhVqOzYsQM33XST4/PTTz8NABg7diy+/vprL1lVSV2NMxoTBEEQBOEZvCpU+vTpY9jQXU9gocnzCIIgCMKr+NTw5KqGZApBEARBeBcSKgq4WDaFIAiCIAiDIKGiQFiwayXzCYIgCIIwBhqerMBT/Zpha8YVjOzs/RFIBEEQBFEdIaGiQJ3oUKx6po+3zSAIgiCIaguFfgiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC0kVAiCIAiCMC2B3jbAHRhjAIC8vDwvW0IQBEEQhFbs/ba9H1fCp4VKfn4+ACApKcnLlhAEQRAEoZf8/HzExMQobsMxLXLGpNhsNpw/fx5RUVHgOM7QtvPy8pCUlIQzZ84gOjra0LbNAJ2f7+Pv5+jv5wf4/znS+fk+njpHxhjy8/NRr149WCzKWSg+7VGxWCxITEz06DGio6P99gYE6Pz8AX8/R38/P8D/z5HOz/fxxDmqeVLsUDItQRAEQRCmhYQKQRAEQRCmhYSKDCEhIZg2bRpCQkK8bYpHoPPzffz9HP39/AD/P0c6P9/HDOfo08m0BEEQBEH4N+RRIQiCIAjCtJBQIQiCIAjCtJBQIQiCIAjCtJBQIQiCIAjCtJBQkeCTTz5Bo0aNEBoaio4dO2L9+vXeNkkTM2fOxA033ICoqCjUqVMHw4cPx9GjRwXbjBs3DhzHCf517dpVsE1JSQkef/xx1KpVCxERERg6dCjOnj1blaciyfTp051sj4+Pd6xnjGH69OmoV68ewsLC0KdPHxw8eFDQhlnPzU7Dhg2dzpHjOEycOBGA712/devW4bbbbkO9evXAcRyWLVsmWG/UNbt69SpGjx6NmJgYxMTEYPTo0cjJyfHw2SmfX1lZGV544QWkpaUhIiIC9erVw5gxY3D+/HlBG3369HG6pvfcc48pzg9Qv4ZG3ZNmvIYAJH+PHMfhnXfecWxj5muopV8w+++QhIqIhQsXYtKkSZgyZQp2796Nnj17YuDAgTh9+rS3TVNl7dq1mDhxIrZs2YKVK1eivLwct956KwoKCgTbDRgwAJmZmY5/v/32m2D9pEmTsHTpUixYsAAbNmzAtWvXMGTIEFit1qo8HUlat24tsH3//v2OdW+//Tbee+89fPzxx9i+fTvi4+Nxyy23OOaEAsx9bgCwfft2wfmtXLkSAHDXXXc5tvGl61dQUIC2bdvi448/llxv1DUbOXIk9uzZgxUrVmDFihXYs2cPRo8e7dXzKywsxK5duzB16lTs2rULS5YswbFjxzB06FCnbcePHy+4pp999plgvbfOD1C/hoAx96QZryEAwXllZmbiq6++AsdxuPPOOwXbmfUaaukXTP87ZISAzp07swkTJgiWtWjRgr344otessh1srOzGQC2du1ax7KxY8eyYcOGye6Tk5PDgoKC2IIFCxzLzp07xywWC1uxYoUnzVVl2rRprG3btpLrbDYbi4+PZ2+99ZZjWXFxMYuJiWGffvopY8zc5ybHk08+yZo0acJsNhtjzLevHwC2dOlSx2ejrtmhQ4cYALZlyxbHNps3b2YA2JEjRzx8VpWIz0+Kbdu2MQDs1KlTjmW9e/dmTz75pOw+Zjk/xqTP0Yh70iznqOUaDhs2jPXt21ewzJeuobhf8IXfIXlUeJSWlmLnzp249dZbBctvvfVWbNq0yUtWuU5ubi4AIC4uTrB8zZo1qFOnDpo1a4bx48cjOzvbsW7nzp0oKysTfAf16tVDamqqKb6D9PR01KtXD40aNcI999yDEydOAAAyMjKQlZUlsDskJAS9e/d22G32cxNTWlqKb7/9Fvfff79g0k1fvn58jLpmmzdvRkxMDLp06eLYpmvXroiJiTHdOefm5oLjOMTGxgqWf/fdd6hVqxZat26NZ599VvAm6wvn5+496QvnCAAXLlzA8uXL8cADDzit85VrKO4XfOF36NOTEhrNpUuXYLVaUbduXcHyunXrIisry0tWuQZjDE8//TRuvPFGpKamOpYPHDgQd911F5KTk5GRkYGpU6eib9++2LlzJ0JCQpCVlYXg4GDUqFFD0J4ZvoMuXbpg7ty5aNasGS5cuIDXX38d3bt3x8GDBx22SV27U6dOAYCpz02KZcuWIScnB+PGjXMs8+XrJ8aoa5aVlYU6deo4tV+nTh1TnXNxcTFefPFFjBw5UjC526hRo9CoUSPEx8fjwIEDmDx5Mvbu3esI+5n9/Iy4J81+jna++eYbREVF4Y477hAs95VrKNUv+MLvkISKBPy3V6Di4oqXmZ3HHnsM+/btw4YNGwTLR4wY4fg7NTUVnTp1QnJyMpYvX+704+Njhu9g4MCBjr/T0tLQrVs3NGnSBN98840jec+Va2eGc5Piyy+/xMCBA1GvXj3HMl++fnIYcc2ktjfTOZeVleGee+6BzWbDJ598Ilg3fvx4x9+pqalo2rQpOnXqhF27dqFDhw4AzH1+Rt2TZj5HO1999RVGjRqF0NBQwXJfuYZy/QJg7t8hhX541KpVCwEBAU7qLzs720ltmpnHH38cP//8M1avXo3ExETFbRMSEpCcnIz09HQAQHx8PEpLS3H16lXBdmb8DiIiIpCWlob09HTH6B+la+dL53bq1Cn89ddfePDBBxW38+XrZ9Q1i4+Px4ULF5zav3jxoinOuaysDHfffTcyMjKwcuVKgTdFig4dOiAoKEhwTc18fmJcuSd94RzXr1+Po0ePqv4mAXNeQ7l+wRd+hyRUeAQHB6Njx44Od52dlStXonv37l6ySjuMMTz22GNYsmQJVq1ahUaNGqnuc/nyZZw5cwYJCQkAgI4dOyIoKEjwHWRmZuLAgQOm+w5KSkpw+PBhJCQkONyufLtLS0uxdu1ah92+dG5z5sxBnTp1MHjwYMXtfPn6GXXNunXrhtzcXGzbts2xzdatW5Gbm+v1c7aLlPT0dPz111+oWbOm6j4HDx5EWVmZ45qa+fykcOWe9IVz/PLLL9GxY0e0bdtWdVszXUO1fsEnfodupeL6IQsWLGBBQUHsyy+/ZIcOHWKTJk1iERER7OTJk942TZVHHnmExcTEsDVr1rDMzEzHv8LCQsYYY/n5+eyZZ55hmzZtYhkZGWz16tWsW7durH79+iwvL8/RzoQJE1hiYiL766+/2K5du1jfvn1Z27ZtWXl5ubdOjTHG2DPPPMPWrFnDTpw4wbZs2cKGDBnCoqKiHNfmrbfeYjExMWzJkiVs//797N///jdLSEjwiXPjY7VaWYMGDdgLL7wgWO6L1y8/P5/t3r2b7d69mwFg7733Htu9e7dj1ItR12zAgAGsTZs2bPPmzWzz5s0sLS2NDRkyxKvnV1ZWxoYOHcoSExPZnj17BL/JkpISxhhjx48fZzNmzGDbt29nGRkZbPny5axFixasffv2pjg/tXM08p404zW0k5uby8LDw9ns2bOd9jf7NVTrFxgz/++QhIoEs2bNYsnJySw4OJh16NBBMLzXzACQ/DdnzhzGGGOFhYXs1ltvZbVr12ZBQUGsQYMGbOzYsez06dOCdoqKithjjz3G4uLiWFhYGBsyZIjTNt5gxIgRLCEhgQUFBbF69eqxO+64gx08eNCx3mazsWnTprH4+HgWEhLCevXqxfbv3y9ow6znxuePP/5gANjRo0cFy33x+q1evVrynhw7dixjzLhrdvnyZTZq1CgWFRXFoqKi2KhRo9jVq1e9en4ZGRmyv8nVq1czxhg7ffo069WrF4uLi2PBwcGsSZMm7IknnmCXL182xfmpnaOR96QZr6Gdzz77jIWFhbGcnByn/c1+DdX6BcbM/zvkrp8IQRAEQRCE6aAcFYIgCIIgTAsJFYIgCIIgTAsJFYIgCIIgTAsJFYIgCIIgTAsJFYIgCIIgTAsJFYIgCIIgTAsJFYIgCIIgTAsJFYIgCIIgTAsJFaLawXEcli1b5vHjNGzYEB988IFp2lHi66+/RmxsrEePoQdXz/ny5cuoU6cOTp486Vi2ceNGpKWlISgoCMOHDzfMRkKdf/3rX3jvvfe8bQbh45BQIfyK7OxsPPzww2jQoAFCQkIQHx+P/v37Y/PmzY5tMjMzMXDgQC9aKY2cWNi+fTseeuihqjeoCjBaIM2cORO33XYbGjZs6Fj29NNPo127dsjIyMDXX39t2LHMxieffIJGjRohNDQUHTt2xPr16xW3z8zMxMiRI9G8eXNYLBZMmjTJcJteeeUVvPHGG8jLyzO8baL6QEKF8CvuvPNO7N27F9988w2OHTuGn3/+GX369MGVK1cc28THxyMkJMSLVuqjdu3aCA8P97YZpqeoqAhffvklHnzwQcHyf/75B3379kViYqKkKGKMoby8vIqs9AwLFy7EpEmTMGXKFOzevRs9e/bEwIEDcfr0adl9SkpKULt2bUyZMkXTjMCu0KZNGzRs2BDfffedR9onqgluzxZEECbh6tWrDABbs2aN4nYA2NKlSxljzDFx3MKFC9mNN97IQkNDWadOndjRo0fZtm3bWMeOHVlERATr378/y87OdrTRu3dv9uSTTwraHTZsmGAis+TkZPb+++87Pr/77rssNTWVhYeHs8TERPbII4+w/Px8xpj0xGjTpk2TbOfUqVNs6NChLCIigkVFRbG77rqLZWVlOdZPmzaNtW3bls2dO5clJyez6OhoNmLECMFMqGLmzJnDYmJiBMt+/vln1qFDBxYSEsIaNWrEpk+fzsrKygTf4+eff86GDx/OwsLCWEpKCvvpp58Ebfz0008sJSWFhYaGsj59+rCvv/6aAWBXr15VPec33niD3XfffSwyMpIlJSWxzz77TNZ+xhhbvHgxq1WrluOz1KSAc+bMcRx3xYoVrGPHjiwoKIitWrWKHT9+nA0dOpTVqVOHRUREsE6dOrGVK1cKjpGcnMxee+01Nnr0aBYREcEaNGjAli1bxrKzsx3XJDU1lW3fvl2w38aNG1nPnj1ZaGgoS0xMZI8//ji7du2aY/2sWbNYSkoKCwkJYXXq1GF33nmn4rmK6dy5M5swYYJgWYsWLdiLL76oaX+p+5kxxsaOHcuGDRvG3nnnHRYfH8/i4uLYo48+ykpLSzXbPn36dNazZ09d50MQfEioEH5DWVkZi4yMZJMmTWLFxcWy20kJlRYtWrAVK1awQ4cOsa5du7IOHTqwPn36sA0bNrBdu3axlJQUQUfgilB5//332apVq9iJEyfY33//zZo3b84eeeQRxhhjJSUl7IMPPmDR0dGOadjtIobfjs1mY+3bt2c33ngj27FjB9uyZQvr0KED6927t+M406ZNY5GRkeyOO+5g+/fvZ+vWrWPx8fHspZdekv1OxEJlxYoVLDo6mn399dfsn3/+YX/++Sdr2LAhmz59uuB7TExMZPPnz2fp6ensiSeeYJGRkY5ZYzMyMlhQUBB79tln2ZEjR9j333/P6tev7xAqauccFxfHZs2axdLT09nMmTOZxWJhhw8flj2HJ598kg0YMMDxuby8nGVmZrLo6Gj2wQcfOKa2twuVNm3asD///JMdP36cXbp0ie3Zs4d9+umnbN++fezYsWNsypQpLDQ0lJ06dUpwTePi4tinn37Kjh07xh555BEWFRXFBgwYwBYtWsSOHj3Khg8fzlq2bMlsNhtjjLF9+/axyMhI9v7777Njx46xjRs3svbt27Nx48Yxxhjbvn07CwgIYPPnz2cnT55ku3btYv/73/8E10bpnbKkpIQFBASwJUuWCJY/8cQTrFevXrL78VESKtHR0WzChAns8OHD7JdffmHh4eHs//7v/zTZzhhjv/32GwsJCVH8TRKEEiRUCL/ixx9/ZDVq1GChoaGse/fubPLkyWzv3r2CbaSEyhdffOFY//333zMA7O+//3YsmzlzJmvevLnjsytCRcyiRYtYzZo1HZ+lvBridv78808WEBAgmF794MGDDADbtm0bY6xCqISHhws8KM899xzr0qWLrC3iY/fs2ZO9+eabgm3mzZvHEhISHJ8BsJdfftnx+dq1a4zjOPb7778zxhh74YUXWGpqqqCNKVOmOISK2jnfe++9js82m43VqVOHzZ49W/Ychg0bxu6//36n5TExMYIp7e1CZdmyZbJt2WnVqhX76KOPZO3KzMxkANjUqVMdyzZv3swAsMzMTMYYY6NHj2YPPfSQoN3169czi8XCioqK2OLFi1l0dLSsx2vJkiWCe0/MuXPnGAC2ceNGwfI33niDNWvWTPUcGVMWKsnJyay8vNyx7K677mIjRoxgjDFV2xljbO/evQwAO3nypCZbCEIM5agQfsWdd96J8+fP4+eff0b//v2xZs0adOjQQTWJsk2bNo6/69atCwBIS0sTLMvOznbLttWrV+OWW25B/fr1ERUVhTFjxuDy5csoKCjQ3Mbhw4eRlJSEpKQkx7JWrVohNjYWhw8fdixr2LAhoqKiHJ8TEhJ02b9z5068+uqriIyMdPwbP348MjMzUVhY6NiO/71FREQgKirKcZyjR4/ihhtuELTbuXNnzTbw2+Y4DvHx8YrnUFRUhNDQUM3td+rUSfC5oKAAzz//vOP7jIyMxJEjR5zyPLTcKwActu7cuRNff/214Lvs378/bDYbMjIycMsttyA5ORmNGzfG6NGj8d133wm+49tvvx1HjhxRPR+O4wSfGWNOy1yhdevWCAgIcHzm30tqtgNAWFgYADgtJwitkFAh/I7Q0FDccssteOWVV7Bp0yaMGzcO06ZNU9wnKCjI8bf94S5eZrPZHJ8tFgsYY4I2ysrKZNs/deoUBg0ahNTUVCxevBg7d+7ErFmzVPcTI9f5iJfzbZeyXw2bzYYZM2Zgz549jn/79+9Henq6QAwoHUfKVvF3poTec6hVqxauXr2quf2IiAjB5+eeew6LFy/GG2+8gfXr12PPnj1IS0tDaWmprF1y9woAh602mw0PP/yw4Lvcu3cv0tPT0aRJE0RFRWHXrl34/vvvkZCQgFdeeQVt27ZFTk6OpvOoVasWAgICkJWVJVienZ3tEE3uoHQdtNhuT2SvXbu227YQ1RMSKoTf06pVK11eCy3Url0bmZmZjs9WqxUHDhyQ3X7Hjh0oLy/Hu+++i65du6JZs2Y4f/68YJvg4GBYrVbF47Zq1QqnT5/GmTNnHMsOHTqE3NxctGzZ0sWzcaZDhw44evQoUlJSnP5ZLNoeGy1atMD27dsFy3bs2CH4rOWctdK+fXscOnTI5f3Xr1+PcePG4fbbb0daWhri4+MF9VhcpUOHDjh48KDkdxkcHAwACAwMRL9+/fD2229j3759OHnyJFatWqWp/eDgYHTs2BErV64ULF+5ciW6d+/utv1qqNl+4MABJCYmolatWh63hfBPSKgQfsPly5fRt29ffPvtt9i3bx8yMjLwww8/4O2338awYcMMPVbfvn2xfPlyLF++HEeOHMGjjz6q+AbcpEkTlJeX46OPPsKJEycwb948fPrpp4JtGjZsiGvXruHvv//GpUuXJF3l/fr1Q5s2bTBq1Cjs2rUL27Ztw5gxY9C7d2+nUIY7vPLKK5g7dy6mT5+OgwcP4vDhw1i4cCFefvllzW08/PDDOHLkCF544QUcO3YMixYtcoTg7F4HLeeslf79++PgwYO6vCp8UlJSsGTJEofHY+TIkbq8UHK88MIL2Lx5MyZOnIg9e/YgPT0dP//8Mx5//HEAwK+//ooPP/wQe/bswalTpzB37lzYbDY0b95c8zGefvppfPHFF/jqq69w+PBhPPXUUzh9+jQmTJjg2Gby5MkYM2aMYD+7h+fatWu4ePEi9uzZo0vsabF9/fr1uPXWWzW3SRBiSKgQfkNkZCS6dOmC999/H7169UJqaiqmTp2K8ePH4+OPPzb0WPfffz/Gjh3rEAmNGjXCTTfdJLt9u3bt8N577+E///kPUlNT8d1332HmzJmCbbp3744JEyZgxIgRqF27Nt5++22nduxVdWvUqIFevXqhX79+aNy4MRYuXGjo+fXv3x+//vorVq5ciRtuuAFdu3bFe++9h+TkZM1tNGrUCD/++COWLFmCNm3aYPbs2ZgyZQoAOOrYaDlnraSlpaFTp05YtGiRS/u///77qFGjBrp3747bbrsN/fv3R4cOHVy2x06bNm2wdu1apKeno2fPnmjfvj2mTp2KhIQEAEBsbCyWLFmCvn37omXLlvj000/x/fffo3Xr1gAqiuKp5ZqMGDECH3zwAV599VW0a9cO69atw2+//Sa4XpmZmU75Nu3bt0f79u2xc+dOzJ8/H+3bt8egQYM0n5ua7cXFxVi6dCnGjx+vuU2CEMMxPUFjgiAIN3jjjTfw6aefCkJXRvLbb7/h2WefxYEDBzSHqMzO9OnTsWbNGqxZs8bbpuhm1qxZ+Omnn/Dnn3962xTChwn0tgEEQfgvn3zyCW644QbUrFkTGzduxDvvvIPHHnvMY8cbNGgQ0tPTce7cOcHIKF/mjz/+wP/+9z9vm+ESQUFB+Oijj7xtBuHjkEeFIAiP8dRTT2HhwoW4cuUKGjRogNGjR2Py5MkIDKR3JIIgtEFChSAIgiAI0+IfQVyCIAiCIPwSEioEQRAEQZgWEioEQRAEQZgWEioEQRAEQZgWEioEQRAEQZgWEioEQRAEQZgWEioEQRAEQZgWEioEQRAEQZiW/wdHgc21Vpal/wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(rmsd.dat[0])\n",
    "plt.xlabel('Simulation length (frames; 0.1ns)', fontsize=10)\n",
    "plt.ylabel('RMSD (Angstroms)', fontsize=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Visualize the trajectory from your browser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "57a24516e8644b939ce52647f5e6e33e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget(max_frame=1999)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "refmol.read('./cxcl12_filtered/10x23/10x23-GERARD_VERYLONG_CXCL12_confAna-0-1-RND9861_9.filtered.xtc')\n",
    "refmol.align('protein')\n",
    "refmol.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This concludes the conformational analysis tutorial"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}