diff --git a/code/.ipynb_checkpoints/generalized_graph_building-checkpoint.ipynb b/code/.ipynb_checkpoints/generalized_graph_building-checkpoint.ipynb
index 9184fb504ecd26f1ad5615cf3c9a61638043089e..6de0cf4156c008ca8fb839439916c0aec79991ab 100644
--- a/code/.ipynb_checkpoints/generalized_graph_building-checkpoint.ipynb
+++ b/code/.ipynb_checkpoints/generalized_graph_building-checkpoint.ipynb
@@ -13,6 +13,8 @@
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"import os\n",
"import json\n",
"import pickle\n",
@@ -91,6 +93,9 @@
}
],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
+ "\n",
"def open_amr_dict(file):\n",
" with open(file,'r') as f:\n",
" return(json.load(f))\n",
@@ -107,7 +112,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 109,
"metadata": {},
"outputs": [
{
@@ -121,15 +126,18 @@
"source": [
"with open('../story_graphs/topic2storyID.json', 'r') as f:\n",
" topics = json.load(f)\n",
- "print(topics['0'])"
+ "print(topics['0'])\n",
+ "topics_0 = topics['0']"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"file = '3500_c14cdda2-738c-4174-94fc-6831c7c33def.pkl'\n",
"with open('../story_graphs/'+file, 'rb') as f:\n",
" graph = pickle.load(f)"
@@ -137,7 +145,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 72,
"metadata": {},
"outputs": [
{
@@ -556,10 +564,12 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"def get_graph_triples_old(amr_parse):\n",
"\n",
" lines = []\n",
@@ -589,15 +599,32 @@
" current_nodes.append(node)\n",
" return(graph_triples)\n",
"\n",
- "def get_graph_triples(amr_parse, sent_index):\n",
+ "def rename_sent_index(sent_index, rule_index=''):\n",
+ " \n",
+ " if 'EVE' in sent_index:\n",
+ " sent_index = 'e'+sent_index.split('_')[-1]\n",
+ " elif 'EMO' in sent_index:\n",
+ " sent_index = 'f'+sent_index.split('_')[-1]\n",
+ " elif 'OTH' in sent_index:\n",
+ " sent_index = 'o'+sent_index.split('_')[-1]\n",
+ " elif 'LOC' in sent_index:\n",
+ " sent_index = 'l'+sent_index.split('_')[-1]\n",
+ " elif 'POS' in sent_index:\n",
+ " sent_index = 'p'+sent_index.split('_')[-1]\n",
+ " else:\n",
+ " sent_index = 's'+sent_index.split('_')[-1]\n",
+ " if rule_index!='':\n",
+ " sent_index = sent_index+'r'+str(rule_index)\n",
+ " return(sent_index)\n",
+ "\n",
+ "def get_graph_triples(amr_parse, sent_index, rule_index):\n",
" \n",
" tree = penman.parse(amr_parse)\n",
- " var_name = sent_index + ':{i}'\n",
+ " sent_index = rename_sent_index(sent_index, rule_index)\n",
+ " var_name = sent_index + '.{i}'\n",
" tree.reset_variables(var_name)\n",
" graph = penman.interpret(tree)\n",
- " #graph_triples = graph.triples\n",
- " #return(graph_triples)\n",
- " return(graph.triples)"
+ " return(graph)"
]
},
{
@@ -609,7 +636,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
@@ -632,7 +659,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
@@ -649,21 +676,30 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 116,
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"gen = '../generalizers/GENERALIZERS_final.json'\n",
"with open(gen,'r') as f:\n",
- " replacers = json.load(f)"
+ " replacers = json.load(f)\n",
+ " add = {key+\"'s\":value+\"'s\" for (key,value) in replacers.items()}\n",
+ " replacers.update(add)\n",
+ " add = {key+\",\":value+\",\" for (key,value) in replacers.items()}\n",
+ " replacers.update(add)\n",
+ " "
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
+ "################################## ####### :op2 etc!!! ######\n",
+ "############# RUN ################ ##########################\n",
"def replace_names(parse):\n",
" \n",
" name = re.findall('[a-z]+[\\s\\n\\t]*:name \\(n[0-9]? / name[\\s\\n\\t]*:op1 (\"[A-Za-z]+\")\\)', parse)\n",
@@ -679,32 +715,50 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 126,
"metadata": {},
"outputs": [],
"source": [
- "def map_arguments(annotation, edge):\n",
+ "##################################\n",
+ "############# RUN ################\n",
+ "def map_arguments(annotation, edge, rule_index):\n",
+ " \n",
+ " #if annotation==None:\n",
+ " #return(None)\n",
+ " \n",
+ " #if annotation['2parse']==None:\n",
+ " #return(None)\n",
+ " \n",
+ " if annotation['2parse'][0]==None or annotation['2parse'][1]==None:\n",
+ " return(None)\n",
+ " \n",
+ " if annotation['2parse'][0][0]==None or annotation['2parse'][0][1]==None or annotation['2parse'][1][0]==None or annotation['2parse'][1][1]==None:\n",
+ " return(None)\n",
" \n",
" argument_mappings = []\n",
" left_over = []\n",
" \n",
" # get general rule\n",
" general_rule = annotation['2parse'][1]\n",
+ " #print(annotation['2parse'])\n",
+ " #print(general_rule)\n",
+ " #print(edge)\n",
" part1, part2 = general_rule[0], general_rule[2]\n",
"\n",
" # rename fillers\n",
- " filler1 = [replacers[word.replace(')','')] for word in annotation['general_0'][0].split(' ') if '_' in word]\n",
- " filler2 = [replacers[word.replace(')','')] for word in annotation['general_0'][2].split(' ') if '_' in word]\n",
+ " filler1 = [replacers[word.replace(')','').replace('\"','')] for word in annotation['general_0'][0].split(' ') if '_' in word]\n",
+ " filler2 = [replacers[word.replace(')','').replace('\"','')] for word in annotation['general_0'][2].split(' ') if '_' in word]\n",
" filler = [el for el in filler1 if el in filler2]\n",
" left_fillers = [el for el in filler1 if el not in filler]+[el for el in filler2 if el not in filler]\n",
" #print(left_fillers,' fillers left')\n",
" \n",
" # look up amr parse\n",
" parse_part1, parse_part2 = replace_names(amr_dict[part1]),replace_names(amr_dict[part2])\n",
- " triples_part1, triples_part2 = get_graph_triples(parse_part1,edge[0]), get_graph_triples(parse_part2,edge[1])\n",
+ " graph1, graph2 = get_graph_triples(parse_part1,edge[0],rule_index), get_graph_triples(parse_part2,edge[1],rule_index)\n",
+ " triples_part1, triples_part2 = graph1.triples, graph2.triples\n",
" \n",
" for fill in filler:\n",
- " fill = re.sub('[()]', '', replace_names(amr_dict[fill]).split('/ ')[1].split('\\n')[0])\n",
+ " fill = re.sub('[()]', '', replace_names(amr_dict[fill.replace(\"'s\",'')]).split('/ ')[1].split('\\n')[0])\n",
" \n",
" for triple in triples_part1:\n",
" \n",
@@ -734,27 +788,67 @@
" left_over.append(annotation)\n",
" #print(triple1,triple2)\n",
" continue\n",
- " #print(list(set(argument_mappings)))\n",
+ " argument_mappings = list(set(argument_mappings))\n",
+ " #for mapping in argument_mappings:\n",
+ " #print(mapping)\n",
" #print('\\n\\n')\n",
- " return((list(set(argument_mappings)),left_over))"
+ " #################\n",
+ " heads = []\n",
+ " triples_part1, triples_part2 = get_graph_triples_old(parse_part1), get_graph_triples_old(parse_part2)\n",
+ " \n",
+ " for fill in filler:\n",
+ " fill = re.sub('[()]', '', replace_names(amr_dict[fill.replace(\"'s\",'')]).split('/ ')[1].split('\\n')[0])\n",
+ " \n",
+ " for triple in triples_part1:\n",
+ " \n",
+ " triple1 = (None,None)\n",
+ " if not '_of' in triple[1]:\n",
+ " if fill in triple[2]:\n",
+ " triple1 = triple\n",
+ " break\n",
+ " else:\n",
+ " if fill in triple[0]:\n",
+ " triple1 = triple\n",
+ " break\n",
+ " for triple in triples_part2:\n",
+ " triple2 = (None,None)\n",
+ " if not '-of' in triple[1]:\n",
+ " if fill in triple[2]:\n",
+ " triple2 = triple\n",
+ " break\n",
+ " else:\n",
+ " if fill in triple[0]:\n",
+ " triple2 = triple\n",
+ " break\n",
+ " if None not in triple1 and None not in triple2:\n",
+ " triple1 = (triple1[0].split('/ ')[1],triple1[1],rename_sent_index(edge[0]))\n",
+ " triple2 = (triple2[0].split('/ ')[1],triple2[1],rename_sent_index(edge[1]))\n",
+ " heads.append((triple1,triple2))\n",
+ " else:\n",
+ " left_over.append(annotation)\n",
+ " #print(triple1,triple2)\n",
+ " continue\n",
+ " return((list(set(argument_mappings)),left_over,heads))"
]
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[(('3500_EMO_1:1', ':instance', '\"Germany\"'), ('3500_2:1', ':instance', '\"Germany\"'))]\n",
+ "[(('want-01', ':ARG0', 'f1'), ('be-located-at-91', ':ARG1', 's2'))]\n",
+ "[(('f1r0.1', ':instance', '\"Germany\"'), ('s2r0.1', ':instance', '\"Germany\"'))]\n",
"[]\n"
]
}
],
"source": [
- "argument_mapping, left_over = map_arguments(annotation, ('3500_EMO_1', '3500_2'))\n",
+ "argument_mapping, left_over, heads = map_arguments(annotation, ('3500_EMO_1', '3500_2'),0)\n",
+ "print(heads)\n",
"print(argument_mapping)\n",
"print(left_over)"
]
@@ -768,7 +862,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
@@ -777,131 +871,121 @@
},
{
"cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "(('3500_EVENT_3:3', ':instance', '\"France\"'), ('3500_0:6', ':instance', '\"France\"'))\n",
- "(('3500_EVENT_3:2', ':instance', '\"France\"'), ('3500_0:2', ':instance', '\"France\"'))\n",
- "(('3500_EVENT_3:3', ':instance', '\"Germany\"'), ('3500_0:3', ':instance', '\"Germany\"'))\n",
- "(('3500_EVENT_3:1', ':instance', '\"Max\"'), ('3500_0:1', ':instance', '\"Max\"'))\n"
- ]
- }
- ],
- "source": [
- "def get_argument_mappings(edge):\n",
- " annotations = graph.edges[edge]['annotations']\n",
- " argument_mappings = []\n",
- " for annotation in annotations:\n",
- " argument_mapping, left_over = map_arguments(annotation,edge)\n",
- " argument_mappings += argument_mapping\n",
- " #print(left_over)\n",
- " return(argument_mappings)\n",
- "\n",
- "edge = ('3500_EMO_0', '3500_0')\n",
- "edge = ('3500_EMO_1', '3500_2')\n",
- "edge = ('3500_EVENT_3', '3500_0')\n",
- "argument_mappings = get_argument_mappings(edge)\n",
- "for map in argument_mappings:\n",
- " print(map)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "(('d / drive-01', ':ARG4', 'c2 / \"France\"'), ('b / be-located-at-91', ':ARG2', 'c / \"France\"'))\n",
- "(('g / go-02', ':accompanier', 'p2 / \"Germany\"'), ('b / be-located-at-91', ':accompanier', 'p2 / \"Germany\"'))\n",
- "(('g / go-02', ':ARG4', 'c / \"France\"'), ('b / be-located-at-91', ':ARG2', 'c / \"France\"'))\n",
- "(('g / go-02', ':ARG0', 'p / \"Max\"'), ('b / be-located-at-91', ':ARG1', 'p / \"Max\"'))\n"
+ "(('e3r0.3', ':instance', '\"France\"'), ('s0r0.6', ':instance', '\"France\"'))\n",
+ "(('e3r1.1', ':instance', '\"Max\"'), ('s0r1.1', ':instance', '\"Max\"'))\n",
+ "(('e3r1.2', ':instance', '\"France\"'), ('s0r1.2', ':instance', '\"France\"'))\n",
+ "(('e3r1.3', ':instance', '\"Germany\"'), ('s0r1.3', ':instance', '\"Germany\"'))\n",
+ "(('drive-01', ':ARG4', 'e3'), ('be-located-at-91', ':ARG2', 's0'))\n",
+ "(('go-02', ':accompanier', 'e3'), ('be-located-at-91', ':accompanier', 's0'))\n",
+ "(('go-02', ':ARG4', 'e3'), ('be-located-at-91', ':ARG2', 's0'))\n",
+ "(('go-02', ':ARG0', 'e3'), ('be-located-at-91', ':ARG1', 's0'))\n"
]
}
],
"source": [
- "def get_argument_mappings(edge):\n",
+ "##################################\n",
+ "############# RUN ################\n",
+ "def get_argument_mappings(graph, edge):\n",
" annotations = graph.edges[edge]['annotations']\n",
" argument_mappings = []\n",
- " for annotation in annotations:\n",
- " argument_mapping, left_over = map_arguments(annotation)\n",
+ " heads = []\n",
+ " for i, annotation in enumerate(annotations):\n",
+ " if map_arguments(annotation,edge,i)==None:\n",
+ " continue\n",
+ " argument_mapping, left_over, head = map_arguments(annotation,edge,i)\n",
" argument_mappings += argument_mapping\n",
+ " heads += head\n",
" #print(left_over)\n",
- " return(argument_mappings)\n",
+ " return((list(set(argument_mappings)), list(set(heads))))\n",
"\n",
"edge = ('3500_EMO_0', '3500_0')\n",
"edge = ('3500_EMO_1', '3500_2')\n",
"edge = ('3500_EVENT_3', '3500_0')\n",
- "argument_mappings = get_argument_mappings(edge)\n",
- "for map in argument_mappings:\n",
- " print(map)"
+ "#edge = ('3500_EVENT_4', '3500_2')\n",
+ "argument_mappings, heads = get_argument_mappings(graph, edge)\n",
+ "for mapping in argument_mappings:\n",
+ " print(mapping)\n",
+ "for head in heads:\n",
+ " print(head)"
]
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "['Some Germans drive to France', 'Causes/Enables', 'Max who is a member of Some Germans is at France']\n",
- "['Max goes to France with Some Germans', 'Causes/Enables', 'Max is at France with Some Germans']\n",
- "36\n",
- "('3500_EVENT_3:1', ':instance', '\"Max\"')\n",
- "('3500_EVENT_3:2', ':instance', '\"France\"')\n",
- "('3500_0:0', ':ARG1', '3500_0:1')\n",
- "('3500_0:2', ':ARG0', '3500_0:1')\n",
- "('3500_0:3', ':quant', '3500_0:4')\n",
- "('3500_0:2', ':ARG1', '3500_0:3')\n",
- "('3500_0:2', ':ARG2', '3500_0:5')\n",
- "('3500_EVENT_3:2', ':instance', 'some')\n",
- "('3500_EVENT_3:1', ':quant', '3500_EVENT_3:2')\n",
- "('3500_0:0', ':ARG2', '3500_0:2')\n",
- "('3500_0:0', ':instance', 'be-located-at-91')\n",
- "('3500_0:4', ':instance', 'some')\n",
- "('3500_0:4', ':op2', '\"Germans\"')\n",
- "('3500_EVENT_3:3', ':instance', '\"France\"')\n",
- "('3500_EVENT_3:0', ':instance', 'go-02')\n",
- "('3500_EVENT_3:3', ':quant', '3500_EVENT_3:4')\n",
- "('3500_0:5', ':instance', 'member')\n",
- "('3500_EVENT_3:1', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:0', ':accompanier', '3500_EVENT_3:3')\n",
- "('3500_0:4', ':op1', '\"Some\"')\n",
- "('3500_0:0', ':accompanier', '3500_0:3')\n",
- "('3500_0:3', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:0', ':ARG0', '3500_EVENT_3:1')\n",
- "('3500_EVENT_3:3', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:4', ':instance', 'some')\n",
- "('3500_EVENT_3:0', ':ARG4', '3500_EVENT_3:3')\n",
- "('3500_0:3', ':name', '3500_0:4')\n",
- "('3500_EVENT_3:0', ':instance', 'drive-01')\n",
- "('3500_0:0', ':ARG2', '3500_0:6')\n",
- "('3500_0:2', ':instance', 'have-org-role-91')\n",
- "('3500_0:3', ':instance', 'organization')\n",
- "('3500_EVENT_3:0', ':ARG4', '3500_EVENT_3:2')\n",
- "('3500_0:4', ':instance', 'name')\n",
- "('3500_0:2', ':instance', '\"France\"')\n",
- "('3500_0:1', ':instance', '\"Max\"')\n",
- "('3500_0:6', ':instance', '\"France\"')\n"
+ "40\n",
+ "('s0r0.4', ':op1', '\"Some\"')\n",
+ "('s0r0.2', ':instance', 'have-org-role-91')\n",
+ "('s0r0.2', ':ARG2', 's0r0.5')\n",
+ "('e3r0.2', ':instance', 'some')\n",
+ "('e3r1.1', ':instance', '\"Max\"')\n",
+ "('e3r1.3', ':instance', '\"Germany\"')\n",
+ "('s0r0.2', ':ARG0', 's0r0.1')\n",
+ "('s0r1.0', ':ARG1', 's0r1.1')\n",
+ "('s0r0.4', ':op2', '\"Germans\"')\n",
+ "('s0r0.0', ':ARG2', 's0r0.6')\n",
+ "('s0r0.0', ':instance', 'be-located-at-91')\n",
+ "('e3r1.0', ':instance', 'go-02')\n",
+ "('s0r1.1', ':instance', '\"Max\"')\n",
+ "('e3r1.4', ':instance', 'some')\n",
+ "('s0r0.0', ':ARG1', 's0r0.1')\n",
+ "('e3r0.1', ':quant', 'e3r0.2')\n",
+ "('s0r1.2', ':instance', '\"France\"')\n",
+ "('e3r0.0', ':ARG4', 'e3r0.3')\n",
+ "('s0r1.4', ':instance', 'some')\n",
+ "('e3r1.3', ':quant', 'e3r1.4')\n",
+ "('s0r0.3', ':instance', 'organization')\n",
+ "('s0r0.1', ':instance', '\"Max\"')\n",
+ "('e3r0.1', ':instance', '\"Germany\"')\n",
+ "('s0r1.3', ':quant', 's0r1.4')\n",
+ "('e3r0.0', ':instance', 'drive-01')\n",
+ "('s0r0.5', ':instance', 'member')\n",
+ "('s0r0.6', ':instance', '\"France\"')\n",
+ "('s0r1.3', ':instance', '\"Germany\"')\n",
+ "('e3r1.0', ':ARG4', 'e3r1.2')\n",
+ "('e3r0.3', ':instance', '\"France\"')\n",
+ "('s0r0.2', ':ARG1', 's0r0.3')\n",
+ "('e3r1.0', ':accompanier', 'e3r1.3')\n",
+ "('s0r1.0', ':accompanier', 's0r1.3')\n",
+ "('e3r0.0', ':ARG0', 'e3r0.1')\n",
+ "('e3r1.2', ':instance', '\"France\"')\n",
+ "('s0r0.3', ':name', 's0r0.4')\n",
+ "('s0r1.0', ':instance', 'be-located-at-91')\n",
+ "('e3r1.0', ':ARG0', 'e3r1.1')\n",
+ "('s0r0.4', ':instance', 'name')\n",
+ "('s0r1.0', ':ARG2', 's0r1.2')\n"
]
}
],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"def unite_graph_triples(edge):\n",
" unite_triples = []\n",
- " for annotation in graph.edges[edge]['annotations']:\n",
+ " for i, annotation in enumerate(graph.edges[edge]['annotations']):\n",
+ " if annotation['2parse'][0]==None or annotation['2parse'][1]==None:\n",
+ " continue\n",
+ " if annotation['2parse'][0][0]==None or annotation['2parse'][0][1]==None or annotation['2parse'][1][0]==None or annotation['2parse'][1][1]==None:\n",
+ " continue\n",
" general_rule = annotation['2parse'][1]\n",
- " print(general_rule)\n",
+ " #print(general_rule)\n",
" part1, part2 = general_rule[0], general_rule[2]\n",
- " unite_triples += get_graph_triples(replace_names(amr_dict[part1]), edge[0])+get_graph_triples(replace_names(amr_dict[part2]), edge[1])\n",
+ " graph1, graph2 = get_graph_triples(replace_names(amr_dict[part1]), edge[0],i), get_graph_triples(replace_names(amr_dict[part2]), edge[1],i)\n",
+ " unite_triples += graph1.triples + graph2.triples\n",
+ " #unite_triples += [('TOPr'+str(i), ':instance', 'cause-01'), ('TOPr'+str(i), ':ARG0', graph1.top), ('TOPr'+str(i), ':ARG1', graph2.top)]\n",
+ " #print(graph1.top, graph2.top)\n",
" unite_triples = list(set(unite_triples))\n",
" return(unite_triples)\n",
"unite_triples = unite_graph_triples(edge)\n",
@@ -923,69 +1007,88 @@
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "33\n",
- "('3500_0:0', ':accompanier', 'EVENT_3:3&0:3')\n",
- "('EVENT_3:2&0:2', ':instance', 'some')\n",
- "('EVENT_3:3&0:3', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:3&0:6', ':instance', '\"France\"')\n",
- "('3500_EVENT_3:3&0:6', ':quant', '3500_EVENT_3:4')\n",
- "('EVENT_3:1&0:1', ':quant', 'EVENT_3:2&0:2')\n",
- "('3500_0:0', ':instance', 'be-located-at-91')\n",
- "('3500_0:0', ':ARG1', 'EVENT_3:1&0:1')\n",
- "('3500_0:4', ':instance', 'some')\n",
- "('EVENT_3:2&0:2', ':ARG2', '3500_0:5')\n",
- "('3500_0:4', ':op2', '\"Germans\"')\n",
- "('3500_EVENT_3:0', ':instance', 'go-02')\n",
- "('EVENT_3:3&0:3', ':name', '3500_0:4')\n",
- "('EVENT_3:1&0:1', ':instance', '\"Germany\"')\n",
- "('3500_0:5', ':instance', 'member')\n",
- "('3500_EVENT_3:3&0:6', ':instance', '\"Germany\"')\n",
- "('3500_0:4', ':op1', '\"Some\"')\n",
- "('3500_EVENT_3:0', ':accompanier', '3500_EVENT_3:3&0:6')\n",
- "('EVENT_3:2&0:2', ':ARG0', 'EVENT_3:1&0:1')\n",
- "('EVENT_3:3&0:3', ':instance', 'organization')\n",
- "('3500_0:0', ':ARG2', '3500_EVENT_3:3&0:6')\n",
- "('3500_EVENT_3:4', ':instance', 'some')\n",
- "('3500_EVENT_3:0', ':ARG0', 'EVENT_3:1&0:1')\n",
- "('3500_EVENT_3:0', ':ARG4', '3500_EVENT_3:3&0:6')\n",
- "('3500_EVENT_3:0', ':instance', 'drive-01')\n",
- "('EVENT_3:3&0:3', ':quant', '3500_0:4')\n",
- "('3500_0:0', ':ARG2', 'EVENT_3:2&0:2')\n",
- "('EVENT_3:2&0:2', ':instance', 'have-org-role-91')\n",
- "('3500_EVENT_3:0', ':ARG4', 'EVENT_3:2&0:2')\n",
- "('3500_0:4', ':instance', 'name')\n",
- "('EVENT_3:2&0:2', ':instance', '\"France\"')\n",
- "('EVENT_3:2&0:2', ':ARG1', 'EVENT_3:3&0:3')\n",
- "('EVENT_3:1&0:1', ':instance', '\"Max\"')\n"
+ "36\n",
+ "('s0r0.4', ':op1', '\"Some\"')\n",
+ "('s0r0.2', ':instance', 'have-org-role-91')\n",
+ "('s0r0.2', ':ARG2', 's0r0.5')\n",
+ "('s0r0.0', ':ARG2', 'e3r0.3-s0r0.6')\n",
+ "('e3r1.2-s0r1.2', ':instance', '\"France\"')\n",
+ "('e3r0.2', ':instance', 'some')\n",
+ "('s0r0.4', ':instance', 'name')\n",
+ "('e3r1.1-s0r1.1', ':instance', '\"Max\"')\n",
+ "('s0r0.2', ':ARG0', 's0r0.1')\n",
+ "('e3r0.3-s0r0.6', ':instance', '\"France\"')\n",
+ "('e3r1.0', ':ARG4', 'e3r1.2-s0r1.2')\n",
+ "('s0r0.4', ':op2', '\"Germans\"')\n",
+ "('s0r0.0', ':instance', 'be-located-at-91')\n",
+ "('e3r1.0', ':instance', 'go-02')\n",
+ "('e3r0.0', ':ARG4', 'e3r0.3-s0r0.6')\n",
+ "('e3r1.3-s0r1.3', ':quant', 's0r1.4')\n",
+ "('s0r1.0', ':ARG1', 'e3r1.1-s0r1.1')\n",
+ "('e3r1.0', ':ARG0', 'e3r1.1-s0r1.1')\n",
+ "('e3r1.4', ':instance', 'some')\n",
+ "('s0r0.0', ':ARG1', 's0r0.1')\n",
+ "('e3r0.1', ':quant', 'e3r0.2')\n",
+ "('s0r1.4', ':instance', 'some')\n",
+ "('e3r1.3-s0r1.3', ':quant', 'e3r1.4')\n",
+ "('e3r1.3-s0r1.3', ':instance', '\"Germany\"')\n",
+ "('s0r0.3', ':instance', 'organization')\n",
+ "('s0r1.0', ':accompanier', 'e3r1.3-s0r1.3')\n",
+ "('s0r0.1', ':instance', '\"Max\"')\n",
+ "('e3r0.1', ':instance', '\"Germany\"')\n",
+ "('e3r0.0', ':instance', 'drive-01')\n",
+ "('s0r0.5', ':instance', 'member')\n",
+ "('s0r0.2', ':ARG1', 's0r0.3')\n",
+ "('e3r0.0', ':ARG0', 'e3r0.1')\n",
+ "('s0r0.3', ':name', 's0r0.4')\n",
+ "('s0r1.0', ':instance', 'be-located-at-91')\n",
+ "('s0r1.0', ':ARG2', 'e3r1.2-s0r1.2')\n",
+ "('e3r1.0', ':accompanier', 'e3r1.3-s0r1.3')\n"
]
}
],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"def rename_variables(unite_triples, argument_mappings):\n",
+ " merged_instances = []\n",
+ " delete = []\n",
+ " rename = {}\n",
" for mapping in argument_mappings:\n",
+ " delete.append(mapping[0])\n",
+ " delete.append(mapping[1])\n",
+ " #print(mapping)\n",
" var1 = mapping[0][0]\n",
" var2 = mapping[1][0]\n",
- " merged_var_name = '_'.join(mapping[0][0].split('_')[1:])+'&'+ '_'.join(mapping[1][0].split('_')[1:])\n",
+ " merged_var_name = mapping[0][0]+'-'+ mapping[1][0]\n",
+ " #merged_var_name = '_'.join(mapping[0][0].split('_')[1:])+'&'+ '_'.join(mapping[1][0].split('_')[1:])\n",
" #print(merged_var_name)\n",
+ " rename[var1] = merged_var_name\n",
+ " rename[var2] = merged_var_name \n",
" merged_instance = (merged_var_name, mapping[0][1], mapping[0][2])\n",
- " #print(merged_instance)\n",
- "\n",
- " for i, triple in enumerate(unite_triples):\n",
- " if triple == mapping[0] or triple == mapping[1]:\n",
- " unite_triples[i] = merged_instance\n",
- " elif var1 in triple or var2 in triple:\n",
- " new_triple = eval(str(triple).replace(var1, merged_var_name).replace(var2, merged_var_name))\n",
- " #print(new_triple)\n",
- " #print(type(new_triple))\n",
- " unite_triples[i] = new_triple\n",
- " unite_triples = list(set(unite_triples))\n",
+ " merged_instances.append(merged_instance)\n",
+ " #print('MERGE INSTANCES:')\n",
+ " #print(merged_instances)\n",
+ " #print('DELETE:')\n",
+ " #print(delete)\n",
+ " unite_triples = [triple for triple in unite_triples if triple not in delete]\n",
+ " for i, triple in enumerate(unite_triples):\n",
+ " if triple[0] in rename.keys():\n",
+ " triple = (rename[triple[0]],triple[1],triple[2])\n",
+ " if triple[2] in rename.keys():\n",
+ " triple = (triple[0],triple[1],rename[triple[2]])\n",
+ " elif triple[2] in rename.keys():\n",
+ " triple = (triple[0],triple[1],rename[triple[2]])\n",
+ " unite_triples[i] = triple\n",
+ " unite_triples = unite_triples + merged_instances\n",
+ " unite_triples = list(set(unite_triples))\n",
" return(unite_triples)\n",
"renamed_triples = rename_variables(unite_triples, argument_mappings)\n",
"\n",
@@ -996,75 +1099,1774 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 65,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "26\n",
+ "('s0r0.4', ':op1', '\"Some\"')\n",
+ "('s0r0.2', ':instance', 'have-org-role-91')\n",
+ "('s0r0.2', ':ARG2', 's0r0.5')\n",
+ "('e3r0.0', ':ARG0', 'e3r1.3-s0r1.3-e3r0.1')\n",
+ "('s0r0.2', ':ARG0', 'e3r1.1-s0r1.1-s0r0.1')\n",
+ "('s0r0.4', ':op2', '\"Germans\"')\n",
+ "('e3r1.3-s0r1.3-e3r0.1', ':instance', '\"Germany\"')\n",
+ "('s0r0.0-s0r1.0', ':ARG2', 'e3r1.2-s0r1.2-e3r0.3-s0r0.6')\n",
+ "('e3r1.0', ':instance', 'go-02')\n",
+ "('e3r1.0', ':ARG0', 'e3r1.1-s0r1.1-s0r0.1')\n",
+ "('s0r0.0-s0r1.0', ':ARG1', 'e3r1.1-s0r1.1-s0r0.1')\n",
+ "('e3r1.2-s0r1.2-e3r0.3-s0r0.6', ':instance', '\"France\"')\n",
+ "('e3r1.3-s0r1.3-e3r0.1', ':quant', 'e3r0.2-e3r1.4-s0r1.4')\n",
+ "('e3r0.2-e3r1.4-s0r1.4', ':instance', 'some')\n",
+ "('s0r0.3', ':instance', 'organization')\n",
+ "('e3r1.1-s0r1.1-s0r0.1', ':instance', '\"Max\"')\n",
+ "('s0r0.0-s0r1.0', ':instance', 'be-located-at-91')\n",
+ "('s0r0.0-s0r1.0', ':accompanier', 'e3r1.3-s0r1.3-e3r0.1')\n",
+ "('e3r0.0', ':instance', 'drive-01')\n",
+ "('s0r0.5', ':instance', 'member')\n",
+ "('e3r0.0', ':ARG4', 'e3r1.2-s0r1.2-e3r0.3-s0r0.6')\n",
+ "('s0r0.2', ':ARG1', 's0r0.3')\n",
+ "('e3r1.0', ':ARG4', 'e3r1.2-s0r1.2-e3r0.3-s0r0.6')\n",
+ "('s0r0.3', ':name', 's0r0.4')\n",
+ "('e3r1.0', ':accompanier', 'e3r1.3-s0r1.3-e3r0.1')\n",
+ "('s0r0.4', ':instance', 'name')\n"
+ ]
+ }
+ ],
+ "source": [
+ "##################################\n",
+ "############# RUN ################\n",
+ "def merge_instances_between_multiple_rules(triples):\n",
+ " # get instances to merge\n",
+ " instance_dict = {}\n",
+ " for triple in triples:\n",
+ " if triple[1]==':instance' or '\"' in triple[2]:\n",
+ " if triple[2] not in instance_dict.keys():\n",
+ " instance_dict[triple[2]] = [triple[0]]\n",
+ " else:\n",
+ " instance_dict[triple[2]] += [triple[0]]\n",
+ " #print(instance_dict)\n",
+ " rename = {}\n",
+ " for instance in instance_dict.keys():\n",
+ " new_var = '-'.join(instance_dict[instance])\n",
+ " for old_var in instance_dict[instance]:\n",
+ " rename[old_var] = new_var\n",
+ " #print(rename)\n",
+ " \n",
+ " # merge instances variable names \n",
+ " new_triples = []\n",
+ " #delete = []\n",
+ " \n",
+ " for triple in triples:\n",
+ " if triple[0] in rename.keys():\n",
+ " #print(triple)\n",
+ " #delete.append(triple)\n",
+ " new_triple = (rename[triple[0]], triple[1], triple[2])\n",
+ " #new_triples.append(new_triple)\n",
+ " #print(new_triple)\n",
+ " if triple[2] in rename.keys():#instance_dict[instance]:\n",
+ " #delete.append(triple)\n",
+ " new_triple = (new_triple[0], triple[1], rename[triple[2]])\n",
+ " new_triples.append(new_triple)\n",
+ " #delete.append(triple)\n",
+ " elif triple[2] in rename.keys():#instance_dict[instance]:\n",
+ " #delete.append(triple)\n",
+ " new_triple = (triple[0], triple[1], rename[triple[2]])\n",
+ " new_triples.append(new_triple)\n",
+ " else:\n",
+ " new_triples.append(triple)\n",
+ " \"\"\"\n",
+ " for instance in instance_dict.keys():\n",
+ " if len(instance_dict[instance])==1:\n",
+ " #print(instance)\n",
+ " continue\n",
+ " new_var_name = '-'.join(instance_dict[instance])\n",
+ " #print(instance, new_var_name)\n",
+ " #for var in instance_dict[instance]:\n",
+ " for triple in triples:\n",
+ " if triple[0] in instance_dict[instance]:\n",
+ " #print(triple)\n",
+ " delete.append(triple)\n",
+ " new_triple = (new_var_name, triple[1], triple[2])\n",
+ " new_triples.append(new_triple)\n",
+ " #print(new_triple)\n",
+ " elif triple[2] in instance_dict[instance]:\n",
+ " delete.append(triple)\n",
+ " new_triple = (triple[0], triple[1], new_var_name)\n",
+ " new_triples.append(new_triple)\n",
+ " \"\"\"\n",
+ " #merged_triples = [triple for triple in triples if triple not in delete]\n",
+ " #merged_triples += new_triples\n",
+ " merged_triples = list(set(new_triples))\n",
+ " return(merged_triples)\n",
+ "super_merged_triples = merge_instances_between_multiple_rules(renamed_triples)\n",
+ "print(len(super_merged_triples))\n",
+ "for triple in super_merged_triples:\n",
+ " print(triple)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "('have-org-role-91', ':ARG2', 'member', 's0', 's0')\n",
+ "('drive-01', ':ARG0', '\"Germany\"', 'e3', 'e3-s0')\n",
+ "('have-org-role-91', ':ARG0', '\"Max\"', 's0', 'e3-s0')\n",
+ "('be-located-at-91', ':ARG2', '\"France\"', 's0', 'e3-s0')\n",
+ "('go-02', ':ARG0', '\"Max\"', 'e3', 'e3-s0')\n",
+ "('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e3-s0')\n",
+ "('\"Germany\"', ':quant', 'some', 'e3-s0', 'e3-s0')\n",
+ "('be-located-at-91', ':accompanier', '\"Germany\"', 's0', 'e3-s0')\n",
+ "('drive-01', ':ARG4', '\"France\"', 'e3', 'e3-s0')\n",
+ "('have-org-role-91', ':ARG1', 'organization', 's0', 's0')\n",
+ "('go-02', ':ARG4', '\"France\"', 'e3', 'e3-s0')\n",
+ "('organization', ':name', 'name', 's0', 's0')\n",
+ "('go-02', ':accompanier', '\"Germany\"', 'e3', 'e3-s0')\n"
+ ]
+ }
+ ],
+ "source": [
+ "##################################\n",
+ "############# RUN ################\n",
+ "def remove_vars(triples):\n",
+ " instances = [triple for triple in triples if triple[1]==':instance' or '\"' in triple[2]]\n",
+ " edges = [triple for triple in triples if triple not in instances]\n",
+ " replaced_triples = []\n",
+ " check = []\n",
+ " replacers = {}\n",
+ " for inst in instances:\n",
+ " var = inst[0]\n",
+ " concept = inst[2]\n",
+ " replacers[var] = concept\n",
+ " #print(inst)\n",
+ " #print('\\n')\n",
+ " #[print(item) for item in replacers.items()]\n",
+ " #print('\\n')\n",
+ " for edge in edges:\n",
+ " #print(edge)\n",
+ " try:\n",
+ " sent_1 = '-'.join(list(set([s[:2] for s in edge[0].split('-')])))\n",
+ " sent_2 = '-'.join(list(set([s[:2] for s in edge[2].split('-')])))\n",
+ " new_edge = (replacers[edge[0]], edge[1], replacers[edge[2]], sent_1, sent_2)\n",
+ " except:\n",
+ " sent_1 = '-'.join([s[:2] for s in edge[0].split('-')])\n",
+ " new_edge = (replacers[edge[0]], edge[1], edge[2], sent_1, sent_1)\n",
+ " replaced_triples.append(new_edge)\n",
+ " return(replaced_triples)\n",
+ "#print(rename_sent_index(edge[0]))\n",
+ "concept_triples = remove_vars(super_merged_triples)\n",
+ "for triple in concept_triples:\n",
+ " print(triple)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[('stand-01', ':ARG0', 'e4'), ('feed-01', ':ARG0', 's2')], [('love-01', ':ARG2', 's2'), ('feed-01', ':ARG2', 's2'), ('come-01', ':ARG1', 'e4')]]\n"
+ ]
+ }
+ ],
+ "source": [
+ "#print(heads)\n",
+ "heads = [(('stand-01', ':ARG0', 'e4'), ('feed-01', ':ARG0', 's2')), \n",
+ " (('come-01', ':ARG1', 'e4'), ('love-01', ':ARG2', 's2')),\n",
+ " (('come-01', ':ARG1', 'e4'), ('feed-01', ':ARG2', 's2'))]\n",
+ "\n",
+ "def make_argument_chains(heads):\n",
+ " arg_map = [[el1,el2] for (el1,el2) in heads]\n",
+ " chains = []\n",
+ " for mapping in arg_map:\n",
+ " #print(mapping)\n",
+ " done = False\n",
+ " for chain in chains:\n",
+ " if mapping[0] in chain or mapping[1] in chain:\n",
+ " chain += mapping\n",
+ " done = True\n",
+ " break\n",
+ " if done == False:\n",
+ " chains.append(mapping)\n",
+ "\n",
+ " chains = [list(set(chain)) for chain in chains]\n",
+ " return(chains)\n",
+ "\n",
+ "chains = make_argument_chains(heads)\n",
+ "print(chains) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_g_nodes(chains, concept_triples):\n",
+ " merges = []\n",
+ " for chain in chains:\n",
+ " merge = []\n",
+ " for triple in chain:\n",
+ " #print(triple)\n",
+ " for concept_triple in concept_triples:\n",
+ " #print(concept_triple)\n",
+ " if concept_triple[0]==triple[0] and concept_triple[1]==triple[1] and triple[2] in concept_triple[4]:\n",
+ " merge.append(concept_triple)\n",
+ " \"\"\" \n",
+ " for edge in concept_triples.keys():\n",
+ " if triple[2] in str(edge):\n",
+ " delete = []\n",
+ " for instance in concept_triples[edge]:\n",
+ " if triple[0]==instance[0] and triple[1]==instance[1]:\n",
+ " delete.append(instance)\n",
+ " instance = (instance[0], instance[1], instance[2], triple[2])\n",
+ " merge.append(instance)\n",
+ " #concept_triples[edge] = [instance for instance in concept_triples[edge] if instance not in delete]\n",
+ " \"\"\"\n",
+ " merges.append(merge)\n",
+ " merges = [list(set(merge)) for merge in merges]\n",
+ " return((merges, concept_triples))\n",
+ "#merges = get_g_nodes(chains, concept_triples)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ " '2parse': \n",
+ " [['A giraffe comes to the fence', 'Causes/Enables', 'Addie feeds the giraffe'], \n",
+ " ['crown comes up to throne that Max is standing by', 'Causes/Enables', 'Max feeds crown']]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 111,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def make_abstract_graph(graph):\n",
+ " \n",
+ " arg_mappings = []\n",
+ " concept_triple_edges = []\n",
+ " for edge in list(graph.edges):\n",
+ " if '_S' in edge[0]:\n",
+ " continue\n",
+ " argument_mappings, heads = get_argument_mappings(graph, edge)\n",
+ " arg_mappings += heads\n",
+ " unite_triples = unite_graph_triples(edge)\n",
+ " renamed_triples = rename_variables(unite_triples, argument_mappings)\n",
+ " super_merged_triples = merge_instances_between_multiple_rules(renamed_triples)\n",
+ " #for t in super_merged_triples:\n",
+ " #print(t)\n",
+ " #print('#'*20)\n",
+ " concept_triples = remove_vars(super_merged_triples)\n",
+ " concept_triple_edges += concept_triples\n",
+ " #edge = (rename_sent_index(edge[0]), rename_sent_index(edge[1]))\n",
+ " #concept_triple_edges[edge] = concept_triples\n",
+ " #print(arg_mappings)\n",
+ " chains = make_argument_chains(arg_mappings)\n",
+ " #concept_triple_edges = list(set(concept_triple_edges))\n",
+ " merges, concept_triples_edges = get_g_nodes(chains, concept_triple_edges)\n",
+ " #for chain in chains:\n",
+ " #print(chain)\n",
+ " #for i, merge in enumerate(merges):\n",
+ " #print(merge)\n",
+ " #print(chains[i])\n",
+ " #print('-'*10)\n",
+ " #for el in merge:\n",
+ " #print('#'*20)\n",
+ " #for e in concept_triples_edges:\n",
+ " #print(e)\n",
+ " #for el in concept_triples_edges[e]:\n",
+ " #print(el)\n",
+ " #print(concept_triples_edges)\n",
+ " return(merges, concept_triples_edges)\n",
+ "\n",
+ "file = '3500_c14cdda2-738c-4174-94fc-6831c7c33def.pkl'\n",
+ "with open('../story_graphs/'+file, 'rb') as f:\n",
+ " graph = pickle.load(f)\n",
+ "merges, concept_triples_edges = make_abstract_graph(graph)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 134,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import networkx as nx\n",
+ "\n",
+ "def add_node_to(graph, node, index, concept_triple):\n",
+ " \n",
+ " if not '-' in index:\n",
+ " node_name = node+'_'+index\n",
+ " if node_name not in list(graph.nodes):\n",
+ " graph.add_node(node_name)\n",
+ " return(graph, node_name)\n",
+ " else:\n",
+ " sents = index.split('-')\n",
+ " if len(sents)>2:\n",
+ " sents = list(set(sents))\n",
+ " if len(sents) == 1:\n",
+ " sents.append(sents[0])\n",
+ " #print('HELP')\n",
+ " #print(sents)\n",
+ " for n in graph.nodes:\n",
+ " if '_G' in n:\n",
+ " if concept_triple in graph.nodes[n]['triples'] and sents[0] in graph.nodes[n]['sentences']:\n",
+ " if node in graph.nodes[n]['representations'] and sents[1] in graph.nodes[n]['sentences']:\n",
+ " return(graph, n)\n",
+ " \n",
+ " node_name = node+'_'+index\n",
+ " if node_name not in list(graph.nodes):\n",
+ " graph.add_node(node_name)\n",
+ " return(graph, node_name)\n",
+ " \n",
+ " \n",
+ "\n",
+ "def craete_graph(merges, concept_triples):\n",
+ " graph = nx.DiGraph()\n",
+ " for i, merge in enumerate(merges):\n",
+ " \n",
+ " sentences = []\n",
+ " representations = []\n",
+ " triples = []\n",
+ " for triple in merge:\n",
+ " triples.append(triple)\n",
+ " sentences += triple[4].split('-')\n",
+ " representations.append(triple[2].replace('\"',''))\n",
+ " sentences = list(set(sentences))\n",
+ " representations = list(set(representations))\n",
+ " graph.add_node('_G'+str(i), sentences=sentences, representations=representations, triples=triples)\n",
+ " \n",
+ " for concept_triple in concept_triples:\n",
+ " #print(concept_triple)\n",
+ " #print(type(concept_triple))\n",
+ " node1, index1 = concept_triple[0].replace('\"',''), concept_triple[3]\n",
+ " node2, index2 = concept_triple[2].replace('\"',''), concept_triple[4]\n",
+ " rel = concept_triple[1]\n",
+ " \n",
+ " #try:\n",
+ " graph, node_name1 = add_node_to(graph, node1, index1, concept_triple)\n",
+ " graph, node_name2 = add_node_to(graph, node2, index2, concept_triple)\n",
+ " #except:\n",
+ " #print(concept_triple, 'FUCK')\n",
+ " if (node_name1, node_name2) in list(graph.edges):\n",
+ " if rel not in graph.edges[(node_name1, node_name2)]['relation']:\n",
+ " graph.edges[(node_name1, node_name2)]['relation'].append(rel)\n",
+ " else:\n",
+ " graph.add_edge(node_name1, node_name2, relation=[rel])\n",
+ " \n",
+ " return(graph)\n",
+ "merged_story_graph = craete_graph(merges, concept_triples_edges)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "IndexError",
+ "evalue": "list index out of range",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m/tmp/ipykernel_5030/2172462540.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'../story_graphs/'\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mgraph\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mmerges\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcept_triples_edges\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmake_abstract_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0mmerged_story_graph\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcraete_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmerges\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcept_triples_edges\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'../story_graphs_merged_general/'\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/tmp/ipykernel_5030/1194400793.py\u001b[0m in \u001b[0;36mmake_abstract_graph\u001b[0;34m(graph)\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m'_S'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0medge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0margument_mappings\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheads\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_argument_mappings\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0marg_mappings\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mheads\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0munite_triples\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0munite_graph_triples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/tmp/ipykernel_5030/2359909504.py\u001b[0m in \u001b[0;36mget_argument_mappings\u001b[0;34m(graph, edge)\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mheads\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mannotation\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotations\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mmap_arguments\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0margument_mapping\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mleft_over\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhead\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_arguments\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/tmp/ipykernel_5030/1262142080.py\u001b[0m in \u001b[0;36mmap_arguments\u001b[0;34m(annotation, edge, rule_index)\u001b[0m\n\u001b[1;32m 101\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 102\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtriple1\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtriple2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 103\u001b[0;31m \u001b[0mtriple1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtriple1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/ '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtriple1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrename_sent_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 104\u001b[0m \u001b[0mtriple2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtriple2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/ '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtriple2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrename_sent_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 105\u001b[0m \u001b[0mheads\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtriple1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtriple2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mIndexError\u001b[0m: list index out of range"
+ ]
+ }
+ ],
+ "source": [
+ "topics_0 = topics['0']\n",
+ "topics_1 = topics['1']\n",
+ "topics_6 = topics['6']\n",
+ "\n",
+ "for file in topics_1:\n",
+ " with open('../story_graphs/'+file, 'rb') as f:\n",
+ " graph = pickle.load(f)\n",
+ " merges, concept_triples_edges = make_abstract_graph(graph)\n",
+ " merged_story_graph = craete_graph(merges, concept_triples_edges)\n",
+ " with open('../story_graphs_merged_general/'+file, 'wb') as f:\n",
+ " pickle.dump(merged_story_graph, f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "193\n",
+ "208\n",
+ "_G0\n",
+ "{'sentences': ['l2', 'p1', 's3', 'e4', 'p3', 'f1', 'e8', 'e0', 'f8', 'p2', 'f0', 'f3', 'o2', 'o3', 'l1', 'e1', 'e9', 'f6', 's1', 'f5', 's0', 'l0', 'e3', 'e2', 'f2', 's4', 's2'], 'representations': ['Germany', 'Max'], 'triples': [('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2-s2'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f5-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'e9-s0'), ('pull-01', ':ARG0', '\"Max\"', 's2', 's2-f1'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'f2-s0'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'p2-s2'), ('pick-01', ':ARG0', '\"Max\"', 's2', 'p2-s2'), ('pull-01', ':ARG0', '\"Max\"', 's2', 's2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e3-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's0-s3'), ('feel-01', ':ARG0', '\"Max\"', 'f3', 's2-f3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's0-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 's0-p1'), ('be-located-at-91', ':ARG1', '\"Max\"', 'l2-s0', 'l2-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f8-s0'), ('feed-01', ':ARG0', '\"Max\"', 'f1', 's2-f1'), ('have-degree-91', ':ARG1', '\"Max\"', 'e8', 'e8-s3'), ('want-01', ':ARG0', '\"Max\"', 'f1', 's2-f1'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f0-s0'), ('crown-01', ':ARG1', '\"Max\"', 's2', 's2-f1'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-f3'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s2'), ('crown-01', ':ARG1', '\"Max\"', 's2-e0', 's2-e0'), ('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2'), ('pick-01', ':ARG0', '\"Max\"', 's2', 'e2-s2'), ('decide-01', ':ARG0', '\"Max\"', 'e0', 's2-e0'), ('surprise-01', ':ARG1', '\"Max\"', 'f6', 'f6-s3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's4-s0'), ('pull-01', ':ARG0', '\"Max\"', 's2', 'e2-s2'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'p3-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s1'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'l0-s3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'l1-s3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's1-s0'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'e4-s2'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'o2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e1-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'o3-s0'), ('feed-01', ':ARG0', '\"Max\"', 's4', 's4-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e8-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l2-s0', 'l2-s0'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-s0')]}\n",
+ "----------\n",
+ "_G1\n",
+ "{'sentences': ['l0', 'e8', 'l1', 'e1', 'f6', 's3', 's0'], 'representations': ['Max'], 'triples': [('surprise-01', ':ARG1', '\"Max\"', 's3', 'l1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 'f6', 'f6-s3'), ('near-02', ':ARG1', '\"Max\"', 'l0', 'l0-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e8-s3'), ('near-02', ':ARG1', '\"Max\"', 'l1', 'l1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's3'), ('feed-01', ':ARG0', '\"Max\"', 'e1', 'e1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's0-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'l0-s3')]}\n",
+ "----------\n",
+ "_G2\n",
+ "{'sentences': ['e2', 'e1', 'e6', 's4', 'f4', 'f1', 'p0'], 'representations': ['crown', 'throne', 'Kim', 'Max'], 'triples': [('eat-01', ':ARG0', 'crown', 's4', 's4-p0'), ('eat-01', ':ARG0', '\"Max\"', 'e1', 'e1-s4'), ('crown-01', ':ARG1', '\"Kim\"', 'e6-s4', 'e6-s4'), ('throne', ':mod', 'crown', 'e2-s4', 'e2-s4'), ('possess-01', ':ARG0', 'throne', 'p0', 'p0'), ('crown-01', ':ARG1', '\"Max\"', 's4', 's4-f4'), ('crown-01', ':ARG1', '\"Max\"', 's4', 'f1-s4'), ('crown-01', ':ARG1', '\"Max\"', 'e1-s4', 'e1-s4'), ('possess-01', ':ARG0', 'crown', 'p0', 's4-p0'), ('possess-01', ':ARG0', '\"Max\"', 'p0', 's4-p0'), ('crown-01', ':ARG1', '\"Max\"', 's4-p0', 's4-p0'), ('eat-01', ':ARG0', 'crown', 's4', 'e2-s4')]}\n",
+ "----------\n",
+ "_G3\n",
+ "{'sentences': ['e2', 'e1', 's4', 's1', 's2', 'p0'], 'representations': ['crown', 'throne', 'grass', 'crown-01'], 'triples': [('eat-01', ':ARG1', 'crown-01', 'e1', 'e1-s4'), ('eat-01', ':ARG1', 'throne', 's4', 'e2-s4'), ('come-up-11', ':ARG1', 'crown', 's1', 'e2-s1'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2-s2'), ('possess-01', ':ARG1', 'throne', 'p0', 's4-p0'), ('eat-01', ':ARG1', 'throne', 's4', 's4-p0'), ('possess-01', ':ARG1', 'grass', 'p0', 's4-p0'), ('possess-01', ':ARG1', 'crown-01', 'p0', 's4-p0'), ('feed-01', ':ARG2', 'throne', 'e2', 'e2-s2'), ('come-up-11', ':ARG1', 'crown', 's1', 's1'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2-s1'), ('feed-01', ':ARG2', 'throne', 'e2', 'e2-s4'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2')]}\n",
+ "----------\n",
+ "_G4\n",
+ "{'sentences': ['s1', 'l2', 'e3', 's0'], 'representations': ['France', 'zoo'], 'triples': [('drive-01', ':ARG4', '\"France\"', 'e3', 'e3-s0'), ('be-located-at-91', ':ARG2', '\"France\"', 's0', 's0'), ('be-located-at-91', ':ARG2', '\"France\"', 's0', 's1-s0'), ('crown', ':location', '\"France\"', 's1', 's1-s0'), ('be-located-at-91', ':ARG2', 'zoo', 's0', 's0'), ('be-located-at-91', ':ARG2', '\"France\"', 'l2-s0', 'l2-s0'), ('go-02', ':ARG4', '\"France\"', 's0', 's1-s0'), ('be-located-at-91', ':ARG2', '\"France\"', 's0', 'e3-s0'), ('go-02', ':ARG4', '\"France\"', 'e3', 'e3-s0')]}\n",
+ "----------\n",
+ "_G5\n",
+ "{'sentences': ['l2', 'l3', 'o2', 'e3', 'f9', 's1', 's0'], 'representations': ['Germany', 'Max', 'family'], 'triples': [('be-located-at-91', ':accompanier', '\"Germany\"', 'l2-s0', 'l2-s0'), ('be-located-at-91', ':accompanier', 'family', 's0', 'o2-s0'), ('go-02', ':accompanier', '\"Germany\"', 'e3', 'e3-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 'l2-s0', 'l2-s0'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-f9'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-s0'), ('be-located-at-91', ':accompanier', '\"Germany\"', 's0', 'e3-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l2-s0', 'l2-s0'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-l3'), ('feel-01', ':ARG0', '\"Germany\"', 'f9', 's1-f9'), ('be-located-at-91', ':accompanier', '\"Germany\"', 's0', 's1-s0')]}\n",
+ "----------\n",
+ "_G6\n",
+ "{'sentences': ['l2', 'p1', 's3', 'e7', 'p3', 'f7', 'f8', 'f0', 'o2', 'o3', 'e9', 's1', 'f5', 's0', 'e3', 'e2', 'f2', 's4', 's2'], 'representations': ['Germany', 'Max'], 'triples': [('see-01', ':ARG0', '\"Max\"', 's1', 's1-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f5-s0'), ('crown-01', ':ARG1', '\"Max\"', 's1', 's1-e7'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'e9-s0'), ('fun-01', ':ARG0', '\"Max\"', 'e7', 's1-e7'), ('feel-01', ':ARG0', '\"Max\"', 'f5', 'f5-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'f2-s0'), ('possess-01', ':ARG0', '\"Germany\"', 'p1', 's0-p1'), ('like-01', ':ARG0', '\"Max\"', 'f0', 'f0-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e3-s0'), ('guest', ':domain', '\"Germany\"', 'o3', 'o3-s0'), ('look-01', ':ARG0', '\"Germany\"', 'e9', 'e9-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's0-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 's0-p1'), ('feel-01', ':ARG0', '\"Max\"', 'f7', 's1-f7'), ('be-located-at-91', ':ARG1', '\"Max\"', 'l2-s0', 'l2-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f8-s0'), ('go-02', ':ARG0', '\"Max\"', 'e3', 'e3-s0'), ('possess-01', ':ARG0', '\"Max\"', 'p3', 'p3-s0'), ('feel-01', ':ARG0', '\"Germany\"', 'f2', 'f2-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f0-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s2'), ('want-01', ':ARG0', '\"Germany\"', 'f2', 'f2-s0'), ('feel-01', ':ARG0', '\"Max\"', 'f8', 'f8-s0'), ('come-up-11', ':ARG2', '\"Max\"', 's1', 'e2-s1'), ('crown-01', ':ARG1', '\"Max\"', 's1', 's1-f5'), ('feel-01', ':ARG0', '\"Max\"', 'f5', 's1-f5'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's4-s0'), ('go-02', ':ARG0', '\"Max\"', 's0', 's1-s0'), ('come-up-11', ':ARG2', '\"Max\"', 's1', 's1-f7'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'p3-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s1'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e2-s0'), ('like-01', ':ARG0', '\"Max\"', 'f0', 's1-f0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's1-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'o2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'o3-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's2-s0'), ('have-03', ':ARG0', '\"Max\"', 'o2', 'o2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l2-s0', 'l2-s0')]}\n",
+ "----------\n",
+ "_G7\n",
+ "{'sentences': ['e2', 'p2', 'e4', 's2', 's0'], 'representations': ['crown', 'throne'], 'triples': [('feed-01', ':ARG2', 'crown', 's2', 'e4-s2'), ('feed-01', ':ARG2', 'throne', 'e2', 'e2-s2'), ('come-01', ':ARG1', 'crown', 'e4', 'e4-s2'), ('feed-01', ':ARG2', 'throne', 's2', 'p2-s2'), ('feed-01', ':ARG2', 'crown', 's2', 's2'), ('feed-01', ':ARG2', 'crown', 's2', 's2-s0'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2-s2')]}\n",
+ "----------\n",
+ "_G8\n",
+ "{'sentences': ['f3', 'e2', 's2', 'e4', 'p2', 'f1', 's0'], 'representations': ['Max'], 'triples': [('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2-s2'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'e4-s2'), ('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2'), ('feed-01', ':ARG0', '\"Max\"', 'f1', 's2-f1'), ('stand-01', ':ARG0', '\"Max\"', 'e4', 'e4-s2'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'p2-s2'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-s0'), ('feel-01', ':ARG0', '\"Max\"', 'f3', 's2-f3'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-f3'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s2')]}\n",
+ "----------\n",
+ "_G9\n",
+ "{'sentences': ['e6', 's4'], 'representations': ['wrap-01', 'Kim'], 'triples': [('take-01', ':ARG0', '\"Kim\"', 's4', 'e6-s4'), ('crown-01', ':ARG1', '\"Kim\"', 'e6-s4', 'e6-s4'), ('take-01', ':ARG0', 'wrap-01', 's4', 's4')]}\n",
+ "----------\n",
+ "_G10\n",
+ "{'sentences': ['e1', 'e6', 's4', 'f4', 'f1', 'p0'], 'representations': ['Kim', 'Max'], 'triples': [('crown-01', ':ARG1', '\"Max\"', 's4', 's4-f4'), ('crown-01', ':ARG1', '\"Max\"', 's4', 'f1-s4'), ('crown-01', ':ARG1', '\"Max\"', 'e1-s4', 'e1-s4'), ('crown-01', ':ARG1', '\"Max\"', 's4-p0', 's4-p0'), ('feel-01', ':ARG0', '\"Max\"', 'f4', 's4-f4'), ('crown-01', ':ARG1', '\"Kim\"', 'e6-s4', 'e6-s4')]}\n",
+ "----------\n",
+ "_G11\n",
+ "{'sentences': ['l0', 'o1', 's3'], 'representations': ['crown', 'tongue'], 'triples': [('surprise-01', ':ARG0', 'crown', 's3', 'l0-s3'), ('surprise-01', ':ARG0', 'crown', 's3', 's3'), ('near-02', ':ARG2', 'crown', 'l0', 'l0-s3'), ('surprise-01', ':ARG0', 'tongue', 's3', 'o1-s3')]}\n",
+ "----------\n",
+ "_G12\n",
+ "{'sentences': ['l3', 's1', 'f9', 's0'], 'representations': ['Germany'], 'triples': [('look-01', ':ARG0', '\"Germany\"', 's1', 's1-s0'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-f9'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l3', 's1-l3'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-l3')]}\n",
+ "----------\n",
+ "_G13\n",
+ "{'sentences': ['p2', 's2'], 'representations': ['throne'], 'triples': [('near-02', ':ARG2', 'throne', 's2', 'p2-s2'), ('eat-01', ':ARG0', 'throne', 'p2', 'p2-s2')]}\n",
+ "----------\n",
+ "_G14\n",
+ "{'sentences': ['e2', 's2'], 'representations': ['Max'], 'triples': [('get-01', ':ARG0', '\"Max\"', 's2', 'e2-s2')]}\n",
+ "----------\n",
+ "_G15\n",
+ "{'sentences': ['s4', 'p2', 's2'], 'representations': ['crown', 'grass'], 'triples': [('possess-01', ':ARG1', 'crown', 'p2', 'p2'), ('pick-01', ':ARG1', 'crown', 's2', 'p2-s2'), ('possess-01', ':ARG1', 'grass', 'p2', 'p2-s4'), ('possess-01', ':ARG1', 'crown', 'p2', 'p2-s2')]}\n",
+ "----------\n",
+ "_G16\n",
+ "{'sentences': ['f6', 's3'], 'representations': ['Max'], 'triples': [('feel-01', ':ARG0', '\"Max\"', 'f6', 'f6'), ('shock-01', ':ARG1', '\"Max\"', 's3', 's3'), ('feel-01', ':ARG0', '\"Max\"', 'f6', 'f6-s3'), ('shock-01', ':ARG1', '\"Max\"', 's3', 'f6-s3')]}\n",
+ "----------\n",
+ "_G17\n",
+ "{'sentences': ['e5', 's4', 's3'], 'representations': ['crown', 'tongue'], 'triples': [('shock-01', ':ARG0', 'crown', 's3', 's4-s3'), ('wrap-01', ':ARG1', 'crown', 's4', 's4'), ('wrap-01', ':ARG1', 'crown', 's4', 's4-s3'), ('shock-01', ':ARG0', 'crown', 's3', 's3'), ('shock-01', ':ARG0', 'tongue', 's3', 's3-e5')]}\n",
+ "----------\n",
+ "crown-01_s2-e0\n",
+ "{}\n",
+ "----------\n",
+ "decide-01_e0\n",
+ "{}\n",
+ "----------\n",
+ "Max_s2-e0\n",
+ "{}\n",
+ "----------\n",
+ "surprise-01_s3\n",
+ "{}\n",
+ "----------\n",
+ "crown_s3\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_e1\n",
+ "{}\n",
+ "----------\n",
+ "animal_e1\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_e2\n",
+ "{}\n",
+ "----------\n",
+ "Max_e2\n",
+ "{}\n",
+ "----------\n",
+ "eat-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "have-org-role-91_s0\n",
+ "{}\n",
+ "----------\n",
+ "member_s0\n",
+ "{}\n",
+ "----------\n",
+ "drive-01_e3\n",
+ "{}\n",
+ "----------\n",
+ "Germany_e3-s0\n",
+ "{}\n",
+ "----------\n",
+ "Max_e3-s0\n",
+ "{}\n",
+ "----------\n",
+ "be-located-at-91_s0\n",
+ "{}\n",
+ "----------\n",
+ "go-02_e3\n",
+ "{}\n",
+ "----------\n",
+ "some_e3-s0\n",
+ "{}\n",
+ "----------\n",
+ "organization_s0\n",
+ "{}\n",
+ "----------\n",
+ "name_s0\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "come-01_e4\n",
+ "{}\n",
+ "----------\n",
+ "throne_e4\n",
+ "{}\n",
+ "----------\n",
+ "cause-01_e4\n",
+ "{}\n",
+ "----------\n",
+ "stand-01_e4\n",
+ "{}\n",
+ "----------\n",
+ "stick-01_e5\n",
+ "{}\n",
+ "----------\n",
+ "crown_s3-e5\n",
+ "{}\n",
+ "----------\n",
+ "tongue_s3-e5\n",
+ "{}\n",
+ "----------\n",
+ "out_e5\n",
+ "{}\n",
+ "----------\n",
+ "shock-01_s3\n",
+ "{}\n",
+ "----------\n",
+ "Max_s3\n",
+ "{}\n",
+ "----------\n",
+ "take-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_e6-s4\n",
+ "{}\n",
+ "----------\n",
+ "Max_e6\n",
+ "{}\n",
+ "----------\n",
+ "zoo_s0\n",
+ "{}\n",
+ "----------\n",
+ "France_s0\n",
+ "{}\n",
+ "----------\n",
+ "like-01_f0\n",
+ "{}\n",
+ "----------\n",
+ "animal_f0\n",
+ "{}\n",
+ "----------\n",
+ "do-02_f0\n",
+ "{}\n",
+ "----------\n",
+ "crown_s1-f0\n",
+ "{}\n",
+ "----------\n",
+ "Max_s1-f0\n",
+ "{}\n",
+ "----------\n",
+ "pull-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "Kim_f1\n",
+ "{}\n",
+ "----------\n",
+ "throne_s2\n",
+ "{}\n",
+ "----------\n",
+ "Crown_f1\n",
+ "{}\n",
+ "----------\n",
+ "want-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_f2-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_f2-s0\n",
+ "{}\n",
+ "----------\n",
+ "fun-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "want-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "crown_s2\n",
+ "{}\n",
+ "----------\n",
+ "close-10_s2\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f3\n",
+ "{}\n",
+ "----------\n",
+ "curiosity_f3\n",
+ "{}\n",
+ "----------\n",
+ "Max_s2-f3\n",
+ "{}\n",
+ "----------\n",
+ "ordinal-entity_s2\n",
+ "{}\n",
+ "----------\n",
+ "1_s2\n",
+ "{}\n",
+ "----------\n",
+ "hunger-01_f4\n",
+ "{}\n",
+ "----------\n",
+ "Max_s4-f4\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f4\n",
+ "{}\n",
+ "----------\n",
+ "near-02_l0\n",
+ "{}\n",
+ "----------\n",
+ "near-02_l1\n",
+ "{}\n",
+ "----------\n",
+ "France_l1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "Max_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "France_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "be-located-at-91_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "be-located-at-91_l3\n",
+ "{}\n",
+ "----------\n",
+ "look-01_s1\n",
+ "{}\n",
+ "----------\n",
+ "crown_s1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s1-l3\n",
+ "{}\n",
+ "----------\n",
+ "some_s1-l3\n",
+ "{}\n",
+ "----------\n",
+ "France_l3\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p0\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s0-p1\n",
+ "{}\n",
+ "----------\n",
+ "some_s0-p1\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p1\n",
+ "{}\n",
+ "----------\n",
+ "money_p1\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p2\n",
+ "{}\n",
+ "----------\n",
+ "eat-01_p2\n",
+ "{}\n",
+ "----------\n",
+ "near-02_s2\n",
+ "{}\n",
+ "----------\n",
+ "Max_p2-s2\n",
+ "{}\n",
+ "----------\n",
+ "crown_p2\n",
+ "{}\n",
+ "----------\n",
+ "hand_s4\n",
+ "{}\n",
+ "----------\n",
+ "around_s4\n",
+ "{}\n",
+ "----------\n",
+ "grass_p2-s4\n",
+ "{}\n",
+ "----------\n",
+ "wrap-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "crown_s4\n",
+ "{}\n",
+ "----------\n",
+ "she_s4\n",
+ "{}\n",
+ "----------\n",
+ "Max_p2\n",
+ "{}\n",
+ "----------\n",
+ "expect-01_o0\n",
+ "{}\n",
+ "----------\n",
+ "-_o0\n",
+ "{}\n",
+ "----------\n",
+ "crown_o0\n",
+ "{}\n",
+ "----------\n",
+ "have-03_o1\n",
+ "{}\n",
+ "----------\n",
+ "crown_o1-s3\n",
+ "{}\n",
+ "----------\n",
+ "tongue_o1-s3\n",
+ "{}\n",
+ "----------\n",
+ "purple-02_o1\n",
+ "{}\n",
+ "----------\n",
+ "long-03_o1\n",
+ "{}\n",
+ "----------\n",
+ "have-03_o2\n",
+ "{}\n",
+ "----------\n",
+ "family_o2-s0\n",
+ "{}\n",
+ "----------\n",
+ "Max_o2-s0\n",
+ "{}\n",
+ "----------\n",
+ "crown_e2\n",
+ "{}\n",
+ "----------\n",
+ "look-01_e9\n",
+ "{}\n",
+ "----------\n",
+ "crown_e9\n",
+ "{}\n",
+ "----------\n",
+ "Germany_e9-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_e9-s0\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "excite-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f5\n",
+ "{}\n",
+ "----------\n",
+ "happy-01_f5\n",
+ "{}\n",
+ "----------\n",
+ "Max_f5-s0\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f8\n",
+ "{}\n",
+ "----------\n",
+ "shock-01_f8\n",
+ "{}\n",
+ "----------\n",
+ "crown_f8\n",
+ "{}\n",
+ "----------\n",
+ "Max_f8-s0\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p3\n",
+ "{}\n",
+ "----------\n",
+ "crown_p3\n",
+ "{}\n",
+ "----------\n",
+ "Germany_o3-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_s0-o3\n",
+ "{}\n",
+ "----------\n",
+ "guest_o3\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s1-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_s1-s0\n",
+ "{}\n",
+ "----------\n",
+ "go-02_s0\n",
+ "{}\n",
+ "----------\n",
+ "see-01_s1\n",
+ "{}\n",
+ "----------\n",
+ "crown_s2-s0\n",
+ "{}\n",
+ "----------\n",
+ "grass_s2\n",
+ "{}\n",
+ "----------\n",
+ "some_s2\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "grass_s4\n",
+ "{}\n",
+ "----------\n",
+ "come-up-11_s1\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s1\n",
+ "{}\n",
+ "----------\n",
+ "fun-01_e7\n",
+ "{}\n",
+ "----------\n",
+ "Max_s1-f5\n",
+ "{}\n",
+ "----------\n",
+ "shock-01_f7\n",
+ "{}\n",
+ "----------\n",
+ "Max_s1-f7\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f7\n",
+ "{}\n",
+ "----------\n",
+ "throne_s1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s1-f9\n",
+ "{}\n",
+ "----------\n",
+ "some_s1-f9\n",
+ "{}\n",
+ "----------\n",
+ "excite-01_f9\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f9\n",
+ "{}\n",
+ "----------\n",
+ "Max_e2-s2\n",
+ "{}\n",
+ "----------\n",
+ "next-to_s2\n",
+ "{}\n",
+ "----------\n",
+ "do-02_s2\n",
+ "{}\n",
+ "----------\n",
+ "throne_e2-s2\n",
+ "{}\n",
+ "----------\n",
+ "crown_e2-s2\n",
+ "{}\n",
+ "----------\n",
+ "get-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "pick-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "need-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "excite-01_f3\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_e8\n",
+ "{}\n",
+ "----------\n",
+ "Max_e8-s3\n",
+ "{}\n",
+ "----------\n",
+ "again_e8\n",
+ "{}\n",
+ "----------\n",
+ "have-degree-91_e8\n",
+ "{}\n",
+ "----------\n",
+ "scare-01_e8\n",
+ "{}\n",
+ "----------\n",
+ "animal_e8\n",
+ "{}\n",
+ "----------\n",
+ "too_e8\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f6\n",
+ "{}\n",
+ "----------\n",
+ "surprise-01_f6\n",
+ "{}\n",
+ "----------\n",
+ "crown_s4-s3\n",
+ "{}\n",
+ "----------\n",
+ "long-03_s3\n",
+ "{}\n",
+ "----------\n",
+ "purple_s3\n",
+ "{}\n",
+ "----------\n",
+ "eat-01_e1\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_e1-s4\n",
+ "{}\n",
+ "----------\n",
+ "Max_f6\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "Max_f1-s4\n",
+ "{}\n",
+ "----------\n",
+ "happy-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "throne_p0\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s4-p0\n",
+ "{}\n",
+ "----------\n",
+ "grass_s4-p0\n",
+ "{}\n",
+ "----------\n",
+ "('_G2', '_G2')\n",
+ "{'relation': [':mod']}\n",
+ "----------\n",
+ "('crown-01_s2-e0', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s2-e0', 'Max_s2-e0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('decide-01_e0', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('decide-01_e0', 'crown-01_s2-e0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('surprise-01_s3', 'crown_s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('surprise-01_s3', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('surprise-01_s3', '_G11')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('surprise-01_s3', 'Max_s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_e1', '_G1')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_e1', 'animal_e1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_e2', 'Max_e2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_e2', '_G3')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_e2', 'crown_e2')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_e2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_s4', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('eat-01_s4', '_G2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-org-role-91_s0', 'member_s0')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('have-org-role-91_s0', 'Max_e3-s0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-org-role-91_s0', 'organization_s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('drive-01_e3', 'Germany_e3-s0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('drive-01_e3', '_G4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('Germany_e3-s0', 'some_e3-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', '_G4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', '_G5')\n",
+ "{'relation': [':accompanier']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', 'zoo_s0')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', 'France_s0')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('go-02_e3', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('go-02_e3', '_G4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('go-02_e3', '_G5')\n",
+ "{'relation': [':accompanier']}\n",
+ "----------\n",
+ "('organization_s0', 'name_s0')\n",
+ "{'relation': [':name']}\n",
+ "----------\n",
+ "('feed-01_s2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_s2', '_G7')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_s2', 'crown_s2')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_s2', 'crown_s2-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('come-01_e4', 'throne_e4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('come-01_e4', '_G7')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('cause-01_e4', 'come-01_e4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('cause-01_e4', 'stand-01_e4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('stand-01_e4', '_G8')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('stick-01_e5', 'crown_s3-e5')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('stick-01_e5', 'tongue_s3-e5')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('stick-01_e5', 'out_e5')\n",
+ "{'relation': [':direction']}\n",
+ "----------\n",
+ "('crown_s3-e5', 'tongue_s3-e5')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('shock-01_s3', 'Max_s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('shock-01_s3', '_G17')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_s3', 'crown_s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_s3', '_G16')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('take-01_s4', 'crown-01_e6-s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('take-01_s4', '_G9')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('take-01_s4', 'hand_s4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('take-01_s4', 'wrap-01_s4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('take-01_s4', 'crown_s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('take-01_s4', 'crown_s4-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_e6-s4', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_e6-s4', 'Max_e6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('like-01_f0', 'animal_f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('like-01_f0', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('like-01_f0', 'do-02_f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('do-02_f0', 'crown_s1-f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_s1-f0', 'Max_s1-f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pull-01_s2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('pull-01_s2', 'throne_s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pull-01_s2', 'feed-01_s2')\n",
+ "{'relation': [':purpose']}\n",
+ "----------\n",
+ "('pull-01_s2', 'grass_s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pull-01_s2', 'crown_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s2', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_f1', 'Kim_f1')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_f1', 'Crown_f1')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_f1', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('want-01_f1', 'feed-01_f1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('want-01_f1', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_f2-s0', 'some_f2-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('fun-01_f2', 'Germany_f2-s0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('want-01_f2', 'fun-01_f2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('want-01_f2', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('close-10_s2', 'crown_s2')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('close-10_s2', 'Max_s2-f3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('close-10_s2', 'ordinal-entity_s2')\n",
+ "{'relation': [':ord']}\n",
+ "----------\n",
+ "('feel-01_f3', 'curiosity_f3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f3', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f3', 'excite-01_f3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('ordinal-entity_s2', '1_s2')\n",
+ "{'relation': [':value']}\n",
+ "----------\n",
+ "('hunger-01_f4', 'Max_s4-f4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('crown-01_s4', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f4', 'hunger-01_f4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f4', '_G10')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('near-02_l0', '_G1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('near-02_l0', '_G11')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('near-02_l1', 'France_l1')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('near-02_l1', '_G1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('Germany_l2-s0', 'some_l2-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('Max_l2-s0', 'France_l2-s0')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('be-located-at-91_l2-s0', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('be-located-at-91_l2-s0', '_G4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('be-located-at-91_l2-s0', '_G5')\n",
+ "{'relation': [':accompanier']}\n",
+ "----------\n",
+ "('be-located-at-91_l3', '_G12')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('be-located-at-91_l3', 'France_l3')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('look-01_s1', 'crown_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('look-01_s1', '_G5')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('look-01_s1', 'throne_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_s1', '_G4')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('Germany_s1-l3', 'some_s1-l3')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('possess-01_p0', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p0', '_G2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('possess-01_p0', 'throne_p0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_s0-p1', 'some_s0-p1')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('possess-01_p1', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('possess-01_p1', 'money_p1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('possess-01_p2', 'crown_p2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p2', '_G15')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p2', 'Max_p2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_p2', '_G13')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_p2', 'crown_p2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('near-02_s2', 'Max_p2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('near-02_s2', '_G13')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('around_s4', 'grass_p2-s4')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('around_s4', 'grass_s4')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('around_s4', 'grass_s4-p0')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('wrap-01_s4', 'crown_s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('wrap-01_s4', 'around_s4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('wrap-01_s4', '_G17')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('she_s4', 'hand_s4')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('expect-01_o0', '-_o0')\n",
+ "{'relation': [':polarity']}\n",
+ "----------\n",
+ "('expect-01_o0', 'crown_o0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('have-03_o1', 'crown_o1-s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-03_o1', 'tongue_o1-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_o1-s3', 'tongue_o1-s3')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('purple-02_o1', 'tongue_o1-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('long-03_o1', 'tongue_o1-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('have-03_o2', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-03_o2', 'family_o2-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('family_o2-s0', 'Max_o2-s0')\n",
+ "{'relation': [':poss']}\n",
+ "----------\n",
+ "('look-01_e9', 'crown_e9')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('look-01_e9', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_e9-s0', 'some_e9-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('feel-01_f2', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f2', 'excite-01_f2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('excite-01_f2', 'Germany_f2-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f5', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f5', 'happy-01_f5')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('happy-01_f5', 'Max_f5-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('happy-01_f5', 'Max_s1-f5')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f8', 'shock-01_f8')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f8', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_f8', 'crown_f8')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_f8', 'Max_f8-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p3', 'crown_p3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p3', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_o3-s0', 'some_s0-o3')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('guest_o3', '_G6')\n",
+ "{'relation': [':domain']}\n",
+ "----------\n",
+ "('Germany_s1-s0', 'some_s1-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('go-02_s0', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('go-02_s0', '_G4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('see-01_s1', 'crown_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('see-01_s1', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('crown_s2-s0', 'France_s0')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('grass_s2', 'some_s2')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('feed-01_s4', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_s4', 'crown_s4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('come-up-11_s1', '_G6')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('come-up-11_s1', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('come-up-11_s1', 'crown_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s1', '_G6')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('fun-01_e7', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_f7', 'Max_s1-f7')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f7', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f7', 'shock-01_f7')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('Germany_s1-f9', 'some_s1-f9')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('excite-01_f9', 'Germany_s1-f9')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f9', '_G5')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f9', 'excite-01_f9')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('Max_e2-s2', 'next-to_s2')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('next-to_s2', 'grass_s2')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('do-02_s2', 'throne_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('do-02_s2', 'Max_e2-s2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('throne_e2-s2', 'Max_e2-s2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('crown_e2-s2', 'grass_s2')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('get-01_s2', '_G14')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('get-01_s2', 'crown_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pick-01_s2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('pick-01_s2', '_G15')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('need-01_s2', 'do-02_s2')\n",
+ "{'relation': [':purpose']}\n",
+ "----------\n",
+ "('need-01_s2', 'crown_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_e8', 'Max_e8-s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_e8', 'again_e8')\n",
+ "{'relation': [':mod']}\n",
+ "----------\n",
+ "('feed-01_e8', 'animal_e8')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('have-degree-91_e8', 'feed-01_e8')\n",
+ "{'relation': [':ARG6']}\n",
+ "----------\n",
+ "('have-degree-91_e8', 'scare-01_e8')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('have-degree-91_e8', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('have-degree-91_e8', 'too_e8')\n",
+ "{'relation': [':ARG3']}\n",
+ "----------\n",
+ "('scare-01_e8', 'Max_e8-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f6', '_G16')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f6', 'surprise-01_f6')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f6', 'Max_f6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('surprise-01_f6', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('surprise-01_f6', 'Max_f6')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_s4-s3', 'purple_s3')\n",
+ "{'relation': [':mod']}\n",
+ "----------\n",
+ "('long-03_s3', 'crown_s4-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('eat-01_e1', '_G2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_e1', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_e1-s4', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f1', 'Max_f1-s4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f1', 'happy-01_f1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('happy-01_f1', 'Max_f1-s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s4-p0', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(len(merged_story_graph.nodes))\n",
+ "print(len(merged_story_graph.edges))\n",
+ "for node in merged_story_graph.nodes:\n",
+ " print(node)\n",
+ " print(merged_story_graph.nodes[node])\n",
+ " print('-'*10)\n",
+ "for edge in merged_story_graph.edges:\n",
+ " print(edge)\n",
+ " print(merged_story_graph.edges[edge])\n",
+ " if len(merged_story_graph.edges[edge]['relation'])!=1:\n",
+ " print('*'*20)\n",
+ " print('-'*10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 108,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "(3500_0:0 / be-located-at-91\n",
- " :accompanier (EVENT_3:3&0:3 / organization\n",
- " / \"Germany\"\n",
- " :name (3500_0:4 / some\n",
- " / name\n",
- " :op1 \"Some\"\n",
- " :op2 \"Germans\")\n",
- " :quant 3500_0:4)\n",
- " :ARG1 (EVENT_3:1&0:1 / \"Max\"\n",
- " / \"Germany\"\n",
- " :ARG0-of (EVENT_3:2&0:2 / some\n",
- " / \"France\"\n",
- " / have-org-role-91\n",
- " :ARG4-of 3500_EVENT_3:0\n",
- " :ARG1 EVENT_3:3&0:3\n",
- " :ARG2 (3500_0:5 / member))\n",
- " :ARG0-of (3500_EVENT_3:0 / go-02\n",
- " / drive-01\n",
- " :ARG4 3500_EVENT_3:3&0:6)\n",
- " :quant EVENT_3:2&0:2)\n",
- " :ARG2 (3500_EVENT_3:3&0:6 / \"Germany\"\n",
- " / \"France\"\n",
- " :quant (3500_EVENT_3:4 / some)\n",
- " :accompanier-of 3500_EVENT_3:0)\n",
- " :ARG2 EVENT_3:2&0:2)\n"
+ "115\n",
+ "102\n"
+ ]
+ }
+ ],
+ "source": [
+ "sentence_nodes = [node for node in merged_story_graph.nodes if '_G' in node or 's' in node.split('_')[1]]\n",
+ "sentence_edges = [edge for edge in merged_story_graph.edges if edge[0] in sentence_nodes and edge[1] in sentence_nodes]\n",
+ "print(len(sentence_nodes))\n",
+ "print(len(sentence_edges))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 101,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "nx.draw(merged_story_graph, with_labels=True, font_weight='bold')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nx.draw_circular(merged_story_graph, with_labels=True, font_weight='bold')#draw_shell"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nx.draw_networkx(merged_story_graph, with_labels=True, font_weight='bold')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 140,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "LayoutError",
+ "evalue": "possibly disconnected graph",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mLayoutError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m/tmp/ipykernel_9281/3403421302.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msuper_merged_triples\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m#g = Graph(triples=renamed_triples)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpenman\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/penman/codec.py\u001b[0m in \u001b[0;36m_encode\u001b[0;34m(g, top, model, indent, compact)\u001b[0m\n\u001b[1;32m 238\u001b[0m \u001b[0mtop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindent\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 240\u001b[0;31m compact=compact)\n\u001b[0m\u001b[1;32m 241\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 242\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/penman/codec.py\u001b[0m in \u001b[0;36mencode\u001b[0;34m(self, g, top, indent, compact)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 129\u001b[0m \"\"\"\n\u001b[0;32m--> 130\u001b[0;31m \u001b[0mtree\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlayout\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 131\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtree\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompact\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompact\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/penman/layout.py\u001b[0m in \u001b[0;36mconfigure\u001b[0;34m(g, top, model)\u001b[0m\n\u001b[1;32m 280\u001b[0m \u001b[0mdata_count\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 281\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mvar\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mdata_count\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 282\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mLayoutError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'possibly disconnected graph'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 283\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 284\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msurprising\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_configure_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnodemap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mLayoutError\u001b[0m: possibly disconnected graph"
]
}
],
"source": [
"from penman.graph import Graph\n",
"\n",
- "g = Graph(renamed_triples)\n",
+ "g = Graph(super_merged_triples)\n",
+ "#g = Graph(triples=renamed_triples)\n",
"print(penman.encode(g))"
]
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": 110,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[Instance(source='EVENT_3:2&0:2', role=':instance', target='some'),\n",
- " Instance(source='EVENT_3:3&0:3', role=':instance', target='\"Germany\"'),\n",
- " Instance(source='3500_EVENT_3:3&0:6', role=':instance', target='\"France\"'),\n",
- " Instance(source='3500_0:0', role=':instance', target='be-located-at-91'),\n",
- " Instance(source='3500_0:4', role=':instance', target='some'),\n",
- " Instance(source='3500_EVENT_3:0', role=':instance', target='go-02'),\n",
- " Instance(source='EVENT_3:1&0:1', role=':instance', target='\"Germany\"'),\n",
- " Instance(source='3500_0:5', role=':instance', target='member'),\n",
- " Instance(source='3500_EVENT_3:3&0:6', role=':instance', target='\"Germany\"'),\n",
- " Instance(source='EVENT_3:3&0:3', role=':instance', target='organization'),\n",
- " Instance(source='3500_EVENT_3:4', role=':instance', target='some'),\n",
- " Instance(source='3500_EVENT_3:0', role=':instance', target='drive-01'),\n",
- " Instance(source='EVENT_3:2&0:2', role=':instance', target='have-org-role-91'),\n",
- " Instance(source='3500_0:4', role=':instance', target='name'),\n",
- " Instance(source='EVENT_3:2&0:2', role=':instance', target='\"France\"'),\n",
- " Instance(source='EVENT_3:1&0:1', role=':instance', target='\"Max\"')]"
+ "[Instance(source='s2r0.0', role=':instance', target='feed-01'),\n",
+ " Instance(source='e4r0.2', role=':instance', target='throne'),\n",
+ " Instance(source='e4r0.4', role=':instance', target='stand-01'),\n",
+ " Instance(source='e4r0.5-s2r0.1', role=':instance', target='\"Max\"'),\n",
+ " Instance(source='e4r0.0', role=':instance', target='come-01'),\n",
+ " Instance(source='e4r0.1-s2r0.2', role=':instance', target='crown'),\n",
+ " Instance(source='e4r0.3', role=':instance', target='cause-01'),\n",
+ " Instance(source='TOPr0', role=':instance', target='cause-01')]"
]
},
- "execution_count": 43,
+ "execution_count": 110,
"metadata": {},
"output_type": "execute_result"
}
@@ -242079,7 +243881,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -242093,7 +243895,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.8"
+ "version": "3.7.11"
}
},
"nbformat": 4,
diff --git a/code/2_0_story_graph_building.ipynb b/code/2_0_story_graph_building.ipynb
index 1f6156e332233f028661a078cb2c626d48b07770..5c5a7195792026b55b8d989b3216fc969da34100 100644
--- a/code/2_0_story_graph_building.ipynb
+++ b/code/2_0_story_graph_building.ipynb
@@ -1144,7 +1144,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -1158,7 +1158,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.8"
+ "version": "3.7.11"
}
},
"nbformat": 4,
diff --git a/code/3_prepare_for_amrparser.ipynb b/code/3_prepare_for_amrparser.ipynb
index a1ec28b8c191e22a50cba1f84602ea5f0997ae6b..ba7902dc9fc3b49e7e9c8ed8ee7cf1897a0f6563 100644
--- a/code/3_prepare_for_amrparser.ipynb
+++ b/code/3_prepare_for_amrparser.ipynb
@@ -654,7 +654,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -668,7 +668,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.5"
+ "version": "3.7.11"
}
},
"nbformat": 4,
diff --git a/code/generalized_graph_building.ipynb b/code/generalized_graph_building.ipynb
index 9184fb504ecd26f1ad5615cf3c9a61638043089e..6de0cf4156c008ca8fb839439916c0aec79991ab 100644
--- a/code/generalized_graph_building.ipynb
+++ b/code/generalized_graph_building.ipynb
@@ -13,6 +13,8 @@
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"import os\n",
"import json\n",
"import pickle\n",
@@ -91,6 +93,9 @@
}
],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
+ "\n",
"def open_amr_dict(file):\n",
" with open(file,'r') as f:\n",
" return(json.load(f))\n",
@@ -107,7 +112,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 109,
"metadata": {},
"outputs": [
{
@@ -121,15 +126,18 @@
"source": [
"with open('../story_graphs/topic2storyID.json', 'r') as f:\n",
" topics = json.load(f)\n",
- "print(topics['0'])"
+ "print(topics['0'])\n",
+ "topics_0 = topics['0']"
]
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"file = '3500_c14cdda2-738c-4174-94fc-6831c7c33def.pkl'\n",
"with open('../story_graphs/'+file, 'rb') as f:\n",
" graph = pickle.load(f)"
@@ -137,7 +145,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 72,
"metadata": {},
"outputs": [
{
@@ -556,10 +564,12 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"def get_graph_triples_old(amr_parse):\n",
"\n",
" lines = []\n",
@@ -589,15 +599,32 @@
" current_nodes.append(node)\n",
" return(graph_triples)\n",
"\n",
- "def get_graph_triples(amr_parse, sent_index):\n",
+ "def rename_sent_index(sent_index, rule_index=''):\n",
+ " \n",
+ " if 'EVE' in sent_index:\n",
+ " sent_index = 'e'+sent_index.split('_')[-1]\n",
+ " elif 'EMO' in sent_index:\n",
+ " sent_index = 'f'+sent_index.split('_')[-1]\n",
+ " elif 'OTH' in sent_index:\n",
+ " sent_index = 'o'+sent_index.split('_')[-1]\n",
+ " elif 'LOC' in sent_index:\n",
+ " sent_index = 'l'+sent_index.split('_')[-1]\n",
+ " elif 'POS' in sent_index:\n",
+ " sent_index = 'p'+sent_index.split('_')[-1]\n",
+ " else:\n",
+ " sent_index = 's'+sent_index.split('_')[-1]\n",
+ " if rule_index!='':\n",
+ " sent_index = sent_index+'r'+str(rule_index)\n",
+ " return(sent_index)\n",
+ "\n",
+ "def get_graph_triples(amr_parse, sent_index, rule_index):\n",
" \n",
" tree = penman.parse(amr_parse)\n",
- " var_name = sent_index + ':{i}'\n",
+ " sent_index = rename_sent_index(sent_index, rule_index)\n",
+ " var_name = sent_index + '.{i}'\n",
" tree.reset_variables(var_name)\n",
" graph = penman.interpret(tree)\n",
- " #graph_triples = graph.triples\n",
- " #return(graph_triples)\n",
- " return(graph.triples)"
+ " return(graph)"
]
},
{
@@ -609,7 +636,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
@@ -632,7 +659,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
@@ -649,21 +676,30 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 116,
"metadata": {},
"outputs": [],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"gen = '../generalizers/GENERALIZERS_final.json'\n",
"with open(gen,'r') as f:\n",
- " replacers = json.load(f)"
+ " replacers = json.load(f)\n",
+ " add = {key+\"'s\":value+\"'s\" for (key,value) in replacers.items()}\n",
+ " replacers.update(add)\n",
+ " add = {key+\",\":value+\",\" for (key,value) in replacers.items()}\n",
+ " replacers.update(add)\n",
+ " "
]
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
+ "################################## ####### :op2 etc!!! ######\n",
+ "############# RUN ################ ##########################\n",
"def replace_names(parse):\n",
" \n",
" name = re.findall('[a-z]+[\\s\\n\\t]*:name \\(n[0-9]? / name[\\s\\n\\t]*:op1 (\"[A-Za-z]+\")\\)', parse)\n",
@@ -679,32 +715,50 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 126,
"metadata": {},
"outputs": [],
"source": [
- "def map_arguments(annotation, edge):\n",
+ "##################################\n",
+ "############# RUN ################\n",
+ "def map_arguments(annotation, edge, rule_index):\n",
+ " \n",
+ " #if annotation==None:\n",
+ " #return(None)\n",
+ " \n",
+ " #if annotation['2parse']==None:\n",
+ " #return(None)\n",
+ " \n",
+ " if annotation['2parse'][0]==None or annotation['2parse'][1]==None:\n",
+ " return(None)\n",
+ " \n",
+ " if annotation['2parse'][0][0]==None or annotation['2parse'][0][1]==None or annotation['2parse'][1][0]==None or annotation['2parse'][1][1]==None:\n",
+ " return(None)\n",
" \n",
" argument_mappings = []\n",
" left_over = []\n",
" \n",
" # get general rule\n",
" general_rule = annotation['2parse'][1]\n",
+ " #print(annotation['2parse'])\n",
+ " #print(general_rule)\n",
+ " #print(edge)\n",
" part1, part2 = general_rule[0], general_rule[2]\n",
"\n",
" # rename fillers\n",
- " filler1 = [replacers[word.replace(')','')] for word in annotation['general_0'][0].split(' ') if '_' in word]\n",
- " filler2 = [replacers[word.replace(')','')] for word in annotation['general_0'][2].split(' ') if '_' in word]\n",
+ " filler1 = [replacers[word.replace(')','').replace('\"','')] for word in annotation['general_0'][0].split(' ') if '_' in word]\n",
+ " filler2 = [replacers[word.replace(')','').replace('\"','')] for word in annotation['general_0'][2].split(' ') if '_' in word]\n",
" filler = [el for el in filler1 if el in filler2]\n",
" left_fillers = [el for el in filler1 if el not in filler]+[el for el in filler2 if el not in filler]\n",
" #print(left_fillers,' fillers left')\n",
" \n",
" # look up amr parse\n",
" parse_part1, parse_part2 = replace_names(amr_dict[part1]),replace_names(amr_dict[part2])\n",
- " triples_part1, triples_part2 = get_graph_triples(parse_part1,edge[0]), get_graph_triples(parse_part2,edge[1])\n",
+ " graph1, graph2 = get_graph_triples(parse_part1,edge[0],rule_index), get_graph_triples(parse_part2,edge[1],rule_index)\n",
+ " triples_part1, triples_part2 = graph1.triples, graph2.triples\n",
" \n",
" for fill in filler:\n",
- " fill = re.sub('[()]', '', replace_names(amr_dict[fill]).split('/ ')[1].split('\\n')[0])\n",
+ " fill = re.sub('[()]', '', replace_names(amr_dict[fill.replace(\"'s\",'')]).split('/ ')[1].split('\\n')[0])\n",
" \n",
" for triple in triples_part1:\n",
" \n",
@@ -734,27 +788,67 @@
" left_over.append(annotation)\n",
" #print(triple1,triple2)\n",
" continue\n",
- " #print(list(set(argument_mappings)))\n",
+ " argument_mappings = list(set(argument_mappings))\n",
+ " #for mapping in argument_mappings:\n",
+ " #print(mapping)\n",
" #print('\\n\\n')\n",
- " return((list(set(argument_mappings)),left_over))"
+ " #################\n",
+ " heads = []\n",
+ " triples_part1, triples_part2 = get_graph_triples_old(parse_part1), get_graph_triples_old(parse_part2)\n",
+ " \n",
+ " for fill in filler:\n",
+ " fill = re.sub('[()]', '', replace_names(amr_dict[fill.replace(\"'s\",'')]).split('/ ')[1].split('\\n')[0])\n",
+ " \n",
+ " for triple in triples_part1:\n",
+ " \n",
+ " triple1 = (None,None)\n",
+ " if not '_of' in triple[1]:\n",
+ " if fill in triple[2]:\n",
+ " triple1 = triple\n",
+ " break\n",
+ " else:\n",
+ " if fill in triple[0]:\n",
+ " triple1 = triple\n",
+ " break\n",
+ " for triple in triples_part2:\n",
+ " triple2 = (None,None)\n",
+ " if not '-of' in triple[1]:\n",
+ " if fill in triple[2]:\n",
+ " triple2 = triple\n",
+ " break\n",
+ " else:\n",
+ " if fill in triple[0]:\n",
+ " triple2 = triple\n",
+ " break\n",
+ " if None not in triple1 and None not in triple2:\n",
+ " triple1 = (triple1[0].split('/ ')[1],triple1[1],rename_sent_index(edge[0]))\n",
+ " triple2 = (triple2[0].split('/ ')[1],triple2[1],rename_sent_index(edge[1]))\n",
+ " heads.append((triple1,triple2))\n",
+ " else:\n",
+ " left_over.append(annotation)\n",
+ " #print(triple1,triple2)\n",
+ " continue\n",
+ " return((list(set(argument_mappings)),left_over,heads))"
]
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "[(('3500_EMO_1:1', ':instance', '\"Germany\"'), ('3500_2:1', ':instance', '\"Germany\"'))]\n",
+ "[(('want-01', ':ARG0', 'f1'), ('be-located-at-91', ':ARG1', 's2'))]\n",
+ "[(('f1r0.1', ':instance', '\"Germany\"'), ('s2r0.1', ':instance', '\"Germany\"'))]\n",
"[]\n"
]
}
],
"source": [
- "argument_mapping, left_over = map_arguments(annotation, ('3500_EMO_1', '3500_2'))\n",
+ "argument_mapping, left_over, heads = map_arguments(annotation, ('3500_EMO_1', '3500_2'),0)\n",
+ "print(heads)\n",
"print(argument_mapping)\n",
"print(left_over)"
]
@@ -768,7 +862,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
@@ -777,131 +871,121 @@
},
{
"cell_type": "code",
- "execution_count": 16,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "(('3500_EVENT_3:3', ':instance', '\"France\"'), ('3500_0:6', ':instance', '\"France\"'))\n",
- "(('3500_EVENT_3:2', ':instance', '\"France\"'), ('3500_0:2', ':instance', '\"France\"'))\n",
- "(('3500_EVENT_3:3', ':instance', '\"Germany\"'), ('3500_0:3', ':instance', '\"Germany\"'))\n",
- "(('3500_EVENT_3:1', ':instance', '\"Max\"'), ('3500_0:1', ':instance', '\"Max\"'))\n"
- ]
- }
- ],
- "source": [
- "def get_argument_mappings(edge):\n",
- " annotations = graph.edges[edge]['annotations']\n",
- " argument_mappings = []\n",
- " for annotation in annotations:\n",
- " argument_mapping, left_over = map_arguments(annotation,edge)\n",
- " argument_mappings += argument_mapping\n",
- " #print(left_over)\n",
- " return(argument_mappings)\n",
- "\n",
- "edge = ('3500_EMO_0', '3500_0')\n",
- "edge = ('3500_EMO_1', '3500_2')\n",
- "edge = ('3500_EVENT_3', '3500_0')\n",
- "argument_mappings = get_argument_mappings(edge)\n",
- "for map in argument_mappings:\n",
- " print(map)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 37,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "(('d / drive-01', ':ARG4', 'c2 / \"France\"'), ('b / be-located-at-91', ':ARG2', 'c / \"France\"'))\n",
- "(('g / go-02', ':accompanier', 'p2 / \"Germany\"'), ('b / be-located-at-91', ':accompanier', 'p2 / \"Germany\"'))\n",
- "(('g / go-02', ':ARG4', 'c / \"France\"'), ('b / be-located-at-91', ':ARG2', 'c / \"France\"'))\n",
- "(('g / go-02', ':ARG0', 'p / \"Max\"'), ('b / be-located-at-91', ':ARG1', 'p / \"Max\"'))\n"
+ "(('e3r0.3', ':instance', '\"France\"'), ('s0r0.6', ':instance', '\"France\"'))\n",
+ "(('e3r1.1', ':instance', '\"Max\"'), ('s0r1.1', ':instance', '\"Max\"'))\n",
+ "(('e3r1.2', ':instance', '\"France\"'), ('s0r1.2', ':instance', '\"France\"'))\n",
+ "(('e3r1.3', ':instance', '\"Germany\"'), ('s0r1.3', ':instance', '\"Germany\"'))\n",
+ "(('drive-01', ':ARG4', 'e3'), ('be-located-at-91', ':ARG2', 's0'))\n",
+ "(('go-02', ':accompanier', 'e3'), ('be-located-at-91', ':accompanier', 's0'))\n",
+ "(('go-02', ':ARG4', 'e3'), ('be-located-at-91', ':ARG2', 's0'))\n",
+ "(('go-02', ':ARG0', 'e3'), ('be-located-at-91', ':ARG1', 's0'))\n"
]
}
],
"source": [
- "def get_argument_mappings(edge):\n",
+ "##################################\n",
+ "############# RUN ################\n",
+ "def get_argument_mappings(graph, edge):\n",
" annotations = graph.edges[edge]['annotations']\n",
" argument_mappings = []\n",
- " for annotation in annotations:\n",
- " argument_mapping, left_over = map_arguments(annotation)\n",
+ " heads = []\n",
+ " for i, annotation in enumerate(annotations):\n",
+ " if map_arguments(annotation,edge,i)==None:\n",
+ " continue\n",
+ " argument_mapping, left_over, head = map_arguments(annotation,edge,i)\n",
" argument_mappings += argument_mapping\n",
+ " heads += head\n",
" #print(left_over)\n",
- " return(argument_mappings)\n",
+ " return((list(set(argument_mappings)), list(set(heads))))\n",
"\n",
"edge = ('3500_EMO_0', '3500_0')\n",
"edge = ('3500_EMO_1', '3500_2')\n",
"edge = ('3500_EVENT_3', '3500_0')\n",
- "argument_mappings = get_argument_mappings(edge)\n",
- "for map in argument_mappings:\n",
- " print(map)"
+ "#edge = ('3500_EVENT_4', '3500_2')\n",
+ "argument_mappings, heads = get_argument_mappings(graph, edge)\n",
+ "for mapping in argument_mappings:\n",
+ " print(mapping)\n",
+ "for head in heads:\n",
+ " print(head)"
]
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "['Some Germans drive to France', 'Causes/Enables', 'Max who is a member of Some Germans is at France']\n",
- "['Max goes to France with Some Germans', 'Causes/Enables', 'Max is at France with Some Germans']\n",
- "36\n",
- "('3500_EVENT_3:1', ':instance', '\"Max\"')\n",
- "('3500_EVENT_3:2', ':instance', '\"France\"')\n",
- "('3500_0:0', ':ARG1', '3500_0:1')\n",
- "('3500_0:2', ':ARG0', '3500_0:1')\n",
- "('3500_0:3', ':quant', '3500_0:4')\n",
- "('3500_0:2', ':ARG1', '3500_0:3')\n",
- "('3500_0:2', ':ARG2', '3500_0:5')\n",
- "('3500_EVENT_3:2', ':instance', 'some')\n",
- "('3500_EVENT_3:1', ':quant', '3500_EVENT_3:2')\n",
- "('3500_0:0', ':ARG2', '3500_0:2')\n",
- "('3500_0:0', ':instance', 'be-located-at-91')\n",
- "('3500_0:4', ':instance', 'some')\n",
- "('3500_0:4', ':op2', '\"Germans\"')\n",
- "('3500_EVENT_3:3', ':instance', '\"France\"')\n",
- "('3500_EVENT_3:0', ':instance', 'go-02')\n",
- "('3500_EVENT_3:3', ':quant', '3500_EVENT_3:4')\n",
- "('3500_0:5', ':instance', 'member')\n",
- "('3500_EVENT_3:1', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:0', ':accompanier', '3500_EVENT_3:3')\n",
- "('3500_0:4', ':op1', '\"Some\"')\n",
- "('3500_0:0', ':accompanier', '3500_0:3')\n",
- "('3500_0:3', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:0', ':ARG0', '3500_EVENT_3:1')\n",
- "('3500_EVENT_3:3', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:4', ':instance', 'some')\n",
- "('3500_EVENT_3:0', ':ARG4', '3500_EVENT_3:3')\n",
- "('3500_0:3', ':name', '3500_0:4')\n",
- "('3500_EVENT_3:0', ':instance', 'drive-01')\n",
- "('3500_0:0', ':ARG2', '3500_0:6')\n",
- "('3500_0:2', ':instance', 'have-org-role-91')\n",
- "('3500_0:3', ':instance', 'organization')\n",
- "('3500_EVENT_3:0', ':ARG4', '3500_EVENT_3:2')\n",
- "('3500_0:4', ':instance', 'name')\n",
- "('3500_0:2', ':instance', '\"France\"')\n",
- "('3500_0:1', ':instance', '\"Max\"')\n",
- "('3500_0:6', ':instance', '\"France\"')\n"
+ "40\n",
+ "('s0r0.4', ':op1', '\"Some\"')\n",
+ "('s0r0.2', ':instance', 'have-org-role-91')\n",
+ "('s0r0.2', ':ARG2', 's0r0.5')\n",
+ "('e3r0.2', ':instance', 'some')\n",
+ "('e3r1.1', ':instance', '\"Max\"')\n",
+ "('e3r1.3', ':instance', '\"Germany\"')\n",
+ "('s0r0.2', ':ARG0', 's0r0.1')\n",
+ "('s0r1.0', ':ARG1', 's0r1.1')\n",
+ "('s0r0.4', ':op2', '\"Germans\"')\n",
+ "('s0r0.0', ':ARG2', 's0r0.6')\n",
+ "('s0r0.0', ':instance', 'be-located-at-91')\n",
+ "('e3r1.0', ':instance', 'go-02')\n",
+ "('s0r1.1', ':instance', '\"Max\"')\n",
+ "('e3r1.4', ':instance', 'some')\n",
+ "('s0r0.0', ':ARG1', 's0r0.1')\n",
+ "('e3r0.1', ':quant', 'e3r0.2')\n",
+ "('s0r1.2', ':instance', '\"France\"')\n",
+ "('e3r0.0', ':ARG4', 'e3r0.3')\n",
+ "('s0r1.4', ':instance', 'some')\n",
+ "('e3r1.3', ':quant', 'e3r1.4')\n",
+ "('s0r0.3', ':instance', 'organization')\n",
+ "('s0r0.1', ':instance', '\"Max\"')\n",
+ "('e3r0.1', ':instance', '\"Germany\"')\n",
+ "('s0r1.3', ':quant', 's0r1.4')\n",
+ "('e3r0.0', ':instance', 'drive-01')\n",
+ "('s0r0.5', ':instance', 'member')\n",
+ "('s0r0.6', ':instance', '\"France\"')\n",
+ "('s0r1.3', ':instance', '\"Germany\"')\n",
+ "('e3r1.0', ':ARG4', 'e3r1.2')\n",
+ "('e3r0.3', ':instance', '\"France\"')\n",
+ "('s0r0.2', ':ARG1', 's0r0.3')\n",
+ "('e3r1.0', ':accompanier', 'e3r1.3')\n",
+ "('s0r1.0', ':accompanier', 's0r1.3')\n",
+ "('e3r0.0', ':ARG0', 'e3r0.1')\n",
+ "('e3r1.2', ':instance', '\"France\"')\n",
+ "('s0r0.3', ':name', 's0r0.4')\n",
+ "('s0r1.0', ':instance', 'be-located-at-91')\n",
+ "('e3r1.0', ':ARG0', 'e3r1.1')\n",
+ "('s0r0.4', ':instance', 'name')\n",
+ "('s0r1.0', ':ARG2', 's0r1.2')\n"
]
}
],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"def unite_graph_triples(edge):\n",
" unite_triples = []\n",
- " for annotation in graph.edges[edge]['annotations']:\n",
+ " for i, annotation in enumerate(graph.edges[edge]['annotations']):\n",
+ " if annotation['2parse'][0]==None or annotation['2parse'][1]==None:\n",
+ " continue\n",
+ " if annotation['2parse'][0][0]==None or annotation['2parse'][0][1]==None or annotation['2parse'][1][0]==None or annotation['2parse'][1][1]==None:\n",
+ " continue\n",
" general_rule = annotation['2parse'][1]\n",
- " print(general_rule)\n",
+ " #print(general_rule)\n",
" part1, part2 = general_rule[0], general_rule[2]\n",
- " unite_triples += get_graph_triples(replace_names(amr_dict[part1]), edge[0])+get_graph_triples(replace_names(amr_dict[part2]), edge[1])\n",
+ " graph1, graph2 = get_graph_triples(replace_names(amr_dict[part1]), edge[0],i), get_graph_triples(replace_names(amr_dict[part2]), edge[1],i)\n",
+ " unite_triples += graph1.triples + graph2.triples\n",
+ " #unite_triples += [('TOPr'+str(i), ':instance', 'cause-01'), ('TOPr'+str(i), ':ARG0', graph1.top), ('TOPr'+str(i), ':ARG1', graph2.top)]\n",
+ " #print(graph1.top, graph2.top)\n",
" unite_triples = list(set(unite_triples))\n",
" return(unite_triples)\n",
"unite_triples = unite_graph_triples(edge)\n",
@@ -923,69 +1007,88 @@
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "33\n",
- "('3500_0:0', ':accompanier', 'EVENT_3:3&0:3')\n",
- "('EVENT_3:2&0:2', ':instance', 'some')\n",
- "('EVENT_3:3&0:3', ':instance', '\"Germany\"')\n",
- "('3500_EVENT_3:3&0:6', ':instance', '\"France\"')\n",
- "('3500_EVENT_3:3&0:6', ':quant', '3500_EVENT_3:4')\n",
- "('EVENT_3:1&0:1', ':quant', 'EVENT_3:2&0:2')\n",
- "('3500_0:0', ':instance', 'be-located-at-91')\n",
- "('3500_0:0', ':ARG1', 'EVENT_3:1&0:1')\n",
- "('3500_0:4', ':instance', 'some')\n",
- "('EVENT_3:2&0:2', ':ARG2', '3500_0:5')\n",
- "('3500_0:4', ':op2', '\"Germans\"')\n",
- "('3500_EVENT_3:0', ':instance', 'go-02')\n",
- "('EVENT_3:3&0:3', ':name', '3500_0:4')\n",
- "('EVENT_3:1&0:1', ':instance', '\"Germany\"')\n",
- "('3500_0:5', ':instance', 'member')\n",
- "('3500_EVENT_3:3&0:6', ':instance', '\"Germany\"')\n",
- "('3500_0:4', ':op1', '\"Some\"')\n",
- "('3500_EVENT_3:0', ':accompanier', '3500_EVENT_3:3&0:6')\n",
- "('EVENT_3:2&0:2', ':ARG0', 'EVENT_3:1&0:1')\n",
- "('EVENT_3:3&0:3', ':instance', 'organization')\n",
- "('3500_0:0', ':ARG2', '3500_EVENT_3:3&0:6')\n",
- "('3500_EVENT_3:4', ':instance', 'some')\n",
- "('3500_EVENT_3:0', ':ARG0', 'EVENT_3:1&0:1')\n",
- "('3500_EVENT_3:0', ':ARG4', '3500_EVENT_3:3&0:6')\n",
- "('3500_EVENT_3:0', ':instance', 'drive-01')\n",
- "('EVENT_3:3&0:3', ':quant', '3500_0:4')\n",
- "('3500_0:0', ':ARG2', 'EVENT_3:2&0:2')\n",
- "('EVENT_3:2&0:2', ':instance', 'have-org-role-91')\n",
- "('3500_EVENT_3:0', ':ARG4', 'EVENT_3:2&0:2')\n",
- "('3500_0:4', ':instance', 'name')\n",
- "('EVENT_3:2&0:2', ':instance', '\"France\"')\n",
- "('EVENT_3:2&0:2', ':ARG1', 'EVENT_3:3&0:3')\n",
- "('EVENT_3:1&0:1', ':instance', '\"Max\"')\n"
+ "36\n",
+ "('s0r0.4', ':op1', '\"Some\"')\n",
+ "('s0r0.2', ':instance', 'have-org-role-91')\n",
+ "('s0r0.2', ':ARG2', 's0r0.5')\n",
+ "('s0r0.0', ':ARG2', 'e3r0.3-s0r0.6')\n",
+ "('e3r1.2-s0r1.2', ':instance', '\"France\"')\n",
+ "('e3r0.2', ':instance', 'some')\n",
+ "('s0r0.4', ':instance', 'name')\n",
+ "('e3r1.1-s0r1.1', ':instance', '\"Max\"')\n",
+ "('s0r0.2', ':ARG0', 's0r0.1')\n",
+ "('e3r0.3-s0r0.6', ':instance', '\"France\"')\n",
+ "('e3r1.0', ':ARG4', 'e3r1.2-s0r1.2')\n",
+ "('s0r0.4', ':op2', '\"Germans\"')\n",
+ "('s0r0.0', ':instance', 'be-located-at-91')\n",
+ "('e3r1.0', ':instance', 'go-02')\n",
+ "('e3r0.0', ':ARG4', 'e3r0.3-s0r0.6')\n",
+ "('e3r1.3-s0r1.3', ':quant', 's0r1.4')\n",
+ "('s0r1.0', ':ARG1', 'e3r1.1-s0r1.1')\n",
+ "('e3r1.0', ':ARG0', 'e3r1.1-s0r1.1')\n",
+ "('e3r1.4', ':instance', 'some')\n",
+ "('s0r0.0', ':ARG1', 's0r0.1')\n",
+ "('e3r0.1', ':quant', 'e3r0.2')\n",
+ "('s0r1.4', ':instance', 'some')\n",
+ "('e3r1.3-s0r1.3', ':quant', 'e3r1.4')\n",
+ "('e3r1.3-s0r1.3', ':instance', '\"Germany\"')\n",
+ "('s0r0.3', ':instance', 'organization')\n",
+ "('s0r1.0', ':accompanier', 'e3r1.3-s0r1.3')\n",
+ "('s0r0.1', ':instance', '\"Max\"')\n",
+ "('e3r0.1', ':instance', '\"Germany\"')\n",
+ "('e3r0.0', ':instance', 'drive-01')\n",
+ "('s0r0.5', ':instance', 'member')\n",
+ "('s0r0.2', ':ARG1', 's0r0.3')\n",
+ "('e3r0.0', ':ARG0', 'e3r0.1')\n",
+ "('s0r0.3', ':name', 's0r0.4')\n",
+ "('s0r1.0', ':instance', 'be-located-at-91')\n",
+ "('s0r1.0', ':ARG2', 'e3r1.2-s0r1.2')\n",
+ "('e3r1.0', ':accompanier', 'e3r1.3-s0r1.3')\n"
]
}
],
"source": [
+ "##################################\n",
+ "############# RUN ################\n",
"def rename_variables(unite_triples, argument_mappings):\n",
+ " merged_instances = []\n",
+ " delete = []\n",
+ " rename = {}\n",
" for mapping in argument_mappings:\n",
+ " delete.append(mapping[0])\n",
+ " delete.append(mapping[1])\n",
+ " #print(mapping)\n",
" var1 = mapping[0][0]\n",
" var2 = mapping[1][0]\n",
- " merged_var_name = '_'.join(mapping[0][0].split('_')[1:])+'&'+ '_'.join(mapping[1][0].split('_')[1:])\n",
+ " merged_var_name = mapping[0][0]+'-'+ mapping[1][0]\n",
+ " #merged_var_name = '_'.join(mapping[0][0].split('_')[1:])+'&'+ '_'.join(mapping[1][0].split('_')[1:])\n",
" #print(merged_var_name)\n",
+ " rename[var1] = merged_var_name\n",
+ " rename[var2] = merged_var_name \n",
" merged_instance = (merged_var_name, mapping[0][1], mapping[0][2])\n",
- " #print(merged_instance)\n",
- "\n",
- " for i, triple in enumerate(unite_triples):\n",
- " if triple == mapping[0] or triple == mapping[1]:\n",
- " unite_triples[i] = merged_instance\n",
- " elif var1 in triple or var2 in triple:\n",
- " new_triple = eval(str(triple).replace(var1, merged_var_name).replace(var2, merged_var_name))\n",
- " #print(new_triple)\n",
- " #print(type(new_triple))\n",
- " unite_triples[i] = new_triple\n",
- " unite_triples = list(set(unite_triples))\n",
+ " merged_instances.append(merged_instance)\n",
+ " #print('MERGE INSTANCES:')\n",
+ " #print(merged_instances)\n",
+ " #print('DELETE:')\n",
+ " #print(delete)\n",
+ " unite_triples = [triple for triple in unite_triples if triple not in delete]\n",
+ " for i, triple in enumerate(unite_triples):\n",
+ " if triple[0] in rename.keys():\n",
+ " triple = (rename[triple[0]],triple[1],triple[2])\n",
+ " if triple[2] in rename.keys():\n",
+ " triple = (triple[0],triple[1],rename[triple[2]])\n",
+ " elif triple[2] in rename.keys():\n",
+ " triple = (triple[0],triple[1],rename[triple[2]])\n",
+ " unite_triples[i] = triple\n",
+ " unite_triples = unite_triples + merged_instances\n",
+ " unite_triples = list(set(unite_triples))\n",
" return(unite_triples)\n",
"renamed_triples = rename_variables(unite_triples, argument_mappings)\n",
"\n",
@@ -996,75 +1099,1774 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 65,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "26\n",
+ "('s0r0.4', ':op1', '\"Some\"')\n",
+ "('s0r0.2', ':instance', 'have-org-role-91')\n",
+ "('s0r0.2', ':ARG2', 's0r0.5')\n",
+ "('e3r0.0', ':ARG0', 'e3r1.3-s0r1.3-e3r0.1')\n",
+ "('s0r0.2', ':ARG0', 'e3r1.1-s0r1.1-s0r0.1')\n",
+ "('s0r0.4', ':op2', '\"Germans\"')\n",
+ "('e3r1.3-s0r1.3-e3r0.1', ':instance', '\"Germany\"')\n",
+ "('s0r0.0-s0r1.0', ':ARG2', 'e3r1.2-s0r1.2-e3r0.3-s0r0.6')\n",
+ "('e3r1.0', ':instance', 'go-02')\n",
+ "('e3r1.0', ':ARG0', 'e3r1.1-s0r1.1-s0r0.1')\n",
+ "('s0r0.0-s0r1.0', ':ARG1', 'e3r1.1-s0r1.1-s0r0.1')\n",
+ "('e3r1.2-s0r1.2-e3r0.3-s0r0.6', ':instance', '\"France\"')\n",
+ "('e3r1.3-s0r1.3-e3r0.1', ':quant', 'e3r0.2-e3r1.4-s0r1.4')\n",
+ "('e3r0.2-e3r1.4-s0r1.4', ':instance', 'some')\n",
+ "('s0r0.3', ':instance', 'organization')\n",
+ "('e3r1.1-s0r1.1-s0r0.1', ':instance', '\"Max\"')\n",
+ "('s0r0.0-s0r1.0', ':instance', 'be-located-at-91')\n",
+ "('s0r0.0-s0r1.0', ':accompanier', 'e3r1.3-s0r1.3-e3r0.1')\n",
+ "('e3r0.0', ':instance', 'drive-01')\n",
+ "('s0r0.5', ':instance', 'member')\n",
+ "('e3r0.0', ':ARG4', 'e3r1.2-s0r1.2-e3r0.3-s0r0.6')\n",
+ "('s0r0.2', ':ARG1', 's0r0.3')\n",
+ "('e3r1.0', ':ARG4', 'e3r1.2-s0r1.2-e3r0.3-s0r0.6')\n",
+ "('s0r0.3', ':name', 's0r0.4')\n",
+ "('e3r1.0', ':accompanier', 'e3r1.3-s0r1.3-e3r0.1')\n",
+ "('s0r0.4', ':instance', 'name')\n"
+ ]
+ }
+ ],
+ "source": [
+ "##################################\n",
+ "############# RUN ################\n",
+ "def merge_instances_between_multiple_rules(triples):\n",
+ " # get instances to merge\n",
+ " instance_dict = {}\n",
+ " for triple in triples:\n",
+ " if triple[1]==':instance' or '\"' in triple[2]:\n",
+ " if triple[2] not in instance_dict.keys():\n",
+ " instance_dict[triple[2]] = [triple[0]]\n",
+ " else:\n",
+ " instance_dict[triple[2]] += [triple[0]]\n",
+ " #print(instance_dict)\n",
+ " rename = {}\n",
+ " for instance in instance_dict.keys():\n",
+ " new_var = '-'.join(instance_dict[instance])\n",
+ " for old_var in instance_dict[instance]:\n",
+ " rename[old_var] = new_var\n",
+ " #print(rename)\n",
+ " \n",
+ " # merge instances variable names \n",
+ " new_triples = []\n",
+ " #delete = []\n",
+ " \n",
+ " for triple in triples:\n",
+ " if triple[0] in rename.keys():\n",
+ " #print(triple)\n",
+ " #delete.append(triple)\n",
+ " new_triple = (rename[triple[0]], triple[1], triple[2])\n",
+ " #new_triples.append(new_triple)\n",
+ " #print(new_triple)\n",
+ " if triple[2] in rename.keys():#instance_dict[instance]:\n",
+ " #delete.append(triple)\n",
+ " new_triple = (new_triple[0], triple[1], rename[triple[2]])\n",
+ " new_triples.append(new_triple)\n",
+ " #delete.append(triple)\n",
+ " elif triple[2] in rename.keys():#instance_dict[instance]:\n",
+ " #delete.append(triple)\n",
+ " new_triple = (triple[0], triple[1], rename[triple[2]])\n",
+ " new_triples.append(new_triple)\n",
+ " else:\n",
+ " new_triples.append(triple)\n",
+ " \"\"\"\n",
+ " for instance in instance_dict.keys():\n",
+ " if len(instance_dict[instance])==1:\n",
+ " #print(instance)\n",
+ " continue\n",
+ " new_var_name = '-'.join(instance_dict[instance])\n",
+ " #print(instance, new_var_name)\n",
+ " #for var in instance_dict[instance]:\n",
+ " for triple in triples:\n",
+ " if triple[0] in instance_dict[instance]:\n",
+ " #print(triple)\n",
+ " delete.append(triple)\n",
+ " new_triple = (new_var_name, triple[1], triple[2])\n",
+ " new_triples.append(new_triple)\n",
+ " #print(new_triple)\n",
+ " elif triple[2] in instance_dict[instance]:\n",
+ " delete.append(triple)\n",
+ " new_triple = (triple[0], triple[1], new_var_name)\n",
+ " new_triples.append(new_triple)\n",
+ " \"\"\"\n",
+ " #merged_triples = [triple for triple in triples if triple not in delete]\n",
+ " #merged_triples += new_triples\n",
+ " merged_triples = list(set(new_triples))\n",
+ " return(merged_triples)\n",
+ "super_merged_triples = merge_instances_between_multiple_rules(renamed_triples)\n",
+ "print(len(super_merged_triples))\n",
+ "for triple in super_merged_triples:\n",
+ " print(triple)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 66,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "('have-org-role-91', ':ARG2', 'member', 's0', 's0')\n",
+ "('drive-01', ':ARG0', '\"Germany\"', 'e3', 'e3-s0')\n",
+ "('have-org-role-91', ':ARG0', '\"Max\"', 's0', 'e3-s0')\n",
+ "('be-located-at-91', ':ARG2', '\"France\"', 's0', 'e3-s0')\n",
+ "('go-02', ':ARG0', '\"Max\"', 'e3', 'e3-s0')\n",
+ "('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e3-s0')\n",
+ "('\"Germany\"', ':quant', 'some', 'e3-s0', 'e3-s0')\n",
+ "('be-located-at-91', ':accompanier', '\"Germany\"', 's0', 'e3-s0')\n",
+ "('drive-01', ':ARG4', '\"France\"', 'e3', 'e3-s0')\n",
+ "('have-org-role-91', ':ARG1', 'organization', 's0', 's0')\n",
+ "('go-02', ':ARG4', '\"France\"', 'e3', 'e3-s0')\n",
+ "('organization', ':name', 'name', 's0', 's0')\n",
+ "('go-02', ':accompanier', '\"Germany\"', 'e3', 'e3-s0')\n"
+ ]
+ }
+ ],
+ "source": [
+ "##################################\n",
+ "############# RUN ################\n",
+ "def remove_vars(triples):\n",
+ " instances = [triple for triple in triples if triple[1]==':instance' or '\"' in triple[2]]\n",
+ " edges = [triple for triple in triples if triple not in instances]\n",
+ " replaced_triples = []\n",
+ " check = []\n",
+ " replacers = {}\n",
+ " for inst in instances:\n",
+ " var = inst[0]\n",
+ " concept = inst[2]\n",
+ " replacers[var] = concept\n",
+ " #print(inst)\n",
+ " #print('\\n')\n",
+ " #[print(item) for item in replacers.items()]\n",
+ " #print('\\n')\n",
+ " for edge in edges:\n",
+ " #print(edge)\n",
+ " try:\n",
+ " sent_1 = '-'.join(list(set([s[:2] for s in edge[0].split('-')])))\n",
+ " sent_2 = '-'.join(list(set([s[:2] for s in edge[2].split('-')])))\n",
+ " new_edge = (replacers[edge[0]], edge[1], replacers[edge[2]], sent_1, sent_2)\n",
+ " except:\n",
+ " sent_1 = '-'.join([s[:2] for s in edge[0].split('-')])\n",
+ " new_edge = (replacers[edge[0]], edge[1], edge[2], sent_1, sent_1)\n",
+ " replaced_triples.append(new_edge)\n",
+ " return(replaced_triples)\n",
+ "#print(rename_sent_index(edge[0]))\n",
+ "concept_triples = remove_vars(super_merged_triples)\n",
+ "for triple in concept_triples:\n",
+ " print(triple)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[('stand-01', ':ARG0', 'e4'), ('feed-01', ':ARG0', 's2')], [('love-01', ':ARG2', 's2'), ('feed-01', ':ARG2', 's2'), ('come-01', ':ARG1', 'e4')]]\n"
+ ]
+ }
+ ],
+ "source": [
+ "#print(heads)\n",
+ "heads = [(('stand-01', ':ARG0', 'e4'), ('feed-01', ':ARG0', 's2')), \n",
+ " (('come-01', ':ARG1', 'e4'), ('love-01', ':ARG2', 's2')),\n",
+ " (('come-01', ':ARG1', 'e4'), ('feed-01', ':ARG2', 's2'))]\n",
+ "\n",
+ "def make_argument_chains(heads):\n",
+ " arg_map = [[el1,el2] for (el1,el2) in heads]\n",
+ " chains = []\n",
+ " for mapping in arg_map:\n",
+ " #print(mapping)\n",
+ " done = False\n",
+ " for chain in chains:\n",
+ " if mapping[0] in chain or mapping[1] in chain:\n",
+ " chain += mapping\n",
+ " done = True\n",
+ " break\n",
+ " if done == False:\n",
+ " chains.append(mapping)\n",
+ "\n",
+ " chains = [list(set(chain)) for chain in chains]\n",
+ " return(chains)\n",
+ "\n",
+ "chains = make_argument_chains(heads)\n",
+ "print(chains) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_g_nodes(chains, concept_triples):\n",
+ " merges = []\n",
+ " for chain in chains:\n",
+ " merge = []\n",
+ " for triple in chain:\n",
+ " #print(triple)\n",
+ " for concept_triple in concept_triples:\n",
+ " #print(concept_triple)\n",
+ " if concept_triple[0]==triple[0] and concept_triple[1]==triple[1] and triple[2] in concept_triple[4]:\n",
+ " merge.append(concept_triple)\n",
+ " \"\"\" \n",
+ " for edge in concept_triples.keys():\n",
+ " if triple[2] in str(edge):\n",
+ " delete = []\n",
+ " for instance in concept_triples[edge]:\n",
+ " if triple[0]==instance[0] and triple[1]==instance[1]:\n",
+ " delete.append(instance)\n",
+ " instance = (instance[0], instance[1], instance[2], triple[2])\n",
+ " merge.append(instance)\n",
+ " #concept_triples[edge] = [instance for instance in concept_triples[edge] if instance not in delete]\n",
+ " \"\"\"\n",
+ " merges.append(merge)\n",
+ " merges = [list(set(merge)) for merge in merges]\n",
+ " return((merges, concept_triples))\n",
+ "#merges = get_g_nodes(chains, concept_triples)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ " '2parse': \n",
+ " [['A giraffe comes to the fence', 'Causes/Enables', 'Addie feeds the giraffe'], \n",
+ " ['crown comes up to throne that Max is standing by', 'Causes/Enables', 'Max feeds crown']]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 111,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def make_abstract_graph(graph):\n",
+ " \n",
+ " arg_mappings = []\n",
+ " concept_triple_edges = []\n",
+ " for edge in list(graph.edges):\n",
+ " if '_S' in edge[0]:\n",
+ " continue\n",
+ " argument_mappings, heads = get_argument_mappings(graph, edge)\n",
+ " arg_mappings += heads\n",
+ " unite_triples = unite_graph_triples(edge)\n",
+ " renamed_triples = rename_variables(unite_triples, argument_mappings)\n",
+ " super_merged_triples = merge_instances_between_multiple_rules(renamed_triples)\n",
+ " #for t in super_merged_triples:\n",
+ " #print(t)\n",
+ " #print('#'*20)\n",
+ " concept_triples = remove_vars(super_merged_triples)\n",
+ " concept_triple_edges += concept_triples\n",
+ " #edge = (rename_sent_index(edge[0]), rename_sent_index(edge[1]))\n",
+ " #concept_triple_edges[edge] = concept_triples\n",
+ " #print(arg_mappings)\n",
+ " chains = make_argument_chains(arg_mappings)\n",
+ " #concept_triple_edges = list(set(concept_triple_edges))\n",
+ " merges, concept_triples_edges = get_g_nodes(chains, concept_triple_edges)\n",
+ " #for chain in chains:\n",
+ " #print(chain)\n",
+ " #for i, merge in enumerate(merges):\n",
+ " #print(merge)\n",
+ " #print(chains[i])\n",
+ " #print('-'*10)\n",
+ " #for el in merge:\n",
+ " #print('#'*20)\n",
+ " #for e in concept_triples_edges:\n",
+ " #print(e)\n",
+ " #for el in concept_triples_edges[e]:\n",
+ " #print(el)\n",
+ " #print(concept_triples_edges)\n",
+ " return(merges, concept_triples_edges)\n",
+ "\n",
+ "file = '3500_c14cdda2-738c-4174-94fc-6831c7c33def.pkl'\n",
+ "with open('../story_graphs/'+file, 'rb') as f:\n",
+ " graph = pickle.load(f)\n",
+ "merges, concept_triples_edges = make_abstract_graph(graph)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 134,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import networkx as nx\n",
+ "\n",
+ "def add_node_to(graph, node, index, concept_triple):\n",
+ " \n",
+ " if not '-' in index:\n",
+ " node_name = node+'_'+index\n",
+ " if node_name not in list(graph.nodes):\n",
+ " graph.add_node(node_name)\n",
+ " return(graph, node_name)\n",
+ " else:\n",
+ " sents = index.split('-')\n",
+ " if len(sents)>2:\n",
+ " sents = list(set(sents))\n",
+ " if len(sents) == 1:\n",
+ " sents.append(sents[0])\n",
+ " #print('HELP')\n",
+ " #print(sents)\n",
+ " for n in graph.nodes:\n",
+ " if '_G' in n:\n",
+ " if concept_triple in graph.nodes[n]['triples'] and sents[0] in graph.nodes[n]['sentences']:\n",
+ " if node in graph.nodes[n]['representations'] and sents[1] in graph.nodes[n]['sentences']:\n",
+ " return(graph, n)\n",
+ " \n",
+ " node_name = node+'_'+index\n",
+ " if node_name not in list(graph.nodes):\n",
+ " graph.add_node(node_name)\n",
+ " return(graph, node_name)\n",
+ " \n",
+ " \n",
+ "\n",
+ "def craete_graph(merges, concept_triples):\n",
+ " graph = nx.DiGraph()\n",
+ " for i, merge in enumerate(merges):\n",
+ " \n",
+ " sentences = []\n",
+ " representations = []\n",
+ " triples = []\n",
+ " for triple in merge:\n",
+ " triples.append(triple)\n",
+ " sentences += triple[4].split('-')\n",
+ " representations.append(triple[2].replace('\"',''))\n",
+ " sentences = list(set(sentences))\n",
+ " representations = list(set(representations))\n",
+ " graph.add_node('_G'+str(i), sentences=sentences, representations=representations, triples=triples)\n",
+ " \n",
+ " for concept_triple in concept_triples:\n",
+ " #print(concept_triple)\n",
+ " #print(type(concept_triple))\n",
+ " node1, index1 = concept_triple[0].replace('\"',''), concept_triple[3]\n",
+ " node2, index2 = concept_triple[2].replace('\"',''), concept_triple[4]\n",
+ " rel = concept_triple[1]\n",
+ " \n",
+ " #try:\n",
+ " graph, node_name1 = add_node_to(graph, node1, index1, concept_triple)\n",
+ " graph, node_name2 = add_node_to(graph, node2, index2, concept_triple)\n",
+ " #except:\n",
+ " #print(concept_triple, 'FUCK')\n",
+ " if (node_name1, node_name2) in list(graph.edges):\n",
+ " if rel not in graph.edges[(node_name1, node_name2)]['relation']:\n",
+ " graph.edges[(node_name1, node_name2)]['relation'].append(rel)\n",
+ " else:\n",
+ " graph.add_edge(node_name1, node_name2, relation=[rel])\n",
+ " \n",
+ " return(graph)\n",
+ "merged_story_graph = craete_graph(merges, concept_triples_edges)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "IndexError",
+ "evalue": "list index out of range",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m/tmp/ipykernel_5030/2172462540.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'../story_graphs/'\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mgraph\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0mmerges\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcept_triples_edges\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmake_abstract_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0mmerged_story_graph\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcraete_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmerges\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconcept_triples_edges\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'../story_graphs_merged_general/'\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/tmp/ipykernel_5030/1194400793.py\u001b[0m in \u001b[0;36mmake_abstract_graph\u001b[0;34m(graph)\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m'_S'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0medge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0margument_mappings\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheads\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_argument_mappings\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgraph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medge\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0marg_mappings\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mheads\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0munite_triples\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0munite_graph_triples\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/tmp/ipykernel_5030/2359909504.py\u001b[0m in \u001b[0;36mget_argument_mappings\u001b[0;34m(graph, edge)\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mheads\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mannotation\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotations\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mmap_arguments\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 9\u001b[0m \u001b[0;32mcontinue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0margument_mapping\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mleft_over\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhead\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmap_arguments\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m/tmp/ipykernel_5030/1262142080.py\u001b[0m in \u001b[0;36mmap_arguments\u001b[0;34m(annotation, edge, rule_index)\u001b[0m\n\u001b[1;32m 101\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 102\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtriple1\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtriple2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 103\u001b[0;31m \u001b[0mtriple1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtriple1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/ '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtriple1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrename_sent_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 104\u001b[0m \u001b[0mtriple2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtriple2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/ '\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtriple2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mrename_sent_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0medge\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 105\u001b[0m \u001b[0mheads\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtriple1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mtriple2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mIndexError\u001b[0m: list index out of range"
+ ]
+ }
+ ],
+ "source": [
+ "topics_0 = topics['0']\n",
+ "topics_1 = topics['1']\n",
+ "topics_6 = topics['6']\n",
+ "\n",
+ "for file in topics_1:\n",
+ " with open('../story_graphs/'+file, 'rb') as f:\n",
+ " graph = pickle.load(f)\n",
+ " merges, concept_triples_edges = make_abstract_graph(graph)\n",
+ " merged_story_graph = craete_graph(merges, concept_triples_edges)\n",
+ " with open('../story_graphs_merged_general/'+file, 'wb') as f:\n",
+ " pickle.dump(merged_story_graph, f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "193\n",
+ "208\n",
+ "_G0\n",
+ "{'sentences': ['l2', 'p1', 's3', 'e4', 'p3', 'f1', 'e8', 'e0', 'f8', 'p2', 'f0', 'f3', 'o2', 'o3', 'l1', 'e1', 'e9', 'f6', 's1', 'f5', 's0', 'l0', 'e3', 'e2', 'f2', 's4', 's2'], 'representations': ['Germany', 'Max'], 'triples': [('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2-s2'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f5-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'e9-s0'), ('pull-01', ':ARG0', '\"Max\"', 's2', 's2-f1'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'f2-s0'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'p2-s2'), ('pick-01', ':ARG0', '\"Max\"', 's2', 'p2-s2'), ('pull-01', ':ARG0', '\"Max\"', 's2', 's2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e3-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's0-s3'), ('feel-01', ':ARG0', '\"Max\"', 'f3', 's2-f3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's0-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 's0-p1'), ('be-located-at-91', ':ARG1', '\"Max\"', 'l2-s0', 'l2-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f8-s0'), ('feed-01', ':ARG0', '\"Max\"', 'f1', 's2-f1'), ('have-degree-91', ':ARG1', '\"Max\"', 'e8', 'e8-s3'), ('want-01', ':ARG0', '\"Max\"', 'f1', 's2-f1'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f0-s0'), ('crown-01', ':ARG1', '\"Max\"', 's2', 's2-f1'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-f3'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s2'), ('crown-01', ':ARG1', '\"Max\"', 's2-e0', 's2-e0'), ('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2'), ('pick-01', ':ARG0', '\"Max\"', 's2', 'e2-s2'), ('decide-01', ':ARG0', '\"Max\"', 'e0', 's2-e0'), ('surprise-01', ':ARG1', '\"Max\"', 'f6', 'f6-s3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's4-s0'), ('pull-01', ':ARG0', '\"Max\"', 's2', 'e2-s2'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'p3-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s1'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'l0-s3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'l1-s3'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's1-s0'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'e4-s2'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'o2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e1-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'o3-s0'), ('feed-01', ':ARG0', '\"Max\"', 's4', 's4-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's2-s0'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e8-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l2-s0', 'l2-s0'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-s0')]}\n",
+ "----------\n",
+ "_G1\n",
+ "{'sentences': ['l0', 'e8', 'l1', 'e1', 'f6', 's3', 's0'], 'representations': ['Max'], 'triples': [('surprise-01', ':ARG1', '\"Max\"', 's3', 'l1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 'f6', 'f6-s3'), ('near-02', ':ARG1', '\"Max\"', 'l0', 'l0-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'e8-s3'), ('near-02', ':ARG1', '\"Max\"', 'l1', 'l1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's3'), ('feed-01', ':ARG0', '\"Max\"', 'e1', 'e1-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 's0-s3'), ('surprise-01', ':ARG1', '\"Max\"', 's3', 'l0-s3')]}\n",
+ "----------\n",
+ "_G2\n",
+ "{'sentences': ['e2', 'e1', 'e6', 's4', 'f4', 'f1', 'p0'], 'representations': ['crown', 'throne', 'Kim', 'Max'], 'triples': [('eat-01', ':ARG0', 'crown', 's4', 's4-p0'), ('eat-01', ':ARG0', '\"Max\"', 'e1', 'e1-s4'), ('crown-01', ':ARG1', '\"Kim\"', 'e6-s4', 'e6-s4'), ('throne', ':mod', 'crown', 'e2-s4', 'e2-s4'), ('possess-01', ':ARG0', 'throne', 'p0', 'p0'), ('crown-01', ':ARG1', '\"Max\"', 's4', 's4-f4'), ('crown-01', ':ARG1', '\"Max\"', 's4', 'f1-s4'), ('crown-01', ':ARG1', '\"Max\"', 'e1-s4', 'e1-s4'), ('possess-01', ':ARG0', 'crown', 'p0', 's4-p0'), ('possess-01', ':ARG0', '\"Max\"', 'p0', 's4-p0'), ('crown-01', ':ARG1', '\"Max\"', 's4-p0', 's4-p0'), ('eat-01', ':ARG0', 'crown', 's4', 'e2-s4')]}\n",
+ "----------\n",
+ "_G3\n",
+ "{'sentences': ['e2', 'e1', 's4', 's1', 's2', 'p0'], 'representations': ['crown', 'throne', 'grass', 'crown-01'], 'triples': [('eat-01', ':ARG1', 'crown-01', 'e1', 'e1-s4'), ('eat-01', ':ARG1', 'throne', 's4', 'e2-s4'), ('come-up-11', ':ARG1', 'crown', 's1', 'e2-s1'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2-s2'), ('possess-01', ':ARG1', 'throne', 'p0', 's4-p0'), ('eat-01', ':ARG1', 'throne', 's4', 's4-p0'), ('possess-01', ':ARG1', 'grass', 'p0', 's4-p0'), ('possess-01', ':ARG1', 'crown-01', 'p0', 's4-p0'), ('feed-01', ':ARG2', 'throne', 'e2', 'e2-s2'), ('come-up-11', ':ARG1', 'crown', 's1', 's1'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2-s1'), ('feed-01', ':ARG2', 'throne', 'e2', 'e2-s4'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2')]}\n",
+ "----------\n",
+ "_G4\n",
+ "{'sentences': ['s1', 'l2', 'e3', 's0'], 'representations': ['France', 'zoo'], 'triples': [('drive-01', ':ARG4', '\"France\"', 'e3', 'e3-s0'), ('be-located-at-91', ':ARG2', '\"France\"', 's0', 's0'), ('be-located-at-91', ':ARG2', '\"France\"', 's0', 's1-s0'), ('crown', ':location', '\"France\"', 's1', 's1-s0'), ('be-located-at-91', ':ARG2', 'zoo', 's0', 's0'), ('be-located-at-91', ':ARG2', '\"France\"', 'l2-s0', 'l2-s0'), ('go-02', ':ARG4', '\"France\"', 's0', 's1-s0'), ('be-located-at-91', ':ARG2', '\"France\"', 's0', 'e3-s0'), ('go-02', ':ARG4', '\"France\"', 'e3', 'e3-s0')]}\n",
+ "----------\n",
+ "_G5\n",
+ "{'sentences': ['l2', 'l3', 'o2', 'e3', 'f9', 's1', 's0'], 'representations': ['Germany', 'Max', 'family'], 'triples': [('be-located-at-91', ':accompanier', '\"Germany\"', 'l2-s0', 'l2-s0'), ('be-located-at-91', ':accompanier', 'family', 's0', 'o2-s0'), ('go-02', ':accompanier', '\"Germany\"', 'e3', 'e3-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 'l2-s0', 'l2-s0'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-f9'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-s0'), ('be-located-at-91', ':accompanier', '\"Germany\"', 's0', 'e3-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l2-s0', 'l2-s0'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-l3'), ('feel-01', ':ARG0', '\"Germany\"', 'f9', 's1-f9'), ('be-located-at-91', ':accompanier', '\"Germany\"', 's0', 's1-s0')]}\n",
+ "----------\n",
+ "_G6\n",
+ "{'sentences': ['l2', 'p1', 's3', 'e7', 'p3', 'f7', 'f8', 'f0', 'o2', 'o3', 'e9', 's1', 'f5', 's0', 'e3', 'e2', 'f2', 's4', 's2'], 'representations': ['Germany', 'Max'], 'triples': [('see-01', ':ARG0', '\"Max\"', 's1', 's1-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f5-s0'), ('crown-01', ':ARG1', '\"Max\"', 's1', 's1-e7'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'e9-s0'), ('fun-01', ':ARG0', '\"Max\"', 'e7', 's1-e7'), ('feel-01', ':ARG0', '\"Max\"', 'f5', 'f5-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'f2-s0'), ('possess-01', ':ARG0', '\"Germany\"', 'p1', 's0-p1'), ('like-01', ':ARG0', '\"Max\"', 'f0', 'f0-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e3-s0'), ('guest', ':domain', '\"Germany\"', 'o3', 'o3-s0'), ('look-01', ':ARG0', '\"Germany\"', 'e9', 'e9-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's0-s3'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 's0-p1'), ('feel-01', ':ARG0', '\"Max\"', 'f7', 's1-f7'), ('be-located-at-91', ':ARG1', '\"Max\"', 'l2-s0', 'l2-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f8-s0'), ('go-02', ':ARG0', '\"Max\"', 'e3', 'e3-s0'), ('possess-01', ':ARG0', '\"Max\"', 'p3', 'p3-s0'), ('feel-01', ':ARG0', '\"Germany\"', 'f2', 'f2-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'f0-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s2'), ('want-01', ':ARG0', '\"Germany\"', 'f2', 'f2-s0'), ('feel-01', ':ARG0', '\"Max\"', 'f8', 'f8-s0'), ('come-up-11', ':ARG2', '\"Max\"', 's1', 'e2-s1'), ('crown-01', ':ARG1', '\"Max\"', 's1', 's1-f5'), ('feel-01', ':ARG0', '\"Max\"', 'f5', 's1-f5'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's4-s0'), ('go-02', ':ARG0', '\"Max\"', 's0', 's1-s0'), ('come-up-11', ':ARG2', '\"Max\"', 's1', 's1-f7'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'p3-s0'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s1'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'e2-s0'), ('like-01', ':ARG0', '\"Max\"', 'f0', 's1-f0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's1-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 'o2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 's0', 'o3-s0'), ('be-located-at-91', ':ARG1', '\"Max\"', 's0', 's2-s0'), ('have-03', ':ARG0', '\"Max\"', 'o2', 'o2-s0'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l2-s0', 'l2-s0')]}\n",
+ "----------\n",
+ "_G7\n",
+ "{'sentences': ['e2', 'p2', 'e4', 's2', 's0'], 'representations': ['crown', 'throne'], 'triples': [('feed-01', ':ARG2', 'crown', 's2', 'e4-s2'), ('feed-01', ':ARG2', 'throne', 'e2', 'e2-s2'), ('come-01', ':ARG1', 'crown', 'e4', 'e4-s2'), ('feed-01', ':ARG2', 'throne', 's2', 'p2-s2'), ('feed-01', ':ARG2', 'crown', 's2', 's2'), ('feed-01', ':ARG2', 'crown', 's2', 's2-s0'), ('feed-01', ':ARG2', 'crown', 'e2', 'e2-s2')]}\n",
+ "----------\n",
+ "_G8\n",
+ "{'sentences': ['f3', 'e2', 's2', 'e4', 'p2', 'f1', 's0'], 'representations': ['Max'], 'triples': [('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2-s2'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'e4-s2'), ('possess-01', ':ARG0', '\"Max\"', 'p2', 'p2'), ('feed-01', ':ARG0', '\"Max\"', 'f1', 's2-f1'), ('stand-01', ':ARG0', '\"Max\"', 'e4', 'e4-s2'), ('feed-01', ':ARG0', '\"Max\"', 's2', 'p2-s2'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-s0'), ('feel-01', ':ARG0', '\"Max\"', 'f3', 's2-f3'), ('feed-01', ':ARG0', '\"Max\"', 's2', 's2-f3'), ('feed-01', ':ARG0', '\"Max\"', 'e2', 'e2-s2')]}\n",
+ "----------\n",
+ "_G9\n",
+ "{'sentences': ['e6', 's4'], 'representations': ['wrap-01', 'Kim'], 'triples': [('take-01', ':ARG0', '\"Kim\"', 's4', 'e6-s4'), ('crown-01', ':ARG1', '\"Kim\"', 'e6-s4', 'e6-s4'), ('take-01', ':ARG0', 'wrap-01', 's4', 's4')]}\n",
+ "----------\n",
+ "_G10\n",
+ "{'sentences': ['e1', 'e6', 's4', 'f4', 'f1', 'p0'], 'representations': ['Kim', 'Max'], 'triples': [('crown-01', ':ARG1', '\"Max\"', 's4', 's4-f4'), ('crown-01', ':ARG1', '\"Max\"', 's4', 'f1-s4'), ('crown-01', ':ARG1', '\"Max\"', 'e1-s4', 'e1-s4'), ('crown-01', ':ARG1', '\"Max\"', 's4-p0', 's4-p0'), ('feel-01', ':ARG0', '\"Max\"', 'f4', 's4-f4'), ('crown-01', ':ARG1', '\"Kim\"', 'e6-s4', 'e6-s4')]}\n",
+ "----------\n",
+ "_G11\n",
+ "{'sentences': ['l0', 'o1', 's3'], 'representations': ['crown', 'tongue'], 'triples': [('surprise-01', ':ARG0', 'crown', 's3', 'l0-s3'), ('surprise-01', ':ARG0', 'crown', 's3', 's3'), ('near-02', ':ARG2', 'crown', 'l0', 'l0-s3'), ('surprise-01', ':ARG0', 'tongue', 's3', 'o1-s3')]}\n",
+ "----------\n",
+ "_G12\n",
+ "{'sentences': ['l3', 's1', 'f9', 's0'], 'representations': ['Germany'], 'triples': [('look-01', ':ARG0', '\"Germany\"', 's1', 's1-s0'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-f9'), ('be-located-at-91', ':ARG1', '\"Germany\"', 'l3', 's1-l3'), ('look-01', ':ARG0', '\"Germany\"', 's1', 's1-l3')]}\n",
+ "----------\n",
+ "_G13\n",
+ "{'sentences': ['p2', 's2'], 'representations': ['throne'], 'triples': [('near-02', ':ARG2', 'throne', 's2', 'p2-s2'), ('eat-01', ':ARG0', 'throne', 'p2', 'p2-s2')]}\n",
+ "----------\n",
+ "_G14\n",
+ "{'sentences': ['e2', 's2'], 'representations': ['Max'], 'triples': [('get-01', ':ARG0', '\"Max\"', 's2', 'e2-s2')]}\n",
+ "----------\n",
+ "_G15\n",
+ "{'sentences': ['s4', 'p2', 's2'], 'representations': ['crown', 'grass'], 'triples': [('possess-01', ':ARG1', 'crown', 'p2', 'p2'), ('pick-01', ':ARG1', 'crown', 's2', 'p2-s2'), ('possess-01', ':ARG1', 'grass', 'p2', 'p2-s4'), ('possess-01', ':ARG1', 'crown', 'p2', 'p2-s2')]}\n",
+ "----------\n",
+ "_G16\n",
+ "{'sentences': ['f6', 's3'], 'representations': ['Max'], 'triples': [('feel-01', ':ARG0', '\"Max\"', 'f6', 'f6'), ('shock-01', ':ARG1', '\"Max\"', 's3', 's3'), ('feel-01', ':ARG0', '\"Max\"', 'f6', 'f6-s3'), ('shock-01', ':ARG1', '\"Max\"', 's3', 'f6-s3')]}\n",
+ "----------\n",
+ "_G17\n",
+ "{'sentences': ['e5', 's4', 's3'], 'representations': ['crown', 'tongue'], 'triples': [('shock-01', ':ARG0', 'crown', 's3', 's4-s3'), ('wrap-01', ':ARG1', 'crown', 's4', 's4'), ('wrap-01', ':ARG1', 'crown', 's4', 's4-s3'), ('shock-01', ':ARG0', 'crown', 's3', 's3'), ('shock-01', ':ARG0', 'tongue', 's3', 's3-e5')]}\n",
+ "----------\n",
+ "crown-01_s2-e0\n",
+ "{}\n",
+ "----------\n",
+ "decide-01_e0\n",
+ "{}\n",
+ "----------\n",
+ "Max_s2-e0\n",
+ "{}\n",
+ "----------\n",
+ "surprise-01_s3\n",
+ "{}\n",
+ "----------\n",
+ "crown_s3\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_e1\n",
+ "{}\n",
+ "----------\n",
+ "animal_e1\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_e2\n",
+ "{}\n",
+ "----------\n",
+ "Max_e2\n",
+ "{}\n",
+ "----------\n",
+ "eat-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "have-org-role-91_s0\n",
+ "{}\n",
+ "----------\n",
+ "member_s0\n",
+ "{}\n",
+ "----------\n",
+ "drive-01_e3\n",
+ "{}\n",
+ "----------\n",
+ "Germany_e3-s0\n",
+ "{}\n",
+ "----------\n",
+ "Max_e3-s0\n",
+ "{}\n",
+ "----------\n",
+ "be-located-at-91_s0\n",
+ "{}\n",
+ "----------\n",
+ "go-02_e3\n",
+ "{}\n",
+ "----------\n",
+ "some_e3-s0\n",
+ "{}\n",
+ "----------\n",
+ "organization_s0\n",
+ "{}\n",
+ "----------\n",
+ "name_s0\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "come-01_e4\n",
+ "{}\n",
+ "----------\n",
+ "throne_e4\n",
+ "{}\n",
+ "----------\n",
+ "cause-01_e4\n",
+ "{}\n",
+ "----------\n",
+ "stand-01_e4\n",
+ "{}\n",
+ "----------\n",
+ "stick-01_e5\n",
+ "{}\n",
+ "----------\n",
+ "crown_s3-e5\n",
+ "{}\n",
+ "----------\n",
+ "tongue_s3-e5\n",
+ "{}\n",
+ "----------\n",
+ "out_e5\n",
+ "{}\n",
+ "----------\n",
+ "shock-01_s3\n",
+ "{}\n",
+ "----------\n",
+ "Max_s3\n",
+ "{}\n",
+ "----------\n",
+ "take-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_e6-s4\n",
+ "{}\n",
+ "----------\n",
+ "Max_e6\n",
+ "{}\n",
+ "----------\n",
+ "zoo_s0\n",
+ "{}\n",
+ "----------\n",
+ "France_s0\n",
+ "{}\n",
+ "----------\n",
+ "like-01_f0\n",
+ "{}\n",
+ "----------\n",
+ "animal_f0\n",
+ "{}\n",
+ "----------\n",
+ "do-02_f0\n",
+ "{}\n",
+ "----------\n",
+ "crown_s1-f0\n",
+ "{}\n",
+ "----------\n",
+ "Max_s1-f0\n",
+ "{}\n",
+ "----------\n",
+ "pull-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "Kim_f1\n",
+ "{}\n",
+ "----------\n",
+ "throne_s2\n",
+ "{}\n",
+ "----------\n",
+ "Crown_f1\n",
+ "{}\n",
+ "----------\n",
+ "want-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_f2-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_f2-s0\n",
+ "{}\n",
+ "----------\n",
+ "fun-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "want-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "crown_s2\n",
+ "{}\n",
+ "----------\n",
+ "close-10_s2\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f3\n",
+ "{}\n",
+ "----------\n",
+ "curiosity_f3\n",
+ "{}\n",
+ "----------\n",
+ "Max_s2-f3\n",
+ "{}\n",
+ "----------\n",
+ "ordinal-entity_s2\n",
+ "{}\n",
+ "----------\n",
+ "1_s2\n",
+ "{}\n",
+ "----------\n",
+ "hunger-01_f4\n",
+ "{}\n",
+ "----------\n",
+ "Max_s4-f4\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f4\n",
+ "{}\n",
+ "----------\n",
+ "near-02_l0\n",
+ "{}\n",
+ "----------\n",
+ "near-02_l1\n",
+ "{}\n",
+ "----------\n",
+ "France_l1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "Max_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "France_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "be-located-at-91_l2-s0\n",
+ "{}\n",
+ "----------\n",
+ "be-located-at-91_l3\n",
+ "{}\n",
+ "----------\n",
+ "look-01_s1\n",
+ "{}\n",
+ "----------\n",
+ "crown_s1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s1-l3\n",
+ "{}\n",
+ "----------\n",
+ "some_s1-l3\n",
+ "{}\n",
+ "----------\n",
+ "France_l3\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p0\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s0-p1\n",
+ "{}\n",
+ "----------\n",
+ "some_s0-p1\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p1\n",
+ "{}\n",
+ "----------\n",
+ "money_p1\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p2\n",
+ "{}\n",
+ "----------\n",
+ "eat-01_p2\n",
+ "{}\n",
+ "----------\n",
+ "near-02_s2\n",
+ "{}\n",
+ "----------\n",
+ "Max_p2-s2\n",
+ "{}\n",
+ "----------\n",
+ "crown_p2\n",
+ "{}\n",
+ "----------\n",
+ "hand_s4\n",
+ "{}\n",
+ "----------\n",
+ "around_s4\n",
+ "{}\n",
+ "----------\n",
+ "grass_p2-s4\n",
+ "{}\n",
+ "----------\n",
+ "wrap-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "crown_s4\n",
+ "{}\n",
+ "----------\n",
+ "she_s4\n",
+ "{}\n",
+ "----------\n",
+ "Max_p2\n",
+ "{}\n",
+ "----------\n",
+ "expect-01_o0\n",
+ "{}\n",
+ "----------\n",
+ "-_o0\n",
+ "{}\n",
+ "----------\n",
+ "crown_o0\n",
+ "{}\n",
+ "----------\n",
+ "have-03_o1\n",
+ "{}\n",
+ "----------\n",
+ "crown_o1-s3\n",
+ "{}\n",
+ "----------\n",
+ "tongue_o1-s3\n",
+ "{}\n",
+ "----------\n",
+ "purple-02_o1\n",
+ "{}\n",
+ "----------\n",
+ "long-03_o1\n",
+ "{}\n",
+ "----------\n",
+ "have-03_o2\n",
+ "{}\n",
+ "----------\n",
+ "family_o2-s0\n",
+ "{}\n",
+ "----------\n",
+ "Max_o2-s0\n",
+ "{}\n",
+ "----------\n",
+ "crown_e2\n",
+ "{}\n",
+ "----------\n",
+ "look-01_e9\n",
+ "{}\n",
+ "----------\n",
+ "crown_e9\n",
+ "{}\n",
+ "----------\n",
+ "Germany_e9-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_e9-s0\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "excite-01_f2\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f5\n",
+ "{}\n",
+ "----------\n",
+ "happy-01_f5\n",
+ "{}\n",
+ "----------\n",
+ "Max_f5-s0\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f8\n",
+ "{}\n",
+ "----------\n",
+ "shock-01_f8\n",
+ "{}\n",
+ "----------\n",
+ "crown_f8\n",
+ "{}\n",
+ "----------\n",
+ "Max_f8-s0\n",
+ "{}\n",
+ "----------\n",
+ "possess-01_p3\n",
+ "{}\n",
+ "----------\n",
+ "crown_p3\n",
+ "{}\n",
+ "----------\n",
+ "Germany_o3-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_s0-o3\n",
+ "{}\n",
+ "----------\n",
+ "guest_o3\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s1-s0\n",
+ "{}\n",
+ "----------\n",
+ "some_s1-s0\n",
+ "{}\n",
+ "----------\n",
+ "go-02_s0\n",
+ "{}\n",
+ "----------\n",
+ "see-01_s1\n",
+ "{}\n",
+ "----------\n",
+ "crown_s2-s0\n",
+ "{}\n",
+ "----------\n",
+ "grass_s2\n",
+ "{}\n",
+ "----------\n",
+ "some_s2\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_s4\n",
+ "{}\n",
+ "----------\n",
+ "grass_s4\n",
+ "{}\n",
+ "----------\n",
+ "come-up-11_s1\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s1\n",
+ "{}\n",
+ "----------\n",
+ "fun-01_e7\n",
+ "{}\n",
+ "----------\n",
+ "Max_s1-f5\n",
+ "{}\n",
+ "----------\n",
+ "shock-01_f7\n",
+ "{}\n",
+ "----------\n",
+ "Max_s1-f7\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f7\n",
+ "{}\n",
+ "----------\n",
+ "throne_s1\n",
+ "{}\n",
+ "----------\n",
+ "Germany_s1-f9\n",
+ "{}\n",
+ "----------\n",
+ "some_s1-f9\n",
+ "{}\n",
+ "----------\n",
+ "excite-01_f9\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f9\n",
+ "{}\n",
+ "----------\n",
+ "Max_e2-s2\n",
+ "{}\n",
+ "----------\n",
+ "next-to_s2\n",
+ "{}\n",
+ "----------\n",
+ "do-02_s2\n",
+ "{}\n",
+ "----------\n",
+ "throne_e2-s2\n",
+ "{}\n",
+ "----------\n",
+ "crown_e2-s2\n",
+ "{}\n",
+ "----------\n",
+ "get-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "pick-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "need-01_s2\n",
+ "{}\n",
+ "----------\n",
+ "excite-01_f3\n",
+ "{}\n",
+ "----------\n",
+ "feed-01_e8\n",
+ "{}\n",
+ "----------\n",
+ "Max_e8-s3\n",
+ "{}\n",
+ "----------\n",
+ "again_e8\n",
+ "{}\n",
+ "----------\n",
+ "have-degree-91_e8\n",
+ "{}\n",
+ "----------\n",
+ "scare-01_e8\n",
+ "{}\n",
+ "----------\n",
+ "animal_e8\n",
+ "{}\n",
+ "----------\n",
+ "too_e8\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f6\n",
+ "{}\n",
+ "----------\n",
+ "surprise-01_f6\n",
+ "{}\n",
+ "----------\n",
+ "crown_s4-s3\n",
+ "{}\n",
+ "----------\n",
+ "long-03_s3\n",
+ "{}\n",
+ "----------\n",
+ "purple_s3\n",
+ "{}\n",
+ "----------\n",
+ "eat-01_e1\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_e1-s4\n",
+ "{}\n",
+ "----------\n",
+ "Max_f6\n",
+ "{}\n",
+ "----------\n",
+ "feel-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "Max_f1-s4\n",
+ "{}\n",
+ "----------\n",
+ "happy-01_f1\n",
+ "{}\n",
+ "----------\n",
+ "throne_p0\n",
+ "{}\n",
+ "----------\n",
+ "crown-01_s4-p0\n",
+ "{}\n",
+ "----------\n",
+ "grass_s4-p0\n",
+ "{}\n",
+ "----------\n",
+ "('_G2', '_G2')\n",
+ "{'relation': [':mod']}\n",
+ "----------\n",
+ "('crown-01_s2-e0', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s2-e0', 'Max_s2-e0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('decide-01_e0', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('decide-01_e0', 'crown-01_s2-e0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('surprise-01_s3', 'crown_s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('surprise-01_s3', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('surprise-01_s3', '_G11')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('surprise-01_s3', 'Max_s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_e1', '_G1')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_e1', 'animal_e1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_e2', 'Max_e2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_e2', '_G3')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_e2', 'crown_e2')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_e2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_s4', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('eat-01_s4', '_G2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-org-role-91_s0', 'member_s0')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('have-org-role-91_s0', 'Max_e3-s0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-org-role-91_s0', 'organization_s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('drive-01_e3', 'Germany_e3-s0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('drive-01_e3', '_G4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('Germany_e3-s0', 'some_e3-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', '_G4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', '_G5')\n",
+ "{'relation': [':accompanier']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', 'zoo_s0')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('be-located-at-91_s0', 'France_s0')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('go-02_e3', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('go-02_e3', '_G4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('go-02_e3', '_G5')\n",
+ "{'relation': [':accompanier']}\n",
+ "----------\n",
+ "('organization_s0', 'name_s0')\n",
+ "{'relation': [':name']}\n",
+ "----------\n",
+ "('feed-01_s2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_s2', '_G7')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_s2', 'crown_s2')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_s2', 'crown_s2-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('come-01_e4', 'throne_e4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('come-01_e4', '_G7')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('cause-01_e4', 'come-01_e4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('cause-01_e4', 'stand-01_e4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('stand-01_e4', '_G8')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('stick-01_e5', 'crown_s3-e5')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('stick-01_e5', 'tongue_s3-e5')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('stick-01_e5', 'out_e5')\n",
+ "{'relation': [':direction']}\n",
+ "----------\n",
+ "('crown_s3-e5', 'tongue_s3-e5')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('shock-01_s3', 'Max_s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('shock-01_s3', '_G17')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_s3', 'crown_s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_s3', '_G16')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('take-01_s4', 'crown-01_e6-s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('take-01_s4', '_G9')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('take-01_s4', 'hand_s4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('take-01_s4', 'wrap-01_s4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('take-01_s4', 'crown_s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('take-01_s4', 'crown_s4-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_e6-s4', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_e6-s4', 'Max_e6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('like-01_f0', 'animal_f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('like-01_f0', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('like-01_f0', 'do-02_f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('do-02_f0', 'crown_s1-f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_s1-f0', 'Max_s1-f0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pull-01_s2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('pull-01_s2', 'throne_s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pull-01_s2', 'feed-01_s2')\n",
+ "{'relation': [':purpose']}\n",
+ "----------\n",
+ "('pull-01_s2', 'grass_s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pull-01_s2', 'crown_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s2', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_f1', 'Kim_f1')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_f1', 'Crown_f1')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('feed-01_f1', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('want-01_f1', 'feed-01_f1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('want-01_f1', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_f2-s0', 'some_f2-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('fun-01_f2', 'Germany_f2-s0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('want-01_f2', 'fun-01_f2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('want-01_f2', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('close-10_s2', 'crown_s2')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('close-10_s2', 'Max_s2-f3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('close-10_s2', 'ordinal-entity_s2')\n",
+ "{'relation': [':ord']}\n",
+ "----------\n",
+ "('feel-01_f3', 'curiosity_f3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f3', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f3', 'excite-01_f3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('ordinal-entity_s2', '1_s2')\n",
+ "{'relation': [':value']}\n",
+ "----------\n",
+ "('hunger-01_f4', 'Max_s4-f4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('crown-01_s4', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f4', 'hunger-01_f4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f4', '_G10')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('near-02_l0', '_G1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('near-02_l0', '_G11')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('near-02_l1', 'France_l1')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('near-02_l1', '_G1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('Germany_l2-s0', 'some_l2-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('Max_l2-s0', 'France_l2-s0')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('be-located-at-91_l2-s0', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('be-located-at-91_l2-s0', '_G4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('be-located-at-91_l2-s0', '_G5')\n",
+ "{'relation': [':accompanier']}\n",
+ "----------\n",
+ "('be-located-at-91_l3', '_G12')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('be-located-at-91_l3', 'France_l3')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('look-01_s1', 'crown_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('look-01_s1', '_G5')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('look-01_s1', 'throne_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_s1', '_G4')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('Germany_s1-l3', 'some_s1-l3')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('possess-01_p0', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p0', '_G2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('possess-01_p0', 'throne_p0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_s0-p1', 'some_s0-p1')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('possess-01_p1', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('possess-01_p1', 'money_p1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('possess-01_p2', 'crown_p2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p2', '_G15')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p2', 'Max_p2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_p2', '_G13')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_p2', 'crown_p2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('near-02_s2', 'Max_p2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('near-02_s2', '_G13')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('around_s4', 'grass_p2-s4')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('around_s4', 'grass_s4')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('around_s4', 'grass_s4-p0')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('wrap-01_s4', 'crown_s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('wrap-01_s4', 'around_s4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('wrap-01_s4', '_G17')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('she_s4', 'hand_s4')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('expect-01_o0', '-_o0')\n",
+ "{'relation': [':polarity']}\n",
+ "----------\n",
+ "('expect-01_o0', 'crown_o0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('have-03_o1', 'crown_o1-s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-03_o1', 'tongue_o1-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_o1-s3', 'tongue_o1-s3')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('purple-02_o1', 'tongue_o1-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('long-03_o1', 'tongue_o1-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('have-03_o2', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('have-03_o2', 'family_o2-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('family_o2-s0', 'Max_o2-s0')\n",
+ "{'relation': [':poss']}\n",
+ "----------\n",
+ "('look-01_e9', 'crown_e9')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('look-01_e9', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_e9-s0', 'some_e9-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('feel-01_f2', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f2', 'excite-01_f2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('excite-01_f2', 'Germany_f2-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f5', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f5', 'happy-01_f5')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('happy-01_f5', 'Max_f5-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('happy-01_f5', 'Max_s1-f5')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f8', 'shock-01_f8')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f8', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_f8', 'crown_f8')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_f8', 'Max_f8-s0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p3', 'crown_p3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('possess-01_p3', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('Germany_o3-s0', 'some_s0-o3')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('guest_o3', '_G6')\n",
+ "{'relation': [':domain']}\n",
+ "----------\n",
+ "('Germany_s1-s0', 'some_s1-s0')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('go-02_s0', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('go-02_s0', '_G4')\n",
+ "{'relation': [':ARG4']}\n",
+ "----------\n",
+ "('see-01_s1', 'crown_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('see-01_s1', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('crown_s2-s0', 'France_s0')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('grass_s2', 'some_s2')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('feed-01_s4', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_s4', 'crown_s4')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('come-up-11_s1', '_G6')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('come-up-11_s1', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('come-up-11_s1', 'crown_s1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s1', '_G6')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('fun-01_e7', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('shock-01_f7', 'Max_s1-f7')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f7', '_G6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f7', 'shock-01_f7')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('Germany_s1-f9', 'some_s1-f9')\n",
+ "{'relation': [':quant']}\n",
+ "----------\n",
+ "('excite-01_f9', 'Germany_s1-f9')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f9', '_G5')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f9', 'excite-01_f9')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('Max_e2-s2', 'next-to_s2')\n",
+ "{'relation': [':location']}\n",
+ "----------\n",
+ "('next-to_s2', 'grass_s2')\n",
+ "{'relation': [':op1']}\n",
+ "----------\n",
+ "('do-02_s2', 'throne_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('do-02_s2', 'Max_e2-s2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('throne_e2-s2', 'Max_e2-s2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('crown_e2-s2', 'grass_s2')\n",
+ "{'relation': [':part']}\n",
+ "----------\n",
+ "('get-01_s2', '_G14')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('get-01_s2', 'crown_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('pick-01_s2', '_G0')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('pick-01_s2', '_G15')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('need-01_s2', 'do-02_s2')\n",
+ "{'relation': [':purpose']}\n",
+ "----------\n",
+ "('need-01_s2', 'crown_e2-s2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feed-01_e8', 'Max_e8-s3')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feed-01_e8', 'again_e8')\n",
+ "{'relation': [':mod']}\n",
+ "----------\n",
+ "('feed-01_e8', 'animal_e8')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('have-degree-91_e8', 'feed-01_e8')\n",
+ "{'relation': [':ARG6']}\n",
+ "----------\n",
+ "('have-degree-91_e8', 'scare-01_e8')\n",
+ "{'relation': [':ARG2']}\n",
+ "----------\n",
+ "('have-degree-91_e8', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('have-degree-91_e8', 'too_e8')\n",
+ "{'relation': [':ARG3']}\n",
+ "----------\n",
+ "('scare-01_e8', 'Max_e8-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f6', '_G16')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f6', 'surprise-01_f6')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f6', 'Max_f6')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('surprise-01_f6', '_G0')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('surprise-01_f6', 'Max_f6')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown_s4-s3', 'purple_s3')\n",
+ "{'relation': [':mod']}\n",
+ "----------\n",
+ "('long-03_s3', 'crown_s4-s3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('eat-01_e1', '_G2')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('eat-01_e1', '_G3')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_e1-s4', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('feel-01_f1', 'Max_f1-s4')\n",
+ "{'relation': [':ARG0']}\n",
+ "----------\n",
+ "('feel-01_f1', 'happy-01_f1')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('happy-01_f1', 'Max_f1-s4')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n",
+ "('crown-01_s4-p0', '_G2')\n",
+ "{'relation': [':ARG1']}\n",
+ "----------\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(len(merged_story_graph.nodes))\n",
+ "print(len(merged_story_graph.edges))\n",
+ "for node in merged_story_graph.nodes:\n",
+ " print(node)\n",
+ " print(merged_story_graph.nodes[node])\n",
+ " print('-'*10)\n",
+ "for edge in merged_story_graph.edges:\n",
+ " print(edge)\n",
+ " print(merged_story_graph.edges[edge])\n",
+ " if len(merged_story_graph.edges[edge]['relation'])!=1:\n",
+ " print('*'*20)\n",
+ " print('-'*10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 108,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "(3500_0:0 / be-located-at-91\n",
- " :accompanier (EVENT_3:3&0:3 / organization\n",
- " / \"Germany\"\n",
- " :name (3500_0:4 / some\n",
- " / name\n",
- " :op1 \"Some\"\n",
- " :op2 \"Germans\")\n",
- " :quant 3500_0:4)\n",
- " :ARG1 (EVENT_3:1&0:1 / \"Max\"\n",
- " / \"Germany\"\n",
- " :ARG0-of (EVENT_3:2&0:2 / some\n",
- " / \"France\"\n",
- " / have-org-role-91\n",
- " :ARG4-of 3500_EVENT_3:0\n",
- " :ARG1 EVENT_3:3&0:3\n",
- " :ARG2 (3500_0:5 / member))\n",
- " :ARG0-of (3500_EVENT_3:0 / go-02\n",
- " / drive-01\n",
- " :ARG4 3500_EVENT_3:3&0:6)\n",
- " :quant EVENT_3:2&0:2)\n",
- " :ARG2 (3500_EVENT_3:3&0:6 / \"Germany\"\n",
- " / \"France\"\n",
- " :quant (3500_EVENT_3:4 / some)\n",
- " :accompanier-of 3500_EVENT_3:0)\n",
- " :ARG2 EVENT_3:2&0:2)\n"
+ "115\n",
+ "102\n"
+ ]
+ }
+ ],
+ "source": [
+ "sentence_nodes = [node for node in merged_story_graph.nodes if '_G' in node or 's' in node.split('_')[1]]\n",
+ "sentence_edges = [edge for edge in merged_story_graph.edges if edge[0] in sentence_nodes and edge[1] in sentence_nodes]\n",
+ "print(len(sentence_nodes))\n",
+ "print(len(sentence_edges))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 101,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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f/53w+/j+IZg7dy6SJNG9e/dqv/0r/CM2x7XNTGG9HkIbUxdnSS6OossEtR0MQJHZfs1+BreoqfyvMoYQO+4jVAHBAD65cLq4RqhNYbjKC7FdOgZuF5JGT8yod4i8/RkemvAIbreb2bNnAxCZLJtinYVZWC8cwhutaWrSS3np6hOaXDUaSTa3qirXh8aa9THWa4+tvBhJo6fmw18RNWQyxgad5T10RgBc5bI5MbjdnQR3uFNOhhduKo6n4qooQh9Xqe3owuMQ1nLcHh+eZDARPeINEp78ofLYbpdPIEv0yLcp2btcETSGpOagUqNSqbj/zluvObeotbjNJWR/+0SllupyUrJ9AZqgCCLveAFUas+pq5DUWkBQvGMBMcNfJ2HSIhKfX0H8498TNWQKuqgk1EERqAKCcBZcQjisSBo92tAa5OQXIUkSjZq14sDveyg+uA7h0WoNSS2Rqsxp+cE1yv9lB68y50oqRowYQVpaGoMGDeLee+/l7rvvZs2aNQSGRWNo3OPa5/onsDpdfJZ69oZtdu7cycGDB+natSsDBgzg3LlzTJ06Vbmn/PjvhV/w/R9FUlISkiSRmpp6w3YL9lxgxNd72HAyB5vT7cPjCLIJyuZ0s/5EDiO+3sOCPReU39b/fpzgZr1QB0eR9fUEsr6eQGBKd9TB0VQc20TJriXkr3gbR246ic/9TNSdL+AqyUMdHEXmxQs0a9UWq9WKEIIzZ84gSRItU+oT1mMsAG5zCVlfPEj8o98S9+h35C55GVeZbPbUhMTgLLqMsV5bNKGyL0k4bVz66B6uLJ5GSIjsV0tNTWXSpEkUXskCQGUMRmUMQRNeE9RqSnYvodxj6tRGJFw1OwJnYSb6uIaV81GQSXn6IfQJTYi55w20YbKgjug/URbqQp4/lcFERP9JBKZ0p/C32ZhP7cLUagAJzywntPtYbBlHlD7dLid2hwNJrUUXm0zUEFmjUOmNhPV8QG7k0TCMjbsRP2kJKo0We/YpJF0ACU8vI2b469Rq1xe32803n32MQav2OZPQbmMI6TBU7kqtRh+fQkC9dgBYzu2ncONXlO3/VQ60iUggqPVATM1vRWUMwVWYjbXKeKtCGx5HWNd7ATAkNif67leIufc9xs1eR7NmzUh54G0SnlxA4vMrMLXoC8hWAG/AD0DF8VQyPxtH7s9vY07bgaSvzO+La9UDh8OBTqfD5XKxYMECli1bhsvlQhWXgr0gi4vvDCLz0/twW8txWcq49PFoLr4zCGvmyWuOGcBRlMOX97ZFkiTmzJlDXFwcUVFRPP/884q/9a677iI9PZ0ff/yR5cuXc9999wFysI4f/93wmzr/wfgzeizheYlLkqqaf+TOZtHcPag/pTkZaMLjMDXpgSM/wyccvnj7DxgbdkYbkYAQbnKXvYY9+xS6mLpoE5pw/Mg2H3Nk48aNOXHiBJGqype2u6IYR1E29stn5LGodQinDckT6m8+tUvRsuRBu7GkH+D9mUcBuHz5Mh999JHys9PjY3JXFKE2ReC2VShaU1CbQYT3Hk/Ge3cCAn2tpkQPnUbu0unK/rFjZqEJjak2Vyq9kfBeD+G2lFNxbBNBLftjatYbAEe+nPagr1EPlVaP3hNh6UXMiDev2SdAUKv+2HPPU3F0E8JhxXxiK+a0HYr2qwmKlNMTnDayTsg5fb/88ouPlqoJjSW43RDKDsialTowjPL9Kyvn2FpG2b5fUZlkZ6Sj4JJPkAtAyZ6lWM7v52qE9x6PoXZLJcAlZ9ELAPywqjEPtlnN1tN51SwBbodNIQNQh8TgKsnBVZqHxePLNTboSMUReTGS4wzg3Pl0WrZsybZt2wgMDKSiogKdwUjZsS0ItZbgdkMo3fsTRZu/RbgcuM3FBHcchiG+ETeDN998k759+/Ljjz/y7rvvkpCQwBNPPEHTpk192tntspUiPj7+pvr14+8Lv+D7P4CrfXPLnh1MWb4c4dijh2wK+u47OeHa7XYzZcoUPvv8CyxCQ0j3sZhS5DZXfpiC7dIxgtvfhTXjKPYrZ4l7+GtUxhBKdizEfHoXropiHvyqJj/36UFpTgZqUzjGBp0o3b0UY4NOVKTtUIJRAht1JXLQswBYzh/Ann0KkHAUZiFpdBjrd6T85A6efPJJHA4HJ07IPq2ycwdQGUy4rXKAQ/aX4xUzn3B6Ako8Ifma0Bo4i6/Ivj/hVhK+XU7fQJAuw8azZ+NqnIWy5odWjzamDtYqCeAVxzYR1n0suriG2LNOYss4yqUP7v4fXx91cBSO/AwK139O6e8rcJbl/flOXgg3IZ1HYM85hyakBo7cdJzFl7F5/H/Osnz02HmocxyTP5DNq0IIpCp5ggH12nrMljJUhiASp6yqxtdZsnc5xVu+w1i/E1F3vqC0d5UXkfnpvdgyjlUbXnjv8SDchPeZQGBKD8oPrsV2+RT56SeYOHU6NBxWbR9n8RW8/tDwXg/KDDZF2eByojaFow2vFCwqSeKO597j/Lp5bNu2TQmKsltls6mjMJuYEa9jOX+A8iOyJqaNrkNol5E3PcU///wzzZs3p3nz5kyaNInvv/+eJ554wqfNsmXLWLx4MREREUyZMuU6Pfnx3wK/4PsvxvXKzaga9kT1+0+47RZqt+1Jx6b1yc2Vgxx27NiB1WoluFZDyo7tpfC32RjrtUelr9SaSvf+REDdNjLVlUZLwZpZmNN2oAmribFhF8xp2/lpwRwAtFGJir/GfGoXhsTmoFaDy4nFE9kohJvCjV8CKHl0lrO/Y/Owh1zMyCA8rg6GoFCsZcW4K4rQhNbEbS31vCSpZFJRqcHtUl7CKmMIFF9BV6NeNTYSk8nE119/zT333MOOH7/ySVrHYfMRegDlh37DUKspAUktsGd5zGRqLUHt76Jsl8xAcnneU0hagxI0IukDSZi0mJIdCynZuUjpq2TnIiqOpxJ+22PoompjPb8f4bQr2h9AUNshhPd6UCHBDu0+lorjW3CW5GJIbE5E/ydx5F4gf/Us9HENUQUE4chNV/aXdAEIuwX7z9M4ktVSEQpqtRqNRoNKrcFirqDs4FochVnoopKudyshSRDRvBfmvcswn95FzpKXFXOy9dIx4ibMua5Wass8Sf7qWagDQ32uQUGZFZvTjfn0bsyn9yi/+RAEAKYW/Sjy3B/aqERUVUyd1vISpo2+FYdH0JnNvoQAAbVbIam1BLcdrATLBLe5HUl986+2Ro1kzbBhQ9mknZnpS34wZ84cHn74YSIiItiwYYNPjqIf/53w+/j+hpAkCUmSmDlzJrVr1yY0NJSZM2eyfft2GjRoQGhoKLcOG6v45qwOF/n71pA95zEy3r+LimObER6fkDm5N9sdtZk8eTIABoOB8+fTuXzuJEgSwmHFUZiFcLtwluV7B4Cz+Ar6hBQkSaXkqDkriojo+yihXe9TxmpNP4TbKZuAtJG1iBo2Xclbc5tLyFvxDhnvDFI0LeG0Yb1wELUpQtHO7DEpSLe/CpEym4ezNA9H/gWCOw5DHRSpHEsVEEzcY/NApVZyzLy+oqqC2+sj0uv1aLVaJVXCnnMOfWILuX1gmJLUrYupi7FRV9x2C7lLp2Oo1ZTEKavkxHiXA1uVxHS3pRRRRZtS6QOuHeGn1uAsvkzBmo8I6zGWxCmrqn3Cez3os0vJriXoaiSjCgjGcmYPhWs/RR0UgTa8JtaLhyk/sEYOmlFrkTQ6uo15jsHDRuGsKFa0Fq1WS69evbDZbNiE/HhLai3W8/tvmAfYqEYQPz0zgPWbNhOY3A57TroshMsLCGo1AJUx+Lr7esfoLMkBlQa1KZyxDzxE86GPe+b9PBXHNinmU3EVm42pSU/kYCMIqNNGCWYCcOScwWE1K7yeKlXlKyuo7RCCO96N21ouR6mq1CCpKN6+AJfVNx3iRjh5Ul7kpKWlAb6mzLfffpsHH3yQhIQEduzYQYsWLW66Xz/+vvBrfH9jvP/++/Tq1YtFixYxZcoUoqKiuO2221i0eAkbls4jekQyAUktKD+4hsL1nyPpAzE2vAXrxSNKBB0C7E6XT78JjVtRsL3SQS/sFoq3zcfl0a50sckyTdhvn+L0JjtLEtgtmM/sRRtR1cchFP5Il7kE67l9SiAGgHD7HhtkNhO3uVT5bmzRH5vTLXNNAsIm568Z4htRpjfi8pCw6BNS0ASGog4I9pA3o+zj9DCIAJiS21N2bDOjR49m0KBBBAUFUVxcjMoYRtRdL5C3ZBq2rDTsFUVyJKQpHOv5/RhqNcN64SAF6z9HYwqvNKtdPoOkC0BlMOGqKFJMsACu0gIKfvsUm8cH6TW5qgJCcJcX4CrN49In9+K2liGptRhikwnvPR5NVBLWjGOKTwwguMPdlO37VeEFNZ/eRcTAp4gZ8QYgE0gLzyKjfqMUXGlb2JWWhhCCW2+9lQ8//JDs7GwOm4NJq7kWqYaswTiLc8j64gGEzUyNsbPQezRfQ2IzEqfIJADp+RUcySxmdIc2jHx59l8iCdeGxyljrEoSPmnJQaCY0FtGEXrLKKW9s6yArNljAUHJrh89kZwClSGIwCY95Shdb9si+Z6sqKhAkiTq1avH6dOy5hjWvBeSJJG//nNcZfmEdBqOcDkp3bucwvWfEzXouZsa/5A77iC2YWv2eXJOA1N68MXWc1iOrGPq1KkAtGvXjs8//xyA8PBwpk2bdnOT48ffEn6N72+M999/n4ULF5KYmIgQgjFjxvD0Gx+hryNXHshd/BIX3x5I2X755RXeezyRAyYRfddLSh/C5evrqt+4Cd0eext1cFRlG6Bs36/Kd3v2KcVPV3HMQy3meQtWHN+Cw+snQ47k82puwuVAHRR+3fNRBYZhbNxDEYzq0FgiBj6NISGletuAYDTh8UhVNDlDQhNc5hI5n8/bziDn/VXNV7PlZwBQaIjly7k/UFoqt29eP5Hizd8Rcftz6JNayI3dLhx5FzDUbYPeGwzhduIovqJoqeqQaLQRCRgSm6OLqQvOqqkYgvJDv+HwJIlrPFGeVYW/LrY+puZ9McXWxXLxCHkr3pHPp1YTgtsNUSJBrRcP4zYXE9T+TmXfqiwriVNWkTBpCaHtBnPq5HG2b99Oly5daN++PT/99BN9+/ZFHVmbWakZitADKjVUSYXadO3r481tO5JZzGPd62HQqKu1yV/1ARdnDubi2wO59NFICjd+ReHGr3zauOxWfpnxGLVq1SLjyB70muqvGGEzKzyk9itnZAtASDQxI95EHVCZxynpjEhqjRzhqlIRFhbGa6+95tNXxcntmE9sRRtZi5DOIwi9ZTTaiATMJ7ZScXLbNc/1alib3cUfO7bgUmkJbncH6TFdmLXxNG8s3am0+fHHH/noo4/46KOP+Pbbb2/Qmx//DfBrfH9jeH0PoaGhXLx4kQYNGjA79SxC60sy7KWb8mpiVcPyi7d+jyak0jeTW+Gi1OpEpQ/EhSzc3LYKRZO4Gm5rOcYGnTGf2gmSCsvZP+QEbEDSG4ke/holOxdTsnMRxuSO6GPrE/fAp1yaNcKnH7UpAld5AY68dLnEj7kEd3mhnBR+FUI636NoCEq+l1qD/cpZOYDBk6heY+wsJEkiZ/HLClMKai32K2dRB0exy12f1DQXUkAwVBTzwQcfsHXrVmbOmoyttEjpt+ZDn6PSGijc9DUgC6qoQc95NJMx4HTgyLuAqcVtqANk+jCEG0kXIJtiXU5cllKErQK1KRxnoa+PSBdTF1x2XBqZBMBecAlHSS7akGhCu95L6R+/yH7Li4fRRtchsGEXyvYul4cXFIHbZlZMuSpDIE5npak1Li4OtVpNVFQUaWlpTPtyCVZt3crrZ7dQsPpDAILbDUFzHcEHlbltX4xuw4v9G/pE/Aq3q3IRhGzy9S6WwnuPl7c5rBRtmkP5id9RqVRMbxLF8RPVj+OylKKPrY82MgHhdGA+tQtXSS7mM7vR1aiDsX5HRRPVa1TsmtzTh0Bh+PDhQGX5qsBGt/j0X/Ohz697jteCvlF34hp1v2ou3AR1Hklwl5HXLRrsx38v/ILvP4gLFy7w3HPPKQEnLVq04O2331Z+b9OmDVu2bFG+P/jggwTUaopkCPLpxxvpaLt0An3NBjiqvHjtuek+lFVXzh5n/sNdcVYxf6r0gUganSL8IvpPwtSsN0IIXCW5qAKCUAdHUn54g+yf8WgzpiY9kFTVNYNrQRuVREByOyzn9immPF1sffRxDf5kTxkhHe7GevEwzqIr6BOaEDFgkuJbixz0LIXrP5eFs8uBpNGj0gVw4fOH0MbUURLDH31mKicP7CEwMBBdYDCOCplA+vLXj6BPaOLRECRMTfvgdtpx555D0ugUs6ohvhEOgwl+l0v+aCNrEdi4uxKYIV8LeQ7dVSjBFMqzKsj+4gESJ6+UmVokFeDh/Sy+rKRPGOq0kaNK1Vo0YbHoompjPrnVp59PP/XlQf3tvYkYG3RC0ugxn96FcLvlckvN+xLafdx157f0j18o27+Sr8oKWDYphCZNUrj/kZf59rgDq9NF8a4lSBo9QW1up3TPMrTRtal5/yeek3YjnA6KN39L+aG1BAQE8Nprr/HSsxO5kpOLWwhUOiPa6CQMtZoR2uUealSpNFFoMFG2f6USyOSFJEGPBlHXZQ16rHs9tp/Jx+Kobk4HcFnKfAKOvFAZgjx+xT+Hn+bs/yb8gu8/hIqKCnr27El6ejpdu3YlMjKSn3766eYqU18Vsaav1RRbxlGKdy3GXpChlOcxNe9LRL8nlLB1AG1IFAkNm3Nu928ABDa7lYDEZgQkd5CrHiBXGihY+7H81EsSmvCaRA58GvPJ7bjsZiXCsuzAGiJufYSg1gNxlRVguXCQjA/uRhtZi+hh0wmo01ox61nT9xNQvyPqwFDZjCpJRA97FbelVC5+qtbKEZrIEZHlRzciaXSKudHtsFFj9MxrT4cxhKghU7DlnCf/5xk4S3JweMydXgYVgJMHZLq0tm3b0rp1azp06MDdd9+NszQPd9o2IhMb0P7OB+jd51bcZ3dxrOASu+vVIS0tTTG9qqosOrSRtTA16Unx1rlykI3bVUl9RqWpU2UKR5JUuMoq/ZCGxOZybuOPr1ZSlyH7W4Xdgi6uMZEDnyJn4VT5XNxuzGd2+5x3y5YtOXjwIHfddRfLli2j9/AH2fTjHMyndqGPa6QIPUkXQEQ/3/D8qnAUZVO06WtUAcEEN+9NnTANGeeP0TZGza2dWjFu2idc2LWE6FsfxqXSVY7VYUOlVtMgyMnLd7Vj0tYZHNJoWLZsGa+88grZ2ZXRm25rGbaMoziLcwjtco8ilNyWMsyndqHSBxLUqr/PuAwaNY92r05Y7UXzhNBqmmlVCJvZx4TvhTo42kfw5f70JrbMk7it5agDgtBGJRLUsj/GBp1wWyso3PAFtqw07ptRyMTQYHr37MF7771HQsLVhAd+/LfAL/j+Q1i9ejXp6enUqVOH1NRUJEnijjvuYMWKFTfczy0Emio5WYBcifvgWsoOrMJ8YhtqUxjBHe8mpJNsbqwao6Ct2RCjKRiVRo/bblYYOUzNb8WacQS3ww52s+J3UgdHozaY5MT0KknRktZA1559uKKWyK6SmG7waE65S6cTM+ptJfgE5KAWe44nHF8IXOUFSmI6LgfuKoLBVZqHZAyRj+l2Un5kA+E977/uvAjhpnDdbJzFl+UE+chasgYnBDGj3sYQ31ipLn7w9CW+/PJLYmIqTcBffP45Dz30ECdOnODcuXOcrCjmt99+o0ePHthsNnpP/5ENJ3OQAkMVHk5jvXaoDIHEjJKFu7P4ilL5QWUKJ7zHWPJ/fRe3pXqJpLAe92O/fAb7lTPKNkNSK6wXDgBgv3ya4q3z0NVsiCM/g+C2g3CW5FJxcjuu8gJ0Go1S+uny5cv07t2bTZ5ST9rIWjiKrygCVdgt5K/9BJVWT2Djbj7Ub/JkyxqT2hSOPrkjzbq245tH++JwOLj33ns5uGQJjZs0o26zBuzcIpdUMkguHuuaxAM9U1g092uWfvk+derUoVGjRvTv35/p02Wtdc6cOeTo45h3wo7FKRQLwdVCSV+riY/f2aCReLF/wxtyaUKlBnat6gya0BjFZHotRA6ZQv4vM7Gc3o0mIp6Aem0Rdgu27FNUnEj1CL5yKk5sRZ+QgiGxKebzf/Djjz9y7tw59u3bd8Ox+fH3hV/w/Ydw4cIFABo0aKCY7Lx5RCNHjmTnzp1KodNDhw4xZ84cHnxQDn+PHPgUoV1GkvWFTGclSRJBrfpXWzF7oYtKVP6vOLqRo0crf1P4ExObk/DEAirSdpC/4m0kvRFhMyOpNdS49z1Zo6kSyNBywChSf/6G6XNW8KqHOitm1DuodAZUAcGU7fuFsgOrfTgZA1O6oY9vpLy8bZdOYL9yfb7EqMGTKU6di/3yaYS1DJe5BLUxBOF2UbDmY8xn9iBsFQS3uwNjwy4Khde1xuHl4wQQtVpy9913K/MNEBsbi91uZ/z48ezbtw+tVkt5eTkLFy4kICCAQXX1bD+jvqZZzRsl6a1M7r0mxoZdMF04TEXadoTd6rNPyd7lilbqhS07jSodUH54PToPp6ct86Sc31erKa7CTHq1bsCOramUlJRw4MABkpKSiKzdmPzzx9HF1KHieKpP3xWH1wGgi65TTfBpIxMI6TKKsv0ryV0yjTlLYOnriUR3HsrlkzIRwum0E9gsHxOl0VAISJZitn01jecHrWLZsmVs3SqbYBMT5Xvtgw8+4NFHH+XBBx9ECIHBGEhw51EY2wxCiEqh5DKXULTlOyqObqRg9SwlOtTphu1n82kaF0rzhNDqN0cVjO6QRLP4UD5LPcuWU3lIVFZ7ADBoVDhcbgTg5VB3O6wU/jYbhBtjo65E3v5MpVB2u5QALlVAELH3f6zkQLoyj5G5YAr79++nsLCQ8PDr+0z9+PvCL/j+Q0hKSgLg9OnTMtOGJHHq1ClAfnkcOnQIQIlIPHbsKtaMKvlMQriRpOrRc4CSHO1F7P2fMvzWzjRTZ3P/3QNwW0rJ/HQM2qhE7DnnlVQClSEIl82MqzSfi28PxNSiX6WpTlLxzAP3cOuttyovPOF2cemDoagCgtFGy+dmObMXISoFRcmuJahNERhqNcVRcImCNbOU36SAIEQVzSgwpTuuklzfhOjfZmOpUj3AC014PDZPBXXhsHHpg6E+v7tKchVtD6B0zzKOIBfJ9eKee+7B4XAQFRUl58B5Ki+o1Wpq167N7tWLefH2h3hlYaoyn25LGZmfjUPYzAQ27a1EhapN4bhKc8mYOZg6T3zHtNmzeaB7Q5+ae+YTVX11cjkjYTcrFF7Geu2wnPsDe5YsDK2XjuM2F2Nq1ou4+BiOH9lJeXk5ERER5OXlIUkSDfrfT/754yCpSZyyCre1XAkyulECunC7COk0jNAu9+AsyaXs4BpK9yzDdeYIxia9qDixDafTyblzlb7i0tJSVq+Ww/+vxQfbpk0bDh8+TElJCYcOHaJv374UbZ3L4FHj2HDkEsJDM6c2hhBQuyUVRzf6RAs73eIv1c9rFh/KF6PbUFBu48d9l3jj029p2b4zybXiMNudbD2d5yMMZdOmfL+FdrnHx1ctqdToIuUkdZXe6Jv478kbDQkJwWQy3XBMfvx94Rd8/yEMGDCApKQkzp07R48ePYiMjOTnn38mICCA+++/n4yMDE6cOMFLL73Epk2b+OKLL3z2VweGyr4+l5P8X99FExxNWI/rBy94kbvkZf7I6cPPx/Yq21wVRbjKC5A0OpkNxOLA5Sn4qjKG4CrNpbxK8nPvO0fz1Xuvs3XrVsJjalKYk62E+Lstpdg8PkaEG40pQglacJUV4CovrIyOzD6l9CmsvknNSNWDZgwJKWiCI7Fln1L2lXQBGBt0VPyaVCvDKqcjBMUmK6Y1fWwynTt3plmzZkqbIUOG0LRpU15//fVq+584cYKTJ08y8OhRkuNa4PXiFe9chD6+MeaT2ynb9wuGpOZowmr6MpNsnEVorzDi4+MVDb53v0H8ccWOJfcizqJs3OYSVIYg3NYyj1CVCGzaG2vGUYTT7sMU48pLZ+xDw3h6rVxWqGvXrkiSxOFLxeSVXb9Ce+7y13EUZqE2mAhs0oPQbmOUl33OD1OxeZhqJI1W8SGr9IEY67T2mAsFAVoNt4hjfP3GczRv3lxZnF0Lbdu25dy5c9jtdjlIyuUiMDCQlokRLP7gZWx5GeiikhAuB+az8r0YULuVTx//P4ElESY9gRm7yF4+g4TM9ry59DeGfb6Ny+u+9mjeFnQxddHXbqns47aZyVn0AtZLJ6AKOcHVZlJXRRFXfvsMgLfeegudTsfN4K233uLFF18E4MMPP2TSpEk3td/1cOHCBSZOnMimTZtQq9X07duXjz/+mBo1avyP+v0nwZ/H9x9CYGAgmzZt4q677iItLY2NGzfSrVs3Nm3aRL169XjjjTfo2LEj58+f58CBAwpBrnDasWWfIu+XmZVUYSe3U/r7z5hPVWpDlguHubLgeSUfD0kFkoRKH8C+jb9w8eJFNBrPuke4URlDkbQBVeq7AZKE2xPIoo2urWweOaC7oukV5lyWGU68uxhMntI2EuH9J2JqcRvaqitmIag4vsWnLI+kC0AbEYfaUwz1ejAmd0ClD/QVmHYLljO/Y2zQCXVIDAjhU74HZO1KExarfLfnZXA5N195GQGsWLGCbdu2+TBzPPvss3Tv3h2NRoMQgiZNmpBirFB+j7z9WSL7T0TvMaM6CjKJH/UmQU2rBCjZyqhZs7LUEsA9Qwcz+ZlJ1B7zDrHjPiawaW9lntWmCKKGvowuspZyLRS6NkCdsZ9RgyvLDnXr1g2A2alncd8g49xRcInAhp2R9EZK9/5E8bb5ym8uczFqU7gS2estMhvSuWpKioTF4WLlkezqnV8DsbGx1RhtKioqmP7VMrQ1GyIcVipObsV8ejdqUzghnUYQ3mfCNfvy5hg+8vQUJEli7NixZGZmMnLkSGrUqIHRaKRnz54cOXIEh8PB008/DcC+ffuY/P1msn/7nLIDq1AHhhKQ3AFbVhple5Yr/dtzzuGqKK6W41i05VuFgMFRfIUr85/HWZRNqzsf5tFHH72peTh48CCvvvpq5bP2P4Tb7WbAgAH8+uuvdO7cmZYtW7J06VLuuOOOf0n//xgIP/72OJRRJJBVGRHWZ4JAUglAaCLiRWCzPsLYsItQB0cJY4NOInHKKpHw9DIhafXyPmqtsi8gmg+4T7z99tsCEE899ZSyPaFZJ2GIbySCUroLTWSizz6AaDFwjAg0BQlAdOzYUdke3HGYiH9igdDFNZS3SZLQxSaL0G5jlHFe/ZH0gSL+iQW+21Vq+eP5Htikl4joP6naviEd7xaoNAIQalO4CGozSNS4730R3u/Jax4LEEGtbxcxo95RvqtDYqq16du3rxBCiEaNGglAfPbZZyI7O1uEh4eLGjVqCECMHDlSpKenK/tkFZSKN5fvFbEp7QUgarbrJxrf9aQIioxV2uj1eqFWq0VoaKgwGAxCkiTlN61eL6L7jBdJU1cJTah8DF2NeiKgblshafTKtYu680XR8OW14qUvfhRNmjQRRqNRjB49WgwfPlwAYvyjj4v6L60RiVNWVfsEtRkkz0GrgSJxyipR8+Gv5GugNYiEp5dWax91xwvyHAVHXbO/uEfniuBmvURsXLzQarVCp9MJnU4nVCr5Wj/00EOicePGQqVSCSGEyM3NFd1uH6ZcW01IjIgeNl1Ej3hD6GLrK3Ohi08R8RMXCZCEKjDUc6zvBCBUxhCROGWliG3YSgCiVq1aIjQ0VD4PSRJqtdy3SqUSt9xyizAYDMp+cY98K98vkkrEP7FAJE5ZJQJTenieDZ18rzXtLWpOmONz/yn3d4ehInbcx0IVGCqQVCL81kfFpMUHhRBCFBYWiqFDh4qIiAih1+tFUlKSGD9+vPLcWiwW0ahRI9GrVy/RtWtXAYgPP/zwhs96YqL87L399tuiSZMmwmQyiSFDhoj8/HwhhBA///yzAETTpk2F2+0WTqdT2WfLli3/8nfP/1X4Bd9/CHllVvF56lkxcfEBMW7u72Li4gPi89SzIr/MWq3tQ9//USk0dIECEMZGXUWt539RXki1nv9FhHYfJ4LaDBKBTXpVaR/g8zcqpoaoU6eOaNy4sfjoo4+UdnXr1hVH0s6K4U9OE6E1alV7AXz33XfCZrOJZs2a+Wyv+fA3nhfsYPllHl3b54WriZT7MiS1UPaJf3KhSJyyykfoBTbpqQhKVWCYSJyyqlLwqbUCj8DQhVUKrcAmvZTzVwdFyttSeoia47+s0rdGaePt31CntcDzotZqZeEyZswYIYQQ/fr1E4CYPn26EEKI+Ph4odFolBfu+fPnlb69GDxYPvdXXnlFCCHEkiVLlDYREREiOTlZ6QMQkZGRigBUqdWi64zfhC42Wfk9ILmD0ITHK99jB04ULXreLoxGowBE9+7dRfv27SuvsaQSalOYMCS1EFF3vOAjqPQJTeRxDHhKhHQZJYJaD/JdkGh0Ql+rqQjuMFQENunps2DS1WwgoodNV/oyNu6u7KfRGZT/u3TpoggfQAwcOFAMHTpU7N69W5hCwq66lySBJImgtkOELqaukDSy8NHG1BNRQ6cp7WJGzhC6mg2U+8OQ1FLoatTz6cs7hwaDQYSFXX0cRFDrgcJQt03lmMNrCk1YzUoBp9HJ4wGhCgi+5qJJ0uoFnmdHG5Uogpp0F6FRNYRarRZ6vTxXbdu2FRMmTBD9+vUTTZo0Ue6LJ598UoSFhYlLly6Jbt26/SXBZzKZxLhx40RSUpIAxJ133imEEGLaNHmOxo4dq+wzZMiQm+rbj0r4Bd//Mg5lFImHvv9D1H9pTbVVegPPtvHz/xCHMoqEELKArP/Smms+kIEp3UWt534WiVNWiZDO91zzwa36UakrX77eFXPVT9WX19WfJ554QgghxNdff+37m1ojdLENBJ6+VUa5X21kpfC8+qWir9VUJDy9rPKFFFrDo+XolJdjcIeh19T4AOXFLRlMQhtdR5ha3FZlPNoq/VR+Yu55S6iDoyuPGRQh//UIpFGjRgkhhFi1ShbIer1ejBkzRoSEhAhA9OnTR9StW1esXLnyhoKvoqJChIeHK23OnDkj9u7dK8+DSiUCAgLEgAEDRHBoZRtVQLAiuAFhrF+pUUuSSiQlJYngYN85rKo5BgSHC32tpp7FgSS00bVFSJdRPgsCrjEnPh+Vxue7JjLRIyA8wqV2S0WIXv0JCAhQhEDVuWzdvvNV90ql9cHY8BZZMMfJGrYmrKYI7jBU1sbVGqEKCFHaaqNre7Q2tc818xFyQUHK/7VqyfeeOqxm5XwZTJX9xdSpfIaa9REBddsqfXvnKrzfE0KlD7zhnIV4nqH69euLvXv3irKyMuF0OoUQQqxfv15IkiQWL14shBDVBF9BQYGYOHGi8lm7dq0QolLwzZo1S35fHDqkHK+srEw8/PDDAhCPP/64cv+NGjVKAGLy5Mn/prfW/z34g1v+FyEXfq2eb+SFN+qsajRbue3arBSyrywVl6UMa5UCoYFNehE58CnMp3aR9/Nbyna1VkdQoJHi4mIA5a8XzZo148iRyirb3bp1U/x4XhQXFyv+E0Cm1nA5sV8+haFuG5mg2hNt6sjPQNIHyukSajXhtz1B4W8y04ct4yjmKtGZzuIrV7F2CGyXjit12fQJTXDkpuP2RJx6cwyFtRyHtbxK0jjgcnD11AbU74Q6OJLg9ndQtOErQCjk28JzIRYvXsyRI0do27YtDz74IDt27GDZsmVotVoaN27MkiVLeO+991i5ciU3ws6dOyksrGRt0Wg0SupKWFgYxcXFrN+4CYdN9ttJugD0NRtg8ZRIUgVF+hR8FcJNkUuHVuubuymEQK1W43K5sJQWonJ6iLHNxThy0ykrzcd++RQuD4OMpDVgqNsO6/l9Pj7DgOQOWM7s8QnqAHDmXwStAdxWkFRY0w95fLfI110I4uo2JOtcGhaLxWffRYsWUbNmTfbv3emzvWqivjf1Q3iikZ0ludgyT2Ko1RTL+f1KoVoAbWQiwm7FWXxZmcdmzZqxadMmpU1ZWWVEcEaGh7ygSpCRSh+I22mXfZgO2V9uSGpBxG2PI6nUZH01oZJqTgiKNn2D8NR8NLUaSMStEyj94xeKNn1NQN221LpnOrbCbEo+f4jTp0/Tvn171Go1w4cPZ/78+SxcuBC9Xs/8+fOZP38+Rz05RF9/LdPiDRkyxKdAcmhoKLfddpvy3UtXGBlf6Vsf8+lvZObL935BUYmyvbxcJk33B7fcPPzBLf9LqKx2fm2hVxVVo9nWHLus1NmrCoM3Ak5SYWzczec3e95F8n6e4bNNa6gUeg8++CAPP/ywz+9Vi2vWrVu3mmDs2bMnjz76qPKC0UYkgBBKQIA3EV3tKSmjCa1BwsSFRPSfiEofSNn+lXLtPq1MP6XSB4InEb/G2FkkTllFYBU2jYj+T2Jq1pukqauoPfZdDFr5Vv36668JSukOyEL+WuV+4ibMUfoJbn8X0Xe+gCa0Bua0nWijk3jwu10KFZzJZEIIQUVFBd9++y1t2rTB5XIpAS01a9YkNzeXX3/9lbZt27J27VrcbrciMEEOjBFC8Oqrryp1D6ti1So5OrCgoACXy+VTJFVtCpcDbzxzYUhoQq1nf/LZP/q+D2jRd3i1fqsGj5ia9iThyQUY63cCQDhtWNIPKQFDwlKK7eIhVEFRPn1YzuzxdFY9ilYdGCb/I9yAqKxxJwRIaiJSugAQEBDgs5/b7ebdd9/lRnBbynDbzBhqeaqcu53YLp+WA4Wu4m81n0hVhB5AcHAw69atIzk5+YbHqApXSY4yx14BZ0k/qJTcUgeGVmnsIKB2S4WwwZvG46X+08UmY3W6cRsj0HmCvkZOfJmUlBQWLlzIzp07EUJgtVpZvXo1q1evVhZDJ06c4NChQyQlJSFki5ty71TFxl0HGD9/H52nVgYh/ZEH6W75+i1fv43x8//gwIUCDhyQSQ+aN29+0/PxT4df4/tfwIJfN/LI869gvnTimrRIAEWpczGf3q1QdEX0nwTNenMsq+SafXq1AnVAMMFtB/vkhcl1z3ylqyEoDGtZMSCT/JaWlvLjjz9SVCSvrIcNG8bzzz9PZmYmeXl5vPnmm4wYURnVt3PnThYtquQ99NZW82oUbnMJSCp0sck48i6gi62PpFLL0ZoBwXK4vLdQanAUAfXaKfRlwm5Br1EptfUAjCERqDQqejSI4tHu9ej6sSz4pkyZQscuPVl//ObnH8BVmo/t0jH00bU5teBVplbIEZMVFRUMHDhQEXpt2rThkUceAeSV9N69e+nXrx+rVq3i4MGDZGVl0bp1a3r16kXbtm1p27YtSUlJihDypix4Ubt2bVJSUpAkSRGWRQd+U353FmZRViV/zXbpmE/ZI4Bzs0ZzpqL6fVCVrLp070+U7q0UmMJpR9IH4iqpFMRuazlct05d9cWV6yruzKqaIiqJIyvlKgXeiOO/BiGnV1SpxoDLgb5mg0rNvgpCu4+leMdCcNq5fPky69at48yZStabqvPr1YRbdO3LoW3rKo9YpV9vBGvButmYz+2rRibgKM4BtxNJayBiwCR5eBXF8ql7ooZL9izFUShrlT//tBwK5WciJCSEuXPnMnfuXPLLbSzbn8kbjwwn6+R+ut73DB3GPUJBue26HKQA7894DWPDTVguyppiQP2OqHQBBNTvgCYiHnveReZPe5gFbgeWS5do164dPXr0uOGM+1EJv+D7N2Pp0qXcN+IehNt1XVokAFv2aTTB0fJKuEpKgfsq7VAX10iuDu4xG1kvHcVlLq5sbzejr5GsUH0BGOq0pfh8ZbVxlUrF9OnTueuuu/jmm2/o1q2bkg80Z84chg0bxvDhw+nVqxexsbE4nU46d+7MzJkzCQoKoqKigvBbH6F0/0r5xarRow2LJbTbfdguyRJJ8qyu9XGNrsuxqYuug6U0jzh7Jv0atGdj+67sPbmNoMgaPHt7K4a2ildeDt6X2ujRoxk2bBhHCiG461hsrurqsyY0hsAmvag4tqmSMs2zvy03ne2b0pW2TqeT1atXV6vsDbI22KtXL1q1asUTTzxB165dmTJlCmlpaYSEhPDDDz8wadIkHA4Hbdq0oW3btkpR06o4fvw4devWVRLAryZjRq1BExSJs/gKrrJ88n7xnS85304gqdUI13VM354k+KoQ1xAg3nqBCjwV7a9thriRaUJS9nFdd0w3hteUWHVszvIiX7OrZ7zFqXOVTWazmfvuu89n16oauNvz0DROrkN2zCtYL53AmnHUkwYjQKVGG1MHe1YawmbGfHxLtbF5y0wJl5OKIxsJbjdE0Qq9qSe6mLrKHFiyTiGpNRgCAujQoQOxcbWI7TSYvFrdAcgvl3Msj2aVkrPxNB9uPE33BlE82q2eDzNNhU0+94DkDpQf3yo/55IKR34GZQdWE9RqANF3v0rRhi+xZhwFSSKoYWdGv/T+n0+4Hwr8ps5/I8xmMw8/PAHhdmFs1JWaD8wmsv9EooZMIW7CN4TcMlppW2PkW8SMeB11UMQN+4y6/VmiR76NlwTZVZKLI+8CWg9tluXcPkr3r/Qx3VgvHSEhuTGRkXI18x07dii+q6q49957Afjuu+8YNWoUPXv2xF3F7CRJEo899hgAJTsXY4hvTEByByStAbfdguXs74omart8muId1ZnxqyK4w12AxIHlnzHz/r7snSvTVb3z2jQe7lqXCJOeZ599llGjRikm1sOHD9O7d2+m3dODlwc2JkCr5qp0MR+4bRXk/fIOOT88j9EURJ8+fTh69CizZs1SzqmoqIjg4GBiYmLQaDTs2rWLCxcuIEkSkiRhMpm4/fbbiYqKIj8/nz179jB16lR++eUX3njjDaKiokhNTeXTTz/l0KFDGI1GnzEEBgb6aIKS1tc0iMvpEYYSqNRY0w/4noOH7iy0p2/F9qpo1n909Y2SSqlGf/UCoGob+a8adL7jVpvCFb+e7qqaiZJKjbF+B59tw4YNqzYEdcj1/U4lu5dRcSJV/qJSg3BTtH42AOG3PlrNhF8VBQUFV22RQCfPqypIvs9XHc3BkNCE0K73UmP0Oz61Ih35GehrNSV27EeKiTx6xBuyMFNrUBlDMDaUyx0VbZ2LcLvQRdcBUNiEDLWaIoQbkFAbQxEOG8bIOJp06Mb5s6fZ+f1MSs4dwuZ0U2PU2yROWUVw28FYnW5sTjfrT+Qw4us9LNhzAYDDl4optsgLWrfdIrsDNDoQAmdhFoXrP6d4x0K0oTWIvvsV9HENkTQ6yk7v5al7bqN3/0Gkp1cu6vy4PvyC79+InTt3UlQkmwJvRIv0V1C8/QdKti/AuxoPTOlB/GPzqDl2FkGtb0el0WE5vZuQDpW0XbUf/oKDBw4QGCi/BOfNm8crr7xSLcG4W7duzJ49m9jYWH777TdGjRqlEDnr9bLm9cYbbzDttTdRB5ioOJ6K9eIRNCHROAsuUbbvV+Wl4Cy4RPmRDTc8l4CayRiSmoMQOBzyA//QQw/x0EMPKW2WLVvGwoULlRV9amoqFouFRo0aMbpDEp/dlUy07TLCaUd9DXNd+dHNmNN20L51C/rf1pfU1FR69OihUMYJIXj22WeZOHEiubm5TJ48mU6dOvn0cfToUUJDQ7FYLMyZMwetVsv27dv58ssveeCBBygvL2f48OFER0dz9uxZnnvuOR+zcEVFBU6XW6k+IewVBNRrV3kASUIymDC16IuqqukPuTSRV3Mr2vAl18ORNfOrbxRuZV9vuSR1cKRvG2/AiXChr0JSAB4ztieB21VeVBncgmz2dFnKMIRV0qAtX74clcr3leK2eEy0KjXGRl2RqghX64UDlSTlnuM4iy4j6QMxNetD1KDn5HqHHqi11zcNgkDyVBPxVuQo/WMFmbPHkbfibS7PnaQU9VUFBBH/yLdE3fECOT++wsV3BmHNPElAUgtUAcEY4htjTPYIdbcTUJG/6kNK9/0CyIvLjA+GcWX+s7I/sEEnpXSVse9TlHZ+Al0NuSai08OAdC2UH0vl3Gfjue+WBpiCQ7m1R1fcTvl6WM7sxW0uRhMSTWCz3kpBZsvZSsYlZ1k+AbVbYWrWGyQVm9auZOzYsTeYIz+88Js6/42oGujgLQZblDqX0j3LlO3XY4+vOJGKvUq0YlCbQaj0gUp9MUmjI6TzCII73K20Ce/zMOF9KoNWgloPRJLg1sYxRJj0XLhwgZ9//pk33niDgQMHIklSNfqkUaNGKawUmZmZvPCCXM6ofv36AGi1Wqa//AKXk25lw4mcGxrDbgSVBK/d0YKLwUN5663TmM1m4uPj2bt3LzVq1KBv377cdttttG7dmubNm7Ns2TIeeeQRCgsLWbZsGWazmenTp/Pxxx8zZswYHn3yee6dNpvLFhW9+g0kuMV7bF/4Eft/nUtcXBxtmjcBoFatWpw7d47Lly9js9lo27Ytc+bIwTAtWrSoFmQAsgb8wAMP8MYbb/DUU08BchTo9u3bAWjXrh2hoaG0adOGU6dO8cUXX3DlyhXuueceAAYOHEjd0a+x8MefyPvpDVQBwYT3fpiss78DENJ5pKdUTynlh2SfVGCTnhgSmxNQuxWZn8qauJfH0+vDAtmfZDab0Wq11c21ai0qvRHhsKIOjsKQ2JzgNkPQhsf6cJeqAoJwW8qQ1JWCLbBZH4Lb3cHlb+R7oWqEpBcxw18jIv8Ixxe+hd1uJzg4GJfLpfDLqoOjCO0yioI1s9DHNSJq8PNkfFgZpGP0RNuCbFIsP7wO3C5PPUFtteM1at6aY/t8uVrVwVEKO5EqIAjh0Hk0ZJfMmVqWj+X0LlSGIIyNu6HSGSk/tJaizd8iXA7c5mKCOw7D4OFZNdRqSvnxzdiyTwESmvA4nIVZmL2aqQfCbsZRcAljk15E9HmY4uBIyv74hZxf3kUbXhP7lXNoo2tjrN+x2nmAXGYrf/UsJLWawMbdUbkdFF85p3CBgkAXWx+XuVgmHHc5QKVGExaHcDqQNFriHqqkMfRGcZ87f/6ax7saixYtYuRIOchq4sSJigXknwK/4Psfwuu8TrtSSqnVSbBBQ8MawdzdOp7o6EoKLmdpHtrwOPTxjTE27nYVSXF1WC8cwnrhkM+2xCmrCOk8Akd+BrnLXqN46/eog6MwpVzfqS2cdrI2fMcKUyYdO3Zk+vTpvP7669W0PS9atmxJ//79iYiIYPHixbjdbvr370/dupVVvYUQhF/5A7cjRonS/CtQSfDu0Gbc1SoBOrxIVFQUEyZMYMqUKTz22GNkZmayZs0apk+fzoULF2jdujV33nknJ06c4Pfff+frr79m+vTpREZGMmjQINxuN29Om8reefMAeHLqnTRq1IjwB5YCkJWV5RM6DnD27Fl0Oh2TJk3i/vvlckdPPvlktbQBkMmshRBERMhmaJvNxvLlyxVBs3z5cp/2OTk5Sog5wLZt2zhV8goF++V6h4FNfK9Xye4fcRZfwZ5zFq8mX3FsM86iyxTv/pFKEmvZJ/b+++8zaZJciLdfv36Eh4ezbt06HxJpXUwd7DnnUQeGoY9riKuiGPPxVPQ1ktGGxyLpA1GbInAWZCjmT5XeRHCHoZTuWSabrKvcI1JAMMJuQW0Kw1WSi+QpXqyvuMLgwYNZunQp5eXl1K1bVyH5DutwF4HNemNq1puizXPIX/UhwlMU2FC7lU9KS1UENu5+ze2WohxUKpVsftfoUGl0uK2Vfkw5ClXCfvmUp1hz5bJM0uqJGvQcbqcdW9ZJyo+sB0AbXYeQjpUm2pBOwwjp5GuyLdm7nOIt36GNSMBQuyW2zBPYc86DcGM+tomAWk0xJnfEfHoPjrwLOPIugEqDMbkDksf8Wlilsok+tj4Bye1BuFEZQgio3wFtZC2ChZvMbx6vPJ/gSB+SdtxuzCe3URwUQVhPuTJL8Y5FuMoL5HQYSUWXO69fusuLzMxMHn30UTQajU+A1D8JfsH3/4nDl4qZnXqWrafl1abNpwzKFT7ceJouSUHoAoOxV5RSsnspEf0nYqzXDk1Q5J8KPm8VdC9SIrWcL3FhcYAuujbaiHhcpXk4C6/PnRigVaE9vZFVP33GpqXf4XA4kCSJsLCw6+7TqlUrFi9eTHl5ObVq1eLZZ5/lpZdeUn4vLCxk3LhxXL58made+Zwv9+Zeswjo9WDQSLw0oLEs9DwYP348LVq0ICVF9iPFx8dTUlKCwWAgMzOTxYsXM3XqVEJCQoiJiSEqKoqJEyfy2WefMXfu3GrH+Pjjj7nttttISkri+PHjtG7dmj/++EMR9sXFxQghKC4uZtq0aUrqwssvv8yQIUOqzU9aWhodOnRQ8sYSExPRaDRkZ2eTkZHBr7/+yu233660T09P92Hub9OmDftPHEK4HBhTehDa9V6fGn3aiATMp3aiCgjC1OI2QruPRW0wYcs6SdGW73AVXVaEU7s7HlTSB0JCQti0aRPFxcVERkYybtw4vvvuOwAGPvYqm1YspuLcPsqPbkIdGIqhbhuCajXE7bQT1bANeadlX6LbVoGhThvCej5A4eZvABAOG+bjqUrOnrCUog6PI7BhF0p3LUEXXRuDRsXp7SvZc0WOSnU4HKSlydUkHnnkEba6G1DhdoNKRUXaTp8qIV4/Zsw9byFpdFjO76dkzzI0oTEYEivJw6sG6OTm5lbykTrtuJ12WeOzywuQqkJCWMtwVQlCdZXlkz3nCZwlV3yCahwFlyjduxx9ZAJ5az9FePpCUhHUsh9hvR7E6YmMdRRcUqKZq8JlK6dg8QtyGoZKjcoYgnDYKNm5CHVgKEGtBvjUHrTFJhOY0h2EG1dZAXnLXqvWJ0Bol5GE3/oIJdt/oPzQb3gFuSX9IN47tPzIBmVetREJOEMSeOihh1i5ciVFRUVER0fTsmVLfv1VPr4QgjFjxlCzZk2aNm3KkiVLrnns/+vwC77/D9xsIvrmcyWE9p5A7q/vUXF0I/acc+hrNsDpJY6ugpLdS3EUZCpmm/Ij67FmHMXU/FZCazdl40tDSGnTiSsWPdaCLKwXDoOkwpDUolpfkiRXr36xf0Oa3BlLxzXfKknGgYGB1KlT57rntmzZsuv+tnv3bkaMGMFdd93F0qVL0el0REbceC6uNaZrsey3a1fp8/r+++/59NNP2blzJ06nkzfeeIN69eohhODNN9/EYrGwdu1aiouLueWWW2jQoAFz585VVq8//vgj6enpPPvss7z++uvs379fqcaQkZFBamoqa9as4auvviIzM5OXXnoJu93OzJkzeeyxx1i4cKHP2O68807CwsJYs2YNIAcBud1ulixZQkZGBqNHj+aOO+7A7Xazb98+oqOjfUr1bN68mSYdepAR0whL9mlUWoPs7/VU19BGxBFQu2W16hreiNiK46nkr3wPSZJQWQqZPHkyAAsXLqRfv34AjB07Fqu18k0vHf6Ffg3DafPKKjItWkqtDoINWhrUCOKpwR04c/YsPd7dTPqXj+AqycF+5SzZ3zzi8QVKRPSfSNGmbyqFlaTCVZhF+X7ZNC9ptJz7eAwGYaV9+/a8+uqr3HbbbeTl5REdHc0PP/zAhgOnGf7pJi7MGo0qMITEKatwluaR9dk4VMYQ4p9YQMmOhZXme50RV0ku2V+OJ/y2x+jZsyeZzspzqpqk7r2pvKZUSatXtEmvsFYioD1w5KWjMoVViyZ1FudSQyqhEBduYyhuczEIN2UHVlN+bLNCpACgq9kAXUwdnCW5ckUQl0NOxvcEgQU27Y3bXILlnFyk1pF/CfuVcz7RtI78S1z5oTJvVgoIRqXWKr5JZbtaiyYwjIB67bBeOKzkMlYNgIt/9FvcdisVxzZTuP4zVrzzOC67jZSUFO68806ys7MVkzzArFmz2LFjB3v37v3HmTerwi/4/iIqE9H/XMsRAgIadSXGFEHpnmXYstIoz7+EOjAEQ+1WGBt2Vtpazu/Hdqmy5p4t8wS2zBNy5FjtpvTq1ZvDB/dTnpeHxhBIQK2mBLe7A0OVaDu1BGqVRM+G0TzavZ5SvTolJYX9++Voy06dOt1Q47sW3G437733Hu+//z5ff/01gwYNUn67mSKgApR8vD+rqL1mzRqef/55tmzZQklJCbfccgsul4unnnqKMWPGoPb4oR5//HEsFgupqam88847SvCLJEmUl5dz4MAB1q5dS/fu3XnhhRfYtm0bBw8epGbNmowePZqLFy+yaNEiGjduzMsvv4wQgpUrV7Jo0SIGDx5M+/btlTFNnz6dp556CiEEzzzzDI899hhXrlxh+vTpfP7553zxxRcsW7YMg8FA48aNlYLBXrRu3ZozJw9QbrGj91wvSa0lrPs4Snb/iPnkdiSt4bplpQJTusv+v32/sn/TSpKSknj//fcVoQdywFJVeM2vM958XQnk8eLt0EBsJfn0aJJAxdBpXPn+GfllL0moAsNQG4N96ztKEpJGi3DYkQKCUeuNWNMPolJrMAs3e/fuZcCAAURFRZGTk0N0dDS5ubl0SI7lqZlf8wECd0Uxlz69T9F0teFxSJKE2yuskGvfCZcDZ/Flche/xOzZBex4LZbMTDnhfPzrn7Fs/Q4Kt8sLE0mjp2DdbO/eleP1VOjwyTv0QB0Yjru8CCX9w+WgTaST1NSN3Pv6HJbN/QLr+SqV1SU19itnlPau8kJcgWHyAsETGGTPqfSrVRzdiKZKJXldzfrkrZghCz1P6ogmPK6yagqgDauJvWoRYg9yFk4loF57XOUFPikwoV3vxW23YM/LwHxSthx5Uyxcdnk+mzZtyqhRo2jcuDHBwTKpxLFjx5g6dSqvvfaaTxWSfyIkIW60Tv/PIikpiYsXL7Jlyxa6d+/+nx4Ohy8VM+LrPdeswv2vQM7il7DnpuO2VqAymDDENyas1/0M7NScL0a3UcYwO/UsqafycAuBs0qin0YloZIkejSszA969dVXmT59erVjHT16lCZNmvzpmPLy8hgzZgzFxcUsXryYWrWuH4laUG5j2YFM0i6XKRpGw9ggn3y8G2Hv3r0MHDiQefPmsXbtWr7++muSk5PZs2ePEpF6PQgh6N69Ow0aNGD9+vVkZ2fTtWtX+vfvT//+/X0q3d8MLly4QO3atZW+y8vLiYmJobCwUIlw7d69O08//bTPQqAqvMdLT08nKSmJ8fP3seFkzp8y91y7L+jbOEa5D/4n6Ny5MzNmzCCkdjP6P/Uu2cvfQm0Kp+bDXynJ2cLlJOvL8bhKcwnpNILQrnK6hCXjKLkLpwKQkFSHvr17snr1ai5fvozRaMRsNivJ5A1TmqFPasHh3xaBy4E6OApJo/OQNEjEjH4Ha/pBReO7GitWrGDcuHEKyUJSy1vIcwVQ4fHPSVoDalO4p/6hLJgUgafWEjnwKfKr5kSqdeCSo1tVQZG4y/IxmUyUl5fTofft7NlYnY5OFRCM224Bl8NDwVclN1KtVYSfpDNWmkkBVGp0sQ1QBwTJdRXtZmVsIZ3vIfSWUT4BRqjU6OMaY7t0tPpEeHMtPUicsoryIxsp2vKtbxkxIDo+ie6d2rFy5UosFguSJNG7d29+/vln3nvvPaZPn85tt92GSqXi8OHDZGZmUrt2bYYPH86MGTOuPvL/Wfg1vr+A2alnsTqrC72qjuuqCO89/i/17w1PlrR6LGd/x3x6F8Jaiin+IQ4eVHOw3MS7G85d16woC0HfytVemEwmJYhj37593Hrrrfzyyy+0bdv2uuPZtm0bo0aNYuTIkbzxxhvXDPyoigiTnoe71r1hm+shLS2NQYMG0b9/f+677z5SUlKoU6cOu3fv/lOhB7KQcTqdjBw5kl9++YW9e/dy6dIl1qxZw6xZs9BoNIoQ7N69e7Vcuz+DyWQiOTmZw4cPK2bZ4cOHs3jx4usKvqvXlI91r8f2M/n/Xwsng0bNo93r/eX9gGqRu3l5ecyYMYO1a9fStYabxYA2KlERekAlPRkoleWhkuJMpVaTdvwoRqORL7/8kgkTJiiRpnfccQc//fQT2aoorH/s8CRhSxhqNZMDPwAQlB1YjTasslbhLWOnEK8qZNG38vM0Z84cQkNDFcF34eB2AupVauIqYzDRw18j+4sH8fq/1CHROPMzkDQ6bFlpMuOLJ/ldpdMT1uNRCtbMQqXV40a2hjw+azEPDukltwkMx11RybVaVbBE3v4MAUktcRRmkr/y/SrnAqZmvTE27ILLUkb+8tfB7cKedULeb/DzOAqyKNm1GICSnYuoOFlpfgTQ1aiHcFSaYCWt3iMobR7NVUIXm4ypRV8ANOFxaMJicbpdsq8zMJTA2i1ZNe8D2jZPwel0cvbsWZ588kk2bNjATz/9pNCjrV271ufY6enp7N69m38S/raCz6vtAQoVz3fffUdISAhvvfUWaWlphIeHM3DgQN58801CQ0N9Vulz5szh1VdfpaysjLFjx/Lhhx8CMr3SxIkTWbx4MeHh4UyePFnhrSwqKiI0NLTaSt2rNQU3601Y/0kAmM/spWTXYhwFmdUZKDwI7z0e68Uj5Cx6AXVwNLH3f0zh2k+wZhzFbbegNoUTULslEbfJkVxxD32hrALDb32UwvWfYbDk88FLk/hqWT9Ce97v83ICcFlKKd76PZbzB3Bby9BFJRHafQwioQlvrjlJw6xiACZPnuwTpPLzzz/Tv39/PvnkEx9qMpBNmzNmzOCTTz7hu+++8zGp/TuQkZFBly5dcLvdmM1mPvroI55++ml2797tEyTyZyguLubAgQOkpKTQsmVLWrZsyaBBgxBCcPz4cdasWcPMmTMZMWIEXbp0UQThjXyeVdGhQwf27NmjCL677rqLqVOnYjabb0qQNk8I5cX+DXlt1XHsf0H2aSQ3L/ZP+VMz8fVwdUQroNB93dW9NYtngzPvIsJpQ9J4mHKqaBheFh5JAsmz3e1y8frrr/PYY49x6pRcGNhLXeYKkYVZxcWjCqWdSm/CeukYrtI8RfNxleT6CL4D635k++VKs+HJkyeV/M5ff/2VDeVxfD/7PTmXTZJwleb70NwB6KISceZnIGwVPgElAO6qEYwen1xASARvrklDeM6xqtADUAWGkvDEAq4smUb+incQLrvsw6iS06gyRVC279fK42l04LSjT2yOPesk5Uc3y+10RtzWMlQBwZWE2B5ULa4MeASeDS9RhaFOK7ThcTjyLlK48SvCe48n9r5KthavReD4wT+4b8RQ2rRpg8lkUsixQ0Nl60/VdJ2xY8cyb968f2Q6w982gf3+++8nKEhO5r3rrruYOHEiFy9e5M477+TIkSPceeedBAUF8dlnn1V7cQO8+uqr3HLLLZSWljJr1iwlIu/NN9/kiy/k/Jdu3boxbdq0vzw2y/n95C1/HWdxDsbkDjLbA6AyhgJyRKY3P08dHElQm0GYmvWh/PefMZ/aiTYsFlOz3mgj4mUOy2ugZOciVGo1019+gbHPvHJNoSeEm7zlb1B+6DeE0yZXZ886Sc7CqVjO7cPicLP1dK4yH14mkkaNGnHHHXewceNGJk+ezLRp0xSGlpycHG677TbWrVvH/v37/1Toefus+nn88cdvuE/l+AVLly6lfv36BAUFsWbNGt5//32effZZ5s+ff9MCyYvi4mJ+/vlnxo/31bQlSaJJkyY8//zzpKamkpGRwf3338+BAwfo3LkzDRs25Omnn2bjxo3YbLKPpCqJsBdewedFdHQ07du3Z/Xq1Tc9xtEdkni6R22Ew3ZDxhl53KDBTRPH6WsGBN0svOeRmJgIwMMPP6zkI/bv35/k5GSc5YWU/vA0xetmk7twCpazlRR3OrUKvUZF38YxvPTAncr2b775hrp16zJr1izl2gPsyrSjiYiXA2M89GNup00mihZuhfxaHRLtI2ArLvvmoFksFrKzs9FoNIwcOZJPRrZWhIsmNBaEm7yf3qicL62e8D4TiBn1DpoqAlWBw0LpAflaeX1m27dt48ruFYqAvhruihKuLHgeW/oBrr5g3kWCOiBIJifwpvY47QQ26YnaFIFw2rGe34f1/D7cVtm/ebV5ErXWR5ACaKNry3y9Hk3Wen6/IlyvFuggv8gLyu2svQQOrYnVq9cwZ84cdDodL730EgMHDqy2zz8Zf1uNb9q0aXz77beUlZXx+OOP0717d/r37w/ACy+8wCuvvEJ+fj6xsbGsW7eO06dPo9PplP2XL19O27ZtyczMVAIbevXqxQ8//ADI0U1jxozh559/5s4777zmGK6Gy+NPK9sv+wJ0MXVRBQShq9kAe845OUDgKmjDaiomz6Itcqh5ctOWFMe2RRUaC7pKM55BU7kOcVUUkZycTKtWrTgYqMJ9KJ3ird8rvwfUaY0qIAhb5gmQVLjNJagCw2QBaDOT98tMEib+gBsVgRGxGLDjcDgoLS0lLS2NdevW0bdvX37//XclR27cuHGMHz+e+++/n1deeQWN5uZuj7i4OIYOrWSKueWWW/50n/379/Pss8+yd+9e+vTpwy+//ILNZqNLly48/fTT3HrrrTd17KooKioiLS2NO+6444btQkNDGTp0KEOHDsXtdnPo0CHWrFnDtGnTOH78uHKv9evXz8en2aFDB157zTf03GvuvPvuu68+zHUxoVdjXnrkXm6f/Am7LpTcMCCoMVlsWJIKPHPT/f8ZIiMjOXv2LABGo5FNmzbx4osvkpqaSu6JzYTFxNO9dUNWbVVTDgxtE8+LD/QkwqTHbG7M5+++Tnp6ulLBQ6PRoNPpqKiQ/V9OpwtDQhPKCzJRBQShDo3FUSXVwFki07MFtexf6SaQKrk/vcjKktMkVCqVok26PdYVXWx9JK3ex9yoMkXgyLuILqYumpAaHt+fLxxXvMTWQo5UtVZQvFFmxJH0JrTRtbFX9bOpVLhtZoI73k1YtzEUbvxKFjxulyK0vWMIT0qh6HI6wmYmuN0dcuWG25+m9I9fKd4+v9IyVIVHF/Ap11QVJk8O5M3AJeCPi0VAFIbBrxEF3H0NLtCq8BJp/yPxb6z19z+Gtyjjli1bhBBCNGokF61csmSJ0qZGjRoCEOvXrxfp6elK0UaHwyGEEGLQILkSuLc6tsEgV47eu3evEEKItLQ0ZZ+ioiIhhFC+p6enCyGEeOmllwTIFb9rTV553WrNV39COt8jYu55Sy6KGRwt4h7/XgQnXV3MUxKh8fXE/Z+sFl9sPVutD2/B0aC2Q6r1HTlkyg2PH9F/kqg1eaWo/9IakV9mFR9++KHy2/jx45U5rKioEM2bNxcajUb88MMPPtfgl19+EW3bthWmoCARHlNTtBwwWtz75TalYjwgunXrdtPX9Pz582LkyJEiNjZWNG/eXAwbNky4XC7hdrvF6NGjxYgRI4Tb7f4Ld4kMu90uJEkSTz/99F/etyry8vLEDz/8IEaNGiUiIiJEkyZNxPPPPy9SU1OF1WoVoaGh4sqVK0r7wsJCERwcLEpKSv7Scdq1ayd27Ngh8sus4outZ8WkxQfF/XN/F5MWHxRfbD0r8susQgghjh8/LurXr3/T/brdbjF16lQRHx8vdDqdiImJEbfeeqvIz89XnqfHHntMmEwmYTQaRb9+/URhYaGy/9atW8Utt9wiQkJCRGxsrLjnnnvE77//LjZu3Cg+//xz8dBDD4nY2FifQrh6vV4MHjxY2RbW80GR8MwyoY9vLD83KT2EsUkvoQ6KFJIuQOhik0XU0Gki/okFngKzKmFM6SH35ylo/Oyzz/o8AzVr1vS5t40NbxEB9TuKgOQOPttVAcEiILn9NZ8HXZVCutro2qLGve9Wq+pe7fnTm3yKRQe1GaS8CxKnrBIxQ18WcclNRUhIiNBqdUIVECxUpnClWLK3+LGkCxCSprJYb0iXkcr/cRPmiIRJi32+e48XPfx1YUhqIVSBoQK1VmjCYkVotzGi1uSVPuO61idp6irR8OW1Yv7u9L90b/4T8LfV+AAldN1rhktKSuLkyZNKkmxBQQH5+XKtLK8ZxwuvtnJ1JF9cXBznzp3jzJkztGvXTumrKrzRaV7qpWPHKtMMrBcPK6YKXXxjNKZwbJknCO54NyW7luCuKMaQ1BJtZAL6uIY+/aoNQZia9qL0wrEqWwXFmWdZPPluNkX51koD2UwV1GYQ4b0eJLyXb5i8rcoqWpeQQuyod+R5Wf8F5QdWYc89j764MVJUPMsO+PoUvHObnZ3NqFGjiIiIYOrUqTz77LPUrl2bjh07sm7dOgYPHowhKBRtYhsq8i9xcPUCTmdcIXLAJAwa2Vy0Y9ceAgKMhIaG0Lt3b2bOnElsbKzP8QoLC3nzzTeZO3cuTzzxBHq9nkuXLvH999+jUqmYNWsWR48eZdeuXX8p+tKLvDw5PPzqOoN/FZGRkYwcOZKRI0ficrn4448/WLNmDc888wznzp1Dr9fz5ptvMnXqVGJjYwkLC6Nbt278+uuvjB59DaLo6yA5OZkzZ87QuXPnGwYE1a1bl4sXL+J0Om9KA9+0aRMzZswgMTGRBx54gPz8fHbs2OGTA/ftt9+iVqsxGAysXbuW999/nwkTJvDbb78pQSpxcXEUFhayaNEili5dSseOHalTpw6rV68mPz+fxMREevTowalTp5g8eTKDBw8mokY8hTlZaKNqkffTW9gyT2Bq3pfw2x6/5jW1XjwCbifqkBiibn8Gbn+Gsj9WULjpG7Zv386PP/7IsGHDMBgMChOOWq3B5XJiSGyKseEtsusgMgHhsFF+eB1uSynqwDCfdAZJH4ipaS/Ce48n96c3sJzegyM3nSvzn5MH4smx08enUGP0O+SvnoU5bbvsZ7OVY714xCepvioM9dpTr2EyOStmUlxcjCswkiKzA4dKg6s0V8mDvDoOoGRHZa6ouI7GBygsMYbEZjJzy+ndFG+dh6QzENz69uvuB/jU9QT+srnc5XLxwAMPsGLFCkpKSnjmmWd47733/lIff1f8rQVfQkIC58+fZ9q0afz6668MHz6ctWvX8tZbb3H+/Hn279+P0+mkT58+1K9fX6l0fSOMHj2a6dOn8+STT7J582YlKbkqWrZsyc6dO3n88cdp0KABv/wik9OqVVIVLj2ZKUJdpw2G2q2oOLpJoU8KbNxNMVFYL1ZWNa/4fRmuExsB3/phBw8eZPv27de8qSRdAGG9ZNJmuZRRJeOLqVV/havQkXOegt8+xVVRrFRIcFUUkbP4ZfIDQ/l0VwrO7BPKvsOHD2f9+vWMGTOGRx55hBdffBG1Wk379u0ZPHgw77//Pu9/IZtmiagNhiC0sfWxXTlLxdFNhN86AStyOLkhoQkagxFLxn4WLFjAuXPn2LVLpqOyWq188sknzJw5k6FDh3L8+HG++OILDh8+TGpqKnq9ns2bN/P222+zZ8+evxxt6cXy5cvR6/UKp+i/Amq1mg4dOigmzitXrjBhwgQ2bNig+CD79+9Pq1atWLRo0f+X4Psz6PV6atasyYULF6hX78+jOr3BIPXq1WPYsGE0btyYqKgo3G63EnXZt29fVq5cSXx8PIWFhcyYMYM5c+YgSRIul4tWrVoxdepUkpKS6N+/P3l5ebz00kuUlpYyb948YmNjOXHihHKtvMd0uOQFauGGL3EWZvkIPUdRNmX7K3lpAxt3U4idVboqvmsPxdfBgwd54w3Zf2exWBQCBpfn+XNcPsXlnYuv6ZsLqNOGiNseVwLFTE16Ke4GcS2KLm9ieZFsWrVlpSFpA5SEeGd5gWKStWbIi1bb5dOU7l9JcOvbKbU4yMzM9Jh+Mwlq1AVJb8RSmlu9DFRV6IxgN1O8azGO3AvK5txl0wm9ZTTGBp0wNuhMaPs7qBkVToXNybll71JxbBPW9IN/Kvi8sDjcPPPKDF7L2MG502m43W5eeeWVa/LSVsXy5cuZN28eERERSlkuL8n71Vi6dKmPu+Pvjr9tcAvIARn16tVj9+7dfPTRR6SkpPDjjz+SkpLCsmXLKCkp4eGHH/5LtDsvvPACEyZMwO12k5qaytSpU5XfvD7CTz75hKZNm3Lo0CEyMzMZN64ysdhQuyWmVgPkyC2XE8uZPVQc24xwu/+0pJC+Rj00kocXUaUiLCyM5s2b06JFC1q3bk3NmtUd8iGdRiirZUf+JR8Ht7uskOC2QwA576r86CbsOefQeKpuqwPDCGreF+GwkbbrN2VhkJKSwrp167j//vtZtGgR06ZNUzTAAQMGsGXLFl75bjWHd20BwHrhIGX7fqX8oHeRIJTggLjH5hE5+HlC+z5O+LA3AZnhJSsri/nz59OgQQN27tzJ9u3b+fzzz1mxYgULFixgzZo1BAUFceHCBUaOHMkPP/xQLdH6r2D+/PnUqHH9Ejj/CtSoUYOHH35Yqco+a9YsnE4ny5cvZ+3atdx9990sWLBA0T5vhJsVfCAThJ8+ffpP2wkhaNasGUOGDGHnzp306NGDmJgYAgMDCQoKIjtb9nlVVFSg1Wpp1kzWYjp16sTly5eVpObhw4czdKgcGejlaL148aJS8qZp06Y+Vde9aS7eOnjeYsrmU7vI/XEaLkspjrwMn3s3d+l0nMVy5QJnWQFZXz5Exvt3UfibnJCemJioWGO8QW4ABoMBjUbDre2b4yovlHP5wmLl51HRKq/O9ZG/uyylClWaqdUA4ictRhMep7RSBwQjhKDmg7N9SLLdFSXKuB0e4nhnwSXMaTsByDx/WvF3ApSn7cR23lNaqqqm64kcDevzMDUnfEOwJzXBcmo3jryqBYwl7J7vuugk0BnJLrFSYnUiPL7BqlUrbgYVWWcox0BCQsKfN/bAe8/179+fjz/+2Cdtp3379kycOFH5JCcn/6Xx/Kfxt9b4unfvXu3l0KZNm+sGEngj8apixYoVPt+dTicff/wxn3/+OYBSPiY+Pl5ZwbZs2ZIjR4747DdnzhzGz9/H+mOZhPeZQHifh3EW58g5Occ2Y2zQEVvGUblq9XVWeC1atKBuzHA++eQTGjVqxM6dOxVWhXbt2rF7925FyHlfdvYja3E17YU6MBRTs96UH92I7dIxIvpPwpDYTK7ZBai0euIfn4+k0XJl/nM4yUIXXRtTsz6EdBrGHS3iSLycylNPPcWlS5fYv38/Bw4c8CHSVuYoOA6pST/YIi8oQruP9Slz5Ci+gja0Bs6yAiSNjpLtP1CRth23rTKBt2/fvphMJl599VUWLFhA27ZtKS8vR61Wc+rUKWJiYjCbzdxxxx1MnjyZXr16XXPObgbPPPMMf/whRyHOmjWrWt7avxLt2rXjjz/+QKVSccstt3DLLbcwY8YMBgwYgNFoZPny5Tz22GM0atRISZdo1apVtXI9f0XwJScnc/r0afr3748Qgry8PM6cOVPtc/bsWfR6PcnJydx9991ERkayb98+tm/fzgsvvMAPP/zAxYsXeeGFF3jssccU94B30eNdeHgFjsPh4LyH7T8xMVFh/Nm1axfBwcG0bduWPn360K5dOzp06IDbU/rIa2Z0O6zYc87jtpkp/f1n+VhBEQTUbo2zJAeBG1QahLUcTc2GGGq3wnL2d1yl8vl16NCBY8eO+Zhp7XY7kiRRQydrY8JhxV1RjEprUI5vvXjEpyqC+bSco6aJSFCeTWNyB9QGE7qYuoqgduRnkLtkGsLlkJlVPNqaLqYOUXe+iPn0HuyXT+MouIQmNBZNSAzlB9dgL7qqsDAQExPN5cuXfRLPZUgUbfiSog1f4RXIwmn3Ce5x5F+kdM9lAlO6oTIEkf31I7gtpYR0GYn5xDZUAcE+zyPI5tLC9Z9jPvs7bms5amMoupg6RA+Vo9Yjb38GvUZF3YOf+9SGvB6qEl/Mnz+f+fPn89133yn3yG233fanGuPfGX9rwffvwOnTpxk+fDh33HEHTqeTb76RSXmffPLJP933se71+G3DZrJ/eR99XENPVKVsP1fpTaiDZB9dUep3lO5fhTYyATz1tYTdzMaPn+M3z4rx2LFjhISEcO+993LixAm++eYbHxqhdevW8eqrrzJv3jycP04jZuTbqPTVzYC6GnUxJLXEeuEgVxZOQR0QjC3rJOrgKIXl3p19kj2HvmX1OTlaze12U6NGDb799lumTJlSrc/ZqWexVUnUL9n+A/ac80gaHY68C7gsZcQ/Mgdr+kGZMsrlQDKY8OYcIUk8/fTTjBs3jlWrVnHlyhXq1KnDkSNHiI6Opm7dugghePDBB0lJSflLgurqahjWy2dZPOsjH9PxvxMRERGKqa9p06bK9nHjxvHll1+yYcMGbDYbO3bsYM2aNdx7770UFhbSr18/+vfvT58+fQgLCyM5OZmzZ88ihKjm/xJCUFBQ4CPUfvvtN+bPn8/Zs2fRaDQkJycrnyFDhij/Hzp0iLFjx5KUlITNZlO0vKu14bi4OEpKSny2jR8/nq+//pp58+ZhsVi4ePEiubm5pKSk0L17d5xOpyKwJUliy5YtbNkiWwUaNGgguwKQ6ci0UYlUHNsMah2O/AxsmceRNDpqjPkQjUkuCCtcTlwleZQfXocj9zzOkhwfKq+mTZuSkJDATz/9pJhp3W43RqORrVu3KuWZJLcTbUxd7JdPI5x2xdTvhau8gLL9Kwnpeq+yrWjLt1Qcr61obQD6Wk3l9CJJwtigE+b0g+DxzdlzzlNxbJPS1ll82cOdKajdfRjHD6+rrH0ohJIWA6AOjpZ9fZ7SQrIw9Fh+AoLlmIGr7l3htFO8dT6SWoPbXIyhbhtKdixEFRBEzIg3FKuOF+XHNlN+eD3ayFoY63fCVV6I7dJxnzYSkF1y7Zzjq9GhQwfat2/P3r17adSoEbfeeiuNGzdWKpJ88MEHzJgxg7i4OEaPHs1LL73kE1X/d8c/TvBFREQQHh7O7NmySaVu3bpMmDChWu7XtdA8IZQnb2/LKztqykEu1grUxmBMLfsR1OI2HIVZcpJuSQ5uS5liFgGQXHbGD72NL774QgnW0el0LF26lAYNGlTjz5w5cyYbN25EkiTsOefJ+vx+VKZwnPkZABSsmUXBmlky/VGvB8ld+EJlEqxKjS46yZOQrMWSlcaeTT8pfZeXl/P9998TFxenCD5vYv+ixYsxSwEEtb9Laa+NSsRyfh8goQ2vSXAb2eShCY1RfJ7CbkVtCkfSaHEWZpF29jySJHH77bdTq1YtunbtqpwzyA/OqVOn2LFjx3WDWXbs2MFLL73E4cOH0eoMhDVoi6vtKNTGYGxON8Jp5/J3k9HFN0YSbqyXjpNVdHMP9v8E3ny+qoKvf//+PPjgg+Tk5BATE0OvXr3o1asX77//Punp6axdu5bvv/+eBx98kBYtWtC/f39UKhWrV6+muLi4muYGKMIsMjKSS5cu8dlnn5GcnEx4ePj1hkZcXBzJyck+VRu89/f777/v0+5qwdeiRQvWr1/Pyy+/zJo1azAajYwYMYKZM2dy4cIFUlNTady4MZcuXfIhxK5fvz67d++mWfPmlBcX4CjIxJ4jl0hyl+Up5kt1cJQi9EBmhwntMQ7zqV2yr+4qf11KSgrNmzdn6dKlPtvNZjMZGRmVwtDp8OG5dVvLfdojBPqEJoR2Gk7Z/lW4K4pwFl/BWZiNJrQGTo9vL/rOF1EZKgkTMj4crhhNQ28ZRegto66abQFIlCEXlq4qugoLK89FbQqXBZ8njSG4w1BUASFUnEjFkVNZSir2gdk4CjLJXzEDVBrMaduV/a3n9qEOiSFm2HS0EfFUg2cutFFJBKZ0x5y2A9uVs1x89w5UGh3aqERCuozCZL12GaKqi8927doxcuRI9uzZw969e2nXrh2zZs1iy5YtPPLIIwpLUt26dUlPT+f111/H6XTy1ltvXbPvvyP+cYIvISGB3bt3+2gOv1udpC09rNTRuxGv5LN396BGws9yRQKHy+dm10UnEf/InGvuF6BV0+rWeiSsXk16ejpqtZrw8HDeeecdRo8erZjChBBs3LiRPn36kJiYKEfb7T9DxokDBLXsR+meZbjKCnwiR1VqDZqQaLT12iJpdFgvHMJy9g+KUucS0fdRTGFR5Fc5/1tuuYXFixeTlZXFpk2b6NWrl5LYHxgcSkDtJj5RZzEj3vB5ISjwZH6oQ2KU8y794xeKNn3N+u17mYnMeTlgwADGjx+vBO9s2LCB9957j7179/r4iqri2LFj9OrVC51OR5OOPTh8+gJ521eiv3iRmHveRJIkuWRPRRHRw18nf6Xc9/d7LtB8z4X/UcL3n8Er+KpWijcajQwcOJDly5crhXxBTqrPz88nNDSUtm3bEhQUxMGDB3n11Vex2Wzccccd1KpVi1atWtG7d2+eeOIJkpOTiYiI8GEQ6tatmw9x9vWQnJzMhg0brvlb1eCvDRs2oNfrq2nJPXr0YPv27Zw6dYqtW7eSmppK+/btUavVdO/endtvv5333nuPTp06UVZWxtChQ/n222/RarWcO3uWxxYfZsPJKziKKt0Appa3UbL9B1ylebjKi1Cb5EWecLtwleTKid2SiprjP2dAp5bsfGcsJ06cUPhXx4wZw7x583jllVd49NFHmTBhAqdOnSI9PR2LxcLtr/3AEXOI3KcQuDxlhK5V5FkfWx/L2b2EdB5BSPu7sKQfJHfJy6iDo659j98Q8vWxnN9fSbatUqMymHCb5UVFSEQ0No8m7DV7lu77FTxm2aoo3vGDsl1tClO0X28Ajz62PmUeP7vKEERol3uUfQOb9MSacRTLmb2YT8p1H1XGUAJTeuDIOYct8wR5y15Dl3JtisKq7D5jxoxRitR6cfHiRfr166fQAv7xxx+cPHmSvn37sm7dOpYvX+4XfH9n3Ewdve5/kvg5ukMSWUUWvtx+/qYJhy0OFzPXn+HBt+fx8j3deeSRRxg5ciRPPfUUH3/8MR9++KGS+H11ZF7rISG8sSULtxCY03biKivwiRwFiLjtcSwXDuI2l6CNrIWzKBvrxSMIp52SfZXku3PmL+IcNdh6MI2skwd45t1vCP98Afs3yBphRFJDirQBGBt1peyPFcp+jqJsSnYvxZp+AFd5EQg3we3kxP+qUXmS5/+cKznk5eXRt29fJk+eTEJCAu+99x5Op5PRo0ezZMmSaoTXVSnnHnjgAex2OwnJjTlVokITVRsy07BlHMFZmImzNJ+y/auIHPwcmuBKR7/DJf6/w7dvFh06dODTTz9VvpeUlHD27FliY2OZOXMme/bsUbQ3m82maG716tWjb9++PP744yQnJ/Pss8/SoEEDAgMDWbNmDc8++yzt2rVTfIMNGzZEkiRq1apFXl7eTVOj3Qzi4uIUP7YQgrS0NFJTUxVhp9fr6d69O3369OHNN9+kdu3aPpr5hAkTMBqNTJ48uZKxZdcuVr94H+UhdRB6U6UbQGdEH5+CLfM4l+c9RUCdVjjLCgio00b2xXl8aaWbv+XIccN1fZ+HDh0iJiaG5s2b88ILLyjcsyunjUIbWUsWpOVFaCPiiR3zwTX7CO5wF5azv1OyYxGOvItKsWevz8xy8Qi5i17w2SdvxQwMSS0Jan07FUc2yM+ZtRxtZC1Cu4zElpUGTo/gc7sUoQdQUpALeOsQel4WTrssZFVqn7aWU5WFeYXd4jGLupX9vBogyL5SR0EGtkvHcTts6GrUI7z3Q0QOehZnUTaFG77CeuEghlpNCOsxjsyP7kE4bajc106dEEKwYcMGpkyZwtKlS/n555997rUPP/wQm83Gvffey7x58zh37hzJycmKqdvrJ/5vwT9K8N1sHb2qJM/XenkevlTM3N0XcQs5xaBkzzJsmSdlp3JAENqoRIJa9sfYoBMARalzMZ/ejbMwixeB+594jhlvTcNkMrF7924WL17M6NGjadu2LTNnzuTWW2/l0UcfZf78+UrosC42mai7Xr7meVWc2Er+r+9W2+42l/Bg63BqNJiomHIfW1+EpCql0CFHmJ0+ly5zH3qQcUSm5ApI7uDTl6s0n4ojlZqEIamF7MME3PZKs5fw/K81hTJgwACGDh3KE088oQQZ5ebm8v777/9ptY2MDNmke+74IeCQz2/2/EsUb/seEOT/+i6F6z5DeMzH5YfX4Swr4OH553g47xzminISExNvKtXlRigrK+PMmTOsWLGCefPmkZGRgVqtRqVSoVaradiwIXXr1iUnJ4dmzZrx0EMPkZycTExMzHVNuQ0aNKC0tJQXX3yRSZMmUV5erqTY9O3bF7VarQjBpKQkzp0752Ne/f+FEAKXy8XOnTsZNmwYW/ceIKBxd6LrtyS0yTAG9nmcNvVib2j9uJrBBmRhmtKwAXv3H6S8pKTSDdCyP4FNelKyYyGWs79TfmwzGlMEmpb90QRHEt7nYUp2LsaVfYJudzyCQQ1bt964UPOoUaPYkpbDnDdkRhuHxwUA+JQ6uhqSSo02th6OK+dkH6QkoQmNRQoIQjhs2C9XF7puSxnmk9uw56bjLLiELqYuhoQmVJzcRu7S6cSMepvyo5t8Cu2C5CkYIZDUWjlXr0pqQzVzLCiLA1Qa3NZyQjoNl6u6519EG5lIzQdne87PyuU5T2A+uQNDnVaotAbMp3dz+dsnMdbviMoYrLDJmE9so+wPOR1LExJNWY48TytWrODChQsMGTKEIUOGUFJSwuDBg7FYLKhUKoQQSh7zqlWrlCC48+fPU79+fTp16oRWq1UYda7WEK/G4cOHmTRpkpKydOedd/LBBx/4ROz+b+K/WvB5c0pu5sX2V+voeRM/f/pmFj/P+UgxtwCMeP8XrE41FWk75LInwo0mIp6Aem0Rdosn3y5VEXy27NNogqNxW8pwW0o5bw3AZDIxd+5cxo0bR7du3UhLS+PDDz+kXbt23Hfffbz55pu0H/UM0xemkrP1ByqObab88Dokb3RglchRL9O7qfmthN/6CBWndlPw60z0GhVPD2rHV+srQ7PtbkleRXpexnLk18tkffEQzuLLRA18GmOTnpjP7FWY+AEMic0wJDbHevEwEf2exNT8VjkPS6WRTVgVRagDw5SkeptKT9OmyUoultekptPpborL06sNBrcbQljPysR9R/EVSvcsw1mQqVysqi8RR34GKk8x0Yj4ZMynDv7psbwoLy/n7NmznD17tlrEZGlpKXXq1CEtLQ2Xy4XBYCApKYm0NDkvavny5dStW5cHHngAtVp9U7RtycnJLF68WPluMpkYNGiQQqx94sQJ1qxZw3vvvcfZs2e57777uP/+++nXr99N5fR54Xa7OXHiBKmpqaSmprJt2zb5pRUUS1zzEYTUH4skSeQ63eRWwOmzJey4UHZT1o+rz8drZr16kanWaAnv8zD08SUYkIDo9oP4aPrzyiLT7XYzbtw4nnrqKYqLixVqrblz5yo5tYcvFbNTaiwXty3OoXDjV3JBWJUKXWSCj0m14sRWSn9fIfsdPc+NJiIefVwj5XnVntvOx8/cw+N7SygGUGtlf1pkLVTGEOzZp7ky/xkkXQAxo95BpTOgCgimbN8v5P08A7cnJxHAkNicmHvepHj7D3IVdq0Op8uBpNbIEZxqrWz2vCr6Wx0ciaQLQNgtqIOjCOk8AkdxLo78izjyL1JxchuBjbpiObcPZ/Fl1EERaD3pGOrAMFzlBVjO70O4XKhNYWijkjy+eUClwVmSi3eUhw8f5vDhw2z9/RAf/bKbyJROchkjlYrY2Jrk5uYolqeCggIKCuQiuZ07d2b37t2sWrVKKfz80EMP8cILvlpyVZSVldGnTx/y8vK46667SE9P55tvvqG8vFyJqv/fxt+6Ht+f4ezZs3z66aeEh4ffkGz6f1JHr3zXIgq2/eAj+Go//h1OfRBZs8fhtpZhbNSVyNufkatqI/suHIVZ6CJ9TXmZn92PqzQXSa0lyGQkJjqaM2fO0K1bN6Vi95UrV3jggQf4bcNGjPXaQ0Aw1vMHcBZfJqz3w9ivnKXi2CYkjQ7hcqIymGSzR2466qAIDLVbYT653acIZ1TvB8jbKPvgvH6P3OVvYDmzR6kNVrxtASW7FqMyBBFQvwPWc/uUBOOESYvJXf6GTwAByETBwu30+CIkJL0RYatA0hpoeecEds6dwcsvv8zXX39NaWkpQgh0Oh333HMPkZGRvPXWW0qljIiICJ5//nmFeWXluk3c3q8vCDcB9dqhNgbjKMiUuUlVGhBu4h//HnVgKPkr36fiuGxyCev1EMFtBwPgOLeH7KVv+CyMzGazItiuFnBFRUXUqFGDsrIyysvLMRgMdOzYkZkzZ5KSkkJ6eroicCZNmkRYWBgff/wxBQUFbN68mR49eijBIXv37uXPcPDgQe677z6FQf9GmDhxIvn5+RgMBiUH0qsNdu3aFYOh0tzsdrs5duyYYrrcunUroaGhdO/enW7duslMMyeLeHfjOVRa/Q3N9ZIkl0S6nvXjRjiSWawUKHYW53BlwzfYMk8gnHZ0MbWJ6nU//Xvewv7Zk9i3Z6dCIr5//36GDBnC8uXLqVOnDleuXKFVq1b07NmT1157jebNm9PumW9Ys/sIWZ8/oBzPULsl1nR5oaMOiUZSaXBVFKEJjkKodThzz8vCRq2Vnx+HFXVAMKYGHUmpEcDp37fSrl27aqQWuujaBLUdQsHqD5Vt2ujanqTza0yeVg830DpvBvrE5tguHq6+PT4FV0XRNXlIvTAktSRmxOuAnOZgyz5F7rLXEDYz3bt358Chw5QWVwpqSWckcsjzOAuyKD+wGsdVfQcFBSkpJXPnzmXMmDGAzHlbUlLCwYMHcbvdTJw4kcOHD+N2u0lKSuKxxx7jkUceYdasWTz11FMMHDiQlStXUl5eTlRUFHa7nTNnzvxlMvp/Bf7WCex/hnr16jFr1qw/rbBwvTp6NwOn+9oaomzalG+G0C73KEIPZHPK1ULPUXRZMYVow+OIqlVP8WV4o9NADjufNWsWUXWaYL54hPJD6xBOmxI5amzcDfDk/gg3klojC73gKNyWMuxXzqI2+Ub9OZx/ruWGdBqOqcVtCOHGevEIwR2H+fyuCYtFSVdAdpw7S3PlMjP6QJCoDOd2WJkyohfTp0/nvffeo6SkRNH47HY78+bNY9myZUpAjUqlomvXrj55QaftYcSPehNdzYZYzv5B+eH1stBTa2Waq6AI1IGhgFzL7FrwJlQXFBTQo0cP4uPjCQ8PZ8SIEcybN4/c3FzatGnDtGnTlAi27OxsJeikRYsW/Pbbb0ycOBFJkqhbt65CgL127Vo+/fRTCgoK6NWrF126dAGgZ8+epKenK/lvN0K9evU4d+6cEuULcOnSJXr06EFAQACSJLFqlbxQadq0KVqtljlz5pCVlcWSJUuIiopi+vTpREVF0a1bN4YNG0bfvn2Jiopi6NChHD16VEmN6NKlC9988w333nsv27LdfLozG0lzY6EHvtaPBXsu/Ok5VUWou5TCX2eS8d6dnP90HOZTOxFOOzWSm2LNOEbm3Gf47oHOHPhdzrN79913iY6OJjExUakgf/78ecxmM9nZ2bzzjkzJ53QL2UdfZezaqCSih1WaX10luWhCa4DbhSM/g4BaTRQNS6U1ENigM6ZmfUBSUXJgDeEqG3v27FFMrAEBAbRu3RoAe246BWs/9jk3R2461xR6gNpTpaVyg28dS1VgGNoq7wdJF4CkkaOdVQFyXq8uurbPPpJO9rfZsk4qbb0wtR4kH0OSX+fGhl0QnjQqSa1FH5+C1iSTa6SmplJmlhfFKoNJfnYR5P/0FobEZtR8+CviJy5U3jMga2xeCsLff/8dkMtalZSUEPj/yHvr8KjOtfv/M5qZuHtIgAAhQHCXBHcpTnFoC6UU2iKlhWIVrLSFCrQ4xa24u7t7EpwE4m4jz++PndnJkARoz3nPed/fd13XXMns2bNt9n7kvte9lp0dwcHBjBo1ipMnT9KqVSv69OmDi4sLly5JZSVXrkiDkVq1JBNle3t7QkJCMJvNReql/1P4r4c63333XY4fP058fDxarZbatWszb948qlSpInvyzZgxg/Xr13P//n3Cw8NZvXo1Li4uRUKdhckR8+fP59tvv8VsFqjq98eo1JJ8eDHCkItjnXdwqi8VwWfcPELamQ0Y0xMQRgNqJ08ca3fGoUZ76QDz7+3cQrPFPKMZUyEnhpfrvsKcm4lCqbIKuznU6oRSZ0/m7eMYU1/Ky+1rdaZ1r578NqihtL38OPnWrVvp3r07Tk7OOHSbRoBbUJHrlZMfunCo0QHXVsMxJMcQ8/sHmLPT8R+1GmW+5JPZmEfMog8xpb5EZetUhOHm2W2S1XuFWoNL8/dQ6uzJunuKlGPL0XqVlcItiU/JvH5QvhgKjc7KiUJpY4cZyZbGMhgY8X6Bc7ZKpZJrsnbs2EHdunU5e/asPHv66aef6N+/Pzt27JDVISLj0jHbuqBx9cWY/Byl3hG1iw+5j68hTFgVy1sINVrfCvJsDyTFepDCq19++SXlypUjICCgxET8rFmzyMvLo3r16nh5eeHl5cXZs2c5cuQI9+7dIyQkROo4jh+XPejs7e3p2rWrrF6iVqvp3r07GzZsKLZGsjAcHBxwcnLi+fPnsqLGjBkzOHr0KJUrV6Z58+byaLh8+fIsWyZJyFkGEba2tnh4eKBWq4mMjCQmJoYXL17g6+tL586dadeuHYcOHeKvv/6S93ntaUo+I9l6MJTz+DrJR5aRF/8Ilc4eu8pNcQ4fKA/oYg4sZeivZ+ifX+y9bNkyBg0aVOK5ZWVl0axZM6Kjo62W69Vw7cgOwsLCiI2NRalUyh2/RqNhzZo17NixgylTpshlHUOGDKF58+ZcunSJH374geSMHPSvSI9pvYOL5FL1ZWqisnMm8+Zh8gq5OGi8yqJ29ibr/mlMGVIIb+fOnaQ4lZUdJnLzDNy5U2AZJkmYZRdTkA76Cg2siCm6UlXIvFHwvNv4VoDkJ+RmSDkztVKBfa2O+WUeCkRedn7Hlie3H3LePL8EwqFWR9JObwBhtnKkAMi4sqvguJRqbHwr8OyX/pLAha0zxrho8hKfolSpMJtMEnFGbYNtxSagVJH37DZ5L6N5sfpzEEjnWWhEpNHa0K9fP+bNm8fvv//O+fPn5d+mWrVq2Nvby2HRdu3aUadOHSpUqCAz1V++lK5FYW9Ni7n0ixdFi///I/gPiWGXiAYNGoh3331XjBgxQjRp0kQAIiQkRAhR4M6g1+vFgAEDhKurqwDEpEmThBBCHDlyRAAiMDBQCCGs3BnKlCkjOzMoVBqhsnMRdpUiBCgEKITvB7+LwAk7hXOT/kJftrawr95W2FVqKiuoe/efIwIn7BRODfsIQNRr09VKPd2j57QCRXhbSTnd8r7IS6mS1doBodQ7Cc9yVQuU4jUaodFo5P8nLt4hyk3cJRzr9xAqB3eBSi2Uds5CV7q60PqGCEC4tBwu7Ku1kdXfAeHWdrSszO7a7hP5mBQaG6H1rSC8+s6SFd+1XmWFQmMjFDa2QutVVni886WwrShdf61XWWFXqWm+C4VC2PhJrhiWc7AJqPJaRfs3vVQqlQgLC7NS+NdqtVbrhL0/W3a2kM+v3SfCvnrb/BoKjXyuLs3fl+6TcvWs1Ok9uk60uj/ehHbt2pV4zDt27BA3b94UCoVC2Nvbizt37gg/Pz/ZNWDXrl3ydo4ePSrCwsLeap+NGzcWhw4dkt83b95cAGLJkiXyMqPRKPbu3Svs7OxEx44dhYuLiwgJCRHDhg0Ta9euFTExMVbrnjt3TkyZMkXUrl1b2NhI93ODBg1EbGyseH/lBRH0hbWKv9+HS6V7RakSdpUihNrVTwDCsV53eR2bUmFCF1Rd6OydBCCWLVv22vPasGGDAIS9vb18DfV6vQDEggULxOjRo4u9zqdOnbL6LdRqtRBCiOTkZNGiRQvpftbqhUOtTsJ78Hz5ew41OojACTuttuVYr7twqNlRAEIXVP2N96V9jfb/0n1tedlVaWH13iagsrBz9ZLfBwYGigaNGr92Gw61OkvnamNXaLn0vHj1+U7YVWlZ7Pf0ZWsL/9Frha50DaldUqqFk6u7aNSspfDrOVloPEuXuE+F2voZVNq7CZeWw+Q2UaVSyfeT5VWqVCkhhBAnT560eqbt7e3FDz/8IIQQYsCAAQIQU6dOFUIIcfjwYflecHFxEePGjZPddP5T+K+HOjds2EC9evVwcHCQtQPv3r0rK04ATJs2jRUrVsikCMvU+XVYsWIFmzdvRqlSI0wGnBr2xr3jWLReZQBBXtxDABzrdsWuSnNUdi4o9Y6o8qnxOY+t8y4Pn720el843GDOlQrZS4QQ2FWKkAkl5uxU4iKvFWhwGgwFQr8GA4t3niA1+gppZzZizs1E4+qPSu+IIf4xpswUANIv7STj6l7Ujh7ysSTulwpgzYZckvb+IheXazxKI/KyZX3NxN0/kRf3ENvyDbAt3wAUCnJj7kn1PwolNn4VUeod8sMxgryXUtjOYiCa+/SVnJRCReCEnZSdsB2NTppxvsraHD9+PKdOneLMmTP89ddfrFy5Eo9CbhSWWa8FaRe3owsMI3DCTgIn7MShVidynt4sEOk2GeUcpIVQ82p46O/CIsf02WefyeatQggePHhAhw4duHPnDkII3NzcCAkJoWHDhjIrrfDsoFGjRiQkJBTr/PEqCkuXRUREyIbJQ4cORaFQEBERgZ2dHR07diQzM5Nr164xd+5c7ty5w8KFC+nevTurVq2iYsWK2NnZUaVKFa5du8bUqVM5f/68/MzExMQw4tPPOXY/vkh4M+3CVjAZcKjWFveOY/HsMQWQ7jGL/533u9/h1ftrhN3r9WgtsORULa4KgCw0fe7cOX777bdiv2fRObVQ6Y1GI61btyYwMFAOnYm8bNIvbkfkFogVmAvltC1Q2bnIz5zSzskq5OjUqC9Bn2/DoVaB/mRhNRSVoyde/Waj8QiSlym01jWnCo0Ofdna6MsW1MZpPMugC6wqv3dr9wnefWfKkp3h4eE8evSIK5ekyE358uUxmUxF2I0KlRSME8XU+4FE+oICM1yLka19WEtUegc8e0ylx6xNXHscT0piPBUHfYc6sDpubT+WVtc7yufm1XcmAWM2W9UxurYaQcDIFWTdPYXIL9WwlNeA5PAhhJDlz2rVqsW1a9dITk7m6NGjGAwGJkyYgNFolBWpzp8/L9cDWu4FZ2dn5syZw1dfFc9Y/5/CfzXUGRkZSY0aNaweDgsKC/1Wr14dkC4SUOz6r6JixYqo1WrUWh152RmyGK3l5rXQ7uM2TZcT4oVhKlRfAwU3IkhhRHN+ByStbMCU9YqrciFoPEtjTE+kcIujdvTEaEV/hpYtW7J69WrGbo9i7779+ceZjSH+EUp7d/w/WsGL1RMwpb7AmPQMhVaP1rssubH5ii0mIxk3DuLUoBcIMyiVYDZhW74+TvW6ycaZwmRCodaiL1cXrUcQaldfcmPuk3ZuMwgz6Zetw6KWh09p54wpIxFduXrkFGJ8giB53y9UcFbwIFe6rmXKlOHkyZMYjUa0Wi0LFy5k5cqVqFQqWrRowfLlyxk2bBhffy0l4evWrcuDBw/k3/3RlZMEt8zFoJQe7MKu00pbJ8xZqbxcOxGNRyBZd06i0OpxqCmp8RsSn5J6ZhMiXdpWQkICgwYNwt3d/bW2KhbJrnnz5vHgwQPc3d25c+cOp0+fxmw2U6tWLWxsbOSH98WLF9y7dw+FQkGDBg3k7ahUKnr27Mn69euZMmVKifsDqeO7d+8e58+fx9nZGZ1OR05ODnZ2dpQtW5bU1FRyc3OpUaMGjx49Ii0tjaFDh1K6dGkiIiL46quvmDlzJhUqVKBHjx4cPnyYDz74AK1Wy8CBA+XwUnh4OPUGf8Wtg0XFri0DG62PJDSscfGVwte5mRiTY/MHi38PcXHSva3VasnLy0Oj0WAwGAgLC+PmzZvyQG/Lli1WRtAxMTFUqVKFW7cK5LZu3LhB27Zt5ZCte2B57Pr8IItcg+SUIl7p0bWepeWBUt7ze+gCw8jJlzNLPbOBzNtH5cEggF1oBKkn1yIMOZiyUsi8fhCVrRMGpQr3DmNIKERuARCGHLKjL1gtM8Q9sHKMEMJM8u6fyEiSrocl9Ovm5sazZ8+IiooiJCTESo8UCpVkWFkWSeeXenodhqTngELulDCbUNjYodDa8nhWJxRqG2KEAc253uzdt5+EhATsqjQn7+UDlLaOmLPS5LREyonV5D65KW8fIGn/b6Rf2YUh4Wn+EgWzfpjPsj9+Y/PmzUVY9B07dsRkMlG2bFnu3bsnS7a5ublRunRp7O3t2b17N82bN5c/69mzJ99++y3lypXj559/ZuLEiVbh0P9J/FdnfLt27SIjI4MqVaqQkpIix4IBq5u4JG+910HO48jykUVP1ZyTIXd6Xn2+o9TnO9CVqWk5Aqt1XZwKZnRKpdJqdKj1D+VVarJzqw/lnZuz0oowtF7t9EBS06hRowb2aiG7QFg6anNGAi9WfobGtcDBwTLyLWyVZEyOQanV49q6kHrI0WU8+3WQrN3n1uYjVPYuJGydScyi4Tyb369I3gDAJqAyXX85hq2LNAtWWAR+g6pZrafW2pBz+wjP7l6Vr/u2bdvYt28fnp6eBAUFkZeXR2ZmJvHx8bx48YLY2FiGDRsmsxEvXrwo6wDK55KeKP8fOGEnAZ+sx7FBL8xZqShsbDFlppB1/yw2fhXw6jUdla0TAKaMZDJvHiIr3xIqMzNTJtS8DlWrVuXgwYM0adKE48ePs27dOtLT0+VcXVBQEFu3bqVBgwacOXOG+/fvo9frWbVqFfXr17falsWZ/dXGGKRZ/blz55g1axYbNmzg559/5r333iMgIEDO6f3yyy8cPHiQq1evolQqadCgAe7u7nh7eyOEYOHChQgh5EL6Bg0a4OzsLI+uLSLshXH3RRrx57aRdPAPkg7+QcpJiUpuiSIoNEWFCEyFaPoA5jewYcxmM1OnTmXt2rX4+fnJM3l/f3+8vLy4fv06ly9flte35C0tGDVqFDdv3pQbQBsbG+Lj47l+/TqfffYZILFMta+kaS0C0xZoPEpbeeiZMlNkRRdQgMmAMel5AanE1on4zd8gTPkzLGMeGdcPkPv8LhpXP1JOrLbqhOyrtcWmVBhKnYPVTNC903jsQhrJ7/NeRJF2/aDcdjk5OXHs2DFsbGzk61W4YN/SThX3PBY+F5uAytiUqmy13LZCA/Slq+FQqxPCkI3JZGLt2rUkxMfh2qAHtuXqSdJqRqNEhMl/GVNeoC7UrsjXNP6x3K6p7JyZOutHdu3aRWBgYJH8bkREBDExMaxevZoTJ6TyqhYtWtCtWzfUajX9+vUjPDxcJn01btyYRYsWERwcjLOzM5mZmXLe8D+B/+qMz8vLC5BmfqNHj+bq1av/9n2oXtNZKjQ6uW4m5eQalDp7qRaoGDjZFoRJGlfw5kxcwXbN6UlS8emTfIaSUoUhNhJUKjAZMedmoC9bh+zo8/J3GjZsyKlTBQK5bdu2Ze/evTx79ow/Jw7E/d2ZxbpA2PhXkoVuFWotSns3TCmxONbthlOjdxG5WaSe2Uhe/BOUWr1UVO/khSn1JcmHl+AzeJ6smGHKTiPn8Q0Sts4g7ewmydjz7gnUzt7ogqphzk5n9xddCPT15F5yPBXLlyXOyQHVyxtYxrR6vZ7r16/LRBVHR0fS09OZOnUqzZo1sxrMpKens2fPHubMmUNAQABqtVpuED777DNmzpzJjRs35MY7onoFDt99KTPalDo7bMvWIu30ekReDgFjt1jNxC3QBYYR9MVOWod6sbBfrRJ//+LQpEkTDh8+XOLnbdq0oU2bNoDkNejm5kaXLl2KrFe3bl2ys7O5fv06oaGhXLx4UVZFOX36NKVLlyY8PJz+/fvz22+/yey2wiFiy6jabDZbKcWAVMqTkJAgRz9e7UCKa0TScoxk3T0ll6WoHD1xbtQHlZ0zxqRnViUwFnKFJbz9NkhLS2PAgAEkJCRw6dIlSU6sY0du3rzJ48ePCQoK4v3332fRokW4urqSmprKrl27rLYREBDAw4cPmTJlClu2bOHixYsYjUaGDBnC2LFjmTFjBuev36HHn/dQO3sROGEnhpQXJB/4nZwnN1Bo9ehLV8elhVQWoy9TU5oNGrIxJFpmL1LnbVe5Oe4dPsWYGsfzP4aRF/cAu4pNyI2NxJj0HJuASpiyUiQnCaNBvg9FXhY2vhVwa/ORfNwW7z+Nm798XCDNzgD69e3LypUrAckRplSpUoSEhLB7926rwZGzsxPZKjuM6Ymonb1RqLU4N+lP/JZvUTl64j9iKcb0BLLuSYIYuU8K0g660jUQZjMuZauhf3yauLg4TCYTHkEV0Dfog0KlxrZcybJ3lnIrrz7fyYOGvLhHJOyciyHuIRcPS+fUrl07WfR8+vTpsi7pRx99xMiRI/Hy8iIzM5Nhw4ZRpUoVypUrhxBCFnq4d+8eo0ePlp1p7OzsSElJ+Y8SXf6rHV/Pnj05dOgQGzZs4ODBg8ydO5fevXv/W/ehUSspSbZYoVLj3v5Tkg4tIu9FJLYhjbGt0JCsQmavFqX3pIcFJq5ZZ9ejDylQejemvcSYXmBjgkJB1v0zqB09MCbHIvKypULS/M+VKhU3btzAw8NDDu35+vri5uZGQkIC6c+jUBz9k8x7Z4q4QKidvPDoMYWELd9JIZnUl2g8gjAkPuX5LwNwaf4+2Q8uWdXcmWRGqdTJxC4bhcrJE7WjB6Z0ScVTaWOHW7tRqJ29yLp3iowbhyQVGr29bItz/dQhq4fUycmJU6dOERwczNixY4mNjZVDNjt37uTcuXO0bNmSqKgoDh06xLVr16hduzadO3dmwoQJLFu2TG745syZw5w5Beoz77zzDp+0CWPHqpGk3TmJ1rscKBRkR0mhJV1g1WI7PQt0ahUjIoqWOVhqP19FcHDwWxXWW+1Dp6Ny5cpcunTJqmA9Ly+PCxcuEBgYSJcuXUhMTKRs2bJEREQwfPhwVq9ejZublCvLysriiy++wGQyFWGbWnKOWq2W58+fs2/fPnbs2MGff/7JixcvcHd3x87OjszMTK5fvy6ruhTOvRSGo06Nd9+ZRZZrPUuT+/QmubH3sa/SHEPSc7keUypjeTMiIyPp3LkzTZo0YcOGDbIYebdu3bh58yb9+/dn2bJlXLp0iUWLFlmJOBeGxfNv7NixANy6dYuVK1eycOFCpkyZQunSpYmLi6P6x79xP1uD2WQi694pDPlOCWoHD3Sla6B+xRvT0skVBznH+QpTOu9FFP4f/ykzpQFiln6cX8pgjeJ0QS0F7GBt7TNo0CA6derEmjVr2L9/vxz2BWnAdPX+Y148kJ53l1cK/g1Jz4ld/kkRR3eQyqRUGXE0sHvBGXt7OdyclZZC2vqv0HqWxqlhH1T6t1NLEWaT5KeYkYR7x7G0bd+B1N0/sGDBAuzt7Zk9ezZLly6V77Xw8HBGjhzJ77//zrhx42T7ODc3N3755Rd69+6Nl5cX9+7ds0pXWf7/n/bTLIz/asenUqlYvHixbA0EUojIglfjyJ988omVinhERIRVQ1ycH19qSgof/HmRA3deIgRFHnzJ5biB1TI6jZP/zcsnTty/V0BU2L5xDX+e+Zb+UnoK19YfkXZuM6asVGzL1ce19Yco88NGmXdPknZmI4ak56j0DjRp1pJNS3/BxcVF9km7efMmK1euxMfHh0mTJlG+3RC+XHGAvPjHxbpAKNQa/D5cQsqJVWRHX8KQ9Bxzbia6srWw8auAfVhz4v+aSW7sfUyZySg1Omz8KuLacjggyY1lR1+QRosqNTalquDa7D2UWj0uEYNwiRgEgI1ayZZBoXwy/D2cnJwwGAxkZ2fLpI+0tDQ5ZLNp0yarxnbfvn0AXLhwgXfeeYepU6fSsGFDK/2/mjVryh2fnZ0darWarKwsateuzR9//IG7uzP92jVh4f2zZN07BWYTKntX7EI74dSoZIkkG5UCv7hzGF56YPatbuWF9+zZMytBXgssD+3fRb169WSHCUvB+NmzZylfvjwVK1bk7t27PHr0qERHBUtJwpMnT+RSHAs8PDzo2bMnGzZsoG7dulStWpUjR44QEBDA8OHDmTp1Kh999BGzZ8+mZcuWdOzYkYyMDM6ePUt4eDjLly+32l6ItyM26hdW+rQAjrW7kH51DxlX9iByM8mNke55hxrt5UY/9cxGDInPZOHk8ePHs3TpUsaPH49KpWLQoEFMnz5dFiB4FVeuXKF8+fIATJo0id69e1OpUiWrEqRZs2Yxf/58nj9/TsuWLQkNDWXMmDHs3buXGjVqUL16df766y/MZjOuT09idmpCysm1pJ3dhNrVH9sKjch5cp2kvb+gUGmwr/Jmj8fsB5dkayJD0jPZad3iKfhPc5wADqUq4p5SjehbV2VrH71ez6hRo1i5ciWurq74+flZtXMPHz7k7OF9lA+piMEksK/UjBxLJAnIjr5YrI4ngE6toE8lO777aKHVcWQmvYSkl+Q+uYFjrc7wlh2fOSdDzldq/UJwc3aidLVqbN++XSZzFaeY1bZtW3nAd/ToUbp3787EiRPp3bs31apV4/jx45w/f56BAwcWqQf8T+G/Xsf3n8BHEcGciEz4R8otIV/tYf0H9Qjzd+b8+fOsWSO5Flxc95O8jjDk4jdskfzemJZA0r7fyHlyA1NmChpnL0oNmEnmrjkc3rqG32qFsmbNGln+Kj4+ni+++IL9+/fz40/zMC3diGOjd/Hq/Q2mrFSeze+L2ZCDa6sPMedk8uz7rijtnAj4eBXGtHie/zYYYczDveNYUk+uIfXUWmwrNEDt6IkpLQGzKYPc2Egy755AobEBhQJ9cB2yH17BlJ5A7pMbxC4fjX2N9uQ8uIQxPRGlVo9XYDDqfmvYt28fP/74I7NmzSI0NJTAwEAOHDhAamoqx48fZ+/evej1etknrkWLFty6dYvIyEju3bvHzJkz+emnn/D392fw4MGMHz9ezttaMH78eP7880/KlSvH7NmzcXeX8oo/ff4BtcJb8c3uO2TnGgsk24qBRWWkbyU9X/WeSv2l38piywMGDKBHjx5FBkv/BLm5uZw7d45jx45x6NAh7t27R9WqVYmIiGD06NFs3LgRZ2dnhBCEhIQQFRVFnTp1Styehdn5ascHkgFymTJl2LRpE7t37yYvL4/OnTvL4dZvvvkGNzc3li9fzqpVq3B0dKR69epWA0gLutf058diyC1qZy88e0wl5ehyMu+eRKmzx7HOOzgX8q97NYoQHx9PfHy8bJ7cv39/qlevjtlsRqlUEh0dzbp162T2pslkYt26ddSoUaPEXP0HH3zA7t27ef78Oe+++y7t27fH09MTpVJJjRo12Lx5M/b29qSmpnJq7xaGzXmHyfOlgZONXwhKG1u0nqXJTosn/cruYju+tEs7MCbHApLDAcIs1/LlPLoqi1Zb8nav5jjfBrLazaj+RO01Me3WVTw8PLh69Srr169n6NCh/P7771bRLUs949SpUwkMDOT0yRPsvhHDmgcacgqbuOeLNiiUKmxDI8iLeyDPQN9rVIaJA9rx8OR21q5dy6RJk8jLy2P27Nk4VArHteM4/g5Utk6oXf0wJj0nccu3XHham+vH9wDIgg3FoXr16gQFBVGqVCmePpXCyxZi4qeffsrChQv5/fffSU1NlQviP/roo/8YsQX+j0uW/R38Ha1OC/QaJRPbVZSlmizamq+idO1maFqPRQFkZWcRu3QUxuQYNK5+6EtVRp8RwxcTJvDj11/y+PFjVCoV3bt3x2QysX79eho2bMjZs2epVq0az/L0JNw9D0Lg1XcmOv9QYhaPwJDwBJ8hP2NMiyd+k6RQ4TvsD/JiI0nYPgfbCg3weOdLkk+sIu1Ugf6j7OycH2ZVu/i+Vu5IqXeUZsB52ThlPGLViuVyZ9GkSRPOnDmDra0t6enpaDQafHx8KF++PJcuXeLw4cNyfi4kJAStVivLcZUqVYr09HSSk5OpW7cu9erVY9CgQTJjV6PR4O3tTVBQELdv36Zr165Mnz5dDn/MXb6JJWeeYvIMQUGBoDiAWmHGbBa0quzLiIhgwvwlkse1a1K+VqlUUrlyZfn930VOTg7nzp2TZ3QXLlygYsWKhIeHExISwsSJE4mNjS22QZ8yZQoZGRlWXnivYtiwYYSFhfHRRx+VuI4FXl5eXLlyBV/fomSEt0Hh6MffhUKBnDfNzMxk6NChREZGMm7cOC5evMj27duJiYlBp9NhMBjo1q0bQ4YMoUGDBkUc6EtCREQEx44dY9myZVSqVKnEAUPNmjXZs2ePLJ78KpR6RwJGr5HDjXZVmuPZ4VNiVk2wynH6j1jKi9XSMrf2n8qd5ZMfeyFyM/EZPN9qxmcJdXp1/BTnqi2t7kOdWokAmlbwYEREME6mVPr168fJkyfx9vZm3rx5dOnSRQ4DCyG4d+8ejRo1krUw//rrLzlnbGlvXPzKkPz8AWonT3yHLSJp769k3j2BysYWjxbvEfuXpGhz5coV2Wg7NDSUK1euIIQgrGo17t+7i3vn8dhVbFLitS8ux2dIfEby0eXkPb+L2pSNn58f7777LlOnTi1RCGLUqFHs2rWLmJgYtFotNWrU4IcffpCf9UOHDvH5559z48YNXFxc6NevHzNmzJBFIP4T+H9ixgcFFjX960ujapeWw0i/sA1Tdjq2FRrg2nI4So0Utsu6f5r0MxshNYaJK9w406ED3377LYMGDeLdd9/lo48+YseOHTJxo4yjgvWfN2Pjpad8P+4DuWOxMWdT083ExoNHcHR05PupnwOSgsGuXbsICwtj0aJFsmJ5fHIaqRkJUkclzMRv/hqPrpOwCagssdY2Tc8PPSgAQdqF7bKImE1Avmp/foNmIe041utO2pmNMjtLmIxF8hGWhxwk00vbCg2oWrkS+yd15cWLF2zYsIE5c+Zw+fJlzGaznMezODIfOnSIMmXKsGDBAvR6Pa6urty9e5dKlSoV7ONJgXr+uXPnOHfuHN27d0etVmM0GmnWrBlnz57lxIkTdOvWDScnJypXrszo0aMZM2YMe1YtZPJ779GyQzM2XX7G3dh00nIMOOo0xEddxT7uJgv7FZQqjBs3jmHDhpGZmYlarWbLlgIj3jchOztblq86evQoFy9elF3Ix40bR8OGDeXEvBCCL7/8kmfPnsnqK4XRq1cvWrVqxZw5c0ps/AvX8r0J5cuX5/79+/+44/tXoh+WvKlF1T8sLIy//vqLcePGcerUKRISEihVqhR2dnakpqayceNGbt++Tbt27Wjbti01a9Z86w4QkDsDkBi3+/fvx9PTE4PBUCTH2f27tVzPckKBJLFmYXCq873w/Jx01CvnwbF/U45zUruKaELLW92HIT4OvFPNlwsnDvPl8KmcOXOGcuWkEpHWrVvTs6ckA5ieno6DgwNJSUkMGDCAMmXKkJiYiI2NDe+88w5HjhyxIjmFBQew+e7tgvs+9Bt5f91r+ONmX3BO1apVk/djwb27d95qwOM/YmmRZRo3fzy7TUKpgOmdKr2VXuv8+fOZP39+iZ83b96cixcvkpiYSJUqVZg7dy6LFy8mJSXljdv+d+H/mY4PpM7PErxJO70eu+DaZESeJ/P6AZQ2dvi2/oCMqAvEb/kOjVZLn969uXTpEr/99hvR0dHs3buXlStXsnjxYipVqkTXrl2JiYnhxIkTuNnbEGx4RPSFI/L+VMLE3du3SE9Px8XFRSayBAQEEBYWxvbt2/n4Y6mgNCcnh9hnjxH5kkO5z+8gDLkYU16gK1WFjCu7MaUloLR1RGljiykjibznBUXTulJSxydPOvI7Ohu/ilbXwJQWhzkno1jTTbvKLciOPk/c+skcWA+6b2xQq9WUKVOGmJgYDh48SMOGDSldujQxMTFcu3YNtVqNq6sr0dHRco1SYGAgkydPfq1jRnp6OnZ2dhgMBtkUWL9vL1tnjGTbjl3M23ud/YPeZ/bXkylTpgxZWVls374dW1sbhjUpa7WtadO2YXa2s1rWrVs3hg8fjqOjI61bt6ZXr17s2rVLZhIXRlZWFmfOnJE7usuXL1OlShUiIiKYMGGCVaH6q1AoFLIxbXEdX2hoKK6urpw6dapEx4bCvmZvQvny5YmMjHyjrVNJqBrgzMR2If8w+hFCYuQVWvTqRYsWLYiLiyMsLAwbGxuZSFG4A9+3bx8qlYo9e/YwcOBAEhISaN26NW3btqV169Yywac4zJgxg5ycHFkgOT09ncmTJ5OYmMiJEyeK5DhPzPuElm3acfdpPE+unEPvHcyAKb8R+cKNXSegfll36pVx4+yDxH9LjnPdqhUEB5/ivffeo1GjRrx8+ZKlS5dSZ8DveHh48OGHH7JhwwZmz55dRLC8S5cuZGZmcu/ePby8vOTnRK/XyzVur8LNvuh9Xxws8m+vDjA+igjm6PWHvDi6qsh3XjW1LXa7Ar7dfZcwf2fC/J3feBxvg+HDh1vVa/8n8V9XbvlPIiGj4KZqOOhLGg2ZRPV3xwNgvHuUT1uWp2KSpLk38csvWbFiBUePHkWtVrNv3z7u378vM7CqVKlC3759WbZsmfzQF2ZngWRQ+t5771GqVCnOnTsn39QVKlTAw8ODoKAg+Ts6nQ5hFih19ijzVWD05etjVykCXaF6HXNOJnaVW2BfrS3G7HTy4h6iUNuQcW0/SQf/IDffT8wiUqssVJtlQUl5C7vKEQSMXoPfh0sJbNCe3Nxc6tatS0JCAgcPHqRp06ZotVqrkIRer7dq8NPT0+UH2cJKBDhy5IiVEoq9vT17z97gvWVnaTjrMD8evM/paGmEbxIw79B9+qyLxqnDWOq164WDgwMNGzaUlU0KIyUlRc4hWKDT6fjjjz84evQo69evp0OHDjRs2JCoqCgyMzM5ePAgkyZNonHjxnh6ejJ58mSMRiOTJk3ixYsXnDlzhhkzZtCmTZs3eoZZOr6S0Lt3b9avX1/i5/9kxvevoF+9ICa2q4heoypSf/oqFArQa1SMaV6Wgwun0rZtWzIzM8nOzmbw4ME8f/6cly9fWindWF6tWrWiefPmfP/999y+fZsLFy7QsGFD1q9fT5kyZahfvz7Tp0/nwoUL5OTksGLFCi5ckFi74eHhVK9enWbNmjF+/HiUSiXLly/n1KlT1K9f3yrHOWvWLFxdXdm0fi1Pbp6njK8nNf3t+bFXNWoFFpCKutf0L/YcLTlOrVcZMu+exJyXVWyOM/PmIVlL89SpU6xYsYKdO3fSu3dvQkJCiI6OZtOmTVy4cIEhQ4aUaBpsYQJnZGQQGxtLhQoVcHFxkWc8TZs2tQqbm81mJkyYgIuLC35+fqxevVr+LCIiAoVCweeff07dunXRarU8efKEzMxMxo0bR9myZbG3t2dgxwhq510j/eL2Iq+0c5t5Mrc7zxe+T3Z+jhPAlJ1G4t5fePbbEJ780IOHSz/jq983vvZ+AWkgOWHCBIKDg7Gzs6NGjRqyH6cFK1asYMuWLUycOPGN2/sfwf+4KNr/Alx9kizeX3lBlJ+0W9aYs2h1lv7wD3nZ+cgXomJFSZdy/fr18ve9vb0FIPbv3y8yMjJEz549Za05hUIhWrZsKTIyMoTRaBS9evUqooFXsWJFMW7cuBI18lxcXCSNP1dvK708pa2T8OrznQicsFMoHdysdfW0+kIaewX6eRbtToVGJwDh0X1ykf0FfLLOSqvRogeosLETthUaCsca7YR3UDlJ+0+vFxcvXhS2traiY8eOYvjw4UKn08nbOnjwoJgxY4b8/u7du/J1++233+TlrVu3Fv379xcVK1YU4eHh4s8zD4Vbk75C5eAmbEPDhV2VFvJx2Ie1ko8t6IudotTYzeL7refExo0bRZkyZUS7du3ErVu35P0MGjRILF26tMTfPz09Xezbt0+0bdtWaDQaodPpRMOGDcXEiRPFgQMHREZGxr90fx0+fFg0aNCgxM+joqKEp6dniXqE2dnZwsbG5q30Cjdv3iw6der0j4+1MK49TRYNxi8TZSZsFxUm7ba6JypM2i3KT9otOs7eLtr2Gy40Go2wt7cXs2fPFsnJyf/yvnNycsTBgwfFyJEjhZeXl1AqlcLb21t88cUX4uXLl6Jv376ibdu2Ijc3929ve+HCheL9998v9rPitErf9lVq/HbxwZ8XREpKipg/f74IDQ0VISEhYt68eW99Ta5cuSJ8fHzEH3/8YbV82rRpwsHBQQCiW7duYvTo0WLWrFlyG1O7dm3RsqWkz2lnZydSU1OFEEKEh4fL63To0EH069dPxMTEiB49eghAlCtXTgwePFjY2toKQHh2GmelQQwIXWBVofWtkN9+eEjn+vl2YeMfKgBh419J2IaGC4VWLxRqrThz6fprz7F3794CEDVq1BD9+/cX7u7uQqFQiCNHjgghhHj06JFwdHQU48aNk/WWnZyc3ur6/bvw/7sZX0JGLguPRfPJ+isMWXGBTr+epNvC0xy4/dIqxGGR4snIdyRW6h0ZsPIKGmcpFGbRWUxMTCQhQap1CwwMRK1Ws379etLS0rhz5w4tWrTgwIEDbNmyBZPJJCdwCyMqKsoq39WqVSuCg4M5e/YsWVlZHD9+XCLNCDMoVWg8S2NXtTXmrFS5AFZfWlKUUejsce8ywaqOxzl8gKxpaUnOW0KZeS+s1fFVjh7FhjlBiufnPL1J2uU9vHgkzUDKli3L7du3ady4MZcuXWLJkiXyzLVv3740b96ctm3bytuYMmWK7Nw8fPhwmb154MABdu/ejbu7OxUjOvPt7juo/augcQ8k59FVMm8fQ2XriFODXla1S0JIeoSLLyWS41+L27dv06JFC7km7uXLl0VmfBkZGezbt48vvviCevXq4eLiQrt27dizZw+1a9fG3t6er776im+++YYWLVrISvH/FLVq1eLq1atF9EYtKFu2LKVKlZI9F1+FTqfD29v7rVzi/x0zPgvC/J3p6ZtK84wjfNqyPO9U86NpBQ/qeSnwS75KwpLhxG3+ltsn9sgSbePGjSsyu/4nSE5O5tChQ6xdu5amTZuybds2pkyZwo0bN/D392f79u3UrFlT9nf7OyiuJtKCjyKC0amL/+xNEKY8/vpmOAEBAZw8eZJff/2V27dvo1QqmTp1qlxuZXm9KiJgse2ZN28e77//vtVnkydPlkteRo4cyU8//SQTd1xcXDh+/Di7du1CpVKRmZlZ5B7o16+fXOOpUqnYuFGamR04cIClS5fy3XffAZD2ihyhxr0Unr2/wT2/hMuUFo8pK5W8F1HkPrstyyKqbJ3QuPgijHlMnVu0DtaC+Ph41q1bJ6sNubq6UqlSJVltyGw2M2DAAEqXLi2bVP838H8ux2cJATx8+NAqlHbtaQq/Ho2SfLqgSBz/VSTu+4WsqHNkR0l0WrvKTck2mMgIjIAzR/nuu+948OABly5dwmg00rJlS8qXL8/y5cuZNWsWtWrVwt7eXmYtOjs7c/r0aWbPni17qVkkuObOnUtKSopM5Dh06BADBw5kxowZHDt2jB9//JGlS5eyboMjtkFVUdi5ypJFSpv8Duz5HXRlaqJ29CDzxkEAtF5l8RlsXZPm3bQ/1ToN5u6NK7xcNYG0c5uxq9yMnEdXMWUk4VSvh7xu8uElmLLSEPm6gEobO5Q6e8xZqajVaurXr094eDhbt27l/PnzeHl5ER4eLruGb9++nSFDhsj5qU6dOsmyWfXq1UOr1cqNlre3Ny1btqTLwBF8cSSJbIMJXanKchjXYouTem4LGdf2v9EW5+eff+bhw4dUqlQJe3t7qlevLhNSbt68Sc2aNYmIiKB169acO3cONzc33n33XVq0aIGbmxutW7eWSRiOjo40btyYuXPnWt1TbwsHBweCg4PlAv3iYAl3tmjRotjPLeHON9UylS1blocPH2I0GouUhPwT+Pn5cfToUUIVMVw/vo7dmzYRGBhI7969+fi3ebIax4QJE/6WZGBJuHfvHnPnzmXTpk28++67nD9/XpZpE0IQGRnJy5cvmTRpEseOHWPgwIEkJibKucFWrVq9NjcIr+/4/mmOE1MepgsbyX4u6VA2adKESjXr8fvxB8z8bTnP71wq8pUuXbrIv+eePXsYMGAAq1atonXr1m+/XyTdYYu0n52dHWlpaUX0ihs2bCj/XzhnGBgYCEgsawBDIX1TAK1XGRQKhdVgWOTlYMwnB8myiIUQHWU9mC6MN6kNPX36lOPHjxMWFkbXrl1lAlNmZiYdOnRg6dKlJTJ1/534P9fxjR49GkBm1Vnoz96dPkNXqdlb07SdG/cj7dxmhMmAXeXmODfpjzHlJUkX96BQSYK6q1atwsvLi2HDhjFjxgzWrl3LrFmzuHfvHnfv3kWhUBAQEMCkSZPo0KEDUVFR1KhRg2vXrpGUlIRSqaRz5860bduW8uXLI4TAz8+PrKwsVq1ahUqlQqlUMmzYMCZOnIibqzOxsZGYslJR5iu/uzSTHKZLKjp/FTm5udzdORvbVp/g3nkcqSfXknn7OCp7F5zDB2LMTJGLdDOuH7CaOeY8LNBQ7N69O2vXrpXfm0wmTpw4ITMxDQYDTk5O7Nq1i7S0NNq3b8+SJUtwd3dn69atdOvWzWqkHhMTw4oVK0jwrU8O1rkWY2ocLzdMAWHGrmJjcmMjSTu3BRRKuZg+N+Y+SkdPdHkZ5GSkEh0djUajwc/Pj+vXr/PNN9/Qvn17vvvuO+rXr49eL5ESLKPKdu3ayUyz5cuXk5mZSVZWFmFhYaSnp7NlyxYSEhJkI9K/C0uer6SOr2fPnlSrVo1ff/1VprMXhoW0Unj2XBz0ej3e3t48fvyYsmXfTHYoCUIILl26xJYtW9i9ezfR0dH07t2b06dPU7ZsWRYvXswHH3zAsmXLaN++/T/ejwVnz55l9uzZnDx5khEjRnDv3j0rdw6QXFgOHjzIkSNHcHV1pVOnTsydO5dHjx6xZ88e1q5dy/DhwwkNDZWZojVq1ChC5HhdxwdSjvP27TusvpOLUm3D65oMYTajxETPchq+m7EaIQT9R09k+uFY5jzei1arRd15GoGdpfUtJQ0RFTxwKSt1euvWrWP06NFs3769iKZrYViO+dUZbuEBTkmDD4uQBBTk1rOzs3ny5AmlSpWS/SMLawxLG5T2+epWLeup7F3xG74EhVrK65sNudQK0FMSXlUbstTjWpi4FtPt69evW5nQGo1Gdu3aVUSv938K/+dCnT/99BM//fSTHBZ4mSZpChqM5r9Vm5R04HeMybG4dxyLe4dPUai1xG2aRnbUOWxKVca5TBgmk4lSpUqxcOFCXFxcuH79Os7OzvLoacCAATx+/Jivv/4ahUJBuXLlOHDgAHFxcezZswcvLy8qV65Mp06dEELg6+vLs2fPSEpKYt++fRiNRho3bkyfPn1ITEzk2dOnuJcqR9C4rQR8sg7PHlNQ54deXVsOw2/4YkqN3UKpTzfg/e4MtN6vNnyC+kGOxF4+zPR3quJWJQLf9xcQOH4r/iOW4VS/B5k3DspJ7cKdnt/wJegDq8jv161bh0Kh4Pbt20yYMIEKFSrQokULlEqlHOoaM2YM77//Pl5eXuzevRsvLy88PT05e/YsDx8+pHnz5jLxZeDAgcSn5xCpKvUv2eKYbaXffd++fdjb2/Pzzz8TGBjI6tWrefHiBWPHjuXMGcnRe+rUqbLdyZ9//olCoWD58uUy+7Rt27aYzWZCQ0OB4lUo3hZvIrgEBARQsWJFDhw4UOzn/ymCy61bt/jqq68oX748vXv3xt3dXb63v/zySwICAhgxYgRz587lxIkT/1KnZzab2blzJ02aNKFPnz40b96cR48eMXXq1CKd3ty5c1m3bh379+8vonITFBTEhx9+yPbt24mLi+Prr78mJSWF/v374+Pjw4ABA1i3bp0sg/amji86OpolXwxiWhMXWlfywkatRKe2bgrNhlwUZhNNyjix7eMIZr3fAZVKxbqLz7jq1hTb8vVBpSHPZH0z5xjN5BrN7L/9kt6LzjJy3nrGjBnDgQMHXtvpAfKzMnnyZD755BO5+PvvwtPTk+7duwOS48uQIUP48ssvAcnA+m2g9Q7Gxi8EU0YSsSs+JXHvL8Rt/obnvwwg8e6FEr9nURvKy8ujbt26DB8+nB49ehAQEMCSJUtkdS3LyxItcnJyQgjxjyIu/wT/Yx3fkydP6N27N35+fjg7O9OqVStu3rzJ8ePHUalU+Pr6kpKSQlJSEl5eXqjVak6flhiVd+7c4Z133sHX1xe9Xk+1atVkOSyFQnL6fvToEbXqN+LuFYkqnLj7Jx7P7CCpqAM5T2/xYvUEnv7Yi2e/DCBh10+Ysgusg9ROnjjU6oTa2Zu0i9uJ+WMYhoQngAJTVhrKsPa4evlx9uxZOTczY8YMzpw5Q6tWrazONS0tjc6dO+Pg4IBCoeCXX35BCMGLFy/4+uuvZXmfmJgYFAoFgwYNkvUvP/roI06fPk2FChUASIq8XGBJ8jeh16j5opOkjNGvXhCT2ldErTBbMff8RyyV84GWV9AXO7H38MHL00NmopUtW5Zq1arRrl07Zs2aRWxsLFqtVlaaAalmyGQy8fjxY4KDg2natCk5OTnMmjWLkJAQdDqdPPN68OABmy49K/a4S7LFsUhGFYZlZDp+/HgmT55MkyZNSEtLo3nz5pw+fZovvviC9957j44dO+Lr60vdupIob8WKFRk9ejShoaH0798fLy8vDh8+TLly5Th4UFLPHz9+/D+67vDmjg+kcKclTPwqLPfD28AyO3xbREdH891331GlShXatGlDdnY2a9euJTIyku+//56kpCRMJhMvX76kRYsWPHv2jLNnz8r35N9FXl4ey5cvp0qVKkyePJkRI0YQGRnJRx99VCzTceHChfzyyy8cOHCg2HITKHjuY2NjadGihexJeO7cOerXr8+aNWsICgqiQYMG7Nu3j/j4+GJzgxkZGXTu3JnJkyczqGNTFvarxcb+IYSaHmKKPoM+KQrbuJuEGqO5+FVr/hzWRKbvF4hgmF47SwQpN51tMLEvzo6xC7fJXqOvw9SpUwkODubMmTPMmzdPfnZeh2fPpGdq8ODB1KpVIMi+dOlSPv30U/Ly8mQW7YDPZ+FatdkbtwlgiH8itUMKBYb4R2RcP0jey2h0ZWvhEhT62u8uWbKECRMmlMjE/d+Af7njO3fuHF27dsXLywutVouPjw/NmjWjbt26bNiwgbCwMFq2bMnRo0dp2rSprL8XGxvL2LFjGT16NHFxcXz++ec0aNCAFy9e0LhxY7Zu3Yq3tzf9+vVDCEFyclEKvk25BqjyxWh1QdVxqNUJG78Q8uIf8XLdROmHKlMTtYsvmTcOEv9XQaGnfZWWuLb4AK17KbLuncaUJRVlK/UOGF5Gk7B1Jlk20rbf5Boxd94vbN++HYXOgYote7HnkYl2HToWkcZSKpWMHj2aVq1akZ6ezocffsjYsWOZNWuWnOewt7NjbIuyRWxXAIwpL4nb9DVP5nbnyY89id86E1OGdF0sdVaFa2z61Qti4/CGaOPuolaIIqNanVqJjVpJq1AvQmP3E+qhkx+elJQUrl69Kg84srKyyM7OlgtyAStbnEaNGlG5cmW5vqxixYr0799fliE6efIkMxes/NdtcV65JmazmbS0NBwdHVEoFPTo0YM7d+7QtGlTJk6cKIdW6tSpw08//USdOnUoVaoU3bp1Iycnhy1btpCTk4OTkxPLli37x0W0FSpUIDExUS5tKQ7du3dn586dsglnYfy7Z3zPnz/nhx9+oE6dOjRo0IDnz5/z22+/8fjxY77//ntq1aqFQqFAq9Xi7OzMwYMHqVOnjpzTdXJyeqtjKYy0tDTmzp1L2bJlWbNmDfPmzePSpUv07t27xHzkqlWr+Oabbzh48GCxdZBvwquzwWnTppGVlcXu3bvx8fFh4MCB8mxQCMHAgQOpV68ew4cPZ+/evXTu3Jmm9Wvhl36HvVP6MKt9afKOLWLztyNwsy8IH157msK3u+/+vbwgYDAr+OXALZq2aoe9vT1OTk707NnTyolg7dq11K5dm1atWhEVFSV3eOPGjePkyZPywPvEiROkpko+oYMGDSI2NpaHDx+iUCgYMmQI774r6dcqFAocHR358ccfefToEVlZWTRp0oS5k0bL+3Ru3JfACTtl4W6lzl4eCKudvUg+ugxD3ENsfCvgUKsT/iOWoSsVRtbtY2yY0EMeiBQnM2Zvb8+MGTOIjIwkJyeHmJgY/vrrL+rVq1dkXSEEtWrVIicnBx8fH8aPH4/RaCyy3r8b/1KOb+PGjfTp0weTyUSFChXw9vYmMjJSnr7a2NgQGBiIEAKdTkdCQgL+/v6EhYVRunRplixZAoCrqyvfffcdT58+5dy5cyQmJuLg4MDmzZsZO3YsUVFRDB8+3CrndP7qTa6dOSo3mubsdBxrd0Ht5Eni/gVgMqLxKovKzhmVnTO5MfcKbIOAlGPLSTm2HLsqLXCq35Os+6fJuLoX24qNJb3KlBeY89VMSrLL2LFzF1q9PYZ8CxeDoy9ZNftz5sI2TIY8UGnQ+VUgwA4i79zEbDYTFBTExYsXGT16NBMmTMDBwYHhw4eTnJwsh0sn94nAs2F3VJU7YlYoESgQwkzcpmkYEp6gK10dYTSQdfckprR4Sg/9iYntQopVVaheypWVHzSm27sDGb9wC4+SDVZKE91r+DPnmylcu3GGQ4cOyaGt77//vljJKEsxbs2aNalcuXKJtjiPHz+mV69e3Llzh8uXL9OpUyfuObny4vSWf6stTkZGhqwTaoGNjQ2fffYZAwcOlM/nxo0bZGdno9frmTJlCr/99hudOnVi9erV7Nixg3fffZe7d+/SuHFj9u7di5+f32v3+yqUSiV16tTh3LlzdOzYsdh1vL29qVGjBnv27LEyXwUoXbo0z58/Jy8vr9gcYGGUK1eOnTuLugHEx8ezadMm1q1bx40bN+jSpQvffvstTZs2fS0RRq/X07t3bxYvXky3bt3e4mytERsby/z581m0aBGtWrVi+/btxbKbX4VF9eXQoUP/Ur7SAp1OR8uWLTl37hwREREMHTqUvXv3snr1aj744AOcnZ0xmUx06dKFcuXK4eLiwocffsiaNWuws7MjMTGRVq1asXbt2iJM31+PRpFj/PtqN0KYebp2Mg8SntCqVStyc3PZuHEjT58+lUPy169fR61WExwcLEeHLFiwYIFMXFm40Fp8Ojo6GrPZLIcRC8PPz08Od4Lkf+dub0N4eY+3kqwzJknqU06N+6MPqmr1mX1YCxwMyXjZSCHlwsYBI0eOfGuxaYuhs8lkolevXly4cIE5c+agUqmYMWPGW23jH+Of1kFkZmYKV1dXAYjevXuLvXv3CkAEBgaKevXqlViz5uDgINRqtVAoFMV+rlarrd6XLVtWaDQaAYjq1atbr69QCKXeseC9SiMoVN9W7EupLLLMb/gSoS8vHbPS3lWoHNylY3Hyko6hXDmrcx89enShujmPItvTBUnH6dSgtwgcv1349f1O/kyr1Yr33ntPzJ07V/j6+gpnZ2f5WtStW1eEhYUJJycnodPpRGCZYFGjy3ui/KTdwrfHJAEIjUeQKPX5DlH+yx1C7STV7C3esOONv9fgwYPFmDFjiiz/8ccfRUhIiEhISBBCCFG3bl1pP/nX3PKbxMfHy9/Jy8sTT548EWazWdjZSbV3168X1PaYzWbx8OFDIURBnZGXl5doNG5RsfVRDjU7SvV7NdqLwAk7he8Hv8u1iAGfbbRaV+NZWgBi2bJlQgghnjx5Ivz9/Us876+++kqucwJE27ZtRbt27QQgJk+eLIQQ4sGDB/K5fvXVVyIwMFDcvn37jde0uH19+eWXr13njz/+ED169Cj2s7Jly4o7d+68cT9RUVEiMDBQCCFEcnKyWLZsmWjdurVwdHQUvXv3Ftu2bRM5OTlv3I7BYBCfffaZsLW1FfPmzXvj+q/i7t274r333hMuLi7i448/Fg8ePHjr7+7Zs0d4eHiIS5cuvdX6lt9n0aJFIiQkRNjb24u+ffvKdX7Xrl0TdevWFc7OzkKpVAp7e3vx0UcfidzcXGE2m8WQIUPkbdjY2AiFQiH0er3o27evSExMFEIIUbq0dG8NHz5ctGnTRuj1elGzZk1x+NQ5UX7SbmFftZUAhHP4APl+tK/WRlrWZECx97ZH14nSc+8ZJOLTsoXRaBSBgYECkOvaLLC0K5ZnysXFRdjY2Ij4+HgRFxcnbGxs5JpfLy+vYtvOpk2bCkCEh4eLxYsXC6VSKXx8fERycrJITEwUru4eAoVSePWbU2K9oqUWuPArcMJOYVe5eUF7WapKse3rq+e0f/9+UaNGDWFrayscHR1F9erVxebNm63Od+TIkUIIISIjI+XzT09Pf+t76Z/gH4c6T506JSeTp0yZIsfTg4ODZbpuWFiYPBVWq9U0a9ZMlqoSQhRhKHl7e1vFqUEKn1iSwleuXLE+iMLDFpUGTAZ0/qGoXQuxBpXSSNehZifpff5xqt1KAVJ4Tal3kMVbzRlJmNIT0PqGyLNJjaOHXJszffp07sYW5Ar1pWugdpLyEhqf8pL7sVGq51La2IJSSeHKCgcHB1atWsX48eNxc3MjOzsbrVbL1q1bCQ4O5vr169SpU4cBAwbg7+PFw2ObefJ9V2I2SuzEoAqV6Vrdn89aV6RVYyl0kP78zc7FM2fOZMWKFdy+XeAruHbtWubOncu+fftkirgloe7p6UmpUqUIDAzEaDQWm6hWKBSysHLLli15//336dOnD4GBgQwcOJDhw4fL6uvp6ekEOKjQFBPCdazdBZRKMi7v4vGsjsQs+hAA++ptZcmoF6sn8OSHnrISvUU79fDhw6+tK7OMoLVaLd27dyc6Olq+j77++mvUarVMVgoJCWH69Ol8/fXXREREWBkFvw3q1atXRJ7qVXTt2pV9+/YVoaPD24c73d3def78OZ06dSIwMJBt27YxePBgYmJiWLt2LZ06dbJi+RWHpKQk2rVrx40bN+jWrdvfEgg+c+YM77zzDk2aNCEgIID79+8zf/78Yt0lisPx48fp378/W7dupUaNGm+9X4AvvviCunXrYjQaWb16NX/++ScgzXa1Wi3dunWjatWqKJVKfv31V3r27EmFChVkiyZLVKVz587k5uayevVq/P39CQkJ4flzqVTm999/x87OjmrVqnHp0iW6du6E2ZiHfVWpXcu8dRSQwnTZ0RLRwza0ePFnS/5a5x3M5ivPUalU8mz4TSmUgQMHkpuby9KlS1m6dCm5ubmy87larZZn52q1mrCwMIKDg+Vo27lz5xg2bBhms5nY2Fi6d+/O6NGjSUqIp1qHAej8K5a0W+zDWsruFLYVGuBQq5PV57HLRpHzIorSoVXZt2+fFVnlVSm9wYMHc+3aNbp160a3bt1QKpXcvClFfCzPoaXN/0+6sf/jUGfhXEZQUBDlypWjevXqHDp0SJaVKkxXVSgUHD9+HCcnJzlO7efnJydnAdm3KTg4mMxMKcxYuXJl+YYsDmYLYcUkSXSZ83LQegdjTLJsV6BxL0VW5Jn8A1GBMOFYpzNJe39FGHIwJD1HX74+qNRgMkqdKCCMuYCCtIws2cNNb2uLyTa/jkipJuPaPvlYDLGRiNxMlHqp1MJsyMFsyCVhV0GtXWJiIp988gkeHh5MnjwZk8mEj48PR44ckTuJunXr0rVrVxYuXMipU6eoXFmqdbt58ybeilROzf2AFVFRslj0iRMnrMINxcEiy/Xxxx9z8OBBDh48yCeffMKhQ4coVaqUvJ6FTuzi4oKnpyebN29m1qxZbNq0ieXLl+Pq6lpEMkqtVrN8+XI53KlUKvHz8yMkJISKFSty+fJlfHx8mP/pu9T57mDRg1MokNLN5lcWF4zL8uIeIvIKqM5RUVFERUXh6+v72nyUpU7Iz8+PjRs3IoTg3XfflUkmQgg5p2Dxkuvfvz+enp688847LFq0iM6dO7/22lpQt25dLly48FpWoZubGw0bNmTHjh306WOtj/i6ji83N5d9+/axdu1a9uzZg42NDXXq1GHlypV/u6DcEgZ95513mDlzJt9++y0xMSU7doCUS921axezZ8/m+fPnjBkzhtWrV5coy1USLly4QPfu3Vm3bh0NGjR48xdewW+//UaPHj0QQrBy5Uq58WzevDkajYZTp05x9uxZOb9++vRpdDodn376KXPnzkWlUnHkyBHc3d359NNP+emnn2jWrBlnzpzBx8eHx48fI4Tg8uXLDBw4kKioKOLjX6KJuoJtcG3J9Dn+EbkvokAITOmJ2PiFoHH2JvvBJdm4GsCpYR85Ry3UOlbvPEL0zt/l/Oy6det48eKFnC+zDLQsQgiWcoCZMyVugoeHh/w7ZWRkyJMKjUaDo6OjlWRiUFAQ8fHx8v1vaZMDAwNJsSt43ouDc6M+ZFw/gCkvG4caHWSnBoVagy6oOmpnLwzxj3l4+xodO3bk0qVLVK5c2cqN3WLsbDAY0Ol0dOrUycqNHZBF/gvnCf9Tbuz/eMZXuMjw6dOnmEwmpk2bVuRhtsBgMGA0GuVODyhy40dHR+Pt7S0LN4N041oICsXBvlpbNB5BWPh+ec9ukXX7aMEKQmBMiy+YHQppWwqFSiZQmLPTSNg6S+r0AExGDHH5I7WyNWnzxR8IIZgwYQLZWVnk5au+YH41CSswZ6XK4tF5sfdJPbUWU5p10ejo0aM5fvy4fF6xsbHMmzdPbvS+++47atSowaJFksffp59+KueE7t+/T1JSEp06dZI1JLdu3Vp0NlwMPvzwQ+Lj45k1axbvvvsumzZtkjtVkGoiLeSOmzdvcvjwYWJiYuTRnEqlwtvbm7Zt23L//n2GDh1KSEgIP/30E+np6ahUKgIDA/n55585c+YMn3zyiZzvep1/V9qFrWA24lCjA4Gf78D3AymXkX55l1zOUOrT9QRO2InGU5pV1KxZk19//ZWAgIASG/6pU6fKI+AHDx6gUChYsWKFPJrs2bMnrq6uMku3cJ6kdevW7N69mw8//JDff//9jdcWpE7Ny8urSJ7mVZTE7ny14zMajRw4cIAhQ4bg4+PD3LlzadKkCZGRkTRv3pzQ0NC/3elt3ryZZs2aMX36dL7//nvUajV+fn4lDi5zc3NZtmwZlStXZurUqYwcOVJmI//dTu/69et06NCBJUuW0Lz5m01ii4NltmQ5b8vMefr06YSHh/Pll19y69YteVCYm5tLx44d6dBBovF7eHjItWWWmf7p06dp3769bJQLkkDG1KlTZQazKV1Sb7IPawlA5q0jZEdKs3u70AhpX8/vWmlgitwsOUdtNuTw8PlLK3Ufd3d3nJyccHBwwN7eXp51WyJharWa2rVrk5ycTHJycpFomOVZzc7O5uTJk1bRhgYNGuDjU9RZ4tmzZ2Qa/kbdVyG4tv4Ir95f49ZmJN795+AZXIW8vDx27NgBSEzSefPmMW/ePDZt2gRIs2cfHx969OhBSEgInp6esqqMhcH733Bj/8czvoYNG+Lq6kpSUhIzZsygf//+fPzxx/LNVBguLi4kJydTo0YNKlWqxNq1azGZTHz88cds2LBBXs9y4xWmNJ89e5aUlBSaNm0KSCSKVq1aUSowCJPRQM6jK+iCqkmlCELg3HQI2VHnC0wzhRmRl41Q5Z+qUgVmEznPbiFypRlE2rkt5DzO92rL968T+TNIlc6RyKgoypV7l0cvEik1dgsKtZaX674CYSLv5UPMOdJDplBrcY4YTNLen0GpIjv6ItnRF4tcj+TMXPbu3VtkeW5uLjY2NmRmZtKkSRMuX5YKyocOHSqvY2trKxejBgUFkZycjNls5siRI28kFKjVaiZMmED//v1ZvXp1EbeA7t27c+fOHeLi4qhXrx5169aVHbADAwPx9vbm2rVrDBs2jPDwcHr0kNhdS5YsoUKFCtSrV4/Dhw8zfPhwdDodAwcOtNr+pkvPUCsVRWqfSipnMOdmFnHAtgTHa9SowYULF9i+fTvp6emEhoYSEBBAQECAPIIMCwujbt26nDt3TnbADg0NlVUwfHx8uHr1qjyouHXrlswQBSkEc/z4cdq0aUNMTAxTp059o3qJpayh8IDiVXTu3JmPP/64iNRauXLl2Lp1KydOnGDdunVsKqSiMn36dPz9C0L4f7ekwWw2M2XKFFauXMnevXupWbOm/Jmvr2+Rji81NZU//viDn376icqVK/Pzzz/TrFmzf6zecv/+fdq0acP8+fNLJP+8DSwkHctxpKWlMWbMGDki06dPH5ycnLh9+zbHjx8nNzeXihUrsmLFCkAiqjVs2JCkpCQePpTC5snJyVy5csXKBkmhUKBSqVCr1eTk5KBykDpLu8pNST66nKzbxyUxeaUK24rSc+TcuC/OjftaHa82f6CWF3ufvDLVWbR1kXwOY8aMkds1kKJoZ86cQaPRkJeXR8+ePWnatCm+vr4oFArWrl3LkSNHWL9+Pc7OzvL9oNFoiI+PJzc3V247P/74Y3744Qdu3bplxS43mUyIrJR/dO2NKbFoXArssFT5v4EluvF/yY39H3d8tra2/Prrr7JDwZkzZzAajVb2Kv3792f79u0kJyfj6+vLvXv3uHbtGiaTicWLF792FvA6+Pr60qJlK/bt2YUpM5nMW0dko9XMm0egUJhJaeuEXWg4GVfzOxqVGszWM8jC9X0FM0Ppb+atI7yo356oqCgc63aVcpNINkDpNw/JnR5ILMUcC3PUah8KUGsgP/e39eJDqlcqWiNlUbQICQmxYuFFREQQFhbGnj17ZHWP3Nxcnj17hlarJS8vD0d3LxYei+buizTScow46tSEeDvSo6a/TMt+8eIFX331FbVq1eLGjRtWDtAgNRpjx44FpHKE58+fyx20VqvF398fNzc3Lly4gLe3NyNGjJA7iQYNGuDo6Ei1atV4+vQpCxYsKNLx3X2RRsL57VYO2M6N+pRczpCbWaScwfIIN2jQgEGDBvHzzz/zzTffcOfOnSIzrWnTphEeHs65c+fkcgaAzz//nDNnzshiCPK2haBixYrMnj2bPn36oFQqCQ4O5tSpU7Rv356YmBgWLFjwWoakpeN7772iqjoWODk50axZM7Zu3cqgQYNkFZVNmzZx7NgxRowYQZ8+fWQVleJQvnz5N9YNWpCaKhmipqamcuHChSKSUH5+fnIILSYmhnnz5rF48WLatGnDrl27ZHPhf4rHjx/TsmVLvvnmm2Kd4d+EwlY9x44d48iRI+zfvx+Abdu2ERgYiE6nIzMzk7Vr18pu5oBshlyYIh8bG0vlypXlmf+sWbMYP348gwYNkjtId3d3AgICuHz5Mk7uXjiVrYYBUOkdsS1fj6w7JzBlJqMrUxOVbcmhdn35eqjd/DEkPMHx0XGyVSrS0tLQ6XTyAG3r1q2yLGDh8z1w4ABdunTh+PHjAEVC+i4u0mzSaDQyevRoq5zhuHHjZLazwWDA2dmZ1NRUhBBk3DyMXdW/J5sGEPPHcGwCKiFys8h7KYlA2NravjYV8L/Wjf1fZcecOHFCdOjQQbi6ugqNRiP8/PxE69atxaJFi4QQEtuqQ4cOwtPTU9ja2oqQkBAxevRombVDPhvIwgLs06eP8PPzk5fXrl1bXL9+XVStWlUAokyZMkKv11utoy9XT3j1nSlULj4CFAJlATNUobMXAZ+sE0q9gxX7yK3dJ1bvLcxCQKBQyqxCQHh2+Vwo9Y5CV7q6cKjVSTjU6iTcO44Vbu0/fT2DtIRX9ylLir2WixcvFlWrVhX29vZCr9fLiuoWBuODBw9Ehw4dhJ2dnbC3txdly5aVGF7lwkS5L3eI8iUo7H/w5wVx6s4zUa1aNTF9+nTx/Plz4ebmJu7fvy/MZrO4e/eu+O2332SVfEDUq1dPfPnllyWeQ82aNUVcXFyJn7u5uQkhhJgyZYoAxMCBA8Xg5eeFTUBleR2Vo6cInLBTXubW/tMijhE+g+e/ltX59ddfi4kTJ8rX0GQyicuXL4s5c+aINm3aCK1WcruoXLmy2Ldvn8jMzBRCCHH79m0xY8YMMXnyZPHXX39Jx6NSiQMHDojatWuLmjVriqNHj8rbTU9PF61btxYdOnSQt1EcLl26JCpVqvTG52bdunWiYcOGYtKkSSI4OFiULVtWfPnll0Kj0Yjs7Ow3fv/IkSOiUaNGb1zv7t27okKFCmLEiBElOh3Ex8cLJycnMXToUOHi4iJGjRolP4//KmJiYkTZsmWtWKMmk0kkJiaKO3fuiGPHjokNGzaIX375RUyePFkMHz5cdO3aVTRq1EiUL19eODk5WTGMS5UqJfR6vcx8rF+/vti1a5dYv369qFKlirCxsREeHh7yd6pWrSqEELILQGBgoJg9e7Zwd3cXOp1ONGnSRD6ugQMHCkC0a9dOdOjQQej1elGjRg1x8MQZq2fLs/c3Bfd5h8/e6OrgO3yxsCtXp0Qm+9ChQ4td3rRp0yLX03KvBgYGis078t1mFAph6+Ip2o4qcElxd3cXKpVKAMLV1VUsWbJE+Pj4CLWNxHp37zz+tcdsYXZa3GECJ+wUDrU6CbWrv0ApbdfL21ucOnVKXLp0SXTo0EH4+fkJGxsbUapUKTFu3DiRk5MjPv74Y1GmTBmh0+mEo6OjiIiIEJcvX5bP5+DBg6JmzZpCq9UKLy8vMWbMGJGXlyeys7PFyJEjhYeHh9DpdKJBgwbi7Nmz/5Z7Uggh/mWtzkaNGr125hYWFibHgIuDeKWg5PHjx4SHh+Ps7CwrvfTs2ZMbN27Inlc1a9YkKCiIrVu3ynkyXUBlvHpMJWH795gNOZhS4xDGXEROBi9Wf44wGV/ZrzWRIuNGIdJF/mcqO2epni8vC7fa7Yk/vpach1IuLS+wGrmPr8pf0bgHYkh4jD64LtlR50Bri9Y9gLyYe+jK1MSck0FejBSiVNgXL7I7dOhQq7CmRYfUgtKlS7Njxw5MJhPDhg1jyZIl6HzKoW3/JXlmhcxYtSAnn066//ZLDtx8TsXw3kycOI67d+/SpEkTwsPDEUKg1Wqxt7fHzc2NwMBAzp8/z7Bhw2Tty5J09wo7YF+/fp0qVarIv6ml8L0wHHVqvP9NDtgWpKSkWOUDlEol1atXp3r16owdO1Z2YVCpVEyfPp2rV69StU4jfBq+g41XDbReTuxdJeX26tSrT4sWLWjWrBnr169n4MCBVKtWjVmzZlGhQgV27NjB0KFDad68OTt27JCvR2FUqVKFR48ekZqaWizpJjo6mvXr17NmzRpu375N1apVWbt2LTVr1kShULB582aio6Ot3DyKQ5nQqlToMpJP1l8pcYa/a9cuBg8ezHfffVfiDPT06dPMmjWL1NRUfH19iYyMfKMIdHHIzs4mLi7O6vXw4UN+++03/P392blzJ0uXLiUuLo6EhATs7Ozw9PTE09NTlrrz9PSkSpUq8v+enp64u7tz6dIlFi5cyLFjx+jQoQPDhw+X77XC6NmzJ0lJSZQuXZo+ffrIs7dXMW7cOAIDA5kyZUqxKYfatWszdepUq2XhDwsczHWBYfnRCSFJl70BWmdv+k7+lX2TuvP48WM6dOiAi4sLe/bsISsriwMHDnDy5EkroWmDwVAs07ZLly5cfZLMr0ej+OJcPOUn7ZYF+W8DFSbtlrVCR4QHUzXAmefPn8ueeIvvKTh8LwFRRJ3TGsW5sbu2+ACAlJOrST25ljatW9OgQQOWL1/OkSNHaN68OQ4ODmzYsIE5c+ZgNpvf2o39VXz88cf8/vvvVK5cmebNm7N+/XpatmzJgwcPin3u/i7+14lUb9iwgS1btvD8+XPCwsI4fvw4d+/e5fTp00RHR2Nvb8+xY8ews7Ojc+fObN++HVX+b6hx9cOtzUhil4+22qYhvmgj/Ooyx9pdSD21Vip/MBtR2NjJlF6BitLu9vi17UN0vMQ2zYqUwkwKjQ5hyEHl4Ioh4bHU6QE2XmWwCw0nOe4ROYWYXgDxGbkkZuRaKUO8LXJycujduzfbtm3Dtkx13Lp8KVP+S4IQIBRqbulCCXz/F1SxN6jv5Y4QgunTp2NnZ8dXX33FhQsXrAqrLbp7GzZsoG7durRs2bJEB+yWLVvSsWNHMjIyOHv2LOHh4TKF3IIQb0ds1C/+LQ7Yixcv5ujRoyQkJBSbV7bAkn+oVq0an379E/MP3WX3rj1c/GMWWp9yGNPipcGMUs2TMp344M8LfBRRjj59+vDOO+8wf/58GjZsSJ8+fZg8eTIrVqzgiy++oFGjRuzdu7eItqBGo5HzjxYnhufPn7NhwwbWrl3Lo0eP6NGjBwsWLOCXX34hLCzMirRgIbiU1PFZu5A4kptQwMbUqV/w48H7hJf3wPbRCTYu/J6tW7cWIZFZNDRnz54tKyhdu3aNgQMHyp2eyWQiKSnJqiN7+fJlkc7N8rLklywdlrOzM4cPHyYsLIxBgwZZfebh4fHGIv3ExESWLVsmlxZ8+OGHrFy58rWmwEajkd69exMYGPhaXcyXL18yatQotm3b9layYCDZGZ2ITCDhxjFyHlxGGHKwr9bmjc8egDDmsWPmSNLy7c169epFv379MBqNzJw5k6+//ppGjRpRtmxZOaWxYMEC/Pz8GD58OM+ePcNgMGBvb49HQFmS7QPRBNXAlJFM4u6fsPEPRetdjowbB1FqbHBuOpj9pqYcv5/AZxGl+G5oe8xmM82aNcOoscOxYR9sKzQk9eQacl9GY0h4gsjLRqnVY+Mfimf3ya89H2V+p3kqKoFP1l/BVRPApRt3qVBayjkGBwczbdo0ORxdHPLy8vjoo4/YsWMHycnJeHp6Ur16dVmBZ+nSpSiVSg4dOoSnpydqtZpVq1bxyy+/FBmU/BP8r+r4IiMjqVGjRrE1TpbcYUBAgKyqEBoayvbt2ynv7UCWRkXCtcMkbJ9T5LtKGzv0wbXl+huA9Cu7rNZRW5K2+UxNG/9QmckFcO3wdvJesfQAZLURy0zQAl1gVZL2/YrK0QOtTwWEMZec/JqfcytmUOavRXQZ/jmfdahF1QDn110WKwwdOpRt27aBQkHWo+tkzeuD2tETx1qdcagpqZQkH/+T7KjzGFOl49V6lMY5fAC6gEqoPMui9QnmskJBvbFdmPbLt+Q8vycr4r+KJUuWUKZMGTZt2sSyZctkhue3337LsmXL6NixI9988w2rV69m1apVODo6Ur169WJzOd1r+vPjwaJSWxYH7JSjy8m8exKlzr5YB2yZsIRUR3rq1Clq1qz5VvJa0fEZ9F50lhyjCYW9G0IIMm8dAwXYlKqCc5P+qP1C2XfzBQdvxtDKI4PxXeszfvx4hgwZwrRp06hYsSLjx49n6tSp+Pr60qhRI3bt2kXVqlWt9lWvXj0OHTpEZGSklYrKN998Q7NmzeQcYWJiIvPmzZPLKOD1JQ2SVuRdcoymYpU35Bn+rVgwBzFhyW4aNCg4tqSkJBYtWiTnKVu0aEGbNm24d+8emZmZsrhwXFwcSUlJODk54eHhYdVpeXl5UbNmTatZmaenpywZB5LFTOvWrenRowfz589/a0KMEIKzZ8+yYMECduzYQadOnVi5ciX16tV7q218+eWXmM1matWq9VqR6hEjRjBo0CBZx/VtYLEz+mDleLKf3kEXWBXnfOeQ10GvUTKxc3XqD19NnTp1yMzMZNCgQXz++ecEBQXJNa+LFi0iOjqaBw8e4Ofnh4eHB8+fP0cIITNB09PTSb99FbiKk8ZWrh/OfXYbYTJg41OenEdXSNr7K7bBdcm2seWzj0eQ8egRLi4uVG/agetRTzEmxSBys0i/ZB2JM+dkkB11nowbh2Rfz+Jgzr/5YlNz2Ho1Bp1ayeq7N4io8IIR4cHy8RYmY72KlStXsnjxYipVqkTXrl2JiYnhxIkTgEQyMxgMBAUFyfnoWrVqsWrVqjfWPr4t/ld1fLt27SIjI4MqVapw4sQJK5ZS8+bNmTp1Ks+ePZOlpyxmsQEutkz/oB6dO88kAXCq1prshKfkPZOKtQXg3Lg/hoQnMoPQoUYH0i9slfdtqRlTaPWIvGxUekerjs9neD7VXQhQKIjbOJXs6Iu4tBgGCNIvbMOYnojK3hXnhr0x5Uidt9rJi+x7J63OM/vRVbKBQzf6cD7WWKLcWHGQ2XdCyKUZxuQYUk6ulju+zJtHUNrYYluhIXmx98l9dou4jVPxfX8hage3fFal4GoiqFuNpUrKFTl09KpZqkV3b8aMGZw8eZLPP/+c0NBQcnJy2Lx5M7/++iuTJ0+2KowvjKlTp1qN0ApLJhnT4knY+QN5MfcQxjw8uk/GNrhOsdvx7jsTYTZTWpPGoWm95YatZcuWcrJ86tSpTJs2jYEDB8qzzalTpxLcZpAsLgyg9S6L79DizTQVSiVmlOyPt2fH4C/RPjlH8+bNad68Ob179+b7779n/vz5ODo6EhcXR7Vq1fjmm2+YOHGiXGZy5swZzGYzFSpUYPbs2bRu3brYgvI2bdowZMgQYmNjZep5uXLlOHbsmNzQJycn4+zsXEgg+S20IhVKUGn54chD/vh9IWmXdxMbG4vRaESn0xEYGEhwcDAGg4HMzEwCAwMpU6aMfI6enp64ubn9raJ2C3JycmRJsHnz5r1Vh5Wens7q1atZuHAhmZmZDB8+nB9//PFvhVzXrFnDpk2buHDhAmPHji3S8UVERCCEYN26dXz99desXr26yDaWL19eJEpRGP3qBcG67a8dfFigUIBOrbJ6th0cHGRB8JiYGGJiYjh9+rQ8kLe1tSUrK4tnz57x4Ycfcv78eTw9Pdm2bRt79h3g6dMnYDahUGvJfX4Hc3a+vrDOAZuAymTll1cIQw5p5/7CoVYHMm5LqZIFa7aycMNucs+cxBh9kczIs7Loh12VFihtbDGmvCA76jzpV3a/tuN7FYVTKnsPHSN2zQ/odDrZEuz8+fOsWbNGXt9S3wdSaqBv376EhobKRLmS6vugZPnIv4v/VR2fpZOLjIwswlLS6XQEBwcTFRVFREQEpUqVYvv2AoPEMH9nWtWqwB+Xj6F4fpVyleoRnRpLTnoyIjeT5wuH4tp2FEl7pHiza/P3cG3+Ho9nSvU9Nn4hBE7YSdLBP2TjRd8hPxc9yPwH2aFGB7KjL5J8UKrxsguNQJn0DFN2OvZVW5Hz7A6gsJqlSN+X2KcOtTqhdvIi8eYJ3l88ivdTY/B0d6NDhw58++23ODs7F+vYPej94XLezyagMl59vuX5wvcxpcWR8/g6usAw3DuNk5UZzHnZPPu5PyIvm7yYe6grFIS9hADUWh44VeOnXZf5pH0NuRYnOjoaHx8fBg8ezPjx41Gr1TRq1MhKzcTFxUU2hH1bWEJG2QYTqWc2kvvkBhqPQHSBVVE7v752R6dVYbi6k4iIhaxatUoqxk1JYf/+/ezatUtmOZ4/f55PPvmEkSNHkmnjzje77sgPJxSY3ubFP0Klsy9iept8dDlZ989gzDe9zcnJYf369Rw7dgx/f39sbGy4c+cOOp2OunXrMmPGDLZu3cqtW7fIzs7Gzs4Oo9HIrFmzcHR0lMsnCmPjxo10796djh07snHjRkaNGiVbVxVmpy5btoyHqWZ25QRjUlg/rsKYR/LhpWTePYHIy0brVRaX5u9h4ysxhnPjn/Liyilynj4DYcbHx6fEQvUnT57g5ub2Vi4CqampjBw5kjNnzhATE4ODgwMRERHMmDGDTz/9FBcXFxYvXlzEJ+9V3LhxgwULFrBu3ToiIiKYM2cOzZs3f+P3XsXly5cZPXo0Bw8exM3NrUQBgRcvXjB69Gh27txZ7G/yNuhXL4gwf2d+OxrFkXvxKMDq3lLm9/NejjpahXrRtnLRHPVff/1Fly5d5PejRo3i559/Rq/XywIST58+xdfXtwgHAiRBaUPSc8z5g2uNewB5L6LROHlhSpZ+X2HKkyM+qNQs2nGSo8tm5bPcI6RUTX7JVmZhfgMUcUR5W2RFXSB+60wQ8Ons32VVntu3b8vlJiDlKQcMGMDRo0fZtm2bbIHWokUL/vrrr/9Ifd//qo6vZ8+eHDp0iA0bNnDw4EHmzp0rU+4TEhJwcXFBoVBw/vx5zGYzQ4cOZdGiRfJoesqUKURGRnLmzBnUyY+oVbUSJ0+eBIUCh5odUTkWeIClnFgt5fT+IfRla+Ha+iOS9v0KQFbUeTRufjjmy/vo/Cvi2noESfsXUNgWyPJ/+sXtZD+4JDeuKFQ8efKE3377jd9//12mXxsMBi5dusSxY8ek121rjy6FUoXWqwzZaXHkxT1EFxhmJUeUcmKVHI6N/+s7VE5emDKSrBt8jQ3zjz9h45xxnD52WP5uRkYGEydOxGAwMGXKFEAKl02fPp3ExEQ2b96Ms7MzH374YYnX6dq1a3z22WecP3+ejIwMAgMD+WbdUb7dfUc+d8danbGv2qrEbYDFfaIifaauYu7cudSuXZv58+eTkpIi1wJZYCltqNygBX9E6awaprc1vVU7emLOTsecnUaLFi0YNGgQRqORy5cvyyINubm5nDx5Ep1Ox507d6hfvz6HDx+ma9euHD16lEqVKsmDgsqVKxMcHExWVhZZWVns3LmTnTt3cvv2bTZv3sz3339PXFwcarXayr3h6tWr3PFthUlRtCFPOvgHGVf3ovEIRBNYlaw7J3i5bhJ+wxejsnXCmBaPKTMFz7KViYu6/tq82uuK2F9FcnIya9asoUmTJjRt2pRt27bJz2z9+vVlk+XiYIkULFiwgEePHvH+++9z48aNvy0KbkF8fDxdu3bl119/lUPOxXV8QgiGDx/Oe++9V6JZ8NsizN+Zhf1qkZiRy/zDkey//VL2BTXn91OxqTmsv/CUdReeykSTkmBJMfj4+JCcnCzLORa2VbKr2BiFjT0ZV/eg9SmPxztfkHp2E3kvokChxPvd7wB4PKuT3MZYQqGYjBxbK7VTrq1GYFu+HtrroSTvlQb2PkN+QesZJF8nU2rJDiMlIePmYRJ3z0OptcWzx2S2J3rS91kKYf7ODBo0SJZasyA3N5f169djNBqJiopi1KhRHDhwgC1bttCqVSs0Gg2PHz8mKCiIly9fyu3h60qJ/g7+V3V8KpWKxYsXs3jxYnmZJVc0YsQILly4ILN8PvjgAz79VLLUsBS++/r6cvhwQcNtIRc0GTKJ40u+Jv3idvyGL0Ht7CX79tlVbi5bc4DEXLLxDyX15Boez+mC0sYehUqFKStN7iyMmSnkPrmJKa3gBhF5WeTFRuJQvcC4U6HRWXV6Cr0DIrug7k/u9EAOW4L04KrVarkGx8XFhYCAAD755BMer9jK7cfWs0hlCRY+wmyS6hpBLtw3pcVjF9qkSINvRsW509JszlIbGBQUxIsXL1iwYIHc8aWlpVmN3sLDw60kz17FkydPePHiBdWrV5dj+P3qBfHtiN6yaEDinvkk7pmPz3u/kXnzMFl3T2HKTELj6o9To964hTZiYrsQetfy54cffmDZsmWkp6czcOBAzGYz+/fvp3Tp0lahzhbDp+bP9Ky9DWXT2xodcG01HENyDDG/f0D6pZ04NeiFUquXG5GYpR9jzk4jI8cg16j2799fDsVYRuNeXl48fvxYvvcs+pGVKlWSH9hHjx7x8OFD2QLJ09OTDh068M477zBgwABq1qzJ0aNHcXNz4/Hjx3KjV7XHaI6dKjoCN2WmkHH9ICiUePX+FpWdMwlKFZm3jpB+aSfOjftiW64utuXqYog+C1HXi2yjMHx9fblwocBg9OTJk0yaNIlr166h1+tp06YNc+bMwc3NDVdXV65duyYX6b/77rs0a9aMpKQkfv/992I72OjoaH7//XeWL19OtWrVGDNmDB07dvyXGjKDwUDPnj3p06cPPXv2LLg2xXR8a9askRm1/y7suRnLhovP3pxzvf2S4/cTyMx9vd2OEEK2kapduzYjRoyQ7dhMuVnkRhYM7hRKFeoS2OEWqGydsA0NJ+v2MYz5M8Gsa3vJi72PXWi4vN7L9ZOwDa6DOS+H3Jh76AIqW7WJb0L2w8sk7vwREGh9y5N55wSZd07Q9/wKbuwtfnKxdu1aZs2aRa1atbC3t+fGjRuAVOPn5eXFoEGDWLRoEUlJSfj7+8s1l1u2bCEqKupfLnD/P+PAbtG3U6lUuLq6MmnSJPbv34+dnR1Dhgwpsn5ERISsT3d8ydfy8tSzm3i+8H1Sz0iKMcZ8liBIHUXi/gUkbJ0pKcEolJizUjClJ0pKIsY80s5tIevmYcxZqVLYMh9KXVG2mSkj0eq9jV8JBo4KJTalqqAsVAir1WrJzc3FbDaTmJjI1atXady4MVpHaypvztNbMsM07ewmXm76GlN2GmZDDvGbv8acnYa+bG0UNpK8lK5UleJdzpVKWSnTkpy2hA5fvnwphxosDspxcXEMHjyYvXv30qZNG0JDQ9Hr9bKW58mTUl6zY8eO3Lp1i88++8zquD8a0g9Pb4lQpC9dHZc6nUk+vIS0s5tQ2tjiENIQU3o88Vu+Y2wVI/3qBfHVV18xfvx4hBD06tULT09PWUC7sFxTdHwG3+62Dm9a8HdMby2Y8stK9Ho97du3Jy4uTs5bOTs7U7ZsWbmTejVEZzQaZXZhRkYGWVlZ6PV6jEYjW7ZsQalU0rlzZ4KDg9m6dStKpZImTazFjn8+UrxYryHhCZiNqBw9UNk5S+fkLTUGeXFvH3q2oHAR+4gRI2jcuDGnTp2iTZs2lC9fnmXLlskamY6OjnKnJ4Tg55+lmYOFDFP4/Ldt20abNm2oV68eZrOZU6dOsX//ft55551/efQ+ZswY9Hq9nEuy4NWOLzY2lk8//ZTly5e/Ubz7bWFlSvtKp2dMecnjmR3kNIrFlDYl21DMlgpQq1Ytzpw5I0e6LALwICnJ2FeT9HGzI8/yeGYHEnf/VLDPtAQSdv4gD7Qzru0jN/Y+OU+tc+9ZD6+gdvHBbCo4FnNmKhnXDpD94BIaVz90ZWrweGYHnvzYEyHMmLLTeTyzI09/7ietn694lXnnOEII0i/twiItkfPgkizZdnPfOhIzijfVrlChAu7u7mzZsoWFCxfy4sUL9Ho933//Pffu3WPevHmMGDECGxsbnj59Sv369WVzgydPnrz2Or4N/msd35w5c1AoFIwcORKAH374AYVCweeffw5I2nsKhYJx48YREBAgd2LXrl1jypQpHD58mDJlyuDi4kJwcDAKhYJu3brRpEkTbG1tefz4cbHV/xlX92BMiZUliHKfXCfnsTQaTjn+JxmXJban1juYwne0OSsFke/PB0ii1oU+V9kXZUSqXhmR5USVoNwvzOQ+uYlduQKWmYXAA8gkg0GDBpFDAeHAbMjh5ZovEPnedWoXX3KizhG36Rterp1EdvRF7Co3w6PbJDDmS7BZnCSKafDVjhKDyqKyb2FxPnjwAHt7e1n/EKRSh5YtJd3Cmzdv8vjxY/r27Uv79u1JS0sjOjq6+HPNx8iRIwkMkMJbM8YO48uJX5Lz4BIKhZKK1WpRq0Ip6taoCkJwYPMqK9PbBg0a4OzsLOejnJ2d6dSpk6xwcf1ZKtkGM2mXdvxLprcWmDIlurXBYEAIIUcYfvzxR86cOSMrUryaj7GxsSE8vGBkrVQqyczMJC1NUgpasGABUJCw/+mnn1i6dKmVnNjTRR/JjWjclu9IOvgHuTH35GM1Z6fJxsSZt45YnUfy8T+JWfoxsX/NkfdjGZC8isKhTsvMzzL6rlatGhqNhiNHjqDX63Fzc+P9998nPT2dMWPGsHv3bgC55jMmJoavv/6a0qVLM2vWLPr27cvTp0/5/vvvrYyM/xUsX76cvXv3smbNmiKzu927d9OrVy8UCgUnT55k2LBhDBs2jKysLFkQ+tUylL+Df2JKm7hnPgq1DQqNjkGDh9CuXTtu3boFSAQsIUQRYk3hQZBL8/dxbfG+RAArNFvTuJciN+YuzxcOJfPmYVlgX6lzwJSeVIRcFFC1AQ7VWpG0J5+/oFBiVykClEpEXjZODXtjHxqOxr0UIjcLQ/xjcp/fAQTmzBQMyTHY+Er3v21wbcnMuJCkoC6wKtr8HLPa0YNNl59RHOrXr8+yZcvIysrC3d2dYcOG0aVLF54+fUpsbCx6vZ5ff/2VP//8k/fffx+NRkNmZuYb68bfFv+1UKfFvuL06dNWfy3kCcv78PBw9u/fT2JiItnZ2bi7u5OQkEBWVhapqanUqFEDg8HAy5cv2bJlC82bN8fd3d1KN87Hx4fY2ILRvMajNCCwBBfTr+7BplQV0i8XlDionDxRpry0GhmpHL1kwWmnul3JjjyDMFiPaDJvHyUvX+BaH1wHhcamYB21VpYtKwpBxq1jVku0Wi3Z2dlyyPPq1at89PNk5hxcjykzCcPLB/IIT6FzQF+2FulX9pD3PH+Up9JgSHxO8uElslWSQlXQcb4qC+ZQsyNJ+3+Ti88XLVrE7Nmz8fT05OjRo4waNYrbt29TpUoVcnNzZXKRQqHAxcWFLl26EBoaSpkyZV4rLG6BZYbhZGtDJR/pARXCzLV91uGoqKgoHj9+/FrT2zp16siNuil/BpZ199S/x/Q2N5NKlSuRm5trpecI1vqEr3Z82dnZ/PXXX/L7V6/JhQsXZOFwQB7oVK5cWZ7BatwCpN/HbCL7vvRMaD3LoMqf+Yu8bNmYWD7X/POwsHtt/ELIeXyN3NxcWrVqxb59+6hTp47V7MfX11cWJLeIHyckJFiFtUESB8/JyWHx4sWcPHmS6OhoDAYD06dPp0KFCnTv3p1Dhw7Rq1cvdu7cWaTU49+Bc+fOMW7cOI4dO1asSHfh32H8+PFkZmayadMmBg8e/G/Z/z8xpc24th+tbwXsQptgfn6TPXv2cP36daKiomSiTXp6OleuXOHy5ctcvnzZqrA79cxG3NqNxja4DmoHd7Ly2ZrGtHhsfEPk316pd8CckYRTg17oy9aCg39Iy22dMGel4lu7LU9jIzHEPwJA6xuCe8cxKPWOpF/cRvrlXej8Q1E5eWFIeELSwUWIvCwUWluEIZv0y7tlMX+bAGsRAY17KTx7f4Mx9SUxC9/DmBbPlXtPoEnxsnsWZqevry9du3YlNDQUf39/q+fk7Nmz8oBXp9PRrl27f8Q2LoJ/mwbM34TRaBQODg5CpVKJ9PR04e3tLcqXLy9sbGxEVlaWcHJyEkqlUjZQLF++vABEy5YthV4vye4olUoxcuRIK/myXr16iSVLllhJ/7Rs2fK1EmJKWyehD67z2nUg3+g2/3/PntOEopDprcY9sKhsV7tPhEuLDwokuvINbgu/bAIqF1puLWmkUCiEq6urOHz4sLzseWKacG825M3HWsLLLqxVibJgpT7fIcq2HSrLltnZ2YnGjRuLP//8UwghxMyZM4WTk5MsvaTVasXQoUPFjBkzZHk1y/JZs2bJv7VFCgoQOp1O6HQ60bRpU1lSSaPRyCagKpVK9O3bV4SHh8umopbf2rKNxo0bi8GDB4uhQ4cKDw8P8eOPP4o5c+YUnGPl5tZSaO0+sTLSBMlAWKG2ERr3UtK1fo3pbcvh04QQBfJ6np6e8rl069ZNPmeLCaharRYODg5CqVRayW2tXLlSBAcHy+/t7e2Fo2OBkXJxklY2/qHy71RYPsqtXYEZst/IlaLU+G1CobHJP/9mInDCTtls1GKGanl5eXkJrVYrAgICRHh4uBg0aJCYPn26sLW1FXv27JHlAUNDQ4UQklkxIJo1ayaEkOTbLIbRCoVCdOvWTZQvX15UrlxZ/PrrryI1NfV/rN2IjY0V/v7+YuvWrSWuY2kfnJycBCAOHTpUxMjVYuRrkUjUarXC3t5eNG3aVDZVPnbsWBEjVw8PzzcaufoNL2h/LMsKr1965DL581GjRonevXuL8uXLC1tbW1GvXj0xYsQIsXjxYvHtt98KX1/fgvtDbSP0wXWFrkxNeZlL0yHCuengQr+vQr5v7Co3F0o76Xwd63aT27rCsoGePaaKwAk7hWvrj6Tv+VUUgRN2Cn2FhsW2HxqvMkLrJUkl+gz5RQRO2CmcGvaR7rtKESJwwk7h/8k6ef0ec0r+nYQQYtq0acLNzU1ev0KFCuLGjRtW6xgMBnHt2jVRqpT0rK5atepfu4nEv0Gy7J9CpVLRqFEj9uzZI/tSTZs2jWHDhrF8+XJ5NmcymahSpYo8Yztw4IC8DbPZLI8GLIiKipK94iwo/B0A/1GrSb+0U2Z1mrNSyXml7MDr3RmknFhtVY6gsnOVZ3wqOxcQRUMdbu0+wT6shfzekPSc5Pz/NR5BVrWBIDGvtN5lSb+wDfLj5BY4Ojpy6NAhOabt4+ODr6sDlcr6c+wwKPWOsh+hQ61OsqSQIeUFmldKA57OexdzdhrGlBfycb0qC6ZQKGjbdzi/H1wpX1sLGysrK4slS5aQmppK+fLladKkCbdu3aJjx47MmDGDrKwsQkNDZaPJzz//nISEBBwdHa3yb7m5uSgUCisxc6VSycOHD3FwcCA9PZ09e/aQlpaGyWRCo9EQEBBAdHS07AZy//59KlSowKNHj0hLS+Pq1atFWGNvgiktHqXeUcqVgZUKx6sqMQ9ObWfQoAfydxPyFThMJhObN2+mVq1aXLx4UY5WGI3GfB8yPVlZmTKxaMDAwVhITJYcrsFgkM9bFMOQ0PqUJ68Y5SFjIeZd3LpJaDwC5ciCRYxBpbcnYeePiPR4q+82b96cFStW8OzZMx48eCC/1Go148aNkwvob9++jY+Pj8wyPXz4MLdv32bfvn1Wos83b96katWq+Pj40KpVK7ke69+N3NxcunXrxnvvvfdaYWTLdXRxcSE1NZWLFy9y4cIFcnNzGTFiBD/++KO87qsSiUeOHKFnz57cuXOHJk2aMGbMGObMmcPYsWPJzc0lPj4O14a9XmvkWhwKr2/IKfCVzMrKom3btkycONFKnD47OxsnJyc0Gg0t27Tl8KnzmDKSyY6+gMreBVRaMOWh9SmHKSu10J6kc899dpvcZ7dR6iXugb5MTVQObqRf2Ebus/xyGZUGm1JSrtaQ71+qcpLSHW6thvPs3ilUjp6Ys1JwaTkcY+JTMu+dlp8djUeg9UnmM48LB1ftbUqenZlMJiZOnMjkyZNlRvusWbP48ccfWbJkCenp6Tg4OMhGuyEhITx58kTme/wr+K+yOsPDw9mzZw9z585Fo9HQr18/Jk6cyNy5c+XPT5w4QWxsLGq1BqPRQPMPvuL4nz9gyM5EqVJzJ+oRHwzqy7Fjx1i0aBGtW7dm8+bNVvtxc3MjMSkJS07uxcoxKGykgkjUGpzqdse5cV+Sjywj7Zz03eQjSzHnFOT0VI4e6MvWIiNf8SX1/F8IQ0lhywKkHFsp//+qdBlAzrNbmCyKMK+EQg0GA7/88oscUrTkQ5uFeHEMUDt5kpeTCcJE+sXt5D67LRW3PrtD4ARJlcHSiFu0SnOfXOfJDz3lTlvj5k/K8T/Rl6mJOf4hF6+mYWNjg8Fg4I8//mD37t20bduWBw8eEBkZiaOjI+3btyc5ORkXFxcmTJggCwncu3fPKgxhCT1bQnkghSvKlCnDrVu3UKvVGI1Ghg8fzrx58/Dz86NLly4sWrQIo9GIWq3G39+fmjVrkpaWRnx8PEOGDOHw4cMsW7YMpVKJQqHA3d1dZoy+DbR+FcFkyCeBKACBLqAyuTH3yLx9TGKVFiImRd+4RPSNgt/O29ubmJgYateuzenTp6lRowYtWrRg9uzZ8joaRzfMLoFw77RcdCzy86wo1VJoWmkmNSUZjUZD27Zt2bNnT5FjdW7YW3YWSbu0k6zIs1YGpxqPQEwZyRiSY+WBkCWMa8pIJvPmoSLbPHXqFGq1mqCgIIKCgmjWrBkAFy9e5NNPP+XcuXNMmzYNNzc3MjIyZFNoFxcXGjRoYOWpKYTg3r17slVWo0aNKFOmzN+uxXsbjBo1Cg8PD7766qu3/k7FihX54w/JTzM0NJQmTZpYdXwlSSTGxMTg6+vLN998w759+2SvRo+gCugbFO85+jYw52UTn59fGzdunHzPFDaSrlOnDp06dcJkMuHp6cmoj0bg2uID1o99BwDvvrN5vmg4IAlu6H3KoXL2wZQiTQ5sQxphykzBsXYXkg7+AflMcsdanXCs1QkhzLz4cxx5Mfd4uepzNO6lyLxzHFDgUL0dAFp7F9Ru/hgTpQ5R518Rg86etPN/AWATUOmtxAnKetoxf/58Zs6cSWxsLDVr1pRDuE+fPqVu3bo0adIET09PeeBoCV97e3vTvHlz/Pz8iIyM5NChQyiVSplb8K/gv9rxWfJ8d+/epW7dutja2tKgQQO5oY+IiCDFLMW/jfmNxtENizDl5tfMmIxUrl4LDVKjPmbMGJ49e1ak4zMYDPmF4yYUGh2m7DREfmej0juhLyORCZyb9Mecl0XGlT3kxUZKup35UNk5k/NI8sdDoSD7/hnZuw+kGRRAxvX95Dy5gX3VVugCKqH1LkvWPUvRt7SuwtYRlY09xuSY/E4vf6T/Sv4vOzub5cuX4+zszJw5c+TyjVKuEkNTZaPHq8+3JB1eguFFJHkvolDZu+FYv3vBNl6R+gKsnMzzXkSR9yIKpY0dOU+uc/bpLfmzM2fOyH8teQiLM3vlypXx9PTk+vXrTJw4EbVajVKpRK/XExwczM2bN/Hy8qJPnz788ccfVudkSepXqVKF3377TSalxMXF4ezsTGBgIImJiRiNRnk2YsGqVatkzfb7QQABAABJREFUkoklF3Dw4EGZyKRy9CygYhczIwfQlaqMS/hAAGJXjiEvnyxizsmQxQsAvN79ji5tW7Kwn6SlaXnQR40axeeff87o0aM5ffo0ubm5zJgxg2XLlsmlDulxzyGuoFzFe+APGOIfS5J6ZiO5aYlYssNJSUns2bMHhUIhz1ZKjf0LhVqTfxrSeVpyfI61Ost5PK13OdzbfyJdv83fkB15Vv5MFxhGqbGb4MCPPLkmWStt3ry5RGZjYWYnQIcOHVi+fLmsiZuZmYlCoWD+/PksXLiQ27dv8/HHH+Pi4iL/TqNGjWLAgAGyGsyrr9KlS79Wb7Mk/P7775w4cYKzZ8++sVO1XMNRo0ahVqsZNWoUgMw+teB1Eonx8fH4+vqi1Wr55JNPZOZ4heY9ear6Z82mKSuVuI1TyYuNpHx4F2bNmgVInV7hXGrFihU5f/48CxYsYNq0abJ/oUKrQx9UA4WNLSo7Z0xp8bxY/glu7T7Bs9skYpdILNCs+2dRu3ijcihKuANJpcqz21ckH11OzqOrGCLPonELQKHWErdeGlQ4+pZB51OejMRnKPWO5L6IlicFQJHIVUmo7aWk7bufIoRgyJAhVKpUiYSEBLp27crNmzdJSUlhy5YtCCFwdXWld+/eTJo0CZBUmS5cuMDevXtxcnIiPDycsWPH/t8mt4CUKLe3tycjI0NWJm/YsCHbt29HoVAQqwvkp5OxODXoReqZjSDM2PhUINdsxpQWh758AwzxD8lKlkbnLj4BeHp6FpHPSktLQ63WYFIo5dGwQ52upJ/fgi6wKjZ+ksixQqXGrfVH6EpVIfXkWmkUbeuEQqkmL+6hrCGZceck5lfCRxaNT0uIQVeqCgRUwql+T5zqSzVGCTt/JPPmIRzza/1ST61F7eyNMaV4Gr2lcbe3t5d98gC5IHTV2UdM2XYd/aAfKRokk1CcG0LxEFR26sW4+s54enqSkpIilyJ4eXmxadMmevToQV5eHgMHDpTr/CxQq9V88803ZGVlSVqiSCO6b7/9VppxJybKVH6j0YgQgrt37zJ69Gi5HCAvL4+jR4/KBry1atViypQpODk54ezsTF5eHv7+/nh4eKBUKlmwYAHXr19nwYIFXLhwgTp16iDyHduFyYghqXiVEkPCU3kdo2UA5OCObXBtqzC1XqNiRETReqGdO3cSGxsrd9jnz5+na9eucqendvbBb/iigv3lh55Tjq8CwL5qK1xbfUjmnZMk7pyLQqXm15/nM27CRDLTpJmcpdOT/tciTAa8+nyHLlBishY2OBVCgDDLHmmWz0zZ6SRunk72szsMGDCAJUuWyKG0qKioImmCW7du8ejRI1kx6OHDh4SHh3PlyhXpegnBsWPHqFSpEuPGjUOhUDB69OginoGZmZk8evSIBw8e8PDhQx48eMDRo0fl93Z2dpQuXbrYjtHf378IS/PkyZN89dVXnDp16o1hVCGETJooXbo0TZs2ZcKECSgUCvr3728VYn+dRKKl80xJSWHy5Mmo1WqEEFz963ecB1RCpft7fnHG1Dherv8KY9JzHOt1p92HE+WB1KsEIosAQ05ODh988AGxsbFs3LiR0aNHQ14mKr0DWs8yZBcqxTJlJAFSZMp/xDJ5eXEuCyAN5C0DJiHMxC4ZSV7sfbSeZdDlJJD65C6eZTW4f7ETISQ1I4Vai8YtAEPiUzRuBbW7rxrwKnX2BE7YSb0yrtiqTZjNZgICAuRZ85MnT8jIyKBz584olUr++usvkpOTad++vZWjxtatW//WNf47+K92fGq12ooiDxILa/z48VbahM5N+lsJFpcEvUbJdxtWWikeWNCmTWueBrYh2a4UivwRo2uzovV/AHYVm2BXsUmxnwG4NBtaZJmngxYfYxy3c5wxlNALuXf41KowtPDNoteoWP9BPSr7Olqp4l+/fp2//vqLunXryqof2dnZGAwG6a+DDx4R/VD5Sw2iQv161fuSoFEIQnnGwYMXSUlJITU1FWdnZ6pWrYqXl5ecZ4yNjcXX19eqBsvR0ZG0tDRmzZqFt7c3t27dQqFQ8P7771O3bl3mz5/Prl276NevHzNnziQgIICsrCzq1KnD0aNHOXr0KE2bNsXNzY1evXqxd+9e1Go1Fy9e5OeffyYoKIjo6GiOHTtGZGSkPOIv7GBevnx5tDo9eTnpJOyYiykzBXMJTtPZUeeJ/+s7TBlJ8jq5z25jG1yg6CEpxYQQ5u/MzJkz5XAuSA1x4bKAO3fukJCULL83psTybMFQlDoHFAqpA/L/cIlcb5f94BKJ+36TmXlCwNips8hKL5yrgeTDSzBlpcm5u9SzmyQB4eptSL8pFcsbEp7wZFZHWWNW61NeashWfCpFLfKxcuVK2bi0TZs26HS6Ig0uYKWPef/+fX7++WeWLl3Knj17MBgMhIeHo9PpZLPU4ODgIhJcdnZ2VKpUqViHCSEEL1++ZMmSJSxYsICNGzei0+nkcpG4uDgCAgLkjtDV1ZWFCxcybdo0qxrBkrB06VKrXKmTk1OJRq6vk0i0YMSIETx79oxJkyaRl5fH7NmzURxYgGvHcSUegzG9IEz+5Mde2PiUJ+9ltJyPT7+0g0trNAw/4siGDRtQqVQcP36cBg0acOfOHb788kvOnTuHTqfD0dGRTp06yezhrEfXUGUmYCw08C5cz+dUrwc5T2+RcvxPDHEPUWhs0JWugUuzIaj0xQ8asiPPYUh4gsYjCO8BczkxtgkNaobxPPoGAU9vovSvLKsaJR38A0Pi02K38ypOHT/O+g8mANIgWKFQULFiRVq1akWTJk2YPHkyrq6uVKpUiTFjxvwt6cN/Ff+rlFsseLVOJjfm3v9H3VuHR3V13+Prjmtm4q4EEoIGggVKcIrT4lLcpXhLcSiUUii0WIEixV0LVHAPhCDBgkUgEPdkktH9++NmTjIkofR9+/m+/e3nmSeZO9fvuWefs/faayE38hD0SU9gKS6AUK6G2NkX6tCOUJThnkyLOo38R9cr3OetW7cwtt2n2JksgLmy6dF/YWn5BqRZ7JB7Yy8sRfkg8IXE1jyh1KMac0rq+p0htqpBAODMRtDDY2jfYCgDhFhZ7wGwF7es1axZExzHQa1WI+bkCrTs0BXS4Ai8NKiRBZVNcf1fmcBiREDBQ5j12ZBotahatSq0Wi06dOiAiRMnYurUqfjpp59sQCplwQ3nzp3D+vXrcebMGcTHx6N+/fqYN28eOnfmC3itBLUKhQLHjx+Hn59fpaTWVrOCJW7duoWrV6/Cx8cH48ePt9HiysnJYXRPGo0Gq1avxefTvkBR/B0ogsIhMQQxDcSypg7tCFNuKgyp8RDI1LAU54MrE76SiXh6NCu58O+//26ji2i1tm3b4syZM2jatKkNhykAmHNTYc5Lh8StCqOx0zTtB2PWWxjexsKQ8gLyqk2ge3IJsJhQnJ0CocrBJoRUGHvNhh2oOJ6fCRvSE2FMLSlsLwHOkKEIEIrg2Hkq9In3YdGX0p5ZzerolEollixZwhyE2WzGb7/9hgULFuD+/fts/fbt26Nq1ar47bff4OvrC71ej9TUVEZwUFbp/EON4zjEx8dj7ty5UCqVGDBgAM6dO4f4+Hhs2LABQ4YMQWJiIuLi4vD06VMsXboU7u7u2LJlC2bPng2hUFjhTDEggK8lmzlzJiv/sVrZusiy9j6KRABMSiokJARz584FEeHY8RN49ugSpIGNKhwcW4zFyPh1Bfsu96vLk0dbSt8XMupx5cReWLPSs2bNQnh4OFJSUvDRRx8hMzMToaGhkMlkSEpKwr59+2zCw2v7hWLi06aIv5xWwtfJgZPIoAhqColXCFK2TwYnFENepQHMBVkofHAWptw0uPZbUmFejpE6uAWC44D6vcYjo6Sms47oLV6Ia/+tmkV2L5QOUAc3RX5s6bthnc0CYPWsx44dg0wmY6mc/xfGUUVQsv+BvX79GoMGDUJkZCSKi4vh0nMe5IENURh7FRnHvwPIApGjF6Se1UGGIujfPoXUvSqcP5kFgAdx5FzaDk6qgNS1CopfPbDZv0QigWeLvjDX+cSmlu2ftqT1w2w6q4qMhazIAiEItczPEUjJTIIkPz8fubm5bOaVk5ODnJwc5OXlQSaTQavVwmKxICUlBfb29mjatCm8vLyg0Wig0WgQL/TC+WwtTIT3Ck5WxCD/ru3evRsrV67ErVu3yoWgrC/Rxo0bsXz5cqSnp6NHjx5Yu3Ytq0k7ceIEFi9ejNjYWNjb28NgMGDNmjXo2bNnuWMBfGHy0KFDERERwUJuly9fxpw5cxATEwOFQoGWLVti+fLlWLhwIUJDQ9G5c2fMnj0bFy9eRNLbZAg1rnDsPBVS92rIOrcZuqfXWS0cyAJlzVZw6jyVhZ7LmkAsg0hA8PTwgIeHB+7cucNmN2KxGHXr1sW3334LkUiEsWPH4tGjRyAiyH1roygxBjK/uihOuAepd024DfgW5uICZP22BsWvHsCiL0Qp5o0gVDlAXiUM5rx0FCc9sSFIsJrvzJM23w2pcUjexuesIBTBZ+ohpO6dBX2JEol9y2Gwa/QpmgQ4oFHhTZvOZM6cOTh37hxiYmLQsGFDNGzYEDk5OTh9+jTc3d3x8ccfY8uWLayQ3cPDA7m5uZg6dSoWLVoEAIiOjmb6gW5ubkhJSSk34wP4wc7ixYsRHx8PuVyOoKAgLF++HM2aNUP37t1x/PhxrFixAtOmTcO5c+fQpk0b+Pr6spkNEWHo0KEoKipiJMZEhKysLBskqjV8+vLlSyQmJkKj0cBsNqNly5Zo1KgRyysGBATAycnpgyWS3mejdpaK0r5rhbFXkXHsWwjVjlAE8embohdRMOUkw6H9OKjrtEX+3i+Q9ZqfjdetWxe3bt2CWCzGihUrMGPGDNStWxfR0dEssmEFelnP/cCBA5g4cSJ8fP0RdSsSbccshHfjDniWmo97+1ei4M4pSDyCGFl5/t3fALMRHiN/gik3DUVlQHaapv2Qc2k7Cu79zmj8Ch6cR+aplQCAL7/8ErKqjfD98hXQvX7MM1aBIFDaw7HdWDbxeJfY3YpuL06MQereWfDw8sbvp09h5syZuHLlCkwmkw0nbaNGjbB161aEhFTCbvUP279mxrd06VJcvHgR1UNqIFkVCKHWDRZjMbJ+XweQBYrqzeHUZRpj0CeLmQFKLHodcq/vA4QiuA9aCZmjBxJXf2YL83XwhblWN3BCMfKjTyIv6hhM+RkQaVyhadKbyXBYjHpknFjOAA8AGL/nh5hNTJ0sAFlAFgvMBdl4s4EPkabunWWzjbpOHfi1aAGtVgutVstyWta/1v81Gg0sFgsWL16Mb775BmPGjMG6desqfJljknIwadNpJBpUkIjFNvRdMpEABKBlkDPGtQhEbS9tpdfTv39/bNiwAZs3b7bRjStr8+bNQ8eOHZnKtlarxffff48//vgD3bp1g5OTE7p164bo6Gi8evUKv/76a6WOr9x1xMSgTZs2MJlM6N27NxITE7Fnzx7ExMSgevXqkMvlaNWqFZ4/fw4nJydIVfYgmQrm/CzAHTDlpkLqEQSBwg5FzyNhzs9EYexVOLQdA7l/KAzJz/jQTYlEi4O9Bu3a8IrPr1+/ZuE1Hlksws2bN9GjRw9YLBbk5ORAKpVCr9ej6J2BltWyz22G7uk1CJT2PCBBx49ypR7BMKTFo+DubzxlnW9tGNMTYSnM5knVQzsBFYA4rHk8AIDZDENaHMROvszxGdLiIRcL8VWH6jh/yJYp6Ouvv8aiRYtw+vRpfPnll1ixYgVEIhEsFgtEIhEOHDhgQ1Sdnp4Oo9HImGkAMGYlgUBQKRF1UVERhgwZArFYjAEDBkCv1+POnTt4+fIlmjVrxnKGVgdq/ZuYmMjC12vWrMHdu3dx/fp11r45joOjoyMcHR3LEU1v2rQJGzduxN69e9GpUyfUrFkTeXl5OHr0KHOQBoOhQrBNQEAA/Pz8PlixYXyLQFyMiUfKxV3lfrPmj835mTZAKYBXPZBLZRg2aRLmT+cR2p9//jlDQltDfQ0bNrQB8LxL7TZlyhT8/PPPDP3ev5EPhgxugGHboxBdoshgePu0XLTDmJ0MQ/Jzm/MqC5SylOAfBDIlm82npKRg14pePH+woxcECjuYMl6BDDoUPr7IHN+7xO7vWk5hMZo2bYr8/Hy0adMGVapUwdOnT/HZZ58hLi4OS5YsQbdu3SrVovyn7V/j+Ky1GWGdB+KmpA70JguK4u/CUsznALXN+jGnB5SoEjjxCVb921iQUQ+hygGZv62GIfVluVyXXZNe4MQSFD6+hKwzG3h5juoRKHpxE5mnVkGo1PLoTrMJhtSXkLhXRdGLW/g7ln1pB/JuHACE4hIqnypwaTsCvduGIzdfjfON2yPt2T0U5mQwpB4ATJ8+HQMHDiy3v9WrV2P16tV48+YNxGIxPD09UVBQACcnJ4SGhjKn99VXX+HIkSPsHm7btg2DBg3C6z3zsGHLDsRzrohNzkdesRF2MjGC3dXoWc/rgxTgOY7D2rVr0a5dO/Ts2bNCjbSNGzeiW7duOH78OLp3744dO3bg+++/x+rVvARUaGgoHB0d2cu8c+dO/PTTTzh27JiNqsIPP/xQbt8bNmyA0WjEkCFDsG3bNhiNRnh5eeHhw4eQSqV49uwZnj9/DqlUCn9/fxw+fBiX3pix+NcHKLYAjh0+h+7pNZhyU8FJFAAyAZMBhvREKGu0QFH8Xd7xmY2wc3BCYnwc1q1bhz179iA4OBgRERF4/vw5cnNzUVhYCKlUiqwsHkhgrb8DeECLlQgY4Du+rLObGB2e5R06NLMuFwKJHGZ9ITiJHBInHwgkCh65SQR5YAMIZCpk/r6WKdJLXPyZLJZQ5QBzQRZStttyoFJRDstNnoetWdGYHMfB19cXjx49YsjYivIrvr6+ePHiBbZv345169Zh69atjDpw2rRpOHCA57vdsmULm52/C8WviM3nXb01q9YawNOq3blzB9988w1u3Lhh81tllpCQgFmzZuHSpUuoVq0aFAoFevXqhbp169qsl5OTw2aI8fHxePToEX799VfExcXh1atXcHJyKucQrR83NzfmgOt4azE23B1TV5wody6CkjyaxC0QboNXsW0sxQWQiThM/sgDi4eNZGCZuXPnonv37rC3t2dUgVFRUbBYLOVmfFZr2bIlunTpwt4Xs9mMW7du4dnD+4ySUN2gOxxaj2DbWAFWisCGNtgCoDxQylKcD5FIBIPBgCNHjsBsNkMdEgH7zlORfX4L8jNeQRHUFHaNSwev7xK7v2tFBfkgYzHmz5+PadOm2YRub9y4gSVLliA+Ph5Go/GfYWb5C/tXOL4WLVqwHMrO774CwMPSbfIbrx/h7c9jIVQ72eRBhHYujDvOXJAFcALIqzaG7nFpXkyg0EBRJQwAh9zIQwB4eQ5lcFPk3/8TWb+tRu6Ng5AH1IdApoTXuG2wFBfg9Q+l8f4PsaISIUiYTSCBAPo3T/B61yykNzyJ7WPb4FePIsycORMCD2c8fMiXGLi5udkwy5e1+Ph41KxZEy1btsRvv/2G2NhYcBwHk8mEw4cPs5fq5s2brATASql18eJFKBQKtG3e5L8O79SpUwe9e/fGnDlzGL9kWatenS/ODQ7m0bEZGRnQ6/UsbHXmzBkbEgEq4f/8888/bVBc7zq+sudtPYZYLEZAQABTCbdygrq6uuLq1auQSCQY6M1vs+jQLcRtGc8Qb2Ut8/c18Byx3qbatig/FydPnmTnHRsbawNqAcDCngDg7e2NvLw8JCUlQah2gin7LQt/mYtyS0fWIglgsdjkeUxlAAKkLyw3OzBmv4VALGc1fABgTItjHZvQ3gMO7cbCkPICxa8fQl9ShlIn0KfSsPWNGzewYcMGfPTRRxW2iRo1atjkXq2M+ETE8mHW63706BHS0vj38+TJ0nDs4MGD0b9//3JQfC8vL+zcuRMtWrRgYClrGUHZcgKDwYD+/ftj9+7dzBG8z6zyZNOnT2dgmsr0+LRaLerVq8d04sqa2WzGmzdvbJCov//+O5st5ufnM2do/Tt94wmceCWEwUwMVW0xFCN56wQYUl4gddcMnrQiLx3Frx7iqx9/waVt35YDy4wfPx579uxh4K+7d++iYcOGqF+/PqKjo7F582YbJz579mwApWCdcePGQaFQoF7P8XCo9zEK7v2B/NsnYMpJgVBhB2Nmkk1t77smr9YYIkcvGDNeIePAPKhIB4PBAFfvAKS+5vN/Yq9gZJ5eDUMyPwjTJz1BXuRhSL1DoK7T/i+fk5UyMSoqipHLBwYGomHDhvj9d76Nt2rV6v+J0+NP6F9ga9asYbRjHjUakTqsK3FimQ1VjkBeQu0kEJaj0RHaOVdIr1PuIxDZ7lOptf2u0JDn57tJXELJwz5CMYm07uTSdzE5dZlOYkdv4kQSEshUJPEIItcBy0hVr0ulx9U2/pQy8ovZ9W7fvp39FhISQm5ubqTVaqlFixYUGRlpc2/OnTtHvr6+5O3tzSitpFIpjRo1qtx9tFJNbdu2jfr27UurV6/+x55RdnY2ubq60u3bt9ky6zVY6aOOHTtGAMjJyYmIiDp27EgAaPXq1fTzzz9T165diYjo5cuXlR5n2zaezikiIsLmHg4dOpSIiAwGA6MMs7e3J6WyhHbN3Z10Oh3bj9FopFU/7+Lbh0JDVSbvJp8ZR4kT8bReEicfqjbnNAU178qO4eTkRAEBARQWFkYAqGFDnsZOJpORvb09hYaGkkxW2i4DAwPJw4+nIBNp3XhKJ5cA/hl51yTfmSdJEcLTmNk16W1DcefS/xuSeATz56d04GmtBnzLf1c5kve0wzY0WFa6NUUIf184qZJ8ph8l35knSeIRxPbLcRxptVqyt7dntGLWT5s2bfhzsbOjhQsX0sqVK2nTpk20d+9e+vXXX9l1Wz+9evUiV1dXEovFNtRrlX3KWnEx397fvn1LP/74IwGllGddu/L3/LvvviMioj///JMAkLe3N9WqVYuaNWtGzs7OJJPJKDw8vNw7UdbWr19PDRs2JKPRyJYFBwfTo0eP/qJF/z3Lz8+nmJgYOn78OK1atYomTpxInTp1ompN2pJrjznkM/0I+c44yijLFCERJFQ7EieSkNrFk3r0H0y//PILe+f1ej0VFxdT9erVCQDt27ePiIgeP35M3bt3Jzc3N5LJZFSnTh1KSEig58+fs/s8f/58atiwITk4OJCTkxOj/vvx5x0UMOsUufb/lqQ+tUkgUxMnkZPY2Y/smvSqlGLNd+ZJ8hizmeRVGhAnlpFIqiBVcFNybjeWHdOuSe8Kn7mVHvBdmj8rTaBrv29s+0Ktltq0acPak1AopICAAJo0aRJlZWX9o8/sffavmPFNmDABhw4dwps3b1Djow6IVda0IYwGALKSRXMCAGab35w+nY3UXya/9xicWGZDTAwAlhKmfqtJPKoj48gSGMvmUQDAbIQpJxmZp36AuTAHnFAIZUgLkNkIQ+pLmHJSWEgW4OtYhHYu/AzAWIyiuLs4dCcJo0vIWq0aWwBPC9W8eXMm0dGqVSvExMTA0dERM2bMwLFjx6DVatnom+M4xhhSmVlpv9avX//ee/J3TKvV4ptvvsGECRNw7do1mxzE6NGjceLECfz6Kz+i/OwzvvRkwoQJOH36NL744gsoFArUr18fYWFhyMzM/FvQZZFIhO3bt6OoqAiJiYlIS0tjdFSnTp3C559/jufPnyM0NBQRERGIjY3F1KlT0agGj/Qz63Lh8GAfXicmMNVpR5UU179shTXCm1h4+QREIhEyMjIglUpZEbc1DFtcXAyVSoV79+6x61YoFHjx4gUrUWBUcOm212XMSAAAFL2MYmFKAMiLPAJjCZm5uTALqfvnMmkrc0EmMk/9AIlbFWga2+ZChQoNZH6hKE64i9drBkIgUcBcAm1386uKTzq0wa5du6BQKCCVSm3Qt1bNM6FQCKPRiFevXiE/Px/5+fnIyclhxAJWO3jwYLlnYUXV6vX6cqVIY8aMQY0aNWBvb4/Ro0ejbt26cHd3Z8/aqkz/xRdf4Ndff8XChQvx8OFDnD3LK4C7uLggLy8PDx48YLqb+/fvR9u2bREXF2eD6AXA0KFXrlyxCQVWNuP7b0ylUqFWrVqoVatWud8sFguexL/Grmsv8PhtLrIEUni06QV9an1k3DqJzLeJiIm6joLMFIwdOxYBAQE4efIkAgICcOPGDZsyi+rVq9sQmwN8fxEWFobq1avj7du3ePnyJRYuXIg2bdpAJBLh/uscrLv4AuuepYPIAplPTRZ6/FATa93g2ms+z8kBvsSmKP5u6fXXag37iEHQvbjFsxuVlOL8lW6fzLc2fGeeRNLaQTAXZGHWrFmYMWMGDh48iN69e8PHx+cvlVz+L+xf4fjKmrtGjocv7vAIPAB2jXog79ZRVphcNlwEAEK1IziLrSOEUMQYxJkJbF8EgdqJr+Eqs57YwR35tyJ5xpZ3jgNY2Qo4cHIVn6ORqyHzqwuRgwdQAjUH+Hg+DzPmzViYg9jk0k7C6iAAICAgABcvXgTHcfjkk09w7NgxfPnll4iMjETXrl0xYsQIfPstX4RurYM5ffo0FApFxTcQPCVVly5dWN3WP2VDhgzBxo0bsWPHDhtuzEWLFmH58uXQ6/UYPHgw00fr0KEDjh49irlz5+LRo0e4desWqlWrxhfi/g37/PPPsX79euzbt4+hWsPDw3H27Fnk5+dDLpdDJBLhxYsXTKTSw8MDDRo0wOzZs7F+/XrE37+BOXPm4Ouvv0ZmZiYclBI4qqQYOXIkDh06xEJ8VnCHXC6H0WgEx3EwGo3IzMyEWCxmUP6On/bBiT/Ow5DxTk1TGaRfxslVMJZo4xnLauQJhCBTMQRKbYnaNYfiVw95yRyZCmTUQxd7Bbrnkci9theKauGgMu3Rqet0pO6bA2NaAswMCcohJeE5tmxJhEAgYHm0smZdlp2dzZ4REaG4uBidOnVCv3798OLFC5vyGblcboO+s/KUAmDkE1Y7duwYtmzZAicnJwiFQkRFRcFkMoHjOEilUly4cAESiQQCgQBEhMLCQuzYsYPRzj1//hwFBQXgOA6tWrWCm5sbXr58iaioKIwbNw7Dhw+HWq2GWq2GQqHAoEGDMHXqVBZit9r/heN7nwkEAtSo4oulVXwr+PV7NmAri0S9evUq+18qlZYD3fj4+ODNmzc4c+YMjh49Cjs7OyxatAjdu3e3yXvy9c6xlYrh/h0jIhsUuNSrOiv3qUwdAuDrUq1IUXNJDWPh44sQquwZK5bYxd8m5UAlJ1uRdNz/C/vXOb4wP3ucvl2KRpJ6hcA1sCEyTq6EOTcV1qcrtPeAOfstwAnLEPbyvIswm23oxADw0ixlYLxie3eQ2tEG+cRkaSpwelbTNP8M+beOoqiMth4nFNvU5SlqtIJzl6nIizqO7HM/Q+JaBXnF/EwjPT3dhlcyKCiI5Vu8vfnk1J9//omTJ08yPa5x48bhk08+QXR0NB4/fgytVou+ffti586dFdI3Xbp0iQEP/kkTCARYu3Ytunbtiu7du9sUCo8aNarCbbp3747ffvsNffr0YVRE7zMrKw1QmuPbvXs3+vXrhyNHjiA3NxcNGzbEwYMHYWdnh969e8PJyQl9+/bF48ePcefOHTRp0oSh/hYvXmwjVKrRaDB06FA4OTnh1q1bWLt2LZvp1KxZE0KhEPfv30eVKlVw/PhxDB48GNHR0SgqKoKfnx8j5851rAGP4T3w+qfhMOem8sXqIjF7uR07TYbhTSyKE+/DnJ/BCswFcjt4DF+Ht5vHwmIo5nUdzSaefNjRCx5D14BMerz5aTgs+kJIvWrDXJSH4jKjb6FCA49ha0pLeCQKKDyrQpARB6PRiEGDBsFoNOLYsWPIzs7G3r17ERYWhpkzZ+Lw4cNQq9WMgsuqYu7s7IxNmzZh6dKliI2NZfk7Ly8vREZGsuv+7LPPsGNHKf/svXv3EBoaCoAHpuTk5ODSpUs4d+4czp07h+TkZERERKB169Zo3bo1rly5gtGjRyMoKAj169fH27dvcevWLVgsFgwdOhQ//vgjHBwc4OzsjNzcXKbmfvXqVWRnZ6OgoAD5+fl4+/Yt8vPzERUVhfnz50OtVkOlUkGtViMpKQmDBw+Gi4sLW1b2979aplAo/pGyB6vJ5XIEBweXc9AA7wAyMjIQFxeHly9f4vLly1i1ahVevHjB8vkA309cunQJr169Ys4xOk+JHy4lovg/qLGr0Equ2aZuumRgVfjgLIpfxUDuX89GvPv1qj48GvSdyUdxwj2YC3PBiWWQedeAc3hPvI6LxtKlS/Hs2TOW1xs8ePA/c+5/0/51jk8tE6NO9WooyaMj59J2yHzrlJIGl8DO7UI7Ivv8ZgA8WTNvfEcsUWpgr5LajHrf1VozpLyAsIziOSeWQepdwjTBCVCW51FWpQGKX/LinMqgptCG94apIAu62KvIPrsJhpTncOgwkak9FL+MQubva6ErQYUKFXawk/FJ2w0bNrBZA8CjWS0WC/bs2cM4LUePHo3mzZszdnIXFxeEhIQgKysL8fHxcHZ2xp49ezBmzBh89NFHFd7Hf4LPriJr0KABunTpggULFlSIwnzX8vPzceDAgXJhtIosKSmJ1eOVfXYWiwXbtm1jtYGXL19GXl4e65wKCgpw4MABxuKyfft2LFiwAH5+fpBIJBgzZgz0ej02bdrEZso3btxAo0aNWIisTp06uH//Pj755BM8ffoUDx8+RLNmzTBs2DBcvXoVAoEAc+fOxcCBA3EtOgYD9j6HuTCHRQEUNVuAA4f86JMAWZB7bT+cOk1CUfxdFD48B3lAGHSxV8CJZSh4dB6W4gKIHb0hsuPLJQQKDUyZSSh+FQOzLg8WfSGEakeQxQJjSiysMSgrSCD35mHkXNkFcAKoa7XGxSO/4O7ZY/jiiy9w/fp1NGjQAFWqVMHt27dx/vx59O3bFxMmTMDhw4eRn5+P1atXs4EMx3Hw8PBAs2bNwHEcMjMzERwcjNjYWDx//twGyWsVza3MtFotunXrxtQTkpOTcf78eZw7dw7Lly9nBNdarRY9evSAr68vOnTogMOHD+PNmzf48ccf4eHhwQZJmzdvxrVr1+Dj48MAUi9fvkSjRo3w8OFDBAUFQa/XM4dYUFCAVq1aYdy4cZDL5WyZ9W9GRka5ZdZwr/V/vV4PpVL5t5zlXy2rbAbKcRyys7Nx+vRp7N69G0KhEAMGDED//v3h4OCAunXrYv78+fD29mYzxIMHD+JZhh65YUPBiT9MUZ5MBmSf34rC2Cs8w49rFdi3HgGZRxAAgj41Dtnnt0D/Jpa1MZGjF+SBDWDKSeHFj/OzUBBzFkKlhhGiixy9IFRoKkTAG9PjkX1hGyy6XJgLsqBW28FkMmHHjh3w9fW14R/+f23/Csc3efJklsPas2cPHN192AjZmPEa5qJ8COUaG8b8siZxrwqJRylLh6EwB6nv1AILJXII7ZyZ1AyIWF4G4GeWUveqkHoGQ//GFslndXoA8Hb7ZMh960CocmBijgKpCmKtOy8hk/wMluL8UjSeQAinJj0R7K7GgwcPsHTpUpt9v3z5EkqlktWDyeVyVi9nZSd/+fIlnjx5wmZY1vCSNTdgpdSy0orJZDIMHToUI0aM+D9xgN988w1CQkIwfPjwCnMeZW3Pnj1o2bIlPDw83rueTqdj9XjVqlXDZ599hs2b+YGNleGh7IAhJSWFjYaLi/ncrXWWQkTIz8+HRqNBbm4uK6sAwJQGPD09ER8fD0dHR6SmprJ6PWtYqbi4GMnJyVi3bh0AsLDpvHnzUOzfDPKGvVAYf5eNdAtu2yLmjBnlpYSsZo1QGDNfl6N/Mma/ZRRl5vwsWPQ6yKs0QHHifVh0uSh6eZsPEz48z46dd/c31Pfji7MtFgsyMzMZahgAC+WWFdGlMiTfAM+faG0/dnZ2cHNzQ2xsLBQKBRo1aoSCggJERUUhJSUFixcvhkgkgkgksnGEP//8M0QiEYRCIftdJBJBpVKhR48e6N27N1Nij4qKQo8ePQDwZSFXr15lEPecnBy8fv0aIpGIyZE5OTkxBfWhQ4di5syZCAriC7SlUimkUilz0EKh8IPaXKXPx2RCYWFhpY6x7LLk5GQ8e/aswvXy8vJQWFjIymDKOkOZTIbc3FykpqaiqKiIlc4EBgbCzs4OV69exaZNm1C/fn2EhIRArVYjKCiIbT9hf0ylRfQVWdbZTSi49zvEzr4Q+9aB7skVpO6bA/euUyGp0hCmvAyYCrJAJW2CE0vhMXxdubppiZMPI1EQyNRwG/AtOKEYKbu+gD7psY0smyknFW82joTMuwYC6zZE5qPrSE9Pt1Fo+F/Zv8LxleUMLAt7t6vVCoWJD2AuzIFI6wq3HiuRfvRbmPPSIHENsGG1cOkxF7mXfkHB48tsxFLW/NzsEWepj4K7vEMSyO2gDu+DnEs8nF7qXg0cJ4Bzj7lIPTAfxpQXAMdBqHaCxL0aikoUFmReITCkvoQ57jYEYhnkVRow7k7nnvOR8sskVm4hUGrh8ulsSF390LOeFx7cvmGTL7GaXq+HVCpFREQEli5disBAnhjZyk7+9u1bCAQC9vHw8MDEiRNRuzbPz/kupVZCQgISEhLQokWL/xPH5+TkhAULFmDixIm4cOFCpWEhIsLGjRvLOfuK7PTp03j+/Dnc3d1x9+5dKBQK5viso+UePXrgwIEDcHJyQnR0NBsIWPXSpkyZgh9++AFdunSBUChE1apVcfv2bdjb26Nq1apISkpCWloaTCYTK0uoWrUqUlNTWe4qJCTERkbJqkZ+9+5dCAQC2NnZoSjpGSyeT1kJATgBvCZsh0CmwutVfUAmQ2mO1xqKLtNDWSMUimrhcP60lMzAXJANTqqA7qkVuEQQO/owAA3A55lNWUnQNO7FqLGcfQIRXieIkYOPHz8erVu3xpAhQ5iuYZcuXZCbm4ulS5dCKBQiLCwMGRkZWLBgAYRCIYqKijB79myo1Wrk5eUxp6HVatGmTRs2u/f390dxcTEjG7c6JoAHA1mXm81m9n/ZZQaDAW5ubnBwcMDjx4+h0+mQn5+PhQsXsoFNUlIS6tSpA7FYzGaIZ86cgZOTE/R6PSwWC65cuYKvvvqqQkebnp7OFObLLn93vXe/f+iyoqIiXLlyBa9fv0ZhYSHs7e3Ru3dv/P7778jOzkbnzp3x9u1bpKamYuvWrSwi8fDhQ7x+/RpCoRAWiwUhISFo2bIljhw5gsePH6NBgwaIiYnBvn37IBKJIJPJUFxcjPDwcAiFQri4uCArK4sfIFdtDIFEDt2zGxAq7eHw8XjI/epW+G6ZC3NQEHMW4ARw7bsEQqUW6RwH3eNLqC5MQ/SFrTBbCGIHbyZDBHCV1k1bSRTELn6wGPXIOrEChhR+4pJ1dhP0b2Ph+PEECORquA9bDY1HFewf1RhZL+6hZcuWiI6ORlZWFqMb/F/Yv8LxUSXDlooStxWxjXMcoNI6wqSxR34FTg8AQn2dYKjXD0XtJ9gs1zTpZfNdqNDAY8gPlZ5r1tlNEDt42izLu30cDm1GQaTUwGv8L+XOrWWQMxxVUrRo0QJEhGfPnmHEiBF48uQJpkyZglmzbJlcrHbs2DGcPXsWY8eOxePHjyutcbEWD69duxZXr17Fvn37Kj3/f8pGjx6Nn3/+Gfv377fhNyxrt2/zhNcfop9lRf7VqlULcrncBpFqndH98ccfAHjUaFkk2Ny5cxEdHc004U6ePIno6GjmkF1dXSGVStG+fXtcvnwZL1++ZLPI2rVr4+rVq4ygOC0tDRkZGSzUB/C5TWunXFxcDKSlAWoXHtQEAGRB1rnNMOWkMPSxoIS9X6TmkYjFr3lEJZkNUIa0QN71A9A9u460/fMg1LjAlJ2M4tcP4TlqE+SBDRgHpyH5KQzJ5Rk4BGXC9F/8uB3TuzaEUqmETqfDL7v348S1B+warQTiS5YsAcCDP6y8q4sXL8ahQ4eQmZmJlJQUFlI7ffo0AD4nvWTJEuh0OoSGhuLgwYOQSCTIyMjA9OnTbZCdVn7MnTt3Vvqcf/nlFyxbtgxSqRRyuRwKhQIpKSk4ePAg2rdvj549e+LXX3+FXq9nTlsikeDQoUMICAhAREQErl+/jsDAQBvnWvb/6tWr48SJE9BoNDAajZWuV9my962j0+mwcuVKZGRkwNHREbVq1UJaWhrevHnDZtCnTp2Cv78/fH19ce7cOZw4cYI9C6szA3i0clZWFhQKBXQ6Ha5fv84GxiaTCXZ2dgxsJRaLbYrai55HQuZbB2JnXxjePkXm6R9tVBls2kvGK8BiglDjygZREtcA6B5fwsvnT5FzpzwXsBUBn33xF+SV1D4DPIWeuQQNLxDLkHfrKHRPr0GocoS5IBOcWAr9G56LUyBVQOMRwAgV/nzMv0MajeZ/Bmqx2r/C8VVmAxv7obaXFusvvsCFp+nggPdSb53RPML0K+Uh2A4ODjj/60H4tZEi1bMZ9Kb/HP70bqExO0abisEdued+RkGaOybf3gWLxYI7d+4gOjoa3333HQwGA+vwK5KJISIcOXIEK1eu/MvCTiLCzz//jJUrV/4HV/X3TSgUYu3atejTpw86d+5cYUPeuHEjRo4c+UGipNZi5ZiYGPTt25c5MYDXAMzMzITRaGSoUesMxBriOnDgACNMDgwMRGxsLPr168douBISEjB48GAGBy8oKICjoyMGDRqElJQUnD9/Hjk5OSgoKEDHjrwYp9XxWQvtL168iLS0NCgc3SGt2RIiO2dkn/0ZIAuK4qKhbdoPxrQEkEnPZnWquu1RnHAP+pIwvKUwB8lbJkDqWxtk1EOfGgdKegROLIdAqsCbDSMAEEQOnjzvISeEIjgcsFige3oNylqtoQhsyCsAlOSiq7moMGrnbVjsvQHdUxTmZcNSUAx1WDfk3z4OgVSBfF0xxo3n9dqsvJdOTk54+vQpVq1axUpQoqL4sL51pms0GmE0GjF69GgsXbqUgU0KCgpsyAcAsO+//PJLpc85KCgIAoEAMTExEIlEcHd3x5w5c9C5c2dwHIf9+/dj+vTpOHDgAMxmM6pVq4bQ0FBGoF21alWcOHECrVu3ZrPCd42I4O/v/4+jmgE+bJyRkQF3d3e8ePGC5YyNRiOqVq2KvLw8zJ49Gx07dsTu3buxe/du5OXx4s5Pnz6Fr68vi0xUrVoVe/bswbhx4/DTTz9hwoQJiIuLw48//giLxYIlS5YgOjoaa9euxXfffYeJEydizpw5WLJkCcROPnDpuxim3FS83TAC5rx0mHW5sOgL+TxziSlDIhj1okBSSslmHZgVZGewyFlR/F2mxydU8WFjqVcIFCERNihOq/O0GIsZKl6g4FNRimpN4NCWT9XIxaU8wKmpqUxI+5tvvmHt6H9l/2rHBwC1vbTYMDAMmQV6HLqT9F7qLZcBA/Dll1+ykRcnkUPm6o+wQTNQLaQmUp/ewbPLe6Bs3Bs8PfT7jPj6vYQ7kASEwcLxt+pd0uD3mQgWZN86jt0VMJ9NnDgRV65cYbVSSUlJFcrEqNXqD+K1jIqKQkFBAVq2bPnB5/ffWtOmTdG6dWt8/fXXTFTTarm5uTh8+DBjYv8r69ixI3x9fZGYmIjff/8dPXv2hEajwdSpUzFp0iRkZmbi1KlTaNGiBZKSknDnzh2IRCLo9Xro9Xq0bt0aFy5cgNlsxtatW5koLgA2K2natCkcHBzYzLFZs2Zo1KgRDh8+jAULFmDhwoXw8PDA7du3MWbMGDbrqVKlig2SccOll1h19hn0JgtUtdui4P4fEKkceOo8kwGcRA6HdmMBAGQoglDjAiQ/47FXJaoZRc9uQFG9Obw/3wkQkHFyJUx56TDlpsGclwaZTy0U5KQCZAGZjBAq7CD1CkHhg/Nw6jQFIrUjlDVaoPDhefT5tDuE9h4ofvscnEQO92FrINa6AeBVQfLv/QGxgwcseenQxfEhYhcXFzg6OiIjIwNarZZFIwBe4mnIkCGYPXs26tSpU6Fcj5+fX6WRmveZvb090tPTcf36dTRu3Ljc73K5HOvWrWO5VautWrUKEokEU6dOxYULF/Dzzz8jMzMTLVu2ZIjRwMBAcBz3f1rOUDYyUbakSCwWsxnv5s2bcfDgQQwcOBCLFi3C559/Dn9/f6hUKsTFxbFyhLt372L37t0smrBu3TrEx8dDJBJBKpXiq6++YqHeefPmYfr06SyvLXENAMdxzIEBABmKYc7LsBmcS1wC2CDMYii2WRcA1A7OsE4lpF7VWb2zRV8IIqqwfEHiwtfHGtPi4dRxMgxp8Uw5pODeb7DoC+HSdRqGhAdgYGM/xMXFoV27dnj58iW+/vprjBs37r95BP+I/esdn9UcVVJWAF6Zubm5oWZEJyRra0EWUB8CAQcSiPHUDDx9kAqZyBt2TftDXpiM7JwcSNyDYDaZQGXUGixGPt/WurobxrUIhFJfGwt2ncWVQleQQPTBMGcxR6iS/wDSkBC8ePECRIT27dtj7NixaNKkCQCew/LBgwcwGAw2HQ/A5/2Cg4Pxyy+/fNAxN23ahBEjRnzQ7OqftGXLlqFmzZoYOnSoDVx79+7daNOmDdzc3D5oP6dPn0Z+fj4aN26MN2/eMMqqsgCFI0eOYM6cOXjy5AkCAgLw8ccfw9HREefOncONGzdQtWpVFBYWon379tDpdDb7V6lUqF69ug25cXFxMVODsHZiSUlJMBgMaNWqFVMk+Oijj5CUlISoqCiEhYVBlXIPiVtnwZDxGpxUydco5WfCmJ0MqWcQ7FsNZ4hhc0G2TacBsjCyA13sVSQ+4cNM7kNXQ+IawKuo56VBqLSHa9/FyLm6B/rXj0AWE0QaV9g1KR0EObQZBaFIjPxHF0ElORaBTI3ihHsQ1/0YAD/iV4ZE8OdSlA/95rEwF+YgPT0d6enpCA4OZiNxq3l6erIZ339iWVlZ7N6VNYVCgcOHD+Pbb7+t0OlVZs+ePcOSJUsQGRmJwMBA9OrFpyeSkpJY2cTXX38NoVCI1q1bw2AwIC0t7S9Faz/EzGYzU0vJy8tjYcpbt25hzZo1SE9PR2RkJO7evcvAQxqNBmq1Gjt27GDLYmNjERgYCK1Wy8BpeXl5OHXqFJu1JiQkoLCwEP3790dhYSFu3rwJg8EArVaLffv24datW9i6dStPqcfxjv3dnsFaMG5zDYXZgEDEzwoLsyFU2kNfQj2mVGtgEAmgN1kgEMugqvsx8qOOgYzFSN72OaQeQTblCwAgcavCSBTSjn8LkUILADwRu0ID3eNLKArtgF+ui2BKi8eaL4YhPT0d69evx9ixY//rZ/JP2P9vHF9GgR6HopMQm5KHvGIT7GQiBLvZoVf90hnfrsgEFDYaCbmFAE5QbkZnDZMa5W6QKd0gjv0Tb968gdY3BD6BwfB1d0aTkKro08CX7fP+a0AeUB/ip2kwleHkq8gEHCAUcGgd7IJxLQKRn2iP4Wd2oF27dujbty9iY2MZos3HxwdNmzaFVqvF6dOn0a1bNxsH99NPP6FGjRqIiIj4y3uTn5//t2ZX/6S5ublh9uzZ+Pzzz/HHH3+wMNrGjRsZe/z7zGg04ssvv8SxY8fw559/2minpaWl4fDhw/D392fyTDNnzkS7du2wYMECKJVKxluYk5MDf39/5OTkoFWrVjh/vpSiedKkSahbty6GDh2KqKgoVKtWDS1atECVKlVYCYmrqyvu3buH5cuXY/HixTh9+jSIiCm7V69eHWFhYfjjjz/wWd+ekKm1UFRtDGPGKxhSX0JZqw1TtC5rMt/aUNZshcKH56Fp1h/aZv0BAG+3fs6YWyqz9zFwSIUcLEo1IFODjHqIHLwg9QhC8asYZP2+FpxQzBRHjNlvkR99Eub8TJh1eRCpHXH01J8Iq+qB+fPno1GjRpg9ezbGjh3Ly3d5eqJmzZofNKNLSkrCF198gfPnzyMvLw+NGzfGjBkzKoxeWM1aQ/ghZjabMWTIEMyfP5+BvqyWkZGBPXv24Pbt2ygqKoKHhwcTaQ4LC4OLiwvCw8NRr149hgC1OrC8vLwK/393WVFREVQqFTQaDezs7KBSqaBQKJCTk4OpU6fCYrFALpfjo48+QlRUFDIzMzFy5Eg0b96crf/JJ58gKioKAQEBqFGjBvbu3cvCulbw2Y0bN5gywdy5c3Hp0iUGVtLpdJgyZQratm2LJk2aICEhAULBh9cZCpX2UNVqjYL7fyB172yInX2he3IVQrEE3Vo1wUEDjzDOvXGo1MlxAhgzXsOYlgCh2gEy/3pQBDdl+3TqOh1ZZzdB9/Q6jGYTBEoHyLxDUFQy8xNIlSjIy8G8USNg0etQs2ZNPH36FJMnTwbAszq9+zwrstWrV2PXrl148eIFDAYDgoODMW/ePHTt2vWDr78i+9c7vs0HTmJkny4QaVwQMPEX6G1yfClYdfYZWgQ5w99Rie03EmAkzoYaqiIjAgxmQBjyMQY0y8WOuSORWFAAt169MG58aeH3h7IiEBE4EOo6C7FhREsoBGbMmjULhw4dwpo1axhs22omkwkxMTG4du0azpw5g+HDh2PkyJEIDw9HeHg4atWqhW+++cam836f7d27Fy1btvzg2dU/bRMmTMDmzZtx7NgxfPLJJ7h58yYKCwvRqlWr92739u1b9O7dG1qtFrdv34aDgwOysrJw5MgR7N+/H1FRUejQoQMmTZrEVMOtlpubC0/PUpDRyZMnkZOTg8DAQJw9e7bSma9arcaePXvw448/Yvny5YwkwMfHB3Z2dhg0aBAWL16MAwcOYNmyZYwIYNCgQQDASiMCq1ZFIqfky2hSX6LwwTk4tBuDomeRbDQN8LOysmAAq5XNtwC8urpQoYWhpESmMuMAcBYT/N20iE3JZ9R+Us9gCKQKSFz8UZSXjvy7p5njM+Wk2oS/pD61cfhJHjp/VA8bN27ExIkT8cUXX2Dt2rVYtmwZ3N3dbeSJKjOz2YyOHTviwYMHaN68Oby9vbFv3z48fPgQeXl5UKvVuH//Pnr27Amz2fxBNHVEBJ1OxxzPTz/9hMLCQri5uWHbtm02jmnjxo0oKCiASqWCXC7Hy5cvGegpPz8fRqMRR48exaFDh5gDc3Nzg7+/PwIDA+Ho6Ahvb2/Y2dkxx1b2f41GA6WSl+gxGo34448/sGvXLjx+/BheXl4oKipCQUEBvL29sWjRIvTq1QuZmZmoX7++TWTh5MmTmDlzJs6cOYNnz54hNDQU8+bNY07Pyp4D8OCXLl262NAazpo1C/PnzwcALFiw4C/vYUVm32YUIBRB9+QKjFlvIfGoBmPGayyZ9xUCBi2FyWCx1aYskVQT2rlUCCgUKjRw7joDuuc3kXt9P4xZb6B7fhMiO2eoP/oMEhd/mHJSYdHzkZeHDx/alNh07979gxzfkSNHkJWVha5du+Lp06eIjIxEjx49cOvWLUac8J/Yv0aItiLbFZmA+bvOI/3mcQhkamib9atwvRK+lv/I5GIhmmafwZa1KyGVSjF//nxMmTIFh+6lYMnpJ39PedhsQMovk2HIeM1GyxcuXECLFi0q3WTt2rV48OAB5s6di+vXr+P69es4cOAAq3cJDw9H06ZNER4eDnd39wr30aBBAyxatAgdOnT4O5f+j9r58+cxbNgwPH78GOPHj0f16tXxxRdfVLr+xYsX0b9/f4wfPx7jxo3DiRMnsH//fly7dg3t2rVD79690alTp0qp2QYMGICOHTtiwABeYmXZsmWYOXMmOnTogNOnT9vMnu3t7VFUVITi4mI4OjqC4zj06dMHN2/eZJB6iUSCkSNHYuXKlYiIiEBkZCQAwN3dHampqUhMTETz5s3f23kra7YCWSzQPb7IlvnOPImMkytR+PA87Jr2A0eE/Hu/8eUO71LtlTGBTAUyGyF28IKmaV84hDQFAQj3luPXRcOQlZ4CkdqpXB1gWbNvPRJ5t0+AA+AxZjP0b58h/chiXiJJIEKLFhFY8+MPqFmzJgDg8OHDGDVqFEMgNmzYEN9++22lJAmPHj1CzZo1IZFIkJ+fD4vFgk8++QS///47Jk+ejC5duiAvLw/nzp3D9u3bWa519OjRlc648vLyIJFIYGdnB6FQiLdv30IkEkEgEMDNzQ2tWrWCl5cXlEolZs2aBSLCunXrUKdOHYwaNYpRzxmNRhv+Tr1ej8jISBYavX//Pho0aMDygw0aNCine0dEuHHjBnbt2oWDBw8iKCgIAwYMQK9evcrxhv5dMxqNuHXrFs6cOYOdO3ciISEBLVu2RPv27dG2bVvUrl37vWmLUTtv48zjVJt+z5SXgZzLO1D8qrQEzKnzVFYCpm3+GQofX4Ix4xVkVcJQ/LKklo7jAE4IiVsVaJv1hzygPsy6XCStHgBOqoD35H2wFBci6cf+ECg18J64C6a8dLxZPxQChQZeE3ch9+oenl4vKBycSGpTZqENrIfrX7aqVAbthx9+wJo1a/DmzRuo1WrUqFEDGzduRFBQECIjI5k+oRXsFBcXh++//x5Tp06tcH8fYv+TGd/NmzexbNkyXLt2DdnZ2XB0dETNmjUxduxYfPrppwCss60nMKtdK0VMWu2/8dzFJjPuveFfyE6dOuHWrVuo3uxjiNpPh9HyN2mLhBKYzSa4evsh9XUCiAirVq0CEaF58+YVJtzDwsKwbds2eHl5oXfv3ggPD8fWrVtRu3Zt3L17Fzdv3mRoOTs7O+YErTPDmJgYpKWloV27du89tfv372Py5MmIjIyEQqHAp59+ipUrV9roYv031qpVKzRq1AgLFy7E0aNHy4FdrEZEWL58OVauXIkhQ4awttCqVSt89tlnOHDgwAdBna2CpVazzv6eP39eLkTn4OBg47BevHiB27dvIyYmBvXr12cUcuvWrYOXlxcGDx7MHF9ycjLatGmD5ORkxMfHMxBD3759sW/fPoiVGkj86vGzvofnoazVplyOReISgEKcR9GzGzCmJ4ATim2YgYDSHF/S2sE8LFwohkftpsh4chPpR7/BwOY7MXt4T0wdPwqZb+IhVDlA4l6NOT5OIofPVB4olfhtZ/4eXdoBedVGEEgVIJMemb+uYLqAAqkCVy5fRsuWLXH//n2IRCIsXboUWVlZcHR0RFZWFiIjI9GqVStMnDgRUqm0nIOyEgYYDAZG82W999u3b2egmBs3bqB58+asRrdOnTqVzrLUajUkEgnevHkDX19fCIVCdOnSBQaDAadOnUJkZCTu3bsHqVSKtLQ0rFq1Chs3bkTVqlXx5MkTxsDzrhOz1slGRERg0aJFyM/Px+XLl3Hu3DmMGTMGCQkJaN68OVq3bg1/f3/cunULe/fuhUwmw4ABA3Dr1q0PkkmqzKxlTFaJrkuXLsHf3x/16tVDRkYG7ty5gzp16vzlfoqLi3H9+nW8OLETZt/OLIpgMRYjde8smLLfQuTgCVXNljBmvOIFmUss58puKIKbwpjxqtTp8ScHkAmGlBdIO7gQrgO+hcwrBGInHxgzXqHo5e0SQg6CpTCHp48sEfmWedewGWTqnl4vV2Zh//l2G5L+svbixQtMmTIFTk5OrO40MjISycnJCAoKKpcLtgKBvLy8PvjeV2j/Z7oPZaxfv37k6elJEomEZDIZk9cJDg5msjJarZY0Gg0pFApq2rINVZ1+wEbWQmjnwiQ/UEIgbt9mNAmUWuLkGnLsPJWcun9FQjtnEsjtSBsxmHxnniSnrjNIqHEtI43BkcjegxzajWVSGg4f9ScANHjwYCIi6v79afL94kSF8h3OPeaSyMGTUHINnFhK6rBu5PPFcfKdeZL8Zp6k0TujSKPREAAaOXIk1atXj1xcXGjs2LF0/vx5MplM7N7odDqSy+VUVFRERETDhg2jdu3aUWhoKJOJiYiIILPZTE+ePKHNmzfTsGHDKDg4mNRqNXl5eVFERAT9/vvvlJOTU+H9z8vLI2dnXrqpR48eVK9ePQJAffv2/Uef86tXr0ihUFCnTp0q/D0pKYnCwsLI3t6eVCoVdezYkbZv317peb/PwsPD6erVq+x7VlYWu+etWrWykUKRyWTk7e1NAMjDw4Ntc+nSJerRowdrfwCobdu2lJWVZSPDs2PHDho3bhwBYPJZ1jYMgCCSlpEc4sh72iFy6jKd1GFdSR3WlVShHYmTqmzaIACSetcqPcdqTYiTKUvXEYpJ4uRNVarx0kV9+vQhk8lEEomEAJBr/6XkO/MkSX1qs21UddqRonpz9t2xw+ck861NQjvncjJfYicfEirt2bXY2fGyXwKBgJycnNi7CoDc3Nxo2rRp1KJFC2rXrh117tyZvv32W4qOjqZOnTrZ7Nf6adu2LWVmZlJAQADt2rWL7t69y377ELNKWlWvXp0mTZpEkyZNYm34t99+Y8/Pz8+v9JrEYpozZw4JhcK/3Z5iYmJo4MCBTOZHoVBQu3btaOPGje+V0Xqfpaen0759+2j48OHk7e1NXl5eNHToUNqzZw+lpqZScXEx1alThzZt2lTpPsxmM0VHR9OyZcuobdu2pFKpyNXVlRwdHWn8D/soaO5pvp/rPpPvJ1UO5D3tEOuvfGYcI6EdL+OlCe9L3lMPkapuhwqfmdavBgEgZUgE+c48SapQ/hmow7pVuL61D/adeZI0TfuxduXz5a/kMWYzW8fr8900ed/dCq/v8ePHBIBq165Nf/zxB71+/ZqIyKaPtNrnn39OACg8PNxGhuo/sf8nji88PJz69+9PI0eOZBpharWajEYj+fr6ss6pa9eu5ODgQABIpHUngUJDnFTBv5Aqx3KOTyBTM301CMvrhXESOUl9apFAoWGdDSdRsG3sW4/k9dNKtlUqlTR95iyqNodvTI4dJ/MdlFcIqcO6vdN5cMSJpey7XeOezNECIGHJdV64cIGIiF68eEFLly5lTjA8PJzc3d1JKpWSUCikevXq0a+//kouLi6UnZ1NRESrVq1ijq8iS0xMJKVSSePHj6d69eqRQCAggUBAIpGIPD09aeHChWSxWNh+OnfuTES8tphMJiOBQPAfv9QVmcViYddmNZ1OR0eOHKF27dqRQCAgHx8f2rBhA2VmZv5XxwoJCaEHDx7YLLt06RLVqFHDRjMPAI0ZM4Zp0bm6uhIR0TfffFOuvQCgunXrEhFRz5492bKff/6ZhEIhcRxHy5YtI39/f1vH987Hffhapp9n/Vj1+so6PrFblTK/u1e6PwBUv359SklJKe1MJu7iB2I95/PLOI7XiFRo2ToeIzeQptmACjUsy36mTp1KBw4cqPR3f39/cnR0tFk2f/589syPHj1Kc+bMoVWrVtHUqVMJ4AdVbdu2pWnTphER/S3H9+jRI5JKpZWez5o1aygjI4MUCr5vuHLlCmVlZVGDBg34eykSfVAbys3NpW3btlGbNm1Iq9XSkCFD6OzZs2QymSghIYG2bNlC/fv3J1dXV/Lz86Phw4fTnj17KCUlpcL9FRUV0dmzZ+nLL7+kevXqkZ2dHXXu3Jl+/PFHevLkCVksFpv1p0yZQp9++mm55XFxcbRp0ybq1asXOTo6UlBQEI0fP562bt1KjRo1oq5du7LB4s4b8RQ89zeybzmU70f9Q8sN1q2Oz6XHXNLU71zhPVWpSgdmYkcv8pl+hJy7Tuf7xRotSepVg5S12pDEI4hUddqRpESz1H3YWhvHp6zRgnxnniSvyfvY/jzHbKFhv9yq9DksXLjQpn0FBQXZvNsmk4mGDx9OACgsLOwf0e17byu0WCz01VdfkZeXF0kkEnJ1daV27dpRRkYGpaWlsZGMWq2mRo0asZEYEdHgwYMJAH322WfUokULEovF5OrqanOz69WrRx4eHgTwopQPHjwgH9/SEZxA5cCEPSEQks/0ozaOD0IxKUJavPelBjgSKDQkVJXeWIGa/19eLZxkfnXZQ7Q6ZfumvfllwlIhT5HWvVQMFyCxky8p67QvdbIiKXlPPciEQsVSmY3jK2tnz55lx5PJZGRnZ0d2dnbUuHFjWrlyJVvvrxzftm3b2OyqadOmBPCzncaNG5OTkxMpFApycXFhs53hw4ezmWXdunUJAB09evRvNpnK7erVqxQYGEhVqlShefPm0YABA0ir1VJwcDCpVCrasGHDP3YsT09PNjq0WlxcHA0bNszmJYqPjyciokmTJhFQOqu3ivZOnTqVevXqRWq1mnUA1peudWtb58VxHNWuXZs6depUoeNT1mxNHmM2l48SfDqb375k4KRp1p91RsxZDl1NXp/vZt8VwR/xI/bpR2jmgsX07Nkz2xnfwO/Id+ZJkvnXY++HIiTCZjDmOWYLHzUZuJzNCMSuAYSSgV/nqSsoOzubsrKy6NatW7yz9PCgvLw8EovFZDKZSKfTUXJyMj148IA+/vhjCgwMpMOHD7POWq/Xs/uv0+koOJifobZv357atm3LRuYf6viMRiM1aNCAPvnkEwJAn376qc3vycnJpNPpKCoqir8esZiJ3g4aNKhSx5eeX0w/XXxBE/fcpo7fnqB6438k5+b9qOMnvenAgQM2IsbvmsVioYcPH9KPP/5IXbt2JY1GQzVr1qTPP/+cfvzxR1q8eDG1b9+eVCoVNW7cmObOnUuXL18mg8FQ6T5/++038vLyoszMTMrIyKADBw7QqFGjKCAggFxdXWnAgAG0bds2evXqFRERRUZGkpeXFy1cuJDMZrPNvu6/zqa2E60ixg42IsbeUw8woW6xgyd7NtZ+t7KPUKEhj+Z9+P/tXIgTScihw+dk1/ATPoLGCUggtyOfL3+1dXwlwrTe7zi+ymZ8JpOJze4SExPpyy+/JAA0bNgwIuIHE9268TPOtm3bUn5+fqX39O/Ye1vhmTNnCAD5+vrS2LFjqVevXuTu7k4vX76kxo0bEwAKDQ2lgQMHkkgkIoFAwMJPVsfHcRxTCK7o866yM+tQOAH/vaxqde+F74Q6R5FL38Xl91uyrUDOd2ZCjUuFx1bV70ouveaT1KeWzbE5sZTACUjiWZ3tTxPel0SO3u9tLG6DV5FAqiROJCGxXFmp4ys7vd+2bRu1b9+e7OzsiOM4GjlyJAuHVub41qxZQ5MmTSI3Nzfq168fERFTC9+yZQs9ePCADAYDGY1GSkxMpNq1+XCYp6cnKRQKCg8PZyG7ZcuW/SMNyWAwUOvWrSksLIxUKhXJZDJatmwZDRw4kIKCgujhw4f/yHGsplQq2UsQFxdHw4cPJ0dHR5o3bx5lZWX9peNr166dTfsrq1bu5OREb968ITc3t3LPWCAQ0FdffUVjxoxhyzRaB5I4+ZBI40pCjWs5x2ftFKztiRNJSKh2Luf4fGeeJJG9R0kblJOq7sekCm5KQrGUJBIJffzxx0yxm5PISV6lgU2kQ+YfSjL/0DLtcWWZDvDQO7NOUECNUJLL5XThwgUym83UpEkTAkC1atUimUxG7du3J61WS9u2bWP3/Y8//qDatWtTs2bNKDIykvr370+dOnWikSNHUmAgr0bv5+dH/v7+lJmZSenp6TR48GDq0qULO+7gwYPZc3jXvvnmG2rTpg0lJSWx8HO7du1o1KhR1Lp1axKJRBQfH08FBQUsOtS0aVMaNGgQe5ZyuZzt796rbBq5/RYFzjpJ/l8es3ku1eacompzTtOonVF071X2B7W7N2/e0NatW5mjk8vlJBKJqFq1ajRt2jQ6f/48G1xWZgkJCeTg4EB9+/alevXqkVqtpk6dOtGqVavowYMH5WaAmzdvJmdnZzpx4kSF+9Pr9bR27VoSiflBkUBpT8rABiR29CL/Zt2JEwhs2rZIJHpvxEIqldLq1avJYrGQm09pVMJj5E/k/Mks9l1erUm5Nl6R4wuYsI02XHpR4bnHx8eTi4sL9ezZk8aNG2czICUi6t+fT0PJZDIaN24cC3vv3r37g55XZfZex3f69GkCQK1bt6YLFy5QamoqWSwWunnzJu84VCoqKCggIqLJkycTANYRWx1f1apVeaflUrHzedcpiiSVhzjs2462cXxug1aSS68F5dYTlcwShWqnio9ZElYSO/lWfCyhmDixjFShnViH5fPFcZJXCSvt7Jr1J9+ZJ8l96OrSZRH8NSuCmpJErqrU8RGVn95zHEfTp08vFw4FQM2bN7fZNiIigm3n6+tLRPxsq3bt2qxBq1QqNnu0joQXLFhA+fn5dO7cOdapKxQKqlKlCn322Wf0008/UUxMTIXx9YrMaDTSmTNnaOTIkeTg4EBCoZC+/vprev36NbVp04Y8PDyoV69elJeX90H7+1AzGAwkEokoLi6ORowYQY6OjjR37lyb8OlfOb5Hjx5RQADfTiQSCRvIWWdUYrGYFAoFmwlyHMd+u3btGhERtWzZknUUCpWaZB7VSFX3Y5bbU4d1Ja9Je0lV92P+mYR2IrvwPnwIXySp0PFZ8yqcRE4QikmociCVY3kHbG3fLMcnELJO6N02av14jN5U+k5wAvLz96eRI0fS27dviYgoLS2NxowZQ76+vsRxHLm5uVH//v3pyZMnNvffZDLRli1byMPDg2rXrk2urq4sotOjRw9ycHCgmJgYIuI7tsre53ftwYMH5OTkRAkJCUREdP/+fercuTO5uLiQQqGg4OBgmjRpEhvwREZGUps2bcjBwYHkcjlVr16dlixZQvb29kREtGD/NfKbeYJ8S2YllX38vjpJwXN/o5034sudU0FBAZ06dYomT55MNWrUIHt7e+rZsydt3LiR4uLiiIiflZw7d45mzZpFjRo1IpVKRW3atKGlS5fSzZs3Sa/XU1RUFH3zzTfUqlUrEgqF5OnpyWaGZWfNZU2v19OYMWMoODiYYmNjy/2el5dHCxYsICcnJ4aVEJRxcmX/B0BTpkyhEydOkKOjI6nVajp27BjDEVg/Wq3W5liDh43g91Uyu/OauKu0P2498oMcn/+EbZSRX1zhNWZmZlLnzp3J3d2dxGIxOTs7U9++fVk4s2xfV/ZT2cDpQ+29js9kMtG4cePYyw+AGjRoQL/88gsBfOLZahs2bCAALL9jdXzWkXXZEfX7HF9lH4HKkbynHbZxfO5DV5PPF8cJAtt9W3N47CV/N/9nHe0I392O74wk7tVIZF8m5yIQklPXGTZOVuTgxce83QLZMol7EN8R+tQiQcm+27dvT4MHD7bpPN6d3ltHw5999hlb58WLFww4IBaLacyYMTbAmEmTJtHs2bPZ+tZwT05ODl28eJGkUn6WYDQaaeXKlQSAOnbsSET8CyOVSonjOHr27Bk9fPiQNm3aRIMHD6aqVauSRqOhdu3a0cKFC+nMmTM2jstkMtHFixdp7Nix5OLiQvXr16fvvvuO5s6dywY9p06dIkdHR1IoFKwT+yctOjqapFIpOTg40Jw5c/7jfOF3331XaXuTy+WVjoqPHTtGRKVt3Jrv2nkjnhybD7BZ13PMltJOoVYb1lHIqzYu13n4zjxJ6rCuNh2I78yTLD9iNptp/fr15O7uTqGf/0R+M0+S1Lc265is61sBLta8s+/Mk+Q97RAbuMmrNKARW6+999506tSJjh8//t51CgoKaOHCheTg4EAzZsygZ8+ekY+PDx08eJC2bdtGQOVh+nfNYDBQ/fr13wv0+BC7d+8eafxrk/+4TSwM96Gf4Lmnafu1OLp16xYtWbKEWrRoQSqViiIiImjx4sV08+bNDxoUZmdn04YNG6hly5YskqNWqykiIoJ69uxJoaGh7w2DEhG9ffuWwsPDqUuXLnTz5k06duwYrVixgsaMGUMtW7Zks11r/ymXyykwMJAcHR1p5syZFBwczAZqrVq1ouLiYrp//z45OTmRRqOhkydPEhE/g7VGSpRKZbnUx84b8eT/1Yffw4oGFaN3Rv3Hz/P/yt5bzmA2m7F27VqsWbMG8fHxWLRoEXbs2MFT5gB4/fo1dDodFAoFIxX29fW12UdwcDC8vb2xa9cumEwmeHp62hTHWomFrWbv6Y/sN/EAAJl/KMigh/7NY1gKMvH6+x5w6PC57UmSBRBJAEOpajqZ9DarqOu0R8HDcyBDiSRQCeSaE0lBZhOESnuYC7NBjHBVC/fBK5F3+1dkn90IWMzIubwTnmM2M9Z8U85bmAuzIbIrrefhWfQ56F89YMusvJBDhgxBcHAwzGYz+vTpgyNHjoCIUKdOHca4YoXqXr16FZs3b2ZwcY1Gg1u3buHEiRMwmUzo2rUrDhw4gOjoUkX5Ll26wGw2o0qVKsjNzYVer4ejoyOEQiFGjBiBJUuW4PTp0+jRowfi4+Oh1+vRu3dvVK1aFQBQo0YNjBw5EgDPyH/jxg1cu3YNCxcuxN27d+Hh4QGZTIbXr1/Dzc2NF2S9dg2BgYEgIoSEhGDdunWYN28etm7dypQlZsyY8Y+pwd+LfYkvfjqMh0nZcPxkNrp2aAtPX2eQRPkf7c9aAqFUKqHRaODk5ISHDx/C19cXXbp0werVq+Hs7IwHDx7A3t4erq6uyMnJYZB9a3mKtQ0PbOyH2rvXYv3FybjwNB1GswUWAiQuPAzekPyM35YsTNrF+tv7zCpiLBAI4O7uDjc3N2T+sR5ZMg8mjSSQyNn6xhJpGasyhLkoH+mHFkL/JhbKmq3g1W0qJrYNee8xPTw8/rKIXalUYt68eRg5ciSqVauG5cuXo379+ujatSv27Nnzl9dVltrs1q1bSE9Px8OHD7Fo0SLMmzfvL7e3Wm5uLnYeOIqtF58gTeoOTa+vYREIy9F5/ZUVGS2Ye+Qu5Nc34uOG1TFjxgw0b97cprxm7969WL9+PWJjY1FYWIiAgABMnToVnTt3xvnz53H27FmcPXsWRqMRbdq0wdChQ1GrVi08fvwYhw4dwpEjR+Dk5IShQ4eidevWqFatGr7//nvcvHkT6enpkMvlsLe3R3JyMuRyOYqLi/Hs2TMEBgbCz88PmZmZePDgAVQqFfLy8iCXy9G+fXtcuHABn3zyCdRqNb777jvodDoQEVasWIFp06bh/v37aNu2LSwWC9avX49OnToBAKZMmYIxY8Zg4cKF+Oqrrxh5tMViwYmr97Hg9yRYSGCryl5cAKFcDbGzL9ShHaEICgcA6N88QfalHTCkvgTHCSCv0gAeHcZiXItALFq0CFlZWeXu+bx58/4n8kTvdXzXr1/HkCFD0KRJEzg4OODaNV6TTqvVolGjRrh58yY++ugjGxqedwlIOY7D5s2bUbNmTUyZMgWBgYHYt28fZsyYgcjISBARPD09ERgYiKioKGS/iYfMszqM+RkoTnwAWEqckVwNRfBHkHqW8kEKpErok55AKFNBWiUMuiel8hr2bUajIOZPmPMzYEh9Wa7YV+IZDPsWQ5D5+1qYc9MgD2wIkdYd+bePQ//6Ad5unwpTRun6FkMxyGIucbJFgIVnNjCmJ1ovFCCCsnYbOHWchJZBzpjcuhrqeGtt7sfhw4dx+PBhiMViiMRixDx4wFhh9u/fj/3795d7DhkZGcjIyEBERAS2bNnCCnebNm2KTz/9FL1790bz5s2xe/duREZGguM4NGjQAEuXLgXHcVCr1Thz5gymTJmC06dPQy6XY9iwYVi1alWFz93Z2RldunSBm5sbTCYTEhISYDQaERAQAHd3d8TExGDdunW4e/cuwsPDoVAoYDKZsHTpUphMJkRHR8PV1ZWJaJ47dw6tW7f+INq5iuyP27GYu/cqUgWOECmCIanGO5zfnmTiwvNsxt4zLiKw3P2uyF69eoUNGzZg8+bNkEgkKCwshE6nQ1paGmrVqoVnz54xFpz09HRMmTIFcXFxjGPRat7e3gCAXbt2ITc3F927d0fLli0Zqfq0Q/dx+Vk65NUaQ+ToBWPGK6TtnwcyG2HOS4fEvRpkvrymou7ZDeieRcJQwvqiT3qMjJOroPKtgeAygz03NzckJiYiOzsbEnkchAoNzAVZMOWlI7WEWd+YFgdOLIUiiKeYSj+0CPo3sRDIVJAoVPB7fhhbV5zBxx9/jI8//rjCe+Tp6Ym3b9/+5b0E+CJ/ay2XQCBAzZo10b59+7/cLi8vrxy12erVq+Hr6/uXjs9gMOC3337DhoO/4b7RFVK/euB8PoLob7s7W+PEUoSP+ho/DGmIjAI9dkUnITblOWuvN7cfQsLLOLRu3RrPnj3D3bt3MXz4cCgUCrRp0wZt2rTBtGnTEBwcbFPf5u3tjXnz5mHMmDFQqVS4fv06vvzyS2RkZICIIBKJoNFokJOTg7y8PISEhODkyZPw9vaG0WjEzz//jO+++w729vZMw7B///64c+cOcnJysGfPHixYsAAvXrxAYWEhVCoVrly5wkjG27VrB4FAgIULF6J/f5427/fff8ft27eZmoZMJkN2dja6d++OqKgoaDpNhySgAXTPriLj+HcAWZgqOxmKoH/7FIWPL0IRFA5jTgpS988DGYqhqP4RLEV5KHx0AXK1BbWX90LXrVuRmFhenHny5Mn/Psfn6emJqlWr4ty5c8jJyYGTkxPGjBmDMWPGoF+/fu+l4XmfNWvWDEuXLkXLli3h6+vLZpAxMTGY8eVXOHflOiyGIojs3XjG8fwM2LcYClUdvki7bIEwWUwQO3igOPE+IBBBqLCDvGojqOt+DLuwLsi5shu51/aWOwdLYS5k3jXhPWoDX79ZslwZ0hwZp1bBaKWd4jgAHCy6HORc3gnfqQdRlHAP6UeWlDCc87wxIkcfmDISoQxpAQC4+DQdkXFZTJbDas+e8fv1bdgWXIvx0Ov1yL//B0zZvKCnSMChMP4eDOmJaNQ0ApFXL5Y7d6vApVUfbfr06UhKSrJxgu8Wy4eGhjLdvsqMiHDv3j3s378fBw4cgEgkQp8+ffDbb78xdg/regkJCbh+/TquXbuGnTt3oqCgAMXFxejXrx9u3ryJJk2awNnZGatWrcLUxT+g0VsNLj3jeQAro51713G9evUKY77fjUfiIHASN3Dg8C7XiZV/9c/Hqbj8LKPc/S57zmfPnsW6detw+fJl1KxZE0qlEnZ2dsjMzIROp4NAIEB+fj4GDhyIIUOGoLCwEOvXr8eZM2cwZ84cpKSk2Ly8I0eOxJkzZ3D79m2sXr0a3t7eTB3DUSXFip510HTZeVgIcOm1ANlnNqL41QOA46AICod9m9FsX4bUOBvKKFNOMkw5yRAKOPSsxxfrpqSkYNq0aYiIiMCOHTugUqnw6YjJOLrlRyiCmoITiaF7eg0iRy+ewFrFy/KY8nmiZEtxAbJvncAft4A/wA9gK3N8Hh4euHHjRoW/vWtOTk6MlcUqa2TVlcvNzcXnU2dg88+bIBBLUb/XRIS26oxgNzvsnDMUAODi4gKdToeCggIMHToUa9aswYwZM3DkyBGkpqYiMDAQ06ZNw4ABA3Dt2jVMnjwZd+7cgdazCkz2Pih8uh1CpT00zfpDF3sVxYn3QRwHkUIDMptg0RdC4uwHob07jGnxMOWmAgAkzv7QRgyCzLsGuxaLsRiHNy7HnmnXYcjPhMTRC3bhfaGoxhPLm9yaQlqzHy4lxsDHzQJ39xQkJyeD4zj88ccfiIqKwrlz5xAWFoaEhAS8ePECT548YdGbDRs2QKPRoEmTJtizZw+USiWysrLw+PFjrFmzhs2KXrx4gXv37uHAgQP48ccfGUVaSkoK+vTpA4vFggsXLuD7779HRkYG+vTpA4AndmjcuDHOnTsHhUKBO3fuoEOHDpDL5Rg1ahQjiS4qKsL48eOxbt06pmICAMUkRrKmBlQfN4UkIAxkNiDr93UAWaCo3hxOXaaVU2UHgOKXt0GGIkh9asG52xcgsiDpx/6IibyE6Oho1sf/W+xfSVk2audtnHmSiuRdM6F//dDmN/cR61H48Dx0sddgLsxilE7WhkkWM/KijqEg5gzMeekQ2blA3aAb1CVs9VZHqKzZGl7dp8JkAUyW0ltQEHMWmad/qPC8OLEMXhN3QiCRIz/6JPKijsGUk2L9FSJHT3iM+AlkMiDjxHIUJ9xjgo5Dhw7F48ePmQCo1Rw7Toaqdhv2ncxGvPlpOMwFWfDsPR/fThnCOvJ3VRoGDx7MRmsvX77EwYMHcfDgwb90gmWNiPDw4UMcOHAA+/fvh8lkQu/evdGnTx/UrVv3vcoQVMLCMnPmTGzcuBH+/v64du0arl+/jsjISLi5ucGn9UDEaer8pQwUxwEyEa/fFeEpxNKlS3EkJg3KjwbBjA+XmJGLBZjdsTq7Z7m5ufjll1+wdOlSpKamws7ODhzHoXPnzujSpQsWLVqEZs2aYc2aNf8nGmHWtvyfvGUcgPY1XLFhYBhu376NTz/9FMOHD8fcuXMZnZVVTqlas04wfzQGRqMBnKh09vyuZmVtL+0HHfv06dP48ccfWai+Mrt58yZatWoFjuNQWFiIHj16wMvLC25ubvjqq68AcJC4BUIkV0EXf5d/hybsgEKpwqsdX6KoJC3g5eWFpKQkjBgxArm5uTh48CCqVq2KZs2aYd++fSgqKoKjoyPc3d3h6uqKc+f4QYLMtw4sxmIY3j5laQipX10Y3j4DGXTgJHLIAxui6MUtkKEIIntPSL1DYEh+BmN6IjiJHB4jN0Ck5vXn0o9/B92Ty5C4VoHYyQdFcdGwFOXDtd8SNjvnnw1BCMLb9UNQlJdlE/YmIoSFhWHkyJEIDAzE7NmzERkZiZYtW6Jq1ap4+fIlRCIRfv/9dwA8Z22PHj3g4eGBZs2aYerUqVAqlTAYDDCbzRCJRDAYDGjSpAnatWuHtWvXYuTIkRg6dCg+//xzvHjxAomJiTCbzViwYAGbLUdHR6Njx47QarXo3LkzVqxYwd7nOXPm4NmzZ3BxcQHHcWjffxROvNDj0rN0XngXJfJZZTT6PEb+BLGjd4XtIP/+n8j6bTVEGle4DfoeZl0OUn6ZDDKbsGXLlr9FTP7/wv6VJNXjWwTiyvMMKIKbwpSTDHN+JoR2zhDI1Eg7sADmvDQIFBoI7ZxhyktH+pFvWMPMubwTeZGHIHLwgiKoWYVs9QCvotC8mjMuPcuwcXyq2m1Q8OAs9K8fwrHTFLbN61V9YNEXwpSdDGPma2Sd2cCrYIskgMkAgKCu14mnbTKbYEh9CSpDS7Vt2zabaxQ7ekPmHwqxk21DKnxyBeaCLIjs3SH0r48lp/n8X9lZjFarLScbU6VKFcycORMzZ85kTvB9M8HY2FgWWi0oKEDv3r2xe/duhIWFfZAMUmFhIUaNGoULFy6ga9euLD/Ypg3vxM1mM1Yci8TP0Vkw019LJREBRUYz5h27D93VnejSrC60LbvYCA9/iBUZLVhyOhaK4gz8uW8z9u/fb0OG6+TkhMjISERHR2Pw4MFYtGgRRo8e/Z492tqpU6ewaNEiPHr0CEqlEn369MF3333HCLT37t2LlStX4v79+zAajejSsx9k1QehyFg5L2dlRiY9sq7uw5To3Vi/fj1UKhW+/vprLF26FIGBgTbSP02qOOH7WW2x92Y81u48ihydHkH+3vi0WWMMbBr43lByRfYhoc7k5GT07NkT+/btw8SJE1FYWIgJEyagRYsWGDV3BQCec9Rt4DKAE+DVik9BxmIYs94gJ82A4pKoikjrBs/gukhKSgLHcUyjMj8/H9u3b2c5VXd3dzx48ABjpszEuXPnyomxwmKGyNEb2uafIXXHNAAcyFCE4vi7LL+vCGoC+xZDYDEUIWnNZyBDEVJ2TINZlwOBXAtLQQbACSD1rA4IBPwHhNS9swAAnEgCkdYN6nqdQSY9ivKyoHV2w/VL5xEUFIRevXrhyJEjiI+Px+PHj9GlSxdG3da2bVt8/PHHqF69Ot68eYNevXrh6tWrSElJgVqtZqK8AK+JWFxcjCdPniAwMBBVqlTBmTNncOvWLTRu3BiJiYlo1KgRAgICEBcXB5lMhqtXr6JRo0YAgNu3b6NTp05wd3dHvXr1bJzekydPsGHDBsTExKB79+54anbGCekzcEJJyfWWvq9mXQ77X6RxBVCxKrsyuBnyIg/BlP0WSWsG2rSTlJQU/NvsX+n46nhrMbtjMJagGz+zy8/ktaTK6EJZdLmw6HIh9a4J/euHyPzzJ5BBB3NJWIcMRRCJJRA7esOcl47M39fwzkrKAyHCqzgiKbsYadcPQ/f4EoxZb0EmPSTOfoxNnyvDps9JZIC+EObCbOSWPHSHduOQe30fjGk8GEcXew129btAIFPCa9w2WIoL8PqHvgCAgAFfAw5eeLVrDkzZb2DMfguxsy9Edi7sGFmXdiD/5mEAgCk7Ga+WfwqJqz8WFn5tM1Jv1aoVjhw5Uun9e9cJrl69Gl27dkVBQQGEQiEUCgXkcjn69u2LzZs3o3Hjxn9Lx+/p06fo0aMH6tevD5VKhenTp5db5+HbfPxyPx+mCpwemU0w52ci6+ymkhC1AHL/enBoMxpQ2UPbcjiuRe9HXPTW94al2P4sZhZ+AYAigxGfbzwFz7i7APiwXfPmzbFy5Uqm4JCXlwdXV1e8fPkSej2vwfhXduPGDXTr1g0ikQh9+/bFkydPsGbNGhiNRvz0008AwJTFAwMD8eTJEzgoJXxb/puE53KxAFPaVceaz+fj0KNHICIWBjObzXj06BHmzZtnI1LsqJJiQutgDG38OWrWrAlxVhUs3T4b0gULMGLECIhEIvj5+SExMfEvydP/Ctyi1+vRo0cPjBo1Cl26dMHEiRPZb7siE/BrDO80xU7e4ET8TJqTyEB6HcwFWcg8uRJkLAGhiSS4eY4X/S0repuWlgaJRMKUC6wAuqgE/j4YM17h1bIuEKhLAWZiJ58y/QTvMC1Feex3U3aJMycCmXnhWHNRPpTVm0P3LLLkNwvy71QuOG3MeIWsP9fzp651g9G5Gjp06Y6MlDcsxJuZmYkff/wRT548wZAhQxATE4O5c+di1qxZkEql6NatG44ePQqAVwzJz89n3zUaDe7evQuhUAipVIo3b94gOTkZu3btQq1atTBkyBCcPn0ahYWFuHPnDjQaDebNmwd7e3sQEW7duoUuXbow5YlmzZph7ty5cHJyQkZGBrZt2wYfHx8MGjQI8UJPaJoPtOnrypqwRGsPAEx56RA7eFaoyi6QKuA+bDUKH12EKTcVYkdvFMScgf7VAzg7O1d6L/9n9v8YRfq3bOeNeJL78sXljh0nk9vgle8teXBwqbjeCQAJhEIKbtiCRKISerJqTcj3yxMldGYl5QximQ07i2OnKQyWy0n5Ohm3watYgbzn2K0kdvEv3V6qtIHy2rIXbCKxk0/p+ZRQS0k8gsocQ2WzL+v/rp+toAZLzrDvVkYRkUhEAwYMYHVA9+/fp0aNGpFWqyWRSERubm7Ut29fVuNT9iOVSmnMmDHk7s6XbURF8ZDj48ePU4MGDUitVpOPjw9NnTqVCgsL2TM5ePAgOTs706ZNm+jcuXMUEhJChw8fZoXrPj4+NG7cOBr003ny/eKYTfmJQ/txJFQ5kMS7JrsXnEhSjqzAvtVwEtq5kNjZj5S125LY2Zf9Lg9qRgBIVfdjkvnVJQhE5NrvG/KZcYy0EYNI5OBFnFhKIgdPatGmPavjs8LrAb5W6ZNPPmElNlKplNzd3Wno0KGUkZFRaXucPp2ncBoyZAgR8bB1lJSbJCcn26z7bt2glVrKrxJouNuQH0jqFUKcRE6cWEYefoEUEhJCLVu2pD59eAaN4OBgMplMH0Q5d/XqVXJzc6Nz585RixYtqGbNmvTnn38yisDK6kuJSmsga3cbSWpnT5IoVBTesSe9TssmIp7JxErzZX3mVq7PTXuPU9CsEyT1rsH2I1Q7kTywIWvTZds2ABLZe5DYxY9/v3wDy7XVsp92HbvYkFoAIJR5Zzmpqkz5EseOD/D1u5zcjiAQ2dAP2rccRm6fLbfZp5XH1KH9eBK7VWXLxc5+rBxKZO9BXhN28m3II4h8Qpux36w1dD4+PlS9enVSqVTUuXNn+vPPP8nVle+n3NuNILV3EAlkqtISq5KPnZ0d1atXz6YM7LPPPiN7e3sKDQ1lZQxBQUFUt25dcnZ2tilMFwgEJJPJKCwsjHx8+HctIiKCPvnkE/L29qbdu3fTzG9+IEXVRnxfJBCRUGlPMr+65PzJrNLymoaf2JybQ8dJ5eqXpV4hrBRM6l2Trxkd+RNfLsZx9OJFxcXr/0v7Vzs+IqKwxjwVl2uXKVRlyl7+ZgtF5PX5bgr46iT5f3WSAgcuJABULbQJ42m8f/8+RUZG8p2kSkVdu3YlsbMvCZS8wxE7+ZZSRHECUtfrTOqwriT1rlnqnGQqgkBoQ3KtqFlKgCx2CSjXYH2mH6nQ8Tm0H1/i8HhHq6zZitFWufb7hnxnnuRfKoCEds7k3GsBo5Zy6v6VTWGy9RqtL9fcuXOpWbNmpFAoSCAQkEajIT8/v3KsOO9+rAS/QqGQxowZwwrdOY4jpVLJSAeGDBlCiYmJ5OnpSQKBgIRCITk5OZGvry8NGTKEdf5l980JxST1qVWOW1VZuy3Jg5rarCur0tCmptK+9UhyHfBdGdaRg6yjKkvsLPWuScpabchtyA9k1+hT/hhyOxu+ShcXF1q/fj0tX853bM7OzqTT6ejBgwfs/mk0GlYo27Jly3LMGVabM2cOAaAmTZpQbm4u/fnnn+w4586ds1n3XcdHxFNLjd4ZRdXmnKagEj5YVtfnFUIAyL9BK2rX5ROSy+UUEhJCBoOBPRcfHx9q0aIFvX79+oMo56ZPn049evQgs9lMR48epSpVqpBcLq/U8d17lU0jd0SVPi+FlpS12rA2a9/oExq1M4r6jZpMAF/sP2jQIKpRo9TJuVatQzLfOqX7UDmQvGpjnldXWn4ABvB1srKSGkOFtmLSidJPBbWVgoprhFlbLOsoOaHNYBcA2bcdw+oq2XmX9BOcSMr4gt/9yALqkzqsKymCm5EqtANxYmk5YgKlUklOTmWuqUx/IbL3rIBHtfR3gUBAYrGYvVsCgYAxLgmFQho9ejRt2bKFjh07RleuXKE9e/aQvb091a5dm+zt7cne3p6Cg4PZoEQmk5FCoaCbN2/SgQMHiCs5tsjRi5S125IiuBkJ7ZxJERTO2qXUpzYbeAL8IEJV92OSBdRnyySuVUhSMjgQKDSkrNmaBCXPOuKTgf9Jt/9/bv/KUGdZU0r5U5zTsTrEIQ3w7dU2SIg6i5Qd06DwD4VJl4fipEcQu1XFi0f3YDHwYZH69eujaVMezl1QUIATJ07Y7NeYkQhdLF+eUVlow1LMw9fNJeE2gJ/SW0sXjGnxgFAImK01hBz0yc8rDMcZM14BAIQqB1h0uQA4SFwDUJSXBkNaPB8yyXgFgIO5KA/pBxewba2hIqsFhTbG/RsX4e/vj5cvX2Lz5s1ITk5G3bp1kZiYiJycHHAch5CQENy/f7/Se2tFWk2ZMgWZmZnYsWMHAEAul0MsFjMkmlViJisrC4GBgZBKpUhMTERGRgaTmhk3bpwNNN2qJVfWnLrPhNyvDnKu7EbRU/7eS31qwbXXPKQd+hpFL0qBPzLvEORc3QtLcT7IbAKZ+BpHTsyHJKXeNeE24Fv+WERI3T2z5P7aw5ieCIlHMAxvY5GdnY2TJ0/i6tWrAICQkBDI5XL89NNPrP5Oq9Wibt26iIyMxIULF/D06VMkJCQw8AEAVq+2YcMG3LhxAxqNxubavjsaiV2v1axEo7iCnF5tLy0rdTh0JwmxyfnIKzbCTibGseNiJADo1rQ2tm/fjpUrV2LkyJEQCoVITeXb34QJE2A0GlG/fn0GAa8sf5KUlITk5GQcP34cMpkMVapUwfbt29GlSxcUFRVh9erVqFWrFmQyGRYsWIAdew8gPS0NIvtSzUfHjydAaOcE/dunsOhykX3zKLa9jGY5t1mzZiE0NBQxMTFsm9Tntu1NqNDCsdNkCCRyvP6xf4XnCouZlQXpcjIqXocZsf84sYwHj1lM71kfpfW7QjFgNsKiyy3dFryIb15JioGZFblo0gPm0nA9J1WASsRVi+OiURxXWksrkKnh0H4sD/0vManGBRlv48ucDJWAcCwwF2RA5heK4rgyEkFlrq/bNwchlStwdP5gICcNzs7OePPmDYKDg3Ht2jWbMoAbN25g0qRJ6NatG27fvo0XL15Aq9XiwoULrLTEGjIeMWIEkpLegCzm9yI1AcCt/zcAgDcbR8KUnQxLUQEKYs5CqNQwVXZ1nfbIizoOQ8pzWIoKUPj4EkQaZzg07Y2Dv6x777P5X9m/3vFZTSUTQyQRQtJqHDQiLQpjryEv5iyEcjWk7kGwa9wTUs8gGDPfIOPXFTCmvsSVks5OKBJB22kaVNU/silvECq1KFkBXuO3Q6jgO7P8mLPIOv0DIORvj0CmAiwWWIrywHEC/qUxFAGgMk4PAAj6pMcgYzGK4qJBJiP7xapfxQlKb7lVhducn4G0w4vBa7RxEDv5gQOxmq70I0vAiUudX3whvw9rzic5mS+FePz4MSuCz8nJKQeAAfikubWkwmqjRo2yERvV6XTQ6XSlV0WE8PBweHp64tSpUzbbpqfz+ZSyABKp0g76wjwogsJ5+H6JFT27AYlrAMwlmnAAGEpMIC2FVFuNR+amse+K4GYMsVi2ntOiy2WdGEruryKwAQxvY2E0GhEVFYXRo0dj+fLlbJs7d+6w/xMTE22ctlWvr+yyyZMnw8/PD7Gxsdi7dy/uPY1HosANl3augjE7GXfTLYiN5c9VJkpB6m2+BjSr0FDuuhxV0nLaZD0816J379744YcfAAAzZsxAUVERpkyZAldXHlSg0+kwf/58tGnThj0vjUaDixcv2pQG6XQ6tGrVCs+fP4ePjw/S0tKgVCqRkZEBOzs7ZGdnw2w2o3r16vD09MS9e/cgdvCAIrgZdLFXSp+NkzcyT/8IU5n6V06qYPWt0XFpWLCgG5ycnCCTyVjHqqjREjCbUPTiFoxpcUj6oR9kfnXhNX47Xq8szUmWtbL5+/cZJxKz94o9878wgVwDS1EuYC59H8tuW5xwj+X1reYxdDWSVg8oWbk0NysQy2EucXyaiMGQulVB2v75AAgStyrIPvtzyYkK+AF1MZ/HFMjUsBTzJR/qsK7Iv3UUZDSgOPEe27fYtQqMqS8h9awO1wHf4k6OEHl/HoI+Jw0irTtMDftjoL8U21d9bZOT37p1K8aOHQuxWIzt27fDw8MD3377Lb7++msmKiyRSGA0GmFvb4+XL1+y99tckAljZhIkzr4lpy2ExMmn/H0vyQE6tBtjg0J/16Re1eE24FtwHNA+xBXOduXf63+DfTii4W/YL7/8Ao7j3ps8/1C7ePEiX+AZ3AJLTj+BnpNAGzEEnqN/hu+Mo/CasAN2Dboh48RyZJxYgfw7J9mIzKn1cFSpGQqzyYS86/uQ+ftaGNLigZIiV4FMBUXwR4DZhJQd05D5+1qkH12K7DMbAPBQad8Zx+A9cRdkfnXZOVlZMjiJAsqarRlgBgAkboHQv4lF/u0TKLj3G1tuKAHAiOzd4TvzJJw6T2Gz0+KkJzCmxUGocQUnksCY/JQ5PYBPoEtcAth3XQlbR3Y270CUSiWkUilzemKxGCtWrKhQDNaqWG41FxcXZGZmIiOj8pG2UqnE5s2byzk9oJRt5ssvv2TL9IX8Cy7SuMCQGseWW5+NUGnPllnBBhZ9qaO1msfI9ZBXCQMAyKs0gFPnaew3Tihm/wsUGvZiqmq3hdjZDzmXd7Lf+/bti5CQUqaS06dP4/ZtfpT96aefgviQP4gIcXFx6Ny5MxYsWGCz3M/PD0QEjUYDbVhnXLNviwcZJhizk8GJZZB6BLH9F5ssMJcghS89S8euyISKb2yJFRUVYd26dXB3d8fDhw/h6uqKgoICfPHFFzCZTKhbty4Ant0EAKpXr84Qel999RUDfZS9vufPn8Pd3R1PnjzBF198AVdXV3To0IGtM2zMeAxespWBSVz6LIZTp8nQNh/E1sm//wcMKS9K77lIArf+37JBx6l9vwDgCRasTg8AdI8uwLHTJDi0Hw9FjZYQ2jmhOOEudM+us3UcPh5vc86c9K/Zd1xdXW0Gkx9q1npGTlqxwHF+9ElwwtIBqdDO2QYsVdbMBZll/s8qEXrlnzXvQEsGdSXOkkragdXpAUDBnVPgZKp3okWAMfUlJG5V4dxrPjiBEDlX9yD7/BaItG5w7bcE6hotcVvzEfbcesW2uXr1KiZPngwigtlsRpcuXZCWlobly5dj9uzZCA8Px759++Dv7489e/YgKysLRmPpPdS/foS0A/PwdtvnSPy2M/tknd2ErLOb/vLeVmYykRDjWgT+9Yr/K/sn4qXvJszfx9OHkrjwsmXLyM/PjzQaDS1btowuX75M1apVI41GQxMnTrTZZsHyNSR18SdOLCORvTtpmw9iwq9WzTxOLCuNr3MCUgQ1JbvGPXmwgETO532EYl6U06rH12o4iZx8yyW7bcitBUISKO1L8wScLfErwNksE7sGlhP9rOgjcvIt3Y4TEDgBufReWC6fIJCpyXvaEZ6TtJJ92dvb07Rp08otr4gH9V2dM4lEYpMHsH5kMhnJZDKyt7cnrVbLyMZVKhUpFAqWZ7T+tfICsu39QsvpJzKZnjIM7wBIFtioXI7Pa9JeknryEjfKmq3Y835X584qvWPXsCTHp3IgVe12xMlKyaUBMG5DFxcXEolEpNFoSCgUklAopO7du9OIESOoadOmxHFcpe08Pz+f7J3dyK52a14CqKS9aVsOs5EgUtZsTeISJQ+R1p3sareh4V8trXCfr1+/prCwMHJzc6OIiAgaOXIk05mzs7Mji8VCeXl5jND8008/pdBQXoGhd+/etH//fibAayUst3KQtmvXjoh4suPQ0FDavHkzuXvx5+U18FvyHrqK5bGs5+/Se6Ftm+EENnknCMWkqt3uL9u3UONKQo0t2My5x9zSZ26VU7K2Q/dq5PPlife+O+/mkcsC0ezC+1S6nVWl5UM/9m3HkqJGi4rPwaWKTU5RFdqRPMduJUEJGEag0JC21fD37J+/l7KAsHJcwewd9a9XSlYukvKgO6WW9UOcWEaeAdVoypQp5OzsTJMnTyYnJyeKiYlhz9ra9p2dnRkQyt7enqRSKU2cOPGD74W1XVhBfI4dJ1cIzrJvPZI/d++aFDz3dIWE3/8m+z+Z8X2Iff/992jSpAlyc3Mxc+ZM9OjRA40aNYJer8eaNWtw9uxZAMDGjRuxYMZEmIoLeAomToicyzuQe92W2ouMekhcq0DiVhUgC4oS7kH3PBJSz2CQoQicUMjPEMdt4+vvAORc3QOpe1UI1Y42oQ+zvrB0xxYzSK8rw/P5LiSd+LAGAKknPxLnJBVDg63rAYApIxEgCwQyNUAWCO2ckXttH0ivsylAFii10L9+YDMC1YT3hd8Xx+Bdm+fIMxgMOHz4sE39nVAoZNREZcMi/v623JC9evXCkydPsG/fPpvler0eRqMRhYWFmD9/PmMk0Wg0DDZtXa9t27bw8PBg28rdA+HSrXyJA/u9hMIL4GcRxS+jALOJzdo4odiGZksgVSL7/BZknd3EWEjeNW3EZ9B8NBBUXIiCB2cAMqNGzVogIjg6OrKSi7S0NJhMJhQUFMDBwQEKhQKnTp3Cvn37kJ+fj5kzZ1Z63k9SClEsd0L+00ieIcXeHQ4dPoem0adsnaK4aBQ+PMfo8Uw5yciLOYuDp84hJikHgwcPhqenJ6RSKbRaLQIDAxEeHo4JEyYgNTUVmzdvZmGovLw8CAQCbNu2De7u7hCJRDhy5Aju3buH6tWrY926dejduzc2btwIgOfOdXd3x6xZfM3Zn3/+iaNHj0IgEPC1dRMmIzmJP6/cp5EgFQ8zJ5Meplw+TFs2vwMAApkSnFQOqU9J8bbZiIJH5+HU9QtwEoXNul5th/DRjO5fQaR2BOkLeTYlO2dowvtAHtiQrVscf8dmW6FSC44TQNuq8kJnuVwOiaT03SgtU+CQd7081V/peiWzLev7J34n/PbO+5of/St0jy+jIjOmvSzNKQrFKLh7Gm+3TIClZKYn9a2LvBsHSzco885DJGbpk+K42++kSUrN8PYZCu7y5R1kNkBo5wSLLh+WwmxwIimUIc2RaRDhp607MWvWLOzatQu//voratWqhR07duDu3bsA+LpH62zc29sbeXl50Ov15d51cBw8J+yA+9DVbJHvzJM2DFkfagIBZ0Mg8W+1/zrHZ60LAsA6R2uxtsViYaweCoUC331XmvR1cHDA3r17YWdnh7y8PGRkZGDRokXIzc3FiRMn0KdPH+j1ephMfOOQulflX8KSAuzcGwdhyk5GYezVkisRw6XvYhjePkXq3lkgfSFILIU+iS8AN+dnwqzLZXk8ANB+NBB2DbrBkBqH5G1lyK/fzR0IRaxIvUKzmKCs3Rb2rYbDnJOKooS7sOhyYcxORtHzSAgUGlh0uZB414LhVUnynxNApHWFUO0E/asHMBdksRe5LMm2KfM19G9iIQ+oD2WNFih8dBFkMYEEIvSYtQ6r+tTF4sWL8d1334GIIBQKUa9ePSxduhStW7dmL0K9evUAgIFgrCEukYhvAh06dMCoUaOwaRMf3lCpVAgODkb//v0xefJkvH37Fs+fP8eNGzdgMBiwdOlSfPnll1CpVGjYsKFNzmzt8iVYFquG3mSBSOta7gXiOAFcei1A1h/roU96DE4shcy3Dopf8SAJkYOHDc1WfvSvbFtN035w67cYid92tt2nUAxt077gOAEKH50H5WcgIT6OcZa2bt0a7u7uGDqUp8kym80sPwkAUqkUZrMZmZmZ2L59O8LDwxEYGGgzmPj5xmu4Dvi2UhYWi14H3TOe5ksRFA5TTioMqS+hqN4cDp0mY/1FnmEjIiICycnJjEJu//79SElJwezZs7Fo0SKsWLEC+fn5jAWlqKgI9vb2GDx4MIRCIU6dOoUnT55g8+bNmDlzJssBWiwWZGZmskEJwIdyAwMD8eLFCwhVDgzUkR91DBIXfyiCmkL39BpS98+F1LM6dNb3qcREGlcIpAoI1c6wtkqBWA5F9Y8gkCqQVgaElRb9JyjmCizFBfAau6Xim2S1EpYVq+lTXsCsy4XasxqyK9lEo9GgWbNaOH36dMk+RCVOiFhOjS3nUOpYOCFAZva7SOsGU3o826+qRkvonlxl4UhTVpLNcYX2HiBjMSwF75Asl+QMyVAapi96csl2HdZ38OfDCcWsFxHI7WxqDK1G+jKcsEQwZZaej0WXA3nVxpC1qYtqiiLMmTMKDg4OaN26NXx9feHlxQ8oBQIBDAYDawuvXr1ibTk9PR3+IaGIf3yXHSP7wtbSAUIZy71xEMbMJJaDLYj5E8WvHkBVpx1k3jVQ/PoRih6cgb4EvKfQpeLshgVIuhj83kHk/9r+a8c3bNiwci+qFQ149epVFBcXo0GDBjhz5owNQ4ZCwY8WrcnXRo0aQSqV2qAQe/fuzZyo7mlpfgAAYDbClJ8BkdqRpw2zmCEQS8FJS0ehIq0bhHbOrNDSkJYAuV8d9ruVNeVdGh6BQstGcAD4ketfmF2DbiiOi0bGieXlfzSbYFc1DHlxpeg3kAWm7GTG0QmzkRXU2oX3Rd51flSmrNUG2o/4vJw1J2jNkeUVG6HT6XDjxg3k5+ejU6dOOHz4cLli7NDQUJvOcMGCBbh37x6jPCsuLsakSZNw/vx5tk5MTAz8/PzYdw8PD5w/fx5Lly7Fixcv8MUXX2DIkCH47rvvsH79egwcOBB9+/bFlStXsG7lMuiqdYPQN9R2xFvGxFo3kEEHRfWPILJzRtGLKJBeB7GLP+Q+NdFzxTHcf537l4wnRYn3kHfwKMz5mVBUbQTHjpPgFtEPX3+kwoq50/H06VN8/PHHcHJyQo8ePaDX6yEWixEQEICEhARER0ejXr16MJlM8PPzw6ZNm5CQkIC5c+ciNzcXAoEARUVFsNNoYfQPh7rZAAgqKfYtiDkDiy4X8ioN4PzJLJ4dZPUA6GKvwpA9CCdP30HH6jUQFXkdCQkJDBCSlpYGo9EIsVjM1C3y8/MZCwoANGjQAMuWLUNUVBRyc3mg1LZt2/DFF1+w46vVaohEIuTk5MDHxwevXvGd0YsXfJ5O7FrFhgIw/+5puPb5Gqb8TBgzXqHw0QUI5XYwlxn4mfIywIkl0L8tzSMKlBq8XtUbZCjigSPFeQARKD8dAic/qMK6Vvq8PEb8hLebx9o4PQCwFGQhaeNoQF8AsVgMtVptw+Zft25dFBQUlDo9AJpm/ZB7eScEcjuIHb2hT+Jz3yALOLEMAqUDD44iM4RqZ5jz+c67rNPjD24u4eTlTeZbG8WvH7FzNGeXZ7ARalxhKchi76zV8QpkKoYG5w9WBtxExNDJACBUaCp0fGURp+z9KRNpSj+0CJxEjjS3QOgLC+Hl5YVWrVqxARHAD4LK5u2pJFdtNeb0Skz3+DKEKnuG1LRaUVy0TZvRJz2GPukxZD61IPCpgRClDhdizrLfM9PTsH37dkRERPyrHd9/HeosKysxYcIE/PDDD3Bx4dlI7O3tcfnyZZw6dQpCoRCFhaUOxDr6sLfnO/HRo0dDKBSy2eNnn32GrVu3QqHhOfREDl7wnXkSmqb9+O/2HnDt9w1UdUsS9hYzzLpcGMsoKkjcAm1meO+OZq3rllVtAACxNQxXknAXlDgaoViMd8135kl4jNkMibMfCp/wiDhVnXbwmXEUTt14wAeZDNi9fSsCxvxks61j56nwmrizZIQqgNfEnfCdeRKmnGS2jlXKRvciimc5AZ+Qzjq7CVG7lqF+/fo4ffo0Bg0ahGPHjn0QA0lZS0hIQLNmzZCVlWXj+Coyi8WCn3/+Gb169cKMGTMQHBwMvV6PBw8eYPXq1QgPD8eXX36J6OhobJj0KUR/wXwmcauKopdRyL1xAOaiPKjqtINL74WQS6WY1aE6ZncMhlxcvokWlYGQZ5/ZCIADGfUofHQRhicXMbtjMOwFekgkEvTo0QPDhg2DUCjEunXrsHLlSnAch4EDeVolqxrG3bt38ebNG1SvXh1//PEHfv75Z+Tl5cFsNsPf3x/5BkLOzaPI+nNDpdfDpIbceakngUQOkYMXQBYY0+JRlBSLnzesx71795CTk8MAISEhIRBX0LasZp2x/vnnn8jOzmZlGM+ePbMBMOXn5yM7Oxv16tWDnZ1duf0Uv4wqDdmDZwcSSBUwF2TxsxaLuVxMw6LLgaUoH+7D1pRul5nE9sOJpZDI+PdkyZIlaDhkLjQNu1V6LWInb2iaDYBAXnp+IgcvCDWukHmUgiHKOj2O4+Dp6Ynnz5/bkKUXPeeZViSuVSBUlWH4Jwu8JuyAoOS8hCpHeI3fxr9rAIRl2JIAno+SOSBOwKOqxaXvkTqsKzzHlM5gOYkCIEup0ys5JgBbpwfwJRQAxG6BPNCnhBMUKN/vWEF34DjIAuqz/ZZNfQCAY+dpILOJyZ+Fh4cjOTkZmZkVpwGsJpFIbCIYYpmChV7dPlsOr/Hb4dpnEdR1SpU13AZ8y8KeZT+q2m0Q7KbG+Y0LbEBg1s9fEeL/r+3/tJyhevXqjMNQqVSy2V1ZUyqVDJ1YlsFbq9UCAHzDWuHJuYMwZb1BxslVrHOx6Av5fFqZBkqGYpjLhCPyb9vW7pnKQOMBIOfKLhjS4m0g9wBYg7LO9Cy6XKg09ijILR+ESf5lMsxF+fAau4WVRxTFRSPrj/UoKqnPEXKE6UN7QSi3t9lWIFVCqLSHqlZrFNz/A6l7Z0Ps7Avdk6uAWAaRyoFJ2RizSjsbKzrOetb29vbQarUsj/U+uZmylpSUhEaNGuGrr77CvXv3bJCZ06dPh0qlwooVK+DkxFNCHTx4EIWFhejXrx8GDBiAmJgYFlp51zo1rolsqN5L1eXQdjQc2tryZPIk08Go7aVlNG1LTsei2GRmIUb9m1i2PpkMNnD7mtKskvyCH8RiMa5du4b09HQEBQXhzZs3OH/+PGbOnIlBgwZh8eLFOHDgAJYtW8Y0AwcN4lGNq1fz+Y7GjRsjJCQE5x+/xYMzB1H44Bwc2o1B0bNI6Msgbx3ajGKQ+LIzQkFJ+8w49QPIpIdYaQeVRMjaPMBHO8LCwvDkyRNERESwzsliseDy5ctYvHgxW7dVq1Zo0qQJlixZAgD44YcfbDoZhUKB6Ohom7wuJ5KATAaIXQNgTI2Dqk572LcfD0tJ+Mpr3FYAgLkwB0nrhgCcADK/uiiOv8Mg9jlXeX09gcqhfMivxFatWoUFq7diVQzKzdTNxQXI+m0NihJjQIYiCNWOUPiHQiCRo+AeXy9pPeeyqEOAn62cOnUKERERDEUMAMZUfuZWnGA7ewGAjOPfwZiWAAAQ2jki8dvOcGvSDWJHL6ZXyM6tbCkFWZAfbdtv6J5et3nWZNDBbHgXhcyrtJSzEudoTH3Ja9g5eDJaxXLbCISAxQQigrpeZ1YjKFDYwZxbMtCQq1H04pZNaca7PMCVWYcOHXD8+HH23WLUA2YzRPYe79mqcnuZXoiYpJwPJj632pw5c3Dy5EnEx/9/3H11eBTn+vY965Js3BWJkSAhBAsQKFKc4u5apEDxUipAgdLiXoq7uxbX4A5BAiSBhBD39ef7YzJvdpNA6Tk9Pd/53dc1V7Kzs+Mzz/vYffPXr2rVqpg1a9YnKfv8XfhbiltKCnIKEPJHQGllgbLmW4bWhHCOi7cfv5xEhoKnl2EoCjuUbI5m+2Ix8vMdv88qv2Rfz7qU375eD+hT4vjwVMVabL5773mwjWhjuZPw8/HGlClTSrnvIpEImqLQjl1Ud8h9wmAuzIU86zUGDhrClouLi8PLBzfYZ8tkv0OTIbCp3gqm/CwUPIuB3CsI7t1mwLXrdCgrREL3lhd/VAXVhdeIDfCbfBiB3x6Fjy/fb5OZmYnFixdj0aJFWLRoEWJiYso8NwKE63T16lXs2bMHY8aMwYYNG7BtW7F80549e7Bhwwbk5eUhNTUVkyZNQu/evREcHIwHDx5g6dKlHzR6AkKk6fBOuwky6EDmso0fA5mhlIpLJcZ71fbHjiG18XklN8glIigkIhb6BQDfoasQMPUI1AH8ufSy4W/p2bNnIzo6Gt988w0WLFjAvFkhrxcQEIA6derg9evXuHbtGnbv3g2RSMQ8QWEQ9scff2DRokV48IdQsEAwZr1D4as7yL15kE1AcV+o2bJQqihkzokksKnSDF6VIqFQKBAbG8s4DNeuXQs/Pz8oFAocO3aMXZ9x48ahUaNGVj2VZ86cwaxZs9jn9+/f4+TJkwD4vKyXlxc4joPZbGaDTmV5viXEkPISEkcvmPWFSFo1mBkzAYa0BMBs5ItRoroB4GBIK2osLyJ7sA1vafUbc2EO9Fp+/8LCwnDl8Hb0ryQt5annXN/HFwRpXMCJRDzBc9xN5D88y5ZRcUYMGTIEXl5eEIvFiIiIYN/J5XK8f//eqmGfLBrXnVqMQrnRm6Gu3AQitQO0CQ8gVhV5lUXXw0ObgHr1ivtVywQngiq4HqTuAWyWKTcN+uQXH/kRIBHSJZbvOcswPxG0r+5AG2+R7ihpKIXjMWgh9wqCU+uvwcltrAg0qDAPhXE3+KhCkTcZHR398WMqgqXRA/g8N8C3FFlGyj4VepMZy899/LyUhc2bN8NsNqNTp07w9fXFxYsX0bJly0/Wf/w78Ld4fD4+Pnj58iW+++47HDx4EE5OTh9cViDHFXIX06dPR79+/dj3nTp1wu7du3H06FFkZ2fjWlEoyqnFKKhDG7IGdIk9LxRqE9qQ9d0BgDo0Gnl3jkD3NhbJG8ZC7hUMVUBtaBMewJCWALlnIBvhAoCmZnv2f8KCrlD4Vkbew9MwpL4GwBcp9P52EcbUsMGcOXNY3kStVqNNu/ZIM8kR1n44crQGxD9Px6OK1RBRMwx+bo5Ys2IhPD09MXr0aHTp0oU9zMt3HMHcq9l4n1vU3CqVw6nZl3Bq9mWp8+Xa+ftS8ziOl5lZWYaw458hLS0NMTExaNiwIbZv384KI6iMio20tDT8+uuvWL16NVq3bg2lUolDhw6VGUYToNPpsGvXLixcuBBxcXHgOA4eobXg/flAvNKqIeJgpbgghhkmkwkFcTfhbXgFz4YDYTR6Ww2aLBlPdt5IwLZj5yEc+ZBGQRjWqjZan56BmOfF+yGEMKdPn45vvvkG8+bNw6RJk6yOs0+fPrh69SomTJiA169fo0mTJsyY+/v74/Hjx1i8eDFGjRqFMTvuYP/dJBiy3kFq7w7n1mPh3Hqs1bHLXMsjH2dYD6ZZVwBjkTchcfCAqmIt1K5VGVvG8qFASx20rKws5um8efMGSqWSFSDJ5XLodMUFTyWvlUgkgtlsRmFhIV6+fAk7OztIJBKW4yl885hfUKqAMeMtjJlJkHtVgjEvnRUJaep0YX2npC+AwrsSnNtNQPofv4EKsgCTASKFrVXqAIBVNbTA4nO2Xz94+odg3PezkXH9IIy56WyAK3X0hEimgCEzmY9gkBkyZx/o0xJRkJvFiqtCQkLQoEED3LrFez1RUVGQSqWIjeW9/a+++grNmzdHy5YtoVAo4Jt6DU/vHgOMOigVcgxecwa2hcmYO6w9dKl8Ycfdu3cRkJ8PR2cXGDgpclP5Fy0nV/OhXqkS0BdA//6VVS4OADS1O7G8u3A9zYW5LLQpFKTIvUNZTsxr6Gq83zOdsdKI7dxhLsgCGbT8No16wGSApm5XGLPeo/D1Hf5cA3i/ZyY0EW3gO3Y7yGxCwoJugIEnzVD4VeH7Y4tykOfPn4erqyuys7OZRywMfgRIpVJ2f1n+rypXDQ7Nv0Lm6d+R8ccKSF384dx2AqRF71d96mtknVsPXfJzgAgKnzA4NB4EiZ0riICzT1ORnqezUv8gIkydOhWbNm3C+/fv4eDggKpVq2Lr1q1wcnLC1q1bUbcuX5Gel5cHd3d35ObmIiYmBh06FFdI/yfxt3h8P/zwAypWrIirV69i0aJFVg/0X8XatWsxduxY6PV67NixAxUqlIdbm7FQhzb8pN9znAguHafBJrwFzLoC5D04DX1KHNQVIyH3Cvrob5X+1aBPiUPe/ZMwpCVAWSES7s2GYHjDinj37h02bNiAs2f5EWp+fj62b92M5zGnMK9zFXR2S0f6kQVIu7gdR/Zsx9mzZyEWi9G/f39MnDgRfn5+GDBgAEaPHo1OjSKxuncNKCT/2un/lObQ48ePY8yYMVaT0MhdvXp1/PHHH8zolURaWhqmTJmCoKAgZGdn486dOwgICEDXrl0/aPQSEhIwZcoUeHh4YMKECXjy5Anatm2L48eP4+GFozjxbSdcnfwZxjYNRPtqXmgc7Ir21bwwsUUl3PquBZZ1q4oH5w9j3Lhx8PLywrBhw3D69GlW1QsA0OVh76zhUNzdyWb1rOUHJxs58w4EFhvh2DZv3oxBgwZh9uzZpfa5a9eukMvluHiRz80KYU6Az1cDwMSJE9G9e3dc3zAL7zaMQcq2qR885zZVm0Gk1KAw7iZS985CytYpvFSOvQcMafF4v+t7bB/fgakkvHnDh9zs7OyQl5eHgADey7C1tUVhYSErALPUCRQMiOU8kUgEOzs7mEwmmEwm5ObmWuV7qCAL4ERw+GwgAEBs6wL7+j2he32XLZN35xgjSTAX5qLw9V2oQxpA7lZEnCCSQBlQq5Sos0zjhPz8fKv8TsOGDVHb2Yj3J3+DxKSFXdUmUJePKIraXIHuzWOY87MAIkT1mYBvp/BRlEqVKiEvLw/Lly/HkydPsG7dOhw/fhyhoaG4evUqXr58ybxkjuPQokUL7Nu3D1WrVkXcs1hIC1JhLzWBCnMgu70N49rXZaw2wr4ZDAZkpKVi8pjiBnrS5UNi5w6byk0BcDBmvC3FJCN19LYiqjBmJlvl80xFFZFUokXBMgJlyn7HBgoSjTOLEOTePIiCx2eZ0QMA/ZvHyH90Dm9XD0P6kYVWoc3CF9d5cV1nH6g1/Drev38PnU5XqohFgGX4uPh/DgWv7uLtb0NgyEqGxN4d+qSnyL64md/fvEykbJmMwld3IfeuBLlnEAqeXUHKzu8YkQAHYPdt69Dx6dOnMXv2bIjFYgwcOBANGjTAgwcPmFixYPQAsGsC4E8jSH8n/r8Uoi2Jf0vMs4g6p15F539JGuZDPSlEhJs3bzK1cplMhri4uFLLCTRSK1aswLp163DlyhXmzWyOef237pMlBIHSkujatWvpPp4ipKenY968eVi1ahW6dOmCKVOmwNfXFyaTCeXLl8fevXutwk9EhNOnT7M8k0KhgK2tLb766iv07dvXikvwU9C3b1+4u7tj6NChTFQ3MTER7du3R0REBGbPno0OHTpgzpw5rBjk1atX8Pf3x5gxY7Bo0SLY29sjNTUVz549Q58+ffDw4UPUrFkTTZs2xXfffYeqVataSd907twZu3fvho2NDd69ewe1uvjltn//fsyZM4evlOM46NRuUIVEQxP54eIN/bs4ZJxeDX3yM3ASGZQBteDQeAhEciUM8feQe2Qu8nKty8Y5joNSqYTBYCiV3wKKPTpnZ2fWrqBWq1mxmL29PQYOHIh58+aVuU8yrxDo3z7hvQxdPsQaV3gPXwtjVgreruSNoXvf+ZBoXPBmSW8AgF1UN9jX74WEeZ1ABi2UAbXh2vFbFDy/htQ9M9i6lWpbeHm4Yd26dVY5mlGjRmHp0qVwdnZGzdp1kWEUQ8spEdi0O7j8TOyZPghGgx4XLlzAo0eP8OWXX7Jrk5yczPpCX758iXLlymHu3LnYvHkzLly4wPL/H8Lbt2/x3Xff4fDhw5g2bRqGDh2Kjh074tChQ/Dz80NSUhKysrLg5+cHtY0N4l+/hrJ8BGRuFZB9dSc4iRxDh4/Ed5PHoWJgMArycuDSYSpESg3e7/yOl1MSS8rsw5N5BPJsN2SG57DfQUY90g/Phz41HnKPQCjKVUP2xS2QupaDROOKwhfXILZ1hllfyK/XbASnsIHvmO3QvX2CzLPrYEhLZK0Wct8q0CXcL7VdS0RGRuLBgweseMrHxwdJSUkstFkWNHW7Qe4RgNQ9MyB19oXnoOXIvrYHWWfXMe1QAMh/fB7mgmy+CK2oAKd9NS8s6FqNrevYsWNo2bIlGjdujG+//RaVKlWCi4sLiMgq92w0GtG1a1fs3bsXnTt3Znn2fwL/E1ydgjDtvyLmKXhHQgJ2/I9zUZBWWmfMNqI1pEVJXks1cEsDQ0S4d+8eM3ZisRhdu3bFkSNHEBYWxkbjPXr0wL59+1ChQgWcOHECjRo1wrVr13D79m2rEJ6w7pLFG2XhQ/v0Ifzwww/44YcfkJ+fj6FDh+LBgwfYs2ePFaemgPT0dMyfPx8rV65E586dcfv2bfj5+bHvT5w4ARcXF2b0srOzsWHDBixYsAA5OTnQarVo1qwZRo0ahUaNGn2SkG1Z+PnnnxEWFoYBAwZg0qRJmDRpEguhDx8+HCqVCnl5eTh//jwMBoPVuVy4cCEWLFiAxo0bY+XKlRg5ciSjJRMwbdq0UtsURE8tYTQakZOTgypVqmD58uXIzs5GVlYWVj0yIzb/41WzMvcKjDwbALTx95G8dhTkXkFQSTiIis5NmzZtcPnyZWRkZOCrr77CypUryzR6liErFxcXpKWlITQ0FN988w169uwJmUyGrKwsHD58GPXq1cOlS5cQHByMJ0+eQKFQQKfTQe0bCqV/tWJvjUo/RzK3CuBEYog1LjDlpCL39lEYMt4yD0XI7XEldBtFMMPHxwfNmzfH4MGD8dNPP0GlUuHQIb73Mi0tDUcPFxeLOBveQ6FQwGjgQ3JTp05l+dTHjx/D19eX1QwEBQXB398fmzZtwrJly3DlypU/NXoAL6K7Zs0a3Lt3DxMmTMCSJUvQt29fHDp0CPHx8fD19cWjd3mAkx/in/KhVJvwlhCrNMi+uhNk1GHTqZtYvysa2nzeq+NAkLn4QeYeAF3iQzg2G4Gc63tYj50wmACAN8sHwJTzHhknV0Dq6AW3HnMYLy8A2BdVpmvfPOa9t6L8vfb1XZjyMuBQRBsn9wqBSKaCSG0Psy4PIIIhM4mnXjPpWThW7hEA+xptkHJoPuydXHD9+nX069cPGzZsAAA4OTkhMTGRtc+4u7vj3bt3EImlMJsMENs4waFBL5Z/FNqmGKlBemKpClRDZhKU4N8HOVrr+7ZZs2YYPnw4Nm3axHq7IyMjceDAAXh48CToBQUF6Ny5M44ePYpWrVph06ZN+CfxP2H4mDDtv+QdBTOj16u2PxZl3cfNm5dLLasKqA0bF97VbhTkYmUsHz58iJ07d2LHjh3Q6/Xo2rUrdu/ejWrVqpV6yZtMJty8eRNKpRKtW7dGcHAw8vPzoVKpEBRUOtTaq7Y/qnjbY/m5Fzj7NBUcrHNgoqLVV3SxwbTWlVA/4NNFHQXB2MjISFy9epWFzgRkZGRg/vz5WLFiBTp16lTK4L158wbe3t5YtWoVM56LFy/G1q1boVQqIRKJMHr0aAwePJjd0P8O3N3dMXXqVHz11Vc4fvw4iAhr167FxYsXERMTAwcHB+zatQuTJk1inmDnzp0RHR0NiUQCjuOwcOFCNG7cGA0bNmQ9bYLh+tD/JecVFhZCo9HA3t6e5+a0t4e9vT1Uzv4QOzWCiSubx7EsiG2dIHX0hC7+PvSGArg4O6NHjx5YuHAhgoKCkJGRAaPRCJ1OB3t7e2RlZbEXE8CHbIX/hXJ+IaQM8Pmajh074tKlS7h6lW+e9y0qehJG12aDDvZN+qHw5S3ok5/BlJ8FU4mye4EZSObij8KcVJgNWl6YtUjRQFDituReBfiQ/9mzZ+Hj44P379+jWrVqWLduHYt+iMViJCQk4Ouvv8aePXtw/rx1g7cQZgb4EFxiYiJ8fX0xYMAAfP/99zh16hTGjx+Ps2fPwsvL65PPO8BXC544cQInTpzA119/zea/00rQacUlGD3CgKe3AHCQ+4RCrLCBpm5X5N0+gsJXd2BXtysM+dkw5bwHkRnpxxYzA5BzfS+M6W9K9+0BcGjUD5ln1kL78ja0L2/Brm7XUuwwAFgeNfvSNuQX9dHZR/eFTXgxp6o28aFVHtWcy+dtpW4VIHPxhy75KXTJz5F5i+fRzc7Nw5pzT6y2ExwcjF27dmHkyJE4ceIEu5/MTIi3dLU9wHPtAoAqsC5cOnzD5pvyMq36pTUK61Yck8mEpUuXYsmSJXj16hWmT5+OjRs34vfff8e0adOQkZGB1q1b4+rVq+jTpw/WrFljNYj9J/A/EeoUwIcG/9w7EhDiYYs57augqo89AOBeYhaWnXuB889SQUTQm4pXIuL4eHWDQBeMaRwIRUEKduzYgR07diAnJwddunRB165dERkZ+VGPZsOGDfjtt9+QnZ0NuVyOu3fvwmw2Q61W4/z581ahwpK48Ow9fjj4AHGpBRCJRFY1XwoJ/7lhkAuGR1dkx/Qh7N69G8OHD8esWbMwcOBAq33OyMjAggULsGLFCnTo0AHffPONVUUtwFc/urq6wt/fH0lJSQgJCUFcXBzMZjNq1qyJMWPGoFWrVn/7DavT6VCtWjUMGzYMe/bsQXZ2NsaNGweO46yMVEJCAp48eYL4+HiWD+M4DgUFBTCbzZDJZPD19bUyXGX9X9Y8GxsbcByHtDwddt96g9h3OcjRGqFRSFCgN+HC81Ro/8bw9LZt29CjRw8W0iwJJycnpKenY+bMmcjNzcWVK1dY0UdBQQH8/f1RrVo1HD58GCaTCRcuXEC9evXw7bff4qeffoJM4wR5UH3k3f/jg6FOofr5/Z6ZKHweA7uo7rCv3xNZFzYj+8p2iBS2UAbWhjbuJqtUzczMLOWB7d+/H8OHD0fLli1x6NAhNGjQAK6urrh8+TLu3buHr7/+ulRIdv369ejfv3+pMPTt27fRvHlz7N279y+Xujds2BDnz5/HunXr0K9fP2zbtg29e/eGsnIzODQe+EESgo8h++pO5Nw8xOcni55Ox+YjYVvtA61DRNZVnp8Ay2viM2Y7rwxjAW38faQdWWilWlIScveKqFGtMq6dOmR1Pwhe4OjRo7Fw4UJ0Hvktdi/7iUl8aePvI2XbN8X3R246kn8fDrMuH4py4ZDYucGYmQxt4kN4DfkNEns3KCQijG0aaKU2cu7cOfTr1w916tSBo6MjTpw4gbi4OFYoFhUVhStXrsDBwQG9e/dm76ZPbcP6O/A/4fEJELyjyXvv43FyaXqdkoh9l4tuq2MwtSXPJv8xo1lEoo6zT9/j7KO3MN7YiY5VXbF69WrUrl3bKjb9IRQWFmLatGnYvn07duzYgeXLl7MXWX5+PtasWWNl+CxfrE+Sc/DifR5MRHy5d4l1C17gyccpuPAs7YMhT4PBgMmTJ2Pv3r04duyY1fYyMzOxYMECLF++HO3bt8eNGzdKcXcKyM3NBcdxLAx17949tGrVCosXL0b58uXL/A3A84Z+ilf1oXl5eTxzx5gxY+Dg4IBKlSph165dVobJ3d0dQUFB6Ny5M+zt7ZGXl4crV67g5MmTSE5ORqtWrbB//35s2bLlowOND8FygAQAOgsPXCERwWAyQ8RLMn6IxA7Ap4enu3TpgtOnT2Pnzp3QaDSYN28eunXrBoBvrP/iiy+Qnp6OqKgoVg2t1+tx5swZfP/993jw4AEOHDgAiUSC2rVr49q1axCLxUw7UZ+XBYq/D01kO2SXaGH4M9jV7QpTQRbyn1yENv4+HOt1ReqJspv4X7x4gXPnzqFt27Y4deoUMjIycPjwYRgMBjg6OqJbt2749ttvP2m7L1++RJs2bbBy5cp/qb+rU6dOqFatGipVqoRr167xBBku5f8lo2cqzEHmqdV8WLKoslLi4AmJxgW5Nw8i42QRMQURQGbIfULh1nUmsi5uRsHzGBiL+E+dWo75qKTPx5B+bAny7p3gP4hLkx2I1A6QeQTCmJkEY14Grpw6CpVCCbPJiPr168PPz6+UWo7e+PHUkcTWCW495yDr/Ebokp9D9+YxxBoX2FZvhbwHp1joPM3mF6BBMTevl5cXAgICcPr0aWRlZcHZ2RlDhw7F9evXYW9vz1rVhDYsAfb29v+Y4fuf8viAf60gRCrmQEQwfvpPPrmIxBJz585FTEwM9u7di9jYWISFhWHIkCFIS0vDvn37IJPJkJ+f/9EX67+zf0lJSazyctOmTay4JDMzE+XKlUN2djZatmyJJUuWlGm8zGYzTp48iV9//RUXL160Ko1Wq9UYPHgwpFLpR42YwWD4oCdVlqdl+Z29vT3Onz+PwYMHw9fXl8kD/RW8fPkSu3fvxrJly5CcnIz+/fujS5cuLBz6Z/grUQURAJPZBIkIMKE4/Cl45yVD5v9JEBESEhJw+fJlnDx5Elu2bGEVsRzHQV21OZyaDgbEsj9Z04chFIqt7FWjzO+FCsqS8Pb2xrNnzz652js1NRV169bF2LFjMXz48L+0j8JAUyQS4enTp5g6dSouXrwIT09PvA/6AlL/6h+k0fsQUnZ8B+2r25B5BhWJseaAU6hBer4YRWLjCFNhDqvolGhcQEY9HJycUSDVQJscB3NhzicZPmPWO7xdOYh9dus1F2ZtHlJ3Ty/BR2rNdWoJr2FrYEh7DcPVzQgr742LFy/C0c0LvRcdQo7WCJPZjJep+UjMLCzz93+GjDNrkHt9H/v8+eefW4k2l4WdO3eia9eucHJyQo8ePdCkSRO0bdsWZ8+excSJE/HgwQPmAc6aNes/Hvr8n/L47iVm4aejsZ9s9HRJT5Edsxva+AdWfJsiuQoyjwDYhreELvkZCp5dLTUqKzSY8dPRWPSuU7ZHJJFIULVqVXz33Xdo27YtXiSmYMHxh2jRfTQGbLiBhOexcIzqgqat26N9y6bQarW4e/fuXw7XfgjC/gkMJ+fOnUOPHj3Qv39/9O/fH/Hx8bh8+TI2b96Mo0ePMiOmVCoxY8YM3L59G69evWKhwZJ9P/b29jAajSxM2759e8jlctjZ2aFcuXJlGjOhpSEmJgZmsxmNGjXC/PnzYWtr+6fHQ0SYNWsWli9fjgMHDsDLywvVq1dH3759Ua5cORYOEao4BXJ0y75QIbQ1ceJEjBs3DqGhocjLy8OkSZOQkJCADh06WOUES+KvDqrMAKRiERqHuEMlkzA19WAPW3Sq7m3V21QSO3fuxKRJkxAfHw9HR8eP6iF+CjiOg0ajwf79+7Fnzx7IZDKYTCZW3p5/7zjAAY6NB/Nahv9CAVJZbTTTp09HRkYGiAhXrlyBjY0NCgoK4OTkhPDwcCxZsgRBQUFQqVTYs2cPOnTowCqOBa7Y+fPnY9y4cZDL5TAajTCZTKhatSqMRiM4joNcLofZzPd7uri4YN68eejZs6dVAUe5cuXw+vVrEBH27t2LHj16QKvVQiqVQqPRoHJETew8sgm6PT/xBoN4ujWlfzgcGg+C9vVd5Nw8CGPWO4htHGBTuSk0tTvCkBoP7avbEClswYklxUTyWv594hpaF/1a1cP27dtZj68xJxUnT55E06ZNseHSCwxswZNjpJ9Yipxre2Ab2Y6FR/OfXkHGiWUwF2QDnAgye2s6tZStU/hzX74GdAkPignszSae6N7RC8b0RMg8g6BPegq7qO6Q2LtBYu8GTVBtSLIfARcvIkdrwP67f94gLjDsaBMewKwvhNjGEcpy4XBqzrf3kFGPvHsninof+T7MJ0+eYMyYMWwdgpiyJQTx65YtW2Lx4sVYvHgxXF1dGaFEz549cePGDfzyyy8Qi8Vlth/9nfivGj6j0fiXLPuycy+g/RP3XEB+7CWkHZhrRe7KyZQAETiZAoaMt8h/fA6mwjxINK68ICqRVfWS1mhC2Ofd0DiY7wnbvXs3kpKSQETw8PDArVu30LFjR7T5bj3u5ttCWbMjzrzMA5AHwBG2dbth3IVCHM+4iUNTOiD5TSJ8es+ByCsMfwcK9Qa0n7oS6QfmICcnBxzHYfny5di0aRP0ej3S09Ph6emJpk2b4tSpU9Dr9XB1dUWNGjVw9uxZFBQUsBJnwfGfMmUKpkyZAltbWzg4OMDZ2Rm3bt36aNM6wIdG27Zti9TUVHTs2BGvXr3C77//jry8PCtGmLKQl5eH/v37IyEhAdevX2dFDGPHjsXXX3+Nffv2lfrNgAEDkJGR8cHeH7FYjFWrVqFPnz548uQJ3r17h927d3/QCJY1qLIMcZHZCLl3KBybDGFcroWv7yL70lasfvcCZNQjOjr6kzgKTSYTBg4ciLy8PHTp0oX176Wnp2PMmDE4fPgw9Ho96tevj0WLFpVZFGWJx48fY/r06di9ezfs7e3x22+/ISYmBr///jsAfrBTr149uLs7o0MbP8w69Rrv9bK/ZPzIoEOHQFUp73Xt2rWMX9cSkZGRuHPnjlW/4dChQ3H16lWreQUFBUy1RafTQSKRQKFQIDo6moXBdDoda+VISUlBr169ULlyZavtvXr1ijX6d+jQwYr+rEmTJjh04AB0ae958VcicDIVxCo7FDy7Au3bJzDnZ0KscYEqKAq6pKfIurARZDZCouGLyaSu/kWKG+8sKMeArPdJmDt3bqnBndBuE3tkDaNRVHgEwpiTiozjS8GJpRCr7ZG2j2fhEYklIBD0mcXMNMyr48Q8cfZL6yplTizh6fpEYuiTefaG3NtHoAqKgszVH7mvHuBskeEksxmmwlwkrf4S5sIcuPX8GQrvkFLXTWDYEansAI6DKfs98u7/AVNeBlw7fYfMs+vAcSJ4DFiKt8v7AeB7eBctWsTWUdLwWbZWbdq0CZs2bQLHceydExUVhc2bN7OIwZw5c7Bs2TI0b94cixcvhru7e6n9/LfxN+v7EREvrtmnTx/y9fUluVxOwcHBdP36dSZYO3PmTKpUqRKJRCIiInr//j0NHDiQfHx8yNbWlmrVqkXHjh1j3wEgW42GAqYeJu/R2wjgSKS254VOh69jApC+kw6RXVR3XkRRZC3yKPetTL4TD5DvxAPkMWg5++s3+TB5DFzKBCLBiYrEH+Uk9woh7z5z2ToEMVAAlJSUxP5XVogksZ0bcXI12TfsR24955DE0Ys4uZpsI9qQ3+RDJNG4EgAS23vwYrMiMYk1LmQX1Z2JOQqiunLvSmRbox1BpiJOKufFJyUykjh48iKW5XiRV4/+i0nq7Mv2w8fHh3744QdycnKifv360fPnz9k1Ec79qVOnaO/evUw4luM4KlcxkNR2jh8Uo1y3bh0REd26dYvq1atHtra2pFarKTQ0lJYvX05ERAsW8KKmrVu3JiJetFUQwIyLi/vgvRIXF0eVK1em/v37U2FhodV3hYWFVKFCBTp27Bjbl1evXpW5nujoaKt9FdC5c2f6/vvvS23z559/poiICHJxcaH58+fT4I03yH+KtbimIJYq8wwiZcWa/PXTuJLvhH3kN/kwOTb7kmRuFUjmzov0liW8XBYSExPZ8ZhMJjb/888/JwBUu3ZtatOmDS8E6udHOp2u1DoMBgPt3buXGjZsSDY2NqRUKmnmzJm0c+dOcnZ2JplMRl988QWJRCKKjIwkT09PysjIICKiixcvUtAXI8ivSNz3o9Okg+Q7bg91n7aMXFxc6MiRI2Ue09GjRwkANW7cmM6ePUspKSlkNpvJZDKxY7158yZ16dKFPUd9+/alXbt2se8lEgk1btyY9Ho9xcTEsPkuLi6k1+tpzJgxbN748eOpb9++7HP16tWZKLJIJKLy5cuz7ypVqkRSlS17J0js3ck2og3ZRrQhkcrO6h0hdS1PEkcv/tlQ2pJ9NL8NsZ0b2dZoS+Ki59h64th2hXldu3Yls9lMNjY2bF7DRo2pSt3PCADZ+QSSwr0C+04mk1GLFi2s1isperalLv4k8wr54PMpcfQmuU9o8Wcnb3b9lAG1+WORKkgd2ogAkKZOlw9eb02tjmw9Yjs3UldpRoqKtUiksCXXrjP4dcnVRcfLC13b2tpSjRo1PvgMHDt2jGrVqkUAKCQkhDp37syf7yJR7PXr15PJZKJKlSqxbUdERLBn4T+Bv93w5efnM7XuwMBAGjRoENWpU4f279/PXr5isZi6du1KnTp1IpPJRLVr8xcnPDycevXqRRKJhEQiEV26dImIiJ0Qv8HLyKXTd+zkeA79jZzbTiAApAqqS36TDxcbvhKTWO1Q5oX2HrmJRAqbUssLSsdM1b3EVK3TCItlVaSqFM0eApHKntRhn7HfunabaXUz21RrTurKTdh2ndtOsDJ8AEjmEUBiGye2TlVQ3WLjDI68Rm4kl47TiJMVK7aLRCLq27evlcET4OPDK28LCurCbzrM3kkB3xwicZGCtKJ8BNnWaEt21YpVttftPkpERFFRUQSAOnbsSIMGDaJ69erRwIEDiYioT58+BIB++OEHts1q1aoRANq3b1+Z98off/xBrq6utHjxYjKbzWUuc/jwYQoMDCxl+IR76ezZs0RkbfhMJhN7uD777DNycHCgEydOUMuWLcnFxYWcnZ2pQ4cOFB8fT3FxcXT68nUK/Pao1X3h0X8xf04VtszQyb35+7CkCrWgPl23Xv0/fT5evXpV6l6Kjo6mO3fuEMArxQuGrl69eqWMeWpqKs2ePZt8fX0pNDSUPDw8qF27dnTkyBGKiooiBwcH8vf3p6dPn5Jer6fevXuTj48PHTlyhJKSkqhXr17k7e1N27dvp7sJGTR00w0K/PYoBZU4fr8J+8hvwj7y7vYjuQbXILVaTZUqVSI7OzvatWtXqeMyGo00fPhwsrUtVjuPjIy0GiAK165jR/7lGhoaSj/99BP7Xq1WU25uLhER7dixg82vU6cOERGtXLmSzevWrRu754SXr2Bk6taty+4HgB/c2Ud15QecHzAeH5ocmg23nieWftLvIiIi2KD9Q1NJRfl/beLfCSUNsswrtMzlObmaN6gcx/9WKie5dyi59fyZdyRGbiSpk0/xbzgRSV3KkUjjWvSboneN2oG4IkPv6OhI7u7u/H6IxRQQEECDBg2i0aNH05YtW4iI6PvvvycAbHBnOTVs2JD27dvHvx8l/ODk8OHDpZ7xvxN/e6jz6NGjeP78OTw8PHDnzh3WO2YwGDB69GgAwDfffIPp06cDAK5fv46YmBjY2Njg4sWLUKvVcHZ2xsKFC7Fs2TJERUUhOjoajx8/Rm7CIxiz30Ns5wZTXjp0iY95lgQAcp/KZe9QEUz5maXESwFe3si6D4cP/5C+EJxEXoqzj1+Ew70Dv7OPDk2GwrZKYyQmPIQ5Lx1k1CH/yUVwRZIfgqIEAKgqRAJiKXJvHAAZ+ORy2qH5yL19FHLvSgAAkcIWLl9MwdtVAsk1QVO7MziJHPmPzgIgFDw+D9sabfmQQVHS29HREY8ePUJYWBgcHBzQq1cvtG3bFj///DMSE/kQbsWKFa1KxvdO6QJOpgTpCyH3CoFrp+/AicR4v4+PsYtUdpiwZCskXiGswbply5aoWbMmgoKCWEgpJYUn0rWxKS6/FlhQLImFAYCIsGDBAsydOxfbt28vsyBCQKtWrbBy5UqWI/gzEBEGDx6MXbt2MX3CqVOnonVr/tq3bt0aer0ee/fuxePHj3H37l2cTCQA1jk24ZpJXf35nBh4GSXdm8fQv7fuZROQmqcrc74lNBoN+vfvzxj1R48ejYoVKzLV7CpVqrBQYI0aNXDp0iXcvXsXt27dwtKlS7F//360bNkS4eHhuHnzJn788UdcunQJ/fr1g0wmw+eff47ff/+dnXu1Wo3PPvsMjx8/Rp8+fTB48GA8efKEXSeBA3X37TeITc5lecpyDjLM/6orVvw6G2Gz++D06dP49ddfWeNxcHAw2rZti7p166JOnTqwt7f/YO+WSqVCQUEBU2cRwuupegkWHSvW33TxC4QOUtjAmrBe6IsVmEgAQKvV4vDhYgL6du3aoUqVKpg4cSKkUinTBAV4rtNyVWrilUyFrLPr2HyJvTu8hv2Ot78NhTHjLVw6ToMqoJis3pD1juXyRAobeI/chJQd06z06QBAJJHiyqWLqF27NgCekmv79u1wdna2Ythxc3Njz4lEIilFWCAWiyGTyVBYWCisuJi4+oMg/pyWaG/Qv+W1CYVnmy2ty4fRqOcFcY16wGSE7s0jvN/1AzwHr4RYqYF73wVIO7wAhXG8CoQh9RXAiSBSO8KcVyQQbaFXaikhZWNjg+fPn+P5cz702rdvX/To0YN9r1Kp0LFjR+zZswdisRgmkwlBQUHs/hdy+V5eXggPD0d8fDzu3r1bqiL138XfbvgEqYnKlStbNUxb6o1FRRULHQrl8j4+PuxhDQ7m2w+E3EHDhg2xYsUK6N48gTH7PRS+lWFIT4Tu7WPo3/EvKIXvxw0fAEg9g2FIirWaZ8orqWFFxf8Zy36RiZR2MFvw6kmdvWE2aGEu5Mt0Oakc6pD6KHh2DYRCkL74gc25tqfU+jipDLo3j6B/97xofT5F4rpGCNIlpC+EzL1ikeED8h+dg9S1PMy6fDiVC0X6q0dIS0tDWloaWrdujRs3buDXX3/FggULoFarmdL9ggULMGfFRpzYyb8AJA6eMGYmQeYeAJfO34MTiUFE0MbxShLmgmxk3jmJn472QOcBE6DVzsCgQYNARLCxscH06dMxduxYxo2Zl1c8iBD+t4zRFxYWYsiQIXj48CFiYmLg7++PxYsXY86cOUhOTkZEREQpxpUFCxZYveQ+hjlz5uDZs2dWorwODg4wGAzw8/Njzd0uLi6IjY3F2bNnce5WKpKP72brsI1oXabEEFfUhGyyeOgt8fZdGpo0aQKJRFLmJBaLIZFIrF7gYrEYiYmJuH79OgC+Mleoart/n2fS+P3337Fp0yY0bNgQ7dq1w/79+xEREYHIyEiMGzcOlStXhk6nQ9euXdGhQwfcuXMHEokEt27dwvbt22FnZ4e4uDhs3boVAQEByMzMRG5uLtsfqUSC3jU8IJH4QCKRsMFM5RWL0bt3b9y/fx8DBw7EwIEDsXPnTgwdOhTx8fF4+fIl7t27h759+8LGxgZZWVmoVKkSypcvz66hvb09wsPDcfnyZYwcORLOXuWwv0glQKt0gV2tLhDdPglzQRbinz1GhQbtoSp4h4kTxqN8+fJ4+fIlDAZDqf7GEydOWM1r3LgxsrL4a3b16lUr+SKO4/ByzzzolM58XrMot2TWFSBl21QmBp12eB5UAXUAMkOb+BDmwjxeAUIsgVmbh+Qtk2AShKOLGvsBwGw0MKMHADExMWjTpg3c3d1Rrlw5PHzIG0rB6AF81amtrS3jrwT4AQEzevyKy7zP+BWUVdVpIXMkVQAGLURKO5j0hVbLOLefCpmzN5JWDuLXIZGD9IXQJz2FPvU1Cp7HQOZSDurQRih4fJ5/D5KZGT22CxIpzEWcnR4eHkhOTkbVqlURHx/PCs8ePnyIMWPGMMUYjUaDfv36Yc+ePVCpVOw+FM6NwWCAWq1GxYoVPzhw/jvwtxs+oS/swYMHKCwsZCXMlmTDlmKpwsguMTERBQUFUKlUePqUV3sWWEQE2Q1t4iOYC7KgrtwYYqUt8p9egSknFZxEhpSd3/OGp4iBoqzRUkniWQA8P54lOA6eg1fi/c4fYMxKBidXgXTW2lvmgiyAE0OgftK+usOvu6ic2b5eT9iGtwCZFiD/4ekyz5OyYk2IbJyQf/cYpO4VoX/zmHmXZr22+OVqcS8LFEIA75Gk7uV12spVjkT6K36E5+joiFOnTrFRtclkwqxZs/DLL78gJ4fvFYwP6gKAN3zGzCQo/MPh0uEbiGT8tSp8cR1k1EOsdoDX8LXgxFLkpiZj/vZVML+Ng62tLapXr44rV65g8uTJGDVqFHsJ/fjjj/jhhx/Qo0cPxMbGguM4VoggsK0EBATg8uXLUKlUSE5OxtixY0FEGDBgAEJDQwEAR44cwfTp0/Ho0SMr/sw/g+AZDhw4kN1ngtxJfHy8VRIe4HvP3r5KtdJuVAXULlNiSBg5i9XWuooClGo1Jk2aBJPJBKPRWOZkMpmsHmRPT08YjUYmyKzT6ZCcnIxbt27hxg1+8OHs7IxatWrhypUryMnJga+vL65evQonJyc4OTnh9u3bqFq1Kp48eYIff/yRUa49fPgQYrEYGo0GqampGDFixAf3SfjfYDCA4zhmFE0mE9zd3Znig0QiYZWbu3fvhru7O/z8/JCfn89Yi4T9lsvlWLRoEdRqNWxtbXEl5hpk3vlQhzVG/oNTMJkJIqkCmlodkXV2DYjMyL5/Cvn2bvjlYjI8AiKAl7x3bWnkZDIZOnXqhJcvX+LyZZ6Fadu2bbhw4QIAvsdRYMEBeONbO6o+Dp2yZI3hQAYtjHnpsK3eGhJHT+TdO4GCp5cBkYSvAuc4qCs1gO7tUxizkmF4/4o94xJbJ3ByNT+PrI2y2WzGvXv38Pr1a9azVupeUSrRvXt3bNy40Up26kOQ+1aBLvEBM9pMNV74LBLzuouCkSuab8ouaTQIBY/PQmGpBFP0nhTbOkEmEiP/wWnkPzoDgOMHe+bS71KpvTtTtAdg1fpk6ant37+/FFuPAI1GA51Oh1WrVqFSpUps/ogRI2BjY1PmwPnvwt9u+Fq2bImAgAA8f/4c4eHhiI6ORmxsrBVlkCVq1KiBWrVq4dq1a6hfvz5CQ0Oxbds2cBzHenjc3Nzg7lsB7xKKvDvvEBgUNsgp6iUhox4ikRg2VZpBm/CAL+91K8cqnQSUHLGUCSIk/VYsjlrS6AkQa5yZTlZ2zG7Y1+nCvuPKaDAtCbPJCO3DM2z/LUdvZNQVv1yLHVDkPeBlXziFGqTN58OxYimcXYtLoHNzc9G7d29MnjwZISEhMJlMVkz9++++hRYWlZBiKSSOnsi6wHPlyT0CkXe/SN+teks+JEJmvN/9Iy/rpNZArVaz6kUnJyeIxWK4urpCIpGwAc7x48eh0+nQpUsXVKhQARcvXkSXLl0wduxYTJgwgYU0BDYYHx8frFnDq1xfvXoV7dq1g0QiQbdu3fDkyRMWurp27VoplhlL9OjRAzt37kSvXr3wxx9/oG7dumx5Z2dn/Pjjj+y+evfuHezs7PDiYCwSXWparUeIJBjevwIZDeAkUnY/yVzLbnFRyGRo2rTpB/dNwOvXr1kj97hx4wDwLCX79u1DcnIyNm3ahJ49e6KwsBB3795FnTp18Mcff6BDhw64desWpFIpdu3ahfnz50MkEuH69etMtUCr1eLXX3/FzJkzERERgQsXLvxltRSz2cwMYW5uLurWrYtvvvkGLVu2ZPN1Oh1mz56NjRs34t27d1i5ciWqVq2KL7/8Enfv3sXw4cPh4uKChw8f4vHjx5AEN4R3dD+gSE3cudUYtj27Wu1hV6t9qf24f2gB+5+KXuTVq1eHXq/Hvn37UFBQwCR2Tp48CalUirCwMGi1WiQlJUEkEkEul0Mmk+FGzGU4Nx2CwrfPkH1lO9Rhn5WSldJE8OHwjFO/IffmQdiGt4Jjs2EwZCYhadUQcCIxvEdvZQNEAEhaOwqG96/g6ekJFxcXNmCwnFJSUvDs2TOr0GZ2djZWrrQmAnB2dgbHcazEn+1XnS5wiO6D9OPLmHSU2MYJ9o36If1QEQuO2QRVYN3igbZRB06qBBkKrQbvnFyFgsfnofSranHBTVAF14Pck68eFqs0xeTY+kK+vSPsM0icfJF+6BcAfBjYEpbvGEtPTXhPlEWaL5FIcPToUUyaNAn37vEhbycnJ8yYMQMmkwm3b98GwFPP/e3427OGRJSQkMCS6mVVdZZMVqakpFD//v3J29ubbGxsKDIykg4dOmS1TN8Bg/ikqlJDvpMOkfeozVYJUoVfVXLrPotsa7bnP1eoYZX8tZo4Ecm8Q0mk1PwNyWV+0tTpwv53/Hwk+U0+TOqwxgTAquCGkyqK9oEjTsJXNbFqM0dv9tmmemur9Ts0GcoS66KiQhQAxClsSFxUZSVMr169skruW07eveaQW8+fP3gcyop89RUnkZH3V1vIb/JhcukwtWi79iR19CalUklcUaL7119/Zdfo9u3b5OXFV8TJZDIaMGAAZWVl0fLly8nFxYVV6go4e/Zsqe337duXxo8fTwCoX79+RESUmZnJvq9QoQIZDIaPFresWbOGP2cODvTgwQN6+/Yt2dvbE8AXFPTt25caN25MEomEXr16RSvOvShV3OI3+TAp/MP5Y/EMImWFSD55r3Eh3/F8sYtbz59JHdaYZB58MZfG0Zn69u1Ls2fP/ujzYVngkp+fT6tXr6aqVauyoqPIyEhq3bo129+aNWvS559/Tr6+vrRlyxa6dOkSeXt709SpU8loNBIRkdlspoMHD1L58uUpKiqKvLy8KCcn5195fEvhypUr5ObmRu/evSv1nYuLCwF8oUpubm6Z1bV3EzIpaJr1+XVsOowk9u4EsYQkjl7k1Gos+85n3B6+GlEitbru/fr1Y4VuIpGIlEol+164DydPnkwAKCgoiPr27Utubm4EgAICAqhjrwEkVtsXPWNiq6IOy0nuE0YArPZJVPSMefRfbLWs1LUcAaAZM2bQnTt36MaNGxQTE0OXLl2ic+fOUffu3UmhUFB0dDSrYgT4IhCOs343qdVqVtzh4OBAIjFfNSm2c+MrMouqKAGQa9cZpQr5XLvOJFVwveJnObCOVWUnAFKHNSbPob+Rukpx8ZrY1plsq7cmh6ZDS50Lr2FrSKSyJ1VQFCkDarHfVGnRg4iI+vXrRwDI2dmZAJCbmxsrpFuwYEGZ95Pw3Pv5+bF5JpOJgoODCQA1bdqUGjRoQACoZs2af8s9XBJ/ix5fSfj4+GDjxo1ISEiAVqvFkydPEBkZyRpMSyYqXV1dsXbtWiQmJiI3NxfXr19nxQgC1q9ZjcEbb8B3zFY+FKO2h9/kw/CdeAA21VtBl/wMKdu+Qe71fZB5BEAdzCstS5284Tf5MPwmH4Zt5BcA+ES1zNUfVBSjl3uHQqwp9prk3pXg0Hgw++zn54c7d+58lLZMpLSBpEjdIefGfqQfXwpjdgpcOnxrpRju2GQYz79HBCIz3y9jNgIiCdy6/QRNrQ6A2Yj8B6eKV86JoXv7uDinYJFjIr0WtkprD/Prr79G8+bNmVdVu3ZtjB49GiN/XgOxSoOU7cWacjIPfpQn960C30mHICpSrVZXashERwViYmX5Gig//DcsOP4A7dq1AwDGpA8A4eHh6NSpEwCge/fuWL58OSZMmIClS5fi8uXLpeiIvL290bFjRwC8Bt3o0aPRrFkzphz+9OlT5OTksNAZwIfPVqxY8cHrAIARHGdmZuLzzz+HXq/H+fPn0bp1a0gkEmzZsgVv377FiBEj4OzsjE4RZfcCOrcdD1WlaBjS30Abfx8K/3C4dZ0OTsKfb2NmMvIfnmaeYE5GGjZs2PCnLBaW8PX1xYEDBzB37ly8evUKPXr0wLNnz3D8+HFIpVLUqlULcXFxaNCgAZ48eYL09HS0b98eK1aswMyZMyEWi/H8+XO0bt0aEyZMwC+//IL4+Hhs2LDhk4gDPgV16tRB//79MWzYsFJab0IePy4uDuXLl7fKWQlYdu6FFTtR/uPzyPhjJcz6QqhDomEuyEb6kQUofMnzj8JkhD4lDlJHn+Lf5Ofj4MGDePyYF9UlIlYYAQA3btxAaq4WCxYtAQAYnSvi5INEZJn4a+Xo6IibF09DLePvV06qgO7NI6Rs/xZpRxcj49RvyLrE95sK+V3uL+R3n+fJ4FMxhEWwoqKi8PTpUxw/fhxarRbnz5+3EhMWyAUskZ+fz7zzzMxMqIr+J20uCp7HQOrix1hnJHausK/fEzZFjfAipQYK/6pMKggA5D5hILPJqrgOAPRpicgviuoAvMJ87u3DyLm6m50DdtxyFeQeAdC9fYLCuJtF50WOZXN/AlBczCYQMKSkpLBCur/iqYlEIhw9ehStW7fGlStXcPv2bXTs2LHMHt6/A/9TzC0l5YkyTv0GMpsBTgR15SYgXQF0yU+hT34OY1EY0pibBrNBC5FUwTStzNo85N05CqGC06QrgFWcvgxKo2rVqmHQoEG8QrRIDLFSA7lvZTg0GgBOJAYnV0EdXB9Z5zdCm/gQeQ9OQ2LvBrGttSad/v1LmLV5fDzeqIe5IBucVAEyaFEYdw32DXqj8OVtpgAvUmpARCh4FsMkY0QqO5gLc/l9NhtZLkPA/v37cfjwYfZgJScnIykpCcnSMKTfPGKlIyZ19oH+/UvoEu5D9zYW+Q/P8ufIpEfGqd9gF9WdPewiqQJaoxmxybl/mnguLCzEZ599BldXV8TExJT5Eq5YsSJGjhyJPXv2wNHRkTW+JiQkYOXKlbh69Srs7OysftO3b1+W+3O1CPGWbBwXZJkscejQIaSnpyMkJAQ7d+5kuUeF0QhH3Tskc86AxeBGrLKDS9sJZR4fANhUaQKbKk3+lMpLgNlsxqlTp7B06VI4OTmhf//+GDRokFWDeu/evXH58mUEBgbi9evXCAoKwq5du2BjY4OBAwciNjYWMTExKF++PPLz8/HTTz/ht99+w+TJk7Fv3z4MHToUbdu2RePGjT+6L0BxBd2SJUuwYMECpKeno2PHjli6dCmUSqUVw8qqVatQo0YNNvgTGHQErFu3DmPGjGEVw0JOLi1PV0QKX7zd7Bi+kMix2XCog6OQe+8kMo4tRvbVXVCWj4BIoYb38HUwa/OQuJDnLHXz8kXV0GBs3LgRAG/49Ho9qwc4fe0+an23D7pCvoIy7vIRq2O9+ygWqzbuwKt7V/Hjjz/CNqAmcp9eBRm0zAiINa6wr9cdYrU9jBlvrFURigrUPpTfPfowGRdnnYKbRoFmldxg/+YqFsyZiWvXriEgIACTJ0/G2bNnER4ejlWrViEgIAAXL15kYs9AseyUACHHJSYjlMENUJj8HCAzFP7hkDryJA9OzUcyVhUAUFdujOxrvFySNu4mCp9dhSknFTKPQHj0nQ8AeLep7HvalJeOvPt/wL5edzZPrLSFa+fvAYCRWDs5OaNemD8AYNGiRTh16hRiY2PRtGlT6HQ6XLhwATVr1vxgtXbDhg3LFMstV64ck7P6T+N/yvCVlCeyLEgoCZFczWh8UjZPgtTZF/lP+OR3sZHjT74x9RW8hq1BwfMYZJ5eDQBwq9seg9rUxy9jilW5v//+e2zauh2FeTmQuvpDJFch/cgCK7Zy5zbjPnoMnJTPcVi2SQgPWO7dE5DYuUET2Q7pR/kiDIdG/WFThc8bJS7gXwKWxrJ69eq4desWXr9+zQqLyELVGABatGiB6OhorHwMlpcUYOlZmrW5sKvTGdmXt6Hg0TkAgKZGO/awC4UeOVrDnyaeDx8+jIkTJ2LatGmfRPBtCV9fX8TGxmLbtm1ITk5GjRo1MGHCBMTFxSE8PBx9+vTBN998w5hJ/gqcnJzw/fff46uvvsKZM2eQmZmJbt26Qap2gyKsh5Uk1KdCoPKyJB2Pe3wPb26chINKDn8HGV4+f4p79+7B1tYW3333HbZv347c3FyEhIRg+/btqFatGsaOHYvTp09DLpfD1tYWf/zxB6pWrYrY2Fg0btyYFbgoFArs3LkT48ePR4MGDXD//n14enri8OHDuHDhAsuXfCpmzJiBVq1a4fDhw1i7di3s7e1LKSjI5XJs3LgR1atXL3Md7u7uuHnzJgICAqDVajF37lw0bdoUq29nw2AqPqdkNsGQyldryz14xhq5O0+Dpn//6oP7+OR9Ae7d4o0ex3GYNGkSmjZtipdib/x68hnys9OQl1zs2SiD64EDoHvzGG4954ITcZhzhxCSlAUA8BLn4EnRANC9zzyW3wL4HK4u8SF0yc9gU7kxr0uoywcnVUDiULb8FhFPdJ+crcWGq69BZlc0+GYTChQu+Pnnn3Ho0CFMnz4dffrw75O6devCzc0NBw8eROfOnfH+/XtIJBJ07NgRu3cXVxivWbMGy5Ytw5PYq5ApbCCv2gxujQfAstRE4IatW8EJl16kwbXzD8j8YxW0CQ8AjoMqqC4cmhTXLRhzy651kHkEQu4VjIxTv7F5dlHdIVbyg1aZhPeW1fJisyF4al999RXOnj0LjuPQsWNHK/Lp/x/xP2X4AGvxVv8ph6FPf4uMkyugf/8KZm0+xCoNlAG1YBveEupK0cg8tx7a13dheB4DmVt52EV1h6oiX8iQdpivurSt0RYSeze2DZGIQ7cgOeYMGsLmERHS0tIQXKkynqTpoH/3AtrER3yvHsfh7cqB0NRsD4fPBn50/yW2TkUbKV0pZUiJgzb+PvIfn+erU4mQdXEzlIF1IFbYQOrsy4c8wUEkEsElOALl249Fn9+vQK0srpQVSySw09jBYNAjNzcXL168gFwuR/az9zAXJbltI7+AY+NiMlxD1jtI7d2hqljTKjQLFBdz6JOfgYhw59plvDjDF+akpqbi/Pnz8PLygpeXFwtF1apVC99///1Hz8WHQESws7PDyJH8SPbs2bOIi4uDWq1G7dq1UatWLQQHB+P69euoWbPmn6ytNIYOHYpVq1axXtF27drh559/xvabb/4lzce+dfyw9Kw16Xje/XtIP1aaqq1du3YYNIg/7/369UNOTg46d+4MsVgMe3t72NraYt68eWjTpg04jsPu3bvx5ZdfYvbs2Rg0aBAePXqEUaNGIT09HVu2bEH9+nxIPyMjA8OGDcOWLVuseik/Bb/99hvatWuHAwcO4IsvvsDGjRvLVHMPDw9n/5c1Yvf29kZ4eDiuXr0KkUiEmj3HIb+wOLwn9wiEqSCbDTyF8KHwl3T5IKMenITvY7SsYnb09EdEFT9cuHABubm5WLFiBVbvOIQCqQa6t09gW62FlfHSvb4LZfkakPuEIWX7N1D4VIak9VhceM5fo5exDwGzEergKKvfvdsyme/T40TIu3MMpMuHLomvFLat3ooVtmRf3QVD+htWKZ53/yS0CQ9gU7UZFD6h4EQSXIrPw7UVl2C4/hD9OnfGyJEj0blzZ8YvCgANGjRAbGwsypcvj5SUFMhkMtSoUQM3b95E69atMWDAAAwYMAAAcOHCBYwcPxkj2tWw6rkUuGHtlRKENGyH5BvnQLr8D76PBMFcS7xZPgD65GfQJ1v3y2pqtAOUtqhT3hFTRgxBlY0TS/32n/TU/i78Y4ZPIBUGgEuXLrFevosXL6JBgwYA+Fya0Nf3MViLt4pg22tWmSN1scTeqnqsJJxbj2WVXTk3DiD/wR/gOBEK4x9gZr/PYTQa0aRJE6hUKlaSnZ2djfCvViCZc0b+08tIO/AzREoN1JWiIfcJK35wSu5LkcaVWa9Fzo39MGa9g9wrGFIXfxhzUqFLeAjXzt8j994JmHLTYFe3K8hkRM61Pcg4uQLOLUfDpf0UJK0ZAXNhDsQOnshTuODgsh/g1OIryNyK1RZcWo5B+pVdMOTy5/vUqVM4dYr37GRuFQCRBLkCIa9KA0P6G+jePIHf5LJvXmVgbUicvGFIS0Dqzu9gEOmQm5sLd3d3xMXF4dtvv8WzZ8+QmprKXogxMTEICAhAcHAwWrVqxQyjl5cXXFxcPuoF5ufnIzg4GI0bN4bBYGBx/h9++IGFTOfMmYMRI0bg2rVrf9mjlEgk6NKlC8aPH49Vq1YxQ9Srtj8ys7Lx66k4iGTyj5KIC5JDTUJcseFqfCnScSEMWmr5IomsS5cu4dAhXi8tJycHcrkc33//Pb788kvIZDIreanjx4+jYsWKGDt2LLZs2YLvv/8eQ4cOteK5HT16NDp27Mhaf/4KQkJ4zkahfzYtLc0qHyVAaJEBgK1bt2Lq1KmllhGa7zOkzlDV6Yl3c79g35nDGsMmvDjPS3otoNSwPldOrmZGr9R6lWq0a9cYISEhWLp0KUgkQUbCMxAIMJuQfXkbnDt+C3V4C+TfOwmzNg/5j88B4EkYFOV4oy1EQnQ6HTiOQ37sZeDwAvYeUAVHQeZWHhIHT+TdPYb8osiHbfVWsG/Qm+1P4ctbVs+57s1j6N48RsGLGJBBD7HaHuqQ+rCv3xviiE7YcesIrl69ivXr1wPgIyIKhYIpEhw9ehQTJ07E3r17IZFIYGdnh8OHD4PjOKYpuHfvXnRu08JK+84SO3fuxPNLRyBWaqCKaAO5D88JbCrMQda5DSh4cQ1mbR7EagfY1eoI24jiOgrBGBa+vFWcawWQd+sAInwd0De62z+iMvJP4b/i8a1YsYIZvpIlvZ+KKt72pVgnLr1IRWpeGUwrnwD9uxdwcHCE3pCNzMxMVpZ//vx5tGrVClqtFoWFhbCzs8Orwyuh6fAdsooUHZTlI+DYdCgfIuA4SF2LjZApJxVmbS6kRSESkUwBt24/IfPCRugSH0Kf8hJiG0eoQxvCmJOKgsfnIXX2hV1UN4jBwfT6JvIfn0dBhUjYhDaEe8+fkXl+A/RJT5GflgCJo1cpscrCzGRwYgkkTr4wpidAaAacNn0WNuQEQ5f0DFmXtkKX+Ign4rVzg6ZOpw+eG44TWYVPcuQSFs7w9PREWloaIiMjrbyAwsJCvHjxAmq1Grdv38ahQ4fw9u1bvH37Fjk5OXB3d4eXlxcjNsjJycHWrVtZWbi/vz8OHDiAwsJCBAYGYsyYMRg4sHj02qtXL6xatQpr165lhutTQEUqECtXrkR0dDTr8RPw9PBqNFG6QlqpJc4+TQUHWA2qLCWHyjmrsf7K60/yEImAQoMJPx19ApPJhDFt2rBGdrFYDL1ejy+++AIymQzJycno0qULNBoNbty4gSNHjqB169Zo3bo1Hj16xFoXBOzfvx8xMTFWjDx/BU+ePEFgYCBiY3lyB2dnZ8jlcpbHFRhXhEZsAJg3bx66d+9eemUCvKsh7dTvEKnsePIFtwqwrd4Scs8gSF38YUh9jfe7foAxJ5X1nn2oTQQAPEJq4MqVK4iLi4ODgwOMdQbA/PI28u4eg9TFDwq/qhDLbWEqzIOQuxfue3NBNnJvHYKyfAR0CQ8AAApbe8CgLboGfKEZAGgi2rBtqipEMlFYscYVSauHwZibBomdG+zqdIF7zzkA+LTF+10/Qht/D6QrgEhhC1NeBnKu7QWIoA5thJSH1xEaVhkF+XyKIDs7G127drVSJBDU6D/77DNIJBLcvn2btQlQkerEsWPH2O9HjhyJq1evIikpCba2tiznXTu6MdIjB6PQYAYZDUjZNhWG968gdfGHKqA2TPlZMAiN+CWgextbKoV05gZQP8z/H9PK+yfwj+nxCR6fg4MDCgoK8ObNGxARfHx8oFKpkJmZyTy+Hj164MKFC0hNTYVMJkNkZCQWLVqEypUr48KFC2jUqBHc3Nzw+PFjmM1mhISE8EoEvX6GyCO4zO2TyYCMkytQ8OI6P+pR2UPmVh6OzYYj68JGXoYjP4tVerITxHFwdHS06lMBAJlCBb32zxtPBbh0nAaZW3m8Xd4fIpUdvEdtRvalrci+vA2qoLrgJHIUPLsKsdoBjs1HQOVfDV1qeCP2XS4evM1mQrkCcm4cQO6tQzDmpkMkU0Lq7Aun5iOZcoCwTObp1VD6VcbKrQcwulV1SBoNhyqgNri/6CXx56J0Ecfdu3fRvn17dO3aFT/99JNVlaeAkswsly9fRlJSEjOElv9bzlMoFFaeouXk6emJjIwM9OrVC7GxsawB/GPIz89nkk379u2DXq9HREQE7ty5A19fXyQkJCA8PByxsbFwcXEpk8pLCCu9ySxEt9UxrNCqLBizUpBx6jdo4+8BIhGU5arDsclQKGzt8WbDeMjykiGTyZCZmQmTyYTevXtj4MCB6NGjB4YNG4YWLVrgq6++gslkwtKlSxEZGVlqG2lpaahSpQp27tyJ2rVrW3mBzZs3x4kTvHjpnTt3UK1atRLXkzcQbm5uaNWqFQ4dOoTU1FSMHTsW8+fPx6lTp9C0aVPI5XKMGDECR48eZcZxypQpuHz5shVLR8OGDdk6JQ4ePCMKx0GscYUpOwWcTAn7Br2RKeSQOBE4hS2o0LrJm5OroPALR+Gzy2xeePTnKEyJZ9t3bDEKOdf3w5ieCImDBxT+1ZB//1Sp59cSYhsnmPLS+YGiRAZzkWoCJ1OCDDp4DV2NtCMLoEt8CKeWY6DwrcwMX/HOFWviiTWuUPiEojDuJl84J5JA6uRdVJjGG12R0hZyrxDo3jyBo4cP0l7xqYCRI0diyZIlePHiBQICAqBWq/Hu3TurMHW1atVw7949rFu3DmFhYejZsycjhXj9+jUqVKiABg0aoGLFiti6dWupRnj3tl/DYDQi/ehiyH2rwK37THB/okX439CS/G/gHzd8Y8aMwcKFC/Hzzz+DiDB58mSMHTsWCxYsYIYvKioK/v7+sLe3x8OHD3HhwgUEBwfjyZMnAICJEyfil19+wcCBA6HT6bB582Y07/UlXvq3+aCoa+69E8g4tgRSZ1/IfcJgysuALvEhREoNjJlJkDh6Qe7kDe2rWzAZrXNvAh1PSag19sjPyQIAqILrQVOzPdKPLoIhLQEeA5Yg78Fp5N7Yz69jyEoY3sUh7eAvUAXVhUv7b5B1cQtTMVb4VYXZoIU+6SnEGhd4D18HMQeYyrg6QkOtSKmB3DcMusRHfMGLTAl1SH04fDYIIrmKGT6IJeDAJ6LdPL0hajQKYveAv3wNzYn34fTsAGIf3INWq4WtrS3y8vKYp1ey0g/gK0q9vLxARKhUqRKcnJxQvXp1vHr1CrGxsXj79i3UajW6du2KuXPnslYGIkJGRkYpY1jSQKanp0OlUiEsLOyDBtLLywtpaWn44osvUKVKFaxatQoKhQJGoxEzZszA06dPsX37dgwdOhSOjo5/qgWm1+vxxbyjeJwt/qCoKZEZyWtGwpCWAEW5cJDRAF3iQ8g8g+DR51dUdxEjKPUCzp07h+zsbDx58gQRERF48+YNlixZgtOnT2P//v2YNWsWmjRpgmnTpuHcuXNISUlBuXLlsHHjRnTu3Bnx8fGIiopCZmYmYmNjYTKZkJqainbt2uHq1atsf5YuXYoRI0YgNTUVrq6ujMJOgFgshlqtRrNmzbB79264uLggJSUFtWvXxvXr19k5FqjV1q9fj9WrV+Px48fIzMwsZfgEiJQamAtzIHHygTE9EcqKtVD44hok9h4AmVn1NcCriHMSGZ83ow970RK5EkaDNekDACj8q0Gb+Ii1/XwqOKkCYhtHmPRaUH4x76RIZW9FTcjJVCB9gTVjiuV+2XvwbE9FhWcl4RTdC+nnNwPgz1/fvn0BgPGQqtVqiMViVK1aFbNmzcKXX36Jhw8fQq1WQ6vVwsbGBl27dsWqVauQk5ODhIQEhIXx4cy5c+di0qRJAIDAwEC0aNECkY3b4IfZv+DF1RNQ+oRCn83n+BXeleDRYjjEdq4o56yGh50SYhH3yVqS/xfwj4c6o6OjcfLkSfz222/sZdigQQMsWLCALbNz507s3bsXb9++RZUqVXDhwgXExsYiKSkJnp6emDlzJk6cOMGYPqpVq4aKzfvhycPSlGQMRfkJqYs/1KENIXX2ReGr20g/MBdiG0fY1e2K9CML2QMnMEIIVE2W4DgOV69exbFjxxgbgVgshp1vCPJ8wmBIS4Du7RPkFeUHwImgfxP7QUJtqbMvXLvNhDE7BUkrB8GUk8oXAaisS/lLHotIZQ/t63sgXT5UQXVhyEpB3r2TMOu1cGlXnIQWydVQB9WFKPkRkuJfwun4L3AZ/PtfLuKo5WHE/cd6hIWF4ebNm8jNzUWDBg0YVVRZiIuLY4ZRKHwRQjpisRi9evXCkydPsGTJEhgMBtajx3Eco+SqUqXKB9c/bdo0zJw5EyqVCl26dMGWLVuwePFihISEwMXFBQ8ePEBmZlE7hkiEu3fv4sGDB0hMTER6ejp27NiBX3/9FU5OTsjIyIBSqcTZs2cxZ84c1m8qiNyOHDkS+/fvx9u3byH3DoVTq7FWRVGWKHx+DYa0BEhd/OHaZTpAZrxdORj6pKfQxj/AI0k1rJ76A2bPluPLL7/EkydP8Pr1a4wdOxYjR45Et27dEBsbC5lMhmrVquH58+cIDAxE7969ce3aNfTt25cJn16+fBkRERHo0KEDzGYzmjZtinv37sHd3Z21m4waNQrVqlVDVFQUKlWqxK6FAJPJhFu3buHmzZvYvXs3GjRoAI7j0KJFC1y/fh0FBQWwtbVlLEvTpk3DmTNnULt2bTx48AAvXrwo1XsrtnODY+PBSN07kxWBGItorsS2TnDvOQdJ68fA8O4FwHFwaTsBUmdfcAobgAMSLfKDlryWRl0hxHauMOWkQ6ANlDj78ffZJxg9iaM3zNo8C6PGwZiZBE5h3XJjLrD2RMUqexj1BRDbecCUZR0i52QqyL2CYMxKtjKKqpAGEKvtIVLYQu7qz+ZbenZC3jEqKgpJSUm4ePEiWrZsySj33NzckJ6ejtDQUFy5cgUAT/clGD0AVt58rVq1WGvQhiU/4wUA7dsnCKzzOdKTXiMt7gYMx+fi+p07/+cN3AfxH2mLLwMC08a+ffto8eLFjAFgyZIlTJLCz8+Pnj17ZqVhZTndvXuXrW/t2rVs/tq1a6n/+usf1RXz+Xo3qYLrF7OlgGP6dnK/qiRS8HIqUg3PQCBT8vuwffd+Gjt2bJn7o9EUM7+EVa5c5jIldQEBXvLIvmE/gsDiIhKTbUQbcmoz3uJ3YoJY8lHdPkuZEHAi0tTrUSSFxM8XdMXkPmFMvglFrBfrLj6j4GnHSmnQOTQeXMSoISVOKidIZASJlDz9KtD8+fMpPT2dMSzUrVvXilWlpFbeX2VmkUqllJyc/Jfuq+vXrzPWC7PZzCRvoqKiiKhY0mry5Mnk6enJjj8sLIzKlStHrVu3tpJpEjTdZDIZDR06lGbPns3uXQBUsWJFcvXhtd5k7hU/eL8JrBrqyk1KaaM5NB5MQd8epZXnX9CDBw8Yq4yDgwM1aNCA7t27x45P0Kvz8PCg/Px8IiqWhxImHx8fJg91+fJldozZ2dlWy3Xv3p2IiL788kur+V5eXiSTyWjdunU0cuRIAkCLFy8momI5mdDQUDKbzfTy5Uv2u5iYGIqKiiKRSESenp7UrFkzq/VKXfzIc/BKq3lie3d2T/LMJ+Wtvgd4SS6vkRvLfp6spjJYmT7he7G9RzGDksUziRJMKlK3Cv/CNi0mC0kzTq4ikbJYsik0NJTS0tKIiNj77s6dO5Sbm0tqtdrq/VKnTh1ydXWlnJwcxtRjiXfv3jEpOOEZE9CjRw8CQC1btiQispJK+mnHBRq9/Tb1X3+dRm+/TSvOvaC0XO1fev7+V/EfYW75M/Tp04dVSvbu3dvquyNHjiAvLw+VK1dGVlaWFaM5FY2ksrKy8N133zHG+2nTpkFm/Hi+jROJ4fLFJPh8vROeg1dA4V+NV10HYEh5yZrbRQ58Y6jQezR+fyzyq/ewXhfHtxNYhoq0lqzqFpDYuVrP4EQgfSGyzm0AhHAIEXJvHUL6oV+LFxNLAZMREjtXkL4Q2Ze38W0OAEvECyNLTq4GyIycKzsgtvcEQOAkchiLim90iQ+Rdng+W/e4cePQr14Adgypjc8ruUEuEUEhEcGQmYTM06th1hVA5uwNMujAmY2Iqh8NbW4mvv76azg7O7Om4bi4OOZNlYW/ysxiMBhKeSJ/hurVq8PW1hb5+flYt24da/6+efMmBg8ejNjYWIhEIkyaNIkV0kydOhUPHjzAy5cvcejQIZw7dw4ikQgNGzZE9+7doVAooNfrERcXh/nz5zMmCo1Gg7dv38K+QS9e9frdC+hT41H48hYyTv3GJlNhrlXTvwCRBfuH1mjGsav3EB0dzdg6KleujHPnzll5uGWpnQgegnAeV6xYgVWrVgEAfv2Vv4fKlSsHjUZjda4s1U4sUadOHVSvXh2XL19mHkXJZapVqwaO46wI5oVqXbPZjKSkJJw8edLqN2a9Fob0NwCKWVBEcpXVMiK1Hf+PWArPoauhDvsM+uTnyLt74oMVnsWgf+l7U1ZyqVAk6QtRMnwpyIoJsKne+oPrFNu5wan113wbkpjfb2W56vCbfBiu3WbyXJkWYfFXr14hNzcXz58/R15eHlMkIIseXCcnvvUpJiYG79+/h4ODA/r06WNF2P3y5UtERUXh+fPnZTaMC/dSQkYBxuy4gwHrr7Pv1l5Lwv67STgT+x777yZh4alnqPvzGQzdfBP3ErPKPM7/K/ivGD47OztcuHAB58+fL8XMIcjbPH/+nL0oS2L48OF48+YNJk+ejHHjxuHt27e4tW0e5JKPlMg/Po+3q4ch/chC5Nw8WMyMonZkRg8AdIm8yoFQafZm82T81ru4qEAqlYKISoU/rYhlueICD5HM+kHnxNIierTiB0gs9PZZQFaUgzNmJkNsx5+T7Cs7kXHqN+SxpvOifIrwgjCbwImK5pV4aIV8iNrBhVXUCpWxVyZ9hrFNA9EkkN8PRxc3UNGg4OyZMzj/x3F069aNHb/QO5eSkoJvvvmGbWLDhg0YM2YMxowZg+nTpzNmFgCMmaVHjx4YPHgwnJ2dGTOL5TX+qxIkYrEY9erVA8BTtb179w5DhgyBTqfDtWvXYDabUa1aNdjb27PfWMpipaenIzo6GmazGefOncO6detYtWVmZiY2btzIeuV++eUX5Ofno27jlhAreaNiyk1jlXDCRLqCUk3/QGn2j5v3HoOI4OnJU92VK1euVI6spNoJwBscuVzO9rNz586sYViQf3n9+jVatGhhtS7BaAktD35+flAoFGjevDmioqJw6tQp3Lt3D05OTlZhNICv7Bw1apTV/CtXrmDHjh2Ij4+Hvb291TkGeLKE9GM8EYNwj0tsrStSpUU0fzAZ8G7LJBQ84/OSnFgMF4/iQi1LhQ6uSIGFsyCLln6gItSSdkyAQ+PB4CQlQnwliOUdPx8BVWBdq3l59/8ocxtA0bEens8/Z0UDU1NeBl/pXdQob8n6otPpMHXqVLRq1QoAr0igUCjQr18/6PV6+Pn5MUYmpVLJ6h62bt3KFCnu3r2LunXr4tWrV1i+fDlrCxNw/ul7HDOGQqRQ4+G1C1g9fSxOzufbNpQVImGUWVeDa41m6IxmnHycgm6rY7A55vUHj/d/Hf8VwwcAERERiIiIKDW/S5cuGDhwIKRSKU6dOoUpU6ZYfb9z505s27YNlSpVwrRp0zB9+nSEhITg5ulDyH1UtvwFAEidvCBWalAYdxN59/4AxBLY1e3Ky/GoLCoCWVN52SM7YTRmqfcFwFp+hIqT7vqUF1bLkVEHU6616Km5MAcloUt8ULzNIq49Q1o8cm8ehP6N4BXx+0gW/IHmIoNNuvxS6+RkShRkpaNTp05W/ZJONnIMbVABP3aojgoVKiA98QUMer6Pq3379hg1ahT27NnDjlvg4wSKvQgAOHbsGBYtWoRFixZh7drSTbICBGaWJUuW4JtvvsHevXtRoQLfm1SyVP9TYNm7JhKJsGjRIiZ+WvJ7wFoWa9u2bSgsLIRGo4G3tzfkcjn7/ttvv7Uq4X7y5Ak4joPMmA9T0TUT2zrDvn5PxgfrN/kwJPZupZr+LTkThe9sZCKcP3+eGe6yIKidJCcnIzw8HL1798aMGTMwc+ZM+PjwXJZGoxGTJ0+G0WhkfXQmk6kUZ6igGefm5obg4GDEx8dDq9UiKioKUVFReP36NUwmE8vv5eTkMF2906dPw9nZ2UpiRtiWUJltSZ0nc+Ovp1mbB7GdK4wZb8HJlFD4VwXAPwdphxdAl1z8fJjzMkD6QohUdujbtx/Wrihm/7C8ZlQ0iCND8TNo+ADri6VnpyjPVyNnnv69tNZmidxgxskVyLpcgoCgDH1OmUdQ6QKnoneIPvkZcm8ehFjjAomjFwxpCVaLbd++HTk5ORg3bhy++eYbtGvXDnv37oWjoyPi4+NZNKWgoACXL1/G27d8BMfOzo4N2FJSUlCpUiXGCwoAiSnpaLH4Avquv4HXeRxcu86A3CuYpy/LS4dNteYfZZiybL35P2v8/quB1r8ZgzfeKJWz+mjeb9xulueznDiZiikhlJo+NP8TJoXAks6J+O18UB2CzyM4NB1Gioq1WJ5QpLIjz8ErybHl6I/kHTgCOPIcurpUjsK53SSWuzxz5kyp89e9O5+Xatq0aal9GjhwIAEglUpFNWvW5Pef42jTpk1smZI5PqKymdjNZjMZDAb2+cyZMwTwebp/RVEgJibGal/nz59Pbdu2ZZ8PHDhARFRK0SE7O5uCgoLYcuHh4SSRSBhD/r59+4ioWPlBJpNRr169yLNcIP/ZrQL5TjpU5r3lO+kgSZx4tQ2Ffzhj/Jd5BJLf5MPkP3E/udf4nMRiMcsruri4UKtWrWj58uVWx2epdiISiUgqlVKNGjWscuFOTk5kNpuJyFrtRPh+0aJFVuscOnSo1e9SUlLYsl999RX169eP7O3tKSQkhABQnz59iIjKzOnOnDmzVF7eY9AKsqneildAEUtJ7hVM7r1/YefHrfusMu99scaVfMfvpXVbdxERsfvL39+/zNyZMDk0GUoeA5d99PnzGb+XV0wRS6zW5dR2AtmEt7BSP+CkClKUj2Cf7aL7sv9Fts7sf2VAbZJ7h/I5wqJnu+SxunaZXub+WKozhIWFsfMsPA8Ar+Igk8lILpdTQEAAy73WqlXrg8fp2Wv2J78Dy5o8BiwlmXtF9t7xL1+RNBoNaTQaql+/Pl28ePEvP6OWOHPmDNWoUYPkcjm5u7vThAkTrN4H/wT+ax7ffwK9qjkh+/Rqq3yLJet6SRTG3WR5Pitw+HB12F8slYbIIuQohLGKQiESjTM/W15SaJUAAJl/rIT2xTU2gjQXZCN5w1gY3r8usU6y+q3CvxqkDh5Q+FiHq7Ivb4O+MA8uLi6Ii4tjYckxY8YAKG5UTk5OZvkjATt37gTAjz6FknYAmDx5Mvt//Pjx6NevnxXRblnIz8+Hv78/+vbtix49eqBly5YArJlZ/grCw8OZ9xEREYFjx46hbl0+TMVxHAtVCkhISMCoUaPg4+OD169fo1u3bnBwcEBiYiLatm1bKoxteayvX79G5rtEKH0rw7n9lFKhSQFC07+yQiR0b59AnxLHt7F04NlOZDIZejetAZPJxEKWqampOHLkCKvAHDhwIJYtW4Y3b95g5cqVmD17NipVqoRvv/0WeXl5MJvNUKvViIyMxI4dO9i+WKqdCCgZBlu5ciWj4eM4DhzHYd68eQgJCcGJEycQGhqKp0+f4vFjPhwr0GzZ29vzHiwR/P39sX79esyYMYNxtwow5aVBJFNCJFeDE4lARgNTPQAAuU8o7Bv1h8TJG5xUDqmTDxybj4TPiLWo5WuDmdMmIzg4GCNGjIBIJLJmdCp6Bm1rtIVr5x8AAFnn1hVpSnIW2wiDKiSafU4/soBXdRm7E5+16woAkKjtYVMpGk6fj4BzqyJ9PokMYo0L338JQBlQC9nni2nGzBYRG04k4kWLBQFsMkNTpwvkXiHFy4glENu5okLtZhg6dCi8vPg6Asv77OHDh1CpVNDpdBg2bFjxbzkOv/32G3Q6HZ4/f46vvvoK5cqVw7Vr1wAArVu3xujRo/H8+XNsuvoKgd8ehdTbumr8ryLz3Dro372A3KMiOJkSWVojqlevDoPBgIsXL6J+/fro0qXLn6+oDMTHx6NFixa4e/cuOnXqBI1Gg19++QXTpk37t/b5L+MfNbP/YVjqnFlNnIg4uZrUVZqSz7g9VlV3wqQKaVA8Eiuhb2epZ1VyEhdpZgmVWCUnkcJiJCyxriST+1YhACSxdytjOx+uHpN5FnkpYim5913AvAlhsm/Qh/wmHyb3fgut1iO2daJ27TvSgwcPqGHDhla/GT58OJ04cYIcHBzK3Ka7uzt16dLlg/tkOVl6fmV5fFqtlurXr092dnYkk8koLCyMfv/993/pmmdnZ1ObNm2ofv36lJKSQnq9nipVqkR79+61Ws5oNNKBAweoadOm5ObmRt9++y21atWK5s6da7WcwWCg0NBQ2rNnD5tXlsbcX40uWE7+Uw7T0E03PnhMBQUFdO3aNVq+fDkNGjSIqlevTgqFgsRiMbVq1YoWLlxIFy5c+Lf19kwmE504cYI6d+5MdnZ21LdvX7p48SLzHP8MR48eJTc3N+rXrx/JZNZemNK3yMN1q0Dq0EZF2pccuXWfRX6TD5Omdif+3nf0JnVYYxJreF0/j7Zf06ELt6hGjRrMK/Lw8LDyjgRtRE2tjkwvUuYZxFchoziiIvcJI4fGg4ueFQnz5Dw7f8c8SImdq7UGY7nqZT9zHoGfdO/LPALJY9Byq3V6DllFqnLh5ODkTFKplDw8PGjYsGHk6+v7Seu8dOlSqfNbcuI4jiQ2juQzZjt5j95GIpU9gRORW69f/sS7W0KKctVJpNSQSKkhZYVIEtvy18K1209kW6MtyT0DSS5XWF2Dhg0bfvC+OHnyJFWvXp1UKhVpNBoKDw9nz9Po0Xy0ysvLixQKBdnZ2bH3Z25u7r91P/8V/J/y+Pz9/UFE2HT1FZsnUtlDHfYZOLEE+ff/YErjJWFXuyP736PfAit9vsIX13mtvRKxfLlczvgN8/Pz0aFDh1LFGT1GfQObai14z8yoBUQSKCrwuQahwEbuHQa/yYeteEXtG/bjv/OtXKwnWKMdgOJKUU4sgdTZB+4958CmRlv2W4FBXu5eEVI3Pp8kUttj0PLj2L93NxITE3Hu3DnIZDL06dMHoaGhWL58OX799VdMmTIFbm5uWLVqFTw8ipnov//+e+zYsYON9oXqP4FuS5hPRZ6AAEGCxHLELpfLceHCBWRlZUGn0+HBgwdWdGSfihcvXqBOnTrw9PTEqVOn4OrqCqlUiiVLlmDs2LEoKChAeno6fvnlF1SsWBGzZs1Cnz59EB8fj86dO+PWrVtMjZ2dO4kEixYtwrhx41gxSVkY0bAiFJLSLDWfAkHN4UNQKpXIyMjA06dPoVarUa9ePbi5uSEkJAQVK1ZEbGwsxo8fD3d3dwQHB6Nnz56YN28ezp49W0qiqiwkJiZi+vTpKF++PKZMmYJGjRohPj4e69evR7169T7oxVrixo0b6NmzJ4KDg3Hq1ClWhLN27Vq0bdsWhQk80bPcKwQipS2kzr4ACLl3j4GIkHublw2SewVDpFCzvKfi+WnYmIpzi0SE5ORkKzo8g1Ct/O4Fz4yT8ACOTYbAqcVXAHipLb/Jh+Hecw4jwJa5VeD1O8ftRmhwAMqX52kFObMRnEXExK3rdKt8rTAJkj4A4DVsjdV3Cgs1c2X5CMicfa3OlcbNB6u27kVGWir0ej2SkpKwYsWKj55ngX+WE4kQ3awV9Ho9pDb2cK5UF2JbZ7bctGnTQESw9ywHY14GkteP5fl8C7L43KKtE1L3zkLCvI5I3jjOSjndmJeBlC2ToX11G3LPIMjcKqAw7gZMRb2W77dPRe7NgzAX5iK8UUvUqFHM2GSp/lIS/fv3x71799CxY0d07NgRIpGI0d0J1/Xt27do1aoVy+3n5+fjxYsXH1zn343/OXWGT0Gv2v4QmiTcW42CbVAdZDy+gtS9M5H/8IyVKoGA1ANz2f9Jq4ZYfacKaYCCx+fh1HY8X1ySxJfzu7q6stJ+ANi7dy82bNgAHx8fFmaqEBYB7tgpCKXSYo0zpA6e0KvsWIOsqSCb1xY0Ft9MQsGLqAwxTBBKSy4VNctLnf2gCqqL/MfnkX11NzOuZl0hkg/Mx/i7njhw4AAAvijh/v377AH8448/cPbsWTRq1AhXrlyxClkeP34cy5YtY5pshw8fBsDzCgptAv8k/vjjD/Tq1Qs//vijVWhI2KfAwEBWsNG2bVvs3LnTivLr+++/x8SJE62qBQU0btwY4eHhmDdvHr799tsyt19SIutToZSKMLVl8J9SQcXExGDRokWl5nfs2JHpDBoMBjx58gS3b9/GrVu3sHfvXta4HhERgerVq7NJo9Hg8OHD+P333xETE4Nu3bph7969H5QZ+hguX76Mpk2bQiKRoGXLlhg1ahRatGiBp0+fguM4jBw5EgcPHgTIjNzbh61+a8xMhrkwh1VNWwkuA0h8/gjVqlWDQqGAVqvFzJkzMX36dIjFYjYQMWYmQaTUQBd/D7qicKTMtTwbEArVswAYAbZlRWVmvg62Rc+jSZsHs0HP5ML+KkqS0mdf3obC+HswpL4GGXQAmaG2d8Fv54JwpmJFyOVynD9/Hk+ePGHPjUgkgkQigY2NDfLy8qyMCpnNPJkFAENeFvQaTygr2CHvLs/ZOXPeUpw4fRaZb3mxaGNWEcMUx8GUnYK3q4ZA4VMJEnt36JOeIvviZji3Gc+f+4dnYNblQ6TUQP/uBS+VZqEaowqqC3AiOLebiJpVPJC4exZrPRJIzKdPn46MDJ7tRqjiLiwsBBFh165d4DgO5cqVY60Zz5/zos0RERHYvXs38vLyWHqjLFq9/xT+Txo+S+yd0gV3c5W44qjDxr28QbE0MALM2uIqSJl3JYvKSd4wcRIpCh6dg0haXEL95s0b+Pj4YOHChejQoQMAfiRTrVo1JCYmQiQSIVPmDLOFp2jKeleKBNasyy81T1RULm9ZDi+8LMQ2DnBsOhSZ59aj8NUd6FNfAyBIHDzh1utncCIxCl/egiG12POFUYeDu7fBz8+PETPHxVkrMwN8heDFixfBcRyCgoKQm5uL+Ph4xmW5Z88eGAwGeHp6onv37v+y9NC/CiLCwoULMXfuXOzcudOqYtNgMGDPnj1YunQpXr58iaysLJw/f74Ux+WtW7dw/fp1bN269YPbmTdvHmrUqIF+/fqVErkVYCmRVVKdoSQEdYapLYPZ7z4GQUj3zZs3qF69OtPms4RUKkWVKlVQpUoV9OvXDwBfzfn06VNmDKdOnYp79+7BaDTC0dERDRs2xO+//46oqCgrId9PQXZ2Nr777jssXboUTZo0wbZt2+Do6FhqOcuX17GrD7DyUjzuvjcAZhOMhbkQKTWM1stvyDI0r18TwxtWRJinBoMGDUKTJk3g6uqKhIQELF26FIMGDcKOHTuY4VMG1oFDo/7FrRBFMOVnAiIJz3yUnwmx2gG6IpkdSwLsejUjEF3fCWfPnoWPpwdaeBTiaDL+kvETcYBaJkZucBSMWckwWWjcWb47AKAwOw0xMZlo1aoVbG1tcesWr34gGDiZTAatVssMiExpA32hdc5UQE7MbqvP6uC6eG5bHsBlwMJz5eRqkDYPIpkCrt1movDFDaTumQF9yku2jEBUbS7MgdwnDGKlBgXPrrDvbau3hsKvCswGLfb+PAZv7l+GWCyGyWRiA8a1a9eyyu7o6GiMHDkSrq6uyMjIYLnrZ8+eYffu3RgxYgQbZAsVyTY2NhCJRDCbzZ8Urfi78H/e8L1LiMPQdu3gnvkQGwEobe3BSaTF3lPRCEfmGcQXkgCwq90Zqbt/ZOvgwIGMehTG3bBaNxGhUaNGLGwCAF5eXhg9ejQOHToEHx8fPHmXC6kzf5FVgXXh0qG4782UlwlOroKojAdO/y4OWeDLtMloACeRQp/Mj5ZkruUgVtvD6fPhSD0wF4XPY6DwD+dbM4p6m5xbfw2XNl+X+bJt2bIlo1tr0KABunbtirS0NJjNZjx9+hSBgYFs2WrVqiE+Ph7Vq1f/r4tLarVaDBs2DHfv3sXVq1dZSPXdu3dYtWoVVq1aheDgYHz99ddo27Yt5s6di59++gn79++3Ws8PP/yAKVOmsMbxslCuXDkMHz4cEydO/KiB7FXbHzaGTEzdfB75dv68Z2/ReP3vkP4SEQYPHoxRo0aVMnofglgshr+/P27duoXbt28jISEBo0ePxmeffYasrCzcunULS5cuxYABA6BWq1G9enXmHUZERMDDw6NUCE6n02H58uWYNWsWAJ7+TKDEKgsuLi7o0qULdu7ciTb1w6FSqVAprAoex8YipFFHhNYciHvNu+HWofUo3D8dJnMbzD6Sh5iYGERHR8Pf3x937twBwLfPaLVaq6iCc8vRpRRJAN6rs6ncGHn3TiBl21RIXfxQ8OQSOJmSSfBwWW8Rs34t7ukyAfAk34UP/kCFHDNeVewAMyf+UwJ3qQiY3jYUvWr7Y+HSV/ju5h4IncDOfoEoFxCM8Io+cHV2QF5eHrZv3453797Bx8cHPXr0wPXr13Hjxg3m1bZr144VJ8kUSjg2H4HkfT/zKxSJrThJfcbsAJkMeLOkFz+DE8MuvBmyL29hpNvgRCAtbzglTj7gOBF7LwjecNbFLci/xxOYcxIZ3HrMBsdxSFjQhW+2L4KpMBepu3+E7m0sgoODGUm4ry8fzh0/fjwLUQqDIIGObdGiRTCZTPj6668ZvZ7QlvL+Pa+1+Pz5c9aQ/ykh9r8L/+cN39ChQ3Hw4EEmlFi3eXskSkSsz0gYJQlGDwCyr+2xWoddnU5w6zadfY7/pT1gMoATS/EqrQBffPEFAL7nTa1WY/Dgwfx68rV48T4P6koNkXNlJwqeXUHKjmmQ2LnBmJnMlNtFZfA9ytwrQGLvDmPWO7xZMYAn7y1iuFeU4/sf044uQuHzGHASGSSOnix/aeMdBNuwRmgU5AL91c0Y26Y3eqelMXXnESNG4NixY5gxYwYkEgnc3d0Zx6Ng9ObMmYPY2Fh2wxv5a8sAAInxSURBVP7+++84d+4cBg0a9NG+s/8UkpOT0b59e/j6+uLy5ctQqVS4cuUKli5dimPHjqFbt244efKkVYP1uHHjEBYWhmPHjrFm7uvXr+Pu3bvYtWvXn25z8mS+svDSpUtlHnNOTg5+/PFHbNy4ER07dsTe7UvQbOg0uFSsihyt8d8m/V27di3ev39vVTn7Mdy9exerV6/G9u3bUatWLYwePRqtW7dmFa8AGBEBEeHVq1e4ffs2bt++jaVLl+LWrVuQSCTMCAqRiwULFqBy5coICgpCUFCQFa9uWTAYDKhcuTIOHjwIvV6PwsJCxL+Kw2cN6mHS+H6oXTsShh6/YcGCEKxfvx6bN2+GRqNBlSpVkJqaiocPH6JLly44ceIEjEYjzpw5g8mTJ7Pq44/BockQQCxBwZOLMGQmQ+4VBIfPBkJcxHtrzMtEzPG9bPn8/Hxs2LABfn5+6FA9AjsfZUHsXQVisRhmCyIKhQU5xuvlA9F7OWDNOcUjLf4Z0uKf4cap0t9ZkVyA99gFcmoACAwJha7uEBTmF3t7IrkNxBpn1subeugXK+8SAAgcIBgPuRpyz2BoX/FepdDs/zGQUY+Ubd9AnxJnZfRybh2CKS8D+qSnkEiliI2NhVKpRGFhISPt3717N+vt9PPzw3fffYe0tDTG1CRA6HuuUaMGEhIScPXqVfTq1cuqQrwkwf1/FP9YGc0/DBRVH61atYoqVuT7UPr27UvxKRkU+O1R8pt8mGwj2pBIriaxjSNJnYsrrERq+6JKJ55bT6hEEyahl08ZUIvkbuVJrlRR27ZtKTU1lXFFAiCxxsWqekpZIZJEKnvipHKSOHmTbY225PP1rg9WXIlsivuFSk7qsMak8A0r87vazTtQWq6Wrl27RgDPP/nll1+yqsTVq1ezKlSO40ij0dCQIUMoIyODnT+hkrHkZFnZ+E/h2rVr5OXlRTNmzKD8/Hxau3YtVa9enSpWrEgLFiygzMzMD/728OHDFBAQQFotz0HYvHlzWrFixSdve+vWrRQeHm7FkWg2m2njxo3k4eFB/fv3p6+//pq8vLz+7f4mS8THx5OzszM9ePDgo8tlZWXRihUrKCIignx9fenHH3+khISEf2mbZrOZ4uPjae/evdS9e3eytbUlqVRKdnZ25OHhQRUqVKBt27ZRXFzcBys/z58/T6GhofT555/T8+fP6cSJE+Tj40NZWVkf3faVK1eoYsWK1KdPH7bsjz/+SMHBwbRy5UqqVKkS1a1blzotPPEfqaadPXs2BQYG0ps3b2j7vsNkV6sjObX6mlrPPUJjtt+hled5HkuhF7RmzZo0evRoGj16NHl5ebFn486dO/yzLxbT48ePyWw2M77YBQsWEBFR3758T6CtLf9+GTBgAF/RGlyd/KdY9ziKVHbkYcV3ypFddB/22SaiLTm3m2T1vcy7EvsscfKx6psUa1xLVbVzEhnfuywSl+qR5OSqMt8DDg4O1LdvX1q9enWpczl8+HAqX748KRQKUqvVfMWpREIGg4Hmz5/PV+RqNCSTycjV1ZVVxr948eIv3K3/Hv4xWaKSEGSKBDmTvxuC21yWVM6QTTfxx5OUj+ZkPoY3ywfAlPMebt1nQeFXBUqpGDuG1Ma2ZT9jzhxenNK5/TeldO9ybhxA3v0/eAYHMsMuqjvs6/f8pG1mnlsPbcIDkK4AhvRE2IQ1Qr+uHXB663IkJCSwasoRI0awSsXNmzejd+/eqF+/PlNQWLVqFYYNGwapVIoePXrgxo0bePz4MebMmcNkTf5/wqZNmzBu3Dj89NNPiIuLw9q1axEZGYmRI0fi888//yT19TZt2qBevXqoX78+evTogWfPnll5QR8DEaFBgwbo3bs3hgwZgjt37mDUqFHQ6XSYOXMm5s2bB4PBgG3btsHd3f3fPVy2zWbNmuGzzz4rxVwkfH/58mX8/vvvOHDgAJo2bYpBgwahcePGZeoh/hXcuHEDkyZNQlJSEmbPno0vvvgCY8aMwbFjx9ClSxc8ePAAt2/fRl5eHsLDw1mY1N/fHytWrMDZs2exYMECdOzYkT2DX375JbRaLdatW1dqe3q9Hj/++CPWrFmD5cuXs1w5EeHgwYMYNmwYMjMzsXr1avTq1Qv332T/qQ7ihyA8pyXDzXPmzMHatWuxbt06zJ8/HwcPHoRUKgXHcSwSIiijC++tcuXKIS4uDhzHMfUOAGjRogUTixX4Te/evQsigkgkgre3NxwcHHDv3j2MHj0a1apVQ//+/QHwtG5mvRYcJ2I0ii4dpkLi6IXk3y2rj4t7d+0a9AMn5pB9ZYeVtyZIKsl9wuDecw608feRsu0biDWu8B6+lkmiCblWuU8YxCoNCp5egSXEdm4wZadAIpEwcW5L9O3bl6nKC2jWrBlMJhMqVKiA7Oxs7Ny5E05OTkhNTUVeXh7KlSuH9PR0dOjQAa9evcKdO3fQpUsX7Nix469e0n8d/5iJLYGSLBp/N4DinrKvvvqKMV2IxWJSKJUk0biQ9+it5P3VFrKp0ozEGhfiZEqSeQaRa5cf2ShRHdaY97BCG5GifASvflDk8cm9Q4mTyknuGUTd5u0vHiUpbHiPUWVHIqWGVIF1yevLtaQObURynzASa1wJgJXigu+kQ6Sp05nEts4EsaTI6wwn79Fb2TJB3x4l+5rt+NGikzvNnTuXmjdvTsOGDaNWrVqx7Z85c4amTZtWapRWqVIlkkr5ff/++++JiNgI1cHB4R9nT/gYDAYDff311+Tp6UmNGjUiR0dHGjt2LD1//vwvr+vFixfk5OREUVFR/1K/4O3bt8nFxYUGDBhAbm5utHr1arp69Sr5+vrSxIkT//bztnLlSoqMjCy13pSUFPr1118pODiYgoOD6ddff6X379//Ldt89uwZde7cmTw9Pem3335j2162bBkFBASU2k5KSgodO3aMZsyYQeHh4SQSiUgmk1HdunVpzJgxtHHjRnr06BEZjUbKzc2l8uXLMwYdAffv36eqVatSmzZt6N27d0TEe51Hjx6lGjVqUNWqVenAgQP0yy+/ULly5Vh/6Karryh42tG/5O0FTztKm66+KnXcs2fPpoCAAHr79i199913ZXo39vb2FBkZSY8ePWLvLY1GQ61atbLy+ITJx8eHlEolqVQqatGiBVPfqFmzplWf7OjRo2ndunXF7w2ZkhT+4aUiRoqKxSwt6spNSFmxZrHHV60F79k5epMyoA6brwysQ36TD5P36G1kW6NtqUnuU7loubqkCqpLIrU9cTIViW2cSFGuOnESOYnkapK7l6VQYa0AURI//fQTBQcHk0qlIrVaTZGRkXTq1Cn2/e3btyk6OpoUCgU5ODjQgAEDKDs7+1+4a/91/FcMn6XMizCtW7eO9u7dywyUr68vDR8+nIWxLJvT16xZQz4+PmRvb09jxoxh69XpdDRs2DB2o/3ZVH7kGhLbOvEhBYUtqUMbFdEWcSRx8iZOpixuigVHqqAoEts4st/L3MqT1IU/FtuwRtS+aw9ycnIqvnFtnUnuV7Uo5OBNvuP3WcnTWBo+124zWSjCJrwlqYLrkdjGkZyaDCFbd38SS+WksrUjVzde1kUikZQKH1UukkZas2ZNmYYPALm58c3ynTp1ovz8fFq9ejX7Li4u7p+8DT6I+Ph4CgkJIbVazUJdeXl5/9Y6e/fuTWq1mvR6/V/6ndFopFWrVpFSqaSqVatSeno6LV++nFxcXEo1yf8dePnyJTk7O9OjR4/Y9o8fP06dOnUie3t76tevH126dOmTm8z/DMnJyfTll1+Sk5MTzZo1i0kfERHt2bOHPD09P3hf3Lx5kyIjIykqKoru379P6enp9Mcff9DPP/9MXbt2pYoVK5JaraY6depQ+/btyc7Ojs6dO0eFhYU0d+5ccnZ2prVr15LZbCaz2UynTp2iOnXqUEhICO3atYtMJhPb1uLFi8nPz4+Fw3jjV1pWq6zwZvC0Y2UavVmzZlFgYCC9ffuWli5dSmq1mkJDQyk9PZ22bNlCXbt2JSLeGK9cuZKcnZ0/+G4R5JvKly9vNWAxmUx05MgRmjFjBo0ZM4Y15g8ePJiIiBk+uY0d+Y7fS74T9rMGfPe+C8j7qy1sGx79FhUPlCfsJ99JhxhVmrpyE7Kt0ZbJLUldy5Hf5MPkNWxN2e+/ooZ+iZOPhUFsZ7WMukIELTpw9d++x/5/xH/F8P34448svt2xY0caPXo0/fDDD7wxkcmoT58+FBoaauW1WRo+Hx8f6tGjB4lE/A0ijCaEEZu9vT3179+fveSFqXHjxuz/ly9f0g+/72OfVZUaWhkliCU840SRTp9I7WgVGxerHch30kFy6cgbGIm9O4klFjyeRbFykdKWRCqenUDwJMs0fJ3541f4VSW37rPIe9Rm8hu3m0RiCalUKho4cCD16tWLHB15w+vi4kJnz56la9eu0VdffUWBgYHMc5szZw4RFT9Unp6eFBQURE+ePKFbt26RUqks82G4fPnyf+N2YIiNjaWePXuSSCSiihUr0qlTp/6WF7zZbKaoqChycnL6SxGGq1evUkREBNWrV4/OnDlDTk5O1KZNGwoLC6Nnz5792/tVEiaTiRo1akRz586l+Ph4+uGHH8jX15ciIiJo5cqVf5on+yvIzs6m7777jhwdHenrr79m2nACLl68SC4uLnTr1q1Sv83MzKQRI0aQm5sbrVu3zspAlURWVhadO3eO5s2bR8HBwaRWq0kkEpGtrS316NGDfvvtN1q9ejXVr1+fAgICaPPmzWVqzhHxnrC3tzfFxsYSEdG9xEzqueIs+Y7fSwFTj1hzpY7fSxW/4XN69xIzS61LMHpv3ryhqVOnkq2tLUVGRjLPY+HChTRy5Eir37x69Yrxqi5atIjq1KlDW7ZsIaJi3cJu3bpZ/WbIkCFlPmtffPEFERU/o07lw9i+C3k1t+6zyL3vfPY+KmnULY1iyUmk1LDlSnp76spNyvyNkP/zGb2F7KryfL1NmjT54LX9X8b/N6HOFi14l/2HH34gIqLU1FR2QU6fPm1l+K5fv05ERA0a8DRjv/zyCxERVajAu+Xr168nIqK9e/ey3wwcOJAZWwBUpUoVWr9+ffHoJqwx+U0+TFJnfr84uZpsa7RlYq5AkTBl0WhMbOtEvhMPFCeii+Z/bHJoOvSDhs934gGSuvhbCdfaevPGTC6XlyIBFkJdlqESYWrQoAERES1atIgAkKOjo9VLMyEhgebNm0dTp06lY8eOMUP4n3iZ/xmMRiMdPHiQmjVrRnZ2dqRSqejXX3/9W7dx6tQpCgwMpO3bt1NYWNifhibfvXtH/fr1I09PT9q8eTOZzWZ69uwZeXh4kIeHx3+MWmnhwoUUGBhIn3/+OTk6OtKIESPo9u3bf+s2dDodLV68mNzc3Kh37970+vXrUss8evSIXF1d6eTJk1bzzWYzbdq0idzd3Wno0KGUnp7+yds1m820bNkyEovF1K1bNzp//jyNHTuWPDw8SCqVkkwmo2rVqtGgQYNo+fLlFBMTQwUFBaXWs2bNGvL09KRHjx6RXq+nyMhImrNgKa08/4JGbL5O/n3mUNvZe2j44r3k6luBZs2aVcqQzpo1i4KCgighIYEGDhxIDg4OFB0dbRVVmDp1KnsXWUJ4b9na2tKgQYOoYsWKpNfrmeErGQIUKLnWr19PJpOJWrduTQAf9oyPj2eC2p4h1S0Mn5oZPiuPr/9iq/eF76RDzMNTVqzFE2R7BJLn0NXkNWxNcTHeR95JwnvPZ+xOCvr2KAV+e5SGbrpBc5bwkSBfX99Pvsb/S/j/xvAJLPA7duxgywgXZ+PGjVaGT3hxCQz8Qr5KGI1du3aNiHgPQvhNRkYGmUwmq4sueJmWHp/g4ZU5cSKSWcS8NbU7lWKZ9/HxYf8LYQjH5iPJe+QmxhNapuGbsM9qPZIipero6GhW9WQ5RUVFMUVtk8lEz58/p+rVeZ7BmTNn0q1bt5h3GB0dzc6pwWCw8qKEB8/Pz+9vC599CtLT01nupkaNGtS5c2fy8PCgK1eu/K3bMZvNVLduXdqyZQuZzWZq3LhxKaUCAXq9nhYuXEjOzs40YcIExoW5b98+cnFxoSVLllBISAjt37//b93H2NhYGjx4MHEcR5GRkbRp06YyX/r/DkwmE23dupXKly9PLVq0oLt375a5XGJiIvn6+tLGjRut5j969Iiio6MpPDycYmJi/tK2k5OTqVWrVhQeHk7btm0jBwcHatKkCfn4+NCqVatIp9NRfn4+xcTE0LJly2jgwIEUHh5OSqWSKleuTP369aPFixfTpUuXKC8vjzZt2kQeHh40cOBAatmyJQuVdurUiYYOHcq2m5CQQNHR0RQdHc0qXX/66ScKCgqily9fUtu2bcnZ2ZlatmxJhYWFVvs8ZMgQWrZsWaljEd5bq1atos8++4w0Gg3NmDHjg4ZPiMRUr16devTowXLsEomEZDIZe7YDqtYk3/F7Sxk+v8mHSVWJr7AWKWxJXaUpKQPrMJ5STS2+ilyktie7ap9ThdrNSGrvRurKjT8aAhYiVw5Vm1CnFZepUnRb8g+pSj379KNevXox9XchJPt/Df81w1e+fHnmzREVe3w//vgjERGlpaV90OPz8fEhW1tbligWDJ/g0X322WfUunVrK2JXHx8f6tatGwuPAqAaNWqwGxFiKZ/jKyJ1tq3R1qq4BQDZVm9dTHoLnvDWpShEKRi5Lzp0IpnCOpQodStPEInZKMzS8Pl8vZs0NTuQSO3APE25X1WSOngQwEvsEBWHUkqeA8tyYiGsUr9+fXJ2dqbhw4eXMnwPHjygihUr0oABA6h9+/YkEomI4zirAcd/Enfv3qVBgwaRvb099erVi86fP0/dunWjyMhIevPmzd++vePHj1NISAgb9T969IicnZ1ZMYWAM2fOUGhoKDVt2pSePHlCRPwgYeLEieTr68sGUydPnqRy5cqVelH+VeTn59OGDRuofv365ObmRt7e3jR58uR/a50fwsmTJyk8PJwiIyPLlKMSkJmZSWFhYSxUTkSUl5dHkyZNIicnJ1q8ePFfLuTZtWsXubm50bRp0+jWrVvUvn17srGxodDQ0D817lqtlm7evEmrVq2ioUOHUo0aNUipVFJISAiFhYURx3E0b948ys7OpoULF1L16tVLXRej0UizZs0iFxcX6tatGwv5R0VFkZubG3Xq1KnMvG+HDh1o586dpeYLhm/fvn1kMplo3LhxJBKJ6LPPPrMyfMIg8sKFCxQcHEwKhYIaNWrEcnzCJBi+uvXqk9+EfWUaPp9xu8mubjc++iSWktjWiRybj2S5PvuG/Ujq5EOcREYuLq5UN7oxtRi/kAK/PUpB31oXAZWbwk/lP+9rtb+rVq2iSpUqsYKU4OBgmjZtGmsD+r+G/5rhE/rEoqKiaPTo0SzsKJfLqW/fvkyfCuBzfHFxcexz+P9r77zDo6q6Lv6bnt4bqXRC70U6CgKCdEHpCCJSpIiCIlIEXiwIKgIivYogKCAC0kF6Cy10EpIQ0nsy/Xx/3MxNhgQE3/a9Out5eJjcuffcOnefs8/aa9WtK/r37y+rhQ8ZMkQIIUTt2rXldcLDw2VfNZDUxP38iuritFqtCA4u5sWnVAmF1ln251OotcKlakuh9iojr+PbaXxR4CtMbfp0GCM9wG4+gsLj0ep0xR5uhVD7hAj3Bl2Ed7s37ZToNQHlZIanyiNAKIsRZ5ROrmLw0DeEh4eH6Nq1q1wL9Oi/oKAgUbduXVG1alU5qAcEBIhLly7JadDigS8+Pl40bNhQuLq6Cp1OJxo1alSCbfevhtFoFJs2bRItWrQQISEhYtasWeLhw4ciNjZWvpf/6hGOENLLp1GjRiWC+oQJE+RnJi4uTvTp00dERESIrVu3yi+sxMRE0bp1a9GuXTuRkpJit33Xrl3F7Nmz/9QxnT9/XowcOVL4+PiITp06iW3btol58+aJ5s2bP3Zu68/i3Llzol27dqJSpUpi8+bNTxzR6/V60apVKzFmzBh5BPXTTz+JiIgI0bdvX/HgwYNn2nd6erro16+fqFSpkvj+++9Fnz59RGBgoPj8889FRkaGqFWr1p+qCTUajeLw4cPC29tb1K9f327kZHPb2Ldvn11NqhBCvPXWW0Kj0YguXbqIyMhIUaZMGTFo0KDHXvMWLVo89Xxw69atRaVKlUTjxo1FdHS0SEpKEhEREeLgwYNi27Zt4s033xQREREiNDRUDB06VLi5uQmFQiE8PT3t5lCrj/hSRLy3/V9Wo5iaoxdLDt8W476/IF5fddquHvHvjv9a4Dt48KCoWLGi/LI+c+aM+OGHH0S9evWEq6urXcrw3r17Ytu2olSgLRdvGzXWqFFDCCEx92xphPLly4vRo0fL2+Tl5cmmllqtVri5uYkOHTrI6UBNYaGnd7s3pUJzV2+BSiP1vgrLF/y6vS8/aDY2aPHSB6VrEeNLoVQJp4jaImTkqhKlEaX9C3lrhbT/wsAaWLGmEEKIXr16ibCwMLsgbqN1BwYGioCAAHm5i4uLqFatWgmiwn8LiYmJYubMmSI4OFi0atVKbN68We5dHz16VJQpU0Z89tln/7YU686dO0WNGjVKkC+ysrJEmTJlZDbjRx99ZMdmPHbsmAgJCRFTp04t9cV4+/Zt4ePj89Qj1IyMDLFo0SJRr149ERERIWbOnCmn3m7cuCF8fX3/VJnG43Dnzh3x2muviTJlyojFixf/IZPVYrGI3r17i169egmz2Szu3r0rOnfuLKpUqSJnZJ4Fe/fuFWFhYWLAgAHitddeE35+fmLOnDl2c6MXL14Ufn5+z1xsb0tpvv3220IIIdatWyeUSqUYP368WL16tRg7dqxo0aKFcHd3F+XKlRM9e/YUL774oggNDRU//PCDcHV1FSqVSvTs2fOJpJzIyEhx5cqVpzqmc+fOieDgYPH5558LDw8PuYOtVCpFu3btxOeffy6uXLkiP+cDBgwQgREVxcdbToqx358XQ1adFmO/Py+m/nS5xAjt6cs1fi1B4vn111/lIvvi/3799ddnuuZ/Rfy/Vm4p/qLftGmTAETVqlXl75cskRQNmjZtKoQQol+/fgIQU6ZMEUJIk9i2NoQQYu7cuQIQHTt2lNt49dVXpQD2XHcRMXmnnbedjeVkW+bbaXyJCejiE84Rk3eKAd8eFosWLSoctbmJsAlb7L4vzq5yqdqicPSoKmJ39p4hpVV9Aux+FB98t93uXIQQYtSoUaJdu3ZySlej0cg0+P8WrFarOH78uOjbt6/w8vISw4cPF1FRUXbrLF26VAQEBPxbf4BWq1XUq1fPzlfPBpuPnKenpx2hx2q1ivnz54uAgACxc+fOJ7b/wQcfiH79+j1x/0eOHBEDBw4Unp6eonfv3mLv3r12L1uz2SyaNm0qu2r/s0hKShJjxowRvr6+YubMmU9FwrFarWLs2LGiZcuWIjMzU8yaNUsubTAYDM+0/7y8PDF69GgRHBwsOnToIHx9fcX06dMfy0adNWuWaNu27TN1fJYvXy5q1qwpCgoKhNlsFi+++KLo1auX8Pf3F4cPH5bXs1gs4vr16+KVV14R3t7eolatWkKhUAiVSiWCgoKEq6urGDhwYInOS9euXUW9evWERqMRffv2FfPmzXvi8aSkpIgNGzaI8PBw4ebmJvz9/eXfqZOTk/j+++/t1r94P0MMWX5cVJryi6wgVbxOt8IHv4hyz6hM87gaxUenR2z/bFNDf2f8z2h12tRX4uLiyM/Px8XFRbYEioiIAIocxA8dOsTEiRP59ttv7dqwOR8X932yia76umrJB4L6zS2xb21AOQxxVyQnhKQ7WPW5CEMeKFXkXNyN2isIj0bdUSgU+Hp60K1lN0aOHIlVn4vGmI1FW2Qt9KgLAwDCgjkrGbVnAOZCrzGTiy8/XSzmDp8aK3+MisukdpgXNWvWZMmSJVgskoqF1WqlX79+ssDvfxJ6vZ7vv/+ehQsXkpGRwahRo1i4cCHe3kV2MCaTifHjx7Nv3z6OHj1qJ4b9r8bPP/+MEILu3bvLy+7evcv48eOJjo5mxYoVzJkzh0OHDlGpUiVycnIYNmwYt27d4uTJk7K/3OPw/vvvExkZyfHjx2W3d4CkpCTWrFnDsmXLUKlUDB06lM8//xx/f/8SbSxYsACNRsOoUaP+qXPNzc3liy++4Msvv6R///5ER0eXur/S8Pnnn7Nv3z4+/vhjGjVqRGRkJGfPnn1m3cRTp07Rt29f1Go1+fn51KtXj/Xr15fq3mDDpEmT+Pnnn1myZAlvvfXWH+7j1q1bTJo0iYMHD+Lk5MTMmTPR6/X88ssvHDp0iJ49e7Jp0yaef/55lEolW7Zs4fLlyyxatIjRo0cTFBRE7969adq0KYcOHeL7779nw4YN+Pj40LBhQ+rXr09CQgLnz58HYMOGDZw4cYIJEybIx2A2mzl9+jR79uxh9+7dXL9+ndatWzNw4EAWL15MQUGB7GCg1+sZOnQonTt3xtXVlXUnYx5x8hB256c3F+ptPuU1/yPHD5vDhwMl8T8T+Bo0aEDjxo05deoULVq0oHr16mzcuBGFQiFLdNmUv0+fPk1UVBTBwcHcvHlTbqNz5854eXlx69Yt2rZti1qt5tKlSwAEeTpzX6nAbBUl9u3RsBs5F38lP/oIiGLea1YLuRd2ofYJIffCLpxDq3L2SgBNJ0uC11WqVGFK39bM+fWG/LBHTLb3J0vZ9g/yb/xO0qap6EKqkn/9GABudTsBkiVSxoEVsoQRQMvOr1Ar1JMa4f5YLBY8PT1p2rQpbdu2pV27dv/spX4m3L9/n8WLF7N8+XLq16/PjBkz6NixYwkpsdTUVF555RVcXV05deoUnp6e/7ZjslqtTJs2jY8//hiFQkF+fj5z585l0aJFTJw4kR9++AGdTkeZMmXo0KEDNWrU4PXXX6d58+YcP34cJyenP9yHm5sbn3zyCW+//TYnTpxg//79LFu2jP3799O9e3dWrlzJc88991jF+evXrzN37lxOnTr1VLJrpcFkMvHdd9/x8ccf8/zzz3PmzBk7p5A/wvr161mwYAENGjRg/PjxfPXVV3Tp0uWPNywGo9HIpEmTWLp0KQqFgrfeeov33nvvqQKvWq1mzZo1NG/enBdffFE2JX3cfvr27cu0adOoUaMGv/32G0uWLOHs2bOo1Wratm3Lli1b6NWrF+vXr+fMmTOsW7eOMWPGMHr0aLRaLe+88w7vvPMOAL179+brr7/mk08+Yd68eVStWhWLxWJ3L5RKJc2aNWPp0qVkZGRw9uxZ9u/fT3h4OO3bt2fu3Lk0a9ZMlr+7fPkyOp2OBg0aEB0dzaVLl4iOjmbPnj3kB9d7au9G2xtIqZCCoEallIMi/HOOHw4U4r895HwSeGROKykpSQwZMkSEhoYKNzc30bBhQ7Fjxw55fZv466NyXMVP8+jRo6JGjRrCxcVF9O/fX3Tr1k0AYsy4d0qkHor/C3h1ltAGVZTlxDwadRfh7/4kIibvFIH9PxPa4CpC6eQmdDqdCA8PF6+//rqIjY0VQkiFtm+uPVMqy6rSu1uEZ6NuQu0ZKBQandD4lxW+L42Tv3+s8gKIbw9cE87OzjLt/j8Fq9Uq9u/fL7p37y58fHzE2LFjn1gDGBUVJcqVKyfef//9fzmBozRs3rxZNGjQQFgsFvHjjz+KiIgI0adPHxEXF1di3Xbt2gknJyexfPnyZ97PvXv3RGhoqPDx8RENGzYU33777VNJL5lMJtGoUSOxaNGiZ96nENL1/+GHH0TFihXFiy+++Kdq/Xbv3i3c3NyEp6eneP/99+3mOJ8WR48eFYGBgUKj0YihQ4eKxMTEZ25DCCG++OKLPyT3TJ48WXTq1ElYrVYRFxcnAgMDS2WoHjt2TLi4uIjQ0FAxY8YMERQUJAIDA594rU+fPi0qVqwohgwZIrKzs+V0ZUhIiAgICBAajUY4OzsLV1dX0bx5c/Hee++J77//Xty8edMudV29enWhUCjEoUOH7Nq/eD9DRE799U/N3VX5cJeYtv3yP01QuXXrlixMX7t27Wfa9q+I/5pI9X8LWVlZ8mjDarVSvXp1rl+/zrJlyzilrf3M4tU2wWqArlOX8dPMoQAcPXqUli1bAlIqNiYmhrRcA1vOx3M9MYdsvQkPJw0ezmo2nYmz69E9LZw1KlxOfMv8qePlfT0O27ZtY86cOVy5cgWtVkvNmjXZsWOHXSryj5Cbm8vatWtZuHAhIPmy9e/fX/bfKg0//vgjI0aM4Ouvv5YtcR6H1FwDW87Fc/1hdqGtj5rIIA9eqf/0tj4Wi4VatWoxduxYtmzZwoMHD/j6669p06aN3XpGo5H33nuPbdu2kZuby/79+5/K/dloNLJ9+3aWLVvG2bNnadu2Lb/99ht37tzBy8vrqc7n4fFtHNu/m7179z7zaO/gwYNMmjQJi8XCJ598Qtu2bZ9pe4BVq1bxxhtvULNmTdavX0/VqlWfafu0tDReffVV9u/fT8uWLVm7dq1sLPpnYLVaadOmDV26dJFHZMVx6NAh+vbty8WLF/H29qZ169Z06tSJDz74oMS6s2bNYtmyZSQnJ8vP5WeffcagQYOeeAyXLl1ixIgRREVFYTAYsFgsTJw4kV69etGgQQNUKhUPHz7kwoULckbp/PnzZGRkULduXerVq8fChQsxmUyo1WoWLVok25P9M6L4CgW0rxbIkv4Nnn3jQlgsFpo1a8a5c+cwm83Url2bixcv/un2/gr4n0l1/qswbNgw1Go1VatW5fDhw1y/fp3g4GB69uxJgxw4eiv1Tym/A5iu7AGkwLdkyRJ5eXZ2dgkvMXdg1OjRfHoiE4Pl2YMegN5swaN2Z86dO/fEwLdx40b69u2LTqejW7duuLm5cebMGfLz858q8N28eZNFixaxdu1aWrVqxcKFC2nduvUTjSOtViszZsxg1apV7Nmzh3r16j123ai4TL45dJvDNyW/MoNdWuch8/fdpHUVf0a2qkjtMK8nHuvq1avJyMhgypQpfPjhh4wcOdLOxBQgISGB3r174+3tLXvzjR49WnaeLw3Xr19n+fLlrFmzhmrVqjFs2DC2bduGs7Mzw4YNY+bMmXzxxRd/eD5aVSIGQwVavvIRlxOy//B85GsUFcXkyZO5efMms2fPpnfv3s8cNNPS0hg1ahSbN29mzJgxzJ8//5nMP7Ozs5k2bRoLFy7E19eXQ4cO/WGH62mgVCpZuXIljRo1omPHjlSrVk3+Lj09nYEDB7JixQoCAgJ455138PLyKuFRuHLlSq5fv8727dt57rnnOH36NPfu3WPs2LGlBr28vDwOHjwoz9Xl5eXRvHlzMjMzuXHjBkqlkp07d9K7d28qVKhAbGwss2bNYsOGDVy/fh2LxUJKSgrjx49n7969nDhxQnZUN5vNDB8+nOHDh+Pu4UHQmA2Y83OI/7IvSldPwsasw5ydQsKiIShdPAkds46sYxvI+n0jLlWaolDryL95ApWrNz4dRnFQVY+0XMNjO38LFizg66+/JiEhAXd3d6pXr863335LlSpVAKkzcOnSJd555x0++eSTf/p+/RXwtxvx/eMf/2DRokUkJycTEBBAs2bNmDVrFhUrVgQonIB+ulw8FI34XN09MRv1xMfHI4QgLCwMFxcXMjIy0Ol0GAyGEtvWqFWbnCbDwScC/f0rkm2IqxfBwxYhhODBd29hLcgmsN8nOIWW3itXKwQVL69AZTVw5swZ2UZn/vz5hIeHI4QgIiKCuLi4Z7KAslqt/Prrr7JB6bBhwxgxYoTsvPwk5OTkMHDgQFJSUvjxxx8JDCxptGtDyQn/0vFHE/lCCNauXcvrr79O27ZtWb16dan7PXjwIP369WPUqFG8//77KJVKLBYLjRo1Yvz48fTv319eNz8/n82bN7Ns2TJu377N4MGDef3116lUqZJdm8nJyVSvXp0jR45wLsv5X3I+NsTExDB16lR+++03PvzwQ4YPH/7Ulko2WK1WVq1axaRJkzCbzXzwwQe8++67T719Xl4eX331FXPmzMFkMjF27FjmzJnzT1sgPYolS5awfPlyTpw4gVqtRghB7969CQkJYcGCBWzdupUJEyZw7tw5fH195e0ePHhAaGgoarWa5s2bk5eXx927d/noo4+YM2cO8+bN47XXXuPq1avs3r2b3bt3c+rUKRo2bEiHDh3o0KEDnoGhNGpQn+T4GNwDwlB5BWFMS2DOzGnM/3QOsbGxqFQqevXqhcViYdOmTTRr1oyTJ09St25dXF1dOXZMmp9XKpX4+/tjtVpJSUkh4o1vyM9IImWLZGYd/OZSjIm3SN3+GS5VmuLf/QPZJgjAKaI2VpMe44MbqDz8qfj2asa3q8ybLUvOgd6+fZtKlSrh5+dHz549yc7O5uTJk6xYsYLWrVtz5swZmjZtypdffomLiwtDhgxxjPj4G4743n///VI9zmywvYSe9uVl6zC/MXQICxYsYMWKFQghMBgMjBw5kvnz5xMUFERMTAzNmjWjbNmyeHl5ceXKFY4cOYI2YS5l3liMU3gNPBp1I/vUVjIOrEBYTFjzM/F4rvdjgx6ANT+T3/bsQoWVzp07YzQa2bp1K9euXePixYvExsYSFxeHs7Mzn376KZ07dyYoKIjx48eXyibMyMhg5cqVfPPNN3h7ezNmzBi2bdv2VIQPgDt37tC1a1eaNm3KhQsXCAoKemzAfZZOhhBQYLIwe1c0gF2wuHjxImPGjCE+Pl52XH90JCOE4NNPP2X+/PmsXbvWjgSkUqlYuHAhvXr1okuXLty6dYtly5axadMmmjZtysSJE3nppZdKjBxtCAgI4IMPPmDwrOVkVXgB/T95PiCRgWbPns2aNWsYM2YMixYtwt3d/Q/bfRSXLl3irbfewmAwUKZMGTp16vTUQa+goIDFixfzj3/8A61WS2hoKJs3b7Zzuf9X4s0332Tr1q3MnTuXDz/8kJUrV3Lz5k3Wrl3L7du3GTFiBDt37rQLegADBkhe6CaTibNnz6LRaNi0aRP169fHaDQybNgwRo0ahbe3Nx06dODtt9+mTZs2uLu7ExWXycJDt9n58zyS42NQufngNWA+So0TKqzMu60nNUvyufvggw+YOVMKXqdPn+bkyZO4ublx9OhRbt26xYgRIzh16hQvv/wyR44c4eWXX2bNmjXk3L+KOStZ8rbLTcMQdw3jQ4lZrguraXcuGr9wAl6dhTkriQdLhmHJTiEvO4PriTmUBtsoMzg4mB49elCtWjVCQ0OxWCzk5+fTv39/2rVrx8iRI0v45v2d8efoZH9x9G9Slk3Dm9C+WiA6tRIntf1lclIr0amVtK8WSIC7lH5o1aoV1apVY+nSpSxdupRq1aqVSAP98MMPNGnSBHd3d2rVqgWAMS0Oc04aAF4tB6DxL0vupb3kXT2IJqA8Xs37PvFYMy4dwGoy4FMmjIAyIVSsWBF/f3+uX7/OwYMHSU1NBaSX2N27d+nduzcJCQmMHj2an376SW7n0qVLDB8+nPLly3P+/HmZGTdo0KCnDnr79++nadOmvPXWWyVKSR5FVFwms3dd/8OgZ3hwg+Sts4n7qj+xn3bj1hf9eLNvD774bi0ZGRmyIW3fvn1RKpUsWLBADno21q9CoaBixYps3bqVM2fOlMp8rVq1KuHh4VSqVIlevXoREhLCpUuX2LlzJ127dn1s0LOhZfcBJAU3e6qgVxwFJiuzd13nUnwmII2u5syZQ2RkJCaTiWvXrjF9+vQnBr0ffviBatWq4ebmhqurK9WrV+eLL75gwoQJtG3blv79+xMUFETdunWZM2fOHx6TwWBg5syZ+Pj48O6775KWloanpyd79uz5twU9kMyjly9fzldffcXPP//MpGmz6DFlEe9uvUKHOT9Tf/TXnC/wJS23KHsyc+ZMDh8+jC1xlZOTg6enJ9OmTSMiIoIDBw4wYcIEdDodkydPZtGiRXTp0gV3d3fWnYzh1e9O8lt0EgXpiQBo/CNQaqTn3YISpc4Fo1V6nrLdI+T9xsTEABAWFoarq6udoWxKSgpDhw7l4cOH0vWMj8YQH41TeE20gRUwJFzDkCB1eJzC7QOfNrA8CoUCpVPRvLkw6snWm0q9ZlWrVmXGjBkkJCTQvn17wsLCiIyMJDo6mjNnznDz5k0yMjLo3LkzCxYsACRz7s6dOz/7DfoL4W834nta1Ar1Ykn/BqUSUiLLuNOrnkS42P1hUVAcMWIEb7/9NgBff/21XXu3bt2iXr165ObmltiXNT8L3H1RqDR4NOxK2q4vAfBo8DIK1ZNvkTlLItYk3b/Lt4sW2n13+/Zt2rdvL/89adIkgoODcXZ2ZtGiRfz000+YTCYWLlwo96ijo6Of2UlcCMHXX3/NnDlz2LRp01OlU785dBu9+clzqXnXj5H686cgrKh9Q3Gu2BBhLMDw4AafLPiGT6e+S48ePbh27Rrbt28nIiJC3nd8fDwjR46UnaPd3Nw4cuSI3byYEIKjR4+ybNkytm/fTuvWrYmOjubAgQNUr179ma7Bt0djUKi1/Jl5A73ZwsKDt2hQcIEZM2bQvHlzTpw4USKl+jjExsYSERFBq1atiIuL45dffuGdd96hQ4cOXLlyhQ8//BCTycSyZcueOKdnMplYuXIlH3/8MRkZGej1epydnYmMjOTChQv06dOHEydO/IkzfHqEhYUxZvrnvLnuHB79v2TD5WxpjjQwkugCuLfvpjznq7t9mM3fLsZisaBQKBBC4OLiQp06dRg5ciTNmzeXO22DBg3ihRdewGQy0aBBA0ZPmsaFs6ewFOSicnZH6SIR3kwpsVhNBrJ+30j+zRNyXS3A92cf4LfpMB/2aSXXOd6/fx9XV1fy8/Px8/MDJDLbpEmT5DpVfdxVrPmZuNZ8AZWzO3k3jmPJTkHp7IHGPwI7KKT08aN3ycOp9I6XxWJhypQpfPTRR9y/f59FixbxySefMH/+fHkkfPLkSbttsrOz+eWXX57txvzF4Ah8fwBfN12pufXSMHDgQCZPnoxCoWDAgAEcPHhQ/u6XX34hNzeXmjVrcvToUQwGQ4k5KKs+l8yj60GpAiHIPLoO58rPoXJ6PGtS7RkAgEvlpvj3+ECeOxrV2Jehz9dApVLh4eFBdnY2I0eOxNPTkw4dOgCwZcsW7t69y+jRo+nevfsfjmpKg16vp3HjxkRHR6NQKHj11VepXbs2GzZskNe5cOECEydOJDo6mlatWvHVtys4fDMFIaSXQuaRtZiS76HQ6HAqVw/v519HodaSvvsbEFZcqrbE7+V3UCill4LVpCdtxzx0hXVsK1euRK/X4+npSc+ePfniiy94/fXXcXV1JTMzEwAvLy8iIyNRKBScOHFCDu4BAQGYzWaEEDRt2pSwsDAaNWqERqNh4MCBfPXVVwD89ttvvPfee9y9e5f8/HyCg4MZPHgwM2bMIDXXwPbNG0jaMR9daDW0QZXIvbwPpUaHV5shuFVvQ+7Vg6TtmIdTuboE9vkYgLxrh0nd/hlOZeuy95WPuHHxZ3766ScaNmxod41TUlJ4//332bt3L5mZmVSrVo3p06fL9/Hdd9/l3Xff5ebNm4wePVqeU37llVdYvHgx58+f5+DBg3b3NyYmRk7N6fV6vLy80Ov1NGjQgA4dOrBs2TJ8fHyIjY3F2dmZChUqcPLkSQ4dOiR3Lv4VLNxHse5kDKvue6Er3xALSiyPsJ1t7Oc9VxKxmstiDG+Mt+EIRqORzZs307Fjx1LbrVSpEocPH6Zx48akpqUhrFJnyrWC1JnSJ1xHoXHCkptO4sqxWI35CJMRhdYZYSyQGlGp+e5MGum3FvDJpFE0atSI06dPy/tITU2V64r9/PwYOXIkn3+1GEMh69sptComJzeyT28DQBdW/anIRTq1ksgypY/44+LiaNy4MS1btiQgIIDff/8dkJ731q1bU5zCsWrVKsccXyEcge9fCE9PT44cOSJ/Lg5bkLt16xZjx44t9cFL27sYS04qnk37ICxmsk/9SPrexfh3efycjGu11mQf/4H8m8dJ2jQVtWcg5oxExsy+gmnLIcZ3b87w4cP5/PPP0ev1GAwGVq9ejUKhYMmSJXZkjmfFw4cPef7554mOjiY8PJxOnTqRmprKsWPHyMkpmpP48MMP6dWrF3fv3uPXX3+l47BJWOr3xpgSQ9L3U1CoNDhXaIglN528y/swZyXj0aSXXLTv1fw1OeiBFDDyb57APawcqrw8DAYDCoWC5s2bs3XrVo4dO0ZKSoodxf748eO0atWKO3fuEBkZaXce7du3Z+PGjUyePBl/f380Gg0FBQV8/fXXdOnShbZt25KQkICfnx+NGjXCZDLx008/MXPmTKpWrUpmmaJAZYi/hrCY0JWpjD7mAum7v8GlYmNcqzQj47dv0cdEYc5NR+3mQ/7t04X3sBUajYbXpnxFw4b2nSyr1UqXLl1kEkWrVq34/vvv6dSpE0eOHKFZs2YUFBQwevRoNmzYQLly5TAYDFStWpWsrCzWrFnD8ePHS6RKP/zwQzl1GRcXh16vp2LFilSvXp0VK1YA0KVLF7kkoG7dusTGxkolBRXq/MtYuMWx7mQMM3dcxaJQ8YfxQKFEqXHC+/mhGF1d+W3xRzKL8XEIDAzEZDIhrCU7U8JqQX//MnmX96OPu4K1IAe1VyDCasViC3yAUqNj930r59u1o27dupw7dw4XFxdycnJwdnbmhx9+oHnz5uzYsYPly5djKJAyPEpnD9Q+oSidiu6DU9jTpY0F0KteaKnfeXh40KhRI37//XdSU1Px8vLi1Vdf5cMPP3yqtv+ucAS+fzHq169f6vLevXuzf/9+fvjhB/bt28e8efPs6tryoo+Sf+0wGr9wPJu9CgIKbp8m/9ph8io1xrVq6bRxtbsvgf3mknl4DYbEWxjir6Hy8Me9XieWnEqhWc2HbNq0SV7f1gMUQrBly5Y/HfjOnj1Ljx49aN68OdHR0SQmJrJ8+XJq167N1q1b7difw8dNIi/yJRT3zHB0Awl3ogmoBzkXfgWLGU1gBVSuXqhcvTA8uIHh/iVMFYquo9pT6jRkHFpF9skt8nKLUoPBYECtVtO9e3eCg4Px9PQkOTmZ8PBwLl++LHdAVCoVOTk5fPDBB/Tp00dePm/ePPr378/x48eJjY1l0KBBdOzYUSYKXbhwgbZt2zJw4EACAgI4f/48aWlpVKhQgbNnz3LgwAFcXqiC2SJdV6WTO0H9PgGFkvuf90CY9JjSE9CVqYRrtdbknN9J/rXDuDfogv7OWRRqLS5VmmKywo2HJQkMZ8+etSNRuLq64ufnx4IFC/jmm2/IyspizJgx+Pj4oNfriY6ORqlUUrlyZT755BOOHj3K/v377UYmX3zxBffu3QOkuta5c+dSvXp13njjDVJSUujZsyerVq2yq890dXUFYP/5G3ybfvKxxC/biGzvtSSO3Ez9Q9aqDVFxmcz6JRrjM1b2mFHi3KwfBteSDN6vvvqKdevWcfv2bYxGI8HBwUUZgEc6UwqlCueydXAuW8eujQcrxmABfF8ah1NELQxJd0k6sJqb8Vc5fPgwlStXZty4cYwcOZLKlSvLc2c7d+4kPT0dzEb8un+Aa6UmoFCgcvUqod4E4NWiH14t+sl/K53ciJi8E4UCXqwW+NgRtI+PDzt27HiqazV48GAGDx78VOv+1eEIfP8kbJPcxWEymdBoNHTr1s0u1bBs2TKWLVsm/92nTx+5uFUbWB7Xqi3s2gl+Y/FTHYM2oBwBr0wrsdyogNnbzpKamoqLi4tcmPvPYv369YwbN46lS5eye/duQJprsFqtnDlzhmbNmhEVFSWv/2OsBpVIQmhcALAW9qAtWUnScT64gfHBDbt9CLNR/mzOTkHjE4IutBou1VqRf+0wAGlxEjPObDazefNmu+0tFoudBJanpyfPP/+8XFRsg61428vLi9jYWKpUqUKbNm0ICAggJiaGvLw8AN566y2WLl1a4lqkpKTgrTeTtmsBAGqvQBRqqdxAoXVCGPLlVJlb7RfJOb+TvKuH0ASUx2rIw6VKM5Q66bo8SmCwpaagiEQByCPWPXv2cPr0ab755hs6dOiA1Wrl7t27dO7cmZ9//pkRI0ZQqVIlZs+ezerVq+V2Dx8+LI8Kb968Ketkvvzyy6xfv55p06Rnqfh8tO3zqUQzLiFPfoZSd84n78p+3Bt0YTYjgJKs1eIQQjB3xwX0RjP8Cfk2o0Ww6NDtEkXeW7duJT09nS5dunDjxg27ua7HdaaKByVzZhKm5Hvy31ZDPkmbpmLNz0Ln7IKTUsHNmzf56KOP5HWmT5/OsGHDWLJkCY0aNeLtt98m+8RmXCs0AOWzlaGANG0xsnVFZs6cKQXSR/DRRx89UQ/VgdLhCHxPgWPHjvHWW29x9+5devTogclkYtOmTYwdO1ZmczVr1oyaNWuybt063nnnHXr06MHw4cO5ceMGubm5cp3NF198gVarJSMjg+HDh7Nv/wGysnNQuvngXK4uvh1GIywm0vcuJv/2aaz6XFTOHqDS4FKpsd1xKZ3c8Wr+GiC9PDKPrCHvykEs+ZkondzQBpRD1X0ScckZ+LrpGDJkCL/++isvv/yyXQB+HAYPHszq1atp06YNWq2WI0eO4OHhgUql4sCBAwQGBtKnTx+USiUJCQnk5eXx4osvcvfuXcaMGUOewQyA0QpOAh7NX6kKXz7uDbvh88Iwebkp8yEqVy9yzmzHqs8h68RmfF8ai0vFRqjd/eTA16T3SE58LwlhZ2Rk4ObmhkqlIisri4SEBLt9JScnl0rMeLQWzfZ3gwYNiImJkV82tlHzqlWrGDBgAKNHj2bx4sUIIfBwKvYzUhRvz/58tYHl0QZVxPjwtvyyda3WSv7+cQQGKBJn12g0rF+/HpAo7GfOnJEp7baaxPv37wNSHSJIxd2vvfYaH330EQUFBUybNo0OHTpw7949+vbti7OzM7du3WLHjh0So7Aw+Bw5coSyZcsSGxuLm7sHACn7lxPRoBuW/CwyD62mIOaCJMbuF45X8744l68vd1pyLuwi/4VhzPzxDAOblicgIICHDx8SFxdHeHg4Hh4e9O7dmx+2/kR2eqpd8bZS54IlNx2VRwChI1c89rpkn/mZ7DM/8W1OKksHSszQhg0bsnTpUubOnUujRo1ITExk2LBhMgEGHt+ZMjy8Tca+pRiT74HVfviZe+k3iYimVGMoyMdc+KzYmNPR0dFERUURHR3Npk2bGDp0KM2aNaNFixboT2zA+/nXn7o+GMBZo2TKS5HUCvWiy4oVxMbGllhn3LhxjsD3J+AIfH+AzMxMXn75ZTIzM2ndujXJycns27evxHq///47KSkp9O3bl/Lly5OSkoJWq6Vnz56oVCp++eUXvvnmG0JDQ5k8eTLz5s1jy5YtNGnSBJcyFTh1+YZMcc69coDcqL1o/MJxqdwUc8YD9DEXSzg7qDwC5MCnj40i+8RmVB4BuNV6EWtBtjTfZCxgy/l4AtIusWrVKnbu3MmZM2cAycFAoVBw7NgxmjVrBthLrdlGGAcPHqRcuXLodDqSkpIoU6YMlSpVktUqVCoV48ePx8fHh6ysLAASHiaTWVA6BdsG99rtyb24h5yz2zFnPkTl4oEpLR5DfDRutdvJI6e8y/vIv/E7zuXqYTXp5e3jL51AoVCQkZEhXQO9HrNZCraDBg2iR48edO3aFZAEkU+dOkWlSpWeKr1rO/c9e/YA0vxQVlYWX331FXv37mXbtm3yupFBHn/Yng1utV8k/eFt9DEXUOhcca4gzQ86PYHA4O7uTk5ODnXr1iUpKYns7GwUCgWLFy/GycmJWrVqUa5cOYKCgtiyZQt6vXSN2rdvz8GDB5k6dSppaWnMmDGDXr16AdC0aVPOnTtH48aNKVu2rF2noHbt2ly/fp27d+/KrMjcnGyUTu44RdRCCCvJW2ZifHADbWAFnMJqkBd9hOTNMwjsN1e+b1jMmFJiKchOQQhBUlISI8dP5MCv0qjKycmJatWqUfVhHqd2biT/xnGcImqj8Y8okQEoDaaMB2Ts/w4UShACVy8fMBs5c+YMbdu25c6dOyiVSlJTU7l16xZarVYWknhcZypj31IM8ddwqdIUFCryrx+V92dMugNI0wvmrKQS2ROjUQr427dv59q1a1SrVo3IyEhiYmLYdvg8624JrpeSzn4UpYkblJZZcuDPwxH4/gA7d+4kMzOT8uXLc+DAARQKBXXq1LFL5YH0cjp16pSdXqNGo5EDYpUqVUhISODAgQNMnjxZ7qU3btyYvn37cinXlc8PxGCwAoU/KI1/WVyrt0bjF45S62w3J1ECFumFr/Eug2tkc2kbF0/MCM5F32Pbh8MZMWIEnTp14vDv9iOfoZNnU6lSZUKcLRza/1upzcfExNCmTRuuXLlCYmIi+/fvlwksTk5O7N+/n8zMTFxcpLRdpvFR05WS0AaWJ/DVWWQe24Ah7irCakbtGYjHc73IPrEZbXAVtIHlKYiNQhgLyL/xOyo3H7TBlbEW5BAXfR6EQKFQoNVqsRb20CMjI1m4cKHdHFX58uXl+cdnsWpJSUlh165dLFu2jOHDh3Pt2jVCQkJ488035bqoXvVDsZnqWPU5JHz7Bpb8bITJXq0n/9Ypci7ulv9Wu/sihAUFmicSGKpUqUJGRgZ37txBpVLh6uqK1Wqld+/etGnThueee45Dhw7x22+/odPp8PX1xWg0MmDAAFQqFR9++CFTpkzhvffe45133uHBgwcIIdDpdJw/f17uCNlgs7UKCQnhwQPJGkuhcUIA+vuXSdowBeODGyi0zgT2+wRj0h0K7p7FWpBD6o7P0QUXkUwMCdF2xdubb5pw96sEN26g0WiYPn26bCemdPEk4NVZ5F87TGph4LNkJxM7V5o3KzE3Zgs8wgpKJa/MWM2KtzvTtWtXtm/fztKlS3nnnXeoXbs2nTp1khm6IHWmCu5dQOXkJqfeAUTh70gIsOqz5eW5l/ZizpTq8tzrdWLQm2MYUMla6py+Xq9nxIgRMtFt2+UUZp/M+8PyHRuqBrkzt0cth+vCvxGOwPcHsKXMqlSpIlOPq1atWiLwVa9e3S7o/eMf/yhVRDclRWLCjRs3jqioKBYtWsSXX36JSqWi/cvdCe3+LgcsbTHFXyb35inJCgkFTmXr4N9jCkpt6cXkTuXq4lavE3lXDpC0Udqvtkwl/HtO5fpZaZ7v3KWrhNdpwcO4u0UbqtTcOLGPO5fOYM6WUjY2PzFrsVSPEIIDBw7IabBTp07Jws95eXl4eHiQnJzMokWLmDJlCil3rxHY/zM71RmPhl3xaCiNwEqkc1280AVWJaCXNF/iXKGRvK05M4mEJZIGqn+vj9AFlMdw9wwp2+bwzTff8OabbzJ9+nRmzJgBSLqa7u7urFy5kkcV+bp06cKOHTuYOnWqrMIBlGDZrlq1ilWrVrFr1y7Gjh3LlStXiI6Otltn/vz5Je6D1ZiPc/kGFNw5gzDk4d6wG04RtSi4e46UHz9G6eyBys0HS246ptT7pO9dgn/ncbSp4l+CwGC7/lFRUYwdO5YePXrQqlUr8vLy6N27N7GxsWzYsIHq1atTsWJFWTA7Li4OtVpNs2bNMJlM1K5dG6VSyeHDh0lOTqZRo0Z4e3vz66+/4ufnx9ixY5k6dSqurq7k5eXRuHFjmjRpQqNGjZg0aZIkw2c24lyuLljMFNyRAqXKzResZlK2zMRqkOZCrfo88q//Lp+DIV4KfE7hNTGlxaFPuE524cjJycsfPz8/rsenYkhLwJqfRX70EdS+IUUXQaPDvXZRLWpxaPzCcG/QRcqEWK2sHPsyR7+uKN/zqKgoLBYLb775JsuXL6datWpcu3at8PlqSMHd81hzJfEI1Fp82r2JxjeM9D2LKLh53G5fhvhr8md9bBRbF85gQ6z9O8DJyQmVSkVBQYFMKkp0rfBMEogA91LzuBSf6Qh8/0Y4At8f4EnmtcVh8wK0wTYnNHPmTD744APmzZvHpEmT5B+lj48Pu3fvxmAwcOPGDQYMGMCun7ZwZMLbTOv0Ajs61WLt73e5d+8O6b8tRR9zgfybx3Gr8XzpByqs+LQbgU+7NzFnJpH1+0byrhwgN2oPTtWlQtozx4+W2Eyh0iCMBbjVk3rVmYdW4dGgCxmntskpM5CCoZ+fH2lpaVitVlauXMmoUaPQaDSYzWYSExOZOHEi+/fvB8AprPoTpdYeTedactMxxF2Vv9f4hpK+TyKTWPVFJIu8a0dw8o8g4/gmtm7dKvvHNWnSRPZrrFq1Ki+++KIsdnz79m0WLlxIQkICu3btIiQkhIEDBz722IrjpZdeYsmSJXzxxRdPlLqzwbf9aFwqNyH/5klSts4i78oBfF4YRs45iXmn0LpgyU5GoXNFGPLIu7yfkE6juLPhY+rOuy+3ExkZKRcZ165dm88++4yRI0diMpkYPHgwK1euxGQyERoaytWrV1GpVGRmZhIXF4enpycxMTFyRywhIYEePXqQn5/Pe++9J8tZHT58WK49g6JA26FDB6ZPn47ZbGb06NEAqNx9UXtIHnu2Y7dkJ5N34zhWQ568zLlCA8xp8XJaUB93FUtuGqjUCIuZvOu/I4wFKJ3dya/WheQz2/D09CI5Tepg6mMv4V2+aBSl1Lnh03Y4AJaCHFnPEsCpbF28nx+KJS+D/Oij8r22ISEhgZ49e/Lzzz/Trl07pk+fLqf0SyODAQizieChC7Hq8yi4e47U7Z8CEP7ez+Sc3UHGgWUYHtzg/t1zxbZSsOPIOTq3qAtIc35Hjx7FNbwas9dGPVPQgyI1n1qhXn86+MXExPDuu+9y5swZHj58iK+vL506deKTTz55JkeWvyocge8P8CTz2ifBVre3bt067t69aycPBjB37ly2b99OzZo10Wq1cg7f09OTvTu2suCTT/AIq0JemglTivSdUuf62P0Z4qNJ/WUBupBIlM7uGOKl0YnOxZ1yTV8i0r+h/AMsLojr13kCmUfWkntxDyDQ+IWjDqkGbEOhUiPMJpRKJTVq1CAlJUWeQ4uPj8disTB48GC+++47dDody5cvBySCgW+X9558gR6TzrVBGPJLdavPv36UkABfwlysHDhwgAMHDtCoUSP69u3LyZMnOXXqFI0aNZLTkLZj/fLLL+W/27Rp89QO5SCN7Bo1akT//v1L2O9cu3bNbmSv8ykjnZevlLa0FmQjzCZZYceS9bDw/PJsZ8rgGs7M/nq/zCAF+xFoVFQUWq1WHm3b5pY0Go3ckYqJiaF169acP3+exo0by0HPxu7s3bs3p06dYtasWSXOr1KlSlSqVIlbt24BsGPHDg4ePMiECRPk+23JTilxP4TZSNbR9cXOR4F73ZfIOf8LxqQ7KJ3cZMsuwyOjI4XWhcTN0oi7+KyXJT+rxPHJ+3v0mRBCCkzCCihQKhVYrVb8/f1JSUnhzJkz5OTkoFKpSEpK4ptvvinav4JSyzGSt8zEkpuGJS8Ta0FOsV0J3Gq/SNaJH7AWZONcqQmm5BjMhfdz7OZLZGq86d+kLH5+fnTv3p3ha88+dXrzUejNllKZqk+LmJgYfv75Z1544QWef/55Nm/ezHfffUd6ejpbtmz54wb+4nBodf4BvLy82LFjBzVq1ODEiRP4+/vLo4xHR3nFMX/+fOrXr09sbCx37txhwoQJdt/Xq1cPtVrNTz/9xJo1awgMDOSrr76iVq1aVKlSBT8/P26dPUrWxb2gUuPZtA9pe5cQO7cz+tiSgVfl7ovGJxh9bBS5F/cgzAbc6nbEvU4HDt9MeWKv061OR8yZiZgzH+JWt0j5QhQyFFUqFVFRUfJ8jw3Nu7zG2h+2olAoMRiLyg9qdhqM2t1eSPhRuNZ4HpfIFhTcOkXSuveIX/AayT9Mx2qURplqr0BC316Ptowk2+VWuz1hE7bQ953ZpJ36idu3b/Pll1/y5Zdfsnfv3ifuq3Xr1litVuLi4ujYsSPr1q1j4sSJT9ymOCpUqMCoUaPsxJ3j4+MZNmwYrVu3pkWLojKUzmEWnDUqzOnxgFS4rFBrZIUd77ZvEjF5J2Xf30nk1F+Zt+Uw7/drT05ODmvWrCEoKIg333yTFStWyIFOo9EwYMAAQkOlYHrkyBFu3LhBvXr15NT52rVrZYmqy5cv8/DhQ4YMGcKECRPYuHEjbdq0ITExEX9/fx4+fIjBYJCDo1arZf/+/XL5R1RUFMnJyQQHB6NWS31jXWh1IibvlP+VeX0hrtWfR5gL5zFVGvx7fohTWHVZ5ktV+AwonT0In7SD0DHr5OtkyZUISX6dxuNew94r0R5F0UntFWh3DBr/CISxQGKRKopqVG3XxDYHbbFYuHTpkp2akJNaerbN2amk7vyC+EVDiP2sO8akO5hzUrEWZNvtO+7zHqBU4dtlIkpXbwpunZSDHgjyUh8wY/NJFAqFVEuaXcCBqLvE/ONl4r7uX7ivFGLndibuq34SC/voemLndiZl2xxSd8zj/rxeJCx5g4KYiwgBB2+k2OmSFkfZsmVRKBR88skn1KxZE3d3d7p3705ampS6tXVkfv31V1asWCFLKP7Rb+XvAseI7ylQs2ZNLl++DBSZ1wJUrlz5sUWh1apV4+zZs3bLpk6dKn9++eWXefnll0vd33PPPcfRo1LqpriJZe6Vg6WuD6DxCSHwVfvevEIBPm46Uh758Xi16Efu5f1yb9ytxvNkHl4FKHCr/jz6+/aB1WQyUbNmTRZt3MG3h26wbrQ053Lv3BFUrt44V2labF5Hwe3fd+JTsf0TpdYUShX+3SYhrBbMGQ9KpHPNWckkbZqKOT0BzyY98ShfmzltA4g5F41o3561a9c+tu3iyMnJwd3dHYVCQWhoKC1atODXX3/l5s2bT7W9DZMnT6Zq1ars2LGD33//ne+++47hw4dz8+ZNtFqtHEi3LZpN3SYtuFdIErK91N3rdabgzlkyD63E/OA6wX4eKDPi+HptJh2q/sLIkSPJzs7mp59+ombNmoSFhcmpxwYNGrB8+XIuXrxIgwYNiI2NpUaNGvL3KpVKps6XLVuWmJgYwsLC5NHa2rVr+fXXXwEpKNjk2myBtV+/fkybNo0WLVpw584dhBBotVouXbrEkCFDWPDV1xjirxL7SRdpmKRSg8VMyIhleLcbTvzCgWA2krpzHkpd0ShP5eZL8NBvyL16kPufvIxTuboyQSXu6wFY84yk/bYE14qNUGl1WIzSc6p0ciNkxHISlgzFmpvO/S9eQZgMKJ3c0PiF49thNBrfUHLOS6lgXUhV3D080FoNPLguEXPCKlXj1MmTlPFxJzU1lYkTJ5Keni4Xe6d8N4zMAhOWrBRAoHL3w61GG0yp9/Fo3Iv0fUvl8wBwqfwchoRoUjbPAKsFpbMHwmpGGKSSEWExYdK6o/ULJzv1Pl9tOUBB/DVAYM3LxJTxAGOiNKJ2ekSq7FE2a/L3kuqKW+UmbHmMHZENs2bN4pVXXiE3N5effvoJpVLJjz/+KE/R2GBjnNo6T393OALfU+BJ5rX/boxqXZGjt1K59eUg+YdoI684la2DQqXBkHgLYZZeDM4VG+HdcgBKJzcUwIO710k7sLLIBiW4Ct7PD7Xbh9LJlcB+n8ifbSheRH7lyhXad+2JKce+iNajaW8MCdex9Y41fmHkp95HuXcxvk+QWsu7dpisU1vQBVVCoXUqkc59uHYiltx0tC4euD04R4eaPvy+fQMbN24swUJ8Erp164bZbCYyMpKMjAy2b5dSZcXFu58GSqWS1q1b0717dwYNGkRUVJT8EiluMjxz5kzef/99DLlZKNQaXNzcCDUlUK5dW45lxZBz7QjG+As8TJAcI4LKl6dVq1ZMmzaNt956C5VKxW+//WZXrKxQKLhx4wYzZ87ExcUFZ2dnkpOT5Zq7du3aoVKp+Pnnn/H09MTJyQl3d3d55LN+/Xr69OnD5cuXiYmJkcs/bMjPz2fy5Mn4+vri5eVFZmYmly5dYuzYsQwfPpx+Away/vvNUimJxQxWMyDQ37+MW622eDToQvbJLVKxvkKJ0sULa34m+tgorIb8UuXatH7h6PMyEGYjwqQntHYLYs8UlQmpvQJxq/UiuZf2SgIAKg1KZ3eMSXfJPLwGlbsvpuQYQAp8GVcPYcnLLLxZanRdptF6/jFaV/Gna3mtXQE/QNpD+zpPS0E2Xi0HoHL1lpid++zFCvy7v0/e9WNglVKXVn0eKldPFC5emDMekHvlAM7l66MLq4Ex9T7Hjx8nN/bmM1kRGVNiebhidNExCR5rR2TDrFmzGDt2LFFRUdSpU4etW7eSm5trx2i+ceMGU6ZMQalU8umnnz6xvb8LHKnOp0C9evU4duwYs2fP5ubNm/Tp04fDhw/bsTj/Xagd5sWUlyLxrvsiimJzYAD6mIsU3DmDNT8Tl8rPodQ6k3v+F+IWvMrD9ZMx5qSTuG4y+nvn0QVXQRtYgYI7Z0ja8D5C2Kc+dUEV0QVJZrwyE7JwHa2LO0II8u+cw7U4uUapIvPIOqkGSqFA6eyOT/vRaHzDyL12mLzoI489L41vCCpnDwrunCU36jc5netcsREAllzpxW/MzybhfgzfffcdS5YsoUaNGk/tWgCSXdSDBw9Ys2YNe/bsoUqVKsybN++piCogpclWr15NlSpVyMzMpFGjRtSsWVMOeocPH2bz5s2kpqYihGD48OFs2bIFDw8PhNlE4sH1nF34Nh+3C2Hvwg+gIIvr0dGsWrWKlJQUypQpw+XLlxk9erRcPJ+cXDTSuHPnDjVq1KBGjRps27aNnJwckpOTGT58OEIIqlSpQpUqVdC5uKHUOpGVlUXT4bPo+/UeuY1FixaxevVqzp8/bxdQV69ejclkIjAwECEEer2eMmXKyJqXH330EV988QWrli2l3ciZeDXtjXv9l9EGSs+Jre5U4yNdC6WTO6Gj1xA6apVUW2e1YEpPQKHW4lqtNQgr+dcOI6wWjA9vo1BrCRu7Eb+eU1FXbsGczUcJ6Fo0N+zRqLv0QakCiwlzegLCmE/+zeOFZCHpOdWFVUfp7IbCJkZgNXN7Xh9i17zHmqlv0KlZbXwDgxkxYoRs4hsZGWlvqmw2kvbzJwiLSZrbLv77UCiJXzyU3AvSqFntE4pbrRcQwiqXOOgLyS66QpuhmGsX7KyI9PFXpcAJZBxYTtzX/cm7KmVwbFZE2Sft1YegpJrPo7ApDxXXny0u3nD27FlatGhBRkYGK1as+NvbEdngGPE9Bf7IvPbfjf5NysLcjxnSYS9mYwGBr83BKaIWST9Mk39wbjXbonl+KPFfDwBhxWoykHflAFZDHrrwmjKL7cGKtzEl38Wnw2jc63QodX9qD8leRaF1xq1WO0l/JO4qxqQ7WPOziJi8E3NWMqk7v8AQd0XaSAicwmuh8Qt9Kqk1XUhVgvo/rvcpCOkznW9eq0PXrl3ZuHEjX331FadOneLcuXPUqFGDCRMm8Prrr9ttNX369BI1eh999JGdpNTTQgjBrl27mDx5Mp6enmzYsIFmzZoRHR1Ny5Ytee2113B1deX1119n8eLFduaozz33HAUFUm2Ys7MzGzZskG1sevToQePGjXFzc2PVqlVySUhxBAQEyJ/r1q3LG2+8QeXKlWUqPhQpzERHR5cos7gQfYs7LkUvwj1pHtSPyywhGL1582bGjx8vk2omTZrEhx9+yODBg7lx44as/PLWW2+xpxS5tkeJKBq/sD8t11a74XN8995AWg35gNOmUPRmCxq/MDyb9yPn3I7COTcp6Ph3n4zGN4z7n3UHYSV1++cIY76simODOT1RYpQCaUkP+GmXJMp9/vx5ypQpI/vl2RRdCu5fIXvLVCw+ZSWFlkKovcug9gqS5y7NWUnkpsej8QtH5eKFKSVGFlZwCpeEpx/euIAxO122Isq9ehBrfiYoFLjVboe1IIeCO4XMUIWK/BvH5SL64niSmg9I9//FF1+0Y5rb0py//fYbPXr0wGw28+OPP8piDg44At//DPo3Kcskdx0PskCjksxxLVnJduuoXDzlFw6WIiahxreIiajxDcWUfFf+DpB7twqFlACwfSeMBSWYfOYMieCS8tNcjIk38Wo1CPcGXcg4uILc87+AQoF/t8lASfq5DcWl1kqF2cS3Y3vS6bkaGI1G9uzZw5UrV6hQoQLlypXjt99+Y+jQofj7+z92nvSfwcmTJ5k0aRIpKSnMnTuXl19+WZ6TKVu2LOHh4bz99tv4+/vTvHlzmexkg5OTExERETKpqVu3bhgMBj777DO2bNmC2Wxm48aNNG/evMS+09LS2L17t/wy7tixI3PmzLFjJEIRScGlUhP8e3wgjbCQSCOKwmBiw+/3sumz9AQvBet5eLRoVFG5cmW+/PJLunXrZpe6fRS20pzhH37OYSJJ+GURuRd2lVxRoSR+0et2c2O2tHyZIV89Ua7tzPEjTJ44kZEjh3EpPpNFh25zIPohgS1fxav5a5izksm5sIvsk1vIPvMzfi+NReMXjiklBmHMR+0VhGvt9tJIUuOEMOlxiWyGNqA8absWoNA6497nUxqZz3L+/HkyMzNZsGABffr0kYWrATLvXYF7V+xOS+1VBv9uk0ClJmn9ZFlVxpSRCBZpROYUUQerIR+Vqzdq31AK0iRy06NWREpnD1wjW6DxCyfbZyfZx7/HajKQtnshrjXbkne5KN2rUvBYNR8bpk6dSlRUlGyB1r17d9zc3Lh69aostN60aVMOHjwor+PQ9wSEA/82RERECKR8jN2/Cxcu/Kn2ypcvLwCxdeev4qOfLwuFWluyfYVSAEITWFHowmtKy1Rq4fvyOyJi8k6hDawgr+vRuKfQlqksUChFyIjlImzCFuHRqIdQuflK6yhVwqfj28Kz2WsCEGp/6XycKzUusV+v1kOkdXzDhFudDkLlESDQ6Eo9f5VHgIiYvNPun9/LE4XGN0wo1Frh4u4pmjRpIjZv3iw0Go3o2LGj8PT0FDExMUIIIVq1aiUAMWbMmH/h3RLi+vXromfPniI0NFQsX75cmEymEuucO3dOqFQqAQg3NzeRlpZWYp379++LgIAAoVAoBCA+/vhjUblyZdG1a1dx7949sWrVKtGoUSNhsViEEEKk5OjFF79eFq3fXyWCX/tYNBm/WLz6zmyhVEr30tvbu8Q1dKvxglDoXAUgnMrVFW51OginiNoCpUqEjFguIibvlNe1/V323W1i+KdrSzyHtWvXFoBYuXKlEEKIQYMGCUBMmzZNCCFEpUqVpPtWeN4oVIXPQRMRMXmn8H1pnACELqyGdN8Lnx1AOFduKtwbdBEho1YJn/Yj5X0rdK4ibPxmETF5pwif+KMYNm9Tiet4/sp14e7tKyo1bisin+8l/CIqC0C4N+wmPzPyM+XmK5SF10MXVkNar0EX+di0wVVE2fd3ivrd35D2X3hvHv2nVGulZ1n96LOrENoylUXI6DXCpWqLUrd1rtJMREzeKdzqdJDacvYQ4ZN2iNAx64rWU2mKHbOPdGwh1aTjDq1u/ztx9Rb9Bgwq9Vm1vVvmzZsnateuLVxdXUWXLl1ESkqKEEKIgwcPlnqMgLh3796z/TD+gnCM+P4D6Ny5s51TQGk1ZDZHhychLCyMu3fvMu8fs8hyDcO5fH3yb0ryYyoPf4RJL9cemZLuoAkoK4kmW8yk7ZxP3qV9UmGxUg1WM9mntuJcoYHU81ZrSNu1gPzrx1B5lUHp4ok1P4v0X7+SxaTNqXEAFNw6hSTAXET3zj71IyAVm+de3I0utDq60KoU3D4NVgvBr3+F2qf0EYXVZCD1lwUoVCpaduxGmKeW8+fPc/PmTTQaDXv27JGp23Pnzv2XM9QSExOZMWMGP/74I++++y5r167F2dm51HXv3bsn+6/l5eXRq1cvfvnlF/IsStmUdc/S2SQnJxMUURFXnYbFixezZMkSeXQaHh7OokWLmLt0I3d0FTh0U6qPVKj90ET4kQhkqCMI6f8Jiks/k3BZchWwiQUo3f3xbv8W7o262dlRKZzdUTq5k/DdiFIZtelH17PqZpFc3fbt26lTp84fXp9+/foxffp0LBYL5cqVI7xCFQ7v240x4TpxC161ExiwQaFSI6wWPOp3ximiVlHtqEIJwlokQefuS+bBFWzSp7FqUj87g9+IMv6UDw8l6tQ+FAoFOicnUKrIu3YIbVAF3Kq3If/uOfKvHpRSmko1KFXy3CMUZTOMyfeI/bwn99VSCZKnpyeZmZloNBrKly9P8+bNWb58OT4hZTGZ9GB+tIxAYEy8iTnjAdqgSuRHH8WpfAN8XhhK2t7FGGIvUXDjOKbMh/h2GM2wyf8gz2jmt+gkFK5ehL+7TTo+hJ3AhGeLfqjd/UlLuIYh/qrdHi15GRw7cuiJ96ZevXolSqWAEia0DtjDEfj+Axg6dCjdunWT/7bJa/Xs2ROlUsmOHTtYvHgxISEhj3X5Bkmd5PDhw7LLMhonbAHImp+F0sUTnW+49ANSKDCnJ6B0csNakAXCiuHhLdS+oZgzJTsghc4Z50qNca/TAUteJvmFk+9Br81GodGR/OMsjAnRsn2QQuuMMORJLLQ+H5O2eyH6QvkqlEpcqjQj/8bvKLTOaIOkQK/xDsaYdAe/B8fJ8OiGEAKlpqj+0WoyIEx6FMKKv28AE4cPoFq1apQvX56oqCj+8Y9/yLT97777Dq1Wy4kTJ6hYsSIjRoz4p+5LVlYWn332GYsXL+b111/nxo0bf5gCunv3rjwnplAouJNhZtT3Ufx+V2JKGsxWku5I80zGyBdxrtuBjlUCCK9TpF+pVCppP2oW317KAVUKCqWySNi5EHqzFWVwVRQhVfHy2EjakfV4eXmRkpKCb9s3UKi0dnZU5qxkEpa+CcKKa9UWGBJvQV4GHk16ofaSOi6GBzdRegTgZMxFn5slkzseJ9dmg20+ccCAAaxZswaQav269+yJk3cQ0Wel5zGo31ziF0nzrk7htVB7lyH/1knyb50sEl8oDERO5eqhcvPGkpOKv78/nZq1K2Hw++qrrzJu3DiGDBmCEILAiEqkGFTk3ysy+PVt96ak2lLINFW5eMnzeiCVCtjgUqW53FG0oVy5cjz33HP8+KPUcXNSq/BpM4Dcy/uwZKeg8vBHodZizkgEYUWpc5XbsOSkkn12u9whBIEp+R7ufsFElnGnSTlfjt5KpcBkeazAhFLnhluttrjVaisfk62TULZCJbp2fsmONQz8qTlrB+zhCHz/ASxfvpxDhw7Jf9vYoD/++CP16tVjwIABBAUFPdHl+9VXX7VjbumCK6PQuqKPkeqW/LpNxqViIxLXvCOv41K1JdaCbArunQeLGefyDcmPPoxCrUUgzeml716IQqWRlUYUap1cbO3V7FWSf5gmz5moPQMwJd9DG1getbsvPu1G8KAw8Pl3fR9Lfgb5N34vdW4wOykeTcYKug0eSZ7Gi22/7MWcn40xJQbnh1HMm/c5n3/+uTwqCg0NZfr06RgMBlQqFSEhIXTq1Ikvv/ySsuXKMWT2Cj769Q7ZejMeTmoigzx4pX7oYw07N2zYwIMHD5g4cSIGg4HFixfzj3/8g5deeokLFy7IQSA11yCP3Epre//+/XIgtlqtmBv25cCNVNly6eH6yTLhJ33PItL3LOLXNxax7bt5qGNPk5uRgpOnH8pGr8rmwsJqIfvMT+Re+g1LdgpqjwDcG3bFvU4HhACzRdqfycmbzr3acq1iYyyPELKzz/wEFhPu9Trj8+IITBkPePDtcHLO7cSzaR+UWmeC+s4BIHHFGMh9vEJKcRTXQF27di1r165l5cqVDB48mLu3bzN7zS4+HNRJXt9aWNdm0/O0wbVWO/mz2ieUgFemoVAocFIrqKh7wOXLlykoKJCzHrNnz+bFF1+Ut/Hx8aHzB9+y43KSncGv2jOgMOhJtaFOEbWwGgsouHUSVBr0hYoxSp0LSidXVK5emI3SMdavX58rV64QGBjIhAkT+Oijj/B00WBCkvIDsOZnIYQVtVcQ7vU6oQ0oJ5c0mDMSMaXFo3LzRuXuhyUnFUtehiw47uumY8pLkczeFY2pmMCEVZ+HysVDFph4FGqV9CwlPbBXHLLh0UDowLPDEfj+A9i5015V3mb0Wb58eU6dOiWrY1it1se6fBd3a3dy8ySg71zJ5fuzboCkCmHJz5In3jUB5fDrNA6A2C96S+LCt6SeqkLnItXoFf64Mw6twqWwjECYDRiT7qINLI+lkMWmdHLFUswOyOY5Z+82hxwwVW4+hIxYjkJd+PIwGTAZ83Hz8qNOjUh2zJ9E0uYfUCqVuLm5kVpYd5SQkEBiYiKbN29m7NixLFq0CJPJRNeuXfH395fYkxFVUHadyurLuRjMRer5TuqHzN93k9ZV/BnZqqIdg/HWrVu88cYbcmH2/PnzqVGjBvv27aNmTYl+HhWXyTeHbnP4plT7ZjBbS21bHVCBN954g++++67wUmjtfAZdIpthzkzEkpOGU9m6aPzCSN+/HP3dc2h8QrBYleQnxsHPn5K+ZxHaoIootM4U3DyB2icUtWcQpvR40ncvJH33QnxfGie3bfUO41piDne32JNpALTBUqfIpnSj8Q5GqXPFasjDnJGINrB8UTuFhIwRI0YwduxY2rdvz1dffSUXtm/cuJEvvviCqKgoTCYTfn5+pKamltBAXXcyhmXHigTPzbnpCIOU9nSKqI1zhQZ4NOpO6i8LyLt6SF7PvWFXFAoFzhol7se+5peDv5Y4nytXrsiuDSDR9vOtKhQqtR1j1FyYjUClJnziVoSw8mDZSADUbj4y+cSal2nXGSsoKHiswMTwtWfJ7jyOtN2LMKXEAgJLXgY2jTONbyjGxJt4NOmJV/O+QKFTe04qKjdvO8Fxm63Q7F0KtK/NKlUmzQabHdGsT2bTv8n6x6+Iw6bon4Uj8P0HsG3bthKpToBGjRrJQQ+e7PJdHB5lyhalxgrnTHLP7yoqLQA73UuFQiHNahcWpFsLC32teRny/7lRRXVfyVtn41a2llx3pC1TmYKckiauj0IbVBFdSCSGhOskrh6PLiQSY0osxoRoFGot4RO3MntXNNZcdxo3bkyvXr1o0KAB4ZWrU6NyBeYu3YDWw5fsBEngOCg4hOWjRnHnzh3mzJkDCiUGz3BSjv0ASDRzj/rSCFFfGKj2XkviyM1U2cvMZDLRvXt3CgoKEEIwc+ZMtm7dKnsOgvQCn73rOnqzpdQXU/G2ncq+TPPnIqAw8D0Kj/ovk3/9dyw5abhWa4VzxYbEf9UPUGAq7Eig1oLZiELjhD7hBpgKHekL6e5KnatM3y8Oi1WQhbN87gqNMwq1Bl1wFQruSC9xqz6XxNUTMKUnyHqgmUfX499tkjTSF1Y51W21WsnOzmbz5s1cu3aNK1ek5+eXX36xCwohISGkpqbaaaBGxWUye9d1DOaiC2bOSJQ/u9fvjEvl5wAwJFxH7eEvM4I1PiEohYUpL1VnyD8khZuKFSvy0ksvkZWVxerVq2nWrBmDBg2SXdOjoqKokJ4AaCje5bI5qWMxk7bnG8zpCZjT4lG5+eBa43kyj6xFmPSUeX0h2oCyAHSrHcy4Jo8Xah7VuiKHox+gKxSrNibfJWnTR2QcXoV7g5fRBpQnjwMYEyX1H6shH1NaPKDAcOsUuYfSGHd2nV2bmyZOZ9Gh2xy8kYKComcKJC9GAbSp4s/I1hUdrgz/ATgC338Rj3N0KM3luzg0xYKlQq2V0j6p9zGlFjk023mMPbK92i8Cc2osvi+Nw7XmC1iyklF7BWI15JN1bD0Ft05ScOMYlStWIK18O/TpDym4+ceBT6FQ4t9zKplH11Fw5xy5l/fLdVoUegkWmKw41+/F0uGfIwTSKGv/WVThtYm9eRVLXgZKjROuFRsSXbYHp7Q1OHt6R+GJWMm9VOQXqHR2lwNf0blCgcnC7F3SHMr+b2dw7do1+RpkZmbi5+cnry8FvaezjbG1vfRo0SinIPYi2Zu3YclJw6VSY3xfGit/l3X8e9L3fWvbuqihwg6IJSfVvv1Ckkjxu5W2awHaQmGBvKuH0Lt6SU0UCzIulRqjcvMpVBDZjynprlQ6kBwDVjMFt0+RdWIzXi36ScSkwlGQm5ubrOJy9epVDh069NSkiG8O3S4hwJy0fpL8OWXrbFxrvIBf5/GEDF9iJ4wOoMt5QP8mXRhSOFpOzTWw8/QN7p+XatmOHz+OQqGgVq1aXLx4EYVCQYDWhE5t/5tRuXiiCSiHKfkeuRd+RaHRoXL3xbl8A1TO7rjX60T2qR9J2vQhLhUboTAZWLfqDpntX7CbxyyO2mFeaPd/RnxyDkrPICl9azGhdPYAhVIWqy64c5aUrXOkUafFhHu1FmRf2sf6SyWNqhcsWMCS/g1IyzWw5Xw81xNzyNab8HDSEFnGXU6NOvCfgSPw/T/Ck1y+i8NFq0KhVkrpuMKAEvjabJwiapGy/TPyrx3GkpVM6q4vsepz8ajbEe82Q2RDT0teOm61X6Tg3nkyf9+IU1gNQru9g1C78dLbH9r1OoevPcsPS78AQBtQnuDXJbHb+/N6IYqlP3PO/Uzupb2ofYJlhQuVRwB+ncZJtVyKojkpvdnC5K2XuJeaL4+yfLtOLnGeVmDv1SREg2FENBiG1ZBP4ooxmLOTQQiExVyoH1moMFOmMgG9p4MQ3Fo5lgEf2wcWpVJJrVq1mDBhAnv27KFzjz4cjLpDfuwldKHV8e04hoz9yyi4dw6Nf1n8uryLxktK/xlTYsg8tAp93DW7887Yt1QiTWQdJe/qIXThtYp2qFDapUGli6Ih8JUZWK0mUn6YZlsRKdxJ/+vCa2EpyMZcKONmK8pWOrnLijbFkXVyC641XsAQdwVzujSq8mo9hOTvp0jPh9UiK4wYk4qCttFSmLrTaDCZTBw7dozq1avz448/4u3tXULabPPmzWzcuBGNVovVtzxeLwwvcW62oIpKTd6VA7jV6VDCnkoBmL3DcfMLxlxoyJz5MI7Mh3G4N+hKztmfEULQcthUno8M5OLFUdSrV49Jg7qw/ZMDJc4/aMBnZJ/YQt71o3INqi3l69VyAEpnd/Iu7yfv6iGUOhcaPteQPn36lGinOF7r2pFvlq4g8dohQIG2TCW8Wg1CoVCg0LkQ2Odj0vd/R8HdsyjUWjzrvMhnn3/OGy/UfGK7vm66J2pvOvCfgSPw/T/Ck1y+i8PfXUdqyc0B8O04Bo1XGfKuSy9ilYsHzsX8zQCUSjW5UVIBtLOnH8936EyndpWpqs3gvXGjaTXmBrm5ufj5+dGqfWdUhWMQS24GsXM7o/IIsHv5QxF7ThNWQ15myU2XfdkAss/tkEcqx4pt616/M2qvMmQeWUPelYNY8jNROrmhDSiHX5d3UTl7AJC+bylWswFtYEWMD29JqiDFAqopJQarIZ/U7Z+VGE2BNMI+fvw4Q4YMAWDn1k3S9koV+pgLPFgxBl1QBdReQRgf3CDr6Dr8Xp6IJTeDpPWTpVG01WK3T2EyoAuJBAR5Vw5gKna+msCKmK8/IttmMZG0eRr2OdXCzyqp9ESitRdL5/mEYk6Px6l8PcmY2GoBlRqVsweW3HSEIV8a7StVCJMepZM7KdskIgtWa6EXnomMI+tk3zoAfb6UCi1Tpgz3799n//79aDQaDAYDI0eOLGG0GxgYSMeOHfnt9zPcijqDfv17OBW737agZyNDeTzXWw56Xi36kX12u5x+NVkE6qrPozi9FWEswKVKU1Tufni1GijJkQkrpw/t5eiaS/gElKFVq1b4uGhoVdkf44RNdpdPqXHCq2V/vFr2L3HPFSo1nk164dmkFwoFtK8W+FRWPx988AEffPCBXEz/aIpSG1SBsoM+daQo/0ehEI5ij/9JFHdteFrYRnxKZw8q1m/B/bP70ev1LFu2jKFDh7J//35mzJhB5cqVUalU/PLLLyQkJND7rfe45NeajNsXZSUO20jChsCB89B4BRH/dX/5pa7QOIFSWahgb1/3Zw+FVHahz5HYcQXZYDaidPagzKD5qL0Cyb9xnJRtc/DvNY3sUz/azWcWR0DvmST/UEj31jpDsZQvSHJgshamQokutJp9W2odSo0z1oLMwnUUuNV5idwLv0jlHMYCaZtijtwKjZNUL2Y2olDrUKi1WPVPFhdWegRgLaZw4tV6MFknt8jpTtu+AJSuPljz0nGt8byk7ygE7g274fPCMOIXD5XKTRQqXKq1IP/qIXne91HYUtyPoly5cty7dw9fX19Z5Hr27Nl07y5pZdauXZuoqCgaNWpEmzZt2H0xhqg9m554fpqA8pQZ9AUKVVHf+v78PghDniy5B8hKL7Zl5pw0Er4ZBIDK3Q/n8vXIv3Ecqz6X+fPn06bnYF797iQFpmf3uXPWqNg0vIkcoHbv3s3u3btLrNehQwc6dLBnWzpSlH8tOEZ8/6OwuTb8mRdA0Euj2bzgXeZNGcuaNWu4cOGC/BIIDAzk559/JjMzU7a1+e3773j3qzYsjlEVNaLW2gWV7FNbpdq9YpFY6eyBW822ZP2+ARBoQ6thfHATrGaUbt74tB1BxoFlWPOz5EAhrBYpgDi5YTUbSfh2OCoPP6z5WbjV7YhLxYZysXxpyL1UzG/skaAHUL169aLAJ6xY8jMlBf2sJKnA2GxAFBvRIQSWXGn0aAtExYMeINUhOrkhzEaUzu4Ik0EWCQBKDUTFgx6AZ5NeGOKvUXD7NAqdC2rPQEzJ96R189LRhdXAq+VA8q5IqT5toJQuU3uVkY5dWDAl3QWlitDRa1C5eJK0cYpM51e5+xH06iyyTm0h58zPdvu2+dalpaWRlpYme7fZUL58ee7cucPp06c5ffq03XdlhnyFNrA8wmwi/ptBMinHrfaLdkHvaaFy8ZCvl/cLw3CNbI7aJ4TMgyvZsHkr48aN4/0OlZnw/lQyL+zBkp+FxjcM71YDca7Q8LHtOmuUTHkp0m5UdvLkyVLLBb766iuEEEybNk0mojlSlH8tONwZ/kdhc21w1jz7LZzQpx21Qr3kesLc3Fz5JbBlyxZSU1PloAeQkZHBmtnjmfZytaJGbEGlcA6r4M5ZeW6vOGzF0wCmlFjZoNaam0H63kU4hVVHmIsU6G1MU6HPRanR4VypMZacNIRJj/HBTZI3zyikmNsg7V8XKh2bPuaivFxXPA2HpJhTpkwZu2XmtPii1GVhoBIm+4BZpGsq7Sto8IIS52kj8ehCqxH69jq7dKhtHvZJSN0xT659U6i1WLJTSqyT8tNc+XPe1UMkbfoIQ+xFeZkp9T5O4TVRuXg+ctyAQoHKzVsKyI8Uy6emphIWFoZarUatVrNz507GjBkjf3/06FFyc3MJCQkhMzOTN74tSd7IOLDMjomadWITlsLRa8aB5aTunC91CJDmJFN3zseUFleiHYVKg9on2H5hYWcqufC2PDjyA2lHNqBUqXGt2hJTWjzJWz7GmFJyNKtQSCO9KS9VlUsLbJg+fTpCCPlf//79adWqlb1rgwN/STgC3/8w+jcpy5SXquKsUZXgUDyK4t/3bFi2cFnRwunTp1O7dm0AJk6cyIIFC2jdurX8/fXr1/FUFM3rKQqVOBTaQtam2SC9rBX2j5Th4S35szDkFdVdAW61XsTv5Yl2NWYAni0HoAurgTU/C0tuOkpnSX7LmHRHsmGySyNKL0XbKKxIPkvYMR8B0rOy7Vy4bbDq80oss4MQhcoj0r6yjpVsw5ItjQrzo4/wcN0kuzQwFhOagHKPb1+hlFOYIJWbPCoDZkiIxpR8F0Wh6o3+3jn0MVElgqrVbCJx9QTuz+uFObPo/G2B1Lv1YNxqtrW7T56engQGBmI2mzGbzezZs4f4+Hj5+9RU6dwSEhLw8vJi2VtFheVpu78h79oR2RRWPo7cDNL3LsaYEkPO+V/Iu7Jf7ljo750n78p+2YX9UXg0knwuU3/+lNhPXibzkOSlpw+pT1JmHp9//jkAa9Z/T/9Jn+DzXE8QVrJPbZXbcFIr0amVtK8WyKbhTdi3ZDoKhYK33nqLjh074uLiQoMGDexUa9auXcuhQ4eeSsbNgf9tOALf/zj6NynLpuFNaF8tEJ1acm0ojuIvgD9CYKC0zrx58xg3bpyd2gxgp2JvK04vHjwVGie7UZa1IJvci0VzKMFvLiN0TFF9k63g/VG5rqyj6+V5N+OD63LdoSagHOHvbivah0pTFNFtAUCpArUO50pNsOQVMSBda7+IxWhA5V5kH1R0HI9op9qCgkJJ6Jh1BLwyjcB+c1G6eAFQcPc8at9QnCtJdWoqD3/C391G8BuLcSpbF+OD6yAs8jUBJNPUUnonCp1L4f4UKJ3c0fhJow21byiuNV4AQBsSCVYLrtVbU6FBa+l7F3cUKjVqrzJ4th6CQuOEQqPDNbIZwqRHWIpG0WqfUNzrSfO7+tgoci/skgMoSGzXTZs20aRJE0CyQmrVqpX8va+vn3TshccvrEVpW2PiDVK3F9pLKYtSm2rvEPKvHebhmncQVivOlZ+TU5Fq31DCJ26T5/mefD8UKLTOKHSuuJatzbI9Z0hLS0OpVNKnYyuW9G/AglFSoHTOieOFyAC61wlhfLvKHJ/0PEv6N7BLb3777be4urpSp04dzp07R+fOndHr7YlaDvz14Zjj+wugVqjXU9UIfTvgye3Mnz+f9u3bEx8fj4uLC+PGjZMKx58CKg9//HtMwZKTRsr9SwAIiwmncvVkPc/MI2vs01uFAcZUWNisdPaQXtrFnN/V/mUR+lwsOamSBY2pmHiwsKJQ6yQmo8YJqyEPr9ZDcAqvQcqWmXbzjbYRmezSXXzezWbL5OSO0Oeg0DrL8mzxi4bg2aQXXi364d/jA5LWTUKhUqMrU1lOqwqLibRfFmBMviuXDRQdohmF1gVhMUru5Y9AqXMjaNin5N84gSU3DWGUajLNafFo/csCkgqKMOrJjdrLbaBOnTrUGLmQo3czybt+DP3d8wiTHrc6HfBo0AWPBpKyi4044tt+ZFGQKTwGpc4Vi7GAys+9yPXfd3PmzBlOnjyJVqvlueeeQ6PRkGe0cPbEMdIzs1CodWiDKmKIu4LK3Q+Xys9heHBDLuL27fIewlhA+m5pfrDMoHnkRO0h8+BKNL5hqD2kYKZ08cScFo/+/iWcy9cndOSKkg9T4TE6hdfEs2kfNH7h0nYILt+6D4CLi4vc6Srj5wWASp/F8kENmTlzJtEn0vl4q1QYP3p0kat5165d2bJlCyaTidDQUBISEti/fz+dOnXCgb8PHIHvL4Q/moB/lMC7YMECu3KJatWq8emnn9K3b1+sVisJCQkyow+gQYMGREREEBsbi1alRA84V36OvEu/ofYMRBdUEX2hViOAys0Xn7ZvyHqe+rjL+LzwBqk/FxnQ5kUflU0/vVoPwrlCYxIWSrR0hVYieejTpbSba/XnseRnyaNBhUpTVFahVOFWuz36e+fJPvFDCeUT/b3zhRfBal9vBpiS70nMTH0OKNUond1lYgkWE7mX90vkncDyeLcbTu75XeRdO4LKzRu3Oh0puH1KUrkp1qYMi1l2yABQOntKouE2WC08+Ha4XbCXvypcplAo8WrUlZRfJCKGX5OuPMiR9pVzbieGhOs4RdTGq/VgaTt9Hum/LcGSI4k1J2+djXO5eng//zpO5eriVq+TPBK/eWIvjRs3ZtSoUdLlEYJFixYBksIKILlzCIt83S05qYUO6EXIOroOpdZJ/jvl509ROEnpcFNaXIn5vOyzO0qU2dhgO8a8KwdkFrG2TCX8e07F6ieVtuTn52O1WlEqleTmSmlhm+TaihUriI2V5vtatWplF/hsjuU2V4bk5GS7tK4Dfw84Up0O2KF3794MHToUjUbDvn37Hus8//V3q4mc+qs8KnkUKo8AQkeuQKEomoMKGbYYQ8J1KGT76e+ew5AQjcpNSj8qFCpMKffk9YXVhMrZHZcqzQBJM1RRLJ0mrGZca7XD47ne+HYaT+7lfejvnZesmZRP6NM9GqBUWjkNp3LzlkoK5LSkAl1oVZQuHhgSojE+uEnwG4uJeO8nwketxLfDKKmovLSgBzhVaEjo6DUoNDoUGidcqjS1u0YejXtIQU+hxLlSE5zLF9WYafzCiJi8E4+GXUk/sl5K4yqUHFy/kNtx0lxpUL+5RLz3E4GvzZatiKz6XPKuHQZl0c87//pRUrbOBmHFp90I3Ou+BIBnYChnzpyRtR91Oh3LDl4jcuounCpIx6IJKEfIm9/hElkk86b2CsL7hTfkv80ZD+yK4/X3zhc5MpQCUyllFTIKjzFs/CaC3/wO1xrPY0y8RW7UHsoEh+Lj44PVauXcOcnB/MwZqWNlm6OOiYmRCSuPputtbvUmk4m7d6Xj/VfZWznwvwNHHZ8DfxrPIvdlg62W8FFETJaEvHOvHiRtxzwAQkatLlG6YDXkyy7VAa/OxrlsbfKuHyP1p08AgUKtw6VaS8nv7eZJmVAh1QkWEka0LmAsqi1UufmidHaT2KIKJSDs0qSBr80h4+CKQgUVBW51OqBSQsG1QxgNBoL6fYKumDpJcRdyn/ajSN8juad7NH2VnDM/yaNUlUcA3q0Hkbr9MxQqDS5VW2JMviuPNnVh1Qnq94msxuPZtA/CYib71I84V2mKAgX6+5exGgtQufngXK4uvh1GYzXkY85OJnnzTCzZyXg/P4yMA8ukY2jyijRaUygRxnyUKjVWi5k+ffoQExPDqVOn0AVVRO0bJgVPYZU6AZKdR5FKTmAF1D4hUkF9KfDvORVtUEUSl43EasjDqVxd1J6BmDMS0cddIWT4UjvGb3HoYy/ZWfjo757HnJlIQPsRzPxgImnHNjFlyhQiIiJo2bIlP/zwA2azmYsXL1KjRo1S2xw8eDCrV69GqVTSvXt3Hjx4wIkTJwgODub27ds4OzuzbNkyjh07xoEDB4iLi6N27drUqVOHbt262WntOvC/D0eq04E/jSLl+ccLPNtgU55vv+AwN5JyHruuqpBAAmBKiy9hb1QcTqHVKLh/mdQd87AxLtXeQSi1zugiagMK8q9LSiWuNV4g56xUv2YrpVf7hmBOi0eYjZhS40ChxCWyuSRxdfVgYeE9FMRclGXDQJB7sahsY9joCcRWaMjNpJJmrI8i/+pBVB7+mAvTfsKYj0tkc9xiosi7fhRL3CWa9R3HocVTAFC6eJMXfZT8a4fR+IXj2exVEFBw+zQFhUo52uAqaAPLY85Klg1YlToXu5G4sBFtCt0aiqvuWAtTsBqNhu3bt9Oi1zDuXDyBMfV+0dynzhWsFrmOUaHW4tvxbXILawpVbr64RDbDkHBdnvNTewaidvclbOCnpB5ajSXpFnnx11B5+ONerxNKF4/HXifVYyx8POp2pFe9ULyaTaKgoIAVK1bw/fffU7VqVWbPnv3YoFccI0eOJCYmhosXL1KvXj2+++472XT42LFjrF69Wl43KiqKqKgoypYt6wh8fzE4Ap8D/xT6NylLrVCvp1aeF4InKm/oQqrKo7O8y/sIn7QdRSEJxpyVjLCYeLD0TUBilhbcPm0/X5cSiyklFmuNF2Q3AACn8Brk3zgm1QQW+rFpgyphTouXRIiFFady9dCFVMWSmybN+RUGPpW7X8m5OSSSSd8enXn++dbSeoXpXRsCX5tT5B4A+PeYQu7lfeQUBj61VxkUShW+L72N70tv071OCCEZURxCgdLZHZ/nX0ftGYBS50LB3XNkHFwptdv/U7JPbiH71I/ogqvgWq0VGr9w0vYsIn7hQCwF2Si1LmiDKuLbcQzpexcD4N1qIO71OuHbfmSp8l2puQZo9RbBjQaR8M0QhNmINqQqQp+LKTMRlUcA7nU74lypMVq/cHyCKuDTtijdmb5/GcbEm5Rr0IY2LRsVkqsi6fXFUHzddE+tNqTxCSHw1Vl2yxQKeKFaoKyS8vHHH/Pxxx8/uaFS4OvrW6JA34ZHDXgd+OvCEfgc+KfxtKxSG2zmnKWlSJVaJ7zbvUnazvnkXT2IMSUGXZnKiPx09Pcu0m36SoonP4vXACp0LghDPmrvMlLd2CNwr/sSmUfWyn+rZFdwKQjr718uIsEUgy64cqnn/fbbb7Ns2bInXpviyDq1DVPSbflvU2osOVF7cK/dHoCze7bw5eq5KJ3dCXx1llzuYUi4bjfy9WjQFfeGXTEk3iLn7I6i79RaVO7+aN18sBoL0N87LzFPhRXPFv1xr1fEXHRSqxjZuqLd8W05J5E8DPHRcq2kMeE6Cq0TrlVboo+NIvPwaklH1c++yNtqLJCdM3oMHM7ng0qqqDyqNpS+r6QFF4BP2+EllpV2vA448GfhCHwO/MvwtLJOf5QidaveBrW7P9mntmBIuE5eWhz+QcEMfnM4b7/SkB8/lNbrXieEaHNZ9hQSDP06jSfnwq4iAs0j5QPu9TqTeWQdj9UMtZjQ+EdIfmtXD8qLFYqSHDCVSsWUKVNIS0tD5+qBIa+IRWobGSZt+lA2+wXIv3bQrg1hNqKPiSLz8Fqs+VnEIlB7BhLQewYa3yLChVeLfni16Cc7RCSumYCwWtGVqWR/LmYjlowE8AjAq9VA0nZ8Lkl/tX0TjwZF9k3F5bs2bNjArFmzuHfvHkKlRXiWwalsneJHiVez17AUZMss0fQ93+Bet6PdueRe2ocw5KENrIAlILLUy2tTG7J1eh6Xxn408JUmN+aAA/8MHIHPgf8K/ihF6lW+Fp7la5WqfF+cj5X/cmXCVkwjPT2d/FunCOg9E4VCgTHpLokr37bbp9LJlaDB80n9+VO7NGhxkokp9T6mlFgUGmc76TKFVgfFlMyaN2/O4cOSd9wLXfuxf/NK+TttQHlUngEondwwJt4qmvfyCkIXVkMKqlYL2uAqKJQqrPmZ8rZOIZXJubCr8Hjd8Wr+GkAxhwg9zhUbYkqJRX/vPAqdCy5VmpF/43eEIR/3Jr2w5mWStlMiCCmdPTBnJsqjK//GXZnS/3n6NylLQUEBgwcPRqPR0K9fPw5de8D9W1ftJORAKiWwGgtwrtKMghu/AxJzVFnIIhVCyOUN7g27kq0vneEK9p2esu/vfKp5YZup8D8DRxrTgeJwBD4H/mt41hRpaXBxceGbb76hb79+5F3ehzHpDrrgKphL0brMOrEZU1q8XONXUKhzKSwmXCKbozqyFkthAbo2JBJDzAVpvTtnEUaJEBIWFoazszMXLlxAqVRitVpJuSmtZy203PHrNkkuSNf4hMqBz71BF7JP/Vio66nA+OAGxgc3ULp4ycEv91qRbZDKI0AOfLlXD2DV5xYVg1stmLOSEIZ88q4cRO0ZgHuLAeTf+N3ObcJakG03smocIDj7/SWUdxvRpUsXLBYLAQEBdOvWDUstwcFEJRZDHnmXfpPTnQqNEy7hNVG5esuBz5KXIQe+gtunMWc8kFzPq7bAw6lolFsannVe2DHSc+BfDUc5gwN/Cezce4BXR79PQVy0RO939UTjF4FLZDN5Du3h+sml2hn5vjQOt1ptH/u9R622aJOjSX2YwLZt27h48SIzZswoeRAKJcFvLCZx1TiZAVkcNicDgNxLv5G2SypI9+00ll6v9sdoERy4nlxiO4C0vYvJfUQP0wbvdm/aOdGX89LgnnqVnfMmolAqmbl+HyM6NcHPvajAfNCgQaxatYqlS5cyY8YMHjyQRsBqdz98O0/AkpdB6vbPAFB5BeFctg6mjEQMhW4PYeO+lwNf0sYP0MdewrNFf4Ja9WV8u8pP7WTgsPtx4L8BR+Bz4C+DP+NR+CQUT7V9+GprYmNj2bZtG23atCE4OBiFQkFCQgLbt29n4MCBKLTOaAMrYIi7gtLZHbfaHXCp0pSHq8cDRYHPqs/lwfLRWPIyQAjUbt4cPH6WLVcz+Onig1KPJevUj2QeXIlL5ab49/hAXm7JzZD0PpFMVxVKFd3rhDC3W1UCAgLIzs7mwIEDtGnTptR2DQYDOp2OxMREVq7byJT33sEpohaBr83h4br3MMRfk2ThrBaUOmesBTkondwJG7cRkJzpE5ePRqHWEjJyJS4e3hyf9LwjaDnw/xqOVKcD/xMYN25cqcuLS679Mx6FxVFaqu3DYt97enpy5MgR+XNBgTS6E8YCecRoLcgh59wO8m+dKNF+2t7FWHJS8WzaB5WwkH5iC4vmfEDLNz9Gp36IwVyS7eparTXZx38g/+ZxkjZNLVEMbs5KInXH57iE1+D8tVDqfxxFdnY2/v7+1KtX77HnGhgYSOvWrQkODuby5csA8kjOq/VgktZNAoUC12otZW1Sr5ZFoq9a/7Ky+IBCIV0zR9Bz4P87HIHPgf8JlGYYCvaB71HW4NNCrYQawZ74uumeOtVWv36RzmRAgFR2EBERwcz1+3l79Ciyrx1BqXPBq3nfEtqktoL0oNb9mNS+Mp+NuMrGjRtp0/4loKR7BIDa3ZfAfnPJPLwGQ+ItDI8Ug6usZtTeweTdu8CJWyfw9/fnlVde4aOPPsLT07PUNseNG4e/vz/79++noKAAtVpNcFg4Ti8Ox4IkEODX9V2yjm2UtUm9Wg3C7RFGpw2OkgMH/lfgSHU68JeDJKX29Goy/wrWYHFcis/808SNfyZdW1pR+pPXL93Ece2Je8/ceZBKDkqavTrgwP9HOEZ8Dvzl8N9mDf5Ztmp6ejp5h5aTdSURs7Uo8hUva3gSnnXE9Ud93v9m58EBB/6dcIz4HPhL43+JNRgTE0O5ciWd2h+VQisN/44R1z8zcnXAgf/PcAQ+Bxz4f4j/drq2OP6XOg8OOPA0cAQ+Bxz4fwrHiMsBB/49cAQ+Bxz4fw7HiMsBB/61cAQ+BxxwwAEH/lYoKTvvgAMOOOCAA39hOAKfAw444IADfys4Ap8DDjjggAN/KzgCnwMOOOCAA38rOAKfAw444IADfys4Ap8DDjjggAN/KzgCnwMOOOCAA38rOAKfAw444IADfys4Ap8DDjjggAN/KzgCnwMOOOCAA38rOAKfAw444IADfys4Ap8DDjjggAN/KzgCnwMOOOCAA38rOAKfAw444IADfys4Ap8DDjjggAN/KzgCnwMOOOCAA38rOAKfAw444IADfys4Ap8DDjjggAN/KzgCnwMOOOCAA38rOAKfAw444IADfys4Ap8DDjjggAN/K/wf53eIXnC5PooAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "nx.draw(merged_story_graph, with_labels=True, font_weight='bold')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nx.draw_circular(merged_story_graph, with_labels=True, font_weight='bold')#draw_shell"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nx.draw_networkx(merged_story_graph, with_labels=True, font_weight='bold')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 140,
+ "metadata": {},
+ "outputs": [
+ {
+ "ename": "LayoutError",
+ "evalue": "possibly disconnected graph",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mLayoutError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m/tmp/ipykernel_9281/3403421302.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGraph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msuper_merged_triples\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m#g = Graph(triples=renamed_triples)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpenman\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/penman/codec.py\u001b[0m in \u001b[0;36m_encode\u001b[0;34m(g, top, model, indent, compact)\u001b[0m\n\u001b[1;32m 238\u001b[0m \u001b[0mtop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 239\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindent\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 240\u001b[0;31m compact=compact)\n\u001b[0m\u001b[1;32m 241\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 242\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/penman/codec.py\u001b[0m in \u001b[0;36mencode\u001b[0;34m(self, g, top, indent, compact)\u001b[0m\n\u001b[1;32m 128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 129\u001b[0m \"\"\"\n\u001b[0;32m--> 130\u001b[0;31m \u001b[0mtree\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlayout\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 131\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtree\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindent\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcompact\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcompact\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/penman/layout.py\u001b[0m in \u001b[0;36mconfigure\u001b[0;34m(g, top, model)\u001b[0m\n\u001b[1;32m 280\u001b[0m \u001b[0mdata_count\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 281\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mvar\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mdata_count\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 282\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mLayoutError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'possibly disconnected graph'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 283\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 284\u001b[0m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msurprising\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_configure_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnodemap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mLayoutError\u001b[0m: possibly disconnected graph"
]
}
],
"source": [
"from penman.graph import Graph\n",
"\n",
- "g = Graph(renamed_triples)\n",
+ "g = Graph(super_merged_triples)\n",
+ "#g = Graph(triples=renamed_triples)\n",
"print(penman.encode(g))"
]
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": 110,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[Instance(source='EVENT_3:2&0:2', role=':instance', target='some'),\n",
- " Instance(source='EVENT_3:3&0:3', role=':instance', target='\"Germany\"'),\n",
- " Instance(source='3500_EVENT_3:3&0:6', role=':instance', target='\"France\"'),\n",
- " Instance(source='3500_0:0', role=':instance', target='be-located-at-91'),\n",
- " Instance(source='3500_0:4', role=':instance', target='some'),\n",
- " Instance(source='3500_EVENT_3:0', role=':instance', target='go-02'),\n",
- " Instance(source='EVENT_3:1&0:1', role=':instance', target='\"Germany\"'),\n",
- " Instance(source='3500_0:5', role=':instance', target='member'),\n",
- " Instance(source='3500_EVENT_3:3&0:6', role=':instance', target='\"Germany\"'),\n",
- " Instance(source='EVENT_3:3&0:3', role=':instance', target='organization'),\n",
- " Instance(source='3500_EVENT_3:4', role=':instance', target='some'),\n",
- " Instance(source='3500_EVENT_3:0', role=':instance', target='drive-01'),\n",
- " Instance(source='EVENT_3:2&0:2', role=':instance', target='have-org-role-91'),\n",
- " Instance(source='3500_0:4', role=':instance', target='name'),\n",
- " Instance(source='EVENT_3:2&0:2', role=':instance', target='\"France\"'),\n",
- " Instance(source='EVENT_3:1&0:1', role=':instance', target='\"Max\"')]"
+ "[Instance(source='s2r0.0', role=':instance', target='feed-01'),\n",
+ " Instance(source='e4r0.2', role=':instance', target='throne'),\n",
+ " Instance(source='e4r0.4', role=':instance', target='stand-01'),\n",
+ " Instance(source='e4r0.5-s2r0.1', role=':instance', target='\"Max\"'),\n",
+ " Instance(source='e4r0.0', role=':instance', target='come-01'),\n",
+ " Instance(source='e4r0.1-s2r0.2', role=':instance', target='crown'),\n",
+ " Instance(source='e4r0.3', role=':instance', target='cause-01'),\n",
+ " Instance(source='TOPr0', role=':instance', target='cause-01')]"
]
},
- "execution_count": 43,
+ "execution_count": 110,
"metadata": {},
"output_type": "execute_result"
}
@@ -242079,7 +243881,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -242093,7 +243895,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.8"
+ "version": "3.7.11"
}
},
"nbformat": 4,
diff --git a/code/penman_merge.ipynb b/code/penman_merge.ipynb
index 02e8fa865dfdb9441342d2f7feff586decaf8876..0001afc5a842416ac4411349d855e8e3f0e7bf6e 100644
--- a/code/penman_merge.ipynb
+++ b/code/penman_merge.ipynb
@@ -399,7 +399,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -413,7 +413,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.8.8"
+ "version": "3.7.11"
}
},
"nbformat": 4,
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