From fcee1c1131d298aa6e75e03eb007a906130f7ae5 Mon Sep 17 00:00:00 2001
From: Lyudmila Vaseva <vaseva@mi.fu-berlin.de>
Date: Thu, 11 Jul 2019 17:35:56 +0200
Subject: [PATCH] Explore 2nd round of manual tags

---
 ...s-sorted-by-hits-manual-tags-2nd-round.csv |    2 +-
 src/explore.ipynb                             | 1070 ++++++++++++++++-
 thesis/appendix.tex                           |   24 +-
 3 files changed, 1066 insertions(+), 30 deletions(-)

diff --git a/filter-lists/20190106115600_filters-sorted-by-hits-manual-tags-2nd-round.csv b/filter-lists/20190106115600_filters-sorted-by-hits-manual-tags-2nd-round.csv
index 54bf86e..db0500e 100644
--- a/filter-lists/20190106115600_filters-sorted-by-hits-manual-tags-2nd-round.csv
+++ b/filter-lists/20190106115600_filters-sorted-by-hits-manual-tags-2nd-round.csv
@@ -9,7 +9,7 @@
 7	636	0	0	1	0	0	default	20181231024947	warn	726764	Unexplained removal of sourced content	good_faith_deletion	
 8	3	0	0	1	0	0	default	20181018194624	warn,tag	700522	New user blanking articles	good_faith_deletion	in the meantime, the filter is set to “disallow” (18.1.2019), which will rather render it ‘general_vandalism’ (since there isn’t a ‘blanking_vandalism’ or similar code at the moment
 9	650	0	0	1	0	0	default	20160721182156		695601	Creation of a new article without any categories	general_tracking	in the meantime handled by https://en.wikipedia.org/wiki/Special:NewPagesFeed
-10	279	0	0	1	0	0	default	20190104180929	throttle,tag	616212	Repeated attempts to vandalize	unclear / hidden_vandalism	undecided between unclear and hidden_vandalism; filter is hidden at the moment, I have an older version whose pattern seems to throttle edits by all non-confirmed users
+10	279	0	0	1	0	0	default	20190104180929	throttle,tag	616212	Repeated attempts to vandalize	unclear	undecided between unclear and hidden_vandalism; filter is hidden at the moment, I have an older version whose pattern seems to throttle edits by all non-confirmed users
 11	432	0	0	1	0	0	default	20160614010135	warn,tag	558578	Starting new line with lowercase letters	good_faith_orthography	although there’s the comment “Test whether starting a new line with small letters is unique to vandalism. […] Exceeded my expectations. High catch rate with nearly no FPs. Turn to warn and tag for now. -Sole Soul”
 12	225	0	0	1	0	0	default	20180807154519	disallow	482872	Vandalism in all caps	profanity_vandalism	judging the comments, the filter has changed substantially
 13	50	0	0	1	0	0	default	20181018234925	warn,tag	480960	Shouting	not_polite	alternative tags: ‘general_vandalism’, ‘good_faith_orthography’
diff --git a/src/explore.ipynb b/src/explore.ipynb
index 35c0d00..5c64633 100644
--- a/src/explore.ipynb
+++ b/src/explore.ipynb
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1316,6 +1316,43 @@
     "## Filter activity"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Hit count"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "count    9.540000e+02\n",
+       "mean     2.401892e+04\n",
+       "std      1.205649e+05\n",
+       "min      0.000000e+00\n",
+       "25%      7.000000e+00\n",
+       "50%      9.050000e+01\n",
+       "75%      1.185250e+03\n",
+       "max      1.611956e+06\n",
+       "Name: af_hit_count, dtype: float64"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " df['af_hit_count'].describe()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -9874,7 +9911,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -10342,7 +10379,7 @@
        "[219 rows x 3 columns]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10380,7 +10417,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Combine manual tags with filter actions"
+    "### Combine manual tags with filter actions"
    ]
   },
   {
@@ -10680,35 +10717,1034 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Hit count"
+    "### Manual tags 2nd labeling"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 43,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[('hidden_vandalism', 333), ('sockpuppetry', 64), ('spam', 43), ('long_term_abuse', 43), ('test', 36), ('silly_vandalism', 26), ('general_vandalism', 25), ('general_tracking', 25), ('personal_attacks', 24), ('good_faith_template', 23), ('wiki_policy', 19), ('profanity_vandalism', 18), ('talk_page_vandalism', 17), ('good_faith', 15), ('good_faith_deletion', 14), ('unclear', 13), ('trolling', 13), ('hoaxing', 12), ('good_faith_wiki_syntax', 12), ('bot_vandalism', 12), ('politically_motivated', 12), ('image_vandalism', 12), ('page_move_vandalism', 11), ('good_faith_refs', 10), ('good_faith_article_creation', 10), ('bug', 9), ('bad_style', 8), ('template_vandalism', 8), ('good_faith_test_edits', 7), ('avoidant_vandalism', 7), ('link_vandalism', 7), ('self_promotion', 6), ('conflict_of_interest', 6), ('harassment', 6), ('doxxing', 5), ('username_vandalism', 4), ('good_faith_redirect', 4), ('good_faith_move', 4), ('impersonation', 4), ('not_polite', 3), ('good_faith_edit_summary', 3), ('copyright_violation', 3), ('good_faith_wiki_links', 2), ('edit_warring', 2), ('good_faith_html', 2), ('malware', 2), ('good_faith_orthography', 1), ('good_faith_external_resources', 1), ('general_maintenance', 1), ('good_faith_revert', 1), ('good_faith_userpage', 1), ('good_faith_image', 1), ('good_faith_categories', 1), ('religiously_motivated', 1), ('phishing', 1), ('good_faith_edits', 1)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "manual_tags_2nd = df_2nd['manual_tags']\n",
+    "all_tags_2nd = flatten([x.split(\", \") for x in list(manual_tags_2nd)])\n",
+    "all_tags_2nd_counts = collections.Counter(all_tags_2nd).most_common()\n",
+    "print(all_tags_2nd_counts)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Ok.\n",
+    "So there are still the majority of filters are hidden filters for which no more precise labeling was feasible; (sounds plausible, 2/3 of all filters are hidden; half of them could be labeled with smth more specific as it seems).\n",
+    "The majority of the \"sockpuppetry\" filters are probably also hidden, same goes for \"long_term_abuse\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "count    9.540000e+02\n",
-       "mean     2.401892e+04\n",
-       "std      1.205649e+05\n",
-       "min      0.000000e+00\n",
-       "25%      7.000000e+00\n",
-       "50%      9.050000e+01\n",
-       "75%      1.185250e+03\n",
-       "max      1.611956e+06\n",
-       "Name: af_hit_count, dtype: float64"
+       "954"
       ]
      },
-     "execution_count": 69,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    " df['af_hit_count'].describe()"
+    "len(all_tags_2nd) # verify every filter is labeled with exactly one label"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     af_id         af_actions                    manual_tags\n",
+      "653    897           disallow                  bot_vandalism\n",
+      "67     803           disallow               personal_attacks\n",
+      "41      12           disallow            profanity_vandalism\n",
+      "37     320           disallow            profanity_vandalism\n",
+      "499    694           disallow            page_move_vandalism\n",
+      "99     782           disallow                        unclear\n",
+      "22     260           disallow            profanity_vandalism\n",
+      "54     365           disallow              general_vandalism\n",
+      "130    784           disallow              general_vandalism\n",
+      "19      46           disallow            profanity_vandalism\n",
+      "171    860           disallow                silly_vandalism\n",
+      "110    554           disallow                           spam\n",
+      "47     680           disallow              general_vandalism\n",
+      "470    843           disallow          politically_motivated\n",
+      "3      384           disallow            profanity_vandalism\n",
+      "234    892           disallow                    wiki_policy\n",
+      "239    930           disallow                 self_promotion\n",
+      "268    812           disallow              general_vandalism\n",
+      "328    788           disallow             avoidant_vandalism\n",
+      "271    642           disallow                        unclear\n",
+      "12     225           disallow            profanity_vandalism\n",
+      "302    828           disallow            talk_page_vandalism\n",
+      "68     117                tag            good_faith_deletion\n",
+      "75     753                tag          good_faith_wiki_links\n",
+      "78     164                tag         good_faith_wiki_syntax\n",
+      "155    632                tag    good_faith_article_creation\n",
+      "85     627                tag           conflict_of_interest\n",
+      "94      59                tag            good_faith_template\n",
+      "100    655                tag               general_tracking\n",
+      "106    224                tag            good_faith_deletion\n",
+      "226    921                tag          politically_motivated\n",
+      "131    735                tag                        hoaxing\n",
+      "134    878                tag            good_faith_template\n",
+      "82     323                tag             avoidant_vandalism\n",
+      "86     846                tag                long_term_abuse\n",
+      "0       61                tag                good_faith_refs\n",
+      "33     180                tag         good_faith_wiki_syntax\n",
+      "14     189                tag               personal_attacks\n",
+      "20      98                tag    good_faith_article_creation\n",
+      "40     631                tag          good_faith_test_edits\n",
+      "29     550                tag                        unclear\n",
+      "6      633                tag              general_vandalism\n",
+      "35     391                tag                        hoaxing\n",
+      "53     339                tag               personal_attacks\n",
+      "24     148                tag                 self_promotion\n",
+      "31      29                tag            good_faith_template\n",
+      "4      172                tag            good_faith_deletion\n",
+      "107    420  throttle,disallow            talk_page_vandalism\n",
+      "10     279       throttle,tag     unclear / hidden_vandalism\n",
+      "71     249       throttle,tag              good_faith_revert\n",
+      "43      80  throttle,warn,tag                           spam\n",
+      "149    869               warn                      bad_style\n",
+      "151    702               warn                     good_faith\n",
+      "157    894               warn                    wiki_policy\n",
+      "189    783               warn            good_faith_template\n",
+      "81     167               warn         good_faith_wiki_syntax\n",
+      "248    879               warn         good_faith_wiki_syntax\n",
+      "7      636               warn            good_faith_deletion\n",
+      "88     664               warn          good_faith_test_edits\n",
+      "375    901               warn                silly_vandalism\n",
+      "391    928               warn            good_faith_template\n",
+      "449    838               warn          good_faith_test_edits\n",
+      "177    850               warn                good_faith_move\n",
+      "158    887      warn,disallow             username_vandalism\n",
+      "125    890      warn,disallow             username_vandalism\n",
+      "233    891           warn,tag                good_faith_refs\n",
+      "11     432           warn,tag         good_faith_orthography\n",
+      "5       30           warn,tag            good_faith_deletion\n",
+      "211    766           warn,tag          politically_motivated\n",
+      "1      135           warn,tag                silly_vandalism\n",
+      "8        3           warn,tag            good_faith_deletion\n",
+      "45      11           warn,tag            profanity_vandalism\n",
+      "160      5           warn,tag                good_faith_move\n",
+      "61      33           warn,tag            good_faith_deletion\n",
+      "64     346           warn,tag          good_faith_test_edits\n",
+      "38      39           warn,tag            profanity_vandalism\n",
+      "34     351           warn,tag         good_faith_wiki_syntax\n",
+      "30     149           warn,tag                 self_promotion\n",
+      "90     657           warn,tag                    wiki_policy\n",
+      "91     113           warn,tag         good_faith_wiki_syntax\n",
+      "95     174           warn,tag            good_faith_template\n",
+      "28      79           warn,tag                good_faith_refs\n",
+      "25     491           warn,tag                      bad_style\n",
+      "101    602           warn,tag                        unclear\n",
+      "108    345           warn,tag                            bug\n",
+      "21     220           warn,tag  good_faith_external_resources\n",
+      "15     132           warn,tag            good_faith_deletion\n",
+      "138    912           warn,tag                silly_vandalism\n",
+      "13      50           warn,tag                     not_polite\n",
+      "17     231           warn,tag                silly_vandalism\n",
+      "9      650           log only               general_tracking\n",
+      "23     686           log only                        hoaxing\n",
+      "26     833           log only                good_faith_refs\n",
+      "27     712           log only                        hoaxing\n",
+      "58     126           log only                           spam\n",
+      "63     867           log only    good_faith_article_creation\n",
+      "79     716           log only              general_vandalism\n",
+      "92     711           log only                           spam\n",
+      "109    733           log only            good_faith_userpage\n",
+      "115    837           log only            good_faith_template\n",
+      "175    777           log only                    wiki_policy\n",
+      "197    861           log only                           test\n",
+      "218    942           log only               general_tracking\n",
+      "257    899           log only                    wiki_policy\n",
+      "273    856           log only            good_faith_template\n",
+      "315    862           log only                           spam\n",
+      "414    798           log only            copyright_violation\n",
+      "640    883           log only            page_move_vandalism\n",
+      "666    929           log only                long_term_abuse\n",
+      "704    932           log only                           spam\n"
+     ]
+    }
+   ],
+   "source": [
+    "# What are the actions and tags of active public filters\n",
+    "active_public_2nd = df_2nd.query('af_hidden==0 and af_enabled==1').sort_values(by=['af_actions'])\n",
+    "\n",
+    "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
+    "    print(active_public_2nd[['af_id', 'af_actions', 'manual_tags']].fillna('log only'))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'bot_vandalism': 'vandalism',\n",
+       " 'page_move_vandalism': 'vandalism',\n",
+       " 'image_vandalism': 'vandalism',\n",
+       " 'talk_page_vandalism': 'vandalism',\n",
+       " 'template_vandalism': 'vandalism',\n",
+       " 'link_vandalism': 'vandalism',\n",
+       " 'avoidant_vandalism': 'vandalism',\n",
+       " 'username_vandalism': 'vandalism',\n",
+       " 'silly_vandalism': 'vandalism',\n",
+       " 'trolling': 'vandalism',\n",
+       " 'hoaxing': 'vandalism',\n",
+       " 'prank': 'vandalism',\n",
+       " 'profanity_vandalism': 'vandalism',\n",
+       " 'religious_vandalism': 'vandalism',\n",
+       " 'politically_motivated': 'vandalism',\n",
+       " 'general_vandalism': 'vandalism'}"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clusters = {}\n",
+    "\n",
+    "vandalism = ['bot_vandalism', 'page_move_vandalism', 'image_vandalism', 'talk_page_vandalism', 'template_vandalism', \\\n",
+    "'link_vandalism', 'avoidant_vandalism', 'username_vandalism', 'silly_vandalism', 'trolling', 'hoaxing', 'prank', \\\n",
+    "'profanity_vandalism', 'religious_vandalism', 'politically_motivated', 'general_vandalism']\n",
+    "\n",
+    "for i in vandalism:\n",
+    "    clusters[i] = 'vandalism'\n",
+    "    \n",
+    "clusters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'bot_vandalism': 'vandalism',\n",
+       " 'page_move_vandalism': 'vandalism',\n",
+       " 'image_vandalism': 'vandalism',\n",
+       " 'talk_page_vandalism': 'vandalism',\n",
+       " 'template_vandalism': 'vandalism',\n",
+       " 'link_vandalism': 'vandalism',\n",
+       " 'avoidant_vandalism': 'vandalism',\n",
+       " 'username_vandalism': 'vandalism',\n",
+       " 'silly_vandalism': 'vandalism',\n",
+       " 'trolling': 'vandalism',\n",
+       " 'hoaxing': 'vandalism',\n",
+       " 'prank': 'vandalism',\n",
+       " 'profanity_vandalism': 'vandalism',\n",
+       " 'religiously_motivated': 'vandalism',\n",
+       " 'politically_motivated': 'vandalism',\n",
+       " 'general_vandalism': 'vandalism',\n",
+       " 'sockpuppetry': 'hardcore_vandalism',\n",
+       " 'long_term_abuse': 'hardcore_vandalism',\n",
+       " 'abuse': 'hardcore_vandalism',\n",
+       " 'harassment': 'hardcore_vandalism',\n",
+       " 'doxxing': 'hardcore_vandalism',\n",
+       " 'personal_attacks': 'hardcore_vandalism',\n",
+       " 'impersonation': 'hardcore_vandalism',\n",
+       " 'not_polite': 'hardcore_vandalism',\n",
+       " 'hidden_vandalism': 'hardcore_vandalism',\n",
+       " 'spam': 'spam',\n",
+       " 'phishing': 'spam',\n",
+       " 'malware': 'spam',\n",
+       " 'copyright_violation': 'disruptive',\n",
+       " 'bad_style': 'disruptive',\n",
+       " 'lazyness': 'disruptive',\n",
+       " 'edit_warring': 'disruptive',\n",
+       " 'wiki_policy': 'disruptive',\n",
+       " 'guideline_vio': 'disruptive',\n",
+       " 'biased_pov': 'pov',\n",
+       " 'conflict_of_interest': 'pov',\n",
+       " 'stockbrocker_vandalism': 'pov',\n",
+       " 'self_promotion': 'pov',\n",
+       " 'seo': 'pov',\n",
+       " 'good_faith': 'good_faith',\n",
+       " 'good_faith_refs': 'good_faith',\n",
+       " 'good_faith_deletion': 'good_faith',\n",
+       " 'good_faith_orthography': 'good_faith',\n",
+       " 'good_faith_article_creation': 'good_faith',\n",
+       " 'good_faith_external_resources': 'good_faith',\n",
+       " 'good_faith_template': 'good_faith',\n",
+       " 'good_faith_wiki_syntax': 'good_faith',\n",
+       " 'good_faith_test_edits': 'good_faith',\n",
+       " 'good_faith_edit_summary': 'good_faith',\n",
+       " 'good_faith_revert': 'good_faith',\n",
+       " 'good_faith_wiki_links': 'good_faith',\n",
+       " 'good_faith_userpage': 'good_faith',\n",
+       " 'good_faith_redirect': 'good_faith',\n",
+       " 'good_faith_html': 'good_faith',\n",
+       " 'good_faith_categories': 'good_faith',\n",
+       " 'good_faith_move': 'good_faith',\n",
+       " 'good_faith_image': 'good_faith',\n",
+       " 'good_faith_edits': 'good_faith',\n",
+       " 'bug': 'maintenance',\n",
+       " 'test': 'maintenance',\n",
+       " 'general_maintenance': 'maintenance',\n",
+       " 'general_tracking': 'maintenance',\n",
+       " 'unknown': 'unknown',\n",
+       " 'misc': 'unknown',\n",
+       " 'unclear': 'unknown'}"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# An auxiliery assignment of manual tags to their corresponding clusters\n",
+    "clusters = {}\n",
+    "\n",
+    "vandalism = ['bot_vandalism', 'page_move_vandalism', 'image_vandalism', 'talk_page_vandalism', 'template_vandalism', \\\n",
+    "'link_vandalism', 'avoidant_vandalism', 'username_vandalism', 'silly_vandalism', 'trolling', 'hoaxing', 'prank', \\\n",
+    "'profanity_vandalism', 'religiously_motivated', 'politically_motivated', 'general_vandalism']\n",
+    "\n",
+    "for i in vandalism:\n",
+    "    clusters[i] = 'vandalism'\n",
+    "\n",
+    "hardcore_vandalism = ['sockpuppetry', 'long_term_abuse', 'abuse', 'harassment', 'doxxing', 'personal_attacks', \\\n",
+    "'impersonation', 'not_polite', 'hidden_vandalism']\n",
+    "\n",
+    "for i in hardcore_vandalism:\n",
+    "    clusters[i] = 'hardcore_vandalism'\n",
+    "\n",
+    "spam = ['spam', 'phishing', 'malware']\n",
+    "\n",
+    "for i in spam:\n",
+    "    clusters[i] = 'spam'\n",
+    "\n",
+    "disruptive = ['copyright_violation', 'bad_style', 'lazyness', 'edit_warring', 'wiki_policy', 'guideline_vio']\n",
+    "\n",
+    "for i in disruptive:\n",
+    "    clusters[i] = 'disruptive'\n",
+    "\n",
+    "pov = ['biased_pov', 'conflict_of_interest', 'stockbrocker_vandalism', 'self_promotion', 'seo']\n",
+    "\n",
+    "for i in pov:\n",
+    "    clusters[i] = 'pov'\n",
+    "    \n",
+    "good_faith = ['good_faith', 'good_faith_refs', 'good_faith_deletion', 'good_faith_orthography', \n",
+    "              'good_faith_article_creation', 'good_faith_external_resources', 'good_faith_template', \\\n",
+    "              'good_faith_wiki_syntax', 'good_faith_test_edits', 'good_faith_edit_summary', 'good_faith_revert', \\\n",
+    "              'good_faith_wiki_links', 'good_faith_userpage', 'good_faith_redirect', 'good_faith_html', \\\n",
+    "              'good_faith_categories', 'good_faith_move', 'good_faith_image', 'good_faith_edits']\n",
+    "\n",
+    "for i in good_faith:\n",
+    "    clusters[i] = 'good_faith'\n",
+    "    \n",
+    "maintenance = ['bug', 'test', 'general_maintenance', 'general_tracking']\n",
+    "\n",
+    "for i in maintenance:\n",
+    "    clusters[i] = 'maintenance'\n",
+    "    \n",
+    "unknown = ['unknown', 'misc', 'unclear']\n",
+    "\n",
+    "for i in unknown:\n",
+    "    clusters[i] = 'unknown'\n",
+    "    \n",
+    "clusters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['hardcore_vandalism',\n",
+       " 'hardcore_vandalism',\n",
+       " 'spam',\n",
+       " 'hardcore_vandalism',\n",
+       " 'maintenance',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'maintenance',\n",
+       " 'hardcore_vandalism',\n",
+       " 'good_faith',\n",
+       " 'disruptive',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'unknown',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'good_faith',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'maintenance',\n",
+       " 'disruptive',\n",
+       " 'vandalism',\n",
+       " 'good_faith',\n",
+       " 'vandalism',\n",
+       " 'vandalism',\n",
+       " 'pov',\n",
+       " 'pov',\n",
+       " 'hardcore_vandalism',\n",
+       " 'hardcore_vandalism',\n",
+       " 'vandalism',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'hardcore_vandalism',\n",
+       " 'hardcore_vandalism',\n",
+       " 'good_faith',\n",
+       " 'disruptive',\n",
+       " 'good_faith',\n",
+       " 'disruptive',\n",
+       " 'good_faith',\n",
+       " 'spam',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'maintenance',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'good_faith',\n",
+       " 'vandalism',\n",
+       " 'spam',\n",
+       " 'good_faith']"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tags_2nd = [x[0] for x in all_tags_2nd_counts]\n",
+    "#tags_2nd\n",
+    "[clusters[x] for x in tags_2nd]\n",
+    "#good_faith_wiki_ĺinks"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'vandalism' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'hardcore_vandalism' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'spam' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'disruptive' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'pov' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'good_faith' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'maintenance' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n",
+      "/home/lus/uni/ma-arbeit-filters/src/env3/lib/python3.6/site-packages/matplotlib/legend.py:798: UserWarning: Legend does not support 'unknown' instances.\n",
+      "A proxy artist may be used instead.\n",
+      "See: http://matplotlib.org/users/legend_guide.html#creating-artists-specifically-for-adding-to-the-legend-aka-proxy-artists\n",
+      "  \"aka-proxy-artists\".format(orig_handle)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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BAAAAsOmpV9B00kknxYwZM2LfffeNli1bRkREJpNp1MYANhXZ8f0KWq7ipEmJOwEAACiuegVNzz77bEyfPr02ZAIAAACAj6vXHE3t27ePFStWNHYvAAAAAGzC6jWi6Wc/+1kcdthhceihh0br1q1rb7/ssssarTEAAAAANi31CpouvPDC2GKLLWL58uVRXV3d2D0BbJYKnespwnxPAADAxqFeQdPLL78cL7/8cmP3AgAAAMAmrF5zNHXu3DmWLFnS2L0AAAAAsAmr14im0tLS6NmzZ3z5y1+uM0fT6NGjG60xAAAAADYt9Qqa9t5779h7770buxcAUng1W/iyHStqf9z76JEFl5nxwM8L7wEAANhk1Stouvzyyxu7DwAAAAA2cfUKmq688sr13n7ZZZclbQYAAACATVe9gqYPPvig9ufly5fHww8/HH379m20pgAAAADY9NQraLrhhhvqXL/iiiti6NChjdEPAAAAAJuoegVNH7fDDjvE66+/nroXAJqpQicW//ik4tnx/QqqU3HSpCT9fLynja0OAAAUW72Cpp///P92YletWhVPPfVU7Lzzzo3WFAAAAACbnnoFTVOmTPm/BUpKYp999olhw4Y1WlMAAAAAbHrqFTTdcccdjd0HAAAAAJu4DQZNEydO3ODCBx98cNJmAAAAANh0bTBoOu+889a5LZPJxFtvvRXz58+PVatWNVpj7733Xhx++OHx8ssvx9KlSxvtcQCgOUk18ToAABRig0HT008/Xef6e++9Fz/+8Y9j3Lhx8aMf/ahRG9tmm23i0UcfjeOOO65RHwcAAACANFrU55eWL18e1157bey9994REfHiiy/GJZdc0qiNtWrVKrbffvtGfQwAAAAA0tlg0LR69er41a9+FXvttVe89NJL8eSTT8bo0aNjhx12yOtBRo4cGe3bt49MJhNTp06tc9/MmTOjX79+0alTp+jdu3dMnz49/2cBAAAAQNFt8NC5rl27xooVK+Kaa66JHj16xOLFi2PatGm193fv3r1eDzJkyJD4wQ9+EAceeOA69w0fPjyGDRsWQ4cOjfvuuy+GDh26ziF7AAAAAGz8Nhg0LVu2LDKZTFx22WXr3JfJZOL111+v14N80tnpFi5cGM8880z89a9/jYiIY489NkaMGBGvvvpqdOzY8VPrjh49OkaPHl173aThAJBGdny/gparOGlSo9QBAGDTsMGg6Y033mjUB58zZ07ssssuUVKypo1MJhPt2rWL2bNnR8eOHeOwww6LKVOmxGGHHRY33XRTdO3atc7yo0aNilGjRtVeLy8vb9R+AQAAAPhkGwyaiu2xxx4rdgsAAAAA1FO9zjrXWHbbbbeYP39+rFy5MiIicrlczJ49O9q1a1fMtgAAAAAoQFGDprZt20bPnj1j3LhxERFx//33R3l5eb3mZwIAAABg49IkQdPw4cOjvLw85s6dGwMHDqwTJI0dOzbGjh0bnTp1iuuuuy7uuOOOpmgJAAAAgMSaZI6msWPHfuJ9nTt3jn//+98Nqp/NZiObzUZVVVWD6gAAG6fp93y34GW7HH9rwk4AANiQoh46l0pFRUVUVlZGaWlpsVsBAAAA2Gw1i6AJAAAAgOITNAEAAACQhKAJAAAAgCQETQAAAAAk0SRnnWtszjoHANTHMd3OL3jZP7zw09qf9z56ZMF1Zjzw84KXBQDY2DWLEU3OOgcAAABQfM0iaAIAAACg+ARNAAAAACQhaAIAAAAgCUETAAAAAEkImgAAAABIQtAEAAAAQBIlxW4ghWw2G9lsNqqqqordCgBAXrLj+xW0XMVJk+pc3/vokQXVmfHAz5PUWV8tAGDz0yxGNFVUVERlZWWUlpYWuxUAAACAzVazCJoAAAAAKD5BEwAAAABJCJoAAAAASELQBAAAAEASgiYAAAAAkhA0AQAAAJBESbEbSCGbzUY2m42qqqpitwIAQETc8sP7C1727OuOTV4nIqJVhz4F1ameNbngHgBgc9MsRjRVVFREZWVllJaWFrsVAAAAgM1WswiaAAAAACg+QRMAAAAASQiaAAAAAEhC0AQAAABAEoImAAAAAJIQNAEAAACQhKAJAAAAgCQETQAAAAAkIWgCAAAAIImSYjeQQjabjWw2G1VVVcVuBQCAZq5Vhz4FLVc9a3LiTgBg49MsRjRVVFREZWVllJaWFrsVAAAAgM1WswiaAAAAACg+QRMAAAAASQiaAAAAAEhC0AQAAABAEoImAAAAAJIQNAEAAACQhKAJAAAAgCQETQAAAAAkIWgCAAAAIAlBEwAAAABJlBS7gRSy2Wxks9moqqoqdisAAFAvex89sqDlZjzw8zrXs+P7FdxDxUmTktdp1aFPwXWqZ00ueFkANg7NYkRTRUVFVFZWRmlpabFbAQAAANhsNYugCQAAAIDiEzQBAAAAkISgCQAAAIAkBE0AAAAAJCFoAgAAACAJQRMAAAAASQiaAAAAAEhC0AQAAABAEoImAAAAAJIQNAEAAACQhKAJAAAAgCQETQAAAAAkIWgCAAAAIAlBEwAAAABJlBS7gRSy2Wxks9moqqoqdisAAEAirTr0KWi56lmT61zPju9XUJ2KkybVuX5Mt/MLqhMR8YcXflrwsgCbkmYxoqmioiIqKyujtLS02K0AAAAAbLaaRdAEAAAAQPEJmgAAAABIQtAEAAAAQBKCJgAAAACSEDQBAAAAkISgCQAAAIAkBE0AAAAAJCFoAgAAACAJQRMAAAAASQiaAAAAAEhC0AQAAABAEoImAAAAAJIQNAEAAACQhKAJAAAAgCQETQAAAAAkIWgCAAAAIAlBEwAAAABJCJoAAAAASELQBAAAAEASgiYAAAAAkhA0AQAAAJBESbEbSCGbzUY2m42qqqpitwIAALBB2fH9Cl624qRJtT8f0+38guv84YWfJulp7X4iIkbdOL6gOqO/d1JBywEbn2YxoqmioiIqKyujtLS02K0AAAAAbLaaRdAEAAAAQPEJmgAAAABIQtAEAAAAQBKCJgAAAACSEDQBAAAAkISgCQAAAIAkBE0AAAAAJCFoAgAAACAJQRMAAAAASQiaAAAAAEhC0AQAAABAEoImAAAAAJIQNAEAAACQhKAJAAAAgCQETQAAAAAkIWgCAAAAIAlBEwAAAABJCJoAAAAASELQBAAAAEASgiYAAAAAkhA0AQAAAJCEoAkAAACAJARNAAAAACQhaAIAAAAgCUETAAAAAEkImgAAAABIQtAEAAAAQBKCJgAAAACSEDQBAAAAkISgCQAAAIAkBE0AAAAAJCFoAgAAACCJjTZoOvvss+Oggw6Ka665ptitAAAAAFAPG2XQ9Mwzz0RJSUk8/vjj8dxzz8WCBQuK3RIAAAAAn2KjDJqefPLJGDBgQEREHHLIIfHss88WuSMAAAAAPk2jB00jR46M9u3bRyaTialTp9a5b+bMmdGvX7/o1KlT9O7dO6ZPnx4REYsWLYo2bdpERMQ222wTixYtauw2AQAAAGigksZ+gCFDhsQPfvCDOPDAA9e5b/jw4TFs2LAYOnRo3HfffTF06NB4+umno6ysLJYsWRIRER988EHsueee6609evToGD16dO31pUuXNs6TAAAAoMlkx/craLmKkyYlqfPxWtPv+W7Bdbocf2vyfhpSa2Or8/Faex89suA6Mx74ee3Po24cX3Cd0d87qc71VH+jzUWjj2g6+OCDo7y8fJ3bFy5cGM8880ycfPLJERFx7LHHxpw5c+LVV1+N/fffP/7xj39ERMTEiROjV69e6609atSomDt3bu1l6623brwnAgAAAMAGFW2Opjlz5sQuu+wSJSVrBlVlMplo165dzJ49O3r37h0rVqyIgw46KHr06BE77bRTsdoEAAAAoJ4a/dC5Qt16662f/ksAAAAAbDSKNqJpt912i/nz58fKlSsjIiKXy8Xs2bOjXbt2xWoJAAAAgAYoWtDUtm3b6NmzZ4wbNy4iIu6///4oLy+Pjh07FqslAAAAABqg0YOm4cOHR3l5ecydOzcGDhxYJ0gaO3ZsjB07Njp16hTXXXdd3HHHHQU9RjabjeOOOy6qqqpStQ0AAABAnhp9jqaxY8d+4n2dO3eOf//73w1+jIqKiqioqFjv2e0AAAAAaBpFO3QOAAAAgOZF0AQAAABAEoImAAAAAJIQNAEAAACQhKAJAAAAgCQa/axzTSGbzUY2m42qqqpitwIAAACw2WoWI5oqKiqisrIySktLi90KAAAAwGarWQRNAAAAABSfoAkAAACAJARNAAAAACQhaAIAAAAgCUETAAAAAEmUFLuBFLLZbGSz2aiqqip2KwAAAACbrWYxoqmioiIqKyujtLS02K0AAAAAbLaaRdAEAAAAQPFlcrlcrthNpLLlllvGjjvuWOw2Gt3SpUtj6623VqcJaqnTNHVS1lKn6Wqp0zR1UtZSp+lqqdM0dVLWUqfpaqnTNHVS1lKn6Wqp0zR1UtZK2dPG7J133okVK1bU75dzbHJ23XVXdZqoljpNUydlLXWarpY6TVMnZS11mq6WOk1TJ2UtdZquljpNUydlLXWarpY6TVMnZa2UPTUXDp0DAAAAIAlBEwAAAABJtLziiiuuKHYT5K9v377qNFEtdZqmTspa6jRdLXWapk7KWuo0XS11mqZOylrqNF0tdZqmTspa6jRdLXWapk7KWil7ag6a1WTgAAAAABSPQ+cAAAAASELQBAAAAEASgiYAAAAAkhA0bWZeeumlYrewXtXV1fHaa68VvPx///vfet3G/8nlcvHBBx8Uuw1gE7R48eL4z3/+U+w2Ngv+1mwsVqxYUewWNiv209a1evXqYrfwiRr6/pg2bVq9bquPhn6uIn+21esyGfgmYv78+XHTTTfFzJkzY+XKlbW3/7//9//yqtO+ffvYa6+9YsSIETFo0KDIZDIF9bNs2bK466671unn5z//ed61JkyYECeeeGKUlJTE7Nmz4+mnn46bb745xo0bV+8aPXv2jOeee+5Tb2tKM2bMiCuuuCJeffXVOn+jfDcas2fPXue2srKyaNOmTd49nXHGGfGzn/0sttpqq+jdu3fMnDkzfvrTn8ZZZ52Vd6358+fHyy+/HIceemisXLkyVq9eHVtssUVeNU444YQ4++yzo1+/fnk//sd7SfH+SPm63pisWrUqBg4cGI899liD6vz2t79d57aysrLo1atX7LrrrnnV6t+//zrrn7Kysujbt2+MHDkyttxyy3rVufbaa+PCCy+svV5dXR3nnntu3HrrrXn1U+PFF19c5/9/zDHHFFQrlSVLltTpZ/vtt89r+VTroiOOOCLuueeeKCkpia5du0ZExCmnnBJXXnllXnUi1nxYePvtt+v0065du7xqTJw4cZ3bysrKolOnTtG6deu8ai1evDguvvjieOONN+Khhx6KGTNmxPPPPx8nnHBCvWukXH+k/FtHNPw1lLLWG2+8Eddff3289tprder8/e9/z6vOj3/847jkkks+9bZPs//++8dTTz31qbd9mvX9b2rWab17986rVkTD10WpnlfEmnXFiSeeGIsWLYq5c+fGs88+G/fee2/85Cc/ybvWk08+uc7//pRTTsm7zv333x8vv/xyXHTRRTFv3rx47733olu3bnnV6NOnT4wcOTIqKiqiVatWefewtlTPK9V+WqptbCop1rERa7YT3/72t+PMM8+MHXfcseB+nn766ejSpUtstdVWUVlZGU899VSMGjUqPve5z+VdK9X7I9VnmRSfqyLS/c/mzJkTO+20U2yxxRbxr3/9K6ZMmRKnnnpqbLPNNnnVSSnV+jr1trq5MaJpE3HMMcfEhx9+GIMHD45vfOMbtZd8vf7663HWWWfFmDFjYs8994yf/OQn8d577xXUz8MPPxxlZWWx00471V4K8cMf/jAef/zx2GGHHSIionfv3jFlypR6LfvRRx/FkiVLYtWqVfHBBx/EkiVLYsmSJTFnzpz48MMPC+pn4sSJsf/++8f2228fbdq0iW222aagUOf444+P/fffP2666ab45S9/WXvJV69evaJDhw7RqVOn6NSpU3To0CF222236NKlS0ydOjWvWs8++2yUlZXFI488Evvuu2+8/fbbcdttt+Xd03333ReJIIy1AAAgAElEQVR9+vSJoUOHRkTE9OnTY/DgwXnX6d+/f5x11lnRs2fP+PWvfx3Lly/Pu0ZEuvdHqtf1c889F0cccUR06tQp9thjj9pLseq0bNkyli1b1uBvAsePHx/Dhw+Pu+++O8aNGxff/va3Y/To0dG7d++orKzMq1avXr2ipKQkzjjjjPjWt74VW2yxRXzuc5+LZ555Js4+++x61/n3v/8dX/3qV+P999+P1157Lfr06RMtWhS2aTvvvPOif//+dd6z+bw/WrRoES1btvzES77uvffeaNu2beywww6x8847x0477RQ777xz3nVSrYsWLFgQZWVl8fDDD8dRRx0VM2fOjAceeCDvOnfeeWeUlZVFt27dolevXtGrV6/Yb7/98q4zcuTI6N+/f+1rqH///nH88cfHnnvuGf/4xz/yqjV8+PDYeeed44033oiIiA4dOsT111+fV42U28VUf+tUr6GUtY477rgoKyuLESNGxHnnnVd7ydcf/vCHet32adYOBmquFzKK5MUXX4xf/vKXMWfOnJg7d27cdtttMWHChDjppJPyDhsbui6KSPe8Ita812677bbaD/Y9e/aM//3f/827zne+85044YQT4r777osHH3wwHnzwwXjooYfyrnPZZZfF7bffHnfeeWdErFn3Dh8+PO86V155ZVRWVkb79u3j0ksvjXnz5uVdIyLd84pIt5/W0G3sdtttF9tvv/06l5rb85ViHRsR8eijj8bChQuja9eu8c1vfjOefPLJvGtERHzrW9+KLbfcMmbOnBkXX3xxtGrVKk477bSCajX0/bFw4cKYNm1aVFVVxQsvvBDTpk2LadOmxeOPP17QZ5mGfK5aW6r/2VFHHRWrV6+OefPmxfHHHx//+te/4vTTT8+rRur9q1Tr61Tb6mYrxyahW7duyWs+88wzud122y1XWlqa+9a3vpWbN29evZf9whe+kKyP/fbbL5fL5XL77LNP7W1r/7whV1xxRS6TyeRatGiRy2QytZdtt902d+WVVxbUT6dOnXLZbDb35ptv5ubOnVt7yVd9n8OnueCCC3J33HFHbvXq1blVq1bl7rrrrtz3v//93B//+MfcAQcckFet7t2753K5XO7888/PZbPZgvvs2bNn7r///W+dZffee++869R4/PHHcyeccEJu5513zn3/+9/PvfHGG3ktn+r9kep13bVr19xtt92We/7553P/+c9/ai/FqpPL5XIjR47MHXnkkbnx48fn/vSnP9Ve8nHMMcfkXnzxxdrrL730Uu7oo4/OzZo1K+//Qd++fXMrV66svf7RRx/lvvjFL+aqq6tzn//85/OqdcMNN+R233333G677Vb7ui7Ennvumfvwww8LXn7p0qW5Dz74IHfVVVflLrrootycOXNyc+bMyV188cW5H//4x3nX69ChQ+7pp58uuJ8aqdZFXbp0yeVyudx3v/vd3IMPPlhw7T322CP30ksvNbif008/PfePf/yj9vqECRNyp512Wu7pp5/O9erVK69a++67by6Xq/t8ataX9ZVyu5jqb53qNZSyVkPX14888kju3HPPzbVt2zb3ve99r/Zy+umn1/4f6+O6667LlZWV5UpKSnLbbbdd7aV169a5YcOG5d3XwIEDc2+//Xbt9bfffjt3+OGH59599928t48NWRelfl65XK72/VTIftraOnbsmKuqqiqoh7V17949t3Llyjo9NOR19eabb+YuvPDC3C677JIbMmRI7oknnshr+VTPK5dLt5/W0G3sG2+8scFLvlKsY9f24Ycf5saOHZtr165dbr/99suNHz8+t3r16rz7ufnmm3M/+9nP1uktHw19f9x000259u3b57bYYotc+/btay89evTI3X777Xn305DPVWtL9T+rqTN27NjcVVddVVCd1PtXqdbXqbbVzZURTZuIXr16xcyZM5PUmjlzZpx77rkxaNCg+OpXvxpPPPFEdO7cOY444oh61/j85z+fbA6k1q1bx9KlS2uH+L7wwgtRWlpar2Uvv/zyWL16dQwbNixWr15de1m0aFFceumlBfXTpk2bGDJkSLRr1y523XXX2ku++vfvv95DO/L1l7/8JYYOHRqZTCZatGgRp5xySjz22GNx1FFHxeLFi/OqtfPOO8d3vvOdyGazcdhhh0V1dXWsWrUq755atmxZ+01JjXwPm1tb586d4wtf+EKUlJTESy+9FAceeGBe35qken+kel23bNkyhg8fHt27d48uXbrUXopVJyJqvy37n//5n7jxxhvjxhtvjJtuuimvGq+88kp8/vOfr73euXPnePXVV6N9+/Z5jyJ699136wzrz2Qy8f7770dJSUlehz1VV1fHm2++GWVlZZHJZAoeFRcRsdtuu+V9yNXaPvOZz8TWW28dDzzwQFx99dVRXl4e5eXl8eMf/7igkRY777xzQSN9Pi7Vuqhr165x5JFHxkMPPRQDBgyIZcuWFVTns5/9bHTu3LnB/TzzzDNx6KGH1l4/5JBD4tlnn4399tsvqqur86r18fVXVVVV5PKcWSDldjHV3zrVayhlra5du673kPD6at26dZSVlUWLFi1i2223rb107do1r/fZt7/97ZgyZUocdthhMWXKlNrLW2+9FWPHjs27r7lz59YZwbbTTjvFW2+9Fdtvv33eh2U1ZF2U+nlFRJSUlER1dXXtOnvOnDkFjSLYZZddkhyyVVpaus7j5/t+Xdv7778fCxYsiBYtWsQuu+wSI0aMiBEjRtR7+VTPKyLdflpDt7G77777Bi/5SrGOrZHL5eKvf/1r3HvvvbH11lvHCSecEL///e/zOrR0xYoVsWDBgnjwwQdrtyOF/J0jGv7+OOecc+K1116Liy++OGbNmlV7mTp1apxxxhl599OQz1VrS/U/W7FiRaxYsSIeffTR6N+/f97LR6Tfv0q1vk61rW6uSordAPUzatSo6NevX+y11151NhD5zmkwcODAmDlzZpx11lkxffr0KCsri4g1wzxrhiDXx9VXX117HOva/fzmN7/Jq5+IiEsvvTS+/OUvx7x58+Lkk0+Oxx57LH73u9/lVeOiiy6Kjz76KMnxv8cee2zcfffd8Y1vfKNB4cmQIUNi4MCBsc0220Tr1q0jl8tFJpOJ119/Pa86K1asiJkzZ8Zee+0VEWuCwpoP0/nu6I0fPz7GjRsXp556apSVlcUbb7wRo0aNyqtGRMQ222wTCxYsqN2I/e1vfytoKPXkyZPjlltuiQkTJsTQoUNj8uTJseuuu8aHH34YX/jCF+KCCy6oV51U749Ur+sDDjggnnnmmQZ/KEtVJyLyPpRofbbZZpv47W9/G9/85jcjIuLuu++OrbfeuqBaX/rSl+LII4+Mk08+OSIifve738WAAQNi6dKlee2w9+vXL/bbb7948sknY8GCBXHCCSfEP/7xj/j1r3+dd08/+clPoqKiIgYOHFjn/5/vPBsffPBBLFy4MNq2bRsRa4bFF3LIyrBhw+Kaa66JIUOG1Okn37mMGroumj59enTp0iXuvPPOeOSRR6JHjx6x1VZbxbx58+Laa6/Nq5eIiMGDB8dNN90UJ554Yp3nle8hyi1atIiJEyfGwQcfHBFrDnuuCTzznX+wf//+cfXVV8fy5cvjscceixtvvDHvublSbhdT/a1TvYZS1nrnnXeiR48e0bdv3zp16vth4ZBDDolDDjkkBg8eHD169MjrsddWE1D9+c9/LrjG2nbdddf40Y9+VHtIyB133BGf+9znYtWqVXm/HhuyLqp5XmPHjo22bdvWLr98+fKYM2dO7Lbbbnn1EhExYsSIGDx4cLzzzjtxySWXxLhx4wqan+mLX/xiDBkyJL7xjW/UeV6DBg3Kq87uu+8ejz/+eGQymaiuro5rrrkm9tlnn7z7+f3vfx9jxoyJJUuWxMiRI2PMmDFRWloaq1atio4dO8aYMWPqVSfV84pIt5+Wahs7ceLEOP/882vn+KvZfixZsiSvflKsYyPWzMv4q1/9Krp06RIXXHBBfPnLX46INfuBNfvJ9fG9730vOnfuHIcddlj07NkzXnvttdhuu+3y7icizfsjk8lEZWVlXHbZZQX1sLYUn6si0v3PTjjhhNh5552jU6dO0a9fv5g/f35stdVWedeJSLd/lWp9nWpb3VyZDHwT0aNHjzjqqKNiv/32qxMufPWrX613jVwuF3fffXecfPLJBc9hUuPAAw+MPfbYY51+vvvd7xZUb9asWfHII49ELpeLgQMHxp577pnX8j179oxJkybFu+++G3369IkDDzwwVq5cGdlsNu9e/vSnP8XJJ59cm0rXbFTz/aajc+fOccEFF6zzN8p3RMqf/vSnOOOMM2p3qKdNmxa33357fOlLX4pbbrmlzkTIn+a5556Lnj171rntgQceiKOPPjqvnp5++ukYPnx4vP7669G1a9eYNWtW/O///m/eO3rdu3ePc845J0466aR1vmEbO3ZsvedcSPH+iGj463rfffet3fF9+eWXo2PHjnWeV74TOnbr1i1JnRrV1dUxa9asOqN+unfvXu/lX3755fjmN78ZU6dOjUwmEz169Ii77ror2rVrF5MmTYrDDz+83rVWrlwZY8eOrQ0DBwwYEMOHD4+Skvy+//jd734XJ554Yp26F154Ydxwww151YlYMwnrxIkTo1u3brX//5qdv3yMHTs2rrjiivjKV74SERGPPPJIXHHFFXHmmWfmXed73/tetG7duk4/CxcuzKtOQ9dFNZORHnjggfHEE0/k9djrs77tTyHr2EmTJsXxxx9f++1jdXV13HPPPdG9e/e4//7749RTT613rZUrV8YNN9wQf/zjHyOXy8XgwYPjggsuyCvMT7ldPOuss+IXv/jFp972aVK9hlLWuuuuu9Z7ez7/r4g18/SMGjUqtt122/ja174WTz75ZIwdOzaOPfbYvOo899xzcdFFF8Xrr79e54N0vl8Kvf322zFy5Mj429/+FhFrPujfdNNNsf3228fMmTPzmqg6xbpo//33j4kTJ9ZuO6qqquLQQw8teE6bSZMmxZ/+9KfI5XIxaNCgOPDAA/Ousb7RDJlMJu8vhRYsWBCnnnpq/O1vf4tMJhP9+/ePcePG5T059Ne//vU455xz4rDDDlvnvgcffDC+/vWv16tOqucVkW4/LdU2tnPnznH11VfH/vvvX2e9lu9I/xTr2IiIs88+O84+++zo1KnTOvc9++yz0atXr7zq1Vi1alWsWrWq4C+YU7w/jjjiiBg3blx89rOfLaiHtTX0c1VEuv9ZRMSiRYuiTZs20aJFi1i6dGksXry4oKNFUu1fpVpfp9pWN1eCpk1Ejx494vnnn29QjVwuF926dUty6sUuXbrE9OnTG1wnImpHIkWsmax8xowZceSRR+a1Iqv5IPSrX/0qFi5cGJdccknBf7M99tgjbr/99nU+LHzmM5/Jq06vXr3i2Wefzfvx12fhwoW1O4d9+vQp+EwbXbp0iT//+c+130D/5S9/iXPPPTdefPHFvGstXrw4Jk2aFLlcLvr161c7Oq4YUrw/Ihr+uv7nP/+5wfsPOeSQJPXyrRMR8dBDD8WZZ54Z77//fnzmM5+J999/P3bfffeYNWtW3rVqvj0q5hlDGsOee+4ZL7/8ct474uvzn//8p3YU2YABAwo65HH33XePv//97wXtIK6toeuivffeOy6//PK48MIL4+abb15n6Hwh39qnUl1dHS+99FJErPlA1JBRqA2Vcru4vjMN7bPPPnmfACLVayh1rYj/O9Sp0LPf1qz3H3300RgzZkz85Cc/ieOPPz7vSW+7desWI0aMiL59+zboS6GUUqyL1vd6KeQ1FLHm0Jt8z+jWFJYtWxa5XC7v/bOINcHC0KFD4+67726EzgqXcj8thd69e8fTTz/doBqrVq2KW2+9NUaOHJmoq4ZbvHhxXHLJJfHGG2/Egw8+WPAZ1SLWjBbccssta9dlq1evjo8++ijvw1+HDBkSkydPjq985St1RouPHj067542JitXroybb745XnvttfjFL34Rr732Wrz55psxYMCAguql2L9KJdW2urly6Nwm4oADDoipU6cWNDS4RiaTifLy8vjvf//b4LS8R48eMW/evILS6I874IAD4u9//3t89NFHcdBBB0X79u3joYceyussG2sf/3vuuec2qJ+2bdsWvPJb21e/+tW8vhH7tJ5S1Lntttti8ODBMWHChHj++edjxIgR8Ze//CXvOjVp/ZFHHrnObfn4yle+EnfffXftfE///e9/Y+jQoXmfrSXF+yOi4a/rmgDoN7/5zTpn1PjNb36Td0BU8/tvvfVWRERBp92tcemll8bkyZNj8ODBMWXKlBg3blxB4dz8+fNj1qxZdc5oVHPoUj4WLVoUY8eOXed00PkeZlRVVRW33HJLTJ06tc5IrUKO2d9jjz0aNM/H2nbYYYfo1q1bHHroobFy5co6gXp9lZeXJ/lQ39B10XXXXRe33XZbvPPOO+vs8GYymYKCpjlz5sTjjz8eEWte54W852rm+dl2220jYs03lBH5Hcr1aWeXyeeDUYrt4r333hv33HNPzJo1q84hCosXLy7ow3Sq11DKWvPnz48zzjij9oPCl770pfif//mf2GWXXfKqUzMy7p///GdUVFRE586dCwqtaubCSyHVKe5TrItqRpvVHGLy9ttvF1xz8ODBsf3228dpp50WJ554YoO+WMpms/Hoo49GxJrpHPIdgRaxZrTWU089Vefwm5rb6qtly5bxyiuv5P3YnyTF84pIt5+WahubYjqJli1bxl133ZUkaPr4CMQa+Y5AHD58eHTt2rV2PdShQ4c48cQTCwqaBgwYEH/+859rt0UffPBB7Ry4+ejWrVuSQLdDhw7rrAvLysqib9++cdVVV9V7qosrr7xyndtq6vTu3bve/YwYMSJWrVpV+/fYYYcd4hvf+EY888wz9a6xthT7VxENW1+n3lY3V4KmTcTjjz8et99+e4MPodl6661jn332aXBa/s4770TXrl0LnmNhbStXrqyd++XUU0+Na665Ju8VbcrjfwcNGhRjxoyJ4447rkHzh9xyyy2xePHiKC0tjS233LJ2OP57772XV51HHnkkzj333Hj99ddj1apVBR/KFxFx0EEHxQ9/+MP48pe/HO+991489NBDsccee+RdZ/LkyevcNmnSpLzrvPXWW3UmFf/sZz9bG6rkI9X7I9XresyYMesETbfeemvep3N98cUXY8iQIbV/k/Ly8shms3Um5K6vFi1axO677167QT355JPjxhtvzKvG1VdfHTfccEPssccedQ7nyGfnvsaQIUNixx13XGcUQb7OPPPMaNOmTUyaNCnOO++8uPPOOwsKviLWfLg79NBD46ijjqrz/8935/i+++6L8847L1q0aBGzZs2K6dOnx4UXXhgPP/xwXnUGDBgQ55133jrzfuRzuGNEw9dFgwYNikGDBsU555wTN998c16PvT41hwMfeOCBkclk4txzz41f//rXeQdhvXr1ikwmE7lcLpYvXx7Lli2LHXbYIa9DuTY0+iXf0CLF+uPzn/98HHXUUfHcc8/FUUcdVXt7mzZt4ktf+lJe/USkew2lrDVs2LA48MADa+cMue2222LYsGHx4IMP5lXnM5/5TFx//fVxzz33xL/+9a/I5XLx0Ucf5VUjIt1ceN/5znfiL3/5S+yzzz511o+FBk0NXReNHDky+vbtWzun3rhx4+Lyyy/Pu5eIiNdeey0mTJgQd955Z1x22WVx+OGHx+mnn57X4dIRaz64/vGPf4xTTjklMplMXHvttfHiiy/GJZdckledtT8YRqwZ2VjIPC39+/ePYcOGxdChQ+vsE+f7mk71vCLS7ael2sZ+4QtfiJNPPjmGDh0aEYVPJ3H44YfH+PHj46STTiq4l4g1h9iubwRivl555ZW455574v7774+INRPMFxrELlu2rDZkiljz5cfSpUvzrlPo+/PjTj755Jg3b17tROJ33HFHlJWVRS6Xi29/+9v1PgT3xRdfjAkTJsTXvva1yGQy8dBDD0WfPn1izJgxMWLEiHqvjyZPnhxTp06NfffdNyLWhFX5nrCjRqr9q4aur1Nvq5srh85tIlIdQvOjH/1ovbfnu3JLNcdCxP8dbnD66afHiSeeGIcddlhBww5THf+bav6QN998c72353u2jk6dOsUtt9yyzkY1n8T849/a//a3v40ePXrUzvtU341FTYI/YcKEOnMSLF68OFasWFHQtzdTpkypPTzgo48+ip49e+Z9eGeq90dDX9dPPfVU/Pvf/46f/vSn8f3vf7/29sWLF8e9996b9/Pq379/nHnmmbVzEN1zzz0xduzYgib27tOnT0yePDmOPPLIGDZsWLRv3z6OPfbYvL4F3HPPPeOpp55a54yDhUh1mFG3bt3ihRdeiO7du8e0adNqv0ks5Cxrp5122jq3ZTKZvL8B7tWrV/z1r3+tPetTRGHPt0OHDuvtJ99vblOtiyLWzIExY8aM+OY3vxmLFi2KqqqqvEei9OzZMyorK6Njx44REfHqq6/GcccdV/DcYzX+8Ic/xPPPP/+J27nGlnK7+M477xR8iPTaUr2GUtZKdUjXq6++GmPGjImDDz44jjnmmHj11Vfjvvvuix/+8Id51Uk1F95ee+0VL7zwQoPOXFkj1bpowoQJtR/Avv71r8dBBx3U4N4+/PDDOP/88+NXv/pV3vtF3bt3j8mTJ9d+Efjhhx9G3759Y9q0afVa/vrrr4/rrrsuli5dWufQ7aqqqjjllFPyPqteqtd0Q59XRLr9tBqptrGpppPYbrvtYvHixbHFFlvEVlttVfCXr6kOS6rZJ9p3331jypQpUVVVFV/84hfz+p/V6N69e0yaNKk2rFyyZEn069cv732+OXP+P3tfHldT/v//vGVfYshHZhiGslZaSMlelKVBMYqiKGQQyszYxr6NZSJ8amwhZJsh2caSLbKlZLJUIlu2tkmobq/fH/d3zqer7bzPfVu/no/HeXBP97zu+577Pq/36/1anq/78Pb2xoMHDxATE4OYmBhERERg4sSJTHLatWunxsVGRGjXrh0uXryIli1bIj4+XpIce3t7bNq0SezO9uTJE7i5uSE0NBQdO3aUPL/evtdKpRImJiaIi4tj+l4AP/uKl77mtVZ/rviS0fSJoPCGOTMzE/fv34ehoSGznP79+xeJ1MhRqnIM55LQtWtXtGzZEkqlEkFBQWL7VRbk5+dj/fr1Yv3vkydPcO/ePVmOpoKCAuZrikO9evWK5Z5ihY6ODuzs7DQay9tReyMjIxQUFDBzWfD24Pfs2RMDBw6Ej48PAGDFihUiwR8LeD0fhec1ERUxZsvC48ePERMTg5ycHLV7q6Ojw9TVUUB6eroa0bWzszMWLVrELAdQtc9NT0/H3Llz4eLigoyMDPj7+zPJqFu3LhcnE6ByWmVkZGjM7SW07C1XrhxevnyJ6tWr49mzZ7Jkbdy4UaOxCNDW1i5yn+SkdcvhzyoOvHTRmjVrEBQUhOzsbLi5ueHFixfw9PRkdnwKHZ0E6Ovrc9G7jo6OWLBggSxHk5WVFcaNG4eBAwcyt6IXoKn+AIBly5bB19e3xK41rNnHvOYQT1lEhNTUVOjp6QGQX9Klr6+PJUuWiCWU+vr6zE4mAJI7i5UFni3ueekia2trNGjQgEvJ49OnT7FlyxZs3LgRRITFixczyyAitWzzqlWrMv32o0ePxqBBg+Dt7a1Gr6CjoyOrYxjPOa3J9wJKt9PklITyWmN50Unw4qzhlYHIq6MaAAwZMgS2trYYPXo0AFWWppx90qhRozB48GCxmYmhoSHc3NyYHU1paWnIyckR52ROTg4yMjIAgMmx8uDBA9HJBKhswEePHqFWrVpM66SxsTFCQkJQUFCAxMRELF68GF26dJF8fWHwsq801de81+rPFV8cTZ8I7O3tERoainLlyonRjaFDhxZbP1sa3N3di0TpijsnBTt37izCiyLnwQoICEBsbCwaN26M8uXLQ6lUYu3atUwyeNb/3r9/H3Xr1kWFChUQGRmJq1evYtiwYcwbBh7cUwDQp08f7N27F/369WO6rjB4Ga1CdK13795cPPjz58/HggUL8NNPPwFQlej8/PPPzHJ4PR8jRozAsmXLUKVKFbRt2xYJCQlYunQpxowZI+n6vn37om/fvjh06JCsjfzb0NbWRnx8PFq2bAkAiI+Pl50qLvAOtGnTBgkJCbJkdO/eHRMmTCjSll5OGU6VKlVgZmYGe3t7NVmsOqRWrVpIT09Hr169YGdnB11dXdSvX595PICqm4mzszNq1KiBsWPHIioqCsuXL2cuxatevTqePHkibg6OHz8umROhMC5duoRWrVqhSpUq2LlzJy5evIhJkyYxc3Xx0kV//PEHoqKi0L59ewCqjYwcp95//vMfrFu3Tq2tsBx9Uri9tlKpxIULF5hbbguYPXs21qxZg8mTJ2P48OEYPXo0c6BCU/0BQIyIFy7D0AS85hBPWX5+fjA1NRV15OHDh2V1iTx58iQGDx6McuXKISUlBZcuXcKKFSsQEhLCJKdz587Iy8tDSkqKRg4Zni3ueegiXvcHUGVDXbhwAU5OTtiwYQMsLCyYZQAqHiU3NzexQ9T69euZZNWoUQM1atTAoUOHZH1+SRB4PgWwUiVo+r0AfnaaAF5rLC86CTkZtIVRuKvv2rVrNc5AnDt3LpYsWQIdHR1MnTpV7KgmBz///DP09PRw4MABAKo9iaurK7Ocp0+fwtXVFcuWLQOgCqDJaQgwePBgWFpaYuDAgQCAPXv2wMXFBdnZ2WjUqJFkOd988w1mz56ttlZ//fXXUCqVTM7P5cuXw9fXF6mpqbC2tka/fv1kB0152Vea6mvea/Xnii+lc58IhHTDnTt3IjIyEkuXLoWZmZnktMOnT58iNTUVg9hjAkIAACAASURBVAYNws6dO8VIS2ZmJjw9PXHr1i2m8YwfPx7Jycm4cuUKXFxcsGvXLnTv3h3r169n/m5CNPJtsBC6Cqm0wn0C5HciMzMzw7lz5/DixQtYWlqiQ4cOyM/Px65du5jkCGPZvHkzbt68KXJPsaaKCunGmnI9AaoSyfHjx6uRb69evVpWXTgvRyMPaPp8CBDmUVhYGP7880+sXLkSHTp0kJz1d+rUKXTu3BlhYWHF/p11w3HkyBEMGTJEdOTExcVh69at6NGjB5McQPWsT5s2Dffu3ZPdYYVnGQ6vMl6lUgltbW0QEbZt24b09HRZjmEAYvldZGQkpk6diqlTp2LGjBnMHFSXLl3CqFGjcOfOHRgaGiI5ORkHDhxgJqtv3bo1oqOjcefOHfTq1QsDBgxAdHQ0MzEsL10kpOMX1rNyyhiSkpIwZMgQREdHQ6FQwMzMDCEhIcybfC0tLZGjSVtbGwYGBli+fDns7e2Z5BRGSkoKAgMDERwcDGtra0yYMAHW1taSrtVUf7wL8JpDvGVdv34dJ0+eBKDKLJDTNcjS0hJbt27FgAEDNCqh4OWQ4dninocu4nV/AGDbtm1wdHTUuMzk5cuXmDNnjthS3NbWFjNmzJBchuXi4oLt27eLToe3wepsiIqKgoeHRxFScNaSQE2/19vgQSrPa40tTCch6Fs5dBJPnz7FzJkzERsbq2Y3Sv3NeHf1/RhhaWmJ8+fPw8zMDFevXkV6ejq6du0qKxvswIEDou7p1q0bevfuzSwjNTUV48ePF+e1jY0N/P39UatWLSQkJHyQTpS87Cue+voLSsaXjKZPBAJp2unTp2Fvb4/y5cszebm3b98Of39/PHr0SG2zW6NGDTGbhAURERGIjY2Fqakpli1bhsmTJ8sup+NB6Pq28aNUKjUqxahUqRIOHDiAUaNGYfr06WKWDAsEUlLBiAUgKxuFZ4vMffv2qRkfurq62LdvH7PhUZKjUSq2b98OFxeXEjs+sXIRaPp8CBAcsGfOnEGfPn2go6PD9JuFhISgc+fOxZJsy+nOZWdnh/j4eHFzYWlpKbtjpNBhRdjcyemwwrMMhxfp5cKFCzF9+nQoFAqRZHTevHmySFiFOXPixAkMHToUdnZ2mDJlCrOctm3bIiIiAufOnQMRoX379rLKF7S1taGtrY1Dhw7B29sbkyZNEsk0WcBLF9WpUwe3b98WN3jBwcFMAQEBTZo0QVRUlEiWWpiElwW8ypwLIz09HU+ePIGWlhbq1auHsWPHwtraWlJ5lab6Ayi+y09h/Prrr0zyeM0h3rIMDQ1llTcXhlKpLOKclFNC8csvv+DMmTMYMGAAANXzy1pWDkAWd15J4KGLeN0fQJUhcfHiRRw7dgyAKruVpeuUAIHAXS78/PwAgLnsuyT4+PggODgYo0ePxunTp7Fy5UpZzjRNv1dh8CKV57XG8tKzQgOI48ePY9myZQgKCmLSH287kh48eACFQiG7y6enpycWL16sFnidNm0aM88XwK/D38CBAzFq1ChkZWVh3bp1CAwMhKenJ/N4AFW3WTnOpcLQ09MrkThcipOJd/AV4Gdfaaqvea/Vnyu+OJo+ERgaGqJnz564ceMGfvvtN+Tk5DBd7+PjAx8fH8ydOxczZszQeDyVKlUSo8l5eXnQ09OT1S0MQJHSC4HQlQU863+FFOqjR49iwoQJsmQAfLinAM3TjQujOINBTpceTR2NN2/eBFB8xyc5XASaPh8C9PT04O3tjUOHDmHatGnIy8tjitoJJZ88Nxz/+c9/0KdPH43laNJh5eXLl6hatWqJZUksKfS8nYx//vlnEadSceekQEtLCzt27MCOHTvEFHg5z8eYMWOwZs0atfJJ4RwL3rx5gydPnmD//v3iJkZOt0leusjf3x8uLi64efMmGjRoAB0dHYSHh0u+PiEhAQYGBiVm+MgpwUxJScHp06ehUCjQqVMnNGjQgFkGoCLaDwgIQFZWFsaPH49Vq1ahcuXKIp+UFEeTpvoDgNg568GDBzh+/Di+//57KBQKhIWFyeLB4zWHeMjinY1SqVIlZGdni7Li4uJEzjYWaOqQeRfzmocu4nV/AFXZ7Lx58+Do6AiFQoEBAwZgxowZkjfBvPS+ubk5AH7ZK3l5eWjXrp3Y/XjatGlo27YtfH19JV3Pez0DgGPHjiE+Pl529hjvMRW3dslZz+7fv4+ff/4ZISEhcHBwgJ2dHTp37oy5c+cyyYmNjYWzszNSU1OhUCigp6eH0NBQ5ufsypUrRboeX7p0iUmGAF4d/nx9fbF9+3ZkZmbi77//xqRJk9R4OqXi1atXCAgIKFJ1IKcz+KNHj3D9+nU1OVIdRLyDr4Dm9hUvfc17rf5c8cXR9IkgODgYhw8fRuvWrVGlShU8fPiwRAKy0jBjxgzs2bMHt27dwtSpU/Ho0SO8ePGCOf2xevXqyMnJQYcOHeDq6go9PT01IkRNIIfQdfr06Zg/f75Y/9u3b1/ZtdYuLi7Q09ND06ZN0b59ezx+/FjWd9OUe4q3UQ4AzZo1w2+//QZfX18QEZYtW4bmzZszy9HU0Sj8trw4CXg9H1u3bkVISAiGDRuGmjVr4u7du5g0aZKsMeXl5SE5OVltcZa6gHXu3BmnTp3CV199pfbba1I2+fbG6dWrV5IdTR07dkR0dDRq1qwpZh8KYE2hL83JyIIjR47g8OHDePjwodpvlJmZKVvmqlWrsGjRInh5eaFhw4a4ffu2LBLUqKioIufOnTvHLGfixIlo1qwZbG1tYWZmhqSkJFmEtzx48IgIVatWxYULF3Dr1i0QEZo1a8ZkVE+cOBHh4eFqjQQEyCnB3LZtG8aNGyfy1kyYMAEBAQFwdnZmkgOonv3Zs2fD1tZW7by2tnaJG7biZGiqPwSuoh49eiAmJkbkP5ozZ47YXpwFvOYQD1m8s1GmT5+OHj164OHDh3B1dcWxY8ewbds2ZjmaOmR4z2uAjy7idX+E8Vy5ckXkUps6dSpsbGwkO5p4BZf69+9f6vtZN9ICoXHt2rURHR2NBg0aMPHO8Q6aAZqTFPMeE6/1TLBBKlWqhBcvXuCrr77C8+fPmeV4enpizpw5Iv/Q7t27MWLECGYnUeHMI0C1xskJLAGqRjBCtp8mePHiBVxcXJgyzYuDl5cXdHR0cO7cOfj6+iI4OJiZaxJQZWTNmTMHaWlpMDAwQGxsLCwtLSU7iNauXYuCggIsXLgQlpaWzJ9fHDSdj7z0Ne+1+nPFF46m/2P49ddfcenSJSQlJeH27dt4/PgxnJycmBeNJ0+eoGbNmigoKMDy5cuRnp4OHx8fWdHk4ghdx48fX6RmvjSYmZkVcbwUd04qMjIyoKOjAy0tLWRnZyMzM1Nyei6v7I8rV67A3Ny8xLp0ORG9R48ewdXVFWfPnhUzADZv3szcnrxbt24IDw/HTz/9hGfPnkFPTw9RUVFq7VRLQ0lptALkRDk+JoSHh8PLywvp6emoWrUq0tPT0bBhQ8mlZ48fP0a9evW4tqWfMmUKqlWrhpCQEAQEBOD3339H27ZtMWvWLGZZHwNOnTqFkydPIjAwUOz0Aqier/79+zMRXvLCjh07EBoaipMnT6rV/2dmZuLNmzdiswK5KCgoQH5+vuRsC56ZaEQEIyMj5nbN7xLNmzfHoUOHRO6wu3fvwt7eXtxosWDDhg0i4Wlp594XDA0Ni9zr4s6xgnUOvQtZPO91cnIyDh8+DCKCnZ2dLDLvv//+G7NmzUJSUhK6d+8uOmR4dNr60OBxf4D/cUaVda4sPH/+vEj5d3HnSsKmTZtK/TsrhcPvv/+OoUOH4sqVK3ByckJeXh7mzZsnOkWlQtPvVRiTJ0/GnTt3NCKVVyqV2Lt3L5ycnJg/XwDv9czV1VXkPgsICICOjg6aNm2K0NBQJjnF8QvKmYteXl6oWLEiJk+eDCLC0qVL8fr1a6xbt45JDqD6bTZv3qxxh7/atWujW7duGD58OOzs7NT4sVgg3CPhvvz777/o3bs3Tp8+zSzn9OnT6NatG65evYrTp08jODiYuSRQLmduYbxr+0ou3tVa/bngi6PpIwfvzAaBzLNNmzZitEOOghagaY00oBmha25uLl6/fo2OHTvi7Nmz4n3JyMiAra0tE8k5r3RKwcFV+HtpQqCYnJxchIT5/PnzsLKyYpJTGC9fvgQA2USVmjoaiyPhE8BCxsfr+eCdPWZqaip2Crx69SpCQkIQGxvL3FmpOK4hufxD+fn5WLJkCfbu3QsiEjusaJLmrQkWLlyoxjmSl5eHCRMmYPXq1UxyYmNjZXGoFYbQprak7BOpJPexsbG4evUqZs6cqVa/r6OjAxsbG8mOHV68Brx1kb29PUJCQmTzhAno168f9u7dW+a5ssAzwFDcdebm5rhy5UqZ176L7FN7e3u0a9dOzBhZv349oqKicPjwYUnX8+TG4M2zocm9FqBUKmFnZ8cliwDg45A5e/YsOnTooHZu165dYuaFFPDSRbzvj5OTE5o3b45Ro0YBUGUqxMfHi6XYUsE7KChsYeRmDxVGXl4eXr9+LauRBM/vxYukWJP7CvBbz4pDZGQk0tPTYW9vz1zGPWzYMHh4eIj0GKdOnUJwcDBzhnxWVhYmTJiA8PBwsYxr+fLlsn5/Z2dnXLx4UeMOfy9fvsSuXbsQHByMpKQkuLq6wsPDA02bNmWSY2FhgYsXL8LMzAxnzpxB1apV0aJFC9y4cYNJjqCXCzv35MyrAQMGYNGiRdDX12e6rjDexXwsKChAamqqWnYbK++kpmv1544vpXMfOQRPPy9C6MqVKxfZWMrxNRZXI719+3ZZGz5NiAYXLlyI2bNnQ6FQqLWY1NHRkVxjL4BXOqWggHkRKDo6OiIiIkKMlFy9ehVubm5ITEyUJS8vLw8PHz6UVdIloG7duuL/p02bxjwGXhxGvJ4P3iUdWlpaaNiwobh4ubq6FlujXhZ48g+VK1cOU6ZMkUVu/bYjT4AmpXznz59H7969ERISgrS0NPzwww9o3749s5xWrVphx44dRUg4WYgYebWpbd26NVq3bo3evXuLJSZywIvXgLcuqlatGkxMTNCrVy81Am9WY7q4TqNJSUmSrxcytHr37o1Zs2bB09MTRISNGzfCwcGBaSwXL17E+fPn8ezZM7USOSFKKgW89QegKgceP348TExMoFAoYGtri+DgYMnX8+TG4CWLx70WoK2tjZycHBQUFMiO+hfGd999B29vb41kuLu7Y+TIkfjpp5+Ql5cHHx8fXLp0icnRxEsX8b4/gYGBGDduHMzMzACoyMD/+9//Sr5eCAoqlUr8+++/ap2PhcAXCx4/fowRI0aItoSNjQ3Wrl3LnJ0NADdu3EBCQoLa+uHo6CjpWt7fC+BnH5mZmRXr/JQKXuuZgJCQENja2kJPT09yJ8/iEB0djZCQEDFr+e7du2jZsqU4N6U4QZRKJY4ePcqcmVMSWrRogRYtWmgsp2rVqnB3d4e7uzuSk5OxcOFCtGjRgjkoVKtWLaSnp6NXr16ws7ODrq4u6tevzzweodN106ZN4e/vj4YNG4pNPFiQlpYGExMTtG/fXs12YCl15T0fhTW2fPnyoo5UKBRMjagKy5G7Vn/u+JLR9H8MgwYNwtixY+Hj44MLFy5gwYIFSExMxJYtW5jktG3bFj/99JNajfTixYtlE+lpSujq7e3NZPR8StizZw9WrlyJo0ePIikpCQ4ODggNDUWbNm2YZWla0sWbHwFQRXyPHj0KQNVlTZNU748FlpaWiIqKQs+ePTFy5Eg0atQITk5Okp2VAv/Qtm3bxE5qgMp4vXr1KlM0qSx+GSnEoCWV8AmQS1i/dOlSrFq1SsyME7o+sWDAgAFITU2FhYWFmhOdNXuMN3bu3FmEiJPVIfOxQdN22UFBQQgMDMTt27fRrFkz8XxmZiZatWpVZkmtgMIZWm+DNVNr37592Lt3L8LCwtQcJjo6OnBzc5OlZ7+gePC+1z4+PkhISICrq6va5oU1w+r06dPw8/NDYmIi8vPzRQd6SSWnJSEtLQ3u7u7Iz8/H06dPYWlpieXLl3MpU5QDXveHB2bPni0GBQs/t0JQkLVJjYODA6ysrDBmzBgAKkdYZGQk9u/fzyTH19cXW7duRcuWLdU6vP3999+Sruf5vXiTyhsaGuLmzZto3Lix2u/Pmo3Cq6PaiBEjcOzYMVSrVg02NjawtbVFly5dmDNRSqKTECCVVkLTjK93hby8PISFhWHDhg24dOkSfvjhB0nNKApDqVRCW1sbRIRt27YhPT0dQ4cOZb7XJ06cgLm5OZ4/f47Ro0cjIyMDCxcuLMJlWBZKKnmV262ch33VpEkTHDx4UM0W+QL++OJo+shRUiq+AFYl+eTJEwwbNgzHjx+HQqFA165dsXXrVuZSCF410kBRQtezZ8/KJnTVBGUZlVIV9LvI/vj9999x4sQJ3L59Gxs2bJAdDdK0pIs3P8KcOXOwd+9eDB06FAqFAlu2bEG/fv0kZ+zwej54O9C2b98Oe3t73LlzB87OzsjIyMCKFSskdw/hyT/k4eFR4t8UCgW3iB4r8vLyMGnSJJw5cwbp6emYP38+XF1dmeU0a9YMN2/e1Kh0gocz7u33Jycn48qVK3BxccGuXbvQvXt3rF+/XtL1ZelRqRuOd6GLSsOKFSvg4+NT4t/v3buH5ORkeHt7IzAwUDyvo6MDY2PjD1bGCQCHDh1S62LDgnfhgM/MzMS0adNw79497N+/H/Hx8YiNjZVMEstrDvGWBWh2rwuDV4lRs2bNMH/+/CLOajmUALt374anpyeqVauGY8eOMTfb4KmLeN0fAYcOHSqS+cNKds8rKGhiYlIkk7m4c2VBX18f165d07iZDY/v1adPH4SHhxehSgDkkcrz4ve0tbUttqPajz/+yCRHwO3bt3HkyBEsX74cDx48QF5eniw5msLT0xPu7u6yM77exsWLF4s4P1hth3HjxmHnzp0wMzODh4cH+vXrJ9tR/fLlS1y9ehUKhQImJiayqTJ4gkepq6b2lYB27dpJ5pUtDZqu1Z87vjiaPnLw8ty/jZycHLGLkBzwqpEG+BK6agJeUXJe2R9vR/fnzp0LS0tLdO/eHYC8qGRx9das3BiFoemiYWxsjKioKNHIe/nyJaysrCQ7LHk9H7wcaALv0IkTJ7gQyfLgH+IB3g5vQJUV2aZNG/j7++PJkydwcXFB8+bNmY0FW1tbHDhwQKMuPbydcUZGRoiNjYWpqSliY2ORmpqKYcOG4ciRI5KuL26jUXg8Ujcc7yoTrSR8rBFiKQgKCoKzszNq1KiBsWPHIioqCsuXL5fUqYe3Ax5QcX4YGhoiNDQU169fx6tXr2BlZSV5I81rDvGWBaiczP7+/mqZrD4+PsxcLbzQtm1b2dnYhTFu3DhERkZi586duHnzJsaOHYt58+YxOdA/1sDAkCFDEB8fD1NTU7XMnz/++OODjKd169Y4cuQI9PT0AACpqamws7NjJhzu2rUrjh8/zqW88GOCUqmEu7s7c7VCcWjVqhX++ecfjeUkJibi2LFjOHr0KK5duwZTU1N0794dXl5eTHJevXqFgICAIk4dVoc+r4wvAFiwYAF2796NlJQUdO7cGUePHoWNjQ3++usvZjlDhw6VVeZWGMePH8fgwYPFTmiPHz/G9u3bS+VHLQ45OTnYtGlTEQez1E6sAniWumpqXwlJBatXr0blypUxePBgNV4t1qwvTdfqzx1fOJo+csh1JJWG0NBQHDt2DAqFAt27d8cPP/zALINHjbSAKlWqqBmyjRo10ji6JAe8eEx4bd7e5sOoVq0arl+/juvXrzNzbAgQWvnWr18ff/31Fxo1aoT09HRmOSkpKfDy8hIdPV27dkVQUBAziR4Rqf3WVatWZeIM4/V8yE3ffRu7du3ClClT4Ofnx2XDXatWLfTp0wcPHjxATEwMYmJiEBERgYkTJzLLmjlzJsaPH4/atWsDUHXEWb16taSyJ57cMwImTpwoZnh9++23OHXqlCz+KH19fXTp0gX9+/dXMxZYIolyHOSloVKlSqLjOi8vD3p6enj06JHk66WWspYF3o6ksiD12eW1UeCJ1atXY9SoUYiMjERcXBzmz58PPz8/XLx4scxreemPwrh9+zZCQ0NFsuXKlSsz6UZec4i3LABimdqYMWOgUCiwbt063Lt3j3nzkp+fjxUrViApKQlr1qxBUlIS7t27x+zkd3JywpYtWzBo0CCNytzevHmD8+fPo2LFitDX14exsTFcXFyYHE08dBHvEixA1QX3n3/+0TjrMCEhAePHj0dsbKzas8+aXenn5wdTU1MxM+7w4cOyyqV/++03DBw4EHZ2dmrrx9ChQ5nk8PhevLLqARVHF0vn5tLQpEkTZGRkaNxRrWnTpmjfvj3mzZuHzp07yw5Qenl5QUdHB+fOnYOvry+Cg4MlBQTeBmvjkdKwbds2XL58GZaWltizZw9u3bqFqVOnMsuZOnUqrly5goiICLi5uSE9PR2vX79mdshMmDABYWFhaNeuHQBVttWIESOKVKKUBUdHR5QvXx5t27bV6NkfOXIkOnTogG3btgFQlbqOHDmSudQV0Ny+qlmzplpSQeGsTDlNUjRdqz93fHE0fSLgZZj7+fnh1KlTouGzbNkyXL58Gb/99huTnML1wunp6bh//z6z8cKT0PVjxNOnTzFz5swihodUBwQvQsjC8PHxQXp6OubNmyeWdMlxIgwdOhS9e/fGzp07QURYt24dhg4dipMnTzLJsbCwgJubmxjRWr9+PSwsLJjHw3Pjqkntd5UqVdCzZ08kJycXSybKOp5Ro0Zh8ODBogFtaGgINzc3WY6mffv2qXHs6OrqYt++fZIcTW879IRFXYiWycHbZYTlypWTtVF48+YNmjdvrtZNRZO07EePHuH69etqvz+rU7d69erIyclBhw4d4OrqCj09PY2c52/evFEjS2aNuGmqi6RC6n3ntVHgCSGb5sSJExg6dCjs7OxkOT55cXO97fB49eqVRsarpnOIp6yIiAjExMSIWSS9e/cWg1QsGDt2LJRKpdjWunbt2hg0aBAuX77MJKdFixZwdXWFu7s7AMjuyvh2do/gQJcLubqIV2OTwmjUqBHevHmjcRDQy8sL3t7emDNnDkJDQxEQEMBUCi7Azc0Npqamos3h6+uLVq1aMcsJDAzEtWvXxK7HgOoesTqaeHyvtzfAhSFnPnbt2hUjR46Eu7u7WsaOVFtd2IBXqVIFZmZmGndUCw8Px7Fjx+Dr64sqVarAxsYG3bt3Z6aCiI2NRVxcHIyNjTFu3Di4u7ujd+/eTDIAvoH8SpUqoVKlSigoKAARoVmzZkwNLgSsWbMGQUFByM7OhpubG9LS0uDp6cm8H9DS0hKdTACKlAVLRUpKCuLj45mvexv3799Xcyr98ssvMDExkSVLU/uKV1KBAN5r9WcH+oJPAkOGDCFvb29q2LAhrVy5kszMzGjChAnMcgwMDCgnJ0d8nZOTQwYGBsxy7OzsKD09nf79919q2LAhNWzYkGbMmMEkQ6FQkJaWFikUiiKHlpYW85h44fbt22Rvb0/16tWjr776SjxY0adPH1q0aBEZGBhQWFgY9e7dm6ZPn84sJygoiF68eCG+fv78Of3xxx/McoiInj17JulcWWjZsmWRc61atWKWk52dTT/99BOZm5uTubk5/fzzz5Sdnc0sh9fzMW7cOOrTpw/Vq1ePJk2aRA0aNKDhw4dLvj4tLY1CQ0Pp22+/peDg4CIHK8zNzYmIyMTERDxX+P8sMDIyKnKO9TeLj4+nli1bUs2aNalmzZpkaGhIN27ckDWenJwcWrx4Mbm4uFD//v3F40Ni/fr11LBhQ6pevTqZmZmRtrY2WVtbM8tJTU2l169fU05ODs2bN498fX0pJSWFWc758+epefPmpKWlpXawgpcuKgumpqaS3mdoaEhE/5uTWVlZ1LFjR+7jYYG5uTmFhoZSq1at6O7du0TE/nxoqj8K45dffqF58+ZR8+bN6ejRo9SrVy+aOXMmsxxec4inLENDQ8rLyxNf5+bminOCBa1btyYidZ1obGzMLOe7776j48ePU2ZmJmVnZ4sHK0aOHElv3rwRX6elpVGfPn2Y5RDx00W8cP36dbKysqIpU6bQ7NmzxYMVgo4Qfu+CggJq27atrDFlZ2fTmTNn6OzZs7J+LyKixo0bq81FueD5vcrC69evJb2vUaNGRY7vvvtO8ufMmjWr1EMuXr16RZs3b6ZGjRrJ0h/CfTU1NRV/9+bNmzPL6dKlC3Xt2rXIIQcdOnSg3NxccnNzo0mTJtHy5ctl67ScnBw1nSbHtvbz86ONGzdSQUEBFRQU0KZNm2jy5MnMcvr37y9rj/A2jI2N6fHjx+Lrx48fy9LVRPzsq5SUFFFfnz17lgICAigrK4tZDq+1+nPFF0fTJwJehnnbtm1JqVSKr/Py8sjCwoJZjqAEd+zYQePHj5dtKH6M6Ny5M4WGhlLLli3p2rVr5OXlRfPnz2eWIxjBwn158+YNWVpaypZTGHKdDcVtBKVuDgvj+++/p1u3bomvb926Rf369ZM1Jh7g9XwYGhqSUqkUF8DHjx9Tjx49mOUcO3as1L/v3LlTkpx27dpRQUGB+HunpaUVOx+kYMCAAbR48WLKz8+nvLw8WrRoETk5OTHJ6NKlC23dulV8vX37durSpYus8fByDlpaWtLWrVspNzdX1jgKw9DQkNLS0sT7ferUKfLw8GCWc+3aNY3HQkRkYWFBUVFRZGJiQllZWTRv3jxaunQpsxxeuqgsSNVLvDYKPBEVFUV9+/Ylf39/IlLptHHjxjHJ4KU/iFRr84IFC8jCwoLatm1L8+fPp/z8fGY5vOYQT1l+fn7UtWtX2rRpE23atIlsbGxkbYLatWtHRP+bd/n5+bLsEEGOpvjxxx/J1NSUatyuawAAIABJREFUEhMTKTIykho3biz7Xmuii+7du1fqIQcODg7UuXNnmjhxIvn5+YkHKwR708rKipKTk+nVq1dMzg8Bx44do//85z9kampKJiYmVLduXTpx4gSzHFtbWy5rB6/vJQVybLZ3CUFnloWFCxeSjY0N1a5dm+zs7Oi3336j6Oho5s+zs7OjtLQ0mjZtGllbW1Pfvn3J1taWWU54eLh47N69mxwdHemXX35hlkNEFBcXR9nZ2fT06VPy9PQkJycnunr1KrMcYR4VXkvl2Hw1a9YkhUJBFSpUoAoVKpBCoRADhCyB8/j4eNLX1ycXFxfy8PAQD1Zs3ryZ9PT0xOvr1atHISEhzHKI+NlXpqam9OrVK3rw4AHVr1+fnJ2dacCAAcxyeK3Vnyu+OJo+EfAyzMeNG0e2tra0efNm2rx5M/Xo0YN8fHxo3759tG/fPslyBA/7jz/+SPv37yciecrwYwSvyJRwTZs2bej58+ekVCpJX1+fWU5xXv/islNKw5s3bygzM5OMjY0pKyuLMjMzKTMzk1JSUqhp06bMY+rWrRtVqlSJunXrRt26daPKlSuTjY0Nc1ZKWloajRo1ipo0aUL6+vrk7e1NaWlpzOPh9Xy0adOGiFRzWTA+34UDVaqhuHTpUvLy8qLGjRvT2rVrydzcnAICAmR95sOHD6lr165Uvnx5qlChAtna2tKjR4+YZBT3jMt97nk5B48cOUJ9+/alr7/+mqZPn04PHjyQNR4iIjMzM7WxEckz6hs3bkxt2rSh1atXU3p6uuzxvK2LiP43R1nASxeVhZiYGEnv47VReJ/46aefynzP+9IfRNI3d7zmEE9ZSqWS1qxZQ05OTuTk5ET//e9/1QJgUuHl5UVbtmwhY2NjSkhIIE9PTxo7diyznPnz51NAQAA9efJEXBszMzOZ5RCpgghfffUV1a9fn86dOydLBpFmukhXV5fq1KlDderUIS0tLapYsSJVrFiRtLS0qE6dOrLGI8dOKA5+fn70/Plz2rp1K9WqVYv09PRkBRgMDQ0pKipKfH3hwgVZz9rIkSOpffv2tHjxYlqxYoV4sILX95IC1kDj69evNZ7XpUHqvJw6dSqdOHFCLetPDoRNfEFBAYWEhFBAQACX75WXl/fBM2t79+5Nt27dEu/pxo0bycHBgVnO3bt3Sz2kwtramtzc3GjFihW0atUq8ZCDuLg4CggIoICAALp+/bosGUT87augoCCaO3cuEcnLiC0LUtfqzxVfOJo+EdSqVQvp6eno1asX7OzsoKurK6srgUAEV7hzSWxsLGJjY5kIpg0NDdGzZ0/cuHEDv/32G3JycmTzovAih+QFgTC7evXquHv3LvT09PD8+XNmOU2bNsWLFy/g6uqKdu3aQUdHB+bm5sxy6tWrh507d4qk7Tt27GAmBly4cKHIz1OjRg3xvI6ODnN7YkDF0VSYw4CVz0CAu7s76tevL5LorVu3Du7u7ti3bx+THF7PB29unZJAEuu3fX19sX37dmRmZuLvv//GpEmTinAbScXXX3+NEydO4OXLlwAgq+OktrY24uPj0bJlSwBAfHy8bILIypUrA1Bx47x8+RLVq1fHs2fPmOX06NEDPXr0QEpKCgIDA9G2bVtYW1tjwoQJzNwPFStWBBGhadOm8Pf3R8OGDZGdnc08pqSkJJw8eRLBwcH49ddf0b17dwwfPlzsGCkVgi6qXbs2oqOj0aBBA1n3iJcuio6OxtSpU3Hnzh21DjQC54vUDokHDhyAtrY25s6di23btiE9PV22DnlfOHr0KBYvXlzqe96X/gBUne58fHzKfB+vOcRTlpaWFry9veHt7S1rHAKWL18OX19fpKamwtraGv369cOiRYuY5UyfPh2AegMBOZw4GRkZCAkJQbt27XDnzh0cP34cVlZWzOMBNNNFwm/y888/Q19fHyNGjACgsvvk8MYAQLNmzZCVlaURtxcAkYdv8ODB6NixIzIzM2FoaMgshxcHTW5uLpo2baoxxx+v7yUFUscXFRUFDw+PIqTgrPO6LEi1Z+bPn6/xZymVStjZ2YkNjYYMGaKxzMKyWUilCyMjIwNBQUFISkpSWxtZu0T6+/vDxcUFN2/eRIMGDaCjo4Pw8HAmGUqlEiNGjMCxY8eYrisO6enp2Lx5s8ZyANW+kcczwcu+ErgGjx49igkTJmg8rpIgda3+bPFh/VxfIBWFPfhbtmzh5sGXi1evXtFff/1Fd+7cISKiBw8e0KFDh2TJ4lWqxgvvIjJ15swZ2r9/vywugBs3blDTpk1FLqwWLVrQ7du3ZY1j9OjRsq57Vygu60hOJhKv54NX7XdZ+FCp748ePaLIyEg6deqUeLDg8OHDVLt2bZHLQFdXl44cOSJrLLyzWmJiYmj48OH0zTff0Lhx48jExIR+/PFHJhnHjx+njIwMSkxMJFtbW2rTpg0dPXpU9piIVDwio0ePlsVFsXz5cnr+/DkdOXKEqlWrRhUrVqQlS5ZoNB5NdJGhoSEFBgZSbGwsXb9+XTzk4NGjRxQREUFEKo4eTaPc7xpSsgjel/6QOh4ivnOIl6xHjx7RTz/9RP379ycHBwfxYAUvzkFeaNKkCS1atIiIVBmaAwcOlK3TeOginmX3P/zwAzVp0oS8vb1p4sSJ4iEHSqWSHj58qFE5Hy8OGk1ROFOouONdQKr9wLNsVpPxmJiYkKmpaYkHK6ysrGRlQL6Nfv36iVn433//PTVq1IjGjBkjS5aNjQ05OztrlPlTUFBAjx49IqVSSfHx8fTPP//ILsHidY9cXFw0yhIXIPCDFT5MTU1pzJgxahy0rNDEvpo7dy7VrFmTLCwsxHv/ISkFPlcoiL5Qo/9fQ2hoqBgN6N69u5gp86FgZmaG6OhoGBkZIS4uDkSEdu3aSWor/a5x//79dxqZkgqlUolbt24BUEUW5WaRjBkzBmvWrCnzXFl4/Pgx/P39kZCQoBa9CQsLY5JjY2OD0NBQ1KlTB4AqEuvi4sIlEvMxQ5jzJaGsLDM5Xazmz5+PJUuWoHHjxmrddVifs2fPnuHChQsAAEtLS+jq6jKPBVDNaW1tbRCRWlYLa8Rc6PCTlZWF8ePHw9XVFZUrV4ZSqYS+vj731uxS8fTpU2zZsgUbN24EEcHDwwN+fn6y5eXl5eH169eoXr06x1GywcTEBDExMRrL2b17N3x9faFQKHD37l3ExsZiypQpOHjwIIdRvhuU9cy+b8gZD885pIksKysrmJubF8lCYc1OKO4eyLkv9+/fR926dVGhQgVERkbi6tWrGDZsGPN3O3PmDDp27Kh2bvXq1fjxxx+Z5PBCy5Yt8ddff6FZs2YAVG24+/XrJ6uLVOGOpYUhpWtpYQQHB2P8+PEoX7682HVQoVDg6dOnTHK++uorZGZmill2eXl5Yra2QqFgyog/dOhQEVtGaqa30Ga9uK2UnKw4KTA1NcXVq1fLfN/btjUAtG3bFpcuXeI6nrKeubI6L7J2f/Px8UFCQgJcXV3VuumxdofdtGmT+P9y5cpBX19fLUuOBa1atcI///wj61oBRAQjIyNcv35dIzkAv3vUvXt3XL58GVZWVmodB1k7KM+YMQMPHz4Usys3btyImjVrgohw//597Ny5k0keL/sqIyMDOjo60NLSQnZ2NjIzM/HNN98wyykNH5vt8L7xpXTuI8d3331Xaposa5taPz8/nDp1Cq6urgCAZcuW4fLly/jtt980Gqcm4FWqpilSUlKKPa+jo4OUlBR8++23kuQIhkdJkGN4aGtro0mTJnjz5o1Y+iQnhT0qKqrIuXPnzjHLcXR0hLm5Ofr16yfb6QWojEUjIyOxNe3BgwfRsWNH0cgry6HC6/no2rVrqXJOnDghSY5UlOXfL1zeyAtC2UTt2rVlXa9UKmFkZIT4+Hj06dNH4/Foa2sjJycHMTEx+O6779C/f39ZZUZbt27F7NmzYWtrW0T+ypUrJcmYM2dOqX//9ddfmcbk4OCACxcuwMnJCRs2bICFhQXT9adPny717506dZIkh7cusra2xuXLl9GmTRum697GwoULER0dLf5mrVu3xr179zSS+SHxvvWHFPCaQ7xlAcDLly+xatUqpmsKIzc3F69fv4ZSqcS///4r6tPMzExxfWRB3759ce7cOTx8+BDOzs7o0KEDTp06hV27djHJ6dixo6jTAJVjltXJxFMXLVq0CNbW1mJJ67Vr15hLeQSU5VBasWKFpPKQuXPn4tKlS6LzSy54OLwBVanbjRs3YGpqqhaAkQrerdKlwNLSUtL7eJbNloay7BlWR1JZuHbtGgBg7dq14jkW6g8Bw4YNA/C/8cul/wCAJk2aICMjAzVr1pQtQ6FQoH79+nj+/LnsAJ4AXvfI1dVV3C9qgr///lsMUAJA+/btxYQCgYpBKjS1rxISEmBgYCDeo7fB29H0fx1fHE0fOYTa3NDQUNy9exejRo0CoFIeDRs2ZJYXFhaG2NhYkR9l5MiRaN269Qd1NHXq1AkvXrzA2LFjYW5ujgoVKsDZ2fm9j8Pc3FxcaF68eKEWKatdu7bkiJtg+Pr7++PVq1ciD0VgYKB431nAo85+x44dCA0NRXJyMhwdHcXzmZmZatEOqdB0oyDAyMgIRkZG4uvRo0czXc/r+RAiIREREYiOjsbw4cOhUCiwceNGmJqaMo1JChYsWFDq31mjxFJQt25d2U4mQOW4qVOnDnJycrjwzpw7dw5OTk6oW7cuFAoFnjx5gj179jBzmuzfv1/8f2ZmJu7fvy9mIDo4OEiS8e+//wIAHjx4gOPHj+P777+HQqFAWFgYbGxsmMYDAC4uLti1a5daBJAFvr6+AFTPeExMDBo3bgyFQoGkpCSYmJhIjo7x0kWmpqZQKBTIy8vD2rVroa+vr/bdWKN12traReZihQoVmGS8b5S2mXrf+qOs8QD85hBvWYBqrRWMfTkQOAcVCkURzkFhrKyoVKkSDhw4gFGjRmH69OmS+cYKQ9Bpenp6ACBLp/HURd9//z1u3LghBpisrKw03sCWBKk8JLq6uho7mQCUub7b2Njg+PHjZcqJjo7GP//8o1HATMD9+/dx5swZACrnCuuG9dSpU+jcuXOJmeGCk+C///2vJHnOzs548eIFpk6dis6dOyMvLw/z5s1jGpMUBAcHS3rfq1evEBAQgJiYGDU+VtbsmIiICKb3l4THjx9jxIgRojwbGxusXbuWmQMVAKpUqQIzMzPY29urrY2s2efVqlWDiYkJevXqpWabs8rhdY8EZ5ymSEtLU7Mdc3JykJGRAQDMdpKm9tXEiRMRHh6Ovn37FvmbQqFgTuAoC//XC8e+lM59Ing73ZWIYGFhwZwCa2FhgaioKDFlOT8/H9bW1mqe5g+J4krVkpOT8d133723MZREoLlw4UImOebm5rhy5UqZ58pCu3btsHLlSowePRqnT5/GypUrUalSJSaDOjY2FlevXsXMmTPVIqY6OjqwsbFhzo7y8PDA1KlTZW8UpEJqlJTX82FpaYmzZ8+iXDmVDz43NxedOnUqNhOsOPDObLh//z68vb3x4MEDxMTEICYmBhEREZg4cSKTHEDlvMrMzMTgwYPVFmhjY2PJMkaMGIHo6GgMHDhQzQgqTKIrFZaWlli2bJlI2H3u3DlMmjRJ8r0WYG9vj9DQUJQrV07UG0OHDi0zM6A49OjRA8HBwfj6668BqAxRd3d3HDlyRNL1L1++RNWqVZGVlVXs31mfs+HDh8PFxUUkuTx27BhCQ0Oxbt06Jjma6iLepQ82NjbYtm0bevbsiejoaBw/fhwLFiyQtDH8UHj27JlY4lsSNNUfhTFv3jyRpLq4c7GxsZKcIbzmEE9ZcXFx6NatGwwMDNR0Eat+9Pb2lrzpLg2tWrVCdHQ0XF1dxSYCrVu3RmxsLJMcXjoN0FwXCbhy5Qri4+Ph5uaGjIwMvHr1StZGuixILedauHAhKleuXGQd0pRkXO547O3t8eeff2ocPNm3bx9GjBiBDh06QKFQIDIyEuvXr5cc7AAALy8vrF27Fl27di3yN4VCoVFmpCalrmU1gZAKV1dX6Ojo4ODBg/D19UVwcDA6deqE33//nUlOcRmWNWvWRNOmTZmcDw4ODrCyssKYMWMAqAIwkZGRasErqeBVWspLTn5+PlasWIGkpCSsWbMGSUlJuHfvHrp16ybp+mXLlsHX17fEElJWx9fMmTPx119/YeDAgQCAPXv2oG/fvpg8eTKGDh0qydnI2756X5C6Vn+2eJ+EUF8gHwYGBmLbdiKif//9lwwMDJjljBs3jmxtbWnz5s20efNm6tGjB/n4+NC+ffto3759PIfMDe+bOJkXgaaBgQE9efJEfP3kyRNZvxnP9tRPnz6Vdd3buHbtGunq6pKVlZVIDN21a1cusgtD6m/P6/kwMDBQI1/My8tjkhMeHk7h4eHk6+tLXbt2pS1btlBISAjZ2NiQn58f83h69uwptu8WxiO3XXqjRo2KHN999x2TjF69epG7u7va0bt3b1njKa6NbHHPXlkQns0dO3bQ+PHjKTc3V/Y9atWqlaRzJUGYrwqFgrS0tIr8ywojI6Mi5+S03+Wli9avXy/pXFm4ePEimZqaUo0aNcja2pq+/vprunr1KrMcHhB+m5IOFmiqPwqjON0nZy3kNYd4yjI2NqYZM2bQvn37RJ0ZHh4ua0w8wIsUlpdOI9JcFxERrV69moyNjalx48ZERJSYmEhdunSRNZ6yIHVuKhSKIocc3chrPNevXycrKyuaMmUKzZ49WzzkfF5CQoL4OiEhgavtKocUesSIEbR9+3Y13S8HvJpACOuyoEeysrKoY8eOzHJat25NWlpapK+vTwYGBqSlpUUtWrSgr7/+mk6cOMEkR8q5jwn+/v6S3jdq1Cjy9PQUm+ukp6eTubm55M8JDAwkIqJZs2YVe8hBeHg4TZo0iSZNmiRL3/O2r4j4NCa4cuUK2dnZkYGBgRrZ+Reo8KV07hPB4MGDYWlpKRJ379q1S1bdrEAIWLhOPzY2FrGxsbLqd98H6D0n3eXm5uLWrVtqBJpv3rxhluPr64vWrVujV69eAIDDhw9j1qxZzHKE6DiPOvs6depg586dRVKXWaMTrq6u8Pb2Rps2bbiknJcEqb89r+fD1tYW9vb2Yqv1kJAQppapAtfU3Llz1TIbBg4cyMxjAqgID11dXbFs2TIAqrkgyGQFD1Lsx48f48CBA2rnzMzMZMmqVq0ajh07JvL0HD9+HFWrVmWWk5eXB0AV5bS3t0f58uVl36P69etj5syZ8PT0BACsX78e9evXl3y9UELEi7dDW1sbERERYoT71KlTYjYqC3jpolWrVmH48OFq51avXl3kXFlo27YtIiIicO7cORAR2rdvrxG3hSbgWeqsqf4AgCNHjuDw4cN4+PChWjQ5MzOTSY4AXnOItyw5GYdv4/Dhw5gwYQLu3LkDpVIJIpJFwDx9+nSMHTsWOjo6UCgU0NHRwe7du5nHw0unAZrrIgD4448/EBUVhfbt2wNQ8ci8C44eFnwITqPSMGXKFFSoUAGvX78W1xI5EJpPCNDX15f9Xd/OZiQiDB06FFu3bmWS07lzZxw8eBB+fn6oVasWbG1tYWtrK64DUqGtrS3SEmgCQZ+WK1cOL1++RPXq1WXNR3Nzc/j7+6NLly4AVHpo06ZNGDNmDEaPHo3Lly9LkkNESE1NFUtdU1NTZe83eGaflwapJapRUVGIiYkRS7dr1qzJNL+F35sXNxugytJs3rw5mjRpInkchcHbvuLVmGDYsGEYO3YsrKys3ul+6JPFh/NxfQErCnuDDx48+KGH897wvjOa9u3bR7Vr16Zu3bpRt27dSFdXl8LCwmTJiouLo5UrV9LKlStltwHn2Z563Lhx1KdPH6pXrx5NmjSJGjRoQMOHD2eWIzcizgqW357H85GXl0erVq0iR0dHcnR0pDVr1shqA88rs6Fdu3ZUUFAgZu2kpaXJjrgVjtiwRm/evHlDmZmZZGxsTFlZWWLr5pSUFGratKms8Vy6dIm+/fZbMfrTsGFDunLlCrOcQYMGkb29PTVs2JBevnxJL1++lN1O9vHjxzRw4ECqVasW1apViwYNGkSPHz9mluPt7S3pXFmIjIykBg0aUOPGjalx48b07bff0vnz55nlEGmmiy5cuED+/v5Uv359WrFihXjMmTOHOcsiPz+fWrRowXTN+4CZmZmkc6WBh/44efIkzZo1i/T09NQiyMuXL6fk5GQmWUR85xAvWd7e3lwy2AwMDOjw4cOUmZlJ2dnZ4sGKsLAwsRX9kiVLyMnJieLi4pjlFNZpjRo1kq3TiPjoIgsLCyJSz8h+VxkbLDo3JSWFtm7dSlu3buXSOr04SLUd5K5fb8PW1pbWrl1LSqWSlEolrVu3jmxtbWXJ6tGjB4WEhIivPT09ycPDQ/bYCgoKaPPmzdSoUSNZmR9jxoyhS5cuyf58AXZ2dpSWlkbTpk0ja2tr6tu3r6x7VJz9KZxjsU03b95Menp65OHhQR4eHlSvXj21+84CntnnpUHqc9auXTu19+fn57+T8Uh9ziIiIqhevXrUoEEDIlJlNQ8ZMkTWZ/Kyrxo3bkw3b96UNYbC+Niz4D40vjia/o/h1KlTxR4fM963o4lIVVoSFhZGYWFh9OzZs/f++QKUSiVFRUWJr3NzcykrK0u2PENDQ1IqleJi+PjxY+rRowezHF4bhbLwIX57HvD29i5SojpmzBhmOUuXLiUvLy9q3LgxrV27lszNzSkgIEDWmHR1dalOnTqkq6tL1apVIy0tLapTp46ka2fNmqWWpiwcNWrUoDlz5sgaD5FqPsfFxVFcXBzl5ubKkvHq1Sv666+/6M6dO0RE9ODBAzp06JD499evX8sen1wUN2/lGiO5ubl07do1unbtmux7pCn27t1L7u7uVKtWLbWyyfHjx8vagHTq1Ilevnz5DkYqH7zKC3khJiaGmyyec4iHLENDQypfvjy1aNGCTE1NxYMVLKUgpUEo5YmJiaHWrVtTYGAgdejQQfL1hR33t2/fpri4OLp+/TolJCTIKsXghd69e9OtW7fEe7tx40ZycHB4J58ldb7u3buXateuTX379qV+/fpRnTp1ZAfySsP3338v6X0ODg6ik1ETJCYmUrt27ah8+fJUoUIFsrS0pMTERFmyMjMzydzcnE6cOEETJ06kQYMGkVKpZJazdu1aGjRoEBkYGJCjoyOtXr2abt++Lfl6ExMTMjU15fa8CsG3goIC2rJlCwUEBMi69yYmJmr7llOnTokOFdZ19vr16xQQEEABAQGyg8FE/9NFhR1BcgNepUHqfffy8hIdXwkJCeTp6Uljx47lPh4Wx1diYqLa+1u2bCnrM3nZV4IjXlPwcsR+rvhCBv6J4O7du1i8eDGSkpLUyPhYyQHbtm0r/v/169e4desWDA0NmbvGvE9IJXX82MCLQFEOKWlJEEizTUxMcOnSJZQvXx5GRkZiSaVUGBkZ4datWxp3nyoLUn97Xs9HRkYGgoKCishhbQmdn5+PoKAg8fNtbW3h5eUlq6Rr+/bt2Lt3L4gI/fr1w+DBg5llFIc///wTsbGxJZJPFgde5LsCCgoKkJqaqnavv/32W27yAVVpH8u8vHDhQpHfXyiFKgtCd8eTJ0+qEbpmZmbizZs3OHv2rPSB/3/wuEe8dNGhQ4fQs2dPpmuKA09SeV4ICgrCrFmzipQXenl5SZbBS38Aqjb2kyZNQo0aNdCnTx9cuHABQUFBcHJyYpbF8znjIaskcnlWUvlZs2bBxMQE/fr1Y7rubQg6YsmSJahatSrGjBnDpDfq1Kmj1rFW6KCYm5vL1LH2bWiiiwAgMTERLi4u+Oeff1C7dm3o6OggPDxcVnMVXjrEzMwMO3fuFMvMEhMT8cMPPzDbDhYWFrh48WKZ58rCoEGDcOXKFfTo0UOjbmECsrOzAUBWN9/CePDgATp16gQjIyP8+eefskpyKlSoAAsLC/zyyy+wsbFhLgXm3QSCF86dOwdnZ2eUL18eRIT8/HyEhobC2NgYe/bskdwpLTc3V3xW79y5g/j4ePTs2VPWvba0tMT58+dhZmaGq1evIj09HV27dkVMTAyzrNIgVS9lZ2fD19dXzXb8/fffZZfyajoeYe9R2KZn3dvxsq8EMvHVq1dr1JigcDfe97Ef+lTxhaPpE8EPP/wAGxsbjB07VqMa0Le7cF28eFFya9IPBUdHx/f6ebx4H3jV7RoYGCAxMVGt/l8uqlevjpycHHTo0AGurq7Q09OT1W1l1apVGo9FCqTOTV7Px4ABA1CnTh2Nf7Ny5crhxx9/FLuZlNaJriy4uLjAxcVF9vUlwdHREQsWLGByNPF0MvGqjy8LLLEUb29vHDlyBCYmJuLvr1AoJG/umjdvjr59+yI6Olqtda7Q3ZEVHwuHgNB2Oy8vr9jW26zcfgUFBTAxMUFCQoJ4TpNnhAdGjRoFa2trsS30pEmT0KpVKyYZvPQHoOpiNWfOHBw9ehTlypVDZGQknJ2dmR1NPJ8zXrKEDeqjR48AQOysxooVK1YgMzMTlStXRsWKFcW1Oi0tjUmOUqnEhQsXsGfPHmzcuBEAmPhMBJ6ZkjrWyoGmuoiIULVqVVy4cAG3bt0CEaFZs2ay5yUve4YXl1FhZ5fw+t9//2WW07JlS7Rs2ZL5OgEJCQkwMDDAtWvXiv07S1dXYeMq4PXr10hISBADxKwb1xcvXiAiIgJ///03ZsyYgZo1a8LW1hbTpk2TdL3wnG7YsKEID9+GDRuYHU2nT5+Gn58fEhMT1X6/krqIlYT27dsjKSkJN2/eBAA0a9ZMdBhJdTIBgLW1NU6cOIHc3Fx07NgRjRo1Qnh4OAIDA5nGA6h4OEeNGoWsrCysW7cOgYGBIr8aT0i1Z6pVq4agoCAEBQVxH4McVKpUCdnZ2eL8jouLY3Z88rLO/eoLAAAgAElEQVSvatasCYVCId7LwlyILHs9f39/yZ/5fxlfMpo+ERgbG5e4kGmKD50xlJOTg02bNiEhIUFt8Vm5cuUHGU/Tpk0REBBQxKBijQSYmJhwiWZ069YNFy9eRPv27dWiZFLagb6NJ0+e4KuvvoJSqcTy5cuRnp4OHx8fNGjQgFlWXl4eUlJSZBH7ubi4YPv27UUMKwGsBhWv56NVq1b4559/NJbz6NEjeHp6iptWGxsbrF27VnJbaQ8Pj1I33nIyJAobc8LGavz48bh9+zazLB5o0qQJDh48KJLuvyuwZCYYGBggLi6OqUVycXj27Bnq1KkjGjJynSi87pGmuuhdtt3+nMBLfwD/W5enT5+O5s2bw9XVlTk7D+D7nPGSdePGDQwYMEB0NNWvXx+7du1C8+bNmeTcu3ev2PMNGzZkkrN//37MmDEDtra2WLp0KW7duoWpU6diz549THKKe87k2lea6iIigpGREa5fvy7r+rfBy57p3r07Bg0aJDouNm7ciNDQUBw9elTS9YsXL8aiRYuQnZ2N6tWri+dfvXqFoUOHvveNdZ8+fUrMElMoFEwZX+8igygvLw9nz57FsWPHsG3bNmRlZeHFixdMMorTO+bm5rhy5QqTnGbNmmH+/PmwsLBQs62/+eYbJjmAKkh+7NgxACqS6TZt2jDLEJ7NzZs34+bNm1iwYIGsDH8B7yr7vDBiY2PRunXrMt8XFBQEZ2dn1KhRA2PHjkVUVBSWL18uqylNaZCq3/7++2/MmjULSUlJ6N69uzgfu3XrxvyZvOwrXijJEcvaJOVzxZeMpk8EhoaGSElJ0bispPBmXNhsatJpgwccHR1Rvnx5tG3b9qNg7NfR0YGdnZ3GcqytrXH58mVZC2BhDBs2jClKUxrq1q0r/r+4qJabmxu2bNlSppyTJ09i8ODBKFeuHFJSUnDp0iWsWLECISEhksbh5+cHgF9EgNfz0aRJE2RkZGjcAWvUqFHo0KEDtm3bBkDVwWrkyJHYv3+/pOuFORMXF4fTp09j8ODBUCgU2L59Ozp27ChrTIWjONra2jAwMPhgzlwA0NXVfedOJlbUq1cPFStW1FhOfn4+evXqJdvRKIDXPdJUF61duxYAxO+jKWbOnInx48ejdu3aAIDnz59j9erVZXa4eZd4+vQpZs6cidjYWLWOnCyOHV76A1AFNhYvXozQ0FBERkaCiJCbm8ssh+dzxkvWmDFjMG3aNHEjFhoaCm9vb+b5xepQKgkODg5wcHAQXzdr1ozZyQTw61gLaK6LFAoF6tevj+fPn0NXV1e2HAG87JnAwEAMGTIEP/74IwCVE0Oq3QAAo0ePxqBBg+Dt7a2WeaKjo4OvvvqKeTwldT/89ddfJV0fHh4OgE9XV96laHZ2drhy5QpMTExga2uLnTt3Mv1+Fy9exPnz5/Hs2TM1W0EoVWKFjo4OBgwYwHzd2/jjjz8wb948ODo6QqFQwMnJCTNmzGDOIBL0qWDPApC9Bzl8+HCR7PPDhw/D3t6eSU5ZJapSnEyAqixs1KhRiIyMRFxcHObPnw8/Pz/m0tKyILXqoEePHjAwMMDhw4dBRJg9e7bs7nO87CsASElJwenTp6FQKNCpUydZQXde3Xg/V3zJaPpE0L17d1y+fBlWVlZqES7WrJbCUZdy5crBwMAAc+fOhbm5ObexsqJly5aIj4//YJ//NnjxPvDiMSpusZKzgEmB1Ii5paUltm7digEDBojRDDnR/OTk5CKRwPPnz8PKyopJDq/nw9nZGRcvXoS9vb1GfA3FRX/lRIQ7deqE8PBwsWY8KysLffr0wenTp5nkfEzgVR8vFSwZBZMnT8adO3cwaNAgtTGxloY5ODjAyspKLJ0MDAxEZGSkZEejgIULF3K5Rzw51fLy8pCcnKzmjGEpDwGKfxbkZOvwhIODAzp06ID169dj2bJlCAoKgqmpKebOnStZBi/9Aai4a1atWoVOnTrB0dERiYmJ2L17N3755RcmObzmEE9ZmupH3hmxgGpTHRMTozavWTnDwsLCMHz4cHEzeO3aNWzYsEHNiSUVPHTRgAEDEBUVhV69eqllQ7PMx3fFQ8KDyygnJ0ecMyYmJrJoACZPniz+//Xr1zh48CCsrKyYnF8A4OvrixEjRmhUhufr64tly5ahf//+xc5rVnvm6NGj6NixY4lZccXZX4Wxb98+7N27F2FhYWrzTkdHB25ubsxOx0WLFuGbb77BoEGDxFI3OTA2Nsbx48dRp04dAKoMFxsbG+as9rFjx+LEiRNQKpW4fv06srOzRVuSFcWtX3LWNCMjo2JLVFnLuIXPnjt3Lr7++muMGDFC1nh4cbPNmzcP06dPL/OcFPCyr7Zt24Zx48aJWV5nz55FQEAAnJ2dJV0vOGKXLl2qpkcyMzOxY8cObtmknzq+ZDR9InB1dYWrq6vGcnhEXXijefPm3KJuPMCL94EXj9HUqVOLOJWKO/c+oVQqi0Qj5BgOjo6OiIiIEDMArl69Cjc3NyQmJjLJ4fV8tGjRAi1atNBYDhEhNTUVenp6AIDU1FQmriABz549U9vE6ejoiHwgnyqKq48XXsvhQisLlpaWkt8rGJiFuagUCgWzo+n+/ftqRs8vv/wCExMTJhnA/7IONb1HvHRReHg4vLy8kJ6ejqpVqyI9PR0NGzZkXleK42SRk63DE/fv38fPP/+MkJAQODg4wM7ODp07d2ZyNPHSH4CKu2bJkiVISUkRX7M6mQB+c4inLG1tbcTHx4ub8vj4eKZMAt4ZsQsWLMDu3buRkpKCzp074+jRo7CxsWF2NH3//fe4ceMGoqKiAABWVlay7RoeusjIyAhGRkayPl8Abx6S/fv3o3PnztDR0cHSpUsRFRWFWbNmwdDQkEnO+fPn4ejoKK6xT548wZ49e5iDVEuWLFF7PWvWLLi7uzPJAFT8l3369IGuri48PDwwePBg1KhRg0lGly5dAEDjIKeA7t27l/p3JyenUh0Pffv2Rd++fbk1gWjRogVcXV3F+6uJLhKcTG//nwUB/4+9M4+rMf3//+sUI0vZYhhR2RqUNmmxJK32bGMrhIRJGNkaxlJhGIPBjOVDUSjZGWthEIVU+CB9kJ1IUqT1/fuj37m/HW33fZ+r06np+Xicx4z7nPt9X51z3dd9Xe/rul6vDRsQHx+P1q1bo2bNmsjLy+NW7/LlwYMHuH//PtLS0mT0C9PS0vD582fBZVJVVYWHh4fg875GRUUFoaGhCA0Nxd9//w1A3DOWlTbbwYMHiySVijvGB1b9q2XLluHGjRtcsjUpKQlOTk68E02vXr1CXFwcPn/+LDOZqaGhofTaxwql/I3tqlE2rl69Sr6+vuTn50dRUVEVXRy6e/cutW3blkaNGkVubm7cq6JISkoq9qVoEhIS6MiRI9S6dWs6cuQI99q1axfp6emVyzX5Wqd2796d0tPTuc/funWLLC0tBV9v//791LNnT8rKyqK7d+9SmzZtqoRN6K5du6hZs2ZcXW7evDkFBwcLjjNixAgaN24cXbx4kS5evEhubm40YsSIcihx5ePChQtERDL3RuFXRdK5c2d69eoV9+9Xr15R586dK7BEbDAyMqKkpCTOojgoKIi8vb0Fxxk2bBj9+uuvlJubSzk5ObRy5UoaOnQo6+IKwszMjIiIunTpQu/evaO8vDxq27ZthZXn/Pnz1Lx5c2rZsiUREV27do3GjBlTYeVhyalTp6hx48ZkY2NDNjY2pKmpSadPn2Z+HRcXF16f69SpE2VmZnIW2ffv36chQ4YwL4+ysW7dOt6f3b59O69jZWFgYEBERHFxcWRoaEibN2+m7t27C45jbm5Oly9f5v4dGRlJ5ubmguMUh1jbdSKic+fO0bhx46hJkyY0evRoUTGys7NFX18IZVnTs37G6urqUkREBKWlpVFGRgb3EsqQIUPIx8eHnjx5Qk+ePKGFCxeKvl/3799P/v7+RET0/PlzunXrlqDzAwMDqVevXlSvXj3q1asX9xo4cCAdP35ccHmmTZvGpA989epVGjRoEHePJyQk0PTp0wXHkbaJYjl16hTNnDmTmjZtSrNmzeJeEyZM4D3e+BpW/aviri+mTCdOnBB8zr+J6hVNlYh9+/YVWdotdEn+b7/9hg0bNnBObiNGjICXl5eM6r6icXd3h6WlJbp06aIUGk2sdB8yMzOxYcOGIr8Z3+XPV69eRWBgIJKTk7F27VruuIaGBtasWcOkjGJZtGgRHBwc8OLFC7i4uHDCfkIZOnQonj59iqFDh+LBgwfYuXOnaA0IFvcHwGYLhaurK4yNjXHhwgUABUvihS59BoD//Oc/WLZsGWbOnAkAsLOzw6JFiwTHqYoEBwfD2tpa5t6QImYVkhQWW8O8vb1hbGzMzQKfOnWqyMy5IpG3LZKioqICbW1tbgm9i4tLsd9/Waxfvx4uLi5YuHAhp43ARxuuPGnfvj1SUlLg4uICc3NzaGhoiNpSzqL9AApmaS9dusRpmpiZmVWoaQdLHB0dce/ePURHRwMoWHVYHiua+W7lVlNTg5qaGvLz8zl3NrFucSxh0RaVxs6dOzFjxgxen2WlQ1KjRsGw48yZM5g8eTI8PDxECXhnZmaiW7du3L+trKxkvie+FNYeysvLw7Vr17hVUmKwsbFBvXr1kJ+fj9DQUOzevVtwjObNm6NLly6wtbWFra0tTExMRJenNMoSUWb9jG3atKko8eev2bx5M6ZPn859L/b29qIccX/55Rdcv34dDx8+hI+PD1RUVODh4YErV67wjiHVUN2+fTvnNimGwltUt23bJvcWVQsLCxw+fJj7d/v27UVpcsqrzaampoYGDRpARUVFZoVfy5YtRfdlWfWv+vXrhyVLlmDSpEkgIgQEBGDAgAGcvENZW8JZu/FWVao1mioJXl5eePz4MWJiYjBq1CiEhYXB3t4e27dvFxSnffv2uHr1KifC+v79e1hYWFSY8xTA1qmHBSxEYYGCQZiGhgZOnDiB2bNnIzAwED179hQ8MCvrARYZGSnT4ZIHMzMzXL9+nddnHz9+zAn7OTo6ChL2+7pR9vX1hYWFBbfUW2gDzer+KGkLxaFDhwTFAdjoR5TF+vXreQ8U/k3k5eWJSlqz2hoGAHfu3OESjTY2NqISjYmJifDy8irSFgndxsuqLbKwsEBUVBT69OmDyZMnQ0dHB0OHDhWs1yDl06dPAIo6erJs08QQGRmJ1NRUODk5cQNjPrBsP6RtcWGNMTEOZqzqEKtYeXl5MDAwUIguI19Nkh49euDcuXOYOHEimjRpAi0tLezYsUO0+xQLWLZFJcGnPrHWITE0NMTWrVsxY8YMBAQEoEOHDqKcvrp164alS5fCzs4OABAREYFffvkFkZGRguK4ublx/1+jRg20bdsWkydPFiwsnpycjKCgIAQEBICI4ObmBhcXF1FJq+zsbM4pLjw8HE+ePIG1tTX27dsnOFZpKFoXb/ny5dDQ0MAPP/xQrrqMfDE0NMTNmzfRpUsX7j6Qx8H41atXePz4sYyWEV+XN9aOgyU5F/N1LGatzcbXLY8vLPpXKioqJb7HZ0tntRsvTypyOVU1/NHX16e8vDxueeCrV6/IwcFBcBxTU1NexxTJqFGj6Pnz5xVahsL079+fVq5cSe3ataOjR49Sv379aOHChYLj6OvrE9H/LRX/+PEj9ejRg2lZifgt9UxLSyv1JRRfX19ex0qi8BLjr182NjaCy8Pq/mC1hSIyMpKaNWtGRkZGZGRkRM2bN6crV64IjlMWYpceVyW+rnf5+fmityyw2hrGCmtrawoJCaGOHTvSrVu3yN3dnVvmLwRWbdGePXvo/fv3dOPGDWrbti1pamrS7t27Bccpi4qq10+ePKGgoCAKDg6mJ0+eCD6f5RYsVtuTWdUhlrF69uxJnz59ElUGIfCtR7dv36aMjAxKTk6mSZMm0dChQyk2NracS1c6imiL+Hw/hw8fpvHjx1OjRo1o/Pjx3MvLy0vUFp9jx46RoaEhzZ49m4jE3yPXr1+nVq1aka6uLunq6pK2tjbFxMQIjsOKxo0bk4eHB129epVJvPT0dDp69Ch5eXlR69atqVu3bkziFqasrXOFyc7OpoSEBIqPj+deQpFIJNxLRUWF+68YoqKiaPfu3bRz507uJRTpVsvC34P0WSkUPz8/ql+/PhkbG1OXLl2oS5cu3HZsIbDaorpx40bu9dtvv5GlpSX9+OOPvM+/cOFCqS8xREdH05YtW2j9+vXcq5qqT3WiqZLQpUsXIirYLyvdvy2mQZwzZ46M5suECRNo3rx5oh8cLLCzs6MGDRpQnz59aPDgwdyropAOEqTfb1ZWFllYWAiOI33IGBsbc/vQv//+e0al/D/4dBYKP9hZPOhZ7W1mBav7Q5p0NTAwoPz8fC6mUMpTP6IwQjqKVRUHBwcZ/atJkyaJ1ngzMTEhItm6Iz0mhH/++YfMzMyoYcOGpK6uTvXq1SN1dXXBcaT3lLQ8+fn5ojqv8rZFy5cvJyKiiIgIwdcWQ0XU6927d1OjRo3I2dmZnJ2dSVNTk/bu3SsoBqv2g4jo9OnTZGlpSU2bNqUxY8bQt99+K+r7Z1WHWMaaMGECGRkZkb+/f7kOOvg8k3Jzc2nu3LnMry0vrNqi0hDyzGahQ5Kbm8v0d87Ozqbbt2/T7du3Resabd68mT58+EBERD/++COZmprSP//8IzjO58+fS31fiB6WlZUV6evrk5eXFx09epQ+fvwouDxEVGyfvvCxZcuW8Ypz7NgxatasGdWqVYsaNWpEEomEdHR0RJWJBVOmTCFdXV0aPHgwDRs2jIYNG0bDhw8XHOeHH36gixcvkrGxMWVnZ9OSJUt467p9TevWrendu3eizi1Mcfcki/v+06dPZGtrK/g8Vokvf39/MjY2psaNG9OQIUNIXV2dnJ2dBcchYte/YgmLRGxVpVqjqZKgrq6Oz58/o3v37txyXDFbccLCwgAUXaYZGhoKiUQieguEPLByDGOF1D1NTU0NKSkpaNiwId69eyc4TqNGjZCamoq+ffvC0dERmpqa0NLSYl3cMvfZA8W7PInh9OnTOHXqFF68eCGj65WWliYoTmJiItq1a1fiEmWhOhSs7o/atWsjJycHRkZG8Pb2hpaWlihHFFb6EWXB57ev6oSFhaF379747rvvcOzYMaSnp4vSCwOAmjVrAgC0tLRw6NAh6OjoIDU1VXAcd3d3+Pv7o2vXrnLpzknLo66ujqSkJDRr1qxC2qKwsDAsWLAA3t7eCtlqURH1Wl4HGoBd+wEADg4OaNeuHbc9eenSpYK2J0thVYdYxsrPz4eRkRESExO5Y0J+87Nnz8Le3h4fP34sddsNn3tPVVUV58+f531tRcGqLSoN4qGcwVKHRFVVFbt27RKlWVZSvEaNGiE3NxevXr0CALRq1UpQjE2bNsHDwwORkZG4ffs2/P394e3tjWvXrgmKU7t27VLfF6KH1aJFC6SkpOD169d48+YNUlJSoK6uLqg8ADB+/Pgi7XXhY3w1chYtWoSoqCg4OzsjNjYWwcHBiI+PF1weVoSHh+Pu3bsyW7nE8Mcff2DcuHG4ffs26tatCxsbG1GaWgDw7bffcpIkYpBuUX379q2MllJaWhqysrJEx5WipqaG58+fCz6PlTbbnj17cOPGDVhYWODAgQNISEiAj4+P4PIA7PpXrFDENufKTHWiqZKwd+9eqKqqYvXq1fj999+RmpqK/fv3C46jbBU/Ly8Pd+/exa+//lrRReFgJQr7999/Q1VVFb6+vtizZw9SU1MxduzYciix4mAl7Ddr1iwcP34cgwYNkrG6ByAq4cnq/vjrr7+QnZ2NNWvWwMfHB5GRkaJEiuvVq4fw8HAZ/YivdWiqYYOGhgYOHz6Mnj17wsDAAAcPHix1731pzJgxA6mpqfDz88PIkSPx4cMHrF+/XlSZpCLO8tCzZ0+kpKTA09MTpqam+OabbwQlPqTI2xbVqVMHffr0wePHjzkjicIIFRVXRurUqcMlmQBAR0dHcLKaVfsBAH5+fli4cCGmTp1a5JgQWNUhlrECAgJEXV/K/PnzYW9vj169epWa+OSrN9i3b1/4+/vDzc0N9erV445XlHYMwK4tKg0+FtysBaHt7Oywe/dujBkzRtB5XxMYGAgvLy/UrFmTa+8lEgmSk5MFxZFqsJ07dw5jx46Fo6MjFixYIFfZioNPUk/Kvn37QESIjY1FeHg4evfuDVVVVZnEbGkkJyfj9evXyMzMxO3bt7lrp6Wlcbp4QmBlAsGK5s2bo1atWnLFyM/PR1JSEk6dOoXPnz+DiOTqo9nb22PmzJkYPXq0TAKM76Tpq1evEBcXh8+fP8vopmloaPC6T7+m8ERwXl4ebty4AX19fd7ns058sTRcYNW/YoWyJWKVjWox8ErC7du3YWBgIHecwMBAjB8/XubYvHnzKjTR07VrV8GzR4pCrCgsABw7dgz9+vUTPejlixCBWFbCsGUJ+/EVqfb19YW9vT26du0q1/fE6v5ISUmRa1ZKyo0bNzB06FCoqqqCCrYo48CBA6ISlqUhRhy4qiAVq5Ty+vVrNGjQgOvkKVLk9GtWrlyJFi1aYMSIEdwKSXl59uwZ0tLSBHUWpcjbFqWmpuLMmTOYO3culi1bVuT9cePGiYpbEoqs11KHmdWrV0NVVVXGgSYvLw9Lly7lHYtV+wEUL9Qrr3ivPHWIZaysrCysXbsW4eHhkEgksLe3x4wZM3gPHjt37owxY8Zgw4YNmDt3bpH3ha6YKXxfSCc++IjBKjs3b96Ej48PHj16JCNQXBEr16U0bNgQaWlp+Oabb1CnTh3uuxbaB2nTpg1OnDgBPT09ucrTpUsXzJkzB76+vvj777+hra0NfX19wSLnZSHk3n39+jXCw8Nx9uxZREREoH79+rCzs+OdaFy/fj3WrVuHly9f4rvvvuOO169fH9OnTxfsjsbaBEIs0hV1ly5dwqNHjzBixAiZpI7QpKehoSGzhEDhSQopYiZNT548ybmpyUPh55ZU5H7IkCHcSsmyOHLkCA4fPoyjR4/KfK8aGhpwdXUV7ELH0nChPPpX8mBqaoqYmBgZUwPpsWqqE02VhjZt2qBRo0Zwc3PD6NGj0aBBA1FxunbtihUrVsDW1hZAwUD/ypUrOHnyJMviCmLJkiWoWbOm0swmbtiwAa6urqK/Yyk2NjZ48OABxowZAzc3N3To0IFRCWURYqvaq1cvTJ06FcuWLUNISAg2bNgAHR0d0UtYS4Jvp8rX1xdnz57FvXv3YGlpCXt7e9ja2qJjx46Crsfq/mjcuDF69+4NNzc3ODk5iR6YP336FNnZ2fjy5QskEglq1aqFpk2bMq/TrJ08KhOsXVqAgno7adIkjBo1SrDrUGGOHDkCFxcXfP78GQBED1xnz56NiRMnCr4fvoZVWxQREcE9O4ojLCwMw4cP5x0vKyur2OSCvFbRQlBRUSmyqlKK0N+MRfsh3Z68Z88emVUfaWlpiI2NFZxoYlWHWMZyc3NDSkoK9xsHBASgYcOGvFc6RUdHY+fOnQgNDS0yuJRIJLydlZQZFm2RgYEBPD09YWlpKbPFRIxDEwDk5OTg8ePHMpNUQre5P3nypNjj2traguKYm5sjOjpa0DnFER0djRUrVsDGxgYzZszAgwcPsHHjRlFW8KUhJNGkpaUFOzs72Nraws7ODs2bNxd1TV9fX9EW8oXZu3cvnJyc8OjRI5nVdaNHj5Y7thCKc/eSIsbla9iwYVi5ciXatm0rb9HkRrpFtbjtqYDwJFpZ8J0MZpX4unPnDnR1dfH582f4+PggNTUVCxcuhJGRkeBYrPpXrFCWRKzSolhJqGrk4fz58zRu3Dhq3LgxjRw5ks6cOSM4xosXL6hTp05069YtWrt2LVlbW1NmZmY5lJY/LJ0oWDB+/Hhq3LgxDR8+nE6cOMGJuorh4cOHtHjxYtLV1SULCwvaunUr73NnzZpV6ksMLIVhS0OomG9GRgbt3LmTdHR0RP/2LO6PjIwMCggIIGtra9LS0qL58+dTQkKC4DiampqkoqJCampqpKamRioqKqShoUEdO3YU5GYUExNDjo6O1K5dO85dR1dXV3B5quHHhQsXuDr0ww8/0KlTp0Td/7q6uhQREUFpaWmUkZHBvYSyZMkS0tXVJTMzM/rzzz850VoxyNMW8YWvuHB8fDx16tSJWrRoQUREN27coDlz5jAvj6Jh0X5cuHCBlixZQs2aNaMlS5Zwr99//50eP34suEws6xCrWHp6ejL3VW5uLunp6QmOs3LlSlHXrwywaIvECtEXB0tB6JcvX9L58+eJiCgnJ4eysrIEx1i+fDmtXbuW3rx5I5eDblmwEopnaXBQlrC49Fkjr8uwok0gFI2NjQ3VrVuX7O3tRRsRsfquJ02aRETFOzKLcWIui7Ke1VJnuSNHjhT7qkhY9a9YoSg33spKdaKpEpKRkUFTpkwRPSC/ffs26erqkqWlZYXenMpMRkYG7dixg6ytrally5bk4+MjV7zMzEzBv1nhQUZxLzF07dqViIgsLS3p8ePHlJmZWS6JC74DzrNnz9K8efPIzMyMTE1Nac6cOaISRIWR9/6Q8ujRI3J3dxcVZ968eRQQEED5+fmUl5dHO3fupDlz5tDhw4cF2RTr6+vT5s2bKT4+nu7cucO9qiH66aefiIjI2dlZppPIwrWycMKgZcuWgs9n7TB47tw5GjduHDVp0oRGjx4tVywxbRFf+A6mrK2t6dKlS9zn8/PzqWPHjszLU5HI034QEcXFxZX6vhAXKyK2dUjeWFZWVvTp0yfu358+fRJt3x4dHU3+/v7k7+9P169fFxXjwYMH5OTkRM2bN6eGDRtyL2VAnrZo2rRpor+TrzEyMqKkpCTung0KCiJvb2/BccLCwqhVq1akra1NRAX1vE+fPoLjKGqCkpoIb0YAACAASURBVG9fxtfXt9RjZd3PLMskfb8kt2Gh16lIR+HiKG5yVMyEaWBgYLEvIbD6rhVNWc9q1omvPn36yLjyvX37lvr16yc4DhH7/pVYqnoilhXVYuCViOTkZAQFBSEgIABEJEhXafDgwTJ6JjVq1MA333wDV1dXABUv5hoTE4O7d+/C1dUVHz58QGZmpujlwiyoW7cu3Nzc0KdPHyxZsgQrV66Ev7+/4Dg3b95EQEAA9u3bBzMzM4SGhvI+d/HixYKvVxYshWFZ4ODgACsrK6xZswY9evSQK5Y890dhpO46O3bswPXr12XEePly+vRprFy5EkDBku6xY8fCxMQEq1atEiTmq6qqCg8PD8HX/zfQq1cvAICzszPz2BkZGXj79i2Sk5NlRO/5MnDgQGzcuBE//PCDjIaE2K2TNjY2qFevHvLz8xEaGirKGUeetogvfJ3DMjIy0L17d5nzlEFrgQUs2g8AZW6JFeJiBbCpQ6xiff/99zA3N8cPP/wAANi/fz/MzMy47Up8NZa2bt0KPz8/DBkyBBKJBEOHDsWiRYswadIkQeVxd3cvdku5MiCmLZLq1+Xk5GDbtm1o27atTDskRueLlSD0ihUrcPPmTc4ow9DQsMTtdKXBykm3LIinusjBgweLPNsLH2O5xb2sMkl/X3m/I2U1gSisNwYUtLnp6emC45SlLchHv5bVd10YFltUy6KsZ/W2bdsAgJkj56tXr2T0CzU1NfHy5UtRsVj3r8SiaDfeykp1oqmSMGDAAERHR2Po0KHYsWMHunbtKuj8rwdjgwYNYlk8ufjzzz+xZcsWZGRkwNXVFSkpKZg0aVKFWQ7n5ubKDBSGDx8uSgugc+fOyM7Oxvjx4xEXFydX4uzatWuIi4uTefCIsQhevXo1AGD06NHo0aMHM2HYr+HbObtz5w7Cw8OxevVqeHh4oGvXrrC3txfsSCPv/SFl+vTpCAsLg7GxMdzc3HDo0CFRA+CsrCwkJiaiXbt2AApE2KW/nRA71m7duuHGjRuChRf/DQwYMABAQV3mK3BZFgcPHkRAQACio6MxfPhw7Ny5E2ZmZoLjSAcXXl5ecokLf508dXNzw6pVqwSXh2VbxIIaNWogJyeH6+w+e/ZMKWyK5YVV+8EHvm0sqzrEMlZ+fj66dOnCaViYmJggLy8PsbGxvJOVQIH1dkxMDJo0aQIA8PHxga2treBE08ePHzFixAj4+fnBwMAAW7Zsgbm5OXPtQiHI0xatW7eOeXmkbayWlhYOHToEHR0dpKamCo6jqqpaRDBfmZPMZdVHqabaixcvZJy+0tLSKqxMrDh27BjOnDmDu3fvKsWY4ddff8XKlSuRkZGBRo0accczMzPLxdH57NmzCjdKOn78ONzd3ZGamoq6desiNTUV2traFeoYziLxlZubi9zcXM5UKTs7G9nZ2aLKw6p/JS/KmohVOipoJVU1Atm9e3epWkqPHj1SYGnYYmhoSJ8/f5ZZytmpU6cKK0/Tpk3J0dGR9u7dS1++fBEdJzIystT3L1++zCuOv78/GRsbU+PGjWnIkCGkrq5Ozs7OosuVl5dHL168oCdPnnAv1ghdJv7o0SPatGkT6ejokKqqquDrsbo//P396dmzZyW+z7c+HD58mBo3bky9e/em3r17k6amJh0+fJjS09O55balYWRkRMbGxqSvr081a9akDh06kLGxMfeq5v9o3LgxOTo60qpVqygmJkauWPb29rRnz55y163jW48aN25MHh4edPXqVbmux6otKgu+W+eCgoKob9++pKWlRT///DNpa2tTaGgokzJUJKzaDz7wbQdY1SHWsUpj3759vD5nYGDA61hZKGpLuRBYtEXbt2/ndYwPrHRIevfuTa9fv+bqb3h4OPXu3VtUmRQBHy0blppqLMok3bZV0kso4eHhpb7P936Vlw8fPtDjx4/JycmJkpKSuNf79+/L5XpCdLVYbb9ltUWVz3X4wEqbbc6cOeTs7Eznz5+n8+fPk7Ozc7npMrJ8zpbG+/fvKSQkhFq1aiX3FsyqTHWiqYrAt9PJcp8sK6SdvMINH0sRS6GUNlAgYvdQ5fubderUiTIzM7nv5P79+zRkyBBR1wwICCB1dXVq1KgRaWpqkqamJjVp0kRwHFYi1ZMnT6Y2bdpQmzZtyMPDg/bt20cpKSmC45QFq+SMkDjJycl09OhROnr0KCUnJwu6zoULF0p9VfN/ZGVlUUREBC1YsIDMzMyoadOmNHz48HK5louLC5M4fOvR58+fS31fqE5PSbC6P06cOMH7s5GRkTR37lyaM2cOXbp0icn1lR2WSeKKqEPKVh+HDBlCPj4+3ITJwoULRT0bvb296d27d7R7925q1KgRNWvWjGbOnCk4jiLh0xYV9z2amJgIug5rHZLr16+TsbEx1a9fn7p160bfffedIIMMRcN3QM5Sg6ksyipTRkYGpaenk6+vL/n4+NCzZ8/o2bNn9PPPP5Ofnx/z8ihy8is3N5dsbW0Vci0hf5e1tTWFhIRQx44d6datW+Tu7k7+/v6Crym9P6WGPYWPsYRvfWWV+MrOzqYlS5aQmZkZmZmZka+vL2VnZwuOwwdFT8YqSyJWWalONFUR+D4Mi0vgVPQKiX79+lFCQgJXjoCAABowYECFlqk0WH1ffH8zU1NTIiqYqZW6zohNxLVu3Zru378v6tzCsBKp3rp1q0JW47FyfGHpHMMHljPSVZn09HQ6evQoeXl5UevWrUULC5eFou/9slBUeaQCoCW9quEHy/ZD2eoQy1h8/7bk5GQaMWIENW7cmDQ1NWnkyJH05s0bua799OlTun37tlwxFEFp33V0dDStW7eOtLS0aP369dxr2bJlgleLl4cg9IcPH+jEiRP0999/U2pqKrO4Ypg6dWqpx/hOEuXk5FBISAj5+/vT0qVLuVd5wDdJUFyCojySForuF1laWlJeXl65X0dInWfl6CwVunZycqKDBw/SzZs3RU3ispoMVlTii9UkBZHi62NZVPQYu6Kp1miqIvDds52Xl8dsnywr1q1bh1GjRuH+/fto2bIlNDQ0cOzYsQotU2kQT22MsuD7m9WuXRs5OTkwMjKCt7c3tLS0RO9F1tTUhJ6enqhzC8NKpNrd3V3uGHxgpWmgKG0EKRs3bsSECRNkjm3atKnIsX8z3bp1w8ePH9G7d2/Y2dnBz88P6urqFV2sUmFVjxTVFnl7ewMoEAa9efMmJkyYAIlEgoCAABgbG/O+ztemFF9T1TUNWLYfgYGBTOKwqkMsY/H9npo0aYKQkJAS3w8LC8Pw4cN5xcrPz8fr169BRNDQ0MDTp0/RqlUrXucqG69evUJcXBw+f/6M2NhY7riGhobgelMeOiRpaWlISUmBRCJBeno6GjRoIDgGK6Kiooocu3LlCvf/Uv2vshg5ciRev36Nrl27yq03d/PmTfj4+ODRo0cywtdSTTO+wuLp6elITk5G06ZNARRorIkRzS4LRfeLzMzM0L9/f7i4uKBevXrc8YEDBzK9jpD2TKphpq6ujqSkJDRr1gzv3r0TfM0ZM2YgNTUVfn5+GDlyJD58+ID169cLjjNu3Dh4enrC0tJSrvrISputLISaW5SGoutjWbB8xlZGqhNN/zL69OmD4cOHczf0+vXr0bdv3wotU9u2bREdHY2EhAQQEfT09JRaGFbRjdhff/2F7OxsrFmzBj4+PoiMjERQUJCoWM7Ozli3bh1Gjx4tl1tDtUh1+XLt2jVcvXoVb9++5ZyYgIIOelZWVgWWTPlo0aIFUlJS8Pr1a7x58wYpKSlKn2hihaLaon79+gEAfH19cfnyZW6iYvjw4ejZsyfvOOXhEFhVYTXYLAuWdUjZOvgrVqzglWgKDAyEl5cXatasCRUVFQAFf0tycnJ5F7FcGDRoEAYNGoSTJ0+iT58+csViLQi9Z88eTJ8+HdbW1iAizJw5Exs2bFC4+21oaChCQkKKJNDS0tJkkhd8uX37Nu7fv8/kHmCVJJg9ezYMDQ25Pv6pU6fKxc1Y0dy6dQvA/zmjAQX3K+tE05kzZ3h/Vl5H5xUrVmDBggX49ttv0bBhQ5iamiIxMVFMsQGwmwxmlfgqi6qcjFG256KiqU40VRH43qT+/v5Yvnw55s6dC6BgBmDevHnlWbQycXZ2xuHDh9GhQ4cix6oyfH6zvLw8BAUF4ddff0XdunVlHqxi+PnnnwFAxh1FiFtDedgmKwJWDzFFPQxZzkhXdfbt2wciQmxsLMLDw9G7d2+oqqrK1Ukrb5StU8W3PO/fv5fpNKmoqOD9+/e8r1OWnXRVR8jvzmqwWRlRdHvt6+uL69evM1ntqwz8888/sLa2Rk5ODo4ePVrkfSED8oYNG2LEiBHQ1NSEra1tiZ/ju3ps2bJluHHjBnR1dQEASUlJcHJyUnii6fvvv8egQYNw8+ZNmQSahoZGqX9nSbRs2RLZ2dmoVauW3GVjlSTw8PBAhw4dEB8fDwCYOXNmudRxRT/P5HWkbtiwYbGDf/r/7mXSZxrf1WyA/I7OYWFhWLBgAby9vZn0o+WdDGad+CoLlskYZetf/dupTjRVEYpb0lwcNWvWxOLFi5VqVuPp06dFjj18+LACSsIPVo2Yp6dnmZ9RVVWV+6FamPz8fLnOLw/bZBbk5+dzM9HFwff+KAsLCwsmccqC5Yx0Vef169cIDw/H2bNnERERgfr168POzq5crsVqwM+qHglti7KysoodCPFpiwDAzs4OTk5OnJV0cHAw7O3tBZUBAPr27YugoCDO5vzdu3cYP348jh8/LjhWZULI785qsFkWitw6Z2lpiatXr2LmzJmlPkuWL1/OpDx8By+stpQrktLaouDgYFhbW2Pt2rVF3hO78qOs5Avf1WN16tThkkwAoKOjgzp16gguj7wYGhrC0NAQ/fr1E5RQ+BrpiuO2bduiV69eGDx4sMzkm5eXl+CYrFaMHzhwAD/99BMkEgmSkpIQHx8PZ2dnnDhxQq64X8PqfhVCWFgYzp49CwBwdHTE0KFDeZ8bFxdXLmX6+PEjkpKSuBWoN2/ehImJCa9zWW1RZTUZzDrxpUgU1U/ny7898SWhf/s3UEnIzc3FgQMH8PDhQ5ll9L/88ougOOnp6Zg/f75MA718+fIK2WqyZcsWbN68GQ8ePJDp5KWlpaFTp07FzsQpgvv37+P7778v8f2yBv+FVwsVx++//y6oPEuWLEHNmjXh5uYms6Rb6HY3Kc+ePcOlS5cAANbW1mjRooXgGDt27CiiE1TcMUXRqlUrTJkyBe7u7nJ1GtPS0vDzzz8jKSkJx48fx927dxEfH49Ro0YxLG3ZSGekS7oHWC8Rr8xoaWnBzs4Otra2sLOzQ/PmzUXHKm4lpZjVlRYWFvDy8sLw4cM5jQOxvHr1CgkJCejVqxdyc3ORn5+Pb775BgAQHx/PawvVrVu3MHr0aHz48AHPnz9HTEwMQkNDsWrVKkFlyc3NxZYtW3Du3DkABYknd3d3bisdX4yMjIp09k1MTCpdh/ZrWLYfP/74I9zc3OQebPr5+WHhwoUlHuNbh4DiB06HDh3C4MGDecXq0KEDLly4AAcHB1y+fLlIB1zsM60kyqpTHz9+BFCge1e7dm25t5Sz5sCBA0hISICPjw9evHiB9+/fw8DAoELLVBLGxsYyq29LYtGiRVBVVcWkSZNARAgICEBeXh5mz54NQHHf+Zo1azB79uwS+2t8+2lubm4lvieRSLBjxw7eZSqcJEhISJB7xbipqSnOnDkDOzs77rfp1KkT/vvf//I638bGptRkrfQ5oGiWLVuGw4cPY+zYsZBIJAgKCoKzs3ORdk6RrF27Fr/88guaNGnCJYElEgkePHjA6/zU1FScOXMGc+fOxbJly4q8z3c18D///FPq+9bW1rzidO/eHerq6oiKioKNjU2R91nrKfJtPwC2/StF8G+fMK5ONFUShg0bVqzQoHS5Jl9cXV1Rp04dTJ06FRKJBFu2bEF6erpozR95ePLkCR4/foypU6di8+bN3HENDQ107ty5wrYL6OjooF27dvD09MTAgQMFL+lcunRpqe8LXU1WeKWORCLhlveKEQQ/cuQIJk6ciO7du0MikSAyMhLbt2/HgAEDBMUprgNvamqKmJgYwWViQUJCAv766y/s3bsXDg4O8PT0hLm5ueA4I0eOhL6+PkJCQnDnzh1kZmbC0tKy3GbASsLd3R3btm0r9gEvkUgqrINXGVm/fj1vkcni6nXnzp05TQi+nDlzBn/++SeuX7+OCRMmYMqUKaISuvv378fs2bNlZqQXLFggeEa6V69e8PPzw/Tp0xEbGwsigr6+Pu8Bx9dIuw1il7sbGBggNjZWxpTCxMQEd+7cERVPWWDRfrAebBZXp8Um9Tp16oSTJ09yItmnT5/GzJkzce/ePV7nL168GKtXr0ZWVpZMHZLnmVYaZQ1eVFRUuOtLKc/yCOGXX37B9evX8fDhQzx48ACvXr3C0KFDZYSq+ZCTk4PHjx/jy5cv3LHOnTuzLi7vOlXaymNFfudbtmyBh4dHif21ilj1zypJIKVr1664du2azH0gZED/999/AyjZBELo+IMVnTt3RlRUFLcS7tOnT7C0tBT8nE5OTsbixYsRHx8vc3+IaRtbt26Ny5cv47vvvhN8bmEiIiKYbFGVdzKYVeKLL0ImPFj1r+RFWROxSke5+dlVw5T27dtz1vby0LlzZ17HlAkXFxeFXi8vL48OHjxIdnZ2pKurS7/++iulpKQotAzlhbGxMSUmJnL/TkxMFGS9ydI2uTz49OkTbdmyhVq1akVdunSh3bt3C7pvpN9FYXtUZb8/qikdPvV78+bNZGRkRHXq1CFjY2Pu1bp1axowYIDoaz958oQWLFhAzZs3p2HDhtHly5cFnW9iYkLv3r2TqY8dO3YUXA5TU1Mikq3XYiyAX7x4QX369CE1NTVSU1Ojfv360cuXLwXHmTNnDjk7O9P58+fp/Pnz5OzsTHPmzBEcR9lg0X5cuHCh1BdfTp06RTNnzqSmTZvSrFmzuNeECRNE2y1fvHiRjI2NKS0tjS5evEht27alhw8fCo5jZWUl6vpfs3379lKPnThxgsl1KoLOnTtTbm6uTF0yMDAQFOPYsWPUrFkzqlWrFjVq1IgkEgnp6OiwLioRVVt479y5s8jryJEj9Pz5c8GxyqrXfOnduze9fv2a+23Cw8Opd+/eguOYm5tTTk4O9++srCwyNzcXHIcV+vr6vI6VRf/+/WnlypXUrl07Onr0KPXr148WLlwoqkzdu3cXdZ5Q+N5nxX3OxMRE8PXCw8NLfX/fvn284sTExJCjoyO1a9eOdHV1uZc8yNu/kpfjx4/T8ePHafbs2WRjY0NBQUEUHBxMtra25O3trdCyKDPVGk2VBFZCg3l5eUhPT+e2yqWnp1forB0fxM66i0VFRQWDBw/G4MGDERMTg8GDB2PJkiUYM2YMli5dKmjG4tq1a4iLi5OZLRGzZz8mJgZ3796Fq6srPnz4gMzMTFFbhPLy8tC2bVvu323bthWk26TMItVEhDNnziA0NBT16tXDqFGjsHfvXoSFheHQoUO8Yki3JEnJzMys8P3VipqRrqrw+f2cnJygp6eHqVOnyuiaSFdXiiU1NRVv3ryBiooKmjdvDk9PT3Tr1g0bN27kdb6qqiqnYyTl6zrKhxo1aiAnJ4ebfXv27JmoFaMeHh7o3r079uzZAwDYvHkzJk+ejGPHjgmKo4ymFCxg0X5IVy2UNCPNd1WDmpoaGjRoABUVFdSvX5873rJlSyxatEhQmaT06NED8+fPh4ODA96/f4/jx4+jdevWguNERkaKuv7XbNy4sch3tGnTJu5YZd6uULt27SL3qNC6tGjRIkRFRcHZ2RmxsbEIDg7mhKFZI7RsHz9+lJGBaNSoEesilUpxqzQKI1SWYvfu3bh48SK3Wvzy5cvo2rUrHjx4gHXr1uGHH37gHauses2XX3/9FX369MGjR4/QvXt3PH78mFulJAR5TSBY07VrV7i6usLd3R0AsH37dnTt2lVwnGfPnmHevHkIDg7GgAED4OjoCGtra/j6+gqO5ePjAy8vL/Tv319mBaoQV1Y+lHWfsXYsZqXNVh7mFvL2r+SFlRtvVac60VRJYCU0OG7cOFhYWGDEiBEAChybxo8fz7KoVYLExERs2rQJYWFhGDhwINzd3XHu3Dk4OTnxXp67fPly7N+/H0+fPoW1tTXOnj0LW1tbwb/Zn3/+iS1btiAjIwOurq5ISUnBpEmTRImEN23aFP/5z3+4DktAQIAgTSNlFalesWIFtm7dik6dOmHevHlwcHAAUKCX1a5dO95xbGxs4O/vjy9fviA8PBxr165lJiQuhuPHj8Pd3R2pqamoW7cuUlNToa2tjcePH1dYmSobfLZ3aWtrQ1tbm9sC9PLlSwAQvQw+JCQEGzZswMePH+Hl5YWNGzeidu3aXKKXb0dIXV0db9684f6GiIgIUQMyT09PODs74+3bt1i4cCGCg4MF6zMBBR3zwkml+fPnw8jISHAcZTSlYEFx7YdUv0go8g42ra2tYW1tDWdnZ95bEkqi8IAFKNDq6tGjB06fPo3Tp0/zfqYNHjy41PuRr+4H68GUMqKtrY1Lly5x2yiXL18u+F5TUVGBtrY2l9BxcXEpViCcBXwFoUNDQzF9+nSZ5IVEIkF2dna5lKsk0tPTAQDPnz9HREQEJ5Nw9OhRUa5z9erVQ2xsLKfvmZCQgAULFuDKlSsYOHAgr0QT63rdpUsXnD9/HleuXAERwcrKCg0aNBAch5UJBCv++OMP+Pr6cvpadnZ2opLn0okBNTU1pKSkoGHDhnj37p2oMl29ehW7du3C5cuXZTSarl27JipeSZTVn1H0ZDDfBDNLcwtW/StWKFsiVtmoTjRVErKysvD999/LaCGI0ceYM2cODAwMEB4ejrS0NHh4eGD69Oksi1rpcXR0RGJiIqZNm4b//ve/3IPZxMREUEO9Z88e3LhxAxYWFjKinkLZunUroqKiYGVlBQBo06YN3r59KzgOULACYcyYMfjxxx8BFPxNwcHBvM9naZvMkpcvX+L06dNo3759kfdCQkJ4x/H19cXq1auhoaEBHx8fODs7V+hKC0XOSFdTYAQwdOhQLtGkpaWFsLCwUs0BimP37t1YunRpEfc7VVXVIoP20mA1I+3i4oLWrVvjyJEjyM7ORnBwMLp37y44DhHh9evXaNasGYACxz8hKxn27t2LUaNGlfgdiFntqUwU137Mnz9fUAzWg81OnTohNDRULiORrzVdDAwMkJ+fj9jYWEH9EGdnZ96fLQ1lXlnLij/++APjxo3D7du3UbduXdjY2Ah6VgPghHK1tLRw6NAh6OjoIDU1VVAMvjokfCeepBpz8orcy4tUX8jBwQFxcXHcpMKyZctETb4+ePBA5jmhp6eH//3vf9DR0SlVl6ow5VGv69evL/ek4B9//IEtW7ZwphjOzs7caqKKoG7duli5cmWJ7/PVZWzfvj1SUlLg4uICc3NzaGhowNTUVFSZdu3ahaSkJFGJPJYoejKYb/vPykkRYNe/YoWyJWKVjWox8H8ZTk5OCAkJQY0aNaCvrw8AGDt2bJnLiCsSRbsRHThwAIMHD+bdOSiJLl264MaNG+jcuTPi4+MhkUiKdVsqC3Nzc0RHR8uIOIqJU5iMjAwAkHGx44OyilSX5axUWZEKrBsYGOD27dsyx6rhhxDxUxsbG7i7u2P06NEACpKUW7ZsEbV6kBVpaWlyz0jfvn2biVtVUFAQ5s6dy3VgT506hdWrV2PMmDG8zl+8eDGWLl1arFOTUIcmZeTWrVtFtloWd6w0jhw5gsOHD+Po0aMyiXsNDQ24uroK7qizMhIpD7KysuSSA1C2lbXlwefPn0FEqFu3ruBz9+7dCycnJzx69AgjR47Ehw8fsH79eq594wNrQWgrKyvBgublib6+fhETguKOlYWVlRWmTJkCV1dXAAVt5ebNm3HlyhXB/TVlrdckpwmEohAzZrh8+TI+fPgAJycnwS6qQMEK0rLE3FlQVn9G0Y7FZX3XrM0tlBFWbrxVlepEUyVBapv85MkTHDt2TLRtsrSR2rdvH65cuYLVq1fDxMSEG8QqI2ZmZrh+/Xq5X0dqdVwSQm13e/TogXPnzmHixIlo0qQJtLS0sGPHDsHfdf/+/fH7779j5MiRuHnzJgIDA3Hw4MESHySlcezYMVhbW0NDQwO//fYboqKisGTJEi7pWFlh5axUXMK1QYMGsLS0hJmZmVxlFIOFhQWioqLQp08fTJ48GTo6Ohg6dCgePXqk8LJUVoS4mRQ3IBAySGC1NYg1bdq0QaNGjeDm5obRo0fLNet6584dXLhwAUBBYq5Tp06CY7x79w6ampplHqtssHR4YzXY1NPTw/3795kNDqOjo4usjpLO5PLl9u3bGDVqFD58+IDnz58jJiYGoaGhgrdzLl68GF5eXpyO2bt377Bp06YqsyXz3r17SExMlPmu+WzlXrFiBRYsWIBz586hd+/eTMpiYWEho0OSnZ2Nnj17IioqSlCcwMBAvHz5EsOGDZMZcEqdDBWNk5MTzM3NMWnSJAAFej9RUVE4deqUoDgJCQlwdXVFXFwcJBIJDA0NsXPnTrRq1QpXrlzhtcJB0UkCvrx8+VJGrsHW1hbbtm0TpROqCIRMLrHC29sbT58+LVKvWf9mZT0XFD0ZzCfxVRpCnBSVtX8lpbIkYhVNdaKpksDKdl06U+Pp6QknJyf079+/Qhrlwjx9+rTIsQYNGghO7MiL1OoYABPr5Tt37kBXVxefP3+Gj48PUlNTsXDhQsE6C//73/8watQo/Pe//0Xjxo2hoaGB48ePQ1dXV1Ac4P+s2uPj4zFu3DhMnToVwcHBuHTpkuBYyiBSffr0aZw6dQp79uyRWVWRlpaG2NhYwQO8UaNG4cKFwiZr7QAAIABJREFUC+jfvz8kEgmOHz8OCwsL7p5R9NYeFjPSVZ2bN2/Cx8cHjx49khmQiUnGmZqaIigoCB07dgQAToCf7wqynTt3lvq+UEvgwm2SlPr168PS0hKbNm2Cjo4O71gXLlxAYGAgjh8/Dnt7e0yYMEHU8u7Pnz9zzx0jIyPOYloILBMyykBycjJev36NESNGYN++fdzzIy0tDZMmTUJCQgLvWKwHm3Z2dvj777/lNhIBgKlTp+L06dMwMjKS0SHZt2+foDi9evWCn58fpk+fjtjYWBAR9PX1BRt/FJcErsz1qDCzZ8/G7t270bFjR5nv+syZM2WeK/0OWH4X7du3x71797iy5ObmomPHjnjw4IGgOFu2bMGsWbOgpqYm83clJyczKadQXr9+DS8vL0REREAikcDOzg7r1q3jtgcLRar9JDXcEYKyrhgfMGAALC0tMW3aNAAFEgyRkZGCTSAUBd96f+rUKcycOROPHj1CXl6e6L4+ALl/M75bVJUNvhMiJZlbCBG4Z92/YkVlS8QqmupEUyVB2nAWTgoZGhoK1msZOXIk0tLScO/ePdy9exdAwd7Zikw0NWnSBO/fv+f0BHJyclCvXj1oaWlh9+7dosRmK5q8vDz4+Pjg119/ZRIvPz8fCQkJICLo6emJdm2Q1qPVq1ejbt26mDZtmqjOqLKIVP/zzz+4cOECNm/ejClTpnDHNTQ0MHjwYEEDcaBgdnPnzp349ttvAQBv3ryBq6srQkJC0KNHD4U5IJbHjHRVxcDAoFg3EzErbU6fPo0xY8agc+fOICLcuXMHu3fv5sTlFY2fnx9yc3Nl3HWysrLw7bff4u+//8bp06cFx/z06RO8vb2xdetWwR3qK1euYOjQodwg7M2bNzhw4AAsLS15nZ+dnY0vX76gR48euHz5skxCxs7OTlBCRplYv3491q1bh5cvX8oIyNevXx/Tp0/HxIkTecdiPdicMmUK4uPj5TYSAYB27drh9u3bMnHEIN1WXrg/I2bCSzpxUhgx256UkbZt2+LWrVuiErndu3eHuro6oqKiiq1HYmb+p02bhsTERBkdkrZt22LTpk2C4mhra+PcuXNo06aN4DIoI4mJiWjXrl2JJjFVwSFW3pW+ioZvn7Z9+/bYsGFDkb6DmG2qZREZGYlu3bqV+D7rLaqAfJPBrBNfxf0mLGQgiAgZGRmiErusqGyJWEVTvYGwksDKdj0wMBCnTp2CoaEh6tSpgxcvXmDFihWsiimKiRMn4vvvv8e4ceNARAgODsadO3fQrVs3eHp64vLlyxVaPjGoqqoy13WpX78+cnNz8eLFCwDilprn5eUhOjoaBw4cQEBAAICCh5FQlEWkmqWzElDgQCNNMgHAt99+i5cvX6JRo0ZcIlQRhIWFYcGCBfD29q4Ss/PlCUs3E0dHR9y7dw/R0dEACraLCNnOJXXBKYnff/9dUHkOHz6MGzducP/+5ZdfuEH61q1bBcVKTk5GUFAQAgICQESikuA//fQT9u/fz3WYr1y5glmzZvHePrNixQosXboUQEF7JkVDQwOzZ88WXB5lYcaMGZgxYwZ8fX1FuR8VZtu2bQDA7PnBykgEAJo3b85kZVSNGjWQk5PDlePZs2eiJk/09PSwatUqzJ49G0SENWvWCBbuV1ZatmwpOqF37NgxnDlzBnfv3sWgQYOYlIeVILSWlpZSJZnklaWYNWsWjh8/Xuz3LJFIRG9zV4YV41LkNYFQNHzLpqGhAUdHx3IuTQHTp08vtS/Xr18/AAWGEoW3qA4fPhw9e/YUfD15J4O9vb0BlJz44kt5OIROnDgRa9asQZ06dWBmZobExET89ttvXKJH0bBy462qVCeaKgmsbNfV1NRknF9atGiBFi1asCyqYE6fPs05SEgkEowdOxYmJiZYtWqVQsWcGzZsWGwHXLqcVqhdZd++feHv7w83NzcZ0W2hWwIDAwPh5eWFmjVrcgLlYpea+/v7w8PDA3Z2dujQoQMSEhKKdWorC0XaJpeG1MXqn3/+KXYvuNBZ+xYtWmDp0qXcct6AgAB89913yMvLU+i+6zp16qBPnz54/Phxsfd5Re9FVyZYupkABUn8Dx8+QCKRIDMzU9C5hZMnLEhPT8fbt2/RpEkTAMDbt2+5rRlCEp8DBgxAdHQ0hg4dih07dqBr166iypOZmSkzK2tlZSUzECqLxYsXY/HixZg6dSr++usvUWVQZqRJpqysLJlOtNht4CwGm9IJBRaYm5tj2LBhGDFihFw6JJ6ennB2dsbbt2+xcOFCBAcHC9ZnAgpWkrm4uGDhwoWQSCTo2bMndu3aJTiOMrJq1SoMHz4cjo6OMt81Hz2shg0bYsSIEdDU1IStrW2JnwsLC8Pw4cN5ladGjRr48ccfucGc2Odh7969MXv27CJ1qKKSKB4eHtDX1+d053R1dTF69Gjeiabjx4+DiBAZGSmzmlEelGXFuBRvb28YGxsXMYFQVvg69PXv3x+HDx9m5oZZGnyTX+/fv5e5t1RUVASPPQD5J4NZJb7Kw0kxJiYGDRo0wNGjR2FsbIxLly6he/fuFZZoqmyJWEVTnWiqJCib7TpLsrKyuOXHQMFSZGnHWuwWMTGwXgYsFZZetGiRXFpPvr6+uH79OvT09OQqT15eHh49eiTzd+rp6eHAgQOCY7GwTWbB/fv3ARS13wbEdYR37twJLy8vbjbC1tYWgYGByMnJUegApjxmpKsahd1Mtm3bxsTNZM+ePZg+fTqsra1BRJg5cyY2bNiAkSNH8jqftQjxTz/9BENDQ66Df/r0aSxcuBAZGRmlLsP/mlGjRiEsLEzuLU/16tVDeHg4ZyscEREheJtBXl6eQtx5KoLo6GiMHz++iG6NGM0PloPNly9f4s6dOzIJKzEitdLVdYWThBKJRHAsFxcXtG7dGkeOHMHbt28RFBSEHj16CC7Pd999h3PnzuHTp08AymfLS0WxefNm3Lp1C0Qko2UkRHi9tCQTULDCkG+iiZUOSXBwMADZyRJ5Vv7Iy4MHDxASEsL1g2rXri1qkOjg4MBsy6ayrBiX4urqCmNjYy4ZN3v2bFFb01lRli4j39Xt69evR1paGmrXro1atWqJnlTmA9/+qJ2dHZycnGS2qIrRUmQ1GSxv4mvQoEEYNGgQUydF6f156dIl9O/fHxoaGgodK35NZUvEKppqjaZqKpwjR45g4sSJ3MPh1q1b+M9//gNbW1ts2LABCxYsqOASVizm5ubcVh55kW67kZdqkWrFEBERwWxGuqrB0s1Eyvfff4+TJ09yQvtJSUlwcnLiEppCuHbtGuLi4mQG92J0ce7cucMN7mxsbEQ7RF67dg3h4eEAAHt7e1Euijdu3MDQoUOhqqoKIgIR4cCBAzA1NRUUx9raGidPnhSlP6PMmJub448//sCUKVNw8eJF/PHHH1BTUxO1LdDY2JibbS882BTagd2xYweWLVuG9+/fo127doiPj+ccxCoKJycnhISEoEaNGlx9Hjt2bLGun8Xxb9DFadOmDRISEsrVIluILlZV1SGROrtKv4vMzEyYm5uXWLdKwsnJCcHBwUycM6XaNQYGBpxLMQs9G3lgYQLBCla6jE+ePCn2uLa2tlzlKw6+ulG5ubnYsmULp4FkZ2cHd3d3we0AK8diebXZysNJ0dHREa1bt8bJkycRFxeHunXrwtTUVPA9yxIWbrxVlepEk5JTVsfrl19+UVBJypfk5GQZXRTpVhFFMmrUKOzdu5dbKfE1YlZIxMTEcM5VHz58QGZmpuAZwBUrVqB27doYPXq0zIoEMdsx5s+fDwMDAxmHNqFlUVaRaha22wC72X9FUFUcluSBhZuJFFZuaMuXL8f+/fvx9OlTWFtb4+zZs7C1tcWhQ4cEl4kFW7duhZ+fH4YMGQKJRIKDBw9i0aJFnKU3X54+fcoJekskEtSqVQtNmzYV3BZNnDgRN2/exPDhw2W2FSva1ZE10rpSeIBoZmaG69evC47FarBpYGCAixcvonfv3oiNjcXFixcRGBiIHTt28I7BOrEjHdTv27cPV65cwerVq2FiYsL9nWXRv3//Ep1XK3J1DEvs7e1x4sSJctUGFNK2ySsI/enTJ9StWxcfP34s9n1FuwxLWbBgAerVq4fg4GBs2LABa9euhZmZGZYsWSIozrBhwxAVFYW+ffvKtGlCdfkAdkkCVshrAsEaFkLkeXl5cHR05CZfyhuhZgeFna/FwGoyWN7EV3k4Kb579w7BwcGwsLCAhYUFkpKScOHCBYwfP15wLFYoUyJW2ahONCk5c+bMAVAgUhwREYGBAwdCIpHg6NGjsLW1xZ49eyq4hFWHmJgYmJqayqyUSE1NxfPnz2FgYCB4hcSff/6JLVu2ICMjAw8fPsTDhw9llp7zRarLBECuLXhAgXZDWloavvnmG9SpU0fwUuHysE1mASvbbWWc/S8NMU5NVQ0WbibSwc/q1auhqqqKSZMmgYgQEBCAvLw8TsCaL/r6+rhx4wYsLCwQFxeHhIQE+Pj4CN6mmpycjMWLFyM+Pl4m8Sn03uvcuTMiIiJktJ5sbW0FzwBKHUKl5hTZ2dmiHELd3NyKHJNIJIKSH8qIdPVpr1698Pvvv6Nly5YwMzNDUlKS4FisBpvFJayEtt+sEztSZzhPT084OTmhf//+1W3ZV3h4eODOnTsYNGiQ3G6BJSGkHhgaGuL06dMyOiSOjo68t3RJr6WiosL1Y6SI7c+wIDc3F6tXr8bhw4dBRJwshdCtOCU9I8Rsp1a2FeMWFhZYs2aNjAnETz/9xNsEgjU//vgj3Nzc5NZltLKywuXLl2X62OXF9u3bebmPyrtFtbwmg+VNfFVllC0Rq2xUazQpOdJl8g4ODoiLi+PEBpctW1ah2VuWnDp1CjNnzsSjR4+Ql5cnVyJFHqTbP1asWFHssn6hiaatW7ciKioKVlZWAAqWwr99+1ZwufLz8wWfUxLyzgIpq0h1eHg47t69K7cGzdq1axEbG4vevXsjJiaGm/1XVv7ND32WbiYNGjSQGfwUXkkqkUgEJ5rU1NSgpqaG/Px8EBH09PTw8OFDQTGAgpU/3bt3R0REBNasWYMtW7YIcnwpTOFVomJXjLJyCGUpUK1MjBw5EikpKfDx8YG1tTVycnLg5+cnKtaMGTOQmpoKPz8/mcGmUKTaI+3bt8e6deugra2NjIwMQTGOHz8OAMzEiPX19dGnTx/cu3cPq1atwufPnwWdX9KqGCkVtTqGJdnZ2Wjfvj0Tt8CSEDLPLK8OiTShxbI/w4IaNWpgwYIFJUo0rF+/HjNmzCgzzqJFi+ROWEiTBN9++y0aNmwIU1NTJCYmyhWTBfKaQLCCtS6jmZkZ+vfvDxcXF5lVaEJWsPN1muWTZAIKEszdu3fnFhFs3rwZkydP5r1FlbVjMSttNoCdk6Kurm6xbWFFrfiT1423qlOdaKokvHz5UsbRonnz5pzNfWXHy8sLGzZsKLLfuqJ48+YNGjRogH379mHQoEH47bffYGJiwls/QkqtWrVQu3ZtmWNi9RZYbMEDCvaev3r1CgkJCejVqxdyc3MFdfyUVaSale32N998g4YNG3Lb73r27ImZM2fKHbca9rB0M2E9+KlduzZycnJgZGQEb29vaGlpiUqcP3v2DPPmzUNwcDAGDBgAR0dHWFtbw9fXV1Ccdu3a4eeff4aHhwcAYNu2bZz5ghBYOoRWpi2qfJk1axaAgomh9+/f48uXL1BXVxcUg/Vg08/PDx8/fsSqVaswZcoUfPjwAX/++aegGKwTO4GBgTh16hQMDQ1Rp04dvHjxAitWrOB9/teJ4cJU5OoYligiGbt8+XLen1U2QWhFsXPnTl6JJh0dHUyZMgWTJ08WrdPEOknAChYmECxYt24d03jSFb3btm3jjgk1N2DtNPvs2TOZpNL8+fN5rxQG2E8Gy5v4ksLS3EI68QEAX758QVBQEBo3biw4DiuUJRGrrFQnmioJWlpaWLx4MaepsX37dmhpaVVwqdigoaEBR0fHii4GR05ODgDg4sWLcHJyQs2aNUUlwJo0aYIHDx5wmffAwEC0atVKcJzCW/BcXV2RkpIiagseAOzfvx+zZ8+GRCJBUlIS/vvf/2LBggU4ceIEr/PLwzaZBaxst1nM/iuSf/PO5/JwM2HFX3/9hezsbKxZswY+Pj6IjIxEUFCQ4DjSLWpqampISUlBw4YN8e7dO8FxNm/ejOnTp8PExARAgf5LYecwvrByCC1pi2plTTSVtQVRyKwt68GmdPtE/fr1cfbsWVExWCd21NTUZCzFW7RogRYtWvA+/9atW6JF8SsTYpOxNjY2pa5+kuqiCG03W7duzSUdi9tGWRXh+4w9e/Ys/vrrL3Tq1AkODg7w9PSEubm5oGsp64rx9evXF2sCoWikuwpK0mUUuutATB/6a1g7zRIRXr9+LbNFVUg/j/VksLyJLyksnRS/TnCbmprCysoKixYtEhVPXpQlEausVCeaKgmBgYEytuv29vZKvaVHCP379+fcdZSB4pb1i1myvm7dOowaNQr3799Hy5YtoaGhIZOJ5wurLXhAwWz5zZs3uQbR0NCwROeN0mBpm8wCVrbbLGb/FYmQGemqhtTNJCcnp1hHk4pMWkgHwXXr1pWZLRVK+/btkZKSAhcXF5ibm0NDQ0OwwxtQkPQOCQkRXQ4pK1asgKWlZRGH0IyMDIwYMYJ3nMq2RbUsSuvQC9UwYjXYZGkkomzbncaOHYubN2+ie/fuSqufJy/yJGO9vb0BFAykb968iQkTJkAikSAgIED01tt/qw4J376fnp4e1q1bh+XLlyM4OBg//PADmjZtilmzZmHUqFG84ijrivGmTZsiIiKiiAlERbFx48YiiaZNmzYJNgDJzc3F+vXr8fDhQ/z55594+PAhnjx5IlrbiIXTrLxbVFlPBsub+JKioqICbW1tbreAi4sL1q5dKzhOcaSkpOD169dMYolBWRKxykp1oqmS0KxZM8HCxpWF9evXIy0tDbVr1+ZWlAgRqGaNvMv6pbRt2xbR0dFISEjgdFrErIxiuQVPVVW1yBJT6aoJlih6pQ2LmSmAzew/C8prRroqERwcDGtr62I7K2KSjCzp27evzHLud+/eYfz48YITzcHBwQAK9Hq6dOmC1NRUODk5iSrTyZMnkZiYKOPKWJa+xNcMGjQIVlZWnPZAYYfQkjROiqOqbVFlpV0EsBtspqenAyjZSKQy8+XLF4SGhuLly5dKl2RmhTzJ2H79+gEAfH19cfnyZa6/MHz4cPTs2VNUeap1SMqGiHDmzBmEhoaiXr16nJNxWFgYL8dRZV0xbmpqysQEQl5Y6jICgKenJ/Ly8rhkdePGjTFixAhu4lIIJTnNCk00sdqiymoyWN7ElxSpe6aWlhYOHToEHR0dpKamCo4DQMYZPC8vD0+ePMHcuXNFxWKBsiVilY3qRJOSs2vXrlLfF2PfrmzIK1DNGnmX9X9N/fr1kZuby2lqCd0+x2oLHgCoq6vjzZs3XKyIiAg0atRIVKzSqAiRahZCg6mpqZg/fz4iIiIgkUhgb28Pf39/NGzYkHVxS6U8ZqSrGtKVQqySjCx59eqVTEJXU1MTL1++FB3v48eP6NChA/f/Qu/ZMWPG4O7duzA2NpZxZRRDkyZNMGDAAFHnSqlsW1SFEBUVhfDwcEgkEtjZ2QnePsNqsFmVjURWrlyJzZs34+3bt0USzRWdZGYFi2Ts+/fvZe5zFRUV0RN4/1YdEr6TZitWrMDWrVvRqVMnzJs3Dw4ODgAKEnRC9fCUbcU4KxMIeWGpywgUtNVxcXFcn6pBgwacdIZQ9uzZwznNHjhwgHOaFYMitqjyrdesEl+szC0AWa2uGjVqoHXr1qI0a1mhLIlYpYWqUWqGDRtGw4YNIwcHB6pVqxbZ2tqSnZ0dqampkaOjY0UXjxmfPn2iyMhIioyMpE+fPlV0cZgQEBBA6urq1KhRI9LU1CRNTU1q0qSJ4DiJiYnUpUsXql27NmlpaVHHjh3p0aNHosp0/fp1MjY2pvr161O3bt3ou+++o9jYWFGxSsPY2Jh5zNI4duwYNWvWjGrVqkWNGjUiiURCOjo6guMMHDiQpk2bRnFxcRQXF0eenp40cODAcigxP8zNzSknJ4f7d1ZWFpmbm1dYeZSV7OxsSkhIoPj4eO5Vkejr6xf53Tp16iQ4TkhICDVp0oRq1KhBNWvW5P4rFD09PcrNzRV8XnkRERFBHz58oP/9739kZ2dHXbp0obNnz1Z0seRm9erV1KpVK5o5cybNnDmTtLW1ac2aNeVyLb5tbHH1TkxdVEa8vLwqugjlhqWlJeXn59OQIUNo7dq1dPDgQWrXrp2gGFOnTiU7OzvatWsX7dq1ixwcHGjatGmiymNlZSVzj4aHh5OVlZWoWJWJuLg4Xp/z9PSkhISEYt+7ceMGyyKRkZER03hiridtf/T19RVaFiKiEydOMIkj7UtJ/77c3FzRf4+pqSkRERkYGFB+fj4RERkaGgqOExkZSc2aNSMjo//X3p3HRVmu/wP/DLiioqZYnWNfQS2UREAs2ZRMFMwMcgk1cUPcU8PdUlNTMg8qWia5YIHLyUwt9+PacUFDhPTgQoLRUVESXFCR7fn94Y/nOIE6yz3zPDN83q9Xr2RG7rnUYWae676v63KX3N3dpRdffFE6duyYQTE9jT6f0Y25Pps/f74kSY/e80W7cuWKdOXKFeHr6mvKlClSXFycVFpaKpWUlEjffPONNGnSJGnr1q2Sr6+v0uEpjokmCxESEiKdOXNG/vrs2bNSjx49FIxIHHO9sJpb06ZNpfPnzxu9zu+//y5lZGRI586dk/7zn/9Ily5dkm7fvm3werdu3ZJ27twp7dixQ8rLyzM6vooo8UHo8uXL8uPGx8dLEydO1HudFi1a6HSbubz88staCYKioiK9Lzasnagko0iTJk2SQkJCpIMHD0oHDx6UQkJCpEmTJum9jpOTk/TLL78YHU9gYKBFJfCXLFmidAgGefnll6U///xT/vrmzZsm+3nV9TU2MDBQmjlzppSVlSVlZWVJs2bNsqpNKmslIhlbVFQkffHFF1KPHj2kHj16SMuXL9dKgOvjl19+kf7v//5PcnJykhwdHaUmTZoIT6Ao4dSpU1JgYKD08ssvS05OTvJ/hsjPz5f+/e9/S0eOHJHy8/MFR/o/5t7Ia9mypXTx4kX564sXL0otW7aUJMmwZIqhDh06JEmSJG3btq3C//QVEREhxcfHS61bt5bS09OloUOHSmPGjDEoNj8/P6mwsFAKCwuTIiMjpUWLFhmUtGrXrp105MgR+eujR4+aZHNR1+eQsddnZY8j8jmblpYmubi4SPXq1ZPq1asntWrVSjp37pyw9fWltkSs2rB0zkL89ttvWlNWXn31VaNGHquJtdb+N2zYEM7OzkavI/pY5u3bt3Hz5k1oNBrcvXsX9erVMzrGvzJ3k2pRjQb/9re/IScnR+47k5OTY1TZpLECAgIQFBQkl8gmJCSgc+fOisWjRiKnmYgyb948zJ8/X+4b8M4772DKlCl6r/PCCy+gbdu2RscTHR2NgIAAvPHGG1pTGfVpCG1Ouo4UVxt7e3utksnnnnsO9vb2JnksXUsfHx8kUlbOZ8mN1x+3e/dujB8/HhkZGSgpKZH7O+o7BU+NRPQLrFKlCkaPHo1Ro0YBMK6k3Vr7kAwcOBBjxoyBt7e3QT00yxw4cAB9+/aVS1SvXbuGDRs2oGPHjqJCVYyoIRDGEt2XcdGiRZgwYQKys7Ph6+uLkJAQfPbZZwbFJmrSrLlKVCUdS+eMvT4zxSTFUaNG4aOPPkK/fv0AABs3bsTIkSMVa6MgahqvtWKiyUKU1SAPHDgQwKMP4rVr11Y4KjGstfY/JCQES5YsQb9+/bQu7vS98BBZH79+/Xp88MEH8Pf3hyRJGD9+PJYtW4Y+ffro9P1qbVItqtFg/fr14erqKjdT3blzJ9q3by83TV60aJG4oHWwdOlSxMbGYuvWrQAePaciIiLMGoPamXKaiaGqVq2KWbNmGT36eNiwYZg/fz569eql9Rqib4+2adOmoVq1aigoKDC4B4U56fohWG3efPNNDBo0COHh4QAeJXkCAgLw66+/AtC/Z5wI1jxIZOzYsVi2bJnRSQI1Ki4uxubNm3Hp0iWtBv76JIevXr2KoUOHyhdgnTp1wsqVKw3qZ2KtfUhsbW0xfPhwo9cZN24cfvzxR7kn28mTJxEeHo4zZ84YvfZfmfv1UdQQCGOJ7stYUFCA2NhYxMbGyrf9+eefeo+mLykpQXx8PBYsWGD0pNnatWtj37598mTo/fv36x2PLnTdDDb2+swUkxTz8vLkJBMA9OnTx+AEoQhqScSqFRNNFmLNmjUICwvDsGHDoNFo4OHhgW+++UbpsIQw1wuruX300UcAHu0IaDQag3db9+zZI7+IajQaDBgwAG3atMHnn3+Ojz/+WK+15syZg6SkJLnB4OXLlxEUFKRzokmtTapFNRp0dXWFq6ur/PWIESNEhqk3kTvS1krkNBNjbdiwAX379tWaiPM4fSfQPHz4EJ9++in+8Y9/aDXxvnHjhl7rXLhwARcuXNDre5Rkqc/zTZs2AQAOHz6sdfs///lPaDQaZGRkCHusZ11sHj58GP7+/hVOZQOsYzKbvb09AgMDlQ7DJPr06YPs7Gy8/vrrBifRhg8fDj8/P6xfvx4AsGLFCgwbNgw//fST3muppSG0aL6+vkhKSjL65KiNjY1W439j/t2exdwnxgExQyBEEjH8pUuXLkhOTn7mbc9ia2srLPkVExODnj17wtbWFtKj9jbYvHmzzt8vejPY2OszU0xStLW1RVpaGlxcXAAAaWlpim40qCURq1ZMNFkIZ2dnnDx5Uh5ZXKdOHYUjEufxF1YAKC0tNeg4pdqUlpYKWUfksUw7OzutKRbenOB0AAAgAElEQVSOjo6ws7PT+ftNMTbZGFFRUZg2bRqef/551K9fH56enkaVlD7rBEpMTIxZS3pE7khbK5HTTIx1/vx5ANCaiFPGkOTJ/PnzcebMGTRr1syouJydnXHnzh2TlXHRI5mZmWZ7rGddbIouM1Gjt99+G1u3btWaEmstzpw5g/PnzxuVdP3jjz+0kkpTp041+OSRyA0vNSgbkV5UVISVK1eiefPmWqdG9U02dOnSRavqID4+Xp48pyu1nhhXm+3btyMiIgJ5eXmoVasW8vLy0KRJE51ffwsLC1FQUICSkhLcvXtXTtrfvn0b9+7dMyimt956C/PmzcPgwYO1qk30fc81tkRV9GawsYmvMiInKc6fPx8dOnSQE4tnzpzBunXr9I5JJLUlYtVEI1nqGfVKoizBUHb0/q+UOIpvCkVFRfKOu7Ozs3xKwdKdOnUKaWlpCAsLw61bt/DgwQO9kwTbtm1DeHh4uWOZnTp1wrJly/TKmM+YMQO2trYYOnQoJElCXFwcSkpKMGHCBAC6vym+8sorOHfunJzoKi4uhouLCy5evKjXn81Ybdq0QXJysvx/cz2euXTv3h3e3t7yiaYVK1bg6NGjBu1IW5uyJOOBAwfkfiZq8eeff6Jhw4bPvO1ZfH19cfToUaPjCQ0NxalTp9ClSxetiylzl4LqysPDo8JknSW4c+cOLl++rFXu1KZNG52/X9eLTXq0W3779m3UrFkT1atXl08N5+bmKh2a0QICArBjxw5Ur17d4DXc3NywZ88evPDCCwCA7OxsBAYGGtTDzsXFBdu2bdPa8AoODkZaWhrc3d2RkpJicJxK+Oupw7/y9/fXa72y52LZZ9eioiLUrVsXAHR+Tu7YsQPAk5MECxcu1Csma+Xh4SEnmB/vy6jr38/s2bMxe/ZsudKgjL29PSZMmIAZM2boHZONjY38a2MqGBwcHISUqHp5eWltBhcWFqJDhw56977NysqSE3OPJ75Eb1rp+55/48YNnDx5EsCjP6u+n63IfJhoUrm3334b27dv1zqFUkb0UXxzu3PnzlPvt/Td9+XLlyM2Nhb5+fm4dOkSLl26pHU6RR85OTkVHsvU1+Nvhn+lz5viqFGjkJ6ertWkunnz5vjyyy8NistQfn5+qFOnDhITEytsuin6ZJy5L4Ar+gBviR/qTcHcSUZ9VBSTIXHOmDED9+/fR2hoqFaCSN8NhtmzZ1d4u7E9pEwlNTVVTqxbksWLF2PmzJlwcHDQKnXUJwFviovNTZs2yQ2lAwMD0bNnT73XUKPff/+9wtubNGli5kjEGzFiBFJTU/Huu+9q/ezrU34bHx+PyZMnyydgdu/ejYULF+L999/XOx6RG15qsmbNGgwZMuSZtz3Lk56LZfR5TopKElgrT09PnDp1Cq6urnIPrLLb9DFy5Eh89dVXpgjRYFOnTn1iierChQt1LlEVtRksKvH1LGr8HEdiMNFEirGxsSm3o2DMToDauLu74/jx4/Dx8ZGTE61atcLZs2cVjsx4xcXFiI2NlXfXAwICEBERIX8wMpe8vDzs3bsXkydPxpw5c8rdX3aMXRRzvxmK3JG2NuZOMuqibOevffv2OHLkiNaR/ICAAL37JJlrg8HcJaHJycmYPn06MjIytE7+WPLGCQA0bdoUR44ckSdPGUPUxeacOXOwdetWDBgwABqNBvHx8QgJCbHIcqeK3L9/X068u7u761UKrmaDBw8ud5tGo8GaNWv0Wufs2bM4dOgQgEen5V599VWDYxK14aUmFb2nG5K0AMQ9F9VyYlytvLy8kJiYiK5du2LYsGFwdHREz5499X7/eLwlRZnjx4/D29vboLhEVDBUtJlZ9hx9PLH2LKI2g0Ulvp5Fl8/W/v7+OHz4MOrXr6916teaTrJaI/ZosiClpaXIzs7W+mCu7/QhNRHVw0itqlevjpo1a2rdZu5EjKmopUm1ro0GLdXEiRPh4eFRbkeaTDPNxFhRUVHykfyysgngf0fy9WWunj/ffPONWRNNokaKq83f//53IUkmAMjNzdV6XbWxsTHog/T333+PxMRE+aJ36NCh8Pb2topE07Fjx9CzZ085EX/9+nVs3rzZ4AtFtSgpKcHbb78t5ORZ06ZN5dPjFSWu9WFNfUhOnjyJ48ePIycnR2t4w+3bt/Hw4UO91xP5XAwICEBQUJBWkqBz5856r2OtRPVlfPPNNxEdHY333nsPAPD5559j5cqVBvX5fLyCISwsDDdv3jSogkFUT1ZRE4vN1ZtNlzMvGzduBACe6Lcw1nHVWwmsXbsWY8eORdWqVeXyJ0OmD5H5ODg44OLFi/LFwtq1ay06Mfg4tTWp9vf3x8KFC7XKQ8aNGyc8sWfuA6BhYWHw8PCQd6QnTJhg1I60NTHFNBNjzZo1C7NmzTL6SP69e/dQq1atJ5YXiy4rNvfzWtRIcbWZPn06xo4di7ffflur3MmQQQmiLjYlSdI6WVGrVi2z/3ubSmRkJL7//nt5/PaxY8fw4YcfWnyJka2tLebNm2d0oslaE3EiXLt2DSkpKbh//77WCRJ7e3usXbtW7/VEPhdFJQmsjejhL4cOHUJoaCgOHDiAK1euAABOnDhh0Fpff/01EhMT4ePjAwBo1qwZcnJy9F4nKioK3t7e5UpU8/PzERoaqvM6ojaDRQ4jehpdJimWXV9YQ2l0ZcLSOQvRrFkz7Ny5E87OzkqHQjr67bff0LdvX/znP/9BgwYNYG9v/8R+W5ZGbU2qx40bh99++w0RERHQaDRYtWoVnJycnjhm/knKev48bsuWLXj33XcBKNM7xlpLQ8zFEmv/y2J+Unmx6LJic/8djR49GoMHDzZ6pLjazJw5E0uXLkXTpk21ejSVNS3Vh6jy5PDwcBQWFsoXqqtXr0aVKlWwevVqvWNSGzc3t3JlxNbSw27o0KEYNGgQ/Pz8DF7Dy8sL0dHRWsmPyMhIi0/EibRr1y4hU9xM8Vwse91X6sS42piiL+Phw4fRpUsXNGzYEKdPn9Zrwtvj2rVrhxMnTmiVvhn67y+iRFXUZrCxvdlMMdzCycmp3Jr16tWDt7c35s6di+eee07vNcl0eKLJQjRs2JBJJgtTrVo1fPfdd3j48CFKS0tRo0YNNGjQQOmwhBA5NlmEgwcPIiUlRT7t161bN70mPZUJCwvDrl275JNne/bswfTp0+VEk7mTTNyRNp4591JE9RAo+xBtbeXFokeKq823336Ly5cvo169ekavJWpHeunSpZgzZw4iIyMBPEpYGTJVSY1q166Nffv2ISAgAACwf/9+1KpVS+GoxEhMTMTatWvRtGlTrXHp+vyMPHjwQE4yAYCPj498GqGyO3z4MPz9/VFUVIQff/yx3P3vvPOOXuuJfC6q7cS4WtjZ2aFr167IzMxEjx49yt2vb1/G6OhoLF++XB684OXlhbi4OL0nDgJiKxhElKgOHz4cfn5+WL9+PYBHm8HDhg3TezM4ODgYPj4+FSa+dBkAMHHiRABPHm5hiP79++PKlSsIDw8HAMTFxaFevXqQJAkjRozAd999Z9C6ZBpMNKlcWelESEgIlixZgn79+ml9MLf0yWzWzNPT0yzTGpQgSRKys7O1mlQreThSkiSUlpbKiSZJkgyKZ8WKFQgJCcGhQ4eQmpqKMWPGYM+ePaLD1Zm1loaYkzl3gy21h4C5fnaXLFlilsdRSpMmTYQkmQBxF5s1atTAggULhMSkNkuXLkWPHj3k02OlpaWKDAEwBRETXK05EWeshIQE+Pv7Y/HixeXu02g0eieaRD4XRSUJrI3ovoz79u3DyZMn0aBBA/j4+MDHxwd9+/bVe2gH8Oi9rW/fvjh//jxeeukluYJBKSI3g41JfHXr1g0AMHfuXK3hFr179zaopBwA9u7dq1Xi6OPjg3bt2uHkyZNwcXExaE0yHSaaVK5evXpapRORkZFWNZnNmoWHhz9xWsOYMWOETWtQgtqaVAcFBaFLly4YNGgQgEcnCww5Dt++fXtMnToVXbp0QW5uLrZv346mTZsKjlZ33JG2LGruIXDt2jVcuHABb7zxBoqLi1FaWionwQ3pSWKIsp3iJ40UN2QnWU1ee+01vPfee+jVq5fWhpC+F62AuIvNxo0bIywsDIMHD0bLli31jkPNrl69iqSkJFy/fh0A8PzzzxtUpqhGZadtsrKy0KxZM4PWiImJQc+ePWFraytvvmzevFlwpJZp5cqVAKB3s+YnEflcVNuJcbUQ3Zdx586dWhtRbdq0QVJSkkGxNW/eHCdOnMCFCxcgSRKcnZ0VHXShts1gUcMtyta6f/++3Ebi/v37uHXrFgBove+SOrBHE5GJiBpTqlYixyYbq7S0FF9//TX27dsH4FF5yLBhw+QTTs/y115O3377Ldzc3ORSubFjx4oNWEe+vr6YPXu21o70zJkzcfToUUXisUQV/Rya8rGedoJKqdKw77//HhMmTIBGo8Hly5eRmpqKadOmYefOnYrEI3KkuJp07Nix3G0ajcagPhQV9fcwpOfH5cuXsXbtWnz77bdwcHDAkCFD0LdvX6s4Df3Xvw9JkuDp6WnxJZjAo0bF/fr1Q5UqVZCVlYVffvkFMTExSEhI0HmNrKwsFBYWoqCgABqNBtWrV0ejRo2s4t9epKKiImRmZmpt4rRu3VqvNUQ+F93c3LBnzx6tJEFgYGC5HlBUMV17ON2+fRsfffQRLl++jO3btyMtLQ2pqano27evQY+rpsng8fHxmDx5crnN4Pfff1+ReEaNGoX09HSt4RbNmzc36OTmrFmzsGXLFjmZuHnzZgQHB2PSpEkYMGCA1ZxqtRY80URkIuaa1qAUkWOTjVFSUoLp06djwYIFGDFihEFr/DUR4erqitLSUpw+fVrRRpzckTaeLtNMRFFraVhUVBSSk5PlhKWbmxt+//13s8cheqS42og6HQGI25F2dHTEJ598gk8++QSHDh3CihUrEBkZiXv37gmLVS2s6ZT31KlT8e9//xu9evUC8Oi0nL4Jc2su3xdl+/btiIiIQF5eHmrVqoW8vDw0adIEmZmZRq1rzHNRbSfGLY2ur5PDhw9Hq1at5A1TJycn9OvXz6BEk9omg6ttYrHISYqzZ8/G66+/Lm/gzJs3Ty7RY5JJfZhoIjIRUWNK1UhNTaptbW2NvsCLi4sTFI1YjRo1wv79+8vtSJPu00xETBTS1V9Lv65evQoA+Nvf/ma2GCpia2tbbhBB2cWnOYkeKa42xcXFiImJwaVLl7B8+XJcunQJv//+O95880291xJ9sXnq1Cls2rQJBw4cqPDklSWqU6cOjh07Jo8UP3r0KOrUqaNwVGKUlJSUK5nT92fWmsv3RZkxYwYSExMREhKC06dPIyEhwaCTQyKfi2pLElgaXTcHL168iI0bN8qbdzVr1jS4vGzu3Ln45ZdfVDW0SS2bwYC44RZlunXrJieXSN2YaCIyEWOnNaiZ2ppUv/XWW5g3bx4GDx6sNaFH1xKBiqbOPM6QHisicEf6yUwxzUSUc+fOoVevXnKiqXHjxti0aRNatGihSDx16tTB9evX5Q93+/fvV2QEcHBwMIKDg4WNFFebMWPGoKSkRL6Ab9CgAUJDQw3q+yHqYjM6Ohpr165FcXExBg8ejNTUVKuZXvX555/j3XfflX+u0tPTsWXLFoWjEqNGjRrIz8+Xf2bPnDmDmjVr6rXGnj178NlnnwF4dGE3YMAAtGnTBp9//jk+/vhj4TFbIhsbGzRp0kQud+rfv3+FDcKfRfRzUU1JAmv118TtgwcPDE40qW0yuJo2gwExwy0mTJiA6OhovPvuuxUmqniaSZ2YaCIyIRFjStVIbU2q58yZAwBaY7v1Obr+tA+WhkygEYU70k9mimkmoowaNQofffQR+vXrB+DRNLqRI0cKLa3Sx4IFC9C1a1dkZGTAz88PmZmZ2LFjh9njED1SXG0SExORkpIiJzrr1auHoqIig9cTcbF54cIFrFy5El5eXgbHoVbe3t44d+4cjh8/DuDR+5CoqX9KmzFjBrp06YIrV66gf//+2Ldvn9wYXlfWXr4vQtWqVQE82gzYsmULHB0dkZeXp/c6Ip+LaksSWBpdk0UdO3bEvHnzUFBQgH379mHx4sXo0aOHQY+ptsngatsMFjHc4o033gDw6O+aLAebgROR3tik2jysvaG8CK+88grOnTsnXzgVFxfDxcUFFy9eVCwmUY2cRbp9+zaOHTsGSZIUuyCPiIjAypUrhTbNVhMvLy8kJibKP7clJSVwd3c36OdU1MXm9evX8cknnyA1NVVrM8AaGmZbu8zMTOzevRuSJCEwMFDv6XPbtm1DeHh4ufL9Tp06YdmyZRZ/slqEDRs2ICgoCBkZGejTpw9u3bqFmJgYeZNACV5eXoiOjtZKEkRGRiqWJLA0up6YLS4uxsKFC7F161ZIkoSQkBBMmTLFoCTs44Nn1DAZ3M3NrVwJqJKfQdT4mYjMgyeaiEhvamxSnZWVhZ9//hkajQYdOnTASy+9ZNA6IibQiMId6WcLCAhAUFCQ1jSTzp07KxqTra0t0tLS4OLiAgBIS0tT/N+rbt26iperiR4prjatW7dGQkICSktL8dtvv2HBggXyLqy+RO1IDx06FH5+fti/fz+io6MRGxureGkpPVthYSGcnJwwcuRIZGRkIC0tDY6Ojnq9jlhz+b6xoqKiMG3aNDz//POoX78+PD09kZ6ernRYANR3YlwtRPdlrFKlCqZNm/bEn4WYmBiMGzdOp7VKS0t1+n3mUrt2bezbt09rM7hWrVqKxSNiuEVkZORT71+0aJHB8ZHpMNFERHpTW5Pq9evX44MPPpBLpsaPH49ly5ahT58+eq1jqgk0hrLmhvKiiJxmIsr8+fPRoUMHtG7dGpIk4ezZs1i3bp1i8djY2JT7gF63bl14e3vjyy+/hKOjo9ljUlNCV5SPP/4Y8+bNQ3Z2Nnx9fREcHIwpU6YYtJaoi80//vgDU6ZMQUJCArp3747AwED4+/tj7ty5BsVF5uHr64sDBw6gsLAQ7du3h6OjI7Zv344VK1botY61lu8ba9OmTZg2bRomTpyoutN9aksSqIW5+zJ+8803OieagEcDF9LS0hAWFoZbt27hwYMHivXDU9tmsIjhFnXr1jVFaGRiLJ0jIr05ODioqkl1ixYtsGvXLrmPyeXLlxEUFITz58/rtY6Hhwe2bt1abgKNkqOFc3JyKtyRJm1lb2XGTjMRJScnBydOnADw6N+tYcOGisXy6aefori4WE7ArV69Gg8fPsTzzz+PHTt2YM+ePWaNR20JXVHKylqfdZsuRJUnv/766zh58iRee+017N69G/Xr14ezs7NqTm9QxcrKL7/99lucP38e8+fPZ7m0QH5+fqhTpw4SExMrLOVVsrFwUlJShUkCT09PxWJSEy8vL62+jIWFhejQoYPw0sKKWhc8yfLlyxEbG4v8/HxcunQJly5d0mp+bW5ZWVkoLCwstxmsVM8oADh79qw83KJjx46cpFhJ8EQTEelNbU2q7ezstJrlOjo6ws7OTu91RE2gEYk70k8nYpqJKTx48AC3bt2CRqPBgwcPFI1l69atWpPPZs6cibZt2yIpKQlff/212eMRNVJcLco+0JeUlODu3btyf45bt27h3r17Bq0pakf6lVdewc2bN9G/f3+0a9cO9vb2vGC1AIWFhQCAQ4cOyf2ClC6/tSY//fQT9u7di7S0NAQHBysdjha1nRhXm9zcXK0NJRsbG+Tm5gp/HH02rb7++mskJibCx8cHANCsWTPk5OQIj0lXapxYLGqS4h9//IGRI0fiv//9L1JSUpCSkoKDBw/iww8/FBUqCcREExHpTW1jk7t164ZPPvkEQ4cOhSRJiIuLQ/fu3eU3NV13cURNoCHzETHNRLSyUk5/f39IkmRwKacod+/eRU5OjnwaLicnB3fv3gXwv+e8OakxoWuMqKgozJ49GxqNRut4v729PSZMmGDQmqIuNhMSEgAA48aNQ9u2bZGXl4egoCCDYiLz6dixI1xcXFBSUoLY2Fjk5eXJJzjIePXr10doaCgaNmyITp06PfH3bdq0Cb179zZjZOpMEqiJGvsyVq9eHTVr1tS6TcmfV7VtBoucpDh8+HD069dPrjRo1aoVwsLCmGhSK4mISE8tW7aULl68KH998eJFqWXLlpIkSZKbm5vZ49FoNE/8z8bGRud1vv32Wyk3N1dKSkqSmjdvLjVs2FCKj483YeRkrIqeb0o8Bx/n7OwsZWRkyF9nZmZKzs7OisWzYsUK6cUXX5SGDBkiDRkyRPr73/8uffXVV9Ldu3el0aNHmz2edu3aSZIkSUFBQdIPP/wgJScnS05OTmaPQ7QRI0YIW6thw4aSjY2NVKNGDalGjRqSjY2NZG9vL7m4uEinT58W9jikTqWlpdLp06el27dvS5IkSTk5OVJycrLCUVU+Hh4eZn/MKVOmSHFxcVJpaalUUlIiffPNN9KkSZOkrVu3Sr6+vmaPR22KioqkL774QurRo4fUo0cPafny5VJRUZHwx3F3d9f593br1k26cOGC/HyJi4uTunfvLjwmXVUUe1lsrVq1Mnc4Urt27aQjR47IXx89elT+HKAvT09PSZK0/4z6/FuReXF7hIj0prYm1aImfixevBhhYWFaE2jatGmD/v37C1mfxJMETDMRTVQppyjDhw+Hr6+vXF744YcfolWrVgCAL774wuzxjBs3Dnl5efj000+1Ropbuq+++krYWmrbkSbz+uOPP/Dcc8/h1q1buHXrFgCgQYMGCkdV+SjxXqK2E+NqU6VKFYwePRqjRo0CYLq+jGvXrtX59y5ZsgR9+/bF+fPn8dJLL8He3h7bt283SVy6UNvEYpGTFKtUqaL1c5mXl6f4Zz56MiaaiEhv1jY22RQ9Vsg8REwzEU1UKadIrVq1kpNLSlHzSHG14cVm5ebp6QmNRgNJklBQUID79++jQYMGuHHjhtKhVSpKDJdQW5JAbUT1ZUxOTsb06dORkZEhl3EDQEZGBgDIG6m6qFatGr777js8fPgQpaWlqFGjhqKJYbVtBoucpNi7d28MHz4cd+7cwapVq7BixQoMHTpUZLgkEKfOEVGlN3v2bLnHyuMviWU9VmbMmKFgdPQsaptmYmNj88T7NBoNSkpKzBgNcOPGDcyaNQupqalau4jmHutdNoHN0ElslYmLiwu2bdumdbEZHByMtLQ0uLu7IyUlReEIyZx++OEHpKamYvbs2UqHUqko8Vq1bds2hIeHl0sSdOrUCcuWLbPIzTyRunfvDm9vb/lE04oVK3D06FG9+zK6urpizJgx8Pb21krgGfL5QW2TmAF1TSwWPUlxw4YN2Lp1KyRJQkhIiDwwgdSHiSYiov9v5MiRQstfyDzu378vX3i7u7srWqamRt27d4efnx9Wr16N6OhoxMbGwsPDA3PnzjVrHGoeKa42vNikvyqbFEnmo8+Ie5HUlCRQm4oS7YYk30Um7KdOnfrEUueFCxdW+lLnrKwsuXLg8eEW+p7uLikpwfTp07FgwQITRUqiMdFEREQWS+Q0E2tV9oHa1dUVZ86cQWFhIfz9/XH8+HGzxpGXl4e9e/di8uTJmDNnTrn7Bw4caNZ41I4Xm5VXWZkt8Oji6sSJExg7diwuXryoYFSVz65du+SybFIHNzc37NmzR6svY2BgIFJTU/VaZ/To0Rg8eDDatm1rdEwVJSTLTsOVve9WZiJPfL3++us4efKkqUIlwdijiYiILFZkZCS+//57udHksWPH8OGHH8oX6AT5w12NGjVw8+ZN1K9fH3/++afZ41DzSHE1cnBwQPfu3ZUOgxRQr149uZTb1tYWL7/8MpYuXap0WFajY8eOT+2/dODAAQBgkkmFjO3L6OHhAY1Gg6KiIqxcuRLNmzdHjRo15PsNKZVkX62nEznc4q233sK8efMwePBg1K5dW75did6X9Gw80URERBbLzc2t3E4me9ho69+/P2JiYpCQkIBly5bB3t4er7zyCjZu3Kh0aBViDyciMqUdO3YAAA4ePIjk5GQMGTIEGo0GcXFx8PDwUHygBD2dMX0ZDx8+/NT7/f399Y6Hpc5PJ/LE1+M9MMuS8Ur0viTd8EQTERFZLJHTTKxVQkICAGDcuHFo27Yt8vLyEBQUpHBUT8b9LyIypW7dugEA5s6diyNHjqBKlUeXQ71790aHDh2UDI100LRpU7m81MnJSa/vLUskrVmzBkOGDNG6b82aNQYlmqxtErNoIk98lZaWCo+PTIeJJiIislgxMTEVTjMhbVlZWfj555+h0WjQvn17+cJKjZQYKU5ElU9ubq7W642NjQ1yc3MVjIieRVRfxi+++KJcounLL78sd5uuWOr8ZFFRUfD29i534is/Px+hoaEKR0empN5PmkRERM/QqFEj7N+/v9w0E/qf9evX44MPPpB36sePH49ly5ahT58+CkdGRKScgIAABAUFYcCAAQAenf7s3LmzwlHR0xjbl/HkyZM4fvw4cnJytPqe3b59Gw8fPjRJzJUdT3xVXkw0ERGRxfL09BQ2zcRazZkzB0lJSXKJweXLlxEUFKTaRBNL54jIHJYuXYrY2Fhs3boVABASEoKIiAiFo6KnefDggZxkAgAfHx+5DEsX165dQ0pKCu7fv6/VN8je3h5r164VGSo9hie+KicmmoiIyGKJnGZirezs7LT6WDg6OsLOzk7BiJ5u/vz5SodARJVAlSpVMHr0aIwaNQoAy3YtgbF9GYODgxEcHIxdu3ZxqiCRiXHqHBERWSyR00ys1YwZM2Bra4uhQ4dCkiTExcWhpKQEEyZMAGC+scC6jhQnIjKHq1evYujQoTh48CAAoFOnTli5ciVefPFFhSOjJ0lKSqqwL6Onp6dO33/48GH4+/vjxx9/rPD+d955R2S4RJUaE01ERGSxXFxcsG3bNq1pJsHBwUhLS637lUUAAAu5SURBVIO7uztSUlIUjlB5j48D/itzjgXmSHEiUpPu3bvD29tbPtG0YsUKHD16FD/99JPCkdGTZGVlobCwsFxfRl03TCIiIrBy5Up07Nix3H0ajYYbHkQCMdFEREQWa9u2bQgPDy83zaRTp05YtmwZG02qkJeXl9ZI8cLCQnTo0EHnZq5ERCJUtBnBDQp1c3BwYF9GIgvBHk1ERGSxOM3E8nCkOBGpgSRJyM7OxgsvvAAAyM7O5jAClRPZl7GoqAiZmZlazcRbt25tirCJKiWeaCIiIiKzGTVqFNLT07VGijdv3hxffvmlwpERUWUSHx+PyZMny02hd+/ejYULF+L9999XODJ6ElF9Gbdv346IiAjk5eWhVq1ayMvLQ5MmTZCZmWmKsIkqJZ5oIiIiIrPhSHEiUoOwsDB4eHjg0KFDAIAJEybg1VdfVTYoeqqHDx8iPT1dqy9j2YkkW1tbndeZMWMGEhMTERISgtOnTyMhIQGpqakmiZmosmKiiYiIiMyGI8WJSC2aNm2KO3fuAACcnJwUjoaeJSoqCt7e3uX6Mubn5yM0NFTndWxsbNCkSRMUFxcDAPr374/FixebJGaiyoqJJiIiIjIbjhQnIjU4duwYevbsKfdoun79OjZv3gxvb2+FI6MnEdWXsWrVqgCAxo0bY8uWLXB0dEReXp74gIkqMfZoIiIiIrPhSHEiUgMvLy9ER0fD19cXwKPEU2RkJCdgVgIbNmxAUFAQMjIy0KdPH9y6dQsxMTHo16+f0qERWQ0mmoiIiMhsOFKciNTAzc2tXF8evhZZt6ioKEybNg0HDhzAm2++qXQ4RFbNRukAiIiIqPIoGylehiPFiUgJtWvXxr59++Sv9+/fj1q1aikYEZnapk2bAAATJ05UOBIi68ceTURERGQ2EydOhIeHR7mR4kRE5hQTE4OePXvC1tYWkiRBkiRs3rxZ6bDIhOzs7NC1a1dkZmaiR48e5e7/4YcfFIiKyDqxdI6IiIjM6uzZs/JI8Y4dO3KkOBGZXVZWFgoLC1FQUACNRoPq1aujUaNGsLe3Vzo0MpG8vDzs3bsXkydPxpw5c8rdP3DgQAWiIrJOTDQRERGRWd2/f1/ug+Lu7g47OzuFIyKiysbBwQG5ubmoVq0aAKCwsBC1a9dG48aNsW7dOri7uyscIZnK/v370alTpyfev2nTJvTu3duMERFZHyaaiIiIyGw4UpyI1GDq1Klo0aIFBg4cCEmSkJCQgLNnz8LX1xcLFy7EkSNHlA6RFNKmTRskJycrHQaRRWOiiYiIiMyGI8WJSA08PDxw+vRprdvKEgyurq44c+aMQpGR0ip6bhCRfjh1joiIiMzmwYMHcpIJAHx8fFBQUKBgRERUGT18+BDp6eny1+np6fJrka2trVJhkQpoNBqlQyCyeJw6R0RERGZTNlI8ICAAAEeKE5EyoqKi4O3tDTc3NwDAr7/+ilWrViE/Px+hoaEKR0dEZNlYOkdERERmk5SUVOFIcU9PT6VDI6JKJicnRy7b9fLygoODg8IRkRqwdI7IeEw0ERERkdlwpDgREanZrl270LVrV6XDILJoTDQRERGR2XCkOBERKaFjx45P7b904MABM0ZDZN3Yo4mIiIjMJjw8/IkjxceMGcOR4kREZBITJ04EABw8eBDJyckYMmQINBoN4uLi4OHhoXB0RNaFJ5qIiIjIbDhSnIiIlOTl5YUjR46gSpVHZy4KCwvRoUMHuV8XERnPRukAiIiIqPLgSHEiIlJSbm6uVgmdjY0NcnNzFYyIyPqwdI6IiIjMhiPFiYhISQEBAQgKCsKAAQMAAAkJCejcubPCURFZF5bOERERkVlxpDgRESmluLgYsbGxcvPvgIAAREREyKV0RGQ8JpqIiIiIiIioUim7DH7aJDoiMgx7NBEREREREVGlcPXqVbz11luws7ODnZ0d3n77bVy7dk3psIisChNNREREREREVCkMHz4cfn5+uHbtGq5duwY/Pz8MGzZM6bCIrApL54iIiIiIiKhScHd3R0pKyjNvIyLD8UQTERERERERVQqSJCE7O1v+Ojs7Gzx7QSQWW+sTERERERFRpTBx4kR4eHiga9euAIDdu3dj4cKFCkdFZF1YOkdERERERESVxtmzZ3Ho0CEAQMeOHfHqq68qGxCRleGJJiIiIiIiIqo0mjZtijt37gAAnJycFI6GyPow0URERERERESVwrFjx9CzZ0+88MILAIDr169j8+bN8Pb2VjgyIuvB0jkiIiIiIiKqFLy8vBAdHQ1fX18AjxJPkZGRSExMVDgyIuvBqXNERERERERUKTx48EBOMgGAj48PCgoKFIyIyPow0URERERERESVQu3atbFv3z756/3796NWrVoKRkRkfVg6R0RERERERJVCUlISevbsCVtbW0iSBEmSsHnzZnh6eiodGpHVYKKJiIiIiIiIKoWsrCwUFhaioKAAGo0G1atXR6NGjWBvb690aERWg4kmIiIiIiIiqhQcHByQm5uLatWqAQAKCwtRu3ZtNG7cGOvWrYO7u7vCERJZvipKB0BERERERERkDuHh4WjRogUGDhwISZKQkJCAs2fPwtfXF2PGjMGRI0eUDpHI4vFEExEREREREVUKHh4eOH36tNZtbdq0QXJyMlxdXXHmzBmFIiOyHpw6R0RERERERJXCw4cPkZ6eLn+dnp6OgoICAICtra1SYRFZFZbOERERERERUaUQFRUFb29vuLm5AQB+/fVXrFq1Cvn5+QgNDVU4OiLrwNI5IiIiIiIiqjRycnKQmJgIAPDy8oKDg4PCERFZFyaaiIiIiIiIiIhICPZoIiIiIiIiIiIiIZhoIiIiIiIiIiIiIZhoIiIiIjKRTz75RJ5mBAAzZ87EunXrFIyIiIiIyLTYo4mIiIjIRDQaDfLy8lCvXj2lQyEiIiIyC55oIiIiItLR+++/j7Zt26J169bo1q0bsrOzAQA7duzAa6+9Bjc3N7i7u+PEiRMYMWIEAKB9+/Zwd3fHjRs3MGjQICxZsgQAkJ+fjyFDhqBVq1Zo1aoVZs+eLT/OG2+8gYkTJ6J9+/Zo1qyZvBYArFq1Ci4uLnB3d4erqytOnDhhxr8BIiIioqfjiSYiIiIiHeXk5MhjsD/77DNcvnwZkZGR8PPzw88//4wWLVqgqKgI9+/fR926dcudaBo0aBDc3d0xfvx4TJkyBf/9738RHx+PBw8ewM/PD1OnTkVoaCjeeOMN1K9fH5s2bUJRURFcXFywfv16eHt7o27dujh//jxefPFFFBUV4eHDh6hdu7aSfy1EREREMp5oIiIiItLR+vXr0bZtW7Rq1QqrVq1CSkoK/vWvfyEoKAgtWrQAAFStWhV169Z95lr79u1DREQEbGxsUKtWLQwYMAD/+te/5PtDQ0NRpUoV1KxZE+7u7rh06RIAoFOnTggLC0NMTAwyMzOZZCIiIiJVYaKJiIiISAdHjhzB0qVLsXPnTpw9exaLFi3SavRtLI1Go/V1jRo15F/b2tqiuLgYALB582Z89tlnKCoqwltvvYWNGzcKi4GIiIjIWEw0EREREekgLy8PderUQYMGDVBYWIjY2FgAQGBgIPbs2YPz588DAIqKinD79m0AQJ06deRf/1VAQABWr14NSZJw7949xMfHo0uXLk+Nobi4GJcuXULbtm0xceJE9OrVCydPnhT4pyQiIiIyDhNNRERERDoICgqCs7MznJ2d5QbfANC8eXPExcWhf//+cHNzQ7t27XDhwgUAwIQJE9C5c2e5GfjjZsyYgapVq8LV1RXt2rXDO++8g/fee++pMZSUlMgNxN3d3XHq1ClERkaa5g9MREREZAA2AyciIiIiIiIiIiF4oomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIRgoomIiIiIiIiIiIT4f47pDde+W3taAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1440x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(num=None, figsize=(18, 6), dpi=80, facecolor='w', edgecolor='k')\n",
+    "\n",
+    "tags_2nd = [x[0] for x in all_tags_2nd_counts]\n",
+    "counts_2nd = [x[1] for x in all_tags_2nd_counts]\n",
+    "\n",
+    "'''\n",
+    "colormap={'vandalism':'#462E74',\n",
+    "          'hardcore_vandalism':'#18063A',\n",
+    "          'spam':'#665091',\n",
+    "          'disruptive':'#7F488C',\n",
+    "          'pov':'#9E72A8',\n",
+    "          'good_faith':'#737D15',\n",
+    "          'maintenance':'#AA9B39',\n",
+    "          'unknown':'#D4C76A'}\n",
+    "'''\n",
+    "\n",
+    "colormap={'vandalism':'#29506D',\n",
+    "          'hardcore_vandalism':'#042037',\n",
+    "          'spam':'#718EA4',\n",
+    "          'disruptive':'#512C73',\n",
+    "          'pov':'#9277AC',\n",
+    "          'good_faith':'#AAA439',\n",
+    "          'maintenance':'#D4A76A',\n",
+    "          'unknown':'#FFDBAA'}\n",
+    "\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel('actions')\n",
+    "plt.xticks(rotation='90')\n",
+    "plt.ylabel('Num filters')\n",
+    "plt.bar(tags_2nd, counts_2nd, color=[colormap[clusters[x]] for x in tags_2nd])\n",
+    "#ax.legend((p1[0], p2[0]), ('Men', 'Women'))\n",
+    "ax.legend(colormap.keys(), colormap.values())\n",
+    "#plt.xticks(matplotlib.dates.date2num(df_hits['LogMonth']))\n",
+    "#plt.setp(plt.gca().xaxis.get_majorticklabels(), 'rotation', 60)\n",
+    "#plt.grid(color='0.7', linestyle='-', linewidth=0.2)\n",
+    "\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>afl_filter</th>\n",
+       "      <th>count(*)</th>\n",
+       "      <th>manual_tags</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>135</td>\n",
+       "      <td>175455</td>\n",
+       "      <td>silly_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>30</td>\n",
+       "      <td>160302</td>\n",
+       "      <td>good_faith_deletion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>61</td>\n",
+       "      <td>147377</td>\n",
+       "      <td>good_faith_refs</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>18</td>\n",
+       "      <td>133640</td>\n",
+       "      <td>good_faith_test_edits</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>3</td>\n",
+       "      <td>95916</td>\n",
+       "      <td>good_faith_deletion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>172</td>\n",
+       "      <td>89710</td>\n",
+       "      <td>good_faith_deletion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>50</td>\n",
+       "      <td>88827</td>\n",
+       "      <td>not_polite</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>98</td>\n",
+       "      <td>80434</td>\n",
+       "      <td>good_faith_article_creation</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>65</td>\n",
+       "      <td>74098</td>\n",
+       "      <td>bad_style</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>132</td>\n",
+       "      <td>68607</td>\n",
+       "      <td>good_faith_deletion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>46</td>\n",
+       "      <td>47280</td>\n",
+       "      <td>profanity_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>225</td>\n",
+       "      <td>45462</td>\n",
+       "      <td>profanity_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>180</td>\n",
+       "      <td>37713</td>\n",
+       "      <td>good_faith_wiki_syntax</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>79</td>\n",
+       "      <td>36645</td>\n",
+       "      <td>good_faith_refs</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>189</td>\n",
+       "      <td>35683</td>\n",
+       "      <td>personal_attacks</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>149</td>\n",
+       "      <td>32336</td>\n",
+       "      <td>self_promotion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>9</td>\n",
+       "      <td>28972</td>\n",
+       "      <td>personal_attacks</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>129</td>\n",
+       "      <td>27780</td>\n",
+       "      <td>sockpuppetry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>29</td>\n",
+       "      <td>27130</td>\n",
+       "      <td>good_faith_template</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>148</td>\n",
+       "      <td>24914</td>\n",
+       "      <td>self_promotion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>231</td>\n",
+       "      <td>21507</td>\n",
+       "      <td>silly_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>220</td>\n",
+       "      <td>19946</td>\n",
+       "      <td>good_faith_external_resources</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>39</td>\n",
+       "      <td>18456</td>\n",
+       "      <td>profanity_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>80</td>\n",
+       "      <td>18189</td>\n",
+       "      <td>spam</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>12</td>\n",
+       "      <td>18159</td>\n",
+       "      <td>profanity_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>155</td>\n",
+       "      <td>17517</td>\n",
+       "      <td>general_tracking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>106</td>\n",
+       "      <td>14513</td>\n",
+       "      <td>hoaxing</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>96</td>\n",
+       "      <td>14399</td>\n",
+       "      <td>good_faith_article_creation</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>11</td>\n",
+       "      <td>14368</td>\n",
+       "      <td>profanity_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>28</td>\n",
+       "      <td>12264</td>\n",
+       "      <td>general_tracking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>189</th>\n",
+       "      <td>245</td>\n",
+       "      <td>7</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>190</th>\n",
+       "      <td>257</td>\n",
+       "      <td>7</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>191</th>\n",
+       "      <td>275</td>\n",
+       "      <td>6</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>192</th>\n",
+       "      <td>70</td>\n",
+       "      <td>6</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>193</th>\n",
+       "      <td>214</td>\n",
+       "      <td>6</td>\n",
+       "      <td>self_promotion</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>194</th>\n",
+       "      <td>207</td>\n",
+       "      <td>6</td>\n",
+       "      <td>good_faith_template</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>195</th>\n",
+       "      <td>38</td>\n",
+       "      <td>6</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>196</th>\n",
+       "      <td>57</td>\n",
+       "      <td>6</td>\n",
+       "      <td>doxxing</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>197</th>\n",
+       "      <td>49</td>\n",
+       "      <td>5</td>\n",
+       "      <td>spam</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>198</th>\n",
+       "      <td>69</td>\n",
+       "      <td>5</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>199</th>\n",
+       "      <td>109</td>\n",
+       "      <td>5</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>200</th>\n",
+       "      <td>20</td>\n",
+       "      <td>5</td>\n",
+       "      <td>silly_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>201</th>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "      <td>test</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>202</th>\n",
+       "      <td>127</td>\n",
+       "      <td>4</td>\n",
+       "      <td>good_faith_template</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>203</th>\n",
+       "      <td>173</td>\n",
+       "      <td>4</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>204</th>\n",
+       "      <td>40</td>\n",
+       "      <td>4</td>\n",
+       "      <td>general_tracking</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>205</th>\n",
+       "      <td>244</td>\n",
+       "      <td>3</td>\n",
+       "      <td>bug</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>206</th>\n",
+       "      <td>184</td>\n",
+       "      <td>3</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>207</th>\n",
+       "      <td>251</td>\n",
+       "      <td>3</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>208</th>\n",
+       "      <td>243</td>\n",
+       "      <td>3</td>\n",
+       "      <td>malware</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>209</th>\n",
+       "      <td>73</td>\n",
+       "      <td>2</td>\n",
+       "      <td>test</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>210</th>\n",
+       "      <td>118</td>\n",
+       "      <td>2</td>\n",
+       "      <td>wiki_policy</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>211</th>\n",
+       "      <td>162</td>\n",
+       "      <td>2</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>212</th>\n",
+       "      <td>142</td>\n",
+       "      <td>1</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>213</th>\n",
+       "      <td>120</td>\n",
+       "      <td>1</td>\n",
+       "      <td>doxxing</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>214</th>\n",
+       "      <td>196</td>\n",
+       "      <td>1</td>\n",
+       "      <td>sockpuppetry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>215</th>\n",
+       "      <td>121</td>\n",
+       "      <td>1</td>\n",
+       "      <td>test</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>216</th>\n",
+       "      <td>198</td>\n",
+       "      <td>1</td>\n",
+       "      <td>test</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>217</th>\n",
+       "      <td>145</td>\n",
+       "      <td>1</td>\n",
+       "      <td>sockpuppetry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>218</th>\n",
+       "      <td>230</td>\n",
+       "      <td>1</td>\n",
+       "      <td>hidden_vandalism</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>219 rows × 3 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     afl_filter  count(*)                    manual_tags\n",
+       "0           135    175455                silly_vandalism\n",
+       "1            30    160302            good_faith_deletion\n",
+       "2            61    147377                good_faith_refs\n",
+       "3            18    133640          good_faith_test_edits\n",
+       "4             3     95916            good_faith_deletion\n",
+       "5           172     89710            good_faith_deletion\n",
+       "6            50     88827                     not_polite\n",
+       "7            98     80434    good_faith_article_creation\n",
+       "8            65     74098                      bad_style\n",
+       "9           132     68607            good_faith_deletion\n",
+       "10           46     47280            profanity_vandalism\n",
+       "11          225     45462            profanity_vandalism\n",
+       "12          180     37713         good_faith_wiki_syntax\n",
+       "13           79     36645                good_faith_refs\n",
+       "14          189     35683               personal_attacks\n",
+       "15          149     32336                 self_promotion\n",
+       "16            9     28972               personal_attacks\n",
+       "17          129     27780                   sockpuppetry\n",
+       "18           29     27130            good_faith_template\n",
+       "19          148     24914                 self_promotion\n",
+       "20          231     21507                silly_vandalism\n",
+       "21          220     19946  good_faith_external_resources\n",
+       "22           39     18456            profanity_vandalism\n",
+       "23           80     18189                           spam\n",
+       "24           12     18159            profanity_vandalism\n",
+       "25          155     17517               general_tracking\n",
+       "26          106     14513                        hoaxing\n",
+       "27           96     14399    good_faith_article_creation\n",
+       "28           11     14368            profanity_vandalism\n",
+       "29           28     12264               general_tracking\n",
+       "..          ...       ...                            ...\n",
+       "189         245         7               hidden_vandalism\n",
+       "190         257         7               hidden_vandalism\n",
+       "191         275         6               hidden_vandalism\n",
+       "192          70         6               hidden_vandalism\n",
+       "193         214         6                 self_promotion\n",
+       "194         207         6            good_faith_template\n",
+       "195          38         6               hidden_vandalism\n",
+       "196          57         6                        doxxing\n",
+       "197          49         5                           spam\n",
+       "198          69         5               hidden_vandalism\n",
+       "199         109         5               hidden_vandalism\n",
+       "200          20         5                silly_vandalism\n",
+       "201           2         4                           test\n",
+       "202         127         4            good_faith_template\n",
+       "203         173         4               hidden_vandalism\n",
+       "204          40         4               general_tracking\n",
+       "205         244         3                            bug\n",
+       "206         184         3               hidden_vandalism\n",
+       "207         251         3               hidden_vandalism\n",
+       "208         243         3                        malware\n",
+       "209          73         2                           test\n",
+       "210         118         2                    wiki_policy\n",
+       "211         162         2               hidden_vandalism\n",
+       "212         142         1               hidden_vandalism\n",
+       "213         120         1                        doxxing\n",
+       "214         196         1                   sockpuppetry\n",
+       "215         121         1                           test\n",
+       "216         198         1                           test\n",
+       "217         145         1                   sockpuppetry\n",
+       "218         230         1               hidden_vandalism\n",
+       "\n",
+       "[219 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# manual tags per year\n",
+    "df_logs_2009 = pd.read_csv(\"data/log-entries-yearly/2009.csv\", sep=',')\n",
+    "df_2nd_ids_manual_tags = df_2nd[['af_id', 'manual_tags']]\n",
+    "df_2009_tags_2nd = df_logs_2009.join(df_2nd_ids_manual_tags.set_index('af_id'), on='afl_filter', how='inner')\n",
+    "df_2009_tags_2nd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#TODO Plot a per year (manual tags)*(hit count) for all filters"
    ]
   },
   {
diff --git a/thesis/appendix.tex b/thesis/appendix.tex
index 76b656f..37ba0b9 100644
--- a/thesis/appendix.tex
+++ b/thesis/appendix.tex
@@ -173,16 +173,16 @@ Note: according to Wikipedia this behaviour constitutes harassment: "Posting ano
   Def: Interaction with others turning non-civil without becoming directly a personal attack? Do we really need this tag if we'll only label one filter with it?
   Examples: 521 "Feedback: All caps" (single example)
 
+'hidden\_vandalism'
+ Def: Tag for hidden filters where a more specific tag could not be determined
+ Example:
+
 \subsubsection{General vandalism}
 
 'general vandalism'
  Def: vandalism for which none of the more specific tags applied
  Example:
 
-'hidden\_vandalism'
- Def: Tag for hidden filters where a more specific tag could not be determined
- Example:
-
 \subsection{Spam/malware/etc.}
 
 'spam'
@@ -279,6 +279,12 @@ Introducing because of filter 18 "Test type edits from clicking on edit bar"
 'general\_maintenance' (used to be 'maintenance' upon 1st labeling)
   Def: Filters taking care of other maintenance tasks (It looks like, I will have problems to distinguish between this one and 'general\_tracking')
   Examples: 728 "Huggle"; 942 "Log edits to protected pages"; 199 "Unflagged Bots"
+\subsection{Contemplating to introduce}
+
+'general\_tracking' %TODO move to maintenance
+  Def: There are various filters introduced with the aim to track certain behaviour in order to determin whether it occurs frequently and how problematic it is
+  Examples: 362 "New user creating page" would fit better in here I think
+
 
 \subsection{Unknown}
 
@@ -292,12 +298,6 @@ Introducing because of filter 18 "Test type edits from clicking on edit bar"
   Def: I'd say that is similar to misc and both should be merged
   Examples: 362 "New user creating page", 300 "Cross-posting"
 
-\subsection{Contemplating to introduce}
-
-'general\_tracking'
-  Def: There are various filters introduced with the aim to track certain behaviour in order to determin whether it occurs frequently and how problematic it is
-  Examples: 362 "New user creating page" would fit better in here I think
-
 
 \section{Extra figures and tables}
 \label{app:appendix-figures}
@@ -394,12 +394,12 @@ abuse_filter_action
   \caption{abuse\_filter\_action schema}~\label{fig:app-db-schemas-afa}
 \end{figure*}
 
-
+%TODO add column "manual tags" (see jupyter NB)
 \begin{table}
   \centering
   \begin{tabular}{r c r }
     % \toprule
-    Filter ID & Publicly available description & Hitcount \\ %TODO is the hitcount for the year or altogether till now?
+    Filter ID & Publicly available description & Hitcount \\ % is the hitcount for the year or altogether till now?-- for the year, of course
     \hline
     135 & repeating characters & 175455 \\
     30 & "large deletion from article by new editors" & 160302 \\
-- 
GitLab