heudiconv_data2bids.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Example of conversion to BIDS from MRI\n",
    "## (EEG approach mentioned for self study)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "## Conversion of MRI data with heudiconv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Adapted in part from https://neuroimaging-core-docs.readthedocs.io/en/latest/pages/heudiconv.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Getting data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This is a dataset from https://osf.io/5q8fb which we know to be a zip file\n",
    "```bash\n",
    "cd\n",
    "cd fair_data\n",
    "wget -O heudiconv_data.zip https://osf.io/5q8fb/download\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Let's unzip it into a new directory `heudiconv_data` "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "```bash\n",
    "unzip heudiconv_data.zip -d heudiconv_data\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Running heudiconv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "*Heudiconv*, is a tool following a trial-and-error approach (i.e. a *heuristic*) to convert MRI data from Dicom format to Nifti format while organizing all files along the BIDS specifications."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "*Note*: HeuDiConv stands for Heuristic Dicom Conversion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The trial and error approach consists in trying to match (i.e. translate) the file names generated by the scanner to the corresponding modality names. In our case, the aim is to:\n",
    "- identify T1 weighted data (type `anat`, modality `T1w`)\n",
    "- identify resting state data (without motion correction) before TMS (type `func`, modality `task-rest`, `run-01`)\n",
    "- identify resting state data (without motion correction) after TMS (type `func`, modality `task-rest`, `run-02`)\n",
    "- convert all mentioned data to BIDS format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The procedure is done in two steps:\n",
    "1. Run heudiconv without conversion (`-c none`) from Dicom to Nifti, to assess how to match file names with their corresponding modalities\n",
    "2. Run heudiconv with conversion (`-c dcm2niix`) to implement the matching found in step 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Step without conversion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Go in the right directory, and activate our conda neuroimaging environment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "```bash\n",
    "cd\n",
    "cd heudiconv_data\n",
    "conda activate ni38\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Run heudiconv without conversion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "```bash\n",
    "heudiconv -d Dicom/{subject}/*/*.dcm -o bids/ -f convertall -s 219 -c none\n",
    "```\n",
    "With:\n",
    "* `-d <glob expression>`: the path to the data, with `{subject}` replaced by the argument of the `-s` option\n",
    "* `-o <output_dir>`: the path to the output directory\n",
    "* `-f <heuristic_type>`: the type of heuristic to use (which will create the associated template script)\n",
    "* `-s <subject_id>:` the subject id(s) (typically only one subject is indicated for the first step without conversion)\n",
    "* `-c <convertor>`: the name of the convertor to use (typically `dcm2niix` but in this case we do not want any conversion)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "This creates a hidden directory (starting with .) `.heudiconv` in the output directory `bids` (use `ls -a` or `tree -a` to also display hidden files and directories):\n",
    "\n",
    "```bash\n",
    "$ cd bids\n",
    "$ tree -a\n",
    ".\n",
    "└── .heudiconv\n",
    "    └── 219\n",
    "        └── info\n",
    "            ├── 219.auto.txt\n",
    "            ├── 219.edit.txt\n",
    "            ├── dicominfo.tsv\n",
    "            ├── filegroup.json\n",
    "            └── heuristic.py\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We are specifically interested in the two files:\n",
    "* `dicominfo.tsv` containing all the information `heudiconv` found about our files\n",
    "* `heuristic.py` which contains a skeleton of the code which will help converting our files with their associated modalities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "First let's copy the `heuristic.py` template in a safe location, not at risk of being overwritten by `heudiconv` (the files in `.heudiconv` can be overwritten every time we run `heudiconv`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "```bash\n",
    "mkdir code\n",
    "cp .heudiconv/219/info/heuristic.py code\n",
    "```\n",
    "*Note*: the directory `code` is ignore by BIDS validation tools"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Now, let's have a look at the dicom information in `dicominfo.tsv` and in the template `heuristic.py` that we will edit. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "ds = pd.read_csv('heudiconv_data/bids/.heudiconv/219/info/dicominfo.tsv', sep='\\t', header=0)\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The main aim is to create in the `heuristic.py`'s `infotodict` function a dictionary `info` to associate to each modality the corresponding series id (i.e. the proper dicom directory)\n",
    "\n",
    "```python\n",
    "info[my_modality_key] = [\"series_id_X\", \"series_id_Y\", ...]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The modality key has to indicate what should be the proper bids path for that modality, and is created with the helper function `create_key`:\n",
    "```python\n",
    "anat_t1w = create_key('sub-{subject}/anat/sub-{subject}_T1w')\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "*Note*: if your data have sessions, use instead\n",
    "```python\n",
    "anat_t1w = create_key('sub-{subject}/{session}/anat/sub-{subject}_{session}_T1w')\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "So to add the T1 mprage sequence to our BIDS structure, that we identifed as having the series id `13-T1_mprage_1mm`, we would simply need to define `info` as:\n",
    "```python\n",
    "info[anat_t1w] = ['13-T1_mprage_1mm']\n",
    "```\n",
    "*Note*: the list has only one element because we run only one T1 sequence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "In practice the series id can change from subject to subject, (e.g. sequence interrupted an re-run which will generate a different sequence integer), so instead of indicating ourselves the `series_id` in this list, we let the function `infotodict` iterate over all the series `s` (i.e. over the rows of `dicominfo.tsv`) and we use robust criteria to pick the series we would like to keep for bids conversion, for example:\n",
    "```python\n",
    "    if ('mprage' in s.protocol_name) and (s.dim3 == 176):\n",
    "        info[anat_t1w].append(s.series_id)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "#### Step with conversion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Let's see now an example of converting the files matching the `T1w` modality, and the files matching the resting state fMRI pre-TMS. After that, as an exercise, you will add to the `heuristic.py` file the code to also convert the resting state fMRI post-TMS. \n",
    "\n",
    "The steps are to:\n",
    "* create all your custom keys with `create_key`\n",
    "* add these newly key objects to initialize the `info` dictionary\n",
    "* edit the loop on all series so that for a given modality with `mod_key`, the series of interest are appended to the list `info[mod_key]`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Before practicing yourself, let's check the current script converting T1 and resting state fMRI pre-TMS works:\n",
    "* this time we use the `dcm2niix` converter with `-c dcm2niix`\n",
    "* we want the output formatted with the bids structure, so with use the `-b` flag\n",
    "* we do not want to be overwhelmed with all the DICOM metadata so we output the minimum amount with `--minmeta`\n",
    "* in case we do subsequent trials, to avoid writing errors we forced overwriting existing files with `--overwrite`\n",
    "```bash\n",
    "heudiconv -d Dicom/{subject}/*/*.dcm -o bids/ -f bids/code/heuristic_v1.py \\\n",
    "            -s 219 -c dcm2niix -b --minmeta --overwrite\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "**Exercise**: modify the script to also convert resting state fmri post TMS as `run-02` of the rest task. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Repeat for each session, or write a for loop if all sessions have same DICOM structure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "In this example no need for anything else as it was a toy dataset with a single session"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# (Optional) Conversion of EEG data with data2bids"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Documentation: http://www.fieldtriptoolbox.org/reference/data2bids/\n",
    "\n",
    "Use cases of data2bids: http://www.fieldtriptoolbox.org/example/bids/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The `data2bids` function is a Matlab function available from github [here](https://github.com/fieldtrip/fieldtrip/blob/master/data2bids.m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Let's look at the example `http://www.fieldtriptoolbox.org/workshop/madrid2019/bids_sedation/`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Getting data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "```bash\n",
    "wget https://www.repository.cam.ac.uk/handle/1810/252736\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "```bash\n",
    "unzip heudiconv_data.zip -d heudiconv_data\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Applying bids2data function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The equivalent of the `heudiconv` mapping function is a config structure in matlab, `cfg ` in the example. Make sure to look in details how it is defined, then run the example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Validation and exploration of BIDS dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Now time to validate the BIDS structure. This is important to make sure everything it where it should be. You could go to the online BIDS validator [here](https://bids-standard.github.io/bids-validator/) (the validation happens client-side so no data is transmitted to the website) or use a locally installed JavaScript version of it, with:\n",
    "```bash \n",
    "bids-validator <path to bids directory>\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "**Exercise**: validate the bids data you obtained after finishing the last exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Exploring a BIDS dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The python package `pybids` offers convenient functions to parse a BIDS dataset. At the heart of this package is a `BIDSLayout` object which offers a representation of the the whole dataset, and can be queried in many different ways. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/shared/envs/ni38/lib/python3.8/site-packages/bids/layout/models.py:148: FutureWarning: The 'extension' entity currently excludes the leading dot ('.'). As of version 0.14.0, it will include the leading dot. To suppress this warning and include the leading dot, use `bids.config.set_option('extension_initial_dot', True)`.\n",
      "  warnings.warn(\"The 'extension' entity currently excludes the leading dot ('.'). \"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "BIDS Layout: .../fair_data/heudiconv_data/bids | Subjects: 1 | Sessions: 0 | Runs: 1"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from bids import BIDSLayout\n",
    "import os\n",
    "\n",
    "data_dir = os.path.join('heudiconv_data', 'bids')\n",
    "bids_layout = BIDSLayout(data_dir)\n",
    "bids_layout"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "The simplest (and least specific output) is to get everything with the `.get()` method without arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<BIDSFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/CHANGES'>,\n",
       " <BIDSJSONFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/dataset_description.json'>,\n",
       " <BIDSJSONFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/participants.json'>,\n",
       " <BIDSDataFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/participants.tsv'>,\n",
       " <BIDSFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/README'>,\n",
       " <BIDSJSONFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/anat/sub-219_T1w.json'>,\n",
       " <BIDSImageFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/anat/sub-219_T1w.nii.gz'>,\n",
       " <BIDSJSONFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/func/sub-219_task-rest_run-01_bold.json'>,\n",
       " <BIDSImageFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/func/sub-219_task-rest_run-01_bold.nii.gz'>,\n",
       " <BIDSDataFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/func/sub-219_task-rest_run-01_events.tsv'>,\n",
       " <BIDSJSONFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/sub-219_scans.json'>,\n",
       " <BIDSDataFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/sub-219_scans.tsv'>,\n",
       " <BIDSJSONFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/task-rest_bold.json'>]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bids_layout.get()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can restrict the output, for example by only looking at the top 5 entries, and only displaying the filenames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/brainhacker/fair_data/heudiconv_data/bids/CHANGES',\n",
       " '/home/brainhacker/fair_data/heudiconv_data/bids/dataset_description.json',\n",
       " '/home/brainhacker/fair_data/heudiconv_data/bids/participants.json']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bids_layout.get(return_type='filename')[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Another useful return type is `subject` to get a list of all the subjects in our study (although in our toy dataset it is just one), or the locations of their data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['219']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bids_layout.get(return_type='id', target='subject')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/brainhacker/fair_data/heudiconv_data/bids/sub-219']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bids_layout.get(return_type='dir', target='subject')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "*Note*: in this case we need to indicate what we would like the `id` of. This is done with the parameter `target` which can be `\"subject\"`, `\"run\"`, `\"session\"`, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Typically, you will want to only get files from a specific subject, or/and a specific modality. This is easily accomplished with `pybids` with the following statement: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/anat/sub-219_T1w.nii.gz']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bids_layout.get(subject='219', suffix='T1w', return_type='filename', extension='nii.gz')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "**Exercise** Use `pybids` to get the list of `run` `id`s for the images of type `bold` (i.e. fmri) for subject `219` (it should be `[1,2]` as we converted two runs of fmri data for that subject)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Even more specific queries could be obtained, according to file attributes and metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "t1_file = bids_layout.get(subject='219', suffix='T1w', extension='nii.gz')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'datatype': 'anat', 'extension': 'nii.gz', 'subject': '219', 'suffix': 'T1w'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1_file.get_entities()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'AcquisitionMatrixPE': 256,\n",
       " 'AcquisitionNumber': 1,\n",
       " 'AcquisitionTime': '11:11:22.442500',\n",
       " 'BaseResolution': 256,\n",
       " 'BodyPartExamined': 'BRAIN',\n",
       " 'ConsistencyInfo': 'N4_VE11A_LATEST_20140830',\n",
       " 'ConversionSoftware': 'dcm2niix',\n",
       " 'ConversionSoftwareVersion': 'v1.0.20181125  (JP2:OpenJPEG) GCC9.3.0',\n",
       " 'DeviceSerialNumber': '45424',\n",
       " 'DwellTime': 1.03e-05,\n",
       " 'EchoTime': 0.00233,\n",
       " 'FlipAngle': 12,\n",
       " 'ImageOrientationPatientDICOM': [-0.0408288,\n",
       "  0.999138,\n",
       "  -0.00749368,\n",
       "  -0.0543137,\n",
       "  -0.00970819,\n",
       "  -0.998477],\n",
       " 'ImageType': ['ORIGINAL', 'PRIMARY', 'M', 'ND', 'NORM'],\n",
       " 'ImagingFrequency': 123.239,\n",
       " 'InPlanePhaseEncodingDirectionDICOM': 'ROW',\n",
       " 'InstitutionAddress': 'North_Warren_Ave_1609_Tucson_Denver_US_85719',\n",
       " 'InstitutionName': 'University_of_Arizona',\n",
       " 'InstitutionalDepartmentName': 'Department',\n",
       " 'InversionTime': 1.1,\n",
       " 'MRAcquisitionType': '3D',\n",
       " 'MagneticFieldStrength': 3,\n",
       " 'Manufacturer': 'Siemens',\n",
       " 'ManufacturersModelName': 'Skyra',\n",
       " 'Modality': 'MR',\n",
       " 'PartialFourier': 1,\n",
       " 'PatientPosition': 'HFS',\n",
       " 'PercentPhaseFOV': 100,\n",
       " 'PhaseEncodingSteps': 255,\n",
       " 'PhaseResolution': 1,\n",
       " 'PixelBandwidth': 190,\n",
       " 'ProcedureStepDescription': 'Kielar_TMS',\n",
       " 'ProtocolName': 'T1_mprage_1mm',\n",
       " 'PulseSequenceDetails': '%SiemensSeq%_tfl',\n",
       " 'ReceiveCoilActiveElements': 'HEA;HEP',\n",
       " 'ReceiveCoilName': 'Head_32',\n",
       " 'ReconMatrixPE': 256,\n",
       " 'RepetitionTime': 2.1,\n",
       " 'SAR': 0.122121,\n",
       " 'ScanOptions': 'IR',\n",
       " 'ScanningSequence': 'GR_IR',\n",
       " 'SequenceName': '_tfl3d1_16ns',\n",
       " 'SequenceVariant': 'SK_SP_MP',\n",
       " 'SeriesDescription': 'T1_mprage_1mm',\n",
       " 'SeriesNumber': 13,\n",
       " 'ShimSetting': [7566, -13961, 14768, -48, 368, -669, -343, -93],\n",
       " 'SliceThickness': 1,\n",
       " 'SoftwareVersions': 'syngo_MR_E11',\n",
       " 'StationName': 'AWP45424',\n",
       " 'TxRefAmp': 336.357}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1_file.get_metadata()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Finding all of your files acquired on a Siemens scanner (actually all our files in this toy dataset) could be obtained with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<BIDSImageFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/anat/sub-219_T1w.nii.gz'>,\n",
       " <BIDSImageFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/func/sub-219_task-rest_run-01_bold.nii.gz'>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bids_layout.get(Manufacturer='Siemens')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Visualizing a Nifti file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "To visualize Nifti files with python, it is convenient to use the `nibabel` package."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "A Nifti image object is composed notably of the image data, the image header containing information about the image (voxel size, data type, etc.) and how is this image oriented with respect to a reference space (this orientation is provided by the affine transform, cf next preprocessing lesson)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "import nibabel as nib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BIDSImageFile filename='/home/brainhacker/fair_data/heudiconv_data/bids/sub-219/anat/sub-219_T1w.nii.gz'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "t1 = nib.load(t1_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "t1_data = t1.get_fdata()\n",
    "t1_header = t1.header # the .get_header() method is deprecated\n",
    "t1_affine = t1.affine # the .get_affine() method is deprecated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[21.,  4., 17., ...,  0.,  0.,  0.],\n",
       "        [17.,  6., 10., ...,  0.,  0.,  0.],\n",
       "        [18.,  7.,  9., ...,  1.,  1.,  0.],\n",
       "        ...,\n",
       "        [ 2.,  2.,  4., ...,  0.,  0.,  0.],\n",
       "        [ 7., 12.,  8., ...,  0.,  0.,  0.],\n",
       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.]],\n",
       "\n",
       "       [[11., 11., 10., ...,  0.,  1.,  0.],\n",
       "        [ 5., 11., 12., ...,  1.,  1.,  0.],\n",
       "        [ 3.,  8.,  9., ...,  1.,  0.,  0.],\n",
       "        ...,\n",
       "        [10., 12.,  8., ...,  0.,  0.,  0.],\n",
       "        [ 2.,  1.,  3., ...,  0.,  0.,  0.],\n",
       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.]],\n",
       "\n",
       "       [[ 8., 12.,  7., ...,  1.,  2.,  0.],\n",
       "        [10., 10., 15., ...,  0.,  0.,  0.],\n",
       "        [15.,  7.,  6., ...,  1.,  0.,  0.],\n",
       "        ...,\n",
       "        [ 4.,  2.,  7., ...,  0.,  0.,  0.],\n",
       "        [ 7.,  4.,  2., ...,  0.,  0.,  0.],\n",
       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[11.,  7.,  8., ...,  0.,  0.,  0.],\n",
       "        [ 4., 13., 14., ...,  0.,  0.,  0.],\n",
       "        [ 4., 10.,  5., ...,  0.,  0.,  0.],\n",
       "        ...,\n",
       "        [ 7.,  8.,  3., ...,  0.,  0.,  0.],\n",
       "        [ 4.,  1.,  4., ...,  0.,  0.,  0.],\n",
       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.]],\n",
       "\n",
       "       [[ 3.,  5., 14., ...,  0.,  0.,  0.],\n",
       "        [ 5.,  7.,  2., ...,  0.,  0.,  0.],\n",
       "        [ 7.,  3.,  5., ...,  0.,  0.,  0.],\n",
       "        ...,\n",
       "        [ 7.,  3.,  8., ...,  0.,  0.,  0.],\n",
       "        [ 5.,  0.,  4., ...,  0.,  0.,  0.],\n",
       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.]],\n",
       "\n",
       "       [[14.,  6., 16., ...,  0.,  0.,  0.],\n",
       "        [14.,  8.,  7., ...,  1.,  0.,  0.],\n",
       "        [14., 16.,  4., ...,  0.,  1.,  0.],\n",
       "        ...,\n",
       "        [ 3.,  7.,  5., ...,  0.,  0.,  0.],\n",
       "        [ 7.,  4.,  4., ...,  0.,  0.,  0.],\n",
       "        [ 0.,  0.,  0., ...,  0.,  0.,  0.]]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The image data is a numpy array so you can apply all your knowledge of `numpy` to manipulated images ! So for example you can plot a slice of the 3D T1 image with the same `imshow` method of the `matplotlib.pyplot` module you were using to plot matrices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(176, 256, 256)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t1_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "t1_xy_slice_z50 = t1_data[:, :, 70]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(t1_xy_slice_z50);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "t1_xy_slice_z150 = t1_data[:, :, 150]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWcAAAD8CAYAAACrbmW5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOz9aaxtSXbfif0iYg9nvOObX86VySKzmqwiWeYkS6ItSlBL6qYbMGUZaEOyZRD+YLttw7CoBhoNGzBAwEbD/cETG25DhmVbarrdErola6DFlgRIVFWRRVZljVk5vcx8+Yb77nimvXdE+MOKiL3Peefed99U9SrrBXBx791nnz3E3vGPFf/1X2sp7z3P2/P2vD1vz9uz1fQP+gKet+fteXvenrf723Nwft6et+fteXsG23Nwft6et+fteXsG23Nwft6et+fteXsG23Nwft6et+fteXsG23Nwft6et+fteXsG21MDZ6XUn1VKfVsp9bZS6jee1nmet+fteXvePo1NPQ2ds1LKAN8B/jTwIfAl4L/tvf/GEz/Z8/a8PW/P26ewPS3L+eeAt73373jvK+D/BfzqUzrX8/a8PW/P26euZU/puNeBG53/PwR+/rSdC1X6HsOndCnP2/P2vD1vz1Y7Zv+u9/7iWfs8LXBWa7Yt8SdKqV8Hfh2gx4CfV3/qKV3KOZpS8KMSxq7Co4n3qzqP6qw+OM9+D+rH1XM/qD3Mc4n7PuyzPGv/h7nedcc5b9/+INuP0rv/DLV/7H/7/Qft87RojQ+BFzv/vwB83N3Be/9b3vsveu+/mFM+pcs4Z3taL6dSywP0SR/7UZr3y/cb/38QQHX3f9Bnp933Wed53BaP+7DHP2v/hznWun0f9Zq+n+2sCeV5+4G2pwXOXwLeUEq9qpQqgL8E/N2ndK7n7Wm1VctvFZifFLA9zPWsA4/zbjtr+6Pu96D2tIH5SYPpszyR/Ii1p0JreO8bpdT/EPgHgAH+Y+/9W0/jXD+w9qDlcBfMTlvynmfbeT47a7/zLs3PojtWj/sgQDjLul63z4Ouq2uBrruu045/Wl887DmfZntcWuG0+3ycYz4KnfS8PfH2tDhnvPd/D/h7T+v4P7D2IOBd97J2QWUVaM77Yq875sPst2oFn0Y7dO/vPN9ZB9oPutazrNpVyuUsWqX7/7pzn6fPTntep7XTntl5+PZ178zDTNCntfNe/3me1fP2zLRPZ4Tg0+TNHjQQzuJdzwPi69rD3E933+41rOOWTwOG+L2z9l8Fl/MC88O21f48a4I4bRJY/d7qsVb3O8tXsO4c53k+Z61Izjr+Wfuetu08x141MM57DavtObg/tfbULOcfaHsWXpgneQ0PY6mts3jXffesz8/a/2Gu8WH2fRDIPEp/nkVNnEb9rP79oPOetqJ4UDttQnnQuR607UlY3s/bM9E+neD8LLbzcp/nkXY97vceZjCuA/KntTI5L1VzWjsPMJ1G5zxue5RjPA2+9qyV0fP2Q9U+nbTG96OtLokfpp1mMa1ygmctrbsW2+rvx3EOPa4D77RjPWj5f9p9r6McTjvXo/L3p332qBRGd//z7nNeR+d59nmatN552g/6/J+S9txyXtfWWZpn0QinHeNxlpfruNx1lus6J895rMPzOIfO4pFXP1vnGAXQBrw7/ZjpmrXsF48dv3cat33asc7i0dfdy7p2Fu1ynn486zzn3f6o13ne73bbk7bgn1vsT6Q9B+d1bR0YP+zgedCAPe+AeNAAXHX6nZfCOAtgVwHzLGtam/C3Wz5eOq+7/zrWTh5Ozpf27/y/+hxOo1rO89y67axnc9/1nQMI1x3jPPz/k+CNz9POa2CcZ9J7Uud+3k5tny5a47zLzofxcK9uf9glWwSqswb/ea5n3XfWgeFp5zvrnGtVAHr9/6vH7lrFq+eLwN3ddh/VocMk4DuAvOa8q/f7oHs7bZLqXtNp7bSJ+HGX6+f9/rpJ9vtJFZxnRfUo4+B5e6j26QHnB/Gb53nZHzTIT+N4T7uGh2nrjrnEt+oHD4oH3dNpALfWmnJn/3/fsfUysCqN0gplTPvZ0ucq7QMIaCYgXrPveVrX4l/33UdRRpzH8j7N0j7Lt/Cga3oUmuO0czzqMU4zKJ4D7fel/fDRGqdxm6ft+6BjnbX9Qcv67vWcBa5w9iBNYLKytE/76ZX9aMFSaVDcD56r5z7vYF2iBzrnSH+r+7d1Ld4u4CoNWqGUx1u7/nNARWNWK3BiQXvXfcZdG2KFJjmNIjntHk97nudZdq8u8896D0+jYr4fFnD3XA+iJs5LdTzuZPG8PXT74QPn1baOZ1zHmXV/r35/XVMKnD39vOt43tP+jvt3nV5Lx+iAibP3A6sP17HqJAP57LQJIVERa+5jXZ91J4l4bgCFWMDGoJTCWydg2wVoZ1F5IbsbDTpY+tbi8fL92LRCxevU4ZxOjuM1KJXJfBPP050k4nV1HY1KLz+r+1Y48Xud+3rQ5HUWiJ7lIF09xmkOzQfxumeB/WnnOGvfJ+U8fNbap5jL/uED59OcJ4+y7FoH7Kcdex0Pdxrtsfp3GqD2/u+c5oyJrQvIXev1NMtx6Xhu/T7r+gw6ANsBUi8A6W0w0LtWrGsnDV3mqNEQVZaQZ/gix/cLfG5QtezntQYj57ZFhrIOvWhQVYM3BuUcejqHusFXNWqxwJ5M0IOBgLi1+LrBN3W4jzA5OLuWS1ZateB+2vO770un8KwPame9Q6v7PMhxexq3vu48T9Jp96B2Fgf9IJ56db/T/o/ffdAK4zy00w95++ED59Pawy4dz3q4Zw2O1f+71uNpbZ0Fdd62Sifc9/kZK4fV8903sQRaIdAM3nUnAB1oBg3Ko3slajhEDfv4QQ+faeywxA4ymoGhHmjqocIW4LXCG/AZOAMxu7fX8pP+zkE1YBagG/BK/s6mnmzu0Y2nOHYU9+Zkd4/x+4f4qhJqJM8ErF1LAymtWjrEO1kwrE6igTZKXLh3+KZJln1Lv5xCCTwIfLqfnQewT5so19FbZ4Hi9wOkTuuD0yic8x5v9btPgi//FLRPDziva+tm6YexMB6HH1wHiuvOfV5L7axJ4Cz+tQNKXRBOvG88tlYoBJhUlqF6Jarfxw/7+GGPZlzSjHKagaYeKFymmF1Q2BIIoFqPoB47XN9C4dCFxdUGZRwmd2S5RWtH0xjqRYbSHmMcVnvqeYbOPHZmoNKoRoGB7Cijd3fM8OaQ4c0dio+P4OZtseYBhQ0g7Fiy+Jf6ZQ1XH/7uctv389wPmHRPa2c909MolPtWf2552/fTQj5PO+saHodCWbdSfRbu9wfQfvjBeR0wncW5PcqDPq81cBr4n8eqXd1237LXnX3tS5wxrPK0Ks+EL/YepbxYxdYKj5xlYokaAwGY3eaQanfA7GLB5IpmsQW273GFxw4cZJ4LVw9RynPvcIh5t08z9LC74PLuMS9t7HOld8R7k10ap3lxuM+V8oiBrrgx3+Gbh5dZNBmXBse8OtzjXj2k0A0fTbeY1AVaebbLKR8cbTNdFHxyr09xs2Tz7YvsfjVH3z3ET2f42azlv5VG6QioprWC1z2quEoIfbq6r1AitJPiw07U6zTa6eTnsMLPA3A/KNB62ud9Fu7xGWg/XOB8bivzEWbbtVZnx0EWnVCwApQrfOZ5+e/7rLqV43SdWKvHDJ8r3ToZu8t5cd4VrfOuqYUOKMK2KKzIMtTmBmyOsTtDptf6zHY19UgFK9jTjCy9ixPeuHSHrWLKVj7j88Mb/Onh21w1fQ7dnC8vdvh/vPrz3J6N2Spn/MToE744fIfPF3f5w+oCX568xgvFPT5T3OZadsy3ehf5la23mLucnq7ZMSe8aE742A74W/d+nn956xXu3h3z7klOdqTZ/cJtvvDmR5y8UfK1V6+x/xNbXPzqJpvfPER9eAtlHarI8VUtEwyI6gMrfddxmipjWmBWGmWWnYaJz07PqNP/3Wey7l1csnRPiYo87dl6/3AgvdrWWZvPitX5pK7jWbmf71NT/hm42Q214++rIfgwzoN1nz9sWweo6zz6q+foqgbiZ9qcrvQ4SyVwmoXeHdSrA3rFERYBW+Uy7/rgRNO9Er29hd8a02z1mV8omFw2NANFtQHVthMeeNSQD2p6/YrL4xP+/JWv8Upxly095a3FdX7/6GXeOd5ltzehcYY7syFHsx7WauYnJUwyYQOcQjega4WyoKxwyj4Db6AZWcxmTdmrGPcX/MzFD7lcHPG1o2t85e2X2fijkqv//Bj9zkec/PHXufFn4Vd++i1+avQhf//25/jme1cpPi7o3VYM7jhGNxZk+zP08QQ/meIXlUxIzqe+iIoQt1gEYDb3y/dch3M+q0WAdSsc9br3cvV7q+9L+mwFxJ+BsfnU26M48j8F7R/73/6K9/6LZ+3zyJazUupF4P8GXEGG42957/9DpdQO8LeAV4D3gL/ovd8/xwHXWyGn0REPAuXz8FYPGgBnnTP+v26grZN1rTveuutZ+j+auOGXMeBbp5cyatlS9E6s4dEQNRriRgPcRsnsco+mr6iHisWWYrHracYOPfeYFyZc2zlktzdh2hT8+ctf46PFNh/Ot7g9G/O3PvhZJouCk4MBTDLUQqEbxUcW8GAWCl2BdjDsUrSeAM4CxnjwGlwOroBskuH2DA099hX8g+EFfOFRlaI4kRs+fmXAsHgJrxTFXc3X9q7yU6MP+ZWL36LQlu9uXODo4oDJYcbBj/UpDvrkx9tkc4+pPPnUkR81qMah5w16MkcdT+DwCG8tSilRgWSB4mkavG+fwaqTMDoRl6zrdc6xdU6t9D6fYVGftZx/VBXJs94exoH4I9Ye2XJWSl0Frnrvf18pNQa+Avw3gL8C3PPe/6ZS6jeAbe/9XzvrWGst5/NfyNkWZ3efdd/t7nfatkdtZ710p/HQaZtedtqBALFrAzpUnqHLEjXow6CPG/Ww4x62Z6g2MhYbmsWWotqCZuBpxpZ8e8HrV+4wyhd8fLLJz1y4wXY+5ZPFBm/du8qV4REfHm9xOOmzmBSoeznZVJGfKHRNAlndhMu0oJxshwDE8RYCK4CSH5eBLQWc8SQAN5WoOlzefldbyKai3HAZzHcV88uO4vqE8WBOL2uY1TlVIyfc7M+5fThicVSKQ9Ep8kNNeU+hGshmnuJY1B/lvQW6dqjaoqoGqhoOT/DTqShArEv9660V4A7PBFjWXrNClZzqMziD7jpLorZu+6eh/aisDE5pT9Vy9t7fBG6Gv4+VUt8ErgO/Cvxy2O1vAL8LnAnOj9XOmnnP4vLid8/a9qDBcRa18kgOJFoudEVNoYyGPJffUV3R7+M3htTbA+YXCqaXDLMLSpQTY1jsOPSFOUp5tjambPVnvDa+y5/Y/A53mjG3hxsMTMWN+TZ/cOcF7ry/za2jy2QzAeKBAzMDU3l8AFgQcFaetM2b8DdhnwjU0eK3nf2CnC5uUx4BzxpsOGbcr+lDtSEcuVnA6F2N/2DMyXDMnZdq8lHFcLDg8viYn999j0+2N7g52wSgZ2o+Ptnk1r0NvFfYhUFNDNnE0Ls9RNcC2PlEALt/a4Q+mqGqGuoGmgaUwleVcNkRoGOwTFKIxOcDvjlD3bFKS535Ljzsu3NOoPt+gf15rudHGJjP256IQ1Ap9Qrw08DvAZcDcOO9v6mUuvQkznFmW2dxnGfbedtpfHc896qzbvWaIi+9zqGUBmyw1iJN0VFeKKNRwwFc2sVu9qlHOfU4WMY7imoTqk2H26jZunDCybe2aS7UvPbybf7M5W9yrxnyXxt/k0+aTT6utvnSyav83u2X2Tsc4j4akB9qTAWbU7GCfff2Mmj6Ch/eFGUFTFUdsDreBi19oRwo6+W3Q6LSuyt2AzZX6bsRzM0sWM+1WM668tieohqDLcTyVk6oksG7ObaXMSkGvJ1v8V3zIm6jYWNnwvXNQy4NTvjCxofsXRwCUOoGrTwfzLb5l++/gm0Mbpah5hq90BSHY/KjMfnEi5U9cWRTR35UYY7mqNkCGis89skEGhV01h5lNN57Yih9ctTGZ50epA7BmmvC89cpQtZRJOcxKB6WwnsYcD/Pfs+B94m0xwZnpdQI+H8D/xPv/ZE656yvlPp14NcBegwe5oTnm5UfViv5ICv4LCXGOi56Lc1yv7JD1AJmWWML6I0RXNpl9tImxy/keCNWZL3hqTc8Pvd4Y8k2KsajGS8Mp7wwPODf2v0Kvc8JJ1pjOLBDvjO5zL/30a9y95MNzEFGNtHoCooItAFEvSbwyJ58KlZlftwIsHpQzqMah5nVqEbuJf5Ga1wvwxUZumpQC4tyDtfPl/cpxAnnMo0rDS5TuFzTDDTVUOEaxMrW4AqFrjyD23J+b2SicIVMILoSC98rhc88xY0CPS+46bf5KH8Fl4Ptgy28cN2lx40sowsTXr5yh0w55laGwCCrGGQ1jdfcON7ixnsX0PMMrzKKwyHlvqK85+kdWHp3FmR3juHgGD+fC3ftfVCI0IavEyiQ6HC0NgTKdCbeGDizKoNcdfY+KPHUab6Z1c8f9rPT9juLinkOzk+kPZZaQymVA/858A+89/9B2PZt4JeD1XwV+F3v/WfPOs4DOeeHAdpVGdF5HXLnoTAedLzu0nVp+3orCkiRbgAqy9AXL9Bc3+H4lQGzXU21AbMrDn1hgTso8IOGa1f3+YWL71F7w3uTXbaKKS/0DhiZBYe2z93FiN/7+GUmt4bouRbFRAPFoaI49BQnArxm7tC1QzdeOFjrxHk2raCqUXUDgX+Ny3yMkevVGopcwrTLDJ8b2dY4dNVAY5f7y0iuDa8Uqm7k2CDHsg7fK3BbQ2w/xxUaW8pPPVA0PQWaJWolWfgByBfb8oGuZZstxMp3edjHeLyGbKoojqAay2feAMpTbXr8uKEYVvTKmsxYro6P6ZmavfmQw1mP6bxgMSlgZuh9kjG86RnfaOh/bw//yR2wFpVlEJUygQ5ZBeilVVEMDFrVZK9T6HTfw25bLWjwMBbyo4LpaXK9J71q/ZS2p63WUMD/BfhmBObQ/i7wl4HfDL//zqOeY+WEZ/PHsa1TWDyIk163fd3xznI+LlEbq5K3QGmshEsD6MEAtTnGD/vYccnkSo/j6xknL3qazQZKx5Wr+/ypq9/hqwcv0DM1rw73uJCf8NFii+Oq5PZkxFv2CtN5yXyvjznR9O5qdvY9Zi6csW48xZElmzSYeSPOsMbhM71sAQNqUYP3+DyDgbwial7hM5OAB6XwmcbnBpcbfKbluIGTxYQczY1FWQcxHYb3wulaAW/fBH53UWCcR2emBfLc4IsMO8iwucaVmnpoqEZKLOdg0aMgPyY5Jr0JKwIPDZHnVngt3Hlvz2HmolyxPQHsbKJwWUEzzDnpycrkXm8TVQpo6szR69VsXDpikNfMX8nYPx5w75MBl750iY13N9CLBhonE9R0LhNQ0+AbUYJghRbxHSs7SvliZr4k59Om856srqwekM51ne/jtLHzqKB5GiA/B+En1h6H1vhjwH8H+JpS6qth27+LgPLfVkr9VeAD4Nce6wrhB/vA1714p3nVYZlbTp8vg7LKMlS/j+qV2Gu7zK4OmW8bqg3F/ALMrzbsXD/g4nBCYSxvjG7zc8Pv0dM1+/WAo6bHl/de4ub+BouDHuYwozhUlIewc8uRTyx6UWNqh5416GmNshY1r8SiBQEFY/CDHmRaOGWl8FqjiiyBrysMKIWeF+FzFVQYDrTGqwC4jUPN5DyAgI9zrfXtwo/3+EXVgne0Kp2FOoB7THzkHcp7dJZRFAV+0KPZGWIulzSlTs5FbxTZ1GMqkjMRCI5HyfPROFCBTPch34fvKETyifDk7lhC05WDbKZp+jlNXwJyJlsFs42CZmPKlbFEQe7tDnm/vsbk2iCpS4pjR29viJk16EZUITQOZS16tpDJKfaF91DVMklZ6QMfA4mWXiGXJv2UZHBVa736Lj4tx+Lz9n1pz24QyuO28yonTluCrXPOrO4Xt591/BDs4Js6pd3UW5vYly9z/OqQw9c0ix2PHUo+inxYc3H7mF978ff58fImB3bAvzz5DH947zq3DsfM9voUdzLG78Jgz6Jrj5k5spMKPa3RJ1OhCeYL/HyOny9QvRJ9cRc37gv9EO7R5QZfxAHeueQmUBwRhJVCzRtUpDpmc/x0BmXZ6Z+gMikFxHEOn4I9dJKnAcGaDGAULG3VK1HbW7jNIapqUEcT/GyGKgpxwtWNBNQ0jcgHtzdxm0Oa7T7z3YL5psblYi0r20r9dCPPzRkVgDzQGUpA3WXyv7YkHXZUh4w/sNhSMdvV2L5sKw594v8XO57qYkM2qrmwfcyizjg8GsCdkt4dTXnPo5vWotcNZHNHPnVEx2k2aciOF+iDE/xkJs+sqsIz8alvvbWoLL8/hWoA8iVa5Lx0A6xPQ/vD3H5IJpjz0BrPJjg/isf5rH3PA9SnOgLXWCfdc6S/O/t1lBgSOCKDy/zEG8xe2uTkWsbkuqIZesaf22OrPyfXlq1yxv/gyu/yT05+gg9mO3z97lX23ttm85uG3r4jnziKo4bsaIE+lmWzP5kupe5Ug54MaqPxmcH3SpqtHs0oR1cOM28wkwo1q/D9QvRrGgFtWKI3ALH6rBOJWXDq+SLHjXs044Kmb7ClxmUBEBVJqYEHnwXuN1PJ0jW1D6oPTza3mFmD14p6nOMzhWo8xWFF9t4tfF23zyEu8yNo1RW+biRvyOYG9tIW80s9FhuGeqCwpdAWuhGaQ1uPrkNgjIauWsRUHm1BOS/XMlDkU089UMwuKua7nmbLokc1bm5ktbKvKQ/EgbrYVswveJoLNeOdCePegoNJn15RU1vDfFZQzzNYGIo9g64leCebBA32iahEspnDLCz53hR9NMWfTPCzuawkVic5kICY05JinbnCO4POe5Qx9rw9VPvhAmf9K0/2QZ+HTz6tnWY5n+e7SxI4I1braMj0p17g5FrO5JpicdHhxg0buxP+jVe+zqvlHSya784u83t3XuHD71xi8JGhf8szvN3Quz3H7B3DbC4HzjLhMAGKXADTiIMOwGuNHZe40qCsx0wr1MJKUbKgPPFKgVG43AhIKRUoinC7WuFD3gldyYTT9A3NyFANNS4PYBuddF6CSUztw/dbQFYB9ID2mLXw4AJIAaCNxhUal8k+ZhEmk6M5ajoXy3I6bZM0xcAPY1B5LtvyDF8WuEGJLw2LnZJqbASog3MQJdedVCoqpCwN+u0YaJPPPIsNCT+P9za9pKlHYmFLcIscr+m3qU/xIvtzBcwvOfxWTTGo0Noz6i+oG4MKHV01GfN5jp1n5Ldzin1FfiKA3b9nyU4s2bTBTGvUyQx/625abWAtrqrRRY5vmmBVP8AgOc2pvQ6Yz/K9dI/1DGDID1t7qg7BH4p2lj75Qd/rtocAaxW4XJxH72zhL+9w8tIG+5/NmF7xcG3G1d1DrgyP2MznfOfkEv/01uvcPhxR3R4w/MBw9V3L4PZMckUcTVsHWlAC+Mygai1L/TwTlYTRKZl9tIL1wgowB8efzwTExYmnhSsGAWoVADmAFgiXrGonluRmTj00ND3J2dzecPvblnKM+H/US/sMlFvdrgL3G8C6cdjS4HIlS37rBaR7GdBD9XPUxgA1G6NmC/xk2gaGYPHaBMfiAjVfYKYykZm7Of1hDzsqqUeZyPb6CluoNHkQuesgJYytKcM+Pbm38sgzuO2oJqIewbWrhRgsE/OI4IUqKe9o7EmBzQucg71yhLLizXQZ+NKhhzVbuycsNjIWVcbMKtwsIzvIyI8yisOS/p6jPBhS7ozQ8xo1q1AnUzg8Cgoa15b7guW81Ge8r+ei/B6Wu37enkh7dsD5Sc++57V01517rUbZr5RGOk0BokWBMRzQvLDL8csDjl/WnLxec+XFe7yxdYervSOcV3x1/wXefvcy5cc5/U8UFz+xDD4+wdw9Rk1m+LoWMUKWQZbhe4WoJZSS7UrJ/1rjjcKblpowtQXrhfro5bh+LiCsFT5TwTpViSoQNUO4BevlpwGzsNjS0PR0AuYU4QdJLSFfDA62OKZd+5lvFxQkHbORyQCv0E1GPdLYXKEbj6k9uvZBApejXIayHj0o0CcFOs+WHWmuI1cLfePnC/y9CpVn5P0+2bAPZYEdFthhLiuBvg4OQI/LFc6odH1ei8VvI0D3NP274njUVqgZbX3gjzVNr71vnylooDgGPw0rgZm8k9J3wVHZz1jsGA4uZ5hBQ1HWjPoLtPIsLmfMFjmHRyXTOzm9uzn5SUZ+4ikPJQw9u91HTWa4uhZHYUwFe57akmvf3zWW8JNQQD1vD92eHXB+2HYWP9bhfE/Nqbu6f3ef1eXaWu1mh+frqDFUr4QrFzj68R2OXjLMrnjq7Yaf/Yl3+bcu/QG5avij6Uv8Fx98Dvtf7nD9A0tvb0G+P0fvHeHu7YuKosglPHs8wGVaLKUYWqwUPjPi4AvKCpdpfKHJ9mbo/SMB7EEPt9GnGebJCla1RS88KjfYfkbT07iipTSUE14WgEbkV6LY6N67WMMJhL10s7Is5daIqghlVzhe5LveiB/Sloraa+ZbOqgnRC1hFpDNhYfNJhbTOLxSNLt93KUhZmExk0q42aPjlJBIZcgqg4X0Q1XjZnO4c1fO7Tz5cEC5McaPBvhSJrhmXNIMM2xPJi+XKUwN2RwWm4rZVc9iF3q3lXDGjUfXKiVZ6u3LpOa1otrQNKVKgTM+E647W8jnynpMLSsG3gXlFdWwZHahz/5VT3Op5uLlQ17d3qO4btl/dcB3P7qEnxn0xFAcZZR7GaOPe4zen6AbCyE3iGsaKRfmvAB21w/yMEbL6hg7T4zBk2rPQf4Z4pyflFrjQUEi61r3hT3tRYz/d3M6w1K4tR4Nca+/wCe/OGZy3dPs1ox2p/zExVvcno758O4Wbq+k94lh4z3Hxntz8vdu449PxBtvDGp7E59nSWscNb8ohe+XuDLHlwZvNE1fzm3mVtQahxP83j5qdxu7M8L2c+F6vXC9PguTiPXo2uKNxvaMlJka6kRpZAuXLGNlPdnUipU5EEqg6anW4RdoAWApTNursD1wuHIwElgrGyYDK444r8AWKlEqEchd1nLCEQTLezVmWglH3c9oegZTOXGi7Z/g5wuhOKIVmZ6hFtAOPDWNSPZW1RGqV6I3N/CbI+y4pNosqMeG+abm+FWoNxy9O4b8pO2DbOrTvek6ZOSzPnHZNnD02voE2iLX8610b+6kPFctATP1UDO5aphe8dQ7lnzfMHpfAm7mlxxuo6H8sGDjHU957CgOGoq9KeqDT/CLBW42S/ed6ikujYcVPf668XDWmFhtDzJoHrV9CoH608E5P6wHeUlpsQqwa6Ktur9hWVq0KuCPeZqVSpnIVCZWl758kdkbF9n7XMHx65ZLr+6x1Ztxbzbgy3/wOuN3DKMGykPP4FZF/3t7sH8oS/BBH1UWEm3nveiRvYfMCKecZ7iRKC6cEZ2xXljMwpEdCi/tZ3PQGvvmKyx2S+E8K4cJnHHkc8UxJtZeohrCfabERLVCLxxm4fCZEmeU9/gsF2COiYy6fK2StKEp2ZEHGlJOjgTS4Ud5yUQnsUzyPLqUCITMdHOftnkN823DYtNQHBei564cpnK4XFNdGGKGpfDs04XI/kIgTKI/4vO04TmWBarIRemSGaGSFhXu8Aju7aOVoqc1/bJgY2uD3a+NOPjxEYstWGxLTpPynqa3196TN1D1BXCjtC/2mVNijVMFTt/LPbpMwHixIfvpWrYPb1oGtxS2MKI8qaDaAtd3XLm2j7+quHVxh8GNjOJQ+qX34pjBjWPMh7ckt7XtSPGaujMmOhTd6rhZHUvd/7vt+xGA8ikD5vO2Zx+cH+XBrBPie7/MF0fAvW+2P4VT7gJ5pDGMQV+8QP3iLocv9Tl+UTN50fLyj33Cj23e5q17V7lzY5vRDUNvzzO43VDemmL2j/Enk1QSKh5b1Q2+LPC9At8rcYMcV2bi0DMKPbcY6yTHRdWgFg1qUcn3tzZoNvvML/Yk3BlQfR3kYz4AdMcRZjrOO2gpCjzOgA7cq66iMqAFyZR5LoJ5x4l436MIzrFutrqklvC0yZFoi7z6LKQX1QqXRxWET0AHQhXYMsNUnmwqfeIzhSsNPuuhRqU4zmorFn0tOm2cE67adS44aYclX7Mq8kCLhOa8ZAGcLTDvHLE7uUCz1afayplvGbzxlIcWWwqV4RTkU9+qXzqTC4RJyQMuWNNeKA7lPBRSlzE6V5VT6Ri6BtuTH7RnXuWUeUO+vWDmFLZnsH3FfDdjsbnJ4OKA8pMJ+s493N69tDpbW76rOyZW3/mzqJDTxuePKKA+yfbsg/OTbA8j/VmjHe0mrYl5MOZvXObej5dMXvDUlyq2Lx3zxd0PeOvwKh/d2GX4bsbohmNwq6b86BB1eCza3SxDFUVKkINSIoczGt8vhP8cGLxR5JMG1XhJOBTzVoAEeoT8FnZcUu0UVKMYORdUEFYqWSvn20AMjSQLilnkfAuW2Bis4QOdEIJRVAfQo+XbUWREOqMLRtCCb9ch6ILFrXxrPfpIdyiw4TwSECKo7pUSJ5wL+weHIgh448HlQYYXrsnMjUwuGlTjRRIIKVpPaBixrFWI2lNUeKdQWgv1oVRawfg8Qx0qOJqQH56Qf2QYlAV2e4BqHPVmSbWRyerCt1SGdER4BaOzETqqyzBzqeX+8ll4VT1Bgy1/mxnkdzMOq01832J6Fj+wVB6agcb1HLPLmtmlktFOzvBGSV4UuDt3ZWUGpwM0LI+Pp20VP2+ntmcHnM8Nmufkvbq/u+1B53iAw0RpJcC8vcXkJ69y7ydyjt9o2Lp6xKvbe/z4+BYLl/Gd33+Jre9pRjctwxsT9Ns3JIBg0EeNhkJXWAlVpshx4z7NuCQ7mCfHlDeiB1aVZIKjcfId7yEAsiuFd3ZG0/S0WMaBHhC1hOSUiBwv3G+1Rn5YwNgnbhitAmftJRlR0XKlXbBNSfUJx7QCelGiF68laaKjQ7EJk4TugkHgbRsftNbQ9BTaeHQjWegkVwjBeelDgiMtvHlnwjGlTvytWOvdCSYEnYSVhZk78hjcM5XISqpKLOjeCLc5oN4oUJeGZCc1Zu9Y5HwHh5i7kgyqvLBDvj2i2iywfYMfa5ooDexOghF8w3VZI07RyNlHEFZOQDk9M+cpTiCfePgIbK5ZbBum1xwMHL5vYafiwtYJ3iv27o6ZXSqYXhyyuVMw/CPwh0fiHFV+PQ8NLX13VlTsw7TVMXnWPs9bas8OOD8OMK9zXnR/dymJB2k3120PTkDJ3WtQL7/A3hcvsPd5RbNZ89pnbvFvXP0j3iw/4j/44M/w0d97mcsfOMbfO0R/eAeaBjUaobKQuc050epuDKFX0OwMWWwX1EPNuLK4XEse4WmNWsiP75e4fk59YUAzNFQjg8tloJYHNdo6kbr1SBVLQJbQIGCXdMiKFMac8i0HIHBGlARRaxwpFFv2JfAkcMuSXzkATxMcXyakG52JQ9GWinqgE43R1T4DKZzaB0COASzagnWC6s1ABVVHa9HrgBs6WNC2DAEz0SoN1r3N28mEaKWnCUlCt0GloBd9JUfXQ4nYO6jI9yZw7xDu7qPv7lMWOf7KLs24hN0xbA7FKq+tcNwnU/TeAWXT4KuK4XgE25tCVeUG18uodgrqoUnvoctVchCmPonKFgd1STvB+Rboo/LD3Pb09hQuM9SjjGob7l4ouPb6HX7t81/h3dd3+cp7L+F1n+mFF9n6zpTs7Y+xe/fkdV+t4rJurHTH1jpOenX8rKNGzqPkeFTw/5S2Zwecz9PO8zJ0t63yaKvbuoVY73sxWpmcyjOUUqjhgMUXXuXeT5Qcve4YvnLAxdGEP3Hxbd46uc7/4Y/+JON/MuDS9xb03vpQ8k8UOWowaKO6QAbr1ohmVGAHGS4TWdbwkwXKOoq7E9SskvzHg5Lm8hhvlKTQHGrqgViIuhGJly0KsoULliBLyX90RQIfZaNMLoBXITmTo3wuLqEFvAM3rRRuUND0dRtJ1wU855PjK4H8QsKys6nCZTk2V4lyVqGLfUjSFzQvaLz806FHlAW9oFV9IPfijETvyfMkTRrKRd7aJxqBpgN24f6WqBgvIBefu9dSa7EZ9FCXS/KTTYrDkHD/eIr/7vtkzqGKQkLGL29x8K9tAVDuW/JpI87a4wWul6FPFujpPMjnSnrzhrI02F6G7YmT1iwU2dSRzS2qEe4cj4TFF200ps1VWhnZQiYlCUuXn/6eY3hL+vPw/Sv8Jy9fZOulA37yxY/5eHuD6T+7iC0HDK68xvDDK+i3P8SdTMCHEPDYZ+sc4t0xeBqArwLxKod9WnsOymvbDxc4r2vrnHrdz8787hkBJeG4SisB5s0Npj/7Mne+kDN9Y8ErL9zllfE9dvIJ/9l7P8Xh+5uMv2fY+caU4t3beOuktp9SUNcw6OPLHF9kuH5OtVkIp6zF2sxmDdnhAnUyC+qMfpLMKe9pSiNhyEXLqUJraXmlQpIfGdhdrtPmCpcLZ+sbEi/rY4Scl/4Tq7LNiwGgrMP1sxBNt3zuZIkGp19UJKDEmjZ1Qz4wuI0w8FWHFjHBMaaFgxZOmYTgLmqkvcfTOa8i5cswdZxoWbbKVctHr+bQ6IZnA+mete12ajiWUTRDg9clWS9Db/bRV7bFyThdwKLC3D2it9tjcjXn5HqGbrJQYLYvMsRJD1M7cagqha6tFBkoxDegGk//oCbfm4hKJySaAoT6Con7faZxIW+2RDka6rGhGrZh9M4odCarpP5tTzYxzD/Z5Q+vb3Lt1buUf+wuJ1/dpekbqvGIwe7r9N/dx394U3JPh/EgfpWOv2W1wvxpAP0oMrrnwHxqe3bA+VE5p3Wz9XnF8GdZ4kGVoTJJqtO8fo39zwowj7Zm3D4aoZXnY7XJybe32fkObL6zoPhoH3dwiN4Yt5WxjcaNerhBgSsNtjTYniQLyuae/CQA80yUF25YYvs53ihJRIREp0XOFzrLX9/+HYut+sCvEmgAGkLkHckJ54xYoEuAvNoVAcxcpu+zPiNd0lVbJCs6HtN6yY9RBerAeLxvgbYNF/ei/Ah5KRIvrUm5OOI9R+C1hVygsirppLufR/CP/dXlxZMMMN5jo/BNO9kkEHeiXKEnO+fe0/QMTb+HWfTJJjXmeEGxv8BnSibPXKSKeCgnVoA5cP/KOlm9zBr0LFSYaRw6UCI+5EtRSrUJjqJxkGWoToRo1s/J5iW6zhO1E1cVtpDzS8ktyCcZH3OBlz9zm8PX5hxdzJkeGuY7OVv5DkOj0Ycn+MlEQLpu1tdDPC2o63H54ufAvLY9O+D8tGfa0wTy90nm2uWd0go1HmNfvcKdLww4edHx8vU97hwPcV/b5L3NMcrC9jdh+zsz8vfv4CdTkcdlmQRBaI3blAofEn1mAiUhjqjy3gKzP0VVNT7PcFtDFjsir9OVQwG2NNT91vPvlUjNohc/0hDZ3KKsFkWY9zglQKGrEOgQ7lm5Frjikrh1FiqhBSBwz75VQMQuV4S8zj4BWUxspBsvCgnvJbIxJDeqh8Fq9p3j0AJwlNClat2huXCNXfDVTvhzFyYcs/DpuiIwexOSD2WqpVy6TsrI4zof02SgbWeycAKSyokGWRsljtnGsdjKWWwalMvJJz36n0wZvHdEr8iwGwX1IEPXjt77+yKPjEUKGguZEQt5NhfVjvPyrhR5SN6kRRUSwvdxwcK2FtVYqSRjHbpuyBcWMyuSUkTC0YXnr4eyUspmMLjlKA4NH7jLfObHP2b4QsUnkzG3NnZo+hnVeIfRjSH53RP0wTF+vsAeHHRWpdFqXllpetH5SyGADhWiNG3S6XOOyXX//4i3Zwecz9vWPbx1jotuO4vqWGNpxwKdemeL+seu88nP95m8JHKln9r5iMVWxj86+Ql2/llJPvFs/+Ee3N5LVIavasgz7OYQOypwuVQJMXMr1IJSaOvIb5/AvUNUUeA2R9QXByIHy2WCsKXB64xqrNMyH0j19VAePSNV+YgqB4ekowQv1nZwvNm4XFaSMS1llZNdE2hqKxnhdCMBLHEJnqL2OlZzPJ4KfHR+YtG1wxUSeSh8qUrnSCDbfQThY1u2FAmQePUuBaEbcQhKgVifOGvJgtdSNS0H3QJystStALquQ/pS1052qV5ioj4C39uDZpjRe3+fUdVIGta+hHoffHZE/25D/5176I/vkHcUEG5RQV2LhE3JZO+bRibwnS38QHJie+ul8ksplWWy/bLVZseSX/OFFJfNMnnPjPStOZ7Tu3eS3mU36jF9aYPFpuRDaXqictn9iuaDey/g35jw+uW7vPJT9/juCxe4fWmHatxjcLvAzLfIj2uyL88k053zbZ3DlUISKqxqWompQ2U5eCcrpAcB74P+X20/YuD9JAq8GuDLwEfe+7+glNoB/hbwCvAe8Be99/sPedDzPYR1lMa6dpZ8p7uPNqmmn3nhKkc/fYX9NwyTlxs+/7n3+fzWh5Sq4Z/vfQaOcopjz/Z/+W6bc7jIwTncK1ckWdBQsqAp60FlmLnFHFcSQDKvYW8fdrepL46xpUFbh1eiVV0FJJAlawIhA961/RT3zxaeKgv8bS2KDFeAbpTIG6BNB9qhD+RcoiHWjaTzVI3H9bMQ2t32VaRGUqXtCGiO5NCypYR7+8A1p9VIoCy9IaQwJcn4Uuvce5L9Bdmb10JpCG0i+0kyJqFxYoBHTN0p8mHhrZXzZHPpI123KyevQo7nRPO070yiaaK0fKOPKzJU5Sinc1TVMNCayasj7v3cJYqTCww+nkmK1zrkuMikyILPM3y/wPbz1nL3Qv/QODAKnChkmm0BX+V90mjryUJUPscnsH+Ins5Qu1v4nqSKVVUNiwp19x7DD24y6vXwO5vUF4fMdwtm25rhR2Dvjnh3c8T8hZqf/Yl3ufbH3+V3XvoxJl/fZPctxWLLoK99gc3fv4W/eVsmE+UT1RHBOkYdqljVxnlUnkk4/CoFsrpSfRSQ/RECZngylvO/A3wT2Aj//wbwO97731RK/Ub4/6891BEf5iE8SD+52lY9yfF/bUQmVxTonS3u/MlrnLyomF+xbFw75k9f/AZTV/Afff2Pkb014uq3LFv/4oaUXAraZ3oldndMMwqDxYOuHdnUYuZSX04valnWWou/cpFmU5LjZyeVOH028qWIuxRsESgM7wEdAvYi79zRzZqFRw0CdRuApekLEuhK7jVWAkn8asyuxjJIinIhE7VFAGOv2rwaUX6nbGcAKtHf2lK1TjnDUnFWnwUqowPK99EdHR9gy6vLuXXdcVrGxxcqnqSC1dH6VbEffMrP0QIzeHyqgtKmSg2/u+HogU/XU8nDoaxvFTga+jfnqEslTU9z9NqQ7HofvejcUMdpK+oYJ4moGjmOBMPI+yjRjhrfqET5uMLgVQmjEr05FHll3aCmc/lulLiVBUpvgPf4+Rxu71HsH5EP+ww3B1S7faqxoTrQFEc5X2leY++NW/zklZt8OJzx8c5FLv2eouopjr5wieHOCPNdUXXESiyxSK0qCnzdoPu9djIrQz7ZqhJmYxWMf8QA9nHaY4GzUuoF4M8D/2vgfxY2/yrwy+HvvwH8LucB54edUc+iKs6S1512OK1QRY7e3ODkJ69y/LJifrlhfO2YP379Haau4P/5zhcx3xyx+5Zl/PW7uHv7qCJH5T0Y9HEbA5qNUrTCToBZVw5zOBerJlyrzwz0S+xQ+EJVyyB3hUm8bEpOr1quWCxBBdEp2M0Ap0RqZ+auBS0vIOJ6KoBly7uq1a7oLOWFcxULuBno9twdgF1SdEQ6JIZfmzZRf1c50aYK7VAqqv2tGtJ+7f2StNVRT61r1l5/Okc4XgxkSdxy064OouUdNd3RQQuttR4drimwxp3y/miNbhzFYYNZmBQe78pII6n23m2whq2WawjVYFTt7ju+8h6iAgbwRs7jlYIiS5XQ1VySQKHFglVW4fNg0S4qfGNRkxlmUdM7mlH2C9ygoNoqyWYZ7zdXOHi5z6XRCdfeuMMni0tsvA2V1+irfQb1NfT3bogFbTQxWZoKJdfqH7tOM5TO07Wj9+1PcHf3QOlQefyUGofw0OP0R6k9ruX8vwP+F8C4s+2y9/4mgPf+plLq0rovKqV+Hfh1gB4D2XheKmPV6l1tp32WnBUrnmilUWWJ3t6ieuUidz6fMb/SUO7OeH3nLj81usF/evOnWfyLXXa+5xi+e4K/eRvV78kx+z3s5pBmU4A5euh1bdHTCj2ZkcKz8wxX5rhBLkvVYIm5XiapOVlesmt8sp6UB7RPiesjDxyBypaKfOLR1mNj+HYAPJcDOZKrIda1gyXAjZaxruQYzkiARHeiaC3J8JUAhpGnloT+7fV2HXkC3CTAjEmT4mc6OAODAZ4mDEkf6iXHRn2/siSeJ4Y/x/Po2qdjR1CO12wqiQrUtSR3coUcIBaw9QQrNgbiWLF2vZFAIq882LgSkXhsM63JTuR52n6ODVkDY6Sjy4OiQstE4LU8HzvX6IUPOaJjLu1Yw9EvgXYqoqt1CmxRRYbXGuVCMdlKaDY/6Mlq0DmR5XkPB8eoWwuMMQw2RpR7W+STIYf3dvjuawPefOkmF/4r7/Kdw89Q7oFXBluM2Dy5AB/fEn138MmoXsnkZ17k9k/nVJvysPKjnMvlNYZfUxKNuFjgq84DWy1+7DvpTM9qDwL1T2F7ZHBWSv0F4Lb3/itKqV9+2O97738L+C2QlKHnDjCJ2x98glMeaMfj7H2bXe6Fqxx9bpe9Nw2Lz854/dpddnsT5k3O//7bf5L6y9vsftsy/tod2D+UMGyl8OMhzfZQEhR5iSzT0wo1W8gpixx7YYN6o8D2NMrSapqnC8gMrp/jevmSXtnM5b5jXuGUP7mzlPeawL+GCMBcPsjmPqkWJGF+cABGAEN465ZfbY8naS4Dt9sXK9AEtccqPaEDHaKDI1JZHxya3RweAp42FFJNKg/XygLxwTKOjrmwTWghTz4JDrxAXcTtEehjeak4KQAhGEf+SdnhAnDrRtKgRmC2pQn8rljnLdhHwJT7VLUFo+S399hhQbVVoBtPeXuKHeTiJCw1XqtEadm+kVqLhVqiWiJdU/c1Ou/IEH0ISw+KHl07dG3FyjdKkprEfCCDkmp3gO0L6OmFIz8qMfdOUMdTUX+UBb5fMLs+Iptuk+/PJHf4nT346Ca7d6+z8e42R6/0+O6br/DKL9zgzT/zHb7yrVcZvJOjbmr2v3iJrf/8DrFqu9rcYO8Xr9D/Kzf5wuAIgMoZpk3B3Z8fMv3bL3LhS3uoGzdRSuGijno1t/Rp4/ZhnYWfwvY4lvMfA/5NpdSfA3rAhlLq/w7cUkpdDVbzVeD2Y13heZZBp21f9RavaphNeNG+8Aa3Pz/m+FWoLta8fu0uf+byN/gb3/kFFm9v0LuruPCdhvGXPpRjbYxxgx7NRonPw0CM9MXNPdSgh72wQbXdo9rMsKVqM8VZyOaGXmkoP3YywABXaJqhSfkizMIKQGVCSUQQ6iof8KLacFZGvPISVZZNLC5T1IGjNZWXSMBIXURQ7HCqUQFh5kFXXUokorZtboo4MdgiAOS85X51vWyZ+qCj9kZq9/mgpHA5suwOFnXKNOdlAklUSbCWi6MAykqoEl1L8n3lfDhGW9lFeb9ERUjeDR8UMi1Ym7mT/h6Ypf6MOS9ihZZs4UKdQIuZNuhFg88kKX/Un8f+cr2MaktC8GNEptcaU4vFGq1n1kxAUU6owpLBhehMoVM8ZqFDIdh5Om8sS1bt9plezjv9ZrB9Q1Fmkk52/wR1PAGjKfYrmmHG9KUx6tqI3idb6Buf4G7ewty+y+7HF+jvXeKDxUvs/NIn/Pyb3+OtC1c4/PomG+8qjv7sm2x95RYAhz9zmc3/3oe8NNrnX3z0Clo7cmM5mfa4uHnC/r95hHK7XDg8we0fiLXNmlDxbhTh6hg9a9z/CLRHBmfv/V8H/jpAsJz/5977f1sp9b8B/jLwm+H333mkE5wWtbf+Ys63LXiQlRHvuTIG9eqL3Py5DU5e8rjrc37ihVv865fe4v/0rf8q1Xc3GH2oGN9oGH/tdqrf53sldrPH/EIBCnp3KrKDmfB7l3eZvjxmsWESz9sFNq+hyhS2zDGLPvmdSQh7FhBqgnXttUI3DlN7zEIkcenWOl3jMgHVaGVVI01x3HKsXivMXAqQJku2c4yu4xFEWuZCqHhMIpQoiSDJi3kf2n6NYBws/M71dbXZ8Yd4nLgSgARcKEJBVU9+4pN0TiIY24nLmRC9WTtUFY8bThxpAN3K+HTtUYuY21p3FCY+WLk+1DqUc+lauOh82mCmjRQ/QOiKZiBCagmpVxSHDfVGQT0yYfVx//snVEnsi5DXI9yrOAnb/pJn70MEpQrnySXnyv48WfCun1NtZC0lFE7Q9DXKZkCf3HrU4Qnq4Bg17pFNGswigKMGNRyg8lzyWB+fMPiWZ3d0lU82L3Hr6gZ5bqlfWjA/7uGN5vgnL7HYMBx8Fj47POD3br5EmdcUmcUoT2/zhON5ydZwxsELm2y8dpn8mwt8HYofuIb7SmidEaH7UD6o837nUfxbP4DJ4WnonH8T+NtKqb8KfAD82lM4R9seStkRgDl4mvXFXe59fpvDH7ewVdMfVNTO8GG1zezjEVvvw8Z7NYMPjiTnrxFgdqMiaJCVLI/ntSypt0fML/SY7Wap1l43dzG0YGgLmO8WmKPg/W/azHESQBFy+TYeUzlUCEZYpRVS8iADvlG4kHMhqjusCdRDFbLV6dVOaZvItoKFm4UkSF0nVefc69QVMfNbd/8ExrqlGOL+KQ1m3N21lIWZt3y5ClRLdMqpxmPidYWJDeclAs9LRKMrpT6grqXgQHS4uSwCQ+denE/XrcIk4JVEZ5p5A1GDnEsKUbNwIT1psHhdSL7UuXVbqOSAXLq/eL20NJHyCueDLyFa0xE/An+utKLeMJhFjjlx+NzQDPIUSNRdMUQ5prIGXZeYuoF7B5hJJVGq8dkYjQ91FVVjxbg4mTB++5jphU2ObZ/FpYpyWHHyWU3xe5K/enJNUV1fUJoGazWDosYoTxat53kpwVN9TzPMyKGdOIFVvfRSWxcodp72sGqQRzn297k9EXD23v8uosrAe78HPJmaU2c5/brtPNRGPFaUy21tMnv9Avuf1QxeOKRpNPNpwTuzC9w+HjH40LD5bi0VSw6O8Re2JJx3VKQ0nfnEkgdwbTZ6VNsFsx2DDZnEuoDlAyBoH6wkDYuxpt/P0ItGgKVxUpk5LteVQhE4R+uXFBBACGsjaZ+jWsLlKi3pIyCYunUsdp2Iy/0dDht5bt09WadbO1baatRgN8dFS8WwrF3WLVAtKUsiMC/Eck7KCitcqiTcD84y65YsZVU7dCWVT1SR4QsdChRIuHRUxGgXnW5OHLQg3+tYXj7TuEyTHS8EmEuDK8Vhq2tHNqkFGLVGNQ5dWaGkgnUcS255A6ZqrfFU+ssJoEe9tyXkxQjqERWiE1N/e/B4mlJyauip5NqwvVBazHpsHu4laNRtrjCFxvYz9KBEHRrUyRSlFLo0abKxG72gGLJCPSwWqA9vsf2dPq4oOTE5tmx47eXb3PnGC5LnZeTZ2J5S6IYis1h3P9B6kDqL1Zpwb2DJKf/9pjF+SCiSZzdC8DTx+mp70AzbGXTKGHk5L+4yfeMCdz9fsHihom8ss/fHDG7Ky+6bPtf+xYT8g7v4+VzyLyuF2+jRDIXfy6Y1Zn+K7xfMLw+oNjPqQbBOFcmBBgIuLhMLx2UKrWIOYmhGOUUtwCyOQOFDk0IiAHLX4bcUweaR4ItCYUN2ObHavACcD7kWosUar6mhxd0OxRHDnqPyofudlNwoBp50H5cK/HcWecTwQccx2HVk6rpjNQeqBQe6avlr0VHLyiGbyQpFCslKonwyASmUgkxDJ7sc1pPNbHLwxRhtPa1F1rjqjwituTim2pJnnN+byvFDQQRdO6musrBkQDYFPZcJYbFbCB0SKeEa6qHcdMw/vbqCiomibK99xsq2ZcCiI1I3MvE6g0xImcblJkSJtvx9nEwjTWJLJdZzVZBtbcDhMWo6R48GIvvc6lGPS5TzkqK2kqAZP59T/tF77GSvgi84yvpMNifMfnZK8U/6KAs7wymX8mMap6kaQ5k3WK25Oy1xTmG0o3fXU354IDnLw8qzW7BCLOjvE2XwuOf5AVAbzx44n9UJZ8Xir1rPUTYHS8afevEat//4Ze5+0XLx5Tt8dmOf33/3JUwlL3nvrufyP7mJv7ePz4KWtLG4fo4tDWbaYI4X6MkMuzVi9sJQ8igXdCL4whI5FPlUDdATqkAD2DjwxLq0vSwlxTHRQgyFWVEi1YpWaTcaL/G5AaS9AbUgObW6VlTsh2Q5dwJAnJH9s8Btt1I4mURszEYX6ZQI7BEUADIFlfR/tJgjmLuecNERnJbkfb6lM8pD14K+F7DKjy3FvZnwrJDA0peSE1nVFjWvcYMSn+mUD0RXrSrAFQZdgaqlFqLb6KeUnT4T6qP88BDfy1G1JT+U88xf2JCIx+CwQyncdiHZ5uYWMws1Cn3o56INvNG1PP9qJDUDzVwJnx/6QCrASEmrGOASn1sM+EGBWcg7Hq1tM7PU44JmaGhKLdx0qVqnrZJ3X4doyqavUS5Hz0u00RJhOJ2hDo7IP87Irl0QusZ7kQn2S1RZ4D7+hN4fvM/F6XWUHXCbC/zMz7zNNy79GIObno++dI3Br/4hf+6Vb/DVey8wqQusV2wM51wYTLjx91/h+peP8R9JsVnvPNhq2UrujuXu9nVj+VGB8UmB6g9Aj/3sgfPDOv1WqYvYujkAwvLXXLnMnV+6zMFnYXhlwhcv3eBeNQCn6O0pdr9eM/yDGxINVRYy0/d7krhoUKCsI791CIDdGVFt98SRNNQCgAGQJJ9Dax3pBnwtionuaq44cZiFTU4pUTNoSXhkxWHjgtXmutZrpAM8S9yv0BFt4vumDBZ4d3IK+0dqwZtgdTceUwFaLakJgJQPZCkDnqcNtrG+VSh6udaY6N4WtPmlI0VRhZzF8TtOqlDHqh+xD3UlkZNqUYPW4gDbKoOqhaQJjhK77LhCV7blvVP8jJK82eNCVBr9UDEmi5MCkpCoavDDgnozp+nLrBNBLk4s8hwUtq/Ro4xsmlPcnVLsV7i8DBnh5F56h55qqHEFNINQQKDDC3cdo+l9CYqNpZwnEELMPfU4S7m2tfUpG133OHF/gnqlGWj8lQH5UYOZFehBT6q9nExRn+yhlcJvjnGjEjveINs7QV/YxU+mFO/f5YK6SL3R5/e/9zL6zRl8o8/Frzr+z/M/x5U//hG1NRzPSybTEne3xP3hBV78l3vwyR1c06SIwvvGLbRG1HlySD8KGD4sF/2wx32K7dkD54dpq7Kbs/hpYzj+2eucvKRoLi24PppQ6Ibfv/ECw6+XXPi68Mu+qqQic57jtzdoNnrYfibL3L0ZeI8b9rGjArNwVD3T6mwjDvrW2dXyjPGaly1Wr1SyjH0mllfynThQWvJC6JBEX6lgRVmPMqp9R1QE2gAiLiSwV5KZzpatNRtb5MG9kaW1DZTCUhdHpkC1P6EgR7J443FtWFa7XOgdZxAQjvfv4oSwbFmbOtQ5DLy66JAd5b5oxe24Jw6wvqEZGWyhg7UqVmYTIvBsoWXlEaPtbKtZ9kEhEANSdAwt9nJdrpBlTTPKqQcih8sWfinwJumTw4pBAD5D2T7Z8YL8KIMxQecs1m+28DSEeoiGoMTpTHIRqFcBOT6b5Ez1SSoJ4ZnF9KSrk2/nt+R5Bt/TuCzHzA1mUaAXPcx0gD4WlZGaL9DOSRX4Xi4SzyLHVxXFR/vsvpWz2C7gxRmz1ypcUbD9bcedxXWqTVlh9Y8UG+9Zxu8ew8e3cdNpqHLeCfxachjHjl2JKjqv+upT3p4dcH6chCj3HWvZQRGLse5/NmN2reHCxWOuDQ955+QC2ddHXP7ynPJ7t/EnE9RoKF/KM5qtPvWG5AooDhZSCWM8wI1km64trijapXnM0eBlWatDaHCb0D5ekPySqhYK5Vsdc8xGp3XU8qpkNTkDOnAb2ipRjEU+NRzX5Z2IvqBzdgWJC0/nDwAQJw2XQz2AfBqfA5IwqMMTL0nhAocr1aRU2idNEiEIphu1lwCj4xw0HQcgEFKMOvLjGj2tZHLsGVypsbEqSFi6+zBxiSUJNjeYSgA6ZtWL+SrSuxCs8m5UpLYeNxDaqunrNkowURAtcMbIyW5/1+OM7KQiP65QPhdte66SgzMDGqWwcfWj2r5SNvSniiDMskImWNexpFa8B5ch5a06z74bTNTNCyIacWhC0QXb1+jaoMc5eT/HHM4kR8d0jpotcDtjfJFLZOF8gT86ZvgtzfCVKxyOCwaXJ7iNBdODMeMPXOC2oTxuGLw/wewf4xYLyR/TvZdVy3j17/M4/3+E2rMDzrGt0yuu45rh9OVONyRUadRoyOHPXWd61bF9/ZBfvPIupW747S9/kdf/2Yz8D9/BG4MaDkTLrBVuayhcsPOYaUN2cx+AZkuqm2R7M5rdvpwiROjhVVuUNaoRaAE7/h1TfLpMJeefS4EUYQlrY5i1J+bIMHVItaBVK7vrWnVhIpCCqKRkRql6SsAkpzvGVocWsf2gMJiHZEAokaS6TiCKWraIu993+TLNklQZwTqP1qKuCMDkU8HWeA/FsUv1E+2wpB7nKe9FF7wSBx9ybsTirU1P4TKNDXysWbiUmMmHCcOWMQWrSp9VGzn1SEva06lLtf10dCh2X6/O81RWuGY7zMn2ZuSzGl31mF0SR5sPNRlNFWsdsvTsErh6OpNxm08l+jFaaR5tGHzIopeKJoRnozJZkUUrPz0nYkVwob9UAbbsUeSG7ChDH03xxyfoe9Bc28F4LzmkrYU7e1z+0ghXjDhmyMa1Y37uL/0h//gP32Tz6zn9Ow6XKQ7eHLPzByGPjDEhm134P1ZUWVVQdSutwP0r4oc12NZhx9PkiJ/SsZ8dcF4bNBJu+j7w7XR893f6nhae2RjM9asc/+QlPvlFxYuf+4Q/c+Wb/NO7r/P2V17ijf9sRva1dwSUwwN0GwPqrZ44fU4qkbnNRP9Zv/my5MuYiXwOJ/kkbG7AhwAO14JN9KSnJWuwcpMu2UE90GRzF5blqrP0Vkmx0K1UEuvkpSRD3Si7yLFmgc4N/ZJKQ4VriSDeVUxEq9iWwkETz1O3fHg3aMPrFYdepCx0CIgIE5bLFa5jKcegCxSYkL5TWU/TU/T2LMW9OT43zC8PQomolk6I/LktZHKyhep8RqsrDvfnMkXTM+32QH1IDUJJSiXgpnClarn6MEmaSq6fzjNIzlXCvYdH3fQzTG7QixpzPKcoDdVmthTVqesYwt5+P05g0UmK8q1DN9IyOvoT6CSuat+JfEpaAXRXb93EWF3HK8RrkhwswmP3yXKDzgzu41voC5u4jb4kAzs8wR0cYr53k+0LrwIZJ/NN/vHtN/nXf/pr3H1zyJfeeo2Nb+b09jyHn9tm89Zd/OGR3FKW45s6VPvujNc4jtclRlpnRZ8XdM/LVz+NgJUn2J4dcF7tqNM6875tHVlO/N87vAVdFFTXttj/sQx1bcovXXyH/+Ljz3HvX1zhlX86x3z1uzAa4p2D8RA/6mOH4jQyM3HUqVmFOjrBXb9EMzCUtyvRvvYyzElFPc7EARh41OjUEiWGOL66wOpiHmNIAOesSgPdBkdP4nYVIv9LL2U81vJyfclC8qR8F0DKdZGsXB+s1/iVCNqxqooGjFjYrlvB2smkEQNf0rZk7XeOZ8TyhvutadtTZLMg9QsAlE885d4cn2nqUSbAHO81UkOqXcbbohMgEyepoH6hA1wq0Ddx5SB8tk+OUK/UsiXs2v1jyL3PZUMEP+lUv3RftifWc3oc4XkpBxqpSqMsacRF6zlFRIaIxKSL135J0qjCBSalRwD0bN4G6MT+TbRR7A/aZ9RdBcRo0aavUybB3Hv00RBu3sV+5iq+l8m2psHtHzD6xm3q4RXmuwq37fidf/DTXPjiLT77xse8Pb5I/v/rS1myl66ibyjc4bGc35hlx2DMsbF2nHc4alh5z1cMtnX0yFlgfZ7tT2OfR2inhOn8gNqDOKf4UJZ+HCniKDx4leUSaHL5IpPrPaZXHRe2j3l7cpE7X73Mxa82lG+HlB/WonolftSnGZdCMzQS6KCPhYcjy6guDMlPGhl0GkmorJGcGlVH+taxproRY0uZ1CJYQFJBdAMyukmDoAWnWPnC69aCW1pyuzh4aS2lKHvr7NeVs3XzZiRLPUj9Ei/d+TumNNWNHHtp0K8uYHw4/8q7K5VIOtfukQRBw5xqq8D2xbqN/HLrKFvO4xyLznapHWeixlwtWY4CeMHij3JBfX8fxn6O/ZsSPulowZ7yHLXC5zq8E1KBO1FSQVkCHet15XlEVY+uZTWRLXwbwBK+lyb+WkC5neBC8E54F+PKKiWkcu3P0tgJfe/DJNz0DfVmDzZG0LR1Dt2gkDJa/T5+/5CNt4/Z+B7ozGF7ntt/eJmPDjd58/on7P18QzVSVLs91GgoKUabWpKLmc4D0V2zfqWtiyA8RZeePntaqowfYHu2wPlxWnemDcnvq+vbHL+oya5P+andj/nazWvsfN0z+s4+/vBISgUpjR/0sINcuMhcoyuLmVaoyUycGpsjiboLiW98bgJIayk9VXcsKlqQSEl1aAdlBALXqUQinwdJmKcTShwHcivnisBsy3iyzk84dxfk4z7xWElB4pe/3wXKLsAvqTtWrLJVpUE30KQ9lm/PHc6v61b+FvsGpcRi7ofEQSsW7bJ1tPzo48Tgctq0nCH83GsVADt8ZtpCqOl6I0CZmHSIBOzdSdLrNqXoKsDGz3FIBZTGLb0Tyrc+ANmw0k8x4CaArG7k7xT0EyclBHRNRVp5xIyAEl3pMPPgEF3xfXSz862mXY0AbXsatyG+FD2vULXFFQa7s4HaHIN3mI/usv2dOfqjHu5ixeBjxeTGmOOq5Kc/+x6zy4rFdobbGomDPdKM3WcW0o4+cmTgabTHp6g9W+D8KMR/97uxtHstNdqOXutz8pmGn37hQ/7E5ndw3x6x9dYx3N6Tr+c5atCTytiFgQCAunHo4xl+NoNeyfz6mPykkZd0mEtl7NzgMo1ZWCk/VbUBFN6oRAd0lQl0BlhMENTm9RWVgtS0a62fVGVEtfvbmD8jbmcZ+PGkKswpmQ8rVrFaP1CjdRiX1HI/tPcSuzxY0V0OvatCiMdKgBWuK3K3UfEQr7keif54ic4J/ZWqpugItoHDDRnn4vGaUoKB5CeuMORvW8rnsSp3dMAm4A7Z/7qBJN3JtTvZxXzbKf+y8+12FxxeOh6j/V7ktNetqGKqVl159KIFVR0KDCyFuTufJvPIxetaNPPZpJEsesERulpZfenvzmqnTWylxHrWUohWVxaXayavjGgubaKGQ/x8TvHdj3npH1X0hhU+g/E7hve/cZXPjO4y/UzFfFszvzyAS7vo4aBTCDacL/69TqnhvdAeicrTraXd3fa4YPwkwfwpTAzPDucMnJt8P8esefCnf4zbv2C58soeJ3XJv/d7v8pn/tEc/fEdUAo1HkFmqK/tiDWsFWZmyY7mcgn7h3Bpl+rKmHpowHlOrhdJiqVrT3loyU5qssMFupaQ33pksNnywE78Y3Q6mhCvEgDXFgpTK7JpoEg6eYoFFeQ4dV9hex31RYe26FqBXSWAy1RIZtSxcsN77jLuG7i2R4hsDI8iqCu8CeNYCfglLrTjCFyKWIyPsqPvFi5c4QiTz8yniaL73KNVKsDa2g9JkaI6Co8wCUHk+Vtwt4UkgpKbDfdXtgEbKnDoacLsBvp4tUwrhY+MjQmq2kRMLpMCBWZSS0rPzCRgTJa2RXjjSPR2LPbkDAzvSJzo65HG1LKjNzGaMHwv0DpREeK1yA3jfcU0s6nvw+/VNBgit4wAGbl4jRoNJJKwX2J7UtV7/80RO7VDf9xg9w/I/+k+w5d/lsMf8/RuKza/rfnt/hfp78yoNguml3OUHdM/muAOjzBFga8qKRzbNOupjXW+J2+X943b4v7d7Q+jnHiSUYeferXGfaqLU8A6zbatM1BludAZRQEvX+fwVc31125zbXTI1z+5yuW/X5D/wTeEOytLKHLc5lCylw2NBF9UUrvNfLIPwwHVlTHVRo6uPUcvF2LtAnjRJtdDTT4xlPsN2aShd2eOsiWzC9kSWImOWaySxC8j3GdMB7rQhnqgW6DoDCJvFE0/LsvpWFAk7FbxO4rlnDLRqm0vfQlYfed4UTkAbURiDH7pZtiLeSriftECX9qHAGo5gROlzducKWzhJcl8JzmTVzEpf5jA4viL2egI157ej/CrY2F283hEJ2U34xy1OPq6gSBLVb4jkLq2n7qWr25ow6uR/XUtyftTNjul0CdzslGegkYkiZNKio2u5t3mYLJ2MtALyCYNLsuxJegAnC5r827YQlYJ+aydIEClSSPeb0o+FSe2FZ5dpffRh2sJ6VMHPTg6Rt07pFdk2HJEPTBMXxoy9B5tLVQ1l373Jtn8CkcvK+aXPOYw4wuf+4g7f/aQ9770Al4VoK/S+5dB++w8KI3KC5HYdWV0cUwrWJLcwfI+XcXGqiBgVcl1HkPvGeWpnx1a40HLgqVwz9Ysi9yV1CrzqEGfez+zzfSNip+5cINpU1C9P2LjexPcdCqFWPMM3y+pt3sSzRX0rrpx6HmDn8+pX75I05Pk9z5U8UjRXcHycgbqoWZ2KWd+qaQZ5WRTSzFxS7KluHSOfHCyfrRYOC4sxZsyLK3D8rrpKeqRohormr5KYNN15qV6fB2n1WrTdQuOiXOOUrlKwMAsOv83bYRjOuaKdS4XEH51wBhI955yfihSFfCUGKpQNANZDdR9RTVU1AO1JI+Lx+qWeIrURpd+kGcRaI1IJ3WA29Q+qSEiwKW+iDK2FVCO16m7tBIQaw4maZ8P2+LraxS+yPBFhl7YxB+rTn8my7lzjZF3lyriSiqf+GWNdeLWg8MzvgPQruZUxwpf5cSj3E5HKsa3QUbt55Afhex+/cA97x9T3qvJJzIJNJslbG8C4O7ssfX1A8oDj+153MDx5Q9e4lcufYv89WNOXlDMdzL8q9elxFXIBOitFQdh15l/WhrRs4y2rkpr1Ype993V9jgh4U+5PTvgHNt9Sxp//3ZID9M7L0EZxqCHffzlHY5fVLz+8i1e7N3jo8NNNt5WZLcOBJizDF8W2FFJtZHhcp2AWS2spFXs9ai2xGLOJpbkMAuWh1h+CgI4NqWiGmkW23kosire9mR9eZZBswNqUZVgSwnxtQU0vQBkBSkUelUqB52B3uW1Cf+Hz6IDLvHdne9Dx3Lqbg9/t4EWLYAkAKNzTXQsVt8eMxVjdZ19AnC2DqhA1fREY93tp8h9J2ddtmYyUm0FlOjIi06/yE8nDnvFWkwgbdvrjdZ9m+lNTPVuuHWrDe9YoR5JNdrPaUYFzbhs+fYAqr7zrLrvQgL62K2Nx5vlcl+xAnv6TghKStrxyrW+j+AcTIBtowa88/zi8+08wxjRqGsrVN+wD3mOny/I700pDyzaepqewW0OJL/5fIH6+A6D2478UIOF7K0hN+Y7vLJ7j9kLDXVfMXlljBr0QWtZ4SaH4P3OwmVLugvEqxiwyp19utpjgbNSaksp9dtKqW8ppb6plPpFpdSOUuofKaW+G35vP8KBT/+s84DSQzUGlWdwcZeT1zdZ7Dp+6cI7HDYDDj7aYPfrc9ydPdR4LOV9+gXNuAjqDKn1piqHnlf4oxPcxS2pnTdryE4qqV9X0zq9Mklkk3SoXpaZ803NYicH7xN/3KUxoDMgOrcoKoMIxAGwimBFRaCM3HLH+SYHJFl9upL9ktUYkgyZeRugkGRW0ZJuOuC7xiBQLqgCOvutUi9J6hdXmPGaOudKIN2ZZCLgpkx43SrdWQxvXwbspdXBSj92HZER2F0ec2DIhwm0Yl9E5UpnQuoCcAT8tGLqnEOehUqZ5Gwvo9qUuoL1Zo4dZO3+UeK3ZpKOibLkmUlGvXqc0/R0+k5X82wqyUWSnH4hElJ+bFJs6EWo/r5wgcf2iZJZ96yjs9HlBjssceMevi+yILV3QO/uHDOTlLbVVilqJ8BPZ4zeO2Hze57iQLP1Xcc/fPvH2Spm7LxwgO3B5IqBjZEYSCDZHjugmsZyNyCl/fAcFrC7f79nlK44b3tczvk/BP6/3vv/plKqAAbAvwv8jvf+N5VSvwH8BvDXHnikrte2S+yvi8VfXf44D5mivrzB3puG4sVjPlls8A+/9jl2f9+Q39rDVRV6e0us5r6U/DGhKrDLNWZWS0HMsuD4tTFm4ZhfKpPl2d+zTC8azDxEYfUV1abCzEIgQC2D3RYwu5hRHrhQ605T94VrTGkzO5ZkBLEUCRYdWBFwQ1i4ZKhbPoauQdUkyZVXUv8zfpYtwiQxF0tINS4t071qyVuhHXQodtomSrJloAv6AVT08rUlTrYDkqmQLK1Fmc069wlJZRAtX9k3qC7iKsFDcdJdRcl2m7fHlwohcgMSbh6ANbwukTqKk5pDUZw4encWzC+VVEONDdVhYkh017pMVIRtgX4x1om2EnCVorb1qFiR1yncSEn0J4RoxXCvNu2SLHZvFPmJ5K32uWa+Y9I9u0ylvhc9s1+e6BRt6a0wHqJ0z8dFU9aZ7DurgnSceK5cMbtUkM2lOG3mPaZu8AdH6IMJWWlY9AsW2xnFCxdRR8dgLfqdj9lpHNXGNns/Ce6jPncujXh5c5+vvbLL1rdg+sYuw7qBm7dEohqCUryNJHmc3SMW6BBV2NWprqysu5z1Ol56NaLwQe0Z4qAfp/r2BvAngL8C4L2vgEop9avAL4fd/gZSIeXB4LxO77hK/sftkq6t5a0A/+Zr3P7ZAeZnD/ibP/0f87+68RcYv1Vw4Q+P8Tdvo7e38aMBzc4Q15PvxJzHxUGF3pdIpuqNa9hCUY0yGqHcyGaQTxyDO5bFhkmAXQ9FqlYPlehOFx6zECCb75hUMTrmbV7iaFULcMmpZyWkOakpcuFmobOkbkDHd0fJOfOpD0EJTtQjJxW4kFPCOZm8XNd8D/2quyaph8yAl7y+PjehAoih6RkB7kKnYrXRYeeM8Oa2R6oQHuvZRQCrQy6paJVap5aX2SFKUNfLS//E04d7Tbk56mVrPeWaiNZtx9m5qsVebGhs0Qv96TGVSn1NEy3cCFxt0v+ojLElLLTGVEIrCE/vU7mqqO32SpLs+5CCNfoWfLQ/wn3pkHZC2bYieLUlldhT7cj4rnRWXVEB5JWstOJ50yMO/Sr9phJnD9AGTMVjtJa00EQSNYgDVefoQQ8OjlCNlax9IeXq0WeGbJ1cw797Az+boe8esvtWn8MvKooPCt5+5wpXXrjH537hHT7+5mvMdjN622P0yQQ/m0PTsFSZ+z5wlUjfUxMjdWV1D6I2nhHAfZj2OJbza8Ad4P+qlPo88BXg3wEue+9vAoQK3Jce6qirqo2utdwl/yHVA9SbY+5+bsTR52r++JUP+btHX+Cr/+p1rn+nwdw5xFmLKnJcmWH7WUraE5f62d4JOI/bGkvRVmiDPAjSMTTFsaOYOJoAUPmJpxmqZFWJo0pyE8v3Qj4ECwSLsOuoSoOu03TjcailJXRaZnc5U+vJT6A8tuTHlmwiWdxU46AJobFRa5tn4TgrL39IsiPHDAM1ALaqLaq26CnkjZN9QwCOK+RnsZ1TD1SKGGz6KlXQTo5HAgB1AFLRgqBYjiJFS+qKuIrIO8AYaYZcSfh8tIppgTopLlQ7wa06MnUjk+kSd6w719vInOWMT1QTjmVVSQaNFspFN1KEpRv67lWkOkja6hQ+T+cdsEESqDpO3uDPiA7CaAhIJjp5XjYnHR/oKHjabeJHaceRrLZaMEa3FEvKvufCRJkclOHLLgDnbE52UlMaAe/5pmb28haDRY3fP8Qfn1C+t8foa9eZX/Rkexm38i1+6Sff5Y9+5hW239IsLg/oL3bh/Y/Aefyq13I1t8YqHtyn3HrG+ebHsMQfh3POgJ8B/o/e+58GJgiFca6mlPp1pdSXlVJfrpG8vWtvIi1POg+hA9LKaPyVixy/pLj+0h4/v/ku3zi+yvhdTf+jCf5kIvxWZsSLHuvjBcVFNrWSeHzUp74wSIU6u44YSWgu4AMdzq8Wqyl6+yPgND3V8sjxfF0rEFh6J307cFLkICw5cpb4UCs8cu/AUu7X5IcL9EmFWjRgVyRI8cXW7d9+1QqJ9ELkJLstdrtzqKpBTyuywznZpMYsnFAn85D2s+METTRI14kW7kEHJ5yO2dm0rBBcsWwtL/Hc8XacT05B3YQafZ0w8q5ErTsZrnNwrmaFawFcQqezeeDs6w4NE0E/8MBNqagHmqanktqm6UXFjUzs0anZ5avlXkjHbcOraR2MATRjAqq4Ekv3x/r7k8lItbx7KEQbHaN+BZjj76UIz/iuRUelMfj5nOx4gQ5VzL2BxaahuSDOPt8I/bH79QpbhFXHfs5X9l5i97V9mp5ivm2odwZLyo3kHFxt59ESP+sW8WNc3+OA84fAh9773wv//zYC1reUUlcBwu/b677svf8t7/0XvfdfzCnXP4gub3SackNrZi+PWVyyvLF1h88Ut7k53WBwy2LuHuIXkjzfB8vZZe0ST1ko7s1AKZqdIfPdPKknkjIjgGxMR2kLsU5iwplsHkCpYwHHQJH43abfRqylprqA5RMHnGRgcXCEkO70NefRFeRTT37SYE4q1LxBWSuWstEtXRGCC1SX4vAhis2JhS262LCtsWkbGqnRVxrcsJSqzb1CJjgjlUWUg2ziKI5DTofu0jtNbiwP+AjM0SkZJrYY9RhVK8majBxpJ0Wmz9rUm9GqBFLU5VKLvG5HypbPfEoFen9ypfBaNUIXFSeSKElXci2uo0eO1n09EGu8CbLAph+BueWKE/9Ne44Y1Zky6zUuRPq5JZ11tNpNmChMHaMDfYosNFVQaHQ+k5O0IexRhtjVySc5YdCSp9WZ8yE1gayaVFFI5O1kLtRUWNU0PUW1XeJHIQpwsWDw7dsoK5ODmSk++M5l3ti+Qz2Gxaai2ipQGyPIcwHoJa6583dspyk1HiYq77z7RqfiMxAK/si0hvf+E6XUDaXUZ73330Yqbn8j/Pxl4DfD779z7oOetZTpLg+0WXIUHHwmx5c1H5xs8//RP8N7717ix799iLu3D1qjhgPsRp96nFOPTIowKw5r1Ed3cNcvMr9YsNgMBV6zqPeVpW3TE61xue9Fi5uLoyefOJSVEe21x3as3m7qTWBJDdFahgJoTaixhxPQjZxnsigDv6sWwn8XJ4782EpFaYcAgNdSSNOIVAnbmps+N5KoKTepH1UdwLzL5+VZy00HykPPG1yR4UuDahzeQ7M1YHqloH+nJj+qBKyLPtOh5EP2HS49JebvAFFKNRosRAiqifhZobDQptjs0DtpWyoz1VJHkY+OuuIU1Uh7nhjSnQrn2vb4ug4crQorHS3PR0EoNCv8uS1bgEuTawR2oUpbUHbtfaqq4zCNVmz8Owb9VJZsohNPHN+XxLd3gmC6ATLxuqGl61oaQ+7HxbSvneuORkgKWFHSf8VRTX53KhN2ZvCjAZxMQCm0dUkqWo8kj0Z+MiKfzHB37uInMy592XP384pm5CjvGipnqN+cwlsDegea+toO5u49sbZdO65TtrrTNMunSWtX27pIw/O0eP6HbU/Bkfi4ao3/EfA3g1LjHeC/i7yWf1sp9VeBD4BfO/fRTo0EDDcePLPKSB4MXRj07g6zy57RhQnOK/75jde49o8N+s4BTmtZbvVKAZiOxWLmjuLmEexsMnl5xGJs0gCTUlEhLWMFGeL8q8dK0k1qaHoacEFLCjomci86oLP6rIIVmCLqMkUT1BlpMshi6G078LI5ZBPfUggzsa7ki0CMgityGXDOLU900Vq2nUnPeSlH1MhxvFJSmshobNDo6tpBBa6fYXsx16WEVBdHNoQQa3Rt6d+tmF7qtQUDovwrfCcpIAKAuQK8a2V2EmjSWrjQLsnTEj5SAIFCsqa1wBPvn4Fz7aRoFh7TDRGHdI1y3+GZa1ArgzJOkF35WXHicXNPNQrgqUDVcf/2PuP9RxUNevlaY794I9cIUG/m1C4XizgmMVpYpIyWph6bNOl0ry3m3FZpBmr3iaCtvA+SvfYe42ot3p8OiZTyk4bscCbAHPftCw2hpnPyuzk4qMcZ9ShjclUDPTaqHfSiwu3vs/2lT1hsXuX4NU3T87z1yVX+W29+hb95+IuUBxmm6jF+eyDGU1RuWItnWWIn/dR5l1fbOiNu3d/nOVb8/BkJTHkscPbefxX44pqP/tTjHHdthytFCun0DpxG9XOOf+Ya1YWGX7p6A4D3P97l+oczKdJa5FKgtczQjWvr000s5d4cVdXUV7dCzTg5nVSV8NiClLIxhh+7PCYcCpUtCtWGGAeLaVU/2mZVYwmwY3h0Gz5LClvuBkiYEPUVHUYSGaexvVDpY5BJkdgqlGWa1YJDUTdq3fJK33uhO4ws33xugqID0YDnotCwucwMWWGSZeVy0YXbQgv4bBj0VkY2deSTJjnL6Iwt3URnabjfuIyOyoywUklBIIFTx4PS4nSNiodYQNfFlU2kUQjPKBy/yzv7TNEETlfb9hmlAgDRiqRjhcZrD9ZnSwW0eZSLY3lHbI+k7Ejn7DzbrhbbxXTP8V2AxCtH30TbRz5o0aXgr5k16Eref1fIkkA5n1KTStCKXr4WAg2T6Y4KpgXw1E8r990MM3w2QC8CrdE4mVzGY/x8AVWNri3ZTGEWGfUAFhuK6fU+o5Mt1PExfjJl852KelRy/OM1/r0Rd14eMbpywmR/k/6ewr1yBfWNd1pgdr4d46ept7r/r/79oO+cxyJ+HJB9wtbzs5NbY7Wtdn7XegbQCtXvc/RyxuDCIReKE37/3ov03u6RHe7JA8/6iX91mQYl1kF+XKMnC3yeUW8UIUUlKWoN4jK5XT7GhPoug0gK63qZR1bOI9lpOpceeMMUKRgHa+QZu2DiaWsP0oK0aF3bpThepQFsKoVuTOAbHdk8a4G6ceiqEQso9mEID/ZaJwpDwDAsgbUWC7sM0XW1Qy8sTZG3Urp+SL2ZA0phBnppmR6lfsmRF6zOrqMrqCFbMOs+7iA7bBUfUjPRd5byq/rqpSAa34Kq14CR98XqVvvbBcdYuYXVPDxhyd/9Pzk1AWpBX1e0Fx/VKDhaxY3qfNb1a3e2LyXKUh7tQ/8S0tjWIeAkGrPxHpSS+oq5JMwXH4MPlJlkOfSx6ELW6ppTbvBIh8TTa5m4vDEYLUseHa+xX8J8gapqSXOgVfC9KFyhWIwNwzKX4JTZnN5HRwyu7HL8pkw0t2YbXBqf8O7mGLxifqFHX2sxFrrtLGt4tT2Iuvh+OhGfMVrjybfVmW7lhqOuWWUZfjxkdtnz0tYRR02Pdz++wLVvWtRkJku5PMfHWP5Mfpu5xUxrqBvc5kDKxne1siFE2CyChUa7VI3a2QhK0KlA0aFMutrcLvB2ucYUyNHh/mJy+sQlRq4xgld34vegnDjQ2glEYyojDqOFJ5tbzMygZzWqato+VQqMEt4ZpI+tE52zRlYZtcNrI4UHaostyuSwi45RdOvw1I1J95/uJQaq+LYP45JbBXVWDABBd/ouWrW2Y812uNuoDU7gFye5blsZJ14h1V3CQ4kKjy5vLNVqO/0beNjVtJvxeMpJoI/14gD0OjyiOImYzvVHEMQvW9SKFAXYcvCyn1cqpYZVTmHmfgmslPO4QuolRqtbnkGgOhbRmehFDqiQ0PBOMYLIR8s9tSDtVLDaG4evwYfIWnWoxGm8qNGZJp9YzGbHCdrPyft93P4B6u4Bg9ubmP0cNHxwuMWV8TF+0OBNTj02DAZ9qGt8I3lyvFujWT6NznhYMFylN55xpcezB85n6pwtkoEuQ29tsri+SbVteWF4wLcPLpN/UDJ6/wR/cCjZ6YpcyrvnIVBFQzZtBJTKgmq71wnDjecngU4cJDpaPNHaMsG60KpNkK87CXdWn3kE5AjKHQmVeNkDePl2MPtwvYljjWCd+qNznghwSqXEN+LBz8inBdnUURxUktIyJNSJumUcovSAFEUoA1mJ9TWvA9XRJhvqanpdiNKrB90gDOQYnXuInDpKHKBJRxt46K7TMCobYni0mXuUaqteZ1MvgReq/U5Sc4QoRB8S7uuadmILE3CTCx0lQUOyvSlVCjFfcpRZH5xwpGjCyPuCHD+b+QSw6TkHPjzmio6UjDcKbAv2LlP4vJ2wupK4VFw2/G97suJpVRVtyPsSlRGsYhtTiHqfglLSe6qXJwTdeNCyOjQdqZxXCl1ZfA52VJIXBYka855ivyLbav011U5BfrOQ8ecdvY+Oufylbe69qTl8Zxvzuifv10yulgxuOfyVXVTT4I9O2kKwq5nmlsbSGiv6PEC7zkG4uu1BfPT3uT1b4Hwesl5pvPdQ5Mwu5GxdP+RXtr/B//K9P8/4Buj9E/x8gb5yCV/muF6G68nMbeaObH8qAScjiTIp9xvqftGJkvIiAypIIb/R8aLi6j8u4UOQwrqqGEsBI64zmAPvGaP7uqWIVr+Hbw+beM/4fxzM4Uchx4y8pg+0gwSJKPTVPsVxj+LQUhxUZPcm4MUp6E0mgR25QS0s5CH15EJ0zYtrGzRlm+dBWwEkW0AKfAj9YubBMgs8sletpSsSxnay6QY/xKod3fwTPvRRkpuF9yIVGojPgo5l3ulD6bfO69ORjvkQ2ehM+wwiXdJOEn4pA2B6lqp1YjY9lVKOto44loNi4jV1JwndOa6LVAKJ4mj6YBYqFVxQTrXRpqot8Cp8c1tVO05Ypupo1uMv3ZbuSkUPMpXC9mMQkHKKbv1BnEPNHG6U40d91NEEdXSC6hfUG0XKnijPK6O/OZQqQnWFunfI+HsZkyubFPua42slu5sTbr3aZ/NdmL0wYnj3EA6PpM5gE2bX1RwbZ6k3zgOm60B49f9niG+GZw2cTxOdR2cgEJ2B3kgI6WRW8NXJS/DukPEHDWq2wMeQbmNAizPE5lpqAM4W+EF0Eooll08dyrXa5zgYovdfBlAbtbekxuhaS7AE1EkREABN/pGBkXIDd7jT1jm0rFKIgSnJMiNcR5LRkQZ+F/wTEDhZcs63oRpnmIsZ/b2C3sdT4aRD36p5CENuHHpaQd3ghz3mO1kKwIkSLeOkT5iF6LUAEKrpImO0RGkldZ3t2vmlpXRSqIT/Y9i7DU7axAHHFYUDbGvpupVq3PEZLNFMse+a9m+vRbfuTGtNLtVN1LHvFca2srk0oUenMaIgkVBuv5ygKp7f096z8jhFStMaK8sQLfegSBHEBpV+s/Q7rTK6fVfF6u2+dWrbeNyVfNYdsCdY2fgwmRYabwx6sUDVDl/mKK3x83lHNx/e0wJmFxX1Tp/ysI8/bPCzGebeCcXRBtPLinqRYYea4tKUajgi1+A3R+j5HD+Ztk7B81i66yR252mrx3oSoPqsqTWealv3ILQJmkjRIjY9Ra9Xc3O+SXlPURxIlQVVhKCTQS6ebSNLeL1Y4DODGxTU41z0uT1xpKTou/Q7LAFjPblII8TB5gN4xPeoC9BuZd/ubbk2I1riO8Ofif6IfycpVBh4EYjjJXQYju53I02QAMy0x5OUmh5nJIF6ftSQTRvMNPLS0u9eaxj2mL4wohrrdL/x+p0JQREh7Loa65Zz7Tjnunmd471GpYH87/GdjlqK9POdvlcqAdF9ioz4Wbe/PYEu8lI9W3W+s0ppxoklzv868iWdYwZ6ICkuOueJlVGwkRrxS1JI5eUeU7AR7YQSzy/n7UxgHes6ArELk0EaFit93AXnGEafnMcelG2voavL7oamx+voBun4XCOrCIcrDDrPwHnUdIGpBvQOHF5rqk0xaBbbOfneAD1f4KczmM3p37XMLmS4WYbRjtcv3eX9y2PGHyrsqCQ7Hki+jdOqbp9lIT8j0rcn3Z5dcF7TUuCJ0pAZbF9xcTTh3mJAfuwxxwtJplIW+DzDlW0eDbxHz2p8r6TeKKnHBpdJgve47IYIGkqEDY3HagWpzl/77iTLLDq9OgCdXnK1vK9weySOGdqBu6rmWBpAdH6H49ynCOm+ayuWfJTtJYDKFHUOzcCQjzXlcUZ+lJGf1CjrcZnGZzpoWA22FElbl9eMypds5loqIoHFMuB2edSEK6qjy+1sS8Ae+yE6QyNnGy3b2FcRADvPJUnRUr6Kzpzm24k3TgDOKHwp0Z5pUlDL/ZqAKi71o1XdsdQVPgW1uFzR9Nr9lkqVdfukc5xoxaZLDSuG9ty0FFb3eXavkc51df72AKa1vuP3u1TPKjUn73aQWypZUbnC4MscjJbc5/Um+XGDNxneaBbbitm2pj/uoY9KWFT4uqb/yRT9mQ1UJQ/s9fEdvn3pFUYfgx3kmDKXsd21ap+BKL0fZPvhAOekdZaRqftSlLUewUujfd7au0J55NEnU1xVo8YjGfyNA61xRtKDqsmM5uo21VbGYqwlZ3Cu0FkYOA50HZLN2BAsFGSX8SVvtbKhbJDqAEbH8ujqehPHXIkDainkWAFGRp8H0G0QSmxJ5aCXB/SyVE3gMC1RO5SdikCv2/Gna3GqzS8oFtsGM9cUxznlkcOGfBH1AJqhapf4CDi58I+oQoSsjdYWsGQdelQKkoBAZUTu06tkxUa1QTYTizVWy+4Ce7znVXqnS0V0l/zRIaesF6lC7Ce3/H0CmPrgnF2qftIBZa/bz1yHGtANqOhMDCsCZ1vdenqNowM5bWivOWb0U3SonpXVWorki5fesbxX1UKrzsV1fHzaHr8T/k+GQ6yWopXURawaKAyuV2CGA9y9A1mZGCm3lk881ZZidknRvG/I8ky084sKc/Me2m6AVTTWYHA0F2q8yoLDVOPrOJv69ncXqH8IrN0n2Z4dcF7X+UuqDQ1aoU2OvrDD5GKPZuD57sFFjv/VRV74aAbzkEBJ6wBQDo+stVXl8EUuidD7qpMVzSevdAzDTdriQqVlbEoW71prRlkS/+npDIBVSxZxlMVkSSqUCrKFToAZEybFhDpp0HasqlaSJgfXFW0AQZoc2ommHZAx8pCUkEciAEmD35aKWV8x39GtFlYty9a8U4nWgGBFdnIERz5T7k/6KoqeHW0Ah8t9Ss+ZQLubQyTcp7G+rQRDe60gYJakiPE5KOi8MSlM3MwBFULx+8HJ1nSW8kpSczZ9hdEeKpV00k1JstqVBRsSCKWERPOW5pH80ir1fzb1bS5sRXq/u4UTXE5Y3axcvCIF43S18TFLXpTHda1f6ciVfqJ9j5Zyn4QPdUgrmt43o/DGg1XpeC7XuEGBnizIDmZ4rfGDHuooI791SDO+QD0QDbyZw/y6Z3YppzgYYI4nuMNj2BiTTT35ieJo0uOo6TPYnKH8WArT5lnrBDxN5/yg9jQB/FGP/RjX9OyA8wOlMS6F1/qyoBobqi3HVm/G7BNPdjDH13Xax45LmmEueXKPK/Siwe4Msf1WdRCXtm1lakXkVl1wziw5/1zrVEGJ5eiDQZ9uIzrvOpRG9LKbugWheA2SwWxZpZCqMXescVP5JQsWwmDqUnRrlqfKt1Kw6PG3PUW33BOEwVmR1BSRH3ampWGSc8mF/onAEaRyAD7zaUKhS6eECSZV/E5A3KEYFCk3cXScKhvKkPkWrGyvUwfQ04ZD00r7nFKpwojqBLmo8GyzKoJR29fQ5qYmWPwu68ol5TtmQUqtqbsrlM51A3itW2olgmsn0lG5YLFDmgzSJOOgG16dlBmRc++eM/Zxt62xkFP0qWuPmXbvXFOUEIJcq2ipDaoS61kSY2mhDydTsklDXmqUU/QOwCtDU4rm2cTkRtbSO3BMJ4Z5ZZg0BcNehS0U9dBghwWqLPFVJaqNrmMw3cQKLjxq/ozT2lnHf9RjP8Y1PTvgHNsZs6T3XoJQnJMBoKFnarIpbUBFnuEzk6KOVOPQiwbVOOpRntJ5dlM/JodM5P1M56XvLJPR4X0J2+4LPOksQ5OOl/Y4Ak5t2aFYQTl6z4F2EKZ8COEyO1bukiY4/q8C6IRcH111R+JFVeDNKw8hcRCQ1AYQrDm6Vjch9Sltis+OJeezNkFPvIbogOqqGZacdUHK1vLisjTucqFda1zXPvWzckEk0JkQ0z10LH6MALSKJaDCZJyeS+d00YJMBWPDu9D9P+WmbpavJ+7bqnECR9yRrSUapiOfW51ApZ98eq6t3HD5mhJ1E/6/r88inq1iQqJGwr17JSzhGgpnNce4V6QgLhlX4eXo9+BkijmeU2QKszDoytHvKxabmnqckY/6qNkQ7z3FQYNyEnruUFinyFxIq9rPyIyR9L5Ko7S7PyDlNDXXk2pP+/gP2Z4tcF6nP0xyGZl9MQbfK2n6Gp9Zpk1BPnOSkU0piRzM4qgIVoz1+EzTDE1bnTksP1Ou3U7zmpTKcq2GubtfF6yWPmRp4Hgt/HbXgpTaee1ghNYiU7QSKNUBqHjd98nDCMCaqZQ2EqL+NZ7Dg5OqLXSCOtJk0wk3vo/zXnou7eepiGpHZZD6ns7E4Feu+bQ5uGsIKYXuJIhPE1gnk1z3+tKzitIyhSQ9Cte5pFXuTHDpex0ruu0vUm4ToTJiZZuVLuk6S31nok8TA8tWb2di6jr0uquluDFZu91Ja12/RVCPx4r9FhiTBPjh/NJVLf/hw/V0lRzxWn1QPKnMpHQAvhCrWB3PMMagBlI/szx0zC5oGaNlji5L/GIh9TjnJW5hOKp65MbhwgRvc00+6LclqboThNLrdc/PKgf9hK7t2QHntZE/wT0dtkWZXHVpyOSqIt+ac2cyYnRsUfNK3qWyIEW/RarCKKmK3NfLg0rRWtChJYffEmfL0svaPcZSkEE4pupQH1F14TNoYgIgRZLJLdEm4fyqU3g0Dl6pmCFBEw4FnWCHbmv6gFeUR5LVjJAIvksViL5a4ZVPmdUI19iVAUb+PT/xKRgkWsZeSZ7o1sNISzV0oh39Ck0S+1ytWL+xpJIAW2uJ+wgMnX11E6p8hP2VDdxtZ/x6JY++m4EOZFI0i47TzXet1TZtpjiHSQ7CVR/Ach8tA3O8x+jXaK9JHvjShL86hjsrjliQQNu2f2zeFm5IqhZYki8KH9X+mfpjVZGh2utLFJFWqJAudak/jaIZl5jcSMWdeS191yvx0xm6iAFfhmxqQUneb59LrAFNg57X5McefZhx62TE9Y0jPupdlPJffQNbG6jZXIDfBp3qWe00P9UPGrSf0PmfHXA+zRmogkMvpgnd3uLkhYLJqw3/9Vfe4Q9uXyc/aSRbVshh7I2iGWSSiHwRw7W7o0R+UpSaW/6JYOjjIItOnrj8DseIQSzpmHGwx1sIFjAECz1QFd1r6DoX02CsW45RN5DNJHWkLQ31UDLDdWmQJOEL6hJxMnnySUM2Uxy/UMp1qBYgdOMpj6AaCYfrcpYGeJxEsrl44ZXzS4VGAfSia1q1TtMu324WbdRiTLKfrEhLCPJRLAWZdC3DzrG6TTchaCRrAWapuKylzf3Myn3FSa+z1I/1JLsBHbFqeboOF0F8eVKOASTKRseuphorSbLUUa7E4y+pKJr22GnVooTDLyaSklaFKEEfiu02PS10WNcp2hk+ppJ3Jo6huGpLK71VmiU+1qhOioE00ciAkPRKU21mmHkhaUXvTcIM6FHTOZnRWN9jsV1Sj2B6QZNPegwOS9zNT9DWixZ6YFnUOZmyzHcVxQFUI01xdYvs1l2oO9pWaEH6cTngpZX4UwDxJ3zMZwecuy3cpDKdyrvB8+arOmTnUtycbXBwY4tL0xOJWAJxCCqFy7VYdsGKbkZFohHSsi1YH2YRQNKSCrXG0NyYsU51BlrynBdBJhYtT9VW6JDgCtr9IQzWuEk+jVW7ozUlFUUC8BiFU9Cgk4WWzRzKQzXUSY2wym1nC0l8pCqHqS3jG5J7N1ZnsXkYUF6S9+vaY0tZXsbKJcqCmXnyEx/45pCn2ZOcZMqDalwqktqVuHWj11K+D9vK7eqBSgDqnTgpddVqqeP3Xd4qJxKIhe3QTgDZTCa0pt/h9UsCJSHAFnNtp5D7OAFasHEVEsBWWVHWxD7VDZiFa/l1WtWGy8Q5bAst9SX7YSJXcvxk4YdzJoCOYNhZQSkXyqDNPKZyra5ayTGzOWjraJpQzbszGZlQmVs3Hh1qE0buWzeqjTSNlEukyFaCYLRVVENFloWqKrZ1RuuQOKke5+AH5B8vYLHAewdljld98mmDmefYvpSxGngvuTYWwWucO/pFzWYxx/ZkRSjjSajLtuBrdxW9wuWcR8Gxuhp/2hb1pzp8e12LUohOMhRTedRCsbCZLL9C2SUVwrVRIetWDEBxLfC0tAIpUY68zAJqksQGmkwny9arNsEMLFuq3aCRBGoBsJfCaUM9vPR92u06JNeJ1nqaRKLVVYAtDdnMSeDHVOiExYZeUhtEZ5csx8XacGUm0rbKSWYxozCRv1Zhye4BpWiy9lhLjilFAm2vxCLMZ64tY6QVypowsJf7KNEZqe+WCwks57tQbX8T6YQW3IBWp8wyqDU9Fax8cJmnGUjYt15RsyQqK1qqUbcd7i1O0gk04/cgpdz0YYWkiNcr1rJM5u25uo4/rxW+c+zUH/G1Du+CqUVyqetAt0QfRONSXmblZOKIah9tZYUjEZty8Ghpx0nAWI/BL72T6VkEeWBK0hQm1aZUqFzAOmrzddVOPK4wrX/HOtS8wkwWVP0hvT2f8m2oxorzEKHI9GHG4bCH3VVL41EMIbXeUk4PcY31fJrF+iCwfBYokDPaY4GzUup/Cvz3kXfra0gllAHwt4BXgPeAv+i933+Eg7d/atUWg8zzkFFMcbwooYgyBA065qiVJZnU3/PpZYqtu3SOEXvZQl5uoKUNOhb2ktpghcpIIBoSpJsq6F47zsYuj9w9Xix/pGsZWPVgmbaQ/WISfo2yDj23FIcObzKasrXuE6A6T8rbHJevSrWWf4eNiEChOw7Q7rlX9beSQ1qqsejKoiuL0QpTZdiyBVdFp8867/+SGka152p3aPtczhes7+ixWt0v3EeqpBKLwjYenUK+VbJ+Y86S5JwLcjirWZIKrtIoqR8j6MaB7QGt0qokAXLHMo4XrJt25RBXWVEfHfOstImOfDIOEkDXDpeZNBEnJ2XtyRYurDwgKUY6/Z/S0i7JMX1SsUSQjgVpcS0FlybTIMGL9E4yWFJhB4taNGTTmnyWU4dqMT4zaTzLdSuaKqNxJjnkZaLoWLqnWcbrrOBnGGAfp60OjXM3pdR14H8MfNF7/68hvu6/hFTg/h3v/RvA7/AQFbmXTxDAOD4wrUVmU0gZHzNXnMxKdGklm1oE7yCxy+YCHHToiCgFg/DiOhkIYmnKB9VIUw/b5f9Srt1ocXeBvsMpKivL63wqNdaSPrhT4WNp6RmAOZs64QgRCyxpkLtWTrBkbCmgmx8t6O3VlIeOfOoSTx3vwxYa2zPCFRsJEGiznnWODwlMupWdI+8YZXTRCSb36KRqufNJqlhMWudgt8adPJP2765qIQKvK8LzSYEhXXBqreOuryAdP57TiuXV9IV71o1Yk0AnvadPgBwnJlNJJXOxWIUikcly+Zqjc1kKLqj0DgifG9KJdu4z0mXZPBSKPfZS+3Eq/+czJxZyisaLGvp2qSE+h1aPnEC7+1mwmrvAvBSFGJ9n19gJhWFjOSxde8zcYWbyHsZrMWE1aRYhH4z1bRBWvA7riAFiGAPek310D6GeAs200RfLurGSCbDweKtovMYO3FKmPKxFytHFvojW9CkAHD8/7/bYvl+A/qDrOKM9Lq2RAX2lVI1YzB8Dfx345fD53wB+F/hrD3VU78FbvFftA6oqEabfO6B3ewddZVzcOOHDxXYI/NBpOaRqKy9HYQR8CYOlCvKxGPXXkKyZeqBxBamYatNXLFlvXSsvgkTWgm7kT6MDz+ZS780EALGF1J9LINzXMgACh2wLzWJTHD0pCCaeS7UWrUTMSb/ke1OU66N8hnIar6WvXCYFaZuBJpsaspldVmF0IiJtLCLacdK1z4FWORCALJ86cQbtzyDTUm0laFinFw2+CdRAcJ52Sz0lo7jpRNR5UHVrFd+nkY797lslTZxousAViyPE4qsxd7FyHu9lf6tVm8OZqPoIk2a1rOqAVmYZt8dnki1a+inq5nUd9ms6oB/SdkZrNTqXYyHZODl183xEjbQrhPOPtE4MDFHWQ646BodPz1Y1bdXubmBPWiUEgwTCPYf6kbY0qb9jJe8Yaq5Cde9WTdR2km6cZC6sKtRoKCHeiwp35y66uS4TV09Rb/UovcMfnwiffqzw04LqtQw2GpqeCc8wjN88w9ewNun+eQJPniW64gcRhOK9/0gp9b9FirjOgH/ovf+HSqnL3vubYZ+bSqlL5zrgqic1tlCWyjcNaINSivzmAeXBgEuDYz5SW7jcYIwWbaSXyh2u0NhCEpPreUN2XMNOlpLJmEoAStcsLUlVGPzi7IqWV5suNN1/HLRxYARQcTnohSOba5q+HFuF6ECzkIrfuhLlhR1kSO5e8cBHTtOWK9ahItxbqwZwRagd2ATLJ8ji4nfFESRWc9NXQYonxxCrUBIWYWTCciG3A16u02UCEMpJgVkg9YmZ1KiqxpU9yDKxlg4X9PdyqpFOy900oQWQjtGVugl5kCOQqPb4CaDCd7NwLbaImeMCWARLOT43r3xSuqRjdu5HTiCcaTbzSWkTE9ODgK+pfZDmhWxudsXatz45Y2PwSXHc5kqJEaER1JbKTznCDUagJoFeWs1EkKx8og6U9ZhZgzlZ4IqhVBdTHlwIRXer72lLdbV69PBAou8gTCSi4/YQVwOeZEBIp7TPQ9cuZXA0MysTdByzIWmRLwvqX3hTcm2k+o8KXzfo0Yj8xDN+T1EeOb772QuYwsoqtQiJuPIcqqqtigIshXWvcxI+Y8EjT6o9MjgrpbaBXwVeBQ6A/0Qp9W8/xPd/Hfh1gB6D+2fD1PGRFDUorXCzOTrwbh+fbLbWtQ9LIsANijQ4xNqwZEcN2bykKU3g+lSb4D2npQ+CsygO3lUao8vZpTDYzpLbZeIwK/drTGWohyY53opjAWavwA4ymoFuqZPoMY9OGeR4cXCZzlI1npdMy2TUeJTxok9VLRUDChO0u5EPjkqQbrh4sowXtA437ZcDdDogSqxxWFuhm7xHVQ2Dj2eoyz2ZkAIF0i1am/pTB+VKqLe41L8tjsprsGI8JZWNBe29AAwCun7leqVcE0vAKTXvAjAHJ3Hkbj3B4sSn/emEOcd+tD2SskfoK58ma6F6WsDsBqdEazdyrOl+4+SefgKo5Yi/RTmU1amiT/dYOkwmkXZhxb+SOPs4yYf3SsqPyY1pwCm9NJEsyz7b8Wgqh5nUmJMFNBa/WKB6Jarfx20OqXcHzC7k1AN5ENk8jMGigMxQDxSzy4rpVcPOcIYfzrib93GFKDuGG2PsrdtgDEr5Vq0Vr2Nde5Ys5dPaaRPJGe1xaI1fAd713t+Rc6v/FPgl4JZS6mqwmq8Ct9d92Xv/W8BvAWyonQdesQqcli5Lqhe2mF9QDID+YAGqFAtbW3AOV8htiZNIkoWr6ZTsxFIYRWNVW7Y+OKjkC/JjktOGJedh1CInqiEOPN8CQLI+DhfoKkPXOS6U/jHTBpdrmkFGNTZt1jIVLd1O0ELsEdX5m3ab7YvVbXuZJETPQqTeSlBNtKC9l2g55cAEzbL38Xo9OkrDOhOTcm1WNWU92dyRTxuUtZKoJjnFZPDqWU15YHAmJJ4KsitbyED1mawQ4sBN3DRy3vuS/8TJydNaiAHMk2Zatc+vO9lE/jda3l1Ne+qXrsOX9hnKDoEWoV0FuEyuMUYMSomxYCEH5U8qIdXx5kQlT1eB0wXKSP0kfp1oJEj/qpBzg6gmiTUNQz8kzXbgm23RTu4s3XP7tzwfJ5yx1igX/BOhgjepuLFPdIqZW8ysliCU2UL6qKqhLPGDHs1mn9nFAq+h2lDYPvgJEhCmFViHz6Da8NiBY9FkbPTmEOi6pg9+Ywi3Q+dpqeLjl7zx7fN5LEB+RB74+9keB5w/AH5BKTVAaI0/BXwZmAB/GfjN8PvvPPSR79M0alAaZQxqc4PDV0pm1xo2yrkkPsqvoYoc7yw4H5Z3oYaagywXlUM2bVAO8okOFIASOVqHV1Vh2W+LuOTtgEHtl1903xnwYSBAsNjmFbpq0IsGb7RUkcg19UZBtWFoymUgcqYTqNIJfPBBrtWVP9kCFls5ZmEkc14HmJ1pNbzJUk1Uhlg+yaLN2lB2b326pq4MLPKP2cKTH1vMUQUOXD9fsljcQIPzmJOKrHGtde0cvsjEou9l6HFONdaB24/UQZCY6U5+izDhxftRUXOs5NnEScRrhc1IRUojL63jRBQoja4Trzsp3jcJLi2bIa6so9RLeck2l7jecK26CiAW3glndDpmt2ZfFywj+MXMf23CpGBVdyMPbQDT2qGsERdLSj4V08RKQnyvwGlNLEKQbidScNFatw49k5OrOkPVBlUYkewFWWO6v9phjufok7mkSnAOX9V479FGY0cli52cxaaiOPZUG1BverKewn2g5F2pa5lMMw8G7u0P6V+qU9Sly8COe+giFxoznr/jTzqzPYwFHY/5/bK6H+Ecj8M5/55S6reB30cWl3+AWMIj4G8rpf4qAuC/9ijHT5mpCFazVuAcZKKnVY3i3mzAL1x+jz8Yvihl25smWA+OOuYCdpF2CC+38xT35igPJy8P2kAOSAAYnVWRZ47FQOOgbzW/4WsRsAPIR2DCOdTCorTFjkom13sphDw63lwWLSr5blIYRIswpNyM12KDlVEPFLrR7YCO4chEvWq49gr0AvKJQ9cuDfisDquKYDmiIJsHK9e3QR/ClVuKwwa9sPhcY4d54stBgMuWGrNwFPsVpqmSQ9BrDc4JmNUWZR1mN2P6khZlxMKjKwH/LuBK1F47OSSOP/6AKCcCd6srMJ2afcrFwBAlCpqJRVeOaivj5IqRCbRqaQ4faQGllibK6HTUQb8eqbLEV2eKbObID6sQrtz6OhLIJq45pFOtOkE1yLu5uuKBsILxLeir2mIWlmaUp4lVKA2PCmHmetZgptAMc2ypU5ZEIEQAimTTzBv0vJGoWqPl2FUjNJgxiTKLEkxdNZI432jUQpx7vmlQgz4M+thREXKAK0m4/0KDGjR4I9tVlkGvxBWy8ijvaOxRD3PFER3eyoku3+QZWIvHizZcK3zwJy2DxAqwPgwAngfsz9PW8eBPCOwfS63hvf/3gX9/ZfMCsaIfrSkFSrcVT7xkp1IqCOjrRgbKXHN3f8y3epdp+hrKQopKWhvkcV6+qxXNKEfNBuhpTb1RwDDHa8VirIVyiNFUEdyCBz5K03QVLLG0/FRYhVRNXnJkSt5mM6nlpdYa389Z7JTMLmatFeg6S/Eo8wp6666ELvGgoWJzSmEaZWhh3HWrpkQOtZiJ1z2fOLKTGlcYSfwU+OD8xKbBF4MdjIXioOoAT3CoVg5XaJqBWbL2owXe9CUAo4yAHLhR1Th8LukgXRFNUCgPbCr2KpF3PihWICpEvJb+iFRHrIEXgRKCVe1IAUSixRXOPwKyWVjMpEZPJLzfljvYvkFXYtY2AUCLiaPpyA1j4EaXb9WN5CuxhVjFuvGYiQzywzcGIbLPkU1sm3iqp+/Tl0utwxY0JVS8HdAp94gKE0LlwHtZrXhPNpPsbt3EVdmkQYfJT1lPfmDJMp2u3SvwuZHArCAvdb0MbwqhHeIr7H1YfbbUk7IemxcwLtHzBhUsZpzDL6qg+pH9N25YdO2Z7xj8iaG8pzC1lXS+ucTS276n2bKYcU1pGpqxozk0ZDPJsZFVNd46AVDvWmBeJxqI207jdLufPy4Ncp5AlydohT97EYI+oE/8DeEhKcCA0UEy5Rn0K3bKKZ9c0Qxv9MgPjvFNI3XOakc9zIW+6GnMJMfcO0G5oTjE8mXeM2Z0iyAX68/FxDPRwopZ7dJyMlnmMqCKYydqkX6OHRTUGxmLDUNMV5kiojpcaQxQiaHEcQntfaD+nG+/S/h++K7rLF1148mnkX7xiVOvN8SKklVAdGBJpZgUrJAi91prT1UueehdVA1UjkjhuFwn3bOuFdmJaMtVHfTlRl5oM6lQNksDvlhYisOqfeE9NMOMZmSCakX6U5yGtOoNBUv5IDq67GwuwKkCgJp5g57VqNqK9R6s4t7dOdkkoxmIJFGsd2jK8D5Yec1sqTAnrmO9kvjk4qhBNw69sOi5vG/VeEA292RTi5lbfKZQtcPMkMjMTAUnn5ZQ9abVCsdnE48vTr5AnYTze6OpNzNiIiggRWeKX0HUDUKLCZccnwMgqRCcx9etZDDSbdExGHltOnrqBDa5aSnD0QCtNf7oGHd4hD84oncjJz/qi2X+yT4Xxi8yu6DbiNa6CROLJNy3taa4UDPIqpQDXAJ8AgWiVZuZbh3gxu2rOuJVMF4XtBLbWcEup+37fXQ8Pnvg/KDO0jo5NppG89rwLv/qJcfWdwvyjw0sRMS6WhzVFYassWjrsJkJnFo8J60zzQtYRkmVeOXbQqbJwg6XGSO7IFrVHt/LsMOcepRRD3Q6bssbk6iElAFvpchmGyZMyxV204z4dltaejfitIMA7hnQxLSknpS3OVjuKlYEUeCVD445oX8AiLyjDzpg64UaCbmzVT9DKqErdK2WNLCAOGKtlUAVAqjEwV/bJaeZbhzZzAhI93WSssV+7WaLi3I6XYuVh1ZiIU8baBzKCeetbFCTxPdKK/RkwfijPosNqd6eeOHoHAx9mk895b6AMDHE3Xl03a44VONanfexTGQ69J2K4OsCNeClL83CopwOEkiHahy2nwWgDZ0RVCIE34nXOujb472E69RhxacV9AyuCMe14nzGWukLwGuhLlLBCqVQRqU+Ss9GqUSlpfGmwAUrXDmPzw06N2ilxIpuGvThMcY5fFlAnjG4VeNVniZoqZgj4JxNxOdwYTxhu5gJLeMJUapeKM2mYal1LeXV9igqjkcB2fN85xFUGae1Zwec73MCng7S///2/jTWtiS778R+EbGHM9zxjflyzipWFVnFWSTVktxtqilLarllyg0JpmAYhC2AcENt2YCFbhEyoP5CoNsNyx8s2AAN0ZKMbhJETyLsVkuiWi26JVIUi0XWxMqqrMysnN783h3POXuICH9YEbHjnHenN2Tmy1c3gPvevfvss4fYsVes+K//+i9lQTeKdlbxcn2X6tUDmq01pkGaUHUWt1Yk70t5sCMjWUqtg0CnE89LDYaSkJiQSUXGqLxEsmOaKwED9SntOTaRVqzoJ+IFJo85LJdBDKvTDIY5eIc5jUo5YVCk+SM6ANmkEL1g0w30Ld26FHH3WpgnUach3Wd2HUlPWKmASWfesjLJA9SNDfS4GJSyIQ4gHnTCYLQYE6UCDNMG7yUmSIRnK3KjWTLFrEXvWcxBSTGtsKNi4Ba7QQ1wYA70UtMuYKTKWtSsEWNsgqfsPD5g6Ngwpqxj8u4B9bSi3SppNkzil6eSZFZgn3KvTeeQZ+Wg7fBrY2HIVCYYOE9x0C15+MJR1vha4YrAYbdRlGjwuvWiRS8q6U+lQjBOflwZfgo1cJghJZio7O21hZxY9x7XKxG9CmNsybsMRkMlqg5yziKj0nlNqhSuBVd3QddDxl64RqUwTYvb2cXP5mJUxxXtixdQTjRCUmWdUCSjWEhGplqDzmnmVgjjySEKY2h42TX4AHECRyamPKn2OJ5xmjzOGLw8Q3t6jDMs40krD8M7j8LCfEF14CkPNf3CcGBHfM/lO3wwWZcB0wlZnwsitBJ5xK4oGRdGMLNJAQrKuafdiOposoSOrIYIY0TKkq0CnFLGlGaVtDiSZ0zkExsJCoXJwQbWR/QsvVbiJMVxEF/o8FKbzqMW4I0PiReyW6TZ6V4CfOVhPxjiaBAKLR5c5LAG0aN+LJgzCnQj2xLtK6wufCEvSfSUbC0p4IK1Wugkuq2MwmMS3q6tE/pc78QglgHD7IMxqyt8HXDo6F1bga5UYQR28B5fyg2awxYzCyyCg7kUWCgLiNg7JI/PVQVuVAAFOgSyvEImlMOF6A5rlTxstz5C787QSuEuVXRrMsEUjTwPVyh8DcoKs0Y3w3WbeUfz/DoHL1QhU9JRzK1MFNYH6ld4VgGjlwmaJYoiHopDRaEQrfHKoHodUqHlbzsygQaq0mQaV1EJGgsfJClSAke+VCgb+nLeCTZcGlxpBu5yPKSWIKaL0EsYR/E5+ZCkszxRgveBfTMZwf0d3Gwm+PTGlNlzlbClShWKGgcWVW/TO2UWiv3//iq/+b1blPeMFD7ukecUf0CCgV6FpJTcC8psxVF/r7azGN78GEf9ftp3leIBNb2jrvGM7ekxzg+A+m4w0HEX5/GLBUUjpHwqx/vNFiPTYccKP6lRoxqsSDvaajCKxVwKvOqDOXqtAgzFoaWYafqJHD/CBzHNWur7DTS1fkSiGJk2eqvZ9WnRv3AmgskDrBLTcpMmg0IU03yEIzzlfo9pXHohXKXRdfBuUiq00LZiSq1pbEo8sWPhqnqlcXXQ/S0Vk1udiOMcirfrA16seyvXFF5K78CNDF4XqT/Kwz5h6wAEbjUghiVQxnQT8GaXDWqj8ONKsO1Z8Ay1JFP4ST2UFjMKV5cSQNQi9Zq84umIfmNEPzESXEsKapn8qx8m1NyQmWYiE0swoOKdz3EbY+79wAbthoyPYi40QlHrkxXS4oKmH5eYpkgp/spWzK4UuBLMrg+0RI+5PwOgvzClnxbYcfDGveDGMVEmN6x2JJS1CCGJxO3ABpHVyLBqiMeLCUoRf/daJWW6yH/WnXzfjQS+S1BLwK7zFZyoxnmUDvh+nMjCmMvFk1L6OUgCkRF8m8lYKhB5D/d2WX+jot+sabcKbKVpN0qqzXX8/kHIbpWs0+1v9hx+RlEeSEKYraDaaYQMEDDnmISSYI5V43tUQO5hoI/HxaIf9RxnaE+PcYYjZsMHlwe+7Ug6BIeGf3XnFX780nf42rpwJMvRCB8GcdE4enSqsu0mNebOrgjw2xJfKCa3+5AQIscvFp7i0NFsGTHMgZKWvNaIRfvl7TFRQvdQ7VuKechWDNSqKCqfUqtVluwRPXejaDfLJAQkdLKQopwZSBUqm2gbZUQdUafYK5XSb3Nqmml6eZEgBebist8pDYEX7iqVPKQl8f0ejHOBeqXop5KEkooRjA2mFWaI7pzQCINQji9NCDIJHKKcGOGIsareiYfrnOgqVAV2Y0Q/LWm2ijTJ+izNXGRZB8wY5ekmwwvltUJN5W/TGExXYhYj6jvzwEJhwPVhSC0PSR2mZfjbiWdqKx1YHPI7a6BbjS826Ccm9T+QNDVy1b3ofSbP1yATadAFl2cjEIZphCEzJNZkcITL5iAjq7m+EAMdITgxvEEdMMEV4X5NuM7ARokypBEFgQGeie+iVKKXseW1UC6LwOqIhlkBqijQB3NMqdFjI7GM3ktAsOspDx04zeKK54PLhumFQ+w7Vbh2MNfvYXvBy73zpBJV2sj/q7S1JePgl/9/nPZhMDsesj1dxjm2o5YoEd5oW4pDi2kEmmit4Uq1jx17bG0olULNm+RFACHhROPGBaYwiW7UTzTlvqXat2IQvTAPujWTStonalvEhKNh9nH5R2JZxCBVnjwQg2jehWojftAAjthzTNlWtQkQDOntE684Hmx4yZQDbz2u0JQzKA4s5YGlXQ8eppZ+NJ3AFf20SFCH1wozl2BXPzICX9Q66fkOynDR4wflNK5xol62sOLhRzyyDMYKDZMisCacULtiRxRheZoFG109MDhQpOV1nCQkkShTgVPLK47I/RYjOyy9pd/CtvC/rTx6BK6cpGCdJH9kgeG8b8Nz70cK3avENc6Dnt4oXA2dKULpqMEweyWfLemGED1wOY9siM82GNG0QonvQfSU1dKYHuIcXrLo1DCZi1HOIcLMQMfT+YyRAdCHGEHcP9Mvd3kR37yrtMLXlWQLZgE81fUo57FjTTvVVCDl42YygesOgezGjr7XmA5hLHUeP5sPhjkdUC3//ySN8IfVnoCBfvqMc35TqzenDd5aisMes6jxWVTZVsIpRSn8bJY8UW/ks26iqOuAXQZ2RF8rilngyjZBwnNumV8qUiAjGeIo+5mCd54orJ8YEzafECRjLh5DKHhqyZNyOluepwE4GIaEI6the/QUdQ/eK2wpARpjRMbTbxoJDhGutfeBU2xQTqcXtfIAPbY2iaecEiP8cK9AWlLbymAqTe1EiEc+05JVFlkAhcZbuWiHCZrKPj3XVMVZKeykxI7CCiXEBmBI8kkKeRGqDf2RxwKcCXYswke5DQn3Er1uW0M/MhIr8EFLJGQnRs64iuyKcJm2HPQ3TDtQ6pJSocmqWMdnp1QSk/J6uTRZAWg/wFIibLTyCniGfmLwvtOKJn0g/agsEFdmxgeWTtzHD0Y+usaRDZIgqKGPI4wyFEAeJkjT+DQpxOxNPyqgMBLws1Z+qhJfSEJKtwbaKkkS21WB0RLuSUPfFZSxgK7zEsyFZYw5L7jxpJJHPsr2iIb66TPO8ODNZG+cMga16EPigmJvNuL9ZgtfiCdMWeAODtGtk6BKGFwxtTkyBfKAR7em5WWZO7RRCZ5IwZGgDZwUx9xgjOP/8UWNlCTVBd6tdfSTgmYz4sGDERatZTWsURmMcvQKfbY9b06xdJ0Rk+2mOnn1eGEgmFAdKNentlVJeSDp3zZ4qUsaysE7jXSzmDYuk0zJ9J0OvehQpUnsCTsqUvAn3qMrtDAmokEIz1ZZT7dW0GxJvT1bK8oDn8pNgUAKeXFaINHp4u/obCkeszpjfykoD0N/ZaugfqQoD4M6nZUswpweqazHuOH5C7QkfVcsXGAhDJx4r8CWeqkM2pIcRLbi8VpRhiuOgby8DmAMxsUyZRBXbFkmY96CN2+9Sp6zMwqtfPKO42rFI4HXlDGbJZzE6tqJGaKFfx0VG3XwbPMUd19oXGUwWqO0lpiQ9zCu6SdlWAXKuIkQi26sjMupZXJxRtcW6dm6QqE21mF3H7wbDLR3y4b5qGQUhutaak8qCeVh2hM6z9NnnFejpJG5EbKFMBW67YWxcU8zr8Z87vM3+G+uNcwvjNgIjI1yr8WbGtNoqn1hN0j2WgHWU8wtRVNklDpwtaIrilAGSgWvR16MeqdPxlRoRwT6lcLXwSAGmldx2FPsLFBNC1VJu70h2XCdSi9zFPpxBRLYie9vJsK0pFgWiohGTzu+KFE03Wto10wSdHLBcCi7rAoX5ShdAe26DqL/LEXxxdiIpxlfzISpd8Ig6TYqKh9SwEuNnvdU9+aZp8YwARYhCFgI/WqZFicMmfLQL6eu6yBgH41ygJaKRs6fymtFrzfYjZx3LuyabPXBMPEIVCRpwfE5OiX0xeiRm85T7bmw+pJJrJto2rUBpogTaVrVkJ3HZs8znNeOBALKFe3AJ/jIKzUUmICB6hhbiFkkaYIAz+jKS0ISYUzmiVYZGyOxIML3o/ceE41iLcxuTYLJueaIT+MoTGYpgUt0b+jFc/ZaM7ta4gopS1XvOlTAnPW8TysX5zRK+zTOYtBcRW0NkMzgPhjqlHSkeADiWLUZ8bOnAQJ5JgKCsR0VKY2VUaLn5YeBv9tPBngu0lnCAC8ah+4V1W4vovMh+qtbi7KijZzExINcpFdKMv3CQHZGsgwj7pZEbEIbcMXAl61kfW1mJvBVh6Vr1IJQDll+BsNrMszaZ0viQUdCPEStPA6VeNgmwDERkzRtUPdSMbi1bDiSdKdSwkWOuGyGq5N5mYLb+mTQXCHn7qcG3cey2uDGRVA4Ez6r6kQhUJrG1QX9OFLE5FoTmyYI/yQPyw8evO59wupj3yeYKIN5XBmNUhDQ79OpB69ZqcSlTRxv5LO8knouZuWLeC6hhRVxaR8m2ZiYEeVH47OzFQHuGK4jesnCloEurNKKuWxPOHEcyyz3x/CMsok0g6JEVEiuqYgTudLDJBk1asIpkhceVn2R4RSfS54VmeCOsAKKfHwdGTfxne17fGkY3+2pdyXW048ChfGWQTkniSg7BYuyppy0aSLTnRcjHpNQMrlQ7zLv9zRWxMdliI/z6PP2ENf29Bnno24wVjgJFDW1aCnmDtMW9K3mVreOKWyoghE87ZhWDQlzVJ2V2R3EcIQXbAnb1SoFtFwoBy9ReJbhh2xgRy/Xe9CEF7XUstyzUv7HTKK3/eBDyzFs5QP+3UVjKOdwqS+CUYkeDaQlcM5mGLRAwmXnDoaDXBIy4tDJm1JqwNuRiSFKdMa/u6nG63IJa3dGYxqLng2wkZvWNBdHQu2qhPuaIJdY2TzBFAEWCHiOtj6Do7JnGYO0oQ90j1QgUUEH2fiEQyctE4WkZVdqadLNE4AiYyLXWYn9kuhlaugX6cvA2209WjPoQ9sHV0XJoYjOsCbJe3pNCozBqjBSfi1+MNgrYygexxmBJLzOqpisQGcpK1bHZxoFn0LyUusTdRMY6l+u3Lued8sGsxCTUu40A2+7LgRaKYqkeOeNx4x6qsrKys4jRYgXjUAj8VpTGvkKpPFRwhRnbUfR+mJ7BGre02Wc8xs4xnv23kPTYuYW3Upwr3UFZWlFOCdqQ3RRhU1LJlXIvkLrJI4E2YuWGTvVe1wtusO2VmEZnX2+stTUWfAsHityh3XvKPc72o0gOpQxIFIlEB0NhSxNi94NNCylEhNh6WVdMlYqaA0HQ+oHY5qYJEEQPve0ospaLsIjnmD0mLJlbcJj5W9nxEOPTAZtvdQs3PWYQ3lZ3aiivTCi3SyWgpy6JwVrV/WNk360BxuMZ87UWIUQIrNCBQ2U+GLnRjTHaV0hASqHz56n/G+USquQxPzIJt/hWMPS2adUkGDgfeALO2F+2UpBlh2aKxLG++rr+Iw9Rku/DxQ62VF5H4SzIqSRH0ct3WPk22sjzsDAuFl2KlykQa5MfHGFkAcqh+K3w8DXnbyLeVNFgbIWs3sIrSyJTFngq5Io0ekKcCNPaVxYvWX32nbZiuspbqdNDicZ6jO2p8c4H0ccTy9vGK0hEcU0kg7sK0ele3TQGYhaCvpwgSl1MHqSNdevlZhZJWm+vUtLRd2RBoiUOVIstkxa3gEh/TcfpPEFyQpqqsH7c6WSpX7nMAcNxaIOinDRKAiZP8pTxmi7TAI6LZUTBUplPwwvUkwpjyWbkmpd8LBFKc1THvTCWAhi99oFNTjnM+9poNLlE0L04mPA3zQ+wA0Bz1YqeV66NRT7GijoLoyYXS4yKIV0L2k1wnA/qQ916iJ5NmlVMxjmJcpcERhpbvDuIRj4Ss6FCp+HPjc2nkvhtJQGK4phLOTBvZiEIhQwlqhrIgY/UCNTYK8XrrRyYigJRXIjXJKeZRg6tiJRB3MZ2MFDVmkSTRIDfejLYrmaDhDojWrJo16djBId0Q+ese6gOnCJz78khuWHYK3yYOY9qumEiWG0OEZKoeYt7sYtfNejRjV6OkEtGtx8EQSxwI8sfWuwVlP3w1heakqjtBvKVeXZd4/rNT9i1l5qH4HX/vQY5+OWKnG7szKmtcK3HbrpRSpyt+CfvvsZZgc1E4WklFal4J4eTFTc8uHhuxCcKCSVOVZthoGB0W4Y+lGg2KUBGl6KEBQzbdBI6JeZGrYWz8YVCltqdKnRB/O09E9GyAec0yspeKHDix883JjgEUtF5YkokUEgnmvwgGKSTEieMKGqsmgZ2BCxF2GcYhEgjeDxRp2QOBm4zDtVMTVYiVJbPwI1GVLXdTdQzBJlbVziSs38crk0mcT77kPWo6wiAsQQX5aMIpcYJJlxj6uClIgUVx6B+uj9sDKBbEKIXp8DAvMiL7yqu9DHWQp2u6HQLbjCo3vxRE3rU5AxZxnobhDaz2GM2Nf9SOFjgFMP1x+zR2Uchu/ZbMUSApTRsMvzXq4AHieheKwHjHBoq6s7GfOhP8P5isZjFj44LfIFkQgYvhOTVsyhVEMRw6xRZYkfVXBvRwxzVaKMFu5yWaCqSi7NAU7hrca1impP+qkfabh2GXX9dtJzlgsISShLN3OM53qSR3tUoPBphEdCe3qMMzzYSaswh3eAwS8azGFLMffYkWN7MufS2iHvvP+C7FeWqIUst+KyOc7Kdq1GzRrUvMHMRRMi6mQUC/HGu0l4IcwQTCoW8gIXCxcE4h06ZtxpFbVxUpkgMVIG5asQfFyGUTzZklINxsRWwfBlS9+k7xuXoSHNNwr1A4nREXWPTZbi3U8NzfYgjq+tZEGWs15EeQKvNXmjhqQfooLxjhVaYkS9m4qX7wrBR0e7kpQSmQLJ6BbiNabEFs8Dy2OQ6xZYauiLeO40CpQYJk1Ycsf9IvzAstedP3+ybXElECe0BIusCKHl0JUXxUxU0IsekpE8tlYpqBmfcc7UMJ1AS32t0kQSseikxXHEmxiNZpqUwmooMiziaibGFlaNcnqewbAm1cVowMWPwIWK76YJ8p4g0qcz0SVxQQfa1gZJbAoT/qzBT0ayWnVOAnjGoNamqMNZuDGh16moz06YEBrN2pUDFvMKVDVca6FR1i7hzvLBCuZ8nGE+atvDettHUXk/BgOuT9tBKfVLSqlbSqmvZtsuKKX+sVLqW+H/7eyzn1dKvaGUel0p9aee9AV7J0Uf1eGc8V2BMjqn6awozdlpiRqNRNx73mEWffKeI2QhnrgYpwglmMYnL9FlL22knyVGQ7Y0l31UCsjFyD3I/sKx1thxmShrHPWM4wuTjy01GO98SZqfO72EgY4mhUqjhx6uqyBxdF0hRrcfKexYQxBFihrNeWHZCNl4HQ23T/cbryFBHVliBpBoWT4aDpv1RzkwUQZRnSwrMhnvgRaX6zuk7MrMGOXJJqtBtPR58OqX7y9MaH28zjDDepYmKh9gA1cK/BE1veOSf9UIQjD+0YsOq5SI8Zdznwn9DM9frY6D+H01HEuEt1QKokXPX6rmLN9/7sWT99dqC9eYUyp10HlWTdAlaWxIIJFKQ1EXxY+rULbKQ13hNsa49akY6aqC8Qg1ilXaBVdyJfiRoy4s3bwMYyNcyqIbSlTlBhlONsrHGe2TjOpZGRVPCkJ5yHaqcQb+DvCnV7b9NeCfeO8/A/yT8DdKqc8DPwN8IXzn/66UWlmPnNLyB5GU6R7sHD9fMLrboVvF/qKmNBY7tSwuVKi6ErZG20mZqC6kGqvsHM6L5i0BpggpybkXO5yMBDvYUHtwUINTJMHzFaMZl/muNjKgsxpzrD6vbDmaMsyypIrlF1aM9oB7Dx7zcCyf9o3CTdFgu0LRjSVAqps+pHIP3sVSmnp2nUuBw3CeZNQYjIFoSUsnirfsU7/mAT2fbVsyqtFQxWX4ClQQ+zY3WvH6orFPLcED8XwrfReMUqwPmWh8kUedGch0Dys/iSusVbqeHB6J1617n7xqUWvL0rFz45mNhfw+vCak+pOCq7EvVhNfliCNrC+XAuDZ59r6peeYuOqBFqmDbKxuRXZXZ1otqmnBi6qgqwx+XIr3vL2Jv3wBrlwI5xQVwX6sKNdaxmWHmpu0wlMe1DwIH52WCfiIBu+B9lF4xI94jlONs/f+N4B7K5t/Gvi74fe/C/y5bPuveO8b7/1bwBvATzzSleVNqYFGpwNJv2mo7swwM8XhwYir433GV2bMrmipDC0XH4R2fCLl52IuqulkidYM0o9RkH4p6BdeUleEkkxjqWYRlcOAIWCVZzMGo+6KoK+bv4xk31v5O3pCUXNjySvMYZATvKHIEZY/hoBhjNr3I0U/NhKwnHWYhU1UsjxDUP4Oesor1xozFCMGnq4tTAB5AHO4QZZXEHHZPlCijzCow/3H55HYKeGzJaMTjGO6Zg+ptFeW5JP63w+JNtE7T/efrSLysZAMcZhcBpxebljn+6f+8om+pnthRMSSW3n/wIPGdZUOF1cDSzCQz/aFRIXLj7XUn/FQYZWi48qBMIkVmijnihfpT7PoMfNOhKraUGlmtpB9gqC/NwoubtG8coGDz2wye3UjXJDCjgu6NVibLtioF+iZxixIBtrPBA7xzqefU9tJGPNJRvwpxZpje1TM+ar3/jqA9/66UupK2P4C8FvZfu+Fbae3h4ye+q5HzVtMo+h6zYVqxpWNA25f2Aj6GVJPLdZL68eKai/IVo5KsBa9P0d3GyLiowCtKGc9k7sqiLCHS3PZyxcMQzcWz7k8CDULnQ+i5eHlZvDkXK1RB57ysAdV4JXGqWWt5hgociUJj0xwRubxpftXCl9k2CcEGhRDWrkj1DlkKUU4nqufauxGJUL6fdCHrkpR9fMAYtBNME65d6vc4IFGA93XijrTuE7ylrlnp0i1EmNWXwwApn3j/RK0SwJLIqfiKRWhg6ECiyjVRYOpwMkEFzH7uCIwTebJZ5BR1HyIhismBMl1hZVRIWnfMmEO4ljG5xodgs8PEM0gdhRjElGvJD1nVlYFfhgH6bN8rMSmSN54PqEOzgKD9x8m9LhfLFacsOiYdBLjNIWWX50YuVQBp+lQiwack9VXEfMPGopFg9tep3lund1PV7TrivEdzXQ6wb5/PfV77zSV7inmpAlKOS+qk0cZ5NXMv3T/GZyxig3n3/kEticdEDyqJ460tkqpnwN+DmDEJP8gfMuTljbeCw6l1KDvOl9g7t5n+sEVmgslr+9dobGGbt1Lhe75AjUaobyn8J56WmAWFlcZ3LiUopNtlwZmt1kKrzkE5KoDJ9lSAV9M3qQaglJ9rVBWhxp6EhDxyshLWihS5Wyl6CellJdvXKI+RSZI6ii9svwMxivS25aWuxpUN2yLWLPugna1GWh2OQVQgnbC6mjXNF5VVHuWcr/D5dBPeJq6l+MkXQUI9fBIcErUFgHQ7SBKlHvEMRlGcFOSR5uzC9LyWw+ealo1xJEUXm7dR1qcfDmmrae+i6nJXomKXbifIVsuGmpSEgmewGsnMWui/Gzqx8CqWA3gSXJR8ITjuXWc2IWpESl5koUXLoghEBkNqQqTXZSUWGqrsIRnKRiZrsdnht1lBtAvVzcHhsBjRBHTCiDqbsjnOhhBRfi8rmQC7C1gUVWJvbRBc3HEwbWCZksNk3JvUXUdFAehLiyXRwfoNlTFibczn6d3fOnmo2Ro2vEYA/0MtUc1zjeVUteC13wNuBW2vwe8lO33IvDBUQfw3v8i8IsAG+qCPzKb5rht2gi0Ya3k7YdRqJUXbyHgnb7vUWFW170PVSc0fqHSMZUVNkO7pkUm1AyMiaLxgTolnnceiBPPFbqJnKu0gluXfRA693pgVyAZW8pL0NEsRM/YVoGLCskQS5UJBjpYXLJHYxeNWY7HGnAoTOCQSqZkOHc08rlIux+MSz/SiYERYQBbiYC7rVTGGFBpKR09u0ink/R0v5QCHQ1pxEeXjLDKJqK4jF+hGcaWKHIp+BYnPAbvL6a6MwhLpSzKCGscAVfEPtUuFr0dJq8l+Cl4lZGlEcWmljzSuKtCtLETk2Tw3lSwtqtJNEuQRT5hZfBOfi+pryLenR0rDxLHsaNCubUU2DZ+iRctsFSgBIYx4EqNiX0dKJaqd6hYt9F7Cfo1raxSqwo/ruk2Kpotk94XYTiJR6zWpswvFnSbjqroKZXDLAYBKpnUNUNl15V2HNX2uH1P+vwT0M4SEDyq/Rrws+H3nwX+frb9Z5RStVLqNeAzwG8/0hmOyxbMk1Kcp9rthRcKlNphK4+vRAg+FdfUy7cZK/wmXedgiCKOGQn8cVkelciSJxcvRwUGQtzXSSkjM+8p5j26GdKYo7GUIp8uHbNosnJY0ehHpkWu4bEyxuKSeGl5TsDFRzqU1crSc6NnFMdsJoZkSyUQR8iG7OugPZ11u+79EMSK4kJuOHZM+V7FklOfR+OS9d1wM/nDOWJb/lk0XjEgGHF+n00g8R5jFt8Rx0rJOuEnaha7PDgZjKHEJQLDoiMZ6PgTedhL8YDwe3oGwWO1K/16FJa8xDpZ6ZeUat7L6kfKqUXMeDD2aSUVufl9qF+YCgkP8gYQJqWgSBcn8/jjzFBfUDkHqWisFHilKGA8wk0qqXyyprAj0A3UOyIaRt/D+pR2U+GmllHR41AUMzLmjEeZfKb7kIKCp2HRT0k71XNWSv0y8JPAJaXUe8DfAP4j4FeVUn8JeAf4CwDe+68ppX4V+DqiKPuXvffHTINnbCsec2re4b2n2m1RtqLpC0pjcVOLHRWUVUXMWCITDhfNWIWrCszBTOQZ4zI996gK4Tt7DdW+pzxwMNUpUSF/eVJlZIXImbY9vi9hVAhPNOhd+LA0VFaKcBocygndLtHO9KCrkBvWJfYCYngUfsAnffCgo4GKnmJmmZa8PRWpauJt90FXuB/Ji5V0hpWct5wNySvdJCvt5bPkC02iYiVGScbVXTKS8Zrjtuw+8muNE4jAIn75XrOAXzovD64aUl/KAxDnLHjdiQs+VikYGycAp0kVOgaO93CNw/AM51Th+G54ZoTLQIs3nbJOM6/4KIz5AaOdxi+J+RGL+3bj6KaT8PaIxevOJ6pjClbnfR+uI1JIXRlWYFqKusbrSLz0UD0lOj60HWpU49ZG2KlUF+qmomg4vuWZXu8ZXT8A73BbU7op6HHPuOg46CvKmWSaKu8p9y2UZUr7TkqUcRX0MO201OqHMc4fE8/5VOPsvf+Lx3z0U8fs/wvALzzORaW24jFHfVelVfCcHfpggWnWee/mNusbc6qthsWVMdW7a/jDGSwa1KgSD3kiRTOdUQIv3PEUC4tyhSyPw+Dux0qCPkA3VtjSMLnTM77ThSopOmkAR6aCraW2npl1w9LaOnQnNQVF0UvhnCxr7ThWZIZEX/PRO/HJU8kTFZaMQghAJQ9XQa8HlbeILwOJgpU83SzrMESw0kTQjwWuUcHbcqWiPPRMbnRU9xeoxuJHBYcvTemmgyZErvOg8ERIQ+XXH5vPoIEsWLia3eYzTDRynmM2ZKQHJrGm2D85eyFqXJUMlTZCZmUx84n2Jzhwdp1K+kH1Q6p69DZTsdPMuJlY4T3qZceJL3HOI9d8uKd81bOqAZL0V/KVhh/6SSdMW1Y5AiephPHH45g2GOfA2vEabC4HwHDeJfqnlg3eyXuSr1iUC2qNwfHxbYsq5EG7QtOua9pNGYOjHcf4/X307R080G3W2BpMYZkULbfm6yEzUKE7RXl/LtocxojzFd6NIQFtdRydwWAeZVgf1th+TNDI05UhuNpWOiUFBV3Iue971L1d6ruXWVwpWL/S8KPPvce//MIPsPbGFHV/V951F8Tga40JxSNdqfHjGrPXUmyVgWYnI1Z30E8UZuHRrQzY+cWC0X1LuW8xzZDinQeZbK1ZPDelm2pynDR6lbqPRURF07ebqFTjL8pMRkqXN16gt8zzW6W4ETw7v/IC96NMdnPlJc/r7rki6ByEbLMUUAusBTuSPtj69oLy9mF6Hvr6HlPvmb00pZ2K7q8ysZ9MwqJNO1DecjGmVI/RhvkiQjImK8Xks/uFlMoeA7LJQDDsJ7rVcYlCUtMr9wdWiysH3eM4afVjteT9ixSmp5gN5471/kyX6UswXGf0wF05VGiHQSo2eqbxu4mCGCbKRKlbXV1kLWHKniDvGe9RDVBHF0SLosphgp4G2CJmf8ZjejWk+wsXOzy/kCMgO6r0v8BzCtVLcWH6XvDoCJlYmNzwjO+06IMFvm3BGO5+vqbdclQhiPvmrYtctjLAi5lF3bgr77h3D1bajgZ1KQ/iDEb2acCcH9HzfjqN85Lg0RGwRphVldL4/QPGdx37C83ufMQ7xTbzV1op9joZiwGfLdBGU5Qab7QYA+tx0xF61lAcjiSTrwzOV+8TBumVeE/eQ7OhlyhQci3xJQu4bTnQpIb7YaBdmUizkkHZ1yotZ9MyOFMxS1i1D1VTinjOQcM57he5xQnDJlIAl4M/OSapPDg8KmLGDFF8s/BsvNNT3glWKmD3fnMNXxp04zGlJ5aAisbJB51iZcFXpOBUZAgoF/fL+hAEc4zXF4yNrYagYA6DSIBqEKGK0pvaygORvglBSyVG2JrBKNtqoOAlbD9itKnYKgMe6sErvxzIzB5xxKpzRkaeKBODY5ESuMSjjo8wg4DwYCK1b8WDTsHEYHyjWJNXoR9aTxGRAS2DI16LC3BQOm6YNNPqpM+uJQWd5YSuMqjOoHrJZfdxBas1vtDYkaGdyhisDmPGbdDCuXRBxghQlT3fM73NF298BpCJpJhZ3L0d0IGRlUpTZe9//v9Z2tMSFHzEVPCn0zjn7dhobHS3HKO7PdVOxeHeiMO65dVXbjO/8hzFrSnc38XP56iyQDclblQmNoQbFZjdQ8q9VsTjR2aosBQj4gVYZMB7FTWPY5CH5NWCLBljFDwJ+cDwMjmxwNEQ5oJFqTko54P3GF8oMc7Rs0M40SbTrM7ww9R12Uu9SlnzSuHKYITUICsZl8bFzDPacYxuL1IACO/xxuCmFa7QklGZcHFZLbhgTHUv3lg3zTLlVq4xTgLahk3xMzV4mqv4rNyLT88oUd7M4PnnfZ4nsMTv+uBZO4ZJNGYIknmnKS09GtHYp+k6OHp8epnQY4mnBFeEf45KPV/iu+fnsJld1tHTHSA13UqgNjoIQymyWJBimJhjPy1BGiYa+eBthxUXIEUj0Mtwiy3QvdBG0VoCeKFiuisVrpIxnRwQrVF1xeK1S/QT8KVnUrdcqfao7mls5TAt6EZmBd9FXuEpwcDT2kmG+eM01g9x7qfLOOcG7aibcDbto2JVB60ZvX/A6O4FFs8VqCueH7v4Dr/+/AtM352g7+/iZ3PUeIxqLIzKwUOspVKJ2Z1TrlcBjhiWeynAEpaopg3c5tzIabmWVWOaIvcq88CcHCeNm9xz9ICD6kCi22IsogcnL6OrdNLJ6Mcq4d4piJXxa1cZCjEpInriXoPL0pzzYFd56BnftYxvLtB7c1Edi0UKjMFOyuAdO/SBQ3cmBSxdodN9iVLbMJElPDRc3yAeH56HUcKlJXqY2cogv5ecC66Gfoy6GxFKUgyriSFAmhlCRYJ5zGG8ftmeUrrj5Hcsa2bYFlc8CjHOieKnhrEizyKb/BWDyt5wWSmAagLbAoIwFMMxVZjIhVseAmsuVB4J9Ma4f8pWDWMprfjSWFXDiiMEmvuxGfrXxxVZIZIIzTB2fF1ha5NYS14RgpHC7FBrU+59X00/9fixZaNqMHiqPYHgRvd6zEEjnOq+44FCrkrDKq/gKAbXagLKJ7w9XcZ5FVs6YdbzsdKvMag33qb+4S3QcG26x512jf1POTbfGjO9McLt7Ergwlp00+PqIlQ5MbitKebGfcq9MeW6oZsYYrpuPgBcLUZSZ5gjBKOWjwk94HkJrrCAjqm7g5FUTuhQUq8ORvcs0zd3UrRaWZeMoq9LqErcuMROKtqtkm6qhfaWeaT5Ej+xGLR48jl+m4xlEOghLI9H9x3TD1oJziw6MczWJS+IIlaH0VL3b6/B7IGyI9EnWZTMLhei7Ww9ZiF183Kv2ZWBaQGJLy6sDz9MiBGK6VUyuqtBrFQEV6ukWzHoiMi5TBtw9YiVBllYVy7DOBIT8MTMx/ico7cZIaSooRz56MYNMEZK6og6y6UaPOFw70n5bgWayOmQMKw8ioUYXxlbeihzZoNC4kIeqowlL2PGi8wADEV7UYNgU9w/CmZ5HRXzpKSVtmoYO2lcqwE6agv0wkBv8V2HH5VDboGB8gCq3R5zawe/d4B/7hI7P9pS3CmpNxo26zm/t/9SgmPG7+7DezcGJbokeKSFBGBXDHP47Il41x+VEX8EiOXpMs6nec75PhHWMAa0Zuv1Q9q1Nb5kXuUHPvsuL/7ADfbeuMb4g03U7h5+NkeParRSkiVoFKaxtNs1dbOGanvq+x3dWJJR8qoayhHKwwt0sUS5i8tUhr+lMjgpg2+I7vuEO8utBAyzJ3k5blIJUmAd3hgYVfJ/qHQsPzp5Wjms4bXUBUxsDw2egbubXv7oyVqZHEzjxVu+3VHfOCTWWcTo4TmUBb40uFEhLzAOW2nUWiXYogKcp9zrKKd6mCAYjBXBa1aOcJ2k/vBKLSWCxH5JBU0DWwIG7nBajofU8hTkChS5yN2NjBZlgR58YGhEXFzqD4JykfkQgoRZxmHcPwZtEy6tSKuZRE3UisWWTkHWARserj956CEArLJ+8nrZMCvvB084eqYhZuBKRb3TgZOAtNOacib0uW6iUq1FFScGO8BJQMpStVVIXiLeB8lAKys6z2lVUmp8VaC6HlWW2HFJjHXoFq78zozy5h7+cIaaTlg8v0Fxu2TzDfCfb9gsF/wP73yKsfOsfdCjD2a4WDMwGt3wfosI0upyRfFYwvsfBzXuEx8QPIp/eNyMEx6O78B3Peb173Bh+j3Mr4zYf7XmtY27/POXrrH+3hprdzex129Avy4VgDs3FEW1Hl+XIi+61zIaGQ6fKwdusY0vkMdnWYIR95WkhME7iYL1qvdDQCXsP+gkZHAFYqi6QtFNDc3mGqN7lnImMo2qsbL0NypVsBbVt4EJsZRcUgxQR8IoYwAqetcxqr+Aes9J8dv9Fj3rJOOrMEO/a4mUeR0qaBsdFPxsqu6MUphOdBZcpanv98KICbS1IQgp/0fvzVXS/6aR/rCj0G8wGPOlsUBgHWSfRWgmwlBxux8MeKry0UsiSZzZVPBOlVPJoOc19PIq1/iQdp6ep0qGNA88JtXCYujz5Dy7yJt2AY9WaZJdgjWiDko2GcWVhhKod4B2Ik4eNL69kbGiW08VOPxxMkirEbV8PjyB4RHPu9LtYQL0scBxhBbnDUzG4HxgHwmkVd49FA++rrGXt7j/GcFj9l+DH9q+y+3FGu71NbxWTN7exe/uJ+9Y6LI60WaXL2TFMXvUFIpHNeqP2p4ZtsZZqDGrTA7ANQ3VrQPWv1Pz9muXsM9ruks9ey+X4j3fviPMDetQbY9uDd1age48rjKYzqLbnup+Q7NVLBsAELqSl8SEVSOn+sEAuMo/sHxMqccPTDCkZXn8pFsDbwq6hcE0g7B/qn4cf3Ss9ccQCDMS7FI+euokfm5iHdggV9l6ypmj3AsqY21P0jhYnSB1YLh4WTYr50XRr1XBaGt8EaCiSgt3vHO4SZEwXq8HI7WK3y4t6dXyZ0sTXKQ6BvpgEncKE6lDDUF+6weNinyitR7fDRzppeewIl0aOcU5xu0ZjpcbsphdmLzi+OzzfT3L4zeDt2I/xO/FAr1LwyVMCLGQgg5OQUyAiiuyWIgBFMbJfq4f4J5kqMNkJsUZYn96Irto6XmE85t5cBo6i28a/OUtfGnoJ5KyXSy8wGBNC87Rb9UcvAzlvqL7wozWFnzz9mXGtySXQO0e4JqGJbEjH0pT5d7xA1Q6t7z9LO1jSiZ51HM+fcY5tpM86BUPO8mJ7h6w+eaU/VfHvOsvUm02HL5YMHtxytp7G9A0Iv696NCFhrUiLBk1utCotsfszKj2RtixTgEUWw0e88C8iCT/+LIg3pWTFF15UTIvUCOkfp9laq3espdlfbsu5aB0b0SboMnqFGYGLaeceUeqxJLTvOJyNnJYdQ9mESRSZ1LuixQ40qiVVPe8r0WM3oalbvhdaxwFBEw+yaYm2mB2qHDNMdC3BFMECGC16nSqDh6vwfnEw9aB7qVCH6tgPdNEFI3jisHP4wTxfE6TWDRLSTP5d7Lnn2P8LuiZLK2O4sRJ9n2FUMUyzZUlCmWcRNxK1ew49EPAMYr2R1jHFwpb6fSMdONEFCpWSnEEyCQWk4hc54D9R9imHZ5J3gkD/99TzHrMrBWBfeuw0wpfqBCEhPEdMZp+sYALW8wvV/QbjtEdww++8g7fvn+J5t01Joee8T0r++XCR6vVto9qudE+ra0a9U9Qe3qNc2zHzZzpc4fUvLfYO3epgMn3vQK+wvzwnNkLDfc/N2L67Qu4r71OMR6LrfSeqjSpBI8rDUpr9OyQ8fv7LJ5fFwxzBF2hlmAC1Q+iP8oJuwHkBU3pzOGNShlXccypIUEkihHJcfJAYxAw0iGpYSQvn3JxMmCQ8AyeD/2Q5JIHM33wtMxCoBzVe7R1mFmPmndL3rLPJ8D4kujMGjkXDF9cW8szUZ3FzDuZ5JD7soVoXuuexIGOjIGkOKeWA3hLgdYVj1mi/4M3GUs9EaCLaDhT4VO/bJwiDBUx2Ng3kX8dYY3cMK/+rRxLHnc0xpEypzvQK95yMuLeZxz5YQI6UtSK4fkmQx76yrQ+K5Plk0Z02tdIgohpXKh/GAofGC8TWeBh+1ZglWYjmwxjf+uYHCXXUbQWZxTjG42ssJpeElDMQLOTOoqw/vouqmnxwP73X2bn05pyx9NP4M9e+n3+T1/9d9h8S4P2TN/ck3FmjHSTVyjs0V5z/v/SxeYP6AjPeDVx5aR2mmf9EXveT49xPm5mix1yFE0mfOb7DlUIIOhnc7beaDl8seKFzV2uXtvji9OXmH19g+k765LS3XWouqboeuylDXnBJiV2MsVs1BTfvk5tDM3VCb3W4h1pUkq3nBtwMLnZ42oRG+pHMRtQjPGSEE/wTuLyMWKv/XjAqeObmQx4fGkD79gFFTtby71HtTH8kCHWh6BONEAxSKUqhZ57dCuGVHXiAQ8UOY1SKtETfSkup+oDHarPXpboXYeBr7xHzTuqtgetaS+OsWuGvlaYxtNNdfKCk2FLSTHiCTuCGpwdDMgAHSzrHkdDloaBIxlpGIxyqsadQSs5jJCOFRgX4kEPHnosXxY9Vm2FVWNDNe8EGVlZMeX6ISnVOqRxL1fSJk1WD+DqYWxJAHC4xuUixHJMnIw1FwSr4n14o+gnhmJmKeYWZUUj2ZdGxvpIgsoaKA8d3VTTjaFExhlK7jnnfBeHPeb9O9jnL8olNi1qY51iv2Hvc5uUc0f9QY+yFnfzNvriBW7/iMZ99gD/9pSf+unf5R/e+wLl3YLiUEp1ua+8jq5rXGQnaRWUJIsH4eRVBtdJhvhRDehpJISPGBJ5eozz6gwYtyk1dHiu6ZrPpikhxeObhtFbdyh+/AW++c5VDq9VbE3n7H5qk+lb1/Bvv4eyIeDVW/TBgn5rQj8x2JHGVJpiYw1z/Q7l+DnsqMYZ8QJjoE334i3XO5Ih0I11KiAbA3Up1RZ5uaSq8bKB0q2sdW0di7Wq5GXlLWpURAOfQyuxSrWwEXzScFZ2YAcAFHPxlk0Q1ledFWwwqoBFulwhFCnRJ155HuF3X5rkRdNLNF31FsqC7uoG7UYhmg92KGoqNzxg64mlEjz06LnmGXNJNS7fli3zI2yR0sPzlbAPz4KMvuYzA50PNzv8r1N18/CVDIJwxaBFLfolMj77kRpWVW54fs6ohAsndoWBoRfkWH09xA8G2Cqv20ii9MVzmU76z6sBepN6mBJL0K2XSjcjIxNNK+nVZtEH4S1DPzWUs2DMayVqcqUKwdCAXSuFXzOYhcHML8gzaXqBNbSm3xix2FKsXXfUNw5EiH97izs/9QrNFcvIeBZbls9ObvB/+4d/msk9RTlzbH5zH7W2hm9bdFXirQtOVrHM0Fj1mk8zvh9G0snHxJl+eoxz3o7qjFz85ChoI7gsvm1xd+4xvv0886sl+9s1l9YOuXsRFtfWGN0cQdtJAVitUU1HrO8XEz/8dAR37lPcn1GOC/paOL22Uug5lHMnKnVAs2lCNF2MwRI+TeaZdWRyjWJIvYaAlgdaVORCD0Y64qdDJRCVtg/4pg9ZY1llFSXwgvOedk0H7QSNb+1weUoN8IVSQ3kvhn6OcqvK2rCvR7X9AH0URvi3G4Z2e0S7VaRkBGckYzBdT5xz4wUYxFN3JCOWU/4ijGDjZBcpaVFPJPtZojT64f+UGh3wXx/ZKzmEkENKAwIVjPEKBh/7O0yKOVNmCSv3SDAur+jtvRjVaITVYFxXWwqS+mzi8XJOWwXoofAJFor94ApFN9EUWuCtpCliJFHIlTpVjVfBy9adFzr7qm55Fqh0paLfrCl2G6G8Ie8aiGKhmVtoWvz9XdSo5uAFhZ5pFnpEfWHOb9z9DJMPdJAQtZj37+CcE4fK24Q1LzE0HnDSngC3+RPUnk7jHNsDRviYGcwv1xrzhzOm13sOXi5ZNCV63dO82HLwYsXo3W24cw+aBl/XwtXsLMXMYoPxtOOSsq7gYE65W9NuFJignVvMA/HfQ7tVDFKTRS54wxAAgvSSDJFxwYDtWOPSfsEqVD554WSGJWKOkbssbyrZiyQeteriix0mKy1JIO2aBl9QKkUBmM4KZhteVIwOxt1lePOwJE8tHrc0wnuuC+yooJ8aFttGqoj4+EIzZKdFAxrv6ahHqZavXTLWwhLfIcUUVmivS4G63MNegTJikDRCCSngBokf7jPDnLIo48QQuikxRHS8XjXcTzahpufm/dJEEHWVgQR7eeNT9l/c7oxPqdt5Rp9XJDF/54brzCe3lCzSq4Dvx2v0uMKgu5C0E6RBhcHCgJ8H/RYdNb/DcfuRodjxacWgAotndN9SHPaorsfN53DtMspBfVfTAC98apcvvfEK2wdBEuDOAre3H24giBylqkfHBPtWDfNJEMTTlh34zFDpYNkory5vjmpBEClJiWrF5Ft3qD53jb29mmar4E/+wNf476//MJOb20ybFnf7LqquBX9uOgpAd2JofKVxV7bR9w/QO4eMxiW21lR3F6ChX69ZXCpZbOkhiSELGsayQUmjIdWmU5RzT3lgKfZbOlvRrRcC4aqQuOKzpBGlQHup4xf4uUnIaEVTOor2DMv7zBNVgQEyNhRrmtE9zcg69EEz9K3zqL5dHkgOUA6llNRlrCS45OoCOy5oNwu6SZZKHvjBTpGU7lZLKEXsNgUFWfYelyiIadXhh8nJgCv8kictXxiOFf/UvceaLHMvGFlXQDGPHrCiLzNRpOiJ64jXk7DcVE0keLTyMwT4hEUh21L9xCBPqyO1z2WwVAgMm8aJh5554BGqitTNaKDzlYXPrtkRoRExuP1IZhptQ2wiZANq73FKB3x/mDi0BQLrKFLtnAEdxxHZpAlQGNzWOrbUjG7O0TuH0LSozQ3u/9AFNt52LC4oFs95PrV+lztffhHlPJPrDeb6PaFezhdIFmCgzgFHro6PYm4dB4N+nO2UrOaHbWcR2/8l4N8Gbnnvvz9s+0+APwu0wLeB/7X3fid89vPAX0IEL/+K9/4fPvRVHcNlPn5/F7xnQBsxcN95n+1vXcJVJe9yic9t3eK1P/oOd95+mdGtdfThHH9wKNS6eQPWiaCL83RbNWyPKXuH2jukeusWhz/0PMpauq0J80slzZYmFhB11YCrDl6uGA9hTwwenWkcxX6L2V/gxgW280F7I3g7nSx9EzziYsBwwGMjlizSoOHFLaAPZaWiMYnKYsYOnmy3prBVQbO9TrU/JZaXMnOLmbVD0ktpsOMSOy6wtaZbN6lCigtVwRM27kMgKnq+SqVJKZZ8ygV8QPbxZvA0lZUlelRmA+lXHeiKEoDzaaKL2sjRmJswzyR8loD5xqra0ft0oWySHgKxg15zvDYyPYnhmHESHvSR1fDMGZ6LeKNDnwwTiXwe1doI1xCDizEBJtIEk5ZGehdYSihKE13s0wh7Zfi1K8BXYZtVoXJK4EgzTFzxPqJxN1m8QnmRuC33OqFddlLZxF3ZlGPtL2BnD+897tVrzJ7TrL1n2f0sbL2ywz9783tYW3imtyzFzV3c/Z0BGrE285qP84Y1S/UDTyMPHLX9pOM/ifYheOxn8Zz/DvC3gL+XbfvHwM9773ul1H8M/DzwHyilPg/8DPAF4Hng15VSnz1TNZTVm1v1mI+KxOb7aEOqnBCQ3Mk379KuX6HZKvj13/88n/ueD7j3Iw6vN7hkNOYb35HDHM4DO0KhOhHT152juzChKA361n3G39mnvTqVqiWZsE7it8ZAkx1eIN1JOmuM2BcLj5k7lHUCC2SiOLnuxQMiO9GLVoiHy2D8U3DLi0gOREOi8PVwnJxZ4LUUEehrk5TXhGhcD9imzoxFZgR98OqGgrFIVmL+LENQzKMGOcuo55Et/+V4KlUIj0VWozEzebpzmBTi56Zd9nKTRwtDhRNYup+4hE8TQPB8cwjEZThyhKEidJLrgaR+9X5pZZTw7wCbDLKkLAVA4zONKdhLFL4AgeVUy/w5DuceApdLafxRaCtMLoTjqWCsJTNRJXnTuEqR+87uISYvhXGjrZOyVH2fGDvlnRlq70Ce/8Vtdj+7zvS6Y+d7DBufuse46mh+8yKm8ax/8QP87p4UQu57kV7oM6gip8vmDloUPMsz+1bzHuL3j2sftlf9IRz/LJVQfkMp9erKtn+U/flbwJ8Pv/808Cve+wZ4Syn1BvATwG+e6WoeZvZ5wHgPD1n0YD3cvMP0+ib7L43prsr+P/j9b/Pl/jVG9yds3d7G3bmHnk6k3A6gyoJiLroRRaQfba2j7+9hNmpsLe6M7sNLEDyQB1Tg+nxZLC94tdNj5lIwwE7roEcclNt8dO/ygzAYETW82K4YjHXiO4f9k+cKgzEMHr7XIoofA3A+HVf2d5kRXtIPyXnBySCqgSccHbslippsTAY2y74bKsUgWK8HTEyhJjE3koG14vXlRniJsqYzxkYYFraM8q7DtScDWmb3R7jnlMAyeNEpCJv1qYp9l02g0ahr75eu4YGM0GQgB1gqXXs4rkMtDYOlcaWG+8kZLUmzeuXZpMBnHBsEgx9tXsEQoMyfrx/OESdj03pU61B7B6AUfm2C6hz6YCYaGpsbtFfW6SaKyV3L4gsNFfDB+xfY2oPNt5tUWdt7L95wrtt8XKBPabnJo2hzq+2EmNTyMZ+8l/thtAdD0Q/f/jfAPwi/vwC8m332Xtj2+O0oHPq4FqlM8wXlnRnjWx46zayr+KGt91h/ZZed7zF0z2/L7n0v5d17i+p6ioMuDWpXGezmGKqS4v5sSObI6Fd5odCIDaZEgbC9mHvKvRbdWVxpcCOTMMP8/pYYAOFFk89J/w+SkUM/5JUu4lONcEH03pLxLgaM3JWSJGLrYMCDgV7SjmbFSGQvfGITZMYu3VKGXccipCmFOk4uLm73if5nQt27eA+691lWXAZB+KF/kzhR3G/JY2Y4lx0+S7cTjHa8lqLxlPOhqG+EYGCAi+K9qJVzrHq3w3OI17MSL8gnurzP0t8s/Z2OFzIs82stFqEQbbvcB/H5pYkmo+YNGtDDpJen/8d+M43D7Df4poWiwI8rdNvDosFbi726xeELIwAOnjN85vlb7B+OGL1TUe176rfuCEuq7yXg7N2DanNHGtzvHnbGanusgKBS6q8jhVz/07jpiN2OtKRKqZ8Dfg5gRKgWetQMt3SkY2bLIwIGSiuU0ai9Q9bfXWPv0xW3L67x3uY233f5Jl/8gZqdD8Zc/s4G7v4OqqqgMKhFg5lVqWKKqwR+cC9sU37rA8pJhR1PBH8tFJhoJMUoRh60yrxm03lG91r0osONBhxXqE1qyRBGmhSQPNPllyx6cCF4kwKEg6eUhHP8AD0sQSfZi5k/MbnuzOBnRm1gJQz6C7knFz2soXpIYL6UA6abUq0hBPaExqU7wcWTAc90rB8wSp5QZJTBq/fx+ofMwzx7D0jFTkVCVCXIRjzuwSsuGieUSgva+FAhJ1TE6SPdcjDKUVhoafglfnK8d59WKy7oruQ1F6PX61W26kkPYXBmI9MkMUK8JJEI1j0oHno98N3jPUY1uyVYJIwN5cAjMYQ8WBur9hRzR3HYo+/uQF3hJyP57KDFW4fe2uT+p9fYf0Uzue65+8c6Xi1a/I0RG295Jjc77Ps3WGJmKC3vrl+BLIAHYIvUsdl+j4MjfwK8ZngM46yU+lkkUPhTPgmx8h7wUrbbi8AHR33fe/+LwC8CbKgL/szLlOMyg1a/6jy+7eD2HUZGs/baC9y9NuJr0+d4dfMeP/7Kd/jtP/UK43svsPZlLbqziwZljGhsLAz9tGRJ8H1rA3Nzh3HvsNWG1HErokH0ELPbOlKZetN6Rnc7zEFLe3kaAmt6CYONGWDiwWaQBGSQgc/ggCBfWcta1bQDVS9R+TIM25UqiABlx+hDV0ZjGrFHg+Dk0dOLS241LJ1dlS15I75uwQWL6TWh4rlPacvxHgaPWI4nHrxg8xH+iUL3Zt7jKi0ZhsFKxwSbaLFyYx4z55LaoF72lFPVk1awf1dJZucwCQ0rolwxLhp9k3RUfMhukUCZcNyHOETq/6WJxVMcdHTrJT6k4g+QCIOMbDDk0ZNPWYcZ3BAntXLhQ9Ha+PxkJ0lhHyRTVZgQbL1s5L2RFV2qXxjwc9M6+pHGtI7iwFLutSjrcLt7qFdfxE0qmSCrEjWqufUnXmL3s9BPLa4w/Pkf/iL/9a//a2x8RzG+2zH58nu4UR3eLxnUAj0qBonQY6CGo5gZOc581L4Ps8p+itsjGWel1J8G/gPgf+y9n2Uf/Rrwnyml/iYSEPwM8NuPfZV5O7PBdpLSrTX+cM6Fr8/o1qfc3r/ErYsbbF844Edffpcv/6+eR/2/nmP69Rv4+7v4xQJVFjCtZXBXGtU7qt2O/sKUojDo/TnrX2vxP3CJzmoZ9MFrzZfj1YHIceqFZfHchG5qHsRLVeBHV4NhVgHPTgao88Nn4fg2VF0uD4ZEB69lezcRIaF8WS1QAqQAYng5c/5vggs0uOgxG1INv+il555bbjRioFAiaQM/OdHOGI4h6dZ+WMbr4fO44ijmluL6Ae3lKe2mrDZiwCtqZns94MsmGLyBRaKCoSPxw8Ww+1CCaRAR8kYFVoJCebVkqE3ns2cWsG+GGo7ahj5JwdXY7z5NJrJCcAlLj1BK1IIesPQhqzAxgOIzcsvZkMrJuJCJw6GcLE1sbYgyoibwnJVTeKUlKajPxqknGWXZMDzX0a0G3Vp8odH35zCd4rWW1P95C7fv4V65xv0vxNqKio1//Sb/xVd/hPX3FRvv9IzfO8AfznCHuZmI76gn4cl5JvBZDfJZPe6j9v0EtLNQ6X4Z+EngklLqPeBvIOyMGvjHSjrjt7z3/1vv/deUUr8KfB2BO/7ymZgaj9uO6fSEac1mFG9e5+L0JVxRM1MVO2bKu4Xls1dv8/offY1rPMf0q16iyUpJ5mBtBsy11IIXVwW6t6hFw/q39zl4bZ1WSXHYaGBM66n2JVnFF4rFlVo8NBO9zbCkrgadhiWebsZKiMbF62CQMtZRMcuW+mFgRp3mVGFZZceIjI8MklgNrMnvg25H8try8/hh/3R+GIxw2D/i7mm5HTF2FVYahGvS4nXnFC5ba9rNEr3oKHYbdOfopwW20rQbOonh58kh+SQQryfP/otwy7AikN9dJdVkUvp4MLIyucTOYqAxBvhB9C1UwsuBhNfmzBiZHN3SdcV+iN59ZG5EaCNOjA+AgqFv03NyfqDj9S4Y+aHGoCuUiFHFvs28ShUmbJOz1JxAOfX9HjProHcyNO/vojbWZRKbt3B/D4B7P7jJ+KZiftXB1YZR0TN6fcTktmPyzj7qnRupovaRGX4nGdR8H3hwv7MGAD+h7Sxsjb94xOa/fcL+vwD8wuNc1EO11aXM0kwqVbppwd/bYfzGiPVLz2NrzaKquK020MpT/8AOdw63KWeXKb/ewGyOGlUiEOTFE3F1gVn0oD2+LsA59O0dxpMS1IhurNLLUh0Gw6xFeL0bR8OshmBbgBuWIurRo41L90BJc8UQrAL5fvTAIqSiHPTBw43ULgwJlhj6ZPn3GCxPm2KwKv9Z/a560GaIEQqwQQzuxQrcBtEPWU1TjverAK1whYeMr9yPNf1GLYUAWkvhPbo2oAq6iR76KjjrcQgk2CFgQzFTLwYUUdBNi8BPD5VFsoxBCEa8VImznQxuoAhCeJ6aJeMP8szi6ke8Zif61oVOFDVikDFOBiFDUWXHyYsE56JKsX+iEhwKSctuRavcxOeoAXSo3iNwR6IKxvtcndCQ6yv3RI85imOp6QQ/qsRrPpzjncW/co3Ftly03eq5vHXAOzcvsHXHs/Z+g751H7u/zxIj4wkmaTzQPk4q3YfQns4MwZPaUUGBU1r0oO37N9j41jq23ABtaJqaDxYX+PM/8kV+rfkBbi3WeH7nEv71t1DrU+F19g6valxtUFaj54GjXI7RO/uU797Fm8uYjSJ5nOVhTzcp6Kc6ZWoJ/jckcETpyTxxIX8aKizPpUo2Ippkh+wt0wTDYwPm7EToJhnA8H2npKBsDPikPgl/+5CznHvR0QONzBOvQ1cHrw5AO5/e6UQlizKTgfFgAo4sBkljKx8mp2Eii/cqkAy4hiAqJNvajQKvpKQYzqMbS9U5dFfST6QqTBwPXoEOzAjdOrR16TxSO1CepysNfrOg2TDYShJYxnd77EiMSNRZSbUPH/DAxcuP0NOQCTr0b9RZ1p0Tcfre4cZFgH6GVUrCprMJIPKcYzZjygSMkFgwzDAwV1ypcKWWcTLrQgEELcJWadIaJoY45lTriHh71GcpZxY17wYul9H017bR8w59b1+gv/U17vzQJmg4fMFx9fkdCu2ovzGm3nVU374lKdrGSEXt1USSE1/YM0ISZ4w/fVLb02OcT8OEjkvnPCkjCFjKPjIG/6VvcOmDy2x8zzVu/viY2VXLvXbKX/jcl/inm5/h9uFVrt65gL99F7W9hS8LzLyj2yzRjQovmMYXiuKVq+h3b1G9eZPi8hbd9ohip6HfqllcNMOys5RyTTGAl6CAEPhZKh2kBq9ZMElSoCsWRh0qWqi0TI/GNFG6woulu/C7Ah/4zMmbzrymqNsRA10xsSTqL3g/cHsjJppsefgl1rnTGdwQP4uQTF8HHYskkxoeWWAHtOtQzBTl3IUsOYXbLlCuSAYyyWe2Xiq5NA5XhsKzQXRJd2BmQaDJelSUPe0tfnOcKHeCVw8lqYq5o9xrMYctdrw2DB8j11Ie+vBMEWA+jK0YpBz4zwozd1S7LXrRC0MkKADmAT4dMyMDq0eF1VGsG9ijJdAaq2YznMeVil6J8FA/UoBBuZLq9iE0HrtWJ0hJWcAE/NkPWZkx+Jo0tT2UOw0UGnUwh6qk3xwL17l3koBycZvZpy5w+Lxicdnxwz/ybb555wrNtzZY24GtL93B3bsvRjm8g8qYk1lxJ73Tq8knx8Egz5BhhqfJOK8GAOK20wD+PFgQMwUfkBXVKCMRYqUV9s49ysMZL968zNvTq3x583n0Zc9nt27zz//NdcZ3X2LjX7yNP5ihe4tfn1DfbbCjAr3oUX2Po6C9MKLuL8H7t9F3dimMor08xlY6eCGEKhXicRazoaioeDvQT9SwtA8/yjNUxY6LhMjn1QHndMN3hIM7GLvIq1UK0D5p/abhv+IFp23h/xwPzjm54uX5JIVpmswIaxHvGdTzghcYWQN4KQagSLoO8r0hmQVPqqhha011EOh4VXaRSiYSEVUCZQ1FIxh/McukTsNkZXZmw9goDH4sB6vutRQzg60NqneYTiRVcaJQqDpLfbeh3aoTPFG0duD/ugH+SfgwpASaYt6n40ntRYVZ9PiiXGLg6B5UrE24BBuJQS0WDldIZRyiXoca5nJnpPJODA5CgW5GFHcPBm8/jCcISUHRQchWA3HlU+31klxyfx97YUNiLYsePWvw711HbW2y/4VL3P4RTXO55w99/5t85YPn4Y0pm2+GZJP3rqe07Lhq9X0uz7fyDseWr4iP+j1vz5ghPqo9Pcb5uLYayc2355+n7e5BuCPUJItFI5V2Iup9b4fn/3+bvHnpAr9jNS9t7fCjL7/Lv/wT38NL7hXWvnYHv7OP+CSgF9Jd4ok4bFXSr9cU1y6iDhaYu/tUwP6n14OojXifJlS4Th5nMLQxg7AfB/w52hU97JPU5iIdzMV7DvsqhsSV0JLuRPCuYKBWLSWVrODR6aVf6b8IW+Si8boVjw0vTAdbKkwj0ESekOMKRXHoYKyxQUtDW9k/tiVlOQImPw5CSg1HVCTx6E6l++wmim5sUM4MSSSHFtOYYSxojQ/lzFxl8KXQ2crdVpIpkAnDTitcpTGHHfqgpagNzmhS9RqjMAtLKgYbcGQfdE3MQgTu8V4MfxD08UYLPBHYLInVEs6boI4wqcmFDrCH6WSSj5NYzryRKixybFcqus0KM6tSX0WcXFnQWZJLLPDgCoHJipml2GvQH9zGX9jEh4lLH8xR+4cwqjn84RfY+bShudxz6aUdvn3vEuoba6y961l/v2f0tfdw3kuKtgtBjaPeyfQwM+cq/p3/v8re+C4wyrE9ncb5tOXKkcE/f/wACJSdpHwFMqPPF9TfeJ/tr3+K+2YTrR3fd/EWP/6D3+ZL+5/lOXWZ9a9r/N37ktQy16LONiqhisvskOI9qqDt0Lszqt0xiwtFipjnmWOJrka2zYIKetCROie8X5aMMIRt8TaiB5wlYgBDBpjOEh78sD0lqsCSxkUeWItLXq/A+ejdB8+NoFGxQl2LfN0hEUQlDzoZowDnDM8yetnh2rLtrpIO9O2gUx1x2dQX+XEKKe2FUngVlAq7iVQVj+W4fAwKenTToxddgnLQkhghanUaX5ssSWTwyJX1A0TQyXG1FfU5s+jRTY9dq3CFFsPbDwV6h4cESZHEHjNu463FxJAw2efZe4Omh4x/rz39WGMnlXi8nUP1WpJQsuCljAOfageWsx6z12J2D0Fr+vURqrHoWYOaN/jZHP/y8+y/ULC44ik2W5TyHHxjm813PBvfaRm9s4Pb21/O/ItBwDPGh5bad6FBztvTaZwfth3lRR9p4GVkeqfBSRppf+sOl750hXZ9nftr61wfL/hfvPA77P7YmHfmL2MW20z3hKuJ96jxGIxG947yUF5E1Tt8VUBp0Hd2Gb+3jx1vCksjvjyw5PlGScZkwIMR173IWUYRoOhNRU8zGbIABURqXvKm85c2W2ovwRN9DCIOBhvtE60tJncY0VLHFT5wuYdjRO9tORim8EEiNF2fHvaP3q+24GJQLVxrUu7LJxkVVxSDtKWkfw9UsSTcBGll4LXAI7Yq8HpMfc9gDlupGO0RT7mXQguqs+JVO5UMNp14w/1GjY10yuiANy5kGOqUQadCoFK3No2HbnOEKzVKOYxVEIKRFJkMXLwn5VPSidx3XqZsRfGQ4fcIH+XJQCB9ZscFZtaim54ipPXH641xDTHMDjPrpH9mC2g73MUtXGUod2ao/UORNtCK2WsbzK8o+gst01HH7VsbXPkqTG92jN+8i33/umDLGdZ87Ap36b3keE/5qPYJ5Cw/Snv6jPNJ1Lj4+eq++e/H4VbxWEoRIxO+s6AN5pvvsPXi99JuV3ww3eRfrn2KH77wHt969Sr39mt88TKT/+5r8n1rUdaiux69q7EXpmK0Oyvle7SGO/dZc47m2gbNhQK8F+wwULNyTjEM1DoclAd+qVZhZDIkLzpb/gqXmKX+GrjRKjN6PvGCi4WnPByyyGwlesz9aAAyTRN0GtqY6KHonKIf+aSg5nXs10G1LQa4hsAhkjUZZEldKQbctHIcR4SsSNW38QzBzKiylwUnAZxmEH8Kz1f3UgZsqEoN/Vhx+Jyhm4wY3zZUdw4zY+zk/xJ5drFklyoD88HQj0WhMBcAcpuGYl4sMV+UheLQSgmoUHPRNBY7EigtFr7VTS962KHUVUreySdvP2RxJk3oCEfFU/ph9TNw04dxoqynnxqqewo9a1GLHj0vBYIJxQ+UdRI/mTVSYqzt8OOa/rkt+vWS8Rt3gnqclcIULz/P3ssF3ednrI1bDm5P2f5Swei+ZfTFN3GHM5QxuEWTagE+0FbjSkfBlGdp3wWGGZ4243xSxHbVWB/F3lgyyIF6sLo08p4ozg8hirxoWHtzn8XmJncuj/jvdr+Xq8/vsL41Y+/zin5UsbHxA1z4lzfhzj1JY53PUWtrmLLAjaTIn+p60Yi+tI3anzHan1GvT1i8sEExt7hS024W9COd6HS2Dst3H8r9NH6J+xy9Im0HTxOiB0l6USN8sFTZ2YmhjXzqYuYpZoPcpouFSoMXFbMOH2BbeB/0khXWZdeXUdhSHcMcw46Go9AykXQek3nLCV8NGYXDF+UzwWhJ+sdDckWWEh68T6+l4osNJOzYP7oTTNpdK+knG0y/fV8MtFH4qsCVJbrtU+GBWLaMtQrdanSp0r0twS9RGyOsgPpxSbtZUB5KVRBX6cS2wSiZYMzgEee6JrrNPP8Vw5xzzQUeyg05KWFG+idUNomT7mZNeceiD2aoppAyZNahul4U4awLOhkaf3EDV4s5GL19X05xcCjvykvXuPej25R/5jZ+d0r/e1s8901H0Tim/8Pr+LbDew+hbFWCNU5KLjnJQ34Y4/sMe9FPl3E+K78x3/cog67UMqdydSBEfVjA9x3easyb73FRKdqNTQ5ec9y6s8H29gGvvHSH/SsVd9cvYuvn2Hj7AvX7u8lIa+8xZSEes3NQleA97sK6lJBftIy+cx+3NZW02jhe88BcesmiIc6gi3wlGKGBPCuPfGmrknc1iNdIwKiYheBa8D6LxgnsEl/8cGzdDRBDfPljUDEmlrgi14PwIbg5GMyUJciwKlD5PSH6Ha5kmUaYeYZyQlKtvlwfI1fqG2AelRgJAMp4CAJUKKHBNZua4toG9Y19MfgV+ErTbIypnXjQsel5hx4XKd0bRBI0BeFWEmqiwJGtNK4oU0FVb4Q6GEt/OaMf7K84BvwQtFWW5fsJEE4iIoVgcUw7V2FSTZXdA1XRjQqUmuBLg541wh7RCkwJVUksTea1Fkhm0ck+u3uiPnftEve/f4PbP9Wg7q0x/uqY6XXP6L5l8gc3cItGVB3dg+/WcPHZavhRveWj2qPg2J+g9nQZ57w9wLg4w4M868NaNejeYg8OMe/e4MoXS+x4wqwoue/XaDcWXFk/oPveHXbdFv2oZm3zItP3xuh3buKbBqWihfCoUY0vC7wx+PUC1ZXo/Tn6/gGFWsOORqhRPHfM+vPp7zyjTQzw4LWx2iWZYc0NWjTiqfgngS0S2CG6z/m0w7GioUv6EPkyWw1L5/QzOH8hSBaOp4fAldJiOHWs1h1a1MOOxjl5o7mB9kCR3WfkZqvle/YqnEcP9+5NoO95Eq/ca8X8comZjzH7jYj3AK7S2I1KqG9hTKjeoRcWU2osGgoPcfLzoZvDM/Fh9bE0mawE+WTic4le6ZVKDJqYAZoCpwzZg6uTc5xcU18Qn6sf+sMIX1v1XpwGLYE9yfk3uFGFC+XYit0GGotetOJVtx1+voCiwL14md3PrrPzWUVR96hvTxnfEpW50fsH+F2pfjJcXw6KH/EuPo4xfsYTTo5qT49xftjOXzWwpyWmnNacxd7bofxyx/aV78NWBruvOTwouXlN8cPPvc9vHow40CPsyNCPp6wX1yhu70nZnrYD7/GjCQRvxI4q/KiQ+oS37mO0pqwlbdgFapXuGF5CRUgXdoMqnPbY1XqBqQ8yI+UjthG6IBpTQyb8H7zckHSw1NURx44ec4QW4gojO14eeIy4Myx784O+RBQR8iKoH1EM67E+O3Z+i9ky3qc/ovHNDGSsx2eWA4vpnoxUH9fdcG3tmqK5VDNu+8BnFoPSTbJXwYHuLLrtMXNZ4kQDHYN1fmnSlIKs2ithYHjCGPBpslXOo1uh2LnKDFmbeFwx5KAnBtARFbmXWDZxEk2/Z2PCQnnQozsr2hhNLynX0zG+LrFrFf20EKhrZ4FqxFvGBw/fefzVixy8JjKg7QULt8ZceBOmN3tG1w9Q12/hrUvlppYH08r7+MCNPAIU8Ywb4qPa02OcH3ZWPI7/eBKd7rRllXe42Yy1//YrKPf97L9YsJgb5s06d7am/Mgr7/LF5lWavsRVmoMXp6y/M2brS3cgqG4p62B/BqMKYz1uUtJenFABeveQ8voOZj6FFyYsto3gwu1g+GwFplWYw8ClDcGp6EQnxgek4E8MyCUvN9GrZH/dDRU64gvdj3QyLkmYKEEEwRCikge/JKgfflyENZL4P0s16aIRjqwAPLhaOM7J+ASDs0SLi6cO1xQpfdEz1X3AwMME4opB/CdAzkPQUithoqQgI8wvGIrDEeXuQuh0XRUYHmboz0JRdBZz0IIv8arAodFO2BoYnyYKp0Gl7KHBcBaHvXCdvdy/6qwECxcGr4vUB1FMKd26BY1AJENnBgPPUCIs19XONULqe52kqjcWvT9DLVr8qMLXBXYsGS/FvBcoZOcA+qiTKkFS+9pzHL48Ye9lgytg/L5hfMuz+VZL/eW3hVYXYjVLlbNX3zcY3sfj3tWj3vOzGO9nGGuO7ekxzo/SjvKYT3vYJw2IINDiu57J/+d3mfzA57j3gxvsjBVv/O5LbH/vPf7Y973B3veM+Mb1K/DmFGc03fgyW2+sU33rA9ydeyLy349RfWB2tJZ+Y4QpDebuPvrdW6zfKDFfuMbhtVIkOd2A50IwVmGJq6xPYukJn1WDtnCkSUVRG1uppICHhyKyGDKOa+oyo0IJqyxRJnZJpKjF98suTyReh67Mf1aaWXhMIxQzvEH1BjcehJx8MRj0pPiWWaoo4iQi+6TU4yWKXjBmWJaKpEZOuCtCvLEfDH27WeCLsVxbJxNHPzHYtSA/unB4PaI47ERwfmHplUr4+0DbU0OdQEWAPsQYJx41YRJte+h6it6hmxI7LumnBW6Ua43IcXXn0DrXwiYdJ28pK9RK4k0x64XSN+/g1j3YWsdeu4CrDHrW4QuNOWjFaB/OQWvc5S28UthpSXOpoh9pDp/T9FOodmHr2x2Tb97F37gtLBfn8F0/FGc9Nccga2dJKDmL0X1aDPOHOEk8Pcb5UW/yKI/4rANl5bwxgxDfiej+G+9w6fAK9f4lbv0hzZ33tri/N+Gly/f5E5/+Jr/uP0fx21PaTcW9z4+YXH6VjX/xtmjXLhpR8+olQGIWRpa0GxPUqIKDOZOvXae+u83i6pjFlhFtXivBOhClMVtp0Zcw2UsajPNQBZqk85sqzKu4T7YUDhmKOVMgYse698GIB4ghiP/EYFrCnwmThGNQn0sBRI/XevDYo3fnkMoy4RoiLVD3HtcrVMj0eyDZww8BL5B9XKxsTVYGzAeZCy8ZcLHKyyB3KkwGzDCZuIKhWG8w5HmhVW+EAudqAxlTJorw5ypxMRibK9v1Y4PuCgmyBQjFVwW+LtGLFr07Q+8pinGFXauxowJfhAk2nFv1XjSqQ4sTQz4J6t5jWpf4ynrWoZpWKsqvTfCFQc9a9K7g6ebOrhxiVGFfuES7VWPHhnY9VHzRsLgs2YiT6+Itj759G7+zi180MvlEbzl6zCexMlY/f5ig/yehfYjX/vQY5ye5jDnJUJ/gaftYcFJpKUR5OENfv8W6Usy3L7OnDH1fc6Pc4OLokE9dvcNbFyaMb0tQ5/CqRv/YK6z9/gf4+RycleoPBE2hSSUvaKHRWqMOZpibO0wOG+rNMc12TbemRefA+JAO7PBG0+UiQV4MXjF3ocyVSkyNlJEYIZDMq1NuENrJ2SIpnbwblv8DNp0ZrGDY8szFofNILI8IKyx50lpSnWG4Bm1joosPVczVA8dM2Xt+WDS4jP2RB0uTXvbqMw8efp5l6IM+B54hizIzuBKkEzxY6dBnhUrb/eop7LAyiQiHrBa84LxFMPQKzNygGllVoVTAouWadKGT+L7oRA9jVHDi4Xko5zFzK9K2iz5R5JTzkrGqNWrRCmzR98LO2JjiJhX9tKRbL2jX5Jm064p2XSUlvvoubL7ZUr9zD3f3Pr5twTt85wcnJj2nE97L04L0n2TD/CG3p8c4n9Qe5wEf6S1rHogsJ9gj/57DHc7Q737Axa+MsfU6sxc0i2LMH+irfObSHdoXOkxTBd1ihSsKyoMr1N+5i5/NoRfuszIapSUlGK1xk0rE4nb24c4Oxc4+Zned7tIa3XoRjKMbdBYIGG/0EHuPbhz9qEjFORNenGHTOpSnEipWUE8zLBmXlEKeviNJM7p12HHAHBKWGjzVlZEjGsZ+CIJlRtxHwxa9/6BfjFwKIKWqXJVPnMNxE8wRjulT3USfMgVThZWIl6uV/sgCl9HzdQbRbNZhSKgMQglGPuLertQJMiHD4tOqK0Au6fc+JDqVRgr6lprI6/ZKQalBy36q7TGdlVVHocVrjkHUPlQ48R7dV2kFEhkl5rCVyvG94Nki/qXBGAnWRU5zXeE2JqlUmlD+ZBLqx9CtKewY7MgzuqPYerNj9PZd3O27UjU7jkO/LINw5nZuhB+6naUSyi8htQJvee+/f+Wzvwr8J8Bl7/2dsO3ngb8EWOCveO//4WNf5aNEf0+i4p20HHMWVRR4TFq6uUUDv/N1rtrv5eYf2QRnaPY3eN1pPvXyLW5urbNYlNi9imq34OaPj3jOX6D8YBe1fyjZU12PvnMfxiP8uMbVpeDQhUYdLuBwDtdvUbx3g+ryRez2FDcq8YWiPOgxjQ7FQcVDLhYWr1XAlwMLwoCrBgOzRJkLBjinoqX062CQvYZy5qjvd6jO4UtNtx5B8Hic6MIO6caApIQ3LiRbhG3hfK5QKSlDOVmGQ6jdhxe2VyelunJcPfKXXVYZJnq4Udc6h3nSdUYja1c+Q7Yn3WUV1O3ivSXb7ZMnDjK5RNnVyIxJ6eRZxqZHpQrgpnO0F0YCGXWCu5v9BXp/LgazkEk6jj9vtFymUujCiEiTCZOA9YJVHyzCBCTCW3SiekcRBJ6yMa/2DsRAVyVusk53ecLB89VwP15iFkXv2XtV4wuPWSim78H26w31V97B7e8LhzlnZJwmnP+o7XHZVs9gO4vn/HeAvwX8vXyjUuol4H8CvJNt+zzwM8AXkBqCv66U+uxDl6o6K61uNWX7pP0TEV4/OLBWDHlKPU3G24HSqK99m2vzl9n7/Db3PmdY3JxQX7rLT770Bq+M72Dw/PKLP0bxX13k7udHTC5VrL05Rr8rpXqUUuLlOJfKFrlxiZ9UqEvrqMZi7uzi7++ibtyiqGvU9ib2whr4AuW1eM2NpdiZ0VzbWAqM5UyOgacc/owGKJSf6uuotRD7QL5b7lnMXguFpl0rA9wgx0piSpmOQwwKKucpZl1a+ueJJZKyHLYFgSDIPPFULko0r+OksaR1Hc8VknSSRnVcMUTaYExWCZlzph1SvW2pMPg0SSTxesUSBS823UrdP68VNgoHxesi9q1Pwda4ynGFolsrKA96ytuHqHu7sooqC1zb4dtWYhpFIRiuMZKJpxVKaygKlAkiW2UxjOeuRxUGX5X4wohRNho1Wwg3ORhRVRT4zXW6K+ssLlc0G5IyPrrnsLWincg9VAdw8IKin3jGtxQb37FsfGMH98bbuIArLynLxXchOktngRofBYo8b8DZylT9hlLq1SM++r8C/z7w97NtPw38ive+Ad5SSr0B/ATwmw91VQ/zoM6KRccBFTOYVqPGR6WDQ2bMRWaU77zPRttRzC9xoyr5xjvP8QfzF6G2XL26y1//3H/D//En/wJrvzOWl+Kz62xo4KtvoNfXgidkUW2HaTvcxiSkEWvctMTXFzD7UwnqLFr83j56bx9Tlvi1CX46wk4r2qvrgHg/oqMcIINe0sCjZ2mrULwzGjLI8NrlfotBse7CCFtp+qlOBVeXuM2xSxMEJEY/cmRz0nJMLU5whBGIIE8YgcgmCfeQY+fhnnK4Qur9DdcQK47n9yHealwRBNgkH+0+gzHiysEM5wdSsogIGzkp7ZjrYFhht7hS0a4ZlJc4QLXXUV7fgxu3JUnDaDGyzqPqSoxyVaLGI9zaBD+SOETUkVZtPwSTu8XyzfUWFcentYlfr8oSv7WB3RzTXBzRbhq6SQgwzz3lHcfsimHne6HfknJrer9g8oHiwtdh480Z1Xv3cLfuDF20SpM763t5nK7NeXuo9qjVt/9nwPve+99Xy17nC8BvZX+/F7Z9uO0otsZJ3vRp+3ovnkwekfYe7zx+vkDfvMPUeZ7zl7nVjejWPP0WzNuSW/0Gf/bzX+Gfrn+Gu+9tMH7f4PU624tX4cZtmC/wxqDqSl60uailqUKLsh0SOGRUoOsKVRjRQGhb1P4hatGiDiv8uMJOa4q5VFxxQTIyCh9pjzAUEKw6Rv2V85LW7FmqUZdXx8gx4sgXXtWMjthzPKayIp1KZrwgGDNN0vcY+niAVmIySw5DLGlbZ4kXObae5hYPqYpL+Ft3JOEmFw6qw73EVUDO3x5414NXbxoRMPJaiqSqhUvfjawF5cHXmmLhqPZ6ip0Gs3soKoZaoTc3Rb+iKoaKLLNgcLVGNbJKAWQc9AE3NnrgH8fxmQVMfVngJyMoNHZcYidFEGpSg5bKIlSOKWH3tYKDVxz+uQbVa9ROyeS6ZvNNy/q399G3g9xnUJRLNLm8nYUG96QzA7+L20MbZ6XUBPjrwJ886uMjth35ZJRSPwf8HMCIyaPNsEfR6B6m5QT51WMeeb4ARRzOoOuYth2Xyhe4/9mC2UjTdgWvz57jM+ObbL4250vbL/EHF57j3mSM7rfY9B7u7ojKl3Uo1aNaLd5PYQbDWJd4o0UXwUxES2PRwKKFvkcd9Ki2S1oQuq/oplpkPQOemJb6IVgYg3E61NJrN8wDt5dU30x4wbNq4THomDII3crvQX1ticUQgoEuQB1L3GQ3VKzOPdjoYeewSA4Z5EG/+NTVioM3JGmQEjeigY6Uv2FfBoPrhf4XNY516wJMEwuzgrYOR1hRaAW9l5jAYYfZnYvh7XtUVeHXp/QX1rCTciit1XuKgyqUzHLyXJ1D9WKcvdb4cSnPdmU1J9i3xlVScNhVQrXsJ1KrMp0jQFcgok+LC4rDlxxstfh5QXGvYHxTsfmWZe1bu6j3rotGhnUDlHFiTamHaOeG+ZHbo3jOnwZeA6LX/CLwu0qpn0A85ZeyfV8EPjjqIN77XwR+EWBDXTj7E1w14g+DNx99IUdPDEtve3DL0mTgBDu8eZvpP76Pct+P1wWH4xHfunKF2+0aF6oZ/87V36V8zvK3tn+SO+oK3eQiW98cU757B384w/tQdt57wQmVYI6qs4lyJ0FBjZqU6NaKBnFMt719j+LeLsWFTYpLaywuVQFHHVKHbZgvY2ReMtc6TFcOy/xgeEzrceFlT9xqJayGZJwJiRwhMBe9VVcEvCFNeAFWqYNxzrBjMbhBoS3HxIMxTn8ruaa8HJYzHlcNzJUUmIvesBv29SYkzYTkDidudObxL58vBlHNwmMWMnN006Fwb7Gwcr+FQDPKe8q5pXrnDu7OPYEu1tbw2xvYtRpXF3QbRfBkVYKIiqkRmmRjKfYLXF2I11xK2ax2q6KYW3RjZQyEiiuukP609fBsVIBVfIB6TBeLCSjmFxWHz0P7XMfkwoz5jTU2v2GY3HaMb7fU7+7g37uOy/SXk2F+AOrTHFug9SiI8DSn6ZPOb/4I2kMbZ+/9V4Ar8W+l1NvAj3nv7yilfg34z5RSfxMJCH4G+O2HOsFJD+1x8KvH4UnngzUNQiu+mNFM/9k3GN94hTv31vhq9wpsdBSl5SuXn+cPX3ybf/e1f8Z/u/ED/NbWZ5ldmzJ9f8LWtw5RX3odvTZFVZUY6IOZFKGdjBIVKxo/c9jSb4zw67Us4a3HHK5jbu/gb92lvHGHam3K4jNXWVwqscGA5UL+tlY0W6XAHAsnpZ0CBJBSxTMPTDmfavol8aBgrCP1jAB52JEeUsYZoJDkMSsGnQ4TBHy6rI+RfbT1uACF4KXqeNEErzkYINerJHHqgtDfkHBCwtSdUbjCU84cziq6iWDdqs9w5WiUO08xd5i5QBnKOnCe8t4MvT+XlOX9A3zXU13chslYGBa9FXjq5efBedyoxE4qfKEpducoN6IfG+G2h0rXLijGdWsFsytVYIwMmY0yyZgHJhHlBpZIZJzElUAsoGtr0bCeX/F0rzTCl9+pMP9ik+fed0xuLKhu7sO9XdzOruDX0SgfNf7TNnc6XHjatpM+P8emH2hnodL9MvCTwCWl1HvA3/De/+2j9vXef00p9avA14Ee+MtnZmo8DGZ82n5nbafR7+I++cDJ0rxxFt8rXNuhv/4mV+9eZnTvKrd/pKa93HN7POWb9RW2y0P+5MWvsf4TC/7R5At4VdFurrH+3A+x/sUPRJ7RGNTG2nCetkN1CmU0tDppCptFj2o63KikvTzGrFUU+w169xB/MKP+/beoL2xht6e027XoRwed5urAURxaYVUYPWScheZKoeZFL9QVKgnDp+SUYBzy6iBeD5VaYqWN6Cku8Y+jAU3HCF59ltGXK97FzEMgBSWjsRfP00t2oVYh0BmKCAQR+hisI7BQyn1Ls11I8E8pyaxrnNT9O2hFZ2LR4LtOAptGC09daWFSTKfouhIq5OYEOy5T4VbVWNyowI3E+wXo1tZFS6TS2BJsXYTUbLk2ryTpQ4W6hyqvIhP7KY3NB/tddpZts8uabl3RbnnaK+Ipt/fHlO9VTN/zrH3QMf3Gbfz9XRHRtxJYXKLKnSWIdxYjuup158c9aQV73pbaWdgaf/GUz19d+fsXgF94vMvi0Q3vk1C8WmVu5IMrpxWpkCnlLL5pcLfvsvnbPcXiGvc/W7LfbvANp1nYkq1qzka54Ic+/S5vXbjA7vsbASt4nrVvTeDmHfzewZKBloyvwGOtSorAd8U5qWMYqVujAl+sw4U19O4M1XYUd/Yx+wvqUUW3PcLWWvQarEse7OhOKwpklaZbK+jHetAYhiEhYwnPZcimi+WxcoPtcw9wUKHLmRm5UlvSoY6G2Sxj0+KpS0DTdKJZ3KthHx1YJ5FGl2thD3oVghWr3jO669ELiw7JH6qVcmWq7STwmuPR62tBjF6lpXq3XmNrPajuhXqD/XaJrQUSatc07caQzp2wdJ31AdHjHa4xp/bletFJsCp3bkMcoJ8oujVotz39usXXFqyieXudze9o1t+1TN6fUdzalRTsthNjHM+Ze8yrTshR78CjvpPn7aHb05kheFrSSb7fWbY9yZaxNxLkEY30fE5/OGOqFbq5gm5qDuYbfOOFirLqeX57l5fX7nPxuUO+Xl/lhrooSR5qi2mhUdfv4mcLWVLHWnPOwaIXZ6ntJIKvJQnBNAK3eKMlaFVqjNGY/YUY9a7HLKS6dL8xWvG4xLCo3glUbAfjkbi/Try8xDtWcRnNYChU+DUaWYb6iMlbXnkkySsO2YrJM9eZZ5gfPxotgmfOoKCXII3sunKIQzBrh24sqrEU9ztJaQ7PLyZ1+FElLJpO0qC9VrhJLdussCh8SP7wRSGXF8aaHWv6kQQNbaXoJ1KVhUWoeG39MKnFPsi0oWOf5J+llPLwmY8ri0Kgi34sVdvtxNNPHGwGt3tWMLpRsPauZ/PNBdX1PdjZw+0fDEY5wBhKK04N/OVB85NyDVbbqheebzvL98/bU2qc4exLqofhOT9qO8pziNv0wHqIwRT7wU1GhzOu3n2O8d117i1Gjg/11gAAIZxJREFUtBuetxcFzeWCT23e4ccvv8P8wg1+vf4+vKnoR1tsag3f+g5+sUCvTaWqSmHwi15SeJ0P51fohQRxXKDfKSXUuH69EkqbF/1gfdigZgvh6BZa9C20GBJXGUl20FFzGUmrzovBWpJXmovLR73pZW+OATtNKdYZ1zi+p4o0OUh6tFoSElplaMRsPeeWxYUYPn4gG1A5gQrq+71Ig847mdx2DyQQOx6LVzySyjV2fYQvpJq26kXPRLe9rEQOZviuQxUF5eEYr7fpNkrsyGArxfyiEMh1FzxlC/X9oRbkcsmxlRqSXj6IDJNU1UbFVQEBYhIvudmGbt1ht3qq9RZnNQYoq5757QlrbxVsf7Nn+sYe6sZtwcq7XrRN8sKrIGnYOVS3WpB1dbyf9V07KkB4Dmc8dHt6jfNR7bgZ+rRBk+9z1pn8OCL9A8u9zJMGSTDwDrezC7v7bF/fppy9ws0fNzR1yfuLi9y4u8nzl3b44899k//pD36Ff1B/HleNaTY22br4vdRffge3t48yBsYj1GSMm46D4JEYaTVbYPYspiyE8zoqE4bbT0PCw6hArVfy4rdOjM0iFAYoC0xvwYjOhytHmC4ay1XjIT96RT9YbpjBmNqhv3yCJBDjk8MaIbjoSpWU0HQoy2QWPh0z4scxoQZC4Ms7urGcP9f6iKwK00K5bxndmEnAdBFWEkWBWp9iN6dS9xHQix5zbw99d294tjE7z0iKtb+4hV2vabZr+qmm2dD0kyjt6SkPJOhoq4FjbFqfaI0uTlYKTBfw5cTJljHVjxS2FE5yPxYZV1uRSozV9z2za57nfvQG46LDodhdjLj9nW3MoUHdU1x5z7P57UOKb1/H3ryFKqtwDhEswoeamW5IrBrG+RGc5qPek9Xtp61ezxNSHrkp/xR01Ia64P+w+qmz7XzWhJPj9jtq+3HtpKXZMdtk8Ge4pVaouobPvMKdH9lk71PQXrJQSaaI2i9Ye3mPq+sH3D2csPf6BS79vmdyo2N0/QA+uIVvGry1mEsX8eNa9BJqKUyKc8IWsC7wow1+XAahneFlcCFIpQLP2dUGM++lXFPIMkNr3PoIO6noJ0b0javAcTYDVBGX2zGoFX+Pnl8sXpvocxnuCmL4y+BV2lLkKQnQxYBns0R1q/cco3s91Z0Zdq0WhbboiQZ8tjzsKfYa9P4i8Y0pS/z6BFeXIjTUWfmZN9D10rdzSQrR21v4jSn91pjmQk2zqYfgqBk83gjJxOIG/ZiQHSiTV0px99IHug/wSitZis2Wpl0X+KNb8/DyHKU8ziuKwnJl84DSWF5eu0/nDF+6/gL91zdAQ3vBUt01VLuKas9T7XnWPmgoP9iF+7tSlDU013Yk6QFj8H0XB2XYwXKs43HaO3FSe5wV7ndJ+3X/n3/Re/9jJ+3zyfKc4cEH/DDLpdWkk4cZLHHwRhhjxWNOu/X90iD3TkPToN+9weWDOZtvbbP/cs3+KwXzF3r8ek+hHeOi40euvM/42tv8g2ufp3hrxPT9C6y/v8no5pziepBtvC+GxJSl0LkKI5oNdcgycw6aDu3MoGCGZAwmQ+l9UJwr6NZKTOdEgP2gwdUFurPU93rqOy7weiXxwY4MdhQSH4Lnql0Q+mmEX9tPZInvlBoKaudwg0dSzA+l/9RYmCjeyzJ+Sfgoznmhq+1Is3huijeKYm4xh53IbfZSUVo17bD8LgvxgOsKlJKJrO0EouitYPp1BRtT/NqIdrPCjgyuipVaVr32AOUEzQ5nlFD+ItSDQDpRlEkyDEXUqR8rmm1NuwHNJYffavGNRs8NOHB7FdVdQ2FFX+S99QneeN5UV8Eqyj3D6L6i3vEUX9VUB5bi0FLut+i9OezsiXZH1+GtEyaGMeR4cjLMuZe8ugp81HacN33aMc8N9ontk2ec8/aw3OVVaONhBuTDeBVLuLQDDG7vAPYOqPYPubBziXK2zl1V0FxV7BYTvFfoLc8Pbb3HH37tbb61dZm7L62zf6Ni4601Njcqyr0Wc9AkoRs1m8tLWBgRzIn3VwWxifhuFnqQsFSI0Y7FRI3ClhrWKtyopLlQCef3oKPY61CzBmUd2miKqhQdkMrQbVSZDGaQN7U+CBJplmhfuQMVMFnh/Cp0KXUGU+AwC/7JBUsacjkTGmDUPtaLHt10yyWWgvef1OoiC6Nph+cxqmFcY6d1SHku6KaSYbdU2qv3aRUADPobKRHHgyUECeU+4+cqKPb1I0VzQdFuQrfmcLXHVw4WhmLXUO4pTAu611Q7PsEztjaS2dhKEk2xcJQHotlR7MyhaVGNCCjRNLhM9Ej6zLFEYM2x5Ic1wie9X3G8rb5TH0eg/hlsT69xfpTgw6pHvHqMo4znajttoD1MWmtkBDiPvMkOd/ceajZnc2cb3T3H7qcKFhdH7G5XfH1Wc2c+5Ycvvs8fu/Ymh5dr3n15i9evXKPZqql3KurdKfX9nvrOHHNnT6pTNI2czwToIrwwykh0XvDTcE9RplIr1FzSx32hhQa2bWjXNMpBVYZsQuththBaX9OJ160UZl+KhfrSpKBeSov2wHhZND5pSSN/FzO7VMS0D+p33kdj6IORhNH9nup+g96bS6KOc1BXsmowRu6v0BBq9NFbWbI70SQBUKMatzah3x6zuFwFjHdIUU/a17EIbu/pxxpbkQrE5vQ83ZGyMAdlO58w534EzbZi/qKFaQjE7RXUNwvGtwSSKOYW03rKA5vw+lhIwSx69MFC4JdFg29aCeoFVbtcgQ7nlylxq2MwttXxflws5lHaWYz/ce/jeTuyPT2Ys/4Tj/+wToMrTsKnj2qrRn51+XbawF7F9pQW+lLW9KsvsfujV9l7WdNteLoNj99uQcGli/v88ee/xR+avsV/fuvH+OLbL6Nu1FQ7Gt3B9APP5HZPMe/RjZVyRHsz/KGI/KeofNuhqlICYkUBZYnbXhPNYEgC73ZUhIKy0SOO1VhsKC8lqmmxirTem4mQk3WSLDMe4aZj+otj2o2Sfqwl+WUnMCZmorQn1JLMm9M6aVxHDWPJ9BNhKO7cF2NUFlAUsD7Fr42XnoPqrNTEy56nNxo/qekuTFhcLGk2xdiiCIp1gzFOOtcBWrGVSvi67qWWXz+Rw09vWkmlrlRIc4d6X+5lfkFx+BLY1+ZMJw179yeUNyvGNxSje57y0CVIB2TFYWY95rBBHyygaQUHn80T9S2JEAXsWG4uS7UO4yr/O6VaJ0djhY2Rxugx8ZTHxYvPIYsT21kw56fHOJ81IPik23EBwrNEnI8agOHzFBiML8uKx62MEWywqtB1jbq4zeK1S9z73pp2C2wNduzpN3uml2f8kRfeRitH7wxNEMX451/7DJtfKVFSO5XywFPvO4q5JFxIBpxwdPWiEwW8eSOKaUYLNFJVIl9ZFELbiywFo/GloV+vcZVJmDFeEjpsbcAF7++gQe8cSEkurfHr0xRYdJWm3GvR9w8E710sxMD2kvzhvR+8wPFIfo/6xoCajAQ3Dn3r6wK16CTgZzIoxzoJ5m1PZGKYarqJiEG5gB/rVrQnUuILJG/fVopyJvh5FD6q7y6YPz+mGwvs0U8Uxcwz2nViwGtFN1XMrigWVy36YovWjm5RoHdLRjc141uees8Fo9xT3J2jD+f42BddhxrVaVx461IGn1yYXRYiUkMc4YFtD3DwT3m3H9eAnhvgR27PnnF+3Bn9rAP2tHach5FvWzXiRxhoAFUIPqzKAjUeoTbWsRfXWVwZM79UsLigaLeguSAvf1n1lGXPy1s7vDy9z7f2LgNQaktjCz64v0kzL/GzgmLHMLmpGN92qRCrBO9cEiUqZo5yJqpqatGjd/YlZdl7lFLCdhhVpEBbYbDrtXilEY/tvRQyXfSiTawVrjL00wI70uhWlNt00wsUYH3Ci0WzuB86pDACV2gt3jXI7zYwUowWKKMuBDceizqbK1UQlVdLSSsg9DUAW0o5JrRQ9iKHu58omdh2fJDchPLQU9+3tBsmVRp3RrxneSYeu9lTby1YnzQ4D/fvrWFu1oxvKKY3HNPrLcVOgz4U9ohfBKlQK9rgEZ5QxYAueu9TogiwXIUkDZrMGJ/FsVjd9iTaUeP8LPufN+BZZGuclanxqO2suNtJ3vZxy8bjsOoEPbTysu4doPf2md5dZ7wxod8Y0VwsmV8wLC6NaTc9B5uON3tD7zQaT130rBUNW9WcF6Y7jE1H6wpuL9Z4d2eLm3enqEODbjS6k0rgcSlfHhjKw4JyVmNaz+juRNKbOyv6w0GWVIV6dKrrMV6qbMfadlhhS9BbfCOG3JQFZlFKoovz6Hk3iDn1UmwACLxtN/weMyNDcG/gYQu27SqDrbWwKqpBjjSp5umg1VEq+qnAFNVOEAUaSSks3YkXrQLV1zSyrR8LLc5rheqhe7FgdkVhx0MgsN90sN6hjacue+qqZ/dgRH9zwvQ9zfQDMcrVnUP0vX3R6eh7UTGcz2WlopSsEIJX7NtugCvCmDgSQ04e8RGc5BPH3odgFFfjN6vtqHfp3EA/VPtkGefT2lGYcP73aQPjKI8XjvZ6VwffA7KiZwiQeD+k0UIKHLqDQzg4hA+gKAqqyxeZXFyn2xoxv1Qyu2KY7a3zzekafmzR45563HFp/ZBL4wOujfbYNHO+d3qD7oJh8WrJ7+28SGMLDtqK+/sTFvfGUDgWhwXlgaI40GgL84uaYibL/yifqTtHsbDouXi/WC9wQNuJUW47oac5C20rHndRYGYF2ujgLUdWRfYcIixRFgNOXAZ4pdB4Y3DjgnarEs3iOtRMzORL86xDs0Cw40LSp5st0TU2CzG2rggi/I0fai6GN6CbKtoN8IXgzLZWLC557MtzJtMGpTxtW3Bx0mCdYnd3QnNvTNsqJh8YrnzLMn3/AHP3AHb28YsFNvaFHqAIn/VDLs/pQcbBUbDF6hg9bVwdtf9R7cP0qj/qcz6D7dkyzk/igScY4pjI9urv6bxuMNC5oT4VAsloT3ESyJay3lrs9Zvw/g0qo6lHNdubG/TXtllcHtFsGhbbJe3mmBvTdd6vPV9aexVVW0zpqEcdf+5TX+ZCfciPbrwDwK/f/j6++car/OC//ib77Yhv37yE/844FIOVpJBYMipqVOT6EKJX4VN2ntC+BH/WbbxvUpLGko6zdSgP/bSkHwuvOGYlJuU1I56wLQVisLVaug7dIca2JIjhBynRSjxcO5J7MC2M7iiZYHpgLka93VTMnoN+zWGnDkpHtdZydWufcdEx70tu7a6hgee39umc5v6BGOP+nakUQr2vGN/2TD9oGb95E/vOe/KsQtBOhdp/3jqBiaIn7DIIJ7ZQdUeqWkeOcre8z0mrxuPgheOC2PH31bH+pAzmke8HD57n3JM+sX1yMOcnQa07SzuOgXHStpNw8LMwSB7YtuypS3aXJLfEwqDeOimDNJmgphP8+oR+a8Lep8bCShhLULGfeOzYY9ctZtrjegW7Jb70/C//yG9yqdznfj/lRrPBS6P7/LPbn+Hm/hr7d6cUt0vGtxVmLgY58pD7kRjLvFRUKieVv5MhbTlVAPcsVR7x0TXIjpEb8qReF/SXVe8pZ1Knz9YqFKmNnTRAFTERxBUwv6JYvNixdvmQFzZ32arnVLqnzQoKHnQ1r39wlf6wDAVoFXquKfcV1T4UMy8Y9I6jvtdQ3D1E7R3gD2e4+UL0STKseDVDNPXHaVWsj5r8z8IuOs5xeNj3Jf/7YQznScfIr/FRjvWMtmcvIPhRtJMG+VEvxZM+Lywb59VIfE6bgsFLMyJiRFkJw2FU4yY13faI5kLB4VWDq4R/22147EsL8ODmhUAC047tjRlGO37o0vvUuudeO+X2fI3SWL721vOUNyrqu4p610tmW0nK+NOBMQIMAklZmSu5WIb//fB5NKZRic20QUQIMbaR1hbF/W0dkjXGnn7ices9axdnzN7ewK1ZRlsLLq4fcthUFMZxeXrARrXAecU7e9scNhXzWY2dFehDQ3VfU+1BteupDoR3HCuRFLshFbztZILse1nZOJ+CeulZLMFTLD83WB5HxwX1HrUdR/P8MNtJ53gUw/xd1J69gOBH0U7yPD7MiPTSUm8FazyqbFCg6PkonK6VpBC7A9SOQVUlelQzuj2mHtesbYxxdUE/KVhcLDm8McYFoR07gn5quLNTwdjyr3rDWt1SFz2XRwdcqg8oPuW4+dwad3fWOLwzQi80buRQVmHmimonMDciwhOSOmKgLpcZjSp3kXOcuMXjQHMrwZWhWrby+IlFjyymsBjjGVUddSlp73XRUxtxzd+4VjAqLZO6wwMHhyNsp7m/O8U7cIsCsyfGeLofqId7jtG9RrjG+w1q0SQdbd91koHXSlmw5B1DKvAa9bzR5mijfNSKK//8YdpJ4+txWEyP2k46x7lBfux2lkoovwT828At7/33Z9v/d8C/h1Q8+f967//9sP3ngb8EWOCveO//4Ydx4Q/VHnawPq6BPe1aTtr3gSXugy+xd/4B6CPHrb210DhhARzOxOMDzHhMMRkznk7Y2Jwmr7rZ0HRTjas03XrB/u2KnYnDTyx3L03YGG1yZbLPZ7Zu88rGfe5emXLQVtTGopTnsK24e28Nb8UK+9ZAp9CtpjhU6E7RrTtc6cErfOlQvcJPLDiFajQ4BZsdyjhGk5at6ZxJKbjrerlgu5ozNh2NK9go5jSuZG7l56CveXdnC2cN80XJbGcMnaa6bahmCt1BsQAz95Qzz+RWI3UU9xvhXh8c4heNJH/EqifGDBKbQ8cvc9fz57O67bhJ/mlatj9N15K3p/W6PuJ2Fs/57wB/C/h7cYNS6o8DPw38oPe+UUpdCds/D/wM8AWkhuCvK6U+e+ZSVU+qrT7co2CJh315TuI0P0w7LXp+nKeV6FJDtuEDy9eYuKGzlHEyrHM+x7ctancPddNQ9j31eITa3MBtr9Ntj5hfrmjWFf1UVOlm717ksPC8s3EVP7GMNhp+6Pn3+dT6HW7ON/jcxk0+PbpF95phpDouFge8vrjGvh0x0h2/9KU/ir5d8ekffo8/dOEdtPJsFjNmtuZatcOdbp1vzy7TuILPr12n8wajHKWydN7wQbPFe7Mtrs83mPcldw6mTOuWm9e3UHMjpbx6RbWnmB4EmlwnuhTlzFPv9lT3FlIZ+2CGn82xOzuoohTholgRJGThKQM4jXf9gypuS/jwUc82m0gfhkp22jh62O+dJRYS9ztL+6iN5blhBs5Wpuo3lFKvrmz+d4H/yHvfhH1uhe0/DfxK2P6WUuoN4CeA33zsK32YIMdZB/JxA/usx3yUgMtRnx91rKOCijm1L5d7jP+HlF1PVgCg75Jx8ZFbqzTKOHzf4ayF+QJ18zal1pTOgdaSELM2xU/HzF7ZpN00tNOSflLxtdH3JknQr08/Rb/m8Os9pnKMxi3OKcZ1ywsbe7BfUt3XfPP153nrwgVGow5rdbrktjX0TYG3mn/efhZhdCiwCrTHzDUq0OFEzwLmLVza8VSHocpJ5yn3e4r9RkpPLVpJK180uP19MGZQKw4TVTK8qY+1rDqcR+lVnHgFosjpbkoHDP0Y2tvjYK/H8ZfPcrwnCcl9GLGVhw1cfhe2R8WcPwv860qpXwAWwF/13v8r4AXgt7L93gvbHr+dFng47QE/CmPjSex/lJE97vOjvOYjj+2Wt+dG2vsHg1DePnjcVA3Do7Ch1JQe8Ouuh4NDVFEwuXWXCaBGI8kW1Bo/rrBrNa4Mkp9G4cqCblKJYFAN7+uLXOgB5anvF6DW0L1ntGCg4IXK3yKx6YI8qE/BP3DBE3YiBjRr0buHokHR93J/2sjE1Elmo890OwQT7pfv+yhPOC7ulJJf85XJA8/iBI2Kk5gXxz7PI45xVh7zacc8a/uoDORp4/28pfaoxrkAtoF/Dfhx4FeVUp/imMXeUQdQSv0c8HMAIyaPeBl8OA/4SUIVp+17HAST/33cBHScV5Z/55hgVCpRROTXQlTOEztlxUBZiw+i7aqap1RjZQzlqF5KsEBrCJVZKCSjT/UykfgyQC6dHWQ+IQkgKefldxsmlqhFHYNwLmhONC12NguXmx3HGPl7NYljCWrIjHL8/UhoKxMOOmnFtMoZXm0P6zic5u1+FJ7tR90+ydf+IbdHNc7vAf+lFx7ebyulHHApbH8p2+9F4IOjDuC9/0XgF0GodI94HfFgj/X1R24fZ6DxtEnpKJx96XN3zO/Z97LECCBV/vY2GL1oJLOmlCLSM5VS2KYR41uLuI+PBjQKD4Xr83qAXmJWXV4lOu4fVdqWVNjCdmnLusar9zP05REwxCpkcVw7rk+PMsaPCn09jUbrPFD3kbYzjMQj238N/JsASqnPAhVwB/g14GeUUrVS6jXgM8BvP/TRPylLnScxUB/lGLmnlXttubccf447x1HHWPXS4z7OJi80GmbvvEAfuQG1lqgy57seFwwzSqVtkfqX/u7DTyc/YnxFh9l3fTinTZ8/IASUy7JGT/kBj/kE7Da/7ySr6Y6Gl/I+Xe3H1X2flJd71DnP23dFOwuV7peBnwQuKaXeA/4G8EvALymlvgq0wM8GL/prSqlfBb6OUOz+8iMxNR41cPK4+3zU7azXdFpQ6SwG42E8uNxAu+HxiWG0S/skCCS2aKhT0kzYL1XSDh5yyHjMIZUl8Z9wDG85wnh6oij/sV7qcX12kqHO7jUZxeMgh9P2eZjxdla46uMOoD2p837c9/EJad9dGYKPS4c7ip4EH80gOyngtLrfSddzlAF+lGuJgbijIJF816IINLVTrinnbefG2J0wtz/g3eoHDexxBvMsE9pR51uFk5Zgk2OezZMaJ59kB+NJfe8Zac9WhuCHFZF+HMz4oxpcJ00KpwUUV9tJnuDDtqPoYyvX8yAMcVwQczUr0kt4+TRoZul8Rx3jOMz9FEw+fnZU3z5s351lsjzL9qfRmD3JOMp5W2qfHOP8LLdH4cI+yhL6SXlwpxmpk5b6sOwl5/usep9nSXHODfSj4verVLfj2ln7+dzwnLcn0B41IPjRt096IOU0ZsVJhu6o/R/23h6nL8763TNTx04R+1mdrM6y70kBu+OCpkde2zI2fuK1HfW9h20nBQ6Pu6fz9l3Rnl3P+UkGL47y7E7a/6jzH7WMPuuy9ShjfFqg6iye9Vlx17N4yEdd50k47FHX8SiwwcNOVGeBtrznSKrdcd//sNq5B/5d3T45nvNp7VG8i7N85zQ89zhPLX52nOdzGua5iivnxz4qCPioRj//Oe5aH9X4HRd4PKrPlD7beU7qy3yf0/Y77Vke1c8Ps7o5yaM/94TP2xnas+M5Pyre+HGcF07GSc/KqHgcrDV+f/X4DxM0PctkddLnS9i0e/Dz1YDfSSuXowz0w7SjjOdZA3kn9dnD9OeH3b7LGRKftPbJ95wf1wt5kl7MaR5s3HYWpsBx3z/p86fBI1v1xs9quI7yUh+WiXJcO+tq4GHhlGexPQ1j6LwBz4JxfpTg2IfRTsKaTzPSRx3nUZkVH0ZfPKlj5vDJafs8TDstyLf62er+T2oSiMf6MMfj4xz7LE7BszrpfALbJ984x/aoL8Xjvoj5cU7DPh8Vu1393kmMgeOu4bhl+yp8chzj4SznP2s7DQ6J13DWZ3NWTzwe+zjI4bRVz1HtpJjDSfs97HEf9rpOaucG+BPRng3jfNIS+iztrMbvqPOe9N3VazrL9Z0lEPWwy++jruM4Q3SWfjzKA3sY47MaLFs970nXcFIA9bTAXH7tRz2X1QnxYQPGJ333rFDWccd9GlaH5+0jbc+GcX4SntxRgaiH+e7HEY1/Ekvcx2mPCwU8zIR6mrE8DT46y3lOmlhPY9Wc5VriZ4/SPixv96yT0Pnk8JG3Z8M4w5Nfap/kuZ00oD+qJeNZcNaPuz3JPnrc1dFqe9iA4LMKBZy1T5/V+3+K27NjnD+qwNnDBPdOO/+TmlA+7CDUo7azYK/5tX/UzJunsc8epT3KfT/KvT8r/fUJac+GcX6U4M3jeAInLXkfBg7JIZHj8NLjPlvFZz8Oz+ZR7/u47592D6fhyg/bB2eBLU47/1mu+XHaWQzpSbj341IGj/veuaH+0NtTIRmqlLoNHCKC/d9t7RLffff93XjPcH7f323tpPt+xXt/+aQvPxXGGUAp9Tun6Zs+i+278b6/G+8Zzu/7476Oj7o97n0/G7DGeTtv5+28PWPt3Dift/N23s7bU9ieJuP8ix/3BXxM7bvxvr8b7xnO7/u7rT3WfT81mPN5O2/n7bydt6E9TZ7zeTtv5+28nbfQPnbjrJT600qp15VSbyil/trHfT0fZlNKva2U+opS6veUUr8Ttl1QSv1jpdS3wv/bH/d1Pm5TSv2SUuqWUuqr2bZj71Mp9fPh+b+ulPpTH89VP3475r7/Q6XU++GZ/55S6s9kn33i71sp9ZJS6p8qpf5AKfU1pdT/Pmx/pp/3Cff95J639/5j+wEM8G3gU0AF/D7w+Y/zmj7k+30buLSy7f8M/LXw+18D/uOP+zqfwH3+G8CPAl897T6Bz4fnXgOvhfFgPu57eIL3/R8Cf/WIfZ+J+wauAT8afl8Hvhnu7Zl+3ifc9xN73h+35/wTwBve+ze99y3wK8BPf8zX9FG3nwb+bvj97wJ/7uO7lCfTvPe/Adxb2Xzcff408Cve+8Z7/xbwBjIuPnHtmPs+rj0T9+29v+69/93w+z7wB8ALPOPP+4T7Pq499H1/3Mb5BeDd7O/3OPkGP+nNA/9IKfVFpdTPhW1XvffXQR44cOVju7oPtx13n98NY+DfU0p9OcAecXn/zN23UupV4EeAf8l30fNeuW94Qs/74zbORyXoP8v0kT/mvf9R4N8C/rJS6t/4uC/oKWjP+hj4fwCfBn4YuA78X8L2Z+q+lVJrwH8B/B+893sn7XrEtmfpvp/Y8/64jfN7wEvZ3y8CH3xM1/KhN+/9B+H/W8B/hSxrbiqlrgGE/299fFf4obbj7vOZHgPe+5vee+u9d8D/k2Ep+8zct1KqRAzUf+q9/y/D5mf+eR9130/yeX/cxvlfAZ9RSr2mlKqAnwF+7WO+pg+lKaWmSqn1+DvwJ4GvIvf7s2G3nwX+/sdzhR96O+4+fw34GaVUrZR6DfgM8Nsfw/V9KC0aqND+58gzh2fkvpVSCvjbwB947/9m9tEz/byPu+8n+ryfgqjnn0Eind8G/vrHfT0f4n1+ConW/j7wtXivwEXgnwDfCv9f+Liv9Qnc6y8jS7oO8Rj+0kn3Cfz18PxfB/6tj/v6n/B9/7+BrwBfDi/otWfpvoH/EbI8/zLwe+Hnzzzrz/uE+35iz/s8Q/C8nbfzdt6ewvZxwxrn7bydt/N23o5o58b5vJ2383bensJ2bpzP23k7b+ftKWznxvm8nbfzdt6ewnZunM/beTtv5+0pbOfG+bydt/N23p7Cdm6cz9t5O2/n7Sls58b5vJ2383bensL2/wd0F+lpRr/ThAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(t1_xy_slice_z150);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "**Exercise**\n",
    "* Get the path to one of the two resting state fMRI (bold) volumes (tip: with BIDS nomenclature, it has a `bold` suffix)\n",
    "* Keeping in mind that such a volume is 4D (it is a series of 3D volumes through time), plot:\n",
    "    * The 17th (axial) slice of the 10th volume in time\n",
    "    * The time variation of one voxel within that slice through all measured time points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:shared-ni38]",
   "language": "python",
   "name": "conda-env-shared-ni38-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}