Untitled5.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import argparse\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Rectangle\n",
    "from matplotlib.backends.backend_pdf import PdfPages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "gene = \"EBF2\"\n",
    "filename = \"/home/annaldas/projects/result/%s/%s_transcripts_filtered_analysis.txt\" %(gene,gene)\n",
    "file = open(filename, \"r\")\n",
    "lines = file.readlines()\n",
    "file.close()\n",
    "\n",
    "class transcript:\n",
    "    def __init__(self, tcons, length, idr, ips, ss8, pss):\n",
    "        self.tcons = tcons\n",
    "        self.length = length\n",
    "        self.idr = idr\n",
    "        self.ips = ips\n",
    "        self.ss8 = ss8\n",
    "        self.pss = pss\n",
    "\n",
    "transcripts = dict()\n",
    "\n",
    "count = False\n",
    "idr_lines = []\n",
    "ips_lines = []\n",
    "ss8_lines = []\n",
    "pss_lines = dict()\n",
    "\n",
    "for line in lines:\n",
    "    if (line.startswith(\">\")):\n",
    "        if (count):\n",
    "            if ((tcons not in transcripts) or ((len(idr_lines) - 1) > transcripts[tcons].length)):\n",
    "                transcripts[tcons] = transcript(tcons, len(idr_lines) - 1, idr_lines, ips_lines, ss8_lines, pss_lines)\n",
    "        count = True\n",
    "        new = True\n",
    "        idr_lines = []\n",
    "        ips_lines = []\n",
    "        ss8_lines = []\n",
    "        pss_lines = dict()\n",
    "        idr = False\n",
    "        ips = False\n",
    "        ss8 = False\n",
    "        pss = False\n",
    "        tcons = line[1:].strip().split(\"|\")[0]      \n",
    "    elif (line.startswith(\"#####IUPred2A Analysis\")):\n",
    "        idr = True\n",
    "    elif (line.startswith(\"#####InterProScan\")):\n",
    "        ips = True\n",
    "        idr = False\n",
    "    elif (line.startswith(\"#####BrewerySS8 Analysis\")):\n",
    "        ss8 = True\n",
    "        ips = False\n",
    "    elif (line.startswith(\"#####PrositeScan Analysis\")):\n",
    "        pss = True\n",
    "        ss8 = False\n",
    "    elif (idr):\n",
    "        idr_lines.append(line.strip().split(\"\\t\"))\n",
    "    elif (ips):\n",
    "        ips_lines.append(line.strip().split(\"\\t\"))\n",
    "    elif (ss8):\n",
    "        ss8_lines.append(line.strip().split(\"\\t\"))\n",
    "    elif (pss):\n",
    "        if (line.startswith(\"#\")):\n",
    "            pss_id = line.strip().split(\" \")[3]\n",
    "            pss_lines[pss_id] = []\n",
    "        else:\n",
    "            pss_lines[pss_id].append(line.strip().replace(\"  \",\" \").split(\" \"))\n",
    "            \n",
    "if ((tcons not in transcripts) or ((len(idr_lines) - 1) > transcripts[tcons].length)):       \n",
    "    transcripts[tcons] = transcript(tcons, len(idr_lines) - 1, idr_lines, ips_lines, ss8_lines, pss_lines)\n",
    "\n",
    "longest_length = 0\n",
    "longest_tcon = \"\"\n",
    "for ids in transcripts:\n",
    "    if (transcripts[ids].length > longest_length):\n",
    "        longest_length = transcripts[ids].length\n",
    "        longest_tcon = ids"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for site_type in transcripts[longest_tcon].pss:\n",
    "    for i in transcripts[longest_tcon].pss[site_type]:\n",
    "        print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for transcript in transcripts:\n",
    "    print(transcripts[transcript].length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(transcripts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "colors=['#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4', '#46f0f0',\n",
    "        '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff', '#9a6324', '#fffac8', \n",
    "        '#800000', '#aaffc3', '#808000', '#ffd8b1', '#000075', '#808080', '#ffffff']\n",
    "#colors = [\"#e6194b\",\"#3cb44b\",\"#ffe119\"]\n",
    "ss3_abbvs = [\"H\",\"E\",\"C\"]\n",
    "#red, green, yellow\n",
    "#helix, strand/sheets, the rest\n",
    "\n",
    "count = -1\n",
    "for ids in transcripts:\n",
    "    fig, ax = plt.subplots(figsize=(18, 10))\n",
    "    ax = plt.gca()\n",
    "    ax.cla()\n",
    "    ax.set_xlim((-50.0, longest_length))\n",
    "    ax.set_ylim((-1.0, 1.75))\n",
    "    \n",
    "    tcons_curr = transcripts[ids]\n",
    "    \n",
    "\n",
    "    for i in transcripts[ids].ips:\n",
    "        start = int(i[3])\n",
    "        stop = int(i[4])\n",
    "        \n",
    "        if (i[1] == \"Pfam\"):\n",
    "            name = i[8].split(\";\")[3].split(\"=\")[-1]\n",
    "            plt.gca().add_patch(Rectangle((start,1.05),stop-start,0.2,edgecolor=\"#3cb44b\",facecolor='#3cb44b'))\n",
    "            ax.annotate(name,(start + (stop-start)/2.0,1.15), fontsize = 14, color = \"#e6194b\", ha = \"center\", va = \"center\")\n",
    "        \n",
    "    \n",
    "    ss8_df = pd.DataFrame(transcripts[ids].ss8[1:], columns = transcripts[ids].ss8[0])\n",
    "    ss = list(ss8_df[\"SS\"])\n",
    "    for i in range(tcons_curr.length):\n",
    "        #plt.plot([i,i+1],[count,count],linewidth=1)\n",
    "        plt.gca().add_patch(Rectangle((i,-0.4),1,0.35,edgecolor=colors[ss3_abbvs.index(ss[i])],facecolor=colors[ss3_abbvs.index(ss[i])]))\n",
    "    \n",
    "    plt.plot((0,longest_length),(1,1),color = \"black\")\n",
    "    plt.plot((0,longest_length),(0,0),color = \"black\")\n",
    "    plt.plot((-1,-1),(1.5,-0.5),color = \"black\")\n",
    "    \n",
    "    \n",
    "    idr_df = pd.DataFrame(transcripts[ids].idr[1:], columns = transcripts[ids].idr[0])\n",
    "    idr_df = idr_df.astype({'# POS': 'int32',\"IUPRED2\":\"float\"})\n",
    "    plt.plot(idr_df[\"# POS\"],idr_df[\"IUPRED2\"])\n",
    "    \n",
    "    buffer = 0\n",
    "    for site_type in transcripts[ids].pss:\n",
    "        for i in transcripts[ids].pss[site_type]:\n",
    "            start = int(i[0])\n",
    "            stop = int(i[2])\n",
    "            plt.gca().add_patch(Rectangle((start,1.3+buffer),stop-start,0.025,edgecolor=\"black\",facecolor='black'))\n",
    "        ax.annotate(site_type,(-50,1.3 + buffer), fontsize = 10, color = \"#e6194b\", ha = \"center\", va = \"center\")\n",
    "\n",
    "            #plt.gca().add_artist(plt.Circle((start + (stop - start)/2,1.35),0.25,color=\"black\"))\n",
    "        buffer += 0.05\n",
    "        \n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    #ax.spines['left'].set_visible(False)\n",
    "    #plt.yticks([])\n",
    "    \n",
    "        \n",
    "    #plt.show()\n",
    "    #fig.savefig(ids + '_plotcircles.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors=['#e6194b', '#3cb44b', '#ffe119', '#4363d8', '#f58231', '#911eb4', '#46f0f0',\n",
    "        '#f032e6', '#bcf60c', '#fabebe', '#008080', '#e6beff', '#9a6324', '#fffac8', \n",
    "        '#800000', '#aaffc3', '#808000', '#ffd8b1', '#000075', '#808080', '#ffffff']\n",
    "ss3_abbvs = [\"H\",\"E\",\"C\"]\n",
    "aa_abbvs = [\"A\",\"C\",\"D\",\"E\",\"F\",\"G\",\"H\",\"I\",\"K\",\"L\",\"M\",\"N\",\"P\",\"Q\",\"R\",\"S\",\"T\",\"V\",\"W\",\"Y\"]\n",
    "\n",
    "def preprocessArguments(args):\n",
    "    if args.geneNames != '':\n",
    "        gene_id='gene_name'\n",
    "        with open(args.geneNames,'r') as f:\n",
    "            targets=[i.strip() for i in f]\n",
    "    elif args.geneIDs != '':\n",
    "        gene_id='gene_id'\n",
    "        with open(args.geneIDs,'r') as f:\n",
    "            targets=[i.strip() for i in f]\n",
    "    annotation=pd.read_csv(args.gtf, delimiter='\\t', header=None, usecols=[0,2,3,4,6,8],\n",
    "                           names=['chrm','type','start','stop','strand','more'])\n",
    "    annotation['transcript_id']=annotation.apply(lambda x:\n",
    "        x['more'].split('transcript_id \"')[1].split('\"')[0],1)\n",
    "    annotation=annotation.drop(columns='more')\n",
    "    data=pd.read_csv(args.csv)\n",
    "    samples=data.columns[~(data.columns.str.startswith('feature')|data.columns.str.startswith('gene')|data.columns.str.startswith('transcript'))]\n",
    "    #conditions=list(set([x.split('_')[0] for x in samples]))\n",
    "    #conditions = [\"0\",\"3\",\"5\"]\n",
    "    conditions = [\"day0\",\"day3\",\"day5\"]\n",
    "    conditions.sort()\n",
    "    number_replicates={}\n",
    "    numerical=True\n",
    "    for cond in conditions:\n",
    "        number_replicates[cond]=samples.str.startswith(cond).sum()\n",
    "        try:\n",
    "            float(cond)\n",
    "        except:\n",
    "            numerical=False\n",
    "    x=np.arange(len(conditions))\n",
    "    if numerical:\n",
    "        x=[float(cond) for cond in conditions]\n",
    "    return gene_id, targets, annotation, data, samples, conditions, number_replicates, x  \n",
    "\n",
    "def calculateStatistics(df,conds,nreps):\n",
    "    for cond in conds: \n",
    "        df['mean'+cond]=df.filter(like=cond+'_').mean(1)\n",
    "        df['stdn'+cond]=df.filter(like=cond+'_').std(1)/np.sqrt(nreps[cond])\n",
    "    df=df.sort_index()\n",
    "    return df\n",
    "\n",
    "def chooseIsoforms2Plot(df,minTPM,minPct,maxIso,annotation):\n",
    "    df['minimum']=df.filter(regex='^mean').min(axis=1)\n",
    "    df=df[df['minimum']>minTPM]\n",
    "    df['maximumPct']=df.filter(regex='^Pct').min(axis=1)\n",
    "    df=df[df['maximumPct']>minPct]\n",
    "    df['maximum']=df.filter(regex='^mean').max(axis=1)\n",
    "    df=df.sort_values('maximum',ascending=False)\n",
    "    df=df.head(maxIso)\n",
    "    return df\n",
    "\n",
    "def plotProfiles(x, df, df_gene, ax, colors, total=True):\n",
    "    if total:\n",
    "        plt.errorbar(x,df_gene.filter(like='mean').iloc[0],yerr=df_gene.filter(like='stdn').iloc[0],color='black',linewidth=2, label = \"Total Expression\")\n",
    "    for j in range(df.shape[0]):\n",
    "        row=df.iloc[j]\n",
    "        plt.errorbar(x+np.random.normal(0, 0.03, len(x)),row.filter(regex='^mean'),yerr=row.filter(like='stdn'),color=colors[j],linewidth=2, label = \"\")\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.spines['left'].set_bounds(0,ax.get_yticks()[-2])\n",
    "    ax.spines['bottom'].set_bounds(min(x),max(x))\n",
    "    plt.xlabel(\"Day\")\n",
    "    plt.ylabel(\"Normalized DeSeq2 TPM\")\n",
    "    plt.legend(loc = \"upper center\", bbox_to_anchor=(0.5,1), frameon=False)\n",
    "    \n",
    "def plotStacked(x,df,ax,colors):\n",
    "    plt.stackplot(x,df.filter(regex='^Pct').values,colors=colors[:df.shape[0]])\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.spines['left'].set_bounds(0,100)\n",
    "    ax.spines['bottom'].set_bounds(min(x),max(x))\n",
    "    ax.axis([min(x),max(x),0,100])\n",
    "    plt.xlabel(\"Day\")\n",
    "    plt.ylabel(\"TPM Percentage (out of 100%)\")\n",
    "    \n",
    "def prepareAnnotation(annotation,df):\n",
    "    cut=annotation[annotation['transcript_id'].isin(df['transcript_id'].values)]\n",
    "    strand=cut.iloc[0]['strand']\n",
    "    if strand=='+':\n",
    "        start=cut['start'].min()\n",
    "        cut['plot_start']=cut['start']-start\n",
    "        cut['plot_stop']=cut['stop']-start\n",
    "    else:\n",
    "        start=cut['stop'].max()\n",
    "        cut['plot_start']=(cut['start']-start)*(-1)\n",
    "        cut['plot_stop']=(cut['stop']-start)*(-1) \n",
    "    return cut\n",
    "\n",
    "def plotAnnotation(annotation, df, plt, colors, length): \n",
    "    transcripts_ids = []\n",
    "    transcripts_pos = []\n",
    "    chrm = \"\"\n",
    "    longest = annotation.loc[annotation['plot_stop'].idxmax()][\"plot_stop\"]\n",
    "    count = 3\n",
    "    panels = df_temp.shape[0] + 1\n",
    "    for j in range(df.shape[0]):\n",
    "        ax=plt.subplot(panels,2,(count,count+1)) \n",
    "        ax.set_xlim((-50, length))\n",
    "        ax.set_ylim((-0.85, 1.85))\n",
    "    \n",
    "        transcript_annotation=annotation[annotation['transcript_id']==df.iloc[j][\"transcript_id\"]] \n",
    "        transcripts_ids.append(df.iloc[j][\"transcript_id\"])\n",
    "        transcripts_pos.append(df.shape[0]-j) \n",
    "        if (transcript_annotation.shape[0] > 2): \n",
    "            for idx,row in transcript_annotation.iterrows(): \n",
    "                chrm = row[\"chrm\"] \n",
    "                if row['type']=='transcript': \n",
    "                    plt.plot([row['plot_start']*length/longest,row['plot_stop']*length/longest],[1.75,1.75],color=colors[j],linewidth=2) \n",
    "                else:\n",
    "                    plt.plot([row['plot_start']*length/longest,row['plot_stop']*length/longest],[1.75,1.75],color=colors[j],linewidth=10) \n",
    "            ax.spines['top'].set_visible(False)\n",
    "            ax.spines['right'].set_visible(False)\n",
    "            ax.spines['left'].set_visible(False)\n",
    "            ax.spines['bottom'].set_bounds(0,ax.get_xticks()[-2]) \n",
    "            #plt.yticks(transcripts_pos,transcripts_ids)\n",
    "            #plt.xlabel(chrm)\n",
    "        count += 2\n",
    "        \n",
    "def plotCodingPotential(plt, panels, df_temp):\n",
    "    count = 3\n",
    "    for ids in list(df_temp[\"transcript_id\"]):\n",
    "        ax = plt.subplot(panels,2,(count,count+1)) \n",
    "        flip = True\n",
    "        tcons_curr = transcripts[ids]\n",
    "        # Pfam domain\n",
    "        for i in tcons_curr.ips:\n",
    "            \n",
    "            start = int(i[3])\n",
    "            stop = int(i[4])\n",
    "            \n",
    "            if (i[1] == \"Pfam\"):\n",
    "                name = i[8].split(\";\")[3].split(\"=\")[-1]\n",
    "                plt.gca().add_patch(Rectangle((start,1.05),stop-start,0.2,edgecolor=\"#3cb44b\",facecolor='#3cb44b'))\n",
    "                if (flip):\n",
    "                    ax.annotate(name,(start + (stop-start)/2.0,1.2), fontsize = 14, color = \"#e6194b\", ha = \"center\", va = \"center\")\n",
    "                else:\n",
    "                    ax.annotate(name,(start + (stop-start)/2.0,1.1), fontsize = 14, color = \"#e6194b\", ha = \"center\", va = \"center\")\n",
    "                flip = not flip\n",
    "                \n",
    "        ax.annotate(\"Pfam Domain\",(-50,1.15), fontsize = 12, color = \"#3cb44b\", ha = \"center\", va = \"center\")\n",
    "\n",
    "        # Secondary structure prediction\n",
    "        ss8_df = pd.DataFrame(tcons_curr.ss8[1:], columns = tcons_curr.ss8[0])\n",
    "        ss = list(ss8_df[\"SS\"])\n",
    "        for i in range(tcons_curr.length):\n",
    "            plt.gca().add_patch(Rectangle((i,-0.4),1,0.35,edgecolor=colors[ss3_abbvs.index(ss[i])],facecolor=colors[ss3_abbvs.index(ss[i])]))\n",
    "\n",
    "        plt.plot((0,longest_length),(1,1),color = \"black\")\n",
    "        plt.plot((0,longest_length),(0,0),color = \"black\")\n",
    "        plt.plot((-1,-1),(1.5,-0.9),color = \"black\")\n",
    "        ax.annotate(\"SS Prediction\",(-50,-0.2), fontsize = 12, color = \"#3cb44b\", ha = \"center\", va = \"center\")\n",
    "        \n",
    "         # Amino acid sequence\n",
    "        aa = list(ss8_df[\"AA\"])\n",
    "        for i in range(tcons_curr.length):\n",
    "            plt.gca().add_patch(Rectangle((i,-0.8),1,0.35,edgecolor=colors[aa_abbvs.index(aa[i])],facecolor=colors[aa_abbvs.index(aa[i])]))\n",
    "        ax.annotate(\"AA Sequence\",(-50,-0.6), fontsize = 12, color = \"#3cb44b\", ha = \"center\", va = \"center\")\n",
    "        \n",
    "        #plt.plot((0,longest_length),(1,1),color = \"black\")\n",
    "        #plt.plot((0,longest_length),(0,0),color = \"black\")\n",
    "        #plt.plot((-1,-1),(1.5,-0.5),color = \"black\")\n",
    "\n",
    "        # IDR prediction\n",
    "        idr_df = pd.DataFrame(tcons_curr.idr[1:], columns = tcons_curr.idr[0])\n",
    "        idr_df = idr_df.astype({'# POS': 'int32',\"IUPRED2\":\"float\"})\n",
    "        plt.plot(idr_df[\"# POS\"],idr_df[\"IUPRED2\"])\n",
    "        ax.annotate(\"IDR Prediction\",(-50,0.5), fontsize = 12, color = \"#3cb44b\", ha = \"center\", va = \"center\")\n",
    "\n",
    "        # Phosphorlyation Site\n",
    "        buffer = 0\n",
    "        for site_type in tcons_curr.pss:\n",
    "            for i in tcons_curr.pss[site_type]:\n",
    "                start = int(i[0])\n",
    "                stop = int(i[2])\n",
    "                plt.gca().add_patch(Rectangle((start,1.3+buffer),stop-start,0.025,edgecolor=\"black\",facecolor='black'))\n",
    "            ax.annotate(site_type,(-50,1.3 + buffer), fontsize = 9, color = \"#e6194b\", ha = \"center\", va = \"center\")\n",
    "\n",
    "                #plt.gca().add_artist(plt.Circle((start + (stop - start)/2,1.35),0.25,color=\"black\"))\n",
    "            buffer += 0.075\n",
    "\n",
    "        ax.spines['top'].set_visible(False)\n",
    "        ax.spines['right'].set_visible(False)\n",
    "        ax.set_yticks([], [])\n",
    "\n",
    "        ax.title.set_text(tcons_curr.tcons) \n",
    "        \n",
    "        count += 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Parser(object):\n",
    "    def __init__(self, csv, gtf, geneIDs, geneNames, outDir, minTPM, maxIso, minPct):\n",
    "        self.csv = csv\n",
    "        self.gtf = gtf\n",
    "        self.geneIDs = geneIDs\n",
    "        self.geneNames = geneNames\n",
    "        self.outDir = outDir\n",
    "        self.minTPM = minTPM\n",
    "        self.maxIso = maxIso\n",
    "        self.minPct = minPct\n",
    "\n",
    "args = Parser('/project/owlmayerTemporary/Sid/nanopore-analysis/Results_5_1/Quantification/all_counts_deseq2norm.txt',\n",
    "              '/project/owlmayerTemporary/Sid/nanopore-analysis/Results_5_1/GffCompare/nanopore.combined.gtf',\n",
    "              '', '/home/annaldas/projects/isoform_differentiation/test/list.txt',\n",
    "              '/home/annaldas/projects/isoform_differentiation/test/',0,18,0)\n",
    "\n",
    "outdir=args.outDir\n",
    "minimumTPM = args.minTPM\n",
    "minimumPct = args.minPct\n",
    "maximumIso = args.maxIso\n",
    "(identifier, targets, annotation, data, samples, conditions, number_replicates, x) = preprocessArguments(args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/pkg/python-3.7.4-0/lib/python3.7/site-packages/ipykernel_launcher.py:50: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/pkg/python-3.7.4-0/lib/python3.7/site-packages/ipykernel_launcher.py:90: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/pkg/python-3.7.4-0/lib/python3.7/site-packages/ipykernel_launcher.py:91: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/pkg/python-3.7.4-0/lib/python3.7/site-packages/ipykernel_launcher.py:127: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n"
     ]
    },
    {
     "data": {
      "image/png": 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YnB3mgnAKw4J15KUcIkwZgYYSjAbvCu7u4t5mtulCpDkthB3ZHVq+iHQdCi5EpEWTJ0/m85//PBdffDEA99xzz0nTI8aOHct1113HV7/6Va6//nrGjh3L5MmTGTFixGn7br7GxXXXXcf8+fN55plneOuttwiFQkyZMoV///d/5+tf/zrZ2dls3LiRb37zm+Tl5bUaIDzxxBPcc889/OhHP6K+vp4rr7ySJ554gqVLl7Jx40Z8Ph/jxo1j+vTprFq1iu9973ukpKQQDodZuXIljz766Gnvf+fOnWf9byoiIh1jf91xXqk4wCsVTVv7kunPY1J2mPHhFIZnRMhPOUwv20tKQzFGnVfl9lxnvM1sSrOpKjnNfrYwrUXbzIp0S9oOVaQLSqapIh2to7ZPbUlP+ncVidFKfJ2kJ2yH2pWkmo8Ls6M7nYzKaGBQajU5vgrS3G7M1Z6+A0lSLWwze8rCpNpmViTJaDtUke5KX6xFRETOXp1r4M3KSt48KRMPYYzmgnCIi7IyOC/TMTithlzfATJcMeaqvCpX2i1R28y2MKqjMQAJdewtiEiLNOJCRCRGIy6kB9KIi06iERdd37kZGVycncmYTOOc4FH6+Q+SSQm+hn1elyadqoVtZlvcblbbzIq0k0ZciIiIiIgkwoc1NXxYU9OkxQ8MIS9tBBf3CnN+yM+5wWMMCFQSZg++hjJMfz/rhhK1zWxrC5Jqm1mRlmjEhYhIjEZcSA+kPwN2Eo246Hl6B1KY1CvMuHAKw9KPkxc4RLad2Okk4nV5kswsu5VRHX3B36/J0V9TV6Q7aNdnEQUXIiIxCi6kB1Jw0UkUXMgJ6X4fE7OymJCVxvD0CPmph+ltFaQ27MY45nV50tVYRrMgo1mw4e8ba++jKSuSrBRcxHT7GxSRxFBwIT2QPsV2EgUXcjopZowLh7kwO8ioDMeg1Gr6+PYRdLsxV+11edLlBWIhRt9YuNH/1NEbJx5bqtfFSs+iNS5ERERERLqC487xx0OH+OOhQ01aM4BRjA6FuCgrnTGZMCR4lFzffjJcMT7X8VuFS3dR/7e1OU7H1zsaYPj6Ngk0mozeOBFw+LI6vmyRGAUXIiIiIiJJ7P0jR3j/yJEmLanAuQxJT+fi7EzOD/koSDtG/8BBMinF37DXq1KlOzixpSzb277O0puEGC2M3GicvtIHzNcppUv3pakiIiIxmioiPZCminQSTRWRztQ3NZWLe4UZGwpwbrCOASlVZFGGv6EUo8Hr8qTH8YM/t8kUlTZGclia18VK59MaFzHd/gZFJDEUXEgPpOCikyi4kGQQ9ge4uFcW48IpDE8/zsCUw2RbOSkNJVj79vYU6ViW3WzkRvOQ48QIj2yvK5XEUXAR0+1vUEQSQ8GF9EAKLjqJggtJZqlmTMzOYkJWkBEZDQyK7XSS5nZj7qjX5YmcyoJNtodtY6FRXy6Y3+tqpW0KLmK6/Q2KSGIouJAeSMFFJ1FwIV2RH+P8cIiLstM5LwOGpEV3Okl3xZg77HV5Iu3gj66x0db0lMZpKkGvi+2ptKuIiIiIiIicnQiOrYcPs/Vw05AiHRjB8IxMJmVnMCbTOCd4lL7+/WRSiq9hv1flirQgAg17o8fxP7d9qWW1PnKjcaHRvuDv3Tmly0kUXIiIiIiIyBnZWVPNzprqJi0pwDkMTBvF5F4hzg/5GRo8Rv9AJWFK8TeUeVWqSPu4Q1B/COp3nubCtCYjNvq2EnDE1ufQNJWEUXAhIgJs3bq18fGnPvUpCgoKKCgoYOjQoY2PhwwZQjCoYYQiIiKtKT12lDXlR1lT3rR1IL0DBUzuHWZsyM+w9HryAlVkWTmBhhKMiFflipyFYxApjh5t8oEvp/XpKb4mz30ZnVJ5V6Y1LkSkx/v973/PzJkzqaysPO21eXl5jUFG80PBhnRBWuOik2iNC5GWZfr9TMzOYnw4lREZ9QxMOUIvKye1oRijzuvyRDqHhVsfveHvFxvB0Q/8OV5X2hG0OGdMt79BETl7RUVFzJ49m5qamsa23/72t3z88cd8/PHHfPTRR42PP/nkEyKRtv8qNHDgwDaDjbQ07U8uSUXBRSdRcCFyZlLMGJ8d5sJwOqMyIgxKrSHHV0HQ7cZczek7EOmWUsGf2/JCo76mz/uBdZnJFQouYrr9DYrI2fnFL37BTTfdRF1dHQsWLGDlypVA67uK1NfXU1pa2hhkND/ONtg4MR1l8ODBCjaksym46CQKLkQSw4Ax4RAXZaUzOhOGpNWS69tPuivB504/clKkZ7DYNJVmU1R8zRce7Z8M01QUXMR0+xsUkTP37LPP8sUvfpFIJMLChQtZtmwZfn90AaWz/b1YX19PSUlJq8HG7t272ww2zOy0IzZSU1PPqjaRVii46CQKLkQ63tCMDCZlZTImZBQEj9LPf5BMSvE3VHhdmkjyssyTR2q0FnL4csA65GODgouYbn+DInJmvv/973PvvfcCUFhYyOLFizEzLPbLuKN+L7YUbDSdirJ7924aGhpaff2JYKPpgqFNj8GDByvYkDOl4KKTKLgQ8U7/1DQm9wpxQSjA0OAxBqRUEWYP/oY9mL4qiLRTSpNpKi1NT2myPoelnEnHCi5iuv0Nikj7OOd4+OGH+cY3vgHA0qVL+ed//ufG8x0dXJzO8ePHTzti43TBRn5+fptTUVJSzuj/SKT7U3DRSRRciCSf7ECASb2yGBdKYXh6PXkpVfSyvQQaijHqvS5PpIsy8PVqY3pK021jQ7EXtKNXBRci0hM453jggQd49NFHMTOWL1/Ol7/85ZOu8Tq4OJ0TwUbTURpNj+Li4jaDDZ/P12Kw0XTEhoKNHkfBRSdRcCHSdaSZj4m9spgQTmVERgODUg/T2ypIbdiNcczr8kS6D8uAwTsVXMR0+xsUkbZFIhHuuusunn76aVJSUli1ahU33njjKdcle3BxOsePH6e4uPiUQONE0FFSUtLuYKOl6SiDBg1SsNH9KLjoJAouRLo+P8a4rBAXZqUzKtMxJLbTSbrbjblqr8sT6ZqGlCq4iOn2Nygiraurq2P+/Pm88MILpKen8+KLLzJjxowWr+3qwcXp1NXVtRhsNB2x0da9+3w+Bg0a1OpUlEGDBhEIdJmttyRKwUUnUXAh0r2NysxkYnYGozONc9Jq6es/QIYrxucOel2aSHJTcNGo29+giLSspqaGG264gfXr15OVlcXatWu5/PLLW72+uwcXp3Mi2GhtKkpJSUmb/zZ+v7/FYKPpiA0FG+3XSf99VHDRSRRciPRMg9ODXJwd4vyQj4K0Y/QPVBKiFH9DudeliSQHBReNuv0NisipqqqqmDVrFps2bSI3N5dXX32Viy66qM3X9PTg4nTq6urYvXt3q1NRSktL2x1stDQVJT8/X8FGEwouuhcFFyLSVN/UVCb1CnNBKMCwYB15KYfIYg/+hlKM1qd1inQ7XSG4MLMVwCxgr3PuglhbDvBToAD4GLjROXfQop/glgEzgRrgNufcO+14G30DEelhKioquOaaa9iyZQv5+fkUFRVx3nnnnfZ1Ci7ic+zYsRaDjRNHe4KNwYMHtzhaY+jQoQwcOLBHBRsKLroXBRci0h6Z/gAXZ4cYn5XG8PR6BqYcppftJaWhGKPO6/JEEq+LBBdXAEeAZ5sEF98FDjjnvmNmDwG9nXNfM7OZwCKiwcUlwDLn3CXteBt9AxHpQYqLi5k2bRrbtm1j+PDhbNiwgYKCgna9VsFFx2oabLQ0HaW0tLTN1wcCgVaDjRMjNvx+fyfdTcdTcNG9KLgQkXikmo+x4RAXhIMMz4D81GP0DVQRYi/+hj0YEa9LFDk7XSG4ADCzAmBtk+BiO/AZ59weM8sD3nDOjTKzJ2OPn2t+3WneQt9ARHqIHTt2MG3aNHbt2sXYsWN57bXXGDBgQLtfr+DCW0ePHm1zKsqePW3/um8ebDSfjjJw4MAuFWwouOheFFyISEdJMx9js0JcEIqGGoPSjtLHf0ihhnQN7QwuknHMbf8mYUQZ0D/2OB/Y3eS64ljbKZ9kzexO4E6AMWPG8Oc//7njqhWRpLB161amT59OeXk5U6ZMYd26deTk5HhdlpyBYDDIiBEjGDFiRIvnjx49yieffNLqVJQ9e/bw0Ucf8dFHH7X4+kAgwJAhQ1qdipKXl9elgg0RERGAY66Bt6sO8XbVoWZn+pHuH8DYcJjzQ2nRUCP1KH38VWQ2hhpaT0O6hmQMLho555yZnfGfmpxzy4HlAJMmTdKfTkW6uc2bNzNjxgwqKyuZOnUqa9asIRQKeV2WJFgwGGTkyJGMHDmyxfNNg42WpqKUlZXx4Ycf8uGHH7b4+pSUlFaDjYKCAgUbIiLS5dRGGnirsoq3Kpu2GtCfdH8e48Nhzg+lMiw2/STXX0kG5fgbyhVqSFJJxuCi3MzymkwV2RtrLwEGN7luUKxNRHqwoqIi5syZQ3V1NbNnz2b16tUEg0GvyxIPnC7YqK2tbXPERllZGR988AEffPBBi69vHmw0n4qSl5eHz+fryFsUERFJmNpIA5srq9h8UqjhA/LI9A9iXFaYC0KpnJvuyG8cqVGOT6GGeCAZg4tfArcC34n9fKlJ+0IzW010cc6qdqxvISLd2C9+8Qtuuukm6urqWLBgAStWrOhRu07ImUlPT2fUqFGMGjWqxfO1tbXs2rWr1WCjvLy8zWAjNTW1zakoAwYMULAhIiJdQnUkwu8PVvL7g01bT4QagxmfFeL8UBrD0hsYmHqUPv7KJqGGBrxL4nm9q8hzwGeAXKAc+CawBngeGALsIrod6oHYdqiPA9cS3Q71dufc26d7j0mTJrm33z7tZSLSxTz77LN88YtfJBKJsHDhQpYtWxb3l0ItziltqampOWXERtMpKXv37m3z9ampqZxzzjmtTkVpHmxocc7uRYtzikhPkOkPcGFWiDGhVIZlOAam1tLHV0UGZfga9irUkFN1lV1FOpqCC5Hu5/vf/z733nsvAIWFhSxevLjxS148FFxIPGpqatocsXGmwcZ///d/AwouugsFFyLS04X9AS7MDjEmM41zMxoYmFpLju8gGZTja6hQqNFTKbiIUnAh0n0453j44Yf5xje+AcCSJUu4//77Pa5KpH2qq6vbDDYqKipafJ2Ci+5BwYWISOuyAwEmZIUZE0rh3HTXGGqkU4a/oeX/f5RuogtvhyoicgrnHA888ACPPvooZsaTTz7JHXfc4XVZIu2WmZnJmDFjGDNmTIvnmwcb//iP/9jJFYqIiHijqr6e3xw4yG8ONG1NAQbTO3AuE7JDjMlMZWh6hIGptfT2HYxNP9nnUcXS2TTiQkSSXiQS4a677uLpp58mJSWFVatWceONN3pdlkiH0hoX3YtGXIiIJF7vQGp0+kkohaHBCHmNIzX24GvY73V50h4acSEi3UFdXR3z58/nhRdeID09nRdffJEZM2Z4XZaIiIiIeOxgfR2/2n+AX52UUaQC59AndXh0+klmCkPTG8hLqaZ3bPqJQo2uR8GFiCStmpoabrjhBtavX09WVhZr167l8ssv97osEREREUly++uO8/q+A7x+0mySNOAc+qaOYEJWiPMyUzg3PUJeSg29fAdId2X43IFWehQvKbgQkaRUVVXFrFmz2LRpE7m5ubz66qtcdNFFXpclIj2MmX0F+DLggD8BtwN5wGqgD/BHYIFzrs6zIkVE5IxU1NWxYd8BNpwUagSBAvqljuLC7BDnZfopCDaQl1JDb98Bgq4Un6v0qGJRcCEiSaeiooJrrrmGLVu2kJ+fT1FREeedd57XZYlID2Nm+cC9wBjnXK2ZPQ/cBMwE/sM5t9rM/gv4EvBDD0sVEZEE2Vt3jFcrjvHqSZuZBIFz6Z+axoXZmYzOTKEgWM+A2EiNoNujUKODKbgQkaRSXFzMtGnT2LZtG8OHD2fDhg0UFBR4XZaI9FwBIN3MjgMZwB7gKuDm2PlngG+h4EJEpNsrrzvG+opjrD8p1EgHziUvLY0J2SHOywgwNL2eASnV9LJoqGGuyqOKuw8FFyKSNHbs2MG0adPYtWsXY8eO5bXXXmPAgAFelyUiPZRzrsTMlgKfALXAa0SnhlQ65+pjlxUD+S293szuBO4ESOub3vEFi2fKDhgAACAASURBVIiIZ/YcO8aevcd45aTWDGAYg9LSGZ+dwXmZAc4JNg01SjF3yJuCuxgFFyKSFLZu3cr06dMpLy9nypQprFu3jpycHK/LEpEezMx6A7OBoUAl8AJwbXtf75xbDiyH6HaoHVGjiIgkv+JjtRTvrWXdSa0ZwHAGpwcZH85sEmocIbsx1DjsTcFJSMGFiHhu8+bNzJgxg8rKSqZOncqaNWsIhUJelyUicjXwkXOuAsDMfg5cCvQys0Bs1MUgoMTDGkVEpAvbXXuU3bVHWXtSayYwgiHp6UzIymRUho9zgpFYqLGfNFeCuWpvCvaIggsR8VRRURFz5syhurqa2bNns3r1aoLBoNdliYhAdIrIFDPLIDpVZCrwNvBrYC7RnUVuBV7yrEIREem2Pqmt5ZPa2matIWAUBekZjM/KYFSmn3PSjtM/pZps20eaK+2WoYaCCxHxzJo1a5g3bx51dXUsWLCAFStWEAjo15IIgHOaWeA159ybZvYz4B2gHthCdOrHOmC1mf1/sbanvatSRER6oo9ra/i4tqZZaxgYxbkZ6YwPZzIy0885weP0Dxwhy/Z36VBD3xBExBPPPvssX/ziF4lEIixcuJBly5bh8/m8LktE5CTOuW8C32zW/CEw2YNyRERETuvDmlo+rGk+UiMaagzPyGRcVjqjMvwMCR6nX+Aw2bafVFeKueZBSPJQcCEine773/8+9957LwCFhYUsXrwYM/O4KhERERGR7m1nTTU7a5qPusgCshgRCzVGxqaf9AscJsv2kepKMHfUi3IbKbgQkU7jnOPhhx/mG9/4BgBLlizh/vvv97gqERERERHZUVPNjlNCjWyMbEZmZjIunMHITGNw2nH6x0KNFFfaKaGGggsR6RTOOR544AEeffRRzIwnn3ySO+64w+uyRERERESkDQ7YXl3N9urmoUYvjF6MCoUYF05nZIaPwWl1jSM1UhpKMI4lpAYFFyLS4SKRCHfddRdPP/00gUCAVatWMW/ePK/LEhERERGRODhg25EjbDtypNmZaKgxOhRibDidkZnGkLQ6+voPE7Z9pDSUnlGooeBCRDpUXV0d8+fP54UXXiAYDPLiiy8yc+ZMr8sSEREREZEO5IC/HDnCX04JNXrjJ4fR4RA/HNK+vhRciEiHqamp4YYbbmD9+vVkZWWxdu1aLr/8cq/LEhERERERD0VwvHf4cLuvV3AhIh2iqqqKWbNmsWnTJnJzc3n11Ve56KKLvC5LRERERES6GAUXIpJwFRUVXHPNNWzZsoX8/HyKioo477zzvC5LRERERES6IAUXIpJQxcXFTJs2jW3btjF8+HA2bNhAQUGB12WJiIiIiEgX5fO6ABHpPnbs2MFll13Gtm3bGDt2LBs3blRoISIiIiIicVFwISIJsXXrVi6//HJ27drFlClTeOONNxgwYIDXZYmIiIiISBen4EJE4rZ582Y+/elPU15eztSpU9mwYQM5OTlelyUiIiIiIt2AggsRiUtRURFXX301lZWVzJ49m7Vr1xIKhbwuS0REREREugkFFyJy1tasWcN1111HdXU1CxYs4Gc/+xnBYNDrskREREREpBtRcCEiZ2XlypXMnTuXuro6Fi5cyI9//GMCAW1UJCLeMLNPmdkTZrbVzCrM7BMze9nM/tHMsr2uT0RERM6eggsROWOPP/44t9xyC5FIhMLCQh577DF8Pv06ERFvmNkrwJeBV4FrgTxgDFAIBIGXzOyz3lUoIiIi8dCfR0Wk3ZxzPPLIIxQWFgKwZMkS7r//fo+rEhFhgXNuX7O2I8A7seNRM8vt/LJEREQkERRciEi7OOd44IEHePTRRzEznnzySe644w6vyxIRoYXQAjObCmQA651zx1u6RkRERLoGBRciclqRSIS77rqLp59+mkAgwKpVq5g3b57XZYmItMjMHgWqgAbgHmCmtxWJiIhIPBRciEib6urqmD9/Pi+88ALBYJAXX3yRmTP1HUBEkkcsqPi2c64y1jQEuDH2+E/eVCUiIiKJouBCRFpVU1PDDTfcwPr16wmHw6xdu5YrrrjC67JERJr7ObDazF4GngCeBX5NdGHO//ayMBEREYmfggsRaVFVVRWzZs1i06ZN5Obmsn79eiZOnOh1WSIip3DO/V/gWjObT3Rnkcecc5/xtioRERFJFO1fKCKnqKio4Morr2TTpk3k5+ezceNGhRYikrTMLGBm1wF7gTnAeDP7pZmN97g0ERERSQCNuBCRkxQXFzNt2jS2bdvG8OHD2bBhAwUFBV6XJSLSljXA74nuIvIF59ytZjYQWGxmzjmnLZBERES6MAUXItJox44dTJs2jV27djF27Fhee+01BgwY4HVZIiKnc45zbpaZpQKbAZxzpcCXzWyCt6WJiIhIvBRciAgAW7duZfr06ZSXlzNlyhTWrVtHTk6O12WJiLTHk2b2+9jj7zU94Zx714N6REREJIEUXIgImzdvZsaMGVRWVjJ16lTWrFlDKBTyuiwRkXZxzj0OPO51HSIiItIxknZxTjP7ipn92czeM7PnzCxoZkPN7E0z22lmP40NCRWROBQVFXH11VdTWVnJ7NmzWbt2rUILEelSYotz3mVmr5jZ1tjxipndbWYpXtcnIiIi8YlrxIWZ/bKt8865z55lv/nAvcAY51ytmT0P3ATMBP7DObfazP4L+BLww7N5DxGBNWvWMG/ePOrq6liwYAErVqwgENBALBHpclYClcD/AopjbYOAW4FVwDyP6hIREZEEiPcbyqeA3cBzwJuAxV3R3wSAdDM7TnSV8D3AVcDNsfPPAN9CwYXIWVm5ciW33347kUiEhQsXsmzZMny+pB2EJSLSlonOuZHN2oqBzWb2Vy8KEhERkcSJ91vKAOBfgAuAZcA0YJ9z7jfOud+cbafOuRJgKfAJ0cCiCvgjUOmcq49dVgzkt/R6M7vTzN42s7crKirOtgyRbuvxxx/nlltuIRKJUFhYyGOPPabQQkS6sgNm9jkza/xFZmY+M5sHHPSwLhEREUmAuL6pOOcizrn1zrlbgSnATuANM1sYT79m1huYDQwFBgKZwLVnUNdy59wk59ykvn37xlOKSLfinOPhhx9m0aJFACxZsoRvf/vbmCVysJSISKe7CZgLlJvZX81sB1AO/EPsnIiIiHRhcU9mN7M04Drg80AB8Bjwizi7vRr4yDlXEXuPnwOXAr3MLBAbdTEIKInzfUR6DOccDz74IEuXLsXMePLJJ7njjju8LktEJG7OuY+JrWNhZn1ibfu9rElEREQSJ97FOZ8lOk3kZeB/OefeS0hV0SkiU8wsA6gFpgJvA78m+heV1UQX3HopQe8n0q1FIhHuvvtunnrqKQKBAKtWrWLePK1VJyLdh5mdR3S0Zn7seQnwknNum6eFiYiISNzindQ+HxgB3Af83swOxY7DZnbobDt1zr0J/Ax4B/hTrM7lwNeAr5rZTqAP8HSc9Yt0e3V1ddx888089dRTBINBXnrpJYUWItKtmNnXiP5Rw4C3YocBq83sIS9rExERkfjFNeLCOddhq/k5574JfLNZ84fA5I56T5HupqamhhtuuIH169cTDodZu3YtV1xxhddliYgk2peA851zx5s2mtn3gD8D3/GkKhEREUmIeKeKBIG7geHAVmBFk10/RMRDVVVVzJo1i02bNpGbm8v69euZOHGi12WJiHSEBqKLee9q1p4XOyciIiJdWLyLcz4DHAc2AjOB84lOGxERD1VUVHDNNdewZcsW8vPz2bBhA6NHj/a6LBGRjvJPwOux3UR2x9qGEP3DSlw7nYmIiIj34g0uxjjnxgKY2dNE55SKiIeKi4uZNm0a27ZtY9iwYRQVFVFQUOB1WSIiHcY5t97MRhKdTpofay4B/uCci3hXmYiIiCRCvMFF41xS51y9mcXZnYjEY8eOHUybNo1du3YxduxYXnvtNQYMGOB1WSIiHc451wBsbt5uZiHn3BEPShIREZEEiTe4GN9k9xAD0mPPDXDOuaw4+xeRdtq6dSvTp0+nvLycKVOmsG7dOnJycrwuS0TEa38hOm1EREREuqh4g4tg8xW8RaTzbd68mRkzZlBZWcnUqVNZs2YNoVDI67JERDqFmX21tVOAfhmKiIh0cfFuZ/pmQqoQkbNWVFTE1VdfTWVlJbNnz2bt2rUKLUSkp3kE6A2Emx0h4v+sIyIiIh6Ld8SFFrUQ8dCaNWuYN28edXV1LFiwgBUrVhAIxPs/axGRLucdYI1z7o/NT5jZlz2oR0RERBIo3m84fdsYnolz7ntx9i8irVi5ciW33347kUiEhQsXsmzZMnw+/WFRRHqk24H9rZyb1JmFiIiISOLFG1z4iQ7D1MgLkU70+OOPs2jRIgAKCwtZvHgx2tVHRHoq59z2Ns6Vd2YtIiIiknjxBhd7nHOLE1KJiJyWc45HHnmEwsJCAJYsWcL999/vcVUiIiIiIiIdR2tciHQRzjkefPBBli5dipnx5JNPcscdd3hdloiIiIiISIeKd0L81IRUISJtikQi3HnnnSxdupRAIMBzzz2n0EJEJMbM/nfs5+e8rkVEREQSL67gwjl3IFGFiEjL6urquPnmm3nqqacIBoO89NJLzJs3z+uyRESSyUyLLvTzda8LERERkcTTvokiSaympoa5c+fyyiuvEA6HWbt2LVdccYXXZYmIJJv1wEEgZGaHiE5ldSd+OueyvCxORERE4qO9E0WSVFVVFddeey2vvPIKubm5/PrXv1ZoISLSAufcA865XsA651yWcy7c9KfX9YmIiEh84gouzGywma02s41m9i9mltLk3Jr4yxPpmSoqKrjyyivZuHEj+fn5/Pa3v2XixIlelyUiktScc7PNrL+ZzYodfb2uSUREROIX74iLFcAbwCIgD/iNmfWJnTsnzr5FeqTi4mKuuOIKtmzZwrBhw9i0aROjR4/2uiwRkaQXW5zzLeBzwI3AW2Y2N84+e5nZz8xsm5m9b2afMrMcM9tgZjtiP3snon4RERFpWbzBRV/n3H855951zi0CfgD81syGEZ1bKiJnYMeOHVx22WVs27aNCy64gI0bN1JQUOB1WSIiXUUhcLFz7lbn3C3AZOAbcfa5DFjvnDsPGA+8DzwEvO6cGwG8HnsuIiIiHSTexTlTzCzonDsK4JxbZWZlwKtAZtzVifQgW7duZfr06ZSXl3PJJZfw8ssvk5OT43VZIiJdic85t7fJ8/3E8UcaM8sGrgBuA3DO1QF1ZjYb+EzssmeIjj792tm+j4iIiLQt3hEXTwGXNG1wzhURHaL5Xpx9i/QYmzdv5tOf/jTl5eVMnTqVoqIihRYiImduvZm9ama3mdltwDrg5Tj6GwpUAD8ysy1m9pSZZQL9nXN7YteUAf1berGZ3Wlmb5vZ28er6uIoQ0REpGeLK7hwzv2Hc+43LbRvcc5Ni6dvkZ6iqKiIq6++msrKSmbPns3atWsJhUJelyUi0uU45x4AngTGxY7lzrl4RkIEgIuAHzrnLgSqaTYtxDnnaGV6rHNuuXNuknNuUkp2ahxliIiI9GzxThUBwMwea+u8c+7eRLyPSHezZs0a5s2bR11dHQsWLGDFihUEAgn5n6WISI/knPs58PMEdVcMFDvn3ow9/xnR4KLczPKcc3vMLA/Y22oPIiIiErd4p4qcECT6F4kdsWMCkAr8MXaISDMrV65k7ty51NXVsXDhQn784x8rtBARSSLOuTJgt5mNijVNBf4C/BK4NdZ2K/CSB+WJiIj0GIn6ljQOuMw5Vw9gZv8FbHTO3Z2g/kW6lccff5xFixYBUFhYyOLFizEzj6sSEZEWLAJ+YmapwIfA7UT/8PO8mX0J2EV061URERHpIIkKLnoDWcCB2PNQrE1EmnDO8cgjj1BYWAjAkiVLuP/++z2uSkSkezCz+5xzy07Xdiacc+8Ck1o4NfVs+xQREZEzk6ipIt8BtpjZj83sGeAd4JEE9S3SLTjnePDBByksLMTMWL58uUILEZHEurWFtts6uwgRERFJrISMuHDO/cjMXuFvW6N+LTYvVESASCTC3XffzVNPPUUgEGDVqlXMmzfP67JERLoFM/s8cDMw1Mx+2eRUmL+NBhUREZEuKlG7ihhwNXCuc26xmQ0xs8nOubcS0b9IV3Zix5Dnn3+eYDDIiy++yMyZM70uS0SkO/kdsAfIBR5t0n4Y2OpJRSIiIpIwiVrj4gdAA3AVsJjoB4UXgYsT1L9Il1RTU8PcuXN55ZVXCIfDrF27liuuuMLrskREuhXn3C6ii2R+yutaREREJPESFVxc4py7yMy2ADjnDsZW3xbpsaqqqrj++uvZuHEjubm5rF+/nokTJ3pdlohIt2VmhwEXe5oKpADVzrks76oSERGReCUquDhuZn5iHxbMrC/RERgiPVJFRQXXXnst77zzDvn5+WzYsIHRo0d7XZaISLfmnAufeBybxjobmOJdRSIiiREOZJJuaVQcP4hrzGdFeo5EBRePAb8A+pnZw8BcoDBBfYt0KcXFxUybNo1t27YxbNgwioqKKCgo8LosacWegbMAyCtd63ElIpJIzjkHrDGzbwIPeV2PiMjZSLEA11edx2e/+yEZ5Qeoy0qlfEIu5aPD7BmcQmmfCCXp1RQ37ONIpMbrckU6TKJ2FfmJmf2Rv+1pPsc5934i+hbpSnbu3MnVV1/Nrl27uOCCC3jttdfIy8vzuiwRkR7BzP6hyVMfMAk46lE5IiJxuZSRfP4HB+n3znuNbamH6hj821IG//bU6w+fk0XZ+N6UDctkT76P0uw6SlIPUXp8H8ddfSdWLpJ4cQUXZpYBHHfOHXfObTMzB8wERgMKLqRH2bp1K9OnT6e8vJxLLrmEl19+mZycHK/LEhHpSa5v8rge+JjodBERkS5jeEo+t/4ylVE//+sZvS686xDhXYcY0ay9IWDsv6AvZednUzY0SGk/R2molmJfJfs09US6iHhHXKwHvgTsMLPhwO+BnwCzzOxi59zX4y1QpCvYvHkzM2bMoLKykquuuoqXXnqJUCjkdVkiIj2Kc+52r2sQETlbOSnZzP9/+fzdY+/jiyQuTPDVO/q+W0HfdysY2+zcsV5p7J2QS9moMHuGBKJTT4JHKGnYr6knklTiDS56O+d2xB7fCjznnFsU21Hkj4CCC+n2ioqKmDNnDtXV1cyePZvVq1cTDAa9LktEpMcxs0HA94FLY00bgfucc8XeVSUi0rZUXyp/v28k131nJ8GDf+nU906rPMbgN0oY/Map5w4VZFE+Loc9wzMoG+ijpMnUk3pNPZFOFm9w0TQKvApYAuCcqzMz7Soi3d6aNWuYN28edXV1LFiwgBUrVhAIJGrNWxEROUM/Av4H+Fzs+fxY2zTPKhIRacOVkdHM+49ycv7y3ukv7mRZHx8i6+OWp57sG9eX8jHZ7BkapLRfA6WhoxTbAfYdr/SkVun+4v2GtdXMlgIlwHDgNQAz6xVvYSLJbuXKldx+++1EIhEWLlzIsmXL8Pl8XpclItKT9XXO/ajJ8x+b2T95Vo2ISCtGp5zDrT91nPtK11sW0Ffv6PdOBf3eOXXqydHewdjUk0zKBqdS0uc4pcHorifVkVpP6pXuId7g4g7gPqAAmO6cOzERagywNM6+RZLW448/zqJFiwAoLCxk8eLFmJnHVYmI9Hj7zWw+8Fzs+eeB/R7WIyJykv4pfZj/Vj8u+UHXCyzaI3jwKEN+XcyQX596rurcbMrH5VA2LJ09A32UZB+jJOUQe47v19QTOa24ggvnXC3wHQAzSzezUc657c653wG/i6fv2KiNp4ALiE5J+SKwHfgp0aDkY+BG59zBeN5H5Ew453jkkUcoLCwEYMmSJdx///0eVyUiIjFfJLrGxX8Q/ezwO0ALdoqI59L9QT5XOoLp/3s7qYd7Zp6a/WEV2R9WMbJZeyTVx76x/Sgfk03Z0DRK+jZQGqqlxA5q6ok0SshkfDO7nugIi1RgqJlNABY75z4bR7fLgPXOubmxxT4zgH8BXnfOfcfMHgIeAr4WZ/ki7eKc48EHH2Tp0qWYGU8++SR33HGH12WJiEiMc24XEM9nDxGRhPLhY1rdecz9XinZH/zJ63KSkr+ugf5/3Ev/P+5lXLNzR3sHKb8wl7JRIcoGByjNqackNvWkRlNPepRErSL4LWAy8AaAc+5dMzv3bDszs2zgCuC2WH91QJ2ZzQY+E7vsmdj7KbiQDheJRLj77rt56qmnCAQCrFq1innz5nldloiIAGZWCPzAOXeglfNXARnOubWdW5mI9GTjA0NZ8Oxxhvy6c3cK6U6CB49yzq+KOedXp56rGtaLsnG9KBuWwZ48H6WxqSelx/cRcZHOL1Y6VKKCi+POuapmc/zj2VVkKFAB/MjMxhPdWvU+oL9zbk/smjKgf0svNrM7gTsBhgwZEkcZIjTuGPL8888TDAZ58cUXmTlzptdlSYI17K/C1yfb6zJE5Oz8Cfg/ZnYUeIfoZ4ggMAKYABQBj3hXnoj0JPmp/bjlN724cMVfvS6lW8v+oJLsDyoZ1aw9kupj37h+lI3JpqwgjdJ+DZRk1lJsBzhwvMqTWiV+iQou/mxmNwN+MxsB3Et8a1wEgIuARc65N81sGdFpIY2cc87MXEsvds4tB5YDTJo0qcVrRNqjpqaGuXPn8sorrxAOh1m7di1XXHGF12VJAkT2V3H4kWcan5eP/QL+/L4Exg0n5cQxdhj+XG2SJJLsnHMvAS/FPoNcCuQBh4BVwJ2xNblERDpUyJ/JTR8P5aol7xOo3et1OT2Wv66B/m/vpf/bexnf7NzRPtFdT/aMCrFncIDS3vWUBI9Q3LCP2shRT+qV9klUcLEI+FfgGNGVvF8Fvh1Hf8VAsXPuzdjznxENLsrNLM85t8fM8gD9RpAOU1VVxfXXX8/GjRvJzc1l/fr1TJw40euyJE4uEqFm5XoOf3clrvJIY7ulpxEpqSBSUsGxV37f2O7Ly40FGcNIGRsNNPz9entRuoichnNuB7DD6zpEpGfxm5+Z1efx90t2ESp+z+typA3B/UcZ8noxQ14/9VzliF6Uj+1N2fB0SgcYpVl1lKRUsef4fk09SQIJCS5i26D+a+xIRH9lZrb7xC4lwFTgL7HjVqI7mdwKvJSI9xNprqKigmuvvZZ33nmH/Px8NmzYwOjRo70uS+JU9/b7VP3rf1H/pw8ASP30hdT9ZgsA/f/6PPUflHD8Tx9Qv3Unx7fu5Ph7H9KwZx/H9uzj2KubG/vxDchpDDFSxg6LhhkD+nhyTyIiIuKdi33Dmf9UNXm//7PXpUiceu2opNeOU6ee1Kf52TeuP2VjsqJTT/o2UJpZy24OcLBeU086S9zBhZndSnT9iRP/Gb8PPOacezbOrhcBP4ntKPIh0e3MfMDzZvYlYBdwY5zvIXKK4uJipk2bxrZt2xg2bBhFRUUUFBR4XZbEIbKvksMP/5janxYB4BvYl6zFdxCc8SnK8q8HwPx+UkYOIWXkELjhSgBcQwORWJhx/E+xMONPH9BQdoBjZW9xbMNbje/h69c7FmT8Lczw5fWh2do/IiIi0g2ck5rHbeszOP+5nV6XIh0scCzCgD+UM+AP5aecq81NZ++FuewZmUnZoBRKco5TknaEEk09Sbi4gotYaPFPwFeJLoZlRNemWGJmzv3/7N15fFTl2f/xzz1LMklmJhDCEsISEhKWxq1YUWupUqIYwVhlcWGRWiwU+7S/VrQVtVVcKmgXqo+AirbYilraxiIqi7XSWrSCPkQhhCQQCEvYQib7ZGbu3x9nMgkEFckkZya53q9XXsmcnHPmO6iYuXJf1631yrO9t9b6Y+DC03zrW2d7TyG+SHFxMePGjaOsrIzs7GzWrVtHSkqK2bHEWdI+P3V/WEv14hfRVbUQYyNhzvU4/2cKlnjHF16vLBZsmQOxZQ4k7vrLjXsGAvj3HDSKGNuCBY2CEgKHK2nc8F8aN/w3dL0luUerFhPjsyW1txQzhBBCiCiVaHNxS+EgxjyxHYtPRul1d3FH6xm8fh+D17f9XmVWDyrOSeJQRhwHUhQH3I3st1VxqOkoft2efSy6p/auuJgLfFtrvafVsbeVUjcAq4CzLlwI0dkKCgrIycmhoqKC0aNHs3btWpKSksyOJc6S94PtVN3zNL7tuwGIvWIU7oW3Y0tPbdd9lcWCLT0VW3oqcdd9EwCtNf6yQ8FiRnObSQmBoydofHsLjW9vCV1vSXJjC67IaP6wDugjxQwhwkAplQU8jbELWbZS6lzgWq31QyZHE0JEObuycW3VcCY+Vkr8YWkLEV+sZ9EJehadYPgpx32xVo6c15eKkW4ODTZaT/Yn1FHOcSp9HlOyRoP2Fi7cpxQtANBa71FKudt5byE6zebNm8nNzaWyspKxY8eSn5+P0+k0O5Y4C/4jlVQ/9Dz1rxobfltTe+N+8HZix1/cYcUBpRS2tBRsaSnEXfsNIFjM2FfRUsgoKKFpWwmB4x68//woNFsDQPV0Yc8+pZgxqK8UM4T48p4B5gPLALTW25RSfwKkcCGEOGuXMYybnjxO749l8KZoP1ujn5QPKkj5oG3rSV2feCrO78WhrAQODbBxoKfRelLuP0pDoNGEtJGjvYWLz9teTLYeE1Fhw4YNXHfdddTW1pKXl8eqVatwOL64jUBEFu3zU/fC60ZbSHUdxNhwfv8GnHdMRp1BW0i4KaWwDeqHbVA/4iZcZmTUGv/+I6Fihq+ghKZtxQSOVeHd9DHeTR+3XJ+YYMzKOKdVMWNwP5TF0umvRYgoEq+1/uCUop/PrDBCiOiWaR/AzHw7WX/daXYU0U3EH65jyLo6hqw7+bhWcCKrJ4fO6UFFRjwH+in2uxvYb6uioulYt2g9aW/hYoRSattpjisgvZ33FqLD/e1vf2Pq1Kl4vV6mTZvGihUrsNvtZscSX5L3/U+M3UK27wEg9lsX4n7wlBtqegAAIABJREFUdmxD+psb7BRKKWwD+mAb0Ie43EsBo5gROHA0uCqjeWVGMYEjJ/D+axvef7X8FavcCdiz00/a0cSa3l+KGUK0OKqUygA0gFJqEnDQ3EhCiGjTy96DaR/355Lf7cDilzkWwnxKQ8+dlfTcWcmp+xz64qwcPbcfB0e6OTQ4xmg9iTdaT050odaTdhcuwpJCCBOsXLmSWbNm4ff7mTdvHkuWLMEibwCjiv9wJdULV1C/+h8AWAf2NdpCrrwoatoslFJYU3tjTe2N4+pLgGAx49CxluGfzbuZVBzH+14B3vcKWq53xgXbTIxWE9s5Q7Gl90dZrWa9JCHMNA9YDgxXSu0HdgPTzI0khIgWsZYYvn0ki9zHinFUbjc7jhBnxFbvp9/7h+j3/qE236vr29x64uRgqjXUerI/CltP2lW40FqXhSuIEJ3pySef5Ac/+AEA9957Lw8++GDUvNEVwbaQ59dQ/fgfjbaQWDvO70/CecckVFys2fHaTSmFNSUZa0oyjqtGh477K463mpdhrNAIHDyGd/MneDe39N2qeAe27PSWmRnnZGAbOkCKGaLL01qXAuOUUgmARWtdbXYmIUTkUygu9w9n6hMVJBXKHAvRdcRX1DHkrTqGvHXyca2gclgSFef04FB6HAdS4ICrkf3WKg41HSNA5LWetHfFhRBRRWvNI488wr333gvA4sWLufPOO01OJb6Mxs2f4LnnaXyFRt00dtzXjLaQtK6/ba21bxLWnItw5FwUOuY/UtlSyAhu0Ro4cISmD7bT9EHLb4tUXCy2r6SHChn2c4diyxyIskkxQ3QdSqkfn/IYoArYEtxmXQghTjLSPpiZqzRD3txhdhQhOo3SkFR4nKTC421aKJoSbBw9ty8HR7iM1pPkAAfi69jHMap85v0+QAoXotvQWnPXXXfx+OOPo5Ri2bJlzJ492+xY4gz5Dx3Ds3AFDX/9JwDWwf1wP3j7SW/iuyNr755Yx16IY+yFoWP+Y1X4CowiRnNBw19+mKYPd9D0YasfzByx2L+SZszMaC5mZA1C2eV/DSJqXRj8+Hvw8QRgGzBHKfWq1nqRacmEEBGlr70X09/vzUVPF5odRYiIYq/1kfKfg6T8p+2IqNqUBCrO70VFZgIHQq0n1ez3HaUx4O3QXErrrj1w5sILL9Qffvih2TGEyfx+P3PmzOHZZ5/FZrPx4osvMnXqVLNjiTOgm3zUPvcaNU+8hK6tB0cMzjsm4/z+DShHjNnxokbgWBVNn5S2DAHdVox/b9ttuIi1Yx855KQdTWzDBqFiZGhtF9WleuSUUu8CuVrrmuBjJ/A6MB5j1cVIs7K5Mnvo839zmVlPL4QIirM6mLx/KFc+tpOYmiaz4wjRJWgFlSOSOJTdk0PpDg70gwPuRsotJzjcdPxzW082XbPmjH4Wadev1ZRSBQQnd5+O1vrc9txfiHDwer1Mnz6dV155BYfDwerVq8nNzTU7ljgDje9tw3PPUnxFewGIvepi3A98F9ugfiYniz6WXonEfvMCYr95QehY4ERNy/DPbSU0fVKMf/dBmj4qoumjopaLY2zYh6e1zMw4dyi2YYNRsVLMEBGnD9B62lgT0FdrXa+Uiq4pZEKIsLJg4UrvcG54Yj+JpTLHQohwUhqSth8naftxTv0NQVOCjSPn9eHQCDcHB8dwINnPgfg6yvUxqnw1Z/wc7V0PPCH4eV7w88rg51vaeV8hwqKuro5Jkybxxhtv4HK5WLNmDWPGjDE7lvgC/oNH8Ty4gob8dwGwpqXgXng7jm99zeRkXYulh5PYb5xP7DfODx0LVNW0rMwIDgL1l+4PPQ6x27ANGxzazcR+7lDsw9NkFYww2x+B95VS+cHHE4E/BYd1yhYBQnRT59vSmf77Rga+I38NCNHZ7LU++r93iP7vtd31pKa/E645s/uEpVVEKfWR1vqCU45t1Vp/td03bydpFem+qqqqmDhxIps2bSI5OZk333yTUaNGmR1LfA7tbaL22deo+fWqYFtILM7/mYxzzvXyhthEgeo6mj4pOWlHE3/Jfjj1/x82K7asQSetzLCPSOsSO710YV2qVQRAKfU14NLgw39rrSPihwBpFRGi86XG9GHmP3pw/gtFX3yyEMIUKQc6oVWkFaWU+rrW+t/BB5cCljDdW4gv7ciRI4wfP56tW7eSmprK+vXrGTHi1Jm5IpI0bvqYqgVL8ReXAxB79SW4H5iNbUAfk5MJiyue2EvOIfaSc0LHAjV1+D4tNVpMgoNAfcXl+Lbvxrd9N/Wr1hsnWi1GMeOcoS2rM0YOQcU7THo1oqvTWv9XKVUGOACUUoO01ntNjiWE6EROawI37h7C2EU7sDUeNjuOECIMwlW4uA1YoZRKDD4+AXwnTPcW4kspLy8nJyeHwsJCMjIy2LBhA2lpaWbHEp/Bf+AongeepeHv/wLAmt6fxIe+R+zlsjomklmc8cSMziZmdHboWKCuAd8npcaqjODsDF/RPnw79uDbsYf6VzYEL7ZgyxwQ3JrV2NHElp2OJSHOpFcjugql1LXAE0B/4DAwCCgEvmJmLiFE57AqK9fUDue6RWU498scCyG6krAULrTWW4DzmgsXWuuqcNxXiC+ruLiYcePGUVZWRnZ2NuvWrSMlJcXsWOI0tLeJ2uX51PxmFbquARUXi/NHU0m4/dsy9DFKWeIdxFw0kpiLWsYy6boGmrbvDrWYNBUU49u5N/RR/+rbxolKYRs6oGX45zkZ2LPTsTjjTXo1IkotBC4GNmitL1BKXQFMMzmTEKITXGTJZNryavq9/6nZUYQQHSAshQulVF/gEaC/1vpqpdRI4BKt9XPhuL8QZ6KgoICcnBwqKioYPXo0a9euJSkpyexY4jQa//kRVfcuw19itIU4rrkU98+/i1XaQrocFe8g5sIRxFzY0qql6xtpKtxjtJkEh376dpbh27UP36591K/+R/BihTU91WgxOSfYZpKdgcWdYNKrEVGgSWt9TCllUUpZtNb/UEr9xuxQQoiOkxaTwsw3E/jKS7vMjiKE6EDhahV5AXgeWBB8XAS8DEjhQnSKzZs3k5ubS2VlJWPHjiU/Px+n02l2LHEKf/lhoy3k9fcAsKanBttCTJ/jKzqRiosl5oJhxFwwLHRMN3hp2lnWspvJtmJ8hWX4S8rxl5TT8Nd/hs61pvcPtZgY7SYZWBLlv3cBwAmllBN4F/ijUuowUGtyJiFEB0i0ubilcBBjntiOxdf+zQaEEJEtXIWLZK31K0qpnwForX1KKX+Y7i3E59q4cSN5eXnU1taSl5fHqlWrcDhk8F8k0Y1N1C77KzW/fRld3xhsC7mRhNuvk7YQAYByxBBzXiYx52WGjmlvE77CstC8jKZtJTTt2I2/9AD+0gOh7XLB2DLXfk5GcAhosJjR02XGSxHmygPqgf+HsTV7IvCAqYmEEGFlVzaurRrOxMdKiT8sbSFCdBfhKlzUKqV6ARpAKXUxIHMuRIfLz89nypQpeL1epk2bxooVK7Db5Y1wJGn4xxY89y3DX3oAAMfEy3DffxvW1N4mJxORTsXYQzMvuMU4ppt8+HbuDc3LaNpWTNP23fj3HMS/52BoyCuAdVDfVqsyjPtYktwmvRrRSe7XWt8NBIDfAyilHgPuNjWVECIsLmMYNz15nN4fy+BNIbqbcBUufgK8BmQopf4N9AYmh+neQpzWypUrmTVrFn6/n3nz5rFkyRIsFtmFN1L4yg/j+fkzNL7xHwCsQweQ+NAcYsecb3IyEc2U3YY9Ox17djpwJRAsZuza19JmUlBC06e78e+twL+3ItSaBGBN7Y0tWAxpXplhTe5h0qsRHSCHtkWKq09zTAgRRTLtA5iZbyfrrzvNjiKEMEnYdhVRSn0TGAYoYKfWuikc9xbidJ588kl+8IMfALBgwQIWLlyIUsrkVAKMWQU1S/9CzZJXoaERFe/A+eObSPjutagYWQ0jwk/ZbdhHDsE+cgjcmAOA9vnxFe9rGQBaUILvkxL8+4/g338kVFADsKQkBwsZLaszrH16mvVyADjYfwIAKQfWmJojWiil5gLfB9KVUttafcsF/NucVEKI9upl78G0j/pzyZM7sPhljoUQ3Vm4dhUpARZrrZe2OrZGaz0hHPcXopnWmkceeYR7770XgMWLF3PnnXeanEo0a3j7Q6MtZPdBABx5Y3Df/x2sKckmJxPdjbJZsQ9Pwz48DaZ8CwDt9+Mr2W8M/mzenvWTUgIHj9J48CiNb20OXW/pl9QyL6N5ZUa/Xia9GnEG/gS8ATwK/LTV8Wqt9XFzIgkhzlasJYbrj2SR+8tdxJ7YbnYcIUQECFerSBNwhVJqNPA9rbUXSA3TvYUAjKLFXXfdxeOPP45SimXLljF79myzYwnAt68Cz/3PhN742bIG4X54DrFfP9fkZEK0UFYr9qxB2LMGwaSxAOhAAH/JfmNeRkHL6ozAoeM0HvqAxvUfhK639Ol50rwM+zkZWFJ6yWqvCKC1rsKYrXWTUsoK9MX4GceplHJqrfeaGlAIcUYUiiv8w5nyRAVJhTLHQgjRIlyFizqt9VSl1F3AJqXUZIKDOoUIB7/fz5w5c3j22Wex2Wy8+OKLTJ061exY3Z5u8FLzv6upefJVaPCiEuJw/uQmEm67FmUP118vQnQcZbFgyxyILXMgcddfAQSLGbsPBod/loSKGoHDlTRu+C+NG/4but6S3KNVi4mxq4kltbcUM0yilLoD+AVQgTGgE4yfR6SKKkSEG2kfzMxVmiFv7jA7ihAiAoXrnYUC0FovUkptBdYBSWG6t+jmvF4v06dP55VXXsHhcLB69Wpyc3PNjtXtNaz/AM/9y/GXHQLA8e1v4r7vO7KcXkQ9ZbFgy0jFlpFK3HXfBILFjLJDLasythXT9EkJgaMnaHx7C41vbwldb0lyYz93KLbmHU3OHYp1QB8pZnSOHwHDtNbHzA4ihDgzfe29mLG5N19bWmh2FCFEBAtX4eL+5i+01huUUlcBM8N0b9GN1dXVMWnSJN544w1cLhdr1qxhzJgxZsfq1nxlh/Dctyz0W2fb8MFGW8gl55icTIiOoywWbEP6YxvSn7hrvwEY7Wv+fRUthYzg6ozAcQ+N72yl8Z2tLdf3dBktJq2LGYP6SjEj/PYh27ELERXirXFMLs8gZ9FOYmqk1iiE+HztKlwopYZrrQuB/Uqpr57ybRmFLtqlqqqKiRMnsmnTJpKTk3nzzTcZNWqU2bG6LV3fSM1Tf6bmqT9DYxPKGYdr/jTib71G2kJEt6SUwjaoH7ZB/YibcBkQLGbsPxIqZviCnwPHPXjf/Qjvux+1XN/DiT074+RiRlqKFDPapxR4Ryn1OtDYfFBr/SvzIgkhWrNg4crG4Ux6ohz3bpljIYQ4M+19t/ETYDbwxGm+p4Gx7by/6KaOHDnC+PHj2bp1K6mpqaxfv54RI0aYHatb0lrTuO4DPD9fjn9vBQBxN1yB695ZWPtKR5gQrSmlsA3og21AH+JyLwWM/4YCB44GB3+2rM4IHD2B91//h/df/9dyvTsBe3Z66HGgpg6LM77TX0cU2xv8iAl+CCEiyPm2dKY/38DAd2WnECHEl9OuwoXWenbw8xXhiSMElJeXk5OTQ2FhIRkZGWzYsIG0tDSzY3VLvt0H8Ny/nMaNHwJgG5FG4iNziBmdbXIyIaKHUgpram+sqb1xXH0JECxmHDpmtJc0FzQKSghUHMf7XkHoWl3XCFK4OGNa6wcAlFLxWus6s/MIIQwDYvow4x89OP+FIrOjCCGiVHtbRa7/vO9rrf/SnvuL7qe4uJhx48ZRVlZGdnY269atIyUlxexY3Y6ua6DmyVep+d/V4PWhXPG45t9C/K0TUDar2fGEiHpKKawpyVhTknFcNTp03F9xnKZtxVTOfBAAa5+eZkWMSkqpS4DnACcwSCl1HsY27d83N5kQ3ZPTmsCNu4cwdtEObI2HzY4jhIhi7W0Vmfg539OAFC7EGSsoKCAnJ4eKigpGjx7N2rVrSUqSVoTOpLWm8c3NeH7+DP5y4weMuMljcS2YJW+ghOgE1r5JWHMuMjtGNPsNcBXwGoDW+v+UUu2e6KyUsgIfAvu11hOUUkOAVUAvYAswXWvtbe/zCNFVWJWVa2qHc92iMpz7ZY6FEKL92tsqMitcQUT3tnnzZnJzc6msrGTs2LHk5+fjdDrNjtWt+Er347lvOY3/MLZ1tI0cQuIjc4m5aKTJyYQQ4sxprfedMuDUH4bb/hDYAbiDjx8Dfq21XqWUWgrcBjwdhucRIupdZMlk2vJq+r3/qdlRhBBdSNi2AlBKXQN8BXA0H9NaPxiu+4uua+PGjeTl5VFbW0teXh6rVq3C4XB88YUiLAJ1DdQseYXapX8x2kLcCbjumkb8jFxpCxFCRJt9SqlLAa2UstNScDhrSqkBwDXAw8CPlVEVGQvcHDzl98AvkMKF6ObSYlKY+UY8X1m1y+woQoguKCyFi+BvG+KBK4BngUnAB+G4t+ja8vPzmTJlCl6vl2nTprFixQrsdrvZsboFrTUNa9/D8/NnCRw4AkDc1HG4FtyKNbmHyemEEOKszAF+C6QC+4F1wLx23vM3wF2AK/i4F3BCa+0LPi4PPl8bSqnbgdsBYnvHtTOGEJGph83NzTsGMuZX27H4tNlxhBBdVLhWXFyqtT5XKbVNa/2AUuoJ4I0w3Vt0UStXrmTWrFn4/X7mzZvHkiVLsFgsZsfqFnwl+6m6dynef34EgC07w9gt5ELZclYIEb201keBW8J1P6XUBOCw1nqLUurys8izHFgO4MrsIe/oRJdiVzbyTgxnwqJS4g9LW4gQomOFq3BRH/xcp5TqDxwDZCsI8Zmeeuop7rjjDgAWLFjAwoULOaUnWXSAQF0DNb9ZRe2yv0GTD5WYgOvuGcRPH4+ySluIECK6KaV+D/xQa30i+Lgn8ITW+jtnecuvA9cqpXIxWmHdGCs6eiilbMFVFwMwVncI0W1cxjBu+t0xev+fDN4UQnSOcBUu1iilegCLga0YO4o8G6Z7iy5Ea80jjzzCvffeC8CiRYuYP3++yam6Pq01DWv+jecXzxI4eBSAuJuuxHXPTKy9Ek1OJ4QQYXNuc9ECQGtdqZS64GxvprX+GfAzgOCKizu11rcopV7FaItdBcwE8tuVWogokWkfwK1/s5P5t51mRxFCdDNhKVxorRcGv1ytlFoDOLTWVeG4t+g6tNbcddddPP744yilWLZsGbNnzzY7Vpfn27WPqnuX4d30MQD2c4fifmQuMV8dZnIyIcRnSTmwxuwI0cqilOqpta4EUEolEcZB5K3cDaxSSj0EfAQ81wHPIUTESLb3YNpH/blkyXaUND0JIUwQruGcVoyJ22nN91RKobX+VTjuL6Kf3+9nzpw5PPvss9hsNl588UWmTp1qdqwuLVBbT82vV1H7TL7RFtLDietnM4m/+UppCxFCdFVPAP8JrogAmIyxG0i7aa3fAd4Jfl0KXBSO+woRyWItMdxweBhXP1ZE7IntZscRQnRj4fotxN+BBqAACITpnqKL8Hq9TJ8+nVdeeQWHw8Hq1avJzc01O1aXpbWm4bVNeB58jsDBY6AUcbdchfunM7BIW4gQogvTWv9BKfUhxnalANdrreXdlhBfkkJxhX84Ux8/RM+dBWbHEUKIsBUuBmitzw3TvUQXUldXx6RJk3jjjTdwuVysWbOGMWPGmB2ry2oq2ovn3qV4/7UNAPv5mUZbyPlZJicTQoiOFVz9+anWejggxQohztJX7IOZ8VKAIW/tMDuKEEKEhKtw8YZS6kqt9bow3Q8I/RDyIbBfaz1BKTUEYxBWL2ALMF1r7Q3nc4rwqaqqYuLEiWzatInk5GTefPNNRo0aZXasLilQU0fNEy9R+9xr4POjerpw3zOTuJuuRMkWs0KIbkBr7VdK7VRKDdJa7zU7jxDRpq+9FzM29+ZrSwvNjiKEEG2Eq3CxGfirUsoCNAEK0Fprdzvv+0NgB8b2YwCPAb/WWq9SSi0FbgOebudziA5w5MgRxo8fz9atW0lNTWX9+vWMGDHC7Fhdjtaahr+9a7SFVBwHpYifPh7X3TOwJLX3Pz8hhIg6PYFPlVIfALXNB7XW15oXSYjIFm+NY3J5BjmLdhJTc8zsOEIIcVrhKlz8CrgEKNBah2XWsFJqAMbAz4eBHyulFEbP6s3BU34P/AIpXESc8vJycnJyKCwsJCMjgw0bNpCWlmZ2rC6nqXAPngVL8f7H2EPdfkGW0RZyXqbJyYQQwjT3mR1AiGhhwcKVjcOZ9EQ57t2fmB1HCCE+V7gKF/uAT8JVtAj6DXAX4Ao+7gWc0Fr7go/LgdTTXaiUuh24HWDQoEFhjCS+SHFxMePGjaOsrIzs7GzWrVtHSkqK2bG6lEB1HTVP/JHa5/4O/gCWJDeue24l7sZx0hYihOjWtNb/VEoNBjK11huUUvGAbKMkxCkusKYz7YUGBr4r42CEENEhXIWLUuAdpdQbQGPzwbPdDlUpNQE4rLXeopS6/Mter7VeDiwHuPDCC2W36U5SUFBATk4OFRUVjB49mrVr15KUlGR2rC5Da039X96heuEKAocrjbaQmdfgumsalp6uL76BEEJ0cUqp2Ri/uEgCMjB+wbEU+JaZuYSIFANi+jDj7R6c//sis6MIIcSXEq7Cxe7gR0zwo72+DlyrlMoFHBgzLn4L9FBK2YKrLgYA+8PwXCIMNm/eTG5uLpWVlYwdO5b8/HycTqfZsbqMpu27jbaQ9z8FwD5qGIkPz8V+7lCTkwkhRESZB1wEvA+gtd6llOpjbiQhzOeyJXBjyRCuWLwDW+Nhs+MIIcSX1u7CRXDnD5fW+s4w5AFAa/0z4GfB+18O3Km1vkUp9SowCWNnkZlAfrieU5y9jRs3kpeXR21tLXl5eaxatQqHw2F2rC4h4Kml+vE/Uvf8GqMtpFcirgW3EjflW9IWIoQQbTVqrb3GWCxQStkAWXkpui2rsnJNzQiuW7wH536ZYyGEiF7tLlwEtx/7ejjCnIG7gVVKqYeAj4DnOul5xWfIz89nypQpeL1epk2bxooVK7Db7WbHinpaa+r//DbVDz1P4MgJsFiInzUB1/xpWHrIShYhhPgM/1RK3QPEKaVygO8Dfzc5kxCmGG3J5OZlHlI+kIKFECL6hatV5GOl1GvAq5y8/dhf2ntjrfU7wDvBr0sxloCKCLBy5UpmzZqF3+9n3rx5LFmyBIusAmi3pk9LqbpnKU3/NQZm2b82ksSH52DPTjc5mRBCRLyfYmyVXgB8D1gLPGtqIiE62ZCYFGaujWfky7vMjiKEEGETrsKFAziGsV1pMw20u3AhItNTTz3FHXfcAcCCBQtYuHAhzUtzxdkJVNVQvfiP1L3wOgQCWJJ74LpvFnGTxsqfrRBCfAGl1PnAUOBfWutnzM4jRGfrYXNzy44BfONXO7D4pENKCNG1hKVwobWeFY77iMintebRRx9lwYIFACxatIj58+ebnCq66UCA+lffpvrhFwgcDbaF3DYR1523YEmUthAhuotvvD4BgE3XrDE5SfRRSt0PTAO2AIuUUo9K8UJ0F3ZlI+/EcCb+soS4o7K9qRCiawpL4UIpNQD4HcZuIACbgB9qrcvDcX8RGbTW3H333SxevBilFMuWLWP27Nlmx4pqTQUlVN3zNE1bCgGwXzSSxEfmYh85xORkQggRVaYC52ut65RSvYA3ASlciC7vMoZx0++O0fv/ZI6FEKJrC1eryPPAn4DJwcfTgsdywnR/YTK/38/cuXN55plnsNlsvPjii0ydOtXsWFErcKKG6sdWUrfyDaMtpE9PXPd9h7jrL5e2ECGE+PIatdZ1AFrrY0opGbgkurQs+0Bm/s1G5t92mh1FCCE6RbgKF7211s+3evyCUupHYbq3MJnX62XGjBm8/PLLOBwOVq9eTW5urtmxopIOBKh/eYPRFnLcA1YLCbfn4fzJLVhc8WbHE0KIaJUeHBIOoICMVo/RWl9rTiwhwivZ3oNpH/XnkiXbUTLGQgjRjYSrcHFMKTUNeCn4+CaMYZ0iytXV1TFp0iTeeOMNXC4Xa9asYcyYMWbHikpN24qNtpCtxm9HYi7Oxv3wHOwj0swNJoQQ0S/vlMePm5JCiA7isMRy/eEsrn6siNgTMsdCCNH9hKtw8R2MGRe/xthN5D1ABnZGuaqqKiZOnMimTZtITk7mzTffZNSoUWbHijqBymqqH/sDdSvfBK2x9E3Cfd93cHz7m9IWIoQQYaC1/qfZGYToCArFWP9wpjx+iJ47C8yOI4QQpgnXriJlgCzD7EKOHDnC+PHj2bp1K6mpqaxfv54RI0aYHSuq6ECA+pfW4XnkD+jKYFvId/Nw/vhmaQsRQgghxOf6in0wM/8UIG3dDrOjCCGE6dpVuAhuP/ZZtNZ6YXvuL8xRXl5OTk4OhYWFZGRksGHDBtLS0syOFVW8Hxfhuedpmj7eBUDMpecYbSHDBpucTAghhBCRrJ89mRn/SebCZYVmRxFCiIjR3hUXtac5lgDcBvQCpHARZYqLixk3bhxlZWVkZ2ezbt06UlJSzI4VNQLHPVT/8g/U/fEtoy2kXxLu+2/DkTdG2kIi0DdenwDApmvWmJxECCFEdxdvjWNyeQY5i3YSU3PU7DhCCBFR2lW40Fo/0fy1UsoF/BBjtsUq4InPuk5EpoKCAnJycqioqGD06NGsXbuWpKQks2NFBe33U/endVT/8g/oymqwWUmYnYfz/92IxSltIUII0ZFa7yByOrKriIhkFixc1TicG54ox737E7PjCCFERGr3jAulVBLwY+AW4PfAV7XWle29r+hcmzdvJjc3l8rKSsaOHUt+fj5Op9PsWFHBu3Wn0RayrRiAmMvOM9pCMgeanEwIIbqNS4B9GLubvY+xJaoQEe8CazrTX2hgwLuyU4gQQnye9s64WAxcDyxk5UUqAAAgAElEQVQHztFa14QllehUGzduJC8vj9raWvLy8li1ahUOh8PsWBHPf6yK6kd+T/1L6wCwpPTC/YvZOCZ8XdpChBCic/UDcjC2Y78ZeB14SWv9qamphPgMA2P6MmOjm/P+sMvsKEIIERXau+LiJ0AjcC+woNWbNYUxnNPdzvuLDpafn8+UKVPwer1MmzaNFStWYLfbzY4V0bTfT93KN6letBJ9ogbsNhJuvw7nj6ZiSYgzO54QQnQ7Wms/8CbwplIqFqOA8Y5S6gGt9ZPmphOihcuWwI0laVyxuBBbY4XZcYQQImq0d8aFJVxBROdbuXIls2bNwu/3M2/ePJYsWYLFIv9IP493SyFV9zyNr6AEgJgxF5D40PewDR1gcjIhhOjeggWLazCKFmnAEuCvZmYSoplVWbmmZgTXLdqD84AsBBJCiC+r3TMuRHR66qmnuOOOOwBYsGABCxculPaGz+E/eoLqh1+g/uUNAFj698b9wHdx5F4qf25CCGEypdQfgGxgLfCA1lomHIqIMdqSyc3LPKR8IP9aCiHE2ZLCRTejtebRRx9lwYIFACxatIj58+ebnCpyab+fuj+8YbSFVNVCjI2EOdfj/J8pWOJlDki08fqb2F1TRlFVCbs8paHj3/3Xj4ixxBBjsRNjDX622I1joccx2K3G8dhWx+2h84KfQ/dp9Th4nd1ix6JkVZMQHWAaxhbtPwR+qJTSwePSuipMMyQmhZlr4xn5ssyxEEKI9pLCRTeitebuu+9m8eLFKKVYtmwZs2fPNjtWxPL+d4fRFvKp8QY39vKv4l74PWwZqSYnE2eizldHsWc3RVWlFHlK2OUpYXf1Xvza3+bcnVXFnZbLbrGFChr2VgWO2GDRxH7aoslpiiitr/0SRRS7xSarhESXI62rIpL0tLm5eccAvvGrHVh8+osvEEII8YWkcNFN+P1+5s6dyzPPPIPNZuPFF19k6tSpZseKSP4jlUZbyCsbAbCm9sb94Gxix18ib/giVGVjFbs8xiqKoqoSijwl7K89iObkHxgVisEJA8hMzCDTnc7Thc8DsPzrv8Ib8OL1NxmfA02tvjaONwWMx42BJrx+47hxrPlx62tbPW51rTfQRFPAR1PARy11ZvxRAbQqhJxc0DAKI0axI9ba6vgpRZPTrShpLprEfkZxxfiecZ5NSfFEhJdSygHMAYYC24AVWmufualEdxNjsXNt5TAm/rKEuKOyvakQQoSTFC66Aa/Xy4wZM3j55ZdxOBysXr2a3Nxcs2NFHO3zU/fC61Q//ke0x2gLcc69AecPJqOkLSQiaK053HCkZRVFsOXjcMPRNufalI0hrsFkudPJSswg051BhjuNeFvLzi/NhYsRPbI6JX9AB2gK+FqKHq2KI42nFDiaiyPtL6KcfK1P+4LfbwKT3tYp1CmFE/spbTrNbTkt7TuxJ60oaX8RxWaxmvPiRUf5PdAEbAJyga9gtI0I0Sm+oYdx02+PkbxN5lgIIURHkMJFF1dXV8fkyZNZu3YtLpeLNWvWMGbMGLNjRRzv+59QtWApvu17AIgdOwr3g7djS5e2ELP4tZ/y2gPsChYpmudSeJqq25wbZ3Uw1J1OpjudrMR0stxDSXMNxG6JrK19LcpCrNV4Q20Wo3hiFC4aWxc9TilwtF1B4g0VPEKPTym2NLY6r+k0K0+av/ZrP42BRhoDjab9OViVpaUQEiqaGAWO2C8oojTPObGfcl7zLJOTZ5sE73nKeXaLHauS4kkYjdRanwOglHoO+MDkPKKbyLIPZOZfrGS+ttPsKEII0aVJ4aILq6qqYuLEiWzatIlevXrx1ltvMWrUKLNjRRT/4UqqH1pB/Z//AYB1YF/cD8wm9qrRspS9EzUFmthdvTdYnCihyFNKiWc39f6GNucm2t1kJqaT5c4IfU5NSJE3gWfIKJ7EEmuNxWVSXccX8IcKHqcWUU4uhhiPG9usKDm1iNJcHDn5vMbWz3FKEcWvA/j9jTT4zSyeWEOFjFhLSzHrQN0h+sf3My1XlGpq/kJr7ZO/v0VHS7b3ZPrWflz8ux0oGWMhhBAdTgoXXdSRI0cYP348W7duJTU1lfXr1zNixAizY0UM7fNT9/waoy2kug5i7Ti/PwnnHZNQcbFmx+vS6nz1FHt2GwWK4CqK3dV78Z2mHb2PozdZic0rKYaS6U6njyNZikpRzmaxYrNYicO8FixfwH/KCpOOLaJ4A62u9besPKn311Pvrzftz6ELOV8p5Ql+rYC44GPZVUSElcMSy/WHM8l9tIgYzw6z4wghRLchhYsuqLy8nJycHAoLC8nIyGDDhg2kpaWZHStiNG7+BM89T+MrLAMgdtzXjLaQtBSTk3U9J7xVoVaPXZ5SdlWVsq92/2mHZg5MSA3OomhZTdEjJtGk5KKrM4onccQT98UndwCttTFvpFULzaS3ZwHQ29HLlExR7v+01heYHUJ0XQrFWN9wpvzmED13yhwLIYTobFK46GKKi4sZN24cZWVlZGdns27dOlJS5A05gP/QMTwLV9Dw138CYB3UF/eDt+O4crTJyaKfMTTzaHBXj+Lg51IONxxpc64xNHNQcBWFMTRzqHvISUMzhejqlFLYlTHrIuGU70XabJYoIYv1RYfJtqUx4yU/aetkhYUQQphFChddSEFBATk5OVRUVDB69GjWrl1LUlKS2bFMp5t81D73GjVPvISurQdHDM55k3B+/wZpCzkLAR2gvPYgRZ5idlWVhrYgrWrytDnXYY1lqDudLHc6mcFVFEOcg4mxyhszIURY9VFK/fizvqm1/lVnhhFdQz97MjPeS+bC5YVmRxFCiG5PChddxObNm8nNzaWyspKxY8eSn5+P0+k0O5bpGt/bhueepfiK9gIQe+Vo3A/OxjZIBt+diaZAE3uq9520q0exZ/dpe/LddldoFUVzq8eAhP4RPTRz0zVrzI4ghAgPK+DEmGkhRLvEW+OYXJ7BlY8VYq9tu922EEKIzieFiy5g48aN5OXlUVtbS15eHqtWrcLhMG/oXSTwHzyK58EVNOS/C4A1LQX3wttxfOtrJieLXPW+hpahmZ5SdlWVsLumjKbA6YZmJpPpTiczOJNiWGIGfRy9ZWimEMIsB7XWD5odQkQ3CxauahzODU+U494tcyyEECKSSOEiyuXn5zNlyhS8Xi/Tpk1jxYoV2O3ddxm+9jZR++xr1Px6VbAtJBbn/0zGOed6lCPmi2/QTXi81SetothVVcLe0wzNBBiQ0J8sd0ZocGamO4OesTI0UwgRUaRqKtrlAms6019oYMC7282OIoQQ4jSkcBHFVq5cyaxZs/D7/cybN48lS5ZgsVjMjmWaxk0fU7VgKf7icgBix1+M+4HZ2Ab2NTmZebTWHGk4dtIqiiJPCRX1bYdmWpU1ODQzg6xgy4cxNDPehORCCPGlfMvsACI6DYzpy4yNbs77wy6zowghhPgcUriIUk899RR33HEHAAsWLGDhwoXddpm+/8BRPA88R8PfNwFgHZKC+6E5OK4YZXKyzhXQAfbXHQytomj+fMJb1ebcWEssQ91pZCUODc2lkKGZQohopbU+bnYGEV1ctgRuLB7CFY/vwNZYYXYcIYQQX0AKF1FGa82jjz7KggULAFi0aBHz5883OZU5tLeJ2uX51PxmFbquARyxuH40lYTvfRsV27XfgPsCPvbU7KWoqtRYTVFVQnH1bup8bYdmuuxOozgRavfIYKAzsodmCiGEEB3BqqxMqBlB3qI9OA/IHAshhIgWUriIIlpr7r77bhYvXoxSimXLljF79myzY5mi8Z8fUXXvMvwlRluII/dSXL/4LrYBfUxOFn4N/gZKPHsoCrZ57PKUUlq957RDM5Njk0LFiazEdLLcQ+kbJ0MzhRBCiItVJjcv89Dvv1KwEEKIaCOFiyjh9/uZO3cuzzzzDDabjRdffJGpU6eaHavT+fcfwfPAszSs+TcA1vRUEh/6HrGXf9XkZOFR3VQTbPEoCRYqStlXs58AgTbnDohPIbPV1qNZ7gx6xvYwIbUQQggRudJj+jPz9ThGvCJzLIQQIlpJ4SIKeL1eZsyYwcsvv4zD4WD16tXk5uaaHatT6cYmapf/lZrfvIyub0TFxeL80Y0k3H5dVLaFaK051nicncEixa6qUnZ5SjlY37bP1qosZDjTgkWK4NBMVzoJdhmaKYQQQnyWnjY3t2wfyGW/3o7F13bXLCGEENFDChcRrq6ujsmTJ7N27VpcLhdr1qxhzJgxZsfqVI3vbDHaQkoPAOCYeBnu+2/Dmtrb5GRnJqADHKg7FBqYWRQsVFR6T7Q5N9YSS4Y77aRVFENcg4m1ylauQgghxJmIsdjJOz6MCY+VEHf0U7PjCCGECAMpXEQwj8fDxIkTeffdd+nVqxdvvfUWo0Z1n50yfOWH8fz8GRrf+A8A1owBJD48h9gx55uc7LMZQzP3sSu09agxPPN0QzOdtoTgPIr0lqGZCanYLDI0UwghhDgbY/RwbvztUZK3yRwLIYToSqRwEaGOHj3K+PHj2bJlC/3792f9+vWMHDnS7FidQjd4qVn6F2qWvAoNjah4B87/dyMJs/NQMZHTFmIMzSwLzaNoHprpDTS1ObdXcGhmljudzOBqipS4vjI0UwghhAiDYfaBzFhtJfPvhWZHEUII0QGkcBGBysvLufLKK9mxYwcZGRmsX7+eIUOGmB2rUzS8/SGe+5bh330QAMe13zDaQvonm5qruqmGXVWloV09iqpK2FtTftqhmanxKWS608lMzGBYsEiRFNvThNRCCCFE15Zs78n0rf24+Hc7UDLGQgghuiwpXESY4uJixo0bR1lZGdnZ2axbt46UlBSzY3U4374KPPc/Q+NbmwGwZQ7E/fAcYi87r9OzHG04ftIqiqKqks8cmpnuTDNWUQRbPjLd6TjtCZ2eWQghhOhOHJZYrj+cSe6jRcR4dpgdRwghRAeLyMKFUmog8AegL6CB5Vrr3yqlkoCXgTRgDzBFa11pVs5wKygoICcnh4qKCkaPHs3atWtJSkoyO1aH0g1eav53NTVPvgoNXlRCHM6f3ETCbdei7B37r6fWmgN1h0LDMo3VFCUcb2w7NDPGEhMcmplOVuJQMt3ppLsGE2uN7dCMQgghhGihUIz1DWfKrw/Ss0jmWAghRHcRkYULwAf8RGu9VSnlArYopdYDtwIbtda/VEr9FPgpcLeJOcNm8+bN5ObmUllZydixY8nPz8fpdJodq0M1rP8Az/3L8ZcdAsBx3Tdx3/8drP16hf25fAE/e2v3BXf1MAZnFnt2U+OrbXOu05YQbPUw5lEMS8xgYMIAGZophBBCmCjblsaMl/ykrZMVFkII0d1EZOFCa30QOBj8uloptQNIBfKAy4On/R54hy5QuNi4cSN5eXnU1taSl5fHqlWrcDgcZsfqML6yQ3juW0bjhv8CYBs2yGgLufTcsNy/0d9ISfUedlWVhlo+SqrL8Aa8bc5Niu150iqKrMQMGZophBAC6L4rQCNNij2Z6e8lc+FyGbwphBDdVUQWLlpTSqUBFwDvA32DRQ2AQxg/SES1/Px8pkyZgtfrZdq0aaxYsQK7PXJ2zggnXd9IzVN/puapP0NjE8oZh/POW0iYNeGs20JqmmpDcyh2BQdnltXsw6/bDs3sH9/PKE64M0Lbj/ZyyNBMIURk2HTNGrMjiLa63QrQSBJvjWPKvgxyFhVirz1qdhwhhBAmiujChVLKCawGfqS19rT+LbjWWit1+vnRSqnbgdsBBg0a1BlRz8rKlSuZNWsWfr+fefPmsWTJEiwWi9mxwk5rTeO6D/D8fDn+vcaQy7gbrsB17yysfc98hsexhkpjBYWnlKKqYnZ5SjlQd6jNeRYsDHEOChUnshLTGepOx2Xv2q03Qgghwqu7rQCNFFZl4aqGEdyweB+uMpljIYQQIoILF0opO0bR4o9a678ED1copVK01geVUinA4dNdq7VeDiwHuPDCCyNyc6ynnnqKO+64A4AFCxawcOHCLtme4Ntz0GgL2fghALYRaUZbyMXZn3mN1pqD9RUn7eqxy1PKscbjbc6NsdjJcKWRmZhBVnDr0QxXmgzNFEIIEVZnswK09S9SYnvHdXzILuCr1gymP19P6qZPzY4ihBAigkRk4UIZ7+CfA3ZorX/V6luvATOBXwY/55sQr1201jz66KMsWLAAgEWLFjF//nyTU4Wfrmug5sk/U/P0aqMtxBWPa/4txN86AWVrGXLpC/jZV1tOUVUpRZ7i4FyK0tMOzUywxQeHZmYYW5C6MxjsHIDNEpH/GgshhOgiznYFaOtfpLgye0TkL1IixcCYvszc4ObclbvMjiKEECICReo7vq8D04ECpdTHwWP3YBQsXlFK3QaUAVNMyndWtNbcfffdLF68GKUUy5YtY/bs2WbHCiutNY1vbsbz82fwlxsLYuImj8W1YBa+XgkUVp+8iqLYs/szhmb2MNo8gqsostwZpMT3xaK6XiuNEEKIyNWeFaDii7ltTm4sHszljxdia6wwO44QQogIFZGFC631v4DP6pv4VmdmCRe/38/cuXN55plnsNlsvPjii0ydOtXsWGHlK92P577lNP5jC3UO2JfTj4OzLqS0Rx1FhfdRVrP3tEMzU+L6BudRpAdnUmSQ7Djz2RdCCCFER+jKK0DNZlM2JtQM59rHduM8KG0hQgghPl9EFi66Gq/Xy4wZM3j55ZdxOBysXr2a3Nxcs2OFzdETh9j24u8p3PZvdmcF2H2loiJZA4egdg0Euz4sWEhzDgptO9q8mkKGZgohhIhQXXIFqNkuVpncsrSKvh/K4E0hhBBnRgoXHayuro7Jkyezdu1aXC4Xa9asYcyYMWbHOitaaw7VHw5tPVpUVULRkUKOUQNDMD6MM7FbbGS4hrSaSZFBhnswDqvDxFcghBBCnLmuuALUTOkx/Zn5ehwjXpE5FkIIIb4cKVx0II/Hw8SJE3n33Xfp1asXb731FqNGjTI71hnxaz97a/azy1PCrqpSijzGTIrqppo258bVw5BjDoZnXsjwrK+R6U4nzTlQhmYKIYQQgp42N7dsH8hlv96OxSczSoUQQnx58s7yLDVPFNf69P8DPnr0KOPHj2fLli3079+f9evXM3LkyM6MeMa8/iZ215Sxs6p5V48SSqr30OBvbHNuD7ub9GNxDPrPYdL2aNKPxzH0uzNxfvdqlNV6mrsLIYQQojuKsdjJOz6MCY+VEHdU5lgIIYQ4e1K46AD79+8nJyeHHTt2kJGRwfr16xkyZMgXX9gJ6nx17PKUBldRlFJUVcyemn34tb/Nuf3i+oTmUGS60hn03+PYf7YKfdCY+h13Yw6uBbdi7ZXY2S9DCCGEEBHsm4Hh3Pjbo/T6ROZYCCGEaD8pXIRZcXExOTk57Nmzh+zsbNatW0dKSoopWSobTxgtHlWlxhaknhLKaw+0Oc+ChcHOgWS12tUj052OO8YFgG/XPqp+uAzvpo/RgO2cDBIfmUvMqOGd/IqEEEIIEcmG2Qcy889Whq4pNDuKEEKILkQKF2fpsjXXtDlWUFDAlVdeyaFDhxg9ejRr164lKanjt/XUWlNRfyQ0h6KoqphdnlKONBxrc67dYiPdlWbs7BFcTZHhGkKcre3QzEBtPTW/XkXtM/nQ5EP1cOL66Qzib7lK2kKEEEIIEZJs78n0Lf24+MkdKBljIYQQIsykcBEm77//PldffTWVlZWMHTuW/Px8nM7wb/Pp13721RwwdvXwlLKryihWeJqq25wbZ40j0z0ktKtHVmI6g50DsVvsn/scWmsaXtuE58HnCBw8BkoRd8tVuH86A4u0hQghhBAiyGGJ5YaKTK7+ZRExnh1mxxFCCNFFSeEiDDZu3EheXh61tbXk5eWxatUqHI72b/vZPDQztKtHVQnF1btPOzQzMcYdLE4YbR5ZiRmkxqdgUZYv9ZxNRXvx3LsU77+2AWA/LxP3I3OIuWBYu1+PEEIIIboGheJbvuFM/vVBehbJHAshhBAdSwoX7ZSfn8+UKVPwer1MmzaNFStWYLd//oqG06nz1VHs2U1RcFePIk8Je6r34dO+Nuf2jesdmkXRPJeit6NXaKeTsxGoqaPmiZeofe418PlRPV24fzaTuJtypC1ECCGEECHZtjRm/snP4PWywkIIIUTnkMJFOxx+u5wbfnsDfr+fefPmsWTJEiyWL17hcMJbFVpFURRs9SivPYDm5KZQhWJwwgAyW62iyHSnkxjjDttr0FrT8Ld3jbaQiuOgFPHTx+O6ewaWpPA9jxBCCCGiW4o9mRn/7sWoZ3aaHUUIIUQ3I4WLs3RgzR5Klxp7ki9YsICFCxe2WfGgteZww5HQKgpjcGYJhxuOtrmfTdkY4hp80iqKDHca8ba4DnsNTTvL8NzzNN7/GEs87Rdk4X5kLjHnZXbYcwohhBAiuiRY45iyN4Nxiwux17b9GUYIIYToaFK4OAvPP/98qGixaNEi5s+fT0AH2Fez/6RVFLuqSqlq8rS5Ps7qYKg7PbSKIsudQZrri4dmhkuguo6aX/2J2mdfA38A1dON+55gW8gZrBgRQgghRNdnVRauqh/BDY/vw1UmcyyEEEKYRwoXZ2H8NVfT69J+9J+Yhu1qF3Pfm0+JZzf1/oY25yba3aEWj8xEYwvSAQn9v/TQzHDQWtPw13fwPLiCwOFKoy1kZi6uu6Zj6enq9DxCCCHO0N7+xudBB8zNIbqNUdYMpj1XR+q/PzU7ihBCCCGFi7Px2vG3GHHPKAD+UrYmdLyPozdZweJE81yKPo7kdg3NDJemHXvwLFiKd3OwLWTUMBIfnov93KEmJxNCCCFEpBgY05dbN7g5Z+Uus6MIIYQQIVK4OAtZiRmhr+cMvzVYqEinR0yiialOL+CppfrxP1L3/BrwB7AkuXHdO4u4Kd+SthAhhBBCAOC2OblpVxqXP74dq7fC7DhCCCHESaRwcRauSLks9PUtGZNMTPLZtNbU//ltqh96nsCRE2CxEH/rNUZbSA+n2fGEEEIIEQFsysbE6uFcu2g3CQdljoUQQojIJIWLLqjp01Kq7llK03+3A2C/cASJj8zFnp1ucjIhhBBCRIpLVBY3Lz1B3w+lYCGEECKySeGiCwlU1VC9+I/UvfA6BAJYknsYbSGTrpC2ECGEaA/tB90IugG0F2hs9bj5a+9nHAs+Dl1zhh+tzxcijNJj+jPz7w5G/LnI7ChCCCHEGZHCRRegAwHqX32b6odfIHA02BZy20Rcd96CJVHaQoQQUU4HTnkj7z2lOPAZx75MoeC05za0FCPwmftnIEQY9LQncktBKpf9ZgcWvzY7jhBCCHHGpHAR5ZoKSqi652mathQCYL9oJIkPz8H+FWkLEUKEgdaA93MKBmdaKGhodY9Wxzj12GnOxWvunwEAClQsKIfxmdjg45iWY+pzjhF7yjmf89HmXAeUyw5Q4uzFWOxcd2wYEx4rxnFsu9lxhBBCiC9NChdRKnCihurHVlK38g2jLaR3D1z3fYe4G66IiO1XhRBhoDXg+/xiAKd70+89TRGgsdW5X9Te0NiqHaLB3D+DkPa88T/dR3NhIabVNacca118wAbyd6uIQt8MDOfG3x6l1ycyx0IIIUT0ksJFlNGBAPUvbzDaQo57wGohYXYezp/cjMWdYHY8IbqW0FyDU1cUfMbqgdMVAs6qvaH1XISAuX8GAMS0ejN/ujf4n/XG/4uKAac5dtpCRIwUDYT4kobZBzLzz1aGrik0O4oQQgjRblK4iCJN24qNtpCtOwGIGf0V/j979x0eVZX/cfx9ZtJJAULJDKCggr0X7KJYl7Gw2FAsa8GGimWta/3Zey+suhZQV8U6WNaGa1u7oNgVFZihtwRIm5zfH+eGTEI6ycwk+byeZ57M3HLumTtzJ/d+7/eck3/daaRvPDC5FRNJZbYcqpZAbDFULar5W7UYYtV/F0PZB255X8+4IEIq9GuQVv9F/+oL+mY0U2hpU4U11lHnviIdRe/0nhzzeV+G3vs9Rt1YiIhIJ6HARSu9PyKcsG1VLSmm+MbHWfnE62Atvj49yL/8BLJGDlOzEOlarAVbHBdw8P6uDkhUT1tSM80ub9k2qhbHvTB1MgRae+HfRDOFWn0nxAcpMsDoZ1pEmpbtz2JUdDD73/gjGcsXN72CiIhIB6Iz4hRmq6pY9dR/WH7d49glXrOQkw4m99yj8OXlJLt6ImvPlkFsSf0ZEFXxz+PmtTgLwg++HuAvdNkUvkLw93TPq//6CmHBaLd4v2/Ur4GknnUiya6BpCiDYe+KjTnspgjdf/4m2dURERFpFwpcpKjyaT+z/JL7qfjKjbGesfPm5F97Kukbrpvkmok0wFqwy+o0yaibDVEnIGGLW74dk+sFHQrrBB/ipxXWTPMVNK+pgy4MRaSD2TxtIMdNrGSdtzVSiIiIdG4KXKSYqsXLKb7hcVZOesM1CynqSf7lJ5J18O5qFiKJZcvimmIsrtM8Y0k985bQ8myItLjgQ2GdIET8tOqARA/XhEJEpAsLpvfm2A97ss0/f0x2VURERBJCgYsUYWMxVj75H4pveBy7pBjS/F6zkCPx5apZiKwlWwVVy+o0v4jPiqg7bRHYFS3fjsmrne3gr5MJUauZRiGYfDXFEBFppm7+bI74Y32G3/ID6SsWJLs6IiIiCaPARQoo/+pHll/yABXTfgYgY9ctyL/mVNKHrJPkmknKqlpVTyZEPU0zVj9fAsRauJH02n1A+HvEZT4U1s6KqH5uMtrj3YqIdGl+42P/VRvz15v/JO/Pb5NdHRERkYRT4CKJqhYtY/n1j7HqqTdds5BAIflXnETWgbuqWUhXYqugamk9GRD1dVTp/bUrW74dk19PvxCFDWdFmDxlQ4iIJNm2/vUZ8/BK+n04I9lVERERSRoFLpLAxmKsnPgGxTc+jl1aAulpdBt7CLnjj8DXLYnkMuIAACAASURBVDvZ1ZO1VbWygeYXdZpirA5ILAWqWriR9DpNMurLgIj/2wNMenu8WxERaQfrZBRx3Ju5bD7xl2RXRUREJOkUuEiw8i9+YNkl91P5za8AZOy2FQXXnELa4AFJrpnUy8a8bIjFjXRUWWeeXdXy7fi6N6NfiLjsCJOrbAgRkU4oPy2X0T8PZNgt3+Evn5vs6oiIiKQEBS4SJLZwKcXXPsqqf78FgC/Ym/wrTyRrxC5qFpIo1rqgQpMZEIvrZEPYFm4oMy740FAGRHxworuyIUREurg0k8aBxRtx0E0z6RZVPxYiIiLxFLhoZzYWY+Xjr1F80xPYZStcs5BTR5J79hH4cjSs41qxlWtmQ9SXAVErG6K05dvx9XCP+jIg6hu20+QoG0JERJptJzOEox5YSt/PFbAQERGpjwIX7aj8s+9ds5AZvwGQscfWFFxzKmnr90tyzVKQta7DySYzIKoDEUtalw1hsurpF6K+viKqp3UHo8NERETa3vrp/TgunMlGz/2U7KqIiIikNF2RtYPYgiWuWcgzbwPg79ebvKtOJuuAnbpOsxBb6YILq7Md4ppn1DttMVDWwo0YLxuiiQyI+ECEyVY2hIiIJFWP9AKO/qYfu97xPb5YS5sjioiIdD0KXLQhWxlj5aNTKL5lEnb5CshII/e0UeSeeRimIzcLsRZsSdNDdK7OhFjsZUO0kMluRgZEXAeVvu5g/G3/fkVERNpBhi+DkYuGMOLGX8ha9F2yqyMiItJhKHDRRso/+ZZllz5A5Xe/A5C517bkXz2WtPVSsFmIrYgLPtSXARHfeWV1NkR5Czfi87IhmsiAWB2E6Am+nPZ4tyIiIkmXSxZ33p5P4bfqx0JERKSlFLhYS7H5Syi+5hFWPfcuAP7+fci/eiyZ+w1NTLMQa8EWN2OoziU1z+3ylm/H5NTJdqhniM5ao2gUKBtCRETE0+ePUgpXLEx2NURERDokBS5aKRoMAWDycrDFKyEz3TULGXfo2jULseXNGKpzSe1OK6lo4UZ8jQzV2XPNZhq+nuDLbv17EhEREREREWmlDhe4MMbsD9wJ+IGHrLU3JLoOFT/8vvq5LV5J5t7bu2YhAwO1F7TWZTc0NkRn3SCFLW55hUy3pjMg4oMUvgIwvrXbCSIiIiIiIiIJ0KECF8YYP3AvsA8wG/jMGPOytTYxPVzZSogtwNcjQsb2y/EVVJJ75t6kD86BqrtgYT0BCSpbuBF/A51S9migo8oebohPERERERERkU6oQwUugB2AX6y1vwEYY54GDgYSE7gonwbzDsQPFN5dPfEhaKzLCJNXz1CdjTTTMAUarlNERERERETE09ECF/2AWXGvZwND6y5kjBkLjAXYZJNN2m7r/l7g61NPfxD1NdOozobIbLvti4iIiIiIiHQxHS1w0SzW2gnAhOqXbVZw2rrQ/+s2K05EREREREREGtfRemicAwyIe93fmyYiIiIiIiIinVBHC1x8Bgw2xgwyxmQARwIvJ7lOIiIiIiIiItJOOlRTEWttpTFmHPAGbjjUR6y1M5JcLRERERERERFpJx0qcAFgrX0VeDXZ9RARERERERGR9tfRmoqIiIiIiIiISBeiwIWIiIiIiIiIpCwFLkREREREREQkZSlwISIiIiIiIiIpS4ELEREREREREUlZClyIiIiItJAxZn9jzI/GmF+MMRcluz4iIiKdmQIXIiIiIi1gjPED9wIHAJsAo40xmyS3ViIiIp2XAhciIiIiLbMD8Iu19jdrbTnwNHBwkuskIiLSaaUluwIJYNqtYGO+BUrbq/wupBewMNmV6AS0H9uG9mPb0H5sG1nW2s2SXQlZQz9gVtzr2cDQugsZY8YCY72XZcHolG8TUDfR70+iaX8njvZ14mhfJ4ox3zbnXKcrBC7aU6m1drtkV6KjM8Z8rv249rQf24b2Y9vQfmwbxpjPk10HaT1r7QRgAuiYSCTt68TS/k4c7evE0b5OnOae66ipiIiIiEjLzAEGxL3u700TERGRdqDAhYiIiEjLfAYMNsYMMsZkAEcCLye5TiIiIp2WmoqsnQnJrkAnof3YNrQf24b2Y9vQfmwb2o8pyFpbaYwZB7wB+IFHrLUzmlhNn2XiaF8nlvZ34mhfJ472deI0a18ba217V0REREREREREpFXUVEREREREREREUpYCFyIiIiIiIiKSshS4aAVjzP7GmB+NMb8YYy5Kdn06KmPMI8aY+cYYjWvfSsaYAcaYd40x3xljZhhjzk52nToiY0yWMeZTY8w0bz9elew6dWTGGL8x5itjTDjZdenIjDG/G2O+McZ8rWFROy6dMySOzisSR+cfiaNzlMTTeUzitORcR31ctJAxxg/8BOwDzMb1LD7aWvtdUivWARljdgdKgMettZsluz4dkTEmAASstV8aY/KAL4BD9H1sGWOMAbpZa0uMMenAB8DZ1tr/JblqHZIx5lxgOyDfWhtKdn06KmPM78B21tqFya6LtI7OGRJL5xWJo/OPxNE5SuLpPCZxWnKuo4yLltsB+MVa+5u1thx4Gjg4yXXqkKy1/wUWJ7seHZm1Nmqt/dJ7Xgx8D/RLbq06HuuUeC/TvYeiuq1gjOkPjAAeSnZdRFKAzhkSSOcViaPzj8TROUpi6TwmdSlw0XL9gFlxr2ejH2pJAcaYgcDWwCfJrUnH5KUFfg3MB9601mo/ts4dwAVAVbIr0glY4D/GmC+MMWOTXRlpFZ0zSKen84/2p3OUhNJ5TGI1+1xHgQuRTsAYkwtMBsZba5cnuz4dkbU2Zq3dCugP7GCMUZpxCxljQsB8a+0Xya5LJ7GrtXYb4ADgDC8NXkQkZej8IzF0jpIYOo9Jimaf6yhw0XJzgAFxr/t700SSwmvvOBmYZK19Ptn16eistUuBd4H9k12XDmgX4CCvveLTwF7GmInJrVLHZa2d4/2dD7yAa3YgHYvOGaTT0vlH4ukcpd3pPCbBWnKuo8BFy30GDDbGDDLGZABHAi8nuU7SRXkdNj0MfG+tvS3Z9emojDG9jTHdvefZuI70fkhurToea+3F1tr+1tqBuN/Gd6y1Y5JcrQ7JGNPN6/AOY0w3YF9AIyV0PDpnkE5J5x+Jo3OUxNF5TGK19FxHgYsWstZWAuOAN3AdET1jrZ2R3Fp1TMaYp4CPgQ2NMbONMScmu04d0C7AMbiI8Nfe4y/JrlQHFADeNcZMx11ovGmt1RBYkkx9gQ+MMdOAT4Ep1trXk1wnaSGdMySWzisSSucfiaNzFOmsWnSuo+FQRURERERERCRlKeNCRERERERERFKWAhciIiIiIiIikrIUuBARERERERGRlKXAhYiIiIiIiIikLAUuRERERERERCRlpSW7AiLSORhjYsA3QDpQCTwO3G6trUpqxURERKTL0PmISOekwIWItJVV1tqtAIwxfYAngXzgiqTWSkRERLoSnY+IdEJqKiIibc5aOx8YC4wzzkBjzPvGmC+9x84AxpjHjTGHVK9njJlkjDk4WfUWERGRzkPnIyKdh7HWJrsOItIJGGNKrLW5daYtBTYEioEqa22pMWYw8JS1djtjzB7AOdbaQ4wxBcDXwGBrbWXC34CIiIh0eDofEemc1FRERBIhHbjHGLMVEAOGAFhr3zPG3GeM6Q2MAibrJEFERETaic5HRDooBS5EpF0YY9bDnRTMx7UrnQdsiWuiVhq36OPAGOBI4G8JrqaIiIh0YjofEekcFLgQkTbn3bF4ALjHWmu9tMvZ1toqY8xxgD9u8UeBT4G51trvEl9bERER6Yx0PiLSeShwISJtJdsY8zU1w489AdzmzbsPmGyMORZ4HVhRvZK1dp4x5nvgxQTXV0RERDofnY+IdELqnFNEksoYk4Mbb30ba+2yZNdHREREuh6dj4ikNg2HKiJJY4zZG/geuFsnCSIiIpIMOh8RSX3KuBARERERERGRlKWMCxERERERERFJWQpciIiIiIiIiEjKUuBCRERERERERFKWAhciIiIiIiIikrIUuBARERERERGRlKXAhYiIiIiIiIikLAUuRERERERERCRlKXAhIiIiIiIiIilLgQsRERERERERSVkKXIiIiIiIiIhIylLgQkRERERERERSlgIXIiIiIiIiIpKyFLgQERERERERkZSlwIWIiIiIiIiIpCwFLkREREREREQkZSlwISIiIiIiIiIpS4ELERGRTsgYUxL3qDLGrIp7fbS3zBBjzLPGmIXGmGXGmOnGmHONMX5vfqYx5npjzJ/e+j8bY/5ujDFx25lqjCk1xgyIm7a3Meb3uNe7GmM+8rax2BjzoTFm+2a8h6OMMX8YY1YYY140xvSMm9fTGPOCN+8PY8xRLVi3us7V++PHOuueaYyZaYxZboz53Bizaz11yzDGfG+MmV1nut8Yc40xJmKMKTbGfGWM6R43fz1jTNibt9AYc1NT+0FERKSrU+BCRESkE7LW5lY/gD+BA+OmTTLGrA98AswCNrfWFgCHAdsBeV4xzwLDgb94044BxgJ31tncCuCy+uphjMkHwsDdQE+gH3AVUNZY/Y0xmwIPetvsC6wE7otb5F6g3Jt3NHC/t05z1gUYF7c/Nozb7lDgBuBQoAB4GHihOpgT5+/AgnqqfhWwM7ATkO/VodQrOwN4E3gHKAL6AxMb2w8iIiICxlqb7DqIiIhIO/KyH06y1r4VN20i0MNaO6KBdYYDU4DB1tpZcdOHAh8BG1prfzHGTAXeBc4HtrLW/mqM2Rt4yFo70BizHfCWtbb7mltptM7XAQOttUd5r9cHvgcKgSpgCbCZtfYnb/4TwBxr7UWNrWutLfbqPNFa+1A92z0COM9au4P3uhtQAgSttVFv2iDgVeBc4J/W2v7e9B64QNCW1tpf6yl7LHCMtXa3luwLERGRrk4ZFyIiIl3T3sBzjczfB/gkPmgBYK39BJiNy8SoNgf4Jy7boK6fgJgx5jFjzAHexX1zbApMi9vur7gMiyHeo7I6aOGZ5q3T1LrVrveaanxojBkWN/01wG+MGeplWZwAfA3MjVvmbuASYFWdOm8OVAKHGmPmGmN+MsacETd/R+B3Y8xr3ranGmM2b87OEBER6coUuBAREemaCoFoI/N7NTI/6s2Pdz1wYHVzjWrW2uXAroDFBTcWGGNeNsb0baJ+ucCyOtOW4Zqs5ALLG5jX1LoAFwLr4ZqtTABe8bIyAIqBycAHuOYsVwBjrZeiaowZCfittS/UU+f+uOYlQ4BBuOYmVxpj9ombfyRwFxDEZbS85DUhERERkQYocCEiItI1LQICjcxf2Mj8gDd/NWvtAuAe4Oq6C1trv7fWHu81qdgMd9F+RxP1K8H1EREvHxdYaGxeU+tirf3EWltsrS2z1j4GfIjrxwPgROBvuKyNDGAMEDbGBL1mIzcBZzVQ5+oMjKuttaustdOBp+PKXgV8YK19zVpbDtyCCyBt3PBuEBEREQUuREREuqa3gFFNzB8aP1oIrO7jYgCug8m6bgb2BLZtqFBr7Q/Ao7gARmNmAFvGbXc9IBPX9OQnIM0YMzhu+S29dZpat95qAdUjpWwFhK21P1lrq6y1r+MyTHYGBgMDgfeNMXOB54GA1yxkIDA9rjzqeT69zmsRERFpBgUuREREuqYrgJ2NMTcbY4oAjDEbGGMmGmO6ex15vg1MNsZs6g3zuSNuFIz7rbU/1y3QWrsUuBW4oHqaMWYjY8x5xpjqDiwHAKOB/zVRv0m4pie7eZkOVwPPe5kSK3BBg6uNMd2MMbsABwNPNLWuMaa7MWY/Y0yWMSbNuKFhdwde99b9DBjhDVtqvGYeQ4BvvccAXHBjK+AkYJ73fJbXl8b7wKXGDSW7Ma5pSNgreyKwo3HDxfqB8bjMle+b2BciIiJdmgIXIiIiXZB3kb0TLoNghjFmGa5vh8+paXIxCjdiyOu45hcTccODntlI0XcCsbjXxcBQ4BNjzApcwOJb4Lwm6jcDOBUXhJiP65/i9LhFTgeyvXlPAad56zS1bjpwDW4o04XeezkkrqPPx3HNO6bi+tG4CzjFWvuDtbbSWju3+gEsBqq819XveTSwLq4pzhTgMmvt2169fsQ1PXkANyrKwcBBXrMRERERaYCGQxURERERERGRlKWMCxERERERERFJWQpciIiISFIYYx4wxpTU83gg2XUTERGR1KGmIiIiIiIiIiKSstKSXYEEUGRGREREREREJPWYphdRUxERERERERERSWEKXIiIiIiIiIhIylLgQkRERERERERSlgIXIiIiIiIiIpKyFLgQERERERERkZSlwIWIiIiIiIiIpKyuMByqNFM0GGrxOoFIuMXrVq8jIiIiIu1D52btozXnyy2lz6NjaOl3IRU/10T/TtS3veaWq4wLEREREREREUlZClyIiIiIiIiISMpS4EJEREREREREUpax1ia7Du2t07/BtpKINnsiIiIiIiIiAIFI2DRnOWVciIiIiIiIiEjK0qgislY0qoiIiIhI6tG5WfvQqCJSTaOKtO/26lLGhYiIiIiIiIikLAUuRERERERERCRlKXAhIiIiIiIiIimrw48qEg2GtgBuBLKBDOA5YBJwD9AnfbuNd88Zsz85hw8HYP7QE/H37716/fxrTiV944GJrraISIdRVFTEvHnzWrxe3759mTt3bjvUSEREREQ6iWaNKtKhO+eMBkMFwERgZCAS/jUaDBlgX1zg4rZAJPyqXVVmF4+5grR1i8gYuin4fRROviGp9RYR6UhaE7RYm/VEREREROJ19KYiI4BXApHwrwCBSNgC3wI5gUj4VQCTnUnumYex8tm3k1hNEREREREREWmNDp1xAQwAZtWZ1h/4M36Cv18fquYuci9iVSwaddHqed0nXIy/sKB9ayki0oH17du31U1FRERERETWVkcPXMwCNqszbQ6wTvyE2JwF+IoK3Qs1FRERaRH1UyEiIiIiydTRm4pMAQ6MBkPrx03bGCiNBkP7A9jSckrufY7sQ/dKSgVFREREREREpPU6w6giW+JGFcnCjSryLPA0cDfQO327jXfPGb0POaP3BdYcVSTvgmNcp50iIiIiIiIikkjNGlWkwwcumqHTv0ERERERERGRDqjjDIcaDYYmAEMCkfAw77UFLg9Ewv/nvb4MuDoQCZtoMDQMGBOIhE+KBkOPAlsCJbhsi+eAW7zRRYgGQztjDL0/+idp6xax4qGXKH3tY6qWraBq4VLS1u+H6ZZNt1NHsmryVLrfeha2opLi6x+n/MsfAMjYekPyLjkOk57G0vG3UzFjJr3+cyfGGIpvmYR/UJCcUXsmdH+JiIiIiIiIdBVJ7+MiGgxl4IIPxdFgqLpTzd+B+E4p9gJmNlDEmYFIeDdgD2Bb4Li4eUd3O+kgVr0wFYBuJx1M4eQbyL/6ZDKHb0/h5Bvo+fgVtQoruedZMNDrxZvo9eJN4DOU3PtczQLWUvb6/1r5bkVERDqOoqIijDGrH0VFRcmukoiIiHRBSQ9cACOAl4HHgKO8aTFgejQY2iYaDG0LTAOqGiskEAmXApcBRwNEg6F0YOu8S46n7J0vml2ZVS+8R955R61+nXfeUax6furq17njDqXk3ufoAk1sRESki6s7DG5rhsUVERERWVupELgYDTwBvAIcEDf9SVwg4yjveXPMAvp5z/cDXjWZ6aRvuh4V039pXgllFZicrNUvTU4WlFWsfu0P9CJ98/Upe/3jZlZJRERERERERForqYGLaDBUAOwCTABeAgZ6o4QQiIQ/AbYHtgtEwp82s8gBwBzv+VHAPouPupyKb39l1eR3m1dCRjp2Zenql3ZlKWSk11ok98zDKbl3srr9FBGRTq1v376NvhYRERFJhGR3znkocH0gEr4HIBoMDcdr6uF5pLkFRYOhTOAq4KloMJQH9A9EwrvjhRcW/uUcbCyG8fsbLSf7kN0pvuNp8i85HoDiO54me+QetZbxB3uRvvkGlL7xP7qd9tfmVlFERKRDmTt3brKrICIiIpL0piJHA6/Hvf4AOAivXoFI+LFAJPxYE2XcHQ2G3gf+C3wD/AsY6b1eLW3jQZS/P63JCuWeeRhUVLLw4AtYeMgFUF5B7rhD612u8tfZTZYnIiIiIiIiIq1nukAnk53+DYqIiIiIiIh0QKY5CyU740JEREREREREpEHJ7uOilmgwNBCYCRwbiISf8KY9DOwFFAO7BiLh5dFgaBDwDK5jz2XAJ0AG8EEgEr7AW28qMKZo9sssv+g+Kn74A3wGf7/e5IzZn5JbJgFQ/tVPZGw9BABfn55kjdiZ7NCuACw+5kpyxx3Gyqf+Q87ofckYummC9oSIiIiIiIiIQGpmXHyJ67SzusPNAUAMuB24zlvmbmB8IBIuB+YEIuFhgUh4Z2C7aDC0cXxhZVO/xFbG6PXyzfR68SYKrjmVzJ02p3DyDRROvgF/UeHq5wXXnELJHU9TVbySVS+/jz/QS8GKehQVFWGMafBRVFSU7Co2S1u9j86yP1KR9q2IiEgN/V9svab2XWv2qz6PxFqbz7Cln48+WyeV9kMqBi6WABXRYKgPEAJeBQhEwv8CNowGQzcAswOR8IfxK0WDoXQglzptZExOFrGZESp+noW1Fl+PvAY37CssoNvYkSy/bAIl9zxH3qXHt+kb6yzmzZu3VvNTRVu9j86yP1KR9q2IiEgN/V9svbXZNw2tq88jsdp6fzZWnj5bJ5X2QyoGLgCeBQ4HjgCejpt+GnAqcFHctH5es5DZwKeBSPi7+IIyd9yM7MOHs/zi+1iw40ms+OdLjW445/DhVM6M0O3EA/EV5LbBW+l8+vbtu1bzU0VbvY/Osj9SkfatiIhIDf1fbL212TcNravPI7Haen82Vp4+WyeV9kNK9XER52XgLWBJIBKeGw2GAAhEwr9Eg6GFgUh4adyycwKR8LBoMNQf+Hc0GMrwmpCsljN6X3JG70tV8UoWjbyQzH2HkrZuw2ktaYMCpA0MtP276iTmzp2b7Cq0ibZ6H51lf6Qi7VsREZEa+r/Yeu2x7/R5JFYi97c+WyeV9kNKZlwEIuFVwAvAfS1YZzbwBnBS/PTY3EVUFa8EwORmY7plQ+cfAnatjR8/nvHjxye7GiIiIiIiItLFpWrGBYFI+JZWrHY/8F40GJpQPSEWXcjyKx4Cn4FYjKx9hrYqm2L5lQ9h8nIA6HbCgWTtv2MrqtdxfP3118mugoiIiIiIiAjGdv7sg07/BtvDsGHDAJg6dWpS6yEiIiIiIiKdlml6kRRtKiIiIiIiIiIiAq1sKhINhrYAbgSygQzgOeD0QCS8gTf/LqAKuAWYhAuQ+ICzA5Hw5w2UORP4A8gE/heIhM+JBkNXAr8EIuGJ3jLHA/0DkfA10WAoD7gD2ADwA68ANwUiYRsNhkYCFwJl6dtuSMFt40kfPIDoen8lY+sh2FVlZB24G7mn/ZWl428nZ/S+ZAzdFIDiWybhHxQkZ9SexBYsYfmlD1C1cBm2MkbOmP3JOXx4vfskNn8Jy8bfji0rx5ZXkBXaldxTRq4uv+SuZ7ClZVT+Mhtfn5748nPIGrELFdN/oWLGTHz5rhlK9uh9yTl0r9Z8LB1GUVHRGkPn9O3bN6U6fxGpS9/b9lN332q/SjV9N0Qk0fT/XiQ1tThwEQ2GCoCJwMhAJPxrNBgywL5x8+8EbCASHu8te1ggEp4fDYY2AR4Edmug6Jg3OogBXo8GQ011InEH8EUgEj4xGgz5vTod7f29Edg2EAkX27IKa2MxAPxFhRROvgFbUcnC/c4me+QejW5g6Rm30O2UQ8gavj12VRmLx1xB2rpFq4Mc8VZMeJGsvw5bHXSoWry81vyek65yZdYJlCwdfzsF15xSb5mdVX3j/XaVsZCl49L3tv3U3Y/ar1JN3w0RSTT9vxdJTa1pKjICeCUQCf8KEIiEbSASfgMgGgzdAZhAJHy2N29ZIBKe761XBlQ2VXggErbAV8C6DS0TDYZ8wJ64zjgJRMIx4ErgOG+RGLBHNBjKMpnp+HKyaq1v0tNIG7IOscjCBusRiy50mRnDt3frZGeSe+ZhrHz27XqXNzlZVHz5I7F5iwHw9cxv6q2KiIiIiIiISBNaE7gYAMxqoKwjcJkQtXgZEXcB1zZVeDQYygD2AL7zJl0aDYamRoOhqcBF3rTewHwvyFHtD6Cf9/xw4EjgxyUnX0fVkuJa26gqXknFjJmkrVsEwLJ/PMiiURexaNRFrHrGBSZi0UX4+/WutZ6/Xx+q5i6qt965p47E1yOfxWOuZMFeZ1D2fvNH5Yjfftl7XzV7vY6qb9++zZomkkr0vW0/dfej9qtU03dDRBJN/+9FUlNr+riYBWxWz/QqXMDgpWgwtG8gEo7GzXsQeC0QCb/VSLl+LzhhgKcDkfA30WBoFHBt3T4ugIVAn2gwZOKCF+sAcwACkfA3wBiA4tuesiseepm8vx9NbO4iFo1ysY+880bjKywAqNVUo/iWSa4yRYXE5iyoVcHYnAX4igrrrbzJySLv70eT9/ejqfxlNouP/z/6fPBgI2+3RldrKqI2gtIR6XvbfrRvpSH6bohIoul3RyQ1tSbjYgpwYDQYWr96QjQY2gcgEAm/j8uKmBINhnp4824BooFI+J4myo0FIuFhgUh4j0AkfGdjC3pNQ94Dxnrb8AGXA094rzeqXtbfpwfYKvfc6+OicPINZB/SeP8W/mAvTFYGpe9+AYAtLafk3ufIbqDjzMqZEar70vD16g6mWaO6iIiIiIiIiEgjWpxxEYiEl0WDoTHAvdFgKAs3qsizcfOnRIOhfFzw4gLgbOBDL5tiQSASPqxtqs7ZwJ3RYOho3KgiYbzABXB9NBgqAsoy996e7rePb9UGut9zPsv/8QAr7n7WjSoyeh8yd6wv2QTKP/6WlWfcjMnKxFZUkn/Fic3ezrJ/PLh6VJGsEbvQ7YQDW1VfERERERERkc7GWGubwSp34gAAIABJREFUXqpj6/RvsD0MGzYMgKlTpya1HiIiIiIiItJpNaupQmv6uFgr0WBoL1yzjnhXByLhdxJdl9Zaetattfq/8PfrTfe7zktijUREREREREQ6pxYHLqLB0EDccKXTgFzgNlxfE2MCkfDsaDB0HrATblSPAuB2XMeZ6cCPwCmBSHhY3TKjwdCS+DIDkfCTXvOSMYFIeLa33KPAQ4FI+INoMDQYuBPohuur47pAJPyat9xVwH5AecbOm1P43PWUfTSdpaffTNr6/bCrysi76Dgyd9+K+TufTJ+P/rm6LotGXUT3u8/HH+xF+dc/UXztoxCrAp8h7x9/I2OrIfUGKco/mcHyax/FpPuxZRXkXXIcmTtvwfydT6bn41ew7ELXxUf5Vz+RsfUQAPIuOIalZ92Gv3/N6CX515xK+sYDW/qxdChFRUW1xsPu27fvWnWEFF/e2pYlIiIijv6/iiSejjuR+rU24+KLQCS8t9eXxXSgOrBwLl7QIhAJV0aDoYnAfYFI+BVv/u7eNiuaKjMaDD3T0MajwVAa8BxwfCAS/ioaDBUCb0eDoR+BTGCXQCS8I0DVkuLVTUUyh29P91vPIjZ7PouPvYre79zb4BusWr6CZWffTo+JV5I2oC+Vs+axZMyVFL5yC778bmssv/zqh+kx4WL8/XpjYzHsitLV89I26E/h5BsAmL/zyaufA+D31X7dBcQHLep7vTblrW1ZIiIi4uj/q0ji6bgTqV9rRhVZLRAJLwfmAoXAeGAXaoIWQSC/OmjhLf/fQCS8qgVlNmQoMCMQCX/lrbMIuB8YDZQCRdFgaNtoMOTz9chbY2V//z61Agv1KXvrUzL335G0AW7c5rQBfcncbyhlb31a7/ImJ4uyD6ZRVbIS4/fXG9wQERERERERkZZZqz4uosFQP6A3MAc4ARgRiIQrvdkDgFlrUWZ1JxLPRoOhMu/5RsBDQH/gzzqr/gFsGYiEZ0aDoUuBa4BNl1/7KPmXHl9rwYpvf8NXmO9exKpYNOqimnkzZrrJkUX4+/WutZ6/fx9i0UX11rvg9vGU3PlvSu78N/4BfSm49SzS+vdp+g3X2X73CRfjLyxoer0OrG/fvms0FWmr8ta2LBEREXH0/1Uk8XTcidSvtYGLbaPB0Lu4ETvGApcBhwOPRIOhUYFI+Dtc0GKd1pYZiISrosEQwGF1+rgAFyg5uM7663jTCUTCLwEvRYOhzMoZv5WWfTgdDJS9/RmLDr0Yk5FOwU1nurXqNNWoDiL4AoVU/lQ7NhKbs4D0Det/S2n9+9D9ZlfmymfepuTmiXS/89ym33UXbCrS1m311PZPRESk7en/q0ji6bgTqV9rm4p8EYiE9wxEwnsFIuG3vWk/AGOA56LB0MBAJBwBlkWDoQOrV4oGQ7tGg6HsFpTZkP8Bm0aDoa28cnsCpwFPR4OhntFgqA9AIBIuM93zoKoKcH1cFD53PT2fvJr0zdZrdANZw7en7PX/UTl7PgCx2fMpe/1/ZA7fvt7lK3+uSS7x9+kBVRqFVURERERERGRttelwqIFI+ItoMHQ68Eo0GNoHOAa4zRtpJA34CfikDbZTGQ2GDgfuiAZDOYAf+EcgEv41GgwNAh6NBkN+wOSccCAZu25J+cfftGgbvu65FNw+nmXjb3dBCJ+h4Pbx+Apy611+xSNhKqb/jMnOdMvecEbzNlSnqUjeBceQMXTTFtVVREREREREpLMy1nb6zIBO/wbbw7BhwwCYOnVqUushIiIiIiIinZZpzkLNyriIBkMTgCGBSHiY9/oqYD+gHIgFIuE9o8HQMOBdYBtviNKBwEOBSHjvOmWdCxwEZAHrA+nA98BM4MxAJLwoGgz9EoiEN4hb5yng34FI+EXv9evAVcBnwOXAMG/RZV4Zv0eDob8BJ2XsuBm+3t3Jv/ZU/L26E5u7iKXj74CKCmx5BdkH707aBv1Z8fhr9HzkHwCsev5dyj/9jqy/7ELplA8ouHHc6vpXLSlmyUnXUjFjJiYzg7QN+pGx61aUf/A14Dr+TBuyDiYjjW4nHUTJAy/S458X4+/Tg/Ivf6T4ukddBoffR/5lJ5C+xQZUzoywYJex9HjscrL22QFbGWPBnmfQ5/0HmvPxiHRp8eOdV9O45yLNp2NIRCRxkvWbq9966eiaDFxEg6EMYEtgfjQYWgfoBuwSiIR39Ob3jFt8Oi6QMLKh8gKR8G3RYOguXJOR/QOR8BdeOZs3Up+zgTejwdBbuKDHr4FI+ONoMPQPXOBjj0AkbL1mIhleEGUMMLzw+RtWlb7xCcvOvp2ek65ixYMvkHPE3mSP3AOAqsXL8fXMZ+Wz71D62sdk7LQ5Jfe/QOHk66n4+uc1KuLrkUf3e85n2QX3ULWkmJ5P/h8mMx3OORKAhQdfsDpQAVDywItuO0tLWHbOHfScdBX+/n2o/GMuS469isIptwKQNngAJXc/S9Y+OzT8YYjIGuob41zjnos0n44hEZHESdZvrn7rpaNrTuecI4CXgceAo4BSoCgaDG0bDYZ8gUh4cdyyn+ECB1s3UeYOwPfVQQuAQCT8TSASrvfoCUTC84G7gDuB84GLvVljgCsDkbD1lpsZiIR/Ao4Drg1EwqUAWfsNpWrxcmILlmCysyj/8gdi85e4HdDTDYuaf/VYim99kuWXPUju2Yfjy+/WYOVXvfAe2YfuRdZ+O1L6ZvO67Cj9zydkjdgFvzdEatq6RWQO356ytz8HwN+vN2kbrkPpm582qzwRERERERGRrqA5gYvRwBPAK8ABgUh4JnApcA3wezQYqjuW51XAFU2UOQA3XCoA0WDo7Wgw9HU0GDqkkXUeATYFbgtEwsu9aRmBSLisnmX7A7XGMvX3701VdBHdxh2KL68bi4+6nAXDx1H20XQ3v7CAnGMPIDZvMdmhXRutfNnbn5G1345kj9qT0pf+28RbdWLRhfj79a41zd+/N7G5i1a/zj37CErueqZZ5YmIU98Y5xr3XKT5dAyJiCROsn5z9VsvHV2jgYtoMFQA7AJMAF4CBkaDoS0DkfBLgUj4AGAwsFU0GNqzep1AJPwprslHY1kXs3DBi+p1hgMvAvUP2eGWscAv3qNaeTQYyqxn8TnAOvETYnMW4AsU4svJIu+CMfR+6266P3Ahyy66b/UyaQODpA0KNFJtqPjxDyp/n8uSE65h2fl3Uf7FD1QtLWl0HQB/USGxOQtqTYvNWYC/qLBm+/37kL7xQMqamcUhIm68c2ttrYfaa4o0n44hEZHESdZvrn7rpaNrKuPiUOD6QCS8fyAS3h84ATgjGgz1AfCyHRbXU85VuL4uGvIpsHE0GNo2blprhmadCFwZDYYMQDQYWjcaDA3BZYhcHA2GsgBK3/wUU5CLv3cPKn+bg43FAJdlYUyzOjFdbdXkdym45Ux6Pnk1PZ+8mtxzRlMa/qDJ9bL22YHSKR+uDl5UzppH2VufkbnXdrWWyz3rcErufrZFdRIRERERERHprJoKFhwNjI17/QHwKi7oYHBDl3wBvAPsUb1QIBL+LBoMzcGNHLKGQCRcGQ2GDgVujQZDhcBKYAkuswMg6HXEWS1U3V9FHTcClwHvRYMhcKOKjAtEwm97HXW+veivF+HrVUD3u84FoPyjb1g57hZMdia2IkbeFSc2ugNK3/qMysMvBVwHmmX//Zq8c0avnp85bBuWnX07OWP2b7QcX898Cm49i6Vn3eoGaPX7KLjzHHx5OVQtXLp6OX//PqRvvj5lH33baHkiIiIiIiIiXYGx1ia7Du2t07/B9jBs2DAApk6dmtR6iIiIiIiISKfVrCYQrWme0SLRYOgoamdtAJweiIS/a+9ti4iIiIiIiEjH1u6Bi0Ak/CTwZHtvRzqHg98cw+LypU0v2AWlV8Ck0+GGcfDllmtX1tkTwB+D205rm7o1JHsVnPEIbPYD5JTCybfAsoL23aYkT3O+V2313bvrEnh7N3jpAPd6wnkweQS8sdfaldsa/7gN5vWGfx6T+G3Ha8vfiJbomdGdl/aZ2KJ19FvfsAvvguJcuO+EZNcEnjkZbj0VPtm26WVbqqnvjb4ja2rNsSYi0lm0e+BCpCXa6iTlmZMbnz91p9Q4KWyJinR34b8ip/nrbPktXHonHHM3lMX1ODNhTDNzstbS3v+F9X+Hf1zkTsSX5619mYkIupgqV/dhH8GACFT5YG5veH8ovLV7zb7MLYFRU2D7r6DnUijJgW82hmcPgrlxI4wdNRkOeX3N7cwvhHHegNI7fQZ7fQCD/oT8Erj0Ivh5/cbruc9UOHmSe15lYFUWRPvA15vDa3tBcdz+rq7DG8Pg4aNrpgejcMflcN6VMKtf7fLHPu7qdO/f4P2dmrHjmqG9vnvnXQllGe1QcAfSmt+IttCa3+2WrnP6I5BXAjee5V4f9jIc9op7XmVgcXeYtik8+VfYZjqc8Wjj5V15Pny3oXu+86dwyGswcHbj61T/36jvYn7dP93xtfFPkLcCluXDn0EXXPt8K7DNGXw+BbXn96mp74CCFmvSPhGRrkyBC+mUTr6l5vm20+HUx2tPK0+vfz1/JcRS8KiorldbZSusStCFTdF8mBWE2f2aXjbRGvysLYyfANt84+7gPzLaBVzWmQMHvA1LusNHO0BeMVx7PZRnwMNHwZ/9oHAJHBqG66+FK/8OfwyoKfb3/nDt+Nqbqoq7mMkqgx82gA93gNMfbf77KO4G514FxkLOKhg8Ew5+HYa/D5dfAPP61Cxbnu6mh/epPb0+mWWw8+fw0v4w/IO2C1y013evuA2CYp1BV8pomlPkAhC+KhfwO/UxF0C85TT4erOa5c58GEq6wb+OrJlW0q3m+fZfw2db1z4+W/J/Y5tpcN4D8M1GcP/xEO0LaZUw+Df466vw60BY3LMt3nHidaXvk4iIpLYUvEQTWXvxJ1vVd4vqnoBV32m+7RTY/13Y4Dd45Cj4Ykv421Ow0S/QbSXM6wUvHgAf7Fiz7jXXubvhMZ+7I12ZBu/uAk+NZPXt5J0+g1FhKFrgTnh/HwC3nQoluW7+dl+7+QPmQGkW/Lg+3HoaVPld2vtre0Fwrjup/mJLeOC42mng1fW/fSyMeAsG/unS1R85CmZs5OZfeqfb1hNnur9v7u7S2etmLaSXwzHPwc6fQVYp/LYuPHFYzR3/6syNK8+HY56F/lF3of7AsTCrf/2fwTXXwZCZ7vkzJ8PXm8J142HYh7D/OxCYB2WZMGNDePSI2p/PgDlw9GTY6Gd3Qf5Hf/f+h30Eu3xWUybUZCYM/BOO+7e7cC/LgE+3hseOcPsWat7zHwNcpkKVD06/ac167/4x7PQFXH8WfLV5zfQFvdznkLPSvR4zGfKL4axrYXm+m7aoEG44E266Gk57FC66rGb9mL/xi4B3d3V/ey5ueJn6WFNT7tLuEAm4937zVXDiJLjunJplZwVhZTYc9Tzcfmrj5e70ubtj/OIBMOF8KJpXO4ukMYe9BPu+BxnlLhDzyGio9C766n73mnMsdV8KpzwOm/8AS/Ph34esuc34piLVTSbuO94dZ1t+B0sKXJkfb1+zzoY/w4lPuuNsVj947kC48J7Gs12ySuHkiS7LZlW2CwLVlVcMxz8NW38L6ZXw/Qbwr9EQLXLz95kKR7wE9x/njqfCpe74uOcE2G6am5dXAp9uA/88umbfbTsNDn6tJgvo50Hw6JE1n0vdpiLVvxE3nQF/ecsdG/N6ud+I6myDjizmq/nuL+kBrw13+w5qH2sVae43uL7jz18JW33rAnTN+b9RV2aZCzR+uTncenrteZEAvLcLjXYRnlEGJ02CHb+E0gz3HurqtgKO/7f7/DMqXIDz0SNqAsJ7fAgnPuX+lx33DPRa7DK/7j4BtvjeHe8FxfD5lvDgMVDhZSZt+S38dYr7PgH8MhAeOxLmBGq2HZ9d0nsh3Huxe73Pe7Dhr7Cg0AWEvtmk8f0kIiKythS4kC7vqOfdRfrv/d0FQkY5/LwevHCAuzDZ+ls441/uBO3HwTXr7fkhvLwvXHIJbDATxj3iTvw+2wZ6LYKzHnInl19u4S52Nvy1Zt3tv4JzH4DnR8A9J7q7c1t96y7Sqx30hruQeu7Axus/5jl3gT474AIYF94D465zd/3uPAnOfsi9Lstw2QH1Of7fLr367hNhYU93x/6SO91Fefyd7CNfgMcPdxkIJ05ydzIvuKL+Mq8/G054EnosgztPdhek4C5anxrp6lew3AVMznwYrnEjFtNrEVx1kzvxvvo81/xhyG/gr3IXpv3mujusDxzrli/p5vrSuPQO+G4IXHwp5C/37pY+AXfHNRvacoYr75pzGm6usOsn8Ee/2kGLeCtzwBdzF/bv7lITtKhW5Ycpe8Npj0Ngbs3FaiKtynYp6ke8BNkra2c5TBoF110H68+EXwc1XMZe78P7O7qyPt/SBRWeHNX0trec4S4UrzoPei92AZwVOTDp0IbXaexYAncs5a5wZVamwd+ehu7Lmq7L4S/DxFHu+N7vXdffyveDXYAnZ6U7Vj7f0n0/ey9yF31N+dvTLqB20zjXHODIF1yd5/WuWebMh9yd/xvHucDZ0ZPd8XTO1TVBiOxSV6c7TnEXv+ff7x5lGXDzGe79nX+fCyK+sadbJ6McXtnPBQ2zSuHwV+CCe+H8K9z3riGjn4eJh7nmToe/7DKKzrjBNS3pTMrTwWfdb0VFM9fZ9EcXzPt9ndZtc4sZrmnXy/s1slAjbaOOec4FF249FRb3gENfgY1/dsHHaqf/C4Lz3PeiJAdGv+i+T2dfUxOESKuE0Jtw10nu+Xn3uyyQinQXEM8rcdP2mwrhfd06WWXw6t4uMJxR4QLpF97tvqeNZR4e+SJMPBQeOto1lRs/AU6/oXZzRBERkbbWQVtdirSdKfu4NOEFvV0zgAW93LQ/1oH5vd1Fw5db1Nzpr/bbOvB8yN3t/GBHlzGx+Q9uXs8lLgjxv21debP6w1t71GRbjAq7/hKePcjd3fpjgOtkMP5kcfomrh7z+jSe1v/acHdnNhJwJ5LLc13/DNZXkw69LM/dOVyVveb63Va4i9LHD4dpm8GcIDx4rLvA3+e92ss+NRK+H+Lq/PwI1yY8r7j+eq3o5gIllV4TlxVeXd7e3W1nfm93V/vh0e7EvbqcA952/WHceTL8NtBd+L+3s7sjXpblLk4qvDKXFbh9tsdHbn/fc4JbbsbGbl/s8hkUxmUwrMqGCce4O5V1+3OoFphf+45jfXoudSf9sxtYbnbQ/Q3OrZk26E94fFztx+mPNL6dtTE76C7ietfJ4PhtIHy8nbuYbkgwCuv/AR952Qn/3Qn2+NgFbJpSkQ4PHO/28Vebw9OHuIwmf2XD6zR2LK0zGzb70aXg/7w+zFzXZVJklTddl3d2cc165vVxfR/4bE0AcY+PoNLvvutzgq5fkEYvPnHHyu4fu2Pl243dd+jeE1y51QbMhq2+c/X9cbA7tu86yQXpdvqiZrn0SphwrLtg/nGw+0w2+Qnu+5sr95tN3O/Opj/UrPPx9u63al4f9/t03/Eu+2ngrMbr/fL+7rOIFrnPo/tyl9XUmQSjLsvn50E1WVbNsf3Xrg+KVm93nvsbiQtQDphd+zjf9X/1r5tZ6n57J45yv4mz+rnP1MYFOormwfbT3O/W90Pc/5K7T3CdHe/2Sc1yaTHXZG3muu44+XCo6xT5vuPhz/4uC+/zLWt/nz7Z1j3m9nXL3Pc36LPQBeIaM2Vvl302ty88OdL16dHUd1BERGRttWvGxW5TQn2BZ4GtgQnvjwif157bSyW3fHMPvbIKOX7w6GRXRZrw67q1X/tiLn12xy9dACIt5u5gxbeZBneiF29Jd3dxAq5N8w+D4c7LYNomLgjxyTZe4MLCurPdyV9jflu38fnVflqv5rn1uW33jzZvXXD9UPirXPpxtVga/DJozXLi3/OS7u5vfnHL+hdYf6a7q7juHHchWJ1l0muxK2fQn+6ueGN3kOvqN9c1xamIyyj5YQN3QdkvCou89uV/9G+6DxPTSFr32pgdhJvrpJK35AKrxWytP7U8NRLuuAy2/sY1Hahr+Afw1WY1waZpm7j9ss037iIvMBduvKZm+X8fBFO8u7gz16l9J/+n9SCz3F0QNZR90tix1C/qAlUz4+6Iz+3rAnRN+SOu3Mp0d7d6dblzXVAh/vvwcyMZKOCaN/mr4Ke4ZiQrc2B23Pvq79X314E100pyXTCsfyRuvWxYWFjzelk+LOrhyoufNvDPuO3PdVk06//u7qD74o6d3+K2V1f8fljsHbcFDQQcO5L+URcY8FW53+jvhrhAVEtsO81dsLelSBH8/XL3/OarXJZZfYoWuABW/PepLMtl1FTrF3Wdj8b/zq/KccvEf5/K02ofX0vzYWlB7d/mZfm1f9P7znffpw1mut9xn3WPXovhx0be3x/1/B/oDN8nERFJbWsduNhtSuh3oC8QA1YArwHj3h8RLgHGAguB/PdHhNvpcmB1PY4HHgZWeZMWAFMn7fEg6+QmvmfA8zcfl/BtSuuUZdZ+/dcpLp320SPcxWZpJhz7jDvBjBerc2FtjTuBBncxdNV5ronDFjNg36nuDvdlF7kO5ZqjNLPpZdpb3YO20r/mPF8Ljuycla5JxxdbwF0nuiYnPZfC5be5C4/2EH/3sjmjTkT6uouFxiwpcJ9P/IVDvOrp0bg+ISrSmu4Qsy31j7o+AOIvjqvN7w1v7uFGGrljbO15/kqXVZBXAk+dUjPdWNex5+dbwfxeNRdm4DJk1kZjx1Jblotpv8BUc8R/Fyvrvmfq2Q/EHV/WNQ+YU+SaSS31LhhvvaLpY6dWuV4dTBvs32Sb29s1Sasy7gK6soVNX9b73WVOfTek9XWIeMd4cG5Nvyix+GO9HYdviv8+1RfoXeM7Vuf7f+HdrnnKP8e4vzEf3Nba71MSjysREeka2qqpyIHvjwjnAtsA2wH/8KavC3zX3kGLOB979SgA9gZWnfTBeH4r/j1Bm5fOYKNfXPviD4e6O7Lze7k7rS1lffDjBvDswXDRP1yzjR0/B4y7Y7X5921T38G/1Tw3Ve5ubHVTh+oT18YuAuf2cSesG/1SM81f6e7CVTd5aCsDIpC70vWz8MMQ17yl+g54tZnruDbeDTVLqPSv+X7mFLlU5fS45gMb/eIuaCIt7GPiw6EuG2Trb+qfn7PSXZh8vK1rPpFfp/6+mGtr/ts67v0lQ/YqF2SYvkn9zYMAngu5fh32+Lj29O2mub4ULrwMLri85nHrqa4flh5Lay7Mqh/xWQIDZ0FaXAcDg39zAaP59WR2NMecgAsaDorLPOg73/UrsDbmFMG6s2o3Ydng98bXifZ1x0r8MZe9EvrHNQma7dV3/biycktcMKyhpkXN0WMp9F0Ik0OuKdScgMtYakngsLOp9L6HC3q3PGgBrpnIV5u3LLurrumbuuyfka+1fN25vd3vWfz3KbOsprNMcJ+zz7ogeLXsVW6Uo7X5PuWWuO/tC39xzZLmBFy/K2nNaA4mIiKSDG3aVOT9EeE5u00JvQZsttuU0KPA0YDdbUpoPHAIsBy4E9gYlxkxGTj3/RHhcoDdpoQscAZwDlAE3AE8CjwBbAa8DoypXr6ResSAX4HTL/jsqtMe+elJrtn2EgA+mPcJD/7wGAtLF7FB/iDO2+wMBua5MQsPe+cERq47gjfmvEtkZZThgd0Zu9GxXDftDqYv/o5Nug/h/7a9mLx0d3vxsi+uZ/qSGZTFyr2yTmdQnsvvv3ba7fTJ6sXJGx7DV4um839f38rhgw5m0q+T8RkfYzc8lhED6umOXpIu2tddtA7+1V2Qhd6Ensvqv3PdkI1+chfO0zdx/Uts8LvrpLI6EPD8CDjnQXcx9/H27kJ8q2/h1eEtH471gHfcHfQ5RfCXt13K71u7u3kLvIvFbafDtE1dnxN1M0xWdIN3dnWjG6zMrumcM7u0ppy2Mr+XO1H/f/buO7zJcn3g+DdJV7p3Szd7bxBUqgjuose9j9tz3Phz73lEz1FxHgfO417gKi4EwYqyl4wCHdC9V7rSrN8fT5I2pSOF0sX9uS4u2uTNmydpmua933uctkI1j4zPV+NDW/pxjipVmP+mmmjR4KOCKPvjVQ14aTgkr1G133W+6t+qY1STuJveVQd2gQY1LWL19OYyEXf9NrO5eeriFPUzrAlQaz19uWrI+cdRKvgyZg88tFA1rcyJVf00zl2qskgevdN1vzoLBLVuKKlR6dugDiTCKppTrqNLVD+PyuADG4C67MLWvF+/evVcnfWjOnh+p4NKNUOA6ulwzveul8/5XdWvtxzlCuq5Lw9RU2G+Sml/v15NqjHqV6epwMhF38DPsw9+zHBOHGwfqaaKvHWpOtt7xWfuZc90ZNUxcP538I8P1fMQXg5n/qius7VzlrzOT70+Lv8c6vTq53Lh1ypA5pAbpyaE3PA/dSa70Vs1AK4OVH0sDlZNgCp1OWmV+jq8XGVxWQ/jGf2BbtoW9X5xKIzeauLR7a/D/S+oEsCiSPV7MGGnmvRibecUkdFHvfdeulj9TCuD1Pthy8BsURSsn6QaDS/6u3q/u/hrqPeB32cc/LrrfFXAZW6aes8PrVSNQltnaQghhBB9RbcGLpKXzosHTgeWpKWkPpS8dB5AXlpK6oP266eighIbgDhUWcmNqACFwynAVCAe2AQcA1wGlAN/AhcD/3N3TcdHH80b6e8DkFObz2Ob/8OCqQ8yOWw8n2V/zb0bHueD41/FU6tO16wq+oPnZzyBxWbh6rT57KnJ4t4Jt5LoH8/d6x/ly+xvuWrEJQDMjJzKfRPn46Hx5PX0d3l8y7O8m/xym+uoMFZSa6rnq7n/Y33ZZh7a+DTHRR/tDIKIvuPzMyGsEh56Xo2nW5EMa6aog1F31fnCmN1qyoe+QX0w/PQs1QgNVDPNF/6hylLO/kEdnKcP67w9avPNAAAgAElEQVTvRVs+PgfO/l71zSiOaJ52ACqgsfh0daAVWKuCBW/+/cB9vHeh+nB9y9tqWkF2IiyY37XeFe6oDFZNCy/8GlKWqcaE758P97X4tSkNh0fugku/VNNFrNrmcagAPx8PIzPgP0+oNG/H6Monb1MHtE896ToOtatsWtWF/+RVaszgOUvVGdmiCNVQdeNEtV1NoJqCcV4qXPuhCkzV+appKPfff2A/h6Q8eLNVMMOihYvfUF8fvQGu+6j5ulvsjTs/Okc1bm1PQJ3ar1WjemYURqp+Kt/P7fznl3qSKmMKtQc+wirUVJCF7YxK/XOamgDy1em0mwK/dSyUhsJjz6iDtj+mq9f+oXj5Wvjn/+DRZ9Rr+/O/de33sS31vmpM6DUfq/G1ObGqWe7/Lep42sZ7F6lxqPe8op7vpSeq16HLeq9R41DvfUmdwd41TP0+HWzwBtRtX7xOTT557hEVYH3vQnjwhc5vKw4UWaoy6Vr3LjoYGybBA/epgO+N76kyqwYflT326pUdBxg+OF9lWdz1qnrf+nGO+r6lV69Uk5/u/m/zONQF8117+nSVTatGaV/1qXo9FUWqtdzx+sHvUwghhDicNDbboeWZ2ntchANmoBpYCtyRlpLaYM+6cAYu2rjtbcDxaSmpZ9u/twGz0lJSV9u/3wh8npaS+m/7988BurSU1Nva2NeVwLVpKamzWl6+tmSj7Z4Nj7Py9G94b+8nZBn28/iUewGw2qycu/xKHp58J5PDJnD+iqu5buTfOTlWzZ57cOMCgr2CuHP8TQB8mf0dG8u38tS0Ax+OwVTL6T9fxA8nf4a/p98BGRd3rnuUn075Ag+tOp1xxrJLeXraQ4wNGeX2c92TZs+eDcDKlSt79H7twS7hhphCeOFhuOPR9idkCCHcd/R6NXr16hfaL7ERbUtLSe18oxZ6+70+ZRmM3wlPzz/4fXia4KMb4embYdPEQ1vP/EUqK2vhDYe2n87oG9RY4HHpajLJdc+q6Uy9paPXTW+/Rg7GJYtVGeh9bX7qdd+iO1TG309zDvy+q79rDmXz7sBr+hgCH7nm0BZ3iMx7cyk9/gbCV7yC56ikg95PzZPv0ZS2hfAfX2jz++5Scsx1+F58Mv63nN+t++2q7nrehOij3Mof7a6Mi7PSUlJ/6Wyj5KXzRgALUX0wfO33v7HVZi27CTS08X2XKtZLG8sJ9FSnHcsaK4jSN3fH02q0ROojKG0sd14W6h3i/NpL60Wod7Dze2+dFw1m1fvTYrPw5u4P+LXwd6qaqtHa24VUN9Xg7+l3wDqCvAKcQQsAH503DZbGrjwUIYQQ3eiE31UPlIpglbH09y9UtooELbpfYYzrQejnra5feTS8enXPraciWJWiHQqTpzrwr/PtfFuHidvhgRfh7y+rUhGHRZcd1j6eTif+pvqvPHivaqpb0w1ZdT0RdNFY1dpn/6F6gFi1zVlwvxzX/Fz616pyvembVVZWrT0L7oszVdmNwyWLVUldayVhcPPT6uuj16vSucE5KmPRkd3XG+549NDL4wY6/9suhBvO6e1lHDa6ITFEbvkAbWgHtaNCDHCHdRxqG14DNgMXp6WkGuwZF+cdzjv8rfhPJoSOASDcJ5Qsw37ndTabjZKGUiJ8utC8wG5Z/ip+L1rD8zP+xSB9FLXmOk7/+SJsbQ4fFEII0deEVKnRvEE1anTk+smq9Ep0v8gtHzi/Ni5bR/VdL3Pds83XN7VTnqMzH1qJTXv+nH5ot3esq7uyFRq6EPw4FNElkBsDeX0wS8/WZELj1cYLwQa3LVLjmBenqN49NQGqQelpy1UJ4h9HQYABnnxK9XJ6+xJ736FKVc731JPw6F2uvXv2xakSw5Za9iPxMaqynNVHqRKg3tTdZZsDkdZPD34DN+qs0enQRYZ0vqEQA1hPBy4CUA06a5OXzhsF3IAaW9qtkpfO0wEJwO16nQ+vHaM+Hc0ZlMxHmV+yoWwLk0LH8UX2t3hqPRkXMrrL99FgbsBT50mQZyCNFiOL7H00hOgpBYPggjd7exVC9F9L5ql/4vBr+YFbE6SyElsf9DvK3xb+E079FYZlwTuXqL4yV32iGh771UNxuMqW+H1m823/tUCdDbdo1Vlys4dqpPvJ2ThTGY5eD+emQnSpCpTsi1f9XGrtraambVHXx+er/iW7h6p+N1adStX/YY4aezp9i1rT61e4loo41v/8P1R/o6Qc1XfonUtgxyh1/QMvqvv64Bb1/7LjVN+h1lkLnk2qWeYx61XfoaxE1YPCccbfkbnx6J0qUyiuUB2ov365ahDbln8tgBHZ6uvPr1NNZBfcphrunrpC9fwwesOOkap/SsufT3y+aiI6aq9qCOzoOzT7Dzh2ffM+oTkzISlH9R0anu3ad6jRnh0xfxFUfr0AjzGDqX//B9Bqidr43gHrPu5POHojPHWrmgLjUBqufg6+9er7yxarxsy3Ptnc0Lg8DJ6+RfWxueE9uPeh5ttbdB0Hnn61Fx6HVrS/TXuO+wMu+Bb861SD5zcuV819Heb+php/R5Spx/HjCfDTCbSbdtOyVMS4chMVlz9G2OKn8ZquPr/WvfUNhuc+JuKXV9DFRri1Rmt5NdUPL8K4YgM2oxmvGWMIeuKfeAxrfgE1fPMbtQs/wbyvEF1kCL5XpuB/U/P5xuKJl+F79RmYd+3DuGwdmkA//G86D79rz+z0/i37iqh58A2aNu3BIzGKwCevx/uYCc7rTbv2YXjiHZrW7UTj64PXcZMIfOw6dGFt/9BalopY6xspO3k+3rMmEPS0Kvc255VQduItBNx1GX7XnNH2moorqL7rZYy/b0UXEYL/3ZcdsI05p4iahxbRtHobaDV4z55C4L+ud77HOdbh+/dTMTz/GbYqA/pzZhO44Abq302l9rXF2IxmfC8+iYAHrkSjUT/0+k+XUfduKpasAjS+3ngdPZ7Ax//h3G/rUpHGXzdSeekjhH65AMPj72Dak4vn6ESCnr0Vz9FJnT7/QvRHPR24uBNYBNyNyrz4DJjTjfs/OnnpvFrUW38ZsHLRsc87p4Yk+Mfx0KQ7eGHHG/apIkP49/SHnY05u+KUuDmsK9vE2cuvINDLn2tHXMbXOd93fkMhhBBCtOuSJeogfV+cGnPq1QR7h6hJNQ16mLxdTRAqDYPdw5tvd8Jq+PZk1Rx3WDbc/A5kJMH6KWoKy61vqQPyTRNUMGBkZvNtHZOElqTAK9eAh1lNetK0SKI88yf48gz1ryOXfakO0PMGqQDGPa/AzQtUQ9UXr4X5b6nvjV4qO6AtV34GU7apRq+OSU/3v6gOyluefb/oK3j/ApWBcM1HqsHy3Y+0vc+n5sPVH6tGwi9ep4I7oAImn5yt1hdUowImt7wN/7pdXR9erhol/zUaHr9DNR4dkQU6qzqYji1Sk1Bev1xtX+unemk88ALsHAH3PaDGRl//vpqO8vJ1zWsyrtyMxs+X0E+fgHZ6rs1aC/tjXYMWLdX7qjHUR29QwarWU5isOtVE94b3YVDRgY2Tu1tMkZrk9e9bVFDl/xapCUbvXaSuP3W5+nm+c7EKniXlqalJJk/VDLwz3rOn4Hf1PKpueZbwZS9jySuh5sn3CH7h/9wOWgBU3vws1qJyQt97GI2/HsOT71Fx2SNErHodjbcnTet3UXXjM/jffRn6ebNo2rCL6vteQxvsj++lpzr3U/fqYvxvvYCAuy7DuGoTNY++hW7wIHzmdpzWZHj6fQIeuoqgpBgMz35E1Q3/IXLtO2h8vLDkl1J+zj34XTWPwMf/ga2xCcOC96i6dgFhX/2708em9fUh+L93Un7mXXjPmYb33GlU3fwsXtNGtRu0AKi6+VmslQbCvliAxtOD6ocWYS1ujlzZLBYqL38cbWggYUuexma2UHP/a1Reu4Dwb59xbmfOzMf421ZCP34MS04xlf94CkteCbq4SMI+exLTrn1U3fgMXjPH4XOi/XkyWwi873J0g2OxllVR8/g7VN3yHGGf/auT5/EDAh69Fm1YEDX3vUrVLc8S8csrnT5HQvRHhxy4SEtJTerguitbff8b0Lob5cMtrte02n5Wq+/bbXeUlpL6Hmp0amuXt/zmuOhjOC76mDb38cWcd1wXNtl1BMAZCadwRsIpAPh66Hlq2kMu158aN9f59QMT/8/59eSwCSyZ6zoIpfV9CSGEEAKWnqTKdlpf5vDTCWrU6LHrXQMXWQnNGTRFUWp07Ph0FbgIrVRBiDVTm8+yt8xMODdV9Uv4osWJ4tYjgbeNcV2Hp6nt9f8wV02OAjXCd+IO1Z9hyTx1UA9qTHbLHhct+dWprJGXroWt9qknb1yuGmqetMo1S+iTs2HXCPX1khR4eKEqmWirtKDOTwVKzK1KXJa3GHtdEgFvXwzPPNG8n9OWq34YL16nggDgevDf5KmCHy33efwq9Xy/crV9+kmsei7ue0mNj3aMqdYE6Al65mY0nu1/HB1UAplJ7V4NqH4WPkYVLGqLYxR5TIvAxeAceP9m1+3WTOmeXiuvXtU8evzXY1VgDACbmlT1ziXqdQlQGqHWdfJK9wIXAAH3XYnx921U3/ky5j370Z+ZjP5v7s8vN+3aR9OqzYQtfQ6vySMBCH7lTkqmX0VD6u/4nnsCdW98hfcJUwiYr8ZzeQyNxZyRR+1/F7sELrxmjHVmYXgMjaVp027q3vi608CF343nOrcJuOfvlB5zHabd+/GaOJy6d77Da9poAu5uHoMW9ML/UTLp75h2ZuM5ZnCnj9Fr4nAC7ryU6ttfxOes47FkFRCyvO3JfwCmndk0rd5G+I8v4DlhmHpOnp9P6ax/OrcxLt+AOSufyE+fQBetysyDXr6DsuNvoGntDrxmjG1e7/Pz0fr64DkiAe9ZEzFtzyTk/UfQeOjwGB5P3aKvaVq9zRm48L2s+TklMZqgJ6+n7ORbsZZXo20nywQg4L7L8Z6p3ij8519IxYUPdnobIfqrns64EEIIIYRoV2ai6/daizrYm7lJBSA8LCojovUo05xWJRKVwSqDANSBb/pwePEh2DpGBSHWTrGXidhUc9bOxlFnJXZ8vcOeIc1f27TqvuMK3bstqD4UOqvqr+Bg8YCMwQfup+VjrrT3Eg9sJ3DRnqHZqtdLYr4KmjiyTMIr1H4G58Cu4c1BC3fEFqlsgpYjW9OHgdYGsYXNgQvP0YM7DFqAa9ZLd8qLgWdudL2ssZ1gUlcURzQHLUA1gg0yqK/DKiHYoDKGWvbN0FpUdpG7NN6eBP/3TspOvAVdTASBTzbPsK7/+GdqHl7k/D70ywV4TRrhcnvz3lzw8sCzxeXa0EA8hsdj3pPj3MbnnNkut/M6agx1ry3BZjSh8VYL9prmWm7tNXUUtS+p9rtVtz1PoxoUCN5eRO/42Lldy3IGXZR6QVjL1Jxr018ZNK3dSdGwA9vgWfYXuhW4APC76Vwal62j/p3vCHnvIXQR7feIcDwnHuObO7B6DIl1aYZp3puLLj7SGbQA8BwejyYkEPPeXGfgQpcYhda3+cWkDQ/GY1gcGg+dy2XW8ua53k2bd1P7/KeYdu7DVl0LVqt6vPmlHQYhPEc3Pxda+7osErgQA5QELoQQQgjRZ7Q86AMVtDhlpSrzyIuBRm+4/HPwNLtuZ2l1YG3TqBIGUAf+j92hShwm7FBnty9dDA/dC/lulg40ene+zeHW+hjerDvwOm0XDvR961VJx8YJ8NI1quQktEplbniYO7/9wbC1yK3V+Hb+pBZEqWBHRyqD1M8nrqDt6x2XF7aYLGLygOLItrc/FK1fh9AcfHH8/+qVBwbCbF0cK2PasAsAa5UBa6UBrb/q8Opzxiy8jm6O6uli3C8fUYvsvvk2AQ9cib89YwOt1vVKzxZPlOM+rTbn/z6nziTg3stpTduFBpXW0iosWfmg02Le14Xo4cFo+br2aHV4pdG0eZnN/nit1bVUXPIwPicdRch/70AbGoSlqJyKCx/EZurkF7HF8+hcgj3oIcRAo+18EyGEEEKI3jEqQzV2XD1DlW+UhKtGkl1l08LuYfDF3+DeB1XZxswNgEY1mxy/q3vWOzyr+WuNVY0fzbeXMDgCDdoOjiuKIlWT0VEZzZfpzKpvh6PkobvEF4B/PXx0LqSPUE2fHVkqDtkJMHqvygpoi1l34OPJj4akXNVk1GFUBlg1agRxV6yeobJBJv/V9vW+9Sow9edUOP5P1U+jJa1FNcLMSlCPrzeVh0CNP0SVqqBJy38lXYgvmDPzqXnkLYKevRWvaaOpuuU5bPaDVW2ALx6DY5z/HJkRLXkMj4cmM6Yte5yXWStqMO/NxXNEvHMb0/qdLrdrWrcTXWKUyz6bNqa7bGPatBuP4SoVSBcR0ryWRPd/8J7jh2LenYMuIcrlsXgMjlHTQ9xgs9mouu15PMYkEfzSHRie+h+mXfva3d7xnJj/am5+Y84uwFpR47KNJbcES1F58+Pdm4utsgaP4QluP77WzLtzsFXXEfDAVXjNGIfH8HispVWd31CII4wELoQQQgjRZxVGqT4RwzPVmfd/fAih1V3bx6g9cNb3MGQfhJXDUZtVk0pHIGBJCiSvhfO+VfcRnw9n/KQCBl112grV0yCmEK75WJVu/GJvP1Aarv6fuk31kPA2Hnj7Oj9YMUtNC5m4HWILVPNGfWPzfrpLSbgKPJy2AiJLYeoWNT60pR/nqFKH+W/C4P0QXQyz1qjnyPGYEvPU5QEGFShYdYzKILjpXbXd2HT1XKye3lwm4q7fZsK6Sap5quNnGF4Ok7fBA8+rJqqggi8Gf3hooQpyhFXAiAzVHDW0Cl67wnW/OgsEVbf61yLo4V8LiTnN5TnRJer71oGRrrBp4YszVBbRqctVs9D4PDh+tXq9ubUPk5mqm5/Fe+40fC88kaAXbsOSmU/ty1+4vQ7P0Ul4z55C9R0v0bRuJ6YdWVTd8hzaiGB85qn2cn7Xn43x103UvvQ55qx86j9fTt3b3+F/47ku+2pas53a15Zgzsqn7r2lNHzzG37XneX2Wtrid82ZWEoqqLrxWZq27MG8vwjjyk1U3f4itqZ2msu0Uv/Wt5i27iX4hdvRn308+jNmUXXTM9gam9rc3nPMYLyOGU/VnS/TtGk3pm0ZVN/+Ivg0ZwV5z52Gx5BYqm56BtO2DJo276b6lufwnD4Gr6PGHPTj1SVEgacHdW9/i3l/EY0/rcXw/KcHvT8hBiopFRFCCCFEn/X5mao3wEPPQ6OXamC4Zoo6GHVXnS+M2a2mfOgb1KSOT8+CtVPV9eumwAv/UAeUZ/+gJmekD+u870VbPj4Hzv5eHcwXR8B/boZqe5l8SQQsPl2VugTWwvJkNQ61tfcuBKtWTffwaYTsRFgwv2u9K9xRGQyvXQkXfg0py2BfArx/PtzXoodhaTg8chdc+qWaLmLVNo9DBfj5eBiZAf95QjXIdIxDffI2NQ71qSddx6F2lU2rxtKevEod4J+zVPXbKIpQDVU3TlTb1QSqiTLnpcK1H6rAVJ2vmoZy//0HThNJyoM3XXuwY9HCxW+or4/eANd91HzdLfae6h+dA9+c1vXH4fDTHPX6mrdMTXAxeqlRtj/M7fy2AIbnPsZSUkHoJ08AKqshaOF8Kq9dgPfxkw/oZ9Ge4JfvoPrhRVRc/hi2JjUONfTDx9B4NfeuCH71LmoXfoLhuY/RRoQQcMfFLo05QTXZNG3eTe2zH6Hx1xPw4FX4nHSU+09IG3RxkYR/8ww1C/5HxUUPYWsyo4uNwHv2ZNB1fs7VtGsfNQveI/jF29HFqGhh4IIbKDvpVmqefJegJ/7Z5u2CX7mT6jtfovzce9GFB+N/12VYWkwV0eh0hLz/MDUPvkH5Ofe6jEM9pMcbHUbQwvnU/udD6t78Bs9xQwh85BoqL3/skPYrxECjsbUzfmoAGfAP8HCYPXs2ACtXruzR+01eOq/zjYQQQvQpaSmpnW/UwkB8r48phBcehjsehdzY3l5N/9DR62Ygvka6Q1d/1w6n4omX4T//Qvyu7mRGsBBCdMyt5jpSKiL6lFCv4N5eghBCiC44mPdtea8Xnb0G5DVyIHlOhBBHMikVEX3KNyd92NtLEEIIcZgNxPd6895cSrmB/x33Cp6jknp7Of3eQHyNCCGEOHgSuBBCCCGEOEQew+MZVNB30viFONyitkpwSQjRc6RURAghhBBCCCGEEH2WBC6EEEIIIYQQQgjRZ0mpiGhXRkaGc7qIEEIIIYQQQgjRndydYikZF0IIIYQQQgghhOizJONCtGvYsGFuR8CEEEIIIYQQQojDQTIuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEEII0WdJ4EIIIYQQQgghhBB9lgQuhBBCCCGEEKKPqjOa2VVY09vLEKJXSeBCCCGEEEIIIfqod1dn87f/rqbRZOntpQjRayRwIYQQQgghhBB91J7iWprMVvIq63t7KUL0GglcCCGEEEIIIUQfta+8DoCcCglciCOXR28vQAghhBBCCCHEgWw2G9llKnCRW9HQ4bZLtxWyfl8FPp46bpkzDD9vOdQTA4e8moUQQgghhBCiD6qsN2FoNAOdZ1w89t0OKuubMFlsjIkJ5MyJMT2xRCF6hJSKCCGEEEIIIUQ3q6xrYk1WOWaL9aD34ci2AMjtIHBRazRTYjBy8wnD8dJp2Z5ffdD3KURfJBkXQgghhBBCCNGNHv9uJ+/+kY3NBq9dOoXTxg86qP3sswcuhoT7dZhx4dhuRJQ/owcF8FeeBC7EwCIZF0IIIYQQQgjRjX7ZVcy4mCAA9pUffFPN/eV1aDVw9NAw8iobsNlsbW7nyMxICvdjXGwQ2wuq291WiP5IAhdCCCGEEEII0U0sVhsFVQ3MGh5OoI8HhdUdN9XsSHZ5PXEhvgyJ8KfWaKay3tTmdo6Mi6QwP8bHBmFoNLP/EAImYuDaX17HppzK3l5Gl0ngQgghhBBCCCG6SVFNI2arjfgQX2KC9RRUNR70vvaV1ZEY5ktCqC/Qfp+L7PI6BgX5oPfSMS5WZXr8JX0uRBue+Wk313+wsbeX0WUSuBBCCCGEEEL0mr/yqskoMfT2MrqNI7gQH6q3By4OLuPCZrOxr7yOweF+xIfqgfYni2SX1ZEU5gfAiKiATht0vrJiLzd/vOmg1iX6t9yKekoMRirrmnp7KV0igQshhBBCCCFEr7n10838a+mu3l5Gt8mrVIGKuBBfBgX5HHSpSEVdE4ZGM0lhfsSH2DMuKtsOXOwrqyMpXAUuvDy0jB4UwO8ZZWSUGDA0mlz+ffDnPp79eQ+p2wr73cGrOHT59gygvSW1LpfnVtRzyvO/8Wt6SW8sq1MyVUQIIYQQQgjRK6obTGSX1eGp0/T2UrpNbkU9Gg3EBPsQE6ynst5EQ5MFvZeuS/txNPVMCvfFz9uDcH9v/sws54bjh6LRND9f1fUmKutNDA73dV42d3QUC5ft4cSFv7W57yERfmSVql4Hc0dHHcSjFP1Ro8lCWa0RgL0lBo4aHOq87pst+ewuNnDLJ5tZcuMxjIgK6K1ltkkCF0IIIYQQQoge5Zh4saNAlTMUVR98H4i+Jq+ygehAH7w9dAwK8gGgoLqBoRH+XdpPy4abANcfP4R/Ld3FKysyuGXucOd22eVqu8Hhzfu/de5wzpkSy+97y6g1ml32q/fScdq4QRz15C9s3K+aNN6zeBs/3nYc4f7eXXy0oj9p+Xu2t9g14+LHHUWMiPKnst7EP97fwA/zj+tysO1wksCFEKLfsFht6LQD54yMEEIIcSQymi0c959fuWXOcBqaLADUNJoPKiuhL8qtrCcuRPWkiAlW/xdWNXY9cFFeh06rIc5eJnLNrMHsKKjhuWV7WJ5ewpSEELQatR3gknEBqlTloqMS2t3/2JhANuyvZGteFWW1Tfyys7jD7UX/l2/vt6LTatjboq9MbkU92/NruO+0UUyMD+aiRWt47ufdPDhvTG8t9QDS40II0S/8vKOIyY//zJqs8t5eihBHtBXpxWzcX9HbyxBC9GPphQaKa4x8uj6H7QXNDSSLawZG1kVeRb2zJ0VMkApcFBxEn4t95fXEBuvx8lCHbBqNhqfOGc89p47CYrXx2focPlmXw5+Z5YyI8ich1K9L+5+aGMqWnCpWZ6jPVr/sKu7yGvu6tL2l/LJz4D2ug+UIXExNDGFPi4yLn3YUAXDK2GhmDgnjspkJvL06m819aGyqZFwIIfqFnYU11DSaufq99XxwzQymJob09pKEOCL9K3UXYf5efHH9Mb29FCFEP7U1rwqA7fk15FU2EOjjQU2jmaKaRmeDyf6qyWylqKaROPv40qggVXpReBAjUVs23HTw8dRxw+yh3DB76CGvdWpiCO+szkajgZNGR7FqT+mAyXpxWPB9OhklBr668VjnmNgjWUFVAxoNHDc8nHXZFVTVNxGk9+TbrQWMig5wvt7uPW00X27MI3VbIZMT+sZnbsm4EEL0CyUGIwHeHgT6ePLyir29vRwhjlilBiPb82swW6y9vRQhRD+1JacKf291/rSq3sTxIyOBgZFxUVjdgNWGs1TE20NHuL93l0ei2mw2FbgI8+1844M0LUkdkM4aFs4VxyRhNFv5PaPssN1fT2syW8koMWCy2Lj5403c/PEm5j63krnPrWTJprzeXt4h25xTSZO5a3+LC6oaiPD3ZmyMCuLsLallyaZ8tuVVc9WxSc7t/L09SAj1dY727QFfS/sAACAASURBVAskcCGE6BdKaozEhuiZnBDc7gxzIcTh1WiyYDCaaTBZyCit7fwGQgjRhi15VcwcEsaUhGAAThytAhd9oUGn0Wwh8xDe3xyjUB2lIgCxwT5dLhWpqGvCYDQ7G3MeDlGBPtx96kjuOXUURw0OJcDHY0CVVWSW1mKy2Lj4qARyKxtYk1XB8MgAGk1WXlmR4WwQ2x+V1DRyzmt/8Nn6nC7dLr+qgdgQPcMiVb+VRb9l8dQPu5icEMz5U+Ndtk0I9etTn7klcCGE6LMMjSbn2ZfSWiMRAd7EhegpqGro139shOivKuqanF9vy63uYEshhGhbdYOJrNI6JicEc/aUOLw8tBwzNBxfLx3FNcbeXh6frM3htBfSMDSa3No+o6TW5TPJzoIaQI0wdRgUpCe/i59dmhtuHt7SmRtnD2NcbBCeOi0zBoeysQ/1NDhU6UXqZ3HVsUmsf+BE1t0/l9f/PpX5c4eTVVbHltyqXl7hwcurasBmgy1d/FtcUNVITLCeuBA9f5sUw297SqmqN/HE38ahbdUA35Fx0Vc+c0vgQgjRZ/0rdRcXv7kGgNKaRiICvIkN1tNoslLe4gBKCNEzymtbBC7y++8HPiFE7/krTx1oTYwL5rIZCaTdfQIRAd5EB/r0iVKR3cW1NFmsziaGHdlVWMOJC1eRtre5vOLbrQWMjw1ikL0pJ0BSuB9ZpXXMftb9EoXsMnWmO/Ewloq0NnpQIFmltTSaLD12n4fTrkIDXjotQ8L9CPXzch6YnzY+Gm8PLUs25ffyCg9eiT3It6PA/cCFzWZTGRfBejQaDS9eNJmtj5zMb3ef0Gb/j4RQPXVNlj7zmVsCF0KIPmtLbhXZZXU0miyU1hqJDPBxjgRzpGIKIXpOWa36oBTg7cG2PMm4EEJ0naMx5/i4IDQaDVGBPoAqWyjqA4ELR02/Oz0ptuer98HdRWqsZEZJLX/lV/O3STEu282fO5z/nDeBYF8vbv98K/cu3obF2vFZ7P2tRqH2hNGDArHaYE+xofON+4FdhTUMj/LHQ+d6yBvg48kpY6P5blsBRnP/DNKUGtTvyt4S9wNNZbVNNJmtxAY3B9V8PHXOkb2tJdiDZn2lXEQCF0KIPslRY2qzqWiyyWIjMsCbWHuzq3wJXAjR4xyBi+NGRLCrsKbffuATQvSe7fnVJIX5EqT3dLk8KtC7T/S42F+hSjTy3ZgC4uj14yjr+GZLPloNnDnRNXCh99JxwbR4Fl9/NP88bgifrs/lu60FHe57e361yyjUnjBmUCCgDvgHgl2FBkbbH1NrKRMGUVVvcmYA9TeOsiqL1UZ6kXuBprxKFYBoL1DRWoJ9Mk5fadApgQvRqzJKDH2mbkr0LRkltZjtZyM27FP1lhEtAheON18hRM9xpIvOHhmByWIjvXBgnJUTQvSczNJahkcFHHB5VJAPJYbGXv1caLJYKbAHLNzJuMgoVoGL/eWqD8A3Wwo4Zmg4kfYsktY8dFruOXUUI6MCeOXXjHazLr7anMevu0s5a3LsQT6Sg5MQ6oufl45dPfzeXmowculbazjrv6t5+of0bttnWa2RUdEHvtYA5+VZpXXdcn89rcTQiKdOlb44Mn86syarAoDxbo6FdWT75JT3jc/cErgQvWZbXhUnLvyNP7PKe3spog9q+Udzw34VuIgM8CbQx5NAHw+3ak+FEN2rvNaI3lPH1EQ1Qm9viUwWEUK4z2yxkl1Wx9AI/wOuiw70wWSxuTQB7mmFVY3OYIJbgYsWGRdFNY3kVNQz1z4hpT1arYab5wwjo6SWpX8VOi+3Wm0s+H4Xl7y5hvuXbOeowaHcOmfYITyartNqNYyMDmBnD2dcrNxdwuqMckoNRt5Znd3lEZ9tcTTmHNNOxkVciC9eOi2ZZf3z71iJwcjI6ACC9J7sKHDv57V8VzHjYgOJDmo7sNaaj6eOqEBvKRURwpGGttPNXzZxZEkvrMHbQ4veU8dGR+DCfgYjNsRXSkWE6AVltU2E+XsRH+qLTqthX1n/PFMlRHf5/q9Cftxe1NvL6DdyKuoxWWzOUYwtRdv/xu8uNnTLgevBcJSJeHloOw1cNJos5FTU423f1vFZZUJccKf3c/r4QQyL9Gf+p5u58I0/WZNVzmurMln0Wxa1RjOzhofz8sWTD+jN0BNGDwpkV2FNj2a+bMmtIsDbg7tPHUmT2XpQPTZMFtfXTKY9sD4s6sDXGoBOqyExzLffZlwU1xiJCvBhbEygWw06K+qa2JRTyZxRUV26n4RQXwlcCOHolnwos7LFwLWrqIaR0QEkhPo6z75EBHgDEBeil+acQvSCsloj4f7eeOq0xIXoyS7vnx/4hOguLy3fy2srM3p7Gf1Gpv0gcWjEgSM+HXX3l7y5lrkLVzp76vQkxwHalIRgZ8lIW2w2G1mlddhsMGtYOFYb/PBXETqtpt0z/C3ptBo+uOYobp0znLzKBi5atIZnf97NGRNj+OamY3nz8mnOpqU9bfSgQAyN5h79nLUlt4oJ8UFMtAd9tudXk1/VwKsrM9oMoLy3OtsluPHd1gLGPfITf2Q2T3fJqWhA76kjwt+73fsdEuFHVj89Dik1NBIZ6M242CDSCzsP9v2aXoLVBid2khHUWrx9JGpfIIEL0Wv22z/wZkiqsWjFZrOxq9DAqOgAZ0djXy8d/t4eAMQGd30euhDi0JXXNhHu7wVAUpifZFyIAenH7UVuj+UsrG6koA80lOwvHJ/5hraRcTEhLogXLpzEgymjKakx8n+fbel08kZ3y6mox0unZUpCCEU1jQfcv81mY+GyPcx8ajkr95QAMHe0OoO9PL2Y4ZH+6L10bt3XoCA9/3fSCJbdfhzXJQ9m1rBwnjpnPBqNpnsfVBeNjVGBlxeX76XOaD7s99fQZCG9yMDk+BASw3wJ8PFgW341r6/M5D8/7ia71d+ZEkMjj363k+eX7QEgdVsB8z/djNFsZXNO85junIo6EkJ9O3w+h0T4k1NRj9nSOxk+B8tksVJe10REgA8T4oJoslhJL6phe341Ex/7mYXL9rgEMmw2Gz9sLyIiwJtxMe71t3BICPWlsKaxTzTjlsCF6DWON6LMfpqiJQ6fUoORiromRg8KdHY0jgxojpjHheipNZqpbjD11hKFOCKV1xkJ81O/i0lhvs6GdEIMFJV1TVz/4Ub+98e+Tretb1J/h8pqjb1W2tDfZJTUOvtVtabRaDhrcizXJg/h0TPHkra3jE/X5/To+nLK64kL1RMX4ovFaqPE0ByUcgQtXlq+l+IaI88v24NWAyeMigCg0WR1u+lhS75eHjyQMoYPrpnhPEHTmybFB3Nd8mAWb8rjkrfWun27oupGrnlvPQ99vb1L9/dXfjUWq41J8cFoNBrGxwaxJaeKH+wlWPtaZfZttDdsX5FeQnmtkYe+3s7E+GDC/b1dsrhzKuqdJ7/aMyTcD5PFRm4/y+ItqzVis6lJPJPiVZbKltwqft5ZTHWDiZeW7+Wyt9eqAEetkWv+t4FfdhVzzuRYtNquBcYGh/ths0FmSe8fr0ngQvQKm83G/nJVF1hR19SrjZhE3/PTDvXHakJcMIn2PzoRrQIXgJSLCNGDrFYb5fYeFwBJ4X7UGs2U1cr7txg4HP239ruRGu0oJbDZcDtD40iXWVrbZn+L1i6aHk+4vxfbcnt2VGVORT2Job4MClZlGo4+FzabjeeX7eHlFRlcOC2eO08egcliIzHMj+hAHwLsAYcJcV0PXPQ1Go2GB1LGMH/ucLbmVlHT2PlJoowSA6e++BvL00tYtrPYrfupM5rZuL+CLbkqEDEpQR2Aj48LYmdhjbNUqHUPCkfDdqPZym2fbaGy3qQmtUT7O0+G2mw2FbgI7SRwYW8S29/KRUrso1AjA3yIDdYT7u/Nlpwq1mSVMyEuiGfPn8i67Aoe+no7F7zxJ6szynjkjDHcc+qoLt9Xy8BIb5PAhegVxTVGGkwWZg0LB6TPhWhW32TmpRUZHJUUypSEYOKdGRfNtZ6O8UwyElWInlPTaMJstRFurxdOClc16q3PhgnRnzmmKbhT011Y3Rw8d2cCxZHOZrORWeJe4EKj0RAbrKeguueeV5vNRk65OtiNtffbyLcHpz5cm8NL9qDFU+eM57rjhjA0wo+JcUFoNBoSw9XnkvFuNObsL0bbe3W4UxL4+qosmsxWzp4cS7GhsdMMpPJaIxe88SfnvvYnzy/bS1yI3vm3ZUKseg71njoCfDzIKjswcDEtMYTIAG/S9pYxelAgMwaHMjTCn6ySWmw2G6UGI40mq/PkV3scvVb6W4POEoMjcOGNRqNhUnwwa7Mr2JJTxcwhYZw3NY6/z0zk0/W5FFY38v7VR3HVsYO7nG0BqlQk1M+LzTmV3f0wukwCF6JXOMpEHHWBmdLnQti9u3ofpQYjd586Un0YCD0w48Lxh2hfH5krLcSRwJFZ4ci4GBymPvC1rj8Woj9zjOJ2p4t+YYveFoXS56JTJQYjBqO5zVGobYkN0ffo6POVu0sxGM0MiwpgUJBrxsUvO1X/iqfOGY9Wq8HbQ8e3N8/i6XMnAJAY5oeHVsOo6IAeW+/hNiS8/fd4q9XG9vxqtuRWUVZr5NstBZw7JY6jh4Rhs6mykfaYLVYueXMtmaW1XDNrMFoNzhOZgLPcZs7oSIZH+pPdIqjQ0GRhR3410weHcvr4QQBcfWwSGo2GoRH+GIxmSg1GZ8ZUfCcZF8G+XoT6eZHVz0aiOjK8HA1cJycEk1/VQJPFyswhoQA8kDKaa2cN5sNrZzBjSNhB35dGo2FyfDCb+0DGRe8XUvWizeXbeGLLcyyZ+z8A/r7qRm4fdz2TwyZ0aT9bK7bz720v8/HsNw7HMgckxxm6WcPC8fbQSsaFAMBotvD279mcMDKCaUnqjTcuREV6R7b4MBDg40m4v5c0BhTiMHM0ptNpNc60XcdZsbgQPR5ajbPRshADgSPjoqreRHWDiSD9gb0YHAqrJHDRFav2lALNZ/I7ExOkZ0V6CTab7bA3rCw1GLnry62Mig7g/Klx+HjqCPTxcAYucirqGRMT6HLG2q9FP4rLZyYyJSEEH0/3GnP2Bwlhvmg0B2Yj1DSaOOX535yv+VHRATRZrFxxTCLF9hKGvKr2+0vkVTawu9jA438by+VHJ3H7SSPQtXhe40P13HzCME4fP4i3f8/m94xSzBYrn2/Iw8dTi9lqY1piCMMjA9Bo4MxJMQDOgFhGaa3zdzOxk8AFqABNX+jf0BUlBiMaDc5m2ZPt5RxaDc7Pzz6eOh6cN6Zb7m9SfDDL00s6fU883A4pcJG8dN4+4Nq0lNRfkpfOuxJ4G3CERkuBlcBTaSmpe+zbJwHZgOPVUQa8npaS+nQH92ED6gEbUA18BtyVlpLa7a1NPzj+Vbe2S146j09mLyLOT/2iTAwdJ0GLLtpXXoeXTktsiJ4hEf5H5GQRm83Gm2lZHD0knPEDoCayO/y8o5iKuiauPHaw8zIvDy2r75mDt4drglhimJ+kqAtxGHy+Ppe12RXUGk2syaogMcyXb2+eRXmrjAsPnZb4UF/2lUnmkxgYmsxWMkoMDAn3I6usjtyKeoI6aLZYWN1AuL83TWaLS9mIUJ9xXluVSZDek1PGRhOs9+S/v2YwNiaQ6Ukhbu0jJlhPo8lKZb2JUD8v5+Vv/pbFJ+tzWH778d0W0Pj3j+kYGs18fN1MZ/AhPtSXfeVq4kRuRT2nj49u9/YzhoQd0lntvsjbQ6fGXrc6SbS3uJbC6kZunTOMmkYz7/2xj+Th4QyLDMBDqz6r5XfQg8yRRTM8Up2Q8mvVkFSj0XDnKSMBNa508aY8Fm/K4/6v/nJuMzUxhGBfLx45Y6zzsqGRKkMks7SOMvuBfay9J1pHxsQEsnhjHharzSWA0pLNZuOVFRmcNn6QW6VOh1upoZEwPy88dOr5Hh8XhEajslXaanx7qCYnqN/ZbXlVJA+PaHc7s8XKi8v3csG0+E6zXQ5Gd5eK/JmWkuoPBAEnooIYG5OXzhvXartg+3bnAQ8lL513Uif7nWjffi5wCXBd6w2Sl847orNH+pt9ZXXEh+rRaTWMiPJnw/5KtuX1fgrS4dZosrDw591s3F/JS8szWPB9Oh+u2d/by+ozPl2fQ2ywnuQWKYMAei/dAXV5ahSjHDAJ0Z1sNhsLftjFzzuK2F1kYEiEH9vyqskoMZBr7ykT4d9ctpUU5svuYkOPjywU4nDIKKnFZLFx8lh1gNpZuUhBdSMxwT7EBOudjTqFUlxj5D8/7uaBr7ZzzNMruP7DTewvr+fWucPdDjbE2PtMtO4fsja7gqzSOqrqu2eymNliZdnOYuZNiGFEVHN258ioAPYUGSioasRsVY04jzRJYX4HBC4cP4+UCTE8euZYPv3HTJ49fyKAs6lpRyU+jv5kcW4EFRzlKv/9NZPIAG8umBbHBdPiCPb1OmDb6EAffL10ZJbUklNRT0yQHm+PzjNgJsUHU9dk6fAkamZpHc8t28ONH22k0dT7Y0HzKhtcer8F+Hhy4bR4LpmRcFjub0K8Coy0HDfblq151by8IoMr3l1HdTf9frZ0WA727dkQmcCNyUvnJQCPooIUrbfbkLx03g5gErDMjf2mJy+dlwaMA2fGx2vApcDI5KXz/IBI4GXgOKB2/ph/cN7gMwEwWow8u/1Vfi9aQ5hPKKfHneiy//NXXM09E25lWvgkLDYLH2UuZmnuz1Qaq4n3i2HBtAd5YsuzAFyVdgsaNNwz4VZCvYNdSk72GXJ5bvt/yajJJtwnjH+OuoJZUTMAeHLr8+h1PhTWF7O1YgdJAfE8MukuYv0Gdek57q+MZgtvrMoibW8Zx9kjdvPnDmfj/koufGMNL140yfmBYSB687csXlqRwUsrMpyX5R6BDSbLao08+NV26u1v/hpUVH11Rjm3nzTCreZBSWG+LN7USEOTxe2Z6UKIjlXUNVFVb+LBlNFcmzyEoupGZj61nJ92FPPd1gImxAUR1iJwccKoSB7+ZgfX/G89L188mYDDcKZHiJ7imChyytgoXl+V2WngorCqgcHhfpgsVsm4aMVxcPpgymi25VXz7dYCRg8K5OQxUW7vw9EgM6+ygXEtMl8cEyCyy+sI8TvwALarNu6vpLrBxImjI10uHxEdwJLN+Wy1n1hzp+xgoBkS7sfiTfku5TqOoESMPUgxs0WmibeHjsgA7w4zLvIqG9BpNc4+Ih3ev738I6einmtmDeahDkofHH0uMktrqW+yEB/aeWAEYKK9zGJrbpVLWXJLf+Wr18Ce4loWLtvD/aePdmvfh0NDk4V12RVcfJRrkMLRb+VwCPTxZHikv3OiS3ucU5nK6/nnhxt4+4rpB2TUHIqeaM65BEhu64rkpfNmooIQGW1d38b2Y+z72tzi4ouBFCAYsALfAVuBWGDu59nfsLZ0IwDv7v2EgrpCPjvhLZ476nF+zFve7n19lvU1ywtW8cz0R/nplM+5b+J8fHTevHL0v9W+kl/m51O/ZG7McS63M1vN3LvhcaZHTOHbkz7ktrH/5PHNz5JTm+fcZnnBb1w14mK+P/lT4nwHsWj3++48/AHhwzU5LFy2h2OHhfNAivqlHxLhz1c3HsuI6AD++eFG3vk9u5dXeXgUVTfy6spMThwdxW0nDuf8qXGcOjbarQZgA83ve8v4cUcRZQYjNQ0mymqNfLhmP14eWs6fFufWPhwTDfZXSLmIEN3FMUpuqD0VNjrIh4nxwbzzezbpRQYunB7vsv3lRyfx5NnjSNtbxsJle3p8vUJ0p005lfh4apkQF0yIr2fngYvqRmKC9QwK1kuPi1Yc48pnj4zkpYsn881Nx/LWFdO6VNrhSPNvmXFhslidP5fu6nO1Ir0ET52GWcNdsz0dB7GOEe2Ozx1HksH2sdel9h5HoMpAAn082g1Ud9ZUNa+ygehAH2eZQ0cS7X02AM6cGNPp9sMi/VmbXcG2vCoSQ937eQ0O8yPQx4PNuVWs2lPKrZ9sxmZzzSLclleN3lPHeVPjeCsty60RsYfL6owyjGYrc1sF2g63Y4eFszarvMOMk12FNQT6ePDs+RNYv6+S81//s1tHRfdE4KIACG11WVny0nkNwJ/Aq8DXnexjU/LSeZWooMRbwLstrnspLSU1Ny0ltQGYDkSkpaQ+npaS2pSWkpp1RsIpLC9IA2BFQRqXD7uQQK8AovQRzkyMtqTm/sy1I/5Ogn8cGo2GYYFDCPLqvJnQjqp0GiwNXDb0PDy1nkwNn8gxUdP5pWCVc5vk6KMZEzwSD62Ok2Jnk1EzMA/U27I5p5K4ED1vXj7NpfYpIsCbT6+bycljong8dSeb+sDIne72nx/TsVhtPDxvDLedOIJnzp/I0Eg/CqsbMVs6Hhs10GSV1aHVwFc3HcPXNx3L0luT2fLwyay6azaDgtyLkCfZUzaPhAadL/6yl2d+Su/tZYgjgONM5rAWXf9PGRtFeV0Tek9dmx8cL52RyKnjovl6c36nI/CE6Ks251Ty6fpcTh8/CJ1WQ0Kob4cjUQ2NJmqNZgYF+RAT5ENFXVOfSCHvCXuKDZ2ORmxdDjAxPtiZQeGuEF9PfDy1LoGL/eX1mO2lad319395egkzh4QdcCDumBCycncpPp5aIltMNztSDLb/LWg52SO/qoHYkPazT2KDOwtc1LtVJgKqwWRMkJ7EMF8muNEP7pIZCcwdFclJY6K4oFWgvT1arYaJ8cFszqnkidSdfLu1gPK6Jpdt/sqrZmxMIKeMjcZqo1d78y1PL8bf24MZg3u2p8oJIyMxmq38mVUOqBKrq95dx7dbC5zb7CysYdSgQM6eHMfbV0xjf3kdt3y8GWs3lZP2ROAiFqhodVk44A/cAcwGOsstnZKWkhqSlpI6NC0l9cG0lNSWn4xyW3ydCMQkL51X5fj3QcYXVBrVm2u5sYJIfXM0NUrffnORkoYyYv26XrJQ1lhBpE8EWk3zUxutj6S0sdz5fZh3c1MiH503DZYjJ71wZ0ENY2PaDgDpvXQsvGASwb6e/HeFW0k4fZbZYnWp7dqcU8mSzflckzzYpctyfIgvFqvtiDtTk1VaS1yIr0vtoZ+3h9tBC8A5M/1IGIm6ZHMeH6/NOeAMgBDdLbO0Fm8PrbO2HOAUe/nevAmD2j3Ddt7UOCrrTaxIL+mRdQrRnRqaLNz22RaiA3149EzV7C8+1LfDjAvH3+1BwXqi7X+7OhoBOZA8kbqTK95Zh6GDs855lapx6aFM2dBoNKp/SIsyHMcUOo2me/7+7y+vI6OkljmjDjx7HR3oQ6CPB7VGM0lhfod9sklf5Ogx8cXGPF5flYnFaiO/sqHDIFRsiJ7CqsZ2D1bzKhvcaprp8NC8MSw4e7xbz//0pFBeu2wqr146lamJ7jWBBdXnIr3I4AxItCx1MVus7CioYXxckLMxZ2YvBS6sVhvLd5Vw3IhwvDx64jC+2VGDQ9F76lhp/zufuq2QX3eX8uXGPOfadhcZGGOfGjR7ZCQPnzGGdfsqnNscqp54xGcDaa0vTEtJtaSlpC4EGoEbD2H/LX8rcoHstJTUYMe/n0/9gmeOegyAMO9QShrKnBsXN5S2u9NIfTj5dUVdXky4TygljaVYbc2xleKGUiJ8Blan4YNRazSTXV7H2Jj2I6Z+3h5cc+xglqeXsD2/ugdX173uXfIXEx//mTnPreSFX/bw2Hc7iQjw5qYThrls58g66eiszkCUVVrHkIhDS7kM9PEkzG/gjURdtaeUx7/b6QxSNDRZyKmop7LexP4jIEgjeldmaR2Dw/1cOqsPjfDnlUsmc9epI9u9XfKwcCIDvLvtw4k4OAu+38WarPLONxQu1maXs7+8nsf/NtbZkT8h1Jf8yoZ2MyIdWQAx9owLwOUAeyDLKq2jptHMR2tz2t0mr7LB7bPqHVFn75sDQo7RnJPig52TxWw2G4t+y+TGjzay6LdM6oxmt/fvCLa2FbjQaDTOcpHEdkZ7DnQxwXp8vXR8uTGPp39IZ/2+CgqqOv7ZxgXrabJYXcpLHJrMVopqGonrIGOjtVPHRXNsq6bt3W2Svc+Fr71nWsuMkczSOhpMFibEBREfosdLpyWjtHcCF9vyqykxGDlxtPu9YrqLj6eOY4aG8evuUqxWG6+uVCeZN+6rwGyxsr+invomizNwAXD+1HimJ4Xw5Pe7qKpvam/XbjssgYvkpfN0yUvnDU5eOu9lVEbFYx1s/jRwd/LSeZ13aOncOsCQvHTePclL5+mTl87TZRn2satK1d2eMGgWH2R+gcFUS0lDGYv3pba7o3nxJ/PWng/JrVMNaTJqsqluUg1HQr2DKahvO6gxJngk3lpvPs5cjNlqZnP5NlYXrzugF8aRaFdhDTYb7WZcOFx+TBIB3h683U97XWzJreLLjXnMGRVJbLCeF37Zy5bcKu46ZST+rRrUxNvfuI+kBp1Wq43ssjqGhB/6OKmkcNdu16YBUHLz8dr9vLM6m98zVJA1s7QWR6LF5tyBV0Il+pbM0lpnf4uW5k2Icelg3pqHTsvZU2L5dXdJt3w4EV1X02hi0W9ZLJbgUZdltjgYdkgM88VstZFf1UBhdQNTnljGua/94Xx+t+aqkysJYb7OkxCtpy8MREazxRmgeSstu93ymK6UA3QkNljvUiqSWVpLZIA342ODyC6rw2azsXDZHhZ8n8667EoWfJ/Okk3u/w6sSC9hWKR/uxNDHIGLpCNwogiATqvhs38czUfXqiEDv+4uwWA0OxtztsWRTZHXRoPOwuoGbDb3Jor0pCkJIQR4e3DnySpAn1/ZQKPJwltpWfywvRCA8bHBeOi0JIX7klnSO7/r767Oxs9Lx9xRPR+4AJg9KpKcinpu+XQze4prOXF0JHVNFnYW1jgbc45uEbjQajU8csZYqhtMLN6Uf8j3392Bi6OTl86rBWqAlUAgMD0tJfWvDm6zFKik2yTixQAAIABJREFUjRGnXWWfZjIPNaUkGyj797aXqTOrg8KrRlxMtD6CC1Zcw+3rHuKU2BPa3deFQ85izqBZ3LH2YU756QL+ve0ljBb1Yeyq4Zfw5NbnOe2nC1lR4JpM4qn15N/TH2ZN6UbmLbuE57a/xoOT/o9Ef/fqrAayHfYMio4yLgCC9J4cNyKCjZ10ru2LbDYb/0rdSbi/Ny9dPJkPrpnBsv87jv+cN4HzphzYdHJQsA9aDeRWHBlnaQCKahppMFkOOeMCVNOonQU1ZJfVsXDZHsY98hNv/57dr0sqtuWp35NX7OVSe4oNAG6NoRLiUBjNFnIr6hkacXBBxVnDwrFYbewsqOnmlQl3OM5E99aZwP4sq7SWIL0noS0mVAyLVAesGSW1bNpfRUVdE0XVjdz55Vb2Fhv4YmMuxw4LIzLAh7gQPSG+nmzNHfjv0bkV6sDzgmlxlNUaWbqt8IBtrPaAT1fOqrcnJlhPqcHIPV9u44M1+8ksrWVIhB+JYX4YGs18uGY/L6/I4KLp8ay7fy5hfl785WbGrqHRxJqscua2kW3hMDJaHYQdiaNQHcbHBXHssHCGRfrz3RbVzyA2uKMeF+q6vDZOyjlKMPpa4CLEz4vND5/EVccm4e/tQX5VAz/vLOZfS3fxwi978fPSOctmHJNLelp2WR3fbS3gspmJBPn2zgSvk8dEERXozYpdJUyKD+bxv40DYF12BbsKa9BpNQyPcv0MMS42iInxwXy6ru2S5x0F7mfYH9J8krSU1KQWX78HvNfJ9vtQkw9bXmYDxnZwm3YLmlref4vLClCTRhycz5CPzocHJ93hsv0lQ891fv3FnHecX+s0Oq4YfhFXDL/ogPs9K/F0zko83eUyxyhUgMEBibxy9NNtrvmBif/n8v3ksAkut+3vPt+Qy+KNeXx07YwDugXvKKghzM+LqMDOmxuNjQ1k6V+FVNebeu2X82As/auQDfsrefqc8c7siuFRAQyPanu8kqdOy6Ag/RGVceH4cN0dgYvrjx/KivQSznz5dwxGM/Ghep5I3UlhVQMPdjAyq68qMTRSWN3I0Ag/1mZXsH5fBbuLDXjqNEyODxlwgQuzxcqvu0tJHh5+SHXQonvsL6/HaoOhB/m7Ocr+AT+9yMAxhzmtVxzI0Vg1o6TWZXRhe15ZsZf6Jgt3nzqqJ5bXpznKF1s+Z45a9r0larSiVgNfXH80c59bxQ0fbSKvssH53Gk0qrnfln4QuHDntdGRHPskrwumxbN0WyHb8qo4d6rriZkSgxGTxdYtB6cj7J+fvtqSz2cbcvHUabhgWjyD7X2uFnyfzsioAJ48ezxarYaxsUFsz3cvePr73jJMFlubZSIOUxNC0GpgXGznDfoHummJIXy6XrUW7KhHRWKYL146LTsLavjbpFi25Fbh7+3BsEh/ZxZGfDcEtbqb47glLkRPXmUDvl46PLQaLp2RQLi/N1p7CeWwSH9+3llMo8nCn5nlHDvs8PabSC+qYU1mOcvTS/DUabkmefBhu6/ORAX6sPb+E10uSwrz5feMMirrTQwJ92vz89zF0+O5d8lfbMqpZGqi68yO7LKO2wi01LNdPUS/12iytNtTYG1WOfcv+Yu1/8/eeQa2Vd5t/3e0rWF57z1ix3GcvfdiFcoepS0FCn0L9GnpYrRPN31aWjrooi1QaCkUKLNskjSBkD2cxIn33tuWJdmy5vtBI3a8HdmWnfP7Aolk+UiRjs593df/uqo6h93xOdvYQ05c8Li+MHM9b+CzTbMn58Jic/Dz94rJjtFx4/LxO2wSw4IuqoyLynb3e8MfoyIZUVr++cVVKOUSblqewN5vbWH7/CjeLRi6AzQbKPC4Lb5/1QJC1XKe3ldFWYuJ9EgtK1JDKWrqoc86N1LrG7r7uPmvh7j7H8f497G6sX9AZMrxho1N1nERqVMSoVVQ3Cw6LmYCryhstNiHnS0/n9dONPDOLD1XTpTSFiMPv1YwqAnA3G/37ZpWtpuGfCfpg+REByspazFR2mwkJVxDXEgQn1+TTHmriRC1nEtyztm1FyeGUNZqGjWwcqZ54XAtS3+yk07z5Me5qtvd1yupERqyYnQUNRvPu908pFHkQrh0QTSHv7ON0z+4hLwEPTaHi7RIrW90o8/m4Os7Mn25PAvjgyltMY7a8GJzOPmkrJ1XjtcTrJKNGuKYExfMie/tIC8hZMT7XCwsHfA6jRbOqZJLWZSo51BlB/12B5976jBXPL6PJz+upLCpB4ngrtoOVLytKEVNPWREafnR1bn8z7ZM3+0ZUVocThePvFPIHc8e5be7pqYK3OZwcs8/j3PZb/fxw7cK2VfWzm1rkkcd25wJVqaGsbekjVN13dw1gqhy1aI4NAopLxweer03kVBjUbgQmRC//KCEK363b0jlXYepn/teOOGzWZ6uGyw4WGwOylqN41bUvDkYZ8epmgcCz+yvpr6rj+9dmTMo2G4sEkPV1A0zBzhXqWwzo1FIx+W8GQ85ccEc/s52fnHDIqQSgdVp4TQaLLQZx75wDzRO1RuQCLAiJZQbliWwq6iFk3XdZEbrWJIYit3p4swELHWBzA//c5biph4UUglV7RePcBfI5Nd1I5UIpEZM3g2VFaOj+LyFzHgpbOxh7c92s+wnO/neG2cmfQxzHaPFNqw46xWFYeyqPovNQXWHedTk/7lAs8HC3z6p4uo/7OdfR2q5+g+f8OudpTz2QQkbf7GHS3/zMeWtJlp6+od1AWZG6ShvNVLaYvTt/N+9IQ2NQsqNyxIG7SwuTgzB5TonQAcax2s6+f6bZ+jqtY17lGI4ajrM6JQywjQK5scGe/LL3O+hl4/VsfmxvfzGs5Dzx6iIIAhEB6tQyaX8+XPL2JwVyaZ5kSSGqZFKBHJig7kk51wLYG6cHrvT5RuzHI5v//sUn3v6MLuLW9meEz3EIXw+IWrFqLdfLCz3CBcKmYQI7eivyeq0cM409rCzsAVTv520SA0/fbeIZw9UExOsQj7Gaz6TxIcG0dDVS3Gz0VeJOxCvuP/PQ7VIJQJ//qhiSsbEipp6eO9MM59fncyhh7dx6vuX8J0r5vv991woW7LcjqUfXpXDzSuShr2PRinj6iXxvH26cYhw2tIjChciU4DN4eSN/AZ6PS0HA3nknSIMfTb+8cWV6FQyTtYP/gDvKmrB5nCxfpz24XCtkji9alYt0l45XseatPAJJx8nhqlpM/bP+f731/PrWf1/u/nwbDOpkf6tFRsoFHl3RU7XB75l93wK6rvJjNKhVsi4eUUSdqeLTrOVeVFaFie5n1d+7ezLfhmOilYTm7IiSYlQX1SjUoGK1e7ktRPuUGGNcvJTpNkx7t1OxzCL4ZN13fxxT/mwc88An5S30WiwEBui4t/H6+i3z+1z4mT59c5S7n3+BGXnLcwq28y+NHdv2ORIlLeacLrA6nDSbp59Iu94eD2/ntU/282P3y4kL0HPf76yjgVxen63u4w/7CknJUKD3eniqX2VwPAjUhlRWkpbTFR3mJnnWcBE6pTs+dZmvnXp4JYdb7Bnfl03fVbHiG0kM4HN4eQrL+QTHezeqS2dpLgI7grS5Ag1giCQHRuM0WKn0WDBYnPwm51uwWJ/ubvZZrRd+ckQFxLEs3esJCNKi1wq4WfXLuSxGxf5LPzgnqcHhoyLWGwODL02Pipt442Tjdy5LpXX7l3LI9fk+vUY5zKpERrCNQriQ4LGvIZblRqOw+nisQ9KUCukvHHfOv795TV8+9Isvn/ViAkBAUF8SBA9FjtNBgvZsUNHhAaKnL+7ZQlROhU/+M9Zvx+Hd61166okYvQq9Gp5QFbyXr4wlqPf3c7t60YfYfnCmhT67U5ePDq4jai5Z/zfQReUcSFycfFJWTsdHpWsss3km//cV9bG6/kNfHVrBtkxweQl6IcsGt/IbyRKp2RN+vhrYRfE6wftCuTXdpEaoQlI5dvucFLb2cslC2LGvvN5eCu2ylpMLExwW+uWJIWglM2tmf838hvpMLvnXtekT938e258MBIBTtV1s20G6qImi8vl4nS9gS2eWduMKC0rU8I4Ut1JZrSOCK2SpDD1nMi5cDpd1Hf1sSMnmn6b86IalQpUdhe10G6ycuvK4XdLxkt2jA6LzUlNh5m0SC0fnm3mmf3V9FrtnPLsRP92Vyn/+6kcvrA2ZdDPljS72wK+ujWTLz13nJO13axKE6vEB2K02Pj3MXdjwvGaLl9+kret6XOrk6nt7PWN/YxEyYCFa2O3JeCsx/7gQHkHoWo5L9y9muwYHYIg8NL/W+3JqxBQySVseWwvr3mS7tOGGZHKjNbS59lUyBqQVRUVPPT1ClErSI3Q8O9jdfzhv+XcvTGNb+yYN0XPbmIcqeqkyWDhz59byvffPDtpVxS4HRdecWC+R8wpbnKHZDcZLPzkmlx+8nYhwSoZQYqpvY65acXQsdyE0CCCVbJBG18ul4sv/O0Ih6s6UcklpEdqePDyrDl3nTXVCILAzSsSGY9Ja2lyCHKpQHVHL5fnxqCSS1mREsaKlLCxf3iGGZjfMZzjQq2QkRKuJkSt4IqFMZQ09/CHPeX0WR2+9/xT+9xjMUuTQtEqZSyICx4x724kvMKFt7UokInUje2izorRsTY9nH8erOFLG9J8TqcWcVREZCp4Pb8BnWcnrnJAzsXju8pIClNz75YMABYlhFDcZKTVaOH3u8soauphb0krVy+Om9AIhbfqytRv59n9VVz7pwP85eNK/z4pP9HQ3YfN4ZqUxXpDZiQyicBbpxs5XNnBLX89xKPvlUzBUc4c/XYHh6s6uHVlEu9+dQPfuWLqwuDUChnzonW+RdJsodFgocNsJS/h3DjV7etSkEsF398tSQrhRG3XrG5NAXdwm9XhJCHMXSNY19k765/T+dgdTlonYH+cKUz9dk7UdvHsgWri9Co2zou8oMcbGNBpsTn43ptnqGgzoZJL+dYl89j1jU3kxuv56zDn8tIWI1kxOlalhSMRYH9FxwUdy1zkpaN1mPrtKKQSTgxwXzV099Fvd5IeqSU9UjPmqMhAG/3Aqsm5RGmrieyYYObHnsvWEgQBjdK9oBYEge3zo7E6nEiEc5sIA8mMOrfQyIoZO/tlcWII1R29WOwOdha2+O/JXCDvnWkiSC5l07wosmJ0lLRMbgzX5nBS39Xny5fwVoUeq+niT3srWJcRzudXJ/PTa3K5c/3MBAgKgkBuvJ4TNV2cqO3C1G/nP6caOVzVydWL41ifEcGvb1osihaT5IHLsnno8rGv4dQKmc8BuyNn9mwiwWCn0PxhHBcAf7t9BX+9bRmCIJATp8fpwpfv5HS6eHx3GW+ebOR/3zjD/S+d5MrffzKi23Ak6jp7CdcofGH/c4Hb16bQaLCwq6jV93fNE7hWmjuvhMiU0mu182FhM9cvTeDDwhbfbk5jdx/Harr49qVZvlnPvIQQ7E4Xt//tKIVNPfx2dxkOp4urF8dP6HfmxgfjcsGnf/+JTygZaxdppvAeX9okhIswjYLNWVG8kd/ge35/P1jNLSsTfTO1gUpVu5leq92XXWJzOPGuP039do7XdBEdrMTc78Bic7I+M5KcuKlP5s5L0LOzsGXU9PQLTVb3N1Uea/fAC+UrFsayITMCncrdrLMkMYQ3TzbSZLAQ52cL7lTSYeqnos3MylT3Tot3NCQxNAir3YnZ6qCr1zaoinC28/zhWn7+XjGHvrMNfVDgNiM9+MppX0Dj17fPm5C4PByZ0Vokglu4aDJYaOnp5193rx7ktrsiN5afvltEm7Hft0vjcLooazXy2VXJ6IPkLEwI4UB5e8DsWAcCLpeLvx+sZkWKewdvoPvK9x0UqSE9UsvBytFFn+Jmoy+ArmEOZiy5XC7KW4zcsGxoDflAtudE89QnVSSEqoddyGZ6nKUKqWRcdZhf2ZrBsuRQ2oz9PL67jC6zldBpPK+daTDwu91lPHp9nu/3Op0uPjjbwuasSIIUUrKidTx3qAaH0zXhz3tjdx92p8sn8uhUchLDgnh6XxVWh5NvX+pe0E4koHwqWJIUwh/3VHDdnw4QopYjEQQWxuv59U2LL/gcJzJ+NmRGUNBgGLW1JRDxZrOEquVEjeAkGOjQ8uXyNfawJCmUqg4zRoudR69fyLqMCNpNVm7560H+790i/vTZZeM+jtrOXpKGEVRnM9vmRxOhVfKfUw1clhuDy+UShQsR/1PaYsJic7JxXiTlrSbfRZK3v/vKvFjffRcluhexhU093LoqiYJ6AzKp4Ptgj5fVaeFcuyQeo8XGpbkxFDX1UNMRmJZy76JzsqF21y2NZ1dRC7uLW/nc6iTeOtXEj946y/N3rfbnYfqdB145xfGaLu7emMbpOsOwF8sahZRLFsR4gjOnxyKYlxDCy8fq+cUHJShlEm5bk0KYRoHF5uD5w7W8W9BEUVMPT922PGBqG72WwPO/pLyiBcCSJHcwVn5t96wSLh59v5jX8xso+OGlqORSajvO2R+9Qb91nb1zSrg4VddNn83BiZou3/hPoOFyuThY2cHmrEjuWp/GitSRk/XHi0ouJS1SyzP7q3C5YF1G+JARwUWeLIBTdd1s9+zE1XX2YrE5fTu4a9PDefLjSsz99gvK3JhLVLabqevs497NGbQb+9lT0oahz4Y+SO6rQk2L1JAepeW1/AaMFtug88dASluMrEoNw1Bko2EOOi4aDRbMVseY1uzlyaGEqOUjVgCHahREaBVEaJXjChN0O160HKvu5PHdZRyu6uCy3Ngxf85f7Cxscdc02k/yzO0rkEoE8uu6aDP2c1mue5Q1K0ZHv/3cONd4qevs5dH3i4HB1zrZMcHUdbZw6YJoX87HTHPflgxWpYbTZ3Pw8tE69pW388NPLxBFi2nmy5vSuXpxfECOeI9GhFaBUiYhO2Z8TYgJoUHog+ScbXQ7Lk56ROUlSaEkhKpJCFVz3+YMfrWzlAMV7awd57h0bWcvS5Mu/Hs5kJBKBC7PjeHfx+sw99ux2p1DCh9GQ7waEBkX1QMcBelRWt7z7NC9fbqRhfH6QTsRMcEq4kPcH+IffXoBcqkEh3Piu9tqhYzf3LzY9+efvF3IocqOgNspB7fzIFglm/TCa2t2FDqVjH6bk69uyyQmWMVjH5bSagzc2WOXy0VhYw86lZy/fFRJhFbBvZvTfYsM9w6VmvtfOsnr+Q0sSw4d8SLa33irzZ7YW4EgwNP7qsiJC6amo5fmHgt5CXosNgeHqjoDRrio6+pFLhWIGWZ22sv82GCUMgn5tV18Km/6LoYnw4tHaum3O/nc6mR2FbVic7h8855ex0V8SNA54aKr17egnQuUtrqt+EerOwcJF96RmEA4h9V09NJptrIjJ5r1mf77HDxyTS4vH6ujqMnIw5cPTUBfGK9HKhE4OUC4KPGMLnhzBNalR/DE3goOVXbMqqyaqeREjXs0ZHlyKK2e1qSTdd0sTgzhtRMNhKrlRGqVvgvdD862DOs4MPTZaDJYyIoJprCpZ06OinhHYcZyLcqkEp66bfmorqiblicSOsGFV15CCEFyKQcrLky4cLlcuFzwSXk7r56o5+4Nab58ieGobDcjkwh8XNrGE3vL+crWTN4raEYhlfh2vb3iYGmLcULCxW1/O0Jjdx/3bE4fVB+aF69nd1EL37oka5Sfnl7UCplv7O3SBTHYHM6AbrGYq6jk0gtqqZopBEHghmUJLBpnBa4guNttCj25KifrutEqZYOqxe/emMZfP67k3YKmcQkXNoeTxm4L1yyeW44LcG92P3eoht3FrT5X23gRhQuRcVHVbkYQ3DukaREaunptnKzr5lS9gYfPm3UTBIHn71pFcJDc90XhD5U7JVyNxeak1djvS8YOFKrazaRGaie9GFHJpTx8+XwsNgdROhXrMiJ47MNSjlV3ccXCwFygNnT3YbY6eOSa+cyP1TE/Nhi1Yugp5eEr5vO9N86Mu1HGH8yPDea1e9eSEBKEoc/GH/aU02ywsCAumF/dtIh1GRFs+uWegBo9qu3sJT4kaNTPikImYWG8nmM1XTidLl+SemN3H4erOjjT0MOd61P9nuQ+GZ76pIrajl4itEpf9VVBvcEtXHT2EeOpt/OGTp3fVDSbcTpdvoyBo9Wdvr//8VuF/G1/FRIBfnPz4gmPz/kbb0aCv3d0VqeFs3qUUE2vXf3kgPo4b8tBZrT7ImZ5SihhGgX/OlIrChceTtR2EaxyXwzHhgQhEeAfB6r5ucFCeauRP966FEFwO9uyonU8/UkV1y+NH/S9dO2f9lPX6RYqsmN0xIUE0WiYe8JFmU+4GPuiePkYYYEPXDbxTCaFTMLylNAxR3ZGo7i5h2v+uB+L7dxuZKhaMapwUdVuYk16OHKphL8frOGezRm8f7aZdRnhvo2DzCgdgmeca7yiiqHPRlW7mQcvy+aezemDbvvihlQuWRAz4eDB6UQULUQmyk+vXTih+y+IC+a5QzXYHU5O1nWTl6AfdD2nkkvJitFR2jy+686mbgsOp2tWBHNOlOUpYUTplLx9qpHPrJpYILgoXIiMi+oOM3H6IFRyqU9BfPCV0yikEq5aFDfk/ilToLB6XR3V7eaAFC688/uT5dYBH97ceD0quYQjVZ0BK1x4U+mzY3QsSx75uX92ZRJBcinbptku712MRQWrePyWJUNuT4/UjhlgN53UdfaO6wtqeUoYf/6ogqWP7CQmWIXRYh9k9Q7TKLjPE5Q7U1jtTqrbzdidLh56zX2eUCulvpaguq5eEsPc4opW6XYqeRdTc4G6LvfYQ4RWwak6Axabg9aefv5+sJoNmRGcaTDwUUnbtAkXFpuDe58/QahawVWLYtns6Vw/UduFVimbkSydxUkhvHWq0SfAFbcYSQpT+8RPlVzK51cn8/juMspbjWREBe6iaLo4UdPN4qRQJBIBrVLGwng9u4tbidIp+evnl/ucPYIgcOf6FB58tYCDlR2+3b0us5X82m4yorQkhAaxNCmUnUUtnJ5lQcbjobTFRKROOaMW9TXp4fzi/RLaTf1EaMdO3D+f3UWtWGxOvro1g5QIDc8dqhnUtHY+LpeLqjYzy5eHsTwllP8Wt/LM/irqu/r4n63nvhOCFFKSw9S8nt+AVinjs6uSx2z/8I4iDTdSo1bIfC4OEZGLlQXxwfTbnRQ29VDU1MPdG9OG3CcrRsdbpxrH5Ryv6XQ73ZPmoHAhlQhcsTCWF47UTnjtJEqQIuOiut3s6y32/rekxcid61OnbdbeGwYVaDkXFpuDhu4+v9rh5FIJSxJDOVbTOfadZwivtXusXRaJxG25m86AsvGQEaWlqt2MYzy9XtNAbWfvuL6gvrotg1/ftIhLc2JIDlezNDmU71+Zw7tf3UCsXhUQYkxNh1u00CllGC121qSHsyQxhALPAqm+s5fE0HPPNTE0aMJp24FMWYv73+CGZYlYHU4KGgz8/r9lSCUCj924iGXJYZweZQHib07WdfPf4lbeKWjk9meOUtTknsM9UdPNokT9jMx9L04MwWix87P3ivj2v09xsKJjyOLntjXJqOQSnvy4atqPL9DosdgobTWybIA75qkvrGD3Nzdx+DvbhuSoXL04nnCNgn8eqvH9Xbln8fndT83njfvWoVfLiQ8JotNspc/qmJ4nMk2UtRgnbEH2N97ax1N1k6uwPlTZQXaMjm9cksV1SxNYkhjK2UYDdsfw8+Ctxn7MVgdpkRq2ZkcRJJfyyw9KkAiwI2dwVfu9mzOQSgQeeaeIt083jnksVb7w15l9TUVEAhVvSP1jH5Zid7qGzXvJitHRY7GPK4zSl3s2B4ULgKsWxWK1O3nhcO2Efk4ULkTGxOVy98N7668SQtUopBIitAru25I+xk/7j/iQIGQSwadCBgrVHRcWzDkSK1LDKGzswWix+fVx/UVps5FYvSqgGxNGIyNSi9XhpM5PIwoOp4udhS2TEkJ6LDa6e23j+oJSK2RctzSBR2/I4y+fX87vP7OEO9enkuPpCC9rNY75GFNNmUc8edAzRnbFwhgWxuspazW65+t7LCQMeK4JnkrUuYI33+LWlW4X1SPvFPFafgO3rkwiOlhFXoKeijYTpn77tByPdyTjva9tRKeU8dtdpZj77RQ39wxaCE8nK1LCEAR4cl8VH5e1ESSXcnnu4MVVuFbJ9UsTeD2/AYttbi2sJ8rJ2m5cLliafO5iOFKnJH2EEUWVXMrq9HBfWBycE9QyBiw+vWNlc2lcxOl0UdZqmvFWrgVxwUgEJlXNbbU7OVbdNWjkyp3N5PQJUC09Fq5/4gCXP76P771xhsoBIeFqhYxt86PotztZlRo+JH/rphWJ7Pz6JlRyCUVNY39nVLaZkUqEObuIEhG5UNIiNCxODOHj0jZkEoElScMIF55zUnHz2J+52s5eFFLJqLlns5kliaHE6lVUtpuJ0I5/Y1MULkTGpNNspcdi941/SCUC3740i1/dtHjawhbBHaKVEBpEdYA5Li60UWQkVqSE4nQxqPIukChpMc1qe2i6ZzfOXw6FV47Xcfc/jvFxaduEf9a7aL/QWcbMKPf4i9Pp4uWjdRyrnhnHTlmLCUGA65cmsPubm7hxWSILE0JwumBXYQsul9tl4SUpTE1Dd9+IO4mzjbIWE7F6FUnhapYkhVDeYmRrdpTPrr0wXo/LBWenyXWRX9tFcria1AgNX9yQygdnW7jvhRM4XbAkeWaEi9QIDR/cv5ET39vB4e9sZ/9DW7lu6dAgyfUZEVgdTl/Y4sXKidouBIEJtTakRWio6+z1BeCWtRoJkksHZeB4HZNzKaCzqsNMr9VB9gx/P6kVMjKjdBTUT/w7/HS9u5VoYBPXwgS95zb3eePlo3Ucr+lCIsBzh2rYX94OnHNFXJnnHuO97DxB0ItUIpAVraO4uWfY2wdS2W4iKUyNQiYuG0REhkMmlfDGfes4+t3tvH//xmGD9bMGy8C6AAAgAElEQVRj3O2KJaMIF4crO8j5/vs8f6iWhLAgX5bZXEMiEfiUZxR+IuP/4hlIZEzOOQrOLaru3pjGJk9i83SSFK6hpiOwHBdFzUYkwrkRGn+xJCkUqUQYFO4XKNgcTipaTT71eDbi3XX07l5dCC6Xi6f2ue3s41HSz6fOT5bAzCgtFpuT0lYj332jgL98XHlBjzdZylqNJIaqCVK4M3EkEoGFnkC5P+wpBwaLNNkxOmwOF6UtMz/m4g9KW4y+EapXvryWUz+4hCdvW064Z87dG6432ry6P/E2TwDcuT6VULWcI1Wd3LM5nU2Z038e9zIvWjdmE5P3tTrTMPbiai5T0mwkNVwzoc2C1AgNTtc5y3F5q4mMKO2gC+F4j4A4l8JxD1a4AzFHC4idLhYm6CloMPjahMaL9zmsSj33HFLDNWiVMgrq3Y/3Wn4Dq9PCeOKzywD4+4FqVHIJsZ5FwI6caB67cRE3r0gc8fdkxwRT3Gwc8/gq28ykzcJ2CBGR6SZSpyRjhDE1vVpOTLBqVOFif3k7FpuD+bE6rl40swHeU423HW8irhJRuBAZk6p29wVNSvjMf2mlhKupae/F5XKxp6SVVf+3a8Z2lb2cru9mXrRu2EaNC0GrlA1J3g8UajrMWB3OGbfiXgh6tZwIrdIvzSIflbb5xiMmM6pR6yfHhffL8p+HarA5XFR4RJmfv1fMpl/u4YXDtdOS6VHeahoyXx4drGRetJbuXitXLYobVDOW5/n/05PYmZxOLDbHmKNbTqf7dZ/nef5SiYDsvET7SJ2SOL1qWkIRmwx9tPT0+4SLYJWcd7+2gQMPbeXBy7IDfjcnITSIYJWMM41zL0ByItR29pIUPrHzg9cl6a0zH+5zGRusQquU+Vpd5gIHKzqI06t8uVgzyaIEPe0mK02GsWfaTf12vvHySXJ/8AFP7qskO0Y3KBtKIhHIjQ/mdIOBE7XdVLWbuW5pAknhavIS9Bj77aSEa3yfaaknX0olHzl4MztWR6fZSpupf8T7OJ3ucWF/b86IiFyMZMXoRhUuCpt6yIjS8u8vr+Vr2zOn8cimn8WJIeTEBvvcZONBbBURGZPqdvdsYyBU8iSHazD22/nmy6d4+3QTVoeTdwuax6wzu1Baeiw8+l4xa9LDuXH5ud0Ll8vFqbpuduRMTV3fokQ97xY0jyuBeDop8dQ5zeZREYCMKI1fHBfP7K8mOlhJSrhmUqMndZ196IPkF5wX4hUuXj3eALiDbK12J/8tbqGxu4/vvF6AVAI3r5hY/dRYuFwu7E4XcqkEu8NJZZuZTVmDd/IFQeD9r20EGLJYTglXE6yScarewC0r/XpofqOizcRtTx8hPiSIl7+8ZsT7FTQYsNico1YWwrmd2KnCanfy/tlmHE73mMDAEYNY/czX5Y4XQRDIjddP21hNoFLX2Tvh2lrvDnlVuxmjxUaTwULGefWgEonAvGgtRXNEuHA6XRys7GBLVlRAfGcuHCDKjhZkbrE5uPaP+6loM3HFwlgq28zctHzo6FReQgjP7K/ie2+cQSWX+FrHrsyL5XS9YcLigvc7vLjJOMTa3m938F5BMxlRWvrtTjGYU0TED2TF6DhY2YHd4UQmlWBzOAfV9Z5t7GHVBbYUzhYEQeDt/1k/oQ0UUbgQGZOqDjOJoUEB0YN9SU40+8ra2FnYwuKkEPptDg5XTb4nfTycrOvmC3874g4VNFgGCRf1XX109dp8O8b+Ji8hhH8dqaOmo3dKKmYnS0lzDxKBEe1ws4WMKC1vnhxfNdVIOJ0ujlZ3ctPyRAQBXjxS56t4HC+1nefqQS+EELWCSJ2SNmM/cqngGb8wUtFm5t7N6Ty7v3pQWJ+/+PHbhbx0tI6bVySyIiUMq8NJ5jD1lSO9JoIgkJcQErCOi4buPm7880E6zVYaDX0Y+mwjiky7i1qQCIw5SpeXEMIHZ1vosdgInoKsoNfz63nw1QKkEgGFVEJOXLDff8d0kRuv59kD1UMu8C4WDL02eiz2CY+ShagVhKrlVLabfYLqcJ/L7Nhg3h5nRV+gU9JipNNsZW36zI+JgHsMTiYROF1v4LLckavN95a4XXu//8ySYSvmvdywLIGzjQZO1HRz/dIEtEr3Zfyn8uL42XvFE64N9s7cFzf3EKZR+Fx6NoeLp/ZVUtxs9FW5iqMiIiIXzqKEEKx2J/vK24nSKbn+iQP89fPL2Tgvkk6z2501m7+vJ8pEXZ+icCEyJrHBKkICpDkiMUzNs3es9F1g/WZnKb/7b9mUXfwDPLG3HJlEYGVqGA3nBZid8iy0Fk2ZcKH3/Z6AEi5ajKSEa0a1oM4G0iO1GC122oz9RE0yubmhu49eq4OsGB0uF/R56nEn4lCqbDf57T2UGaWlzdjPlXlxvJ7fwLsFTTicLhbEBZMcofZ7nfDp+m6ePVBNZpSW5w7W8Mz+at9xTIS8BD1//bgSi80RcO+rj0vb6DRb+d9PzeeRd4o4XtPJ5nlR9FhshKgHZzTsKmplWXLomPW/6Z6d0Zr23gnZJMfLocpOglUyNEoZGVFalLLAek0nwoK4YKx2J+WtJubHXjwXdF4uZJQsNUJDdbvZN8o23OdyfoyOFw7baTJYprTe3Nxv5+VjdWTF6FibHuHXx3a5XFR39PqqPdcEiHChkkvJitGN6a56/0wToWr5iEGaXuZF63j+rtVDxPH4kCD+dffqCQeShmkURAcrefV4A4++XzJolDBCq+Sezek8sbcCEKtQRUT8wY6caGL1Kv68twK1QorF5uSlY3VsnBfpqyrPifX/NcFcQRQuRMbkf6/MmelDGIJ3V2hVWhiu3XCsupOt2f4f1+gw9bO7qJU71qUgk0p4al8lDqcLqeeC4XS9AYVMMmUjE/OidShlEk7XG7h6ceCE9JS2mGY8sd0feB0j5W2mSQsX3raDedE6nJ6As/JW07gXGX1WB/VdfdywdOQAtYmQGaXlQEUHt69N4fX8Bt7yXMjnxOpJDtNQ2OQ/x4XT6eJ7b54lQqvklXvW0m9zcqiyg1Zjvy+Mc7zkJeixO10UNvVM2BI/1dR09CKXCnxmZRK/eL+Ew5WdnKjp5i8fV/DApdl8cX0qEolAY3cfhU09POSpgR2NpDCPcNFpnhLh4khVJxsyI/ntLYunJddkKjkX0GmY88LF+2ea2FnYSkN3L4sSQ7htTYpPuJhMeG9KhIYD5R0cqepEJZcMe17Kjj2XdD+ScNHda6WgwcCGSYa5lrYYufkvB+nqtbE0KYTX7vWvcHGwsoNbnzwMuIOyp1KAmShZ0ToOVY7sDO23O9hd1MrlC2PG7SgabpdysmGk2THBfFTaRnaMjt9/Zonv+iZWH0SQQkqsXsWuotYJVRaKiIgMj0Im4a4Nafzk7UIAwjUKdhW2YOq3U+hxxM6Pnf3X11PFxee5FJlTLEkMRS4VOFw5NQGdb55sxO50cf2yBOJDgrA5XLQaLZj67ZQ0G8mv7SInNnjKKsLkUgkL4oIDykLfZ3VQ3WGe1cGcXrzCxYUEdJb4hAutbzdzIgGdFW0mXC7/jd3cuDyR+7akk5egJ1avoq6zD51SRkJoEEnhauq7ev22kD1V382pum6+dck8glVyInVKrloU51vITwTvuNW7p5somIbQyolQ22kmIVSNRiljUaKePSWt/P1ANWqFjJ++W8T6R//L117M59H3iwHYPj9qzMf0Bi362wEDUN/VS0N3HytTw5BLJQHnYJkoqeEaNArptISZziQ9Fhtf/ucJdhe30Gt18LdPqnjglVMDHBcTX4ynRWho7rHwen4Dt6xI8i1KB+I9lxeNUov5zP5qPv/0EXYVtkz4GAB2FrbQ1WtjQ2YE5a2mCbdsjMVZT+vM47cs5m9fWOHXx75QUiM0NBos9Fkdw95+oLwDY7+dy0cZJZlKVqWFEalT8uRty8mM1pEWqSUtUkuQwn3euG1NCv+4c+WsHyMSEQkUblmRiD7IHRD/m5sX0293srOwmcKmHmKCVb4GMpGhiMKFyKwmSCFlUUIIe0paKTmv0stqd/J6fv2wLQBOp2tcF06vHK9nYbye7JhgX21cQ1cfj7xdyKW//Zij1V0smoLd0oHkJYRwpqGHN/IbOF7TNaW/azy4LzpnfzAnuCuYtErZpAI1vZQ2G4nTq9Cp5L6MiYnUenpnijOj/SNc5Mbr+fal2QiC4BND5scGI5EIJIepsTlcNJ438jRZTnkabzbNG3uhPhaxehXxIUE89UkVV/3hk4AS62o6en273atSwyltMWHst/PPL67i8VsWsyQplAMVHbx5spH0SA3p47BUa5UyIrQKav0gXPTbHbx0tNb3WF4hd+UcCfiSSARWpIaxr6xtpg9lSvF+Lh+5Jpf/fGU9d6xL5WhVF2UtRsI0iglVoXpJjXC/F+VSgXs3pw97H32QnPiQIIqbRhZcvSn4D71WQKfZOuHjqO/qJUKrYPv8aHo843n+pKLNRIRWwdWL4wNqrBLOtbvUdA5f5f7B2WZ0KhlrM2ZmvOWeTensf3BrQASwi4hcDGiUMp68bTlP3raM9RkRxIcE8fQnVRyu7Lio8i0mgyhciMx6Ll0QQ2mLiUt/+zE/9+x41nf1cuNfDvL1l07xyw9KhvzM118+yZbH9o66OGoz9lPY1MOVnp7hBI/1tKG7j/zabnJig/l/m9K4bW2K/5/UAJYkhdBnc3D/Syf55ssnp/R3jQevw2AuCBeCIJAeeWHNIiUtJuYNeC0yo7SjVl2dT1mLCalEmJK6Ye8C2vtF6N3l9+7gXiin6w1E6ZTE6Cc3ZjMQQRB4+ctr+P1nlgCMuoiaTlwuF7Udvb5qxVVpbjFgTVo4CxP0XL04nj9+dilHvrONj7+9hX99afW4dyaTwtQjLmbGS11nLzc8cZAHXy1gy6/28sArp3jvTBP6IDlZc8AV5WVLVhTVHb1UtV/Y6xXIeCszYz2fp/UZEVgd7naYxNDJjT6kR7nPK19YkzLqOFx2jI7iURwXZa1GsmN0GPqs/G532YSPo76rj/hQtU9MLfNDDfVAyltNAZvBkOptd2kb/r1b0GBgaVLojOXQCIIwZa5RERGR4VmZGsaSpFAkEoFbVyVxpqGHRoOFDZn+HaOba4hnKpFZz90b09j3wBY+vSiOp/ZVcaSqk1v+eojKVhMrU8J48UgdTYZzO8xnGgy8ebKRxm4L1z9xgMMjzJ5Wd7gvMryLUq/joqLNTHmbia3ZUTx8+fxx7a5eCJfnxvKbmxfxmZVJVHf0DusgmU5KW4woZBKS58juTHqklorWyS2G7A4nFa2mQQvE9ZkRFDQYxm2pLm81kRyunpILx3TPIiHHM8Oe7BFHvO/tC+VUfbcvQNYfxIcEcXluDHKpQGWALFC7em0Y+881OqxICWNrdhTfvixr0P0EQSApXD2kUnA0ksM1F+y4eOi101S3m/nVjYu4bU0yb5xsZFdRKytSwiY8rhPIbMlyu3r2lrSOej9/jyBMJ80e4SLGU1e7MjUMhUxCr9Ux6d3wrGgdf/7cMu7fPm/U+y2IC6aizUz1MJ87q91JdUcv2+dHsyQxlLONEx/ZaejqIyEkyDdOdyEut+GoaDNN+XfxZPE6LqqGOe86nS4q2kyzvqFLRERk8ty3JYOSRy6j5JHLuGNd6kwfTkAjChcic4LEMDU/uCoHtULKZ548RKuxn+fuWsWvb16E0+Xi5+8V80lZO/VdvTy+u4xglYzd39yEUib1hReej/cCzrsTrlbICNMo2FvSisPpmjY7l0Im4dolCezIcV+4F09gN/9C6TD1D7EFFzcbyYjUIpsjtYTpUVqaeyyTEoSqO3qxOpyD8j7uWp9GdoyOh18voLt3bEt1Wav79ZwKVqWGEa5R+ELbYoJVKKQSv4wnGC02KtvNfq8ClkklJIdrqGr378JmstR4Fhte0Ucll/K321f4JUA0KUxNU4+Ffvvws+9j4XK53MG9S+K4flkCP7hqAfse2MLXtmXyla0ZF3x8gURSuJq0SA17SkYeF3n1eD15P/yQspbAcOtMlCaDBYkAUTr3fLNKLmVFivt9NplgTnALapflxvjyCkbic6uTUcok/Oy9oiG3VXeYcThdZEZrSYlQUz3B84fT6aK+u4+E0CAidUqCVbIJ5QCNRafZSlevzdfUE2holTKidMphHRcN3X1YbM4JtzCJiIjMLZQy6axu/5ou5sbKQ0QECNcq+caOeTicLn527UIWJ4aQEKrm5hWJvHmykc89fZj1j+5hZ2ELd21IIzFMzbLkUN88+PGazkELuuoOM1KJQMIAi258SJAvIC5nmtPtvfVI3tTh6eArL+Tz5X8e9/3Z5XJR3NQzJxpFvPgCOkew8Y5G2TBjMwqZhMduXESn2cqPPanRI+HdyfRXvsX5zIvWcfx7O3wjIlKJQEJYkF8CIQsaDLhc+NVx4SU1QkPlJP49pgLvWI13VMSfJIercbmgrnNymSONBgtGi53smHPnouhgFV/fMY/FiVNT0TyTbMmK4lBlB71W+5DbXs+v51uvnMLYb+dw1dSENU81zYY+InXKQc0S6zPcLR6TFS7GS1Swivu2ZPDB2RYOlLcPuq3Mk9mTEaUlOVxDm7EfU//Qf4ORaDf1Y7U7SQgNQhAEMqN1vsf0B96coPQAXvynRGiGdbp5nSei40JERERkbEThQmROcfvaFA49vI3rlyX4/u57V+bw6j1rePFLq/n+lTnctiaZO9e7rVgrU8MoazVR19nL558+wk/eObfQrO7oJSE0aNBFZLwn50KjkE75heT5RAcrCdMopk24cLlcnG00cKSq02dhPlDhrrpclzF3ZvAyLsC6fLaxB6lEGGJRzo3Xc+/mdF470cAb+Q08+XElzx2s9qXKN3b38dtdpTz1ibtedzovWpPD1NT4IePCK+D523EB7jrDmg7/tZ9cCF6RZyo+714XR+0kcy6KPdW2c0lIHI0NmRFY7U7ya4dmE/3fu8UsSQxBHyT3a+XvdNJksPjGRLxcsiAarVLGomkQor64PpX4kCB+/n7xoJGb0hYjEsE9VufNaxhupGQk6rrcwlxCqPszlBmlpaLNhNXupMvj6Gs1Wnh8VxlWu3PCx+1thZoq55o/SIvQDJvPIgoXIiIiIuNHNtMHICLiTwRBGBIUqJJLWZbsDtQ7v+d8tSdo7/tvnqHX6iC/tguXy4UgCFS3m4cEJnpzLrwtDdOJIAjkxAZT2NSDy+WivqsPq8NJTYeZqvZe0iI1rEgJQ6v0z8e602ylx+LeVfuwsNldiXawmjCNgk/lzUxt21SQFKZGJhEmZV3Or+siO0Y3rA37f7ZmsrOwhftfOheo+tiHpe4mic5ebI5zC4PMqOlbeCaHazhS1el7n0+W0/XdJIYFEaZR+PHo3KRFaLA6nDR09fncIjNFTUcvMcGqKakUTR5nJaqhz8bXXsznR59e4BM74NzY2LyLRLhYEOd29xQ3GweJp23GftqM/fy/jWnsLmrl7DS60vxJs8EyRARNj9RS8MNLpqWKUiWX8rXtmTzwymk+LGzh0gUxgHtxnRSmRiWXDnrP5saPz21V3+V+f3u/PzOitLx4tI7LH/8Yq8PJvge28vapJn6zq5ToYCW3rEya0HFXtJlQyiTEhUwuwHQ6SI3Q0G6y0mOxETygHaas1UiEVkGI2v/nUREREZG5hihciFzULIwPQSWX+Oam201W6jr7SPTY6ZcnD55j9zou5k/zmIiXnLhgnt1fzQ/+c5Z/HKwZcntmlJb3vrbBL/kT3t0hiQDvFTSzIyeanYUtfGlj+pQs4mYKuVTCgng9x6onVjXrcLo4WdvNdUsThr1dIZPw+88s4blDNdy8IhGTxc7Lx+qx2BxsyYriC2tTONNg4FS9YVp3zJPD1ZitDtpNViJ1k+8KP11vmLJdYG+FY2W7aUaEiy6zlecO1VDdYeZkXfeUHUO4RoFGIR1TuDhY0cHekjb2lrTxhbWDhYuE0KBBC6G5TKROSYRW4XOaePG2+MyPDabJYOGfh2qwO5yzLoen2WAZ1s02HaKFl+uWxPPnvRX8+sNSdsyPRuIRdTM84mrKJAJ+6z2OC+/35/njeR2mfio9mTZ/2lvBmvRwfvZuMYY+G1kxOn746QWjPn5Fm5nUCA3SAA6jTRngVBnoUitvDdxQUREREZFAQxQuRC5qFDIJS5NCOVDRwXVL4nktv4ETtV0EKaSY+u1D+uC9eRcz1bOcExuM1eHkHwdruG5pPBszI4nVq0iN1PDh2Rb+940zvHGykRuWDV1MG/psmPvtI+5K/eWjCn7+fjEC8NNrF/ouAq/Mi+Pt04186R/HcQGfXTWx3bDZwIaMCJ74qGLIbtholLYYMVsdLE0eefGeGa3jx1fn+v686jzHT2KYmssXTq97xWf17jBPWrjoMPVT39XHbWuS/XloPtI8IXuVbWZSws0khqmnbVHSabay7Vd76eq1oVXKMPXbhwiY/kIQBDKidRyoaMfpdI3o4jrlqW2uOK+2d67lzYyH7JjgIQHF3hrP7BgdzQYL/XYn1R1m32J7NmC0uNtrYv1QLXwhyKQS7t8xj6/+K5+3C5q4dEE0Ve1mts2PBkDjDZqcwKhIQ3cfYRoFGo8bcGVqGLesSCQuJIhf7yylos1MZZsZlVxCbWcvl/12HzKJQLRexcEDHdy+NmXId/FAKtpMLByn+2OmSPMcf35tt0+4cLlclLeauGpR3EwemoiIiMisYXZtR4iITAEb50USJJfy0OXZqBVS8mu7fE0C54+KLEsOZX1GBJuzImfiUH2CSU5sMD+7biHXLIlnVVo4UToVn12VRE5sMH/4bxl2x9A54R+/VciNfz44Yl3ge2eaSQ5TE6sP4t2CJirbzMilAl/amAZAd5+Vx25YNOlavkBmXUYEDqfLF9Q6Hrxz9ksSp2ZRO1WkedwMwyXcj5fTDe58i4XxU+O4CNco0KlkPHeohs2P7eXZA9VT8nuG41BlB129Np65YwVHvruNx25cxH1bpq6h4851KZS2mHinoGnE+5weRrjotzuobDcPCua8GMiO0VHaYhx0jitqMhKpUxKuVfrOkbNtXMSbIxQbAOMOVy6MJTtGx293lvL73eXYHC7WpZ9zgqSEa3zfkeOhvqtvUMi1WiHj59fncd3SeMDtOqhsM3N5biwL4oIJDpLx73vW8MztKwDYVTRytbTF5qCuszfgXQvpkVqWJYfy652ltPa4/63bTP30WOxivoWIiIjIOBGFC5GLni+uT+WjBzYTFaxiUUIIJ2q7fXVv5+/yhGuV/POuVcTqZ+biMjNKy4OXZfOXzy8bUpskCAJf3ZZJdUcvr+c34HK5uP/FfJ78uBJwt6Y0dPf5WhIGYrE5ONto4LLcWHbkRHOsuouyFiNJYWpy4/Xse3Are7+1ZVDo6VxiaXIIQXIpn5SNXLV4PidquwjTKKakbWIqiQ8NQi4VqJzAjun5nK4zIAiwcAoaRcD9Xk6L1Pp2dc9vOZhKjtd0oZJLWJ8RgVoh44ZlCYNyJfzNVXlxZEXr+M2u0mEFR6fTxek6t1BU0Xru36y81YTD6SI7dva4CvxBdmywx1Fx7jxW3HzOeZIRpUUhlcy6gM4mr3Axw44LAIlE4Bs75lHZbuYPe8q5ZnEc6zMHCBcRaqraxx/wW9/V6xsTGUicPogguZSChm6aeyykR2p48Uur+e83N5MdE0ximJrsGB07C0cWLmo6enG6ArtRBNyv6S9uyMNic/DwawXYHU4OVnQAYjCniIiIyHgRhQuRix65VEKUzn2xuCQphKKmHo5WdQ6pQg0EBEHgns3pI7oeLsmJZlGCnl9+UMKLR+t442Qj/zpSi6HX5rvQHy7L4XS9AZvDxfLkUFalhtFnc7CvrJ00zy5WfEhQQM8PXyhKmZSVqWHsm8AC+URtF0uTQqZ1/twfSCUCyeEaqtonX0d4ur6b9Eit34Jgh2PH/Cg2zYvkyrxYjtd24ZymhpFjNV3kJYQMahOaSiQSga/vyKSyzczekqHCWVWHGWO/nZRwNc09Fl8NZYGn1eVidFzAufEQu8NJWavJlzskl0qYF6Od1tpof+B1XMQEz7xwAbAjJ5rFiSFEaJX84KrBGRMpERraTf0YLbYxH6fdM1Y2nHAhkQikRWrYVdQKQFqkFp1K7hsp8R7HsZouX/vI+XhbOdIjp05c9BfpkVoeujyb3cWtfO7pwzz0agHzY4NZkRI204cmIiIiMisQhQsRkQGsSAnD7nTx0rE6UsLV07Z48RcSicAPP72AVmM/D79WgESAynbzIKvtsZqhwsVxz98tTQ5lZar7IsrqcPrmci8GNmRGUNlmZutje/n5e8VDbrfanbx8rA67w13hV9lmZknS7BoT8ZI6QjXfeHC5XJyqN5A3RW4LL1/Zmsnf71zJxsxIunttvvC+qcRic3C2wcCyKcq0GIkt2VGo5BL2VwwVzk7VucdErl3idjt5R3z2lLQSq1fNigWbP8mI0iKVCL5AzuoOM1a7c1DWx/LkMA5XdlLnh9rf6cLruIgOEOFCEAT+edcqPvz6RkLPaw7yjlCerBtaSzsQQ6+Nzz99BIkAVy+OH/Y+6ZFa2oz9wLlsm4Fsnx+Nw+kacVzEOz7lHYELdO5Yl8oj1+RytLqLGL2Kf9y5ck6FXYuIiIhMJbNrVSYiMsVsmhfJM3es4InPLuWvty2f6cOZFEuSQrnRM9LxvStzAHhyn3tcZGlSCMeqh+Y4HK/pIi1CQ5hGQbhWSVa0exGQehEJF1cvjuf6pQlIJQLPHaweYtv/z6lGHnjlNDsLWzjieQ29Is9sIy1CQ3VHL45JuBiaDBbaTf0sSpiafIvzWZ7iFhGOTrD1ZTKcrjdgd7pYNs2ClFImZXlymM86PpBTdd2oFVIuzXWHI1a0mei3O/ikrJ0t2VGzzvFzoajkUtIiNBQ1uYUL738HOk/+36Y0BAF+vS9ftngAACAASURBVLOUN/IbuPf54/SMwx0wkzQZ+ojQKlHIAueyTKuUDVt3vC49goTQIL76r3xKWwYHpR6u7PCJSr/8sJjyViN/+fzyEcfKvGMSgjA0UwpgYbyetEgN33/zLO8VNA1xXlW0mYgPCRq2kjpQ+dzqZN796gZeu2ftBTU7iYiIiFxsBM43pIhIACCRCGzJiuLyhbEBH/Y1Gj+9diHv37+B29akoFPKKG42khqhYdv8aMpaTbT2WNhT3MoTeyt4+Vide+xhwC7zqjT3gjxtFr8GEyVSp+RXNy3iK1szMFsdQ2bk95S47cz7yts5XNmJUiaZctfBVJEaocFqd9LY3Tfhn/U6AKbruadGaAjXKCZcVzsZjtW4Baml0+y4AFiTHk5xs5EOUz/PH67hrr8fZe3PdvP3gzXkJeh9dY8VbSaOVHVitjrYlh017ccZCGTHBlPY6B6VKWzqQSYRSI86t+iN1Qdxx7pUXs9v4P6XTvJuQTMPvXp6xGDiQKCo2Tis4yAQ0avlPH/XKuRSCV/42xE6TG7HRKfZyh3PHuWH/zkLwNGqLtZlRLBp3shh1ukDxhGHcx5IJAIv3r2aeTE67nn+BAt/+MEgR1xFmyng8y2GIytGN8TJIiIiIiIyOqJwISIyB1HIJGTHBCOVCD5XQF6C3meB3/brj7jj2aM8+n4xD7xymk6zdZA9/qpFcWRGaS+64D8456I4UnXOmWJ3ONlX6s4f+Li0jcNVHSxNCh0SkDpb8DppJjMusqekFZ1SxoK46REuBEFgWXIoR6s7pzzn4nh1F2mRmmF3maeaNenuqtxH3iniu6+fobzVxPKUMB6+PJtHr89DKZOSFKamos3E7qJWlDIJawc0PVxM5MYF02iw0Gm2cqbBwLxo3ZDP4j2b08mJDeZLG9P49qVZvFvQzL+O1M3QEY+OxeagsNHAkqTpcTH5g+RwDX+7fQUdZitfe/EkDqeLpz+ppNfq4GRdNz0WG2WtRl/150h4HRejieRRwSpe+tJqfnlDHjlxwfzjYDX9dgdOp4uKVvNFNy4lIiIicrEydclqIiIiAcGa9HB2F7eyMF7P4sQQwjQKooNVfHPHPFakhlHRZuJAeTufHtAlvyIljJ3f2DSDRz1zxOqDSAgN4mh1J3dtcFfB5td102OxszY9nAMVHdR39XH/9swZPtLJkxp5TrjYOMpu6PnYHU52FrawbX7UtFraN2dF8WFhC1f+/hMeu3GRr/LSn1hsDg5UdHDDDDXnLIzXo1FIeT2/gewYHW/9z/ohGTvpkRoOVXbidLlYmx4+q+zx/iQ33i2anWkwcLaxh+3zhzpP9EFy3v3aBsDdzPJhYQvPH67h1lVJ03qs46GwqQebwzXrqpVz4/X85OoFPPhqAbc+eYizjT2EaxR0mK28cqwepwsWjeHMSolQI5cKZI7hmlDJpdy4PJFwrYI7nz3G4cpOMqK09Nkcs9odKSIiIiIyfkTHhYjIHGfb/GiidEo2zYtEJZdy4KGtvPM/69meE40+SM7SpFC+sjVzUJL7xc7KlDCOVXf5rOV7iluRSgS+c8V8331WpYbP1OFdMJFaJVqljNfyG3hqXyXPHazmcOXQfIXzOVLVSVevjctyY6b+IAdwy4pEHr9lMU2GPn72XtGU/I4DFe302RzsyImekscfC7lU4nP7/PTa3GGDgddlRGCzu0Nzv7QxfboPMWDI9bh9dha20Gm2sjB+9MWxRCKwPTuKwqaeEdspZpL8Wvf41WxyXHi5eUUSP702l/JWE2arnV/ckAfA3w9WA4zpuFDKpDz3xVV8edP43s9r0iJQyiT8t7jVF8wpChciIiIiFwfiSkVEZI6TGqHhyHe3+/4sJpiPzYrUMF7Lb+BYTRedZiuvnqhnWXIoufF6ksLUNBsss3KR4UUQBG5YlsCrJ+p55J1zQsBXt2Zw//Z5SEaovn3/bDMquYRN86Y3W0EiEbh6cTyHKjt5+3QjTqdrxGOcLDsLW9AqZb58l5ngm5dkcc2SeJYlD38Md6xL5Y51qdN8VIGHXi0nMSyIN042ALBgDOECYG1GBL/aWcrByg6uWBg71Yc4IfJru4jTqwKmUWSifHZVMlcvjqexu4/MKC0xwSpqOnqJ06vGFT65Om38InCQQsra9HD2lLT6HntgvomIiIiIyNxFFC5EREREzmOVZ+f7xj8fBCA5XM23L80C4K4NqdR19s56AeiHn17AD67KwdBnw2p38tiHJfzuv+X0Wh38r6eNxsurx+v5095y6rv62JIVNWMjCkuTQvjXkVoq2kxkRvsvf8XpdLGrqJVNWZEzmluSG6/3jUGIjE5unJ73zjQjEWB+zNijQ3kJ7lGc/eXtASdcnKzrnrXVyl60ShnzPJ/JZcmhvFPQNKbbYrJsyY5iz5tneezDEhYnhhCpFZs5RERERC4GROFCRERE5DzSIrU8ddty2kz9hGkUbMuOQuax7t+2JmVmD86PCIJAiNodRPno9Xmo5FKe+qSKlalhXLLg3DjIC0dqMVrsXLIghrs3zNyOv7ftI7+226/CxekGA23GfnbMn5kxEZGJkxvvFi4yo3TjEtLkUgmr0twZNYFEq9FCfVcfX5hD5xWfcJE4NSLctvnR/N+7RWzJiuKxGxdddJXAIiIiIhcrYsaFiIiIyDBsz4nmMyuTuHRBjE+0mMsIgsB3PzWfvAQ93/r3KYwWGwC9Vjun6rq5flkCv//MkinbRR0PqeEa9EFyTtT6txp1V2ELUonA5qzxB5WKzCxeZ8qC+PEHta5ND6eq3cyj7xfzwdnmqTq0QZxpMLDhF/+ltqN32Ns/KnG3FS1Pmd2Oi4FsnBeBQiZhfcbUtN7EhwRx9Lvb+dNnl4rZTCIiIiIXEXP/alxEREREZFwoZVK+e8V8eix2PilrB+B4TRd2p2tCc+hThUQisCQpxP/CRVELK1JCfe4TkcAnL16PSi5hZcr4M0m2z49Go5DyxN4K7nv+BI3dfVN4hG6e2V9NXWcfrxwfvor1hSO1ZERpWZw4ezNzzicjSkfhjy6dUpFTp5KLTgsRERGRiwxRuBARERER8bEsORR9kJzdxa0AHKrsQCoRWJ4cGDvCSxJDKWs1caCinTMNBpoMfRyp6uTj0rZJPV5dZy/FzUa2i2Mis4pQjYKPH9jCTcsTx/0zKREazv74Mj55cAsAT+6rpLajl+cO1eB0uvx+jD0WG+8UNALw5qlGX0uRl6KmHvJru/nMyqQ5twi/GFxqIiIiIiLTi+ixExERERHxIZNK2Dgvkr0lrTidLg5XdrqDDQPEkr0yNQyXC2598vCQ2z78+kZfQOB42VXUAjBjNagikydKN7kWjoRQNZ9eHMeLR+p461Qj7SYrSWFqNs3z76jQW6casdicfHZVEs8fruVUvYHFiSGY++0cr+ni+cM1KGQSrl8a79ffKyIiIiIiMhcJjCtREREREZGAYVt2FG+damR/RTun6ru5a0PaTB+Sj9VpYbzy5TX0Wh30Wh20m/rRB8n52ov5vH2qkW9ckjWuxylvNXKkqotXjteTGaUlOVysVLyYuGdTOq/nNxCmUaAPkvPK8Xq/Chcul4sXj9SRFa3jgcuy+ffxen71YQmpERreyG+gx2IH4OblieKIkoiIiIiIyDgQhQsRERERkUFsmheJRIDbnzmKw+liW3bUTB+SD0EQWD5MrsG/jtTy1ukmvr5j3qi2e1O/nQdfPc27BU14nftf3z5vqg5XJEDJjNbxypfXkByu4Xe7y3jxaB2GXht6tXzcj2FzOGkz9iOTCkPcHwcrOyhoMPCTa3LRB8m5IjeGN042criykx050dy8IpGkMDWJYWp/PzUREREREZE5iShciIiIiIgMIlSj4Mq8OJoNFh64LGtYoSDQuGpRHA+/VsDZxh5f48T5uFwuHnr1NO8VNHHv5nRuWZGEUi4hUquc5qMVCQSWJbvf1zcuS+QfB2v400flbM2Kos/mIEyjGDVcss3Yz3VP7Keusw+JAH+4dSlXLIz13f7HPeVE6pTcuCwBgF/dtJgfXZ1LsEo25/IsREREREREpgNRuBD5/+zdZ3gc1fn38e/Z1a62qEuWG6aXUIKdUAwBJaYXiZLQHcAQSP4PIQQChJBCAiQhhBgIPTEQeu8g0YtBkGBIQjOB0EK1LUtW36Jd7Z7nxcyOV7JlyUZYi/37XJcuzU45c8+ZM2dGt2ZnRESWcekRXxvrEFbK3ltO4Kz753PjPz7k/O9sjc838I9Day1XPfs+ja8v5Kd7bcaJu2w8NoFKwdlqchlbTS7jr89+wF+f/cAbv+OG1Zyy+yZMH/RGnUzWcvLtr7C4u49z9t+S+175jNPveo2KSIDqaDEvf9jOC+8t4Rf7foVQwA+A32coD4/8bg4REREZyAx+yvUaaI3fwC/CjBkzAJg7d+6YxiEiMlJn3T+fm178iB02rGKHDaupjgbZoKaEtt4+7v7Xpzz/Xht7bzmBK7/79WUSG7J260qkeb+1l3hfhnDQxysfd/KXZz+grbeP7davZKeNa5i6TgW1ZcVc/MS7PPlWCxccvDWHbjuFlu4kDZc9T2tPn1felKowj578zYJ5qK2IiEgBG9FFmRIXslxKXIjIl421lttf/oQ/Pvo2nfH0gGmlxUWcsc9X+O726yppISOSSGW49aWPuePlj3l3ca/3TJRwwM8pu2/C/31rI2/eBZ0JXv6wHZ8xbFATZZPxJRQX+ccochERkS8VJS5ca/wGfhFmzJjBe++9x8Yb63ZqEfnysRgygSjpcCX+dIJAsh1js2MdlnxJZX0BUtHxpMPVhDvepyjdO9YhiYiIrBHmzp07osSF7mEUEZE1jsFSlO7VH5gyKnzZNKGeTwn1fDrWoYiIiKyVlLiQIW288cb6qoiIiIiIiIiMKd9YByAiIiIiIiIiMhQlLkRERERERESkYClxISIiIiIiIiIFS4kLERERERERESlYejinrNinUyHbivN6XcvS1+wub3hVpo9OmS37bk223Q/GnW4ttY/Mx1+ZWi0xH/DW1rT3+zEYLBbjTl/ecO73A5u/QWXR8uJb+ZiGW//yxg1c/6pv04Obzx9iO5zhA96a6pWzctu8cvVwwFtT6egvWuE2j9Z+yN+mz1vPn2eb84db9p26zDGwzLC1fP8iQ3fpsvsudwwNNf2LiHmk0w94ayrXb/LWiOpxefvG2Y70ao15JO1lYHxjX89jtW/zj9vRPl6G6xdWpW2sbMyD+9Jl1zn8fhjtehquf//8+2H1H6MDrgPcPq/24TeGuA4Y3euN/HXmxjnXIMtu00iXH9n1zFj0C593eiHGpJgLY3ohxqSYV8v0dT9jJJS4kBXLtroDdtDvoYZXZfrnLzPb7ncHl053TvKrJ+b2fr87ZAf8HmrYYt2LwtGJaSTrHzxu2fWv2jateDsYUM7Kb/PI68FZz8BYv6j9MLhuVrTO4ep5pOscbvryjoHlDXeVLn/f5ZYfavoXEfNIp7f3+0dcj8vbN0uXXX0xj7S9DIxvbOt5rPZt/nE72sfLcP3CqrSNlY158P5f/jpXvP7Rrqfh+vfR2Q+r9xhdpg+0dpjrgFVrzyvsa5d7DbJqy4/8eqYQ+43hphdiTMNNL8SYhpteiDENN70QYxpueiHGNNz0QoxpePqqiIiIiIiIiIgULCUuRERERERERKRgKXEhIiIiIiIiIgVLiQsRERERERERKVhKXIiIiIiIiIhIwVLiQkREREREREQKlhIXIiIiIiIiIlKwlLgQERERERERkYKlxIWIiIiIiIiIFCwlLkRERERERESkYK11iYtXlrzOd56a5X0+6tkf8sqS11e6nNfa5zNz7v+NZmgiIiIiIiIiMkjRaBVU19SwM3ABsCWQAd4CTmmub3y5rqkhCPwBOAyoANqA+5vrG08ZoiwLxAELdAF3AD9trm/MjFa8OTd968oRzVfX1MBtM+awTnQSAFOrtuLWGX8d7XBEREREREREJM+o3HFR19RQBjQClwFVwGTgHKDPneXnwLbA9kApMAP49zDFTm2ubywBdgNmAt9fznpHLfEiIiIiIiIiIoVntP7w3xSgub7xNvdzAng8b/p2wH3N9Y0L3M8fuj/Daq5vfLuuqaEZ2AqgrqnhQ+Aq4LvAZnVNDVGgFidp8k2gF7i4ub7xUoC+TB+z51/J84tepDpUxb7r7D6g/EOe/h4/2/rHbFszjYzNcMv799D0yeN09HUxJTqJ87b9Fb99dTYAxzafhMHws61/TFVxBb999ULu3e0GZ4N6PuHC+VfwXvf/qAlV839fmcXO46cD8PvXLibsD7Ew3sJr7W+yfukUfjPtp0yOThxJFYiIiIiIiIistUbrGRfvAJm6poYb6poa9qlraqgcNP1F4NS6poYf1jU1fLWuqcGMtOC6poYtgDrglbzRRwD1OF87yQIPAa/h3OmxG3BKXVPDXgDXvXsbC2ILuWOXa7hw+3N59NOnhlzXHR/cz1MLnuVP253NY3vdyc+nnkzIX8zlO/4RgOvqLuPxve9mt0nfHLBcf7afM/95LtuN+zoP7nEzp2z5f5z7ymw+7v3Um+epBc9x7KZH8PCet7NOZCJz/nvjSKtAREREREREZK01KomL5vrGbmBnnGdSXA201jU1PFjX1DDeneUPwB9x7pL4J/BZXVPDrOUWttS/65oaOnCSEtcA1+VNu7S5vvGT5vrGBM7dHOOa6xvPba5vTDXXN37gxnA4wNMLmjl648MoC5YyPjyOgzfYf8gVNn7yOMdvehTrlqyDMYaNyzakPFg27Pa/2fk2iUyCIzc6mIAvwDY1U/nG+O14csGz3jx1E3Zki4rNKPL52WPyDN7r/t+w5YqIiIiIiIis7UbtGRHN9Y1vAccA1DU1fAW4GfgzcIT7UM0rgCvqmhrCwPeAv9U1NbzkLrc8X2+ub3xviGmf5A2vB0yqa2rozBvnB5oBlvS1Uxuu8SaMD48bchsWJ9qYHJ0w5PShtCXbqQ2Nw2eW5oEmhGtpTS7xPlcXL70JJeQvJpFJrPR6RERERERERNY2X8jDLd3nUlwPLPO+UPcuiSvqmhrOAbbAefvIyrJ5w58A/2uub9xkeTNWF1exONHGBqXrAdCSaB2y0NpwDZ/FFrFh6forFUxNqIrFyVayNuslL1oSrUxx30AiIiIiIiIiIqtmVBIX7h0W9cAdzfWNn9Y1NUzBeQ7Fi+70U4BXgXlAGucrI6UMfG7FqnoJ6KlravgZcCmQAjYHws31jS/vMnFnbnr/Lrao3IxEf5J7PmwcsqCGKXtyzTs3s37pFNaJTOL9ng8ZF6qmPFhGVXEFC+KLvNeh5tuiYjOKfcXc+v49HL7ht3mj4z+80PISV+980ShsnoiIiIiIiMjaa7QeztkDTAfm1TU1xHASFvOB09zpceBCYBHQBpwIHOQ+j+Jzcb+G0gBMA/7nln8NUA5w7KZHMCE8jkOfPo5TXzqLvSbvMmRZh214ILtO3JnT5v2avR47lD++fil9mRQAx24yk9+/djH7PHYYTy9oHrBcwBfgj9v9mhdb/0XDEzO5cP5V/GraT1ivZMrn3TwRERERERGRtdqo3HHRXN/4GXDoCqbPAeasRHlDvnWkub5x/eWMW4Bzh8cyQv4Qv5p22oBxMzc6yBu+a9e/ecN+42fWJocza5PDlynnwPX25cD19h0wLvcqVIANStfj8h3PX27Mv5z6kwGfv1a99YBlRURERERERGT5RuuOCxERERERERGRUafEhYiIiIiIiIgULCUuRERERERERKRgKXEhIiIiIiIiIgVLiQsRERERERERKVhKXIiIiIiIiIhIwVLiQkREREREREQKlhIXIiIiIiIiIlKwlLgQERERERERkYKlxIWIiIiIiIiIFCwlLkRERERERESkYClxISIiIiIiIiIFS4kLERERERERESlYSlyIiIiIiIiISMFS4kJERERERERECpYSFyIiIiIiIiJSsJS4EBEREREREZGCpcSFrJhvnDtg8n4PNbwq00enTF9Vxh00zg+Q6QiutpirijLukPF+DzWc+93RP1R8Kx/TcOtf3riB61/1bRp6O5zh/HJWbptXrh6qijLDbvNo7Yf8bfq89Txax8PyjoFlhoHynuXvu9zyQ03/oo/hFU2vKsqMuB6Xt2+cZVdvzCNpL4VWz2O1b7/I42W4fmFV2sbKxjy4L112ncPvh9Gup+H698+/H4Ze5os6Rgf0ge7voa8DVi7mIdczqH9d9hpk1Zcf2fXMyGIurOmFGJNiLozphRiTYl59MQ3PWGtHPPOX1Bq/gV+EGTNmADB37twxjUNERERERETWWCPKXuiOCxEREREREREpWEpciIiIiIiIiEjBUuJCRERERERERAqWEhciIiIiIiIiUrCKxjoAKWwTZs+mJRbjQ99jjCPJLbeeyf6RHQgRoPSRT/GlZkG2k9m3txJL9HPyjvdy1+nFJLosXQuOomzi5RhTTnjGWRDooWXyR/xopzuIBir4xzazSAc6uPQXj3P8z48gUrqEztBt7PVClOI0XH9ygkSXZb/MDZy+28/oCpTw/OT7+Xjm1dSG4zw4+Rr6/GXs914nl+94NLG2DjZreZATtn6JzpY+Wl6YTm11gNk7H8N35rxNuKKW2gmPcd0R/cQ74Pg7M0Qq3A0NnQGmm5Z9p5L9/W1QVkHthMfw+/poOehmsh0JsJbaf52KvybKg0VpPt62m2yb5fg7M/QcdzPZ9jhVV52AryzCIzsFeGPdA+hvaeeoCXty5gvX0FVdxvXXfIfyeAdHf/pXZv32ECKlS6jz382dZ/6SRHcXGAPWUn7RJezw+u4E0kGqeJ7LDj6AWHs70z8qITAOOkO3sd0LexJIBymdtwe+dDtgOfb4e+mMVHL9Nd9hwu7HY0JR0otKIGtY8sO/UHn+0fjKIlzy4ouc8J1riYbjzN62lVhrP6d/+gi37W+Jt2U5fl4V915wEonuLo488RzCkRIOuXJjLpxXTnnax3Fb9/CVO3ciEG+DM3wQyXLUTXtSe1g7vlCG8P4/xVScA6ab+B3jIWkI7/9TDv3bVDpifq44aCM2/so2+P2tNFfHSfkyXPqLx7n+LD+VpZZrdmgn3pZlv0t35/QnPqErmeHk8/Zi/g2fkopnOGrHFsKBWgAeOvkJkl0pumYexUs/folUZBzbz5lDUTzO9BOvou7tvxBMl1O0fZj+V5KQXvq83ktefJF1fjwdfzTI9Oe359EfPkuyK+W1jdk7H0Pse10QyTJvwQvc8ociKksttBwL2U7SH17FJS/8h1gqxekHfpVoqIjZOx/D8XOuJVpRQfycjSm9bF985UsGttd7jiaW7GD6iSXsWnY3QVPBzT87kUR3F/vPf4DsZ7+DTDc3zfoac9sPJpUJsfdz/yPYl+H4eVX0vLct2XSA/26zERu9/iJF6XE8cc+O9CXbeMDcwpOTnqHPl2SHaa+y27GPEuhIcvoLNxKtLvfag7P9BxNLtfPPH7xL8gKL7cly14nvsfnjr9GSTLPDtFcpKkrz/d1/zCfrHUF/SzvNt+xJqjyIxVL8yDmQLOHk8/YiUuq0wc7Qbcx58ibiqRj7n3kMxd1h9rt0d+763nok2ls46t4WfvpUN13JDDtM3pmAr40JCzak8k+XYcrK2O/TH3D3n9IkYnhtr/uEadjuAFgovX5PfOVLmL1tK8d8bwsiUT9gKJp+NiZQ4vUr2165EYG4H7AUTT+HF3c4kXSgg9nP70RvqoirwzezyfQP8AfTtMz7Osd1H0uX7eSe8AlUmgj/2GYWL/x1gdPebtqTJ/u/T9I62xIqK+aJe3bk4+v+RSae5vR/T2CjJ46hJRHijNmzifT2gs/HiT/dikjUT/ikCzDRUvioFTJZANKLSnhkxyB9QXhn9gH0x9oBH6cfeD3RUDkti/aipnYufl+f1z9dc8BFPHjvbvRVBblj8d+JLij2jm3bFaP2vqNo2mYifUU+9vv0B3R98BzZTA1TX5xNa8rpx9fd/yRMKMrhtTtyzvxqyvqX/v9i3k7ziGYOwUcHV6ReJUYNe+wyj8Qbh5Pt7wCfj6NqdydsAtzU+hSJ/iT4fJx8991EKyooWv+H3PLnfhIxKL/oEkxZGTedWs2f7j+XsmQPN816ivL2SfgyPu7adxMSxT5uvuBCPrxtb/or29h0+k6UFl2CMWXMfeJDUlUZuk89hdKzz/XK+mbjRwT7Mpy14B9096c444wriUQSQJaK22/BJMrBwn6ZGwhl40yd9TXmH/41akNFTjvqCix9BJiFOzpe58j7TiZS2U3Lh6+TzdQM6FPDh7Vy7WF/It5eyjGXhgmXGYq2D2MWtnn7Mv7gbEj2csutZ5KIR+maeRQXhL5PLxE+3XFHJk3pw/gsE3Z+iZa2FNe07MUD508i3u3jtoMWEfzjhtBTxJy9pxIPtjJhwYY8/OsnSZZUcWndDylr6yI84UKufrOOeKrVOZa/vjH4fcy+pJ5YbAkTFmyIL+sHa2m57SPmvfYfUuPGcfVBcco74MGtD6TzhVOxfSUDzn2HXLkxHTE/d534Htc+fhSxZAcn73gvz80Y57bNZvpjKaafeBWx6mvImgoqEjP5lv9qgqaC+GU/g1g3h289keNnzCMa7OO/O8+hv62M/TI30LzbfPoCaZLP/Y7O/51Atr+DE3+2NZGon/SjtzBnxkPEgwlgNkfd9A3C8YB3Hl3CTpx4z8d0JTMcaI6ic9KrZHxpfvD460SSNZRevycXPdJALBGi4vZpHPmdCwmHer3jbfaUeo6/6mqnbW4f5nnfoaTooO7Tqwhmy+g+YRoPrHcISX87Lbd9RCae5p/vvsteVxxJcc8Sks/9juPu+g2Rym5uvjBKIgYPmFuYdms9gXgbJ997L8lf3I7tivHfl14kU93Hpb94nMfKnqPPl+TTHXekNhAA8Pqll9ZPcJhvN8ImLZ4GpwAAIABJREFUAMZQ+/Ab+CtTpD+8CjJlFE3o5dC/bOScJ58+m/UvPtI7Z8dSKSpun0b3gceSDXU4+zzjo/Gcx7ngg/W8Y7l2+3/jD6a981T3sU9gu6rAQvjsd3nxW0d6saQWZzhqwp6EfUHnGueR+cRObcJ2VhFffBpkuvnRHudwXvNsypI9VF11Apf953ViqRSbnV6HPxpkv/c6ufuyX5OI9dBy20fMvPlTwhW13jmp/KJL2D9cTQhIz0tA2nL7PadT9/B4ipM+qq46gcf2KacvyADdp55CtruLPZ7ehDOe/Ctd1WUcWfoWIV8/Ldt088s9X6U7lMYH/Pb2aZTEizis5quECBA/u5Z5e/2TdDDNO7ObKbl2C0y8iPH/KsNXY9gvHcDvxnL9yQm+e3U/kQp4cKMK+op8zNhzff5++yekqjLcdGo18W4fR1+0hE/m7Ed/rJ3TT36E23az3nVKqKx4QN1fs0M7C/d8hWwozQ8eP4pIMsyc+VM56Pb5hCtquenFCaz746vxRyu97c1fZ/epp7Dwr6+TiaepmHILxpTTNfM1NvnVDvijgyrK9c7sA6h5twJfxseRF1xJuLQMgAeL0vQZmP789tzefCmJVMzbd+/MPoCNTrjei2P689sTSAeZt9M80sE0P5jdzHNb/5iaQJSHTn6ClvqXyYbS3vLTn9+eydXP4Pf1cfOVZ/Ojir3p8hXz+k2vUhNPw1U3U1U2Hx/pAfV885Vnk4j1kHzud9T+fRK+GuPt7+Rzv2PmIVcQDvVSNP0c2gN7YQl613rj/1VG73k/IdvdRcvkjyi983pMvNzbt92nnsLC0j3J+IqpuH0ah0e+RogAm+59E4uDCa45vY6yvDrMrbdl8kdkfGlOP/BGbptVRbwDr8zB9ZxfZ7l9V37SB5iSDLffczr14ywhHzxx6nmkoiUDlt/vvU6y910AyV7u+TRGMpNlj6c3Ycpts/BXhGme/EOmB68laCpo7j+EFB3ONf+0mwi0xig9toXeO2qxccMTe3xAXyDNkSeeQ/q0nbFdAebMn0rZIaX4QkvbwTU7tFP6WMmAei6/6BJ6zv61d4z96Dw/XaWW7+/+Y8LFEQBatnH+ztnv0t154qznSHalvPb+0MlPcNB+vyUc6uWKP73JQdEZhE2AqbO+RmuoiDOYzaTb/4qJl3PMpWFKN41hfEuvv2++8mwS8V6wlp9OPoTOc85bbrseTHdcyAq1xGIAjCMJQCIeJYRzIvZVZiHbCUAs0Q9ANFBBostpmNn+DowpdwoK9ACQ8aWJBpwrpnSgw1m2p4pI6RJnGVNBcdpZJFdOKBunK+Ac+H2+JLXhuDPsdzrlUCZLrM0py19bSWdLHwC11U6csbYOwhXOH7l+Xx9xZ9alSQsA0+2sv90PZRXevM64OLhv3/HXRJ11G8i2Wa+cbLsTk6/MOdj7gtDf0g5A2AToqnZiLXdX3pkp87Y5aCqcpAV46zFlZQTSTsfqI02s3Skr4L6dNmsqlk5PLyH38pzOSKW3HhOK5mZ2iu6KefHFUimibj3GWt19V1tJvM25EI9U+7yYwhGn7jtifsrTTpfR6bdO0gIg4iwTjgfwhdzX3IWiXp2SNN64jpgfgLJQEX5/KwApn7NMrKfKSQqAF0eorJiupDM9UrqEVNwZziUtAJJdKWczQx2kIk4FFcWdbQtEYwTTThs0QTMgaZGrh9xFQCAd9MrKtY1YW4e3falMtRdfrt2TKSOWcpaJhoq8ZaIVbgE9RfjKnf08oL0mO9z4nP0PePUdSldCxqm7RKiIVCYEQLDPrYdqH9m007YzgcUUpZ1t7ks6+yNpy+nzOcdrUVGaQIczHK12j8Xs0pNwLOW0q1RkHLbH2c7KSIaWZNpbHiBcHPHac195AJt7WVPSaRtOW3aPe1NBPOX0G8XdYWebyopJtLc4ZVXUevs04HNi9mV8mDK3frKdJJzFvbZnuwLe+6Fy9Rlr7XeTFgAW4/YRuX4lEPd5MZlAiTe+N+Xsp3JT4VzcA9l0gC7r7NNKE/HK8dpbPEDSLt2WXH1n4mm3bg0tCWc/RXp73XrOevGZaKkzzv1D160o70LdSVoAZImGyt3Fi70+KHcsxdtL6atyFqrIpgcc2wD+ijB9RT6vHrOZGgBaU0v78Vy/0OELDkhaAKSDaXy4/TLOssElaSdp4W5T2DhtL9Gf9Mbl2rvxd3n7Lrc/490+ypJO/58IJfFlnHUmip3fFb1l9Fc67aCorQhjnOVS7isjs91dA8rKHQfd/e6xGokBTr2aeLnXTkJZpw9oDRVR6x6btsuJHYs3XzLTT6TS7f/d+srvU00oQ7zd2X/hMrcvC5qB+zLp7PNE3KnbbKiDXpx2VBsIeBdrLW1OzGW1xcS73e0PZaHHiS8edPpEX8ZHsqTKmbfN6ReMKSOecqZHq8vB7ywfiy3xlsmdPzLxNKlxTr9Q7u66pL8d2+cer3nnvlyfXBnJeP1SNFCR1zadmAPRGFm3r/LR4fVbxJy66ygyRINOe+1vyx3LcfoCzjFi+0q8duQdt8kKN2kB0Es47l5buOcpS9DrK4ptBxmfU1Yk6e6n8iXE3OPOxIsIh5z9kDveYi1LlrbNoCHltu1g1onPdgVI+tu9OgNIjRtHcc8SL+Zc28i166Qt98590YoK79jLVDvbHuup8vrfXNIClvZLqcUZ7xjCWvyVTv2ScWIyPrv0PJnsGXDOzm1nNuSUlTuWkiVVA47lXL+WO0/ZziqvvZuSzIBYwLlG8a5xKlPO/OCdh7oCJd4x7CuLeLHkzp2hTJZErMerx9z1Vu6cZMrKCHkV4awnmeymOOnzyhyctADn2AcoTvq8a6iQz7leybZZukNu/w2UxJ1jKHd9SomftFsP/bEUxp2e+yM0lBdLost6x0Su/wwu8Xt9UO5YDZdlvb46Gq0ccJ2Sk6v7eFuWbCjXXp1zRzzV6tVNItUy4A/fwevMdnd5bTJ3HZ0NpYdMWjjb2e61iVzSApzrVXCucRLuuSBXTn+sfUAcuevKXN11xlLUBJx+LdmV8rYp/7opd55KxHro8jl1UePGTlkFPpzh/HrOtRfbV+Ltk9z+tn0lS4/lQAmWoLd+cPZhbt6ML+30+zCgnIwbh4kXeW1isdvXlA2qw/yyAKKhcu/vhMFJi+XVGTj7zpQ4+y6Z7CbkHo6DkxbgHC+5c0bSPY8UJ334K5x2kvJ3ef1rrs/KmgoCrc6+84Uy2LgTV65/DUdKvPNbPNWKLzSwHcTbssvUsykrG3iMude3uaQFLP07J1RW7NV/rr0nu1Lefor3pLx+rdU930bo9fZNuMwMSFqA2wbcfifXbkZCiQsRERERERERKVhKXIiIiIiIiIhIwVLiQkREREREREQKlhIXIiIiIiIiIlKwlLgQERERERERkYKlxIWIiIiIiIiIFCwlLkRERERERESkYClxISIiIiIiIiIFS4kLERERERERESlYSlyIiIiIiIiISMFS4kJEREREREREClbRaBZW19QwF5gKTGiub+xbzvSzgd8AOzTXN85bQTkVwEXAvkAUWAj8rbm+8fzRjFdERERERERECtuo3XFR19SwPlAHWGD/5Uw3wNFAu/t7RS4GSoDNgXK3vPdGK1YRERERERER+XIYzTsujgZeBOYBs4C7Bk2vAyYCxwOX1jU1/KS5vjE1RFnbAb9qrm/scD+/7f44BTU1fAW4DNgGaAXOaq5vvNOdVg1cB8wA3p618WH8e8kbXPmNC1gYb+HQZ47jmX0eoMjnB+Ckf5zJnpN3Yb919wKg6ZPHue39e1nS18HmFZtyxldPYkKkNrdeTtvqh9zxwX10prrZY/IMfrLl/8MYA8CDHz/KnR/cz+LkEmrDNZw17TQ2K9+YtuQS/vzmX3m1fT4Rf5hDNziAgzdYJrcjIiIiIiIiIoOM5jMujgZucX/2qmtqGD9o+izgIeBO9/N+KyjrReD3dU0Nx9Y1NWySP6GuqSEKPAHcCtQChwNX1jU1bOHOcgWQxEmSfK/pkydGvAHNi17kpvfu4nfb/JKH9riVqVVbcs4rFwyY5++LX2bOzhdz/Tcv4+mFzbzU+m8Anln4PNe9cyu/nHYqj+11J+dvexblgTKyNsvPXj6Xjco24L7dbuDPO/yeO//3APNa/zXiuERERERERETWVqOSuKhratgZWA+4s7m+8V/A+8DMvOkR4BDg1ub6xjRwNyv+ushJOAmQHwH/qWtqeK+uqWEfd1oD8GFzfeN1zfWN/c31ja8A9wCH1DU1+IGDgF831zfGmusb5++9zm4j3o4HPn6EIzc6hPVLp1Dk83PUxofybvf/WBRf7M1z5EYHUxooYXy4lq9Xb8273R8A8NDHjzFzo4PYvGJTjDGsE53EhEgtb3W+S2eqm2M3OYKAL8CkyAT2W3cvnlrQPOK4RERERERERNZWo/VVkVnA4831jW3u51vdcRe7n78N9AMPu59vAZ6sa2oY11zf2Dq4sOb6xgRwHnBeXVNDGXAmcFddU8O6OAmS6XVNDZ2DtuMmYJw7/EluwoRwLa/x5og2YlFiMZf+Zw5XvHWtN85iaU0u8b4uUlVc6U0r9heTyCQBWJxsY1Jk4jJltiQWs6RvCfs8dpg3LmOzTK3aYpl5RURERERERGSgz524qGtqCAOHAv66poZF7uhioKKuqWFqc33jazhJjBLg47qmBgADBHDuyrhkReU31zd21zU1nAf8HNgAJynxbHN94x7LicWPkyCZgvtMjJbE0rxIyB8CoC/TR5EvAkB739L8R22ohqM3PpQ9J++yUnWQW3ZBfOGy48M1TAyP57Zdrl7pMkVERERERETWdqNxx8WBQAb4KpD/sM07gaPrmhouAnYD9gFez5t+Cs7XRZZJXNQ1NZwFPAq8hvN1lpOBTuC/wDvA+XVNDUcBt7uLTAN6m+sb36prargXOLuuqeF7wPrjQtVMCDuP26gsLmdcqJrHP3uG/dfbm0c/fYrP8pINB663D9f892Y2KduQDUrXozcd4+W2V9hl4s7DVsJ+6+7F5f+5hq2rtmTTso34LL6QIlPE5hWbEi6KcMv7d3Pw+vtR5Cvio95P6Muk2Lxi02HLFREREREREVmbjUbiYhZwXXN948f5I+uaGi4HLgU6gFeb6xsfHzT9UuC0uqaGrZrrG+cPKtPivBlkXZw7KF4H6pvrG3vdZfcELnJ/fDgJjlPdZX/kLrsIeHvfdXbn30ve8Ao+46sncdH8q5jz3xupn7IHW1Vu7k375oRvEO9PcvYrF7AosZiSoijb1kwbUeJil4k705Xq5pxX/kRbcgkTwrX8atppTIjUcsF2v+byt67l0GeOI5VJs27JOnx/s6OGLVNERERERERkbfe5ExfN9Y17DzH+Tpa+QeR3y5m+AOfrIstb9nfLWyZv+n+B+iGmteI8wBOAhz950uYnLnao3ZY7d712eYsCsPc6u7L3OrsOtd4Bn3859ScDPh+43r4cuN6+yyxXE6rm7K+dMeQ6RURERERERGT5RvN1qCIiIiIiIiIio0qJCxEREREREREpWKP1OtSCte+U3dl3yu5jHYaIiIiIiIiIrALdcSEiIiIiIiIiBUuJCxEREREREREpWEpciIiIiIiIiEjBUuJCRERERERERAqWEhciIiIiIiIiUrCUuBARERERERGRgqXEhYiIiIiIiIgULCUuRERERERERKRgKXEhIiIiIiIiIgVLiQsRERERERERKVhKXIiIiIiIiIhIwVLiQkREREREREQKlhIXIiIiIiIiIlKwlLgQERERERERkYKlxIWs0PhoFIBWQgCEIzGSpAHIdvjAVwFANFwEQCzdSbjcAOArqsTaLqegdCkA/myAWLoTgEC60lm2tJ14T7WzjO2kL+Askisn6YtQnu4FoDgbYnEi4gxnup3pfh/RGqeszOIOKsYXA7B4iRNntKaSROdiZ3q2mIgzK/HOvA21Zc76qzLQ3enN64yLgHFiybTFnHVb8NUYrxxflRNTtjvuTE9B0fgqABI2TfkSJ9Yud+UV/m5vm1O2k3BZuROHux7b3U06kHLKJEC0yikr3YpXT970QDXgLFcR7/DWY5Ox3MxO0eVRL75oMEjMrcfoOHffLe4gUuN0CfElWS+mRNyp+8pohq5A1llPxpCO1LgV6SyTiKTJJv1O/MmYV6eErDeuMpoBoDvZTyYzDoBg1lkmWtpOR4+zHbk4kt19lIec6fGeaoIRZziRdvYnQKg86GxmspJg3Kmg/oizbelYlFTAaYM2ZSFgyBcNBsnEnHpMB1JeWbm2Ea2p9LYv6F/ixZdr9/i7iQadZWLJfm+ZWKdbQGk/2S5nPw9or6FKNz5n/wNefScDHeB36i6c7CfoTwKQKnbrYUkWX8Bp2/50Lf0BZ5uLQ87+CJkuirPO8drfHyBd6QzHlrjHotsenO132lUw3oopdbazI+5nfCjgLQ+Q6It77bm4K41x2xshp204bdk97m0nkaDTb/SVJZxt6u4jXDXeKatzsbdP01kn5qw/i+1268dXQdhZ3Gt7pjydK96rz+i4IuKxjLslBuv2Ebl+JR3JejHZdK83viTo7Kcu20km5WyfL5Cm3Dj7tMPGvXK89hZJEzJLtyVX3/5IwK1by/iws5/iJSVuPfu8+Gysxxnnzzvl+izFTtOjKFqVG0ks2eUu3uf1QbljKVLVQ3G7s1CnLzDg2AbIdCYo7s969ejztwEwLri0H8/1C5XZFN1FWfIFUgGyuP0yzrKp6gC+okpvmxLWaXvhopA3Ltfebabc23e5/Rkpy9Idcvr/cDJE1u+sM9zn/O4s6aaow2kH/TX9WOssF2x36t5XVj6grNxxUFbkHqvxKLlLGRvp8tpJ0uf0AeOS/Sx2j01T7sSOwZsv5C8i3uH2/2595fepNuknUuXsv0S325el7MB9GXL2eTji1K0vWUkJTjtanE5js05Z42ucmLsX9xEpc7c/6YNSJ75IyukTs/4sod52Z94ap1+wtptI0JkeW9IFGWf5aLTaWyZ3/vBHAgRbnX6hy911oUwVptg9XvPOfbk+uSPu9/qlWLozr206MadjUXxuX5Wl0uu3iDp1V9lviaWc9lpUkzuWIxSnnWPEFPd67cg7bkOdRFJhN5ISEhH32sI9TxlSXl/RZyrxZ52y4iF3P3VVE3WPOxvpJ5F09kPueIuOr17aNlOWoNu2Uz4nPlOeJpSp8uoMINjaSl9ptRdzrm3k2nXIdHnnvlhnp3fs+Zc42x4tbff638XptFfPuf4nWOv3jiGMIdPh1C9+JyabNUvPk6HSAefs3Hb6kk5ZuWMp1Ns+4FjO9Wu585SpaPfau+31D4gFnGsU7xqnI+jMD955qDzd6x3D2e64F0vu3Jn0+whHS716zF1v5c5JtrubpFcRznpCoTL6QlmvzFx7y+dzz4l9oax3DZXMOtcrvhpDWdLtv4HeiHMM5a5P6c0QcOuhKBrEutOzbdadb2ks4XLjHRO5/jNVnfH6oNyxmuj2eX11LNYx4DolJ1f3kRofvmSuvTrnjkhwnFc34eB4MrGOAdubv05fWbnXJnPX0b5kwKvz5SmKVnltItHT7Y0vdk/56UCKsHsuyJVTFK0aEEfuujJXdxXRIG1pp18LlQe9bcq/bsqdp8LRUsqzTl20ubHT3UkWZzi/nnPtxRT3evskt79Nce/SYzndiyHlrR+cfZib158NOP0+DCjH78ZhI/1em6h1+5ruQXWYXxZALNnl/Z2QKzPf4DoDZ9/ZXmffhUJlJN3DMRjrXWb5pN/nnTNC7nmkL5Ql0+m0k2Cm3Otfc32Wz3aSHufsu2zSj4k4ceX610S81zu/RYLjyCYHtoNIjW+Zerbd3QOPMff6NtEXX1o37t85ye4+r/5z7T1UHvT2U6Q06PVr49zzbZwSb98kuq13HswJR0u9fifXbkbCWLvsTlnDrPEb+EWYMWMGAHPnzh3TOERERERERGSNZYafRXdciIiIiIiIiEgBU+JCRERERERERAqWEhciIiIiIiIiUrCUuBARERERERGRgrU2PJxTPgdjzHxY+kBokTFQA+4rDkTGhtqgjDW1QRlLan8y1kLW2q3GOggZW0VjHYAUvKS1dtuxDkLWXsaYf6oNylhSG5SxpjYoY0ntT8aaMeafYx2DjD19VURERERERERECpYSFyIiIiIiIiJSsJS4kOHMGesAZK2nNihjTW1QxpraoIwltT8Za2qDoodzioiIiIiIiEjh0h0XIiIiIiIiIlKwlLgQERERERERkYKlxIUMyRiztzHmv8aY94wxZ451PLJmMsb8zRiz2BgzP29clTHmCWPMu+7vSne8McZc6rbJ140xXx+7yGVNYIyZYox5xhjzH2PMm8aYk93xaoOyWhhjQsaYl4wxr7lt8Bx3/AbGmHluW7vDGBN0xxe7n99zp68/lvHLmsEY4zfGvGKMaXQ/q/3JamOM+dAY84Yx5tXcq091HpbBlLiQ5TLG+IErgH2ALYAjjDFbjG1Usoa6Hth70LgzgaestZsAT7mfwWmPm7g/PwCuWk0xypqrHzjNWrsFsANwotvXqQ3K6tIH7GqtnQpMA/Y2xuwA/BG42Fq7MdABHOfOfxzQ4Y6/2J1P5PM6GXgr77Pan6xuu1hrp1lrt3U/6zwsAyhxIUPZHnjPWvuBtTYF3A4cMMYxyRrIWvsc0D5o9AHADe7wDcCBeeNvtI4XgQpjzMTVE6msiay1C621/3aHe3Au3CejNiiriduWet2PAffHArsCd7vjB7fBXNu8G9jNGGNWU7iyBjLGrAPUA9e4nw1qfzL2dB6WAZS4kKFMBj7J+/ypO05kdRhvrV3oDi8CxrvDapfyhXFvef4aMA+1QVmN3Nv0XwUWA08A7wOd1tp+d5b8dua1QXd6F1C9eiOWNcyfgTOArPu5GrU/Wb0s8Lgx5l/GmB+443QelgGKxjoAEZEVsdZaY4ze2yxfKGNMCXAPcIq1tjv/H4hqg/JFs9ZmgGnGmArgPuArYxySrCWMMQ3AYmvtv4wxM8Y6Hllr7Wyt/cwYUws8YYx5O3+izsMCuuNChvYZMCXv8zruOJHVoSV325/7e7E7Xu1SRp0xJoCTtLjFWnuvO1ptUFY7a20n8AywI87tz7l/MOW3M68NutPLgSWrOVRZc+wE7G+M+RDna8G7Apeg9ierkbX2M/f3Ypzk7fboPCyDKHEhQ3kZ2MR9qnQQOBx4cIxjkrXHg8Asd3gW8EDe+KPdJ0rvAHTl3UYostLc72ZfC7xlrb0ob5LaoKwWxphx7p0WGGPCwB44z1p5BjjYnW1wG8y1zYOBp621+k+krBJr7c+ttetYa9fHudZ72lr7XdT+ZDUxxkSNMaW5YWBPYD46D8sgRn2NDMUYsy/O9x79wN+stb8f45BkDWSMuQ2YAdQALcBvgPuBO4F1gY+AQ6217e4fmZfjvIUkDhxrrf3nWMQtawZjzM5AM/AGS7/f/Quc51yoDcoXzhizNc6D5/w4/1C601p7rjFmQ5z/gFcBrwBHWmv7jDEh4Cac57G0A4dbaz8Ym+hlTeJ+VeR0a22D2p+sLm5bu8/9WATcaq39vTGmGp2HJY8SFyIiIiIiIiJSsPRVEREREREREREpWEpciIiIiIiIiEjBUuJCRERERERERAqWEhciIiIiIiIiUrCUuBARERERERGRgqXEhYiIiIiIiIgULCUuRERERERERKRgKXEhIiIiIiIiIgVLiQsRERERERERKVhKXIiIiIiIiIhIwVLiQkREREREREQKlhIXIiIiIiIiIlKwlLgQERERERERkYKlxIWIiIiIiIiIFCwlLkRERERERESkYClxISIiIiIiIiIFS4kLERERERERESlYSlyIiIiIiIiISMFS4kJERERERERECpYSFyIiIiIiIiJSsJS4EBEREREREZGCpcSFiIiIiIiIiBQsJS5EREREREREpGApcSEiIiIiIiIiBUuJCxEREREREREpWEpciIiIiIiIiEjBUuJCRERERERERAqWEhciIiIiIiIiUrCUuBARERERERGRgqXEhYiIiIiIiIgULCUuRERERERERKRgKXEhIiIiIiIiIgVLiQsREZE1kDGmN+8na4xJ5H3+rjvPpsaYu4wxbcaYLmPM68aYU40xfnd6sTHmD8aYj93l3zXG/NQYY/LWM9cYkzTGTMkbt7sx5sO8zzsbY/7urqPdGPOCMWa7EWzDTGPMR8aYmDHmfmNMVd60KmPMfe60j4wxM1di2VzMufr476BlTzLG/M8Y022M+acxZuflxBY0xrxljPk0b1zdoHrvNcZYY8xB7vStjDGPufVth9t+ERERcShxISIisgay1pbkfoCPgf3yxt1ijNkImAd8AnzVWlsOHAJsC5S6xdwF7Abs6447CvgBcMmg1cWAs5YXhzGmDGgELgOqgMnAOUDfiuI3xmwJ/NVd53ggDlyZN8sVQMqd9l3gKneZkSwL8KO8+tgsb73TgfOBg4Fy4FrgvlwyJ89Pgdb8Edba5kH13gD0Ao+6s6SBO4HjVrTtIiIiMpCxVgl/ERGRNZl798Px1ton88bdDFRaa+uHWGY3oAnYxFr7Sd746cDfgc2ste8ZY+YCzwCnA9Oste8bY3YHrrHWrm+M2RZ40lpbsZIxnwesb62d6X7eCHgLqAayQAewlbX2HXf6TcBn1tozV7SstbbHjflma+01y1nvYcBp1trt3c9RnOTDJGvtQnfcBsDDwKnA1dbadYbYhusArLXHDhq/MfCutdYsbzkREREZSHdciIiIrJ12B+5ewfQ9gHn5SQsAa+084FOcOzFyPgOuxrmTYrB3gIwx5gZjzD7GmMoRxrcl8Freet/HucNiU/enP5e0cL3mLjPcsjl/cL+y8YIxZkbe+EcAvzFmunuXxfeAV4FFefNcBvwCSAwVvJvwOBi4YURbKyIiIkMyjPv8AAAgAElEQVRS4kJERGTtVA0sXMH0mhVMX+hOz/cHYL/c1zVyrLXdwM6AxUlutBpjHjTGjB8mvhKga9C4LpyvrJQA3UNMG25ZgJ8BG+J8bWUO8JB7VwZAD3AP8DzO11l+A/zAureoGmO+DfittfcNE/93gDbg2WHmExERkWEocSEiIrJ2WgJMXMH0thVMn+hO91hrW4HLgXMHz2ytfctae4z7lYqtgEnAn4eJrxcoGzSuDCexsKJpwy2LtXaetbbHWttnrb0BeAHnOR7gPH/iWJy7NoLAkUCjMWaSexfFBcCPh4kdYBZwYy7hISIiIqtOiQsREZG105PAQcNMn57/thDwnnExBXh6Ocv8CdgF2GaoQq21bwPX4yQwVuRNYGreejcEinG+evIOUGSM2SRv/qnuMsMtu9ywgNzzJqYBjdbad6y1WWvtozh3mHwD2ARYH2g2xiwC7gUmGmMWGWPWz1vfFGAGcOMw2ygiIiIjoMSFiIjI2uk3wDeMMX8yxkwA56GRxpibjTEV7oM8nwLuMcZsaYzxG2N2AG4GrrLWvju4QGttJ3AhcEZunDHmK8aY04wx67ifpwBHAC8OE98tOF89qXPvdDgXuNe9UyKGkzQ41xgTNcbsBBwA3DTcssaYCmPMXsaYkDGmyDivhv0mS9/88TJQb4zZ0Dj2wHk2xnz3ZwpOcmMacDzQ4g7nPwvkKODv7rM1PG55IZw7OXBjKB6mHkRERNZ6SlyIiIishdw/qnfEuYPgTWNMF86zHf7J0q9cHITzxpBHcb5+cTPO60FPWkHRlwCZvM89wHRgnjEmhpOwmA+cNkx8bwL/DycJsRjn+RQ/zJvlh0DYnXYbcIK7zHDLBoDf4bzKtM3dlgPzHvR5I3A7MBfnORqXAv9nrX3bWttvrV2U+wHagaz7OX+bj2b5D+VcD+eBnrk7QxLAf1dUDyIiIqLXoYqIiIiIiIhIAdMdFyIiIiIiIiJSsJS4EBERkTFhjPmLMaZ3OT9/GevYREREpHDoqyIiIiIiIiIiUrCKxjqA1UCZGREREREREZHCY4afRV8VEREREREREZECpsSFiIiIiIiIiBQsJS5EREREREREpGApcSEiIiIiIiIiBUuJCxEREREREREpWGvDW0VkJdQ1NazU/M31jSu9XG4ZEREREfli6Nrsi7Gy18qrm/alrKl0x4WIiIiIiIiIFCwlLkRERERERESkYClxISIiIiIiIiIFy1hrxzqGL9oav4GjqdC/tyciIiIiIsunZ1zIl5AZyUy640JERERERERECpbeKiKfi94qIiIiIlJ4dG32xdDdySJjQ3dciIiIiIiIiEjBUuJCRERERERERAqWEhciIiIiIiIiUrC+9G8VWTipYWvgj0AYCAJ3A7cAlwO1gW03/2bkyL2JHLobAIunH4d/nXHe8mW/+38ENl9/dYctIiIiIiIisrYb0VtFvtQP51w4qaEcuBn49sQFje8vnNRggD1xEhcXTVzQ+LBN9Nn2I39D0XoTCE7fEvw+qu85f0zjFhH5MpkwYQItLS0rvdz48eNZtGjRFxCRiIiIiKxNvuxfFakHHpq4oPF9gIkLGi0wH4hMXND4MIAJF1Ny0iHE73pqDMMUEfnyWpWkxedZTkREREQk35f6jgtgCvDJoHHrAB/nj/BPriW7aInzIZNlyUFnetMq5vwcf3X5FxuliIiIiIiIiKySL3vi4hNgq0HjPgPWzR+R+awV34Rq54O+KiIislLGjx+/yl8VERERERH5vL7sXxVpAvZbOKlho7xxmwPJhZMa9gawyRS9V9xN+OBdxyRAEZEvu0WLFmGtXekfPd9CREREREbDmvBWkak4bxUJ4bxV5C7gduAyYFxg282/GTliDyJH7Aks+1aR0jOOch7aKSIiIiIiIiKr04jeKvKlT1yMwBq/gSIiIiIiIiJfQiNKXHzZvyoiIiIiIiIiImuwgng458JJDXOATScuaJzhfrbArycuaPyt+/ks4NyJCxrNwkkNM4AjJy5oPH7hpIbrgalAL87XRO4GZruvRWXhpIZvYAzj/n41RetNIHbNAyQf+QfZrhjZtk6KNpqMiYaJ/r9vk7hnLhUX/hib7qfnDzeS+vfbAAS/thmlv5iFCRTRecrFpN/8HzWPX4Ixhp7Zt+DfYBKRg3ZZrfUlIiIiIiIisrYY8zsuFk5qCOIkH3oWTmrIvQ3kQyD/aZq7Av8booiTJi5orAO+BWwDzMqb9t3o8fuTuG8uANHjD6D6nvMpO/f7FO+2HdX3nE/Vjb8ZUFjv5XeBgZr7L6Dm/gvAZ+i94u6lM1hL36MvruLWioiIfHlMmDABY4z3M2HChLEOSURERNZCY564AOqBB4EbgJnuuAzw+sJJDV9fOKlhG+A1ILuiQiYuaEwCZwHfBVg4qSEAfK30F8fQ9/S/RhxM4r5nKT1tpve59LSZJO6d630u+dHB9F5xN2vBs0FERGQtN/g1uKvyWlwRERGRz6sQEhdHADcBDwH75I2/FSeRMdMdHolPgMnu8F7Aw6Y4QGDLDUm//t7ISuhLYyIh76OJhKAv7X32T6wh8NWN6Hv0HyMMSURERERERERW1ZgmLhZOaigHdgLmAA8A67uvN2XigsZ5wHbAthMXNL40wiKnAJ+5wzOBPdpn/pr0/PdJ3PPMyEoIBrDxpPfRxpMQDAyYpeSkQ+m94h69r0RERNZo48ePX+FnERERkdVhrB/OeTDwh4kLGi8HWDipYTfcr3q4/jbSghZOaigGzgFuWzipoRRYZ+KCxm/iphfa9v0JNpPB+P0rLCd84Dfp+fPtlP3iGAB6/nw74W9/a8A8/kk1BL66McnHXiR6wndGGqKIiMiXyqJFi8Y6BBEREZEx/6rId4FH8z4/D+yPG9fEBY03TFzQeMMwZVy2cFJDM/Ac8AZwHfx/9u47PIqq7eP4N5seUiB9l9CUpqAIiD2CYs/qY0VRbCj2guWxd8Xe8bFg7xVfy8YuogEbIL0KhJLsAkkIaaRu9v3jbLJJSIWEhOT3ua5c7M6cOXNmMrtk7jnnPpzmfV8tYJ9+lKUtbLJB4deeBeUVZP/nFrJPvQXKygm/5sx6y1WsyWiyPhERERERERHZeX5dIMlkpz9AERERERERkT2QX3MKtXePCxERERERERGRBrV3jotaXDZ7XyAduMDqdLzrXfY6cDRQABxhdTryXTZ7P+ATTGLPPOAvIAiYZXU6bvFuNxOYkJjxFfm3vUj5ivVg8cO/ZxxhE06g8Mn3ASibv4qg4QMBsMRHE5JyGKH2IwDYev59hF9zFts//IGw8ccRdPCQ3XQmOrbExMRGp8RLSEjYI8ZFt9ZxdJbz0RHp3IqIiIiISIcKXHj9g0na+a434WYvwA08AzwMXANMBSZbnY4yl82eaXU6xgC4bPYZLpt9H6vTsbyqstKZ/+CpcBP71RMAVOYWYOkRQfD0RwHYctgkYryvK3PyyDn7ToJHj6D0l3n4W2MJOngI2z/8YTcd+p6hsRvJ5qzvKFrrODrL+eiIdG5FRERERKQjDhXJBcpdNns8YAe+AbA6HW8Cg1w2+6NAhtXpmF1zI5fNHgiEU2eMjF9YCO50J+X/bsTj8WDpEdHgji0xUXS77DTy755G4QufEXHnRa16YCIiIiIiIiLSMh0xcAHwKTAOOBv4qMbyK4ErgNtqLOvpHRaSAfxtdTqW1awo+JChhI4bS/7tL5J1yKUUvfplozsOGzeWinQn3S45GUtUeCscSueTkJCwS+s7itY6js5yPjoinVsREREREemogYuvgPFAmNXpqB7AbnU6VgPZVqdjW42yVUNFRgLDXTZ7UN3KwsYfR8xnjxD701S2f/wTFesbHxMf0M9KQF9raxxHp7Rp0yY8Hk+DP3tKzoHWOo7Ocj46Ip1bERERERHpkIELq9NRDPwf8GILtskAvgcurbncvSmHyoLtAPiFh+LXLRQ6/xSwu2zy5MlMnjy5vZshIiIiIiIiXVxHTM4JgNXpeHInNnsJ+NVls0+rWuB2ZZN/72tg8QO3m5BjD96p3hT5972GX0QYAN0mnkzICYfsRPP2HAsWLGjvJoiIiIiIiIjg5+n8vQ86/QG2hTFjxgAwc+bMdm2HiIiIiIiIdFp+TRfpoENFRERERERERERgJ4eKuGz2/YHHgFAgCPgMuMrqdPT3rn8eqASeBN7HBEgswPVWp2NuA3WmA+uBYOBPq9Nxg8tmvw9YbXU63vOWuQhIsjodD7ls9gjgWaA/4A98DTxudTo8Lpv9NOBWoDRw5CCinp5M4IBeuPY6naDhA/EUlxJycjLhV57OtsnPEDb+OIIOHgJAwZPv49/PRtgZR+HOyiX/zpepzM7DU+EmbMIJhI0bW+85cW/JJW/yM3hKy/CUlRNiP4Lwy0+rrr/w+U/wlJRSsToDS3w0lsgwQlIOp3zRasqXpmOJNMNQQscfR9iZR+/Mr2WPkZiYyObNm2stS0hIUKJF6dB03baduudW51Wq6NoQERER2InAhctmjwLeA06zOh1rXDa7H3BcjfXPAR6r0zHZW/Ysq9OxxWWz7wu8AiQ3ULXb6nSM8db3nctmbyqJxLPAPKvTcYnLZvf3tuk877+PASOtTkeBp7Tc43G7AfBPjCFm+qN4yivIPv56Qk8b3egOtl39JN0uP5WQsaPwFJeydcK9BPRJrA5y1FQ07QtCTh9THXSo3Jpfa330+/ebOusESrZNfoaohy6vt87Oqu7NX0PLRDoSXbdtp+551HmVKro2REREBHZuqEgK8LXV6VgDYHU6PFan43sAl83+LOBndTqu967LszodW7zblQIVTVVudTo8wHygT0NlXDa7BTgKk4wTq9PhBu4DLvQWcQOjXTZ7iF9wIJawkFrb+wUGEDCwN25ndoPtcLuyTc+MsaPMNqHBhF97Fts//bne8n5hIZT/sxL35q0AWKIjmzpUEREREREREWnCzgQuegEbG6jrbExPiFq8PSKeB6Y0VbnLZg8CRgPLvIvudNnsM102+0zgNu+yOGCLN8hRZT3Q0/t6HHAOsDJ30sNU5hbU2kdlwXbKl6YT0CcRgLy7XiHnjNvIOeM2ij8xgQm3Kwf/nnG1tvPvGU/lppx62x1+xWlYekSydcJ9ZB19NaVpzZ+Vo+b+S3+d3+zt9lQJCQnNWibSkei6bTt1z6POq1TRtSEiIiKwczkuNgJD61leiQkYfOmy2Y+zOh2uGuteAb61Oh0/NVKvvzc44Qd8ZHU6Frts9jOAKXVzXADZQLzLZverEbzoDWQCWJ2OxcAEgIKnP/QUvfYVEf89D/emHHLOMLGPiJvGY4mJAqg1VKPgyfdNYxJjcGdm1WqgOzMLS2JMvY33Cwsh4r/nEfHf86hYncHWix4kftYrjRyuT1cbKqLxybIn0nXbdnRupSG6NkRERAR2rsdFKnCyy2bfu2qBy2Y/FsDqdKRhekWkumz2Ht51TwIuq9PxQhP1uq1Oxxir0zHa6nQ811hB79CQX4HLvPuwAPcA73rfD64q6x/fAzyV5rU3x0XM9EcJPbXx/Bb+tlj8QoIo+WUeAJ6SMgr/9xmhDSTOrEh3UpVLwxLbHfyaNauLiIiIiIiIiDSixT0urE5HnstmnwD8z2Wzh2BmFfm0xvpUl80eiQle3AJcD8z29qbIsjodZ7VO07keeM5ls5+HmVXEgTdwATzistkTgdLgY0bR/ZnJO7WD7i/cTP5dL1M09VMzq8j4Ywk+pL7OJlD2xxK2X/0EfiHBeMoriLz3kmbvJ++uV6pnFQlJOZxuE0/eqfaKiIiIiIiIdDZ+Ho+n6VJ7tk5/gG1hzJgxAMycObNd2yEiIiIiIiKdVrOGKuxMjotd4rLZj8YM66jpAavTMWN3t2VnbbvuqVr5L/x7xtH9+ZvasUUiIiIiIiIinVOLAxcum70vZrrShUA48DQm18QEq9OR4bLZbwIOxczqEQU8g0mcGQisBC63Oh1j6tbpstlza9ZpdTo+8A4vmWB1OjK85d4CXrM6HbNcNvsA4DmgGyZXx8NWp+Nbb7n7geOBsqDD9iPms0co/X0R2656goC9e+IpLiXitgsJPvIAthw2ifjfX61uS84Zt9F96s3422IpW7CKgilvgbsSLH5E3HUxQQcMrDdIUfbXUvKnvIVfoD+e0nIi7riQ4MP2Z8thk4h+517ybjUpPsrmryJo+EAAIm45n23XPY1/km/2ksiHriBwn74t/bXsURITE9m8eXP1+4SEhF1KwFazvl2tS0RERIzd+f9ra/9tICIincvO9riYZ3U6jvHmslgEVAUWbsQbtLA6HRUum/094EWr0/G1d/2R3n2WN1Wny2b/pKGdu2z2AOAz4CKr0zHfZbPHAD+7bPaVQDBwuNXpOASgMregeqhI8NhRdH/qOtwZW9h6wf3EzfhfgwdYmV9E3vXP0OO9+wjolUDFxs3kTriPmK+fxBLZbYfy+Q+8To9pt+PfMw6P242nqKR6XUD/JGKmPwrAlsMmVb8GwN9S+30XUPMPk/re70p9u1qXiIiIGLvz/9fW/ttAREQ6l52ZVaSa1enIBzYBMcBk4HB8QQsbEFkVtPCW/83qdBS3oM6GHAwstTod873b5AAvAeOBEiDRZbOPdNnsFkuPiB029k+KrxVYqE/pT38TfMIhBPQyc8YH9Eog+PiDKf3p73rL+4WFUDprIZWF2/Hz9683uCEiIiIiIiIiLbNLOS5cNntPIA7IBCYCKVano8K7uhewcRfqrEoi8anLZi/1vh4MvAYkARvqbLoeGGZ1OtJdNvudwEPAkPwpbxF550W1CpYvWYslJtK8cVeSc8ZtvnVL081iZw7+PeNqbeefFI/blVNvu6OemUzhcx9T+NzH+PdKIOqp6whIim/6gOvsv/u02/GPiWp6uz1YQkLCDt1BW6u+Xa1LREREjN35/2tr/20gIiKdy84GLka6bPZfMDN2XAbcDYwD3nDZ7GdYnY5lmKBF752t0+p0VLpsdoCz6uS4ABMo+U+d7Xt7l2N1Or4EvnTZ7MEVS9eWlM5eBH5Q+vMccs68Hb+gQKIev9ZsVWeoRlUQwWKNoWJV7diIOzOLwEH1H1JAUjzdnzB1bv/kZwqfeI/uz93Y9FF3waEirT1mVWNgRUREWt/u/P9V/5eLiEhjdnaoyDyr03GU1ek42up0/OxdtgKYAHzmstn7Wp0OJ5DnstlPrtrIZbMf4bLZQ1tQZ0P+BIa4bPYDvPVGA1cCH7ls9miXzR4PYHU6Sv26R0BlJWByXMR89gjRHzxA4NC9Gt1ByNhRlH73JxUZWwBwZ2yh9Ls/CR47qt7yFf/6Opf4x/eASs3CKiIiIiIiIrKrWnU6VKvTMc9ls18FfO2y2Y8Fzgee9s40EgCsAv5qhf1UuGz2ccCzLps9DPAH7rI6HWtcNns/4C2Xze4P+IVNPJmgI4ZR9sfiFu3D0j2cqGcmkzf5GROEsPgR9cxkLFHh9ZYvesNB+aJ/8QsNNmUfvbp5O6ozVCTilvMJOnhIi9oqIiIiIiIi0ln5eTydvmdApz/AtjBmzBgAZs6c2a7tEBERERERkU7LrzmFmtXjwmWzTwMGWp2OMd739wPHA2WA2+p0HOWy2ccAvwAjvFOU9gVeszodx9Sp60bgFCAE2BsIBJYD6cC1Vqcjx2Wzr7Y6Hf1rbPMh8LHV6fjC+/474H5gDnAPMMZbNM9bxzqXzX4xcGnQIUOxxHUncsoV+Md2x70ph22Tn4Xycjxl5YT+50gC+idR9M63RL9xFwDFn/9C2d/LCDnpcEpSZxH12DXV7a/MLSD30imUL03HLziIgP49CTriAMpmLQBM4s+Agb3xCwqg26WnUPjyF/R49Xb843tQ9s9KCh5+y/Tg8LcQefdEAvfvT0W6k6zDL6PH2/cQcuxBeCrcZB11NfFpLzfn1yPSpSUmJu4wbV5CQoLGS4s0kz5DIiIi0tE1Gbhw2exBwDBgi8tm7w10Aw63Oh2HeNdH1yi+CBNIOK2h+qxOx9Mum/15zJCRE6xOxzxvPfs10p7rgR9dNvtPmKDHGqvT8YfLZr8LE/gYbXU6PN5hIkHeIMoEYGzM548Wl3z/F3nXP0P0+/dT9Mr/EXb2MYSeNhqAyq35WKIj2f7pDEq+/YOgQ/ej8KX/I2b6I5Qv+HeHhlh6RND9hZvJu+UFKnMLiP7gQfyCA+GGcwDI/s8t1YEKgMKXvzD72VZI3g3PEv3+/fgnxVOxfhO5F9xPTOpTAAQM6EXh1E8JOfaghn8ZIrKDujdcDS0TkfrpMyQiIiIdXXOSc6YAXwFvA+cCJUCiy2Yf6bLZLVanY2uNsnMwgYPhTdR5ELC8KmgBYHU6Fludjnr/UrI6HVuA54HngJuB272rJgD3WZ0Oj7dcutXpWAVcCEyxOh0lACHHH0zl1nzcWbn4hYZQ9s8K3FtyzQmINtOiRj5wGQVPfUD+3a8Qfv04LJHdGmx88f/9SuiZRxNy/CGU/Ni8lB0lP/xFSMrh+HunSA3ok0jw2FGU/jwXAP+ecQQM6k3Jj383qz4RERERERGRrqA5gYvxwLvA18CJVqcjHbgTeAhY57LZ687leT9wbxN19sJMlwqAy2b/2WWzL3DZ7Kc2ss0bwBDgaavTke9dFmR1OkrrKZsE1JrL1D8pjkpXDt2uORNLRDe2nnsPWWOvofT3RWZ9TBRhF5yIe/NWQu1HNNr40p/nEHL8IYSecRQlX/7WxKEablc2/j3jai3zT4rDvSmn+n349WdT+PwnzapPRIyEhIRmLROR+ukzJCIiIh1do4ELl80eBRwOTAO+BPq6bPZhVqfjS6vTcSIwADjAZbMfVbWN1en4GzPko7FeFxsxwYuqbcYCXwD1T9lhyniA1d6fKmUumz24nuKZQO+aC9yZWVisMVjCQoi4ZQJxP02l+8u3knfbi9VlAvraCOhnbaTZUL5yPRXrNpE78SHybn6esnkrqNxW2Og2AP6JMbgzs2otc2dm4Z8Y49t/UjyB+/SltJm9OEQENm3ahMfjqfWjsfkizafPkIiIiHR0TfW4OBN4xOp0nGB1Ok4AJgJXu2z2eABvb4et9dRzPybXRUP+BvZx2ewjayzbmalZ3wPuc9nsfgAum72Py2YfiOkhcrvLZg8BKPnxb/yiwvGP60HF2kw8bjdgeln4+TUriWm14um/EPXktUR/8ADRHzxA+A3jKXHManK7kGMPoiR1dnXwomLjZkp/mkPw0QfWKhd+3TgKp37aojaJiIiIiIiIdFZNBQvOAy6r8X4W8A0m6OCHmbpkHjADGF1VyOp0zHHZ7JmYmUN2YHU6Klw2+5nAUy6bPQbYDuRienYA2LyJOKvYq/JV1PEYcDfwq8tmBzOryDVWp+Nnb6LOn3NOvw1LbBTdn78RgLLfF7P9mifxCw3GU+4m4t5LGj0BJT/NoWLcnYBJoFn62wIibhhfvT54zAjyrn+GsAknNFqPJTqSqKeuY9t1T5kJWv0tRD13A5aIMCqzt1WX80+KJ3C/vSn9fUmj9YmIiIiIiIh0BX4ej6e929DWOv0BtoUxY8YAMHPmzHZth4iIiIiIiHRazRoC0ZzknLvEZbOf67LZZ9b52bet9yvS2XhKynDZ7K0y80zuFY+RO+nhVmhV4yoLtrN14kNsGngWLpu9ejYf6Zyac1211rW35bBJtYbVbR42gaI3vt7lendGzrg7ybv1hXbZd02t+R0hIiIi0pGox4XUq716XPznxwlsLdvWdMEmfDKp8fUzD4UXJ+7ybna7qDwoCoOKwOaVH7YE7nwOzp8KpTUGboVuN6HN7WFt0sxqJ38PJ/0EUyZDQTjkR4BnF8Ol108Dfzc8fWXrtLE+fpVwzG8w5nfo5YRKC2yKg7SD4acjfecyvBDOSIVR8yF6GxSGweJ94NNTYFONSRnOnQ6nfrfjfrbEwDXeeZkOnQNHz4J+GyCyEO68Df7du/F2HjsTJr1vXlf6QXEIuOJhwX7w7dFQELFjG74fA6+f51tuc8Gz98BN98HGnrXrv+wd06b/XQxphzZ93przu2mta+/5O+DnZPjyRPM+ogBKg6CsvnTNbeyup2FzHLx6/u7fd10t/Y5oDdFB3fny2PdatE1rfdfLnmtnrhsREemUmtXjYmcSYoq0mdb6Q3bSk77XIxfBFe/UXlbWwB/1/hXg7oCfiqp25UW1Tn3FbRywqJK4BTbaIKNn02V3twZ/1x6YPA1GLIbpKfDGeBNw6Z0JJ/4Mud3h94PMjfKUR6AsCF4/Fzb0hJhcONMBj0yB+/4L63v5ql2XZAI4NVXWCOKElMKK/jD7ILjqreYfR0E3uPF+8PNAWDEMSIf/fAdj0+CeW2BzvK9sWaBZ7ji29vL6BJfCYXPhyxNg7KzmBS6ao62uvZpBmq6stb4jWmJnvrcVtBBdAyIi0hId8BZNZNfV/OO9KGzHZeB70vz05XDCL9B/LbxxLswbBhd/CINXQ7ftsDkWvjgRZh3i2/ahh83TcLfFPJGuCIBfDocPT6M6ZnjoHDjDAYlZ5oZxXS94+goo9E76e+ACs75XJpSEwMq94akrodIfpt1knpjbNsGoBaZNL18I718Fj14D/wzztf+ZyyDlJ+i7wTz1feNcWDrYrL/zObOvd681//54pHkqXPfJeGAZnP8ZHDYHQkpgbR949yzfE/+qnhv33QznfwpJLnOj/vIFsDGp/t/BQw/DwHTz+pNJsGAIPDwZxsyGE2aAdTOUBsPSQfDW2bV/P70y4bzpMPhfc0O+Pskc/5jf4fA5vjrB1zOh7wa48GNz414aBH8Ph7fPNucWfMe8vpfpqVBpgase37HdR/4Bh86DR66D+fv5lmfFmt9D2HbzfsJ0iCyA66ZAfqRZlhMDj14Ljz8AV74Ft93t297t3/hN5S9HmH+jtzZcpj4eP1+927qD02qO/Yn74ZL34eEbfGU32mB7KKsWMnYAACAASURBVJz7OTxzReP1HjoXNtjMtT/tZkjcXLsXSWPO+hKO+xWCykwg5o3xvh4Ada+95nyWum+Dy9+B/VbAtkj4+NQd9zntJhNo+v5oCCw3n5UXLzKfs2HLIDfK1PnHKN82g/6FSz4wn7ONPeGzk+HWFxrv7RJSApPeM71sikNNEKiuiAK46CMYvgQCK2B5f3hzPLgSzfpjZ8LZX8JLF5rPU8w28/l4YSIcuNCsiyiEv0fAq+f5zt3IhfCfb329gP7tB2+d4/u9VB133e+Ix682PZ8GpJvvszfOhWWDmve7FBEREekIFLiQLu/cz81N+rokc4MQVAb/7gX/d6K5MRm+BK5+E7JiYOUA33ZHzYavjoM77oD+6XDNG7C6L8wZAbE5cN1r5ob8n/3Nzc6gNb5tR82HG1+Gz1PghUsgoAIOWGJu0quc8r25kfrs5MbbP+Ezc4OeYTUBjFtfgGseBlcCPHcpXP+aeV8aZHoH1Oeij2HEIph6CWRHmyf2dzxnbsprPsk+5//gnXGmB8Il78O1r8Mt99Zf5yPXw8QPoEcePDfJ3JCCuWn98DTTvqh8EzC59nV4yEz8Q2wO3P+4GXLxwE1m+MPAteBfaW5Me24CS6UJmgAUdoPQYrjzWVg2EG6/EyLzvb1s3oWpNYYNDVtq6nvohob7pB3xF6zvWTtoUdP2MLC4zY39L4f7ghZVKv0h9Ri48h2wbvLdrO5OxaFmGMXZX5qhGTV7Obx/Bjz8MOydDmv6NVzH0WmQdoipa+4wE1T44Iym9z1sKZQHwP03QdxWE8ApCoP3z2x4m8Y+S2A+S+FFps6KALj4I+ie13Rbxn0F751hPt/H/wJXvwHLB5gAT9h281mZO8xcn3E5cOEnTdd58UcmoPb4NZAXaT4T/dNN0LDKta+ZoUOPXWMCZ+dNN5+nGx7wBSFCS0ybnr3c9G65+SXzUxoET1xtju/mF00Q8fujzDZBZfD18SZoGFIC476GW/4HN99rrruGjP8c3jvLDHca95XpUXT1o1C+G4eTiIiIiOyKNk/OKdLRpR4Lc4ZDVpwZBpAVa5at7w1b4sxNwz/7+570V1nbGz63m6edsw4xPSb2W2HWReeaIMSfI019G5Pgp9G+3hZnOEy+hE9PgUyr6QXw5Ym1hy4s2te0Y3N84936vx1rnsw6rfDaeZAfbvIzeCzmph4gL8I8lS8O3XH7bkXmpvSdcbBwKGTa4JULzA3+sb/WLvvhabB8oGnz5ynQN8M8Xa5PUTcTKKnwDnEp8rbl5yPNfrbEmafar4+H/Zf76jnxZ5MP47lJsLavufH/9TDzRLw0xPReKffWmRdlztno3835fmGiKbd0H3MuDp8DMTV6MBSHwrTzzdCVuvkcqli3mONrTPQ2M7Qjo4FyGTbzr22Tb1m/DfDONbV/rnqj8f3sigwbWDwmeFDT2r7wx4HmZrohNhfsvR5+9/ZO+O1QGP2HCdg0pTwQXr7InOP5+8FHp5oeTf4VDW/T2GepdwYMXQkvXWSul/Q+pidFSFnTbZlxuBnWszkePjjdnI+qAOLo36HC31zrmTaTF+Sr4xuvr1uR6ZHzzjhYso+5hv430dRbpVcGHLDMtHflAPPZfv5SE6Q7dJ6vXGAFTLsA1vU25f44EPZdBS9ebOpdvK/53hmywrfNH6PMd9XmePP99OJFpvdT342Nt/urE8zvwpVofh/d802vJhEREZE9hXpcSJe3pk/t9xY3nJ4Kh/xjAhABbtMjYsHQ2uU21Bkikdvd3JwArOkLKwbAc3fDwn1NEOKvEd7AhQf6ZJin8o1Z26fx9VVW7eV77bGYfSe5mrctmDwU/pUmv0IVdwCs7rdjPTWPObe7+TeyoGX5BfZOhzO/hj6Z5kawqpdJ7FZTT78N5ql4Y0+Q6+q5yQzFKa/Ro2RFf3ND2dMFOdFm2fqkpnOY1Oz10poybPDEVbWXlYTUX7ZVeGr9U8uHp8Gzd8PwxWboQF1jZ8H8ob5g08J9zXkZsRjmHmB6kjz2kK/8x6dA6nHmdXrv2k/yV+0FwWUQn91w75PGPks9XSZQld7bt35TggnQNWV9jXorAk3y1Op6N5mgQs3r4d9GeqCAGd7kXwmragwj2R4GGTWOK8nb3jV9fcsKw00wLMlZY7tQyI7xvc+LhJwetZOW5kWaIVDV+99ketHsvc4MJbHU+OysrbG/umqeh63ez21UAwFHERERkY6oTQMXyan2BOBTYDgwLS3FcVNb7q8jeXLxC8SGxHDRgPHt3RRpQmmdWQhOT4XjZ5phHhk2KAmGCz4xT0hrcte5sfb4mSEMYG6G7r/JDHHYfykcN9M84b77Nshs5tCBknaYHaGuuje9Ff47rrO04EY/bLsZ0jFvf3j+EjPkJHob3PO0CQ61BU+NMSGlDQyVqcmZYG6WG5MbZX4/NW9Ea6pa7qqRE6I8oOmEmK0pyWXyRtS8Oa6yJQ5+HG1mGnn2strr/CtMr4KIQvjwct9yP49J7Dn3ANgSC/+9x7euoBlBhMY09llqzXrxa7vAVHPUvBYr6h4z9ZwHany+PGa4SWaiGSa1zRuAeOrepj87ter1tsGvFc6viIiIyO6yy4GL5FT7OiABcANFwLfANWkpjkLgMiAbiExLcbTpn4vJqfaLgNeBYu+iLGDm+6NfoXf47p/S4Ob9rtnt+5TWMXi1SW44+2Dz3q/SPGmt7wawMR4LrOxvfj47GZ67Cw6ZC9NPNk9A91veOjM1DFgLq/r72rr3Ol+ix6qbo8ZuAjfFmxvcwat9iQv9K8y4/R9H73r7aurlhPDtJs9C1Y1Xvw21y6T3NgkKLe76e11U+JskhDVlJpqcE4Flvl4Xg1ebKUKdLcwxMftgk9Nk+OL681yEbTdPxf8YaYZPTLfXznNhcYP9RzP8wdnEkJO2ElpsggyL9q1/eBDAZ3aY+rs5hpoOXGhyKdx6d+1ZTxI3w42vQI9tpkdEQ0GYvhshoNyXy2HAWhMw2lJPz47myLSaoGG/DWaYCEDCFjNl7K7ITISD/qk9u0z/dY1v40own5UBa83wLDA5RJI2+dqW4W3v3ut8OUTCC00wrKleVo3psQ0Sss2wk6rEoQNXtyxwKCIiIrKnaq0cFyenpTjCgRHAgcBd3uV9gGVtHbSo4Q9vO6KAY4DiS2dNZm3But20e+kMXAkmweCANeZm47L3ILoZiQBrGrwKTv0G9loHMTlw0HyTpLIq98HnKZD8F5z5ldlHr0w4+fvG8wA05MQZJtmnzWVmSIgsgJ+ONOuyvDeLIxeZHBLBpTtuX9QNZhxhZjcYtgR6Os0MDqElvnpay5ZYE3g4cQbEZ8HIBWb60Jq+O9p0Y7/+Vei33twwH/Gnb0x+VqwZapO42RyTxW1yYHj8TMChV6bJC3DJBzB7lG+YSHP9dgj8fYBJnlr1O4zNgeGL4M5nTBJVMMGXgnC4+2kT5IjZam4kb33B9CJ56cLa9fq7ISqvzk++b314IfTZ4Buek7jFvI/Mp1F+Hl99Nhcc+buZpjWwwszm0ZCCCJPT4aSfay8/epaZPWV9L5NroepnzggzlGHM7MbbE1RmEqP2dMIBi+GcL+GHMTs/zfCGJFgyyFyT/deaa+LKt5rXe6Yxvx5mhoFd9p75DA5bAqd8Z9Z5GsjcWtTNXB8XfAJDlptr7eo3TYCsysYkM0PIlW/DoNXQZ6NJPpsXafJY7Kz8CDPU5dhfTeBmyHIzc0llQ1lmRURERDqRVh0qkpbiyExOtX8LDE1Otb8FnAd4klPtk4FTgXzgOWAfTM+I6cCNaSmOMoDkVLsHuBq4AUgEngXeAt4FhgLfAROqyjfSDjewBrjqljn3X/nGqg94aOQdAMza/BevrHib7JIc+kf246ahV9M3ohcAZ82YyGl9Uvg+8xec212MtR7JZYMv4OGFz7Jo6zL27T6QB0feTkSg6Rd997xHWJS7lFJ3mbeuq+gXYR67TVn4DPEhsUwadD7zcxbx4IKnGNfvP7y/ZjoWPwuXDbqAlF71zKMn7e6TUyAmF+5+BkqCYEYy/DnC3Iw2V1EY7LvSzPIRWmxm6vjoVPhrpFn/9wjTRf/0VDjtW5MIc0X/nXsi+8HpcNo35mZ+c5xvtgMwQwKmn2RutCILzUwTr56/Yx1vnW2erl/7upmtIL0PPHx9y3JXNEdud5O08OwvIOVHk5jwnbPg9qm+MlmxcO9/4bzPzOwilRbfdKgAP4w2N4SPP2gSZFZNXTllspkO9ZEptadDbSmPxUxLe9yvMHq2+R1V+psZGdIONjf1YHpZ3HGHCbxc+p4JTBWFmdlQ7rhjx3wOfTPg1ZtrL3NbYPwr5vWhc2HS+75113oTd75/uknc2pCIIlNvpZ/JmeGKN/lUvhnb9O/PcawZxlQVmIvZaoJ2TzcwVeofB5oZQP7vJBqclmXhEMiKhvufMD1jfh9lrv1dMfVSuPxtuO8Jc21/8p+WfR7rsz3MTBN6yQdm+toNPU2y3BumNT7bxlvnmOlQb33BnO/UY8x1WKu9l5igwm3Pm+DI8v7m87SzwRsw2z43ycx88tS9JsD61tlw17M7X6eIiIjInsLP49m1zhDeoSKXpqU4fkpOtffCBBc+T0tx3O0NXmSkpTju8pYdCQQCc4EkzLCSV9JSHM9613uAr4DzgV7AP8AsYBKQA/wBPJaW4ni7nnZc5G3HETWXp278wfPKinf46tj32FCYySWzruPhkXcxPGY/Pk7/gq83fM+7o18k0BLIWTMmEh3cg0cOvAu3x83EtOuJC4nltv2vo094L26Zcx8HRA/l4oHnVtXNUdYjCPAL5OUVbzJ/62LeTDZ3YHUDFzf8dRcT9h7HRQPOYU72fO6e9yj/d8zb1UGQjmbMmDEAzJw5c7fuNznVvlv3tyezueDZe+Cm+xqeIUNEmu/QOWbq1YnPNjzERuqXluJoulAN+q4XaPl1IyIinVKz+o+21lCRL5JT7dswQYZfgYfrK5SW4piXluL4My3FUZGW4lgHvALUHUX/eFqKIz8txbEUWAL8kJbiWJuW4sjDBDqGt6RhscEx5Jeb9OkzXL9xaPwoRsUNJ8ASwPi9TqfUXcqS3OXV5c/oayc6uAdxIbEMix7Cvt0HMjBqb4L9g0hOOJRV+Wury6b0Oo6wgDCC/AO5eOC5rM5Pp7C8qN52+PsFcNGA8QRYAjg0fhShASFsKMxoyaGIiEgrOmqW6b0Tlw0HLjDDpf4aoaCFtK9bn2/bqZJb4pNJcPC8psuJiIi0tdYaKnJqWorjp6YKJafaBwJPY/JghHn3X/e/xM01XhfX875FqfaySnKIDDT9pbNLtpIQ6ssoZ/GzEB8aR1ZJTvWy6OAe1a+DLEFEB3evfh/sH0Rxhcn96fa4eXXlu/zimsW2sjws3hhQXlk+4YHddmhHVFAEARZfpsEQ/2CK3SUtORQREWlFPbaZqXmj8mFbFMwZboZeScdz1RtmppvHrjPvz/oKzvravK70M9O8Lhxifn8jFsHVbzVe3303w7JB5vVhf8Op35rhXI2ZeSi8ONHczD91hW/oH5h8NKd+B/usMsO38iJhg80Mz5t7gBmCtiea9KQZAiciItLe2nQ61Hq8BMwHxqelOAq8uS/ObMsd/rb5D/aP3heA2JBo1hasr17n8XjYUpxFXEgLp4sAfsz8lVmb/uSZgx/CGppAYUURJ/1wDp4dJpAUaRtOK4x7tb1bIbLn+txufmTPlJloAhCWSjPrzBVvm9wnT14JC4b6yl37OhR2gzfP8S0rrPF8YdQCE7SaMtm3bOQik2R20pO+ZWUN5D4ZsRBuehkWDzY5fFwJZoraAWvh9G9gTV/Y2sIkwR1FXlR7t0BERMTY3YGLCEyCzsLkVPtg4ErMtKWtKjnV7g/0Bm4M9Q/hpcPMXx5HW5N5f81nzM1ewAHRQ/k0/SsCLYEM7bFPi/dRXFFMoH8gUYGRlLhLmbbindY9CBEREWmQ2+K7sc7tAd+OhbO/NO9r3nCXB5igQ3034f4VZqagL0+ovb6ql0FTN+7BpXDVW/DPfvDUVbXXOa3w6+HQ2POMoFK49H045B+TDPrbsTuW6VYEF30MIxdCULlJ5PzW2ZDhzW00ejZc8iE8fblJ3hq71SQJnjoR9l8O535uZmqaOwxeOd83ZfSwJSb5cC+neb+6L7x9jpmCuErN3iVx2fC/2837Y3+FQWsgK8YEhBbv2/h5EhER2VW7u/PizcC5QAHwKvBxK9d/aHKqvRATHJkJRE47/Bn2juwLQO/wJO4+4CaeXfoK9h/PZfaWv3ls1D0EWhpJId+A45OOJjE0ntN+vpDzf7uSIT0GteJhiIiISEuUBYLFA/6Vzd9myErYHmpmONoZ+y81MzZ9dXwjhRpJOXb+Zya48NQV8OBN0Hcj7PNv7TJXvQn90+GJq+H2O6AsCO54DgJrzK8WUAH2H+H5S+GBG800zje9DGN+N7MkPXGVGUJz/EzfNiGl8M0xZhak+/5rcrvcOrXpabnP+cIEWP57j+lNMnkaBGvkq4iItLFd7nGRluLo28i6i+q8/w0YXKfYPTXW+9Upf0Sd93c1sq+3MFOn1nVBzTdHJh7GkYmH1VvHp0fXzoZ1z/Dacxee3Pt4Tu5t/joJCwjlkQPvrrX+hCTfo5I7h91Q/Xp4zP58Prb2RCh19yUiIiI7x+YyUxj/289MU9tcoxaYHBQ7vV9vFi5njexbvTJgyqO+99MmwKxDdtw2uASOngUvXQgLvUNbXrwIXr7FVyZxM4xaaKaIXj7QLJs6EV66DZL/MtN1g5l29/VzfdMwzz7YTDk96SnftMhzh8GQFeA4zryvmaMD4MWL4e1rTZBk5YCGjzn1GN+00B+cBqP/MAGXxrYRERHZVbt7qIiIiIjILktywTvXmBwXARWwbCC8ckHT29U0cqG5YW9NzkTTGwHgifvB311/ucQsCKyAVXv7lpWGwIYa01v3dJnko6v28i0rDjNlkpy+ZWUBvqAFwLZIk3C2KmgBJmFoksv3PmGLGVrTPx0iC0xvFYvHDDVZ2cjxrU/yvc715i+PKmhkAxERkVagwIWIiIjscTbFwSPXmxv73O5Q0cJRn3utM8Mllg3c+TY4E8y/tk3wrzcA4Q6AzVUTmDVrZvqd46lRd6X/jusr6izz+IFfjXwbt06FrT3g1QnmX7cFnr7XBIEa465Zr7cNfspLLiIibWwPnaBLREREurIKb4AgK67lQQsww0Tm71f/TX9zLRoC+eFw2rct33ZTnAkuDFjrWxZc6kuWCSZRpsUDA2uUCS2G3pmQUSOJZkuFF0LSJvi/k0xizUwrhJaYISciIiIdkXpciIiISJdz4AKYvovT4ZYGw8sXwo0vwx3PmvwPm+IhqAz2XwaB5VDZwCOi0hCYcQScNx3yIyA3Cs50mKEvVTYlwJwDYNK7MO18M9vJ+C9gewjMOnjn210UZgIuY9MgOxqic02i0Lq9NERERDoKBS5ERESkS4nPAutmWDB01+uaewDceTv85zszNWpEIRSHQHpvk2yzsQDDu2eZXhb/fRFKg+C7o837ml68yEyHesv/fNOhPny9b1rTneGxwDOXwcUfwVP3mmDLu2eZmUhEREQ6Ij+Pp9MPTOz0B9gWxowZA8DMmTN3636TU3fx8ZeIiOx2aSmOFpVv7+/6lB9hv2Xw6PXt2owur6XXjYiIdErNygilHBfSoUQHdW/vJoiISAvszPd2e3/Xb+0OX5zYrk3o8tr7GhARkT2LelxIvdqrx4WIiIiIiIh0GepxISIiIiIiIiJ7NgUuRERERERERKTDUuBCRERERERERDosTYcqDVq9enV1rgsRERERERGR1tTcnIrqcSEiIiIiIiIiHZZ6XEiD+vfvr1lFREREREREpF2px4WIiIiIiIiIdFgKXIiIiIiIiIhIh6XAhYiIiIiIiIh0WApciIiIiIiIiEiHpcCFiIiIiIiIiHRYClyIiIiIiIiISIelwIWIiIiIiIiIdFgKXIiIiIiIiIhIh6XAhYiIiIiIiIh0WApciIiIiIiIiEiHpcCFiIiIiIiIiHRYClyIiIiIiIiISIelwIWIiIiIiIiIdFgKXIiIiIiIiIhIh6XAhYiIiIiIiIh0WApciIiIiIiIiEiHpcCFiIiIiIiIiHRYClyIiIiIiIiISIelwIWIiIiIiIiIdFgKXIiIiIiIiIhIh6XAhYiIiIiIiIh0WApciIiIiIiIiEiHpcCFiIiIiIiIiHRYClyIiIiIiIiISIelwIWIiIiIiIiIdFgKXIiIiIiIiIhIh6XAhYiIiIiIiIh0WApciIiIiIiIiEiHpcCFiIiIiIiIiHRYClyIiIiIiIiISIelwIWIiIiIiIiIdFgKXIjIHsHj8ZC3vby9myEiIiIiIruZAhciskf4coGTkQ/9yLeLXe3dFJEu7dO5G5mxYnN7N0NERES6EAUuRGSPsDarkIpKD9d+OJ9fVmxp7+aIdFlTZ6xm6ozV7d0MERER6UIUuBCRPcKWglK6hwVi6x7K67PS27s5Il1WTmEpy135uCs97d0UERER6SIUuBCRPUJWQSm2qFD2T4oiI3d7ezdHpEsqLnNTVOampLyStVmF7d0cERER6SIUuBCRDmtLfgmrNheY1wWlxEUE07NHKM5tJVTqaa/IbpdTVFr9eokzrx1bIiIiIl2JAhci0mE9lLqci9+cA5geF/ERwST1CKPMXUlWYWkTW4tIa8suLKt+vTQzvx1bIiIiIl2JAhci0mEtceaRua2Y7WUVZBeWEh8ZTFL3UAAycovbuXUiXU+ON2AYHGBRjwsRERHZbRS4EJEOqbjMzbrsIgAWbsyjotJDXLgZKgIoz4VIO8jx9rg4ZK8Yljrz8Xg0ZEtERETangIX0m48Hg+z/s1WrgKp16rNBVRdGvPWbwUgPjKEnt4eF5nb1ONCZHfL9ua4GD0wjoKSCjZu1edQRERE2p4CF9Ju5qzLZcLrf/Hrqqz2bop0QMtdvvHzc9fnAhAfEUy34AB6hAWSqaEiIrtddkEZ4cEBjOjTA4Dlm5TnQkRERNqeAhfSbv7dYmaLWOmdNUKkphWbCggL8ic8OIB53sBFXEQwAEk9wpTjQqQd5BSVEhMeRL/YbgDVw7lERERE2pICF9Ju1ueYHAVrthS2c0ukI1rmymdwYgS9o8MoKKkAfIGLnt1DNVREpB3kFJYR0y2IqNBAorsFsS5HgQsRERFpewpcSLtJ9z6pW52lwIXU5vF4WOHKZ7A1kt7RYQCEBwcQFhQAQFKPUDJytysxoMhull1YSky4CSD2jQmr/h4XERERaUsKXEi7qepivGZLoW5ApRZXXgn5JRXskxhBnxgTuIj39rYA6NkjlJLySrYWlbVXE0W6pOzCMmLDgwDoG9uNddma3UdERETangIX0i4qKz2s37qd8OAA8ksqyCosbe8mSQfyxYJMAEb06UEvb4+LuJqBC80sIrLbVVZ62FpUSqy3x0W/mG5syi+huMzdzi0TERGRzk6BC2kXzrxiyioqOXJgLABrtqi7sRh528t5eeYaxg6OZ4gtqrrHRc3ARVUwY8NWPe0V2V22FZdT6YGYbr4eF4DyXIiIiEibU+BC2kVV9+Jj9kkAYI3yXIjXy7+toaC0gpuPHwRQneMiPiKkukxVMKMqwauItL1sb8+4qhwXmllEREREdpcuHbiYn7OI03++sPr9+b9exfycRS2uZ+HWJZw78/LWbFqnl+59QnfIXjGEBfmzWjOLCLC9rIJ3/1hPyn5W9rFGAmZYyF6x3RjWK6q6XFhQAPERwUoMKNLG8kvKySsuB2oGLkyPi6oA4joFEEVERKSNBezKxsmp9nXApWkpjp+SU+0XAa8DVYPOs4CZwCNpKY5V3vJ9gXSg6m4jG3g5LcXxaCP78ADbAQ+QB3wM/DctxdHqg2rfHf1is8olp9r5cMw0krrZABgWPZQPxrzS2s3p1NZnFxEcYCExMoS948K7ZI+LCnclj3y7grGD4zmsf2x7N6dDcCxyUVhawYWH9a1eFuBvYcbNY3Yo2ze2G+vVRV2k1f3vl9X8uTaHgpIKFmfm0Sc6jJ9vGk1OoUmGG+ftcREREkhseJB6XIiIiEiba+0eF3+kpTjCgSjgGEwQY15yqn1onXLdveXOBO5OTrUf20S9w7zlxwLnApPqFkhOte9SEEZ2r3U5RfSN6YbF4sfgxAjmrNvKzJVb2rtZba6gpJxbP1vEd0tc3P/1Ml6flc70fzLbu1kdxkd/b6B/fDgH9unRZFkzFaOe9Iq0Jo/Hw8sz17BqcwHBARaOGhTH2uwiljrzq3s41cw30zemW3UPOhEREZG20iY3+97eEGuAq5JT7b2B+zBBirrl5ian2pcCBwA/NqPeFcmp9jRgKFT3+HgJOA8YlJxq7wbEA1OBI4HC6/e9jDP7nQJAqbuUJ5e8yKxNfxITEs1JScfUqv+sGRO5df/rODD2ANweN++vmU7qxh/ILc2jVzcbDx94Fw8ueBKAi9OuxQ8/bt3/OqKDu/Pggqf4fOzbAKwr2MhTS/7H6vx0YkNiuHzwhRyRcDAAUxY+Q6h/CK7tm1m4dSl9I3px7wH/pWc3a4vO8Z6qsLSCh79ZzsyVWdj3N8d88/GDWOrM55K35/LAf4Zw3sF92rmVbWfqjNV8PHcjH8/dCIC/xY+NuV3v5tu5rZir3v+nejYCPz/YK64b/2zYxl0p++Dn59dkHX1ju5FdmEFhaQXhwYpbirSGrIJSCkoruOm4gVx0eD9yCksZNeUnvl+6ia8XOjmoXzTdw4Kqy+9jjeT9v9Zz0ycLuTNlH6K7BTVSu4iIiMjO2R05Lj4HkutbkZxqPwQThFjdnIqSU+37euuaX2PxeCAF6A5UAl8DC4GewNhP0r/kr6x5ALz574c4i1x8fNRrPHXQA3yX8XOD+/p47Rf87PyVJ0bdx/fHf8Ltw64npMbaKQAAIABJREFUxD+YFw59zNSVPJUfTviMsbYja21XUVnBbXMfYFTcCL469j0mD7mcB+Y/yYbCjOoyPzt/4+KB4/nmuI9ICrMybeU7zTn8TuHt39fxwV8bGH9Qb+627wtAQmQIn1xxKEcOiOXO/1vCI98ux+PxtHNLW196dhFvzk7njBFJPHr6flx7dH9O3t9KRhecGeP3NTks2LgNa/cQ+sV2o2f3UP5au5WIkABOH5HUrDr6xSgxoEhrW+0dtrd3fDhgEnEe2DeaN2evY13OdsYf1KtW+ZuPH8TEw/vx1cJMHv9uxW5vr4iIiHQNu+MxpROIrrMsOznVHgyEAE8BXzRRxz/JqXY3sBV4DXizxrrn01IcGwGSU+0HA3FpKY4HvOvWvrv6E352pnFw3EhmONO4aehVRAZFEEkEZ/Y7hbf+/bDeHTo2/sCVgy+md7i5ieofuVezDnbpthUUu4uZsPeZWPwsjIwdxmEJo/jJ+SsTB54HQHLioezb3cyYcGzPMbyw7PVm1d0ZLM7Io19sNx48tfboofDgAF694EDu/nIpr/y6luT+cRwxoHPlfZiSupzgAH9uPXFQ9QwZT/+4ii8XOimrqCQooOvkyk3PLiTA4serFxxIoL857spKD2XuSkIC/ZtVR58Y31SMQ3tGNVF6z3bfV0sprXDzyOn7t3dTpJNbm2UCgXvHhVcvO2FIIn+nbyUyJIATh9buHRgVGshd9n3ZVlyOY5GLe08eQmhQ8z7DIiIiIs21OwIXPTEBh5piMck2r8fkrAgEyhqpY0RaiqOhXhkba7zuA9iSU+3bqhaE+ocyLNo82c8p3Up8qO9mOCE0rsEdbinOpme3xEaaVL/skq3Eh8Rh8fPdhCaGxpNVklP9PibYN34/xD+YYncxXcVSVx77J3Wvd12Av4X7TtmXGSs2M3XGv3t04KKotILMbcXsHReOv8WPWf9m89Pyzdx6wuBa03r26hGKx2OGTvT1Ti3YFazNKqJ3dFh10ALAYvEjxNL8G56+sV1nStQfl20mv6ScKafuh8XS9DAakZ21JquQsCB/EiN931PHDUngwdRlnDa8Z4OBxTNHJvHZvAy+X7qJU4f33F3NFRERkS5idwQuTgPS6i705sF4OjnVfjpwFfDsTtZfc0zBRiA9LcUxoL71McHRbCnOpl+EyaGwuTirwUrjQ2PJLNrEXhF9W9SY2JBotpRkUemprA5ebC7Oopd3BpKuLG97ORu3FjP+oN4NlgkO8OfyI/fmAccy/k7fykH96nbW2TNM/ngBPy7bTERwAPZhVuauy6VXdCgXH963Vrle0ebme2Pu9i4XuNgrbteOt7NOiepY5OTbxZuYOn44Fosfhd4gGMDa7EL6x0e0cwulM1vj/WzWDJAl9Qjjo0mHsK8tssHtDuobTe/oMD6bl6HARTsqq6gkwOKnAKeIiHQ6bdI3PTnV7p+cau+XnGqfCowB7m+k+KPALcmp9pBGyjTX30BBcqr91uRUe2hyqt1/bcE6lm9bBcBR1iN4d82nFJQXsqU4m+nrHA1WZO91HK+teo+NRZl4PB5W56eTV5YPQHRwd5zbN9W73b7dBxFsCeaDNdOpqKxgfs4iZm/+e4dcGF3RUlceAENsjXfrH39Qb2K6BfHW7+m7o1mtbvbqbH5ctpkzRyZx/NBEpv+Tyb9bCrnzpH12eFpZHbjY2nV63bgrPaTnFLFXja7oO6tvbLfqHBcej4ctBSW7XGd7+/yfTFIXu/hhmfmO+XdzQfW6f9Zva2gzkVaxZkthrWEiVQ7eK4aIkMAGt7NY/Dh9RE9mr8kmu7C0LZsoDais9HDUkzN5Y/ae+X+niIhIY1o7cHFocqq9EMgHZgKRwKi0FMfiRrZJBXKpZ4rTlvL24rBjZilJB7IfWzSVogrTlfzigeNJDI1j3IxLuPHvuzm+51EN1nX2XqdytPUIbvrrHo7/fhyPLXqeUrcZzXLxgHOZsvAZTvz+bGY4a3cmCbQE8tioe/gzax72H8/lqSUvcdcBN9AnvFd9u+lSljlN4GdII0/tAEKD/DliQCwLNux5N2nuSg8POpaR1COUh04dypNnDWP2rUfzzsSDOH7IjkOPEiNDCPTvWjOLOLcVU1ZRyV6t0MOkf3w4S5x5LNi4jdumL+agKT/zyDfLKauobIWW7n4ej4dFGSbA98Ivq/F4PPy72SRL9Lf4MX9jbns2Tzq54jI3zrziegMXzXFwvxg8Ht93vexervwSMrcVM2+9vidERKTz8euMszfU0ekPsC2MGTMGgJkzZ7ZouxdnrubTuRl8P/nIHZJN3vDxAn5fk81fdxzTwNY+r/62linfLGfeXccQEx7coja0pw//3sDtny/mf+eOIGX/5k1xO/qJX9ivZxQvnDuijVvXMcxcuYWL3pzDJ5cfustDgVx5xYx75Q+c20pwV3oY2acH89bnMu7AJB4/c1grtXj3cW4r5rBHZzAsKYqFGXm8efEoZv+bzbt/ruegftFkFZTy3eTO03tre1kF0//J5JRhNqJCG36aL7vHMmc+Jz2fxgvnDse+f8uHN+YWlTH8wR+546TBXHbk3m3QQmnMb6uyuOCNvxmcGNGpvidERKTTa9b4xq4zjYG0irzi8gaf5ny/dBOPf7eS9OwiVtXo3l5lqTOvyWEiVYb0NL0yluxBT+4KSsp56oeVHNinByft1/zErkk9QtmY23WGilTNWtCvFXpcWKNC+eDSQxgQH851R/fnsysO5eRhNmasyNojp9RdlGF6Gd1l35fEyBDemr2OVVsK6R8fzsg+PVi5uYDC0op2bmXrWLmpAPvzs7j7iyV8Ondj0xtIm1tTNRXqTva46NEtiITIYFa4dvz+l7ZX9ftLzy6isnLP+/4TERFpjAIX0iKPfrucc6b9QUm5u9byjNzt3Pjxguru/ws21h7mUVBSzpqsoiaHiVSpCnAsycxrhVbvHi/NXEN2YRl32/fFz6/5idF69QgjY2vnHyri8Xgoq6hkbXYhESEBxIYHtUq9vaLD+G7ykdx43CD8/PwY2bs72YWluPL2vHwXizLyCLD4sV/PKMYdmMRv/2Yxf30uAxMiGN67Bx4PLNq45w2hqs/D3ywnd3sZIYEWNnaB639P8MfaHIICLLsUVBycGMmKTTsfuCguczddSOpVFbgoraisTujbGHelB7cCHCIisodQ4EKaraTcjWORi3K3p9YUlB6Ph3u+XEqlB96eeBA9wgKrnxxX+X7pZtyVHsYMangK2pqiQgPpExPGUueeE7j4ZrGLowfHM6xX/dO9NqRXdBg5RWUUdZIn6Q1598/1DL33e75ZvIm94sJbFNxpiarzX/ca3BMsyshjUGIEIYH+jBtl8uIUlFYwICGcA7zTCM/vJIGL9OwijhgQR7/Y8C7V46ij2ra9jM//yeDUA2wNTnnaHIOtEazeUki5u+V5Zv5cm8M+93zHUU/O5PN/Mna6DZ3dmqxCHnIso6LOOV6zpYgg7xTTzZlt6eZPF3LFe/P+n737Dm+rvho4/tX0kPeM904cZydkkRgSEgI0ZrdQoKwy2jJKB6XlpQv60kGhtKWFt0AptGWPFkiYARJMQvZ0Esd7T3lbki1rvH9oJI7teMmWnJzP8/Cg6EpXv3t1Jeuee37nTMgYhRBCCE+TwIUYsU8Lm+jqcZxclzmv7AC8d6iBTwub+OG66SRFBDIvKYwD1f0DDm/vryUpIoCFyeEjfr3Z8aEU1Dqmitjtdj483EB9h2+e4JgtNqrbTCPOKDlRaqTj6ubR+k7sdjtv76+ls6fP00P0uvcPNaBVK2k3mpmTMPr9NFIz40JQKxUcqJk6QS9wFeZsZ64zQJEYHkhuliPQNyM2mNBADRnROvZVTf3Ce1abnbp2E0nhASSFB0jGhQ94eWc1PX02bl6RNq71zJwWgtlqc584v767miue3MqD7x7mrpf2cvmTW3ltV/WggY1d5a0AqJUK/nfjUZnuMAi73c6P3zjIs1+UD/iOK23uZnlGJND/b/RQtpXqp1RWoxBCiDObBC7EiP1nXy2ROkd6f+kJP4qe3FzCjNhgbjo7FYC5iWEUN3VRoTfwwH8O8UWxnq0lei6bnzCqq+yzEkKoajXSYezjkQ+P8a1/7eHZfN9s81bdZsRqs48pxTp3ehR+aiVv769j87Fm7nllPw+9e2QCRuk9JrOVPZVtXLMkie33r+F/vjJzwl7LX6MiOy6YA1MsM6G61URnj4W5icfrwNy6Mo3wQI07mLEgOZx9Ve1Tsn7Hieo7TFhsdpIiAkmKCKSmzTTlt+lkPX1WCht8v0bPBwX13PrCbp7+vJTl6ZHMjBtfUHHGtGDAEYjt6unj4feOUtVq5MUdVeyuaMPQa+G+Nw9y3xsHBzy3sLGLpIgA7lidQavBzJF6399/k+3dg/XsdtaZ2lXR6r6/s6ePpq5elqVHEuSnpmyYjItWg5nGzl4aO3vGlB0jhBBCTDa1twcgpobOnj42H2vixuWpbDxU7y6wWK43cLiuk5+un4namaI6LzEUmx2uf24H1a0mXtxRBcCl8xNG9ZqznXUuch/5lM4eC0oFVIwg/dUbysdRcDLEX8P5ObG8e7COY86ipm/sqeG6pcksGEWGijccqG6n3dTHudOj3VfRXbp7LeypbCMhPAClQoHZamNlVjQxIf4TPq55iWG8s78Om82OUjl4sKyzp49gP/WETVkZrfIWxzGUGXO8MOI506PZ9/N17n8vSA7jjT01VLeaSI4MnPQxjlV1q5FDtR18ZU6c89+O4yQpPJDePiumPiv6bjPRwVOng9Bwnt9WwaMfHmPH/6zx6c5IT20upUxvIDVSx/fPnz7u9WVEB6FWKjjW0EWF3ki7sY937lrBrPhQXB/FH7x2gE1HGwd8Po81dDEjNoQVmVEAfF7czOyEkRV0PhNYbXZ++95RZsWHYDJb2VXeyrfPdXRvcf1NzowJIj1aN+xUkaPOoJDNDo2dPSSGT53vEyGEEGcmCVyIESlu7KbPaufszEgKG7oodf4o2nCgDqBf60/X1eHqVhP3rMnicF0nSkX/E7KRWJYeybfPzaCrp4/pscFsLdEPexXJW1w/Esda1O7KhYlsOFjPzvJW7j4vk1d3VfPLd4/w9p0rPDlMj/v52wUcqOngsvnxFNR1UtI0MD1Zq1KSmxWFVqVkSer42p+O1LzEMF7cUcWP3jiIVq3g9nMySIvS0WYw89SWUt47VE9Nm4lnbziLtTmxkzKm4VQ5p0skneIEYkGSI5C1r7ptSgUufv/hMd49WMehX15AkJ+a6jbntkYE0GtxFGOsajWeVoGLw3WdWGx2dle2ccGskXcZmky9FitH6ju5ZWU6P7ko2yPr1KqVZMUG8/TnZSgVCtblxLr/JriszIziP/tqKWnuZnpssHss5XoDF86aRkywP9nTgvmiWM8dqzI9Mq7TQXFTF3UdPfxg3Qx2V7TyfkGDO/hT2uTqCKMjPUrHropTTyk7ekI2S22bSQIXQgghfJ4ELsSIuE7MUyN1pEfr+M/eWux2OxsO1rM4NZy40AD3Y6OD/UiP1hEb7M89a7KGvOI9HK1a2e/HdF27ic3HmrHa7KjGuM6JUqY3EKHTEhY4tk4ZuVlRRAVpMZqt3LoyndAADf+78Si17SYSwgKGX4EXWG12jjV2kRAWwH/315ERreOhS2cRqHV8rWhUClIjddz0j518UtjE8vRIArRjL/o3GmelhqNQwMZDdShQ8PruGhLDA2ju6sXUZ2XNzFjqO3rYV93mM4GL6lYjWrWSmFOcvE+PDSJQq2JvZduoM5gm25ObSzCZrdx9XhafHWvCbofDtR0sTY+kptWIUgHxYQGYLY409Zo2I4tSfDvDaDSKndlTu8pb3YELq81OU1cPKoWC6GA/r2f7HKnrpM9qZ36SZ7MaHr96Hu/sr+NIfSc/HiQg4nqf9zg75oCjsKTVZndPNVmZGcU/v6zEZLZO2veGr9tb6Zj+tiglHAXwyq5qipq6mBEbzLbSFjQqBUkRgaRFBfHf/XWn3HdH67tQKRWOTDkfrR0lhBBCnEgCF2JEKvQGVErHj6L0KB1dvRa+KNFzrLGLBy+ZNeDxb3z7bAK1qjEHLQaTEqnDbLXR0Nnjcyfz5frucbUQVKuU/O9ls+m12AgN1LgLrO0qbyVhgW+eoFa3Gunps/HdNZmcnRFFfFjAoAGlhy6dzd0v7yN3etSkjS09Ooj8+1YTFeRHZ08ff88vp6GzB52fmpvOTmV6bDDnPbZ50AwRb6lqMZIUHnDKz4xapWRuYig7ylvp6ukj2F9Dn9VGQW0H28taOVzXwffWZpEZEzyJIx/c67trqGo1Eh8W4C7qe8gZuKhuMxEXGoBGpXRf6T2dCnRarDZ36v6uyuNXvn/42n7+u9+Rpfbw5bO5bmmKV8bn4qoDMz/JswGj7GkhZF84dK2MlMhAInRaZ92bZACONXY6n+s4dnOnR/PsF+VsL2thdXaMR8c3Ve2pbCNCpyU1MhC183viw4JGXt5RxZt7a7hxeQoalZLZzuLHW4qauXD24Nk+R+s7WZQSzs7yVurap17raCGEEGceCVyIESlvMZAY7jjRSI92TPn4yZuH0GlV5J0wTcQlQje2zINTSXGmxlfqDT4YuDC4O0CM1YWzj+/H7GkhBPup2VXRymU+Grhw1eOYMS2EpIih04zz5sYRFqgZVUcZT3CdEPtrVNw/SDHQzOggnwpcVLcZST7FfnRZnh7F45uKmP/QxwT7qzGZrfRajhfXy4oJ5p613g1c9PRZqWwxYLPDL985TIBGhc5PzSFnB4PqViOJ4Y7PcIBWRVSQn7vuxemgstWI2WojPtSfw7UdGM0WqltNvH2gjkvmxfNlWQtflrZMWuCiu9fCZX/dir67l6TwQF7/9nL8NSoO1HQQG+LHtNCJrztzIoVCwcLkcPaeENQpbOhCq1KS6gwAL02LIFKn5bmt5RK4cNpX1cbC5DAUCgWJ4QFMC/Hn8U1FANy8IpWfrc8B4Nzp0SSGB/BsftmggYs+q42Spm5uXplKaVM3NdKOWAghxBQgXUXEiFQ4i7cBpEc7/l/bbuLO8zInrfCcO3DhY1dmDb0WGjt7x5VxcTKVUsHClPB+VeN9TVGDI3CRNUztEoVCQW5WNDo/34qTZsQEUdli9ImK+na73ZFxMYLAxV3nZfLSrUu5c3Uml86L54blKTx53UJ2/3QtyRGBFDd1TcKIT61c7whaRAX50Wuxcc70KBYkhx0PXLT139akiAB33YvTgWuayDVLkrHY7OyvaudPnxSh06p56NJZnJUS7t4Xk2FfVRslTd0sSHK8By85Cybvr25n3kn1JybLopRwyvQGWg1mwFGYMyMmCI2zyLO/RsXt56STX6xnT6Xvfg9OllaDmTK9wV2wWaFQ8OsrZnP/RdlsuHslv7h4ljtbS61S8s0VaeyubGPvSe2T//BxET987QBmq42cuBDiwwL6FVUWQgghfJUELsSw7HY7FXqD+8Q8PjQAf42SxPAAvrkibdLGERcagFalpKLFtwp0uup/pHswcAGwODWcosZu2o1mj67XU1ytC30tIDFSmdFBWGx2Kls8c8Lca7Hyr+2V7mKTo9Fh6qOr1zKijAuVUsHZmVH84PzpPHjpbB5Yn8NX5sQRFeRHZoxvZJEUO8fws7yZaFQKLp4Xz9yEUMqaDbR099LY2duvCGlyRKC7OOnpoKjRsf1XLU5CoYAH/lvAe4cauHlFKmGBWuYkhlLZ4mj1PBn2V7WjUMCfrlnAsvQIntpSSkNHD+V6A/OTvRe4ADj395+x8Fcfk1+sZ0Zs/yDo9ctTiNBp+eOmYm8M0afscwYgTqwDc152LN86N2PQzitXLU4ixF/NC9sq3PcZzRae+LSYdw7UoVIqWJAUToIELoQQQkwRErgQw2ru6sVgtroDF0qlgt9cMYe/XrsQf83kFU1TKRUkRgRQqfetExx3R5FoTwcuHB04dg9THd5bihocReGmKleXG0+d6L+4vYqf/beAzwqbR/1cd0eREQQuTiUrJogyvQGL1cZfPyvh08LGca1vrEoau1Aq4MLZ09j1wFrWz4ljdqLj5OrDw44xJUUcn+6VHBFIfUfPmII+vqi4qZukiABiQ/xZOzMWu93O9ctS+JazdeXcBEewYLKyLvZXt5MRHUSIv4bvr51Oc1cv5z22GYD5Sd4JXCxMDuO752Vy2fwE1s+J47qlydx2Tnq/xwRq1Vy/LIX8Yr3PBnAny96qNlRKBXMTR1ZINchPzYrMKA7VHD/Gihq7sdvhyesWsuuBtSRHBhIfFkBtuwm73T5RQxdCCCE8YmpeKhWTyt1R5ISMgssXJHplLKmRun4ZF70WK35q71acP1LfiVqpcE+l8ZR5SWFoVUp2Vbb6TOcLF1frwnWzfGtco5HhDFyUNo8/cGG12XluazkAJU1dwOjaX7rqO4wk4+JUMmOCMFtsHK7r5A8fF3Hu9GjOy47FYrVhszs69UyG4qZuUiN1+KlV7s/nHOdV4T865+SfGKSZGReC1WansL6LeV46kfak4sYuspwFUp+54awBy1374mBtOyuzJrZord1uZ391u7tOxNL0SG7LTaOl28yKzCiWpUVO6OsPRa1S8oN1M4Z9nCuAe7iukxWZk1fg19cca+gmPUrn7to0EimROjYdbcRitaFWKSl0tkCdHR/qrkMVH+aP0Wylw9Q35q5YQgghxGSQjAsxLFegIM3DJ+ZjkRLpSCm32+28uaeGOb/4iC1Fo7/C7UkHa9rJjgv2ePaJv0bFzPgQ9le1e3S9nlDWbMBis7tbGU5FQX5q4kL9PZJx8eHhBmraTCgUx6dJjIbHMi6c78cLX1Zgtdnd2/bzdw6z6Fcf8/jHRZOS1VDc1O3OaHGJCvJjRWYkYYEabl2Z1q+2gusq8sEa3zvWT9Tc1UtDx6k7MLg6imTFDl37JTRQQ0pkYL+r4ROlutVEi8HcL7PigfU5/OHq+Vy5KNGjnZ8mwqx4R4eMgkmsCeKLqluN7jpPI5UWFUif1U6985gtbOhCp1W5C+MC7ttSoFMIIYSvk8CFGFa53ohGpSA+bHIrzw8mNVKH0WzlG3/fwb1vOAqMbToy8enwRY1dXPvMdp75vKzf/TabnYM1HRNW4G5eYigFtR1Ybb6Vxlvk7igydQMXABnRQR7JuHh+WwUpkYHkZkW76xuMRlWrkQidlqBx1gtxBQvePeBouVndZqSnz8r20hZHjYNPinnZWZjRk8wWG/ruXvftCv3gJ+4v3rqMj75/Lj/Ny+mX/ZEQFkCETsuBSTiRH6u9VW2c//gWbnlh1zCPa8dstQ37nTAnIZSDE7i9hl4Lz3xe5p4u5K0pIeMVrtOSEBYwqcVMfY3dbqeq1UhyxOguHqQ4Lza4siaP1ncyY1pwv2BVvLNDl6/UudhWomdbqd7bwxBCCOGDJHAhhlWhN5AUEYha5f3D5Stz4rj6rCTqO3rImxvP0rQIdpS3TOhrbi3Rk/fEF2wrbeHjo/2DJBUtBrp6LBMWuJibGIbBbKXMAyfXnnSsoQu1UkF61Kk7ivi6zJggSpu6xzW/22qzc6C6nfNnxpI9LZjS5u5RB5qqW0fWUWQ4riySPqsdf40Su92RYl/eYuDW3HTCAjUUTUDxzvveOMCShzdxx4t7eHlnFRab3T1VYiQUCsfcfV/NuCht7ua6Z3bQ1WPhcF2nuxPGYD452ohGpSB3mCkgcxJCqW03TVjthjf31vDwe0f55btH8NcoyZ7CQcY5CaEcruv09jC8prmrF1OfddQZF67pi5UtBux2O4UNXWTHhfR7jGt6mq8UvX5owxF++NoBbD4WrBdCCOF93j8TFT5vTmIoeXPivD0MAKKD/fjdV+fy6Q9X8cQ1CzhnuuMK96lOJMbrb5+XEanTsmpGNLUnpdMecJ5ozU0aWcG00ZrnTKH3tSvRxxq6SI/WTVrNhImSEROEwWx1p1KPRVWrkV6LjRnTgt01JqpH2SGjrLmbtFGelAzFlXVxxUJHHZqNB+ux2yEnLoSUiECqPNRFxWVbiZ7/7q9jSVoE+cV6fvHOYYBRTyOamxhGSVM3hl6LR8fnCV+WtmDqs/LbK+YAsLO8hV6LddBpRpuONrI0LZJgf80p15ke7XifKjz8frjsKG8lKkjLnIRQ1syM9YnA81jNTgihXG+gs2dyurD4GlcL8ORRfkfEhvjhr1FS0WKkobOHDlPfgABWWKCW2BA/Chu830a5z2qjtLmb+o4edvpwK3AhhBDeMXV/yYhJc+fqzBEVUfOGpWmOwm07Jyjror7DRH5xM19blMjs+FAaOnuwWG3u5QeqOwjQqMiMnpjMg/ToIHRalc9diT7W2DWl61u4uN638dS5OOb8wT89NpgsZ9BgNHUuunst1HX0uOtTjJcr0+Gms1NRKGDDQce0kZz4EJIjdVS2eu7Kap/Vxs/fOUxyRCDP37yE3T9dy+vfXs5frl3AzLjRbc+8xFBszgwRX1PVakSrVnLxvHj8NUq2l7Xy8MajrP3DFh569wg9fY66IRV6A6XNBtbOjBl2na6r55UTcKXbbrezo6yVlZlRvHv3Sv567UKPv8ZkmuUsZnrEB48NT/vnlxV849kdrH50M997ZR9H6zvdLZtTRpmVpVA4ikZXthjcgYnsaSEDHjdjWgiF9d4PXFToDfRZHZkWb++v8/JohBBC+BrpKiKmtLmJYfiplewob+XC2Z7PCnlrby12O1y5KJFtpS1YbXYaOnvQqpUU1nexp7KN2QkhE3Y1U6VUMDsh1KcyLrp7LdS0mfj64iRvD2XcMmIcqdSlzd2cMz16TOtw1fvIig1yTxEpauzi/BF2gil1BjlOLmY5VjcsTyEtKpDpscEkhgdQ3WoiLFBDXKg/KRGBvHeonj6rDY0Hjtm9lW2UNHXz52sWuIvTurpAjNZc53Sr13b1L23wAAAgAElEQVRX02HqY+3MGBQK3ygcWdliIDkiEH+NikUp4Xxa2ERjZw9JEQE8t7WcF3dUMj8pDD/nPlgzc/j33pWi7+kMGHDUNNB397I03TsdQzxtdrwjcFFQ28Gy02SbBtNmMPPztw+TEun4/H5ytImKFiPnZEWhVEBi+OizslIiAylp6nYHfQarSzRzWjD/KG1xdx/xlmONruBKMO8dqufBS2ZN+aw+IYQQniN/EcSUplUrWZjsOJH4vKi5XzZEZ08fT20upalr4DSAnj4rJvOpuyu4OpcsSY0gJVJHgrOIWW2biV9vPMoNz+3kUO3EFeZ0mZcUxtG6Tv62pXRSCpEOp7jxeIbBVBcd5EeIv3p8GReNXSRHBBKoVRPsrxl1p5JiDwcuUqN0XL88FXAUHwXHNBGFQkFyZCBWm33AlKexchWXPDtj/CeT0cF+ZETreGNPDbf9czd7KtvGvU5PqWwxuq92L02LdE8P+sdNS3j5tmV8Y1kKpj4rW0v0zEsMHVG9En+NitgQP/c0gPHoMPXxp03F7n22s9yRZr8kbWxBJF8THexHfKg/e6t855iYCK4paz+5MJtnbjiLW3PTOVDTzr7qduJCA8Z0Ep8aqaO61cQru6qYlxhKaMDAKUzZccGYrTZ3Ec+JYLPZh63nUtTYjVIB31s7nQ5Tn9c7hgkhhPAtErgQU95lC+KpbTNxw3M7uf+tQ4AjpfjiJ77gdx8U8tv3Cwc857Z/7ubs337CZ4VNQ663sbOXMr2Bi+ZMA463jattN3GwtoNFKeH8PC+HW3PTJ2CrjluYHI7ZauM37xe66wd4k2tqxFTvKAKOVOrMmKBxBS6KT5o2kxkTxJG6zhEX/Cxp6kajUow6DXwkMk8IXMAJxfo8cLIMjhovCWEBRAX5eWR9b9+1kte+tRwYW1vZieDu6BDpClw4ggFrZ8aQGRPE8oxIfpaXwzt3reTgL9bxyu3LR7zulAjduDMujtR1kvdEPo9vKuLKp7Zxw3M7+c++WqKC/EiP8n4La09ZmRVFfrG+X3D6dFPf4QgoTgt1dPBanR2N3Q75xfpRF+Z0SY3SYbbaqG418b210wd9zIxYx/fD0VPUuejq6WPfOAJH7x6sY8mvPzllcKSooYvUSB1rZsZw68o0Uj1U90cIIcTpQQIXYsq7enEyB3+5jhuXp/D6nhreO1TP9X/fQU+flfNzYvnvvtp+XTm2l7WQX6zHZoebn981ZPDC9QPLdSXc1TauuKmbcr2B3Kwovrkyzf0jc6Ksy4nlpduW8u1zMya0C8FIHWvsIkCjImkMacu+KDNm7C1RzRYbZc0GZkw7ni2xLieWY41dvLW3dkTrKGnqIi1KNyEp2hnOYzcn3nFi4jr5qfJQXYWDNR3MTfRcYdogPzVnpYTjp1b6TCcdfbcZo9nqDiwtTAnnmiVJ3Hdh9oDH6vzUBGhVI153cmTguLs5/PztAkxmGy/eupT7L8qmoLaDHeWtLEkL95mpNp6wakYMXT0W9lb5Vr0fT3JlXMSFOv7WzI4PJSpICzDmwIXrefOTwlg1Y/DpcBkxOtRKBccahq4h8o+tFVz+5Da2lYytVemeyjbMFhv/2Fo+5GOKnEFgjUrJT/NyPFb3RwghxOlBAhfitBCoVfOjC7OJCvLjjhf3YrbYeOm2Zfz68jlo1UoefPcIb+ypYU9lK3/cVER0sB9bfrSK0AAN7xfUD7pOV9E811Vqf42KqCA/Pj3a5O7SMBmUSgVnZ0S50/GP1E9egboKvWFAhwzHj8sglMrT46QoIzoIfbd5TAGhcr0Bi83eL+PiuqUpLE4N58F3D9PYOXy3kpKm7lG1Dh2NFRlR5MSFcHaGozVnTLCjy0ClB+oqtBvNVLUa3bUpPEWpVJAWpZvQtPXRcH0PpDi/BzQqJb+5Yq5HpkqlRATS1NU77LS1odhsdo7Ud5I3N44VmVF869wM8u9bza8vn8MPzvfNgspjtSIzCpVSweZjQ2fJmS02vixtGVd7Y29q6OhBpVQQHezIYFIqFZw73VHoNTlibNkzs+JDmRUfwgPrZw4ZyPJTq8iIDjplgU5XjYz73jw4ps4/ruKgr++uocM4sDtMT5+VihYD00+DTD4hhBATQwIX4rQR5KfmgfXZaNVK/nTNfDKig4gO9uPmFWlsKWrm3tcPcOVTX7K9rJVvn5tBWKCWxakR7vngHx5u4HDd8SKY5S0GNCqFO9MCICE8wF1AzHUVe7LMdAZKJrOy/vdf28+3/73H/W+rzc7R+tOjo4iLK6NmLFkXxwap96FUKnjkq/Potdj4n7cOnfIkqqfPSlWr0Z0Z4WnJkYG8d0+uOytIoVCQHBHokakirvoW8zyYceGSFqWjrNlXAhdja0U5Eq51Vo3x/ahuM2I0W/u1uNT5qbl2abLHaqb4itAADYuSw9l8bPC6B3XtJq7625dc88x2vhhjVoC31Xf0EBvsh+qEoPDqbEeWxFgzLkIDNGz8bu6wRXNnTAs+ZUvUoqYu0qN01Lab+OtnJaMag91up6ixi4XJYZj6rLy4s3LAY0qbu7HZYcZp9LdFCCGEZ0lXEXFauXxBIhfNjnN3OAD40boZXLc0GYvVcXWyXG/guqXJACxLj2DT0UYKGzq5+6V9LM+I5IVvLgGgUm8kKSKw34/IxLAADlS3E+KvdhfrnCzRwX7EBPtNWsaF3W6nuLGb7l4LVS2OOf6fFjbRajBzXvbw7R6nCtcJXklTN4tSRlfM8HBtBxqVgvTo/ldD06J0/OiCGfzvxqM8/XkZTV29BGhU3LQilaggPwpqO3hxRyV+ahU2O+42qpMh2QN1FQB3i97ZExC4SI/W8fGRRo91PxmPylYjCsXxGjee5MriqGwxjKlmzFHnFfLsScr+8rZzZ0Tz+w+P0dTZQ0xI/yl6t/9rN+XOYNfBmg5ys8bWJcibGjpNA6YersuZxs/ycib8O3dxajjvHKhjR1nLgG40PX1WKvQG7jovi60lenaPsnBuU1cv7cY+LpkXj85PzXNflHPj8lR0fsd/ghY3OgLH02NPr4CbEEIIz5HAhTjtnBi0AMcVcFcbudSTitW5qu4/8J8CzFYb+6vbsdnsKJUKKloMpEX2f7zr5CUnPsQr88dz4kM4UteJxWpjX3U7fRYbFS1GKloMpEfpWJ0dQ2yIZ2puNHf10u1MCf7gcD23n5PBP7+sYFqI/4hbfU4FieGBaNVKihpHn3Gxr6qdWfGh+KkH1jW4eUUaHxQ08Jv3C9GoFFhtdv5vSykBGhVdvRb81Ep6LY5Cg5N5dTwlMpCtJXrsdvu4juEDNR2kR+kI8R/YpWC80qKCsNjsVLcaSY/27olMVYuB+NCAQd/j8XLVzRgu40Lf3cs3nt3BH78+n+xpx4MUxxq6UCjOnJM913S5vVVt/dpfd/daOFzXyffXTueNPTX9MuemkvqOHmZO6x+E0qqV3LIybcJf+2tnJfHEpyU89lERr35rWb/vhhOzIRo7evikcHTdrQrdBZ1DmJMYxpVPbeP5bRXcuTrT/ZiKFgMKxcRkNgkhhDg9SOBCnNFy4kII8lOzp7INpcLRVrBMbyAjWkdFi8FdG8AlwRm4mOmlK5w5cSF8Uazn7pf38X5Bg/t+tVKBxWYnLtSfz+5dNSB4MxJ2u53mrl5QONqEljlrDGhVSt4vaGDtzFjyi/X84PzpE1JI0ltUSgXzE8PcU4ZGqs9q42BtO9cuSRlyvX++ZgH/2VfLlQsTMZotvLGnBlOflYSwAK5anERxYzeHatr7pfpPtNTIQEx9Vho7e8dVWPZgTTvL08ffBnUwac4AY7ne4JXARYXewDP5ZVS2GCnXG0iegI4vAGGBGoL91cPWHPmytIXChi6+KNb3C1wUNnSS4mzFeyaYGReCSqngcF1nv8BFYX0ndjvMig/haH3IpE6n8xS73U5DRw+rZ3gnm81fo+Lu8zL52duH2VLUzKoTxlHknhIXRG27kVd3m+kw9hEaeOqg5Wu7q9lZ3urOKMueFky4Tst52TH8bUsp31iW4m7PWtViJC7Ef0IChEIIIU4PZ8avHSGGoFYpWZQSzpaiZm5Ynsrz2yrYW9VGsL+anj4baVH9T1hc00MmqzDnyXLiQ7DY7Lxf0MDt56SzekYM8WH+JIUH8klhE7f9czev7qrmxrNTBzy3oaOHVoN5yNocj3x4jKc2lwJw/0XZhDh/UF65KIGXd1Zz4z92olEp+PqSpAnbPm9ZmRXF45uKaDOYCddpR/Sco/Wd9PTZWJgydHHK+LCAflcVT+5EsSglnEUp4WMb9BilRTlOIsr1hjEHLho7e2js7PV4YU6XDOfUm7JmA0F+LcxLChtTMG4sGjt7uOhP+VjtdqKD/KhtNw3ZjWG8FAoFM+NC2FLUfMppMa5pOWUnFSw91tDVL5BxuvPXqMiMDqKgtn9GxWFnoGJWfChH6zt5v6CBrp4+gicgG2iidJosGM1W4ia4S9WpXL04mafzy3jo3SMsS490f+aKGh0tm1OjdGS0OmsC6btZmHzq767nt1ZwpL6TuFB/YoL93N+tPzh/OnlPfMErO6v41rkZgCPrKGmCAoRCCCFOD6fPZVMhxmhtTizhgRq+v3Y6If5q9lW1uzsapJw0VWRxWgRXLkxkzUzvTJWYFe+oJ7A0LYIfX5jN8oxIUiJ1KJUK1s6MYUlqBE9tLqXXMrBLwa82HuH6v+/AZhu8WOTnRc3MjAshPUrHp4VNlDV3o1UruS03Ha1aSXSQH8/euJiYYO/9sJ4oKzKjsNthW2nLiJ+zz9mWccEwP959TVr08WyGsTpQ7dj2eUmer28BEBaoJTxQwzP5ZVz99Hb+/sXQLRQ9bXtZC6Y+K6/evozP71vNv29ZyvfWTp+w1/vWOelUtRp5Y0/NkI85UO04US9tOj6dyWS2Ut5iIDvuzCpmOCshhIKTMiqO1HUSodMSG+Ln/o48eooOGb6ovtMEHG+F6g1atZJfXz6HMr2BxzcVue8vaugiIzoIjUpJhjMD6sRjcTD67l53Pab6jp5+NVxmJ4SyJC2Cf++oxOr8e1TZahxzAVIhhBBnBglciDPeN5Yms/1/1hAaqGF+cjj7qtrcLRDTTqqJEeKv4bGr5hExwqvynpYWpePxq+fx5HUL+xUNBcfV23vWZtHQ2cNLO6qw2uxc8/R2HvmgEID9Ve20GMyU6Qf+4DT0Wjha38n5ObGsmRnDvup2Chu6SIvUkR4dxMFfrOOtO1Zw7vSpV/BuJOYlhhLsr+aLksE7Fgxmb1UbsSF+xHvxCulYONKxlZQPchyM1MGaDlRKBTlxExO4AEiPDqKpqxdwBBMmy57KNnRaFXMTw1ApFazMinK3p5wI52XHsCA5jD9/UkxP38CAo8Vq45Azw6D0hE4rRY1d2O2cURkXALPjQ2nu6qXphFbDh+s7mOWsOzTLmVE21epc1Hc4tmc807c8ITcrmq8vTuKZz8s45qxNcazxeCepxPAAtCplv2NxMFudnV1+dIGjLe/J0ytvWJ5CdauJLUVNGM0Wmrt6B1woEEIIIU4kgQtxxlMoFO55tQuSwjjW2MWWomY0KoVX03aHcvmCRCKDBj+ROjsjkpWZUTz+cRFPflbCl2UtvL2/Dn13L7Xtjit6uysGVoTfX92Oze6YurAsPRKzxcbWEr27W8Zkpel7i1qlZHl6JPnF+lO2Lz3Rvqp2FiaHe6VI63golQrSonTjyrg4WNvB9NhgArQTd1xcviCBq89K4uqzkthX1e6+MjvRdle0sSA5fEBgcKIoFAq+v3Y69R09fHK0acDykuZuTH2Olqf67l46jH0AHHBOH/HWtDVvmZ3gCJa5pof0WW0UNXS790N0sB9RQVr38qmiwRm48IW/OT+5KBt/jYr/21JKXbuJmjaTuwCsWqUkNSpw2PbRXxTrCQ3Q8O1zM/jLtQv45or+BUYvmDWNmGA//vllpbs47UTVkhFCCHF6kMCFECdYlh6J3Q7vHWogKyZ4yhWhVCgU/OLiHIxmK499XISfWkltu4n3D9W7HzNYK7s9lW0oFDA/KYyzUiNQKsBmH5hxcjpbmRVFTZuJ2b/4kHtfPzBguaHXwhPOq+JNXT1UtRpZkDwxNR4mWlqUbkC9hJGy2+0crGlnbsLEZVsAfGNZCr/76lyWZUTQ3WuhsGHiT0Rdr7NwkuuOnJ0RSZCfmm2l+gHLDjqniVyxMAFw1BYA+LSwidTIQJIivDe1wBtmOqfGuOpclDR1Y7ba3LV7FAoFOfGh7K1sG3JanC+q7+hBqWBCs3tGKixQy7VLknnnQB13vrSXAI2KS+YluJdnRAedMnBht9vJL9ZzdkYkKqWCvLnxAzJJNColXzsrkc+Lmt1Tz2SqiBBCiFOZWmdlQkywZekRvH9PLm/dcTb/vGWJt4czJlmxwXxzZRoalYJHvjoXgGe/KEehgBWZkeyuGNg9Y09lG9NjggkN0BAaoHGfBJxJgYvLFiRwx6oMZkwL5t0DdQPqhPx3fy2PfVzEh4cb2FHm2IdL0iamq8ZES4vSUdVixGK1jfq51a0m2o19zJ2g+hYnOyvF0bJ4zyABN0874Mw8OmuSAxdqlZIlaRF8edKUmD6rje3lLQT7qzkv21FXp6zZgNFsYVtpC6uzY6Zcxs94BftrSIvSUeCcCnLEXZjzeObJpfPiKdMbePdgnVfGOBb17Saig/2GLNA62W7JTUOpcGSW3f+V7H5tSjOig6hqMdI3yPfHfW8cYPHDn9DQ2UNu1qmnFq7LmYbNDi9sqwQk40IIIcSpSVcRIU7gqvI/1d1/UTa35aYTqdPy4LtHqGwxkhUTxLnTo/n1e4WUNHWzu6KVwoYuooK07K1qI29uvPv5y9IiKajt9EorSm8J8ddw34XZfFBQz7f/vZeC2g4WOU+aAT4rdNS/yC/W469RotOqmD1EhxZflxalw2KzU9NmInWUwal91Y4AwrwJ6ihyssTwAGJD/NhV0cYNy1Mn9LXcmUdeyKRZnh7Jp4VNNHT08NKOSj471syxxi7MFhvnTo8mJTIQjUpBaXM320paMFtsrMn2TpFgb5sVH8J+51X6w3Wd+GuU7m454Jhm9Pcvynnkg2OYzFYqWoz84PzpaNW+ERQYzOG6TrJifKfQalxoAHefl0VFi4FvLO3f8jk92vH9sb2spV9wot1o5o09NSxIDufieXGsnxt38mr7mZMQSkywH0fqOwnxVxMW6J3aUUIIIaYGCVwIcRpSKBTulOOlaRG8X9DA3ETHNBCAC//4ORabnUCtCqPZkVlw4lXmyxcmcKyxy52WfSZx7aOd5W3uwEWvxepO488vbibYX8Oi1IgpN5XIJf2EziKjDVx8crSJCJ2W7GmTc2woFArOSo1gV3krPX3WCa23squilRmxwYR4oY3m8gxH9s6P3zzIlqJmFqeGc9PZqcyKD2FlZhQalZKUSB2lTd20G/vQaVUsSYsYZq2np9kJoWw4WE+70czhug6yp4X0q0miVCr46fqZXPvsDn7y1iEAjGYLD10621tDPiWj2cKxxi7uWJXh7aH08901WYPef3ZGFFFBWq7/+05uOjuVX14yC4AtRc3Y7PDT9TNH1G1JqVSwZmYsL++sksKcQgghhiWBCyFOc8vSI3m/oIF5SaHMjg8lPUpHcmQg966bQU5cCLXtJraXtXDxvOMZF7PiQ/nXLUu9OGrviQryIz1ax66KVr6D40RiV3kbRrOVC2bF8uHhRho7e7l8QcIwa/JdrqvTZXoDq0fxvF6LlU8Lm1g/J25SgzbrcmLZeLCe1Y9u5vGr57Ms3fNTdLp7Lewoa+XGs1OGf/AEyIkLITRAw5aiZhalhPPq7ctRnlQgNCNax9aSFmx2O+dkRft0BsFEck0LKajt5Eh9J5ec8N3lcnZmFP/3jYXEhvjzfkEDT39exsLkcC7zwc/toZoOrDb7lKmZMy3Un8/uXcWv3yvk+W0VLEuP5MLZ0/i0sIlInXZU2VhrZ8bw8s6qflNRhBBCiMFI4EKI09z5ObG8ubeG1TNi0KqVfHrvqn7LkyICSZK5xf0sSY3gvUP12Gx2lEoFm481oVUpue/CbD483Ag46qFMVeGBjlomL++soqHDhFatZMa0EC6eG3fKmglbS/R091q4cM60SRwtXDo/gZhgf37w2n7+uKmIV25f7vHXyC9qxmy1cX7O5G6bi1KpYFl6BJ8cbeLhy2cPCFqAoyZAabOBrJgg7lyd6YVR+oZZ8Y76Kh8ebqCrx+KuyXOyC2c7pirMSQhla4mepz8v88nAxT7ntJf5SZNbW2U8gv01PHTpLPZXt/PztwtYnBrO5mPNrJ0ZO+ixO5QVmVGEB2r61SgRQgghBiOBCyFOc/FhAbxz10pvD2NKWZwawSu7qnmvoJ5Wg5k39tawND2CjOggsmKCqG4zMidhalwdHYxCoeC23DTe3l/HP7+sxGKzY7XZ2Vqs56HLZrnbA5/sg4IGgv3UnJ0x+UVJl2dEsi4nltf31GCx2jye8fHx0UbCAzUs9OJV7we+ksONy1PJnjb4SdyVixK5clHiJI/K90TotCSEBfD2/lrgeCBjKGqVkvVz43jkg2M0dfYQE+L9lqMn2lfVRkpkIBG6qVXjQaNS8rsr53D5k9s49/eb6e61sGZmzKjW4a9R8dm9q9D5yc9RIYQQpyZ/KYQQ4iRL0yNQKOCul/YBsCglnJ+uzwHg7jVZ1Lebpnya/l3nZXHXeY457Dabncc3FfHEpyX0WW08dtW8fpkXz31Rzh8+LsJotnDxvPghAxsTbWFKOC98Wcmxxq5hT1ZHw2K18WlhE+dlx3i1bklyZKCkzI9QTnwIHx9pRKmAGbHD11tZNT2GRz44xuaiZq46K2kSRjgydrudfVXtXgkGesLcxDBe//ZyHv+4iOLGbnKzoka9DinKKYQQYiQkcCGEECdJDA/k7TtX0NJtJkKnZW5iqPtEfrD59FOdUqngh+tmoFIq+OOmYpalR3LV4uMnd//dX0tkkJZrcpL4+pJkr41zgTOVfl9Vu0cDF3sq22g39nH+zDOzS8dUNDs+lI+PNJIRHUSAdvhA2sy4YGJD/Nh8rMmnAhf1HT00dfUyP2nqZnAtTA4/Y2siCSGEmDxT+5KhEEJMkLmJYazOjmFeUtgp6z6cTu4+L4uVmVH8/J0C2gxmADp7+iio7eCy+Qk8sD6HDC+2yE2KCHC37/WkTUcb0aqU5E6PHv7BwifMTnBMpxmqvsXJFAoFq6bHkF+sx2K1TeTQ+ukw9vH4x0WYnN2bTvbR4QYAlk5AwVkhhBDidCKBCyGEEAColAruvWAGPX02thQ1A7C7ohWbnQnp5DFaCoWCBcnh7Ktq99g67XY7Hx9pZHlGJEEyz37KmJMQikqpGFWmwursaLp6LGQ+8D6X/uWLSQlgvPBlBX/6pJj/7KsdsMxut/Ov7ZXMTwpjZpwUpxRCCCFORQIXQggh3OYmhBIVpOXTwiYAtpe1olUrfaZV44LkMMr1Bv6zr4ZPjjayv7qddw7U8fruaux2+6jXV9psoKLFyNocmSYylcSE+PPuXSu5dunIpy6tmRnL/Rdlc82SZA7UdAwaTPAkm83Oq7uqAXh9T/WA5dtKWyhtNnD9Mu+04BVCCCGmErm8JIQQwk2pVLBqRgwfHW7AYrWxvayF+Ulh+Gu8U5DzZGdnRAHH+P6rBwYsmzEtmLmJowuwbDrqaG+7dpTdEIT3jXSaiItGpeRb52Zgt9s5XNfBHzcVs7+6nS1FzfznjhVEB/t5dHxbS/XUtptYmBzG3qp2Spq6yIwJpqC2g42H6vmssInwQA3r58Z59HWFEEKI05EELoQQQvSzJjuGN/bUsPFQPQW1He7uI75gflIY+fetxtRnxWi2ou/qJTRQw7XPbGfDwfoRBS7sdjtflrawvbyVDQfqmJ0QQlxowCSMXvgChULBjy6YwfV/38lLO6uw2+GVnVXcvcazx/kru6oJC9TwxLULOeeRz3how1H81Uo+OtKIRqUgKsiP762d7jNBQSGEEMKXSeBCCCFEPyuzotCoFNzzyn40KgUXzPKtaRRJEQNbhp6TFc2GA3X85MJslMqhi6m2dPfy7X/vYVeFo8CnQgG/vHjWhI1V+KaVmVE8fPlssqeF8MdNRby0s4rvrMrwWDvccr2BDwoa+OaKVBLCArhgVizvHWogJtiPu8/L5LZz0gnx13jktYQQQogzgQQuhBBC9BPsr+HG5ak0dvXy/bVZpHuxk8hI5c2L45PCJvZVt7EoJWLQx1htdr736n4O1HTwq0tn8bWzkuRq9xlKoVBw3VJHbYnrl6Vw+7/28Pb+OvLmxWG22NColKc8Ngy9Fu56aS/7q9vRqpU8ed3CfsfdHz4uQqtScvs5GQD88eoFPHyZhXCddmI3TAghhDhNSeBCCCHEAD/Ny/H2EEZl7cxYtGolz3xezuxrQvFT9z/p7LPa+PV7R8kv1vPbK+bw9SUjL+ooTm9rZsaSGB7AD18/wA9fd9ROCdSquOqsJG5ZmTYgw8fmDIBtKWrm6sVJbCtt4ZYXdvO3bywiJEDD4bpO3j1Qx52rM9x1M7RqJVq1BC2EEEKIsVKMpQr7FHPab+BEWLVqFQCbN2/26jiEEGKk/rSpmMc3FTE9NohFKeFE6LSkRQXR0t3Lf/bVUtjQxQ3LU3jwklkoFENPJxFnnrp2E58XNaPv7kWrVnK0vot3D9Rhs9tZMzOWBclhZMUEExao4cnPSvjsWDO/vDiHm1akUdli4MqntqHvNrvXFxfqzwf3nENooEwHEUIIIYYxoh9lErgQg5LAhRBiKvq0sJHfvX+MFoOZdqMZi83xJyAtSsf9F2WzbtY0L49QTBX1HSae31bBO/vrqO/ocd8f7KfmnrVZ3LIyzR0Aq+8wsaeyDaVCQVJ4IFmxQTINSQghhBgZCVw4nfYbOBFWrVpFSUkJmZmZ3h6KEGj/w90AACAASURBVEKMiV2hxOIXirLPhMraM/wThBiCTaWlLyASi18I/h2VqCxyPAkhhBCesHnz5hEFLqTGhRBCiNOSwm5D09Pm7WGI04DSasavux6/7npvD0UIIYQ4I0ngQgwpMzNTpooIIYQQQgghhPAqzzQsF0IIIYQQQgghhJgAErgQQgghhBBCCCGEz5LAhRBCCCGEEEIIIXyWBC6EEEIIIYQQQgjhs6Q4pzi1mnlga8bRXtfO8Ta7g90ey/KJWKdnljd+ZR62VhUx7xegCu875XMuPTqXVosKBQrs2FE4lw92246dd2YWEK7uG+L1Rz/m4V5/sPvennmIcLV53Nvk2BbzgOe7bl96dJ57Pf1fc7htHt1+uPToPNos6lNu82D7ZHRjGrhNw+3nke6niT6eh34ffPcz6Fp+4ns72H4cyXvvjW321Gdo7O/tcPvx1N9rk3U8DrZPPPVdORHHxsnrdK3rxPfxxPf+5G0azXHgyf00ljGN/X3wwN8UZTQkHkAIIYQACVyI4dianTfsJ/1/qNtjWT4R6xz/clurCgBVuHnY57RaVM5b9n7/H+q248ep58Y8ktc/+b7jYxjfNg1cT//bJ67n1I8d335wvE7/sQ73PoxtTAzYNyN5zeH200Qfz6d+H3zzM+i6feJ7O9h+HMl7741t9tRnaHzv7fHbg+/H4dY/8cfj8aWe/66ciGNjsHX2H+vA9/5Urz/Y8108uZ/GMqbxvQ/j/Jvi/v0hhBBCyFQRIYQQQgghhBBC+DAJXAghhBBCCCGEEMJnSeBCCCGEEEIIIYQQPksCF0IIIYQQQgghhPBZErgQQgghhBBCCCGEz5LAhRBCCCGEEEIIIXyWBC6EEEIIIYQQQgjhsyRwIYQQQgghhBBCCJ8lgQshhBBCCCGEEEL4LAlcCCGEEEIIIYQQwmedcYGLfS0HueKTG93/vn7LHexrOTjq9RxoLeDazd/y5NCEEEIIIYQQQghxErWnVpS7MW8l8AgwC7ACR4Hv5a/fsCt3Y54W+A1wNRAG6IH/5q/f8L0h1mUHjIAd6ABeBX6Uv36D1VPjdfnXuU+O6HG5G/N4edXTJOriAZgXMZuXVv3N08MRQgghhBBCCCHECTyScZG7MS8E2AA8AUQACcCDQK/zIfcDZwFLgGBgFbB3mNXOy1+/IQhYA1wL3DbI63os8CKEEEIIIYQQQgjf46kT/+kA+es3vOz8twn46ITli4H/5K/fUOf8d4Xzv2Hlr99QmLsxLx+YDZC7Ma8CeAq4DpiRuzFPB8TgCJqcA3QDj+ev3/BngF5rL48WPMkXDduJ9I/gK4lr+63/a59+kx/P/S5nRc3HarfyYumbbKz+iLbeDpJ08fz6rJ/yq/2PAnBz/t0oUPDjud8lwi+MX+1/jLfWvODYoK5qHiv4KyWd5UT5R/Kt7BtZGbsUgIcPPE6Ayp96YyMHWg+TGpzEL+b/iARd3Eh2gRBCCCGEEEIIccbyVI2LIsCauzHvhdyNeRflbswLP2n5duAHuRvz7sjdmDcnd2OeYqQrzt2YlwPkAvtOuPsaYD2OaSc24F3gAI5MjzXA93I35l0A8I/il6kz1PPq6md5bMlDfFDzyZCv9WrZf/mkbgu/X/xLPrzgNe6fdw/+Kj/+svx3APwj9wk+uvAN1sSf0+95FpuFn+x+iMXRC3nn/H/zvVnf4qF9j1LVXeN+zCd1n3Pz9Gt4b90rJAbG8fSxf450FwghhBBCCCGEEGcsjwQu8tdv6ARW4qhJ8QzQnLsx753cjXmxzof8BvgdjiyJ3UBt7sa8Gwdd2XF7czfmteEISjwL/OOEZX/OX7+hOn/9BhOObI7o/PUbHspfv8Gcv35DmXMMXwf4tC6fGzKvJkQbTGxANF9Nu2TIF9xQ/RG3Tr+e5KBEFAoFmSHphGpDht3+w+2FmKwmvpHxVTRKDYui5nF27GI21W1xPyZ32nJywmagVqo4P2EVJZ3lw65XCCGEEEIIIYQ403msRkT++g1HgZsAcjfmZQP/Bv4IXOMsqvlX4K+5G/MCgG8Cz+VuzNvpfN5gFuav31AyxLLqE26nAPG5G/PaT7hPBeQDtPS2EhMQ5V4QGxA95DY0mfQk6KYNuXwo+p5WYvyjUSqOx4GmBcTQ3NPi/nek3/EkFH+VHyaradSvI4QQQgghhBBCnGkmpLilsy7F88CAfqHOLIm/5m7MexDIwdF9ZLTsJ9yuBsrz12/IGuyBkX4RNJn0pAWnANBoah5ypTEBUdQaGkgPTh3VYKL8I2jqacZmt7mDF42mZpKcHUiEEEIIIYQQQggxNh4JXDgzLNYDr+av31CTuzEvCUcdiu3O5d8D9gM7gD4cU0aC6V+3Yqx2Al25G/N+DPwZMAMzgYD89Rt2rY5byb9KXycnfAYmSw9vVmwYckV5Set4tujfpAYnkRgYT2lXBdH+kYRqQ4jwC6PO2OBuh3qinLAZ+Cn9eKn0Tb6efjmH2o6wtXEnz6z8gwc2TwghhBBCCCGEOHN5qjhnF7AU2JG7Mc+AI2BRAPzQudwIPAY0AHrgTuBKZz2KcXFOQ8kD5gPlzvU/C4QC3Dz9GqYFRHPVp7fwg50/44KE1UOu6+r0yzgvbiU/3PFzLvjwKn538M/0Ws0A3Jx1LQ8feJyLPryaT+vy+z1Po9Twu8U/Z3vzHvI+vpbHCp7ip/O/T0pQ0ng3TwghhBBCCCGEOKN5JOMif/2GWuCqUyx/Gnh6FOsbsutI/voNqYPcV4cjw2MAf5U/P53/w373XZtxpfv26+c9576tUqi4Mevr3Jj19QHruSzlK1yW8pV+97laoQKkBafwl+W/HXTMD8z7fr9/L4ic2++5QgghhBBCCCGEGJynMi6EEEIIIYQQQgghPE4CF0IIIYQQQgghhPBZErgQQgghhBBCCCGEz5LAhRBCCCGEEEIIIXyWBC6EEEIIIYQQQgjhsyRwIYQQQgghhBBCCJ8lgQshhBBCCCGEEEL4LAlcCCGEEEIIIYQQwmdJ4EIIIYQQQgghhBA+SwIXQgghhBBCCCGE8FkSuBBCCCGEEEIIIYTPksCFEEIIIYQQQgghfJYELoQQQgghhBBCCOGzJHAhhBBCCCGEEEIInyWBCyGEEEIIIYQQQvgsCVwIIYQQQgghhBDCZ0ngQgghhBBCCCGEED5LAhfi1JTRzhuKE/4/1O2xLJ+IdXpmuTLCCoC1TTvscyLUVucthfv/Q90GaLOcvM7xjXm41x/sPscYxr9N/dczcF0nrmfox45/P0SorcNu82DLRzemgds00tccbj9N9PE89PvgvTGNdPmJ7+1g+3Ek7703ttlTn6Gxv7fD7UfPfgY98Rny9HflRBwbJ69zsPfRU98RntxPYxnT2N+HgfeN+vPg/v0hhBBCgMJut3t7DBPttN/AibBq1SoANm/e7NVxCCGEEEIIIYQ4bSmGf4hkXAghhBBCCCGEEMKHSeBCCCGEEEIIIYQQPksCF0IIIYQQQgghhPBZErgQQgghhBBCCCGEz1J7ewDCt0179FEaDQYqlB8STQ8vvvQTLglchj8agt+vQWm+EWztPPpKMwaThXuWv8Xr9/ph6rDTUXc9IXF/QaEIJWDVz0DTRWNCJXeteBWdJowvF91In6aNP//PR9x6/zUEBrfQ7v8yF2zV4dcHz99jwtRh52LrC9y75sd0aIL4IuG/VF37DDEBRt5JeJZeVQgXl7Tzl+U3YNC3MaPxHb4zdyftjb00bl1KTKSGR1fexBVPFxIQFkPMtA/5xzUWjG1w62tWAsOcG+p/Hyg6afzKPGwPvwwhYcRM+xCVspfGK/+Nrc0Edjsxe36AKkrHO+o+qs7qxKa3c+trVrpu+Te2ViMRT30HZUgg76/QcCj5UiyNrVw/bR0/2fosHZEhPP/sFYQa27ih5m/c+KuvERjcQq7qDV77yQOYOjtAoQC7ndA//IllB9ei6dMSwRc88dVLMbS2srQyCE00tPu/zOKt69D0aQnecT7KvlbAzs23vkV7YDjPP3sF09beisJfR19DENgUtNzxf4T/9gaUIYH8aft2vnPF39EFGHn0rGYMzRburXmfly+xY9TbuHVHBG89cjemzg6+ceeDBAQG8bUnM3lsRyihfUpumdtF9msr0Bj1cJ8SAm1c/691xFzditLfSsAlP0IR9iAoOjG+Ggs9CgIu+RFXPTePNoOKv16ZQWb2IlSqZvIjjZiVVv78Px/x/M9UhAfbeXZZK0a9jYv/vJZ7P66mo8fKPb++gIIXajAbrVy/vJEATQwA797zMT0dZjquvZ6d392JOTCaJU8/jdpoZOmdT5Fb+H9o+0JRLwnAsq8H+o7X6/3T9u0kfncpKp2WpV8s4YM7ttDTYXYfG4+uvAnDNzsg0MaOuq28+Bs14cF2aLwZbO30VTzFn7YewWA2c+9lc9D5q3l05U3c+vTf0YWFYXwwk+AnvoIytKX/8frmDRh62lh6ZxDnhbyBVhHGv398J6bODi4peBtb7f+CtZN/3biAza1fxWz158LPy9H2Wrl1RwRdJWdh69NwbFEGGQe3o+6L5uM3l9Pbo+dtxYtsiv+MXmUPy+bvZ83NH6Bp6+Herf9EFxnqPh4c2/9VDOZWdt9eTM8jduxdNl6/s4SZHx2gsaePZfP3o1b3cdva71Kdcg2WxlbyX1yHOVSLHTt+7z8IPUHc8+sLCAx2HIPt/i/z9KZ/YTQbuOQnN+HXGcDFf17L699MwdTayPVvNfKjTzrp6LGyLGElGqWeaXXphP/+CRQhIVxccztv/L4PkwH3sdf5nfn8P3t3Hp5HVehx/HveN3vabE3TFtpSoOxIUUBAiRYBQRIUFVRQwP0qXhVBUa/igst1QcFdEdzYFBAVEy8KSDWgoCJbWYSyQ2mbtmnSZl/O/WMmL2npKm0ztt/P8+TJbOfMmZnzTpJfZoldxRBh4k9eSa56Gecd2M5b3743FZV5IFB08GcIxRMK55UDv7srxT15IFJ08Ge59ZD3MVjcwXk3v5RVA0X8sPxSdjv4EfIlgyy+7UW8o+ttdMYV/LL8vdSGCv56wGnc8oOFSX+75JXcMPQu+mKyLWVVpVz/y0N54se3M9wzyIf/OZVdr38ri3vLOPu886hYtQpyOd73kX2pqMxT/v6vEConwuPtMDwCwOCiCfzfoSX0l8CD572Goe7lQI4PH/8TKsuqWbzoaOob5pHP9RfOTxe95utce80R9NeV8Islf6FyYWnhsx07u2n41Sm0HjCN/qIcxz31bjof+TMjw/XMufU82geS8/jMV7+fUFbJmxoO5bPzJ1E19Oz/L2576W1UDp9Ijg6+M3An3dRz1OG30XvPmxgZ6oBcjlMajqQ8FHNJ+430DvVBLscHr76aypoaimadzmUXDNHbDdVf/wahqopLzpzEV399LlV9K7nktBupXr4DueEcVx27G72lOS79ytd47IpjGKpdyu4Hv5SJRd8ghCrmXf8YA3XDdJ15BhM/c26hrpe1PE5J/zDnLPwrXUMDnH32d6mo6AVGqPn5ZYTeaohw3PBPKRvpYc5pL2T+m15IQ1lR0o86i599BFiEX3TczVt+9UEqartY/NjdjAzXr3ZOLX9jOxe/8av0LJ/IW79ZTnlVoOjF5YRnlhaOZc+150HfKi67/GP09lTSefIpfKXsXayigqcOPZQdZvQTcpGph/2NxUsHuGjx0fzmSzvQ05XjitcvouTLu8DKIi48Zg49Je1MXbgLv/vUDfRNqOObjadTtbST8qlf44f3NtIz0J58ll80G/I5zvtGE93dy5i6cBdyI3mIkcVXPM5td93HwOTJ/PD1PVR3wLX7Hc+KW84k9k9Y7Wffid+dTUd3nqvet4CL/3AK3X0dfPDQa/jz3Mlp32xjqHuAg9/3PbonXcRIqKGm92Renv8hJaGGnm99FLq7eNN+03jn3NuoLOnnX4ddyNDSKo4b/iltR8ynv3iQvj9/nhWPvpeRoQ7e99H9qKjMM3jdZVw497f0lPQC51Hz8x8QeqrpXHgKI0MdVE6ZwocXLdr8v9hIkv4jecWF1mtxdzcAk+kDoLenkjKKAcjVjsDICgC6e4cAqCyuobcz+cNwZKiDEKqTiopXAjCcG6SyOPmNabC4Iym7so6KicuSMqGG0sGkyGg9ZSM9dBZPAKA/10dDeU8ynK9K5g+P0L00qSvfUMuKxf0ANExK2tm9tIPymuSP3Hyun55k0WdDC4DQlax/eR6qagrLJtN6IH37Tr6+Mll3gJGlsVDPyPKkTbmqimR+CQwtXg5AeSimc1LS1up05SuGqwrbXBJqktACCusJVVUUDyavhMsxSPfypK7i9O1wI6Hm2fmDyxh9ec6KitrCekJZ5ejCSdWd3YX2dQ8MUJnux+729Ng11NKzNPlFvGJSrtCm8opk33d056keTE4ZK/IxCS0AKpIy5T3F5MrS192VVRb2KX2hMK2jOw9AVVkR+Xw7AAO5pEz3yrokFIBCO8qqSunsS+ZXTFzGQE8yPBpaAPR1DiSbWdbBQEWyg4p6km0rruymZDDpg6EkrBZajO6HfGWyH4sHSwp1jfaN7qUdhe0bGJ5UaN9ov2e4iu6BpExlWVGhTGVNWsHKInLVyXFerb/2daTtS44/UNjfZYO1MJzsu96yIgaGywAo6U/3w6QcI4NJ3x4uXkLRYLLN/X3J8eiL1fTnks9rUdEgxR3JcOWk9LM48uyDm7sHkn41UDGZuDLZztqKYRb3DRbKA5SXVhT6c391MXH0ZU19Sd9I+nL6uQ819Awk543SrvJkm6pK6V2+OKmrpqFwTItzSZtzwzlCVbp/RlbQmxQv9L3YWVx4P9To/uxuH0pDC4BISM8Ro+eV4p5coU2heEJh+qqB5DhVhxryJcn2jQwW0xmTY1obKgr1FPpbTzF98dltGd3fwz2D6b4NLO5NjlPFqlXpfh4ptC9UTkympX/opjuK/vStj0loATBCZVl1Wry0cA4a/Sz1LJ9If11SqGZkcLXPNkC+ppz+olxhP44M1wPQPvDseXz0vNCRK1kttAAYLBkkR3peJilbsmwwCS3SbSoPSd/rHeorTBvt7yHfWTh2o8ezpytHVV9y/u8t6yM3nKyztzT5XrOqiqHapB8ULS0ihKTcQPo66pGuztXqGv0cdA2ln9WKbiDZr6GnutBPykaSc0B7WREN6WczdiZtJ1JYrm94iIra9Pyf7q+x59RQNkzP8uT4lVel57KSsPqx7EuOeW9Psm9HyjpYRdKPGoqLCbmkrsVLkzZXNZTS05Vuf9kIrEza11OSnBNzwzn6JtQlyy5NzgshVNEzkMyvnFQN+aR8d/eyQpnRnx/DPYMMTE7OC9XpoevLLyf2p5/XMT/7Rs/JtRXDhfNSZXHNmL6ZtLm4spuR9FyVo6Nw3qI72XcdRYHKkqS/Di0d/Sz30F+cfEZi/4RCPyp8bvtq0tACYFVy/KCwXPfixUiSNMrgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZRZuzssbW5nnAHGBqW1NL/1rmfwb4NHBIW1PLbeuppwb4OnAsUAk8A/yoranlS5uzvZIkSZIkKds22xUXja3Ns4BGIAKvXsv8AJwKLE+/r8/5wARgL6A6rW/B5mqrJEmSJEn6z7A5r7g4FbgVuA04DbhqjfmNwDTgncA3G1ubP9TW1DKwjroOAj7Z1tTSkY4/kH4lFbU27wl8CzgAaAfOaWtquTKdNwn4MTAXeOC02W/kn8vu4bsv+QrP9CzmDTe9g5te9RuKcnkA3v/Xj/HKHQ/nuJlHA9D65B+44uFrWNbfwV41u3P2C97P1IqG0fVy1r6n84tHfsWKgS6O2nEuH9rnPYQQALj2ieu48pFfs6RvGQ3l9Zyz/1nsUT2bpX3LuODeH3Dn8vlU5Mt5w86v4YSdn5PtSJIkSZKkNWzOZ1ycClyWfh3d2No8ZY35pwG/Ba5Mx49bT123Al9obG1+W2Nr825jZzS2NlcC1wOXAw3Am4DvNrY2750u8h2gjyQkeXvrk9dv9Aa0LbqVSxZcxecP+AS/Pepy5tTtw2fv+Mpqy/xlyd+58LDz+cnLvsUfn2njb+3/BOCmZ27mxw9ezif2P5PfH30lXzrwHKqLqxiJI3z07+eya9XO/OqIn3LBIV/gykd/w23tt290uyRJkiRJ2l5tluCisbX5MGAn4Mq2ppbbgYeBk8fMrwBOBC5va2oZBK5m/beLvJ8kAPlv4L7G1uYFja3Nr0rnNQOPtTW1/LitqWWoranlDuCXwImNrc154PXAp9qaWrrbmlrmHzP9iI3ejt888X+8ZdcTmTVxBkW5PKfMfgMPdT3Kop4lhWXesusJTCyewJTyBl40aT8e6noEgN8+8XtO3vX17FWzOyEEplfuwNSKBu5f8RArBrp4224nUZwrZoeKqRw382huXNi20e2SJEmSJGl7tbluFTkN+ENbU8vSdPzydNr56fhrgSHgd+n4ZcANja3Nk9uaWtrXrKytqaUX+CLwxcbW5irgY8BVja3NM0kCkoMbW5tXrLEdlwCT0+EnR2dMLW/gLu7dqI1Y1LuEb953Id+5/+LCtEikvW9Z4XaRutLawrzSfCm9w30ALOlbyg4V055T5+LeJSzrX8arfv/GwrThOMKcur2fs6wkSZIkSVrd8w4uGluby4E3APnG1uZF6eRSoKaxtXlOW1PLXSQhxgTgicbWZoAAFJNclfGN9dXf1tTS1dja/EXg48DOJKHEn9qaWo5aS1vyJAHJDNJnYizufTYXKcuXAdA/3E9RrgKA5f3P5h8NZfWcOvsNvHLHwzdpH4yWXdjzzHOnl9czrXwKVxz+w02uU5IkSZKk7d3muOLieGAYeAEw9mGbVwKnNrY2fx04AngVcPeY+WeQ3C7ynOCisbX5HOA64C6S21k+CKwA/gU8CHypsbX5FODnaZH9gVVtTS33N7Y2XwN8prG1+e3ArMllk5hanjxuo7a0msllk/jD0zfx6p2O4bqnbuTpMWHD8Tu9iov+dSm7Ve3CzhN3YtVgN39fegeHTztsgzvhuJlH8+37LmK/un3YvWpXnu55hqJQxF41u1NeVMFlD1/NCbOOoyhXxOOrnqR/eIC9anbfYL2SJEmSJG3PNkdwcRrw47amlifGTmxsbf428E2gA7izranlD2vM/yZwVmNr875tTS3z16gzkrwZZCbJFRR3A01tTS2r0rKvBL6efuVIAo4z07L/nZZdBDxw7PQj+eeyewoVn/2C9/P1+d/jwn/9jKYZR7Fv7V6FeS+b+hJ6hvr4zB1fYVHvEiYUVXJg/f4bFVwcPu0wOge6+OwdX2Vp3zKmljfwyf3PYmpFA1856FN8+/6LecNN72BgeJCZE6bzrj1O2WCdkiRJkiRt7553cNHW1HLMOqZfybNvEPn8WuYvJLldZG1lP7+2MmPm/wtoWse8dpIHeALwuydviGODi0MaDuTKV1y8tqIAHDP9FRwz/RXrWu9q45+Y86HVxo/f6ViO3+nY55SrL5vEZ1549jrXKUmSJEmS1m5zvg5VkiRJkiRpszK4kCRJkiRJmbW5XoeaWcfOOJJjZxw53s2QJEmSJEn/Bq+4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC60XlMqKwFopwyA8opu+hgEYKQjB7kaACrLiwDoHlxBeXUAIFdUS4ydSUWDEwHIjxTTPbgCgOLB2qTsxOX0rJyUlIkr6C9OiozW05eroHpwFQClI2Us6a1Ihoe7kvn5HJX1SV3DSzqomVIKwJJlSTsr62vpXbEkmT9SSkWyKD0rxmxorErWXzcMXSsKyybTKiAkbRle2p2sO0KuPhTqydUlbRrp6knmD0DRlDoAeuMg1cuStnamK6/JdxW2eSCuoLyqOmlHup7Y1cVg8UBSJ8VU1iV1DbZT2E+F+cWTgKRcTU9HYT2xr3t04aTq6spC+ypLSuhO92Pl5PTYLemgoj45JfQsGym0qbcn2fe1lcN0Fo8k6xkODFbUpzsyKdNbMchIXz5pf193YZ9SFgvTaiuHAejqG2J4eDIAJSNJmcqJy+lYmWzHaDv6uvqpLkvm96ycRElFMtw7mBxPgLLqkmQz+2op6Ul20FBFsm2D3ZUMFCd9MA5EKA6MVVlSwnB3sh8HiwcKdY32jcr62sL2leSXFdo32u/Jd1FZkpTp7hsqlOlekVYwcYiRzuQ4r9Zfy2rT9iXHHyjs777iDsgn+668b4iSfB8AA6Xpflg2Qq446dv5wQaGipNtLi1LjkdZ6KR0JPm8Dg0VM1ibDHcvSz+LaX9Itj/pVyU97YSJyXZ29OSZUlZcKA/Q299T6M+lnYOEtL9RlvSNpC+nn/u4goqS5LzRX9WbbFNXP+V1U5K6ViwpHNPBkaTNI/kRYle6f3I1lCfFC30vVA+OVl/Yn5WTi+jpHk63JBDTc8ToeWWwYqTQpji4qjB9QklynDrjCoYHku3LFQ9SHZJj2hF7CvUU+lvFIGXh2W0Z3d/5iuJ030amlCfHqWfChHQ/5wrti90rk2n5MT9yc5HSpOtRVFk3OpHuvs60eH/hHDT6WaqoW0np8qTQilzxap9tgOEVvZQOjRT2Yy6/FIDJJc+ex0fPC7UjA3QVjTBW8UAxI6TnZZKyA5OKyRXVFrapNyZ9r7yorDBttL/H4erCsRs9nhVVI3SVJef/8r4yRvLJOsv7k+8rJnRR1JH0g6H6V0EENAAAIABJREFUIWJMypUsT/Z9rqp6tbpGPwdVRelntaeS0V9lYkVnoZ/05ZJzwOS+IZakn81QnbSdQGG5snwRPR3p+T/dX2PPqbEvT0Vdcvx6u9Jz2UBc/ViWJce8vCLZt7m+WiaQ9KMlg4PEkaSuKfVJm7uW9FNRlW5/Xw4mJu2rGEjOiSP5EcpWLU+WrU/OCzF2UVGSzO9e1gnDSfnKykmFMqM/P/IVxZS0J+eFzvTQlQ3XEUrTz+uYn32j5+SOnnzhvNQ9uGJM30zaPNhdSS49V41QWzhvUZnsu9qhSPdA0l+L6kc/yxWUDiafkVC6qtCPCp/bshVUDJSnLZmQHD8oLFc5ZQqSJI0KMcYNL/WfbZvfwC1h7ty5AMybN29c2yFJkiRJ2maFDS/iFReSJEmSJCnDDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZtT08nFPPQwhhPtA33u3Qdq0e0lccSOPDPqjxZh/UeLL/abyVxRj3He9GaHwVjXcDlHl9McYDx7sR2n6FEP5hH9R4sg9qvNkHNZ7sfxpvIYR/jHcbNP68VUSSJEmSJGWWwYUkSZIkScosgwttyIXj3QBt9+yDGm/2QY03+6DGk/1P480+KB/OKUmSJEmSsssrLiRJkiRJUmYZXEiSJEmSpMwyuNA6hRCOCSH8K4SwIITwsfFuj7ZNIYQfhRCWhBDmj5lWF0K4PoTwUPq9Np0eQgjfTPvk3SGEF41fy7UtCCHMCCHcFEK4L4Rwbwjhg+l0+6C2ihBCWQjhbyGEu9I++Nl0+s4hhNvSvvaLEEJJOr00HV+Qzp81nu3XtiGEkA8h3BFCaEnH7X/aakIIj4UQ7gkh3Dn66lN/DmtNBhdaqxBCHvgO8Cpgb+CkEMLe49sqbaN+AhyzxrSPATfGGHcDbkzHIemPu6Vf7wa+t5XaqG3XEHBWjHFv4BDgfem5zj6oraUfeEWMcQ6wP3BMCOEQ4MvA+THG2UAH8I50+XcAHen089PlpOfrg8D9Y8btf9raDo8x7h9jPDAd9+ewVmNwoXV5MbAgxvhIjHEA+DnwmnFuk7ZBMcY/A8vXmPwa4Kfp8E+B48dM/1lM3ArUhBCmbZ2WalsUY3wmxvjPdHglyS/uO2If1FaS9qVV6Whx+hWBVwBXp9PX7IOjffNq4IgQQthKzdU2KIQwHWgCLkrHA/Y/jT9/Dms1Bhdalx2BJ8eMP5VOk7aGKTHGZ9LhRcCUdNh+qS0mveT5hcBt2Ae1FaWX6d8JLAGuBx4GVsQYh9JFxvazQh9M53cCk7Zui7WNuQA4GxhJxydh/9PWFYE/hBBuDyG8O53mz2Gtpmi8GyBJ6xNjjCEE39usLSqEMAH4JXBGjLFr7D8Q7YPa0mKMw8D+IYQa4FfAnuPcJG0nQgjNwJIY4+0hhLnj3R5ttw6LMT4dQmgArg8hPDB2pj+HBV5xoXV7GpgxZnx6Ok3aGhaPXvaXfl+STrdfarMLIRSThBaXxRivSSfbB7XVxRhXADcBh5Jc/jz6D6ax/azQB9P51cCyrdxUbTteCrw6hPAYyW3BrwC+gf1PW1GM8en0+xKS8PbF+HNYazC40Lr8Hdgtfap0CfAm4NpxbpO2H9cCp6XDpwG/GTP91PSJ0ocAnWMuI5Q2WXpv9sXA/THGr4+ZZR/UVhFCmJxeaUEIoRw4iuRZKzcBJ6SLrdkHR/vmCcAfY4z+J1L/lhjjx2OM02OMs0h+1/tjjPHN2P+0lYQQKkMIE0eHgVcC8/HnsNYQPNdoXUIIx5Lc95gHfhRj/MI4N0nboBDCFcBcoB5YDHwa+DVwJTATeBx4Q4xxefpH5rdJ3kLSA7wtxviP8Wi3tg0hhMOANuAenr2/+39InnNhH9QWF0LYj+TBc3mSfyhdGWM8N4SwC8l/wOuAO4C3xBj7QwhlwCUkz2NZDrwpxvjI+LRe25L0VpEPxxib7X/aWtK+9qt0tAi4PMb4hRDCJPw5rDEMLiRJkiRJUmZ5q4gkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEnboBDCqjFfIyGE3jHjb06X2T2EcFUIYWkIoTOEcHcI4cwQQj6dXxpC+N8QwhNp+YdCCB8JIYQx65kXQugLIcwYM+3IEMJjY8YPCyH8JV3H8hDCLSGEgzZiG04OITweQugOIfw6hFA3Zl5dCOFX6bzHQwgnb0LZ0TaP7o9/rVH2/SGER0MIXSGEf4QQDltL20pCCPeHEJ5aY3o+hPD5EMLCEMLKEMIdIYSadN731zgu/SGElRvaD5Ikbe8MLiRJ2gbFGCeMfgFPAMeNmXZZCGFX4DbgSeAFMcZq4ETgQGBiWs1VwBHAsem0U4B3A99YY3XdwDlra0cIoQpoAb4F1AE7Ap8F+tfX/hDCPsAP0nVOAXqA745Z5DvAQDrvzcD30jIbUxbgv8fsjz3GrPdg4EvACUA1cDHwq9EwZ4yPAO1rafpngZcAhwJVaRv6AGKM71njuFxBso8lSdJ6hBjjeLdBkiRtQenVD++MMd4wZtqlQG2MsWkdZY4AWoHdYoxPjpl+MPAXYI8Y44IQwjzgJuDDwP4xxodDCEcCF8UYZ4UQDgRuiDHWbGKbvwjMijGenI7vCtwPTAJGgA5g3xjjg+n8S4CnY4wfW1/ZGOPKtM2XxhgvWst63wicFWN8cTpeCawCdogxPpNO2xn4HXAm8MMY4/R0ei1JEDQnxvjwBravElgENMcY/7Qp+0aSpO2NV1xIkrR9OhK4ej3zjwJuGxtaAMQYbwOeIrkSY9TTwA9JrjZY04PAcAjhpyGEV6V/3G+MfYC7xqz3YZIrLHZPv4ZGQ4vUXWmZDZUd9b/pLTK3hBDmjpn+f0A+hHBwepXF24E7SUKGUd8C/gfoXaPNLwCGgBNCCItCCA+GEN63ju17PckVG39ex3xJkpQyuJAkafs0CXhmPfPr1zP/mXT+WP8LHDd6u8aoGGMXcBgQScKN9hDCtSGEKRto3wSgc41pnSS3rEwAutYxb0NlAT4K7EJy28qFwG/TqzIAVgK/BG4muZ3l08C7Y3qJagjhtUA+xvirtbR5OsntJbsDO5PcbvKZEMJRa1n2NOBn0UtfJUnaIIMLSZK2T8uAaeuZv3Q986el8wtijO3At4Fz11w4xnh/jPGt6S0V+wI7ABdsoH2rSJ4RMVYVSbCwvnkbKkuM8bYY48oYY3+M8afALSTP8QB4B/A2kqs2SoC3AC0hhB3S2zu+AnxgHW0evQLj3Bhjb4zxbuDnY+oGIIQwE5gL/Gwd9UiSpDEMLiRJ2j7dQHK7wvrmHzz2bSFQeMbFDOCPaynzVeBw4IB1VRpjfAD4CUmAsT73AnPGrHcXoJTk1pMHgaIQwm5jlp+TltlQ2bU2Cxh9U8r+QEuM8cEY40iM8TqSK0xeAuwGzALaQgiLgGuAaeltIbOAu8fUx1qGR50C3BJjfGRdGy9Jkp5lcCFJ0vbp08BLQghfDSFMBQghzA4hXBpCqEkf5Hkj8MsQwj7paz4PAS4FvhdjfGjNCmOMK4CvAWePTgsh7BlCOCuEMPoAyxnAScCtG2jfZSS3njSmVzqcC1yTXinRTRIanBtCqAwhvBR4DXDJhsqGEGpCCEeHEMpCCEUheTXsy4Dr0rJ/B5pCCLuExFEkt37MT79mkIQb+wPvBBanw0+mz9JoAz4RklfJ7gW8ieStKmOdShLeSJKkjWBwIUnSdij9I/tQkisI7g0hdJI82+EfPHvLxetJ3hhyHcntF5eSvB70/eup+hvA8JjxlcDBwG0hhG6SwGI+cNYG2ncv8B6SEGIJyfMpTh+zyOlAeTrvCuC9aZkNlS0GPk/yYMyl6bYcP+ZBnz8jub1jHslzNL4J/FeM8YEY41CMcdHoF7AcGEnHR7f5JGAnkltxWoFzYow3jjY6hHAoybMwfA2qJEkbydehSpIkSZKkzPKKC0mSJEmSlFkGF5IkaVyEEL4fQli1lq/vj3fbJElSdniriCRJkiRJyqyi8W7AVmAyI0mSJElS9oQNL+KtIpIkSZIkKcMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjJre3iriDbWEztsepmZCze97GgZSZIkbRn+brZl/Du/L28qj8d/hk3tC1k8rlv7PLG29W1kvV5xIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyqwQYxzvNmxp2/wGbjZb4549SZIkSZIAZi4MG7OYV1xIkiRJkqTM8q0ien58q4gkSVL2+LvZluFbRTTKt4ps2fWtwSsuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmeVbRSRJkiRJ0njwrSKSJEmSJOk/m8GFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMrjQWp1xxhmcccYZ490MSZIkSdJ2rmi8G6BsuvPOO8e7CZIkSZIkecWFJEmSJEnKLoMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFlFW7LyxtbmKcBVwAuBC9uaWs7akuvLkvPu+Tb1ZZN4624njXdTJEmSJEn6j/W8g4vG1ubHgCnAMNAN/B/w321NLauAdwNLgaq2ppb4fNe1gXa8FbgY6E0ntQPzLnv5D5g5Ycctueq1+vAL/nurr1OSJEmSpG3N5rpV5Li2ppYJwIuAA4FPptN3Au7b0qHFGH9N21ENHAn0vvPmM3hk5WNbafWSJEmSJGlz2qy3irQ1tTzd2Nr8f8C+ja3NPwHeDMTG1uYzgOOBLuAbwF4kV0b8EjizrallAKCxtTkC7wM+BEwFLgB+AlwC7AtcB7xldPn1tGMYeBg4/ey/f/a9P3rwcj5/wP8AcPPi2/jBAz9lad8yZlftzFn7vo9ZE2cAcOIf385rd2ri90/fxMKeZzhi2st4956n8sW7LuDu5fexd83ufO6AjzOxeAIA59z+v9zdcS/9wwNpXaez88SdAPjCXefTUFbPu/Y4hTuW3c3n7vwab9j5NVz28C/JhRzv3uNUmmYctRn2uiRJkiRJ267N+nDOxtbmGcCxwB1tTS1vBS4DvtLW1DKhranlBpLbST4E1AOHAkcAp69RzdHAAcAhwNnAhcBbgBkk4cUmPTTi5VMP5e7l9wHwxKqn+ewdX+EDe7+L3x51GYc0HMjH/nEugyODheX/tOgvnH/w57h87g+4Zcnf+PDfPsO79ziV3x51GZHI1Y9eW1j2kIYDuGLuhVx75GXsXrUr59553jrbsby/g1WDPfzqiJ/ysf0+wPnzv8/KwVWbsimSJEmSJG13Nldw8evG1uYVwM3An4Avrm2htqaW29uaWm5ta2oZamtqeQz4AfDyNRb7SltTS1dbU8u9wHzgD21NLY+0NbV0kjw/44Wb0rD60kl0Da4E4I/P/JlDGw7ioMkvpChXxEm7vI7+4X7md9xfWP71s5qpK61lclk9c+r2Ye+a3dm9eldK8yU0TjmUB7seKSzbNOOVVBRVUJIv5m27n8yCrkdZNdi91nbkQxFv3e0kinJFHNpwEOVFZTyx6qlN2RRJkiRJkrY7m+tWkePTKyrWq7G1eXfg6yTPwahI13/7GostHjPcu5bxqZvSsPa+ZVQVTwRgad9yppQ3FOblQo6G8sm09y0rTKsrrS0Ml+RKqCutKYyX5kvoHUqe/Tkch/nhvy7hpmduZsVAJ7k0A+oc6GJCceVz2lFdMpGiXL4wXpYvpXe4b1M2RZIkSZKk7c5mvVVkI3wPeADYra2ppQr4HyBsyRX+efFf2a9ubwDqy+pY3LukMC/GyJLediaXTdrkeq9/+k/cvOhWzj/481z3yiu58hUXJ3WytZ5DKkmSJEnStm+zPpxzI0wkeUDnqsbW5j2B95K8tnSzamxtzgMzgTPL82V87yXJsydeMa2Ryx6+mn8svZP96/blqkevpThXzL61e23yOnqHeinOF1NdXEXfcD8XPvCzzbsRkiRJkiRpq19x8WHgZGAl8EPgF5u5/kMbW5tXkYQj84CqC196PrtWzQJg5oTpnLP/WVxw7w9ovv5kblnyN7580KcozhVv8oqOnv4KppY38NobT+OUP7+XfWr32IybIUmSJEmSAEKM2/ytDdv8Bm4Jc+fOBWDevHnj2g5JkiRJ0jZrox4dsbWvuJAkSZIkSdpoBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQps4rGuwHKrgULFjB37tzxboYkSZIkaRs0b968jVrOKy4kSZIkSVJmecWF1mn27NkbnYBJkiRJkrQleMWFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEmSJEnKLIMLSZIkSZKUWdt1cHHHsrt53Y2nFcZP+dPp3LHs7k2u567l8zl53n9tzqZJkiRJkiSg6PkUbmxtfgx4Z1tTyw2Nrc1vBS4GetPZ7cA84H/bmloeTJefBTwKdKfLLAW+39bU8qX1rCMCPUAEOoFfAB9pa2oZfj5tX5tLXv7djVqusbWZK+ZeyPTKHQCYU7cvl8/9weZujiRJkiRJ273NfcXFX9uaWiYA1cCRJCHG7Y2tzfuusVxNutwJwDmNrc1HbaDeOenyRwAnA+9ac4HG1ubnFcJIkiRJkqTs2SJ/7KdXQzwMnN7Y2jwT+AxJSLHmcv9obG2+F9gfuH4j6n2gsbW5DdgXCld8fA94M7BHY2tzJdAAfAt4GbDqg3u/mxN2fjUA/cP9nDf/u9y86FYmldVx7PQjV6v/xD++nY/u9wEOrN+f4TjMZQ//ktYn/0BHfyczKnfgiwd+ks/deR4Ab2t7P4HAR/f7AHWlNXzuzq9xzRE/BeCxlU/ytfnfYUHXo9SXTeK/9jyNw6YcDMAX7jqf8nwZz/Qs5q7l9zJr4gw+vf9H2LFy2ibtY0mSJEmStgdb4xkX1wCNa5vR2Np8CEkIsWBjKmpsbd47reuOMZNPApqAGmAE+C1wF7AjcMSVj/6G29pvB+DHD13Bwu5n+MXhF/G1F5/LdU/duM51/eKRX3Pjwj/x1YM+w++PvpKPz/kgZflSvn3ol5O6Gr/FH465miN2eNlq5YZGhvjYP87loMkv4tqjLuWMff6Lc+84jydWPVVY5saFf+Ztu5/E7175c6ZXTOPCf/1sYzZfkiRJkqTtztYILhYCdWtMW9rY2twL/BX4LvDrDdTxz8bW5g6SUOIi4Mdj5n2zranlybamll7gIGByW1PLuW1NLQNtTS2PHDfzaG5c2AbAHxe2cersN1JVMpEp5ZMLV2KsTcuTf+Cdu5/CzAnTCSEwu2oXqkuqNrix9654gN7hXt6y6wkU54o5oH4OL5lyEDcs/FNhmcaph7J3zR4U5fIcteNcFnQ9usF6JUmSJEnaHm2N50LsCCxfY1o9ycM2P0jyzIpiYGA9dbyorallXVdlPDlmeCdgh8bW5hWjE8rz5cyp2xuAZf3LaSivLyw8pXzyOle4pHcpO1ZOXU+T1m5p33IayiaTC89mQlPLG2jvW1YYn1RaWxguy5fSO9yLJEmSJEl6rq0RXLwWaFtzYvocjK83tja/DjgduODfrD+OGX4SeLStqWW3tc2fVFrHkt6l7DxxJwAW97avs9KG8nqe7l7ELhNnbVJj6svqWNLXzkgcKYQXi3vbmZG+gUSSJEmSJG28LXKrSGNrc76xtXnnxtbmbwFzgc+uZ/EvAWc3tjaXbYZV/w1Y2dja/NHG1ubyxtbm/CMrH+P+FQ8CcPi0w7jk4atYObiKJb1L+eVjLeusqHnGK7nowUt5svtpYows6HqUzoEuAOpKa1jYs2it5fau2YPSXCmXP/xLhkaGuGPZ3dyy+G/PeRaGJEmSJEnasM0dXBza2Nq8CugC5gFVwEFtTS33rKdMK9DBWl5xuqnSqziaSd5S8iiw9Mt3f4vuoR4A3rb7SUwtn8wb/vgOzvzbORy94+HrrOuNuxzPK6Ydxlm3fYqjf/8Gvnz3N+kfTu5medtuJ/OFu87nVb9/I39cuPrFJMW5Yr580Ke4tf12mq8/ma/N/x6f3P9D7DRhxvPdPEmSJEmStjshxrjhpf6zbfMbuCXMnTsXgHnz5o1rOyRJkiRJ26ywMQttjbeKSJIkSZIk/VsMLiRJkiRJUmYZXEiSJEmSpMwyuJAkSZIkSZllcCFJkiRJkjLL4EKSJEmSJGWWwYUkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXAhSZIkSZIyy+BCkiRJkiRllsGFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQpswwuJEmSJElSZhlcSJIkSZKkzDK4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiyDC0mSJEmSlFkGF5IkSZIkKbMMLiRJkiRJUmYZXEiSJEmSpMwyuNC4+PBVd/GdmxaMdzMkSZIkSRlncKGtbnB4hGvvWsgN9y8e76ZIkiRJkjLO4EJb3cPtqxgYGuHRpd3j3RRJkiRJUsYZXGiru/fpLgBW9AzS0T0wzq2RJEmSJGWZwYW2unsXdhWGH/GqC0mSJEnSehhcaKu7d2EnkypLANZ5u8h7LrmdT/zqnq3ZLEmSJElSBhlcaKuKMXLfM10ctfcUinKBR5eues4ywyOReQ8u4ff3LibGOA6tlCRJkiRlhcGFtqonl/eysm+IOTNqmFlXsdYrLh5pX0Xf4AhLV/Xz5PLecWilJEmSJCkrDC60xd3++HIu/PPDLFiyil/f+TQA++xQxaz6Sh5pf25wMX9hZ2H4H48v32rtlCRJkiRlT9F4N0Dbvk9fey/zn+7ii797AIA9p05kj6kT2bm+kr88vJTf3Pk0T3X08r7DZwMw/+kuyopzFOdy/OPxDl73ounj2XxJkiRJ0jgyuNAW9eTyHuY/3cW7Gndmem0FsxsmcMguk8jnAjvXV9I3OMIHf34nADPrKjhuzg7Mf7qTvaZVMbGsmNsf69jgOq69ayGtdy/ke28+gFwuAPCdmxbQMzDER47ec4tunyRJkiRpy/JWEW1R181fBMAph8zitJfM4qWz68mn4cLshgkAHL7HZObMqOGc38xnSVcf9y3sYt8dqjlwp1oeXLKSzt7B9a7jRzc/yu/vXcyfHmwvTLv01sf50c2P0Tc4vIW2TJIkSZK0NRhcaKMMDo9w6a2P09mz7hBh/tOd9A+tHhRcd+8i9p5WxcxJFc9Z/sWz6rjo1AP5/ikH8LUT96N3YJjXf/8vrOwfYt8dqzhwp1pihHn/WvKcsm0PtXPLgqUs6erjzidXAPCjWx4FYOGKXp7p7KN3cJi/Przs+Wy2JEmSJGmcGVxog2KMfPyae/jkr+dzYdvDa13m9sc7aP7WzVzU9mhh2kOLV3L74x28at+pay2TywWO3HsKpUVz4pUoAAAY4UlEQVR5ZjdM5OLTDmLZqgEA9tmhmhfvXMde06r44u/up6vv2cCkb3CY919xB++59Hauuv0pAF49ZwfaHlpaWOeoGx9Y/Ly3X5IkSZI0fgwutEHfuPEhrr79KSaWFtF69zPEGLnghge5Kb0SIsbIl69LHrx5zT+fIsbINf98ild/+xaqy4s5/oU7btR6DtutnivedQgfOGI39ppWRVE+x5de9wKWrOznU7+ez/LuJNS49s6FrOgZZGXfEF/7w7+YWVfBZ169D6VFOS6++VFuf7yD8uI8R+zZwB/vX0KMccvsGEmSJEnSFufDObVeMUaWdw9wwgHTOWCnWj5+zT38sO0RLrjhIXapr+Tlu03mzw+187dHl7P/jBrufHIF1961kLOvvpsDdqrlgjftz7Tq8o1e35wZNcyZUbPa+Htevivfm/cwrfc8w2mHzuIvDy9jjykTOWjnWi699QmO2nsKdZUlnHjgdK78+1NMrS5jzoxqXrnPFG58YAkPLFrJXtOqtsTukSRJkiRtYV5xofUKIfDZV+/Dl1+/H8fsM5V8LvDF3z1AcT7wyNJubrh/MZ9ruY+ZdRVceOoBFOUCZ115F+Uleb775hdtUmixLh89Zk+uO6OR171wOhfd/Cj3PdPFqS/ZiQ8duTuv2LOBk148A4B3N+7K0MgITyzv4YCdajl8jwZCgDueWPG82yBJkiRJGh8GF9qgEAL5XKC2soSXzq4H4PPH78ukyhI++PM7ebi9my+8dl8aJpbx8t0nMzQSOfOo3Zk0oXSztWHPqVV8+YT9+PHbDuKkF8/gdS+czqQJpfzorQcxu2EiADMnJa9TBXjRzFoaqsr4+yeO5OSDZ262dkiSJEmSti5vFdEmed/cXZk1qYITD5jBk8t7+fZNCzjpxTNp3G0yAKcfPpsp1WW85ZCdtsj6D9+jgcP3aFjn/DOP2p18LnDorpMAqN+M4YkkSZIkaesL28GDC7f5DdwS5s6dC8C8efPWuUxnzyCX/e1xTj10FhNKzcAkSZIkSZskbMxC/rWpf1t1RTGnz5093s2QJEmSJG3DfMaFJEmSJEnKLIMLSZIkSZKUWQYXkiRJkiQps3zGhdZpwYIFhYd0SpIkSZK0Oa3vZRBjecWFJEmSJEnKLK+40DrNnj17oxMwSZIkSZK2BK+4kCRJkiRJmWVwIUmSJEmSMsvgQpIkSZIkZZbBhSRJkiRJyiwfzqn1e2oOjLQDAYjpdwrDi4/dj5HleQgBYky+w9qH1zOt4Xf3kK8deE79a13PBupcva4Iuckw/a4tt48kSZIkSVuMwYXWb6Q9HYhrfE+GR5bn08G4+vd1Da9jWhI0PLf+da5nPXU+p67CNkiSJEmS/tN4q4gkSZIkScosgwtJkiRJkpRZBheSJEmSJCmzDC4kSZIkSVJmGVxIkiRJkqTMMriQJEmSJEmZZXDx/+3deZhU1YH38e/pZumm2RsakNUNFY0wRhPNUHlBVJAqE2eiuERljMlkJjNOTMxEncREnZiJjkuGaHzGmBg1QiRu0apMxLhkypkBN0RxxyWi7JsovYDNef+oCzRIA2rbdUN/P89TT917zr3nnlvPebrgV+feK0mSJEmSUsvgQpIkSZIkpZbBhSRJkiRJSi2DC0mSJEmSlFodLriYu/Jp/vqBqZvXT//j15i78ukP3M68VfM59eGvtmXXJEmSJEnSNjq1VUOZQm4scDlwINAMPA+cU8zmH8sUcl2AfwNOAnoDK4C7i9n8Oa20FYF6IAJvA7cB/1zM5pvbqr+b3PL/frpL22UKOWaMu54hNXsAMLrvQUwf959t3R1JkiRJktRCm8y4yBRyPYE88BOgLzAYuBhoSja5ADgU+BTQAxgHPLmTZkcXs/nuwATgVOAr2zlumwUvkiRJkiQpfdrqP/4jAYrZ/IxkvQGY1aL+MOCuYja/KFl/PXntVDGbfyFTyBWBgwAyhdzrwHXAF4H9MoVcDVBHKTT5LPAucHUxm58G0NTcxBXzf8ojS2ZTW9WXyUOO2qr9Ex/8Eucd/E8c2m8MzbGZW1+5g8LCWaxuepuhNXvww0O/y78+dQUAZxbPJhA47+B/om/X3vzrU1dy54SbSif0zkKunH8tC9a+Rr+qWr66/1TGDvg0AJfOu5rqyioW1y9l3qpnGdFjKN8f888Mrhm0Kx+BJEmSJEkdVlvd4+IloDlTyN2UKeSOzRRyfbapnw18M1PIfS1TyH0iU8iFXW04U8iNAjLA3BbFpwBZSpedbATuBeZRmukxATgnU8hNBLjx5RksWreY28bfwJWfuoTfv/lAq8e67dW7eWDRH/n3wy7ivokzuWD016mq7Mo1R1wGwI2ZnzBr0u1M2OOzW+333sb3OP/xSzis/yHcc/SvOOfAr3LJ3Ct44903N2/zwKL/5syRp/C7Y37NkG6DuP7Fm3f1I5AkSZIkqcNqk+CimM2vBcZSuifFz4DlmULunkwhNyDZ5N+AyyjNkngceCtTyE3dbmNbPJkp5FZTCiVuAG5sUTetmM0vLGbzDZRmc/QvZvOXFLP59cVs/tWkDycDPLioyBn7nETPLj0YUN2fE/b8XKsHzC+cxZdHns6w7kMIIbBPz73o1aXnTs//2TUv0NDcwGl7n0Dnis58st9oPjPgMP6w6I+bt8kMPIJRvfejU0UlRw8ex4K1r+20XUmSJEmSOro2u0dEMZt/HvgbgEwhtz/wK+DHwCnJTTWvBa7NFHLVwJeAX2QKuUeT/bbnkGI2v6CVuoUtlocDe2QKuTUtyiqBIsDKplXUVffbXDGgun+r57CsYQWDawa2Wt+aFY2rqKvqT0XYkgMNrK5jeePKzeu1XbdMQqmq7EpDc8MHPo4kSZIkSR3Nx3Jzy+S+FL8E3ve80GSWxLWZQu5iYBSlp498ULHF8kLgtWI2v+/2Nqzt2pdlDSvYs8dwAJY2LG+10brqfry1bgl79RjxgTrTr6ovyxqXszFu3BxeLG1YztDkCSSSJEmSJOnDaZPgIplhkQVuK2bzb2YKuaGU7kMxO6k/B3gKmANsoHTJSA+2vm/Fh/Uo8E6mkDsPmAasBw4AqovZ/GPjB43llld+w6g++9HwXiN3vJ5vtaHc0GO44aVfMaLHUIZ024NX3nmd/lW19OrSk75de7Oofsnmx6G2NKr3fnSt6Mr0V+7g5L3+imdWP8f/LH2Un429qg1OT5IkSZKkjqutbs75DvBpYE6mkFtHKbCYD5yb1NcDVwJLgBXAPwBfSO5H8ZEkl6HkgDHAa0n7NwC9AM4ceQoDq/sz5cGz+OajFzJx8PhW2zppr+M5ctBYzp3zPSbeN4XLnp5GU/N6AM7c91QunXc1x953Eg8uKm61X+eKzlx22PeYvfwJcvefypXzr+O7Y77B8O5DP+rpSZIkSZLUoYUY4863+vO225/gx2HcuHEAPHzzSzvcbvHhh7TJ8QbNfrLNjrPdtoYten+ZJEmSJKmcdumJo20140KSJEmSJKnNGVxIkiRJkqTUMriQJEmSJEmpZXAhSZIkSZJSy+BCkiRJkiSllsGFJEmSJElKLYMLSZIkSZKUWgYXkiRJkiQptQwuJEmSJElSahlcSJIkSZKk1DK4kCRJkiRJqWVwIUmSJEmSUsvgQpIkSZIkpZbBhSRJkiRJSi2DC0mSJEmSlFoGF5IkSZIkKbUMLiRJkiRJUmoZXGjHKvonC6HF+5blir7NyWLY8t7a8g7Kmld32W772z3OTtrcuq2W5yBJkiRJ+nPTqdwdUMoNmbfD6gHz26cb7XUcSZIkSVK6OONCkiRJkiSllsGFJEmSJElKLYMLSZIkSZKUWgYXkiRJkiQptbw5p3Zo4BVXsHTdOt484gjqOncGYCV/SaQLX2k4jVv2f4Q+ndZzco9HWF1Ryy9v+GsGnnUBoaYHJ57Xkx/cfQk9G98pPfUjRvpe9/d0OaqW0CWwYU4DbIicesdAPj3rT3Rpaubey24iPnIeNHbn8Blj6Vy/goFf3Ivldy2kuX4D3/qfm/mb2z7J6nWVPDJjOk31Dbx55wRmfPlU1q1aBRUVfOuNAjV1fVg7eTBxVSWhtoKeswaU+ZOUJEmSJH0YzrjQDi1dtw5gc2gBECk9bvTtuIY+ndYDsLqiFoBe9asJNT1KZWsrSqEFQIwAVPTsRuiSPKZ0Q6lsdWMFXZpKjztt7FEPjd0B6Fy/orRPVQXN9RsAqKntxep1lQA01TeU+ta7Sym0ANi4kZq6PqVDriptF1du/OgfhCRJkiSpLAwuJEmSJElSahlcSJIkSZKk1DK4kCRJkiRJqWVwIUmSJEmSUsvgQpIkSZIkpZbBhSRJkiRJSi2DC0mSJEmSlFoGF5IkSZIkKbUMLiRJkiRJUmoZXEiSJEmSpNTq1JaNZQq5h4HRwMBiNt+0nfqLgO8Dhxez+Tk7aKc3cBUwGagBFgO/KGbzP2rL/kqSJEmSpHRrsxkXmUJuBJABIvC57dQH4AxgVfK+I1cD3YEDgF5Jewvaqq+SJEmSJOnPQ1vOuDgDmA3MAaYCv9mmPgMMAr4MTMsUct8oZvPrW2nrMOC7xWx+dbL+QvIqNVTI7Q/8BPgksBy4sJjNz0zqaoEbgXHAC1P3OYknVz7DTz9zOYvrlzLlobN46Njf0qmiEoCz/+98jhk8nuOGTQSgsHAWM165k5VNqzmg90i+/YmzGditbtNxOfegr3Hbq3exZv1ajh48jm8c+HeEEAC4543fM/PVu1nWuJK66n5cOOZc9uu1DysaV/LjZ/+Tp1bNp1tlNVP2/Dwn7Pm+bEeSJEmSJG2jLe9xcQZwa/KamCnkBmxTPxW4F5iZrB+3g7ZmA5dmCrkzM4Xcvi0rMoVcDXA/MB2oA04Gfpop5EYlm1wLNFIKSb5UWHj/Lp9AcclsblnwG37wye9w79HTGd33QC6ee/lW2/zvsse4fuzV/PKzP+HBxUUeXf4kAA8tfoQbX5rOd8Z8k/smzuRHh15Ir8492Rg3ct5jl7B3zz25a8JN/PjwS5n52m+Zs/yJXe6XJEmSJEkdVZsEF5lCbiwwHJhZzOafAF4BTm1R3w04EZhezOY3ALez48tFzqYUgPwj8FymkFuQKeSOTepywOvFbP7GYjb/XjGbnwvcAZyYKeQqgS8A3ytm8+uK2fz8SUMm7PJ5/PaN/+K0vU9kRI+hdKqo5PR9pvDy2tdYUr9s8zan7X0CPTp3Z0B1HYfUHszLa18F4N437uPUvb/AAb1HEkJgSM0eDOxWx/NrXmbN+rWcue8pdK7ozB7dBnLcsIk8sKi4y/2SJEmSJKmjaqtLRaYCs4rZ/IpkfXpSdnWy/lfAe8DvkvVbgT9kCrn+xWx++baNFbP5BuCHwA8zhVxP4HzgN5lCbhilgOTTmUJuzTbncQvQP1leuKliYHUd83h2l05iScMypj13Pdc+//PNZZHI8saVmy8X6du1z+a6rpVdaWhuBGBZ4wr26DbofW0ubVjGyqaVHHvfSZvLmuNGRvcd9b5tJUmSJEnS1j5ycJEp5KqBKUBlppBbkhR3BXpnCrnRxWx+HqUQozvwRqaQAwhAZ0qzMv5jR+0Xs/m1mULuh8AFwJ6UQok/FrP5o7fTl0pKAclQkntiLG3YkotUVVYB0NTcRKeKbgCsatqSf9RV9eOMfaZwzODxH+gz2LTvovrF7y+v7seg6gHMGP+zD9ymJEmSJEkdXVvMuDgeaAY+AbS82eZM4IxMIXcVMAE4Fni6Rf05lC4XeV9wkSnkLgR+D8yjdDnL14E1wIvAS8CPMoXc6cCvk13GAO8Ws/nnM4XcncBFmULuS8CI/lW1DKwu3W6jT9de9K+qZdZbD/G54ZP4/ZsP8FaLsOH44cdyw4u/Yt+ee7Fnj+G8u2Edj62Yy/hBY3f6IRw3bCLXPHcDB/c9kJE99+at+sV0Cp04oPdIqjt149ZXbueEEcfRqaITf3p3IU3N6zmg98idtitJkiRJUkfWFsHFVODGYjb/RsvCTCF3DTANWA08VczmZ21TPw04N1PIHVTM5udv02ak9GSQYZRmUDwNZIvZ/LvJvscAVyWvCkoBxzeTff8x2XcJ8MLkIUfx5MpnNjf87U+czVXzr+P6F28mO/RoDupzwOa6zw78DPXvNXLR3MtZ0rCM7p1qOLTfmF0KLsYPGsvb69dy8dx/Z0XjSgZW1/HdMecysFsdlx/2Pa55/udMeegs1jdvYFj3IXxlv9N32qYkSZIkSR3dRw4uitn8pFbKZ7LlCSI/2E79IkqXi2xv3x9sb58W9S8C2VbqllO6gScAv1v4h9gyuDi87lBmHvnz7e0KwKQhRzJpyJGtHXer9e+M/sZW68cPn8zxwye/b79+VbVc9BffbvWYkiRJkiRp+9rycaiSJEmSJEltyuBCkiRJkiSlVls9DjW1Jg89islDjyp3NyRJkiRJ0ofgjAtJkiRJkpRaBheSJEmSJCm1DC4kSZIkSVJqGVxIkiRJkqTUMriQJEmSJEmpZXAhSZIkSZJSy+BCkiRJkiSllsGFJEmSJElKLYMLSZIkSZKUWgYXkiRJkiQptQwuJEmSJElSahlcSJIkSZKk1DK4kCRJkiRJqWVwIUmSJEmSUsvgQpIkSZIkpZbBhXZoQE0NAMs2bNhcFlgPQK/Qm9XvdQGgz8aVALzdrQ9x3Tulsp4bWVvVI9kpALBxbT1xfSyVdS6V9anayPqulQBUvdMNqt4FYEO3fqV9GjdS2a0zAOtWvk2fmmYAunarLvVtzXpq+vYttVlRwbplq0uH7FvaLtQ6zCVJkiTpz1WIMZa7Dx+33f4EPw7jxo0D4OGHHy5rPyRJkiRJu62wKxv5U7QkSZIkSUotgwtJkiRJkpRaBheSJEmSJCm1DC4kSZIkSVJqdYSbc+ojCCHMBxrL3Q91aP2AFeXuhDo0x6DKzTGocnL8qdyqYowHlbsTKq9O5e6AUq8xxnhouTuhjiuE8LhjUOXkGFS5OQZVTo4/lVsI4fFy90Hl56UikiRJkiQptQwuJEmSJElSahlcaGeuL3cH1OE5BlVujkGVm2NQ5eT4U7k5BuXNOSVJkiRJUno540KSJEmSJKWWwYUkSZIkSUotgwu1KoQwKYTwYghhQQjh/HL3R7unEMIvQgjLQgjzW5T1DSHcH0J4OXnvk5SHEMK0ZEw+HUI4pHw91+4ghDA0hPBQCOG5EMKzIYSvJ+WOQbWLEEJVCOHREMK8ZAxenJTvGUKYk4y120IIXZLyrsn6gqR+RDn7r91DCKEyhDA3hJBP1h1/ajchhNdDCM+EEJ7a9OhTv4e1LYMLbVcIoRK4FjgWGAWcEkIYVd5eaTf1S2DSNmXnAw/EGPcFHkjWoTQe901efwtc10591O7rPeDcGOMo4HDgH5K/dY5BtZcm4MgY42hgDDAphHA4cBlwdYxxH2A1cFay/VnA6qT86mQ76aP6OvB8i3XHn9rb+BjjmBjjocm638PaisGFWvMpYEGM8dUY43rg18Dny9wn7YZijP8NrNqm+PPATcnyTcDxLcpvjiWzgd4hhEHt01PtjmKMi2OMTybL71D6h/tgHINqJ8lYejdZ7Zy8InAkcHtSvu0Y3DQ2bwcmhBBCO3VXu6EQwhAgC9yQrAccfyo/v4e1FYMLtWYwsLDF+ptJmdQeBsQYFyfLS4ABybLjUh+bZMrzXwBzcAyqHSXT9J8ClgH3A68Aa2KM7yWbtBxnm8dgUv82UNu+PdZu5sfAt4GNyXotjj+1rwjMCiE8EUL426TM72FtpVO5OyBJOxJjjCEEn9usj1UIoTtwB3BOjHFtyx8QHYP6uMUYm4ExIYTewF3A/mXukjqIEEIOWBZjfCKEMK7c/VGHNTbG+FYIoQ64P4TwQstKv4cFzrhQ694ChrZYH5KUSe1h6aZpf8n7sqTccak2F0LoTCm0uDXGeGdS7BhUu4sxrgEeAo6gNP150w9MLcfZ5jGY1PcCVrZzV7X7+EvgcyGE1yldFnwk8B84/tSOYoxvJe/LKIW3n8LvYW3D4EKteQzYN7mrdBfgZOCeMvdJHcc9wNRkeSrw2xblZyR3lD4ceLvFNELpA0uuzf458HyM8aoWVY5BtYsQQv9kpgUhhGrgaEr3WnkIOCHZbNsxuGlsngA8GGP0l0h9KDHGC2KMQ2KMIyj9W+/BGOMXcfypnYQQakIIPTYtA8cA8/F7WNsI/q1Ra0IIkyld91gJ/CLGeGmZu6TdUAhhBjAO6AcsBb4P3A3MBIYBfwKmxBhXJf/JvIbSU0jqgTNjjI+Xo9/aPYQQxgJF4Bm2XN/9L5Tuc+EY1McuhHAwpRvPVVL6QWlmjPGSEMJelH4B7wvMBU6LMTaFEKqAWyjdj2UVcHKM8dXy9F67k+RSkW/FGHOOP7WXZKzdlax2AqbHGC8NIdTi97BaMLiQJEmSJEmp5aUikiRJkiQptQwuJEmSJElSahlcSJIkSZKk1DK4kCRJkiRJqWVwIUmSJEmSUsvgQpIkSZIkpZbBhSRJkiRJSq3/D918VAZgFcG3AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1296x1728 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df=data[data[identifier]==gene]\n",
    "df_temp = df\n",
    "for j in range(df.shape[0]):\n",
    "    transcript_annotation=annotation[annotation['transcript_id']==df.iloc[j][\"transcript_id\"]] \n",
    "    if (transcript_annotation.shape[0] < 3):\n",
    "        df_temp = df_temp[df_temp[\"transcript_id\"] != df.iloc[j][\"transcript_id\"]]\n",
    "\n",
    "# total gene expression calculation\n",
    "data_gene=df_temp[samples].sum().to_frame().transpose()\n",
    "data_gene=calculateStatistics(data_gene,conditions,number_replicates)\n",
    "# mean transcript expression calculation\n",
    "df_temp=calculateStatistics(df_temp,conditions,number_replicates)\n",
    "# isoform percentage calculation\n",
    "df_temp=(df_temp.filter(like='mean').div(data_gene.filter(like='mean').values[0],1)*100).add_prefix('Pct_').join(df_temp)\n",
    "#choose isoforms to plot\n",
    "df_temp=chooseIsoforms2Plot(df_temp,minimumTPM,minimumPct,maximumIso,annotation)\n",
    "x = [0,3,5]\n",
    "if df_temp.shape[0]:\n",
    "    panels = df_temp.shape[0] + 1\n",
    "    fig,axes = plt.subplots(panels,2,figsize = (18,24)) \n",
    "    fig.subplots_adjust(top = 0.95) \n",
    "    fig.suptitle(gene,fontsize=16) \n",
    "    \n",
    "    #plot isoform expression \n",
    "    axg=plt.subplot(panels,2,1) \n",
    "    plotProfiles(x, df_temp, data_gene, axg, colors) \n",
    "    \n",
    "    #plot isoform expression percentage \n",
    "    axt=plt.subplot(panels,2,2) \n",
    "    plotStacked(x,df_temp,axt,colors) \n",
    "    \n",
    "    #prepare annotation\n",
    "    annotation_cut=prepareAnnotation(annotation,df_temp) \n",
    "    \n",
    "    #plot annotation \n",
    "    #axa=plt.subplot(panels,2,(3,4)) \n",
    "    plotAnnotation(annotation_cut, df_temp, plt, colors,longest_length) \n",
    "    \n",
    "    plotCodingPotential(plt,panels,df_temp)\n",
    "#fig.savefig('EBF2.pdf')\n",
    "    #plt.show()"
   ]
  }
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